xszheng2020/the_stack_dedup_python · Datasets at Hugging Face

bddda4c040819b870403559ed00ebaab7190ea8f

679

py

Python

rxsci/internal/utils.py

maki-nage/rxsci

64c9956752cbdd4c65aa9f054b6b28318a056625

[ "MIT" ]

3

2021-05-03T13:40:46.000Z

2022-03-06T07:59:30.000Z

rxsci/internal/utils.py

maki-nage/rxsci

64c9956752cbdd4c65aa9f054b6b28318a056625

[ "MIT" ]

9

2020-10-22T21:08:10.000Z

2021-08-05T09:01:26.000Z

rxsci/internal/utils.py

maki-nage/rxsci

64c9956752cbdd4c65aa9f054b6b28318a056625

[ "MIT" ]

2

2021-01-05T16:48:54.000Z

2021-08-07T12:51:01.000Z

class NotSet(object): """Sentinel value.""" def __eq__(self, other): return self is other def __repr__(self): return 'NotSet' class StateNotSet(object): def __eq__(self, other): return self is other def __repr__(self): return 'NotSet' def value(self): return 0 class StateSet(object): def __eq__(self, other): return self is other def __repr__(self): return 'Set' def value(self): return 1 class StateCleared(object): def __eq__(self, other): return self is other def __repr__(self): return 'Cleared' def value(self): return 2

15.431818

28

0.584683

81

679

4.506173

0.246914

0.191781

0.09863

0.153425

0.608219

0

0.006508

0.32106

679

43

29

15.790698

0.785249

0.022091

0

0.653846

0

0.033537

0

1

0.423077

false

0

0.423077

1

0

null

0

1

0

null

0

1

0

1

0

3

bdde05efcf874ead71f10d44b9b94987c03fce5e

995

py

Python

tests/test_git.py

graycarl/hbk

d4c90807b2558a2b61fb1253d9804fbaf373443f

[ "MIT" ]

1

2021-07-22T05:25:35.000Z

tests/test_git.py

graycarl/hbk

d4c90807b2558a2b61fb1253d9804fbaf373443f

[ "MIT" ]

37

2017-07-27T06:07:25.000Z

2020-12-11T12:57:31.000Z

tests/test_git.py

graycarl/hbk

d4c90807b2558a2b61fb1253d9804fbaf373443f

[ "MIT" ]

1

2019-04-02T08:36:32.000Z

# -*- coding: utf-8 -*- from __future__ import absolute_import, unicode_literals from builtins import * # noqa import pytest from hbkit import libs @pytest.fixture def git_config(): content = \ """ [core] repositoryformatversion = 0 filemode = true bare = false logallrefupdates = true ignorecase = true precomposeunicode = true [remote "origin"] url = https://github.com/graycarl/hbkit.git fetch = +refs/heads/*:refs/remotes/origin/* [remote "other"] url = https://gitlab.com/graycarl/hbkit.git fetch = +refs/heads/*:refs/remotes/origin/* [branch "master"] remote = origin merge = refs/heads/master [branch "Github-Check-CI"] remote = origin merge = refs/heads/Github-Check-CI """ return content def test_iter_remote_from_git_config(git_config): remotes = list(libs.git.iter_remotes_from_git_config(git_config)) expect = [ 'https://github.com/graycarl/hbkit.git', 'https://gitlab.com/graycarl/hbkit.git' ] assert remotes == expect

23.690476

69

0.706533

127

995

5.393701

0.417323

0.065693

0.093431

0.110949

0.405839

0.265693

0.145985

0

0.002398

0.161809

995

41

70

24.268293

0.818945

0.026131

0

0.15914

0

0.066667

1

0.133333

false

0

0.266667

0

0.466667

0

null

0

null

0

1

0

bddf37e95b95085df635e34da4f5fe3ecddbccb0

1,751

py

Python

src/richie/apps/courses/migrations/0013_migrate_data_translated_licence_fields.py

leduong/richie

bf7ed379b7e2528cd790dadcec10ac2656efd189

[ "MIT" ]

174

2018-04-14T23:36:01.000Z

2022-03-10T09:27:01.000Z

src/richie/apps/courses/migrations/0013_migrate_data_translated_licence_fields.py

leduong/richie

bf7ed379b7e2528cd790dadcec10ac2656efd189

[ "MIT" ]

631

2018-04-04T11:28:53.000Z

2022-03-31T11:18:31.000Z

src/richie/apps/courses/migrations/0013_migrate_data_translated_licence_fields.py

leduong/richie

bf7ed379b7e2528cd790dadcec10ac2656efd189

[ "MIT" ]

64

2018-06-27T08:35:01.000Z

2022-03-10T09:27:43.000Z

# Generated by Django 2.2.8 on 2020-01-02 13:56 from django.conf import settings from django.core.exceptions import ObjectDoesNotExist from django.db import migrations def forwards_func(apps, schema_editor): Licence = apps.get_model("courses", "Licence") LicenceTranslation = apps.get_model("courses", "LicenceTranslation") for licence in Licence.objects.all(): LicenceTranslation.objects.create( master_id=licence.pk, language_code=settings.LANGUAGE_CODE, name=licence.name_deprecated, ) def backwards_func(apps, schema_editor): Licence = apps.get_model("courses", "Licence") LicenceTranslation = apps.get_model("courses", "LicenceTranslation") for licence in Licence.objects.all(): translation = _get_translation(licence, LicenceTranslation) licence.name_deprecated = translation.name licence.save() # Note this only calls Model.save() def _get_translation(licence, LicenceTranslation): translations = LicenceTranslation.objects.filter(master_id=licence.pk) try: # Try default translation return translations.get(language_code=settings.LANGUAGE_CODE) except ObjectDoesNotExist: try: # Try default language return translations.get(language_code=settings.PARLER_DEFAULT_LANGUAGE_CODE) except ObjectDoesNotExist: # Maybe the object was translated only in a specific language? # Take the first existing translation return translations.first() class Migration(migrations.Migration): dependencies = [("courses", "0012_add_translation_model_for_licence_fields")] operations = [migrations.RunPython(forwards_func, backwards_func)]

35.02

88

0.718447

191

1,751

6.418848

0.39267

0.058728

0.039152

0.06199

0.326264

0.290375

0.223491

0

0.013542

0.198744

1,751

49

89

35.734694

0.860299

0.126214

0

0.322581

1

0

0.085358

0.029547

0

1

0.096774

false

0

0.096774

0

0.387097

0

null

0

1

0

null

0

1

bddf54c37693012c2ebee8e890c2bc5f10dfd58d

5,510

py

Python

responsible_ai/gan_data_debiased/main.py

AaratiAkkapeddi/nnabla-examples

db9e5ad850303c158773aeb275e5c3821b4a3935

[ "Apache-2.0" ]

null

responsible_ai/gan_data_debiased/main.py

AaratiAkkapeddi/nnabla-examples

db9e5ad850303c158773aeb275e5c3821b4a3935

[ "Apache-2.0" ]

null

responsible_ai/gan_data_debiased/main.py

AaratiAkkapeddi/nnabla-examples

db9e5ad850303c158773aeb275e5c3821b4a3935

[ "Apache-2.0" ]

null

# Copyright 2022 Sony Group Corporation. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os import sys from nnabla.ext_utils import get_extension_context import nnabla as nn import args import data_loader as dl import classifier as clf from utils import utils def model_train_setting(opt): """ Get the model train settings Args: opt : variables that containing values for all of your options Returns: variables which you need to train """ attr_list = utils.get_all_attr() if opt['model_train'] == 'baseline': data_params = { "train_beg": opt['train_beg'], "valid_beg": opt['valid_beg'], "test_beg": opt['test_beg'], } data_setting = { 'path': opt['base_img_path'], 'protected_attribute': opt['protected_attribute'], 'attribute': opt['attribute'], 'data_params': data_params, 'batch_size': opt['batch_size'], 'learning_rate': opt['learning_rate'], 'max_iter': opt['max_iter_base'] } opt['data_setting'] = data_setting if opt['model_train'] == 'gan_debiased': data_params = { "train_beg": opt['train_beg'], "valid_beg": opt['valid_beg'], "test_beg": opt['test_beg'], } real_params = { 'path': opt['base_img_path'], 'attribute': opt['attribute'], 'protected_attribute': opt['protected_attribute'], 'data_params': data_params } generated_images = "{}/AllGenImages".format(opt["fake_data_dir"]) flipped_images = "{}/{}/".format(opt["fake_data_dir"], attr_list[opt['attribute']]) label_score = "{}/all_{}_scores.pkl".format(opt['fake_data_dir'], attr_list[opt['attribute']]) domain_score = "{}/all_{}_scores.pkl".format(opt['fake_data_dir'], attr_list[opt['protected_attribute']]) generated_params = { 'generated_image_path': generated_images, 'flipped_images_path': flipped_images, 'label_path': label_score, 'domain_path': domain_score, # flipped the images from 15000 to 175000 'flipped_image_range': (15000, 175000), 'orig_label_range': (160000, 320000), # original label range 'new_range': (0, 160000), # new images } data_setting = { 'real_params': real_params, 'gen_params': generated_params, 'batch_size': opt['batch_size'], 'learning_rate': opt['learning_rate'], 'max_iter': opt['max_iter_gan_debiased'] } opt['data_setting'] = data_setting return opt def main(): """ main method """ opt = args.get_args() opt = model_train_setting(opt) ctx = get_extension_context( opt['context'], device_id=opt['device_id'], type_config=opt['type_config']) nn.set_default_context(ctx) # model configurations batch_size = opt['data_setting']['batch_size'] learning_rate = opt['data_setting']['learning_rate'] max_iter = opt['data_setting']['max_iter'] if (opt["model_train"] == 'baseline'): train = dl.actual_celeba_dataset(opt['data_setting'], batch_size, augment=True, split='train', shuffle=True) val = dl.actual_celeba_dataset(opt['data_setting'], batch_size, augment=False, split='valid', shuffle=False) val_weight = None elif (opt["model_train"] == 'gan_debiased'): train = dl.debiased_celeba_dataset(opt['data_setting'], batch_size, augment=True, split='train', shuffle=True) val = dl.actual_celeba_dataset(opt['data_setting']['real_params'], batch_size, augment=False, split='valid', shuffle=False) val_weight = utils.compute_class_weight(val) else: print("please provide proper argument") sys.exit(0) attr_list = utils.get_all_attr() if not os.path.exists(opt['model_save_path']): os.makedirs(opt['model_save_path']) monitor_path = os.path.join( opt['model_save_path'], attr_list[opt['attribute']]) if not os.path.exists(monitor_path): os.makedirs(monitor_path) attribute_classifier_model = clf.attribute_classifier(batch_size=batch_size, learning_rate=learning_rate, max_iter=max_iter, monitor_path=monitor_path, val_weight=val_weight) attribute_classifier_model.train(train, val) if __name__ == '__main__': main()

38.531469

91

0.580581

622

5,510

4.853698

0.287781

0.047367

0.041736

0.027824

0.398145

0.262007

0.245446

0.229215

0

0.013089

0.306715

5,510

142

92

38.802817

0.777225

0.147913

0

0.294118

0

0.229275

0.004534

0

1

0.019608

false

0

0.078431

0

0.107843

0.009804

0

null

0

null

0

1

0

bde0ad9f17012d7ebc6ee66313fe41b54189ab35

5,109

py

Python

hstools/utilities.py

saisiddu/pub_bandaragoda_etal_ems

d06e23c7c5dfa772d5dfe55c33bcf7abbd5e2060

[ "MIT" ]

1

2019-09-24T15:22:05.000Z

hstools/utilities.py

saisiddu/pub_bandaragoda_etal_ems

d06e23c7c5dfa772d5dfe55c33bcf7abbd5e2060

[ "MIT" ]

null

hstools/utilities.py

saisiddu/pub_bandaragoda_etal_ems

d06e23c7c5dfa772d5dfe55c33bcf7abbd5e2060

[ "MIT" ]

null

from __future__ import print_function import os from IPython.core.display import display, HTML import glob from .compat import * def sizeof_fmt(num, suffix='B'): for unit in ['', 'Ki', 'Mi', 'Gi', 'Ti', 'Pi', 'Ei', 'Zi']: if abs(num) < 1024.0: return "%3.1f%s%s" % (num, unit, suffix) num /= 1024.0 return "%.1f%s%s" % (num, 'Yi', suffix) def get_hs_content(resid): resdir = find_resource_directory(resid) content = {} for f in glob.glob('%s/*/data/contents/*' % resdir): fname = os.path.basename(f) content[fname] = f return content def find_resource_directory(resid): download_dir = os.environ.get('JUPYTER_DOWNLOADS', 'hs_downloads') # loop over all the files in userspace for dirpath, dirnames, filenames in os.walk(download_dir): for dirname in [d for d in dirnames]: if dirname == resid: return os.path.join(dirpath, dirname) return None def check_for_ipynb(content_files): links = {} for f, p in content_files.items(): if f[-5:] == 'ipynb': fname = os.path.basename(p) url = urlencode(p) links[fname] = url return links def display_tree(resid): # todo: display a tree view of the resource bagit, based on id pass def display_resource_content_files(content_file_dictionary, text='Found the following content when parsing the HydroShare resource:'): # get ipynb files nbs = check_for_ipynb(content_file_dictionary) if len(nbs.keys()) > 0: display(HTML('<b>Found the following notebook(s) associated with this HydroShare resource.</b><br>Click the link(s) below to launch the notebook.')) for name, url in nbs.items(): display(HTML('<a href=%s target="_blank">%s<a>' % (url, name))) # print the remaining files if len(content_file_dictionary.keys()) > 0: display(HTML('<b>Found the following file(s) associated with this HydroShare resource.</b>')) text = '<br>'.join(content_file_dictionary.keys()) display(HTML(text)) if (len(content_file_dictionary.keys()) + len(nbs.keys())) > 0: display(HTML('These files are stored in a dictionary called <b>hs.content</b> for your convenience. To access a file, simply issue the following command where MY_FILE is one of the files listed above: <pre>hs.content["MY_FILE"] </pre> ')) def load_environment(env_path=None): # load the environment path (if it exists) if env_path is None: env_path = os.path.join(os.environ.get('NOTEBOOK_HOME', './'), '.env' ) if not os.path.exists(env_path): return with open(env_path, 'r') as f: lines = f.readlines() print('Adding the following system variables:') for line in lines: k, v = line.strip().split('=') os.environ[k] = v print(' %s = %s' % (k, v)) print('\nThese can be accessed using the following command: ') print(' os.environ[key]') print('\n (e.g.)\n os.environ["HS_USR_NAME"] => %s' % os.environ['HS_USR_NAME']) def get_env_var(varname): if varname in os.environ.keys(): return os.environ[varname] else: return input('Could not find %s, please specify a value: ' % varname).strip() def get_server_url_for_path(p): """ gets the url corresponding to a given file or directory path p : path to convert into a url returns the url path for the filepath p """ load_environment() rel_path = os.path.relpath(p, os.environ['NOTEBOOK_HOME']) url = urlencode(rel_path) return url def get_relative_path(p): """ gets the path relative to the jupyter home directory p: path to convert into relative path returns the path relative to the default jupyter home directory """ return os.path.relpath(p, os.environ['NOTEBOOK_HOME']) def _realname(path, root=None): if root is not None: path = os.path.join(root, path) result = os.path.basename(path) if os.path.islink(path): realpath = os.readlink(path) result = '%s -> %s' % (os.path.basename(path), realpath) return result def tree(startpath, depth=-1): prefix = 0 if startpath != '/': if startpath.endswith('/'): startpath = startpath[:-1] prefix = len(startpath) for root, dirs, files in os.walk(startpath): level = root[prefix:].count(os.sep) if depth > -1 and level > depth: continue indent = subindent = '' if level > 0: indent = '| ' * (level-1) + '|-- ' subindent = '| ' * (level) + '|-- ' print('{}{}/'.format(indent, _realname(root))) # print dir only if symbolic link; otherwise, will be printed as root for d in dirs: if os.path.islink(os.path.join(root, d)): print('{}{}'.format(subindent, _realname(d, root=root))) for f in files: print('{}{}'.format(subindent, _realname(f, root=root)))

30.963636

247

0.607164

702

5,109

4.323362

0.294872

0.0257

0.034596

0.015815

0.135091

0.098188

0.070511

0.04547

0

0.006094

0.261304

5,109

164

248

31.152439

0.798092

0.106087

0

0.019417

0.204873

0.020819

0

0.006098

0

1

0.116505

false

0.009709

0.048544

0

0.281553

0.087379

0

null

0

null

0

1

0

bde1d05ede2b3e57e640969726cd7f09fb8e5559

155

py

Python

assignment2/earth_electrons.py

guozhonghao1994/ec602

e8f6b61e5cdad64e9fe943fc4f61d1fc9ad85f74

[ "Unlicense" ]

3

2018-11-14T16:07:31.000Z

2018-11-15T16:44:51.000Z

assignment2/earth_electrons.py

guozhonghao1994/ec602

e8f6b61e5cdad64e9fe943fc4f61d1fc9ad85f74

[ "Unlicense" ]

null

assignment2/earth_electrons.py

guozhonghao1994/ec602

e8f6b61e5cdad64e9fe943fc4f61d1fc9ad85f74

[ "Unlicense" ]

null

17.222222

43

0.754839

30

155

3.9

0.666667

0.102564

0

0.205674

0.090323

155

8

44

19.375

0.624113

0.270968

0

1

0

false

0

0.142857

0

0.142857

0.428571

0

null

0

1

0

1

0

null

0

1

0

3

bde5bd2cb3f7fdf8cc6f96a4c93e07d27f29156e

16,286

py

Python

activity/activity_IngestDigestToEndpoint.py

elifesciences/elife-bot

d3a102c8030e4b7ec83cbd45e5f839dba4f9ffd9

[ "MIT" ]

17

2015-02-10T07:10:29.000Z

2021-05-14T22:24:45.000Z

activity/activity_IngestDigestToEndpoint.py

elifesciences/elife-bot

d3a102c8030e4b7ec83cbd45e5f839dba4f9ffd9

[ "MIT" ]

459

2015-03-31T18:24:23.000Z

2022-03-30T19:44:40.000Z

activity/activity_IngestDigestToEndpoint.py

elifesciences/elife-bot

d3a102c8030e4b7ec83cbd45e5f839dba4f9ffd9

[ "MIT" ]

9

2015-04-18T16:57:31.000Z

2020-10-30T11:49:13.000Z

import os import time import json from collections import OrderedDict from digestparser import json_output from provider.execution_context import get_session from provider.article_processing import download_jats from provider import digest_provider, email_provider, lax_provider, utils from activity.objects import Activity class activity_IngestDigestToEndpoint(Activity): def __init__(self, settings, logger, conn=None, token=None, activity_task=None): super(activity_IngestDigestToEndpoint, self).__init__( settings, logger, conn, token, activity_task ) self.name = "IngestDigestToEndpoint" self.pretty_name = "Ingest Digest to API endpoint" self.version = "1" self.default_task_heartbeat_timeout = 30 self.default_task_schedule_to_close_timeout = 60 * 5 self.default_task_schedule_to_start_timeout = 30 self.default_task_start_to_close_timeout = 60 * 5 self.description = ( "Send Digest JSON to an API endpoint," + " to be run when a research article is ingested" ) # Local directory settings self.directories = { "TEMP_DIR": os.path.join(self.get_tmp_dir(), "tmp_dir"), "INPUT_DIR": os.path.join(self.get_tmp_dir(), "input_dir"), } # Track the success of some steps self.statuses = OrderedDict( [ ("approve", None), ("download", None), ("generate", None), ("ingest", None), ] ) # Digest JSON content self.digest_content = None # Load the config self.digest_config = digest_provider.digest_config( self.settings.digest_config_section, self.settings.digest_config_file ) def do_activity(self, data=None): self.logger.info("data: %s" % json.dumps(data, sort_keys=True, indent=4)) success, run, session, article_id, version = self.session_data(data) self.make_activity_directories() # get session data if success is not True: self.logger.error("Failed to parse session data in %s" % self.pretty_name) return self.ACTIVITY_PERMANENT_FAILURE # emit start message success = self.emit_start_message(article_id, version, run) if success is not True: self.logger.error("Failed to emit a start message in %s" % self.pretty_name) return self.ACTIVITY_PERMANENT_FAILURE # Approve for ingestion self.statuses["approve"] = self.approve( article_id, session.get_value("status"), version, session.get_value("run_type"), ) if self.statuses.get("approve") is not True: self.logger.info( "Digest for article %s was not approved for ingestion" % article_id ) self.emit_end_message(article_id, version, run) return self.ACTIVITY_SUCCESS try: digest_details = self.gather_digest_details( article_id, version, session.get_value("expanded_folder") ) except Exception as exception: # send email error if any error message is returned message = "Error in gathering digest details: %s" % str(exception) self.logger.exception(message) return self.email_error_return(article_id, message) # generate the digest content try: self.digest_content = self.generate_digest_content( article_id, digest_details ) except Exception as exception: # send email error if unable to generate digest content message = "Error in generating digest content for article: %s" % str( exception ) self.logger.exception(message) return self.email_error_return(article_id, message) # issue put to the endpoint digest_id = self.digest_content.get("id") # set the stage attribute depending on silent correction or not if ( session.get_value("run_type") and session.get_value("run_type") == "silent-correction" ): digest_provider.set_stage(self.digest_content, "published") else: digest_provider.set_stage(self.digest_content, "preview") self.logger.info( "Digest stage value %s" % str(self.digest_content.get("stage")) ) try: put_response = digest_provider.put_digest_to_endpoint( self.logger, digest_id, self.digest_content, self.settings ) if put_response: self.statuses["ingest"] = True except Exception as exception: # email error message and return self.ACTIVITY_SUCCESS message = "Failed to ingest digest json to endpoint %s in %s: %s" % ( article_id, self.pretty_name, str(exception), ) self.logger.exception(message) return self.email_error_return(article_id, message) self.logger.info( "%s for article_id %s statuses: %s" % (self.name, str(article_id), self.statuses) ) self.emit_end_message(article_id, version, run) return self.ACTIVITY_SUCCESS def session_data(self, data): "get session data and return basic values" run = None session = None version = None article_id = None success = None try: run = data["run"] session = get_session(self.settings, data, run) version = session.get_value("version") article_id = session.get_value("article_id") success = True except (TypeError, KeyError) as exception: self.logger.exception( "Exception when getting the session for Starting ingest digest " + " to endpoint. Details: %s" % str(exception) ) return success, run, session, article_id, version def email_error_return(self, article_id, message): """log exception, email error message and return activity result""" send_error_email(article_id, message, self.settings, self.logger) return self.ACTIVITY_SUCCESS def emit_message(self, article_id, version, run, status, message): "emit message to the queue" try: self.emit_monitor_event( self.settings, article_id, version, run, self.pretty_name, status, message, ) return True except Exception as exception: self.logger.exception( "Exception emitting %s message. Details: %s" % (str(status), str(exception)) ) def emit_start_message(self, article_id, version, run): "emit the start message to the queue" return self.emit_message( article_id, version, run, "start", "Starting ingest digest to endpoint for " + str(article_id), ) def digest_preview_link(self, article_id): "preview link for the digest using the preview base url" return "%s/digests/%s" % ( self.settings.journal_preview_base_url, utils.pad_msid(article_id), ) def activity_end_message(self, article_id, statuses): "different end message to emit based on the ingest status" if statuses.get("ingest") is True: return ( "Finished ingest digest to endpoint for %s. Statuses %s Preview link %s" % (article_id, statuses, self.digest_preview_link(article_id)) ) return "No digest ingested for %s. Statuses %s" % (article_id, statuses) def emit_end_message(self, article_id, version, run): "emit the end message to the queue" return self.emit_message( article_id, version, run, "end", self.activity_end_message(article_id, self.statuses), ) def emit_error_message(self, article_id, version, run, message): "emit an error message to the queue" return self.emit_message(article_id, version, run, "error", message) def approve(self, article_id, status, version, run_type): "should we ingest based on some basic attributes" approve_status = True # check by status return_status = digest_provider.approve_by_status( self.logger, article_id, status ) if return_status is False: approve_status = return_status # check silent corrections and consider the first vor version run_type_status = digest_provider.approve_by_run_type( self.settings, self.logger, article_id, run_type, version ) first_vor_status = digest_provider.approve_by_first_vor( self.settings, self.logger, article_id, version, status ) if first_vor_status is False and run_type != "silent-correction": # not the first vor and not a silent correction, do not approve approve_status = False elif run_type_status is False: # otherwise depend on the silent correction run_type logic approve_status = False # check if there is a digest docx in the bucket for this article if approve_status: if not digest_provider.docx_exists_in_s3( self.settings, article_id, self.settings.bot_bucket, self.logger ): self.logger.info( "Digest docx file does not exist in S3 for article %s" % article_id ) approve_status = False return approve_status def gather_digest_details(self, article_id, version, expanded_folder): digest_details = OrderedDict() # Download digest from the S3 outbox digest_details["docx_file"] = digest_download_docx_from_s3( article_id, self.settings.bot_bucket, self.directories.get("INPUT_DIR"), self.settings, self.logger, ) self.statuses["download"] = True # find the image file name digest_details["image_file"] = digest_image_file_name_from_s3( article_id, self.settings.bot_bucket, self.settings ) # download jats file digest_details["jats_file"] = download_jats_for_digest( expanded_folder, self.settings, self.directories.get("TEMP_DIR"), self.logger, ) # related article data digest_details["related"] = get_related_from_lax( article_id, version, self.settings, self.pretty_name, self.logger ) return digest_details def generate_digest_content(self, article_id, digest_details): digest_content = None try: digest_content = self.digest_json( digest_details.get("docx_file"), digest_details.get("jats_file"), digest_details.get("image_file"), digest_details.get("related"), ) except Exception as exception: # email error message and return self.ACTIVITY_SUCCESS message = "Failed to generate digest json for %s in %s: %s" % ( article_id, self.pretty_name, str(exception), ) raise Exception(message) if digest_content: self.statuses["generate"] = True else: # email error message and return self.ACTIVITY_SUCCESS message = ( "Unable to generate Digest content for docx_file %s, " + "jats_file %s, image_file %s" ) % ( digest_details.get("docx_file"), digest_details.get("jats_file"), digest_details.get("image_file"), ) raise Exception(message) return digest_content def digest_json(self, docx_file, jats_file=None, image_file=None, related=None): "generate the digest json content from the docx file and other data" json_content = None try: json_content = json_output.build_json( docx_file, self.directories.get("TEMP_DIR"), self.digest_config, jats_file, image_file, related, ) except Exception as exception: self.logger.exception( "Exception generating digest json for docx_file %s. Details: %s" % (str(docx_file), str(exception)) ) return json_content def digest_download_docx_from_s3(article_id, bucket_name, input_dir, settings, logger): try: return digest_provider.download_docx_from_s3( settings, article_id, bucket_name, input_dir, logger ) except Exception as exception: message = "Unable to download digest docx file for article %s: %s" % ( article_id, str(exception), ) raise Exception(message) def digest_image_file_name_from_s3(article_id, bucket_name, settings): try: return digest_provider.image_file_name_from_s3( settings, article_id, bucket_name ) except Exception as exception: message = "Failed to get image file name from S3 for digest %s: %s" % ( article_id, str(exception), ) raise Exception(message) def download_jats_for_digest(expanded_folder, settings, temp_dir, logger): try: return download_jats(settings, expanded_folder, temp_dir, logger) except Exception as exception: message = "Failed to download JATS from expanded folder %s: %s" % ( expanded_folder, str(exception), ) raise Exception(message) def get_related_from_lax(article_id, version, settings, pretty_name, logger): try: return related_from_lax(article_id, version, settings, logger) except Exception as exception: message = "Failed to get related from lax for digest %s in %s: %s" % ( article_id, pretty_name, str(exception), ) raise Exception(message) def related_from_lax(article_id, version, settings, logger=None, auth=True): "get article json from Lax and return as a list of related data" related = None related_json = None try: related_json = lax_provider.article_snippet(article_id, version, settings, auth) except Exception as exception: logger.exception( ( "Exception in getting article snippet from Lax for article_id" " %s, version %s. Details: %s" ) % (str(article_id), str(version), str(exception)) ) raise if related_json: related = [related_json] return related def error_email_subject(article_id): "email subject for an error email" return u"Error ingesting digest to endpoint: {article_id}".format( article_id=article_id ) def send_error_email(article_id, message, settings, logger): "email error message to the recipients" datetime_string = time.strftime(utils.DATE_TIME_FORMAT, time.gmtime()) body = email_provider.simple_email_body(datetime_string, message) subject = error_email_subject(article_id) sender_email = settings.digest_sender_email recipient_email_list = email_provider.list_email_recipients( settings.digest_validate_error_recipient_email ) messages = email_provider.simple_messages( sender_email, recipient_email_list, subject, body, logger=logger ) logger.info("Formatted %d email error messages" % len(messages)) details = email_provider.smtp_send_messages(settings, messages, logger) logger.info("Email sending details: %s" % str(details))

36.191111

88

0.608805

1,860

16,286

5.109677

0.12043

0.063447

0.035354

0.021991

0.384785

0.306923

0.246107

0.202757

0.140257

0.126368

0

0.001973

0.315179

16,286

449

89

36.271715

0.850175

0.09106

0

0.277473

0

0.148821

0.001437

0

1

0.057692

false

0

0.024725

0

0.156593

0

null

0

null

0

1

0

bde6c2d4e221af5daf9ceb3a165e32e65089ccfe

249

py

Python

utils/forgiveness_of_the_offender.py

bbt-t/simple-bot_discord

46fa629e8278e8e453b3c272b2e838d0762aaaf8

[ "MIT" ]

null

utils/forgiveness_of_the_offender.py

bbt-t/simple-bot_discord

46fa629e8278e8e453b3c272b2e838d0762aaaf8

[ "MIT" ]

null

utils/forgiveness_of_the_offender.py

bbt-t/simple-bot_discord

46fa629e8278e8e453b3c272b2e838d0762aaaf8

[ "MIT" ]

null

from discord import Member, utils async def unmute_user(member: Member): role = utils.get(member.guild.roles, id=809817869914341396) await member.edit(roles=()) await member.add_roles(role) await member.send('Ты размучен! :)')

19.153846

63

0.706827

33

249

5.272727

0.636364

0.189655

0

0.087379

0.172691

249

12

64

20.75

0.757282

0

0.060484

0

1

0

false

0

0.166667

0

0.166667

0

null

0

null

0

1

0

bde798fb51621c003debde76678c82dcde2604d3

443

py

Python

mailing/urls.py

Aladom/django-mailing

aa18963b1902e4b7f066b0064a832e26e725f643

[ "MIT" ]

null

mailing/urls.py

Aladom/django-mailing

aa18963b1902e4b7f066b0064a832e26e725f643

[ "MIT" ]

13

2016-02-04T14:56:11.000Z

2021-06-10T20:39:51.000Z

mailing/urls.py

Aladom/django-mailing

aa18963b1902e4b7f066b0064a832e26e725f643

[ "MIT" ]

null

# -*- coding: utf-8 -*- from django.conf.urls import url from .views import MirrorView, SubscriptionsManagementView __all__ = [ 'app_name', 'urlpatterns', ] app_name = 'mailing' urlpatterns = [ url(r'^mirror/(?P<signed_pk>[0-9]+:[a-zA-Z0-9_-]+)/$', MirrorView.as_view(), name='mirror'), url(r'^subscriptions/(?P<signed_email>.+:[a-zA-Z0-9_-]+)/$', SubscriptionsManagementView.as_view(), name='subscriptions'), ]

26.058824

69

0.643341

54

443

5.055556

0.574074

0.051282

0.03663

0.043956

0

0.01847

0.14447

443

16

70

27.6875

0.701847

0.047404

0

0.340476

0.233333

0

1

0

false

0

0.166667

0

0.166667

0

null

0

null

0

1

0

bdea2dca87fdb221f4d7b5d7f20709164e7c3a60

1,029

py

Python

code2/day07/demo03.py

picktsh/python

0f758dcdf9eee3580d8f6e2241ef557b6320ef54

[ "MIT" ]

1

2019-12-31T16:44:06.000Z

code2/day07/demo03.py

picktsh/python

0f758dcdf9eee3580d8f6e2241ef557b6320ef54

[ "MIT" ]

null

code2/day07/demo03.py

picktsh/python

0f758dcdf9eee3580d8f6e2241ef557b6320ef54

[ "MIT" ]

1

2022-01-13T10:32:22.000Z

# 引入requests import requests # 封装headers headers = { 'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_13_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/71.0.3578.98 Safari/537.36'} # 写入网址 url = 'https://www.zhihu.com/api/v4/members/zhang-jia-wei/articles?' # 封装参数 params = { 'include': 'data[*].comment_count,suggest_edit,is_normal,thumbnail_extra_info,thumbnail,can_comment,comment_permission,admin_closed_comment,content,voteup_count,created,updated,upvoted_followees,voting,review_info,is_labeled,label_info;data[*].author.badge[?(type=best_answerer)].topics', 'offset': '10', 'limit': '10', 'sort_by': 'voteups', } # 发送请求，并把响应内容赋值到变量res里面 res = requests.get(url, headers=headers, params=params) # 确认请求成功，即这个response对象状态正确 print(res.status_code) # 用json()方法解析response对象，并赋值给变量articles articles = res.json() # 打印这个json文件 print(articles) # 取出键为data的值 data = articles['data'] # 遍历列表，拿到的是列表里的每一个元素，这些元素都是字典，再通过键把值取出来 for i in data: print(i['title']) print(i['url']) print(i['excerpt'])

32.15625

292

0.739553

140

1,029

5.3

0.742857

0.024259

0

0.033659

0.104956

1,029

31

293

33.193548

0.771987

0.169096

0

0.157895

0.614929

0.324645

0

1

0

false

0

0.052632

0

0.052632

0.263158

0

null

0

1

0

null

0

1

bdeb63bd228672aa0d61f1e5f7d0335e8f073585

12,597

py

Python

pykit/codegen/llvm/llvm_codegen.py

ContinuumIO/pyk

1730d7b831e0cf12a641ac23b5cf03e17e0dc550

[ "BSD-3-Clause" ]

9

2015-06-23T00:13:49.000Z

2022-02-23T02:46:43.000Z

pykit/codegen/llvm/llvm_codegen.py

ContinuumIO/pyk

1730d7b831e0cf12a641ac23b5cf03e17e0dc550

[ "BSD-3-Clause" ]

1

2017-08-30T08:13:12.000Z

2017-08-31T06:36:32.000Z

pykit/codegen/llvm/llvm_codegen.py

ContinuumIO/pyk

1730d7b831e0cf12a641ac23b5cf03e17e0dc550

[ "BSD-3-Clause" ]

7

2015-05-08T10:17:47.000Z

2021-04-01T15:00:57.000Z

from functools import partial from pykit.ir import vvisit, ArgLoader, verify_lowlevel from pykit.ir import defs, opgrouper from pykit.types import Boolean, Integral, Real, Pointer, Function, Int64 from pykit.codegen.llvm.llvm_types import llvm_type import llvm.core as lc from llvm.core import Type, Constant #===------------------------------------------------------------------=== # Definitions #===------------------------------------------------------------------=== compare_float = { '>': lc.FCMP_OGT, '<': lc.FCMP_OLT, '==': lc.FCMP_OEQ, '>=': lc.FCMP_OGE, '<=': lc.FCMP_OLE, '!=': lc.FCMP_ONE, } compare_signed_int = { '>': lc.ICMP_SGT, '<': lc.ICMP_SLT, '==': lc.ICMP_EQ, '>=': lc.ICMP_SGE, '<=': lc.ICMP_SLE, '!=': lc.ICMP_NE, } compare_unsiged_int = { '>': lc.ICMP_UGT, '<': lc.ICMP_ULT, '==': lc.ICMP_EQ, '>=': lc.ICMP_UGE, '<=': lc.ICMP_ULE, '!=': lc.ICMP_NE, } compare_bool = { '==' : lc.ICMP_EQ, '!=' : lc.ICMP_NE } # below based on from npm/codegen def integer_invert(builder, val): return builder.xor(val, Constant.int_signextend(val.type, -1)) def integer_usub(builder, val): return builder.sub(Constant.int(val.type, 0), val) def integer_not(builder, value): return builder.icmp(lc.ICMP_EQ, value, Constant.int(value.type, 0)) def float_usub(builder, val): return builder.fsub(Constant.real(val.type, 0), val) def float_not(builder, val): return builder.fcmp(lc.FCMP_OEQ, val, Constant.real(val.type, 0)) binop_int = { '+': (lc.Builder.add, lc.Builder.add), '-': (lc.Builder.sub, lc.Builder.sub), '*': (lc.Builder.mul, lc.Builder.mul), '/': (lc.Builder.sdiv, lc.Builder.udiv), '//': (lc.Builder.sdiv, lc.Builder.udiv), '%': (lc.Builder.srem, lc.Builder.urem), '&': (lc.Builder.and_, lc.Builder.and_), '|': (lc.Builder.or_, lc.Builder.or_), '^': (lc.Builder.xor, lc.Builder.xor), '<<': (lc.Builder.shl, lc.Builder.shl), '>>': (lc.Builder.ashr, lc.Builder.lshr), } binop_float = { '+': lc.Builder.fadd, '-': lc.Builder.fsub, '*': lc.Builder.fmul, '/': lc.Builder.fdiv, '//': lc.Builder.fdiv, '%': lc.Builder.frem, } unary_bool = { '!': integer_not, } unary_int = { '~': integer_invert, '!': integer_not, "+": lambda builder, arg: arg, "-": integer_usub, } unary_float = { '!': float_not, "+": lambda builder, arg: arg, "-": float_usub, } #===------------------------------------------------------------------=== # Utils #===------------------------------------------------------------------=== i1, i16, i32, i64 = map(Type.int, [1, 16, 32, 64]) def const_int(type, value): return Constant.int(type, value) const_i32 = partial(const_int, i32) const_i64 = partial(const_int, i64) zero = partial(const_int, value=0) one = partial(const_int, value=1) def sizeof(builder, ty, intp): ptr = Type.pointer(ty) null = Constant.null(ptr) offset = builder.gep(null, [Constant.int(Type.int(), 1)]) return builder.ptrtoint(offset, intp) #===------------------------------------------------------------------=== # Translator #===------------------------------------------------------------------=== class Translator(object): """ Translate a function in low-level form. This means it can only use values of type Bool, Int, Float, Struct or Pointer. Values of type Function may be called. """ def __init__(self, func, env, lfunc, llvm_typer, llvm_module): self.func = func self.env = env self.lfunc = lfunc self.llvm_type = llvm_typer self.lmod = llvm_module self.builder = None self.phis = [] # [pykit_phi] def blockswitch(self, newblock): if not self.builder: self.builder = lc.Builder.new(newblock) self.builder.position_at_end(newblock) # __________________________________________________________________ def op_arg(self, arg): return self.lfunc.args[self.func.args.index(arg)] # __________________________________________________________________ def op_unary(self, op, arg): opmap = { Boolean: unary_bool, Integral: unary_int, Real: unary_float }[type(op.type)] unop = defs.unary_opcodes[op.opcode] return opmap[unop](self.builder, arg) def op_binary(self, op, left, right): binop = defs.binary_opcodes[op.opcode] if op.type.is_int: genop = binop_int[binop][op.type.unsigned] else: genop = binop_float[binop] return genop(self.builder, left, right, op.result) def op_compare(self, op, left, right): cmpop = defs.compare_opcodes[op.opcode] type = op.args[0].type if type.is_int and type.unsigned: cmp, lop = self.builder.icmp, compare_unsiged_int[cmpop] elif type.is_int or type.is_bool: cmp, lop = self.builder.icmp, compare_signed_int[cmpop] else: cmp, lop = self.builder.fcmp, compare_float[cmpop] return cmp(lop, left, right, op.result) # __________________________________________________________________ def op_convert(self, op, arg): from llpython.byte_translator import LLVMCaster unsigned = op.type.is_int and op.type.unsigned # The float cast doens't accept this keyword argument kwds = {'unsigned': unsigned} if unsigned else {} return LLVMCaster.build_cast(self.builder, arg, self.llvm_type(op.type), **kwds) # __________________________________________________________________ def op_call(self, op, function, args): # Get the callee LLVM function from the cache. This is put there by # pykit.codegen.codegen cache = self.env["codegen.cache"] lfunc = cache[function] return self.builder.call(lfunc, args) def op_call_math(self, op, name, args): # Math is resolved by an LLVM postpass argtypes = [arg.type for arg in args] lfunc_type = self.llvm_type(Function(op.type, argtypes)) lfunc = self.lmod.get_or_insert_function( lfunc_type, 'pykit.math.%s.%s' % (map(str, argtypes), name.lower())) return self.builder.call(lfunc, args, op.result) # __________________________________________________________________ def op_getfield(self, op, struct, attr): index = const_i32(op.type.names.index(attr)) return self.builder.extract_value(struct, index, op.result) def op_setfield(self, op, struct, attr, value): index = const_i32(op.type.names.index(attr)) return self.builder.insert_element(struct, value, index, op.result) # __________________________________________________________________ def op_getindex(self, op, array, indices): return self.builder.gep(array, indices, op.result) def op_setindex(self, op, array, indices, value): ptr = self.builder.gep(array, indices) self.builder.store(ptr, value) # __________________________________________________________________ def op_getindex(self, op, array, indices): return self.builder.gep(array, indices, op.result) # __________________________________________________________________ def op_alloca(self, op): llvm_pointer_type = self.llvm_type(op.type) return self.builder.alloca(llvm_pointer_type.pointee, op.result) def op_load(self, op, stackvar): return self.builder.load(stackvar, op.result) def op_store(self, op, value, stackvar): self.builder.store(value, stackvar) # __________________________________________________________________ def op_jump(self, op, block): self.builder.branch(block) def op_cbranch(self, op, test, true_block, false_block): self.builder.cbranch(test, true_block, false_block) def op_phi(self, op): phi = self.builder.phi(self.llvm_type(op.type), op.result) self.phis.append(op) return phi def op_ret(self, op, value): if value is None: assert self.func.type.restype.is_void self.builder.ret_void() else: self.builder.ret(value) # __________________________________________________________________ def op_sizeof(self, op, type): int_type = self.llvm_type(op.type) item_type = self.llvm_type(type) return sizeof(self.builder, item_type, int_type, op.result) def op_addressof(self, op, func): assert func.address addr = const_int(i64, func.address) return self.builder.inttoptr(addr, self.llvm_type(Pointer(func.type))) # __________________________________________________________________ def op_ptradd(self, op, ptr, val): return self.builder.gep(ptr, [val], op.result) def op_ptrload(self, op, ptr): return self.builder.load(ptr, op.result) def op_ptrstore(self, op, ptr, val): return self.builder.store(val, ptr, op.result) def op_ptrcast(self, op, val): return self.builder.bitcast(val, self.llvm_type(op.type), op.result) def op_ptr_isnull(self, op, val): intval = self.builder.ptrtoint(val, self.llvm_type(Int64)) return self.builder.icmp(lc.ICMP_EQ, intval, zero(intval.type), op.result) # __________________________________________________________________ def allocate_blocks(llvm_func, pykit_func): """Return a dict mapping pykit blocks to llvm blocks""" blocks = {} for block in pykit_func.blocks: blocks[block] = llvm_func.append_basic_block(pykit_func.name) return blocks def update_phis(phis, valuemap, argloader): """ Update LLVM phi values given a list of pykit phi values and block and value dicts mapping pykit values to LLVM values """ for phi in phis: llvm_phi = valuemap[phi.result] llvm_blocks = map(argloader.load_op, phi.args[0]) llvm_values = map(argloader.load_op, phi.args[1]) for llvm_block, llvm_value in zip(llvm_blocks, llvm_values): llvm_phi.add_incoming(llvm_value, llvm_block) #===------------------------------------------------------------------=== # Pass to group operations such as add/mul #===------------------------------------------------------------------=== class LLVMArgLoader(ArgLoader): """ Load Operation arguments as LLVM values passed and extra *args to the Translator. """ def __init__(self, store, engine, llvm_module, lfunc, blockmap): super(LLVMArgLoader, self).__init__(store) self.engine = engine self.llvm_module = llvm_module self.lfunc = lfunc self.blockmap = blockmap def load_GlobalValue(self, arg): if arg.external: value = self.lmod.get_or_insert_function(llvm_type(arg.type)) if arg.address: self.engine.add_global_mapping(value, arg.address) else: assert arg.value value = arg.value.const return value def load_Block(self, arg): return self.blockmap[arg] def load_Constant(self, arg): ty = type(arg.type) lty = llvm_type(arg.type) if ty == Pointer: if arg.const == 0: return lc.Constant.null(lty) else: return const_i64(arg.const).inttoptr(i64) elif ty == Integral: if arg.type.unsigned: return lc.Constant.int(lty, arg.const) else: return lc.Constant.int_signextend(lty, arg.const) elif ty == Real: return lc.Constant.real(lty, arg.const) else: raise NotImplementedError("Constants for", ty) def load_Undef(self, arg): return lc.Constant.undef(llvm_type(arg.type)) def initialize(func, env): verify_lowlevel(func) llvm_module = env["codegen.llvm.module"] return llvm_module.add_function(llvm_type(func.type), func.name) def translate(func, env, lfunc): engine, llvm_module = env["codegen.llvm.engine"], env["codegen.llvm.module"] blockmap = allocate_blocks(lfunc, func) ### Create visitor ### translator = Translator(func, env, lfunc, llvm_type, llvm_module) visitor = opgrouper(translator) ### Codegen ### argloader = LLVMArgLoader(None, engine, llvm_module, lfunc, blockmap) valuemap = vvisit(visitor, func, argloader) update_phis(translator.phis, valuemap, argloader) return lfunc

32.135204

82

0.618322

1,515

12,597

4.479208

0.179538

0.055113

0.024315

0.02682

0.220159

0.107722

0.062334

0.046124

0.037135

0

0.004887

0.220291

12,597

392

83

32.135204

0.686011

0.166945

0

0.091954

0

0.016368

0

0.011494

1

0.168582

false

0

0.030651

0.061303

0.356322

0

null

0

null

0

1

0

bdebe8ab095dd6dc14338c32ad38db4e4ac43ada

1,056

py

Python

ads_dashboard/ads/models.py

vintage/ads_dashboard

85a8540411a9af0a2e41dd3730b52e3c6b3805d4

[ "MIT" ]

null

ads_dashboard/ads/models.py

vintage/ads_dashboard

85a8540411a9af0a2e41dd3730b52e3c6b3805d4

[ "MIT" ]

5

2020-02-12T09:18:05.000Z

2021-09-22T18:05:21.000Z

ads_dashboard/ads/models.py

vintage/ads_dashboard

85a8540411a9af0a2e41dd3730b52e3c6b3805d4

[ "MIT" ]

null

from django.db import models class Campaign(models.Model): name = models.CharField("name", unique=True, max_length=255) class Meta: verbose_name = "campaign" verbose_name_plural = "campaigns" def __str__(self): return self.name class DataSource(models.Model): name = models.CharField("name", unique=True, max_length=255) class Meta: verbose_name = "data source" verbose_name_plural = "data sources" def __str__(self): return self.name class CampaignStats(models.Model): date = models.DateField("date") data_source = models.ForeignKey(DataSource, on_delete=models.CASCADE) campaign = models.ForeignKey(Campaign, on_delete=models.CASCADE) clicks = models.IntegerField("clicks") impressions = models.IntegerField("impressions") class Meta: verbose_name = "campaign stats" verbose_name_plural = "campaign stats" unique_together = (("date", "data_source", "campaign",),) def __str__(self): return f"Stats #{self.pk}"

26.4

73

0.673295

121

1,056

5.644628

0.338843

0.096633

0.070278

0.087848

0.360176

0.307467

0.222548

0

0.007238

0.214962

1,056

39

74

27.076923

0.816647

0

0.37037

0

0.128788

0

1

0.111111

false

0

0.037037

0.111111

0.740741

0

null

0

null

0

1

0

2

bdeef5ecb135e522f7c40abc5e24bd958b8ff052

1,859

py

Python

DatabaseHandler/sqlite_operations.py

utkarsh7236/SCILLA

e11e4d753823ad522a1b3168283b6e6ffe3ea393

[ "Apache-2.0" ]

17

2019-12-09T19:09:07.000Z

2021-08-29T01:11:13.000Z

DatabaseHandler/sqlite_operations.py

utkarsh7236/SCILLA

e11e4d753823ad522a1b3168283b6e6ffe3ea393

[ "Apache-2.0" ]

1

2021-04-14T15:08:18.000Z

DatabaseHandler/sqlite_operations.py

utkarsh7236/SCILLA

e11e4d753823ad522a1b3168283b6e6ffe3ea393

[ "Apache-2.0" ]

2

2020-06-05T03:01:06.000Z

2020-07-09T07:13:12.000Z

#!/usr/bin/env python __author__ = 'Florian Hase' #======================================================================== import time import sqlalchemy as sql #======================================================================== class AddEntry(object): def __init__(self, database, table, entry): self.db = database self.table = table self.entry = entry def execute(self): start = time.time() with self.db.connect() as conn: conn.execute(self.table.insert(), self.entry) conn.close() end = time.time() #======================================================================== class FetchEntries(object): def __init__(self, database, table, selection, name = 'test'): self.db = database self.table = table self.selection = selection self.entries = None self.executed = False self.entries_fetched = False self.name = name def execute(self): start = time.time() with self.db.connect() as conn: selected = conn.execute(self.selection) entries = selected.fetchall() conn.close() self.entries = entries self.executed = True end = time.time() def get_entries(self): iteration_index = 0 while not self.executed: pass self.entries_fetched = True return self.entries #======================================================================== class UpdateEntries(object): def __init__(self, database, table, updates): self.db = database self.table = table self.updates = updates def execute(self): start = time.time() if isinstance(self.updates, list): with self.db.connect() as conn: for updates in self.updates: updated = conn.execute(updates) conn.close() else: with self.db.connect() as conn: updated = conn.execute(self.updates) conn.close() end = time.time()

23.833333

73

0.550834

201

1,859

4.995025

0.293532

0.041833

0.039841

0.067729

0.39741

0.35757

0.195219

0.099602

0

0.000669

0.196342

1,859

77

74

24.142857

0.671352

0.166218

0

0.418182

0

0.010356

0

1

0.127273

false

0.018182

0.036364

0

0.236364

0

null

0

null

0

1

0

bdf105752f21bbc068ce977d28dde3f6db125f50

8,818

py

Python

main.py

omegaBionic/pysparkPower

1354247e4ec085a65f288a1f31a05875f003da72

[ "Apache-2.0" ]

null

main.py

omegaBionic/pysparkPower

1354247e4ec085a65f288a1f31a05875f003da72

[ "Apache-2.0" ]

null

main.py

omegaBionic/pysparkPower

1354247e4ec085a65f288a1f31a05875f003da72

[ "Apache-2.0" ]

null

import matplotlib.pyplot as plt import numpy as np import pylab as pl import pandas as pd from pyspark import SQLContext from pyspark.ml.clustering import KMeans from pyspark.ml.feature import VectorAssembler from pyspark.sql import SparkSession from pyspark.sql.types import StructType, StructField, IntegerType from data.process_initial_file import dict_education, list_education, list_race def elbow_method_evaluation(df): # Calculate cost and plot cost = np.zeros(10) for k in range(2, 10): kmeans = KMeans().setK(k).setSeed(1).setFeaturesCol("features") model = kmeans.fit(df) cost[k] = model.summary.trainingCost # Plot the cost df_cost = pd.DataFrame(cost[2:]) df_cost.columns = ["cost"] new_col = [2, 3, 4, 5, 6, 7, 8, 9] df_cost.insert(0, 'cluster', new_col) pl.plot(df_cost.cluster, df_cost.cost) pl.xlabel('Number of Clusters') pl.ylabel('Score') pl.title('Elbow Curve') pl.show() spark = SparkSession \ .builder \ .appName("Python Spark SQL basic example") \ .config("spark.some.config.option", "some-value") \ .getOrCreate() # Define information nullable = True schema = StructType([ StructField("age", IntegerType(), nullable), StructField("workclass", IntegerType(), nullable), StructField("fnlwgt", IntegerType(), nullable), StructField("education", IntegerType(), nullable), StructField("marital-status", IntegerType(), nullable), StructField("occupation", IntegerType(), nullable), StructField("relationship", IntegerType(), nullable), StructField("race", IntegerType(), nullable), StructField("sex", IntegerType(), nullable), StructField("capital-gain", IntegerType(), nullable), StructField("capital-loss", IntegerType(), nullable), StructField("hours-per-week", IntegerType(), nullable), StructField("native-country", IntegerType(), nullable), StructField("is-upper-than-50k", IntegerType(), nullable) ]) # Connect to bdd sqlContext = SQLContext(sparkContext=spark.sparkContext, sparkSession=spark) # Read file df = sqlContext.read.csv("data/adult_processed_data.data", header=True, sep=",", schema=schema) # Display all columns # print(df.collect()) # Display columns print(df.columns) # df.select("is-upper-than-50k").show() df.select("*").show() # Create features column, assembling together the numeric data col1_name = 'education' col2_name = 'capital-gain' col3_name = 'race' col4_name = 'hours-per-week' inputCols = [col1_name, col2_name, col3_name] vecAssembler = VectorAssembler( inputCols=inputCols, outputCol="features") adults_with_features = vecAssembler.transform(df) # Figure 1 # Do K-means # Evaluate number of clusters with the elbow method elbow_method_evaluation(adults_with_features) k = 3 kmeans_algo = KMeans().setK(k).setSeed(1).setFeaturesCol("features") model = kmeans_algo.fit(adults_with_features) centers = model.clusterCenters() # Assign clusters to adults # Cluster prediction, named prediction and used after for color adults_with_clusters = model.transform(adults_with_features) # Display Centers print("Centers: '{}'".format(centers)) # Convert Spark Data Frame to Pandas Data Frame adults_for_viz = adults_with_clusters.toPandas() print("STARTING PRINTING ADULTS_for") print("adults_for_viz.prediction.value_counts(): '{}'".format(adults_for_viz.prediction.value_counts())) # Vizualize A = adults_for_viz[adults_for_viz["is-upper-than-50k"] == 0] B = adults_for_viz[adults_for_viz["is-upper-than-50k"] == 1] # Colors code k-means results, cluster numbers colors = {0: 'red', 1: 'blue', 2: 'orange'} # Draw dots fig = plt.figure().add_subplot() fig.scatter(A[col1_name], A[col2_name], c=A.prediction.map(colors), marker='.') fig.scatter(B[col1_name], B[col2_name], c=B.prediction.map(colors), marker='x') # Draw grid plt.grid() # Set text plt.title("Combined Statistics 1") plt.xlabel(col1_name) plt.ylabel(col2_name) # TODO To change in case col1_name is changed plt.xticks(range(0, len(list_education)), list_education, rotation='vertical') plt.legend(['is-upper-than-50k: False', 'is-upper-than-50k: True']) # Save figure plt.savefig("picture1.png", bbox_inches='tight') # Show fig plt.show() # Figure 2 # Draw dots fig = plt.figure().add_subplot() fig.scatter(A[col1_name], A[col2_name], c=A.prediction.map(colors), marker='.') fig.scatter(B[col1_name], B[col2_name], c=B.prediction.map(colors), marker='x') # fig.set_yscale('log', base=2) # Draw grid plt.grid() # Set text plt.title("Combined Statistics 2") plt.xlabel(col1_name) plt.ylabel(col2_name) plt.xticks(range(0, len(list_education)), list_education, rotation='vertical') plt.legend(['is-upper-than-50k: False', 'is-upper-than-50k: True']) # Save figure plt.savefig("picture2.png", bbox_inches='tight') # Show fig plt.show() # Figure 3 inputCols = [col2_name, col3_name] vecAssembler = VectorAssembler( inputCols=inputCols, outputCol="features") adults_with_features = vecAssembler.transform(df) # Do K-means k = 3 kmeans_algo = KMeans().setK(k).setSeed(1).setFeaturesCol("features") model = kmeans_algo.fit(adults_with_features) centers = model.clusterCenters() # Assign clusters to flowers # Cluster prediction, named prediction and used after for color adults_with_clusters = model.transform(adults_with_features) # Display Centers print("Centers: '{}'".format(centers)) # Convert Spark Data Frame to Pandas Data Frame adults_for_viz = adults_with_clusters.toPandas() print("STARTING PRINTING ADULTS_for") print("adults_for_viz.prediction.value_counts(): '{}'".format(adults_for_viz.prediction.value_counts())) # Vizualize A = adults_for_viz[adults_for_viz["is-upper-than-50k"] == 0] B = adults_for_viz[adults_for_viz["is-upper-than-50k"] == 1] # Colors code k-means results, cluster numbers colors = {0: 'red', 1: 'blue', 2: 'orange'} # Draw dots fig = plt.figure().add_subplot() fig.scatter(A[col3_name], A[col2_name], c=A.prediction.map(colors), marker='.') fig.scatter(B[col3_name], B[col2_name], c=B.prediction.map(colors), marker='x') # fig.set_yscale('log', base=2) # Draw grid plt.grid() # Set text plt.title("Combined Statistics 3") plt.xlabel(col3_name) plt.ylabel(col2_name) plt.xticks(range(0, len(list_race)), list_race, rotation='vertical') plt.legend(['is-upper-than-50k: False', 'is-upper-than-50k: True']) # Save figure plt.savefig("picture3.png", bbox_inches='tight') # Show fig plt.show() # TODO PUT HERE # Figure 4 inputCols = [col1_name, col3_name, col4_name] vecAssembler = VectorAssembler( inputCols=inputCols, outputCol="features") adults_with_features = vecAssembler.transform(df) elbow_method_evaluation(adults_with_features) # Do K-means k = 3 kmeans_algo = KMeans().setK(k).setSeed(1).setFeaturesCol("features") model = kmeans_algo.fit(adults_with_features) centers = model.clusterCenters() # Assign clusters to flowers # Cluster prediction, named prediction and used after for color adults_with_clusters = model.transform(adults_with_features) # Display Centers print("Centers: '{}'".format(centers)) # Convert Spark Data Frame to Pandas Data Frame adults_for_viz = adults_with_clusters.toPandas() print("STARTING PRINTING ADULTS_for") print("adults_for_viz.prediction.value_counts(): '{}'".format(adults_for_viz.prediction.value_counts())) # Vizualize A = adults_for_viz[adults_for_viz["is-upper-than-50k"] == 0] B = adults_for_viz[adults_for_viz["is-upper-than-50k"] == 1] # Colors code k-means results, cluster numbers colors = {0: 'red', 1: 'blue', 2: 'orange'} # Draw dots fig_3d = plt.figure() ax = plt.axes(projection='3d') ax.set_xlabel(col1_name) ax.set_ylabel(col3_name) ax.set_zlabel(col4_name) ax.set_xticks(range(0, len(list_education))) ax.set_xticklabels(list_education, rotation=90, verticalalignment='baseline', horizontalalignment='left') ax.set_yticks(range(0, len(list_race))) ax.set_yticklabels(list_race, rotation=-15, verticalalignment='baseline', horizontalalignment='left') # Data for three-dimensional scattered points ax.scatter3D(A[col1_name], A[col3_name], A[col4_name], c=A.prediction.map(colors), cmap='Greens', marker='.') ax.scatter3D(B[col1_name], B[col3_name], B[col4_name], c=B.prediction.map(colors), cmap='Greens', marker='x') # Save figure plt.savefig("picture4.png", bbox_inches='tight') plt.show() # DEBUG: Display stats print("k: '{}'".format(k)) print("A.prediction.value_counts(): '{}'".format(A.prediction.value_counts())) print("B.prediction.value_counts(): '{}'".format(B.prediction.value_counts()))

