\n
\n
\n \"\"\".format(reply.get('user_name'), self._timestamp2str(reply.get('ctime')),\n reply.get('content')) if reply else ''\n\n c_html = \"\"\"\n{}{}
\n {}
\n\n
\n\n {user_name} {comment_time}\n
\n \n {comment_content} {like_count}\n
\n {replies}\n \\n'.join([\n self._render(c)\n for c in comments\n ])\n h = \"\"\"
精选留言：
\n- \n \"\"\"\n f = '
Sorry,not you need html
'\n else:\n responseHeaders = 'HTTP/1.1 200 OK\\r\\n'\n responseHeaders += '\\r\\n'\n responseBody = f.read()\n finally:\n \n response = responseHeaders + responseBody\n \n connfd.send(response.encode())\n\n def get_data(self,connfd,getRequest):\n urls = ['/time','/tedu','/hello']\n if getRequest in urls:\n responseHeaders = 'HTTP/1.1 200 OK\\r\\n'\n responseHeaders += '\\r\\n'\n if getRequest =='/time':\n import time\n responseBody = time.ctime()\n elif getRequest =='/tedu':\n responseBody = 'laji tedu'\n elif getRequest =='/hello':\n responseBody = \"Welcome to Luoyang
\"\n else:\n responseHeaders = 'HTTP/1.1 404 Not found\\r\\n'\n responseHeaders += '\\r\\n'\n responseBody = \"Sorry,not you need content
\"\n\n response = responseHeaders + responseBody\n connfd.send(response.encode())\n\nif __name__ == \"__main__\":\n \n addr = ('0.0.0.0',9999)\n static_dir = '3-pythonNet/2019-1-18/static'\n # 创建服务器对象\n httpd = HTTPServer(addr,static_dir)\n # 启动服务\n httpd.serve_forever()\n\n","sub_path":"03-pythonNet/2019-1-18/http_server.py","file_name":"http_server.py","file_ext":"py","file_size_in_byte":3392,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"276513578","text":"#-*- coding: utf-8 -*-\n# 基本信息统计\nimport pandas as pd\ncatering_sale='C:\\\\Users\\\\Administrator\\\\Desktop\\\\data\\\\catering_sale.xls'\ndata=pd.read_excel(catering_sale,index_col='日期')\ndetails=data.describe()\nprint(details)\nprint('')\n\n# 异常值检测\nimport matplotlib.pyplot as plt #图像库\nplt.rcParams['font.sans-serif']=['SimHei'] #用来正常显示中文标签\nplt.rcParams['axes.unicode_minus']=False\n\nplt.figure() #画图\np=data.boxplot(return_type='dict')#画箱线图，直接使用DataFrame的方法\nx=p['fliers'][0].get_xdata()# 第一个异常点的数值\ny=p['fliers'][0].get_ydata()# 'flies'即为异常值的标签\ny.sort()#排序\n\n#用annotate添加注释\n#其中有些相近的点，注解会出现重叠，难以看清，需要一些技巧来控制。\n#以下参数都是经过调试的，需要具体问题具体调试。\nfor i in range(len(x)): \n if i>0:\n plt.annotate(y[i], xy = (x[i],y[i]), xytext=(x[i]+0.05 -1.8/(y[i]-y[i-1]),y[i]))\n else:\n plt.annotate(y[i], xy = (x[i],y[i]), xytext=(x[i]+0.08,y[i]))\n\nplt.show() #展示箱线图\n\n\n#一致性分析\n","sub_path":"数据探索/基本信息和异常值分析.py","file_name":"基本信息和异常值分析.py","file_ext":"py","file_size_in_byte":1096,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"92726024","text":"#!/usr/bin/python3\nimport requests\nfrom leia_api.constants import GBIF_API_SUGGEST_URL, GBIF_API_DISTRIBUTIONS_PREFIX_URL, GBIF_API_DISTRIBUTIONS_SUFFIX_URL\n\n\ndef get_gbif_taxonomy(name: str):\n payload = {'q': name, 'limit': 1}\n gbif_request = requests.get(url=GBIF_API_SUGGEST_URL, params=payload)\n gbif_response = gbif_request.json()\n return gbif_response\n\n\ndef get_gbif_distributions(key: str):\n gbif_request = requests.get(\n url=GBIF_API_DISTRIBUTIONS_PREFIX_URL + str(key) + GBIF_API_DISTRIBUTIONS_SUFFIX_URL)\n gbif_response = gbif_request.json()\n return gbif_response\n","sub_path":"backend/leia_api/helpers/gbif.py","file_name":"gbif.py","file_ext":"py","file_size_in_byte":602,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"209265906","text":"from google.cloud import pubsub_v1\n\npublisher = pubsub_v1.PublisherClient()\ntopic_path = publisher.topic_path(\"babylon-258211\",\"babylon-topic\")\n\nf = open(\"babylon.json\", \"r\")\nfor appointment in f:\n\tprint(appointment)\n\tfuture = publisher.publish(topic_path, data=appointment.encode('utf-8'))\n\tprint(future.result())\nf.close()\n\n","sub_path":"producer/producer.py","file_name":"producer.py","file_ext":"py","file_size_in_byte":326,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"66200271","text":"# -*- coding: utf-8 -*-\r\n\"\"\"\r\n@author: Afnan\r\nNote: some of this is carried over from lab 1\r\n\"\"\"\r\nfrom bs4 import BeautifulSoup\r\nfrom typing import Tuple\r\nimport csv\r\nimport re\r\n# BEGIN PART FROM https://towardsdatascience.com/implementing-a-trie-data-structure-in-python-in-less-than-100-lines-of-code-a877ea23c1a1\r\nclass TrieNode(object):\r\n \"\"\"\r\n Trie node implementation.\r\n \"\"\"\r\n \r\n def __init__(self, char: str):\r\n self.char = char\r\n self.children = []\r\n # Is it the last character of the word.\r\n self.word_finished = False\r\n # How many times this character appeared in the addition process\r\n self.counter = 1\r\n \r\n\r\ndef add(root, word: str):\r\n \"\"\"\r\n Adding a word in the trie structure\r\n \"\"\"\r\n node = root\r\n for char in word:\r\n found_in_child = False\r\n # Search for the character in the children of the present `node`\r\n for child in node.children:\r\n if child.char == char:\r\n # We found it, increase the counter by 1 to keep track that another\r\n # word has it as well\r\n child.counter += 1\r\n # And point the node to the child that contains this char\r\n node = child\r\n found_in_child = True\r\n break\r\n # We did not find it so add a new chlid\r\n if not found_in_child:\r\n new_node = TrieNode(char)\r\n node.children.append(new_node)\r\n # And then point node to the new child\r\n node = new_node\r\n # Everything finished. Mark it as the end of a word.\r\n node.word_finished = True\r\n\r\n\r\ndef find_prefix(root, prefix: str) -> Tuple[bool, int]:\r\n \"\"\"\r\n Check and return \r\n 1. If the prefix exsists in any of the words we added so far\r\n 2. If yes then how may words actually have the prefix\r\n \"\"\"\r\n node = root\r\n # If the root node has no children, then return False.\r\n # Because it means we are trying to search in an empty trie\r\n if not root.children:\r\n return False, 0\r\n for char in prefix:\r\n char_not_found = True\r\n # Search through all the children of the present `node`\r\n for child in node.children:\r\n if child.char == char:\r\n # We found the char existing in the child.\r\n char_not_found = False\r\n # Assign node as the child containing the char and break\r\n node = child\r\n break\r\n # Return False anyway when we did not find a char.\r\n if char_not_found:\r\n return False, 0\r\n # Well, we are here means we have found the prefix. Return true to indicate that\r\n # And also the counter of the last node. This indicates how many words have this\r\n # prefix\r\n return True, node.counter\r\n\r\n# END PART FROM https://towardsdatascience.com/implementing-a-trie-data-structure-in-python-in-less-than-100-lines-of-code-a877ea23c1a1\r\n\r\n# This method works like str.split, but splits for as many times as a delimiter shows up in the doc\r\n# It is also original work based on prior knowledge of how string splits work in Python.\r\ndef multi_splitter(input_string, delimiter): \r\n out_strings = []\r\n new_sub = str(input_string).split(delimiter)\r\n for str_element in new_sub:\r\n sub = str_element.split(\"\")\r\n out_strings.append(sub[0])\r\n return out_strings\r\n\r\n\r\ndef get_text(place, sources, places_bag_vector, t_type):\r\n # This portion involving reading the body text in from the file mostly done by Kumar\r\n print (place)\r\n total_text = \"\"\r\n for source in sources:\r\n with open(source) as f:\r\n data = f.read()\r\n soup = BeautifulSoup(data, 'html.parser') # parse using HTML parser, close to structure of these files\r\n reuters_tags = soup.find_all('reuters')\r\n for reuter_tag in reuters_tags: # get information stored within each reuters tag\r\n if t_type == 'topics':\r\n p_tag = reuter_tag.topics\r\n else:\r\n p_tag = reuter_tag.places\r\n d_tags = p_tag.find_all('d') # find all places/topics mentioned\r\n for d_tag in d_tags:\r\n for child in d_tag.children: # find relevant tags to current call and add text to a master string\r\n if(place == child):\r\n try:\r\n total_text += reuter_tag.body.get_text()\r\n except:\r\n total_text += \"\"\r\n \r\n # This subsequent section is devoted to removing a few bits of rather unwieldy extra characters in our \r\n # output string. We wanted to retain as many words as possible, so more tedious methods of extraction,\r\n # such as removing '\\n' from the MIDDLE of the word was required. This part written by Afnan.\r\n array = total_text.split()\r\n new_array = []\r\n for word in array: # each word gets examined and picked apart if it contains the offending characters\r\n new_word = \"\"\r\n if '\\n' in word: # removing line breaks, wherever they may occur\r\n subword = word.split('\\n')\r\n for part in subword:\r\n if '\\n' not in part:\r\n new_word += part\r\n word = new_word\r\n new_word = \"\"\r\n if '.' in word: # removing punctuation\r\n subword = word.split('.')\r\n for part in subword:\r\n if '.' not in part:\r\n new_word += part\r\n word = new_word\r\n new_word = \"\"\r\n if ',' in word: # removing punctuation\r\n subword = word.split(',')\r\n for part in subword:\r\n if ',' not in part:\r\n new_word += part\r\n word = new_word\r\n new_word = \"\"\r\n if '\"' in word: # removing punctuation\r\n subword = word.split('\"')\r\n for part in subword:\r\n if '\"' not in part:\r\n new_word += part\r\n word = new_word\r\n word += \" \"\r\n new_array.append(word)\r\n \r\n cleaned_text = \"\"\r\n for newword in new_array:# now removing some final pesky words as well as any numbers we don't want in our analysis\r\n if \"reuter\" not in newword.lower() and \"\\x03\" not in newword and '\"' not in newword and newword.isdigit() == False:\r\n cleaned_text += newword \r\n \r\n # Create vector and return to calling function\r\n places_bag_vector[place] = cleaned_text\r\n # output looks like: {'afghanistan' : 'Pakistan complained to the United Nations today that...', 'algeria' : 'Liquefied natural gas imports from Algeria...', ....}\r\n return places_bag_vector\r\n\r\n\r\n\r\ndef weighted_get_text(header_importance, place, sources, weighted_bag_vector, t_type):\r\n\r\n # This portion involving reading the body text in from the file mostly done by Kumar\r\n print (place)\r\n total_text = \"\"\r\n for source in sources:\r\n with open(source) as f:\r\n data = f.read()\r\n soup = BeautifulSoup(data, 'html.parser') # parse using HTML parser, close to structure of these files\r\n reuters_tags = soup.find_all('reuters')\r\n for reuter_tag in reuters_tags: # get information stored within each reuters tag\r\n if t_type == 'topics':\r\n p_tag = reuter_tag.topics\r\n else:\r\n p_tag = reuter_tag.places\r\n \r\n d_tags = p_tag.find_all('d') # find all places/topics mentioned\r\n for d_tag in d_tags:\r\n for child in d_tag.children: # find relevant tags to current call and add text to a master string\r\n if(place == child):\r\n \r\n try:\r\n total_text += reuter_tag.body.get_text()\r\n except:\r\n total_text += \"\"\r\n\r\n title_tags = reuter_tag.find_all('title')\r\n if (len(title_tags) > 0):\r\n for title_tag in title_tags:\r\n for i in range(header_importance):\r\n total_text += title_tag.get_text()\r\n total_text += ' '\r\n \r\n # This subsequent section is devoted to removing a few bits of rather unwieldy extra characters in our \r\n # output string. We wanted to retain as many words as possible, so more tedious methods of extraction,\r\n # such as removing '\\n' from the MIDDLE of the word was required. This part written by Afnan.\r\n array = total_text.split()\r\n new_array = []\r\n for word in array: # each word gets examined and picked apart if it contains the offending characters\r\n new_word = \"\"\r\n if '\\n' in word: # removing line breaks, wherever they may occur\r\n subword = word.split('\\n')\r\n for part in subword:\r\n if '\\n' not in part:\r\n new_word += part\r\n word = new_word\r\n new_word = \"\"\r\n if '.' in word: # removing punctuation\r\n subword = word.split('.')\r\n for part in subword:\r\n if '.' not in part:\r\n new_word += part\r\n word = new_word\r\n new_word = \"\"\r\n if ',' in word: # removing punctuation\r\n subword = word.split(',')\r\n for part in subword:\r\n if ',' not in part:\r\n new_word += part\r\n word = new_word\r\n new_word = \"\"\r\n if '\"' in word: # removing punctuation\r\n subword = word.split('\"')\r\n for part in subword:\r\n if '\"' not in part:\r\n new_word += part\r\n word = new_word\r\n new_word = \"\"\r\n if '<' in word: # removing punctuation\r\n subword = word.split('<')\r\n for part in subword:\r\n if '<' not in part:\r\n new_word += part\r\n word = new_word\r\n new_word = \"\"\r\n if '>' in word: # removing punctuation\r\n subword = word.split('>')\r\n for part in subword:\r\n if '>' not in part:\r\n new_word += part\r\n word = new_word\r\n word += \" \"\r\n new_array.append(word)\r\n \r\n cleaned_text = \"\"\r\n for newword in new_array:# now removing some final pesky words as well as any numbers we don't want in our analysis\r\n if \"reuter\" not in newword.lower() and \"\\x03\" not in newword and '\"' not in newword and newword.isdigit() == False:\r\n if (re.search(place, newword, re.IGNORECASE)):\r\n for i in range(header_importance * 2):\r\n cleaned_text += newword\r\n else:\r\n cleaned_text += newword\r\n \r\n cleaned_text.rstrip()\r\n\r\n wordList = []\r\n words = re.findall(r'\\b[a-zA-Z]+\\b', cleaned_text)\r\n for word in words:\r\n wordList.append(word.lower())\r\n\r\n wordPairs = []\r\n for word in set(wordList):\r\n wordPairs.append([word, wordList.count(word)])\r\n \r\n cleaned_text = \"\"\r\n for wordPair in wordPairs:\r\n if wordPair[1] > 1:\r\n for i in range(wordPair[1]):\r\n cleaned_text += wordPair[0] + ' '\r\n \r\n # Create vector and return to calling function\r\n weighted_bag_vector[place] = cleaned_text\r\n # output looks like: {'afghanistan' : 'Pakistan complained to the United Nations today that...', 'algeria' : 'Liquefied natural gas imports from Algeria...', ....}\r\n return weighted_bag_vector\r\n\r\n\r\nif __name__ == \"__main__\":\r\n sources = [\"files/reut2-000.sgm\", \"files/reut2-001.sgm\", \"files/reut2-002.sgm\", \\\r\n \"files/reut2-003.sgm\", \"files/reut2-004.sgm\", \"files/reut2-005.sgm\", \\\r\n \"files/reut2-006.sgm\", \"files/reut2-007.sgm\", \"files/reut2-008.sgm\", \\\r\n \"files/reut2-009.sgm\", \"files/reut2-010.sgm\", \"files/reut2-011.sgm\", \\\r\n \"files/reut2-012.sgm\", \"files/reut2-013.sgm\", \"files/reut2-014.sgm\", \\\r\n \"files/reut2-015.sgm\", \"files/reut2-016.sgm\", \"files/reut2-017.sgm\", \\\r\n \"files/reut2-018.sgm\", \"files/reut2-019.sgm\", \"files/reut2-020.sgm\", \\\r\n \"files/reut2-021.sgm\"]\r\n \r\n total_blank_places = 0\r\n total_blank_topics = 0\r\n total_countries = []\r\n total_topics = []\r\n root = TrieNode('*')\r\n \r\n \r\n # Here, my algorithm for splitting the elements of the TOPICS and PLACES fields is my original work\r\n for source in sources:\r\n with open(source) as f: # Open the file and read line by line to a list array\r\n array = []\r\n for line in f:\r\n array.append(line)\r\n # Since PLACES were contained within one line of code according to the data I saw, I assumed \r\n # that any line with the PLACES tag would contain all of the location info for that article\r\n places = []\r\n for index in array: # Look at lines containing the \"PLACES\" tag and read those into a separate list\r\n if \"- \")\n for schema in root.iter('schema'):\n f.write(\"
- \" + schema.find('name').text + \"
- \")\n for table in schema.iter('table'):\n f.write(\"
- \" + table.find('name').text + \"
- \")\n for column in table.iter('column'):\n f.write(\"
- \" + column.find('name').text + \" \")\n f.write(\"
\")\n f.write(\"
\")\n f.write(\" - \" + table.find('name').text + \"
你是大帅逼
')\n ticket = ''\n s = 'abcdefghijklmnopqrstuvwxyz0123456789'\n for i in range(20):\n ticket += random.choice(s)\n response.set_cookie('ticket', ticket, max_age='', expires='')\n return response\n\n\n@blue.route('/deletecookie/')\ndef del_cookie():\n # 删除cookie\n response = make_response('你是大帅逼
')\n response.delete_cookie('ticket')\n return response","sub_path":"day2/App/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":1251,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"302730534","text":"\n# Copyright 2016 RIFT.IO Inc\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain 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,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport asyncio\nimport time\nfrom collections import defaultdict\n\nfrom enum import Enum\n\nfrom gi.repository import NsdYang, NsrYang, RwDts\nimport rift.tasklets\n\n\nclass ScalingGroupIndexExists(Exception):\n pass\n\n\nclass ScaleGroupTrigger(Enum):\n \"\"\" Trigger for scaling config \"\"\"\n PRE_SCALE_IN = 1\n POST_SCALE_IN = 2\n PRE_SCALE_OUT = 3\n POST_SCALE_OUT = 4\n\n\nclass ScaleGroupState(Enum):\n \"\"\" Scaling group state \"\"\"\n RUNNING = 1\n SCALING_IN = 2\n SCALING_OUT = 3\n\n\nclass ScalingGroup(object):\n \"\"\" This represents a configured NSR scaling group \"\"\"\n def __init__(self, log, group_msg):\n \"\"\" Create a ScalingGroup instance\n\n This class is responsible for representing a configured scaling group\n which is present within an NSR.\n\n :param log: A logger instance\n :param group_msg: A NSD scaling group pb message\n \"\"\"\n self._log = log\n self._group_msg = group_msg\n\n self._instances = {}\n\n def __str__(self):\n return \"ScalingGroup(%s)\" % self.name\n\n @property\n def name(self):\n \"\"\" Name of the scaling group \"\"\"\n return self._group_msg.name\n\n @property\n def state(self):\n \"\"\" State of the scaling group \"\"\"\n state = ScaleGroupState.RUNNING\n for instance in self._instances.values():\n if instance.operational_status in [\"init\", \"vnf_init_phase\"]:\n self._log.debug(\"Scaling instance %s in scaling-out state: %s\",\n instance, instance.operational_status)\n state = ScaleGroupState.SCALING_OUT\n\n elif instance.operational_status in [\"terminate\", \"vnf_terminate_phase\"]:\n self._log.debug(\"Scaling instance %s in scaling-in state: %s\",\n instance, instance.operational_status)\n state = ScaleGroupState.SCALING_IN\n\n return state\n\n @property\n def vnf_index_count_map(self):\n \"\"\" The mapping of member_vnf_index_ref to count\"\"\"\n return {mbr.member_vnf_index_ref: mbr.count for mbr in self._group_msg.vnfd_member}\n\n @property\n def group_msg(self):\n \"\"\" Return the scale group PB message \"\"\"\n return self._group_msg\n\n @property\n def min_instance_count(self):\n \"\"\" Minimum (and default) number of instance of the scaling group \"\"\"\n return self._group_msg.min_instance_count\n\n @property\n def max_instance_count(self):\n \"\"\" Maximum number of instance of the scaling group \"\"\"\n return self._group_msg.max_instance_count\n\n def create_record_msg(self):\n \"\"\" Returns a NSR Scaling group record \"\"\"\n msg = NsrYang.YangData_Nsr_NsInstanceOpdata_Nsr_ScalingGroupRecord(\n scaling_group_name_ref=self.name,\n )\n\n for instance in self.instances:\n msg.instance.append(instance.create_record_msg())\n\n return msg\n\n @property\n def instances(self):\n return self._instances.values()\n\n def get_instance(self, instance_id):\n \"\"\" Get a scaling group instance\n\n :param instance_id: The instance's instance_id\n \"\"\"\n return self._instances[instance_id]\n\n def create_instance(self, instance_id, is_default=False):\n \"\"\" Create a scaling group instance\n\n :param instance_id: The new instance's instance_id\n \"\"\"\n self._log.debug(\"Creating %s instance instance_id %s \", self, instance_id)\n\n if instance_id in self._instances:\n raise ScalingGroupIndexExists(\"%s instance_id %s already exists\" % (self, instance_id))\n\n instance = ScalingGroupInstance(\n log=self._log,\n group_name=self.name,\n instance_id=instance_id,\n is_default=is_default,\n )\n\n self._instances[instance_id] = instance\n\n return instance\n\n def delete_instance(self, instance_id):\n self._log.debug(\"Deleting %s instance instance_id %s \", self, instance_id)\n del self._instances[instance_id]\n\n def trigger_map(self, trigger):\n trig_map = {\n NsdYang.ScalingTrigger.PRE_SCALE_IN : 'pre_scale_in',\n NsdYang.ScalingTrigger.POST_SCALE_IN : 'post_scale_in',\n NsdYang.ScalingTrigger.PRE_SCALE_OUT : 'pre_scale_out',\n NsdYang.ScalingTrigger.POST_SCALE_OUT : 'post_scale_out',\n }\n\n try:\n return trig_map[trigger]\n except Exception as e:\n self._log.error(\"Unknown scaling group trigger passed: {}\".format(trigger))\n self._log.exception(e)\n\n def trigger_config(self, trigger):\n \"\"\" Get the config action for the trigger \"\"\"\n self._log.debug(\"Trigger config {}: {}\".format(trigger, self._group_msg))\n trig = self.trigger_map(trigger)\n if trig is None:\n return\n\n for config in self._group_msg.scaling_config_action:\n if trig == config.trigger:\n return config\n\n\nclass ScalingGroupInstance(object):\n \"\"\" This class represents a configured NSR Scaling Group instance\"\"\"\n\n valid_status_list = (\n \"init\",\n \"vnf_init_phase\",\n \"running\",\n \"terminate\",\n \"vnf_terminate_phase\",\n \"terminated\",\n \"failed\",\n )\n\n def __init__(self, log, group_name, instance_id, is_default=False):\n self._log = log\n self._group_name = group_name\n self._instance_id = instance_id\n self._is_default = is_default\n\n self._vnfrs = {}\n\n self._create_time = int(time.time())\n self._op_status = \"init\"\n\n def __str__(self):\n return \"ScalingGroupInstance(%s #%s)\" % (self._group_name, self.instance_id)\n\n @property\n def operational_status(self):\n return self._op_status\n\n @operational_status.setter\n def operational_status(self, op_status):\n if op_status not in ScalingGroupInstance.valid_status_list:\n raise ValueError(\"Invalid scaling group instance status: %s\", op_status)\n\n self._op_status = op_status\n\n @property\n def instance_id(self):\n return self._instance_id\n\n @property\n def is_default(self):\n return self._is_default\n\n @property\n def vnfrs(self):\n \"\"\" Return all VirtualNetworkFunctionRecord's that have been added\"\"\"\n return self._vnfrs.values()\n\n def create_record_msg(self):\n msg = NsrYang.YangData_Nsr_NsInstanceOpdata_Nsr_ScalingGroupRecord_Instance(\n instance_id=self._instance_id,\n create_time=self._create_time,\n op_status=self._op_status,\n is_default=self._is_default\n )\n\n for vnfr in self.vnfrs:\n msg.vnfrs.append(vnfr.id)\n\n return msg\n\n def add_vnfr(self, vnfr):\n \"\"\" Add a VirtualNetworkFunctionRecord\"\"\"\n self._log.debug(\"Added %s to %s\", vnfr, self)\n self._vnfrs[vnfr.id] = vnfr","sub_path":"modules/core/mano/rwlaunchpad/plugins/rwnsm/rift/tasklets/rwnsmtasklet/scale_group.py","file_name":"scale_group.py","file_ext":"py","file_size_in_byte":7551,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"57121283","text":"# Copyright Max Kolosov 2009-2013 pyirrlicht@gmail.com\n# http://pybass.sf.net\n# BSD license\n\n\nimport pybass\nimport sys\n\n\ntry:\n import pybassmidi\nexcept Exception:\n pybassmidi = None\n\n\ntry:\n from exe import wx\nexcept Exception:\n import wx\n\n\nfrom wx.lib.ticker import Ticker\n\n\ndef print_error():\n exc, err, traceback = sys.exc_info()\n print('%s %s ERROR ON LINE %d %s\\n' % (exc, traceback.tb_frame.f_code.co_filename, traceback.tb_lineno, err))\n del exc, err, traceback\n\n\nclass memory_stream:\n\n def __init__(self, data, name='memory_stream'):\n self.name = name\n self.current_position = 0\n self.data = data\n self.end_position = len(self.data) - 1\n self.decode_length = 0\n self.seconds = 0\n\n def read(self, size=1024):\n result = ''\n if self.current_position is not self.end_position and size > 0:\n last_index = self.current_position + size\n if last_index > self.end_position:\n last_index = self.end_position\n result = self.data[self.current_position: last_index]\n self.current_position = last_index\n return result\n\n def write(self, value=''):\n self.data += value\n\n def seek(self, position, whence=0):\n if whence is 0:\n if position <= self.end_position:\n self.current_position = position\n elif whence is 1:\n if position + self.current_position <= self.end_position:\n self.current_position += position\n elif whence is 2:\n if position < 0:\n position *= -1\n if self.end_position - position > 0:\n self.current_position = self.end_position - position\n\n def tell(self):\n return self.current_position\n\n def isatty(self):\n return 1\n\n def flush(self):\n pass\n\n def is_eof(self):\n return self.current_position == self.end_position\n\n\nclass slider_ctrl(wx.Slider):\n\n def __init__(self, *args, **kwargs):\n self.timer_interval = 500\n self.player_ctrl = args[0]\n wx.Slider.__init__(self, *args, **kwargs)\n self.timer = wx.Timer(self)\n self.Bind(wx.EVT_LEFT_DOWN, self.event_left_down)\n self.Bind(wx.EVT_LEFT_UP, self.event_left_up)\n self.Bind(wx.EVT_TIMER, self.event_timer)\n\n def __del__(self):\n if hasattr(self, 'timer'):\n self.timer.Stop()\n\n def timer_start(self):\n if not self.timer.IsRunning():\n self.timer.Start(self.timer_interval)\n\n def timer_stop(self):\n if self.timer.IsRunning():\n self.timer.Stop()\n\n def event_timer(self, event):\n if self.player_ctrl.method_get_position() < self.player_ctrl.method_get_length() - 1:\n self.SetValue(self.player_ctrl.method_get_position())\n else:\n self.player_ctrl.method_stop_audio()\n\n def event_left_down(self, event):\n self.timer_stop()\n event.Skip()\n\n def event_left_up(self, event):\n self.player_ctrl.method_set_position(self.GetValue())\n self.timer_start()\n event.Skip()\n\n\nclass player_ctrl(wx.Panel):\n\n def __init__(self, *args, **kwargs):\n\n self.stream = kwargs.pop('stream', None)\n self.name_stream = kwargs.pop('name_stream', 'memory_stream')\n self.bass_handle = 0\n self.sound_font = 0\n\n result = pybass.BASS_Init(-1, 44100, 0, 0, 0)\n if not result:\n bass_error_code = pybass.BASS_ErrorGetCode()\n if bass_error_code != pybass.BASS_ERROR_ALREADY:\n self.slider.Enable(False)\n self.btn_play.Enable(False)\n self.btn_stop.Enable(False)\n print('BASS_Init error %s' % pybass.get_error_description(bass_error_code))\n self.plugins = {}\n self.plugins['aac'] = (pybass.BASS_PluginLoad('bass_aac.dll', 0), '|AAC|*.aac')\n self.plugins['ac3'] = (pybass.BASS_PluginLoad('bass_ac3.dll', 0), '|AC3|*.ac3')\n self.plugins['aix'] = (pybass.BASS_PluginLoad('bass_aix.dll', 0), '|AIX|*.aix')\n self.plugins['ape'] = (pybass.BASS_PluginLoad('bass_ape.dll', 0), '|APE|*.ape')\n self.plugins['mpc'] = (pybass.BASS_PluginLoad('bass_mpc.dll', 0), '|MPC|*.mpc')\n self.plugins['ofr'] = (pybass.BASS_PluginLoad('bass_ofr.dll', 0), '|OFR|*.ofr')\n self.plugins['spx'] = (pybass.BASS_PluginLoad('bass_spx.dll', 0), '|SPX|*.spx')\n self.plugins['tta'] = (pybass.BASS_PluginLoad('bass_tta.dll', 0), '|TTA|*.tta')\n self.plugins['cda'] = (pybass.BASS_PluginLoad('basscd.dll', 0), '|CDA|*.cda')\n self.plugins['flac'] = (pybass.BASS_PluginLoad('bassflac.dll', 0), '|FLAC|*.flac')\n self.plugins['wma'] = (pybass.BASS_PluginLoad('basswma.dll', 0), '|WMA, WMV|*.wma;*.wmv')\n if pybassmidi:\n sound_font_file_name = 'CT4MGM.SF2'\n self.sound_font = pybassmidi.BASS_MIDI_FontInit(sound_font_file_name, 0)\n if self.sound_font == 0:\n print('BASS_MIDI_FontInit error %s (sound font file must be %s)' %\n (pybass.get_error_description(pybass.BASS_ErrorGetCode()), sound_font_file_name))\n else:\n self.plugins['midi'] = (pybass.BASS_PluginLoad('bassmidi.dll', 0), '|MID|*.mid')\n else:\n print('pybassmidi module not accessible')\n\n wx.Panel.__init__(self, *args, **kwargs)\n\n sizer_h = wx.BoxSizer(wx.HORIZONTAL)\n\n self.btn_play = wx.Button(self, wx.ID_ANY, _('Play'), style=wx.NO_BORDER)\n self.btn_play.SetToolTip(_('Play media data'))\n self.Bind(wx.EVT_BUTTON, self.event_play, self.btn_play)\n sizer_h.Add(self.btn_play)\n\n self.btn_stop = wx.Button(self, wx.ID_ANY, _('Stop'), style=wx.NO_BORDER)\n self.Bind(wx.EVT_BUTTON, self.event_stop, self.btn_stop)\n sizer_h.Add(self.btn_stop)\n\n self.btn_open = wx.Button(self, wx.ID_OPEN, _('Open'), style=wx.NO_BORDER)\n self.Bind(wx.EVT_BUTTON, self.event_open, self.btn_open)\n sizer_h.Add(self.btn_open)\n\n sizer_v = wx.BoxSizer(wx.VERTICAL)\n\n self.status_line = Ticker(self, fgcolor='#000062', bgcolor='#7F7F8F',\n start=False, ppf=1, fps=50, direction='ltr')\n sizer_v.Add(self.status_line, 0, wx.EXPAND)\n\n self.slider = slider_ctrl(self, wx.ID_ANY, 0, 0, 1)\n sizer_v.Add(self.slider, 0, wx.EXPAND)\n\n sizer_v.Add(sizer_h)\n\n self.SetSizer(sizer_v)\n self.SetAutoLayout(True)\n\n self.volume_slider = wx.Slider(self, wx.ID_ANY, pybass.BASS_GetVolume() * 100, 0, 100)\n self.Bind(wx.EVT_SCROLL, self.event_volume_slider, self.volume_slider)\n sizer_h.Add(self.volume_slider, 0, wx.EXPAND)\n\n self.method_check_controls()\n\n def method_load_file(self):\n import os\n wildcard = 'music sounds (MO3, IT, XM, S3M, MTM, MOD, UMX)|*.mo3;*.it;*.xm;*.s3m;*.mtm;*.mod;*.umx'\n wildcard += '|stream sounds (MP3, MP2, MP1, OGG, WAV, AIFF)|*.mp3;*.mp2;*.mp1;*.ogg;*.wav;*.aiff'\n for plugin in self.plugins.itervalues():\n if plugin[0] > 0:\n wildcard += plugin[1]\n wildcard += '|All files (*.*)|*.*'\n dlg = wx.FileDialog(self, message=_('Choose a file'), defaultDir=os.getcwd(),\n defaultFile='', wildcard=wildcard, style=wx.FD_OPEN | wx.FD_CHANGE_DIR)\n if dlg.ShowModal() == wx.ID_OK:\n self.name_stream = file_name = dlg.GetPath()\n if os.path.isfile(file_name):\n flags = 0\n if isinstance(file_name, unicode):\n flags |= pybass.BASS_UNICODE\n try:\n pybass.BASS_CHANNELINFO._fields_.remove(('filename', pybass.ctypes.c_char_p))\n except Exception:\n pass\n else:\n pybass.BASS_CHANNELINFO._fields_.append(('filename', pybass.ctypes.c_wchar_p))\n error_msg = 'BASS_StreamCreateFile error %s'\n new_bass_handle = 0\n if dlg.GetFilterIndex() == 0: # BASS_CTYPE_MUSIC_MOD\n flags |= pybass.BASS_MUSIC_PRESCAN\n new_bass_handle = pybass.BASS_MusicLoad(False, file_name, 0, 0, flags, 0)\n error_msg = 'BASS_MusicLoad error %s'\n else: # other sound types\n new_bass_handle = pybass.BASS_StreamCreateFile(False, file_name, 0, 0, flags)\n if new_bass_handle == 0:\n print(error_msg % pybass.get_error_description(pybass.BASS_ErrorGetCode()))\n else:\n self.method_stop_audio()\n self.bass_handle = new_bass_handle\n self.stream = None\n self.method_slider_set_range()\n self.method_check_controls()\n\n def method_load_wav_file(self):\n import os\n wildcard = 'wav (*.wav)|*.wav|All files (*.*)|*.*'\n dlg = wx.FileDialog(self, message=_('Choose a file'), defaultDir=os.getcwd(),\n defaultFile='', wildcard=wildcard, style=wx.OPEN | wx.CHANGE_DIR)\n if dlg.ShowModal() == wx.ID_OK:\n self.name_stream = file_name = dlg.GetPath()\n if os.path.isfile(file_name):\n flags = 0\n if isinstance(file_name, unicode):\n flags |= pybass.BASS_UNICODE\n try:\n pybass.BASS_CHANNELINFO._fields_.remove(('filename', pybass.ctypes.c_char_p))\n except Exception:\n pass\n else:\n pybass.BASS_CHANNELINFO._fields_.append(('filename', pybass.ctypes.c_wchar_p))\n\n def stream_callback(handle, buffer, length, user):\n b = pybass.ctypes.cast(buffer, pybass.ctypes.c_char_p)\n pybass.ctypes.memset(b, 0, length)\n data = pybass.ctypes.c_char_p(self.stream.read(length))\n pybass.ctypes.memmove(b, data, length)\n if self.stream.is_eof():\n length |= pybass.BASS_STREAMPROC_END\n self.stream.current_position = 0\n return length\n self.stream_callback = stream_callback\n self.user_func = pybass.STREAMPROC(self.stream_callback)\n self.stream = memory_stream(open(file_name, 'rb').read(), file_name)\n new_bass_handle = pybass.BASS_StreamCreate(44100, 2, flags, self.user_func, 0)\n if new_bass_handle == 0:\n print('BASS_StreamCreate error %s' % pybass.get_error_description(pybass.BASS_ErrorGetCode()))\n else:\n self.method_stop_audio()\n self.bass_handle = new_bass_handle\n self.stream = None\n self.method_slider_set_range()\n self.method_check_controls()\n\n def method_load_data(self, stream, name_stream='memory_stream'):\n if stream is not None:\n if isinstance(stream, (str, list, tuple, buffer)):\n self.stream = memory_stream(stream, name_stream)\n else:\n self.stream = stream\n if isinstance(self.stream, memory_stream):\n system = pybass.STREAMFILE_BUFFER\n flags = 0\n\n def callback_close(user):\n self.stream.current_position = 0\n self.callback_close = callback_close\n\n def callback_length(user):\n return len(self.stream.data)\n self.callback_length = callback_length\n\n def callback_read(buffer, length, user):\n b = pybass.ctypes.cast(buffer, pybass.ctypes.c_char_p)\n pybass.ctypes.memset(b, 0, length)\n data = pybass.ctypes.c_char_p(self.stream.read(length))\n pybass.ctypes.memmove(b, data, length)\n return length\n self.callback_read = callback_read\n\n def callback_seek(offset, user):\n self.stream.seek(offset)\n return True\n self.callback_seek = callback_seek\n self.bass_file_procs = pybass.BASS_FILEPROCS()\n self.bass_file_procs.close = pybass.FILECLOSEPROC(self.callback_close)\n self.bass_file_procs.length = pybass.FILELENPROC(self.callback_length)\n self.bass_file_procs.read = pybass.FILEREADPROC(self.callback_read)\n self.bass_file_procs.seek = pybass.FILESEEKPROC(self.callback_seek)\n new_bass_handle = pybass.BASS_StreamCreateFileUser(\n system, flags, self.bass_file_procs, id(self.stream.data))\n if new_bass_handle == 0:\n print('BASS_StreamCreateFileUser error %s' %\n pybass.get_error_description(pybass.BASS_ErrorGetCode()))\n else:\n self.method_stop_audio()\n self.bass_handle = new_bass_handle\n channel_info = self.method_get_channel_info()\n if channel_info.ctype == pybass.BASS_CTYPE_STREAM_OGG:\n import pyogginfo\n ogg_info = pyogginfo.VorbisStreamInfo()\n stream = pyogginfo.SimpleDemultiplexer(ogg_info)\n if isinstance(self.stream.data, str):\n stream.process(self.stream.data)\n else:\n stream.process(str(self.stream.data))\n self.stream.decode_length = ogg_info.lastPosition\n self.stream.seconds = ogg_info.stop\n try:\n for key, value in ogg_info.comments.comments:\n if key == 'TITLE':\n if value.strip() > '':\n self.stream.name = value\n except Exception:\n pass\n self.method_slider_set_range()\n self.method_check_controls()\n\n def method_get_channel_info(self):\n channel_info = pybass.BASS_CHANNELINFO()\n if not pybass.BASS_ChannelGetInfo(self.bass_handle, channel_info):\n print('BASS_ChannelGetInfo error %s' % pybass.get_error_description(pybass.BASS_ErrorGetCode()))\n return channel_info\n\n def method_get_state(self):\n return pybass.BASS_ChannelIsActive(self.bass_handle)\n\n def method_get_length(self):\n result = pybass.BASS_ChannelGetLength(self.bass_handle, pybass.BASS_POS_BYTE)\n if result <= 0 and isinstance(self.stream, memory_stream):\n result = self.stream.decode_length\n return result\n\n def method_get_position(self):\n return pybass.BASS_ChannelGetPosition(self.bass_handle, pybass.BASS_POS_BYTE)\n\n def method_set_position(self, value):\n if not pybass.BASS_ChannelSetPosition(self.bass_handle, value, pybass.BASS_POS_BYTE):\n print('BASS_ChannelSetPosition error %s' % pybass.get_error_description(pybass.BASS_ErrorGetCode()))\n\n def method_slider_set_range(self):\n self.slider.SetRange(0, self.method_get_length())\n\n def method_check_controls(self):\n if self.bass_handle:\n self.slider.Enable(True)\n self.btn_play.Enable(True)\n if self.method_get_state() == pybass.BASS_ACTIVE_STOPPED:\n self.btn_stop.Enable(False)\n else:\n self.btn_stop.Enable(True)\n\n if hasattr(self.stream, 'name'):\n text = self.stream.name + ' (' + pybass.seconds_to_string(self.stream.seconds) + ')'\n else:\n # ~ channel_info = self.method_get_channel_info()\n # ~ text = channel_info.filename\n text = self.name_stream + ' (' + pybass.stream_length_as_hms(self.bass_handle) + ')'\n self.status_line.SetText(text)\n if self.status_line.GetText() != '':\n self.status_line.Start()\n else:\n self.slider.Enable(False)\n self.btn_play.Enable(False)\n self.btn_stop.Enable(False)\n if self.status_line.GetText() == '':\n if self.status_line.IsTicking():\n self.status_line.Stop()\n\n def method_is_end(self):\n return self.method_get_state() == pybass.BASS_ACTIVE_STOPPED and self.method_get_position() == 0\n\n def method_play(self):\n if self.bass_handle:\n if self.method_get_state() in (pybass.BASS_ACTIVE_STOPPED, pybass.BASS_ACTIVE_PAUSED):\n if not pybass.BASS_ChannelPlay(self.bass_handle, False):\n print('BASS_ChannelPlay error %s' % pybass.get_error_description(pybass.BASS_ErrorGetCode()))\n else:\n self.slider.timer_start()\n self.btn_play.SetLabel(_('Pause'))\n self.btn_stop.Enable(True)\n else:\n if not pybass.BASS_ChannelPause(self.bass_handle):\n print('BASS_ChannelPause error %s' % pybass.get_error_description(pybass.BASS_ErrorGetCode()))\n else:\n self.slider.timer_stop()\n self.btn_play.SetLabel(_('Unpause'))\n\n def event_volume_slider(self, event):\n pybass.BASS_SetVolume(event.GetPosition() / 100.0)\n\n def event_play(self, event):\n self.method_play()\n\n def event_open(self, event):\n self.method_load_file()\n\n def event_stop(self, event):\n self.method_stop_audio()\n\n def method_stop_audio(self):\n self.method_stop_audio_stream()\n self.btn_play.SetLabel(_('Play'))\n self.slider.SetValue(0)\n self.btn_stop.Enable(False)\n\n def method_stop_audio_stream(self):\n self.slider.timer_stop()\n if self.bass_handle:\n if not pybass.BASS_ChannelStop(self.bass_handle):\n print('BASS_ChannelStop error %s' % pybass.get_error_description(pybass.BASS_ErrorGetCode()))\n else:\n self.method_set_position(0)\n\n def method_free_handle(self):\n if self.bass_handle:\n channel_info = self.method_get_channel_info()\n if channel_info.ctype >= pybass.BASS_CTYPE_MUSIC_MOD:\n if not pybass.BASS_MusicFree(self.bass_handle):\n print('BASS_MusicFree error %s' % pybass.get_error_description(pybass.BASS_ErrorGetCode()))\n else:\n self.bass_handle = 0\n elif channel_info.ctype >= pybass.BASS_CTYPE_STREAM:\n if not pybass.BASS_StreamFree(self.bass_handle):\n print('BASS_StreamFree error %s' % pybass.get_error_description(pybass.BASS_ErrorGetCode()))\n else:\n self.bass_handle = 0\n\n def method_reset(self):\n self.method_free_handle()\n self.status_line.SetText('')\n self.method_check_controls()\n\n def __del__(self):\n self.method_free_handle()\n if self.sound_font != 0 and pybassmidi:\n if pybassmidi.BASS_MIDI_FontFree(self.sound_font):\n print('BASS_MIDI_FontFree error %s' % pybass.get_error_description(pybass.BASS_ErrorGetCode()))\n for plugin in self.plugins.itervalues():\n if plugin[0] > 0:\n if pybass.BASS_PluginFree(plugin[0]):\n print('BASS_PluginFree error %s' % pybass.get_error_description(pybass.BASS_ErrorGetCode()))\n\n\nif __name__ == '__main__':\n import os\n import gettext\n from locale import getdefaultlocale, setlocale, LC_ALL\n from wx.lib.agw.aui import AuiManager\n from wx.lib.agw.aui import AuiPaneInfo\n # from wx.lib.agw.aui import AuiToolBar\n # from wx.lib.agw.aui import AUI_TB_DEFAULT_STYLE\n # from wx.lib.agw.aui import AUI_TB_OVERFLOW\n from wx.html import HtmlHelpController\n setlocale(LC_ALL, '')\n\n class log_ctrl(wx.TextCtrl):\n\n def __init__(self, *args, **kwargs):\n self.file_name = kwargs.pop('file_name', 'log.txt')\n self.main_frame = kwargs.pop('main_frame', None)\n self.add_to_file = kwargs.pop('add_to_file', False)\n if self.main_frame is None:\n self.main_frame = args[0]\n super(log_ctrl, self).__init__(*args, **kwargs)\n\n def __write__(self, content):\n self.WriteText(content)\n\n def show_control(self, ctrl_name='log_ctrl'):\n if self.main_frame is not None:\n if hasattr(self.main_frame, 'aui_manager'):\n self.main_frame.show_aui_pane_info(ctrl_name)\n self.SetInsertionPointEnd()\n if self.add_to_file:\n self.flush()\n\n def write(self, content):\n self.show_control()\n self.__write__(content)\n\n def writelines(self, l):\n self.show_control()\n map(self.__write__, l)\n\n def flush(self):\n self.SaveFile(self.file_name)\n\n class main_frame(wx.Frame):\n\n def __init__(self, *args, **kwargs):\n self.app = kwargs.pop('app', None)\n wx.Frame.__init__(self, *args, **kwargs)\n # =============== Logging Text Control ================\n self.log_ctrl = log_ctrl(self, style=wx.TE_MULTILINE, add_to_file=True)\n sys.stdout = self.log_ctrl\n sys.stderr = self.log_ctrl\n self.log = wx.LogTextCtrl(self.log_ctrl)\n self.log.SetLogLevel(wx.LOG_Error)\n # ~ wx.Log_SetActiveTarget(self.log)\n # =============== player Control ================\n self.player = player_ctrl(self)\n # =============== StatusBar ================\n statusbar = self.CreateStatusBar(2)\n statusbar.SetStatusWidths([-1, -1])\n statusbar.SetStatusText(_('Welcome into application!'), 0)\n # =============== AuiManager ================\n self.aui_manager = AuiManager()\n self.aui_manager.SetManagedWindow(self)\n self.aui_manager.AddPane(self.player, AuiPaneInfo().Name('player').CenterPane())\n self.aui_manager.AddPane(self.log_ctrl, AuiPaneInfo().Name(\n 'log_ctrl').Bottom().Layer(0).BestSize((100, 100)).Hide())\n if self.log_ctrl.GetValue() != '':\n self.aui_manager.GetPane('log_ctrl').Show()\n self.aui_manager.Update()\n\n def DoUpdate(self):\n self.aui_manager.Update()\n\n def show_aui_pane_info(self, name):\n if not self.aui_manager.GetPane(name).IsShown():\n self.aui_manager.GetPane(name).Show()\n self.aui_manager.Update()\n\n def show_hide_aui_pane_info(self, name):\n if self.aui_manager.GetPane(name).IsShown():\n self.aui_manager.GetPane(name).Hide()\n else:\n self.aui_manager.GetPane(name).Show()\n self.aui_manager.Update()\n\n # ~ class application(wx.PySimpleApp):\n class application(wx.App):\n app_version = '0.4'\n app_path = os.getcwd()\n app_name = os.path.basename(sys.argv[0].split('.')[0])\n help_file = app_path + '/' + app_name + '.htb'\n settings_name = app_path + '/' + app_name + '.cfg'\n\n def start(self):\n result = True\n self.help_file = self.app_name + '.htb'\n # SETUP LANGUAGE\n lang_catalog = getdefaultlocale()[0]\n list_trans = []\n current_trans = -1\n i = 0\n if os.path.exists('lang/%s' % lang_catalog):\n for dir_name in os.listdir('lang'):\n if os.path.exists('lang/%s/%s.mo' % (dir_name, self.app_name)):\n if dir_name == lang_catalog:\n current_trans = i\n self.help_file = 'lang/' + dir_name + '/' + self.help_file\n list_trans.append(gettext.GNUTranslations(\n open('lang/%s/%s.mo' % (dir_name, self.app_name), 'rb')))\n i += 1\n if len(list_trans) > 0:\n try:\n list_trans[current_trans].install(unicode=True) # wx.USE_UNICODE\n except Exception:\n print_error()\n if current_trans == -1:\n trans = gettext.NullTranslations()\n trans.install(unicode=True) # wx.USE_UNICODE\n # SETUP WX LANGUAGE TRANSLATION TO OS DEFAULT LANGUAGE\n # WX DIRECTORY MUST BE TO CONTAIN LANG DIRECTORY\n self.locale = wx.Locale(wx.LANGUAGE_DEFAULT)\n # CHECK EXISTS INSTANCE\n name_user = wx.GetUserId()\n name_instance = self.app_name + '::'\n self.instance_checker = wx.SingleInstanceChecker(name_instance + name_user)\n if self.instance_checker.IsAnotherRunning():\n wx.MessageBox(_('Software is already running.'), _('Warning'))\n return False\n # CREATE HTML HELP CONTROLLER\n # ~ wx.FileSystem.AddHandler(wx.ZipFSHandler())\n self.help_controller = HtmlHelpController()\n if os.path.exists(self.help_file):\n self.help_controller.AddBook(self.help_file)\n # ABOUT APPLICATION\n self.developers = [_('Maxim Kolosov')]\n self.copyright = _('(C) 2013 Max Kolosov')\n self.web_site = ('http://pybass.sf.net', _('Home page'))\n self.email = ('mailto:pyirrlicht@gmail.com', _('email for feedback'))\n self.license = _('BSD license')\n self.about_description = _('wxPython bass music player.')\n # CREATE MAIN FRAME\n self.main_frame = main_frame(None, wx.ID_ANY, self.app_name, app=self)\n self.SetTopWindow(self.main_frame)\n self.main_frame.Show()\n return result\n\n def OnExit(self):\n try:\n del self.instance_checker\n except Exception:\n print_error()\n\n app = application(0)\n if app.start():\n app.MainLoop()\n else:\n app.OnExit()\n","sub_path":"source/pybass/wx_ctrl_phoenix.py","file_name":"wx_ctrl_phoenix.py","file_ext":"py","file_size_in_byte":26415,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"150293049","text":"# Runs on Leetcode\n # Solution 1\n # Runtime - O(n)\n # Memory - O(n)\n # Solution 2\n # Runtime - O(n)\n # Memory - O(1)\n\n\"\"\"\n# Definition for a Node.\nclass Node:\n def __init__(self, val: int = 0, left: 'Node' = None, right: 'Node' = None, next: 'Node' = None):\n self.val = val\n self.left = left\n self.right = right\n self.next = next\n\"\"\"\n\n\n# Solution 1\n\nclass Solution:\n def connect(self, root: 'Node') -> 'Node':\n if not root:\n return \n queue = [root]\n while queue:\n first = queue[0]\n for i in range(len(queue)-1):\n queue[i].next = queue[i+1]\n temp = queue\n queue = []\n for i in range(len(temp)):\n if temp[i].left:\n queue.append(temp[i].left)\n if temp[i].right:\n queue.append(temp[i].right)\n return root\n \n \n# Solution 2\n\nclass Solution:\n def connect(self, root: 'Node') -> 'Node':\n if not root:\n return \n temp = root\n while temp:\n curr = temp\n while curr:\n if curr.left:\n curr.left.next = curr.right\n if curr.right and curr.next:\n curr.right.next = curr.next.left\n curr = curr.next\n temp = temp.left\n return root\n","sub_path":"Problem_1.py","file_name":"Problem_1.py","file_ext":"py","file_size_in_byte":1428,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"45385437","text":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\nimport pywikibot, re, sys, argparse\n\nimport blib\nfrom blib import getparam, rmparam, tname, msg, site\n\nimport lalib\n\ndef investigate_possible_adj(index, adj_pagename, adv, adv_defns):\n def pagemsg(txt):\n msg(\"Page %s %s: %s\" % (index, adj_pagename, txt))\n pagemsg(\"Trying for adverb %s\" % adv)\n page = pywikibot.Page(site, adj_pagename)\n if not page.exists():\n pagemsg(\"Doesn't exist for adverb %s\" % adv)\n return\n\n text = str(page.text)\n\n retval = lalib.find_latin_section(text, pagemsg)\n if retval is None:\n return\n\n sections, j, secbody, sectail, has_non_latin = retval\n\n subsections = re.split(\"(^===+[^=\\n]+===+\\n)\", secbody, 0, re.M)\n\n for k in range(2, len(subsections), 2):\n parsed = blib.parse_text(subsections[k])\n for t in parsed.filter_templates():\n origt = str(t)\n tn = tname(t)\n if tn in [\"la-adj\", \"la-part\"]:\n adj = lalib.la_get_headword_from_template(t, adj_pagename, pagemsg)[0]\n adj_defns = lalib.find_defns(subsections[k])\n msg(\"%s /// %s /// %s /// %s\" % (adv, adj, \";\".join(adv_defns), \";\".join(adj_defns)))\n\ndef process_page(page, index):\n pagetitle = str(page.title())\n def pagemsg(txt):\n msg(\"Page %s %s: %s\" % (index, pagetitle, txt))\n\n notes = []\n\n if \" \" in pagetitle:\n pagemsg(\"WARNING: Space in page title, skipping\")\n return\n pagemsg(\"Processing\")\n\n text = str(page.text)\n\n retval = lalib.find_latin_section(text, pagemsg)\n if retval is None:\n return\n\n sections, j, secbody, sectail, has_non_latin = retval\n\n subsections = re.split(\"(^===+[^=\\n]+===+\\n)\", secbody, 0, re.M)\n\n for k in range(2, len(subsections), 2):\n parsed = blib.parse_text(subsections[k])\n for t in parsed.filter_templates():\n origt = str(t)\n tn = tname(t)\n if tn == \"la-adv\":\n adv = blib.remove_links(getparam(t, \"1\")) or pagetitle\n macron_stem, is_stem = lalib.infer_adv_stem(adv)\n if not is_stem:\n pagemsg(\"WARNING: Couldn't infer stem from adverb %s, not standard: %s\" % (\n adv, origt))\n continue\n adv_defns = lalib.find_defns(subsections[k])\n possible_adjs = []\n stem = lalib.remove_macrons(macron_stem)\n possible_adjs.append(stem + \"us\")\n possible_adjs.append(stem + \"is\")\n if stem.endswith(\"nt\"):\n possible_adjs.append(stem[:-2] + \"ns\")\n if stem.endswith(\"plic\"):\n possible_adjs.append(stem[:-2] + \"ex\")\n if stem.endswith(\"c\"):\n possible_adjs.append(stem[:-1] + \"x\")\n if re.search(\"[aeiou]r$\", stem):\n possible_adjs.append(stem)\n elif stem.endswith(\"r\"):\n possible_adjs.append(stem[:-1] + \"er\")\n if adv.endswith(\"iē\"):\n possible_adjs.append(stem + \"ius\")\n for possible_adj in possible_adjs:\n investigate_possible_adj(index, possible_adj, adv, adv_defns)\n\nparser = blib.create_argparser(\"Find corresponding adjectives for Latin adverbs\",\n include_pagefile=True)\nargs = parser.parse_args()\nstart, end = blib.parse_start_end(args.start, args.end)\n\nblib.do_pagefile_cats_refs(args, start, end, process_page,\n default_cats=[\"Latin adverbs\"])\n","sub_path":"find_latin_adj_for_adv.py","file_name":"find_latin_adj_for_adv.py","file_ext":"py","file_size_in_byte":3204,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"189851833","text":"#!/usr/bin/env python2.7\n# -*- coding: utf-8 -*-\n\nimport os\n\nimport tornado.web\n\nfrom handlers.index import fe_url\nfrom handlers.admin_index import admin_url\n\nsettings = dict(\n ##设置cookie密钥,默认为字符串\"secure cookies\"\n cookie_secret= \"lN2ImsFwS0yZlOM+d68dJZ5Ko7mrqEPEpInixMSWG84=\",\n ##设置登陆路径，未登陆用户在操作时跳转会用到这个参数,默认为@tornado.web.authenticated\n #login_url= \"/login\",\n ##设置防跨站请求攻击,默认为False，即不可防御。\n #xsrf_cookies= True,\n\n #设置templates路径\n template_path = os.path.join(os.path.dirname(__file__), \"templates\"),\n\n ##设置静态文件解析路径\n static_path = os.path.join(os.path.dirname(__file__), \"static\"),\n\n #设置调试模式,默认为False，即不是调试模式。\n debug = True,\n\n ##设置是否自动编码：在2.0以上需要设置此项来兼容您之前的APP,不设置默认为自动编码。\n #autoescape = None,\n\n ##设置template_loader，可以从独立的路径中导入template：其中utils为自己定义的模块，ZipLoader是tornado.template.BaseLoader的子类。\n #template_loader=utils.ZipLoader,\n\n ##设置gzip压缩：\n #gzip=True\n\n #设置静态路径头部,默认是\"/static/\"\n #static_url_prefix = \"/templates/\"\n\n\n ##设置静态文件处理类.默认是tornado.web.StaticFileHandler\n #static_handler_class = MyStaticFileHandler,\n\n ##设置静态文件的参数,默认为空字典。\n #static_handler_args = {{ \"key1\":\"value1\", \"key2\":\"value2\" }\n\n ##设置日志处理函数,日志处理函数your_fun，按照自己的意图记录日志。\n #log_function = your_fun,\n )\n\nroutes = fe_url + admin_url\n\napplication = tornado.web.Application(\n handlers = routes,\n **settings\n )","sub_path":"vmall/application.py","file_name":"application.py","file_ext":"py","file_size_in_byte":1811,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"117327148","text":"#! /home/michael/.local/share/virtualenvs/DeepLearningProject-WE2UAgWf/bin/python\n\nimport rospy\nimport time\nimport tf\nfrom tf3D import GazeboModel\nimport sys\n\ndef handle_turtle_pose (pose_msg, robot_name):\n\tbr = tf.TransformBroadcaster()\n\tbr.sendTransform((pose_msg.position.x,pose_msg.position.y,pose_msg.position.z),\n\t\t(pose_msg.orientation.x,pose_msg.orientation.y,pose_msg.orientation.z,pose_msg.orientation.w),\n\t\trospy.Time.now(),\n\t\trobot_name,\n\t\t\"/world\")\n\ndef publisher_of_tf():\n\trospy.init_node('publisher_of_tf_node', anonymous=True)\n\trobot_name_list=[\"turtlebot3_waffle_pi_fol_\" + sys.argv[1],\"turtlebot3_waffle_pi_fol_\" + sys.argv[2]]\n\tgazebo_model_object = GazeboModel(robot_name_list)\n\n\tfor robot_name in robot_name_list:\n\t\tpose_now = gazebo_model_object.get_model_pose(robot_name)\n\n\ttime.sleep(1)\n\trospy.loginfo(\"Ready .. Starting to Publish TF data now ...\")\n\n\trate = rospy.Rate(5)\n\twhile not rospy.is_shutdown():\n\t\tfor robot_name in robot_name_list:\n\t\t\tpose_now = gazebo_model_object.get_model_pose(robot_name)\n\t\t\tif not pose_now:\n\t\t\t\tprint(\"The pose of \" + str(robot_name) + \" is not yet availble.\")\n\t\t\telse:\n\t\t\t\thandle_turtle_pose(pose_now, robot_name)\n\t\trate.sleep()\n\nif __name__=='__main__':\n\ttry:\n\t\tpublisher_of_tf()\n\texcept rospy.ROSInterruptException:\n\t\tpass\n","sub_path":"scripts/multipleBroadcaster.py","file_name":"multipleBroadcaster.py","file_ext":"py","file_size_in_byte":1282,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"584144293","text":"\"\"\"\n434. Number of Segments in a String\nGiven a string s, return the number of segments in the string.\n\nA segment is defined to be a contiguous sequence of non-space characters.\n\nExample 1:\n\nInput: s = \"Hello, my name is John\"\nOutput: 5\nExplanation: The five segments are [\"Hello,\", \"my\", \"name\", \"is\", \"John\"]\nExample 2:\n\nInput: s = \"Hello\"\nOutput: 1\n\nConstraints:\n\n0 <= s.length <= 300\ns consists of lowercase and uppercase English letters, digits, or one of the following characters \"!@#$%^&*()_+-=',.:\".\nThe only space character in s is ' '.\n\"\"\"\n\n\nclass Solution:\n def countSegments(self, s: str) -> int:\n allowed = \"!@#$%^&*()_+-=',.:\"\n answer = []\n for val in s.split():\n valid = True\n for rec in val:\n if not rec.isalnum() and rec not in allowed:\n valid = False\n break\n if valid:\n answer.append(val)\n return len(answer)\n\n\ns = \"Hello?, my name is John\"\ns = \" \"\n\nobj = Solution()\nprint(obj.countSegments(s))\n","sub_path":"leetcode/401_500/434_Number_of_Segments_in_a_String.py","file_name":"434_Number_of_Segments_in_a_String.py","file_ext":"py","file_size_in_byte":1045,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"11569532","text":"# -*- coding: utf-8 -*-\n\n\"\"\" Deep Residual Network.\nApplying a Deep Residual Network to CIFAR-10 Dataset classification task.\nReferences:\n - K. He, X. Zhang, S. Ren, and J. Sun. Deep Residual Learning for Image\n Recognition, 2015.\n - Learning Multiple Layers of Features from Tiny Images, A. Krizhevsky, 2009.\nLinks:\n - [Deep Residual Network](http://arxiv.org/pdf/1512.03385.pdf)\n - [CIFAR-10 Dataset](https://www.cs.toronto.edu/~kriz/cifar.html)\n\"\"\"\n\nfrom __future__ import division, print_function, absolute_import\n\nimport tflearn\nimport argparse\nimport os\n\nparser = argparse.ArgumentParser(description='ResNet.')\nparser.add_argument('-n', metavar='--nBlocks',nargs=1,type=int,required=True,\n help='Parametro n segun paper. #layers = 2 + (6n)')\nparser.add_argument('-e', metavar='--nBlocks',nargs=1,type=int,required=True,\n help='Cantidad de epochs')\nparser.add_argument('-a', metavar='--act',nargs=4,type=str,required=False,\n help='Configuracion de activaciones')\n\nparser.add_argument('-exp', metavar='--experimento',nargs=2,type=str,required=False,\n help='Id de experimento y funcion de activacion a aplicar')\n\nparser.add_argument('-b', metavar='--block-mode',nargs=1,type=str,required=False,\n help='Id de experimento y funcion de activacion a aplicar')\n\nparser.add_argument('-suf2', metavar='--suffix2',nargs=1,type=str,required=False,\n help='Sufijo 2 al nombre del modelo')\n\nargs = vars(parser.parse_args())\n\n# Residual blocks\n# 20 layers: n=3\n# 32 layers: n=5,\n# 44 layers: n=7,\n# 56 layers: n=9,\n# 110 layers: n=18\nexperimentos = {\n 'default':['relu','relu','relu','relu'],\n 'E1':[None,None,None,None],\n 'E2':[None,None,'relu','relu'],\n 'E3':['relu','relu',None,None],\n 'E4':[None,'relu','relu','relu'],\n 'E5':[None,'relu',None,None],\n 'E6':['relu',None,None,None]\n}\nn = args['n'][0]\nEPOCHS=args['e'][0]\nactivations = args['a']\nexperimento = args['exp']\n\nsuffix2 = args['suf2']\n\n\nif args['b'] == None:\n block_mode = 'reference'\nelse:\n block_mode = args['b'][0]\n\nif block_mode.upper() == 'REFERENCE':\n bn_position = 'before'\n last_actv = True\nelif block_mode.upper() == 'BN_AA':\n bn_position = 'after'\n last_actv = True\nelif block_mode.upper() == 'NO_RELU':\n bn_position = 'before'\n last_actv = False\n\nif experimento != None:\n id_exp = experimento[0]\n activ_fn = experimento[1]\n activations = experimentos[id_exp]\n activations = [activ_fn if v is None else v for v in activations]\n suffix = id_exp+'_'+activ_fn\nelif activations == None:\n activations = experimentos['default']\n suffix = 'default'\nelse:\n suffix = 'acts='+'_'.join(activations)\n\nlayers = (n*6)+2\n\n# Data loading\nfrom tflearn.datasets import cifar10\nfrom modulos import my_plain_block\n\n\n(X, Y), (testX, testY) = cifar10.load_data()\nY = tflearn.data_utils.to_categorical(Y,nb_classes=10)\ntestY = tflearn.data_utils.to_categorical(testY,nb_classes=10)\n\n# Real-time data preprocessing\nimg_prep = tflearn.ImagePreprocessing()\nimg_prep.add_featurewise_zero_center(per_channel=True)\n\n# Real-time data augmentation\nimg_aug = tflearn.ImageAugmentation()\nimg_aug.add_random_flip_leftright()\nimg_aug.add_random_crop([32, 32], padding=4)\n\n# Building Residual Network\nnet = tflearn.input_data(shape=[None, 32, 32, 3],\n data_preprocessing=img_prep,\n data_augmentation=img_aug)\nnet = tflearn.conv_2d(net, 16, 3, regularizer='L2', weight_decay=0.0001)\nnet = tflearn.batch_normalization(net)\nnet = tflearn.activation(net,activation=activations[0])\nnet = my_plain_block(net, n, 16,activation=activations[1],bn_position=bn_position,last_actv=last_actv)\nnet = my_plain_block(net, 1, 32, downsample=True,activation=activations[2],bn_position=bn_position,last_actv=last_actv)\nnet = my_plain_block(net, n-1, 32,activation=activations[2],bn_position=bn_position,last_actv=last_actv)\nnet = my_plain_block(net, 1, 64, downsample=True,activation=activations[3],bn_position=bn_position,last_actv=last_actv)\nnet = my_plain_block(net, n-1, 64,activation=activations[3],bn_position=bn_position,last_actv=last_actv)\nnet = tflearn.global_avg_pool(net)\n# Regression\nnet = tflearn.fully_connected(net, 10, activation='softmax')\nmom = tflearn.Momentum(0.1, lr_decay=0.1, decay_step=32000, staircase=True)\nnet = tflearn.regression(net, optimizer=mom,\n loss='categorical_crossentropy')\n# Training\nmodel = tflearn.DNN(net, checkpoint_path='./checkpoints/', tensorboard_verbose=0,tensorboard_dir='log',\n clip_gradients=0.)\n\n\nmodel_name = 'PLAIN_'+str(layers)+'_layers_'+str(EPOCHS)+'_epochs_BM='+block_mode+'_'+suffix\n\nif suffix2 != None:\n model_name = model_name +'_'+suffix2[0]\n\nmodel.fit(X, Y, n_epoch=EPOCHS, validation_set=(testX, testY),\n snapshot_epoch=True,\n show_metric=True, batch_size=128, shuffle=True,\n run_id='resnet_cifar10_'+model_name)\n\nmodel.save('./models_trained/resnet_cifar10_'+model_name+'_model')","sub_path":"Experiments_PlainNet.py","file_name":"Experiments_PlainNet.py","file_ext":"py","file_size_in_byte":5073,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"323571127","text":"from math import sqrt, cos, acos\n\nx1, y1 = map(float, input('Введите координаты первой точки: ').split())\nx2, y2 = map(float, input('Введите координаты первой точки: ').split())\nx3, y3 = map(float, input('Введите координаты первой точки: ').split())\n\nAB = sqrt((x2 - x1)**2 + (y2 - y1)**2)\nBC = sqrt((x3 - x2)**2 + (y3 - y2)**2)\nAC = sqrt((x1 - x3)**2 + (y1 - y3)**2)\n\nif (AC + AB) < BC or (AB + BC) < AC or (AC + BC) < AB \\\n or (x1 == x2 and y1 == y2) or (x2 == x3 and y2 == y3) or (x1 == x3 and y1 == y3):\n print('Треугольник не существует')\nelse:\n if AB > BC:\n maxSideValue = AB\n angle = acos((AC ** 2 + BC ** 2 - AB ** 2) / (2 * AC * BC))\n bisector = (2 * BC * AC * cos(angle / 2)) / (BC + AC)\n else:\n maxSideValue = BC\n angle = acos(((AB ** 2 + AC ** 2 - BC ** 2) / (2 * AB * AC)))\n bisector = (2 * AB * AC * cos(angle / 2)) / (AB + AC)\n if maxSideValue < AC:\n angle = acos(((BC ** 2 + AB ** 2 - AC ** 2) / (2 * AB * BC)))\n bisector = (2 * AB * BC * cos(angle / 2)) / (AB + BC)\n\n print('Биссектриса из большего угла:', '{:.7g}'.format(bisector))","sub_path":"1st_semester/Lab 3/Bogatyrev/def_Lab 3.py","file_name":"def_Lab 3.py","file_ext":"py","file_size_in_byte":1264,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"279280629","text":"# !/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\nfrom tkinter import *\nimport math\n\n# Изучите приведенную программу и самостоятельно запрограммируйте постепенное\n# движение фигуры в ту точку холста, где пользователь кликает левой кнопкой мыши.\n# Координаты события хранятся в его атрибутах x и y ( event.x , event.y ).\n\nclass Main_prog:\n def __init__(self, master, width=600, height=600):\n self.vect_x = 1\n self.vect_y = 1\n self.path = 0\n self.center_x = 0\n self.center_y = 0\n self.move_x = 0\n self.move_y = 0\n self.clck_x = 0\n self.clck_y = 0\n self.height = height\n self.width = width\n self.main_canv = Canvas(master, width=self.width, height=self.height, bg='black')\n self.rad = 10\n self.ball = self.main_canv.create_oval(self.width // 2 - self.rad + 100, self.height // 2 - self.rad + 100,\n self.width // 2 + self.rad + 100, self.height // 2 + self.rad + 100,\n fill='white')\n self.line =self.main_canv.create_line(self.width // 2, self.height / 2 - 200,\n self.width // 2, self.height / 2 + 200, fill='white')\n self.main_canv.pack()\n self.main_canv.bind('\n\n# ## 2 - Initialization\n# \n# We will write an helper functions that will initialize the parameters for our model using *Xavier initialization*.\n\n# In[5]:\n\n\ndef initialize_parameters_deep(layer_dims):\n \"\"\"\n Arguments:\n layer_dims -- python array (list) containing the dimensions of each layer in our network\n \n Returns:\n parameters -- python dictionary containing your parameters \"W1\", \"b1\", ..., \"WL\", \"bL\":\n Wl -- weight matrix of shape (layer_dims[l], layer_dims[l-1])\n bl -- bias vector of shape (layer_dims[l], 1)\n \"\"\"\n \n np.random.seed(3)\n parameters = {}\n L = len(layer_dims) # number of layers in the network\n\n for l in range(1, L):\n parameters['W' + str(l)] = np.random.randn(layer_dims[l], layer_dims[l-1])* np.sqrt((1/layers_dims[l-1]))\n parameters['b' + str(l)] = np.zeros((layer_dims[l], 1))\n \n assert(parameters['W' + str(l)].shape == (layer_dims[l], layer_dims[l-1]))\n assert(parameters['b' + str(l)].shape == (layer_dims[l], 1))\n\n \n return parameters\n\n\n# ### 3 - Forward propagation module\n# \n# Now that we have initialized our parameters, we will do the forward propagation module. We will start by implementing some basic functions that we will use later when implementing the model. We will complete two functions in this order:\n# \n# - LINEAR -> ACTIVATION where ACTIVATION will be either ReLU or Sigmoid. \n# - [LINEAR -> RELU] $\\times$ (L-1) -> LINEAR -> SIGMOID (whole model)\n# \n# The linear forward module (vectorized over all the examples) computes the following equations:\n# \n# $$Z^{[l]} = W^{[l]}A^{[l-1]} +b^{[l]}\\tag{4}$$\n# \n# where $A^{[0]} = X$. \n\n# In[7]:\n\n\ndef sigmoid(Z):\n \"\"\"\n Implementing the sigmoid activation in numpy\n \n Arguments:\n Z -- numpy array of any shape\n \n Returns:\n A -- output of sigmoid(z), same shape as Z\n cache -- returns Z as well, useful during backpropagation\n \"\"\"\n \n A = 1/(1+np.exp(-Z))\n cache = Z\n \n return A, cache\n\ndef relu(Z):\n \"\"\"\n Implementing the RELU function.\n\n Arguments:\n Z -- Output of the linear layer, of any shape\n\n Returns:\n A -- Post-activation parameter, of the same shape as Z\n cache -- a python dictionary containing \"A\" ; stored for computing the backward pass efficiently\n \"\"\"\n \n A = np.maximum(0,Z)\n \n assert(A.shape == Z.shape)\n \n cache = Z \n return A, cache\n\n\n# In[8]:\n\n\ndef linear_activation_forward(A_prev, W, b, activation):\n \"\"\"\n The forward propagation for the LINEAR->ACTIVATION layer\n\n Arguments:\n A_prev -- activations from previous layer (or input data): (size of previous layer, number of examples)\n W -- weights matrix: numpy array of shape (size of current layer, size of previous layer)\n b -- bias vector, numpy array of shape (size of the current layer, 1)\n activation -- the activation to be used in this layer, stored as a text string: \"sigmoid\" or \"relu\"\n\n Returns:\n A -- the output of the activation function, also called the post-activation value \n cache -- a python tuple containing \"linear_cache\" and \"activation_cache\";\n stored for computing the backward pass efficiently\n \"\"\"\n \n if activation == \"sigmoid\":\n # Inputs: \"A_prev, W, b\". Outputs: \"A, activation_cache\".\n \n Z, linear_cache = (np.dot(W, A_prev) + b, np.dot(W, A_prev) + b)\n A, activation_cache = sigmoid(Z)\n \n \n elif activation == \"relu\":\n # Inputs: \"A_prev, W, b\". Outputs: \"A, activation_cache\".\n \n Z, linear_cache = (np.dot(W, A_prev) + b, np.dot(W, A_prev) + b)\n A, activation_cache = relu(Z)\n \n \n assert (A.shape == (W.shape[0], A_prev.shape[1]))\n cache = (linear_cache, activation_cache)\n\n return A, cache\n\n\n# In[9]:\n\n\ndef L_model_forward(X, parameters):\n \"\"\"\n Implementing forward propagation for the [LINEAR->RELU]*(L-1)->LINEAR->SIGMOID computation\n \n Arguments:\n X -- data, numpy array of shape (input size, number of examples)\n parameters -- output of initialize_parameters_deep()\n \n Returns:\n AL -- last post-activation value\n caches -- list of caches containing:\n every cache of linear_activation_forward() (there are L-1 of them, indexed from 0 to L-1)\n \"\"\"\n\n caches = []\n A = X\n L = len(parameters) // 2 # number of layers in the neural network\n # Implement [LINEAR -> RELU]*(L-1). Add \"cache\" to the \"caches\" list.\n for l in range(1, L):\n A_prev = A \n \n W = parameters['W' + str(l)]\n b = parameters['b' + str(l)]\n A, cache = linear_activation_forward(A_prev, W, b, \"relu\")\n caches.append(cache)\n \n \n # Implement LINEAR -> SIGMOID. Add \"cache\" to the \"caches\" list.\n \n AL, cache = linear_activation_forward(A, parameters['W' + str(L)], parameters['b' + str(L)], \"sigmoid\")\n caches.append(cache)\n \n assert(AL.shape == (1,X.shape[1]))\n \n return AL, caches\n\n\n# ## 4 - Cost function\n# \n# Now we will implement forward. We need to compute the cost, because you want to check if your model is actually learning.\n\n# In[11]:\n\n\ndef compute_cost(AL, Y):\n \"\"\"\n Implement the cost function.\n\n Arguments:\n AL -- probability vector corresponding to your label predictions, shape (1, number of examples)\n Y -- true \"label\" vector (for example: containing 0 if non-cat, 1 if cat), shape (1, number of examples)\n\n Returns:\n cost -- cross-entropy cost\n \"\"\"\n \n m = Y.shape[1]\n\n # Compute loss from aL and y.\n cost = -(np.dot(Y,np.log(AL).T) + np.dot((1-Y),np.log(1-AL).T))/m\n \n cost = np.squeeze(cost) # To make sure your cost's shape is what we expect (e.g. this turns [[17]] into 17).\n assert(cost.shape == ())\n \n return cost\n\n\n# ## 5 - Backward propagation module\n# \n# Just like with forward propagation, you will implement helper functions for backpropagation. Remember that back propagation is used to calculate the gradient of the loss function with respect to the parameters. \n# \n# Now, similar to forward propagation, you are going to build the backward propagation in three steps:\n# - LINEAR backward\n# - LINEAR -> ACTIVATION backward where ACTIVATION computes the derivative of either the ReLU or sigmoid activation\n# - [LINEAR -> RELU] $\\times$ (L-1) -> LINEAR -> SIGMOID backward (whole model)\n\n# In[12]:\n\n\ndef relu_backward(dA, cache):\n \"\"\"\n Implementing the backward propagation for a single RELU unit.\n\n Arguments:\n dA -- post-activation gradient, of any shape\n cache -- 'Z' where we store for computing backward propagation efficiently\n\n Returns:\n dZ -- Gradient of the cost with respect to Z\n \"\"\"\n \n Z = cache\n dZ = np.array(dA, copy=True) # just converting dz to a correct object.\n \n # When z <= 0, you should set dz to 0 as well. \n dZ[Z <= 0] = 0\n \n assert (dZ.shape == Z.shape)\n \n return dZ\n\ndef sigmoid_backward(dA, cache):\n \"\"\"\n Implementing the backward propagation for a single SIGMOID unit.\n\n Arguments:\n dA -- post-activation gradient, of any shape\n cache -- 'Z' where we store for computing backward propagation efficiently\n\n Returns:\n dZ -- Gradient of the cost with respect to Z\n \"\"\"\n \n Z = cache\n \n s = 1/(1+np.exp(-Z))\n dZ = dA * s * (1-s)\n \n assert (dZ.shape == Z.shape)\n \n return dZ\n\n\n# In[ ]:\n\n\ndef linear_backward(dZ, cache):\n \"\"\"\n Implementing the linear portion of backward propagation for a single layer (layer l)\n\n Arguments:\n dZ -- Gradient of the cost with respect to the linear output (of current layer l)\n cache -- tuple of values (A_prev, W, b) coming from the forward propagation in the current layer\n\n Returns:\n dA_prev -- Gradient of the cost with respect to the activation (of the previous layer l-1), same shape as A_prev\n dW -- Gradient of the cost with respect to W (current layer l), same shape as W\n db -- Gradient of the cost with respect to b (current layer l), same shape as b\n \"\"\"\n A_prev, W, b = cache\n m = A_prev.shape[1]\n\n \n dW = np.dot(dZ, A_prev.T)/m\n db = np.sum(dZ, axis=1, keepdims=True)/m\n dA_prev = np.dot(W.T, dZ)\n \n \n assert (dA_prev.shape == A_prev.shape)\n assert (dW.shape == W.shape)\n assert (db.shape == b.shape)\n \n return dA_prev, dW, db\n\n\n# In[ ]:\n\n\ndef linear_activation_backward(dA, cache, activation):\n \"\"\"\n Implement the backward propagation for the LINEAR->ACTIVATION layer.\n \n Arguments:\n dA -- post-activation gradient for current layer l \n cache -- tuple of values (linear_cache, activation_cache) we store for computing backward propagation efficiently\n activation -- the activation to be used in this layer, stored as a text string: \"sigmoid\" or \"relu\"\n \n Returns:\n dA_prev -- Gradient of the cost with respect to the activation (of the previous layer l-1), same shape as A_prev\n dW -- Gradient of the cost with respect to W (current layer l), same shape as W\n db -- Gradient of the cost with respect to b (current layer l), same shape as b\n \"\"\"\n linear_cache, activation_cache = cache\n \n if activation == \"relu\": \n dZ = relu_backward(dA, activation_cache)\n dA_prev, dW, db = linear_backward(dZ, linear_cache)\n \n \n elif activation == \"sigmoid\":\n dZ = sigmoid_backward(dA, activation_cache)\n dA_prev, dW, db = linear_backward(dZ, linear_cache)\n \n \n return dA_prev, dW, db\n\n\n# In[13]:\n\n\ndef L_model_backward(AL, Y, caches):\n \"\"\"\n Implement the backward propagation for the [LINEAR->RELU] * (L-1) -> LINEAR -> SIGMOID group\n \n Arguments:\n AL -- probability vector, output of the forward propagation (L_model_forward())\n Y -- true \"label\" vector (containing 0 if non-cat, 1 if cat)\n caches -- list of caches containing:\n every cache of linear_activation_forward() with \"relu\" (it's caches[l], for l in range(L-1) i.e l = 0...L-2)\n the cache of linear_activation_forward() with \"sigmoid\" (it's caches[L-1])\n \n Returns:\n grads -- A dictionary with the gradients\n grads[\"dA\" + str(l)] = ... \n grads[\"dW\" + str(l)] = ...\n grads[\"db\" + str(l)] = ... \n \"\"\"\n grads = {}\n L = len(caches) # the number of layers\n m = AL.shape[1]\n Y = Y.reshape(AL.shape) # after this line, Y is the same shape as AL\n \n # Initializing the backpropagation\n dAL = - (np.divide(Y, AL) - np.divide(1 - Y, 1 - AL))\n \n # Lth layer (SIGMOID -> LINEAR) gradients. Inputs: \"dAL, current_cache\". Outputs: \"grads[\"dAL-1\"], grads[\"dWL\"], grads[\"dbL\"]\n current_cache = caches[L-1]\n grads[\"dA\" + str(L-1)], grads[\"dW\" + str(L)], grads[\"db\" + str(L)] = linear_activation_backward(dAL, current_cache, 'sigmoid')\n \n # Loop from l=L-2 to l=0\n for l in reversed(range(L-1)):\n # lth layer: (RELU -> LINEAR) gradients.\n # Inputs: \"grads[\"dA\" + str(l + 1)], current_cache\". Outputs: \"grads[\"dA\" + str(l)] , grads[\"dW\" + str(l + 1)] , grads[\"db\" + str(l + 1)] \n current_cache = caches[l]\n dA_prev_temp, dW_temp, db_temp = linear_activation_backward(grads[\"dA\" + str(l + 1)], current_cache, 'relu')\n grads[\"dA\" + str(l)] = dA_prev_temp\n grads[\"dW\" + str(l + 1)] = dW_temp\n grads[\"db\" + str(l + 1)] = db_temp\n\n return grads\n\n\n# ### 6 - Update Parameters\n# \n# In this section you will update the parameters of the model, using gradient descent: \n# \n# $$ W^{[l]} = W^{[l]} - \\alpha \\text{ } dW^{[l]} \\tag{16}$$\n# $$ b^{[l]} = b^{[l]} - \\alpha \\text{ } db^{[l]} \\tag{17}$$\n# \n# where $\\alpha$ is the learning rate. After computing the updated parameters, store them in the parameters dictionary. \n\n# In[15]:\n\n\ndef update_parameters(parameters, grads, learning_rate):\n \"\"\"\n Update parameters using gradient descent\n \n Arguments:\n parameters -- python dictionary containing your parameters \n grads -- python dictionary containing your gradients, output of L_model_backward\n \n Returns:\n parameters -- python dictionary containing your updated parameters \n parameters[\"W\" + str(l)] = ... \n parameters[\"b\" + str(l)] = ...\n \"\"\"\n \n L = len(parameters) // 2 # number of layers in the neural network\n\n # Update rule for each parameter. Use a for loop.\n for l in range(L):\n parameters[\"W\" + str(l+1)] = parameters[\"W\" + str(l+1)] - learning_rate*grads[\"dW\" + str(l + 1)]\n parameters[\"b\" + str(l+1)] = parameters[\"b\" + str(l+1)] - learning_rate*grads[\"db\" + str(l + 1)]\n return parameters\n\n\n# ## 7 - L-layer Neural Network\n# \n# By useing the helper functions we have implemented previously to build an $L$-layer neural network with the following structure: *[LINEAR -> RELU]$\\times$(L-1) -> LINEAR -> SIGMOID*. The functions you may need and their inputs are:\n# ```python\n# def initialize_parameters_deep(layers_dims):\n# ...\n# return parameters \n# def L_model_forward(X, parameters):\n# ...\n# return AL, caches\n# def compute_cost(AL, Y):\n# ...\n# return cost\n# def L_model_backward(AL, Y, caches):\n# ...\n# return grads\n# def update_parameters(parameters, grads, learning_rate):\n# ...\n# return parameters\n# ```\n\n# In[17]:\n\n\ndef L_layer_model(X, Y, layers_dims, learning_rate = 0.0075, num_iterations = 3000, print_cost=False):#lr was 0.009\n \"\"\"\n Implementing a L-layer neural network: [LINEAR->RELU]*(L-1)->LINEAR->SIGMOID.\n \n Arguments:\n X -- data, numpy array of shape (num_px * num_px * 3, number of examples)\n Y -- true \"label\" vector (containing 0 if cat, 1 if non-cat), of shape (1, number of examples)\n layers_dims -- list containing the input size and each layer size, of length (number of layers + 1).\n learning_rate -- learning rate of the gradient descent update rule\n num_iterations -- number of iterations of the optimization loop\n print_cost -- if True, it prints the cost every 100 steps\n \n Returns:\n parameters -- parameters learnt by the model. They can then be used to predict.\n \"\"\"\n\n np.random.seed(1)\n costs = [] # keep track of cost\n \n # Parameters initialization. (≈ 1 line of code)\n parameters = initialize_parameters_deep(layers_dims)\n \n # Loop (gradient descent)\n for i in range(0, num_iterations):\n\n # Forward propagation: [LINEAR -> RELU]*(L-1) -> LINEAR -> SIGMOID.\n AL, caches = L_model_forward(X, parameters)\n ### END CODE HERE ###\n \n # Compute cost.\n cost = compute_cost(AL, Y)\n \n # Backward propagation.\n grads = L_model_backward(AL, Y, caches)\n \n # Update parameters.\n parameters = update_parameters(parameters, grads, learning_rate)\n \n \n # Print the cost every 100 training example\n if print_cost and i % 100 == 0:\n print (\"Cost after iteration %i: %f\" %(i, cost))\n if print_cost and i % 100 == 0:\n costs.append(cost)\n \n # plot the cost\n plt.plot(np.squeeze(costs))\n plt.ylabel('cost')\n plt.xlabel('iterations (per hundreds)')\n plt.title(\"Learning rate =\" + str(learning_rate))\n plt.show()\n \n return parameters\n\n\nmodel = L_layer_model(X, Y, [128,64,64,1], learning_rate = 0.0075, num_iterations = 3000, print_cost=False)\n\n\n\n\n","sub_path":"dnn.py","file_name":"dnn.py","file_ext":"py","file_size_in_byte":17163,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"287100036","text":"# -*- coding: utf-8 -*-\n#动态规划解决方案\ninput = [2,1,0,-1,-2,3,1,2,3,-1,-2,-3]\n\ninput = [2,1,3,1,2, 3,-1,-2,-3]\njilu = []#-------------记录断点---位置---index-------------\nfor i in range(0,len(input)):\n cond = input[i] < input[i+1]#符合条件吗\n if(cond):\n jilu.append(i)#记录不连续的断点\n \n if(i==(len(input)-2)):\n jilu = [x + 1 for x in jilu] #将每次不合规律的下标index+1，指向下一个合规律的元素位置\n #为了不超出寻址范围，限定访问倒数第二个元素，就break\n break\n \nsta_jilu = jilu.copy() \njilu.insert(0,0) #方便运算\njilu.append(len(input))#方便运算\nle2 = []#------------每个子序列的长度\npos = []#------------每个子序列的起始位置\nfor x in range(0,len(jilu)-1): #--------记录的是index\n if(jilu[x+1]-jilu[x]>1):\n le2.append(jilu[x+1]-jilu[x] - 1)#记录长度，\n pos.append(jilu[x]) #记录长度对应的位置\n\nprint(\"max length is:\",max(le2))#寻找最大长度\nlook = pos[le2.index(max(le2))]#\nprint(\"result is:\",input[ pos[le2.index(max(le2))]: jilu[jilu.index(look) + 1] ])\n \n\n\n\n\n\n\n\ndef removeDuplicates(nums):\n \"\"\"\n :type nums: List[int]\n :rtype: int\n \"\"\"\n if not nums:return\n a = nums[0] \n i=1\n while i < len(nums):\n if nums[i] == a :\n del nums[i] \n else:\n a = nums[i]\n i += 1\n return len(nums)\n \nnums = [1,1,2,2,3,4]\ni=2\n","sub_path":"降连续最长.py","file_name":"降连续最长.py","file_ext":"py","file_size_in_byte":1609,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"249037077","text":"# Copyright (c) Microsoft Corporation. All rights reserved.\n# Licensed under the MIT license.\n\"\"\"tf2onnx.rewriter module.\"\"\"\n\nfrom __future__ import division\nfrom __future__ import print_function\nfrom __future__ import unicode_literals\n\n__all__ = [\n \"cond_rewriter\",\n \"custom_rnn_rewriter\",\n \"gru_rewriter\",\n \"loop_rewriter\",\n \"loop_rewriter_base\",\n \"lstm_rewriter\",\n \"random_uniform\",\n \"rnn\",\n \"rnn_utils\",\n \"unit_rewriter_base\"\n ]\n","sub_path":"tf2onnx/rewriter/__init__.py","file_name":"__init__.py","file_ext":"py","file_size_in_byte":466,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"287482537","text":"import pytest\n\nimport os\nimport pandas as pd\nfrom dataland.dataset import IncrementalDataset\n\n@pytest.fixture\ndef dataset():\n return pd.DataFrame({'col_a': [1, 2, 3], 'col_b': [4, 5, 6]})\n\nclass TestIncrementalDataset(object):\n def test_creates_new_local_dataset(self):\n incremental = IncrementalDataset('tmp/sample_dataset')\n metadata = open('tmp/sample_dataset/.metadata')\n\n assert metadata.read() == '{\"first_drop\": null, \"drop_count\": 0, \"last_drop\": null, columns: []}'\n\n @pytest.mark.freeze_time('2018-04-20 16:20:00.012')\n def test_store_create_new_data_drop(self, dataset):\n incremental = IncrementalDataset('tmp/sample_dataset/')\n\n assert not os.path.isfile('tmp/sample_dataset/2018-04-20-1620.csv')\n incremental.store(dataset)\n\n assert os.path.isfile('tmp/sample_dataset/2018-04-20-1620.csv')\n","sub_path":"tests/dataland/test_dataset.py","file_name":"test_dataset.py","file_ext":"py","file_size_in_byte":864,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"245313206","text":"# -*- coding: utf-8 -*-\n\nimport json\nimport os\nimport datetime\nimport urllib2\nimport time\n\nfrom settings import download_dir, configurelog, testlogger\nfrom lib.nonsdmx import NonSdmx\n\nendpoint = 'http://data.stats.gov.cn/english/easyquery.htm'\nTREE_URL = endpoint + '?id=%(id)s&dbcode=%(dbcode)s&wdcode=%(wdcode)s&m=getTree'\n\nABORT_ON_UNCHANGED = True\nlogger = testlogger()\n\n\ndef is_parent(nodes):\n \"\"\"\n Parse pages for item tha have no child recursively, if find that\n item pass it to scrape data function\n \"\"\"\n for node in nodes:\n if node['isParent']:\n time.sleep(1)\n new_page = urllib2.urlopen(TREE_URL % node).read()\n new_page = json.loads(new_page)\n is_parent(new_page)\n else:\n parse_table(node)\n\n\ndef parse_table(terminal_node):\n tgt_dir = os.path.join(download_dir, 'china_nbs')\n if not os.path.exists(tgt_dir):\n os.makedirs(tgt_dir)\n\n lastupdate = datetime.datetime.today().date()\n item_id = terminal_node['id']\n item_name = terminal_node['name']\n url = endpoint + ('?m=QueryData&dbcode=%(dbcode)s&'\n 'rowcode=%(wdcode)s&colcode=sj&wds=[]&'\n 'dfwds=[{\"wdcode\":\"zb\",\"valuecode\":\"%(id)s\"},'\n '{\"wdcode\":\"sj\",\"valuecode\":\"LAST200\"}]') % terminal_node\n in_in_page = urllib2.urlopen(url).read()\n json_response = json.loads(in_in_page.decode('utf8'))\n data, returncode = json_response['returndata'], json_response['returncode']\n assert(returncode == 200)\n\n nsi = NonSdmx(**{'db_name': 'NBS',\n 'dataset': 'NBS_'+ item_id,\n 'logger': logger,\n 'lastupdate': lastupdate, # need to change\n 'source': 'National Bureau of Statistics, China',\n 'description': terminal_node['name'],\n 'access_url': endpoint,\n 'ABORT_ON_UNCHANGED': ABORT_ON_UNCHANGED})\n\n if not nsi.create_conn():\n return nsi.unchanged()\n\n for v in data['returndata']['wdnodes'][0]['nodes']:\n serial = v['code']\n descrip = v['memo']\n units = v['unit']\n scale = 0\n sadj = None\n addinfo = {}\n dates = []\n all_values = []\n\n for val in data['returndata']['datanodes']:\n if serial == val['wds'][0]['valuecode']:\n date = (val['wds'][1]['valuecode'])\n date = datetime.datetime.strptime(date, '%Y%m')\n\n dates.append(date)\n all_values.append(val['data']['data'])\n\n values = {'serial': serial,\n 'freq': freq,\n 'iso2': 'CN',\n 'descrip': descrip,\n 'seasonaladj': sadj,\n 'scale': scale,\n 'units': units,\n 'addinfo': addinfo,\n 'lastupdate': datetime.datetime.today().date(),\n 'values': {'dates': dates[::-1],\n 'data': all_values[::-1]}\n }\n nsi.append_values(values)\n nsi.process_and_close()\n\n\n@configurelog(__file__)\ndef domain(logger):\n \"\"\"\n get dict item as input form request for non parent item, create\n path like in initial tree and save json file there\n \"\"\"\n parse_page = urllib2.urlopen(endpoint +\n '?id=&dbcode=hgyd&wdcode=zb&m=getTree').read()\n start_nodes = json.loads(parse_page)\n is_parent(start_nodes)\n\n\nif __name__ == \"__main__\":\n if 0:\n domain()\n","sub_path":"ch_stat_example.py","file_name":"ch_stat_example.py","file_ext":"py","file_size_in_byte":3523,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"240796070","text":"import os\r\npath = 'C:/Users/Ane/Desktop/Gehitutakoak2'\r\n\r\nfor direkt in os.listdir(path):\r\n bidea = os.path.join(path,direkt)\r\n if os.path.isdir(bidea):\r\n files = os.listdir(bidea)\r\n\r\n #hitza = 'Octopus_'\r\n hitza = direkt\r\n\r\n for file in files:\r\n if file[0].isdigit():\r\n berria = hitza+'_'+file\r\n os.rename(os.path.join(bidea, file), os.path.join(bidea, berria))\r\n","sub_path":"izenak2.py","file_name":"izenak2.py","file_ext":"py","file_size_in_byte":439,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"7070258","text":"import itertools, functools, numpy as np, xarray as xr, rpxdock as rp, rpxdock.homog as hm\nfrom rpxdock.search import hier_search, trim_ok\n\ndef make_onecomp(\n body,\n spec,\n hscore,\n search=hier_search,\n sampler=None,\n fixed_components=False,\n **kw,\n):\n arg = rp.Bunch(kw)\n t = rp.Timer().start()\n arg.nresl = hscore.actual_nresl if arg.nresl is None else arg.nresl\n arg.output_prefix = arg.output_prefix if arg.output_prefix else spec.arch\n\n assert isinstance(body, rp.Body)\n if not fixed_components:\n body = body.copy_xformed(rp.homog.align_vector([0, 0, 1], spec.axis))\n\n dotrim = arg.max_trim and arg.trimmable_components\n evaluator = OneCompEvaluator(body, spec, hscore, **arg)\n xforms, scores, extra, stats = search(sampler, evaluator, **arg)\n ibest = rp.filter_redundancy(xforms, body, scores, **arg)\n # tdump = _debug_dump_cage(xforms, body, spec, scores, ibest, evaluator, **arg)\n\n if arg.verbose:\n print(f\"rate: {int(stats.ntot / t.total):,}/s ttot {t.total:7.3f}\")\n print(\"stage time:\", \" \".join([f\"{t:8.2f}s\" for t, n in stats.neval]))\n print(\"stage rate: \", \" \".join([f\"{int(n/t):7,}/s\" for t, n in stats.neval]))\n\n xforms = xforms[ibest]\n wrpx = arg.wts.sub(rpx=1, ncontact=0)\n wnct = arg.wts.sub(rpx=0, ncontact=1)\n rpx, extra = evaluator(xforms, arg.nresl - 1, wrpx)\n ncontact, *_ = evaluator(xforms, arg.nresl - 1, wnct)\n data = dict(\n attrs=dict(arg=arg, stats=stats, ttotal=t.total, output_prefix=arg.output_prefix,\n output_body='all', sym=spec.arch),\n scores=([\"model\"], scores[ibest].astype(\"f4\")),\n xforms=([\"model\", \"hrow\", \"hcol\"], xforms),\n rpx=([\"model\"], rpx.astype(\"f4\")),\n ncontact=([\"model\"], ncontact.astype(\"f4\")),\n )\n for k, v in extra.items():\n if not isinstance(v, (list, tuple)) or len(v) > 3:\n v = ['model'], v\n data[k] = v\n data['disp'] = (['model'], np.sum(xforms[:, :3, 3] * spec.axis[None, :3], axis=-1).squeeze())\n data['angle'] = (['model'], rp.homog.angle_of(xforms[:]) * 180 / np.pi)\n default_label = ['compA']\n\n return rp.Result(\n body_=None if arg.dont_store_body_in_results else [body],\n body_label_=[] if arg.dont_store_body_in_results else default_label,\n **data,\n )\n\nclass OneCompEvaluator:\n def __init__(self, body, spec, hscore, wts=rp.Bunch(ncontact=0.1, rpx=1.0),\n trimmable_components=\"AB\", **kw):\n self.arg = rp.Bunch(kw)\n self.hscore = hscore\n self.symrot = rp.geom.symframes(spec.nfold)\n self.spec = spec\n self.arg.wts = wts\n self.body = body.copy_with_sym(spec.nfold, spec.axis)\n self.trimmable_components = trimmable_components\n\n def __call__(self, xforms, iresl=-1, wts={}, **kw):\n arg = self.arg.sub(wts=wts)\n xeye = np.eye(4, dtype=\"f4\")\n body, sfxn = self.body, self.hscore.scorepos\n X = xforms.reshape(-1, 4, 4) #@ body.pos\n Xsym = self.spec.to_neighbor_olig @ X\n\n # check clash, or get non-clash range\n ok = np.ones(len(xforms), dtype='bool')\n if arg.max_trim > 0:\n trim = body.intersect_range(body, X[ok], Xsym[ok], **arg)\n trim, trimok = rp.search.trim_ok(trim, body.nres, **arg)\n ok[ok] &= trimok\n else:\n ok[ok] &= body.clash_ok(body, X[ok], Xsym[ok], **arg)\n trim = [0], [body.nres - 1]\n\n # if iresl == 4:\n # i = 0\n # body.pos = X[i]\n # body.dump_pdb('topscore1.pdb')\n # body.pos = Xsym[i]\n # body.dump_pdb('topscore2.pdb')\n # assert 0\n\n # score everything that didn't clash\n scores = np.zeros(len(X))\n bounds = (*trim, -1, *trim, -1)\n scores[ok] = sfxn(body, body, X[ok], Xsym[ok], iresl, bounds, **arg)\n\n # record ranges used\n lb = np.zeros(len(scores), dtype=\"i4\")\n ub = np.ones(len(scores), dtype=\"i4\") * (body.nres - 1)\n if trim: lb[ok], ub[ok] = trim[0], trim[1]\n\n return scores, rp.Bunch(reslb=lb, resub=ub)\n","sub_path":"rpxdock/search/onecomp.py","file_name":"onecomp.py","file_ext":"py","file_size_in_byte":4003,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"345387554","text":"# template for \"Stopwatch: The Game\"\r\n\r\nimport simplegui\r\n\r\n# define global variables\r\ntime = 0\r\nstop_count = 0\r\nsuc_count = 0\r\n\r\n# define helper function format that converts time\r\n# in tenths of seconds into formatted string A:BC.D\r\ndef format(t):\r\n min = t / 600\r\n sec = (t % 600) / 10\r\n tenth_sec = (t % 600) % 10\r\n \r\n result = str(min).rjust(1, '0') + ':' + \\\r\n str(sec).rjust(2, '0') + '.' + \\\r\n str(tenth_sec)\r\n return result\r\n \r\n# define event handlers for buttons; \"Start\", \"Stop\", \"Reset\"\r\ndef start_handler():\r\n timer.start()\r\n \r\ndef stop_handler():\r\n global stop_count, suc_count\r\n timer.stop()\r\n stop_count = stop_count + 1\r\n if(time % 10 == 0):\r\n suc_count = suc_count + 1\r\n \r\ndef reset_handler():\r\n global time, stop_count, suc_count\r\n time = 0\r\n stop_count = 0\r\n suc_count = 0\r\n \r\n\r\n# define event handler for timer with 0.1 sec interval\r\ndef timer_handler():\r\n global time\r\n time = time + 1\r\n #print time\r\n\r\n\r\n# define draw handler\r\ndef draw_handler(canvas):\r\n global time, stop_count, suc_count\r\n canvas.draw_text(format(time), [20, 50], 20, 'Blue')\r\n canvas.draw_text(str(suc_count) + '/' + \\\r\n str(stop_count), [20, 25], 20, 'Blue')\r\n \r\n# create frame\r\nf = simplegui.create_frame('StopWatch', 100, 200)\r\n\r\n# register event handlers\r\n\r\nf.set_draw_handler(draw_handler)\r\nf.set_canvas_background('white')\r\n\r\n# add buttons:\r\nf.add_button('START', start_handler, 70)\r\nf.add_button('STOP', stop_handler, 70)\r\nf.add_button('RESET', reset_handler, 70)\r\n\r\ntimer = simplegui.create_timer(10, timer_handler)\r\n#timer.start()\r\n\r\n\r\n# start frame\r\nf.start()\r\n\r\n# Please remember to review the grading rubric\r\n","sub_path":"StopWatch.py","file_name":"StopWatch.py","file_ext":"py","file_size_in_byte":1733,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"321085723","text":"#!/usr/bin/env python2.7\n# encoding: utf-8\n# Copyright (c) 2016 Dilusense Inc. All Rights Reserved.\nimport logging\nfrom msg_trans import ZMQPort\nfrom msg_trans.thread_subs_msg import SubsMsgServer\nfrom services.msg_center.zmq_msg_connections import ZMQConns\nfrom utils.global_info import GlobalInfo\nfrom utils.my_constant import MyConstant\nfrom utils.regular_expression import Regular\nfrom utils.serialize_utils import SerializeUtils\n\n\nclass PortalMsgManager(object):\n\n @staticmethod\n def add_new_conn(ip):\n if Regular.verify_ip(ip):\n sms = SubsMsgServer(ip, ZMQPort.SUBS)\n sms.start()\n if sms.isAlive():\n ZMQConns().put(ip, sms)\n else:\n logging.getLogger(GlobalInfo.logger_main).info('ip: ' + ip + ' is unlawful can not connect to server')\n\n\n @staticmethod\n def init_portals():\n ips = SerializeUtils.get(MyConstant.portal_ips_serialize_data_key)\n if ips is None:\n logging.getLogger(GlobalInfo.logger_main).info('no ip to init zmq conn')\n return\n ips = set(ips)\n for ip in ips:\n PortalMsgManager.add_new_conn(ip)\n\n\n @staticmethod\n def update_portals(ips):\n smss = ZMQConns().get_all()\n sms_keys = ([])\n ip_keys = ([])\n\n if type(ips) == dict:\n ip_keys_store = {}\n elif type(ips) == list:\n ip_keys_store = []\n else:\n raise NameError('parameter of this method must be dict or list')\n\n try:\n ip_keys = set(ips)\n except:\n pass\n try:\n sms_keys = set(smss)\n except:\n pass\n\n new_ips = ip_keys - sms_keys\n old_ips = sms_keys - ip_keys\n intersection_ips = ip_keys & sms_keys\n\n for ip_key in ip_keys:\n if type(ips) == dict:\n ip_keys_store[ip_key] = ips[ip_key]\n else:\n ip_keys_store.append(ip_key)\n\n\n for ip in intersection_ips:\n logging.getLogger(GlobalInfo.logger_main).info('portal of ip: ' + ip + ' msg passageway is already exits')\n\n for ip in old_ips:\n if ZMQConns().get(ip) is not None:\n ZMQConns().get(ip).run_flag = False\n ZMQConns().remove(ip)\n\n for ip in new_ips:\n PortalMsgManager.add_new_conn(ip)\n\n SerializeUtils.update(MyConstant.portal_ips_serialize_data_key, ip_keys_store)\n\n","sub_path":"backend/src/app/services/msg_center/portal_msg_manager.py","file_name":"portal_msg_manager.py","file_ext":"py","file_size_in_byte":2451,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"117125525","text":"from fire_eye.fire_eye import FireEye\nimport os\nimport matplotlib.pyplot as plt\nimport seaborn as sns\n\n\nif __name__ == '__main__':\n\t# create an instance of a FireEye object\n\teye = FireEye()\n\n\t# scrape some new images\n\teye.scrape_more_data(num_images=2,\n\t\t\t\t\t\t pos_queries=['Forest Fire', 'wildfire'],\n\t\t\t\t\t\t neg_queries=['Forest', 'autumn forest'])\n\t\n\t# load any previously scraped images into the preprocessed dataset\n\teye.load_scraped_data(pos_queries=['Forest Fire', 'wildfire'],\n\t\t\t\t\t\t neg_queries=['Forest', 'autumn forest'])\n\t# load kaggle dataset images into the preprocessed dataset\n\teye.load_kaggle_data()\n\t# print the dataset breakdown of train/validation/test\n\tprint(eye.get_dataset_sizes())\n\n\t# train the model for a specified number of epochs\n\tfig0 = eye.train_model(num_epochs=2)\n\t\n\t# evaluate the model and produce relevant figures\n\tfig1, fig2 = eye.evaluate_model()\n\n\t# optionally save the model\n\teye.save_model('demo_model')\n\t\n\t# display all figures\n\tplt.show()\n\n\n\t'''\n\tThe following is an example script that might be run after training\n\tto further evaluate the trained model. In general, scripts should first\n\tload data, then either load or train a model, and finally evaluate the\n\tperformance of the model.\n\n\tthe preprocessed directory should be cleaned before starting a new dataset.\n\tRefer to the Makefile and README.md\n\n\t# after training (and cleaning preprocessed data), consider loading new data\n\teye.load_scraped_data(pos_queries=['Forest Fire'],\n \t\t\t\t\t\t neg_queries=['autumn forest'])\n\t# load the trained model as well\n\teye.load_model('full_dataset_model')\n\t# evaluate the model on the new dataset\n\tfig1, fig2 = eye.evaluate_model(title_prefix='Kaggle Datasets ')\n\tplt.show()\n\t'''\n\n","sub_path":"fire_eye/__main__.py","file_name":"__main__.py","file_ext":"py","file_size_in_byte":1711,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"592030549","text":"# Modules\nimport datetime as dt\nfrom typing import List\nimport matt\n# ------------------------------------------------------------------------------------------------------------------------------------------------------\n# User Input\narguments = {\n \"BranchIds\" : {\"type\" : List[int], \"names\" : [\"i\", \"bids\", \"branchids\"], \"default\" : [], \"info\" : \"List of branches to assign surveys for.\"},\n \"ClosureDate\" : {\"type\" : dt.date, \"names\" : [\"c\", \"cl\", \"closuredate\"], \"default\" : dt.date.today(), \"info\" : \"Date at which the branches will close.\"},\n \"Logging\" : {\"type\" : bool, \"names\" : [\"l\", \"log\", \"logging\"], \"default\" : True, \"info\" : R\"Log the SQL statments executed by this script in 'E:\\Oneoffs'.\"},\n \"Autocommit\" : {\"type\" : bool, \"names\" : [\"a\", \"ac\", \"autocommit\"], \"default\" : False, \"info\" : \"Automatically commit all transactions in this script instead of requesting user permission.\"}\n}\nargs = matt.args.IOHandler(arguments=arguments, program_desc=\"Script to make new entries in the branch closures table.\")\nbranch_ids, closure_date, logging, autocommit = args[\"BranchIds\"], args[\"ClosureDate\"], args[\"Logging\"], args[\"Autocommit\"]\n# ------------------------------------------------------------------------------------------------------------------------------------------------------\n# Setup\nalch = matt.sql.Alchemy(schemas=[\"base\"])\ns, tables = alch.session, alch.reflection.classes\nClosures = tables.branch_closures\nalch.initialize_log(\"BranchClosures\", logdir=matt.lbg.one_offs_path, active=logging)\n# ------------------------------------------------------------------------------------------------------------------------------------------------------\n# Execution\nextant = [rec[0] for rec in s.query(Closures.branch_id).filter(Closures.branch_id.in_(branch_ids)).all()]\nif extant:\n raise ValueError(f\"Duplicate branch ids {[branch for branch in branch_ids if branch in extant]} not allowed.\")\n\nnew = [Closures(branch_id=branch, closure_date=closure_date, processed=None, created_date=alch.func.now(), last_modified_date=alch.func.now()) for branch in branch_ids]\nalch.insert_statement_with_safeguards(new, select_from=Closures, autocommit=autocommit)\n","sub_path":"Scripts/Ongoing/NewBranchClosures.py","file_name":"NewBranchClosures.py","file_ext":"py","file_size_in_byte":2240,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"610011612","text":"'''\n输入一个整数数组，实现一个函数来调整该数组中数字的顺序，使得所有的奇数位于数组的前半部分，所有的偶数位于数组的后半部分，\n并保证奇数和奇数，偶数和偶数之间的相对位置不变。\n'''\n'''\narray = [1,2,3,4,5,6,]\ndef reOrderArray(array):\n help1 = []\n help2 = []\n for i in array:\n if i % 2 != 0:\n help1.append(i)\n else:\n help2.append(i)\n help1.extend(help2)\n return help1\na = reOrderArray(array)\nprint(a)\n'''\narray = [1,2,3,4,5,6,]\ndef reOrderArray1(array):\n for i in range(len(array)-1):\n for j in range(len(array)-1,0,-1):\n if array[j] % 2 == 1 and array[j-1] % 2 == 0:\n array[j],array[j-1] = array[j-1],array[j]\n return array\nb = reOrderArray1(array)\nprint(b)\n","sub_path":"day20/reOrderArray.py","file_name":"reOrderArray.py","file_ext":"py","file_size_in_byte":828,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"118999857","text":"# -*- coding: utf-8 -*-\n\n'''\nThis code calculates impacts of temperature changes induced by aerosols on GDP\n\npositive results mean benefits from aerosol-induced cooling\n\ndamage function developed in Burke, Matthew Davis, and Diffenbaugh (2018) \n\nassume results of each year is independent for the CESM repeating cycle simulations\n\ncalculate for each grid\n\nclimatological temeprature obtained from the ERA-Interim reanalysis dataset\n\nby Yixuan Zheng (yxzheng@carnegiescience.edu)\n''' \n \n\nimport pandas as pd\nimport numpy as np\nimport _env\nimport datetime\nimport xarray as xr\n\nnens = _env.nens\n\nyear = _env.year\nsyr = str(year)\ngdp_year = year\nsgdp_year = str(gdp_year)\n\npar = 'TREFHT' \nds = 'ERA-Interim'\n\nrean_ttag = '2001-2018'\n\nif_base = _env.idir_root+ '/reanalysis/ERA-Interim_Surface_Temp_' + rean_ttag + '_Regridded.nc'\nif_sim = _env.odir_root + '/sim_temperature/Simulated_Global_Gridded_' + par + '.nc'\n\nif_boot_par = _env.idir_root + 'Burke2018_Replication/data/output/bootstrap.csv'\nif_pop = _env.idir_root + '/pop/GPW_POP_25x19deg_2000.nc'\n\n\nodir_gdp = _env.odir_root + '/gdp_' + ds + '/'\n_env.mkdirs(odir_gdp)\n\nscenarios = ['With-Aerosol','No-Aerosol'] \n#read gridded temperature\n\n##base temperature from reanalysis data (ERA-Interim)\ni_base = xr.open_dataset(if_base)\ni_base = i_base.expand_dims({'ensembles':8})\n\ni_base.transpose('ensembles', 'lat', 'lon')\nT_grid_base = i_base['t2m_mean'] - 273.15 #K to C\n\n\ni_sim = xr.open_dataset(if_sim)\n\nT_grid_wa = i_sim[par + '_' +scenarios[0] + '_ensemble'] #With-Aerosol\nT_grid_na = i_sim[par + '_' +scenarios[1] + '_ensemble'] #No-Aerosol\n\nT_grid_na = T_grid_base - T_grid_wa + T_grid_na\nT_grid_wa = T_grid_base.copy()\n\n#bootstrap methods\nitbl_boots_par = pd.read_csv(if_boot_par,index_col=0)\nboot_methods = (pd.unique(itbl_boots_par['spec'])).tolist() #['country-lag0','country-lag1','country-lag5','year','year-blocks']\n\n#columns of output gdp ratio tables\n\n#dict stores all output tables\notbls_boot = {}\nomtrxs_ratio = {}\nomtrxs_gdp = {}\n\nfor b_m in boot_methods: #loop of bootstarpping methods \n \n mtbl_boot_par_b1 = xr.DataArray(itbl_boots_par.loc[itbl_boots_par['spec'] == b_m,'b1'],\n dims=('boots')\n )\n \n mtbl_boot_par_b2 = xr.DataArray(itbl_boots_par.loc[itbl_boots_par['spec'] == b_m,'b2'],\n dims=('boots')\n )\n \n o_dgr = xr.DataArray(np.zeros([len(mtbl_boot_par_b1),i_sim.ensembles.size,i_sim.lat.size,i_sim.lon.size]),\n dims=('boots', 'ensembles','lat','lon'),\n coords={'lat': i_sim.lat,\n 'lon': i_sim.lon})\n \n o_dgr = (T_grid_na*mtbl_boot_par_b1 + T_grid_na**2*mtbl_boot_par_b2) - (T_grid_wa*mtbl_boot_par_b1 + T_grid_wa**2*mtbl_boot_par_b2)\n \n o_dgr_m = o_dgr.median(dim=['boots','ensembles'])\n \n o_dgr.attrs['desc'] = 'Median of impacts of aerosol-induced cooling on annual GDP growth rate'\n \n ods = xr.Dataset({'GDP_Ratio_Median': o_dgr_m})\n \n ods.attrs['by'] = 'Yixuan Zheng (yxzheng@carnegiescience.edu)'\n ods.attrs['desc'] = 'Impacts of aerosol-induced cooling on GDP growth rate (based on damage functions developed by Burke et al. 2018)'\n ods.attrs['creattime'] = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')\n \n ods.to_netcdf(odir_gdp + 'GDP_Changes_Burke_' + b_m + '_' + sgdp_year +'_' + ds + '_' + scenarios[1] + '_gridded.nc')\n","sub_path":"modules/5.Cal_gdp_benefit_grid_Burke.py","file_name":"5.Cal_gdp_benefit_grid_Burke.py","file_ext":"py","file_size_in_byte":3487,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"296224955","text":"from django import forms\nfrom .models import Club\nfrom django.core.exceptions import ValidationError\nfrom django.utils.translation import ugettext_lazy as _\n\n\n# Form for adding a new Club\nclass ClubForm(forms.Form):\n\tname = forms.CharField(label='Club Name', max_length=64,required=True)\n\twebsite = forms.CharField(label='Website', max_length=128,required=False)\n\n\tclass Meta:\n\t\tmodel = Club\n\t\tfields = {'name' , 'email' , 'website' , 'meeting_times' , 'president' , 'treasurer' , 'icc_rep'}\n\n\tdef save(self, commit=True):\n\t\tclub = Club()\n\t\tclub.name = self.cleaned_data['name']\n\t\tclub.website = self.cleaned_data['website']\n\n\t\tif commit:\n\t\t\tclub.save()\n\n\t\treturn club\n\t\n# Form for editing the a Club that already exists\nclass EditClubForm(forms.Form):\n\tid = forms.IntegerField(required=True)\n\tname = forms.CharField(label='Club Name', max_length=64,required=True)\n\twebsite = forms.URLField(label='Website', max_length=128,required=False)\n\temail = forms.EmailField(label='Email', max_length=256,required=False)\n\tmeeting_times = forms.CharField(label='Meeting Times', max_length=256,required=False)\n\n\tclass Meta:\n\t\tmodel = Club\n\t\tfields = {'id', 'name' , 'email' , 'website' , 'meeting_times'}\n\n\tdef save(self, commit=True, user_id = None):\n\t\tclub = Club.objects.filter(id=self.cleaned_data['id'])\n\t\tif len(club) == 1:\n\t\t\tclub = club[0]\n\t\t# check if the person updating the club actually has access\n\t\tif user_id in {club.president, club.treasurer, club.icc_rep}:\n\t\t\tclub.name = self.cleaned_data['name']\n\t\t\tclub.website = self.cleaned_data['website']\n\t\t\tclub.email = self.cleaned_data['email']\n\t\t\tclub.meeting_times = self.cleaned_data['meeting_times']\n\t\n\t\t\tif commit:\n\t\t\t\tclub.save()\n\t\telse:\n\t\t\traise ValidationError(message = \"User ID \" + str(user_id) + \" doesn't have permission to edit Club ID \" + str(club.id) )\n\n\t\treturn club","sub_path":"projectx/forms.py","file_name":"forms.py","file_ext":"py","file_size_in_byte":1830,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"190699760","text":"#following the implementation found on https://github.com/boppreh/aes/blob/master/aes.py\r\n#load the Sbox and Sbox_inv into our python file\r\nSbox = (\r\n 0x63, 0x7C, 0x77, 0x7B, 0xF2, 0x6B, 0x6F, 0xC5, 0x30, 0x01, 0x67, 0x2B, 0xFE, 0xD7, 0xAB, 0x76,\r\n 0xCA, 0x82, 0xC9, 0x7D, 0xFA, 0x59, 0x47, 0xF0, 0xAD, 0xD4, 0xA2, 0xAF, 0x9C, 0xA4, 0x72, 0xC0,\r\n 0xB7, 0xFD, 0x93, 0x26, 0x36, 0x3F, 0xF7, 0xCC, 0x34, 0xA5, 0xE5, 0xF1, 0x71, 0xD8, 0x31, 0x15,\r\n 0x04, 0xC7, 0x23, 0xC3, 0x18, 0x96, 0x05, 0x9A, 0x07, 0x12, 0x80, 0xE2, 0xEB, 0x27, 0xB2, 0x75,\r\n 0x09, 0x83, 0x2C, 0x1A, 0x1B, 0x6E, 0x5A, 0xA0, 0x52, 0x3B, 0xD6, 0xB3, 0x29, 0xE3, 0x2F, 0x84,\r\n 0x53, 0xD1, 0x00, 0xED, 0x20, 0xFC, 0xB1, 0x5B, 0x6A, 0xCB, 0xBE, 0x39, 0x4A, 0x4C, 0x58, 0xCF,\r\n 0xD0, 0xEF, 0xAA, 0xFB, 0x43, 0x4D, 0x33, 0x85, 0x45, 0xF9, 0x02, 0x7F, 0x50, 0x3C, 0x9F, 0xA8,\r\n 0x51, 0xA3, 0x40, 0x8F, 0x92, 0x9D, 0x38, 0xF5, 0xBC, 0xB6, 0xDA, 0x21, 0x10, 0xFF, 0xF3, 0xD2,\r\n 0xCD, 0x0C, 0x13, 0xEC, 0x5F, 0x97, 0x44, 0x17, 0xC4, 0xA7, 0x7E, 0x3D, 0x64, 0x5D, 0x19, 0x73,\r\n 0x60, 0x81, 0x4F, 0xDC, 0x22, 0x2A, 0x90, 0x88, 0x46, 0xEE, 0xB8, 0x14, 0xDE, 0x5E, 0x0B, 0xDB,\r\n 0xE0, 0x32, 0x3A, 0x0A, 0x49, 0x06, 0x24, 0x5C, 0xC2, 0xD3, 0xAC, 0x62, 0x91, 0x95, 0xE4, 0x79,\r\n 0xE7, 0xC8, 0x37, 0x6D, 0x8D, 0xD5, 0x4E, 0xA9, 0x6C, 0x56, 0xF4, 0xEA, 0x65, 0x7A, 0xAE, 0x08,\r\n 0xBA, 0x78, 0x25, 0x2E, 0x1C, 0xA6, 0xB4, 0xC6, 0xE8, 0xDD, 0x74, 0x1F, 0x4B, 0xBD, 0x8B, 0x8A,\r\n 0x70, 0x3E, 0xB5, 0x66, 0x48, 0x03, 0xF6, 0x0E, 0x61, 0x35, 0x57, 0xB9, 0x86, 0xC1, 0x1D, 0x9E,\r\n 0xE1, 0xF8, 0x98, 0x11, 0x69, 0xD9, 0x8E, 0x94, 0x9B, 0x1E, 0x87, 0xE9, 0xCE, 0x55, 0x28, 0xDF,\r\n 0x8C, 0xA1, 0x89, 0x0D, 0xBF, 0xE6, 0x42, 0x68, 0x41, 0x99, 0x2D, 0x0F, 0xB0, 0x54, 0xBB, 0x16\r\n )\r\nSbox_inv = (\r\n 0x52, 0x09, 0x6A, 0xD5, 0x30, 0x36, 0xA5, 0x38, 0xBF, 0x40, 0xA3, 0x9E, 0x81, 0xF3, 0xD7, 0xFB,\r\n 0x7C, 0xE3, 0x39, 0x82, 0x9B, 0x2F, 0xFF, 0x87, 0x34, 0x8E, 0x43, 0x44, 0xC4, 0xDE, 0xE9, 0xCB,\r\n 0x54, 0x7B, 0x94, 0x32, 0xA6, 0xC2, 0x23, 0x3D, 0xEE, 0x4C, 0x95, 0x0B, 0x42, 0xFA, 0xC3, 0x4E,\r\n 0x08, 0x2E, 0xA1, 0x66, 0x28, 0xD9, 0x24, 0xB2, 0x76, 0x5B, 0xA2, 0x49, 0x6D, 0x8B, 0xD1, 0x25,\r\n 0x72, 0xF8, 0xF6, 0x64, 0x86, 0x68, 0x98, 0x16, 0xD4, 0xA4, 0x5C, 0xCC, 0x5D, 0x65, 0xB6, 0x92,\r\n 0x6C, 0x70, 0x48, 0x50, 0xFD, 0xED, 0xB9, 0xDA, 0x5E, 0x15, 0x46, 0x57, 0xA7, 0x8D, 0x9D, 0x84,\r\n 0x90, 0xD8, 0xAB, 0x00, 0x8C, 0xBC, 0xD3, 0x0A, 0xF7, 0xE4, 0x58, 0x05, 0xB8, 0xB3, 0x45, 0x06,\r\n 0xD0, 0x2C, 0x1E, 0x8F, 0xCA, 0x3F, 0x0F, 0x02, 0xC1, 0xAF, 0xBD, 0x03, 0x01, 0x13, 0x8A, 0x6B,\r\n 0x3A, 0x91, 0x11, 0x41, 0x4F, 0x67, 0xDC, 0xEA, 0x97, 0xF2, 0xCF, 0xCE, 0xF0, 0xB4, 0xE6, 0x73,\r\n 0x96, 0xAC, 0x74, 0x22, 0xE7, 0xAD, 0x35, 0x85, 0xE2, 0xF9, 0x37, 0xE8, 0x1C, 0x75, 0xDF, 0x6E,\r\n 0x47, 0xF1, 0x1A, 0x71, 0x1D, 0x29, 0xC5, 0x89, 0x6F, 0xB7, 0x62, 0x0E, 0xAA, 0x18, 0xBE, 0x1B,\r\n 0xFC, 0x56, 0x3E, 0x4B, 0xC6, 0xD2, 0x79, 0x20, 0x9A, 0xDB, 0xC0, 0xFE, 0x78, 0xCD, 0x5A, 0xF4,\r\n 0x1F, 0xDD, 0xA8, 0x33, 0x88, 0x07, 0xC7, 0x31, 0xB1, 0x12, 0x10, 0x59, 0x27, 0x80, 0xEC, 0x5F,\r\n 0x60, 0x51, 0x7F, 0xA9, 0x19, 0xB5, 0x4A, 0x0D, 0x2D, 0xE5, 0x7A, 0x9F, 0x93, 0xC9, 0x9C, 0xEF,\r\n 0xA0, 0xE0, 0x3B, 0x4D, 0xAE, 0x2A, 0xF5, 0xB0, 0xC8, 0xEB, 0xBB, 0x3C, 0x83, 0x53, 0x99, 0x61,\r\n 0x17, 0x2B, 0x04, 0x7E, 0xBA, 0x77, 0xD6, 0x26, 0xE1, 0x69, 0x14, 0x63, 0x55, 0x21, 0x0C, 0x7D\r\n )\r\n\r\nrcon_i = (0x00, 0x01, 0x02, 0x04, 0x08, 0x10, 0x20, 0x40, 0x80, 0x1B, 0x36)\r\n\r\n'''\r\nbyte = 8 bits\r\nplaintext is in 128-bits blocks\r\nmat is a 4x4 matrix of bytes\r\n'''\r\n\r\n#define the actions performed per round\r\ndef sub_bytes(mat):\r\n for i in range(0, 4):\r\n for j in range(0, 4):\r\n mat[i][j] = Sbox[mat[i][j]] #Sbox will return the replacement for each bit of the 4x4 mat\r\n\r\ndef sub_bytes_inv(mat):\r\n for i in range(0, 4):\r\n for j in range(0, 4):\r\n mat[i][j] = Sbox_inv[mat[i][j]] #Sbox_inv will return the replacement for each bit of the 4x4 mat\r\n\r\ndef shift_rows(mat):\r\n #shifting rows in a 4x4 will leave the first row untouched and the last 3 touched\r\n #done by moving the column values one over (rolling and wrapping around)\r\n mat[0][1], mat[1][1], mat[2][1], mat[3][1] = mat[1][1], mat[2][1], mat[3][1], mat[0][1]\r\n mat[0][2], mat[1][2], mat[2][2], mat[3][2] = mat[2][2], mat[3][2], mat[0][2], mat[1][2]\r\n mat[0][3], mat[1][3], mat[2][3], mat[3][3] = mat[3][3], mat[0][3], mat[1][3], mat[2][3]\r\n\r\ndef shift_rows_inv(mat):\r\n #the inverse is just the reverse direction\r\n mat[0][1], mat[1][1], mat[2][1], mat[3][1] = mat[3][1], mat[0][1], mat[1][1], mat[2][1]\r\n mat[0][2], mat[1][2], mat[2][2], mat[3][2] = mat[2][2], mat[3][2], mat[0][2], mat[1][2]\r\n mat[0][3], mat[1][3], mat[2][3], mat[3][3] = mat[1][3], mat[2][3], mat[3][3], mat[0][3]\r\n\r\ndef add_round_key(mat, key):\r\n #adding round key is a XOR with the provided key\r\n for i in range(0, 4):\r\n for j in range(0, 4):\r\n mat[i][j] ^= key[i][j]\r\n\r\n\r\n#defining multiplication in field 2^8\r\n#understanding that multiplication is just a left-shift of one bit and a conditional XOR with 0x1B (00011011) if\r\n#the leftmost bit is 1 (checked via x &ing 0x80) because 0x80 is 10000000 so it's the leftmost bit as 1\r\n#we also have to keep it 8 bits since that's the size we want to work with, which is why with & with 0xFF, since 0xFF is all 8 bits of 1s\r\nmul_GF28 = lambda x: (((x << 1) ^ 0x1B) & 0xFF) if (x & 0x80) else (x << 1)\r\n\r\ndef mix_column(col):\r\n\r\n a = col[0] ^ col[1] ^ col[2] ^ col[3]\r\n b = col[0]\r\n col[0] ^= a ^ mul_GF28(col[0] ^ col[1]) #multiply each column value and add, like matrix multiplication,\r\n col[1] ^= a ^ mul_GF28(col[1] ^ col[2])\r\n col[2] ^= a ^ mul_GF28(col[2] ^ col[3])\r\n col[3] ^= a ^ mul_GF28(col[3] ^ b)\r\n\r\n\r\ndef mix_columns(mat):\r\n\r\n for i in range(0, 4): #for 4x4 matrix\r\n mix_column(mat[i]) #do for each column\r\n\r\ndef mix_columns_inv(mat):\r\n\r\n for i in range(0, 4): #for 4x4 matrix\r\n a = mul_GF28(mul_GF28(mat[i][0] ^ mat[i][2])) #it is essentially a wrap around since we are in a field\r\n b = mul_GF28(mul_GF28(mat[i][1] ^ mat[i][3]))\r\n mat[i][0] ^= a #applying it twice and XOR'ing it with the column again\r\n mat[i][1] ^= b\r\n mat[i][2] ^= a\r\n mat[i][3] ^= b\r\n\r\n mix_columns(mat)\r\n\r\ndef make_mat(text):\r\n return [list(text[i:i+4]) for i in range(0, len(text), 4)] #returns a list of lists (which makes a matrix 4x4) in col order\r\n\r\ndef make_128bits(mat):\r\n return bytes(sum(mat, [])) #returns a list which is the 4x4 matrix flattened\r\n\r\ndef XOR_bytes(a, b):\r\n return bytes(i^j for i,j in zip(a,b))\r\n\r\ndef make_split(text, size):\r\n return [text[i:i+16] for i in range(0, len(text), size)] #make sizes blocks of 16\r\n\r\n#AES Proper\r\ndef key_expansion(init_key):\r\n\r\n #make sure the init_key is in the right format\r\n key_col = make_mat(init_key)\r\n\r\n #since the key is 128 bits, 192 bits, or 256 bits represented by hex, size 16 24, 32\r\n num_rounds = {16: 10, 24: 12, 32: 14}\r\n N = num_rounds[len(init_key)]\r\n\r\n #other initializations\r\n iterations = len(init_key) // 4 #we split the rounds\r\n i = 1\r\n\r\n while(len(key_col) < (N+1)*4): #while there is still key to go around\r\n\r\n word = list(key_col[-1]) #take the previous sub_key\r\n\r\n if len(key_col) % iterations == 0:\r\n word.append(word.pop(0)) #circular shift\r\n word = [Sbox[b] for b in word] #apply sbox\r\n word[0] ^= rcon_i[i] #XOR with r_con\r\n i += 1\r\n\r\n elif len(init_key) == 32 and len(key_col) % iterations == 4: #todo when 256-bit key is used\r\n word = [Sbox[b] for b in word]\r\n\r\n word = XOR_bytes(word, key_col[-iterations])\r\n key_col.append(word)\r\n\r\n return N, [key_col[4*i:4*(i+1)] for i in range(len(key_col)//4)] #return keys in chunks of 4x4 bytes\r\n\r\ndef encrypt(plaintext, my_keys, R):\r\n '''\r\n plaintext should be 16 bytes long (128 bits)\r\n '''\r\n assert len(plaintext) == 16\r\n\r\n plain = make_mat(plaintext) #turn to 4x4\r\n\r\n add_round_key(plain, my_keys[0]) #initial step is an XOR with the first sub_key\r\n\r\n for i in range(1, R): #do the rounds\r\n sub_bytes(plain)\r\n shift_rows(plain)\r\n mix_columns(plain)\r\n add_round_key(plain, my_keys[i]) #add the round key\r\n\r\n #last round is no mix_cols\r\n sub_bytes(plain)\r\n shift_rows(plain)\r\n add_round_key(plain, my_keys[-1]) #add the last key\r\n\r\n return make_128bits(plain) #return as len 128 bit encrypted\r\n\r\ndef decrypt(ciphertext, my_keys, R):\r\n '''\r\n ciphertext should be 16 bytes long (128 bits)\r\n '''\r\n assert len(ciphertext) == 16\r\n\r\n cipher = make_mat(ciphertext) #turn to 4x4\r\n\r\n #do the first stage of decryption, which is the inverse of the last stage of encryption (without mix col)\r\n add_round_key(cipher, my_keys[-1]) #the last round-key\r\n shift_rows_inv(cipher)\r\n sub_bytes_inv(cipher)\r\n\r\n #do the rounds\r\n for i in range(R-1, 0, -1): #do it in reverse\r\n add_round_key(cipher, my_keys[i]) #add round key\r\n mix_columns_inv(cipher) #inverse col mix\r\n shift_rows_inv(cipher) #inverse shift row\r\n sub_bytes_inv(cipher) #inverse byte sub\r\n\r\n #add the round key that we init'd with in the encrypt stage\r\n add_round_key(cipher, my_keys[0]) #the first round-key\r\n\r\n return make_128bits(cipher) #return as len 128 bit decrypted\r\n\r\ndef CBC_encrypt(plaintext, IV, my_keys, R):\r\n '''\r\n XOR with an IV\r\n '''\r\n chunks = []\r\n prev = IV\r\n\r\n for plain_chunks in make_split(plaintext, 16):\r\n #XOR with IV or previous plaintext\r\n chunk = encrypt(XOR_bytes(plain_chunks, prev), my_keys, R)\r\n chunks.append(chunk)\r\n prev = chunk #set the new prev to be the last added plaintext\r\n\r\n return b''.join(chunks) #return as bits\r\n\r\ndef CBC_decrypt(ciphertext, IV, my_keys, R):\r\n\r\n chunks = []\r\n prev = IV\r\n\r\n for cipher_chunk in make_split(ciphertext, 16):\r\n chunks.append(XOR_bytes(prev, decrypt(cipher_chunk, my_keys, R))) #XOR with the decrypt at each step to undo XOR with each chunk\r\n prev = cipher_chunk #set the new chunk\r\n\r\n return b''.join(chunks) #return as bits\r\n\r\nif __name__ == \"__main__\":\r\n\r\n #for testing purposes\r\n initial_key = [0x54, 0x68, 0x61, 0x74, 0x73, 0x20, 0x6D, 0x79, 0x20, 0x4B, 0x75, 0x6E, 0x67, 0x20, 0x46, 0x75]\r\n plain_text = [0x54, 0x77, 0x6F, 0x20, 0x4F, 0x6E, 0x65, 0x20, 0x4E, 0x69, 0x6E, 0x65, 0x20, 0x54, 0x77, 0x6F]\r\n\r\n #expand keys to encrypt\r\n N, my_keys = key_expansion(initial_key)\r\n\r\n #test encryption\r\n encrypted_text = encrypt(plain_text, my_keys, N)\r\n\r\n #test decryption\r\n decrypted_text = decrypt(encrypted_text, my_keys, N)\r\n\r\n print(encrypted_text)\r\n print(decrypted_text, \"\\n\") #should output the plain_text\r\n\r\n #test CBC\r\n cbc_e_text = CBC_encrypt(plain_text, initial_key, my_keys, N) #using initial key as IV value, just for consistency not for security\r\n cbc_d_text = CBC_decrypt(cbc_e_text, initial_key, my_keys, N)\r\n\r\n print(cbc_e_text)\r\n print(cbc_d_text) #should be the plain_text\r\n","sub_path":"computer_security/tp1/aes_fix.py","file_name":"aes_fix.py","file_ext":"py","file_size_in_byte":11442,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"95073183","text":"import pygame \nimport sys\nimport copy\nfrom Board.board import Board\nfrom Board.tile import Tile\nfrom Pieces.NullPiece import NullPiece\nfrom image import Image\n\nimport bot\n\ndef check_events(screen,board):\n mx = 0\n my = 0\n for event in pygame.event.get():\n if event.type == pygame.QUIT :\n board.end_game = True\n # or event.key == pygame.K_ESCAPE :\n sys.exit()\n if event.type == pygame.MOUSEBUTTONDOWN and board.selectedStartTile.tileCoordinate == []:\n board.mx,board.my = pygame.mouse.get_pos()\n for i in range(8):\n for j in range(8):\n if board.gameTiles[i][j].pos[0]
