ytzi/the-stack-dedup-python-scored · Datasets at Hugging Face

a96d57b61d8688819ccbbbd9291ae22fdd80039b

566

py

Python

sqlite_framework/sql/item/constraint/table/base.py

alvarogzp/python-sqlite-framework

29db97a64f95cfe13eb7bae1d00b624b5a37b152

[ "Apache-2.0" ]

1

2020-08-29T12:42:11.000Z

sqlite_framework/sql/item/constraint/table/base.py

alvarogzp/python-sqlite-framework

29db97a64f95cfe13eb7bae1d00b624b5a37b152

[ "Apache-2.0" ]

4

2018-05-07T19:36:30.000Z

2018-05-29T05:18:13.000Z

sqlite_framework/sql/item/constraint/table/base.py

alvarogzp/python-sqlite-framework

29db97a64f95cfe13eb7bae1d00b624b5a37b152

[ "Apache-2.0" ]

null

from sqlite_framework.sql.item.base import SqlItem from sqlite_framework.sql.item.column import Column class TableConstraint(SqlItem): def str(self): raise NotImplementedError() class ColumnListTableConstraint(TableConstraint): def __init__(self, constraint_type: str, *columns: Column): super().__init__() self.type = constraint_type self.columns = columns def str(self): columns = ", ".join(column.name for column in self.columns) return "{type} ({columns})".format(type=self.type, columns=columns)

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0.80742

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24

0.042403

a97015a85173cf78e85bed10e73b68dc69502a9d

78

py

Python

pydemic/report/__init__.py

GCES-Pydemic/pydemic

f221aa16e6a32ed1303fa11ebf8a357643f683d5

[ "MIT" ]

null

pydemic/report/__init__.py

GCES-Pydemic/pydemic

f221aa16e6a32ed1303fa11ebf8a357643f683d5

[ "MIT" ]

null

pydemic/report/__init__.py

GCES-Pydemic/pydemic

f221aa16e6a32ed1303fa11ebf8a357643f683d5

[ "MIT" ]

null

from .report_group import GroupReport from .report_single import SingleReport

26

39

0.871795

0

a97282eeac0597449d543922ed87821479844a39

724

py

Python

src/baboon_tracking/mixins/history_frames_mixin.py

radioactivebean0/baboon-tracking

062351c514073aac8e1207b8b46ca89ece987928

[ "MIT" ]

6

2019-07-15T19:10:59.000Z

2022-02-01T04:25:26.000Z

src/baboon_tracking/mixins/history_frames_mixin.py

radioactivebean0/baboon-tracking

062351c514073aac8e1207b8b46ca89ece987928

[ "MIT" ]

86

2019-07-02T17:59:46.000Z

2022-02-01T23:23:08.000Z

src/baboon_tracking/mixins/history_frames_mixin.py

radioactivebean0/baboon-tracking

062351c514073aac8e1207b8b46ca89ece987928

[ "MIT" ]

7

2019-10-16T12:58:21.000Z

2022-03-08T00:31:32.000Z

""" Mixin for returning history frames. """ from collections import deque from typing import Deque from rx.core.typing import Observable from baboon_tracking.models.frame import Frame class HistoryFramesMixin: """ Mixin for returning history frames. """ def __init__(self, history_frame_count: int, history_frame_popped: Observable): self.history_frames: Deque[Frame] = deque([]) self.history_frame_popped = history_frame_popped self._history_frame_count = history_frame_count def is_full(self): """ Returns true if the history frame deque is full. """ return len(self.history_frames) >= self._history_frame_count

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0.722376

0

172

0.237569

a972d95469a20ffc4d590103acea6ae8f6b2b426

1,746

py

Python

src/elm_doc/tasks/html.py

brilliantorg/elm-doc

69ddbcd57aee3da6283c2497d735951d95b85426

[ "BSD-3-Clause" ]

29

2017-02-01T11:58:44.000Z

2021-05-21T15:18:33.000Z

src/elm_doc/tasks/html.py

brilliantorg/elm-doc

69ddbcd57aee3da6283c2497d735951d95b85426

[ "BSD-3-Clause" ]

143

2017-07-26T17:34:44.000Z

2022-03-01T18:01:43.000Z

src/elm_doc/tasks/html.py

brilliantorg/elm-doc

69ddbcd57aee3da6283c2497d735951d95b85426

[ "BSD-3-Clause" ]

7

2018-03-09T10:04:45.000Z

2021-10-19T19:17:40.000Z

import json import html from pathlib import Path from elm_doc.utils import Namespace # Note: title tag is omitted, as the Elm app sets the title after # it's initialized. PAGE_TEMPLATE = ''' <!DOCTYPE html> <html> <head> <meta charset="UTF-8"> <link rel="shortcut icon" size="16x16, 32x32, 48x48, 64x64, 128x128, 256x256" href="{mount_point}/assets/favicon.ico"> <link rel="stylesheet" href="{mount_point}/assets/style.css"> <script src="{mount_point}/artifacts/elm.js"></script> <script src="{mount_point}/assets/highlight/highlight.pack.js"></script> <link rel="stylesheet" href="{mount_point}/assets/highlight/styles/default.css"> </head> <body> <script> try {{ const fontsLink = document.createElement("link"); fontsLink.href = "{mount_point}/assets/fonts/" + ((navigator.userAgent.indexOf("Macintosh") > -1) ? "_hints_off.css" : "_hints_on.css"); fontsLink.rel = "stylesheet"; document.head.appendChild(fontsLink); }} catch(e) {{ // loading the font is not essential; log the error and move on console.log(e); }} Elm.Main.init({init}); </script> </body> </html> ''' # noqa: E501 def _render(mount_point: str = ''): if mount_point and mount_point[-1] == '/': mount_point = mount_point[:-1] init = { 'flags': { 'mountedAt': mount_point, }, } return PAGE_TEMPLATE.format( mount_point=html.escape(mount_point), init=json.dumps(init)) class actions(Namespace): def write(output_path: Path, mount_point: str = ''): output_path.parent.mkdir(parents=True, exist_ok=True) with open(str(output_path), 'w') as f: f.write(_render(mount_point=mount_point))

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245

0.140321

0

1,096

0.627721

a9747260a42549b174eafc1943184e3614f86276

1,031

py

Python

pyPico/2.传感器实验/6.水位传感器/main.py

01studio-lab/MicroPython_Examples

f06a1bee398674ceafebed2aac88d8413cc8abad

[ "MIT" ]

73

2020-05-02T13:48:27.000Z

2022-03-26T13:15:10.000Z

pyPico/2.传感器实验/6.水位传感器/main.py

01studio-lab/MicroPython_Examples

f06a1bee398674ceafebed2aac88d8413cc8abad

[ "MIT" ]

null

pyPico/2.传感器实验/6.水位传感器/main.py

01studio-lab/MicroPython_Examples

f06a1bee398674ceafebed2aac88d8413cc8abad

[ "MIT" ]

50

2020-05-15T13:57:28.000Z

2022-03-30T14:03:33.000Z

''' 实验名称：水位传感器版本：v1.0 日期：2021.1 作者：01Studio 【www.01Studio.org】说明：通过水位传感器对水位测量并显示。 ''' #导入相关模块 import time from machine import Pin,SoftI2C,ADC from ssd1306 import SSD1306_I2C #初始化oled i2c = SoftI2C(scl=Pin(10), sda=Pin(11)) #软件I2C初始化：scl--> 10, sda --> 11 oled = SSD1306_I2C(128, 64, i2c, addr=0x3c) #OLED显示屏初始化：128*64分辨率,OLED的I2C地址是0x3c #初始化ADC1,Pin=27 Water_level = ADC(1) while True: oled.fill(0) # 清屏显示黑色背景 oled.text('01Studio', 0, 0) # 首行显示01Studio oled.text('Water Level test', 0, 15) # 次行显示实验名称 value=Water_level.read_u16() #获取ADC数值 #显示数值 oled.text(str(value)+' (65535)',0,40) #计算电压值，获得的数据0-4095相当于0-3V，（'%.2f'%）表示保留2位小数 oled.text(str('%.2f'%(value/65535*3.3))+' V',0,55) #判断水位，分5档显示，0-4cm if 0 <= value <=9602: oled.text('0cm', 60, 55) if 9602 < value <= 14403: oled.text('1cm', 60, 55) if 14403 < value <= 19204: oled.text('2cm', 60, 55) if 19204 < value <= 20804: oled.text('3cm', 60, 55) if 20804 < value: oled.text('4cm', 60, 55) oled.show() time.sleep_ms(1000)

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0

633

0.487298

a975a7568cae17acd3d7b4203c548d145cfe9d6a

147

py

Python

src/assisters/mytypes.py

khyreek/Codeforcescord-Bot

b47ce6b1bf779e6d3f904b3dcb2a811b74e90b17

[ "Apache-2.0" ]

null

src/assisters/mytypes.py

khyreek/Codeforcescord-Bot

b47ce6b1bf779e6d3f904b3dcb2a811b74e90b17

[ "Apache-2.0" ]

null

src/assisters/mytypes.py

khyreek/Codeforcescord-Bot

b47ce6b1bf779e6d3f904b3dcb2a811b74e90b17

[ "Apache-2.0" ]

null

from typing import Annotated Problem = Annotated[str, "code cfs problems have, ex. 1348B"] ProblemWidth = int CFSSectionsData = tuple[int, ...]

18.375

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0.734694

0

35

0.238095

a9767449042e9e6827a47f70074761e36edb412a

2,666

py

Python

nb.py

corytaitchison/online-reviews

10de9218137658269ba36849dfa7e8f643335d01

[ "MIT" ]

null

nb.py

corytaitchison/online-reviews

10de9218137658269ba36849dfa7e8f643335d01

[ "MIT" ]

null

nb.py

corytaitchison/online-reviews

10de9218137658269ba36849dfa7e8f643335d01

[ "MIT" ]

null

import pandas as pd import numpy as np import matplotlib.pyplot as plt ### import nltk from nltk.corpus import stopwords from nltk.tokenize import word_tokenize # from nltk.stem import WordNetLemmatizer from nltk.stem import PorterStemmer ### from sklearn.naive_bayes import MultinomialNB from sklearn.metrics import confusion_matrix, classification_report from sklearn.model_selection import train_test_split from sklearn.feature_extraction.text import CountVectorizer ### from loadRandom import loadRandom2 ps = PorterStemmer() # lemmatizer = WordNetLemmatizer() def textProcess(text): stopWords = set(stopwords.words('english')) noPunc = word_tokenize(text) return [ps.stem(word) for word in noPunc if word not in stopWords] if __name__ == '__main__': _seed = 123 _observations = 1e4 _subsets = [1, 2, 3, 4] location = '/Users/caitchison/Documents/Yelp/yelp_dataset/restaurants_only.csv' data = loadRandom2(location, _observations, seed=_seed, n=3778803).loc[:, ('text', 'useful', 'cool', 'funny', 'stars_x')] # Calculate "interaction" score data['interactions'] = data.useful + data.cool + data.funny data = data[data['interactions'] >= _subsets[0]].dropna() # Subset to get equal amounts of low-useful and high-useful masks = [data.interactions == x for x in _subsets] masks.append(data.interactions > _subsets[-1]) subsetSize = min([sum(mask) for mask in masks]) print("Creating subsets of size %i" % subsetSize) newData = pd.DataFrame([]) for mask in masks: df = data[mask].sample(n=subsetSize, random_state=_seed) newData = newData.append(df) data = newData # Split interactions into quantiles (5) data['group'] = pd.qcut(data['interactions'], q=5, labels=False) print(pd.qcut(data['interactions'], q=5).cat.categories) data.rename(columns={"stars_x": "stars"}) # Create a bag of words and convert the text to a sparse matrix text = np.array(data['text']) bow = CountVectorizer(analyzer=textProcess).fit(text) print("Unique (Not Stop) Words:", len(bow.vocabulary_)) text = bow.transform(text) # Split into features for testing and training at 30% xTrain, xTest, yTrain, yTest = train_test_split( text, np.array(data['group']), test_size=0.3, random_state=_seed) # Train model (Multinomial Naive Bayes) nb = MultinomialNB() nb.fit(xTrain, yTrain) # Test and Evaluate Model preds = nb.predict(xTest) print(confusion_matrix(yTest, preds)) print('\n') print(classification_report(yTest, preds))

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0

667

0.250188

a9767fe03cd95cd1ee4f89e2a2b53d9dc840600a

4,032

py

Python

1_Basics:warmup/2_TweetsFilter/twitter_exerciseB.py

ferreiro/Python_course

73eb41e248d702741a4109a78b15ef8e5e6341f2

[ "MIT" ]

2

2016-02-15T04:12:22.000Z

2021-09-05T23:26:53.000Z

1_Basics:warmup/2_TweetsFilter/twitter_exerciseB.py

ferreiro/Python-course

73eb41e248d702741a4109a78b15ef8e5e6341f2

[ "MIT" ]

10

2015-10-16T14:37:41.000Z

2015-11-16T22:29:39.000Z

2_TwitterAPI/twitter_exerciseB.py

ferreiro/Python

9a0292d4898571fcef95546eec977d3138c7c23b

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- import csv import json outdirectory = "outputCSV/" tweetsFile = "tweets.txt"; outputFile = "mostUsedHasgtags.csv"; tweetsList = [] # List that contains all the tweets readed from a file hashtagTable = {}; # Dictionary with key= hashtags and value= frecuency for this hashtag """ Returns a list of tweets readen from a file. if there's a problem None object will be returned """ def loadTweets(inputFilename): tweetsList = [] # returns a list of tweets try: openedFile = open(inputFilename, "r"); for line in openedFile: tweet = json.loads(line); if not tweet.has_key('delete'): tweetsList.append(tweet); # else: skip objects with "delete" key openedFile.close(); # Close the file except: return None; return tweetsList; """ Creates a hasmap frecuency table where keys are the hashtags and values are the number or appeareances of that hashtag in all the twetts. Returns None if we coudn't create the Hashmap and a dictionary if everything works""" def createHashtagFrecuencyTable(inputList): if (not isinstance(inputList, list)): return None; # exit function if the input object is not a list try: hashtagTable = {} # create empty dictionary for tweet in inputList: # iterate all the tweets loaded in the list for hashtag in tweet['entities']['hashtags']: # iterate all the hastags for each tweet hashtagName = hashtag['text']; # Get a hashtag from the weet if (hashtagName in hashtagTable): hashtagTable[hashtagName] += 1; # Hashtag was previously added to the dictionary. Increase value by one else: hashtagTable[hashtagName] = 1; # Hashtag wasn't in the directionary. Add it with 1 value except: return None; return hashtagTable """ Returns a ordered hasmap, where the sorting was made taking into acccount the value of each key on the hasmap and desdending order. """ def orderHashtagTable(dictionary): if (not isinstance(dictionary, dict)): return None; # exit function if the input object is not a dictionay return sorted(dictionary.items(), key = lambda t:t[1], reverse=True); # INFO: https://www.youtube.com/watch?v=MGD_b2w_GU4 """ This function writes header and data to a .csv file pass by value If the outputFile passed is not a .csv type. A failure will returned (False) """ def writeFile(headerList, data, outputFile): success = True; # 0 means success | -1 = fails writing the file if not outputFile.endswith(".csv"): # Check if the file has .csv format. If not. Will return false print "Outpufile extension %s not valid" % (outputFile[-4:]) # Notify file output extension doesn't exist return False; # output file format not valid try: outputFile = open(outputFile, 'w') csvWriter = csv.writer(outputFile, delimiter=',', skipinitialspace=True, dialect='excel'); # http://stackoverflow.com/questions/29335614/python-csv-writer-leave-a-empty-line-at-the-end-of-the-file csvWriter.writerow(headerList); # write the header to the csv file for hashtag in data: csvWriter.writerow(hashtag); outputFile.close(); except: return False; # Problems writting the file return success; tweetsList = loadTweets(tweetsFile); # Loading a list of twetts from a file if (tweetsList != None): print "Loading twetts from file...[OK]" else: "Loading twetts from file...[ERROR]" hashtagTable = createHashtagFrecuencyTable(tweetsList); if (hashtagTable != None): print "Creating hashtags table with its frecuencies...[OK]" else: "Creating hashtags table with its frecuencies...[ERROR]" orderedHashtagTable = orderHashtagTable(hashtagTable) if (orderedHashtagTable != None): print "Ordering hashtags table in desdending order...[OK]" else: "Ordering hashtags table in desdending order...[ERROR]" headerList = ["hashtag", "frecuency"] # .csv header to write on the file if (writeFile(headerList, orderedHashtagTable[:10], outputFile)): print "Writing csv file with top used hashtags...[OK]" else: "Writing csv file with top used hashtags...[ERROR]"

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0

2,241

0.55484

a976a9884a077db66cbb3f3d300b2d865662f9c4

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py

Python

docker-images/slack-prs/main.py

kiteco/kiteco-public

74aaf5b9b0592153b92f7ed982d65e15eea885e3

[ "BSD-3-Clause" ]

17

2022-01-10T11:01:50.000Z

2022-03-25T03:21:08.000Z

docker-images/slack-prs/main.py

kiteco/kiteco-public

74aaf5b9b0592153b92f7ed982d65e15eea885e3

[ "BSD-3-Clause" ]

1

2022-01-13T14:28:47.000Z

docker-images/slack-prs/main.py

kiteco/kiteco-public

74aaf5b9b0592153b92f7ed982d65e15eea885e3

[ "BSD-3-Clause" ]

7

2022-01-07T03:58:10.000Z

2022-03-24T07:38:20.000Z

import time import json import argparse import websocket import requests import github MY_NAME = 'kit' # should be able to avoid this in the future TOKEN = 'XXXXXXX' GITHUB_USERNAME_BY_SLACK_USERNAME = { "adam": "adamsmith", # XXXXXXX ... } channel_ids_by_name = {} channel_names_by_id = {} next_id = 0 def send(conn, channel, text): global next_id, last_send_timestamp channel_id = channel_ids_by_name.get(channel, channel) payload = dict( id=next_id, type="message", channel=channel_id, text=text) msg = json.dumps(payload) conn.send(json.dumps(payload)) next_id += 1 last_send_timestamp = time.time() def slack_escape(s): s = s.replace("&", "&") s = s.replace("<", "<") s = s.replace(">", ">") return s def pr_queue_for(github_username, prs, comments_by_pr): response = "" for role, pr in github.prs_for(github_username, prs): title, url, number = pr["title"], pr["html_url"], pr["number"] comments = comments_by_pr.get(number, None) if not comments: comments = github.fetch_comments(number) comments_by_pr[number] = comments updates_by_user = github.summarize_updates_for(github_username, comments) if len(updates_by_user) == 0: update_msg = "no updates" else: update_msg = ", ".join("%d new from %s" % (count, user) for user, count in updates_by_user.items()) response += 'you are *%s* for %s %s: *%s*\n' % (role, url, slack_escape(title), update_msg) if response == "": return "you are not on any pull requests" else: return response def updates_since(github_username, prs, comments_by_pr, since): response = "" for role, pr in github.prs_for(github_username, prs): title, url, number = pr["title"], pr["html_url"], pr["number"] comments = comments_by_pr.get(number, None) if not comments: comments = github.fetch_comments(number) comments_by_pr[number] = comments updates_by_user = github.summarize_updates_since(github_username, comments, since) if updates_by_user: status = ", ".join("%d new from %s" % (count, user) for user, count in updates_by_user.items()) response += '*%s* (%s) %s\n' % (status, url, slack_escape(title)) return response def main(): parser = argparse.ArgumentParser() parser.add_argument("--daily", action="store_true") parser.add_argument("--since", type=str) args = parser.parse_args() conn = None user_ids_by_name = {} user_names_by_id = {} im_channel_by_user = {} # Get messaging setup info payload = dict(token=TOKEN) r = requests.post('https://slack.com/api/rtm.start', data=payload).json() if r["ok"]: print("Successfully connected to messaging API") else: print("Error:\n" + str(r)) return # Unacpk general info dial_url = r["url"] # Unpack channel info users = r["users"] for user in users: name = user["name"] id = user["id"] user_ids_by_name[name] = id user_names_by_id[id] = name # Unpack channel info channels = r["channels"] for channel in channels: name = channel["name"] id = channel["id"] channel_ids_by_name[name] = id channel_names_by_id[id] = name for im_channel in r["ims"]: im_channel_by_user[user_names_by_id[im_channel["user"]]] = im_channel["id"] # Open websocket conn = websocket.create_connection(dial_url) print("Connected") # Send private messages prs = github.fetch_prs() comments = {} if args.daily: for user, ch in im_channel_by_user.items(): github_username = GITHUB_USERNAME_BY_SLACK_USERNAME.get(user, None) if github_username: print('Sending PM to %s...' % user) msg = pr_queue_for(github_username, prs, comments) print(msg.replace("\n", "\n ")) send(conn, ch, "Here is your daily pull request update:\n" + msg) else: since = 0 try: if args.since: # Read prev timestamp with open(args.since) as f: since = float(f.read().strip()) # Write new timestamp with open(args.since, "w") as f: f.write(str(time.time())) except (IOError, ValueError): pass for user, ch in im_channel_by_user.items(): github_username = GITHUB_USERNAME_BY_SLACK_USERNAME.get(user, None) if github_username: msg = updates_since(github_username, prs, comments, since) if msg: print('Sending PM to %s...' % user) print(msg) send(conn, ch, msg) if __name__ == '__main__': try: main() except KeyboardInterrupt: pass

24.834286

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0.685228

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0.179705

a9775f738c3044fcff42b57c7ed49ac310db7479

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py

Python

commands/meme.py

EFFLUX110/efflux-discord-bot

fe382fc822f852efab8d4742daa756045a17bff3

[ "MIT" ]

null

commands/meme.py

EFFLUX110/efflux-discord-bot

fe382fc822f852efab8d4742daa756045a17bff3

[ "MIT" ]

4

2022-02-03T18:24:32.000Z

2022-02-03T19:24:51.000Z

commands/meme.py

EFFLUX110/efflux-discord-bot

fe382fc822f852efab8d4742daa756045a17bff3

[ "MIT" ]

1

2022-02-03T18:12:44.000Z

import discord import requests from discord.ext import commands class Meme(commands.Cog): def __init__(self, bot): self.bot = bot @commands.command() async def meme(self,ctx): r=requests.get("https://memes.blademaker.tv/api?lang=en") res=r.json() title=res['title'] ups=res['ups'] downs=res['downs'] sub=res['subreddit'] m=discord.Embed(title=f"{title}\nsubreddit: {sub}") m.set_image(url=res["image"]) m.set_footer(text=f"Requested by {ctx.author}", icon_url=ctx.author.avatar_url) await ctx.send(embed=m) def setup(bot): bot.add_cog(Meme(bot))

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0

460

0.70122

436

0.664634

134

0.204268

a977697bb7ffe10b5b5f5a391df5f58451adfd57

717

py

Python

45.py

brianfl/project-euler

9f83a3c2da04fd0801a4a575081add665edccd5f

[ "MIT" ]

null

45.py

brianfl/project-euler

9f83a3c2da04fd0801a4a575081add665edccd5f

[ "MIT" ]

null

45.py

brianfl/project-euler

9f83a3c2da04fd0801a4a575081add665edccd5f

[ "MIT" ]

null

target_num = 0 j = 0 while target_num == 0: pent_ind = float((1 + ( 1 + 24*j*(2*j-1))**.5)/6) tri_ind = float((-1 + (1+8*j*(2*j-1)))/2) if pent_ind.is_integer() and tri_ind.is_integer(): num = j*(2*j-1) if num != 1 and num != 40755: target_num = num j += 1 print(target_num) # 1533776805 """ I had a brute force solution, but it was a bit over a minute. By solving for the index values of pentagon and triangle numbers in terms of the index value of the hexagon numbers, the formulas in pent_ind and tri_ind pop out of the quadratic equation. Basically those variables will only be integers if j is a valid index for a pentagon number and triangle number as well. """

29.875

71

0.661088

0

393

0.548117

a97827ef5e7685a79286da4ad9d58d63d84d97d6

801

py

Python

client.py

hani9/smartlockers

bd7a996be58769341367d58d5c80c70ad7bd1cb6

[ "MIT" ]

null

client.py

hani9/smartlockers

bd7a996be58769341367d58d5c80c70ad7bd1cb6

[ "MIT" ]

null

client.py

hani9/smartlockers

bd7a996be58769341367d58d5c80c70ad7bd1cb6

[ "MIT" ]

null

#!/usr/bin/python # -*- coding: utf-8 -*- # Importo les llibreries import socket import RPi.GPIO as GPIO import time # Faig la configuració bàsica del GPIO GPIO.setwarnings(False) GPIO.setmode(GPIO.BCM) GPIO.setup(18, GPIO.OUT) # Només utilitzo el 18. Es podria fer un bucle per activar-ne diversos alhora. # Indico la IP del servidor i el port de comunicació host = "PLACE_YOUR_SERVER_IP_HERE" port = 12345 # Inicio un bucle infinit while 1: s = socket.socket() # Creo el socket s.connect((host, port)) # Connecto al servidor data = s.recv(1024) # Rebo dades GPIO.output(int(data), GPIO.HIGH) # La dada rebuda indica el pin del gpio que es farà UP time.sleep(1) # S'espera 1 segon GPIO.output(int(data), GPIO.LOW) # Fa un DOWN del pin s.close() # Tanca la connexió

26.7

103

0.705368

0

451

0.55886

a978a3e063f71ae417a8f86e87e70e36b033503d

16,820

py

Python

src/mlpro/rl/pool/envmodels/mlp_robotinhtm.py

fhswf/MLPro

e944b69bed9c2d5548677711270e4a4fe868aea9

[ "Apache-2.0" ]

5

2022-01-31T15:52:19.000Z

2022-03-21T18:34:27.000Z

src/mlpro/rl/pool/envmodels/mlp_robotinhtm.py

fhswf/MLPro

e944b69bed9c2d5548677711270e4a4fe868aea9

[ "Apache-2.0" ]

61

2021-12-17T13:03:59.000Z

2022-03-31T10:24:37.000Z

src/mlpro/rl/pool/envmodels/mlp_robotinhtm.py

fhswf/MLPro

e944b69bed9c2d5548677711270e4a4fe868aea9

[ "Apache-2.0" ]