29.790541

109

0.713087

1,203

8,818

5.075644

0.202826

0.035375

0.041271

0.0321

0.590894

0.587455

0.556666

0.543727

0.522764

0

0.017317

0.142096

8,818

295

110

29.891525

0.789822

0.150488

0

0.536313

0

0.160409

0.031355

0

0.00339

0

1

0.005587

false

0

0.055866

0

0.061453

0.072626

0

null

0

null

0

1

0

bdf19052bf08ce92ba043372f3b11061a349f71e

408

py

Python

app/pages/urls.py

julianpetrich/jpdotcom

ba9dac9c86f6d15374da9a37aac68963e56bcd93

[ "MIT" ]

null

app/pages/urls.py

julianpetrich/jpdotcom

ba9dac9c86f6d15374da9a37aac68963e56bcd93

[ "MIT" ]

null

app/pages/urls.py

julianpetrich/jpdotcom

ba9dac9c86f6d15374da9a37aac68963e56bcd93

[ "MIT" ]

null

from django.urls import path from .views import AboutView, ContactView, HomePageView, PrivacyView, TermsView urlpatterns = [ path("", HomePageView.as_view(), name="home"), path("about", AboutView.as_view(), name="about"), path("contact", ContactView.as_view(), name="contact"), path("terms", TermsView.as_view(), name="terms"), path("privacy", PrivacyView.as_view(), name="privacy"), ]

34

79

0.688725

48

408

5.75

0.416667

0.108696

0.181159

0

0.129902

408

11

80

37.090909

0.777465

0

0.127451

0

1

0

false

0

0.222222

0

0.222222

0

null

0

1

0

null

0

1

bdf4b884e53e55033540d679eaf6e95f48c085d7

118

py

Python

tests/test_crawler.py

Yotamho/nba-analytics

13174040198d44aab035de58cf785bce6926958a

[ "MIT" ]

null

tests/test_crawler.py

Yotamho/nba-analytics

13174040198d44aab035de58cf785bce6926958a

[ "MIT" ]

null

tests/test_crawler.py

Yotamho/nba-analytics

13174040198d44aab035de58cf785bce6926958a

[ "MIT" ]

null

from nba_analytics.crawler import pbp_for_range def test_crawler(): assert pbp_for_range(3, 2008, 2009) != None

19.666667

47

0.762712

19

118

4.421053

0.789474

0.142857

0.261905

0

0.09

0.152542

118

5

48

23.6

0.75

0

0.333333

1

0.333333

true

0

0.333333

0

0.666667

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

7

bdf5bfe6b045a2bc243a77cfba2030c81bcde42d

3,781

py

Python

src/open3DTool/visualizer.py

MobileRoboticsSkoltech/plane-segmentation-research

0627512c4cb53326de1aabf815e755d9e4484c9c

[ "Apache-2.0" ]

1

2021-10-15T08:18:55.000Z

src/open3DTool/visualizer.py

MobileRoboticsSkoltech/plane-segmentation-research

0627512c4cb53326de1aabf815e755d9e4484c9c

[ "Apache-2.0" ]

1

2021-11-18T16:37:28.000Z

src/open3DTool/visualizer.py

MobileRoboticsSkoltech/plane-segmentation-research

0627512c4cb53326de1aabf815e755d9e4484c9c

[ "Apache-2.0" ]

null

from src.open3DTool.planeUtils import ( segment_points_on_plane_by_picked_points, pick_points_utils, ) from src.algorithmsForPointCloud.fileUtils import ( get_point_cloud_from_bin_file, generate_labels_and_object_files, ) from src.open3DTool.fileUtils import update_label_files import numpy as np import open3d as o3d class Visualizer: point_cloud = o3d.geometry.PointCloud() path_to_pcd_file = "" path_to_label_file = "" path_to_object_file = "" main_visualizer = o3d.visualization.VisualizerWithKeyCallback() picked_indexes = [] distance = 0 pick_points_count = 3 def __init__( self, path_to_bin_file: str, path_to_save_file_label: str, path_to_save_file_object: str, path_to_pcd_file: str, distance: np.intc, pick_points_count: np.intc, ): self.point_cloud = get_point_cloud_from_bin_file(path_to_bin_file) self.point_cloud.paint_uniform_color([0.51, 0.51, 0.51]) self.path_to_pcd_file = path_to_pcd_file self.path_to_label_file = path_to_save_file_label self.path_to_object_file = path_to_save_file_object self.distance = distance self.pick_points_count = pick_points_count self.generate_label_files([]) def generate_label_files(self, indexes: list): generate_labels_and_object_files( len(self.point_cloud.points), indexes, self.path_to_label_file, self.path_to_object_file, ) def update_pcd_and_label_files(self, count_of_points: int, is_append_right: bool): update_label_files( self.point_cloud, count_of_points, self.path_to_pcd_file, self.path_to_label_file, self.path_to_object_file, is_append_right, ) def run(self): self.main_visualizer = o3d.visualization.VisualizerWithKeyCallback() self.main_visualizer.create_window() self.main_visualizer.add_geometry(self.point_cloud) self.set_hotkeys() self.main_visualizer.run() self.main_visualizer.destroy_window() def set_hotkeys(self): self.main_visualizer.register_key_callback(32, self.pick_points) # Space self.main_visualizer.register_key_callback( 259, self.get_previous_snapshot ) # Backspace def pick_points(self, visualizer): indexes_of_points = pick_points_utils(self.point_cloud) assert len(indexes_of_points) == self.pick_points_count self.update_main_window_by_plane(indexes_of_points) def get_previous_snapshot(self, visualizer): if len(self.picked_indexes) == 0: return number_of_last_indexes = self.picked_indexes[-1] self.picked_indexes = self.picked_indexes[:-1] point_cloud_len = len(self.point_cloud.points) last_indexes = [ i for i in range(point_cloud_len - number_of_last_indexes, point_cloud_len) ] picked_cloud = self.point_cloud.select_by_index(last_indexes) picked_cloud.paint_uniform_color([0.51, 0.51, 0.51]) self.point_cloud = picked_cloud + self.point_cloud.select_by_index( last_indexes, invert=True ) self.update_pcd_and_label_files(number_of_last_indexes, False) visualizer.clear_geometries() visualizer.add_geometry(self.point_cloud) def update_main_window_by_plane(self, picked_points: list): self.point_cloud, indexes = segment_points_on_plane_by_picked_points( self.point_cloud, picked_points, self.distance ) self.picked_indexes.append(len(indexes)) self.update_pcd_and_label_files(len(indexes), True) self.run()

34.372727

87

0.691351

497

3,781

4.802817

0.197183

0.079598

0.076246

0.027231

0.455802

0.274822

0.150398

0.12191

0.103058

0

0.012081

0.233801

3,781

109

88

34.688073

0.811874

0.003967

0

0.043011

0

0.010753

1

0.086022

false

0

0.053763

0

0.247312

0

null

0

null

0

1

0

bdfa7f51aa6bca9797c581b745c48d3a51fc0b8d

8,868

py

Python

submission_utils.py

ameyagodbole/multihop_inference_explanation_regeneration

ab742433034b251a819b6eb898686530bd055cd0

[ "MIT" ]

7

2019-08-31T22:58:41.000Z

2021-02-06T17:41:38.000Z

submission_utils.py

ameyagodbole/multihop_inference_explanation_regeneration

ab742433034b251a819b6eb898686530bd055cd0

[ "MIT" ]

2

2020-02-19T13:32:03.000Z

2020-07-29T09:24:53.000Z

submission_utils.py

ameyagodbole/multihop_inference_explanation_regeneration

ab742433034b251a819b6eb898686530bd055cd0

[ "MIT" ]

1

2020-10-01T09:48:07.000Z

import argparse import logging import numpy as np import pandas as pd from sklearn.feature_extraction.text import TfidfVectorizer from sklearn.metrics.pairwise import cosine_distances import torch def create_predictions_file(questions_file, facts_file, examples_file, logits_file, pred_output_file, mcq_choices="correct", write_debug_file=False): """ Utility to generate submission file from predictions (logits scores) """ df_questions = pd.read_csv(questions_file, sep='\t') df_facts = pd.read_csv(facts_file, sep='\t').drop_duplicates(subset=["uid"], keep="first").reset_index() examples = torch.load(examples_file) logits = np.load(logits_file) logit_1 = logits[:, 1] - logits[:, 0] if write_debug_file: f_tmp = open(pred_output_file + "-as-text", "w") # Remove wrong choices def remove_wrong_answer_choices(row, choices): correct_choice = row["AnswerKey"] option_start_loc = row["Question"].rfind("(A)") split0, split1 = row["Question"][:option_start_loc], row["Question"][option_start_loc:] if choices == "none": return split0 if correct_choice == "A" and "(B)" in split1: split0 += (split1[3:split1.rfind("(B)")]) elif correct_choice == "A": split0 += (split1[3:]) elif correct_choice == "B" and "(C)" in split1: split0 += (split1[split1.rfind("(B)") + 3:split1.rfind("(C)")]) elif correct_choice == "B": split0 += (split1[split1.rfind("(B)") + 3:]) elif correct_choice == "C" and "(D)" in split1: split0 += (split1[split1.rfind("(C)") + 3:split1.rfind("(D)")]) elif correct_choice == "C": split0 += (split1[split1.rfind("(C)") + 3:]) elif correct_choice == "D" and "(E)" in split1: split0 += (split1[split1.rfind("D)") + 3:split1.rfind("(E)")]) elif correct_choice == "D": split0 += (split1[split1.rfind("D)") + 3:]) elif correct_choice == "E" and "(F)" in split1: split0 += (split1[split1.rfind("(E)") + 3:split1.rfind("(F)")]) elif correct_choice == "E": split0 += (split1[split1.rfind("(E)") + 3:]) else: raise ValueError("Unhandled option type: {}".format(correct_choice)) return split0 if mcq_choices != "all": df_questions["ProcessedQuestion"] = df_questions.apply(remove_wrong_answer_choices, 1, choices=mcq_choices) else: df_questions["ProcessedQuestion"] = df_questions["Question"] vectorizer = TfidfVectorizer().fit(df_questions['Question']).fit(df_facts['text']) X_q = vectorizer.transform(df_questions['ProcessedQuestion']) X_e = vectorizer.transform(df_facts['text']) X_dist = cosine_distances(X_q, X_e) idx_start = 0 predictions = [] prev_query = examples[0].text_a for i, example in enumerate(examples): if example.text_a == prev_query: continue qid = examples[idx_start].guid.split('###')[0] q = df_questions.loc[df_questions["questionID"] == qid] assert q["ProcessedQuestion"].item() == examples[idx_start].text_a relevant_logits = logit_1[idx_start:i] relevant_examples = examples[idx_start:i] sorted_preds, sorted_examples = zip(*sorted(zip(relevant_logits, relevant_examples), key=lambda e: e[0], reverse=True)) added_uids = set() example_preds = [] for se in sorted_examples: for fid in se.guid.split('###')[1:]: if fid not in added_uids: added_uids.add(fid) example_preds.append('\t'.join([qid, fid])) for dist_idx in np.argsort(X_dist[q.index.to_numpy()[0]]): fid = df_facts.loc[dist_idx, "uid"] if fid not in added_uids: added_uids.add(fid) example_preds.append('\t'.join([qid, fid])) predictions.extend(example_preds) if write_debug_file: f_tmp.write(q["questionID"].item()) f_tmp.write('\n') f_tmp.write(q["Question"].item()) f_tmp.write('\n') f_tmp.write(q["ProcessedQuestion"].item()) f_tmp.write("\n*************\n") for i_tmp in range(40): f_tmp.write(sorted_examples[i_tmp].guid.split('###')[1:].__str__()) f_tmp.write(' Score:{:.3f}\n'.format(sorted_preds[i_tmp])) f_tmp.write(sorted_examples[i_tmp].text_b.__str__()) f_tmp.write('\n') f_tmp.write("*************\n") for i_tmp in range(40): f_tmp.write(df_facts.loc[df_facts["uid"] == example_preds[i_tmp].split('\t')[1], "text"].item()) f_tmp.write('\n') f_tmp.write("*************\n") for expl in q["explanation"].item().split(' '): f_tmp.write(df_facts.loc[df_facts["uid"] == expl.split('|')[0], "text"].item()) f_tmp.write('\n') f_tmp.write("*************\n") prev_query = example.text_a idx_start = i qid = examples[idx_start].guid.split('###')[0] q = df_questions.loc[df_questions["questionID"] == qid] assert q["ProcessedQuestion"].item() == examples[idx_start].text_a relevant_logits = logit_1[idx_start:] relevant_examples = examples[idx_start:] sorted_preds, sorted_examples = zip(*sorted(zip(relevant_logits, relevant_examples), key=lambda e: e[0], reverse=True)) added_uids = set() example_preds = [] for se in sorted_examples: for fid in se.guid.split('###')[1:]: if fid not in added_uids: added_uids.add(fid) example_preds.append('\t'.join([qid, fid])) for dist_idx in np.argsort(X_dist[q.index.to_numpy()[0]]): fid = df_facts.loc[dist_idx, "uid"] if fid not in added_uids: added_uids.add(fid) example_preds.append('\t'.join([qid, fid])) predictions.extend(example_preds) if write_debug_file: f_tmp.write(q["questionID"].item()) f_tmp.write('\n') f_tmp.write(q["Question"].item()) f_tmp.write('\n') f_tmp.write(q["ProcessedQuestion"].item()) f_tmp.write("\n*************\n") for i_tmp in range(40): f_tmp.write(sorted_examples[i_tmp].guid.split('###')[1:].__str__()) f_tmp.write(' Score:{:.3f}\n'.format(sorted_preds[i_tmp])) f_tmp.write(sorted_examples[i_tmp].text_b.__str__()) f_tmp.write('\n') f_tmp.write("*************\n") for i_tmp in range(40): f_tmp.write(df_facts.loc[df_facts["uid"] == example_preds[i_tmp].split('\t')[1], "text"].item()) f_tmp.write('\n') f_tmp.write("*************\n") for expl in q["explanation"].item().split(' '): f_tmp.write(df_facts.loc[df_facts["uid"] == expl.split('|')[0], "text"].item()) f_tmp.write('\n') f_tmp.write("*************\n") f_tmp.close() logging.info("Writing to file") with open(pred_output_file, "w") as f: f.write('\n'.join(predictions)) f.write('\n') logging.info("len(df_questions)={}".format(len(df_questions))) logging.info("len(predictions)={}".format(len(predictions))) if __name__=='__main__': parser = argparse.ArgumentParser() parser.add_argument("--questions_file", type=str, required=True, help="The tsv file containing the evaluation") parser.add_argument("--facts_file", type=str, required=True, help="The tsv file containing the common sense facts") parser.add_argument("--examples_file", type=str, help="Examples file that is being evaluated") parser.add_argument("--logits_file", type=str, help="Model predictions (liekly some file of the form *_preds.npy)") parser.add_argument("--pred_output_file", type=str, required=True, help="Name of the file where predictions will be written") parser.add_argument("--mcq_choices", type=str, choices=['none', 'correct', 'all'], default="correct", help="The choices to keep in the questions") parser.add_argument("--write_debug_file", action='store_true') args = parser.parse_args() create_predictions_file(questions_file=args.questions_file, facts_file=args.facts_file, examples_file=args.examples_file, logits_file=args.logits_file, pred_output_file=args.pred_output_file, mcq_choices=args.mcq_choices, write_debug_file=args.write_debug_file)

45.948187

119

0.579725

1,130

8,868

4.309735

0.158407

0.029569

0.062834

0.036961

0.558111

0.482752

0.424641

0

0.012739

0.256428

8,868

193

120

45.948187

0.725811

0.010149

0

0.491124

0

0.124501

0

0.011834

1

0.011834

false

0

0.04142

0

0.065089

0

null

0

null

0

1

0

bdfb7f7d975d38d147cc79c67eb8466db9daf8e8

1,884

py

Python

pysm/semantic_modeling/assembling/autolabel/auto_label.py

binh-vu/semantic-modeling

b387584502ba1daa6abd6b7573828416f6426b49

[ "MIT" ]

3

2019-10-31T15:26:20.000Z

2022-03-03T06:04:03.000Z

pysm/semantic_modeling/assembling/autolabel/auto_label.py

binh-vu/semantic-modeling

b387584502ba1daa6abd6b7573828416f6426b49

[ "MIT" ]

1

2021-10-05T14:57:29.000Z

2022-03-27T01:58:41.000Z

pysm/semantic_modeling/assembling/autolabel/auto_label.py

binh-vu/semantic-modeling

b387584502ba1daa6abd6b7573828416f6426b49

[ "MIT" ]

null

#!/usr/bin/python # -*- coding: utf-8 -*- from typing import Dict, Tuple, List, Set, Union, Optional from data_structure import Graph from semantic_modeling.assembling.autolabel.heuristic import preserved_structure_with_heuristic, get_gold_semantic_types from semantic_modeling.assembling.autolabel.maxf1 import get_gold_triples, max_f1, max_f1_no_ambiguous from semantic_modeling.assembling.autolabel.preserved_structure import preserved_structure class AutoLabel: @staticmethod def auto_label_max_f1(gold_sm: Graph, pred_sm: Graph, is_blurring_label: bool) -> Tuple[Dict[int, bool], Dict[int, Optional[int]], float]: gold_triples = get_gold_triples(gold_sm, is_blurring_label) return max_f1(gold_sm, pred_sm, is_blurring_label, gold_triples) @staticmethod def auto_label_max_f1_no_ambiguous(gold_sm: Graph, pred_sm: Graph, is_blurring_label: bool ) -> Tuple[Dict[int, bool], Dict[int, Optional[int]], float]: gold_triples = get_gold_triples(gold_sm, is_blurring_label) return max_f1_no_ambiguous(gold_sm, pred_sm, is_blurring_label, gold_triples) @staticmethod def auto_label_preserved_structure(gold_sm: Graph, pred_sm: Graph) -> Tuple[Dict[int, bool], Dict[int, Optional[int]]]: gold_triples = get_gold_triples(gold_sm, is_blurring_label=False) return preserved_structure(gold_sm, pred_sm, gold_triples) @staticmethod def auto_label_preserved_structure_heuristic_fix( gold_sm: Graph, pred_sm: Graph) -> Tuple[Dict[int, bool], Dict[int, Optional[int]]]: gold_triples = get_gold_triples(gold_sm, is_blurring_label=False) gold_stypes = get_gold_semantic_types(gold_sm) return preserved_structure_with_heuristic(gold_sm, pred_sm, gold_triples, gold_stypes)

49.578947

120

0.728769

255

1,884

4.992157

0.196078

0.112333

0.094266

0.080126

0.699921

0.608013

0.536528

0.480754

0

0.005225

0.187367

1,884

37

121

50.918919

0.826257

0.02017

0

0.296296

0

1

0.148148

false

0

0.185185

0

0.518519

0

null

0

null

0

1

0

bdfb84bba555606efcd2d3ca97385378284beca7

8,203

py

Python

tests/test_levdistresult.py

ZenulAbidin/bip39validator

b78f2db6f46b56b408eef3a51e921e96247a9b46

[ "MIT" ]

3

2021-02-11T20:37:56.000Z

2021-06-11T03:29:15.000Z

tests/test_levdistresult.py

ZenulAbidin/bip39validator

b78f2db6f46b56b408eef3a51e921e96247a9b46

[ "MIT" ]

4

2020-10-04T23:11:08.000Z

2020-12-23T00:32:52.000Z

tests/test_levdistresult.py

ZenulAbidin/bip39validator

b78f2db6f46b56b408eef3a51e921e96247a9b46

[ "MIT" ]

null

from unittest import TestCase from bip39validator import ValidationFailed from bip39validator.BIP39WordList import BIP39WordList levdist_gt2 = """brown brpyt""" levdist_le2 = """brow brol""" # Expected results *must* be in word alphabetical order. class TestLevDistResult(TestCase): def test_getwordpairs_eq(self): bip39 = BIP39WordList("levdist_le2", string=levdist_le2) try: res = bip39.test_lev_distance(2) except ValidationFailed as e: res = e.status_obj expected_res = [("brol", "brow")] self.assertEqual(expected_res, res.getwordpairs_eq(1)) try: res.getwordpairs_eq(2) self.fail() except AssertionError as e: pass def test_getlinepairs_eq(self): bip39 = BIP39WordList("levdist_le2", string=levdist_le2) try: res = bip39.test_lev_distance(2) except ValidationFailed as e: res = e.status_obj expected_res = [(2,1)] self.assertEqual(expected_res, res.getlinepairs_eq(1)) try: res.getwordpairs_eq(0) self.fail() except AssertionError as e: pass def test_getwordpairs_lt(self): bip39 = BIP39WordList("levdist_le2", string=levdist_le2) try: res = bip39.test_lev_distance(2) except ValidationFailed as e: res = e.status_obj expected_res = [("brol", "brow")] self.assertEqual(expected_res, res.getwordpairs_lt(2)) try: res.getwordpairs_lt(0) self.fail() except AssertionError as e: pass def test_getlinepairs_lt(self): bip39 = BIP39WordList("levdist_le2", string=levdist_le2) try: res = bip39.test_lev_distance(2) except ValidationFailed as e: res = e.status_obj expected_res = [(2, 1)] self.assertEqual(expected_res, res.getlinepairs_lt(2)) try: res.getlinepairs_lt(0) self.fail() except AssertionError as e: pass def test_getwordpairs_gt(self): bip39 = BIP39WordList("levdist_gt2", string=levdist_gt2) try: res = bip39.test_lev_distance(2) except ValidationFailed as e: res = e.status_obj expected_res = [("brown", "brpyt")] self.assertEqual(expected_res, res.getwordpairs_gt(2)) try: res.getwordpairs_gt(0) self.fail() except AssertionError as e: pass def test_getlinepairs_gt(self): bip39 = BIP39WordList("levdist_gt2", string=levdist_gt2) try: res = bip39.test_lev_distance(2) except ValidationFailed as e: res = e.status_obj expected_res = [(1, 2)] self.assertEqual(expected_res, res.getlinepairs_gt(2)) try: res.getlinepairs_gt(0) self.fail() except AssertionError as e: pass def test_getwordpairs_list(self): concat = "\n".join([levdist_le2]+["zzyzx"]) bip39 = BIP39WordList("levdist_concat", string=concat) try: res = bip39.test_lev_distance(2) except ValidationFailed as e: res = e.status_obj expected_res = [("brol", "brow")] self.assertEqual(expected_res, res.getwordpairs_list([1,2])) for t in ["abc", [], ["a"], 0]: try: res.getwordpairs_list(t) self.fail() except AssertionError as e: pass def test_getlinepairs_list(self): concat = "\n".join([levdist_le2]+["zzyzx"]) bip39 = BIP39WordList("levdist_concat", string=concat) try: res = bip39.test_lev_distance(2) except ValidationFailed as e: res = e.status_obj expected_res = [(2, 1)] self.assertEqual(expected_res, res.getlinepairs_list([1,2])) for t in ["abc", [], ["a"], 0]: try: res.getlinepairs_list(t) self.fail() except AssertionError as e: pass def test_getdist(self): bip39 = BIP39WordList("levdist_le2", string=levdist_le2) try: res = bip39.test_lev_distance(2) except ValidationFailed as e: res = e.status_obj expected_res = 1 self.assertEqual(expected_res, res.getdist("brow", "brol")) for t in [(1, "abc"), ("", "abc"), ("ABC", "abc"), ("abc", 1), ("abc", ""), ("abc", "ABC")]: try: res.getdist(*t) self.fail() except AssertionError as e: pass def test_getdist_all(self): bip39 = BIP39WordList("levdist_le2", string=levdist_le2) try: res = bip39.test_lev_distance(2) except ValidationFailed as e: res = e.status_obj expected_res = [(("brol", "brow"), (2, 1), 1)] self.assertEqual(expected_res, res.getdist_all("brow")) for t in [1, "", "ABC"]: try: res.getdist_all(t) self.fail() except AssertionError as e: pass def test_getdist_all_eq(self): bip39 = BIP39WordList("levdist_le2", string=levdist_le2) try: res = bip39.test_lev_distance(2) except ValidationFailed as e: res = e.status_obj expected_res = [(("brol", "brow"), (2, 1), 1)] self.assertEqual(expected_res, res.getdist_all_eq("brow", 1)) for t in [1, "", "ABC"]: try: res.getdist_all_eq(t, 1) self.fail() except AssertionError as e: pass except KeyError as e: pass try: res.getdist_all_eq("abc", 0) self.fail() except AssertionError as e: pass except KeyError as e: pass def test_getdist_all_lt(self): bip39 = BIP39WordList("levdist_le2", string=levdist_le2) try: res = bip39.test_lev_distance(2) except ValidationFailed as e: res = e.status_obj expected_res = [(("brol", "brow"), (2, 1), 1)] self.assertEqual(expected_res, res.getdist_all_lt("brow", 2)) for t in [1, "", "ABC"]: try: res.getdist_all_lt(t, 1) self.fail() except AssertionError as e: pass except KeyError as e: pass try: res.getdist_all_lt("abc", 0) self.fail() except AssertionError as e: pass except KeyError as e: pass def test_getdist_all_gt(self): bip39 = BIP39WordList("levdist_gt2", string=levdist_gt2) try: res = bip39.test_lev_distance(2) except ValidationFailed as e: res = e.status_obj expected_res = [(("brpyt", "brown"), (2, 1), 3)] self.assertEqual(expected_res, res.getdist_all_gt("brown", 2)) for t in [1, "", "ABC"]: try: res.getdist_all_gt(t, 1) self.fail() except AssertionError as e: pass try: res.getdist_all_gt("abc", 0) self.fail() except AssertionError as e: pass except KeyError as e: pass def test_getdist_all_list(self): concat = "\n".join([levdist_le2]+["zzyzx"]) bip39 = BIP39WordList("concat", string=concat) try: res = bip39.test_lev_distance(2) except ValidationFailed as e: res = e.status_obj expected_res = [(("brol", "brow"), (2, 1), 1)] self.assertEqual(expected_res, res.getdist_all_list("brow", [1])) for t in [1, "", "ABC"]: for u in ["abc", [], ["a"], 0]: try: res.getdist_all_list(t, u) self.fail() except AssertionError as e: pass except KeyError as e: pass

33.076613

73

0.536633

922

8,203

4.590022

0.069414

0.026229

0.038043

0.112476

0.889887

0.884688

0.851371

0.825142

0.804112

0

0.036539

0.356089

8,203

247

74

33.210526

0.764672

0.006583

0

0.734783

0

0.044311

0

0.134783

1

0.06087

false

0.1

0.013043

0

0.078261

0

null

0

1

0

1

0

null

0

1

0

8

bdfb8afb236fa2a59d4614b476d34a5d38aae988

694

py

Python

landscapes/scripts/convert_fitness_to_s.py

Peyara/Evolution-Counterdiabatic-Driving

e695fad703b2d339bed0013e5b4254ba2365c105

[ "MIT" ]

3

2020-08-24T20:24:41.000Z

2020-08-26T02:16:16.000Z

landscapes/scripts/convert_fitness_to_s.py

hincz-lab/Evolution-Counterdiabatic-Driving

e695fad703b2d339bed0013e5b4254ba2365c105

[ "MIT" ]

null

landscapes/scripts/convert_fitness_to_s.py

hincz-lab/Evolution-Counterdiabatic-Driving

e695fad703b2d339bed0013e5b4254ba2365c105

[ "MIT" ]

null

import sys import numpy as np # This script takes in a file with fitness values separated by commas # and converts the values to be s values (relative fitness as used in # the model) instead. # WARNING: Overwrites given file! if len(sys.argv) < 2: print("Usage: python convert_fitness_to_s.py [name of file to convert]") data = [] # Read in fitness values with open(sys.argv[1]) as infile: data = [float(i.strip()) for i in infile.readline().split(",")] # Do conversion data = [np.format_float_positional(data[-1]/i - 1) if i != 0 else 10000000000000 for i in data] # Write out s values with open(sys.argv[1], "w") as outfile: outfile.write(",".join([str(i) for i in data]))

30.173913

95

0.695965

119

694

4.016807

0.546218

0.043933

0.037657

0.07113

0.09205

0

0.035149

0.180115

694

23

96

30.173913

0.804921

0.353026

0

0.149321

0.052036

0

1

0

false

0

0.2

0

0.2

0.1

0

null

0

null

0

1

0

bdfc1be607446f5c58bd0a13c161e7d2e69d78e2

4,629

py

Python

test/test_ui/test_render.py

hrnciar/poezio

12b8af11df35dda535412b0c02ba792890095a7d

[ "Zlib" ]

50

2015-02-11T12:00:25.000Z

2022-01-18T05:26:40.000Z

test/test_ui/test_render.py

hrnciar/poezio

12b8af11df35dda535412b0c02ba792890095a7d

[ "Zlib" ]

3

2017-11-27T20:55:42.000Z

2020-03-20T18:05:53.000Z

test/test_ui/test_render.py

hrnciar/poezio

12b8af11df35dda535412b0c02ba792890095a7d

[ "Zlib" ]

15

2015-04-22T14:33:36.000Z

2021-09-29T21:33:50.000Z

import pytest from contextlib import contextmanager from datetime import datetime from poezio.theming import get_theme from poezio.ui.render import build_lines, Line, write_pre from poezio.ui.types import BaseMessage, Message, StatusMessage, XMLLog def test_simple_build_basemsg(): msg = BaseMessage(txt='coucou') line = build_lines(msg, 100, True, 10)[0] assert (line.start_pos, line.end_pos) == (0, 6) def test_simple_render_message(): msg = Message(txt='coucou', nickname='toto') line = build_lines(msg, 100, True, 10)[0] assert (line.start_pos, line.end_pos) == (0, 6) def test_simple_render_xmllog(): msg = XMLLog(txt='coucou', incoming=True) line = build_lines(msg, 100, True, 10)[0] assert (line.start_pos, line.end_pos) == (0, 6) def test_simple_render_separator(): line = build_lines(None, 100, True, 10)[0] assert line is None def test_simple_render_status(): class Obj: name = 'toto' msg = StatusMessage("Coucou {name}", {'name': lambda: Obj.name}) assert msg.txt == "Coucou toto" Obj.name = 'titi' build_lines(msg, 100, True, 10)[0] assert msg.txt == "Coucou titi" class FakeBuffer: def __init__(self): self.text = '' @contextmanager def colored_text(self, *args, **kwargs): yield None def addstr(self, txt): self.text += txt @pytest.fixture(scope='function') def buffer(): return FakeBuffer() @pytest.fixture def time(): return datetime.strptime('2019-09-27 10:11:12', '%Y-%m-%d %H:%M:%S') def test_write_pre_basemsg(buffer): str_time = '10:11:12' time = datetime.strptime(str_time, '%H:%M:%S') msg = BaseMessage(txt='coucou', time=time) size = write_pre(msg, buffer, True, 10) assert buffer.text == '10:11:12 ' assert size == len(buffer.text) def test_write_pre_message_simple(buffer, time): msg = Message(txt='coucou', nickname='toto', time=time) size = write_pre(msg, buffer, True, 10) assert buffer.text == '10:11:12 toto> ' assert size == len(buffer.text) def test_write_pre_message_simple_history(buffer, time): msg = Message(txt='coucou', nickname='toto', time=time, history=True) size = write_pre(msg, buffer, True, 10) assert buffer.text == '2019-09-27 10:11:12 toto> ' assert size == len(buffer.text) def test_write_pre_message_highlight(buffer, time): msg = Message(txt='coucou', nickname='toto', time=time, highlight=True) size = write_pre(msg, buffer, True, 10) assert buffer.text == '10:11:12 toto> ' assert size == len(buffer.text) def test_write_pre_message_no_timestamp(buffer): msg = Message(txt='coucou', nickname='toto') size = write_pre(msg, buffer, False, 10) assert buffer.text == 'toto> ' assert size == len(buffer.text) def test_write_pre_message_me(buffer, time): msg = Message(txt='/me coucou', nickname='toto', time=time) size = write_pre(msg, buffer, True, 10) assert buffer.text == '10:11:12 * toto ' assert size == len(buffer.text) def test_write_pre_message_revisions(buffer, time): msg = Message(txt='coucou', nickname='toto', time=time, revisions=5) size = write_pre(msg, buffer, True, 10) assert buffer.text == '10:11:12 toto5> ' assert size == len(buffer.text) def test_write_pre_message_revisions_me(buffer, time): msg = Message(txt='/me coucou', nickname='toto', time=time, revisions=5) size = write_pre(msg, buffer, True, 10) assert buffer.text == '10:11:12 * toto5 ' assert size == len(buffer.text) def test_write_pre_message_ack(buffer, time): ack = get_theme().CHAR_ACK_RECEIVED expected = '10:11:12 %s toto> ' % ack msg = Message(txt='coucou', nickname='toto', time=time, ack=1) size = write_pre(msg, buffer, True, 10) assert buffer.text == expected assert size == len(buffer.text) def test_write_pre_message_nack(buffer, time): nack = get_theme().CHAR_NACK expected = '10:11:12 %s toto> ' % nack msg = Message(txt='coucou', nickname='toto', time=time, ack=-1) size = write_pre(msg, buffer, True, 10) assert buffer.text == expected assert size == len(buffer.text) def test_write_pre_xmllog_in(buffer): msg = XMLLog(txt="coucou", incoming=True) size = write_pre(msg, buffer, True, 10) assert buffer.text == '%s IN ' % msg.time.strftime('%H:%M:%S') assert size == len(buffer.text) def test_write_pre_xmllog_out(buffer): msg = XMLLog(txt="coucou", incoming=False) size = write_pre(msg, buffer, True, 10) assert buffer.text == '%s OUT ' % msg.time.strftime('%H:%M:%S') assert size == len(buffer.text)

31.924138

76

0.669259

684

4,629

4.378655

0.141813

0.066778

0.04808

0.0601

0.696828

0.689816

0.611018

0.601336

0

0.039164

0.183625

4,629

144

77

32.145833

0.753374

0

0.321101

0

0.093109

0

0.275229

1

0.201835

false

0

0.055046

0.018349

0.302752

0

null

0

1

0

null

0

1

0

2

bdfcac80e4077fb1f2378b55cba1401431e2ffec

1,099

py

Python

eats/behave/driver_steps.py

Etiqa/eats

8c8e2da93d0014f6fbb208185712c5526dba1174

[ "BSD-2-Clause" ]

null

eats/behave/driver_steps.py

Etiqa/eats

8c8e2da93d0014f6fbb208185712c5526dba1174

[ "BSD-2-Clause" ]

5

2021-03-18T21:34:44.000Z

2022-03-11T23:35:23.000Z

eats/behave/driver_steps.py

Etiqa/eats

8c8e2da93d0014f6fbb208185712c5526dba1174

[ "BSD-2-Clause" ]

null

from behave import * from hamcrest import * from selenium.common.exceptions import RemoteDriverServerException from eats.pyhamcrest import array_equal_to_by_key from eats.utils.mapping import table_mapping from ..users import Users @when(u'I press "{key}" key') @when(u'{user_name:Username} presses "{key}" key') def step_impl(context, key, user_name=Users.DEFAULT_USERNAME): user = context.users.get(user_name) application = user.current_application assert_that( calling(application.driver.send_special_key).with_args(key), not(raises(RemoteDriverServerException)), "{unsupported} key is not supported".format(unsupported=key) ) @then(u'{user_name:Username} should have "{name}" meta contents element') def step_impl(context, user_name, name): user = context.users.get(user_name) application = user.current_application contents = application.driver.get_metadata_elements_content_by_name(name) keys = context.table.headings assert_that(table_mapping(contents, keys=keys), array_equal_to_by_key(table_mapping(context.table), "content"))

40.703704

115

0.767971

147

1,099

5.52381

0.408163

0.059113

0.029557

0.034483

0.189655

0.147783

0

0.128298

1,099

27

115

40.703704

0.847599

0

0.173913

0

0.148182

0

0.086957

1

0.086957

false

0

0.26087

0

0.347826

0

null

0

null

0

1

0

bdfcb80abeeba8ef801afb6b8c9b9a48834e2016

5,526

py

Python

homebytwo/routes/utils.py

drixselecta/homebytwo

29d26ce9f5586943e3b64c95aa4ce9ea7263bd10

[ "MIT" ]

7

2018-03-10T20:58:59.000Z

2021-08-22T17:18:09.000Z

homebytwo/routes/utils.py

HomebyTwo/homebytwo

29d26ce9f5586943e3b64c95aa4ce9ea7263bd10

[ "MIT" ]

69

2017-02-01T21:15:43.000Z

2022-02-26T09:33:27.000Z

homebytwo/routes/utils.py

drixselecta/homebytwo

29d26ce9f5586943e3b64c95aa4ce9ea7263bd10

[ "MIT" ]

null

from collections import namedtuple from itertools import accumulate, chain, islice, tee from pathlib import Path from django.contrib.gis.db.models.functions import Distance, LineLocatePoint from django.contrib.gis.measure import D from .fields import LineSubstring from .models import ActivityType, Place # named tuple to handle Urls Link = namedtuple("Link", ["url", "text"]) GARMIN_ACTIVITY_TYPE_MAP = { ActivityType.ALPINESKI: "resort_skiing_snowboarding", ActivityType.BACKCOUNTRYSKI: "backcountry_skiing_snowboarding", ActivityType.ELLIPTICAL: "elliptical", ActivityType.HANDCYCLE: "cycling", ActivityType.HIKE: "hiking", ActivityType.ICESKATE: "skating", ActivityType.INLINESKATE: "skating", ActivityType.NORDICSKI: "cross_country_skiing", ActivityType.RIDE: "cycling", ActivityType.ROCKCLIMBING: "rock_climbing", ActivityType.ROWING: "rowing", ActivityType.RUN: "running", ActivityType.SNOWBOARD: "resort_skiing_snowboarding", ActivityType.SNOWSHOE: "hiking", ActivityType.STAIRSTEPPER: "fitness_equipment", ActivityType.STANDUPPADDLING: "stand_up_paddleboarding", ActivityType.SWIM: "swimming", ActivityType.VIRTUALRIDE: "cycling", ActivityType.VIRTUALRUN: "running", ActivityType.WALK: "walk", ActivityType.WEIGHTTRAINING: "fitness_equipment", ActivityType.WORKOUT: "strength_training", } def get_image_path(instance, filename): """ callable to define the image upload path according to the type of object: segment, route, etc.. as well as the id of the object. """ return Path("images", instance.__class__.__name__, str(instance.id), filename) def current_and_next(some_iterable): """ use itertools to make current and next item of an iterable available: http://stackoverflow.com/questions/1011938/python-previous-and-next-values-inside-a-loop used to 'create_segments_from_checkpoints'. """ items, nexts = tee(some_iterable, 2) nexts = chain(islice(nexts, 1, None), [None]) return zip(items, nexts) def create_segments_from_checkpoints(checkpoints, start=0, end=1): """ returns a list of segments as tuples with start and end locations along the original line. """ # sorted list of line_locations from the list of places as # well as the start and the end location of the segment where # the places were found. line_locations = chain( [start], [checkpoint.line_location for checkpoint in checkpoints], [end] ) # use the custom iterator, exclude segments where start and end # locations are the same. Also exclude segment where 'nxt == None`. segments = [ (crt, nxt) for crt, nxt in current_and_next(line_locations) if crt != nxt and nxt ] return segments def get_places_from_segment(segment, line, max_distance): """ find places within the segment of a line and annotate them with the line location on the original line. """ start, end = segment # create the Linestring geometry subline = LineSubstring(line, start, end) # find places within max_distance of the linestring places = get_places_from_line(subline, max_distance) # iterate over found places to change the line_location # from the location on the segment to the location on # the original linestring. for place in places: # relative line location to the start point of the subline length = place.line_location * (end - start) # update attribute with line location on the original line place.line_location = start + length return places def get_places_from_line(line, max_distance): """ returns places within a max_distance of a Linestring Geometry ordered by, and annotated with the `line_location` and the `distance_from_line`: * `line_location` is the location on the line expressed as a float between 0.0 and 1.0. * `distance_from_line` is a geodjango Distance object. """ # convert max_distance to Distance object max_d = D(m=max_distance) # find all places within max distance from line places = Place.objects.filter(geom__dwithin=(line, max_d)) # annotate with distance to line places = places.annotate(distance_from_line=Distance("geom", line)) # annotate with location along the line between 0 and 1 places = places.annotate(line_location=LineLocatePoint(line, "geom")) # remove start and end places within 1% of start and end location places = places.filter( line_location__gt=0.01, line_location__lt=0.99, ) # sort in order of appearance along the line places = places.order_by("line_location") return places def get_places_within(point, max_distance=100): # make range a distance object max_d = D(m=max_distance) # get places within range places = Place.objects.filter(geom__distance_lte=(point, max_d)) # annotate with distance places = places.annotate(distance_from_line=Distance("geom", point)) # sort by distance places = places.order_by( "distance_from_line", ) return places def get_distances(points): """ Return a list with the distance of each point relative to the previous one in the list. """ def get_relative_distances(): if points: yield 0 yield from (p2.distance(p1) for p1, p2 in zip(points[1:], points)) return list(accumulate(get_relative_distances()))

31.758621

92

0.707926

711

5,526

5.35865

0.298172

0.040945

0.025197

0.016535

0.096588

0.056693

0.04147

0

0.00755

0.209012

5,526

173

93

31.942197

0.864104

0.344734

0

0.061728

0

0.097864

0.0306

0

1

0.098765

false

0

0.08642

0

0.271605

0

null

0

null

0

1

0

bdfe275d909128740904498e8c3a21dcaa2bafb4

263

py

Python

aureaSym.py

osmartormena/introMATLAB

6e505a17d6666d92b4502eff746f4b4dcdcd3c1c

[ "CC0-1.0" ]

null

aureaSym.py

osmartormena/introMATLAB

6e505a17d6666d92b4502eff746f4b4dcdcd3c1c

[ "CC0-1.0" ]

null

aureaSym.py

osmartormena/introMATLAB

6e505a17d6666d92b4502eff746f4b4dcdcd3c1c

[ "CC0-1.0" ]

null

# Cálculo da razão áurea (phi) import sympy d = 20 phi = sympy.symbols('phi', nonnegative=True) eqn = sympy.Eq(1/phi, phi - 1) sol = sympy.solve(eqn) sympy.pprint(sol) phiAprox = sympy.N(sol[0], d) print('Para ', d, ' dígitos significativos, ϕ = ', phiAprox)

18.785714

60

0.669202

42

263

4.190476

0.619048

0.090909

0

0.022727

0.163498

263

13

61

20.230769

0.777273

0.106464

0

0.158798

0

1

0

false

0

0.125

0

0.125

0.25

0

null

0

null

0

1

0

bdfe32d084754eda156889373513889dc3a4c1f0

15,732

py

Python

core/src/structs_classes/extract_structs.py

azurlane-doujin/AzurLanePaintingExtract-v1.0

ef4f25e70b3ca1b9df4304132cc7612c8f5efebb

[ "MIT" ]

144

2019-06-13T06:43:43.000Z

2022-03-29T15:07:57.000Z

core/src/structs_classes/extract_structs.py

Shabi1213/AzurLanePaintingExtract-v1.0

ef4f25e70b3ca1b9df4304132cc7612c8f5efebb

[ "MIT" ]

2

2020-08-02T15:08:58.000Z

2021-11-29T02:34:18.000Z

core/src/structs_classes/extract_structs.py

Shabi1213/AzurLanePaintingExtract-v1.0

ef4f25e70b3ca1b9df4304132cc7612c8f5efebb

[ "MIT" ]

19

2020-03-01T10:06:52.000Z

2022-02-06T13:49:26.000Z

import collections import os import re import time from itertools import filterfalse import wx from core.src.static_classes.static_data import GlobalData from core.src.structs_classes.basic_class import BasicInfo, BasicInfoList class PerInfo(BasicInfo): def __init__(self, name, val, has_cn): super(PerInfo, self).__init__(name, val) self.sub_data = 1 self.tex_step = 2 self.mesh_step=2 self.data = GlobalData() # tree储存结构组 self._tex_path = "Empty" self.more_tex = ["Empty"] self._mesh_path = "Empty" self.more_mesh = ["Empty"] # 目标文件位置 self.lay_in = "" # 是否可以使用还原 self._is_able_work = False # 导出目标位置 self._save_path: str = "" # 中文名称 self.cn_name = val self.has_cn = has_cn # 父组件 self.parent = None self.must_able = False # tree ID self.key = ... self.tree_ID = ... self.tex_id = ... self.more_tex_per_id = [] self.mesh_id = ... self.more_mesh_per_id = [] self.action_group = [ "independent", "face_match", "atlas_split", "set_able", "split_only", "remove_item", "sprite_spilt" ] # 是否以中文保存 self._is_save_as_cn = True def __contains__(self, item): if self.name in item or self.cn_name in item: return True else: return False @property def is_able_work(self): if self.must_able: return True else: return self._is_able_work @property def tex_path(self): return self._tex_path @tex_path.setter def tex_path(self, value): self._tex_path = value self._is_able_work = self.is_able() @property def mesh_path(self): return self._mesh_path @mesh_path.setter def mesh_path(self, value): self._mesh_path = value self._is_able_work = self.is_able() @property def save_path(self): return self._save_path @save_path.setter def save_path(self, value): if self._is_save_as_cn: self._save_path = os.path.join(value, self.cn_name + ".png") else: self._save_path = os.path.join(value, self.name + ".png") @property def is_save_as_cn(self): return self._is_save_as_cn @is_save_as_cn.setter def is_save_as_cn(self, value): if isinstance(value, bool): self._is_save_as_cn = value @staticmethod def is_def(val): return bool(val) def get_is_able_work(self): return self._is_able_work def is_able(self): if os.path.isfile(self.tex_path) and os.path.isfile(self.mesh_path): return True else: return False def transform_able(self): self.must_able = not self.must_able def set_single_path(self, path): self._save_path = path def append_item_tree(self, tree: wx.TreeCtrl): # 名称 self.key = key = tree.AppendItem(self.tree_ID, f"名称：{self.cn_name}") if self.is_able_work: tree.SetItemTextColour(key, wx.Colour(253, 86, 255)) tree.AppendItem(self.tree_ID, f"索引名称：{self.name}") # texture self.tex_id = tree.AppendItem(self.tree_ID, f"Texture文件路径：{self.tex_path}") more_tex_id = tree.AppendItem(self.tree_ID, f"其他Texture路径({len(self.more_tex)})") for each_path in self.more_tex: val = tree.AppendItem(more_tex_id, each_path) self.more_tex_per_id.append(val) # mesh self.mesh_id = tree.AppendItem(self.tree_ID, f"Mesh文件路径：{self.mesh_path}") more_mesh_id = tree.AppendItem(self.tree_ID, f"其他Mesh路径({len(self.more_mesh)})") for each_path in self.more_mesh: val = tree.AppendItem(more_mesh_id, each_path) self.more_mesh_per_id.append(val) action_root = tree.AppendItem(self.tree_ID, "功能按键") # 功能键 independent = self.action_group[self.data.at_independent] = tree.AppendItem(action_root, "将当前的组合独立") tree.SetItemTextColour(independent, wx.Colour(255, 0, 166)) face_match = self.action_group[self.data.at_face_match] = tree.AppendItem(action_root, "为当前立绘添加附加表情") tree.SetItemTextColour(face_match, wx.Colour(0, 16, 166)) atlas_spilt = self.action_group[self.data.at_atlas_split] = tree.AppendItem(action_root, "进行Q版小人切割") tree.SetItemTextColour(atlas_spilt, wx.Colour(140, 0, 166)) sprite_spilt = self.action_group[self.data.at_sprite_split] = tree.AppendItem(action_root, "进行Sprite切割 ") tree.SetItemTextColour(sprite_spilt, wx.Colour(248, 40, 255)) set_able = self.action_group[self.data.at_set_able] = tree.AppendItem(action_root, f"强制转换为可还原状态【当前{self.must_able}】") tree.SetItemTextColour(set_able, wx.Colour(255, 177, 166)) split_only = self.action_group[self.data.at_split_only] = tree.AppendItem(action_root, "仅进行立绘还原切割 ") tree.SetItemTextColour(split_only, wx.Colour(248, 66, 255)) remove_item = self.action_group[self.data.at_remove_item] = tree.AppendItem(action_root, "删除该元素 ") tree.SetItemTextColour(remove_item, wx.Colour(248, 0, 255)) def append_to_tree(self, tree: wx.TreeCtrl, tree_root: wx.TreeItemId): """ 添加到树，构建tree列表 :param tree: tree 对象 :param tree_root: 根id :return: """ self.more_mesh_per_id.clear() self.more_tex_per_id.clear() self.tree_ID = tree.AppendItem(tree_root, self.cn_name) self.append_item_tree(tree) def get_select(self, type_is: bool): """ 获取选中的列表 :param type_is: true ：texture，false：mesh :return: list，选中的列表 """ if type_is: return self.more_tex else: return self.more_mesh # 路径设置相关 def set_tex(self, index): self.tex_path = self.more_tex[index] return self.tex_id, f"Texture文件路径：{self.tex_path}" def set_mesh(self, index): self.mesh_path = self.more_mesh[index] return self.mesh_id, f"Mesh文件路径：{self.mesh_path}" def add_save(self, path): self.save_path = path def clear_tex(self): self.tex_id, self.more_tex, self.tex_path, self.more_tex_per_id = None, [], "Empty", [] def clear_mesh(self): self.mesh_id, self.more_mesh, self.mesh_path, self.more_mesh_per_id = None, [], "Empty", [] def build_sub(self, value_type, file_type, index): """ 从自身的treeid中寻找目标 :param value_type: :param file_type: :param index: :return: """ val = PerInfo(self.name, self.val, self.has_cn) if value_type == self.data.td_single: if file_type == self.data.td_texture_type: val.tex_path = self.tex_path elif file_type == self.data.td_mesh_type: val.mesh_path = self.mesh_path elif value_type == self.data.td_list_item: if file_type == self.data.td_texture_type: val.tex_path = self.more_tex[index] elif file_type == self.data.td_mesh_type: val.mesh_path = self.more_mesh[index] return os.path.isfile(val.tex_path), val def independent(self, name, tree, tree_root): # 独立 target = PerInfo(name, f"{self.val}-# {self.sub_data}", self.has_cn) target.tex_path = self.tex_path target.mesh_path = self.mesh_path target.append_to_tree(tree, tree_root) self.parent[target.name] = target self.sub_data += 1 class PerWorkList(BasicInfoList): def __init__(self, item: collections.abc.Iterable = None, mesh_match=None, texture_match=None, is_ignore_case=False): super(PerWorkList, self).__init__(item) self.is_ignore_case = is_ignore_case self.texture_match = texture_match self.mesh_match = mesh_match self.data = GlobalData() # 显示部分 def show_in_tree(self, tree, tree_root): list(map(lambda x: self._info_dict[x].append_to_tree(tree, tree_root), self._key_list)) def append(self, name, cn_name, has_cn): value = PerInfo(name, cn_name, has_cn) self[value.name] = value return value def remove(self, item: collections.abc.Iterable): return PerWorkList(super(PerWorkList, self).remove(item)) # 查找部分 def find_by_id(self, id): values = list(filter(lambda x: self._info_dict[x].tree_ID == id, self._key_list)) if values.__len__() == 0: return False, None return True, self[values[0]] def find_in_each(self, id) -> (bool, bool, bool, int, PerInfo): """ 从每一个中寻找指定id :param id: :return: (是否成功，类型【单个True，列表False】，类型[tex(True),mesh(False)]，索引，对象本身) """ target = None for value in self: # 如果id为以下的部分，进入 if id == value.tex_id == id or id in value.more_tex_per_id or value.mesh_id == id or \ id in value.more_mesh_per_id: target = value if target is None: return False, False, False, -1, None if id == target.tex_id: return True, self.data.td_single, self.data.td_texture_type, 0, target elif id == target.mesh_id: return True, self.data.td_single, self.data.td_mesh_type, 0, target elif id in target.more_tex_per_id: return True, self.data.td_list_item, self.data.td_texture_type, target.more_tex_per_id.index(id), target elif id in target.more_mesh_per_id: return True, self.data.td_list_item, self.data.td_mesh_type, target.more_mesh_per_id.index(id), target def find_action(self, id) -> (bool, int, PerInfo): """ 查找是否为特殊动作按键 :param id: :return: 是否成功【true/false】，动作类型，作用目标 """ target = None for value in self: # 如果id为以下的部分，进入 if id in value.action_group: target = value break if target is None: return False, -1, target else: index = target.action_group.index(id) return True, index, target # 添加部分 def set_tex(self, value, name=None): """ 添加贴图 :param name: [可选]新添加的texture地址的指向项目名称，为None会根据value获取 :param value: 新添加的texture地址 :return: """ has_ = False if isinstance(value, str) and os.path.isfile(value): if name is not None: key = name else: key = os.path.splitext(os.path.basename(value))[0] if re.match(r'.+\s#\d+\.png', value, re.IGNORECASE): has_ = True key = re.split(r'\s#\d+(\[alpha\])?$', key)[0] # 赋值过程 val: PerInfo = self._info_dict[key] if value not in val.more_tex: val.more_tex.append(value) lower_path = os.path.split(value)[0].lower() # 如果非空考虑优先级 if 0 < val.tex_step and lower_path.endswith(self.texture_match[0]): val.tex_path = value val.tex_step = 0 elif 1 < val.tex_step and lower_path.endswith(self.texture_match[1]): val.tex_path = value val.tex_step = 1 else: val.tex_path = value val.tex_step = 2 if not has_: val.tex_path = value def set_mesh(self, value, name=None): """ 添加mesh网格 :param name: [可选]新添加的mesh地址的指向项目名称，为None会根据value获取 :param value: 新添加的mesh地址 :return: """ has_ = False if isinstance(value, str) and os.path.isfile(value): if name is not None: key = name else: key = os.path.splitext(os.path.basename(value))[0] if re.match(r'.+\s#\d+\.obj', value, re.IGNORECASE): has_ = True key = re.split(r'\s#\d+(\[alpha\])?$', key)[0] val: PerInfo = self._info_dict[key] if value not in val.more_mesh: val.more_mesh.append(value) lower_path = os.path.split(value)[0].lower() # 如果非空考虑优先级 if 0 < val.mesh_step and lower_path.endswith(self.mesh_match[0]): val.mesh_path = value val.mesh_step = 0 elif 1 < val.mesh_step and lower_path.endswith(self.mesh_match[1]): val.mesh_path = value val.mesh_step = 1 else: val.mesh_path = value val.mesh_step = 2 if not has_: val.mesh_path = value def append_name(self, name, names: dict, *, has_cn=False): """ 添加新对象 :param names: 预设键-值对应组 :param name: 对象索引key :param has_cn: 对象是否有中文名 :return: """ # if name == "unknown4": # print(name) if self.is_ignore_case: name=name.lower() if name not in self._key_list: if name not in names.keys(): has_cn = False target_cn = name else: has_cn = True target_cn = names[name] # 如果中文名为空，也认为没有中文名 if target_cn == "": target_cn = name has_cn = False value = PerInfo(name, target_cn, has_cn) value.parent = self self[name] = value return name else: return name # 清空部分 def clear_mesh(self): list(map(lambda x: x.clear_mesh(), self)) def clear_tex(self): list(map(lambda x: x.clear_tex(), self)) # 生成部分 def build_able(self): val = filter(lambda x: x.get_is_able_work(), self) value = PerWorkList(val) return value def build_unable(self): val = filterfalse(lambda x: x.get_is_able_work(), self) value = PerWorkList(val) return value def build_search(self): val = map(lambda x: f"{x.name}{x.cn_name}", self) return list(val) def build_filter(self): val = map(lambda x: f"{x.name}", self) val = list(enumerate(list(val), 0)) return val def build_skip(self, filename): filename = list(map(lambda x: os.path.splitext(os.path.basename(x))[0], filename)) val = filter(lambda x: x in filename, self) return PerWorkList(val) def build_from_indexes(self, indexes): val = map(lambda x: self[x], indexes) value = PerWorkList(val) return value def build_from_pattern(self, pattern): val = list(filter(lambda x: re.match(pattern, list(x)[1]), self.build_filter())) val = list(zip(*val)) if len(val) == 2: return self.build_from_indexes(val[0]) else: return PerWorkList()

33.189873

117

0.557335

1,992

15,732

4.165161

0.11496

0.022177

0.016874

0.010124

0.42883

0.343136

0.252139

0.191877

0.164156

0

0.009229

0.3388

15,732

473

118

33.260042

0.788406

0.054475

0

0.267913

0

0.037146

0.014171

0

1

0.140187

false

0

0.024922

0.021807

0.28972

0

null

0

null

0

1

0

bdff65087e9d7a27500aa847fc385ea3b6c07441

3,950

py

Python

scbw_mq/tournament/benchmark/storage.py

Games-and-Simulations/sc-mq

f9ae798948add7fd84b77d75ca26ade94620f84e

[ "MIT" ]

2

2018-05-10T18:10:28.000Z

2018-05-13T18:14:33.000Z

scbw_mq/tournament/benchmark/storage.py

Games-and-Simulations/sc-mq

f9ae798948add7fd84b77d75ca26ade94620f84e

[ "MIT" ]