')\nremovefootercode = re.compile('$')\n\n\ndef parseENML(node, level=0, result='', option=parserOption()): # {{{\n# import html2text\n# return html2text.html2text(node.toxml())\n# print node.toxml()\n# print \"{0}:{1}:{2}:{3}:{4}:{5}\".format(\n# level ,\n# _getNodeType(node) ,\n# _getTagName(node),\n# _getAttribute(node),\n# _getData(node), option)\n if node.nodeType == node.ELEMENT_NODE:\n tag = _getTagName(node)\n if tag == \"en-note\":\n for child in node.childNodes:\n if child.nodeType == node.ELEMENT_NODE:\n # Partition block\n if len(result) == 0 or result[-2:] == '\\n\\n':\n pass\n elif result[-1:] == '\\n':\n result += '\\n'\n else:\n result += '\\n\\n'\n result += parseENML(child, level + 1, \"\", option) + '\\n'\n elif node.nodeType == node.TEXT_NODE:\n result += parseENML(child, level + 1, \"\", option)\n elif tag == \"a\":\n htmlhref = _getAttribute(node)\n option.a = True\n htmltext = \"\".join([parseENML(child, level + 1, \"\", option) for child in node.childNodes])\n option.a = False\n# result += '[{0}]({1})'.format(htmltext, htmlhref) # this code does not work multibyte!\n result += '[' + htmltext + '](' + htmlhref + ')'\n elif tag == \"pre\":\n option.pre = True\n result += \"\".join([parseENML(child, level + 1, result, option) for child in node.childNodes])\n option.pre = False\n elif tag == \"code\":\n option.code = True\n if option.pre == True:\n # precode = removeheadercode.sub('', xml.sax.saxutils.unescape(node.toxml()))\n precode = removeheadercode.sub('', _unescape(node.toxml()))\n precode = removefootercode.sub('', precode)\n for line in precode.splitlines():\n result += __INDENT__ + \"%s\\n\" % line.rstrip()\n result += \"\\n\"\n else:\n # incode = removeheadercode.sub('`', xml.sax.saxutils.unescape(node.toxml()))\n incode = removeheadercode.sub('`', _unescape(node.toxml()))\n incode = removefootercode.sub('`', incode)\n result += incode\n option.code = False\n elif tag == \"p\":\n option.p = True\n result += \"\".join([parseENML(child, level + 1, \"\", option) for child in node.childNodes])\n result = re.compile(r' of name and get its value\npaperLink = soup.find('a', text=\"Epaper\")\nepaperLink = paperLink.get('href')\n\nreq = urllib2.Request(epaperLink, headers=hdr)\npage = urllib2.urlopen(req)\n\n# parse the html using beautiful soup and store in variable `soup`\nsoup = BeautifulSoup(page, \"html.parser\")\n\nstateNameList = []\nsuperCityState = [[]]\ncitiesFromSupercity = {}\npaperLink = soup.find('ul', id=\"navbar\").find_all(recursive=False)\nfor name in paperLink:\n findStateName = name.find('a', href=\"#\")\n if findStateName is not None:\n stateName = findStateName.text.strip(\";\")\n stateNameList.append(stateName)\n\n\n\n#capa = DesiredCapabilities.CHROME\n#capa[\"pageLoadStrategy\"] = \"none\"\ndriver = webdriver.Chrome()\nwait = WebDriverWait(driver, 10)\ndriver.get(\"http://epaper.jagran.com/homepage.aspx\")\ndataEpaper = {}\ndataEpaper['state'] = []\nfor stateVar in stateNameList:\n # select first state\n print(\"+++++++++++++++++++++++++\")\n print(stateVar)\n print(\"@@@@@@@@@@@@@@@@@@@@@@@@@@@\")\n #if (stateVar==\"Delhi\") | (stateVar==\"UP\") | (stateVar==\"Haryana\") | (stateVar==\"Uttarakhand\") | (stateVar==\"Bihar\") :\n #continue\n epaperLinkList = []\n dataEpaper['state'].append({\n 'name':stateVar,\n 'city':epaperLinkList\n })\n stateWebElement = driver.find_element_by_xpath('//ul[@id=\"navbar\"]//a[text()=\"%s\" and @href=\"#\"]' %stateVar)\n hoverOverOnState = ActionChains(driver).move_to_element(stateWebElement).perform()\n superCityWebElement = stateWebElement.find_elements_by_xpath('./..//section/ul/li/a[@href=\"#\" or text()=\"%s\"]' %stateVar)\n\n print(len(superCityWebElement))\n superCityList = []\n for superCityWeb in superCityWebElement:\n print(superCityWeb)\n superCityList.append(superCityWeb.text)\n print(superCityWeb.text)\n print(\"-----------\")\n for superCity in superCityList:\n #if (superCity == \"Dhanbad\") | (superCity == \"Jamshedpur\") : #| (superCity == \"Allahabad\") | (superCity == \"Bareilly\") | (superCity == \"Gorakhpur\") | (superCity == \"Kanpur\") | (superCity == \"Jhansi\") :\n #continue\n stateWebElementFirst = driver.find_element_by_xpath(\n '//ul[@id=\"navbar\"]//a[text()=\"%s\" and @href=\"#\"]' % stateVar)\n superCityWebElementFirst = stateWebElementFirst.find_element_by_xpath(\n './..//section/ul/li/a[text()=\"%s\"]' %superCity)\n hoverOverOnStateFirst = ActionChains(driver).move_to_element(stateWebElementFirst)\n hoverOverOnSuperCityFirst = hoverOverOnStateFirst.move_to_element(superCityWebElementFirst)\n hoverOverOnSuperCityFirst.perform()\n\n superCityName = superCity\n print(\"#################\")\n print(superCity)\n print(\"#################\")\n citiWebElement = superCityWebElementFirst.find_elements_by_xpath('./../ul//li')\n cityList = []\n for cityWeb in citiWebElement:\n cityList.append(cityWeb.text)\n print(cityWeb.text)\n print(\"^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\")\n\n for city in cityList:\n cityObject = {}\n cityCode = \"\"\n staleElement = True\n while (staleElement):\n try:\n wait.until(EC.visibility_of_element_located((By.ID, 'navbar')))\n #driver.execute_script(\"window.stop();\")\n stateWebElementAgain = driver.find_element_by_xpath(\n '//ul[@id=\"navbar\"]//a[text()=\"%s\" and @href=\"#\"]' % stateVar)\n superCityWebElementAgain = stateWebElementAgain.find_element_by_xpath(\n './..//section/ul/li/a[text()=\"%s\"]' % superCityName)\n hoverOverOnStateAgain = ActionChains(driver).move_to_element(stateWebElementAgain)\n hoverOverOnSuperCityAgain = hoverOverOnStateAgain.move_to_element(superCityWebElementAgain)\n hoverOverOnSuperCityAgain.perform()\n #cityName = city.text\n print(\"#################\")\n print(city)\n print(\"#################\")\n cityXPath = superCityWebElementAgain.find_element_by_xpath(\n './..//li/a[text()=\"%s\"]' % city)\n #myxpath = ('//li/a[text()=\"%s\"]' % city)\n #element = wait.until(\n #EC.element_to_be_clickable((By.XPATH, cityXPath)))\n #time.sleep(1)\n cityXPath.click()\n #time.sleep(1)\n wait.until(EC.visibility_of_element_located((By.ID, 'navbar')))\n print(\"&&&&&&&&&&&&&&&&&&&&&&found &&&&&&&&&&&&&&&&&&&&&&&&&&&\")\n driver.execute_script(\"window.stop();\")\n elementPdfLink = wait.until(\n EC.element_to_be_clickable((By.XPATH, '//a[@href=\"#\" and @class=\"pdf\"]')))\n driver.find_element_by_xpath('//a[@href=\"#\" and @class=\"pdf\"]').send_keys(Keys.ESCAPE)#findElement((By.XPATH, '//a[@href=\"#\" and @class=\"pdf\"]')).sendKeys(\"Keys.ESCAPE\");\n elementPdfLink.click()\n #time.sleep(1)\n windowTab = driver.window_handles\n for tab in windowTab:\n if tab != windowTab[0]:\n driver.switch_to.window(tab)\n codeUrl = driver.current_url\n print(codeUrl)\n matchObj = re.match(r'http://epaper.jagran.com/epaperimages/\\d+/.+/\\d\\d(.+)-pg.+', codeUrl, re.M | re.I)\n cityCode = matchObj.group(1)\n driver.close()\n cityObject[city] = cityCode\n epaperLinkList.append(cityObject)\n driver.switch_to.window(windowTab[0])\n print(\"coming till here\")\n json_data = json.dumps(dataEpaper)\n print(json_data)\n staleElement = False\n except Exception as e:\n print(\"it is stale\")\n print(e)\n cityObject[city] = \"NOT Found\"\n for window in driver.window_handles:\n driver.switch_to.window(window)\n try:\n driver.switch_to.alert.accept()\n except NoAlertPresentException:\n pass\n windowTab = driver.window_handles\n for tab in windowTab:\n if tab != windowTab[0]:\n driver.switch_to.window(tab)\n codeUrl = driver.current_url\n print(codeUrl)\n driver.close()\n driver.switch_to.window(windowTab[0])\n traceback.print_exc()\n staleElement = False\n\n\n\nassert \"No results found.\" not in driver.page_source\ndriver.close()\n\njson_data = json.dumps(dataEpaper)\nprint(json_data)\n\n\n","sub_path":"scrapy.py","file_name":"scrapy.py","file_ext":"py","file_size_in_byte":8314,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"373122207","text":"#!/usr/bin/env pythonw\n\n#--------------------------------------------------------------\n# converting magnetometer files to MagIC format\n#--------------------------------------------------------------\nimport wx\nimport wx.grid\nimport os\nimport subprocess\nimport sys\nfrom pmagpy import pmag\nfrom pmagpy import ipmag\nfrom pmagpy import convert_2_magic as convert\nfrom dialogs import pmag_widgets as pw\nfrom dialogs import drop_down_menus3\nfrom dialogs import magic_grid2 as magic_grid\n#sys.path.append(\"../programs\") #later fix imports further down in code to \"from programs import ....\" also imports should be moved to top of file unless import is so large it slows down the program\nfrom pmagpy import convert_2_magic as convert\nfrom programs.conversion_scripts import tdt_magic\nfrom programs.conversion_scripts import jr6_txt_magic\nfrom programs.conversion_scripts import jr6_jr6_magic\nfrom programs.conversion_scripts import iodp_jr6_magic\nfrom pmagpy.mapping import map_magic\n\n\nclass import_magnetometer_data(wx.Dialog):\n def __init__(self, parent, id, title, WD):\n wx.Dialog.__init__(self, parent, id, title, name='import_magnetometer_data')\n self.parent = parent\n self.WD = WD\n self.InitUI()\n self.SetTitle(title)\n\n\n def InitUI(self):\n self.panel = wx.Panel(self)\n vbox = wx.BoxSizer(wx.VERTICAL)\n\n formats = ['generic format','SIO format','CIT format','2g-binary format','2g-ascii format',\n 'HUJI format','LDEO format','IODP format','PMD (ascii) format',\n 'TDT format', 'JR6 format', 'Utrecht format', 'BGC format']\n sbs = wx.StaticBoxSizer(wx.StaticBox(self.panel, wx.ID_ANY, 'step 1: choose file format'), wx.VERTICAL)\n sbs.AddSpacer(5)\n\n radio_buttons = []\n for fmt in formats:\n radio_button = wx.RadioButton(self.panel, -1, label=fmt, name=fmt)\n radio_buttons.append(radio_button)\n sbs.Add(radio_button, flag=wx.BOTTOM, border=5)\n if len(radio_buttons) == 1:\n sbs.Add(wx.StaticLine(self.panel), 0, wx.ALL|wx.EXPAND, 5)\n #sbs.AddSpacer(5)\n self.Bind(wx.EVT_RADIOBUTTON, self.OnRadioButtonSelect, radio_button)\n\n radio_buttons[0].SetValue(True)\n self.checked_rb = radio_buttons[0]\n\n #---------------------\n # OK/Cancel buttons\n #---------------------\n\n hboxok = wx.BoxSizer(wx.HORIZONTAL)\n self.okButton = wx.Button(self.panel, id=-1, label='Import file')\n self.okButton.SetDefault()\n self.Bind(wx.EVT_BUTTON, self.on_okButton, self.okButton)\n self.cancelButton = wx.Button(self.panel, wx.ID_CANCEL, '&Cancel')\n self.Bind(wx.EVT_BUTTON, self.on_cancelButton, self.cancelButton)\n self.Bind(wx.EVT_CLOSE, self.on_cancelButton)\n # re-do the 'quit' binding so that it only closes the current window\n self.parent.Bind(wx.EVT_MENU, lambda event: self.parent.menubar.on_quit(event, self), self.parent.menubar.file_quit)\n\n self.nextButton = wx.Button(self.panel, id=-1, label='Go to next step')\n self.Bind(wx.EVT_BUTTON, self.on_nextButton, self.nextButton)\n hboxok.Add(self.okButton)\n hboxok.AddSpacer(20)\n hboxok.Add(self.cancelButton )\n hboxok.AddSpacer(20)\n hboxok.Add(self.nextButton )\n\n #-----------------------\n # design the frame\n #-----------------------\n vbox.AddSpacer(10)\n vbox.Add(sbs)\n vbox.AddSpacer(10)\n vbox.Add(hboxok)\n vbox.AddSpacer(10)\n\n hbox1=wx.BoxSizer(wx.HORIZONTAL)\n hbox1.AddSpacer(10)\n hbox1.Add(vbox)\n hbox1.AddSpacer(10)\n\n self.panel.SetSizer(hbox1)\n hbox1.Fit(self)\n\n #-----------------------\n # button methods\n #-----------------------\n\n def on_cancelButton(self,event):\n self.Destroy()\n self.Parent.Show()\n self.Parent.Raise()\n\n\n def on_okButton(self,event):\n os.chdir(self.WD)\n file_type = self.checked_rb.Label.split()[0] # extracts name of the checked radio button\n if file_type == 'generic':\n dia = convert_generic_files_to_MagIC(self, self.WD, \"PmagPy generic file conversion\")\n elif file_type == 'SIO':\n dia = convert_SIO_files_to_MagIC(self, self.WD, \"PmagPy SIO file conversion\")\n elif file_type == 'CIT':\n dia = convert_CIT_files_to_MagIC(self, self.WD, \"PmagPy CIT file conversion\")\n elif file_type == '2g-binary':\n dia = convert_2g_binary_files_to_MagIC(self, self.WD, \"PmagPy 2g-binary file conversion\")\n elif file_type == '2g-ascii':\n dia = convert_2g_ascii_files_to_MagIC(self, self.WD, \"PmagPy 2g-ascii file conversion\")\n elif file_type == 'HUJI':\n dia = convert_HUJI_files_to_MagIC(self, self.WD, \"PmagPy HUJI file conversion\")\n elif file_type == 'LDEO':\n dia = convert_LDEO_files_to_MagIC(self, self.WD, \"PmagPy LDEO file conversion\")\n elif file_type == 'IODP':\n dia = convert_IODP_files_to_MagIC(self, self.WD, \"PmagPy IODP csv conversion\")\n elif file_type == 'PMD':\n dia = convert_PMD_files_to_MagIC(self, self.WD, \"PmagPy PMD conversion\")\n elif file_type == 'BGC':\n dia = convert_BGC_files_to_magic(self, self.WD, \"PmagPy BGC conversion\")\n elif file_type == 'TDT':\n tdt_magic.convert(False, self.WD)\n return True\n elif file_type == 'JR6':\n dia = convert_JR6_files_to_MagIC(self, self.WD)\n elif file_type == 'Utrecht':\n dia = convert_Utrecht_files_to_MagIC(self, self.WD, \"PmagPy Utrecht conversion\")\n dia.Center()\n dia.Show()\n\n\n def OnRadioButtonSelect(self, event):\n self.checked_rb = event.GetEventObject()\n\n def on_nextButton(self,event):\n self.Destroy()\n combine_dia = combine_magic_dialog(self.WD, self.parent)\n combine_dia.Show()\n combine_dia.Center()\n\n#--------------------------------------------------------------\n# dialog for combine_magic.py\n#--------------------------------------------------------------\n\n\nclass combine_magic_dialog(wx.Frame):\n \"\"\"\"\"\"\n title = \"Combine magic files\"\n\n def __init__(self, WD, parent):\n wx.Frame.__init__(self, parent, wx.ID_ANY, self.title)\n self.panel = wx.ScrolledWindow(self) #wx.Panel(self)\n self.parent = parent\n self.panel.SetScrollbars(20, 20, 50, 50)\n self.WD=WD\n self.InitUI()\n\n def InitUI(self):\n pnl = self.panel\n\n #---sizer information ----\n\n TEXT=\"Step 2: \\nCombine different MagIC formatted files to one file named 'measurements.txt'\"\n bSizer_info = wx.BoxSizer(wx.HORIZONTAL)\n bSizer_info.Add(wx.StaticText(pnl,label=TEXT),wx.ALIGN_LEFT)\n\n\n #---sizer 0 ----\n self.bSizer0 = pw.combine_files(self, \".magic\", DM=3)\n #------------------\n\n self.okButton = wx.Button(self.panel, wx.ID_OK, \"&OK\")\n self.Bind(wx.EVT_BUTTON, self.on_okButton, self.okButton)\n\n self.cancelButton = wx.Button(self.panel, wx.ID_CANCEL, '&Cancel')\n self.Bind(wx.EVT_BUTTON, self.on_cancelButton, self.cancelButton)\n self.Bind(wx.EVT_CLOSE, self.on_cancelButton)\n\n self.nextButton = wx.Button(self.panel, id=-1, label='Go to last step')\n self.Bind(wx.EVT_BUTTON, self.on_nextButton, self.nextButton)\n # re-do the 'quit' binding so that it only closes the current window\n self.parent.Bind(wx.EVT_MENU, lambda event: self.parent.menubar.on_quit(event, self), self.parent.menubar.file_quit)\n #\n hboxok = wx.BoxSizer(wx.HORIZONTAL)\n hboxok.Add(self.okButton)\n hboxok.Add(self.cancelButton, flag=wx.LEFT, border=5)\n hboxok.Add(self.nextButton, flag=wx.LEFT, border=5)\n\n #------\n vbox=wx.BoxSizer(wx.VERTICAL)\n vbox.AddSpacer(10)\n vbox.Add(bSizer_info, flag=wx.ALIGN_LEFT)\n vbox.AddSpacer(10)\n vbox.Add(self.bSizer0, flag=wx.ALIGN_LEFT)\n vbox.AddSpacer(10)\n vbox.AddSpacer(10)\n vbox.Add(wx.StaticLine(self.panel), 0, wx.ALL|wx.EXPAND, 5)\n vbox.Add(hboxok, flag=wx.ALIGN_CENTER)\n vbox.AddSpacer(5)\n\n hbox_all= wx.BoxSizer(wx.HORIZONTAL)\n hbox_all.AddSpacer(20)\n hbox_all.Add(vbox)\n hbox_all.AddSpacer(20)\n\n self.panel.SetSizer(hbox_all)\n hbox_all.Fit(self)\n self.Centre()\n self.Show()\n\n\n def on_cancelButton(self,event):\n self.Parent.Show()\n self.Parent.Raise()\n self.Destroy()\n # make sure contribution is created\n self.Parent.get_wd_data()\n\n def on_nextButton(self, event):\n combine_dia = combine_everything_dialog(self.WD, self.Parent)\n combine_dia.Show()\n combine_dia.Center()\n self.Destroy()\n\n def on_okButton(self,event):\n os.chdir(self.WD) # make sure OS is working in self.WD (Windows issue)\n files_text=self.bSizer0.file_paths.GetValue()\n files=files_text.strip('\\n').replace(\" \",\"\")\n if files:\n files = files.split('\\n')\n files = [os.path.join(self.WD, f) for f in files]\n COMMAND=\"combine_magic.py -F measurements.txt -f %s\"%(\" \".join(files) )\n\n if ipmag.combine_magic(files, 'measurements.txt', data_model=3.0):\n MSG=\"%i file are merged to one MagIC format file:\\n measurements.txt.\\n\\nSee Terminal/message window for errors\"%(len(files))\n dlg1 = wx.MessageDialog(None,caption=\"Message:\", message=MSG ,style=wx.OK|wx.ICON_INFORMATION)\n dlg1.ShowModal()\n dlg1.Destroy()\n else:\n pw.simple_warning()\n return\n\n self.on_nextButton(event)\n self.Destroy()\n\n\nclass combine_everything_dialog(wx.Frame):\n \"\"\"\"\"\"\n title = \"Combine MagIC files\"\n\n def __init__(self, WD, parent):\n wx.Frame.__init__(self, parent, wx.ID_ANY, self.title)\n self.panel = wx.ScrolledWindow(self) #wx.Panel(self)\n self.panel.SetScrollbars(20, 20, 50, 50)\n self.parent = parent\n self.WD=WD\n self.InitUI()\n\n def InitUI(self):\n\n pnl = self.panel\n\n #---sizer information ----\n\n TEXT=\"Step 3: \\nCombine different MagIC formatted files to one file name (if necessary). All files should be from the working directory.\"\n bSizer_info = wx.BoxSizer(wx.HORIZONTAL)\n bSizer_info.Add(wx.StaticText(pnl,label=TEXT),wx.ALIGN_LEFT)\n\n possible_file_dias = ['specimens.txt', 'samples.txt', 'sites.txt', 'locations.txt']\n self.file_dias = []\n all_files = os.listdir(self.WD)\n for dia in possible_file_dias:\n for f in all_files:\n if dia in f:\n bSizer = pw.combine_files(self, dia, DM=3)\n self.file_dias.append(bSizer)\n break\n if not self.file_dias:\n file_string = ', '.join(possible_file_dias)\n MSG = \"You have no more files that can be combined.\\nFile types that can be combined are:\\n{}\\nNote that your file name must end with the file type, i.e.:\\nsomething_something_specimens.txt\".format(file_string)\n dlg = wx.MessageDialog(None,caption=\"Message:\", message=MSG ,style=wx.OK|wx.ICON_INFORMATION)\n dlg.ShowModal()\n dlg.Destroy()\n\n #------------------\n # re-do the 'quit' binding so that it only closes the current window\n self.parent.Bind(wx.EVT_MENU, lambda event: self.parent.menubar.on_quit(event, self), self.parent.menubar.file_quit)\n\n self.okButton = wx.Button(self.panel, wx.ID_OK, \"&OK\")\n self.Bind(wx.EVT_BUTTON, self.on_okButton, self.okButton)\n\n self.cancelButton = wx.Button(self.panel, wx.ID_CANCEL, '&Cancel')\n self.Bind(wx.EVT_BUTTON, self.on_cancelButton, self.cancelButton)\n self.Bind(wx.EVT_CLOSE, self.on_cancelButton)\n\n hboxok = wx.BoxSizer(wx.HORIZONTAL)\n hboxok.Add(self.okButton)\n hboxok.Add(self.cancelButton, flag=wx.LEFT, border=5 )\n\n #file_dias = [self.bSizer0, self.bSizer1, self.bSizer2]\n if len(self.file_dias) == 4:\n num_cols, num_rows = 2, 2\n else:\n num_cols = min(len(self.file_dias), 3)\n num_rows = 2 if len(self.file_dias) > 3 else 1\n hboxfiles = wx.GridSizer(num_rows, num_cols, 1, 1)\n hboxfiles.AddMany(self.file_dias)\n\n #hboxfiles = wx.BoxSizer(wx.HORIZONTAL)\n #hboxfiles.AddMany([self.bSizer0, self.bSizer1, self.bSizer2])\n\n #------\n vbox=wx.BoxSizer(wx.VERTICAL)\n vbox.AddSpacer(10)\n vbox.Add(bSizer_info, flag=wx.ALIGN_LEFT|wx.BOTTOM, border=5)\n vbox.AddSpacer(10)\n vbox.Add(hboxfiles, flag=wx.ALIGN_LEFT)\n vbox.AddSpacer(10)\n vbox.AddSpacer(10)\n vbox.Add(wx.StaticLine(self.panel), 0, wx.ALL|wx.EXPAND, 5)\n vbox.Add(hboxok, flag=wx.ALIGN_CENTER)\n vbox.AddSpacer(5)\n\n hbox_all= wx.BoxSizer(wx.HORIZONTAL)\n hbox_all.AddSpacer(20)\n hbox_all.Add(vbox)\n hbox_all.AddSpacer(20)\n\n self.panel.SetSizer(hbox_all)\n hbox_all.Fit(self)\n self.Centre()\n self.Show()\n\n def on_cancelButton(self,event):\n self.Parent.Show()\n self.Parent.Raise()\n self.Destroy()\n # make sure contribution is created\n self.Parent.get_wd_data()\n\n def on_okButton(self,event):\n os.chdir(self.WD)\n success = True\n new_files = []\n # go through each pw.combine_files sizer, extract the files, try to combine them into one:\n for bSizer in self.file_dias:\n full_list = bSizer.file_paths.GetValue()\n file_name = bSizer.text\n files = full_list.strip('\\n').replace(\" \", \"\")\n if files:\n files = files.split('\\n')\n else:\n print('No files of {} type found, skipping'.format(file_name))\n continue\n res = ipmag.combine_magic(files, file_name, data_model=3.0)\n if res:\n new_files.append(file_name) # add to the list of successfully combined files\n else:\n success = False\n if success:\n new = '\\n' + '\\n'.join(new_files)\n MSG = \"Created new file(s): {} \\nSee Terminal/message window for details and errors\".format(new)\n dlg1 = wx.MessageDialog(None,caption=\"Message:\", message=MSG ,style=wx.OK|wx.ICON_INFORMATION)\n dlg1.ShowModal()\n dlg1.Destroy()\n self.Parent.Show()\n self.Parent.Raise()\n self.Destroy()\n # make sure contribution is created\n self.Parent.get_wd_data()\n\n else:\n pw.simple_warning()\n # make sure contribution is created\n self.Parent.get_wd_data()\n\n\n#--------------------------------------------------------------\n# MagIC generic files conversion\n#--------------------------------------------------------------\n\n\nclass convert_files_to_MagIC(wx.Frame):\n \"\"\"\n Abstract class for file conversion frames\n \"\"\"\n\n def __init__(self, parent, WD, title):\n self.parent = parent\n self.WD = WD\n self.title = title\n wx.Frame.__init__(self, parent, wx.ID_ANY, self.title)\n self.panel = wx.ScrolledWindow(self)\n self.panel.SetScrollbars(20, 20, 50, 50)\n self.InitUI()\n\n def InitUI(self):\n pass\n\n def on_cancelButton(self, event):\n self.Destroy()\n self.parent.Show()\n self.parent.Raise()\n\n def on_add_file_button(self, event):\n text = \"choose file to convert to MagIC\"\n pw.on_add_file_button(self.bSizer0, text)\n\n def on_add_dir_button(self, event):\n text = \"choose directory of files to convert to MagIC\"\n pw.on_add_dir_button(self.bSizer0, text)\n\n\nclass convert_generic_files_to_MagIC(convert_files_to_MagIC):\n \"\"\"\"\"\"\n title = \"PmagPy generic file conversion\"\n\n def InitUI(self):\n\n pnl = self.panel\n\n #---sizer infor ----\n\n TEXT = \"convert generic file to MagIC format\"\n bSizer_info = wx.BoxSizer(wx.HORIZONTAL)\n bSizer_info.Add(wx.StaticText(pnl,label=TEXT),wx.ALIGN_LEFT)\n\n\n #---sizer 0 ----\n self.bSizer0 = pw.choose_file(pnl, 'add', method = self.on_add_file_button)\n\n #---sizer 1 ----\n self.bSizer1 = pw.labeled_text_field(pnl)\n\n #---sizer 2 ----\n # unique because only accepts 1 experiment type\n TEXT=\"Experiment:\"\n self.bSizer2 = wx.StaticBoxSizer( wx.StaticBox( self.panel, wx.ID_ANY, \"\" ), wx.HORIZONTAL)\n self.gridBSizer = wx.GridBagSizer(5, 10)\n self.label1 = wx.StaticText(pnl, label=TEXT)\n self.experiments_names=['Demag (AF and/or Thermal)','Paleointensity-IZZI/ZI/ZI','ATRM 6 positions','AARM 6 positions','cooling rate','TRM']\n self.protocol_info = wx.ComboBox(self.panel, -1, self.experiments_names[0], size=(300,25),choices=self.experiments_names, style=wx.CB_READONLY)\n self.gridBSizer.Add(self.label1, (0, 0))\n self.gridBSizer.Add(self.protocol_info, (1, 0))\n self.bSizer2.Add(self.gridBSizer, wx.ALIGN_LEFT)\n #\n self.Bind(wx.EVT_COMBOBOX, self.on_select_protocol, self.protocol_info)\n self.bSizer2a = wx.StaticBoxSizer( wx.StaticBox( self.panel, wx.ID_ANY, \"\" ), wx.HORIZONTAL )\n text = 'Cooling Rate, format is xxx,yyy,zzz with no spaces '\n self.cooling_rate = wx.TextCtrl(pnl)\n self.bSizer2a.AddMany([wx.StaticText(pnl, label=text), self.cooling_rate])\n\n #---sizer 3 ----\n self.bSizer3 = pw.lab_field(pnl)\n\n #---sizer 4 ----\n # unique because only allows 4 choices (most others have ncn choices)\n self.bSizer4 = wx.StaticBoxSizer( wx.StaticBox( self.panel, wx.ID_ANY, \"\" ), wx.VERTICAL )\n self.sample_naming_conventions=['sample=specimen','no. of initial characters','no. of terminal characters','character delimited']\n self.sample_naming_convention = wx.ComboBox(self.panel, -1, self.sample_naming_conventions[0], size=(250,25), choices=self.sample_naming_conventions, style=wx.CB_READONLY)\n self.sample_naming_convention_char = wx.TextCtrl(self.panel, id=-1, size=(40,25))\n gridbSizer4 = wx.GridSizer(2, 2, 0, 10)\n gridbSizer4.AddMany( [(wx.StaticText(self.panel,label=\"specimen-sample naming convention\",style=wx.TE_CENTER),wx.ALIGN_LEFT),\n (wx.StaticText(self.panel,label=\"delimiter/number (if necessary)\",style=wx.TE_CENTER),wx.ALIGN_LEFT),\n (self.sample_naming_convention,wx.ALIGN_LEFT),\n (self.sample_naming_convention_char,wx.ALIGN_LEFT)])\n #bSizer4.Add(self.sample_specimen_text,wx.ALIGN_LEFT)\n self.bSizer4.AddSpacer(10)\n self.bSizer4.Add(gridbSizer4,wx.ALIGN_LEFT)\n\n #---sizer 5 ----\n self.bSizer5 = wx.StaticBoxSizer( wx.StaticBox( self.panel, wx.ID_ANY, \"\" ), wx.VERTICAL )\n self.site_naming_conventions=['site=sample','no. of initial characters','no. of terminal characters','character delimited']\n self.site_naming_convention_char = wx.TextCtrl(self.panel, id=-1, size=(40,25))\n self.site_naming_convention = wx.ComboBox(self.panel, -1, self.site_naming_conventions[0], size=(250,25), choices=self.site_naming_conventions, style=wx.CB_READONLY)\n gridbSizer5 = wx.GridSizer(2, 2, 0, 10)\n gridbSizer5.AddMany( [(wx.StaticText(self.panel,label=\"site-sample naming convention\",style=wx.TE_CENTER),wx.ALIGN_LEFT),\n (wx.StaticText(self.panel,label=\"delimiter/number (if necessary)\",style=wx.TE_CENTER),wx.ALIGN_LEFT),\n (self.site_naming_convention,wx.ALIGN_LEFT),\n (self.site_naming_convention_char,wx.ALIGN_LEFT)])\n self.bSizer5.AddSpacer(10)\n self.bSizer5.Add(gridbSizer5,wx.ALIGN_LEFT)\n\n #---sizer 6 ----\n TEXT=\"Location name:\"\n self.bSizer6 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 7 ----\n #self.bSizer7 = pw.site_lat_lon(pnl)\n\n #---sizer 8 ----\n self.bSizer8 = pw.replicate_measurements(pnl)\n\n #---buttons ---\n hboxok = pw.btn_panel(self, pnl)\n\n #------\n vbox=wx.BoxSizer(wx.VERTICAL)\n vbox.Add(bSizer_info, flag=wx.ALIGN_LEFT|wx.TOP, border=5)\n vbox.Add(self.bSizer0, flag=wx.ALIGN_LEFT|wx.TOP, border=5)\n vbox.Add(self.bSizer1, flag=wx.ALIGN_LEFT|wx.TOP, border=5)\n vbox.Add(self.bSizer2, flag=wx.ALIGN_LEFT|wx.TOP, border=5)\n vbox.Add(self.bSizer2a, flag=wx.ALIGN_LEFT|wx.TOP, border=5)\n\n vbox.Add(self.bSizer3, flag=wx.ALIGN_LEFT|wx.TOP, border=5)\n vbox.Add(self.bSizer4, flag=wx.ALIGN_LEFT|wx.TOP, border=5)\n vbox.Add(self.bSizer5, flag=wx.ALIGN_LEFT|wx.TOP, border=5)\n vbox.Add(self.bSizer6, flag=wx.ALIGN_LEFT|wx.TOP, border=5)\n #vbox.Add(self.bSizer7, flag=wx.ALIGN_LEFT|wx.TOP, border=5)\n vbox.Add(self.bSizer8, flag=wx.ALIGN_LEFT|wx.TOP|wx.BOTTOM, border=5)\n vbox.Add(wx.StaticLine(self.panel), 0, wx.ALL|wx.EXPAND, 5)\n vbox.Add(hboxok, flag=wx.ALIGN_CENTER)\n vbox.AddSpacer(5)\n\n\n self.hbox_all= wx.BoxSizer(wx.HORIZONTAL)\n self.hbox_all.AddSpacer(20)\n self.hbox_all.Add(vbox)\n self.hbox_all.AddSpacer(20)\n\n self.panel.SetSizer(self.hbox_all)\n self.bSizer2a.ShowItems(False)\n self.hbox_all.Fit(self)\n self.Centre()\n self.Show()\n\n\n def on_select_protocol(self, event):\n if self.protocol_info.GetValue() == \"cooling rate\":\n self.bSizer2a.ShowItems(True)\n else:\n self.bSizer2a.ShowItems(False)\n self.hbox_all.Fit(self)\n\n\n def on_add_file_button(self,event):\n text = \"choose file to convert to MagIC\"\n pw.on_add_file_button(self.bSizer0, text)\n\n\n def on_okButton(self,event):\n os.chdir(self.WD)\n # generic_magic.py -WD WD - f FILE -fsa er_samples.txt -F OUTFILE.magic -exp [Demag/PI/ATRM 6/AARM 6/CR -samp X Y -site X Y -loc LOCNAME -dc B PHI THETA [-A] -WD path\n options = {}\n\n ErrorMessage = \"\"\n #-----------\n if not self.bSizer0.file_path.GetValue():\n pw.simple_warning('You must provide a generic format file')\n return False\n FILE = str(self.bSizer0.file_path.GetValue())\n options['magfile'] = FILE\n\n #-----------\n # WD=\"/\".join(FILE.split(\"/\")[:-1])\n WD=self.WD\n options['dir_path'] = WD\n input_dir = os.path.split(FILE)[0]\n magicoutfile=os.path.split(FILE)[1]+\".magic\"\n options['meas_file'] = magicoutfile\n print(\"magicoutfile\", magicoutfile)\n OUTFILE=os.path.join(self.WD,magicoutfile)\n #-----------\n #OUTFILE=self.WD+\"/\"+FILE.split('/')[-1]+\".magic\"\n #-----------\n EXP = \"\"\n exp = str(self.protocol_info.GetValue())\n if exp == 'Demag (AF and/or Thermal)':\n EXP = 'Demag'\n elif exp == 'Paleointensity-IZZI/ZI/ZI':\n EXP = 'PI'\n elif exp == 'ATRM 6 positions':\n EXP ='ATRM 6'\n elif exp == 'AARM 6 positions':\n EXP = 'AARM 6'\n elif exp == 'cooling rate':\n cooling = self.cooling_rate.GetValue()\n if not cooling:\n text = \"You must provide cooling rate for this experiment type!\\nThe format is: xxx, yyy,zzz...\\nThis should be cooling rates in [K/minutes], seperated by comma, ordered at the same order as XXX.10,XXX.20 ...XX.70\"\n pw.simple_warning(text)\n return False\n EXP = 'CR {}'.format(cooling)\n if 'CR' in EXP:\n options['experiment'], options['cooling_times_list'] = EXP.split()\n elif 'AARM' in EXP:\n options['experiment'] = EXP\n #options['experiment'], options['aarm_n_pos'] = EXP.split()\n elif 'ATRM' in EXP:\n options['experiment'] = EXP\n #options['experiment'], options['atrm_n_pos'] = EXP.split()\n else:\n options['experiment'] = EXP\n #-----------\n SAMP=\"1 0\" #default\n\n samp_naming_convention = str(self.sample_naming_convention.GetValue())\n try:\n samp_naming_convention_char=int(self.sample_naming_convention_char.GetValue())\n except:\n samp_naming_convention_char = \"0\"\n\n if samp_naming_convention == 'sample=specimen':\n SAMP = \"1 0\"\n elif samp_naming_convention == 'no. of initial characters':\n SAMP = \"0 %i\" % int(samp_naming_convention_char)\n elif samp_naming_convention == 'no. of terminal characters':\n SAMP = \"1 %s\" % samp_naming_convention_char\n elif samp_naming_convention == 'character delimited':\n SAMP = \"2 %s\" % samp_naming_convention_char\n\n options['sample_nc'] = SAMP.split()\n #-----------\n\n SITE = \"1 0\" #default\n\n site_naming_convention = str(self.site_naming_convention.GetValue())\n try:\n site_naming_convention_char = int(self.site_naming_convention_char.GetValue())\n except:\n site_naming_convention_char = \"0\"\n\n if site_naming_convention == 'sample=specimen':\n SITE = \"1 0\"\n elif site_naming_convention == 'no. of initial characters':\n SITE = \"0 %i\" % int(site_naming_convention_char)\n elif site_naming_convention == 'no. of terminal characters':\n SITE = \"1 %s\" % site_naming_convention_char\n elif site_naming_convention == 'character delimited':\n SITE = \"2 %s\" % site_naming_convention_char\n\n options['site_nc'] = SITE.split()\n\n #-----------\n\n LOC = str(self.bSizer6.return_value())\n if LOC!=\"\": options['location'] = LOC\n\n if str(self.bSizer6.return_value()) != \"\":\n LOC=\"-loc \\\"%s\\\"\"%LOC\n else:\n LOC=\"\"\n\n #-----------\n\n LABFIELD=\" \"\n try:\n B_uT, DEC, INC = self.bSizer3.return_value().split()\n except ValueError:\n B_uT, DEC, INC = '0', '0', '0'\n\n #print \"B_uT, DEC, INC\", B_uT, DEC, INC\n options['labfield'], options['labfield_phi'], options['labfield_theta'] = B_uT, DEC, INC\n\n if EXP != \"Demag\":\n LABFIELD=\"-dc \" +B_uT+ \" \" + DEC + \" \" + INC\n\n #-----------\n\n #try: lat,lon = self.bSizer7.return_value().split()\n #except ValueError: lat,lon = '',''\n #options['lat'] = lat\n #options['lon'] = lon\n #lat = '-lat ' + lat\n #lon = '-lat ' + lon\n\n #-----------\n\n DONT_AVERAGE = \" \"\n if not self.bSizer8.return_value():\n DONT_AVERAGE = \"-A\"\n options['noave'] = 1\n else:\n options['noave'] = 0\n\n #-----------\n # some special\n\n SPEC_OUTFILE = magicoutfile[:magicoutfile.find('.')] + \"_specimens.txt\"\n SAMP_OUTFILE = magicoutfile[:magicoutfile.find('.')] + \"_samples.txt\"\n SITE_OUTFILE = magicoutfile[:magicoutfile.find('.')] + \"_sites.txt\"\n LOC_OUTFILE = magicoutfile[:magicoutfile.find('.')] + \"_locations.txt\"\n options['spec_file'] = SPEC_OUTFILE\n options['samp_file'] = SAMP_OUTFILE\n options['site_file'] = SITE_OUTFILE\n options['loc_file'] = LOC_OUTFILE\n\n COMMAND=\"generic_magic.py -WD %s -f %s -fsa er_samples.txt -F %s -exp %s -samp %s -site %s %s %s %s -Fsp %s -Fsa %s -Fsi %s -Flo %s \"\\\n %(WD,FILE,OUTFILE,EXP,SAMP,SITE,LOC,LABFIELD,DONT_AVERAGE, SPEC_OUTFILE, SAMP_OUTFILE, SITE_OUTFILE, LOC_OUTFILE)#, lat, lon)\n\n print(\"-I- Running Python command:\\n %s\"%COMMAND)\n program_run, error_message = convert.generic(**options)\n\n if program_run:\n pw.close_window(self, COMMAND, OUTFILE)\n else:\n pw.simple_warning(error_message)\n return False\n\n self.Destroy()\n self.parent.Raise()\n\n #def on_cancelButton(self,event):\n # self.Destroy()\n # self.parent.Raise()\n\n def on_helpButton(self, event):\n pw.on_helpButton(text=convert.generic.__doc__)\n\n def get_sample_name(self, specimen, sample_naming_convenstion):\n if sample_naming_convenstion[0] == \"sample=specimen\":\n sample = specimen\n elif sample_naming_convenstion[0] == \"no. of terminal characters\":\n n = int(sample_naming_convenstion[1]) * -1\n sample = specimen[:n]\n elif sample_naming_convenstion[0] == \"character delimited\":\n d = sample_naming_convenstion[1]\n sample_splitted = specimen.split(d)\n if len(sample_splitted) == 1:\n sample = sample_splitted[0]\n else:\n sample = d.join(sample_splitted[:-1])\n return sample\n\n def get_site_name(self, sample, site_naming_convention):\n if site_naming_convention[0] == \"site=sample\":\n site = sample\n elif site_naming_convention[0] == \"no. of terminal characters\":\n n = int(site_naming_convention[1])*-1\n site = sample[:n]\n elif site_naming_convention[0] == \"character delimited\":\n d = site_naming_convention[1]\n site_splitted = sample.split(d)\n if len(site_splitted) == 1:\n site = site_splitted[0]\n else:\n site = d.join(site_splitted[:-1])\n\n return site\n\nclass convert_SIO_files_to_MagIC(convert_files_to_MagIC):\n \"\"\"\n convert SIO formatted measurement file to MagIC formated files\n \"\"\"\n\n def InitUI(self):\n pnl = self.panel\n TEXT = \"SIO Format file\"\n bSizer_info = wx.BoxSizer(wx.HORIZONTAL)\n bSizer_info.Add(wx.StaticText(pnl, label=TEXT), wx.ALIGN_LEFT)\n# bSizer_info.Add(wx.StaticText(self), wx.ALIGN_LEFT)\n\n self.bSizer0 = pw.choose_file(pnl, method = self.on_add_file_button)\n\n #---sizer 1 ----\n self.bSizer1 = pw.labeled_text_field(pnl)\n\n #---sizer 2 ----\n self.bSizer2 = pw.experiment_type(pnl)\n\n #---sizer 3 ----\n self.bSizer3 = pw.lab_field(pnl)\n\n #---sizer 4 ----\n self.bSizer4 = pw.specimen_n(pnl)\n\n #---sizer 4a ----\n self.bSizer4a = pw.select_ncn(pnl)\n\n #---sizer 5 ----\n TEXT=\"Location name:\"\n self.bSizer5 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 11 ----\n #self.bSizer11 = pw.site_lat_lon(pnl)\n\n #---sizer 6 ---\n TEXT=\"Instrument name (optional):\"\n self.bSizer6 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 7 ----\n self.bSizer7 = pw.replicate_measurements(pnl)\n\n #---sizer 8 ----\n\n TEXT = \"peak AF field (mT) if ARM: \"\n self.bSizer8 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 9 ----\n\n TEXT = \"Coil number for ASC impulse coil (if treatment units in Volts): \"\n self.bSizer9 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 10 ---\n #self.bSizer10 = pw.synthetic(pnl)\n\n #---sizer 10 ---\n TEXT = \"cooling rates [K/minutes] (seperated by comma) for cooling rate experiment:\"\n self.bSizer10 = pw.labeled_text_field(pnl, TEXT)\n\n #---buttons ----\n hboxok = pw.btn_panel(self, pnl)\n\n #------\n vbox=wx.BoxSizer(wx.VERTICAL)\n hbox0 = wx.BoxSizer(wx.HORIZONTAL)\n hbox0.Add(self.bSizer5, flag=wx.ALIGN_LEFT)\n #hbox0.Add(self.bSizer11, flag=wx.ALIGN_LEFT|wx.LEFT, border=5)\n hbox0.Add(self.bSizer6, flag=wx.ALIGN_LEFT|wx.LEFT, border=5)\n hbox1 =wx.BoxSizer(wx.HORIZONTAL)\n hbox1.Add(self.bSizer8, flag=wx.ALIGN_LEFT)\n hbox1.Add(self.bSizer9, flag=wx.ALIGN_LEFT|wx.LEFT, border=5)\n hbox2 =wx.BoxSizer(wx.HORIZONTAL)\n hbox2.Add(self.bSizer10, flag=wx.ALIGN_LEFT|wx.LEFT, border=5)\n\n vbox.Add(bSizer_info, flag=wx.ALIGN_LEFT|wx.TOP, border=8)\n vbox.Add(self.bSizer0, flag=wx.ALIGN_LEFT|wx.TOP, border=8)\n vbox.Add(self.bSizer1, flag=wx.ALIGN_LEFT|wx.TOP, border=8)\n vbox.Add(self.bSizer2, flag=wx.ALIGN_LEFT|wx.TOP, border=8)\n vbox.Add(self.bSizer3, flag=wx.ALIGN_LEFT|wx.TOP, border=8)\n vbox.Add(self.bSizer4, flag=wx.ALIGN_LEFT|wx.TOP, border=8)\n vbox.Add(self.bSizer4a, flag=wx.ALIGN_LEFT|wx.TOP, border=8)\n vbox.Add(hbox0, flag=wx.ALIGN_LEFT|wx.TOP, border=8)\n vbox.Add(self.bSizer7, flag=wx.ALIGN_LEFT|wx.TOP, border=8)\n vbox.Add(hbox1, flag=wx.ALIGN_LEFT|wx.TOP, border=8)\n vbox.Add(wx.StaticLine(pnl), 0, wx.ALL|wx.EXPAND, 5)\n vbox.Add(hbox2, flag=wx.ALIGN_LEFT|wx.TOP, border=8)\n vbox.Add(wx.StaticLine(pnl), 0, wx.ALL|wx.EXPAND, 5)\n vbox.Add(hboxok, flag=wx.ALIGN_CENTER)\n vbox.Add(wx.StaticLine(pnl), 0, wx.ALL|wx.EXPAND, 5)\n vbox.AddSpacer(20)\n\n hbox_all= wx.BoxSizer(wx.HORIZONTAL)\n hbox_all.AddSpacer(20)\n hbox_all.Add(vbox)\n hbox_all.AddSpacer(20)\n\n self.panel.SetSizer(hbox_all)\n self.panel.SetScrollbars(20, 20, 50, 50)\n hbox_all.Fit(self)\n self.Centre()\n self.Show()\n\n\n def on_okButton(self, event):\n os.chdir(self.WD)\n options_dict = {}\n SIO_file = self.bSizer0.return_value()\n if not SIO_file:\n pw.simple_warning('You must provide a SIO format file')\n return False\n options_dict['mag_file'] = str(SIO_file)\n magicoutfile=os.path.split(SIO_file)[1]+\".magic\"\n outfile =os.path.join(self.WD, magicoutfile)\n options_dict['meas_file'] = str(outfile)\n user = self.bSizer1.return_value()\n options_dict['user'] = str(user)\n if user:\n user = \"-usr \" + user\n experiment_type = self.bSizer2.return_value()\n options_dict['codelist'] = str(experiment_type)\n if experiment_type:\n experiment_type = \"-LP \" + experiment_type\n lab_field = self.bSizer3.return_value()\n if not lab_field.strip():\n lab_field = \"\"\n options_dict['labfield'] = 0\n options_dict['phi'] = 0\n options_dict['theta'] = 0\n else:\n lab_field_list = str(lab_field).split()\n options_dict['labfield'] = lab_field_list[0]\n options_dict['phi'] = lab_field_list[1]\n options_dict['theta'] = lab_field_list[2]\n lab_field = \"-dc \" + lab_field\n spc = self.bSizer4.return_value()\n options_dict['specnum'] = spc\n ncn = self.bSizer4a.return_value()\n options_dict['samp_con'] = ncn\n loc_name = self.bSizer5.return_value()\n options_dict['location'] = str(loc_name)\n if loc_name:\n loc_name = \"-loc \" + loc_name\n instrument = self.bSizer6.return_value()\n options_dict['instrument'] = str(instrument)\n if instrument:\n instrument = \"-ins \" + instrument\n replicate = self.bSizer7.return_value()\n if replicate:\n options_dict['noave'] = 0\n else:\n options_dict['noave'] = 1\n if replicate:\n replicate = ''\n else:\n replicate = '-A'\n peak_AF = self.bSizer8.return_value()\n if not peak_AF:\n peak_AF = 0\n options_dict['peakfield'] = peak_AF\n if peak_AF:\n peak_AF = \"-ac \" + peak_AF\n coil_number = self.bSizer9.return_value()\n options_dict['coil'] = coil_number\n if coil_number:\n coil_number = \"-V \" + coil_number\n cooling_rates=\"\"\n cooling_rates = self.bSizer10.return_value()\n options_dict['cooling_rates'] = cooling_rates\n\n lat, lon = '', ''\n #try: lat,lon = self.bSizer11.return_value().split()\n #except ValueError: pass\n options_dict['lat'] = lat\n options_dict['lon'] = lon\n lat = '-lat ' + lat\n lon = '-lat ' + lon\n\n # Force -A option on cooling rate correction experiment\n if cooling_rates !=\"\" and experiment_type ==\"-LP CR\":\n replicate = '-A'\n options_dict['noave'] = 1\n\n SPEC_OUTFILE = magicoutfile[:magicoutfile.find('.')] + \"_specimens.txt\"\n SAMP_OUTFILE = magicoutfile[:magicoutfile.find('.')] + \"_samples.txt\"\n SITE_OUTFILE = magicoutfile[:magicoutfile.find('.')] + \"_sites.txt\"\n LOC_OUTFILE = magicoutfile[:magicoutfile.find('.')] + \"_locations.txt\"\n options_dict['spec_file'] = SPEC_OUTFILE\n options_dict['samp_file'] = SAMP_OUTFILE\n options_dict['site_file'] = SITE_OUTFILE\n options_dict['loc_file'] = LOC_OUTFILE\n\n COMMAND = \"sio_magic.py -F {0} -Fsp {1} -Fsa {2} -Fsi {3} -Flo {4} -f {5} -spc {6} -ncn {7} {8} {9} {10} {11} {12} {13} {14} {15} {16}\".format(outfile, SPEC_OUTFILE, SAMP_OUTFILE, SITE_OUTFILE, LOC_OUTFILE, SIO_file, spc, ncn, user, experiment_type, cooling_rates, loc_name, lab_field, peak_AF, coil_number, instrument, replicate)#, lat, lon)\n print(\"COMMAND\", COMMAND)\n # to run as module:\n if convert.sio(**options_dict):\n pw.close_window(self, COMMAND, outfile)\n else:\n pw.simple_warning()\n\n def on_helpButton(self, event):\n pw.on_helpButton(text=convert.sio.__doc__)\n\n\nclass convert_CIT_files_to_MagIC(convert_files_to_MagIC):\n \"\"\"Class that converts CIT files magnetometer files into MagIC format for analysis and archiving\"\"\"\n\n def InitUI(self):\n pnl = self.panel\n\n TEXT = \"CIT Format file (.sam)\"\n bSizer_info = wx.BoxSizer(wx.HORIZONTAL)\n bSizer_info.Add(wx.StaticText(pnl, label=TEXT), wx.ALIGN_LEFT)\n\n #---sizer 0 ----\n self.bSizer0 = pw.choose_file(pnl, 'add', method = self.on_add_file_button)\n\n #---sizer 1 ----\n TEXT=\"Measurer (optional):\"\n self.bSizer1 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 2 ----\n self.bSizer2 = pw.sampling_particulars(pnl)\n\n #---sizer 3 ----\n self.bSizer3 = pw.lab_field(pnl)\n\n #---sizer 4 ----\n self.bSizer4 = pw.select_ncn(pnl)\n\n #---sizer 5 ---\n TEXT = \"specify number of characters to designate a specimen, default = 0\"\n self.bSizer5 = pw.specimen_n(pnl)\n\n #---sizer 6 ----\n TEXT=\"Location name:\"\n self.bSizer6 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 7 ----\n self.bSizer7 = pw.replicate_measurements(pnl)\n self.bSizer7.replicate_rb2.SetValue(True)\n\n #---sizer 9 ----\n TEXT=\"Number of measurement orientations (default=8)\"\n self.bSizer9 = pw.labeled_text_field(pnl, TEXT)\n\n #---buttons ---\n hboxok = pw.btn_panel(self, pnl)\n\n #------\n vbox=wx.BoxSizer(wx.VERTICAL)\n\n vbox.Add(bSizer_info, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer0, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer1, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer2, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer3, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer4, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer5, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer6, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer7, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer9, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.AddSpacer(10)\n vbox.Add(wx.StaticLine(self.panel), 0, wx.ALL|wx.EXPAND, 5)\n vbox.Add(hboxok, flag=wx.ALIGN_CENTER)\n vbox.AddSpacer(20)\n\n hbox_all= wx.BoxSizer(wx.HORIZONTAL)\n hbox_all.AddSpacer(20)\n hbox_all.Add(vbox)\n hbox_all.AddSpacer(20)\n\n self.panel.SetSizer(hbox_all)\n self.panel.SetScrollbars(20, 20, 50, 50)\n hbox_all.Fit(self)\n self.Centre()\n self.Show()\n\n def on_okButton(self, event):\n os.chdir(self.WD)\n options_dict = {}\n wd = self.WD\n options_dict['dir_path'] = wd\n full_file = self.bSizer0.return_value()\n if not full_file:\n pw.simple_warning('You must provide a CIT format file')\n return False\n input_directory, CIT_file = os.path.split(full_file)\n options_dict['magfile'] = CIT_file\n options_dict['input_dir_path'] = input_directory\n if input_directory:\n ID = \"-ID \" + input_directory\n else:\n ID = ''\n outfile = CIT_file + \".magic\"\n options_dict['meas_file'] = outfile\n samp_outfile = CIT_file[:CIT_file.find('.')] + \"_samples.txt\"\n options_dict['samp_file'] = samp_outfile\n spec_outfile = CIT_file[:CIT_file.find('.')] + \"_specimens.txt\"\n options_dict['spec_file'] = spec_outfile\n site_outfile = CIT_file[:CIT_file.find('.')] + \"_sites.txt\"\n options_dict['site_file'] = site_outfile\n loc_outfile = CIT_file[:CIT_file.find('.')] + \"_locations.txt\"\n options_dict['loc_file'] = loc_outfile\n user = self.bSizer1.return_value()\n options_dict['user'] = user\n dc_flag,dc_params = '',''\n if self.bSizer3.return_value() != '':\n dc_params = self.bSizer3.return_value().split()\n options_dict['labfield'] = dc_params[0]\n options_dict['phi'] = dc_params[1]\n options_dict['theta'] = dc_params[2]\n dc_flag = '-dc'\n if user:\n user = \"-usr \" + user\n spec_num = self.bSizer5.return_value()\n options_dict['specnum'] = spec_num\n if spec_num:\n spec_num = \"-spc \" + str(spec_num)\n else:\n spec_num = \"-spc 0\" # defaults to 0 if user doesn't choose number\n loc_name = self.bSizer6.return_value()\n options_dict['locname'] = loc_name\n if loc_name:\n loc_name = \"-loc \" + loc_name\n ncn = self.bSizer4.return_value()\n options_dict['samp_con'] = ncn\n particulars = self.bSizer2.return_value()\n options_dict['methods'] = particulars\n if particulars:\n particulars = \"-mcd \" + particulars\n replicate = self.bSizer7.return_value()\n if replicate:\n options_dict['noave'] = False\n replicate = ''\n else:\n options_dict['noave'] = True\n replicate = '-A'\n\n meas_n_orient = self.bSizer9.return_value()\n if meas_n_orient!='':\n try:\n int(meas_n_orient)\n options_dict['meas_n_orient'] = meas_n_orient\n except ValueError:\n pw.simple_warning(\"value for number of measured orienations must be a positive integer\")\n\n COMMAND = \"cit_magic.py -WD {} -f {} -F {} {} {} {} {} -ncn {} {} -Fsp {} -Fsa {} -Fsi {} -Flo {} {} {} {} -mno {}\".format(wd, CIT_file, outfile, particulars, spec_num, loc_name, user, ncn, ID, spec_outfile, samp_outfile, site_outfile, loc_outfile, replicate, dc_flag, dc_params, meas_n_orient)\n # to run as module:\n program_ran, error_message = convert.cit(**options_dict)\n if program_ran:\n pw.close_window(self, COMMAND, outfile)\n else:\n pw.simple_warning(error_message)\n\n def on_helpButton(self, event):\n pw.on_helpButton(text=convert.cit.__doc__)\n\n\nclass convert_HUJI_files_to_MagIC(convert_files_to_MagIC):\n \"\"\" \"\"\"\n def InitUI(self):\n\n pnl = self.panel\n\n TEXT = \"HUJI format file\"\n bSizer_info = wx.BoxSizer(wx.HORIZONTAL)\n bSizer_info.Add(wx.StaticText(pnl, label=TEXT), wx.ALIGN_LEFT)\n\n #---sizer 0 ----\n self.bSizer0 = pw.choose_file(pnl, 'add', method = self.on_add_file_button)\n\n TEXT = \"HUJI sample orientation data file (Optional)\"\n bSizer_infoA = wx.BoxSizer(wx.HORIZONTAL)\n bSizer_infoA.Add(wx.StaticText(pnl, label=TEXT), wx.ALIGN_LEFT)\n\n #---sizer 0A ----\n self.bSizer0A = pw.choose_file(pnl, 'add', method = self.on_add_dat_file_button)\n\n #---sizer 1 ----\n self.bSizer1 = pw.labeled_text_field(pnl)\n\n #---sizer 2 ----\n exp_names=['AF Demag', 'Thermal (includes thellier but not trm)', 'NRM only', 'TRM acquisition', 'Anisotropy experiment', 'Cooling rate experiment']\n self.bSizer2 = pw.experiment_type(pnl, exp_names)\n\n #---sizer 2a ---\n #for box in self.bSizer2.boxes:\n # self.Bind(wx.EVT_CHECKBOX, self.on_select_protocol, box)\n self.bSizer2a = wx.StaticBoxSizer( wx.StaticBox( self.panel, wx.ID_ANY, \"\" ), wx.HORIZONTAL )\n text = 'Cooling Rate (required only for cooling rate type experiments)\\nformat is xxx,yyy,zzz with no spaces '\n self.cooling_rate = wx.TextCtrl(pnl)\n self.bSizer2a.AddMany([wx.StaticText(pnl, label=text), self.cooling_rate])\n\n #---sizer 3 ----\n self.bSizer3 = pw.lab_field(pnl)\n\n #---sizer 4 ---\n TEXT = \"specify number of characters to designate a specimen, default = 0\"\n self.bSizer4 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 5 ----\n self.bSizer5 = pw.select_ncn(pnl)\n\n #---sizer 6 ----\n TEXT=\"Location name:\"\n self.bSizer6 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 7 ---\n #TEXT = \"peak AF field (mT) if ARM: \"\n #self.bSizer7 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 8 ---\n self.bSizer8 = pw.replicate_measurements(pnl)\n\n\n #---buttons ---\n hboxok = pw.btn_panel(self, pnl)\n\n #------\n vbox=wx.BoxSizer(wx.VERTICAL)\n\n vbox.Add(bSizer_info, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer0, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(bSizer_infoA, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer0A, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer1, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer2, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer2a, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer3, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer4, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer5, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer6, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n #vbox.Add(self.bSizer7, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer8, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(wx.StaticLine(pnl), 0, wx.ALL|wx.EXPAND, 5)\n vbox.Add(hboxok, flag=wx.ALIGN_CENTER)\n vbox.AddSpacer(20)\n\n self.hbox_all= wx.BoxSizer(wx.HORIZONTAL)\n self.hbox_all.AddSpacer(20)\n self.hbox_all.Add(vbox)\n self.hbox_all.AddSpacer(20)\n\n self.panel.SetSizer(self.hbox_all)\n self.bSizer2a.ShowItems(True)\n self.hbox_all.Fit(self)\n self.Centre()\n self.Show()\n\n\n def on_add_dat_file_button(self,event):\n text = \"HUJI sample orientation data file (Optional)\"\n pw.on_add_file_button(self.bSizer0A, text)\n\n def on_okButton(self, event):\n \"\"\"\n grab user input values, format them, and run huji_magic.py with the appropriate flags\n \"\"\"\n os.chdir(self.WD)\n options = {}\n HUJI_file = self.bSizer0.return_value()\n if not HUJI_file:\n pw.simple_warning(\"You must select a HUJI format file\")\n return False\n options['magfile'] = HUJI_file\n dat_file = self.bSizer0A.return_value()\n if os.path.isfile(dat_file): options['datafile'] = dat_file\n else: dat_file=\"\"\n magicoutfile=os.path.split(HUJI_file)[1]+\".magic\"\n outfile=os.path.join(self.WD, magicoutfile)\n options['meas_file'] = outfile\n magicoutfile=os.path.split(HUJI_file)[1]+\"_specimens.txt\"\n spec_outfile=os.path.join(self.WD, magicoutfile)\n options['spec_file'] = spec_outfile\n magicoutfile=os.path.split(HUJI_file)[1]+\"_samples.txt\"\n samp_outfile=os.path.join(self.WD, magicoutfile)\n options['samp_file'] = samp_outfile\n magicoutfile=os.path.split(HUJI_file)[1]+\"_sites.txt\"\n site_outfile=os.path.join(self.WD, magicoutfile)\n options['site_file'] = site_outfile\n magicoutfile=os.path.split(HUJI_file)[1]+\"_locations.txt\"\n loc_outfile=os.path.join(self.WD, magicoutfile)\n options['loc_file'] = loc_outfile\n user = self.bSizer1.return_value()\n options['user'] = user\n if user:\n user = '-usr ' + user\n experiment_type = self.bSizer2.return_value()\n options['codelist'] = experiment_type\n if not experiment_type:\n pw.simple_warning(\"You must select an experiment type\")\n return False\n cooling_rate = self.cooling_rate.GetValue() or 0\n if cooling_rate:\n experiment_type = experiment_type + \" \" + cooling_rate\n lab_field = self.bSizer3.return_value()\n if not lab_field:\n lab_field = \"0 0 0\"\n lab_field_list = lab_field.split()\n options['labfield'] = lab_field_list[0]\n options['phi'] = lab_field_list[1]\n options['theta'] = lab_field_list[2]\n lab_field = '-dc ' + lab_field\n spc = self.bSizer4.return_value()\n options['specnum'] = spc or 0\n if not spc:\n spc = '-spc 0'\n else:\n spc = '-spc ' + spc\n ncn = self.bSizer5.return_value()\n options['samp_con'] = ncn\n loc_name = self.bSizer6.return_value()\n options['location'] = loc_name\n if loc_name:\n loc_name = '-loc ' + loc_name\n #peak_AF = self.bSizer7.return_value()\n #options['peakfield'] = peak_AF\n\n replicate = self.bSizer8.return_value()\n if replicate:\n options['noave'] = 0\n replicate = ''\n else:\n options['noave'] = 1\n replicate = '-A'\n\n COMMAND = \"huji_magic_new.py -f {} -fd {} -F {} -Fsp {} -Fsa {} -Fsi {} -Flo {} {} -LP {} {} -ncn {} {} {} {}\".format(HUJI_file, dat_file, outfile, spec_outfile, samp_outfile, site_outfile, loc_outfile, user, experiment_type, loc_name, ncn, lab_field, spc, replicate)\n program_ran, error_message = convert.huji(**options)\n if program_ran:\n pw.close_window(self, COMMAND, outfile)\n else:\n pw.simple_warning(error_message)\n\n def on_helpButton(self, event):\n pw.on_helpButton(text=convert.huji.__doc__())\n\n\nclass convert_2g_binary_files_to_MagIC(convert_files_to_MagIC):\n\n def InitUI(self):\n\n pnl = self.panel\n\n TEXT = \"Folder containing one or more 2g-binary format files\"\n bSizer_info = wx.BoxSizer(wx.HORIZONTAL)\n bSizer_info.Add(wx.StaticText(pnl, label=TEXT), wx.ALIGN_LEFT)\n\n #---sizer 0 ----\n #self.bSizer0 = pw.choose_file(pnl, 'add', method = self.on_add_file_button)\n self.bSizer0 = pw.choose_dir(pnl, btn_text = 'add', method = self.on_add_dir_button)\n\n #---sizer 1 ----\n self.bSizer1 = pw.sampling_particulars(pnl)\n\n #---sizer 2 ----\n ncn_keys = ['XXXXY', 'XXXX-YY', 'XXXX.YY', 'XXXX[YYY] where YYY is sample designation, enter number of Y', 'sample name=site name', 'Site is entered under a separate column', '[XXXX]YYY where XXXX is the site name, enter number of X']\n self.bSizer2 = pw.select_ncn(pnl, ncn_keys)\n\n #---sizer 3 ----\n TEXT = \"specify number of characters to designate a specimen, default = 0\"\n self.bSizer3 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 4 ----\n self.bSizer4 = pw.select_specimen_ocn(pnl)\n\n #---sizer 5 ----\n TEXT=\"Location name:\"\n self.bSizer5 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 6 ---\n TEXT=\"Instrument name (optional):\"\n self.bSizer6 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 7 ----\n self.bSizer7 = pw.replicate_measurements(pnl)\n\n #---sizer 8 ----\n self.bSizer8 = pw.site_lat_lon(pnl)\n\n #---buttons ---\n hboxok = pw.btn_panel(self, pnl) # creates ok, cancel, help buttons and binds them to appropriate methods\n\n #------\n vbox=wx.BoxSizer(wx.VERTICAL)\n\n vbox.Add(bSizer_info, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer0, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer1, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer2, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer3, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer4, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer5, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer8, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer6, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer7, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(wx.StaticLine(pnl), 0, wx.ALL|wx.EXPAND, 5)\n vbox.Add(hboxok, flag=wx.ALIGN_CENTER)\n vbox.AddSpacer(20)\n\n hbox_all= wx.BoxSizer(wx.HORIZONTAL)\n hbox_all.AddSpacer(20)\n hbox_all.Add(vbox)\n hbox_all.AddSpacer(20)\n\n self.panel.SetSizer(hbox_all)\n self.panel.SetScrollbars(20, 20, 50, 50)\n hbox_all.Fit(self)\n self.Centre()\n self.Show()\n\n\n #---button methods ---\n\n def on_okButton(self, event):\n os.chdir(self.WD)\n options_dict = {}\n WD = self.WD\n options_dict['dir_path'] = WD\n directory = self.bSizer0.return_value()\n options_dict['input_dir'] = directory\n if not directory:\n pw.simple_warning('You must select a directory containing 2g binary files')\n return False\n files = os.listdir(directory)\n files = [str(f) for f in files if str(f).endswith('.dat') or str(f).endswith('.DAT')]\n if not files:\n pw.simple_warning('No .dat files found in {}'.format(directory))\n return False\n ID = \"-ID \" + directory\n if self.bSizer1.return_value():\n particulars = self.bSizer1.return_value()\n options_dict['gmeths'] = particulars\n mcd = '-mcd ' + particulars\n else:\n mcd = ''\n ncn = self.bSizer2.return_value()\n options_dict['samp_con'] = ncn\n spc = self.bSizer3.return_value()\n options_dict['specnum'] = spc or 0\n if not spc:\n spc = '-spc 1'\n else:\n spc = '-spc ' + spc\n ocn = self.bSizer4.return_value()\n options_dict['or_con'] = ocn\n loc_name = self.bSizer5.return_value()\n options_dict['location'] = loc_name\n if loc_name:\n loc_name = \"-loc \" + loc_name\n try: lat,lon = self.bSizer8.return_value().split()\n except ValueError: lat,lon = '',''\n options_dict['lat'] = lat\n options_dict['lon'] = lon\n instrument = self.bSizer6.return_value()\n options_dict['inst'] = instrument\n if instrument:\n instrument = \"-ins \" + instrument\n replicate = self.bSizer7.return_value()\n if replicate:\n replicate = '-a'\n options_dict['noave'] = 0\n else:\n replicate = ''\n options_dict['noave'] = 1\n for f in files:\n file_2g_bin = f\n outfile = file_2g_bin + \".magic\"\n options_dict['meas_file'] = outfile\n options_dict['mag_file'] = f\n spec_outfile = file_2g_bin + \"_specimens.txt\"\n samp_outfile = file_2g_bin + \"_samples.txt\"\n site_outfile = file_2g_bin + \"_sites.txt\"\n loc_outfile = file_2g_bin + \"_locations.txt\"\n options_dict['spec_file'] = spec_outfile\n options_dict['samp_file'] = samp_outfile\n options_dict['site_file'] = site_outfile\n options_dict['loc_file'] = loc_outfile\n COMMAND = \"_2g_bin_magic.py -WD {} -f {} -F {} -Fsp {} -Fsa {} -Fsi {} -Flo {} -ncn {} {} {} -ocn {} {} {} {} {} -lat {} -lon {}\".format(WD, file_2g_bin, outfile, spec_outfile, samp_outfile, site_outfile, loc_outfile, ncn, mcd, spc, ocn, loc_name, replicate, ID, instrument,lat,lon)\n if files.index(f) == (len(files) - 1): # terminate process on last file call\n # to run as module:\n if convert._2g_bin(**options_dict):\n pw.close_window(self, COMMAND, outfile)\n else:\n pw.simple_warning()\n\n else:\n print(\"Running equivalent of python command: \", COMMAND)\n if convert._2g_bin(**options_dict):\n pass # success, continue on to next file\n else:\n pw.simple_warning()\n\n def on_helpButton(self, event):\n # to run as module:\n pw.on_helpButton(text=convert._2g_bin.__doc__)\n\n # to run as command line:\n #pw.on_helpButton(\"_2g_bin_magic.py -h\")\n\n\nclass convert_2g_ascii_files_to_MagIC(convert_files_to_MagIC):\n\n def InitUI(self):\n\n pnl = self.panel\n\n TEXT = \"Folder containing one or more 2g-ascii format files\"\n bSizer_info = wx.BoxSizer(wx.HORIZONTAL)\n bSizer_info.Add(wx.StaticText(pnl, label=TEXT), wx.ALIGN_LEFT)\n\n #---sizer 0 ----\n #self.bSizer0 = pw.choose_file(pnl, 'add', method = self.on_add_file_button)\n self.bSizer0 = pw.choose_dir(pnl, btn_text = 'add', method = self.on_add_dir_button)\n\n #---sizer 1 ----\n self.bSizer1 = pw.sampling_particulars(pnl)\n\n #---sizer 2 ----\n ncn_keys = ['XXXXY', 'XXXX-YY', 'XXXX.YY', 'XXXX[YYY] where YYY is sample designation, enter number of Y', 'sample name=site name', 'Site is entered under a separate column', '[XXXX]YYY where XXXX is the site name, enter number of X']\n self.bSizer2 = pw.select_ncn(pnl, ncn_keys)\n\n #---sizer 3 ----\n TEXT = \"specify number of characters to designate a specimen, default = 0\"\n self.bSizer3 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 4 ----\n self.bSizer4 = pw.select_specimen_ocn(pnl)\n\n #---sizer 5 ----\n TEXT=\"Location name:\"\n self.bSizer5 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 6 ---\n TEXT=\"Instrument name (optional):\"\n self.bSizer6 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 7 ----\n self.bSizer7 = pw.replicate_measurements(pnl)\n\n #---sizer 8 ----\n self.bSizer8 = pw.site_lat_lon(pnl)\n\n #---buttons ---\n hboxok = pw.btn_panel(self, pnl) # creates ok, cancel, help buttons and binds them to appropriate methods\n\n #------\n vbox=wx.BoxSizer(wx.VERTICAL)\n\n vbox.Add(bSizer_info, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer0, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer1, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer2, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer3, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer4, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer5, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer8, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer6, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer7, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(wx.StaticLine(pnl), 0, wx.ALL|wx.EXPAND, 5)\n vbox.Add(hboxok, flag=wx.ALIGN_CENTER)\n vbox.AddSpacer(20)\n\n hbox_all= wx.BoxSizer(wx.HORIZONTAL)\n hbox_all.AddSpacer(20)\n hbox_all.Add(vbox)\n hbox_all.AddSpacer(20)\n\n self.panel.SetSizer(hbox_all)\n self.panel.SetScrollbars(20, 20, 50, 50)\n hbox_all.Fit(self)\n self.Centre()\n self.Show()\n\n\n #---button methods ---\n\n def on_okButton(self, event):\n os.chdir(self.WD)\n options_dict = {}\n WD = self.WD\n options_dict['dir_path'] = WD\n directory = self.bSizer0.return_value()\n options_dict['input_dir'] = directory\n if not directory:\n pw.simple_warning('You must select a directory containing 2g ascii files')\n return False\n files = os.listdir(directory)\n files = [str(f) for f in files if str(f).endswith('.asc') or str(f).endswith('.ASC')]\n if not files:\n pw.simple_warning('No .dat files found in {}'.format(directory))\n return False\n ID = \"-ID \" + directory\n if self.bSizer1.return_value():\n particulars = self.bSizer1.return_value()\n options_dict['gmeths'] = particulars\n mcd = '-mcd ' + particulars\n else:\n mcd = ''\n ncn = self.bSizer2.return_value()\n options_dict['samp_con'] = ncn\n spc = self.bSizer3.return_value()\n options_dict['specnum'] = spc or 0\n if not spc:\n spc = '-spc 1'\n else:\n spc = '-spc ' + spc\n ocn = self.bSizer4.return_value()\n options_dict['or_con'] = ocn\n loc_name = self.bSizer5.return_value()\n options_dict['location'] = loc_name\n if loc_name:\n loc_name = \"-loc \" + loc_name\n try: lat,lon = self.bSizer8.return_value().split()\n except ValueError: lat,lon = '',''\n options_dict['lat'] = lat\n options_dict['lon'] = lon\n instrument = self.bSizer6.return_value()\n options_dict['inst'] = instrument\n if instrument:\n instrument = \"-ins \" + instrument\n replicate = self.bSizer7.return_value()\n if replicate:\n replicate = '-a'\n options_dict['noave'] = 0\n else:\n replicate = ''\n options_dict['noave'] = 1\n for f in files:\n file_2g_asc = f\n outfile = file_2g_asc + \".magic\"\n options_dict['meas_file'] = outfile\n options_dict['mag_file'] = f\n spec_outfile = file_2g_asc + \"_specimens.txt\"\n samp_outfile = file_2g_asc + \"_samples.txt\"\n site_outfile = file_2g_asc + \"_sites.txt\"\n loc_outfile = file_2g_asc + \"_locations.txt\"\n options_dict['spec_file'] = spec_outfile\n options_dict['samp_file'] = samp_outfile\n options_dict['site_file'] = site_outfile\n options_dict['loc_file'] = loc_outfile\n COMMAND = \"_2g_asc_magic.py -WD {} -f {} -F {} -Fsp {} -Fsa {} -Fsi {} -Flo {} -ncn {} {} {} -ocn {} {} {} {} {} -lat {} -lon {}\".format(WD, file_2g_asc, outfile, spec_outfile, samp_outfile, site_outfile, loc_outfile, ncn, mcd, spc, ocn, loc_name, replicate, ID, instrument,lat,lon)\n if files.index(f) == (len(files) - 1): # terminate process on last file call\n # to run as module:\n if convert._2g_asc(**options_dict):\n pw.close_window(self, COMMAND, outfile)\n else:\n pw.simple_warning()\n\n else:\n print(\"Running equivalent of python command: \", COMMAND)\n if convert._2g_asc(**options_dict):\n pass # success, continue on to next file\n else:\n pw.simple_warning()\n\n def on_helpButton(self, event):\n # to run as module:\n pw.on_helpButton(text=convert._2g_bin.__doc__)\n\n # to run as command line:\n #pw.on_helpButton(\"_2g_asc_magic.py -h\")\n\nclass convert_LDEO_files_to_MagIC(convert_files_to_MagIC):\n\n \"\"\" \"\"\"\n def InitUI(self):\n\n pnl = self.panel\n\n TEXT = \"LDEO format file\"\n bSizer_info = wx.BoxSizer(wx.HORIZONTAL)\n bSizer_info.Add(wx.StaticText(pnl, label=TEXT), wx.ALIGN_LEFT)\n\n #---sizer 0 ----\n self.bSizer0 = pw.choose_file(pnl, 'add', method = self.on_add_file_button)\n\n #---sizer 2 ---\n exp_names=['AF Demag', 'Thermal (includes thellier but not trm)', 'Shaw method', 'IRM (acquisition)', 'NRM only', 'TRM acquisition', 'double AF demag', 'triple AF demag (GRM protocol)', 'Anisotropy experiment']\n self.bSizer2 = pw.experiment_type(pnl, exp_names)\n\n #---sizer 2a ---\n # add conditional boxsizer for Shaw experiments\n # if arm_labfield and trm_peakT are properly added into ldeo_magic\n\n #---sizer 3 ----\n self.bSizer3 = pw.lab_field(pnl)\n\n #---sizer 4 ----\n self.bSizer4 = pw.select_ncn(pnl)\n\n #---sizer 5 ----\n TEXT = \"specify number of characters to designate a specimen, default = 0\"\n self.bSizer5 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 6 ---\n TEXT=\"Location name:\"\n self.bSizer6 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 8 ---\n self.bSizer8 = pw.replicate_measurements(pnl)\n\n #---sizer 9 ----\n TEXT = \"peak AF field (mT) if ARM: \"\n self.bSizer9 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 10 ---\n TEXT = \"Coil number for ASC impulse coil (if treatment units in Volts): \"\n self.bSizer10 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 11 ---\n self.bSizer11 = pw.mass_or_volume_buttons(pnl)\n\n #---buttons ---\n hboxok = pw.btn_panel(self, pnl)\n\n #------\n vbox=wx.BoxSizer(wx.VERTICAL)\n hbox0 = wx.BoxSizer(wx.HORIZONTAL)\n hbox0.Add(self.bSizer6, flag=wx.ALIGN_LEFT|wx.RIGHT, border=5)\n hbox1 = wx.BoxSizer(wx.HORIZONTAL)\n hbox1.Add(self.bSizer9, flag=wx.ALIGN_LEFT|wx.RIGHT, border=5)\n hbox1.Add(self.bSizer10, flag=wx.ALIGN_LEFT)\n\n vbox.Add(bSizer_info, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer0, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer2, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer11, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer3, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer4, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer5, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(hbox0, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer8, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(hbox1, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.AddSpacer(10)\n vbox.Add(wx.StaticLine(pnl), 0, wx.ALL|wx.EXPAND, 5)\n vbox.Add(hboxok, flag=wx.ALIGN_CENTER|wx.BOTTOM, border=20)\n\n hbox_all= wx.BoxSizer(wx.HORIZONTAL)\n hbox_all.AddSpacer(20)\n hbox_all.Add(vbox)\n hbox_all.AddSpacer(20)\n\n self.panel.SetSizer(hbox_all)\n self.panel.SetScrollbars(20, 20, 50, 50)\n hbox_all.Fit(self)\n self.Centre()\n self.Show()\n\n def on_okButton(self, event):\n os.chdir(self.WD)\n options_dict = {}\n LDEO_file = self.bSizer0.return_value()\n if not LDEO_file:\n pw.simple_warning(\"You must provide a LDEO format file\")\n return False\n options_dict['magfile'] = LDEO_file\n magicoutfile=os.path.split(LDEO_file)[1]+\".magic\"\n outfile=os.path.join(self.WD, magicoutfile)\n options_dict['meas_file'] = outfile\n magicoutfile=os.path.split(LDEO_file)[1]+\"_specimens.txt\"\n spec_outfile=os.path.join(self.WD, magicoutfile)\n options_dict['spec_file'] = spec_outfile\n magicoutfile=os.path.split(LDEO_file)[1]+\"_samples.txt\"\n samp_outfile=os.path.join(self.WD, magicoutfile)\n options_dict['samp_file'] = samp_outfile\n magicoutfile=os.path.split(LDEO_file)[1]+\"_sites.txt\"\n site_outfile=os.path.join(self.WD, magicoutfile)\n options_dict['site_file'] = site_outfile\n magicoutfile=os.path.split(LDEO_file)[1]+\"_locations.txt\"\n loc_outfile=os.path.join(self.WD, magicoutfile)\n options_dict['loc_file'] = loc_outfile\n experiment_type = self.bSizer2.return_value()\n options_dict['codelist'] = experiment_type\n if experiment_type:\n experiment_type = \"-LP \" + experiment_type\n lab_field = self.bSizer3.return_value()\n if lab_field:\n options_dict['labfield'], options_dict['phi'], options_dict['theta'] = lab_field.split()\n lab_field = \"-dc \" + lab_field\n ncn = self.bSizer4.return_value()\n options_dict['samp_con'] = ncn\n spc = self.bSizer5.return_value()\n options_dict['specnum'] = spc or 0\n if spc:\n spc = \"-spc \" + spc\n else:\n spc = \"-spc 0\"\n loc_name = self.bSizer6.return_value()\n options_dict['location'] = loc_name\n if loc_name:\n loc_name = \"-loc \" + loc_name\n replicate = self.bSizer8.return_value()\n if replicate:\n replicate = \"\"\n options_dict['noave'] = 0 # do average\n else:\n replicate = \"-A\"\n options_dict['noave'] = 1 # don't average\n AF_field = self.bSizer9.return_value()\n options_dict['peakfield'] = AF_field or 0\n if AF_field:\n AF_field = \"-ac \" + AF_field\n coil_number = self.bSizer10.return_value()\n options_dict['coil'] = coil_number\n if coil_number:\n coil_number = \"-V \" + coil_number\n mv = self.bSizer11.return_value()\n options_dict['mass_or_vol'] = mv\n COMMAND = \"ldeo_magic.py -f {0} -F {1} -Fsp {2} -Fsa {3} -Fsi {4} -Flo {5} {6} {7} -ncn {8} {9} {10} {11} {12} {13} -mv {14}\".format(LDEO_file, outfile, spec_outfile, samp_outfile, site_outfile, loc_outfile, experiment_type, lab_field, ncn, spc, loc_name, replicate, AF_field, coil_number, mv)\n # to run as module:\n program_ran, error_message = convert.ldeo(**options_dict)\n if program_ran:\n pw.close_window(self, COMMAND, outfile)\n else:\n pw.simple_warning(error_message)\n\n def on_helpButton(self, event):\n pw.on_helpButton(text=convert.ldeo.__doc__)\n\n\nclass convert_IODP_files_to_MagIC(convert_files_to_MagIC):\n\n \"\"\" \"\"\"\n\n def InitUI(self):\n\n pnl = self.panel\n\n TEXT = \"IODP format file\"\n bSizer_info = wx.BoxSizer(wx.HORIZONTAL)\n bSizer_info.Add(wx.StaticText(pnl, label=TEXT), wx.ALIGN_LEFT)\n\n #---sizer 0a ---\n TEXT = \"IODP file type\"\n self.bSizer0a = pw.radio_buttons(pnl, ['SRM discrete', 'SRM section', 'JR6', 'KLY4S'], \"Format: \", wx.HORIZONTAL)\n self.Bind(wx.EVT_RADIOBUTTON, self.on_switch_format)\n\n #self.bSizer0a = pw.labeled_yes_or_no(pnl, TEXT, label1, label2)\n #self.Bind(wx.EVT_RADIOBUTTON, self.on_switch_format, self.bSizer0a.rb1)\n #self.Bind(wx.EVT_RADIOBUTTON, self.on_switch_format, self.bSizer0a.rb2)\n\n #---sizer 0b ---\n TEXT = \"If you haven't already imported a samples data file from LIMS, please do so below!\\nThis is required to complete the SRM discrete import.\"\n self.bSizer0b = pw.simple_text(pnl, TEXT)\n\n #---sizer 0 ----\n self.bSizer0 = pw.choose_file(pnl, 'add', method = self.on_add_file_button)\n\n #---sizer 1 ----\n self.bSizer1 = pw.site_lat_lon(pnl)\n\n #---sizer 2 ----\n self.bSizer2 = pw.replicate_measurements(pnl)\n\n #---sizer 3 ----\n #self.bSizer1a = pw.labeled_text_field(pnl, 'Specimen volume, default is 12 cc.\\nPlease provide volume in cc.')\n self.bSizer3 = pw.labeled_text_field(pnl, 'Volume in cc, default is 7cc.')\n\n #---sizer 4 ---\n self.bSizer4 = pw.labeled_text_field(pnl, 'Depth Key, default is \"Depth CSF-B (m)\"')\n\n #---sizer 5 ---\n self.bSizer5 = pw.choose_file(pnl, 'add', method = self.on_add_samples_button,\n text=\"IODP samples data file downloaded from LIMS\")\n\n #---buttons ---\n hboxok = pw.btn_panel(self, pnl)\n\n #------\n vbox=wx.BoxSizer(wx.VERTICAL)\n\n vbox.AddSpacer(10)\n vbox.Add(bSizer_info, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer0a, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer0, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer1, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer2, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer0b, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer3, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer4, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer5, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n #vbox.Add(self.bSizer6, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n #vbox.Add(self.bSizer7, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n #vbox.AddSpacer(10)\n #vbox.Add(wx.StaticLine(pnl), 0, wx.ALL|wx.EXPAND, 5)\n vbox.Add(hboxok, flag=wx.ALIGN_CENTER)\n vbox.AddSpacer(20)\n\n # grey out what isn't initially needed\n self.bSizer3.text_field.Disable()\n self.bSizer3.label.SetForegroundColour((190, 190, 190))\n self.bSizer4.text_field.Disable()\n self.bSizer4.label.SetForegroundColour((190, 190, 190))\n\n\n self.hbox_all = wx.BoxSizer(wx.HORIZONTAL)\n self.hbox_all.AddSpacer(20)\n self.hbox_all.Add(vbox)\n self.hbox_all.AddSpacer(20)\n\n self.panel.SetSizer(self.hbox_all)\n self.panel.SetScrollbars(20, 20, 50, 50)\n self.hbox_all.Fit(self)\n self.Centre()\n self.Show()\n\n def on_okButton(self, event):\n os.chdir(self.WD)\n wait = wx.BusyInfo(\"Please wait, working...\\nFor large files, this may take a few minutes\")\n wx.SafeYield()\n wd = self.WD\n full_file = self.bSizer0.return_value()\n ID, IODP_file = os.path.split(full_file)\n if not ID:\n ID = '.'\n fmt = self.bSizer0a.return_value()\n if not IODP_file:\n article = \"an\" if fmt[0] == \"S\" else \"a\"\n pw.simple_warning(\"You must provide {} {} file to convert\".format(article, fmt))\n return\n outfile = IODP_file + \".magic\"\n spec_outfile = IODP_file[:IODP_file.find('.')] + \"_specimens.txt\"\n samp_outfile = IODP_file[:IODP_file.find('.')] + \"_samples.txt\"\n site_outfile = IODP_file[:IODP_file.find('.')] + \"_sites.txt\"\n loc_outfile = IODP_file[:IODP_file.find('.')] + \"_locations.txt\"\n replicate = self.bSizer2.return_value()\n if replicate: # do average\n noave = 0\n else: # don't average\n noave = 1\n try: lat,lon = self.bSizer1.return_value().split()\n except ValueError: lat,lon = '',''\n volume = self.bSizer3.return_value()\n if not volume and fmt != 'KLY4S':\n volume = 7\n comp_depth_key = self.bSizer4.return_value()\n dc_field = self.bSizer4.return_value()\n instrument = self.bSizer4.return_value()\n samp_infile = self.bSizer5.return_value()\n\n # if sample file is available, run that conversion first\n if samp_infile:\n program_ran, error_message = convert.iodp_samples_csv(samp_infile)\n if program_ran:\n print('-I- samples are read in')\n else:\n print('-W ', error_message)\n pw.simple_warning(\"Couldn't read in {}. Trying to continue with next step.\".format(samp_infile))\n\n if fmt == 'SRM section': # SRM section\n COMMAND = \"convert.iodp_srm_lore({}, {}, {}, noave={}, comp_depth_key={}, meas_file={}, lat={}, lon={})\".format(IODP_file, wd, ID, noave, comp_depth_key, outfile, lat, lon)\n program_ran, error_message = convert.iodp_srm_lore(IODP_file, wd, ID, noave=noave,\n comp_depth_key=comp_depth_key,\n meas_file=outfile,\n lat=lat, lon=lon)\n elif fmt == 'SRM discrete': # SRM discrete\n COMMAND = \"convert.iodp_dscr_lore({}, dir_path={}, input_dir_path={}, volume={}, noave={}, meas_file={}, spec_file='specimens.txt')\".format(IODP_file, wd, ID, volume, noave, outfile)\n # check for needed specimens file\n if not os.path.exists(os.path.join(wd, \"specimens.txt\")):\n pw.simple_warning(\"You need to provide an IODP samples data file\")\n return\n program_ran, error_message = convert.iodp_dscr_lore(IODP_file, dir_path=wd,\n input_dir_path=ID, volume=volume, noave=noave,\n meas_file=outfile, spec_file=\"specimens.txt\")\n\n elif fmt == \"JR6\":\n COMMAND = \"convert.iodp_jr6_lore({}, dir_path={}, input_dir_path={}, volume={}, noave={}, dc_field={}, meas_file={}, spec_file='specimens.txt')\".format(IODP_file, wd, ID, volume, noave, dc_field, outfile)\n program_ran, error_message = convert.iodp_jr6_lore(IODP_file, dir_path=wd,\n input_dir_path=ID, volume=volume, noave=noave,\n dc_field=dc_field,\n meas_file=outfile, spec_file=\"specimens.txt\")\n\n print(\"convert JR6\")\n\n elif fmt == \"KLY4S\":\n COMMAND = \"convert.iodp_kly4s_lore({}, meas_out={}, spec_infile='specimens.txt', spec_out='kly4s_specimens.txt', instrument={}, actual_volume={}, dir_path={}, input_dir_path={})\".format(IODP_file, outfile, instrument, volume, wd, ID)\n program_ran, error_message = convert.iodp_kly4s_lore(IODP_file, meas_out=outfile, spec_infile='specimens.txt',\n spec_out='kly4s_specimens.txt', instrument=instrument,\n actual_volume=volume, dir_path=wd, input_dir_path=ID)\n print(\"convert KLY4S\")\n\n print(COMMAND)\n if program_ran:\n pw.close_window(self, COMMAND, outfile)\n else:\n pw.simple_warning(error_message)\n\n\n del wait\n\n def on_switch_format(self, event):\n fmt = self.bSizer0a.return_value()\n if fmt == \"SRM section\":\n self.bSizer0b.static_text.SetLabel(\"Please provide Depth key and Volume below.\\nYou may optionally provide a samples data file.\")\n self.bSizer3.label.SetLabel('Volume in cc, default is 7cc.')\n self.bSizer3.text_field.Enable()\n self.bSizer3.label.SetForegroundColour(wx.BLACK)\n self.bSizer4.label.SetLabel('Depth Key, default is \"Depth CSF-B (m)\"')\n self.bSizer4.text_field.Enable()\n self.bSizer4.label.SetForegroundColour(wx.BLACK)\n elif fmt == \"SRM discrete\":\n self.bSizer0b.static_text.SetLabel(\"If you haven't already imported a samples data file from LIMS, please do so below!\\nThis is required to complete the SRM discrete import.\")\n self.bSizer3.text_field.Disable()\n self.bSizer3.label.SetForegroundColour((190, 190, 190))\n self.bSizer4.text_field.Disable()\n self.bSizer4.label.SetForegroundColour((190, 190, 190))\n elif fmt == \"JR6\":\n self.bSizer0b.static_text.SetLabel(\"If you haven't already imported a samples data file from LIMS, please do so below!\\nThis is required to complete the JR6 import.\")\n self.bSizer3.label.SetLabel('Volume in cc, default is 7cc.')\n self.bSizer3.text_field.Enable()\n self.bSizer3.label.SetForegroundColour(wx.BLACK)\n self.bSizer4.label.SetLabel('DC field, default is 50e-6 ')\n self.bSizer4.text_field.Enable()\n self.bSizer4.label.SetForegroundColour(wx.BLACK)\n elif fmt == \"KLY4S\":\n self.bSizer0b.static_text.SetLabel(\"Please provide Instrument name and actual specimen volume below (if known).\\nIf you haven't already imported a samples data file from LIMS, please do so below!\")\n self.bSizer3.label.SetLabel(\"Actual specimen volume\")\n self.bSizer3.text_field.Enable()\n self.bSizer3.label.SetForegroundColour(wx.BLACK)\n self.bSizer4.label.SetLabel('Instrument name, default is IODP-KLY4S ')\n self.bSizer4.text_field.Enable()\n self.bSizer4.label.SetForegroundColour(wx.BLACK)\n\n\n self.hbox_all.Fit(self)\n\n\n def on_add_samples_button(self, event):\n text = \"choose sample file downloaded from LIMS\"\n pw.on_add_file_button(self.bSizer5, text)\n\n\n def on_helpButton(self, event):\n fmt = self.bSizer0a.return_value()\n if fmt == 'SRM section':\n pw.on_helpButton(text=convert.iodp_srm_lore.__doc__)\n elif fmt == 'SRM discrete':\n pw.on_helpButton(text=convert.iodp_dscr_lore.__doc__)\n elif fmt == 'JR6':\n pw.on_helpButton(text=convert.iodp_jr6_lore.__doc__)\n elif fmt == 'KLY4S':\n pw.on_helpButton(text=convert.iodp_kly4s_lore.__doc__)\n\n\n\nclass convert_PMD_files_to_MagIC(convert_files_to_MagIC):\n \"\"\" \"\"\"\n\n def InitUI(self):\n pnl = self.panel\n\n TEXT = \"Folder containing one or more PMD format files\"\n bSizer_info = wx.BoxSizer(wx.HORIZONTAL)\n bSizer_info.Add(wx.StaticText(pnl, label=TEXT), wx.ALIGN_LEFT)\n\n #---sizer 0 ----\n self.bSizer0 = pw.choose_dir(pnl, 'add', method = self.on_add_dir_button)\n\n #---sizer 2 ----\n ncn_keys = ['XXXXY', 'XXXX-YY', 'XXXX.YY', 'XXXX[YYY] where YYY is sample designation, enter number of Y', 'sample name=site name', 'Site is entered under a separate column', '[XXXX]YYY where XXXX is the site name, enter number of X']\n self.bSizer2 = pw.select_ncn(pnl, ncn_keys)\n\n #---sizer 3 ---\n # TEXT = \"specify number of characters to designate a specimen, default = 0\"\n # self.bSizer3 = pw.labeled_text_field(pnl, TEXT)\n self.bSizer3 = pw.specimen_n(pnl)\n\n\n #---sizer 4 ----\n TEXT=\"Location name:\"\n self.bSizer4 = pw.labeled_text_field(pnl, TEXT)\n\n\n #---sizer 5 ----\n\n self.bSizer5 = pw.sampling_particulars(pnl)\n\n #---sizer 6 ---\n self.bSizer6 = pw.replicate_measurements(pnl)\n\n #---sizer 7 ---\n self.bSizer7 = pw.site_lat_lon(pnl)\n\n #---sizer 8 ----\n TEXT=\"Demagnetization Method: t for thermal, af for AF demag (optional):\\nDemag type is automatically detected for files using the H or M labels\\nfor AF demag or the T label for thermal demag in step names.\"\n \n self.bSizer8 = pw.labeled_text_field(pnl, TEXT)\n\n #---buttons ---\n hboxok = pw.btn_panel(self, pnl)\n\n #------\n vbox=wx.BoxSizer(wx.VERTICAL)\n\n vbox.AddSpacer(10)\n vbox.Add(bSizer_info, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer0, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer2, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer3, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer4, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer5, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer7, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer8, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer6, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(hboxok, flag=wx.ALIGN_CENTER)\n vbox.AddSpacer(20)\n\n hbox_all= wx.BoxSizer(wx.HORIZONTAL)\n hbox_all.AddSpacer(20)\n hbox_all.Add(vbox)\n hbox_all.AddSpacer(20)\n\n self.panel.SetSizer(hbox_all)\n self.panel.SetScrollbars(20, 20, 50, 50)\n hbox_all.Fit(self)\n self.Centre()\n self.Show()\n\n\n def on_okButton(self, event):\n os.chdir(self.WD)\n options = {}\n WD = self.WD\n options['dir_path'] = WD\n directory = self.bSizer0.return_value() or '.'\n options['input_dir_path'] = directory\n files = os.listdir(directory)\n files = [str(f) for f in files if str(f).upper().endswith('.PMD')]\n if files:\n samp_outfile = files[0][:files[0].find('.')] + files[-1][:files[-1].find('.')] + \"_samples.txt\"\n options['samp_file'] = samp_outfile\n else:\n #raise Exception(\"No pmd files found in {}, try a different directory\".format(WD))\n pw.simple_warning(\"No pmd files found in {}, try a different directory\".format(WD))\n ID = \"-ID \" + directory\n ncn = self.bSizer2.return_value()\n options['samp_con'] = ncn\n spc = self.bSizer3.return_value() or 0\n options['specnum'] = spc\n loc_name = self.bSizer4.return_value()\n options['location'] = loc_name\n dmg = self.bSizer8.return_value().lower() #Make lower case because the dmg options are t or af\n options['dmg'] = dmg\n if dmg != \"\" and dmg != \"t\" and dmg != \"af\":\n pw.simple_warning(\"The only valid demagnetization methods t and af, but program recieved: %s\"%dmg)\n return\n if loc_name:\n location = loc_name\n loc_name = \"-loc \" + loc_name\n particulars = self.bSizer5.return_value()\n options['meth_code'] = particulars\n if particulars:\n particulars = \"-mcd \" + particulars\n try: lat,lon = self.bSizer7.return_value().split()\n except ValueError: lat,lon = '',''\n options['lat'] = lat\n options['lon'] = lon\n lat = '-lat ' + lat\n lon = '-lat ' + lon\n replicate = self.bSizer6.return_value()\n if replicate:\n replicate = ''\n else:\n replicate = '-A'\n options['noave'] = 1 # don't average\n for f in files:\n options['mag_file'] = f\n outfile = f + \".magic\"\n options['meas_file'] = outfile\n spec_outfile = f[:f.find('.')] + \"_specimens.txt\"\n options['spec_file'] = spec_outfile\n samp_outfile = f[:f.find('.')] + \"_samples.txt\"\n options['samp_file'] = samp_outfile\n site_outfile = f[:f.find('.')] + \"_sites.txt\"\n options['site_file'] = site_outfile\n loc_outfile = f[:f.find('.')] + \"_locations.txt\"\n options['loc_file'] = loc_outfile\n COMMAND = \"pmd_magic.py -WD {} -f {} -F {} -Fsp {} -Fsa {} -Fsi {} -Flo {} -dmg {} -ncn {} {} -spc {} {} {} {} {} {}\".format(WD, f, outfile, spec_outfile, samp_outfile, site_outfile, loc_outfile, dmg, ncn, particulars, spc, replicate, ID, loc_name, lat, lon)\n\n program_ran, error_message = convert.pmd(**options)\n if not program_ran:\n pw.simple_warning(error_message)\n return False\n elif files.index(f) == len(files) -1:\n pw.close_window(self, COMMAND, outfile)\n else:\n print(\"Just ran equivalent of Python command: \", COMMAND)\n\n\n def on_helpButton(self, event):\n # to run as module:\n pw.on_helpButton(text=convert.pmd.__doc__)\n\n\nclass convert_JR6_files_to_MagIC(wx.Frame):\n\n \"\"\" \"\"\"\n title = \"PmagPy JR6 file conversion\"\n\n def __init__(self, parent, WD):\n wx.Frame.__init__(self, parent, wx.ID_ANY, self.title)\n self.panel = wx.ScrolledWindow(self)\n self.WD = WD\n self.InitUI()\n\n def InitUI(self):\n\n pnl = self.panel\n TEXT = \"JR6 format file (currently .txt format only)\"\n bSizer_info = wx.BoxSizer(wx.HORIZONTAL)\n bSizer_info.Add(wx.StaticText(pnl, label=TEXT), wx.ALIGN_LEFT)\n\n #---sizer 0a ----\n TEXT = \"JR6 file Type\"\n label1 = \".txt format\"\n label2 = \".jr6 format\"\n self.bSizer0a = pw.labeled_yes_or_no(pnl, TEXT, label1, label2)\n\n #---sizer 0b ---\n self.bSizer0b = pw.check_box(pnl, 'Joides Resolution')\n self.Bind(wx.EVT_CHECKBOX, self.on_check_joides, self.bSizer0b.cb)\n\n #---sizer 0 ----\n self.bSizer0 = pw.choose_file(pnl, btn_text='add measurement file', method = self.on_add_file_button)\n\n #---sizer 1b ----\n TEXT=\"User (Optional):\"\n self.bSizer1b = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 1c ----\n TEXT=\"Expedition (i.e. 312)\"\n self.bSizer1c = pw.labeled_text_field(pnl, TEXT)\n self.bSizer1c.ShowItems(False)\n\n #---sizer 1d ----\n TEXT=\"Hole name (i.e. U1456A)\"\n self.bSizer1d = pw.labeled_text_field(pnl, TEXT)\n self.bSizer1d.ShowItems(False)\n\n #---sizer 1 ----\n self.bSizer1 = pw.sampling_particulars(pnl)\n\n #---sizer 1a ---\n self.bSizer1a = pw.labeled_text_field(pnl, 'Specimen volume, default is 12 cc.\\nPlease provide volume in cc.')\n\n #---sizer 2 ---\n self.bSizer2 = pw.specimen_n(pnl)\n\n #---sizer 3 ----\n ncn_keys = ['XXXXY', 'XXXX-YY', 'XXXX.YY', 'XXXX[YYY] where YYY is sample designation, enter number of Y', 'sample name=site name']\n self.bSizer3 = pw.select_ncn(pnl, ncn_keys)\n\n #---sizer 4 ----\n TEXT=\"Location name:\"\n self.bSizer4 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 6 ----\n self.bSizer6 = pw.site_lat_lon(pnl)\n\n #---sizer 5 ----\n self.bSizer5 = pw.replicate_measurements(pnl)\n\n #---buttons ---\n hboxok = pw.btn_panel(self, pnl)\n\n #------\n vbox=wx.BoxSizer(wx.VERTICAL)\n hbox0 = wx.BoxSizer(wx.HORIZONTAL)\n hbox0.AddMany([(self.bSizer0a,wx.ALIGN_LEFT|wx.TOP), (self.bSizer0b,wx.ALIGN_LEFT|wx.TOP)])\n\n vbox.AddSpacer(10)\n vbox.Add(bSizer_info, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(hbox0, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer0, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer1d, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer1c, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer1b, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer1, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer1a, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer2, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer3, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer4, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer6, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer5, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.AddSpacer(10)\n vbox.Add(wx.StaticLine(pnl), 0, wx.ALL|wx.EXPAND, 5)\n vbox.Add(hboxok, flag=wx.ALIGN_CENTER)\n vbox.AddSpacer(20)\n\n hbox_all= wx.BoxSizer(wx.HORIZONTAL)\n hbox_all.AddSpacer(20)\n hbox_all.Add(vbox)\n hbox_all.AddSpacer(20)\n\n self.panel.SetSizer(hbox_all)\n self.panel.SetScrollbars(20, 20, 50, 50)\n hbox_all.Fit(self)\n self.Centre()\n self.Show()\n\n def on_check_joides(self, event):\n if self.bSizer0b.cb.IsChecked():\n self.bSizer0a.ShowItems(False)\n self.bSizer1.ShowItems(False)\n self.bSizer1a.ShowItems(False)\n self.bSizer2.ShowItems(False)\n self.bSizer3.ShowItems(False)\n self.bSizer4.ShowItems(False)\n self.bSizer1b.ShowItems(True)\n self.bSizer1c.ShowItems(True)\n self.bSizer1d.ShowItems(True)\n else:\n self.bSizer1b.ShowItems(False)\n self.bSizer1c.ShowItems(False)\n self.bSizer1d.ShowItems(False)\n self.bSizer0a.ShowItems(True)\n self.bSizer1.ShowItems(True)\n self.bSizer1a.ShowItems(True)\n self.bSizer2.ShowItems(True)\n self.bSizer3.ShowItems(True)\n self.bSizer4.ShowItems(True)\n self.panel.Layout()\n\n def on_add_file_button(self,event):\n text = \"choose file to convert to MagIC\"\n pw.on_add_file_button(self.bSizer0, text)\n\n def on_add_sampfile_button(self, event):\n text = \"choose samples type file\"\n pw.on_add_file_button(self.bSizer0c, text)\n\n def on_okButton(self, event):\n samp_file = ''\n options = {}\n input_format = self.bSizer0a.return_value()\n JR = self.bSizer0b.return_value()\n if input_format:\n input_format = 'txt'\n else:\n input_format = 'jr6'\n output_dir_path = self.WD\n options['dir_path'] = str(output_dir_path)\n input_dir_path, mag_file = os.path.split(self.bSizer0.return_value())\n if not mag_file:\n pw.simple_warning(\"You must select a JR6 format file\")\n return False\n options['input_dir_path'], options['mag_file'] = str(input_dir_path), str(mag_file)\n meas_file = os.path.split(mag_file)[1]+\".magic\"\n options['meas_file'] = str(meas_file)\n spec_file = os.path.split(mag_file)[1]+\"_specimens.txt\"\n options['spec_file'] = str(spec_file)\n samp_file = os.path.split(mag_file)[1]+\"_samples.txt\"\n options['samp_file'] = str(samp_file)\n site_file = os.path.split(mag_file)[1]+\"_sites.txt\"\n options['site_file'] = str(site_file)\n loc_file = os.path.split(mag_file)[1]+\"_locations.txt\"\n options['loc_file'] = str(loc_file)\n specnum = self.bSizer2.return_value()\n options['specnum'] = specnum\n samp_con = self.bSizer3.return_value()\n options['samp_con'] = samp_con\n user = self.bSizer1b.return_value()\n options['user'] = str(user)\n location = self.bSizer4.return_value()\n if location!='':\n options['location'] = str(location)\n expedition = self.bSizer1c.return_value()\n options['expedition'] = str(expedition)\n site = self.bSizer1d.return_value()\n options['site'] = str(site)\n average = self.bSizer5.return_value()\n if average:\n noave = 0\n else:\n noave = 1\n options['noave'] = noave\n meth_code = self.bSizer1.return_value()\n options['meth_code'] = meth_code\n try: lat,lon = self.bSizer6.return_value().split()\n except ValueError: lat,lon = '',''\n options['lat'] = lat\n options['lon'] = lon\n lat,lon = '-lat '+str(lat), '-lon '+str(lon)\n volume = self.bSizer1a.return_value()\n os.chdir(self.WD)\n COMMAND = \"\"\n\n # validate arguments;\n if volume!='':\n try:\n volume = float(volume)\n options['volume'] = volume\n except:\n pw.simple_warning(\"You must provide a valid quanity for volume, or no volume\")\n return False\n\n # validate file type and run jr6_magic:\n if not JR:\n if 'jr6' in input_format and 'jr6' not in mag_file.lower():\n pw.simple_warning(\"You must provide a .jr6 format file\")\n return False\n elif 'txt' in input_format and 'txt' not in mag_file.lower():\n pw.simple_warning(\"You must provide a .txt format file\")\n return False\n # remove unneeded options for jr6_txt/jr6_jr6\n for key in ['expedition', 'site']:\n try:\n options.pop(key)\n except KeyError:\n pass\n if input_format == 'txt': # .txt format\n program_ran, error_message = convert.jr6_txt(**options)\n if program_ran:\n COMMAND = \"options={}\\nconvert.jr6_txt(**options)\".format(str(options))\n pw.close_window(self, COMMAND, meas_file)\n else:\n pw.simple_warning(error_message)\n else:\n program_ran, error_message = convert.jr6_jr6(**options)\n if program_ran:\n COMMAND = \"options={}\\nconvert.jr6_jr6(**options)\".format(str(options))\n pw.close_window(self, COMMAND, meas_file)\n else:\n pw.simple_warning(error_message)\n else: # Joides Resolution\n if not mag_file:\n pw.simple_warning('You must provide a valid IODP JR6 file')\n program_ran, error_message = convert.iodp_jr6(**options)\n if program_ran:\n COMMAND = \"options={}\\nconvert.iodp_jr6(**options)\".format(str(options))\n pw.close_window(self, COMMAND, meas_file)\n else:\n pw.simple_warning(error_message)\n\n\n def on_cancelButton(self,event):\n self.Destroy()\n self.Parent.Raise()\n\n def on_helpButton(self, event):\n input_format = self.bSizer0a.return_value()\n if input_format:\n input_format = 'txt'\n else:\n input_format = 'jr6'\n if input_format == 'txt': # .txt format\n pw.on_helpButton(text=jr6_txt_magic.do_help())\n else:\n pw.on_helpButton(text=jr6_jr6_magic.do_help())\n\n\nclass convert_BGC_files_to_magic(wx.Frame):\n\n \"\"\" \"\"\"\n title = \"PmagPy BGC file conversion\"\n\n def __init__(self, parent, WD, title):\n wx.Frame.__init__(self, parent, wx.ID_ANY, self.title)\n self.panel = wx.ScrolledWindow(self)\n self.WD = WD\n self.InitUI()\n\n def InitUI(self):\n\n pnl = self.panel\n\n text = \"convert Berkeley Geochronology Center file to MagIC format\"\n bSizer_info = wx.BoxSizer(wx.HORIZONTAL)\n bSizer_info.Add(wx.StaticText(pnl, label=text), wx.ALIGN_LEFT)\n\n #---sizer 0 ----\n self.bSizer0 = pw.choose_file(pnl, 'add', method = self.on_add_file_button)\n\n #---sizer 1a ----\n self.bSizer1a = pw.labeled_text_field(pnl, 'User (Optional):')\n\n #---sizer 1 ----\n self.bSizer1 = pw.labeled_text_field(pnl, 'Location name:')\n\n #---sizer 2 ----\n self.bSizer2 = pw.labeled_text_field(pnl, 'Site name (if using convention bellow leave blank):')\n # sitename\n\n #---sizer 3 ----\n self.bSizer3 = pw.sampling_particulars(pnl)\n # meth codes\n\n #---sizer 4 ----\n self.bSizer4 = pw.replicate_measurements(pnl)\n # average replicates\n\n #---sizer 5 ---\n self.bSizer5 = pw.labeled_text_field(pnl, 'Provide specimen volume in cubic centimeters\\nNote: the volume given in data file will be used unless it equals 0.0 ')\n\n #---sizer 6 ----\n self.bSizer6 = pw.select_ncn(pnl)\n\n #---sizer 7 ----\n TEXT = \"specify number of characters to designate a specimen, default = 0\"\n self.bSizer7 = pw.specimen_n(pnl)\n\n\n #---buttons ---\n hboxok = pw.btn_panel(self, pnl)\n\n\n #------\n vbox=wx.BoxSizer(wx.VERTICAL)\n\n vbox.AddSpacer(10)\n vbox.Add(bSizer_info, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer0, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer1a, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer3, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer2, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer6, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer7, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer1, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer4, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer5, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n #vbox.AddSpacer(10)\n #vbox.Add(wx.StaticLine(pnl), 0, wx.ALL|wx.EXPAND, 5)\n vbox.Add(hboxok, flag=wx.ALIGN_CENTER)\n vbox.AddSpacer(20)\n\n hbox_all= wx.BoxSizer(wx.HORIZONTAL)\n hbox_all.AddSpacer(20)\n hbox_all.Add(vbox)\n hbox_all.AddSpacer(20)\n\n self.panel.SetSizer(hbox_all)\n self.panel.SetScrollbars(20, 20, 50, 50)\n hbox_all.Fit(self)\n self.Centre()\n self.Show()\n\n\n def on_add_file_button(self,event):\n text = \"choose file to convert to MagIC\"\n pw.on_add_file_button(self.bSizer0, text)\n\n def on_okButton(self, event):\n os.chdir(self.WD)\n\n options = {}\n full_file = self.bSizer0.return_value()\n\n ID, infile = os.path.split(full_file)\n options['dir_path'] = self.WD\n options['input_dir_path'] = ID\n options['mag_file'] = infile\n outfile = infile + \".magic\"\n options['meas_file'] = outfile\n spec_outfile = infile + \"_specimens.txt\"\n options['spec_file'] = spec_outfile\n samp_outfile = infile + \"_samples.txt\"\n options['samp_file'] = samp_outfile\n site_outfile = infile + \"_sites.txt\"\n options['site_file'] = site_outfile\n loc_outfile = infile + \"_locations.txt\"\n options['loc_file'] = loc_outfile\n\n user = str(self.bSizer1a.return_value())\n options['user'] = str(user)\n loc_name = str(self.bSizer1.return_value())\n options['location'] = str(loc_name)\n site_name = self.bSizer2.return_value()\n if site_name!='': options['site'] = str(site_name)\n spec_num = self.bSizer7.return_value()\n options['specnum'] = spec_num\n if spec_num:\n spec_num = \"-spc \" + str(spec_num)\n else:\n spec_num = \"-spc 0\" # defaults to 0 if user doesn't choose number\n ncn = self.bSizer6.return_value()\n options['samp_con'] = ncn\n\n meth_code = self.bSizer3.return_value()\n options['meth_code'] = meth_code\n\n average = self.bSizer4.return_value()\n options['noave'] = average\n\n volume = self.bSizer5.return_value()\n if volume:\n try:\n options['volume'] = float(volume)\n except ValueError:\n pw.simple_warning('You must provide a valid numerical value for specimen volume')\n return False\n\n for key, value in list(options.items()):\n print(key, value)\n\n COMMAND = \"options = {}\\convert.bgc(**options)\".format(str(options))\n\n if infile=='':\n all_files=[f for f in os.listdir('.') if os.path.isfile(f)]\n outfiles=[]\n for infile in all_files:\n options['mag_file'] = infile\n outfile = infile + \".magic\"\n options['meas_file'] = outfile\n spec_outfile = infile + \"_specimens.txt\"\n options['spec_file'] = spec_outfile\n samp_outfile = infile + \"_samples.txt\"\n options['samp_file'] = samp_outfile\n site_outfile = infile + \"_sites.txt\"\n options['site_file'] = site_outfile\n loc_outfile = infile + \"_locations.txt\"\n options['loc_file'] = loc_outfile\n try:\n program_ran, error_message = convert.bgc(**options)\n except IndexError:\n continue\n if program_ran:\n outfiles.append(outfile)\n outfile = str(outfiles)\n else:\n program_ran, error_message = convert.bgc(**options)\n\n if program_ran:\n pw.close_window(self, COMMAND, outfile)\n else:\n pw.simple_warning(error_message)\n\n def on_cancelButton(self,event):\n self.Destroy()\n self.Parent.Raise()\n\n def on_helpButton(self, event):\n pw.on_helpButton(text=convert.bgc.__doc__)\n\nclass convert_Utrecht_files_to_MagIC(convert_files_to_MagIC):\n \"\"\"\n A GUI which allows easy input of meta data required to convert Utrecht\n Magnetometer files into MagIC format for analysis or contribution to the\n EarthRef MagIC Archive.\n \"\"\"\n\n def InitUI(self):\n \"\"\"\n Override of InitUI in parent class convert_files_to_MagIC.\n Creates UI for input of relavent data to convert Utrecht to MagIC.\n \"\"\"\n\n pnl = self.panel\n\n TEXT = \"Convert Utrecht Magnetometer file format\"\n bSizer_info = wx.BoxSizer(wx.HORIZONTAL)\n bSizer_info.Add(wx.StaticText(pnl, label=TEXT), wx.ALIGN_LEFT)\n\n #---sizer 0 ----\n self.bSizer0 = pw.choose_file(pnl, 'add', method = self.on_add_file_button)\n\n #---sizer 1 ----\n self.bSizer1 = pw.sampling_particulars(pnl)\n\n #---sizer 2 ----\n self.bSizer2 = pw.select_ncn(pnl)\n\n #---sizer 3 ----\n TEXT = \"specify number of characters to designate a specimen, default = 0\"\n self.bSizer3 = pw.specimen_n(pnl)\n\n #---sizer 4 ----\n TEXT=\"Location name:\"\n self.bSizer4 = pw.labeled_text_field(pnl, TEXT)\n\n #---sizer 5 ---\n self.bSizer5 = pw.replicate_measurements(pnl)\n\n #---sizer 6 ----\n self.bSizer6 = pw.lab_field(pnl)\n\n #---sizer 7 ---\n TEXT= \"use the European date format (dd/mm/yyyy)\"\n self.bSizer7 = pw.check_box(pnl, TEXT)\n\n #---sizer 8 ---\n self.bSizer8 = pw.site_lat_lon(pnl)\n\n\n #---buttons ---\n hboxok = pw.btn_panel(self, pnl)\n\n #------\n vbox=wx.BoxSizer(wx.VERTICAL)\n\n vbox.AddSpacer(10)\n vbox.Add(bSizer_info, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer0, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer1, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer6, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer2, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer3, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer4, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer8, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer7, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer5, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.AddSpacer(10)\n vbox.Add(wx.StaticLine(pnl), 0, wx.ALL|wx.EXPAND, 5)\n vbox.Add(hboxok, flag=wx.ALIGN_CENTER)\n vbox.AddSpacer(20)\n\n hbox_all= wx.BoxSizer(wx.HORIZONTAL)\n hbox_all.AddSpacer(20)\n hbox_all.Add(vbox)\n hbox_all.AddSpacer(20)\n\n self.panel.SetSizer(hbox_all)\n self.panel.SetScrollbars(20, 20, 50, 50)\n hbox_all.Fit(self)\n self.Centre()\n self.Show()\n\n def on_okButton(self, event):\n \"\"\"\n Complies information input in GUI into a kwargs dictionary which can\n be passed into the utrecht_magic script and run to output magic files\n \"\"\"\n os.chdir(self.WD)\n options_dict = {}\n wd = self.WD\n options_dict['dir_path'] = wd\n full_file = self.bSizer0.return_value()\n if not full_file:\n pw.simple_warning('You must provide a Utrecht format file')\n return False\n input_directory, Utrecht_file = os.path.split(full_file)\n options_dict['mag_file'] = Utrecht_file\n options_dict['input_dir_path'] = input_directory\n if input_directory:\n ID = \"-ID \" + input_directory\n else:\n ID = ''\n outfile = Utrecht_file + \".magic\"\n options_dict['meas_file'] = outfile\n spec_outfile = Utrecht_file[:Utrecht_file.find('.')] + \"_specimens.txt\"\n options_dict['spec_file'] = spec_outfile\n samp_outfile = Utrecht_file[:Utrecht_file.find('.')] + \"_samples.txt\"\n options_dict['samp_file'] = samp_outfile\n site_outfile = Utrecht_file[:Utrecht_file.find('.')] + \"_sites.txt\"\n options_dict['site_file'] = site_outfile\n loc_outfile = Utrecht_file[:Utrecht_file.find('.')] + \"_locations.txt\"\n options_dict['loc_file'] = loc_outfile\n dc_flag,dc_params = '',''\n if self.bSizer6.return_value() != '':\n dc_params = list(map(float,self.bSizer6.return_value().split()))\n options_dict['lab_field'] = dc_params[0]\n options_dict['phi'] = dc_params[1]\n options_dict['theta'] = dc_params[2]\n dc_flag = '-dc ' + self.bSizer6.return_value()\n spec_num = self.bSizer3.return_value()\n options_dict['specnum'] = spec_num\n if spec_num:\n spec_num = \"-spc \" + str(spec_num)\n else:\n spec_num = \"-spc 0\" # defaults to 0 if user doesn't choose number\n loc_name = self.bSizer4.return_value()\n options_dict['location'] = loc_name\n if loc_name:\n loc_name = \"-loc \" + loc_name\n ncn = self.bSizer2.return_value()\n options_dict['samp_con'] = ncn\n particulars = self.bSizer1.return_value()\n options_dict['meth_code'] = particulars\n if particulars:\n particulars = \"-mcd \" + particulars\n euro_date = self.bSizer7.return_value()\n if euro_date: options_dict['dmy_flag'] = True; dmy_flag='-dmy'\n else: options_dict['dmy_flag'] = False; dmy_flag=''\n try: lat,lon = self.bSizer8.return_value().split()\n except ValueError: lat,lon = '',''\n options_dict['lat'] = lat\n options_dict['lon'] = lon\n replicate = self.bSizer5.return_value()\n if replicate:\n options_dict['noave'] = True\n replicate = ''\n else:\n options_dict['noave'] = False\n replicate = '-A'\n\n COMMAND = \"utrecht_magic.py -WD {} -f {} -F {} {} {} {} -ncn {} {} -Fsp {} -Fsa {} -Fsi {} -Flo {} {} {} {} -lat {} -lon {}\".format(wd, Utrecht_file, outfile, particulars, spec_num, loc_name, ncn, ID, spec_outfile, samp_outfile, site_outfile, loc_outfile, replicate, dc_flag, dmy_flag, lon, lat)\n # to run as module:\n program_ran, error_message = convert.utrecht(**options_dict)\n if program_ran:\n pw.close_window(self, COMMAND, outfile)\n else:\n pw.simple_warning(error_message)\n\n def on_helpButton(self, event):\n \"\"\"\n Displays utrecht_magic scripts help message\n \"\"\"\n pw.on_helpButton(text=convert.utrecht.__doc__)\n\n\n# template for an import window\nclass something(wx.Frame):\n\n \"\"\" \"\"\"\n def InitUI(self):\n\n pnl = self.panel\n\n text = \"Hello here is a bunch of text\"\n bSizer_info = wx.BoxSizer(wx.HORIZONTAL)\n bSizer_info.Add(wx.StaticText(pnl, label=text), wx.ALIGN_LEFT)\n\n #---sizer 0 ----\n self.bSizer0 = pw.choose_file(pnl, 'add', method = self.on_add_file_button)\n\n #---sizer 1 ----\n\n #---sizer 2 ----\n\n #---sizer 3 ----\n\n #---sizer 4 ----\n\n #---sizer 5 ---\n\n #---sizer 6 ----\n\n #---sizer 7 ---\n\n\n #---buttons ---\n hboxok = pw.btn_panel(self, pnl)\n\n\n #------\n vbox=wx.BoxSizer(wx.VERTICAL)\n\n vbox.AddSpacer(10)\n vbox.Add(bSizer_info, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n vbox.Add(self.bSizer0, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n #vbox.Add(self.bSizer1, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n #vbox.Add(self.bSizer2, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n #vbox.Add(self.bSizer3, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n #vbox.Add(self.bSizer4, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n #vbox.Add(self.bSizer5, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n #vbox.Add(self.bSizer6, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n #vbox.Add(self.bSizer7, flag=wx.ALIGN_LEFT|wx.TOP, border=10)\n #vbox.AddSpacer(10)\n #vbox.Add(wx.StaticLine(pnl), 0, wx.ALL|wx.EXPAND, 5)\n vbox.Add(hboxok, flag=wx.ALIGN_CENTER)\n vbox.AddSpacer(20)\n\n hbox_all= wx.BoxSizer(wx.HORIZONTAL)\n hbox_all.AddSpacer(20)\n hbox_all.Add(vbox)\n hbox_all.AddSpacer(20)\n\n self.panel.SetSizer(hbox_all)\n self.panel.SetScrollbars(20, 20, 50, 50)\n hbox_all.Fit(self)\n self.Centre()\n self.Show()\n\n def on_add_file_button(self,event):\n text = \"choose file to convert to MagIC\"\n pw.on_add_file_button(self.bSizer0, self.WD, event, text)\n\n def on_okButton(self, event):\n os.chdir(self.WD)\n COMMAND = \"\"\n pw.run_command_and_close_window(self, COMMAND, outfile)\n\n def on_helpButton(self, event):\n pw.on_helpButton(text='')\n\n\n#=================================================================\n# demag_orient:\n# read/write demag_orient.txt\n# calculate sample orientation\n#=================================================================\n\n\nclass OrientFrameGrid3(wx.Frame):\n def __init__(self, parent, id, title, WD, contribution, size):\n wx.Frame.__init__(self, parent, -1, title, size=size,\n name='calculate geographic directions')\n\n #--------------------\n # initialize stuff\n #--------------------\n self.parent = parent\n if sys.platform in ['win32', 'win64']:\n self.panel = wx.ScrolledWindow(self, style=wx.SIMPLE_BORDER|wx.ALWAYS_SHOW_SB)\n else:\n self.panel = wx.Panel(self, style=wx.SIMPLE_BORDER)\n\n self.WD = WD\n #self.Data_hierarchy = Data_hierarchy\n self.contribution = contribution\n\n # contribution has already propagated measurement data...\n if 'samples' not in self.contribution.tables:\n print('-E- No sample data available')\n samples_name_list = []\n else:\n samples_name_list = self.contribution.tables['samples'].df.index.unique()\n\n self.orient_data = {}\n try:\n fname = os.path.join(self.WD, \"demag_orient.txt\")\n self.orient_data, dtype, keys = pmag.magic_read_dict(fname, sort_by_this_name=\"sample_name\",\n return_keys=True)\n\n except Exception as ex:\n print(\"-W-\", ex)\n\n # re-do the 'quit' binding so that it only closes the current window\n self.parent.Bind(wx.EVT_MENU, lambda event: self.parent.menubar.on_quit(event, self), self.parent.menubar.file_quit)\n\n # self.headers is a list of two-item tuples.\n #the first is the proper column name as understood by orientation_magic.py\n # the second is the name for display in the GUI\n self.header_display_names = [\"sample_name\", \"sample_orientation_flag\", \"mag_azimuth\",\n \"field_dip\", \"bedding_dip_direction\", \"bedding_dip\",\n \"shadow_angle\", \"latitude\", \"longitude\", \"mm/dd/yy\",\n \"hh:mm\", \"GPS_baseline\", \"GPS_Az\"]\n self.header_names = [\"sample_name\", \"sample_orientation_flag\", \"mag_azimuth\",\n \"field_dip\", \"bedding_dip_direction\", \"bedding_dip\",\n \"shadow_angle\", \"lat\", \"long\", \"date\",\n \"hhmm\", \"GPS_baseline\", \"GPS_Az\"]\n self.headers = list(zip(self.header_names, self.header_display_names))\n\n # get sample table and convert relevant headers to orient.txt format\n if (not self.orient_data) and ('samples' in self.contribution.tables):\n print(\"-I- Couldn't find demag_orient.txt, trying to extract information from samples table\")\n samp_container = self.contribution.tables['samples']\n # get lat/lon from sites if available\n if 'sites' in self.contribution.tables:\n site_contianer = self.contribution.tables['sites']\n self.contribution.propagate_cols(['lat', 'lon'], 'samples', 'sites')\n #\n raw_orient_data = samp_container.convert_to_pmag_data_list(\"dict\")\n # convert from 3.0. headers to orient.txt headers\n self.orient_data = {}\n orient_data = {}\n # must group to ensure that lat/lon/etc. are found no matter what\n df = samp_container.df\n res = df.T.apply(dict).groupby(df.index)\n for grouped in res:\n new_dict = {}\n ind_name = grouped[0]\n dictionaries = grouped[1]\n for dictionary in dictionaries:\n for key, value in dictionary.items():\n if key in new_dict:\n continue\n if (value and (value != 'None')) or (value == 0):\n new_dict[key] = value\n for key in dictionary.keys():\n if key not in new_dict:\n new_dict[key] = None\n orient_data[ind_name] = new_dict\n for key, rec in list(orient_data.items()):\n self.orient_data[key] = map_magic.mapping(rec, map_magic.magic3_2_orient_magic_map)\n # create grid\n self.create_sheet()\n\n TEXT = \"\"\"A template file named 'demag_orient.txt', for sample-level orientation data, was created in your MagIC working directory.\n\n You can view/modify demag_orient.txt here. To edit all the values in a column, click on the column header and then enter your desired value, or select an item from the drop-down menu.\n\n If you already have these data in MagIC format in Excel or Open Office, save the file as 'tab delimited' and then use the 'Import Orientation File' button below.\n\n After orientation data is filled in, you can Calculate sample orientations. Method codes will be added during this step. This will write orientation data to the site and sample tables.\n\"\"\"\n label_boxsizer = wx.StaticBoxSizer( wx.StaticBox( self.panel, wx.ID_ANY, 'input orientation data ' ), wx.VERTICAL )\n # width, height\n label = wx.StaticText(self.panel, label=TEXT, size=(600, 200))\n btn_box = wx.BoxSizer(wx.HORIZONTAL)\n save_btn = wx.Button(self.panel, wx.ID_ANY, \"Save Orientation File\")\n self.Bind(wx.EVT_BUTTON, self.on_m_save_file, save_btn)\n import_btn = wx.Button(self.panel, wx.ID_ANY, \"Import Orientation File\")\n self.Bind(wx.EVT_BUTTON, self.on_m_open_file, import_btn)\n calculate_btn = wx.Button(self.panel, wx.ID_ANY, \"Calculate Sample Orientations\")\n self.Bind(wx.EVT_BUTTON, self.on_m_calc_orient, calculate_btn)\n btn_box.Add(save_btn)\n btn_box.Add(import_btn, flag=wx.LEFT, border=5)\n btn_box.Add(calculate_btn, flag=wx.LEFT, border=5)\n\n self.vbox = wx.BoxSizer(wx.VERTICAL)\n #\n label_boxsizer.Add(label, flag=wx.CENTRE)\n self.vbox.Add(label_boxsizer, flag=wx.CENTRE|wx.ALL, border=15)\n #self.vbox.Add(label, flag=wx.CENTRE|wx.ALL, border=15)\n self.vbox.Add(btn_box, flag=wx.CENTRE)\n self.vbox.Add(self.grid, flag=wx.ALL, border=20)\n self.hbox_all = wx.BoxSizer(wx.HORIZONTAL)\n self.hbox_all.Add(self.vbox)\n if sys.platform in ['win32', 'win64']:\n self.panel.SetScrollbars(20, 20, 50, 50)\n self.panel.SetSizer(self.hbox_all)\n self.hbox_all.Fit(self)\n\n self.Bind(wx.EVT_CLOSE, self.OnCloseWindow)\n # save the template\n self.on_m_save_file(None)\n self.Centre()\n self.Show()\n\n\n\n def create_sheet(self):\n '''\n create an editable grid showing demag_orient.txt\n '''\n #--------------------------------\n # orient.txt supports many other headers\n # but we will only initialize with\n # the essential headers for\n # sample orientation and headers present\n # in existing demag_orient.txt file\n #--------------------------------\n\n\n #--------------------------------\n # create the grid\n #--------------------------------\n\n samples_list = list(self.orient_data.keys())\n samples_list.sort()\n self.samples_list = [ sample for sample in samples_list if sample is not \"\" ]\n #self.headers.extend(self.add_extra_headers(samples_list))\n display_headers = [header[1] for header in self.headers]\n self.grid = magic_grid.MagicGrid(self.panel, 'orient grid',\n self.samples_list, display_headers)\n self.grid.InitUI()\n\n #--------------------------------\n # color the columns by groups\n #--------------------------------\n\n for i in range(len(self.samples_list)):\n self.grid.SetCellBackgroundColour(i, 0, \"LIGHT GREY\")\n self.grid.SetCellBackgroundColour(i, 1, \"LIGHT STEEL BLUE\")\n self.grid.SetCellBackgroundColour(i, 2, \"YELLOW\")\n self.grid.SetCellBackgroundColour(i, 3, \"YELLOW\")\n self.grid.SetCellBackgroundColour(i, 4, \"PALE GREEN\")\n self.grid.SetCellBackgroundColour(i, 5, \"PALE GREEN\")\n self.grid.SetCellBackgroundColour(i, 6, \"KHAKI\")\n self.grid.SetCellBackgroundColour(i, 7, \"KHAKI\")\n self.grid.SetCellBackgroundColour(i, 8, \"KHAKI\")\n self.grid.SetCellBackgroundColour(i, 9, \"KHAKI\")\n self.grid.SetCellBackgroundColour(i, 10, \"KHAKI\")\n self.grid.SetCellBackgroundColour(i, 11, \"LIGHT MAGENTA\")\n self.grid.SetCellBackgroundColour(i, 12, \"LIGHT MAGENTA\")\n\n\n #--------------------------------\n # fill data from self.orient_data\n #--------------------------------\n\n headers = [header[0] for header in self.headers]\n for sample in self.samples_list:\n for key in list(self.orient_data[sample].keys()):\n if key in headers:\n sample_index = self.samples_list.index(sample)\n i = headers.index(key)\n val = str(self.orient_data[sample][key])\n # if it's a pmag_object, use its name\n try:\n val = val.name\n except AttributeError:\n pass\n if val and val != \"None\":\n self.grid.SetCellValue(sample_index, i, val)\n\n #--------------------------------\n\n #--------------------------------\n # fill in some default values\n #--------------------------------\n for row in range(self.grid.GetNumberRows()):\n col = 1\n if not self.grid.GetCellValue(row, col):\n self.grid.SetCellValue(row, col, 'g')\n\n #--------------------------------\n\n # temporary trick to get drop-down-menus to work\n self.grid.changes = {'a'}\n\n self.grid.AutoSize()\n self.drop_down_menu = drop_down_menus3.Menus(\"orient\", self.contribution, self.grid)\n self.Bind(wx.grid.EVT_GRID_LABEL_LEFT_CLICK, self.onLeftClickLabel, self.grid)\n\n def update_sheet(self):\n self.grid.Destroy()\n self.create_sheet()\n self.vbox.Add(self.grid, flag=wx.ALL, border=20)\n #self.Hide()\n #self.Show()\n self.hbox_all.Fit(self.panel)\n #self.panel.Refresh()\n self.Hide()\n self.Show()\n\n def onLeftClickLabel(self, event):\n \"\"\"\n When user clicks on a grid label, determine if it is a row label or a col label.\n Pass along the event to the appropriate function.\n (It will either highlight a column for editing all values, or highlight a row for deletion).\n \"\"\"\n #if event.Col == -1 and event.Row == -1:\n # pass\n #elif event.Col < 0:\n # self.onSelectRow(event)\n if event.Row < 0:\n self.drop_down_menu.on_label_click(event)\n\n\n def on_m_open_file(self,event):\n '''\n open orient.txt\n read the data\n display the data from the file in a new grid\n '''\n dlg = wx.FileDialog(\n self, message=\"choose orient file\",\n defaultDir=self.WD,\n defaultFile=\"\",\n style=wx.FD_OPEN | wx.FD_CHANGE_DIR\n )\n if dlg.ShowModal() == wx.ID_OK:\n orient_file = dlg.GetPath()\n dlg.Destroy()\n new_data, dtype, keys = pmag.magic_read_dict(orient_file,\n sort_by_this_name=\"sample_name\",\n return_keys=True)\n\n if len(new_data) > 0:\n self.orient_data={}\n self.orient_data=new_data\n #self.create_sheet()\n self.update_sheet()\n print(\"-I- If you don't see a change in the spreadsheet, you may need to manually re-size the window\")\n\n def on_m_save_file(self,event):\n\n '''\n save demag_orient.txt\n (only the columns that appear on the grid frame)\n '''\n fout = open(os.path.join(self.WD, \"demag_orient.txt\"), 'w')\n STR = \"tab\\tdemag_orient\\n\"\n fout.write(STR)\n headers = [header[0] for header in self.headers]\n STR = \"\\t\".join(headers) + \"\\n\"\n fout.write(STR)\n for sample in self.samples_list:\n STR = \"\"\n for header in headers:\n sample_index = self.samples_list.index(sample)\n i = headers.index(header)\n value = self.grid.GetCellValue(sample_index, i)\n STR = STR + value + \"\\t\"\n fout.write(STR[:-1] + \"\\n\")\n fout.close()\n if event != None:\n dlg1 = wx.MessageDialog(None,caption=\"Message:\", message=\"data saved in file demag_orient.txt\" ,style=wx.OK|wx.ICON_INFORMATION)\n dlg1.ShowModal()\n dlg1.Destroy()\n\n\n def on_m_calc_orient(self,event):\n '''\n This fucntion does exactly what the 'import orientation' fuction does in MagIC.py\n after some dialog boxes the function calls orientation_magic.py\n '''\n # first see if demag_orient.txt\n self.on_m_save_file(None)\n orient_convention_dia = orient_convention(None)\n orient_convention_dia.Center()\n #orient_convention_dia.ShowModal()\n if orient_convention_dia.ShowModal() == wx.ID_OK:\n ocn_flag = orient_convention_dia.ocn_flag\n dcn_flag = orient_convention_dia.dcn_flag\n gmt_flags = orient_convention_dia.gmt_flags\n orient_convention_dia.Destroy()\n else:\n return\n\n or_con = orient_convention_dia.ocn\n dec_correction_con = int(orient_convention_dia.dcn)\n try:\n hours_from_gmt = float(orient_convention_dia.gmt)\n except:\n hours_from_gmt = 0\n try:\n dec_correction = float(orient_convention_dia.correct_dec)\n except:\n dec_correction = 0\n\n method_code_dia=method_code_dialog(None)\n method_code_dia.Center()\n if method_code_dia.ShowModal() == wx.ID_OK:\n bedding_codes_flags=method_code_dia.bedding_codes_flags\n methodcodes_flags=method_code_dia.methodcodes_flags\n method_code_dia.Destroy()\n else:\n print(\"-I- Canceling calculation\")\n return\n\n method_codes = method_code_dia.methodcodes\n average_bedding = method_code_dia.average_bedding\n bed_correction = method_code_dia.bed_correction\n\n command_args=['orientation_magic.py']\n command_args.append(\"-WD %s\"%self.WD)\n command_args.append(\"-Fsa er_samples_orient.txt\")\n command_args.append(\"-Fsi er_sites_orient.txt \")\n command_args.append(\"-f %s\"%\"demag_orient.txt\")\n command_args.append(ocn_flag)\n command_args.append(dcn_flag)\n command_args.append(gmt_flags)\n command_args.append(bedding_codes_flags)\n command_args.append(methodcodes_flags)\n commandline = \" \".join(command_args)\n\n print(\"-I- executing command: %s\" %commandline)\n os.chdir(self.WD)\n if os.path.exists(os.path.join(self.WD, 'er_samples.txt')) or os.path.exists(os.path.join(self.WD, 'er_sites.txt')):\n append = True\n elif os.path.exists(os.path.join(self.WD, 'samples.txt')) or os.path.exists(os.path.join(self.WD, 'sites.txt')):\n append = True\n else:\n append = False\n samp_file = \"er_samples.txt\"\n site_file = \"er_sites.txt\"\n success, error_message = ipmag.orientation_magic(or_con, dec_correction_con, dec_correction,\n bed_correction, hours_from_gmt=hours_from_gmt,\n method_codes=method_codes, average_bedding=average_bedding,\n orient_file='demag_orient.txt', samp_file=samp_file,\n site_file=site_file, input_dir_path=self.WD,\n output_dir_path=self.WD, append=append, data_model=3)\n\n if not success:\n dlg1 = wx.MessageDialog(None,caption=\"Message:\", message=\"-E- ERROR: Error in running orientation_magic\\n{}\".format(error_message) ,style=wx.OK|wx.ICON_INFORMATION)\n dlg1.ShowModal()\n dlg1.Destroy()\n\n print(\"-E- ERROR: Error in running orientation_magic\")\n return\n else:\n dlg2 = wx.MessageDialog(None,caption=\"Message:\", message=\"-I- Successfully ran orientation_magic\", style=wx.OK|wx.ICON_INFORMATION)\n dlg2.ShowModal()\n dlg2.Destroy()\n self.Parent.Show()\n self.Parent.Raise()\n self.Destroy()\n self.contribution.add_magic_table('samples')\n return\n\n\n def OnCloseWindow(self,event):\n dlg1 = wx.MessageDialog(self,caption=\"Message:\", message=\"Save changes to demag_orient.txt?\\n \" ,style=wx.OK|wx.CANCEL)\n result = dlg1.ShowModal()\n if result == wx.ID_OK:\n self.on_m_save_file(None)\n dlg1.Destroy()\n self.Parent.Show()\n self.Parent.Raise()\n self.Destroy()\n if result == wx.ID_CANCEL:\n dlg1.Destroy()\n self.Parent.Show()\n self.Parent.Raise()\n self.Destroy()\n\n\nclass orient_convention(wx.Dialog):\n\n def __init__(self, *args, **kw):\n super(orient_convention, self).__init__(*args, **kw)\n\n self.InitUI()\n #self.SetSize((250, 200))\n self.SetTitle(\"set orientation convention\")\n\n def InitUI(self):\n\n pnl = wx.Panel(self)\n vbox=wx.BoxSizer(wx.VERTICAL)\n\n #-----------------------\n # orientation convention\n #-----------------------\n\n sbs = wx.StaticBoxSizer( wx.StaticBox( pnl, wx.ID_ANY, 'orientation convention' ), wx.VERTICAL )\n\n sbs.AddSpacer(5)\n self.oc_rb1 = wx.RadioButton(pnl, -1,label='Pomeroy: Lab arrow azimuth = mag_azimuth; Lab arrow dip=-field_dip (field_dip is hade)',name='1', style=wx.RB_GROUP)\n sbs.Add(self.oc_rb1)\n sbs.AddSpacer(5)\n self.oc_rb2 = wx.RadioButton(pnl, -1, label='Lab arrow azimuth = mag_azimuth-90 (mag_azimuth is strike); Lab arrow dip = -field_dip', name='2')\n sbs.Add(self.oc_rb2)\n sbs.AddSpacer(5)\n self.oc_rb3 = wx.RadioButton(pnl, -1, label='Lab arrow azimuth = mag_azimuth; Lab arrow dip = 90-field_dip (field_dip is inclination of lab arrow)', name='3')\n sbs.Add(self.oc_rb3)\n sbs.AddSpacer(5)\n self.oc_rb4 = wx.RadioButton(pnl, -1, label='Lab arrow azimuth and dip are same as mag_azimuth, field_dip', name='4')\n sbs.Add(self.oc_rb4)\n sbs.AddSpacer(5)\n self.oc_rb5 = wx.RadioButton(pnl, -1, label='ASC: Lab arrow azimuth and dip are mag_azimuth, field_dip-90 (field arrow is inclination of specimen Z direction)',name='5')\n sbs.Add(self.oc_rb5)\n sbs.AddSpacer(5)\n self.oc_rb6 = wx.RadioButton(pnl, -1, label='Lab arrow azimuth = mag_azimuth-90 (mag_azimuth is strike); Lab arrow dip = 90-field_dip', name='6')\n sbs.Add(self.oc_rb6)\n sbs.AddSpacer(5)\n\n #-----------------------\n # declination correction\n #-----------------------\n sbs2 = wx.StaticBoxSizer( wx.StaticBox( pnl, wx.ID_ANY, 'declination correction' ), wx.VERTICAL )\n hbox_dc1 = wx.BoxSizer(wx.HORIZONTAL)\n\n sbs2.AddSpacer(5)\n self.dc_rb1 = wx.RadioButton(pnl, -1, 'Use the IGRF DEC value at the lat/long and date supplied', (10, 50), style=wx.RB_GROUP)\n self.dc_rb2 = wx.RadioButton(pnl, -1, 'Use this DEC:', (10, 50))\n self.dc_tb2 = wx.TextCtrl(pnl,style=wx.CENTER)\n self.dc_rb3 = wx.RadioButton(pnl, -1, 'DEC=0, mag_az is already corrected in file', (10, 50))\n\n sbs2.Add(self.dc_rb1)\n sbs2.AddSpacer(5)\n hbox_dc1.Add(self.dc_rb2)\n hbox_dc1.AddSpacer(5)\n hbox_dc1.Add(self.dc_tb2)\n sbs2.Add(hbox_dc1)\n\n sbs2.AddSpacer(5)\n sbs2.Add(self.dc_rb3)\n sbs2.AddSpacer(5)\n\n\n #-----------------------\n # orienation priority\n #-----------------------\n sbs3 = wx.StaticBoxSizer( wx.StaticBox( pnl, wx.ID_ANY, 'orientation priority' ), wx.VERTICAL )\n\n sbs3.AddSpacer(5)\n self.op_rb1 = wx.RadioButton(pnl, -1, label='1) sun compass 2) differential GPS 3) magnetic compass',\n name='1', style=wx.RB_GROUP)\n sbs3.Add(self.op_rb1)\n sbs3.AddSpacer(5)\n self.op_rb2 = wx.RadioButton(pnl, -1, label='1) differential GPS 2) magnetic compass 3) sun compass ',\n name='2')\n sbs3.Add(self.op_rb2)\n sbs3.AddSpacer(5)\n\n\n #-----------------------\n # add local time for GMT\n #-----------------------\n\n sbs4 = wx.StaticBoxSizer( wx.StaticBox( pnl, wx.ID_ANY, 'add local time' ), wx.HORIZONTAL )\n #hbox_alt = wx.BoxSizer(wx.HORIZONTAL)\n\n sbs4.AddSpacer(5)\n self.dc_alt = wx.TextCtrl(pnl,style=wx.CENTER)\n alt_txt = wx.StaticText(pnl, label=\"Hours to ADD to local time for GMT, default is 0\",\n style=wx.TE_CENTER)\n sbs4.Add(alt_txt)\n sbs4.AddSpacer(5)\n sbs4.Add(self.dc_alt)\n\n #-----------------------\n # OK button\n #-----------------------\n\n hbox2 = wx.BoxSizer(wx.HORIZONTAL)\n self.okButton = wx.Button(pnl, wx.ID_OK, \"&OK\")\n self.Bind(wx.EVT_BUTTON, self.OnOK, self.okButton)\n hbox2.Add(self.okButton)\n self.cancelButton = wx.Button(pnl, wx.ID_CANCEL, \"&Cancel\")\n self.Bind(wx.EVT_BUTTON, self.OnCancel, self.cancelButton)\n hbox2.Add(self.cancelButton)\n\n\n #-----------------------\n # design the frame\n #-----------------------\n\n vbox.AddSpacer(10)\n vbox.Add(sbs)\n vbox.AddSpacer(10)\n vbox.Add(sbs2)\n vbox.AddSpacer(10)\n vbox.Add(sbs3)\n vbox.AddSpacer(10)\n vbox.Add(sbs4)\n vbox.AddSpacer(10)\n vbox.Add(hbox2)\n vbox.AddSpacer(10)\n\n hbox1=wx.BoxSizer(wx.HORIZONTAL)\n hbox1.AddSpacer(10)\n hbox1.Add(vbox)\n hbox1.AddSpacer(10)\n\n pnl.SetSizer(hbox1)\n hbox1.Fit(self)\n\n #-----------------------\n # intialize defalut value\n #-----------------------\n\n self.oc_rb4.SetValue(True)\n self.dc_rb1.SetValue(True)\n self.op_rb1.SetValue(True)\n\n def OnCancel(self, e):\n self.EndModal(wx.ID_CANCEL)\n\n def OnOK(self, e):\n self.ocn = \"\"\n if self.oc_rb1.GetValue() == True:\n self.ocn = \"1\"\n if self.oc_rb2.GetValue() == True:\n self.ocn=\"2\"\n if self.oc_rb3.GetValue() == True:\n self.ocn=\"3\"\n if self.oc_rb4.GetValue() == True:\n self.ocn = \"4\"\n if self.oc_rb5.GetValue() == True:\n self.ocn=\"5\"\n if self.oc_rb6.GetValue() == True:\n self.ocn=\"6\"\n\n self.dcn = \"\"\n self.correct_dec = \"\"\n if self.dc_rb1.GetValue() == True:\n self.dcn = \"1\"\n if self.dc_rb2.GetValue() == True:\n self.dcn=\"2\"\n try:\n self.correct_dec = float(self.dc_tb2.GetValue())\n except:\n dlg1 = wx.MessageDialog(None, caption=\"Error:\", message=\"Add declination\", style=wx.OK|wx.ICON_INFORMATION)\n dlg1.ShowModal()\n dlg1.Destroy()\n\n if self.dc_rb3.GetValue()==True:\n self.dcn = \"3\"\n\n if self.op_rb1.GetValue() == True:\n self.op = \"1\"\n if self.op_rb2.GetValue() == True:\n self.op = \"2\"\n\n if self.dc_alt.GetValue() != \"\":\n try:\n self.gmt = float(self.dc_alt.GetValue())\n gmt_flags = \"-gmt \" + self.dc_alt.GetValue()\n except:\n gmt_flags=\"\"\n else:\n self.gmt = \"\"\n gmt_flags = \"\"\n #-------------\n self.ocn_flag = \"-ocn \"+ self.ocn\n self.dcn_flag = \"-dcn \"+ self.dcn\n self.gmt_flags = gmt_flags\n self.EndModal(wx.ID_OK)\n #self.Close()\n\n\nclass method_code_dialog(wx.Dialog):\n\n def __init__(self, *args, **kw):\n super(method_code_dialog, self).