null

## ------------------------------------------------------------------------------------------------- ## -- Project : MLPro - A Synoptic Framework for Standardized Machine Learning Tasks ## -- Package : mlpro.rl.envmodels ## -- Module : mlp_robotinhtm ## ------------------------------------------------------------------------------------------------- ## -- History : ## -- yyyy-mm-dd Ver. Auth. Description ## -- 2021-12-17 0.0.0 MRD Creation ## -- 2021-12-17 1.0.0 MRD Released first version ## -- 2021-12-20 1.0.1 DA Replaced 'done' by 'success' ## -- 2021-12-21 1.0.2 DA Class MLPEnvMdel: renamed method reset() to _reset() ## -- 2022-01-02 2.0.0 MRD Refactoring due to the changes on afct pool on ## -- TorchAFctTrans ## -- 2022-02-25 2.0.1 SY Refactoring due to auto generated ID in class Dimension ## ------------------------------------------------------------------------------------------------- """ Ver. 2.0.1 (2022-02-25) This module provides Environment Model based on MLP Neural Network for robotinhtm environment. """ import torch import transformations from mlpro.rl.models import * from mlpro.rl.pool.envs.robotinhtm import RobotArm3D from mlpro.rl.pool.envs.robotinhtm import RobotHTM from mlpro.sl.pool.afct.afctrans_pytorch import TorchAFctTrans from torch.utils.data.sampler import SubsetRandomSampler from collections import deque def init(module, weight_init, bias_init, gain=1): weight_init(module.weight.data, gain=gain) bias_init(module.bias.data) return module class RobotMLPModel(torch.nn.Module): def __init__(self, n_joint, timeStep): super(RobotMLPModel, self).__init__() self.n_joint = n_joint self.timeStep = timeStep self.hidden = 128 init_ = lambda m: init(m, torch.nn.init.orthogonal_, lambda x: torch.nn.init. constant_(x, 0), np.sqrt(2)) self.model1 = torch.nn.Sequential( init_(torch.nn.Linear(self.n_joint,self.hidden)), torch.nn.Tanh(), init_(torch.nn.Linear(self.hidden,self.hidden)), torch.nn.Tanh(), init_(torch.nn.Linear(self.hidden,self.hidden)), torch.nn.Tanh(), init_(torch.nn.Linear(self.hidden,7*(self.n_joint+1))), torch.nn.Tanh() ) def forward(self, I): BatchSize=I.shape[0] newI = I.reshape(BatchSize,2,self.n_joint) * torch.cat([torch.Tensor([self.timeStep]).repeat(1,self.n_joint), torch.ones(1,self.n_joint)]) newI = torch.sum(newI,dim=1) out2 = self.model1(newI) out2 = out2.reshape(BatchSize,self.n_joint+1,7) return out2 class IOElement(BufferElement): def __init__(self, p_input: torch.Tensor, p_output: torch.Tensor): super().__init__({"input": p_input, "output": p_output}) # Buffer class MyOwnBuffer(Buffer, torch.utils.data.Dataset): def __init__(self, p_size=1): Buffer.__init__(self, p_size=p_size) self._internal_counter = 0 def add_element(self, p_elem: BufferElement): Buffer.add_element(self, p_elem) self._internal_counter += 1 def get_internal_counter(self): return self._internal_counter def __getitem__(self,idx): return self._data_buffer["input"][idx], self._data_buffer["output"][idx] class RobothtmAFct(TorchAFctTrans): C_NAME = "Robothtm Adaptive Function" C_BUFFER_CLS = MyOwnBuffer def _setup_model(self): self.joint_num = self._output_space.get_num_dim() - 6 self.net_model = RobotMLPModel(self.joint_num, 0.01) self.optimizer = torch.optim.Adam(self.net_model.parameters(), lr=3e-4) self.loss_dyn = torch.nn.MSELoss() self.train_model = True self.input_temp = None self.sim_env = RobotArm3D() joints = [] jointType = [] vectLinkLength = [[0, 0, 0], [0, 0, 0]] jointType.append("rz") for joint in range(self.joint_num - 1): vectLinkLength.append([0, 0.7, 0]) jointType.append("rx") jointType.append("f") for x in range(len(jointType)): vectorLink = dict(x=vectLinkLength[x][0], y=vectLinkLength[x][1], z=vectLinkLength[x][2]) joint = dict( Joint_name="Joint %d" % x, Joint_type=jointType[x], Vector_link_length=vectorLink, ) joints.append(joint) for robo in joints: self.sim_env.add_link_joint( lvector=torch.Tensor( [ [ robo["Vector_link_length"]["x"], robo["Vector_link_length"]["y"], robo["Vector_link_length"]["z"], ] ] ), jointAxis=robo["Joint_type"], thetaInit=torch.Tensor([np.radians(0)]), ) self.sim_env.update_joint_coords() def _input_preproc(self, p_input: torch.Tensor) -> torch.Tensor: input = torch.cat([p_input[0][6+self.joint_num:], p_input[0][6:6+self.joint_num]]) input = input.reshape(1,self.joint_num*2) self.input_temp = p_input[0][:3].reshape(1,3) return input def _output_postproc(self, p_output: torch.Tensor) -> torch.Tensor: angles = torch.Tensor([]) thets = torch.zeros(3) for idx in range(self.joint_num): angle = torch.Tensor(transformations.euler_from_quaternion(p_output[-1][idx][3:].detach().numpy(), axes="rxyz")) - thets thets = torch.Tensor(transformations.euler_from_quaternion(p_output[-1][idx][3:].detach().numpy(), axes="rxyz")) angles = torch.cat([angles, torch.norm(angle).reshape(1, 1)], dim=1) output = torch.cat([self.input_temp, p_output[-1][-1][:3].reshape(1,3)], dim=1) output = torch.cat([output, angles], dim=1) return output def _adapt(self, p_input: Element, p_output: Element) -> bool: model_input = deque(p_input.get_values()[6:]) model_input.rotate(self.joint_num) model_input = torch.Tensor([list(model_input)]) self.sim_env.set_theta(torch.Tensor([p_output.get_values()[6 : 6 + self.joint_num]])) self.sim_env.update_joint_coords() model_output = self.sim_env.convert_to_quaternion().reshape(1,self.joint_num+1,7) self._add_buffer(IOElement(model_input, model_output)) if self._buffer.get_internal_counter() % 100 != 0: return False # Divide Test and Train if self.train_model: dataset_size = len(self._buffer) indices = list(range(dataset_size)) split = int(np.floor(0.3 * dataset_size)) np.random.seed(random.randint(1,1000)) np.random.shuffle(indices) train_indices, test_indices = indices[split:], indices[:split] train_sampler = SubsetRandomSampler(train_indices) test_sampler = SubsetRandomSampler(test_indices) trainer = torch.utils.data.DataLoader(self._buffer, batch_size=100, sampler=train_sampler) tester = torch.utils.data.DataLoader(self._buffer, batch_size=100, sampler=test_sampler) # Training self.net_model.train() for i, (In, Label) in enumerate(trainer): outputs = self.net_model(In) loss = self.loss_dyn(outputs, Label) self.optimizer.zero_grad() loss.backward() self.optimizer.step() test_loss = 0 self.net_model.eval() for i, (In, Label) in enumerate(tester): outputs = self.net_model(In) loss = self.loss_dyn(outputs, Label) test_loss += loss.item() if test_loss/len(tester) < 5e-9: self.train_model = False return True def _add_buffer(self, p_buffer_element: IOElement): self._buffer.add_element(p_buffer_element) class MLPEnvModel(EnvModel, Mode): C_NAME = "HTM Env Model" def __init__( self, p_num_joints=4, p_target_mode="Random", p_ada=True, p_logging=False, ): # Define all the adaptive function here self.RobotArm1 = RobotArm3D() roboconf = {} roboconf["Joints"] = [] jointType = [] vectLinkLength = [[0, 0, 0], [0, 0, 0]] jointType.append("rz") for joint in range(p_num_joints - 1): vectLinkLength.append([0, 0.7, 0]) jointType.append("rx") jointType.append("f") for x in range(len(jointType)): vectorLink = dict(x=vectLinkLength[x][0], y=vectLinkLength[x][1], z=vectLinkLength[x][2]) joint = dict( Joint_name="Joint %d" % x, Joint_type=jointType[x], Vector_link_length=vectorLink, ) roboconf["Joints"].append(joint) roboconf["Target_mode"] = p_target_mode roboconf["Update_rate"] = 0.01 for robo in roboconf["Joints"]: self.RobotArm1.add_link_joint( lvector=torch.Tensor( [ [ robo["Vector_link_length"]["x"], robo["Vector_link_length"]["y"], robo["Vector_link_length"]["z"], ] ] ), jointAxis=robo["Joint_type"], thetaInit=torch.Tensor([np.radians(0)]), ) self.RobotArm1.update_joint_coords() self.jointangles = self.RobotArm1.thetas self.dt = roboconf["Update_rate"] self.modes = roboconf["Target_mode"] self.target = None self.init_distance = None self.num_joint = self.RobotArm1.get_num_joint() self.reach = torch.norm(torch.Tensor([[0.0, 0.0, 0.0]]) - self.RobotArm1.joints[:3, [-1]].reshape(1, 3)) # Setup space # 1 Setup state space obs_space = ESpace() obs_space.add_dim(Dimension("Tx", "Targetx", "", "m", "m", p_boundaries=[-np.inf, np.inf])) obs_space.add_dim(Dimension("Ty", "Targety", "", "m", "m", p_boundaries=[-np.inf, np.inf])) obs_space.add_dim(Dimension("Tz", "Targetz", "", "m", "m", p_boundaries=[-np.inf, np.inf])) obs_space.add_dim(Dimension("Px", "Targetx", "", "m", "m", p_boundaries=[-np.inf, np.inf])) obs_space.add_dim(Dimension("Py", "Targety", "", "m", "m", p_boundaries=[-np.inf, np.inf])) obs_space.add_dim(Dimension("Pz", "Targetz", "", "m", "m", p_boundaries=[-np.inf, np.inf])) for idx in range(self.num_joint): obs_space.add_dim( Dimension("J%i" % (idx), "Joint%i" % (idx), "", "deg", "deg", p_boundaries=[-np.inf, np.inf]) ) # 2 Setup action space action_space = ESpace() for idx in range(self.num_joint): action_space.add_dim( Dimension( "A%i" % (idx), "AV%i" % (idx), "", "rad/sec", "\frac{rad}{sec}", p_boundaries=[-np.pi, np.pi], ) ) # Setup Adaptive Function # HTM Function Here afct_strans = AFctSTrans( RobothtmAFct, p_state_space=obs_space, p_action_space=action_space, p_threshold=-1, p_buffer_size=10000, p_ada=p_ada, p_logging=p_logging, ) EnvModel.__init__( self, p_observation_space=obs_space, p_action_space=action_space, p_latency=timedelta(seconds=self.dt), p_afct_strans=afct_strans, p_afct_reward=None, p_afct_success=None, p_afct_broken=None, p_ada=p_ada, p_logging=p_logging, ) Mode.__init__(self, p_mode=Mode.C_MODE_SIM, p_logging=p_logging) if self.modes == "random": num = random.random() if num < 0.2: self.target = torch.Tensor([[0.5, 0.5, 0.5]]) self.init_distance = torch.norm(self.RobotArm1.joints[:3, [-1]].reshape(1, 3) - self.target) elif num < 0.4: self.target = torch.Tensor([[0.0, 0.5, 0.5]]) self.init_distance = torch.norm(self.RobotArm1.joints[:3, [-1]].reshape(1, 3) - self.target) elif num < 0.6: self.target = torch.Tensor([[-0.5, 0.0, 0.5]]) self.init_distance = torch.norm(self.RobotArm1.joints[:3, [-1]].reshape(1, 3) - self.target) elif num < 0.8: self.target = torch.Tensor([[0.0, -0.5, 0.5]]) self.init_distance = torch.norm(self.RobotArm1.joints[:3, [-1]].reshape(1, 3) - self.target) else: self.target = torch.Tensor([[-0.5, -0.5, 0.5]]) self.init_distance = torch.norm(self.RobotArm1.joints[:3, [-1]].reshape(1, 3) - self.target) else: self.target = torch.Tensor([[0.5, 0.5, 0.5]]) self.init_distance = torch.norm(self.RobotArm1.joints[:3, [-1]].reshape(1, 3) - self.target) self.reset() ## ------------------------------------------------------------------------------------------------- def _compute_success(self, p_state: State = None) -> bool: # disterror = np.linalg.norm(p_state.get_values()[:3] - p_state.get_values()[3:6]) disterror = np.linalg.norm(np.array(p_state.get_values())[:3] - np.array(p_state.get_values())[3:6]) if disterror <= 0.1: self._state.set_terminal(True) return True else: return False ## ------------------------------------------------------------------------------------------------- def _compute_broken(self, p_state: State) -> bool: return False ## ------------------------------------------------------------------------------------------------- def _compute_reward(self, p_state_old: State, p_state_new: State) -> Reward: reward = Reward(self.C_REWARD_TYPE) # disterror = np.linalg.norm(p_state_new.get_values()[:3] - p_state_new.get_values()[3:6]) disterror = np.linalg.norm(np.array(p_state_new.get_values())[:3] - np.array(p_state_new.get_values())[3:6]) ratio = disterror / self.init_distance.item() rew = -np.ones(1) * ratio rew = rew - 10e-2 if disterror <= 0.1: rew = rew + 1 rew = rew.astype("float64") reward.set_overall_reward(rew) return reward def set_theta(self, theta): self.RobotArm1.thetas = theta.reshape(self.num_joint) self.RobotArm1.update_joint_coords() self.jointangles = self.RobotArm1.thetas def _reset(self, p_seed=None) -> None: self.set_random_seed(p_seed) theta = torch.zeros(self.RobotArm1.get_num_joint()) self.RobotArm1.set_theta(theta) self.RobotArm1.update_joint_coords() self.jointangles = self.RobotArm1.thetas if self.modes == "random": num = random.random() if num < 0.2: self.target = torch.Tensor([[0.5, 0.5, 0.5]]) self.init_distance = torch.norm(self.RobotArm1.joints[:3, [-1]].reshape(1, 3) - self.target) elif num < 0.4: self.target = torch.Tensor([[0.0, 0.5, 0.5]]) self.init_distance = torch.norm(self.RobotArm1.joints[:3, [-1]].reshape(1, 3) - self.target) elif num < 0.6: self.target = torch.Tensor([[-0.5, 0.0, 0.5]]) self.init_distance = torch.norm(self.RobotArm1.joints[:3, [-1]].reshape(1, 3) - self.target) elif num < 0.8: self.target = torch.Tensor([[0.0, -0.5, 0.5]]) self.init_distance = torch.norm(self.RobotArm1.joints[:3, [-1]].reshape(1, 3) - self.target) else: self.target = torch.Tensor([[-0.5, -0.5, 0.5]]) self.init_distance = torch.norm(self.RobotArm1.joints[:3, [-1]].reshape(1, 3) - self.target) obs = torch.cat( [ self.target, self.RobotArm1.joints[:3, [-1]].reshape(1, 3), self.RobotArm1.thetas.reshape(1, self.num_joint), ], dim=1, ) obs = obs.cpu().flatten().tolist() self._state = State(self._state_space) self._state.set_values(obs)

39.299065

146

0.542866

15,189

0.903032

0

2,363

0.140488

a979eac6a7daaac0fe50d966818c9860d5136601

3,474

py

Python

pyxlpr/data/icdar/__init__.py

XLPRUtils/pyUtils

3a62c14b0658ad3c24d83f953ee0d88530b02b23

[ "Apache-2.0" ]

15

2020-06-09T07:03:07.000Z

2022-02-25T06:59:34.000Z

pyxlpr/data/icdar/__init__.py

XLPRUtils/pyUtils

3a62c14b0658ad3c24d83f953ee0d88530b02b23

[ "Apache-2.0" ]

5

2020-08-08T07:11:21.000Z

2020-08-08T07:11:24.000Z

pyxlpr/data/icdar/__init__.py

XLPRUtils/pyUtils

3a62c14b0658ad3c24d83f953ee0d88530b02b23

[ "Apache-2.0" ]

2

2020-06-09T07:03:26.000Z

2020-12-31T06:50:37.000Z

#!/usr/bin/env python3 # -*- coding: utf-8 -*- # @Author : 陈坤泽 # @Email : [email protected] # @Date : 2021/02/22 10:29 """ 对icdar2013的三种测评方法的接口封装官方原版处理两个 zip 文件，这里扩展支持目录、内存对象 """ import re from pyxllib.xl import File, Dir, shorten class IcdarEval: """ >>> gt = {'1.abc': [[158, 128, 411, 181], [443, 128, 450, 169]], '2': [[176, 189, 456, 274]]} >>> dt = {'1.abc': [[158, 128, 411, 185], [443, 120, 450, 169]]} >>> ie = IcdarEval(gt, dt) # 除了内存格式，也兼容原来的zip文件、目录初始化方法 >>> ie.icdar2013() {'precision': 1.0, 'recall': 0.6667, 'hmean': 0.8} >>> ie.deteval() {'precision': 1.0, 'recall': 0.6667, 'hmean': 0.8} >>> ie.iou() {'precision': 1.0, 'recall': 0.6667, 'hmean': 0.8, 'AP': 0} """ def __init__(self, gt, dt): """ 输入gt和dt文件官方原版是支持【zip文件】，必须要遵循官方原版所有的规则压缩包里的文件名格式为： gt_img_1.txt， res_img_1.txt 我这里扩展，也支持输入【目录】，注意这种操作格式，除了文件名也要完全遵守官方的规则这里文件名降低要求，只匹配出第一个出现的数值还扩展了内存操作方式，这个格式比官方简洁，不需要遵循官方琐碎的规则，只需要 gt是一个dict key写图片名或id编号都可以 value写若干个定位框，例如 [[xmin1, ymin1, xmax1, ymax1], [xmin2, ymin2, xmax2, ymax2], ...] dt同gt，注意key要对应 icdar系列指标，原本是用于文本检测效果的评测，也可以扩展应用到一般性的检测任务 icdar只考虑单类，不考虑多类别问题，如果要加入类别问题，可以修改key达到更精细的分组效果附，官方原版格式说明 {'1': b'38,43,...', '2':, b'...', ...} key是图片编号1,2,3...233，其实改成其他各种key也行，就是一个分组概念 value是匹配效果，使用bytes格式，用\r\n作为换行符分开每个检测框对gt而言，存储x1,y1,x2,y2,label，最后必须要有个label值对dt而言，存储x1,y1,x2,y2 因为我这里底层做了扩展，所以从IcdarEval入口调用的测评，都是转成了我新的字典数据结构来预测的 """ self.gt = self.init_label(gt) self.dt = self.init_label(dt) @classmethod def init_label(cls, label): if isinstance(label, dict): # 如果是字典，信任其是按照官方格式来标注的 # {'16000,1': b'566,227,673,261,0\n682,210,945,260,0', '16001,1': ... return label elif isinstance(label, (str, File)) and str(label)[-4:].lower() == '.zip': # 官方原版的 zip 文件初始化方法 return label elif Dir.safe_init(label): # 输入是目录，则按照数字编号大小顺序依次读数数据 d = Dir(label) res = dict() for f in d.select_files('*.txt'): k = re.search(r'\d+', f.stem).group() res[k] = f.read(mode='b') return res else: raise TypeError(shorten(label)) def _eval(self, evaluate_method, default_evaluation_params, update_params): eval_params = default_evaluation_params() if update_params: eval_params.update(update_params) eval_data = evaluate_method(self.gt, self.dt, eval_params) # eval_data字典还存有'per_sample'的每张图片详细数据 res = {k: round(v, 4) for k, v in eval_data['method'].items()} # 只保留4位小数，看起来比较舒服 return res def icdar2013(self, params=None): from pyxllib.data.icdar.icdar2013 import evaluate_method, default_evaluation_params return self._eval(evaluate_method, default_evaluation_params, params) def deteval(self, params=None): from pyxllib.data.icdar.deteval import evaluate_method, default_evaluation_params return self._eval(evaluate_method, default_evaluation_params, params) def iou(self, params=None): from pyxllib.data.icdar.iou import evaluate_method, default_evaluation_params return self._eval(evaluate_method, default_evaluation_params, params)

35.814433

97

0.600173

4,185

0.928762

0

820

0.18198

0

2,770

0.614736

a97a18817825892c952ac7174c04fcf55fabab56

6,441

py

Python

MTL/features.py

usc-sail/mica-riskybehavior-identification

dd8d1bb795ca1b8273625713887c6c4b747fd542

[ "MIT" ]

2

2020-11-19T21:22:53.000Z

2021-02-25T00:29:38.000Z

MTL/features.py

usc-sail/mica-riskybehavior-identification

dd8d1bb795ca1b8273625713887c6c4b747fd542

[ "MIT" ]

null

MTL/features.py

usc-sail/mica-riskybehavior-identification

dd8d1bb795ca1b8273625713887c6c4b747fd542

[ "MIT" ]

1

2021-02-05T22:45:51.000Z

import os import numpy as np import torch from transformers import BertTokenizer from tensorflow.keras.utils import to_categorical from NewDataLoader import * from config import * import warnings class Features: def __init__(self, **kwargs): self.max_len = kwargs.get('max_len', 250) self.categorical = kwargs.get('categorical', True) self.wordrepr = kwargs.get('wordrepr', 'toronto_sent2vec') self.sentrepr = kwargs.get('sentrepr', 'sentiment') self.bert_selector = kwargs.get('bert_selector', 'None') # Transform into H/M/L self.categorize_F = np.vectorize(self.categorize) # Feature size self.WORD_SIZE = FEATS_SIZES[self.wordrepr] if self.bert_selector == "first" or self.bert_selector == "last": self.WORD_SIZE = int(self.WORD_SIZE / 2) self.SENT_SIZE = FEATS_SIZES[self.sentrepr] if self.sentrepr == "bert": if self.bert_selector == "first" or self.bert_selector == "last": self.SENT_SIZE = int(self.SENT_SIZE / 2) print("Features:", self.wordrepr, self.sentrepr, self.max_len, self.bert_selector) ################################################ # Transform ordinal ratings into categorical ################################################ def categorize(self, rating): if rating >= 4: return 0 #HIGH elif rating > 2: return 1 #MED else: return 2 #LOW ################################################ # Loads features and trims them to max_len ################################################ def get_feats(self, label_f, batch_dir = None): if not batch_dir: batch_dir = os.path.dirname(label_f) # Labels batch_labels, additional_labels = load_labels(label_f) batch_labels = np.c_[batch_labels, additional_labels] if self.categorical: batch_labels = self.categorize_F(batch_labels) #H/M/L batch_labels = to_categorical(batch_labels, num_classes = 3) #One-hot encoding vio, sex, drugs = batch_labels[:, 0, :], batch_labels[:, 1, :], batch_labels[:, 2, :] y = [vio, sex, drugs] # Get the index from the filename i = os.path.basename(label_f).split("_")[0] i = i.replace('.npz', '') # Genre batch_genre = load_genre(i, batch_dir) # Words if self.wordrepr in ['sent2vec', 'word2vec', 'script_word2vec', 'toronto_sent2vec']: word_features = load_w2v_or_p2v(i, batch_dir, FEATS_SIZES, self.wordrepr) elif self.wordrepr in ['bert_large', 'bert_base', 'sst', 'moviebert']: word_features = load_BERT(i, batch_dir, FEATS_SIZES, mode = self.wordrepr, bert_selector = self.bert_selector) elif self.wordrepr in ['ngrams', 'tfidf']: word_features = load_tf_or_idf(i, batch_dir, self.wordrepr) # Sentiment if self.sentrepr in ['sentiment']: sentiment_features = load_w2v_or_p2v(i, batch_dir, FEATS_SIZES, "sentiment") elif self.sentrepr in ['bert_large', 'bert_base', 'sst', 'moviebert']: sentiment_features = load_BERT(i, batch_dir, FEATS_SIZES, mode = self.sentrepr, bert_selector = self.bert_selector) # elif sentrepr in ['sent_post', 'posteriors']: # sentiment_features = ??? word_features = word_features[:, -self.max_len:, :] #Trim sentiment_features = sentiment_features[:, -self.max_len:, :] return ([word_features, sentiment_features, batch_genre], y) def get_feats_any_only(self, label_f, index = 0, batch_dir = None): ([word_features, sentiment_features, batch_genre], y) = self.get_feats(label_f, batch_dir = batch_dir) return ([word_features, sentiment_features, batch_genre], y[index]) def get_feats_vio_only(self, label_f, batch_dir = None): return self.get_feats_any_only(label_f, index = 0, batch_dir = batch_dir) def get_feats_sex_only(self, label_f, batch_dir = None): return self.get_feats_any_only(label_f, index = 1, batch_dir = batch_dir) def get_feats_drugs_only(self, label_f, batch_dir = None): return self.get_feats_any_only(label_f, index = 2, batch_dir = batch_dir) def get_concat_feats(self, label_f, batch_dir = None): (word_features, sentiment_features, batch_genre), batch_labels = self.get_feats(label_f, batch_dir) feats = np.concatenate([word_features, sentiment_features], axis = 2) return [feats, batch_genre], batch_labels[0] class BertFeatures(Features): """This class goes from text to padded transformer features""" def __init__(self, **kwargs): super().__init__(**kwargs) self.name = kwargs.get('bert_name', 'bert-base-uncased') self.tokenizer = BertTokenizer.from_pretrained(self.name) self.max_len = kwargs.get('max_len', self.tokenizer.max_len) self.categorical = kwargs.get('categorical', True) if self.max_len > self.tokenizer.max_len: warnings.warn("max_len > tokenizer({}).max_len.".format(self.name)) print("BertFeatures:", self.name, self.max_len) def get_feats(self, label_f, batch_dir = None): if not batch_dir: batch_dir = os.path.dirname(label_f) # Labels batch_labels, additional_labels = load_labels(label_f) batch_labels = np.c_[batch_labels, additional_labels] if self.categorical: batch_labels = self.categorize_F(batch_labels) #H/M/L batch_labels = to_categorical(batch_labels, num_classes = 3) #One-hot encoding vio, sex, drugs = batch_labels[:, 0], batch_labels[:, 1], batch_labels[:, 2] y = [vio, sex, drugs] # Get the index from the filename i = os.path.basename(label_f).split("_")[0] i = i.replace('.npz', '') # Genre batch_genre = load_genre(i, batch_dir) # features = [] for row in load_text(i, batch_dir): # Tokenize and trim text = self.tokenizer.tokenize(row)[-self.max_len:] # Encode text input_ids = torch.tensor([self.tokenizer.encode(text, add_special_tokens = True)]) features.append(input_ids) # Convert to tensor features = torch.cat(features, dim = 0) return ([features, batch_genre], y)

38.568862

127

0.621798

6,237

0.968328

0

1,107

0.171868

a97af6a55423ad89ce397dfb867db2824473473b

1,233

py

Python

project_4_data_pipelines/airflow/plugins/helpers/sparkify_dim_subdag.py

jpuris/udacity-data-engineering-submissions

e71e2569241c76b5e6c3cd074667b19bde4d7b9e

[ "MIT" ]

null

project_4_data_pipelines/airflow/plugins/helpers/sparkify_dim_subdag.py

jpuris/udacity-data-engineering-submissions

e71e2569241c76b5e6c3cd074667b19bde4d7b9e

[ "MIT" ]

null

project_4_data_pipelines/airflow/plugins/helpers/sparkify_dim_subdag.py

jpuris/udacity-data-engineering-submissions

e71e2569241c76b5e6c3cd074667b19bde4d7b9e

[ "MIT" ]

null

from airflow import DAG from operators import LoadDimensionOperator def load_dim_subdag( parent_dag_name: str, task_id: str, redshift_conn_id: str, sql_statement: str, do_truncate: bool, table_name: str, **kwargs, ): """ Airflow's subdag wrapper. Implements LoadDimensionOperator operator. Subdag's name will be f'{parent_dag_name}.{task_id}' Subdag related keyword arguments: - parent_dag_name -- Parent DAG name - task_id -- Task ID for the subdag to use Keyword arguments: redshift_conn_id -- Airflow connection name for Redshift detail sql_statement -- SQL statement to run do_truncate -- Does the table need to be truncated before running SQL statement table_name -- Dimension table name All keyword arguments will be passed to LoadDimensionOperator """ dag = DAG(f'{parent_dag_name}.{task_id}', **kwargs) load_dimension_table = LoadDimensionOperator( task_id=task_id, dag=dag, redshift_conn_id=redshift_conn_id, sql_query=sql_statement, do_truncate=do_truncate, table_name=table_name, ) load_dimension_table return dag

26.804348

75

0.673155

0

673

0.545823

a97bced1b47f7e35fb054962b9c59fd468c4c16b

1,816

py

Python

inference.py

Retrospection/Yolo-v2-pytorch

d2028219a250e50e03340538faab197ac8ece8a8

[ "MIT" ]

null

inference.py

Retrospection/Yolo-v2-pytorch

d2028219a250e50e03340538faab197ac8ece8a8

[ "MIT" ]

null

inference.py

Retrospection/Yolo-v2-pytorch

d2028219a250e50e03340538faab197ac8ece8a8

[ "MIT" ]

1

2021-12-28T08:13:05.000Z

# coding: utf-8 from __future__ import print_function from __future__ import absolute_import from __future__ import division from src.yolo_net import YoloTest, Yolo import torch import cv2 import numpy as np def read_image(path): img1 = cv2.imread(path) img1 = cv2.resize(img1, (224, 224)) img1 = img1.transpose((2, 0, 1)) img1 = img1[np.newaxis, :, :, :] return torch.Tensor(img1) class FeatureExtractor(object): def __init__(self): self.net = YoloTest() state_dict = torch.load('trained_models\\only_params_trained_yolo_coco') del state_dict['stage3_conv2.weight'] self.net.load_state_dict(state_dict) self.net.eval() def get_feature(self, image_path): image = read_image(image_path) return self.net(image).reshape((1024 * 7 * 7)).detach().numpy() # net = Yolo(10177) # state_dict = torch.load('trained_models\\only_params_trained_yolo_coco') # net.load_state_dict(state_dict) # net.eval() # img10 = readImage('D:\\dev\\dataset\\CASIA-WebFace\\0000045\\001.jpg') # img11 = readImage('D:\\dev\\dataset\\CASIA-WebFace\\0000045\\002.jpg') # img21 = readImage('D:\\dev\\dataset\\CASIA-WebFace\\0000099\\001.jpg') # # logits = net(img10) # print(logits.view(1, 5, -1, 49).shape) # output10 = net(img10).reshape((1024*7*7,)).detach().numpy() # output11 = net(img11).reshape((1024*7*7,)).detach().numpy() # output21 = net(img21).reshape((1024*7*7,)).detach().numpy() # dis11 = np.linalg.norm(output10 - output11) # dis21 = np.linalg.norm(output10 - output21) # # print(dis11) # print(dis21) # # # def cosdis(vec1, vec2): # return np.dot(vec1,vec2)/(np.linalg.norm(vec1)*(np.linalg.norm(vec2))) # # cosdis11 = cosdis(output10, output11) # cosdis21 = cosdis(output10, output21) # print(cosdis11) # print(cosdis21)

24.876712

80

0.680617

433

0.238436

0

1,017

0.560022

a97e81a89bda65fad9ab35f52160822fa9349f8c

11,572

py

Python

geetools/collection/modis.py

carderne/gee_tools

4003e75ffb0ffefc9f41b1a34d849eebdb486161

[ "MIT" ]

null

geetools/collection/modis.py

carderne/gee_tools

4003e75ffb0ffefc9f41b1a34d849eebdb486161

[ "MIT" ]

null

geetools/collection/modis.py

carderne/gee_tools

4003e75ffb0ffefc9f41b1a34d849eebdb486161

[ "MIT" ]