1

2019-09-20T14:14:49.000Z

scbw_mq/tournament/benchmark/storage.py

Games-and-Simulations/sc-mq

f9ae798948add7fd84b77d75ca26ade94620f84e

[ "MIT" ]

null

import logging import os import shutil from os.path import exists from typing import Optional from scbw.map import check_map_exists from scbw.player import check_bot_exists from scbw.utils import download_extract_zip from ...utils import read_lines logger = logging.getLogger(__name__) class BenchmarkException(Exception): pass class RerunningBenchmarkException(BenchmarkException): pass class Benchmark: bot_file: str map_file: str elo_file: str repeat_games: int bot_dir: str map_dir: str result_dir: str def check_structure(self): if not exists(f"{self.bot_file}"): raise BenchmarkException(f"Bot file cannot be found in {self.bot_file}") if not exists(self.map_file): raise BenchmarkException(f"Map file cannot be found in {self.map_file}") if not exists(self.elo_file): raise BenchmarkException(f"Elo file cannot be found in {self.elo_file}") if not exists(self.bot_dir): raise BenchmarkException(f"Bot dir cannot be found in {self.bot_dir}") if not exists(f"{self.map_dir}"): raise BenchmarkException(f"Map dir cannot be found in {self.map_dir}") if not exists(f"{self.result_dir}"): raise BenchmarkException(f"Result dir cannot be found in {self.result_dir}") bots = read_lines(self.bot_file) for bot in bots: check_bot_exists(bot, self.bot_dir) maps = read_lines(self.map_file) for map_file in maps: check_map_exists(f"{self.map_dir}/{map_file}") def has_results(self): return len(os.listdir(self.result_dir)) > 0 class BenchmarkStorage: def find_benchmark(self, name: str) -> Optional[Benchmark]: raise NotImplemented def get_benchmark(self, local_benchmark_dir): with open(f'{local_benchmark_dir}/BENCHMARK_REPEAT_GAMES', 'r') as f: repeat_games = int(f.read().strip()) benchmark = Benchmark() benchmark.bot_file = f"{local_benchmark_dir}/BENCHMARK_BOTS" benchmark.map_file = f"{local_benchmark_dir}/BENCHMARK_MAPS" benchmark.elo_file = f"{local_benchmark_dir}/BENCHMARK_ELOS" benchmark.bot_dir = f"{local_benchmark_dir}/bots" benchmark.map_dir = f"{local_benchmark_dir}/maps" benchmark.result_dir = f"{local_benchmark_dir}/results" benchmark.repeat_games = repeat_games return benchmark class LocalBenchmarkStorage(BenchmarkStorage): def __init__(self, base_dir: str): self.base_dir = base_dir def find_benchmark(self, name: str) -> Optional[Benchmark]: if exists(self.benchmark_dir(name)): return self.get_benchmark(self.benchmark_dir(name)) return None def benchmark_dir(self, benchmark_name: str): return f'{self.base_dir}/{benchmark_name}' class SscaitBenchmarkStorage(LocalBenchmarkStorage): BASE_URL = "http://sscaitournament.com/benchmarks" def find_benchmark(self, name: str) -> Optional[Benchmark]: if not name.startswith("SSCAIT"): return None if exists(self.benchmark_dir(name)): return self.get_benchmark(self.benchmark_dir(name)) return self.try_download(name) def try_download(self, name: str) -> Optional[Benchmark]: benchmark_dir = self.benchmark_dir(name) try: os.makedirs(benchmark_dir, exist_ok=False) download_extract_zip(f"{self.BASE_URL}/{name}.zip", benchmark_dir) return self.get_benchmark(benchmark_dir) except Exception as e: logger.exception(f"Failed to download benchmark {name}") logger.exception(e) logger.info(f"Cleaning up dir {benchmark_dir}") shutil.rmtree(self.benchmark_dir(name)) return None # Feel free to include other benchmark sources! # But they need to respect benchmark / bot structure :)

31.854839

88

0.678481

517

3,950

4.969052

0.197292

0.093422

0.052939

0.049046

0.317633

0.234332

0.111327

0.0942

0.059167

0

0.000328

0.227848

3,950

123

89

32.113821

0.841967

0.025063

0

0.137931

0

0.189709

0.082121

0

1

0.103448

false

0.022989

0.103448

0.022989

0.482759

0

null

0

null

0

1

0

bdff857464c359af0d0606a7da2091b6840dd15a

21,855

py

Python

dev-server/scripts/docker-entrypoint.py

circlenaut/docker-images

1768222b496288b6d08a51f979ade97554648817

[ "MIT" ]

null

dev-server/scripts/docker-entrypoint.py

circlenaut/docker-images

1768222b496288b6d08a51f979ade97554648817

[ "MIT" ]

null

dev-server/scripts/docker-entrypoint.py

circlenaut/docker-images

1768222b496288b6d08a51f979ade97554648817

[ "MIT" ]

null

#!/usr/bin/python """ Main Workspace Run Script """ import os import sys import logging import coloredlogs import json import math import glob import yaml import yamale import scripts.functions as func from copy import copy from subprocess import run, call ### Enable logging logging.basicConfig( format="%(asctime)s [%(levelname)s] %(message)s", level=logging.INFO, stream=sys.stdout, ) log = logging.getLogger(__name__) log.info("Starting...") ### Read YAML config file #configs = list() configs_list = dict() #yaml_exts = ["yaml", "yml"] config_path = str() # Load config files with alternative extensions #for ext in yaml_exts: # path = f'/scripts/config.{ext}' # if os.path.exists(path): # configs.append(path) # Check if multiple config files exist and load the user defined one or system/user overwritten one if os.path.exists('/scripts/config.yaml'): config_path = '/scripts/config.yaml' # Validate file schema = yamale.make_schema('/scripts/schema.yaml') data = yamale.make_data(config_path) valid_config = func.yaml_valid(schema, data, "INFO") elif os.path.exists('/scripts/config.yml'): config_path = '/scripts/config.yml' # Validate file schema = yamale.make_schema('/scripts/schema.yaml') data = yamale.make_data(config_path) valid_config = func.yaml_valid(schema, data, "INFO") elif os.path.exists('/scripts/config.yml') and os.path.exists('/scripts/config.yaml'): config_path = '/scripts/config.yml' log.warning("both config.yaml and config.yml exists, using config.yml") if os.path.exists('/scripts/config.yaml'): os.remove('/scripts/config.yaml') # Validate file schema = yamale.make_schema('/scripts/schema.yaml') data = yamale.make_data(config_path) valid_config = func.yaml_valid(schema, data, "INFO") else: log.debug("No yaml config files available to load") # Load config as yaml object if os.path.exists(config_path): if valid_config: log.info(f"Loading config file: '{config_path}'") with open(config_path, "r") as f: configs_list = yaml.load(f, Loader=yaml.FullLoader) log.debug(configs_list) else: log.debug(f"Config does not exist: '{config_path}'") ### Read or set docker default envs docker_env = { 'LOG_VERBOSITY': os.getenv("LOG_VERBOSITY", "INFO"), 'CONFIG_BACKUP_ENABLED': os.getenv("CONFIG_BACKUP_ENABLED", "true"), 'WORKSPACE_USER': os.getenv("WORKSPACE_AUTH_USER", "coder"), 'WORKSPACE_GROUP': os.getenv("WORKSPACE_AUTH_GROUP", "users"), 'WORKSPACE_USER_SHELL': os.getenv("WORKSPACE_USER_SHELL", "zsh"), 'WORKSPACE_USER_PASSWORD': os.getenv("WORKSPACE_AUTH_PASSWORD", "password"), 'RESOURCES_PATH': os.getenv("RESOURCES_PATH", "/resources"), 'WORKSPACE_HOME': os.getenv("WORKSPACE_HOME", "/workspace"), 'APPS_PATH': os.getenv("APPS_PATH", "/apps"), 'DATA_PATH': os.getenv("DATA_PATH", "/data"), 'PROXY_BASE_URL': os.getenv("PROXY_BASE_URL", "/"), 'ZSH_PROMPT': os.getenv("ZSH_PROMPT", "none"), 'ZSH_THEME': os.getenv("ZSH_THEME", "spaceship"), 'ZSH_PLUGINS': os.getenv("ZSH_PLUGINS", "all"), 'CONDA_ENV_PATH': os.getenv("CONDA_ENV_PATH", ""), 'CADDY_VIRTUAL_PORT': os.getenv("VIRTUAL_PORT", "80"), 'CADDY_VIRTUAL_HOST': os.getenv("VIRTUAL_HOST", ""), 'CADDY_VIRTUAL_BIND_NET': os.getenv("VIRTUAL_BIND_NET", "proxy"), 'CADDY_VIRTUAL_PROTO': os.getenv("VIRTUAL_PROTO", "http"), 'CADDY_VIRTUAL_BASE_URL': os.getenv("VIRTUAL_BASE_URL", "/"), 'CADDY_PROXY_ENCODINGS_GZIP': os.getenv("PROXY_ENCODINGS_GZIP", "true"), 'CADDY_PROXY_ENCODINGS_ZSTD': os.getenv("PROXY_ENCODINGS_ZSTD", "true"), 'CADDY_PROXY_TEMPLATES': os.getenv("PROXY_TEMPLATES", "true"), 'CADDY_LETSENCRYPT_EMAIL': os.getenv("LETSENCRYPT_EMAIL", "admin@example.com"), 'CADDY_LETSENCRYPT_ENDPOINT': os.getenv("LETSENCRYPT_ENDPOINT", "dev"), 'CADDY_HTTP_PORT': os.getenv("HTTP_PORT", "80"), 'CADDY_HTTPS_ENABLE': os.getenv("HTTPS_ENABLE", "true"), 'CADDY_HTTPS_PORT': os.getenv("HTTPS_PORT", "443"), 'CADDY_AUTO_HTTPS': os.getenv("AUTO_HTTPS", "true"), 'CADDY_WORKSPACE_SSL_ENABLED': os.getenv("WORKSPACE_SSL_ENABLED", "false"), 'FB_PORT': os.getenv("FB_PORT", "8055"), 'FB_BASE_URL': os.getenv("FB_BASE_URL", "/data"), 'FB_ROOT_DIR': os.getenv("FB_ROOT_DIR", "/workspace"), 'VSCODE_BIND_ADDR': os.getenv("VSCODE_BIND_ADDR", "0.0.0.0:8300"), 'VSCODE_BASE_URL': os.getenv("VSCODE_BASE_URL", "/code"), 'APP_BIND_ADDR': os.getenv("APP_BIND_ADDR", "0.0.0.0:8080"), 'APP_BASE_URL': os.getenv("APP_BASE_URL", "/app"), 'APP_ROOT_DIR': os.getenv("APP_ROOT_DIR", "/apps/app"), 'APP_USER': os.getenv("APP_USER", "admin"), 'APP_PASSWORD': os.getenv("APP_PASSWORD", "password") } ### Set verbosity level. log.info occasinally throws EOF errors with high verbosity if docker_env.get("LOG_VERBOSITY") in [ "DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL" ]: verbosity = docker_env.get("LOG_VERBOSITY") else: log.info("invalid verbosity: '{}".format(docker_env.get("LOG_VERBOSITY"))) verbosity = "INFO" ### opts_json cli options opts = { "verbosity": verbosity } log.setLevel(verbosity) # Setup colored console logs coloredlogs.install(fmt='%(asctime)s [%(levelname)s] %(message)s', level=verbosity, logger=log) ### Reconcile docker env var with corresponding config setting system_configs = dict() # copy and save user configs users_config_copy = copy(configs_list["users"]) # if system not configured in yaml, then set to docker envs if configs_list.get("system") == None: log.info(f"System not defined in yaml config file. Importing settings from docker env.") for env, value in docker_env.items(): log.debug(f"setting: '{env.lower()}' --> '{value}'") system_configs[env.lower()] = value # copy into system key configs_list["system"] = copy(system_configs) # copy users back configs_list["users"] = copy(users_config_copy) # reconcile if env appears in both else: for env, value in docker_env.items(): for config, setting in configs_list.get("system").items(): if config == env.lower(): if setting == value: log.debug(f"yaml config same as docker environment value: '{config}' --> '{setting}'") system_configs[config] = value else: log.warning(f"using config setting instead of docker environment value - {config}: '{value}'--> '{setting}'") system_configs[config] = setting if not env.lower() in list(configs_list.get("system").keys()): log.debug(f"not set in yaml config, setting: '{env.lower()}' --> '{value}'") system_configs[env.lower()] = value # copy into system key configs_list["system"] = copy(system_configs) # copy users back configs_list["users"] = copy(users_config_copy) ### Reset verbosity level according to yaml file. log.info occasinally throws EOF errors with high verbosity if configs_list.get("system").get("log_verbosity") in [ "DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL" ]: verbosity = configs_list.get("system").get("log_verbosity") else: log.info("invalid verbosity: '{}".format(configs_list.get("system").get("log_verbosity"))) verbosity = "INFO" ### opts_json cli options opts = { "verbosity": verbosity } log.setLevel(verbosity) default_user = [{ 'name': configs_list.get("system").get("workspace_user"), 'group': configs_list.get("system").get("workspace_group"), 'uid': "1000", 'gid': "100", 'shell': configs_list.get("system").get("workspace_user_shell"), 'password': configs_list.get("system").get("workspace_user_password"), 'directories': [ { 'name': 'home', 'path': os.path.join("/home", configs_list.get("system").get("workspace_user")), 'mode': '755' }, { 'name': 'resources', 'path': configs_list.get("system").get("resources_path"), 'mode': '755' }, { 'name': 'workspace', 'path': configs_list.get("system").get("workspace_home"), 'mode': '755' }, { 'name': 'data', 'path': configs_list.get("system").get("data_path"), 'mode': '755' }, { 'name': 'apps', 'path': configs_list.get("system").get("apps_path"), 'mode': '755' }, { 'name': 'app', 'path': configs_list.get("system").get("app_root_dir"), 'mode': '755' }], 'backup_paths': [ f'/home/{configs_list.get("system").get("workspace_user")}/.config', f'/home/{configs_list.get("system").get("workspace_user")}/.ssh', f'/home/{configs_list.get("system").get("workspace_user")}/.zshrc', f'/home/{configs_list.get("system").get("workspace_user")}/.bashrc', f'/home/{configs_list.get("system").get("workspace_user")}/.profile', f'/home/{configs_list.get("system").get("workspace_user")}/.condarc', f'/home/{configs_list.get("system").get("workspace_user")}/.oh-my-zsh', f'/home/{configs_list.get("system").get("workspace_user")}/.gitconfig', f'/home/{configs_list.get("system").get("workspace_user")}/filebrowser.db', f'/home/{configs_list.get("system").get("workspace_user")}/.local', f'/home/{configs_list.get("system").get("workspace_user")}/.conda', f'/home/{configs_list.get("system").get("workspace_user")}/.vscode', f'/home/{configs_list.get("system").get("workspace_user")}/.jupyter' ], 'conda': { 'env': '' }, 'zsh': { 'set_prompt': configs_list.get("system").get("zsh_prompt"), 'set_theme': configs_list.get("system").get("zsh_theme"), 'set_plugins': configs_list.get("system").get("zsh_plugins"), 'prompt': [ 'https://github.com/sindresorhus/pure' ], 'theme': [ 'https://github.com/romkatv/powerlevel10k', 'https://github.com/denysdovhan/spaceship-prompt', 'https://github.com/sobolevn/sobole-zsh-theme' ], 'plugins': [ 'git', 'k', 'extract', 'cp', 'yarn', 'npm', 'supervisor', 'rsync', 'command-not-found', 'autojump', 'colored-man-pages', 'git-flow', 'git-extras', 'python', 'zsh-autosuggestions', 'history-substring-search', 'zsh-completions', 'ssh-agent', 'https://github.com/zsh-users/zsh-autosuggestions', 'https://github.com/zsh-users/zsh-completions', 'https://github.com/zsh-users/zsh-syntax-highlighting', 'https://github.com/zsh-users/zsh-history-substring-search', 'https://github.com/supercrabtree/k' ]}, 'ssh': { 'pub_keys': [''], 'configs': [{ 'hostname': '', 'port': '', 'user': '', 'pub_key_auth': '', 'id_only': '', 'id_file_path': '' }] }, 'filebrowser': { 'port': configs_list.get("system").get("fb_port"), 'base_url': configs_list.get("system").get("fb_base_url"), 'root_dir': configs_list.get("system").get("fb_root_dir") }, 'vscode': { 'bind_addr': configs_list.get("system").get("vscode_bind_addr"), 'base_url': configs_list.get("system").get("vscode_base_url"), 'extensions': [ 'ms-python.python', 'almenon.arepl', 'batisteo.vscode-django', 'bierner.color-info', 'bierner.markdown-footnotes', 'bierner.markdown-mermaid', 'bierner.markdown-preview-github-styles', 'CoenraadS.bracket-pair-colorizer-2', 'DavidAnson.vscode-markdownlint', 'donjayamanne.githistory', 'donjayamanne.python-extension-pack', 'eamodio.gitlens', 'hbenl.vscode-test-explorer', 'henriiik.docker-linter', 'kamikillerto.vscode-colorize', 'kisstkondoros.vscode-gutter-preview', 'littlefoxteam.vscode-python-test-adapter', 'magicstack.MagicPython', 'ms-azuretools.vscode-docker', 'ms-toolsai.jupyter', 'naumovs.color-highlight', 'shd101wyy.markdown-preview-enhanced', 'streetsidesoftware.code-spell-checker', 'tht13.html-preview-vscode', 'tht13.python', 'tushortz.python-extended-snippets', 'wholroyd.jinja', 'yzhang.markdown-all-in-one' ] }, 'app': { 'bind_addr': configs_list.get("system").get("app_bind_addr"), 'base_url': configs_list.get("system").get("app_base_url"), 'root_dir': configs_list.get("system").get("app_root_dir"), 'user': configs_list.get("system").get("app_user"), 'password': configs_list.get("system").get("app_password") } }] def set_user_config(user_config, default_user, level): log.setLevel(level) log.info(user_config.get("yaml_config_value")) log.info(user_config.get("docker_env_value")) if user_config.get("yaml_config_value") == None: log.info("no setting found for '{}', setting: '{}'".format(user_config.get("yaml_config_name"), user_config.get("docker_env_value"))) if user_config.get("dict_path") == 2: configs_list.get(user_config.get("dict_path")[0])[user_config.get("dict_path")[1]] = user_config.get("docker_env_value") elif user_config.get("yaml_config_value") == user_config.get("docker_env_value"): log.debug("yaml config same as docker environment value: {} --> '{}'".format(user_config.get("docker_env_name"), user_config.get("docker_env_value"))) else: log.warning("using user config setting instead of docker environment value - {}: '{}'--> '{}'".format(user_config.get("docker_env_name"), user_config.get("docker_env_value"), user_config.get("yaml_config_value"))) user_configs = [ { "yaml_config_name": "name", "docker_env_name": "workspace_user", "yaml_config_value": configs_list.get("users")[0].get("name"), "docker_env_value": configs_list.get("system").get("workspace_user"), "dict_path": ["users", "name"] }, { "yaml_config_name": "group", "docker_env_name": "workspace_group", "yaml_config_value": configs_list.get("users")[0].get("group"), "docker_env_value": configs_list.get("system").get("workspace_group"), "dict_path": ["users", "group"] }, { "yaml_config_name": "shell", "docker_env_name": "workspace_user_shell", "yaml_config_value": configs_list.get("users")[0].get("shell"), "docker_env_value": configs_list.get("system").get("workspace_user_shell"), "dict_path": ["users", "shell"] }, { "yaml_config_name": "password", "docker_env_name": "workspace_user_password", "yaml_config_value": configs_list.get("users")[0].get("password"), "docker_env_value": configs_list.get("system").get("workspace_user_password"), "dict_path": ["users", "shell"] }, ] ### Set user config if configs_list.get("users") == None: log.info(f"Users not defined in yaml config file. Going with single user mode and importing settings from docker env or setting from default") configs_list["users"] = default_user # Show to console default_user_json = json.dumps(default_user, indent = 4) elif len(configs_list.get("users")) == 0: log.info("User's list empty, populate and restart container") sys.exit() elif len(configs_list.get("users")) == 1: log.info("Building a single user environment") # what's the point of this? overwrite workspace envs with corresponding user envs? Maybe not good to touch and better keep docker envs concistent with this dict. Don't overwrite with user settings. Also simpler #for uc in user_configs: #set_user_config(uc, default_user, verbosity) user_count = 0 for u in configs_list.get("users"): log.debug(f"working on user count: '{user_count}'") for default_config, default_setting in default_user[0].items(): for config, setting in u.items(): if config == default_config: if setting == default_setting: log.debug(f"yaml config setting same as default: '{config}' --> '{setting}'") else: log.debug(f"yaml config setting differs from default - {config}: '{default_setting}'--> '{setting}'") if config == "name": user = setting home = os.path.join("/home", user) if config == "password": password = setting if not default_config in list(u.keys()): log.info(f"not set in yaml config, setting from default settings: '{default_config}' --> '{default_setting}'") configs_list.get("users")[user_count][default_config] = default_setting user_count+=1 log.info(f"setting workspace user to: '{user}'") elif len(configs_list.get("users")) > 1: log.info("More than 2 users defined, haven't build this functionality yet. Remove extra users and restart container.") sys.exit() # Dump into JSON for passage into scripts configs_list_json = json.dumps(configs_list) ### Write docker envs to system environment #for env, value in docker_env.items(): # func.set_env_variable(env, value) ### Clean up envs # opts_json arguments to json opts_json = json.dumps(opts) ### Dynamiruny set MAX_NUM_THREADS ENV_MAX_NUM_THREADS = os.getenv("MAX_NUM_THREADS", None) if ENV_MAX_NUM_THREADS: # Determine the number of availabel CPU resources, but limit to a max number if ENV_MAX_NUM_THREADS.lower() == "auto": ENV_MAX_NUM_THREADS = str(math.ceil(os.cpu_count())) try: # read out docker information - if docker limits cpu quota cpu_count = math.ceil( int( os.popen("cat /sys/fs/cgroup/cpu/cpu.cfs_quota_us") .read() .replace("\n", "") ) / 100000 ) if cpu_count > 0 and cpu_count < os.cpu_count(): ENV_MAX_NUM_THREADS = str(cpu_count) except: pass if ( not ENV_MAX_NUM_THREADS or not ENV_MAX_NUM_THREADS.isnumeric() or ENV_MAX_NUM_THREADS == "0" ): ENV_MAX_NUM_THREADS = "4" if int(ENV_MAX_NUM_THREADS) > 8: # there should be atleast one thread less compared to cores ENV_MAX_NUM_THREADS = str(int(ENV_MAX_NUM_THREADS) - 1) # set a maximum of 32, in most cases too many threads are adding too much overhead if int(ENV_MAX_NUM_THREADS) > 32: ENV_MAX_NUM_THREADS = "32" # only set if it is not None or empty # OMP_NUM_THREADS: Suggested value: vCPUs / 2 in which vCPUs is the number of virtual CPUs. set_env_variable( "OMP_NUM_THREADS", ENV_MAX_NUM_THREADS, ignore_if_set=True ) # OpenMP set_env_variable( "OPENBLAS_NUM_THREADS", ENV_MAX_NUM_THREADS, ignore_if_set=True ) # OpenBLAS set_env_variable("MKL_NUM_THREADS", ENV_MAX_NUM_THREADS, ignore_if_set=True) # MKL set_env_variable( "VECLIB_MAXIMUM_THREADS", ENV_MAX_NUM_THREADS, ignore_if_set=True ) # Accelerate set_env_variable( "NUMEXPR_NUM_THREADS", ENV_MAX_NUM_THREADS, ignore_if_set=True ) # Numexpr set_env_variable( "NUMEXPR_MAX_THREADS", ENV_MAX_NUM_THREADS, ignore_if_set=True ) # Numexpr - maximum set_env_variable( "NUMBA_NUM_THREADS", ENV_MAX_NUM_THREADS, ignore_if_set=True ) # Numba set_env_variable( "SPARK_WORKER_CORES", ENV_MAX_NUM_THREADS, ignore_if_set=True ) # Spark Worker set_env_variable( "BLIS_NUM_THREADS", ENV_MAX_NUM_THREADS, ignore_if_set=True ) # Blis set_env_variable("TBB_NUM_THREADS", ENV_MAX_NUM_THREADS, ignore_if_set=True) # TBB # GOTO_NUM_THREADS ### Set container environment # Get system env and display system_env = os.environ.copy() log.debug("System Environments:") log.debug(func.capture_cmd_stdout('env', system_env)) # Display docker env log.debug("Docker Environments:") log.debug(func.capture_cmd_stdout('env', docker_env)) # Merge system, docker env as workspace env and display workspace_env = func.merge_two_dicts(system_env, docker_env) log.debug("Workspace Environment") log.debug(func.capture_cmd_stdout('env', workspace_env)) # Format workspace env as json for passage into scripts workspace_env_json = json.dumps(workspace_env) ### Configure user log.info(f"configuring user") run( ['python', f"/scripts/configure_user.py", '--opts', opts_json, '--env', workspace_env_json, '--configs', configs_list_json ], env=workspace_env ) ### Set workspace user and home workspace_env['USER'] = user workspace_env['HOME'] = home workspace_env['WORKSPACE_USER'] = user workspace_env['WORKSPACE_USER_HOME'] = home workspace_env['WORKSPACE_USER_PASSWORD'] = password ### Start workspace sys.exit( run( ['python', '/scripts/run_workspace.py', '--opts', opts_json], env=workspace_env ) )

39.307554

221

0.625212

2,729

21,855

4.775009

0.163796

0.05909

0.061239

0.070601

0.421687

0.37288

0.311872

0.256005

0.233136

0.150027

0

0.005598

0.223564

21,855

555

222

39.378378

0.762331

0.103363

0

0.164835

0

0.004396

0.39213

0.102611

0

1

0.002198

false

0.026374

0.030769

0

0.032967

0

null

0

null

0

1

0

da0211204f7b106ec6a65423c21ac69cd0c6c658

11,524

py

Python

py/host.py

black-parrot-hdk/arty-parrot

d5d1c5859cbe6a7acad9147b0d815fe478f92ec9

[ "BSD-3-Clause" ]

1

2022-01-09T07:45:12.000Z

py/host.py

black-parrot-hdk/arty-parrot

d5d1c5859cbe6a7acad9147b0d815fe478f92ec9

[ "BSD-3-Clause" ]

2

2021-05-26T02:27:26.000Z

2021-05-28T07:02:48.000Z

py/host.py

black-parrot-hdk/arty-parrot

d5d1c5859cbe6a7acad9147b0d815fe478f92ec9

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python3 import sys import argparse from enum import Enum from typing import Optional import serial from tqdm import tqdm from nbf import NBF_COMMAND_LENGTH_BYTES, NbfCommand, NbfFile, OPCODE_FINISH, OPCODE_PUTCH, OPCODE_READ_8, OPCODE_WRITE_8, ADDRESS_CSR_FREEZE DRAM_REGION_START = 0x00_8000_0000 DRAM_REGION_END = 0x10_0000_0000 def _debug_format_message(command: NbfCommand) -> str: if command.opcode == OPCODE_PUTCH: return str(command) + f" (putch {repr(command.data[0:1].decode('utf-8'))})" else: return str(command) class LogDomain(Enum): # meta info on requested commands COMMAND = 'command' # sent messages TRANSMIT = 'transmit' # received messages out-of-turn RECEIVE = 'receive' # received messages in response to a transmitted command REPLY = 'reply' @property def message_prefix(self): if self == LogDomain.COMMAND: return "[CMD ]" elif self == LogDomain.TRANSMIT: return "[TX ]" elif self == LogDomain.RECEIVE: return "[RX ]" elif self == LogDomain.REPLY: return "[REPLY]" else: raise ValueError(f"unknown log domain '{self}'") def _log(domain: LogDomain, message: str): tqdm.write(domain.message_prefix + " " + message) class HostApp: def __init__(self, serial_port_name: str, serial_port_baud: int): self.port = serial.Serial( port=serial_port_name, baudrate=serial_port_baud, bytesize=serial.EIGHTBITS, parity=serial.PARITY_NONE, stopbits=serial.STOPBITS_ONE, # Without a timeout, SIGINT can't end the process while we are blocking on a read. timeout=3.0 ) self.commands_sent = 0 self.commands_received = 0 self.reply_violations = 0 def close_port(self): if self.port.is_open: self.port.close() def _send_message(self, command: NbfCommand): self.port.write(command.to_bytes()) self.port.flush() self.commands_sent += 1 def _receive_message(self, block=True) -> Optional[NbfCommand]: if block or self.port.in_waiting >= NBF_COMMAND_LENGTH_BYTES: buffer = self.port.read(NBF_COMMAND_LENGTH_BYTES) if len(buffer) != NBF_COMMAND_LENGTH_BYTES: raise ValueError(f"serial port returned {len(buffer)} bytes, but {NBF_COMMAND_LENGTH_BYTES} requested") self.commands_received += 1 return NbfCommand.from_bytes(buffer) else: return None def _receive_until_opcode(self, opcode: int, block=True) -> Optional[NbfCommand]: message = self._receive_message(block=block) while message is not None and message.opcode != opcode: _log(LogDomain.RECEIVE, _debug_format_message(message)) message = self._receive_message() return message def print_summary_statistics(self): _log(LogDomain.COMMAND, f" Sent: {self.commands_sent} commands") _log(LogDomain.COMMAND, f" Received: {self.commands_received} commands") if self.reply_violations > 0: _log(LogDomain.COMMAND, f" Reply violations: {self.reply_violations} commands") def _validate_reply(self, command: NbfCommand, reply: NbfCommand) -> bool: if not command.is_correct_reply(reply): self.reply_violations += 1 _log(LogDomain.REPLY, f'Unexpected reply: {command} -> {reply}') # TODO: abort on invalid reply? return False return True def _validate_outstanding_replies(self, command_queue_expecting_replies: list, sliding_window_num_commands: int, log_all_rx: bool = False): """ Reads replies from the incoming data stream, matching them with the provided command queue in-order and validating each. If more than "sliding_window_num_commands" commands are in the queue, blocks waiting for an incoming command. Pops all validated commands from the front of the queue, in-place. """ while len(command_queue_expecting_replies) > 0: sent_command = command_queue_expecting_replies[0] is_window_full = len(command_queue_expecting_replies) > sliding_window_num_commands reply = self._receive_until_opcode( sent_command.opcode, block=is_window_full ) if reply is None: # all queued packets have been processed break if log_all_rx: # TODO: indicate this is an expected reply _log(LogDomain.RECEIVE, _debug_format_message(reply)) # TODO: verbose/echo mode was_valid = self._validate_reply(sent_command, reply) if was_valid: # TODO: consider aborting on invalid reply command_queue_expecting_replies.pop(0) def load_file(self, source_file: str, ignore_unfreezes: bool = False, sliding_window_num_commands: int = 0, log_all_messages: bool = False): file = NbfFile(source_file) outstanding_commands_expecting_replies = [] command: NbfCommand for command in tqdm(file, total=file.peek_length(), desc="loading nbf"): if ignore_unfreezes and command.matches(OPCODE_WRITE_8, ADDRESS_CSR_FREEZE, 0): continue if log_all_messages: _log(LogDomain.TRANSMIT, _debug_format_message(command)) self._send_message(command) if command.expects_reply(): outstanding_commands_expecting_replies.append(command) self._validate_outstanding_replies(outstanding_commands_expecting_replies, sliding_window_num_commands, log_all_rx=log_all_messages) self._validate_outstanding_replies(outstanding_commands_expecting_replies, 0, log_all_rx=log_all_messages) _log(LogDomain.COMMAND, "Load complete") def unfreeze(self): unfreeze_command = NbfCommand.with_values(OPCODE_WRITE_8, ADDRESS_CSR_FREEZE, 0) self._send_message(unfreeze_command) reply = self._receive_until_opcode(unfreeze_command.opcode) self._validate_reply(unfreeze_command, reply) def listen_perpetually(self, verbose: bool): _log(LogDomain.COMMAND, "Listening for incoming messages...") while message := self._receive_message(): # in "verbose" mode, we'll always print the full message, even for putchar if not verbose and message.opcode == OPCODE_PUTCH: print(chr(message.data[0]), end = '') continue _log(LogDomain.RECEIVE, _debug_format_message(message)) if message.opcode == OPCODE_FINISH: print(f"FINISH: core {message.address_int}, code {message.data_int}") # TODO: this assumes unicore return def verify(self, reference_file: str): file = NbfFile(reference_file) writes_checked = 0 writes_corrupted = 0 command: NbfCommand for command in tqdm(file, total=file.peek_length(), desc="verifying nbf"): if command.opcode != OPCODE_WRITE_8: continue if command.address_int < DRAM_REGION_START or command.address_int > DRAM_REGION_END - 8: continue read_message = NbfCommand.with_values(OPCODE_READ_8, command.address_int, 0) self._send_message(read_message) reply = self._receive_until_opcode(OPCODE_READ_8) self._validate_reply(read_message, reply) writes_checked += 1 if reply.data != command.data: writes_corrupted += 1 _log(LogDomain.COMMAND, f"Corruption detected at address 0x{command.address_hex_str}") _log(LogDomain.COMMAND, f" Expected: 0x{command.data_hex_str}") _log(LogDomain.COMMAND, f" Actual: 0x{reply.data_hex_str}") _log(LogDomain.COMMAND, "Verify complete") _log(LogDomain.COMMAND, f" Writes checked: {writes_checked}") _log(LogDomain.COMMAND, f" Corrupt writes found: {writes_corrupted}") if writes_corrupted > 0: _log(LogDomain.COMMAND, "== CORRUPTION DETECTED ==") def _load_command(app: HostApp, args): app.load_file( args.file, ignore_unfreezes=args.no_unfreeze, sliding_window_num_commands=args.window_size, log_all_messages=args.verbose ) app.print_summary_statistics() if args.listen: app.listen_perpetually(verbose=args.verbose) def _unfreeze_command(app: HostApp, args): app.unfreeze() if args.listen: app.listen_perpetually(verbose=False) def _verify_command(app: HostApp, args): app.verify(args.file) app.print_summary_statistics() def _listen_command(app: HostApp, args): app.listen_perpetually(verbose=False) if __name__ == "__main__": root_parser = argparse.ArgumentParser() root_parser.add_argument('-p', '--port', dest='port', type=str, default='/dev/ttyS4', help='Serial port (full path or name)') root_parser.add_argument('-b', '--baud', dest='baud_rate', type=int, default=2_000_000, help='Serial port baud rate') command_parsers = root_parser.add_subparsers(dest="command") command_parsers.required = True load_parser = command_parsers.add_parser("load", help="Stream a file of NBF commands to the target") load_parser.add_argument('file', help="NBF-formatted file to load") load_parser.add_argument('--no-unfreeze', action='store_true', dest='no_unfreeze', help='Suppress any "unfreeze" commands in the input file') load_parser.add_argument('--listen', action='store_true', dest='listen', help='Continue listening for incoming messages until program is aborted') load_parser.add_argument('--window-size', type=int, default=500, dest='window_size', help='Specifies the maximum number of outstanding replies to allow before blocking') load_parser.add_argument('--verbose', action='store_true', dest='verbose', help='Log all send and received commands, even if valid') # TODO: add --verify which automatically implies --no-unfreeze then manually unfreezes after # TODO: add --verbose which prints all sent and received commands load_parser.set_defaults(handler=_load_command) unfreeze_parser = command_parsers.add_parser("unfreeze", help="Send an \"unfreeze\" command to the target") unfreeze_parser.add_argument('--listen', action='store_true', dest='listen', help='Continue listening for incoming messages until program is aborted') unfreeze_parser.set_defaults(handler=_unfreeze_command) verify_parser = command_parsers.add_parser("verify", help="Read back the results of an NBF file's memory writes and confirm that their values match the original file") verify_parser.add_argument('file', help="NBF-formatted file to load") verify_parser.set_defaults(handler=_verify_command) listen_parser = command_parsers.add_parser("listen", help="Watch for incoming messages and print the received data") listen_parser.set_defaults(handler=_listen_command) args = root_parser.parse_args() app = HostApp(serial_port_name=args.port, serial_port_baud=args.baud_rate) try: args.handler(app, args) app.close_port() except KeyboardInterrupt: app.close_port() print("Aborted") sys.exit(1)

41.602888

173

0.674505

1,421

11,524

5.209008

0.204082

0.02756

0.030802

0.021616

0.215212

0.141043

0.106188

0.075925

0.058363

0

0.008165

0.234814

11,524

276

174

41.753623

0.831254

0.083391

0

0.09596

0

0.005051

0.155509

0.019998

0

0.007246

0

1

0.09596

false

0

0.035354

0

0.222222

0.035354

0

null

0

null

0

1

0

da02379e9f1f2797e8f3d2fe77571451d25da847

618

py

Python

mistex/plugins/citation.py

martinosorb/mistex

27db70a95ae4bb8bc84c17c9d59c1bef5b5e92f4

[ "BSD-3-Clause" ]

null

mistex/plugins/citation.py

martinosorb/mistex

27db70a95ae4bb8bc84c17c9d59c1bef5b5e92f4

[ "BSD-3-Clause" ]

null

mistex/plugins/citation.py

martinosorb/mistex

27db70a95ae4bb8bc84c17c9d59c1bef5b5e92f4

[ "BSD-3-Clause" ]

null

from mistune.inline_parser import LINK_LABEL CITATION_PATTERN = r'\[\^@(' + LINK_LABEL + r')\]' def render_citation(text): return '\\cite{' + text + '}' def parse_citation(self, m, state): text = m.group(1) self._ensure_bib() return 'citation', self.render(text, state) def plugin_citation(md): md.inline.register_rule('citation', CITATION_PATTERN, parse_citation) index = md.inline.rules.index('std_link') if index != -1: md.inline.rules.insert(index, 'citation') else: md.inline.rules.append('citation') md.renderer.register('citation', render_citation)

22.888889

73

0.666667

80

618

4.975

0.4375

0.080402

0.09799

0

0.003945

0.179612

618

26

74

23.769231

0.781065

0

0.105178

0

1

0.1875

false

0

0.0625

0.375

0

null

0

null

0

1

0

da0300886933dfe76dadbea34ca3db3b9a2e627c

355

py

Python

src/sima/simo/linearization.py

SINTEF/simapy

650b8c2f15503dad98e2bfc0d0788509593822c7

[ "MIT" ]

null

src/sima/simo/linearization.py

SINTEF/simapy

650b8c2f15503dad98e2bfc0d0788509593822c7

[ "MIT" ]

null

src/sima/simo/linearization.py

SINTEF/simapy

650b8c2f15503dad98e2bfc0d0788509593822c7

[ "MIT" ]

null

# Generated with Linearization # from enum import Enum from enum import auto class Linearization(Enum): """""" STOCHASTIC = auto() DIFFERENTIATION = auto() def label(self): if self == Linearization.STOCHASTIC: return "Stochastic" if self == Linearization.DIFFERENTIATION: return "Differentiation"

23.666667

49

0.64507

33

355

6.939394

0.454545

0.069869

0.122271

0

0.264789

355

15

50

23.666667

0.877395

0.078873

0

1

0

0.078616

0

1

0.1

false

0

0.2

0

0.8

0

null

0

1

0

null

0

1

0

2

da03370dc8f2f31bcdc7fd9d8a5697527015558e

2,881

py

Python

2020_August_Leetcode_30_days_challenge/Week_3_Non-overlapping Intervals/by_sorting.py

coderMaruf/leetcode-1

20ffe26e43999e44c8acf9800acb371a49bb5853

[ "MIT" ]

32

2020-01-05T13:37:16.000Z

2022-03-26T07:27:09.000Z

2020_August_Leetcode_30_days_challenge/Week_3_Non-overlapping Intervals/by_sorting.py

coderMaruf/leetcode-1

20ffe26e43999e44c8acf9800acb371a49bb5853

[ "MIT" ]

null

2020_August_Leetcode_30_days_challenge/Week_3_Non-overlapping Intervals/by_sorting.py

coderMaruf/leetcode-1

20ffe26e43999e44c8acf9800acb371a49bb5853

[ "MIT" ]

8

2020-06-18T16:17:27.000Z

2022-03-15T23:58:18.000Z

''' Description: Given a collection of intervals, find the minimum number of intervals you need to remove to make the rest of the intervals non-overlapping. Example 1: Input: [[1,2],[2,3],[3,4],[1,3]] Output: 1 Explanation: [1,3] can be removed and the rest of intervals are non-overlapping. Example 2: Input: [[1,2],[1,2],[1,2]] Output: 2 Explanation: You need to remove two [1,2] to make the rest of intervals non-overlapping. Example 3: Input: [[1,2],[2,3]] Output: 0 Explanation: You don't need to remove any of the intervals since they're already non-overlapping. Note: You may assume the interval's end point is always bigger than its start point. Intervals like [1,2] and [2,3] have borders "touching" but they don't overlap each other. ''' from typing import List class Solution: def eraseOverlapIntervals(self, intervals: List[List[int]]) -> int: # sort segments by start index in ascending order intervals.sort( key = lambda segment: segment[0] ) last_compare_idx = 0 removal_counter = 0 for cur_idx in range(1, len(intervals)): cur_start, cur_end = intervals[cur_idx] last_start, last_end = intervals[last_compare_idx] if cur_start < last_end: # need to remove one interval to avoid overlapping removal_counter += 1 if cur_end < last_end: # remove last interval, because it is lefter then current last_compare_idx = cur_idx else: # remove current interval, because it is lefter then last one # last compare idx keeps the same pass else: # so far so good, no need to remove last_compare_idx = cur_idx return removal_counter # n : the length of input list, intervals ## Time Complexity: O( n log n) # # The overhead in time is the cost of sorting, which is of O( n log n ). ## Space Complexity: O( 1 ) # # The overhead in space is the storage for loop index and temporary variable, which is of O( 1 ). import unittest class Testing( unittest.TestCase ): def test_case_1( self ): result = Solution().eraseOverlapIntervals( intervals=[[1,2],[2,3],[3,4],[1,3]] ) self.assertEqual(result, 1) def test_case_2( self ): result = Solution().eraseOverlapIntervals( intervals=[[1,2],[1,2],[1,2]] ) self.assertEqual(result, 2) def test_case_3( self ): result = Solution().eraseOverlapIntervals( intervals=[[1,2],[2,3]] ) self.assertEqual(result, 0) if __name__ == '__main__': unittest.main()

25.052174

139

0.588684

386

2,881

4.297927

0.339378

0.014467

0.036166

0.009644

0.191682

0.141049

0.10006

0.069922

0.062688

0

0.032209

0.321069

2,881

115

140

25.052174

0.815951

0.449844

0

0.129032

0

0.005122

0

0.096774

1

0.129032

false

0.032258

0.064516

0

0.290323

0

null

0

null

0

1

0

da0469fe0ec53d36c9f4e75701bb9541ada5eeed

1,220

py

Python

hive_plug_play/engine/processor.py

seakintruth/hive-plug-play

032caed7a0690a58410b3d4e93a1fdecf2009d58

[ "MIT" ]

3

2021-05-11T07:12:05.000Z

2021-10-04T04:01:38.000Z

hive_plug_play/engine/processor.py

seakintruth/hive-plug-play

032caed7a0690a58410b3d4e93a1fdecf2009d58

[ "MIT" ]

9

2021-06-02T03:43:01.000Z

2021-07-23T14:52:03.000Z

hive_plug_play/engine/processor.py

seakintruth/hive-plug-play

032caed7a0690a58410b3d4e93a1fdecf2009d58

[ "MIT" ]

1

2021-05-24T15:57:20.000Z

from os import truncate from hive_plug_play.database.handlers import PlugPlayDb class BlockProcessor: @classmethod def init(cls, config): cls.config = config cls.db = PlugPlayDb(config) cls.head_block = {} cls.block_num = 0 cls.block_time = '' @classmethod def check_op_id(cls, op_id): allowed_op_ids = cls.config['op_ids'] if allowed_op_ids == []: return True else: return op_id in allowed_op_ids @classmethod def process_block(cls, block_num, block): prev = block['previous'] block_hash = block['block_id'] timestamp = block['timestamp'] cls.db.add_block(block_num, block_hash, prev, timestamp) transactions = block['transactions'] for i in range(len(transactions)): trans = transactions[i] for op in trans['operations']: if op['type'] == 'custom_json_operation': if cls.check_op_id(op['value']['id']): cls.db.add_op(block_num, block['transaction_ids'][i], op['value']) cls.db._save() cls.block_num = block_num cls.block_time = timestamp

32.105263

90

0.584426

149

1,220

4.557047

0.355705

0.070692

0.076583

0.047128

0

0.001183

0.307377

1,220

38

91

32.105263

0.802367

0

0.090909

0

0.085995

0.017199

0

1

0.090909

false

0

0.060606

0

0.242424

0

null

0

null

0

1

0

da04bc9087b18cc1593f2b126074d0370e63d6a0

1,040

py

Python

tests/integration/conftest.py

gcallaghan/openapi-spec-validator

3ab3411936faaee91246627f957ba6108cd47d44

[ "Apache-2.0" ]

null

tests/integration/conftest.py

gcallaghan/openapi-spec-validator

3ab3411936faaee91246627f957ba6108cd47d44

[ "Apache-2.0" ]

null

tests/integration/conftest.py

gcallaghan/openapi-spec-validator

3ab3411936faaee91246627f957ba6108cd47d44

[ "Apache-2.0" ]

null

from os import path import pytest from six.moves.urllib import request from six.moves.urllib.parse import urlunparse from yaml import safe_load from openapi_spec_validator import openapi_v3_spec_validator def spec_url(spec_file, schema='file'): directory = path.abspath(path.dirname(__file__)) full_path = path.join(directory, spec_file) return urlunparse((schema, None, full_path, None, None, None)) def spec_from_file(spec_file): directory = path.abspath(path.dirname(__file__)) path_full = path.join(directory, spec_file) with open(path_full) as fh: return safe_load(fh) def spec_from_url(spec_url): content = request.urlopen(spec_url) return safe_load(content) class Factory(dict): __getattr__ = dict.__getitem__ __setattr__ = dict.__setitem__ @pytest.fixture def factory(): return Factory( spec_url=spec_url, spec_from_file=spec_from_file, spec_from_url=spec_from_url, ) @pytest.fixture def validator(): return openapi_v3_spec_validator

22.608696

66

0.742308

146

1,040

4.876712

0.294521

0.067416

0.046348

0.067416

0.224719

0.109551

0

0.002328

0.174038

1,040

45

67

23.111111

0.826542

0

0.129032

0

0.003846

0

1

0.16129

false

0

0.193548

0.064516

0.612903

0

null

0

null

0

1

0

1

da058a79bcff3d1633c9de586676094982ec1208

24,030

py

Python

scripts/populate_conferences.py

sf2ne/Playground

95b2d222d7ac43baca0249acbfc34e043d6a95b3

[ "Apache-2.0" ]

null

scripts/populate_conferences.py

sf2ne/Playground

95b2d222d7ac43baca0249acbfc34e043d6a95b3

[ "Apache-2.0" ]

13

2020-03-24T15:29:41.000Z

2022-03-11T23:15:28.000Z

scripts/populate_conferences.py

sf2ne/Playground

95b2d222d7ac43baca0249acbfc34e043d6a95b3

[ "Apache-2.0" ]

null

#!/usr/bin/env python # encoding: utf-8 import os from modularodm import Q from modularodm.exceptions import ModularOdmException from framework.auth.core import User from website import settings from website.app import init_app from website.conferences.model import Conference def main(): init_app(set_backends=True, routes=False) populate_conferences() MEETING_DATA = { 'spsp2014': { 'name': 'Society for Personality and Social Psychology 2014', 'info_url': None, 'logo_url': None, 'active': False, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'asb2014': { 'name': 'Association of Southeastern Biologists 2014', 'info_url': 'http://www.sebiologists.org/meetings/talks_posters.html', 'logo_url': None, 'active': False, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'aps2014': { 'name': 'Association for Psychological Science 2014', 'info_url': 'http://centerforopenscience.org/aps/', 'logo_url': '/static/img/2014_Convention_banner-with-APS_700px.jpg', 'active': False, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'annopeer2014': { 'name': '#annopeer', 'info_url': None, 'logo_url': None, 'active': False, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'cpa2014': { 'name': 'Canadian Psychological Association 2014', 'info_url': None, 'logo_url': None, 'active': False, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'filaments2014': { 'name': 'National Radio Astronomy Observatory Filaments 2014', 'info_url': None, 'logo_url': 'https://science.nrao.edu/science/meetings/2014/' 'filamentary-structure/images/filaments2014_660x178.png', 'active': False, 'admins': [ 'lvonschi@nrao.edu', # 'Dkim@nrao.edu', ], 'public_projects': True, 'poster': True, 'talk': True, }, 'bitss2014': { 'name': 'Berkeley Initiative for Transparency in the Social Sciences Research Transparency Forum 2014', 'info_url': None, 'logo_url': os.path.join( settings.STATIC_URL_PATH, 'img', 'conferences', 'bitss.jpg', ), 'active': False, 'admins': [ 'gkroll@berkeley.edu', 'awais@berkeley.edu', ], 'public_projects': True, 'poster': False, 'talk': True, }, 'spsp2015': { 'name': 'Society for Personality and Social Psychology 2015', 'info_url': None, 'logo_url': None, 'active': False, 'admins': [ 'meetings@spsp.org', ], 'poster': True, 'talk': True, }, 'aps2015': { 'name': 'Association for Psychological Science 2015', 'info_url': None, 'logo_url': 'http://www.psychologicalscience.org/images/APS_2015_Banner_990x157.jpg', 'active': True, 'admins': [ ], 'public_projects': True, 'poster': True, 'talk': True, }, 'icps2015': { 'name': 'International Convention of Psychological Science 2015', 'info_url': None, 'logo_url': 'http://icps.psychologicalscience.org/wp-content/themes/deepblue/images/ICPS_Website-header_990px.jpg', 'active': False, 'admins': [ ], 'public_projects': True, 'poster': True, 'talk': True, }, 'mpa2015': { 'name': 'Midwestern Psychological Association 2015', 'info_url': None, 'logo_url': 'http://www.midwesternpsych.org/resources/Pictures/MPA%20logo.jpg', 'active': True, 'admins': [ 'mpa@kent.edu', ], 'public_projects': True, 'poster': True, 'talk': True, }, 'NCCC2015': { 'name': 'North Carolina Cognition Conference 2015', 'info_url': None, 'logo_url': None, 'active': False, 'admins': [ 'aoverman@elon.edu', ], 'public_projects': True, 'poster': True, 'talk': True, }, 'VPRSF2015': { 'name': 'Virginia Piedmont Regional Science Fair 2015', 'info_url': None, 'logo_url': 'http://vprsf.org/wp-content/themes/VPRSF/images/logo.png', 'active': False, 'admins': [ 'director@vprsf.org', ], 'public_projects': True, 'poster': True, 'talk': True, }, 'APRS2015': { 'name': 'UVA Annual Postdoctoral Research Symposium 2015', 'info_url': None, 'logo_url': 'http://s1.postimg.org/50qj9u6i7/GPA_Logo.jpg', 'active': False, 'admins': [ 'mhurst@virginia.edu', ], 'public_projects': True, 'poster': True, 'talk': True, }, 'ASB2015': { 'name': 'Association of Southeastern Biologists 2015', 'info_url': None, 'logo_url': 'http://www.sebiologists.org/wp/wp-content/uploads/2014/09/banner_image_Large.png', 'active': False, 'admins': [ 'amorris.mtsu@gmail.com', ], 'public_projects': True, 'poster': True, 'talk': True, }, 'TeaP2015': { 'name': 'Tagung experimentell arbeitender Psychologen 2015', 'info_url': None, 'logo_url': None, 'active': False, 'admins': [ ], 'public_projects': True, 'poster': True, 'talk': True, }, 'VSSEF2015': { 'name': 'Virginia State Science and Engineering Fair 2015', 'info_url': 'http://www.vmi.edu/conferences/vssef/vssef_home/', 'logo_url': 'http://www.vmi.edu/uploadedImages/Images/Headers/vssef4.jpg', 'active': False, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'RMPA2015': { 'name': 'Rocky Mountain Psychological Association 2015', 'info_url': 'http://www.rockymountainpsych.org/uploads/7/4/2/6/7426961/85th_annual_rmpa_conference_program_hr.pdf', 'logo_url': 'http://www.rockymountainpsych.org/uploads/7/4/2/6/7426961/header_images/1397234084.jpg', 'active': False, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'ARP2015': { 'name': 'Association for Research in Personality 2015', 'info_url': 'http://www.personality-arp.org/conference/', 'logo_url': 'http://www.personality-arp.org/wp-content/uploads/conference/st-louis-arp.jpg', 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'SEP2015': { 'name': 'Society of Experimental Psychologists Meeting 2015', 'info_url': 'http://faculty.virginia.edu/Society_of_Experimental_Psychologists/', 'logo_url': 'http://www.sepsych.org/nav/images/SEP-header.gif', 'active': False, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'Reid2015': { 'name': 'L. Starling Reid Undergraduate Psychology Conference 2015', 'info_url': 'http://avillage.web.virginia.edu/Psych/Conference', 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'NEEPS2015': { 'name': 'Northeastern Evolutionary Psychology Conference 2015', 'info_url': 'http://neeps2015.weebly.com/', 'logo_url': None, 'active': False, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'VaACS2015': { 'name': 'Virginia Section American Chemical Society Student Poster Session 2015', 'info_url': 'http://virginia.sites.acs.org/', 'logo_url': 'http://virginia.sites.acs.org/Bulletin/15/UVA.jpg', 'active': False, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'MADSSCi2015': { 'name': 'Mid-Atlantic Directors and Staff of Scientific Cores & Southeastern Association of Shared Services 2015', 'info_url': 'http://madssci.abrf.org', 'logo_url': 'http://s24.postimg.org/qtc3baefp/2015madssci_seasr.png', 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'NRAO2015': { 'name': 'National Radio Astronomy Observatory Accretion 2015', 'info_url': 'https://science.nrao.edu/science/meetings/2015/accretion2015/posters', 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'ARCS2015': { 'name': 'Advancing Research Communication and Scholarship 2015', 'info_url': 'http://commons.pacificu.edu/arcs/', 'logo_url': 'http://commons.pacificu.edu/assets/md5images/4dfd167454e9f4745360a9550e189323.png', 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'singlecasedesigns2015': { 'name': 'Single Case Designs in Clinical Psychology: Uniting Research and Practice', 'info_url': 'https://www.royalholloway.ac.uk/psychology/events/eventsarticles/singlecasedesignsinclinicalpsychologyunitingresearchandpractice.aspx', 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'OSFM2015': { 'name': 'OSF for Meetings 2015', 'info_url': None, 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'JSSP2015': { 'name': 'Japanese Society of Social Psychology 2015', 'info_url': 'http://www.socialpsychology.jp/conf2015/index.html', 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, '4S2015': { 'name': 'Society for Social Studies of Science 2015', 'info_url': 'http://www.4sonline.org/meeting', 'logo_url': 'http://www.4sonline.org/ee/denver-skyline.jpg', 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'IARR2016': { 'name': 'International Association for Relationship Research 2016', 'info_url': 'http://iarr.psych.utoronto.ca/', 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'IA2015': { 'name': 'Inclusive Astronomy 2015', 'info_url': 'https://vanderbilt.irisregistration.com/Home/Site?code=InclusiveAstronomy2015', 'logo_url': 'https://vanderbilt.blob.core.windows.net/images/Inclusive%20Astronomy.jpg', 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'R2RC': { 'name': 'Right to Research Coalition', 'info_url': None, 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'OpenCon2015': { 'name': 'OpenCon2015', 'info_url': 'http://opencon2015.org/', 'logo_url': 'http://s8.postimg.org/w9b30pxyd/Open_Con2015_new_logo.png', 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'ESIP2015': { 'name': 'Earth Science Information Partners 2015', 'info_url': 'http://esipfed.org/', 'logo_url': 'http://s30.postimg.org/m2uz2g4pt/ESIP.png', 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'SPSP2016': { 'name': 'Society for Personality and Social Psychology 2016 ', 'info_url': 'http://meeting.spsp.org', 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'NACIII': { 'name': '2015 National Astronomy Consortium (NAC) III Workshop', 'info_url': 'https://info.nrao.edu/do/odi/meetings/2015/nac111/', 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'CDS2015': { 'name': 'Cognitive Development Society 2015', 'info_url': 'http://meetings.cogdevsoc.org/', 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'SEASR2016': { 'name': 'Southeastern Association of Shared Resources 2016', 'info_url': 'http://seasr.abrf.org', 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'Accretion2015': { 'name': 'Observational Evidence of Gas Accretion onto Galaxies?', 'info_url': 'https://science.nrao.edu/science/meetings/2015/accretion2015', 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, '2020Futures': { 'name': 'U.S. Radio/Millimeter/Submillimeter Science Futures in the 2020s', 'info_url': 'https://science.nrao.edu/science/meetings/2015/2020futures/home', 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'RMPA2016': { 'name': 'Rocky Mountain Psychological Association 2016', 'info_url': 'http://www.rockymountainpsych.org/convention-info.html', 'logo_url': 'http://www.rockymountainpsych.org/uploads/7/4/2/6/7426961/header_images/1397234084.jpg', 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'CNI2015': { 'name': 'Coalition for Networked Information (CNI) Fall Membership Meeting 2015', 'info_url': 'https://wp.me/P1LncT-64s', 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': False, 'talk': True, }, 'SWPA2016': { 'name': 'Southwestern Psychological Association Convention 2016', 'info_url': 'https://www.swpsych.org/conv_dates.php', 'logo_url': 'http://s28.postimg.org/xbwyqqvx9/SWPAlogo4.jpg', 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'ESIP2016W': { 'name': 'Earth Science Information Partners Winter Meeting 2016', 'info_url': 'http://commons.esipfed.org/2016WinterMeeting', 'logo_url': 'http://s30.postimg.org/m2uz2g4pt/ESIP.png', 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'MiamiBrainhack15': { 'name': 'University of Miami Brainhack 2015', 'info_url': 'http://brainhack.org/americas/', 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'PsiChiRepository': { 'name': 'Psi Chi', 'info_url': 'http://www.psichi.org/?ResearchAdvisory#.VmBpeOMrI1g', 'logo_url': 'http://s11.postimg.org/4g2451vcz/Psi_Chi_Logo.png', 'admins': [ 'research.director@psichi.org', ], 'field_names': { 'submission1': 'measures', 'submission2': 'materials', 'submission1_plural': 'measures/scales', 'submission2_plural': 'study materials', 'meeting_title_type': 'Repository', 'add_submission': 'materials', 'mail_subject': 'Title', 'mail_message_body': 'Measure or material short description', 'mail_attachment': 'Your measure/scale or material file(s)' }, }, 'GI2015': { 'name': 'Genome Informatics 2015', 'info_url': 'https://meetings.cshl.edu/meetings.aspx?meet=info&year=15', 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'MADSSCi2016': { 'name': 'Mid-Atlantic Directors and Staff of Scientific Cores & Southeastern Association of Shared Services 2016', 'info_url': 'http://madssci.abrf.org', 'logo_url': 'http://madssci.abrf.org/sites/default/files/madssci-logo-bk.png', 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'SMM2015': { 'name': 'The Society for Marine Mammalogy', 'info_url': 'https://www.marinemammalscience.org/conference/', 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'TESS': { 'name': 'Time-sharing Experiments for the Social Sciences', 'info_url': 'http://www.tessexperiments.org', 'logo_url': None, 'active': False, 'admins': [], 'public_projects': True, 'poster': False, 'talk': True, 'field_names': { 'submission1': 'poster', 'submission2': 'study', 'submission1_plural': 'posters', 'submission2_plural': 'studies', 'meeting_title_type': 'Studies', 'add_submission': 'studies', } }, 'ASCERM2016': { 'name': 'ASCE Rocky Mountain Student Conference 2016', 'info_url': 'http://luninuxos.com/asce/', 'logo_url': 'http://s2.postimg.org/eaduh2ovt/2016_ASCE_Rocky_Mtn_banner.png', 'active': True, 'admins': [], 'public_projects': True, 'poster': False, 'talk': True, }, 'ARCA2016': { 'name': '5th Applied Research Conference in Africa', 'info_url': 'http://www.arcaconference.org/', 'logo_url': 'http://www.arcaconference.org/images/ARCA_LOGO_NEW.JPG', 'active': True, 'admins': [], 'public_projects': True, 'poster': False, 'talk': True, }, 'CURCONF2016': { 'name': 'CUR Biennial Conference 2016', 'info_url': 'http://www.cur.org/conferences_and_events/biennial2016/', 'logo_url': 'http://s11.postimg.org/v8feuna4y/Conference_logo_eps.jpg', 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'CATALISE2016': { 'name': 'Criteria and Terminology Applied to Language Impairments: Synthesising the Evidence (CATALISE) 2016', 'info_url': None, 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'Emergy2016': { 'name': '9th Biennial Emergy Research Conference', 'info_url': 'http://www.cep.ees.ufl.edu/emergy/conferences/ERC09_2016/index.shtml', 'logo_url': 'http://s12.postimg.org/uf9ioqmct/emergy.jpg', 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'aps2016': { 'name': '28th APS Annual Convention', 'info_url': 'http://www.psychologicalscience.org/convention', 'logo_url': 'http://www.psychologicalscience.org/redesign/wp-content/uploads/2015/03/APS_2016_Banner_990x157.jpg', 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'jssp2016': { 'name': 'Japanese Society of Social Psychology 2016', 'info_url': 'http://www.socialpsychology.jp/conf2016/', 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'sepech2016': { 'name': 'XI SEPECH - Research Seminar in Human Sciences (Seminário de Pesquisa em Ciências Humanas)', 'info_url': 'http://www.uel.br/eventos/sepech/sepech2016/', 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'etmaal2016': { 'name': 'Etmaal van de Communicatiewetenschap 2016 - Media Psychology', 'info_url': 'https://etmaal2016.wordpress.com', 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'WSAN2016': { 'name': 'WSAN2016 Erasmus University Rotterdam', 'info_url': 'http://www.humane.eu/wsan/', 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': True, 'talk': True, }, 'ContainerStrategies': { 'name': 'Container Strategies for Data & Software Preservation', 'info_url': 'https://daspos.crc.nd.edu/index.php/workshops/container-strategies-for-data-software-preservation-that-promote-open-science', 'logo_url': 'http://s17.postimg.org/8nl1v5mxb/Screen_Shot_2016_03_02_at_9_05_24_PM.png', 'active': True, 'admins': [], 'public_projects': True, 'poster': True, }, 'CNI2016': { 'name': 'Coalition for Networked Information (CNI) Spring Membership Meeting 2016', 'info_url': 'https://wp.me/P1LncT-6fd', 'logo_url': None, 'active': True, 'admins': [], 'public_projects': True, 'poster': False, 'talk': True, }, } def populate_conferences(): for meeting, attrs in MEETING_DATA.iteritems(): meeting = meeting.strip() admin_emails = attrs.pop('admins', []) admin_objs = [] for email in admin_emails: try: user = User.find_one(Q('username', 'iexact', email)) admin_objs.append(user) except ModularOdmException: raise RuntimeError('Username {0!r} is not registered.'.format(email)) custom_fields = attrs.pop('field_names', {}) conf = Conference( endpoint=meeting, admins=admin_objs, **attrs ) conf.field_names.update(custom_fields) try: conf.save() except ModularOdmException: conf = Conference.find_one(Q('endpoint', 'eq', meeting)) for key, value in attrs.items(): if isinstance(value, dict): current = getattr(conf, key) current.update(value) setattr(conf, key, current) else: setattr(conf, key, value) conf.admins = admin_objs changed_fields = conf.save() if changed_fields: print('Updated {}: {}'.format(meeting, changed_fields)) else: print('Added new Conference: {}'.format(meeting)) if __name__ == '__main__': main()