__init__(*args, **kw)\n\n self.InitUI()\n self.SetTitle(\"additional required information\")\n\n def InitUI(self):\n\n pnl = wx.Panel(self)\n vbox=wx.BoxSizer(wx.VERTICAL)\n\n #-----------------------\n # MagIC codes\n #-----------------------\n\n sbs1 = wx.StaticBoxSizer( wx.StaticBox( pnl, wx.ID_ANY, 'MagIC codes' ), wx.VERTICAL )\n self.cb1 = wx.CheckBox(pnl, -1, 'FS-FD: field sampling done with a drill')\n self.cb2 = wx.CheckBox(pnl, -1, 'FS-H: field sampling done with hand sample')\n self.cb3 = wx.CheckBox(pnl, -1, 'FS-LOC-GPS: field location done with GPS')\n self.cb4 = wx.CheckBox(pnl, -1, 'FS-LOC-MAP: field location done with map')\n self.cb5 = wx.CheckBox(pnl, -1, 'SO-POM: a Pomeroy orientation device was used')\n self.cb6 = wx.CheckBox(pnl, -1, 'SO-ASC: an ASC orientation device was used')\n self.cb7 = wx.CheckBox(pnl, -1, 'SO-MAG: magnetic compass used for all orientations')\n self.cb8 = wx.CheckBox(pnl, -1, 'SO-SUN: sun compass used for all orientations')\n self.cb9 = wx.CheckBox(pnl, -1, 'SO-SM: either magnetic or sun used on all orientations ')\n self.cb10 = wx.CheckBox(pnl, -1, 'SO-SIGHT: orientation from sighting')\n\n for cb in [self.cb1, self.cb2, self.cb3, self.cb4, self.cb5,\n self.cb6, self.cb7, self.cb8, self.cb9, self.cb10]:\n sbs1.Add(cb, flag=wx.BOTTOM, border=5)\n\n #-----------------------\n # Bedding convention\n #-----------------------\n\n sbs2 = wx.StaticBoxSizer(wx.StaticBox(pnl, wx.ID_ANY, 'bedding convention'), wx.VERTICAL)\n self.bed_con1 = wx.CheckBox(pnl, -1, 'Take fisher mean of bedding poles?')\n self.bed_con2 = wx.CheckBox(pnl, -1, \"Don't correct bedding dip direction with declination - already correct\")\n\n sbs2.Add(self.bed_con1, flag=wx.BOTTOM, border=5)\n sbs2.Add(self.bed_con2, flag=wx.BOTTOM, border=5)\n\n #-----------------------\n # OK button\n #-----------------------\n\n hbox2 = wx.BoxSizer(wx.HORIZONTAL)\n self.okButton = wx.Button(pnl, wx.ID_OK, \"&OK\")\n self.Bind(wx.EVT_BUTTON, self.OnOK, self.okButton)\n hbox2.Add(self.okButton)\n self.cancelButton = wx.Button(pnl, wx.ID_CANCEL, \"&Cancel\")\n self.Bind(wx.EVT_BUTTON, self.OnCancel, self.cancelButton)\n hbox2.Add(self.cancelButton)\n\n #-----------------------\n # design the frame\n #-----------------------\n vbox.Add(sbs1)\n vbox.AddSpacer(5)\n vbox.Add(sbs2)\n vbox.AddSpacer(5)\n vbox.Add(hbox2)\n vbox.AddSpacer(10)\n\n hbox1=wx.BoxSizer(wx.HORIZONTAL)\n hbox1.AddSpacer(10)\n hbox1.Add(vbox)\n hbox1.AddSpacer(10)\n\n pnl.SetSizer(hbox1)\n hbox1.Fit(self)\n\n def OnCancel(self, e):\n self.EndModal(wx.ID_CANCEL)\n\n def OnOK(self, e):\n methodcodes=[]\n if self.cb1.GetValue() == True:\n methodcodes.append('FS-FD')\n if self.cb2.GetValue() == True:\n methodcodes.append('FS-H')\n if self.cb3.GetValue() == True:\n methodcodes.append('FS-LOC-GPS')\n if self.cb4.GetValue() == True:\n methodcodes.append('FS-LOC-MAP')\n if self.cb5.GetValue() == True:\n methodcodes.append('SO-POM')\n if self.cb6.GetValue() == True:\n methodcodes.append('SO-ASC')\n if self.cb7.GetValue() == True:\n methodcodes.append('SO-MAG')\n if self.cb8.GetValue() == True:\n methodcodes.append('SO-SUN')\n if self.cb9.GetValue() == True:\n methodcodes.append('SO-SM')\n if self.cb10.GetValue() == True:\n methodcodes.append('SO-SIGHT')\n\n if methodcodes == []:\n self.methodcodes_flags=\"\"\n self.methodcodes = \"\"\n else:\n self.methodcodes_flags = \"-mcd \" + \":\".join(methodcodes)\n self.methodcodes = \":\".join(methodcodes)\n\n bedding_codes=[]\n\n if self.bed_con1.GetValue() == True:\n bedding_codes.append(\"-a\")\n self.average_bedding = True\n else:\n self.average_bedding = False\n if self.bed_con2.GetValue() ==True:\n bedding_codes.append(\"-BCN\")\n self.bed_correction = False\n else:\n self.bed_correction = True\n self.bedding_codes_flags = \" \".join(bedding_codes)\n self.EndModal(wx.ID_OK)\n #self.Close()ls *.html\n","sub_path":"dialogs/pmag_gui_dialogs.py","file_name":"pmag_gui_dialogs.py","file_ext":"py","file_size_in_byte":141142,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"85094619","text":"from django.urls import path\n\nfrom . import views\n\nurlpatterns = [\n path('is_logged_in', views.is_logged_in, name='is_logged_in'),\n path('register', views.save_user_token, name='register'),\n path('get_pages', views.get_pages, name='get_pages'),\n path('update_page', views.update_page_info, name='update_page'),\n path('revoke', views.revoke_all_permissions, name='revoke'),\n]\n","sub_path":"FacebookManager/urls.py","file_name":"urls.py","file_ext":"py","file_size_in_byte":390,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"8832747","text":"import matplotlib.pyplot as plt\nimport numpy as np\n\ndef plot_persistence(data,params):\n \n \"\"\"Arguments in are (0) a dictionary and (1) parameters\"\"\"\n \n # Extract parameters\n dim = params['dim']\n thr = params['max_persistence']\n \n # Plot figure\n fig = plt.figure(figsize = (8,8))\n ax = fig.add_subplot(1,1,1)\n ax.plot([0,thr],[0,thr],'k')\n for d in range(dim+1):\n data_array = np.array(data[d])\n ax.plot(data_array[:,0],data_array[:,1],'x',label='dim = '+str(d),clip_on=False)\n data_array = []\n ax.set_xlabel('birth')\n ax.set_ylabel('death')\n ax.axis([0,thr,0,thr])\n ax.legend(numpoints=1,loc=4)\n \n # Create title with parameter info\n title = params.copy()\n del title['dim']\n del title['max_persistence']\n string = 'persistence diagram with the following parameters:\\n'\n j = 1\n k = 1\n for i in sorted(title):\n string += str(i) + ' = ' + str(title[i])\n if k < len(title):\n string += ','\n if j > 3:\n j = 1\n string += '\\n'\n else:\n j += 1\n string += ' '\n k += 1\n ax.set_title(string)\n \n return fig\n ","sub_path":"scripts/PlotPersistence.py","file_name":"PlotPersistence.py","file_ext":"py","file_size_in_byte":1216,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"118143802","text":"\"\"\"\nhttps://leetcode.com/problems/reverse-linked-list/\n\"\"\"\n\n\n# Definition for singly-linked list.\nclass ListNode(object):\n def __init__(self, x):\n self.val = x\n self.next = None\n\n def __str__(self):\n text = ''\n curr = self\n while curr:\n text += str(curr.val) + '->'\n curr = curr.next\n return text\n\n# Iterative\nclass Solution(object):\n def reverseList(self, head):\n cur = head\n prv = None\n while cur:\n nxt = cur.next\n cur.next = prv\n prv = cur\n cur = nxt\n return prv\n\nnode3 = ListNode('C')\nnode2 = ListNode('B')\nnode1 = ListNode('A')\nnode2.next = node3\nnode1.next = node2\nprint(node1)\n\nreversed1 = Solution().reverseList(node1)\n\nprint(reversed1)\n","sub_path":"leetcode/reverse-linked-list/reverse-linked-list.py","file_name":"reverse-linked-list.py","file_ext":"py","file_size_in_byte":790,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"522754193","text":"import sys\r\nimport glob\r\nimport os\r\nimport shutil as sh\r\nimport random\r\n\r\ntry:\r\n dir = input(\"Enter Directory : \")\r\n try:\r\n percentage_train_data = int(input(\"Enter percentage of train_data : \"))\r\n except ValueError:\r\n print(\"Value Error : Please Enter inteager.\")\r\n sys.exit()\r\n train_dir = dir + '\\\\' + 'Train set' # Train data directory name\r\n test_dir = dir + '\\\\' + 'Test set' # Test data directory name\r\n os.mkdir(train_dir)\r\n os.mkdir(test_dir)\r\nexcept FileExistsError:\r\n print(\"Directory 'Train set' and 'Test set' already exist. Please check again\")\r\n sys.exit()\r\nexcept FileNotFoundError:\r\n print(\"Input Directory Not found. Please check again\")\r\n sys.exit()\r\n\r\n\r\nprint(\"Now in Process...\")\r\n\r\n# Name list of paired JPG & JSON\r\npaired_list = []\r\nextention = '*.jpg'\r\n\r\n#for index number set as random based on time seed\r\nrandom_index = []\r\n\r\nfor process in glob.glob(os.path.join(dir, extention)):\r\n paired_list.append(process.split('\\\\')[-1].split('.')[0]) # Make a list based on JPG file name\r\n\r\n\r\ntrain_data_num = int(len(paired_list) * (percentage_train_data / 100))\r\n\r\nrand_in = random.randint(0,len(paired_list) - 1)\r\n\r\n# Copy paired list for comparison\r\ncpy_paired = paired_list[:]\r\n\r\nfor ind in range(0,train_data_num):\r\n while rand_in in random_index:\r\n rand_in = random.randint(0,len(paired_list) - 1) # Return index as random\r\n random_index.append(rand_in)\r\n\r\nfor comp in range(0, len(random_index)):\r\n if paired_list[random_index[comp]] in cpy_paired:\r\n cpy_paired.remove(paired_list[random_index[comp]])\r\n else:\r\n pass\r\n\r\nstandard_dir = dir + '\\\\'\r\n\r\nfor rmd in range(0,len(random_index)):\r\n sh.move(standard_dir + paired_list[random_index[rmd]] + '.jpg', train_dir + '\\\\' + paired_list[random_index[rmd]] + '.jpg')\r\n sh.move(standard_dir + paired_list[random_index[rmd]] + '.json', train_dir + '\\\\' + paired_list[random_index[rmd]] + '.json')\r\n\r\nfor rmd2 in range(0, len(cpy_paired)):\r\n sh.move(standard_dir + cpy_paired[rmd2] + '.jpg', test_dir + '\\\\' + cpy_paired[rmd2] + '.jpg')\r\n sh.move(standard_dir + cpy_paired[rmd2] + '.json', test_dir + '\\\\' + cpy_paired[rmd2] + '.json')\r\n\r\n ","sub_path":"TrD_TeD.py","file_name":"TrD_TeD.py","file_ext":"py","file_size_in_byte":2214,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"163280468","text":"#!/usr/bin/python\n\nimport click\nimport requests\nfrom utils import file_util\nimport os\n\njson_rest_header = {'Accept' : 'application/json', 'Content-Type' : 'application/json'}\n\n\n@click.group()\ndef cli():\n pass\n\ndef load_config():\n current_dir = os.path.dirname(os.path.realpath(__file__))\n config_file = os.path.join(current_dir, \"config.json\")\n config_json = file_util.load_json_file(config_file)\n return config_json\n\n@cli.command()\n@click.argument('path')\ndef rest_get(path):\n config = load_config()\n res = requests.get(config['restapi_url'] + path)\n print(res.json())\n\n@cli.command()\n@click.argument('path')\n@click.argument('json_data_file')\ndef rest_post(path, json_data_file):\n config = load_config()\n url = config['restapi_url'] + path\n payload = open(json_data_file, 'rb').read()\n res = requests.post(url, data=payload, headers=json_rest_header)\n print(res.json())\n\n\nif __name__ == '__main__':\n cli()\n","sub_path":"cli/heycli.py","file_name":"heycli.py","file_ext":"py","file_size_in_byte":949,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"58085241","text":"import RPi.GPIO as GPIO\n\n\n# Sätter hur den ska läsa pin\nGPIO.setmode(GPIO.BOARD)\n# Sätter vilka pins och om det I eller O'\nbtn = GPIO.setup(16, GPIO.IN)\nrelay = GPIO.setup(15, GPIO.OUT)\n\n\n# connect button to GPIO BOARD 16, relay to GPIO BOARD 15,\n\n\ndef main():\n # might be able to read relay signal instead\n pwr = 0\n # run loop cheking if btn is pressed\n while True:\n # listening for a button press\n if btn == 1:\n # check if power is on or off\n if pwr == 0:\n # if power is off, we turn it on here\n print('The power is off,\\n')\n pwr = 1\n print('The power is on\\n')\n else:\n # if power is on, we turn it on here\n print('The power is on,\\n')\n pwr = 0\n print('The power is off\\m')\n\n '''\n while True:\n button = 0\n power = 0\n\n button = input('1 = button pressed')\n power = input('[0]PowerOff | [1]PowerOn')\n\n if button == '1':\n if power == '0':\n powerOn()\n elif power == '1':\n powerOff()\n'''\n\n\nif __name__ == '__main__':\n main()","sub_path":"test.py","file_name":"test.py","file_ext":"py","file_size_in_byte":1199,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"637072153","text":"# -*- coding: utf-8 -*-\n# Вашей программе на вход подается ссылка на HTML файл.\n# Вам необходимо скачать этот файл, затем найти в нем все ссылки вида и вывести список сайтов, на которые есть ссылка.\n\n# Сайтом в данной задаче будем называть имя домена вместе с именами поддоменов. То есть, это последовательность символов, которая следует сразу после символов протокола, если он есть, до символов порта или пути, если они есть.\n\n# Сайты следует выводить в алфавитном порядке.\n\n# Пример HTML файла:\n\n# \n# \n# \n# \n# \n# \n\n# Пример ответа:\n\n# mail.ru\n# neerc.ifmo.ru\n# stepic.org\n# www.ya.ru\n# ya.ru\n\nimport requests\nimport re\n# url = input()\nurl = \"http://ya.ru\"\n\nres = requests.get(url)\n# print(res.status_code)\n# print(res.headers['Content-Type'])\n# print(res.url)\nhtml = res.text\n# links = re.findall('\"((http|ftp)s?://.*?)\"', html)\n# print(links)\n\nregexp_link = r'''s]+))?)+s*|s*)/?>w+'''\npattern = re.compile(regexp_link)\nlinks = re.findall(pattern, html)\n\n#print all matches\nprint(links)\n\n# link_list = re.findall(r\"(?<=href=\\\").+?(?=\\\")|(?<=href=\\').+?(?=\\')\", html)\n# link_list = re.findall(r'href=[\\'\"]?([^\\'\" >]+)', html)\n# # for url in link_list:\n# print(link_list)\n\n\n# linkregex = re.compile('')\n# links = linkregex.findall(html)\n# # links = re.findall(r\"(.*?)\", html)\n# print(links)\n# for link in links:\n # print('href: %s, HTML text: %s' % (link[0], link[1]))","sub_path":"stepic_py_basic_use/w3/3-3-7.py","file_name":"3-3-7.py","file_ext":"py","file_size_in_byte":2046,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"583727020","text":"import twitter\n\nfrom main_config import Config\n\napi = twitter.Api(consumer_key=Config.API_key,\n consumer_secret=Config.API_secret_key,\n access_token_key='1110445913791713280-2UYoQtPqZ5FhBX4fQfGHclShDtm64W',\n access_token_secret='M9g1nOtTyqLQ5qA72AFwwjsv6tqHfyoHTJM2ujaw5PjNj',\n tweet_mode='extended')\nstatuses = api.GetHomeTimeline(exclude_replies=True)\nprint(statuses)\n","sub_path":"twitter_api/test.py","file_name":"test.py","file_ext":"py","file_size_in_byte":438,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"515568287","text":"from aiohttp_jinja2 import template\n\nfrom app.service.auth_svc import check_authorization\n\n\nclass SandGuiApi:\n\n def __init__(self, services):\n self.auth_svc = services.get('auth_svc')\n self.app_svc = services.get('app_svc')\n self.data_svc = services.get('data_svc')\n\n @check_authorization\n @template('sandcat.html')\n async def splash(self, request):\n delivery_cmds = await self.data_svc.locate('abilities', dict(ability_id='2f34977d-9558-4c12-abad-349716777c6b'))\n return dict(delivery_cmds=delivery_cmds)\n","sub_path":"app/sand_gui_api.py","file_name":"sand_gui_api.py","file_ext":"py","file_size_in_byte":553,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"447564364","text":"import cPickle as pickle\nfrom itertools import compress\n\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom mpl_toolkits.mplot3d import Axes3D\nfrom mpl_toolkits.axes_grid1 import ImageGrid\nfrom sklearn.decomposition import PCA \nfrom sklearn.manifold import TSNE\n\n\ndef pca(states, labels, n_components, plot_by_colors=False):\n assert n_components == 2 or n_components == 3, 'Wrong number of components'\n\n print('PCA')\n pca = PCA(n_components=n_components)\n\n print('Fitting & transforming')\n transformed_states = pca.fit_transform(states)\n\n print('Visual')\n plt.clf()\n plt.cla()\n color_names = ['blue', 'red', 'black', 'green', 'pink', 'yellow', 'brown', 'magenta', 'cyan', 'orange']\n colors = np.choose(labels, color_names)\n if n_components == 2:\n\n if plot_by_colors:\n fig = plt.figure(1, (4., 4.))\n grid = ImageGrid(fig, 111, # similar to subplot(111)\n nrows_ncols=(3, 4), # creates 2x2 grid of axes\n axes_pad=0.1, # pad between axes in inch.\n )\n\n for i in range(10):\n\n labels_one = np.array(labels)\n idxs = labels_one == i\n states_one = np.array(list(compress(transformed_states, idxs)))\n labels_one = [color_names[i] for _ in range(len(states_one))]\n grid[i].scatter(states_one[:, 0], states_one[:, 1], c=labels_one)\n\n # plt.scatter(transformed_states[:, 0], transformed_states[:, 1], c=colors)\n elif n_components == 3:\n fig = plt.figure(1, figsize=(4, 3))\n ax = Axes3D(fig, rect=[0, 0, .95, 1], elev=48, azim=134)\n ax.scatter(transformed_states[:, 0], transformed_states[:, 1], transformed_states[:, 2], c=colors)\n\n plt.show()\n\n\ndef tsne(states, labels, n_components):\n assert n_components == 2 or n_components == 3, 'Wrong number of components'\n\n print('T-SNE')\n tsne = TSNE(n_components=n_components)\n\n print('Fitting & transforming')\n transformed_states = tsne.fit_transform(states)\n\n print('Visual')\n plt.clf()\n plt.cla()\n colors = np.choose(labels, ['blue', 'red', 'black', 'green', 'pink', 'yellow', 'brown', 'magenta', 'cyan', 'orange'])\n if n_components == 2:\n plt.scatter(transformed_states[:, 0], transformed_states[:, 1], c=colors)\n elif n_components == 3:\n fig = plt.figure(1, figsize=(4, 3))\n ax = Axes3D(fig, rect=[0, 0, .95, 1], elev=48, azim=134)\n ax.scatter(transformed_states[:, 0], transformed_states[:, 1], transformed_states[:, 2], c=colors)\n\n plt.show()\n\n\nif __name__ == '__main__':\n print('Loading')\n df = pickle.load(open('/home/petrbel/Dropbox/ALI/states.pkl', 'rb'))\n pca(states=list(df['states']), labels=list(df['labels']), n_components=2, plot_by_colors=True)\n # pca(states=list(df['states']), labels=list(df['labels']), n_components=3)\n # tsne(states=list(df['states']), labels=list(df['labels']), n_components=2)\n # tsne(states=list(df['states']), labels=list(df['labels']), n_components=3)\n print('Finished')\n","sub_path":"visual.py","file_name":"visual.py","file_ext":"py","file_size_in_byte":3103,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"622976454","text":"from telegram.ext import *\nfrom telegram import InlineKeyboardButton, InlineKeyboardMarkup, KeyboardButton\nimport random\n\n############################### Bot ############################################\n\ncurrent_balance = 1000\nbet_size = 50\nuser_choice = ''\ndrawn_choice = ''\n\n\ndef start_message():\n return 'Welcome to Eta Eta! A classic game that offers 50/50 chance of winning.'\n\n\ndef start(update, context):\n update.message.reply_text(start_message())\n update.message.reply_text(main_menu_message(drawn_choice, bet_size, current_balance),\n reply_markup=main_menu_keyboard())\n\n\ndef conv(inp):\n if (inp == 'h'):\n return 1\n if (inp == 't'):\n return 0\n if (inp == 'cbs'):\n return 2\n if (int(inp) % 50 == 0):\n return 3\n\n\ndef main_menu(update, context):\n query = update.callback_query\n query.answer()\n cn = random.randint(0, 1)\n if (cn == 0):\n drawn_choice = 'Tails'\n else:\n drawn_choice = 'Heads'\n\n # query.message.reply_text(text=main_menu_message(drawn_choice,bet_size,current_balance),reply_markup=main_menu_keyboard())\n # print(query.data+'\\n')\n if (conv(query.data) == 3):\n global bet_size\n global current_balance\n bet_size = int(query.data)\n query.edit_message_text('Bet size changed to ' + query.data)\n query.message.reply_text(text=main_menu_message(drawn_choice, bet_size, current_balance),\n reply_markup=main_menu_keyboard())\n\n\n else:\n if (query.data == 'cbs'):\n query.edit_message_text('Choose bet size in coins', reply_markup=bet_choice_keyboard())\n if (query.data != 'cbs'):\n if(current_balance cutoff:\n graph.add_edge(node, f'patient:{patient}', value=value, status='sans')\n\n for patient_idx in range(n_patients_with):\n patient = patient_idx + n_nodes + n_patients_sans\n value = with_profile[node, patient_idx]\n if value > cutoff:\n graph.add_edge(node, f'patient:{patient}', value=value, status='with')\n\n print('Nodes', graph.number_of_nodes())\n print('Edges', graph.number_of_edges())\n\n # Fit embedding model to graph\n g2v = Node2Vec()\n g2v.fit(graph, verbose=True) # takes about 1 second\n\n print('Training and evaluating classifier')\n # Train classifier between nodes in community and outside of community\n x = [\n g2v.predict(f'patient:{patient_idx + n_nodes}')\n for patient_idx in range(n_patients_sans)\n ] + [\n g2v.predict(f'patient:{patient_idx + n_nodes + n_patients_sans}')\n for patient_idx in range(n_patients_with)\n ]\n y = [False] * n_patients_sans + [True] * n_patients_with\n\n x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.33, random_state=42)\n\n print(f'Training on {len(x_train)} samples')\n logistic_regression = LogisticRegression()\n logistic_regression.fit(x_train, y_train)\n\n print(f'Evaluating on {len(x_test)} holdout samples')\n y_pred = logistic_regression.predict(x_test)\n accuracy, mcc = accuracy_score(y_test, y_pred), matthews_corrcoef(y_test, y_pred)\n print('Accuracy:', accuracy)\n print('MCC:', mcc)\n\n return graph, g2v, logistic_regression,\n\n\nif __name__ == '__main__':\n main()\n","sub_path":"src/lpe/network.py","file_name":"network.py","file_ext":"py","file_size_in_byte":3213,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"228192171","text":"import MultiLayerPerceptron as MLP\nimport pandas as pd\n\ndef get_dataset1():\n \"\"\"Retrieve the kuwait dataset and process the data.\"\"\"\n # Set defaults.\n global input_shape\n filename = \"Kuwait.xlsx\"\n df = pd.read_excel(filename, 'DataSet2', header= 0, usecols=\"B:X\")\n dm = pd.read_excel(filename, 'DataSet2', header= 0, usecols=\"AF\")\n X = df.values\n Y = dm.values\n input_shape = 23\n return X, Y, input_shape\n\n\ndef get_dataset2():\n \"\"\"Retrieve the gcc dataset and process the data.\"\"\"\n # Set defaults.\n global input_shape\n filename = \"FinancialData.xlsx\"\n df = pd.read_excel(filename, 'DataSet2', header=0, usecols=\"B:R\")\n dm = pd.read_excel(filename, 'DataSet2', header=0, usecols=\"Y\")\n X = df.values\n Y = dm.values\n input_shape = 17\n return X, Y, input_shape\n\n\nX, Y, Input_shape = get_dataset1()\nMLP.MLP_evaluate(X, Y, Input_shape)","sub_path":"Analysis.py","file_name":"Analysis.py","file_ext":"py","file_size_in_byte":889,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"281036527","text":"# -*- coding: utf-8 -*-\nfrom PyQt4.QtCore import *\n# ---\nfrom datetime import datetime\nfrom datetime import timedelta\n# ---\nfrom dbgw import DbgwLite, DbgwMy\nfrom curve_pull import CurvePull\nfrom utils import *\nfrom excs import *\n\nDEFAULT_SELECT_INTERVAL = 48 # hours\nDEFAULT_X_SCALE_INTERVAL = 12 # hours\nDEFAULT_STEP_SIZE = 3600.0 # seconds\n\nTMP_INDEX = 0\nHMD_INDEX = 1\nMQ135_INDEX = 2\nMQ7_INDEX = 3\nPHOTO_INDEX = 4\n\nclass Plotter():\n\n def __init__(self):\n # ---\n self.db = None\n self.model = {}\n # ---\n\n def initialized(self):\n if not self.db:\n return False\n return True\n\n def init_my(self, params):\n self.db = DbgwMy()\n if not self.db.connect(params):\n return False\n return self.init_model()\n\n def init_lite(self, filename):\n self.db = DbgwLite()\n if not self.db.connect(filename):\n return False\n return self.init_model()\n\n def init_model(self):\n # ---\n init_date = self.db.get_dt_start()\n init_stamp = timestamp(init_date)\n to_date = self.db.get_dt_finish()\n from_date = to_date - timedelta(hours=DEFAULT_SELECT_INTERVAL) \n for device_tuple in self.db.select_devices():\n device = device_tuple[0]\n pull = CurvePull()\n stamps = []\n values = {}\n # -- data\n for row in self.db.select_data(device, from_date, to_date):\n stamps.append(timestamp(row[0]) - init_stamp)\n for index, value in enumerate(row[1:]):\n values.setdefault(index, []).append(value)\n pull.set_x_data(stamps)\n for index in sorted(values.keys()):\n pull.set_y_data(index, values[index])\n # --- x_scale\n x_max = stamps[-1]\n x_min = timestamp(to_date - timedelta(hours=DEFAULT_X_SCALE_INTERVAL)) - init_stamp\n pull.set_x_scale(x_min, x_max)\n # --- motion\n motion_stamps = []\n for row in self.db.select_event(device, 'MOTION', init_date, to_date): # !!! take all motions\n motion_stamps.append(timestamp(row[0]) - init_stamp)\n pull.set_m_markers(motion_stamps)\n # --- info\n info_stamps = []\n for row in self.db.select_event(device, 'INFO', init_date, to_date): # !!! take all info\n label = row[1]\n if label == \"ARDUINO STARTED\":\n label = \"*\"\n info_stamps.append((timestamp(row[0]) - init_stamp, label))\n pull.set_i_markers(info_stamps)\n # --- error\n error_stamps = []\n for row in self.db.select_event(device, 'ERROR', init_date, to_date): # !!! take all errors\n error_stamps.append((timestamp(row[0]) - init_stamp, row[1]))\n pull.set_e_markers(error_stamps)\n # ---\n self.model[device] = pull\n # ---\n self.init_date, self.from_date, self.to_date = init_date, from_date, to_date\n self.finish_date = self.db.get_dt_finish()\n self.init_stamp = init_stamp\n return True\n\n def get_more_data(self):\n to_date = self.from_date\n from_date = to_date - timedelta(hours=DEFAULT_SELECT_INTERVAL)\n if from_date < self.init_date:\n return\n init_stamp = timestamp(self.init_date)\n for device in self.devices():\n pull = self.model[device]\n stamps = []\n values = {}\n # -- data\n for row in self.db.select_data(device, from_date, to_date):\n stamps.append(timestamp(row[0]) - init_stamp)\n for index, value in enumerate(row[1:]):\n values.setdefault(index, []).append(value)\n pull.prepend_x_data(stamps)\n for index in sorted(values.keys()):\n pull.prepend_y_data(index, values[index])\n # ---\n self.from_date, self.to_date = from_date, to_date\n\n def devices(self):\n return sorted(self.model.keys())\n\n def curve(self, device, index):\n return self.model[device].curve(index)\n\n def x_scale(self, device):\n return self.model[device].get_x_scale()\n\n def m_markers(self, device):\n return self.model[device].get_m_markers()\n\n def i_markers(self, device):\n return self.model[device].get_i_markers()\n\n def e_markers(self, device):\n return self.model[device].get_e_markers()\n\n def back_step(self):\n for device in self.devices():\n pull = self.model[device]\n try:\n pull.move_scale_left( DEFAULT_STEP_SIZE )\n except ScaleError:\n self.get_more_data()\n\n def forward_step(self):\n for device in self.devices():\n pull = self.model[device]\n try:\n pull.move_scale_right( DEFAULT_STEP_SIZE )\n except ScaleError:\n pass\n\n def x_scale_dt(self):\n from_date = self.finish_date\n to_date = self.init_date\n for device in self.devices():\n scale_min, scale_max = self.x_scale(device)\n scale_min_dt = from_timestamp(scale_min + self.init_stamp)\n scale_max_dt = from_timestamp(scale_max + self.init_stamp)\n from_date = min(from_date, scale_min_dt)\n to_date = max(to_date, scale_max_dt)\n return from_date, to_date\n\n def timestamp_dt(self, stamp):\n return from_timestamp(stamp + self.init_stamp)\n\n","sub_path":"plotter.py","file_name":"plotter.py","file_ext":"py","file_size_in_byte":5562,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"322560967","text":"#!/usr/bin/env python3 -W ignore::DeprecationWarning\n\nimport sys\nimport warnings\n\nfrom fetch import fetch_data\nfrom train import train_data\n\n# suppress all warnings\nwarnings.filterwarnings(\"ignore\")\n\n\nif __name__== \"__main__\":\n\n fetch_obj = fetch_data(data_type=0)\n test_obj = fetch_data(data_type=1)\n train_obj = train_data(fetch_obj.label_df, fetch_obj.pseudo_df, test_obj.unlabel_df)\n # apply a tf-idf model with SVD\n combine_data = [*train_obj.labeled_data, *train_obj.pseudo_data]\n train_obj.fit_vectorizer(combine_data, min_df=0.010, max_df=0.8, ngram_range=(1, 2), svd=True)\n # using lda\n train_obj.train_model()\n # test data\n train_obj.fit_vectorizer(train_obj.test_data, min_df=0.010, max_df=0.8, ngram_range=(1, 2), svd=True, n_components=77)\n train_obj.test_model(n_clusters=5)","sub_path":"code/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":821,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"87089229","text":"import discord\nimport os\nimport re\n\nfrom redbot.core import checks, Config, commands\n\nBaseCog = getattr(commands, \"Cog\", object)\n\n\nclass sthcommands(BaseCog):\n\n \"\"\"All STH reaction commands conveniently located in one file!\"\"\"\n\n default_global_settings = {\n \"channels_ignored\": [],\n \"guilds_ignored\": []\n }\n\n def __init__(self, bot):\n self.bot = bot\n self.conf = Config.get_conf(self, identifier=527690525)\n self.conf.register_global(\n **self.default_global_settings\n )\n\n @commands.guild_only()\n @commands.command()\n async def workout(self, ctx, arg):\n \"\"\"Get motivated to workout\"\"\"\n \n msg = arg\n await ctx.send(msg)\n\n\n embed = discord.Embed(\n description = 'ITS TIME MOTHERFUCKER!!!',\n color = discord.Color.red()\n )\n embed.set_image(url='https://media1.tenor.com/images/316802abc29c277b08bae799b1fbe52c/tenor.gif')\n await ctx.send(embed=embed)\n \n","sub_path":"sthcommands/sthcommands.py","file_name":"sthcommands.py","file_ext":"py","file_size_in_byte":1007,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"618424406","text":"# uncompyle6 version 3.7.4\n# Python bytecode 3.4 (3310)\n# Decompiled from: Python 3.6.9 (default, Apr 18 2020, 01:56:04) \n# [GCC 8.4.0]\n# Embedded file name: build/bdist.linux-x86_64/egg/mendeley2biblatex/__init__.py\n# Compiled at: 2016-07-20 10:13:03\n# Size of source mod 2**32: 1329 bytes\nimport sys\nfrom argparse import ArgumentParser\nfrom mendeley2biblatex.library_converter import LibraryConverter\n__all__ = [\n 'bib_entry', 'library_converter']\n\ndef main():\n \"\"\"Set this script some command line options. See usage.\"\"\"\n parser = ArgumentParser(description='Convert a sqlite database from mendeley to bibetex')\n parser.add_argument('-q', '--quiet', action='store_true', default=False, dest='quiet', help='Do not display any information.')\n parser.add_argument('-f', '--folder', default=None, dest='folder', help='Limit output to mendeley folder')\n parser.add_argument('-o', '--output', dest='bibtex_file', default=sys.stdout, help='BibTeX file name, else output will be printed to stdout')\n parser.add_argument('input', metavar='INPUT_FILE', nargs='?', help='the mendeley database')\n parser.add_argument('--version', action='version', version='mendeley2biblatex')\n args = parser.parse_args()\n if not args.input:\n parser.error('No file specified')\n LibraryConverter.convert_library(args.input, args.bibtex_file, args.quiet, args.folder)\n\n\nif __name__ == '__main__':\n try:\n main()\n except KeyboardInterrupt:\n print('Interrupted by user')","sub_path":"pycfiles/mendeley2biblatex-0.1.8-py3.4/__init__.cpython-34.py","file_name":"__init__.cpython-34.py","file_ext":"py","file_size_in_byte":1496,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"583931104","text":"from grafo import *\r\n\r\nif __name__ == \"__main__\":\r\n grafos = []\r\n\r\n print(\"POST criação de grafos\")\r\n print(\"Criando lista de grafos e listando vertices!\")\r\n G = Grafo()\r\n H = Grafo()\r\n\r\n grafos.append(G)\r\n grafos.append(H)\r\n \r\n\r\n print(\"PUT vertice\")\r\n G.add_vertice(1,\"teste\")\r\n G.add_vertice(2, \"teste\")\r\n G.add_vertice(3, \"teste\")\r\n G.add_vertice(4, \"teste\")\r\n print(\"PUT aresta\")\r\n G.add_aresta(1, 2,0)\r\n G.add_aresta(1, 3,10)\r\n G.add_aresta(3, 4,20)\r\n \r\n \r\n H.add_vertice(10,\"teste\")\r\n H.add_vertice(20,\"teste\")\r\n H.add_vertice(30,\"teste\")\r\n H.add_vertice(40,\"teste\")\r\n H.add_vertice(50,\"teste\")\r\n H.add_vertice(60,\"teste\")\r\n H.add_aresta(10, 30,0)\r\n H.add_aresta(20, 30,100)\r\n H.add_aresta(10, 40,200)\r\n H.add_aresta(10, 10,300)\r\n\r\n print(\"DELETE aresta 10-30\")\r\n H.deleta_aresta(10,30)\r\n print(H.vizinhos(10))\r\n print(\"DELETE vertice 40\")\r\n H.deleta_vertice(40,\"teste\")\r\n print(H.vizinhos(10))\r\n print(H.vertices())\r\n\r\n print(\"Listar vertices de um grafo !\")\r\n print(H.vertices())\r\n\r\n print(\"GET peso de uma aresta\")\r\n print(H.retornaPeso(10,10))\r\n\r\n print(\"POST altera peso aresta\")\r\n print(H.lista_vizinhos[10])\r\n H.alteraPesoAresta(10,10,1)\r\n print(H.lista_vizinhos[10])\r\n print(H.retornaPeso(10,10))\r\n\r\n print(\"DELETE grafo\")\r\n grafos.remove(G)\r\n \r\n \r\n i = 0\r\n for x in grafos:\r\n print(\"Grafo \",i)\r\n print(x.vertices())\r\n i = i+1\r\n \r\n","sub_path":"testegrafo.py","file_name":"testegrafo.py","file_ext":"py","file_size_in_byte":1525,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"45264770","text":"import pickle\nimport cv2\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport matplotlib.image as mpimg\nimport glob\n\ndef camera_calibrate(cal_images, nx=9, ny=6):\n '''\n camera_calibrate finds camera calibration parameters\n :param cal_images:\n :param nx: number of squares in width of checkerboard\n :param ny: number of square in height of checkerboard\n :return:\n '''\n # prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)\n objp = np.zeros((nx*ny,3), np.float32)\n objp[:,:2] = np.mgrid[0:nx,0:ny].T.reshape(-1, 2)\n\n # Arrays to store object points and image points from all the images.\n objpoints = [] # 3d points in real world space\n imgpoints = [] # 2d points in image plane.\n\n # Step through the list and search for chessboard corners\n for idx, fname in enumerate(cal_images):\n img = cv2.imread(fname)\n gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n\n # Find the chessboard corners\n ret, corners = cv2.findChessboardCorners(gray, (nx,ny), None)\n\n # If found, add object points, image points\n if ret == True:\n objpoints.append(objp)\n imgpoints.append(corners)\n\n ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)\n\n return mtx, dist\n\ndef camera_setup(calibration_path='camera_cal/calibration*.jpg', nx=9, ny=6):\n '''\n camera_setup sets up calibration images and returns camera calibration results\n :param calibration_path:\n :param nx: number of squares in width of checkerboard\n :param ny: number of square in height of checkerboard\n :return:\n '''\n # Make a list of calibration images\n cal_images = glob.glob(calibration_path)\n cam_mtx, cam_dist = camera_calibrate(cal_images, nx, ny)\n return cam_mtx, cam_dist\n\ndef cal_undistort(img, mtx, dist):\n '''\n cal_undistort undistorts images\n :param img:\n :param objpoints:\n :param imgpoints:\n :return:\n '''\n # Use cv2.calibrateCamera() and cv2.undistort()\n #gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)\n #ret, corners = cv2.findChessboardCorners(gray, (8,6), None)\n undist = cv2.undistort(img, mtx, dist, None, mtx)\n #undist = np.copy(img) # Delete this line\n return undist\n\n# Define a function that takes an image, number of x and y points,\n# camera matrix and distortion coefficients\ndef corners_unwarp(img, nx, ny, mtx, dist):\n # Use the OpenCV undistort() function to remove distortion\n undist = cv2.undistort(img, mtx, dist, None, mtx)\n # Convert undistorted image to grayscale\n gray = cv2.cvtColor(undist, cv2.COLOR_BGR2GRAY)\n # Search for corners in the grayscaled image\n ret, corners = cv2.findChessboardCorners(gray, (nx, ny), None)\n\n if ret == True:\n # If we found corners, draw them! (just for fun)\n cv2.drawChessboardCorners(undist, (nx, ny), corners, ret)\n # Choose offset from image corners to plot detected corners\n # This should be chosen to present the result at the proper aspect ratio\n # My choice of 100 pixels is not exact, but close enough for our purpose here\n offset = 100 # offset for dst points\n # Grab the image shape\n img_size = (gray.shape[1], gray.shape[0])\n\n # For source points I'm grabbing the outer four detected corners\n src = np.float32([corners[0], corners[nx-1], corners[-1], corners[-nx]])\n # For destination points, I'm arbitrarily choosing some points to be\n # a nice fit for displaying our warped result\n # again, not exact, but close enough for our purposes\n dst = np.float32([[offset, offset], [img_size[0]-offset, offset],\n [img_size[0]-offset, img_size[1]-offset],\n [offset, img_size[1]-offset]])\n # Given src and dst points, calculate the perspective transform matrix\n M = cv2.getPerspectiveTransform(src, dst)\n # Warp the image using OpenCV warpPerspective()\n warped = cv2.warpPerspective(undist, M, img_size)\n\n # Return the resulting image and matrix\n return warped, M\n\n# Define a function that takes an image, gradient orientation,\n# and threshold min / max values.\ndef abs_sobel_thresh(img, orient='x', thresh_min=0, thresh_max=255, sobel_kernel = 3):\n # Convert to grayscale\n gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)\n # Apply x or y gradient with the OpenCV Sobel() function\n # and take the absolute value\n if orient == 'x':\n abs_sobel = np.absolute(cv2.Sobel(gray, cv2.CV_64F, 1, 0, ksize=sobel_kernel))\n if orient == 'y':\n abs_sobel = np.absolute(cv2.Sobel(gray, cv2.CV_64F, 0, 1, ksize=sobel_kernel))\n # Rescale back to 8 bit integer\n scaled_sobel = np.uint8(255*abs_sobel/np.max(abs_sobel))\n # Create a copy and apply the threshold\n binary_output = np.zeros_like(scaled_sobel)\n # Here I'm using inclusive (>=, <=) thresholds, but exclusive is ok too\n binary_output[(scaled_sobel >= thresh_min) & (scaled_sobel <= thresh_max)] = 1\n\n # Return the result\n return binary_output\n\n# Define a function to return the magnitude of the gradient\n# for a given sobel kernel size and threshold values\ndef mag_thresh(img, sobel_kernel=3, mag_thresh=(0, 255)):\n # Convert to grayscale\n gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)\n # Take both Sobel x and y gradients\n sobelx = cv2.Sobel(gray, cv2.CV_64F, 1, 0, ksize=sobel_kernel)\n sobely = cv2.Sobel(gray, cv2.CV_64F, 0, 1, ksize=sobel_kernel)\n # Calculate the gradient magnitude\n gradmag = np.sqrt(sobelx**2 + sobely**2)\n # Rescale to 8 bit\n scale_factor = np.max(gradmag)/255\n gradmag = (gradmag/scale_factor).astype(np.uint8)\n # Create a binary image of ones where threshold is met, zeros otherwise\n binary_output = np.zeros_like(gradmag)\n binary_output[(gradmag >= mag_thresh[0]) & (gradmag <= mag_thresh[1])] = 1\n\n # Return the binary image\n return binary_output\n\n# Define a function to threshold an image for a given range and Sobel kernel\ndef dir_threshold(img, sobel_kernel=3, thresh=(0, np.pi/2)):\n # Grayscale\n gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)\n # Calculate the x and y gradients\n sobelx = cv2.Sobel(gray, cv2.CV_64F, 1, 0, ksize=sobel_kernel)\n sobely = cv2.Sobel(gray, cv2.CV_64F, 0, 1, ksize=sobel_kernel)\n # Take the absolute value of the gradient direction,\n # apply a threshold, and create a binary image result\n absgraddir = np.arctan2(np.absolute(sobely), np.absolute(sobelx))\n binary_output = np.zeros_like(absgraddir)\n binary_output[(absgraddir >= thresh[0]) & (absgraddir <= thresh[1])] = 1\n\n # Return the binary image\n return binary_output\n\ndef color_threshold(img, channel=2, s_thresh=(170, 255)):\n # Convert to HSV color space and separate the V channel\n hsv = cv2.cvtColor(img, cv2.COLOR_RGB2HLS).astype(np.float)\n s_channel = hsv[:, :, channel]\n\n # Threshold color channel\n s_binary = np.zeros_like(s_channel)\n s_binary[(s_channel >= s_thresh[0]) & (s_channel <= s_thresh[1])] = 1\n\n return s_binary\n\ndef pipeline(img, s_thresh=(170, 255), sx_thresh=(20, 100)):\n img = np.copy(img)\n\n # gradient\n ksize = 3 # Choose a larger odd number to smooth gradient measurements\n gradx = abs_sobel_thresh(img, orient='x', thresh_min=sx_thresh[0], thresh_max=sx_thresh[1], sobel_kernel=ksize)\n grady = abs_sobel_thresh(img, orient='y', thresh_min=sx_thresh[0], thresh_max=sx_thresh[1], sobel_kernel=ksize)\n\n # color\n s_binary = color_threshold(img, 2, s_thresh)\n color_binary = np.dstack((np.zeros_like(gradx), gradx, s_binary))\n\n # mag and dir\n mag_binary = mag_thresh(img, sobel_kernel=ksize, mag_thresh=(0, 255))\n dir_binary = dir_threshold(img, sobel_kernel=ksize, thresh=(0, np.pi / 2))\n\n combined_binary = np.zeros_like(dir_binary)\n combined_binary[(s_binary == 1)|((gradx == 1) & (grady == 1))]=255# | ((mag_binary == 1) & (dir_binary == 1))] = 1\n\n return color_binary, combined_binary\n\ndef window_mask(width, height, img_ref, center, level):\n output = np.zeros_like(img_ref)\n output[int(img_ref.shape[0] - (level + 1) * height):int(img_ref.shape[0] - level * height),\n max(0, int(center - width / 2)):min(int(center + width / 2), img_ref.shape[1])] = 1\n return output\n\ndef find_window_centroids(warped, window_width, window_height, margin):\n window_centroids = [] # Store the (left,right) window centroid positions per level\n window = np.ones(window_width) # Create our window template that we will use for convolutions\n\n # First find the two starting positions for the left and right lane by using np.sum to get the vertical image slice\n # and then np.convolve the vertical image slice with the window template\n\n # Sum quarter bottom of image to get slice, could use a different ratio\n l_sum = np.sum(warped[int(3 * warped.shape[0] / 4):, :int(warped.shape[1] / 2)], axis=0)\n l_center = np.argmax(np.convolve(window, l_sum)) - window_width / 2\n r_sum = np.sum(warped[int(3 * warped.shape[0] / 4):, int(warped.shape[1] / 2):], axis=0)\n r_center = np.argmax(np.convolve(window, r_sum)) - window_width / 2 + int(warped.shape[1] / 2)\n\n # Add what we found for the first layer\n window_centroids.append((l_center, r_center))\n\ndef get_perspective_transform(image, src_in = None, dst_in = None):\n img_size = image.shape\n a = 60\n b = 10\n d = 100\n if src_in is None:\n src_out = np.array([[(img_size[1]/2) - a, (img_size[0]/2) + d],\n [(img_size[1]/6) - b, img_size[0]],\n [(img_size[1]*5/6)+a-b, img_size[0]],\n [(img_size[1]/2)+a+0.5*b, (img_size[0]/2) + d]], np.float32)\n else:\n src_out = src_in\n\n if dst_in is None:\n dst_out = np.array([[(img_size[1]/4), 0],\n [(img_size[1]/4), img_size[0]],\n [(img_size[1]*3/4), img_size[0]],\n [(img_size[1]*3/4), 0]], np.float32)\n\n else:\n dst_out = dst_in\n\n warp_m = cv2.getPerspectiveTransform(src_out, dst_out)\n warp_minv = cv2.getPerspectiveTransform(dst_out, src_out)\n\n return src_out, dst_out, warp_m, warp_minv\n\ndef generate_plot(binary_warped, left_fit, right_fit, line=None):\n # Generate x and y values for plotting\n ploty = np.linspace(0, binary_warped.shape[0] - 1, binary_warped.shape[0])\n left_fitx = left_fit[0] * ploty ** 2 + left_fit[1] * ploty + left_fit[2]\n right_fitx = right_fit[0] * ploty ** 2 + right_fit[1] * ploty + right_fit[2]\n\n return left_fitx, right_fitx, ploty\n\n\ndef get_lane_lines(binary_warped):\n # Assuming you have created a warped binary image called \"binary_warped\"\n # Take a histogram of the bottom half of the image\n histogram = np.sum(binary_warped[np.int(binary_warped.shape[0] / 2):, :], axis=0)\n # Create an output image to draw on and visualize the result\n out_img = np.dstack((binary_warped, binary_warped, binary_warped)) * 255\n # Find the peak of the left and right halves of the histogram\n # These will be the starting point for the left and right lines\n midpoint = np.int(histogram.shape[0] / 2)\n leftx_base = np.argmax(histogram[:midpoint])\n rightx_base = np.argmax(histogram[midpoint:]) + midpoint\n\n # Choose the number of sliding windows\n nwindows = 9\n # Set height of windows\n window_height = np.int(binary_warped.shape[0] / nwindows)\n # Identify the x and y positions of all nonzero pixels in the image\n nonzero = binary_warped.nonzero()\n nonzeroy = np.array(nonzero[0])\n nonzerox = np.array(nonzero[1])\n # Current positions to be updated for each window\n leftx_current = leftx_base\n rightx_current = rightx_base\n # Set the width of the windows +/- margin\n margin = 100\n # Set minimum number of pixels found to recenter window\n minpix = 50\n # Create empty lists to receive left and right lane pixel indices\n left_lane_inds = []\n right_lane_inds = []\n\n # Step through the windows one by one\n for window in range(nwindows):\n # Identify window boundaries in x and y (and right and left)\n win_y_low = binary_warped.shape[0] - (window + 1) * window_height\n win_y_high = binary_warped.shape[0] - window * window_height\n win_xleft_low = leftx_current - margin\n win_xleft_high = leftx_current + margin\n win_xright_low = rightx_current - margin\n win_xright_high = rightx_current + margin\n # Draw the windows on the visualization image\n cv2.rectangle(out_img, (win_xleft_low, win_y_low), (win_xleft_high, win_y_high), (0, 255, 0), 2)\n cv2.rectangle(out_img, (win_xright_low, win_y_low), (win_xright_high, win_y_high), (0, 255, 0), 2)\n # Identify the nonzero pixels in x and y within the window\n good_left_inds = ((nonzeroy >= win_y_low) & (nonzeroy < win_y_high) & (nonzerox >= win_xleft_low) & (\n nonzerox < win_xleft_high)).nonzero()[0]\n good_right_inds = ((nonzeroy >= win_y_low) & (nonzeroy < win_y_high) & (nonzerox >= win_xright_low) & (\n nonzerox < win_xright_high)).nonzero()[0]\n # Append these indices to the lists\n left_lane_inds.append(good_left_inds)\n right_lane_inds.append(good_right_inds)\n # If you found > minpix pixels, recenter next window on their mean position\n if len(good_left_inds) > minpix:\n leftx_current = np.int(np.mean(nonzerox[good_left_inds]))\n if len(good_right_inds) > minpix:\n rightx_current = np.int(np.mean(nonzerox[good_right_inds]))\n\n # Concatenate the arrays of indices\n left_lane_inds = np.concatenate(left_lane_inds)\n right_lane_inds = np.concatenate(right_lane_inds)\n\n # Extract left and right line pixel positions\n leftx = nonzerox[left_lane_inds]\n lefty = nonzeroy[left_lane_inds]\n rightx = nonzerox[right_lane_inds]\n righty = nonzeroy[right_lane_inds]\n\n # Fit a second order polynomial to each\n left_fit = np.polyfit(lefty, leftx, 2)\n right_fit = np.polyfit(righty, rightx, 2)\n\n # Generate x and y values for plotting\n left_fitx, right_fitx, ploty = generate_plot(binary_warped, left_fit, right_fit)\n\n out_img[nonzeroy[left_lane_inds], nonzerox[left_lane_inds]] = [255, 0, 0]\n out_img[nonzeroy[right_lane_inds], nonzerox[right_lane_inds]] = [0, 0, 255]\n\n return left_fit, right_fit, left_fitx, right_fitx, ploty, out_img\n\ndef get_lane_lines_with_prior(binary_warped, left_fit, right_fit):\n # Assume you now have a new warped binary image\n # from the next frame of video (also called \"binary_warped\")\n # It's now much easier to find line pixels!\n nonzero = binary_warped.nonzero()\n nonzeroy = np.array(nonzero[0])\n nonzerox = np.array(nonzero[1])\n margin = 150\n left_lane_inds = ((nonzerox > (left_fit[0] * (nonzeroy ** 2) + left_fit[1] * nonzeroy + left_fit[2] - margin)) & (\n nonzerox < (left_fit[0] * (nonzeroy ** 2) + left_fit[1] * nonzeroy + left_fit[2] + margin)))\n right_lane_inds = (\n (nonzerox > (right_fit[0] * (nonzeroy ** 2) + right_fit[1] * nonzeroy + right_fit[2] - margin)) & (\n nonzerox < (right_fit[0] * (nonzeroy ** 2) + right_fit[1] * nonzeroy + right_fit[2] + margin)))\n\n # Again, extract left and right line pixel positions\n leftx = nonzerox[left_lane_inds]\n lefty = nonzeroy[left_lane_inds]\n rightx = nonzerox[right_lane_inds]\n righty = nonzeroy[right_lane_inds]\n # Fit a second order polynomial to each\n left_fit = np.polyfit(lefty, leftx, 2)\n right_fit = np.polyfit(righty, rightx, 2)\n # Generate x and y values for plotting\n ploty = np.linspace(0, binary_warped.shape[0] - 1, binary_warped.shape[0])\n left_fitx = left_fit[0] * ploty ** 2 + left_fit[1] * ploty + left_fit[2]\n right_fitx = right_fit[0] * ploty ** 2 + right_fit[1] * ploty + right_fit[2]\n\n # Create an image to draw on and an image to show the selection window\n out_img = np.dstack((binary_warped, binary_warped, binary_warped)) * 255\n window_img = np.zeros_like(out_img)\n # Color in left and right line pixels\n out_img[nonzeroy[left_lane_inds], nonzerox[left_lane_inds]] = [255, 0, 0]\n out_img[nonzeroy[right_lane_inds], nonzerox[right_lane_inds]] = [0, 0, 255]\n\n # Generate a polygon to illustrate the search window area\n # And recast the x and y points into usable format for cv2.fillPoly()\n left_line_window1 = np.array([np.transpose(np.vstack([left_fitx - margin, ploty]))])\n left_line_window2 = np.array([np.flipud(np.transpose(np.vstack([left_fitx + margin, ploty])))])\n left_line_pts = np.hstack((left_line_window1, left_line_window2))\n right_line_window1 = np.array([np.transpose(np.vstack([right_fitx - margin, ploty]))])\n right_line_window2 = np.array([np.flipud(np.transpose(np.vstack([right_fitx + margin, ploty])))])\n right_line_pts = np.hstack((right_line_window1, right_line_window2))\n\n # Draw the lane onto the warped blank image\n cv2.fillPoly(window_img, np.int_([left_line_pts]), (0, 255, 0))\n cv2.fillPoly(window_img, np.int_([right_line_pts]), (0, 255, 0))\n result = cv2.addWeighted(out_img, 1, window_img, 0.3, 0)\n plt.imshow(result)\n plt.plot(left_fitx, ploty, color='yellow')\n plt.plot(right_fitx, ploty, color='yellow')\n plt.xlim(0, 1280)\n plt.ylim(720, 0)\n\n # Create an image to draw on and an image to show the selection window\n out_img = np.dstack((binary_warped, binary_warped, binary_warped)) * 255\n window_img = np.zeros_like(out_img)\n # Color in left and right line pixels\n out_img[nonzeroy[left_lane_inds], nonzerox[left_lane_inds]] = [255, 0, 0]\n out_img[nonzeroy[right_lane_inds], nonzerox[right_lane_inds]] = [0, 0, 255]\n\n # Generate a polygon to illustrate the search window area\n # And recast the x and y points into usable format for cv2.fillPoly()\n left_line_window1 = np.array([np.transpose(np.vstack([left_fitx - margin, ploty]))])\n left_line_window2 = np.array([np.flipud(np.transpose(np.vstack([left_fitx + margin, ploty])))])\n left_line_pts = np.hstack((left_line_window1, left_line_window2))\n right_line_window1 = np.array([np.transpose(np.vstack([right_fitx - margin, ploty]))])\n right_line_window2 = np.array([np.flipud(np.transpose(np.vstack([right_fitx + margin, ploty])))])\n right_line_pts = np.hstack((right_line_window1, right_line_window2))\n\n # Draw the lane onto the warped blank image\n cv2.fillPoly(window_img, np.int_([left_line_pts]), (0, 255, 0))\n cv2.fillPoly(window_img, np.int_([right_line_pts]), (0, 255, 0))\n result = cv2.addWeighted(out_img, 1, window_img, 0.3, 0)\n\n return left_fit, right_fit, left_fitx, right_fitx, ploty, result\n\ndef window_mask(width, height, img_ref, center, level):\n output = np.zeros_like(img_ref)\n output[int(img_ref.shape[0] - (level + 1) * height):int(img_ref.shape[0] - level * height),\n max(0, int(center - width / 2)):min(int(center + width / 2), img_ref.shape[1])] = 1\n return output\n\n\ndef find_window_centroids(warped, window_width, window_height, margin):\n window_centroids = [] # Store the (left,right) window centroid positions per level\n window = np.ones(window_width) # Create our window template that we will use for convolutions\n\n # First find the two starting positions for the left and right lane by using np.sum to get the vertical image slice\n # and then np.convolve the vertical image slice with the window template\n\n # Sum quarter bottom of image to get slice, could use a different ratio\n l_sum = np.sum(warped[int(3 * warped.shape[0] / 4):, :int(warped.shape[1] / 2)], axis=0)\n l_center = np.argmax(np.convolve(window, l_sum)) - window_width / 2\n r_sum = np.sum(warped[int(3 * warped.shape[0] / 4):, int(warped.shape[1] / 2):], axis=0)\n r_center = np.argmax(np.convolve(window, r_sum)) - window_width / 2 + int(warped.shape[1] / 2)\n\n # Add what we found for the first layer\n window_centroids.append((l_center, r_center))\n\n # Go through each layer looking for max pixel locations\n for level in range(1, (int)(warped.shape[0] / window_height)):\n # convolve the window into the vertical slice of the image\n image_layer = np.sum(\n warped[int(warped.shape[0] - (level + 1) * window_height):int(warped.shape[0] - level * window_height), :],\n axis=0)\n conv_signal = np.convolve(window, image_layer)\n # Find the best left centroid by using past left center as a reference\n # Use window_width/2 as offset because convolution signal reference is at right side of window, not center of window\n offset = window_width / 2\n l_min_index = int(max(l_center + offset - margin, 0))\n l_max_index = int(min(l_center + offset + margin, warped.shape[1]))\n l_center = np.argmax(conv_signal[l_min_index:l_max_index]) + l_min_index - offset\n # Find the best right centroid by using past right center as a reference\n r_min_index = int(max(r_center + offset - margin, 0))\n r_max_index = int(min(r_center + offset + margin, warped.shape[1]))\n r_center = np.argmax(conv_signal[r_min_index:r_max_index]) + r_min_index - offset\n # Add what we found for that layer\n window_centroids.append((l_center, r_center))\n\n return window_centroids\n\ndef sliding_window_convolution(warped):\n # window settings\n window_width = 50\n window_height = 80 # Break image into 9 vertical layers since image height is 720\n margin = 100 # How much to slide left and right for searching\n\n window_centroids = find_window_centroids(warped, window_width, window_height, margin)\n\n # If we found any window centers\n if len(window_centroids) > 0:\n\n # Points used to draw all the left and right windows\n l_points = np.zeros_like(warped)\n r_points = np.zeros_like(warped)\n\n # Go through each level and draw the windows\n for level in range(0, len(window_centroids)):\n # Window_mask is a function to draw window areas\n l_mask = window_mask(window_width, window_height, warped, window_centroids[level][0], level)\n r_mask = window_mask(window_width, window_height, warped, window_centroids[level][1], level)\n # Add graphic points from window mask here to total pixels found\n l_points[(l_points == 255) | ((l_mask == 1))] = 255\n r_points[(r_points == 255) | ((r_mask == 1))] = 255\n\n # Draw the results\n template = np.array(r_points + l_points, np.uint8) # add both left and right window pixels together\n zero_channel = np.zeros_like(template) # create a zero color channle\n template = np.array(cv2.merge((zero_channel, template, zero_channel)), np.uint8) # make window pixels green\n warpage = np.array(cv2.merge((warped, warped, warped)),\n np.uint8) # making the original road pixels 3 color channels\n output = cv2.addWeighted(warpage, 1, template, 0.5, 0.0) # overlay the orignal road image with window results\n\n # If no window centers found, just display orginal road image\n else:\n output = np.array(cv2.merge((warped, warped, warped)), np.uint8)\n\n return output\n\ndef get_curvature(ploty, left_fit, right_fit, leftx, rightx, xm_per_pix = 3.7 / 700, ym_per_pix= 30 / 720):\n # Define y-value where we want radius of curvature\n # I'll choose the maximum y-value, corresponding to the bottom of the image\n y_eval = np.max(ploty)\n #left_curverad = ((1 + (2 * left_fit[0] * y_eval + left_fit[1]) ** 2) ** 1.5) / np.absolute(2 * left_fit[0])\n #right_curverad = ((1 + (2 * right_fit[0] * y_eval + right_fit[1]) ** 2) ** 1.5) / np.absolute(2 * right_fit[0])\n #print(left_curverad, right_curverad)\n # Example values: 1926.74 1908.48\n\n # Define conversions in x and y from pixels space to meters\n #ym_per_pix = 30 / 720 # meters per pixel in y dimension\n #xm_per_pix = 3.7 / 700 # meters per pixel in x dimension\n\n # Fit new polynomials to x,y in world space\n left_fit_cr = np.polyfit(ploty * ym_per_pix, leftx * xm_per_pix, 2)\n right_fit_cr = np.polyfit(ploty * ym_per_pix, rightx * xm_per_pix, 2)\n # Calculate the new radii of curvature\n left_curverad = ((1 + (2 * left_fit_cr[0] * y_eval * ym_per_pix + left_fit_cr[1]) ** 2) ** 1.5) / np.absolute(\n 2 * left_fit_cr[0])\n right_curverad = ((1 + (2 * right_fit_cr[0] * y_eval * ym_per_pix + right_fit_cr[1]) ** 2) ** 1.5) / np.absolute(\n 2 * right_fit_cr[0])\n\n return left_curverad, right_curverad\n\ndef draw(undist, image, warped, left_fitx, right_fitx, ploty, Minv, left_curverad, right_curverad, line_base_pos, detected, left_curverad_current, right_curverad_current, line_base_pos_current, straightAway=False):\n # Create an image to draw the lines on\n warp_zero = np.zeros_like(warped).astype(np.uint8)\n color_warp = np.dstack((warp_zero, warp_zero, warp_zero))\n\n # Recast the x and y points into usable format for cv2.fillPoly()\n pts_left = np.array([np.transpose(np.vstack([left_fitx, ploty]))])\n pts_right = np.array([np.flipud(np.transpose(np.vstack([right_fitx, ploty])))])\n pts = np.hstack((pts_left, pts_right))\n\n # Draw the lane onto the warped blank image\n cv2.fillPoly(color_warp, np.int_([pts]), (0, 255, 0))\n\n # Warp the blank back to original image space using inverse perspective matrix (Minv)\n newwarp = cv2.warpPerspective(color_warp, Minv, (image.shape[1], image.shape[0]))\n # Combine the result with the original image\n result = cv2.addWeighted(undist, 1, newwarp, 0.3, 0)\n plt.imshow(result)\n\n # write curvature and position findings\n font = cv2.FONT_HERSHEY_SIMPLEX\n fontColor = (255, 255, 255)\n if(not detected):\n fontColor = (255,0,0)\n cv2.putText(result, 'Radius of left line curvature: ' + str(left_curverad) + ' compared to '+str(left_curverad_current)+ ' m', (50, 20), font, 1, fontColor, 2, cv2.LINE_AA)\n cv2.putText(result, 'Radius of right line curvature: ' + str(right_curverad) + ' compared to '+str(right_curverad_current)+ ' m', (50, 50), font, 1, fontColor, 2,\n cv2.LINE_AA)\n cv2.putText(result, 'Vehicle position : %.2f m %s of center compared to %s' % (abs(line_base_pos), 'left' if line_base_pos < 0 else 'right', str(line_base_pos_current)), (50, 80),\n font, 1, fontColor, 2, cv2.LINE_AA)\n if(straightAway):\n cv2.putText(result, 'Straight Lanes Detected', (50, 100), font, 1, fontColor, 2, cv2.LINE_AA)\n\n return result\n\ndef get_vehicle_position(image, left_fitx, right_fitx, xm_per_pix):\n # determine vehicle position\n vehicle_pos = image.shape[1] // 2\n middle = (left_fitx[-1] + right_fitx[-1]) // 2\n line_base_pos = (vehicle_pos - middle) * xm_per_pix\n\n return line_base_pos\n\n\n","sub_path":"Helper_Functions.py","file_name":"Helper_Functions.py","file_ext":"py","file_size_in_byte":26825,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"626813099","text":"\"\"\"\n\n DBMANAGER HANDLES ALL INTERACTION WITH DATABASE\n\n - Connection\n - Receiving Login\n - Loading of data (e.g. Loading available slots)\n - Updating of data (e.g. Confirming of slots)\n - Structuring of data\n\n FOR TESTING PURPOSES:\n \n Running the following command simulates a login:\n \n $ python3 DBManager.py login\n\n Running the following command will prompt user to re-populate database:\n\n $ python3 DBManager.py\n\n\"\"\"\n\nimport time\nfrom threading import Timer\nfrom libdw import pyrebase\nimport TemplateData\nimport copy\n\nFIREBASE_ENDPOINT = 'https://basic-dc724.firebaseio.com/'\nREFRESH_RATE = 60 #firebase calls are still a bottleneck\n\nconfig = {\n \"apiKey\": \"AIzaSyByqBZnJMeBo9CjNn111hRYWo34ipRIOwM\",\n \"authDomain\": \"basic-dc724.firebaseapp.com\",\n \"databaseURL\": \"https://basic-dc724.firebaseio.com/\",\n \"storageBucket\": \"basic-dc724.appspot.com\"\n}\n\nclass DBManager: \n def __init__(self, loginCallback=None):\n self.loggedIn = False\n self.structured_data = {} \n self.loginCallback = loginCallback\n \n #connect\n firebase = pyrebase.initialize_app(config)\n self.db = firebase.database() \n \n def cleanup(self):\n print('Cleaning Up...')\n self.cleanup = True\n\n def InitalizeFirebase(self):\n confirmed = input('Warning: Initializing removes all current data. Continue? y/n\\n')\n \n if confirmed != 'y':\n return\n\n print('Initializing database...')\n\n shouldLoginStudent = input('Include template \\'current\\' student user? y/n\\n')\n\n data = TemplateData.loggedindbtemplate if shouldLoginStudent else TemplateData.dbtemplate\n \n self.db.update(data)\n \n print('Initializing done!')\n\n #For testing purposes, this function lets you simulate the tapping of a card and login\n def FirebaseForceLogin(self):\n current = self.db.child('students/{0}'.format('1003501')).get().val()\n self.db.update({'current': current})\n\n def login(self, structured_data):\n self.loggedIn = True\n self.structured_data = structured_data\n\n print('USER LOGGED IN') \n\n if self.loginCallback != None:\n self.loginCallback(structured_data)\n\n def logout(self):\n self.db.child('current').remove()\n self.loggedIn = False\n self.structured_data = {} \n self.beginCheckLoginCycle() \n \n def beginCheckLoginCycle(self):\n t = Timer(1/REFRESH_RATE, self._beginCheckLoginCycle)\n t.start() \n \n #this is an internal function because it has to be run with a timer (so that it is multithreaded)\n def _beginCheckLoginCycle(self): \n #if it is logged in, no more need to check\n if self.loggedIn or self.cleanup == True:\n return\n\n print('Reading from firebase..')\n\n #get current student (logged in)\n current = self.db.child('current').get().val()\n if current != None: \n full_db = self.db.get().val()\n structured_data = self.structure_data(full_db, current)\n self.full_data = full_db\n self.login(structured_data)\n return\n\n #call itself to keep checking database\n time.sleep(1/REFRESH_RATE)\n self.beginCheckLoginCycle()\n\n #retrieves all data again, structures it, then returns it\n def reloadStructuredData(self):\n \n print('Reloading all data...')\n current = self.db.child('current').get().val()\n\n if current != None: \n full_db = self.db.get().val()\n self.structured_data = self.structure_data(full_db, current)\n self.full_data = full_db \n return self.structured_data\n else:\n print('ERROR: NO CURRENT USER')\n return None\n\n #takes in the full database and structures the data accordingly, making the links between the separate tables\n def structure_data(self, full_data, current_data): \n #make a replica of the student details as a starting point\n current_student = copy.deepcopy(current_data)\n output = {}\n\n #step 1: get all subjects that the student has\n subjects = []\n for subject in full_data['modules']:\n if subject['id'] in current_data['modules']:\n \n #step 2: for each subject, get the professors that belong to that subject\n professors = []\n for prof in full_data['professors']:\n if subject['id'] in prof['modules']:\n \n \n #step 3: for each professor, get the slots that belong to that professor\n slots = [] \n for slot in full_data['slots'].values():\n if slot['prof_id'] == prof['id']:\n slots.append(copy.deepcopy(slot)) \n\n profdata = copy.deepcopy(prof)\n profdata['slots'] = slots\n professors.append(profdata)\n \n subjectdata = copy.deepcopy(subject)\n subjectdata['professors'] = professors\n subjects.append(subjectdata) \n \n output['modules'] = subjects \n output['current'] = current_student \n\n return output\n\n #confirm the slot by updating firebase and allocating the currently logged in student's id as the student of the slot\n #returns the slot that was confirmed\n def confirm_slot(self, slot_uuid):\n print('Confirming Slot...') \n allslots = self.full_data['slots']\n student = self.full_data['current'] \n student_id = student['id']\n \n price = 50\n newcredits = student['credits'] - price \n\n if newcredits < 0: \n return None\n \n print('new credits: ', newcredits) \n\n #update database with student_id, signifying the slot has been booked, and allocating the new credits amount\n self.db.update({\n 'slots/{0}/student_id'.format(slot_uuid): student_id,\n 'students/{0}/credits'.format(student_id) : newcredits,\n 'current/credits' : newcredits\n }) \n\n return self.db.child('slots/{0}'.format(slot_uuid)).get().val()\n\n def get_student(self):\n return self.structure_data['current']\n\n def get_prof_with_id(self, id): \n for prof in self.full_data['professors']:\n if prof['id'] == id:\n return prof\n\n\n \n \n \nimport sys\nif __name__ == '__main__':\n db = DBManager()\n\n if len(sys.argv) > 1 and sys.argv[1] == 'login':\n db.FirebaseForceLogin()\n else: \n db.InitalizeFirebase() \n\n","sub_path":"DBManager.py","file_name":"DBManager.py","file_ext":"py","file_size_in_byte":6986,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"306234088","text":"# Macros and libararies\nfrom math import isinf\nfrom numpy import array, zeros, full, argmin, inf, ndim\nimport numpy as np\nimport torch as T\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\ndef _traceback(D):\n i, j = array(D.shape) - 2\n p, q = [i], [j]\n while (i > 0) or (j > 0):\n tb = argmin((D[i, j], D[i, j + 1], D[i + 1, j]))\n if tb == 0:\n i -= 1\n j -= 1\n elif tb == 1:\n i -= 1\n else: # (tb == 2):\n j -= 1\n p.insert(0, i)\n q.insert(0, j)\n return array(p), array(q)\n\ndef dtw(x, y, dist, warp=1, w=inf, s=1.0):\n \"\"\"\n Computes Dynamic Time Warping (DTW) of two sequences.\n :param array x: N1*M array\n :param array y: N2*M array\n :param func dist: distance used as cost measure\n :param int warp: how many shifts are computed.\n :param int w: window size limiting the maximal distance between indices of matched entries |i,j|.\n :param float s: weight applied on off-diagonal moves of the path. As s gets larger, the warping path is increasingly biased towards the diagonal\n Returns the minimum distance, the cost matrix, the accumulated cost matrix, and the wrap path.\n \"\"\"\n assert len(x)\n assert len(y)\n assert isinf(w) or (w >= abs(len(x) - len(y)))\n assert s > 0\n r, c = len(x), len(y)\n if not isinf(w):\n D0 = full((r + 1, c + 1), inf)\n for i in range(1, r + 1):\n D0[i, max(1, i - w):min(c + 1, i + w + 1)] = 0\n D0[0, 0] = 0\n else:\n D0 = zeros((r + 1, c + 1))\n D0[0, 1:] = inf\n D0[1:, 0] = inf\n D1 = D0[1:, 1:] # view\n for i in range(r):\n for j in range(c):\n if (isinf(w) or (max(0, i - w) <= j <= min(c, i + w))):\n D1[i, j] = dist(x[i], y[j])\n C = D1.copy()\n jrange = range(c)\n for i in range(r):\n if not isinf(w):\n jrange = range(max(0, i - w), min(c, i + w + 1))\n for j in jrange:\n min_list = [D0[i, j]]\n for k in range(1, warp + 1):\n i_k = min(i+k, r)\n j_k = min(j+k, c)\n min_list += [D0[i_k, j] * s, D0[i, j_k] * s]\n D1[i, j] += min(min_list)\n if len(x) == 1:\n path = zeros(len(y)), range(len(y))\n elif len(y) == 1:\n path = range(len(x)), zeros(len(x))\n else:\n path = _traceback(D0)\n return D1[-1, -1], C, D1, path\n\n\n\n# We define two sequences x, y as numpy array\n# where y is actually a sub-sequence from x\nx = np.array([2, 0, 1, 1, 2, 4, 2, 1, 2, 0]).reshape(-1, 1)\ny = np.array([1, 1, 2, 4, 2, 1, 2, 0]).reshape(-1, 1)\n\n\neuclidean_norm = lambda x, y: np.abs(x - y)\n\nd, cost_matrix, acc_cost_matrix, path = dtw(x, y, dist=euclidean_norm)\n\n\n# You can also visualise the accumulated cost and the shortest path\nimport matplotlib.pyplot as plt\n\nplt.imshow(acc_cost_matrix.T, origin='lower', cmap='gray', interpolation='nearest')\nplt.plot(path[0], path[1], 'w')\n#plt.show()\n\n\n\n\n# this cannot handle inf, -\\rho * x too big, e^{- \\rho * x} close to 0\ndef smooth_min(x, rho=10):\n eps = 1e-12\n val = -1/rho * T.log(T.mean(T.exp(x * (-rho))) + eps)\n assert val!=float('inf'), T.mean(T.exp(x * (-rho)))\n return val\n\nrho = 10\nx = T.tensor([100.0, 2.0231, 100.0])\nprint (smooth_min(x,rho))\n\n\n# 1d min func is 1\n\n\n# this will serve as a loss function\ndef _traceback(D):\n i, j = array(D.shape) - 2\n p, q = [i], [j]\n while (i > 0) or (j > 0):\n tb = argmin((D[i, j], D[i, j + 1], D[i + 1, j]))\n if tb == 0:\n i -= 1\n j -= 1\n elif tb == 1:\n i -= 1\n else: # (tb == 2):\n j -= 1\n p.insert(0, i)\n q.insert(0, j)\n return array(p), array(q)\n\n\ndef diff_dtw_loss(x, y, dist, warp=1, w=inf, s=1.0, rho=40):\n \"\"\" differentiable dtw, takes two sequences and\n compute the distance under the metric\n x, y is a tensor seq_len x dim\n dist is a bi-variate function\n \"\"\"\n\n assert x.shape[0]\n assert y.shape[0]\n assert isinf(w) or (w >= abs(len(x) - len(y)))\n assert s > 0\n\n MAX_VAL = 1e2\n\n r, c = x.shape[0], y.shape[0]\n if not isinf(w):\n D0 = T.full((r + 1, c + 1), MAX_VAL)\n for i in range(1, r + 1):\n D0[i, max(1, i - w):min(c + 1, i + w + 1)] = 0\n D0[0, 0] = 0\n else:\n D0 = T.zeros(r + 1, c + 1)\n D0[0, 1:] = MAX_VAL\n D0[1:, 0] = MAX_VAL\n D1 = D0[1:, 1:] # view\n for i in range(r):\n for j in range(c):\n #print(\"dtw size\", x.size(), y.size())\n if (isinf(w) or (max(0, i - w) <= j <= min(c, i + w))):\n D1[i, j] = dist(x[0][i], y[0][j])\n C = D1.clone()\n jrange = range(c)\n for i in range(r):\n if not isinf(w):\n jrange = range(max(0, i - w), min(c, i + w + 1))\n for j in jrange:\n min_list = D0[i, j]\n for k in range(1, warp + 1):\n # print(i+k, r)\n i_k = min(i + k, r)\n j_k = min(j + k, c)\n min_list = T.cat((T.tensor([min_list], requires_grad=True), \\\n T.tensor([D0[i_k, j] * s], requires_grad=True), \\\n T.tensor([D0[i, j_k] * s], requires_grad=True)))\n # Softmin is NOT a smooth min function\n min_val = smooth_min(min_list, rho)\n # print('min:', i, j, min_val, min_list)\n D1[i, j] = D1[i, j] + min_val\n if len(x) == 1:\n path = zeros(len(y)), range(len(y))\n elif len(y) == 1:\n path = range(len(x)), zeros(len(x))\n else:\n path = _traceback(D0)\n return D1[-1, -1], C, D1, path\n\n\n\nx = np.array([2, 0, 1, 1, 2, 4, 2, 1, 2, 0], dtype=np.float32).reshape(-1, 1)\ny = np.array([1, 1, 2, 4, 2, 1, 2, 0], dtype=np.float32).reshape(-1, 1)\n\n\ntensor_x = T.tensor(T.from_numpy(x), requires_grad=True)\ntensor_y = T.tensor(T.from_numpy(y), requires_grad=True)\n\n\neuclidean_norm = lambda x, y: T.abs(x - y)\n\n#diff_d, diff_cost_matrix, diff_acc_cost_matrix, diff_path = diff_dtw_loss(tensor_x, tensor_y, dist=euclidean_norm)\n\n#print('distance', diff_d, 'diff distance:', diff_d.detach().numpy())\n#diff_acc_cost_matrix = diff_acc_cost_matrix.detach().numpy()\n# print(acc_cost_matrix)\n\n\n# You can also visualise the accumulated cost and the shortest path\nimport matplotlib.pyplot as plt\n\n#fig, (ax1, ax2) = plt.subplots(1, 2)\n#fig.suptitle('Original and Differentiable Accumated Cost Matrix')\n#ax1.imshow(acc_cost_matrix.T, origin='lower', cmap='gray', interpolation='nearest')\n#ax1.plot(path[0], path[1], 'w')\n#ax2.imshow(diff_acc_cost_matrix.T, origin='lower', cmap='gray', interpolation='nearest')\n#ax2.plot(diff_path[0], diff_path[1], 'w')\n\n\n# plt.imshow(acc_cost_matrix.T, origin='lower', cmap='gray', interpolation='nearest')\n# plt.plot(path[0], path[1], 'w')\n# plt.show()\n\n\nimport torch as T\nfrom torch.nn import functional as F\n\nfrom torch.nn.modules import Module\n\nclass _Loss(Module):\n def __init__(self, size_average=None, reduce=None, reduction='mean', _Reduction=None):\n super(_Loss, self).__init__()\n if size_average is not None or reduce is not None:\n self.reduction = _Reduction.legacy_get_string(size_average, reduce)\n else:\n self.reduction = reduction\n\n\nclass DTW_Loss(_Loss):\n def __init__(self, rho=10, size_average=None, reduce=None, reduction='mean'):\n super(DTW_Loss, self).__init__(size_average, reduce, reduction)\n self.rho = rho\n\n def forward(self, output, target):\n # batch x seq_len x dim\n if ndim(output)==3:\n dist = []\n for b in range(output.size(0)):\n #print(\"sizes\", output.size(), target.size())\n d_b, cost_matrix, diff_acc_cost_matrix, diff_path = diff_dtw_loss(output[b], target[b], dist=euclidean_norm, rho=rho)\n dist.append(d_b)\n d = T.mean(T.stack(dist))\n else:\n d, cost_matrix, diff_acc_cost_matrix, diff_path = diff_dtw_loss(output, target, dist=euclidean_norm, rho=rho)\n #F.mse_loss(output, target, reduction=self.reduction)\n loss_val = d #.detach().numpy()\n return loss_val\n\nx = np.array([2, 0, 1, 1, 2, 4, 2, 1, 2, 0], dtype=np.float32).reshape(1, -1, 1)\ny = np.array([1, 1, 2, 4, 2, 1, 2, 0], dtype=np.float32).reshape(1, -1, 1)\n\ntensor_x = T.tensor(T.from_numpy(x),requires_grad=True)\ntensor_y = T.tensor(T.from_numpy(y),requires_grad=True)\nloss_vals = []\n\nrhos = np.linspace(1, 10,10)\n#for rho in rhos:\n #print(rho)\n #my_loss = DTW_Loss(rho)\n #loss_vals.append(my_loss(tensor_x, tensor_y))\n","sub_path":"Peg In Hole HDR-IL/differentiableDP.py","file_name":"differentiableDP.py","file_ext":"py","file_size_in_byte":8531,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"324049835","text":"# pearson.py\n# Pearson correlation coefficient\n#\n# Luana Goncalves\n# 02.jun.2017\n\nimport random\nimport numpy as np\nfrom math import sqrt\n\ndef pearson(x,y):\n\n dif_x = np.mean(x) - x\n dif_y = np.mean(y) - y\n\n num = np.sum(dif_x*dif_y)\n den = sqrt((np.sum(dif_x**2))*(np.sum(dif_y**2)))\n\n r = num/den\n\n return r\n","sub_path":"pearson.py","file_name":"pearson.py","file_ext":"py","file_size_in_byte":327,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"104749277","text":"\"\"\"\nCopyright (c) 2016-present, Facebook, Inc.\nAll rights reserved.\n\nThis source code is licensed under the BSD-style license found in the\nLICENSE file in the root directory of this source tree. An additional grant\nof patent rights can be found in the PATENTS file in the same directory.\n\"\"\"\n\nfrom magma.common.redis.client import get_default_client\nfrom magma.common.redis.containers import RedisDict\nfrom magma.common.redis.mocks.mock_redis import MockRedis\nfrom magma.common.redis.serializers import get_proto_deserializer, \\\n get_proto_serializer\nfrom orc8r.protos.service303_pb2 import LogVerbosity\nfrom unittest import TestCase, main, mock\n\n\nclass RedisTests(TestCase):\n \"\"\"\n Tests for the RedisDict container\n \"\"\"\n @mock.patch(\"redis.Redis\", MockRedis)\n def setUp(self):\n # Use arbitrary orc8r proto to test with\n self._dict = RedisDict(\n get_default_client(),\n \"unittest\",\n get_proto_serializer(),\n get_proto_deserializer(LogVerbosity))\n\n @mock.patch(\"redis.Redis\", MockRedis)\n def test_insert(self):\n expected = LogVerbosity(verbosity=0)\n expected2 = LogVerbosity(verbosity=1)\n\n # insert proto\n self._dict['key1'] = expected\n version = self._dict.get_version(\"key1\")\n actual = self._dict['key1']\n self.assertEqual(1, version)\n self.assertEqual(expected, actual)\n\n # update proto\n self._dict['key1'] = expected2\n version2 = self._dict.get_version(\"key1\")\n actual2 = self._dict['key1']\n self.assertEqual(2, version2)\n self.assertEqual(expected2, actual2)\n\n @mock.patch(\"redis.Redis\", MockRedis)\n def test_missing_version(self):\n missing_version = self._dict.get_version(\"key2\")\n self.assertEqual(0, missing_version)\n\n @mock.patch(\"redis.Redis\", MockRedis)\n def test_delete(self):\n expected = LogVerbosity(verbosity=2)\n self._dict['key3'] = expected\n\n actual = self._dict['key3']\n self.assertEqual(expected, actual)\n\n self._dict.pop('key3')\n self.assertRaises(KeyError, self._dict.__getitem__, 'key3')\n\n\nif __name__ == \"__main__\":\n main()\n","sub_path":"orc8r/gateway/python/magma/common/redis/tests/dict_tests.py","file_name":"dict_tests.py","file_ext":"py","file_size_in_byte":2196,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"504846289","text":"#\n# Copyright 2015 Benjamin Kiessling\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain 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,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express\n# or implied. See the License for the specific language governing\n# permissions and limitations under the License.\n\"\"\"\nTraining loop interception helpers\n\"\"\"\nimport re\nimport torch\nimport pathlib\nimport logging\nimport warnings\nimport numpy as np\nimport torch.nn.functional as F\nimport pytorch_lightning as pl\n\nfrom functools import partial\nfrom torch.multiprocessing import Pool\nfrom torch.optim import lr_scheduler\nfrom typing import Callable, Dict, Optional, Sequence, Union, Any, List\nfrom pytorch_lightning.callbacks import Callback, EarlyStopping\n\nfrom kraken.lib import models, vgsl, default_specs, progress\nfrom kraken.lib.xml import preparse_xml_data\nfrom kraken.lib.util import make_printable\nfrom kraken.lib.codec import PytorchCodec\nfrom kraken.lib.dataset import (ArrowIPCRecognitionDataset, BaselineSet,\n GroundTruthDataset, PolygonGTDataset,\n ImageInputTransforms, compute_error,\n collate_sequences)\nfrom kraken.lib.models import validate_hyper_parameters\nfrom kraken.lib.exceptions import KrakenInputException, KrakenEncodeException\n\nfrom torch.utils.data import DataLoader, random_split, Subset\n\n\nlogger = logging.getLogger(__name__)\n\n\ndef _star_fun(fun, kwargs):\n try:\n return fun(**kwargs)\n except FileNotFoundError as e:\n logger.warning(f'{e.strerror}: {e.filename}. Skipping.')\n except KrakenInputException as e:\n logger.warning(str(e))\n return None\n\n\nclass KrakenTrainer(pl.Trainer):\n def __init__(self,\n enable_progress_bar: bool = True,\n enable_summary: bool = True,\n min_epochs: int = 5,\n max_epochs: int = 100,\n pb_ignored_metrics: Sequence[str] = ('loss', 'val_metric'),\n move_metrics_to_cpu: bool = True,\n *args,\n **kwargs):\n kwargs['logger'] = False\n kwargs['enable_checkpointing'] = False\n kwargs['enable_progress_bar'] = enable_progress_bar\n kwargs['min_epochs'] = min_epochs\n kwargs['max_epochs'] = max_epochs\n kwargs['callbacks'] = ([] if 'callbacks' not in kwargs else kwargs['callbacks'])\n kwargs['move_metrics_to_cpu'] = move_metrics_to_cpu\n if not isinstance(kwargs['callbacks'], list):\n kwargs['callbacks'] = [kwargs['callbacks']]\n\n if enable_progress_bar:\n progress_bar_cb = progress.KrakenTrainProgressBar(ignored_metrics=pb_ignored_metrics)\n kwargs['callbacks'].append(progress_bar_cb)\n\n if enable_summary:\n from pytorch_lightning.callbacks import RichModelSummary\n summary_cb = RichModelSummary(max_depth=2)\n kwargs['callbacks'].append(summary_cb)\n kwargs['enable_model_summary'] = False\n\n kwargs['callbacks'].extend([KrakenSetOneChannelMode(), KrakenSaveModel()])\n super().__init__(*args, **kwargs)\n\n def fit(self, *args, **kwargs):\n with warnings.catch_warnings():\n warnings.filterwarnings(action='ignore', category=UserWarning,\n message='The dataloader,')\n super().fit(*args, **kwargs)\n\n\nclass KrakenSetOneChannelMode(Callback):\n \"\"\"\n Callback that sets the one_channel_mode of the model after the first epoch.\n \"\"\"\n def on_train_epoch_end(self, trainer: \"pl.Trainer\", pl_module: \"pl.LightningModule\") -> None:\n # fill one_channel_mode after 1 iteration over training data set\n if not trainer.sanity_checking and trainer.current_epoch == 0 and trainer.model.nn.model_type == 'recognition':\n ds = getattr(pl_module, 'train_set', None)\n if not ds and trainer.datamodule:\n ds = trainer.datamodule.train_set\n im_mode = ds.dataset.im_mode\n if im_mode in ['1', 'L']:\n logger.info(f'Setting model one_channel_mode to {im_mode}.')\n trainer.model.nn.one_channel_mode = im_mode\n\n\nclass KrakenSaveModel(Callback):\n \"\"\"\n Kraken's own serialization callback instead of pytorch's.\n \"\"\"\n def on_validation_end(self, trainer: \"pl.Trainer\", pl_module: \"pl.LightningModule\") -> None:\n if not trainer.sanity_checking:\n trainer.model.nn.hyper_params['completed_epochs'] += 1\n metric = float(trainer.logged_metrics['val_metric']) if 'val_metric' in trainer.logged_metrics else -1.0\n trainer.model.nn.user_metadata['accuracy'].append((trainer.global_step, metric))\n trainer.model.nn.user_metadata['metrics'].append((trainer.global_step, {k: float(v) for k, v in trainer.logged_metrics.items()}))\n\n logger.info('Saving to {}_{}'.format(trainer.model.output, trainer.current_epoch))\n trainer.model.nn.save_model(f'{trainer.model.output}_{trainer.current_epoch}.mlmodel')\n\n\nclass RecognitionModel(pl.LightningModule):\n def __init__(self,\n hyper_params: Dict[str, Any] = None,\n output: str = 'model',\n spec: str = default_specs.RECOGNITION_SPEC,\n append: Optional[int] = None,\n model: Optional[Union[pathlib.Path, str]] = None,\n reorder: Union[bool, str] = True,\n training_data: Union[Sequence[Union[pathlib.Path, str]], Sequence[Dict[str, Any]]] = None,\n evaluation_data: Optional[Union[Sequence[Union[pathlib.Path, str]], Sequence[Dict[str, Any]]]] = None,\n partition: Optional[float] = 0.9,\n binary_dataset_split: bool = False,\n num_workers: int = 1,\n load_hyper_parameters: bool = False,\n repolygonize: bool = False,\n force_binarization: bool = False,\n format_type: str = 'path',\n codec: Optional[Dict] = None,\n resize: str = 'fail'):\n \"\"\"\n A LightningModule encapsulating the training setup for a text\n recognition model.\n\n Setup parameters (load, training_data, evaluation_data, ....) are\n named, model hyperparameters (everything in\n `kraken.lib.default_specs.RECOGNITION_HYPER_PARAMS`) are in in the\n `hyper_params` argument.\n\n Args:\n hyper_params (dict): Hyperparameter dictionary containing all fields\n from\n kraken.lib.default_specs.RECOGNITION_HYPER_PARAMS\n **kwargs: Setup parameters, i.e. CLI parameters of the train() command.\n \"\"\"\n super().__init__()\n hyper_params_ = default_specs.RECOGNITION_HYPER_PARAMS\n if model:\n logger.info(f'Loading existing model from {model} ')\n self.nn = vgsl.TorchVGSLModel.load_model(model)\n\n if self.nn.model_type not in [None, 'recognition']:\n raise ValueError(f'Model {model} is of type {self.nn.model_type} while `recognition` is expected.')\n\n if load_hyper_parameters:\n hp = self.nn.hyper_params\n else:\n hp = {}\n hyper_params_.update(hp)\n else:\n self.nn = None\n\n if hyper_params:\n hyper_params_.update(hyper_params)\n self.save_hyperparameters(hyper_params_)\n\n self.reorder = reorder\n self.append = append\n self.model = model\n self.num_workers = num_workers\n self.resize = resize\n self.format_type = format_type\n self.output = output\n\n self.best_epoch = 0\n self.best_metric = 0.0\n\n DatasetClass = GroundTruthDataset\n valid_norm = True\n if format_type in ['xml', 'page', 'alto']:\n logger.info(f'Parsing {len(training_data)} XML files for training data')\n training_data = preparse_xml_data(training_data, format_type, repolygonize)\n if evaluation_data:\n logger.info(f'Parsing {len(evaluation_data)} XML files for validation data')\n evaluation_data = preparse_xml_data(evaluation_data, format_type, repolygonize)\n if binary_dataset_split:\n logger.warning('Internal binary dataset splits are enabled but using non-binary dataset files. Will be ignored.')\n binary_dataset_split = False\n DatasetClass = PolygonGTDataset\n valid_norm = False\n elif format_type == 'binary':\n DatasetClass = ArrowIPCRecognitionDataset\n if repolygonize:\n logger.warning('Repolygonization enabled in `binary` mode. Will be ignored.')\n valid_norm = False\n logger.info(f'Got {len(training_data)} binary dataset files for training data')\n training_data = [{'file': file} for file in training_data]\n if evaluation_data:\n logger.info(f'Got {len(evaluation_data)} binary dataset files for validation data')\n evaluation_data = [{'file': file} for file in evaluation_data]\n elif format_type == 'path':\n if force_binarization:\n logger.warning('Forced binarization enabled in `path` mode. Will be ignored.')\n force_binarization = False\n if repolygonize:\n logger.warning('Repolygonization enabled in `path` mode. Will be ignored.')\n if binary_dataset_split:\n logger.warning('Internal binary dataset splits are enabled but using non-binary dataset files. Will be ignored.')\n binary_dataset_split = False\n logger.info(f'Got {len(training_data)} line strip images for training data')\n training_data = [{'image': im} for im in training_data]\n if evaluation_data:\n logger.info(f'Got {len(evaluation_data)} line strip images for validation data')\n evaluation_data = [{'image': im} for im in evaluation_data]\n valid_norm = True\n # format_type is None. Determine training type from length of training data entry\n elif not format_type:\n if len(training_data[0]) >= 4:\n DatasetClass = PolygonGTDataset\n valid_norm = False\n else:\n if force_binarization:\n logger.warning('Forced binarization enabled with box lines. Will be ignored.')\n force_binarization = False\n if repolygonize:\n logger.warning('Repolygonization enabled with box lines. Will be ignored.')\n if binary_dataset_split:\n logger.warning('Internal binary dataset splits are enabled but using non-binary dataset files. Will be ignored.')\n binary_dataset_split = False\n else:\n raise ValueError(f'format_type {format_type} not in [alto, page, xml, path, binary].')\n\n spec = spec.strip()\n if spec[0] != '[' or spec[-1] != ']':\n raise ValueError(f'VGSL spec {spec} not bracketed')\n self.spec = spec\n # preparse input sizes from vgsl string to seed ground truth data set\n # sizes and dimension ordering.\n if not self.nn:\n blocks = spec[1:-1].split(' ')\n m = re.match(r'(\\d+),(\\d+),(\\d+),(\\d+)', blocks[0])\n if not m:\n raise ValueError(f'Invalid input spec {blocks[0]}')\n batch, height, width, channels = [int(x) for x in m.groups()]\n else:\n batch, channels, height, width = self.nn.input\n\n self.transforms = ImageInputTransforms(batch,\n height,\n width,\n channels,\n self.hparams.pad,\n valid_norm,\n force_binarization)\n\n self.example_input_array = torch.Tensor(batch,\n channels,\n height if height else 32,\n width if width else 400)\n\n if 'file_system' in torch.multiprocessing.get_all_sharing_strategies():\n logger.debug('Setting multiprocessing tensor sharing strategy to file_system')\n torch.multiprocessing.set_sharing_strategy('file_system')\n\n if evaluation_data:\n train_set = self._build_dataset(DatasetClass, training_data)\n self.train_set = Subset(train_set, range(len(train_set)))\n val_set = self._build_dataset(DatasetClass, evaluation_data)\n self.val_set = Subset(val_set, range(len(val_set)))\n elif binary_dataset_split:\n train_set = self._build_dataset(DatasetClass, training_data, split_filter='train')\n self.train_set = Subset(train_set, range(len(train_set)))\n val_set = self._build_dataset(DatasetClass, training_data, split_filter='validation')\n self.val_set = Subset(val_set, range(len(val_set)))\n logger.info(f'Found {len(self.train_set)} (train) / {len(self.val_set)} (val) samples in pre-encoded dataset')\n else:\n train_set = self._build_dataset(DatasetClass, training_data)\n train_len = int(len(train_set)*partition)\n val_len = len(train_set) - train_len\n logger.info(f'No explicit validation data provided. Splitting off '\n f'{val_len} (of {len(train_set)}) samples to validation '\n 'set. (Will disable alphabet mismatch detection.)')\n self.train_set, self.val_set = random_split(train_set, (train_len, val_len))\n\n if len(self.train_set) == 0 or len(self.val_set) == 0:\n raise ValueError('No valid training data was provided to the train '\n 'command. Please add valid XML, line, or binary data.')\n\n logger.info(f'Training set {len(self.train_set)} lines, validation set '\n f'{len(self.val_set)} lines, alphabet {len(train_set.alphabet)} '\n 'symbols')\n alpha_diff_only_train = set(self.train_set.dataset.alphabet).difference(set(self.val_set.dataset.alphabet))\n alpha_diff_only_val = set(self.val_set.dataset.alphabet).difference(set(self.train_set.dataset.alphabet))\n if alpha_diff_only_train:\n logger.warning(f'alphabet mismatch: chars in training set only: '\n f'{alpha_diff_only_train} (not included in accuracy test '\n 'during training)')\n if alpha_diff_only_val:\n logger.warning(f'alphabet mismatch: chars in validation set only: {alpha_diff_only_val} (not trained)')\n logger.info('grapheme\\tcount')\n for k, v in sorted(train_set.alphabet.items(), key=lambda x: x[1], reverse=True):\n char = make_printable(k)\n if char == k:\n char = '\\t' + char\n logger.info(f'{char}\\t{v}')\n\n if codec:\n logger.info('Instantiating codec')\n self.codec = PytorchCodec(codec)\n for k, v in self.codec.c2l.items():\n char = make_printable(k)\n if char == k:\n char = '\\t' + char\n logger.info(f'{char}\\t{v}')\n else:\n self.codec = None\n\n logger.info('Encoding training set')\n\n def _build_dataset(self,\n DatasetClass,\n training_data,\n **kwargs):\n dataset = DatasetClass(normalization=self.hparams.normalization,\n whitespace_normalization=self.hparams.normalize_whitespace,\n reorder=self.reorder,\n im_transforms=self.transforms,\n augmentation=self.hparams.augment,\n **kwargs)\n\n if (self.num_workers and self.num_workers > 1) and self.format_type != 'binary':\n with Pool(processes=self.num_workers) as pool:\n for im in pool.imap_unordered(partial(_star_fun, dataset.parse), training_data, 5):\n logger.debug(f'Adding sample {im} to training set')\n if im:\n dataset.add(**im)\n else:\n for im in training_data:\n try:\n dataset.add(**im)\n except KrakenInputException as e:\n logger.warning(str(e))\n if self.format_type == 'binary' and self.hparams.normalization:\n logger.debug('Rebuilding dataset using unicode normalization')\n dataset.rebuild_alphabet()\n return dataset\n\n def forward(self, x, seq_lens=None):\n return self.net(x, seq_lens)\n\n def training_step(self, batch, batch_idx):\n input, target = batch['image'], batch['target']\n # sequence batch\n if 'seq_lens' in batch:\n seq_lens, label_lens = batch['seq_lens'], batch['target_lens']\n target = (target, label_lens)\n o = self.net(input, seq_lens)\n else:\n o = self.net(input)\n\n seq_lens = o[1]\n output = o[0]\n target_lens = target[1]\n target = target[0]\n # height should be 1 by now\n if output.size(2) != 1:\n raise KrakenInputException('Expected dimension 3 to be 1, actual {}'.format(output.size(2)))\n output = output.squeeze(2)\n # NCW -> WNC\n loss = self.nn.criterion(output.permute(2, 0, 1), # type: ignore\n target,\n seq_lens,\n target_lens)\n return loss\n\n def validation_step(self, batch, batch_idx):\n chars, error = compute_error(self.rec_nn, batch)\n chars = torch.tensor(chars)\n error = torch.tensor(error)\n return {'chars': chars, 'error': error}\n\n def validation_epoch_end(self, outputs):\n chars = torch.stack([x['chars'] for x in outputs]).sum()\n error = torch.stack([x['error'] for x in outputs]).sum()\n accuracy = (chars - error) / (chars + torch.finfo(torch.float).eps)\n if accuracy > self.best_metric:\n logger.debug(f'Updating best metric from {self.best_metric} ({self.best_epoch}) to {accuracy} ({self.current_epoch})')\n self.best_epoch = self.current_epoch\n self.best_metric = accuracy\n logger.info(f'validation run: total chars {chars} errors {error} accuracy {accuracy}')\n self.log_dict({'val_accuracy': accuracy, 'val_metric': accuracy}, prog_bar=True)\n\n def setup(self, stage: Optional[str] = None):\n # finalize models in case of appending/loading\n if stage in [None, 'fit']:\n if self.append:\n self.train_set.dataset.encode(self.codec)\n # now we can create a new model\n self.spec = '[{} O1c{}]'.format(self.spec[1:-1], self.train_set.dataset.codec.max_label + 1)\n logger.info(f'Appending {self.spec} to existing model {self.nn.spec} after {self.append}')\n self.nn.append(self.append, self.spec)\n self.nn.add_codec(self.train_set.dataset.codec)\n logger.info(f'Assembled model spec: {self.nn.spec}')\n elif self.model:\n self.spec = self.nn.spec\n\n # prefer explicitly given codec over network codec if mode is 'both'\n codec = self.codec if (self.codec and self.resize == 'both') else self.nn.codec\n\n codec.strict = True\n\n try:\n self.train_set.dataset.encode(codec)\n except KrakenEncodeException:\n alpha_diff = set(self.train_set.dataset.alphabet).difference(\n set(codec.c2l.keys())\n )\n alpha_diff_val = set(self.val_set.dataset.alphabet).difference(\n set(codec.c2l.keys())\n )\n if self.resize == 'fail':\n raise KrakenInputException(f'Training data and model codec alphabets mismatch: {alpha_diff}')\n elif self.resize == 'add':\n logger.info(f'Resizing codec to include '\n f'{len(alpha_diff.union(alpha_diff_val))} new code points')\n # Add the characters in val only\n codec = codec.add_labels(alpha_diff.union(alpha_diff_val))\n self.nn.add_codec(codec)\n logger.info(f'Resizing last layer in network to {codec.max_label+1} outputs')\n self.nn.resize_output(codec.max_label + 1)\n self.train_set.dataset.encode(self.nn.codec)\n elif self.resize == 'both':\n logger.info(f'Resizing network or given codec to '\n f'{len(self.train_set.dataset.alphabet)+len(self.val_set.dataset.alphabet)} '\n f'code sequences')\n self.train_set.dataset.encode(None)\n ncodec, del_labels = codec.merge(self.train_set.dataset.codec)\n # Add the characters in val only\n val_diff = set(self.val_set.dataset.alphabet).difference(\n set(ncodec.c2l.keys())\n )\n ncodec.add_labels(val_diff)\n # Switch codec.\n self.nn.add_codec(ncodec)\n logger.info(f'Deleting {len(del_labels)} output classes from network '\n f'({len(codec)-len(del_labels)} retained)')\n self.train_set.dataset.encode(ncodec)\n self.nn.resize_output(ncodec.max_label + 1, del_labels)\n else:\n raise ValueError(f'invalid resize parameter value {self.resize}')\n\n self.nn.codec.strict = False\n\n else:\n self.train_set.dataset.encode(self.codec)\n logger.info(f'Creating new model {self.spec} with {self.train_set.dataset.codec.max_label+1} outputs')\n self.spec = '[{} O1c{}]'.format(self.spec[1:-1], self.train_set.dataset.codec.max_label + 1)\n self.nn = vgsl.TorchVGSLModel(self.spec)\n # initialize weights\n self.nn.init_weights()\n self.nn.add_codec(self.train_set.dataset.codec)\n\n self.val_set.dataset.encode(self.nn.codec)\n\n if self.nn.one_channel_mode and self.train_set.dataset.im_mode != self.nn.one_channel_mode:\n logger.warning(f'Neural network has been trained on mode {self.nn.one_channel_mode} images, '\n f'training set contains mode {self.train_set.dataset.im_mode} data. Consider setting `force_binarization`')\n\n if self.format_type != 'path' and self.nn.seg_type == 'bbox':\n logger.warning('Neural network has been trained on bounding box image information but training set is polygonal.')\n\n self.nn.hyper_params = self.hparams\n self.nn.model_type = 'recognition'\n\n if not self.nn.seg_type:\n logger.info(f'Setting seg_type to {self.train_set.dataset.seg_type}.')\n self.nn.seg_type = self.train_set.dataset.seg_type\n\n self.rec_nn = models.TorchSeqRecognizer(self.nn, train=None, device=None)\n self.net = self.nn.nn\n\n torch.set_num_threads(max(self.num_workers, 1))\n\n def train_dataloader(self):\n return DataLoader(self.train_set,\n batch_size=self.hparams.batch_size,\n num_workers=self.num_workers,\n pin_memory=True,\n shuffle=True,\n collate_fn=collate_sequences)\n\n def val_dataloader(self):\n return DataLoader(self.val_set,\n shuffle=False,\n batch_size=self.hparams.batch_size,\n num_workers=self.num_workers,\n pin_memory=True,\n collate_fn=collate_sequences)\n\n def configure_callbacks(self):\n callbacks = []\n if self.hparams.quit == 'early':\n callbacks.append(EarlyStopping(monitor='val_accuracy',\n mode='max',\n patience=self.hparams.lag,\n stopping_threshold=1.0))\n return callbacks\n\n # configuration of optimizers and learning rate schedulers\n # --------------------------------------------------------\n #\n # All schedulers are created internally with a frequency of step to enable\n # batch-wise learning rate warmup. In lr_scheduler_step() calls to the\n # scheduler are then only performed at the end of the epoch.\n def configure_optimizers(self):\n return _configure_optimizer_and_lr_scheduler(self.hparams,\n self.nn.nn.parameters(),\n len_train_set=len(self.train_set),\n loss_tracking_mode='max')\n\n def optimizer_step(self, epoch, batch_idx, optimizer, optimizer_idx,\n optimizer_closure, on_tpu=False, using_native_amp=False,\n using_lbfgs=False):\n # update params\n optimizer.step(closure=optimizer_closure)\n\n # linear warmup between 0 and the initial learning rate `lrate` in `warmup`\n # steps.\n if self.hparams.warmup and self.trainer.global_step < self.hparams.warmup:\n lr_scale = min(1.0, float(self.trainer.global_step + 1) / self.hparams.warmup)\n for pg in optimizer.param_groups:\n pg[\"lr\"] = lr_scale * self.hparams.lrate\n\n def lr_scheduler_step(self, scheduler, optimizer_idx, metric):\n if not self.hparams.warmup or self.trainer.global_step >= self.hparams.warmup:\n # step OneCycleLR each batch if not in warmup phase\n if isinstance(scheduler, lr_scheduler.OneCycleLR):\n scheduler.step()\n # step every other scheduler epoch-wise\n elif self.trainer.is_last_batch:\n scheduler.step()\n\n\nclass SegmentationModel(pl.LightningModule):\n def __init__(self,\n hyper_params: Dict = None,\n load_hyper_parameters: bool = False,\n progress_callback: Callable[[str, int], Callable[[None], None]] = lambda string, length: lambda: None,\n message: Callable[[str], None] = lambda *args, **kwargs: None,\n output: str = 'model',\n spec: str = default_specs.SEGMENTATION_SPEC,\n model: Optional[Union[pathlib.Path, str]] = None,\n training_data: Union[Sequence[Union[pathlib.Path, str]], Sequence[Dict[str, Any]]] = None,\n evaluation_data: Optional[Union[Sequence[Union[pathlib.Path, str]], Sequence[Dict[str, Any]]]] = None,\n partition: Optional[float] = 0.9,\n num_workers: int = 1,\n force_binarization: bool = False,\n format_type: str = 'path',\n suppress_regions: bool = False,\n suppress_baselines: bool = False,\n valid_regions: Optional[Sequence[str]] = None,\n valid_baselines: Optional[Sequence[str]] = None,\n merge_regions: Optional[Dict[str, str]] = None,\n merge_baselines: Optional[Dict[str, str]] = None,\n bounding_regions: Optional[Sequence[str]] = None,\n resize: str = 'fail',\n topline: Union[bool, None] = False):\n \"\"\"\n A LightningModule encapsulating the training setup for a page\n segmentation model.\n\n Setup parameters (load, training_data, evaluation_data, ....) are\n named, model hyperparameters (everything in\n `kraken.lib.default_specs.SEGMENTATION_HYPER_PARAMS`) are in in the\n `hyper_params` argument.\n\n Args:\n hyper_params (dict): Hyperparameter dictionary containing all fields\n from\n kraken.lib.default_specs.SEGMENTATION_HYPER_PARAMS\n **kwargs: Setup parameters, i.e. CLI parameters of the segtrain() command.\n \"\"\"\n\n super().__init__()\n\n self.best_epoch = 0\n self.best_metric = 0.0\n\n self.model = model\n self.num_workers = num_workers\n self.resize = resize\n self.format_type = format_type\n self.output = output\n self.bounding_regions = bounding_regions\n self.topline = topline\n\n hyper_params_ = default_specs.SEGMENTATION_HYPER_PARAMS\n\n if model:\n logger.info(f'Loading existing model from {model}')\n self.nn = vgsl.TorchVGSLModel.load_model(model)\n\n if self.nn.model_type not in [None, 'segmentation']:\n raise ValueError(f'Model {model} is of type {self.nn.model_type} while `segmentation` is expected.')\n\n if load_hyper_parameters:\n hp = self.nn.hyper_params\n else:\n hp = {}\n hyper_params_.update(hp)\n batch, channels, height, width = self.nn.input\n else:\n self.nn = None\n\n spec = spec.strip()\n if spec[0] != '[' or spec[-1] != ']':\n raise ValueError(f'VGSL spec \"{spec}\" not bracketed')\n self.spec = spec\n blocks = spec[1:-1].split(' ')\n m = re.match(r'(\\d+),(\\d+),(\\d+),(\\d+)', blocks[0])\n if not m:\n raise ValueError(f'Invalid input spec {blocks[0]}')\n batch, height, width, channels = [int(x) for x in m.groups()]\n\n if hyper_params:\n hyper_params_.update(hyper_params)\n\n validate_hyper_parameters(hyper_params_)\n self.save_hyperparameters(hyper_params_)\n\n if not training_data:\n raise ValueError('No training data provided. Please add some.')\n\n transforms = ImageInputTransforms(batch, height, width, channels, 0, valid_norm=False, force_binarization=force_binarization)\n\n self.example_input_array = torch.Tensor(batch,\n channels,\n height if height else 400,\n width if width else 300)\n\n # set multiprocessing tensor sharing strategy\n if 'file_system' in torch.multiprocessing.get_all_sharing_strategies():\n logger.debug('Setting multiprocessing tensor sharing strategy to file_system')\n torch.multiprocessing.set_sharing_strategy('file_system')\n\n if not valid_regions:\n valid_regions = None\n if not valid_baselines:\n valid_baselines = None\n\n if suppress_regions:\n valid_regions = []\n merge_regions = None\n if suppress_baselines:\n valid_baselines = []\n merge_baselines = None\n\n train_set = BaselineSet(training_data,\n line_width=self.hparams.line_width,\n im_transforms=transforms,\n mode=format_type,\n augmentation=self.hparams.augment,\n valid_baselines=valid_baselines,\n merge_baselines=merge_baselines,\n valid_regions=valid_regions,\n merge_regions=merge_regions)\n\n if format_type is None:\n for page in training_data:\n train_set.add(**page)\n\n if evaluation_data:\n val_set = BaselineSet(evaluation_data,\n line_width=self.hparams.line_width,\n im_transforms=transforms,\n mode=format_type,\n augmentation=False,\n valid_baselines=valid_baselines,\n merge_baselines=merge_baselines,\n valid_regions=valid_regions,\n merge_regions=merge_regions)\n\n if format_type is None:\n for page in evaluation_data:\n val_set.add(**page)\n\n train_set = Subset(train_set, range(len(train_set)))\n val_set = Subset(val_set, range(len(val_set)))\n else:\n train_len = int(len(train_set)*partition)\n val_len = len(train_set) - train_len\n logger.info(f'No explicit validation data provided. Splitting off '\n f'{val_len} (of {len(train_set)}) samples to validation '\n 'set.')\n train_set, val_set = random_split(train_set, (train_len, val_len))\n\n if len(train_set) == 0:\n raise ValueError('No valid training data provided. Please add some.')\n\n if len(val_set) == 0:\n raise ValueError('No valid validation data provided. Please add some.')\n\n # overwrite class mapping in validation set\n val_set.dataset.num_classes = train_set.dataset.num_classes\n val_set.dataset.class_mapping = train_set.dataset.class_mapping\n\n self.train_set = train_set\n self.val_set = val_set\n\n def forward(self, x):\n return self.nn.nn(x)\n\n def training_step(self, batch, batch_idx):\n input, target = batch['image'], batch['target']\n output, _ = self.nn.nn(input)\n output = F.interpolate(output, size=(target.size(2), target.size(3)))\n loss = self.nn.criterion(output, target)\n return loss\n\n def validation_step(self, batch, batch_idx):\n x, y = batch['image'], batch['target']\n pred, _ = self.nn.nn(x)\n # scale target to output size\n y = F.interpolate(y, size=(pred.size(2), pred.size(3))).squeeze(0).bool()\n pred = pred.squeeze() > 0.3\n pred = pred.view(pred.size(0), -1)\n y = y.view(y.size(0), -1)\n\n return {'intersections': (y & pred).sum(dim=1, dtype=torch.double),\n 'unions': (y | pred).sum(dim=1, dtype=torch.double),\n 'corrects': torch.eq(y, pred).sum(dim=1, dtype=torch.double),\n 'cls_cnt': y.sum(dim=1, dtype=torch.double),\n 'all_n': torch.tensor(y.size(1), dtype=torch.double, device=self.device)}\n\n def validation_epoch_end(self, outputs):\n smooth = torch.finfo(torch.float).eps\n\n intersections = torch.stack([x['intersections'] for x in outputs]).sum()\n unions = torch.stack([x['unions'] for x in outputs]).sum()\n corrects = torch.stack([x['corrects'] for x in outputs]).sum()\n cls_cnt = torch.stack([x['cls_cnt'] for x in outputs]).sum()\n all_n = torch.stack([x['all_n'] for x in outputs]).sum()\n\n # all_positives = tp + fp\n # actual_positives = tp + fn\n # true_positivies = tp\n pixel_accuracy = corrects.sum() / all_n.sum()\n mean_accuracy = torch.mean(corrects / all_n)\n iu = (intersections + smooth) / (unions + smooth)\n mean_iu = torch.mean(iu)\n freq_iu = torch.sum(cls_cnt / cls_cnt.sum() * iu)\n\n if mean_iu > self.best_metric:\n logger.debug(f'Updating best metric from {self.best_metric} ({self.best_epoch}) to {mean_iu} ({self.current_epoch})')\n self.best_epoch = self.current_epoch\n self.best_metric = mean_iu\n\n logger.info(f'validation run: accuracy {pixel_accuracy} mean_acc {mean_accuracy} mean_iu {mean_iu} freq_iu {freq_iu}')\n self.log_dict({'val_accuracy': pixel_accuracy,\n 'val_mean_acc': mean_accuracy,\n 'val_mean_iu': mean_iu,\n 'val_freq_iu': freq_iu,\n 'val_metric': mean_iu}, prog_bar=True)\n\n def setup(self, stage: Optional[str] = None):\n # finalize models in case of appending/loading\n if stage in [None, 'fit']:\n if not self.model:\n self.spec = f'[{self.spec[1:-1]} O2l{self.train_set.dataset.num_classes}]'\n logger.info(f'Creating model {self.spec} with {self.train_set.dataset.num_classes} outputs ', nl=False)\n nn = vgsl.TorchVGSLModel(self.spec)\n if self.bounding_regions is not None:\n nn.user_metadata['bounding_regions'] = self.bounding_regions\n nn.user_metadata['topline'] = self.topline\n self.nn = nn\n else:\n if self.train_set.dataset.class_mapping['baselines'].keys() != self.nn.user_metadata['class_mapping']['baselines'].keys() or \\\n self.train_set.dataset.class_mapping['regions'].keys() != self.nn.user_metadata['class_mapping']['regions'].keys():\n\n bl_diff = set(self.train_set.dataset.class_mapping['baselines'].keys()).symmetric_difference(\n set(self.nn.user_metadata['class_mapping']['baselines'].keys()))\n regions_diff = set(self.train_set.dataset.class_mapping['regions'].keys()).symmetric_difference(\n set(self.nn.user_metadata['class_mapping']['regions'].keys()))\n\n if self.resize == 'fail':\n raise ValueError(f'Training data and model class mapping differ (bl: {bl_diff}, regions: {regions_diff}')\n elif self.resize == 'add':\n new_bls = self.train_set.dataset.class_mapping['baselines'].keys() - self.nn.user_metadata['class_mapping']['baselines'].keys()\n new_regions = self.train_set.dataset.class_mapping['regions'].keys() - self.nn.user_metadata['class_mapping']['regions'].keys()\n cls_idx = max(max(self.nn.user_metadata['class_mapping']['baselines'].values()) if self.nn.user_metadata['class_mapping']['baselines'] else -1,\n max(self.nn.user_metadata['class_mapping']['regions'].values()) if self.nn.user_metadata['class_mapping']['regions'] else -1)\n logger.info(f'Adding {len(new_bls) + len(new_regions)} missing types to network output layer.')\n self.nn.resize_output(cls_idx + len(new_bls) + len(new_regions) + 1)\n for c in new_bls:\n cls_idx += 1\n self.nn.user_metadata['class_mapping']['baselines'][c] = cls_idx\n for c in new_regions:\n cls_idx += 1\n self.nn.user_metadata['class_mapping']['regions'][c] = cls_idx\n elif self.resize == 'both':\n logger.info('Fitting network exactly to training set.')\n new_bls = self.train_set.dataset.class_mapping['baselines'].keys() - self.nn.user_metadata['class_mapping']['baselines'].keys()\n new_regions = self.train_set.dataset.class_mapping['regions'].keys() - self.nn.user_metadata['class_mapping']['regions'].keys()\n del_bls = self.nn.user_metadata['class_mapping']['baselines'].keys() - self.train_set.dataset.class_mapping['baselines'].keys()\n del_regions = self.nn.user_metadata['class_mapping']['regions'].keys() - self.train_set.dataset.class_mapping['regions'].keys()\n\n logger.info(f'Adding {len(new_bls) + len(new_regions)} missing '\n f'types and removing {len(del_bls) + len(del_regions)} to network output layer ')\n cls_idx = max(max(self.nn.user_metadata['class_mapping']['baselines'].values()) if self.nn.user_metadata['class_mapping']['baselines'] else -1,\n max(self.nn.user_metadata['class_mapping']['regions'].values()) if self.nn.user_metadata['class_mapping']['regions'] else -1)\n\n del_indices = [self.nn.user_metadata['class_mapping']['baselines'][x] for x in del_bls]\n del_indices.extend(self.nn.user_metadata['class_mapping']['regions'][x] for x in del_regions)\n self.nn.resize_output(cls_idx + len(new_bls) + len(new_regions) -\n len(del_bls) - len(del_regions) + 1, del_indices)\n\n # delete old baseline/region types\n cls_idx = min(min(self.nn.user_metadata['class_mapping']['baselines'].values()) if self.nn.user_metadata['class_mapping']['baselines'] else np.inf,\n min(self.nn.user_metadata['class_mapping']['regions'].values()) if self.nn.user_metadata['class_mapping']['regions'] else np.inf)\n\n bls = {}\n for k, v in sorted(self.nn.user_metadata['class_mapping']['baselines'].items(), key=lambda item: item[1]):\n if k not in del_bls:\n bls[k] = cls_idx\n cls_idx += 1\n\n regions = {}\n for k, v in sorted(self.nn.user_metadata['class_mapping']['regions'].items(), key=lambda item: item[1]):\n if k not in del_regions:\n regions[k] = cls_idx\n cls_idx += 1\n\n self.nn.user_metadata['class_mapping']['baselines'] = bls\n self.nn.user_metadata['class_mapping']['regions'] = regions\n\n # add new baseline/region types\n cls_idx -= 1\n for c in new_bls:\n cls_idx += 1\n self.nn.user_metadata['class_mapping']['baselines'][c] = cls_idx\n for c in new_regions:\n cls_idx += 1\n self.nn.user_metadata['class_mapping']['regions'][c] = cls_idx\n else:\n raise ValueError(f'invalid resize parameter value {self.resize}')\n # backfill train_set/val_set mapping if key-equal as the actual\n # numbering in the train_set might be different\n self.train_set.dataset.class_mapping = self.nn.user_metadata['class_mapping']\n self.val_set.dataset.class_mapping = self.nn.user_metadata['class_mapping']\n\n # updates model's hyper params with user-defined ones\n self.nn.hyper_params = self.hparams\n\n # change topline/baseline switch\n loc = {None: 'centerline',\n True: 'topline',\n False: 'baseline'}\n\n if 'topline' not in self.nn.user_metadata:\n logger.warning(f'Setting baseline location to {loc[self.topline]} from unset model.')\n elif self.nn.user_metadata['topline'] != self.topline:\n from_loc = loc[self.nn.user_metadata['topline']]\n logger.warning(f'Changing baseline location from {from_loc} to {loc[self.topline]}.')\n self.nn.user_metadata['topline'] = self.topline\n\n logger.info('Training line types:')\n for k, v in self.train_set.dataset.class_mapping['baselines'].items():\n logger.info(f' {k}\\t{v}\\t{self.train_set.dataset.class_stats[\"baselines\"][k]}')\n logger.info('Training region types:')\n for k, v in self.train_set.dataset.class_mapping['regions'].items():\n logger.info(f' {k}\\t{v}\\t{self.train_set.dataset.class_stats[\"regions\"][k]}')\n\n if len(self.train_set) == 0:\n raise ValueError('No valid training data was provided to the train command. Please add valid XML data.')\n\n # set model type metadata field and dump class_mapping\n self.nn.model_type = 'segmentation'\n self.nn.user_metadata['class_mapping'] = self.val_set.dataset.class_mapping\n\n # for model size/trainable parameter output\n self.net = self.nn.nn\n\n torch.set_num_threads(max(self.num_workers, 1))\n\n def train_dataloader(self):\n return DataLoader(self.train_set,\n batch_size=1,\n num_workers=self.num_workers,\n shuffle=True,\n pin_memory=True)\n\n def val_dataloader(self):\n return DataLoader(self.val_set,\n shuffle=False,\n batch_size=1,\n num_workers=self.num_workers,\n pin_memory=True)\n\n def configure_callbacks(self):\n callbacks = []\n if self.hparams.quit == 'early':\n callbacks.append(EarlyStopping(monitor='val_mean_iu',\n mode='max',\n patience=self.hparams.lag,\n stopping_threshold=1.0))\n\n return callbacks\n\n # configuration of optimizers and learning rate schedulers\n # --------------------------------------------------------\n #\n # All schedulers are created internally with a frequency of step to enable\n # batch-wise learning rate warmup. In lr_scheduler_step() calls to the\n # scheduler are then only performed at the end of the epoch.\n def configure_optimizers(self):\n return _configure_optimizer_and_lr_scheduler(self.hparams,\n self.nn.nn.parameters(),\n len_train_set=len(self.train_set),\n loss_tracking_mode='max')\n\n def optimizer_step(self, epoch, batch_idx, optimizer, optimizer_idx,\n optimizer_closure, on_tpu=False, using_native_amp=False,\n using_lbfgs=False):\n # update params\n optimizer.step(closure=optimizer_closure)\n\n # linear warmup between 0 and the initial learning rate `lrate` in `warmup`\n # steps.\n if self.hparams.warmup and self.trainer.global_step < self.hparams.warmup:\n lr_scale = min(1.0, float(self.trainer.global_step + 1) / self.hparams.warmup)\n for pg in optimizer.param_groups:\n pg[\"lr\"] = lr_scale * self.hparams.lrate\n\n def lr_scheduler_step(self, scheduler, optimizer_idx, metric):\n if not self.hparams.warmup or self.trainer.global_step >= self.hparams.warmup:\n # step OneCycleLR each batch if not in warmup phase\n if isinstance(scheduler, lr_scheduler.OneCycleLR):\n scheduler.step()\n # step every other scheduler epoch-wise\n elif self.trainer.is_last_batch:\n scheduler.step()\n\n\ndef _configure_optimizer_and_lr_scheduler(hparams, params, len_train_set=None, loss_tracking_mode='max'):\n # XXX: Warmup is not configured here because it needs to be manually done in optimizer_step()\n logger.debug(f'Constructing {hparams.optimizer} optimizer (lr: {hparams.lrate}, momentum: {hparams.momentum})')\n if hparams.optimizer == 'Adam':\n optim = torch.optim.Adam(params, lr=hparams.lrate, weight_decay=hparams.weight_decay)\n else:\n optim = getattr(torch.optim, hparams.optimizer)(params,\n lr=hparams.lrate,\n momentum=hparams.momentum,\n weight_decay=hparams.weight_decay)\n lr_sched = {}\n if hparams.schedule == 'exponential':\n lr_sched = {'scheduler': lr_scheduler.ExponentialLR(optim, hparams.gamma, last_epoch=hparams.completed_epochs-1),\n 'interval': 'step'}\n elif hparams.schedule == 'cosine':\n lr_sched = {'scheduler': lr_scheduler.CosineAnnealingLR(optim, hparams.gamma, last_epoch=hparams.completed_epochs-1),\n 'interval': 'step'}\n elif hparams.schedule == 'step':\n lr_sched = {'scheduler': lr_scheduler.StepLR(optim, hparams.step_size, hparams.gamma, last_epoch=hparams.completed_epochs-1),\n 'interval': 'step'}\n elif hparams.schedule == 'reduceonplateau':\n lr_sched = {'scheduler': lr_scheduler.ReduceLROnPlateau(optim,\n mode=loss_tracking_mode,\n factor=hparams.rop_factor,\n patience=hparams.rop_patience),\n 'interval': 'step'}\n elif hparams.schedule == '1cycle':\n if hparams.epochs <= 0:\n raise ValueError('1cycle learning rate scheduler selected but '\n 'number of epochs is less than 0 '\n f'({hparams.epochs}).')\n last_epoch = hparams.completed_epochs*len_train_set if hparams.completed_epochs else -1\n lr_sched = {'scheduler': lr_scheduler.OneCycleLR(optim,\n max_lr=hparams.lrate,\n epochs=hparams.epochs,\n steps_per_epoch=len_train_set,\n last_epoch=last_epoch),\n 'interval': 'step'}\n elif hparams.schedule != 'constant':\n raise ValueError(f'Unsupported learning rate scheduler {hparams.schedule}.')