null

# coding=utf-8 """ Google Earth Engine MODIS Collections """ from . import Collection, TODAY, Band from functools import partial IDS = [ 'MODIS/006/MOD09GQ', 'MODIS/006/MYD09GQ', 'MODIS/006/MOD09GA', 'MODIS/006/MYD09GA', 'MODIS/006/MOD13Q1', 'MODIS/006/MYD13Q1' ] START = { 'MODIS/006/MOD09GQ': '2000-02-24', 'MODIS/006/MYD09GQ': '2000-02-24', 'MODIS/006/MOD09GA': '2000-02-24', 'MODIS/006/MYD09GA': '2000-02-24', 'MODIS/006/MOD13Q1': '2000-02-18', 'MODIS/006/MYD13Q1': '2000-02-18', } END = { 'MODIS/006/MOD09GQ': TODAY, 'MODIS/006/MYD09GQ': TODAY, 'MODIS/006/MOD09GA': TODAY, 'MODIS/006/MYD09GA': TODAY, 'MODIS/006/MOD13Q1': TODAY, 'MODIS/006/MYD13Q1': TODAY, } class MODIS(Collection): """ MODIS Collections """ SHORTS = { 'MODIS/006/MOD09GQ': 'TERRA_SR_250_DAILY', 'MODIS/006/MYD09GQ': 'AQUA_SR_250_DAILY', 'MODIS/006/MOD09GA': 'TERRA_SR_1KM_DAILY', 'MODIS/006/MYD09GA': 'AQUA_SR_1KM_DAILY', 'MODIS/006/MOD13Q1': 'TERRA_IND_250_16DAYS', 'MODIS/006/MYD13Q1': 'AQUA_IND_250_16DAYS' } def __init__(self, product_id): """ Initialize a MODIS collection with it's product id """ super(MODIS, self).__init__() self.product_id = product_id self._id = self._make_id() self._bands = self._make_bands() # dates self.start_date = START[self._id] self.end_date = END[self._id] self.spacecraft = 'MODIS' self.cloud_cover = None self.short_name = self.SHORTS.get(self.id) if self._id in ['MODIS/006/MOD09GQ', 'MODIS/006/MYD09GQ']: self.common_masks = [self.qc250] if self._id in ['MODIS/006/MOD09GA', 'MODIS/006/MYD09GA']: self.common_masks = [self.state_1km] if self._id in ['MODIS/006/MOD13Q1', 'MODIS/006/MYD13Q1']: self.common_masks = [self.detailed_qa] def state_1km(self, image, classes=('cloud', 'shadow', 'snow', 'average_cirrus', 'high_cirrus'), renamed=False): return self.applyMask(image, 'state_1km', classes, renamed) def qc250(self, image, classes=('B1_highest_quality', 'B2_highest_quality'), renamed=False): return self.applyPositiveMask(image, 'QC_250m', classes, renamed) def detailed_qa(self, image, classes=('cloud', 'shadow', 'snow'), renamed=False): if renamed: band ='DetailedQA' else: band = 'detailed_qa' return self.applyMask(image, band, classes, renamed) def _make_bands(self): bands = [None]*30 # Partial bands sur_refl_b01 = partial(Band, id='sur_refl_b01', name='red', precision='int16', min=-100, max=16000, reference='optical') sur_refl_b02 = partial(Band, id='sur_refl_b02', name='nir', precision='int16', min=-100, max=16000, reference='optical') num_observations = partial(Band, precision='int8', min=0, max=127, reference='classification') QC_250m = Band('QC_250m', 'QC_250m', 'uint16', 250, 0, 4096, 'bits', bits={ '4-7': {0: 'B1_highest_quality'}, '8-11': {0: 'B2_highest_quality'}, '12': {1: 'atmospheric_corrected'} }) obscov = partial(Band, precision='int8', min=0, max=100, reference='classification') iobs_res = partial(Band, id='iobs_res', name='obs_number', precision='uint8', min=0, max=254, reference='classification') orbit_pnt = partial(Band, id='orbit_pnt', name='orbit_pointer', precision='int8', min=0, max=15, reference='classification') granule_pnt = partial(Band, id='granule_pnt', name='granule_pointer', precision='uint8', min=0, max=254, reference='classification') state_1km = Band('state_1km', 'state_1km', 'uint16', 1000, 0, 57335, 'bits', bits={ '0-1': {0: 'clear', 1:'cloud', 2:'mix'}, '2': {1: 'shadow'}, '8-9': {1: 'small_cirrus', 2: 'average_cirrus', 3: 'high_cirrus'}, '13': {1: 'adjacent'}, '15': {1: 'snow'} }) sezenith = Band('SensorZenith', 'sensor_zenith', 'int16', 1000, 0, 18000, 'classification') seazimuth = Band('SensorAzimuth', 'sensor_azimuth', 'int16', 1000, -18000, 18000, 'classification') range_band = Band('Range', 'range', 'uint16', 1000, 27000, 65535, 'classification') sozenith = Band('SolarZenith', 'solar_zenith', 'int16', 1000, 0, 18000, 'classification') soazimuth = Band('SolarAzimuth', 'solar_azimuth', 'int16', 1000, -18000, 18000, 'classification') gflags = Band('gflags', 'geolocation_flags', 'uint8', 1000, 0, 248, 'bits') sur_refl_b03 = partial(Band, id='sur_refl_b03', name='blue', precision='int16', min=-100, max=16000, reference='optical') sur_refl_b04 = partial(Band, id='sur_refl_b04', name='green', precision='int16', min=-100, max=16000, reference='optical') sur_refl_b05 = partial(Band, id='sur_refl_b05', name='swir3', precision='int16', min=-100, max=16000, reference='optical') sur_refl_b06 = partial(Band, id='sur_refl_b06', name='swir', precision='int16', min=-100, max=16000, reference='optical') sur_refl_b07 = partial(Band, id='sur_refl_b07', name='swir2', precision='int16', min=-100, max=16000, reference='optical') QC_500m = Band('QC_500m', 'QC_500m', 'uint32', 500, 0, 4294966019, 'bits', bits={ '2-5': {0: 'B1_highest_quality'}, '6-9': {0: 'B2_highest_quality'}, '10-13': {0: 'B3_highest_quality'}, '14-17': {0: 'B4_highest_quality'}, '18-21': {0: 'B5_highest_quality'}, '22-25': {0: 'B6_highest_quality'}, '26-29': {0: 'B7_highest_quality'}, }) qscan = Band('q_scan', 'q_scan', 'uint8', 250, 0, 254, 'bits') NDVI = Band('NDVI', 'ndvi', 'int16', 250, -2000, 10000, 'classification') EVI = Band('EVI', 'evi', 'int16', 250, -2000, 10000, 'classification') DetailedQA = Band('DetailedQA', 'detailed_qa', 'uint16', 250, 0, 65534, 'bits', bits={ '0-1': {0: 'good_qa'}, '2-5': {0: 'highest_qa'}, '8': {1: 'adjacent'}, '10': {1: 'cloud'}, '14': {1: 'snow'}, '15': {1: 'shadow'} }) view_zenith = Band('ViewZenith', 'view_zenith', 'int16', 250, 0, 18000, 'classification') relative_azimuth = Band('RelativeAzimuth', 'relative_azimuth', 'int16', 250, -18000, 18000, 'classification') DayOfYear = Band('DayOfYear', 'day_of_year', 'int16', 250, 1, 366, 'classification') SummaryQA = Band('SummaryQA', 'summary_qa', 'int8', 250, 0, 3, 'bits', bits={ '0-1': {0: 'clear', 1: 'marginal', 2: 'snow', 3: 'cloud'} }) if self.product_id in ['MOD09GQ', 'MYD09GQ']: bands[0] = num_observations(id='num_observations', name='num_observations', scale=250) bands[1] = sur_refl_b01(scale=250) bands[2] = sur_refl_b02(scale=250) bands[3] = QC_250m bands[4] = obscov(id='obscov', name='observation_coverage', scale=250) bands[5] = iobs_res(scale=250) bands[6] = orbit_pnt(scale=250) bands[7] = granule_pnt(scale=250) if self.product_id in ['MOD09GA', 'MYD09GA']: bands[0] = num_observations(id='num_observations_1km', scale=1000, name='num_observations_1km') bands[1] = state_1km bands[2] = sezenith bands[3] = seazimuth bands[4] = range_band bands[5] = sozenith bands[6] = soazimuth bands[7] = gflags bands[8] = orbit_pnt(scale=500) bands[9] = granule_pnt(scale=500) bands[10] = num_observations(id='num_observations_500m', scale=500, name='num_observations_500m') bands[11] = sur_refl_b01(scale=500) bands[12] = sur_refl_b02(scale=500) bands[13] = sur_refl_b03(scale=500) bands[14] = sur_refl_b04(scale=500) bands[15] = sur_refl_b05(scale=500) bands[16] = sur_refl_b06(scale=500) bands[17] = sur_refl_b07(scale=500) bands[18] = QC_500m bands[19] = obscov(id='obscov_500m', scale=500, name='observation_coverage_500m') bands[20] = iobs_res(scale=500) bands[21] = qscan if self.product_id in ['MOD13Q1', 'MYD13Q1']: bands[0] = NDVI bands[1] = EVI bands[2] = DetailedQA bands[3] = sur_refl_b01(scale=250) bands[4] = sur_refl_b02(scale=250) bands[5] = sur_refl_b03(scale=250) bands[6] = sur_refl_b07(scale=250) bands[7] = view_zenith bands[8] = sozenith bands[9] = relative_azimuth bands[10] = DayOfYear bands[11] = SummaryQA return [b for b in bands if b] def _make_id(self): return 'MODIS/006/{}'.format(self.product_id) @staticmethod def fromId(id): """ Make a MODIS collection from its ID """ def error(): msg = 'Collection {} not available' raise ValueError(msg.format(id)) if id not in IDS: error() splitted = id.split('/') prod = splitted[2] return MODIS(prod) @classmethod def MOD09GQ(cls): return cls(product_id='MOD09GQ') @classmethod def MYD09GQ(cls): return cls(product_id='MYD09GQ') @classmethod def MOD09GA(cls): return cls(product_id='MOD09GA') @classmethod def MYD09GA(cls): return cls(product_id='MYD09GA') @classmethod def MOD13Q1(cls): return cls(product_id='MOD13Q1') @classmethod def MYD13Q1(cls): return cls(product_id='MYD13Q1')

38.317881

89

0.497753

10,841

0.93683

0

773

0.066799

0

3,118

0.269443

a97f5a52d2112340dd02628abcf36314406fa57c

338

py

Python

random-py/app.py

traian-mihali/publishing-py

fa050b1169258b50678f00b97958499bc0210ca3

[ "MIT" ]

null

random-py/app.py

traian-mihali/publishing-py

fa050b1169258b50678f00b97958499bc0210ca3

[ "MIT" ]

null

random-py/app.py

traian-mihali/publishing-py

fa050b1169258b50678f00b97958499bc0210ca3

[ "MIT" ]

null

""" This module provides a method to generate a random number between 0 and the specified number """ import random import math def random_num(max): """ Generates a random number Parameters: max(int): the range upper limit Returns: int: the random number """ return math.floor(random.random() * max)

19.882353

100

0.668639

0

238

0.704142

a980ed05ffe9a9c97a1b948b9c9b922dc89fb870

847

py

Python

sympy/printing/printer.py

certik/sympy-oldcore

eb5bd061c309d88cdfb502bfd5df511b30368458

[ "BSD-3-Clause" ]

1

2016-05-08T17:54:57.000Z

sympy/printing/printer.py

certik/sympy-oldcore

eb5bd061c309d88cdfb502bfd5df511b30368458

[ "BSD-3-Clause" ]

null

sympy/printing/printer.py

certik/sympy-oldcore

eb5bd061c309d88cdfb502bfd5df511b30368458

[ "BSD-3-Clause" ]

null

class Printer(object): """ """ def __init__(self): self._depth = -1 self._str = str self.emptyPrinter = str def doprint(self, expr): """Returns the pretty representation for expr (as a string)""" return self._str(self._print(expr)) def _print(self, expr): self._depth += 1 # See if the class of expr is known, or if one of its super # classes is known, and use that pretty function res = None for cls in expr.__class__.__mro__: if hasattr(self, '_print_'+cls.__name__): res = getattr(self, '_print_'+cls.__name__)(expr) break # Unknown object, just use its string representation if res is None: res = self.emptyPrinter(expr) self._depth -= 1 return res

27.322581

70

0.565525

845

0.997639

0

250

0.295159

a981fd9db88834f380bdfbae5402c0c579a7fa58

272

py

Python

pleiades/transforms.py

jcwright77/pleiades

e3e208e94feee299589a094f361b301131d1bd15

[ "MIT" ]

3

2020-03-27T19:27:01.000Z

2021-07-15T16:28:54.000Z

pleiades/transforms.py

jcwright77/pleiades

e3e208e94feee299589a094f361b301131d1bd15

[ "MIT" ]

6

2020-03-30T17:12:42.000Z

2020-07-14T03:07:02.000Z

pleiades/transforms.py

jcwright77/pleiades

e3e208e94feee299589a094f361b301131d1bd15

[ "MIT" ]

6

2020-03-30T17:05:58.000Z

2021-08-18T19:21:00.000Z

import math import numpy as np def rotate(pts, angle, pivot=(0., 0.)): pivot = np.asarray(pivot) angle = math.pi*angle/180 c, s = np.cos(angle), np.sin(angle) rotation = np.array([[c, -s], [s, c]]) return (np.asarray(pts) - pivot) @ rotation + pivot

24.727273

55

0.602941

0

a982f1f9c012c80b9c26e9e99c4415060d09e04a

166

py

Python

Project/Python/project/public/auto/__init__.py

renwei-release/dave

773301edd3bee6e7526e0d5587ff8af9f01e288f

[ "MIT" ]

null

Project/Python/project/public/auto/__init__.py

renwei-release/dave

773301edd3bee6e7526e0d5587ff8af9f01e288f

[ "MIT" ]

null

Project/Python/project/public/auto/__init__.py

renwei-release/dave

773301edd3bee6e7526e0d5587ff8af9f01e288f

[ "MIT" ]

null

import ctypes import struct from .dave_define import * from .dave_enum import * from .dave_msg_id import * from .dave_msg_struct import * from .dave_struct import *

18.444444

30

0.789157

0

a9840415a7cc2a3662940dac6af33c62299a8276

551

py

Python

Methods/Machine/Conductor/check.py

Superomeg4/pyleecan

2b695b5f39e77475a07aa0ea89489fb0a9659337

[ "Apache-2.0" ]

2

2020-06-29T13:48:37.000Z

2021-06-15T07:34:05.000Z

Methods/Machine/Conductor/check.py

Superomeg4/pyleecan

2b695b5f39e77475a07aa0ea89489fb0a9659337

[ "Apache-2.0" ]

null

Methods/Machine/Conductor/check.py

Superomeg4/pyleecan

2b695b5f39e77475a07aa0ea89489fb0a9659337

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- """@package Methods.Machine.Conductor.check Check that the Conductor is correct @date Created on Thu Jan 22 17:50:02 2015 @copyright (C) 2015-2016 EOMYS ENGINEERING. @author pierre_b """ from pyleecan.Methods.Machine.LamSlotWind.check import Lam_WindCheckError def check(self): """Check that the Conductor object is correct Parameters ---------- self : Conductor A Conductor object Returns ------- None """ pass class CondCheckError(Lam_WindCheckError): """ """ pass

17.774194

73

0.658802

63

0.114338

0

382

0.693285

a98465a5dbaaa69b7d18d16711f08102c5a830eb

3,414

py

Python

wholeslidedata/annotation/write_mask2.py

kaczmarj/pathology-whole-slide-data

3adb86af716ca89f336b6c935f90bd13183572b7

[ "Apache-2.0" ]

1

2022-02-17T19:47:14.000Z

wholeslidedata/annotation/write_mask2.py

kaczmarj/pathology-whole-slide-data

3adb86af716ca89f336b6c935f90bd13183572b7

[ "Apache-2.0" ]

null

wholeslidedata/annotation/write_mask2.py

kaczmarj/pathology-whole-slide-data

3adb86af716ca89f336b6c935f90bd13183572b7

[ "Apache-2.0" ]

null

from pathlib import Path from typing import List import cv2 import numpy as np from shapely import geometry from shapely.strtree import STRtree from wholeslidedata.annotation.structures import Annotation, Point, Polygon from wholeslidedata.image.wholeslideimage import WholeSlideImage from wholeslidedata.image.wholeslideimagewriter import WholeSlideMaskWriter from wholeslidedata.samplers.utils import shift_coordinates def select_annotations( stree: STRtree, center_x: int, center_y: int, width: int, height: int ): box = geometry.box( center_x - width // 2, center_y - height // 2, center_x + width // 2, center_y + height // 2, ) annotations = stree.query(box) return sorted(annotations, key=lambda item: item.area, reverse=True) def get_mask(stree, point, size, ratio): center_x, center_y = point.x, point.y width, height = size # get annotations annotations = select_annotations( stree, center_x, center_y, (width * ratio) - 1, (height * ratio) - 1 ) # create mask placeholder mask = np.zeros((height, width), dtype=np.int32) # set labels of all selected annotations for annotation in annotations: coordinates = np.copy(annotation.coordinates) coordinates = shift_coordinates( coordinates, center_x, center_y, width, height, ratio ) if isinstance(annotation, Polygon): holemask = np.ones((height, width), dtype=np.int32) * -1 for hole in annotation.holes: hcoordinates = shift_coordinates( hole, center_x, center_y, width, height, ratio ) cv2.fillPoly(holemask, np.array([hcoordinates], dtype=np.int32), 1) holemask[holemask != -1] = mask[holemask != -1] cv2.fillPoly( mask, np.array([coordinates], dtype=np.int32), annotation.label.value, ) mask[holemask != -1] = holemask[holemask != -1] elif isinstance(annotation, Point): mask[int(coordinates[1]), int(coordinates[0])] = annotation.label.value return mask.astype(np.uint8) def convert_annotations_to_mask( wsi: WholeSlideImage, annotations: List[Annotation], spacing: float, mask_output_path: Path, tile_size: int = 1024, ): stree = STRtree(annotations) ratio = wsi.get_downsampling_from_spacing(spacing) shape = wsi.shapes[wsi.get_level_from_spacing(spacing)] ratio = wsi.get_downsampling_from_spacing(spacing) write_spacing = wsi.get_real_spacing(spacing) wsm_writer = WholeSlideMaskWriter() wsm_writer.write( path=mask_output_path, spacing=write_spacing, dimensions=(shape[0], shape[1]), tile_shape=(tile_size, tile_size), ) for y_pos in range(0, shape[1], tile_size): for x_pos in range(0, shape[0], tile_size): mask = get_mask( stree, geometry.Point( (x_pos + tile_size // 2) * ratio, (y_pos + tile_size // 2) * ratio, ), (tile_size, tile_size), ratio, ) if np.any(mask): wsm_writer.write_tile(tile=mask, coordinates=(int(x_pos), int(y_pos))) print("closing...") wsm_writer.save() print("done")

32.207547

86

0.621558

0

100

0.029291

a984e763170541feb20e89e4a6245f1b8e706963

578

py

Python

tuples_05/tests/test_slicing_tuples.py

njoroge33/py_learn

6ad55f37789045bc5c03f3dd668cf1ea497f4e84

[ "MIT" ]

null

tuples_05/tests/test_slicing_tuples.py

njoroge33/py_learn

6ad55f37789045bc5c03f3dd668cf1ea497f4e84

[ "MIT" ]

2

2019-04-15T06:29:55.000Z

2019-04-19T17:34:32.000Z

tuples_05/tests/test_slicing_tuples.py

njoroge33/py_learn

6ad55f37789045bc5c03f3dd668cf1ea497f4e84

[ "MIT" ]

1

2019-11-19T04:51:18.000Z

import pytest from ..slicing_tuples import tuple_slice @pytest.mark.parametrize('names, ages, cities, expected', [ (('Gitau', 'Kanyoi', 'Ndegwa'), (13, 24, 5), ('Njogu-ini', 'Limuru', 'Kamae'), ( ('Gitau', 13, 'Njogu-ini'), ('Kanyoi', 24, 'Limuru'), ('Ndegwa', 5, 'Kamae') )), (('Totua', 'Suhi'), (95, 12, 36, 78), ('Tokyo', 'Vatican', 'Hyderabad'), ( ('Totua', 95, 'Tokyo'), ('Suhi', 12, 'Vatican') )), ]) def test_tuple_slice(names, ages, cities, expected): actual = tuple_slice(names, ages, cities) assert actual == expected

36.125

88

0.570934

0

520

0.899654

0

198

0.342561

a9856cedef8243944a78d8985c56e556db9faae0

28,653

py

Python

dftimewolf/lib/state.py

hkhalifa/dftimewolf

0a6d62fdb362c8618bd373c18a7f446b959f1a0f

[ "Apache-2.0" ]

null

dftimewolf/lib/state.py

hkhalifa/dftimewolf

0a6d62fdb362c8618bd373c18a7f446b959f1a0f

[ "Apache-2.0" ]

null

dftimewolf/lib/state.py

hkhalifa/dftimewolf

0a6d62fdb362c8618bd373c18a7f446b959f1a0f

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- """This class maintains the internal dfTimewolf state. Use it to track errors, abort on global failures, clean up after modules, etc. """ from dataclasses import dataclass from concurrent.futures import ThreadPoolExecutor, Future import importlib import logging import threading import traceback from typing import TYPE_CHECKING, Callable, Dict, List, Sequence, Type, Any, TypeVar, cast # pylint: disable=line-too-long from dftimewolf.cli import curses_display_manager as cdm from dftimewolf.config import Config from dftimewolf.lib import errors, utils from dftimewolf.lib.containers.interface import AttributeContainer from dftimewolf.lib.errors import DFTimewolfError from dftimewolf.lib.modules import manager as modules_manager from dftimewolf.lib.module import ThreadAwareModule, BaseModule if TYPE_CHECKING: from dftimewolf.lib import module as dftw_module from dftimewolf.lib.containers import interface T = TypeVar("T", bound="interface.AttributeContainer") # pylint: disable=invalid-name,line-too-long # TODO(tomchop): Consider changing this to `dftimewolf.state` if we ever need # more granularity. logger = logging.getLogger('dftimewolf') NEW_ISSUE_URL = 'https://github.com/log2timeline/dftimewolf/issues/new' @dataclass class StatsEntry: """A simple dataclass to store module-related statistics. Attributes: module_type: Type of the module that generated the stats. module_name: Name of the module that generated the stats. This has the same value as module_type when no runtime_name has been specified for the module. stats: Dictionary of stats to store. Contents are arbitrary, but keys must be strings. """ module_type: str module_name: str stats: Dict[str, Any] class DFTimewolfState(object): """The main State class. Attributes: command_line_options (dict[str, Any]): Command line options passed to dftimewolf. config (dftimewolf.config.Config): Class to be used throughout execution. errors (list[tuple[str, bool]]): errors generated by a module. These should be cleaned up after each module run using the CleanUp() method. global_errors (list[tuple[str, bool]]): the CleanUp() method moves non critical errors to this attribute for later reporting. input (list[str]): data that the current module will use as input. output (list[str]): data that the current module generates. recipe: (dict[str, str]): recipe declaring modules to load. store (dict[str, object]): arbitrary data for modules. stats_store: store for statistics generated by modules. """ def __init__(self, config: Type[Config]) -> None: """Initializes a state.""" super(DFTimewolfState, self).__init__() self.command_line_options = {} # type: Dict[str, Any] self._cache = {} # type: Dict[str, str] self._module_pool = {} # type: Dict[str, BaseModule] self._state_lock = threading.Lock() self._stats_lock = threading.Lock() self._threading_event_per_module = {} # type: Dict[str, threading.Event] self.config = config self.errors = [] # type: List[DFTimewolfError] self.global_errors = [] # type: List[DFTimewolfError] self.recipe = {} # type: Dict[str, Any] self.store = {} # type: Dict[str, List[interface.AttributeContainer]] self.stats_store = [] # type: List[StatsEntry] self.streaming_callbacks = {} # type: Dict[Type[interface.AttributeContainer], List[Callable[[Any], Any]]] # pylint: disable=line-too-long self._abort_execution = False self.stdout_log = True def _InvokeModulesInThreads(self, callback: Callable[[Any], Any]) -> None: """Invokes the callback function on all the modules in separate threads. Args: callback (function): callback function to invoke on all the modules. """ threads = [] for module_definition in self.recipe['modules']: thread_args = (module_definition, ) thread = threading.Thread(target=callback, args=thread_args) threads.append(thread) thread.start() for thread in threads: thread.join() self.CheckErrors(is_global=True) def ImportRecipeModules(self, module_locations: Dict[str, str]) -> None: """Dynamically loads the modules declared in a recipe. Args: module_location (dict[str, str]): A dfTimewolf module name - Python module mapping. e.g.: {'GRRArtifactCollector': 'dftimewolf.lib.collectors.grr_hosts'} Raises: errors.RecipeParseError: if a module requested in a recipe does not exist in the mapping. """ for module in self.recipe['modules'] + self.recipe.get('preflights', []): name = module['name'] if name not in module_locations: msg = (f'In {self.recipe["name"]}: module {name} cannot be found. ' 'It may not have been declared.') raise errors.RecipeParseError(msg) logger.debug('Loading module {0:s} from {1:s}'.format( name, module_locations[name])) location = module_locations[name] try: importlib.import_module(location) except ModuleNotFoundError as exception: msg = f'Cannot find Python module for {name} ({location}): {exception}' raise errors.RecipeParseError(msg) def LoadRecipe(self, recipe: Dict[str, Any], module_locations: Dict[str, str]) -> None: """Populates the internal module pool with modules declared in a recipe. Args: recipe (dict[str, Any]): recipe declaring modules to load. Raises: RecipeParseError: if a module in the recipe has not been declared. """ self.recipe = recipe module_definitions = recipe.get('modules', []) preflight_definitions = recipe.get('preflights', []) self.ImportRecipeModules(module_locations) for module_definition in module_definitions + preflight_definitions: # Combine CLI args with args from the recipe description module_name = module_definition['name'] module_class = modules_manager.ModulesManager.GetModuleByName(module_name) runtime_name = module_definition.get('runtime_name') if not runtime_name: runtime_name = module_name # pytype: disable=wrong-arg-types self._module_pool[runtime_name] = module_class(self, name=runtime_name) # pytype: enable=wrong-arg-types def FormatExecutionPlan(self) -> str: """Formats execution plan. Returns information about loaded modules and their corresponding arguments to stdout. Returns: str: String representation of loaded modules and their parameters. """ plan = "" maxlen = 0 modules = self.recipe.get('preflights', []) + self.recipe.get('modules', []) for module in modules: if not module['args']: continue spacing = len(max(module['args'].keys(), key=len)) maxlen = maxlen if maxlen > spacing else spacing for module in modules: runtime_name = module.get('runtime_name') if runtime_name: plan += '{0:s} ({1:s}):\n'.format(runtime_name, module['name']) else: plan += '{0:s}:\n'.format(module['name']) new_args = utils.ImportArgsFromDict( module['args'], self.command_line_options, self.config) if not new_args: plan += ' *No params*\n' for key, value in new_args.items(): plan += ' {0:s}{1:s}\n'.format(key.ljust(maxlen + 3), repr(value)) return plan def LogExecutionPlan(self) -> None: """Logs the result of FormatExecutionPlan() using the base logger.""" for line in self.FormatExecutionPlan().split('\n'): logger.debug(line) def AddToCache(self, name: str, value: Any) -> None: """Thread-safe method to add data to the state's cache. If the cached item is already in the cache it will be overwritten with the new value. Args: name (str): string with the name of the cache variable. value (object): the value that will be stored in the cache. """ with self._state_lock: self._cache[name] = value def GetFromCache(self, name: str, default_value: Any=None) -> Any: """Thread-safe method to get data from the state's cache. Args: name (str): string with the name of the cache variable. default_value (object): the value that will be returned if the item does not exist in the cache. Optional argument and defaults to None. Returns: object: object from the cache that corresponds to the name, or the value of "default_value" if the cache does not contain the variable. """ with self._state_lock: return self._cache.get(name, default_value) def StoreContainer(self, container: "interface.AttributeContainer") -> None: """Thread-safe method to store data in the state's store. Args: container (AttributeContainer): data to store. """ with self._state_lock: self.store.setdefault(container.CONTAINER_TYPE, []).append(container) def StoreStats(self, stats_entry: StatsEntry) -> None: """Thread-safe method to store stats in the state's stats store. Args: statsentry: The stats object to store. """ with self._stats_lock: self.stats_store.append(stats_entry) def GetStats(self) -> List[StatsEntry]: """Get stats entries that have been stored in the state. Returns: The stats objects stored in the state's stats store. """ with self._stats_lock: return self.stats_store def GetContainers(self, container_class: Type[T], pop: bool=False) -> Sequence[T]: """Thread-safe method to retrieve data from the state's store. Args: container_class (type): AttributeContainer class used to filter data. pop (Optional[bool]): Whether to remove the containers from the state when they are retrieved. Returns: Collection[AttributeContainer]: attribute container objects provided in the store that correspond to the container type. """ with self._state_lock: container_objects = cast( List[T], self.store.get(container_class.CONTAINER_TYPE, [])) if pop: self.store[container_class.CONTAINER_TYPE] = [] return tuple(container_objects) def DedupeContainers(self, container_class: Type[T]) -> None: """Thread safe deduping of containers of the given type. This requires the container being deduped to override `__eq__()`. Args: container_class (type): AttributeContainer class to dedupe. """ with self._state_lock: deduped = [] for c in self.store.get(container_class.CONTAINER_TYPE, []): if c not in deduped: deduped.append(c) self.store[container_class.CONTAINER_TYPE] = deduped def _SetupModuleThread(self, module_definition: Dict[str, str]) -> None: """Calls the module's SetUp() function and sets a threading event for it. Callback for _InvokeModulesInThreads. Args: module_definition (dict[str, str]): recipe module definition. """ module_name = module_definition['name'] runtime_name = module_definition.get('runtime_name', module_name) logger.info('Setting up module: {0:s}'.format(runtime_name)) new_args = utils.ImportArgsFromDict( module_definition['args'], self.command_line_options, self.config) module = self._module_pool[runtime_name] try: self._RunModuleSetUp(module, **new_args) except errors.DFTimewolfError: msg = "A critical error occurred in module {0:s}, aborting execution." logger.critical(msg.format(module.name)) except Exception as exception: # pylint: disable=broad-except msg = 'An unknown error occurred in module {0:s}: {1!s}'.format( module.name, exception) logger.critical(msg) # We're catching any exception that is not a DFTimewolfError, so we want # to generate an error for further reporting. error = errors.DFTimewolfError( message=msg, name='dftimewolf', stacktrace=traceback.format_exc(), critical=True, unexpected=True) self.AddError(error) self._threading_event_per_module[runtime_name] = threading.Event() self.CleanUp() def _RunModuleSetUp(self, module: BaseModule, **new_args: Dict[str, object]) -> None: """Runs SetUp of a single module. Designed to be wrapped by an output handling subclass. Args: module: The modulke that will have SetUp called. new_args: kwargs to pass to SetUp.""" module.SetUp(**new_args) def _RunModuleProcess(self, module: BaseModule) -> None: """Runs Process of a single module. Designed to be wrapped by an output handling subclass. Args: module: The module to run Process() on.""" module.Process() def _RunModuleProcessThreaded( self, module: ThreadAwareModule ) -> List[Future]: # type: ignore """Runs Process of a single ThreadAwareModule module. Designed to be wrapped by an output handling subclass. Args: module: The module that will have Process(container) called in a threaded fashion.""" cont_count = len(self.GetContainers(module.GetThreadOnContainerType())) logger.info( f'Running {cont_count} threads, max {module.GetThreadPoolSize()} ' f'simultaneous for module {module.name}') futures = [] with ThreadPoolExecutor(max_workers=module.GetThreadPoolSize()) \ as executor: pop = not module.KeepThreadedContainersInState() for c in self.GetContainers(module.GetThreadOnContainerType(), pop): futures.append( executor.submit(module.Process, c)) return futures def _RunModulePreProcess(self, module: ThreadAwareModule) -> None: """Runs PreProcess of a single module. Designed to be wrapped by an output handling subclass. Args: module: The module that will have PreProcess() called.""" module.PreProcess() def _RunModulePostProcess(self, module: ThreadAwareModule) -> None: """Runs PostProcess of a single module. Designed to be wrapped by an output handling subclass. Args: module: The module that will have PostProcess() called.""" module.PostProcess() # pylint: disable=unused-argument def _HandleFuturesFromThreadedModule( self, futures: List[Future], # type: ignore runtime_name: str) -> None: """Handles any futures raised by the async processing of a module. Args: futures: A list of futures, returned by RunModuleProcessThreaded(). runtime_name: runtime name of the module.""" for fut in futures: if fut.exception(): raise fut.exception() # type: ignore # pylint: disable=unused-argument def SetupModules(self) -> None: """Performs setup tasks for each module in the module pool. Threads declared modules' SetUp() functions. Takes CLI arguments into account when replacing recipe parameters for each module. """ # Note that vars() copies the values of argparse.Namespace to a dict. self._InvokeModulesInThreads(self._SetupModuleThread) def _RunModuleThread(self, module_definition: Dict[str, str]) -> None: """Runs the module's Process() function. Callback for _InvokeModulesInThreads. Waits for any blockers to have finished before running Process(), then sets an Event flag declaring the module has completed. Args: module_definition (dict): module definition. """ module_name = module_definition['name'] runtime_name = module_definition.get('runtime_name', module_name) for dependency in module_definition['wants']: self._threading_event_per_module[dependency].wait() module = self._module_pool[runtime_name] # Abort processing if a module has had critical failures before. if self._abort_execution: logger.critical( 'Aborting execution of {0:s} due to previous errors'.format( module.name)) self._threading_event_per_module[runtime_name].set() self.CleanUp() return logger.info('Running module: {0:s}'.format(runtime_name)) try: if isinstance(module, ThreadAwareModule): self._RunModulePreProcess(module) futures = self._RunModuleProcessThreaded(module) self._RunModulePostProcess(module) self._HandleFuturesFromThreadedModule(futures, runtime_name) else: self._RunModuleProcess(module) except errors.DFTimewolfError: logger.critical( "Critical error in module {0:s}, aborting execution".format( module.name)) except Exception as exception: # pylint: disable=broad-except msg = 'An unknown error occurred in module {0:s}: {1!s}'.format( module.name, exception) logger.critical(msg) # We're catching any exception that is not a DFTimewolfError, so we want # to generate an error for further reporting. error = errors.DFTimewolfError( message=msg, name='dftimewolf', stacktrace=traceback.format_exc(), critical=True, unexpected=True) self.AddError(error) logger.info('Module {0:s} finished execution'.format(runtime_name)) self._threading_event_per_module[runtime_name].set() self.CleanUp() def RunPreflights(self) -> None: """Runs preflight modules.""" for preflight_definition in self.recipe.get('preflights', []): preflight_name = preflight_definition['name'] runtime_name = preflight_definition.get('runtime_name', preflight_name) args = preflight_definition.get('args', {}) new_args = utils.ImportArgsFromDict( args, self.command_line_options, self.config) preflight = self._module_pool[runtime_name] try: self._RunModuleSetUp(preflight, **new_args) self._RunModuleProcess(preflight) finally: self.CheckErrors(is_global=True) def CleanUpPreflights(self) -> None: """Executes any cleanup actions defined in preflight modules.""" for preflight_definition in self.recipe.get('preflights', []): preflight_name = preflight_definition['name'] runtime_name = preflight_definition.get('runtime_name', preflight_name) preflight = self._module_pool[runtime_name] try: preflight.CleanUp() finally: self.CheckErrors(is_global=True) def InstantiateModule(self, module_name: str) -> "BaseModule": """Instantiates an arbitrary dfTimewolf module. Args: module_name (str): The name of the module to instantiate. Returns: BaseModule: An instance of a dftimewolf Module, which is a subclass of BaseModule. """ module_class: Type["BaseModule"] module_class = modules_manager.ModulesManager.GetModuleByName(module_name) # pytype: disable=wrong-arg-types return module_class(self) # pytype: enable=wrong-arg-types def RunModules(self) -> None: """Performs the actual processing for each module in the module pool.""" self._InvokeModulesInThreads(self._RunModuleThread) def RegisterStreamingCallback( self, target: Callable[["interface.AttributeContainer"], Any], container_type: Type["interface.AttributeContainer"]) -> None: """Registers a callback for a type of container. The function to be registered should a single parameter of type interface.AttributeContainer. Args: target (function): function to be called. container_type (type[interface.AttributeContainer]): container type on which the callback will be called. """ if container_type not in self.streaming_callbacks: self.streaming_callbacks[container_type] = [] self.streaming_callbacks[container_type].append(target) def StreamContainer(self, container: "interface.AttributeContainer") -> None: """Streams a container to the callbacks that are registered to handle it. Args: container (interface.AttributeContainer): container instance that will be streamed to any registered callbacks. """ for callback in self.streaming_callbacks.get(type(container), []): callback(container) def AddError(self, error: DFTimewolfError) -> None: """Adds an error to the state. Args: error (errors.DFTimewolfError): The dfTimewolf error to add. """ if error.critical: self._abort_execution = True self.errors.append(error) def CleanUp(self) -> None: """Cleans up after running a module. The state's output becomes the input for the next stage. Any errors are moved to the global_errors attribute so that they can be reported at a later stage. """ # Move any existing errors to global errors self.global_errors.extend(self.errors) self.errors = [] def CheckErrors(self, is_global: bool=False) -> None: """Checks for errors and exits if any of them are critical. Args: is_global (Optional[bool]): True if the global_errors attribute should be checked. False if the error attribute should be checked. """ error_objects = self.global_errors if is_global else self.errors critical_errors = False if error_objects: logger.error('dfTimewolf encountered one or more errors:') for index, error in enumerate(error_objects): logger.error('{0:d}: error from {1:s}: {2:s}'.format( index+1, error.name, error.message)) if error.stacktrace: for line in error.stacktrace.split('\n'): logger.error(line) if error.critical: critical_errors = True if any(error.unexpected for error in error_objects): logger.critical('One or more unexpected errors occurred.') logger.critical( 'Please consider opening an issue: {0:s}'.format(NEW_ISSUE_URL)) if critical_errors: raise errors.CriticalError('Critical error found. Aborting.') def PublishMessage(self, source: str, message: str, is_error: bool = False) -> None: """Receives a message for publishing. The base class does nothing with this (as the method in module also logs the message). This method exists to be overridden for other UIs. Args: source: The source of the message. message: The message content. is_error: True if the message is an error message, False otherwise.""" class DFTimewolfStateWithCDM(DFTimewolfState): """The main state class, extended to wrap methods with updates to a CursesDisplayManager object.""" def __init__(self, config: Type[Config], cursesdm: cdm.CursesDisplayManager) -> None: """Initializes a state.""" super(DFTimewolfStateWithCDM, self).__init__(config) self.cursesdm = cursesdm self.stdout_log = False def LoadRecipe(self, recipe: Dict[str, Any], module_locations: Dict[str, str]) -> None: """Populates the internal module pool with modules declared in a recipe. Args: recipe (dict[str, Any]): recipe declaring modules to load. Raises: RecipeParseError: if a module in the recipe has not been declared. """ super(DFTimewolfStateWithCDM, self).LoadRecipe(recipe, module_locations) module_definitions = recipe.get('modules', []) preflight_definitions = recipe.get('preflights', []) self.cursesdm.SetRecipe(self.recipe['name']) for module_definition in preflight_definitions: self.cursesdm.EnqueuePreflight(module_definition['name'], module_definition.get('wants', []), module_definition.get('runtime_name')) for module_definition in module_definitions: self.cursesdm.EnqueueModule(module_definition['name'], module_definition.get('wants', []), module_definition.get('runtime_name')) self.cursesdm.Draw() def _RunModuleSetUp(self, module: BaseModule, **new_args: Dict[str, object]) -> None: """Runs SetUp of a single module. Args: module: The modulke that will have SetUp called. new_args: kwargs to pass to SetUp.""" self.cursesdm.UpdateModuleStatus(module.name, cdm.Status.SETTINGUP) module.SetUp(**new_args) self.cursesdm.UpdateModuleStatus(module.name, cdm.Status.PENDING) def _RunModuleProcess(self, module: BaseModule) -> None: """Runs Process of a single module. Args: module: The module to run Process() on.""" self.cursesdm.UpdateModuleStatus(module.name, cdm.Status.PROCESSING) module.Process() self.cursesdm.UpdateModuleStatus(module.name, cdm.Status.COMPLETED) def _RunModuleProcessThreaded( self, module: ThreadAwareModule ) -> List[Future]: # type: ignore """Runs Process of a single ThreadAwareModule module. Args: module: The module that will have Process(container) called in a threaded fashion.""" cont_count = len(self.GetContainers(module.GetThreadOnContainerType())) logger.info( f'Running {cont_count} threads, max {module.GetThreadPoolSize()} ' f'simultaneous for module {module.name}') self.cursesdm.SetThreadedModuleContainerCount(module.name, cont_count) self.cursesdm.UpdateModuleStatus(module.name, cdm.Status.PROCESSING) futures = [] with ThreadPoolExecutor(max_workers=module.GetThreadPoolSize()) \ as executor: pop = not module.KeepThreadedContainersInState() for c in self.GetContainers(module.GetThreadOnContainerType(), pop): futures.append( executor.submit( self._WrapThreads, module.Process, c, module.name)) return futures def _RunModulePreProcess(self, module: ThreadAwareModule) -> None: """Runs PreProcess of a single module. Args: module: The module that will have PreProcess() called.""" self.cursesdm.UpdateModuleStatus(module.name, cdm.Status.PREPROCESSING) module.PreProcess() self.cursesdm.UpdateModuleStatus(module.name, cdm.Status.PENDING) def _RunModulePostProcess(self, module: ThreadAwareModule) -> None: """Runs PostProcess of a single module. Args: module: The module that will have PostProcess() called.""" self.cursesdm.UpdateModuleStatus(module.name, cdm.Status.POSTPROCESSING) module.PostProcess() self.cursesdm.UpdateModuleStatus(module.name, cdm.Status.COMPLETED) def _HandleFuturesFromThreadedModule( self, futures: List[Future], # type: ignore runtime_name: str) -> None: """Handles any futures raised by the async processing of a module. Args: futures: A list of futures, returned by RunModuleProcessThreaded(). runtime_name: runtime name of the module.""" for fut in futures: if fut.exception(): self.cursesdm.SetError(runtime_name, str(fut.exception())) raise fut.exception() # type: ignore def _WrapThreads(self, process: Callable[[AttributeContainer], None], container: AttributeContainer, module_name: str) -> None: """Wraps a ThreadPoolExecutor call to module.process with the CursesDisplayManager status update methods. Args: process: A callable method: Process, belonging to a ThreadAwareModule. container: The Container being processed by the thread. module_name: The runtime name of the module.""" thread_id = threading.current_thread().getName() self.cursesdm.UpdateModuleThreadState( module_name, cdm.Status.RUNNING, thread_id, str(container)) process(container) self.cursesdm.UpdateModuleThreadState( module_name, cdm.Status.COMPLETED, thread_id, str(container)) def AddError(self, error: DFTimewolfError) -> None: """Adds an error to the state. Args: error (errors.DFTimewolfError): The dfTimewolf error to add. """ super(DFTimewolfStateWithCDM, self).AddError(error) name = error.name if error.name else 'no_module_name' self.cursesdm.SetError(name, error.message) def PublishMessage(self, source: str, message: str, is_error: bool = False) -> None: """Receives a message for publishing to the list of messages. Args: source: The source of the message. message: The message content. is_error: True if the message is an error message, False otherwise.""" self.cursesdm.EnqueueMessage(source, message, is_error)