32.693878

156

0.544112

2,335

24,030

5.475803

0.241113

0.034491

0.085875

0.1145

0.489989

0.430705

0.373221

0.347411

0.328641

0.308619

0

0.044415

0.297295

24,030

734

157

32.73842

0.71278

0.002206

0

0.534819

0

0.013928

0.497414

0.009594

0

1

0.002786

false

0

0.009749

0

0.012535

0.002786

0

null

0

null

0

1

0

da0602f1e855ed3a2c59e5d54ad317e3bc77bd87

3,563

py

Python

clinicadl/clinicadl/subject_level/train_autoencoder.py

921974496/AD-DL

9a0303579a665800633024bdab1ac44f794a0c38

[ "MIT" ]

1

2020-11-30T01:39:12.000Z

clinicadl/clinicadl/subject_level/train_autoencoder.py

921974496/AD-DL

9a0303579a665800633024bdab1ac44f794a0c38

[ "MIT" ]

null

clinicadl/clinicadl/subject_level/train_autoencoder.py

921974496/AD-DL

9a0303579a665800633024bdab1ac44f794a0c38

[ "MIT" ]

null

from __future__ import print_function import argparse from os import path from time import time import sys import torch import torch.nn as nn from torch.utils.data import DataLoader from .utils import ae_finetuning from ..tools.deep_learning.iotools import Parameters from ..tools.deep_learning.data import MinMaxNormalization, MRIDataset, load_data from ..tools.deep_learning import create_autoencoder, commandline_to_json def train_autoencoder(params): """ Parameters params: class from utils module containing all the parameters for training a CNN. """ if params.evaluation_steps % params.accumulation_steps != 0 and params.evaluation_steps != 1: raise Exception('Evaluation steps %d must be a multiple of accumulation steps %d' % (params.evaluation_steps, params.accumulation_steps)) if params.minmaxnormalization: transformations = MinMaxNormalization() else: transformations = None total_time = time() criterion = torch.nn.MSELoss() training_tsv, valid_tsv = load_data(params.tsv_path, params.diagnoses, params.split, params.n_splits, params.baseline) data_train = MRIDataset(params.input_dir, training_tsv, params.preprocessing, transformations) data_valid = MRIDataset(params.input_dir, valid_tsv, params.preprocessing, transformations) # Use argument load to distinguish training and testing train_loader = DataLoader(data_train, params.batch_size, shuffle=True, num_workers=params.num_workers, drop_last=True ) valid_loader = DataLoader(data_valid, ) valid_loader = DataLoader(data_valid, batch_size=params.batch_size, shuffle=False, num_workers=params.num_workers, drop_last=False ) text_file = open(path.join(params.output_dir, 'python_version.txt'), 'w') text_file.write('Version of python: %s \n' % sys.version) text_file.write('Version of pytorch: %s \n' % torch.__version__) text_file.close() decoder = create_autoencoder(params.model, params.pretrained_path, difference=params.pretrained_difference) optimizer = eval("torch.optim." + params.optimizer)(filter(lambda x: x.requires_grad, decoder.parameters()), params.learning_rate, weight_decay=params.weight_decay) if params.add_sigmoid: if isinstance(decoder.decoder[-1], nn.ReLU): decoder.decoder = nn.Sequential(*list(decoder.decoder)[:-1]) decoder.decoder.add_module("sigmoid", nn.Sigmoid()) ae_finetuning(decoder, train_loader, valid_loader, criterion, optimizer, False, params) total_time = time() - total_time print('Total time', total_time) #if __name__ == "__main__": # commandline = parser.parse_known_args() # commandline_to_json(commandline, 'ConvAutoencoder') # options = commandline[0] # if commandline[1]: # print("unknown arguments: %s" % parser.parse_known_args()[1]) # train_params_autoencoder = Parameters(tsv_path, output_dir, input_dir, model) # train_params_autoencoder.write(options) # train_autoencoder(train_parameters_autoencoder)

39.153846

168

0.63991

383

3,563

5.704961

0.342037

0.020595

0.017849

0.028833

0.118993

0.071396

0.031121

0

0.002716

0.276733

3,563

90

169

39.588889

0.845169

0.158855

0

0.105263

0

0.053908

0

1

0.017544

false

0

0.210526

0

0.22807

0.035088

0

null

0

null

0

1

0

da08fa8384c712fcc3ccc0c8023334a1b12a22c0

375

py

Python

globals/mime.py

RogueScholar/debreate

0abc168c51336b31ff87c61f84bc7bb6000e88f4

[ "MIT" ]

97

2016-09-16T08:44:04.000Z

2022-01-29T22:30:18.000Z

globals/mime.py

RogueScholar/debreate

0abc168c51336b31ff87c61f84bc7bb6000e88f4

[ "MIT" ]

34

2016-09-20T00:42:45.000Z

2021-04-16T07:21:44.000Z

globals/mime.py

RogueScholar/debreate

0abc168c51336b31ff87c61f84bc7bb6000e88f4

[ "MIT" ]

24

2016-09-16T08:44:56.000Z

2021-07-29T11:32:47.000Z

# -*- coding: utf-8 -*- ## \package globals.mime # MIT licensing # See: docs/LICENSE.txt from globals.execute import GetCommandOutput from globals.execute import GetExecutable ## TODO: Doxygen def GetFileMimeType(filename): CMD_file = GetExecutable(u'file') if not CMD_file: return None return GetCommandOutput(CMD_file, (u'--mime-type', u'--brief', filename,))

17.857143

75

0.728

48

375

5.625

0.645833

0.077778

0.133333

0.177778

0

0.003106

0.141333

375

20

76

18.75

0.835404

0.248

0

0.080292

0

0.05

0

1

0.142857

false

0

0.285714

0

0.714286

0

null

0

1

0

null

0

1

0

2

da09c6430f4f0663e4ddd43367f12c8087614e78

1,761

py

Python

src/deployer/result.py

jbenden/deployer

b036fa3030f99ed0730bb3770cf7e01c58c257f1

[ "Apache-2.0" ]

2

2018-08-30T14:14:13.000Z

2022-03-24T15:19:29.000Z

src/deployer/result.py

jbenden/deployer

b036fa3030f99ed0730bb3770cf7e01c58c257f1

[ "Apache-2.0" ]

null

src/deployer/result.py

jbenden/deployer

b036fa3030f99ed0730bb3770cf7e01c58c257f1

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # Copyright 2018 Joseph Benden <joe@benden.us> # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """ A module holding the results of all plug-ins. .. moduleauthor:: Joseph Benden <joe@benden.us> :copyright: (c) Copyright 2018 by Joseph Benden. :license: Apache License 2.0, see LICENSE.txt for full details. """ class Result(dict): """Represents the resultant of a plug-in's execution.""" def __bool__(self): """Cast to boolean.""" return self['result'] != 'failure' and self['result'] != 'continue' def __nonzero__(self): """Cast to boolean.""" return self.__bool__() # noqa: no-cover def __str__(self): """Return our `stdout` if present, otherwise returns the `result` value.""" return self['stdout'] if 'stdout' in self else str(self['result']) def failed(self): """Determine if the resultant is a failure.""" return self['result'] == 'failure' # noqa: no-cover def succeeded(self): """Determine if the resultant is a success.""" return self['result'] != 'failure' # noqa: no-cover def skipped(self): """Determine if the resultant was skipped.""" return self['result'] == 'skipped' # noqa: no-cover

33.865385

83

0.662124

241

1,761

4.771784

0.46888

0.052174

0.055652

0.06

0.226957

0.163478

0.116522

0.064348

0

0.010815

0.212379

1,761

51

84

34.529412

0.818313

0.64452

0

0.14841

0

1

0.461538

false

0

1

0

null

0

null

0

1

0

1

0

2

da0cc012c8071ddd102f587a464226bdf7578158

1,381

py

Python

app.py

dhairyaostwal/bankingo

cc148940a9d4ae60d80acdc2e3c90a01a8a99c46

[ "MIT" ]

2

2021-12-11T02:32:35.000Z

2021-12-12T08:42:41.000Z

app.py

dhairyaostwal/bankingo

cc148940a9d4ae60d80acdc2e3c90a01a8a99c46

[ "MIT" ]

null

app.py

dhairyaostwal/bankingo

cc148940a9d4ae60d80acdc2e3c90a01a8a99c46

[ "MIT" ]

null

from flask import Flask, render_template, request import pickle app = Flask(__name__) userInput = [] @app.route("/", methods=["GET", "POST"]) def hello(): userInput.clear() if request.method == "POST": variance = request.form.get("variance") skewness = request.form.get("skewness") curtosis = request.form.get("curtosis") entropy = request.form.get("entropy") userInput.append(variance) userInput.append(skewness) userInput.append(curtosis) userInput.append(entropy) # converting string to float values for i in range(len(userInput)): userInput[i] = float(userInput[i]) print("User input: ", userInput) # testing our pickle file with open('pickleOutput2', 'rb') as f: mp = pickle.load(f) pickle_test = mp.predict([userInput]) print("Predicted Output: ", pickle_test) if pickle_test[0]==1: return render_template("trueBundle.html") else: return render_template("falseBundle.html") return render_template("index.html") @app.route("/verified/") def verified(): return render_template("trueBundle.html") @app.route("/not-verified/") def notVerified(): return render_template("falseBundle.html") if __name__ == '__main__': app.debug = True app.run()

26.557692

54

0.620565

152

1,381

5.5

0.447368

0.100478

0.119617

0.07177

0.165072

0

0.002882

0.246198

1,381

52

55

26.557692

0.800192

0.041274

0

0.108108

0

0.145234

0

1

0.081081

false

0

0.054054

0.27027

0.054054

0

null

0

null

0

1

0

da0d025051a5ed1885fbb8e49bb40af12912744c

3,210

py

Python

AlarmTimer.py

amjith/PyAlarmTimer

f664daa42d9ec70fc7ac512ce71868c703e8a011

[ "MIT" ]

2

2015-01-13T00:36:29.000Z

2015-04-12T19:17:32.000Z

AlarmTimer.py

amjith/PyAlarmTimer

f664daa42d9ec70fc7ac512ce71868c703e8a011

[ "MIT" ]

1

2015-01-12T23:02:28.000Z

2015-01-13T00:36:26.000Z

AlarmTimer.py

amjith/PyAlarmTimer

f664daa42d9ec70fc7ac512ce71868c703e8a011

[ "MIT" ]

null

import sys from PyQt4 import QtCore, QtGui from itertools import cycle from Resources.LcdNumber_ui import Ui_Form class AlarmTimer(QtGui.QMainWindow): def __init__(self, timer_values, parent=None): QtGui.QWidget.__init__(self, parent) QtGui.QMainWindow.__init__(self, None, QtCore.Qt.WindowStaysOnTopHint|QtCore.Qt.FramelessWindowHint) self.ui = Ui_Form() self.ui.setupUi(self) # Initialize member variables self.color_names = [ "Normal", "Yellow" ] self.color_idx = 1 self.updateTimers(timer_values) self.cur_timer = self.timer_iter.next() # Current timer value self.snooze_time = 1 * 60 self.show() self.oneSecondCounter = 0 self.timerPause = False # Start a timer for 250ms and call showTimer() timer = QtCore.QTimer(self) timer.timeout.connect(self.showTimer) timer.start(250) def showTimer(self): if self.timerPause: return text = "%d:%02d" % (self.cur_timer/60,self.cur_timer % 60) self.ui.lcdNumber.display(text) if (self.cur_timer == 0): self.color_idx = 3 - self.color_idx self.show() self.setStyleSheet("QWidget { background-color: %s }" % self.color_names[self.color_idx - 1]) elif self.oneSecondCounter == 3: self.cur_timer -= 1 self.oneSecondCounter = 0 else: self.oneSecondCounter += 1 def updateTimers(self, timer_list): self.alarm_times = timer_list self.timer_iter = cycle(self.alarm_times) # An iterator that cycles through the list def pauseTimer(self): self.timerPause = not self.timerPause def resetTimer(self): # Reset the timer back to the head of the list self.timer_iter = cycle(self.alarm_times) self.cur_timer = self.timer_iter.next() def mouseReleaseEvent(self, event): button = event.button() if button == 2: self.hide() if (self.cur_timer == 0): self.cur_timer = self.snooze_time # Start the timer with snooze value if teh cur_timer has expired elif button == 1: # left click if (self.cur_timer == 0): # blinking timer should be closed on a left click self.cur_timer = self.timer_iter.next() self.setStyleSheet("QWidget { background-color: Normal }" ) def mousePressEvent(self, event): button = event.button() if button == 1: self.dragPosition = event.globalPos() - self.frameGeometry().topLeft(); def mouseMoveEvent(self, event): if event.buttons() != QtCore.Qt.LeftButton: # not left click return self.move(event.globalPos() - self.dragPosition) def Str2Num(str_list): num = [] for str in str_list: try: num.append(int(str)) except ValueError: num.append(float(str)) return num if __name__ == "__main__": app = QtGui.QApplication(sys.argv) timerList = Str2Num(sys.argv[1:]) myapp = AlarmTimer(timerList) myapp.show() sys.exit(app.exec_())

33.092784

121

0.610592

385

3,210

4.942857

0.348052

0.046243

0.063058

0.033631

0.20494

0.139254

0.119285

0.037835

0

0.014442

0.288162

3,210

96

122

33.4375

0.818381

0.098131

0

0.213333

0

0.03294

0

1

0.12

false

0

0.053333

0

0.226667

0

null

0

null

0

1

0

da0dfc1a5ddc1f3fd9cff38b3e12d87c2cfff865

3,200

py

Python

backend/handlers/graphql/resolvers/quota.py

al-indigo/vmemperor

80eb6d47d839a4736eb6f9d2fcfad35f0a7b3bb1

[ "Apache-2.0" ]

null

backend/handlers/graphql/resolvers/quota.py

al-indigo/vmemperor

80eb6d47d839a4736eb6f9d2fcfad35f0a7b3bb1

[ "Apache-2.0" ]

8

2017-10-11T13:26:10.000Z

2021-12-13T20:27:52.000Z

backend/handlers/graphql/resolvers/quota.py

ispras/vmemperor

80eb6d47d839a4736eb6f9d2fcfad35f0a7b3bb1

[ "Apache-2.0" ]

4

2017-07-27T12:25:42.000Z

2018-01-28T02:06:26.000Z

from graphql import ResolveInfo from rethinkdb.errors import ReqlNonExistenceError from handlers.graphql.graphql_handler import ContextProtocol from handlers.graphql.types.pool import Quota from handlers.graphql.utils.query import resolve_from_root import constants.re as re from utils.quota import check_vdi_size, check_memory, check_vcpu_count, check_vm_count, get_used_vdi_size, \ get_used_memory, get_used_vcpu_count, get_used_vm_count from utils.user import user_entities, get_user_object def resolve_quotas(root, info, **args): from xenadapter import Pool ctx: ContextProtocol = info.context if ctx.user_authenticator.is_admin(): return re.db.table(Pool.quotas_table_name).coerce_to('array').run() else: return re.db.table(Pool.quotas_table_name).get_all(*user_entities(ctx.user_authenticator)).coerce_to('array').run() def get_item(user): from xenadapter import Pool result = re.db.table(Pool.quotas_table_name).get(user).run() if result: return result else: user_object = get_user_object(user) if user_object: result = {key: None for key in Quota._meta.fields.keys()} result.update({ "user_id": user }) return result else: raise ValueError(f"No such user: {user}") def resolve_quota(root, info, user): ctx: ContextProtocol = info.context if not ctx.user_authenticator.is_admin(): if user not in user_entities(ctx.user_authenticator): raise ValueError(f"Access denied: Not a member of an entity: {user}") return get_item(user) def resolve_quota_left(root, info : ResolveInfo, user): ctx: ContextProtocol = info.context if not ctx.user_authenticator.is_admin() and user not in user_entities(ctx.user_authenticator): raise ValueError(f"Access denied: Not a member of an entity: {user}") fields = [item.name.value for item in info.field_asts[0].selection_set.selections] result = {} if 'vdiSize' in fields: result['vdi_size'] = check_vdi_size(user) if 'memory' in fields: result['memory'] = check_memory(user) if 'vcpuCount' in fields: result['vcpu_count'] = check_vcpu_count(user) if 'vmCount' in fields: result['vm_count'] = check_vm_count(user) if 'user' in fields: result['user_id'] = user return result def resolve_quota_usage(root, info : ResolveInfo, user): ctx: ContextProtocol = info.context if not ctx.user_authenticator.is_admin() and user not in user_entities(ctx.user_authenticator): raise ValueError(f"Access denied: Not a member of an entity: {user}") fields = [item.name.value for item in info.field_asts[0].selection_set.selections] result = {} if 'vdiSize' in fields: result['vdi_size'] = get_used_vdi_size(user) if 'memory' in fields: result['memory'] = get_used_memory(user) if 'vcpuCount' in fields: result['vcpu_count'] = get_used_vcpu_count(user) if 'vmCount' in fields: result['vm_count'] = get_used_vm_count(user) if 'user' in fields: result['user_id'] = user return result

32

123

0.690938

446

3,200

4.748879

0.201794

0.037771

0.0661

0.054769

0.621341

0.556185

0.508026

0.429651

0

0.000792

0.210625

3,200

99

124

32.323232

0.837688

0

0.478873

0

0.101753

0

1

0.070423

false

0

0.140845

0

0.309859

0

null

0

null

0

1

0

da0e334dd350b538cbe6369f8de20266f08cd7ab

23,670

py

Python

webapp/creators/parse_eml.py

PASTAplus/umbra

25f179801ab86d6506759b19849de1f7a8bf9e8d

[ "Apache-2.0" ]

null

webapp/creators/parse_eml.py

PASTAplus/umbra

25f179801ab86d6506759b19849de1f7a8bf9e8d

[ "Apache-2.0" ]

null

webapp/creators/parse_eml.py

PASTAplus/umbra

25f179801ab86d6506759b19849de1f7a8bf9e8d

[ "Apache-2.0" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- """ :Mod: propagate_names :Synopsis: Parse EML files to collect information on the responsible parties, creating RESPONSIBLE_PARTIES_TEXT_FILE. :Author: ide :Created: 6/1/21 """ from enum import Enum, auto import glob import os import pickle import daiquiri from flask import ( Flask, Blueprint, jsonify, request, current_app ) from recordclass import recordclass from webapp.config import Config import webapp.creators.db as db import webapp.creators.nlp as nlp from metapype.eml import names from metapype.model.metapype_io import from_xml from metapype.model.node import Node logger = daiquiri.getLogger(Config.LOG_FILE) def log_info(msg): app = Flask(__name__) with app.app_context(): current_app.logger.info(msg) def log_error(msg): app = Flask(__name__) with app.app_context(): current_app.logger.error(msg) class EMLTextComponents(Enum): DATASET_TITLE = auto(), DATASET_ABSTRACT = auto(), DATASET_KEYWORDS = auto(), DATATABLE_DESCRIPTIONS = auto(), DATASET_GEO_DESCRIPTIONS = auto(), METHOD_STEP_DESCRIPTIONS = auto(), PROJECT_TITLES = auto(), PROJECT_ABSTRACTS = auto(), RELATED_PROJECT_TITLES = auto(), RELATED_PROJECT_ABSTRACTS = auto() ProjectText = recordclass( 'ProjectText', 'project_title project_abstract' ) EMLText = recordclass( 'EMLText', 'dataset_title dataset_abstract dataset_keywords datatable_descriptions dataset_geographic_descriptions method_step_descriptions projects related_projects' ) eml_text_by_pid = {} def xml_to_json(filepath): cwd = os.getcwd() with open(filepath, 'r') as fp: xml = fp.read() try: return from_xml(xml) except Exception as err: print(f'Metapype failed to convert xml to json for file {filepath}. Error:{err}') return None def parse_section(node): text = [] if node.content: text.append(node.content) return text title = node.find_child(names.TITLE) if title and title.content: text.append(title.content) section = node.find_child(names.SECTION) if section: text.extend(parse_section(section)) return text para = node.find_child(names.PARA) if para: text.extend(parse_para(para)) return text return text def parse_para(node): text = [] if node.content: text.append(node.content) return text value = node.find_child(names.VALUE) if value and value.content: return [value.content] return text def parse_text_type(node): text = [] if node.content: text.append(node.content) return text section = node.find_child(names.SECTION) if section: return parse_section(section) para = node.find_child(names.PARA) if para: return parse_para(para) return text def get_existing_eml_files(): filelist = glob.glob(f'{Config.EML_FILES_PATH}/*.xml') return [os.path.basename(x) for x in filelist] def get_dataset_title(eml_node): title_node = eml_node.find_single_node_by_path([names.DATASET, names.TITLE, names.VALUE]) if not title_node: title_node = eml_node.find_single_node_by_path([names.DATASET, names.TITLE]) return [title_node.content] def get_dataset_abstract(eml_node): abstract_node = eml_node.find_single_node_by_path([names.DATASET, names.ABSTRACT, names.PARA]) if not abstract_node: abstract_node = eml_node.find_single_node_by_path([names.DATASET, names.ABSTRACT, names.SECTION, names.PARA]) if abstract_node: return parse_text_type(abstract_node) else: return [] def harvest_projects(eml_node): project_nodes = eml_node.find_all_nodes_by_path([names.DATASET, names.PROJECT]) project_text = get_project_text(project_nodes) related_project_nodes = eml_node.find_all_nodes_by_path([names.DATASET, names.PROJECT, names.RELATED_PROJECT]) related_project_text = get_project_text(related_project_nodes) return project_text, related_project_text def get_project_text(project_nodes): project_text = [] for project_node in project_nodes: title = '' abstract = '' title_node = project_node.find_child(names.TITLE) if title_node: title = [title_node.content] abstract_node = project_node.find_child(names.ABSTRACT) if abstract_node: abstract = parse_text_type(abstract_node) project_text.append(ProjectText( project_title=title, project_abstract=abstract)) return project_text def get_project_titles(eml_node): project_titles = [] title_nodes = eml_node.find_all_nodes_by_path([names.DATASET, names.PROJECT, names.TITLE]) for title_node in title_nodes: if title_node.content: project_titles.append([title_node.content]) return project_titles def get_project_abstracts(eml_node): project_abstracts = [] abstract_nodes = eml_node.find_all_nodes_by_path([names.DATASET, names.PROJECT, names.ABSTRACT, names.PARA]) for abstract_node in abstract_nodes: project_abstracts.extend(parse_text_type(abstract_node)) return project_abstracts def get_keywords(eml_node): kw = [] keyword_nodes = [] eml_node.find_all_descendants(names.KEYWORD, keyword_nodes) for keyword_node in keyword_nodes: kw.append(keyword_node.content) return kw def get_all_ranks(eml_node, rank): rank_nodes = [] eml_node.find_all_descendants(names.TAXONRANKNAME, rank_nodes) found = set() for rank_node in rank_nodes: if rank_node.content.lower() == rank: parent = rank_node.parent rank_value = parent.find_child(names.TAXONRANKVALUE).content found.add(rank_value) return sorted(found) def get_all_genera(eml_node): return get_all_ranks(eml_node, 'genus') def get_all_species(eml_node): return get_all_ranks(eml_node, 'species') def get_children(parent_node, child_name): children = [] child_nodes = parent_node.find_all_children(child_name) for child_node in child_nodes: if child_node.content: children.append((child_name, child_node.content)) return children def get_person(rp_node): person = [] individual_name_node = rp_node.find_child(names.INDIVIDUALNAME) if individual_name_node: person.extend(get_children(individual_name_node, names.SALUTATION)) person.extend(get_children(individual_name_node, names.GIVENNAME)) person.extend(get_children(individual_name_node, names.SURNAME)) person.extend(get_children(rp_node, names.ORGANIZATIONNAME)) person.extend(get_children(rp_node, names.POSITIONNAME)) return person def get_address(rp_node): address = [] address_node = rp_node.find_child(names.ADDRESS) if address_node: address.extend(get_children(address_node, names.DELIVERYPOINT)) address.extend(get_children(address_node, names.CITY)) address.extend(get_children(address_node, names.ADMINISTRATIVEAREA)) address.extend(get_children(address_node, names.POSTALCODE)) address.extend(get_children(address_node, names.COUNTRY)) return address def get_responsible_party(rp_node): party = [] party.extend(get_person(rp_node)) party.extend(get_address(rp_node)) party.extend(get_children(rp_node, names.PHONE)) party.extend(get_children(rp_node, names.ELECTRONICMAILADDRESS)) party.extend(get_children(rp_node, names.ONLINEURL)) party.extend(get_children(rp_node, names.USERID)) return party def get_responsible_parties(pid, eml_node, path): rp_nodes = eml_node.find_all_nodes_by_path(path) parties = [] for rp_node in rp_nodes: party = get_responsible_party(rp_node) parties.append((pid, path[-1], party)) return parties def get_creators(pid, eml_node): return get_responsible_parties(pid, eml_node, [names.DATASET, names.CREATOR]) def get_contacts(pid, eml_node): return get_responsible_parties(pid, eml_node, [names.DATASET, names.CONTACT]) def get_associated_parties(pid, eml_node): return get_responsible_parties(pid, eml_node, [names.DATASET, names.ASSOCIATEDPARTY]) def get_metadata_providers(pid, eml_node): return get_responsible_parties(pid, eml_node, [names.DATASET, names.METADATAPROVIDER]) def get_project_personnel(pid, eml_node): return get_responsible_parties(pid, eml_node, [names.DATASET, names.PROJECT, names.PERSONNEL]) def get_related_project_personnel(pid, eml_node): return get_responsible_parties(pid, eml_node, [names.DATASET, names.PROJECT, names.RELATED_PROJECT, names.PERSONNEL]) def get_all_responsible_parties(pid, eml_node): responsible_parties = [] responsible_parties.extend(get_creators(pid, eml_node)) responsible_parties.extend(get_contacts(pid, eml_node)) responsible_parties.extend(get_associated_parties(pid, eml_node)) responsible_parties.extend(get_metadata_providers(pid, eml_node)) responsible_parties.extend(get_project_personnel(pid, eml_node)) responsible_parties.extend(get_related_project_personnel(pid, eml_node)) return responsible_parties def get_data_table_descriptions(eml_node): data_table_descriptions = [] description_nodes = eml_node.find_all_nodes_by_path([names.DATASET, names.DATATABLE, names.ENTITYDESCRIPTION]) for description_node in description_nodes: data_table_descriptions.extend(parse_text_type(description_node)) return data_table_descriptions def get_method_step_descriptions(eml_node): method_step_descriptions = [] description_nodes = eml_node.find_all_nodes_by_path([names.DATASET, names.METHODS, names.METHODSTEP, names.DESCRIPTION]) for description_node in description_nodes: method_step_descriptions.extend(parse_text_type(description_node)) return method_step_descriptions def get_all_titles_and_abstracts(eml_node): dataset_title = get_dataset_title(eml_node) dataset_abstract = get_dataset_abstract(eml_node) project_titles = [] project_abstracts = [] all_text = dataset_title[0] + " " if dataset_abstract: all_text += ' '.join(dataset_abstract) for title in project_titles: all_text += title[0] + " " for abstract in project_abstracts: all_text += ' '.join(dataset_abstract) return dataset_title, dataset_abstract, project_titles, project_abstracts, all_text def get_dataset_geographic_descriptions(eml_node): geographic_descriptions = [] geographic_description_nodes = eml_node.find_all_nodes_by_path([names.DATASET, names.COVERAGE, names.GEOGRAPHICCOVERAGE, names.GEOGRAPHICDESCRIPTION]) for geographic_description_node in geographic_description_nodes: description = geographic_description_node.content if description: geographic_descriptions.append(description) return geographic_descriptions def parse_eml_file(filename): pid = filename[:-4] filepath = f'{Config.EML_FILES_PATH}/{filename}' eml_node = xml_to_json(filepath) return pid, eml_node def collect_responsible_parties(filename, added_package_ids=None, removed_package_ids=None, trace=False): if added_package_ids == [] and removed_package_ids == []: return responsible_parties = db.parse_responsible_parties_file(filename) db.prune_pids(responsible_parties, removed_package_ids) # write the existing responsible parties, minus the ones to be removed output_filename = f'{Config.EML_FILES_PATH}/{filename}' with open(output_filename, 'w') as output_file: for _, val in responsible_parties.items(): for line in val: output_file.write(line) output_file.write('\n') # now, append the new responsible parties with open(output_filename, 'a') as output_file: filelist = get_existing_eml_files() if trace: log_info(f'len(filelist)={len(filelist)}') for index, filename in enumerate(filelist): pid = os.path.splitext(filename)[0] if added_package_ids and pid not in added_package_ids: continue pid, eml_node = parse_eml_file(filename) if eml_node: if trace: log_info(f' Adding {index} - {pid}') responsible_parties = get_all_responsible_parties(pid, eml_node) for responsible_party in responsible_parties: output_file.write(str(responsible_party)) output_file.write('\n') output_file.flush() # We're done with the JSON model. Delete it so we don't run out of memory. Node.delete_node_instance(eml_node.id, True) def collect_titles_and_abstracts(output_filename): with open(output_filename, 'w') as output_file: filelist = get_existing_eml_files() for index, filename in enumerate(filelist): # if filename.startswith('edi.'): # TEMP pid = filename[:-4] filepath = f'{Config.EML_FILES_PATH}/{filename}' eml_node = xml_to_json(filepath) if not eml_node: continue dataset_title, dataset_abstract, project_titles, project_abstracts, all_text = get_all_titles_and_abstracts(eml_node) all_text = all_text.replace('\n', '') output_file.write(f'{pid}\n') output_file.write(f'{all_text}\n') def collect_method_step_descriptions(output_filename): with open(output_filename, 'w') as output_file: filelist = get_existing_eml_files() for index, filename in enumerate(filelist): # if filename.startswith('edi.'): # TEMP pid = filename[:-4] filepath = f'{Config.EML_FILES_PATH}/{filename}' eml_node = xml_to_json(filepath) if not eml_node: continue text = get_data_table_descriptions(eml_node) text = get_method_step_descriptions(eml_node) # all_text = all_text.replace('\n', '') # output_file.write(f'{pid}\n') # output_file.write(f'{all_text}\n') def collect_text_for_scope(scope): text = [] filelist = get_existing_eml_files() for index, filename in enumerate(filelist): if filename.startswith(scope): filepath = f'{Config.EML_FILES_PATH}/{filename}' eml_node = xml_to_json(filepath) if not eml_node: continue text1 = get_data_table_descriptions(eml_node) text2 = [] #get_method_step_descriptions(eml_node) *_, text3 = get_all_titles_and_abstracts(eml_node) text.append(' '.join(text1) + ' '.join(text2) + text3) return ' '.join(text) def collect_text(pids): text = [] for pid in pids: filename = pid + '.xml' filepath = f'{Config.EML_FILES_PATH}/{filename}' eml_node = xml_to_json(filepath) if not eml_node: continue text1 = [] #get_data_table_descriptions(eml_node) text2 = [] #get_method_step_descriptions(eml_node) *_, text3 = get_all_titles_and_abstracts(eml_node) text.append(' '.join(text1) + ' '.join(text2) + text3) return ' '.join(text) def init_eml_text_by_pid(): global eml_text_by_pid filename = 'eml_text_by_pid.pkl' filepath = f'{Config.DATA_FILES_PATH}/{filename}' try: with open(filepath, 'rb') as pf: eml_text_by_pid = pickle.load(pf) print(f'Init harvest EML text... count={len(eml_text_by_pid)}') return eml_text_by_pid except FileNotFoundError: pass def save_eml_text_by_pid(): global eml_text_by_pid filename = 'eml_text_by_pid.pkl' filepath = f'{Config.DATA_FILES_PATH}/{filename}' with open(filepath, 'wb') as pickle_file: pickle.dump(eml_text_by_pid, pickle_file) def clean_projects(projects): cleaned = [] for project in projects: project.project_title = clean_list(project.project_title) project.project_abstract = clean_list(project.project_abstract) cleaned.append(project) return cleaned def clean_list(l): return [nlp.clean(s, remove_digits=True) for s in l] def harvest_eml_text(pids=None): global eml_text_by_pid if not pids: pids = db.get_all_pids() init_eml_text_by_pid() count = len(eml_text_by_pid) for pid in pids: if eml_text_by_pid.get(pid): continue filename = pid + '.xml' filepath = f'{Config.EML_FILES_PATH}/{filename}' eml_node = xml_to_json(filepath) if not eml_node: continue dataset_title = get_dataset_title(eml_node) dataset_abstract = get_dataset_abstract(eml_node) dataset_keywords = get_keywords(eml_node) datatable_descriptions = get_data_table_descriptions(eml_node) dataset_geographic_descriptions = get_dataset_geographic_descriptions(eml_node) method_step_descriptions = get_method_step_descriptions(eml_node) projects, related_projects = harvest_projects(eml_node) eml_text_by_pid[pid] = EMLText( dataset_title=clean_list(dataset_title), dataset_abstract=clean_list(dataset_abstract), dataset_keywords=clean_list(dataset_keywords), datatable_descriptions=clean_list(datatable_descriptions), dataset_geographic_descriptions=clean_list(dataset_geographic_descriptions), method_step_descriptions=clean_list(method_step_descriptions), projects=clean_projects(projects), related_projects=clean_projects(related_projects) ) count += 1 if count % 100 == 0: print(f'Saving... count={count}') save_eml_text_by_pid() save_eml_text_by_pid() def concat_project_text(projects, related_projects, components=(EMLTextComponents.PROJECT_TITLES, EMLTextComponents.PROJECT_ABSTRACTS, EMLTextComponents.RELATED_PROJECT_TITLES, EMLTextComponents.RELATED_PROJECT_ABSTRACTS)): project_text = '' for project in projects: if EMLTextComponents.PROJECT_TITLES in components: project_text += ' '.join(project.project_title) if EMLTextComponents.PROJECT_ABSTRACTS in components: project_text += ' '.join(project.project_abstract) for related_project in related_projects: if EMLTextComponents.PROJECT_TITLES in components: project_text += ' '.join(related_project.project_title) if EMLTextComponents.PROJECT_ABSTRACTS in components: project_text += ' '.join(related_project.project_abstract) return project_text def get_eml_text_as_string(pid, components=(EMLTextComponents.DATASET_TITLE, EMLTextComponents.DATASET_ABSTRACT, EMLTextComponents.DATASET_KEYWORDS, EMLTextComponents.DATATABLE_DESCRIPTIONS, EMLTextComponents.PROJECT_TITLES, EMLTextComponents.PROJECT_ABSTRACTS, EMLTextComponents.RELATED_PROJECT_TITLES, EMLTextComponents.RELATED_PROJECT_ABSTRACTS)): if not eml_text_by_pid: init_eml_text_by_pid() eml_string = '' eml_text = eml_text_by_pid.get((pid)) if not eml_text: return '' if EMLTextComponents.DATASET_TITLE in components: eml_string += ' '.join(eml_text.dataset_title) if EMLTextComponents.DATASET_ABSTRACT in components: eml_string += ' '.join(eml_text.dataset_abstract) if EMLTextComponents.DATASET_KEYWORDS in components: eml_string += ' '.join(eml_text.dataset_keywords) if EMLTextComponents.DATATABLE_DESCRIPTIONS in components: eml_string += ' '.join(eml_text.datatable_descriptions) if EMLTextComponents.DATASET_GEO_DESCRIPTIONS in components: eml_string += ' '.join(eml_text.dataset_geographic_descriptions) if EMLTextComponents.METHOD_STEP_DESCRIPTIONS in components: eml_string += ' '.join(eml_text.method_step_descriptions) eml_string += concat_project_text(eml_text.projects, eml_text.related_projects, components) return eml_string def get_eml_text_as_string_by_name(givenname, surname, components=(EMLTextComponents.DATASET_TITLE, EMLTextComponents.DATASET_ABSTRACT, EMLTextComponents.DATASET_KEYWORDS, EMLTextComponents.DATATABLE_DESCRIPTIONS, EMLTextComponents.PROJECT_TITLES, EMLTextComponents.PROJECT_ABSTRACTS, EMLTextComponents.RELATED_PROJECT_TITLES, EMLTextComponents.RELATED_PROJECT_ABSTRACTS)): if not eml_text_by_pid: init_eml_text_by_pid() pids = db.get_pids_by_name(givenname, surname) eml_string = '' for pid in pids: eml_string += get_eml_text_as_string(pid, components) return eml_string def get_eml_keywords_by_name(givenname, surname): if not eml_text_by_pid: init_eml_text_by_pid() pids = db.get_pids_by_name(givenname, surname) keywords = [] for pid in pids: eml_text = eml_text_by_pid.get((pid)) if not eml_text: continue keywords.extend(eml_text.dataset_keywords) return keywords if __name__ == '__main__': pass # collect_responsible_parties(f'{EML_FILES_PATH}/responsible_parties.txt') # harvest_eml_text() # raise ValueError # # from collections import Counter # givenname = 'Diana' # surname = 'Wall' # keywords = get_eml_keywords_by_name(givenname, surname) # counter = Counter(keywords) # highest = counter.most_common(20) # # text = get_eml_text_as_string_by_name(givenname, surname) # lemmas = nlp.lemmatize(text) # counter = Counter(lemmas) # highest = counter.most_common(30) # pids = db.get_all_pids() # harvest_eml_text(pids) # for pid in pids: # eml_string = get_eml_text_as_string(pid) # text = collect_text_for_scope('knb-lter-sbc') # collect_method_step_descriptions('foo.txt') # filename = 'knb-lter-fce.1143.2.xml' # pid, eml_node = parse_eml_file(filename) # if eml_node: # text1 = get_data_table_descriptions(eml_node) # text2 = get_method_step_descriptions(eml_node) # *_, text3 = get_all_titles_and_abstracts(eml_node) # all_text = ' '.join(text1) + ' '.join(text1) + text3 # collect_responsible_parties(f'{EML_FILES_PATH}/responsible_parties.txt') # collect_titles_and_abstracts(f'{EML_FILES_PATH}/titles_and_abstracts.txt')

35.170877

159

0.673722

2,855

23,670

5.239229

0.100525

0.041182

0.015644

0.020858

0.574007

0.518853

0.458484

0.391496

0.334336

0.324041

0

0.00245

0.241318

23,670

672

160

35.223214

0.830493

0.075792

0

0.323045

0

0.039316

0.021583

0

1

0.098765

false

0.004115

0.026749

0.018519

0.257202

0.00823

0

null

0

null

0

1

0

da0ee8203f152fc62fcdc9038c65fc7421a7da86

2,399

py

Python

pywrap.py

rosejn/pywrap

21076e66e3ae99013524e4f391a5928193072fd6

[ "MIT" ]

null

pywrap.py

rosejn/pywrap

21076e66e3ae99013524e4f391a5928193072fd6

[ "MIT" ]

null

pywrap.py

rosejn/pywrap

21076e66e3ae99013524e4f391a5928193072fd6

[ "MIT" ]

null

import ctypes def _wrap(functype, name, library, restype, params, errcheck=None): prototype = functype(restype, *(param.type for param in params)) paramflags = tuple(param.paramflags for param in params) wrapper = prototype((name, library), paramflags) if errcheck: wrapper.errcheck = errcheck return wrapper def wrap_winapi(name, library, restype, params, errcheck=None): return _wrap(ctypes.WINFUNCTYPE, name, library, restype, params, errcheck=errcheck) def wrap_cdecl(name, library, restype, params, errcheck=None): return _wrap(ctypes.CFUNCTYPE, name, library, restype, params, errcheck=errcheck) class Parameter(object): def __init__(self, name, type_, default=None, out=False): self._name = name self._type = type_ self._out = out self._default = default @property def flag(self): if self._out: return 2 else: return 1 @property def type(self): return self._type @property def paramflags(self): paramflags = (self.flag, self._name, self._default) if self._default is None: return paramflags[:-1] else: return paramflags class Errcheck(object): @staticmethod def expect_true(result, func, args): if not result: raise ctypes.WinError() return result @staticmethod def expect_null(result, func, args): if result: raise ctypes.WinError() return result @staticmethod def expect_not_null(result, func, args): if not result: raise ctypes.WinError() return result @staticmethod def expect_value(value): def errcheck(result, func, args): if result != value: raise ctypes.WinError() return result return errcheck @staticmethod def expect_lasterror(value): def errcheck(result, func, args): if ctypes.get_last_error() != value: raise ctypes.WinError() return result return errcheck @staticmethod def expect_no_error(result, func, args): if ctypes.get_last_error(): raise ctypes.WinError() return result @staticmethod def print_all(result, func, args): print(result, func, args) return result

24.731959

87

0.615673

265

2,399

5.449057

0.215094

0.055402

0.077562

0.066482

0.530471

0.509695

0.429363

0.364266

0.317175

0.204986

0

0.001784

0.298875

2,399

96

88

24.989583

0.856718

0

0.424658

0

1

0.219178

false

0

0.013699

0.041096

0.493151

0.027397

0

null

0

null

0

1

0

1

da0fb1e76df7bb263d04fdeb069e451fb04e547a

2,756

py

Python

pp/components/ring_single.py

flaport/gdsfactory

1f2e844c1fe27b9c6340e2d51500fd3358fa16e5

[ "MIT" ]

8

2020-08-25T11:25:18.000Z

2022-03-27T11:32:11.000Z

pp/components/ring_single.py

flaport/gdsfactory

1f2e844c1fe27b9c6340e2d51500fd3358fa16e5

[ "MIT" ]

null

pp/components/ring_single.py

flaport/gdsfactory

1f2e844c1fe27b9c6340e2d51500fd3358fa16e5

[ "MIT" ]

1

2022-03-04T07:03:29.000Z

from typing import Callable from pp.cell import cell from pp.component import Component from pp.components.bend_circular import bend_circular from pp.components.coupler_ring import coupler_ring from pp.components.waveguide import waveguide as waveguide_function from pp.config import call_if_func from pp.drc import assert_on_2nm_grid @cell def ring_single( wg_width: float = 0.5, gap: float = 0.2, bend_radius: float = 10.0, length_x: float = 4.0, length_y: float = 0.001, coupler: Callable = coupler_ring, waveguide: Callable = waveguide_function, bend: Callable = bend_circular, pins: bool = False, ) -> Component: """Single bus ring made of a ring coupler (cb: bottom) connected with two vertical waveguides (wl: left, wr: right) two bends (bl, br) and horizontal waveguide (wg: top) Args: wg_width: waveguide width gap: gap between for coupler bend_radius: for the bend and coupler length_x: ring coupler length length_y: vertical waveguide length coupler: ring coupler function waveguide: waveguide function bend: bend function pins: add pins .. code:: bl-wt-br | | wl wr length_y | | --==cb==-- gap length_x .. plot:: :include-source: import pp c = pp.c.ring_single(wg_width=0.5, gap=0.2, length_x=4, length_y=0.1, bend_radius=5) pp.plotgds(c) """ bend_radius = float(bend_radius) assert_on_2nm_grid(gap) coupler = call_if_func( coupler, gap=gap, wg_width=wg_width, bend_radius=bend_radius, length_x=length_x ) waveguide_side = call_if_func(waveguide, width=wg_width, length=length_y) waveguide_top = call_if_func(waveguide, width=wg_width, length=length_x) bend_ref = bend(width=wg_width, radius=bend_radius) if callable(bend) else bend c = Component() cb = c << coupler wl = c << waveguide_side wr = c << waveguide_side bl = c << bend_ref br = c << bend_ref wt = c << waveguide_top wl.connect(port="E0", destination=cb.ports["N0"]) bl.connect(port="N0", destination=wl.ports["W0"]) wt.connect(port="W0", destination=bl.ports["W0"]) br.connect(port="N0", destination=wt.ports["E0"]) wr.connect(port="W0", destination=br.ports["W0"]) wr.connect(port="E0", destination=cb.ports["N1"]) # just for netlist c.add_port("E0", port=cb.ports["E0"]) c.add_port("W0", port=cb.ports["W0"]) if pins: pp.add_pins_to_references(c) return c if __name__ == "__main__": import pp c = ring_single() cc = pp.add_pins(c) # print(c.settings) # print(c.get_settings()) pp.show(cc)

27.56

90

0.645501

400

2,756

4.2575

0.25

0.032883

0.023488

0.017616

0.086905

0.050499

0

0.018634

0.240566

2,756

99

91

27.838384

0.795031

0.286647

0

0.021552

0

0.039216

1

0.019608

false

0

0.176471

0

0.215686

0

null

0

null

0

1

0

da1134de439d802fe50733f5cc4818017bddfa77

1,469

py

Python

uninstall.py

Manisso/LFSET

df5f104687daf66ef4a0cb9808a0ce377415e2dc

[ "MIT" ]

8

2019-05-29T22:49:04.000Z

2021-02-28T21:05:28.000Z

uninstall.py

Manisso/LFSET

df5f104687daf66ef4a0cb9808a0ce377415e2dc

[ "MIT" ]

null

uninstall.py

Manisso/LFSET

df5f104687daf66ef4a0cb9808a0ce377415e2dc

[ "MIT" ]

2

2019-06-09T17:52:31.000Z

2019-09-09T17:14:46.000Z

#!/usr/bin/env python # -*- codeing: UTF-8 -*- import time import sys import os print(''' ____ ___ .__ __ .__ .__ .____ __________________________________________ | | \____ |__| ____ _______/ |______ | | | | ______ ___.__. | | \_ _____/ _____/\_ _____/\__ ___/ | | / \| |/ \ / ___/\ __\__ \ | | | | \____ < | | ______ | | | __) \_____ \ | __)_ | | | | / | \ | | \\___ \ | | / __ \| |_| |__ | |_> >___ | /_____/ | |___| \ / \ | \ | | |______/|___| /__|___| /____ > |__| (____ /____/____/ /\ | __// ____| |_______ \___ / /_______ //_______ / |____| \/ \/ \/ \/ \/ |__| \/ \/ \/ \/ \/ ''') ch = raw_input('Do you REALLY want to uninstall LFSET? (N/y): ') if ch == 'N': print("Have a good day!") elif ch == 'y': print('sorry you didnt like it :( BUT, HAVE A GOOD DAY :))))') time.sleep(5) os.system('clear') os.system('cd .. && cd .. && cd ..') os.system('rm -rf etc') os.system('rm -rf files') os.system('rm -rf tools') os.system('rm -rf .git') os.system('rm -rf LICENSE') os.system('rm -rf README.md') print('All files uninstalled, after 10sec this file will be del...') time.sleep(10) os.system('sudo rm -rf uninstall.py')

43.205882

136

0.429544

111

1,469

3.585586

0.54955

0.180905

0.150754

0.180905

0

0.006572

0.378489

1,469

33

137

44.515152

0.429354

0.029272

0

0.142857

0.79073

0.029494

0

1

0

false

0

0.107143

0

0.107143

0.142857

0

null

0

1

0

1

0

1

0

null

0

3

da1152e98be68574744964ed8c665a43ee954229

13,297

py

Python

src/services/db/oracle.py

daesnorey/PPRJ

f826eb194f895d13522f61a51a5100a5cdbead99

[ "Apache-2.0" ]

null

src/services/db/oracle.py

daesnorey/PPRJ

f826eb194f895d13522f61a51a5100a5cdbead99

[ "Apache-2.0" ]

null

src/services/db/oracle.py

daesnorey/PPRJ

f826eb194f895d13522f61a51a5100a5cdbead99

[ "Apache-2.0" ]

null

"""oracle.py. db_connection.py file will contain the connection behaviour to the database """ import traceback import random import copy import cx_Oracle import json from src.objects.third import Third from src.services.db.db_types import DbTypes class Oracle(object): """Oracle class will handle the conection to the database.""" def __init__(self): """Constructor.""" self.__data_base = None self.__cursor = None def __open(self, debug=False): """Connect to the database.""" username = 'pre_dnovoa'#'PPRJ' password = 'w27XYfj5' hostname = '127.0.0.1' servicename = 'XE' port = 1521 dsn_tns = cx_Oracle.makedsn(hostname, port, servicename) if debug is True: print(dsn_tns) try: self.__data_base = cx_Oracle.connect(username, password, dsn_tns) except cx_Oracle.DatabaseError as e: error, = e.args if error.code == 1017: print('Please check your credentials.') # sys.exit()? else: print(e) # Very important part! raise # If the database connection succeeded create the cursor # we-re going to use. self.__cursor = self.__data_base.cursor() def __close(self): if self.__data_base is not None: self.__data_base.close() self.__data_base = None self.__cursor = None def get_cursor(self): """Get cursor connection.""" if self.__cursor is None: self.__open() return self.__cursor def execute(self, query, bindvars={}, commit=False, debug=False): """Execute query, return cursor.""" __noramalizate = self.normalize_query(query, bindvars) __query = __noramalizate[0] __bindvars = __noramalizate[1] if debug: print(query, bindvars) print("*" * 10) print(__query, __bindvars) response = self.get_cursor().execute(__query, __bindvars) if commit is True: self.__data_base.commit() return response def normalize_query(self, query, bindvars): """Method normalize_query.""" if not bindvars or "." not in query: return [query, bindvars] new_bindvars = {} for key in bindvars: value = bindvars[key] if DbTypes.exist(value): continue if "." in key: new_key = self.get_condition_key(key) new_bindvars[new_key] = value query = query.replace(":" + key, ":" + new_key) else: new_bindvars[key] = value return [query, new_bindvars] def get_condition_key(self, key): """Method get_condition_key.""" dot = "." new_key = "" if dot in key: new_key = str(random.choice('abcdefghij')) new_key += str(random.randint(0, 1000)) new_key += key.split(dot)[1] return new_key def get_join_select(self, fields=None, conditions=None, join_fields=None, *table): """Method get_query. @param table: table name in database @param fields: dictionary which contain the fields to affect. @param condition: dictionary which contain the fields and values to filter """ if not fields: fields = [] if not conditions: conditions = {} if not join_fields: join_fields = {} __inst = self.get_join_instruction(fields, len(table), join_fields) __inst += self.get_conditions(1, conditions) query = __inst for number in range(len(table)): str_replace = ":table" + str(number) __table = table[number].replace("l__", "") __table = table[number].replace("r__", "") query = query.replace(str_replace, table[number]) return query def get_join_instruction(self, fields, n_tables=1, join=None): """get_instruction. This method will evaluate the action and will return the right instruction """ if not join: join = [] __ini = "SELECT :fields FROM :table0" if n_tables > 1: for index in range(n_tables - 1): to_join = join[index] str_table = ":table" + str(index + 1) str_join = "" if to_join.startswith("l__"): __ini += " LEFT JOIN " elif to_join.startswith("r__"): __ini += " RIGHT JOIN " else: __ini += " INNER JOIN " __ini += str_table print("to_join", to_join) for field in to_join: print("field", field) if str_join: str_join += " AND " str_join += str_table + "." + field str_join += "= :table0." + field __ini += " ON " + str_join __inst = "" for field in fields: if __inst: __inst += "," __inst += field if not fields: __inst = "*" response = __ini.replace(":fields", __inst) return response def get_query(self, table, fields=None, conditions=None, action=1): """Method get_query. @param table: table name in database @param fields: dictionary which contain the fields to affect. @param condition: dictionary which contain the fields and values to filter @param action: 0=INSERT, 1=SELECT, 2=UPDATE, 3=DELETE """ if not fields: fields = [] if not conditions: conditions = {} __inst = self.get_instruction(action, fields) __inst += self.get_conditions(action, conditions) if action == 0: __inst += " returning :return_id INTO :new_id" query = __inst.replace(":table", table) return query def get_instruction(self, action, fields): """get_instruction. This method will evaluate the action and will return the right instruction """ __ini = "" if action == 0: __ini = "INSERT INTO :table (:fields) VALUES (:values)" elif action == 1: __ini = "SELECT :fields FROM :table" elif action == 2: __ini = "UPDATE :table SET :fields" elif action == 3: __ini = "DELETE FROM :table" return __ini __inst = "" __values = "" for field in fields: try: __type = fields[field].get("type")# if isinstance(fields[field], dict) else None except: __type = None if __inst: __inst += "," __values += "," if action == 0: __inst += field __values += "TO_DATE(:{0}, 'yyyy-MM-dd')".format(field) if __type == "date" else ":{}".format(field) elif action == 2: __inst += "{0}= TO_DATE(:{0}, 'yyyy-MM-dd')".format(field) if __type == "date" else "{0}=:{0}".format(field) else: __inst += field __values += ":" + field if not fields and action == 1: __inst = "*" response = __ini.replace(":fields", __inst).replace(":values", __values) return response def get_conditions(self, action, conditions): """Method get_conditions. this method will evaluate the action and the conditions if the action is 0 or there are no conditions then it returns an empty string otherwise it return the right condition """ s_conditions = len(conditions) if action == 0 or s_conditions == 0: return "" __condition = " WHERE " __cond = "" for condition in conditions: try: __type = conditions[condition].get("type") except: __type = None __value = conditions[condition] if not __type else conditions[condition].get("value") if not isinstance(__value, list): __value = [__value] for __val in __value: if __cond: __cond += " AND " if DbTypes.exist(__val): __sentence = DbTypes.get_sentence(__val) if '{}' in __sentence: __cond += __sentence.format(condition) else: __cond += condition + " " + __sentence else: __cond += "{0} = TO_DATE(:{0}, 'yyyy-MM-dd')".format(condition) if __type == "date" else "{0}=:{0}".format(condition) __condition += __cond return __condition def save(self, table, generic_object, name_id): """Method save. @attribute table @attribute generic_object @attribute name_id """ __fields = copy.copy(generic_object) if name_id in __fields: del __fields[name_id] if isinstance(generic_object[name_id], dict): id_object = generic_object[name_id]['value'] else: id_object = generic_object[name_id] else: id_object = -1 response = {} try: response = dict(error=0, text="success") if id_object > 0: __condition = {name_id: id_object} __update_query = self.get_query(table, __fields, __condition, action=2) for field in generic_object: generic_object[field] = generic_object[field].get("value") print(__update_query) self.execute(__update_query, generic_object, True) else: newest_id_wrapper = self.get_cursor().var(cx_Oracle.NUMBER) __insert_query = self.get_query(table, fields=__fields, action=0) for field in __fields: __fields[field] = __fields[field].get("value") __fields["new_id"] = newest_id_wrapper __insert_query = __insert_query.replace(":return_id", name_id) print(__insert_query) self.execute(__insert_query, __fields, True, False) new_id = newest_id_wrapper.getvalue() response["id"] = int(new_id) except Exception as e: formatted_lines = traceback.format_exc().splitlines() print(formatted_lines[0]) print(formatted_lines[-1]) print(e) response = dict(error=1, text="There was an error saving", desc_error=formatted_lines[-1]) return response def delete(self, table, conditions): """Method delete. @attribute table @attribute name_id @attribute id_object """ condition_size = len(conditions) if condition_size == 0: return dict(error=2, text="Data incomplete at delete") __delete_query = self.get_query(table, conditions=conditions, action=3) response = {} try: self.execute(__delete_query, conditions, True) response = dict(error=0, text="success") except Exception: response = dict(error=2, text="There was an error deleting") return response def search(self, **options): table = options.get("table") if not table: raise Exception("fuck you") tmp = {} if isinstance(table, list): pass else: query = self.get_instruction(1, {}).replace(":table", table) fields = options.get("fields") conditions = options.get("conditions") class_object = options.get("class_object") for field in fields: nquery = "{} WHERE".format(query) for condition in conditions: if len(condition.strip()) == 0: continue nquery += " LOWER({}) LIKE LOWER('%{}%') OR".format(field, condition) nquery = nquery.strip("OR").strip() response = self.execute(nquery, {}, debug=False) if not response: continue for row in response.fetchall(): id = row[0] if not tmp.get(id): tmp[id] = [row, 1] else: tmp[id][1] += 1 if class_object: result = [] for key in tmp.keys(): item = class_object(tmp[key][0], tmp[key][1]) result.append(item) result.sort(key=lambda x: x.w, reverse=True) else: result = tmp return result