\n\n if lr_sched:\n lr_sched['monitor'] = 'val_metric'\n\n return [optim], lr_sched if lr_sched else []\n","sub_path":"kraken/lib/train.py","file_name":"train.py","file_ext":"py","file_size_in_byte":50671,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"217659164","text":"import face_recognition\r\nimport os\r\nfrom PIL import Image\r\nimport pickle\r\nimport gzip\r\n#pathik = \"/root/env/megasuperfacedetectionbot/\"\r\npathik = \"\"\r\ndef listdir_nohidden(path):\r\n for f in os.listdir(path):\r\n if not f.startswith('.'):\r\n yield f\r\n\r\ndef analyzeValues(values):\r\n try: \r\n return int((sum(values)/len(values)))\r\n except: \r\n return 0\r\n\r\n\r\n\r\ndef checkFace(**kwargs):\r\n\terrorCounter=0\r\n\tmaxValue=0\r\n\tmostLikely=\"unknown\"\r\n\tanalyze = -1\r\n\t#path=f\"{pathik}faces/known_faces/\"\r\n\tpath=\"faces/known_faces/\"\r\n\tWDILL = face_recognition.load_image_file(\"WDILL.jpg\")\r\n\tWDILLenc=face_recognition.face_encodings(WDILL)\r\n\tfiles = listdir_nohidden(path)\r\n\tfor file in files:\r\n\t\tfaces = listdir_nohidden(path+file+\"/faceEncodings/\")\r\n\t\tfor face in faces:\r\n\t\t\twith gzip.open(path+file+\"/faceEncodings/\"+face, 'rb') as f:\r\n\t\t\t\ttry:\r\n\t\t\t\t\timageEncoding = pickle.load(f)\r\n\t\t\t\t\tanalyze=((1-(face_recognition.face_distance(imageEncoding,WDILLenc))[0])*100)\r\n\t\t\t\t\tf.close()\r\n\t\t\t\texcept:\r\n\t\t\t\t\terrorCounter+=1\r\n\t\t\t\t\t#analyze=analyzeValues(percentage)\r\n\t\tif(kwargs.get(\"outputEveryLine\",True)==True):\r\n\t\t\tyield (\"You look like \"+file+\" with \"+str(analyze)+\"chance\")\r\n\t\tif (analyze>maxValue):\r\n\t\t\tmaxValue=analyze\r\n\t\t\tmostLikely=file\r\n\t\t\t#percentage=[]\r\n\tyield \"end\"\r\n\tyield \"end\"\r\n\t#answer = str(\"most likely you look like \"+(mostLikely)+\" with \"+str(maxValue)+\"chance\\nErrors:\"+str(errorCounter))\r\n\tanswer = \"most likely you look like \" + str(mostLikely) + \" with \" + str(maxValue)+\" percent chance \\n Errors:\" +str(errorCounter)\r\n\tyield answer\r\n\tif(kwargs.get(\"getFinalFace\",False)==True):\r\n\t\tim1 = Image.open(path+mostLikely+\"/main.jpg\")\r\n\t\tim1 = im1.save(f\"{pathik}mostLikely.jpg\")\r\n\r\n \r\n\r\nfor i in checkFace(getFinalFace=True,outputEveryLine=False):\r\n print(i)","sub_path":"checkGenerator.py","file_name":"checkGenerator.py","file_ext":"py","file_size_in_byte":1802,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"151533077","text":"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\"\"\"test for parse_atat\"\"\"\nfrom __future__ import division\nimport os\nimport unittest\nfrom pymatgen.io.vasp import Poscar\nfrom pymatgen.symmetry.analyzer import SpacegroupAnalyzer\n\n__date__ = 'Mar 28 2017'\n\nTEST_PATH = '/Users/enoki/Researches/Analysis/Codes/01_testRun/'\n\n\ndef main():\n \"\"\"\n Test\n \"\"\"\n unittest.main()\n\n\nclass Test(unittest.TestCase): #pylint: disable=R0903\n \"\"\"\n 空間群が変わってしまう問題について\n \"\"\"\n PATH = os.path.join(TEST_PATH, 'vasp_poscar')\n\n def test_read_str(self):\n \"\"\" read_str \"\"\"\n src = os.path.join(self.PATH, 'POSCAR_GS2_34246_cart')\n srcpos = Poscar.from_file(src)\n dst = os.path.join(self.PATH, 'POSCAR_GS2_34246_remake')\n srcpos.write_file(dst)\n print(srcpos)\n finder = SpacegroupAnalyzer(srcpos.structure)\n spg = finder.get_space_group_symbol()\n print(spg)\n\n prim_str = finder.get_primitive_standard_structure()\n finder2 = SpacegroupAnalyzer(prim_str)\n spg2 = finder2.get_space_group_symbol()\n print(spg2)\n # print(finder)\n\n src = os.path.join(self.PATH, 'SPOSCAR')\n srcpos = Poscar.from_file(src)\n finder = SpacegroupAnalyzer(srcpos.structure)\n spg = finder.get_space_group_symbol()\n print(spg)\n\n # prim_str = finder.get_primitive_standard_structure()\n prim_str = finder.get_conventional_standard_structure()\n finder2 = SpacegroupAnalyzer(prim_str)\n spg2 = finder2.get_space_group_symbol()\n dst2 = os.path.join(self.PATH, 'POSCAR_GS2_34246_remake2')\n dstpos = Poscar(prim_str)\n dstpos.write_file(dst2)\n # print(spg2)\n\n def _test_withoutN(self):\n \"\"\" withoutN \"\"\"\n src = os.path.join(self.PATH, 'POSCAR_withoutN')\n srcpos = Poscar.from_file(src)\n dst = os.path.join(self.PATH, 'POSCAR_withoutN_remake')\n srcpos.write_file(dst)\n print(srcpos)\n finder = SpacegroupAnalyzer(srcpos.structure)\n spg = finder.get_space_group_symbol()\n print(spg)\n\n # prim_str = finder.get_primitive_standard_structure()\n # finder2 = SpacegroupAnalyzer(prim_str)\n # spg2 = finder2.get_space_group_symbol()\n # print(spg2)\n\n # std_str = finder.get_conventional_standard_structure()\n\n\n\n\n\nif __name__ == '__main__':\n main()\n","sub_path":"test/test_vasp_poscar.py","file_name":"test_vasp_poscar.py","file_ext":"py","file_size_in_byte":2417,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"458216766","text":"# Copyright 2016 Amazon.com, Inc. or its affiliates. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\"). You\n# may not use this file except in compliance with the License. A copy of\n# the License is located at\n#\n# http://aws.amazon.com/apache2.0/\n#\n# or in the \"license\" file accompanying this file. This file is\n# distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF\n# ANY KIND, either express or implied. See the License for the specific\n# language governing permissions and limitations under the License.\nimport copy\n\nfrom botocore.compat import OrderedDict\nfrom botocore.endpoint import DEFAULT_TIMEOUT, MAX_POOL_CONNECTIONS\nfrom botocore.exceptions import (\n InvalidMaxRetryAttemptsError,\n InvalidRetryConfigurationError,\n InvalidRetryModeError,\n InvalidS3AddressingStyleError,\n)\n\n\nclass Config:\n \"\"\"Advanced configuration for Botocore clients.\n\n :type region_name: str\n :param region_name: The region to use in instantiating the client\n\n :type signature_version: str\n :param signature_version: The signature version when signing requests.\n\n :type user_agent: str\n :param user_agent: The value to use in the User-Agent header.\n\n :type user_agent_extra: str\n :param user_agent_extra: The value to append to the current User-Agent\n header value.\n\n :type user_agent_appid: str\n :param user_agent_appid: A value that gets included in the User-Agent\n string in the format \"app/\". Allowed characters are\n ASCII alphanumerics and ``!$%&'*+-.^_`|~``. All other characters will\n be replaced by a ``-``.\n\n :type connect_timeout: float or int\n :param connect_timeout: The time in seconds till a timeout exception is\n thrown when attempting to make a connection. The default is 60\n seconds.\n\n :type read_timeout: float or int\n :param read_timeout: The time in seconds till a timeout exception is\n thrown when attempting to read from a connection. The default is\n 60 seconds.\n\n :type parameter_validation: bool\n :param parameter_validation: Whether parameter validation should occur\n when serializing requests. The default is True. You can disable\n parameter validation for performance reasons. Otherwise, it's\n recommended to leave parameter validation enabled.\n\n :type max_pool_connections: int\n :param max_pool_connections: The maximum number of connections to\n keep in a connection pool. If this value is not set, the default\n value of 10 is used.\n\n :type proxies: dict\n :param proxies: A dictionary of proxy servers to use by protocol or\n endpoint, e.g.:\n ``{'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}``.\n The proxies are used on each request.\n\n :type proxies_config: dict\n :param proxies_config: A dictionary of additional proxy configurations.\n Valid keys are:\n\n * ``proxy_ca_bundle`` -- The path to a custom certificate bundle to use\n when establishing SSL/TLS connections with proxy.\n\n * ``proxy_client_cert`` -- The path to a certificate for proxy\n TLS client authentication.\n\n When a string is provided it is treated as a path to a proxy client\n certificate. When a two element tuple is provided, it will be\n interpreted as the path to the client certificate, and the path\n to the certificate key.\n\n * ``proxy_use_forwarding_for_https`` -- For HTTPS proxies,\n forward your requests to HTTPS destinations with an absolute\n URI. We strongly recommend you only use this option with\n trusted or corporate proxies. Value must be boolean.\n\n :type s3: dict\n :param s3: A dictionary of S3 specific configurations.\n Valid keys are:\n\n * ``use_accelerate_endpoint`` -- Refers to whether to use the S3\n Accelerate endpoint. The value must be a boolean. If True, the\n client will use the S3 Accelerate endpoint. If the S3 Accelerate\n endpoint is being used then the addressing style will always\n be virtual.\n\n * ``payload_signing_enabled`` -- Refers to whether or not to SHA256\n sign sigv4 payloads. By default, this is disabled for streaming\n uploads (UploadPart and PutObject).\n\n * ``addressing_style`` -- Refers to the style in which to address\n s3 endpoints. Values must be a string that equals one of:\n\n * ``auto`` -- Addressing style is chosen for user. Depending\n on the configuration of client, the endpoint may be addressed in\n the virtual or the path style. Note that this is the default\n behavior if no style is specified.\n\n * ``virtual`` -- Addressing style is always virtual. The name of the\n bucket must be DNS compatible or an exception will be thrown.\n Endpoints will be addressed as such: ``mybucket.s3.amazonaws.com``\n\n * ``path`` -- Addressing style is always by path. Endpoints will be\n addressed as such: ``s3.amazonaws.com/mybucket``\n\n * ``us_east_1_regional_endpoint`` -- Refers to what S3 endpoint to use\n when the region is configured to be us-east-1. Values must be a\n string that equals:\n\n * ``regional`` -- Use the us-east-1.amazonaws.com endpoint if the\n client is configured to use the us-east-1 region.\n\n * ``legacy`` -- Use the s3.amazonaws.com endpoint if the client is\n configured to use the us-east-1 region. This is the default if\n the configuration option is not specified.\n\n\n :type retries: dict\n :param retries: A dictionary for configuration related to retry behavior.\n Valid keys are:\n\n * ``total_max_attempts`` -- An integer representing the maximum number of\n total attempts that will be made on a single request. This includes\n the initial request, so a value of 1 indicates that no requests\n will be retried. If ``total_max_attempts`` and ``max_attempts``\n are both provided, ``total_max_attempts`` takes precedence.\n ``total_max_attempts`` is preferred over ``max_attempts`` because\n it maps to the ``AWS_MAX_ATTEMPTS`` environment variable and\n the ``max_attempts`` config file value.\n * ``max_attempts`` -- An integer representing the maximum number of\n retry attempts that will be made on a single request. For\n example, setting this value to 2 will result in the request\n being retried at most two times after the initial request. Setting\n this value to 0 will result in no retries ever being attempted after\n the initial request. If not provided, the number of retries will\n default to the value specified in the service model, which is\n typically four retries.\n * ``mode`` -- A string representing the type of retry mode botocore\n should use. Valid values are:\n\n * ``legacy`` - The pre-existing retry behavior.\n\n * ``standard`` - The standardized set of retry rules. This will also\n default to 3 max attempts unless overridden.\n\n * ``adaptive`` - Retries with additional client side throttling.\n\n :type client_cert: str, (str, str)\n :param client_cert: The path to a certificate for TLS client authentication.\n\n When a string is provided it is treated as a path to a client\n certificate to be used when creating a TLS connection.\n\n If a client key is to be provided alongside the client certificate the\n client_cert should be set to a tuple of length two where the first\n element is the path to the client certificate and the second element is\n the path to the certificate key.\n\n :type inject_host_prefix: bool\n :param inject_host_prefix: Whether host prefix injection should occur.\n\n Defaults to True.\n\n Setting this to False disables the injection of operation parameters\n into the prefix of the hostname. This is useful for clients providing\n custom endpoints that should not have their host prefix modified.\n\n :type use_dualstack_endpoint: bool\n :param use_dualstack_endpoint: Setting to True enables dualstack\n endpoint resolution.\n\n Defaults to None.\n\n :type use_fips_endpoint: bool\n :param use_fips_endpoint: Setting to True enables fips\n endpoint resolution.\n\n Defaults to None.\n\n :type ignore_configured_endpoint_urls: bool\n :param ignore_configured_endpoint_urls: Setting to True disables use\n of endpoint URLs provided via environment variables and\n the shared configuration file.\n\n Defaults to None.\n\n :type tcp_keepalive: bool\n :param tcp_keepalive: Enables the TCP Keep-Alive socket option used when\n creating new connections if set to True.\n\n Defaults to False.\n\n :type request_min_compression_size_bytes: int\n :param request_min_compression_bytes: The minimum size in bytes that a\n request body should be to trigger compression. All requests with streaming\n input that don't contain the `requiresLength` trait will be compressed\n regardless of this setting.\n\n Defaults to None.\n\n :type disable_request_compression: bool\n :param disable_request_compression: Disables request body compression if\n set to True.\n\n Defaults to None.\n \"\"\"\n\n OPTION_DEFAULTS = OrderedDict(\n [\n ('region_name', None),\n ('signature_version', None),\n ('user_agent', None),\n ('user_agent_extra', None),\n ('user_agent_appid', None),\n ('connect_timeout', DEFAULT_TIMEOUT),\n ('read_timeout', DEFAULT_TIMEOUT),\n ('parameter_validation', True),\n ('max_pool_connections', MAX_POOL_CONNECTIONS),\n ('proxies', None),\n ('proxies_config', None),\n ('s3', None),\n ('retries', None),\n ('client_cert', None),\n ('inject_host_prefix', True),\n ('endpoint_discovery_enabled', None),\n ('use_dualstack_endpoint', None),\n ('use_fips_endpoint', None),\n ('ignore_configured_endpoint_urls', None),\n ('defaults_mode', None),\n ('tcp_keepalive', None),\n ('request_min_compression_size_bytes', None),\n ('disable_request_compression', None),\n ]\n )\n\n NON_LEGACY_OPTION_DEFAULTS = {\n 'connect_timeout': None,\n }\n\n def __init__(self, *args, **kwargs):\n self._user_provided_options = self._record_user_provided_options(\n args, kwargs\n )\n\n # Merge the user_provided options onto the default options\n config_vars = copy.copy(self.OPTION_DEFAULTS)\n defaults_mode = self._user_provided_options.get(\n 'defaults_mode', 'legacy'\n )\n if defaults_mode != 'legacy':\n config_vars.update(self.NON_LEGACY_OPTION_DEFAULTS)\n config_vars.update(self._user_provided_options)\n\n # Set the attributes based on the config_vars\n for key, value in config_vars.items():\n setattr(self, key, value)\n\n # Validate the s3 options\n self._validate_s3_configuration(self.s3)\n\n self._validate_retry_configuration(self.retries)\n\n def _record_user_provided_options(self, args, kwargs):\n option_order = list(self.OPTION_DEFAULTS)\n user_provided_options = {}\n\n # Iterate through the kwargs passed through to the constructor and\n # map valid keys to the dictionary\n for key, value in kwargs.items():\n if key in self.OPTION_DEFAULTS:\n user_provided_options[key] = value\n # The key must exist in the available options\n else:\n raise TypeError(f\"Got unexpected keyword argument '{key}'\")\n\n # The number of args should not be longer than the allowed\n # options\n if len(args) > len(option_order):\n raise TypeError(\n f\"Takes at most {len(option_order)} arguments ({len(args)} given)\"\n )\n\n # Iterate through the args passed through to the constructor and map\n # them to appropriate keys.\n for i, arg in enumerate(args):\n # If it a kwarg was specified for the arg, then error out\n if option_order[i] in user_provided_options:\n raise TypeError(\n f\"Got multiple values for keyword argument '{option_order[i]}'\"\n )\n user_provided_options[option_order[i]] = arg\n\n return user_provided_options\n\n def _validate_s3_configuration(self, s3):\n if s3 is not None:\n addressing_style = s3.get('addressing_style')\n if addressing_style not in ['virtual', 'auto', 'path', None]:\n raise InvalidS3AddressingStyleError(\n s3_addressing_style=addressing_style\n )\n\n def _validate_retry_configuration(self, retries):\n valid_options = ('max_attempts', 'mode', 'total_max_attempts')\n valid_modes = ('legacy', 'standard', 'adaptive')\n if retries is not None:\n for key, value in retries.items():\n if key not in valid_options:\n raise InvalidRetryConfigurationError(\n retry_config_option=key,\n valid_options=valid_options,\n )\n if key == 'max_attempts' and value < 0:\n raise InvalidMaxRetryAttemptsError(\n provided_max_attempts=value,\n min_value=0,\n )\n if key == 'total_max_attempts' and value < 1:\n raise InvalidMaxRetryAttemptsError(\n provided_max_attempts=value,\n min_value=1,\n )\n if key == 'mode' and value not in valid_modes:\n raise InvalidRetryModeError(\n provided_retry_mode=value,\n valid_modes=valid_modes,\n )\n\n def merge(self, other_config):\n \"\"\"Merges the config object with another config object\n\n This will merge in all non-default values from the provided config\n and return a new config object\n\n :type other_config: botocore.config.Config\n :param other config: Another config object to merge with. The values\n in the provided config object will take precedence in the merging\n\n :returns: A config object built from the merged values of both\n config objects.\n \"\"\"\n # Make a copy of the current attributes in the config object.\n config_options = copy.copy(self._user_provided_options)\n\n # Merge in the user provided options from the other config\n config_options.update(other_config._user_provided_options)\n\n # Return a new config object with the merged properties.\n return Config(**config_options)\n","sub_path":"botocore/config.py","file_name":"config.py","file_ext":"py","file_size_in_byte":15129,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"632583726","text":"#!/usr/bin/env python3\n\"\"\"targz plugin for the archive wrapper.\n\nBearable: Tolerable backup and restore.\nhttps://www.github.com/Effenberg0x0/bearable\n\nAlvaro Leal , 2019\n\"\"\"\nimport tarfile\n# from os.path import basename\nimport uuid\nimport os\nimport json\nfrom os import path\n\n\nclass Archive(object):\n\n def get_unique_filename(self, filename):\n return filename + '.' + str(uuid.uuid4())\n\n def create_from_buffer(self, buffer, buffer_filename, tarfile_path):\n tmp_file_name = self.get_unique_filename(buffer_filename)\n with open(tmp_file_name, 'w') as tmp_file:\n tmp_file.write(json.dumps(buffer))\n\n tar_file = tarfile.open(tarfile_path, \"w|gz\")\n tar_file.add(name=tmp_file_name, arcname=buffer_filename, recursive=False)\n tar_file.close()\n os.remove(tmp_file_name)\n\n def create(self, archive_path, file_paths, dirname, save_full_path=False):\n tar = tarfile.open(archive_path, \"w:gz\")\n print(\"ARCHIVE_PATH: {0}\".format(archive_path))\n if not save_full_path:\n base_path = os.path.commonpath(file_paths)\n\n for _file in file_paths:\n if not save_full_path:\n arcname = _file[_file.find(base_path) + len(base_path):] \n else:\n arcname = _file\n\n arcname = '/' + dirname + arcname\n tar.add(name=_file, arcname=arcname, recursive=False)\n tar.close()\n\n def extract(self, archive_path, destination_path):\n if not path.isfile(archive_path):\n raise FileNotFoundError(\"Source archive not found.\")\n\n if not path.isdir(destination_path):\n raise FileNotFoundError(\"Destination dir not found.\")\n\n archive = tarfile.open(archive_path)\n archive.extractall(path=destination_path)","sub_path":"plugins/archive/targz.py","file_name":"targz.py","file_ext":"py","file_size_in_byte":1823,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"466805762","text":"instruction=\"welcome to our program.\\ninput negative number into numbe of item to quit\"\n\n\nprint(instruction)\nnumberofitem=1\nwhile numberofitem>0:\n numberofitem = int(input('enter number of items:'))\n costperitem = float (input('enter cost:$'))\n salesofitem = numberofitem * costperitem\n if salesofitem > 100:\n salesofitem = salesofitem - (salesofitem * 0.1)\n print(\"the total cost:\",salesofitem)","sub_path":"practical 01/shippingcost.py","file_name":"shippingcost.py","file_ext":"py","file_size_in_byte":421,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"72457447","text":"#!/usr/bin/env python\n\n## Benjamin Williams \n## \n## --\n## Tower of Babel script, determines which language a particular piece of text is\n## by making use of nltk.\n##\n\nimport nltk;\n\ncommonWords = {\n\t\"English\" : [\n\t\t\"the\", \"of\", \"and\", \"to\", \"in\", \"i\", \"that\", \"was\", \"his\", \"he\", \"it\", \"with\", \"is\", \"for\", \"as\", \"had\", \"you\", \"not\", \n\t\t\"be\", \"her\", \"on\", \"at\", \"by\", \"which\", \"have\", \"or\", \"from\", \"this\", \"him\", \"but\", \"all\", \"she\", \"they\", \"were\", \"my\",\n\t\t\"are\", \"me\"\n\t],\n\t\n\t\"Spanish\" : [\n\t\t\"que\", \"de\", \"no\", \"a\", \"la\", \"el\", \"es\", \"y\", \"en\", \"lo\", \"un\", \"por\", \"me\", \"una\", \"te\", \"los\", \"se\", \"con\", \"para\",\n\t\t\"mi\", \"esta\", \"si\", \"bien\", \"pero\", \"yo\", \"eso\", \"las\", \"su\", \"tu\", \"aqui\", \"del\", \"al\", \"como\", \"le\", \"mas\"\n\t],\n\t\n\t\"German\" : [\n\t\t\"der\", \"und\", \"die\", \"in\", \"ist\", \"von\", \"den\", \"des\", \"eine\", \"im\", \"ein\", \"mit\", \"das\", \"zu\", \"für\", \"dem\", \"sich\",\n\t\t\"auf\", \"als\", \"auch\", \"wird\", \"oder\", \"aus\", \"wurde\", \"werden\", \"sind\", \"an\", \"einer\", \"nicht\", \"durch\", \"nach\", \"bei\",\n\t\t\"es\", \"war\", \"zum\", \"er\", \"zur\", \"am\", \"einem\", \"einen\", \"sie\", \"bis\", \"man\", \"über\", \"um\", \"dass\", \"wie\", \"hat\", \"eines\",\n\t\t\"nur\", \"Stadt\", \"kann\", \"bezeichnet\", \"noch\", \"aber\", \"siehe\", \"vor\", \"so\", \"unter\"\n\t],\n\t\n\t\"Dutch\" : [\n\t\t\"de\", \"van\", \"een\", \"het\", \"en\", \"in\", \"is\", \"dat\", \"op\", \"te\", \"De\", \"zijn\", \"voor\", \"met\", \"die\", \"niet\", \"aan\", \"er\", \n\t\t\"om\", \"Het\", \"ook\", \"als\", \"dan\", \"maar\", \"bij\", \"of\", \"uit\", \"nog\", \"worden\", \"door\", \"naar\", \"heeft\", \"tot\", \"ze\", \"wordt\",\n\t\t\"over\", \"hij\", \"In\", \"meer\", \"jaar\", \"was\", \"ik\", \"kan\", \"je\"\n\t],\n\t\n\t\"Croatian\" : [\n\t\t\"je\", \"da\", \"ne\", \"se\", \"to\", \"sam\", \"što\", \"na\", \"ti\", \"si\", \"mi\", \"za\", \"li\", \"ja\", \"su\", \"ali\", \"nije\", \"me\", \"ga\", \"te\",\n\t\t\"ovo\", \"samo\", \"bi\", \"kako\", \"od\", \"će\", \"sa\", \"dobro\", \"smo\", \"ako\", \"sve\", \"ću\", \"kao\", \"tako\", \"znam\", \"biti\", \"ovdje\",\n\t\t\"nisam\", \"mogu\", \"ste\", \"bio\", \"zašto\", \"još\", \"pa\", \"nešto\", \"redu\", \"on\", \"bilo\", \"koji\", \"vas\"\n\t]\n};\n\nwhile True:\n\t#Get input and split it\n\tsentence = input(\"[Enter a sentence]\\r\\n$ \");\n\tsentenceChunks = nltk.word_tokenize(sentence);\n\n\t#Get the keys and setup another dictionary for counts of each language\n\tkeys = list(commonWords.keys());\n\tfreqCounts = dict(zip(keys, [ 0 ] * len(keys)));\n\n\t#Run through each word, if the word is in the common words, increment the counter\n\t#for the language.\n\tfor chunk in sentenceChunks:\n\t\tfor key in commonWords:\n\t\t\tif chunk in commonWords[key]:\n\t\t\t\tfreqCounts[key] += 1;\n\t\t\n\t#Find the language with the highest count\n\thighestValue = max(freqCounts.values());\n\n\t#Find all values and keys of the frequency count\n\tvalues = list(freqCounts.values());\n\tkeys = list(freqCounts.keys());\n\n\t#If there are more than one values in the frequency count dict with the same highest value,\n\t#we have a tie\n\tif values.count(highestValue) > 1:\n\t\tprint(\"I couldn't determine what language you typed.\\r\\n\");\n\t\t\n\t#Otherwise display the highest ranking (most likely) language\n\telse:\n\t\tindex = values.index(highestValue);\n\t\tprint(\"I think the language is \" + keys[index] + \"\\r\\n\");\n\t\t\n\t#And display the \"reasoning\"\n\t#print(\"\\r\\nREASONING (count of words matched)\");\n\t#print( \"----------------------------------\");\n\t#for key, value in freqCounts.items():\n\t#\tprint(\"%-10s --> %-3d\" % (key, value));\n\n","sub_path":"lab4/babel.py","file_name":"babel.py","file_ext":"py","file_size_in_byte":3258,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"548541204","text":"import random\nimport json\nimport os\nimport time\n\nfrom cookie import *\nfrom back_ground import *\nfrom ground import *\nfrom obstacle import *\nfrom item import *\nfrom score import *\nimport game_framework\nimport title_state\nimport result_state\nimport stage1_select\nimport stage2_select\nimport stage3_select\nimport stage4_select\n\nname = \"MainState\"\n\ncookie = None\nbackground = None\nnomal_fork = None\nnomal_thorn = None\nspecial_fork = None\ndouble_thorn = None\nboard = None\nitem_jelly = None\nhp_jelly = None\nobject = []\nranking_data = []\ncurrent_time = 0.0\n\ndef collide(a, b):\n left_a, bottom_a, right_a, top_a = a.get_bb()\n left_b, bottom_b, right_b, top_b = b.get_bb()\n\n if left_a > right_b: return False\n if right_a < left_b: return False\n if top_a < bottom_b: return False\n if bottom_a > top_b: return False\n\n return True\n\ndef get_frame_time():\n\n global current_time\n\n frame_time = get_time() - current_time\n current_time += frame_time\n return frame_time\n\ndef enter():\n global cookie, background, ground, nomal_fork, nomal_thorn, special_fork, double_thorn, board, \\\n start, score_jelly, hp_jelly, font, objects, score, brave_cookie, ginger_brave_cookie, f, ranking_data\n\n cookie = stage1_select.get_cookie\n brave_cookie = stage1_select.brave_cookie_select\n ginger_brave_cookie = stage1_select.ginger_brave_cookie_select\n background = Stage1_Background(800, 600)\n ground = Stage1_Ground(800, 150)\n score = Score()\n board = Stage1_Board().create()\n nomal_fork = Stage1_Nomal_Fork().create()\n nomal_thorn = Stage1_Nomal_Thorn().create()\n special_fork = Stage1_Special_Fork().create()\n double_thorn = Stage1_Double_Thorn().create()\n score_jelly = Stage1_Score_Jelly().create()\n hp_jelly = Stage1_Hp_Jelly().create()\n objects = [nomal_fork, special_fork, nomal_thorn, double_thorn, score_jelly, hp_jelly, board]\n font = load_font('Resource\\\\ENCR10B.TTF')\n start = time.time()\n\n f = open('ranking_data.txt', 'r')\n ranking_data = json.load(f)\n f.close()\n\ndef exit():\n global cookie, background, ground, nomal_fork, nomal_thorn, special_fork, double_thorn, board, start, \\\n score_jelly, hp_jelly, objects, score\n del(cookie)\n del(background)\n del(ground)\n\n for list in objects:\n for dict in list:\n list.remove(dict)\n del(dict)\n del(list)\n\n end = time.time()\n\n print(\"Stage1 Clear Time : \", (end - start))\n\ndef pause():\n pass\n\n\ndef resume():\n pass\n\n\ndef handle_events():\n global cookie\n events = get_events()\n\n for event in events:\n if event.type == SDL_QUIT:\n game_framework.quit()\n\n elif event.type == SDL_KEYDOWN and event.key == SDLK_ESCAPE:\n game_framework.change_state(title_state)\n\n elif event.type == SDL_KEYDOWN and event.key == SDLK_2:\n game_framework.change_state(stage2_select)\n\n elif event.type == SDL_KEYDOWN and event.key == SDLK_3:\n game_framework.change_state(stage3_select)\n\n elif event.type == SDL_KEYDOWN and event.key == SDLK_4:\n game_framework.change_state(stage4_select)\n\n else:\n cookie.handle_events(event)\n\ndef update():\n global cookie, brave_cookie, ginger_brave_cookie, background, ground, nomal_fork, nomal_thorn, special_fork, double_thorn, board, \\\n score_jelly, hp_jelly, objects, score\n\n frame_time = get_frame_time()\n background.update(frame_time)\n ground.update(frame_time)\n score.stage1_score()\n cookie.update(frame_time)\n\n if brave_cookie == True and cookie.hp <= 0:\n cookie = Ginger_Brave_Cookie()\n if ginger_brave_cookie == True and cookie.hp <= 0:\n cookie = Brave_Cookie()\n\n for list in objects:\n for dict in list:\n dict.update(frame_time)\n if collide(cookie, dict):\n if list == score_jelly:\n list.remove(dict)\n cookie.scoreSound(dict)\n elif list == hp_jelly:\n list.remove(dict)\n cookie.heal(dict)\n elif list == board:\n for dict in list:\n dict.state = \"None\"\n else:\n cookie.state = \"Collide\"\n\n if background.map_size >= 55 and cookie.y == 200:\n game_framework.change_state(stage2_select)\n elif background.map_size >= 55 and cookie.y == 250:\n game_framework.change_state(stage3_select)\n if (Brave_Cookie.hp <= 0) and (Ginger_Brave_Cookie.hp <= 0):\n game_framework.change_state(result_state)\n\ndef draw():\n global cookie, background, ground, objects, score\n clear_canvas()\n background.draw()\n ground.draw()\n\n for list in objects:\n for dict in list:\n dict.draw()\n\n font.draw(100, 550, 'Score : %3.2d' % score.score, (255, 255, 255))\n cookie.draw()\n\n delay(0.03)\n update_canvas()","sub_path":"stage1.py","file_name":"stage1.py","file_ext":"py","file_size_in_byte":4950,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"339849957","text":"import matplotlib.pyplot as plt\nfont = {'family' : 'MicroSoft YaHei',\n 'weight' : 'bold'\n }\nplt.rc('font', **font)\n#绘制横着的条形图\na = ['战狼2','速激2','变形金刚5','摔跤吧爸爸']\nb = [56.01,26.94,44.9,39.2]\nx = len(a)\nplt.figure(figsize=(15,10),dpi=100)\nplt.barh(a,b,height=0.3)\nplt.savefig(\"../imag/piaofang.png\")","sub_path":"code/py_matplotlib/ex4.py","file_name":"ex4.py","file_ext":"py","file_size_in_byte":350,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"278594668","text":"class Solution:\n def findSmallestSetOfVertices(self, n: int, edges: List[List[int]]) -> List[int]:\n indegree = defaultdict(list)\n \n result = []\n for i, j in edges:\n indegree[j].append(i)\n \n for i in range(n):\n if i not in indegree:\n result.append(i)\n return result","sub_path":"1557-minimum-number-of-vertices-to-reach-all-nodes/1557-minimum-number-of-vertices-to-reach-all-nodes.py","file_name":"1557-minimum-number-of-vertices-to-reach-all-nodes.py","file_ext":"py","file_size_in_byte":351,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"482457222","text":"import json\nfrom time import sleep\nfrom selenium import webdriver\nfrom selenium.webdriver.chrome.options import Options\n\n\nopts = Options()\nopts.add_argument(\n \"user-agent=Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/50.0.2661.86 Safari/537.36\")\n# opts.add_argument('--headless') # 无头模式\n\ndriver = webdriver.Chrome(chrome_options=opts)\n\n\ndef Login():\n driver.get(\"http://s.dianping.com/event/shenzhen\")\n login = driver.find_element_by_xpath('//*[contains(text(),\"登录\")]')\n login.click()\n print('请扫描登录')\n sleep(10)\n dp = driver.get_cookie('dper')\n if dp is not None:\n print(dp)\n with open(\"dper.txt\", \"r+\") as f:\n f.seek(0)\n f.write(dp['value'])\n f.write('\\n')\n print('登录成功，dper存入成功')\n else:\n print('未登录成功，dper存取失败')\n\n\n\n#\n# def writeCookies(cookies):\n# \"\"\"\n# 从浏览器中向文件写入cookies\n# \"\"\"\n# with open(\"cookies.json\", \"w\") as f:\n# json.dump(cookies, f)\n\n\nif __name__ == '__main__':\n try:\n Login()\n except Exception as e:\n print(e)\n # driver.quit()\n print('退出浏览器了')\n","sub_path":"src/login.py","file_name":"login.py","file_ext":"py","file_size_in_byte":1238,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"566910151","text":"black, white, empty, outer = 1, 2, 0, 3\ndirections = [-11, -10, -9, -1, 1, 9, 10, 11]\n\ndef bracket(board, player, square):\n\topp = opponent_color(player)\n\tfor d in directions:\n\t\tk = square + d\n\t\tif board[k] is not opp:\n\t\t\tcontinue\n\t\twhile board[k] is opp:\n\t\t\tk = k + d\n\t\tif board[k] is player:\n\t\t\tk = k - d\n\t\t\twhile k != square:\n\t\t\t\tboard[k] = player\n\t\t\t\tk = k - d\n\ndef would_bracket(board, player, square):\n\topp = opponent_color(player)\n\tfor d in directions:\n\t\tk = square + d\n\t\tif board[k] is not opp:\n\t\t\tcontinue\n\t\twhile board[k] is opp:\n\t\t\tk = k + d\n\t\tif board[k] is player:\n\t\t\treturn True\n\treturn False\n\ndef get_legal_moves(board, player):\n\tpossible = []\n\tfor row in range(10, 90, 10):\n\t\tfor col in range(1, 9):\n\t\t\tsquare = row + col\n\t\t\tif board[square] is not empty:\n\t\t\t\tcontinue\n\t\t\tif would_bracket(board, player, square):\n\t\t\t\tpossible.append(square)\n\treturn possible\n\ndef opponent_color(player):\n\tif player is black: \n\t\treturn white\n\treturn black\n\ndef pick(board,player):\n\tposs=get_legal_moves(board,player)\n\tif len(poss)==0:\n\t\treturn None\n\n\treturn poss[0]\n","sub_path":"AI_1/Lab10/jlowest.py","file_name":"jlowest.py","file_ext":"py","file_size_in_byte":1063,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"593230159","text":"\"\"\"\nThe wrapper over the spaCy's Tokenizer for `English`,`German`,`Spanish`,`Portuguese`,`French`,`Italian`, and `Dutch`.\n Based on the library's documentation website, the tokenization algorithm can be summarized as follows:\n 1. Iterate over space-separated substrings\n 2. Check whether we have an explicitly defined rule for this substring. If we do, use it.\n 3. Otherwise, try to consume a prefix.\n 4. If we consumed a prefix, go back to the beginning of the loop, so that special-cases always get priority.\n 5. If we didn't consume a prefix, try to consume a suffix.\n 6. If we can't consume a prefix or suffix, look for \"infixes\" — stuff like hyphens etc.\n 7. Once we can't consume any more of the string, handle it as a single token.\nFor more info regarding the tokenizer please see the \"Tokenization\" part of https://spacy.io/usage/linguistic-features\nA valid use case of the tokenizer wrapper class could be:\n SpaCyTokenizer().tokenize(\"This is a test\", LanguageIdentifier.en)\n\"\"\"\nfrom typing import List\n\nimport spacy\n\nfrom translate.readers.constants import LanguageIdentifier as LId\n\n__author__ = \"Hassan S. Shavarani\"\n\n\nclass SpaCyTokenizer:\n def __init__(self):\n \"\"\"\n The tokenizer performs lazy instantiation of the models. You don't need multiple instances of this class for\n tokenization of sentences from different languages.\n \"\"\"\n self._models = {}\n self._supported_languages = [LId.en, LId.de, LId.es, LId.pt, LId.fr, LId.it, LId.nl]\n\n def tokenize(self, text: str, lang_identifier: LId, lower_case: bool = False) -> List[str]:\n \"\"\"\n :param text: the string to be tokenized\n :param lang_identifier: one of the langugage values defined in `translate.readers.constants.LanguageIdentifier`\n :param lower_case: the flag indicating whether the resulting tokens need to be lower-cased or not.\n :return: the list of tokenized strings\n \"\"\"\n if lang_identifier not in self._supported_languages:\n raise ValueError(\"SpaCyTokenizer cannot tokenize utterances in \\\"{}\\\"\".format(lang_identifier.name))\n if lang_identifier not in self._models:\n try:\n self._models[lang_identifier] = spacy.load(lang_identifier.name)\n except OSError:\n raise EnvironmentError(\"The spaCy resources for \\\"{0}\\\" might not be installed correctly, please try \"\n \"running the following command in your comman-line before running this project\\n\"\n \"python -m spacy download {0}\".format(lang_identifier.name))\n tokenized_document = self._models[lang_identifier].tokenizer(text)\n if lower_case:\n return [token.text.lower() for token in tokenized_document]\n else:\n return [token.text for token in tokenized_document]\n","sub_path":"src/translate/readers/tokenizer.py","file_name":"tokenizer.py","file_ext":"py","file_size_in_byte":2903,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"286900595","text":"# OWD - 36821\n# Delete the NO revoked URL in Shared URL when there are NO revoked\n# entries in different days - Clean Shared Links - Clean All\n\nfrom gaiatest import GaiaTestCase\nfrom OWDTestToolkit.utils.utils import UTILS\nfrom OWDTestToolkit.apps.loop import Loop\nfrom OWDTestToolkit.apps.settings import Settings\nfrom OWDTestToolkit import DOM\nfrom OWDTestToolkit.utils.contacts import MockContact\n\n\nclass main(GaiaTestCase):\n\n def setUp(self):\n GaiaTestCase.setUp(self)\n self.UTILS = UTILS(self)\n self.loop = Loop(self)\n self.settings = Settings(self)\n\n self.scenario = \"scenarios/urls/multiple/available/diff_day/idb\"\n self.aux_files_dir = self.UTILS.general.get_config_variable(\"aux_files\", \"loop\")\n self.fxa_user = self.UTILS.general.get_config_variable(\"fxa_user\", \"common\")\n self.fxa_pass = self.UTILS.general.get_config_variable(\"fxa_pass\", \"common\")\n self.connect_to_network()\n\n # Insert our test contacts\n number_of_contacts = 3\n contact_given = \"Test\"\n contact_family = map(str, range(1, number_of_contacts + 1))\n contact_name = [\"{} {}\".format(contact_given, contact_family[i])\n for i in range(number_of_contacts)]\n contact_numbers = [\"666666666666\", \"777777777777\", \"888888888888\"]\n\n test_contacts = [MockContact(name=contact_name[i], givenName=contact_given,\n familyName=contact_family[i],\n tel={'type': 'Mobile', 'value': contact_numbers[i]})\n for i in range(number_of_contacts)]\n map(self.UTILS.general.insertContact, test_contacts)\n\n self.loop.initial_test_checks()\n\n # Make sure we're not logged in FxA\n self.settings.launch()\n self.settings.fxa()\n self.settings.fxa_log_out()\n\n def tearDown(self):\n self.UTILS.reporting.reportResults()\n GaiaTestCase.tearDown(self)\n\n def test_run(self):\n self.loop.launch()\n # This needs to be done at this point, bcs if the app is freshly installed the persistence\n # directories are not in its place until the app is launched for the first time\n self.loop.update_db(\"{}/{}\".format(self.aux_files_dir, self.scenario))\n result = self.loop.wizard_or_login()\n\n if result:\n self.loop.firefox_login(self.fxa_user, self.fxa_pass)\n self.loop.allow_permission_ffox_login()\n self.UTILS.element.waitForElements(DOM.Loop.app_header, \"Loop main view\")\n\n self.loop.switch_to_urls()\n previous = self.loop.get_number_of_available_urls()\n\n self.loop.open_settings()\n self.loop.delete_all_urls(cancel=False)\n\n self.UTILS.element.waitForElements(DOM.Loop.call_log, \"Check we are returned to the call log\")\n current = self.loop.get_number_of_available_urls()\n self.UTILS.test.test(\n previous > current and current == 0,\n \"Check that after deleting all URLs of different days when there are only available, there's nothing\")\n","sub_path":"tests/LOOP/test_36821.py","file_name":"test_36821.py","file_ext":"py","file_size_in_byte":3101,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"168950299","text":"###############################################################################\n# Controller file that will hold the main driver function #\n# This will also deal with the startup script #\n# #\n###############################################################################\n################################ Daniel Massa #################################\n\nimport sys\nimport cocos\nimport random\nimport time\nfrom Person import Person\nfrom UI import UI\nfrom settings import Road\nfrom settings import Mode\nfrom settings import DEFAULT_SPEEDS\nfrom cocos.director import director\nfrom cocos.scene import Scene\n\nrandom.seed(time.time())\n\n\n#Program Launch settings management \nif __name__ == \"__main__\":\n guide = \"\"\"\n $ python {0} Program Mode [speed1 [speed2 [...]]]\n\n Program_Mode:\n 0 -- Single Person Bridge Simulator\n 1 -- Single Direction Bridge Simulation\n\n Speed and Number of People: To indicate the number of cars and the initial\n walking speed of the people, please enter positive integers for speed. Enter \n speeds for the number of people you desire for the simulation\n\n For the animation, reasonable speeds are between 75 and 300\n \"\"\".format(sys.argv[0])\n\n\n #Make sure user has entered enough arguements\n if len(sys.argv) < 2:\n print (\"ERROR: Not enough arguements\")\n print (guide)\n sys.exit()\n #Make sure user has selected a valid Mode\n if int(sys.argv[1]) not in Mode():\n print (\"ERROR: Invalid Program Mode\")\n print (guide)\n sys.exit()\n #Make sure selected speeds are positive numbers\n if len(sys.argv) > 2:\n speeds = sys.argv[2:]\n for input_speed in speeds:\n try:\n speed = int(input_speed)\n if speed <= 0:\n raise ValueError\n except ValueError:\n print(\"ERROR: {0} is not a valid speed.\".format(input_speed))\n print(guide)\n sys.exit()\n\n\ndef main():\n\n #Identify Mode\n mode = int(sys.argv[1])\n #Save walking speeds for the creation of the people objects\n if len(sys.argv) > 2:\n walkingSpeeds = sys.argv[2:]\n else:\n walkingSpeeds = DEFAULT_SPEEDS\n #Identify Number of People\n numPeople = len(walkingSpeeds)\n\n\n #Print program settings to shell\n if mode == 0:\n print (\"Mode: Single Person Bridge\\n\")\n if mode == 1:\n print (\"Mode: Single Direction Bridge\\n\")\n print (\"Selected Walking Speeds: {0}\\n\".format(walkingSpeeds))\n print (\"Number of People: {0}\\n\".format(numPeople))\n\n director.init(caption=\"Daniel Massa - Comp Sci 5800 - Bridge Problem\")\n\n #Initiate People\n People = [Person(count, walkingSpeeds[count], mode) for count in range(0,len(walkingSpeeds))]\n\n # Make each person aware of all other people, this is the list of objects a person needs \n # permission from in order to enter the bridge\n for count in range(0,len(walkingSpeeds)):\n People[count].other_People = People\n \n for count in range(0,len(People)):\n if any(People[count].position == P for P in [Road.W, Road.SW, Road.NW]):\n People[count].bridge_entry_point = Road.E\n else:\n People[count].bridge_entry_point = Road.W\n\n #Load UI\n layer = UI.Layer(People)\n eventHandler = UI.Event_Handler(People)\n color_layer = cocos.layer.ColorLayer(144,238,144, 255)\n scene = Scene(eventHandler, color_layer, layer)\n print(\"Launching UI\")\n director.run(scene)\n\n\nif __name__ == \"__main__\":\n main()","sub_path":"demo.py","file_name":"demo.py","file_ext":"py","file_size_in_byte":3650,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"550891620","text":"\"\"\"added skipped_wells table\n\nRevision ID: ef256df5169c\nRevises: 5181de7d6275\nCreate Date: 2017-05-10 10:27:49.116133\n\n\"\"\"\nfrom alembic import op\nimport sqlalchemy as sa\n\n\n# revision identifiers, used by Alembic.\nrevision = 'ef256df5169c'\ndown_revision = '5181de7d6275'\nbranch_labels = None\ndepends_on = None\n\n\ndef upgrade():\n # ### commands auto generated by Alembic - please adjust! ###\n op.create_table('skipped_wells',\n sa.Column('schedule_id', sa.Integer(), nullable=True),\n sa.Column('well_id', sa.Integer(), nullable=True),\n sa.ForeignKeyConstraint(['schedule_id'], ['schedule.id'], ),\n sa.ForeignKeyConstraint(['well_id'], ['well.id'], )\n )\n # ### end Alembic commands ###\n\n\ndef downgrade():\n # ### commands auto generated by Alembic - please adjust! ###\n op.drop_table('skipped_wells')\n # ### end Alembic commands ###\n","sub_path":"alembic/versions/ef256df5169c_added_skipped_wells_table.py","file_name":"ef256df5169c_added_skipped_wells_table.py","file_ext":"py","file_size_in_byte":860,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"1144281","text":"import requests\nimport base64\nclass OpenHab:\n\n def __init__(self): \n self.openhab_host = \"localhost\"\n self.openhab_port = \"8080\"\n\n def post_command(self, key, value):\n print(\"appel de post_command(\" + key +\",\"+ value +\")\")\n \"\"\" Post a command to OpenHAB - key is item, value is command \"\"\"\n url = 'http://%s:%s/rest/items/%s'%(self.openhab_host,\n self.openhab_port, key)\n try:\n req = requests.post(url, data=value,\n headers=self.basic_header())\n except requests.ConnectionError:\n print (\" Erreur dans l'adressage du serveur openHab\")\n\n def put_status(self, key, value):\n \"\"\" Put a status update to OpenHAB key is item, value is state \"\"\"\n url = 'http://%s:%s/rest/items/%s/state'%(self.openhab_host,\n self.openhab_port, key)\n req = requests.put(url, data=value, headers=self.basic_header())\n if req.status_code != requests.codes.ok:\n req.raise_for_status()\n\n def get_status(self, name):\n \"\"\" Request updates for any item in group NAME from OpenHAB.\n Long-polling will not respond until item updates.\n \"\"\"\n # When an item in Group NAME changes we will get all items in the group \n # and need to determine which has changed\n url = 'http://%s:%s/rest/items/%s'%(self.openhab_host,\n self.openhab_port, name)\n payload = {'type': 'json'}\n try:\n req = requests.get(url, params=payload,\n headers=self.polling_header())\n if req.status_code != requests.codes.ok:\n req.raise_for_status()\n # Try to parse JSON response\n # At top level, there is type, name, state, link and members array\n members = req.json()[\"members\"]\n for member in members:\n # Each member has a type, name, state and link\n name = member[\"name\"]\n state = member[\"state\"]\n do_publish = True\n # Pub unless we had key before and it hasn't changed\n if name in self.prev_state_dict:\n if self.prev_state_dict[name] == state:\n do_publish = False\n self.prev_state_dict[name] = state\n if do_publish:\n self.publish(name, state)\n except:\n print(\"error located in openhab.py\")\n\n def basic_header(self):\n \"\"\" Header for OpenHAB REST request - standard \"\"\"\n \"\"\"self.auth = base64.encodestring('%s:%s'\n %(self.username, self.password)\n ).replace('\\n', '')\"\"\"\n return {\n #\"Authorization\" : \"Basic %s\" %self.auth,\n \"Content-type\": \"text/plain\"}\n\n\n","sub_path":"openhab.py","file_name":"openhab.py","file_ext":"py","file_size_in_byte":2933,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"570612328","text":"# Install python 3, duh!\n# Run the command below in a cmd window to install the needed packages, without the #, duh!\n# pip install bs4 requests pandas openpyxl lxml html5lib\n# Run the python file with the included batch file, DUH!\n\ntry:\n # Error handling if something happens during script initialisation\n from csv import QUOTE_ALL # Needed to export data to CSV\n from bs4 import BeautifulSoup # Needed to parse the dynamic webpage of the Ducanator\n from requests import get # Needed to get the webpage of the Ducanator\n from re import search # Needed to find the json string to import into pandas\n from pandas import read_csv, set_option, concat, DataFrame, read_json, read_html, ExcelWriter # Needed to convert the json string into a usable dataframe object for manipulation\n from traceback import format_exc # Needed for more friendly error messages.\n from openpyxl import load_workbook\n from numpy import arange\n from os import path\nexcept ModuleNotFoundError:\n print('OOPSIE WOOPSIE!! Uwu We made a fucky wucky!! A wittle fucko boingo! The code monkeys at our headquarters are working VEWY HAWD to fix this!')\n print('You didn\\'t install the packages like I told you to. Please run \\\"pip install bs4 requests pandas\\\" in a cmd window to install the required packages!')\n print('\\033[1;31m' + format_exc())\n exit(1)\n\ntry:\n #User Variables\n workbook_name = 'Prime_Relic_Data.xlsx'\n csv_name = 'Prime-Relic Data.csv'\n sheet_name_day = 'Day'\n sheet_name_hour = 'Hour'\n sheet_name_relic = 'Relic_Data'\n retry_attempts = 10\n # Sets the URL to scrape, because hard-coding is bad\n print('Downloading Ducat Data')\n url_ducats = \"https://warframe.market/tools/ducats\"\n # Scrapes the given URL\n soup = str(BeautifulSoup(get(url_ducats).content, \"html.parser\")).replace('\\n', '')\n print('Ducat Data Downloaded')\n print('Processing Ducat Data')\n # Finds the needed json string for item data, previous hour data, and previous day data.\n # Slices off the first bit to make a valid json string for pandas later\n items = search('\"items\": (\\[(?:\\[??[^\\[]*?\\]))', soup).group(0)[9:]\n previous_hour = search('\"previous_hour\": (\\[(?:\\[??[^\\[]*?\\]))', soup).group(0)[17:]\n previous_day = search('\"previous_day\": (\\[(?:\\[??[^\\[]*?\\]))', soup).group(0)[16:]\n\n # Reads and sanitises the item data into a pandas dataframe\n df_items = read_json(items)\n df_items = df_items.drop(columns=['url_name', 'thumb'])\n df_items = df_items.reindex(columns=['id', 'item_name'])\n\n # Reads and sanitises the previous day data into a pandas dataframe\n df_previous_day = read_json(previous_day)\n df_previous_day = df_previous_day.drop(columns=['id', 'plat_worth', 'median'])\n df_previous_day = df_previous_day.rename(columns={'item': 'id'})\n # Merges the item data and previous day data on the id column, drops the redundant id column, then renames the column names for export\n df_previous_day_merged = df_items.merge(df_previous_day, how='inner', on='id')\n df_previous_day_merged = df_previous_day_merged.drop(columns=['id'])\n df_previous_day_merged = df_previous_day_merged.reindex(columns=['item_name', 'datetime', 'ducats_per_platinum', 'ducats', 'wa_price','ducats_per_platinum_wa', 'position_change_month', 'position_change_week', 'position_change_day', 'volume'])\n df_previous_day_merged = df_previous_day_merged.sort_values(by='item_name')\n df_previous_day_merged['datetime'] = df_previous_day_merged['datetime'].astype(str).str[:-6]\n\n # Reads and sanitises the previous hour data into a pandas dataframe\n df_previous_hour = read_json(previous_hour)\n df_previous_hour = df_previous_hour.drop(columns=['id', 'plat_worth', 'median'])\n df_previous_hour = df_previous_hour.rename(columns={'item': 'id'})\n # Merges the item data and previous hour data on the id column, drops the redundant id column, then renames the column names for export\n df_previous_hour_merged = df_items.merge(df_previous_hour, how='inner', on='id')\n df_previous_hour_merged = df_previous_hour_merged.drop(columns=['id'])\n df_previous_hour_merged = df_previous_hour_merged.reindex(columns=['item_name', 'datetime', 'ducats_per_platinum', 'ducats', 'wa_price','ducats_per_platinum_wa', 'position_change_month', 'position_change_week', 'position_change_day', 'volume'])\n df_previous_hour_merged = df_previous_hour_merged.sort_values(by='item_name')\n df_previous_hour_merged['datetime'] = df_previous_hour_merged['datetime'].astype(str).str[:-6]\n df_previous_hour_merged = df_previous_hour_merged.reset_index(drop=True)\n\n print('Ducat Data Processed')\n # Fuck Comments\n print('Downloading Relic Data')\n url_relics = \"https://n8k6e2y6.ssl.hwcdn.net/repos/hnfvc0o3jnfvc873njb03enrf56.html\"\n relic_data_txt_name = 'RelicData.txt'\n\n if path.isfile(relic_data_txt_name):\n with open(relic_data_txt_name) as f:\n soup = str(f.readlines())\n print(\"Loaded Local Relic Data\")\n else:\n print(\"Loading Remote Item Data\")\n\n for x in range(0, retry_attempts):\n try:\n soup = str(BeautifulSoup(get(url_relics).content, \"html.parser\")).replace('\\n', '')\n print('Saving Local Data')\n with open(relic_data_txt_name, 'w') as f:\n f.write(soup)\n break\n except Exception:\n print('Relic data download failed, retrying... ' + str(retry_attempts - x - 1) + ' attempts left...', end='\\r')\n\n\n print('Relic Data Downloaded')\n print('Processing Relic Data')\n parsed_relics = search('.*?
', soup).group(0)[34:].replace('th>', 'td>').replace(r'', r' ').replace('X Kuva', 'x Kuva')\n df_parsed_relics = read_html(parsed_relics, header=None)\n df_parsed_relics = df_parsed_relics[0].replace(to_replace=r'.+\\((.+)\\%\\)', value=r'\\1', regex=True)\n df_parsed_relics[1] = df_parsed_relics[1].astype(float)\n df_parsed_relics = df_parsed_relics.dropna(how='all').fillna(999)\n groups = df_parsed_relics.groupby(arange(len(df_parsed_relics.index)) // 7, sort=False).apply(lambda x: x.sort_values(by=1, ascending=False))\n groups[1] = ' (' + groups[1].astype(str) + '%)'\n groups = groups[0] + groups[1]\n groups = groups.replace(to_replace=r'\\(999.0\\%\\)', value=r'', regex=True)\n templist = []\n templist2 = []\n for count, value in enumerate(groups):\n if count % 7 == 0 and count != 0:\n templist2.append(templist)\n templist = []\n templist.append(value)\n df_even_more_parsed_relics = DataFrame(templist2, columns=['Relic_Name', 'C1', 'C2', 'C3', 'U1', 'U2', 'Rare'])\n df_relic_class = df_even_more_parsed_relics['Relic_Name'].str.split().str[0]\n df_even_more_parsed_relics.insert(len(df_even_more_parsed_relics.columns), 'Class', df_relic_class, allow_duplicates=True)\n df_even_more_parsed_relics.insert(len(df_even_more_parsed_relics.columns), 'Type', df_even_more_parsed_relics['Relic_Name'].str.upper().str.split().str[1], allow_duplicates=True)\n df_even_more_parsed_relics.insert(len(df_even_more_parsed_relics.columns), 'Refinement', df_even_more_parsed_relics['Relic_Name'].str.split().str[3].replace(to_replace=r'[\\(\\)]', value=r'', regex=True), allow_duplicates=True)\n dict = {'Exceptional':'','Flawless':'','Radiant':''}\n df_even_more_parsed_relics.insert(len(df_even_more_parsed_relics.columns), 'C1_Raw', df_even_more_parsed_relics['C1'].replace(to_replace=r' \\(.+\\)',value='',regex=True))\n df_even_more_parsed_relics.insert(len(df_even_more_parsed_relics.columns), 'C2_Raw', df_even_more_parsed_relics['C2'].replace(to_replace=r' \\(.+\\)',value='',regex=True))\n df_even_more_parsed_relics.insert(len(df_even_more_parsed_relics.columns), 'C3_Raw', df_even_more_parsed_relics['C3'].replace(to_replace=r' \\(.+\\)',value='',regex=True))\n df_even_more_parsed_relics.insert(len(df_even_more_parsed_relics.columns), 'U1_Raw', df_even_more_parsed_relics['U1'].replace(to_replace=r' \\(.+\\)',value='',regex=True))\n df_even_more_parsed_relics.insert(len(df_even_more_parsed_relics.columns), 'U2_Raw', df_even_more_parsed_relics['U2'].replace(to_replace=r' \\(.+\\)',value='',regex=True))\n df_even_more_parsed_relics.insert(len(df_even_more_parsed_relics.columns), 'Rare_Raw', df_even_more_parsed_relics['Rare'].replace(to_replace=r' \\(.+\\)',value='',regex=True))\n df_even_more_parsed_relics.insert(len(df_even_more_parsed_relics.columns), 'C1_Odds', df_even_more_parsed_relics['C1'].replace(to_replace=r'.+\\((.+)\\%\\)',value=r'\\1',regex=True).astype(float))\n df_even_more_parsed_relics.insert(len(df_even_more_parsed_relics.columns), 'C2_Odds', df_even_more_parsed_relics['C2'].replace(to_replace=r'.+\\((.+)\\%\\)',value=r'\\1',regex=True).astype(float))\n df_even_more_parsed_relics.insert(len(df_even_more_parsed_relics.columns), 'C3_Odds', df_even_more_parsed_relics['C3'].replace(to_replace=r'.+\\((.+)\\%\\)',value=r'\\1',regex=True).astype(float))\n df_even_more_parsed_relics.insert(len(df_even_more_parsed_relics.columns), 'U1_Odds', df_even_more_parsed_relics['U1'].replace(to_replace=r'.+\\((.+)\\%\\)',value=r'\\1',regex=True).astype(float))\n df_even_more_parsed_relics.insert(len(df_even_more_parsed_relics.columns), 'U2_Odds', df_even_more_parsed_relics['U2'].replace(to_replace=r'.+\\((.+)\\%\\)',value=r'\\1',regex=True).astype(float))\n df_even_more_parsed_relics.insert(len(df_even_more_parsed_relics.columns), 'Rare_Odds', df_even_more_parsed_relics['Rare'].replace(to_replace=r'.+\\((.+)\\%\\)',value=r'\\1',regex=True).astype(float))\n df_even_more_parsed_relics = df_even_more_parsed_relics.replace(to_replace=r'Systems Blueprint',value=r'Systems', regex=True)\n df_even_more_parsed_relics = df_even_more_parsed_relics.replace(to_replace=r'Neuroptics Blueprint',value=r'Neuroptics', regex=True)\n df_even_more_parsed_relics = df_even_more_parsed_relics.replace(to_replace=r'Chassis Blueprint',value=r'Chassis', regex=True)\n #print(df_even_more_parsed_relics.head(5))\n #df_even_more_parsed_relics['Relic_Name'] = df_even_more_parsed_relics['Relic_Name'].str.split(n=1).str[1]\n #df_axi = df_even_more_parsed_relics[df_even_more_parsed_relics['Relic_Class']=='Axi'].reset_index(drop=True)\n #df_lith = df_even_more_parsed_relics[df_even_more_parsed_relics['Relic_Class']=='Lith'].reset_index(drop=True)\n #df_meso = df_even_more_parsed_relics[df_even_more_parsed_relics['Relic_Class']=='Meso'].reset_index(drop=True)\n #df_neo = df_even_more_parsed_relics[df_even_more_parsed_relics['Relic_Class']=='Neo'].reset_index(drop=True)\n #df_requiem = df_even_more_parsed_relics[df_even_more_parsed_relics['Relic_Class']=='Requiem'].reset_index(drop=True)\n #df_final_export_relic = concat([df_axi,df_lith,df_meso,df_neo,df_requiem], axis=1, ignore_index=True)\n #print(df_even_more_parsed_relics)\n print('Relic Data Processed')\n\n # Export data\n print('Exporting Worksheet')\n df_even_more_parsed_relics.to_csv(csv_name, index=None, quoting=QUOTE_ALL)\n df_previous_day_merged.to_csv('DayPrices.csv', index=None, quoting=QUOTE_ALL)\n with ExcelWriter(workbook_name, mode='a', engine='openpyxl', if_sheet_exists='replace') as writer:\n df_previous_day_merged.to_excel(writer, sheet_name=sheet_name_day)\n df_previous_hour_merged.to_excel(writer, sheet_name=sheet_name_hour)\n df_even_more_parsed_relics.to_excel(writer, sheet_name=sheet_name_relic)\n #df_final_export_relic.to_excel(writer, sheet_name=sheet_name_relic)\n book = load_workbook(workbook_name)\n sheet = book[sheet_name_day]\n sheet.delete_cols(1,1)\n sheet = book[sheet_name_hour]\n sheet.delete_cols(1,1)\n sheet = book[sheet_name_relic]\n sheet.delete_cols(1,1)\n book.save(workbook_name)\n print('If you see this message, things should have worked correctly. Remove the \\\"pause\\\" from the batch script to automatically close this window after use.')\n\nexcept Exception:\n # Error handling if something happens during the main script\n print('OOPSIE WOOPSIE!! Uwu We made a fucky wucky!! A wittle fucko boingo! The code monkeys at our headquarters are working VEWY HAWD to fix this!')\n print('\\033[1;31m' + format_exc())\n exit(1)\n","sub_path":"Scrape the Ducanator.py","file_name":"Scrape the Ducanator.py","file_ext":"py","file_size_in_byte":12314,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"421601245","text":"import re\n\nfrom get_word import get_word\nfrom clear import clear\nfrom color import gray, red\nfrom render_noose import render_noose\n\nCHANCES = 7\n\nclass Hangman:\n def __init__(self):\n self.word = get_word().upper()\n self.used_incorrect_letters = []\n self.messages = []\n \n self.letters = {}\n for letter in self.word:\n if letter in [\".\", \" \"]:\n continue\n self.letters[letter] = False\n \n \n def render(self):\n clear()\n print(gray(\"( To exit, hit Ctrl + C )\\n\\n\"))\n count = \"(\" + str(len(self.used_incorrect_letters)) + \"/\" + str(CHANCES) + \")\"\n if (CHANCES - len(self.used_incorrect_letters) < 3):\n count = red(count)\n else:\n count = gray(count)\n render_noose(len(self.used_incorrect_letters))\n print(\"Used \" + count + \": \" + \" \".join(self.used_incorrect_letters))\n print(self.make_word_bar())\n print(self.make_message_box()) \n\n def make_word_bar(self):\n word_bar = \"\"\n for letter in self.word:\n if letter == \" \":\n word_bar = word_bar + \" \"\n elif letter == \".\":\n word_bar = word_bar + \" . \"\n elif self.has_letter(letter) and self.letters[letter]:\n word_bar = word_bar + \" \" + letter + \" \"\n else:\n word_bar = word_bar + \" _ \"\n return word_bar\n \n def make_message_box(self):\n box = \" ____________________________________________________ \"\n box = box + \"\\n| |\"\n \n for message in self.messages:\n box = box + \"\\n| \" + message\n for i in range(50 - len(message)):\n box = box + \" \"\n box = box + \" |\"\n\n if not len(self.messages):\n box = box + \"\\n| |\"\n box = box + \"\\n| |\"\n \n box = box + \"\\n|____________________________________________________|\"\n \n return box\n\n def prompt(self):\n letter = input(\"Pick a letter > \")\n self.clear_messages()\n\n if (letter.upper() in self.used_incorrect_letters \n or (self.has_letter(letter) and self.letters[letter])):\n self.message(\"Whoa there partner, you already used that letter. The ole thinker gettin dusty?\")\n return\n \n if not re.match(r'[A-Z]', letter.upper()):\n self.message(\"Ope, I guess I should've told ya, you only need to worry about letters from A-Z\")\n return\n \n if letter.upper() not in self.letters:\n self.used_incorrect_letters.append(letter.upper())\n self.message(\"Careful there partner. The ole rascal can only take so much. Be more careful next time.\")\n return\n self.letters[letter.upper()] = True\n\n def message(self, message):\n line = \"\"\n for letter in message:\n line = line + letter\n \n if (len(line) == 50):\n self.messages.append(line)\n line = \"\"\n if len(line):\n self.messages.append(line)\n \n def clear_messages(self):\n self.messages = []\n\n def has_letter(self, letter):\n return letter in self.letters\n \n def has_won(self):\n for letter in self.word:\n if not self.has_letter(letter):\n continue\n if not self.letters[letter]:\n return False\n return True\n\n def has_lost(self):\n return len(self.used_incorrect_letters) >= CHANCES\n","sub_path":"hangman.py","file_name":"hangman.py","file_ext":"py","file_size_in_byte":3737,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"152187708","text":"from PyQt5.QtCore import QThread, pyqtSignal\nimport socket\nimport errno\n\n\nclass ClientThread(QThread):\n oppo = pyqtSignal(str)\n rply = pyqtSignal(str)\n error = pyqtSignal(str)\n rematch = pyqtSignal(str)\n draw = pyqtSignal(str)\n\n def __init__(self, username, ip, parent=None):\n super(ClientThread, self).__init__(parent)\n self.username = username\n self.ip = ip\n\n def run(self):\n rcv = False\n self.s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n try:\n self.s.connect((self.ip, 1234))\n self.s.sendall(bytes(self.username, 'utf-8'))\n except ConnectionRefusedError as e:\n self.error.emit(\"nTarget Refused to Connect\")\n\n try:\n while True:\n msg = self.s.recv(10)\n msg = msg.decode('utf-8')\n\n if not rcv:\n self.oppo.emit(msg)\n rcv = True\n\n elif msg == \"D\":\n self.draw.emit(msg)\n\n elif msg == \"R\":\n self.rematch.emit(msg)\n\n else:\n self.rply.emit(msg)\n\n except IOError as e:\n if e.errno != errno.EAGAIN and e.errno != errno.EWOULDBLOCK:\n if rcv:\n self.error.emit(\"yOpponent Disconnected\")\n\n except Exception as e:\n self.error.emit('yUnknown Error: {}'.format(str(e)))\n\n def send(self, data):\n self.s.sendall(bytes(data, \"utf-8\"))\n","sub_path":"Client.py","file_name":"Client.py","file_ext":"py","file_size_in_byte":1513,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"495205823","text":"from lxml import etree\nimport dateutil.parser\nfrom pandas import DataFrame, Series\nimport pandas as pd\nfrom functools import reduce\nimport json\nimport pymongo\nfrom pymongo import MongoClient\n\nclass MroReader:\n def __init__(self, afilter, **kwargs):\n super().__init__(**kwargs)\n self.item_dicts=[]\n self.afilter=afilter\n\n def display(self):\n for item_dict in self.item_dicts:\n print(item_dict)\n\n def read(self, item_measurement, item_id):\n for item_element in item_measurement:\n if item_element.tag == 'smr':\n item_key = item_element.text.replace('MR.', '').split(' ')\n else:\n centerFilled=False\n item_dict = {}\n neighbor_list=[]\n for item_v in item_element:\n item_value = item_v.text.replace('NIL', '-1').split(' ')\n _item_sub_dict = dict(zip(item_key, map(int, item_value)))\n _item_sub_dict = {k: v for k, v in _item_sub_dict.items() if not any(ext in k for ext in self.afilter)}\n if _item_sub_dict['LteNcPci']>=0:\n _neighbor={}\n _neighbor.update({'Pci': _item_sub_dict['LteNcPci']})\n _neighbor.update({'Rsrp': _item_sub_dict['LteNcRSRP']})\n neighbor_list.append(_neighbor)\n else:\n break\n if not centerFilled:\n item_dict.update(item_element.attrib)\n item_dict.update({'Rsrp': _item_sub_dict['LteScRSRP']})\n item_dict.update({'SinrUl': _item_sub_dict['LteScSinrUL']})\n item_dict.update({'Ta': _item_sub_dict['LteScTadv']})\n item_dict.update({'Pci': _item_sub_dict['LteScPci']})\n centerFilled=True\n if len(neighbor_list)>0:\n item_dict.update({'NeighborList': neighbor_list})\n self.item_dicts.append(item_dict)\n\n def read_zte(self, item_measurement, item_id):\n for item_element in item_measurement:\n if item_element.tag == 'smr':\n item_key = item_element.text.replace('MR.', '').split(' ')\n if 'LteScEarfcn' not in item_key:\n return\n else:\n centerFilled=False\n item_dict = {}\n neighbor_list=[]\n for item_v in item_element:\n item_value = item_v.text.replace('NIL', '-1').split(' ')\n _item_sub_dict = dict(zip(item_key, map(int, item_value)))\n _item_sub_dict = {k: v for k, v in _item_sub_dict.items() if not any(ext in k for ext in self.afilter)}\n if _item_sub_dict['LteNcPci']>=0:\n _neighbor={}\n _neighbor.update({'Pci': _item_sub_dict['LteNcPci']})\n _neighbor.update({'Rsrp': _item_sub_dict['LteNcRSRP']})\n neighbor_list.append(_neighbor)\n else:\n break\n if not centerFilled:\n item_dict.update({'id': item_id+'-'+item_element.attrib['MR.objectId']})\n item_dict.update({'Rsrp': _item_sub_dict['LteScRSRP']})\n item_dict.update({'SinrUl': _item_sub_dict['LteScSinrUL']})\n item_dict.update({'Ta': _item_sub_dict['LteScTadv']})\n item_dict.update({'Pci': _item_sub_dict['LteScPci']})\n centerFilled=True\n if len(neighbor_list)>0:\n item_dict.update({'NeighborList': neighbor_list})\n self.item_dicts.append(item_dict)\n\n def _filter_by_neighbor_len(self, length):\n return list(filter(lambda x: True if len(x['NeighborList'])==length else False, self.item_dicts))\n\n def _map_neighbor_rsrp_diff(self, index):\n measureList=self._filter_by_neighbor_len(index)\n if len(measureList)==0:\n return []\n return list(map(lambda item: {\n 'CellId': item['id'],\n 'NeighborPci': item['NeighborList'][index-1]['Pci'],\n 'RsrpDiff': item['Rsrp']-item['NeighborList'][index-1]['Rsrp'],\n 'Rsrp': item['Rsrp'],\n 'Pci': item['Pci'],\n 'Ta': item['Ta'],\n 'SinrUl': item['SinrUl']\n }, measureList))\n\n def map_rsrp_diff(self):\n diff_list=list(map(lambda index: self._map_neighbor_rsrp_diff(index+1), list(range(6))))\n combined_list=reduce(lambda first,second: first+second,diff_list,[])\n if len(combined_list)==0:\n return []\n stat_list=list(map(lambda item: {\n 'CellId': item['CellId'],\n 'NeighborPci': item['NeighborPci'],\n 'Pci': item['Pci'],\n 'Diff0': 1 if item['RsrpDiff']<=0 else 0,\n 'Diff3': 1 if item['RsrpDiff']<=3 and item['RsrpDiff']>0 else 0,\n 'Diff6': 1 if item['RsrpDiff']<=6 and item['RsrpDiff']>3 else 0,\n 'Diff9': 1 if item['RsrpDiff']<=9 and item['RsrpDiff']>6 else 0,\n 'Diff12': 1 if item['RsrpDiff']<=12 and item['RsrpDiff']>9 else 0,\n 'DiffLarge': 1 if item['RsrpDiff']>12 else 0,\n 'RsrpBelow120': 1 if item['Rsrp']<20 else 0,\n 'RsrpBetween120110': 1 if item['Rsrp']<30 and item['Rsrp']>=20 else 0,\n 'RsrpBetween110105': 1 if item['Rsrp']<35 and item['Rsrp']>=30 else 0,\n 'RsrpBetween105100': 1 if item['Rsrp']<40 and item['Rsrp']>=35 else 0,\n 'RsrpBetween10090': 1 if item['Rsrp']<50 and item['Rsrp']>=40 else 0,\n 'RsrpAbove90': 1 if item['Rsrp']>=50 else 0,\n 'Ta0or1': 1 if item['Ta']==0 or item['Ta']==1 else 0,\n 'Ta2or3': 1 if item['Ta']==2 or item['Ta']==3 else 0,\n 'Ta4or5': 1 if item['Ta']==4 or item['Ta']==5 else 0,\n 'Ta6or7': 1 if item['Ta']==6 or item['Ta']==7 else 0,\n 'Ta8or9': 1 if item['Ta']==8 or item['Ta']==9 else 0,\n 'Ta10to12': 1 if item['Ta']>=10 and item['Ta']<=12 else 0,\n 'Ta13to15': 1 if item['Ta']>=13 and item['Ta']<=15 else 0,\n 'Ta16to19': 1 if item['Ta']>=16 and item['Ta']<=19 else 0,\n 'Ta20to24': 1 if item['Ta']>=20 and item['Ta']<=24 else 0,\n 'Ta25to29': 1 if item['Ta']>=25 and item['Ta']<=29 else 0,\n 'Ta30to39': 1 if item['Ta']>=30 and item['Ta']<=39 else 0,\n 'TaAbove40': 1 if item['Ta']>=40 else 0,\n 'SinrUl0to9': 1 if item['SinrUl']>=0 and item['SinrUl']<=9 else 0,\n 'SinrUl10to19': 1 if item['SinrUl']>=10 and item['SinrUl']<=19 else 0,\n 'SinrUl20to24': 1 if item['SinrUl']>=20 and item['SinrUl']<=24 else 0,\n 'SinrUl25to29': 1 if item['SinrUl']>=25 and item['SinrUl']<=29 else 0,\n 'SinrUl30to34': 1 if item['SinrUl']>=30 and item['SinrUl']<=34 else 0,\n 'SinrUlAbove35': 1 if item['SinrUl']>=35 else 0\n }, combined_list))\n df = DataFrame(stat_list)\n stat=df.groupby(['CellId','Pci','NeighborPci']).sum().reset_index()\n return json.loads(stat.T.to_json()).values()\n\nclass MrsReader:\n def __init__(self, mrNames, startTime, date_dir, db, **kwargs):\n self.mrNames=mrNames\n self.startTime=startTime\n self.date_dir=date_dir\n self.db=db\n return super().__init__(**kwargs)\n\n def read(self, item_measurement):\n mrName=item_measurement.attrib['mrName'].replace('MR.','')\n if mrName in self.mrNames:\n item_dicts=[]\n for item_element in item_measurement.iterchildren():\n if item_element.tag == 'smr':\n item_key = item_element.text.replace('MR.', '').replace('.','_').split(' ')\n else:\n item_dict={}\n item_dict.update({'CellId': item_element.attrib['id']})\n item_value = item_element[0].text.split(' ')\n item_dict.update(dict(zip(item_key, map(int, item_value))))\n item_dict.update({'StartTime': self.startTime})\n item_dicts.append(item_dict)\n if len(item_dicts)>0:\n self.db['mrs_'+mrName+'_'+self.date_dir].insert_many(item_dicts)\n\n def read_zte(self, item_measurement, eNodebId):\n mrName=item_measurement.attrib['mrName'].replace('MR.','')\n if mrName in self.mrNames:\n item_dicts=[]\n for item_element in item_measurement.iterchildren():\n if item_element.tag == 'smr':\n item_key = item_element.text.replace('MR.', '').replace('.','_').split(' ')\n else:\n item_dict={}\n item_dict.update({'CellId': eNodebId+'-'+item_element.attrib['MR.objectId']})\n item_value = item_element[0].text.split(' ')\n item_dict.update(dict(zip(item_key, map(int, item_value))))\n item_dict.update({'StartTime': self.startTime})\n item_dicts.append(item_dict)\n if len(item_dicts)>0:\n self.db['mrs_'+mrName+'_'+self.date_dir].insert_many(item_dicts)","sub_path":"Lte.Auxilary/mr/mr_service.py","file_name":"mr_service.py","file_ext":"py","file_size_in_byte":9319,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"630662295","text":"import math\n\nfrom latale.planner.Searcher import Searcher\nfrom latale.planner.State import State, OPEN, CLOSED\nfrom latale.planner.ReconstructionGoalDetection import ReconstructionGoalDetection\n\n\nclass GBFS(Searcher, ReconstructionGoalDetection):\n def __init__(self, oae, pruning_methods, available_actions, sae, image_threshold):\n Searcher.__init__(self, oae, pruning_methods, available_actions)\n ReconstructionGoalDetection.__init__(self, sae, image_threshold)\n self.N = None\n\n def search(self, init, goal, distance):\n self.N = len(init)\n\n def heuristic(x):\n return distance(x, goal)\n\n _init = State(init, g=0, h=heuristic(init))\n\n self.open_list.put((_init.h, _init.hash()))\n self.close_list[_init.hash()] = _init\n\n best_h = math.inf\n while True:\n if self.open_list.empty():\n raise Exception(\"Open list is empty!\")\n h, s_hash = self.open_list.get()\n state = self.close_list[s_hash]\n if state.status == CLOSED:\n continue\n\n state.status = CLOSED\n\n if best_h > h:\n best_h = h\n print(\"new h = {}\".format(h))\n\n if self.goalp(state.state, goal):\n yield state\n else:\n print(\"Expanding state [{}].\".format(s_hash))\n for c in self.successors(state):\n new_g = state.g + 1\n if c.g > new_g and c.status == OPEN:\n c.g = new_g\n c.parent = state\n c.status = OPEN\n c.h = heuristic(c.state)\n self.open_list.put((c.h, c.hash()))\n","sub_path":"latale/latale/planner/GBFS.py","file_name":"GBFS.py","file_ext":"py","file_size_in_byte":1747,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"620904715","text":"import tm1637\nfrom time import sleep\n\ndisplay = tm1637.TM1637(CLK=20,DIO=21,brightness=7)\n\ndisplay.Clear()\n\n#a=b=c=d=0\n\n#data = [a,b,c,d]\n\n#display.Show(data)\n#n=20\ni=0\nn=60\n\nfor i in range(n):\n display.ShowRoute(i%6)\n sleep(0.05)\n\n\n#while True:\n# d=int(i%10)\n# c=int(i/10)\n# c=int(c%10)\n# b=int(i/100)\n# b=int(b%10)\n# a=int(i/1000)\n# a=int(a%10)\n# sleep(0.1)\n# data = [a,b,c,d]\n# display.Show(data)\n# i+=1","sub_path":"tm1637/test.py","file_name":"test.py","file_ext":"py","file_size_in_byte":419,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"411078685","text":"# Importamos los módulos y bibliotecas necesarios para realizar este programa\nimport http.client\nimport json\n\n# Empleamos un código que utiliza la biblioteca http.client que hemos importado para leer repositorios\nheaders = {'User-Agent': 'http-client'}\nconn = http.client.HTTPSConnection(\"api.fda.gov\")\nconn.request(\"GET\", \"/drug/label.json?limit=10\", None, headers) # Con limit=10 encontraremos 10 medicamentos distintos\nr1 = conn.getresponse()\nprint(r1.status, r1.reason)\nrepos_raw = r1.read().decode(\"utf-8\")\nconn.close()\ninformacion = json.loads(repos_raw)\n\n# sabemos que en la página a la que accedemos el contenido es json y json se encuentra en forma de diccionario por tanto utilizamos las funciones de un diccionario para encontrar los diferentes elementos\nmedicamento_info=informacion[\"results\"]\n\n# Indexamos entre los distintos elementos de la página para imprimir los diez que hay en ella\nfor i in range(len(medicamento_info)):\n info = medicamento_info[i]\n print(\"Id del medicamento:\",info[\"id\"])\n","sub_path":"openfda-1/Programa 2.py","file_name":"Programa 2.py","file_ext":"py","file_size_in_byte":1019,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"4928489","text":"# -*- coding: utf-8 -*-\n#%% NumPyの読み込み\nimport numpy as np\n# SciPyのstatsモジュールの読み込み\nimport scipy.stats as st\n# CVXPYの読み込み\nimport cvxpy as cvx\n# Pandasの読み込み\nimport pandas as pd\n# MatplotlibのPyplotモジュールの読み込み\nimport matplotlib.pyplot as plt\n# 日本語フォントの設定\nfrom matplotlib.font_manager import FontProperties\nimport sys\nif sys.platform.startswith('win'):\n FontPath = 'C:\\\\Windows\\\\Fonts\\\\meiryo.ttc'\nelif sys.platform.startswith('darwin'):\n FontPath = '/System/Library/Fonts/ヒラギノ角ゴシック W4.ttc'\nelif sys.platform.startswith('linux'):\n FontPath = '/usr/share/fonts/truetype/takao-gothic/TakaoPGothic.ttf'\njpfont = FontProperties(fname=FontPath)\n#%% 収益率データの読み込みとベンチマークの生成\nR = pd.read_csv('asset_return_data.csv', index_col=0)\n# R = R.asfreq(pd.infer_freq(R.index)) # この行は無視する\nT = R.shape[0]\nN = R.shape[1]\nnp.random.seed(8888)\nBenchmarkIndex = R.dot(np.tile(1.0/N, N)) + st.norm(0.0, 3.0).rvs(T)\n#%% トラッキングエラー最小化問題のバックテスト\nMovingWindow = 96\nBackTesting = T - MovingWindow\nV_Tracking = np.zeros(BackTesting)\nWeight = cvx.Variable(N)\nError = cvx.Variable(MovingWindow)\nTrackingError = cvx.sum_squares(Error)\nAsset_srT = R / np.sqrt(MovingWindow)\nIndex_srT = BenchmarkIndex / np.sqrt(MovingWindow)\nfor Month in range(0, BackTesting):\n Asset = Asset_srT.values[Month:(Month + MovingWindow), :]\n Index = Index_srT.values[Month:(Month + MovingWindow)]\n Min_TrackingError = cvx.Problem(cvx.Minimize(TrackingError),\n [Index - Asset @ Weight == Error,\n cvx.sum(Weight) == 1.0,\n Weight >= 0.0])\n Min_TrackingError.solve(solver=cvx.ECOS)\n V_Tracking[Month] = R.values[Month + MovingWindow, :].dot(Weight.value)\n#%% バックテストの結果のグラフ\nfig1 = plt.figure(1, facecolor='w')\nplt.plot(list(range(1, BackTesting + 1)), BenchmarkIndex[MovingWindow:], 'k-')\nplt.plot(list(range(1, BackTesting + 1)), V_Tracking, 'k--')\nplt.legend([u'ベンチマーク・インデックス', u'インデックス・ファンド'],\n loc='best', frameon=False, prop=jpfont)\nplt.xlabel(u'運用期間(年）', fontproperties=jpfont)\nplt.ylabel(u'収益率(%)', fontproperties=jpfont)\nplt.xticks(list(range(12, BackTesting + 1, 12)),\n pd.date_range(R.index[MovingWindow], periods=BackTesting//12,\n freq='AS').year)\nplt.show()\n","sub_path":"python/pyfin_min_tracking_error_ver1_1.py","file_name":"pyfin_min_tracking_error_ver1_1.py","file_ext":"py","file_size_in_byte":2589,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"582931582","text":"#!/usr/bin/env python\nimport random\n\ncities=\"ABCDEFGHIJKLMNOPQRSTUVWXYZ\"\n#cities=\"ABCDEFGHIJKLMNOP\"\n\ncost_min=1\ncost_max=99\n\nn=len(cities)\n\nprint(n,n*100)\n\nprint(\" \".join(cities))\n\ncost=[ [ 0 for x in range(n) ] for y in range(n) ]\n\nfor i in range(0,n):\n for j in range(i+1,n):\n cost[i][j] = int(random.randint(cost_min,cost_max))\n cost[j][i] = cost[i][j]\n\nfor i in range(0,n):\n line=[]\n for j in range(0,n):\n if i==j:\n line.append(\"-\")\n else:\n line.append(str(cost[i][j]))\n print(\" \".join(line))\n\n","sub_path":"A2/gen_instance.py","file_name":"gen_instance.py","file_ext":"py","file_size_in_byte":560,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"641210815","text":"from Actor import *\n\nclass Player(Actor):\n\tdef __init__(self, offset_x, offset_y, actor_type, collision_type, threat_level):\n\t\tActor.__init__(self, offset_x, offset_y, actor_type, collision_type)\n\n\t\t# The threat level that the player will start from\n\t\tself.threat_level = threat_level\n\n\t\t# Health of the player\n\t\tself.health = 75\n\n\t\t# Stamina of the player\n\t\tself.stamina = 100\n\n\t\t# Skills that the player has\n\t\tself.strength_exp = 0\n\t\tself.intelligence_exp = 0\n\t\tself.charisma_exp = 0\n\n\t\tself.strength_level = 1\n\t\tself.intelligence_level = 1\n\t\tself.charisma_level = 1\n\n\t\t# Amount of currency that the player has\n\t\tself.currency = 1\n\n\t\t# Inventory list\n\t\tself.inventory = [None]*5\n\n\t\t# camera\n\t\tself.camera_pos = (self.rect.x/4, -self.rect.y/4) # Create Camara Starting Position\n\n\tdef increase_exp(self, skill, amount):\n\t\tif skill == STRENGTH_SKILL:\n\t\t\tself.strength_exp += amount\n\t\t\texp_to_level = self.amount_to_increase_level(skill, self.strength_level)\n\t\t\tif self.strength_exp >= exp_to_level:\n\t\t\t\tself.strength_level += 1\n\t\t\t\tself.strength_exp = self.strength_exp - exp_to_level\n\t\tif skill == INTELLIGENCE_SKILL:\n\t\t\t\tself.intelligence_exp += amount\n\t\t\t\texp_to_level = self.amount_to_increase_level(skill, self.intelligence_level)\n\t\t\t\tif self.intelligence_exp >= exp_to_level:\n\t\t\t\t\tself.intelligence_level += 1\n\t\t\t\t\tself.intelligence_exp = self.intelligence_exp - exp_to_level\n\t\tif skill == CHARISMA_SKILL:\n\t\t\tself.charisma_exp += amount\n\t\t\texp_to_level = self.amount_to_increase_level(skill, self.charisma_level)\n\t\t\tif self.charisma_exp >= exp_to_level:\n\t\t\t\tself.charisma_level += 1\n\t\t\t\tself.charisma_exp = self.charisma_exp - exp_to_level\n\n\tdef amount_to_increase_level(self, skill, level):\n\t\tif skill == STRENGTH_SKILL:\n\t\t\tcurrent_exp = self.strength_exp\n\t\tif skill == INTELLIGENCE_SKILL:\n\t\t\tcurrent_exp = self.intelligence_exp\n\t\tif skill == CHARISMA_SKILL:\n\t\t\tcurrent_exp = self.charisma_exp\n\n\t\tnext_level_exp = level**2 * level + 100\n\t\treturn next_level_exp\n\n\tdef get_stat(self, stat):\n\t\tif stat == HEALTH:\n\t\t\treturn self.health\n\t\tif stat == STAMINA:\n\t\t\treturn self.stamina\n\n\tdef get_inventory(self):\n\t\treturn self.inventory\n\n\tdef get_ramen(self):\n\t\treturn self.currency\n\n\tdef add_item(self, item):\n\t\tfor i in range(0, len(self.inventory)):\n\t\t\tif self.inventory[i] == None:\n\t\t\t\tself.inventory[i] = item\n\t\t\t\titems_group.remove(item)\n\t\t\t\tbreak\n\n\tdef drop_item(self, index):\n\t\tif self.inventory[index] != None:\n\t\t\titem = self.inventory[index]\n\t\t\titem.rect.x = ((self.rect.x+self.rect.width/2)/TILESIZE * TILESIZE)\n\t\t\titem.rect.y = ((self.rect.y+self.rect.height/2)/TILESIZE * TILESIZE)\n\t\t\titems_group.add(item)\n\t\t\tself.inventory[index] = None\n\n\tdef get_skill(self, skill, exp):\n\t\tif exp:\n\t\t\tif skill == STRENGTH_SKILL:\n\t\t\t\treturn self.strength_exp\n\t\t\telif skill == INTELLIGENCE_SKILL:\n\t\t\t\treturn self.intelligence_exp\n\t\t\telif skill == CHARISMA_SKILL:\n\t\t\t\treturn self.charisma_exp\n\t\telse:\n\t\t\tif skill == STRENGTH_SKILL:\n\t\t\t\treturn self.strength_level\n\t\t\telif skill == INTELLIGENCE_SKILL:\n\t\t\t\treturn self.intelligence_level\n\t\t\telif skill == CHARISMA_SKILL:\n\t\t\t\treturn self.charisma_level\n\n\t# Works Nicely\n\tdef update(self, move, direction):\n\t\tself.direction = direction\n\t\tif move == True:\n\t\t\tself.count += 1\n\t\t\tif self.count % self.change_timer == 0:\n\t\t\t\tself.index += 1\n\t\t\tif self.index >= len(self.direction_map[direction]):\n\t\t\t\tself.index = 1\n\t\t\tself.current_image = self.direction_map[direction][self.index]\n\t\t\tif direction == UP:\n\t\t\t\tself.move(0, -self.speed)\n\t\t\t\tself.move_camera(UP)\n\t\t\tif direction == DOWN:\n\t\t\t\tself.move(0, self.speed)\n\t\t\t\tself.move_camera(DOWN)\n\t\t\tif direction == LEFT:\n\t\t\t\tself.move(-self.speed, 0)\n\t\t\t\tself.move_camera(LEFT)\n\t\t\tif direction == RIGHT:\n\t\t\t\tself.move(self.speed, 0)\n\t\t\t\tself.move_camera(RIGHT)\n\t\telse:\n\t\t\tself.index = 0\n\t\t\tself.count = 0\n\t\t\tself.current_image = self.direction_map[direction][self.index]\n\n\tdef move(self, dx, dy):\n\t\tif dx != 0:\n\t\t\tself.move_single_axis(dx, 0)\n\t\tif dy != 0:\n\t\t\tself.move_single_axis(0, dy)\n\n\tdef move_single_axis(self, dx, dy):\n\t\t# Move the rect\n\t\tself.rect.x += dx\n\t\tself.rect.y += dy\n\n\t\tfor other_object in self.collision_list:\n\t\t\tif self.rect.colliderect(other_object) and other_object.collision_type == BLOCKING:\n\t\t\t\tpos_x, pos_y = self.camera_pos\n\t\t\t\tif dx > 0: # Moving right; Hit the left side of the object\n\t\t\t\t\tself.rect.right = other_object.rect.left\n\t\t\t\t\t# Code for the camera\n\t\t\t\t\tif other_object.get_direction() == RIGHT:\n\t\t\t\t\t\tpos_x += self.speed - other_object.get_speed()\n\t\t\t\t\telse:\n\t\t\t\t\t\tpos_x += self.speed\n\t\t\t\tif dx < 0: # Moving left; Hit the right side of the object\n\t\t\t\t\tself.rect.left = other_object.rect.right\n\t\t\t\t\t# Code for the camera\n\t\t\t\t\tif other_object.get_direction() == LEFT:\n\t\t\t\t\t\tpos_x -= self.speed - other_object.get_speed()\n\t\t\t\t\telse:\n\t\t\t\t\t\tpos_x -= self.speed\n\t\t\t\tif dy > 0: # Moving down; Hit the top side of the object\n\t\t\t\t\tself.rect.bottom = other_object.rect.top\n\t\t\t\t\t# Code for the camera\n\t\t\t\t\tif other_object.get_direction() == DOWN:\n\t\t\t\t\t\tpos_y += self.speed - other_object.get_speed()\n\t\t\t\t\telse:\n\t\t\t\t\t\tpos_y += self.speed\n\t\t\t\tif dy < 0: # Moving up; Hit the bottom side of the object\n\t\t\t\t\tself.rect.top = other_object.rect.bottom\n\t\t\t\t\tif other_object.get_direction() == UP:\n\t\t\t\t\t\tpos_y -= self.speed - other_object.get_speed()\n\t\t\t\t\telse:\n\t\t\t\t\t\tpos_y -= self.speed\n\n\t\t\t\tself.camera_pos = (pos_x, pos_y)\n\n\n\tdef move_camera(self, direction):\n\n\t pos_x,pos_y = self.camera_pos # Split camara_pos\n\n\t if direction == UP: # Check Key\n\t pos_y += self.speed # Move Camara Coord Against Player Rect\n\t if direction == RIGHT:\n\t pos_x -= self.speed\n\t if direction == DOWN:\n\t pos_y -= self.speed\n\t if direction == LEFT:\n\t pos_x += self.speed\n\n\t self.camera_pos = (pos_x,pos_y) # Return New Camera Pos\n\n\tdef collided(self, other):\n\t\tdelta_x = other.rect.x - self.rect.x\n\t\tdelta_y = other.rect.y - self.rect.y\n\n\t\tif abs(delta_x) < TILESIZE+1 and abs(delta_y) < TILESIZE+1:\n\t\t\treturn True\n\t\telse:\n\t\t\treturn False\n\n\n\tdef interact(self, flag):\n\t\tif flag:\n\t\t\tfor interaction in interactable_group:\n\t\t\t\tif self.collided(interaction):\n\t\t\t\t\tinteraction.perform_action(self)\n\t\t\tfor item in items_group:\n\t\t\t\tif self.collided(item):\n\t\t\t\t\tself.add_item(item)\n\t\t\t\t\titems_group.remove(item)\n","sub_path":"Phase2/Classes/Player.py","file_name":"Player.py","file_ext":"py","file_size_in_byte":6231,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"412269518","text":"# -*- coding: utf-8 -*-\n\nimport base64\nfrom Crypto.Cipher import AES\nfrom Crypto import Random\nfrom Crypto.Hash import SHA256\nimport pylzma\nimport os\nimport sys\nsys.path.insert(0, os.path.abspath('./encrepo'))\nimport hash_helper\nimport pack\nimport time\n\nBS = 32\nAES_KEY_SIZE = 32 #Key is 256 bit\npad = lambda s : s if len(s) % AES_KEY_SIZE == 0 else \\\n s + (AES_KEY_SIZE - len(s) % AES_KEY_SIZE) \\\n * chr(AES_KEY_SIZE - len(s) % AES_KEY_SIZE)\n\nunpad = lambda s : s if len(s) % AES_KEY_SIZE == 0 else \\\n s[:-ord(s[len(s)-1])]\n\nclass AESCipher:\n def __init__( self, key ):\n self.key = key\n\n def encrypt( self, raw ):\n raw = pad(raw)\n iv = Random.new().read( AES.block_size )\n cipher = AES.new( self.key, AES.MODE_CBC, iv )\n return base64.b64encode( iv + cipher.encrypt( raw ) )\n\n def decrypt( self, enc ):\n enc = base64.b64decode(enc)\n iv = enc[:16]\n cipher = AES.new(self.key, AES.MODE_CBC, iv )\n return unpad(cipher.decrypt( enc[16:] ))\n\nraw_info = \"\"\"awsome text goes here,\n U cannot see me,\n One good turn deserves another\"\"\"\n\nwith open('/home/xin/iprule') as input_file:\n raw_info = input_file.read()\n\nkey = 'abcdefghijklmnopqrstuvwxyz123456'\n\n\nkey = pad(key)\n\nAES_KEY = 'asdfas2\"%H:%M:%'\n\ndef test_compressed():\n print(\"key=%s length:%d\"%(key,len(key)))\n print(\"Original length of data:%d\"%len(raw_info))\n\n raw_hash = hash_helper.hash_str(raw_info)\n print(\"Original hash:%s\"%raw_hash)\n h = SHA256.new()\n h.update(raw_info)\n print(\"Original hashA:%s\"%h.hexdigest())\n\n\n compressed_info = pylzma.compress(raw_info)\n\n print(\"compressed length of data:%d\"%len(compressed_info))\n\n\n cf = AESCipher(key)\n encrypted = cf.encrypt(compressed_info)\n decrypted = cf.decrypt(encrypted)\n print(\"encrypted length of data:%d\"%len(encrypted))\n decompressed = pylzma.decompress(decrypted)\n print(\"Decrypted hash:%s\"%hash_helper.hash_str(decompressed))\n\n\n\n\ndef test_run1():\n print(\"Original length of data:%d\"%len(raw_info))\n raw_hash = hash_helper.hash_str(raw_info)\n print(\"Original hash:%s\"%raw_hash)\n\n cf = AESCipher(key)\n encrypted = cf.encrypt(raw_info)\n print(\"length of encrypted data:%d\"%len(encrypted))\n compressed_info = pylzma.compress(encrypted)\n print(\"compressed length of encrypted data:%d\"%len(compressed_info))\n\n decompressed = pylzma.decompress(compressed_info)\n decrypted = cf.decrypt(decompressed)\n print(\"Decrypted hash:%s\"%hash_helper.hash_str(decrypted))\n\n\ndef test_run2():\n info = \"the red fox jumps over the lazy dog\\n\"\n more_info = lambda i : '' if i ==0 else \\\n more_info(i-1) + 'Line {0:10d} : {1}'.format(i, info) * 100\n with open('/tmp/test.txt','w') as afile:\n afile.write(more_info(100))\n t0 = time.time()\n print(t0)\n t1 = t0\n t2 = t1\n print('{0}:....total={1:20f}, step={2:20f}'.format(\n time.strftime(\"%H:%M:%S\", time.localtime(t0)),\n t2 - t0,\n t2 - t1))\n\ndef noautorun_test_pack_large():\n t0 = time.time()\n print(t0)\n t1 = t0\n t2 = t1\n\n print('{0}:....total={1:12f}, step={2:12f}..starting'.format(\n time.strftime(\"%H:%M:%S\", time.localtime(t0)),\n t2 - t0,\n t2 - t1))\n\n #test_file = '/tmp/Inside.Out.2015.BD1080P.X264.AAC.English&Mandarin.CHS-ENG.Mp4Ba.mp4'\n test_file = '/home/xin/下载/头脑特工队.Inside.Out.2015.BD1080P.X264.AAC.English&Mandarin.CHS-ENG.Mp4Ba.mp4'\n with open(test_file) as afile:\n dgst_original = hash_helper.hash_file(afile)\n #dgst_original ='370cbba5943b5ba6ab868e9f0e098d8ccb8aa5f7396f82ebe22ac6a072c001f8'\n print(\"Original SHA256:%s\"%dgst_original)\n t2 = time.time()\n print('{0}:....total={1:12f}, step={2:12f}..dgst original'.format(\n time.strftime(\"%H:%M:%S\", time.localtime(t0)),\n t2 - t0,\n t2 - t1))\n t1 = t2\n packed_file_name = '/tmp/Inside.Out.2015.BD1080P.X264.AAC.English&Mandarin.CHS-ENG.Mp4Ba.mp4.pack'\n unpacked_file_name = '/tmp/Inside.Out.2015.BD1080P.X264.AAC.English&Mandarin.CHS-ENG.Mp4Ba.unpack.mp4'\n pack.pack_file(AES_KEY, test_file, packed_file_name)\n t2 = time.time()\n print('{0}:....total={1:12f}, step={2:12f}..packing..'.format(\n time.strftime(\"%H:%M:%S\", time.localtime(t0)),\n t2 - t0,\n t2 - t1))\n t1 = t2\n pack.unpack_file(AES_KEY, packed_file_name, unpacked_file_name)\n t2 = time.time()\n print('{0}:....total={1:12f}, step={2:12f}..Unpacking..'.format(\n time.strftime(\"%H:%M:%S\", time.localtime(t0)),\n t2 - t0,\n t2 - t1))\n t1 = t2\n with open(unpacked_file_name) as newfile:\n dgst_new = hash_helper.hash_file(newfile)\n\n\n t2 = time.time()\n print('{0}:....total={1:12f}, step={2:12f}..dgst result..'.format(\n time.strftime(\"%H:%M:%S\", time.localtime(t0)),\n t2 - t0,\n t2 - t1))\n t1 = t2\n print(\"New SHA256:%s\"%dgst_new)\n assert dgst_original == dgst_new\n\ndef noautorun_test_pad():\n with open('/tmp/3.mp4') as afile:\n s = afile.read()\n print(hash_helper.hash_str(s))\n encrypted = pack.encrypt(AES_KEY, s)\n decrypted = pack.decrypt1(AES_KEY, encrypted)\n print(hash_helper.hash_str(decrypted))\n print(unpad(hash_helper.hash_str(decrypted)))\n\ndef split_file_writer(file_name, split_size=32):\n file_size = split_size * 2 ** 20\n sum_len = [0]\n def write_file(buf):\n sum_len[0] += len(buf)\n file_no = sum_len[0] // file_size\n new_filename = file_name if file_no==0 else file_name+'.'+('0000'+str(file_no))[-4:]\n with open(new_filename,'a') as afile:\n afile.write(buf)\n return write_file\n\n\ndef split_file_reader(file_name):\n files = [open(file_name,'r')]\n file_no = [0]\n def read_file(buf_size):\n buf = files[0].read(buf_size)\n if len(buf) == 0:\n file_no[0] += 1\n files[0].close()\n try:\n files[0] = open(file_name+'.'+('0000'+str(file_no[0]))[-4:])\n return read_file(buf_size)\n except IOError:\n return ''\n else:\n return buf\n return read_file\n\ndef tester_split():\n original_file_name = '/home/xin/下载/头脑特工队.Inside.Out.2015.BD1080P.X264.AAC.English&Mandarin.CHS-ENG.Mp4Ba.mp4'\n splited_file_name = '/tmp/new/inside.out.mp4'\n recombined_file_name = '/tmp/inside.out.recombined.mp4'\n writer = split_file_writer(splited_file_name)\n\n with open(original_file_name) as afile:\n buf = afile.read(65536)\n while len(buf) >0 :\n writer(buf)\n buf = afile.read(65536)\n\ndef tester_combine():\n original_file_name = '/home/xin/下载/头脑特工队.Inside.Out.2015.BD1080P.X264.AAC.English&Mandarin.CHS-ENG.Mp4Ba.mp4'\n splited_file_name = '/tmp/new/inside.out.mp4'\n recombined_file_name = '/tmp/inside.out.recombined.mp4'\n reader = split_file_reader(splited_file_name)\n with open(recombined_file_name,'w') as afile:\n buf = reader(65536)\n while len(buf)>0:\n afile.write(buf)\n buf = reader(65536)\n\n dgst1 = hash_helper.hash_file(open(original_file_name))\n dgst2 = hash_helper.hash_file(open(recombined_file_name))\n\n assert dgst1 == dgst2\n\n\ntester_combine()\n","sub_path":"encrypted_file_repo/test/test_run.py","file_name":"test_run.py","file_ext":"py","file_size_in_byte":7461,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"620220901","text":"import sys, subprocess\nfrom PyQt5.QtWidgets import QWidget, QVBoxLayout, QHBoxLayout, QTreeWidget, QTreeWidgetItem, QGroupBox, QPushButton, QApplication\nfrom PyQt5 import QtCore\n\nclass MyApp(object): \n def __init__(self):\n super(MyApp, self).__init__() \n self.mainWidget = QWidget()\n self.mainLayout = QVBoxLayout()\n self.mainWidget.setLayout(self.mainLayout)\n\n self.hLayout = QHBoxLayout()\n self.mainLayout.insertLayout(0, self.hLayout)\n\n\n self.listA=QTreeWidget()\n self.listA.setColumnCount(3)\n self.listA.setHeaderLabels(['Checkbox','Name','Data'])\n for i in range(3):\n item=QTreeWidgetItem()\n item.setCheckState(0, 2)\n item.setText(1, 'Item '+str(i))\n item.setData(2, 256, id(item) )\n item.setText(2, str(id(item) ) )\n self.listA.addTopLevelItem(item)\n\n self.hLayout.addWidget(self.listA)\n\n self.buttonGroupbox = QGroupBox()\n self.buttonlayout = QVBoxLayout()\n self.buttonGroupbox.setLayout(self.buttonlayout)\n\n okButton = QPushButton('Remove Selected')\n okButton.clicked.connect(self.removeSel)\n self.buttonlayout.addWidget(okButton)\n\n getDataButton = QPushButton('Get Items Data')\n getDataButton.clicked.connect(self.getItemsData)\n self.buttonlayout.addWidget(getDataButton)\n\n self.mainLayout.addWidget(self.buttonGroupbox)\n self.mainWidget.show()\n sys.exit(app.exec_())\n\n def removeSel(self):\n listItems = []\n for i in range(self.listA.topLevelItemCount()):\n item=self.listA.topLevelItem(i)\n print(\"item\", item)\n if (item.checkState(0) == 2):\n listItems.append(item)\n\n print(\"listItems: \",listItems)\n\n for item in listItems:\n print(\"item: \", item)\n itemIndex=self.listA.indexOfTopLevelItem(item)\n print(\"itemIndex\", itemIndex)\n self.listA.takeTopLevelItem(itemIndex)\n print('\\n\\t Number of items remaining', self.listA.topLevelItemCount())\n\n def getItemsData(self):\n for i in range(self.listA.topLevelItemCount()):\n item=self.listA.topLevelItem(i)\n itmData=item.data(2, 256)\n print('\\n\\t Item Id Stored as Item Data:', itmData, 'Item Checkbox State:', item.checkState(0))\n\nif __name__ == '__main__':\n what = subprocess.Popen(['adb', 'devices', '-l'], stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n out, errs = what.communicate()\n out = str(out, 'utf-8')\n outs = out.split()\n del outs[0:4]\n length = len(outs)\n n = length/6\n struct = [[] for i in range(int(n))]\n for i in range(int(n)):\n print(n, i)\n struct[i] = outs[i*6:(i+1)*6]\n print(struct[i])\n app = QApplication(sys.argv)\n MyApp()","sub_path":"PythGUI/gui2.py","file_name":"gui2.py","file_ext":"py","file_size_in_byte":2871,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"617248015","text":"import tornado.ioloop\nimport tornado.web\nimport psycopg2.extras\nimport notorm\nimport tornado.autoreload\n\nclass Game(notorm.record):\n _fields = {'id':None,\n 'name':None\n }\n\n insert_qry = \"\"\"\n insert into game (name)\n values(%(name)s)\n returning id\n \"\"\"\n\n update_qry = \"\"\"\n update game set name=%(name)s where id = %(id)s\n \"\"\"\n\n @classmethod\n def get(cls, game_id):\n cursor = notorm.db.cursor(cursor_factory=psycopg2.extras.NamedTupleCursor)\n cursor.execute(\"\"\"select game.*::game from game where id = %(game_id)s\"\"\",\n {'game_id': game_id})\n\n results = cursor.fetchall()\n games = notorm.build_relationships(results, 'game')\n if not games:\n return None\n return games[0]\n\n @classmethod\n def get_all(cls):\n cursor = notorm.db.cursor(cursor_factory=psycopg2.extras.NamedTupleCursor)\n cursor.execute(\"\"\"select game.*::game from game order by name\"\"\")\n\n results = cursor.fetchall()\n games = notorm.build_relationships(results, 'game')\n return games\n\nclass GameComposite(psycopg2.extras.CompositeCaster):\n def make(self, values):\n d = dict(zip(self.attnames, values))\n return Game(**d)\n\nclass ExampleRequestHandler(tornado.web.RequestHandler):\n def on_finish(self):\n notorm.db.commit()\n\n def log_exception(self, typ, value, tb):\n print(\"Exception\")\n notorm.db.rollback()\n return super(ExampleRequestHandler, self).log_exception(typ, value, tb)\n\nclass MainHandler(ExampleRequestHandler):\n def get(self):\n games = Game.get_all()\n self.render(\"../main.html\", games=games)\n\nclass GameHandler(ExampleRequestHandler):\n def get(self, game_id=None):\n if game_id:\n game = Game.get(game_id)\n else:\n game = Game()\n self.render(\"../edit.html\", game=game)\n\n def post(self, game_id=None):\n if game_id:\n game = Game.get(game_id)\n else:\n game = Game()\n game.name = self.get_argument('name')\n game.save()\n self.redirect(\"/\")\n\ndef make_app():\n return tornado.web.Application([\n (r\"/\", MainHandler),\n (r\"/game/new\", GameHandler),\n (r\"/game/([0-9]+)\", GameHandler)\n ])\n\nif __name__ == \"__main__\":\n notorm.db = psycopg2.connect(\"dbname=notorm_example user=dbuser\")\n\n cursor = notorm.db.cursor()\n psycopg2.extras.register_composite('game', cursor, globally=True, factory = GameComposite)\n app = make_app()\n app.listen(8888)\n tornado.autoreload.start(tornado.ioloop.IOLoop.current())\n tornado.ioloop.IOLoop.current().start()","sub_path":"examples/tornadosync/tornadosync.py","file_name":"tornadosync.py","file_ext":"py","file_size_in_byte":2690,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"285717113","text":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thr Oct 18 14:25:12 2019\n@author: TestEnC hanrim lee\n\n\"\"\"\nimport os\nimport sys\nimport re\nimport openpyxl\n# import pkg_resources.py2_warn\nfrom os.path import expanduser\nimport threading\n\n#from konlpy.tag import Komoran\nfrom time import sleep\nfrom datetime import datetime\n\n#import pytagcloud\nfrom PyQt5.QtCore import QThread, pyqtSignal\n#selenium library\nfrom openpyxl.styles import Alignment, Font, NamedStyle, PatternFill\nfrom openpyxl import formatting, styles, Workbook\nfrom openpyxl.styles.borders import Border, Side\n\nclass Formater(QThread):\n\n print_flag = pyqtSignal(str)\n end_flag = pyqtSignal()\n fileCheck_flag = pyqtSignal()\n progress_flag = pyqtSignal()\n count_flag = pyqtSignal()\n dict_result = None\n tot_count = 0\n\n def __init__(self, filePath, opFlag, modeFlag, parent=None):\n QThread.__init__(self, parent)\n\n self.file_names = filePath\n self.list_files = self.file_names.split(\",\")\n self.list_out_files = []\n self.dict_out = {}\n self.dict_readData = {}\n # self.list_sheet_names = []\n\n self.opFlag = opFlag\n self.modeFlag = modeFlag\n self.home = expanduser(\"~\")\n\n self.end_count = \"n\"\n self.totalRows = 0\n self.currentRow = 0\n self.current_path = os.getcwd()\n self.battery_spec = 0.0\n\n # style fill pattern\n # FF0000 red\n # 0000FF blue\n\n self.brown_fill = PatternFill(start_color='DDD9C4', end_color='DDD9C4', fill_type='solid')\n self.light_brown_fill = PatternFill(start_color='EEECE1', end_color='EEECE1', fill_type='solid')\n self.gray_fill = PatternFill(start_color='E7E6E6', end_color='E7E6E6', fill_type='solid')\n self.dark_gray_fill = PatternFill(start_color='D9D9D9', end_color='D9D9D9', fill_type='solid')\n self.light_gray_fill = PatternFill(start_color='F2F2F2', end_color='F2F2F2', fill_type='solid')\n self.apricot_fill = PatternFill(start_color='FDE9D9', end_color='FDE9D9', fill_type='solid')\n self.skyBlue_fill = PatternFill(start_color='DCE6F1', end_color='DCE6F1', fill_type='solid')\n self.yellow_fill = PatternFill(start_color='FFFF00', end_color='FFFF00', fill_type='solid')\n self.orange_fill = PatternFill(start_color='FFC000', end_color='FFC000', fill_type='solid')\n\n # style font color and size\n self.top_font = Font(name='맑은 고딕', size=12, bold=True, color='2B2B2B')\n self.index_font = Font(name='맑은 고딕', size=11, bold=True, color='2B2B2B')\n self.value_font = Font(name='맑은 고딕', size=11, bold=False, color='2B2B2B')\n self.value2_font = Font(name='맑은 고딕', size=10, bold=True, color='2B2B2B')\n self.f2_value_font = Font(name='맑은 고딕', size=10, bold=False, color='2B2B2B')\n self.f2_blue_font = Font(name='맑은 고딕', size=10, bold=False, color='0000FF')\n self.f2_red_font = Font(name='맑은 고딕', size=10, bold=False, color='FF0000')\n\n # style Alignment\n self.general_alignment = Alignment(wrap_text=True, horizontal=\"center\", vertical=\"center\")\n self.top_alignment = Alignment(wrap_text=False, horizontal=\"left\", vertical=\"center\")\n self.top_alignment_2 = Alignment(wrap_text=True, horizontal=\"left\", vertical=\"center\")\n self.top_alignment_3 = Alignment(wrap_text=True, horizontal=\"left\", vertical=\"top\")\n\n # style border\n self.thin_border = Border(left=Side(style='thin'), right=Side(style='thin'), top=Side(style='thin'), bottom=Side(style='thin'))\n\n # ftp 관련 변수 및 설정\n # self.hostname = '192.168.0.108'\n # self.port = 21\n # self.username = 'voc'\n # self.password = 'testenc@01'\n\n # 분석 처리 개수 체크 함수\n def getCountRows(self):\n\n while True:\n if self.end_count is \"n\":\n sleep(0.5)\n self.count_flag.emit()\n else:\n break\n\n # 로그 문자 처리 함수\n def setPrintText(self, text):\n\n strToday = datetime.today().strftime(\"%Y-%m-%d %H:%M:%S\")\n text = self.find_between(text, \"/s\", \"/e\")\n print_text = strToday+\":\\n\"+text+\"\\n\"\n self.print_flag.emit(\"{}\".format(print_text))\n\n # 쓰레드 종료 함수\n def stop(self):\n sleep(0.5)\n self.terminate()\n\n # 특수 문자 제거 함수\n def removeString(self, text):\n\n tempText = re.sub('[-=+,#/\\?^$@*\\\"※~&%ㆍ!』\\\\‘|\\(\\)\\[\\]\\<\\>\\{\\}`><]\\'', '', text)\n return tempText\n\n # 문장 앞 부터 조건에 맞는 문자열 substring\n def find_between(self, s, first, last):\n try:\n returnData = \"\"\n start = s.index(first)+len(first)\n end = s.index(last, start)\n returnData = s[start:end]\n return returnData\n except ValueError:\n return returnData\n\n # 문장 뒤 부터 조건에 맞는 문자열 substring\n def find_between_r(self, s, first, last ):\n try:\n returnData = \"\"\n start = s.rindex(first)+len(first)\n end = s.rindex(last, start)\n returnData = s[start:end]\n return returnData\n except ValueError:\n return returnData\n\n # float num check a point\n def check_num(self, num):\n\n return_data = None\n if num is None or num == '':\n return_data = '-'\n else:\n try:\n return_data = '%.2f'%float(num)\n except:\n return_data = str(num)\n\n return return_data\n\n # check calculate comparison\n def cal_comparison(self, standard, measure):\n\n return_data = None\n try:\n return_data = self.check_num(abs(round(abs(float(measure)) - float(standard), 2)))\n except:\n return_data = '-'\n\n return return_data\n\n # check convert num available\n def isNumber(self, string_data):\n\n try:\n temp_data = float(string_data)\n return True\n except:\n return False\n\n # check convert num available\n def check_empty(self, string_data):\n\n return_data = None\n if string_data is None or string_data == '' or string_data.lower() in ['n/a', 'na', 'nt', 'n/t']:\n return_data = '-'\n else:\n return_data = str(string_data)\n\n return return_data\n\n # summary Tab\n def summary_generate_data(self):\n\n try:\n for idx, item in enumerate(self.list_files):\n\n temp_data = {}\n wb_input = openpyxl.load_workbook(item, data_only=True)\n wb_output = openpyxl.load_workbook(self.list_out_files[idx])\n\n # get data from wb_input\n sheet_in = wb_input['Summary']\n temp_data['팻네임 / 모델명'] = sheet_in['C5'].value\n temp_data['OS 및 Binary Version'] = sheet_in['C8'].value + \"/\" + sheet_in['C6'].value\n temp_data['Chipset (AP / CP)'] = sheet_in['K6'].value\n temp_data['가로 폭 (mm) / Display Size (inch)'] = sheet_in['K7'].value\n temp_data['배터리 용량 (mAh)'] = str(sheet_in['K8'].value)+'mAh'\n self.battery_spec = float(sheet_in['K8'].value)\n temp_data['검증 차수'] = sheet_in['C9'].value\n temp_data['검증 기간'] = sheet_in['K5'].value\n\n #option setting wb.output\n sheet_out = wb_output['검증결과요약']\n # sheet row 3 handle\n sheet_out.merge_cells('B3:C3')\n sheet_out['B3'] = \"1. 단말 기본 정보\"\n # sheet row 4 handle\n sheet_out.merge_cells('B4:C4')\n sheet_out.merge_cells('D4:E4')\n sheet_out['B4'] = \"팻네임 / 모델명\"\n sheet_out['D4'] = temp_data['팻네임 / 모델명']\n # sheet row 5 handle\n sheet_out.merge_cells('B5:C5')\n sheet_out.merge_cells('D5:E5')\n sheet_out['B5'] = \"OS 및 Binary Version\"\n sheet_out['D5'] = temp_data['OS 및 Binary Version']\n # sheet row 6 handle\n sheet_out.merge_cells('B6:C6')\n sheet_out.merge_cells('D6:E6')\n sheet_out['B6'] = \"Chipset (AP / CP)\"\n sheet_out['D6'] = temp_data['Chipset (AP / CP)']\n # sheet row 7 handle\n sheet_out.merge_cells('B7:C7')\n sheet_out.merge_cells('D7:E7')\n sheet_out['B7'] = \"가로 폭 (mm) / Display Size (inch)\"\n sheet_out['D7'] = temp_data['가로 폭 (mm) / Display Size (inch)']\n # sheet row 7 handle\n sheet_out.merge_cells('B8:C8')\n sheet_out.merge_cells('D8:E8')\n sheet_out['B8'] = \"배터리 용량 (mAh)\"\n sheet_out['D8'] = temp_data['배터리 용량 (mAh)']\n # sheet row 10 handle\n sheet_out.merge_cells('B10:C10')\n sheet_out['B10'] = \"2. 검증 차수 및 검증 기간\"\n # sheet row 11 handle\n sheet_out.merge_cells('B11:C11')\n sheet_out.merge_cells('D11:E11')\n sheet_out['B11'] = \"검증 차수\"\n sheet_out['D11'] = temp_data['검증 차수']\n # sheet row 12 handle\n sheet_out.merge_cells('B12:C12')\n sheet_out.merge_cells('D12:E12')\n sheet_out['B12'] = \"검증 기간\"\n sheet_out['D12'] = temp_data['검증 기간']\n # sheet row 14 handle\n sheet_out.merge_cells('B14:D14')\n sheet_out['B14'] = '3. 검증 결과 (항목수 : 00, Test Case 수 : 78)'\n # sheet row 15 handle\n sheet_out.merge_cells('B15:C15')\n sheet_out['B15'] = '항목'\n sheet_out['D15'] = 'Pass'\n sheet_out['E15'] = 'Fail'\n # sheet row 16 handle\n sheet_out.merge_cells('B16:B19')\n sheet_out['B16'] = 'RF성능'\n sheet_out['C16'] = 'TRP'\n # sheet row 17 handle\n sheet_out['C17'] = 'TIS'\n # sheet row 18 handle\n sheet_out['C18'] = '속도'\n # sheet row 19 handle\n sheet_out['C19'] = 'Call Setup Test'\n # sheet row 20 handle\n sheet_out.merge_cells('B20:C20')\n sheet_out['B20'] = 'MOS'\n # sheet row 21 handle\n sheet_out.merge_cells('B21:C21')\n sheet_out['B21'] = '배터리소모전류 (시간)'\n # sheet row 22 handle\n sheet_out.merge_cells('B22:C22')\n sheet_out['B22'] = '주파수동조'\n # sheet row 23 handle\n sheet_out.merge_cells('B23:C23')\n sheet_out['B23'] = '발열'\n sheet_out['D23'] = ''\n sheet_out['E23'] = ''\n # sheet row 24 handle\n sheet_out.merge_cells('B24:C24')\n sheet_out['B24'] = '소계'\n sheet_out['D24'] = ''\n sheet_out['E24'] = ''\n # sheet row 25 handle\n sheet_out.merge_cells('B25:C25')\n sheet_out.merge_cells('D25:E25')\n sheet_out['B25'] = '점수 (가/감점)'\n sheet_out['D25'] = '86.9(+12)'\n # sheet row 26 handle\n sheet_out.merge_cells('B26:C26')\n sheet_out.merge_cells('D26:E26')\n sheet_out['B26'] = '배터리소모전류 (DOU, Test case : 35)'\n sheet_out['D26'] = '1.44일'\n\n # sheet row 26 handle\n sheet_out.merge_cells('B28:E28')\n sheet_out.merge_cells('B29:E29')\n sheet_out['B28'] = '4. 