36.640665

144

0.682965

27,376

0.955432

0

505

0.017625

0

12,843

0.448225

a98618135a8eb68ea555b4e82e1d790635fb2594

1,374

py

Python

DBManager.py

d0d0d0/Kerberos

38bf0b8388bc4f3571e790d5bc626d050df5d4dc

[ "MIT" ]

null

DBManager.py

d0d0d0/Kerberos

38bf0b8388bc4f3571e790d5bc626d050df5d4dc

[ "MIT" ]

null

DBManager.py

d0d0d0/Kerberos

38bf0b8388bc4f3571e790d5bc626d050df5d4dc

[ "MIT" ]

null

### Implements database management for Authentication Server and TGS ### from Query import * from sqlite3 import * from config import * class DBManager(object): def __init__(self, dbname): try: self.conn = connect(dbname) self.cursor = self.conn.cursor() except Exception as e: print str(e) def createTable(self, ttype): try: if ttype in TYPE_SERVICE: self.cursor.execute(CREATE_SERVICE_TABLE) elif ttype in TYPE_USER: self.cursor.execute(CREATE_USER_TABLE) elif ttype in TYPE_AUTH: self.cursor.execute(CREATE_AUTH_TABLE) elif ttype in TYPE_TGS: self.cursor.execute(CREATE_TGS_TABLE) else: print "Invalid table type." self.conn.commit() except Exception as e: print str(e) def insert(self, ttype, val): try: if ttype in TYPE_SERVICE: self.cursor.execute(INSERT_SERVICE, val) elif ttype in TYPE_USER: self.cursor.execute(INSERT_USER, val) elif ttype in TYPE_AUTH: self.cursor.execute(INSERT_AUTH, val) elif ttype in TYPE_TGS: self.cursor.execute(INSERT_TGS, val) else: print "Invalid table type." self.conn.commit() except Exception as e: print str(e) def isAuthExist(self, val): try: self.cursor.execute(IS_AUTH, val) data = self.cursor.fetchone() if data == None: return False return True except Exception as e: print str(e)

21.809524

72

0.697234

1,230

0.895197

0

114

0.082969

a987d4f7ac2585765bc67edb9138327e5465eec0

451

py

Python

people/views.py

kackey0-1/drf-sample

914907320bc317240b4d7c07968b6d4ea80b4511

[ "MIT" ]

null

people/views.py

kackey0-1/drf-sample

914907320bc317240b4d7c07968b6d4ea80b4511

[ "MIT" ]

6

2021-03-30T12:05:07.000Z

2021-04-05T14:21:46.000Z

people/views.py

kackey0-1/drf-sample

914907320bc317240b4d7c07968b6d4ea80b4511

[ "MIT" ]

null

from rest_framework.decorators import api_view from rest_framework.response import Response from rest_framework import status from .models import Person from .serializers import PersonSerializer @api_view(['GET']) def list_people(request): people = Person.objects.all() serializer = PersonSerializer(people, many=True) content = { "people": serializer.data, } return Response(data=content, status=status.HTTP_200_OK)

22.55

60

0.75388

0

249

0.552106

0

13

0.028825

a98828e92b274eb6eae13e6556ae7fff3be2a963

8,867

py

Python

simple_soccer/two_dimension.py

RyoheiGoto/reinforcement_learning

ff2ddded7fd24c831a5103818b8a747a66a75f0c

[ "MIT" ]

2

2015-11-18T17:47:19.000Z

2016-03-20T08:22:42.000Z

simple_soccer/two_dimension.py

RyoheiGoto/reinforcement_learning

ff2ddded7fd24c831a5103818b8a747a66a75f0c

[ "MIT" ]

1

2015-11-19T18:15:13.000Z

2016-02-09T16:48:23.000Z

simple_soccer/two_dimension.py

RyoheiGoto/ReinforcementLearning

ff2ddded7fd24c831a5103818b8a747a66a75f0c

[ "MIT" ]

null

import numpy as np import matplotlib.pyplot as plt field_width = 396 #cm field_hight = 180 #cm goal_length = 180 #cm threshold = 36 field_width_threshold_num = field_width / threshold + 1 field_width_threshold = [Y * threshold - field_width / 2.0 for Y in xrange(field_width_threshold_num)] field_hight_threshold_num = field_hight / threshold + 1 field_hight_threshold = [X * threshold for X in xrange(field_hight_threshold_num)] ball_velo_x_threshold = [X * 100.0 for X in [-1.0, -0.8, -0.6, -0.4, -0.2, 0.0]] ball_velo_x_threshold_num = len(ball_velo_x_threshold) + 1 ball_velo_y_threshold = [Y * 50.0 for Y in [-1.0, -0.8, -0.6, -0.4, -0.2, 0.0, 0.2, 0.4, 0.6, 0.8, 1.0]] ball_velo_y_threshold_num = len(ball_velo_y_threshold) + 1 tau = 0.2 #sec fall_time = 10 robot_states = 3 #epsilon = 0.1 epsilon = 0.00001 alpha = 0.5 gamma = 0.5 STAND, LEFT, RIGHT, BALL = range(4) COMPLETED = "COMPLETED" FAILED = "FAILED" ACTIVE = "ACTIVE" class Soccer(object): def __init__(self, max_episode=10000, plot=False): np.random.seed() self.Q = np.zeros([robot_states, field_hight_threshold_num, field_width_threshold_num, ball_velo_x_threshold_num, ball_velo_y_threshold_num]) self.robot_state = None self.fall_count = None self.ball_states = None self.result = None self.clear = None self.process(max_episode, plot) def status_init(self): ball_x = np.random.randint(80, 180) ball_y = np.random.randint(-150, 150) ball_dx = -np.random.random() * 100 ball_dy = np.random.choice([-50, 50]) * np.random.random() self.ball_states = (ball_x, ball_y, ball_dx, ball_dy) self.robot_state = STAND def threslold(self, states): x, y, dx, dy = states for field_x, num in zip(field_hight_threshold, xrange(field_hight_threshold_num)): if x < field_x: threshold_x = num break else: threshold_x = field_hight_threshold_num - 1 for field_y, num in zip(field_width_threshold, xrange(field_width_threshold_num)): if y < field_y: threshold_y = num break else: threshold_y = field_width_threshold_num - 1 for ball_dx, num in zip(ball_velo_x_threshold, xrange(ball_velo_x_threshold_num)): if dx < ball_dx: threshold_dx = num break else: threshold_dx = ball_velo_x_threshold_num - 1 for ball_dy, num in zip(ball_velo_y_threshold, xrange(ball_velo_y_threshold_num)): if dy < ball_dy: threshold_dy = num break else: threshold_dy = ball_velo_y_threshold_num - 1 return threshold_x, threshold_y, threshold_dx, threshold_dy def update_status(self, ball_states): ball_x, ball_y, ball_dx, ball_dy = ball_states ball_x += ball_dx * tau ball_y += ball_dy * tau self.ball_states = [ball_x, ball_y, ball_dx, ball_dy] def decide_action(self, ball_states, robot_state): if robot_state == (LEFT or RIGHT): self.fall_count -= 1 else: policy = self.e_greedy(ball_states) prob = 0.0 for action, policy in zip(xrange(robot_states), policy): prob += policy if np.random.random() < prob: self.robot_state = action if action == (LEFT or RIGHT): self.fall_count = fall_time break else: self.robot_state = STAND def e_greedy(self, ball_states): policy = [] x, y, dx, dy = self.threslold(ball_states) q = [self.Q[action, x, y, dx, dy] for action in xrange(robot_states)] for action in xrange(len(q)): if action == q.index(max(q)): policy.append(1.0 - epsilon + epsilon / robot_states) else: policy.append(epsilon / robot_states) if sum(policy) != 1.0 or not sum(q): return map(lambda n: 1.0 / robot_states, policy) else: return policy def get_reward(self, ball_states, robot_state): x, y, dx, dy = self.threslold(ball_states) reward = 0.0 result = ACTIVE if robot_state == STAND: if x == 1 and y == 6: reward = 5.0 result = COMPLETED else: reward = 1.0 elif robot_state == LEFT: if x == 1 and y in (4, 5): reward = 5.0 result = COMPLETED elif not self.fall_count > 0: reward = -10.0 result = FAILED else: reward = -5.0 elif robot_state == RIGHT: if x == 1 and y in (7, 8): reward = 5.0 result = COMPLETED elif not self.fall_count > 0: reward = -10.0 result = FAILED else: reward = -5.0 if x == 0 and (3 < y < 9): reward = -10.0 result = FAILED elif x in (0, 6) and (y < 4 or y > 8): if robot_state == STAND: reward = 5.0 else: reward = -5.0 result = COMPLETED return reward, result def q_learning(self, ball_states, new_ball_states, new_robot_state, reward): x, y, dx, dy = self.threslold(new_ball_states) new = max([self.Q[action, x, y, dx, dy] for action in xrange(robot_states)]) x, y, dx, dy = self.threslold(ball_states) old = self.Q[new_robot_state, x, y, dx, dy] self.Q[new_robot_state, x, y, dx, dy] += alpha * (reward + gamma * new - old) def step(self): ball_states = self.ball_states robot_state = self.robot_state self.decide_action(ball_states, robot_state) self.update_status(ball_states) new_ball_states = self.ball_states new_robot_states = self.robot_state reward, result = self.get_reward(new_ball_states, new_robot_states) self.q_learning(ball_states, new_ball_states, new_robot_states, reward) if result == ACTIVE: return True else: self.result = result return False def process(self, max_episode, plot): clear = 0.0 self.clear = 0.0 for episode in np.arange(1, max_episode): self.status_init() log = [] for step in np.arange(1, 1000000): ball_x, ball_y, ball_dx, ball_dy = self.ball_states log.append([step * tau, ball_x, ball_y, ball_dx, ball_dy, self.robot_state]) if not self.step(): ball_x, ball_y, ball_dx, ball_dy = self.ball_states log.append([step * tau, ball_x, ball_y, ball_dx, ball_dy, self.robot_state]) if self.result == COMPLETED: clear += 1.0 self.show_result(episode, self.result) #if plot and episode > max_episode * 0.9: if plot and episode > 10000: self.plotgame(log, self.result) break print "-" * 30 print "episode:\t%d\nclear:\t\t%d(%.3lf%%)" % (max_episode, clear, (clear / max_episode) * 100) def show_result(self, episode, result): if result == COMPLETED: self.clear += 1 if episode % 1000 == 0: print "-" * 30 print "episode:\t%d ~ %d" % ((episode - 999), episode) print "clear:\t\t%d(%.3lf%%)" % (self.clear, (self.clear / 1000 * 100)) self.clear = 0.0 """ global epsilon epsilon -= 0.01 if epsilon < 0.002: epsilon = 0.002 print "epsilon:\t%lf" % epsilon """ def plotgame(self, episode, result): field = np.zeros([field_hight_threshold_num + 1, field_width_threshold_num]) for step in episode: time, ball_x, ball_y, ball_dx, ball_dy, robot_state = step x, y, dx, dy = self.threslold([ball_x, ball_y, ball_dx, ball_dy]) field[x, y] = BALL field[0, 3] = field[0, 9] = -15 if robot_state == STAND: field[1, 6] = -20 elif robot_state == LEFT: field[1, 4] = field[1, 5] = -5 elif robot_state == RIGHT: field[1, 7] = field[1, 8] = -10 plt.imshow(field, interpolation='none', cmap="BuGn") plt.title(result) plt.show() if __name__ == '__main__': #Soccer(max_episode=100, plot=True) Soccer(max_episode=10000000, plot=False)

33.587121

149

0.551483

7,811

0.880907

0

419

0.047254

a98a17680f92454408a66d8e581e032e851f1d31

1,089

py

Python

tests/test_molecular_signatures_db.py

krassowski/gsea-api

deb562ea55871b799eb501a798dd49a881ff9523

[ "MIT" ]

8

2020-03-06T02:03:40.000Z

2022-01-22T15:57:17.000Z

tests/test_molecular_signatures_db.py

krassowski/gsea-api

deb562ea55871b799eb501a798dd49a881ff9523

[ "MIT" ]

3

2020-03-06T01:48:53.000Z

2021-10-06T04:15:55.000Z

tests/test_molecular_signatures_db.py

krassowski/gsea-api

deb562ea55871b799eb501a798dd49a881ff9523

[ "MIT" ]

2

2019-12-01T18:41:07.000Z

2020-07-15T14:52:17.000Z

from pytest import raises from gsea_api.molecular_signatures_db import MolecularSignaturesDatabase def test_load(): msigdb_7_1 = MolecularSignaturesDatabase('tests/test_msigdb', version=7.1) assert msigdb_7_1.version == '7.1' assert msigdb_7_1.gene_sets == [ { 'name': 'c2.cp.reactome', 'id_type': 'symbols' } ] reactome_7_1 = msigdb_7_1.load('c2.cp.reactome', 'symbols') assert 'REACTOME_NERVOUS_SYSTEM_DEVELOPMENT' in reactome_7_1.gene_sets_by_name assert 'REACTOME_SERINE_BIOSYNTHESIS' not in reactome_7_1.gene_sets_by_name msigdb_7_0 = MolecularSignaturesDatabase('tests/test_msigdb', version=7.0) reactome_7_0 = msigdb_7_0.load('c2.cp.reactome', 'symbols') assert 'REACTOME_NERVOUS_SYSTEM_DEVELOPMENT' not in reactome_7_0.gene_sets_by_name assert 'REACTOME_SERINE_BIOSYNTHESIS' in reactome_7_0.gene_sets_by_name def test_fail_no_dir(): with raises(ValueError, match='Could not find MSigDB: wrong_dir_name does not exist'): MolecularSignaturesDatabase('wrong_dir_name', version=7.1)

38.892857

90

0.747475

0

337

0.309458

a98a271a4efe485ccb8f3daffb76dc91992cf6a3

11,387

py

Python

froide_govplan/admin.py

okfde/froide-govplan

1ae085c39c25af7c7a74d90ce39580119942a328

[ "MIT" ]

2

2022-03-13T14:49:46.000Z

2022-03-14T18:39:04.000Z

froide_govplan/admin.py

okfde/froide-govplan

1ae085c39c25af7c7a74d90ce39580119942a328

[ "MIT" ]

3

2022-03-18T11:52:46.000Z

2022-03-18T14:13:43.000Z

froide_govplan/admin.py

okfde/froide-govplan

1ae085c39c25af7c7a74d90ce39580119942a328

[ "MIT" ]

1

2022-03-18T09:36:20.000Z

from django.contrib import admin, auth from django.contrib.auth.models import Group from django.shortcuts import get_object_or_404, redirect, render from django.urls import path, reverse, reverse_lazy from django.utils.translation import gettext_lazy as _ from adminsortable2.admin import SortableAdminMixin from froide.api import api_router from froide.follow.admin import FollowerAdmin from froide.helper.admin_utils import make_choose_object_action, make_emptyfilter from froide.helper.widgets import TagAutocompleteWidget from froide.organization.models import Organization from .api_views import GovernmentPlanViewSet from .auth import get_allowed_plans, has_limited_access from .forms import ( GovernmentPlanForm, GovernmentPlanUpdateAcceptProposalForm, GovernmentPlanUpdateForm, ) from .models import ( Government, GovernmentPlan, GovernmentPlanFollower, GovernmentPlanSection, GovernmentPlanUpdate, ) User = auth.get_user_model() api_router.register(r"governmentplan", GovernmentPlanViewSet, basename="governmentplan") class GovPlanAdminSite(admin.AdminSite): site_header = "Regierungsvorhaben" site_url = "/koalitionstracker/" class GovernmentPlanAdminForm(GovernmentPlanForm): class Meta: model = GovernmentPlan fields = "__all__" widgets = { "categories": TagAutocompleteWidget( autocomplete_url=reverse_lazy("api:category-autocomplete") ), } class GovernmentAdmin(admin.ModelAdmin): prepopulated_fields = {"slug": ("name",)} list_display = ("name", "public", "start_date", "end_date") list_filter = ("public",) def execute_assign_organization(admin, request, queryset, action_obj): queryset.update(organization=action_obj) def execute_assign_group(admin, request, queryset, action_obj): queryset.update(group=action_obj) PLAN_ACTIONS = { "assign_organization": make_choose_object_action( Organization, execute_assign_organization, _("Assign organization...") ), "assign_group": make_choose_object_action( Group, execute_assign_group, _("Assign permission group...") ), } class GovernmentPlanAdmin(admin.ModelAdmin): form = GovernmentPlanForm save_on_top = True prepopulated_fields = {"slug": ("title",)} search_fields = ("title",) raw_id_fields = ("responsible_publicbody",) actions = ["make_public"] def get_queryset(self, request): qs = get_allowed_plans(request) qs = qs.prefetch_related( "categories", "organization", "group", ) return qs def view_on_site(self, obj): # Avoid Django's redirect through normal admin # TODO: remove on https://github.com/django/django/pull/15526 return obj.get_absolute_url() def get_actions(self, request): actions = super().get_actions(request) if not has_limited_access(request.user): admin_actions = { action: ( func, action, func.short_description, ) for action, func in PLAN_ACTIONS.items() } actions.update(admin_actions) return actions def get_urls(self): urls = super().get_urls() my_urls = [ path( "<int:pk>/accept-proposal/", self.admin_site.admin_view(self.accept_proposal), name="froide_govplan-plan_accept_proposal", ), ] return my_urls + urls def get_list_display(self, request): list_display = [ "title", "public", "status", "rating", "organization", "get_categories", ] if not has_limited_access(request.user): list_display.append("group") return list_display def get_list_filter(self, request): list_filter = [ "status", "rating", "public", ] if not has_limited_access(request.user): list_filter.extend( [ make_emptyfilter( "proposals", _("Has change proposals"), empty_value=None ), "organization", "group", "government", "categories", ] ) return list_filter def get_fields(self, request, obj=None): if has_limited_access(request.user): return ( "title", "slug", "description", "quote", "public", "due_date", "measure", "status", "rating", "reference", ) return super().get_fields(request, obj=obj) def get_categories(self, obj): """ Return the categories linked in HTML. """ categories = [category.name for category in obj.categories.all()] return ", ".join(categories) get_categories.short_description = _("category(s)") def make_public(self, request, queryset): queryset.update(public=True) make_public.short_description = _("Make public") def accept_proposal(self, request, pk): obj = get_object_or_404(self.get_queryset(request), pk=pk) plan_url = reverse( "admin:froide_govplan_governmentplan_change", args=(obj.pk,), current_app=self.admin_site.name, ) if not obj.proposals: return redirect(plan_url) if request.method == "POST": proposals = obj.proposals or {} proposal_id = request.POST.get("proposal_id") delete_proposals = request.POST.getlist("proposal_delete") update = None if proposal_id: data = proposals[proposal_id]["data"] form = GovernmentPlanUpdateAcceptProposalForm(data=data, plan=obj) if form.is_valid(): update = form.save( proposal_id=proposal_id, delete_proposals=delete_proposals, ) else: form = GovernmentPlanUpdateAcceptProposalForm(data={}, plan=obj) form.delete_proposals(delete_proposals) if update is None: self.message_user(request, _("The proposal has been deleted.")) return redirect(plan_url) self.message_user( request, _("An unpublished update has been created."), ) update_url = reverse( "admin:froide_govplan_governmentplanupdate_change", args=(update.pk,), current_app=self.admin_site.name, ) return redirect(update_url) else: form = GovernmentPlanUpdateAcceptProposalForm(plan=obj) opts = self.model._meta context = { "form": form, "proposals": form.get_proposals(), "object": obj, "app_label": opts.app_label, "opts": opts, } return render( request, "froide_govplan/admin/accept_proposal.html", context, ) class GovernmentPlanUpdateAdmin(admin.ModelAdmin): form = GovernmentPlanUpdateForm save_on_top = True raw_id_fields = ("user", "foirequest") date_hierarchy = "timestamp" search_fields = ("title", "content") list_display = ( "title", "timestamp", "plan", "user", "status", "rating", "public", ) list_filter = ( "status", "public", "organization", ) search_fields = ( "title", "plan__title", ) date_hierarchy = "timestamp" def get_queryset(self, request): qs = super().get_queryset(request) qs = qs.prefetch_related( "plan", "user", ) if has_limited_access(request.user): qs = qs.filter(plan__in=get_allowed_plans(request)) return qs def view_on_site(self, obj): # Avoid Django's redirect through normal admin # TODO: remove on https://github.com/django/django/pull/15526 return obj.get_absolute_url() def save_model(self, request, obj, form, change): limited = has_limited_access(request.user) if not change and limited: # When added by a limited user, # autofill user and organization obj.user = request.user if obj.plan.organization: user_has_org = request.user.organization_set.all().filter(pk=1).exists() if user_has_org: obj.organization = obj.plan.organization res = super().save_model(request, obj, form, change) obj.plan.update_from_updates() return res def get_fields(self, request, obj=None): if has_limited_access(request.user): return ( "plan", "title", "timestamp", "content", "url", "status", "rating", "public", ) return super().get_fields(request, obj=obj) def formfield_for_foreignkey(self, db_field, request, **kwargs): if db_field.name == "plan": if has_limited_access(request.user): kwargs["queryset"] = get_allowed_plans(request) return super().formfield_for_foreignkey(db_field, request, **kwargs) def user_in_obj_group(self, request, obj): if not obj.plan.group_id: return False user = request.user return User.objects.filter(pk=user.pk, groups=obj.plan.group_id).exists() def has_view_permission(self, request, obj=None): if obj and self.user_in_obj_group(request, obj): return True return super().has_view_permission(request, obj=obj) def has_add_permission(self, request): return super().has_add_permission(request) def has_change_permission(self, request, obj=None): if obj and self.user_in_obj_group(request, obj): return True return super().has_change_permission(request, obj=obj) class GovernmentPlanSectionAdmin(SortableAdminMixin, admin.ModelAdmin): save_on_top = True prepopulated_fields = {"slug": ("title",)} search_fields = ("title",) raw_id_fields = ("categories",) list_display = ( "title", "featured", ) list_filter = ( "featured", "categories", "government", ) admin.site.register(Government, GovernmentAdmin) admin.site.register(GovernmentPlan, GovernmentPlanAdmin) admin.site.register(GovernmentPlanUpdate, GovernmentPlanUpdateAdmin) admin.site.register(GovernmentPlanSection, GovernmentPlanSectionAdmin) admin.site.register(GovernmentPlanFollower, FollowerAdmin) govplan_admin_site = GovPlanAdminSite(name="govplanadmin") govplan_admin_site.register(GovernmentPlan, GovernmentPlanAdmin) govplan_admin_site.register(GovernmentPlanUpdate, GovernmentPlanUpdateAdmin)

30.859079

88

0.596557

9,290

0.815843

0

1,685

0.147976

a98a8630e0f08cab9b6667bd3db9422e0508306a

2,995

py

Python

tests/test_xmltompd.py

thiblahute/python-mpegdash

e7702dec59fe61668888ba5c9e1cb2f495b72c17

[ "MIT" ]

1

2021-06-08T04:25:04.000Z

tests/test_xmltompd.py

thiblahute/python-mpegdash

e7702dec59fe61668888ba5c9e1cb2f495b72c17

[ "MIT" ]

null

tests/test_xmltompd.py

thiblahute/python-mpegdash

e7702dec59fe61668888ba5c9e1cb2f495b72c17

[ "MIT" ]