31.88729

137

0.518087

1,379

13,297

4.704859

0.166062

0.010789

0.012947

0.015413

0.183724

0.156134

0.120376

0.110512

0.083847

0

0.009855

0.381891

13,297

416

138

31.963942

0.779535

0.106565

0

0.250883

0

0.063891

0

1

0.053004

false

0.010601

0.024735

0

0.137809

0.045936

0

null

0

null

0

1

0

da11aa1d5d2c57b57bf78f6eb3a605f93202667a

2,211

py

Python

utils/utils_math.py

spisakt/PUMI

bea29696aa90e5581f08919e1a2cd9f569284984

[ "BSD-3-Clause" ]

5

2018-06-12T08:17:13.000Z

2022-02-25T20:07:00.000Z

utils/utils_math.py

spisakt/PUMI

bea29696aa90e5581f08919e1a2cd9f569284984

[ "BSD-3-Clause" ]

null

utils/utils_math.py

spisakt/PUMI

bea29696aa90e5581f08919e1a2cd9f569284984

[ "BSD-3-Clause" ]

2

2020-10-19T15:27:28.000Z

2021-06-04T17:02:27.000Z

from nipype.interfaces.utility import Function def add_two(a, b): return float(a)+float(b) def sum_list(in_list): return sum(in_list) def sub_two(a,b): return float(a)-float(b) def abs_val(x): return abs(x) def sec2sigmaV(TR, sec): sigmaV=sec/(2*TR) return sigmaV # calculates colmeans, rowmenas or global mean, depenxding on the 'axis' parameter # and saves it to another txt def txt2MeanTxt(in_file, axis=None, header=False): import numpy as np import os if header: print "drop first line" data = np.loadtxt(in_file, skiprows=1) #header -> dropline else: print "don't drop first line" data = np.loadtxt(in_file) mean = data.mean(axis=axis) np.savetxt('mean.txt', [mean]) return os.getcwd() + '/mean.txt' def txt2MaxTxt(in_file, axis=None, header=False): import numpy as np import os if header: print "drop first line" data = np.loadtxt(in_file, skiprows=1) #header -> dropline else: print "don't drop first line" data = np.loadtxt(in_file) mean = data.max(axis=axis) np.savetxt('max.txt', [mean]) return os.getcwd() + '/max.txt' ############################################### AddTwo = Function(input_names=['a', 'b'], output_names=['sum'], function=add_two) SumList = Function(input_names=['in_list'], output_names=['sum'], function=sum_list) SubTwo = Function(input_names=['a', 'b'], output_names=['dif'], function=sub_two) Abs = Function(input_names=['x'], output_names=['abs'], function=abs_val) Sec2sigmaV = Function(input_names=['TR', 'sec'], output_names=['sigmaV'], function=sec2sigmaV) Txt2meanTxt = Function(input_names=['in_file', 'axis', 'header'], output_names=['mean_file'], function=txt2MeanTxt) Txt2maxTxt = Function(input_names=['in_file', 'axis', 'header'], output_names=['max_file'], function=txt2MaxTxt)

27.6375

82

0.557214

267

2,211

4.483146

0.280899

0.0401

0.105263

0.056809

0.487886

0.452799

0.401003

0.282373

0

0.007717

0.296698

2,211

80

83

27.6375

0.762058

0.065129

0

0.315789

0

0.094246

0

null

0

0.087719

null

0.070175

0

null

0

null

0

1

0

1

da11fc5980e78cefaeb92357886c125f256182a0

439

py

Python

exercicio_py/ex0007_progressao_aritmetica/main_v1.py

danielle8farias/Exercicios-Python-3

f2fe9b6ca63536df1d83fd10162cfc04de36b830

[ "MIT" ]

null

exercicio_py/ex0007_progressao_aritmetica/main_v1.py

danielle8farias/Exercicios-Python-3

f2fe9b6ca63536df1d83fd10162cfc04de36b830

[ "MIT" ]

null

exercicio_py/ex0007_progressao_aritmetica/main_v1.py

danielle8farias/Exercicios-Python-3

f2fe9b6ca63536df1d83fd10162cfc04de36b830

[ "MIT" ]

null

######## # autora: danielle8farias@gmail.com # repositório: https://github.com/danielle8farias # Descrição: Usuário informa o 1º termo de uma PA e sua razão. O programa retorna os 10 primeiros termos dessa PA. ######## A1 = int(input('Primeiro termo: ')) r = int(input('Razão: ')) i = 1 An = A1 while i < 11: print(f'{An}', end=' -> ') #fórmula da Progressão aritmética An = A1 + i*r #i = i + 1 i += 1 print('FIM')

23.105263

114

0.610478

65

439

4.123077

0.676923

0.022388

0

0.037791

0.216401

439

18

115

24.388889

0.741279

0.537585

0

0.187845

0

1

0

false

0

0.222222

0

null

0

null

0

1

0

da12532f996b1734f9456dcccabecc881b1e321b

2,165

py

Python

rns/viz.py

matwilso/relation-networks

66c67b342a90ae3699e576dcec883c329905b2e0

[ "MIT" ]

null

rns/viz.py

matwilso/relation-networks

66c67b342a90ae3699e576dcec883c329905b2e0

[ "MIT" ]

null

rns/viz.py

matwilso/relation-networks

66c67b342a90ae3699e576dcec883c329905b2e0

[ "MIT" ]

null

import io import os import matplotlib.pyplot as plt import matplotlib.patches as mpatches import seaborn as sns from rns.constant import W, H # Plotter functions PLOT_FUNCS = {} def register_plotter(func): PLOT_FUNCS[func.__name__] = func def func_wrapper(images, **conv_kwargs): return func(images, **conv_kwargs) return func_wrapper def plot(mode, vals, FLAGS, itr=0, save=True, return_buf=False, show=False): func = PLOT_FUNCS[mode] path = func(vals, FLAGS, itr=itr) buf = None if save: plt.savefig(path) if return_buf: buf = io.BytesIO() plt.savefig(buf) buf.seek(0) if show: plt.show() plt.close() return buf @register_plotter def arr(arr, FLAGS, itr=None): plt.imshow(arr, cmap='binary') @register_plotter def in_out_vae(vals, FLAGS, itr=0): vae_title = '{}-vae.png'.format(itr) os.makedirs(FLAGS['plot_path'], exist_ok=True) vae_path = os.path.join(FLAGS['plot_path'], vae_title) fig, (ax1, ax2) = plt.subplots(1,2) ax1.imshow(vals['img1'])#, cmap='binary') ax2.imshow(vals['img2'])#, cmap='binary') return vae_path @register_plotter def contour(vals, FLAGS, itr=0): X, Y, Z, state = vals['X'], vals['Y'], vals['Z'], vals['state'] prob_title = '{}-prob.png'.format(itr) os.makedirs(FLAGS['plot_path'], exist_ok=True) prob_path = os.path.join(FLAGS['plot_path'], prob_title) plt.contour(X,Y,Z[:,:,0]) plt.scatter(state[0,:,0], state[0,:,1]) plt.title(prob_title) return prob_path @register_plotter def samples(vals, FLAGS, itr=0): samples = vals['samples'] sample_title = '{}-sample.png'.format(itr) sample_path = os.path.join(FLAGS['plot_path'], sample_title) sns.jointplot(samples[:,0,0], samples[:,0,1], kind='hex', color='#4cb391', xlim=(-1.0,1.0), ylim=(-1.0,1.0)) return sample_path @register_plotter def shapes(vals, FLAGS, itr=None): dg = vals['dg'] ax = plt.gca(aspect='equal', xlim=W, ylim=H) rect = mpatches.Rectangle((0,0), W, H, color='C0') ax.add_patch(rect) objs = dg.__next__() for o in objs['shapes']: o.plot(ax)

27.0625

112

0.639261

332

2,165

4.03012

0.298193

0.041854

0.053812

0.038864

0.168161

0.129297

0.068759

0

0.021155

0.192148

2,165

79

113

27.405063

0.743854

0.022633

0

0.109375

0

0.063003

0

1

0.125

false

0

0.09375

0.015625

0.3125

0

null

0

null

0

1

0

da1332cc41c82ca79874cad9790e459f7a50414e

591

py

Python

payments/tests.py

asm3ft/cs3240-quickthooters

53000deca2d4a4ff4244cde76f36e7adcfb52784

[ "MIT", "PostgreSQL", "Unlicense" ]

null

payments/tests.py

asm3ft/cs3240-quickthooters

53000deca2d4a4ff4244cde76f36e7adcfb52784

[ "MIT", "PostgreSQL", "Unlicense" ]

9

2021-04-08T21:41:10.000Z

2022-03-12T00:26:00.000Z

payments/tests.py

asm3ft/cs3240-quickthooters

53000deca2d4a4ff4244cde76f36e7adcfb52784

[ "MIT", "PostgreSQL", "Unlicense" ]

null

from django.test import TestCase from django.test import RequestFactory, TestCase from .views import charge, HomePageView from login.models import Profile from django.contrib.auth.models import User # class PaymentViewsTestCase(TestCase): # def setUp(self): # # Every test needs access to the request factory. # self.factory = RequestFactory() # self.user = User.objects.create_user( # username='jacob', email='jacob@…', password='top_secret') # def charge_view_test(self): # # tbd # self.assertEquals(1, 1)

26.863636

71

0.663283

69

591

5.666667

0.57971

0.076726

0.071611

0.102302

0

0.004454

0.240271

591

21

72

28.142857

0.859688

0.588832

0

1

0

true

0

1

0

1

0

null

0

null

0

1

0

1

0

1

0

3

da1588b9217dc470ed263275774b3681de6ca380

642

py

Python

MTRF/r3l/r3l/robot/robot.py

facebookresearch/MTRF

2fee8f3f1c2150fcecc2db2fa9e122a664a72d72

[ "Apache-2.0" ]

2

2021-11-29T10:09:56.000Z

2022-02-01T05:48:32.000Z

MTRF/r3l/r3l/robot/robot.py

facebookresearch/MTRF

2fee8f3f1c2150fcecc2db2fa9e122a664a72d72

[ "Apache-2.0" ]

null

MTRF/r3l/r3l/robot/robot.py

facebookresearch/MTRF

2fee8f3f1c2150fcecc2db2fa9e122a664a72d72

[ "Apache-2.0" ]

null

# Copyright (c) Facebook, Inc. and its affiliates # Copyright (c) MTRF authors import abc class Robot(metaclass=abc.ABCMeta): def __init__(self, env=None): self._env = env if env: self._sim = env.sim else: self._sim = None @property @abc.abstractmethod def is_hardware(self): raise NotImplementedError @abc.abstractmethod def step(self, action): raise NotImplementedError @abc.abstractmethod def set_state(self, state): raise NotImplementedError @abc.abstractmethod def get_obs_dict(self): raise NotImplementedError

21.4

49

0.640187

71

642

5.633803

0.507042

0.17

0.2

0.3075

0.33

0

0.281931

642

29

50

22.137931

0.867679

0.115265

0

0.380952

0

1

0.238095

false

0

0.047619

0

0.333333

0

null

0

1

0

null

0

1

0

3

da160107a31d4d4dd133e4fba3b2b4c6286bd983

2,955

py

Python

pycurb/time_rule.py

azavea/PyCurb

9492ca40b0639680b73aa7bdfcf9f744f9e75727

[ "Apache-2.0" ]

null

pycurb/time_rule.py

azavea/PyCurb

9492ca40b0639680b73aa7bdfcf9f744f9e75727

[ "Apache-2.0" ]

8

2020-09-30T17:15:50.000Z

2020-10-23T21:00:53.000Z

pycurb/time_rule.py

azavea/PyCurb

9492ca40b0639680b73aa7bdfcf9f744f9e75727

[ "Apache-2.0" ]

null

from abc import ABC from pycurb.utils import (parse_date, parse_day_of_month, parse_day_of_week, parse_occurrence, parse_time) class TimeRule(ABC): pass class DaysOfWeek(TimeRule): def __init__(self, days, occurences_in_month=None): if isinstance(days, str): days = [days] self.days = [parse_day_of_week(day) for day in days] self.occurences_in_month = None if occurences_in_month: self.occurences_in_month = [ parse_occurrence(o) for o in occurences_in_month ] @staticmethod def from_dict(d): return DaysOfWeek(d['days']) def to_dict(self): return {'days': self.days} class DaysOfMonth(TimeRule): def __init__(self, days): if isinstance(days, 'str'): days = [days] self.days = [parse_day_of_month(day) for day in days] @staticmethod def from_dict(d): return DaysOfMonth(d['days']) def to_dict(self): return {'days': self.days} class DesignatedPeriod(TimeRule): def __init__(self, name, apply): self.name = name apply = apply.lower() self.apply = None if apply in ('except during', 'only during'): self.apply = apply @staticmethod def from_dict(d): return DesignatedPeriod(d['name'], d['apply']) def to_dict(self): d = {'name': self.name} if self.apply: d['apply'] = self.apply return d class EffectiveDates(TimeRule): def __init__(self, date_from, date_to): self.date_from = parse_date(date_from) self.date_to = parse_date(date_to) self.year = False if len(date_from.split('-')) > 2 and len(date_to.split('-')) > 2: self.year = True @staticmethod def from_dict(d): return EffectiveDates(d['from'], d['to']) def to_dict(self): d = { 'from': '{}-{}'.format(self.date_from.month, self.date_from.day), 'to': '{}-{}'.format(self.date_to.month, self.date_to.day) } if self.year: d['from'] = '{}-'.format(self.date_from.year) + d['from'] d['to'] = '{}-'.format(self.date_to.year) + d['to'] return d class TimeOfDay(TimeRule): def __init__(self, time_from, time_to): self.time_from = parse_time(time_from) self.time_to = parse_time(time_to) def is_equal(self, time_of_day): return self.to_dict() == time_of_day.to_dict() @staticmethod def from_dict(d): return TimeOfDay(d['from'], d['to']) def to_dict(self): st_h = str(self.time_from.hour).zfill(2) st_m = str(self.time_from.minute).zfill(2) en_h = str(self.time_to.hour).zfill(2) en_m = str(self.time_to.minute).zfill(2) return { 'from': '{}:{}'.format(st_h, st_m), 'to': '{}:{}'.format(en_h, en_m) }

26.863636

77

0.575973

394

2,955

4.068528

0.154822

0.044916

0.046787

0.059264

0.361822

0.25577

0.1335

0.107299

0

0.002844

0.285956

2,955

109

78

27.110092

0.756872

0

0.256098

0

0.042301

0

1

0.195122

false

0.012195

0.02439

0.097561

0.426829

0

null

0

null

0

1

0

da170ec47cebeb13d6c068d32835dcf9ac0425e1

2,653

py

Python

amrlib/models/parse_gsii/vocabs.py

plandes/amrlib

c31f92f05a265362367eea85f512e54030860147

[ "MIT" ]

103

2020-09-04T07:21:09.000Z

2022-03-31T23:06:41.000Z

amrlib/models/parse_gsii/vocabs.py

plandes/amrlib

c31f92f05a265362367eea85f512e54030860147

[ "MIT" ]

39

2020-09-03T14:26:22.000Z

2022-03-08T20:18:59.000Z

amrlib/models/parse_gsii/vocabs.py

plandes/amrlib

c31f92f05a265362367eea85f512e54030860147

[ "MIT" ]

19

2020-09-30T12:15:08.000Z

2022-02-18T18:15:31.000Z

import os PAD, UNK, DUM, NIL, END, CLS = '<PAD>', '<UNK>', '<DUMMY>', '<NULL>', '<END>', '<CLS>' # Note: for the function that saves the vocabs, see create_vocabs.py def get_vocabs(vocab_dir): vocabs = dict() vocabs['tok'] = Vocab(os.path.join(vocab_dir, 'tok_vocab'), 5, [CLS]) vocabs['lem'] = Vocab(os.path.join(vocab_dir, 'lem_vocab'), 5, [CLS]) vocabs['pos'] = Vocab(os.path.join(vocab_dir, 'pos_vocab'), 5, [CLS]) vocabs['ner'] = Vocab(os.path.join(vocab_dir, 'ner_vocab'), 5, [CLS]) vocabs['predictable_concept'] = Vocab(os.path.join(vocab_dir, 'predictable_concept_vocab'), 5, [DUM, END]) vocabs['concept'] = Vocab(os.path.join(vocab_dir, 'concept_vocab'), 5, [DUM, END]) vocabs['rel'] = Vocab(os.path.join(vocab_dir, 'rel_vocab'), 50, [NIL]) vocabs['word_char'] = Vocab(os.path.join(vocab_dir, 'word_char_vocab'), 100, [CLS, END]) vocabs['concept_char'] = Vocab(os.path.join(vocab_dir, 'concept_char_vocab'), 100, [CLS, END]) return vocabs class Vocab(object): def __init__(self, filename, min_occur_cnt, specials = None): idx2token = [PAD, UNK] + (specials if specials is not None else []) self._priority = dict() num_tot_tokens = 0 num_vocab_tokens = 0 with open(filename) as f: lines = f.readlines() for line in lines: try: token, cnt = line.rstrip('\n').split('\t') cnt = int(cnt) num_tot_tokens += cnt except: print(line) if cnt >= min_occur_cnt: idx2token.append(token) num_vocab_tokens += cnt self._priority[token] = int(cnt) self.coverage = num_vocab_tokens/num_tot_tokens self._token2idx = dict(zip(idx2token, range(len(idx2token)))) self._idx2token = idx2token self._padding_idx = self._token2idx[PAD] self._unk_idx = self._token2idx[UNK] def priority(self, x): return self._priority.get(x, 0) @property def size(self): return len(self._idx2token) @property def unk_idx(self): return self._unk_idx @property def padding_idx(self): return self._padding_idx def idx2token(self, x): if isinstance(x, list): return [self.idx2token(i) for i in x] return self._idx2token[x] def token2idx(self, x): if isinstance(x, list): return [self.token2idx(i) for i in x] return self._token2idx.get(x, self.unk_idx)

37.366197

110

0.574821

344

2,653

4.235465

0.264535

0.054907

0.067948

0.092656

0.289636

0.264928

0.156486

0.043926

0

0.017433

0.286468

2,653

70

111

37.9

0.752245

0.024878

0

0.087719

0

0.083172

0.009671

0

1

0.140351

false

0

0.017544

0.070175

0.333333

0.017544

0

null

0

null

0

1

0

da1752aa56e3a9f32b692a7cdcc8c12c9105eaac

1,139

py

Python

MAR2020/MakingChange.py

dexterchan/DailyChallenge

1f38dc3b22983835836a84d6281777d8e20fce7a

[ "Apache-2.0" ]

null

MAR2020/MakingChange.py

dexterchan/DailyChallenge

1f38dc3b22983835836a84d6281777d8e20fce7a

[ "Apache-2.0" ]

null

MAR2020/MakingChange.py

dexterchan/DailyChallenge

1f38dc3b22983835836a84d6281777d8e20fce7a

[ "Apache-2.0" ]

null

#Given a list of possible coins in cents, and an amount (in cents) n, # return the minimum number of coins needed to create the amount n. # If it is not possible to create the amount using the given coin denomination, return None. #Here's an example and some starter code: #ANalysis, sort the list of possible coins O(nlogn) from largest to smallest #for each cent, #divide amount by cent value = d, if d >= 1 # amt = amt - d*cent value # store cent value to list # iterate for next cent # at end of list # if amt > 0 , return None def make_change(coins, n): # Fill this in. lst = [] coinsLst = sorted(coins, reverse=True) amt = n for c in coinsLst: d = amt // c amt = amt - d * c for i in range(d): lst.append(str(c)) if amt > 0: return None else: result = "%d coins (%s)"%(len(lst), "+".join((lst))) return result if __name__ == "__main__": print(make_change([1, 5, 10, 25], 36)) # 3 coins (25 + 10 + 1) print(make_change([1, 5, 10, 25], 30)) # 2 coins (25 + 5) print(make_change([1, 5, 10, 25], 27)) # 2 coins (25 + 1 + 1)

28.475

92

0.603161

191

1,139

3.534031

0.445026

0.059259

0.066667

0.071111

0.140741

0.093333

0

0.050971

0.276558

1,139

40

93

28.475

0.768204

0.510975

0

0.04059

0

1

0.055556

false

0

0.166667

0

null

0

null

0

1

0

da17721d993049cf0bec2f0d42ed1fdb58798fac

951

py

Python

lightcycle-frontend/tournament/admin.py

Onapsis/pytron

2ed0622ae13f010bcd8fdbbd2f1e9cba3d2e3d58

[ "MIT" ]

1

2015-11-04T12:04:42.000Z

lightcycle-frontend/tournament/admin.py

Onapsis/pytron

2ed0622ae13f010bcd8fdbbd2f1e9cba3d2e3d58

[ "MIT" ]

null

lightcycle-frontend/tournament/admin.py

Onapsis/pytron

2ed0622ae13f010bcd8fdbbd2f1e9cba3d2e3d58

[ "MIT" ]

null

from django.contrib import admin from django.contrib.auth.admin import UserAdmin from django.contrib.auth.models import User from tournament.models import Bot, Challenge, UserProfile class UserProfileAdmin(admin.ModelAdmin): list_display = ('user', 'score') model = UserProfile class UserProfileInline(admin.TabularInline): model = UserProfile class UserWithProfileAdmin(UserAdmin): inlines = [UserProfileInline] list_display = ( 'email', 'username', 'is_active') class BotAdmin(admin.ModelAdmin): list_display = ('owner', 'creation_date', 'modification_date') class ChallengeAdmin(admin.ModelAdmin): list_display = ('requested_by', 'creation_date', 'winner_bot', 'challenger_bot', 'challenged_bot') admin.site.register(Bot, BotAdmin) admin.site.register(Challenge, ChallengeAdmin) admin.site.unregister(User) admin.site.register(User, UserWithProfileAdmin) admin.site.register(UserProfile, UserProfileAdmin)

32.793103

84

0.773922

104

951

6.961538

0.403846

0.062155

0.093923

0.107735

0

0.115668

951

28

85

33.964286

0.86088

0

0.090909

0

0.135647

0

1

0

false

0

0.181818

0

0.727273

0

null

0

null

0

1

0

1

da18045dfd912105fc7a816ba7142c291b5641e5

358

py

Python

scripts/plotting/utils.py

ltiao/pynance

1f170f9d32262eacf566a8d7647be04715c47dc1

[ "MIT" ]

1

2021-04-24T09:23:35.000Z

scripts/plotting/utils.py

ltiao/pynance

1f170f9d32262eacf566a8d7647be04715c47dc1

[ "MIT" ]

null

scripts/plotting/utils.py

ltiao/pynance

1f170f9d32262eacf566a8d7647be04715c47dc1

[ "MIT" ]

1

2021-07-14T08:55:39.000Z

import numpy as np import pandas as pd import yaml from pynance.benchmarks import make_benchmark from pathlib import Path GOLDEN_RATIO = 0.5 * (1 + np.sqrt(5)) WIDTH = 397.48499 def pt_to_in(x): pt_per_in = 72.27 return x / pt_per_in def size(width, aspect=GOLDEN_RATIO): width_in = pt_to_in(width) return (width_in, width_in / aspect)

17.9

45

0.72067

64

358

3.8125

0.53125

0.086066

0.04918

0.065574

0

0.055556

0.195531

358

19

46

18.842105

0.791667

0

1

0.153846

false

0

0.384615

0

0.692308

0

null

0

null

0

1

0

1

0

2

da1abe2987395fdd9c8ec09105630f0f84d026d1

3,637

py

Python

tests/test_per_sample_wrapper.py

NiWaRe/deepee

98b5cd09f356f4a597fe204799a524c4d444dd2d

[ "Apache-2.0" ]

16

2021-03-24T09:50:32.000Z

2022-03-10T12:03:37.000Z

tests/test_per_sample_wrapper.py

NiWaRe/deepee

98b5cd09f356f4a597fe204799a524c4d444dd2d

[ "Apache-2.0" ]

4

2021-03-27T09:36:20.000Z

2021-10-18T09:30:47.000Z

tests/test_per_sample_wrapper.py

NiWaRe/deepee

98b5cd09f356f4a597fe204799a524c4d444dd2d

[ "Apache-2.0" ]

4

2021-06-24T08:30:47.000Z

2021-11-09T08:33:57.000Z

from deepee import PerSampleGradientWrapper import torch import pytest class MiniModel(torch.nn.Module): def __init__(self): super().__init__() self.lin = torch.nn.Linear(10, 1) def forward(self, x): return self.lin(x) def test_wrap(): wrapped = PerSampleGradientWrapper(MiniModel(), 2) def test_forward(): data = torch.randn(2, 1, 10) wrapped = PerSampleGradientWrapper(MiniModel(), 2) output = wrapped(data) assert output.shape == (2, 1, 1) def test_raises_param_error(): wrapped = PerSampleGradientWrapper(MiniModel(), 2) with pytest.raises(ValueError): params = wrapped.parameters() def test_check_device_cpu(): wrapped = PerSampleGradientWrapper(MiniModel(), 2).to("cpu") assert ( next( iter( set([param.device.type for param in wrapped.wrapped_model.parameters()]) ) ) == "cpu" ) for model in wrapped.models: assert ( next(iter(set([param.device.type for param in model.parameters()]))) == "cpu" ) def test_check_device_gpu(): if torch.cuda.is_available(): wrapped = PerSampleGradientWrapper(MiniModel(), 2).to("cuda") assert "cuda" in next( iter( set([param.device.type for param in wrapped.wrapped_model.parameters()]) ) ) for model in wrapped.models: assert "cuda" in next( iter(set([param.device.type for param in model.parameters()])) ) else: pass def test_per_sample_grads(): torch.manual_seed(42) data = torch.randn(2, 1, 10) torch.manual_seed(42) wrapped = PerSampleGradientWrapper(MiniModel(), 2) torch.manual_seed(42) model = MiniModel() # single copy output_single = model(data) output_wrapped = wrapped(data) loss_single = output_single.mean() loss_wrapped = output_wrapped.mean() loss_single.backward() loss_wrapped.backward() wrapped.calculate_per_sample_gradients() single_grads = torch.cat([param.grad.flatten() for param in model.parameters()]) accumulated_grads = torch.cat( [ param.accumulated_gradients.sum(dim=0).flatten() for param in wrapped.wrapped_model.parameters() ] ) assert torch.allclose(single_grads, accumulated_grads) def test_per_sample_grads_transfer_learning(): class MiniModel(torch.nn.Module): def __init__(self): super().__init__() self.lin = torch.nn.Linear(10, 1) list(self.lin.parameters())[0].requires_grad_(False) def forward(self, x): return self.lin(x) "One model parameter does not requires_grad" torch.manual_seed(42) data = torch.randn(2, 1, 10) torch.manual_seed(42) wrapped = PerSampleGradientWrapper(MiniModel(), 2) torch.manual_seed(42) model = MiniModel() # single copy output_single = model(data) output_wrapped = wrapped(data) loss_single = output_single.mean() loss_wrapped = output_wrapped.mean() loss_single.backward() loss_wrapped.backward() wrapped.calculate_per_sample_gradients() single_grads = torch.cat( [param.grad.flatten() for param in model.parameters() if param.requires_grad] ) accumulated_grads = torch.cat( [ param.accumulated_gradients.sum(dim=0).flatten() for param in wrapped.wrapped_model.parameters() if hasattr(param, "accumulated_gradients") ] ) assert torch.allclose(single_grads, accumulated_grads)

29.096

88

0.636239

420

3,637

5.311905

0.207143

0.028687

0.035858

0.128642

0.753922

0.696549

0.667862

0.626625

0.600628

0

0.01582

0.252681

3,637

125

89

29.096

0.805004

0.006324

0

0.596154

0

0.023256

0.005814

0

0.067308

1

0.105769

false

0.009615

0.028846

0.019231

0.173077

0

null

0

1

0

null

0

1

da1ae3572abdad23c9e302bb355fe093cb9ac8e8

1,981

py

Python

graphid/util/util_grabdata.py

Erotemic/graphid

5d04c2eec609f135464a921ba03d9578fa6e22fd

[ "Apache-2.0" ]

4

2019-03-04T02:49:26.000Z

2021-10-06T00:51:13.000Z

graphid/util/util_grabdata.py

Erotemic/graphid

5d04c2eec609f135464a921ba03d9578fa6e22fd

[ "Apache-2.0" ]

1

2019-02-15T23:42:26.000Z

graphid/util/util_grabdata.py

Erotemic/graphid

5d04c2eec609f135464a921ba03d9578fa6e22fd

[ "Apache-2.0" ]

null

import ubelt as ub from os.path import exists # NOQA TESTIMG_URL_DICT = { 'astro.png' : 'https://i.imgur.com/KXhKM72.png', # Use instead of 'carl.jpg' : 'http://i.imgur.com/flTHWFD.jpg', 'grace.jpg' : 'http://i.imgur.com/rgQyu7r.jpg', 'jeff.png' : 'http://i.imgur.com/l00rECD.png', 'ada2.jpg' : 'http://i.imgur.com/zHOpTCb.jpg', 'ada.jpg' : 'http://i.imgur.com/iXNf4Me.jpg', 'easy1.png' : 'http://i.imgur.com/Qqd0VNq.png', 'easy2.png' : 'http://i.imgur.com/BDP8MIu.png', 'easy3.png' : 'http://i.imgur.com/zBcm5mS.png', 'hard3.png' : 'http://i.imgur.com/ST91yBf.png', 'zebra.png' : 'http://i.imgur.com/58hbGcd.png', 'star.png' : 'http://i.imgur.com/d2FHuIU.png', 'patsy.jpg' : 'http://i.imgur.com/C1lNRfT.jpg', } def grab_test_imgpath(key='astro.png', allow_external=True, verbose=True): """ Gets paths to standard / fun test images. Downloads them if they dont exits Args: key (str): one of the standard test images, e.g. astro.png, carl.jpg, ... allow_external (bool): if True you can specify existing fpaths Returns: str: testimg_fpath - filepath to the downloaded or cached test image. Example: >>> testimg_fpath = grab_test_imgpath('carl.jpg') >>> assert exists(testimg_fpath) """ if allow_external and key not in TESTIMG_URL_DICT: testimg_fpath = key if not exists(testimg_fpath): raise AssertionError( 'testimg_fpath={!r} not found did you mean on of {!r}' % ( testimg_fpath, sorted(TESTIMG_URL_DICT.keys()))) else: testimg_fname = key testimg_url = TESTIMG_URL_DICT[key] testimg_fpath = ub.grabdata(testimg_url, fname=testimg_fname, verbose=verbose) return testimg_fpath if __name__ == '__main__': """ CommandLine: python -m graphid.util.util_grabdata all """ import xdoctest xdoctest.doctest_module(__file__)

34.754386

86

0.627461

273

1,981

4.399267

0.432234

0.064946

0.097419

0.129892

0.159867

0

0.01297

0.221605

1,981

56

87

35.375

0.765888

0.218576

0

0.40268

0

0.03125

1

0.03125

false

0

0.09375

0

0.15625

0

null

0

null

0

1

0

da1b4387561fab9dc87a8b4f0a9f01c7e63f73be

308

py

Python

pyschieber/deck.py

Murthy10/pyschieber

f9db28c9553b8f321f6ed71cff04eff7879af5f6

[ "MIT" ]

5

2018-01-17T08:11:14.000Z

2018-11-27T11:37:15.000Z

pyschieber/deck.py

Murthy10/pyschieber

f9db28c9553b8f321f6ed71cff04eff7879af5f6

[ "MIT" ]

4

2018-05-09T08:41:05.000Z

2018-11-16T08:07:39.000Z

pyschieber/deck.py

Murthy10/pyschieber

f9db28c9553b8f321f6ed71cff04eff7879af5f6

[ "MIT" ]

3

2018-04-20T07:39:30.000Z

2018-11-10T12:44:08.000Z

from pyschieber.suit import Suit from pyschieber.card import Card class Deck: def __init__(self): self.cards = [] for suit in Suit: self.cards += [Card(suit=suit, value=i) for i in range(6, 15)] def __str__(self): return str([str(card) for card in self.cards])

23.692308

74

0.62013

46

308

3.978261

0.434783

0.147541

0

0.013333

0.269481

308

12

75

25.666667

0.8

0

1

0.222222

false

0

0.222222

0.111111

0.666667

0

null

0

null

0

1

0

1

0

3

da1cd997565c598625d3fbc3be2100124fc27c2c

21,915

py

Python

multipy/flux.py

kamilazdybal/multipy

ebdcddb63bfb1cd647ca99bbf9002b04a9b50ed9

[ "MIT" ]

null

multipy/flux.py

kamilazdybal/multipy

ebdcddb63bfb1cd647ca99bbf9002b04a9b50ed9

[ "MIT" ]

null

multipy/flux.py

kamilazdybal/multipy

ebdcddb63bfb1cd647ca99bbf9002b04a9b50ed9

[ "MIT" ]

null

"""multipy: Python library for multicomponent mass transfer""" __author__ = "James C. Sutherland, Kamila Zdybal" __copyright__ = "Copyright (c) 2022, James C. Sutherland, Kamila Zdybal" __license__ = "MIT" __version__ = "1.0.0" __maintainer__ = ["Kamila Zdybal"] __email__ = ["kamilazdybal@gmail.com"] __status__ = "Production" import numpy as np import pandas as pd import random import copy import scipy import multipy import warnings gas_constant = 8.31446261815324 ################################################################################ ################################################################################ #### #### Class: Flux #### ################################################################################ ################################################################################ class Flux: """ Supports computing and storing fluxes. This class assumes that the species velocities, :math:`\\mathbf{u}_i`, are known. Diffusive fluxes: - mass diffusive flux relative to a mass-averaged velocity, :math:`\mathbf{j}_i` - mass diffusive flux relative to a molar-averaged velocity, :math:`\mathbf{j}_i^u` - molar diffusive flux relative to a mass-averaged velocity, :math:`\mathbf{J}_i^v` - molar diffusive flux relative to a molar-averaged velocity, :math:`\mathbf{J}_i` :param species_velocities: vector ``numpy.ndarray`` specifying the species velocities :math:`\mathbf{u}_i` in :math:`[m/s]`. It should be of size ``(n_species,n_observations)``. **Getters:** - **get_species_velocities** - **get_diffusive_molar_molar** (is set to ``None`` at class init) - **get_diffusive_molar_mass** (is set to ``None`` at class init) - **get_diffusive_mass_molar** (is set to ``None`` at class init) - **get_diffusive_mass_mass** (is set to ``None`` at class init) **Setters:** - **set_species_velocities** - **set_diffusive_molar_molar** (is set to ``None`` at class init) - **set_diffusive_molar_mass** (is set to ``None`` at class init) - **set_diffusive_mass_molar** (is set to ``None`` at class init) - **set_diffusive_mass_mass** (is set to ``None`` at class init) """ # -------------------------------------------------------------------------- def __init__(self, species_velocities): if not isinstance(species_velocities, np.ndarray): raise ValueError("Parameter `species_velocities` has to be of type `numpy.ndarray`.") try: (n_species, n_observations) = np.shape(species_velocities) except: raise ValueError("Parameter `species_velocities` has to be a matrix.") if n_species < 2: raise ValueError("Parameter `species_velocities` has to have at least two species.") self.__species_velocities = species_velocities self.__velocity = multipy.Velocity(self.get_species_velocities) self.__diffusive_molar_molar = None self.__diffusive_molar_mass = None self.__diffusive_mass_molar = None self.__diffusive_mass_mass = None @property def get_species_velocities(self): return self.__species_velocities @property def get_diffusive_molar_molar(self): return self.__diffusive_molar_molar @property def get_diffusive_molar_mass(self): return self.__diffusive_molar_mass @property def get_diffusive_mass_molar(self): return self.__diffusive_mass_molar @property def get_diffusive_mass_mass(self): return self.__diffusive_mass_mass @get_species_velocities.setter def set_species_velocities(self, new_species_velocities): if new_species_velocities is not None: if not isinstance(new_species_velocities, np.ndarray): raise ValueError("Parameter `species_velocities` has to be of type `numpy.ndarray`.") try: (n_species, n_observations) = np.shape(new_species_velocities) except: raise ValueError("Parameter `species_velocities` has to be a matrix.") self.__species_velocities = new_species_velocities @get_diffusive_molar_molar.setter def set_diffusive_molar_molar(self, new_diffusive_molar_molar): if new_diffusive_molar_molar is not None: if not isinstance(new_diffusive_molar_molar, np.ndarray): raise ValueError("Parameter `diffusive_molar_molar` has to be of type `numpy.ndarray`.") try: (n_species, n_observations) = np.shape(new_diffusive_molar_molar) except: raise ValueError("Parameter `diffusive_molar_molar` has to be a matrix.") self.__diffusive_molar_molar = new_diffusive_molar_molar @get_diffusive_molar_mass.setter def set_diffusive_molar_mass(self, new_diffusive_molar_mass): if new_diffusive_molar_mass is not None: if not isinstance(new_diffusive_molar_mass, np.ndarray): raise ValueError("Parameter `diffusive_molar_mass` has to be of type `numpy.ndarray`.") try: (n_species, n_observations) = np.shape(new_diffusive_molar_mass) except: raise ValueError("Parameter `diffusive_molar_mass` has to be a matrix.") self.__diffusive_molar_mass = new_diffusive_molar_mass @get_diffusive_mass_molar.setter def set_diffusive_mass_molar(self, new_diffusive_mass_molar): if new_diffusive_mass_molar is not None: if not isinstance(new_diffusive_mass_molar, np.ndarray): raise ValueError("Parameter `diffusive_mass_molar` has to be of type `numpy.ndarray`.") try: (n_species, n_observations) = np.shape(new_diffusive_mass_molar) except: raise ValueError("Parameter `diffusive_mass_molar` has to be a matrix.") self.__diffusive_mass_molar = new_diffusive_mass_molar @get_diffusive_mass_mass.setter def set_diffusive_mass_mass(self, new_diffusive_mass_mass): if new_diffusive_mass_mass is not None: if not isinstance(new_diffusive_mass_mass, np.ndarray): raise ValueError("Parameter `diffusive_mass_mass` has to be of type `numpy.ndarray`.") try: (n_species, n_observations) = np.shape(new_diffusive_mass_mass) except: raise ValueError("Parameter `diffusive_mass_mass` has to be a matrix.") self.__diffusive_mass_mass = new_diffusive_mass_mass # -------------------------------------------------------------------------- def plot_diffusive_flux(self, species_names=None, colors=None, figsize=(10,5), filename=None): """ Plots the computed diffusive fluxes. **Example:** .. image:: ../images/stefan-tube-diffusive-flux-molar-diff-molar-avg.svg :width: 400 :param species_names: (optional) ``list`` of ``str`` specifying the species names. :param colors: (optional) ``list`` of ``str`` specifying the plotting colors for each species. Example: ``colors=['#C7254E', '#BBBBBB', '#008CBA']``. :param figsize: (optional) ``tuple`` specifying the figure size. :param filename: (optional) ``str`` specifying the filename. If set to ``None``, plot will not be saved to a file. """ if filename is not None: path = False if filename[0:2] == '..': __filename = filename[2::] path = True else: __filename = filename __base = __filename.split('.')[0] __extension = __filename.split('.')[1] if path: __filename = '..' + __base else: __filename = __base if self.get_diffusive_molar_molar is not None: if filename is not None: plt = multipy.plot.plot_1d_diffusive_flux(self.get_diffusive_molar_molar, flux='molar', velocity='molar', species_names=species_names, colors=colors, figsize=figsize, filename=__filename + '-molar-diff-molar-avg.' + __extension) else: plt = multipy.plot.plot_1d_diffusive_flux(self.get_diffusive_molar_molar, flux='molar', velocity='molar', species_names=species_names, colors=colors, figsize=figsize, filename=None) if self.get_diffusive_molar_mass is not None: if filename is not None: plt = multipy.plot.plot_1d_diffusive_flux(self.get_diffusive_molar_mass, flux='molar', velocity='mass', species_names=species_names, colors=colors, figsize=figsize, filename=__filename + '-molar-diff-mass-avg.' + __extension) else: plt = multipy.plot.plot_1d_diffusive_flux(self.get_diffusive_molar_mass, flux='molar', velocity='mass', species_names=species_names, colors=colors, figsize=figsize, filename=None) if self.get_diffusive_mass_molar is not None: if filename is not None: plt = multipy.plot.plot_1d_diffusive_flux(self.get_diffusive_mass_molar, flux='mass', velocity='molar', species_names=species_names, colors=colors, figsize=figsize, filename=__filename + '-mass-diff-molar-avg.' + __extension) else: plt = multipy.plot.plot_1d_diffusive_flux(self.get_diffusive_mass_molar, flux='mass', velocity='molar', species_names=species_names, colors=colors, figsize=figsize, filename=None) if self.get_diffusive_mass_mass is not None: if filename is not None: plt = multipy.plot.plot_1d_diffusive_flux(self.get_diffusive_mass_mass, flux='mass', velocity='mass', species_names=species_names, colors=colors, figsize=figsize, filename=__filename + '-mass-diff-mass-avg.' + __extension) else: plt = multipy.plot.plot_1d_diffusive_flux(self.get_diffusive_mass_mass, flux='mass', velocity='mass', species_names=species_names, colors=colors, figsize=figsize, filename=None) # -------------------------------------------------------------------------- def diffusive_molar_molar(self, species_mole_fractions, species_molar_densities): """ Computes the molar diffusive flux relative to a molar-averaged velocity: .. math:: \mathbf{J}_i = c_i \mathbf{u}_i + c_i \mathbf{u} :param species_mole_fractions: scalar ``numpy.ndarray`` specifying the species mole fractions, :math:`X_i`, in :math:`[-]`. It should be of size ``(n_species,n_observations)``. :param species_molar_densities: scalar ``numpy.ndarray`` specifying the molar densities of species, :math:`c_i`, in :math:`[mole/m^3]`. It should be of size ``(n_species,n_observations)``. :return: - **diffusive_flux** - vector ``numpy.ndarray`` of molar diffusive fluxes relative to a molar-averaged velocity :math:`\mathbf{J}_i` in :math:`[mole/(m^2s)]`. It has size ``(n_species,n_observations)``. """ if not isinstance(species_mole_fractions, np.ndarray): raise ValueError("Parameter `species_mole_fractions` has to be of type `numpy.ndarray`.") try: (n_species_1, n_observations_1) = np.shape(species_mole_fractions) except: raise ValueError("Parameter `species_mole_fractions` has to be a matrix.") if not isinstance(species_molar_densities, np.ndarray): raise ValueError("Parameter `species_molar_densities` has to be of type `numpy.ndarray`.") try: (n_species_2, n_observations_2) = np.shape(species_molar_densities) except: raise ValueError("Parameter `species_molar_densities` has to be a matrix.") if n_observations_1 != n_observations_2: raise ValueError("Parameters `species_mole_fractions` and `species_molar_densities` have different number of observations `n_observations`.") if n_species_1 != n_species_2: raise ValueError("Parameters `species_mole_fractions` and `species_molar_densities` have different number of species `n_species`.") (n_species, n_observations) = np.shape(self.get_species_velocities) if n_observations != n_observations_1: raise ValueError("Parameters `species_mole_fractions`, `species_molar_densities` and `species_velocities` have different number of observations `n_observations`.") if n_species != n_species_1: raise ValueError("Parameters `species_mole_fractions`, `species_molar_densities` and `species_velocities` have different number of species `n_species`.") molar_averaged_velocity = self.__velocity.molar_averaged(species_mole_fractions) diffusive_flux = np.multiply(species_molar_densities, self.get_species_velocities) - np.multiply(species_molar_densities, molar_averaged_velocity) self.__diffusive_molar_molar = diffusive_flux return diffusive_flux # -------------------------------------------------------------------------- def diffusive_molar_mass(self, species_mass_fractions, species_molar_densities): """ Computes the molar diffusive flux relative to a mass-averaged velocity: .. math:: \mathbf{J}_i^v = c_i \mathbf{u}_i + c_i \mathbf{v} :param species_mass_fractions: scalar ``numpy.ndarray`` specifying the species mass fractions, :math:`Y_i`, in :math:`[-]`. It should be of size ``(n_species,n_observations)``. :param species_molar_densities: scalar ``numpy.ndarray`` specifying the species molar densities :math:`c_i` in :math:`[mole/m^3]`. It should be of size ``(n_species,n_observations)``. :return: - **diffusive_flux** - vector ``numpy.ndarray`` of molar diffusive fluxes relative to a mass-averaged velocity :math:`\mathbf{J}_i^v` in :math:`[mole/(m^2s)]`. It has size ``(n_species,n_observations)``. """ if not isinstance(species_mass_fractions, np.ndarray): raise ValueError("Parameter `species_mass_fractions` has to be of type `numpy.ndarray`.") try: (n_species_1, n_observations_1) = np.shape(species_mass_fractions) except: raise ValueError("Parameter `species_mass_fractions` has to be a matrix.") if not isinstance(species_molar_densities, np.ndarray): raise ValueError("Parameter `species_molar_densities` has to be of type `numpy.ndarray`.") try: (n_species_2, n_observations_2) = np.shape(species_molar_densities) except: raise ValueError("Parameter `species_molar_densities` has to be a matrix.") if n_observations_1 != n_observations_2: raise ValueError("Parameters `species_mass_fractions` and `species_molar_densities` have different number of observations `n_observations`.") if n_species_1 != n_species_2: raise ValueError("Parameters `species_mass_fractions` and `species_molar_densities` have different number of species `n_species`.") (n_species, n_observations) = np.shape(self.get_species_velocities) if n_observations != n_observations_1: raise ValueError("Parameters `species_mass_fractions`, `species_molar_densities` and `species_velocities` have different number of observations `n_observations`.") if n_species != n_species_1: raise ValueError("Parameters `species_mass_fractions`, `species_molar_densities` and `species_velocities` have different number of species `n_species`.") mass_averaged_velocity = self.__velocity.mass_averaged(species_mass_fractions) diffusive_flux = np.multiply(species_molar_densities, self.get_species_velocities) - np.multiply(species_molar_densities, mass_averaged_velocity) self.__diffusive_molar_mass = diffusive_flux return diffusive_flux # -------------------------------------------------------------------------- def diffusive_mass_molar(self, species_mole_fractions, species_mass_densities): """ Computes the mass diffusive flux relative to a molar-averaged velocity: .. math:: \mathbf{j}_i^u = \\rho_i \mathbf{u}_i + \\rho_i \mathbf{u} :param species_mole_fractions: scalar ``numpy.ndarray`` specifying the species mole fractions :math:`X_i` in :math:`[-]`. It should be of size ``(n_species,n_observations)``. :param species_mass_densities: scalar ``numpy.ndarray`` specifying the species mass densities :math:`\mathbf{\\rho}_i` in :math:`[kg/m^3]`. It should be of size ``(n_species,n_observations)``. :return: - **diffusive_flux** - vector ``numpy.ndarray`` of mass diffusive fluxes relative to a molar-averaged velocity :math:`\mathbf{j}_i^u` in :math:`[kg/(m^2s)]`. It has size ``(n_species,n_observations)``. """ if not isinstance(species_mole_fractions, np.ndarray): raise ValueError("Parameter `species_mole_fractions` has to be of type `numpy.ndarray`.") try: (n_species_1, n_observations_1) = np.shape(species_mole_fractions) except: raise ValueError("Parameter `species_mole_fractions` has to be a matrix.") if not isinstance(species_mass_densities, np.ndarray): raise ValueError("Parameter `species_mass_densities` has to be of type `numpy.ndarray`.") try: (n_species_2, n_observations_2) = np.shape(species_mass_densities) except: raise ValueError("Parameter `species_mass_densities` has to be a matrix.") if n_observations_1 != n_observations_2: raise ValueError("Parameters `species_mole_fractions` and `species_mass_densities` have different number of observations `n_observations`.") if n_species_1 != n_species_2: raise ValueError("Parameters `species_mole_fractions` and `species_mass_densities` have different number of species `n_species`.") (n_species, n_observations) = np.shape(self.get_species_velocities) if n_observations != n_observations_1: raise ValueError("Parameters `species_mole_fractions`, `species_mass_densities` and `species_velocities` have different number of observations `n_observations`.") if n_species != n_species_1: raise ValueError("Parameters `species_mole_fractions`, `species_mass_densities` and `species_velocities` have different number of species `n_species`.") molar_averaged_velocity = self.__velocity.molar_averaged(species_mole_fractions) diffusive_flux = np.multiply(species_mass_densities, self.get_species_velocities) - np.multiply(species_mass_densities, molar_averaged_velocity) self.__diffusive_mass_molar = diffusive_flux return diffusive_flux # -------------------------------------------------------------------------- def diffusive_mass_mass(self, species_mass_fractions, species_mass_densities): """ Computes the mass diffusive flux relative to a mass-averaged velocity: .. math:: \mathbf{j}_i = \\rho_i \mathbf{u}_i + \\rho_i \mathbf{v} :param species_mass_fractions: scalar ``numpy.ndarray`` specifying the species mass fractions :math:`Y_i` in :math:`[-]`. It should be of size ``(n_species, n_observations)``. :param species_mass_densities: scalar ``numpy.ndarray`` specifying the species mass densities :math:`\mathbf{\\rho}_i` in :math:`[kg/m^3]`. It should be of size ``(n_species, n_observations)``. :return: - **diffusive_flux** - vector ``numpy.ndarray`` of mass diffusive fluxes relative to a mass-averaged velocity :math:`\mathbf{j}_i` in :math:`[kg/(m^2s)]`. It has size ``(n_species, n_observations)``. """ if not isinstance(species_mass_fractions, np.ndarray): raise ValueError("Parameter `species_mass_fractions` has to be of type `numpy.ndarray`.") try: (n_species_1, n_observations_1) = np.shape(species_mass_fractions) except: raise ValueError("Parameter `species_mass_fractions` has to be a matrix.") if not isinstance(species_mass_densities, np.ndarray): raise ValueError("Parameter `species_mass_densities` has to be of type `numpy.ndarray`.") try: (n_species_2, n_observations_2) = np.shape(species_mass_densities) except: raise ValueError("Parameter `species_mass_densities` has to be a matrix.") if n_observations_1 != n_observations_2: raise ValueError("Parameters `species_mass_fractions` and `species_mass_densities` have different number of observations `n_observations`.") if n_species_1 != n_species_2: raise ValueError("Parameters `species_mass_fractions` and `species_mass_densities` have different number of species `n_species`.") (n_species, n_observations) = np.shape(self.get_species_velocities) if n_observations != n_observations_1: raise ValueError("Parameters `species_mass_fractions`, `species_mass_densities` and `species_velocities` have different number of observations `n_observations`.") if n_species != n_species_1: raise ValueError("Parameters `species_mass_fractions`, `species_mass_densities` and `species_velocities` have different number of species `n_species`.") mass_averaged_velocity = self.__velocity.mass_averaged(species_mass_fractions) diffusive_flux = np.multiply(species_mass_densities, self.get_species_velocities) - np.multiply(species_mass_densities, mass_averaged_velocity) self.__diffusive_mass_mass = diffusive_flux return diffusive_flux # --------------------------------------------------------------------------

47.745098

244

0.657906

2,632

21,915

5.159954

0.06421

0.032987

0.020543

0.035564

0.869008

0.83256

0.801856

0.78168

0.759591

0.718136

0

0.005602

0.209902

21,915

458

245

47.849345

0.778747

0.244809

0

0.461538

0

0.261039

0.091635

0

1

0.068376

false

0

0.029915

0.021368

0.141026

0

null

0

1

0

null

0

6

da1d6a02eeb844897d0b4f2d15640a391973f96d

1,971

py

Python

ENotePadAlgorithm/strEncrypt/Morse.py

xioacd99/EnhancedNotePad

b95da1c4d957061ad60015f3b9ab5c445b5a1bc4

[ "MIT" ]

null

ENotePadAlgorithm/strEncrypt/Morse.py

xioacd99/EnhancedNotePad

b95da1c4d957061ad60015f3b9ab5c445b5a1bc4

[ "MIT" ]

null

ENotePadAlgorithm/strEncrypt/Morse.py

xioacd99/EnhancedNotePad

b95da1c4d957061ad60015f3b9ab5c445b5a1bc4

[ "MIT" ]

null

# encode时会将非ANSII字符变为空格 # decode时会跳过非ANSII字符 # 摩斯电码加密的字符只有字符，数字，标点，不区分大小写 class MorseCoder: def __init__(self): self.encode_alphabet = {"A": ".-", "B": "-...", "C": "-.-.", "D": "-..", # 加密对照表 "E": ".", "F": "..-.", "G": "--.", "H": "....", "I": "..", "J": ".---", "K": "-.-", "L": ".-..", "M": "--", "N": "-.", "O": "---", "P": ".--.", "Q": "--.-", "R": ".-.", "S": "...", "T": "-", "U": "..-", "V": "...-", "W": ".--", "X": "-..-", "Y": "-.--", "Z": "--..", "1": ".---", "2": "..---", "3": "...--", "4": "....-", "5": ".....", "6": "-....", "7": "--...", "8": "---..", "9": "----.", "0": "-----", "(": ".--.-", "-": "-....-", "?": "..--..", "/": "-..-.", ".": ".-.-.-", "@": ".--.-." } def encode(self, plaintext): """Encode AscII chars in plaintext to morse code""" charList = list(plaintext.upper()) morsecodeList = \ [self.encode_alphabet[char] if char in self.encode_alphabet.keys() else " " for char in charList] return " ".join(morsecodeList) def decode(self, morsecode): morsecodeList = morsecode.split(" ") charList = \ [self.decode_alphabet[char] if char in self.decode_alphabet.keys() else char for char in morsecodeList] return "".join(charList) def get_encode_alphabet(self): return self.encode_alphabet def get_decode_alphabet(self): return self.decode_alphabet def strEncrypt(self, msg): return self.encode(msg) if __name__ == '__main__': test = MorseCoder() result = test.strEncrypt('ABCD12345678') print(result)