특이사항'\n sheet_out['B29'] = ''\n\n self.setPrintText('/s {}번 파일 \"검증결과요약\" 테이터 입력 완료 /e'.format(idx+1))\n\n if self.opFlag:\n\n # all cell aligment adjust\n for mCell in sheet_out[\"B3:E26\"]:\n for cell in mCell:\n cell.alignment = self.general_alignment\n\n for mCell in sheet_out[\"B29:E29\"]:\n for cell in mCell:\n cell.alignment = self.top_alignment_3\n\n # each coloum width adjust\n sheet_cell_list = ['A', 'B', 'C', 'D', 'E']\n sheet_width_list = [3.38, 20, 20, 20, 20]\n for i in range(len(sheet_cell_list)):\n sheet_out.column_dimensions[sheet_cell_list[i]].width = sheet_width_list[i]\n sheet_out.row_dimensions[29].height = 85.5\n\n # Set style on Cell\n # row 3\n sheet_out['B3'].font = self.top_font\n sheet_out['B3'].alignment = self.top_alignment\n # row 4\n sheet_out['B4'].font = self.index_font\n sheet_out['B4'].fill = self.brown_fill\n sheet_out['B4'].border = self.thin_border\n sheet_out['D4'].font = self.index_font\n sheet_out['D4'].border = self.thin_border\n sheet_out['C4'].border = self.thin_border\n sheet_out['E4'].border = self.thin_border\n # row 5\n sheet_out['B5'].font = self.index_font\n sheet_out['B5'].fill = self.brown_fill\n sheet_out['B5'].border = self.thin_border\n sheet_out['D5'].font = self.index_font\n sheet_out['D5'].border = self.thin_border\n sheet_out['C5'].border = self.thin_border\n sheet_out['E5'].border = self.thin_border\n # row 6\n sheet_out['B6'].font = self.index_font\n sheet_out['B6'].fill = self.brown_fill\n sheet_out['B6'].border = self.thin_border\n sheet_out['D6'].font = self.index_font\n sheet_out['D6'].border = self.thin_border\n sheet_out['C6'].border = self.thin_border\n sheet_out['E6'].border = self.thin_border\n # row 7\n sheet_out['B7'].font = self.index_font\n sheet_out['B7'].fill = self.brown_fill\n sheet_out['B7'].border = self.thin_border\n sheet_out['D7'].font = self.index_font\n sheet_out['D7'].border = self.thin_border\n sheet_out['C7'].border = self.thin_border\n sheet_out['E7'].border = self.thin_border\n # row 8\n sheet_out['B8'].font = self.index_font\n sheet_out['B8'].fill = self.brown_fill\n sheet_out['B8'].border = self.thin_border\n sheet_out['D8'].font = self.index_font\n sheet_out['D8'].border = self.thin_border\n sheet_out['C8'].border = self.thin_border\n sheet_out['E8'].border = self.thin_border\n # row 10\n sheet_out['B10'].font = self.top_font\n sheet_out['B10'].alignment = self.top_alignment\n # row 11\n sheet_out['B11'].font = self.index_font\n sheet_out['B11'].fill = self.brown_fill\n sheet_out['B11'].border = self.thin_border\n sheet_out['C11'].font = self.index_font\n sheet_out['C11'].border = self.thin_border\n sheet_out['D11'].border = self.thin_border\n sheet_out['D11'].font = self.index_font\n sheet_out['E11'].border = self.thin_border\n\n # row 12\n sheet_out['B12'].font = self.index_font\n sheet_out['B12'].fill = self.brown_fill\n sheet_out['B12'].border = self.thin_border\n sheet_out['C12'].font = self.index_font\n sheet_out['C12'].border = self.thin_border\n sheet_out['D12'].border = self.thin_border\n sheet_out['D12'].font = self.index_font\n sheet_out['E12'].border = self.thin_border\n # row 14\n sheet_out['B14'].font = self.top_font\n sheet_out['B14'].alignment = self.top_alignment\n # row 15\n sheet_out['B15'].font = self.index_font\n sheet_out['B15'].fill = self.brown_fill\n sheet_out['B15'].border = self.thin_border\n sheet_out['D15'].font = self.index_font\n sheet_out['D15'].fill = self.brown_fill\n sheet_out['D15'].border = self.thin_border\n sheet_out['E15'].font = self.index_font\n sheet_out['E15'].fill = self.brown_fill\n sheet_out['E15'].border = self.thin_border\n sheet_out['C15'].border = self.thin_border\n # row 16\n sheet_out['B16'].font = self.index_font\n sheet_out['B16'].fill = self.gray_fill\n sheet_out['B16'].border = self.thin_border\n sheet_out['C16'].font = self.index_font\n sheet_out['C16'].fill = self.gray_fill\n sheet_out['C16'].border = self.thin_border\n sheet_out['D16'].font = self.index_font\n sheet_out['D16'].border = self.thin_border\n sheet_out['E16'].font = self.index_font\n sheet_out['E16'].border = self.thin_border\n # row 17\n sheet_out['B17'].border = self.thin_border\n sheet_out['C17'].font = self.index_font\n sheet_out['C17'].fill = self.gray_fill\n sheet_out['C17'].border = self.thin_border\n sheet_out['D17'].font = self.index_font\n sheet_out['D17'].border = self.thin_border\n sheet_out['E17'].font = self.index_font\n sheet_out['E17'].border = self.thin_border\n # row 18\n sheet_out['B18'].border = self.thin_border\n sheet_out['C18'].font = self.index_font\n sheet_out['C18'].fill = self.gray_fill\n sheet_out['C18'].border = self.thin_border\n sheet_out['D18'].font = self.index_font\n sheet_out['D18'].border = self.thin_border\n sheet_out['E18'].font = self.index_font\n sheet_out['E18'].border = self.thin_border\n # row 19\n sheet_out['B19'].border = self.thin_border\n sheet_out['C19'].font = self.index_font\n sheet_out['C19'].fill = self.gray_fill\n sheet_out['C19'].border = self.thin_border\n sheet_out['D19'].font = self.index_font\n sheet_out['D19'].border = self.thin_border\n sheet_out['E19'].font = self.index_font\n sheet_out['E19'].border = self.thin_border\n # row 20\n sheet_out['B20'].font = self.index_font\n sheet_out['B20'].fill = self.gray_fill\n sheet_out['B20'].border = self.thin_border\n sheet_out['D20'].font = self.index_font\n sheet_out['D20'].border = self.thin_border\n sheet_out['E20'].font = self.index_font\n sheet_out['E20'].border = self.thin_border\n sheet_out['C20'].border = self.thin_border\n # row 21\n sheet_out['B21'].font = self.index_font\n sheet_out['B21'].fill = self.gray_fill\n sheet_out['B21'].border = self.thin_border\n sheet_out['D21'].font = self.index_font\n sheet_out['D21'].border = self.thin_border\n sheet_out['E21'].font = self.index_font\n sheet_out['E21'].border = self.thin_border\n sheet_out['C21'].border = self.thin_border\n # row 22\n sheet_out['B22'].font = self.index_font\n sheet_out['B22'].fill = self.gray_fill\n sheet_out['B22'].border = self.thin_border\n sheet_out['D22'].font = self.index_font\n sheet_out['D22'].border = self.thin_border\n sheet_out['E22'].font = self.index_font\n sheet_out['E22'].border = self.thin_border\n sheet_out['C22'].border = self.thin_border\n # row 23\n sheet_out['B23'].font = self.index_font\n sheet_out['B23'].fill = self.gray_fill\n sheet_out['B23'].border = self.thin_border\n sheet_out['D23'].font = self.index_font\n sheet_out['D23'].border = self.thin_border\n sheet_out['E23'].font = self.index_font\n sheet_out['E23'].border = self.thin_border\n sheet_out['C23'].border = self.thin_border\n # row 24\n sheet_out['B24'].font = self.index_font\n sheet_out['B24'].fill = self.light_brown_fill\n sheet_out['B24'].border = self.thin_border\n sheet_out['D24'].font = self.index_font\n sheet_out['D24'].fill = self.light_brown_fill\n sheet_out['D24'].border = self.thin_border\n sheet_out['C24'].border = self.thin_border\n sheet_out['E24'].border = self.thin_border\n sheet_out['E24'].fill = self.light_brown_fill\n # row 25\n sheet_out['B25'].font = self.index_font\n sheet_out['B25'].fill = self.light_brown_fill\n sheet_out['B25'].border = self.thin_border\n sheet_out['D25'].font = self.index_font\n sheet_out['D25'].fill = self.light_brown_fill\n sheet_out['D25'].border = self.thin_border\n sheet_out['C25'].border = self.thin_border\n sheet_out['E25'].border = self.thin_border\n # row 26\n sheet_out['B26'].font = self.index_font\n sheet_out['B26'].fill = self.gray_fill\n sheet_out['B26'].border = self.thin_border\n sheet_out['D26'].font = self.index_font\n sheet_out['D26'].fill = self.light_brown_fill\n sheet_out['D26'].border = self.thin_border\n sheet_out['C25'].border = self.thin_border\n sheet_out['E25'].border = self.thin_border\n # row 28\n sheet_out['B28'].font = self.index_font\n # row 29\n sheet_out['B29'].font = self.index_font\n sheet_out['B29'].border = self.thin_border\n sheet_out['C29'].border = self.thin_border\n sheet_out['D29'].border = self.thin_border\n sheet_out['E29'].border = self.thin_border\n\n self.currentRow = self.currentRow + 1\n self.setPrintText('/s {}번 파일 \"검증요약결과\" 시트 스타일 적용 완료 /e'.format(idx+1))\n # save file\n wb_output.save(self.list_out_files[idx])\n except:\n self.setPrintText('/s Error: {}. {}, line: {}'.format(sys.exc_info()[0], sys.exc_info()[1], sys.exc_info()[2].tb_lineno)+' /e')\n self.end_count = \"y\"\n self.end_flag.emit()\n\n # 시험결과요약 Tab\n def test_generate_data(self):\n\n try:\n for idx, item in enumerate(self.list_files):\n\n temp_data = []\n wb_input = openpyxl.load_workbook(item, data_only=True)\n wb_output = openpyxl.load_workbook(self.list_out_files[idx])\n\n # get data from wb_input\n sheet_in = wb_input['시험결과요약']\n for i in range(6, 28):\n temp_data.append([sheet_in['F'+str(i)].value, sheet_in['G'+str(i)].value, sheet_in['H'+str(i)].value])\n\n #option setting wb.output\n sheet_out = wb_output['시험결과요약']\n # sheet row 2 handle\n sheet_out.merge_cells('B2:H2')\n sheet_out['B2'] = 'H/W 검증결과 요약'\n\n # sheet row 4 and 5 handle\n sheet_out.merge_cells('B4:C5')\n sheet_out['B4'] = \"항목\"\n sheet_out.merge_cells('D4:E5')\n sheet_out['D4'] = 'Test case'\n sheet_out.merge_cells('F4:H4')\n sheet_out['F4'] = '결과'\n sheet_out['F5'] = 'Pass'\n sheet_out['G5'] = 'Fail'\n sheet_out['H5'] = '점수'\n\n # sheet 6 ~ 20 handle\n sheet_out.merge_cells('B6:B20')\n sheet_out['B6'] = sheet_in['B6'].value\n sheet_out.merge_cells('C6:C10')\n sheet_out['C6'] = sheet_in['C6'].value\n sheet_out.merge_cells('C11:C15')\n sheet_out['C11'] = sheet_in['C11'].value\n sheet_out.merge_cells('C16:C19')\n sheet_out['C16'] = sheet_in['C16'].value\n sheet_out['C20'] = sheet_in['C20'].value\n sheet_out.merge_cells('D6:D7')\n sheet_out['D6'] = sheet_in['D6'].value\n sheet_out.merge_cells('D8:D9')\n sheet_out['D8'] = sheet_in['D8'].value\n sheet_out['D10'] = sheet_in['D10'].value\n sheet_out.merge_cells('D11:D12')\n sheet_out['D11'] = sheet_in['D11'].value\n sheet_out.merge_cells('D13:D14')\n sheet_out['D13'] = sheet_in['D13'].value\n sheet_out['D15'] = sheet_in['D15'].value\n sheet_out.merge_cells('D16:D17')\n sheet_out['D16'] = sheet_in['D16'].value\n sheet_out.merge_cells('D18:D19')\n sheet_out['D18'] = sheet_in['D18'].value\n sheet_out['D20'] = sheet_in['D20'].value\n sheet_out['E6'] = sheet_in['E6'].value\n sheet_out['E7'] = sheet_in['E7'].value\n sheet_out['E8'] = sheet_in['E8'].value\n sheet_out['E9'] = sheet_in['E9'].value\n sheet_out['E10'] = sheet_in['E10'].value\n sheet_out['E11'] = sheet_in['E11'].value\n sheet_out['E12'] = sheet_in['E12'].value\n sheet_out['E13'] = sheet_in['E13'].value\n sheet_out['E14'] = sheet_in['E14'].value\n sheet_out['E15'] = sheet_in['E15'].value\n sheet_out['E16'] = sheet_in['E16'].value\n sheet_out['E17'] = sheet_in['E17'].value\n sheet_out['E18'] = sheet_in['E18'].value\n sheet_out['E19'] = sheet_in['E19'].value\n sheet_out['E20'] = sheet_in['E20'].value\n\n # sheet 21 ~ 24 handle\n sheet_out.merge_cells('B21:C24')\n sheet_out['B21'] = sheet_in['B21'].value\n sheet_out.merge_cells('D21:D22')\n sheet_out['D21'] = sheet_in['D21'].value\n sheet_out.merge_cells('D23:D24')\n sheet_out['D23'] = sheet_in['D23'].value\n sheet_out['E21'] = sheet_in['E21'].value\n sheet_out['E22'] = sheet_in['E22'].value\n sheet_out['E23'] = sheet_in['E23'].value\n sheet_out['E24'] = sheet_in['E24'].value\n\n #sheet 25 ~ 28 handle\n sheet_out.merge_cells('B25:C25')\n sheet_out['B25'] = sheet_in['B25'].value\n sheet_out.merge_cells('D25:E25')\n sheet_out['D25'] = sheet_in['D25'].value\n sheet_out.merge_cells('B26:C26')\n sheet_out['B26'] = sheet_in['B26'].value\n sheet_out.merge_cells('D26:E26')\n sheet_out['D26'] = sheet_in['D26'].value\n sheet_out.merge_cells('B27:C27')\n sheet_out['B27'] = '발열'\n sheet_out.merge_cells('D27:E27')\n sheet_out['D27'] = 'Live Streaming (충전/미충전), 게임(충전/미충전)'\n sheet_out.merge_cells('B28:E28')\n sheet_out['B28'] = sheet_in['B27'].value\n sheet_out.merge_cells('B29:C29')\n sheet_out['B29'] = sheet_in['B28'].value\n sheet_out.merge_cells('D29:E29')\n sheet_out['D29'] = sheet_in['D28'].value\n sheet_out.merge_cells('F29:H29')\n sheet_out['F29'] = sheet_in['F28'].value\n\n self.setPrintText('/s {}번 파일 \"시험결과요약\" 테이터 입력 완료 /e'.format(idx+1))\n\n # set temp data\n for i in range(6, 27):\n\n sheet_out['F' + str(i)] = temp_data[i-6][0]\n sheet_out['G' + str(i)] = temp_data[i-6][1]\n sheet_out['H' + str(i)] = temp_data[i-6][2]\n\n sheet_out['F28'] = temp_data[21][0]\n sheet_out['G28'] = temp_data[21][1]\n sheet_out['H28'] = temp_data[21][2]\n\n if self.opFlag:\n\n # all cell aligment adjust\n for mCell in sheet_out[\"B4:H29\"]:\n for cell in mCell:\n cell.alignment = self.general_alignment\n\n # all cell border adjust\n for mCell in sheet_out[\"B4:H29\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n # all cell font adjust\n for mCell in sheet_out[\"B4:H29\"]:\n for cell in mCell:\n cell.font = self.index_font\n\n sheet_out['B2'].font = Font(name='맑은 고딕', size=22, bold=True, color='2B2B2B')\n sheet_out['B2'].alignment = self.general_alignment\n\n # each coloum width adjust\n sheet_cell_list = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H']\n sheet_width_list = [3.38, 9, 14.25, 8.5, 36.75, 11.25, 11.25, 11.25]\n\n for i in range(len(sheet_cell_list)):\n sheet_out.column_dimensions[sheet_cell_list[i]].width = sheet_width_list[i]\n sheet_out.row_dimensions[2].height = 26.25\n\n # Set Pattern Fill\n sheet_out['B4'].fill = self.brown_fill\n sheet_out['D4'].fill = self.brown_fill\n sheet_out['F4'].fill = self.brown_fill\n sheet_out['F5'].fill = self.brown_fill\n sheet_out['G5'].fill = self.brown_fill\n sheet_out['H5'].fill = self.brown_fill\n\n for i in range(6, 28):\n sheet_out['B' + str(i)].fill = self.gray_fill\n sheet_out['C' + str(i)].fill = self.gray_fill\n sheet_out['D' + str(i)].fill = self.gray_fill\n sheet_out['E' + str(i)].fill = self.gray_fill\n\n sheet_out['B28'].fill = self.dark_gray_fill\n sheet_out['F28'].fill = self.dark_gray_fill\n sheet_out['G28'].fill = self.dark_gray_fill\n sheet_out['H28'].fill = self.dark_gray_fill\n sheet_out['B29'].fill = self.gray_fill\n sheet_out['D29'].fill = self.gray_fill\n self.currentRow = self.currentRow + 1\n self.setPrintText('/s {}번 파일 \"시험결과요약\" 시트 스타일 적용 완료 /e'.format(idx+1))\n # save file\n wb_output.save(self.list_out_files[idx])\n except:\n self.setPrintText('/s Error: {}. {}, line: {}'.format(sys.exc_info()[0], sys.exc_info()[1], sys.exc_info()[2].tb_lineno)+' /e')\n self.end_count = \"y\"\n self.end_flag.emit()\n\n # TRP Tab\n def trp_generate_data(self):\n # 절대값 abs\n try:\n for idx, item in enumerate(self.list_files):\n\n wb_input = openpyxl.load_workbook(item, data_only=True)\n wb_output = openpyxl.load_workbook(self.list_out_files[idx])\n list_5g_trp = []\n list_lte_trp = []\n list_wcdma_trp = []\n\n # get data from wb_input\n sheet_in = wb_input['5G OTA']\n list_5g_trp.append(self.check_num(sheet_in['J5'].value))\n list_5g_trp.append(self.check_num(sheet_in['J6'].value))\n\n sheet_in = wb_input['LTE OTA']\n list_lte_trp.append(self.check_num(sheet_in['K17'].value))\n list_lte_trp.append(self.check_num(sheet_in['C17'].value))\n list_lte_trp.append(self.check_num(sheet_in['C10'].value))\n list_lte_trp.append(self.check_num(sheet_in['G17'].value))\n list_lte_trp.append(self.check_num(sheet_in['G10'].value))\n list_lte_trp.append(self.check_num(sheet_in['M17'].value))\n list_lte_trp.append(self.check_num(sheet_in['E17'].value))\n list_lte_trp.append(self.check_num(sheet_in['E10'].value))\n list_lte_trp.append(self.check_num(sheet_in['I17'].value))\n list_lte_trp.append(self.check_num(sheet_in['I10'].value))\n\n sheet_in = wb_input['WCDMA OTA']\n list_wcdma_trp.append(self.check_num(sheet_in['D9'].value))\n\n #option setting wb.output\n sheet_out = wb_output['TRP']\n # sheet row 2 handle\n sheet_out.merge_cells('A1:C1')\n sheet_out['A1'] = 'TRP 결과'\n\n # 3~4 row\n sheet_out['A3'] = '▣ SISO TRP'\n sheet_out['A4'] = ' - 5G'\n\n # sheet row 5 and 7 handle\n sheet_out['A5'] = '구분'\n sheet_out['B5'] = '기준(RHP)'\n sheet_out['C5'] = '측정결과'\n sheet_out['D5'] = '비교'\n sheet_out['A6'] = 'CP-OFDM (n78)'\n sheet_out['B6'] = '16.86dBm(V50S)'\n sheet_out['C6'] = list_5g_trp[0]+'dBm'\n # sheet_out['D6'] = self.check_num(abs(round(abs(float(list_5g_trp[0]))-16.86, 2))) + 'dBm'\n sheet_out['D6'] = self.cal_comparison(16.86, list_5g_trp[0]) + 'dBm'\n sheet_out['A7'] = 'DFTs-OFDM (n78)'\n sheet_out['B7'] = '-'\n sheet_out['C7'] = list_5g_trp[1]+'dBm'\n sheet_out['D7'] = '-'\n\n # sheet row 8 and 15 handle\n sheet_out['A8'] = ' - LTE'\n sheet_out['A9'] = '구분'\n sheet_out['B9'] = '기준(RHP)'\n sheet_out['C9'] = '측정결과'\n sheet_out['D9'] = '비교'\n\n sheet_out['A10'] = 'Band 1 15M'\n sheet_out['B10'] = '14.00dBm'\n sheet_out['C10'] = list_lte_trp[0] + 'dBm'\n # sheet_out['D10'] = self.check_num(abs(round(abs(float(list_lte_trp[0]))-14.00, 2))) + 'dBm'\n sheet_out['D10'] = self.cal_comparison(14.00, list_lte_trp[0]) + 'dBm'\n sheet_out['A11'] = 'Band 3 20M'\n sheet_out['B11'] = '15.00dBm'\n sheet_out['C11'] = list_lte_trp[1] + 'dBm'\n # sheet_out['D11'] = self.check_num(abs(round(abs(float(list_lte_trp[1]))-15.00, 2))) + 'dBm'\n sheet_out['D11'] = self.cal_comparison(15.00, list_lte_trp[1]) + 'dBm'\n sheet_out['A12'] = 'Band 5 10M'\n sheet_out['B12'] = '13.50dBm'\n sheet_out['C12'] = list_lte_trp[2] + 'dBm'\n # sheet_out['D12'] = self.check_num(abs(round(abs(float(list_lte_trp[2]))-13.50, 2))) + 'dBm'\n sheet_out['D12'] = self.cal_comparison(13.50, list_lte_trp[2]) + 'dBm'\n sheet_out['A13'] = 'Band 7 20M'\n sheet_out['B13'] = '13.00dBm'\n sheet_out['C13'] = list_lte_trp[3] + 'dBm'\n # sheet_out['D13'] = self.check_num(abs(round(abs(float(list_lte_trp[3])) - 13.00, 2))) + 'dBm'\n sheet_out['D13'] = self.cal_comparison(13.00, list_lte_trp[3]) + 'dBm'\n sheet_out['A14'] = 'Band 7 10M'\n sheet_out['B14'] = '13.00dBm'\n sheet_out['C14'] = list_lte_trp[4] + 'dBm'\n # sheet_out['D14'] = self.check_num(abs(round(abs(float(list_lte_trp[4])) - 13.00, 2))) + 'dBm'\n sheet_out['D14'] = self.cal_comparison(13.00, list_lte_trp[4]) + 'dBm'\n\n # sheet row 15 and 17 handle\n sheet_out['A15'] = ' - WCDMA (납품검사 결과)'\n sheet_out['A16'] = '구분'\n sheet_out['B16'] = '기준(RHP)'\n sheet_out['C16'] = '측정결과'\n sheet_out['A17'] = 'Band 1'\n sheet_out['B17'] = '15.00dBm'\n sheet_out['C17'] = list_wcdma_trp[0] + 'dBm'\n # sheet_out['D17'] = self.check_num(abs(round(abs(float(list_wcdma_trp[0])) - 15.00, 2))) + 'dBm'\n sheet_out['D17'] = self.cal_comparison(15.00, list_wcdma_trp[0]) + 'dBm'\n\n # sheet row 19 and 27 handle\n sheet_out['A19'] = '▣ MIMO TRP'\n sheet_out['A20'] = ' - LTE'\n sheet_out['A21'] = '구분'\n sheet_out['B21'] = '기준(RHP)'\n sheet_out['C21'] = '측정결과'\n sheet_out['A22'] = 'Band 1 15M'\n sheet_out['B22'] = '14.00dBm'\n sheet_out['C22'] = list_lte_trp[5] + 'dBm'\n # sheet_out['D22'] = self.check_num(abs(round(abs(float(list_lte_trp[5])) - 14.00, 2))) + 'dBm'\n sheet_out['D22'] = self.cal_comparison(14.00, list_lte_trp[5]) + 'dBm'\n sheet_out['A23'] = 'Band 3 20M'\n sheet_out['B23'] = '15.00dBm'\n sheet_out['C23'] = list_lte_trp[6] + 'dBm'\n # sheet_out['D23'] = self.check_num(abs(round(abs(float(list_lte_trp[6])) - 15.00, 2))) + 'dBm'\n sheet_out['D23'] = self.cal_comparison(15.00, list_lte_trp[6]) + 'dBm'\n sheet_out['A24'] = 'Band 5 10M'\n sheet_out['B24'] = '13.50dBm'\n sheet_out['C24'] = list_lte_trp[7]+'dBm'\n # sheet_out['D24'] = self.check_num(abs(round(abs(float(list_lte_trp[7])) - 13.50, 2))) + 'dBm'\n sheet_out['D24'] = self.cal_comparison(13.50, list_lte_trp[7]) + 'dBm'\n sheet_out['A25'] = 'Band 7 20M'\n sheet_out['B25'] = '13.00dBm'\n sheet_out['C25'] = list_lte_trp[8] + 'dBm'\n # sheet_out['D25'] = self.check_num(abs(round(abs(float(list_lte_trp[8])) - 13.00, 2))) + 'dBm'\n sheet_out['D25'] = self.cal_comparison(13.00, list_lte_trp[8]) + 'dBm'\n sheet_out['A26'] = 'Band 7 10M'\n sheet_out['B26'] = '13.00dBm'\n sheet_out['C26'] = list_lte_trp[9] + 'dBm'\n # sheet_out['D26'] = self.check_num(abs(round(abs(float(list_lte_trp[9])) - 13.00, 2))) + 'dBm'\n sheet_out['D26'] = self.cal_comparison(13.00, list_lte_trp[9]) + 'dBm'\n\n self.setPrintText('/s {}번 파일 \"TRP\" 테이터 입력 완료 /e'.format(idx+1))\n\n # set temp data\n\n if self.opFlag:\n\n # all cell alignment adjust\n for mCell in sheet_out[\"A1:D26\"]:\n for cell in mCell:\n cell.alignment = self.general_alignment\n # top alignment adjust\n sheet_out['A3'].alignment = self.top_alignment\n sheet_out['A4'].alignment = self.top_alignment\n sheet_out['A8'].alignment = self.top_alignment\n sheet_out['A15'].alignment = self.top_alignment\n sheet_out['A19'].alignment = self.top_alignment\n sheet_out['A20'].alignment = self.top_alignment\n\n # all cell border adjust\n for mCell in sheet_out[\"A5:D7\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n # all cell border adjust\n for mCell in sheet_out[\"A9:D14\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n # all cell border adjust\n for mCell in sheet_out[\"A16:D17\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n # all cell border adjust\n for mCell in sheet_out[\"A21:D26\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n # all cell font adjust\n for mCell in sheet_out[\"A3:D26\"]:\n for cell in mCell:\n cell.font = self.index_font\n\n sheet_out['A1'].font = Font(name='맑은 고딕', size=22, bold=True, color='2B2B2B')\n\n # each coloum width adjust\n sheet_cell_list = ['A', 'B', 'C', 'D']\n sheet_width_list = [25, 16.75, 17, 15]\n\n for i in range(len(sheet_cell_list)):\n sheet_out.column_dimensions[sheet_cell_list[i]].width = sheet_width_list[i]\n sheet_out.row_dimensions[1].height = 45\n\n # Set Pattern Fill\n for i in [5, 9, 16, 21]:\n sheet_out['A' + str(i)].fill = self.brown_fill\n sheet_out['B' + str(i)].fill = self.brown_fill\n sheet_out['C' + str(i)].fill = self.brown_fill\n sheet_out['D' + str(i)].fill = self.brown_fill\n\n for i in [6, 7, 10, 11, 12, 13, 14, 17, 22, 23, 24, 25, 26]:\n sheet_out['A'+str(i)].fill = self.gray_fill\n sheet_out['B'+str(i)].fill = self.apricot_fill\n\n self.currentRow = self.currentRow + 1\n self.setPrintText('/s {}번 파일 \"TRP\" 시트 스타일 적용 완료 /e'.format(idx+1))\n # save file\n wb_output.save(self.list_out_files[idx])\n except:\n self.setPrintText('/s Error: {}. {}, line: {}'.format(sys.exc_info()[0], sys.exc_info()[1], sys.exc_info()[2].tb_lineno)+' /e')\n self.end_count = \"y\"\n self.end_flag.emit()\n\n # TIS Tab\n def tis_generate_data(self):\n\n try:\n for idx, item in enumerate(self.list_files):\n\n wb_input = openpyxl.load_workbook(item, data_only=True)\n wb_output = openpyxl.load_workbook(self.list_out_files[idx])\n list_5g_tis = []\n list_lte_tis = []\n list_wcdma_tis = []\n\n # get data from wb_input\n sheet_in = wb_input['5G OTA']\n list_5g_tis.append(self.check_num(sheet_in['J7'].value))\n list_5g_tis.append(self.check_num(sheet_in['J8'].value))\n\n sheet_in = wb_input['LTE OTA']\n list_lte_tis.append(self.check_num(sheet_in['L17'].value))\n list_lte_tis.append(self.check_num(sheet_in['D17'].value))\n list_lte_tis.append(self.check_num(sheet_in['D10'].value))\n list_lte_tis.append(self.check_num(sheet_in['H17'].value))\n list_lte_tis.append(self.check_num(sheet_in['H10'].value))\n list_lte_tis.append(self.check_num(sheet_in['N17'].value))\n list_lte_tis.append(self.check_num(sheet_in['F17'].value))\n list_lte_tis.append(self.check_num(sheet_in['F10'].value))\n list_lte_tis.append(self.check_num(sheet_in['J17'].value))\n list_lte_tis.append(self.check_num(sheet_in['J10'].value))\n\n sheet_in = wb_input['WCDMA OTA']\n list_wcdma_tis.append(self.check_num(sheet_in['E9'].value))\n\n #option setting wb.output\n sheet_out = wb_output['TIS']\n # sheet row 2 handle\n sheet_out.merge_cells('A1:C1')\n sheet_out['A1'] = 'TIS 결과'\n\n # 3~4 row\n sheet_out['A3'] = '▣ SISO TIS'\n sheet_out['A4'] = ' - 5G'\n\n # sheet row 5 and 7 handle\n sheet_out['A5'] = '구분'\n sheet_out['B5'] = '기준(RHP)'\n sheet_out['C5'] = '측정결과'\n sheet_out['D5'] = '비교'\n sheet_out['A6'] = 'SISO (n78)'\n sheet_out['B6'] = '-'\n sheet_out['C6'] = list_5g_tis[0] + 'dBm'\n sheet_out['D6'] = '-'\n\n # sheet row 8 and 14 handle\n sheet_out['A8'] = ' - LTE'\n sheet_out['A9'] = '구분'\n sheet_out['B9'] = '기준(RHP)'\n sheet_out['C9'] = '측정결과'\n sheet_out['D9'] = '비교'\n sheet_out['A10'] = 'Band 1 15M'\n sheet_out['B10'] = '-92.00dBm'\n sheet_out['C10'] = list_lte_tis[0] + 'dBm'\n # sheet_out['D10'] = self.check_num(abs(round(abs(float(list_lte_tis[0])) - 92.00, 2))) + 'dBm'\n sheet_out['D10'] = self.cal_comparison(92.00, list_lte_tis[0]) + 'dBm'\n sheet_out['A11'] = 'Band 3 20M'\n sheet_out['B11'] = '-91.00dBm'\n sheet_out['C11'] = list_lte_tis[1] + 'dBm'\n # sheet_out['D11'] = self.check_num(abs(round(abs(float(list_lte_tis[1])) - 91.00, 2))) + 'dBm'\n sheet_out['D11'] = self.cal_comparison(91.00, list_lte_tis[1]) + 'dBm'\n sheet_out['A12'] = 'Band 5 10M'\n sheet_out['B12'] = '-87.00dBm'\n sheet_out['C12'] = list_lte_tis[2] + 'dBm'\n # sheet_out['D12'] = self.check_num(abs(round(abs(float(list_lte_tis[2])) - 87.00, 2))) + 'dBm'\n sheet_out['D12'] = self.cal_comparison(87.00, list_lte_tis[2]) + 'dBm'\n sheet_out['A13'] = 'Band 7 20M'\n sheet_out['B13'] = '-90.00dBm'\n sheet_out['C13'] = list_lte_tis[3] + 'dBm'\n sheet_out['D13'] = self.check_num(abs(round(abs(float(list_lte_tis[3])) - 90.00, 2))) + 'dBm'\n sheet_out['D13'] = self.cal_comparison(90.00, list_lte_tis[3]) + 'dBm'\n sheet_out['A14'] = 'Band 7 10M'\n sheet_out['B14'] = '-93.00dBm'\n sheet_out['C14'] = list_lte_tis[4] + 'dBm'\n # sheet_out['D14'] = self.check_num(abs(round(abs(float(list_lte_tis[4])) - 93.00, 2))) + 'dBm'\n sheet_out['D14'] = self.cal_comparison(93.00, list_lte_tis[4]) + 'dBm'\n\n # sheet row 16 and 18 handle\n sheet_out['A15'] = ' - WCDMA (납품검사 결과)'\n sheet_out['A16'] = '구분'\n sheet_out['B16'] = '기준(RHP)'\n sheet_out['C16'] = '측정결과'\n sheet_out['D16'] = '비교'\n sheet_out['A17'] = 'Band 1'\n sheet_out['B17'] = '-104.00dBm'\n sheet_out['C17'] = list_wcdma_tis[0] + 'dBm'\n # sheet_out['D17'] = self.check_num(abs(round(abs(float(list_wcdma_tis[0])) - 104.00, 2))) + 'dBm'\n sheet_out['D17'] = self.cal_comparison(104.00, list_wcdma_tis[0]) + 'dBm'\n\n # sheet row 19 and 22 handle\n sheet_out['A19'] = '▣ MIMO TRP'\n sheet_out['A20'] = ' - 5G'\n sheet_out['A21'] = '구분'\n sheet_out['B21'] = '기준(RHP)'\n sheet_out['C21'] = '측정결과'\n sheet_out['D21'] = '비교'\n sheet_out['A22'] = 'MIMO 4X4 (n78)'\n sheet_out['B22'] = '-'\n sheet_out['C22'] = list_5g_tis[1] + 'dBm'\n sheet_out['D22'] = '-'\n\n # sheet row 24 and 30 handle\n sheet_out['A24'] = ' - LTE'\n sheet_out['A25'] = '구분'\n sheet_out['B25'] = '기준(RHP)'\n sheet_out['C25'] = '측정결과'\n sheet_out['D25'] = '비교'\n sheet_out['A26'] = 'Band 1 15M'\n sheet_out['B26'] = '-86.00dBm'\n sheet_out['C26'] = list_lte_tis[5] + 'dBm'\n # sheet_out['D26'] = self.check_num(abs(round(abs(float(list_lte_tis[5])) - 86.00, 2))) + 'dBm'\n sheet_out['D26'] = self.cal_comparison(86.00, list_lte_tis[5]) + 'dBm'\n sheet_out['A27'] = 'Band 3 20M'\n sheet_out['B27'] = '-86.00dBm'\n sheet_out['C27'] = list_lte_tis[6] + 'dBm'\n # sheet_out['D27'] = self.check_num(abs(round(abs(float(list_lte_tis[6])) - 86.00, 2))) + 'dBm'\n sheet_out['D27'] = self.cal_comparison(86.00, list_lte_tis[6]) + 'dBm'\n sheet_out['A28'] = 'Band 5 10M'\n sheet_out['B28'] = '-82.50dBm'\n sheet_out['C28'] = list_lte_tis[7] + 'dBm'\n # sheet_out['D28'] = self.check_num(abs(round(abs(float(list_lte_tis[7])) - 82.50, 2))) + 'dBm'\n sheet_out['D28'] = self.cal_comparison(82.50, list_lte_tis[7]) + 'dBm'\n sheet_out['A29'] = 'Band 7 20M'\n sheet_out['B29'] = '-84.00dBm'\n sheet_out['C29'] = list_lte_tis[8] + 'dBm'\n # sheet_out['D29'] = self.check_num(abs(round(abs(float(list_lte_tis[8])) - 84.00, 2))) + 'dBm'\n sheet_out['D29'] = self.cal_comparison(84.00, list_lte_tis[8]) + 'dBm'\n sheet_out['A30'] = 'Band 7 10M'\n sheet_out['B30'] = '-87.00dBm'\n sheet_out['C30'] = list_lte_tis[9] + 'dBm'\n # sheet_out['D30'] = self.check_num(abs(round(abs(float(list_lte_tis[9])) - 87.00, 2))) + 'dBm'\n sheet_out['D30'] = self.cal_comparison(87.00, list_lte_tis[9]) + 'dBm'\n\n self.setPrintText('/s {}번 파일 \"TIS\" 테이터 입력 완료 /e'.format(idx+1))\n\n # set temp data\n\n if self.opFlag:\n\n # all cell alignment adjust\n for mCell in sheet_out[\"A1:D30\"]:\n for cell in mCell:\n cell.alignment = self.general_alignment\n # top alignment adjust\n sheet_out['A3'].alignment = self.top_alignment\n sheet_out['A4'].alignment = self.top_alignment\n sheet_out['A8'].alignment = self.top_alignment\n sheet_out['A15'].alignment = self.top_alignment\n sheet_out['A19'].alignment = self.top_alignment\n sheet_out['A20'].alignment = self.top_alignment\n sheet_out['A24'].alignment = self.top_alignment\n\n # all cell border adjust\n for mCell in sheet_out[\"A5:D6\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n # all cell border adjust\n for mCell in sheet_out[\"A9:D14\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n # all cell border adjust\n for mCell in sheet_out[\"A16:D17\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n # all cell border adjust\n for mCell in sheet_out[\"A21:D22\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n # all cell border adjust\n for mCell in sheet_out[\"A25:D30\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n # all cell font adjust\n for mCell in sheet_out[\"A3:D30\"]:\n for cell in mCell:\n cell.font = self.index_font\n\n sheet_out['A1'].font = Font(name='맑은 고딕', size=22, bold=True, color='2B2B2B')\n\n # each coloum width adjust\n sheet_cell_list = ['A', 'B', 'C', 'D']\n sheet_width_list = [25, 15, 17, 15]\n\n for i in range(len(sheet_cell_list)):\n sheet_out.column_dimensions[sheet_cell_list[i]].width = sheet_width_list[i]\n sheet_out.row_dimensions[1].height = 45\n\n # Set Pattern Fill\n\n for i in [5, 9, 16, 21, 25]:\n sheet_out['A' + str(i)].fill = self.brown_fill\n sheet_out['B' + str(i)].fill = self.brown_fill\n sheet_out['C' + str(i)].fill = self.brown_fill\n sheet_out['D' + str(i)].fill = self.brown_fill\n\n for i in [6, 10, 11, 12, 13, 14, 17, 22, 26, 27, 28, 29, 30]:\n sheet_out['A'+str(i)].fill = self.gray_fill\n sheet_out['B'+str(i)].fill = self.apricot_fill\n\n self.currentRow = self.currentRow + 1\n self.setPrintText('/s {}번 파일 \"TIS\" 시트 스타일 적용 완료 /e'.format(idx+1))\n # save file\n wb_output.save(self.list_out_files[idx])\n except:\n self.setPrintText('/s Error: {}. {}, line: {}'.format(sys.exc_info()[0], sys.exc_info()[1], sys.exc_info()[2].tb_lineno)+' /e')\n self.end_count = \"y\"\n self.end_flag.emit()\n\n # 속도 Tab\n def spd_generate_data(self):\n\n try:\n for idx, item in enumerate(self.list_files):\n\n wb_input = openpyxl.load_workbook(item, data_only=True)\n wb_output = openpyxl.load_workbook(self.list_out_files[idx])\n list_lte_spd = []\n\n # get data from wb_input\n sheet_in = wb_input['LTE OTA']\n # MIMO\n list_lte_spd.append(self.check_num(sheet_in['I25'].value))\n list_lte_spd.append(self.check_num(sheet_in['J25'].value))\n list_lte_spd.append(self.check_num(sheet_in['K25'].value))\n list_lte_spd.append(self.check_num(sheet_in['F25'].value))\n list_lte_spd.append(self.check_num(sheet_in['G25'].value))\n list_lte_spd.append(self.check_num(sheet_in['H25'].value))\n list_lte_spd.append(self.check_num(sheet_in['C25'].value))\n list_lte_spd.append(self.check_num(sheet_in['D25'].value))\n list_lte_spd.append(self.check_num(sheet_in['E25'].value))\n list_lte_spd.append(self.check_num(sheet_in['L25'].value))\n list_lte_spd.append(self.check_num(sheet_in['M25'].value))\n list_lte_spd.append(self.check_num(sheet_in['N25'].value))\n list_lte_spd.append(self.check_num(sheet_in['O25'].value))\n list_lte_spd.append(self.check_num(sheet_in['P25'].value))\n list_lte_spd.append(self.check_num(sheet_in['Q25'].value))\n # CA\n list_lte_spd.append(self.check_num(sheet_in['C33'].value))\n list_lte_spd.append(self.check_num(sheet_in['D33'].value))\n list_lte_spd.append(self.check_num(sheet_in['E33'].value))\n list_lte_spd.append(self.check_num(sheet_in['F33'].value))\n list_lte_spd.append(self.check_num(sheet_in['G33'].value))\n list_lte_spd.append(self.check_num(sheet_in['H33'].value))\n list_lte_spd.append(self.check_num(sheet_in['I33'].value))\n list_lte_spd.append(self.check_num(sheet_in['J33'].value))\n list_lte_spd.append(self.check_num(sheet_in['K33'].value))\n list_lte_spd.append(self.check_num(sheet_in['L33'].value))\n list_lte_spd.append(self.check_num(sheet_in['M33'].value))\n list_lte_spd.append(self.check_num(sheet_in['N33'].value))\n list_lte_spd.append(self.check_num(sheet_in['O33'].value))\n list_lte_spd.append(self.check_num(sheet_in['P33'].value))\n list_lte_spd.append(self.check_num(sheet_in['Q33'].value))\n list_lte_spd.append(self.check_num(sheet_in['R33'].value))\n list_lte_spd.append(self.check_num(sheet_in['S33'].value))\n list_lte_spd.append(self.check_num(sheet_in['T33'].value))\n\n #option setting wb.output\n sheet_out = wb_output['속도']\n # sheet row 2 handle\n sheet_out.merge_cells('A1:C1')\n sheet_out['A1'] = '속도 결과'\n\n # 3~4 row\n sheet_out['A3'] = '▣ MIMO 속도'\n sheet_out['A4'] = ' - LTE'\n\n # sheet row 5 and 20 handle\n sheet_out['A5'] = '구분'\n sheet_out.merge_cells('B5:C5')\n sheet_out['B5'] = '기준(Free)'\n sheet_out['D5'] = '측정결과'\n sheet_out['E5'] = '비교'\n\n sheet_out.merge_cells('A6:A8')\n sheet_out['A6'] = 'Band 1 15M(MCS28)'\n sheet_out['B6'] = 'RSSI'\n sheet_out['B7'] = '속도(Absolute)'\n sheet_out['B8'] = 'BLER'\n sheet_out['C6'] = '-61.00dBm'\n sheet_out['C7'] = '87700Kbps'\n sheet_out['C8'] = '20.00%'\n sheet_out['D6'] = list_lte_spd[0] + 'dBm'\n sheet_out['D7'] = list_lte_spd[1] + 'Kbps'\n sheet_out['D8'] = list_lte_spd[2] + '%'\n # sheet_out['E6'] = self.check_num(abs(round(abs(float(list_lte_spd[0])) - 61.00, 2))) + 'dBm'\n # sheet_out['E7'] = self.check_num(abs(round(abs(float(list_lte_spd[1])) - 87700, 2))) + 'Kbps'\n # sheet_out['E8'] = self.check_num(abs(round(abs(float(list_lte_spd[2])) - 20.00, 2))) + '%'\n sheet_out['E6'] = self.cal_comparison(61.00, list_lte_spd[0]) + 'dBm'\n sheet_out['E7'] = self.cal_comparison(87700.00, list_lte_spd[1]) + 'Kbps'\n sheet_out['E8'] = self.cal_comparison(20.00, list_lte_spd[2]) + '%'\n\n sheet_out.merge_cells('A9:A11')\n sheet_out['A9'] = 'Band 3 20M(MCS28)'\n sheet_out['B9'] = 'RSSI'\n sheet_out['B10'] = '속도(Absolute)'\n sheet_out['B11'] = 'BLER'\n sheet_out['C9'] = '-61.00dBm'\n sheet_out['C10'] = '119900Kbps'\n sheet_out['C11'] = '20.00%'\n sheet_out['D9'] = list_lte_spd[3] + 'dBm'\n sheet_out['D10'] = list_lte_spd[4] + 'Kbps'\n sheet_out['D11'] = list_lte_spd[5] + '%'\n # sheet_out['E9'] = self.check_num(abs(round(abs(float(list_lte_spd[3])) - 61.00, 2))) + 'dBm'\n # sheet_out['E10'] = self.check_num(abs(round(abs(float(list_lte_spd[4])) - 119900, 2))) + 'Kbps'\n # sheet_out['E11'] = self.check_num(abs(round(abs(float(list_lte_spd[5])) - 20.00, 2))) + '%'\n sheet_out['E9'] = self.cal_comparison(61.00, list_lte_spd[3]) + 'dBm'\n sheet_out['E10'] = self.cal_comparison(119900.00, list_lte_spd[4]) + 'Kbps'\n sheet_out['E11'] = self.cal_comparison(20.00, list_lte_spd[5]) + '%'\n\n sheet_out.merge_cells('A12:A14')\n sheet_out['A12'] = 'Band 5 10M(MCS27)'\n sheet_out['B12'] = 'RSSI'\n sheet_out['B13'] = '속도(Absolute)'\n sheet_out['B14'] = 'BLER'\n sheet_out['C12'] = '-60.00dBm'\n sheet_out['C13'] = '50300Kbps'\n sheet_out['C14'] = '20.00%'\n sheet_out['D12'] = list_lte_spd[6] + 'dBm'\n sheet_out['D13'] = list_lte_spd[7] + 'Kbps'\n sheet_out['D14'] = list_lte_spd[8] + '%'\n # sheet_out['E12'] = self.check_num(abs(round(abs(float(list_lte_spd[6])) - 60.00, 2))) + 'dBm'\n # sheet_out['E13'] = self.check_num(abs(round(abs(float(list_lte_spd[7])) - 50300, 2))) + 'Kbps'\n # sheet_out['E14'] = self.check_num(abs(round(abs(float(list_lte_spd[8])) - 20.00, 2))) + '%'\n sheet_out['E12'] = self.cal_comparison(60.00, list_lte_spd[6]) + 'dBm'\n sheet_out['E13'] = self.cal_comparison(50300.00, list_lte_spd[7]) + 'Kbps'\n sheet_out['E14'] = self.cal_comparison(20.00, list_lte_spd[8]) + '%'\n\n sheet_out.merge_cells('A15:A17')\n sheet_out['A15'] = 'Band 7 20M(MCS28)'\n sheet_out['B15'] = 'RSSI'\n sheet_out['B16'] = '속도(Absolute)'\n sheet_out['B17'] = 'BLER'\n sheet_out['C15'] = '-60.00dBm'\n sheet_out['C16'] = '119900Kbps'\n sheet_out['C17'] = '20.00%'\n sheet_out['D15'] = list_lte_spd[9] + 'dBm'\n sheet_out['D16'] = list_lte_spd[10] + 'Kbps'\n sheet_out['D17'] = list_lte_spd[11] + '%'\n # sheet_out['E15'] = self.check_num(abs(round(abs(float(list_lte_spd[9])) - 60.00, 2))) + 'dBm'\n # sheet_out['E16'] = self.check_num(abs(round(abs(float(list_lte_spd[10])) - 119900, 2))) + 'Kbps'\n # sheet_out['E17'] = self.check_num(abs(round(abs(float(list_lte_spd[11])) - 20.00, 2))) + '%'\n sheet_out['E15'] = self.cal_comparison(60.00, list_lte_spd[9]) + 'dBm'\n sheet_out['E16'] = self.cal_comparison(119900.00, list_lte_spd[10]) + 'Kbps'\n sheet_out['E17'] = self.cal_comparison(20.00, list_lte_spd[11]) + '%'\n\n sheet_out.merge_cells('A18:A20')\n sheet_out['A18'] = 'Band 7 10M(MCS27)'\n sheet_out['B18'] = 'RSSI'\n sheet_out['B19'] = '속도(Absolute)'\n sheet_out['B20'] = 'BLER'\n sheet_out['C18'] = '-60.00dBm'\n sheet_out['C19'] = '50300Kbps'\n sheet_out['C20'] = '20.00%'\n sheet_out['D18'] = list_lte_spd[12] + 'dBm'\n sheet_out['D19'] = list_lte_spd[13] + 'Kbps'\n sheet_out['D20'] = list_lte_spd[14] + '%'\n # sheet_out['E18'] = self.check_num(abs(round(abs(float(list_lte_spd[12])) - 60.00, 2))) + 'dBm'\n # sheet_out['E19'] = self.check_num(abs(round(abs(float(list_lte_spd[13])) - 50300, 2))) + 'Kbps'\n # sheet_out['E20'] = self.check_num(abs(round(abs(float(list_lte_spd[14])) - 20.00, 2))) + '%'\n sheet_out['E18'] = self.cal_comparison(60.00, list_lte_spd[12]) + 'dBm'\n sheet_out['E19'] = self.cal_comparison(50300.00, list_lte_spd[13]) + 'Kbps'\n sheet_out['E20'] = self.cal_comparison(20.00, list_lte_spd[14]) + '%'\n\n\n # 22 ~ 23 row\n sheet_out['A22'] = '▣ CA 속도'\n sheet_out['A23'] = ' - LTE'\n\n # sheet row 24 and 42 handle\n sheet_out['A24'] = '구분'\n sheet_out.merge_cells('B24:C24')\n sheet_out['B24'] = '기준(Free)'\n sheet_out['D24'] = '측정결과'\n sheet_out['E24'] = '비교'\n\n sheet_out.merge_cells('A25:A27')\n sheet_out['A25'] = '2CA : B3+B5(MCS28)'\n sheet_out['B25'] = 'RSSI'\n sheet_out['B26'] = '속도(Absolute)'\n sheet_out['B27'] = 'BLER'\n sheet_out['C25'] = '-58.00dBm'\n sheet_out['C26'] = '178390Kbps'\n sheet_out['C27'] = '-'\n sheet_out['D25'] = list_lte_spd[15] + 'dBm'\n sheet_out['D26'] = list_lte_spd[16] + 'Kbps'\n sheet_out['D27'] = list_lte_spd[17] + '%'\n # sheet_out['E25'] = self.check_num(abs(round(abs(float(list_lte_spd[15])) - 58.00, 2))) + 'dBm'\n # sheet_out['E26'] = self.check_num(abs(round(abs(float(list_lte_spd[16])) - 178390, 2))) + 'Kbps'\n sheet_out['E25'] = self.cal_comparison(58.00, list_lte_spd[15]) + 'dBm'\n sheet_out['E26'] = self.cal_comparison(178390.00, list_lte_spd[16]) + 'Kbps'\n sheet_out['E27'] = '-'\n\n sheet_out.merge_cells('A28:A30')\n sheet_out['A28'] = '3CA : B7(20M)+B3+B1(MCS28)'\n sheet_out['B28'] = 'RSSI'\n sheet_out['B29'] = '속도(Absolute)'\n sheet_out['B30'] = 'BLER'\n sheet_out['C28'] = '-58.00dBm'\n sheet_out['C29'] = '327500Kbps'\n sheet_out['C30'] = '-'\n sheet_out['D28'] = list_lte_spd[18] + 'dBm'\n sheet_out['D29'] = list_lte_spd[19] + 'Kbps'\n sheet_out['D30'] = list_lte_spd[20] + '%'\n # sheet_out['E28'] = self.check_num(abs(round(abs(float(list_lte_spd[18])) - 58.00, 2))) + 'dBm'\n # sheet_out['E29'] = self.check_num(abs(round(abs(float(list_lte_spd[19])) - 327500, 2))) + 'Kbps'\n sheet_out['E28'] = self.cal_comparison(58.00, list_lte_spd[18]) + 'dBm'\n sheet_out['E29'] = self.cal_comparison(327500.00, list_lte_spd[19]) + 'Kbps'\n sheet_out['E30'] = '-'\n\n sheet_out.merge_cells('A31:A33')\n sheet_out['A31'] = '3CA : B7(20M)+B3+B5(MCS28)'\n sheet_out['B31'] = 'RSSI'\n sheet_out['B32'] = '속도(Absolute)'\n sheet_out['B33'] = 'BLER'\n sheet_out['C31'] = '-58.00dBm'\n sheet_out['C32'] = '298300Kbps'\n sheet_out['C33'] = '-'\n sheet_out['D31'] = list_lte_spd[21] + 'dBm'\n sheet_out['D32'] = list_lte_spd[22] + 'Kbps'\n sheet_out['D33'] = list_lte_spd[23] + '%'\n # sheet_out['E31'] = self.check_num(abs(round(abs(float(list_lte_spd[21])) - 58.00, 2))) + 'dBm'\n # sheet_out['E32'] = self.check_num(abs(round(abs(float(list_lte_spd[22])) - 298300, 2))) + 'Kbps'\n sheet_out['E31'] = self.cal_comparison(58.00, list_lte_spd[21]) + 'dBm'\n sheet_out['E32'] = self.cal_comparison(298300.00, list_lte_spd[22]) + 'Kbps'\n sheet_out['E33'] = '-'\n\n sheet_out.merge_cells('A34:A36')\n sheet_out['A34'] = '3CA : B7(20M)+B3+B7(MCS28)'\n sheet_out['B34'] = 'RSSI'\n sheet_out['B35'] = '속도(Absolute)'\n sheet_out['B36'] = 'BLER'\n sheet_out['C34'] = '-58.00dBm'\n sheet_out['C35'] = '298300Kbps'\n sheet_out['C36'] = '-'\n sheet_out['D34'] = list_lte_spd[24] + 'dBm'\n sheet_out['D35'] = list_lte_spd[25] + 'Kbps'\n sheet_out['D36'] = list_lte_spd[26] + '%'\n # sheet_out['E34'] = self.check_num(abs(round(abs(float(list_lte_spd[24])) - 58.00, 2))) + 'dBm'\n # sheet_out['E35'] = self.check_num(abs(round(abs(float(list_lte_spd[25])) - 298300, 2))) + 'Kbps'\n sheet_out['E34'] = self.cal_comparison(58.00, list_lte_spd[24]) + 'dBm'\n sheet_out['E35'] = self.cal_comparison(298300.00, list_lte_spd[25]) + 'Kbps'\n sheet_out['E36'] = '-'\n\n sheet_out.merge_cells('A37:A39')\n sheet_out['A37'] = '4CA : B7(20M)+B3+B5+B1(MCS28)'\n sheet_out['B37'] = 'RSSI'\n sheet_out['B38'] = '속도(Absolute)'\n sheet_out['B39'] = 'BLER'\n sheet_out['C37'] = '-57.00dBm'\n sheet_out['C38'] = '386000Kbps'\n sheet_out['C39'] = '-'\n sheet_out['D37'] = list_lte_spd[27] + 'dBm'\n sheet_out['D38'] = list_lte_spd[28] + 'Kbps'\n sheet_out['D39'] = list_lte_spd[29] + '%'\n # sheet_out['E37'] = self.check_num(abs(round(abs(float(list_lte_spd[27])) - 57.00, 2))) + 'dBm'\n # sheet_out['E38'] = self.check_num(abs(round(abs(float(list_lte_spd[28])) - 386000, 2))) + 'Kbps'\n sheet_out['E37'] = self.cal_comparison(57.00, list_lte_spd[27]) + 'dBm'\n sheet_out['E38'] = self.cal_comparison(386000.00, list_lte_spd[28]) + 'Kbps'\n sheet_out['E39'] = '-'\n\n sheet_out.merge_cells('A40:A42')\n sheet_out['A40'] = '5CA : B7+B3+B5+B1+B7(MCS28)'\n sheet_out['B40'] = 'RSSI'\n sheet_out['B41'] = '속도(Absolute)'\n sheet_out['B42'] = 'BLER'\n sheet_out['C40'] = '-56.00dBm'\n sheet_out['C41'] = '444500Kbps'\n sheet_out['C42'] = '-'\n sheet_out['D40'] = list_lte_spd[30] + 'dBm'\n sheet_out['D41'] = list_lte_spd[31] + 'Kbps'\n sheet_out['D42'] = list_lte_spd[32] + '%'\n # sheet_out['E40'] = self.check_num(abs(round(abs(float(list_lte_spd[30])) - 56.00, 2))) + 'dBm'\n # sheet_out['E41'] = self.check_num(abs(round(abs(float(list_lte_spd[31])) - 444500, 2))) + 'Kbps'\n sheet_out['E40'] = self.cal_comparison(56.00, list_lte_spd[30]) + 'dBm'\n sheet_out['E41'] = self.cal_comparison(444500.00, list_lte_spd[31]) + 'Kbps'\n sheet_out['E42'] = '-'\n\n self.setPrintText('/s {}번 파일 \"속도\" 테이터 입력 완료 /e'.format(idx+1))\n\n # set temp data\n\n if self.opFlag:\n\n # all cell alignment adjust\n for mCell in sheet_out[\"A1:E42\"]:\n for cell in mCell:\n cell.alignment = self.general_alignment\n # top alignment adjust\n sheet_out['A3'].alignment = self.top_alignment\n sheet_out['A4'].alignment = self.top_alignment\n sheet_out['A22'].alignment = self.top_alignment\n sheet_out['A23'].alignment = self.top_alignment\n\n # all cell border adjust\n for mCell in sheet_out[\"A5:E20\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n # all cell border adjust\n for mCell in sheet_out[\"A24:E42\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n # all cell font adjust\n for mCell in sheet_out[\"A3:E42\"]:\n for cell in mCell:\n cell.font = self.index_font\n\n sheet_out['A1'].font = Font(name='맑은 고딕', size=22, bold=True, color='2B2B2B')\n\n # each column width adjust\n sheet_cell_list = ['A', 'B', 'C', 'D', 'E']\n sheet_width_list = [20.63, 14, 14, 17, 15]\n\n for i in range(len(sheet_cell_list)):\n sheet_out.column_dimensions[sheet_cell_list[i]].width = sheet_width_list[i]\n sheet_out.row_dimensions[1].height = 45\n\n # Set Pattern Fill\n for i in [6, 9, 12, 15, 18, 25, 28, 31, 34, 37, 40]:\n sheet_out['A' + str(i)].fill = self.gray_fill\n\n for col in ['A', 'B', 'D', 'E']:\n sheet_out[col + '5'].fill = self.brown_fill\n sheet_out[col + '24'].fill = self.brown_fill\n\n for i in range(6, 21):\n sheet_out['B'+str(i)].fill = self.apricot_fill\n sheet_out['C'+str(i)].fill = self.apricot_fill\n\n for i in range(25, 43):\n sheet_out['B'+str(i)].fill = self.apricot_fill\n sheet_out['C'+str(i)].fill = self.apricot_fill\n\n self.currentRow = self.currentRow + 1\n self.setPrintText('/s {}번 파일 \"속도\" 시트 스타일 적용 완료 /e'.format(idx+1))\n # save file\n wb_output.save(self.list_out_files[idx])\n except:\n self.setPrintText('/s Error: {}. {}, line: {}'.format(sys.exc_info()[0], sys.exc_info()[1], sys.exc_info()[2].tb_lineno)+' /e')\n self.end_count = \"y\"\n self.end_flag.emit()\n\n # Call Setup Tab\n def call_generate_data(self):\n\n try:\n for idx, item in enumerate(self.list_files):\n\n wb_input = openpyxl.load_workbook(item, data_only=True)\n wb_output = openpyxl.load_workbook(self.list_out_files[idx])\n call_val = ''\n\n # get data from wb_input\n sheet_in = wb_input['Call Test']\n\n call_val = self.check_num(sheet_in['D8'].value)\n\n #option setting wb.output\n sheet_out = wb_output['Call Setup Test']\n # sheet row 2 handle\n sheet_out.merge_cells('A1:C1')\n sheet_out['A1'] = 'Call Setup Test 결과'\n\n # 3~4 row\n sheet_out['A2'] = ' - WCDMA Call Setup Test'\n sheet_out['A3'] = '구분'\n sheet_out['B3'] = '기준'\n sheet_out['C3'] = '측정결과'\n sheet_out['D3'] = '비교'\n sheet_out['A4'] = 'Band 1'\n sheet_out['B4'] = ' -104.5dBm 이하'\n sheet_out['C4'] = call_val\n sheet_out['D4'] = '-'\n\n self.setPrintText('/s {}번 파일 \"Call Setuo Test\" 테이터 입력 완료 /e'.format(idx+1))\n\n # set temp data\n\n if self.opFlag:\n\n # all cell alignment adjust\n for mCell in sheet_out[\"A1:D4\"]:\n for cell in mCell:\n cell.alignment = self.general_alignment\n # top alignment adjust\n sheet_out['A2'].alignment = self.top_alignment\n\n # all cell border adjust\n for mCell in sheet_out[\"A3:D4\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n # all cell font adjust\n for mCell in sheet_out[\"A2:D4\"]:\n for cell in mCell:\n cell.font = self.index_font\n\n sheet_out['A1'].font = Font(name='맑은 고딕', size=22, bold=True, color='2B2B2B')\n\n # each column width adjust\n sheet_cell_list = ['A', 'B', 'C', 'D']\n sheet_width_list = [25, 15.88, 17, 15]\n\n for i in range(len(sheet_cell_list)):\n sheet_out.column_dimensions[sheet_cell_list[i]].width = sheet_width_list[i]\n sheet_out.row_dimensions[1].height = 45\n\n # Set Pattern Fill\n sheet_out['A4'].fill = self.gray_fill\n\n for col in ['A', 'B', 'C', 'D']:\n sheet_out[col + '3'].fill = self.brown_fill\n\n sheet_out['B4'].fill = self.apricot_fill\n\n self.currentRow = self.currentRow + 1\n self.setPrintText('/s {}번 파일 \"Call Setup Test\" 시트 스타일 적용 완료 /e'.format(idx+1))\n # save file\n wb_output.save(self.list_out_files[idx])\n except:\n self.setPrintText('/s Error: {}. {}, line: {}'.format(sys.exc_info()[0], sys.exc_info()[1], sys.exc_info()[2].tb_lineno)+' /e')\n self.end_count = \"y\"\n self.end_flag.emit()\n\n # 주파수동조 Tab\n def fre_generate_data(self):\n\n try:\n for idx, item in enumerate(self.list_files):\n\n wb_input = openpyxl.load_workbook(item, data_only=True)\n wb_output = openpyxl.load_workbook(self.list_out_files[idx])\n list_c1 = []\n list_c2 = []\n list_c3 = []\n # get data from wb_input\n sheet_in = wb_input['주파수동조']\n\n for i in ['C', 'D', 'E', 'F']:\n list_c1.append(str(sheet_in[i + '5'].value))\n list_c1.append(str(sheet_in[i + '6'].value))\n list_c1.append(str(sheet_in[i + '7'].value))\n\n for i in ['C', 'D']:\n list_c2.append(str(sheet_in[i + '11'].value))\n list_c2.append(str(sheet_in[i + '12'].value))\n list_c2.append(str(sheet_in[i + '13'].value))\n\n for i in ['C', 'D', 'E', 'F']:\n list_c3.append(str(sheet_in[i + '17'].value))\n list_c3.append(str(sheet_in[i + '18'].value))\n list_c3.append(str(sheet_in[i + '19'].value))\n\n # option setting wb.output\n sheet_out = wb_output['주파수동조']\n\n # sheet row 2 handle\n sheet_out.merge_cells('A1:D1')\n sheet_out['A1'] = '주파수동조 결과'\n\n # 3~8 row\n sheet_out['A3'] = '▣ LTE'\n sheet_out.merge_cells('A4:B4')\n sheet_out['A4'] = '지원 Band 및 정보'\n sheet_out['C4'] = '측정결과'\n sheet_out['D4'] = '비고'\n i = 0\n j = 0\n while i < len(list_c1):\n\n sheet_out['A' + str(5 + j)] = list_c1[i]\n sheet_out['B' + str(5 + j)] = list_c1[i+1]\n sheet_out['C' + str(5 + j)] = list_c1[i+2]\n sheet_out['D' + str(5 + j)] = ''\n i = i + 3\n j = j + 1\n\n # 10~13 row\n sheet_out['A10'] = '▣ WCDMA'\n sheet_out.merge_cells('A11:B11')\n sheet_out['A11'] = '지원 Band 및 정보'\n sheet_out['C11'] = '측정결과'\n sheet_out['D11'] = '비고'\n i = 0\n j = 0\n while i < len(list_c2):\n sheet_out['A' + str(12 + j)] = list_c2[i]\n sheet_out['B' + str(12 + j)] = list_c2[i + 1]\n sheet_out['C' + str(12 + j)] = list_c2[i + 2]\n sheet_out['D' + str(12 + j)] = ''\n i = i + 3\n j = j + 1\n\n # 15~20 row\n sheet_out['A15'] = '▣ GMS'\n sheet_out.merge_cells('A16:B16')\n sheet_out['A16'] = '지원 Band 및 정보'\n sheet_out['C16'] = '측정결과'\n sheet_out['D16'] = '비고'\n i = 0\n j = 0\n while i < len(list_c3):\n sheet_out['A' + str(17 + j)] = list_c3[i]\n sheet_out['B' + str(17 + j)] = list_c3[i + 1]\n sheet_out['C' + str(17 + j)] = list_c3[i + 2]\n sheet_out['D' + str(17 + j)] = ''\n i = i + 3\n j = j + 1\n\n self.setPrintText('/s {}번 파일 \"주파수동조\" 테이터 입력 완료 /e'.format(idx+1))\n\n # set temp data\n if self.opFlag:\n\n # all cell alignment adjust\n for mCell in sheet_out[\"A1:D20\"]:\n for cell in mCell:\n cell.alignment = self.general_alignment\n # top alignment adjust\n sheet_out['A3'].alignment = self.top_alignment\n sheet_out['A10'].alignment = self.top_alignment\n sheet_out['A15'].alignment = self.top_alignment\n\n # all cell border adjust\n for mCell in sheet_out[\"A4:D8\"]:\n for cell in mCell:\n cell.border = self.thin_border\n for mCell in sheet_out[\"A11:D13\"]:\n for cell in mCell:\n cell.border = self.thin_border\n for mCell in sheet_out[\"A16:D20\"]:\n for cell in mCell:\n cell.border = self.thin_border\n # all cell font adjust\n for mCell in sheet_out[\"A3:D20\"]:\n for cell in mCell:\n cell.font = self.index_font\n\n sheet_out['A1'].font = Font(name='맑은 고딕', size=22, bold=True, color='2B2B2B')\n\n # each column width adjust\n sheet_cell_list = ['A', 'B', 'C', 'D']\n sheet_width_list = [15.13, 24.5, 17, 15]\n\n for i in range(len(sheet_cell_list)):\n sheet_out.column_dimensions[sheet_cell_list[i]].width = sheet_width_list[i]\n sheet_out.row_dimensions[1].height = 45\n\n # Set Pattern Fill\n for i in [5, 6, 7, 8, 12, 13, 17, 18, 19, 20]:\n sheet_out['A' + str(i)].fill = self.gray_fill\n sheet_out['B' + str(i)].fill = self.gray_fill\n\n for i in [4, 11, 16]:\n sheet_out['A' + str(i)].fill = self.brown_fill\n sheet_out['C' + str(i)].fill = self.brown_fill\n sheet_out['D' + str(i)].fill = self.brown_fill\n\n self.currentRow = self.currentRow + 1\n self.setPrintText('/s {}번 파일 \"주파수동조\" 시트 스타일 적용 완료 /e'.format(idx+1))\n # save file\n wb_output.save(self.list_out_files[idx])\n except:\n self.setPrintText('/s Error: {}. {}, line: {}'.format(sys.exc_info()[0], sys.exc_info()[1], sys.exc_info()[2].tb_lineno)+' /e')\n self.end_count = \"y\"\n self.end_flag.emit()\n\n # Call Setup Tab\n def mos_generate_data(self):\n\n try:\n for idx, item in enumerate(self.list_files):\n\n wb_input = openpyxl.load_workbook(item, data_only=True)\n wb_output = openpyxl.load_workbook(self.list_out_files[idx])\n list_val = []\n\n # get data from wb_input\n sheet_in = wb_input['MOS']\n list_val.append(self.check_num(sheet_in['C6'].value))\n list_val.append(self.check_num(sheet_in['D6'].value))\n list_val.append(self.check_num(sheet_in['E6'].value))\n list_val.append(self.check_num(sheet_in['F6'].value))\n\n #option setting wb.output\n sheet_out = wb_output['MOS']\n # sheet row 1 handle\n sheet_out.merge_cells('A1:D1')\n sheet_out['A1'] = 'MOS 결과'\n\n # sheet row 2 handle\n sheet_out['A2'] = '- MOS 결과'\n sheet_out['A3'] = '▣ POLQA_48K'\n\n # 4~6 row\n sheet_out['A4'] = '구분'\n sheet_out['B4'] = '기준'\n sheet_out['C4'] = '측정결과'\n sheet_out['D4'] = '비교'\n sheet_out['A5'] = 'Downlink MOS'\n sheet_out['B5'] = '3.5 이상'\n sheet_out['C5'] = list_val[0]\n # sheet_out['D5'] = self.check_num(abs(round(abs(float(list_val[0])) - 3.5, 2)))\n sheet_out['D5'] = self.cal_comparison(3.5, list_val[0])\n sheet_out['A6'] = 'Uplink MOS'\n sheet_out['B6'] = '3.5 이상'\n sheet_out['C6'] = list_val[1]\n # sheet_out['D6'] = self.check_num(abs(round(abs(float(list_val[1])) - 3.5, 2)))\n sheet_out['D6'] = self.cal_comparison(3.5, list_val[1])\n\n # sheet row 8 handle\n sheet_out['A8'] = '▣ POLQA_8K'\n\n # 9~11 row\n sheet_out['A9'] = '구분'\n sheet_out['B9'] = '기준'\n sheet_out['C9'] = '측정결과'\n sheet_out['A10'] = 'Downlink MOS'\n sheet_out['B10'] = '3.0 이상'\n sheet_out['C10'] = list_val[2]\n # sheet_out['D10'] = self.check_num(abs(round(abs(float(list_val[2])) - 3.0, 2)))\n sheet_out['D10'] = self.cal_comparison(3.0, list_val[2])\n sheet_out['A11'] = 'Uplink MOS'\n sheet_out['B11'] = '3.0 이상'\n sheet_out['C11'] = list_val[3]\n # sheet_out['D11'] = self.check_num(abs(round(abs(float(list_val[3])) - 3.0, 2)))\n sheet_out['D11'] = self.cal_comparison(3.0, list_val[2])\n\n self.setPrintText('/s {}번 파일 \"MOS\" 테이터 입력 완료 /e'.format(idx+1))\n\n # set temp data\n\n if self.opFlag:\n\n # all cell alignment adjust\n for mCell in sheet_out[\"A1:D11\"]:\n for cell in mCell:\n cell.alignment = self.general_alignment\n # top alignment adjust\n sheet_out['A2'].alignment = self.top_alignment\n sheet_out['A3'].alignment = self.top_alignment\n sheet_out['A8'].alignment = self.top_alignment\n\n # all cell border adjust\n for mCell in sheet_out[\"A4:D6\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n for mCell in sheet_out[\"A9:D11\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n # all cell font adjust\n for mCell in sheet_out[\"A2:D11\"]:\n for cell in mCell:\n cell.font = self.index_font\n\n sheet_out['A1'].font = Font(name='맑은 고딕', size=22, bold=True, color='2B2B2B')\n\n # each column width adjust\n sheet_cell_list = ['A', 'B', 'C', 'D']\n sheet_width_list = [25, 15.88, 17, 13.13]\n\n for i in range(len(sheet_cell_list)):\n sheet_out.column_dimensions[sheet_cell_list[i]].width = sheet_width_list[i]\n sheet_out.row_dimensions[1].height = 45\n\n # Set Pattern Fill\n for i in [4, 9]:\n sheet_out['A' + str(i)].fill = self.brown_fill\n sheet_out['B' + str(i)].fill = self.brown_fill\n sheet_out['C' + str(i)].fill = self.brown_fill\n sheet_out['D' + str(i)].fill = self.brown_fill\n\n for i in [5, 6, 10, 11]:\n sheet_out['A' + str(i)].fill = self.gray_fill\n sheet_out['B' + str(i)].fill = self.apricot_fill\n\n self.currentRow = self.currentRow + 1\n self.setPrintText('/s {}번 파일 \"MOS\" 시트 스타일 적용 완료 /e'.format(idx+1))\n # save file\n wb_output.save(self.list_out_files[idx])\n except:\n self.setPrintText('/s Error: {}. {}, line: {}'.format(sys.exc_info()[0], sys.exc_info()[1], sys.exc_info()[2].tb_lineno)+' /e')\n self.end_count = \"y\"\n self.end_flag.emit()\n\n # DOU Tab\n def dou_generate_data(self):\n\n try:\n for idx, item in enumerate(self.list_files):\n\n list_input = []\n wb_input = openpyxl.load_workbook(item, data_only=True)\n wb_output = openpyxl.load_workbook(self.list_out_files[idx])\n col_sum = list(range(4, 16))\n col_a = [1, 2, 4, 7, 13, 16, 17]\n col_b = [2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]\n col_c = [2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]\n col_d = [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]\n col_e = [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]\n i_sum = 0.0\n r_sum = 0.0\n t_sum = 0.0\n\n # get data from wb_input\n sheet_in = wb_input['배터리소모전류(DOU)']\n temp_data = []\n for i in col_a:\n if i == 1:\n temp_data.append(str(sheet_in['A' + str(i)].value))\n else:\n temp_data.append(str(sheet_in['A' + str(i + 1)].value))\n list_input.append(temp_data)\n\n temp_data = []\n for i in col_b:\n temp_data.append(str(sheet_in['B' + str(i + 1)].value))\n list_input.append(temp_data)\n\n temp_data = []\n for i in col_c:\n temp_data.append(str(sheet_in['C' + str(i + 1)].value))\n if i in col_sum:\n if self.isNumber(sheet_in['C' + str(i + 1)].value):\n t_sum = t_sum + float(sheet_in['C' + str(i + 1)].value)\n list_input.append(temp_data)\n\n temp_data = []\n for i in col_d:\n if i in col_sum:\n if self.isNumber(sheet_in['D' + str(i + 1)].value):\n i_sum = i_sum + float(sheet_in['D' + str(i + 1)].value)\n temp_data.append(round(float(sheet_in['D' + str(i + 1)].value), 1))\n else:\n temp_data.append(self.check_empty(sheet_in['D' + str(i + 1)].value))\n else:\n temp_data.append(self.check_empty(sheet_in['D' + str(i + 1)].value))\n list_input.append(temp_data)\n\n temp_data = []\n for i in col_e:\n if i in col_sum:\n if self.isNumber(sheet_in['E' + str(i + 1)].value):\n r_sum = r_sum + float(sheet_in['E' + str(i + 1)].value)\n temp_data.append(round(float(sheet_in['E' + str(i + 1)].value), 1))\n else:\n temp_data.append(self.check_empty(sheet_in['E' + str(i + 1)].value))\n else:\n temp_data.append(self.check_empty(sheet_in['E' + str(i + 1)].value))\n list_input.append(temp_data)\n\n # input the data on output sheet\n sheet_out = wb_output['배터리소모전류(DOU)']\n\n for idx_2, item2 in enumerate(list_input):\n\n if idx_2 == 0:\n for i in range(len(item2)):\n sheet_out['A'+str(col_a[i])] = item2[i]\n elif idx_2 == 1:\n for i in range(len(item2)):\n sheet_out['B'+str(col_b[i])] = item2[i]\n elif idx_2 == 2:\n for i in range(len(item2)):\n sheet_out['C'+str(col_c[i])] = item2[i]\n elif idx_2 == 3:\n for i in range(len(item2)):\n sheet_out['D'+str(col_d[i])] = item2[i]\n else:\n for i in range(len(item2)):\n sheet_out['E'+str(col_e[i])] = item2[i]\n\n # fill rest values\n sheet_out.merge_cells('A1:E1')\n sheet_out.merge_cells('A2:A3')\n sheet_out.merge_cells('B2:B3')\n sheet_out.merge_cells('C2:C3')\n sheet_out.merge_cells('D2:E2')\n sheet_out.merge_cells('A4:A6')\n sheet_out.merge_cells('A7:A12')\n sheet_out.merge_cells('A13:A15')\n sheet_out.merge_cells('A16:B16')\n sheet_out.merge_cells('A17:C17')\n sheet_out.merge_cells('D17:E17')\n\n sheet_out['A16'] = '소계'\n if str(t_sum) == '0' or str(t_sum) == '0.0':\n sheet_out['C16'] = ''\n else:\n sheet_out['C16'] = round(t_sum, 1)\n\n if str(r_sum) == '0' or str(r_sum) == '0.0':\n sheet_out['E16'] = ''\n else:\n sheet_out['E16'] = round(r_sum, 1)\n\n if str(i_sum) == '0' or str(i_sum) == '0.0':\n sheet_out['D16'] = ''\n else:\n sheet_out['D16'] = round(i_sum, 1)\n\n sheet_out['A17'] = '사용시간'\n sheet_out['D17'] = str(round(self.battery_spec/r_sum, 2))+\"일\"\n\n self.setPrintText('/s {}번 파일 \"베터리소모전류(DOU)\" 테이터 입력 완료 /e'.format(idx+1))\n\n if self.opFlag:\n\n # all cell aligment adjust\n for mCell in sheet_out[\"A1:E17\"]:\n for cell in mCell:\n cell.alignment = self.general_alignment\n\n # all cell border adjust\n for mCell in sheet_out[\"A2:E17\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n # all cell font adjust\n for mCell in sheet_out[\"A2:E17\"]:\n for cell in mCell:\n cell.font = self.index_font\n\n sheet_out['A1'].font = Font(name='맑은 고딕', size=22, bold=True, color='2B2B2B')\n\n # each coloum width adjust\n sheet_cell_list = ['A', 'B', 'C', 'D', 'E']\n sheet_width_list = [10.25, 27.38, 15.5, 17, 17]\n\n for i in range(len(sheet_cell_list)):\n sheet_out.column_dimensions[sheet_cell_list[i]].width = sheet_width_list[i]\n sheet_out.row_dimensions[1].height = 45\n\n # Set Pattern Fill\n sheet_out['A2'].fill = self.brown_fill\n sheet_out['B2'].fill = self.brown_fill\n sheet_out['C2'].fill = self.brown_fill\n sheet_out['D2'].fill = self.brown_fill\n sheet_out['D3'].fill = self.brown_fill\n sheet_out['E3'].fill = self.brown_fill\n sheet_out['A16'].fill = self.light_brown_fill\n sheet_out['C16'].fill = self.light_brown_fill\n sheet_out['D16'].fill = self.light_brown_fill\n sheet_out['E16'].fill = self.light_brown_fill\n sheet_out['A17'].fill = self.brown_fill\n sheet_out['D17'].fill = self.brown_fill\n\n for i in range(4, 16):\n sheet_out['A' + str(i)].fill = self.gray_fill\n sheet_out['B' + str(i)].fill = self.gray_fill\n sheet_out['C' + str(i)].fill = self.gray_fill\n\n self.currentRow = self.currentRow + 1\n self.setPrintText('/s {}번 파일 \"베터리소모전류(DOU)\" 시트 스타일 적용 완료 /e'.format(idx+1))\n # save file\n wb_output.save(self.list_out_files[idx])\n except:\n self.setPrintText('/s Error: {}. {}, line: {}'.format(sys.exc_info()[0], sys.exc_info()[1], sys.exc_info()[2].tb_lineno)+' /e')\n self.end_count = \"y\"\n self.end_flag.emit()\n\n # 베터리소모전류 Tab\n def bat_generate_data(self):\n\n try:\n for idx, item in enumerate(self.list_files):\n\n wb_input = openpyxl.load_workbook(item, data_only=True)\n wb_output = openpyxl.load_workbook(self.list_out_files[idx])\n col_out = ['Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z', 'AA', 'AB']\n\n # get data from wb_input\n sheet_in = wb_input['배터리소모전류']\n #option setting wb.output\n sheet_out = wb_output['배터리소모전류 세부데이터']\n\n # sheet row 1 handle\n sheet_out.merge_cells('A1:P1')\n sheet_out['A1'] = '베터리소모전류 결과'\n # sheet row 3~5 handle\n sheet_out['A3'] = '▣ 5G 측정내역'\n sheet_out.merge_cells('A4:A5')\n sheet_out['A4'] = '차수'\n sheet_out.merge_cells('B4:B5')\n sheet_out['B4'] = '시료번호'\n sheet_out.merge_cells('C4:C5')\n sheet_out['C4'] = '베터리용량'\n sheet_out.merge_cells('D4:D5')\n sheet_out['D4'] = '측정채널'\n sheet_out.merge_cells('E4:H4')\n sheet_out['E4'] = sheet_in['E8'].value\n sheet_out.merge_cells('I4:L4')\n sheet_out['I4'] = sheet_in['I8'].value\n sheet_out.merge_cells('M4:P4')\n sheet_out['M4'] = sheet_in['M8'].value\n\n sheet_out.merge_cells('E5:F5')\n sheet_out['E5'] = sheet_in['E9'].value\n sheet_out.merge_cells('G5:H5')\n sheet_out['G5'] = sheet_in['G9'].value\n sheet_out.merge_cells('I5:J5')\n sheet_out['I5'] = sheet_in['I9'].value\n sheet_out.merge_cells('K5:L5')\n sheet_out['K5'] = sheet_in['K9'].value\n sheet_out.merge_cells('M5:N5')\n sheet_out['M5'] = sheet_in['M9'].value\n sheet_out.merge_cells('O5:P5')\n sheet_out['O5'] = sheet_in['O9'].value\n\n # sheet row 6~7 handle\n sheet_out.merge_cells('A6:D7')\n sheet_out['A6'] = 'SKT 기준'\n for col in ['E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P']:\n sheet_out[col + '6'] = sheet_in[col+'10'].value\n sheet_out[col + '7'] = sheet_in[col+'11'].value\n\n # sheet row 8~9 handle\n for col in ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P']:\n\n if col in ['A', 'B', 'C', 'D']:\n sheet_out[col + '8'] = sheet_in[col + '12'].value\n sheet_out[col + '9'] = sheet_in[col + '13'].value\n else:\n # row 8\n if self.isNumber(sheet_in[col + '12'].value):\n sheet_out[col + '8'] = self.check_num(round(float(sheet_in[col + '12'].value), 2))\n else:\n sheet_out[col + '8'] = self.check_empty(sheet_in[col + '12'].value)\n\n # row 9\n if self.isNumber(sheet_in[col + '13'].value):\n sheet_out[col + '9'] = self.check_num(round(float(sheet_in[col + '13'].value), 2))\n else:\n sheet_out[col + '9'] = self.check_empty(sheet_in[col + '13'].value)\n\n # sheet row 12~15 handle\n sheet_out.merge_cells('A10:A11')\n sheet_out['A10'] = '차수'\n sheet_out.merge_cells('B10:B11')\n sheet_out['B10'] = '시료번호'\n sheet_out.merge_cells('C10:C11')\n sheet_out['C10'] = '베터리용량'\n sheet_out.merge_cells('D10:D11')\n sheet_out['D10'] = '측정채널'\n\n sheet_out.merge_cells('E10:F10')\n sheet_out['E10'] = sheet_in['Q8'].value\n sheet_out.merge_cells('G10:H10')\n sheet_out['G10'] = sheet_in['S8'].value\n sheet_out.merge_cells('I10:J10')\n sheet_out['I10'] = sheet_in['U8'].value\n sheet_out.merge_cells('K10:L10')\n sheet_out['K10'] = sheet_in['W8'].value\n sheet_out.merge_cells('M10:N10')\n sheet_out['M10'] = sheet_in['Y8'].value\n sheet_out.merge_cells('O10:P10')\n sheet_out['O10'] = sheet_in['AA8'].value\n\n sheet_out.merge_cells('E11:F11')\n sheet_out['E11'] = sheet_in['Q9'].value\n sheet_out.merge_cells('G11:H11')\n sheet_out['G11'] = sheet_in['S9'].value\n sheet_out.merge_cells('I11:J11')\n sheet_out['I11'] = sheet_in['U9'].value\n sheet_out.merge_cells('K11:L11')\n sheet_out['K11'] = sheet_in['W9'].value\n sheet_out.merge_cells('M11:N11')\n sheet_out['M11'] = sheet_in['Y9'].value\n sheet_out.merge_cells('O11:P11')\n sheet_out['O11'] = sheet_in['AA9'].value\n\n # sheet row 12~13 handle\n sheet_out.merge_cells('A12:D13')\n sheet_out['A12'] = 'SKT 기준'\n\n for i, col in enumerate(['E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P']):\n sheet_out[col + '12'] = sheet_in[col_out[i] + '10'].value\n sheet_out[col + '13'] = sheet_in[col_out[i] + '11'].value\n\n # sheet row 14~15 handle\n for i, col in enumerate(['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P']):\n\n if col in ['A', 'B', 'C', 'D']:\n sheet_out[col + '14'] = sheet_in[col + '12'].value\n sheet_out[col + '15'] = sheet_in[col + '13'].value\n else:\n # row 14\n if self.isNumber(sheet_in[col_out[i-4] + '12'].value):\n sheet_out[col + '14'] = self.check_num(round(float(sheet_in[col_out[i-4] + '12'].value), 2))\n else:\n sheet_out[col + '14'] = self.check_empty(sheet_in[col_out[i-4] + '12'].value)\n\n # row 15\n if self.isNumber(sheet_in[col_out[i-4] + '13'].value):\n sheet_out[col + '15'] = self.check_num(round(float(sheet_in[col_out[i-4] + '13'].value), 2))\n else:\n sheet_out[col + '15'] = self.check_empty(sheet_in[col_out[i-4] + '13'].value)\n\n # sheet row 17~19 handle\n sheet_out['A17'] = '▣ LTE 측정내역'\n sheet_out.merge_cells('A18:A19')\n sheet_out['A18'] = '차수'\n sheet_out.merge_cells('B18:B19')\n sheet_out['B18'] = '시료번호'\n sheet_out.merge_cells('C18:C19')\n sheet_out['C18'] = '베터리용량'\n sheet_out.merge_cells('D18:D19')\n sheet_out['D18'] = '측정채널'\n sheet_out.merge_cells('E18:H18')\n sheet_out['E18'] = sheet_in['E16'].value\n sheet_out.merge_cells('I18:L18')\n sheet_out['I18'] = sheet_in['I16'].value\n sheet_out.merge_cells('M18:P18')\n sheet_out['M18'] = sheet_in['M16'].value\n\n sheet_out.merge_cells('E19:F19')\n sheet_out['E19'] = sheet_in['E17'].value\n sheet_out.merge_cells('G19:H19')\n sheet_out['G19'] = sheet_in['G17'].value\n sheet_out.merge_cells('I19:J19')\n sheet_out['I19'] = sheet_in['I17'].value\n sheet_out.merge_cells('K19:L19')\n sheet_out['K19'] = sheet_in['K17'].value\n sheet_out.merge_cells('M19:N19')\n sheet_out['M19'] = sheet_in['M17'].value\n sheet_out.merge_cells('O19:P19')\n sheet_out['O19'] = sheet_in['O17'].value\n\n # sheet row 20~21 handle\n sheet_out.merge_cells('A20:D21')\n sheet_out['A20'] = 'SKT 기준'\n for col in ['E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P']:\n sheet_out[col + '20'] = sheet_in[col+'18'].value\n sheet_out[col + '21'] = sheet_in[col+'19'].value\n\n # sheet row 22~23 handle\n for col in ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P']:\n\n if col in ['A', 'B', 'C', 'D']:\n sheet_out[col + '22'] = sheet_in[col + '12'].value\n sheet_out[col + '23'] = sheet_in[col + '13'].value\n else:\n # row 22\n if self.isNumber(sheet_in[col + '20'].value):\n sheet_out[col + '22'] = self.check_num(round(float(sheet_in[col + '20'].value), 2))\n else:\n sheet_out[col + '22'] = self.check_empty(sheet_in[col + '20'].value)\n\n # row 23\n if self.isNumber(sheet_in[col + '21'].value):\n sheet_out[col + '23'] = self.check_num(round(float(sheet_in[col + '21'].value), 2))\n else:\n sheet_out[col + '23'] = self.check_empty(sheet_in[col + '21'].value)\n\n # sheet row 24~25 handle\n sheet_out.merge_cells('A24:A25')\n sheet_out['A24'] = '차수'\n sheet_out.merge_cells('B24:B25')\n sheet_out['B24'] = '시료번호'\n sheet_out.merge_cells('C24:C25')\n sheet_out['C24'] = '베터리용량'\n sheet_out.merge_cells('D24:D25')\n sheet_out['D24'] = '측정채널'\n\n sheet_out.merge_cells('E24:F24')\n sheet_out['E24'] = sheet_in['Q16'].value\n sheet_out.merge_cells('G24:H24')\n sheet_out['G24'] = sheet_in['S16'].value\n sheet_out.merge_cells('I24:J24')\n sheet_out['I24'] = sheet_in['U16'].value\n sheet_out.merge_cells('K24:L24')\n sheet_out['K24'] = sheet_in['W16'].value\n\n sheet_out.merge_cells('E25:F25')\n sheet_out['E25'] = sheet_in['Q17'].value\n sheet_out.merge_cells('G25:H25')\n sheet_out['G25'] = sheet_in['S17'].value\n sheet_out.merge_cells('I25:J25')\n sheet_out['I25'] = sheet_in['U17'].value\n sheet_out.merge_cells('K25:L25')\n sheet_out['K25'] = sheet_in['W17'].value\n\n # sheet row 26~27 handle\n sheet_out.merge_cells('A26:D27')\n sheet_out['A26'] = 'SKT 기준'\n\n for i, col in enumerate(['E', 'F', 'G', 'H', 'I', 'J', 'K', 'L']):\n sheet_out[col + '26'] = sheet_in[col_out[i] + '18'].value\n sheet_out[col + '27'] = sheet_in[col_out[i] + '19'].value\n\n # sheet row 28~29 handle\n for i, col in enumerate(['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L']):\n\n if col in ['A', 'B', 'C', 'D']:\n sheet_out[col + '28'] = sheet_in[col + '12'].value\n sheet_out[col + '29'] = sheet_in[col + '13'].value\n else:\n # row 28\n if self.isNumber(sheet_in[col_out[i-4] + '20'].value):\n sheet_out[col + '28'] = self.check_num(round(float(sheet_in[col_out[i-4] + '20'].value), 2))\n else:\n sheet_out[col + '28'] = self.check_empty(sheet_in[col_out[i-4] + '20'].value)\n # row 29\n if self.isNumber(sheet_in[col_out[i-4] + '21'].value):\n sheet_out[col + '29'] = self.check_num(round(float(sheet_in[col_out[i-4] + '21'].value), 2))\n else:\n sheet_out[col + '29'] = self.check_empty(sheet_in[col_out[i-4] + '21'].value)\n\n\n # sheet row 31~33 handle\n sheet_out['A31'] = '▣ WCDMA 측정내역'\n sheet_out.merge_cells('A32:A33')\n sheet_out['A32'] = '차수'\n sheet_out.merge_cells('B32:B33')\n sheet_out['B32'] = '시료번호'\n sheet_out.merge_cells('C32:C33')\n sheet_out['C32'] = '베터리용량'\n sheet_out.merge_cells('D32:D33')\n sheet_out['D32'] = '측정채널'\n\n sheet_out.merge_cells('E32:F32')\n sheet_out['E32'] = sheet_in['E24'].value\n sheet_out.merge_cells('G32:J32')\n sheet_out['G32'] = sheet_in['G24'].value\n sheet_out.merge_cells('K32:L32')\n sheet_out['K32'] = sheet_in['K24'].value\n\n sheet_out.merge_cells('E33:F33')\n sheet_out['E33'] = sheet_in['E25'].value\n sheet_out.merge_cells('G33:H33')\n sheet_out['G33'] = sheet_in['G25'].value\n sheet_out.merge_cells('I33:J33')\n sheet_out['I33'] = sheet_in['I25'].value\n sheet_out.merge_cells('K33:L33')\n sheet_out['K33'] = sheet_in['K25'].value\n\n # sheet row 34~35 handle\n sheet_out.merge_cells('A34:D35')\n sheet_out['A34'] = 'SKT 기준'\n for col in ['E', 'F', 'G', 'H', 'I', 'J', 'K', 'L']:\n sheet_out[col + '34'] = sheet_in[col+'26'].value\n sheet_out[col + '35'] = sheet_in[col+'27'].value\n\n # sheet row 36~37 handle\n for col in ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L']:\n\n if col in ['A', 'B', 'C', 'D']:\n sheet_out[col + '36'] = sheet_in[col + '12'].value\n sheet_out[col + '37'] = sheet_in[col + '13'].value\n else:\n # row 36\n if self.isNumber(sheet_in[col + '28'].value):\n sheet_out[col + '36'] = self.check_num(round(float(sheet_in[col + '28'].value), 2))\n else:\n sheet_out[col + '36'] = self.check_empty(sheet_in[col + '28'].value)\n # row 37\n if self.isNumber(sheet_in[col + '29'].value):\n sheet_out[col + '37'] = self.check_num(round(float(sheet_in[col + '29'].value), 2))\n else:\n sheet_out[col + '37'] = self.check_empty(sheet_in[col + '29'].value)\n\n # sheet row 39~41 handle\n sheet_out['A39'] = '▣ WiFi 측정내역'\n sheet_out.merge_cells('A40:A41')\n sheet_out['A40'] = '차수'\n sheet_out.merge_cells('B40:B41')\n sheet_out['B40'] = '시료번호'\n sheet_out.merge_cells('C40:C41')\n sheet_out['C40'] = '베터리용량'\n sheet_out.merge_cells('D40:D41')\n sheet_out['D40'] = '측정채널'\n\n sheet_out.merge_cells('E40:F40')\n sheet_out['E40'] = sheet_in['E32'].value\n sheet_out.merge_cells('G40:H40')\n sheet_out['G40'] = sheet_in['G32'].value\n sheet_out.merge_cells('I40:J40')\n sheet_out['I40'] = sheet_in['I32'].value\n sheet_out.merge_cells('K40:L40')\n sheet_out['K40'] = sheet_in['K32'].value\n sheet_out.merge_cells('M40:N40')\n sheet_out['M40'] = sheet_in['M32'].value\n\n sheet_out.merge_cells('E41:F41')\n sheet_out['E41'] = sheet_in['E33'].value\n sheet_out.merge_cells('G41:H41')\n sheet_out['G41'] = sheet_in['G33'].value\n sheet_out.merge_cells('I41:J41')\n sheet_out['I41'] = sheet_in['I33'].value\n sheet_out.merge_cells('K41:L41')\n sheet_out['K41'] = sheet_in['K33'].value\n sheet_out.merge_cells('M41:N41')\n sheet_out['M41'] = sheet_in['M33'].value\n\n # sheet row 42~43 handle\n sheet_out.merge_cells('A42:D43')\n sheet_out['A42'] = 'SKT 기준'\n for col in ['E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N']:\n sheet_out[col + '42'] = sheet_in[col+'34'].value\n sheet_out[col + '43'] = sheet_in[col+'35'].value\n\n # sheet row 44~45 handle\n for col in ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N']:\n\n if col in ['A', 'B', 'C', 'D']:\n sheet_out[col + '44'] = sheet_in[col + '12'].value\n sheet_out[col + '45'] = sheet_in[col + '13'].value\n else:\n # row 44\n if self.isNumber(sheet_in[col + '36'].value):\n sheet_out[col + '44'] = self.check_num(round(float(sheet_in[col + '36'].value), 2))\n else:\n sheet_out[col + '44'] = self.check_empty(sheet_in[col + '36'].value)\n # row 45\n if self.isNumber(sheet_in[col + '37'].value):\n sheet_out[col + '45'] = self.check_num(round(float(sheet_in[col + '37'].value), 2))\n else:\n sheet_out[col + '45'] = self.check_empty(sheet_in[col + '37'].value)\n\n # sheet row 47~49 handle\n sheet_out['A47'] = '▣ BlueTooth 측정내역'\n sheet_out.merge_cells('A48:A49')\n sheet_out['A48'] = '차수'\n sheet_out.merge_cells('B48:B49')\n sheet_out['B48'] = '시료번호'\n sheet_out.merge_cells('C48:C49')\n sheet_out['C48'] = '베터리용량'\n sheet_out.merge_cells('D48:D49')\n sheet_out['D48'] = '측정채널'\n sheet_out.merge_cells('E48:N48')\n sheet_out['E48'] = sheet_in['E40'].value\n\n sheet_out.merge_cells('E49:F49')\n sheet_out['E49'] = sheet_in['E41'].value\n sheet_out.merge_cells('G49:H49')\n sheet_out['G49'] = sheet_in['G41'].value\n sheet_out.merge_cells('I49:J49')\n sheet_out['I49'] = sheet_in['I41'].value\n sheet_out.merge_cells('K49:L49')\n sheet_out['K49'] = sheet_in['K41'].value\n sheet_out.merge_cells('M49:N49')\n sheet_out['M49'] = sheet_in['M41'].value\n\n # sheet row 50~51 handle\n sheet_out.merge_cells('A50:D51')\n sheet_out['A50'] = 'SKT 기준'\n\n for col in ['E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N']:\n sheet_out[col + '50'] = sheet_in[col+'42'].value\n sheet_out[col + '51'] = sheet_in[col+'43'].value\n\n for col in ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N']:\n\n # sheet row 52~53 handle\n if col in ['A', 'B', 'C', 'D']:\n sheet_out[col + '52'] = sheet_in[col + '12'].value\n sheet_out[col + '53'] = sheet_in[col + '13'].value\n else:\n # row 52\n if self.isNumber(sheet_in[col + '44'].value):\n sheet_out[col + '52'] = self.check_num(round(float(sheet_in[col + '44'].value), 2))\n else:\n sheet_out[col + '52'] = self.check_empty(sheet_in[col + '44'].value)\n # row 53\n if self.isNumber(sheet_in[col + '45'].value):\n sheet_out[col + '53'] = self.check_num(round(float(sheet_in[col + '45'].value), 2))\n else:\n sheet_out[col + '53'] = self.check_empty(sheet_in[col + '45'].value)\n\n self.setPrintText('/s {}번 파일 \"배터리소모전류 세부데이터\" 테이터 입력 완료 /e'.format(idx+1))\n\n # set temp data\n if self.opFlag:\n\n # all cell alignment adjust\n for mCell in sheet_out[\"A1:Z53\"]:\n for cell in mCell:\n cell.alignment = self.general_alignment\n # top alignment adjust\n sheet_out['A3'].alignment = self.top_alignment\n sheet_out['A17'].alignment = self.top_alignment\n sheet_out['A31'].alignment = self.top_alignment\n sheet_out['A39'].alignment = self.top_alignment\n sheet_out['A47'].alignment = self.top_alignment\n\n # all cell border adjust\n for mCell in sheet_out[\"A4:P15\"]:\n for cell in mCell:\n cell.border = self.thin_border\n for mCell in sheet_out[\"A18:P23\"]:\n for cell in mCell:\n cell.border = self.thin_border\n for mCell in sheet_out[\"A24:L29\"]:\n for cell in mCell:\n cell.border = self.thin_border\n for mCell in sheet_out[\"A32:L37\"]:\n for cell in mCell:\n cell.border = self.thin_border\n for mCell in sheet_out[\"A40:N45\"]:\n for cell in mCell:\n cell.border = self.thin_border\n for mCell in sheet_out[\"A48:N53\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n # all cell font adjust\n for mCell in sheet_out[\"A3:P53\"]:\n for cell in mCell:\n cell.font = self.index_font\n\n sheet_out['A1'].font = Font(name='맑은 고딕', size=22, bold=True, color='2B2B2B')\n\n # each column width adjust\n sheet_cell_list = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N',\n 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z']\n sheet_width_list = [29.88, 11.38, 11.38, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11,\n 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11]\n\n for i in range(len(sheet_cell_list)):\n sheet_out.column_dimensions[sheet_cell_list[i]].width = sheet_width_list[i]\n\n sheet_out.row_dimensions[1].height = 45\n\n # Set Pattern Fill\n for col in ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P']:\n\n sheet_out[col + '4'].fill = self.brown_fill\n sheet_out[col + '5'].fill = self.brown_fill\n sheet_out[col + '6'].fill = self.apricot_fill\n sheet_out[col + '7'].fill = self.apricot_fill\n sheet_out[col + '10'].fill = self.brown_fill\n sheet_out[col + '11'].fill = self.brown_fill\n sheet_out[col + '12'].fill = self.apricot_fill\n sheet_out[col + '13'].fill = self.apricot_fill\n sheet_out[col + '18'].fill = self.brown_fill\n sheet_out[col + '19'].fill = self.brown_fill\n sheet_out[col + '20'].fill = self.apricot_fill\n sheet_out[col + '21'].fill = self.apricot_fill\n\n for col in ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N']:\n\n sheet_out[col + '40'].fill = self.brown_fill\n sheet_out[col + '41'].fill = self.brown_fill\n sheet_out[col + '42'].fill = self.apricot_fill\n sheet_out[col + '43'].fill = self.apricot_fill\n sheet_out[col + '48'].fill = self.brown_fill\n sheet_out[col + '49'].fill = self.brown_fill\n sheet_out[col + '50'].fill = self.apricot_fill\n sheet_out[col + '51'].fill = self.apricot_fill\n\n for col in ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L']:\n\n sheet_out[col + '24'].fill = self.brown_fill\n sheet_out[col + '25'].fill = self.brown_fill\n sheet_out[col + '26'].fill = self.apricot_fill\n sheet_out[col + '27'].fill = self.apricot_fill\n sheet_out[col + '32'].fill = self.brown_fill\n sheet_out[col + '33'].fill = self.brown_fill\n sheet_out[col + '34'].fill = self.apricot_fill\n sheet_out[col + '35'].fill = self.apricot_fill\n\n for i in [8, 9, 14, 15, 22, 23, 28, 29, 36, 37, 44, 45, 52, 53]:\n\n sheet_out['A' + str(i)].fill = self.gray_fill\n sheet_out['B' + str(i)].fill = self.gray_fill\n sheet_out['C' + str(i)].fill = self.gray_fill\n sheet_out['D' + str(i)].fill = self.gray_fill\n\n self.currentRow = self.currentRow + 1\n self.setPrintText('/s {}번 파일 \"배터리소모전류 세부데이터\" 시트 스타일 적용 완료 /e'.format(idx+1))\n\n # save file\n wb_output.save(self.list_out_files[idx])\n except:\n self.setPrintText('/s Error: {}. {}, line: {}'.format(sys.exc_info()[0], sys.exc_info()[1], sys.exc_info()[2].tb_lineno)+' /e')\n self.end_count = \"y\"\n self.end_flag.emit()\n\n # 베터리소모전류(시간) Tab\n def time_generate_data(self):\n\n try:\n for idx, item in enumerate(self.list_out_files):\n\n wb_output = openpyxl.load_workbook(item, data_only=True)\n\n # get data from wb_input\n sheet_in = wb_output['배터리소모전류 세부데이터']\n #option setting wb.output\n sheet_out = wb_output['배터리소모전류(시간)']\n target = sheet_in['A8'].value\n ref = sheet_in['A9'].value\n\n # sheet row 1 handle\n sheet_out.merge_cells('A1:H1')\n sheet_out['A1'] = '배터리소모전류 결과 (시간)'\n # sheet row 3~5 handle\n sheet_out['A3'] = '▣ 5G '\n sheet_out.merge_cells('A4:A5')\n sheet_out['A4'] = '구분'\n sheet_out.merge_cells('B4:C4')\n sheet_out['B4'] = sheet_in['E4'].value\n sheet_out.merge_cells('D4:E4')\n sheet_out['D4'] = sheet_in['I4'].value\n sheet_out.merge_cells('F4:H4')\n sheet_out['F4'] = sheet_in['M4'].value\n\n sheet_out['B5'] = sheet_in['E5'].value\n sheet_out['C5'] = sheet_in['G5'].value\n sheet_out['D5'] = sheet_in['I5'].value\n sheet_out['E5'] = sheet_in['K5'].value\n sheet_out['F5'] = sheet_in['M5'].value\n sheet_out['G5'] = sheet_in['O5'].value\n sheet_out['H5'] = sheet_in['G11'].value\n\n # sheet row 6 handle\n sheet_out['A6'] = 'SKT 기준'\n sheet_out['B6'] = sheet_in['F6'].value\n sheet_out['C6'] = sheet_in['H6'].value\n sheet_out['D6'] = sheet_in['J6'].value\n sheet_out['E6'] = sheet_in['L6'].value\n sheet_out['F6'] = sheet_in['N6'].value\n sheet_out['G6'] = sheet_in['P6'].value\n sheet_out['H6'] = sheet_in['H12'].value\n\n # sheet row 7~8\n sheet_out['A7'] = target\n sheet_out['B7'] = sheet_in['F8'].value\n sheet_out['C7'] = sheet_in['H8'].value\n sheet_out['D7'] = sheet_in['J8'].value\n sheet_out['E7'] = sheet_in['L8'].value\n sheet_out['F7'] = sheet_in['N8'].value\n sheet_out['G7'] = sheet_in['P8'].value\n sheet_out['H7'] = sheet_in['H14'].value\n sheet_out['A8'] = ref\n sheet_out['B8'] = sheet_in['F9'].value\n sheet_out['C8'] = sheet_in['H9'].value\n sheet_out['D8'] = sheet_in['J9'].value\n sheet_out['E8'] = sheet_in['L9'].value\n sheet_out['F8'] = sheet_in['N9'].value\n sheet_out['G8'] = sheet_in['P9'].value\n sheet_out['H8'] = sheet_in['H15'].value\n\n # sheet row 9~10\n sheet_out.merge_cells('A9:A10')\n sheet_out['A9'] = '구분'\n sheet_out['B9'] = sheet_in['I10'].value\n sheet_out['C9'] = sheet_in['K10'].value\n sheet_out['D9'] = sheet_in['M10'].value\n sheet_out['E9'] = '동영상'\n sheet_out['F9'] = sheet_in['E10'].value\n\n sheet_out['B10'] = sheet_in['I11'].value\n sheet_out['C10'] = sheet_in['K11'].value\n sheet_out['D10'] = sheet_in['M11'].value\n sheet_out['E10'] = '녹화'\n sheet_out['F10'] = sheet_in['E11'].value\n\n # sheet row 11 handle\n sheet_out['A11'] = 'SKT 기준'\n sheet_out['B11'] = sheet_in['J12'].value\n sheet_out['C11'] = sheet_in['L12'].value\n sheet_out['D11'] = sheet_in['N12'].value\n sheet_out['E11'] = sheet_in['P12'].value\n sheet_out['F11'] = sheet_in['F12'].value\n\n # sheet row 12~13\n sheet_out['A12'] = target\n sheet_out['B12'] = sheet_in['J14'].value\n sheet_out['C12'] = sheet_in['L14'].value\n sheet_out['D12'] = sheet_in['N14'].value\n sheet_out['E12'] = sheet_in['P14'].value\n sheet_out['F12'] = sheet_in['F14'].value\n sheet_out['A13'] = ref\n sheet_out['B13'] = sheet_in['F15'].value\n sheet_out['C13'] = sheet_in['H15'].value\n sheet_out['D13'] = sheet_in['J15'].value\n sheet_out['E13'] = sheet_in['L15'].value\n sheet_out['F13'] = sheet_in['N15'].value\n\n # sheet row 15~17 handle\n sheet_out['A15'] = '▣ LTE'\n sheet_out.merge_cells('A16:A17')\n sheet_out['A16'] = '구분'\n sheet_out.merge_cells('B16:C16')\n sheet_out['B16'] = sheet_in['E18'].value\n sheet_out.merge_cells('D16:E16')\n sheet_out['D16'] = sheet_in['I18'].value\n sheet_out.merge_cells('F16:H16')\n sheet_out['F16'] = sheet_in['M18'].value\n\n sheet_out['B17'] = sheet_in['E19'].value\n sheet_out['C17'] = sheet_in['G19'].value\n sheet_out['D17'] = sheet_in['I19'].value\n sheet_out['E17'] = sheet_in['K19'].value\n sheet_out['F17'] = sheet_in['M19'].value\n sheet_out['G17'] = sheet_in['O19'].value\n sheet_out['H17'] = sheet_in['E25'].value\n\n # sheet row 18 handle\n sheet_out['A18'] = 'SKT 기준'\n sheet_out['B18'] = sheet_in['F20'].value\n sheet_out['C18'] = sheet_in['H20'].value\n sheet_out['D18'] = sheet_in['J20'].value\n sheet_out['E18'] = sheet_in['L20'].value\n sheet_out['F18'] = sheet_in['N20'].value\n sheet_out['G18'] = sheet_in['P20'].value\n sheet_out['H18'] = sheet_in['F26'].value\n\n # sheet row 19~20\n sheet_out['A19'] = target\n sheet_out['B19'] = sheet_in['F22'].value\n sheet_out['C19'] = sheet_in['H22'].value\n sheet_out['D19'] = sheet_in['J22'].value\n sheet_out['E19'] = sheet_in['L22'].value\n sheet_out['F19'] = sheet_in['N22'].value\n sheet_out['G19'] = sheet_in['P22'].value\n sheet_out['H19'] = sheet_in['F28'].value\n sheet_out['A20'] = ref\n sheet_out['B20'] = sheet_in['F23'].value\n sheet_out['C20'] = sheet_in['H23'].value\n sheet_out['D20'] = sheet_in['J23'].value\n sheet_out['E20'] = sheet_in['L23'].value\n sheet_out['F20'] = sheet_in['N23'].value\n sheet_out['G20'] = sheet_in['P23'].value\n sheet_out['H20'] = sheet_in['F29'].value\n\n # sheet row 21~22\n sheet_out.merge_cells('A21:A22')\n sheet_out['A21'] = '구분'\n sheet_out['B21'] = sheet_in['G24'].value\n sheet_out['C21'] = sheet_in['I24'].value\n sheet_out['D21'] = sheet_in['K24'].value\n\n sheet_out['B22'] = sheet_in['G25'].value\n sheet_out['C22'] = sheet_in['I25'].value\n sheet_out['D22'] = sheet_in['K25'].value\n\n # sheet row 23 handle\n sheet_out['A23'] = 'SKT 기준'\n sheet_out['B23'] = sheet_in['H26'].value\n sheet_out['C23'] = sheet_in['J26'].value\n sheet_out['D23'] = sheet_in['L26'].value\n\n # sheet row 24~25\n sheet_out['A24'] = target\n sheet_out['B24'] = sheet_in['H28'].value\n sheet_out['C24'] = sheet_in['J28'].value\n sheet_out['D24'] = sheet_in['L28'].value\n sheet_out['A25'] = ref\n sheet_out['B25'] = sheet_in['H29'].value\n sheet_out['C25'] = sheet_in['J29'].value\n sheet_out['D25'] = sheet_in['L29'].value\n\n # sheet row 27~29 handle\n sheet_out['A27'] = '▣ WCDMA'\n sheet_out.merge_cells('A28:A29')\n sheet_out['A28'] = '구분'\n sheet_out['B28'] = sheet_in['E32'].value\n sheet_out.merge_cells('C28:D28')\n sheet_out['C28'] = sheet_in['G32'].value\n sheet_out['E28'] = sheet_in['K32'].value\n\n sheet_out['B29'] = sheet_in['E33'].value\n sheet_out['C29'] = sheet_in['G33'].value\n sheet_out['D29'] = sheet_in['I33'].value\n sheet_out['E29'] = sheet_in['K33'].value\n\n # sheet row 30 handle\n sheet_out['A30'] = 'SKT 기준'\n sheet_out['B30'] = sheet_in['F34'].value\n sheet_out['C30'] = sheet_in['H34'].value\n sheet_out['D30'] = sheet_in['J34'].value\n sheet_out['E30'] = sheet_in['L34'].value\n\n # sheet row 31~32\n sheet_out['A31'] = target\n sheet_out['B31'] = sheet_in['F36'].value\n sheet_out['C31'] = sheet_in['H36'].value\n sheet_out['D31'] = sheet_in['J36'].value\n sheet_out['E31'] = sheet_in['L36'].value\n sheet_out['A32'] = ref\n sheet_out['B32'] = sheet_in['F37'].value\n sheet_out['C32'] = sheet_in['H37'].value\n sheet_out['D32'] = sheet_in['J37'].value\n sheet_out['E32'] = sheet_in['L37'].value\n\n\n # sheet row 34~36 handle\n sheet_out['A34'] = '▣ WiFi'\n sheet_out.merge_cells('A35:A36')\n sheet_out['A35'] = '구분'\n sheet_out.merge_cells('B35:C35')\n sheet_out['B35'] = sheet_in['E40'].value\n sheet_out['D35'] = sheet_in['I40'].value\n sheet_out['E35'] = sheet_in['K40'].value\n sheet_out['F35'] = sheet_in['M40'].value\n\n sheet_out['B36'] = sheet_in['E41'].value\n sheet_out['C36'] = sheet_in['G41'].value\n sheet_out['D36'] = sheet_in['I41'].value\n sheet_out['E36'] = sheet_in['K41'].value\n sheet_out['F36'] = sheet_in['M41'].value\n\n # sheet row 37 handle\n sheet_out['A37'] = 'SKT 기준'\n sheet_out['B37'] = sheet_in['F42'].value\n sheet_out['C37'] = sheet_in['H42'].value\n sheet_out['D37'] = sheet_in['J42'].value\n sheet_out['E37'] = sheet_in['L42'].value\n sheet_out['F37'] = sheet_in['N42'].value\n\n # sheet row 38~39\n sheet_out['A38'] = target\n sheet_out['B38'] = sheet_in['F44'].value\n sheet_out['C38'] = sheet_in['H44'].value\n sheet_out['D38'] = sheet_in['J44'].value\n sheet_out['E38'] = sheet_in['L44'].value\n sheet_out['F38'] = sheet_in['N44'].value\n sheet_out['A39'] = ref\n sheet_out['B39'] = sheet_in['F45'].value\n sheet_out['C39'] = sheet_in['H45'].value\n sheet_out['D39'] = sheet_in['J45'].value\n sheet_out['E39'] = sheet_in['L45'].value\n sheet_out['F39'] = sheet_in['N45'].value\n\n # sheet row 41~43 handle\n sheet_out['A41'] = '▣ Bluetooth'\n sheet_out.merge_cells('A42:A43')\n sheet_out['A42'] = '구분'\n sheet_out.merge_cells('B42:F42')\n sheet_out['B42'] = sheet_in['E48'].value\n\n sheet_out['B43'] = sheet_in['E49'].value\n sheet_out['C43'] = sheet_in['G49'].value\n sheet_out['D43'] = sheet_in['I49'].value\n sheet_out['E43'] = sheet_in['K49'].value\n sheet_out['F43'] = sheet_in['M49'].value\n\n # sheet row 44 handle\n sheet_out['A44'] = 'SKT 기준'\n sheet_out['B44'] = sheet_in['F50'].value\n sheet_out['C44'] = sheet_in['H50'].value\n sheet_out['D44'] = sheet_in['J50'].value\n sheet_out['E44'] = sheet_in['L50'].value\n sheet_out['F44'] = sheet_in['N50'].value\n\n # sheet row 45~46\n sheet_out['A45'] = target\n sheet_out['B45'] = sheet_in['F52'].value\n sheet_out['C45'] = sheet_in['H52'].value\n sheet_out['D45'] = sheet_in['J52'].value\n sheet_out['E45'] = sheet_in['L52'].value\n sheet_out['F45'] = sheet_in['N52'].value\n sheet_out['A46'] = ref\n sheet_out['B46'] = sheet_in['F53'].value\n sheet_out['C46'] = sheet_in['H53'].value\n sheet_out['D46'] = sheet_in['J53'].value\n sheet_out['E46'] = sheet_in['L53'].value\n sheet_out['F46'] = sheet_in['N53'].value\n\n self.setPrintText('/s {}번 파일 \"배터리소모전류 결과 (시간)\" 테이터 입력 완료 /e'.format(idx+1))\n\n # set temp data\n if self.opFlag:\n\n # all cell alignment adjust\n for mCell in sheet_out[\"A1:H46\"]:\n for cell in mCell:\n cell.alignment = self.general_alignment\n\n # top alignment adjust\n sheet_out['A3'].alignment = self.top_alignment\n sheet_out['A15'].alignment = self.top_alignment\n sheet_out['A27'].alignment = self.top_alignment\n sheet_out['A34'].alignment = self.top_alignment\n sheet_out['A41'].alignment = self.top_alignment\n\n # all cell border adjust\n for mCell in sheet_out[\"A4:H8\"]:\n for cell in mCell:\n cell.border = self.thin_border\n for mCell in sheet_out[\"A9:F13\"]:\n for cell in mCell:\n cell.border = self.thin_border\n for mCell in sheet_out[\"A16:H20\"]:\n for cell in mCell:\n cell.border = self.thin_border\n for mCell in sheet_out[\"A21:D25\"]:\n for cell in mCell:\n cell.border = self.thin_border\n for mCell in sheet_out[\"A28:E32\"]:\n for cell in mCell:\n cell.border = self.thin_border\n for mCell in sheet_out[\"A35:F39\"]:\n for cell in mCell:\n cell.border = self.thin_border\n for mCell in sheet_out[\"A42:F46\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n # all cell font adjust\n for mCell in sheet_out[\"A3:H46\"]:\n for cell in mCell:\n cell.font = self.index_font\n\n sheet_out['A1'].font = Font(name='맑은 고딕', size=22, bold=True, color='2B2B2B')\n\n # each column width adjust\n sheet_cell_list = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H']\n sheet_width_list = [29.88, 13.38, 13.38, 13.38, 13.38, 13.38, 13.38, 13.38]\n\n for i in range(len(sheet_cell_list)):\n sheet_out.column_dimensions[sheet_cell_list[i]].width = sheet_width_list[i]\n\n sheet_out.row_dimensions[1].height = 45\n\n # Set Pattern Fill\n for col in ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H']:\n\n sheet_out[col + '4'].fill = self.brown_fill\n sheet_out[col + '5'].fill = self.brown_fill\n sheet_out[col + '6'].fill = self.apricot_fill\n sheet_out[col + '16'].fill = self.brown_fill\n sheet_out[col + '17'].fill = self.brown_fill\n sheet_out[col + '18'].fill = self.apricot_fill\n\n for col in ['A', 'B', 'C', 'D', 'E', 'F']:\n\n sheet_out[col + '9'].fill = self.brown_fill\n sheet_out[col + '10'].fill = self.brown_fill\n sheet_out[col + '11'].fill = self.apricot_fill\n sheet_out[col + '35'].fill = self.brown_fill\n sheet_out[col + '36'].fill = self.brown_fill\n sheet_out[col + '37'].fill = self.apricot_fill\n sheet_out[col + '42'].fill = self.brown_fill\n sheet_out[col + '43'].fill = self.brown_fill\n sheet_out[col + '44'].fill = self.apricot_fill\n\n for col in ['A', 'B', 'C', 'D', 'E']:\n\n sheet_out[col + '28'].fill = self.brown_fill\n sheet_out[col + '29'].fill = self.brown_fill\n sheet_out[col + '30'].fill = self.apricot_fill\n\n\n for col in ['A', 'B', 'C', 'D']:\n\n sheet_out[col + '21'].fill = self.brown_fill\n sheet_out[col + '22'].fill = self.brown_fill\n sheet_out[col + '23'].fill = self.apricot_fill\n\n for i in [7, 8, 12, 13, 19, 20, 24, 25, 31, 32, 38, 39, 45, 46]:\n\n sheet_out['A' + str(i)].fill = self.gray_fill\n\n self.currentRow = self.currentRow + 1\n self.setPrintText('/s {}번 파일 \"배터리소모전류 결과 (시간)\" 시트 스타일 적용 완료 /e'.format(idx+1))\n\n # save file\n wb_output.save(self.list_out_files[idx])\n except:\n self.setPrintText('/s Error: {}. {}, line: {}'.format(sys.exc_info()[0], sys.exc_info()[1], sys.exc_info()[2].tb_lineno)+' /e')\n self.end_count = \"y\"\n self.end_flag.emit()\n\n # 첨부 1 측정기준 Tab\n def attach_generate_data_1(self):\n\n try:\n for idx, item in enumerate(self.list_out_files):\n\n wb_output = openpyxl.load_workbook(item)\n # option setting wb.output\n sheet_out = wb_output['첨부1. 측정기준 및 가점']\n list_band = ['Band 1 15M', 'Band 3 20M', 'Band 5 10M',\n 'Band 7 20M', 'Band 7 10M']\n list_trp_base = ['14.00dBm', '15.00dBm', '13.50dBm',\n '13.00dBm', '13.00dBm']\n list_tis_base = ['-92.00dBm', '-91.00dBm', '-87.00dBm',\n '-90.00dBm', '-93.00dBm']\n\n # sheet row 1 handle\n sheet_out.merge_cells('A1:D1')\n sheet_out['A1'] = '첨부1. 측정기준 및 가점'\n\n # sheet row 3 handle\n sheet_out['A3'] = '▣ RF 성능 : 기 출시 단말 측정하여 상위 70% 수준으로 설정'\n sheet_out['A4'] = ' -TRP'\n\n # 5~10 row\n sheet_out['A5'] = 'SISO LTE'\n sheet_out['B5'] = '기준(RHP)'\n sheet_out.merge_cells('C5:D5')\n sheet_out['C5'] = '측정기준 History'\n\n for i in range(6, 11):\n sheet_out['A' + str(i)] = list_band[i - 6]\n sheet_out['B' + str(i)] = list_trp_base[i - 6]\n sheet_out.merge_cells('C6:D10')\n sheet_out['C6'] = '기준대비 1dB 증가후 +1점/1dBm 가점\\n기준대비 1dB 저하후 - 1점/1dBm 감점'\n # 11~17 row\n sheet_out['A11'] = ' -TIS (SISO LTE)'\n\n # 12~17 row\n sheet_out['A12'] = 'SISO LTE'\n sheet_out['B12'] = '기준(RHP)'\n sheet_out.merge_cells('C12:D12')\n sheet_out['C12'] = '측정기준 History'\n\n for i in range(13, 18):\n sheet_out['A' + str(i)] = list_band[i - 13]\n sheet_out['B' + str(i)] = list_trp_base[i - 13]\n sheet_out.merge_cells('C13:D17')\n sheet_out['C13'] = '기준대비 1dB 증가후 +1점/3dBm 가점\\n기준대비 1dB 저하후 - 1점/3dBm 감점'\n\n # 19~25 row\n sheet_out['A19'] = '▣ 배터리 소모전류'\n sheet_out.merge_cells('A20:D20')\n sheet_out['A20'] = \" - '18.1 ~ '19.8 납품검사 삼성/LG 단말 29종으로\\n측정 기준으로 소모전류 (평균+STD), 배터리 용량 (3000mA) 산출\"\n sheet_out.merge_cells('A21:D21')\n sheet_out['A21'] = \" - Ref. 단말 대비 10% 이내 (측정기준부재항목)\"\n\n sheet_out['A23'] = '▣ MOS'\n sheet_out.merge_cells('A24:D24')\n sheet_out['A24'] = \" - ITU-T 권고 P.800 항목에 규정 참고 (LTE : 3.5, WCDMA : 3.0)\"\n sheet_out.merge_cells('A25:D25')\n sheet_out['A25'] = '. MOS 3.5~4 : 자연스러운 통화 수준\\n. MOS 3~3.5 : 대화는 잘 이루어지지만 품질저하 느낄 수 있음'\n\n self.setPrintText('/s {}번 파일 \"첨부1\" 테이터 입력 완��� /e'.format(idx+1))\n\n # set temp data\n\n if self.opFlag:\n\n # all cell alignment adjust\n for mCell in sheet_out[\"A1:D25\"]:\n for cell in mCell:\n cell.alignment = self.general_alignment\n\n # top alignment adjust\n sheet_out['A3'].alignment = self.top_alignment\n sheet_out['A4'].alignment = self.top_alignment\n sheet_out['C6'].alignment = self.top_alignment_3\n sheet_out['A11'].alignment = self.top_alignment\n sheet_out['C13'].alignment = self.top_alignment_3\n sheet_out['A19'].alignment = self.top_alignment\n sheet_out['A20'].alignment = self.top_alignment_3\n sheet_out['A21'].alignment = self.top_alignment\n sheet_out['A23'].alignment = self.top_alignment\n sheet_out['A24'].alignment = self.top_alignment\n sheet_out['A25'].alignment = self.top_alignment_3\n\n # all cell border adjust\n for mCell in sheet_out[\"A5:D10\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n for mCell in sheet_out[\"A12:D17\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n # all cell font adjust\n for mCell in sheet_out[\"A2:D25\"]:\n for cell in mCell:\n cell.font = self.index_font\n\n sheet_out['A1'].font = Font(name='맑은 고딕', size=22, bold=True, color='2B2B2B')\n\n # each column width adjust\n sheet_cell_list = ['A', 'B', 'C', 'D']\n sheet_width_list = [25, 15.88, 17, 17]\n\n for i in range(len(sheet_cell_list)):\n sheet_out.column_dimensions[sheet_cell_list[i]].width = sheet_width_list[i]\n sheet_out.row_dimensions[1].height = 45\n sheet_out.row_dimensions[20].height = 45\n sheet_out.row_dimensions[25].height = 45\n\n # Set Pattern Fill\n for i in [5, 12]:\n sheet_out['A' + str(i)].fill = self.brown_fill\n sheet_out['B' + str(i)].fill = self.brown_fill\n sheet_out['C' + str(i)].fill = self.brown_fill\n sheet_out['D' + str(i)].fill = self.brown_fill\n\n for i in [5, 6, 7, 8, 9, 10, 13, 14, 15, 16, 17]:\n sheet_out['A' + str(i)].fill = self.gray_fill\n sheet_out['B' + str(i)].fill = self.apricot_fill\n\n self.currentRow = self.currentRow + 1\n self.setPrintText('/s {}번 파일 \"첨부1\" 시트 스타일 적용 완료 /e'.format(idx+1))\n # save file\n wb_output.save(self.list_out_files[idx])\n except:\n self.setPrintText('/s Error: {}. {}, line: {}'.format(sys.exc_info()[0], sys.exc_info()[1], sys.exc_info()[2].tb_lineno)+' /e')\n self.end_count = \"y\"\n self.end_flag.emit()\n\n # 첨부 2 측정기준 Tab\n def attach_generate_data_2(self):\n\n try:\n for idx, item in enumerate(self.list_out_files):\n\n wb_output = openpyxl.load_workbook(item)\n # option setting wb.output\n sheet_out = wb_output['첨부2. 납품검사']\n list_items = ['고온 고습/저온 Cycling 시험\t', '낙하시험', '방수시험', 'ESD (정전기) 시험',\n '개통 및 사용성 시험', 'RF Auto (50대, 제조사 자체 측정)', 'CATS_Priority1 (제조사 자체 측정)',\n 'GPS (제조사 자체 측정)', '발열 (제조사 자체 측정)', '카메라 전.후면 화질평가 (제조사 자체 측정)',\n 'WiFi 무선성능(제조사 자체 측정)', 'BT 무선성능(제조사 자체 측정)']\n list_items_2 = ['무선기기 형식등록', 'GCF 인증서', 'WiFi 인증서', 'NFC 인증서', 'Bluetooth 인증서']\n\n # sheet row 1 handle\n sheet_out.merge_cells('A1:D1')\n sheet_out['A1'] = '첨부2. 납품검사'\n\n # sheet row 3 handle\n sheet_out['A3'] = '▣ 장소 : (빈곳)'\n\n # 4~16 row\n sheet_out['A4'] = '구분'\n sheet_out.merge_cells('B4:C4')\n sheet_out['B4'] = 'Item'\n sheet_out['D4'] = '결과'\n\n sheet_out.merge_cells('A5:A8')\n sheet_out['A5'] = '신뢰성 시험'\n sheet_out.merge_cells('A9:A16')\n sheet_out['A9'] = 'Performance'\n\n for i in range(5, 17):\n sheet_out.merge_cells('B' + str(i) + ':C' + str(i))\n sheet_out['B' + str(i)] = list_items[i - 5]\n\n # 18~24 row\n sheet_out['A18'] = '▣ 시험 인증서 (PLM 등록)'\n sheet_out['A19'] = '구분'\n sheet_out.merge_cells('B19:C19')\n sheet_out['B19'] = 'Item'\n sheet_out['D19'] = '결과'\n\n sheet_out.merge_cells('A20:A24')\n sheet_out['A20'] = '인증서'\n\n for i in range(20, 25):\n sheet_out.merge_cells('B' + str(i) + ':C' + str(i))\n sheet_out['B' + str(i)] = list_items_2[i - 20]\n\n\n self.setPrintText('/s {}번 파일 \"첨부2\" 테이터 입력 완료 /e'.format(idx+1))\n\n # set temp data\n\n if self.opFlag:\n\n # all cell alignment adjust\n for mCell in sheet_out[\"A1:D24\"]:\n for cell in mCell:\n cell.alignment = self.general_alignment\n # top alignment adjust\n sheet_out['A3'].alignment = self.top_alignment\n sheet_out['A18'].alignment = self.top_alignment\n\n # all cell border adjust\n for mCell in sheet_out[\"A4:D16\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n for mCell in sheet_out[\"A19:D24\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n # all cell font adjust\n for mCell in sheet_out[\"A2:D24\"]:\n for cell in mCell:\n cell.font = self.index_font\n\n sheet_out['A1'].font = Font(name='맑은 고딕', size=22, bold=True, color='2B2B2B')\n\n # each column width adjust\n sheet_cell_list = ['A', 'B', 'C', 'D']\n sheet_width_list = [25, 15.88, 23.75, 17]\n\n for i in range(len(sheet_cell_list)):\n sheet_out.column_dimensions[sheet_cell_list[i]].width = sheet_width_list[i]\n sheet_out.row_dimensions[1].height = 45\n\n # Set Pattern Fill\n for i in [4, 19]:\n sheet_out['A' + str(i)].fill = self.brown_fill\n sheet_out['B' + str(i)].fill = self.brown_fill\n sheet_out['C' + str(i)].fill = self.brown_fill\n sheet_out['D' + str(i)].fill = self.brown_fill\n\n for i in range(5,17):\n sheet_out['A' + str(i)].fill = self.gray_fill\n sheet_out['B' + str(i)].fill = self.gray_fill\n\n for i in range(20,25):\n sheet_out['A' + str(i)].fill = self.gray_fill\n sheet_out['B' + str(i)].fill = self.gray_fill\n\n self.currentRow = self.currentRow + 1\n self.setPrintText('/s {}번 파일 \"첨부2\" 시트 스타일 적용 완료 /e'.format(idx+1))\n # save file\n wb_output.save(self.list_out_files[idx])\n except:\n self.setPrintText('/s Error: {}. {}, line: {}'.format(sys.exc_info()[0], sys.exc_info()[1], sys.exc_info()[2].tb_lineno)+' /e')\n self.end_count = \"y\"\n self.end_flag.emit()\n\n # 첨부 3 측정기준 Tab\n def attach_generate_data_3(self):\n\n try:\n for idx, item in enumerate(self.list_out_files):\n\n wb_output = openpyxl.load_workbook(item)\n # option setting wb.output\n sheet_out = wb_output['첨부3. 단말 상세 SPEC']\n list_items = ['모뎀', 'RFIC', 'Display', '크기', '배터리 용량', 'Flash ROM', 'SRAM', '카메라', '사운드', 'MIC', '방수/방진', '페이', '생체인식',\n '충전', '기타', 'LTE 주파수', 'LTE 로밍 지원 주파수', 'WCDMA 주파수', 'OS(출시버전)', '출시']\n list_items_2 = ['5G NW options', '5G Frequency', 'UE-Category', 'Max Throughput', 'ENDC capability',\n 'LTE capability', 'Modulation', 'MIMO', 'CSI-RS', 'Power', 'Waveform']\n\n # sheet row 1 handle\n sheet_out.merge_cells('A1:C1')\n sheet_out['A1'] = '첨부3. 단말 상세 SPEC'\n\n # sheet row 2 handle\n sheet_out['A2'] = '▣ 기본 정보 '\n\n # 3~23 row\n sheet_out['A3'] = '구분'\n sheet_out['B3'] = '모델1'\n sheet_out['C3'] = 'Ref. 모델'\n\n for i in range(4, 24):\n sheet_out['A' + str(i)] = list_items[i - 4]\n\n # 25~37 row\n sheet_out['A25'] = '▣ N/W Feature 비교'\n sheet_out['A26'] = '구분'\n sheet_out['B26'] = '모델1'\n sheet_out['C26'] = 'Ref. 모델'\n\n for i in range(27, 38):\n sheet_out['A' + str(i)] = list_items_2[i - 27]\n\n self.setPrintText('/s {}번 파일 \"첨부3\" 테이터 입력 완료 /e'.format(idx+1))\n\n # set temp data\n\n if self.opFlag:\n\n # all cell alignment adjust\n for mCell in sheet_out[\"A1:C37\"]:\n for cell in mCell:\n cell.alignment = self.general_alignment\n # top alignment adjust\n sheet_out['A2'].alignment = self.top_alignment\n sheet_out['A25'].alignment = self.top_alignment\n\n # all cell border adjust\n for mCell in sheet_out[\"A3:C23\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n for mCell in sheet_out[\"A26:C37\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n # all cell font adjust\n for mCell in sheet_out[\"A2:C3\"]:\n for cell in mCell:\n cell.font = self.index_font\n for mCell in sheet_out[\"A4:C23\"]:\n for cell in mCell:\n cell.font = self.value_font\n for mCell in sheet_out[\"A25:C26\"]:\n for cell in mCell:\n cell.font = self.index_font\n for mCell in sheet_out[\"A27:C37\"]:\n for cell in mCell:\n cell.font = self.value_font\n sheet_out['A1'].font = Font(name='맑은 고딕', size=22, bold=True, color='2B2B2B')\n\n # each column width adjust\n sheet_cell_list = ['A', 'B', 'C']\n sheet_width_list = [20.13, 39, 39]\n\n for i in range(len(sheet_cell_list)):\n sheet_out.column_dimensions[sheet_cell_list[i]].width = sheet_width_list[i]\n sheet_out.row_dimensions[1].height = 45\n\n # Set Pattern Fill\n for i in [3, 26]:\n sheet_out['A' + str(i)].fill = self.brown_fill\n sheet_out['B' + str(i)].fill = self.brown_fill\n sheet_out['C' + str(i)].fill = self.brown_fill\n\n for i in range(4, 24):\n sheet_out['A' + str(i)].fill = self.gray_fill\n\n for i in range(27, 38):\n sheet_out['A' + str(i)].fill = self.gray_fill\n\n self.currentRow = self.currentRow + 1\n self.setPrintText('/s {}번 파일 \"첨부3\" 시트 스타일 적용 완료 /e'.format(idx+1))\n # save file\n wb_output.save(self.list_out_files[idx])\n except:\n self.setPrintText('/s Error: {}. {}, line: {}'.format(sys.exc_info()[0], sys.exc_info()[1], sys.exc_info()[2].tb_lineno)+' /e')\n self.end_count = \"y\"\n self.end_flag.emit()\n\n # f2 function\n def f2_generate_data(self):\n\n try:\n for idx, item in enumerate(self.list_files):\n\n wb_output = openpyxl.load_workbook(item, data_only=True)\n # option setting wb.output\n sheet_in = wb_output['Profile']\n wb_output.create_sheet('Comparison', 2)\n sheet_out = wb_output['Comparison']\n # 1st list items are fixed usim info, 2nd list items are variable usim info\n list_find = [['ESN', 'HPPLMN', 'HPLMNNWACT', 'FPLMN', 'PWS', 'HPLMNwACT', 'DOMAIN'],\n ['IMEI', 'IMSI', 'KEYS', 'KEYSPS', 'MSISDN', 'SMSP', 'PSLOCI', 'ACC', 'LOCI', 'IMSI_M',\n 'MDN', 'IRM', 'IMPI', 'IMPU', 'P_CSCF']]\n list_fixed_item = []\n list_variable_item = []\n list_reference_item = [\n '0000FFFFFFFFFFFF',\n '01',\n '54F050400054F0508000FFFFFF0000FFFFFF0000FFFFFF0000FFFFFF0000FFFFFF0000FFFFFF0000FFFFFF0000FFFFFF0000',\n '54F08054F06054F00354F040',\n 'FCFFFFFFFFFFFFFFFFFF',\n '54F050400054F0508000FFFFFF0000FFFFFF0000FFFFFF0000FFFFFF0000FFFFFF0000FFFFFF0000FFFFFF0000FFFFFF0000',\n '800A736B74696D732E6E6574FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF',\n ]\n\n total_row = len(sheet_in['A'])\n\n # sheet row 1 handle\n sheet_out.merge_cells('B1:E1')\n sheet_out['B1'] = 'USIM DATA COMPARISON'\n # sheet row 2 handle\n sheet_out['B2'] = 'EF��일명'\n sheet_out['C2'] = 'DATA값'\n sheet_out['D2'] = '고정기준값'\n sheet_out['E2'] = '비교'\n\n # finding fixed value\n for fixed in list_find[0]:\n for i in range(2, total_row+1):\n if sheet_in['A' + str(i)].value == fixed:\n data = sheet_in['Q' + str(i)].value.strip()\n data = re.sub(r'[\\n,\\s,\\t]', '', data)\n list_fixed_item.append(data)\n break\n\n # finding variable value\n for variable in list_find[1]:\n for i in range(2, total_row+1):\n if sheet_in['A' + str(i)].value == variable:\n data = sheet_in['Q' + str(i)].value.strip()\n data = re.sub(r'[\\n,\\s,\\t]', '', data)\n list_variable_item.append(data)\n break\n\n # red\n # 3~ 24 rows fill data\n # 3~9까지 fixed\n # 10~24까지 variable\n\n # all cell font adjust\n for mCell in sheet_out[\"B2:E24\"]:\n for cell in mCell:\n cell.font = self.f2_value_font\n\n sheet_out['B1'].font = Font(name='맑은 고딕', size=22, bold=True, color='2B2B2B')\n # 고정값 Set\n for i, f_item in enumerate(list_fixed_item):\n sheet_out['B' + str(i + 3)] = list_find[0][i]\n sheet_out['B' + str(i + 3)].fill = self.yellow_fill\n sheet_out['C' + str(i + 3)] = f_item\n sheet_out['D' + str(i + 3)] = list_reference_item[i]\n sheet_out['D' + str(i + 3)].fill = self.yellow_fill\n\n if list_fixed_item[i] == list_reference_item[i]:\n sheet_out['E' + str(i + 3)] = 'True(일치함)'\n sheet_out['E' + str(i + 3)].font = self.f2_blue_font\n else:\n sheet_out['E' + str(i + 3)] = 'False(불일치)'\n sheet_out['E' + str(i + 3)].font = self.f2_red_font\n\n sheet_out['E' + str(i + 3)].fill = self.yellow_fill\n\n # 가변값 Set\n for i, v_item in enumerate(list_variable_item):\n sheet_out['B' + str(i + 10)] = list_find[1][i]\n sheet_out['B' + str(i + 10)].fill = self.orange_fill\n sheet_out['C' + str(i + 10)] = v_item\n sheet_out['D' + str(i + 10)].fill = self.orange_fill\n sheet_out['E' + str(i + 10)].fill = self.orange_fill\n\n self.setPrintText('/s {}번 파일 \"Comparison\" 테이터 입력 완료 /e'.format(idx+1))\n\n # set temp data\n\n if self.opFlag:\n\n # all cell alignment adjust\n for mCell in sheet_out[\"B2:E24\"]:\n for cell in mCell:\n cell.alignment = self.general_alignment\n\n # top alignment adjust\n for mCell in sheet_out[\"C4:C24\"]:\n for cell in mCell:\n cell.alignment = self.top_alignment_3\n\n for mCell in sheet_out[\"D4:D24\"]:\n for cell in mCell:\n cell.alignment = self.top_alignment_3\n\n # all cell border adjust\n for mCell in sheet_out[\"B2:E24\"]:\n for cell in mCell:\n cell.border = self.thin_border\n\n # set filter\n sheet_out.auto_filter.ref = \"B2:E24\"\n\n # each column width adjust\n sheet_cell_list = ['A', 'B', 'C', 'D', 'E']\n sheet_width_list = [4.25, 14.75, 57, 57, 23]\n\n for i in range(len(sheet_cell_list)):\n sheet_out.column_dimensions[sheet_cell_list[i]].width = sheet_width_list[i]\n sheet_out.row_dimensions[1].height = 45\n\n # Set Pattern Fill\n sheet_out['B2'].fill = self.brown_fill\n sheet_out['C2'].fill = self.brown_fill\n sheet_out['D2'].fill = self.brown_fill\n sheet_out['E2'].fill = self.brown_fill\n\n\n self.currentRow = self.currentRow + 1\n self.totalRows = self.totalRows + 1\n self.progress_flag.emit()\n self.setPrintText('/s {}번 파일 \"Comparison\" 시트 스타일 적용 완료 /e'.format(idx+1))\n # save file\n wb_output.save(self.list_out_files[idx])\n except:\n self.setPrintText('/s Error: {}. {}, line: {}'.format(sys.exc_info()[0], sys.exc_info()[1], sys.exc_info()[2].tb_lineno)+' /e')\n self.end_count = \"y\"\n self.end_flag.emit()\n\n # main method\n def run(self):\n\n try:\n ###########################__Setting print Text Thread__######################\n\n self.thread_count = threading.Thread(target=self.getCountRows, args=())\n self.thread_count.daemon = True\n self.thread_count.start()\n self.nowTime = datetime.today().strftime(\"%Y-%m-%d\")\n\n #################################################################_SETTING INPUT_###########################################################################\n # Save root directory\n self.flag_root = os.path.isdir(self.home+\"\\\\Desktop\\\\DOC\\\\\")\n if not self.flag_root:\n os.mkdir(self.home + \"\\\\Desktop\\\\DOC\\\\\")\n\n # extract file name each list_files and make every out file path\n for item in self.list_files:\n temp_filename = os.path.basename(item)\n temp_filename = re.sub(\"(.xlsx|.xls)\", \"\", temp_filename)\n output_file = self.home+\"\\\\Desktop\\\\DOC\\\\result_\"+temp_filename+\"(\"+self.nowTime+\").xlsx\"\n self.list_out_files.append(output_file)\n\n if self.modeFlag == \"f1\":\n\n #################################################################_RESULT FILE Generate_###########################################################################\n # output file generate\n for item in self.list_out_files:\n\n wb = Workbook()\n s1 = wb.active\n s1.title = \"검증결과요약\"\n wb.create_sheet('시험결과요약', 1)\n wb.create_sheet('TRP', 2)\n wb.create_sheet('TIS', 3)\n wb.create_sheet('속도', 4)\n wb.create_sheet('Call Setup Test', 5)\n wb.create_sheet('주파수동조', 6)\n wb.create_sheet('MOS', 7)\n wb.create_sheet('배터리소모전류(시간)', 8)\n wb.create_sheet('배터리소모전류 세부데이터', 9)\n wb.create_sheet('배터리소모전류(DOU)', 10)\n wb.create_sheet('첨부1. 측정기준 및 가점', 11)\n wb.create_sheet('첨부2. 납품검사', 12)\n wb.create_sheet('첨부3. 단말 상세 SPEC', 13)\n wb.save(item)\n\n self.setPrintText(\"/s Complete making Result excel file /e\")\n self.setPrintText(\"/s Extract Original Data in each file /e\")\n\n #Core Code\n self.start_time = datetime.today().strftime(\"%Y-%m-%d %H:%M:%S\")\n #Excel input Data read\n self.setPrintText(\"/s STARTED_TIME: \"+self.start_time+\" /e\")\n\n ########################################################################Start to generate openpyXL Sheet Style########################################################################\n # 검증결과요약 텝 생성\n self.summary_generate_data()\n self.totalRows = 1\n self.currentRow = 0\n self.progress_flag.emit()\n\n # 시험결과요약 텝 생성\n self.test_generate_data()\n self.totalRows = 2\n self.currentRow = 0\n self.progress_flag.emit()\n\n # TRP 텝 생성\n self.trp_generate_data()\n self.totalRows = 3\n self.currentRow = 0\n self.progress_flag.emit()\n\n # TIS 텝 생성\n self.tis_generate_data()\n self.totalRows = 4\n self.currentRow = 0\n self.progress_flag.emit()\n\n # 속도 텝 생성\n self.spd_generate_data()\n self.totalRows = 5\n self.currentRow = 0\n self.progress_flag.emit()\n\n # Call Setup Test 텝 생성\n self.call_generate_data()\n self.totalRows = 6\n self.currentRow = 0\n self.progress_flag.emit()\n\n # 주파수동조 텝 생성\n self.fre_generate_data()\n self.totalRows = 7\n self.currentRow = 0\n self.progress_flag.emit()\n\n # MOS 텝 생성\n self.mos_generate_data()\n self.totalRows = 8\n self.currentRow = 0\n self.progress_flag.emit()\n\n # 베터리소모전류(DOU) 텝 생성\n self.dou_generate_data()\n self.totalRows = 9\n self.currentRow = 0\n self.progress_flag.emit()\n\n # 베터리소모전류 세부테이터 텝 생성\n self.bat_generate_data()\n self.totalRows = 10\n self.currentRow = 0\n self.progress_flag.emit()\n\n # 베터리소모전류 세부테이터 텝 생성\n self.time_generate_data()\n self.totalRows = 11\n self.currentRow = 0\n self.progress_flag.emit()\n\n # 베터리소모전류 세부테이터 텝 생성\n self.attach_generate_data_1()\n self.totalRows = 12\n self.currentRow = 0\n self.progress_flag.emit()\n\n # 베터리소모전류 세부테이터 텝 생성\n self.attach_generate_data_2()\n self.totalRows = 13\n self.currentRow = 0\n self.progress_flag.emit()\n\n # 베터리소모전류 세부테이터 텝 생성\n self.attach_generate_data_3()\n self.totalRows = 14\n self.currentRow = 0\n self.progress_flag.emit()\n\n #############################################__progress 100%__#############################################\n self.end_count = \"y\"\n self.end_flag.emit()\n\n #Core Code\n self.end_time = datetime.today().strftime(\"%Y-%m-%d %H:%M:%S\")\n #Excel input Data read\n self.setPrintText(\"/s FINISHED_TIME: \"+self.end_time+\" /e\")\n\n else:\n #Core Code\n self.start_time = datetime.today().strftime(\"%Y-%m-%d %H:%M:%S\")\n #Excel input Data read\n self.setPrintText(\"/s STARTED_TIME: \"+self.start_time+\" /e\")\n self.f2_generate_data()\n self.end_count = \"y\"\n self.end_flag.emit()\n #Core Code\n self.end_time = datetime.today().strftime(\"%Y-%m-%d %H:%M:%S\")\n #Excel input Data read\n self.setPrintText(\"/s FINISHED_TIME: \"+self.end_time+\" /e\")\n\n except:\n self.setPrintText('/s Error: {}. {}, line: {}'.format(sys.exc_info()[0], sys.exc_info()[1], sys.exc_info()[2].tb_lineno)+' /e')\n self.end_count = \"y\"\n self.end_flag.emit()\n\nif __name__ == '__main__':\n moduler = Formater('C:\\\\Users\\\\TestEnC\\\\Desktop\\\\VOC\\\\input_sample.xlsx', 'y', 'f1')\n moduler.run()\n","sub_path":"docBeFormater/newModule.py","file_name":"newModule.py","file_ext":"py","file_size_in_byte":171877,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"210347852","text":"import os\nos.environ[\"GOOGLE_APPLICATION_CREDENTIALS\"] = './config/My Project-bd8af4dfa881.json'\nfrom google.cloud import texttospeech\nimport base64\nimport subprocess\nfrom pydub import AudioSegment\nfrom pydub.playback import play\nimport io\n\n\n\ndef create_google_sst(text):\n client = texttospeech.TextToSpeechClient()\n synthesis_input = texttospeech.types.SynthesisInput(text=text)\n voice = texttospeech.types.VoiceSelectionParams(\n name=\"en-US-Wavenet-F\",\n language_code='en-US', \n ssml_gender=texttospeech.enums.SsmlVoiceGender.FEMALE\n )\n audio_config = texttospeech.types.AudioConfig(\n audio_encoding=texttospeech.enums.AudioEncoding.MP3,\n pitch=2.0,\n speaking_rate=1.26\n )\n \n response = client.synthesize_speech(synthesis_input, voice, audio_config)\n audio = base64.b64decode(response.audio_content)\n\n song = AudioSegment.from_file(io.BytesIO(audio), format=\"mp3\")\n play(song)\n\ncreate_google_sst(\"how can I help you ?\")","sub_path":"scrath.py","file_name":"scrath.py","file_ext":"py","file_size_in_byte":1028,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"190884705","text":"import sys\nimport json\nfrom splunklib.searchcommands import dispatch, StreamingCommand, Configuration, Option\nfrom splunklib.searchcommands.validators import Fieldname\nimport environment_data\n\n\n@Configuration(local=True)\nclass EnvironmentInstancesUpdateState(StreamingCommand):\n\n state_field = Option(validate=Fieldname())\n name_field = Option(validate=Fieldname())\n\n def stream(self, instances):\n for instance in instances:\n environment_id = instance[\"environment_id\"]\n instance_state = instance[self.state_field]\n instance_name = instance[self.name_field]\n\n self.service.post(\"/services/msaas/environments/%s/instances/%s\" % (environment_id, instance_name), body=json.dumps({\n \"state\": instance_state,\n }))\n # environment_data.update_instance(\n # self.service, environment_id, instance_name,\n # instance_state=instance_state)\n yield instance\n\ndispatch(EnvironmentInstancesUpdateState,\n sys.argv, sys.stdin, sys.stdout, __name__)\n","sub_path":"apps/msaas/bin/environment_instances_update_state_command.py","file_name":"environment_instances_update_state_command.py","file_ext":"py","file_size_in_byte":1069,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"341896877","text":"class Node:\n def __init__(self, value):\n self.value = value\n self.next = None\n\n def __repr__(self):\n return str(self.value)\n\n\nclass LinkedList:\n def __init__(self):\n self.head = None\n\n def __str__(self):\n cur_head = self.head\n out_string = \"\"\n while cur_head:\n out_string += str(cur_head.value) + \" -> \"\n cur_head = cur_head.next\n return out_string\n\n def append(self, value):\n\n if self.head is None:\n self.head = Node(value)\n return\n\n node = self.head\n while node.next:\n node = node.next\n\n node.next = Node(value)\n\n def size(self):\n size = 0\n node = self.head\n while node:\n size += 1\n node = node.next\n\n return size\n\n\n# def union(llist_1, llist_2):\n# # Your Solution Here\n# union_list = LinkedList()\n# curr_node = llist_1.head\n# while curr_node is not None:\n# if union_list.head is None:\n# union_list.head = Node(curr_node.value)\n# else: \n# node = union_list.head\n# while node:\n# if node.value == curr_node.value:\n# break\n# else:\n# node = node.next\n# if node is None:\n# union_list.append(curr_node.value)\n# curr_node = curr_node.next\n# curr_node = llist_2.head\n# while curr_node is not None:\n# if union_list.head is None:\n# union_list.head = Node(curr_node.value)\n# else:\n# node = union_list.head\n# while node:\n# if node.value == curr_node.value:\n# break\n# else:\n# node = node.next\n# if node is None:\n# union_list.append(curr_node.value)\n# curr_node = curr_node.next\n# return union_list\n\ndef union(llist_1, llist_2):\n union_list = {}\n answer_list = LinkedList()\n node = llist_1.head\n while node:\n if node.value in union_list:\n union_list[node.value] += 1\n else:\n union_list[node.value] = 1\n node = node.next\n node = llist_2.head\n while node:\n if node.value in union_list:\n union_list[node.value] += 1\n else:\n union_list[node.value] = 1\n node = node.next\n for element in union_list:\n answer_list.append(element)\n return answer_list\n\ndef intersection(llist_1, llist_2):\n intersection_list = {}\n answer_list = LinkedList()\n node = llist_1.head\n while node:\n if node.value in intersection_list:\n intersection_list[node.value] += 1\n else:\n intersection_list[node.value] = 1\n node = node.next\n node = llist_2.head\n while node:\n if node.value in intersection_list:\n answer_list.append(node.value)\n del intersection_list[node.value]\n node = node.next\n \n return answer_list\n\n# Test case 1\n\nlinked_list_1 = LinkedList()\nlinked_list_2 = LinkedList()\n\nelement_1 = [3, 2, 4, 35, 6, 65, 6, 4, 3, 21]\nelement_2 = [6, 32, 4, 9, 6, 1, 11, 21, 1]\n\nfor i in element_1:\n linked_list_1.append(i)\n\nfor i in element_2:\n linked_list_2.append(i)\n\nprint(union(linked_list_1, linked_list_2))\nprint(intersection(linked_list_1, linked_list_2))\n\n# Test case 2\nlinked_list_3 = LinkedList()\nlinked_list_4 = LinkedList()\n\nelement_1 = [3, 2, 4, 35, 6, 65, 6, 4, 3, 23]\nelement_2 = [1, 7, 8, 9, 11, 21, 1]\n\nfor i in element_1:\n linked_list_3.append(i)\n\nfor i in element_2:\n linked_list_4.append(i)\n\nprint(union(linked_list_3, linked_list_4))\nprint(intersection(linked_list_3, linked_list_4))\n\n","sub_path":"union_intersection_linkedlist.py","file_name":"union_intersection_linkedlist.py","file_ext":"py","file_size_in_byte":3751,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"545420405","text":"import random\nfrom datetime import datetime, timedelta\n\nfrom Person import Person\n\n\nclass Place:\n\n def __init__(self, place_info):\n self.population = set()\n self.place_info = place_info # (40.760265, -73.989105, 'Italian', '217', '291', 'Ristorante Da Rosina')\n self.time_to_recover = 14\n self.total_infected_number = 0\n self.immune_population = set()\n\n def get_population(self):\n return self.population\n\n def get_total_infected(self):\n return self.total_infected_number\n\n def set_population(self, new_population):\n self.population = new_population\n\n def set_total_movements(self, number):\n self.total_movements = number\n self.init_population(self.total_movements) # initilise population according to place popularity\n\n def init_population(self, number):\n start_time = datetime(2010, 12, 21, 20, 0, 0)\n for i in range(number):\n person = Person()\n # infect with a certain probability\n if random.random() <= 0.001:\n person.set_infected(start_time)\n self.add_person(person)\n\n def get_total_movements(self):\n return self.total_movements\n\n def add_person(self, person):\n self.population.add(person)\n\n def incubate_cycle(self, current_time_o):\n ''' Process local population at a place and yield a new cycle of infections '''\n\n # set recovered timedelta(days=1): set time_to_recover, current_time\n infected_pop = [p for p in self.population if p.get_status() == 1]\n recovered_pop = [p.set_immune(current_time_o) for p in infected_pop if\n current_time_o - p.get_time_infected() > timedelta(days=self.time_to_recover)]\n infected_pop = set(infected_pop).difference(recovered_pop) # infected pop - recovered\n # print (len(infected_pop))\n # print (len(recovered_pop))\n # print (len(self.population))\n # print ('----')\n\n # calculate number of infected people\n total_infected = len(infected_pop)\n # if total_infected == 0:\n # \t#if there is no infected person at place, no one else can be infected (ie do not execute code below)\n # \treturn\n\n total_pop = len(self.population)\n\n # calculate susceptible to infection\n susceptible_pop = self.population.difference(infected_pop)\n susceptible_pop = susceptible_pop.difference(self.immune_population)\n self.immune_population = self.immune_population.union(recovered_pop)\n\n # calculate probability of infection\n if total_pop == 0:\n prob_infection = 0.0\n else:\n prob_infection = total_infected / total_pop\n\n # calculate newly infected number\n newly_infected_num = int(len(susceptible_pop) * prob_infection)\n\n # set newly infected persons accordingly\n newly_infected_pop = random.choices(tuple(susceptible_pop), k=newly_infected_num)\n for i in range(newly_infected_num):\n newly_infected_pop[i].set_infected(current_time_o)\n\n # count number infected\n self.total_infected_number = len(infected_pop) + newly_infected_num\n\n def set_recovered(self):\n ''' Process local population and yield a new cycle of recoveries (death case will be added later)'''\n pass\n","sub_path":"Place.py","file_name":"Place.py","file_ext":"py","file_size_in_byte":3342,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"622662040","text":"import pylab\n\npylab.figure('Temperature_Graph')\npylab.title('Boston July Temperatures')\npylab.xlabel('Day')\npylab.ylabel('Temperature')\ndates = []\nhigh = []\nlow = []\nfileline =[]\nwith open('BostonJulyTemperatures.txt', 'r') as file:\n\tfile.readline()\n\tfor line in file:\n\t\tfileline = line.split()\n\t\tdates.append(int(fileline[0]))\n\t\thigh.append(int(fileline[1]))\n\t\tlow.append(int(fileline[2]))\nfile.close()\ncount = 0\nfor date in dates:\n\tpylab.plot([date,date],[low[count], high[count]])\n\tcount = count + 1\npylab.show()","sub_path":"temperature.py","file_name":"temperature.py","file_ext":"py","file_size_in_byte":515,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"9320961","text":"\"\"\"\nUnicorn core.logutils module\nUnicorn module which provides common logging functions. \nIn order to initialize logger function init_logger should be used.\n\"\"\"\n\nimport sys\nimport os\nimport logging\nimport copy\nimport shutil\nimport re\nfrom datetime import datetime\nfrom threading import Lock\n\ntry:\n from core import logutils_conversions\n from core import environment_preparation\nexcept ImportError:\n import logutils_conversions\n import environment_preparation\n\ntry:\n import colorama\nexcept ImportError as e:\n colorama = None\nelse:\n colorama.init() \n\nloglock = Lock()\n \n# PATCHING CUSTOM LEVELS\nlogging.H1 = 99\nlogging.H2 = 98\nlogging.H3 = 97\nlogging.PLAIN = 29\nlogging.FRAME = 28\nlogging.TABLE = 27\nlogging.VERBOSE = 21\n\nlevel_styles = {}\nmessage_styles = {}\n\n\n\n# ==============================================================================\nclass EnhancedLogger(logging.getLoggerClass()):\n \"\"\"\n Logger class with additional methods / log levels.\n \"\"\"\n def __init__(self, name, level = logging.NOTSET):\n super().__init__(name, level)\n logging.addLevelName(logging.H1, \"H1\")\n logging.addLevelName(logging.H2, \"H2\")\n logging.addLevelName(logging.H3, \"H3\")\n logging.addLevelName(logging.TABLE, \"TABLE\")\n logging.addLevelName(logging.FRAME, \"FRAME\")\n logging.addLevelName(logging.PLAIN, \"PLAIN\")\n logging.addLevelName(logging.VERBOSE, \"VERBOSE\")\n \n def h1(self, msg, *args, **kwargs):\n if self.isEnabledFor(logging.H1):\n msg = logutils_conversions._string_to_h1(msg)\n self._log(logging.H1, msg, args, **kwargs)\n \n def h2(self, msg, *args, **kwargs):\n if self.isEnabledFor(logging.H2):\n msg = logutils_conversions._string_to_h2(msg)\n self._log(logging.H2, msg, args, **kwargs)\n \n def h3(self, msg, *args, **kwargs):\n if self.isEnabledFor(logging.H3):\n msg = logutils_conversions._string_to_h3(msg)\n self._log(logging.H3, msg, args, **kwargs)\n \n def table(self, msg, *args, **kwargs):\n if self.isEnabledFor(logging.TABLE):\n msg = logutils_conversions._table_to_string(msg)\n self._log(logging.TABLE, msg, args, **kwargs)\n \n def frame(self, msg, *args, **kwargs):\n if self.isEnabledFor(logging.FRAME):\n msg = logutils_conversions._string_to_framed_string(msg)\n self._log(logging.FRAME, msg, args, **kwargs)\n \n def com(self, msg, *args, **kwargs):\n if self.isEnabledFor(logging.PLAIN):\n self._log(logging.PLAIN, msg, args, **kwargs)\n \n def comment(self, msg, *args, **kwargs):\n if self.isEnabledFor(logging.PLAIN):\n self._log(logging.PLAIN, msg, args, **kwargs)\n \n def plain(self, msg, *args, **kwargs):\n if self.isEnabledFor(logging.PLAIN):\n self._log(logging.PLAIN, msg, args, **kwargs)\n \n def verbose(self, msg, *args, **kwargs):\n if self.isEnabledFor(logging.VERBOSE):\n msg = logutils_conversions._verbose_message_to_string(msg)\n self._log(logging.VERBOSE, msg, args, **kwargs)\n\n def configure(self, log_config={}, file=\"\"):\n \"\"\"\n Common function which initializes logger, makes target log directories and creates file.\n Args:\n name (String) - name of the logger\n log_config (dict) - optional - configuration for the logger. New entries will override default configuration.\n file (String) - optional - fixed path to the logfile\n Returns:\n logging object\n \"\"\"\n\n # TODO function that initialize default values\n log_c = {\n \"log_fmt\": \"%(asctime)-16s - %(levelname)-8s - %(message)s\",\n \"log_path\": \"\",\n \"log_colors\": True,\n \"log_default_font\": \"\",\n \"log_default_back\": \"\",\n \"log_default_style\": \"\",\n \"log_debug_font\": \"white\",\n \"log_debug_back\": \"\",\n \"log_debug_style\": \"\",\n \"log_info_font\": \"green\",\n \"log_info_back\": \"\",\n \"log_info_style\": \"bright\",\n \"log_warning_font\": \"yellow\",\n \"log_warning_back\": \"\",\n \"log_warning_style\": \"bright\",\n \"log_error_font\": \"red\",\n \"log_error_back\": \"\",\n \"log_error_style\": \"bright\",\n \"log_critical_font\": \"white\",\n \"log_critical_back\": \"red\",\n \"log_critical_style\": \"bright\",\n \"log_header_font\": \"cyan\",\n \"log_header_back\": \"\",\n \"log_header_style\": \"bright\",\n \"log_verbose_font\": \"magenta\",\n \"log_verbose_back\": \"\",\n \"log_verbose_style\": \"bright\",\n \"log_strong_font\": \"yellow\",\n \"log_strong_back\": \"black\",\n \"log_strong_style\": \"\",\n \"log_send_font\": \"cyan\",\n \"log_send_back\": \"\",\n \"log_send_style\": \"bright\",\n \"log_receive_font\": \"yellow\",\n \"log_receive_back\": \"\",\n \"log_receive_style\": \"bright\",\n \"log_file_max_size\": \"0\",\n \"log_file_max_count\": \"0\",\n \"log_width\": 120,\n \"test_file\": \"\",\n \"file\": \"\" }\n log_c.update(log_config)\n logutils_conversions.LINE_WIDTH = log_c[\"log_width\"]\n if any(sub in str(log_c[\"log_colors\"]).lower() for sub in [\"1\", \"enable\", \"true\", \"yes\"]):\n log_c[\"log_colors\"] = True\n\n # TODO move to function close handlers\n handlers = self.handlers[:]\n for hdlr in handlers:\n hdlr.close()\n self.removeHandler(hdlr)\n\n # TODO move to function set logging level, it would be good to use configuration parameter instead of directly parsing sys.argv\n if any(\"debug\" in ar.lower() for ar in sys.argv):\n level_to_set = logging.DEBUG\n else:\n level_to_set = logging.INFO\n self.setLevel(logging.DEBUG)\n self.propagate = 0\n\n # TODO move to function set formatter\n fmt = log_c[\"log_fmt\"]\n\n if colorama and log_c[\"log_colors\"] is True:\n handler = ColorStreamHandler(sys.stdout)\n cc_fmt = ColorFormatter(fmt)\n cc_fmt.configure(log_c)\n handler.setFormatter(cc_fmt)\n else:\n handler = logging.StreamHandler()\n c_fmt = CustomFormatter(fmt)\n handler.setFormatter(c_fmt)\n handler.setLevel(level_to_set)\n self.addHandler(handler)\n timestamp = datetime.now().strftime(\"%Y-%m-%d_%H.%M.%S\")\n\n # TODO move to function set file handler\n log_dir_path = \"\"\n log_file_path = \"\"\n if log_c[\"log_path\"] and log_c[\"test_file\"]:\n log_dir_path = log_c[\"log_path\"]\n if os.path.isabs(log_dir_path): pass\n else: \n log_dir_path = os.path.realpath(os.path.join(os.path.dirname(__file__), \"..\", log_dir_path))\n testname = os.path.basename(log_c[\"test_file\"])\n try:\n testname = os.path.splitext(testname)[0]\n except Exception as e:\n print(\"Could not remove extension from file named: {}. Skipping.\".format(testname))\n log_dir_name = \"{}_{}\".format(testname, timestamp)\n log_dir_path = os.path.realpath(os.path.join(log_c[\"log_path\"], log_dir_name))\n log_file_name = \"{}_{}_{}.log\".format(testname, timestamp, self.name)\n log_file_path = os.path.join(log_dir_path, log_file_name)\n elif file:\n log_dir_path = os.path.dirname(file)\n log_file_path = file\n if log_dir_path and not os.path.exists(log_dir_path):\n try:\n os.makedirs(log_dir_path)\n except Exception as ex:\n print(\"ERROR: Log directory {} could not be created\".format(log_dir_path))\n print(\n \"Please ensure that\\n\\t\\\"{}\\\"\\ndirectory exists or Unicorn has sufficient rights to create it.\".format(\n log_dir_path))\n raise ex from None\n\n if log_c[\"log_path\"] and file and os.path.isfile(file):\n shutil.copyfile(file, log_file_path)\n os.remove(file)\n\n if log_file_path:\n lfmc_text = str(log_c[\"log_file_max_size\"]).upper()\n lfmc_num = int(''.join(str(d) for d in [int(s) for s in list(lfmc_text) if s.isdigit()]))\n if lfmc_text.endswith(\"MB\") or lfmc_text.endswith(\"M\"):\n log_c[\"log_file_max_size\"] = lfmc_num * 1024 * 1024\n elif lfmc_text.endswith(\"KB\") or lfmc_text.endswith(\"K\"):\n log_c[\"log_file_max_size\"] = lfmc_num * 1024\n else:\n log_c[\"log_file_max_size\"] = lfmc_num\n if log_file_path:\n f_fmt = CustomFormatter(fmt)\n if log_c[\"log_file_max_size\"] > 0:\n from logging.handlers import RotatingFileHandler\n fh = RotatingFileHandler(log_file_path, maxBytes=log_c[\"log_file_max_size\"],\n backupCount=int(log_c[\"log_file_max_count\"]) )\n else:\n fh = logging.FileHandler(log_file_path)\n fh.setLevel(logging.DEBUG)\n fh.setFormatter(f_fmt)\n self.addHandler(fh)\n return self\n\n def close(self):\n \"\"\"\n Function to remove handlers and shut down the logger\n Args:\n logger (logger object)\n Returns:\n None\n \"\"\"\n try:\n handlers = self.handlers[:]\n for handler in handlers:\n handler.close()\n self.removeHandler(handler)\n del self\n except Exception as ex:\n pass \n\n\nclass ColorStreamHandler(logging.StreamHandler):\n \"\"\"\n StreamHandler with customized color output.\n \"\"\"\n def __init__(self, *args, **kwargs):\n super().__init__(*args, **kwargs)\n def emit(self, record):\n try:\n loglock.acquire()\n message = self.format(record)\n self.stream.write(message)\n self.stream.write(getattr(self, 'terminator', '\\n'))\n self.flush()\n except (KeyboardInterrupt, SystemExit) as e:\n raise e\n except Exception:\n self.handleError(record)\n finally:\n loglock.release()\n\nclass CustomFormatter(logging.Formatter):\n \"\"\"\n Formatter which selects modified log formats depending on the message LEVEL\n \"\"\"\n def __init__(self, fmt):\n self.general_fmt = \"%(asctime)-16s - %(levelname)-8s - %(message)s\"\n self.plain_fmt = \"%(asctime)-16s - %(message)s\"\n self.no_fmt = \"%(message)s\"\n # self.verbose_fmt = \"%(asctime)-16s - [ Logged from: %(module)s; line: %(lineno)d ]:\\n %(msg)s\"\n self.verbose_fmt = \"\\n %(msg)s\"\n if fmt: \n self.general_fmt = fmt\n super().