1

2021-09-27T12:57:51.000Z

try: import unittest2 as unittest except: import unittest from mpegdash.parser import MPEGDASHParser class XML2MPDTestCase(unittest.TestCase): def test_xml2mpd_from_string(self): mpd_string = ''' <MPD xmlns="urn:mpeg:DASH:schema:MPD:2011" mediaPresentationDuration="PT0H1M52.43S" minBufferTime="PT1.5S" profiles="urn:mpeg:dash:profile:isoff-on-demand:2011" type="static"> <Period duration="PT0H1M52.43S" start="PT0S"> <AdaptationSet> <ContentComponent contentType="video" id="1" /> <Representation bandwidth="4190760" codecs="avc1.640028" height="1080" id="1" mimeType="video/mp4" width="1920"> <BaseURL>motion-20120802-89.mp4</BaseURL> <SegmentBase indexRange="674-981"> <Initialization range="0-673" /> </SegmentBase> </Representation> </AdaptationSet> </Period> </MPD> ''' self.assert_mpd(MPEGDASHParser.parse(mpd_string)) def test_xml2mpd_from_file(self): self.assert_mpd(MPEGDASHParser.parse('./tests/mpd-samples/sample-001.mpd')) self.assert_mpd(MPEGDASHParser.parse('./tests/mpd-samples/motion-20120802-manifest.mpd')) self.assert_mpd(MPEGDASHParser.parse('./tests/mpd-samples/oops-20120802-manifest.mpd')) self.assert_mpd(MPEGDASHParser.parse('./tests/mpd-samples/360p_speciment_dash.mpd')) def test_xml2mpd_from_url(self): mpd_url = 'http://yt-dash-mse-test.commondatastorage.googleapis.com/media/motion-20120802-manifest.mpd' self.assert_mpd(MPEGDASHParser.parse(mpd_url)) def test_xml2mpd_from_file_with_utc_timing(self): mpd = MPEGDASHParser.parse('./tests/mpd-samples/utc_timing.mpd') self.assertEqual(mpd.utc_timings[0].scheme_id_uri, 'urn:mpeg:dash:utc:http-iso:2014') self.assertEqual(mpd.utc_timings[0].value, 'https://time.akamai.com/?iso') def test_xml2mpd_from_file_with_event_messagedata(self): mpd = MPEGDASHParser.parse('./tests/mpd-samples/with_event_message_data.mpd') self.assertTrue(mpd.periods[0].event_streams[0].events[0].message_data is not None) self.assertTrue(mpd.periods[0].event_streams[0].events[0].event_value is None) self.assertTrue(mpd.periods[0].event_streams[0].events[1].message_data is None) self.assertEqual(mpd.periods[0].event_streams[0].events[1].event_value, "Some Random Event Text") def assert_mpd(self, mpd): self.assertTrue(mpd is not None) self.assertTrue(len(mpd.periods) > 0) self.assertTrue(mpd.periods[0].adaptation_sets is not None) self.assertTrue(len(mpd.periods[0].adaptation_sets) > 0) self.assertTrue(mpd.periods[0].adaptation_sets[0].representations is not None) self.assertTrue(len(mpd.periods[0].adaptation_sets[0].representations) > 0) self.assertTrue(len(mpd.periods[0].adaptation_sets[0].representations[0].id) > 0)

50.762712

126

0.686477

2,882

0.96227

0

1,211

0.404341

a98cc0ed5054e6dba3e35b5238cafe5ac890c96b

513

py

Python

algorithm_toolbox/week_4/03_divide_and_conquer_1_search_array/iterativeBinSearch.py

dibyanshushekhardey/data_struct_and_algo_coursera

ce579ba0be19d0415dc5a9526fd04bcdb803dbc0

[ "MIT" ]

null

algorithm_toolbox/week_4/03_divide_and_conquer_1_search_array/iterativeBinSearch.py

dibyanshushekhardey/data_struct_and_algo_coursera

ce579ba0be19d0415dc5a9526fd04bcdb803dbc0

[ "MIT" ]

null

algorithm_toolbox/week_4/03_divide_and_conquer_1_search_array/iterativeBinSearch.py

dibyanshushekhardey/data_struct_and_algo_coursera

ce579ba0be19d0415dc5a9526fd04bcdb803dbc0

[ "MIT" ]

null

def BinarySearchIt(A, low, high, key): while low <= high: mid = low + ((high - low)//2) if key == A[mid]: return mid elif key < A[mid]: high = mid - 1 else: low = mid + 1 return low - 1 arr = [3, 5, 8, 10, 12, 15, 18, 20, 20, 50, 60] low = 1 high = 11 key = 50 index = BinarySearchIt(arr, low, high, key) if index != -1: print ("Element", key,"is present at index %d" %(index)) else: print ("Element %d is not present" %(key))

23.318182

60

0.502924

0

60

0.116959

a98fe624f9604a44b5865d4659413307a64a58db

2,133

py

Python

2016/day-02.py

mharty3/advent_of_code

f86e67eb772f4c328e30744610606fc154930aef

[ "MIT" ]

null

2016/day-02.py

mharty3/advent_of_code

f86e67eb772f4c328e30744610606fc154930aef

[ "MIT" ]

null

2016/day-02.py

mharty3/advent_of_code

f86e67eb772f4c328e30744610606fc154930aef

[ "MIT" ]

null

#--- Day 2: Bathroom Security --- from typing import List def parse(input_data: str) -> List[List[str]]: lines = input_data.strip().split() directions = [list(line) for line in lines] return directions def move1(x, y, direction): if direction == 'U': y -= 1 elif direction == 'D': y += 1 elif direction == 'L': x -= 1 elif direction == 'R': x += 1 if y < 0: y = 0 if y > 2: y = 2 if x < 0: x = 0 if x > 2: x = 2 return x, y def move2(x, y, direction, keypad): last_x = x last_y = y if direction == 'U': y -= 1 elif direction == 'D': y += 1 elif direction == 'L': x -= 1 elif direction == 'R': x += 1 if keypad[x][y] == '-': return last_x, last_y else: return x, y def solve1(input_data: str) -> str: keypad = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] x = 1 y = 1 keycode = [] for line in parse(input_data): for direction in line: x, y = move1(x, y, direction) keycode.append(str(keypad[y][x])) return ''.join(keycode) def solve2(input_data): keypad = [['-', '-', '-', '-', '-', '-', '-'], ['-', '-', '-', '1', '-', '-', '-'], ['-', '-', '2', '3', '4', '-', '-'], ['-', '5', '6', '7', '8', '9', '-'], ['-', '-', 'A', 'B', 'C', '-', '-'], ['-', '-', '-', 'D', '-', '-', '-'], ['-', '-', '-', '-', '-', '-', '-']] x = 1 y = 3 keycode = [] for line in parse(input_data): for direction in line: x, y = move2(x, y, direction, keypad) keycode.append(keypad[y][x]) return ''.join(keycode) test_data = """ULL RRDDD LURDL UUUUD""" assert solve1(test_data) == '1985' assert solve2(test_data) == '5DB3' if __name__ == '__main__': from aocd.models import Puzzle puzzle = Puzzle(2016, 2) answer_1 = solve1(puzzle.input_data) print(answer_1) puzzle.answer_a = answer_1 answer_2 = solve2(puzzle.input_data) puzzle.answer_b = answer_2

21.118812

50

0.449602

0

260

0.121894

a99348b5bc6c6ccf0bf508d81eb41b18d8e6cf18

2,875

py

Python

compose.py

gicmo/koji-osbuild

d8107f23478ca12cd376098a79c7465cc5dd12d1

[ "Apache-2.0" ]

null

compose.py

gicmo/koji-osbuild

d8107f23478ca12cd376098a79c7465cc5dd12d1

[ "Apache-2.0" ]

null

compose.py

gicmo/koji-osbuild

d8107f23478ca12cd376098a79c7465cc5dd12d1

[ "Apache-2.0" ]

null

#!/usr/bin/python3 import argparse import koji import os from pprint import pprint def main(): parser = argparse.ArgumentParser(description="osbuild koji client") parser.add_argument("--url", metavar="URL", type=str, default="https://localhost/kojihub", help="The URL koji hub API endpoint") parser.add_argument("--repo", metavar="REPO", help='The repository to use', type=str, action="append", default=[]) parser.add_argument("--release", metavar="RELEASE", help='The distribution release') parser.add_argument("--user", metavar="USER", default="kojiadmin") parser.add_argument("--password", metavar="PASSWORD", default="kojipass") parser.add_argument("--principal", metavar="USER", default="osbuild-krb@LOCAL") parser.add_argument("--keytab", metavar="FILE", help="kerberos keytab", default="/tmp/osbuild-composer-koji-test/client.keytab") parser.add_argument("--serverca", metavar="FILE", help="Server CA", default="/tmp/osbuild-composer-koji-test/ca-crt.pem") parser.add_argument("--plain", help="use plain text login", default=False, action="store_true") parser.add_argument("name", metavar="NAME", help='The distribution name') parser.add_argument("version", metavar="VERSION", help='The distribution version') parser.add_argument("distro", metavar="DISTRO", help='The distribution') parser.add_argument("target", metavar="TARGET", help='The build target') parser.add_argument("arch", metavar="ARCHITECTURE", help='Request the architecture', type=str, nargs="+") parser.add_argument("--image-type", metavar="TYPE", help='Request an image-type [default: qcow2]', type=str, action="append", default=[]) args = parser.parse_args() opts = {"user": args.user, "password": args.password, "serverca": args.serverca} session = koji.ClientSession(args.url, opts) if args.plain: session.login() else: session.gssapi_login(principal=args.principal, keytab=args.keytab) name, version, arch, target = args.name, args.version, args.arch, args.target distro, image_types = args.distro, args.image_type if not image_types: image_types = ["qcow2"] opts = {} if args.release: opts["release"] = args.release if args.repo: opts["repo"] = ",".join(args.repo) print("name:", name) print("version:", version) print("distro:", distro) print("arches:", ", ".join(arch)) print("target:", target) print("image types ", str(image_types)) if opts: pprint(opts) session.osbuildImage(name, version, distro, image_types, target, arch, opts=opts) if __name__ == "__main__": main()

39.930556

88

0.631652

0

878

0.305391

a9939846090c5322d4926d75f10b1fc68c18dada

153

py

Python

{{cookiecutter.repo_name}}/{{cookiecutter.package_name}}/{{cookiecutter.package_name}}.py

numengo/cc-py-setup

392dfb85acb9052bf48586b9be98fc1f591d8991

[ "ISC", "Apache-2.0", "MIT" ]

3

2018-02-16T17:10:15.000Z

2018-03-01T19:38:54.000Z

{{cookiecutter.repo_name}}/{{cookiecutter.package_name}}/{{cookiecutter.package_name}}.py

numengo/cc-py-setup

392dfb85acb9052bf48586b9be98fc1f591d8991

[ "ISC", "Apache-2.0", "MIT" ]

null

{{cookiecutter.repo_name}}/{{cookiecutter.package_name}}/{{cookiecutter.package_name}}.py

numengo/cc-py-setup

392dfb85acb9052bf48586b9be98fc1f591d8991

[ "ISC", "Apache-2.0", "MIT" ]

null

# -*- coding: utf-8 -*- """Main module {{cookiecutter.project_name}} """ from __future__ import absolute_import from __future__ import unicode_literals

25.5

48

0.751634

0

71

0.464052

a995cea083a766e717127d27dd67556ccd2542a5

5,382

py

Python

src/models/def_features.py

jshcs/cfe

dc6ca928a124a3e0e0dd64a1d3667a9b313e8c50

[ "MIT" ]

null

src/models/def_features.py

jshcs/cfe

dc6ca928a124a3e0e0dd64a1d3667a9b313e8c50

[ "MIT" ]

null

src/models/def_features.py

jshcs/cfe

dc6ca928a124a3e0e0dd64a1d3667a9b313e8c50

[ "MIT" ]

null

from config import * from utils import * import datetime import pickle indir_vocab_jnames = VOCAB_JNAMES indir_bio_srt = BIO_SRT indir_sorted_fperson_fname = SORTED_FPERSON_FNAME indir_sorted_lperson_fname = SORTED_LPERSON_FNAME print indir_vocab_jnames with open(indir_vocab_jnames,'rb') as v: all_vocab=pickle.load(v) with open(indir_bio_srt,'rb') as v: all_bio_vocab=pickle.load(v) all_bio_vocab = [a.decode('utf-8') for a in all_bio_vocab] sorted_fname= read_sorted_file_into_array(indir_sorted_fperson_fname) sorted_lname= read_sorted_file_into_array(indir_sorted_lperson_fname) class CRF_Features(): def __init__(self,token): self.token = token self.jnames_vocab=all_vocab self.bioterms_vocab=all_bio_vocab self.features = {k:False for k in config_params['feature_names']} # self.db =simstring.reader(DB_JNAMES) def is_title(self): self.features["is_title"] = self.token.istitle() def is_upper(self): self.features["is_upper"] = self.token.isupper() def is_alpha_num(self): self.features["is_alpha_num"] = self.token.isalnum() def word_length(self): self.features["word_length"] = len(self.token) def is_num(self): self.features["is_number"] = self.token.isdigit() def ends_with_period(self): self.features["ends_with_period"]=self.token[-1]=='.' def enclosed_brackets(self): if self.token[0] in BRACKETS: if self.token[-1]==BRACKETS[self.token[0]]: self.features["enclosed_brackets"]=True else: self.features["enclosed_brackets"]=False else: self.features["enclosed_brackets"]=False def has_hyphen(self): self.features["has_hyphen"] = False parts = self.token.split('-') if len(parts) > 1 : self.features["has_hyphen"] = True is_digit = True for part in parts : if part != '': is_digit = is_digit and part.isdigit() self.features["is_number"] = is_digit def has_colon(self): self.features["has_colon"]= False parts = self.token.split(':') if len(parts) > 1 : self.features["has_colon"]= True def is_etal(self): self.features["et_al"] = self.token == 'et' or self.token == 'al' def is_valid_year(self): self.features["is_valid_year"] = self.token.isdigit() and self.features["word_length"] <= 4 \ and self.features["word_length"] >=2 and 1<=int(self.token)<=datetime.datetime.now().year def is_special_token(self): self.features["is_special_token"] = True if self.token in SPCL_KEYS else False def has_period_period(self): #12 # s=time.time() self.features["has_period_period"]=False if ".." in self.token: self.features["has_period_period"]=True def has_period_comma(self): #13 if ".," in self.token: self.features["has_period_comma"]=True def is_url(self): #14 if "http://" in self.token or "www." in self.token : self.features["is_url"]=True else : self.features["is_url"] = False def is_email(self): #15 stra = self.token if '@' in stra and '.' in stra.split('@')[1] : self.features["is_email"]=True else : self.features["is_email"]=False def first_name_lexicon(self): #16 # s=time.time() if len(self.token)==2 and self.features["is_upper"] and self.features["ends_with_period"]: self.features["first_name_lexicon"]=True return arr= sorted_fname start=0 end=len(arr)-1 self.features["first_name_lexicon"]=binary_search(arr,self.token.upper(),start,end) def last_name_lexicon(self): #17 # s=time.time() #arr=read_sorted_file_into_array(SORTED_LPERSON_FNAME) arr= sorted_lname start=0 end=len(arr)-1 self.features["last_name_lexicon"]=binary_search(arr,self.token.upper(),start,end) # e=time.time() # self.times.append(e-s) def journal_lexicon(self): #18 if self.token.lower() in self.jnames_vocab: self.features['journal_name']=True else : self.features['journal_name']=False def is_bio_term(self): #19 token = self.token.decode('utf-8') self.features["is_bio_term"]=binary_search(all_bio_vocab,token.lower(),0,len(all_bio_vocab)-1) def get_features(self): self.is_title() self.is_upper() self.is_alpha_num() self.word_length() self.is_num() self.ends_with_period() self.enclosed_brackets() self.has_hyphen() self.has_colon() self.is_etal() self.is_valid_year() self.is_special_token() self.has_period_comma() self.has_period_period() self.is_url() self.is_email() self.first_name_lexicon() self.last_name_lexicon() self.is_bio_term() self.journal_lexicon() return self.features def test(): citation = 'A. Mironov A. Morozov And Morozov arXiv:1003.5752' words = citation.split(' ') for word in words : feats = CRF_Features(word) print feats.get_features() #test()

31.290698

102

0.622074

4,566

0.848384

0

825

0.153289

a9971d06d9c16341c965038e22004beaf49e0586

2,182

py

Python

profile_python/profile.py

heroesofcode/profile-python

e4e6ee2f3739ea6edad30999b74b3d42f754a86c

[ "MIT" ]

null

profile_python/profile.py

heroesofcode/profile-python

e4e6ee2f3739ea6edad30999b74b3d42f754a86c

[ "MIT" ]

1

2021-10-09T01:26:29.000Z

profile_python/profile.py

heroesofcode/profile-python

e4e6ee2f3739ea6edad30999b74b3d42f754a86c

[ "MIT" ]

null

from rich.console import Console from rich.table import Table from rich.progress import track from time import sleep import sys class Profile(object): def get_datas(self, datas): try: print(datas['login']) print(datas['name']) print(datas['bio']) print(datas['company']) print(datas['blog']) print(datas['location']) except: print("This user does not exist") def get_repos(self, repos): try: for repo in repos: table = Table(show_header=True, header_style="bold magenta") table.add_column("Name Repository") table.add_column("Language") table.add_column("Forks") table.add_column("Stars") table.add_row( repo['name'], repo['language'], str(repo['forks_count']), str(repo['stargazers_count']) ) console = Console() console.print(table) except: print("This user does not exist") def exist_application(self): option_exist = input("Do you really want to exit the system? y/n: ") if option_exist == "y": sys.exit() def process_data(self): for _ in track(range(100), description='[green]Processing data'): sleep(0.02) def run_app(self, values_datas, values_repos): while True: print("-----------------------------------------------") print("1 - My datas") print("2 - Repositories") print("3 - Exist") print("-----------------------------------------------") option = input("Choose an option: ") if option == "1": self.process_data() self.get_datas(values_datas) elif option == "2": self.process_data() self.get_repos(values_repos) elif option == "3": self.exist_application() else: print("This option does not exist")

29.486486

76

0.47846

2,051

0.939963

0

468

0.214482

a99744e768b04af0c0bed6111d20060a12e0cfeb

2,459

py

Python

app/view/admin/notification_manage.py

G1NTOKI0522/WeChatterBot

1a5377713fd3d6c7a6bca1c20e8fdcf70e8215f5

[ "BSD-3-Clause" ]

1

2020-04-03T02:54:18.000Z

app/view/admin/notification_manage.py

G1NTOKI0522/WeChatterBot

1a5377713fd3d6c7a6bca1c20e8fdcf70e8215f5

[ "BSD-3-Clause" ]

7

2020-04-11T13:22:50.000Z

2020-05-14T00:19:37.000Z

app/view/admin/notification_manage.py

G1NTOKI0522/WeChatterBot

1a5377713fd3d6c7a6bca1c20e8fdcf70e8215f5

[ "BSD-3-Clause" ]

3

2020-04-11T12:09:56.000Z

2020-12-16T13:26:20.000Z

# coding: utf-8 import datetime from flask_login import login_required, current_user from flask import Blueprint, request from app.libs.http import jsonify, error_jsonify from app.libs.db import session from app.serializer.notice import NoticeParaSchema from app.model.notice import Notice bp_admin_notification = Blueprint('admin_notification', __name__, url_prefix='/admin/notification') @bp_admin_notification.route("/", methods=["POST"]) @login_required def notification_manage(): # 管理员设定通知 if current_user.isAdmin == 0: # 只能为管理员 return error_jsonify(10000003) json = request.get_json() data, errors = NoticeParaSchema().load(json) if errors: return error_jsonify(10000001, errors) now = datetime.datetime.now() data['created_at'] = now data['source'] = '山东省人力资源管理部门' data['user_id'] = current_user.id new_data = Notice(**data) session.add(new_data) session.commit() return jsonify({}) @bp_admin_notification.route("/", methods=["GET"]) @login_required def notification_get(): # 管理员获得通知 if current_user.isAdmin == 0: # 只能为管理员 return error_jsonify(10000003) if current_user.isAdmin == 2: # 如果是省级管理员 res = Notice.query.all() # 获得所有通知 if current_user.isAdmin == 1: # 市级管理员 res = Notice.query.filter_by(user_id=current_user.id).all() data_need, errors = NoticeParaSchema(many=True).dump(res) if errors: return error_jsonify(10000001, errors) return jsonify(data_need) @bp_admin_notification.route("/<int:id>", methods=["POST"]) @login_required def notice_manage_id(id): # 更改管理员获得的通知 if current_user.isAdmin == 0: # 只能为管理员 return error_jsonify(10000003) json = request.get_json() data, errors = NoticeParaSchema().load(json) if errors: return error_jsonify(10000001, errors) data_need = Notice.query.filter_by(id=id) if data_need.first() is None: # 没有这个id，更改失败 return error_jsonify(10000018) data_need.update(data) session.commit() return jsonify({}) @bp_admin_notification.route("/<int:id>", methods=["DELETE"]) @login_required def notice_manage_delete(id): # 删除id对应的通知 if current_user.isAdmin == 0: # 只能为管理员 return error_jsonify(10000003) data_need = Notice.query.filter_by(id=id).first() if data_need is None: return error_jsonify(10000017) session.delete(data_need) session.commit() return jsonify({})

28.264368

99

0.699471

0

2,240

0.846241

0

451

0.170382

a998c1d627b7fcf20a5161fbb3c3b4a79699eea3

1,345

py

Python

test/test_delete_contact_from_group.py

schukinp/python_training

8140bbf1aae10052055f272c8deb3a7bdb7abcfb

[ "Apache-2.0" ]

null

test/test_delete_contact_from_group.py

schukinp/python_training

8140bbf1aae10052055f272c8deb3a7bdb7abcfb

[ "Apache-2.0" ]

null

test/test_delete_contact_from_group.py

schukinp/python_training

8140bbf1aae10052055f272c8deb3a7bdb7abcfb

[ "Apache-2.0" ]

null

from fixture.orm import ORMfixture from model.group import Group from model.contact import Contact import random db = ORMfixture(host='127.0.0.1', name='addressbook', user='root', password='') def test_delete_contact_from_group(app): if len(db.get_contact_list()) == 0: app.contact.create(Contact(firstname="Russel", lastname="Westbrook")) if len(db.get_group_list()) == 0: app.group.create(Group(name="Test")) old_contacts = db.get_contact_list() old_groups = db.get_group_list() contact = random.choice(old_contacts) group = random.choice(old_groups) old_contacts_in_group = db.get_contacts_in_group(group) if len(db.get_contacts_in_group(group)) == 0: app.contact.add_contact_to_group(contact, group) else: contact = random.choice(old_contacts_in_group) old_contacts_in_group_update = db.get_contacts_in_group(group) app.contact.delete_contact_from_group(contact, group) new_contacts_in_group = db.get_contacts_in_group(group) assert len(old_contacts_in_group_update) - 1 == len(new_contacts_in_group) old_contacts_in_group_update.remove(contact) assert sorted(old_contacts_in_group_update, key=Contact.id_or_max) == sorted(new_contacts_in_group, key=Contact.id_or_max)

44.833333

130

0.710781

0

57

0.042379

a9993f306b253d20a5358a309289cc43d569a04f

323

py

Python

apps/accounts/views.py

martindwyer/Juntos

0aac3add432f5f3fc42befc720b70253d4fef2b4

[ "MIT" ]

null

apps/accounts/views.py

martindwyer/Juntos

0aac3add432f5f3fc42befc720b70253d4fef2b4

[ "MIT" ]

null

apps/accounts/views.py

martindwyer/Juntos

0aac3add432f5f3fc42befc720b70253d4fef2b4

[ "MIT" ]

null

from django.urls import reverse_lazy from django.contrib.auth import get_user_model from django.views.generic import CreateView from . import forms User = get_user_model() class SignUp(CreateView): form_class = forms.UserCreateForm success_url = reverse_lazy('login') template_name = 'accounts/signup.html'

23.071429

46

0.783282

146

0.452012

0

29

0.089783

a99aa91e73c38055d1f2d643a8c77c56216293f4

6,498

py

Python

colossalai/engine/_base_engine.py

rahulgupta9202/ColossalAI

993088d45eaa032e39cf5959df2a506f0663bc2e

[ "Apache-2.0" ]

1

2022-03-12T04:49:19.000Z

colossalai/engine/_base_engine.py

rahulgupta9202/ColossalAI

993088d45eaa032e39cf5959df2a506f0663bc2e

[ "Apache-2.0" ]

null

colossalai/engine/_base_engine.py

rahulgupta9202/ColossalAI

993088d45eaa032e39cf5959df2a506f0663bc2e

[ "Apache-2.0" ]

null

#!/usr/bin/env python # -*- encoding: utf-8 -*- from torch.nn import Module from torch.nn.modules.loss import _Loss from torch.optim import Optimizer from colossalai.builder import build_gradient_handler from colossalai.context import ParallelMode from colossalai.core import global_context as gpc from colossalai.logging import get_global_dist_logger from colossalai.nn import (ZeroRedundancyOptimizer_Level_2, ZeroRedundancyOptimizer_Level_3) from .schedule import BaseSchedule class Engine: """Basic engine class for training and evaluation. It runs a specific process method :meth:`step` which is based on the given :attr:`schedule` over each batch of a dataset. It controls a iteration in training. :param model: The neural network model :param optimizer: Optimizer for updating the parameters :param step_schedule: Running schedule in :meth:`step` :param gradient_accumulation: Steps of gradient accumulation :param gradient_clipping: The norm of gradient clipping :type model: Module :type optimizer: Optimizer :type step_schedule: BaseSchedule, optional :type gradient_accumulation: int, optional :type gradient_clipping: float, optional """ def __init__(self, model: Module, optimizer: Optimizer, criterion: _Loss, step_schedule: BaseSchedule, gradient_handlers: list = None, gradient_accumulation: int = 1, gradient_clipping: float = 0.0, ): self._model = model self._optimizer = optimizer self._criterion = criterion self._schedule = step_schedule # schedule initialize self._schedule.initialize(model, optimizer) # state self.training = True # default # gradient accumulation assert gradient_accumulation > 0, 'gradient accumulation size must be larger than 0' self._grad_accum_size = gradient_accumulation self._grad_clip = gradient_clipping self._logger = get_global_dist_logger() # build gradient handler self._gradient_handlers = [] if gradient_handlers is not None: assert isinstance(gradient_handlers, list), \ f'argument gradient_handler_cfg expected type list, ' \ f'but got type {type(gradient_handlers)}' elif isinstance(optimizer, (ZeroRedundancyOptimizer_Level_2, ZeroRedundancyOptimizer_Level_3)): gradient_handlers = [dict(type='ZeROGradientHandler')] self._logger.info( "Training with zero is detected, ZeROGradientHandler is automatically " "added even though not specified in the configuration", ranks=[0]) elif gpc.is_initialized(ParallelMode.DATA) and gpc.get_world_size( ParallelMode.DATA) > 1: gradient_handlers = [dict(type='DataParallelGradientHandler')] self._logger.info( "Data parallel training is detected, DataParallelGradientHandler is automatically " "added even though not specified in the configuration", ranks=[0]) if gradient_handlers is None: self._logger.warning( "No gradient handler is set up, please make sure you do not need " "to all-reduce the gradients after a training step.", ranks=[0]) else: for cfg in gradient_handlers: handler = build_gradient_handler(cfg, model, optimizer) self._gradient_handlers.append(handler) @property def model(self): return self._model @property def optimizer(self): return self._optimizer @property def criterion(self): return self._criterion @property def schedule(self): return self._schedule @property def gradient_accumulation(self): return self._grad_accum_size def handle_gradient(self): """Handles all-reduce operations of gradients across different parallel groups. """ for handler in self._gradient_handlers: handler.handle_gradient() def train(self): """Sets the model to training mode. """ self.training = True self._model.train() def eval(self): """Sets the model to evaluation mode. """ self.training = False self._model.eval() def step(self, data_iter, is_last_iteration: bool = False, return_loss=True): """A running step based on the schedule. Usually, it runs a training or evaluation over a batch of dataset. :param data_iter: Data iterator of the dataset :param is_last_iteration: If True, this iteration is the last iteration in the epoch :param return_loss: loss will be returned if True :type data_iter: Iterator :type is_last_iteration: bool, optional :type return_loss: bool, optional :return: (output, lablel, loss) """ if self.training: self._optimizer.zero_grad() # differentiate training and eval with grad accum if self.training: for i in range(self._grad_accum_size): output, label, loss = self._schedule.forward_backward_step( data_iter, self._model, self._criterion, self._optimizer, forward_only=False, grad_accum_size=self._grad_accum_size, return_loss=return_loss) if i == self._grad_accum_size - 1: # all reduce gradients self.handle_gradient() self._schedule.optimizer_step(self._model, self._optimizer, self._grad_clip) else: output, label, loss = self._schedule.forward_backward_step( data_iter, self._model, self._criterion, self._optimizer, forward_only=True, grad_accum_size=1, return_loss=return_loss) # consume the remaining dataset left out due to gradient accumulation if is_last_iteration: while True: try: _ = next(data_iter) except StopIteration: break return output, label, loss

36.711864

99

0.622499

5,986

0.921207

0

333

0.051247

0

2,238

0.344414

a99b36048f5d32ab6c9b6ad9baf0b5a681590fdd

718

py

Python

11. Optical Flow/optical_flow.py

farhan0syakir/OpenCv-tutorial

b3d78f3567f4ea61b8955190f51097b6ceb4b318

[ "MIT" ]

15

2021-05-04T15:03:14.000Z

2022-03-20T11:57:55.000Z

11. Optical Flow/optical_flow.py

farhan0syakir/OpenCv-tutorial

b3d78f3567f4ea61b8955190f51097b6ceb4b318

[ "MIT" ]

12

2020-09-24T16:57:45.000Z

2020-10-23T15:13:06.000Z

11. Optical Flow/optical_flow.py

farhan0syakir/OpenCv-tutorial

b3d78f3567f4ea61b8955190f51097b6ceb4b318

[ "MIT" ]

18

2020-09-21T13:01:37.000Z

2020-10-15T19:42:28.000Z

import numpy as np import cv2 cap = cv2.VideoCapture('motion.avi') ret, frame = cap.read() gs_im0 = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) points_prev = cv2.goodFeaturesToTrack(gs_im0, 100, 0.03, 9.0, False) while(cap.isOpened()): ret, frame = cap.read() gs_im1 = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) # Call tracker. points, st, err = cv2.calcOpticalFlowPyrLK(gs_im0, gs_im1, points_prev, None, (3,3)) for i,p in enumerate(points): a,b = p.ravel() frame = cv2.circle(frame,(a,b),3,(255,255,255),-1) cv2.imshow('frame',frame) points_prev = points gs_im0 = gs_im1 if cv2.waitKey(1) & 0xFF == ord('q'): break cap.release() cv2.destroyAllWindows()

25.642857

88

0.650418

0

37

0.051532

a99d2fd19858a720fd9deb294de8995490e6da48

574

py

Python

game/rendering.py

rajbala5479/asteroid

73c6eab1bbdb68ff6c7f337c9517ba0ac1f34294

[ "MIT" ]

null

game/rendering.py

rajbala5479/asteroid

73c6eab1bbdb68ff6c7f337c9517ba0ac1f34294

[ "MIT" ]

null

game/rendering.py

rajbala5479/asteroid

73c6eab1bbdb68ff6c7f337c9517ba0ac1f34294

[ "MIT" ]

null

import math class Renderer: # Convenience methods def drawCircle( self, radius = 10, res = 30): pass class FilledPolygon(): def __init__(): pass def render(self): if len class PolyLine(): def __init__(): pass def make_circle(radius = 10, res = 20, filled = True): points = [] for i in range(res): ang = 2*math.pi * i / res points.append((math.cos(ang) * radius, math.sin(ang) * radius) ) if filled: return FilledPolygon(points) else: return PolyLine(points, True)