41.0625

115

0.367326

152

1,971

4.611842

0.526316

0.071327

0.10271

0.051355

0.068474

0

0.014377

0.364789

1,971

47

116

41.93617

0.545527

0.060883

0

0.124864

0

1

0.171429

false

0

0.085714

0.342857

0.028571

0

null

0

null

0

1

0

da1fedbc0ae28396d7b17794e490d8e258826958

4,800

py

Python

Yolov3_deepsort/Badminton_Service/player.py

Haosam/BadmintonAI

4a1e837109cd279fb7480b90b31003c259e063cf

[ "Apache-2.0" ]

null

Yolov3_deepsort/Badminton_Service/player.py

Haosam/BadmintonAI

4a1e837109cd279fb7480b90b31003c259e063cf

[ "Apache-2.0" ]

null

Yolov3_deepsort/Badminton_Service/player.py

Haosam/BadmintonAI

4a1e837109cd279fb7480b90b31003c259e063cf

[ "Apache-2.0" ]

null

from tkinter import * import cv2 # Global Variables, can be translated to database if it becomes production lcw = "Lee Chong Wei" swh = "Son Wan Ho" lyd = "Lee Yong Dae" kgj = "Kim Gi Jung" ksh = "Ko Sung Hyun" yys = "Yo Yeon Seong" csg = "Choi Sol Gyu" wcl = "Wang Chi-Lin" chl = "Chen Hung-Lin" lcw_height = 1.72 swh_height = 1.77 lyd_height = 1.76 kkj_height = 1.79 ksh_height = 1.79 yys_height = 1.81 csg_height = 1.81 wcl_height = 1.86 chl_height = 1.77 ################################################################################ player_names1 = ["Player 1",lcw,swh,lyd,kgj,ksh,yys,csg,wcl,chl] player_names2 = ["Player 2",lcw,swh,lyd,kgj,ksh,yys,csg,wcl,chl] player_names3 = ["Player 3",lcw,swh,lyd,kgj,ksh,yys,csg,wcl,chl] player_names4 = ["Player 4",lcw,swh,lyd,kgj,ksh,yys,csg,wcl,chl] player_heights = [lcw_height,swh_height,lyd_height,kkj_height,ksh_height,yys_height,csg_height] ################################################################################# def player_main(): print("If no player is present, please at least select None") def callback1(selection): global name_1, height_1 name_1 = selection height_1 = playercheck(selection) return(name_1, height_1) def callback2(selection): global name_2, height_2 name_2 = selection height_2 = playercheck(selection) return(name_1, height_1) def callback3(selection): global name_3, height_3 name_3 = selection height_3 = playercheck(selection) return(name_3, height_3) def callback4(selection): global name_4, height_4 name_4 = selection height_4 = playercheck(selection) return(name_4, height_4) def playercheck(selection): if selection == "Lee Chong Wei": return lcw_height elif selection == "Son Wan Ho": return swh_height elif selection == "Lee Yong Dae": return swh_height elif selection == "Kim Gi Jung": return kkj_height elif selection == "Ko Sung Hyun": return ksh_height elif selection == "Yo Yeon Seong": return yys_height elif selection == "Choi Sol Gyu": return csg_height elif selection == "Wang Chi-Lin": return wcl_height elif selection == "Chen Hung-Lin": return chl_height elif "None" or "Select Player" or "Player 1" or "Player 2" or "Player 3" or "Player 4": return 1 else: return 1 def playerselection(): window = Tk() window.geometry('400x400') window.title("Player Selection") label1 = Label(window, text="Player 1: ") label1.config(width=10, font=('Helvetica', 10)) label2 = Label(window, text="Player 2: ") label2.config(width=10, font=('Helvetica', 10)) label3 = Label(window, text="Player 3: ") label3.config(width=10, font=('Helvetica', 10)) label4 = Label(window, text="Player 4: ") label4.config(width=10, font=('Helvetica', 10)) label5 = Label(window, text="If no player is present,") label6 = Label(window, text=", please at least select None") label1.grid(row=0,column=0) label2.grid(row=1,column=0) label3.grid(row=2,column=0) label4.grid(row=3,column=0) label5.grid(row=8,column=0) label6.grid(row=8,column=1) clicked1 = StringVar() clicked1.set("Select Player") clicked2 = StringVar() clicked2.set("Select Player") clicked3 = StringVar() clicked3.set("Select Player") clicked4 = StringVar() clicked4.set("Select Player") drop1 = OptionMenu(window, clicked1, *player_names1, command=callback1) drop1.config(width=20, font=('Helvetica', 10)) drop2 = OptionMenu(window, clicked2, *player_names2, command=callback2) drop2.config(width=20, font=('Helvetica', 10)) drop3 = OptionMenu(window, clicked3, *player_names3, command=callback3) drop3.config(width=20, font=('Helvetica', 10)) drop4 = OptionMenu(window, clicked4, *player_names4, command=callback4) drop4.config(width=20, font=('Helvetica', 10)) drop1.grid(row=0,column=1) drop2.grid(row=1,column=1) drop3.grid(row=2,column=1) drop4.grid(row=3,column=1) labelTest1 = Label(text="", font=('Helvetica', 8), fg='red') labelTest1.grid(row=4,column=1) labelTest2 = Label(text="", font=('Helvetica', 8), fg='red') labelTest2.grid(row=5,column=1) labelTest3 = Label(text="", font=('Helvetica', 8 ), fg='red') labelTest3.grid(row=6,column=1) labelTest4 = Label(text="", font=('Helvetica', 8), fg='red') labelTest4.grid(row=7,column=1) window.mainloop() playerselection() return(name_1,height_1,name_2,height_2,name_3,height_3,name_4,height_4) # print(name_1,height_1,",", name_2,height_2,",",name_3,height_3,",",name_4,height_4) if __name__ == "__main__": # stuff only to run when not called via 'import' here player_main() print(name_1) print(name_2) print(name_3) print(name_4)

33.103448

96

0.660417

692

4,800

4.453757

0.208092

0.034069

0.049319

0.019468

0.27255

0.209604

0.136924

0.100584

0.073978

0

0.055221

0.17

4,800

145

97

33.103448

0.718373

0.043333

0

0.047244

0

0.15056

0

1

0.055118

false

0

0.015748

0

0.15748

0.03937

0

null

0

null

0

1

0

da2374aced1b72eebcc58d79ed22779475feb324

4,749

py

Python

scripts/install.py

discord-package-bot/discord-package-bot

109603c57a668d75f6939e3c97aae72f2691640e

[ "MIT" ]

1

2021-07-12T05:56:00.000Z

scripts/install.py

discord-package-bot/discord-package-bot

109603c57a668d75f6939e3c97aae72f2691640e

[ "MIT" ]

null

scripts/install.py

discord-package-bot/discord-package-bot

109603c57a668d75f6939e3c97aae72f2691640e

[ "MIT" ]

null

""" syntax: | install <パッケージ> install update:<パッケージ> install file:<ファイル> syntax_description: | パッケージ: インストールするパッケージ。update:をつけると、パッケージが更新されます。ファイル: エクスポートしたファイルのパス。 --- パッケージをインストールします。 """ import os import re import requests import shlex import shutil import subprocess import sys import yaml import zipfile from colorama import Fore, Style # , Back from .utils import command, token def get_info(repo): resp = None repo_data = requests.get( f"https://api.github.com/repos/{repo}", headers={"authorization": token.github_token}, ) if repo_data.status_code != 200: print(Fore.RED + f"パッケージ{repo}が見付かりませんでした。" + Fore.RESET) return False resp = requests.get(f"https://raw.githubusercontent.com/{repo}/dpb/dpb.yml") if resp.status_code == 200: branch = "dpb" else: branch = repo_data.json()["default_branch"] resp = requests.get( f"https://raw.githubusercontent.com/{repo}/{branch}/dpb.yml" ) if resp.status_code != 200: print(Fore.RED + f"{repo}の情報を取得できませんでした。" + Fore.RESET) return False print(Fore.GREEN + f"{repo}の情報を取得しました。" + Fore.RESET) info = yaml.safe_load(resp.text) print(Fore.CYAN + f"{repo}の情報" + Fore.RESET) print(f"名前: {info['name']}") print(f"作者: {repo.split('/')[0]}") info["branch"] = branch return info def download_repo(repo, info): if os.path.exists("./savedata/delete-install-tmp"): try: subprocess.run(shlex.split("rm -rf ./.install-tmp")) except PermissionError: print(Fore.RED + "展開先が使用中のため、インストール出来ませんでした。" + Fore.RESET) sys.exit(1) except FileNotFoundError: os.unlink("./savedata/delete-install-tmp") else: os.unlink("./savedata/delete-install-tmp") print(Fore.LIGHTBLACK_EX + f"{info['name']}をダウンロードしています..." + Fore.RESET) with requests.get( f"https://github.com/{repo}/archive/refs/heads/{info['branch']}.zip", stream=True, ) as r: with open(".install-tmp.zip", "wb") as f: for chunk in r.iter_content(chunk_size=8192): f.write(chunk) with zipfile.ZipFile(".install-tmp.zip") as existing_zip: existing_zip.extractall(".install-tmp") print(Fore.LIGHTBLACK_EX + "インストールしています..." + Fore.RESET) zip_dir = repo.split("/")[1] + "-" + info["branch"] shutil.copytree(f"./.install-tmp/{zip_dir}", f"./packages/{repo.replace('/', '@')}") if info["requirements"] is not None and os.path.exists( f"./.install-tmp/{zip_dir}/" + (info.get("requirements", None) or "dpb_requirements.txt") ): with open(f"./.install-tmp/{zip_dir}/{info['requirements']}", "r") as f: requirements = re.sub(r"#.*|\n{2,}", "", f.read()) with open("./savedata/package_requirements.txt", "a") as f: f.write(f"#!==={repo}===!\n" + requirements.strip() + "\n") subprocess.run( shlex.split(command.pip + "install -r ./savedata/package_requirements.txt"), stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, ) try: subprocess.run(shlex.split("rm -rf ./.install-tmp .install-tmp.zip")) except PermissionError: with open("./savedata/delete-install-tmp", "w"): pass print(Fore.GREEN + "インストールが完了しました。" + Fore.RESET) def main(): if len(sys.argv) <= 2: repos = input("インストールするパッケージを○○/○○で入力して下さい。") elif sys.argv[2].startswith("file:"): try: os.chdir("..") with open(sys.argv[2][5:]) as f: repos = re.sub(r"#.*|\n{2,}", "", f.read()).replace("\n", " ") os.chdir(".main") except FileNotFoundError: print(Fore.RED + "ファイルが見付かりませんでした。" + Fore.RESET) sys.exit(1) else: repos = " ".join(sys.argv[2:]) for repo in repos.split(): if os.path.exists( f"./packages/{repo.replace('/', '@')}" ) and not repo.startswith("update:"): with open(f"./packages/{repo.replace('/', '@')}/dpb.yml") as f: info = yaml.safe_load(f) print( f"{Fore.RED}パッケージ {Style.BRIGHT}{info['name']}（{repo}）{Style.NORMAL}はすでにインストールされています。{Fore.RESET}\n" f"{Fore.CYAN}アップデートするには {Style.BRIGHT}dpb install update:{repo}{Style.NORMAL} を実行して下さい。{Fore.RESET}" ) continue if repo.startswith("update:"): repo = repo.replace("update:", "") subprocess.run(shlex.split(f"rm -rf ./packages/{repo.replace('/', '@')}")) info = get_info(repo) if info is False: continue download_repo(repo, info)

34.664234

116

0.579912

576

4,749

4.739583

0.28125

0.047619

0.028571

0.024908

0.18315

0.164469

0.106593

0.064469

0

0.006683

0.243841

4,749

136

117

34.919118

0.752437

0.042114

0

0.159292

0

0.017699

0.299934

0.148646

0

1

0.026549

false

0.00885

0.097345

0

0.150442

0.106195

0

null

0

null

0

1

0

da23f0ddb62bb0c0988bd093b73535c31a660639

72

py

Python

plugin/src/test/resources/refactoring/extractmethod/Comment.after.py

consulo/consulo-python

586c3eaee3f9c2cc87fb088dc81fb12ffa4b3a9d

[ "Apache-2.0" ]

null

plugin/src/test/resources/refactoring/extractmethod/Comment.after.py

consulo/consulo-python

586c3eaee3f9c2cc87fb088dc81fb12ffa4b3a9d

[ "Apache-2.0" ]

11

2017-02-27T22:35:32.000Z

2021-12-24T08:07:40.000Z

plugin/src/test/resources/refactoring/extractmethod/Comment.after.py

consulo/consulo-python

586c3eaee3f9c2cc87fb088dc81fb12ffa4b3a9d

[ "Apache-2.0" ]

null

def bar(): print("Hello") #Comment to method def foo(): bar()

9

18

0.555556

10

72

4

0.8

0

0.263889

72

7

19

10.285714

0.754717

0.236111

0

0.092593

0

1

0.5

true

0

0.5

0.25

1

0

null

0

1

0

null

0

1

0

4

da24c7b3d7ea12e45a63e2df57343289b27d952a

1,565

py

Python

rlkeras/utils/memory.py

will-hcau/rlkeras

9cc36b238dae794197fcb8689a5a1ffa1c0a42c0

[ "MIT" ]

null

rlkeras/utils/memory.py

will-hcau/rlkeras

9cc36b238dae794197fcb8689a5a1ffa1c0a42c0

[ "MIT" ]

null

rlkeras/utils/memory.py

will-hcau/rlkeras

9cc36b238dae794197fcb8689a5a1ffa1c0a42c0

[ "MIT" ]

null

from collections import deque import numpy as np import random class RandomReplayBuffer(object): """Experience replay buffer that samples uniformly.""" def __init__(self, buffer_size): self.buffer_size = buffer_size self.buffer = deque(maxlen=buffer_size) def __len__(self): return len(self.buffer) def append(self, state, action, reward, next_state, done): """ Store transition into replay buffer "D" Refering to the DQN paper (S, A, R, S t+1, terminate) should be stored into a buffer with limited size. When hitting the maximum size of buffer, the oldest transition will be discard. """ self.buffer.append((state, action, reward, next_state, done)) def sample(self, batch_size, num_of_step=1): """ Sampling Random sample a minibatch from the replay buffer """ sample_data = [] sample_indices = np.random.random_integers(0, len(self.buffer) - num_of_step, size=batch_size) for s in sample_indices: n_state = [] n_action = [] n_reward = [] n_next_state = [] n_done = [] for n in range(num_of_step): exp = self.buffer[s + n] n_state.append(exp[0]) n_action.append(exp[1]) n_reward.append(exp[2]) n_next_state.append(exp[3]) n_done.append(exp[4]) sample_data.append((n_state, n_action, n_reward, n_next_state, n_done)) return sample_data

28.454545

102

0.600639

207

1,565

4.318841

0.362319

0.0783

0.030201

0.044743

0.145414

0.0783

0

0.007353

0.304792

1,565

55

103

28.454545

0.814338

0.212141

0

1

0.137931

false

0

0.103448

0.034483

0.344828

0

null

0

null

0

1

0

da24d2c86b3410255d8a070349c1d9c6e890f449

6,335

py

Python

PathPlanning/RRTStar/rrt_star.py

cmuehlbacher/PythonRobotics

c66fccc71c681387ff61b59554694b25399ca790

[ "MIT" ]

38

2019-12-08T12:26:04.000Z

2022-03-06T11:29:08.000Z

PathPlanning/RRTStar/rrt_star.py

YoungGer/PythonRobotics

9b8f2bd88a3d516d8deb473693661c1aea59fe68

[ "MIT" ]

null

PathPlanning/RRTStar/rrt_star.py

YoungGer/PythonRobotics

9b8f2bd88a3d516d8deb473693661c1aea59fe68

[ "MIT" ]

15

2020-02-12T15:57:28.000Z

2021-08-28T07:39:18.000Z

""" Path planning Sample Code with RRT* author: Atsushi Sakai(@Atsushi_twi) """ import copy import math import os import sys import matplotlib.pyplot as plt sys.path.append(os.path.dirname(os.path.abspath(__file__)) + "/../RRT/") try: from rrt import RRT except ImportError: raise show_animation = True class RRTStar(RRT): """ Class for RRT Star planning """ class Node: def __init__(self, x, y): self.x = x self.y = y self.cost = 0.0 self.parent = None def __init__(self, start, goal, obstacle_list, rand_area, expand_dis=0.5, goal_sample_rate=20, max_iter=500, connect_circle_dist=50.0 ): super().__init__(start, goal, obstacle_list, rand_area, expand_dis, goal_sample_rate, max_iter) """ Setting Parameter start:Start Position [x,y] goal:Goal Position [x,y] obstacleList:obstacle Positions [[x,y,size],...] randArea:Random Sampling Area [min,max] """ self.connect_circle_dist = connect_circle_dist def planning(self, animation=True, search_until_maxiter=True): """ rrt star path planning animation: flag for animation on or off search_until_maxiter: search until max iteration for path improving or not """ self.node_list = [self.start] for i in range(self.max_iter): rnd = self.get_random_point() nearest_ind = self.get_nearest_list_index(self.node_list, rnd) new_node = self.steer(rnd, self.node_list[nearest_ind]) if self.check_collision(new_node, self.obstacleList): near_inds = self.find_near_nodes(new_node) new_node = self.choose_parent(new_node, near_inds) if new_node: self.node_list.append(new_node) self.rewire(new_node, near_inds) if animation and i % 5 == 0: self.draw_graph(rnd) if not search_until_maxiter and new_node: # check reaching the goal d, _ = self.calc_distance_and_angle(new_node, self.end) if d <= self.expand_dis: return self.generate_final_course(len(self.node_list) - 1) print("reached max iteration") last_index = self.search_best_goal_node() if last_index: return self.generate_final_course(last_index) return None def choose_parent(self, new_node, near_inds): if not near_inds: return None # search nearest cost in near_inds costs = [] for i in near_inds: d, theta = self.calc_distance_and_angle(self.node_list[i], new_node) if self.check_collision_extend(self.node_list[i], theta, d): costs.append(self.node_list[i].cost + d) else: costs.append(float("inf")) # the cost of collision node min_cost = min(costs) if min_cost == float("inf"): print("There is no good path.(min_cost is inf)") return None new_node.cost = min_cost min_ind = near_inds[costs.index(min_cost)] new_node.parent = self.node_list[min_ind] return new_node def search_best_goal_node(self): dist_to_goal_list = [self.calc_dist_to_goal(n.x, n.y) for n in self.node_list] goal_inds = [dist_to_goal_list.index(i) for i in dist_to_goal_list if i <= self.expand_dis] if not goal_inds: return None min_cost = min([self.node_list[i].cost for i in goal_inds]) for i in goal_inds: if self.node_list[i].cost == min_cost: return i return None def find_near_nodes(self, new_node): nnode = len(self.node_list) + 1 r = self.connect_circle_dist * math.sqrt((math.log(nnode) / nnode)) dist_list = [(node.x - new_node.x) ** 2 + (node.y - new_node.y) ** 2 for node in self.node_list] near_inds = [dist_list.index(i) for i in dist_list if i <= r ** 2] return near_inds def rewire(self, new_node, near_inds): for i in near_inds: near_node = self.node_list[i] d, theta = self.calc_distance_and_angle(near_node, new_node) new_cost = new_node.cost + d if near_node.cost > new_cost: if self.check_collision_extend(near_node, theta, d): near_node.parent = new_node near_node.cost = new_cost self.propagate_cost_to_leaves(new_node) def propagate_cost_to_leaves(self, parent_node): for node in self.node_list: if node.parent == parent_node: d, _ = self.calc_distance_and_angle(parent_node, node) node.cost = parent_node.cost + d self.propagate_cost_to_leaves(node) def check_collision_extend(self, near_node, theta, d): tmp_node = copy.deepcopy(near_node) for i in range(int(d / self.expand_dis)): tmp_node.x += self.expand_dis * math.cos(theta) tmp_node.y += self.expand_dis * math.sin(theta) if not self.check_collision(tmp_node, self.obstacleList): return False return True def main(): print("Start " + __file__) # ====Search Path with RRT==== obstacle_list = [ (5, 5, 1), (3, 6, 2), (3, 8, 2), (3, 10, 2), (7, 5, 2), (9, 5, 2) ] # [x,y,size(radius)] # Set Initial parameters rrt = RRTStar(start=[0, 0], goal=[10, 10], rand_area=[-2, 15], obstacle_list=obstacle_list) path = rrt.planning(animation=show_animation, search_until_maxiter=False) if path is None: print("Cannot find path") else: print("found path!!") # Draw final path if show_animation: rrt.draw_graph() plt.plot([x for (x, y) in path], [y for (x, y) in path], '-r') plt.grid(True) plt.pause(0.01) # Need for Mac plt.show() if __name__ == '__main__': main()

30.311005

99

0.572691

857

6,335

3.968495

0.199533

0.047339

0.056454

0.022934

0.206116

0.0788

0.051749

0.022346

0

0.011762

0.328966

6,335

208

100

30.456731

0.788285

0.06693

0

0.065693

0

0.020982

0

1

0.072993

false

0

0.051095

0

0.226277

0.036496

0

null

0

null

0

1

0

da2640c8cad77dff99c17a878df82c7bc7beb176

786

py

Python

accountlist.py

beitnes/accountlist

5bca4960405a23b20bce0d9928536ed6db8c39d0

[ "Apache-2.0" ]

null

accountlist.py

beitnes/accountlist

5bca4960405a23b20bce0d9928536ed6db8c39d0

[ "Apache-2.0" ]

null

accountlist.py

beitnes/accountlist

5bca4960405a23b20bce0d9928536ed6db8c39d0

[ "Apache-2.0" ]

null

import boto3 import pprint def account_list(output_format = "json"): #TODO: Add other output formats client = boto3.client('organizations') pretty_printer = pprint.PrettyPrinter(indent=4) accounts = list() response = client.list_accounts() while True: next_token = response.get('NextToken') for account in response['Accounts']: accounts.append(account) if next_token == None: break else: response = client.list_accounts(NextToken=next_token) # print("quantity: " + str(len(accounts))) if output_format == "json": pretty_printer.pprint(accounts) def main(): #TODO: parse args #TODO: Set up logging account_list() if __name__ == "__main__": main()

18.714286

65

0.625954

87

786

5.436782

0.528736

0.057082

0.067653

0.109937

0

0.005199

0.265903

786

41

66

19.170732

0.814558

0.136132

0

0.068148

0

0.02439

0

1

0.095238

false

0

0.095238

0

0.190476

0.142857

0

null

0

null

0

1

0

1

da2652bdef2ea0254c65e10f3f8343f49c9b32ff

745

py

Python

test/commentProcessor_test.py

ponder-lab/GitHub-Issue-Mining

5cff97bd2322894338c71f5ba7bd743e2e204a72

[ "MIT" ]

3

2021-04-18T04:07:35.000Z

2021-12-25T06:35:32.000Z

test/commentProcessor_test.py

ponder-lab/GitHub-Issue-Classifier

5cff97bd2322894338c71f5ba7bd743e2e204a72

[ "MIT" ]

4

2021-04-06T01:06:36.000Z

2021-08-06T00:34:53.000Z

test/commentProcessor_test.py

ponder-lab/GitHub-Issue-Mining

5cff97bd2322894338c71f5ba7bd743e2e204a72

[ "MIT" ]

null

from utils.commentProcessor import processComment TEST_CASES = [ { "test": "Hello this is a pre processed string", "expected_result": "hello pre processed string" }, { "test": "This string contains a screen name @y3pio tag", "expected_result": "this string contains screen name SCREEN_NAME tag" }, { "test": "Testing this url string https://test.foo.com token", "expected_result": "testing url string URL token" }, { "test": "> This line is a quote, should expect a single QUOTE token", "expected_result": "QUOTE" } ] def test_comment_processor(): for TEST in TEST_CASES: assert(processComment(TEST['test'])) == TEST['expected_result']

31.041667

77

0.628188

88

745

5.204545

0.431818

0.152838

0.078603

0

0.001808

0.257718

745

24

78

31.041667

0.826401

0

0.524129

0

0.045455

1

0.045455

false

0

0.045455

0

0.090909

0

null

0

null

0

1

0

da26ac275ef766fda1ea905a5a0277b1855e977b

7,275

py

Python

plus_reader/plus_highlighting.py

ShashkovS/plus_reader

e53a7af01ae480f7a63e33d01a0a99ea681e7fee

[ "MIT" ]

3

2017-11-27T10:01:42.000Z

2018-05-07T09:37:24.000Z

plus_reader/plus_highlighting.py

ShashkovS/plus_reader

e53a7af01ae480f7a63e33d01a0a99ea681e7fee

[ "MIT" ]

5

2017-09-28T09:53:13.000Z

2017-11-25T20:10:00.000Z

plus_reader/plus_highlighting.py

ShashkovS/plus_reader

e53a7af01ae480f7a63e33d01a0a99ea681e7fee

[ "MIT" ]

2

2017-09-14T11:56:07.000Z

2017-09-14T12:49:46.000Z

import logging import sys import traceback import numpy as np from PyQt5.QtGui import QPixmap, QPainter, QMouseEvent from PyQt5.QtWidgets import QApplication, QWidget, QGridLayout, QMenu, QSlider, QLabel from PyQt5.QtCore import Qt sys._excepthook = sys.excepthook def excepthook(excType, excValue, tracebackobj): traceback.print_tb(tracebackobj, excType, excValue) sys.excepthook = excepthook VIRTUAL_BORDER_WIDTH = 5 class Label(QWidget): def __init__(self, parent=None): QWidget.__init__(self, parent=parent) self.page = self.parentWidget() self.p = None def setPixmap(self, p): self.p = p def paintEvent(self, event): if self.p: painter = QPainter(self) painter.setRenderHint(QPainter.SmoothPixmapTransform) painter.drawPixmap(self.rect(), self.p) def contextMenuEvent(self, QContextMenuEvent): cmenu = QMenu(self) positionx = QContextMenuEvent.x() positiony = QContextMenuEvent.y() im_pos_x, im_pos_y = list( map(int, self.page.image.window_coords_to_image_coords(positionx, positiony, self.width(), self.height()))) logging.info(str(positionx) + ' ' + str(positiony) + ' -> ' + str(im_pos_x) + ' ' + str(im_pos_y)) min_vline_dist = min(abs(im_pos_x - vl) for vl in self.page.image.coords_of_vert_lns) if self.page.image.coords_of_vert_lns\ else float('inf') min_hline_dist = min(abs(im_pos_y - vl) for vl in self.page.image.coords_of_horiz_lns) if self.page.image.coords_of_horiz_lns\ else float('inf') self._actions = [] self._actions_objects = [] if min_hline_dist <= VIRTUAL_BORDER_WIDTH * 3: DelHorAction = cmenu.addAction('Delete Horizontal line here') self._actions.append('DelHorAction') self._actions_objects.append(DelHorAction) else: AddHorAction = cmenu.addAction('Add Horizontal line here') self._actions.append('AddHorAction') self._actions_objects.append(AddHorAction) if min_vline_dist <= VIRTUAL_BORDER_WIDTH * 3: DelVertAction = cmenu.addAction('Delete Vertical line here') self._actions.append('DelVertAction') self._actions_objects.append(DelVertAction) else: AddVertAction = cmenu.addAction('Add Vertical line here') self._actions.append('AddVertAction') self._actions_objects.append(AddVertAction) action = cmenu.exec_(self.mapToGlobal(QContextMenuEvent.pos())) if action: selected_action_index = self._actions_objects.index(action) selected_action = self._actions[selected_action_index] logging.info(str(selected_action)) # TODO работающих методов ещё нет поэтому этот кусок пока не нужен method = getattr(self, selected_action) method((im_pos_x, im_pos_y)) def AddHorAction(self, coords): logging.info('ДОБАВИТЬ ГОРИЗОНТАЛЬ') self.page.image.coords_of_horiz_lns.append(coords[1]) # TODO: Сделать бисектом self.page.image.coords_of_horiz_lns.sort() self.page.image.find_filled_cells() self.page.image.initial_mark_filled_cells() self.page.reload_image() def DelHorAction(self, coords): logging.info('УДАЛИТЬ ГОРИЗОНТАЛЬ') min_dist = float('inf') min_line = float('inf') for i in self.page.image.coords_of_horiz_lns: dist = abs(i - coords[1]) if dist < min_dist: min_dist = dist min_line = i self.page.image.coords_of_horiz_lns.remove(min_line) self.page.image.find_filled_cells() self.page.image.initial_mark_filled_cells() self.page.reload_image() def DelVertAction(self, coords): logging.info('УДАЛИТЬ ВЕРТИКАЛЬ') min_dist = float('inf') min_line = float('inf') for i in self.page.image.coords_of_vert_lns: dist = abs(i - coords[0]) if dist < min_dist: min_dist = dist min_line = i self.page.image.coords_of_vert_lns.remove(min_line) self.page.image.find_filled_cells() self.page.image.initial_mark_filled_cells() self.page.reload_image() def AddVertAction(self, coords): logging.info('ДОБАВИТЬ ВЕРТИКАЛЬ') self.page.image.coords_of_vert_lns.append(coords[0]) self.page.image.coords_of_vert_lns.sort() self.page.image.find_filled_cells() self.page.image.initial_mark_filled_cells() self.page.reload_image() def mousePressEvent(self, a0: QMouseEvent): button_pressed = a0.button() cursor_pos_x = int(a0.x()) cursor_pos_y = int(a0.y()) logging.info(str(cursor_pos_x) + ' ' + str(cursor_pos_y)) if button_pressed == 1: cell_pos = self.page.image.coord_to_cell(cursor_pos_x, cursor_pos_y, self.width(), self.height()) if cell_pos: self.page.image.toggle_highlight_cell(*cell_pos) self.page.reload_image() class ScannedPageWidget(QWidget): def __init__(self, image): super(ScannedPageWidget, self).__init__() self.image = image self.initUi() def reload_image(self, *, update=True): self.qp.loadFromData(self.image.to_bin()) self.lb.setPixmap(self.qp) if update: self.lb.update() def initUi(self): self.lay = QGridLayout(self) self.lay.setSpacing(10) self.lay.setContentsMargins(0, 0, 0, 0) self.slide = QSlider(Qt.Horizontal, self) self.slide.setFocusPolicy(Qt.NoFocus) self.slide.setTickInterval(5) self.slide.setMaximum(255) self.slide.setMinimum(0) self.slide.setTickPosition(QSlider.TicksBelow) self.slide.setTickInterval(5) self.slide.setValue(self.image.black_threshold) self.slide.valueChanged.connect(self.sliderchange) self.slide.sliderReleased.connect(self.valuechange) self.lb = Label(self) self.qp = QPixmap() self.reload_image(update=False) self.slval = QLabel(str(self.slide.sliderPosition())) self.lay.addWidget(QLabel('Change B/W Threshold'), 0, 0) self.lay.addWidget(self.slide, 0, 2) self.lay.addWidget(self.slval, 0, 9) self.lay.addWidget(self.lb, 1, 0, 10, 10) self.setLayout(self.lay) def sliderchange(self): self.slval.setText(str(self.slide.sliderPosition())) def valuechange(self): self.image.black_threshold = self.slide.sliderPosition() self.image.bitmap_lines_filled_cells_and_marking() self.reload_image() def show(image): app = QApplication(sys.argv) _, _, screen_w, screen_h = app.primaryScreen().availableGeometry().getRect() img_scale = max(image.W / screen_w, image.H / screen_h) w_height, w_width = int(image.H / img_scale), int(image.W / img_scale), w = ScannedPageWidget(image) w.resize(w_width, w_height) w.show() app.exec_() def feature_qt(image_cls): show(image_cls) return image_cls.filled_cells if __name__ == '__main__': pass

36.742424

134

0.650034

908

7,275

4.976872

0.227974

0.051339

0.066165

0.050454

0.315114

0.258022

0.193406

0.154016

0.147378

0.1341

0

0.007063

0.240962

7,275

197

135

36.928934

0.8113

0.011959

0

0.177914

0

0.038274

0

0.005076

0

1

0.104294

false

0.006135

0.042945

0

0.165644

0.006135

0

null

0

null

0

1

0

da27bfe1b6414a6b5de205fb3cd12650ba9370f4

22,206

py

Python

dlrnapi_client/shell.py

softwarefactory-project/dlrnapi_client

ad21fe759597968c0f691b37dc681232dcd8f2aa

[ "Apache-2.0" ]

1

2017-10-02T19:36:52.000Z

dlrnapi_client/shell.py

softwarefactory-project/dlrnapi_client

ad21fe759597968c0f691b37dc681232dcd8f2aa

[ "Apache-2.0" ]

4

2018-07-16T20:14:58.000Z

2022-02-04T07:03:03.000Z

dlrnapi_client/shell.py

softwarefactory-project/dlrnapi_client

ad21fe759597968c0f691b37dc681232dcd8f2aa

[ "Apache-2.0" ]

1

2019-12-09T14:40:47.000Z

# Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. from __future__ import print_function import argparse import json import os import sys import dlrnapi_client from dlrnapi_client.rest import ApiException # Helper class to allow us to convert API response objects into JSON for output class ResponseEncoder(json.JSONEncoder): def default(self, obj): # All the API response objects have a "swagger_types" attribute if hasattr(obj, 'swagger_types'): return obj.to_dict() # Use the default encoder for anything else return json.JSONEncoder.default(self, obj) def get_last_tested_repo(api_instance, options): params = dlrnapi_client.Params() # Params | The JSON params to post params.max_age = options.max_age if options.success: params.success = str(options.success) if options.component: params.component = str(options.component) params.job_id = options.job_id params.sequential_mode = str(options.sequential) params.previous_job_id = options.previous_job_id try: api_response = api_instance.api_last_tested_repo_get(params) return api_response except ApiException as e: raise e def post_last_tested_repo(api_instance, options): params = dlrnapi_client.Params1() # Params1 | The JSON params to post params.max_age = options.max_age params.reporting_job_id = options.reporting_job_id if options.success: params.success = str(options.success) if options.component: params.component = str(options.component) params.job_id = options.job_id params.sequential_mode = str(options.sequential) params.previous_job_id = options.previous_job_id try: api_response = api_instance.api_last_tested_repo_post(params) return api_response except ApiException as e: raise e def repo_status(api_instance, options): params = dlrnapi_client.Params2() # Params2 | The JSON params to post params.commit_hash = options.commit_hash params.distro_hash = options.distro_hash if options.success: params.success = str(options.success) if options.extended_hash and options.extended_hash != 'None': params.extended_hash = options.extended_hash try: api_response = api_instance.api_repo_status_get(params) return api_response except ApiException as e: raise e def agg_status(api_instance, options): params = dlrnapi_client.AggQuery() # AggQuery | The JSON params to post params.aggregate_hash = options.agg_hash if options.success: params.success = str(options.success) try: api_response = api_instance.api_agg_status_get(params) return api_response except ApiException as e: raise e def repo_promote(api_instance, options): params = dlrnapi_client.Promotion() # Promotion | The JSON params to post params.commit_hash = options.commit_hash params.distro_hash = options.distro_hash if options.extended_hash != 'None': params.extended_hash = options.extended_hash else: params.extended_hash = None params.promote_name = options.promote_name try: api_response = api_instance.api_promote_post(params) return api_response except ApiException as e: raise e def repo_promote_batch(api_instance, options): params = list() hash_pairs = options.hash_pairs.split(',') for pair in hash_pairs: pair_list = pair.split('_') commit_hash = pair_list[0] distro_hash = pair_list[1] if len(pair_list) > 2: extended_hash = '_'.join(pair_list[2:]) else: extended_hash = None param = dlrnapi_client.Promotion() param.commit_hash = commit_hash param.distro_hash = distro_hash if extended_hash == 'None': param.extended_hash = None else: param.extended_hash = extended_hash param.promote_name = options.promote_name params.append(param) try: api_response = api_instance.api_promote_batch_post(params) return api_response except ApiException as e: raise e def get_promotions(api_instance, options): params = dlrnapi_client.PromotionQuery() # PromotionQuery if options.commit_hash: params.commit_hash = options.commit_hash if options.distro_hash: params.distro_hash = options.distro_hash if options.extended_hash and options.extended_hash != 'None': params.extended_hash = options.extended_hash if options.agg_hash: params.aggregate_hash = options.agg_hash if options.promote_name: params.promote_name = options.promote_name if options.offset: params.offset = options.offset if options.limit: params.limit = options.limit if options.component: params.component = options.component try: api_response = api_instance.api_promotions_get(params) return api_response except ApiException as e: raise e def report_result(api_instance, options): params = dlrnapi_client.Params3() # Params3 | The JSON params to post params.job_id = options.job_id params.commit_hash = options.commit_hash params.distro_hash = options.distro_hash params.aggregate_hash = options.agg_hash params.success = str(options.success) params.url = options.info_url params.timestamp = options.timestamp params.notes = options.notes if options.extended_hash and options.extended_hash != 'None': params.extended_hash = options.extended_hash if (params.commit_hash and not params.distro_hash) or\ (not params.commit_hash and params.distro_hash): raise Exception('Both --commit-hash and --distro-hash must be ' 'specified together') if params.aggregate_hash and (params.commit_hash or params.distro_hash): raise Exception('--agg-hash is mutually exclusive with --commit-hash ' 'and --distro-hash') if (not params.aggregate_hash and not params.commit_hash and not params.distro_hash): raise Exception('Must specify either --agg-hash or --commit-hash and ' '--distro-hash') try: api_response = api_instance.api_report_result_post(params) return api_response except ApiException as e: raise e def import_commit(api_instance, options): params = dlrnapi_client.ModelImport() # ModelImport | JSON params to post params.repo_url = options.repo_url try: api_response = api_instance.api_remote_import_post(params) return api_response except ApiException as e: raise e def get_metrics_builds(api_instance, options): # MetricRequest | JSON params to post params = dlrnapi_client.MetricsRequest() params.start_date = options.start_date params.end_date = options.end_date if options.package_name: params.package_name = options.package_name try: api_response = api_instance.api_build_metrics_get(params) return api_response except ApiException as e: raise e command_funcs = { 'repo-get': get_last_tested_repo, 'repo-use': post_last_tested_repo, 'repo-status': repo_status, 'agg-status': agg_status, 'report-result': report_result, 'repo-promote': repo_promote, 'repo-promote-batch': repo_promote_batch, 'commit-import': import_commit, 'promotion-get': get_promotions, 'build-metrics': get_metrics_builds, } def main(): parser = argparse.ArgumentParser(prog='dlrnapi') parser.add_argument('--url', required=True, help='URL to use') parser.add_argument('--username', '-u', help='username for authentication, defaults to ' '"DLRNAPI_USERNAME" environment variable if set', default=os.getenv('DLRNAPI_USERNAME', None) ) parser.add_argument('--password', '-p', help='password for authentication, defaults to ' '"DLRNAPI_PASSWORD" environment variable if set', default=os.getenv('DLRNAPI_PASSWORD', None) ) subparsers = parser.add_subparsers(dest='command', title='subcommands', description='available subcommands') # Subcommand repo-get parser_last = subparsers.add_parser('repo-get', help='Get last tested repo') parser_last.add_argument('--max-age', type=int, default=0, help='max_age') parser_last.add_argument('--success', type=str, default=None, help='Find repos with a successful/unsuccessful ' 'vote, if true or false are specified') parser_last.add_argument('--job-id', type=str, default=None, help='Name of the CI that sent the vote. If not ' 'set, no filter will be set on CI') parser_last.add_argument('--sequential-mode', dest='sequential', action='store_true', help='Use the sequential mode algorithm. In this ' 'case, return the last tested repo within ' 'that timeframe for the CI job described by ' '--previous-job-id') parser_last.set_defaults(sequential=False) parser_last.add_argument('--previous-job-id', type=str, default=None, help='If --sequential-mode is set, look for jobs' ' tested by this CI') parser_last.add_argument('--component', type=str, default=None, required=False, help='Only search for repos related to ' 'this component.') # Subcommand repo-use parser_use_last = subparsers.add_parser('repo-use', help='Get the last tested repo ' 'since a specific time ' '(optionally for a CI job), ' 'and add an "in progress" ' 'entry in the CI job table ' 'for this.') parser_use_last.add_argument('--max-age', type=int, default=0, help='max_age') parser_use_last.add_argument('--reporting-job-id', type=str, required=True, help=' Name of the CI that will add the "in ' 'progress" entry in the CI job table.') parser_use_last.add_argument('--success', type=str, default=None, help='Find repos with a successful/' 'unsuccessful vote, if true or false ' 'are specified') parser_use_last.add_argument('--job-id', type=str, default=None, help='Name of the CI that sent the vote. If ' 'not set, no filter will be set on CI') parser_use_last.add_argument('--sequential-mode', dest='sequential', action='store_true', help='Use the sequential mode algorithm. In ' 'this case, return the last tested repo ' 'within that timeframe for the CI job ' 'described by --previous-job-id') parser_use_last.set_defaults(sequential=False) parser_use_last.add_argument('--previous-job-id', type=str, default=None, help='If --sequential-mode is true, look for ' 'jobs tested by this CI') parser_use_last.add_argument('--component', type=str, default=None, required=False, help='Only search for repos related to ' 'this component.') # Subcommand repo-status parser_st = subparsers.add_parser('repo-status', help='Get all the CI reports for a ' 'specific repository.') parser_st.add_argument('--commit-hash', type=str, required=True, help='commit_hash of the repo to fetch ' 'information for.') parser_st.add_argument('--distro-hash', type=str, required=True, help='distro_hash of the repo to fetch ' 'information for.') parser_st.add_argument('--extended-hash', type=str, required=False, help='extended_hash of the repo to fetch ' 'information for.') parser_st.add_argument('--success', type=str, default=None, help='If set to a value (true/false), only return ' 'the CI reports with the specified vote. If ' 'not set, return all CI reports.') # Subcommand agg-status parser_st = subparsers.add_parser('agg-status', help='Get all the CI reports for a ' 'specific aggregated repository.') parser_st.add_argument('--agg-hash', type=str, required=True, help='hash of the aggregated repo to fetch ' 'information for.') parser_st.add_argument('--success', type=str, default=None, help='If set to a value (true/false), only return ' 'the CI reports with the specified vote. If ' 'not set, return all CI reports.') # Subcommand report-result parser_rep = subparsers.add_parser('report-result', help='Report the result of a CI job') parser_rep.add_argument('--job-id', type=str, required=True, help='Name of the CI sending the vote') parser_rep.add_argument('--commit-hash', type=str, required=False, help='commit_hash of tested repo') parser_rep.add_argument('--distro-hash', type=str, required=False, help='distro_hash of tested repo') parser_rep.add_argument('--extended-hash', type=str, required=False, help='extended_hash of tested repo') parser_rep.add_argument('--agg-hash', type=str, required=False, help='hash of the tested aggregated repo. Note ' 'that either --commit-hash and --distro-hash or' ' --agg-hash must be specified.') parser_rep.add_argument('--info-url', type=str, required=True, help='URL where to find additional information ' 'from the CI execution') parser_rep.add_argument('--timestamp', type=str, required=True, help='Timestamp (in seconds since the epoch)') parser_rep.add_argument('--success', type=str, required=True, help='Was the CI execution successful? Set to ' 'true or false.') parser_rep.add_argument('--notes', type=str, help='Additional notes') # Subcommand promote parser_prom = subparsers.add_parser('repo-promote', help='Promote a repository') parser_prom.add_argument('--commit-hash', type=str, required=True, help='commit_hash of the repo to be promoted') parser_prom.add_argument('--distro-hash', type=str, required=True, help='distro_hash of the repo to be promoted') parser_prom.add_argument('--extended-hash', type=str, required=False, help='extended_hash of the repo to be promoted') parser_prom.add_argument('--promote-name', type=str, required=True, help='Name to be used for the promotion') # Subcommand repo-promote-batch parser_prom = subparsers.add_parser('repo-promote-batch', help='Promote multiple repositories ' 'at the same time, as an atomic ' 'operation.') parser_prom.add_argument('--hash-pairs', type=str, required=True, help='commit_hash+distro_hash or ' 'commit_hash+distro_hash+extended_hash of ' 'the repos to be promoted, specified as a ' 'comma-separated list of commit_distro or ' 'commit_distro_extended hash groups. If no ' 'extended hash is included, the latest ' 'commit matching the commit and distro ' 'hashes will be promoted.') parser_prom.add_argument('--promote-name', type=str, required=True, help='Name to be used for the promotion') # Subcommand promotion-get parser_promget = subparsers.add_parser('promotion-get', help='Get information about ' 'promotions') parser_promget.add_argument('--commit-hash', type=str, required=False, help='commit_hash of the repo to search ' 'promotions for. Requires --distro-hash ' 'if specified.') parser_promget.add_argument('--distro-hash', type=str, required=False, help='distro_hash of the repo to search ' 'promotions for. Requires --commit-hash ' 'if specified.') parser_promget.add_argument('--extended-hash', type=str, required=False, help='extended_hash of the repo to search ' 'promotions for. Requires --commit-hash ' 'and --distro-hash if specified.') parser_promget.add_argument('--agg-hash', type=str, required=False, help='hash of the tested aggregated repo.') parser_promget.add_argument('--promote-name', type=str, required=False, help='Filter results for this promotion name.') parser_promget.add_argument('--offset', type=int, required=False, help='Show results after this offset. Each ' 'query will only return 100 entries by ' 'default.') parser_promget.add_argument('--limit', type=int, required=False, help='Limit the results to the first limit ' 'items') parser_promget.add_argument('--component', type=str, required=False, help='Only search for promotions related to ' 'this component.') # Subcommand commit-import parser_imp = subparsers.add_parser('commit-import', help='Import a commit built by another' ' instance') parser_imp.add_argument('--repo-url', type=str, required=True, help='Base repository URL for the remote repo ' 'to import') # Subcommand build-metrics parser_metrics = subparsers.add_parser( 'build-metrics', help='Fetch build metrics in a time period') parser_metrics.add_argument( '--start-date', type=str, required=True, help='Start date for the query, in YYYY-MM-DD format') parser_metrics.add_argument( '--end-date', type=str, required=True, help='End date for the query, in YYYY-MM-DD format') parser_metrics.add_argument( '--package-name', type=str, required=False, help='If specified, only fetch metrics for this package name') options, args = parser.parse_known_args(sys.argv[1:]) # create an instance of the API class api_client = dlrnapi_client.ApiClient(host=options.url) dlrnapi_client.configuration.username = options.username dlrnapi_client.configuration.password = options.password api_instance = dlrnapi_client.DefaultApi(api_client=api_client) try: api_response = command_funcs[options.command](api_instance, options) print(json.dumps(api_response, cls=ResponseEncoder, indent=2, sort_keys=True)) except ApiException as e: # Handle 404 exceptions gracefully if e.status == 404: print("ERROR: Got error 404, probably endpoint %s is not available" % options.url) return 1 else: raise except Exception as e: raise e

45.880165

79

0.577141

2,483

22,206

4.996778

0.125654

0.043443

0.035061

0.024502

0.610623

0.556541

0.497139

0.455307

0.416136

0.400983

0

0.002111

0.338737

22,206

483

80

45.975155

0.842822

0.058453

0

0.313433

0

0.231219

0.005031

0

1

0.029851

false

0.012438

0.034826

0

0.099502

0.007463

0

null

0

null

0

1

0

da27fd506b778e15d02b14a496203d5d175a39c3

1,051

py

Python

python-mundo3/ex094.py

abm-astro/estudos-python

c0dcd71489e528d445efa25d4986bf2fd08f8fe6

[ "MIT" ]

1

2021-08-15T18:18:43.000Z

python-mundo3/ex094.py

abm-astro/estudos-python

c0dcd71489e528d445efa25d4986bf2fd08f8fe6

[ "MIT" ]

null

python-mundo3/ex094.py

abm-astro/estudos-python

c0dcd71489e528d445efa25d4986bf2fd08f8fe6

[ "MIT" ]

null

cadastro = dict() pessoas = list() soma = 0 while True: cadastro.clear() cadastro['nome'] = str(input('Nome: ')).capitalize() while True: cadastro['sexo'] = str(input('Sexo [M/F]: ')).upper() if cadastro['sexo'] in 'MF': break print('ERRO! Digite apenas M ou F!') cadastro['idade'] = int(input('Idade: ')) soma += cadastro['idade'] pessoas.append(cadastro.copy()) while True: res = str(input('Quer continuar? [S/N] ')).upper() if res in 'SN': break print('ERRO! Digite apenas S ou N!') if res in "Nn": break print(20*'-=') media = soma / len(pessoas) print(f'- Ao todo temos {len(pessoas)} pessoas cadastradas.') print(f'- A média de idade é de {media:5.2f} anos.') print('- As mulheres cadastradas foram:', end=' ') for m in pessoas: if m['sexo'] in 'F': print(f"{m['nome']}", end=" ; ") print() print('- A lista de pessoas acima da média:') for p in pessoas: print(' ') for k, v in p.items(): if p['idade'] > media: print(f'{k} = {v}', end=' ') print('\n>> ENCERRADO <<')

27.657895

61

0.586108

157

1,051

3.923567

0.407643

0.038961

0.055195

0.064935

0.084416

0

0.005988

0.205519

1,051

37

62

28.405405

0.731737

0

0.162162

0

0.32921

0

1

0

false

0

0.324324

0

null

0

null

0

1

0

da284cabcfa7c599a3b1aad0183ba6d119a7c17a

23,536

py

Python

vendor/packages/translate-toolkit/translate/storage/base.py

jgmize/kitsune

8f23727a9c7fcdd05afc86886f0134fb08d9a2f0

[ "BSD-3-Clause" ]

2

2019-08-19T17:08:47.000Z

2019-10-05T11:37:02.000Z

vendor/packages/translate-toolkit/translate/storage/base.py

jgmize/kitsune

8f23727a9c7fcdd05afc86886f0134fb08d9a2f0

[ "BSD-3-Clause" ]

null

vendor/packages/translate-toolkit/translate/storage/base.py

jgmize/kitsune

8f23727a9c7fcdd05afc86886f0134fb08d9a2f0

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- # # Copyright 2006-2009 Zuza Software Foundation # # This file is part of the Translate Toolkit. # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, see <http://www.gnu.org/licenses/>. """Base classes for storage interfaces. @organization: Zuza Software Foundation @copyright: 2006-2009 Zuza Software Foundation @license: U{GPL <http://www.fsf.org/licensing/licenses/gpl.html>} """ try: import cPickle as pickle except: import pickle from exceptions import NotImplementedError import translate.i18n from translate.storage.placeables import StringElem, general, parse as rich_parse from translate.misc.typecheck import accepts, Self, IsOneOf from translate.misc.multistring import multistring def force_override(method, baseclass): """Forces derived classes to override method.""" if type(method.im_self) == type(baseclass): # then this is a classmethod and im_self is the actual class actualclass = method.im_self else: actualclass = method.im_class if actualclass != baseclass: raise NotImplementedError( "%s does not reimplement %s as required by %s" % \ (actualclass.__name__, method.__name__, baseclass.__name__) ) class ParseError(Exception): def __init__(self, inner_exc): self.inner_exc = inner_exc def __str__(self): return repr(self.inner_exc) class TranslationUnit(object): """Base class for translation units. Our concept of a I{translation unit} is influenced heavily by XLIFF: U{http://www.oasis-open.org/committees/xliff/documents/xliff-specification.htm} As such most of the method- and variable names borrows from XLIFF terminology. A translation unit consists of the following: - A I{source} string. This is the original translatable text. - A I{target} string. This is the translation of the I{source}. - Zero or more I{notes} on the unit. Notes would typically be some comments from a translator on the unit, or some comments originating from the source code. - Zero or more I{locations}. Locations indicate where in the original source code this unit came from. - Zero or more I{errors}. Some tools (eg. L{pofilter <filters.pofilter>}) can run checks on translations and produce error messages. @group Source: *source* @group Target: *target* @group Notes: *note* @group Locations: *location* @group Errors: *error* """ rich_parsers = [] """A list of functions to use for parsing a string into a rich string tree.""" def __init__(self, source): """Constructs a TranslationUnit containing the given source string.""" self.notes = "" self._store = None self.source = source self._target = None self._rich_source = None self._rich_target = None def __eq__(self, other): """Compares two TranslationUnits. @type other: L{TranslationUnit} @param other: Another L{TranslationUnit} @rtype: Boolean @return: Returns True if the supplied TranslationUnit equals this unit. """ return self.source == other.source and self.target == other.target def __str__(self): """Converts to a string representation that can be parsed back using L{parsestring()}.""" # no point in pickling store object, so let's hide it for a while. store = getattr(self, "_store", None) self._store = None dump = pickle.dumps(self) self._store = store return dump def rich_to_multistring(cls, elem_list): """Convert a "rich" string tree to a C{multistring}: >>> from translate.storage.placeables.interfaces import X >>> rich = [StringElem(['foo', X(id='xxx', sub=[' ']), 'bar'])] >>> TranslationUnit.rich_to_multistring(rich) multistring(u'foo bar') """ return multistring([unicode(elem) for elem in elem_list]) rich_to_multistring = classmethod(rich_to_multistring) def multistring_to_rich(cls, mulstring): """Convert a multistring to a list of "rich" string trees: >>> target = multistring([u'foo', u'bar', u'baz']) >>> TranslationUnit.multistring_to_rich(target) [<StringElem([<StringElem([u'foo'])>])>, <StringElem([<StringElem([u'bar'])>])>, <StringElem([<StringElem([u'baz'])>])>] """ if isinstance(mulstring, multistring): return [rich_parse(s, cls.rich_parsers) for s in mulstring.strings] return [rich_parse(mulstring, cls.rich_parsers)] def setsource(self, source): """Sets the source string to the given value.""" self._rich_source = None self._source = source source = property(lambda self: self._source, setsource) def settarget(self, target): """Sets the target string to the given value.""" self._rich_target = None self._target = target target = property(lambda self: self._target, settarget) def _get_rich_source(self): if self._rich_source is None: self._rich_source = self.multistring_to_rich(self.source) return self._rich_source def _set_rich_source(self, value): if not hasattr(value, '__iter__'): raise ValueError('value must be iterable') if len(value) < 1: raise ValueError('value must have at least one element.') if not isinstance(value[0], StringElem): raise ValueError('value[0] must be of type StringElem.') self._rich_source = list(value) self.source = self.rich_to_multistring(value) rich_source = property(_get_rich_source, _set_rich_source) """ @see: rich_to_multistring @see: multistring_to_rich""" def _get_rich_target(self): if self._rich_target is None: self._rich_target = self.multistring_to_rich(self.target) return self._rich_target def _set_rich_target(self, value): if not hasattr(value, '__iter__'): raise ValueError('value must be iterable') if len(value) < 1: raise ValueError('value must have at least one element.') if not isinstance(value[0], StringElem): raise ValueError('value[0] must be of type StringElem.') self._rich_target = list(value) self.target = self.rich_to_multistring(value) rich_target = property(_get_rich_target, _set_rich_target) """ @see: rich_to_multistring @see: multistring_to_rich""" def gettargetlen(self): """Returns the length of the target string. @note: Plural forms might be combined. @rtype: Integer """ length = len(self.target or "") strings = getattr(self.target, "strings", []) if strings: length += sum([len(pluralform) for pluralform in strings[1:]]) return length def getid(self): """A unique identifier for this unit. @rtype: string @return: an identifier for this unit that is unique in the store Derived classes should override this in a way that guarantees a unique identifier for each unit in the store. """ return self.source def setid(self, value): """Sets the unique identified for this unit. only implemented if format allows ids independant from other unit properties like source or context""" pass def getlocations(self): """A list of source code locations. @note: Shouldn't be implemented if the format doesn't support it. @rtype: List """ return [] def addlocation(self, location): """Add one location to the list of locations. @note: Shouldn't be implemented if the format doesn't support it. """ pass def addlocations(self, location): """Add a location or a list of locations. @note: Most classes shouldn't need to implement this, but should rather implement L{addlocation()}. @warning: This method might be removed in future. """ if isinstance(location, list): for item in location: self.addlocation(item) else: self.addlocation(location) def getcontext(self): """Get the message context.""" return "" def setcontext(self, context): """Set the message context""" pass def getnotes(self, origin=None): """Returns all notes about this unit. It will probably be freeform text or something reasonable that can be synthesised by the format. It should not include location comments (see L{getlocations()}). """ return getattr(self, "notes", "") def addnote(self, text, origin=None, position="append"): """Adds a note (comment). @type text: string @param text: Usually just a sentence or two. @type origin: string @param origin: Specifies who/where the comment comes from. Origin can be one of the following text strings: - 'translator' - 'developer', 'programmer', 'source code' (synonyms) """ if getattr(self, "notes", None): self.notes += '\n'+text else: self.notes = text def removenotes(self): """Remove all the translator's notes.""" self.notes = u'' def adderror(self, errorname, errortext): """Adds an error message to this unit. @type errorname: string @param errorname: A single word to id the error. @type errortext: string @param errortext: The text describing the error. """ pass def geterrors(self): """Get all error messages. @rtype: Dictionary """ return {} def markreviewneeded(self, needsreview=True, explanation=None): """Marks the unit to indicate whether it needs review. @keyword needsreview: Defaults to True. @keyword explanation: Adds an optional explanation as a note. """ pass def istranslated(self): """Indicates whether this unit is translated. This should be used rather than deducing it from .target, to ensure that other classes can implement more functionality (as XLIFF does). """ return bool(self.target) and not self.isfuzzy() def istranslatable(self): """Indicates whether this unit can be translated. This should be used to distinguish real units for translation from header, obsolete, binary or other blank units. """ return True def isfuzzy(self): """Indicates whether this unit is fuzzy.""" return False def markfuzzy(self, value=True): """Marks the unit as fuzzy or not.""" pass def isobsolete(self): """indicate whether a unit is obsolete""" return False def makeobsolete(self): """Make a unit obsolete""" pass def isheader(self): """Indicates whether this unit is a header.""" return False def isreview(self): """Indicates whether this unit needs review.""" return False def isblank(self): """Used to see if this unit has no source or target string. @note: This is probably used more to find translatable units, and we might want to move in that direction rather and get rid of this. """ return not (self.source or self.target) def hasplural(self): """Tells whether or not this specific unit has plural strings.""" #TODO: Reconsider return False def getsourcelanguage(self): return getattr(self._store, "sourcelanguage", "en") def gettargetlanguage(self): return getattr(self._store, "targetlanguage", None) def merge(self, otherunit, overwrite=False, comments=True, authoritative=False): """Do basic format agnostic merging.""" if not self.target or overwrite: self.rich_target = otherunit.rich_target def unit_iter(self): """Iterator that only returns this unit.""" yield self def getunits(self): """This unit in a list.""" return [self] def buildfromunit(cls, unit): """Build a native unit from a foreign unit, preserving as much information as possible.""" if type(unit) == cls and hasattr(unit, "copy") and callable(unit.copy): return unit.copy() newunit = cls(unit.source) newunit.target = unit.target newunit.markfuzzy(unit.isfuzzy()) locations = unit.getlocations() if locations: newunit.addlocations(locations) notes = unit.getnotes() if notes: newunit.addnote(notes) return newunit buildfromunit = classmethod(buildfromunit) xid = property(lambda self: None, lambda self, value: None) rid = property(lambda self: None, lambda self, value: None) class TranslationStore(object): """Base class for stores for multiple translation units of type UnitClass.""" UnitClass = TranslationUnit """The class of units that will be instantiated and used by this class""" Name = "Base translation store" """The human usable name of this store type""" Mimetypes = None """A list of MIME types associated with this store type""" Extensions = None """A list of file extentions associated with this store type""" _binary = False """Indicates whether a file should be accessed as a binary file.""" suggestions_in_format = False """Indicates if format can store suggestions and alternative translation for a unit""" def __init__(self, unitclass=None): """Constructs a blank TranslationStore.""" self.units = [] self.sourcelanguage = None self.targetlanguage = None if unitclass: self.UnitClass = unitclass super(TranslationStore, self).__init__() def getsourcelanguage(self): """Gets the source language for this store""" return self.sourcelanguage def setsourcelanguage(self, sourcelanguage): """Sets the source language for this store""" self.sourcelanguage = sourcelanguage def gettargetlanguage(self): """Gets the target language for this store""" return self.targetlanguage def settargetlanguage(self, targetlanguage): """Sets the target language for this store""" self.targetlanguage = targetlanguage def unit_iter(self): """Iterator over all the units in this store.""" for unit in self.units: yield unit def getunits(self): """Return a list of all units in this store.""" return [unit for unit in self.unit_iter()] def addunit(self, unit): """Appends the given unit to the object's list of units. This method should always be used rather than trying to modify the list manually. @type unit: L{TranslationUnit} @param unit: The unit that will be added. """ unit._store = self self.units.append(unit) def addsourceunit(self, source): """Adds and returns a new unit with the given source string. @rtype: L{TranslationUnit} """ unit = self.UnitClass(source) self.addunit(unit) return unit def findid(self, id): """find unit with matching id by checking id_index""" self.require_index() return self.id_index.get(id, None) def findunit(self, source): """Finds the unit with the given source string. @rtype: L{TranslationUnit} or None """ if len(getattr(self, "sourceindex", [])): if source in self.sourceindex: return self.sourceindex[source][0] else: for unit in self.units: if unit.source == source: return unit return None def findunits(self, source): """Finds the units with the given source string. @rtype: L{TranslationUnit} or None """ if len(getattr(self, "sourceindex", [])): if source in self.sourceindex: return self.sourceindex[source] else: #FIXME: maybe we should generate index here instead since #we'll scan all units anyway result = [] for unit in self.units: if unit.source == source: result.append(unit) return result return None def translate(self, source): """Returns the translated string for a given source string. @rtype: String or None """ unit = self.findunit(source) if unit and unit.target: return unit.target else: return None def remove_unit_from_index(self, unit): """Remove a unit from source and locaton indexes""" def remove_unit(source): if source in self.sourceindex: try: self.sourceindex[source].remove(unit) if len(self.sourceindex[source]) == 0: del(self.sourceindex[source]) except ValueError: pass if unit.hasplural(): for source in unit.source.strings: remove_unit(source) else: remove_unit(unit.source) for location in unit.getlocations(): if location in self.locationindex and self.locationindex[location] is not None \ and self.locationindex[location] == unit: del(self.locationindex[location]) def add_unit_to_index(self, unit): """Add a unit to source and location idexes""" self.id_index[unit.getid()] = unit def insert_unit(source): if not source in self.sourceindex: self.sourceindex[source] = [unit] else: self.sourceindex[source].append(unit) if unit.hasplural(): for source in unit.source.strings: insert_unit(source) else: insert_unit(unit.source) for location in unit.getlocations(): if location in self.locationindex: # if sources aren't unique, don't use them #FIXME: maybe better store a list of units like sourceindex self.locationindex[location] = None else: self.locationindex[location] = unit def makeindex(self): """Indexes the items in this store. At least .sourceindex should be usefull.""" self.locationindex = {} self.sourceindex = {} self.id_index = {} for index, unit in enumerate(self.units): unit.index = index if unit.istranslatable(): self.add_unit_to_index(unit) def require_index(self): """make sure source index exists""" if not hasattr(self, "sourceindex"): self.makeindex() def getids(self): """return a list of unit ids""" self.require_index() return self.id_index.keys() def __getstate__(self): odict = self.__dict__.copy() odict['fileobj'] = None return odict def __setstate__(self, dict): self.__dict__.update(dict) if getattr(self, "filename", False): self.fileobj = open(self.filename) def __str__(self): """Converts to a string representation that can be parsed back using L{parsestring()}.""" # We can't pickle fileobj if it is there, so let's hide it for a while. fileobj = getattr(self, "fileobj", None) self.fileobj = None dump = pickle.dumps(self) self.fileobj = fileobj return dump def isempty(self): """Returns True if the object doesn't contain any translation units.""" if len(self.units) == 0: return True for unit in self.units: if unit.istranslatable(): return False return True def _assignname(self): """Tries to work out what the name of the filesystem file is and assigns it to .filename.""" fileobj = getattr(self, "fileobj", None) if fileobj: filename = getattr(fileobj, "name", getattr(fileobj, "filename", None)) if filename: self.filename = filename def parsestring(cls, storestring): """Converts the string representation back to an object.""" newstore = cls() if storestring: newstore.parse(storestring) return newstore parsestring = classmethod(parsestring) def parse(self, data): """parser to process the given source string""" self.units = pickle.loads(data).units def savefile(self, storefile): """Writes the string representation to the given file (or filename).""" if isinstance(storefile, basestring): mode = 'w' if self._binary: mode = 'wb' storefile = open(storefile, mode) self.fileobj = storefile self._assignname() storestring = str(self) storefile.write(storestring) storefile.close() def save(self): """Save to the file that data was originally read from, if available.""" fileobj = getattr(self, "fileobj", None) mode = 'w' if self._binary: mode = 'wb' if not fileobj: filename = getattr(self, "filename", None) if filename: fileobj = file(filename, mode) else: fileobj.close() filename = getattr(fileobj, "name", getattr(fileobj, "filename", None)) if not filename: raise ValueError("No file or filename to save to") fileobj = fileobj.__class__(filename, mode) self.savefile(fileobj) def parsefile(cls, storefile): """Reads the given file (or opens the given filename) and parses back to an object.""" mode = 'r' if cls._binary: mode = 'rb' if isinstance(storefile, basestring): storefile = open(storefile, mode) mode = getattr(storefile, "mode", mode) #For some reason GzipFile returns 1, so we have to test for that here if mode == 1 or "r" in mode: storestring = storefile.read() storefile.close() else: storestring = "" newstore = cls.parsestring(storestring) newstore.fileobj = storefile newstore._assignname() return newstore parsefile = classmethod(parsefile)