__init__(fmt = self.general_fmt)\n\n def format(self, record, *args, **kwargs):\n new_record = copy.copy(record)\n format_orig = self._style._fmt\n if new_record.levelno == logging.DEBUG:\n self._style._fmt = self.general_fmt\n elif new_record.levelno == logging.INFO:\n self._style._fmt = self.general_fmt\n elif new_record.levelno == logging.WARNING or new_record.levelno == logging.WARN:\n self._style._fmt = self.general_fmt\n elif new_record.levelno == logging.ERROR or new_record.levelno == logging.CRITICAL:\n self._style._fmt = self.general_fmt\n elif new_record.levelno == logging.H1:\n self._style._fmt = self.no_fmt\n elif new_record.levelno == logging.H2:\n self._style._fmt = self.plain_fmt\n elif new_record.levelno == logging.H3:\n self._style._fmt = self.plain_fmt \n elif new_record.levelno == logging.TABLE:\n self._style._fmt = self.no_fmt\n elif new_record.levelno == logging.FRAME:\n self._style._fmt = self.no_fmt\n elif new_record.levelno == logging.PLAIN:\n self._style._fmt = self.plain_fmt \n elif new_record.levelno == logging.VERBOSE:\n self._style._fmt = self.verbose_fmt\n else:\n self._style._fmt = self.no_fmt\n result = logging.Formatter.format(self, new_record)\n self._style._fmt = format_orig\n return result\n\n\nclass ColorFormatter(CustomFormatter):\n \"\"\"\n Formatter which adds colors to messages going to the screen depending on message LEVEL\n \"\"\"\n def __init__(self, *args, **kwargs):\n super().__init__(*args, **kwargs)\n self.color_send = \"\"\n self.color_receive = \"\"\n self.color_strong = \"\"\n self.regex_send = re.compile(\"(.*?\\|.?\\-\\-\\>.*?\\|.)(.*)\", re.IGNORECASE | re.MULTILINE)\n self.regex_receive = re.compile(\"(.*?\\|.?\\<\\-\\-.*?\\|.)(.*)\", re.IGNORECASE | re.MULTILINE)\n self.regex_strong = re.compile(\"\\[(.*)\\]\", re.IGNORECASE | re.MULTILINE)\n\n def create_color_entry(self, colorama_assignments, style_name_lowercase):\n \"\"\"Method which assigns colorama style basing on global configuration stored in self.log_conf, \n styles dictionary colorama_dict and name of the style defined in style_name_lowercase\n self.log_conf - generated framework configuration for the logs (all parameters with log_ prefix) \n - taken from global config file, local config file, command line args and default settings.\n Args:\n colorama_assignments(dict) - assignments of logging level and colorama style\n style_name_lowercase(string) - value of configuration parameter. e.g. yellow\n Returns:\n colorama style(colorama attribute) - e.g. colorama.Style.BRIGHT\"\"\"\n try:\n log_param_value = self.log_conf[style_name_lowercase]\n except KeyError as e:\n log_param_value = \"\"\n try:\n return colorama_assignments[log_param_value]\n except (KeyError, Exception) as e:\n print(\"WARNING: Style or color name \\\"{}\\\" for {} was not recognized. Empty value will be used.\".format(log_param_value, style_name_lowercase))\n return \"\" \n \n def configure(self, log_conf):\n \"\"\"\n Method to set configuration of ColorFormatter from dictionary with log_ parameters.\n Args:\n log_conf(dictionary): configuration of the logger, keys are prefixed with log_\n Returns:\n None\n \"\"\"\n self.log_conf = log_conf\n self.level_styles = {\n logging.DEBUG: colorama.Style.BRIGHT + colorama.Fore.WHITE,\n logging.INFO: colorama.Style.BRIGHT + colorama.Fore.GREEN,\n logging.WARN: colorama.Style.BRIGHT + colorama.Fore.YELLOW,\n logging.WARNING: colorama.Style.BRIGHT + colorama.Fore.YELLOW,\n logging.ERROR: colorama.Style.BRIGHT + colorama.Fore.RED,\n logging.CRITICAL: colorama.Style.BRIGHT + colorama.Back.RED + colorama.Fore.WHITE\n }\n self.message_styles = {\n logging.DEBUG: colorama.Style.BRIGHT + colorama.Fore.WHITE,\n logging.INFO: colorama.Style.BRIGHT + colorama.Fore.GREEN,\n logging.WARN: colorama.Style.BRIGHT + colorama.Fore.YELLOW,\n logging.WARNING: colorama.Style.BRIGHT + colorama.Fore.YELLOW,\n logging.ERROR: colorama.Style.BRIGHT + colorama.Fore.RED,\n logging.CRITICAL: colorama.Style.BRIGHT + colorama.Back.RED + colorama.Fore.WHITE,\n logging.H1: colorama.Style.BRIGHT + colorama.Fore.CYAN,\n logging.H2: colorama.Style.BRIGHT + colorama.Fore.CYAN,\n logging.H3: colorama.Style.BRIGHT + colorama.Fore.CYAN,\n logging.VERBOSE: colorama.Style.BRIGHT + colorama.Fore.MAGENTA,\n logging.FRAME: \"\",\n logging.TABLE: \"\",\n logging.PLAIN: \"\"\n }\n self.colorama_styles = {\n \"bright\": colorama.Style.BRIGHT,\n \"dim\": colorama.Style.DIM,\n \"none\": \"\",\n \"\": \"\"\n } \n self.colorama_backgrounds = {\n \"red\": colorama.Back.RED,\n \"white\": colorama.Back.WHITE,\n \"green\": colorama.Back.GREEN,\n \"yellow\": colorama.Back.YELLOW,\n \"blue\": colorama.Back.BLUE,\n \"cyan\": colorama.Back.CYAN,\n \"magenta\": colorama.Back.MAGENTA,\n \"black\": colorama.Back.BLACK,\n \"\": \"\"\n } \n self.colorama_fonts = {\n \"red\": colorama.Fore.RED,\n \"white\": colorama.Fore.WHITE,\n \"green\": colorama.Fore.GREEN,\n \"yellow\": colorama.Fore.YELLOW,\n \"blue\": colorama.Fore.BLUE,\n \"cyan\": colorama.Fore.CYAN,\n \"magenta\": colorama.Fore.MAGENTA,\n \"black\": colorama.Fore.BLACK,\n \"\": \"\"\n }\n self.message_styles = {\n logging.DEBUG: self.create_color_entry(self.colorama_styles, \"log_debug_style\") \\\n + self.create_color_entry(self.colorama_backgrounds, \"log_debug_back\") \\\n + self.create_color_entry(self.colorama_fonts, \"log_debug_font\"),\n logging.INFO: self.create_color_entry(self.colorama_styles, \"log_info_style\") \\\n + self.create_color_entry(self.colorama_backgrounds, \"log_info_back\") \\\n + self.create_color_entry(self.colorama_fonts, \"log_info_font\"),\n logging.WARN: self.create_color_entry(self.colorama_styles, \"log_warning_style\") \\\n + self.create_color_entry(self.colorama_backgrounds, \"log_warning_back\") \\\n + self.create_color_entry(self.colorama_fonts, \"log_warning_font\"),\n logging.WARNING: self.create_color_entry(self.colorama_styles, \"log_warning_style\") \\\n + self.create_color_entry(self.colorama_backgrounds, \"log_warning_back\") \\\n + self.create_color_entry(self.colorama_fonts, \"log_warning_font\"),\n logging.ERROR: self.create_color_entry(self.colorama_styles, \"log_error_style\") \\\n + self.create_color_entry(self.colorama_backgrounds, \"log_error_back\") \\\n + self.create_color_entry(self.colorama_fonts, \"log_error_font\"),\n logging.CRITICAL: self.create_color_entry(self.colorama_styles, \"log_critical_style\") \\\n + self.create_color_entry(self.colorama_backgrounds, \"log_critical_back\") \\\n + self.create_color_entry(self.colorama_fonts, \"log_critical_font\"),\n logging.H1: self.create_color_entry(self.colorama_styles, \"log_header_style\") \\\n + self.create_color_entry(self.colorama_backgrounds, \"log_header_back\") \\\n + self.create_color_entry(self.colorama_fonts, \"log_header_font\"),\n logging.H2: self.create_color_entry(self.colorama_styles, \"log_header_style\") \\\n + self.create_color_entry(self.colorama_backgrounds, \"log_header_back\") \\\n + self.create_color_entry(self.colorama_fonts, \"log_header_font\"), \n logging.H3: self.create_color_entry(self.colorama_styles, \"log_header_style\") \\\n + self.create_color_entry(self.colorama_backgrounds, \"log_header_back\") \\\n + self.create_color_entry(self.colorama_fonts, \"log_header_font\"), \n logging.VERBOSE: self.create_color_entry(self.colorama_styles, \"log_verbose_style\") \\\n + self.create_color_entry(self.colorama_backgrounds, \"log_verbose_back\") \\\n + self.create_color_entry(self.colorama_fonts, \"log_verbose_font\") \n }\n self.level_styles = dict(self.message_styles)\n self.color_send = self.create_color_entry(self.colorama_styles, \"log_send_style\") \\\n + self.create_color_entry(self.colorama_backgrounds, \"log_send_back\") \\\n + self.create_color_entry(self.colorama_fonts, \"log_send_font\")\n self.color_receive = self.create_color_entry(self.colorama_styles, \"log_receive_style\") \\\n + self.create_color_entry(self.colorama_backgrounds, \"log_receive_back\") \\\n + self.create_color_entry(self.colorama_fonts, \"log_receive_font\")\n self.color_strong = self.create_color_entry(self.colorama_styles, \"log_strong_style\") \\\n + self.create_color_entry(self.colorama_backgrounds, \"log_strong_back\") \\\n + self.create_color_entry(self.colorama_fonts, \"log_strong_font\")\n \n def _apply_special_styles(self, message):\n \"\"\"\n Method to apply special style to the message which matches expected format (based on regex search).\n It is called from \"format\" method\n It returns same message if no special match is found.\n Args:\n message (String): log entry to add the style\n Returns:\n message (String): colorized log entry\n \"\"\"\n if self.regex_send.search(message):\n return self.regex_send.sub(\"\\\\1\" + self.color_send + \"\\\\2\" + colorama.Style.RESET_ALL, str(message))\n elif self.regex_receive.search(message):\n return self.regex_receive.sub(\"\\\\1\" + self.color_receive + \"\\\\2\" + colorama.Style.RESET_ALL, str(message))\n elif self.regex_strong.search(message):\n return self.regex_strong.sub(self.color_strong + \"[\\\\1]\" + colorama.Style.RESET_ALL, str(message))\n else:\n return message\n\n def format(self, record, *args, **kwargs):\n \"\"\"\n Method to apply all color formats basing on self.level_styles and self.message_styles dictionaries.\n Args:\n record (String): log entry to add the style\n Returns:\n result (String): formatted log entry\n \"\"\" \n new_record = copy.copy(record) \n if isinstance(new_record.msg, str) and new_record.levelno == logging.PLAIN:\n new_record.msg = self._apply_special_styles(new_record.msg) \n if new_record.levelno in self.level_styles:\n new_record.levelname = \"{color_begin}{level}{color_end}\".format(\n color_begin = self.level_styles[new_record.levelno],\n level = new_record.levelname,\n color_end = colorama.Style.RESET_ALL,\n ) \n if new_record.levelno in self.message_styles:\n new_record.msg = \"{color_begin}{msg}{color_end}\".format(\n color_begin = self.message_styles[new_record.levelno],\n msg = new_record.msg,\n color_end = colorama.Style.RESET_ALL,\n )\n result = super(ColorFormatter, self).format(new_record, *args, **kwargs)\n return result\n\nlogging.setLoggerClass(EnhancedLogger)\n \n\ndef init_logger(name = \"log\", log_config = {}, file = \"\"): \n \"\"\"\n External function which initializes logger, makes target log directories and creates file.\n Args:\n name (String) - name of the logger\n log_config (dict) - optional - configuration for the logger. New entries will override default configuration.\n file (String) - optional - fixed path to the logfile\n Returns:\n logging object\n \"\"\"\n logger = logging.getLogger(name)\n logger.configure(log_config, file)\n return logger\n \n\nif __name__ == \"__main__\":\n\n logger = init_logger(\"test\")\n logger = init_logger(\"test\")\n\n logger.debug(\"This is a debug!\")\n logger.info(\"This is an info!\")\n logger.warning(\"This is a warning!\")\n logger.error(\"This is an error!\")\n logger.critical(\"This is a critical!\")\n\n logger.h1(\"1. Header\")\n logger.h2(\"1.1. Header\")\n logger.h3(\"1.1.1 Header\")\n\n logger.table([[\"Name\", \"Value\"],[1,2],[10,20],[30,40]])\n logger.com(\"Path [ AAA ] format\")\n logger.com(\"| --> D | Send format\")\n logger.com(\"| <-- D | Receive format\")\n logger.verbose([\n \"This is a long message\",\n \"which explains in details\",\n \"what is going on here\"\n ])\n logger.frame(\"Used for generic messages which should be emphasized\")\n logger.frame(\"Used for generic messages which should be emphasized\\n - like communication with the module\")\n logger.frame([\n \"Used for generic messages which should be emphasized\",\n \"- like communication with the module\"])\n try:\n i = 3/0\n except Exception as e:\n logger.verbose(\"You tried to do action which is not allowed. Handling exception.\")\n logger.info(\"[ c:\\\\temp ]\")\n","sub_path":"unicorn_core/logutils.py","file_name":"logutils.py","file_ext":"py","file_size_in_byte":24390,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"533821563","text":"from seal import *\nfrom seal_helper import *\n\n\ndef example_rotation_bfv():\n print_example_banner(\"Example: Rotation / Rotation in BFV\")\n parms = EncryptionParameters(scheme_type.BFV)\n\n poly_modulus_degree = 8192\n parms.set_poly_modulus_degree(poly_modulus_degree)\n parms.set_coeff_modulus(CoeffModulus.BFVDefault(poly_modulus_degree))\n parms.set_plain_modulus(PlainModulus.Batching(poly_modulus_degree, 20))\n\n context = SEALContext.Create(parms)\n print_parameters(context)\n print(\"-\" * 50)\n\n keygen = KeyGenerator(context)\n public_key = keygen.public_key()\n secret_key = keygen.secret_key()\n relin_keys = keygen.relin_keys()\n\n encryptor = Encryptor(context, public_key)\n evaluator = Evaluator(context)\n decryptor = Decryptor(context, secret_key)\n\n batch_encoder = BatchEncoder(context)\n slot_count = batch_encoder.slot_count()\n row_size = int(slot_count / 2)\n print(\"Plaintext matrix row size: \" + str(row_size))\n\n pod_matrixs = [0] * slot_count\n pod_matrixs[0] = 0\n pod_matrixs[1] = 1\n pod_matrixs[2] = 2\n pod_matrixs[3] = 3\n pod_matrixs[row_size] = 4\n pod_matrixs[row_size + 1] = 5\n pod_matrixs[row_size + 2] = 6\n pod_matrixs[row_size + 3] = 7\n\n pod_matrix = uIntVector()\n for i in range(slot_count):\n pod_matrix.push_back(pod_matrixs[i])\n\n print(\"Input plaintext matrix:\")\n print_matrix(pod_matrix, row_size)\n\n '''\n\tFirst we use BatchEncoder to encode the matrix into a plaintext. We encrypt\n \tthe plaintext as usual.\n\t'''\n plain_matrix = Plaintext()\n print(\"-\" * 50)\n print(\"Encode and encrypt.\")\n batch_encoder.encode(pod_matrix, plain_matrix)\n encrypted_matrix = Ciphertext()\n encryptor.encrypt(plain_matrix, encrypted_matrix)\n print(\" + Noise budget in fresh encryption: \" +\n str(decryptor.invariant_noise_budget(encrypted_matrix)) + \" bits\")\n\n '''\n\tRotations require yet another type of special key called `Galois keys'. These\n \tare easily obtained from the KeyGenerator.\n\t'''\n gal_keys = keygen.galois_keys()\n '''\n\tNow rotate both matrix rows 3 steps to the left, decrypt, decode, and print.\n\t'''\n print(\"-\" * 50)\n print(\"Rotate rows 3 steps left.\")\n\n evaluator.rotate_rows_inplace(encrypted_matrix, 3, gal_keys)\n plain_result = Plaintext()\n print(\" + Noise budget after rotation: \" +\n str(decryptor.invariant_noise_budget(encrypted_matrix)) + \" bits\")\n print(\" + Decrypt and decode ...... Correct.\")\n decryptor.decrypt(encrypted_matrix, plain_result)\n batch_encoder.decode(plain_result, pod_matrix)\n print_matrix(pod_matrix, row_size)\n\n '''\n We can also rotate the columns, i.e., swap the rows.\n '''\n print(\"-\" * 50)\n print(\"Rotate columns.\")\n evaluator.rotate_columns_inplace(encrypted_matrix, gal_keys)\n print(\" + Noise budget after rotation: \" +\n str(decryptor.invariant_noise_budget(encrypted_matrix)) + \" bits\")\n print(\" + Decrypt and decode ...... Correct.\")\n decryptor.decrypt(encrypted_matrix, plain_result)\n batch_encoder.decode(plain_result, pod_matrix)\n print_matrix(pod_matrix, row_size)\n\n '''\n Finally, we rotate the rows 4 steps to the right, decrypt, decode, and print.\n '''\n print(\"-\" * 50)\n print(\"Rotate rows 4 steps right.\")\n evaluator.rotate_rows_inplace(encrypted_matrix, -4, gal_keys)\n print(\" + Noise budget after rotation: \" +\n str(decryptor.invariant_noise_budget(encrypted_matrix)) + \" bits\")\n print(\" + Decrypt and decode ...... Correct.\")\n decryptor.decrypt(encrypted_matrix, plain_result)\n batch_encoder.decode(plain_result, pod_matrix)\n print_matrix(pod_matrix, row_size)\n\n '''\n Note that rotations do not consume any noise budget. However, this is only\n the case when the special prime is at least as large as the other primes. The\n same holds for relinearization. Microsoft SEAL does not require that the\n special prime is of any particular size, so ensuring this is the case is left\n for the user to do.\n '''\n\n\ndef example_rotation_ckks():\n print_example_banner(\"Example: Rotation / Rotation in CKKS\")\n parms = EncryptionParameters(scheme_type.CKKS)\n poly_modulus_degree = 8192\n parms.set_poly_modulus_degree(poly_modulus_degree)\n parms.set_coeff_modulus(CoeffModulus.Create(\n poly_modulus_degree, [40, 40, 40, 40, 40]))\n context = SEALContext.Create(parms)\n print_parameters(context)\n\n keygen = KeyGenerator(context)\n public_key = keygen.public_key()\n secret_key = keygen.secret_key()\n relin_keys = keygen.relin_keys()\n gal_keys = keygen.galois_keys()\n\n encryptor = Encryptor(context, public_key)\n evaluator = Evaluator(context)\n decryptor = Decryptor(context, secret_key)\n\n ckks_encoder = CKKSEncoder(context)\n slot_count = ckks_encoder.slot_count()\n print(\"Number of slots: \" + str(slot_count))\n # inputer = [0] * slot_count\n inputs = DoubleVector()\n curr_point = 0.0\n step_size = 1.0 / (slot_count - 1)\n\n for i in range(slot_count):\n inputs.push_back(curr_point)\n curr_point += step_size\n\n print(\"Input vector:\")\n print_vector(inputs, 3, 7)\n\n scale = pow(2.0, 50)\n\n print(\"-\" * 50)\n print(\"Encode and encrypt.\")\n plain = Plaintext()\n\n ckks_encoder.encode(inputs, scale, plain)\n encrypted = Ciphertext()\n encryptor.encrypt(plain, encrypted)\n\n rotated = Ciphertext()\n print(\"-\" * 50)\n print(\"Rotate 2 steps left.\")\n evaluator.rotate_vector(encrypted, 2, gal_keys, rotated)\n print(\" + Decrypt and decode ...... Correct.\")\n decryptor.decrypt(rotated, plain)\n result = DoubleVector()\n ckks_encoder.decode(plain, result)\n print_vector(result, 3, 7)\n\n '''\n With the CKKS scheme it is also possible to evaluate a complex conjugation on\n a vector of encrypted complex numbers, using Evaluator::complex_conjugate.\n This is in fact a kind of rotation, and requires also Galois keys.\n '''\n\n\nif __name__ == '__main__':\n print_example_banner(\"Example: Rotation\")\n\n example_rotation_bfv()\n # example_rotation_ckks()\n","sub_path":"tests/5_rotation.py","file_name":"5_rotation.py","file_ext":"py","file_size_in_byte":6135,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"176762850","text":"#!/usr/local/bin/python3\n# -*- coding: utf-8 -*-\n# 412 Fizz Buzz\n\n__author__ = 'Libao Jin'\n__date__ = '02/04/2017'\n\nimport time\n\nclass Solution(object):\n def fizzBuzz(self, n):\n '''\n :type n: int\n :rtype: List[str]\n '''\n i = 1\n fb = []\n while i <= n:\n if i % 3 == 0 and i % 5 == 0:\n fb.append('FizzBuzz')\n elif i % 3 == 0:\n fb.append('Fizz')\n elif i % 5 == 0:\n fb.append('Buzz')\n else:\n fb.append(str(i))\n i += 1\n return fb\n\n def test(self):\n start_time = time.time()\n result = self.fizzBuzz(15)\n end_time = time.time()\n print(result)\n print('Elapsed time: {0:.6f}'.format(end_time - start_time))\n\nif __name__ == '__main__':\n s = Solution()\n s.test()\n","sub_path":"solutions/412_Fizz_Buzz.py","file_name":"412_Fizz_Buzz.py","file_ext":"py","file_size_in_byte":869,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"125428796","text":"import pdb\nimport sys\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport numpy as np\n\nsys.path.append(\"..\")\nfrom utils.misc import ixvr\n\nclass AttendFeedForward(nn.Module):\n\t\"\"\"\n\tSimiliar to the attend (Section 3.1) module of the DecAtt paper\n\t\"\"\"\n\tdef __init__(self, inp_size, hidden_size=200):\n\t\tsuper(AttendFeedForward, self).__init__()\n\n\t\tself.hidden_size = hidden_size\n\t\tself.linear = nn.Sequential( \\\n\t\t\tnn.Linear(inp_size, hidden_size), \\\n\t\t\tnn.ReLU(), \\\n\t\t\tnn.BatchNorm1d(num_features=hidden_size), \\\n\t\t\tnn.Linear(hidden_size, hidden_size), \\\n\t\t\tnn.ReLU(), \\\n\t\t\tnn.BatchNorm1d(num_features=hidden_size))\n\n\tdef forward(self, s1, s2, mask1, mask2):\n\t\t\"\"\"\n\t\tArgs:\n\t\t\ts1: Sentence 1 BiLSTM embeddings (b x LA x inp_size)\n\t\t\ts2: Sentence 2 BiLSTM embeddings (b x LB x inp_size)\n\t\t\tmask1: Sentence 1 mask (b x LA)\n\t\t\tmask2: Sentence 2 mask (b x LB)\n\t\tOutput:\n\t\t\talphas: Soft aligned combinations of s1 w.r.t. s2 tokens (b x maxlen x inp_size)\n\t\t\tbetas: Soft aligned combinations of s2 w.r.t. s1 tokens (b x maxlen x inp_size)\n\t\t\"\"\"\n\t\tbatch_size = s1.shape[0]\n\t\tmaxlen = s1.shape[1]\n\t\tinp_size = s1.shape[2]\n\n\t\th1 = self.linear(s1.view(-1, inp_size)).view(batch_size, maxlen, -1)\n\t\t# b x LA x hidden_size\n\t\th2 = self.linear(s2.view(-1, inp_size)).view(batch_size, maxlen, -1)\n\t\t# b x LB x hidden_size\n\t\th2t = torch.transpose(h2, 1, 2)\n\t\t# b x hidden_size x LB\n\n\t\te = torch.bmm(h1, h2t)\n\n\t\te_alpha = torch.mul(e, mask1.unsqueeze(-1))\n\t\te_alpha = torch.exp(e_alpha - torch.max(e_alpha, dim=1)[0].unsqueeze(1))\n\t\te_alpha = torch.div(e_alpha, torch.sum(e_alpha, dim=1).unsqueeze(1))\n\t\t# b x LA x LB\n\n\t\te_beta = torch.mul(e, mask2.unsqueeze(1))\n\t\te_beta = torch.exp(e_beta - torch.max(e_beta, dim=2)[0].unsqueeze(-1))\n\t\te_beta = torch.div(e_beta, torch.sum(e_beta, dim=2).unsqueeze(-1))\n\t\t# b x LA x LB\n\n\t\talphas = torch.bmm(torch.transpose(e_alpha, 1, 2), s1)\n\t\talphas = torch.mul(alphas, mask2.unsqueeze(-1))\n\t\t# b x LB x inp_size\n\t\tbetas = torch.bmm(e_beta, s2)\n\t\tbetas = torch.mul(betas, mask1.unsqueeze(-1))\n\t\t# b x LA x inp_size\n\n\t\treturn alphas, betas\n\nclass CompareFeedForward(nn.Module):\n\t\"\"\"\n\tSimilar to the compare (Section 3.2) module of the DecAtt paper\n\texcept instead of returning the sum of the embeddings v1 and v2\n\t(which might be susceptible to the length of the sequence),\n\tthis returns v1_avg, v1_max, v2_avg, v2_max.\n\t\"\"\"\n\tdef __init__(self, inp_size, hidden_size=200):\n\t\tsuper(CompareFeedForward, self).__init__()\n\n\t\tself.linear = nn.Sequential( \\\n\t\t\tnn.Linear(inp_size * 2, hidden_size), \\\n\t\t\tnn.ReLU(), \\\n\t\t\tnn.BatchNorm1d(num_features=hidden_size), \\\n\t\t\tnn.Linear(hidden_size, hidden_size), \\\n\t\t\tnn.ReLU(), \\\n\t\t\tnn.BatchNorm1d(num_features=hidden_size))\n\n\tdef forward(self, s1, s2, alphas, betas, mask1, mask2):\n\t\t\"\"\"\n\t\tArgs:\n\t\t\ts1: Sentence 1 BiLSTM embeddings (b x LA x inp_size)\n\t\t\ts2: Sentence 2 BiLSTM embeddings (b x LB x inp_size)\n\t\t\talphas: Aligned phrases (b x LB x inp_size)\n\t\t\tbetas: Aligned phrases (b x LA x inp_size)\n\t\t\tmask1: Sentence 1 mask (b x LA)\n\t\t\tmask2: Sentence 2 mask (b x LB)\n\t\tOutput:\n\t\t\tv1_avg: Comparison avg. pooled vector for aligned sentence s1 (b x hidden_size)\n\t\t\tv1_max: Comparison max. pooled vector for aligned sentence s1 (b x hidden_size)\n\t\t\tv2_avg: Comparison avg. pooled vector for aligned sentence s2 (b x hidden_size)\n\t\t\tv2_max: Comparison max. pooled vector for aligned sentence s2 (b x hidden_size)\n\t\t\"\"\"\n\t\tbatch_size = s1.shape[0]\n\t\tmaxlen = s1.shape[1]\n\t\tinp_size = s1.shape[2]\n\n\t\tin1 = torch.cat((s1, betas), dim=2)\n\t\t# b x LA x (inp_size * 2)\n\t\tin2 = torch.cat((s2, alphas), dim=2)\n\t\t# b x LB x (inp_size * 2)\n\n\t\tv1 = self.linear(in1.view(-1, inp_size * 2)).view(batch_size, maxlen, -1)\n\t\t# b x LA x hidden_size\n\t\tv1_avg = torch.sum(torch.mul(v1, mask1.unsqueeze(-1)), dim=1)\n\t\tv1_avg = torch.div(v1_avg, torch.sum(mask1, dim=1).unsqueeze(-1))\n\t\t# b x hidden_size\n\t\tv1_max = torch.max(torch.mul(v1, mask1.unsqueeze(-1)), dim=1)[0]\n\t\t# b x hidden_size\n\n\t\tv2 = self.linear(in2.view(-1, inp_size * 2)).view(batch_size, maxlen, -1)\n\t\t# b x LB x hidden_size\n\t\tv2_avg = torch.sum(torch.mul(v2, mask2.unsqueeze(-1)), dim=1)\n\t\tv2_avg = torch.div(v2_avg, torch.sum(mask2, dim=1).unsqueeze(-1))\n\t\t# b x hidden_size\n\t\tv2_max = torch.max(torch.mul(v2, mask2.unsqueeze(-1)), dim=1)[0]\n\t\t# b x hidden_size\n\n\t\treturn v1_avg, v1_max, v2_avg, v2_max\n\nclass ESIMBNMultiTask(nn.Module):\n\t\"\"\"\n\tModel architecture similar to the Enhanced Sequential Inference Model (ESIM)\n\tas described in https://arxiv.org/abs/1609.06038 without the Tree LSTM. This\n\tmodel also has BatchNorm layers for preventing overfitting instead of dropout\n\tlayers.\n\n\tThe BatchNorm order followed here is LIN -> ReLU -> BN even though the original\n\tpaper used BN before the non-linearity. Some online sources claim that BN after\n\tthe ReLU gives better results.\n\n\tThe model is designed for both Reddit response prediction task and Quora\n\tsemantic question matching task.\n\t\"\"\"\n\tdef __init__(self, hidden_size=200, glove_loader=None, pretrained_emb=True):\n\t\t\"\"\"\n\t\tArgs:\n\t\t\thidden_size: Size of the intermediate linear layers\n\t\t\tglove_loader: GLoVe embedding loader\n\t\t\tpretrained_emb: Use pretrained embeddings\n\t\t\"\"\"\n\t\tsuper(ESIMBNMultiTask, self).__init__()\n\n\t\tif not pretrained_emb:\n\t\t\traise NotImplementedError('always loads pretrained embeddings')\n\n\t\tword_vectors = glove_loader.word_vectors\n\t\tword_vectors = np.vstack(word_vectors)\n\t\tvocab_size = word_vectors.shape[0]\n\t\tembed_size = word_vectors.shape[1]\n\n\t\tself.embedding = nn.Embedding(vocab_size, embed_size)\n\t\tself.embedding.load_state_dict({'weight': torch.Tensor(word_vectors)})\n\t\tself.encoder = nn.LSTM(input_size=embed_size, hidden_size=hidden_size, num_layers=1, bidirectional=True)\n\t\tself.attend = AttendFeedForward(inp_size=hidden_size * 2, hidden_size=hidden_size)\n\t\tself.compare = CompareFeedForward(inp_size=hidden_size * 2, hidden_size=hidden_size)\n\n\t\t# prediction layer for the Quora task\n\t\tself.sts_pred = nn.Sequential( \\\n\t\t\tnn.Linear(hidden_size * 4, hidden_size), \\\n\t\t\tnn.ReLU(), \\\n\t\t\tnn.BatchNorm1d(num_features=hidden_size), \\\n\t\t\tnn.Linear(hidden_size, 2))\n\n\t\t# tranformation layer for the response\n\t\tself.response_transform = nn.Sequential( \\\n\t\t\tnn.Linear(hidden_size * 2, hidden_size * 2), \\\n\t\t\tnn.ReLU(), \\\n\t\t\tnn.BatchNorm1d(num_features=hidden_size * 2), \\\n\t\t\tnn.Linear(hidden_size * 2, hidden_size * 2), \\\n\t\t\tnn.BatchNorm1d(num_features=hidden_size * 2))\n\n\t\tself.reset_parameters()\n\n\tdef reset_parameters(self):\n\t\t\"\"\"Initialize network weights using Xavier init (with bias 0.01)\"\"\"\n\t\tself.apply(ixvr)\n\n\tdef forward(self, s1, s2, len1, len2):\n\t\t\"\"\"\n\t\tArgs:\n\t\t\ts1: Sentence 1 embeddings (b x LA)\n\t\t\ts2: Sentence 2 embeddings (b x LB)\n\t\t\tlen1: Sentence 1 length (b)\n\t\t\tlen2: Sentence 2 length (b)\n\t\t\"\"\"\n\t\tbatch_size = s1.shape[0]\n\t\tmaxlen = s1.shape[1]\n\n\t\ts1 = self.embedding(s1).transpose(0, 1)\n\t\ts1, _ = self.encoder(s1)\n\t\ts1 = torch.transpose(s1, 0, 1).contiguous()\n\t\t# b x LA x (hidden_size * 2)\n\t\ts2 = self.embedding(s2).transpose(0, 1)\n\t\ts2, _ = self.encoder(s2)\n\t\ts2 = torch.transpose(s2, 0, 1).contiguous()\n\t\t# b x LB x (hidden_size * 2)\n\n\t\tmask1 = torch.arange(0, maxlen).expand(batch_size, maxlen)\n\t\tif torch.cuda.is_available():\n\t\t\tmask1 = mask1.cuda()\n\t\tmask1 = mask1 < len1.unsqueeze(-1)\n\t\tmask2 = torch.arange(0, maxlen).expand(batch_size, maxlen)\n\t\tif torch.cuda.is_available():\n\t\t\tmask2 = mask2.cuda()\n\t\tmask2 = mask2 < len2.unsqueeze(-1)\n\n\t\tmask1 = mask1.float()\n\t\tmask2 = mask2.float()\n\n\t\talphas, betas = self.attend(s1, s2, mask1, mask2)\n\t\tv1_avg, v1_max, v2_avg, v2_max = self.compare(s1, s2, alphas, betas, mask1, mask2)\n\t\tassert batch_size > 1\n\t\tout = self.sts_pred(torch.cat((v1_avg, v1_max, v2_avg, v2_max), dim=1))\n\n\t\treturn out\n\n\tdef rank_responses(self, q, resp, len_q, len_resp):\n\t\t\"\"\"\n\t\tArgs:\n\t\t\tq: Reddit question embeddings (b x LA)\n\t\t\tresp: Reddit response candidates embeddings (b x K x LB)\n\t\t\tlen_q: Length of the input question (b)\n\t\t\tlen_resp: Length of the response candidates (b x K)\n\t\t\"\"\"\n\n\t\tbatch_size = q.shape[0]\n\t\tmaxlen = q.shape[1]\n\t\tK = resp.shape[1]\n\n\t\tq = self.embedding(q).transpose(0, 1)\n\t\tq, _ = self.encoder(q)\n\t\tq = torch.transpose(q, 0, 1).contiguous()\n\t\t# b x LA x (hidden_size * 2)\n\t\tresp = self.embedding(resp).view(batch_size * K, maxlen, -1).transpose(0, 1)\n\t\tresp, _ = self.encoder(resp)\n\t\tresp = torch.transpose(resp, 0, 1).view(batch_size, K, maxlen, -1).contiguous()\n\t\t# b x K x LB x (hidden_size * 2)\n\n\t\tmask1 = torch.arange(0, maxlen).expand(batch_size, maxlen)\n\t\tif torch.cuda.is_available():\n\t\t\tmask1 = mask1.cuda()\n\t\tmask1 = mask1 < len_q.unsqueeze(-1)\n\t\tmask1 = mask1.float()\n\t\t# b x LA\n\n\t\tmask2 = torch.arange(0, maxlen).expand(batch_size * K, maxlen)\n\t\tif torch.cuda.is_available():\n\t\t\tmask2 = mask2.cuda()\n\t\tmask2 = mask2 < len_resp.view(-1).unsqueeze(-1)\n\t\tmask2 = mask2.view(batch_size, K, -1).float()\n\t\t# b x K x LB\n\n\t\tq = q.unsqueeze(1).expand(-1, K, -1, -1).contiguous().view(batch_size * K, maxlen, -1)\n\t\t# (b * K) x LA x (hidden_size * 2)\n\t\tmask1 = mask1.unsqueeze(1).expand(-1, K, -1).contiguous().view(batch_size * K, maxlen)\n\t\t# (b * K) x LA\n\n\t\tresp = resp.view(batch_size * K, maxlen, -1)\n\t\t# (b * K) x LB x (hidden_size * 2)\n\t\tmask2 = mask2.view(batch_size * K, maxlen)\n\t\t# (b * K) x LB\n\n\t\talphas, betas = self.attend(q, resp, mask1, mask2)\n\t\tv1_avg, v1_max, v2_avg, v2_max = self.compare(q, resp, alphas, betas, mask1, mask2)\n\n\t\tv1 = torch.cat((v1_avg, v1_max), dim=1)\n\t\t# (b * K) x (hidden_size * 2)\n\t\tv2 = self.response_transform(torch.cat((v2_avg, v2_max), dim=1))\n\t\t# (b * K) x (hidden_size * 2)\n\n\t\tscores = torch.sum(torch.mul(v1, v2), dim=1).view(batch_size, -1)\n\t\t# b x K\n\n\t\treturn scores\n","sub_path":"models/ESIMBNMultiTask.py","file_name":"ESIMBNMultiTask.py","file_ext":"py","file_size_in_byte":9601,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"9881298","text":"#Fantome\nfrom random import randrange, choice\nimport logger\nfrom list_card import weight_data\nfrom lien_map import passages, pass_ext\n\nGREEN = '\\033[92m'\nYELLOW = '\\033[93m'\nRED = '\\033[91m'\nENDC = '\\033[0m'\nlog = logger.log\n\ndef lancer():\n fini = False\n old_question = \"\"\n manager = Manager()\n infoEndOfPartie = open('./1/infos.txt','r')\n positionForEndOfPartie = 0\n lastInfo = \"\"\n while len(manager.fantome) <= 0:\n infof = open('./1/infos.txt','r')\n manager.fantome = infof.readline().split(':')[-1].strip()\n log(\"Fantome : \" + manager.fantome)\n infof.close()\n while not fini:\n manager.getGameState()\n qf = open('./1/questions.txt','r')\n question = qf.read().strip()\n qf.close()\n if len(question) > 3 and question != old_question :\n log(GREEN, end='')\n rf = open('./1/reponses.txt','w')\n log(\"Q: \" + question, end=' A: ')\n answer = manager.selectQuestion(question)\n log(answer)\n log(ENDC, end='')\n rf.write(answer)\n rf.close()\n old_question = question\n infoEndOfPartie.seek(positionForEndOfPartie)\n lastInfos = infoEndOfPartie.readlines()\n for l in lastInfos:\n if \"Score final\" in l:\n fini = True\n elif not any(w in l for w in [\"QUESTION\", \"REPONSE\"]):\n if \"NOUVEAU PLACEMENT\" in l:\n manager.movedPersonnage(l)\n # else:\n # log(\"Info : \" + l)\n positionForEndOfPartie = infoEndOfPartie.tell()\n infoEndOfPartie.close()\n manager.closeFD()\n\n\"\"\"\nTuiles disponibles : [bleu-2-suspect, noir-3-suspect, violet-6-suspect, rouge-5-suspect] choisir entre 0 et 3\nVoulez-vous activer le pouvoir (0/1) ?\npositions disponibles : {1, 3}, choisir la valeur\n\"\"\"\n\nclass Manager:\n def __init__(self):\n self.Tour = 0\n self.Points = 0\n self.Ombre = 0\n self.Lock = 0\n self.Personnages = {'bleu': {'room': '3', 'suspect': 1}, 'rouge': {'room': '4', 'suspect': 1}, 'marron': {'room': '7', 'suspect': 1},\\\n 'violet': {'room': '1', 'suspect': 1}, 'gris': {'room': '6', 'suspect': 1}, 'noir': {'room': '5', 'suspect': 1},\\\n 'rose': {'room': '2', 'suspect': 1}, 'blanc': {'room': '0', 'suspect': 1}}\n self.Rooms = {'0':[], '1':[], '2':[], '3':[], '4':[], '5':[], '6':[], '7':[], '8':[], '9':[]}\n self.Cleans = []\n self.FDGameState = open('./1/infos.txt','r')\n self.posFDGameState = 0\n self.fantome = \"\"\n self.selectedPersonnage = \"\"\n self.split = True\n\n def closeFD(self):\n self.FDGameState.close()\n\n def calcPoint(self):\n suspectAlone = 0\n for r in self.Rooms:\n for p in self.Rooms[r]:\n #is supect\n self.Rooms[r][p]\n #How many in this room\n len(self.Rooms[r])\n roomFantome = \"\"\n try:\n log ()\n log (\"ppl in fantome room: \" + str(len(self.Rooms[self.Personnages[self.fantome][\"room\"]])))\n except:\n pass\n # for p in self.Personnages:\n # if p[\"color\"] == self.fantome:\n # roomFantome = p[\"room\"]\n # log (ENDC)\n # log (rooms)\n # log (\"len: \" + str(len(rooms[roomFantome])))\n # log (GREEN)\n\n def getGameState(self):\n self.FDGameState.seek(self.posFDGameState)\n line = self.FDGameState.readline()\n while line != '' and \"Tour:\" + str(self.Tour + 1) not in line:\n line = self.FDGameState.readline()\n if line == '':\n return\n state = line.split(',')\n self.Tour = int(state[0].split(':')[1])\n log(\"Tour:\", end='')\n log(self.Tour, end=' ; ')\n self.Points = int(state[1].split(':')[1].split('/')[0])\n log(\"Points:\", end='')\n log(self.Points, end=' ; ')\n self.Ombre = int(state[2].split(':')[1])\n log(\"Ombre:\", end='')\n log(self.Ombre, end=' ; ')\n self.Lock = state[3].split(':')[1] + ', ' + state[4].strip()\n log(\"Lock:\", end='')\n log(self.Lock)\n personnages = self.FDGameState.readline()\n self.posFDGameState = self.FDGameState.tell()\n self.Rooms = {'0':{}, '1':{}, '2':{}, '3':{}, '4':{}, '5':{}, '6':{}, '7':{}, '8':{}, '9':{}}\n self.Cleans = []\n for p in personnages.split(\" \"):\n #pI = personnage Information\n pI = p.strip().split('-')\n self.Personnages[pI[0]][\"room\"] = pI[1]\n self.Personnages[pI[0]][\"suspect\"] = 1 if pI[2] == \"suspect\" else 0\n self.Rooms[pI[1]][pI[0]] = self.Personnages[pI[0]][\"suspect\"]\n if pI[2] == \"clean\":\n self.Cleans.append(pI[0])\n log (\"Perso: \")\n log(self.Personnages)\n log (\"Rooms: \")\n log(self.Rooms)\n log (\"Clean: \")\n log(self.Cleans)\n\n #Fonction qui determine si les personnages doivent se regrouper\n #ou se separer\n def shouldISplit(self):\n nbSuspect = 0\n nbSuspectAlone = 0\n for r in self.Rooms:\n for p in self.Rooms[r]:\n #is supect\n if self.Rooms[r][p] > 0:\n nbSuspect += 1\n if len(self.Rooms[r]) == 1:\n nbSuspectAlone += 1\n log (\"nbSuspect: \" + str(nbSuspect))\n log (\"nbSuspectAlone: \" + str(nbSuspectAlone))\n if nbSuspectAlone >= 4 and len(self.Rooms[self.Personnages[self.fantome][\"room\"]]) == 1:\n return (True)\n return (False)\n\n #Selectionne une tuile en fonction de:\n #Si le fantome est tout seul ou non\n #Si la tuile est suspect\n #Si le pouvoir de la tuile a un poids plus eleve\n def selectTuile(self, question):\n self.calcPoint()\n tuiles = question.split('[')[1].split(']')[0].split(',')\n #isFantomAlone = True if len(self.Rooms[self.Personnages[self.fantome][\"room\"]]) == 1 else False\n isFantomAlone = self.shouldISplit()\n self.split = isFantomAlone\n log (\"Should suspects split ? \" + str(isFantomAlone))\n #Don t waste time if only one available\n if len(tuiles) == 1:\n self.selectedPersonnage = tuiles[0].strip().split('-')[0]\n return str(0)\n posInQuestion = 0\n persoPossibility = {}\n heaviestCard_pos = 0\n heaviestCard_weight = 0\n for t in tuiles:\n #pI = personnage Information\n pI = t.strip().split('-')\n room = self.Personnages[pI[0]][\"room\"]\n log (\"Current (\" + pI[0] + \") \" + pI[2] + \"; room: \" + room + \"; ppl in room: \" + str(len(self.Rooms[room])))\n zePassage = passages\n if pI[0] == \"rose\":\n zePassage = pass_ext\n for p in zePassage[int(room)]:\n #Locked passage\n if room in self.Lock and str(p) in self.Lock:\n log (\"Passage \" + room + \" to \" + str(p) + \" is locked..\")\n continue\n #Estime l etat des salles apres les deplacements\n sizeOfRoomAfterMove = len(self.Rooms[str(p)])\n if str(p) in question.split(']')[0]:\n sizeOfRoomAfterMove -= 1\n isOmbre = \"\"\n if self.Ombre == p:\n isOmbre = \" into the Darkness..\"\n log (\"ppl in room annex (\" + str(p) + \") : \" + str(len(self.Rooms[str(p)])) + \" after move: \" + str(sizeOfRoomAfterMove) + isOmbre)\n if isFantomAlone and (sizeOfRoomAfterMove == 0 or self.Ombre == p):\n persoPossibility[posInQuestion] = pI[0]\n continue\n elif not isFantomAlone and sizeOfRoomAfterMove > 0:\n persoPossibility[posInQuestion] = pI[0]\n continue\n if weight_data[pI[0]] > heaviestCard_weight:\n heaviestCard_pos = posInQuestion\n heaviestCard_weight = weight_data[pI[0]]\n self.selectedPersonnage = pI[0]\n posInQuestion += 1\n log (persoPossibility)\n if len(persoPossibility) > 0:\n heaviestCard_weight = 0\n for p in persoPossibility:\n bonus = int(self.Personnages[persoPossibility[p]][\"suspect\"]) * 10\n if bonus + weight_data[persoPossibility[p]] > heaviestCard_weight:\n heaviestCard_pos = p\n heaviestCard_weight = bonus + weight_data[persoPossibility[p]]\n self.selectedPersonnage = persoPossibility[p]\n return str(heaviestCard_pos)\n\n def usePositionPower(self, question):\n posDispo = question.split('{')[1].split('}')[0].split(',')\n pos = []\n for p in posDispo:\n pos.append(int(p.strip()))\n return choice(pos)\n\n #Selectionne le lieu ou se deplacer en fct de si le fantome est tout seul ou non\n def movePersonnage(self, question):\n posDispo = question.split('{')[1].split('}')[0].split(',')\n pos = 0\n posValue = 0\n if self.split == True:\n posValue = 10\n for p in posDispo:\n cleanPos = p.strip()\n if self.split is True:\n if len(self.Rooms[cleanPos]) == 0 or int(cleanPos) == self.Ombre:\n pos = cleanPos\n break\n if len(self.Rooms[cleanPos]) < posValue:\n posValue = len(self.Rooms[cleanPos])\n pos = cleanPos\n elif self.split is False:\n if len(self.Rooms[cleanPos]) > 0 and len(self.Rooms[cleanPos]) > posValue:\n pos = cleanPos\n posValue = len(self.Rooms[cleanPos])\n else:\n pos = cleanPos\n return pos\n\n def selectQuestion(self, question):\n if \"Tuiles disponibles :\" in question:\n return str(self.selectTuile(question))\n elif \"Voulez-vous activer le pouvoir\" in question:\n return str(self.shouldIUseMyPower())\n elif \", positions disponibles\" in question:\n return str(self.usePositionPower(question))\n elif \"positions disponibles\" in question:\n return str(self.movePersonnage(question))\n elif \"Avec quelle couleur échanger\" in question:\n return str(self.useSwitchPower())\n elif \"Quelle salle obscurcir ?\" in question:\n self.ombre = self.roomBlacked()\n return str(self.ombre)\n elif \"Quelle salle bloquer ?\" in question:\n return str(2)\n elif \"Quelle sortie ?\" in question:\n return str(self.usePositionPower(question))\n else:\n return str(0)\n\n def movedPersonnage(self, info):\n try:\n info = info.split(' : ')[1]\n #pI = personnage Information\n pI = info.strip().split('-')\n del self.Rooms[self.Personnages[pI[0]][\"room\"]][pI[0]]\n self.Personnages[pI[0]][\"room\"] = pI[1]\n self.Personnages[pI[0]][\"suspect\"] = 1 if pI[2] == \"suspect\" else 0\n self.Rooms[pI[1]][pI[0]] = self.Personnages[pI[0]][\"suspect\"]\n except:\n pass\n\n def shouldIUseMyPower(self):\n if self.selectedPersonnage == \"noir\" and self.split == True:\n return (0)\n if self.selectedPersonnage == \"noir\" and self.split == False:\n return (1)\n if self.selectedPersonnage == \"gris\":\n return (1)\n if self.selectedPersonnage == \"violet\":\n return (1)\n if self.selectedPersonnage == \"rouge\":\n return (1)\n if self.selectedPersonnage == \"blanc\":\n #Evite de perdre du temps de calcule si le blanc est tout seul\n if len(self.Rooms[self.Personnages[\"blanc\"][\"room\"]]) > 1:\n if self.Personnages[\"blanc\"][\"suspect\"] == 1 and self.split == True:\n return (1)\n else:\n return (0)\n return (0)\n\n def roomBlacked(self):\n #Si fantome tout seul\n #Return la case avec le plus de suspect\n if len(self.Rooms[self.Personnages[self.fantome][\"room\"]]) == 1:\n nbRoom = 0\n maxSuspectInRoom = 0\n for r in self.Rooms:\n suspectInRoom = 0\n for p in self.Rooms[r]:\n #is suspect\n if self.Rooms[r][p] > 0:\n suspectInRoom += 1\n if suspectInRoom > maxSuspectInRoom:\n nbRoom = r\n maxSuspectInRoom = suspectInRoom\n #Si tout les suspects solo alors return fantome\n if maxSuspectInRoom == 1:\n return (self.Personnages[self.fantome][\"room\"])\n return (nbRoom)\n #Si le fantome n est pas tout seul et qu il devrait\n #return la case du fantome\n elif self.split == True or len(self.Rooms[self.Personnages[self.fantome][\"room\"]]) > 1:\n return (self.Personnages[self.fantome][\"room\"])\n #Si les suspect ne doivent pas se split et que le fantome n est pas tout seul\n #return une case aleatoire sans suspect\n else:\n nbRoom = 0\n maxNoneSuspectInRoom = 0\n for r in self.Rooms:\n noneSuspectInRoom = 0\n for p in self.Rooms[r]:\n #is not suspect\n if self.Rooms[r][p] == 0:\n noneSuspectInRoom += 1\n else:\n continue\n if noneSuspectInRoom > maxNoneSuspectInRoom:\n nbRoom = r\n maxNoneSuspectInRoom = noneSuspectInRoom\n return (nbRoom)\n\n #Utilise le pouvoir violet\n def useSwitchPower(self):\n #Sauve le fantome si il doit etre seul\n if len(self.Rooms[self.Personnages[\"violet\"][\"room\"]]) == 1 and self.split == True and len(self.Rooms[self.Personnages[self.fantome][\"room\"]]) > 1:\n return (self.fantome)\n #Sauve le fantome si il doit etre en groupe\n if len(self.Rooms[self.Personnages[\"violet\"][\"room\"]]) > 1 and self.split == False and len(self.Rooms[self.Personnages[self.fantome][\"room\"]]) == 1:\n return (self.fantome)\n if self.Personnages[\"violet\"][\"suspect\"] == 1:\n #Sauve le violet si il doit etre seul\n if len(self.Rooms[self.Personnages[\"violet\"][\"room\"]]) > 1 and self.split == True:\n for r in self.Rooms:\n if r != self.Personnages[\"violet\"][\"room\"]:\n if len(self.Rooms[r]) == 1:\n for p in self.Rooms[r]:\n #is not suspect\n if self.Rooms[r][p] == 0:\n return (p)\n #Sauve le violet si il doit etre en groupe\n if len(self.Rooms[self.Personnages[\"violet\"][\"room\"]]) == 1 and self.split == False:\n colorOfNoneSuspect = \"\"\n colorToKeep = \"\"\n maxNoneSuspectInRoom = 0\n for r in self.Rooms:\n noneSuspectInRoom = 0\n if r != self.Personnages[\"violet\"][\"room\"]:\n if len(self.Rooms[r]) > 1:\n for p in self.Rooms[r]:\n #is not suspect\n if self.Rooms[r][p] == 0:\n noneSuspectInRoom += 1\n colorOfNoneSuspect = p\n if noneSuspectInRoom > maxNoneSuspectInRoom:\n colorToKeep = colorOfNoneSuspect\n maxNoneSuspectInRoom = noneSuspectInRoom\n if len(colorToKeep):\n return (colorToKeep)\n else:\n #Sauve un suspect si il doit etre seul\n if len(self.Rooms[self.Personnages[\"violet\"][\"room\"]]) == 1 and self.split == True:\n colorOfSuspect = \"\"\n colorToKeep = \"\"\n maxSuspectInRoom = 0\n for r in self.Rooms:\n suspectInRoom = 0\n if r != self.Personnages[\"violet\"][\"room\"]:\n if len(self.Rooms[r]) > 1:\n for p in self.Rooms[r]:\n #is suspect\n if self.Rooms[r][p] > 0:\n suspectInRoom += 1\n colorOfSuspect = p\n if suspectInRoom > maxSuspectInRoom:\n colorToKeep = colorOfSuspect\n maxSuspectInRoom = suspectInRoom\n if len(colorToKeep):\n return (colorToKeep)\n #Sauve un suspect si il doit etre en groupe\n if len(self.Rooms[self.Personnages[\"violet\"][\"room\"]]) > 1 and self.split == False:\n for r in self.Rooms:\n if r != self.Personnages[\"violet\"][\"room\"]:\n if len(self.Rooms[r]) == 1:\n for p in self.Rooms[r]:\n #is suspect\n if self.Rooms[r][p] == 1:\n return (p)\n if self.fantome != \"bleu\":\n return (\"bleu\")\n return (\"marron\")\n","sub_path":"dummy1.py","file_name":"dummy1.py","file_ext":"py","file_size_in_byte":17574,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"194247979","text":"# coding:utf-8\n\nimport logging\nimport psutil \nimport time\nimport json\nimport winreg\nimport requests\nimport os\nimport subprocess\nimport globalvar as gl\nfrom urllib.parse import parse_qs\n\n\nlogging.basicConfig(level=logging.DEBUG,format=' %(asctime)s - %(levelname)s - %(message)s')\n#logging.disable(logging.CRITICAL) # 加这句话，就是log全部禁止，不加，就可以log打印了\n\n\n\n# 定义函数，两个参数，都是python本身定义的，默认就行了。\ndef application(environ, start_response):\n \n recordLog('start in webapi')\n # 定义文件请求的类型和当前请求成功的code\n try:\n start_response('200 OK', [('Content-Type', 'application/json;charset=utf-8')])\n d = parse_qs(environ['QUERY_STRING'])\n recordLog(environ['QUERY_STRING'])\n key = d.get('key', [''])[0] # 返回第一个age值.\n recordLog(key)\n except Exception as err:\n recordLog('web err!')\n recordLog(str(err))\n \n \n\n # 获取服务器的硬件运行信息\n if key=='getinfo':\n info=sysInfo()\n json_str = json.dumps(info,ensure_ascii=False,indent=4)\n recordLog('record getinfo')\n recordLog(json.dumps(json_str))\n return [json_str.encode('utf-8')]\n \n # 主动触发服务器下载最新版的热更新\n elif key=='download':\n info = {\"status\": \"download\"}\n try:\n res =requests.get(r'http://47.75.120.191:83/PCInfoService.exe',timeout=30)\n except Exception as err:\n info = {\"status\":str(err)}\n recordLog(str(err))\n\n down=os.path.join(getPath(),'PCInfoService.exe')\n\n try:\n downloadFile = open(down,'wb')\n for chunk in res.iter_content(100000):\n downloadFile.write(chunk)\n #recordLog(os.path.getsize(downloadFile))\n downloadFile.close()\n info = {\"status\":\"download finish\"}\n\n recordLog(\"download finish\")\n \n WriteRestartCmd()\n recordLog(\"update Start\")\n recordLog(\"shutdown\")\n \n except Exception as err:\n recordLog(str(err))\n info = {\"status\":str(err)}\n \n finally:\n return [json_str.encode('utf-8')]\n \n else:\n logging.debug('Noget')\n info = {\"status\": \"none\"}\n json_str = json.dumps(info,ensure_ascii=False,indent=4)\n return [json_str.encode('utf-8')]\n \n#编写bat脚本，删除旧程序，运行新程序\ndef WriteRestartCmd():\n os.chdir(getPath())\n b = open(\"upgrade.bat\",'w')\n TempList = \"@echo off\\n\"; #关闭bat脚本的输出\n TempList += \"if not exist pcinfoservice.exe exit \\n\"; #新文件不存在,退出脚本执行\n TempList += \"sc stop pcinfo \\n\" \n TempList += \"ping /n 5 127.1>nul \\n\" #5秒后删除旧程序（3秒后程序已运行结束，不延时的话，会提示被占用，无法删除）\n TempList += \"del PCInfo.exe /q \\n\"\n TempList += \"ren PCInfoService.exe PCInfo.exe \\n\"\n TempList += \"pcinfo.exe install \\n\"\n TempList += \"sc start pcinfo \\n\"\n TempList += \"sc config pcinfo start= auto\" \n b.write(TempList)\n b.close()\n subprocess.Popen(\"upgrade.bat\")\n\n\ndef recordLog(strmsg): #把strmsg写入日志\n \n os.chdir(getPath())\n try:\n logFile = open(r'web.log','a')\n logFile.write(get_time_stamp()+' ') #写入日志\n logFile.write(strmsg+'\\n')\n except Exception as err:\n logFile.write(get_time_stamp()+' ') #写入日志\n logFile.write('write web.log err!\\n')\n pass\n finally:\n logFile.close()\n return\n\ndef sysInfo():\n info={}\n \n line={}\n try:\n line.setdefault('CPU核心',str(psutil.cpu_count()))\n line.setdefault('CPU利用率',str(int(psutil.cpu_percent())) + '%')\n info['CPU']=line\n\n line={}\n line.setdefault('空闲内存G',str(round(psutil.virtual_memory().free/(1024.0*1024.0*1024.0), 2)))\n line.setdefault('总内存G',str(int(round(psutil.virtual_memory().total/(1024.0*1024.0*1024.0)))))\n line.setdefault('内存利用率',str(int((psutil.virtual_memory().total-psutil.virtual_memory().free)/float(psutil.virtual_memory().total)*100))+ '%')\n info['Memory'] =line\n \n line={}\n \n io = psutil.disk_partitions()\n j=0\n except Exception as err:\n recordLog(str(err))\n\t\n for i in io:\n diskstr=[]\n try:\n o = psutil.disk_usage(i.device)\n except Exception as err:\n recordLog(str(err))\n j=j+1\n continue\n \n disk=io[j][0].strip(r':\\\\')\n diskstr.append(str(int(o.free/(1024.0*1024.0*1024.0)))+\"G\")\n diskstr.append(str(int(o.total/(1024.0*1024.0*1024.0)))+\"G\") \n line.setdefault(disk,diskstr)\n del(diskstr)\n j=j+1\n\n info['Disk']=line\n try:\n info.setdefault('version',gl.getvalue('version'))\n except Exception as err:\n recordLog(\"version write err\")\n \n return info\n\ndef getPath():\n #获取服务执行程序的路径\n try:\n key = winreg.OpenKey(winreg.HKEY_LOCAL_MACHINE,r\"SYSTEM\\CurrentControlSet\\Services\\PCInfo\")\n downloadPath =winreg.QueryValueEx(key,\"ImagePath\")\n path=os.path.dirname(downloadPath[0][1:])\n except Exception as err:\n path=r'c:\\windows\\system32'\n recordLog('Path change err: '+ str(err))\n return path\n\n\ndef get_time_stamp():\n ct = time.time()\n local_time = time.localtime(ct)\n data_head = time.strftime(\"%Y-%m-%d %H:%M:%S\", local_time)\n data_secs = (ct - int(ct)) * 1000\n time_stamp = \"%s.%03d\" % (data_head, data_secs)\n return time_stamp\n","sub_path":"python-book01/2018/2018-07/PChealth/pc_info_windowsService/WebAPI.py","file_name":"WebAPI.py","file_ext":"py","file_size_in_byte":5748,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"469019174","text":"#!/usr/local/bin/python3\n\nimport time\nimport numpy as np\n\n\ndef power(x, y, sn):\n box_id = x + 10\n level = box_id * y\n level += sn\n level *= box_id\n hnd = level // 100 % 10\n return hnd - 5\n\n\ndef setup():\n return np.fromfunction(lambda x, y :power(x, y, 6042), (300, 300))\n\n\ndef part1(grid):\n best = 0\n coords = 0, 0\n for x in range(298):\n for y in range(298):\n temp = np.sum(grid[x:x+3, y:y+3])\n if temp > best:\n best = temp\n coords = x, y\n return coords\n\n\ndef part2(grid):\n best = 0\n coords = 0, 0, 0\n for size in range(1, 301):\n if not size % 10:\n print(size)\n for x in range(300 - size):\n for y in range(300 - size):\n temp = np.sum(grid[x:x+size, y:y+size])\n if temp > best:\n best = temp\n coords = x + 1, y + 1, size\n return coords\n\n\ndef main():\n start_setup = time.time()\n grid = setup()\n end_setup = time.time()\n\n start_part1 = time.time()\n res_part1 = part1(grid)\n end_part1 = time.time()\n\n start_part2 = time.time()\n res_part2 = part2(grid)\n end_part2 = time.time()\n\n print(f\"part 1: {res_part1}\")\n print(f\"part 2: {res_part2}\")\n print(f\"setup took {end_setup - start_setup} seconds\")\n print(f\"part 1 took {end_part1 - start_part1} seconds\")\n print(f\"part 2 took {end_part2 - start_part2} seconds\")\n print(f\"overall took {end_part2 - start_setup} seconds\")\n\n\nif __name__ == '__main__':\n main()\n","sub_path":"2018/code/python/day11.py","file_name":"day11.py","file_ext":"py","file_size_in_byte":1556,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"340990095","text":"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\nfrom commons import logger\nimport os\n\nimport yaml\nfrom appium import webdriver\n\nlogger = logger.Logger().getLogger()\n\n\ndef appium_desired():\n dirname = os.path.dirname(os.path.dirname(__file__))\n filename = os.path.join(dirname, 'config/kyb_caps.yaml')\n with open(filename, 'r', encoding='utf-8') as file:\n data = yaml.load(file)\n\n base_dir = os.path.dirname(os.path.dirname(__file__))\n app_path = os.path.join(base_dir, 'app', data['appname'])\n desired_caps = {\n \"platformName\": data['platformName'],\n \"platformVersion\": data['platformVersion'],\n\n \"deviceName\": data['deviceName'],\n \"udid\": data['udid'],\n\n \"app\": app_path,\n \"appPackage\": data['appPackage'],\n \"appActivity\": data['appActivity'],\n\n \"automationName\": data['automationName'],\n \"noReset\": data['noReset'],\n\n \"unicodeKeyboard\": data['unicodeKeyboard'],\n \"resetKeyboard\": data['resetKeyboard']\n }\n logger.info('start app......')\n\n driver = webdriver.Remote('http://' + str(data['ip']) + ':' + str(data['port']) + '/wd/hub', desired_caps)\n driver.implicitly_wait(3)\n return driver\n\n\nif __name__ == '__main__':\n appium_desired()\n","sub_path":"commons/desired_caps.py","file_name":"desired_caps.py","file_ext":"py","file_size_in_byte":1255,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"615884768","text":"import models\nfrom models import Organisation, User, Role\n\nmodels.drop_talbes()\nmodels.create_tables()\n\norg0 = Organisation(\n name=\"The Royal Society of NewZealand\",\n email=\"nzorcidhub@royalsociety.org.nz\",\n tuakiri_name=\"The Royal Society of NewZealand\",\n orcid_client_id=\"client-123\",\n orcid_secret=\"secret-123\",\n confirmed=True)\norg0.save()\n\nsuper_user = User(\n name=\"The Royal Society of NewZealand\",\n email=\"nzorcidhub@royalsociety.org.nz\",\n edu_person_shared_token=\"aaRtDix1l2z43M0vvWTBpBuf_ek\",\n confirmed=True,\n roles=Role.SUPERUSER)\nsuper_user.save()\n\nsuper_user = User(\n name=\"The Root\",\n email=\"root@mailinator.com\",\n confirmed=True,\n roles=Role.SUPERUSER)\nsuper_user.save()\n","sub_path":"orcidhub-core/initializedb.py","file_name":"initializedb.py","file_ext":"py","file_size_in_byte":731,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"452878630","text":"# import predefined function\nfrom random import randint\n\nvarname = 'Rahul' #can be given at runtime dynamically but, for now defining it fixed.\n\n#define a function which takes the string as variable name\ndef NameGenNum(str):\n print('{} {}'.format(str, randint(6, 15))) #concatinate the string and generated random number\n\n#call the function with a variable name\nNameGenNum(varname)","sub_path":"answer.pseudo.py","file_name":"answer.pseudo.py","file_ext":"py","file_size_in_byte":384,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"167001807","text":"\"\"\"\nSimple implementation of (Fisher's) Linear Discriminant Analysis.\nThanks to: https://www.python-course.eu/linear_discriminant_analysis.php\n\nThe L. D. Matrix is a transformation matrix which best separates\nthe instances of different classes in data projection.\n\"\"\"\nimport numpy as np\n\n\nclass LDA:\n def fit(self, X, y):\n \"\"\"Fit dataset into LDA model.\"\"\"\n self.X = np.array(X)\n self.y = np.array(y)\n\n self.classes, self.cls_freqs = np.unique(y, return_counts=True)\n\n def _scatter_within(self):\n \"\"\"This measure describes how scattered are each class.\"\"\"\n scatter_within = np.array([\n (cls_freq - 1) * np.cov(self.X[self.y == cls, :], rowvar=False)\n for cls, cls_freq in zip(self.classes, self.cls_freqs)\n ]).sum(axis=0)\n\n return scatter_within\n\n def _scatter_between(self):\n \"\"\"This measure describes the separation between different classes.\"\"\"\n class_means = np.array(\n [self.X[self.y == cls, :].mean(axis=0) for cls in self.classes])\n\n total_mean = self.X.mean(axis=0)\n\n scatter_factor = class_means - total_mean\n\n scatter_between = np.array([\n freq * np.outer(sf, sf)\n for freq, sf in zip(self.cls_freqs, scatter_factor)\n ]).sum(axis=0)\n\n return scatter_between\n\n def _get_eig(self, sw, sb):\n \"\"\"Get eigenval/vec from (ScatterWithin)^(-1)*(ScatterBetween) mat.\"\"\"\n sw_inv = np.linalg.inv(sw)\n\n return np.linalg.eig(np.matmul(sw_inv, sb))\n\n def _project(self, eig, num_dim):\n \"\"\"Get the K (``num_dim``) most expressive eigenvalues/vectors.\"\"\"\n eig_vals, eig_vecs = eig\n\n eig_vals, eig_vecs = zip(\n *sorted(\n zip(eig_vals, eig_vecs),\n key=lambda item: item[0],\n reverse=True)[:num_dim])\n\n return eig_vals, eig_vecs\n\n def predict(self, max_dim=2):\n \"\"\"Create transf. matrix which best separates the fitted data proj.\"\"\"\n sw = self._scatter_within()\n sb = self._scatter_between()\n\n max_dim = min(max_dim, self.classes.size-1)\n\n eig = self._get_eig(sw, sb)\n\n eig_vals, eig_vecs = self._project(eig, num_dim=max_dim)\n\n _, num_col = self.X.shape\n\n self.eig_vals = np.array(eig_vals)\n self.transf_mat = np.concatenate(eig_vecs).reshape(num_col, max_dim)\n\n self.transf_mat = self.transf_mat.real\n\n return self.transf_mat\n\n def wilks_lambda(self):\n \"\"\"Compute Wilks' Lambda measure using eigenvalues of L. D. matrix.\"\"\"\n return np.prod(1.0 / (1.0 + self.eig_vals))\n\n def canonical_corr(self):\n \"\"\"Calculate canonical correlation values from L. D. matrix.\"\"\"\n return (self.eig_vals / (1.0 + self.eig_vals))**0.5\n\n\nif __name__ == \"__main__\":\n from sklearn import datasets\n iris = datasets.load_iris()\n\n model = LDA()\n model.fit(iris.data, iris.target)\n ans = model.predict(max_dim=2)\n\n print(\"Transformation Matrix:\", ans, sep=\"\\n\", end=\"\\n\\n\")\n print(\"Eigenvalues of L. D. matrix:\", model.eig_vals, end=\"\\n\\n\")\n print(\"Canonical Correlation:\", model.canonical_corr(), end=\"\\n\\n\")\n print(\"Wilks' Lambda:\", model.wilks_lambda())\n","sub_path":"model-implementation/py-linear-disc-analysis/lda.py","file_name":"lda.py","file_ext":"py","file_size_in_byte":3243,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"613704701","text":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Fri Mar 22 18:33:47 2019\n\n@author: user\n\"\"\"\nimport numpy as np\nimport struct\nimport matplotlib.pyplot as plt #for displaying data\nfrom mpl_toolkits.mplot3d import Axes3D\nimport csv\nimport pandas as pd #to manage dataframe\nimport struct\nfrom math import sqrt\nimport os # file and path operrations\nimport time\nimport sys # get input arguments of the python program\n\n\n\nimport plotly\nimport plotly.graph_objs as go\nfrom plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot\nfrom plotly.offline.offline import _plot_html\n\nimport glob #listing of files\nimport json\n\ndata_path = r\"../out/*/\"\noutput_path = r\"../temp/\"\npng_resolution_dpi = 300\n\n\ndirectories = glob.glob(data_path)\nic_cycle_order = []\n\n\nsorted_directories = sorted(directories)#sorted( directories, key = lambda directory: os.path.getctime(directory)) #getmtime for modified time\nprint(sorted_directories)\n# # for directory in sorted_directories:\n # # print(directory+'\\n')#print(\"{} - {}\".format(directory, time.ctime(os.path.getctime(directory))) )\n\nchannel = int(sys.argv[1]) \nprint('channel = \\n', channel);\nic_cycle = int(sys.argv[2]) \nprint('ic_cycle = \\n', ic_cycle);\nwb_cycle = int(sys.argv[3])\nprint('wb_cycle = \\n', wb_cycle);\nwb_sub_cycle = int(sys.argv[4])\nprint('wb_sub_cycle = \\n', wb_sub_cycle);\n\ntotal_ic_cycles = len(directories) # may add additional checks to avoid parasite folders added for testing\n# may also check json file to get metadata\n# manage the cases where user inputs exceed the limits ic and wb\n# total_wb_cycles = #get this from json file\n\n\n\nif ic_cycle > (total_ic_cycles - 1) :\n\tic_cycle = total_ic_cycles - 1 # this is to display the last data\n\n# confirm the data exist\n\nstream_filename = sorted_directories[ic_cycle] + \"ch_\" + str(channel) + \"_raw.dat\"\nprint(stream_filename);\n\nresult = sorted_directories[ic_cycle].find('IC_CYCLE') \nif result == -1:\n\tprint('Folder name incorrect \\n')\n\tsys.exit()\n\n\t\nwith open(sorted_directories[ic_cycle]+'cfg.json') as json_file: \n\tdata = json.load(json_file)\n\tsampling_period_ns = data['Oscilloscopes']['Picoscope 4444']['Sampling Period NS']\n\tresolution_bits = data['Oscilloscopes']['Picoscope 4444']['Sample Resolution bits']\n\tvoltage_range_str = data['Oscilloscopes']['Picoscope 4444']['Channels']['Channel '+str(channel)]['Voltage Range']\n\ttotal_samples_per_waveform = data['Oscilloscopes']['Picoscope 4444']['Channels']['Channel '+str(channel)]['Waveform Number of Samples']\t\n\twaveforms_per_wb_cycle = data['Oscilloscopes']['Picoscope 4444']['Channels']['Channel '+str(channel)]['Waveforms per WB Cycle']\t\n\t\n\trange_val, range_unit = voltage_range_str.split()\n\trange_val_mv = 0\n\tif range_unit == 'V':\n\t\trange_val_mv = 1000 * int(range_val)\n\telse:\n\t\trange_val_mv = int(range_val)\n\tprint ('range_mv =', range_val_mv)\t\t\t\n\t\n\t\nwith open(sorted_directories[ic_cycle]+'stat.json') as json_file: \n\tdata = json.load(json_file)\n\tcaptured_waveforms = data['Oscilloscopes']['Picoscope 4444']['Channels']['Channel '+str(channel)]['Waveforms found']\n\t\n\n\n\n# get the following data from json\nwb_cycle_total_samples = waveforms_per_wb_cycle * total_samples_per_waveform\ni = 0\nsample_offset = wb_cycle * wb_cycle_total_samples + wb_sub_cycle * total_samples_per_waveform\n\n\n\n\t\n\nexists = os.path.isfile(stream_filename)\nif exists:\n\t# Store configuration file values\n\ttest = 0\nelse:\n\t# Keep presets\n\tprint('ch1 file doesn t exist \\n')\n\tsys.exit()\n\nfp_stream = open(stream_filename, \"rb\")\nfp_stream.seek(sample_offset * 2)\nstream1 = np.fromfile(fp_stream, dtype=([('channel', 'maxADCValue;\ndata = np.float64(stream1['channel'])\ndata = data * range_val_mv / 32768\n\n\n\n\n# # Create a trace\ntrace = go.Scatter(\n y = stream1['channel']\n)\nlayout = go.Layout(\n margin=dict(\n l=0,\n r=0,\n b=0,\n t=0,\n\t\tpad=4\n ),\n paper_bgcolor='#7f7f7f',\n plot_bgcolor='#c7c7c7'\t\n)\nfig = plt.figure()\nfig = go.Figure(data=[trace], layout=layout)\nplotly.offline.plot(fig, filename= output_path + 'ch_' + str(channel) + \".html\", auto_open=False)\n\n\n","sub_path":"prg/picoscope_4444/python/process_raw_html.py","file_name":"process_raw_html.py","file_ext":"py","file_size_in_byte":4168,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"451255657","text":"# -*- coding: utf-8 -*-\nimport unittest\n\nfrom openregistry.assets.core.tests.base import MigrationResourcesDTO_mock\nfrom openregistry.assets.bounce.tests.base import (\n BaseAssetWebTest,\n get_snapshot,\n)\nfrom openregistry.assets.bounce.migration import (\n AddRelatedProcessesStep,\n BounceMigrationsRunner,\n)\nfrom openregistry.assets.bounce.tests.json_data import test_asset_bounce_data_schema_0\n\n\nclass AddRelatedProcessesMigrationStepTest(BaseAssetWebTest):\n\n def setUp(self):\n super(AddRelatedProcessesMigrationStepTest, self).setUp()\n self.initial_data = test_asset_bounce_data_schema_0\n\n asset_data = get_snapshot('bounce_migration_1.json')\n # create relatedLot\n lot_data = {'lotID': 'id' * 16}\n self.lot_id = self.db.save(lot_data)[0]\n # connect asset to the lot\n asset_data['relatedLot'] = self.lot_id\n self.asset_id = self.db.save(asset_data)[0]\n aliases_info = {'openregistry.assets.bounce': ('bounce', )}\n migration_resources = MigrationResourcesDTO_mock(self.db, aliases_info)\n self.runner = BounceMigrationsRunner(migration_resources)\n\n def test_ok(self):\n \"\"\"General migration test\"\"\"\n steps = (AddRelatedProcessesStep,)\n self.runner.migrate(steps, schema_version_max=1)\n\n asset_doc = self.db[self.asset_id]\n self.assertIn('relatedProcesses', asset_doc.keys())\n self.assertNotIn('relatedLot', asset_doc.keys())\n self.assertEqual(self.lot_id, asset_doc['relatedProcesses'][0]['relatedProcessID'])\n\n def test_status_without_related_lot(self):\n \"\"\"\n Only certain statuses could have the `relatedLot` attribute\n\n So there is a need to test that skip predicate works correctly with them.\n \"\"\"\n # set lot status to that one, that have not relatedLot\n TARGET_STATUS = 'draft'\n\n asset_doc = self.db[self.asset_id]\n asset_doc['status'] = TARGET_STATUS\n self.db.save(asset_doc)\n\n steps = (AddRelatedProcessesStep, )\n self.runner.migrate(steps, schema_version_max=1)\n\n\ndef suite():\n tests = unittest.TestSuite()\n tests.addTest(unittest.makeSuite(Migration0to1Test))\n return tests\n\n\nif __name__ == '__main__':\n unittest.main(defaultTest='suite')\n","sub_path":"openregistry/assets/bounce/tests/migration.py","file_name":"migration.py","file_ext":"py","file_size_in_byte":2289,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"318862926","text":"#! /usr/bin/env python\n#$ -S /home/masaki/programs/anaconda/envs/research/bin/python\n#$ -cwd\n\nimport os\nimport matplotlib.pyplot as plt\nfrom matplotlib import font_manager as fm\nimport numpy as np\nimport utils\n\ndef main():\n (curr_wk_dir, asset_dir, program_dir, conda_program_dir) = utils.getDirs()\n utils.initMpl()\n input_file = asset_dir + '/func_ncrnas.fa'\n ncrna_types = getNcrnaTypeRatio(input_file)\n print(ncrna_types)\n plt.axis('equal')\n (fig, ax) = plt.subplots()\n legend = ncrna_types.keys()\n colors = ['aqua', 'yellowgreen', 'gold', 'lightskyblue', 'lightcoral', 'magenta']\n radius = 1.0\n (patches, texts, autotexts) = ax.pie(ncrna_types.values(), colors = colors, autopct = '%1.1f%%', shadow = False, startangle = 90, radius = radius, pctdistance = radius * 1.15)\n ax.set_aspect('equal')\n ax.legend(patches, legend, loc = 2)\n # ax.set_title('Ratio of ncRNAs of type')\n proptease = fm.FontProperties()\n proptease.set_size('x-large')\n plt.setp(autotexts, fontproperties = proptease)\n # plt.show()\n fig.savefig(asset_dir + '/images/func_ncrna_stats.eps', bbox_inches = 'tight')\n \ndef getNcrnaTypeRatio(file): \n input_handle = open(file, 'rU')\n lines = input_handle.readlines()\n input_handle.close()\n ncrna_types = {}\n for line in lines: \n if not line.startswith('>'): \n continue\n rna_str_pos = line.find('RNA')\n ncrna_type = 'pseudogene' if rna_str_pos == -1 else line[3 : rna_str_pos].lower() + line[rna_str_pos : rna_str_pos + 3]\n if ncrna_type.find('tRNA') != -1: \n ncrna_type = 'tRNA'\n try: \n ncrna_types[ncrna_type] += 1\n except: \n ncrna_types[ncrna_type] = 1 \n return ncrna_types\n\nif __name__ == '__main__':\n main()\n","sub_path":"src/get_func_ncrna_stats.py","file_name":"get_func_ncrna_stats.py","file_ext":"py","file_size_in_byte":1697,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"596920294","text":"import json\nimport tweepy\nfrom tweepy import OAuthHandler\n\nclass _Twitter(type):\n\tdef __call__(cls, *args, **kwargs):\n\t\tif not hasattr(cls, 'instance'):\n\t\t\tcls.instance = super(_Twitter, cls).__call__(*args, **kwargs)\n\t\treturn cls.instance\n\nclass Twitter(object, metaclass=_Twitter):\n\tdef __init__(self):\n\t\tself.consumer_key = ''\n\t\tself.consumer_secret = ''\n\t\tself.access_key = ''\n\t\tself.access_secret = ''\n\t\tself.session = None\n\t\tself.api = None\n\t\tself.maxPage = 0\n\t\tself.maxCount = 0\n\n\tdef loadConfig(self):\n\t\twith open(\"config.json\") as data:\n\t\t\tconf = json.load(data)\n\t\t\tself.consumer_key = conf['consumer_key']\n\t\t\tself.consumer_secret = conf['consumer_secret']\n\t\t\tself.access_key = conf['access_key']\n\t\t\tself.access_secret = conf['access_secret']\n\t\t\tself.maxCount = int(conf['maxCount'])\n\t\t\tself.maxPage = int(conf['maxPage'])\n\t\treturn self\n\n\tdef auth(self):\n\t\tif self.session is None:\n\t\t\tself.session = OAuthHandler(self.consumer_key, self.consumer_secret)\n\t\t\tself.session.set_access_token(self.access_key, self.access_secret)\n\t\t\tself.api = tweepy.API(self.session, wait_on_rate_limit=True, wait_on_rate_limit_notify=True, compression=True)\n\t\treturn self\n\n\tdef getAPI(self):\n\t\treturn self.api\n\n\tdef getMaxCount(self):\n\t\treturn self.maxCount\n\n\tdef getMaxPage(self):\n\t\treturn self.maxPage\n\n\nAPI = Twitter().loadConfig().auth().getAPI()\nMaxCount = Twitter().getMaxCount()\nMaxPage = Twitter().getMaxPage()","sub_path":"TwitterScraper/Twitter/Twitter.py","file_name":"Twitter.py","file_ext":"py","file_size_in_byte":1407,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"291454234","text":"import os\nimport time\n\nfrom telegram import Update\nfrom telegram.ext import Updater, CommandHandler\n\nfrom data.copart import Copart\nfrom data.utils import EditThread\n\n\ndef search(update: Update, context):\n default_args = [*([0, float('inf')] * 2)]\n names = ['year_from', 'year_to', 'price_from', 'price_to']\n try:\n filters = {names[i]: int(context.args[i]) if i < len(context.args) and context.args[i] != '-1'\n else default_args[i] for i in range(len(default_args))}\n except ValueError:\n return update.message.reply_text('Все аргументы должны быть целочисленными!')\n message = update.message.reply_text('Начинаем поиск...')\n edit_thread = EditThread(message)\n edit_thread.start()\n start_time = time.time()\n copart = Copart()\n output = copart.get_data(filters)\n edit_thread.stop()\n update.message.reply_text(f'Найдено {len(output)} автомобилей.\\n'\n f'Время поиска: {time.time() - start_time:.2f} секунд')\n for car in output:\n update.message.reply_text(car['ld'])\n\n\ndef start(update, _):\n update.message.reply_text('Привет! Это бот-парсер американских автобирж. '\n 'Введите /search {year_from} {year_to} {price_from} {price_to} '\n 'для поиска авто')\n\n\ndef main():\n updater = Updater(os.getenv('tg_token'))\n updater.dispatcher.add_handler(CommandHandler('start', start))\n updater.dispatcher.add_handler(CommandHandler('search', search, pass_args=True))\n updater.start_polling()\n updater.idle()\n\n\nif __name__ == '__main__':\n main()\n","sub_path":"parsing/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":1756,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"262417305","text":"from random import randint\n\ncards = {1 : \"Ace of Hearts\",\n 2 : \"Two of Hearts\",\n 3 : \"Three of Hearts\",\n 4 : \"Four of Hearts\",\n 5 : \"Five of Hearts\",\n 6 : \"Six of Hearts\",\n 7 : \"Seven of Hearts\",\n 8 : \"Eight of Hearts\",\n 9 : \"Nine of Hearts\",\n 10 : \"Ten of Hearts\",\n 11 : \"Jack of Hearts\",\n 12 : \"Queen of Hearts\",\n 13 : \"King of Hearts\",\n 14 : \"Ace of Diamonds\",\n 15 : \"Two of Diamonds\",\n 16 : \"Three of Diamonds\",\n 17 : \"Four of Diamonds\",\n 18 : \"Five of Diamonds\",\n 19 : \"Six of Diamonds\",\n 20 : \"Seven of Diamonds\",\n 21 : \"Eight of Diamonds\",\n 22 : \"Nine of Diamonds\",\n 23 : \"Ten of Diamonds\",\n 24 : \"Jack of Diamonds\",\n 25 : \"Queen of Diamonds\",\n 26 : \"King of Diamonds\",\n 27 : \"Ace of Clubs\",\n 28 : \"Two of Clubs\",\n 29 : \"Three of Clubs\",\n 30 : \"Four of Clubs\",\n 31 : \"Five of Clubs\",\n 32 : \"Six of Clubs\",\n 33 : \"Seven of Clubs\",\n 34 : \"Eight of Clubs\",\n 35 : \"Nine of Clubs\",\n 36 : \"Ten of Clubs\",\n 37 : \"Jack of Clubs\",\n 38 : \"Queen of Clubs\",\n 39 : \"King of Clubs\",\n 40 : \"Ace of Spades\",\n 41 : \"Two of Spades\",\n 42 : \"Three of Spades\",\n 43 : \"Four of Spades\",\n 44 : \"Five of Spades\",\n 45 : \"Six of Spades\",\n 46 : \"Seven of Spades\",\n 47 : \"Eight of Spades\",\n 48 : \"Nine of Spades\",\n 49 : \"Ten of Spades\",\n 50 : \"Jack of Spades\",\n 51 : \"Queen of Spades\",\n 52 : \"King of Spades\"\n}\n\ndef five_card_draw(card):\n already_drawn = []\n first_card = randint(1, 52)\n already_drawn.append(first_card)\n second_card = randint(1,52)\n \n while second_card in already_drawn:\n second_card = randint(1,52)\n already_drawn.append(second_card)\n third_card = randint(1, 52)\n \n while third_card in already_drawn:\n third_card = randint(1, 52)\n already_drawn.append(third_card)\n fourth_card = randint(1, 52)\n \n while fourth_card in already_drawn:\n fourth_card = randint(1, 52)\n already_drawn.append(fourth_card)\n fifth_card = randint(1, 52)\n \n while fifth_card in already_drawn:\n fifth_card = randint(1, 52)\n already_drawn.append(fifth_card)\n return already_drawn\n\nyour_hand = five_card_draw(cards)\n\nfor i in your_hand:\n print(cards[i])\n","sub_path":"fiveCardDraw-Copy1.py","file_name":"fiveCardDraw-Copy1.py","file_ext":"py","file_size_in_byte":2461,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"413518482","text":"from .models import User\nfrom django import forms\n\nclass UserForm(forms.ModelForm):\n class Meta:\n # specify model to be used\n model = User\n\n # specify fields to be used\n fields = [\n \"first_name\",\n \"second_name\",\n ]","sub_path":"students/y2333/practical_works/Gordienko_Maxim/Practice 2/forms.py","file_name":"forms.py","file_ext":"py","file_size_in_byte":282,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"506242001","text":"\"\"\"\nWSGI Apps\nDefine your flask applications here to mount them to root urls.\n\"\"\"\napps = dict(default_app='backend', apps={})\n\n# frontend app\napps['apps']['backend'] = dict(\n module='project.backend',\n base_url='/'\n)","sub_path":"boiler/boiler_template/config/apps.py","file_name":"apps.py","file_ext":"py","file_size_in_byte":222,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"290058908","text":"from django.urls import path\nfrom customers.views import (\n\tcustomer_create_view, \n\tcustomer_detail_view, \n\tcustomer_delete_view, \n\tcustomer_list_view,\n\tcustomer_update_view,\n\n)\n\napp_name = 'customers'\nurlpatterns = [\n path('create/', customer_create_view),\n path('/', customer_detail_view, name='customer-detail'),\n path('/update', customer_update_view, name='customer-update'),\n path('/delete', customer_delete_view, name='customer-delete'),\n path('', customer_list_view, name='customer-list'),\n\n]\n","sub_path":"src/customers/urls.py","file_name":"urls.py","file_ext":"py","file_size_in_byte":548,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"379636459","text":"from manimlib import *\r\n\r\nclass d123(ThreeDScene):\r\n def construct(self):\r\n dotA = Dot(3*LEFT+2*UP)\r\n dotB = Dot(3*LEFT+2*UP)\r\n dotC = Dot(3*LEFT+2*UP)\r\n numberl = NumberLine(x_range=np.array([0,7,1]), unit_size=1,include_numbers=False,\r\n include_tip=True, line_to_number_direction=DOWN,numbers_to_exclude=[8])\r\n self.play(ShowCreation(numberl))\r\n numberp = NumberPlane(x_range=np.array([0,7,1]),y_range=np.array([0,7,1]), unit_size=1,include_numbers=False,\r\n include_tip=True, line_to_number_direction=DOWN,numbers_to_exclude=[8])\r\n self.play(ShowCreation(numberp))\r\n numberz = ThreeDAxes()\r\n self.play(ShowCreation(numberz))\r\n # self.play(numberl.copy().rotate,90*DEGREES)\r\n line = Line(ORIGIN+1.5*LEFT+1.5*DOWN,1.5*RIGHT+1.5*DOWN)\r\n square = Square(side_length = 3)\r\n cube = Cube(side_length = 3)\r\n line.set_color(color = BLUE)\r\n square.set_color(color = BLUE)\r\n \r\n \r\n cube.move_to([0,0,-1.5])\r\n\r\n brace_line = Brace(line,DOWN)\r\n brace_line.set_color(color = BLACK)\r\n brace_sq1 = Brace(square,RIGHT)\r\n brace_sq1.set_color(color = BLACK)\r\n brace_cube = Brace(cube,LEFT)\r\n brace_cube.set_color(color = BLACK)\r\n d1 = Tex(\"1D\")\r\n d2 = Tex(\"2D\")\r\n d3 = Tex(\"3D\")\r\n d1.to_edge(UP)\r\n d2.to_edge(UP)\r\n d3.to_edge(UP)\r\n self.play(ShowCreation(line))\r\n self.play(ShowCreation(brace_line))\r\n self.play(Write(d1))\r\n self.wait()\r\n self.play(ShowCreation(square))\r\n self.play(ShowCreation(brace_sq1))\r\n self.play(ReplacementTransform(d1,d2))\r\n self.wait()\r\n self.play(ShowCreation(cube))\r\n self.play(ReplacementTransform(d2,d3))\r\n\r\n frame = self.camera.frame\r\n self.play(frame.animate.increment_phi(70 * DEGREES),\r\n frame.animate.increment_gamma(130 * DEGREES),\r\n frame.animate.increment_theta(-30 * DEGREES))\r\n # frame.set_euler_angles(\r\n # theta=-30 * DEGREES,\r\n # phi=70 * DEGREES,\r\n # )\r\n self.wait(3)\r\n\r\n\r\nclass space_slide3(Scene):\r\n def construct(self):\r\n tda = ThreeDAxes()\r\n cub = Cube()\r\n cub.scale(0.5)\r\n cub.move_to(ORIGIN)\r\n frame = self.camera.frame\r\n self.play(frame.animate.increment_phi(70 * DEGREES),\r\n frame.animate.increment_gamma(130 * DEGREES),\r\n frame.animate.increment_theta(-30 * DEGREES))\r\n frame.set_euler_angles(\r\n theta=-30 * DEGREES,\r\n phi=70 * DEGREES,\r\n )\r\n self.play(ShowCreation(tda))\r\n self.play(ShowCreation(cub))\r\n self.play(cub.shift,3*UP)\r\n self.play(cub.shift,-3*UP)\r\n self.play(cub.shift,3*IN)\r\n self.play(cub.shift,-3*IN)\r\n self.play(cub.shift,3*RIGHT)\r\n self.play(cub.shift,-3*RIGHT)\r\n self.play(cub.move_to,3*RIGHT+2*UP+2*OUT)\r\n self.play(cub.move_to,-3*RIGHT-2*UP+2*OUT)\r\n self.play(cub.move_to,3*RIGHT+2*UP-2*OUT)\r\n self.wait(3)\r\n\r\n\r\nclass space_slide4(Scene):\r\n def construct(self):\r\n numberl = NumberLine(x_range=np.array([0,12,1]), unit_size=1,\r\n include_numbers=True,include_tip=True, line_to_number_direction=DOWN,numbers_to_exclude=[12])\r\n numberl.shift(2*DOWN)\r\n self.play(ShowCreation(numberl))\r\n w = 6\r\n h = 3.5\r\n \r\n paralelogram = Polygon(\r\n ORIGIN, w*RIGHT,w*RIGHT+h*UP+2*RIGHT,h*UP+2*RIGHT,\r\n width = width_stroke,stroke_color = color_stroke,\r\n fill_color = color_fill,\r\n fill_opacity = opacity_fill\r\n )\r\n paralelogram.move_to(ORIGIN)\r\n self.play(ShowCreation(paralelogram))\r\n self.wait(3)\r\n\r\n\r\n\r\nclass space_slide5(Scene):\r\n def construct(self):\r\n A = 3.5\r\n dotA = Dot(A*RIGHT)\r\n numberl = NumberLine(x_range=np.array([0,7,1]), unit_size=1,include_numbers=False,\r\n include_tip=True, line_to_number_direction=DOWN,numbers_to_exclude=[8])\r\n self.play(ShowCreation(numberl))\r\n self.play(ShowCreation(dotA))\r\n self.play(dotA.move_to,5*RIGHT)\r\n gd = VGroup(dotA,numberl)\r\n self.remove(gd)\r\n axes = Axes(\r\n \r\n x_range=(-1, 10),\r\n \r\n y_range=(-2, 2, 0.5),\r\n \r\n height=6,\r\n width=10,\r\n \r\n axis_config={\r\n \"stroke_color\": GREY_A,\r\n \"stroke_width\": 2,\r\n },\r\n \r\n y_axis_config={\r\n \"include_tip\": False,\r\n }\r\n )\r\n \r\n axes.add_coordinate_labels(\r\n font_size=20,\r\n num_decimal_places=1,\r\n )\r\n self.add(axes)\r\n\r\n \r\n dot = Dot(color=RED)\r\n dot.move_to(axes.c2p(0, 0))\r\n self.play(FadeIn(dot, scale=0.5))\r\n self.play(dot.animate.move_to(axes.c2p(3, 2)))\r\n self.wait()\r\n self.play(dot.animate.move_to(axes.c2p(5, 0.5)))\r\n self.wait()\r\n\r\n \r\n h_line = always_redraw(lambda: axes.get_h_line(dot.get_left()))\r\n v_line = always_redraw(lambda: axes.get_v_line(dot.get_bottom()))\r\n\r\n self.play(\r\n ShowCreation(h_line),\r\n ShowCreation(v_line),\r\n )\r\n self.play(dot.animate.move_to(axes.c2p(3, -2)))\r\n self.wait()\r\n self.play(dot.animate.move_to(axes.c2p(1, 1)))\r\n self.wait()\r\n\r\n \r\n f_always(dot.move_to, lambda: axes.c2p(1, 1))\r\n self.play(\r\n axes.animate.scale(0.75),\r\n axes.animate.to_corner(UL),\r\n run_time=2,\r\n )\r\n self.wait()\r\n self.play(FadeOut(VGroup(axes, dot, h_line, v_line)))\r\n\r\n\r\n\r\nclass space_slide6(Scene):\r\n def construct(self):\r\n numberl = NumberLine(x_range=np.array([-7,7,1]), unit_size=1,\r\n include_numbers=True,include_tip=True, line_to_number_direction=DOWN,numbers_to_exclude=[8])\r\n \r\n self.play(ShowCreation(numberl))\r\n line1 = Line(ORIGIN,2*RIGHT)\r\n brace1 = Brace(line1,UP)\r\n self.play(ShowCreation(brace1))\r\n self.wait()\r\n self.play(FadeOut(brace1))\r\n line1 = Line(ORIGIN,5*RIGHT)\r\n brace1 = Brace(line1,UP)\r\n self.play(ShowCreation(brace1))\r\n self.wait()\r\n self.play(FadeOut(brace1))\r\n line1 = Line(ORIGIN,-4*RIGHT)\r\n brace1 = Brace(line1,UP)\r\n self.play(ShowCreation(brace1))\r\n self.play(FadeOut(brace1))\r\n self.wait(3)\r\n\r\nclass space_slide7(Scene):\r\n def construct(self):\r\n A = 3*UP+2*LEFT\r\n B = 2*UP+0*RIGHT\r\n C = -2*UP+2*RIGHT\r\n D = -3*UP-2*RIGHT\r\n E = 0*UP-4*RIGHT\r\n lineAB = Line(A,B)\r\n lineBC = Line(B,C)\r\n lineCD = Line(C,D)\r\n lineDE = Line(D,E)\r\n lineEA = Line(E,A)\r\n\r\n dotA = SmallDot(A)\r\n dotB = SmallDot(B)\r\n dotC = SmallDot(C)\r\n dotD = SmallDot(D)\r\n dotE = SmallDot(E)\r\n\r\n self.play(ShowCreation(dotA),ShowCreation(dotB),\r\n ShowCreation(lineAB))\r\n \r\n self.play(ShowCreation(dotC),ShowCreation(lineBC))\r\n self.play(ShowCreation(dotD),ShowCreation(lineCD))\r\n self.play(ShowCreation(dotE),ShowCreation(lineDE))\r\n self.play(ShowCreation(lineEA))\r\n \r\n self.wait(3)\r\n","sub_path":"bazinga_2_geometry2d_space.py","file_name":"bazinga_2_geometry2d_space.py","file_ext":"py","file_size_in_byte":7547,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"96215502","text":"import re\nimport json\nimport pprint\n\nfrom django.core.urlresolvers import reverse\nfrom django.test import TestCase\nfrom django.test.client import Client\n\nfrom assessment.tests import build_assessments_for_permissions_testing\nfrom utils.helper import HAWCDjangoJSONEncoder\n\nfrom .models import SummaryText\n\nclass SummaryTextTests(TestCase):\n def setUp(self):\n build_assessments_for_permissions_testing(self)\n\n @staticmethod\n def clean_json(json_dump):\n remove_fields = ['created', 'last_updated', 'slug', 'text', 'assessment']\n for node in json_dump:\n node.pop('id')\n for field in remove_fields:\n node['data'].pop(field)\n if node.get('children'):\n SummaryTextTests.clean_json(node['children'])\n\n\n def test_adding_texts(self):\n lvl_1a = SummaryText.add_summarytext(assessment=self.assessment_working,\n title='lvl_1a',\n slug='lvl_1a',\n text='text')\n\n lvl_1b = SummaryText.add_summarytext(assessment=self.assessment_working,\n title='lvl_1b',\n slug='lvl_1b',\n text='text')\n\n lvl_2a = SummaryText.add_summarytext(assessment=self.assessment_working,\n parent=[lvl_1a],\n title='lvl_2a',\n slug='lvl_2a',\n text='text')\n\n lvl_2b = SummaryText.add_summarytext(assessment=self.assessment_working,\n sibling=[lvl_2a],\n title='lvl_2b',\n slug='lvl_2b',\n text='text')\n\n assessment_root = SummaryText.get_assessment_root_node(self.assessment_working)\n\n tree_form = SummaryText.dump_bulk(assessment_root)\n # print pprint.pprint(tree_form)\n\n SummaryTextTests.clean_json(tree_form)\n self.assertEqual(json.dumps(tree_form),\"\"\"[{\"data\": {\"title\": \"assessment-1\"}, \"children\": [{\"data\": {\"title\": \"lvl_1a\"}, \"children\": [{\"data\": {\"title\": \"lvl_2a\"}}, {\"data\": {\"title\": \"lvl_2b\"}}]}, {\"data\": {\"title\": \"lvl_1b\"}}]}]\"\"\")\n\n\n # Swap 2a and 2b\n lvl_2b.move_summarytext(parent=lvl_1a, sibling=None)\n tree_form = SummaryText.dump_bulk(assessment_root)\n SummaryTextTests.clean_json(tree_form)\n self.assertEqual(json.dumps(tree_form),\"\"\"[{\"data\": {\"title\": \"assessment-1\"}, \"children\": [{\"data\": {\"title\": \"lvl_1a\"}, \"children\": [{\"data\": {\"title\": \"lvl_2b\"}}, {\"data\": {\"title\": \"lvl_2a\"}}]}, {\"data\": {\"title\": \"lvl_1b\"}}]}]\"\"\")\n\n # Swap back\n lvl_2b.move_summarytext(parent=None, sibling=lvl_2a)\n tree_form = SummaryText.dump_bulk(assessment_root)\n SummaryTextTests.clean_json(tree_form)\n self.assertEqual(json.dumps(tree_form),\"\"\"[{\"data\": {\"title\": \"assessment-1\"}, \"children\": [{\"data\": {\"title\": \"lvl_1a\"}, \"children\": [{\"data\": {\"title\": \"lvl_2a\"}}, {\"data\": {\"title\": \"lvl_2b\"}}]}, {\"data\": {\"title\": \"lvl_1b\"}}]}]\"\"\")\n\n","sub_path":"project/summary/tests.py","file_name":"tests.py","file_ext":"py","file_size_in_byte":3342,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"499603482","text":"import os\nimport sys\nimport torch\nfrom collections import defaultdict\nimport json\nimport pickle\nimport logging\nlogging.basicConfig()\n\nsys.path.append(os.getcwd())\nfrom generalization_config import config\nfrom utils.graph_utils import create_adj_matrix, blockify_A, create_coordinate_channel, \\\n create_edge_index_from_adjacency_matrix\nfrom utils.training_gcn_utils import validate\nfrom utils.training_unet_utils import validate as validate_unet\nfrom utils.videoloader import trafic4cast_dataset\n\n\nfrom models.unet import UNet\nfrom models.graph_models import KipfNet_orig, KipfNet, KipfNetd2, Graph_resnet\n\n\n\ndef get_graphdata_obj(inputs, edge_index, y, num_features=38, num_classes=9):\n graphdata = Data(x=inputs, edge_index=edge_index, y=y)\n\n return graphdata\n\n\ndef get_n_params(model):\n pp = 0\n for p in list(model.parameters()):\n nn = 1\n for s in list(p.size()):\n nn = nn * s\n pp += nn\n return pp\n\n\nif __name__ == \"__main__\":\n print('batch_size: ', config['dataloader']['batch_size'])\n print(config['device_num'])\n device = torch.device(config['device_num'])\n\n model_tuple_list = config['model_tuple_list']\n\n resultdict = defaultdict(dict)\n\n for city in ['Berlin', 'Moscow', 'Istanbul']:\n config['dataset']['cities'] = [city]\n\n dataset_val = trafic4cast_dataset(split_type='validation', **config['dataset'],\n reduce=True, filter_test_times=True)\n\n val_loader = torch.utils.data.DataLoader(dataset_val, shuffle=False,\n **config['dataloader'])\n\n for model_tuple in model_tuple_list:\n model_plot_name = model_tuple[0]\n model_path = model_tuple[1]\n is_graph = model_tuple[2]\n graph_model_name = model_tuple[3]\n\n with open(os.path.join(model_path, 'config.json'), 'r') as f:\n model_config = json.load(f)\n\n adj, nn_ixs, G, mask = create_adj_matrix(city=config['dataset']['cities'][0],\n mask_threshold=config['mask_threshold'])\n\n if not is_graph:\n model_config['model']['batch_norm'] = True\n model = UNet(**model_config['model']).to(device)\n model.load_state_dict(torch.load(os.path.join(model_path, 'checkpoint.pt'),\n map_location=device))\n\n mask = torch.from_numpy(mask).to(device)\n\n if 'MIE-Lab' in model_plot_name:\n norm = False\n else:\n norm = True\n\n val_loss = validate_unet(model=model, val_loader=val_loader, device=device, mask=mask,\n config=model_config, print_loss=False, norm=norm)\n\n if is_graph:\n\n n_features = 38\n batch_size = config['dataloader']['batch_size']\n assert batch_size == 1, \"batch_size should be 1 for graphs\"\n\n coords = create_coordinate_channel(b=batch_size)\n\n if config['dataloader']['batch_size'] > 1:\n adj = blockify_A(adj, config['dataloader']['batch_size'])\n\n edge_index = create_edge_index_from_adjacency_matrix(adj)\n edge_index = edge_index.to(device)\n\n if graph_model_name == 'kipfnet':\n model = KipfNet_orig(num_features=n_features,\n num_classes=9, **model_config['model']['KIPF']).to(device)\n model.load_state_dict(torch.load(os.path.join(model_path, 'checkpoint.pt'),\n map_location=device))\n\n elif graph_model_name == 'skipfnet':\n model = KipfNet(num_features=n_features,\n num_classes=9, **model_config['model']['KipfNet']).to(device)\n model.load_state_dict(torch.load(os.path.join(model_path, 'checkpoint.pt'),\n map_location=device))\n\n elif graph_model_name == 'skipfnet2d':\n model = KipfNetd2(num_features=n_features,\n num_classes=9, **model_config['model']['KipfNetd2']).to(device)\n model.load_state_dict(torch.load(os.path.join(model_path, 'checkpoint.pt'),\n map_location=device))\n\n elif graph_model_name == 'Graph_resnet':\n model = Graph_resnet(num_features=n_features,\n num_classes=9, **model_config['model']['Graph_resnet']).to(device)\n model.load_state_dict(torch.load(os.path.join(model_path, 'checkpoint.pt'),\n map_location=device))\n\n mask = None\n val_loss = validate(model=model, val_loader=val_loader, device=device,\n adj=adj, nn_ixs=nn_ixs, edge_index=edge_index, coords=coords,\n mask=mask, batch_size=batch_size, print_loss=False)\n\n print(\"Validation loss {}: {} = {:.2f}\".format(city, model_plot_name, val_loss))\n resultdict[model_plot_name][city] = val_loss\n\n nb_params = get_n_params(model)\n resultdict[model_plot_name]['nb_params'] = nb_params\n\n pickle.dump(resultdict, open(os.path.join('.', 'output', 'data_generalization.p'), 'wb'))\n","sub_path":"experiment/generalization.py","file_name":"generalization.py","file_ext":"py","file_size_in_byte":5807,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"127485154","text":"from datetime import datetime, timezone\n\nfrom app.configs.database import SingletonSQLAlchemy\n\n\ndb = SingletonSQLAlchemy()\n\n\nclass BaseModel(db.Model):\n __abstract__ = True\n\n id = db.Column(db.Integer, primary_key=True)\n create_at = db.Column(db.DateTime(timezone=True), default=lambda: datetime.now(timezone.utc))\n updated_at = db.Column(db.DateTime(timezone=True), nullable=True)\n\n def before_save(self, *args, **kwargs):\n return\n\n def before_save(self, *args, **kwargs):\n return\n\n def save(self, commit=True):\n self.before_save()\n\n db.session.add(self)\n if commit:\n try:\n db.session.commit()\n except Exception as error:\n db.session.rollback()\n raise error\n\n self.before_save()\n\n def delete(self, commit=True):\n db.session.delete(self)\n if commit:\n db.session.delete(self)\n","sub_path":"app/models/bases_model.py","file_name":"bases_model.py","file_ext":"py","file_size_in_byte":933,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"96900209","text":"import logging\nimport serial\nimport time\n\n###################################################################################\n\n\nclass CommUART(object):\n def __init__(self, address):\n self.address = address\n self.sc = None\n\n def connect(self):\n logging.debug(\"Opening COM port : {0}\".format(self.address))\n self.sc = None\n while self.sc is None:\n try:\n self.sc = serial.Serial(port=self.address, baudrate=3000000, rtscts=False)\n except serial.serialutil.SerialException as se:\n if 'Device or resource busy:' in se.__str__():\n logging.info('Opening COM port is taking a little while, please stand by...')\n else:\n logging.error('se: {0}'.format(se))\n time.sleep(1)\n logging.debug(\"COM port open successfully.\")\n self.sc.flushInput()\n\n def disconnect(self):\n logging.debug(\"Closing COM port : {0}\".format(self.address))\n self.sc.close()\n\n def receivedPacket(self, length):\n if self.sc is None:\n raise Exception('COM port is not opened.')\n packet = b''\n received = 0\n while received < length:\n serialByte = self.sc.read(1)\n if serialByte is None:\n raise Exception('Bad character.')\n elif len(serialByte) == 0:\n break\n elif received < length:\n received += 1\n packet += serialByte\n return packet\n \n def send(self, data):\n self.sc.write(bytes([data]))\n\n def prbs8(self, curval):\n newbit = (((curval >> 6) ^ (curval >> 5)) & 1)\n return ((curval << 1) | newbit) & 0x7f\n###################################################################################\n\ndef main():\n logging.basicConfig(level=logging.DEBUG, format='%(asctime)s : %(message)s')\n\n #comm = CommUART(\"/dev/cu.usbserial-FT0NCE8B\")\n #comm = CommUART(\"/dev/cu.usbmodem143422\")\n comm = CommUART(\"/dev/cu.usbmodem143132\")\n comm.connect()\n\n curval = 0\n #packet = comm.receivedPacket(1)\n #curval = int.from_bytes(packet, byteorder = 'little')\n val = comm.prbs8(0xff)\n byteCount = 0\n dropcnt = 0\n deltatime = 0\n drop = False\n while True:\n try:\n comm.send(val)\n startTime = time.time()\n# packet = comm1.receivedPacket(1)\n endTime = time.time()\n deltatime += endTime - startTime\n # curval = int.from_bytes(packet, byteorder = 'little')\n # if curval != val:\n # dropcnt += 1\n val = comm.prbs8(val)\n byteCount += 1\n\n if deltatime > 0:\n bytesPerSec = byteCount / deltatime #(endTime - startTime)\n\n #print(\"Bytes : {0}\".format(bytes))\n #if drop:\n # print(\"Dropped.... Bytes/sec : {0}\".format(bytesPerSec))\n #else:\n if (byteCount & 0xff) == 0:\n print(\"Bytes/sec : %.2f, drop %d \" %(bytesPerSec, dropcnt))\n except KeyboardInterrupt:\n print(\"KeyboardInterrupt. Exiting.\")\n break\n\n comm.disconnect()\n # comm1.disconnect()\n###################################################################################\n\n\nif __name__ == '__main__':\n main()\n","sub_path":"Python/uartprbs_tx.py","file_name":"uartprbs_tx.py","file_ext":"py","file_size_in_byte":3348,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"356452838","text":"#!/usr/bin/env python3\nfrom __future__ import print_function\n\nimport os\n\nimport pprint\nimport sys\nfrom googleapiclient.discovery import build\n\nif len(sys.argv) < 2:\n print('Usage: python3 group-allow-external-users.py group@email.address', file=sys.stderr)\n sys.exit(1)\n\ngroupId = sys.argv[1]\nservice = build('groupssettings', 'v1')\n\ngroup = service.groups()\ng = group.get(groupUniqueId=groupId).execute()\n\nbody = {\n 'allowExternalMembers': True\n}\ngroup.update(groupUniqueId=groupId, body=body).execute()\nprint('Group %s now allowed to have external members, enjoy.' % groupId)\n","sub_path":"scripts/group-allow-external-users.py","file_name":"group-allow-external-users.py","file_ext":"py","file_size_in_byte":587,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"311423379","text":"from tkinter import *\nwindow = Tk()\ndef km_to_miles():\n miles = float(e1_value.get())*.6\n t1.insert(END, miles)\ndef kg_conversion():\n grams = float(e1_value.get())*1000\n t1.insert(END, grams)\n pounds = float(e1_value.get())*2.20462\n t2.insert(END,pounds)\n ounces = float(e1_value.get())*35.274\n t3.insert(END, ounces)\nb1 = Button(window, text='Execute',command=kg_conversion)\nb1.grid(row=0,column=3)\nlabel = Label(window, text='Kg')\nlabel.grid(row=0,column=1)\ne1_value=StringVar()\ne1=Entry(window,textvariable=e1_value)\ne1.grid(row=0,column=2)\nt1=Text(window,height=1,width=20)\nt1.grid(row=1,column=1)\nt2=Text(window,height=1,width=20)\nt2.grid(row=1,column=2)\n\nt3=Text(window,height=1,width=20)\nt3.grid(row=1,column=3)\n\nwindow.mainloop()\n()","sub_path":"script1.py","file_name":"script1.py","file_ext":"py","file_size_in_byte":764,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"111741236","text":"from copy import deepcopy\nfrom opengever.base.schema import TableChoice\nfrom opengever.oneoffixx import _\nfrom opengever.oneoffixx.api_client import OneoffixxAPIClient\nfrom opengever.oneoffixx.command import CreateDocumentFromOneOffixxTemplateCommand\nfrom opengever.oneoffixx.utils import whitelisted_template_types\nfrom plone.i18n.normalizer.interfaces import IFileNameNormalizer\nfrom plone.supermodel import model\nfrom plone.z3cform.layout import FormWrapper\nfrom z3c.form import button\nfrom z3c.form.field import Fields\nfrom z3c.form.form import Form\nfrom zope import schema\nfrom zope.component import getUtility\nfrom zope.i18n import translate\nfrom zope.interface import provider\nfrom zope.schema.interfaces import IContextSourceBinder\nfrom zope.schema.vocabulary import SimpleVocabulary\n\n\ndef get_oneoffixx_favorites():\n \"\"\"Return the user chosen favorites as a template group, if any.\"\"\"\n api_client = OneoffixxAPIClient()\n favorites = api_client.get_oneoffixx_favorites()\n if favorites.get('templates'):\n return favorites\n return None\n\n\ndef get_oneoffixx_template_groups():\n \"\"\"Return the template groups.\n\n Potentially amended with user chosen favorites.\n \"\"\"\n api_client = OneoffixxAPIClient()\n # We need to work on a copy to not pollute the cached one\n template_groups = deepcopy(api_client.get_oneoffixx_template_groups())\n favorites = get_oneoffixx_favorites()\n if favorites:\n template_groups.insert(0, favorites)\n return template_groups\n\n\ndef get_oneoffixx_templates():\n \"\"\"Return all oneoffixx templates.\n\n We do not want duplicates from favorites here.\n \"\"\"\n api_client = OneoffixxAPIClient()\n return (\n OneOffixxTemplate(template, template_group.get('localizedName', ''))\n for template_group in api_client.get_oneoffixx_template_groups()\n for template in template_group.get(\"templates\")\n if template.get('metaTemplateId') in whitelisted_template_types\n )\n\n\ndef default_template_group():\n \"\"\"Return all templates, or the user favorites, if defined by user.\"\"\"\n favorites = get_oneoffixx_favorites()\n if favorites:\n return favorites.get('id')\n return None\n\n\n@provider(IContextSourceBinder)\ndef list_templates(context):\n \"\"\"Return a list available templates.\"\"\"\n templates = get_oneoffixx_templates()\n template_group = context.REQUEST.form.get('form.widgets.template_group')\n terms = []\n\n for template in templates:\n terms.append(SimpleVocabulary.createTerm(\n template, template.template_id, template.title))\n\n # We filter templates when template_group has been selected\n if template_group is not None:\n favorites = get_oneoffixx_favorites()\n # Favorites are a special case\n if favorites and template_group[0] == favorites.get('id'):\n terms = [\n SimpleVocabulary.createTerm(\n OneOffixxTemplate(\n template, favorites.get('localizedName', '')),\n template.get('id'),\n template.get('localizedName'),\n )\n for template in favorites.get('templates')\n ]\n elif template_group[0] != '--NOVALUE--':\n terms = [term for term in terms if term.value.group == template_group[0]]\n\n return MutableObjectVocabulary(terms)\n\n\n@provider(IContextSourceBinder)\ndef list_template_groups(context):\n \"\"\"Return the list of available template groups.\"\"\"\n template_groups = get_oneoffixx_template_groups()\n terms = []\n for group in template_groups:\n terms.append(SimpleVocabulary.createTerm(group.get(\"id\"),\n group.get(\"id\"),\n group.get(\"localizedName\")))\n return MutableObjectVocabulary(terms)\n\n\nclass OneOffixxTemplate(object):\n\n def __init__(self, template, groupname):\n self.title = template.get(\"localizedName\")\n self.template_id = template.get(\"id\")\n self.group = template.get('templateGroupId')\n self.groupname = groupname\n template_type = template['metaTemplateId']\n template_type_info = whitelisted_template_types[template_type]\n self.content_type = template_type_info['content-type']\n filename = template.get(\"localizedName\")\n normalizer = getUtility(IFileNameNormalizer, name='gever_filename_normalizer')\n self.filename = normalizer.normalize(filename, extension=template_type_info['extension'])\n self.languages = template.get(\"languages\")\n\n def __eq__(self, other):\n if type(other) == type(self):\n return self.template_id == other.template_id\n return False\n\n\nclass MutableObjectVocabulary(SimpleVocabulary):\n\n def __contains__(self, value):\n try:\n return any([value == val for val in self.by_value])\n except TypeError:\n return False\n\n\nclass ICreateDocumentFromOneOffixxTemplate(model.Schema):\n\n # XXX - this always renders the --NOVALUE-- as the actually chosen\n # default is actually loaded over AJAX - confusing and bad UX\n template_group = schema.Choice(\n title=_(u'label_template_group', default=u'Template group'),\n source=list_template_groups,\n required=False,\n defaultFactory=default_template_group,\n )\n\n template = TableChoice(\n title=_(u\"label_template\", default=u\"Template\"),\n source=list_templates,\n required=True,\n show_filter=True,\n vocabulary_depends_on=['form.widgets.template_group'],\n columns=(\n {'column': 'title',\n 'column_title': _(u'label_title', default=u'Title'),\n 'sort_index': 'sortable_title'},\n )\n )\n\n title = schema.TextLine(\n title=_(u\"label_title\", default=u\"Title\"),\n required=True)\n\n\nclass SelectOneOffixxTemplateDocumentWizardStep(Form):\n\n label = _(u'create_document_with_template', default=u'Create document from template')\n ignoreContext = True\n fields = Fields(ICreateDocumentFromOneOffixxTemplate)\n\n def updateWidgets(self, prefix=None):\n super(SelectOneOffixxTemplateDocumentWizardStep, self).updateWidgets(prefix=prefix)\n self.widgets['template_group'].noValueMessage = translate(\n _(u'label_all_template_groups', default=u'All templates'), context=self.request)\n\n def finish_document_creation(self, data):\n new_doc = self.create_document(data)\n self.activate_external_editing(new_doc)\n return self.request.RESPONSE.redirect(new_doc.absolute_url())\n\n def activate_external_editing(self, new_doc):\n \"\"\"Add the oneoffixx external_editor URL to redirector queue.\"\"\"\n new_doc.setup_external_edit_redirect(self.request, action=\"oneoffixx\")\n\n def create_document(self, data):\n \"\"\"Create a new document based on a template.\"\"\"\n command = CreateDocumentFromOneOffixxTemplateCommand(self.context, data['title'], data['template'])\n return command.execute()\n\n @button.buttonAndHandler(_('button_save', default=u'Save'), name='save')\n def handleApply(self, action):\n data, errors = self.extractData()\n\n if not errors:\n return self.finish_document_creation(data)\n\n self.status = self.formErrorsMessage\n return None\n\n @button.buttonAndHandler(_(u'button_cancel', default=u'Cancel'), name='cancel')\n def cancel(self, action):\n return self.request.RESPONSE.redirect(self.context.absolute_url())\n\n\nclass SelectOneOffixxTemplateDocumentView(FormWrapper):\n\n form = SelectOneOffixxTemplateDocumentWizardStep\n","sub_path":"opengever/oneoffixx/browser/form.py","file_name":"form.py","file_ext":"py","file_size_in_byte":7651,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"132085398","text":"'''\nCreated on Jan 28, 2017\n\n@author: vbera\n'''\nn = int(input().strip())\narr = [ int(x) for x in input().strip().split(' ')]\narr = sorted(arr, reverse=True)\nlengthArr = len(arr)\nwhile lengthArr > 0:\n print(lengthArr)\n minValue = arr[len(arr) - 1]\n arr[:] = [x - minValue for x in arr]\n zIndex = arr.index(0)\n arr = arr[0:zIndex]\n lengthArr = len(arr)\n \n ","sub_path":"CutTheSticks.py","file_name":"CutTheSticks.py","file_ext":"py","file_size_in_byte":378,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"533072377","text":"import matplotlib.pyplot as plt \r\nimport numpy as np\r\nimport matplotlib.ticker as ticker\r\n\r\n# result_file = \"../expt/results/task4_1.txt\"\r\nresult_file = \"finalT2.txt\"#\"outputDataT2.txt\"\r\ninstance_list = [\"../instances/i-1.txt\",\"../instances/i-2.txt\",\"../instances/i-3.txt\"]\r\n# instance_list = [\"i-1.txt\",\"i-2.txt\",\"i-3.txt\"]\r\nalgorithms = [\"thompson-sampling\", \"thompson-sampling\"]\r\nfinal_dict = {\"../instances/i-1.txt\":{}, \"../instances/i-2.txt\":{}, \"../instances/i-3.txt\":{}}\r\nhorizons = [100, 400, 1600, 6400, 25600, 102400]\r\n# final_dict = {\"i-3.txt\":{}, \"i-1.txt\":{}, \"i-2.txt\":{}}\r\nwith open(result_file,'r') as f:\r\n lines = f.readlines()\r\n for line in lines:\r\n x = line.rstrip().split(', ')\r\n if x[1] in final_dict[x[0]].keys():\r\n final_dict[x[0]][x[1]][int(np.log2(int(x[4])/100)/2)] += float(x[5])/50.0\r\n else:\r\n final_dict[x[0]][x[1]] = [0]*6\r\n final_dict[x[0]][x[1]][int(np.log2(int(x[4])/100)/2)] += float(x[5])/50.0\r\n\r\nfor i,instance in enumerate(instance_list):\r\n fig = plt.figure()\r\n ax = fig.add_subplot(111)\r\n ax.set_xscale('log')\r\n ax.xaxis.set_ticks(horizons)\r\n ax.get_xaxis().set_major_formatter(ticker.ScalarFormatter())\r\n ts = final_dict[instance][\"thompson-sampling\"]\r\n plt.plot(horizons,ts,label=\"Thompson-Sampling\")\r\n ts = final_dict[instance][\"thompson-sampling-with-hint\"]\r\n plt.plot(horizons,ts,label=\"Thompson-Sampling (with Hint)\")\r\n plt.xlabel(\"Horizon (Logarithmic Scale, Base 2)\")\r\n plt.ylabel(\"Average Regret\")\r\n plt.legend()\r\n\r\n pltTitle = instance.replace('../instances/', '')\r\n pltTitle = pltTitle.replace('.txt', '')\r\n pltTitle = pltTitle.replace('i-', 'Instance ')\r\n # plt.plot(x_axis,kl_ucb,x_axis,ts,x_axis,ucb,x_axis,eg)\r\n plt.title(\"{}\".format(pltTitle))\r\n plt.savefig(\"testT2_instance{}.png\".format(i+1))","sub_path":"Assignment1/submission/PlotGenT2.py","file_name":"PlotGenT2.py","file_ext":"py","file_size_in_byte":1863,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"8280225","text":"# Example solution for HW 4\n\n# %%\n# Import the modules we will use\nimport os\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\n\n# %%\n# ** MODIFY **\n# Set the file name and path to where you have stored the data\nfilename = 'streamflow_week5.txt'\nfilepath = os.path.join('data', filename)\nprint(os.getcwd())\nprint(filepath)\n\n# filepath = '../Assignments/Solutions/data/streamflow_week1.txt'\n\n# %%\n#Read the data into a pandas dataframe\ndata=pd.read_table(filepath, sep = '\\t', skiprows=30,\n names=['agency_cd', 'site_no', 'datetime', 'flow', 'code']\n )\n\n# Expand the dates to year month day\ndata[[\"year\", \"month\", \"day\"]] =data[\"datetime\"].str.split(\"-\", expand=True)\ndata['year'] = data['year'].astype(int)\ndata['month'] = data['month'].astype(int)\ndata['day'] = data['day'].astype(int)\n\n# %%\n# Sorry no more helpers past here this week, you are on your own now :) \n# Hints - you will need the functions: describe, info, groupby, sort, head and tail.\n#%%\n# Esimation5\ndata.flow\n# print(data.datetime[(data.flow >= rnge[0]) & (data.flow <= rnge[1])])\n\n# list_2010 = []\n# list_2011 = []\n# list_2012 = []\n# list_2013 = []\n# list_2014 = []\n# list_2015 = []\n# list_2016 = []\n# list_2017 = []\n# list_2016 = []\n# list_2017 = []\n# list_2020 = []\n\n# data.flow[(data.year >= 2010) & (data.year <= 2020) & (data.month == i)].mean]\n#%%\n# 1, 3, 5, 7, 8, 10, 12\nfor d in range(2010, 2020):\n fig1 = plt.figure()\n fig1.patch.set_facecolor('xkcd:mint green')\n plt.title('%d'%(d))\n plt.ylabel('flow')\n for i in (1, 3, 5, 7, 8, 10, 12):\n # print(i)\n # print(data.flow[(data.year == 2010) & (data.month == i)].mean)\n # print(\"\\n\")\n # data.flow[(data.year == 2010) & (data.month == i)]\n x = list(range(1, 32))\n plt.plot(x, (data.flow[(data.year == d) & (data.month == i)]))\n plt.xlabel('days in month')\n plt.legend(['1', '3', '5', '7', '8', '10', '12'])\n plt.savefig('graphs/flow-set1_%d'%(d))\n\n \n# x = list(range(1, 32))\n# print(x)\n\n\n# print(flow_data.size)\n# print(flow_data.shape)\n# flow_202009 = flow_data[11571:11585, 3]\n# print(flow_202009)\n\n# x = [6.,7,8,9,10,11,12,13,14,15,16,17,18,19]\n# fig9 = plt.figure()\n# fig9.patch.set_facecolor('xkcd:mint green')\n# plt.plot(x, flow_202009)\n# plt.xlabel('days in September 2020')\n# plt.ylabel('flow')\n# plt.legend()\n# plt.savefig('graphs/flow_202009')\n\n# %%\n# 4, 6, 9, 11\nfor d in range(2010, 2020):\n fig2 = plt.figure()\n fig2.patch.set_facecolor('xkcd:mint green')\n plt.title('%d'%(d))\n plt.ylabel('flow')\n for i in (4, 6, 9, 11):\n # print(i)\n # print(data.flow[(data.year == 2010) & (data.month == i)].mean)\n # print(\"\\n\")\n # data.flow[(data.year == 2010) & (data.month == i)]\n x = list(range(1, 31))\n # print(x)\n plt.plot(x, (data.flow[(data.year == d) & (data.month == i)]))\n plt.xlabel('days in the month')\n plt.legend(['4', '6', '9', '11'])\n plt.savefig('graphs/flow-set2_%d'%(d))\n# %%\n# 2020\n\nfig3 = plt.figure()\nfig3.patch.set_facecolor('xkcd:mint green')\nplt.title('2020')\nplt.ylabel('flow')\nfor i in (1, 3, 5, 7, 8):\n # print(i)\n # print(data.flow[(data.year == 2010) & (data.month == i)].mean)\n # print(\"\\n\")\n # data.flow[(data.year == 2010) & (data.month == i)]\n x = list(range(1, 32))\n # print(x)\n plt.plot(x, (data.flow[(data.year == 2020) & (data.month == i)]))\n plt.xlabel('days in the month')\n plt.legend(['1', '3', '5', '7', '8'])\n plt.savefig('graphs/flow-set3_2020-%i'%(i))\n\ndata.flow[(data.year == 2020) & (data.month == 1)]\n\nfig4 = plt.figure()\nfig4.patch.set_facecolor('xkcd:mint green')\nplt.title('2020')\nplt.ylabel('flow')\nfor i in (4, 6):\n # print(i)\n # print(data.flow[(data.year == 2010) & (data.month == i)].mean)\n # print(\"\\n\")\n # data.flow[(data.year == 2010) & (data.month == i)]\n x = list(range(1, 31))\n # print(x)\n plt.plot(x, (data.flow[(data.year == 2020) & (data.month == i)]))\n plt.xlabel('days in the month')\n plt.legend(['4', '6'])\n plt.savefig('graphs/flow-set4_2020-%i'%(i))\n# %%\n# When September Ends\nx = list(range(1, 27))\nfig5 = plt.figure()\nfig5.patch.set_facecolor('xkcd:mint green')\nplt.title('2020-9')\nplt.ylabel('flow')\nplt.plot(x, (data.flow[(data.year == 2020) & (data.month == 9)]))\nplt.xlabel('days in the month')\nplt.legend([])\nplt.savefig('graphs/flow-set5_2020-9')\n\nprint((data.flow[(data.year == 2020) & (data.month == 9)]))\n# %%\n","sub_path":"assignment_5/week5_pandas_starter_BM.py","file_name":"week5_pandas_starter_BM.py","file_ext":"py","file_size_in_byte":4760,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"141690023","text":"import sys\nimport threading\nfrom threading import *\n\n\nclass ReusableBarrierCond():\n\t\"\"\" Bariera reentranta, implementata folosind o variabila conditie \"\"\"\n\n\tdef __init__(self, num_threads):\n\t\tself.num_threads = num_threads\n\t\tself.count_threads = self.num_threads\n\t\tself.cond = Condition(Lock())\n\n\tdef wait(self):\n\t\tself.cond.acquire() # intra in regiunea critica\n\t\tself.count_threads -= 1; \n\t\tif self.count_threads == 0:\n\t\t\tself.cond.notify_all() # trezeste toate thread-urile, acestea vor putea reintra in regiunea critica dupa release\n\t\t\tself.count_threads=self.num_threads \n\t\telse: \n\t\t\tself.cond.wait(); # iese din regiunea critica, se blocheaza, cand se deblocheaza face acquire pe lock\n\t\tself.cond.release(); # iesim din regiunea critica\n\nclass ReusableBarrierSem():\n\t\"\"\" Bariera reentranta, implementata folosind semafoare \"\"\"\n\t\n\tdef __init__(self, num_threads):\n\t\tself.num_threads = num_threads\n\t\tself.count_threads1 = self.num_threads\n\t\tself.count_threads2 = self.num_threads\n\t\t\n\t\tself.counter_lock = Lock() # protejam decrementarea numarului de threaduri\n\t\tself.threads_sem1 = Semaphore(0) # contorizam numarul de threaduri pentru prima etapa\n\t\tself.threads_sem2 = Semaphore(0) # contorizam numarul de threaduri pentru a doua etapa\n\n\tdef wait(self):\n\t\tself.phase1()\n\t\tself.phase2()\n\n\tdef phase1(self):\n\t\twith self.counter_lock:\n\t\t\tself.count_threads1 -= 1\n\t\t\tif self.count_threads1 == 0:\n\t\t\t\tfor i in range(self.num_threads):\n\t\t\t\t\tself.threads_sem1.release()\n\t\t\tself.count_threads2 = self.num_threads\n\t\t \n\t\tself.threads_sem1.acquire()\n\t\t \n\tdef phase2(self):\n\t\twith self.counter_lock:\n\t\t\tself.count_threads2 -= 1\n\t\t\tif self.count_threads2 == 0:\n\t\t\t\tfor i in range(self.num_threads):\n\t\t\t\t\tself.threads_sem2.release()\n\t\t\tself.count_threads1 = self.num_threads\n\t\t \n\t\tself.threads_sem2.acquire()\n\nclass Request():\n\t\"\"\" Class that represent a request data type.\"\"\"\n\n\tdef __init__(self, op_type, node, pivot, item = []):\n\t\t\"\"\"\n\t\t\tConstructor.\n\n\t\t\t@type op_type: Integer\n\t\t\t@param op_type: 0 for get_data, \n\t\t\t\t\t\t\t1 for put_data,\n\t\t\t\t\t\t\t2 for get_x\n\t\t\t@type node: Node\n\t\t\t@param node: the node upon which the request is made\n\t\t\t@type item: List\n\t\t\t@param item: the list to be put in the Node datastore;\n\t\t\t\tit will only be called by the Node who owns the datastore\n\t\t\t@type pivot: Integer\n\t\t\t@param pivot: the position from which to start working with \n\t\t\t\tthe datastore\n\t\t\"\"\"\n\t\tself.type = op_type\n\t\tself.node = node\n\t\tself.item = item\n\t\tself.pivot = pivot\n\n\n\tdef __str__(self):\n\t\t\"\"\" \n\t\t\tPrints the Request type \n\n\t\t\t@rtype: String\t\t\t\n\t\t\t@return: a string of the following format: \n\t\t\t[operation] [node] @ [pivot] - \n\n\t\t\"\"\"\n\n\t\tif self.type == 0:\n\t\t\tt = \"get\"\n\t\t\ti = \"\"\n\t\telif self.type == 1:\n\t\t\tt = \"put\"\n\t\t\ti = \": {}\".format(self.item)\n\t\telif self.type == 2:\n\t\t\tt = \"done\"\n\t\t\ti = \"\"\n\t\telse:\n\t\t\treturn \"break\"\n\n\t\tret = \"{} th-{} @ {}{}\".format(t, self.node.node_id, self.pivot, i)\n\t\treturn ret","sub_path":"ASC_Tema01/tema/my_utils.py","file_name":"my_utils.py","file_ext":"py","file_size_in_byte":2931,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"541244773","text":"from Acquisition import aq_parent\nfrom ftw.solr.interfaces import ISolrSearch\nfrom ftw.solr.query import make_filters\nfrom opengever.base.browser.navigation import make_tree_by_url\nfrom opengever.base.interfaces import IOpengeverBaseLayer\nfrom opengever.base.solr import OGSolrDocument\nfrom opengever.repository.interfaces import IRepositoryFolder\nfrom opengever.repository.repositoryfolder import REPOSITORY_FOLDER_STATE_INACTIVE\nfrom opengever.repository.repositoryroot import IRepositoryRoot\nfrom plone.app.contentlisting.interfaces import IContentListingObject\nfrom plone.restapi.interfaces import IExpandableElement\nfrom plone.restapi.serializer.converters import json_compatible\nfrom plone.restapi.services import Service\nfrom Products.CMFPlone.interfaces.siteroot import IPloneSiteRoot\nfrom zExceptions import BadRequest\nfrom zope.component import adapter\nfrom zope.component import getUtility\nfrom zope.dottedname.resolve import resolve\nfrom zope.interface import implementer\nfrom zope.interface import Interface\n\n\n@implementer(IExpandableElement)\n@adapter(Interface, IOpengeverBaseLayer)\nclass Navigation(object):\n\n FIELDS = [\n 'UID',\n 'path',\n 'portal_type',\n 'review_state',\n 'Title',\n 'title_de',\n 'title_en',\n 'title_fr',\n 'Description',\n 'filename',\n 'has_sametype_children',\n 'is_subdossier',\n 'dossier_type',\n ]\n\n def __init__(self, context, request):\n self.context = context\n self.request = request\n self.solr = getUtility(ISolrSearch)\n\n def __call__(self, expand=False):\n root_interface = self.get_root_interface()\n content_interfaces = self.get_content_interfaces()\n\n if self.request.form.get('include_root'):\n content_interfaces.append(root_interface)\n\n result = {\n 'navigation': {\n '@id': '{}/@navigation'.format(self.context.absolute_url()),\n },\n }\n\n if not expand:\n return result\n\n root = self.find_root(root_interface, content_interfaces)\n solr_docs = self.query_solr(root, content_interfaces)\n\n nodes = map(self.solr_doc_to_node, solr_docs)\n result['navigation']['tree'] = make_tree_by_url(nodes)\n\n return result\n\n def find_root(self, root_interface, content_interfaces):\n context = self.context\n\n if root_interface not in content_interfaces:\n while (not root_interface.providedBy(context)\n and not IPloneSiteRoot.providedBy(context)):\n context = aq_parent(context)\n else:\n # This happens i.e. on lookup a dossier tree from a subdossier.\n #\n # The current context is the subdossier which is also\n # providing the root_interface. We have to get sure, that we return\n # the most upper object providing the given root_interface if\n # the root_interface is within `content_interfaces`\n current = context\n while (not IPloneSiteRoot.providedBy(current)):\n if root_interface.providedBy(current):\n context = current\n current = aq_parent(current)\n\n if root_interface.providedBy(context):\n root = context\n else:\n response = self.solr.search(\n filters=make_filters(\n object_provides=root_interface.__identifier__),\n sort='path asc',\n fl=[\"path\"],\n )\n roots = [OGSolrDocument(d) for d in response.docs]\n\n if roots:\n root = roots[0].getObject()\n else:\n raise BadRequest(\"No root found for interface: {}\".format(\n root_interface.__identifier__))\n return root\n\n def query_solr(self, root, content_interfaces):\n query = {\n 'object_provides': [i.__identifier__ for i in content_interfaces],\n 'path_parent': '/'.join(root.getPhysicalPath()),\n 'trashed': 'false',\n }\n\n review_states = self.request.form.get('review_state', [])\n if review_states:\n query['review_state'] = review_states\n\n filters = make_filters(**query)\n\n if self.request.form.get('include_context'):\n # Include context branch's UIDs in the query, by adding them as\n # a filter that is OR'ed with the main filters (which themselves\n # are AND'ed together). This is necessary because restrictions\n # from the main filters must not be applied to the context branch.\n context_uids = list(self.get_context_branch_uids(root))\n if context_uids:\n context_filter = make_filters(UID=context_uids)[0]\n main_filters = self._join_filters(make_filters(**query), 'AND')\n filters = self._join_filters([main_filters, context_filter], 'OR')\n\n resp = self.solr.search(\n filters=filters,\n sort='sortable_title asc',\n rows=10000,\n fl=self.FIELDS)\n\n return [OGSolrDocument(doc) for doc in resp.docs]\n\n def get_context_branch_uids(self, root):\n \"\"\"Return UIDs of the current context's chain up to the root.\n \"\"\"\n for item in self.context.aq_chain:\n item_uid = item.UID()\n if item_uid == root.UID():\n break\n yield item_uid\n\n def _lookup_iface_by_identifier(self, identifier):\n return resolve(identifier) if identifier else None\n\n def _join_filters(self, filters, op):\n op = ' %s ' % op\n return op.join(['(%s)' % flt for flt in filters])\n\n def get_root_interface(self):\n \"\"\"Lookups the root_interface provided within the request parameter.\n\n This interface is used as the navigation root identifier.\n \"\"\"\n interface = self.request.form.get('root_interface')\n try:\n return self._lookup_iface_by_identifier(\n interface) or IRepositoryRoot\n except ImportError:\n raise BadRequest(\"The provided `root_interface` could not be \"\n \"looked up: {}\".format(interface))\n\n def get_content_interfaces(self):\n \"\"\"Lookups the content_interfaces provided within the request parameter.\n\n The interfaces provided in `content_interfaces` are used as navigation\n items.\n \"\"\"\n interfaces = self.request.form.get('content_interfaces')\n if not interfaces:\n return [IRepositoryFolder]\n\n if not isinstance(interfaces, list):\n interfaces = [interfaces]\n\n content_interfaces = []\n for interface in interfaces:\n try:\n content_interfaces.append(\n self._lookup_iface_by_identifier(interface))\n except ImportError:\n raise BadRequest(\"The provided `content_interfaces` could not be \"\n \"looked up: {}\".format(interface))\n return content_interfaces\n\n def solr_doc_to_node(self, solr_doc):\n wrapper = IContentListingObject(solr_doc)\n context_url = self.context.absolute_url()\n\n node = {\n '@type': wrapper.portal_type,\n 'text': wrapper.Title(),\n 'description': wrapper.Description(),\n 'url': wrapper.getURL(),\n 'uid': wrapper.UID,\n 'active': wrapper.review_state() != REPOSITORY_FOLDER_STATE_INACTIVE,\n 'current': context_url == wrapper.getURL(),\n 'current_tree': context_url.startswith(wrapper.getURL()),\n 'is_leafnode': None,\n 'is_subdossier': wrapper.is_subdossier,\n 'review_state': wrapper.review_state(),\n 'dossier_type': wrapper.dossier_type,\n }\n if wrapper.portal_type == 'opengever.repository.repositoryfolder':\n node['is_leafnode'] = not wrapper.has_sametype_children\n return json_compatible(node)\n\n\nclass NavigationGet(Service):\n\n def reply(self):\n navigation = Navigation(self.context, self.request)\n return navigation(expand=True)['navigation']\n","sub_path":"opengever/api/navigation.py","file_name":"navigation.py","file_ext":"py","file_size_in_byte":8202,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"134125473","text":"import socket\nimport ssl\nimport sys\n\nIP_ADDR = '192.168.43.65' #CHANGE IT\nPORT = 8090 #CHANGE IT\nCERTFILE = '192.168.43.65.cert.pem' #CHANGE IT\nKEYFILE = '192.168.43.65.key.pem' #CHANGE IT\nCACERT = 'dev_cert_ca.cert.pem' #CHANGE IT\n\ns = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\ns.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)\ns.bind((IP_ADDR, PORT))\ns.listen(0)\n\nprint(\"Server started in {0}:{1}\".format(IP_ADDR, PORT))\n\nwhile True:\n print(\"Waiting for connections....\")\n client, addr = s.accept()\n print('Client connected: ', addr)\n \n secure_sock = ssl.wrap_socket(client, server_side=True, certfile=CERTFILE,\n cert_reqs=ssl.CERT_REQUIRED, keyfile=KEYFILE,\n ca_certs=CACERT, ssl_version=ssl.PROTOCOL_TLSv1_2)\n #print(repr(secure_sock))\n #print(\"Certificado cliente:\", secure_sock.getpeercert())\n #print(repr(secure_sock.getpeername()))\n #print(secure_sock.cipher())\n\n try:\n ssl.match_hostname(secure_sock.getpeercert(), 'client')\n #ssl.match_hostname(secure_sock.getpeercert(), 'client2')\n\n content = secure_sock.recv(1024)\n \n if len(content) == 0:\n break\n else:\n data_received = content.decode(\"utf-8\")\n print(\"Data received: \" + data_received)\n \n temperature = float(data_received)\n print(\"Temperature received: \" + str(temperature) + \"°\")\n response = ''\n if temperature >= 28:\n response = 'R'\n elif temperature <=17:\n response = 'B'\n else:\n response = 'G'\n \n print(\"Response \" + response)\n secure_sock.send(response.encode(\"utf-8\"))\n #print(response.encode(\"utf-8\").hex())\n except ssl.CertificateError:\n print(\"Common name not valid\")\n pass\n except ValueError:\n print(\"Anomaly detected\")\n response = 'A'\n secure_sock.send(response.encode(\"utf-8\"))\n pass\n \n print(\"Closing connection...\")\n secure_sock.close()\n print(\"\")\n","sub_path":"CPS/Raspberry/ServerTempTLS_IDS.py","file_name":"ServerTempTLS_IDS.py","file_ext":"py","file_size_in_byte":2139,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"366902020","text":"num = int(input('Informe o numero: '))\nresultado = num\ndicionario = {}\nfator = 2\nwhile not resultado == 1:\n quantidade = 0\n if resultado % fator == 0:\n quantidade += 1\n resultado /= fator\n if fator in dicionario.keys():\n dicionario[fator]+= 1\n else:\n dicionario.update({ fator:quantidade })\n else:\n fator += 1\nfor dados in dicionario:\n print('O fator %i apareceu %i veze(s).' %(dados, dicionario[dados]))\n","sub_path":"Masanori/Lista de Exercícios III Algoritmos 2013 (Avançado)/exercicio4.py","file_name":"exercicio4.py","file_ext":"py","file_size_in_byte":474,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"548821273","text":"import cPickle\nimport gzip\nimport os.path\nimport sys\nfrom subprocess import PIPE, Popen\nfrom warnings import warn\n\nimport yaml\n\nfrom koert.gnucash.xmlformat import SaxHandler\n\n\ndef open_gcf_in_git_repo(repopath, filepath, cachepath=None, scheme=None):\n from git import Repo\n\n repo = Repo(repopath)\n commit = repo.head.commit\n mtime = commit.authored_date\n f = commit.tree[filepath].data_stream\n\n result = parse_gcf(f, mtime, cachepath=cachepath, scheme=scheme)\n\n f.read()\n\n return result\n\n\ndef open_pos_gzipped(filepath):\n f = None\n try:\n # Only after a byte is read, is the check whether filepath\n # points to a gzipped file performed.\n f = gzip.open(filepath)\n f.read(1)\n f.rewind()\n except IOError:\n # message should read: \"Not a gzipped file\"\n f = open(filepath)\n return f\n\n\ndef saxparse(f, handler):\n from xml.sax import parse as saxparse\n saxparse(f, handler)\n\n\ndef lxmlparse(f, handler):\n from lxml.etree import parse as lxmlparse\n from lxml.sax import saxify\n etree = lxmlparse(f)\n saxify(etree, handler)\n\n\ndef cache_path(filepath):\n return filepath + \".pickled\"\n\n\ndef get_commit_name():\n directory = os.path.dirname(__file__)\n p = Popen('git rev-parse HEAD',\n stdout=PIPE, shell=True, cwd=directory)\n outp, err = p.communicate()\n return outp\n\n\ndef load_cache(cachepath, mtime):\n if not os.path.exists(cachepath):\n return False\n # Do not use the cache if the gnucash file is newer\n if mtime >= os.path.getmtime(cachepath):\n return False\n with open(cachepath, \"r\") as f:\n current_commit_name = get_commit_name()\n try:\n cached_commit_name, gcf = cPickle.load(f)\n if cached_commit_name != current_commit_name:\n return False\n print(\"loaded cache %s\" % cachepath)\n return gcf\n except Exception as e:\n warn(\"Failed to load pickled cache of Gnucash file \"\n \"'%s': %s\" % (cachepath, repr(e)))\n return False\n\n\ndef update_cache(cachepath, gcf):\n if sys.getrecursionlimit() < 2000:\n sys.setrecursionlimit(2000)\n with open(cachepath, \"w\") as f:\n try:\n cPickle.dump((get_commit_name(), gcf), f)\n except RuntimeError as e:\n warn(\"\"\"Failed to dump a pickled version of the \\\ngnucash file \"%s\" due to the RuntimeError below. If this is a stack \\\noverflow, you might want to increase the maximum recursion depth by \\\nsys.setrecursionlimit.\"\"\")\n raise e\n\n\ndef parse_gcf(f, mtime, scheme=None, parse=saxparse, cachepath=None):\n if cachepath is not None:\n result = load_cache(cachepath, mtime)\n if result:\n return result\n handler = SaxHandler(scheme)\n parse(f, handler)\n result = handler.result\n result.mtime = mtime\n update_cache(cachepath, result)\n return result\n\n\ndef open_gcf(filepath, scheme=None, parse=saxparse, cachepath=None):\n if cachepath is None:\n cachepath = cache_path(filepath)\n with open(filepath) as f:\n return parse_gcf(f, os.path.getmtime(filepath),\n scheme=scheme, parse=parse, cachepath=cachepath)\n\n\ndef open_yaml(path):\n with open(path) as f:\n d = yaml.load(f)\n\n dirname = os.path.dirname(path)\n gcf_path = os.path.join(dirname, d['path'])\n cache_path = None\n if \"cache\" in d:\n cache_path = os.path.join(dirname, d['cache'])\n gcf = None\n if 'repo' in d:\n repo_path = os.path.join(dirname, d['repo'])\n gcf = open_gcf_in_git_repo(repo_path, d['path'], cachepath=cache_path)\n else:\n gcf = open_gcf(gcf_path, cachepath=cache_path)\n if 'meta' in d:\n gcf.meta = d['meta']\n\n return gcf\n","sub_path":"sm/gnucash/tools.py","file_name":"tools.py","file_ext":"py","file_size_in_byte":3788,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"380884730","text":"'''\nDocumentation, License etc.\n\n@package projet_morpion\n'''\n\n# 1ère étape : Ecrire une fonction pour afficher le tableau de jeu. Configurer votre tableau comme une liste, où chaque index 1-9 correspond à un nombre sur un clavier, de sorte que vous obtenez un terrain de 3 par 3.\n\nfrom IPython.display import clear_output\n\ndef affiche_tableau(tableau):\n clear_output()\n print(\"Bienvenue dans le jeu du morpion : \\n\") \n print(' | |')\n print(' ' + tableau[7] + ' | ' + tableau[8] + ' | ' + tableau[9])\n print(' | |')\n print('-----------')\n print(' | |')\n print(' ' + tableau[4] + ' | ' + tableau[5] + ' | ' + tableau[6])\n print(' | |')\n print('-----------')\n print(' | |')\n print(' ' + tableau[1] + ' | ' + tableau[2] + ' | ' + tableau[3])\n print(' | |')\n\naffiche_tableau(['','X','X','X','O',' ','O','X','X','X'])\n\n# **2ème étape : Ecrire une fonction qui demande au joueur quelle marque «X» ou «O» il veut utiliser et lui assigner. Pensez à utiliser une boucle *while* pour demander une réponse au joueur jusqu'à obtenir une réponse correcte.** \n\ndef pion_joueur():\n \n marque = ''\n while not (marque == 'X' or marque == 'O'):\n marque = input('Joueur 1: Est-ce que vous voulez jouer X ou O ? ').upper()\n\n if marque == 'X':\n return ('X', 'O')\n else:\n return ('O', 'X') \n\n\n\n\n\nimport tkinter as Tk\nimport time\n\ndef affiche_canevas_tk() :\n N = 3 \n pas=600/N \n root = Tk.Tk() \n c = Tk.Canvas(root,height=600,width=600) \n listidrec=N*[[]] \n for i in range(N): \n listidrec[i]=N*[-1] \n for i in range(N): \n for j in range(N): \n listidrec[i][j] = c.create_rectangle(pas*i, pas*j, pas*(i+1), pas*(j+1), fill='#00FF00') \n \n c.pack()\n def test():\n for i in range(17,256):\n c.itemconfig(listidrec[1][1],fill='#0000'+hex(i)[2:])\n print(hex(i)[2:])\n time.sleep(0.05) \n root.update()\n \n \n b = Tk.Button(text = 'test', command= test)\n b.pack()\n root.mainloop()\n\n# affiche_canevas_tk()\n","sub_path":"projet_morpion.py","file_name":"projet_morpion.py","file_ext":"py","file_size_in_byte":2106,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"461396696","text":"# Copyright 2016 Google Inc. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain 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,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\n\"\"\"In-memory input source.\"\"\"\n\nimport itertools\n\nfrom google.cloud.dataflow import coders\nfrom google.cloud.dataflow.io import iobase\n\n\nclass InMemorySource(iobase.NativeSource):\n \"\"\"In-memory input source.\"\"\"\n\n def __init__(\n self, elements, coder=coders.Base64PickleCoder(), start_index=None,\n end_index=None):\n self.elements = elements\n self.coder = coder\n\n if start_index is None:\n self.start_index = 0\n else:\n self.start_index = start_index\n\n if end_index is None:\n self.end_index = len(elements)\n else:\n self.end_index = end_index\n\n def __eq__(self, other):\n return (self.elements == other.elements and\n self.coder == other.coder and\n self.start_index == other.start_index and\n self.end_index == other.end_index)\n\n def reader(self):\n return InMemoryReader(self)\n\n\nclass InMemoryReader(iobase.NativeSourceReader):\n \"\"\"A reader for in-memory source.\"\"\"\n\n def __init__(self, source):\n self.source = source\n\n # Index of the next item to be read by the InMemoryReader.\n # Starts at source.start_index.\n self.current_index = source.start_index\n\n def __enter__(self):\n return self\n\n def __exit__(self, exception_type, exception_value, traceback):\n pass\n\n def __iter__(self):\n for value in itertools.islice(self.source.elements,\n self.source.start_index,\n self.source.end_index):\n self.current_index += 1\n yield self.source.coder.decode(value)\n\n def get_progress(self):\n if (self.current_index >= self.source.end_index or\n self.source.start_index >= self.source.end_index):\n percent_complete = 1\n elif self.current_index == self.source.start_index:\n percent_complete = 0\n else:\n percent_complete = (\n float(self.current_index - self.source.start_index) / (\n self.source.end_index - self.source.start_index))\n\n return iobase.ReaderProgress(percent_complete=percent_complete)\n","sub_path":"google/cloud/dataflow/worker/inmemory.py","file_name":"inmemory.py","file_ext":"py","file_size_in_byte":2620,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"414588211","text":"# 求数组中超过一半的数\n\n# 思路：如果存在超过一半的数，则该数一定在排序之后的中位数,则我们只要判断中位数是否占有数组一半以上即可\n# 那么核心问题就转化成如何最快得到中位数，全部排序取中间？如果数据量过大的话，这种方法是不可行的\n# 该问题类似于求乱序大数组中的第k个元素，结合快排的元素定位+二分法 能够最大效率地找到某个位置的数,获取当我们可以移动数组的情况下(大数据情况下分机不能使用该思路)求最大或者最小的k个数 (无序)\n# 例如，要求第k个元素，先求出某个元素在有序数组的下标x,因此此时数组0-x之间都小于x的乱序元素，x-len(arr)是大于x的乱序元素集合，若该x小于k,则我们要求出的\n# 第k个元素一定在0-x之间，否则在x-len(arr)之间，我们利用二分法不断缩小这个范围，最终找到第k个元素。\n\n\nclass Solution:\n def helper(self, arr):\n def quickSort(start, end):\n guard = arr[start]\n temp = start\n while start < end:\n\n while start < end and arr[end] >= guard:\n end -= 1\n while start < end and arr[start] <= guard:\n start += 1\n\n if start < end:\n arr[end], arr[start] = arr[start], arr[end]\n\n arr[start], arr[temp] = arr[temp], arr[start]\n return start\n\n def handle(arr):\n\n mid = len(arr) >> 1\n start, end = 0, len(arr) - 1\n index = quickSort(0, end)\n while index != mid:\n if index < mid:\n start = index + 1\n if index > mid:\n end = index - 1\n\n index = quickSort(start, end)\n\n num = arr[index]\n\n return num if arr.count(num) > len(arr) >> 1 else -1\n\n return handle(arr)\n\n # 思路二：利用数组的特点 巧妙\n\n # 一个数超过一半，则说明该数出现的次数一定大于其他所有的数，则我们遍历，如果当前数和上一个数一样则次数加1，不一样则减1，如果次数为0，则将当前数保存下来，并且次数置一，\n # 则遍历到最后如果计数大于等于1，则说明有一个数大于其他所有数的之和。则返回该数。2，3，2，3，3，3，5\n\n def helper2(self, arr):\n count, temp = 0, -1\n for i in arr:\n if count == 0:\n temp = i\n count = 1\n elif temp != i:\n count -= 1\n else:\n count += 1\n\n return temp if count >= 1 else -1\n\n\ns = Solution()\nprint(s.helper([2, 3, 5, 2, 2, 2, 3, 3, 3, 3, 3]))\nprint(s.helper2([2, 3]))\n","sub_path":"loop/29.py","file_name":"29.py","file_ext":"py","file_size_in_byte":2815,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"422134328","text":"import random\n\ndef rndstr(n):\n s = \"\"\n nletras = ord('z') - ord('a') + 1\n for i in range(n):\n s = s + chr(int(random.random()*1000) % nletras + ord('a'))\n return s\n\nprint(\"Lista original\")\nl=[]\nfor i in range(5):\n tupla = (i,rndstr(10))\n l.append(tupla)\n print(tupla)\n\nfp=open(\"lista.txt\",\"w\")\nfor item in l:\n fp.write(repr(item)+'\\n')\nfp.close()\n\nprint(\"\\nLista recuperada del fichero\")\nl_new=[]\nfp=open(\"lista.txt\",\"r\")\nfor line in fp:\n tupla = eval(line)\n l_new.append(tupla)\n print(tupla)\nfp.close()\n","sub_path":"1ºCurso/Fundamentos-de-la-programacion/1_Modulo random + Repaso Ficheros/Ejemplos ficheros/repr() y eval()/almacenamiento_lista.py","file_name":"almacenamiento_lista.py","file_ext":"py","file_size_in_byte":544,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"135107518","text":"# Persians: Sydney Anderson, Tram Doan, Devon Knudsen, Zackary Phillips, Promyse Ward, James Wilson\r\n# GitHub Repo URL: https://github.com/devonknudsen/FTP-Covert\r\n# Written in Python 3.7\r\n\r\nfrom ftplib import FTP\r\n\r\nMETHOD = 10\r\nSERVER = 'jeangourd.com'\r\nUSERNAME = 'anonymous'\r\nPASSWORD = ''\r\n\r\n# appends the file permissions to a list\r\ndef retrieveFilePerms():\r\n if(METHOD == 7):\r\n ftp.cwd('7')\r\n if(METHOD == 10):\r\n ftp.cwd('10')\r\n\r\n filePerms = []\r\n ftp.retrlines('LIST', filePerms.append)\r\n filePerms = [filePerms[i][:10] for i in range(len(filePerms))]\r\n\r\n ftp.quit()\r\n \r\n return filePerms\r\n\r\n# removes the 'noise' from messages made of 7 right most bits\r\ndef removeNoise(pList):\r\n newList = []\r\n for pSet in pList:\r\n if(pSet[:3] == '---'):\r\n newList.append(pSet)\r\n\r\n return newList\r\n\r\n# converts each index of file permissions into binary\r\ndef permsToBinaryList(pList):\r\n if(METHOD == 7):\r\n for i in range(len(pList)):\r\n pList[i] = pList[i] [3:]\r\n\r\n if(METHOD == 10):\r\n pList = ''.join(pList)\r\n pList = [pList[i:i + 7] for i in range(0, len(pList), 7)]\r\n\r\n for i in range(len(pList)):\r\n currPerm = pList[i]\r\n currPerm = currPerm.replace('-', '0')\r\n currPerm = currPerm.replace('d', '1')\r\n currPerm = currPerm.replace('w', '1')\r\n currPerm = currPerm.replace('r', '1')\r\n currPerm = currPerm.replace('x', '1')\r\n pList[i] = currPerm\r\n\r\n return pList\r\n\r\n# decodes the binary into the plain text message\r\ndef binaryToText(pList):\r\n completeMessage = ''\r\n \r\n for i in range(len(pList)):\r\n asc = int(pList[i], 2)\r\n\r\n # if: there's a backspace\r\n if(asc == 8):\r\n completeMessage = completeMessage[:-1]\r\n else:\r\n newChar = chr(asc)\r\n completeMessage += newChar\r\n \r\n return completeMessage\r\n\r\n\r\n# MAIN\r\nftp = FTP(SERVER)\r\nftp.login(USERNAME, PASSWORD)\r\n\r\nif(METHOD == 7):\r\n fPs = retrieveFilePerms()\r\n refinedfPs = removeNoise(fPs)\r\n binaryList = permsToBinaryList(refinedfPs)\r\n print(binaryToText(binaryList))\r\n\r\nif(METHOD == 10):\r\n fPs = retrieveFilePerms()\r\n binaryList = permsToBinaryList(fPs)\r\n print(binaryToText(binaryList))\r\n","sub_path":"FTPFetch.py","file_name":"FTPFetch.py","file_ext":"py","file_size_in_byte":2284,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"317494085","text":"from django.conf.urls import url\n\nfrom . import views\n\napp_name = 'account'\nurlpatterns = [\n url(r'^$', views.show, name='show'),\n url(r'^save/$', views.save_list, name='save_list'),\n url(r'^import/$', views.import_page, name='import_page'),\n url(r'^import/submit$', views.import_csv, name='import_csv'),\n url(r'^export/$', views.export_csv, name='export_csv'),\n url(r'^customize/$', views.custom, name='customize'),\n url(r'^customize/(?P