19.793103

72

0.574913

252

0.439024

0

21

0.036585

a99e5850b3151bb654dd58f3e042f9310c260e3c

2,770

py

Python

tests/components/test_servo.py

Shivam60/j5

18069737644c8f1c95944386773c7643d5df5aeb

[ "MIT" ]

null

tests/components/test_servo.py

Shivam60/j5

18069737644c8f1c95944386773c7643d5df5aeb

[ "MIT" ]

null

tests/components/test_servo.py

Shivam60/j5

18069737644c8f1c95944386773c7643d5df5aeb

[ "MIT" ]

null

"""Tests for the servo classes.""" from typing import List, Optional, Type import pytest from j5.backends import Backend from j5.boards import Board from j5.components.servo import Servo, ServoInterface, ServoPosition class MockServoDriver(ServoInterface): """A testing driver for servos.""" def get_servo_position(self, board: Board, identifier: int) -> ServoPosition: """Get the position of a Servo.""" return 0.5 def set_servo_position( self, board: Board, identifier: int, position: ServoPosition, ) -> None: """Set the position of a Servo.""" pass class MockServoBoard(Board): """A testing board for servos.""" @property def name(self) -> str: """The name of this board.""" return "Testing Servo Board" @property def serial(self) -> str: """The serial number of this board.""" return "SERIAL" @property def firmware_version(self) -> Optional[str]: """Get the firmware version of this board.""" return self._backend.get_firmware_version(self) @property def supported_components(self) -> List[Type["Component"]]: """List the types of component that this Board supports.""" return [Servo] def make_safe(self): """Make this board safe.""" pass @staticmethod def discover(backend: Backend): """Detect all of the boards on a given backend.""" return [] def test_servo_interface_implementation(): """Test that we can implement the ServoInterface.""" MockServoDriver() def test_servo_interface_class(): """Test that the interface class is ServoInterface.""" assert Servo.interface_class() is ServoInterface def test_servo_instantiation(): """Test that we can instantiate a Servo.""" Servo(0, MockServoBoard(), MockServoDriver()) def test_servo_get_position(): """Test that we can get the position of a servo.""" servo = Servo(2, MockServoBoard(), MockServoDriver()) assert type(servo.position) is float assert servo.position == 0.5 def test_servo_set_position(): """Test that we can set the position of a servo.""" servo = Servo(2, MockServoBoard(), MockServoDriver()) servo.position = 0.6 def test_servo_set_position_none(): """Test that we can set the position of a servo to None.""" servo = Servo(2, MockServoBoard(), MockServoDriver()) servo.position = None def test_servo_set_position_out_of_bounds(): """Test that we cannot set < -1 or > 1.""" servo = Servo(2, MockServoBoard(), MockServoDriver()) with pytest.raises(ValueError): servo.position = 2 with pytest.raises(ValueError): servo.position = -2

26.634615

81

0.652708

1,280

0.462094

0

677

0.244404

0

809

0.292058

a99e9b3110ca912a6a3fdcacc3a5951f95d02cb7

327

py

Python

Desafios/des029.py

vitormrts/ExerciciosPython

176b1c21e147670f7495678bdd4fc97241440d28

[ "MIT" ]

1

2021-02-07T18:58:57.000Z

Desafios/des029.py

vitormrts/ExerciciosPython

176b1c21e147670f7495678bdd4fc97241440d28

[ "MIT" ]

null

Desafios/des029.py

vitormrts/ExerciciosPython

176b1c21e147670f7495678bdd4fc97241440d28

[ "MIT" ]

null

frase = str(input('Digite uma frase: ')).lower() print('Sobre a letra "a": \nQuantas vezes ela aparece? {} vezes;'.format(frase.count('a'))) print('Em que posição ela aparece pela primeira vez? {};'.format(frase.strip().index('a')+1)) print('Em que posição ela aparece pela última vez? {}.'.format(frase.strip().rfind('a')+1))

65.4

93

0.678899

0

193

0.581325

a9a00c334939540391cc64f13f7f530cabcf615a

7,546

py

Python

unfold/transactions/views.py

wesny/unfold

6594054f7408ac142fc6e902093b6fc8cbfda94e

[ "MIT" ]

null

unfold/transactions/views.py

wesny/unfold

6594054f7408ac142fc6e902093b6fc8cbfda94e

[ "MIT" ]

null

unfold/transactions/views.py

wesny/unfold

6594054f7408ac142fc6e902093b6fc8cbfda94e

[ "MIT" ]

null

from django.contrib.auth.mixins import LoginRequiredMixin from django.views import View from django.views.generic import ListView from django.utils.http import is_safe_url from django.contrib import messages from rest_framework import status from django.core.exceptions import ObjectDoesNotExist from django.shortcuts import redirect, render from mama_cas.models import ServiceTicket from mama_cas.utils import redirect as cas_redirect from mama_cas.utils import to_bool from rest_framework.response import Response from decimal import Decimal from django.urls import reverse import urllib from pinax.stripe.mixins import CustomerMixin from pinax.stripe.models import Charge from pinax.stripe.actions import charges from stripe.error import CardError from rest_framework_jwt.settings import api_settings from unfold.transactions.models import Purchase, Article from unfold.transactions.admin import PurchaseForm from unfold.users.models import User jwt_payload_handler = api_settings.JWT_PAYLOAD_HANDLER jwt_encode_handler = api_settings.JWT_ENCODE_HANDLER def bad_request(message): return Response({ 'status': 'error', 'message': message, }, status=status.HTTP_400_BAD_REQUEST) class PurchaseView(LoginRequiredMixin, View): template_name = "pages/purchase_article.html" form_class = PurchaseForm # def test_func(self): # return self.request.user.is_publisher def get(self, request, *args, **kwargs): publisherusername = request.GET.get('publisher', None) external_id = request.GET.get('id', None) new_token = to_bool(request.GET.get('new_token', None)) if publisherusername == None or external_id == None: return bad_request("Invalid Parameters") try: article = Article.objects.get(publisher__username=publisherusername, external_id=external_id) except ObjectDoesNotExist: return bad_request("Article referenced does not exist") purchase = Purchase.objects.filter(article=article, buyer=request.user) if purchase.exists(): if new_token != None: publisher = User.objects.get(username=publisherusername) st = ServiceTicket.objects.create_ticket(service=publisherusername + '.com', user=request.user) return cas_redirect(article.url, params={'token': st.ticket}) else: return redirect(article.url) try: publisher = User.objects.get(username=publisherusername) except ObjectDoesNotExist: return bad_request("Publisher does not exist") next_url = '' if article.price > request.user.balance: next_url = urllib.parse.quote(request.get_full_path(), safe='~()*!.\'') form = self.form_class(initial={ 'external_id': external_id, 'publisher': publisherusername, 'price': article.price }) data = { 'form': form, 'price': article.price, 'publisher': publisher.name, 'title': article.title, 'balance': request.user.balance, 'next': next_url or '' } return render(request, self.template_name, data) def post(self, request, *args, **kwargs): form = self.form_class(request.POST) if form.is_valid(): external_id = form.cleaned_data['external_id'] publisherusername = form.cleaned_data['publisher'] price = form.cleaned_data['price'] new_token = to_bool(request.GET.get('new_token', None)) try: article = Article.objects.get(publisher__username=publisherusername, external_id=external_id) except ObjectDoesNotExist: return bad_request("Article referenced does not exist") if article.price != price: return bad_request("Price has changed since submission") purchase = Purchase(article=article, price=price, buyer=request.user) purchase.save() request.user.balance = request.user.balance - purchase.price request.user.save() publisher = User.objects.get(username=publisherusername) publisher.balance = publisher.balance + purchase.price publisher.save() if new_token != None: st = ServiceTicket.objects.create_ticket(service=publisherusername + '.com', user=request.user) return cas_redirect(article.url, params={'token': st.ticket}) else: return redirect(article.url) return render(request, self.template_name, {'form': form}) class ReloadView(LoginRequiredMixin, View): template_name = "pages/refill_account.html" def get_redirect_url(self): redirect_to = self.request.POST.get( 'next', self.request.GET.get('next', '') ) url_is_safe = is_safe_url(url=redirect_to) return redirect_to if url_is_safe else '' def get(self, request, *args, **kwargs): can_charge = True balance = request.user.balance data = { 'balance': balance, 'can_charge': can_charge } return render(request, self.template_name, data) def post(self, request, *args, **kwargs): try: add_on = Decimal(request.POST.get('amount')) except: messages.error(request, 'Amount was not in the desired format.') can_charge = True balance = request.user.balance data = { 'balance': balance, 'can_charge': can_charge } return render(request, self.template_name, data) try: charges.create(amount=add_on, customer=request.user.customer.stripe_id) except CardError as e: body = e.json_body err = body.get('error', {}) messages.error(request, err.get('message')) return redirect("/reload") user = User.objects.get(username=request.user.username) user.balance = user.balance + add_on user.save() messages.success(request, "Payment was successfully processed.") url = self.get_redirect_url() or '/user' return redirect(url) class NewAPIKeyView(LoginRequiredMixin, View): def post(self, request, *args, **kwargs): payload = jwt_payload_handler(request.user) token = jwt_encode_handler(payload) request.user.token = token request.user.save() return redirect('/user') class StripeAccountFromCustomerMixin(object): @property def stripe_account(self): customer = getattr(self, "customer", None) return customer.stripe_account if customer else None @property def stripe_account_stripe_id(self): return self.stripe_account.stripe_id if self.stripe_account else None stripe_account_stripe_id.fget.short_description = "Stripe Account" class ChargeListView(LoginRequiredMixin, CustomerMixin, ListView): model = Charge context_object_name = "charge_list" template_name = "pinax/stripe/charge_list.html" def get_queryset(self): return super(ChargeListView, self).get_queryset().order_by("charge_created") class PurchaseListView(LoginRequiredMixin, ListView): model = Purchase template_name = "pages/articles_list.html" def get_queryset(self): return Purchase.objects.filter(buyer=self.request.user)

39.507853

111

0.658362

6,326

0.838325

0

278

0.036841

0

781

0.103499

a9a1965586fb4160c10932687996645bcd809a1c

1,843

py

Python

interviewbit/Programming/Arrays/Rotate Matrix/solution.py

pablotrinidad/competitive-programming

de16d007ca276330cd0a92bd5b75ce4e9e75fb59

[ "MIT" ]

null

interviewbit/Programming/Arrays/Rotate Matrix/solution.py

pablotrinidad/competitive-programming

de16d007ca276330cd0a92bd5b75ce4e9e75fb59

[ "MIT" ]

null

interviewbit/Programming/Arrays/Rotate Matrix/solution.py

pablotrinidad/competitive-programming

de16d007ca276330cd0a92bd5b75ce4e9e75fb59

[ "MIT" ]

null

"""InterviewBit. Programming > Arrays > Rotate Matrix. """ class Solution: """Solution.""" def rotate(self, A): """Rotate matrix.""" n = len(A) for l in range(0, n // 2): # l = level for o in range(0, n - (l * 2) - 1): # o = offset tlr, tlc = l, l + o # Top Left row/column trr, trc = l + o, n - 1 - l # Top Right row/column brr, brc = n - 1 - l, n - 1 - l - o # Bottom right row/column blr, blc = n - 1 - l - o, l # Bottom left row/column # Switch corner values A[tlr][tlc], A[trr][trc], A[brr][brc], A[blr][blc] = A[blr][blc], A[tlr][tlc], A[trr][trc], A[brr][brc] return A matrices = [ [ [1] ], [ [1, 2], [3, 4] ], [ [1, 2, 3], [4, 5, 6], [7, 8, 9] ], [ ['a', 'b', 'c', 'd'], ['e', 'f', 'g', 'h'], ['i', 'j', 'k', 'l'], ['m', 'n', 'o', 'p'], ], [ [str(x).zfill(2) for x in range(1, 6)], [str(x).zfill(2) for x in range(6, 11)], [str(x).zfill(2) for x in range(11, 16)], [str(x).zfill(2) for x in range(16, 21)], [str(x).zfill(2) for x in range(21, 26)] ], [ [str(x).zfill(2) for x in range(1, 7)], [str(x).zfill(2) for x in range(7, 13)], [str(x).zfill(2) for x in range(13, 19)], [str(x).zfill(2) for x in range(19, 25)], [str(x).zfill(2) for x in range(25, 31)], [str(x).zfill(2) for x in range(31, 37)] ] ] solution = Solution() for matrix in matrices: print("Matrix before rotation:") for row in matrix: print('\t', row) print("Matrix after rotation:") for row in solution.rotate(matrix): print('\t', row) print('\n' * 3)

26.328571

119

0.429192

672

0.364623

0

340

0.184482

a9a1ee58b00c556118c2fed52b5d79faa8995835

2,334

py

Python

integration-tests/src/test/resources/model-in-image/scripts/verify-jdbc-resource.py

tanmaygarg-oracle/weblogic-kubernetes-operator

2920cf3d9ba5c63ef1af6d9e4a574995286f524e

[ "UPL-1.0", "MIT" ]

null

integration-tests/src/test/resources/model-in-image/scripts/verify-jdbc-resource.py

tanmaygarg-oracle/weblogic-kubernetes-operator

2920cf3d9ba5c63ef1af6d9e4a574995286f524e

[ "UPL-1.0", "MIT" ]

null

integration-tests/src/test/resources/model-in-image/scripts/verify-jdbc-resource.py

tanmaygarg-oracle/weblogic-kubernetes-operator

2920cf3d9ba5c63ef1af6d9e4a574995286f524e

[ "UPL-1.0", "MIT" ]

null

# Copyright (c) 2019, 2020, Oracle Corporation and/or its affiliates. # Licensed under the Universal Permissive License v 1.0 as shown at https://oss.oracle.com/licenses/upl. connect('weblogic', 'welcome1', 't3://DOMAINNAME-admin-server:7001') # get all JDBC Properties dsCounter = 0 allJDBCResources = cmo.getJDBCSystemResources() for jdbcResource in allJDBCResources: dsCounter = dsCounter + 1 dsname = jdbcResource.getName() dsResource = jdbcResource.getJDBCResource() dsJNDIname = dsResource.getJDBCDataSourceParams().getJNDINames()#[0] dsDriver = dsResource.getJDBCDriverParams().getDriverName() conn = dsResource.getJDBCDriverParams().getUrl() dsInitialCap = dsResource.getJDBCConnectionPoolParams().getInitialCapacity() dsMaxCap = dsResource.getJDBCConnectionPoolParams().getMaxCapacity() dsParams = dsResource.getJDBCDataSourceParams() dsProps = dsResource.getJDBCDriverParams().getProperties() dsParams = dsResource.getJDBCConnectionPoolParams() user = get("/JDBCSystemResources/"+ dsname +"/Resource/" + dsname + "/JDBCDriverParams/" + dsname + "/Properties/" + dsname + "/Properties/user/Value") readTimeOut = get("/JDBCSystemResources/"+ dsname +"/Resource/" + dsname + "/JDBCDriverParams/" + dsname + "/Properties/" + dsname + "/Properties/oracle.jdbc.ReadTimeout/Value") connTimeOut = get("/JDBCSystemResources/"+ dsname +"/Resource/" + dsname + "/JDBCDriverParams/" + dsname + "/Properties/" + dsname + "/Properties/oracle.net.CONNECT_TIMEOUT/Value") print 'datasource.name.' + str(dsCounter) +'=' + str(dsname) print 'datasource.jndiname.' + str(dsCounter) + '=' + str(dsJNDIname) print 'datasource.driver.class.' + str(dsCounter) + '=' + dsDriver print 'datasource.url.' + str(dsCounter) + '=' + conn print 'datasource.initialCapacity.' + str(dsCounter) + '=' + str(dsInitialCap) print 'datasource.maxCapacity.' + str(dsCounter) + '=' + str(dsMaxCap) print 'datasource.readTimeout.' + str(dsCounter) + '=' + readTimeOut print 'datasource.connectionTimeout.' + str(dsCounter) + '=' + connTimeOut print 'datasource.username.' + str(dsCounter) + '=' + str(user) print 'datasource.dsProps.' + str(dsCounter) + '=' + str(dsProps) print 'datasource.dsParams.' + str(dsCounter) + '=' + str(dsParams) disconnect() exit()

61.421053

184

0.711225

0

868

0.371894

a9a32c0822386523441969c6648b6dd0e0b1aae2

682

py

Python

Projeto_2/no.py

claudiodacruz/Projetos-ED

4495ed792be77f988b12c63f356f68ca709005fe

[ "MIT" ]

null

Projeto_2/no.py

claudiodacruz/Projetos-ED

4495ed792be77f988b12c63f356f68ca709005fe

[ "MIT" ]

null

Projeto_2/no.py

claudiodacruz/Projetos-ED

4495ed792be77f988b12c63f356f68ca709005fe

[ "MIT" ]

null

class No: def __init__(self, dado): self._dado = dado self._direita = None self._esquerda = None self._pai = None def get_dado(self): return self._dado def get_direita(self): return self._direita def get_esquerda(self): return self._esquerda def get_pai(self): return self._pai def set_dado(self, novoDado): self._dado = novoDado def set_direita(self, setarDireita): self._direita = setarDireita def set_esquerda(self, setarEsquerda): self._esquerda = setarEsquerda def set_pai(self, novoPai): self._pai = novoPai

22

42

0.592375

681

0.998534

0

a9a3856b6e71069b01f3d5066c6f323c68f21ce5

1,283

py

Python

tests/dao_tests/test_stored_sample_dao.py

all-of-us/raw-data-repository

d28ad957557587b03ff9c63d55dd55e0508f91d8

[ "BSD-3-Clause" ]

39

2017-10-13T19:16:27.000Z

2021-09-24T16:58:21.000Z

tests/test_stored_sample_dao.py

all-of-us/raw-data-repository

d28ad957557587b03ff9c63d55dd55e0508f91d8

[ "BSD-3-Clause" ]

312

2017-09-08T15:42:13.000Z

2022-03-23T18:21:40.000Z

tests/test_stored_sample_dao.py

all-of-us/raw-data-repository

d28ad957557587b03ff9c63d55dd55e0508f91d8

[ "BSD-3-Clause" ]

19

2017-09-15T13:58:00.000Z

2022-02-07T18:33:20.000Z

from rdr_service import clock from rdr_service.dao.biobank_stored_sample_dao import BiobankStoredSampleDao from rdr_service.dao.participant_dao import ParticipantDao from rdr_service.model.biobank_stored_sample import BiobankStoredSample from rdr_service.model.participant import Participant from tests.helpers.unittest_base import BaseTestCase class BiobankStoredSampleDaoTest(BaseTestCase): """Tests only that a sample can be written and read; see the reconciliation pipeline.""" def setUp(self): super().setUp() self.participant = Participant(participantId=123, biobankId=555) ParticipantDao().insert(self.participant) self.dao = BiobankStoredSampleDao() def test_insert_and_read_sample(self): sample_id = "WEB123456" test_code = "1U234" now = clock.CLOCK.now() created = self.dao.insert( BiobankStoredSample( biobankStoredSampleId=sample_id, biobankId=self.participant.biobankId, biobankOrderIdentifier="KIT", test=test_code, confirmed=now, ) ) fetched = self.dao.get(sample_id) self.assertEqual(test_code, created.test) self.assertEqual(test_code, fetched.test)

37.735294

92

0.694466

935

0.728761

0

111

0.086516

a9a3934109af932f3d04644fe8eb5b82a3bf255d

2,769

py

Python

server/pantryflask/__init__.py

jernaumorat/IntelligentPantry

33d1ee867a5b6e0169fb44918069fbec5bfde259

[ "MIT" ]

null

server/pantryflask/__init__.py

jernaumorat/IntelligentPantry

33d1ee867a5b6e0169fb44918069fbec5bfde259

[ "MIT" ]

null

server/pantryflask/__init__.py

jernaumorat/IntelligentPantry

33d1ee867a5b6e0169fb44918069fbec5bfde259

[ "MIT" ]

1

2021-11-11T09:25:34.000Z

import socket, os, atexit from flask import Flask, jsonify, request from flask_sqlalchemy import SQLAlchemy from flask_migrate import Migrate from flask.helpers import send_from_directory, url_for from zeroconf import ServiceInfo, Zeroconf from pantryflask.config import FlaskConfig from pantryflask.auth import token_auth, generate_pairing_code, generate_user_token from pantryflask.models import AuthToken from pantryflask.db import db from pantryflask.pantry_api import bp as pantry_bp from pantryflask.robot_api import bp as robot_bp from pantryflask.util import bp as util_bp ip = os.environ.get('LISTEN_IP') httpZconf = ServiceInfo( "_http._tcp.local.", "intpantry._http._tcp.local.", addresses=[socket.inet_aton(ip)], port=5000) httpsZconf = ServiceInfo( "_https._tcp.local.", "intpantry._https._tcp.local.", addresses=[socket.inet_aton(ip)], port=5443) zc = Zeroconf() zc.register_service(httpZconf) print('Service Registered:', httpZconf) def app_factory(config={}): app = Flask(__name__) app.config.from_object(FlaskConfig) if config == {} else app.config.from_object(config) db.init_app(app) migrate = Migrate(app, db) @app.route('/') def get_root(): links = [] for rule in app.url_map.iter_rules(): methods = ','.join(rule.methods) links.append((f'{rule}', methods, rule.endpoint)) return jsonify(links) @app.route('/cert', methods=['GET']) def get_cert(): response = send_from_directory(os.path.join('.', 'static'), 'ssr.crt') return response @app.route('/pair', methods=['GET']) def pair_device(): code = request.args.get('code') if len(AuthToken.query.filter_by(token_class='user').all()) == 0 and not code: return jsonify(generate_pairing_code()) token = generate_user_token(code) if token == None: return jsonify(None), 401 return jsonify(token), 201 @app.route('/pair', methods=['POST']) @token_auth.login_required(role=['user']) def get_pairing_code(): return jsonify(generate_pairing_code()) @app.route('/pair', methods=['DELETE']) @token_auth.login_required(role=['user']) def delete_token(): token = request.headers.get('Authorization') print(token) token = token.split(' ')[1] db.session.delete(AuthToken.query.get(token)) db.session.commit() return jsonify('OK') app.register_blueprint(pantry_bp) app.register_blueprint(robot_bp) app.register_blueprint(util_bp) return app, db, migrate @atexit.register def shutdown(): zc.unregister_all_services() app, db, migrate = app_factory()

29.457447

91

0.669195

0

1,340

0.483929

0

263

0.09498

8d10162b60dc80362847021a74c900fd613e0ff7

39,370

py

Python

lingua_franca/lang/parse_eu.py

OpenVoiceOS/ovos-lingua-franca

392cc37cbfde3b8d6f11258c1e148e63ba2fb951

[ "Apache-2.0" ]

null

lingua_franca/lang/parse_eu.py

OpenVoiceOS/ovos-lingua-franca

392cc37cbfde3b8d6f11258c1e148e63ba2fb951

[ "Apache-2.0" ]

13

2022-01-26T03:43:46.000Z

2022-03-25T17:00:18.000Z

lingua_franca/lang/parse_eu.py

OpenVoiceOS/ovos-lingua-franca

392cc37cbfde3b8d6f11258c1e148e63ba2fb951

[ "Apache-2.0" ]