34.209302

97

0.613443

2,795

23,536

5.088372

0.194991

0.008438

0.00443

0.007031

0.20187

0.160245

0.126916

0.113275

0.104556

0.076079

0

0.001928

0.29491

23,536

687

98

34.259098

0.855077

0.337313

0

0.307479

0

0.034779

0

0.004367

0

1

0.204986

false

0.022161

0.019391

0.00831

0.412742

0

null

0

null

0

1

0

1

da296592fb077c1bc7a27382f8604a31a8ab30e3

520

py

Python

task2C.py

jfs60/Group-147-PartIA-Flood-Warning-System

3fb52e3e028ec8e0b70ccb1cfc61bcf76b42f2c1

[ "MIT" ]

null

task2C.py

jfs60/Group-147-PartIA-Flood-Warning-System

3fb52e3e028ec8e0b70ccb1cfc61bcf76b42f2c1

[ "MIT" ]

null

task2C.py

jfs60/Group-147-PartIA-Flood-Warning-System

3fb52e3e028ec8e0b70ccb1cfc61bcf76b42f2c1

[ "MIT" ]

1

2022-02-06T06:45:15.000Z

from floodsystem.station import MonitoringStation from floodsystem.stationdata import build_station_list, update_water_levels from floodsystem.flood import stations_highest_rel_level, stations_level_over_threshold def run (): stations = build_station_list() update_water_levels(stations) list = stations_highest_rel_level(stations, 9) return(list) stations_Task_2C = run() print (stations_Task_2C) if __name__ == "__main__": print("*** Task 2C: CUED Part IA Flood Warning System ***") run()

30.588235

87

0.775

67

520

5.58209

0.492537

0.120321

0.085562

0.117647

0.342246

0.176471

0

0.008989

0.144231

520

17

88

30.588235

0.831461

0

0.111324

0

1

0.076923

false

0

0.230769

0

0.307692

0.153846

0

null

0

null

0

1

0

da2e43a4657d302992b18fd2e6651b3dd93dac4f

6,112

py

Python

docs/examples/viz_emwave_animation.py

iamansoni/fury

2e7971a176c2540e10a9a6da861097583d08cb4a

[ "BSD-3-Clause" ]

149

2018-09-20T18:36:16.000Z

2022-03-29T05:16:25.000Z

docs/examples/viz_emwave_animation.py

iamansoni/fury

2e7971a176c2540e10a9a6da861097583d08cb4a

[ "BSD-3-Clause" ]

523

2018-09-20T16:57:16.000Z

2022-03-31T18:52:41.000Z

docs/examples/viz_emwave_animation.py

iamansoni/fury

2e7971a176c2540e10a9a6da861097583d08cb4a

[ "BSD-3-Clause" ]

150

2018-10-10T07:21:27.000Z

2022-03-29T08:33:17.000Z

""" =============================================== Electromagnetic Wave Propagation Animation =============================================== A linearly polarized sinusoidal electromagnetic wave, propagating in the direction +x through a homogeneous, isotropic, dissipationless medium, such as vacuum. The electric field (blue arrows) oscillates in the ±z-direction, and the orthogonal magnetic field (red arrows) oscillates in phase with the electric field, but in the ±y-direction. Function of the sinusoid used in the animation = sin(k*x - w*t + d) Where, k:wavenumber, x:abscissa, w:angular frequency, t:time, d:phase angle Importing necessary modules """ from fury import window, actor, utils, ui import numpy as np import itertools ############################################################################### # function that updates and returns the coordinates of the waves which are # changing with time def update_coordinates(wavenumber, ang_frq, time, phase_angle): x = np.linspace(-3, 3, npoints) y = np.sin(wavenumber*x - ang_frq*time + phase_angle) z = np.array([0 for i in range(npoints)]) return x, y, z ############################################################################### # Variable(s) and their description- # npoints: For high quality rendering, keep the number of npoints high # but kindly note that higher values for npoints will slow down the # rendering process (default = 800) # wavelength : wavelength of the wave (default = 2) # wavenumber : 2*pi/wavelength # time: time (default time i.e. time at beginning of the animation = 0) # incre_time: value by which time is incremented for each call of # timer_callback (default = 0.1) # angular_frq: angular frequency (default = 0.1) # phase_angle: phase angle (default = 0.002) npoints = 800 wavelength = 2 wavenumber = 2*np.pi/wavelength time = 0 incre_time = 0.1 angular_frq = 0.1 phase_angle = 0.002 ############################################################################### # Creating a scene object and configuring the camera's position scene = window.Scene() scene.set_camera(position=(-6, 5, -10), focal_point=(0.0, 0.0, 0.0), view_up=(0.0, 0.0, 0.0)) showm = window.ShowManager(scene, size=(800, 600), reset_camera=True, order_transparent=True) showm.initialize() ############################################################################### # Creating a yellow colored arrow to show the direction of propagation of # electromagnetic wave centers = np.array([[3, 0, 0]]) directions = np.array([[-1, 0, 0]]) heights = np.array([6.4]) arrow_actor = actor.arrow(centers, directions, window.colors.yellow, heights, resolution=20, tip_length=0.06, tip_radius=0.012, shaft_radius=0.005) scene.add(arrow_actor) ############################################################################### # Creating point actor that renders the magnetic field x = np.linspace(-3, 3, npoints) y = np.sin(wavenumber*x - angular_frq*time + phase_angle) z = np.array([0 for i in range(npoints)]) pts = np.array([(a, b, c) for (a, b, c) in zip(x, y, z)]) pts = [pts] colors = window.colors.red wave_actor1 = actor.line(pts, colors, linewidth=3) scene.add(wave_actor1) vertices = utils.vertices_from_actor(wave_actor1) vcolors = utils.colors_from_actor(wave_actor1, 'colors') no_vertices_per_point = len(vertices)/npoints initial_vertices = vertices.copy() - \ np.repeat(pts, no_vertices_per_point, axis=0) ############################################################################### # Creating point actor that renders the electric field xx = np.linspace(-3, 3, npoints) yy = np.array([0 for i in range(npoints)]) zz = np.sin(wavenumber*xx - angular_frq*time + phase_angle) pts2 = np.array([(a, b, c) for (a, b, c) in zip(xx, yy, zz)]) pts2 = [pts2] colors2 = window.colors.blue wave_actor2 = actor.line(pts2, colors2, linewidth=3) scene.add(wave_actor2) vertices2 = utils.vertices_from_actor(wave_actor2) vcolors2 = utils.colors_from_actor(wave_actor2, 'colors') no_vertices_per_point2 = len(vertices2)/npoints initial_vertices2 = vertices2.copy() - \ np.repeat(pts2, no_vertices_per_point2, axis=0) ############################################################################### # Initializing text box to display the title of the animation tb = ui.TextBlock2D(bold=True, position=(160, 90)) tb.message = "Electromagnetic Wave" scene.add(tb) ############################################################################### # end is used to decide when to end the animation end = 300 ############################################################################### # Initializing counter counter = itertools.count() ############################################################################### # Coordinates to be plotted are changed everytime timer_callback is called by # using the update_coordinates function. The wave is rendered here. def timer_callback(_obj, _event): global pts, pts2, time, time_incre, angular_frq, phase_angle, wavenumber time += incre_time cnt = next(counter) x, y, z = update_coordinates(wavenumber, angular_frq, phase_angle, time) pts = np.array([(a, b, c) for (a, b, c) in zip(x, y, z)]) vertices[:] = initial_vertices + \ np.repeat(pts, no_vertices_per_point, axis=0) utils.update_actor(wave_actor1) xx, zz, yy = update_coordinates(wavenumber, angular_frq, phase_angle, time) pts2 = np.array([(a, b, c) for (a, b, c) in zip(xx, yy, zz)]) vertices2[:] = initial_vertices2 + \ np.repeat(pts2, no_vertices_per_point2, axis=0) utils.update_actor(wave_actor2) showm.render() # to end the animation if cnt == end: showm.exit() ############################################################################### # Run every 25 milliseconds showm.add_timer_callback(True, 25, timer_callback) interactive = False if interactive: showm.start() window.record(showm.scene, size=(800, 600), out_path="viz_emwave.png")

34.925714

79

0.59375

786

6,112

4.507634

0.301527

0.006774

0.248095

0.186847

0.154107

0.117979

0.078465

0

0.026153

0.155432

6,112

174

80

35.126437

0.659822

0.310046

0

0.146341

0

0.013872

0

1

0.02439

false

0

0.036585

0

0.073171

0

null

0

null

0

1

0

da2f601feb319bbef64c8038bd332c6cea544cb4

3,243

py

Python

report_templates.py

averlarque/l1-zabbix-reporter

5d8ea4d432b7b518f954d806a86fe5bcafca3f9d

[ "MIT" ]

1

2017-03-27T02:59:09.000Z

report_templates.py

averlarque/l1-zabbix-reporter

5d8ea4d432b7b518f954d806a86fe5bcafca3f9d

[ "MIT" ]

1

2018-01-16T04:56:16.000Z

report_templates.py

averlarque/l1-zabbix-reporter

5d8ea4d432b7b518f954d806a86fe5bcafca3f9d

[ "MIT" ]

2

2016-11-24T07:06:51.000Z

2019-11-16T15:12:54.000Z

from report_generator import * class PeriodReport: """ Parent class for time periods reports """ def __init__(self, since, till, report_format='count', report_type='txt'): # Define time limits self.since = since self.till = till self.report_type = report_type self.report_format = report_format # Generate a title for a report self.report_name = self.get_report_name(self.report_format + '_report_all') # According to the db_path and redefinition of child classes self.report_class = self.choose_report_class() # Generating the data for the report self.report_data = self.report_class.generate_report_data() # For further generating a report the self.generate_report() should be called def get_report_name(self, slug): time_format = '%H.%M_%d%m%y' since = self.since.strftime(time_format) till = self.till.strftime(time_format) time_alias = since + '-' + till report_name = slug + '(' + time_alias + ')' return report_name def choose_report_class(self): if self.report_format == 'count': report_class = CountPeriodReport(self.since, self.till) elif self.report_format == 'event': report_class = EventPeriodReport(self.since, self.till) else: report_class = CountPeriodReport(self.since, self.till) return report_class def generate_report(self): """ Main reporting function :return: None """ if self.report_type == 'txt': self.report_class.create_txt_report(self.report_data, self.report_name) elif self.report_type == 'html': self.report_class.create_html_report(self.report_data, self.report_name) else: self.report_class.create_txt_report(self.report_data, self.report_name) class ProjectPeriodReport(PeriodReport): def __init__(self, since, till, project, report_format='count', report_type='txt'): self.project = project super().__init__(since, till, report_format=report_format, report_type=report_type) # Redefines report name according to the sibling class alias self.report_name = self.get_report_name(self.report_format + '_' + self.project + '_project_report') def choose_report_class(self): if self.report_format == 'count': report_class = ProjectCountPeriodReport(self.since, self.till, self.project) elif self.report_format == 'event': report_class = ProjectEventPeriodReport(self.since, self.till, self.project) else: report_class = ProjectCountPeriodReport(self.since, self.till, self.project) return report_class class ItemPeriodReport(PeriodReport): def __init__(self, since, till, item, report_format='count', report_type='txt'): self.item = item super().__init__(since, till, report_format=report_format, report_type=report_type) # Redefines report name according to the sibling class alias self.report_name = self.get_report_name(self.report_format + '_' + self.item + '_item_report') def choose_report_class(self): if self.report_format == 'count': report_class = ItemCountPeriodReport(self.since, self.till, self.item) elif self.report_format == 'event': report_class = ItemEventPeriodReport(self.since, self.till, self.item) self.report_name = 'event_' + self.report_name else: report_class = ItemCountPeriodReport(self.since, self.till, self.item) return report_class

38.152941

102

0.755782

442

3,243

5.266968

0.171946

0.128866

0.055842

0.065722

0.592354

0.583763

0.507732

0.383591

0.289948

0

0.136602

3,243

84

103

38.607143

0.831429

0.127351

0

0.440678

0

0.043556

0

1

0.135593

false

0

0.016949

0

0.271186

0

null

0

null

0

1

0

da32e41f6a6f935279a78a5bb3c83c1544bb8fec

494

py

Python

CodeWars/Python/EvenTimesLast.py

BobbyRobillard/CodingChallenges

71d5ca0b7f7c470c547d858dde7a799ce7d0d1a0

[ "MIT" ]

null

CodeWars/Python/EvenTimesLast.py

BobbyRobillard/CodingChallenges

71d5ca0b7f7c470c547d858dde7a799ce7d0d1a0

[ "MIT" ]

null

CodeWars/Python/EvenTimesLast.py

BobbyRobillard/CodingChallenges

71d5ca0b7f7c470c547d858dde7a799ce7d0d1a0

[ "MIT" ]

null

# First Correct Solution # def even_last(numbers): return ( 0 if len(numbers) == 0 else sum(numbers[x] for x in range(0, len(numbers), 2)) * numbers[len(numbers) - 1] ) # REFACTORED Solution # def even_last(numbers): return sum(numbers[::2]) * numbers[-1] if numbers else 0 # EXAMPLE AND TESTING # print("\nInput: {0}\nEven Times Last: {1}".format("[2,3,4,5]", even_last([2, 3, 4, 5]))) assert even_last([2, 3, 4, 5]) == 30 # Simple Unit Tests

24.7

88

0.595142

77

494

3.766234

0.467532

0.110345

0.031034

0.041379

0.303448

0

0.063492

0.234818

494

19

89

26

0.703704

0.168016

0

0.181818

0

0.1067

0

0.090909

1

0.181818

false

0

0.181818

0.363636

0.090909

0

null

0

null

0

1

0

1

da35f10f0968905caacfa6b0d419287aa50e3f84

603

py

Python

scatter.py

Deego88/pands-project

89f0baad690b0772502d5d336c9fd56ad5470cdc

[ "MIT" ]

null

scatter.py

Deego88/pands-project

89f0baad690b0772502d5d336c9fd56ad5470cdc

[ "MIT" ]

null

scatter.py

Deego88/pands-project

89f0baad690b0772502d5d336c9fd56ad5470cdc

[ "MIT" ]

null

# Third output required for project- A scatter plot of the output of the variables import seaborn as sns import pandas as pd import matplotlib.pyplot as plt # First output required for project- Read iris CSV file to into DataFrame iris = pd.read_csv("iris.csv") sns.set_style("darkgrid") sns.pairplot(iris, hue="species", height=2, markers= ["o","s", "D"]) #hue distinguished by species plt.show() # Fit a linear regression line to the scatter plots sns.pairplot(iris, kind="reg") plt.show() #References #1.seaborn.pairplot ,https://seaborn.pydata.org/generated/seaborn.pairplot.html

35.470588

99

0.739635

94

603

4.723404

0.606383

0.063063

0.076577

0.108108

0

0.003899

0.149254

603

17

100

35.470588

0.861598

0.529022

0

0.222222

0

0.110687

0

1

0

false

0

0.333333

0

0.333333

0

null

0

null

0

1

0

1

da36cd3ef7bb152a5c978fa2a7968dad8b22592a

28

py

Python

image_predictor/__init__.py

shakedlokits/pyArt

ffac65e91b7f97f0fa95f4ee7bfffcff4f6249aa

[ "Unlicense" ]

3

2017-03-26T16:42:18.000Z

2021-12-30T06:28:34.000Z

image_predictor/__init__.py

shakedlokits/pyArt

ffac65e91b7f97f0fa95f4ee7bfffcff4f6249aa

[ "Unlicense" ]

null

image_predictor/__init__.py

shakedlokits/pyArt

ffac65e91b7f97f0fa95f4ee7bfffcff4f6249aa

[ "Unlicense" ]

null

__author__ = 'shakedlokits'

14

27

0.785714

2

28

9

1

0

0.107143

28

1

28

0.72

0

0.428571

0

1

0

false

0

1

0

null

0

1

0

null

0

3

da378e0eafeab07a79465181d9fc51e82389ac0a

6,674

py

Python

officevideo/officevideo.py

introp-software/xblock-officevideo

6e475df782a4b0a2d2d9f7e2e5b9bae441b56024

[ "MIT" ]

4

2020-02-09T09:39:06.000Z

2021-12-30T09:50:57.000Z

officevideo/officevideo.py

acidburn0zzz/xblock-officevideo

6e475df782a4b0a2d2d9f7e2e5b9bae441b56024

[ "MIT" ]

null

officevideo/officevideo.py

acidburn0zzz/xblock-officevideo

6e475df782a4b0a2d2d9f7e2e5b9bae441b56024

[ "MIT" ]

8

2019-11-02T21:34:20.000Z

2021-12-30T09:50:59.000Z

""" Copyright (c) Microsoft Corporation. All Rights Reserved. """ """ Licensed under the MIT license. See LICENSE file on the project webpage for details. """ import textwrap import pkg_resources import urllib2 import mimetypes import urlparse, requests, json import xml.etree.ElementTree as ET from xblock.core import XBlock from xblock.fragment import Fragment from xblock.fields import Scope, String from django.conf import settings from django.contrib.auth.models import User from social.apps.django_app.utils import load_strategy import logging LOG = logging.getLogger(__name__) import time import re from urlparse import parse_qs, urlsplit, urlunsplit from urllib import urlencode """test url: https://wwedudemo17.sharepoint.com/portals/hub/_layouts/15/PointPublishing.aspx?app=video&p=p&chid=4fe89746-6fd9-4a2b-9a42-ea41c5853a53&vid=70113d75-9a34-494a-972d-dc498c12168f """ """ <iframe width=640 height=360 src='https://wwedudemo17.sharepoint.com/portals/hub/_layouts/15/VideoEmbedHost.aspx?chId=4fe89746%2D6fd9%2D4a2b%2D9a42%2Dea41c5853a53&vId=70113d75%2D9a34%2D494a%2D972d%2Ddc498c12168f&width=640&height=360&autoPlay=false&showInfo=true' allowfullscreen></iframe> """ DEFAULT_VIDEO_URL = ('https://www.youtube.com/embed/uXsJ_9lQubc') class OfficeVideoXBlock(XBlock): EMBED_CODE_TEMPLATE = textwrap.dedent(""" <iframe src="{}" width="640" height="360" allowfullscreen> </iframe> """) display_name = String( display_name="Display Name", help="This name appears in the horizontal navigation at the top of the page.", scope=Scope.settings, default="OfficeVideo", ) video_url = String( display_name="Video URL", help="Navigate to the video in your browser and ensure that it is accessible to your intended audience. Copy its URL or embed code and paste it into this field.", scope=Scope.settings, default=EMBED_CODE_TEMPLATE.format(DEFAULT_VIDEO_URL) ) output_code = String( display_name="Output Iframe Embed Code", help="Copy the embed code into this field.", scope=Scope.settings, default=EMBED_CODE_TEMPLATE.format(DEFAULT_VIDEO_URL) ) message = String( display_name="video display status message", help="Message to help students in case of errors.", scope=Scope.settings, default="" ) message_display_state = String( display_name="Whether to display the status message", help="Determines whether to display the message to help students in case of errors.", scope=Scope.settings, default="block" ) def resource_string(self, path): """Handy helper for getting resources from our kit.""" data = pkg_resources.resource_string(__name__, path) return data.decode("utf8") def student_view(self, context=None): """ The primary view of the OfficeVideoXBlock, shown to students when viewing courses. """ embed_code = self.output_code if embed_code == '': embed_code = self.get_officevideo_embed_code(officevideo_url=self.video_url) html = self.resource_string("static/html/officevideo.html") frag = Fragment(html.format(embed_code=embed_code, message=self.message, message_display_state=self.message_display_state)) frag.add_css(self.resource_string("static/css/officevideo.css")) frag.add_javascript(self.resource_string("static/js/src/officevideo.js")) frag.initialize_js('OfficeVideoXBlock') return frag def studio_view(self, context=None): """ he primary view of the OfficeVideoXBlock, shown to teachers when viewing courses. """ html = self.resource_string("static/html/officevideo_edit.html") frag = Fragment(html.format(self=self)) frag.add_css(self.resource_string("static/css/officevideo.css")) frag.add_javascript(self.resource_string("static/js/src/officevideo_edit.js")) frag.initialize_js('OfficeVideoXBlock') return frag @XBlock.json_handler def studio_submit(self, submissions, suffix=''): # pylint: disable=unused-argument """ Change the settings for this XBlock given by the Studio user """ if not isinstance(submissions, dict): LOG.error("submissions object from Studio is not a dict - %r", submissions) return { 'result': 'error' } self.display_name = submissions['display_name'] self.video_url = submissions['video_url'] # Check if user have entered embed code embed_code_regex = '<iframe ' matched = re.match(embed_code_regex, self.video_url, re.IGNORECASE) if matched is not None: self.output_code = self.video_url else: self.output_code = '' self.message = "" self.message_display_state = "block" return {'result': 'success'} def get_officevideo_embed_code(self, officevideo_url): embed_code = '' try: django_user_social = User.objects.get(id=self.xmodule_runtime.user_id).social_auth.get(provider='azuread-oauth2') if int(django_user_social.extra_data['expires_on']) < int(time.time()): django_user_social.refresh_token(load_strategy()) django_user_social = User.objects.get(id=self.xmodule_runtime.user_id).social_auth.get(provider='azuread-oauth2') url = self.video_url parsed = urlparse.urlparse(url) query_params = urlparse.parse_qs(parsed.query) resp = requests.get("https://" + parsed.netloc + "/portals/hub/_api/VideoService/Channels('" + query_params['chid'][0] + "')/Videos('" + query_params['vid'][0] + "')/GetVideoEmbedCode", headers={'Authorization': 'Bearer ' + django_user_social.tokens, 'Content-Type': 'application/json;odata=verbose'}) root = ET.fromstring(resp._content) embed_code = unicode(root.text, "utf-8") except: embed_code = '<a target="_blank" href="'+ officevideo_url +'">Office 365 Video</a>' return embed_code @staticmethod def workbench_scenarios(): """A canned scenario for display in the workbench.""" return [ ("OfficeVideoXBlock", """<vertical_demo> <officevideo/> <officevideo/> </vertical_demo> """), ]

38.578035

284

0.657177

791

6,674

5.384324

0.353982

0.042263

0.025358

0.033811

0.251702

0.239493

0.179385

0.156844

0

0.026491

0.23644

6,674

172

285

38.802326

0.809262

0.067726

0

0.125

0

0.008333

0.234288

0.045556

0

1

0.05

false

0

0.141667

0

0.308333

0

null

0

null

0

1

0

da37fa1cf8aa9ced7ef291cee98575d2cbc3ace4

4,594

py

Python

stn/task.py

anenriquez/STNU

a02a13730cc0f31521e01e186c158533479090f5

[ "Unlicense" ]

null

stn/task.py

anenriquez/STNU

a02a13730cc0f31521e01e186c158533479090f5

[ "Unlicense" ]

null

stn/task.py

anenriquez/STNU

a02a13730cc0f31521e01e186c158533479090f5

[ "Unlicense" ]

null

from stn.utils.as_dict import AsDictMixin class Edge(AsDictMixin): def __init__(self, name, mean, variance, **kwargs): self.name = name self.mean = round(mean, 3) self.variance = round(variance, 3) self.standard_dev = round(variance ** 0.5, 3) def __str__(self): to_print = "" to_print += "{}: N({}, {})".format(self.name, self.mean, self.standard_dev) return to_print def __sub__(self, other): # Difference of two independent random variables mean = self.mean - other.mean variance = self.variance + other.variance return mean, variance def __add__(self, other): # Addition of two independent random variables mean = self.mean + other.mean variance = self.variance + other.variance return mean, variance class Timepoint(AsDictMixin): """ r_earliest_time (float): earliest time relative to a ztp r_latest_time (float): latest time relative to a ztp """ def __init__(self, name, r_earliest_time, r_latest_time, **kwargs): self.name = name self.r_earliest_time = round(r_earliest_time, 3) self.r_latest_time = round(r_latest_time, 3) def __str__(self): to_print = "" to_print += "{}: [{}, {}]".format(self.name, self.r_earliest_time, self.r_latest_time) return to_print class Task(AsDictMixin): def __init__(self, task_id, timepoints, edges, pickup_action_id, delivery_action_id): """ Constructor for the Task object Args: task_id (UUID): An instance of an UUID object timepoints (list): list of timepoints (Timepoints) Edges (list): list of edges (Edges) pickup_action_id (UUID): Action id of the pickup action delivery_action_id (UUID): Action id of te delivery action """ self.task_id = task_id self.timepoints = timepoints self.edges = edges self.pickup_action_id = pickup_action_id self.delivery_action_id = delivery_action_id def __str__(self): to_print = "" to_print += "{} \n".format(self.task_id) to_print += "Timepoints: \n" for timepoint in self.timepoints: to_print += str(timepoint) + "\t" to_print += "\n Edges: \n" for edge in self.edges: to_print += str(edge) + "\t" to_print += "\n Pickup action:" + str(self.pickup_action_id) to_print += "\n Delivery action:" + str(self.delivery_action_id) return to_print def get_timepoint(self, timepoint_name): for timepoint in self.timepoints: if timepoint.name == timepoint_name: return timepoint def get_edge(self, edge_name): for edge in self.edges: if edge.name == edge_name: return edge def update_timepoint(self, timepoint_name, r_earliest_time, r_latest_time=float('inf')): in_list = False for timepoint in self.timepoints: if timepoint.name == timepoint_name: in_list = True timepoint.r_earliest_time = r_earliest_time timepoint.r_latest_time = r_latest_time if not in_list: self.timepoints.append(Timepoint(timepoint_name, r_earliest_time, r_latest_time)) def update_edge(self, edge_name, mean, variance): in_list = False for edge in self.edges: if edge.name == edge_name: in_list = True edge.mean = round(mean, 3) edge.variance = round(variance, 3) edge.standard_dev = round(variance ** 0.5, 3) if not in_list: self.edges.append(Edge(name=edge_name, mean=mean, variance=variance)) def to_dict(self): dict_repr = super().to_dict() timepoints = list() edges = list() for t in self.timepoints: timepoints.append(t.to_dict()) for e in self.edges: edges.append(e.to_dict()) dict_repr.update(timepoints=timepoints) dict_repr.update(edges=edges) return dict_repr @classmethod def to_attrs(cls, dict_repr): attrs = super().to_attrs(dict_repr) timepoints = list() edges = list() for t in attrs.get("timepoints"): timepoints.append(Timepoint.from_dict(t)) for e in attrs.get("edges"): edges.append(Edge.from_dict(e)) attrs.update(timepoints=timepoints) attrs.update(edges=edges) return attrs

34.80303

94

0.60579

581

4,594

4.538726

0.137694

0.039818

0.044369

0.021236

0.372014

0.28176

0.265074

0.212363

0.174441

0

0.003706

0.295168

4,594

131

95

35.068702

0.810686

0.110797

0

0.360825

0

0.028557

0

1

0.14433

false

0

0.010309

0

0.278351

0.154639

0

null

0

null

0

1

0

da382dde5d81096600a758eea608666b31d3c7b7

2,959

py

Python

src/bxgateway/messages/btc/data_btc_message.py

blockchain-development-resources/bxgateway

761b5085f9c7c6527f0b9aaae06d2f70f3786db2

[ "MIT" ]

1

2021-11-26T07:49:24.000Z

src/bxgateway/messages/btc/data_btc_message.py

beepool/bxgateway

761b5085f9c7c6527f0b9aaae06d2f70f3786db2

[ "MIT" ]

null

src/bxgateway/messages/btc/data_btc_message.py

beepool/bxgateway

761b5085f9c7c6527f0b9aaae06d2f70f3786db2

[ "MIT" ]

1

2021-09-06T02:10:08.000Z

import struct from bxgateway.btc_constants import BTC_HDR_COMMON_OFF, BTC_SHA_HASH_LEN from bxgateway.messages.btc.btc_message import BtcMessage from bxgateway.messages.btc.btc_message_type import BtcMessageType from bxgateway.messages.btc.btc_messages_util import btc_varint_to_int, pack_int_to_btc_varint from bxgateway.utils.btc.btc_object_hash import BtcObjectHash class DataBtcMessage(BtcMessage): def __init__(self, magic=None, version=None, hashes=None, hash_stop=None, command=None, buf=None): if hashes is None: hashes = [] if buf is None: buf = bytearray(BTC_HDR_COMMON_OFF + 9 + (len(hashes) + 1) * 32) self.buf = buf off = BTC_HDR_COMMON_OFF struct.pack_into("<I", buf, off, version) off += 4 off += pack_int_to_btc_varint(len(hashes), buf, off) for hash_val in hashes: buf[off:off + 32] = hash_val.get_big_endian() off += 32 buf[off:off + 32] = hash_stop.get_big_endian() off += 32 BtcMessage.__init__(self, magic, command, off - BTC_HDR_COMMON_OFF, buf) else: self.buf = buf self._memoryview = memoryview(buf) self._magic = self._command = self._payload_len = self._checksum = None self._payload = None self._version = self._hash_count = self._hashes = self._hash_stop = None def version(self): if self._version is None: self._version, = struct.unpack_from("<I", self.buf, BTC_HDR_COMMON_OFF) return self._version def hash_count(self): if self._hash_count is None: off = BTC_HDR_COMMON_OFF + 4 self._hash_count, size = btc_varint_to_int(self.buf, off) return self._hash_count def __iter__(self): off = BTC_HDR_COMMON_OFF + 4 # For the version field. b_count, size = btc_varint_to_int(self.buf, off) off += size for i in range(b_count): yield BtcObjectHash(buf=self.buf, offset=off, length=BTC_SHA_HASH_LEN) off += 32 def hash_stop(self): return BtcObjectHash(buf=self.buf, offset=BTC_HDR_COMMON_OFF + self.payload_len() - 32, length=BTC_SHA_HASH_LEN) class GetHeadersBtcMessage(DataBtcMessage): MESSAGE_TYPE = BtcMessageType.GET_HEADERS def __init__(self, magic=None, version=None, hashes=None, hash_stop=None, buf=None): if hashes is None: hashes = [] super(GetHeadersBtcMessage, self).__init__(magic, version, hashes, hash_stop, self.MESSAGE_TYPE, buf) class GetBlocksBtcMessage(DataBtcMessage): MESSAGE_TYPE = BtcMessageType.GET_BLOCKS def __init__(self, magic=None, version=None, hashes=None, hash_stop=None, buf=None): if hashes is None: hashes = [] super(GetBlocksBtcMessage, self).__init__(magic, version, hashes, hash_stop, self.MESSAGE_TYPE, buf)

36.9875

120

0.657993

396

2,959

4.580808

0.184343

0.026461

0.052922

0.066152

0.481257

0.292172

0.233738

0.216648

0.180265

0

0.00857

0.25076

2,959

79

121

37.455696

0.809653

0.007435

0

0.254237

0

0.001363

0

1

0.118644

false

0

0.101695

0.016949

0.355932

0

null

0

null

0

1

0

da39df4b22e6c016cc25f0ba477072a025a6794f

8,188

py

Python

alexber/utils/_ymlparsers_extra.py

AndreyRub/AlexBerUtils

b2d79c98c083533534470b62632a36dfd730be48

[ "BSD-2-Clause" ]

null

alexber/utils/_ymlparsers_extra.py

AndreyRub/AlexBerUtils

b2d79c98c083533534470b62632a36dfd730be48

[ "BSD-2-Clause" ]

8

2019-12-15T05:13:27.000Z

2021-02-16T20:03:40.000Z

alexber/utils/_ymlparsers_extra.py

AndreyRub/AlexBerUtils

b2d79c98c083533534470b62632a36dfd730be48

[ "BSD-2-Clause" ]

2

2019-12-12T03:52:37.000Z

2021-05-21T21:14:34.000Z

""" This module adopts its behavior dependent on availability of Python packages. This module optionally depends on ymlparseser module. Method format_template() is used in emails module. Note: This module will work if you have only standard Python package. You just can't change delimiters values. Note: API and implementation of this module is unstable and can change without prior notice. """ import warnings def format_template(template, **kwargs): """ This is main method of this module. Note: API of this method is unstable and can change without prior notice. Template is expected to be compatible with Jinja2 one. Current implementation make delimiters compatible with str.format() and use it. :param template: str, typically with {{my_variable}} :param jinja2ctx: Jinja2 Environment that is consulted what is delimiter for variable's names. if is not provided, HiYaPyCo.jinja2ctx is used. See ymlparsers.initConfig(). if is not provided, than defaults are used (see jinja2.defaults). :param jinja2Lock: Lock to be used to atomically get variable_start_string and variable_end_string from jinja2ctx. if is not provided, HiYaPyCo.jinja2Lock is used.. See ymlparsers.initConfig(). :return: fromated str """ if template is None: return None s = _convert_template_to_string_format(template, **kwargs) ret = s.format(template, **kwargs) return ret try: with warnings.catch_warnings(): warnings.filterwarnings("ignore", message=r'.*?yaml*?', module=r'.*?ymlparsers.*?') from . ymlparsers import HiYaPyCo _isHiYaPyCoAvailable = True except ImportError: _isHiYaPyCoAvailable = False _a1 = None _a2 = None try: try: from jinja2.defaults import VARIABLE_START_STRING as _a1, VARIABLE_END_STRING as _a2 _isJinja2DefaultAvailable = True except ImportError: try: from jinja2.environment import VARIABLE_START_STRING as _a1, VARIABLE_END_STRING as _a2 _isJinja2DefaultAvailable = True except ImportError: _isJinja2DefaultAvailable = False finally: del _a1 del _a2 _VARIABLE_START_STRING = None _VARIABLE_END_STRING = None def _init_globals(): """ This method is called during module import. This method is idempotent. """ global _VARIABLE_START_STRING, _VARIABLE_END_STRING if _isJinja2DefaultAvailable: p1 = None p2 = None try: from jinja2.defaults import VARIABLE_START_STRING as p1, VARIABLE_END_STRING as p2 except ImportError: from jinja2.environment import VARIABLE_START_STRING as p1, VARIABLE_END_STRING as p2 if p1 is None or p2 is None: raise ImportError('VARIABLE_START_STRING or VARIABLE_END_STRING are not defined') _VARIABLE_START_STRING = p1 _VARIABLE_END_STRING = p2 else: _VARIABLE_START_STRING = '{{' _VARIABLE_END_STRING = '}}' _init_globals() def _normalize_var_name(text, start_del, end_del): """ Search&replace all pairs of (start_del, end_del) with pairs of ({, }). :param text: str to normalize :param start_del: delimiter that indicates start of variable name, typically {{ :param end_del: delimiter that indicates end of variable name, typically }} :return: """ if start_del is None or start_del not in text or end_del not in text: return text first_ind = 0 len_end_del = len(end_del) while True: first_ind = text.find(start_del, first_ind) if first_ind < 0: break last_ind = text.find(end_del, first_ind) var = text[first_ind:last_ind+len_end_del] var = var.replace('.', '_') #text[first_ind:last_ind] = var text = text[:first_ind]+var+text[last_ind+len_end_del:] first_ind = last_ind+len_end_del return text def __convert_template_to_string_format(template, **kwargs): """ This is utility method that make template usable with string format. :param template: str, typically with {{my_variable}} :param default_start: Typically {{ but can be any other delimiter that points to start of the token variable. :param default_end: Typically }} but can be any other delimiter that points to end of the token variable. :return: template: str with {my_variable} """ if template is None: return None default_start = kwargs.pop('default_start', None) default_end = kwargs.pop('default_end', None) template = _normalize_var_name(template, default_start, default_end) ret = template.replace(f'{default_start} ', f'{default_start}') \ .replace(f'{default_start}', '{') \ .replace(f' {default_end}', f'{default_end}') \ .replace(f'{default_end}', '}') return ret def _convert_template_to_string_format(template, **kwargs): """ This is utility method that make template usable with string format. if both jinja2ctx and jinja2Lock are provided, than they are used to determine various delimiters (jinja2Lock is used to read the values from jinja2ctx atomically). if both jinja2ctx and jinja2Lock are not provided, than If ymlparsers is usable (it's 3rd party dependencies are available, one if each is jinja2) than it's jinja2ctx (Jinja2's Environment) will be consulted for the various delimiters. Otherwise, if jinja2 is available than we will use it's defaults for constricting Jinja2's Environment for the various delimiters. Otherwise, some sensible defaults (default values from some version of Jinja2) will be used. You can't provide jinja2Lock without providing jinja2ctx (you can't provide your jinja2Lock for HiYaPyCo.jinja2ctx). You can provide jinja2ctx without jinja2Lock. Than you will give up atomicity for determining various delimiters. :param template: str, typically with {{my_variable}} :param jinja2ctx: Jinja2 Environment that is consulted what is delimiter for variable's names. if is not provided, HiYaPyCo.jinja2ctx is used. See ymlparsers.initConfig(). if is not provided, than defaults are used (see jinja2.defaults). :param jinja2Lock: Lock to be used to atomically get variable_start_string and variable_end_string from jinja2ctx. if is not provided, HiYaPyCo.jinja2Lock is used.. See ymlparsers.initConfig(). :return: template: str with {my_variable} """ if template is None: return None jinja2ctx = kwargs.pop('jinja2ctx', None) jinja2Lock = kwargs.pop('jinja2Lock', None) if _isHiYaPyCoAvailable and jinja2ctx is None and jinja2Lock is not None: raise ValueError("You can't provide your jinja2Lock for HiYaPyCo.jinja2ctx") if _isHiYaPyCoAvailable and jinja2ctx is None: jinja2ctx = HiYaPyCo.jinja2ctx jinja2Lock = HiYaPyCo.jinja2Lock #we should use HiYaPyCo.jinja2Lock for HiYaPyCo.jinja2ctx #default_start, default_end if jinja2ctx is None: if jinja2Lock is None: default_start = _VARIABLE_START_STRING default_end = _VARIABLE_END_STRING else: with jinja2Lock: default_start = _VARIABLE_START_STRING default_end = _VARIABLE_END_STRING else: if _isHiYaPyCoAvailable and HiYaPyCo.jinja2ctx is not None and HiYaPyCo.jinja2Lock is None: raise ValueError('HiYaPyCo.jinja2ctx is not None, but HiYaPyCo.jinja2Lock is None') if jinja2Lock is None: # jinja2ctx was provided, but jinja2Lock wasn't, it is ok # (maybe jinja2ctx is local variable?) default_start = jinja2ctx.variable_start_string default_end = jinja2ctx.variable_end_string else: with jinja2Lock: default_start = jinja2ctx.variable_start_string default_end = jinja2ctx.variable_end_string ret = __convert_template_to_string_format(template, default_start=default_start, default_end=default_end) return ret

38.261682

120

0.69553

1,052

8,188

5.230989

0.173954

0.035435

0.05179

0.016355

0.491914

0.463747

0.396329

0.379793

0.343812

0.318735

0

0.014947

0.240107

8,188

213

121

38.441315

0.869495

0.447606

0

0.365385

0

0.080886

0.004895

0

1

0.048077

false

0

0.105769

0

0.230769

0

null

0

null

0

1

0

da3bd0652c70b407476c6f160e8a128d0c51ee92

32

py

Python

pyglview/__init__.py

weltonrodrigo/python_glview

6680601aea5ae67ca8c5ccbf03847e6abc6f270c

[ "MIT" ]

6

2019-04-29T05:44:51.000Z

2022-01-28T15:31:57.000Z

pyglview/__init__.py

weltonrodrigo/python_glview

6680601aea5ae67ca8c5ccbf03847e6abc6f270c

[ "MIT" ]

1

2021-06-12T01:49:10.000Z

pyglview/__init__.py

weltonrodrigo/python_glview

6680601aea5ae67ca8c5ccbf03847e6abc6f270c

[ "MIT" ]

2

2019-12-16T20:34:59.000Z

2020-08-24T14:57:50.000Z

from pyglview.pyglview import *

16

31

0.8125

4

32

6.5

0.75

0

0.125

32

1

32

0.928571

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

da3c5141c6711e22ea8ee4bbbf6d8f4d99c372b5

163

py

Python

unused_stuff/save_image.py

JDJGInc/JDJGBotSupreme

fd8a5679f05cb90ebec8dbfc297445f9773ebe5f

[ "MIT" ]

4

2020-07-10T04:02:23.000Z

2021-02-13T16:38:54.000Z

unused_stuff/save_image.py

JDJGInc/JDJGBotSupreme

fd8a5679f05cb90ebec8dbfc297445f9773ebe5f

[ "MIT" ]

3

2021-07-13T15:38:39.000Z

2022-02-15T15:17:17.000Z

unused_stuff/save_image.py

johndpope/JDJGBotSupreme

64fde0e169811e1866eb29174ac5dd8e052d830a

[ "MIT" ]

2

2020-08-01T11:15:09.000Z

2022-02-15T11:46:22.000Z

async with aiohttp.ClientSession() as cs: async with cs.get(url) as r: image=await r.read() f = open("reverse.png","wb") f.write(image) f.close()

27.166667

41

0.625767

27

163

3.777778

0.703704

0.176471

0

0.208589

163

6

42

27.166667

0.790698

0

0.079268

0

1

0

false

0

1

0

null

0

1

0

null

0

2

da3cdf32ec5c491bbbd379b8659c9adccf3080ca

2,653

py

Python

models/house_water_drain.py

susundberg/python-freecad-3dparts

248e6f5eb4ce3d1921b3d4875e9c1d112f7b7498

[ "MIT" ]

null

models/house_water_drain.py

susundberg/python-freecad-3dparts

248e6f5eb4ce3d1921b3d4875e9c1d112f7b7498

[ "MIT" ]

null

models/house_water_drain.py

susundberg/python-freecad-3dparts

248e6f5eb4ce3d1921b3d4875e9c1d112f7b7498

[ "MIT" ]

null

import supalib TOLE=0.2 OUTSIZE=60.0 SIZE_CONST=25.0 SIZE_DROP=20.0 ANGLE_DROP=45.0 BASE_THICK=5.0 BASE_WIDE=20.0 PIPE_RAD=OUTSIZE/2.0 + TOLE hole = supalib.create_cyl( radius=PIPE_RAD , size_z = OUTSIZE, place=(0, PIPE_RAD + 1.0, -OUTSIZE/2.0) ) outer_hole = supalib.create_cyl( radius=PIPE_RAD + 5.0 , size_z = OUTSIZE, place=(0, PIPE_RAD + 5.0, -OUTSIZE/2.0) ) tr1 = supalib.create_triangle( SIZE_DROP, BASE_THICK, BASE_WIDE/2.0 ) tr2 = supalib.create_triangle( SIZE_DROP, BASE_THICK, BASE_WIDE/2.0,rotate=(1,0,0,180),place=(0,+BASE_THICK,0) ) drop = supalib.create_union( (tr1, tr2) ) drop = supalib.relocate( drop, rotate=(0,1,0,90) ) drop = supalib.create_cut( drop, hole ) drop = supalib.relocate( drop, rotate=(1,0,0,30) ) drop = supalib.relocate( drop, place=(0,0,SIZE_CONST + SIZE_DROP ) ) drop = supalib.relocate( drop, place=(0,-9,-1) ) base = supalib.create_box( (BASE_WIDE,BASE_THICK,SIZE_CONST + 4.0), place = ( -BASE_WIDE/2.0,0.0,0.0) ) base = supalib.create_intersection( ( base, outer_hole ) ) base = supalib.create_union( ( base, drop ) ) base = supalib.create_cut( base, hole ) base.Label="house_drain" holder_rad = PIPE_RAD + 0.5 + TOLE HOLDER_SIZE=5.0 outer_hole2 = supalib.create_cyl( radius=holder_rad , size_z = HOLDER_SIZE, place=(0, 0, 0) ) outer_hole3 = supalib.create_cyl( radius=holder_rad + 1.0 , size_z = HOLDER_SIZE, place=(0, 0, 0) ) outer_holder = supalib.create_cut( outer_hole3, outer_hole2 ) outer_holder = supalib.relocate( outer_holder, place=(0,+holder_rad,0) ) outer_holder.Label="house_holder" thight = supalib.create_box( (BASE_WIDE,BASE_THICK,10), place = ( -BASE_WIDE/2.0,0.0,0.0) ) thight = supalib.create_cut( thight, hole ) thight = supalib.create_intersection( ( thight, outer_hole ) ) thight = supalib.relocate( thight, rotate=(0,0,1,180), place=(0,2*holder_rad,0) ) thight.Label = "house_wedge" parts = [ thight, outer_holder, base ] for p in parts: supalib.creta_mesh_from( p, save_to="/home/pauli/", version=3 ) #hole_app = supalib.create_box( (0.5,0.25 + TOLE,5.0) , place=(offset - 0.25, 5.0 - rad_size/2.0 - 2*TOLE, 2.5 ) ) #offset += rad_size + RADS[loop+1] + 2.0 #holes.append(hole) #hole_adds.append( hole_app ) #holes = supalib.create_union( holes ) #hole_adds = supalib.create_union( hole_adds ) #box_bound = supalib.create_box( (offset, 10.0, 10 ) ) #box_bound = supalib.create_fillet( box_bound ) #box_bound = supalib.create_cut( box_bound, holes ) #box_bound = supalib.create_union( (box_bound,hole_adds) ) #box_bound.Label="Tool_holder" #mesh = supalib.creta_mesh_from( box_bound, save_to="/home/pauli/", version=1 ) supalib.finish()

35.851351

119

0.710516

449

2,653

3.973274

0.167038

0.167601

0.013453

0.049327

0.33296

0.275785

0.20852

0.106502

0.053812

0

0.058185

0.131926

2,653

73

120

36.342466

0.716457

0.223897

0

0.022483

0

1

0

false

0

0.025

0

0.025

0

null

0

null

0

1

0

da3d14bdecf4a0d019902eff7b7a5c16a38e1ceb

2,434

py

Python

privatebin.py

iomintz/python-snippets

982861c173bf4bcd5d908514a9e8b1914a580a5d

[ "CC0-1.0" ]

2

2020-04-10T07:29:56.000Z

2020-05-27T03:45:21.000Z

privatebin.py

LyricLy/python-snippets

9d868b7bbccd793ea1dc513f51290963584a1dee

[ "CC0-1.0" ]

null

privatebin.py

LyricLy/python-snippets

9d868b7bbccd793ea1dc513f51290963584a1dee

[ "CC0-1.0" ]

2

2018-11-24T08:16:59.000Z

2019-02-24T04:41:30.000Z

#!/usr/bin/env python3 # encoding: utf-8 """ privatebin.py: uploads text to privatebin using code from <https://github.com/r4sas/PBinCLI/blob/master/pbincli/actions.py>, © 2017–2018 R4SAS <r4sas@i2pmail.org> using code from <https://github.com/khazhyk/dango.py/blob/master/dango/zerobin.py>, © 2017 khazhyk """ import asyncio import base64 import json import os import sys import zlib import aiohttp from sjcl import SJCL def encrypt(text): key = base64.urlsafe_b64encode(os.urandom(32)) # Encrypting text encrypted_data = SJCL().encrypt(compress(text.encode('utf-8')), key, mode='gcm') return encrypted_data, key def compress(s: bytes): co = zlib.compressobj(wbits=-zlib.MAX_WBITS) b = co.compress(s) + co.flush() return base64.b64encode(''.join(map(chr, b)).encode('utf-8')) def make_payload(text): # Formatting request request = dict( expire='never', formatter='plaintext', burnafterreading='0', opendiscussion='0', ) cipher, key = encrypt(text) # TODO: should be implemented in upstream for k in ['salt', 'iv', 'ct']: cipher[k] = cipher[k].decode() request['data'] = json.dumps(cipher, ensure_ascii=False, indent=None, default=lambda x: x.decode('utf-8')) return request, key lock = asyncio.Lock() class PrivateBinException(Exception): pass async def upload(text, loop=None): loop = loop or asyncio.get_event_loop() await lock.acquire() result = None payload, key = await loop.run_in_executor(None, make_payload, text) python_version = '.'.join(map(str, sys.version_info[:3])) async with aiohttp.ClientSession(headers={ 'User-Agent': 'privatebin.py/0.0.2 aiohttp/%s python/%s' % (aiohttp.__version__, python_version), 'X-Requested-With': 'JSONHttpRequest' }) as session: for tries in range(2): async with session.post('https://privatebin.net/', data=payload) as resp: resp_json = await resp.json() if resp_json['status'] == 0: result = url(resp_json['id'], key) break elif resp_json['status'] == 1: # rate limited await asyncio.sleep(10) lock.release() if result is None: raise PrivateBinException('Failed to upload to privatebin') else: return result def url(paste_id, key): return 'https://privatebin.net/?%s#%s' % (paste_id, key.decode('utf-8')) if __name__ == '__main__': import contextlib loop = asyncio.get_event_loop() with closing(asyncio.get_event_loop()) as loop: print(loop.run_until_complete(upload(sys.stdin.read())))

26.747253

107

0.711586

356

2,434

4.766854

0.457865

0.011786

0.026517

0.033589

0.031821

0

0.021408

0.136401

2,434

90

108

27.044444

0.784491

0.158998

0

0.116519

0

0.011111

0

1

0.067797

false

0.016949

0.152542

0.016949

0.322034

0.016949

0

null

0

null

0

1

0

1

da3d5161d87de56a9bc36edca5bba5b60b08bd39

6,556

py

Python

dace/libraries/standard/nodes/gearbox.py

thobauma/dace

668e4c49e476437e1ea3b272e9dbefca2b92d2e7

[ "BSD-3-Clause" ]

null

dace/libraries/standard/nodes/gearbox.py

thobauma/dace

668e4c49e476437e1ea3b272e9dbefca2b92d2e7

[ "BSD-3-Clause" ]

null

dace/libraries/standard/nodes/gearbox.py

thobauma/dace

668e4c49e476437e1ea3b272e9dbefca2b92d2e7

[ "BSD-3-Clause" ]

null

# Copyright 2019-2021 ETH Zurich and the DaCe authors. All rights reserved. import collections import copy import dace @dace.library.expansion class ExpandGearbox(dace.transformation.ExpandTransformation): environments = [] @staticmethod def expansion(node: "Gearbox", parent_state: dace.SDFGState, parent_sdfg: dace.SDFG): (in_edge, in_desc, out_edge, out_desc, is_pack, gear_factor) = node.validate(parent_sdfg, parent_state) if is_pack: vtype = out_desc.dtype else: vtype = in_desc.dtype sdfg = dace.SDFG("gearbox") in_desc_inner = copy.deepcopy(in_desc) in_desc_inner.transient = False sdfg.add_datadesc(in_edge.dst_conn, in_desc_inner) out_desc_inner = copy.deepcopy(out_desc) out_desc_inner.transient = False sdfg.add_datadesc(out_edge.src_conn, out_desc_inner) sdfg.add_array("gearbox_buffer", (1, ), vtype, storage=in_desc.storage, transient=True) state = sdfg.add_state("gearbox") buffer_read = state.add_read("gearbox_buffer") buffer_write = state.add_write("gearbox_buffer") input_read = state.add_read(in_edge.dst_conn) output_write = state.add_write(out_edge.src_conn) iteration_space = { "_gearbox_i": f"0:{node.size}", "_gearbox_w": f"0:{gear_factor}" } entry, exit = state.add_map("gearbox", iteration_space, schedule=node.schedule) tasklet = state.add_tasklet( "gearbox", { "val_in", "buffer_in" }, { "val_out", "buffer_out" }, f"""\ wide = buffer_in wide[_gearbox_w] = val_in if _gearbox_w == {gear_factor} - 1: val_out = wide buffer_out = wide""" if is_pack else """\ wide = val_in if _gearbox_w == 0 else buffer_in val_out = wide[_gearbox_w] buffer_out = wide""") state.add_memlet_path(input_read, entry, tasklet, dst_conn="val_in", memlet=dace.Memlet(f"{in_edge.dst_conn}[0]", dynamic=not is_pack)) state.add_memlet_path(buffer_read, entry, tasklet, dst_conn="buffer_in", memlet=dace.Memlet(f"gearbox_buffer[0]")) state.add_memlet_path(tasklet, exit, output_write, src_conn="val_out", memlet=dace.Memlet(f"{out_edge.src_conn}[0]", dynamic=is_pack)) state.add_memlet_path(tasklet, exit, buffer_write, src_conn="buffer_out", memlet=dace.Memlet(f"gearbox_buffer[0]")) return sdfg @dace.library.node class Gearbox(dace.sdfg.nodes.LibraryNode): """ Provides a library node that converts from a stream of type vector(vector(dtype, w0)) to a stream of type vector(dtype, w1), or vice versa. This is useful for achieving efficient memory reads on Xilinx FPGAs, where modules accessing memories should always read or write 512-bit vectors, which then potentially need to be narrowed down to the vector width of the computational kernel. The node expects to have a single input and a single output, where one end is of type vector(vector(dtype, w0)), and the other is of type vector(dtype, w1). """ implementations = { "pure": ExpandGearbox, } default_implementation = "pure" # Properties size = dace.properties.SymbolicProperty( desc="Number of wide vectors to convert to/from narrow vectors.", default=0) def __init__(self, size, name=None, schedule=None, **kwargs): """ :param size: Number of wide vectors to convert to/from narrow vectors. For example, if converting n/16 reads (vector size 16) from memory into n/4 elements (vector size 4), this parameter should be set to n/16. """ super().__init__(name=name or "gearbox", schedule=schedule or dace.ScheduleType.FPGA_Device, **kwargs) self.size = size if schedule is not None: self.schedule = schedule def validate(self, sdfg: dace.SDFG, state: dace.SDFGState): try: size = dace.symbolic.evaluate(self.size, sdfg.constants) if size < 1: raise ValueError(f"Invalid size parameter for {self}: {size}") except TypeError: pass # Not a constant in_edge = state.in_edges(self) if len(in_edge) != 1: raise ValueError( f"Expected only one input edge, found {len(in_edge)} edges.") out_edge = state.out_edges(self) if len(out_edge) != 1: raise ValueError( f"Expected only one input edge, found {len(out_edge)} edges.") in_edge = in_edge[0] in_desc = sdfg.arrays[in_edge.data.data] if not isinstance(in_desc, dace.data.Stream): raise TypeError( f"Expected input to be a stream, got {type(in_desc)}.") out_edge = out_edge[0] out_desc = sdfg.arrays[out_edge.data.data] if not isinstance(out_desc, dace.data.Stream): raise TypeError( f"Expected input to be a stream, got {type(out_desc)}.") # The type of one side must be a vector of the other if (isinstance(in_desc.dtype, dace.vector) and in_desc.dtype.base_type == out_desc.dtype): is_pack = False # Is unpack gear_factor = in_desc.dtype.veclen elif (isinstance(out_desc.dtype, dace.vector) and out_desc.dtype.base_type == in_desc.dtype): is_pack = True gear_factor = out_desc.dtype.veclen else: raise TypeError( f"Cannot gearbox between {in_desc.dtype} and {out_desc.dtype}.") return (in_edge, in_desc, out_edge, out_desc, is_pack, gear_factor)