[0-9]+)/edit/$', views.edit, name='edit'),\n url(r'^customize/(?P[0-9]+)/edit/save$', views.edit_save, name='edit_save'),\n url(r'^customize/(?P[0-9]+)/remove/$', views.remove, name='remove'),\n url(r'^customize/(?P[0-9]+)/remove/confirm$', views.remove_confirm, name='remove_confirm'),\n] \n","sub_path":"urls.py","file_name":"urls.py","file_ext":"py","file_size_in_byte":795,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"434590240","text":"\n# coding: utf-8\n\n# In[1]:\n\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\n\n# Draw inline\nget_ipython().magic(u'matplotlib inline')\n\n# Set figure aesthetics\nsns.set_style(\"white\", {'ytick.major.size': 10.0})\nsns.set_context(\"poster\", font_scale=1.1)\n\n\n# In[2]:\n\n# Load the data into DataFrames\ntrain_users = pd.read_csv('../input/train_users_2.csv')\ntest_users = pd.read_csv('../input/test_users.csv')\n\n\n# In[4]:\n\nprint(train_users.shape[0],test_users.shape[0])\n\n\n# In[6]:\n\n# Merge train and test users\nusers = pd.concat((train_users, test_users), axis=0, ignore_index=True)\n\n# Remove ID\nusers.drop('id',axis=1, inplace=True)\n\nusers.head(10)\n\n\n# In[6]:\n\nusers.gender.replace('-unknown-', np.nan, inplace=True)\n\n\n# In[15]:\n\nusers_nan = (users.isnull().sum() / users.shape[0]) * 100\nusers_nan[users_nan > 0].drop('country_destination')\n\n\n# In[18]:\n\n#check\nprint(int((train_users.date_first_booking.isnull().sum() / train_users.shape[0]) * 100))\n\n\n# In[19]:\n\nusers.age.describe()\n\n\n# In[20]:\n\nprint(sum(users.age > 100))\nprint(sum(users.age < 18))\n\n\n# In[21]:\n\nusers[users.age > 100]['age'].describe()\n\n\n# In[22]:\n\nusers[users.age < 18]['age'].describe()\n\n\n# In[23]:\n\nusers.loc[users.age > 95, 'age'] = np.nan\nusers.loc[users.age < 13, 'age'] = np.nan\n\n\n# In[24]:\n\ncategorical_features = [\n 'affiliate_channel',\n 'affiliate_provider',\n 'country_destination',\n 'first_affiliate_tracked',\n 'first_browser',\n 'first_device_type',\n 'gender',\n 'language',\n 'signup_app',\n 'signup_method'\n]\n\nfor categorical_feature in categorical_features:\n users[categorical_feature] = users[categorical_feature].astype('category')\n\n\n# In[25]:\n\nusers['date_account_created'] = pd.to_datetime(users['date_account_created'])\nusers['date_first_booking'] = pd.to_datetime(users['date_first_booking'])\nusers['date_first_active'] = pd.to_datetime((users.timestamp_first_active // 1000000), format='%Y%m%d')\n\n\n# In[26]:\n\nseries = pd.Series(users.gender.value_counts(dropna=False))\n\n\n# In[28]:\n\nseries.plot.pie(figsize=(5, 5))\n\n\n# In[37]:\n\nwomen = sum(users['gender'] == 'FEMALE')\nmen = sum(users['gender'] == 'MALE')\n\nfemale_destinations = users.loc[users['gender'] == 'FEMALE', 'country_destination'].value_counts() / women * 100\nmale_destinations = users.loc[users['gender'] == 'MALE', 'country_destination'].value_counts() / men * 100\n\n# Bar width\nwidth = 0.4\n\nmale_destinations.plot(kind='bar', width=width, color='#3CB371', position=0, label='Male', rot=0)\nfemale_destinations.plot(kind='bar', width=width, color='#6495ED', position=1, label='Female', rot=0)\n\nplt.legend()\nplt.xlabel('Destination Country')\nplt.ylabel('Percentage of the user')\n\nsns.despine()\nplt.show()\n\n\n# In[42]:\n\ndestination_percentage = users.country_destination.value_counts() / users.shape[0] * 100\ndestination_percentage.plot(kind='bar',color='#20B2AA', rot=0)\n# Using seaborn to plot\nsns.countplot(x=\"country_destination\", data=users, order=list(users.country_destination.value_counts().keys()))\nplt.xlabel('Destination Country')\nplt.ylabel('Percentage of the user')\n# sns.despine()\n\n\n# In[44]:\n\nsns.kdeplot(users.age.dropna(), color='#20B2AA', shade=True)\nplt.xlabel('Age')\nplt.ylabel('Distribution of age')\nsns.despine()\n\n\n# In[45]:\n\nage = 40\n\nyounger = sum(users.loc[users['age'] < age, 'country_destination'].value_counts())\nolder = sum(users.loc[users['age'] > age, 'country_destination'].value_counts())\n\nyounger_destinations = users.loc[users['age'] < age, 'country_destination'].value_counts() / younger * 100\nolder_destinations = users.loc[users['age'] > age, 'country_destination'].value_counts() / older * 100\n\nyounger_destinations.plot(kind='bar', width=width, color='#3CB371', position=0, label='Youngers', rot=0)\nolder_destinations.plot(kind='bar', width=width, color='#6495ED', position=1, label='Olders', rot=0)\n\nplt.legend()\nplt.xlabel('Destination Country')\nplt.ylabel('Percentage of the user')\n\nsns.despine()\nplt.show()\n\n\n# In[50]:\n\ndf=users.date_account_created.value_counts()\nplt.figure()\ndf.plot(colormap='winter')\nplt.xlabel('First create account')\n\n\n# In[51]:\n\ndf=users.date_first_active.value_counts()\nplt.figure()\ndf.plot(colormap='winter')\nplt.xlabel('Fisrt active account')\n\n","sub_path":"Visualization.py","file_name":"Visualization.py","file_ext":"py","file_size_in_byte":4231,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"245387715","text":"import numpy\nimport os\n\nif __name__ == '__main__':\n loadpath = 'D:\\\\ProjectData\\\\LIDC\\\\LIDC-Positive-FC7\\\\'\n savepath = 'D:\\\\ProjectData\\\\LIDC\\\\LIDC-Positive-FC7-Assembly\\\\'\n for indexA in os.listdir(loadpath):\n writeFile = open(savepath + indexA + '.csv', 'w')\n for indexB in os.listdir(loadpath + indexA):\n print(indexA, indexB)\n for indexC in os.listdir(loadpath + indexA + '\\\\' + indexB):\n readFile = open(loadpath + indexA + '\\\\' + indexB + '\\\\' + indexC, 'r')\n data = readFile.read()\n writeFile.write(data + '\\n')\n readFile.close()\n writeFile.close()\n","sub_path":"Main_LIDC/CsvAssembly.py","file_name":"CsvAssembly.py","file_ext":"py","file_size_in_byte":669,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"270541196","text":"#!/usr/bin/env python\n# -*- encoding: utf-8 -*-\nimport os\nfrom pathlib import Path\n\nBATCH_SIZE = 128\nIMG_SIZE = 224\nNUM_CLS = 1000\n\n# resnet 18\nmodel = dict(\n type='VanillaResNet',\n block_type='ResNetBottleneck',\n layers=[3, 4, 6, 3],\n num_cls=NUM_CLS\n)\n\ntrain_data = dict(\n dataset=dict(\n type='CIFAR10Dataset',\n root=Path(os.environ['DATA']),\n transform_pipeline=[\n dict(type='RandomResizedCrop', size=IMG_SIZE),\n dict(type='RandomHorizontalFlip'),\n dict(type='ToTensor'),\n dict(type='Normalize', mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5))\n ]\n ),\n dataloader=dict(\n batch_size=64,\n pin_memory=True,\n num_workers=4,\n sampler=dict(\n type='DataParallelSampler',\n shuffle=True,\n )\n )\n)\n\ntest_data = dict(\n dataset=dict(\n type='CIFAR10Dataset',\n root=Path(os.environ['DATA']),\n train=False,\n transform_pipeline=[\n dict(type='Resize', size=(IMG_SIZE, IMG_SIZE)),\n dict(type='ToTensor'),\n dict(type='Normalize', mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5))\n ]\n ),\n dataloader=dict(\n batch_size=BATCH_SIZE,\n pin_memory=True,\n num_workers=4,\n )\n)\n\ndist_initializer = [\n dict(type='DataParallelInitializer'),\n]\n\nparallelization = dict(\n pipeline=1,\n tensor=1,\n sequence=-1\n)\n\noptimizer = dict(\n type='Adam',\n lr=0.01\n)\n\nloss = dict(\n type='CrossEntropyLoss'\n)\n\ntrainer = dict(\n max_epochs=5,\n max_iters=1000\n)\n\namp = dict(\n fp16=None,\n)\n\nlevel = 2\n\nparallel = dict(\n pipeline=dict(size=1),\n tensor=dict(size=1, mode=None)\n)\n","sub_path":"tests/test_zero_data_parallel/config.py","file_name":"config.py","file_ext":"py","file_size_in_byte":1704,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"113244271","text":"__author__ = 'jkf'\n\nimport json\n\nfrom adengine.model import User, Ad, Comment\n\n\ndef build_api_url(id_=None):\n if id_ is not None:\n return \"/api/ads/{}\".format(id_)\n return \"/api/ads\"\n\n\ndef _add_resource(session, resource):\n session.add(resource)\n session.commit()\n return resource\n\n\ndef _new_ad(user, text=\"ad-text\"):\n ad = Ad(text=text, author_id=user.id)\n return ad\n\n\ndef _new_user(name='Peter'):\n user = User(email='{name}@example.com'.format(name=name),\n name=name,\n username=name,\n password_hash='12346')\n return user\n\n\ndef _new_comment(ad, user, text='bla-bla-bla'):\n comment = Comment(text=text,\n ad_id=ad.id,\n author_id=user.id)\n return comment\n\n\ndef test_comments_refers_both_ad_and_user(session, client):\n \"Ensure comments added are referneced from the Ad\"\n # given\n user = _add_resource(session, _new_user(name='PeterGeneralUser'))\n user1 = _add_resource(session, _new_user(name='PeterGeneralUserGrant'))\n ad = _add_resource(session, _new_ad(user, text=\"ad1-text1\"))\n _add_resource(session, _new_comment(ad, user, text=\"ad11-text1\"))\n _add_resource(session, _new_comment(ad, user1, text=\"ad12-text1\"))\n\n # exercise\n result = client.get(build_api_url()).data\n doc = json.loads(result)\n\n # verify\n ads_dicts = doc.get(\"objects\")\n assert 1 == len(ads_dicts), \"Expected only one advertisement.\"\n assert \"ad1-text1\" == ads_dicts[0].get('text')\n","sub_path":"tests/views/test_ads.py","file_name":"test_ads.py","file_ext":"py","file_size_in_byte":1519,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"74423526","text":"import urllib\nimport urllib.request\nimport re\nfrom bs4 import BeautifulSoup\nimport time\nimport os\n\nfile_path = \"modern_paintings\"\nos.makedirs(file_path, exist_ok=True)\n\ndef url_open(url):\n req = urllib.request.Request(url, headers={'User-Agent': 'Mozilla/5.0'})\n retrycount = 0\n s = None\n while s is None:\n try:\n s = urllib.request.urlopen(req,timeout=50).read()\n except Exception as e:\n print(str(e))\n retrycount+=1\n if retrycount > 10:\n raise\n time.sleep(10)\n\n return BeautifulSoup(s, \"lxml\")\n\ndef urlretrieve(image_url, save_path):\n retrycount = 0\n s = None\n while s is None:\n try:\n s = urllib.request.urlretrieve(image_url, save_path)\n except Exception as e:\n print(str(e))\n retrycount+=1\n if retrycount > 10:\n raise\n time.sleep(10)\n\ndef get_images(url):\n print(url)\n genre_soup = url_open(url)\n artist_list_main = genre_soup.find(\"main\")\n lis = artist_list_main.find_all(\"li\")\n\n # for each list element\n for li in lis: \n born = 0\n died = 0\n\n # get the date range\n for line in li.text.splitlines():\n if line.startswith(\",\") and \"-\" in line:\n parts = line.split('-')\n if len(parts) == 2:\n born = int(re.sub(\"[^0-9]\", \"\",parts[0]))\n died = int(re.sub(\"[^0-9]\", \"\",parts[1]))\n\n # look for artists who may have created work that could in public domain\n if born>1800 and died>0 and died<1978:\n link = li.find(\"a\")\n artist = link.attrs[\"href\"]\n\n # get the artist's main page\n artist_url = base_url + artist\n artist_soup = url_open(artist_url)\n\n # only look for artists with the word modern on their main page\n if \"modern\" in artist_soup.text.lower():\n print(artist + \" \" + str(born) + \" - \" + str(died))\n\n # get the artist's web page for the artwork\n url = base_url + artist + '/all-works/text-list'\n artist_work_soup = url_open(url)\n\n # get the main section\n artist_main = artist_work_soup.find(\"main\")\n image_count = 0\n artist_name = artist.split(\"/\")[2]\n os.makedirs(file_path + \"/\" + artist_name, exist_ok=True)\n\n # get the list of artwork\n lis = artist_main.find_all(\"li\")\n\n # for each list element\n for li in lis:\n link = li.find(\"a\")\n\n if link != None:\n painting = link.attrs[\"href\"]\n\n # get the painting\n url = base_url + painting\n print(url)\n\n try:\n painting_soup = url_open(url)\n\n except:\n print(\"error retreiving page\")\n continue\n\n # check the copyright\n if \"Public domain\" in painting_soup.text:\n\n # get the url\n og_image = painting_soup.find(\"meta\", {\"property\":\"og:image\"})\n image_url = og_image[\"content\"].split(\"!\")[0] # ignore the !Large.jpg at the end\n print(image_url)\n\n parts = url.split(\"/\")\n painting_name = parts[-1]\n save_path = file_path + \"/\" + artist_name + \"/\" + painting_name + \".jpg\"\n\n #download the file\n try:\n print(\"downloading to \" + save_path)\n time.sleep(0.2) # try not to get a 403 \n urlretrieve(image_url, save_path)\n image_count = image_count + 1\n except Exception as e:\n print(\"failed downloading \" + image_url, e)\n\nbase_url = \"https://www.wikiart.org\"\nurls = []\nfor c in range(ord('a'), ord('z') + 1):\n char = chr(c)\n artist_list_url = base_url + \"/en/Alphabet/\" + char + \"/text-list\"\n urls.append(artist_list_url)\n\nprint(urls)\n\nfrom concurrent.futures import ThreadPoolExecutor\nexecutor = None\nwith ThreadPoolExecutor(max_workers = 16) as executor:\n ex = executor\n executor.map(get_images, urls)\n ","sub_path":"download.py","file_name":"download.py","file_ext":"py","file_size_in_byte":3991,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"145311008","text":"# -*- coding: utf-8 -*-\r\nimport re,pymysql\r\nconnection = pymysql.connect(host='127.0.0.1',port=3306,user='root',password='*',db='ysdd',charset='utf8')\r\ncursor = connection.cursor()\r\nsql=\"select ROE,ycpdays,cpdays,realid from cpgz where red=1 and zf=1\"\r\ncursor.execute(sql)\r\ndates = cursor.fetchall()\r\nfor date in dates:\r\n dalygrade = float(date[0][:-1]) / date[1]\r\n ROE = dalygrade * date[2]\r\n parameter = 0.3 + (date[2] / 5) * 0.5\r\n gROE = (ROE*1.113-parameter)*0.19+parameter if ROE*1.1113 > parameter else parameter\r\n wgROE = (ROE*1.113-parameter)*0.2+parameter if ROE*1.1113 > parameter else parameter\r\n fxROE = 10 * ROE - 9 * wgROE\r\n sql=\"update cpgz set dalygrade=%0.4f,gROE=%0.4f,ROE='%0.2f%%' where realid='%s'\" %(dalygrade,gROE,ROE,date[3])\r\n cursor.execute(sql)\r\n connection.commit()\r\n sql = \"select stocks from hzb where realid='%s'\" %(date[3])\r\n cursor.execute(sql)\r\n stocks = cursor.fetchone()\r\n money = stocks[0] * (100+ROE) * 100\r\n sql=\"update hzb set investor='%0.2f%%',trader='%0.2f%%',money=%d where realid='%s'\" %(gROE,fxROE,money,date[3])\r\n cursor.execute(sql)\r\n connection.commit()\r\nconnection.close()\r\n \r\n \r\n\r\n \r\n \r\n","sub_path":"cpxz.py","file_name":"cpxz.py","file_ext":"py","file_size_in_byte":1199,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"}
+{"seq_id":"59612291","text":"import flask\nimport os\nimport datetime\nimport sys\n\nimport tensorflow as tf\nfrom flask import json\nfrom keras import models\n\n# initialize our Flask application and the Keras model\nfrom safetoswim.core import PhotoProcessor\nfrom safetoswim.repository import PostgresRepository, SqliteRepository\n\napplication = flask.Flask(__name__)\nmodel = None\ngraph = tf.get_default_graph()\nALLOWED_EXTENSIONS = set(['png', 'jpg', 'jpeg', 'gif'])\nUPLOAD_FOLDER = 'images'\napplication.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER\n\n\ndef load_model():\n global model\n file_dir = os.path.abspath(os.path.dirname(__file__))\n #model = ResNet50(weights=\"imagenet\")\n model_path = os.path.join(file_dir, 'models', 'hab_KerasBinaryClassifier_model.h5')\n print(f'Loading model from: {model_path}')\n model = models.load_model(model_path)\n if model is None:\n raise TypeError(f'Failed to load model from file {model_path}')\n\ndef get_model():\n global modele\n if model is None:\n load_model()\n return model\n\n\ndef allowed_file(filename):\n return '.' in filename and \\\n filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS\n\n\ndef save_image(submitter, image_location, date, time, name='', location='', latitude=0.0, longitude=0.0):\n repo = SqliteRepository('test.sqlite')\n id = repo.add_sample(submitter, image_location, date, time, name, location, latitude, longitude)\n return id\n\n@application.route(\"/\", methods=['GET'])\ndef index():\n return '''\n Safe To Swim \n Upload new File \n
\".join(os.listdir(application.config['UPLOAD_FOLDER'], ))\n\n\nif __name__ == \"__main__\":\n print((\"* Loading Keras model and Flask starting server...\"\n \"please wait until server has fully started\"))\n load_model()\n application.run(host=\"0.0.0.0\", debug=True)\n\n","sub_path":"safetoswim/servers/flask_server.py","file_name":"flask_server.py","file_ext":"py","file_size_in_byte":4954,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"596506285","text":"import logging\r\nimport requests\r\n\r\nfrom apiproxy import constants\r\nfrom .exceptions import LoggedDetailsAPIException\r\n\r\nlogger = logging.getLogger(__name__)\r\n\r\nclass APIActionCaller():\r\n\t\"\"\"Abstract class which must be inherited to handle a call to a Calendar42 API action\r\n\t\r\n\tThe abstract methods to implement are:\r\n\t* extract_data()\r\n\t* get_relative_url()\r\n\t\"\"\"\r\n\t\r\n\tdef __init__(self, token):\r\n\t\t\"\"\"\r\n\t\t@param {str} token\tThe authentication token to use when calling the Calendar42 API\r\n\t\t\"\"\"\r\n\t\tself._token = token\r\n\t\r\n\tdef call(self, *args, **kwargs):\r\n\t\t\"\"\"Calls the Calendar42 API and returns the response\r\n\t\tParameters (if any) are forwarded to self.get_relative_url(), which may need some runtime data to compute the URL\r\n\t\t\r\n\t\t@return\t{dict}\tThe JSON API response\r\n\t\t\"\"\"\r\n\t\t\r\n\t\t# Call the Calendar42 API\r\n\t\tfull_url = constants.CALENDAR42_API_BASE_URL + self.get_relative_url(*args, **kwargs)\r\n\t\t\r\n\t\theaders = {\r\n\t\t\t'Accept': 'application/json',\r\n\t\t\t'Content-type': 'application/json',\r\n\t\t\t'Authorization': 'Token %s' % self._token,\r\n\t\t}\r\n\t\tresponse = requests.get(full_url, headers=headers)\r\n\t\t\r\n\t\t# Parse response as JSON\r\n\t\ttry:\r\n\t\t\tjson_data = response.json()\r\n\t\texcept ValueError as e:\r\n\t\t\tlogger.exception(e)\r\n\t\t\tlogger.error(\"URL called: %s\\nHere's the body of the response which couldn't get parsed to JSON: %s\" % (full_url, response.text))\r\n\t\t\traise LoggedDetailsAPIException()\r\n\t\t\r\n\t\t# Extract desired information\r\n\t\ttry:\r\n\t\t\tif 'error' in json_data:\r\n\t\t\t\t# Forward error from Calendar42 API to client\r\n\t\t\t\traise LoggedDetailsAPIException(json_data['error']['message'])\r\n\t\t\t\t\r\n\t\t\treturn self.extract_data(json_data)\r\n\t\texcept (KeyError, ValueError, AttributeError) as e:\r\n\t\t\tlogger.exception(e)\r\n\t\t\tlogger.error(\"URL called: %s\\nHere's the JSON data which didn't fit the expected format: %s\" % (full_url, json_data))\r\n\t\t\traise LoggedDetailsAPIException()\r\n\t\r\n\tdef extract_data(self, json_data):\r\n\t\t\"\"\"ABSTRACT METHOD - TO BE IMPLEMENTED IN CHILD CLASS\r\n\t\t\r\n\t\tExtracts the desired information from the JSON data returned by the Calendar42 API\r\n\t\t@param {dict} json_data\r\n\t\t@return {dict}\tThe extracted data\r\n\t\t\"\"\"\r\n\t\tlogger.exception(NotImplementedError())\r\n\t\traise LoggedDetailsAPIException()\r\n\t\r\n\tdef get_relative_url(self, *args, **kwargs):\r\n\t\t\"\"\"ABSTRACT METHOD - TO BE IMPLEMENTED IN CHILD CLASS\r\n\t\t\r\n\t\tReturns the end of the URL, corresponding to the API action to call\r\n\t\t\"\"\"\r\n\t\tlogger.exception(NotImplementedError())\r\n\t\traise LoggedDetailsAPIException()\r\n\r\n\r\nclass EventDetailsAPIActionCaller(APIActionCaller):\r\n\t\"\"\"Gets details (ID and title) of an event\"\"\"\r\n\r\n\tdef get_relative_url(self, event_id):\r\n\t\treturn constants.CALENDAR42_API_EVENT.format(event_id)\r\n\r\n\tdef extract_data(self, json_data):\r\n\t\traw_details = json_data['data'][0]\r\n\t\tdetails = {\r\n\t\t\t'id': raw_details['id'],\r\n\t\t\t'title': raw_details['title'],\r\n\t\t}\r\n\t\treturn details\r\n\r\n\t\t\r\nclass EventParticipantsAPIActionCaller(APIActionCaller):\r\n\t\"\"\"Gets list of participants to an event\"\"\"\r\n\r\n\tdef get_relative_url(self, event_id):\r\n\t\treturn constants.CALENDAR42_API_PARTICIPANTS.format(event_id)\r\n\r\n\tdef extract_data(self, json_data):\r\n\t\treturn [item['subscriber']['first_name'] for item in json_data['data']]\r\n","sub_path":"apiproxy/events/api_action_caller.py","file_name":"api_action_caller.py","file_ext":"py","file_size_in_byte":3199,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"509688631","text":"from rest_framework import filters, mixins, viewsets\nfrom rest_framework.decorators import action\nfrom rest_framework.permissions import IsAdminUser\nfrom sreps.api.v1.serializers.customer import CustomerSerializer\nfrom sreps.api.v1.serializers.invoice import InvoiceListSerializer\nfrom sreps.core.models import Customer, Invoice\n\n\nclass CustomerViewSet(\n mixins.ListModelMixin,\n mixins.RetrieveModelMixin,\n mixins.CreateModelMixin,\n mixins.UpdateModelMixin,\n mixins.DestroyModelMixin,\n viewsets.GenericViewSet,):\n\n queryset = Customer.objects.all()\n serializer_class = CustomerSerializer\n permission_classes = (IsAdminUser,)\n\n @action(detail=True, methods=['GET'], name='Customer invoices')\n def invoices(self, request, pk=None):\n \"\"\"Get invoices made by a customer.\"\"\"\n\n customer = get_object_or_404(self.queryset, pk=pk)\n\n invoices = Invoice.objects.filter(\n customer=customer).order_by('-datetime_created')\n serializer = InvoiceListSerializer(invoices, many=True)\n\n return Response(serializer.data)\n","sub_path":"sreps/api/v1/views/customer.py","file_name":"customer.py","file_ext":"py","file_size_in_byte":1105,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"290191003","text":"#from fastapi import FastAPI\r\n#from pydantic import BaseModel\r\nimport pickle\r\nimport streamlit as st\r\nfrom sklearn.naive_bayes import GaussianNB\r\nimport numpy as np\r\nimport pandas as pd\r\n\r\n'''\r\napp=FastAPI()\r\nclass request_body(BaseModel):\r\n Age:float\r\n Hypertension:str\r\n Heart_disease:str\r\n Average_glucose: float\r\n BMI: float\r\n Marital_status: str\r\n Gender: str\r\n Work_type: str\r\n Residence:str\r\n Smoking_status: str\r\n'''\r\ndf=pd.read_csv(\"stroke_data_Cleaned3.csv\",header=0)\r\nprint(df.head())\r\n\r\n#Creating X and y Variables for Training Testing datasets\r\nX=df.drop([\"stroke\"],axis=1)\r\ny=df[\"stroke\"] #Target Variable\r\n\r\n#Creating Training Testing datasets\r\nfrom sklearn.model_selection import train_test_split\r\nX_train, X_test, y_train, y_test= train_test_split(X,y, test_size=0.2, random_state=5)\r\n#I have tried using K-best(taking 6 Variables) and the Classification Report doesnot show much Variation thus we are not using K-best\r\n\r\n#Creating Classification Models\r\n#I am using Naive Bayes Classification here, thus Scaling and One Hot Encoding is not Required\r\nmodel=GaussianNB()\r\nmodel.fit(X_train,y_train)\r\ny_pred=model.predict(X_test)\r\n\r\n#Testing effeciency of Naive Bayes Classifier\r\nfrom sklearn.metrics import confusion_matrix, classification_report,recall_score,f1_score\r\ncm=confusion_matrix(y_test, y_pred)\r\nprint(\"Confusion Matrix\")\r\nprint(cm)\r\ncr=classification_report(y_test, y_pred)\r\nprint(\"Classification Report\")\r\nprint(cr)\r\n#Since this dataset is not balanced accuracy is not the measure we will be looking for\r\n# Here we want to reduce the number of False negatives so we will look at Recall and F1 Score\r\nrs=recall_score(y_test,y_pred, average=\"weighted\")\r\nfs=f1_score(y_test,y_pred,average=\"weighted\")\r\nprint(\"Recall Value: \",rs)\r\nprint(\"F1 Score: \",fs)\r\n\r\n#Pickle is used for saving .pkl file\r\n#We are using .pkl file because we are going to deploy the model on Streamlit\r\npickle.dump(model,open('stroke.pkl','wb'))\r\nloaded_model=pickle.load(open('stroke.pkl','rb'))\r\n\r\n#For deploying on the Website\r\ndef predict_input_page():\r\n loaded_model = pickle.load(open('stroke.pkl', 'rb'))\r\n st.title(\"Stroke Prediction Model\")\r\n Age=st.slider(\"Age: \", min_value=0, max_value=90)\r\n Hypertension = st.radio(\"Do you suffer from Hypertension: \",(\"Yes\",\"No\"))\r\n Heart_disease=st.radio(\"Do you suffer from Heart Disease: \",(\"Yes\",\"No\"))\r\n Average_glucose=st.slider(\"Average Glucose Levels: \", min_value=50, max_value=280)\r\n BMI=st.slider(\"BMI: \",min_value=10, max_value=70)\r\n Marrital_status=st.radio(\"Are you married: \",(\"Yes\",\"No\"))\r\n Gender=st.radio(\"What is your Gender: \",(\"Male\",\"Female\"))\r\n Work_type=st.radio(\"What is your Work type?\",(\"Private\",\"Self-employed\",\"children\",\"Govt_job\",\"Never_worked\"))\r\n Residence=st.radio(\"What is your area of Residence\",(\"Urban\",\"Rural\"))\r\n Smoking_status=st.radio(\"Enter your Smoking Status:\",(\"never smoked\",\"Unknown\",\"formerly smoked\",\"smokes\"))\r\n ok=st.button(\"Predict\")\r\n\r\n #Since we are taking the input as a string and the model needs the values in numbers we convert the String to int\r\n if Hypertension==\"Yes\":\r\n Hypertension= 1\r\n elif Hypertension==\"No\":\r\n Hypertension=0\r\n\r\n if Heart_disease==\"Yes\":\r\n Heart_disease= 1\r\n elif Heart_disease==\"No\":\r\n Heart_disease=0\r\n\r\n if Marrital_status==\"Yes\":\r\n Marrital_status=1\r\n elif Marrital_status==\"No\":\r\n Marrital_status=0\r\n\r\n if Gender==\"Male\":\r\n Gender=1\r\n elif Gender==\"Female\":\r\n Gender=0\r\n\r\n if Work_type==\"Govt_job\":\r\n Work_type=0\r\n elif Work_type==\"Never_worked\":\r\n Work_type=1\r\n elif Work_type==\"Private\":\r\n Work_type=2\r\n elif Work_type==\"Self-employed\":\r\n Work_type=3\r\n elif Work_type==\"children\":\r\n Work_type=4\r\n\r\n if Residence==\"Rural\":\r\n Residence=0\r\n elif Residence==\"Urban\":\r\n Residence=1\r\n\r\n if Smoking_status==\"Unknown\":\r\n Smoking_status=0\r\n elif Smoking_status==\"formerly smoked\":\r\n Smoking_status=1\r\n elif Smoking_status==\"never smoked\":\r\n Smoking_status=2\r\n elif Smoking_status==\"smokes\":\r\n Smoking_status=3\r\n\r\n testdata=np.array([[Age, Hypertension, Heart_disease, Average_glucose, BMI, Marrital_status,Gender,Work_type,Residence,Smoking_status]])\r\n classi=loaded_model.predict(testdata)[0]\r\n\r\n try:\r\n if ok==True:\r\n if classi == 0:\r\n st.success(\"Awesome! You are on low risk of getting Stroke\")\r\n elif classi == 1:\r\n st.error(\"Cautious! You are on high risk of getting Stroke\")\r\n except:\r\n st.info(\"Enter some Data\")\r\n\r\n\r\n\r\n\r\n","sub_path":"ML_Project_2_209027.py","file_name":"ML_Project_2_209027.py","file_ext":"py","file_size_in_byte":4696,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"200320471","text":"#!/usr/bin/python3\n\nimport spaceking.net as net\nimport spaceking.common as com\nimport spaceking.log as log\nimport spaceking.event as ev\n\nimport shutil\nimport atexit\nimport os\nimport tempfile\nimport asyncio\nimport socket\n\nEVT_SERVER_RUNNING = 15000\nEVT_SERVER_QUIT = 15001\nEVT_SERVER_CONNECTED = 15002\nEVT_SERVER_DISCONNECTED = 15003\nEVT_SERVER_FAILED_JOIN = 15004\nEVT_SERVER_FAILED_CLIENT = 15005\nEVT_SERVER_NEW_CLIENT = 15006\nEVT_SERVER_DISCONNECTED_CLIENT = 15007\n\n\nclass ServerClient:\n\n __slots__ = [\"uid\", \"addr\", \"reader\", \"writer\"]\n\n def __init__(self, uid, addr, reader, writer):\n self.uid = uid\n self.addr = addr\n self.reader = reader\n self.writer = writer\n\n def __str__(self):\n return \"client: uid={0}, addr={1}\".format(self.uid, self.addr)\n\n\nclass ServerConnection(net.Connection):\n \"\"\"Game server\"\"\"\n\n MAX_CLIENTS = 16\n\n def __init__(self,\n bind_to=None,\n loop=asyncio.get_event_loop(),\n socket_type=\"tcp\"):\n \"\"\"NOTE: with socket_type = unix, the bind_to needs to be None or a\n temporary directory. This directory is removed on exit.\"\"\"\n super().__init__()\n self.clients = []\n self.server = None\n self._uid_cursor = 0 # ringbuf cur.\n self.loop = loop\n\n self.proto_map = {\n \"tcp\": self._start_tcp_server,\n \"unix\": self._start_unix_server\n }\n if socket_type not in self.proto_map:\n raise ValueError(\"socket type: {0} not valid.\".format(socket_type))\n self.socket_type = socket_type\n\n if bind_to is None:\n if socket_type == \"unix\":\n self.bind_to = self._unique_unix_socket_path()\n else:\n self.bind_to = \"localhost\"\n else:\n self.bind_to = bind_to\n\n self.register_handler(net.EVT_PACKET_SEND, self.handle_packet_send)\n\n def _unique_unix_socket_path(self):\n directory = tempfile.mkdtemp(prefix=\"sock-serv\", dir=com.CONFIG_HOME)\n sock_name = \"socket\"\n return os.path.join(directory, \"socket\")\n\n def _create_client(self, uid, *args, **kwargs):\n client = ServerClient(uid, *args, **kwargs)\n self._add_client(client)\n\n def create_evt(pkt):\n return net.NetEvent(net.EVT_PACKET_RECV, uid, pkt)\n\n # Server listens for client packets\n coro = self.listen_packets(client.reader, create_evt)\n task = asyncio.Task(coro, loop=self.loop)\n # Cleanup on socket death\n task.add_done_callback(lambda t: self.disconnect_client(client, t))\n return client\n\n def _add_client(self, client):\n self.clients.append(client)\n\n def _remove_client_by_uid(self, uid):\n for idx, client in enumerate(self.clients):\n if idx == uid:\n del self.clients[idx]\n\n def _get_client_by_uid(self, uid):\n for idx, client in enumerate(self.clients):\n if client.uid == uid:\n return self.clients[idx]\n\n def _next_uid(self):\n # Spawn new unique client ID. ring used for simplicity.\n uid = self._uid_cursor\n self._uid_cursor = (uid + 1) % ServerConnection.MAX_CLIENTS\n return uid\n\n def get_client_count(self):\n return len(self.clients)\n\n @asyncio.coroutine\n def accept_client(self, reader, writer):\n uid = self._next_uid()\n\n remote_addr = self._get_addr(writer)\n if remote_addr is None:\n log.warn(\"Error on client uid={0} connect.\".format(uid))\n return\n\n client = self._create_client(uid, remote_addr, reader, writer)\n\n yield from self.notify(net.NetEvent(EVT_SERVER_NEW_CLIENT, uid))\n log.info(\"{0} connected.\".format(client))\n\n @asyncio.coroutine\n def handle_packet_send(self, event):\n client = self._get_client_by_uid(event.uid)\n if client is None:\n return\n try:\n yield from self.send_packets(client.writer, event.pkt)\n except socket.error as err:\n log.debug(\"Error while sending packets to {0}\".format(client))\n self.disconnect_client(client)\n return\n\n def disconnect_client_by_uid(self, uid):\n # task of disconnect notification is returned\n self._remove_client_by_uid(uid)\n event = net.NetEvent(EVT_SERVER_DISCONNECTED_CLIENT, uid)\n\n task = asyncio.Task(self.notify(event), loop=self.loop)\n return task\n\n def disconnect_client(self, client, client_task=None):\n if client_task:\n try:\n result = client_task.result()\n except Exception as err:\n msg = \"{0} completed with an error. {1}\".format(client, err)\n log.debug(msg)\n\n log.info(\"{0} disconnected.\".format(client))\n self.disconnect_client_by_uid(client.uid)\n\n def _start_server(self, coro):\n try:\n self.server = self.loop.run_until_complete(coro)\n except Exception as err:\n log.error(\"server connection crashed on startup\")\n raise err\n\n def _start_tcp_server(self):\n self._start_server(asyncio.start_server(self.accept_client,\n loop=self.loop,\n host=self.bind_to,\n port=net.SERVER_PORT,\n reuse_address=True))\n\n def _start_unix_server(self):\n def socket_cleanup():\n shutil.rmtree(os.path.dirname(self.bind_to))\n log.debug(\"UNIX socket {0} cleaned up.\".format(self.bind_to))\n\n atexit.register(socket_cleanup)\n self._start_server(asyncio.start_unix_server(self.accept_client,\n path=self.bind_to,\n loop=self.loop))\n\n def start_server(self):\n self.proto_map[self.socket_type]()\n\n log.info(\"spaceking server listening.\")\n self.notify(net.NetEvent(EVT_SERVER_RUNNING, None))\n\n def quit(self):\n log.debug(\"spaceking server connection shutting down.\")\n if self.server:\n self.server.close()\n self.server = None\n self.notify(net.NetEvent(EVT_SERVER_QUIT, None))\n else:\n log.debug(\"Calling quit on a dead server\")\n","sub_path":"spaceking/server/net.py","file_name":"net.py","file_ext":"py","file_size_in_byte":6412,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"531321693","text":"# -*- coding: utf-8 -*-\n# Cardboardlint is a cheap lint solution for pull requests.\n# Copyright (C) 2011-2017 The Cardboardlint Development Team\n#\n# This file is part of Cardboardlint.\n#\n# Cardboardlint is free software; you can redistribute it and/or\n# modify it under the terms of the GNU General Public License\n# as published by the Free Software Foundation; either version 3\n# of the License, or (at your option) any later version.\n#\n# Cardboardlint 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 this program; if not, see
Relics:
Welcome to SafeToSwim!
'''\n\n@application.route(\"/predict\", methods=['GET', 'POST'])\ndef predict():\n # initialize the data dictionary that will be returned from the\n # view\n data = {\"success\": False}\n\n # ensure an image was properly uploaded to our endpoint\n if flask.request.method == \"POST\":\n if flask.request.files.get(\"image\"):\n # read the image in PIL format\n image = flask.request.files[\"image\"].read()\n photo_processor = PhotoProcessor(image)\n location = 'OakLedge'\n submitter = 'admin@safetoswim.org'\n longitude = 0.0\n # photo_processor.exif['DateTime']\n # photo_processor.exif['DateTimeOriginal']\n # photo_processor.exif['']\n # photo_processor.exif['']\n # photo_processor.exif['']\n # photo_processor.exif['']\n # photo_processor.exif['']\n # photo_processor.exif['']\n if 'DateTime' in photo_processor.exif_data:\n date = datetime.datetime.strptime(photo_processor.exif_data['DateTime'], '%Y:%m:%d %H:%M:%S')\n else:\n date = datetime.datetime.now()\n time = date.time()\n date = date.date()\n #date, time, name='', location='', latitude=0.0, longitude=0.0\n save_image(submitter, 'images/one.jpg', str(date), str(time), 'New Sample', location,\n photo_processor.latitude, photo_processor.longitude)\n\n # preprocess the image and prepare it for classification\n rgb_data = photo_processor.prepare_rgb_data(img_size=(128, 128))\n\n # classify the input image and then initialize the list\n # of predictions to return to the client\n # classify the input image and then initialize the list\n # of predictions to return to the client\n preds = None\n model = get_model()\n with graph.as_default():\n preds = model.predict(rgb_data)\n if preds[0][0] >= 0.5:\n data[\"prediction\"] = 'bloom'\n else:\n data[\"prediction\"] = 'not-bloom'\n\n #data['exif'] = photo_processor.exif\n\n # loop over the results and add them to the list of\n # returned predictions\n '''\n for (imagenetID, label, prob) in results[0]:\n r = {\"label\": label, \"probability\": float(prob)}\n data[\"predictions\"].append(r)\n '''\n\n # indicate that the request was a success\n data[\"success\"] = True\n\n # return the data dictionary as a JSON response\n response = flask.jsonify(data)\n return response\n else:\n pass\n else:\n return '''\n \nUpload new File
\n \n%s
\n ''' % \"\".join(os.listdir(application.config['UPLOAD_FOLDER'], ))\n\n\nif __name__ == \"__main__\":\n print((\"* Loading Keras model and Flask starting server...\"\n \"please wait until server has fully started\"))\n load_model()\n application.run(host=\"0.0.0.0\", debug=True)\n\n","sub_path":"safetoswim/servers/flask_server.py","file_name":"flask_server.py","file_ext":"py","file_size_in_byte":4954,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"596506285","text":"import logging\r\nimport requests\r\n\r\nfrom apiproxy import constants\r\nfrom .exceptions import LoggedDetailsAPIException\r\n\r\nlogger = logging.getLogger(__name__)\r\n\r\nclass APIActionCaller():\r\n\t\"\"\"Abstract class which must be inherited to handle a call to a Calendar42 API action\r\n\t\r\n\tThe abstract methods to implement are:\r\n\t* extract_data()\r\n\t* get_relative_url()\r\n\t\"\"\"\r\n\t\r\n\tdef __init__(self, token):\r\n\t\t\"\"\"\r\n\t\t@param {str} token\tThe authentication token to use when calling the Calendar42 API\r\n\t\t\"\"\"\r\n\t\tself._token = token\r\n\t\r\n\tdef call(self, *args, **kwargs):\r\n\t\t\"\"\"Calls the Calendar42 API and returns the response\r\n\t\tParameters (if any) are forwarded to self.get_relative_url(), which may need some runtime data to compute the URL\r\n\t\t\r\n\t\t@return\t{dict}\tThe JSON API response\r\n\t\t\"\"\"\r\n\t\t\r\n\t\t# Call the Calendar42 API\r\n\t\tfull_url = constants.CALENDAR42_API_BASE_URL + self.get_relative_url(*args, **kwargs)\r\n\t\t\r\n\t\theaders = {\r\n\t\t\t'Accept': 'application/json',\r\n\t\t\t'Content-type': 'application/json',\r\n\t\t\t'Authorization': 'Token %s' % self._token,\r\n\t\t}\r\n\t\tresponse = requests.get(full_url, headers=headers)\r\n\t\t\r\n\t\t# Parse response as JSON\r\n\t\ttry:\r\n\t\t\tjson_data = response.json()\r\n\t\texcept ValueError as e:\r\n\t\t\tlogger.exception(e)\r\n\t\t\tlogger.error(\"URL called: %s\\nHere's the body of the response which couldn't get parsed to JSON: %s\" % (full_url, response.text))\r\n\t\t\traise LoggedDetailsAPIException()\r\n\t\t\r\n\t\t# Extract desired information\r\n\t\ttry:\r\n\t\t\tif 'error' in json_data:\r\n\t\t\t\t# Forward error from Calendar42 API to client\r\n\t\t\t\traise LoggedDetailsAPIException(json_data['error']['message'])\r\n\t\t\t\t\r\n\t\t\treturn self.extract_data(json_data)\r\n\t\texcept (KeyError, ValueError, AttributeError) as e:\r\n\t\t\tlogger.exception(e)\r\n\t\t\tlogger.error(\"URL called: %s\\nHere's the JSON data which didn't fit the expected format: %s\" % (full_url, json_data))\r\n\t\t\traise LoggedDetailsAPIException()\r\n\t\r\n\tdef extract_data(self, json_data):\r\n\t\t\"\"\"ABSTRACT METHOD - TO BE IMPLEMENTED IN CHILD CLASS\r\n\t\t\r\n\t\tExtracts the desired information from the JSON data returned by the Calendar42 API\r\n\t\t@param {dict} json_data\r\n\t\t@return {dict}\tThe extracted data\r\n\t\t\"\"\"\r\n\t\tlogger.exception(NotImplementedError())\r\n\t\traise LoggedDetailsAPIException()\r\n\t\r\n\tdef get_relative_url(self, *args, **kwargs):\r\n\t\t\"\"\"ABSTRACT METHOD - TO BE IMPLEMENTED IN CHILD CLASS\r\n\t\t\r\n\t\tReturns the end of the URL, corresponding to the API action to call\r\n\t\t\"\"\"\r\n\t\tlogger.exception(NotImplementedError())\r\n\t\traise LoggedDetailsAPIException()\r\n\r\n\r\nclass EventDetailsAPIActionCaller(APIActionCaller):\r\n\t\"\"\"Gets details (ID and title) of an event\"\"\"\r\n\r\n\tdef get_relative_url(self, event_id):\r\n\t\treturn constants.CALENDAR42_API_EVENT.format(event_id)\r\n\r\n\tdef extract_data(self, json_data):\r\n\t\traw_details = json_data['data'][0]\r\n\t\tdetails = {\r\n\t\t\t'id': raw_details['id'],\r\n\t\t\t'title': raw_details['title'],\r\n\t\t}\r\n\t\treturn details\r\n\r\n\t\t\r\nclass EventParticipantsAPIActionCaller(APIActionCaller):\r\n\t\"\"\"Gets list of participants to an event\"\"\"\r\n\r\n\tdef get_relative_url(self, event_id):\r\n\t\treturn constants.CALENDAR42_API_PARTICIPANTS.format(event_id)\r\n\r\n\tdef extract_data(self, json_data):\r\n\t\treturn [item['subscriber']['first_name'] for item in json_data['data']]\r\n","sub_path":"apiproxy/events/api_action_caller.py","file_name":"api_action_caller.py","file_ext":"py","file_size_in_byte":3199,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"509688631","text":"from rest_framework import filters, mixins, viewsets\nfrom rest_framework.decorators import action\nfrom rest_framework.permissions import IsAdminUser\nfrom sreps.api.v1.serializers.customer import CustomerSerializer\nfrom sreps.api.v1.serializers.invoice import InvoiceListSerializer\nfrom sreps.core.models import Customer, Invoice\n\n\nclass CustomerViewSet(\n mixins.ListModelMixin,\n mixins.RetrieveModelMixin,\n mixins.CreateModelMixin,\n mixins.UpdateModelMixin,\n mixins.DestroyModelMixin,\n viewsets.GenericViewSet,):\n\n queryset = Customer.objects.all()\n serializer_class = CustomerSerializer\n permission_classes = (IsAdminUser,)\n\n @action(detail=True, methods=['GET'], name='Customer invoices')\n def invoices(self, request, pk=None):\n \"\"\"Get invoices made by a customer.\"\"\"\n\n customer = get_object_or_404(self.queryset, pk=pk)\n\n invoices = Invoice.objects.filter(\n customer=customer).order_by('-datetime_created')\n serializer = InvoiceListSerializer(invoices, many=True)\n\n return Response(serializer.data)\n","sub_path":"sreps/api/v1/views/customer.py","file_name":"customer.py","file_ext":"py","file_size_in_byte":1105,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"290191003","text":"#from fastapi import FastAPI\r\n#from pydantic import BaseModel\r\nimport pickle\r\nimport streamlit as st\r\nfrom sklearn.naive_bayes import GaussianNB\r\nimport numpy as np\r\nimport pandas as pd\r\n\r\n'''\r\napp=FastAPI()\r\nclass request_body(BaseModel):\r\n Age:float\r\n Hypertension:str\r\n Heart_disease:str\r\n Average_glucose: float\r\n BMI: float\r\n Marital_status: str\r\n Gender: str\r\n Work_type: str\r\n Residence:str\r\n Smoking_status: str\r\n'''\r\ndf=pd.read_csv(\"stroke_data_Cleaned3.csv\",header=0)\r\nprint(df.head())\r\n\r\n#Creating X and y Variables for Training Testing datasets\r\nX=df.drop([\"stroke\"],axis=1)\r\ny=df[\"stroke\"] #Target Variable\r\n\r\n#Creating Training Testing datasets\r\nfrom sklearn.model_selection import train_test_split\r\nX_train, X_test, y_train, y_test= train_test_split(X,y, test_size=0.2, random_state=5)\r\n#I have tried using K-best(taking 6 Variables) and the Classification Report doesnot show much Variation thus we are not using K-best\r\n\r\n#Creating Classification Models\r\n#I am using Naive Bayes Classification here, thus Scaling and One Hot Encoding is not Required\r\nmodel=GaussianNB()\r\nmodel.fit(X_train,y_train)\r\ny_pred=model.predict(X_test)\r\n\r\n#Testing effeciency of Naive Bayes Classifier\r\nfrom sklearn.metrics import confusion_matrix, classification_report,recall_score,f1_score\r\ncm=confusion_matrix(y_test, y_pred)\r\nprint(\"Confusion Matrix\")\r\nprint(cm)\r\ncr=classification_report(y_test, y_pred)\r\nprint(\"Classification Report\")\r\nprint(cr)\r\n#Since this dataset is not balanced accuracy is not the measure we will be looking for\r\n# Here we want to reduce the number of False negatives so we will look at Recall and F1 Score\r\nrs=recall_score(y_test,y_pred, average=\"weighted\")\r\nfs=f1_score(y_test,y_pred,average=\"weighted\")\r\nprint(\"Recall Value: \",rs)\r\nprint(\"F1 Score: \",fs)\r\n\r\n#Pickle is used for saving .pkl file\r\n#We are using .pkl file because we are going to deploy the model on Streamlit\r\npickle.dump(model,open('stroke.pkl','wb'))\r\nloaded_model=pickle.load(open('stroke.pkl','rb'))\r\n\r\n#For deploying on the Website\r\ndef predict_input_page():\r\n loaded_model = pickle.load(open('stroke.pkl', 'rb'))\r\n st.title(\"Stroke Prediction Model\")\r\n Age=st.slider(\"Age: \", min_value=0, max_value=90)\r\n Hypertension = st.radio(\"Do you suffer from Hypertension: \",(\"Yes\",\"No\"))\r\n Heart_disease=st.radio(\"Do you suffer from Heart Disease: \",(\"Yes\",\"No\"))\r\n Average_glucose=st.slider(\"Average Glucose Levels: \", min_value=50, max_value=280)\r\n BMI=st.slider(\"BMI: \",min_value=10, max_value=70)\r\n Marrital_status=st.radio(\"Are you married: \",(\"Yes\",\"No\"))\r\n Gender=st.radio(\"What is your Gender: \",(\"Male\",\"Female\"))\r\n Work_type=st.radio(\"What is your Work type?\",(\"Private\",\"Self-employed\",\"children\",\"Govt_job\",\"Never_worked\"))\r\n Residence=st.radio(\"What is your area of Residence\",(\"Urban\",\"Rural\"))\r\n Smoking_status=st.radio(\"Enter your Smoking Status:\",(\"never smoked\",\"Unknown\",\"formerly smoked\",\"smokes\"))\r\n ok=st.button(\"Predict\")\r\n\r\n #Since we are taking the input as a string and the model needs the values in numbers we convert the String to int\r\n if Hypertension==\"Yes\":\r\n Hypertension= 1\r\n elif Hypertension==\"No\":\r\n Hypertension=0\r\n\r\n if Heart_disease==\"Yes\":\r\n Heart_disease= 1\r\n elif Heart_disease==\"No\":\r\n Heart_disease=0\r\n\r\n if Marrital_status==\"Yes\":\r\n Marrital_status=1\r\n elif Marrital_status==\"No\":\r\n Marrital_status=0\r\n\r\n if Gender==\"Male\":\r\n Gender=1\r\n elif Gender==\"Female\":\r\n Gender=0\r\n\r\n if Work_type==\"Govt_job\":\r\n Work_type=0\r\n elif Work_type==\"Never_worked\":\r\n Work_type=1\r\n elif Work_type==\"Private\":\r\n Work_type=2\r\n elif Work_type==\"Self-employed\":\r\n Work_type=3\r\n elif Work_type==\"children\":\r\n Work_type=4\r\n\r\n if Residence==\"Rural\":\r\n Residence=0\r\n elif Residence==\"Urban\":\r\n Residence=1\r\n\r\n if Smoking_status==\"Unknown\":\r\n Smoking_status=0\r\n elif Smoking_status==\"formerly smoked\":\r\n Smoking_status=1\r\n elif Smoking_status==\"never smoked\":\r\n Smoking_status=2\r\n elif Smoking_status==\"smokes\":\r\n Smoking_status=3\r\n\r\n testdata=np.array([[Age, Hypertension, Heart_disease, Average_glucose, BMI, Marrital_status,Gender,Work_type,Residence,Smoking_status]])\r\n classi=loaded_model.predict(testdata)[0]\r\n\r\n try:\r\n if ok==True:\r\n if classi == 0:\r\n st.success(\"Awesome! You are on low risk of getting Stroke\")\r\n elif classi == 1:\r\n st.error(\"Cautious! You are on high risk of getting Stroke\")\r\n except:\r\n st.info(\"Enter some Data\")\r\n\r\n\r\n\r\n\r\n","sub_path":"ML_Project_2_209027.py","file_name":"ML_Project_2_209027.py","file_ext":"py","file_size_in_byte":4696,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"200320471","text":"#!/usr/bin/python3\n\nimport spaceking.net as net\nimport spaceking.common as com\nimport spaceking.log as log\nimport spaceking.event as ev\n\nimport shutil\nimport atexit\nimport os\nimport tempfile\nimport asyncio\nimport socket\n\nEVT_SERVER_RUNNING = 15000\nEVT_SERVER_QUIT = 15001\nEVT_SERVER_CONNECTED = 15002\nEVT_SERVER_DISCONNECTED = 15003\nEVT_SERVER_FAILED_JOIN = 15004\nEVT_SERVER_FAILED_CLIENT = 15005\nEVT_SERVER_NEW_CLIENT = 15006\nEVT_SERVER_DISCONNECTED_CLIENT = 15007\n\n\nclass ServerClient:\n\n __slots__ = [\"uid\", \"addr\", \"reader\", \"writer\"]\n\n def __init__(self, uid, addr, reader, writer):\n self.uid = uid\n self.addr = addr\n self.reader = reader\n self.writer = writer\n\n def __str__(self):\n return \"client: uid={0}, addr={1}\".format(self.uid, self.addr)\n\n\nclass ServerConnection(net.Connection):\n \"\"\"Game server\"\"\"\n\n MAX_CLIENTS = 16\n\n def __init__(self,\n bind_to=None,\n loop=asyncio.get_event_loop(),\n socket_type=\"tcp\"):\n \"\"\"NOTE: with socket_type = unix, the bind_to needs to be None or a\n temporary directory. This directory is removed on exit.\"\"\"\n super().__init__()\n self.clients = []\n self.server = None\n self._uid_cursor = 0 # ringbuf cur.\n self.loop = loop\n\n self.proto_map = {\n \"tcp\": self._start_tcp_server,\n \"unix\": self._start_unix_server\n }\n if socket_type not in self.proto_map:\n raise ValueError(\"socket type: {0} not valid.\".format(socket_type))\n self.socket_type = socket_type\n\n if bind_to is None:\n if socket_type == \"unix\":\n self.bind_to = self._unique_unix_socket_path()\n else:\n self.bind_to = \"localhost\"\n else:\n self.bind_to = bind_to\n\n self.register_handler(net.EVT_PACKET_SEND, self.handle_packet_send)\n\n def _unique_unix_socket_path(self):\n directory = tempfile.mkdtemp(prefix=\"sock-serv\", dir=com.CONFIG_HOME)\n sock_name = \"socket\"\n return os.path.join(directory, \"socket\")\n\n def _create_client(self, uid, *args, **kwargs):\n client = ServerClient(uid, *args, **kwargs)\n self._add_client(client)\n\n def create_evt(pkt):\n return net.NetEvent(net.EVT_PACKET_RECV, uid, pkt)\n\n # Server listens for client packets\n coro = self.listen_packets(client.reader, create_evt)\n task = asyncio.Task(coro, loop=self.loop)\n # Cleanup on socket death\n task.add_done_callback(lambda t: self.disconnect_client(client, t))\n return client\n\n def _add_client(self, client):\n self.clients.append(client)\n\n def _remove_client_by_uid(self, uid):\n for idx, client in enumerate(self.clients):\n if idx == uid:\n del self.clients[idx]\n\n def _get_client_by_uid(self, uid):\n for idx, client in enumerate(self.clients):\n if client.uid == uid:\n return self.clients[idx]\n\n def _next_uid(self):\n # Spawn new unique client ID. ring used for simplicity.\n uid = self._uid_cursor\n self._uid_cursor = (uid + 1) % ServerConnection.MAX_CLIENTS\n return uid\n\n def get_client_count(self):\n return len(self.clients)\n\n @asyncio.coroutine\n def accept_client(self, reader, writer):\n uid = self._next_uid()\n\n remote_addr = self._get_addr(writer)\n if remote_addr is None:\n log.warn(\"Error on client uid={0} connect.\".format(uid))\n return\n\n client = self._create_client(uid, remote_addr, reader, writer)\n\n yield from self.notify(net.NetEvent(EVT_SERVER_NEW_CLIENT, uid))\n log.info(\"{0} connected.\".format(client))\n\n @asyncio.coroutine\n def handle_packet_send(self, event):\n client = self._get_client_by_uid(event.uid)\n if client is None:\n return\n try:\n yield from self.send_packets(client.writer, event.pkt)\n except socket.error as err:\n log.debug(\"Error while sending packets to {0}\".format(client))\n self.disconnect_client(client)\n return\n\n def disconnect_client_by_uid(self, uid):\n # task of disconnect notification is returned\n self._remove_client_by_uid(uid)\n event = net.NetEvent(EVT_SERVER_DISCONNECTED_CLIENT, uid)\n\n task = asyncio.Task(self.notify(event), loop=self.loop)\n return task\n\n def disconnect_client(self, client, client_task=None):\n if client_task:\n try:\n result = client_task.result()\n except Exception as err:\n msg = \"{0} completed with an error. {1}\".format(client, err)\n log.debug(msg)\n\n log.info(\"{0} disconnected.\".format(client))\n self.disconnect_client_by_uid(client.uid)\n\n def _start_server(self, coro):\n try:\n self.server = self.loop.run_until_complete(coro)\n except Exception as err:\n log.error(\"server connection crashed on startup\")\n raise err\n\n def _start_tcp_server(self):\n self._start_server(asyncio.start_server(self.accept_client,\n loop=self.loop,\n host=self.bind_to,\n port=net.SERVER_PORT,\n reuse_address=True))\n\n def _start_unix_server(self):\n def socket_cleanup():\n shutil.rmtree(os.path.dirname(self.bind_to))\n log.debug(\"UNIX socket {0} cleaned up.\".format(self.bind_to))\n\n atexit.register(socket_cleanup)\n self._start_server(asyncio.start_unix_server(self.accept_client,\n path=self.bind_to,\n loop=self.loop))\n\n def start_server(self):\n self.proto_map[self.socket_type]()\n\n log.info(\"spaceking server listening.\")\n self.notify(net.NetEvent(EVT_SERVER_RUNNING, None))\n\n def quit(self):\n log.debug(\"spaceking server connection shutting down.\")\n if self.server:\n self.server.close()\n self.server = None\n self.notify(net.NetEvent(EVT_SERVER_QUIT, None))\n else:\n log.debug(\"Calling quit on a dead server\")\n","sub_path":"spaceking/server/net.py","file_name":"net.py","file_ext":"py","file_size_in_byte":6412,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"531321693","text":"# -*- coding: utf-8 -*-\n# Cardboardlint is a cheap lint solution for pull requests.\n# Copyright (C) 2011-2017 The Cardboardlint Development Team\n#\n# This file is part of Cardboardlint.\n#\n# Cardboardlint is free software; you can redistribute it and/or\n# modify it under the terms of the GNU General Public License\n# as published by the Free Software Foundation; either version 3\n# of the License, or (at your option) any later version.\n#\n# Cardboardlint 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 this program; if not, see
- (.*?)
- .*?'\n re_time=''\n re_content=r'(.*?)'\n re_hand=[]\n typeid=186\n typeid2=155\n url='http://info.1688.com/tags_list/v5003220-l18935.html'\n get_net_news(main_url,url,typeid,typeid2,re_html,re_list,re_time,re_content,re_hand)\n\ntest_ali88()","sub_path":"zzpython/数据更新/get_zz91_news/ali88.py","file_name":"ali88.py","file_ext":"py","file_size_in_byte":497,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"321796321","text":"#!/usr/bin/env python3\n\nimport re\nimport os\nimport sys\nimport time\nimport signal\nimport msfrpc\nimport asyncio\nimport argparse\nimport netifaces\nfrom IPython import embed\nfrom termcolor import colored\nfrom netaddr import IPNetwork, AddrFormatError\nfrom subprocess import Popen, PIPE, CalledProcessError\n\nBUSY_SESSIONS = []\n\ndef parse_args():\n # Create the arguments\n parser = argparse.ArgumentParser()\n parser.add_argument(\"-l\", \"--hostlist\", help=\"Host list file\")\n parser.add_argument(\"-p\", \"--password\", default='123', help=\"Password for msfrpc\")\n parser.add_argument(\"-u\", \"--username\", default='msf', help=\"Username for msfrpc\")\n return parser.parse_args()\n\n# Colored terminal output\ndef print_bad(msg):\n print((colored('[-] ', 'red') + msg))\n\ndef print_info(msg):\n print((colored('[*] ', 'blue') + msg))\n\ndef print_good(msg):\n print((colored('[+] ', 'green') + msg))\n\ndef print_great(msg):\n print((colored('[!] {}'.format(msg), 'yellow', attrs=['bold'])))\n\ndef kill_tasks():\n print()\n print_info('Killing tasks then exiting...')\n for task in asyncio.Task.all_tasks():\n task.cancel()\n\ndef get_iface():\n '''\n Gets the right interface for Responder\n '''\n try:\n iface = netifaces.gateways()['default'][netifaces.AF_INET][1]\n except:\n ifaces = []\n for iface in netifaces.interfaces():\n # list of ipv4 addrinfo dicts\n ipv4s = netifaces.ifaddresses(iface).get(netifaces.AF_INET, [])\n\n for entry in ipv4s:\n addr = entry.get('addr')\n if not addr:\n continue\n if not (iface.startswith('lo') or addr.startswith('127.')):\n ifaces.append(iface)\n\n iface = ifaces[0]\n\n return iface\n\ndef get_local_ip(iface):\n '''\n Gets the the local IP of an interface\n '''\n ip = netifaces.ifaddresses(iface)[netifaces.AF_INET][0]['addr']\n return ip\n\nasync def get_shell_info(CLIENT, sess_num):\n sysinfo_cmd = 'sysinfo'\n sysinfo_end_str = b'Meterpreter : '\n\n sysinfo_output = await run_session_cmd(CLIENT, sess_num, sysinfo_cmd, sysinfo_end_str)\n # Catch error\n if type(sysinfo_output) == str:\n return sysinfo_output\n\n else:\n sysinfo_utf8_out = sysinfo_output.decode('utf8')\n sysinfo_split = sysinfo_utf8_out.splitlines()\n\n getuid_cmd = 'getuid'\n getuid_end_str = b'Server username:'\n\n getuid_output = await run_session_cmd(CLIENT, sess_num, getuid_cmd, getuid_end_str)\n # Catch error\n if type(getuid_output) == str:\n return getuid_output\n else:\n getuid_utf8_out = getuid_output.decode('utf8')\n getuid = 'User : '+getuid_utf8_out.split('Server username: ')[-1].strip().strip()\n\n # We won't get here unless there's no errors\n shell_info_list = [getuid] + sysinfo_split\n\n return shell_info_list\n\ndef get_domain(shell_info):\n for l in shell_info:\n l_split = l.split(':')\n if 'Domain ' in l_split[0]:\n if 'WORKGROUP' in l_split[1]:\n return False\n else:\n domain = l_split[-1].strip()\n return domain\n\ndef is_domain_joined(user_info, domain):\n info_split = user_info.split(':')\n dom_and_user = info_split[1].strip()\n dom_and_user_split = dom_and_user.split('\\\\')\n dom = dom_and_user_split[0]\n user = dom_and_user_split[1]\n if domain:\n if dom.lower() in domain.lower():\n return True\n\n return False\n\ndef print_shell_data(shell_info, admin_shell, local_admin, sess_num_str):\n print_info('New shell info')\n for l in shell_info:\n print(' '+l)\n msg = ''' Admin shell : {}\n Local admin : {}\n Session number : {}'''.format( \n admin_shell.decode('utf8'), \n local_admin.decode('utf8'),\n sess_num_str)\n print(msg)\n\nasync def sess_first_check(CLIENT, session, sess_num):\n if b'first_check' not in session:\n print_good('Session {} found, gathering shell info...'.format(str(sess_num)))\n\n # Give meterpeter chance to open\n await asyncio.sleep(2)\n\n sess_num_str = str(sess_num)\n session[b'first_check'] = b'False'\n session[b'session_number'] = sess_num_str.encode()\n\n shell_info = await get_shell_info(CLIENT, sess_num)\n # Catch errors\n if type(shell_info) == str:\n session[b'error'] = shell_info.encode()\n return session\n\n # returns either a string of the domain name or False\n domain = get_domain(shell_info)\n if domain:\n session[b'domain'] = domain.encode()\n\n domain_joined = is_domain_joined(shell_info[0], domain)\n if domain_joined == True:\n session[b'domain_joined'] = b'True'\n else:\n session[b'domain_joined'] = b'False'\n\n admin_shell, local_admin = await is_admin(CLIENT, sess_num)\n # Catch errors\n if type(admin_shell) == str:\n session[b'error'] = admin_shell.encode()\n return session\n\n session[b'admin_shell'] = admin_shell\n session[b'local_admin'] = local_admin\n\n print_shell_data(shell_info, admin_shell, local_admin, sess_num_str)\n\n return session\n\nasync def is_admin(CLIENT, sess_num):\n cmd = 'run post/windows/gather/win_privs'\n\n output = await run_session_cmd(CLIENT, sess_num, cmd, None)\n # Catch error\n if type(output) == str:\n return (output, None)\n\n if output:\n split_out = output.decode('utf8').splitlines()\n user_info_list = split_out[5].split()\n admin_shell = user_info_list[0]\n system = user_info_list[1]\n local_admin = user_info_list[2]\n user = user_info_list[5]\n\n # Byte string\n return (str(admin_shell).encode(), str(local_admin).encode())\n\n else:\n return (b'ERROR', b'ERROR')\n\nasync def get_domain_controller(CLIENT, domain_data, sess_num):\n print_info('Getting domain controller...')\n cmd = 'run post/windows/gather/enum_domains'\n end_str = b'[+] Domain Controller:'\n output = await run_session_cmd(CLIENT, sess_num, cmd, end_str)\n\n # Catch timeout\n if type(output) == str:\n domain_data['err'].append(sess_num)\n return domain_data\n\n output = output.decode('utf8')\n if 'Domain Controller: ' in output:\n dc = output.split('Domain Controller: ')[-1].strip()\n domain_data['domain_controllers'].append(dc)\n print_good('Domain controller: '+dc)\n else:\n print_bad('No domain controller found')\n\n return domain_data\n\nasync def get_domain_admins(CLIENT, domain_data, sess_num):\n print_info('Getting domain admins...')\n cmd = 'run post/windows/gather/enum_domain_group_users GROUP=\"Domain Admins\"'\n end_str = b'[+] User list'\n\n output = await run_session_cmd(CLIENT, sess_num, cmd, end_str)\n # Catch timeout\n if type(output) == str:\n domain_data['err'].append(sess_num)\n return domain_data\n\n output = output.decode('utf8')\n da_line_start = '[*] \\t'\n\n if da_line_start in output:\n split_output = output.splitlines()\n print_info('Domain admins:')\n\n domain_admins = []\n for l in split_output:\n if l.startswith(da_line_start):\n domain_admin = l.split(da_line_start)[-1].strip()\n domain_admins.append(domain_admin)\n print(' '+domain_admin)\n domain_data['domain_admins'] = domain_admins\n\n else:\n print_bad('No domain admins found')\n sys.exit()\n\n return domain_data\n\nasync def get_domain_data(CLIENT, session, sess_num, domain_data):\n # Check if we did domain recon yet\n if domain_data['domain_admins'] == []:\n if session[b'domain_joined'] == b'True':\n domain_data = await get_domain_controller(CLIENT, domain_data, sess_num)\n domain_data = await get_domain_admins(CLIENT, domain_data, sess_num)\n\n return domain_data\n\nasync def attack_with_sessions(CLIENT, sessions, domain_data):\n\n if len(sessions) > 0:\n\n for s in sessions:\n\n # Get and print session info if first time we've checked the session\n sessions[s] = await sess_first_check(CLIENT, sessions[s], s)\n \n # Update domain data\n if b'domain' in sessions[s]:\n domain_data['domains'].append(sessions[s][b'domain'])\n\n if domain_data['domain_admins'] == []:\n domain_data = await get_domain_data(CLIENT, sessions[s], s, domain_data)\n\n return (sessions, domain_data)\n\ndef get_output(CLIENT, cmd, sess_num):\n output = CLIENT.call('session.meterpreter_read', [str(sess_num)])\n\n # Everythings fine\n if b'data' in output:\n return output[b'data']\n\n # Got an error from the CLIENT.call\n elif b'error_message' in output:\n decoded_err = output[b'error_message'].decode('utf8')\n print_bad(error_msg.format(sess_num_str, decoded_err))\n return decoded_err\n\n # Some other error catchall\n else:\n return cmd\n\ndef get_output_errors(output, counter, cmd, sess_num, timeout, sleep_secs):\n script_errors = [b'[-] post failed', \n b'error in script', \n b'operation failed', \n b'unknown command', \n b'operation timed out']\n\n # Got an error from output\n if any(x in output.lower() for x in script_errors):\n print_bad(('Command [{}] in session {} '\n 'failed with error: {}'\n ).format(cmd, str(sess_num), output.decode('utf8')))\n return cmd, counter\n\n # If no terminating string specified just wait til timeout\n if output == b'':\n counter += sleep_secs\n if counter > timeout:\n print_bad('Command [{}] in session {} timed out'.format(cmd, str(sess_num)))\n return 'timed out', counter\n\n # No output but we haven't reached timeout yet\n return output, counter\n\nasync def run_session_cmd(CLIENT, sess_num, cmd, end_str, timeout=30):\n ''' Will only return a str if we failed to run a cmd'''\n global BUSY_SESSIONS\n\n error_msg = 'Error in session {}: {}'\n sess_num_str = str(sess_num)\n\n print_info('Running [{}] on session {}'.format(cmd, str(sess_num)))\n\n while sess_num in BUSY_SESSIONS:\n await asyncio.sleep(.1)\n\n BUSY_SESSIONS.append(sess_num)\n\n res = CLIENT.call('session.meterpreter_run_single', [str(sess_num), cmd])\n\n if b'error_message' in res:\n err_msg = res[b'error_message'].decode('utf8')\n print_bad(error_msg.format(sess_num_str, err_msg))\n return err_msg\n\n elif res[b'result'] == b'success':\n\n counter = 0\n sleep_secs = 0.5\n\n try:\n while True:\n await asyncio.sleep(sleep_secs)\n\n output = get_output(CLIENT, cmd, sess_num)\n # Error from meterpreter console\n if type(output) == str:\n BUSY_SESSIONS.remove(sess_num)\n return output\n\n # Successfully completed\n if end_str:\n if end_str in output:\n BUSY_SESSIONS.remove(sess_num)\n return output\n # If no end_str specified just return once we have any data\n else:\n if len(output) > 0:\n BUSY_SESSIONS.remove(sess_num)\n return output\n\n # Check for errors from cmd's output\n output, counter = get_output_errors(output, counter, cmd, sess_num, timeout, sleep_secs)\n # Error from cmd output including timeout\n if type(output) == str:\n BUSY_SESSIONS.remove(sess_num)\n return output\n\n # This usually occurs when the session suddenly dies or user quits it\n except Exception as e:\n err = 'exception below likely due to abrupt death of session'\n print_bad(error_msg.format(sess_num_str, err))\n print_bad(' '+str(e))\n BUSY_SESSIONS.remove(sess_num)\n return err\n\n # b'result' not in res, b'error_message' not in res, just catch everything else as an error\n else:\n print_bad(res[b'result'].decode('utf8'))\n BUSY_SESSIONS.remove(sess_num)\n return cmd\n \ndef get_perm_token(CLIENT):\n # Authenticate and grab a permanent token\n CLIENT.login(args.username, args.password)\n CLIENT.call('auth.token_add', ['123'])\n CLIENT.token = '123'\n return CLIENT\n\ndef filter_broken_sessions(updated_sessions):\n ''' We remove 2 kinds of errored sessions: 1) timed out on sysinfo 2) shell died abruptly '''\n unbroken_sessions = {}\n\n for s in updated_sessions:\n if b'error' in updated_sessions[s]:\n # Session timed out on initial sysinfo cmd\n if b'domain' not in updated_sessions[s]:\n continue\n # Session abruptly died\n elif updated_sessions[s][b'error'] == b'exception below likely due to abrupt death of session':\n continue\n\n unbroken_sessions[s] = updated_sessions[s]\n\n return unbroken_sessions\n\ndef update_sessions(sessions, updated_sessions):\n ''' Four keys added after we process a new session: \n first_check, domain_joined, local_admin, admin_shell \n This function does not overwrite data from MSF\n it only adds previously known data to the MSF session'''\n if updated_sessions:\n udpated_sessions = filter_broken_sessions(updated_sessions)\n\n # s = session number, sessions[s] = session data dict\n for s in sessions:\n if s in updated_sessions:\n for k in updated_sessions[s]:\n if k not in sessions[s]:\n sessions[s][k] = updated_sessions[s].get(k)\n\n return sessions\n\nasync def check_for_sessions(CLIENT):\n domain_data = {'domains':[], \n 'domain_controllers':[], \n 'domain_admins':[], \n 'err':[]}\n updated_sessions = None\n print_info('Waiting for Meterpreter shell')\n\n while True:\n\n # Get list of MSF sessions from RPC server\n sessions = CLIENT.call('session.list')\n\n # Update the session info dict with previously found information\n sessions = update_sessions(sessions, updated_sessions)\n\n # Do stuff with the sessions\n updated_sessions, domain_data = await attack_with_sessions(CLIENT, sessions, domain_data)\n \n await asyncio.sleep(10)\n\ndef main(args):\n\n CLIENT = msfrpc.Msfrpc({})\n CLIENT = get_perm_token(CLIENT)\n\n loop = asyncio.get_event_loop()\n loop.add_signal_handler(signal.SIGINT, kill_tasks)\n task = asyncio.ensure_future(check_for_sessions(CLIENT))\n try:\n loop.run_until_complete(task)\n except asyncio.CancelledError:\n print_info('Tasks gracefully downed a cyanide pill before defecating themselves and collapsing in a twitchy pile')\n finally:\n loop.close()\n\nif __name__ == \"__main__\":\n args = parse_args()\n if os.geteuid():\n print_bad('Run as root')\n sys.exit()\n main(args)\n\n","sub_path":"msf-netpwn.py","file_name":"msf-netpwn.py","file_ext":"py","file_size_in_byte":15336,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"508440947","text":"import sys, os\nimport numpy as np\nfrom pyemma.thermo.util import get_averaged_bias_matrix as _get_averaged_bias_matrix\n\nnew_ass = np.load('../combined_assignment.npy',allow_pickle=True)\ndtraj = [[] for i in range(len(new_ass))]\nfor i in range(len(new_ass)):\n for j in range(len(new_ass[i])):\n dtraj[i].append(int(new_ass[i][j]))\ndtrajs = []\nfor i in range(len(dtraj)):\n dtrajs.append(np.array(dtraj[i]))\nbias = np.load('../bias_tram.npy',allow_pickle=True)\n\nbias_dtram = _get_averaged_bias_matrix(bias,dtrajs,nstates = 18)\n\nnp.save('bias_dtram.npy',bias_dtram)\n\n","sub_path":"lambda_only/results/cumu8/100/dtram/compute_bias_dtram.py","file_name":"compute_bias_dtram.py","file_ext":"py","file_size_in_byte":587,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"278185694","text":"#!/usr/bin/env python3.5\n\n\nimport aiohttp\nimport argparse\nimport asyncio\nimport functools\nimport requests\nimport multiprocessing as mp\nimport time\n\nimport config\nfrom logger import *\n\n\nclass ReusedSession:\n \"\"\" Session for connect to a server. Reuse after return a response (for keep-alive)\n Parameters:\n session (aiohttp.ClientSession): session for connect\n working (bool): flag shows the session does not have work for server \n \"\"\"\n def __init__(self):\n self.session = aiohttp.ClientSession()\n self.working = False\n self.failed = False\n\n\ndef get_free_session(sessions, loggers):\n \"\"\" Find not working session for assign new work. Create new one if no available sessions\n Args:\n sessions (list)\n sessions.item (ReusedSession)\n Returns:\n ReusedSession\n \"\"\"\n LOG, LOG_ERR = loggers\n\n failed_session_num = []\n free_session = None\n for i, s in enumerate(sessions):\n if s.failed:\n failed_session_num.append(i)\n continue\n\n if not s.working:\n free_session = s\n break\n\n # Reverse sort for correct delete in array - index out of range\n failed_session_num = sorted(failed_session_num, reverse=True)\n for i in failed_session_num:\n #LOG.put( LogMsg(LN.err.FAIL_SESSION, time.time()) )\n sessions[i].session.close()\n del sessions[i]\n\n if free_session is not None:\n return free_session\n\n s = ReusedSession()\n sessions.append(s)\n #LOG.put( LogMsg(LN.info.NEW_SESSION, time.time()) )\n\n return s\n\n\ndef free_session(session, *args):\n \"\"\" Returns for session opportunity reused\n Args:\n session (ReusedSession)\n Returns:\n void\n \"\"\"\n session.working = False\n\n\nasync def request(host, port, path, session, loggers):\n \"\"\" Requests server and wait response \n Args:\n session (ReusedSession)\n Returns:\n void\n \"\"\"\n LOG, LOG_ERR = loggers\n\n request_url = \"http://\" + host + \":\" + port + path\n\n try:\n async with aiohttp.client._RequestContextManager(session.session._request(aiohttp.hdrs.METH_GET, request_url)) as resp:\n #LOG.put( LogMsg(LN.info.REQUEST, time.time()) )\n await resp.text()\n asyncio.sleep(1)\n except Exception as err:\n #LOG_ERR.put( LogMsg(LN.err.REQUEST, time.time()) )\n session.failed = True\n asyncio.sleep(1)\n\n\ndef calc_rate(time_since_start, limit_rate):\n \"\"\" Suppose we need reach `limit_rate` in some time\n Args:\n time_since_start (int): num of seconds since start\n limit_rate (int): max rate for perfomance test\n Returns:\n curr_rate (int): rate for current time\n \"\"\"\n init_rate = config.INIT_RATE\n step_rate = config.STEP_RATE\n\n rate = init_rate + time_since_start * step_rate\n\n return [round(rate), limit_rate][rate > limit_rate]\n\n\nasync def schedule_send_requests(loop, host, port, path, rate, loggers):\n \"\"\" Schedule envoke send_requests with calculated rate every second\n Args:\n loop (asyncio.BaseEventLoop)\n host (str)\n port (str)\n rate (int)\n Returns:\n void\n \"\"\"\n reused_sessions = []\n it_num = -1\n \n while True:\n it_num += 1\n\n curr_rate = calc_rate(it_num, rate)\n task = loop.create_task( send_requests(loop=loop, host=host, port=port, path=path, rate=curr_rate, sessions=reused_sessions, loggers=loggers) )\n await asyncio.sleep(1)\n\n\nasync def send_requests(loop, host, port, path, rate, sessions, loggers):\n \"\"\" Sent requests for server 'host:port' with specified rate (rps)\n Args:\n loop (asyncio.BaseEventLoop)\n host (str)\n port (str)\n rate (int)\n Returns:\n void\n \"\"\"\n for i in range(rate):\n session = get_free_session(sessions, loggers)\n session.working = True\n task = loop.create_task( request(host, port, path, session, loggers) )\n task.add_done_callback( functools.partial(free_session, session) )\n\n\ndef load(host, port, path, rate, loggers):\n loop = asyncio.get_event_loop()\n loop.run_until_complete(\n schedule_send_requests(loop=loop, host=host, port=port, path=path, rate=rate, loggers=loggers))\n loop.close()\n\n\ndef parse_cmd():\n # for load simple nginx with sleep 1sec - the max for localhost 6processes x40 rate\n # beyond can't guarantee to maintain the level of rate (limit at cpu)\n parser = argparse.ArgumentParser()\n parser.add_argument(\"--rate\", type=int, required=True)\n parser.add_argument(\"--host\", type=str, required=True)\n parser.add_argument(\"--port\", type=str, required=True)\n parser.add_argument(\"--path\", type=str, required=True)\n\n return parser.parse_args()\n\n\nif __name__ == \"__main__\":\n args = parse_cmd()\n load(args.host, args.port, args.path, args.rate, (None, None))\n","sub_path":"loader/src/loader.py","file_name":"loader.py","file_ext":"py","file_size_in_byte":4883,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"51484934","text":"#!/usr/bin/env python3\n\nimport torch\nfrom torch import nn\nfrom torch.nn import functional as F\n#from model_utils import nll_categ_global, nll_gauss_global\n#from EmbeddingMul import EmbeddingMul\n\ndef nll_categ_global(categ_logp_feat, input_idx_feat, cat_feat_size,\n isRobust=False, w=None, isClean=False):\n\n # Normal\n if not isRobust:\n return F.nll_loss(categ_logp_feat, input_idx_feat, reduction='none').view(-1,1)\n\n # Robust\n w_r = w.view(-1,1)\n if isClean:\n return F.nll_loss(w_r*categ_logp_feat, input_idx_feat, reduction='none').view(-1,1)\n else:\n categ_logp_robust = torch.log(torch.tensor(1.0/cat_feat_size))\n categ_logp_robust = categ_logp_robust*torch.ones(categ_logp_feat.shape)\n categ_logp_robust = categ_logp_robust.type(categ_logp_feat.type())\n two_compnts = w_r*categ_logp_feat + (1-w_r)*categ_logp_robust\n\n return F.nll_loss(two_compnts, input_idx_feat, reduction='none').view(-1,1)\n\n\ndef nll_gauss_global(gauss_params, input_val_feat, logvar, isRobust=False, w=None,\n std_0_scale=2, isClean=False, shape_feats=[1]):\n\n # Normal\n mu = gauss_params.view([-1] + shape_feats)\n logvar_r = (logvar.exp() + 1e-9).log()\n\n data_compnt = 0.5*logvar_r + (input_val_feat.view([-1] + shape_feats) - mu)**2 / (2.* logvar_r.exp() + 1e-9)\n\n if not isRobust:\n return data_compnt.view([-1] + shape_feats)\n\n # Robust\n w_r = w.view([-1] + shape_feats)\n if isClean:\n return (w_r*data_compnt).view([-1] + shape_feats)\n else:\n #Outlier model\n mu_0 = 0.0\n var_0 = torch.tensor(std_0_scale**2).type(gauss_params.type())\n robust_compnt = 0.5*torch.log(var_0) + (input_val_feat.view([-1] + shape_feats) - mu_0)**2 / (2.* var_0 + 1e-9)\n\n return (w_r*data_compnt + (1-w_r)*robust_compnt).view([-1] + shape_feats)\n\n\nclass EmbeddingMul(nn.Module):\n \"\"\"This class implements a custom embedding mudule which uses matrix\n multiplication instead of a lookup. The method works in the functional\n way.\n Note: this class accepts the arguments from the original pytorch module\n but only with values that have no effects, i.e set to False, None or -1.\n \"\"\"\n\n def __init__(self, depth, device):\n super(EmbeddingMul, self).__init__()\n # i.e the dictionnary size\n self.depth = depth\n self.device = device\n self.ones = torch.eye(depth, requires_grad=False, device=self.device)\n self._requires_grad = False\n # \"oh\" means One Hot\n self.last_oh = None\n self.last_weight = None\n\n @property\n def requires_grad(self):\n return self._requires_grad\n\n @requires_grad.setter\n def requires_grad(self, value):\n self._requires_grad = value\n\n def forward(self, input, weight, padding_idx=None, max_norm=None,\n norm_type=2., scale_grad_by_freq=False, sparse=False, one_hot_input=True):\n \"\"\"Declares the same arguments as the original pytorch implementation\n but only for backward compatibility. Their values must be set to have\n no effects.\n Args:\n - input: of shape (bptt, bsize)\n - weight: of shape (dict_size, emsize)\n Returns:\n - result: of shape (bptt, bsize, dict_size)\n \"\"\"\n # ____________________________________________________________________\n # Checks if unsupported argument are used\n if padding_idx != -1:\n raise NotImplementedError(\n f\"padding_idx must be -1, not {padding_idx}\")\n # if max_norm is not None:\n # raise NotImplementedError(f\"max_norm must be None, not {max_norm}\")\n if scale_grad_by_freq:\n raise NotImplementedError(f\"scale_grad_by_freq must be False, \"\n f\"not {scale_grad_by_freq}\")\n if sparse:\n raise NotImplementedError(f\"sparse must be False, not {sparse}\")\n # ____________________________________________________________________\n\n if self.last_oh is not None:\n del self.last_oh\n if one_hot_input:\n self.last_oh = input\n else:\n self.last_oh = self.to_one_hot(input)\n\n with torch.set_grad_enabled(self.requires_grad):\n result = torch.stack(\n [torch.mm(batch.float(), weight)\n for batch in self.last_oh], dim=0)\n\n if max_norm is not None:\n # result = F.normalize(result, p=2, dim=-1)\n norm = result.norm(p=norm_type, dim=-1, keepdim=True)\n norm_mask = (norm > max_norm).float() # ).squeeze()\n result_new = result / norm * norm_mask + result * (1 - norm_mask)\n #result[:,norm_mask,:] = result[:,norm_mask,:].div(norm[:,norm_mask,:])\n else:\n result_new = result\n\n # self.last_weight = weight.clone() # NOTE: waste of memory?\n\n return result_new\n\n def to_one_hot(self, input):\n # Returns a new tensor that doesn't share memory\n result = torch.index_select(\n self.ones, 0, input.view(-1).long()).view(\n input.size()+(self.depth,))\n result.requires_grad = self.requires_grad\n return result\n\n def __repr__(self):\n return self.__class__.__name__ + \"({})\".format(self.depth)\n\n \nclass VAE(nn.Module):\n def __init__(self):\n\n super(VAE, self).__init__()\n\n feats = 3\n embedding_size = 50\n layer_size = 400\n latent_size = 5\n\n self.feat_info = [[\"time\",'categ',745],['pulocation','categ',266],['dozone','categ',7],['cnt','real',1]]\n self.size_input = feats*50+1\n self.size_output = feats + 1\n self.alpha = 0.95\n self.gauss = 2\n ## Encoder Params\n\n # define a different embedding matrix for each feature\n self.feat_embedd = nn.ModuleList([nn.Embedding(c_size, embedding_size, max_norm=1)\n for _, col_type, c_size in self.feat_info\n if col_type==\"categ\"])\n\n self.fc1 = nn.Linear(self.size_input, layer_size)\n self.fc21 = nn.Linear(layer_size, latent_size)\n self.fc22 = nn.Linear(layer_size, latent_size)\n\n ## Decoder Params\n\n self.fc3 = nn.Linear(latent_size,layer_size)\n\n self.out_cat_linears = nn.ModuleList([nn.Linear(layer_size, c_size) if col_type==\"categ\"\n else nn.Linear(layer_size, c_size)\n for _, col_type, c_size in self.feat_info])\n\n self.logvar_x = nn.Parameter(torch.zeros(1,1).float())\n\n ## Other\n\n self.activ = nn.ReLU()\n\n self.logSoftmax = nn.LogSoftmax(dim=1)\n self.sigmoid = nn.Sigmoid()\n\n # define encoder / decoder easy access parameter list\n encoder_list = [self.fc1, self.fc21, self.fc22]\n self.encoder_mod = nn.ModuleList(encoder_list)\n if self.feat_embedd:\n self.encoder_mod.append(self.feat_embedd)\n\n self.encoder_param_list = nn.ParameterList(self.encoder_mod.parameters())\n\n decoder_list = [self.fc3, self.out_cat_linears]\n self.decoder_mod = nn.ModuleList(decoder_list)\n self.decoder_param_list = nn.ParameterList(self.decoder_mod.parameters())\n if len(self.logvar_x):\n self.decoder_param_list.append(self.logvar_x)\n\n\n def get_inputs(self, x_data):\n input_list = []\n cursor_embed = 0\n start = 0\n \n for feat_idx, ( _, col_type, feat_size ) in enumerate(self.feat_info):\n if col_type == \"categ\":\n aux_categ = self.feat_embedd[cursor_embed](x_data[:,feat_idx].long())#*drop_mask[:,feat_idx].view(-1,1)\n input_list.append(aux_categ)\n cursor_embed += 1\n \n elif col_type == \"real\": \n input_list.append((x_data[:,feat_idx]).view(-1,1).float())#*drop_mask[:,feat_idx]\n \n return torch.cat(input_list, 1)\n\n def encode(self, x_data):\n q_params = dict()\n input_values = self.get_inputs(x_data)\n fc1_out = self.fc1(input_values)\n h1_qz = self.activ(fc1_out)\n q_params['z'] = {'mu': self.fc21(h1_qz), 'logvar': self.fc22(h1_qz)}\n return q_params\n\n def sample_normal(self, q_params_z):\n if self.training:\n eps = torch.randn_like(q_params_z['mu'])\n std = q_params_z['logvar'].mul(0.5).exp_()\n return eps.mul(std).add_(q_params_z['mu'])\n else:\n return q_params_z['mu']\n\n def reparameterize(self, q_params):\n q_samples = dict()\n q_samples['z'] = self.sample_normal(q_params['z'])\n return q_samples\n\n def decode(self, z):\n p_params = dict()\n h3 = self.activ(self.fc3(z))\n out_cat_list = []\n\n for feat_idx, out_cat_layer in enumerate(self.out_cat_linears):\n if self.feat_info[feat_idx][1] == \"categ\": # coltype check\n out_cat_list.append(self.logSoftmax(out_cat_layer(h3)))\n elif self.feat_info[feat_idx][1] == \"real\":\n out_cat_list.append(out_cat_layer(h3))\n\n # tensor with dims (batch_size, self.size_output)\n p_params['x'] = torch.cat(out_cat_list, 1)\n p_params['logvar_x'] = self.logvar_x.clamp(-3,3)\n return p_params\n\n def forward(self, x_data, n_epoch=None):\n q_params = self.encode(x_data)\n q_samples = self.reparameterize(q_params)\n return self.decode(q_samples['z']), q_params, q_samples\n\n def loss_function(self, input_data, p_params, q_params, q_samples, clean_comp_only=False, data_eval_clean=False):\n\n \"\"\" ELBO: reconstruction loss for each variable + KL div losses summed over elements of a batch \"\"\"\n\n dtype_float = torch.cuda.FloatTensor\n nll_val = torch.zeros(1).type(dtype_float)\n # mixed datasets, or just categorical / continuous with medium number of features\n start = 0\n cursor_num_feat = 0\n\n for feat_select, (_, col_type, feat_size) in enumerate(self.feat_info):\n pi_feat = torch.sigmoid(q_params['w']['logit_pi'][:,feat_select]).clamp(1e-6, 1-1e-6)\n \n if clean_comp_only and data_eval_clean:\n pi_feat = torch.ones_like(q_params['w']['logit_pi'][:,feat_select])\n \n # compute NLL\n if col_type == 'categ':\n nll_val += nll_categ_global(p_params['x'][:,start:(start + feat_size)],\n input_data[:,feat_select].long(), feat_size, isRobust=True,\n w=pi_feat, isClean=clean_comp_only).sum()\n start += feat_size\n elif col_type == 'real':\n nll_val += nll_gauss_global(p_params['x'][:,start:(start + 1)], # 2\n input_data[:,feat_select],\n p_params['logvar_x'][:,cursor_num_feat], isRobust=True,\n w=pi_feat, isClean=clean_comp_only, \n std_0_scale=self.gauss).sum()\n start += 1 # 2\n cursor_num_feat +=1\n\n\n # kld regularizer on the latent space\n z_kld = -0.5 * torch.sum(1 + q_params['z']['logvar'] - q_params['z']['mu'].pow(2) - q_params['z']['logvar'].exp())\n\n # prior on clean cells (higher values means more likely to be clean)\n prior_sig = torch.tensor(self.alpha).type(dtype_float)\n\n # kld regularized on the weights\n pi_mtx = torch.sigmoid(q_params['w']['logit_pi']).clamp(1e-6, 1-1e-6)\n w_kld = torch.sum(pi_mtx * torch.log(pi_mtx / prior_sig) + (1-pi_mtx) * torch.log((1-pi_mtx) / (1-prior_sig)))\n\n loss_ret = nll_val + z_kld if clean_comp_only else nll_val + z_kld + w_kld\n\n return loss_ret, nll_val, z_kld, w_kld \n\n\n\n \n","sub_path":"archived/RVAE_org_minimal/RVAE.py","file_name":"RVAE.py","file_ext":"py","file_size_in_byte":12049,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"308417780","text":"import xlwt\nimport time\n\ndef timeCove(a):\n timeArray = time.strptime(a, \"%Y%m%d\")\n otherStyleTime = time.strftime(\"%Y-%m-%d\",timeArray)\n return otherStyleTime\ndef set_style(name, height, bold=False):\n\n style = xlwt.XFStyle() # 初始化样式\n\n font = xlwt.Font() # 为样式创建字体\n font.name = name # 'Times New Roman'\n font.bold = bold\n font.color_index = 4\n font.height = height\n\n # borders= xlwt.Borders()\n # borders.left= 6\n # borders.right= 6\n # borders.top= 6\n # borders.bottom= 6\n\n style.font = font\n # style.borders = borders\n\n return style\n\n\n# 写excel\ndef write_excel(db,filename):\n f = xlwt.Workbook() # 创建工作簿\n '''\n 创建第一个sheet:\n sheet1\n '''\n sheet1 = f.add_sheet(u'sheet1', cell_overwrite_ok=True) # 创建sheet\n row0 = [u'收费员工号', u'日志日期', u'收入(元)']\n for i in range(0, len(row0)):\n sheet1.write(0, i, row0[i], set_style('Times New Roman', 220, True))\n\n for (i,j) in db.items():\n sheet1.write(i+1, 0, int('017'+str(j[2])), set_style('Times New Roman', 220, True))\n sheet1.write(i+1, 1, timeCove(j[0][0:8]), set_style('Times New Roman', 220, True))\n sheet1.write(i+1, 2, int(j[1])/100, set_style('Times New Roman', 220, True))\n f.save(filename[0:-4] + '.xlsx') # 保存文件\n\n\n","sub_path":"123/creatXls.py","file_name":"creatXls.py","file_ext":"py","file_size_in_byte":1355,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"479770045","text":"# Crie uma função que retorna os números pares, a seguir, utilize a função .filter() na\n# variável numerosAleatorios passando a função que você criou como callback. Veja\n# no slide sobre .filter() como fizemos\n\n\nnumerosAleatorios = [12, 47, 66, 35, 142, 71, 14, 6]\n\n\nnumFiltrado = filter(lambda x: x % 2 ==0, numerosAleatorios)\nnumFiltrado = list(numFiltrado)\n\nprint(numFiltrado)","sub_path":"Cappacita/ex_22.py","file_name":"ex_22.py","file_ext":"py","file_size_in_byte":388,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"61919113","text":"import pyautogui\r\nimport time\r\nfrom selenium import webdriver\r\n\r\n#定义图像识别双击事件\r\ndef mouseDoubleClick(image):\r\n x,y=pyautogui.locateCenterOnScreen(image,confidence=0.9)\r\n pyautogui.click(x,y,clicks=2,interval=0.2,duration=0.2,button='left')\r\n\r\n#定义单击事件\r\ndef mouseClick(image):\r\n x,y=pyautogui.locateCenterOnScreen(image,confidence=0.9)\r\n pyautogui.click(x,y,clicks=1,interval=0.2,duration=0.2,button='left')\r\n\r\nmouseDoubleClick(image = 'chorm.png')\r\n\r\npyautogui.write(\"www.baidu.com\")\r\ntime.sleep(1)\r\npyautogui.press(\"enter\")\r\ntime.sleep(3)\r\n\r\npyautogui.write(\"Detroit: Become Human\")\r\ntime.sleep(2)\r\npyautogui.press(\"enter\")\r\n","sub_path":"students/Siyang Liu/pyaotugui/pyautogui_serch.py","file_name":"pyautogui_serch.py","file_ext":"py","file_size_in_byte":667,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"296870774","text":"try:\n import numpy as np\nexcept ImportError:\n raise Exception(\"numpy is required for pygme\")\n\nfrom numpy import asarray\nfrom numpy import cos, sin, sqrt, arctan\n\ntry:\n from scipy import interpolate\nexcept ImportError:\n raise Exception(\"scipy is required for pygme\")\n\nimport os\nfrom .rwcfor import floatMGE\nfrom pygme.dynMGE import dynMGE\nfrom pygme.paramMGE import dynParamMGE\nfrom pygme.mge_miscfunctions import sample_trunc_r2gauss, sample_trunc_gauss\n\n__version__ = '2.0.4 (24/10/2014)' # Changed default value for SigmaGas and fixed comment in realise_Nbody\n#__version__ = '2.0.3 (21/08/2013)' \n#__version__ = '2.0.2 (16/01/2013)'\n# Version 2.0.3: Changed imin imax into ilist\n# Version 2.0.2: 16/01/2013 - Simplification in the derivation of sigR, sigZ, sigTheta\n# Version 2.0.1: 18/12/2012 - Adding the FacBetaEps factor as a parameter of the realise_Nbody routine\n\nclass nbodyMGE(dynMGE) :\n def __init__(self, infilename=None, indir=None, saveMGE=None, **kwargs) :\n dynMGE.__init__(self, infilename=infilename, indir=indir, saveMGE=saveMGE, **kwargs)\n\n########################################### N BODY #############################################\n ################################################################\n ### Generate N bodies consistent with the existing MGE model ###\n ################################################################\n def realise_Nbody(self, **kwargs):\n \"\"\" Generate particles within the potential defined by the MGE model\n Cuts in R and Z, in pc, are defined by Rcut and Zcut\n The number of particles and the way the particles have their\n dynamics derived is specified in the Ascii input MGE model\n (e.g. NGROUP, NDYNCOMP, NPARTGROUP1, 2, ...)\n Anisotropy can be specified in the input Ascii Model with\n numbers (if negative, the Spin will be reversed), 'epicycle' or 'betaeps'\n Rcut: cut in R, in pc - default is 50000\n Zcut: cut in Z, in pc - default is 50000\n mcut: cut in ellipsoidal coordinates, in pc (think of this as an ellipsoid with major-axis max radius = mcut )\n Default is 50000\n ComputeV: Boolean (True/False), if True (default) velocities are derived, otherwise only the positions\n GasDisk: Boolean (True/False), if True (default) the Gas component will have velocities compatible with a thin disk\n Otherwise, we will follow the prescription given by the kRZ and kRTheta components in the mge file\n SigmaGas: SigmaR, SigmaTheta and SigmaZ for the Gas, in km/s - default to 10 km/s for all 3 values\n TruncationMethod : Method to sample the positions.\n \"Ellipsoid\" (default): will follow the isosurface of each Gaussians at that radius as a cut\n mcut will be used (in pc)\n \"Cylindre\" means an R, Z Cylindrical cal (Rcut, Zcut will be used - in pc)\n Add_BHParticle : boolean, if defined (Default is True):\n True means that a BH particle is added if Mbh > 0\n False means that if Mbh > 0, the potential will take it\n into account but no particle is added\n Softening: in pc, softening added in quadrature to the gaussian Sigmas for the potential, Default is 0 (no softening)\n FacBetaEps : factor involved when using the BETAEPS option as an anisotropy parameter for the\n Gaussians. When one of the Gaussian component is using BETAEPS for K_R_Z, we fix the\n anisotropy to -> delta = FacBetaEps * Epsilon where delta = 1 - Sigma_Z^2/Sigma_R^2 and\n Epsilon is the intrinsic ellipticity of that Gaussian. Setting FacBetaEps >= 0.8 is not\n permitted (as this would break the requirement on the second order moments).\n\n verbose: default is 1, will print some more information\n \"\"\"\n import time\n\n ## Checking a Few things before starting ########################\n if self.nGauss <= 0 :\n print('ERROR: NGAUSS is not right (= %d)' %self.nGauss)\n return\n if self.TtruncMass <= 0:\n print('ERROR: Mass of the model (= %g) is not right' %self.TtruncMass)\n return\n opGAS = (self.nGasGauss != 0)\n opSTAR = (self.nStarGauss != 0)\n opHALO = (self.nHaloGauss != 0)\n\n ## Number of Groups -------------------------##\n if self.nGroup == 0:\n print(\"ERROR: nGroup is 0\")\n return\n if self.nDynComp == 0:\n print(\"ERROR: nDynComp is 0\")\n return\n\n ## Some options from kwargs -- INITIALISATION -------------------------------------- ##\n ##--- Compute only positions or also velocities ? ---##\n ComputeV = kwargs.get('ComputeV', True)\n GasDisk = kwargs.get('GasDisk', True)\n ## Get the dispersion for the gas in km/s -----------##\n (self.SigRGas, self.SigThetaGas, self.SigZGas) = kwargs.get('SigmaGas',(10.0,10.0,10.0))\n ## Add a BH particle or not? --- ##\n self.Add_BHParticle = kwargs.get('Add_BHParticle', True)\n ## Overwrite mode : 'o' or None ------------------------ ##\n self.overwrite = kwargs.get('overwrite', None)\n ## First Realised Particle, and Max number of Particle -- ##\n self.FirstRealisedPart = np.int(kwargs.get('FirstRealisedPart', 0))\n self.nMaxPart = np.int(kwargs.get('nMaxPart', 0))\n ## Softening -- default is 0 (no softening)--------- ##\n self.Softening = kwargs.get('Softening', 0.0)\n ## Verbose: default is 1 ----------##\n verbose = kwargs.get('verbose', 1)\n ## -------------------------------------------------------------------------------------##\n\n ## Softening in pc----------------------------------##\n if self.Softening > 0. :\n print(\"WARNING: Softening will be %g (pc) !!!\"%(self.Softening))\n self.Softarc = self.Softening / self.pc_per_arcsec # Softening in Arcseconds\n self.SoftarcMbh = self.Softarc # best approx for Mbh smoothing\n self.SoftarcMbh2 = self.SoftarcMbh**2\n\n ## -- Method for Truncating the Density distribution of particles ---##\n self.TruncationMethod = kwargs.get('TruncationMethod', 'Ellipsoid')\n if self.TruncationMethod == \"Cylindre\" :\n self.Rcut = kwargs.get('Rcut', 50000)\n self.Zcut = kwargs.get('Zcut', 50000)\n Xcut = self.Rcut\n self.Rcutarc = self.Rcut / self.pc_per_arcsec\n self.Zcutarc = self.Zcut / self.pc_per_arcsec\n elif self.TruncationMethod == \"Ellipsoid\" :\n self.mcut = kwargs.get('mcut', 50000)\n Xcut = self.mcut\n self.mcutarc = self.mcut / self.pc_per_arcsec\n else :\n print(\"ERROR: TruncationMethod should be Cylindre or Ellipsoid. not %s\" %(self.TruncationMethod))\n return\n\n ## We first save the MGE file for archival purposes, as well as the initial parameters\n self.RealisationTime = time.time()\n dest_filename = self.saveMGE + \"/\" + \"%s_\"%(str(self.RealisationTime)) + self.MGEname\n if os.path.isfile(dest_filename) & (str(self.overwrite).lower() != \"o\") :\n print(\"ERROR: filename already exists in Archival Directory %s\"%(dest_filename))\n print(\" Please use overwrite mode (O) or provide a different output directory (saveMGE)\")\n return\n os_command = \"cp %s %s\"%(self.fullMGEname, dest_filename)\n os.system(os_command)\n #--------------------------------------------------------------------------------------#\n\n ## Save the command into a file with the same time\n text = \"init_nbody(Rcut=%g, Zcut=%g, mcut=%g, ComputeV=%d, GasDisk=%s, SigRGas=%g, SigThetaGas=%g, SigZGas=%g, TruncationMethod=%s, Add_BHParticle=%r, FirstRealisedPart=%r, nMaxPart=%r, overwrite=%r)\\n\"%(self.Rcut, self.Zcut, self.mcut, ComputeV, GasDisk, self.SigRGas, self.SigThetaGas, self.SigZGas, self.TruncationMethod, self.Add_BHParticle, self.FirstRealisedPart, self.nMaxPart, self.overwrite)\n fout = open(self.saveMGE + \"/\" + \"%s\"%(str(self.RealisationTime)) + \".MGE_CI\", \"w+\")\n fout.write(text)\n fout.close()\n #-------------------------------------------------#\n\n ## Get all parameters right and the number of particles too\n self._comp_Nparticles()\n\n #==============================================================================================================\n ## End of parameter initialisation\n #==============================================================================================================\n ## Beginning of allocation\n #==============================================================================================================\n\n self.R = np.zeros(self.nRealisedPart, floatMGE)\n self.theta = np.zeros(self.nRealisedPart, floatMGE)\n self.z = np.zeros(self.nRealisedPart, floatMGE) ## in Parsec\n self.x = np.zeros(self.nRealisedPart, floatMGE) ## in Parsec\n self.y = np.zeros(self.nRealisedPart, floatMGE) ## in Parsec\n self.BodGroup = np.zeros(self.nRealisedPart, int)\n self.BodGauss = np.zeros(self.nRealisedPart, int)\n self.BodMass = np.zeros(self.nRealisedPart, floatMGE)\n ## Add the mass of the particle at 0,0,0 0,0,0 (last particle)\n if self.nRealisedPartBH == 1 :\n self.BodMass[-1] = self.Mbh\n\n ## Allocation for particles dynamics ############################\n self.NSpin = np.ones(self.nRealisedPart, floatMGE)\n self.NkRTheta = np.zeros(self.nRealisedPart, floatMGE)\n self.NkRZ = np.zeros(self.nRealisedPart, floatMGE)\n\n # Now: how do we derive sigma_R or sigma_Theta\n if self.epicycle.any() : ## Theta will be derived from sigma_R with the epicycle approximation\n R = np.linspace(0., Xcut, 1000) ## Derive a range of R in parsec\n epiratio = self.EpicycleRatio(R / self.pc_per_arcsec) # R is passed in arcsec\n # Function to have from R in pc, sigma_R / sigma_Theta from the epicycle approximation\n funcEpiratio = interpolate.interp1d(R, epiratio)\n\n ## Now we implement (if betaeps=1) the relation beta = 0.6 * eps\n ## Only if specified\n if 'FacBetaEps' in kwargs :\n self.FacBetaEps = kwargs.get('FacBetaEps', 0.6)\n self._init_BetaEps(verbose=True)\n\n ## Derive required values from the anisotropy kRZ2 (sig_R2/ sig_z2)\n self._dParam = dynParamMGE(self)\n\n ############### Computing POSITIONS for the N body realisation ##################\n # for each Gaussian, derive initial positions for particles\n ## Only do this if it is axisymmetric\n if self.axi == 1 :\n\n ##################################### BEGIN STARS, GAS, HALO ######################################\n self.Spin = np.ones(self.nGauss, np.int)\n for i in range(self.nGauss) :\n sigma = self.Sig3D[i]\n\n if self.TruncationMethod == \"Cylindre\" :\n self.x[self.nRealisedPartCum[i]:self.nRealisedPartCum[i+1]] = sample_trunc_gauss(sigma=sigma, cutX=self.Rcut, npoints=self.nRealisedPartGauss[i], even=1)\n self.y[self.nRealisedPartCum[i]:self.nRealisedPartCum[i+1]] = sample_trunc_gauss(sigma=sigma, cutX=self.Rcut, npoints=self.nRealisedPartGauss[i], even=1)\n sigma = self.Sig3D[i]*self.QxZ[i]\n self.z[self.nRealisedPartCum[i]:self.nRealisedPartCum[i+1]] = sample_trunc_gauss(sigma=sigma, cutX=self.Zcut, npoints=self.nRealisedPartGauss[i], even=1)\n self.theta[self.nRealisedPartCum[i]:self.nRealisedPartCum[i+1]] = asarray(np.random.uniform(0., 2.*np.pi, size=(self.nRealisedPartGauss[i],)), dtype=floatMGE)\n elif self.TruncationMethod == \"Ellipsoid\" :\n r = sample_trunc_r2gauss(sigma=sigma, cutr=self.mcut, npoints=self.nRealisedPartGauss[i])\n U = asarray(np.random.uniform(-1., 1., size=(self.nRealisedPartGauss[i],)), dtype=floatMGE)\n V = asarray(np.random.uniform(0.,1., size=(self.nRealisedPartGauss[i],)), dtype=floatMGE)\n sqU = np.sqrt(1. - U*U)\n theta = 2. * np.pi * V\n self.x[self.nRealisedPartCum[i]:self.nRealisedPartCum[i+1]] = r*sqU*cos(theta)\n self.y[self.nRealisedPartCum[i]:self.nRealisedPartCum[i+1]] = r*sqU*sin(theta)\n self.z[self.nRealisedPartCum[i]:self.nRealisedPartCum[i+1]] = r * U * self.QxZ[i]\n self.theta[self.nRealisedPartCum[i]:self.nRealisedPartCum[i+1]] = theta\n\n self.BodGauss[self.nRealisedPartCum[i]:self.nRealisedPartCum[i+1]] = i+1\n self.BodGroup[self.nRealisedPartCum[i]:self.nRealisedPartCum[i+1]] = self.GaussDynCompNumber[i]\n self.BodMass[self.nRealisedPartCum[i]:self.nRealisedPartCum[i+1]] = self.pmassGauss[i]\n\n ## We set up things so that at the end we have kRZ and kRTheta\n ## First we test if one of the set up variable is negative, which means that we should inverse the Spin\n if (self.kRTheta[i] < 0) :\n self.kRTheta[i] = np.abs(self.kRTheta[i])\n self.Spin[i] = -1\n self.NSpin[self.nRealisedPartCum[i]:self.nRealisedPartCum[i+1]] = - np.ones(self.nRealisedPartGauss[i], dtype=floatMGE)\n\n self.NkRZ[self.nRealisedPartCum[i]:self.nRealisedPartCum[i+1]] = np.zeros(self.nRealisedPartGauss[i], dtype=floatMGE) + self.kRZ[i]\n if self.epicycle[i] :\n self.NkRTheta[self.nRealisedPartCum[i]:self.nRealisedPartCum[i+1]] = funcEpiratio(self.R[self.nRealisedPartCum[i]:self.nRealisedPartCum[i+1]])\n else :\n self.NkRTheta[self.nRealisedPartCum[i]:self.nRealisedPartCum[i+1]] = np.zeros(self.nRealisedPartGauss[i], dtype=floatMGE) + self.kRTheta[i]\n\n print(\"NStar = %d particles Realised over a total of %d\" %(self.nRealisedPartStar, self.nPartStar))\n print(\"NGas = %d particles Realised over a total of %d\" %(self.nRealisedPartGas, self.nPartGas))\n print(\"NHalo = %d particles Realised over a total of %d\" %(self.nRealisedPartHalo, self.nPartHalo))\n if self.nRealisedPartBH == 1:\n print(\"Adding a BH particle of %e Msun\" %(self.Mbh))\n firstStar = 0 # index for the first Star particle\n firstGas = lastStar = self.nRealisedPartStar # index for the first Gas particle - last Star particle\n firstHalo = lastGas = firstGas + self.nRealisedPartGas # index for the first Halo particle - last Gas particle\n firstBH = lastHalo = firstHalo + self.nRealisedPartHalo # index for the BH particle - last Halo particle\n ##################################### END STARS, GAS, HALO ######################################\n\n ## Computing some important quantities : R, r, theta, xarc etc ------------------------- ##\n self.R = sqrt(self.x**2 + self.y**2)\n ## And r spherical\n self.r = sqrt(self.x**2 + self.y**2+self.z**2)\n\n ## Now computing the true theta\n self.theta[(self.x == 0.) & (self.y >= 0.)] = np.pi / 2.\n self.theta[(self.x == 0.) & (self.y < 0.)] = -np.pi / 2.\n self.theta[(self.x < 0.)] = arctan(self.y[(self.x < 0.)] / self.x[(self.x < 0.)]) + np.pi\n self.theta[(self.x > 0.)] = arctan(self.y[(self.x > 0.)] / self.x[(self.x > 0.)])\n\n ### Transforming in arcsecond\n self.xarc = self.x / self.pc_per_arcsec ### Normalisation using the distance of the galaxy\n self.yarc = self.y / self.pc_per_arcsec ### Normalisation using the distance of the galaxy\n self.zarc = self.z / self.pc_per_arcsec ### Normalisation using the distance of the galaxy\n self.Rarc = self.R / self.pc_per_arcsec ### Normalisation using the distance of the galaxy\n self.rarc = self.r / self.pc_per_arcsec ### Normalisation using the distance of the galaxy\n\n R2 = (self.Rarc)**2 ## R in arcsec\n Z2 = (self.zarc)**2 ## z in arcsec\n\n ############### Computing velocities for the N body realisation ##################\n if ComputeV :\n ### Integration using gaussian quadrature ###\n ### First compute the gaussian quadrature points, and weights\n print(\"Starting the derivation of velocities\")\n self.muTheta2 = np.zeros(self.nRealisedPart, floatMGE)\n self.sigz = np.zeros(self.nRealisedPart, floatMGE)\n self.sigR = np.zeros(self.nRealisedPart, floatMGE)\n self.sigT = np.zeros(self.nRealisedPart, floatMGE)\n self.vt = np.zeros(self.nRealisedPart, floatMGE)\n if verbose :\n print(\"End of memory alloc\")\n\n##### OPTION REMOVE if self.GLOBAL_Sigma == False :\n ## Doing it in Dynamical groups #################################\n if verbose :\n print(\"STARTING Local Sigma for each Dynamical Group\")\n ## First check that Dynamical Groups are ordered\n setGauss_Stars = list(range(self.nStarGauss))\n setGauss_Halo = list(range(self.nStarGauss + self.nGasGauss, self.nGauss))\n setGauss = np.concatenate((setGauss_Stars, setGauss_Halo))\n nRealisedPart = self.nRealisedPartStar + self.nRealisedPartHalo\n ## First derive the equations for each INDIVIDUAL DYNAMICAL GROUP for SIGMA_Z\n if nRealisedPart != 0 :\n for i in range(self.nDynComp) :\n iminG = np.min(self.listGaussDynComp[i])\n imaxG = np.max(self.listGaussDynComp[i])\n if (iminG >= self.nStarGauss) & (imaxG < self.nStarGauss+self.nGasGauss) & GasDisk:\n continue\n for j in range(iminG+1, imaxG) :\n if j not in self.listGaussDynComp[i] :\n print(\"ERROR: Dynamical Group %d should included ordered Gaussians\"%(i+1))\n print(\"ERROR: Dynamical Group %d is \"%(i+1),self.listGaussDynComp[i])\n return\n\n startI, endI = self.nRealisedPartCum[iminG], self.nRealisedPartCum[imaxG+1]\n if endI <= startI :\n continue\n R2comp = R2[startI: endI]\n Z2comp = Z2[startI: endI]\n self.rho, self.rhoT = self._MassDensity(R2comp, Z2comp, ilist=list(range(iminG,imaxG+1)))\n self.rhoT = np.where(self.rhoT > 0., self.rhoT, 1.0)\n temp1, temp2 = self._sigmaz2_muTheta2_fromR2Z2(R2comp, Z2comp, ilist=list(range(iminG,imaxG+1)))\n self.sigz[startI: endI] = sqrt(temp1)\n self.muTheta2[startI: endI] = temp2\n if verbose :\n print(\"End of sigz2 and mu2 derivation for Dynamical Group %02d\"%(i+1))\n\n##### REMOVING THIS OPTION - NOT REQUIRED CONSIDERING THE INPUT ASCII FILE WITH DYN GROUPS ###### else :\n#### OPTION REMOVED ###### if verbose :\n#### OPTION REMOVED ###### print \"STARTING GLOBAL Sigma for All Stars and then Halo\"\n#### OPTION REMOVED ###### ## STARS ####################\n#### OPTION REMOVED ###### R2Star = R2[firstStar:lastStar]\n#### OPTION REMOVED ###### Z2Star = Z2[firstStar:lastStar]\n#### OPTION REMOVED\n#### OPTION REMOVED ###### imin = 0\n#### OPTION REMOVED ###### imax = self.nStarGauss-1 # Include all Gaussians, including Halo ones\n#### OPTION REMOVED ###### self.rho, self.rhoT = self._MassDensity(R2Star, Z2Star, imin=imin, imax=imax)\n#### OPTION REMOVED\n#### OPTION REMOVED ###### ## Compute both sigmaz2 and mu2 for the Stars\n#### OPTION REMOVED ###### temp1, temp2 = self.sigmaz2_mut2(R2Star, Z2Star, imin=imin, imax=imax)\n#### OPTION REMOVED ###### self.sigz2[firstStar:lastStar] = temp1\n#### OPTION REMOVED ###### self.mut2[firstStar:lastStar] = temp2\n#### OPTION REMOVED ###### if verbose :\n#### OPTION REMOVED ###### print \"End of sigz2 and mu2 derivation for Stars\"\n#### OPTION REMOVED\n#### OPTION REMOVED ###### ## HALO ####################\n#### OPTION REMOVED ###### R2Halo = R2[firstHalo:lastHalo]\n#### OPTION REMOVED ###### Z2Halo = Z2[firstHalo:lastHalo]\n#### OPTION REMOVED\n#### OPTION REMOVED ###### imin = self.nStarGauss + self.nGasGauss\n#### OPTION REMOVED ###### imax = self.nGauss-1 # Include all Gaussians, including Halo ones\n#### OPTION REMOVED ###### self.rho, self.rhoT = self._MassDensity(R2Halo, Z2Halo, imin=imin, imax=imax)\n#### OPTION REMOVED ###### self.rhoT = np.where(self.rhoT > 0., self.rhoT, 1.0)\n#### OPTION REMOVED\n#### OPTION REMOVED ###### ## Compute both sigmaz2 and mu2 for the Halos\n#### OPTION REMOVED ###### temp1, temp2 = self.sigmaz2_mut2(R2Halo, Z2Halo, imin=imin, imax=imax)\n#### OPTION REMOVED ###### self.sigz2[firstHalo:lastHalo] = temp1\n#### OPTION REMOVED ###### self.mut2[firstHalo:lastHalo] = temp2\n#### OPTION REMOVED ###### if verbose :\n#### OPTION REMOVED ###### print \"End of sigz2 and mu2 derivation for Halo\"\n\n ## Using only kRZ and kRTheta\n sigR = self.sigz * self.NkRZ\n sigTheta = np.minimum(sqrt(self.muTheta2), sigR / self.NkRTheta) # sigma Theta from sigma R\n vt = sqrt(np.clip(self.muTheta2 - sigTheta**2, 0., np.inf))\n self.sigR[firstStar:lastStar] = sigR[firstStar:lastStar] # sigma R from sigma Z\n self.sigR[firstHalo:lastHalo] = sigR[firstHalo:lastHalo] # sigma R from sigma Z\n self.sigT[firstStar:lastStar] = sigTheta[firstStar:lastStar] # sigma Theta from sigma R\n self.sigT[firstHalo:lastHalo] = sigTheta[firstHalo:lastHalo] # sigma Theta from sigma R\n # Mean V theta\n self.vt[firstStar:lastStar] = vt[firstStar:lastStar]\n self.vt[firstHalo:lastHalo] = vt[firstHalo:lastHalo]\n if not GasDisk :\n self.sigR[firstGas:lastGas] = sigR[firstGas:lastGas] # sigma R from sigma Z\n self.sigT[firstGas:lastGas] = sigTheta[firstGas:lastGas] # sigma Theta from sigma R\n self.vt[firstGas:lastGas] = vt[firstGas:lastGas]\n if verbose :\n if GasDisk :\n print(\"End of sigz2 and mu2 derivation for All Stars and Halo particles\")\n else :\n print(\"End of sigz2 and mu2 derivation for All Stars, Gas and Halo particles\")\n\n ## GAS ######################\n if opGAS & GasDisk:\n self.vt[firstGas:lastGas] = self.Vcirc(self.Rarc[firstGas:lastGas])\n self.muTheta2[firstGas:lastGas] = self.vt[firstGas:lastGas]**2 + self.SigThetaGas**2\n temp = np.zeros_like(self.sigR[firstGas:lastGas])\n self.sigR[firstGas:lastGas] = temp + self.SigRGas # sigma R for the Gas\n self.sigT[firstGas:lastGas] = temp + self.SigThetaGas # sigma Theta for the Gas\n self.sigz[firstGas:lastGas] = temp + self.SigZGas # sigma Z for the Gas\n if verbose :\n print(\"End of sigz2 and mu2 derivation for Gas\")\n\n ## Changing the spin of the component\n self.vt *= self.NSpin\n\n ## Starting the randomization of velocities using the derived V and Sigma values\n print(\"Randomizing the Velocities\")\n Vescape = self.Vescape(self.Rarc,self.zarc) # Vescape : cut it if the total velocity is higher\n Nrejected = 0\n Nstart = 0\n Nremain = self.nRealisedPart\n ind = list(range(self.nRealisedPart))\n self.Vz = np.zeros(self.nRealisedPart, floatMGE)\n self.VR = np.zeros(self.nRealisedPart, floatMGE)\n self.Vtheta = np.zeros(self.nRealisedPart, floatMGE)\n self.Vtot = np.zeros(self.nRealisedPart, floatMGE)\n iter = 0\n while Nremain != 0 :\n ### Randomize the positions taking into account the 3D width of the Gaussian\n self.Vz[ind] = asarray(np.random.normal(0., 1., Nremain), dtype=floatMGE) * self.sigz[ind]\n self.VR[ind] = asarray(np.random.normal(0., 1., Nremain), dtype=floatMGE) * self.sigR[ind]\n self.Vtheta[ind] = asarray(np.random.normal(0., 1., Nremain), dtype=floatMGE) * self.sigT[ind] + self.vt[ind]\n\n self.Vtot[ind] = sqrt(self.Vz[ind]**2 + self.VR[ind]**2 + self.Vtheta[ind]**2)\n\n ind = np.ravel(np.where(self.Vtot[ind] > Vescape[ind])) # indices which are NOT ok with Vesc\n nrealised = Nremain - ind.size\n Nstart = Nstart+nrealised\n Nremain = ind.size\n iter += 1\n print(\"NtotalV = %d, Nrealised = %d, Nremaining = %d, Iter = %d\" %(Nstart, nrealised, Nremain, iter))\n Nrejected += Nremain\n\n print(\"Rejected (recalculated) points above Vescape: %d\" %(Nrejected))\n\n self.Vx = self.VR * cos(self.theta) - self.Vtheta * sin(self.theta)\n self.Vy = self.VR * sin(self.theta) + self.Vtheta * cos(self.theta)\n\n return\n\n############################################################################################################\n####################################### END OF NBODY REALIZATION ###########################################\n############################################################################################################\n\n def comp_Pot(self) :\n self.EcPot = self.Pot(self.Rarc, self.zarc)\n self.EcPotT = np.sum(self.EcPot)\n return\n\n def comp_Ep(self) :\n print(\"==== Potential Energy ====\")\n print(\"WARNING: this is a direct computation of the potential energy: can be time consuming!