1

2022-01-18T21:11:44.000Z

# # Copyright 2017 Mycroft AI Inc. # # 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. # """ Parse functions for Basque (eu) TODO: numbers greater than 999999 """ from datetime import datetime from dateutil.relativedelta import relativedelta from dateutil.tz import gettz from lingua_franca.lang.format_eu import pronounce_number_eu from lingua_franca.lang.parse_common import * from lingua_franca.lang.common_data_eu import _NUM_STRING_EU def isFractional_eu(input_str): """ This function takes the given text and checks if it is a fraction. Args: text (str): the string to check if fractional Returns: (bool) or (float): False if not a fraction, otherwise the fraction """ if input_str.endswith('s', -1): input_str = input_str[:len(input_str) - 1] # e.g. "fifths" aFrac = {"erdia": 2, "erdi": 2, "heren": 3, "laurden": 4, "laurdena": 4, "bosten": 5, "bostena": 5, "seiren": 6, "seirena": 6, "zazpiren": 7, "zapirena": 7, "zortziren": 8, "zortzirena": 8, "bederatziren": 9, "bederatzirena": 9, "hamarren": 10, "hamarrena": 10, "hamaikaren": 11, "hamaikarena": 11, "hamabiren": 12, "hamabirena": 12} if input_str.lower() in aFrac: return 1.0 / aFrac[input_str] if (input_str == "hogeiren" or input_str == "hogeirena"): return 1.0 / 20 if (input_str == "hogeita hamarren" or input_str == "hogeita hamarrena"): return 1.0 / 30 if (input_str == "ehunen" or input_str == "ehunena"): return 1.0 / 100 if (input_str == "milaren" or input_str == "milarena"): return 1.0 / 1000 return False # TODO: short_scale and ordinals don't do anything here. # The parameters are present in the function signature for API compatibility # reasons. # # Returns incorrect output on certain fractional phrases like, "cuarto de dos" def extract_number_eu(text, short_scale=True, ordinals=False): """ This function prepares the given text for parsing by making numbers consistent, getting rid of contractions, etc. Args: text (str): the string to normalize Returns: (int) or (float): The value of extracted number """ aWords = text.lower().split() count = 0 result = None while count < len(aWords): val = 0 word = aWords[count] next_next_word = None if count + 1 < len(aWords): next_word = aWords[count + 1] if count + 2 < len(aWords): next_next_word = aWords[count + 2] else: next_word = None # is current word a number? if word in _NUM_STRING_EU: val = _NUM_STRING_EU[word] elif word.isdigit(): # doesn't work with decimals val = int(word) elif is_numeric(word): val = float(word) elif isFractional_eu(word): if next_word in _NUM_STRING_EU: # erdi bat, heren bat, etab result = _NUM_STRING_EU[next_word] # hurrengo hitza (bat, bi, ...) salto egin next_word = None count += 2 elif not result: result = 1 count += 1 result = result * isFractional_eu(word) continue if not val: # look for fractions like "2/3" aPieces = word.split('/') # if (len(aPieces) == 2 and is_numeric(aPieces[0]) # and is_numeric(aPieces[1])): if look_for_fractions(aPieces): val = float(aPieces[0]) / float(aPieces[1]) if val: if result is None: result = 0 # handle fractions if next_word == "en" or next_word == "ren": result = float(result) / float(val) else: result = val if next_word is None: break # number word and fraction ands = ["eta"] if next_word in ands: zeros = 0 if result is None: count += 1 continue newWords = aWords[count + 2:] newText = "" for word in newWords: newText += word + " " afterAndVal = extract_number_eu(newText[:-1]) if afterAndVal: if result < afterAndVal or result < 20: while afterAndVal > 1: afterAndVal = afterAndVal / 10.0 for word in newWords: if word == "zero" or word == "0": zeros += 1 else: break for _ in range(0, zeros): afterAndVal = afterAndVal / 10.0 result += afterAndVal break elif next_next_word is not None: if next_next_word in ands: newWords = aWords[count + 3:] newText = "" for word in newWords: newText += word + " " afterAndVal = extract_number_eu(newText[:-1]) if afterAndVal: if result is None: result = 0 result += afterAndVal break decimals = ["puntu", "koma", ".", ","] if next_word in decimals: zeros = 0 newWords = aWords[count + 2:] newText = "" for word in newWords: newText += word + " " for word in newWords: if word == "zero" or word == "0": zeros += 1 else: break afterDotVal = str(extract_number_eu(newText[:-1])) afterDotVal = zeros * "0" + afterDotVal result = float(str(result) + "." + afterDotVal) break count += 1 # Return the $str with the number related words removed # (now empty strings, so strlen == 0) # aWords = [word for word in aWords if len(word) > 0] # text = ' '.join(aWords) if "." in str(result): integer, dec = str(result).split(".") # cast float to int if dec == "0": result = int(integer) return result or False # TODO Not parsing 'cero' def eu_number_parse(words, i): def eu_cte(i, s): if i < len(words) and s == words[i]: return s, i + 1 return None def eu_number_word(i, mi, ma): if i < len(words): v = _NUM_STRING_EU.get(words[i]) if v and v >= mi and v <= ma: return v, i + 1 return None def eu_number_1_99(i): if i >= len(words): return None r1 = eu_number_word(i, 1, 29) if r1: return r1 composed = False if words[i] != "eta" and words[i][-2:] == "ta": composed = True words[i] = words[i][:-2] r1 = eu_number_word(i, 20, 90) if r1: v1, i1 = r1 if composed: # i2 = r2[1] r3 = eu_number_word(i1, 1, 19) if r3: v3, i3 = r3 return v1 + v3, i3 return r1 return None def eu_number_1_999(i): r1 = eu_number_word(i, 100, 900) if r1: v1, i1 = r1 r2 = eu_cte(i1, "eta") if r2: i2 = r2[1] r3 = eu_number_1_99(i2) if r3: v3, i3 = r3 return v1 + v3, i3 else: return r1 # [1-99] r1 = eu_number_1_99(i) if r1: return r1 return None def eu_number(i): # check for cero r1 = eu_number_word(i, 0, 0) if r1: return r1 # check for [1-999] (mil [0-999])? r1 = eu_number_1_999(i) if r1: v1, i1 = r1 r2 = eu_cte(i1, "mila") if r2: i2 = r2[1] r3 = eu_number_1_999(i2) if r3: v3, i3 = r3 return v1 * 1000 + v3, i3 else: return v1 * 1000, i2 else: return r1 return None return eu_number(i) def extract_numbers_eu(text, short_scale=True, ordinals=False): """ Takes in a string and extracts a list of numbers. Args: text (str): the string to extract a number from short_scale (bool): Use "short scale" or "long scale" for large numbers -- over a million. The default is short scale, which is now common in most English speaking countries. See https://en.wikipedia.org/wiki/Names_of_large_numbers ordinals (bool): consider ordinal numbers, e.g. third=3 instead of 1/3 Returns: list: list of extracted numbers as floats """ return extract_numbers_generic(text, pronounce_number_eu, extract_number_eu, short_scale=short_scale, ordinals=ordinals) def normalize_eu(text, remove_articles=True): """ Basque string normalization """ words = text.split() # this also removed extra spaces normalized = "" i = 0 while i < len(words): word = words[i] # Convert numbers into digits r = eu_number_parse(words, i) if r: v, i = r normalized += " " + str(v) continue normalized += " " + word i += 1 return normalized[1:] # strip the initial space return text # TODO MycroftAI/mycroft-core#2348 def extract_datetime_eu(input_str, anchorDate=None, default_time=None): def clean_string(s): # cleans the input string of unneeded punctuation and capitalization # among other things symbols = [".", ",", ";", "?", "!", "."] # noise_words = ["entre", "la", "del", "al", "el", "de", # "para", "una", "cualquier", "a", # "e'", "esta", "este"] # TODO noise_words = ["artean", "tartean", "edozein", "hau", "hontan", "honetan", "para", "una", "cualquier", "a", "e'", "esta", "este"] for word in symbols: s = s.replace(word, "") for word in noise_words: s = s.replace(" " + word + " ", " ") s = s.lower().replace( "-", " ").replace( "_", "") # handle synonyms and equivalents, "tomorrow early = tomorrow morning synonyms = {"goiza": ["egunsentia", "goiz", "oso goiz"], "arratsaldea": ["arratsa", "bazkalostea", "arratsalde", "arrats"], "gaua": ["iluntzea", "berandu", "gau", "gaba"]} for syn in synonyms: for word in synonyms[syn]: s = s.replace(" " + word + " ", " " + syn + " ") # relevant plurals wordlist = ["goizak", "arratsaldeak", "gauak", "egunak", "asteak", "urteak", "minutuak", "segunduak", "hurrengoak", "datozenak", "orduak", "hilabeteak"] for _, word in enumerate(wordlist): s = s.replace(word, word.rstrip('ak')) # s = s.replace("meses", "mes").replace("anteriores", "anterior") return s def date_found(): return found or \ ( datestr != "" or yearOffset != 0 or monthOffset != 0 or dayOffset is True or hrOffset != 0 or hrAbs or minOffset != 0 or minAbs or secOffset != 0 ) if input_str == "": return None if anchorDate is None: anchorDate = datetime.now() found = False daySpecified = False dayOffset = False monthOffset = 0 yearOffset = 0 dateNow = anchorDate today = dateNow.strftime("%w") currentYear = dateNow.strftime("%Y") fromFlag = False datestr = "" hasYear = False timeQualifier = "" words = clean_string(input_str).split(" ") timeQualifiersList = ['goiza', 'arratsaldea', 'gaua'] time_indicators = ["en", "la", "al", "por", "pasados", "pasadas", "día", "hora"] days = ['astelehena', 'asteartea', 'asteazkena', 'osteguna', 'ostirala', 'larunbata', 'igandea'] months = ['urtarrila', 'otsaila', 'martxoa', 'apirila', 'maiatza', 'ekaina', 'uztaila', 'abuztua', 'iraila', 'urria', 'azaroa', 'abendua'] monthsShort = ['urt', 'ots', 'mar', 'api', 'mai', 'eka', 'uzt', 'abu', 'ira', 'urr', 'aza', 'abe'] nexts = ["hurrengo", "datorren", "ondorengo"] suffix_nexts = ["barru"] lasts = ["azken", "duela"] suffix_lasts = ["aurreko"] nxts = ["ondorengo", "hurrengo", "datorren"] prevs = ["aurreko", "duela", "previo", "anterior"] # TODO froms = ["desde", "en", "para", "después de", "por", "próximo", "próxima", "de"] thises = ["hau"] froms += thises lists = nxts + prevs + froms + time_indicators for idx, word in enumerate(words): if word == "": continue wordPrevPrev = words[idx - 2] if idx > 1 else "" wordPrev = words[idx - 1] if idx > 0 else "" wordNext = words[idx + 1] if idx + 1 < len(words) else "" wordNextNext = words[idx + 2] if idx + 2 < len(words) else "" wordNextNextNext = words[idx + 3] if idx + 3 < len(words) else "" start = idx used = 0 # save timequalifier for later if word in timeQualifiersList: timeQualifier = word # parse today, tomorrow, yesterday elif (word == "gaur" or word == "gaurko") and not fromFlag: dayOffset = 0 used += 1 elif (word == "bihar" or word == "biharko") and not fromFlag: dayOffset = 1 used += 1 elif (word == "atzo" or word == "atzoko") and not fromFlag: dayOffset -= 1 used += 1 # before yesterday elif (word == "herenegun" or word == "herenegungo") and not fromFlag: dayOffset -= 2 used += 1 # if wordNext == "ayer": # used += 1 # elif word == "ante" and wordNext == "ante" and wordNextNext == \ # "ayer" and not fromFlag: # dayOffset -= 3 # used += 3 # elif word == "ante anteayer" and not fromFlag: # dayOffset -= 3 # used += 1 # day after tomorrow elif (word == "etzi" or word == "etziko") and not fromFlag: dayOffset += 2 used = 1 elif (word == "etzidamu" or word == "etzidamuko") and not fromFlag: dayOffset += 3 used = 1 # parse 5 days, 10 weeks, last week, next week, week after elif word == "egun" or word == "eguna" or word == "eguneko": if wordPrevPrev and wordPrevPrev == "duela": used += 1 if wordPrev and wordPrev[0].isdigit(): dayOffset -= int(wordPrev) start -= 1 used += 1 elif (wordPrev and wordPrev[0].isdigit() and wordNext not in months and wordNext not in monthsShort): dayOffset += int(wordPrev) start -= 1 used += 2 elif wordNext and wordNext[0].isdigit() and wordNextNext not in \ months and wordNextNext not in monthsShort: dayOffset += int(wordNext) start -= 1 used += 2 elif word == "aste" or word == "astea" or word == "asteko" and not fromFlag: if wordPrev[0].isdigit(): dayOffset += int(wordPrev) * 7 start -= 1 used = 2 for w in nexts: if wordPrev == w: dayOffset = 7 start -= 1 used = 2 for w in lasts: if wordPrev == w: dayOffset = -7 start -= 1 used = 2 for w in suffix_nexts: if wordNext == w: dayOffset = 7 start -= 1 used = 2 for w in suffix_lasts: if wordNext == w: dayOffset = -7 start -= 1 used = 2 # parse 10 months, next month, last month elif word == "hilabete" or word == "hilabetea" or word == "hilabeteko" and not fromFlag: if wordPrev[0].isdigit(): monthOffset = int(wordPrev) start -= 1 used = 2 for w in nexts: if wordPrev == w: monthOffset = 7 start -= 1 used = 2 for w in lasts: if wordPrev == w: monthOffset = -7 start -= 1 used = 2 for w in suffix_nexts: if wordNext == w: monthOffset = 7 start -= 1 used = 2 for w in suffix_lasts: if wordNext == w: monthOffset = -7 start -= 1 used = 2 # parse 5 years, next year, last year elif word == "urte" or word == "urtea" or word == "urteko" and not fromFlag: if wordPrev[0].isdigit(): yearOffset = int(wordPrev) start -= 1 used = 2 for w in nexts: if wordPrev == w: yearOffset = 1 start -= 1 used = 2 for w in lasts: if wordPrev == w: yearOffset = -1 start -= 1 used = 2 for w in suffix_nexts: if wordNext == w: yearOffset = 1 start -= 1 used = 2 for w in suffix_lasts: if wordNext == w: yearOffset = -1 start -= 1 used = 2 # parse Monday, Tuesday, etc., and next Monday, # last Tuesday, etc. elif word in days and not fromFlag: d = days.index(word) dayOffset = (d + 1) - int(today) used = 1 if dayOffset < 0: dayOffset += 7 if wordPrev == "hurrengo": dayOffset += 7 used += 1 start -= 1 elif wordPrev == "aurreko": dayOffset -= 7 used += 1 start -= 1 if wordNext == "hurrengo": # dayOffset += 7 used += 1 elif wordNext == "aurreko": # dayOffset -= 7 used += 1 # parse 15 of July, June 20th, Feb 18, 19 of February elif word in months or word in monthsShort: try: m = months.index(word) except ValueError: m = monthsShort.index(word) used += 1 datestr = months[m] if wordPrev and wordPrev[0].isdigit(): # 13 mayo datestr += " " + wordPrev start -= 1 used += 1 if wordNext and wordNext[0].isdigit(): datestr += " " + wordNext used += 1 hasYear = True else: hasYear = False elif wordNext and wordNext[0].isdigit(): # mayo 13 datestr += " " + wordNext used += 1 if wordNextNext and wordNextNext[0].isdigit(): datestr += " " + wordNextNext used += 1 hasYear = True else: hasYear = False elif wordPrevPrev and wordPrevPrev[0].isdigit(): # 13 dia mayo datestr += " " + wordPrevPrev start -= 2 used += 2 if wordNext and word[0].isdigit(): datestr += " " + wordNext used += 1 hasYear = True else: hasYear = False elif wordNextNext and wordNextNext[0].isdigit(): # mayo dia 13 datestr += " " + wordNextNext used += 2 if wordNextNextNext and wordNextNextNext[0].isdigit(): datestr += " " + wordNextNextNext used += 1 hasYear = True else: hasYear = False if datestr in months: datestr = "" # parse 5 days from tomorrow, 10 weeks from next thursday, # 2 months from July validFollowups = days + months + monthsShort validFollowups.append("gaur") validFollowups.append("bihar") validFollowups.append("atzo") # validFollowups.append("atzoko") validFollowups.append("herenegun") validFollowups.append("orain") validFollowups.append("oraintxe") # validFollowups.append("ante") # TODO if word in froms and wordNext in validFollowups: if not (word == "bihar" or word == "herenegun" or word == "atzo"): used = 1 fromFlag = True if wordNext == "bihar": dayOffset += 1 elif wordNext == "atzo" or wordNext == "atzoko": dayOffset -= 1 elif wordNext == "herenegun": dayOffset -= 2 # elif (wordNext == "ante" and wordNext == "ante" and # wordNextNextNext == "ayer"): # dayOffset -= 3 elif wordNext in days: d = days.index(wordNext) tmpOffset = (d + 1) - int(today) used = 2 # if wordNextNext == "feira": # used += 1 if tmpOffset < 0: tmpOffset += 7 if wordNextNext: if wordNextNext in nxts: tmpOffset += 7 used += 1 elif wordNextNext in prevs: tmpOffset -= 7 used += 1 dayOffset += tmpOffset elif wordNextNext and wordNextNext in days: d = days.index(wordNextNext) tmpOffset = (d + 1) - int(today) used = 3 if wordNextNextNext: if wordNextNextNext in nxts: tmpOffset += 7 used += 1 elif wordNextNextNext in prevs: tmpOffset -= 7 used += 1 dayOffset += tmpOffset # if wordNextNextNext == "feira": # used += 1 if wordNext in months: used -= 1 if used > 0: if start - 1 > 0 and words[start - 1] in lists: start -= 1 used += 1 for i in range(0, used): words[i + start] = "" if start - 1 >= 0 and words[start - 1] in lists: words[start - 1] = "" found = True daySpecified = True # parse time hrOffset = 0 minOffset = 0 secOffset = 0 hrAbs = None minAbs = None for idx, word in enumerate(words): if word == "": continue wordPrevPrev = words[idx - 2] if idx > 1 else "" wordPrev = words[idx - 1] if idx > 0 else "" wordNext = words[idx + 1] if idx + 1 < len(words) else "" wordNextNext = words[idx + 2] if idx + 2 < len(words) else "" wordNextNextNext = words[idx + 3] if idx + 3 < len(words) else "" # parse noon, midnight, morning, afternoon, evening used = 0 if word == "eguerdi" or word == "eguerdia" or word == "eguerdian": hrAbs = 12 used += 2 elif word == "gauerdi" or word == "gauerdia" or word == "gauerdian": hrAbs = 0 used += 2 elif word == "goiza": if not hrAbs: hrAbs = 8 used += 1 elif word == "arratsaldea" or word == "arratsa" or word == "arratsean" or word == "arratsaldean": if not hrAbs: hrAbs = 15 used += 1 # TODO # elif word == "media" and wordNext == "tarde": # if not hrAbs: # hrAbs = 17 # used += 2 elif word == "iluntze" or word == "iluntzea" or word == "iluntzean": if not hrAbs: hrAbs = 20 used += 2 # TODO # elif word == "media" and wordNext == "mañana": # if not hrAbs: # hrAbs = 10 # used += 2 # elif word == "fim" and wordNext == "tarde": # if not hrAbs: # hrAbs = 19 # used += 2 elif word == "egunsentia" or word == "egunsentian" or word == "egunsenti": if not hrAbs: hrAbs = 6 used += 1 # elif word == "madrugada": # if not hrAbs: # hrAbs = 1 # used += 2 elif word == "gaua" or word == "gauean" or word == "gau": if not hrAbs: hrAbs = 21 used += 1 # parse half an hour, quarter hour # TODO elif (word == "hora" and (wordPrev in time_indicators or wordPrevPrev in time_indicators)): if wordPrev == "media": minOffset = 30 elif wordPrev == "cuarto": minOffset = 15 elif wordPrevPrev == "cuarto": minOffset = 15 if idx > 2 and words[idx - 3] in time_indicators: words[idx - 3] = "" words[idx - 2] = "" else: hrOffset = 1 if wordPrevPrev in time_indicators: words[idx - 2] = "" words[idx - 1] = "" used += 1 hrAbs = -1 minAbs = -1 # parse 5:00 am, 12:00 p.m., etc elif word[0].isdigit(): isTime = True strHH = "" strMM = "" remainder = "" if ':' in word: # parse colons # "3:00 in the morning" stage = 0 length = len(word) for i in range(length): if stage == 0: if word[i].isdigit(): strHH += word[i] elif word[i] == ":": stage = 1 else: stage = 2 i -= 1 elif stage == 1: if word[i].isdigit(): strMM += word[i] else: stage = 2 i -= 1 elif stage == 2: remainder = word[i:].replace(".", "") break if remainder == "": nextWord = wordNext.replace(".", "") if nextWord == "am" or nextWord == "pm": remainder = nextWord used += 1 elif wordNext == "goiza" or wordNext == "egunsentia" or wordNext == "goizeko" or wordNext == "egunsentiko": remainder = "am" used += 1 elif wordPrev == "arratsaldeko" or wordPrev == "arratsaldea" or wordPrev == "arratsaldean": remainder = "pm" used += 1 elif wordNext == "gaua" or wordNext == "gauean" or wordNext == "gaueko": if 0 < int(word[0]) < 6: remainder = "am" else: remainder = "pm" used += 1 elif wordNext in thises and (wordNextNext == "goiza" or wordNextNext == "goizean" or wordNextNext == "goizeko"): remainder = "am" used = 2 elif wordNext in thises and \ (wordNextNext == "arratsaldea" or wordNextNext == "arratsaldean" or wordNextNext == "arratsaldeko"): remainder = "pm" used = 2 elif wordNext in thises and (wordNextNext == "gaua" or wordNextNext == "gauean" or wordNextNext == "gaueko"): remainder = "pm" used = 2 else: if timeQualifier != "": if strHH <= 12 and \ (timeQualifier == "goiza" or timeQualifier == "arratsaldea"): strHH += 12 else: # try to parse # s without colons # 5 hours, 10 minutes etc. length = len(word) strNum = "" remainder = "" for i in range(length): if word[i].isdigit(): strNum += word[i] else: remainder += word[i] if remainder == "": remainder = wordNext.replace(".", "").lstrip().rstrip() if ( remainder == "pm" or wordNext == "pm" or remainder == "p.m." or wordNext == "p.m."): strHH = strNum remainder = "pm" used = 1 elif ( remainder == "am" or wordNext == "am" or remainder == "a.m." or wordNext == "a.m."): strHH = strNum remainder = "am" used = 1 else: if (wordNext == "pm" or wordNext == "p.m." or wordPrev == "arratsaldeko"): strHH = strNum remainder = "pm" used = 0 elif (wordNext == "am" or wordNext == "a.m." or wordPrev == "goizeko"): strHH = strNum remainder = "am" used = 0 elif (int(word) > 100 and ( # wordPrev == "o" or # wordPrev == "oh" or wordPrev == "zero" )): # 0800 hours (pronounced oh-eight-hundred) strHH = int(word) / 100 strMM = int(word) - strHH * 100 if wordNext == "orduak": used += 1 elif ( wordNext == "orduak" and word[0] != '0' and ( int(word) < 100 and int(word) > 2400 )): # ignores military time # "in 3 hours" hrOffset = int(word) used = 2 isTime = False hrAbs = -1 minAbs = -1 elif wordNext == "minutu": # "in 10 minutes" minOffset = int(word) used = 2 isTime = False hrAbs = -1 minAbs = -1 elif wordNext == "segundu": # in 5 seconds secOffset = int(word) used = 2 isTime = False hrAbs = -1 minAbs = -1 elif int(word) > 100: strHH = int(word) / 100 strMM = int(word) - strHH * 100 if wordNext == "ordu": used += 1 elif wordNext == "" or ( wordNext == "puntuan"): strHH = word strMM = 00 if wordNext == "puntuan": used += 2 if wordNextNextNext == "arratsaldea": remainder = "pm" used += 1 elif wordNextNextNext == "goiza": remainder = "am" used += 1 elif wordNextNextNext == "gaua": if 0 > strHH > 6: remainder = "am" else: remainder = "pm" used += 1 elif wordNext[0].isdigit(): strHH = word strMM = wordNext used += 1 if wordNextNext == "orduak": used += 1 else: isTime = False strHH = int(strHH) if strHH else 0 strMM = int(strMM) if strMM else 0 strHH = strHH + 12 if (remainder == "pm" and 0 < strHH < 12) else strHH strHH = strHH - 12 if (remainder == "am" and 0 < strHH >= 12) else strHH if strHH > 24 or strMM > 59: isTime = False used = 0 if isTime: hrAbs = strHH * 1 minAbs = strMM * 1 used += 1 if used > 0: # removed parsed words from the sentence for i in range(used): words[idx + i] = "" if wordPrev == "puntuan": words[words.index(wordPrev)] = "" if idx > 0 and wordPrev in time_indicators: words[idx - 1] = "" if idx > 1 and wordPrevPrev in time_indicators: words[idx - 2] = "" idx += used - 1 found = True # check that we found a date if not date_found(): return None if dayOffset is False: dayOffset = 0 # perform date manipulation extractedDate = dateNow extractedDate = extractedDate.replace(microsecond=0, second=0, minute=0, hour=0) if datestr != "": en_months = ['january', 'february', 'march', 'april', 'may', 'june', 'july', 'august', 'september', 'october', 'november', 'december'] en_monthsShort = ['jan', 'feb', 'mar', 'apr', 'may', 'june', 'july', 'aug', 'sept', 'oct', 'nov', 'dec'] for idx, en_month in enumerate(en_months): datestr = datestr.replace(months[idx], en_month) for idx, en_month in enumerate(en_monthsShort): datestr = datestr.replace(monthsShort[idx], en_month) temp = datetime.strptime(datestr, "%B %d") temp = temp.replace(tzinfo=None) if not hasYear: temp = temp.replace(year=extractedDate.year, tzinfo=extractedDate.tzinfo) if extractedDate < temp: extractedDate = extractedDate.replace(year=int(currentYear), month=int( temp.strftime( "%m")), day=int(temp.strftime( "%d"))) else: extractedDate = extractedDate.replace( year=int(currentYear) + 1, month=int(temp.strftime("%m")), day=int(temp.strftime("%d"))) else: extractedDate = extractedDate.replace( year=int(temp.strftime("%Y")), month=int(temp.strftime("%m")), day=int(temp.strftime("%d"))) if yearOffset != 0: extractedDate = extractedDate + relativedelta(years=yearOffset) if monthOffset != 0: extractedDate = extractedDate + relativedelta(months=monthOffset) if dayOffset != 0: extractedDate = extractedDate + relativedelta(days=dayOffset) if hrAbs is None and minAbs is None and default_time: hrAbs = default_time.hour minAbs = default_time.minute if hrAbs != -1 and minAbs != -1: extractedDate = extractedDate + relativedelta(hours=hrAbs or 0, minutes=minAbs or 0) if (hrAbs or minAbs) and datestr == "": if not daySpecified and dateNow > extractedDate: extractedDate = extractedDate + relativedelta(days=1) if hrOffset != 0: extractedDate = extractedDate + relativedelta(hours=hrOffset) if minOffset != 0: extractedDate = extractedDate + relativedelta(minutes=minOffset) if secOffset != 0: extractedDate = extractedDate + relativedelta(seconds=secOffset) resultStr = " ".join(words) resultStr = ' '.join(resultStr.split()) # resultStr = pt_pruning(resultStr) return [extractedDate, resultStr] def get_gender_eu(word, raw_string=""): # There is no gender in Basque gender = False return gender

36.218951

132

0.436297

0

7,733

0.196394

8d1326f81b702308f07d05eaa330ea71663f64ad

6,976

py

Python

path-generation/velocity_profile.py

iqzprvagbv/path-planning

c5b1099dbe1aadbd78a1fdb16c0a2f82245c19bc

[ "MIT" ]

null

path-generation/velocity_profile.py

iqzprvagbv/path-planning

c5b1099dbe1aadbd78a1fdb16c0a2f82245c19bc

[ "MIT" ]

1

2021-06-01T21:26:25.000Z

path-generation/velocity_profile.py

iqzprvagbv/path-planning

c5b1099dbe1aadbd78a1fdb16c0a2f82245c19bc

[ "MIT" ]

null

# Defines a velocity profile, which is the big object we've been # working towards. from math import sqrt, ceil import json class PlanningPoint(object): # pylint: disable=too-many-instance-attributes # planning points unfortunately require this much data def __init__(self, position, time, radius, distance, heading): # pylint: disable=bad-whitespace # this next block is unreadable without the spacing self.radius = radius self.heading = heading self.position = position self.distance = distance self.internal_time = time self.total_time = None self.external_time = None self.max_velocity = None self.left_velocity = None self.right_velocity = None self.actual_velocity = None def __str__(self): return ("Planning Point: " + "\n" + "Time: " + str(self.internal_time) + "\n" + "Max Velocity: " + str(self.max_velocity) + "\n" + "Velocity: " + str(self.actual_velocity) + "\n") def compute_max_velocity(self, robot): if self.radius == 0: velocity = robot.max_velocity elif self.radius > 0: velocity = (self.radius*robot.max_velocity)/(self.radius + (robot.width/2.)) else: velocity = (self.radius*robot.max_velocity)/(self.radius - (robot.width/2.)) self.max_velocity = velocity def compute_wheel_velocity(self, robot): if self.actual_velocity is None: velocity = self.max_velocity else: velocity = self.actual_velocity if self.radius == 0: self.right_velocity = velocity self.left_velocity = velocity else: self.right_velocity = velocity/self.radius*(self.radius+robot.width/2) self.left_velocity = velocity/self.radius*(self.radius-robot.width/2) def json_object(self): return {"time": self.external_time, "heading": self.heading, "left velcoity": self.left_velocity, "right velocity": self.right_velocity} class VelocityProfile(object): def __init__(self, path, robot, distance): self.path = path self.robot = robot self.distance = distance self.points = [] self.__init_points() #broken #self.__establish_accel() # Dirty Hack actual_max_accel = self.robot.max_acceleration current_max_accel = float('inf') while current_max_accel > actual_max_accel: print "Ensuring Consitency of Wheels" self.__forward_consistency(0) self.__reverse_consistency(0) self.__establish_timestamps() self.__init_wheels() current_max_accel = self.__get_max_accel() self.robot.max_acceleration = 3./4 * self.robot.max_acceleration def __init_points(self): print "Initializing Planning Points..." last_t = 0 steps = ceil(self.path.total_length/self.distance) step = 1 progress = 0 for t in self.path.planning_times(self.distance): print '\r[{0}{1}] {2}%'.format('#'*int(progress * 30), '-'*(int((1-progress) * 30)), int(progress*100)), radius = self.path.curvature_radius(t) distance = self.path.length(last_t, t) position = self.path.eval(t) heading = self.path.heading(t) point = PlanningPoint(position, t, radius, distance, heading) point.compute_max_velocity(self.robot) point.compute_wheel_velocity(self.robot) self.points.append(point) last_t = t step += 1 progress = step/steps print "Done!" def __forward_consistency(self, initial_velocity): print "Establishing Forward Consistency..." last_velocity = None for point in self.points: if last_velocity is None: point.actual_velocity = min(initial_velocity, point.max_velocity) else: obtainable = sqrt(last_velocity**2+2*self.robot.max_acceleration*point.distance) point.actual_velocity = min(point.max_velocity, obtainable) last_velocity = point.actual_velocity print "Done!" def __reverse_consistency(self, final_velocity): print "Establishing Reverse Consistency..." last_velocity = None last_distance = None for point in reversed(self.points): if last_velocity is None: point.actual_velocity = min(final_velocity, point.actual_velocity) else: obtainable = sqrt(last_velocity**2+2*self.robot.max_acceleration*last_distance) point.actual_velocity = min(point.actual_velocity, obtainable) last_distance = point.distance last_velocity = point.actual_velocity print "Done!" def __establish_timestamps(self): print "Establishing Timestamps..." last_time = None last_velocity = None for point in self.points: if last_time is None: point.external_time = 0 else: dt = (2*point.distance)/(point.actual_velocity + last_velocity) point.external_time = last_time + dt last_time = point.external_time last_velocity = point.actual_velocity self.total_time = last_time print "Done!" def __init_wheels(self): print "Computing Wheel Velocities..." for point in self.points: point.compute_wheel_velocity(self.robot) print "Done!" def __get_max_accel(self): last_point = None max_accel = 0 for point in self.points: if last_point is None: last_point = point else: dt = point.external_time - last_point.external_time left_accel = (abs(point.left_velocity - last_point.left_velocity))/dt right_accel = (abs(point.right_velocity - last_point.right_velocity))/dt max_accel = max(max_accel, left_accel, right_accel) return max_accel class ProfileEncoder(json.JSONEncoder): # pylint: disable=arguments-differ # pylint: disable=method-hidden # This code is copy pasted from the official python docs, I assume it's fine def default(self, obj): if isinstance(obj, VelocityProfile): output = [] for point in obj.points: output.append(point.json_object()) return output # This will throw an error if it's given the wrong type return json.JSONEncoder.default(self, obj)

38.32967

96

0.591886

6,845

0.981221

0

881

0.12629

8d1378b3e67d5a0964ccf48994e4da6105c0ae60

472

py

Python

move_py_files.py

rune-l/coco-annotator

a7ae8004c5e1ca74e5bbc41d09edc5cfab117a14

[ "MIT" ]

null

move_py_files.py

rune-l/coco-annotator

a7ae8004c5e1ca74e5bbc41d09edc5cfab117a14

[ "MIT" ]

null

move_py_files.py

rune-l/coco-annotator

a7ae8004c5e1ca74e5bbc41d09edc5cfab117a14

[ "MIT" ]

null

import os import subprocess test_set_path = '/Users/runelangergaard/Documents/SmartAnnotation/data/test_set' test_imgs = os.listdir(test_set_path) test_imgs cwd_path = '/Users/runelangergaard' os.chdir(cwd_path) for img in test_imgs: full_path = os.path.join(test_set_path, img) subprocess.run([ "scp", "-i", "coco-anno.pem", full_path, "[email protected]:/datasets/tmp" ])

23.6

83

0.684322

0

187

0.396186

8d13e8253f51474a77c77b964813f16a0d1c345f

304

py

Python

examples/apply.py

PictElm/grom

52e28efad1edae447347dd396e80a665c283b05d

[ "Apache-2.0" ]

1

2019-06-29T18:53:31.000Z

examples/apply.py

PictElm/grom

52e28efad1edae447347dd396e80a665c283b05d

[ "Apache-2.0" ]

null

examples/apply.py

PictElm/grom

52e28efad1edae447347dd396e80a665c283b05d

[ "Apache-2.0" ]

null

import random import grom grom.debug(False) dirName = "dump\\" inputName = "example.bmp" outputName = "output.bmp" g = grom.Genome(dirName + inputName, partition=[ ('head', 0x76), ('raw') ]) print(g) print(g.partition) g.apply(lambda x: 255 - x, ['raw']) g(dirName + outputName, pause=False)

16

48

0.661184

0

49

0.161184

8d14a69daed26d53510912624929725162594aec

3,351

py

Python

statefun-sdk-python/statefun/statefun_builder.py

MartijnVisser/flink-statefun

66b2fc5a178d916756428f65a197095fbb43f57d

[ "Apache-2.0" ]

null

statefun-sdk-python/statefun/statefun_builder.py

MartijnVisser/flink-statefun

66b2fc5a178d916756428f65a197095fbb43f57d

[ "Apache-2.0" ]

7

2022-02-24T17:20:28.000Z

2022-03-25T13:18:44.000Z

statefun-sdk-python/statefun/statefun_builder.py

MartijnVisser/flink-statefun

66b2fc5a178d916756428f65a197095fbb43f57d

[ "Apache-2.0" ]

null

################################################################################ # Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you 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 typing from statefun.core import ValueSpec from statefun.context import Context from statefun.messages import Message from statefun.storage import make_address_storage_spec, StorageSpec import inspect class StatefulFunction(object): __slots__ = ("fun", "storage_spec", "is_async") def __init__(self, fun: typing.Callable[[Context, Message], None], specs: StorageSpec, is_async: bool): if fun is None: raise ValueError("function code is missing.") self.fun = fun if specs is None: raise ValueError("storage spec is missing.") self.storage_spec = specs self.is_async = is_async class StatefulFunctions(object): __slots__ = ("_functions",) def __init__(self): self._functions = {} def register(self, typename: str, fun, specs: typing.Optional[typing.List[ValueSpec]] = None): """registers a StatefulFunction function instance, under the given namespace with the given function type. """ if fun is None: raise ValueError("function instance must be provided") if not typename: raise ValueError("function typename must be provided") storage_spec = make_address_storage_spec(specs if specs else []) is_async = inspect.iscoroutinefunction(fun) sig = inspect.getfullargspec(fun) if len(sig.args) != 2: raise ValueError( f"The registered function {typename} does not expect a context and a message but rather {sig.args}.") self._functions[typename] = StatefulFunction(fun=fun, specs=storage_spec, is_async=is_async) def bind(self, typename, specs: typing.List[ValueSpec] = None): """wraps a StatefulFunction instance with a given namespace and type. for example: s = StatefulFunctions() @s.define("com.foo.bar/greeter") def greeter(context, message): print("Hi there") This would add an invokable stateful function that can accept messages sent to "com.foo.bar/greeter". """ def wrapper(function): self.register(typename, function, specs) return function return wrapper def for_typename(self, typename: str) -> StatefulFunction: return self._functions[typename]

39.423529

118

0.640107

2,177

0.649657

0

1,709

0.509997

8d17091c2b65264aa06f866332b484a8ae11e68d

2,195

py

Python

Solutions/236.py

ruppysuppy/Daily-Coding-Problem-Solutions

37d061215a9af2ce39c51f8816c83039914c0d0b

[ "MIT" ]

70

2021-03-18T05:22:40.000Z

2022-03-30T05:36:50.000Z

Solutions/236.py

ungaro/Daily-Coding-Problem-Solutions

37d061215a9af2ce39c51f8816c83039914c0d0b

[ "MIT" ]

null

Solutions/236.py

ungaro/Daily-Coding-Problem-Solutions

37d061215a9af2ce39c51f8816c83039914c0d0b

[ "MIT" ]

30

2021-03-18T05:22:43.000Z

2022-03-17T10:25:18.000Z

""" Problem: You are given a list of N points (x1, y1), (x2, y2), ..., (xN, yN) representing a polygon. You can assume these points are given in order; that is, you can construct the polygon by connecting point 1 to point 2, point 2 to point 3, and so on, finally looping around to connect point N to point 1. Determine if a new point p lies inside this polygon. (If p is on the boundary of the polygon, you should return False). """ from typing import List, Tuple Point = Tuple[int, int] def is_inside(points: List[Point], p: Point) -> bool: # Using the following concept: # if a stright line in drawn from the point p to its right (till infinity), the # drawn line will intersect the lines connecting the points odd number of times # (if p is enclosed by the points) else the the number of intersections will be # even (implying its outside the figure created by the points) # Details: # https://www.geeksforgeeks.org/how-to-check-if-a-given-point-lies-inside-a-polygon if len(points) in (0, 1, 2): return False x, y = p last = points[0] intersections = 0 same_height = set() for point in points[1:]: x1, y1 = last x2, y2 = point if min(y1, y2) <= y <= max(y1, y2) and x <= min(x1, x2): if y2 == y and point not in same_height: intersections += 1 same_height.add(point) elif y1 == y and last not in same_height: intersections += 1 same_height.add(last) last = point point = points[0] x1, y1 = last x2, y2 = point if max(y1, y2) >= y >= min(y1, y2) and x <= min(x1, x2): if y2 == y and point not in same_height: intersections += 1 same_height.add(point) elif y1 == y and last not in same_height: intersections += 1 same_height.add(last) if intersections % 2 == 1: return True return False if __name__ == "__main__": print(is_inside([(4, 3), (5, 4), (6, 3), (5, 2)], (3, 3))) print(is_inside([(4, 3), (5, 4), (6, 3), (5, 2)], (5, 3))) """ SPECS: TIME COMPLEXITY: O(n) SPACE COMPLEXITY: O(n) """