39.257485

80

0.558115

783

6,556

4.466156

0.240102

0.027452

0.020589

0.278524

0.212182

0.157278

0.117815

0

0.008975

0.354179

6,556

166

81

39.493976

0.816958

0.145363

0

0.130769

0

0.157703

0.007813

0

1

0.023077

false

0.007692

0.023077

0

0.107692

0

null

0

null

0

1

0

da3fd113ae5463775113a2aa795b9fc22645ae0c

5,662

py

Python

reprlearn/data/samplers/kshot_sampler.py

cocoaaa/ReprLearn

58dc682aa62dbd59201ccc55b9b26480ff3d6773

[ "MIT" ]

null

reprlearn/data/samplers/kshot_sampler.py

cocoaaa/ReprLearn

58dc682aa62dbd59201ccc55b9b26480ff3d6773

[ "MIT" ]

null

reprlearn/data/samplers/kshot_sampler.py

cocoaaa/ReprLearn

58dc682aa62dbd59201ccc55b9b26480ff3d6773

[ "MIT" ]

null

from reprlearn.data.datasets.base import ImageDataset from collections import defaultdict from typing import Iterable, Optional, Callable, List, Dict, Tuple import numpy as np # =============== # Returns a list of datapoints from the dataset so that # the list contains the same number of datapoints per class (if possible) # =============== class KShotSampler(): def __init__(self, shuffle:bool=True) -> None: """Given the dataset of labelled images, return the indices for sampling the same number of datapts per class for each class the dataset's targets. If shuffle, we shuffle the indices of the dataset before collecting the datapoints. Args ---- dset : ImageDataset k_shot: int number of images per class shuffle : bool (default True) """ pass def get_sample_inds_per_class(self, dset: ImageDataset, num_per_class: int, shuffle: bool=True, verify: bool=True, ): """Given the dataset of labelled images, return the indices for sampling `num_per_class` number of images per class in the dataset's classes. If shuffle, we shuffle the indices of the dset for each call to the iterator Returns: (List[int]) : indices to the datapts to sample for this iteration """ unique_classes = np.unique(dset.targets) n_ways = len(unique_classes) if num_per_class * n_ways > len(dset.targets): raise ValueError inds = list(range(len(dset))) if shuffle: np.random.shuffle(inds) # shuffle in-place inds_per_class = {c:[] for c in unique_classes} done_for_class = {c:False for c in unique_classes} for i in inds: c = dset.targets[i] if not done_for_class[c]: # len(inds_per_class[c]) < num_per_class: inds_per_class[c].append(i) if len(inds_per_class[c]) == num_per_class: done_for_class[c] = True # done collecting dpts for this class if np.alltrue(np.fromiter(done_for_class.values(), dtype=bool)): break print("Done collecting datapts for each class...") if verify: for c in np.unique(dset.targets): inds = inds_per_class[c] if len(inds) != num_per_class: raise ValueError return inds_per_class def sample(self, dset: ImageDataset, num_per_class: int, shuffle: bool=True, collate_fn: Optional[Callable]=None ) -> List[Tuple]: # [(x,y),...] #List[int]: """Given the dataset of labelled images, return the collection/list of datapoints from the dataset; the collection of datapoints (aka. sample) contains equal number of datapoints per class (with best effort) Args ---- dset : ImageDataset source dataset to sample datapoints from num_per_class : int k in k-shot shuffle : bool if shuffle, shuffle the indices of the dataset before collecting the datapoints collate_fn : Callable Similar to the collating function in torch's DataLoader argument; It take a list of datapoints and apply it to turn the list into a desired form of 'batch' Returns: (Batch or List[datapts]) : A collection of datapts sampled """ inds_per_class = self.get_sample_inds_per_class(dset, num_per_class, shuffle) sample_inds = np.stack( [np.fromiter(ilist, dtype=int) for ilist in inds_per_class.values()] ).flatten() # we don't want to load imgs for one-class all in a row, # and then next class's images in a row, etc np.random.shuffle(sample_inds) sample = [dset[i] for i in sample_inds] # apply current dataset's image transform if specified if collate_fn is not None: sample = collate_fn(sample) return sample def get_support_and_query( self, dset: ImageDataset, num_per_class: int, shuffle: bool=True, collate_fn: Optional[Callable] = None ) -> Dict: inds_per_class = self.get_sample_inds_per_class(dset, 2*num_per_class, shuffle) n_way = len(np.unique(dset.targets)) support_inds = [] query_inds = [] for clabel, cinds in inds_per_class.items(): cids = np.fromiter(cinds, dtype=int) support_inds.append(cids[:num_per_class]) query_inds.append(cinds[num_per_class:]) support_inds = np.array(support_inds) query_inds = np.array(query_inds) # we don't want to load imgs for one-class all in a row, # and then next class's images in a row, etc np.random.shuffle(support_inds) support_sample = [dset[i] for i in support_inds] # apply current dataset's image transform if specified if collate_fn is not None: support_sample = collate_fn(support_sample) # Similarly for the query sample np.random.shuffle(query_inds) query_sample = [dset[i] for i in query_inds] # apply current dataset's image transform if specified if collate_fn is not None: query_sample = collate_fn(query_sample) return {'support': support_sample, 'query': query_sample}

39.048276

112

0.598905

733

5,662

4.472033

0.210096

0.075656

0.04759

0.019829

0.397804

0.350519

0.316657

0.274558

0

0.000261

0.32409

5,662

144

113

39.319444

0.856284

0.347051

0

0.202532

0

0.01575

0

1

0.050633

false

0.012658

0.050633

0

0.151899

0.012658

0

null

0

null

0

1

0

da40b32e1d6bf126d545d746d9c0416f4eb38e0a

7,117

py

Python

phaseprep/workflows/preprocess_phase_wf.py

ostanley/phaseprep

6e721ea43755f10eb8569b1f4d4461efa3d85a1a

[ "Apache-2.0" ]

1

2019-10-11T17:04:25.000Z

phaseprep/workflows/preprocess_phase_wf.py

ostanley/phaseprep

6e721ea43755f10eb8569b1f4d4461efa3d85a1a

[ "Apache-2.0" ]

2

2019-10-16T13:13:52.000Z

2019-12-10T19:38:39.000Z

phaseprep/workflows/preprocess_phase_wf.py

ostanley/phaseprep

6e721ea43755f10eb8569b1f4d4461efa3d85a1a

[ "Apache-2.0" ]

2

2019-11-18T19:21:44.000Z

2021-10-19T18:01:03.000Z

import nipype.pipeline.engine as pe import nipype.interfaces.fsl as fsl import nipype.interfaces.afni as afni import phaseprep.interfaces as pp import nipype.interfaces.utility as ul def findscalingarg(in_file, bit_depth=12): import nibabel as nb import numpy as np img = nb.load(in_file) if img.dataobj.slope != 1.0: print('Removing rescale before conversion') mul = np.pi/(2**(bit_depth-1)*img.dataobj.slope) sub = np.pi*((img.dataobj.slope+1)/(2**(bit_depth-1)*img.dataobj.slope)) return '-mul %s -sub %s' % (mul, sub) def create_preprocess_phase_wf(): """Create's phase preprocessing workflow with the following steps: 1) Convert data to float 2) Determine scaling required for radians 3) Apply radian scaling 4) Convert to real and imaginary 5) Apply magnitude motion correction parameters 6) Correct geometry changes (AFNI issue) 7) Convert back to phase 8) Unwrap and detrend data 9) Mask data using magnitude mask 10) Calculate noise from data """ preprocphase = pe.Workflow(name="preprocphase") preprocphase.config['execution']['remove_unnecessary_outputs'] = False # define inputs inputspec = pe.Node(ul.IdentityInterface(fields=['input_phase', # raw phase data 'input_mag', # raw mag data 'motion_par', # afni transform concatenated from magnitude data 'mask_file', # bet mask from magnitude data 'rest', # volumes of rest in block design 'task', # volumes of task in block design ]), name='inputspec') # 1) Convert data to float img2float = pe.MapNode(interface=fsl.ImageMaths(out_data_type='float', op_string='', suffix='_dtype'), iterfield=['in_file'], name='img2float') # 2) Determine radian scaling required findscaling = pe.MapNode(interface=ul.Function(input_names=['in_file'], output_names=['scaling_arg'], function=findscalingarg), name='findscaling', iterfield=['in_file']) # 3) Apply radian scaling convert2rad = pe.MapNode(interface=fsl.maths.MathsCommand(), name='convert2rad', iterfield=['in_file', 'args']) # 4) Convert to real and imaginary (2 step process) # modified from fslcomplex to fslmaths in Sep 2020, bonus also preserves geometry info convert2real = pe.MapNode(interface=fsl.maths.MultiImageMaths(op_string=' -cos -mul %s'), name='convert2real', iterfield=['in_file','operand_files']) convert2imag = pe.MapNode(interface=fsl.maths.MultiImageMaths(op_string=' -sin -mul %s'), name='convert2imag', iterfield=['in_file','operand_files']) # 5) Apply magnitude motion correction parameters mocoreal = pe.MapNode(interface=afni.Allineate(), name='mocoreal', iterfield=['in_file', 'in_matrix']) mocoreal.inputs.outputtype = 'NIFTI_GZ' mocoreal.inputs.out_file = 'mocophase.nii.gz' mocoreal.inputs.num_threads = 2 mocoimag = mocoreal.clone('mocoimag') # 6) Correct geometry changes (AFNI issue) cpgeommocoreal = pe.MapNode(interface=fsl.CopyGeom(), name='cpgeommoco', iterfield=['dest_file', 'in_file']) cpgeommocoimag = cpgeommocoreal.clone('cpgeommocoimag') # 7) Convert back to phase custom interface to use atan2 and avoid sign ambiguity convert2phase = pe.MapNode(interface=pp.Convert2Phase(), name='convert2phase', iterfield=['real_image','imaginary_image']) # 8) Remove first volume, unwrap and detrend phase data prepphase = pe.MapNode(interface=pp.PreprocessPhase(), name='prepphase', iterfield=['phase']) # 9) Mask data using magnitude mask maskfunc = pe.MapNode(interface=fsl.ImageMaths(suffix='_bet', op_string='-mas'), iterfield=['in_file'], name='maskfunc') # 10) Calculate noise from data calcSNR = pe.MapNode(interface=pp.RestAverage(), name='calcSNR', iterfield=['func', 'rest', 'task']) # outputspec outputspec = pe.Node(ul.IdentityInterface(fields=['proc_phase', 'uw_phase', 'delta_phase','std_phase']), name='outputspec') preprocphase = pe.Workflow(name='preprocphase') preprocphase.connect([(inputspec, img2float, [('input_phase', 'in_file')]), # 1 (inputspec, findscaling, [('input_phase', 'in_file')]), # 2 (findscaling, convert2rad, [('scaling_arg', 'args')]), (img2float, convert2rad, [('out_file', 'in_file')]), (convert2rad, convert2real, [('out_file', 'in_file')]), (convert2rad, convert2imag, [('out_file', 'in_file')]), (inputspec, convert2real, [('input_mag', 'operand_files')]), (inputspec, convert2imag, [('input_mag', 'operand_files')]), (inputspec, mocoreal, [('motion_par', 'in_matrix')]), # 5 real (convert2real, mocoreal, [('out_file', 'in_file')]), (mocoreal, cpgeommocoreal, [('out_file','dest_file')]), #6 real (img2float, cpgeommocoreal, [('out_file', 'in_file')]), (inputspec, mocoimag, [('motion_par', 'in_matrix')]), # 5 imag (convert2imag, mocoimag, [('out_file', 'in_file')]), (mocoimag, cpgeommocoimag, [('out_file','dest_file')]), # 6 imag (img2float, cpgeommocoimag, [('out_file', 'in_file')]), (cpgeommocoimag, convert2phase, [('out_file', 'imaginary_image')]), # 7 (cpgeommocoreal, convert2phase, [('out_file', 'real_image')]), (convert2phase, prepphase, [('phase_image', 'phase')]), # 8 (prepphase, maskfunc, [('detrended_phase', 'in_file')]), # 9 (inputspec, maskfunc, [('mask_file', 'in_file2')]), (maskfunc, outputspec, [('out_file', 'proc_phase')]), (prepphase, outputspec, [('uw_phase', 'uw_phase')]), (prepphase, outputspec, [('delta_phase', 'delta_phase')]), (inputspec, calcSNR, [('rest', 'rest'), # 10 ('task', 'task')]), (prepphase, calcSNR, [('detrended_phase', 'func')]), (calcSNR, outputspec, [('noise', 'std_phase')]) ]) return preprocphase if __name__ == "__main__": workflow = create_preprocess_phase_wf()

53.511278

153

0.559646

701

7,117

5.53067

0.28388

0.032499

0.05107

0.023472

0.269796

0.128966

0.038174

0.025277

0

0.015925

0.311789

7,117

132

154

53.916667

0.775623

0.159618

0

0.023256

0

0.179292

0.004406

0

1

0.023256

false

0

0.081395

0

0.127907

0.011628

0

null

0

null

0

1

0

da426e6fadffb074142a9d08e0b642ab357e46fc

2,514

py

Python

zorg/buildbot/builders/AnnotatedBuilder.py

DalavanCloud/zorg

d55f03740e589d504dbfe2d5dc9fbc5d551f31fb

[ "Apache-2.0" ]

1

2019-02-10T03:05:05.000Z

zorg/buildbot/builders/AnnotatedBuilder.py

DalavanCloud/llvm-zorg

14d347a312d5a19bec421f553a3c1cbe1735b273

[ "Apache-2.0" ]

null

zorg/buildbot/builders/AnnotatedBuilder.py

DalavanCloud/llvm-zorg

14d347a312d5a19bec421f553a3c1cbe1735b273

[ "Apache-2.0" ]

null

import os import buildbot from buildbot.process.properties import WithProperties from buildbot.steps.shell import SetProperty, ShellCommand from buildbot.steps.source import SVN from zorg.buildbot.commands.AnnotatedCommand import AnnotatedCommand from zorg.buildbot.process.factory import LLVMBuildFactory def getAnnotatedBuildFactory( script, clean=False, depends_on_projects=None, env=None, timeout=1200): """ Returns a new build factory that uses AnnotatedCommand, which allows the build to be run by version-controlled scripts that do not require a buildmaster restart to update. """ f = LLVMBuildFactory( depends_on_projects=depends_on_projects, llvm_srcdir='llvm.src') if clean: f.addStep(SetProperty(property='clean', command='echo 1')) # We normally use the clean property to indicate that we want a # clean build, but AnnotatedCommand uses the clobber property # instead. Therefore, set clobber if clean is set to a truthy # value. This will cause AnnotatedCommand to set # BUILDBOT_CLOBBER=1 in the environment, which is how we # communicate to the script that we need a clean build. f.addStep(SetProperty( property='clobber', command='echo 1', doStepIf=lambda step: step.build.getProperty('clean', False))) merged_env = { 'TERM': 'dumb' # Be cautious and disable color output from all tools. } if env is not None: # Overwrite pre-set items with the given ones, so user can set # anything. merged_env.update(env) scripts_dir = "annotated" f.addStep(SVN(name='update-annotate-scripts', mode='update', svnurl='http://llvm.org/svn/llvm-project/zorg/trunk/' 'zorg/buildbot/builders/annotated', workdir=scripts_dir, alwaysUseLatest=True)) # Explicitly use '/' as separator, because it works on *nix and Windows. script_path = "../%s/%s" % (scripts_dir, script) f.addStep(AnnotatedCommand(name="annotate", description="annotate", timeout=timeout, haltOnFailure=True, command=WithProperties( "python %(script)s --jobs=%(jobs:-)s", script=lambda _: script_path), env=merged_env)) return f

36.970588

78

0.622514

285

2,514

5.431579

0.477193

0.020672

0.032946

0.034884

0

0.00395

0.295147

2,514

67

79

37.522388

0.869639

0.280827

0

0.122817

0.030986

0

1

0.022727

false

0

0.159091

0

0.204545

0

null

0

null

0

1

0

da43c8aa3780e6b294ec06869cbcdecb77cd3961

196

py

Python

ex001 a ex114/ex008.py

kesia-barros/exercicios-python

12a019e61c4b29fa29803f394b15d0af304c2ff0

[ "MIT" ]

null

ex001 a ex114/ex008.py

kesia-barros/exercicios-python

12a019e61c4b29fa29803f394b15d0af304c2ff0

[ "MIT" ]

null

ex001 a ex114/ex008.py

kesia-barros/exercicios-python

12a019e61c4b29fa29803f394b15d0af304c2ff0

[ "MIT" ]

null

m = float(input("Digite os metros a serem convertidos: ")) c = 100 * m mm = 1000 * m print("{} metros tem {:.0f} centimetros!".format(m, c)) print("{} metros tem {:.0f} milimetros!".format(m, mm))

39.2

58

0.632653

31

196

4

0.612903

0.048387

0.225806

0.258065

0

0.054217

0.153061

196

5

59

39.2

0.692771

0

0.522843

0

1

0

false

0

0.4

0

null

0

1

0

1

0

null

0

3

da44b530cb372e0a45fbccf1c2f6a0b2f6789174

511

py

Python

oscar/shared/economy.py

Xaxetrov/OSCAR

f3a264e2bc7d4253756b11b0dbaa58c4f9ea82a6

[ "Apache-2.0" ]

5

2017-10-11T18:08:13.000Z

2018-06-11T09:23:03.000Z

oscar/shared/economy.py

Xaxetrov/OSCAR

f3a264e2bc7d4253756b11b0dbaa58c4f9ea82a6

[ "Apache-2.0" ]

2

2018-04-18T16:25:20.000Z

2019-04-26T14:49:52.000Z

oscar/shared/economy.py

Xaxetrov/OSCAR

f3a264e2bc7d4253756b11b0dbaa58c4f9ea82a6

[ "Apache-2.0" ]

null

class Economy: """ Stores economic state """ def __init__(self): self.supply_depots = [] self.command_centers = [] self.scv = 8 def add_supply_depot(self, obs, shared, location): location.compute_minimap_loc(obs, shared) self.supply_depots.append(location) def add_command_center(self, obs, shared, location): location.compute_minimap_loc(obs, shared) self.command_centers.append(location) def add_scv(self): self.scv += 1

26.894737

56

0.645793

62

511

5.048387

0.403226

0.115016

0.102236

0.134185

0.376997

0

0.005208

0.248532

511

18

57

28.388889

0.809896

0.041096

0

0.153846

0

1

0.307692

false

0

0.384615

0

null

0

null

0

1

0

1

da45407cbca582a2a771bd09b1b4379b9b0b026a

10,818

py

Python

tcga_encoder/analyses/old/survival_from_z_space3.py

tedmeeds/tcga_encoder

805f9a5bcc422a43faea45baa0996c88d346e3b4

[ "MIT" ]

2

2017-12-19T15:32:46.000Z

2018-01-12T11:24:24.000Z

tcga_encoder/analyses/old/survival_from_z_space3.py

tedmeeds/tcga_encoder

805f9a5bcc422a43faea45baa0996c88d346e3b4

[ "MIT" ]

null

tcga_encoder/analyses/old/survival_from_z_space3.py

tedmeeds/tcga_encoder

805f9a5bcc422a43faea45baa0996c88d346e3b4

[ "MIT" ]

null

from tcga_encoder.utils.helpers import * from tcga_encoder.data.data import * from tcga_encoder.definitions.tcga import * #from tcga_encoder.definitions.nn import * from tcga_encoder.definitions.locations import * #from tcga_encoder.algorithms import * import seaborn as sns from sklearn.manifold import TSNE, locally_linear_embedding import lifelines from lifelines import CoxPHFitter from lifelines.datasets import load_regression_dataset from lifelines.utils import k_fold_cross_validation from lifelines import KaplanMeierFitter from lifelines.statistics import logrank_test, multivariate_logrank_test def main( data_location, results_location ): data_path = os.path.join( HOME_DIR ,data_location ) #, "data.h5" ) results_path = os.path.join( HOME_DIR, results_location ) data_filename = os.path.join( data_path, "data.h5") fill_filename = os.path.join( results_path, "full_vae_fill.h5" ) save_dir = os.path.join( results_path, "survival_concordance" ) check_and_mkdir(save_dir) survival_curves_dir = os.path.join( save_dir, "sig_curves" ) check_and_mkdir(survival_curves_dir) print "HOME_DIR: ", HOME_DIR print "data_filename: ", data_filename print "fill_filename: ", fill_filename print "LOADING stores" data_store = pd.HDFStore( data_filename, "r" ) fill_store = pd.HDFStore( fill_filename, "r" ) Z_train = fill_store["/Z/TRAIN/Z/mu"] Z_val = fill_store["/Z/VAL/Z/mu"] Z = np.vstack( (Z_train.values, Z_val.values) ) n_z = Z.shape[1] #pdb.set_trace() z_names = ["z_%d"%z_idx for z_idx in range(Z.shape[1])] Z = pd.DataFrame( Z, index = np.hstack( (Z_train.index.values, Z_val.index.values)), columns = z_names ) barcodes = np.union1d( Z_train.index.values, Z_val.index.values ) Z=Z.loc[barcodes] tissues = data_store["/CLINICAL/TISSUE"].loc[barcodes] #Overall Survival (OS) The event call is derived from "vital status" parameter. The time_to_event is in days, equals to days_to_death if patient deceased; in the case of a patient is still living, the time variable is the maximum(days_to_last_known_alive, days_to_last_followup). This pair of clinical parameters are called _EVENT and _TIME_TO_EVENT on the cancer browser. ALL_SURVIVAL = data_store["/CLINICAL/data"][["patient.days_to_last_followup","patient.days_to_death","patient.days_to_birth"]] tissue_barcodes = np.array( ALL_SURVIVAL.index.tolist(), dtype=str ) surv_barcodes = np.array([ x+"_"+y for x,y in tissue_barcodes]) NEW_SURVIVAL = pd.DataFrame( ALL_SURVIVAL.values, index =surv_barcodes, columns = ALL_SURVIVAL.columns ) NEW_SURVIVAL = NEW_SURVIVAL.loc[barcodes] #clinical = data_store["/CLINICAL/data"].loc[barcodes] Age = NEW_SURVIVAL[ "patient.days_to_birth" ].values.astype(int) Times = NEW_SURVIVAL[ "patient.days_to_last_followup" ].fillna(0).values.astype(int)+NEW_SURVIVAL[ "patient.days_to_death" ].fillna(0).values.astype(int) Events = (1-np.isnan( NEW_SURVIVAL[ "patient.days_to_death" ].astype(float)) ).astype(int) ok_age_query = Age<-10 ok_age = pp.find(ok_age_query ) tissues = tissues[ ok_age_query ] #pdb.set_trace() Age=-Age[ok_age] Times = Times[ok_age] Events = Events[ok_age] barcodes = barcodes[ok_age] NEW_SURVIVAL = NEW_SURVIVAL.loc[barcodes] #ok_followup_query = NEW_SURVIVAL[ "patient.days_to_last_followup" ].fillna(0).values>=0 #ok_followup = pp.find( ok_followup_query ) bad_followup_query = NEW_SURVIVAL[ "patient.days_to_last_followup" ].fillna(0).values.astype(int)<0 bad_followup = pp.find( bad_followup_query ) ok_followup_query = 1-bad_followup_query ok_followup = pp.find( ok_followup_query ) bad_death_query = NEW_SURVIVAL[ "patient.days_to_death" ].fillna(0).values.astype(int)<0 bad_death = pp.find( bad_death_query ) #pdb.set_trace() Age=Age[ok_followup] Times = Times[ok_followup] Events = Events[ok_followup] barcodes = barcodes[ok_followup] NEW_SURVIVAL = NEW_SURVIVAL.loc[barcodes] Z = Z.loc[barcodes] Z["E"] = Events Z["T"] = Times Z["Age"] = np.log(Age) tissues = data_store["/CLINICAL/TISSUE"].loc[barcodes] tissue_names = tissues.columns tissue_idx = np.argmax( tissues.values, 1 ) Z["Tissue"] = tissue_idx n_tissues = len(tissue_names) n_random = 100 random_names = ["r_%d"%(trial_idx) for trial_idx in range(n_random)] alpha=0.02 nbr_to_plot = 5 concordance_values = {} concordance_random = {} concordance_z_values = pd.DataFrame( np.nan*np.ones((n_tissues,n_z) ), index = tissue_names, columns=z_names ) concordance_z_random = pd.DataFrame( np.nan*np.ones((n_tissues,n_random) ), index = tissue_names, columns=random_names ) concordance_z_values_xval = pd.DataFrame( np.nan*np.ones((n_tissues,n_z) ), index = tissue_names, columns=z_names ) concordance_I_values = pd.DataFrame( np.nan*np.ones((n_tissues,n_z) ), index = tissue_names, columns=z_names ) concordance_I_random = pd.DataFrame( np.nan*np.ones((n_tissues,n_random) ), index = tissue_names, columns=random_names ) concordance_z_p_values = pd.DataFrame( np.ones( (n_tissues,n_z) ), \ index = tissue_names, \ columns = z_names ) # cf = CoxPHFitter() # scores = k_fold_cross_validation(cf, Z, 'T', event_col='E', k=5) # pdb.set_trace() split_nbr = 2 for t_idx in range(n_tissues): t_ids = tissue_idx == t_idx tissue_name = tissue_names[t_idx] if tissue_name == "gbm": print "skipping gbm" continue print "working %s"%(tissue_name) bcs = barcodes[t_ids] Z_tissue = Z.loc[ bcs ] events = Z_tissue["E"] times = Z_tissue["T"] Z_values = Z_tissue[z_names].values n_tissue = len(bcs) print " using z_values" for z_idx in range(n_z): z = Z_values[:,z_idx] z_data = Z_tissue[ ["z_%d"%(z_idx), "E","T"] ] I = np.argsort(z) z_concordance = lifelines.utils.concordance_index(times[I], z, event_observed=events[I]) z_concordance = max( z_concordance, 1.0-z_concordance ) concordance_z_values["z_%d"%(z_idx)].loc[tissue_name] = z_concordance print " using random" for r_idx in range(n_random): #z = Z_values[:,z_idx] z = np.random.randn(n_tissue) I = np.argsort(z) #np.random.permutation(n_tissue) z_concordance = lifelines.utils.concordance_index(times[I], z, event_observed=events[I]) z_concordance = max( z_concordance, 1.0-z_concordance ) concordance_z_random["r_%d"%(r_idx)].loc[tissue_name] = z_concordance v = concordance_z_values.loc[tissue_name].values r = concordance_z_random.loc[tissue_name].values concordance_z_p_values.loc[tissue_name] = (1.0 + (v[:,np.newaxis]>r).sum(1))/(1.0+len(r)) conc=concordance_z_p_values.loc[tissue_name] sig = (concordance_z_p_values.loc[tissue_name] < alpha ).astype(int) z_sig_names = sig[ sig==1 ].index.values for z_name in z_sig_names: z_idx = int( z_name.split("_")[1] ) z = Z_values[:,z_idx] #z_data = Z_tissue[ ["z_%d"%(z_idx), "E","T"] ] I = np.argsort(z) cum_events = events[I].cumsum() I_splits = [] #[[],[]] #np.array_split( I, split_nbr ) I_splits.append( pp.find( cum_events <= events.sum()/2.0 ) ) I_splits.append( pp.find( cum_events > events.sum()/2.0 ) ) #groups = np.zeros(n_tissue) # k = 1 # for splits in I_splits[1:]: # groups[splits] = k; k+=1 results = logrank_test(times[I_splits[0]], times[I_splits[-1]], events[ I_splits[0] ], events[ I_splits[-1] ] ) p_value = results.p_value #results2 = logrank_test(times[I_splits[0]]/365.0, times[I_splits[-1]]/365.0, events[ I_splits[0] ], events[ I_splits[-1] ] ) #pdb.set_trace() c = conc[ z_name ] f = pp.figure() ax= f.add_subplot(111) kmf = KaplanMeierFitter() k=0 for splits in I_splits: kmf.fit(times[splits], event_observed=events[splits], label="q=%d/%d"%(k+1,split_nbr) ) ax=kmf.plot(ax=ax,at_risk_counts=False,show_censors=True,ci_show=False) k+=1 pp.ylim(0,1) pp.title( "%s %s p-value = %0.4f concordance = %0.3f "%( tissue_name, z_name, p_value, c ) ) pp.savefig( survival_curves_dir + "/%s_%s_p%0.5f_c%0.3f.png"%(tissue_name, z_name, p_value, c), format="png", dpi=300) pp.savefig( survival_curves_dir + "/%s_%s_p%0.5f_c%0.3f.png"%(z_name, tissue_name, p_value, c), format="png", dpi=300) #pdb.set_trace() concordance_z_random.drop("gbm",inplace=True) concordance_z_values.drop("gbm",inplace=True) concordance_z_p_values.drop("gbm",inplace=True) # concordance_z_p_values = pd.DataFrame( np.ones( concordance_z_values.values.shape), \ # index = concordance_z_values.index, \ # columns = concordance_z_values.columns ) # for tissue in concordance_z_random.index.values: # v = concordance_z_values.loc[tissue].values # r = concordance_z_random.loc[tissue].values # concordance_z_p_values.loc[tissue] = (1.0 + (v[:,np.newaxis]>r).sum(1))/(1.0+len(r)) concordance_z_p_values.to_csv( save_dir + "/concordance_z_p_values.csv" ) concordance_z_random.to_csv( save_dir + "/concordance_z_random.csv" ) concordance_z_values.to_csv( save_dir + "/concordance_z_values.csv" ) #pdb.set_trace() f = pp.figure() ax_z = f.add_subplot(221) ax_log_z = f.add_subplot(223) ax_p = f.add_subplot(222) ax_log_p = f.add_subplot(224) bins_conc=np.linspace(0.5,1,21) bins_p=np.linspace(0.0,1,21) ax_z.hist( concordance_z_values.values.flatten(), bins=bins_conc, normed=True, histtype="step", lw=2, log=False) ax_z.hist( concordance_z_random.values.flatten(), bins=bins_conc, normed=True, histtype="step", lw=2, log=False) ax_log_z.hist( concordance_z_values.values.flatten(), bins=bins_conc, normed=True, histtype="step", lw=2, log=True) ax_log_z.hist( concordance_z_random.values.flatten(), bins=bins_conc, normed=True, histtype="step", lw=2, log=True) ax_p.hist( concordance_z_p_values.values.flatten(), bins=bins_p, normed=True, histtype="step", lw=2, log=False) ax_log_p.hist( concordance_z_p_values.values.flatten(), bins=bins_p, normed=True, histtype="step", lw=2, log=True) pp.savefig( save_dir + "/p_values.png", format="png", dpi=300) return concordance_z_random, concordance_z_values, concordance_z_p_values #, concordance_z_p_values_xval if __name__ == "__main__": data_location = sys.argv[1] results_location = sys.argv[2] concordance_z_random, concordance_z_values, concordance_z_p_values = main( data_location, results_location )

41.930233

376

0.68839

1,667

10,818

4.170366

0.15117

0.070771

0.038838

0.038262

0.50561

0.44275

0.384494

0.321922

0.281789

0.270282

0

0.014281

0.177944

10,818

258

377

41.930233

0.767458

0.155574

0

0.106509

0

0.079213

0.037135

0

null

0

0.071006

null

0.047337

0

null

0

null

0

1

0

1

da46e9da88a69412b02b4465644d5259231c811b

274

py

Python

genaperiodic.py

gmayankcse15/Poller-and-Deferrable-Server

9c4c5cae670c6e97959570592135b5c22bdfa4f7

[ "MIT" ]

null

genaperiodic.py

gmayankcse15/Poller-and-Deferrable-Server

9c4c5cae670c6e97959570592135b5c22bdfa4f7

[ "MIT" ]

null

genaperiodic.py

gmayankcse15/Poller-and-Deferrable-Server

9c4c5cae670c6e97959570592135b5c22bdfa4f7

[ "MIT" ]

null

import numpy as np arr_time = np.random.exponential(3, 3) print(arr_time) Exec_Time = np.random.exponential(1, 3) print(Exec_Time) for i in range(0,3): print "A(",round(arr_time[i],1),",",round(Exec_Time[i],1),")" ''' Output A(0.3, 1.1) A(2.5, 2.0) A(0.0, 4.7) '''

13.7

63

0.627737

58

274

2.862069

0.413793

0.126506

0.144578

0.277108

0

0.084746

0.138686

274

20

64

13.7

0.618644

0

0.0181

0

null

0

0.142857

null

0.428571

0

null

0

1

0

null

0

1

0

1

0

3

da4804a69488cffc401e2be47069232bee7d172a

4,828

py

Python

train.py

yazar1993/TextBoxes-mxnet

89fbf4151473ab4575a032871683e76978deec0a

[ "MIT" ]

1

2019-02-04T19:03:27.000Z

train.py

yazar1993/TextBoxes-mxnet

89fbf4151473ab4575a032871683e76978deec0a

[ "MIT" ]

null

train.py

yazar1993/TextBoxes-mxnet

89fbf4151473ab4575a032871683e76978deec0a

[ "MIT" ]

null

import time from matplotlib import pyplot as plt import numpy as np import mxnet as mx from mxnet import autograd, gluon import gluoncv as gcv from gluoncv.utils import download, viz from model import model_zoo import argparse def get_dataloader(net, train_dataset, data_shape, batch_size, num_workers): from gluoncv.data.batchify import Tuple, Stack, Pad from gluoncv.data.transforms.presets.ssd import SSDDefaultTrainTransform width, height = data_shape, data_shape with autograd.train_mode(): _, _, anchors = net(mx.nd.zeros((1, 3, height, width))) batchify_fn = Tuple(Stack(), Stack(), Stack()) # stack image, cls_targets, box_targets train_loader = gluon.data.DataLoader( train_dataset.transform(SSDDefaultTrainTransform(width, height, anchors)), batch_size, True, batchify_fn=batchify_fn, last_batch='rollover', num_workers=num_workers) return train_loader parser = argparse.ArgumentParser() parser.add_argument('--images_root',type=str,help='root folder of images') parser.add_argument('--LSTpath', type=str, help= 'path to LST file') parser.add_argument('--batch_size', default = 16, type=int) parser.add_argument('--num_epochs', default = 100, type=int) parser.add_argument('--lr', type=float, default = 0.001, help='learning rate') parser.add_argument('--wd', type=float, default = 0.0005) parser.add_argument('--momentum',type=float,default = 0.9) parser.add_argument('--netName', type=str, help='name of network to train') parser.add_argument('--gpu_ind', type=str, help='comma seperated gpu indicies', default = '0') parser.add_argument('--finetune_model',type=str, help='path to model to finetune from', default = '') args = parser.parse_args() images_root = args.images_root LSTpath = args.LSTpath classes = ['text'] batch_size = args.batch_size num_epochs = args.num_epochs lr = args.lr wd = args.wd momentum = args.momentum netName = args.netName gpu_ind=args.gpu_ind path_to_model = args.finetune_model # load dataset from Lst file dataset = gcv.data.LstDetection(LSTpath, root=images_root) print(dataset) image= dataset[0][0] label = dataset[0][1] print('label:', label) # display image and label ax = viz.plot_bbox(image, bboxes=label[:, :4], labels=label[:, 4:5], class_names=classes) plt.savefig('labeled_image.jpg') #initalize model net, input_size = model_zoo.get_model(netName, pretrained=False, classes=classes) if finetune_model == '': net.initialize() net.reset_class(classes) else: net.load_parameters(path_to_model) net.reset_class(classes) print(net) train_data = get_dataloader(net, dataset, input_size, batch_size, 0) ############################################################################################# # Try use GPU for training try: gpu_ind = gpu_ind.split(',') ctx = [] for cur_gpu in gpu_ind: cur_gpu = int(cur_gpu) a = mx.nd.zeros((1,), ctx=mx.gpu(cur_gpu)) ctx.append(mx.gpu(cur_gpu)) print('gpu mode is used') except: print('cpu mode is used') ctx = [mx.cpu()] ############################################################################################# # Start training net.collect_params().reset_ctx(ctx) trainer = gluon.Trainer( net.collect_params(), 'sgd', {'learning_rate': lr, 'wd': wd, 'momentum': momentum}) mbox_loss = gcv.loss.SSDMultiBoxLoss() ce_metric = mx.metric.Loss('CrossEntropy') smoothl1_metric = mx.metric.Loss('SmoothL1') for epoch in range(0, num_epochs): ce_metric.reset() smoothl1_metric.reset() tic = time.time() btic = time.time() net.hybridize(static_alloc=True, static_shape=True) for i, batch in enumerate(train_data): data = gluon.utils.split_and_load(batch[0], ctx_list=ctx, batch_axis=0) cls_targets = gluon.utils.split_and_load(batch[1], ctx_list=ctx, batch_axis=0) box_targets = gluon.utils.split_and_load(batch[2], ctx_list=ctx, batch_axis=0) with autograd.record(): cls_preds = [] box_preds = [] for x in data: cls_pred, box_pred, _ = net(x) cls_preds.append(cls_pred) box_preds.append(box_pred) sum_loss, cls_loss, box_loss = mbox_loss( cls_preds, box_preds, cls_targets, box_targets) autograd.backward(sum_loss) trainer.step(1) ce_metric.update(0, [l * batch_size for l in cls_loss]) smoothl1_metric.update(0, [l * batch_size for l in box_loss]) name1, loss1 = ce_metric.get() name2, loss2 = smoothl1_metric.get() if i % 20 == 0: print('[Epoch {}][Batch {}], Speed: {:.3f} samples/sec, {}={:.3f}, {}={:.3f}'.format( epoch, i, batch_size/(time.time()-btic), name1, loss1, name2, loss2)) btic = time.time() net.save_parameters(netName + '_icdar2013.params')

37.426357

101

0.665493

673

4,828

4.579495

0.283804

0.029202

0.055159

0.016548

0.095717

0.069111

0.040883

0.018819

0

0.015178

0.167564

4,828

128

102

37.71875

0.75168

0.029619

0

0.037383

0

0.095948

0

1

0.009346

false

0

0.102804

0

0.121495

0.056075

0

null

0

null

0

1

0

da48925dd8d85e25b1591c7ad7324c1b91372e21

484

py

Python

aws/build_saint_features.py

fabien-vavrand/kaggle-riiid

3302955980e0d4bb2dbc72bcd369000b0724f1e7

[ "MIT" ]

null

aws/build_saint_features.py

fabien-vavrand/kaggle-riiid

3302955980e0d4bb2dbc72bcd369000b0724f1e7

[ "MIT" ]

null

aws/build_saint_features.py

fabien-vavrand/kaggle-riiid

3302955980e0d4bb2dbc72bcd369000b0724f1e7

[ "MIT" ]

null

from doppel import DoppelProject from riiid.utils import configure_console_logging from riiid.config import SRC_PATH from riiid.aws.config import CONTEXT, PACKAGES configure_console_logging() project = DoppelProject( name='riiid-saint-features', path=SRC_PATH, entry_point='-m riiid.aws.build_saint_features', packages=PACKAGES, python='3.7.6', n_instances=1, min_memory=128, env_vars={'PYTHONHASHSEED': '1'}, context=CONTEXT ) project.start()

22

52

0.743802

64

484

5.4375

0.578125

0.077586

0.132184

0

0.019512

0.152893

484

21

53

23.047619

0.829268

0

0.150826

0.061983

0

1

0

false

0

0.235294

0

0.235294

0

null

0

null

0

1

0

da48982c5d0c6163ec2e9654c124d812f977e516

14,174

py

Python

effects/card_draw.py

MrCoft/EngiMod

65c90bd9231ac388d8af7849a1835914f1eefc78

[ "MIT" ]

null

effects/card_draw.py

MrCoft/EngiMod

65c90bd9231ac388d8af7849a1835914f1eefc78

[ "MIT" ]

null

effects/card_draw.py

MrCoft/EngiMod

65c90bd9231ac388d8af7849a1835914f1eefc78

[ "MIT" ]

null

from engi_mod import * Java( path = "fruitymod.actions.ChooseCardActionBase", base = "AbstractGameAction", code = """ protected AbstractPlayer p; private String text; private boolean isDraw = false; // NOTE: to trigger events and disable on "No Draw" private boolean putsIntoHand = true; // NOTE: to make decisions if hand is full private boolean random = false; // NOTE: skip selection public ChooseCardActionBase(final AbstractCreature source, int amount, String text, boolean isDraw, boolean putsIntoHand, boolean random) { this.isDraw = isDraw; if (isDraw && AbstractDungeon.player.hasPower("No Draw")) { // NOTE: "put into hand" is not draw AbstractDungeon.player.getPower("No Draw").flash(); setValues(AbstractDungeon.player, source, amount); isDone = true; duration = 0.0f; actionType = ActionType.WAIT; return; } if (isDraw) putsIntoHand = true; p = AbstractDungeon.player; this.text = text; this.putsIntoHand = putsIntoHand; this.random = random; setValues(null, source, amount); actionType = ActionType.CARD_MANIPULATION; if (isDraw) actionType = ActionType.DRAW; duration = Settings.ACTION_DUR_FASTER; } private CardGroup cards; private HashMap<AbstractCard,AbstractCard> handMap; @Override public void update() { if (AbstractDungeon.getCurrRoom().isBattleEnding()) { isDone = true; return; } if (duration == Settings.ACTION_DUR_FASTER) { cards = new CardGroup(CardGroup.CardGroupType.UNSPECIFIED); handMap = new HashMap<AbstractCard,AbstractCard>(); CardGroup[] groups = new CardGroup[]{p.drawPile, p.hand, p.discardPile, p.exhaustPile}; for (CardGroup group : groups) { for (AbstractCard card : group.group) { if (cardFilter(card)) { if (group == p.hand) { AbstractCard copy = card.makeStatEquivalentCopy(); handMap.put(copy, card); card = copy; } cards.addToTop(card); card.stopGlowing(); card.unhover(); card.unfadeOut(); } } if (group == p.drawPile) cards.shuffle(); } init(); if (cards.isEmpty()) { isDone = true; finish(); return; } if (random) { cards.shuffle(); // NOTE: random order even if instant if (cards.size() > amount) cards.group.subList(amount, cards.size()).clear(); isDone = true; for (AbstractCard card : cards.group) { card = handMap.getOrDefault(card, card); cardChosen(card); if (isDraw) SpireUtils.drawTriggers(card); } finish(); return; } if (cards.size() <= amount && (!putsIntoHand || (putsIntoHand && cards.size() <= 10 - p.hand.size()))) { isDone = true; for (AbstractCard card : cards.group) { card = handMap.getOrDefault(card, card); cardChosen(card); if (isDraw) SpireUtils.drawTriggers(card); } finish(); return; } else { AbstractDungeon.gridSelectScreen.open(cards, amount, text, false, false, false, false); tickDuration(); return; } } if (!AbstractDungeon.gridSelectScreen.selectedCards.isEmpty()) { for (AbstractCard card : AbstractDungeon.gridSelectScreen.selectedCards) { card = handMap.getOrDefault(card, card); cardChosen(card); if (isDraw) SpireUtils.drawTriggers(card); } for (AbstractCard card : cards.group) { card = handMap.getOrDefault(card, card); card.unhover(); card.untip(); // NOTE: after duplicating a card, the original is drawn still showing the tooltip } AbstractDungeon.gridSelectScreen.selectedCards.clear(); finish(); } tickDuration(); } public boolean cardFilter(AbstractCard card) { return true; } public void cardChosen(AbstractCard card) {} protected CardDraw cardDraw; public void init() { cardDraw = new CardDraw(); } public void finish() { p.hand.refreshHandLayout(); cardDraw.msg(); } """ ) Java( # NOTE: PRIORITY # to upgrade and draw cards, you look through the deck, # picking unupgraded cards first # NOTE: SHUFFLE # if there are less than `amount` unupgraded cards, # you draw upgraded cards off the top # this special seeking only sees to the bottom of the deck # which is shuffled when empty, so drawing with an empty deck is worse # than with a full one, as it has more prioritized cards to find # NOTE: FULL HAND # when the hand is full, the extra cards aren't drawn, # but they can be selected, so the full amount is upgraded # even if it isn't drawn # NOTE: REPEATED UPGRADES # if being upgradable gives a card priority, repeatedly upgradable cards # could be found as the first prioritized card repeatedly # e.g. Battle Trance path = "fruitymod.actions.DrawCardActionBase", base = "AbstractGameAction", code = """ private boolean shuffleCheck; private static final Logger logger; public DrawCardActionBase(final AbstractCreature source, final int amount, final boolean endTurnDraw) { this.shuffleCheck = false; if (endTurnDraw) { AbstractDungeon.topLevelEffects.add(new PlayerTurnEffect()); } else if (AbstractDungeon.player.hasPower("No Draw")) { AbstractDungeon.player.getPower("No Draw").flash(); this.setValues(AbstractDungeon.player, source, amount); this.duration = 0.0f; this.actionType = ActionType.WAIT; return; } this.setValues(AbstractDungeon.player, source, amount); this.actionType = ActionType.DRAW; if (Settings.FAST_MODE) { this.duration = Settings.ACTION_DUR_XFAST; } else { this.duration = Settings.ACTION_DUR_FASTER; } } public DrawCardActionBase(final AbstractCreature source, final int amount) { this(source, amount, false); } @Override public void update() { if (this.actionType == ActionType.WAIT) { this.isDone = true; finish(); return; } if (this.amount <= 0) { this.isDone = true; return; } final int deckSize = AbstractDungeon.player.drawPile.size(); final int discardSize = AbstractDungeon.player.discardPile.size(); if (SoulGroup.isActive()) { return; } if (deckSize + discardSize == 0) { this.isDone = true; return; } if (AbstractDungeon.player.hand.size() == 10) { finish(); AbstractDungeon.player.createHandIsFullDialog(); this.isDone = true; return; } if (!this.shuffleCheck) { if (this.amount > deckSize) { final int tmp = this.amount - deckSize; AbstractDungeon.actionManager.addToTop(new DrawCardActionBase(AbstractDungeon.player, tmp)); AbstractDungeon.actionManager.addToTop(new EmptyDeckShuffleAction()); if (deckSize != 0) { AbstractDungeon.actionManager.addToTop(new DrawCardActionBase(AbstractDungeon.player, deckSize)); } this.amount = 0; this.isDone = true; } this.shuffleCheck = true; } this.duration -= Gdx.graphics.getDeltaTime(); if (this.amount != 0 && this.duration < 0.0f) { if (Settings.FAST_MODE) { this.duration = Settings.ACTION_DUR_XFAST; } else { this.duration = Settings.ACTION_DUR_FASTER; } --this.amount; if (!AbstractDungeon.player.drawPile.isEmpty()) { AbstractCard card = findCard(); AbstractDungeon.player.drawPile.group.remove(card); AbstractDungeon.player.drawPile.addToTop(card); onSelect(card); AbstractDungeon.player.draw(); AbstractDungeon.player.hand.refreshHandLayout(); onDraw(card); } else { DrawCardActionBase.logger.warn("Player attempted to draw from an empty drawpile mid-DrawAction?MASTER DECK: " + AbstractDungeon.player.masterDeck.getCardNames()); this.isDone = true; } if (this.amount == 0) { this.isDone = true; finish(); } } } public AbstractCard findCard() { if (AbstractDungeon.player.drawPile.isEmpty()) { return null; } for (int i = 0; i < AbstractDungeon.player.drawPile.size(); ++i) { AbstractCard card = AbstractDungeon.player.drawPile.getNCardFromTop(i); if (cardPriority(card)) { return card; } } return AbstractDungeon.player.drawPile.getTopCard(); } public void finish() { for (int i = 0; i < amount; ++i) { AbstractCard card = findCard(); if (card == null) return; onSelect(card); } } public boolean cardPriority(AbstractCard card) { return false; } public void onSelect(AbstractCard card) {} public void onDraw(AbstractCard card) {} static { logger = LogManager.getLogger(DrawCardActionBase.class.getName()); } """ ) Java( path = "fruitymod.actions.DrawSpecificCardAction", base = "AbstractGameAction", code = """ public DrawCardActionBase drawAction; public AbstractCard card; public DrawSpecificCardAction(final AbstractCreature source) { if (AbstractDungeon.player.hasPower("No Draw")) { AbstractDungeon.player.getPower("No Draw").flash(); this.setValues(AbstractDungeon.player, source, amount); this.duration = 0.0f; this.actionType = ActionType.WAIT; return; } this.setValues(AbstractDungeon.player, source, 1); this.actionType = ActionType.DRAW; if (Settings.FAST_MODE) { this.duration = Settings.ACTION_DUR_XFAST; } else { this.duration = Settings.ACTION_DUR_FASTER; } } @Override public void update() { if (this.actionType == ActionType.WAIT) { drawAction.onSelect(card); this.isDone = true; return; } if (AbstractDungeon.player.hand.size() == 10) { drawAction.onSelect(card); AbstractDungeon.player.createHandIsFullDialog(); this.isDone = true; return; } this.duration -= Gdx.graphics.getDeltaTime(); if (this.amount != 0 && this.duration < 0.0f) { AbstractDungeon.player.drawPile.group.remove(card); AbstractDungeon.player.drawPile.addToTop(card); drawAction.onSelect(card); AbstractDungeon.player.draw(); AbstractDungeon.player.hand.refreshHandLayout(); drawAction.onDraw(card); this.isDone = true; } } """ ) Java( path = "fruitymod.CardDraw", code = """ private boolean failed = false; public AbstractCard get(AbstractCard card) { if (AbstractDungeon.player.hand.size() == 10) { failed = true; return null; } card.unfadeOut(); card.unhover(); card.fadingOut = false; return card; } public void msg() { if (failed) AbstractDungeon.player.createHandIsFullDialog(); } """ ) # problem - because of animations, shuffling is solved by parting the problem into "draw deck / shuffle / draw rest" # find the cards first, then push their specific # continue doing it until empty, then push reshuffle, then a revive? # i hate this code so much

38.832877

182

0.506632

1,146

14,174

6.247819

0.22164

0.105587

0.019553

0.027933

0.382682

0.334358

0.326257

0.272346

0.25419

0.217039

0

0.003319

0.404826

14,174

364

183

38.93956

0.845424

0.0678

0

0.439628

0

0.01548

0.975286

0.243348

0

1

0

true

0

0.003096

0

0.021672

0

null

0

1

0

null

0

1

0

2

da49b2e919a71a34082302973c4047cd68a8918b

2,205

py

Python

data_structures.py

davecom/MazeSolvingGUI

291e0dfb146d7743ecb108413f5e7422e0719019

[ "Apache-2.0" ]

6

2020-06-26T00:45:35.000Z

2022-01-15T19:37:36.000Z

data_structures.py

davecom/MazeSolvingGUI

291e0dfb146d7743ecb108413f5e7422e0719019

[ "Apache-2.0" ]

null

data_structures.py

davecom/MazeSolvingGUI

291e0dfb146d7743ecb108413f5e7422e0719019

[ "Apache-2.0" ]

3

2021-05-03T16:48:29.000Z

2021-11-19T20:21:29.000Z

# data_structures.py # Copyright 2020 David Kopec # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from __future__ import annotations from typing import TypeVar, Generic, List, Deque, Optional T = TypeVar('T') class Stack(Generic[T]): def __init__(self) -> None: self.container: List[T] = [] @property def empty(self) -> bool: return not self.container # not is true for empty container def push(self, item: T) -> None: self.container.append(item) def pop(self) -> T: return self.container.pop() # LIFO def __repr__(self) -> str: return repr(self.container) class Node(Generic[T]): def __init__(self, state: T, parent: Optional[Node], cost: float = 0.0, heuristic: float = 0.0) -> None: self.state: T = state self.parent: Optional[Node] = parent self.cost: float = cost self.heuristic: float = heuristic def __lt__(self, other: Node) -> bool: return (self.cost + self.heuristic) < (other.cost + other.heuristic) def node_to_path(node: Node[T]) -> List[T]: path: List[T] = [node.state] # work backwards from end to front while node.parent is not None: node = node.parent path.append(node.state) path.reverse() return path class Queue(Generic[T]): def __init__(self) -> None: self.container: Deque[T] = Deque() @property def empty(self) -> bool: return not self.container # not is true for empty container def push(self, item: T) -> None: self.container.append(item) def pop(self) -> T: return self.container.popleft() # FIFO def __repr__(self) -> str: return repr(self.container)

29.4

108

0.65805

307

2,205

4.625407

0.371336

0.091549

0.047887

0.03169

0.320423

0.307042

0.204225

0

0.007092

0.232653

2,205

75

109

29.4

0.832151

0.303855

0

0.428571

0

0.00066

0

1

0.309524

false

0

0.047619

0.166667

0.619048

0

null

0

null

0

1

0

1

0

2

da4a7e68c0832aca421b9ec0a6a9d00a1f584040

1,933

py

Python

src/sentry/incidents/endpoints/organization_alert_rule_trigger_details.py

kinghuang/sentry

5c22673994a62f54a782d1c595852986ccc51ae9

[ "BSD-3-Clause" ]

1

2019-10-17T17:46:16.000Z

src/sentry/incidents/endpoints/organization_alert_rule_trigger_details.py

kinghuang/sentry

5c22673994a62f54a782d1c595852986ccc51ae9

[ "BSD-3-Clause" ]

null

src/sentry/incidents/endpoints/organization_alert_rule_trigger_details.py

kinghuang/sentry

5c22673994a62f54a782d1c595852986ccc51ae9

[ "BSD-3-Clause" ]

null

from __future__ import absolute_import from rest_framework import status from rest_framework.response import Response from sentry.api.serializers import serialize from sentry.api.serializers.models.alert_rule_trigger import DetailedAlertRuleTriggerSerializer from sentry.incidents.endpoints.bases import OrganizationAlertRuleTriggerEndpoint from sentry.incidents.endpoints.serializers import AlertRuleTriggerSerializer from sentry.incidents.logic import AlreadyDeletedError, delete_alert_rule_trigger class OrganizationAlertRuleTriggerDetailsEndpoint(OrganizationAlertRuleTriggerEndpoint): def get(self, request, organization, alert_rule, alert_rule_trigger): """ Fetch an alert rule trigger. `````````````````` :auth: required """ data = serialize(alert_rule_trigger, request.user, DetailedAlertRuleTriggerSerializer()) return Response(data) def put(self, request, organization, alert_rule, alert_rule_trigger): serializer = AlertRuleTriggerSerializer( context={ "organization": organization, "alert_rule": alert_rule, "access": request.access, }, instance=alert_rule_trigger, data=request.data, partial=True, ) if serializer.is_valid(): trigger = serializer.save() return Response(serialize(trigger, request.user), status=status.HTTP_200_OK) return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) def delete(self, request, organization, alert_rule, alert_rule_trigger): try: delete_alert_rule_trigger(alert_rule_trigger) return Response(status=status.HTTP_204_NO_CONTENT) except AlreadyDeletedError: return Response( "This trigger has already been deleted", status=status.HTTP_400_BAD_REQUEST )

39.44898

96

0.702535

188

1,933

6.989362

0.351064

0.10274

0.121766

0.079148

0.17656

0.153729

0.109589

0

0.008

0.224004

1,933

48

97

40.270833

0.868

0.032592

0

0.035519

0

1

0.085714

false

0

0.228571

0

0.485714

0

null

0

null

0

1

0

da4b5460725c138c9033a42b82f19db166cfb84d

1,935

py

Python

tests/test_one_of_schema.py

bwind/sticky-marshmallow

e3e7c215fe9b221164c17121197ffca1b396e81a

[ "MIT" ]

2

2019-11-28T11:25:47.000Z

2019-12-05T09:53:31.000Z

tests/test_one_of_schema.py

bwind/sticky-marshmallow

e3e7c215fe9b221164c17121197ffca1b396e81a

[ "MIT" ]

null

tests/test_one_of_schema.py

bwind/sticky-marshmallow

e3e7c215fe9b221164c17121197ffca1b396e81a

[ "MIT" ]

1

2019-11-29T15:32:14.000Z

from dataclasses import dataclass from typing import List import bson from sticky_marshmallow import Repository from marshmallow_oneofschema import OneOfSchema from marshmallow import fields, post_load, Schema from tests.db import connect @dataclass class Foo: id: str foo: str @dataclass class A(Foo): bar: str @dataclass class B(Foo): baz: str class BaseSchema(Schema): id = fields.Str(allow_none=True) foo = fields.Str() class ASchema(BaseSchema): bar = fields.Str() @post_load def make_object(self, data, **kwargs): return A(**data) class BSchema(BaseSchema): baz = fields.Str() class FooSchema(OneOfSchema): type_schemas = {"a": ASchema, "b": BSchema} def get_obj_type(self, obj): return obj.__class__.__name__.lower() class FooRepository(Repository): class Meta: schema = FooSchema @dataclass class Master: foos: List[Foo] class MasterSchema(Schema): foos = fields.Nested(FooSchema, many=True) class MasterRepository(Repository): class Meta: schema = MasterSchema class TestOneOfSchema: def setup(self): connect() FooRepository().delete_many() MasterRepository().delete_many() def teardown(self): FooRepository().delete_many() MasterRepository().delete_many() def test_collection_name(self): assert FooRepository().collection.name == "foo" def test_saves_reference(self): a = A(id=None, foo="x", bar="y") master = Master(foos=[a]) MasterRepository().save(master) assert isinstance( MasterRepository().collection.find_one()["foos"][0], bson.ObjectId ) assert FooRepository().collection.find_one() def test_dereferences(self): a = A(id=None, foo="x", bar="y") master = Master(foos=[a]) MasterRepository().save(master) MasterRepository().get()

19.744898

78

0.657364

222

1,935

5.603604

0.324324

0.045016

0.027331

0.040193

0.184887

0.101286

0

0.00067

0.228941

1,935

97

79

19.948454

0.83311

0

0.246154

0

0.006718

0

0.046154

1

0.107692

false

0

0.107692

0.030769

0.630769

0

null

0

null

0

1

0

1