\")\n self.Ep = np.zeros(self.nRealisedPart, floatMGE)\n for i in range(self.nRealisedPart) :\n Ep = np.sum(concatenate((1./sqrt((self.x[:i] - self.x[i])**2 + (self.y[:i] - self.y[i])**2 + (self.z[:i] - self.z[i])**2), 1./sqrt((self.x[i+1:] - self.x[i])**2 + (self.y[i+1:] - self.y[i])**2 + (self.z[i+1:] - self.z[i])**2))),axis=0)\n self.Ep[i] = - Ep * self.Gorig * self.BodMass**2\n\n self.EpT = np.sum(self.Ep,axis=0) / 2.\n return\n\n def comp_Ec(self) :\n print(\"==== Kinetic Energy ====\")\n self.Ec = 0.5 * self.BodMass * (self.Vx**2 + self.Vy**2 + self.Vz**2)\n self.EcT = np.sum(self.Ec,axis=0)\n return\n\n ################## Projection of the MGE model ################\n def projpart(self, inclin=90.) :\n \"\"\" Projection of an MGE realization (N particles) using a defined inclination\n inclin: inclination in degrees, 90 being edge-on, 0 being face-on\n \"\"\"\n\n inclin_rad = inclin * np.pi / 180.\n self.Xp = self.x\n self.Yp = self.y * cos(inclin_rad) + self.z * sin(inclin_rad)\n self.Zp = - self.y * sin(inclin_rad) + self.z * cos(inclin_rad)\n self.Xparc = self.Xp / self.pc_per_arcsec\n self.Yparc = self.Yp / self.pc_per_arcsec\n self.Zparc = self.Zp / self.pc_per_arcsec\n\n self.Vrad = self.Vy * sin(inclin_rad) - self.Vz * cos(inclin_rad)\n\n return\n #===================================================================\n\n ##################################################################\n ### Save the Nbody coordinates x,y,z,Vx,Vy,Vz in an ascii file #\n ##################################################################\n def save_nbody(self, outdir=None, outfilename=None, overwrite=False, arcsec=False) :\n \"\"\" Save the N body realizationof an MGE model into an ascii file\n name : string defining the name of the output file\n overwrite: if file exists, overwrite or not - default = False\n arcsec: save the positions in arcseconds or pc - default= False (pc)\n \"\"\"\n if outfilename is None :\n print(\"You must specify an output ascii file\")\n return\n\n if outdir is not None :\n outfilename = outdir + outfilename\n\n if os.path.isfile(outfilename) and overwrite==False : # testing the existence of the file\n print('WRITING ERROR: File %s already exists, use overwrite=True if you wish' %outfilename)\n return\n\n ascii_file = open(outfilename, mode=\"w\")\n\n if arcsec == True :\n outx = self.xarc\n outy = self.yarc\n outz = self.zarc\n else :\n outx = self.x\n outy = self.y\n outz = self.z\n\n for i in range(self.nRealisedPart) :\n line = \"%12.5e %12.5e %12.5e %12.5e %12.5e %12.5e %12.5e \\n\" %(outx[i], outy[i], outz[i], self.Vx[i], self.Vy[i], self.Vz[i], self.BodMass[i])\n ascii_file.write(line)\n\n ascii_file.close\n return\n #===================================================================\n","sub_path":"pygme/init_partMGE.py","file_name":"init_partMGE.py","file_ext":"py","file_size_in_byte":30045,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"213947405","text":"#!/usr/bin/env python\n# encoding=utf8\n#########################################################################\n# Author:\n# Created Time: Thu 08 Nov 2018 08:48:39 PM CST\n# File Name: convert.py\n# Description: tensor pil cv numpy\n#########################################################################\n\nimport cv2\nimport numpy as np\nimport PIL\nimport torch\nfrom torchvision import transforms\n\n# tensor [C, H, W] 取值范围是[0, 1.0] 一般经过normalization\n# pil [H,W,C] 取值范围是[0,255] RGB\n# cv [H,W,C] 取值范围是[0,255] GBR\n\n# pil to numpy\n# np_obj = np.array( pil_obj )\n\n# numpy to pil i\n# pil_obj = PIL.Image.fromarray( np_obj ).convert('RGB')\n\n# tensor => numpy\n# np_obj = tensor.numpy()\n\n# numpy => tensor\n# tensor = torch.Tensor(np_obj)\n\n# pil to cv\n# cv_obj = np.array(pil_img)[:, :, ::-1].copy()\n\n# cv to pil\n# pil_obj = PIL.Image.fromarray(cv_obj.astype('uint8')[:, :, ::-1], mode='RGB')\n\n# tensor to pil\n# pil_img = transforms.ToPILImage()(tensor_obj).convert(\"RGB\")\n# = transpose + *255\n\ndef tensor_to_pil(tensor_img, MEAN=[], STD=[]):\n if MEAN and STD:\n np_img = tensor_img.numpy()\n for i in range(0, 3):\n np_img[i] = np_img[i] * STD[i] + MEAN[i] # unnormalize\n pil_img = transforms.ToPILImage()(torch.from_numpy(np_img)).convert(\"RGB\")\n else:\n pil_img = transforms.ToPILImage()(tensor_img).convert(\"RGB\")\n return pil_img\n\ndef tensor_to_cv(tensor_img, MEAN=[], STD=[]):\n pil_img = tensor_to_pil(tensor_img, MEAN, STD)\n cv_img = np.array(pil_img)[:, :, ::-1].copy()\n return cv_img\n\n\nif __name__ == '__main__':\n\n MEAN = [0.485, 0.456, 0.406]\n STD = [0.229, 0.224, 0.225]\n img_transform = transforms.Compose([transforms.Resize((224, 224)), transforms.ToTensor(), transforms.Normalize(MEAN, STD)])\n pil_img = PIL.Image.open(\"color.jpg\").convert(\"RGB\")\n\n # pil to tensor\n tensor_img = img_transform(pil_img)\n\n pil_img = tensor_to_pil(tensor_img, MEAN, STD)\n pil_img.save(\"pil.jpg\")\n cv_img = np.array(pil_img)[:, :, ::-1].copy()\n cv2.imwrite(\"cv.jpg\", cv_img)\n","sub_path":"mmcv/image/convert.py","file_name":"convert.py","file_ext":"py","file_size_in_byte":2079,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"89568133","text":"from django.contrib.auth.hashers import check_password\nfrom rest_framework import viewsets, status, mixins\nfrom rest_framework.decorators import action\nfrom rest_framework.response import Response\nfrom rest_framework.utils import json\nfrom django.forms.models import model_to_dict\nfrom django.db.models import ObjectDoesNotExist\nimport logging\nfrom ServeUp.Views.helper import *\n\nclass NarociloViewSet(viewsets.ModelViewSet):\n \"\"\"\n ViewSet provides 'list', 'create', 'retrieve', 'update' and 'destroy' actions\n\n Additional actions can be added using '@action()' decorator, default response\n is GET, you can add POST using 'methods' argument\n \"\"\"\n queryset = Narocilo.objects.all()\n serializer_class = NarociloSerializer\n\n def list(self, request, *args, **kwargs):\n \"\"\"\n Returns all orders for restaurant with specified id in GET parameter 'id_restavracija'.\n\n ORDER_NEW = 0 # \"Nova Naročila\"\n ORDER_PREPARING = 1 # \"V Pripravi\"\n ORDER_DONE = 2 # \"Pripravljeno\"\n ORDER_FINISHED = 3 # \"Končano\"\n \"\"\"\n get_params = request.query_params\n response = {}\n return_data = {}\n\n try:\n id_restavracija = get_params['id_restavracija']\n except KeyError:\n response['status'] = 0\n response['description'] = \"Missing id, add ?id_restavracija=x to call\"\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n\n data = JediNarocilaPodatki.objects.filter(id_restavracija=id_restavracija,\n status__in=[ORDER_NEW, ORDER_DONE, ORDER_PREPARING, ORDER_FINISHED])\n data = JediNarocilaPodatkiSerializer(data, many=True).data\n\n for order in data:\n id_narocila = order['id_narocila']\n if id_narocila not in return_data:\n return_data[id_narocila] = {\n 'cas_prevzema': order['cas_prevzema'],\n 'cas_narocila': order['cas_narocila'],\n 'id_restavracija': order['id_restavracija'],\n 'id_uporabnik': order['id_uporabnik'],\n 'cena': 0,\n 'id_narocila': order['id_narocila'],\n 'status': order['status'],\n 'checked_in': order['checked_in'],\n 'id_miza': order['id_miza'],\n 'jedi': []\n }\n\n return_data[id_narocila]['jedi'].append({\n 'id_jed': order['id_jed'],\n 'ime_jedi': order['ime_jedi'],\n 'kolicina': order['kolicina'],\n 'cena': order['cena']\n })\n return_data[id_narocila]['cena'] += order['cena']\n\n response['status'] = 1\n response['data'] = list(return_data.values())\n return Response(response, status=status.HTTP_200_OK)\n\n @action(detail=False, methods=['GET'])\n def refresh(self, request):\n \"\"\"\n Returns new and cancelled orders for a restaurant\n GET params:\n id_restavracija: id of the restaurant to refresh orders\n \"\"\"\n get_params = request.query_params\n response = {}\n\n try:\n id_restavracija = get_params['id_restavracija']\n except KeyError:\n response['status'] = 0\n response['description'] = \"Missing id, add ?id_restavracija=x to call\"\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n\n new, cancelled, checked_in = get_new_cancelled_checked_in_orders(int(id_restavracija))\n response['status'] = 1\n response['new_orders'] = new\n response['cancelled_orders'] = cancelled\n response['checked_in_orders'] = checked_in\n return Response(response, status=status.HTTP_200_OK)\n\n @action(detail=False, methods=['POST'])\n def cancel_order(self, request):\n \"\"\"\n Receive order id and delete that order from the database effectively cancelling it.\n Add the order id to the cancelled orders list\n Return conformation of action or error.\n \"\"\"\n response = {}\n data = json.load(request)\n try:\n order_id = data['id_narocilo']\n except KeyError as e:\n response['status'] = 0\n response['description'] = \"Missing key data \" + str(e) + \"\"\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n\n # noinspection PyBroadException\n try:\n narocilo = Narocilo.objects.get(id_narocila=order_id)\n order = {'id_narocila': narocilo.id_narocila, 'id_restavracija': narocilo.id_restavracija.id_restavracija}\n narocilo.delete()\n add_cancelled_order(order)\n response['status'] = 1\n response['description'] = \"Successfully deleted order\"\n return Response(response, status=status.HTTP_200_OK)\n except Exception:\n response['status'] = 0\n response['description'] = \"Could not delete order {}\".format(order_id)\n return Response(response, status=status.HTTP_503_SERVICE_UNAVAILABLE)\n\n @action(detail=False, methods=['POST'])\n def new_order(self, request):\n \"\"\"\n The function receives JSON data with the details of a new order and stores it.\n Return values\n status: 0 - Error, 1 - Successfully added\n description: Short description of Error or confirm desired action\n \"\"\"\n response = {}\n data = json.load(request)\n\n try:\n order = {\n \"cas_prevzema\": data['cas_prevzema'],\n \"cas_narocila\": data['cas_narocila'],\n \"id_restavracija\": data['id_restavracija'],\n \"id_uporabnik\": data['id_uporabnik'],\n \"status\": ORDER_NEW,\n \"checked_in\": False\n }\n meals = data['jedi']\n except KeyError as e:\n response['status'] = 0\n response['description'] = \"Missing key data \" + str(e) + \"\"\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n\n if len(meals) == 0: # If there are no meals in order wrong formatting\n response['status'] = 0\n response['description'] = \"No meal data\"\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n\n serializer = NarociloSerializer(data=order)\n if serializer.is_valid():\n narocilo = serializer.save()\n id_narocila = narocilo.id_narocila\n\n success, price = add_meals_to_order(meals, id_narocila)\n if not success: # Something went wrong delete order\n narocilo.delete()\n response['status'] = 0\n response['description'] = \"Could not insert meals\"\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n\n order['cena'] = price\n order['id_narocila'] = id_narocila\n order['jedi'] = meals\n add_new_order(order)\n response['status'] = 1\n response['description'] = \"New order created\"\n return Response(response, status=status.HTTP_201_CREATED)\n else:\n response['status'] = 0\n response['description'] = \"Could not add new order\"\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n\n @action(detail=False, methods=['POST'])\n def status_update(self, request):\n response = {'status': \"\",\n 'description': \"\"}\n order = Narocilo.objects.get(id_narocila=request.data['id_narocilo'])\n data = model_to_dict(order)\n data[\"status\"] = request.data[\"status\"]\n\n if not 0 <= request.data[\"status\"] <= 3:\n response['status'] = 0\n response['description'] = \"Invalid status value\"\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n\n serializer = NarociloSerializer(data=data, instance=order)\n if serializer.is_valid():\n serializer.save()\n response['status'] = 1\n response['description'] = \"Successfully changed status\"\n return Response(response, status=status.HTTP_200_OK)\n else:\n response['status'] = 0\n response['description'] = serializer.errors\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n\n\nclass RestavracijaViewSet(viewsets.ModelViewSet):\n \"\"\"\n ViewSet provides 'list', 'create', 'retrieve', 'update' and 'destroy' actions\n\n Additional actions can be added using '@action()' decorator, default response\n is GET, you can add POST using 'methods' argument\n \"\"\"\n queryset = Restavracija.objects.all()\n serializer_class = RestavracijaSerializer\n\n @action(detail=False, methods=['POST'])\n def home(self, request):\n \"\"\"\n The function receives JSON data with the name of a city.\n Return all restaurants in given city.\n Return values\n status: 0 - Error\n description: Short description of Error or confirm desired action\n\n If valid input return only array of restaurants, request by Urban.\n \"\"\"\n response = {}\n try:\n location = request.data['location']\n except KeyError:\n location = None\n\n if location is None:\n response['status'] = 0\n response['description'] = \"Error: Please input the location\"\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n else:\n response = get_restaurants(location)\n return Response(response, status=status.HTTP_200_OK)\n\n @action(detail=False, methods=['POST'])\n def register(self, request):\n \"\"\"\n The function receives a JSON data with the admin email, restaurant name,\n restaurant type, address and rating\n Return values\n status: 0 - Error, 1 - OK\n description: Short description of Error or confirm desired action\n additional actions: Set of actions that also had to be performed, in ex. updating address table\n \"\"\"\n response = {'status': \"\",\n 'description': \"\",\n 'additional actions': \"\"}\n\n # Get admin id\n id_admin = AdminUporabnik.objects.get(email=request.data['email']).id\n\n # Deal with address id\n requested_data = request.data['naslov'].split(', ')\n address = requested_data[0].split(' ')\n post = requested_data[1].split(' ')\n\n try:\n id_address = Naslov.objects.get(ulica=\" \".join(address[:-1]), hisna_stevilka=address[-1]).id_naslov\n except Naslov.DoesNotExist:\n naslov_data = {'ulica': \" \".join(address[:-1]),\n 'hisna_stevilka': address[-1],\n 'postna_stevilka': post[0]}\n\n # Add post to Posta table, if it doesn't exist\n try:\n Posta.objects.get(postna_stevilka=post[0])\n except Posta.DoesNotExist:\n posta_data = {'postna_stevilka': post[0], 'kraj': post[1]}\n serializer_posta = PostaSerializer(data=posta_data)\n if serializer_posta.is_valid():\n serializer_posta.save()\n response['additional actions'] += \"\\nUpdated Posta table\"\n else:\n response['status'] = 0\n response['description'] = serializer_posta.errors\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n\n # Add address to Naslov table, if it doesn't exist\n serializer_naslov = NaslovSerializer(data=naslov_data)\n if serializer_naslov.is_valid():\n serializer_naslov.save()\n response['additional actions'] += \"\\nUpdated Address table\"\n else:\n response['status'] = 0\n response['description'] = serializer_naslov.errors\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n id_address = Naslov.objects.get(ulica=\" \".join(address[:-1]), hisna_stevilka=address[-1]).id_naslov\n\n # Build JSON object\n data = {'id_admin': id_admin,\n 'ime_restavracije': request.data['ime_restavracije'],\n 'id_tip_restavracije': request.data['id_tip_restavracije'],\n 'id_naslov': id_address, 'ocena': request.data['ocena']}\n\n serializer = RestavracijaSerializer(data=data)\n if serializer.is_valid():\n serializer.save()\n response['status'] = 1\n response['description'] = \"Restaurant added to admin\"\n return Response(response, status=status.HTTP_201_CREATED)\n else:\n response['status'] = 0\n response['description'] = serializer.errors\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n\n @action(detail=False, methods=['GET'])\n def fetch_qr(self, request):\n \"\"\"\n Function receives id_restavracija parameter\n Returns all QR codes for a given id_restavracija\n Return values:\n status: 0 || 1\n data: JSON array with QR codes\n \"\"\"\n\n get_params = request.query_params\n response = {}\n return_data = []\n\n try:\n id_restavracija = get_params['id_restavracija']\n except KeyError:\n response['status'] = 0\n response['description'] = \"Missing id, add ?id_restavracija=x to call\"\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n\n data = Mize.objects.filter(id_restavracija=id_restavracija)\n data = MizeSerializer(data, many=True).data\n\n for obj in data:\n id_miza = obj['id_miza']\n if id_miza not in return_data:\n return_data.append(id_miza)\n\n response['status'] = 1\n response['data'] = return_data\n return Response(response, status=status.HTTP_200_OK)\n\n @action(detail=False, methods=['POST'])\n def add_table(self, request):\n response = {}\n data = request.data\n\n try:\n id_restavracija = data['id_restavracija']\n qr = data['qr']\n except KeyError as e:\n response['status'] = 0\n response['description'] = \"Missing key data \" + str(e) + \"\"\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n\n if not len(qr):\n response['status'] = 0\n response['description'] = \"Missing data\"\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n\n table = {\n 'id_restavracija': id_restavracija,\n 'id_miza': qr\n }\n\n serializer = MizeSerializer(data=table)\n if serializer.is_valid():\n serializer.save()\n response['status'] = 1\n response['description'] = \"Successfully added table to restaurant\"\n return Response(response, status=status.HTTP_200_OK)\n else:\n response['status'] = 0\n response['description'] = serializer.errors\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n\n\nclass TipRestavracijeViewSet(viewsets.ModelViewSet):\n \"\"\"\n ViewSet provides 'list', 'create', 'retrieve', 'update' and 'destroy' actions\n\n Additional actions can be added using '@action()' decorator, default response\n is GET, you can add POST using 'methods' argument\n \"\"\"\n serializer_class = TipRestavracijeSerializer\n queryset = TipRestavracije.objects.all()\n model = TipRestavracije\n\n\nclass AdminUporabnikViewSet(mixins.ListModelMixin, viewsets.GenericViewSet):\n serializer_class = AdminUporabnikSerializer\n queryset = AdminUporabnik.objects.all()\n model = AdminUporabnik\n\n @action(detail=False, methods=['POST'])\n def login(self, request):\n \"\"\"\n The function receives JSON data with the email and the password. If the user exist and the password is\n correct we return the id of the restaurant the user manages, if he does not manage any restaurant returns None.\n Return values\n status: 0 - Error, 1 - OK\n description: Short description of Error or confirm desired action\n id_restavracija: If status 1, id of restaurant or None\n \"\"\"\n response = {}\n\n # First try to get the user\n try:\n user = AdminUporabnik.objects.get(email=request.data['email'])\n except AdminUporabnik.DoesNotExist:\n user = None\n\n # if user exist check password\n if user is not None:\n password = request.data['password']\n match = check_password(password, user.password)\n if not match:\n response['status'] = 0\n response['description'] = \"Password does not match\"\n return Response(response, status=status.HTTP_401_UNAUTHORIZED)\n else:\n query = Restavracija.objects.all().filter(id_admin=user.id)\n data = RestavracijaSerializer(query, many=True).data\n\n if len(data) != 0:\n id_restavracija = data[0]['id_restavracija']\n else:\n id_restavracija = None\n\n response['status'] = 1\n response['description'] = \"Username and password match\"\n response['id_restavracija'] = id_restavracija\n return Response(response, status=status.HTTP_200_OK)\n else:\n response['status'] = 0\n response['description'] = \"Username does not exist\"\n return Response(response, status=status.HTTP_401_UNAUTHORIZED)\n\n @action(detail=False, methods=['POST'])\n def register(self, request):\n \"\"\"\n The function receives JSON data with the email and the password.\n If the input data is valid it creates a new admin user.\n Return values\n status: 0 - Error, 1 - OK\n description: Short description of Error or confirm desired action\n \"\"\"\n serializer = AdminUporabnikSerializer(data=request.data)\n response = {}\n if serializer.is_valid():\n serializer.save()\n response['status'] = 1\n response['description'] = \"New user created\"\n return Response(response, status=status.HTTP_201_CREATED)\n else:\n email_error = (\"Email - \" + serializer.errors['email'][0]) if 'email' in serializer.errors else \"\"\n password_error = (\n \"Password - \" + serializer.errors['password'][0]) if 'password' in serializer.errors else \"\"\n\n response['status'] = 0\n response['description'] = \"Error: \" + email_error + password_error\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n\n\nclass UporabnikViewSet(mixins.ListModelMixin, viewsets.GenericViewSet):\n serializer_class = UporabnikSerializer\n queryset = Uporabnik.objects.all()\n model = Uporabnik\n\n @action(detail=False, methods=['POST'])\n def get_orders(self, request):\n \"\"\"\n Return all orders and meal data for given user\n \"\"\"\n response = {}\n try:\n id_uporabnik = request.data['id_uporabnik']\n except KeyError:\n id_uporabnik = None\n\n try:\n limit = int(request.data['num_orders'])\n except KeyError:\n limit = 10\n\n if id_uporabnik is None:\n response['status'] = 0\n response['description'] = \"Error: Please input the user id\"\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n else:\n response['status'] = 1\n response['description'] = \"Orders for user: \" + id_uporabnik + \"\"\n response['orders'] = get_orders(id_uporabnik, limit)\n return Response(response, status=status.HTTP_200_OK)\n\n @action(detail=False, methods=['POST'])\n def register(self, request):\n \"\"\"\n The function receives JSON data with the token of the new user.\n If the input data is valid it creates a new user.\n Return values\n status: 0 - Error, 1 - New user created, 2 - User already registered\n description: Short description of Error or confirm desired action\n \"\"\"\n try:\n user = Uporabnik.objects.get(id_uporabnik=request.data['id_uporabnik'])\n except Uporabnik.DoesNotExist:\n user = None\n\n response = {}\n if user is None:\n serializer = UporabnikSerializer(data=request.data)\n if serializer.is_valid():\n serializer.save()\n response['status'] = 1\n response['description'] = \"New user created\"\n return Response(response, status=status.HTTP_201_CREATED)\n else:\n id_error = \"ID: \" + serializer.errors['id_uporabnik'][0]\n response['status'] = 0\n response['description'] = \"Error: \" + id_error\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n else:\n response['status'] = 2\n response['description'] = \"User already registered\"\n return Response(response, status=status.HTTP_200_OK)\n\n @action(detail=False, methods=['POST'])\n def check_in(self, request):\n # TODO: Implement check in from user\n response = {}\n try:\n id_narocila = request.data['id_narocilo']\n qr = request.data['qr']\n except KeyError:\n response['status'] = 0\n response['description'] = \"Error: Missing either id_narocilo or qr\"\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n\n # noinspection PyBroadException\n try:\n order = Narocilo.objects.get(id_narocila=id_narocila)\n order_id_restaurant = order.id_restavracija\n except Exception:\n response['status'] = 0\n response['description'] = \"Could not retrieve order {}\".format(id_narocila)\n return Response(response, status=status.HTTP_503_SERVICE_UNAVAILABLE)\n\n try:\n Mize.objects.get(id_restavracija=order_id_restaurant, id_miza=qr)\n except models.ObjectDoesNotExist:\n response['status'] = 0\n response['description'] = \"Error: Restaurant ID and QR do not match for provided Order\"\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n\n data = model_to_dict(order)\n data[\"checked_in\"] = True\n data[\"id_miza\"] = qr\n\n serializer = NarociloSerializer(data=data, instance=order)\n if serializer.is_valid():\n serializer.save()\n # Add order to checked_in array to be used in refresh api call\n order_dict = {'id_narocila': order.id_narocila, 'qr': qr,\n 'id_restavracija': order.id_restavracija.id_restavracija}\n add_checked_in_order(order_dict)\n\n response['status'] = 1\n response['description'] = \"Successfully checked in order\"\n return Response(response, status=status.HTTP_200_OK)\n else:\n response['status'] = 0\n response['description'] = serializer.errors\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n\n\nclass JedViewSet(mixins.ListModelMixin, viewsets.GenericViewSet):\n serializer_class = JedSerializer\n queryset = Jed.objects.all()\n model = Jed\n\n def list(self, request, *args, **kwargs):\n return_data = defaultdict(list)\n get_params = request.query_params\n\n try:\n id_restavracija = get_params['id_restavracija']\n except KeyError:\n response = {\n 'status': 0,\n 'description': \"Missing id, add ?id_restavracija=x to call\"\n }\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n\n meal_types = JedilniList.objects.all()\n meal_types = JedilniListSerializer(meal_types, many=True).data\n meal_types = {x['id_jedilni_list']: x['vrsta'] for x in meal_types} # Transform OrderDict to dict\n\n meals = Jed.objects.filter(id_restavracija=id_restavracija)\n meals = JedSerializer(meals, many=True).data\n\n for meal in meals:\n typ = meal_types[meal['id_jedilni_list']]\n return_data[typ].append({\n 'id_jed': meal['id_jed'],\n 'ime_jedi': meal['ime_jedi'],\n 'opis_jedi': meal['opis_jedi'],\n 'cena': meal['cena'],\n 'kolicina': 1\n })\n\n return Response(return_data, status=status.HTTP_200_OK)\n\n @action(detail=False, methods=['POST'])\n def new_meal(self, request):\n \"\"\"\n Create new meal\n \"\"\"\n serializer = JedSerializer(data=request.data)\n if serializer.is_valid():\n serializer.save()\n response = {'status': 1, 'description': \"New meal created\"}\n return Response(response, status=status.HTTP_201_CREATED)\n else:\n response = {'status': 0, 'description': \"Could not create meal\"}\n return Response(response, status=status.HTTP_400_BAD_REQUEST)\n","sub_path":"ServeUp/Views/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":25251,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"580906518","text":"import requests\nfrom bs4 import BeautifulSoup\nimport re\nimport urllib.request\nimport time\nimport csv\n\n\ndef get_request_years():\n headers = {\n 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/80.0.3987.87 Safari/537.36'}\n page = requests.get(\"http://www.stats.gov.cn/tjsj/ndsj/\", headers = headers)\n\n html = BeautifulSoup(page.content, 'html.parser')\n table = html.find('table', 'ztzw_tab')\n print(table)\n links = table.findAll('a')\n years_hrefs = []\n for link in links:\n years_hrefs.append(link['href'])\n\n print(years_hrefs)\n return years_hrefs\n\n\n\n\ndef get_data_for_year(year):\n headers = {\n 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/80.0.3987.87 Safari/537.36'}\n left_link = re.sub('indexch', 'left', year)\n base_link = re.sub('indexch.htm', '', year)\n base_year = re.findall('\\d+', base_link)[0]\n year_page = requests.get(left_link, headers=headers)\n year_html = BeautifulSoup(year_page.content)\n if len(year_html.findAll('ul', {'id': 'foldinglist'})) != 0:\n folding_lists = year_html.findAll('ul', {'id': 'foldinglist'})\n else:\n folding_lists = year_html.findAll('ul', {'id': re.compile('divOne_*')})\n\n\n for folding_list in folding_lists:\n li_lists = folding_list.findAll('li')\n\n for li_list in li_lists:\n file = li_list.find(\"a\").get('href')\n name = li_list.find(\"a\").text.strip()\n name = re.sub('\\W+', '', name)\n print(file)\n\n if '.jpg' in file:\n retries = 3\n success = False\n while not success and retries >= 0:\n if retries == 0:\n raise Exception(\"cause of the problem, time out\")\n\n try:\n urllib.request.urlretrieve(base_link + file,\n 'C:\\\\Users\\\\jocel\\\\OneDrive\\\\Desktop\\\\test\\\\' + base_year + name + '.jpg')\n success = True\n except Exception as e:\n wait = retries * 30\n time.sleep(wait)\n retries -= 1\n print(e)\n elif '简要说明' in name:\n pass\n elif '主要统计指标解释' in name:\n pass\n elif '.htm' in file:\n retries = 3\n success = False\n while not success and retries >= 0:\n if retries == 0:\n raise Exception(\"cause of the problem, time out\")\n\n try:\n print(file)\n print(base_link)\n add = re.sub(r'\\b.htm\\b', '.xls', base_link + file)\n print(add)\n urllib.request.urlretrieve(add,\n 'C:\\\\Users\\\\jocel\\\\OneDrive\\\\Desktop\\\\test\\\\' + base_year + name + '.xls')\n\n success = True\n except Exception as e:\n wait = retries * 30\n time.sleep(wait)\n retries -= 1\n print(e)\n\n\n else:\n raise Exception(\"cause of the problem\")\n\ndef flow():\n years_hrefs = get_request_years()\n for year_href in years_hrefs:\n print(year_href)\n get_data_for_year(year_href)\n\n\n\nif __name__== \"__main__\":\n flow()\n","sub_path":"get_stat_data.py","file_name":"get_stat_data.py","file_ext":"py","file_size_in_byte":3595,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"230810907","text":"import time\r\nimport numpy as np\r\nimport transforms\r\nfrom datasets import ImageFolder#torch package\r\nimport cv2\r\nimport matplotlib.pyplot as plt\r\nimport os\r\nimport onnx\r\nimport onnxruntime\r\nimport utils.data.dataloader#torch package\r\n\r\nimport sys\r\ndef OppositePath():\r\n \"\"\"相对路径\"\"\"\r\n dirname, filename = os.path.split(os.path.abspath(sys.argv[0]))\r\n return dirname\r\n\r\nif __name__ == '__main__':\r\n class_name=['背景','港口','机场','雷达阵地','战场场景']\r\n class_name_pinyin=['background','port','airport','radar positioons','battlefield scenes']\r\n BATCH_SIZE = 1\r\n num_classes=5\r\n test_transform = transforms.Compose([\r\n transforms.Resize((224, 224)), # resize鍒?24x224澶у皬\r\n transforms.ToTensor(), # 杞寲鎴怲ensor\r\n transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) # 姝ｅ垯鍖?\r\n ])\r\n img_test=OppositePath()+'\\\\pictures'\r\n\r\n test_dataset = ImageFolder(img_test, transform=test_transform)\r\n test_dataset_original=ImageFolder(img_test)\r\n print(test_dataset_original.imgs[0][0])\r\n test_loader = utils.data.DataLoader(dataset=test_dataset, batch_size=BATCH_SIZE, shuffle=False,num_workers=2)\r\n\r\n onnx_model = onnx.load('history_best_resnet50.onnx')\r\n onnx.checker.check_model(onnx_model)\r\n ort_session = onnxruntime.InferenceSession(\"history_best_resnet50.onnx\")\r\n\r\n def to_numpy(tensor):\r\n return tensor.detach().cpu().numpy() if tensor.requires_grad else tensor.cpu().numpy()\r\n\r\n for j, (inputs, labels) in enumerate(test_loader):\r\n img_path=test_dataset_original.imgs[j][0].split('\\\\')\r\n add_path=''\r\n for i in range(len(img_path)):\r\n add_path+=img_path[i]+'\\\\\\\\'\r\n add_path=add_path[:-2]\r\n print('图片序号：', add_path)\r\n # ***************\r\n ort_inputs = {ort_session.get_inputs()[0].name: to_numpy(inputs)}\r\n outputs = ort_session.run(None, ort_inputs)[0][0]\r\n for i in range(len(outputs)):\r\n if outputs[i]==max(outputs):\r\n predictions=i\r\n else:\r\n pass\r\n print(class_name[int(predictions)])\r\n image = cv2.imdecode(np.fromfile(file=add_path, dtype=np.uint8), cv2.IMREAD_COLOR)\r\n cv2.putText(image,class_name_pinyin[int(predictions)], (40, 50), cv2.FONT_HERSHEY_PLAIN, 3.0, (0, 0, 255), 2)\r\n cv2.imshow(add_path, image)\r\n cv2.waitKey(0)\r\n\r\n\r\n\r\n\r\n\r\n","sub_path":"test1_onnx.py","file_name":"test1_onnx.py","file_ext":"py","file_size_in_byte":2465,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"505515051","text":"import os\nimport stat\nimport sys\nfrom datetime import datetime\nimport argparse\n\n# -------------------------------------------------------------------------\n''' Main Class '''\nclass ClassTemplate:\n# ------------------\n def __init__(self, args):\n os.system('cls')\n self.start_time = datetime.now().replace(microsecond=0)\n self.end_time = 0\n self.stdout_orig = sys.stdout\n self.verbose = args.verbose\n self.output = open('Output.txt', 'w')\n# ------------------\n def __del__(self):\n self.output.close()\n self.end_time = datetime.now()\n print('==========================')\n print('Finished. Duration = {0}'.format(self.end_time - self.start_time) )\n print('==========================')\n# ------------------\n def StdOutToFile(self):\n sys.stdout = open('Output.txt', 'w')\n# ------------------\n def StdOutRestore(self):\n sys.stdout = self.stdout_orig\n\n# ------------------\n def Print(self,msg, toFile=False):\n if self.verbose and (toFile == False):\n print(msg)\n else:\n self.output.write(str(msg) + '\\n')\n# ------------------\n def Run(self, path):\n print('Run')\n'''End of CodeReview class definition'''\n# -------------------------------------------------------------------------\n# -------------------------------------------------------------------------\n# MAIN program.\n# -------------------------------------------------------------------------\nif __name__ == '__main__':\n parser = argparse.ArgumentParser()\n parser.add_argument(\"-v\", \"--verbose\", \n help=\"enable verbose mode\",\n default = False,\n action=\"store_true\")\n parser.add_argument(\"-f\", \"--file\", \n type = str,\n default = 'DD DB Bubbles.xlsm',\n help=\"The excel file where the table resides\",\n )\n parser.add_argument(\"-s\", \"--sheet\", \n type = str,\n default = 'Data Range',\n help=\"The excel file worksheet name where the table resides\",\n )\n parser.add_argument(\"-c\", \"--column\", \n type = int,\n default = 0,\n help=\"The column to check for worst case matching\",\n )\n args = parser.parse_args()\n obj = ClassTemplate(args)\n obj.Run()\n","sub_path":"Template.py","file_name":"Template.py","file_ext":"py","file_size_in_byte":2500,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"586055444","text":"#!/usr/bin/python\n#\n# Scaleway volumes management module\n#\n# Copyright (C) 2018 Henryk Konsek Consulting (hekonsek@gmail.com).\n#\n# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)\n\nfrom __future__ import absolute_import, division, print_function\n\n__metaclass__ = type\n\nANSIBLE_METADATA = {\n 'metadata_version': '1.1',\n 'status': ['preview'],\n 'supported_by': 'community'\n}\n\nDOCUMENTATION = '''\n---\nmodule: scaleway_volume\nshort_description: Scaleway volumes management module\nversion_added: \"2.7\"\nauthor: Henryk Konsek (@hekonsek)\ndescription:\n - This module manages volumes on Scaleway account\n U(https://developer.scaleway.com)\nextends_documentation_fragment: scaleway\n\noptions:\n state:\n description:\n - Indicate desired state of the volume.\n default: present\n choices:\n - present\n - absent\n region:\n description:\n - Scaleway region to use (for example par1).\n required: true\n choices:\n - ams1\n - EMEA-NL-EVS\n - par1\n - EMEA-FR-PAR1\n name:\n description:\n - Name used to identify the volume.\n required: true\n organization:\n description:\n - ScaleWay organization ID to which volume belongs.\n size:\n description:\n - Size of the volume in bytes.\n volume_type:\n description:\n - Type of the volume (for example 'l_ssd').\n'''\n\nEXAMPLES = '''\n - name: Create 10GB volume\n scaleway_volume:\n name: my-volume\n state: present\n region: par1\n organization: \"{{ scw_org }}\"\n \"size\": 10000000000\n volume_type: l_ssd\n register: server_creation_check_task\n\n - name: Make sure volume deleted\n scaleway_volume:\n name: my-volume\n state: absent\n region: par1\n\n'''\n\nRETURN = '''\ndata:\n description: This is only present when C(state=present)\n returned: when C(state=present)\n type: dict\n sample: {\n \"volume\": {\n \"export_uri\": null,\n \"id\": \"c675f420-cfeb-48ff-ba2a-9d2a4dbe3fcd\",\n \"name\": \"volume-0-3\",\n \"organization\": \"000a115d-2852-4b0a-9ce8-47f1134ba95a\",\n \"server\": null,\n \"size\": 10000000000,\n \"volume_type\": \"l_ssd\"\n }\n}\n'''\n\nfrom ansible.module_utils.scaleway import SCALEWAY_LOCATION, scaleway_argument_spec, Scaleway\nfrom ansible.module_utils.basic import AnsibleModule\n\n\ndef core(module):\n state = module.params['state']\n name = module.params['name']\n organization = module.params['organization']\n size = module.params['size']\n volume_type = module.params['volume_type']\n\n account_api = Scaleway(module)\n response = account_api.get('volumes')\n status_code = response.status_code\n volumes_json = response.json\n\n if not response.ok:\n module.fail_json(msg='Error getting volume [{0}: {1}]'.format(\n status_code, response.json['message']))\n\n volumeByName = None\n for volume in volumes_json['volumes']:\n if volume['organization'] == organization and volume['name'] == name:\n volumeByName = volume\n\n if state in ('present',):\n if volumeByName is not None:\n module.exit_json(changed=False)\n\n payload = {'name': name, 'organization': organization, 'size': size, 'volume_type': volume_type}\n\n response = account_api.post('/volumes', payload)\n\n if response.ok:\n module.exit_json(changed=True, data=response.json)\n\n module.fail_json(msg='Error creating volume [{0}: {1}]'.format(\n response.status_code, response.json))\n\n elif state in ('absent',):\n if volumeByName is None:\n module.exit_json(changed=False)\n\n if module.check_mode:\n module.exit_json(changed=True)\n\n response = account_api.delete('/volumes/' + volumeByName['id'])\n if response.status_code == 204:\n module.exit_json(changed=True, data=response.json)\n\n module.fail_json(msg='Error deleting volume [{0}: {1}]'.format(\n response.status_code, response.json))\n\n\ndef main():\n argument_spec = scaleway_argument_spec()\n argument_spec.update(dict(\n state=dict(default='present', choices=['absent', 'present']),\n name=dict(required=True),\n size=dict(type='int'),\n organization=dict(),\n volume_type=dict(),\n region=dict(required=True, choices=SCALEWAY_LOCATION.keys()),\n ))\n module = AnsibleModule(\n argument_spec=argument_spec,\n supports_check_mode=True,\n )\n\n core(module)\n\n\nif __name__ == '__main__':\n main()\n","sub_path":"env/lib/python3.9/site-packages/ansible/modules/cloud/scaleway/scaleway_volume.py","file_name":"scaleway_volume.py","file_ext":"py","file_size_in_byte":4522,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"449433351","text":"# -*- coding: utf-8 -*-\n# @Time: 2020/10/20 9:11\n# @Author: Rollbear\n# @Filename: dblp_total.py\n\n\nimport tiles as t\nimport os\nfrom tqdm import tqdm # 进度条支持\n\n\ndef run_tiles_on_a_dataset(dataset, edgelist_name=None, obs=365, ttl=float('inf'), out=\"tiles_output\"):\n working_dir = f\"../dblp/datasets/frame_with_timestamp/{dataset}/\"\n if edgelist_name is None:\n edgelist_name = sorted([path for path in os.listdir(working_dir) if path.endswith(\".edgelist\")])[-1]\n data_path = working_dir + edgelist_name\n if not os.path.exists(working_dir + out):\n os.mkdir(working_dir + out)\n output_path = working_dir + out\n\n tl = t.TILES(data_path,\n path=output_path,\n obs=obs,\n ttl=ttl)\n\n print(f\"run on {data_path}\\noutput to {output_path}\")\n tl.execute() # 执行算法\n\n\nif __name__ == '__main__':\n avail_types = [\n \"phdthesis\",\n \"www\",\n \"book\",\n \"incollection\",\n \"article\",\n \"inproceedings\"\n ]\n\n for avail_type in tqdm(avail_types):\n run_tiles_on_a_dataset(avail_type,\n edgelist_name=f\"{avail_type}_sorted.edgelist\",\n obs=365,\n out=\"tiles_output_test3\")\n","sub_path":"basic/dblp_total.py","file_name":"dblp_total.py","file_ext":"py","file_size_in_byte":1286,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"434401550","text":"#encoding: utf-8\nfrom OpenOrange import *\n\nParentVoucherDoc = SuperClass(\"VoucherDoc\",\"Document\",__file__)\nclass VoucherDoc(ParentVoucherDoc):\n\n def printAditionalVoucher(self, var):\n endLine = 80\n text = var.Comment.split(\" \")\n accum = \"\"\n for i in range(len(text)):\n if len(accum + \" \") < endLine:\n accum = accum + text[i] + \" \"\n if (i+1) == len(text):\n self.addString(\"Comment2\", accum)\n else:\n self.addString(\"Comment2\", accum)\n accum = text[i] + \" \"","sub_path":"standard/documents/VoucherDoc.py","file_name":"VoucherDoc.py","file_ext":"py","file_size_in_byte":586,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"291478275","text":"def guest():\n '''保存姓名并访问'''\n while True:\n user = input('please input yor account: \\n')\n if user == 'quit':\n break\n filename = r'C:\\Users\\42582\\Desktop\\pcc-master\\Users_name.txt'\n with open(filename,'a') as file_object:\n file_object.write(user + '\\n')\n print('hello ' + user)\n\nguest()","sub_path":"05-FileAndAbnormal/guests.py","file_name":"guests.py","file_ext":"py","file_size_in_byte":360,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"154704828","text":"from NN.Basic.Networks import *\n\nfrom Util.Util import DataUtil\n\n\ndef main():\n nn = NNDist()\n save = False\n load = False\n show_loss = True\n train_only = False\n verbose = 2\n\n lr = 0.001\n lb = 0.001\n epoch = 5\n record_period = 1\n use_cnn = True\n\n x, y = DataUtil.get_dataset(\"mnist\", \"../../../_Data/mnist.txt\", quantized=True, one_hot=True)\n if use_cnn:\n x = x.reshape(len(x), 1, 28, 28)\n batch_size = 32\n else:\n batch_size = 128\n\n if not load:\n if use_cnn:\n nn.add(\"ConvReLU\", (x.shape[1:], (16, 3, 3)))\n nn.add(\"MaxPool\", ((3, 3),), 1)\n nn.add(\"ConvNorm\")\n nn.add(\"ConvDrop\")\n else:\n nn.add(\"ReLU\", (x.shape[1], 1024))\n nn.add(\"ReLU\", (1024,))\n nn.add(\"CrossEntropy\", (y.shape[1],))\n nn.optimizer = \"Adam\"\n nn.preview()\n nn.fit(x, y, lr=lr, lb=lb,\n epoch=epoch, batch_size=batch_size, record_period=record_period,\n show_loss=show_loss, train_only=train_only, do_log=True, verbose=verbose)\n if save:\n nn.save()\n nn.draw_results()\n else:\n nn.load()\n nn.preview()\n print(nn.evaluate(x, y)[0])\n\n nn.show_timing_log()\n\nif __name__ == '__main__':\n main()\n","sub_path":"MachineLearning-master/NN/Test/Basic/Test.py","file_name":"Test.py","file_ext":"py","file_size_in_byte":1307,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"121503687","text":"import os, ctypes\nfrom ._core import visual_action, _expand_path\nfrom xbot._core import try_get_sdmodule\n\n@visual_action\ndef read(**args):\n sdmodule = try_get_sdmodule()\n resources = sdmodule['resources']\n\n file_name = args['file_name']\n read_way = args['read_way']\n encoding = args['encoding']\n\n if read_way == 'text':\n return resources.get_text(file_name, encoding)\n else:\n return resources.get_bytes(file_name)\n\n@visual_action\ndef copy_to(**args):\n sdmodule = try_get_sdmodule()\n resources = sdmodule['resources']\n\n file_name = args['file_name']\n dest_file_name = args['dest_file_name']\n\n resources.copy_to(file_name, dest_file_name)\n\n@visual_action\ndef copy_to_clipboard(**args):\n sdmodule = try_get_sdmodule()\n resources = sdmodule['resources']\n\n file_name = args['file_name']\n resources.copy_to_clipboard([_expand_path(file_name)])\n\n\n\n ","sub_path":"RPA/组件/ShadowBot/3.9.9/xbot_visual/resourcesfile.py","file_name":"resourcesfile.py","file_ext":"py","file_size_in_byte":907,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"380873133","text":"#8) Să se afişeze cel mai mare număr par dintre doua numere introduse în calculator. \r\na=int(input('Primul numar este'))\r\nb=int(input('Al doilea numar este'))\r\nif (a%2==0) and (b%2==0):\r\n if a>b:\r\n print(a)\r\n else:\r\n print(b)\r\nelse:\r\n print('Numerele nu sunt pare')","sub_path":"problema_8_IF.py","file_name":"problema_8_IF.py","file_ext":"py","file_size_in_byte":292,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"252197386","text":"# Copyright 2015 IBM Corp.\n#\n# All Rights Reserved.\n#\n# 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\nimport unittest\n\nimport mock\n\nimport pypowervm.entities as ent\nimport pypowervm.tasks.cluster_ssp as cs\nimport pypowervm.tests.tasks.util as tju\nimport pypowervm.util as u\nimport pypowervm.wrappers.cluster as clust\nimport pypowervm.wrappers.job as jwrap\nimport pypowervm.wrappers.storage as stor\n\nCREATE_CLUSTER = 'cluster_create_job_template.txt'\n\n\nclass TestClusterSSP(unittest.TestCase):\n\n @mock.patch('pypowervm.wrappers.job.Job.delete_job')\n @mock.patch('pypowervm.wrappers.job.Job._monitor_job')\n @mock.patch('pypowervm.wrappers.job.Job.job_status')\n @mock.patch('pypowervm.adapter.Adapter')\n def test_crt_cluster_ssp(self, mock_adp, mock_status, mock_monitor_job,\n mock_del_job):\n # Load up GET Cluster/do/Create (job template)\n mock_adp.read.return_value = tju.load_file(CREATE_CLUSTER, mock_adp)\n # We'll pretend the job ran and completed successfully\n mock_monitor_job.return_value = False\n mock_status.__get__ = mock.Mock(\n return_value=jwrap.JobStatus.COMPLETED_OK)\n\n # Mock Job.create_job to check job parameter values\n def create_job(job_el, entry_type, *args, **kwargs):\n self.assertEqual(entry_type, clust.Cluster.schema_type)\n job = jwrap.Job.wrap(ent.Entry({}, job_el, None))\n param_vals = job._get_vals(u.xpath(\n 'JobParameters', 'JobParameter', 'ParameterValue'))\n self.assertEqual(\n param_vals[0],\n '
\",self.add_file_type)\r\n\r\n def __setup_frames(self):\r\n self.top_frame=TkinterWrapper.WindowFrame(self.window.get_window())\r\n self.bottom_frame=TkinterWrapper.WindowFrame(self.window.get_window())\r\n self.left_frame=TkinterWrapper.WindowFrame(self.top_frame.get_frame())\r\n self.right_frame=TkinterWrapper.WindowFrame(self.top_frame.get_frame())\r\n for item in [[self.top_frame,\"top\"],[self.left_frame,\"left\"],[self.right_frame,\"right\"],\r\n [self.bottom_frame,\"bottom\"]]:\r\n item[0].pack_frame(item[1],1,0)\r\n self.left_frame.configure_border(\"ridge\",2)\r\n\r\n def __setup_right_frame(self):\r\n self.file_type_listbox=TkinterWrapper.WindowListbox(self.right_frame.get_frame())\r\n self.file_type_listbox.configure_size(20,10)\r\n self.file_type_listbox.pack_listbox(\"left\",0,0)\r\n y_scrollbar=TkinterWrapper.WindowScrollbar(self.right_frame.get_frame(),\"y\")\r\n y_scrollbar.attach_to_widget(self.file_type_listbox.get_listbox())\r\n self.file_type_listbox.attach_scrollbar(\"y\",y_scrollbar.get_scrollbar())\r\n y_scrollbar.pack_scrollbar(\"left\",0,0)\r\n\r\n def __setup_left_frame(self):\r\n self.insert_explanitory_label(self.left_frame.get_frame(),\"Enter File Extension to Add:\")\r\n self.__setup_entry_frame()\r\n self.insert_explanitory_label(self.left_frame.get_frame(),\"Select a File Extension to Delete\")\r\n self.insert_button(self.left_frame.get_frame(),\"Delete\",self.delete_file_type,\"top\")\r\n self.error_frame=TkinterWrapper.WindowFrame(self.left_frame.get_frame())\r\n self.error_frame.pack_frame(\"top\",0,0)\r\n \r\n def __setup_entry_frame(self):\r\n entry_frame=TkinterWrapper.WindowFrame(self.left_frame.get_frame())\r\n entry_frame.pack_frame(\"top\",0,0)\r\n self.file_type_entry=TkinterWrapper.WindowEntry(entry_frame.get_frame())\r\n self.file_type_entry.configure_size(20)\r\n self.file_type_entry.pack_entry(\"left\",0,2)\r\n self.insert_button(entry_frame.get_frame(),\"Add\",self.add_file_type,\"left\")\r\n\r\n def __setup_bottom_frame(self):\r\n self.insert_button(self.bottom_frame.get_frame(),\"Cancel\",partial(self.window.destroy_window,False),\"left\")\r\n self.insert_button(self.bottom_frame.get_frame(),\"Save\",self.save_all_file_types_and_exit,\"left\")\r\n\r\n def insert_explanitory_label(self,frame,text):\r\n label=TkinterWrapper.WindowLabel(frame,text)\r\n label.configure_colors(\"dodgerblue2\",\"grey95\",\"times 11\")\r\n label.pack_label(\"top\",0,10)\r\n\r\n def insert_button(self,frame,button_text,button_action,side):\r\n button=TkinterWrapper.WindowButton(frame,button_text,button_action)\r\n button.pack_button(side,2,2)\r\n\r\n def add_file_type(self,*args):\r\n new_file_type=self.file_type_entry.get_entry()\r\n if len(new_file_type)>0 and new_file_type[0]==\".\" and (new_file_type not in self.file_type_list):\r\n self.file_type_list.append(new_file_type)\r\n self.append_list.append(new_file_type)\r\n self.update_listbox_text()\r\n self.file_type_entry.configure_entry_text(\"\")\r\n else:\r\n user_error=UserErrorMessage.UserErrorMessage(self.error_frame.get_frame(),\"Please enter a valid file type\")\r\n self.file_type_entry.select_range(0,\"end\")\r\n \r\n def delete_file_type(self):\r\n selection=self.file_type_listbox.get_current_selection()\r\n selection=self.file_type_listbox.get_text_from_index(selection)\r\n if selection!=None:\r\n for x in range(0,len(self.file_type_list)):\r\n if self.file_type_list[x]==selection:\r\n self.delete_list.append(self.file_type_list[x])\r\n del(self.file_type_list[x])\r\n break\r\n self.update_listbox_text()\r\n else:\r\n user_error=UserErrorMessage.UserErrorMessage(self.error_frame.get_frame(),\"Please select a file to delete\")\r\n \r\n def update_listbox_text(self):\r\n self.file_type_listbox.delete_text(0,\"end\")\r\n for item in self.file_type_list:\r\n self.file_type_listbox.insert_text(\"{0}\\n\".format(item),\"end\")\r\n\r\n def save_all_file_types_and_exit(self):\r\n for item in self.delete_list:\r\n saved_information.delete_file_type(self.edit_type,item)\r\n for item in self.append_list:\r\n saved_information.add_file_type(self.edit_type,item)\r\n self.window.destroy_window(False)\r\n\r\n \r\nclass SetDirWindow(object):\r\n def __init__(self,parent_window):\r\n self.window=TkinterWrapper.DialogBox(parent_window,\"Choose Folder\")\r\n self.directory_to_search=\"\"\r\n self.__setup_window()\r\n self.__setup_frames()\r\n self.__setup_information_frame()\r\n self.__setup_directory_frame()\r\n self.__setup_button_frame()\r\n self.window.start_mainloop()\r\n\r\n def __setup_window(self):\r\n self.window.remove_min_max_buttons(True)\r\n self.window.resizable(False,False)\r\n\r\n def __setup_frames(self):\r\n self.information_frame=TkinterWrapper.WindowFrame(self.window.get_window())\r\n self.directory_frame=TkinterWrapper.WindowFrame(self.window.get_window())\r\n self.button_frame=TkinterWrapper.WindowFrame(self.window.get_window())\r\n self.information_frame.pack_frame(\"top\",0,0)\r\n self.directory_frame.pack_frame(\"top\",0,0)\r\n self.button_frame.pack_frame(\"top\",0,0)\r\n\r\n def __setup_information_frame(self):\r\n description_label=TkinterWrapper.WindowLabel(self.information_frame.get_frame(),\"\")\r\n description_label.configure_text(\"Please chose a file to search from the list below:\")\r\n description_label.configure_colors(\"grey20\",\"grey95\",\"times 11\")\r\n description_label.pack_label(\"top\",0,5)\r\n\r\n def __setup_directory_frame(self):\r\n self.__setup_directory_entry_frame()\r\n self.__setup_directory_listbox_frame()\r\n\r\n def __setup_directory_entry_frame(self):\r\n directory_entry_frame=TkinterWrapper.WindowFrame(self.directory_frame.get_frame())\r\n directory_entry_frame.pack_frame(\"top\",0,0)\r\n current_directory_label=TkinterWrapper.WindowLabel(directory_entry_frame.get_frame(),\"Current Directory:\\n\")\r\n current_directory_label.pack_label(\"left\",0,0)\r\n current_directory_label.configure_colors(\"dodgerblue2\",\"grey95\",\"times 10\")\r\n self.current_directory_entry=TkinterWrapper.WindowEntry(directory_entry_frame.get_frame())\r\n self.current_directory_entry.configure_size(65)\r\n self.current_directory_entry.pack_entry(\"top\",0,0)\r\n x_scrollbar=TkinterWrapper.WindowScrollbar(directory_entry_frame.get_frame(),\"x\")\r\n x_scrollbar.attach_to_widget(self.current_directory_entry.get_entry_widget())\r\n self.current_directory_entry.attach_scrollbar(x_scrollbar.get_scrollbar())\r\n x_scrollbar.pack_scrollbar(\"bottom\",0,0)\r\n\r\n def __setup_directory_listbox_frame(self):\r\n directory_listbox_frame=TkinterWrapper.WindowFrame(self.directory_frame.get_frame())\r\n directory_listbox_frame.pack_frame(\"top\",0,0)\r\n self.dir_listbox=DirectoryListbox(directory_listbox_frame.get_frame(),self.current_directory_entry)\r\n\r\n def __setup_button_frame(self):\r\n self.search_button=TkinterWrapper.WindowButton(self.button_frame.get_frame(),\"Scan\",self.set_directory_and_destory_window)\r\n self.search_button.pack_button(\"top\",0,0)\r\n\r\n def set_directory_and_destory_window(self):\r\n self.directory_to_search=self.current_directory_entry.get_entry()\r\n print(\"Directory to scan: \"+self.directory_to_search)\r\n self.window.destroy_window(True)\r\n def get_saved_directory(self):\r\n return self.directory_to_search\r\n \r\n\r\n#Might have to split up into two classes: DirectoryListboxFormating and DirectoryListboxActions\r\nclass DirectoryListbox(TkinterWrapper.WindowListbox):\r\n def __init__(self,frame,companion_text_entry):\r\n self.frame=frame\r\n self.selections=[\"\",\"\"]\r\n self.current_directory_entry=companion_text_entry\r\n self.computer_directory=ComputerDirectory()\r\n self.__setup_listbox_frame()\r\n self.__setup_error_frame()\r\n self.insert_harddrives()\r\n self.start_checking_for_selection()\r\n\r\n def __setup_listbox_frame(self):\r\n self.listbox_frame=TkinterWrapper.WindowFrame(self.frame)\r\n self.listbox_frame.pack_frame(\"top\",0,0)\r\n super(DirectoryListbox, self).__init__(self.listbox_frame.get_frame())\r\n super(DirectoryListbox, self).pack_listbox(\"left\",0,0)\r\n super(DirectoryListbox, self).configure_size(80,10)\r\n self.__setup_scrollbar()\r\n def __setup_scrollbar(self):\r\n y_scrollbar=TkinterWrapper.WindowScrollbar(self.listbox_frame.get_frame(),\"y\")\r\n y_scrollbar.attach_to_widget(super(DirectoryListbox, self).get_listbox())\r\n super(DirectoryListbox, self).attach_scrollbar(\"y\",y_scrollbar.get_scrollbar())\r\n y_scrollbar.pack_scrollbar(\"left\",0,0)\r\n\r\n def __setup_error_frame(self):\r\n self.error_frame=TkinterWrapper.WindowFrame(self.frame)\r\n self.error_frame.pack_frame(\"top\",0,0)\r\n\r\n def insert_harddrives(self):\r\n super(DirectoryListbox, self).delete_text(0,\"end\")\r\n for harddrive in self.computer_directory.get_harddrives():\r\n print(harddrive)\r\n super(DirectoryListbox, self).insert_text(\"{0} {1}\\n\".format(RIGHT_TRIANGLE,harddrive),\"end\")\r\n\r\n def start_checking_for_selection(self):\r\n self.selections[0]=super(DirectoryListbox, self).get_current_selection()\r\n self.selections[0]=super(DirectoryListbox, self).get_text_from_index(self.selections[0])\r\n if self.selections[0]!=self.selections[1] and self.selections[0]!=None:\r\n print(\"Selection changed to: {0}\".format(self.selections[0]))\r\n self.selection_actions()\r\n self.selections[1]=self.selections[0]\r\n self.frame.after(250,self.start_checking_for_selection)\r\n\r\n def selection_actions(self):\r\n if RIGHT_TRIANGLE in self.selections[0]:\r\n self.go_to_subdirectory()\r\n elif LEFT_TRIANGLE in self.selections[0]:\r\n self.go_up_directory()\r\n\r\n def go_to_subdirectory(self):\r\n self.computer_directory.set_current_directory(self.get_rid_of_arrows_in_directory(self.selections[0]))\r\n subdirectories=self.computer_directory.get_sub_directories()\r\n if subdirectories!=\"ACCESS DENIED\":\r\n self.update_directory_entry()\r\n self.add_directional_information()\r\n for subdirectory in subdirectories:\r\n super(DirectoryListbox, self).insert_text(\" {0} {1}\\n\".format(RIGHT_TRIANGLE,subdirectory),\"end\")\r\n else:\r\n error_message=UserErrorMessage.UserErrorMessage(self.error_frame.get_frame(),\"Access to file was denied.\")\r\n self.go_up_directory()\r\n print(\"Access to file denied\")\r\n\r\n def add_directional_information(self):\r\n super(DirectoryListbox, self).delete_text(0,\"end\")\r\n super(DirectoryListbox, self).insert_text(\"{0} Back to {1}\\n\".format(LEFT_TRIANGLE,self.computer_directory.get_previous_directory()),\"end\")\r\n super(DirectoryListbox, self).insert_text(\"{0} {1}\\n\".format(DOWN_TRIANGLE,self.computer_directory.get_current_directory()),\"end\")\r\n\r\n def get_rid_of_arrows_in_directory(self,directory):\r\n for x in range(0,len(directory)):\r\n if (directory[x]!=RIGHT_TRIANGLE and directory[x]!=DOWN_TRIANGLE and directory[x]!=LEFT_TRIANGLE)\\\r\n and ((x!=1 or x!=2 or x!=3) and (directory[x]!=\" \")):\r\n directory=directory[x:len(directory):1]\r\n break\r\n return directory\r\n\r\n def go_up_directory(self):\r\n self.computer_directory.trim_from_current_directory(1)\r\n self.update_directory_entry()\r\n new_directories=self.computer_directory.get_sub_directories()\r\n if new_directories!=self.computer_directory.get_harddrives():\r\n self.add_directional_information()\r\n else:\r\n super(DirectoryListbox, self).delete_text(0,\"end\")\r\n for new_directory in new_directories:\r\n super(DirectoryListbox, self).insert_text(\" {0} {1}\\n\".format(RIGHT_TRIANGLE,new_directory),\"end\")\r\n\r\n def update_directory_entry(self):\r\n self.current_directory_entry.configure_entry_text(self.computer_directory.get_formated_current_directory())\r\n \r\n \r\nclass ComputerDirectory(object):\r\n def __init__(self):\r\n self.harddrives=[]\r\n self.current_directory=[]\r\n self.formated_current_directory=\"\"\r\n self.find_harddrives()\r\n\r\n def find_harddrives(self):\r\n self.harddrives=[\"{0}:\".format(drive) for drive in ALAPHABET if os.path.exists(\"{0}:\\\\\".format(drive))]\r\n def get_harddrives(self):\r\n return self.harddrives\r\n\r\n def set_current_directory(self, directory):\r\n self.current_directory.append(\"{0}\\\\\".format(directory))\r\n self.set_formated_current_directory()\r\n print(\"Current Dir: \",self.current_directory)\r\n\r\n def get_current_directory(self):\r\n return self.current_directory[len(self.current_directory)-1]\r\n def get_previous_directory(self):\r\n if len(self.current_directory)==1:\r\n return \"Hard drives\"\r\n else:\r\n return self.current_directory[(len(self.current_directory)-1)-1]\r\n\r\n def trim_from_current_directory(self,number_of_levels):\r\n self.delete_last_directories(number_of_levels)\r\n self.set_formated_current_directory()\r\n print(\"Current Dir: \",self.current_directory)\r\n\r\n def delete_last_directories(self,number_of_levels):\r\n for x in range(0,len(self.current_directory)):\r\n if len(self.current_directory)-x<=number_of_levels:\r\n del(self.current_directory[x])\r\n break\r\n print(self.current_directory)\r\n\r\n def get_sub_directories(self):\r\n if len(self.current_directory)==0:\r\n return self.harddrives\r\n else:\r\n try:\r\n os.listdir(self.formated_current_directory)\r\n except:\r\n print(\"Error opening file\")\r\n return \"ACCESS DENIED\"\r\n else:\r\n sub_directories=[sub_dir for sub_dir in os.listdir(self.formated_current_directory) if os.path.isdir(os.path.join(self.formated_current_directory, sub_dir))]\r\n print(sub_directories)\r\n return sub_directories\r\n \r\n def set_formated_current_directory(self):\r\n self.formated_current_directory=\"\"\r\n for x in range(0,len(self.current_directory)):\r\n self.formated_current_directory=\"{0}{1}\".format(self.formated_current_directory,self.current_directory[x])\r\n print(\"Formated Cur Dir: \"+self.formated_current_directory)\r\n def get_formated_current_directory(self):\r\n return self.formated_current_directory\r\n\r\n\r\nclass SavedInfo(object):\r\n def __init__(self):\r\n self.known_good_file=FileWrapper.File(os.curdir,\"KnownGoodFiletypes.txt\")\r\n self.known_bad_file=FileWrapper.File(os.curdir,\"KnownBadFiletypes.txt\")\r\n self.__setup_filetypes()\r\n self.directory_to_scan=\"\"\r\n\r\n def __setup_filetypes(self):\r\n self.known_good_filetypes=self.known_good_file.read_lines(0,'end')\r\n self.known_bad_filetypes=self.known_bad_file.read_lines(0,'end')\r\n\r\n def get_known_good_filetypes(self):\r\n good_file_types=self.known_good_filetypes\r\n return good_file_types[0:len(good_file_types)]\r\n def get_known_bad_filetypes(self):\r\n bad_file_types=self.known_bad_filetypes\r\n return bad_file_types[0:len(bad_file_types)]\r\n\r\n def add_file_type(self,file_consensus,file_type):\r\n if file_consensus==\"KnownGood\":\r\n self.known_good_filetypes.append(file_type)\r\n elif file_consensus==\"KnownBad\":\r\n self.known_bad_filetypes.append(file_type)\r\n def delete_file_type(self,file_consensus,file_type):\r\n if file_consensus==\"KnownGood\":\r\n file_list=self.known_good_filetypes\r\n elif file_consensus==\"KnownBad\":\r\n file_list=self.known_bad_filetypes\r\n for x in range(0,len(file_list)):\r\n if file_list[x]==file_type:\r\n del(file_list[x])\r\n break\r\n \r\n def set_directory_to_scan(self,new_directory):\r\n self.directory_to_scan=new_directory\r\n def get_directory_to_scan(self):\r\n return self.directory_to_scan\r\n\r\n def save_info_to_file(self):\r\n self.known_good_file.delete_all_file_contents()\r\n self.known_bad_file.delete_all_file_contents()\r\n for item in self.known_good_filetypes:\r\n self.known_good_file.append_line_to_file(item)\r\n for item in self.known_bad_filetypes:\r\n self.known_bad_file.append_line_to_file(item)\r\n\r\n def close_all_files(self):\r\n self.known_good_file.close_file()\r\n self.known_bad_file.close_file()\r\n\r\n\r\n\r\ndef main():\r\n application_window=AppWindow()\r\n print(\"here\")\r\n saved_information.save_info_to_file()\r\n saved_information.close_all_files()\r\nsaved_information=SavedInfo()\r\nmain()\r\n","sub_path":"FileScanner.pyw","file_name":"FileScanner.pyw","file_ext":"pyw","file_size_in_byte":42493,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"7517000","text":"import sys\nimport random\npunctuation = ['.', ',', '!', '?', ';', '\"', \"(\", \")\", '\\'']\nend_punctuation = [\".\", \"!\", \"?\"]\ndef parse(text):\n words = []\n start = 0\n spaces = [' ', '\\n', '\\t', '\\r']\n for cur, char in enumerate(text):\n if text[start] in spaces:\n start = cur\n continue\n if char in spaces or char in punctuation:\n word = text[start : cur]\n words.append(word)\n start = cur\n return words\n\ndef build_markov_chain(words):\n chains = {}\n for i, word in enumerate(words):\n\n if word not in chains and word not in end_punctuation:\n chains[word] = {}\n if i == 0:\n continue\n prev_word = words[i - 1]\n if prev_word in end_punctuation:\n continue\n if word not in chains[prev_word]:\n chains[prev_word][word] = 0\n chains[prev_word][word] += 1\n return chains\n\ndef generate_sentence(word, chains, sentence):\n sentence.append(word)\n if word in end_punctuation:\n return sentence\n\n next_words = chains[word]\n next_word = random.choices([k for k in next_words.keys()], weights = [v for v in next_words.values()]) [0]\n return generate_sentence(next_word, chains, sentence)\n\n\ndef main():\n filename = sys.argv[1]\n with open(filename) as f:\n text = f.read()\n words = parse(text)\n chains = build_markov_chain(words)\n start_words = [w for w in chains.keys() if w[0].isupper()]\n start_word = random.choice(start_words)\n sentence = generate_sentence(start_word, chains, [])\n sentenceSTR = \"\"\n for word in sentence:\n if word in punctuation:\n sentenceSTR = sentenceSTR[: -1]\n sentenceSTR += word\n sentenceSTR += \" \"\n print(sentenceSTR)\n\nmain()\n","sub_path":"main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":1839,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"56638927","text":"from django.shortcuts import render\nfrom django.shortcuts import render, Http404, get_object_or_404, HttpResponsePermanentRedirect\nfrom django.http import HttpResponse\nfrom models import Question, Answer\nfrom forms import AskForm, AnswerForm\nfrom django.core.paginator import Paginator\n\ndef test(request, page=2):\n return HttpResponse(' '+page+'
')\n\ndef error (request, *args, **kwargs):\n raise Http404('Not working')\n# Create your views here.\ndef qa_new(request):\n last_questions = Question.objects.order_by('id')\n limit = request.GET.get('limit', 10)\n page = request.GET.get('page', 1)\n paginator = Paginator(last_questions, limit)\n paginator.baseurl = '/?page='\n page = paginator.page(page)\n return render(request, 'qa_new.html', {\n 'last_questions': page.object_list,\n 'paginator': paginator,\n 'page': page,\n })\n\ndef qa_popular(request):\n questions = Question.objects.order_by('-rating')\n limit = request.GET.get('limit', 10)\n page = request.GET.get('page')\n paginator = Paginator(questions, limit)\n paginator.baseurl = '/popular/?page='\n page = paginator.page(page)\n return render(request, 'qa_popular.html', {\n 'questions': page.object_list,\n 'paginator': paginator,\n 'page': page,\n })\n\ndef qa_question(request, question_id):\n question = get_object_or_404(Question, id=question_id)\n answers = Answer.objects.filter(question=question_id)\n if request.method is 'POST':\n return answer_form(request)\n form = AnswerForm()\n context = {\n 'title': question.title,\n 'text': question.text,\n 'answers': answers,\n 'rating': question.rating,\n 'from': form,\n }\n return render(request, 'qa_question.html', context)\n","sub_path":"ask/qa/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":1776,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"598225079","text":"# emacs: -*- mode: python-mode; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-\n# ex: set sts=4 ts=4 sw=4 et:\n\"\"\"\nClass and functions for functional decoding.\n\"\"\"\nfrom __future__ import print_function, division\n\nfrom builtins import object\nimport numpy as np\nimport pandas as pd\nimport nibabel as nib\nfrom nilearn.masking import apply_mask, unmask\nfrom sklearn.feature_extraction.text import CountVectorizer\n\nfrom .due import due, Doi\n\n\n@due.dcite(Doi('10.1371/journal.pcbi.1005649'),\n description='Describes decoding methods using GC-LDA.')\nclass Decoder(object):\n \"\"\"\n Class object for a gcLDA decoder\n \"\"\"\n def __init__(self, model):\n \"\"\"\n Class object for a gcLDA decoder\n \"\"\"\n self.model = model\n self.dataset = model.dataset\n\n def decode_roi(self, roi, topic_priors=None):\n \"\"\"\n Perform image-to-text decoding for discrete image inputs (e.g., regions\n of interest, significant clusters).\n\n 1. Compute p_topic_g_voxel.\n - I think you need p_voxel_g_topic for this, then you do:\n - p_topic_g_voxel = p_voxel_g_topic * p_topic / p_voxel\n - What is p_voxel here?\n 2. Compute topic weight vector (tau_t).\n - topic_weights = np.sum(p_topic_g_voxel, axis=1) (across voxels)\n 3. Multiply tau_t by topic-by-word matrix (p_word_g_topic).\n 4. The resulting vector (tau_t*p_word_g_topic) should be word weights\n for your selected studies.\n \"\"\"\n if type(roi) == str:\n roi = nib.load(roi)\n\n if not np.array_equal(roi.affine, self.model.dataset.mask_img.affine):\n str1 = np.array2string(roi.affine)\n str2 = np.array2string(self.model.dataset.mask_img.affine)\n raise ValueError('Input roi must have same affine as mask img:'\n '\\n{0}\\n{1}'.format(str1, str2))\n\n # Load ROI file and get ROI voxels overlapping with brain mask\n roi_arr = roi.get_data() & self.model.dataset.mask_img.get_data()\n roi_voxels = np.where(roi_arr > 0)[0]\n\n p_topic_g_voxel, _ = self.model.get_spatial_probs()\n p_topic_g_roi = p_topic_g_voxel[roi_voxels, :] # p(T|V) for voxels in ROI only\n topic_weights = np.sum(p_topic_g_roi, axis=0) # Sum across words\n if topic_priors is not None:\n topic_weights *= topic_priors\n topic_weights /= np.sum(topic_weights) # tau_t\n\n # Multiply topic_weights by topic-by-word matrix (p_word_g_topic).\n n_word_tokens_per_topic = np.sum(self.model.n_word_tokens_word_by_topic, axis=0)\n p_word_g_topic = self.model.n_word_tokens_word_by_topic / n_word_tokens_per_topic[None, :]\n p_word_g_topic = np.nan_to_num(p_word_g_topic, 0)\n word_weights = np.dot(p_word_g_topic, topic_weights)\n\n decoded_df = pd.DataFrame(index=self.model.dataset.word_labels, columns=['Weight'],\n data=word_weights)\n decoded_df.index.name = 'Term'\n return decoded_df, topic_weights\n\n def decode_continuous(self, image, topic_priors=None):\n \"\"\"\n Perform image-to-text decoding for continuous inputs (e.g.,\n unthresholded statistical maps).\n\n 1. Compute p_topic_g_voxel.\n 2. Compute topic weight vector (tau_t) by multiplying p_topic_g_voxel\n by input image.\n 3. Multiply tau_t by topic-by-word matrix (p_word_g_topic).\n 4. The resulting vector (tau_t*p_word_g_topic) should be word weights\n for your map, but the values are scaled based on the input image, so\n they won't necessarily mean much.\n \"\"\"\n # Load image file and get voxel values\n input_values = apply_mask(image, self.model.dataset.mask_img)\n p_topic_g_voxel, _ = self.model.get_spatial_probs()\n topic_weights = np.abs(np.squeeze(np.dot(p_topic_g_voxel.T, input_values[:, None])))\n if topic_priors is not None:\n topic_weights *= topic_priors\n topic_weights /= np.sum(topic_weights) # tau_t\n\n # Multiply topic_weights by topic-by-word matrix (p_word_g_topic).\n n_word_tokens_per_topic = np.sum(self.model.n_word_tokens_word_by_topic, axis=0)\n p_word_g_topic = self.model.n_word_tokens_word_by_topic / n_word_tokens_per_topic[None, :]\n p_word_g_topic = np.nan_to_num(p_word_g_topic, 0)\n word_weights = np.dot(p_word_g_topic, topic_weights)\n\n decoded_df = pd.DataFrame(index=self.model.dataset.word_labels, columns=['Weight'],\n data=word_weights)\n decoded_df.index.name = 'Term'\n return decoded_df, topic_weights\n\n def encode(self, text, out_file=None, topic_priors=None):\n \"\"\"\n Perform text-to-image encoding.\n\n 1. Compute p_topic_g_word.\n - p_topic_g_word = p_word_g_topic * p_topic / p_word\n - p_topic is uniform (1/n topics)\n 2. Compute topic weight vector (tau_t).\n - tau_t = np.sum(p_topic_g_word, axis=1) (across words)\n 3. Multiply tau_t by topic-by-voxel matrix of smoothed p_voxel_g_topic\n (A; not sure where it is, but I don't think it's the same as A in\n model.py).\n 4. The resulting map (tau_t*A) is the encoded image. Values are *not*\n probabilities.\n \"\"\"\n if isinstance(text, list):\n text = ' '.join(text)\n\n # Assume that words in word_labels are underscore-separated.\n # Convert to space-separation for vectorization of input string.\n vocabulary = [term.replace('_', ' ') for term in self.model.dataset.word_labels]\n max_len = max([len(term.split(' ')) for term in vocabulary])\n vectorizer = CountVectorizer(vocabulary=self.model.dataset.word_labels,\n ngram_range=(1, max_len))\n word_counts = np.squeeze(vectorizer.fit_transform([text]).toarray())\n keep_idx = np.where(word_counts > 0)[0]\n text_counts = word_counts[keep_idx]\n\n n_topics_per_word_token = np.sum(self.model.n_word_tokens_word_by_topic, axis=1)\n p_topic_g_word = self.model.n_word_tokens_word_by_topic / n_topics_per_word_token[:, None]\n p_topic_g_word = np.nan_to_num(p_topic_g_word, 0)\n p_topic_g_text = p_topic_g_word[keep_idx] # p(T|W) for words in text only\n prod = p_topic_g_text * text_counts[:, None] # Multiply p(T|W) by words in text\n topic_weights = np.sum(prod, axis=0) # Sum across words\n if topic_priors is not None:\n topic_weights *= topic_priors\n topic_weights /= np.sum(topic_weights) # tau_t\n\n _, p_voxel_g_topic = self.model.get_spatial_probs()\n voxel_weights = np.dot(p_voxel_g_topic, topic_weights)\n voxel_weights_matrix = unmask(voxel_weights, self.model.dataset.mask_img)\n\n img = nib.Nifti1Image(voxel_weights_matrix, self.model.dataset.mask_img.affine)\n if out_file is not None:\n img.to_filename(out_file)\n return img, topic_weights\n","sub_path":"gclda/decode.py","file_name":"decode.py","file_ext":"py","file_size_in_byte":7117,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"604990399","text":"#!/usr/local/bin/python2.7\n\n\"\"\"\n Copyright (c) 2015 Jos Schellevis - Deciso B.V.\n All rights reserved.\n\n Redistribution and use in source and binary forms, with or without\n modification, are permitted provided that the following conditions are met:\n\n 1. Redistributions of source code must retain the above copyright notice,\n this list of conditions and the following disclaimer.\n\n 2. Redistributions in binary form must reproduce the above copyright\n notice, this list of conditions and the following disclaimer in the\n documentation and/or other materials provided with the distribution.\n\n THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES,\n INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY\n AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE\n AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY,\n OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF\n SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS\n INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN\n CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)\n ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE\n POSSIBILITY OF SUCH DAMAGE.\n\"\"\"\n\nimport urllib2\nimport os\nimport os.path\nimport tarfile\nimport gzip\nimport zipfile\nimport StringIO\nimport syslog\nfrom ConfigParser import ConfigParser\n\nacl_config_fn = ('/usr/local/etc/squid/externalACLs.conf')\nacl_target_dir = ('/usr/local/etc/squid/acl')\nacl_max_timeout = 30\n\nclass ACLDownload(object):\n\n def __init__(self, url, timeout):\n \"\"\" init new\n \"\"\"\n self._url = url\n self._timeout = timeout\n self._source_data = None\n self._target_data = None\n\n def fetch(self):\n \"\"\" fetch (raw) source data into self._source_data\n \"\"\"\n try:\n f = urllib2.urlopen(self._url,timeout = self._timeout)\n self._source_data = f.read()\n f.close()\n except (urllib2.URLError, urllib2.HTTPError, IOError) as e:\n syslog.syslog(syslog.LOG_ERR, 'proxy acl: error downloading %s'%self._url)\n self._source_data = None\n\n def pre_process(self):\n \"\"\" pre process downloaded data, handle compression\n \"\"\"\n if self._source_data is not None:\n # handle compressed data\n if (len(self._url) > 8 and self._url[-7:] == '.tar.gz') \\\n or (len(self._url) > 4 and self._url[-4:] == '.tgz'):\n # source is in tar.gz format, extract all into a single string\n try:\n tf = tarfile.open(fileobj=StringIO.StringIO(self._source_data))\n target_data = []\n for tf_file in tf.getmembers():\n if tf_file.isfile():\n target_data.append(tf.extractfile(tf_file).read())\n self._target_data = ''.join(target_data)\n except IOError as e:\n syslog.syslog(syslog.LOG_ERR, 'proxy acl: error downloading %s (%s)'%(self._url, e))\n elif len(self._url) > 4 and self._url[-3:] == '.gz':\n # source is in .gz format unpack\n try:\n gf = gzip.GzipFile(mode='r', fileobj=StringIO.StringIO(self._source_data))\n self._target_data = gf.read()\n except IOError as e:\n syslog.syslog(syslog.LOG_ERR, 'proxy acl: error downloading %s (%s)'%(self._url, e))\n elif len(self._url) > 5 and self._url[-4:] == '.zip':\n # source is in .zip format, extract all into a single string\n target_data = []\n with zipfile.ZipFile(StringIO.StringIO(self._source_data),\n mode='r',\n compression=zipfile.ZIP_DEFLATED) as zf:\n for item in zf.infolist():\n target_data.append(zf.read(item))\n self._target_data = ''.join(target_data)\n else:\n self._target_data = self._source_data\n\n def download(self):\n self.fetch()\n self.pre_process()\n\n def is_valid(self):\n \"\"\" did this ACL download successful\n \"\"\"\n if self._target_data is not None:\n return True\n else:\n return False\n\n def get_data(self):\n \"\"\" retrieve data\n \"\"\"\n # XXX: maybe some postprocessing is needed here, all will be used with a squid dstdom_regex tag\n return self._target_data\n\n\n# parse OPNsense external ACLs config\nif os.path.exists(acl_config_fn):\n # create acl directory (if new)\n if not os.path.exists(acl_target_dir):\n os.mkdir(acl_target_dir)\n # read config and download per section\n cnf = ConfigParser()\n cnf.read(acl_config_fn)\n for section in cnf.sections():\n # check if tag enabled exists in section\n if cnf.has_option(section,'enabled'):\n # if enabled fetch file\n target_filename = acl_target_dir+'/'+section\n if cnf.get(section,'enabled')=='1':\n if cnf.has_option(section,'url'):\n download_url = cnf.get(section,'url')\n acl = ACLDownload(download_url, acl_max_timeout)\n acl.download()\n if acl.is_valid():\n output_data = acl.get_data()\n with open(target_filename, \"wb\") as code:\n code.write(output_data)\n elif not os.path.isfile(target_filename):\n # if there's no file available, create an empty one (otherwise leave the last download).\n with open(target_filename, \"wb\") as code:\n code.write(\"\")\n # if disabled or not 1 try to remove old file\n elif cnf.get(section,'enabled')!='1':\n try:\n os.remove(acl_target_dir+'/'+section)\n except OSError:\n pass\n","sub_path":"src/opnsense/scripts/proxy/fetchACLs.py","file_name":"fetchACLs.py","file_ext":"py","file_size_in_byte":6201,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"618195129","text":"import numpy as np\nimport cv2 as cv2\nimport glob\nimport time\nimport os\nimport shutil\n\nglobal m_fit_num\n\nclass GMM():\n\n def __init__(self):\n self.GMM_MAX_COMPONT = 5 # 混合高斯数\n self.SIGMA = 30\n self.WEIGHT = 0.05\n self.T = 0.7 # 模型排序判读阀值\n self.alpha = 0.005 # 学习率\n self.eps = pow(10, -10)\n self.channel = 3 # RGB三个通道\n self.m_weight = [[] for i in range(self.GMM_MAX_COMPONT * self.channel)] # 权重\n self.m_mean = [[] for i in range(self.GMM_MAX_COMPONT * self.channel)] # 均值\n self.m_sigma = [[] for i in range(self.GMM_MAX_COMPONT * self.channel)] # 方差\n\n def init_model(self,img):\n row , col , channel = img.shape # 得到图片的长宽高 以及其中的通道数\n global m_fit_num\n for i in range(self.GMM_MAX_COMPONT * self.channel):\n self.m_weight[i] = np.zeros((row,col),dtype=\"float32\") # 每个点有5个高斯模型，总共三个通道\n self.m_mean[i] = np.zeros((row, col), dtype='float32')\n self.m_sigma[i] = np.ones((row, col), dtype='float32')\n self.m_sigma[i] *= self.SIGMA\n m_fit_num = np.zeros((row,col),dtype=\"int32\")\n\n def train_model(self,images):\n row, col, channel = images.shape # 得到图片的长宽高 以及其中的通道数\n B,R,G = cv2.split(images) # 利用cv2提取图像RGB三个通道的图形矩阵\n m_mask = np.zeros((row,col),dtype=np.uint8)\n m_mask[:] = 255\n for i in range(row): # 遍历每一个像素点\n for j in range(col):\n cnt = 0\n for c,img in enumerate((B,G,R)):\n num_fit = 0\n for k in range(c * self.GMM_MAX_COMPONT,c * self.GMM_MAX_COMPONT + self.GMM_MAX_COMPONT):\n if self.m_weight[k][i][j] != 0: # 权重不等于0\n delta = abs(img[i][j] - self.m_mean[k][i][j])\n if float(delta) < 2.5 * self.m_sigma[k][i][j]: # 在2.5个方差之内 平均数 方差 等参数\n self.m_weight[k][i][j] = (1 - self.alpha) * self.m_weight[k][i][j] + self.alpha * 1\n self.m_mean[k][i][j] = (1 - self.alpha) * self.m_mean[k][i][j] + self.alpha * img[i][j]\n self.m_sigma[k][i][j] = np.sqrt((1 - self.alpha) * self.m_sigma[k][i][j] * self.m_sigma[k][i][j] + self.alpha * (img[i][j] - self.m_mean[k][i][j]) * (img[i][j] - self.m_mean[k][i][j]))\n num_fit += 1\n else:\n self.m_weight[k][i][j] *= (1 - self.alpha)\n\n for p in range(c * self.GMM_MAX_COMPONT, c * self.GMM_MAX_COMPONT + self.GMM_MAX_COMPONT): # 对权重进行降序 根据𝜔/𝜎降序排序 等会进行选择\n for q in range(p + 1, c * self.GMM_MAX_COMPONT + self.GMM_MAX_COMPONT):\n if (self.m_weight[p][i][j] / self.m_sigma[p][i][j]) <= (self.m_weight[q][i][j] / self.m_sigma[q][i][j]):\n self.m_sigma[p][i][j], self.m_sigma[q][i][j] = self.m_sigma[q][i][j], self.m_sigma[p][i][j]\n self.m_weight[p][i][j], self.m_weight[q][i][j] = self.m_weight[q][i][j], self.m_weight[p][i][j]\n self.m_mean[p][i][j], self.m_mean[q][i][j] = self.m_mean[q][i][j], self.m_mean[p][i][j]\n if num_fit == 0: # 没有匹配到任何一个高斯模型\n if self.m_weight[c * self.GMM_MAX_COMPONT + self.GMM_MAX_COMPONT-1][i][j] ==0 :\n for kk in range(c * self.GMM_MAX_COMPONT, c * self.GMM_MAX_COMPONT + self.GMM_MAX_COMPONT):\n if (0 == self.m_weight[kk][i][j]): # 重新初始化参数\n self.m_weight[kk][i][j] = self.WEIGHT\n self.m_mean[kk][i][j] = img[i][j]\n self.m_sigma[kk][i][j] = self.SIGMA\n break\n else:\n self.m_weight[c * self.GMM_MAX_COMPONT + self.GMM_MAX_COMPONT - 1][i][j] = self.WEIGHT\n self.m_mean[c * self.GMM_MAX_COMPONT + self.GMM_MAX_COMPONT - 1][i][j] = img[i][j]\n self.m_sigma[c * self.GMM_MAX_COMPONT + self.GMM_MAX_COMPONT - 1][i][j] = self.SIGMA\n\n weight_sum = 0 # 每个高斯模型的权重要进行归一化操作\n for nn in range(c * self.GMM_MAX_COMPONT, c * self.GMM_MAX_COMPONT + self.GMM_MAX_COMPONT):\n if self.m_weight[nn][i][j] != 0:\n weight_sum += self.m_weight[nn][i][j]\n else:\n break\n weight_scale = 1.0 / (weight_sum + self.eps)\n weight_sum = 0\n\n for nn in range(c * self.GMM_MAX_COMPONT, c * self.GMM_MAX_COMPONT + self.GMM_MAX_COMPONT):\n if self.m_weight[nn][i][j] != 0:\n self.m_weight[nn][i][j] *= weight_scale\n weight_sum += self.m_weight[nn][i][j]\n if abs(img[i][j] - self.m_mean[nn][i][j]) < 2 * self.m_sigma[nn][i][j]:\n cnt += 1\n break\n if weight_sum > self.T:\n if abs(img[i][j] - self.m_mean[nn][i][j]) < 2 * self.m_sigma[nn][i][j]:\n cnt += 1\n break\n else:\n break\n if cnt == channel:\n m_mask[i][j] = 0\n\n m_mask = cv2.medianBlur(m_mask, 7)\n\n kernel_d = np.ones((5, 5), np.uint8)\n m_mask = cv2.dilate(m_mask, kernel_d)\n # element = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3)) # 调用库函数开启形态学去噪\n # m_mask = cv2.morphologyEx(m_mask, cv2.MORPH_OPEN, element) # 开运算去噪\n return m_mask\n\n def judge_img(self,imgs):\n row, col, channel = imgs.shape\n B, G, R = cv2.split(imgs)\n m_mask = np.zeros((row, col), dtype=np.uint8)\n m_mask[:] = 255\n for i in range(row):\n for j in range(col):\n cnt = 0\n for c, img in enumerate((B, G, R)): # 一张图片的每个像素点进行判断 是否是作为前景还是背景\n weight_sum = 0\n for nn in range(c * self.GMM_MAX_COMPONT, c * self.GMM_MAX_COMPONT + self.GMM_MAX_COMPONT):\n if self.m_weight[nn][i][j] != 0:\n weight_sum += self.m_weight[nn][i][j]\n if abs(img[i][j] - self.m_mean[nn][i][j]) < 2 * self.m_sigma[nn][i][j]:\n cnt += 1\n break\n if weight_sum > self.T:\n if abs(img[i][j] - self.m_mean[nn][i][j]) < 2 * self.m_sigma[nn][i][j]:\n cnt += 1\n break\n else:\n break\n\n if cnt == channel:\n m_mask[i][j] = 0\n\n m_mask = cv2.medianBlur(m_mask, 7)\n kernel_d = np.ones((5, 5), np.uint8)\n m_mask = cv2.dilate(m_mask, kernel_d)\n return m_mask\n\n\n\n\nif __name__ == '__main__':\n file_list = glob.glob('WavingTrees/b*.bmp') # 读入测试文件得列表\n GMM_Model = GMM()\n GMM_Model.__init__() # 初始化模型\n path = \"GMM_OUTPUT_Primordial\"\n if os.path.exists(path):\n shutil.rmtree(path)\n os.mkdir(path)\n else:\n os.mkdir(path)\n i = -1\n for file in file_list:\n i += 1\n img = cv2.imread(file)\n if i == 0:\n GMM_Model.init_model(img) # 第一张图片\n if i <= 200: # 前面的200张用于训练模型\n t1 = time.time()\n print(\"第{}次训练\".format(i))\n m_mask = GMM_Model.train_model(img)\n t2 = time.time()\n print(\"花费时间：\",t2 - t1)\n if i == 286: # 训练完毕 开始识别\n print(\"开始背景检测\")\n t1 = time.time()\n j = 0\n for temp_file in file_list:\n temp_img = cv2.imread(temp_file)\n m_mask = GMM_Model.judge_img(temp_img)\n cv2.imwrite(\"GMM_OUTPUT_Primordial/{}.jpg\".format(str(j).zfill(3)), m_mask)\n j += 1\n t2 = time.time()\n print(\"检测花费时间：\",t2 - t1)\n\n\n\n\n\n\n\n","sub_path":"GMM_Backgroundsubtraction.py","file_name":"GMM_Backgroundsubtraction.py","file_ext":"py","file_size_in_byte":8867,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"411086113","text":"import numpy as np\n\nclass Line:\n def __init__(self, x_0, y_0, x_1, y_1):\n\n self.x_0 = x_0\n self.y_0 = y_0\n\n self.x_1 = x_1\n self.y_1 = y_1\n\n # slope and y-intercept\n self.alpha = (y_1 - y_0)/(x_1 - x_0)\n self.beta = y_0 - self.alpha*x_0\n\n def evaluate_at(self, x):\n y = self.alpha * x + self.beta\n return y\n\n def exp(self, x):\n y = np.exp(self.alpha*x+self.beta)\n return y\n\n def intersection_with(self, line2):\n # mx+b = ax+c\n # mx-ax = c-b\n # x(m-a)=c-b\n # x = (c-b)/(m-a)\n x = (line2.beta - self.beta) / (self.alpha - line2.alpha)\n y = self.evaluate_at(x)\n coord = {'x': x, 'y': y}\n return coord\n\n def area(self):\n dist = self.x_1 - self.x_0\n triangle = np.abs(self.y_1-self.y_0) * dist / 2\n area = dist * self.y_0 + triangle\n return area\n\n def __repr__(self):\n return (\"from (%f, %f) to (%f, %f) \\n\"\n \"alpha = %f \\n \"\n \"beta = %f\" %\n (self.x_0,\n self.y_0,\n self.x_1,\n self.y_1,\n self.alpha,\n self.beta))","sub_path":"AcceptReject/AdaptiveAcceptReject/line.py","file_name":"line.py","file_ext":"py","file_size_in_byte":1218,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"223163255","text":"def disemvowel(word):\n vowels = [\"a\", \"e\", \"i\", \"o\", \"u\"]\n newWord = list(word)\n for letter in word:\n if letter.lower() in vowels:\n newWord.remove(letter)\n newWord = \"\".join(newWord)\n\n\n\n print(newWord)\n\n\n\n\n\n\ndisemvowel(\"Hello\")","sub_path":"Disemvowelment.py","file_name":"Disemvowelment.py","file_ext":"py","file_size_in_byte":260,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"522957404","text":"import serial\nimport time\nimport json\nimport random\nimport arena\nfrom threading import Thread\nfrom utils import send_alert2\n\n# Global for keeping track of which sensor to display data from\n\ntest_email = True\n\n\n\n\nemail_status= False\n\nif test_email and email_status==False:\n send_alert2()\n email_status=True\n\ndef start_serial():\n global sensor_to_read\n global reading_text\n\n\n\n global email_status \n# global test_email\n global door_status\n\n # set up the serial line\n ser = serial.Serial('COM4', 9600)\n time.sleep(2)\n \n \n while True:\n if email_status and door_status == True:\n ser.write(\"blink\\n\".encode())\n \n elif email_status and door_status == False:\n ser.write(\"dont blink\\n\".encode())\n time.sleep(1)\n\n ser.close()\n\n\ndef scene_callback(msg):\n print(\"scene_callback: \", msg)\n\narena.init(\"arena.andrew.cmu.edu\", \"realm\", \"patrick_scene\")#, scene_callback)\n\n\n\n\ndoor_status = False\ndef door_button_callback(event):\n global door_obj\n global door_status\n if event.event_type == arena.EventType.mousedown:\n if door_status:\n door_status = False\n door_obj.update(data='{\"animation\": { \"property\": \"rotation\", \"from\": \"0 90 0\", \"to\": \"0 0 0\", \"loop\": false, \"dur\": 1000}}')\n else:\n door_status = True\n door_obj.update(data='{\"animation\": { \"property\": \"rotation\",\"from\": \"0 0 0\", \"to\": \"0 90 0 \", \"loop\": false, \"dur\": 1000}}')\ndoor_obj = arena.Object(\n objName = \"door\",\n objType=arena.Shape.cube,\n scale=(0.1,2,1.2),\n location=(-9,1.6,-2),\n clickable=False,\n data='{\"animation\": { \"property\": \"rotation\", \"to\": \"0 0 0\", \"loop\": false, \"dur\": 0}}',\n)\nbutton_door = arena.Object(\n objName = \"button_dor\",\n objType=arena.Shape.cube,\n scale=(1,1,1),\n location=(-11,1.6,-3),\n clickable=True,\n callback=door_button_callback,\n color = (255,0, 255)\n)\n \n\nthread = Thread(target = start_serial)\nthread.start()\narena.handle_events()\n\nthread.join()","sub_path":"misc_files/source_code/ECE202A-main/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":2090,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"202369208","text":"def Permutation(index, N, M):\n global result\n\n if index == M:\n result_str = ' '.join(map(str, result))\n if result_str not in result_set:\n print(result_str)\n result_set.add(result_str)\n return 0\n\n for j in range(1, N+1):\n if visited[j][1] is not True:\n result[index] = visited[j][0]\n visited[j][1] = True\n Permutation(index + 1, N, M)\n visited[j][1] = False\n\n\n\nN, M = map(int, input().split())\nnode = list(map(int, input().split()))\nnode.sort()\nvisited = {}\nresult_set = set()\n\nfor i in range(1, N+1):\n visited[i] = [node[i-1], False]\n\nresult = [0 for i in range(M)]\nPermutation(0, N, M)","sub_path":"Python/NM9.py","file_name":"NM9.py","file_ext":"py","file_size_in_byte":692,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"245138893","text":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\n# Libraries\nimport os\nimport argparse\nimport sys\nimport time\nimport json\nimport re\nimport numpy as np\nimport pandas as pd\nimport statistics as stat\nimport lstm_binary\nimport lstm_multiclass\nfrom pprint import pprint\nfrom datetime import datetime\nfrom shutil import copy2\nfrom sklearn.model_selection import train_test_split\nimport pickle\n\n# constants\nmodels_path = '../data/local/models/'\ndata_path = '../data/local/staging/'\n\nREFPATH = \"./\"\nPROJECT_ROOT = \"/Users/nscsekhar/Desktop/nscsekhar/Desktop/Surya/Personal/MIDS/W210/Project/team_cyber/\"\nMULTI_TOKENIZER_FILE = PROJECT_ROOT + \"saved_models/multiclass_tokenizer.pkl\"\nMULTI_CATEGORIES_FILE = PROJECT_ROOT + \"saved_models/multiclass_categories.pkl\"\nMULTI_MODEL_JSON = PROJECT_ROOT + \"saved_models/multiclass_LSTM.json\"\nMULTI_MODEL_H5 = PROJECT_ROOT + \"saved_models/multiclass_LSTM.h5\"\n\n\ndef valid_filename(filename, path=''):\n '''valid_filename: determines if the given filename is a real file. Assumes that the file is in the current working directory for the program.\n\n returns: given file name\n '''\n if path == '':\n path = os.getcwd()+'/'\n\n if not os.path.isfile(path+filename):\n msg = \"The given file '{}' does not exist at '{}'.\".format(\n filename,\n path\n )\n raise argparse.ArgumentTypeError(msg)\n\n return filename\n\n\ndef parse_args():\n '''parse_args: parse command line arguments\n\n return: dictionary of arguments\n '''\n parser = argparse.ArgumentParser(\n description='Runs models either in train or inference mode.',\n prog='models',\n epilog='Models requires at least one of -t/--train or -i/--inference to operate correctly. Both may be provided for sequential analysis.')\n parser.add_argument('config_file',\n type=valid_filename,\n metavar='CONFIG_FILE',\n help=\"File path to the requex configuration file. File must be in JSON format.\")\n parser.add_argument('-t', '--train',\n metavar='TRAINING_FILE',\n nargs=1,\n help=\"Runs models in training mode. Training will be run on the given file. The training file must be a prepared '.csv' file. The program will search for the file in the models, then staging, and finally downloads directories.\")\n parser.add_argument('-i', '--inference',\n metavar='INFERENCE_FILE',\n nargs=1,\n help=\"Runs models in inference mode. Inference will be run on the given file. The inference file must be a list of domains separated by carriage returns with no header. The program will search for the file in the models, then staging, and finally downloads directories.\")\n parser.add_argument('-m', '--model', choices=['binary', 'multiclass'],\n metavar='model_type',\n required=True,\n help=\"This required option indicates which type of model is being built or used. Using 'binary' selects a benign/malicious model. Using 'multiclass' will classify the malware family for each malicious classified entry.\")\n\n return vars(parser.parse_args())\n\n\ndef get_config_filename(filename=None):\n '''get_config_filename: returns a verified Requex configuration file name. This function handles the ambiguity around whether the module was called from a shell with command line arguments or if called from another program using the run() function. If filename is none, the function assumes that there are\n\n return: string; valid filename.\n '''\n if filename is None:\n # get command line arguments\n args = parse_args()\n filename = args['config_file']\n else:\n # filename provided, verify the file exists\n if not os.path.isfile(filename):\n print(\"The given file '{}' does not exist at '{}'.\".format(\n filename,\n os.getcwd()\n ))\n exit(1)\n return filename\n\n\ndef get_config(filename):\n '''get_config: reads the configuration JSON file and stores values in a dictionary for processing.\n\n PRE: assumes the file already exists\n\n return: dict of configuration settings\n '''\n\n with open(filename, \"r\") as f:\n config = json.load(f)\n\n return config\n\n\ndef get_file_date(filename):\n '''get_file_date: extracts file date from file name. File date must be in YYYY-MM-DD format.\n\n returns: datetime object of file date.\n '''\n date = re.search(r'\\d\\d\\d\\d-\\d\\d-\\d\\d|$', filename).group()\n year, month, day = date.split('-')\n return datetime(int(year), int(month), int(day))\n\n\ndef write_to_train_logfile(metrics, logpath, stdout=True):\n '''write_to_train_logfile: writes metadata in the metrics dict to a logfile\n '''\n # constants\n logfile = 'requex_training_log.csv'\n\n # write to logfile\n stamp = datetime.utcnow().strftime('%Y-%m-%d-%H:%M')\n\n # extract the filename\n # filename = os.path.basename(datafile)\n\n if stdout:\n # print(\"info:{:>10} rows: {:>10} malicious, {:>10} benign, a {:>3.3f} ratio\".format(total_rows, malicious_rows, benign_rows, ratio))\n print('info: {}, {}, {}, {:>3.3f}s, {:>3.2f} MB, {} rows: {} malicious, {} benign, {:>3.3f} ratio, {}, {} categories, train rows: {}, test rows: {}, train time: {:>3.3f}s, inference time: {:>3.3f}s'.format(\n stamp, metrics['filename'], metrics['filedate'], metrics['time'], metrics['memory'], metrics['total_rows'], metrics['malicious_rows'], metrics['benign_rows'], metrics['ratio'], metrics['model'], metrics['categories'], metrics['train_rows'], metrics['test_rows'], metrics['train_time'], metrics['inference_time']))\n\n with open(logpath+logfile, 'at') as log:\n log.write('{}, {}, {}, {:>3.3f}, {:>3.2f}, {}, {}, {}, {:>3.3f}, {}, {}, {}, {}, {:>3.3f}, {:>3.3f}\\n'.format(\n stamp, metrics['filename'], metrics['filedate'], metrics['time'], metrics['memory'], metrics['total_rows'], metrics['malicious_rows'], metrics['benign_rows'], metrics['ratio'], metrics['model'], metrics['categories'], metrics['train_rows'], metrics['test_rows'], metrics['train_time'], metrics['inference_time']))\n\n\ndef copy_models(src, dst):\n '''copy_models: copies the source file (src) to the dst directory. src must be a file and dst must be a directory. Exclusions is an optional parameter that allows for files with certain file names to be excluded from being moved.\n '''\n # check to see if a directory for the dst directory exists\n if not os.path.isdir(dst):\n # directory does not exist, create it\n os.mkdir(dst)\n\n # verify whether the source and destination are the same\n src_path, filename = os.path.split(src)\n if os.path.isfile(dst+filename):\n print(\"A file by the name '{}' already exists. File not copied. Processing will continue using the file already in the '{}' directory.\".format(filename, dst))\n elif os.path.isfile(src):\n copy2(src, dst)\n else:\n print(\"The given file '{}' does not exist.\".format(src))\n exit(1)\n\n\ndef get_training_data(filename, metrics, logpath):\n '''get_training_data: reads the csv file into a pandas dataframe\n\n return: pandas dataframe\n '''\n # constants\n MB = 1024*1024\n\n start_time = time.time()\n df = pd.read_csv(filename,\n sep=',',\n parse_dates=[0],\n dtype={1: int, 2: str, 3: str},\n engine='c')\n end_time = time.time()\n read_time = end_time - start_time\n\n # calculate the memory footprint of the dataframe\n memory = sys.getsizeof(df)/MB\n\n filedate = get_file_date(filename)\n total = df.shape[0]\n benign = df.loc[df['dga'] == 0].shape[0]\n malicious = df.loc[df['dga'] == 1].shape[0]\n ratio = malicious / benign\n\n # write to logfile\n # write_to_train_logfile(logpath, filename, filedate.strftime('%Y-%m-%d'), read_time, memory, total, malicious, '2',benign, ratio)\n metrics = {\n 'filename': filename,\n 'filedate': filedate.strftime('%Y-%m-%d'),\n 'time': read_time,\n 'memory': memory,\n 'total_rows': total,\n 'malicious_rows': malicious,\n 'benign_rows': benign,\n 'ratio': ratio,\n 'categories': 0,\n 'model': 'unknown',\n 'train_rows': 0,\n 'test_rows': 0,\n 'train_time': 0,\n 'inference_rows': 0,\n 'inference_time': 0,\n 'inference_time_mean': 0.0\n }\n\n return df, metrics\n\n\ndef prep_training_dataset_binary(df):\n '''prep_training_dataset_binary: creates X, Y datasets for training and testing.\n\n returns: pandas dataframe x4: X_train, X_test, Y_train, Y_test\n '''\n # create X, Y dataframes. X = 'domain' and the model will try to\n # predict Y the catengory index.\n X = df['domain']\n Y = df['dga']\n\n X_train, X_test, Y_train, Y_test = train_test_split(\n X, Y, test_size=0.2, random_state=23)\n\n return X_train, X_test, Y_train, Y_test\n\n\ndef prep_training_dataset_multiclass(df, categories_file):\n '''prep_training_dataset_multiclass: creates X, Y datasets for training and testing.\n\n returns: pandas dataframe x4: X_train, X_test, Y_train, Y_test and the number of uniques\n '''\n\n # factorize the malware column\n df['catIndex'], uniques = pd.factorize(df['malware'], sort=True)\n\n # display factorized values\n # print('malware uniques: total - {}\\n{}'.format(len(uniques), uniques))\n # print('catIndex uniques: {}'.format(\n # pd.unique(df['catIndex'].sort_values())))\n\n # record the categories to disk\n with open(categories_file, 'wb') as f:\n pickle.dump(uniques, f, protocol=pickle.HIGHEST_PROTOCOL)\n\n # create X, Y dataframes. X = 'domain' and the model will try to\n # predict Y the catengory index.\n X = df['domain']\n Y = df['catIndex']\n\n X_train, X_test, Y_train, Y_test = train_test_split(\n X, Y, test_size=0.2, random_state=23)\n\n return X_train, X_test, Y_train, Y_test, len(uniques)\n\n\ndef get_model_info(model_type, config):\n '''get_model_info: returns a dictionary with key value pairs of model file keys and model file names. The model file names are full path names anchored to the root_dir and placed in the models directory.\n\n type: a string indicating the type of model ['binary', ['multiclass']\n config: a dict filled with configuration parameters\n\n return: dict of model:filename pairs\n '''\n\n if model_type == 'binary':\n model = config['binary_model']\n elif model_type == 'multiclass':\n model = config['multiclass_model']\n else:\n # this branch shouldn't happen with the way parse_args() written\n msg = \"error: unsupported model type '{}'.\".format(model_type)\n raise argparse.ArgumentTypeError(msg)\n exit(1)\n\n root_dir = config['root_dir']\n models_dir = config['models_dir']\n\n model = {\n 'model_json': root_dir+models_dir+model['model_json'],\n 'model_H5': root_dir+models_dir+model['model_H5'],\n 'model_tokenizer': root_dir+models_dir+model['model_tokenizer'],\n 'model_categories': root_dir+models_dir+model['model_categories'],\n 'model_algorithm': model['model_algorithm']\n }\n\n return model\n\n\ndef find_file(filename, config):\n '''find_file: looks for the file in a few directories and moves it into the models_dir. Returns the full path to the training file.\n\n return: string of full file path in the models_dir or an empty string\n '''\n root_dir = config['root_dir']\n downloads_dir = config['downloads_dir']\n staging_dir = config['staging_dir']\n models_dir = config['models_dir']\n\n # look for file in models_dir\n # look for file in staging_dir\n # look for file in downloads_dir\n if os.path.isfile(root_dir+models_dir+filename):\n return root_dir+models_dir\n elif os.path.isfile(root_dir+staging_dir+filename):\n return root_dir+staging_dir\n elif os.path.isfile(root_dir+downloads_dir+filename):\n return root_dir+downloads_dir\n else:\n return ''\n # msg = \"The given file '{}' does not exist at any of these locations '{}', '{}', '{}'.\".format(\n # filename,\n # models_dir,\n # staging_dir,\n # downloads_dir\n # )\n # print(msg)\n # exit(1)\n\n\ndef get_model_type(model_type):\n '''get_model_type: evaluates model_type to see if it is a valid option. If model_type is empty, function will attempt to pull the parameters from the command line. This function should mirror the choices in parse_args() for -m/--models.\n\n return: a string with the model_type; empty string if not correct.\n '''\n if model_type is '':\n args = parse_args()\n return args['model']\n elif model_type.lower() == 'binary':\n return 'binary'\n elif model_type.lower() == 'multiclass':\n return 'multiclass'\n else:\n return ''\n\n\ndef get_train_file(filename, config):\n '''get_train_file: evaluates the filename as well as command line arguments to get the training file name. Verifies that the training file exists.\n\n returns: string of a filename or empty string if not valid.\n '''\n root_dir = config['root_dir']\n models_dir = config['models_dir']\n\n if filename == '':\n # no filename provided, attempt to get it from the command line\n # parameters\n args = parse_args()\n train_file = args['train']\n if train_file is not None:\n # extract the filename from the parameter list\n train_file = train_file[0]\n location = find_file(train_file, config)\n if location == '':\n # file was not found\n return ''\n else:\n copy_models(location+train_file, root_dir+models_dir)\n return root_dir+models_dir+train_file\n else:\n # the command line parameter for train_file was also None\n return ''\n else:\n # filename was provided\n location = find_file(train_file, config)\n if location == '':\n # file was not found\n return ''\n else:\n copy_models(location+train_file, root_dir+models_dir)\n return root_dir+models_dir+train_file\n\n\ndef get_inference_file(filename, config):\n '''get_inference_file: evaluates the filename as well as command line arguments to get the inference file name. Verifies that the inference file exists.\n\n returns: string of a filename or empty string if not valid.\n '''\n root_dir = config['root_dir']\n models_dir = config['models_dir']\n\n if filename == '':\n # no filename provided, attempt to get it from the command line\n # parameters\n args = parse_args()\n inference_file = args['inference']\n if inference_file is not None:\n # extract the filename from the parameter list\n inference_file = inference_file[0]\n location = find_file(inference_file, config)\n if location == '':\n # file was not found\n return ''\n else:\n copy_models(location+inference_file, root_dir+models_dir)\n return root_dir+models_dir+inference_file\n else:\n # the command line parameter for inference_file was also None\n return ''\n else:\n # filename was provided\n location = find_file(inference_file, config)\n if location == '':\n # file was not found\n return ''\n else:\n copy_models(location+inference_file, root_dir+models_dir)\n return root_dir+models_dir+inference_file\n\n\ndef load_inference_data(filename):\n '''load_inference_data: reads data from the given filename. The file must be a text file with '\\n' at the end of each entry, one entry per line.\n\n returns: list of data to be analyzed\n '''\n domains = []\n with open(filename, 'rt', newline='\\n') as f:\n lines = f.readlines()\n\n for line in lines:\n domains.append(line.strip())\n\n return domains\n\n\ndef write_predictions(domains, predictions, model_type, model_algo, version, config):\n '''write_predictions: takes a 1-D list of domains and predictions and writes them to the inference file output. File name will be 'predictions_YYYY-MM-DD.txt'.\n '''\n\n # create filename\n root_dir = config['root_dir']\n models_dir = config['models_dir']\n\n # get the current date and time:\n datestamp = time.strftime('%Y-%m-%d', time.gmtime())\n timestamp = time.strftime('%H:%M.%S', time.gmtime())\n\n output_file = root_dir+models_dir+model_type+model_algo+'_predictions_'+datestamp+'_v'+version+'.csv'\n\n # write the predictions to disk\n with open(output_file, 'wt') as f:\n f.write('creation_date: {} {}\\n'.format(datestamp, timestamp))\n for i, p in enumerate(predictions):\n # print('i: {}, p: {}, domains: {}'.format(i, p, domains[i]))\n f.write('{}, {}\\n'.format(domains[i], p))\n\n\ndef get_version_number(filename):\n '''get_version_number: extracts the version number from the filename.\n\n returns: string with a version number in it.\n '''\n basename = os.path.basename(filename)\n reg = re.compile(r'(?:_v\\d+)|$', flags=re.IGNORECASE)\n return re.search(reg, basename).group()[2:]\n\n\ndef run(config_file=None, model_type='', train_file='', inference_file=''):\n # get configuration parameters\n config_file = get_config_filename(config_file)\n config = get_config(config_file)\n # print('configuration settings:')\n # pprint(config)\n\n # parse function/command line parameters\n model_type = get_model_type(model_type)\n train_file = get_train_file(train_file, config)\n inference_file = get_inference_file(inference_file, config)\n\n # assemble the path to the log directory\n root_dir = config['root_dir']\n models_dir = config['models_dir']\n logpath = root_dir+models_dir\n\n if model_type == '':\n print(\"error: an invalid model type was given. See the -h/--help command line options for valid model choices.\")\n exit(1)\n\n if train_file == '' and inference_file == '':\n print(\"error: neither train or inference were given as arguments. Please run again, but with either -t/--train or -i/--inference options (or both) enabled.\")\n exit(1)\n\n # get the model information from the configuration file\n model_info = get_model_info(model_type, config)\n metrics = {\n 'filename': '',\n 'filedate': '',\n 'time': 0.0,\n 'memory': 0.0,\n 'total_rows': 0,\n 'malicious_rows': 0,\n 'benign_rows': 0,\n 'ratio': 0.0,\n 'categories': 0,\n 'model': 'unknown',\n 'train_rows': 0,\n 'test_rows': 0,\n 'train_time': 0,\n 'inference_rows': 0,\n 'inference_time': 0,\n 'inference_time_mean': 0.0\n }\n\n if train_file != '':\n # a training file was provided\n model_version = get_version_number(train_file)\n\n # get training data from disk\n df, metrics = get_training_data(train_file, metrics, logpath)\n\n if model_type == 'binary':\n X_train, X_test, Y_train, Y_test = prep_training_dataset_binary(df)\n metrics['model'] = model_type\n metrics['categories'] = 2\n metrics['train_rows'] = X_train.shape[0]\n metrics['test_rows'] = X_test.shape[0]\n # pprint(metrics)\n print('info: {} – training started.'.format(time.strftime('%Y-%m-%d %H:%M.%S', time.gmtime())))\n train_model = lstm_binary.LSTMBinary()\n start_time = time.time()\n train_model.train(X_train, Y_train)\n end_time = time.time()\n train_time = end_time - start_time\n metrics['train_time'] = train_time\n print('info: {} – training ended. Train time {:>3.3f}s.'.format(time.strftime('%Y-%m-%d %H:%M.%S', time.gmtime()), train_time))\n write_to_train_logfile(metrics, logpath, True)\n\n train_model.save(model_info['model_tokenizer'],\n model_info['model_json'],\n model_info['model_H5'])\n\n elif model_type == 'multiclass':\n # create X and Y and split into train and test\n X_train, X_test, Y_train, Y_test, categories = prep_training_dataset_multiclass(\n df, model_info['model_categories'])\n metrics['model'] = model_type\n metrics['categories'] = categories\n metrics['train_rows'] = X_train.shape[0]\n metrics['test_rows'] = X_test.shape[0]\n\n print('info: {} – training started.'.format(time.strftime('%Y-%m-%d %H:%M.%S', time.gmtime())))\n start_time = time.time()\n train_model = lstm_multiclass.LSTMMulti()\n train_model.train(X_train, Y_train)\n end_time = time.time()\n train_time = end_time - start_time\n metrics['train_time'] = train_time\n print('info: {} – training ended. Train time {:>3.3f}s.'.format(time.strftime('%Y-%m-%d %H:%M.%S', time.gmtime()), train_time))\n write_to_train_logfile(metrics, logpath, True)\n\n train_model.save(model_info['model_tokenizer'],\n model_info['model_categories'],\n model_info['model_json'],\n model_info['model_H5'])\n else:\n print(\"error: unrecognized model type.\")\n exit(1)\n # train the model (which model is set by models input)\n # train_model.train(X_train, Y_train)\n # train_model.save(TOKENIZER_FILE, MODEL_JSON, MODEL_H5)\n # save the model to disk\n\n if inference_file != '':\n # an inference file was provided\n model_version = get_version_number(inference_file)\n print('inference file: {}'.format(inference_file))\n if model_type == 'binary':\n metrics['filename'] = inference_file\n metrics['filedate'] = time.strftime('%Y-%m-%d', time.gmtime())\n\n predict_model = lstm_binary.LSTMBinary()\n predict_model.load(model_info['model_tokenizer'],\n model_info['model_json'],\n model_info['model_H5'])\n domains = load_inference_data(inference_file)\n # print(\"Number of domains: \", len(domains))\n # print(\"Top 10:\\n\", domains[:10])\n\n # run predictions, record timings\n timestamp = time.strftime('%Y-%m-%d %H:%M.%S', time.gmtime())\n print('info: {} – inference started.'.format(timestamp))\n start_time = time.time()\n predictions = predict_model.predict(domains)\n end_time = time.time()\n prediction_time = end_time - start_time\n domain_count = len(domains)\n metrics['inference_rows'] = domain_count\n metrics['inference_time'] = prediction_time\n metrics['inference_time_mean'] = prediction_time / domain_count\n timestamp = time.strftime('%Y-%m-%d %H:%M.%S', time.gmtime())\n print('info: {} – inference ended. Inference time {:>3.3f}s.'.format(timestamp, prediction_time))\n\n # reshape the predictions\n predictions = np.reshape(predictions, [predictions.shape[0], ]).tolist()\n # print(predictions[:10])\n # print(\"domains: {}, predictions: {}\".format(len(domains), len(predictions)))\n\n # write the predictions to file\n write_predictions(domains, predictions, model_type, model_info['model_algorithm'], model_version, config)\n\n # write_to_train_logfile(metrics, logpath, True)\n elif model_type == 'multiclass':\n metrics['filename'] = inference_file\n metrics['filedate'] = time.strftime('%Y-%m-%d', time.gmtime())\n\n predict_model = lstm_multiclass.LSTMMulti()\n predict_model.load(model_info['model_tokenizer'],\n model_info['model_categories'],\n model_info['model_json'],\n model_info['model_H5'])\n domains = load_inference_data(inference_file)\n # print(\"Number of domains: \", len(domains))\n # print(\"Top 10:\\n\", domains[:10])\n\n # run predictions, record timings\n timestamp = time.strftime('%Y-%m-%d %H:%M.%S', time.gmtime())\n print('info: {} – inference started.'.format(timestamp))\n start_time = time.time()\n predictions, pred_prob = predict_model.predict(domains)\n end_time = time.time()\n prediction_time = end_time - start_time\n domain_count = len(domains)\n metrics['inference_rows'] = domain_count\n metrics['inference_time'] = prediction_time\n metrics['inference_time_mean'] = prediction_time / domain_count\n timestamp = time.strftime('%Y-%m-%d %H:%M.%S', time.gmtime())\n print('info: {} – inference ended. Inference time {:>3.3f}s.'.format(timestamp, prediction_time))\n\n # reshape the predictions\n # predictions = np.reshape(predictions, [predictions.shape[0], ]).tolist()\n # print(predictions[:10])\n # print(\"domains: {}, predictions: {}\".format(len(domains), len(predictions)))\n\n # write the predictions to file\n write_predictions(domains, predictions, model_type, model_info['model_algorithm'], model_version, config)\n else:\n print(\"error: unrecognized model type.\")\n exit(1)\n # get test data\n # load the model (based on models input)\n # testmodel = lstm_binary.LSTMBinary()\n # testmodel.load(BINARY_TOKENIZER_FILE, BINARY_MODEL_JSON, BINARY_MODEL_H5)\n # make predictions\n # urllist = [\"www.google.com\", \"www.netflix.com\", \"plvklpgwivery.com\"]\n # urltypes = testmodel.predict(urllist)\n # print(\"URL type:\", urltypes)\n\n\nif __name__ == '__main__':\n run()\n","sub_path":"code/models/models.py","file_name":"models.py","file_ext":"py","file_size_in_byte":26220,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"148249861","text":"from apiclient.discovery import build\n\n\nDEVELOPER_KEY = \"AIzaSyDngQv_cVeUuk1LMrqwvP0M-8s6XfgqpGs\"\nYOUTUBE_API_SERVICE_NAME = \"youtube\"\nYOUTUBE_API_VERSION = \"v3\"\nyoutube = build(YOUTUBE_API_SERVICE_NAME, YOUTUBE_API_VERSION, developerKey=DEVELOPER_KEY)\nsearch_response = youtube.search().list(\n q='asmr 귀',\n part=\"id,snippet\",\n maxResults=25\n ).execute()\n\nprint(search_response)","sub_path":"startone.py","file_name":"startone.py","file_ext":"py","file_size_in_byte":391,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"179958025","text":"import multiprocessing\r\n\r\ndef myProcFn():\r\n print('Executing child process (with its own GIL)')\r\n\r\ndef main():\r\n print('Executign the main process')\r\n myProc2 = multiprocessing.Process(target=myProcFn)\r\n myProc2.start()\r\n myProc2.join()\r\n print('child process has terminated')\r\n\r\nif __name__ == '__main__':\r\n main()","sub_path":"data/beyondAdvancedPythonApril2021-main/using_processes/p1_proc_fn.py","file_name":"p1_proc_fn.py","file_ext":"py","file_size_in_byte":336,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"289374951","text":"import numpy as np\nfrom matplotlib import pyplot as plt\n\ndef genDataSet(N):\n x = np.random.normal(0, 1, N)\n ytrue = (np.cos(x) + 2) / (np.cos(x * 1.4) + 2)\n noise = np.random.normal(0, 0.2, N)\n y = ytrue + noise\n return x, y, ytrue\n\nx, y, ytrue = genDataSet(100)\nplt.plot(x,y,'.')\nplt.plot(x,ytrue,'rx')\nplt.show()\n","sub_path":"mulligan-03/hw3_1_a_gendata.py","file_name":"hw3_1_a_gendata.py","file_ext":"py","file_size_in_byte":330,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"609220111","text":"########################################\n\nimport os, sys, xbmc, xbmcgui, xbmcplugin, xbmcaddon\n\t\n#Belgique Direct By Sphinxroot QC\n\n# Various constants used throughout the script\nHANDLE = int(sys.argv[1])\nADDON = xbmcaddon.Addon(id='plugin.video.BelgiqueDirect')\nLANGUAGE = ADDON.getLocalizedString\nTHUMBNAIL_PATH = os.path.join( ADDON.getAddonInfo( 'path' ), 'resources', 'media')\n\ndef start() :\n\n\tli = xbmcgui.ListItem(label=LANGUAGE(30000), thumbnailImage=os.path.join(THUMBNAIL_PATH, 'belgique.gif'))\n\txbmcplugin.addDirectoryItem(handle=HANDLE, url=\"https://raw.githubusercontent.com/Sphinxroot/M3U-URL/master/Belgique.fr.m3u\", listitem=li, isFolder=False) \n\tsetViewMode(\"500\")\t\t\n\txbmcplugin.endOfDirectory( HANDLE )\t\t\n\t\ndef setViewMode(id):\n\tif xbmc.getSkinDir() == \"skin.confluence\":\n\t\txbmc.executebuiltin(\"Container.SetViewMode(\" + id + \")\")\n\t\t\t\nstart()","sub_path":"plugin.video.BelgiqueDirect/default.py","file_name":"default.py","file_ext":"py","file_size_in_byte":864,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"14"} +{"seq_id":"113674010","text":"#!/usr/bin/env python3\r\n\r\nimport sys\r\nimport time\r\nimport re\r\nimport filehelper\r\n\r\nargc = len(sys.argv)\r\nargv = sys.argv\r\n\r\nif argc != 4:\r\n print(\"Filters ICS files for events based on regex\")\r\n print(\"Usage: %s
'\n re_list=r'