29.662162

87

0.596811

0

927

0.422323

8d199b44ca6bfd408aa35f9d1da7c224cc1e44a1

968

py

Python

tests/modules/generate/fake_package_repository_resolver.py

goldstar611/appimage-builder

62e4b8781e604545817eb47c058f5be0c0d27d15

[ "MIT" ]

155

2019-12-16T00:04:03.000Z

2022-03-28T11:22:55.000Z

tests/modules/generate/fake_package_repository_resolver.py

goldstar611/appimage-builder

62e4b8781e604545817eb47c058f5be0c0d27d15

[ "MIT" ]

151

2019-11-22T13:13:22.000Z

2022-03-30T21:27:32.000Z

tests/modules/generate/fake_package_repository_resolver.py

goldstar611/appimage-builder

62e4b8781e604545817eb47c058f5be0c0d27d15

[ "MIT" ]

28

2020-01-15T15:30:43.000Z

2022-03-22T08:58:06.000Z

# Copyright 2021 Alexis Lopez Zubieta # # Permission is hereby granted, free of charge, to any person obtaining a # copy of this software and associated documentation files (the "Software"), # to deal in the Software without restriction, including without limitation the # rights to use, copy, modify, merge, publish, distribute, sublicense, and/or # sell copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. from appimagebuilder.modules.generate.package_managers.apt import ( PackageRepositoryResolver, ) class FakePackageRepositoryResolver(PackageRepositoryResolver): def resolve_source_lines(self, packages) -> []: return [ "deb http://archive.ubuntu.com/ubuntu/ focal main restricted universe multiverse" ]

44

93

0.759298

236

0.243802

0

698

0.721074

8d19a458c0aeddafe12f42faf41b63a52a85ae7f

2,546

py

Python

Oblig3/test_benchmark.py

fabiorodp/IN5550_Neural_Methods_in_Natural_Language_Processing

4d3b2ed56b56e016413ae1544e19ad2a2c0ef047

[ "MIT" ]

null

Oblig3/test_benchmark.py

fabiorodp/IN5550_Neural_Methods_in_Natural_Language_Processing

4d3b2ed56b56e016413ae1544e19ad2a2c0ef047

[ "MIT" ]

null

Oblig3/test_benchmark.py

fabiorodp/IN5550_Neural_Methods_in_Natural_Language_Processing

4d3b2ed56b56e016413ae1544e19ad2a2c0ef047

[ "MIT" ]

null

# Author: Fabio Rodrigues Pereira # E-mail: [email protected] # Author: Per Morten Halvorsen # E-mail: [email protected] # Author: Eivind Grønlie Guren # E-mail: [email protected] try: from Oblig3.packages.preprocess import load_raw_data, filter_raw_data, pad from Oblig3.packages.preprocess import OurCONLLUDataset from Oblig3.packages.model import Transformer except: from packages.preprocess import load_raw_data, filter_raw_data, pad from packages.preprocess import OurCONLLUDataset from packages.model import Transformer from sklearn.model_selection import train_test_split from torch.utils.data import DataLoader from transformers import BertTokenizer import torch # first step # datapath = '/cluster/projects/nn9851k/IN5550/norne-nb-in5550-train.conllu' # NORBERT = '/cluster/shared/nlpl/data/vectors/latest/216' datapath = 'Oblig3/saga/norne-nb-in5550-train.conllu' NORBERT = 'Oblig3/saga/216/' device = "cuda" if torch.cuda.is_available() else "cpu" torch.cuda.empty_cache() if torch.cuda.is_available() else None # loading raw data con_df = load_raw_data(datapath=datapath) con_df = filter_raw_data(df=con_df, min_entities=5) # splitting data train_df, val_df = train_test_split( con_df, # train_size=0.50, test_size=0.25, random_state=1, shuffle=True, ) tokenizer = BertTokenizer.from_pretrained(NORBERT) # creating data sets train_dataset = OurCONLLUDataset( df=train_df, tokenizer=tokenizer, device=device ) val_dataset = OurCONLLUDataset( df=val_df, tokenizer=tokenizer, label_vocab=train_dataset.label_vocab, device=device ) # creating data loaders train_loader = DataLoader( train_dataset, batch_size=32, collate_fn=lambda batch: pad(batch, train_dataset.IGNORE_ID) ) val_loader = DataLoader( val_dataset, batch_size=len(val_dataset), collate_fn=lambda batch: pad(batch, train_dataset.IGNORE_ID) ) # calling transformer model transformer = Transformer( NORBERT=NORBERT, num_labels=len(train_dataset.label_indexer), NOT_ENTITY_ID=train_dataset.label_indexer['O'], device=device, epochs=100, # 12 for the optimal lr_scheduler=False, factor=0.1, patience=2, loss_funct='cross-entropy', random_state=1, verbose=True, lr=0.01, momentum=0.9, epoch_patience=1, # 0 for the optimal label_indexer=train_dataset.label_indexer ) transformer.fit( loader=train_loader, test=val_loader, verbose=True ) torch.save(transformer, "transformer_benchmark_12ep.pt")

24.480769

78

0.749411

0

598

0.234786

8d1acd1c8212f19c55510b4dd8c3544bf2548519

11,176

py

Python

test/test_box/test_box_storage.py

cmc333333/parsons

50804a3627117797570f1e9233c9bbad583f7831

[ "Apache-2.0" ]

null

test/test_box/test_box_storage.py

cmc333333/parsons

50804a3627117797570f1e9233c9bbad583f7831

[ "Apache-2.0" ]

2

2021-11-24T19:39:57.000Z

2022-01-03T23:03:35.000Z

test/test_box/test_box_storage.py

cmc333333/parsons

50804a3627117797570f1e9233c9bbad583f7831

[ "Apache-2.0" ]

null

import logging import os import random import string import unittest import warnings from boxsdk.exception import BoxAPIException, BoxOAuthException from parsons.box import Box from parsons.etl import Table """Prior to running, you should ensure that the relevant environment variables have been set, e.g. via # Note: these are fake keys, provided as examples. export BOX_CLIENT_ID=txqedp4rqi0cz5qckz361fziavdtdwxz export BOX_CLIENT_SECRET=bk264KHMDLVy89TeuUpSRa4CN5o35u9h export BOX_ACCESS_TOKEN=boK97B39m3ozIGyTcazbWRbi5F2SSZ5J """ TEST_CLIENT_ID = os.getenv('BOX_CLIENT_ID') TEST_BOX_CLIENT_SECRET = os.getenv('BOX_CLIENT_SECRET') TEST_ACCESS_TOKEN = os.getenv('BOX_ACCESS_TOKEN') def generate_random_string(length): """Utility to generate random alpha string for file/folder names""" return ''.join(random.choice(string.ascii_letters) for i in range(length)) @unittest.skipIf(not os.getenv('LIVE_TEST'), 'Skipping because not running live test') class TestBoxStorage(unittest.TestCase): def setUp(self) -> None: warnings.filterwarnings(action="ignore", message="unclosed", category=ResourceWarning) # Create a client that we'll use to manipulate things behind the scenes self.client = Box() # Create test folder that we'll use for all our manipulations self.temp_folder_name = generate_random_string(24) logging.info(f'Creating temp folder {self.temp_folder_name}') self.temp_folder_id = self.client.create_folder(self.temp_folder_name) def tearDown(self) -> None: logging.info(f'Deleting temp folder {self.temp_folder_name}') self.client.delete_folder_by_id(self.temp_folder_id) def test_list_files_by_id(self) -> None: # Count on environment variables being set box = Box() subfolder = box.create_folder_by_id(folder_name='id_subfolder', parent_folder_id=self.temp_folder_id) # Create a couple of files in the temp folder table = Table([['phone_number', 'last_name', 'first_name'], ['4435705355', 'Warren', 'Elizabeth'], ['5126993336', 'Obama', 'Barack']]) box.upload_table_to_folder_id(table, 'temp1', folder_id=subfolder) box.upload_table_to_folder_id(table, 'temp2', folder_id=subfolder) box.create_folder_by_id(folder_name='temp_folder1', parent_folder_id=subfolder) box.create_folder_by_id(folder_name='temp_folder2', parent_folder_id=subfolder) file_list = box.list_files_by_id(folder_id=subfolder) self.assertEqual(['temp1', 'temp2'], file_list['name']) # Check that if we delete a file, it's no longer there for box_file in file_list: if box_file['name'] == 'temp1': box.delete_file_by_id(box_file['id']) break file_list = box.list_files_by_id(folder_id=subfolder) self.assertEqual(['temp2'], file_list['name']) folder_list = box.list_folders_by_id(folder_id=subfolder)['name'] self.assertEqual(['temp_folder1', 'temp_folder2'], folder_list) def test_list_files_by_path(self) -> None: # Count on environment variables being set box = Box() # Make sure our test folder is in the right place found_default = False for item in box.list(): if item['name'] == self.temp_folder_name: found_default = True break self.assertTrue(found_default, f'Failed to find test folder f{self.temp_folder_name} ' f'in default Box folder') subfolder_name = 'path_subfolder' subfolder_path = f'{self.temp_folder_name}/{subfolder_name}' box.create_folder(path=subfolder_path) # Create a couple of files in the temp folder table = Table([['phone_number', 'last_name', 'first_name'], ['4435705355', 'Warren', 'Elizabeth'], ['5126993336', 'Obama', 'Barack']]) box.upload_table(table, f'{subfolder_path}/temp1') box.upload_table(table, f'{subfolder_path}/temp2') box.create_folder(f'{subfolder_path}/temp_folder1') box.create_folder(f'{subfolder_path}/temp_folder2') file_list = box.list(path=subfolder_path, item_type='file') self.assertEqual(['temp1', 'temp2'], file_list['name']) # Check that if we delete a file, it's no longer there for box_file in file_list: if box_file['name'] == 'temp1': box.delete_file(path=f'{subfolder_path}/temp1') break file_list = box.list(path=subfolder_path, item_type='file') self.assertEqual(['temp2'], file_list['name']) folder_list = box.list(path=subfolder_path, item_type='folder') self.assertEqual(['temp_folder1', 'temp_folder2'], folder_list['name']) # Make sure we can delete by path box.delete_folder(f'{subfolder_path}/temp_folder1') folder_list = box.list(path=subfolder_path, item_type='folder') self.assertEqual(['temp_folder2'], folder_list['name']) def test_upload_file(self) -> None: # Count on environment variables being set box = Box() table = Table([['phone_number', 'last_name', 'first_name'], ['4435705355', 'Warren', 'Elizabeth'], ['5126993336', 'Obama', 'Barack']]) box_file = box.upload_table_to_folder_id(table, 'phone_numbers', folder_id=self.temp_folder_id) new_table = box.get_table_by_file_id(box_file.id) # Check that what we saved is equal to what we got back self.assertEqual(str(table), str(new_table)) # Check that things also work in JSON box_file = box.upload_table_to_folder_id(table, 'phone_numbers_json', folder_id=self.temp_folder_id, format='json') new_table = box.get_table_by_file_id(box_file.id, format='json') # Check that what we saved is equal to what we got back self.assertEqual(str(table), str(new_table)) # Now check the same thing with paths instead of file_id path_filename = 'path_phone_numbers' box_file = box.upload_table(table, f'{self.temp_folder_name}/{path_filename}') new_table = box.get_table(path=f'{self.temp_folder_name}/{path_filename}') # Check that we throw an exception with bad formats with self.assertRaises(ValueError): box.upload_table_to_folder_id(table, 'phone_numbers', format='illegal_format') with self.assertRaises(ValueError): box.get_table_by_file_id(box_file.id, format='illegal_format') def test_download_file(self) -> None: box = Box() table = Table([['phone_number', 'last_name', 'first_name'], ['4435705355', 'Warren', 'Elizabeth'], ['5126993336', 'Obama', 'Barack']]) uploaded_file = table.to_csv() path_filename = f'{self.temp_folder_name}/my_path' box.upload_table(table, path_filename) downloaded_file = box.download_file(path_filename) with open(uploaded_file) as uploaded, open(downloaded_file) as downloaded: self.assertEqual(str(uploaded.read()), str(downloaded.read())) def test_get_item_id(self) -> None: # Count on environment variables being set box = Box() # Create a subfolder in which we'll do this test sub_sub_folder_name = 'item_subfolder' sub_sub_folder_id = box.create_folder_by_id(folder_name=sub_sub_folder_name, parent_folder_id=self.temp_folder_id) table = Table([['phone_number', 'last_name', 'first_name'], ['4435705355', 'Warren', 'Elizabeth'], ['5126993336', 'Obama', 'Barack']]) box_file = box.upload_table_to_folder_id(table, 'file_in_subfolder', folder_id=self.temp_folder_id) box_file = box.upload_table_to_folder_id(table, 'phone_numbers', folder_id=sub_sub_folder_id) # Now try getting various ids file_path = f'{self.temp_folder_name}/item_subfolder/phone_numbers' self.assertEqual(box_file.id, box.get_item_id(path=file_path)) file_path = f'{self.temp_folder_name}/item_subfolder' self.assertEqual(sub_sub_folder_id, box.get_item_id(path=file_path)) file_path = self.temp_folder_name self.assertEqual(self.temp_folder_id, box.get_item_id(path=file_path)) # Trailing "/" with self.assertRaises(ValueError): file_path = f'{self.temp_folder_name}/item_subfolder/phone_numbers/' box.get_item_id(path=file_path) # Nonexistent file with self.assertRaises(ValueError): file_path = f'{self.temp_folder_name}/item_subfolder/nonexistent/phone_numbers' box.get_item_id(path=file_path) # File (rather than folder) in middle of path with self.assertRaises(ValueError): file_path = f'{self.temp_folder_name}/file_in_subfolder/phone_numbers' box.get_item_id(path=file_path) def test_errors(self) -> None: # Count on environment variables being set box = Box() nonexistent_id = '9999999' table = Table([['phone_number', 'last_name', 'first_name'], ['4435705355', 'Warren', 'Elizabeth'], ['5126993336', 'Obama', 'Barack']]) # Upload a bad format with self.assertRaises(ValueError): box.upload_table_to_folder_id(table, 'temp1', format='bad_format') # Download a bad format with self.assertRaises(ValueError): box.get_table_by_file_id(file_id=nonexistent_id, format='bad_format') # Upload to non-existent folder with self.assertLogs(level=logging.WARNING): with self.assertRaises(BoxAPIException): box.upload_table_to_folder_id(table, 'temp1', folder_id=nonexistent_id) # Download a non-existent file with self.assertLogs(level=logging.WARNING): with self.assertRaises(BoxAPIException): box.get_table_by_file_id(nonexistent_id, format='json') # Create folder in non-existent parent with self.assertRaises(ValueError): box.create_folder('nonexistent_path/path') # Create folder in non-existent parent with self.assertLogs(level=logging.WARNING): with self.assertRaises(BoxAPIException): box.create_folder_by_id(folder_name='subfolder', parent_folder_id=nonexistent_id) # Try using bad credentials box = Box(access_token='5345345345') with self.assertLogs(level=logging.WARNING): with self.assertRaises(BoxOAuthException): box.list_files_by_id()

42.656489

97

0.642895

10,209

0.913475

0

10,296

0.92126

0

3,660

0.327487

8d1b66ad840bf7a208b29ea852c07fe8f18d11de

3,961

py

Python

Task2.py

sahil7pathak/Image_Segmentation_and_Point_Detection

7cf00f1c0a10ee0384eba7cbbb17f0779642cfa3

[ "MIT" ]

null

Task2.py

sahil7pathak/Image_Segmentation_and_Point_Detection

7cf00f1c0a10ee0384eba7cbbb17f0779642cfa3

[ "MIT" ]

null

Task2.py

sahil7pathak/Image_Segmentation_and_Point_Detection

7cf00f1c0a10ee0384eba7cbbb17f0779642cfa3

[ "MIT" ]

null

import matplotlib.pyplot as plt import numpy as np import cv2 '''Erosion Method''' def erosion(image, kernel): img_height = image.shape[0] img_width = image.shape[1] kernel_height = kernel.shape[0] kernel_width = kernel.shape[1] h = kernel_height//2 w = kernel_width//2 res = [[0 for x in range(img_width)] for y in range(img_height)] res = np.array(res) for i in range(h, img_height-h): for j in range(w, img_width-w): a = np.array(image[(i-h):(i-h)+kernel_height, (j-w):(j-w)+kernel_width]) if(np.array_equal(a, kernel)): res[i][j] = 1 else: res[i][j] = 0 return res '''Point Detection Method''' def point_detection(image, kernel): img_height = image.shape[0] img_width = image.shape[1] image = cv2.Laplacian(image, cv2.CV_32F) kernel_height = kernel.shape[0] kernel_width = kernel.shape[1] h = kernel_height//2 w = kernel_width//2 '''Threshold chosen to be a value which is 90% of maximum sum value''' T = 8382 sum_arr = [] res = [[0 for x in range(img_width)] for y in range(img_height)] res = np.array(res) for i in range(h, img_height-h): for j in range(w, img_width-w): a = np.array(image[(i-h):(i-h)+kernel_height, (j-w):(j-w)+kernel_width]) out = ((np.multiply(kernel, a))) sum = np.abs(np.sum(out)) sum_arr.append(sum) if(sum > T): co_ord = (i, j) res[i][j] = 1 print("Maximum sum: ",np.max(np.array(sum_arr))) return res, co_ord def check_segment(image): img_height = image.shape[0] img_width = image.shape[1] '''Threshold chosen by observing the plotted histogram''' T = 204 res = [[0 for x in range(img_width)] for y in range(img_height)] res = np.array(res) for i in range(image.shape[0]): for j in range(image.shape[1]): if(image[i][j] > T): res[i][j] = 255 else: res[i][j] = 0 return res img = cv2.imread("point.jpg",0) sample = img kernel = np.array([[-1,-1,-1], [-1,8,-1], [-1,-1,-1]]) output, co_ord = point_detection(img, kernel) output = output*255 output = np.asarray(output, np.uint8) cv2.rectangle(output,(424,230),(464,272),(255,255,255),2) cv2.imwrite("res_point.jpg",output) '''Code for segmenting the object from the background''' img2 = cv2.imread("segment.jpg", 0) seg = check_segment(img2) seg = np.asarray(seg, np.uint8) cv2.rectangle(seg,(155,115),(208,172),(255,255,255),2) cv2.rectangle(seg,(245,68),(300,223),(255,255,255),2) cv2.rectangle(seg,(322,13),(370,291),(255,255,255),2) cv2.rectangle(seg,(382,33),(430,264),(255,255,255),2) '''Observed co-ordinates of bounding boxes, in col, row format''' print("1st box: ") print("Upper left: (155,115)") print("Upper right: (208,115)") print("Bottom left: (155,172)") print("Bottom right: (208,172)\n") print("2nd box: ") print("Upper left: (245,68)") print("Upper right: (300,68)") print("Bottom left: (245,223)") print("Bottom right: (300,223)\n") print("3rd box: ") print("Upper left: (322,13)") print("Upper right: (370,13)") print("Bottom left: (322,291)") print("Bottom right: (370,291)\n") print("4th box: ") print("Upper left: (382,33)") print("Upper right: (430,33)") print("Bottom left: (382,264)") print("Bottom right: (430,264)") cv2.imwrite("res_segment.jpg",seg) '''Plotting Histogram''' my_dict = {} for i in range(np.unique(img2).shape[0]): a = np.unique(img2)[i] count = np.sum(img2 == a) my_dict[a] = count sorted_by_value = sorted(my_dict.items(), key=lambda kv: kv[1]) uniq = list(np.unique(img2)) val = list(my_dict.values()) plt.plot(uniq[1:],val[1:]) plt.show()

30.705426

85

0.578642

0

819

0.206766

8d1f2e38cdfd31edc3acb7a262903d61da73d831

1,652

py

Python

Subjects/migrations/0001_initial.py

Mithzyl/Master-college-selecting-api

ec8f36067fb648238df4faeaa6a65e5a78740e6c

[ "MIT" ]

null

Subjects/migrations/0001_initial.py

Mithzyl/Master-college-selecting-api

ec8f36067fb648238df4faeaa6a65e5a78740e6c

[ "MIT" ]

null

Subjects/migrations/0001_initial.py

Mithzyl/Master-college-selecting-api

ec8f36067fb648238df4faeaa6a65e5a78740e6c

[ "MIT" ]

null

# Generated by Django 3.1.5 on 2021-02-07 08:19 from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='FirstMajorSubject', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('code', models.IntegerField(blank=True, null=True)), ('name', models.CharField(max_length=40)), ], ), migrations.CreateModel( name='ForeignLanguageSubject', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('code', models.IntegerField(blank=True, null=True)), ('name', models.CharField(max_length=40)), ], ), migrations.CreateModel( name='PoliticSubject', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('code', models.IntegerField(blank=True, null=True)), ('name', models.CharField(max_length=40)), ], ), migrations.CreateModel( name='SecondMajorSubject', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('code', models.IntegerField(blank=True, null=True)), ('name', models.CharField(max_length=40)), ], ), ]

35.148936

114

0.552663

1,559

0.943705

0

206

0.124697

8d1f97cb6d168a2c8e3c97a6da76772adf11469f

239

py

Python

app/__init__.py

pahumadad/flask-oauth

309e235da8d72bb4e33d6fb68eb90b2f5392823a

[ "MIT" ]

1

2017-04-27T09:23:48.000Z

app/__init__.py

pahumadad/flask-oauth

309e235da8d72bb4e33d6fb68eb90b2f5392823a

[ "MIT" ]

null

app/__init__.py

pahumadad/flask-oauth

309e235da8d72bb4e33d6fb68eb90b2f5392823a

[ "MIT" ]

null

from flask import Flask from flask_sqlalchemy import SQLAlchemy from flask_login import LoginManager app = Flask(__name__) app.config.from_object('config') db = SQLAlchemy(app) lm = LoginManager(app) from app import views, models, oauth

21.727273

39

0.803347

0

8

0.033473

8d212f11594f7ae449b95c565655219888507326

511

py

Python

Python/toLowerCase.py

dianeyeo/LeetCode

b814831e7a4296a4e95785b75ea5c540a3fca63d

[ "MIT" ]

null

Python/toLowerCase.py

dianeyeo/LeetCode

b814831e7a4296a4e95785b75ea5c540a3fca63d

[ "MIT" ]

null

Python/toLowerCase.py

dianeyeo/LeetCode

b814831e7a4296a4e95785b75ea5c540a3fca63d

[ "MIT" ]

null

""" https://leetcode.com/problems/to-lower-case/ Difficulty: Easy Given a string s, return the string after replacing every uppercase letter with the same lowercase letter. Example 1: Input: s = "Hello" Output: "hello" Example 2: Input: s = "here" Output: "here" Example 3: Input: s = "LOVELY" Output: "lovely" Constraints: 1 <= s.length <= 100 s consists of printable ASCII characters. """ class Solution: def toLowerCase(self, str: str) -> str: return str.lower()

17.033333

106

0.661448

86

0.168297

0

422

0.825832

8d213f69d083136ed499e8028606ef1e8d49f01e

2,495

py

Python

covid_phylo/src/analysis.py

mrubio-chavarria/covidMonitor

8d59b17dbff46a781527de181f22b115565e5c2d

[ "MIT" ]

1

2021-03-22T17:05:52.000Z

covid_phylo/src/analysis.py

mrubio-chavarria/covidMonitor

8d59b17dbff46a781527de181f22b115565e5c2d

[ "MIT" ]

6

2020-06-06T01:51:21.000Z

2022-01-13T02:39:02.000Z

covid_phylo/src/analysis.py

mrubio-chavarria/covidMonitor

8d59b17dbff46a781527de181f22b115565e5c2d

[ "MIT" ]

null

import align_tools as at import matplotlib.pyplot as plt import numpy as np from collections import Counter def h(x): if x>0: return 1 else: return 0 def get_counter(arr, lower_sat=None, upper_sat=None): result = {} for val in arr: if (upper_sat is None or val < upper_sat) and (lower_sat is None or val > lower_sat): result[val] = result.get(val, 0) + 1 elif upper_sat is not None and val >= upper_sat: result[upper_sat] = result.get(upper_sat, 0) + 1 else: result[lower_sat] = result.get(lower_sat, 0) + 1 return result def analyse_gaps(num_gaps, collaps_factor=1): print(get_counter(num_gaps, upper_sat=1)) has_gaps = [h(num_gap) for num_gap in num_gaps] num_gaps_collaps = [sum(has_gaps[max([collaps_factor*i, 0]):min([collaps_factor*(i+1), len(has_gaps)])]) for i in range(int(len(has_gaps)/collaps_factor)+1)] ax = plt.subplot(111) x = [n for n in num_gaps_collaps] ax.bar(range(len(num_gaps_collaps)), num_gaps_collaps) plt.xlabel('x') plt.ylabel('y') plt.title('Posiciones con gaps') plt.show() def analyse_changes(num_vars_det, num_vars_all): vars_det_sites = get_counter(num_vars_det, 0, 4) vars_all_sites = get_counter(num_vars_all, 0, 4) print('only determined') print([f'k={k}: {vars_det_sites.get(k, 0)}, {vars_det_sites.get(k, 0) / len(num_vars_det) * 100:.2f}%' for k in vars_det_sites]) print('also undetermined') print([f'k={k}: {vars_all_sites.get(k, 0)}, {vars_all_sites.get(k, 0) / len(num_vars_all) * 100:.2f}%' for k in vars_all_sites]) x = [n for n in vars_det_sites] y = [vars_det_sites.get(n, 0) for n in x] z = [vars_all_sites[n] for n in x] ax = plt.subplot(111) bar1 = ax.bar(np.array(x)-0.1, y, width=0.2, color='b', align='center') bar2 = ax.bar(np.array(x)+0.1, z, width=0.2, color='r', align='center') ax.legend( (bar1[0], bar2[0]), ('Solo bases conocidas', 'Incluyendo bases desconocidas')) plt.xlabel('k (saturación en 4)') plt.xticks([1, 2, 3, 4]) plt.ylabel('n_k') plt.title('Histograma de nucleotidos distintos por posición') plt.show() def main(): records = at.aligned_records_by_tag("complete") num_gaps, num_vars_det, num_vars_all = at.analyse_alignment(records) print("done anaylsis") analyse_gaps(num_gaps, collaps_factor=300) analyse_changes(num_vars_det, num_vars_all) if __name__ == '__main__': main()

34.178082

161

0.658116

0

441

0.176612

8d21b09432278f9368a292eca49b25d9da12e492

88

py

Python

apps/salt/apps.py

plsof/tabops_api

39f5d2fd5158ae0c22e43ab6ff7e2b07a68a62d8

[ "MIT" ]

1

2019-07-31T07:34:38.000Z

apps/salt/apps.py

plsof/tabops_api

39f5d2fd5158ae0c22e43ab6ff7e2b07a68a62d8

[ "MIT" ]

9

2019-12-05T00:39:29.000Z

2022-02-10T14:13:29.000Z

apps/salt/apps.py

plsof/tabops_api

39f5d2fd5158ae0c22e43ab6ff7e2b07a68a62d8

[ "MIT" ]

null

from django.apps import AppConfig class SaltConfig(AppConfig): name = 'apps.salt'

14.666667

33

0.738636

51

0.579545

0

11

0.125

8d21d5ac301b7c2c83e332f0f0cea5a96ae6d81d

1,266

py

Python

pygears_vivado/vivmod.py

Anari-AI/pygears-vivado

a9d928d9914b479739ff8fc1e208813292c4b711

[ "MIT" ]

1

2022-03-19T02:11:12.000Z

pygears_vivado/vivmod.py

Anari-AI/pygears-vivado

a9d928d9914b479739ff8fc1e208813292c4b711

[ "MIT" ]

null

pygears_vivado/vivmod.py

Anari-AI/pygears-vivado

a9d928d9914b479739ff8fc1e208813292c4b711

[ "MIT" ]

1

2021-06-01T13:21:12.000Z

import os from pygears.hdl.sv import SVModuleInst from .ip_resolver import IPResolver class SVVivModuleInst(SVModuleInst): def __init__(self, node, lang=None): resolver = IPResolver(node) super().__init__(node, resolver.lang, resolver) @property def is_generated(self): return True @property def include(self): return [os.path.join(self.ipdir, 'hdl')] def get_wrap_portmap(self, parent_lang): sig_map = {} for s in self.node.meta_kwds['signals']: sig_map[s.name] = s.name port_map = {} for p in self.node.in_ports + self.node.out_ports: name = p.basename if self.lang == 'sv': port_map[name] = name elif parent_lang == 'sv': sig_map[f'{name}_tvalid'] = f'{name}.valid' sig_map[f'{name}_tready'] = f'{name}.ready' sig_map[f'{name}_tdata'] = f'{name}.data' elif parent_lang == 'v': sig_map[f'{name}_tvalid'] = f'{name}_valid' sig_map[f'{name}_tready'] = f'{name}_ready' sig_map[f'{name}_tdata'] = f'{name}_data' else: port_map[name] = name return port_map, sig_map

30.878049

59

0.553712

1,177

0.9297

0

138

0.109005

0

207

0.163507

8d24383aba0b77760774f695ed82a4ade6ace738

1,841

py

Python

commodore/inventory/render.py

projectsyn/commodore

afd924a2aa8abb79cd6a8970ff225756469dd2b3

[ "BSD-3-Clause" ]

39

2019-12-17T13:40:19.000Z

2021-12-31T08:22:52.000Z

commodore/inventory/render.py

projectsyn/commodore

afd924a2aa8abb79cd6a8970ff225756469dd2b3

[ "BSD-3-Clause" ]

161

2020-02-14T18:32:49.000Z

2022-03-25T09:23:35.000Z

commodore/inventory/render.py

projectsyn/commodore

afd924a2aa8abb79cd6a8970ff225756469dd2b3

[ "BSD-3-Clause" ]

12

2019-12-18T15:43:09.000Z

2021-06-28T11:51:59.000Z

import shutil import tempfile from pathlib import Path from typing import Dict import click from commodore.config import Config from .parameters import ClassNotFound, InventoryFactory, InventoryFacts def _cleanup_work_dir(cfg: Config, work_dir: Path): if not cfg.debug: # Clean up work dir if we're not in debug mode shutil.rmtree(work_dir) def extract_components( cfg: Config, invfacts: InventoryFacts ) -> Dict[str, Dict[str, str]]: if cfg.debug: click.echo( f"Called with: global_config={invfacts.global_config} " + f"tenant_config={invfacts.tenant_config} " + f"extra_classes={invfacts.extra_classes} " + f"allow_missing_classes={invfacts.allow_missing_classes}." ) global_dir = Path(invfacts.global_config).resolve().absolute() tenant_dir = None if invfacts.tenant_config: tenant_dir = Path(invfacts.tenant_config).resolve().absolute() work_dir = Path(tempfile.mkdtemp(prefix="commodore-reclass-")).resolve() if global_dir.is_dir() and (not tenant_dir or tenant_dir.is_dir()): invfactory = InventoryFactory.from_repo_dirs( work_dir, global_dir, tenant_dir, invfacts ) else: _cleanup_work_dir(cfg, work_dir) raise NotImplementedError("Cloning global or tenant repo not yet implemented") try: inv = invfactory.reclass(invfacts) components = inv.parameters("components") except ClassNotFound as e: _cleanup_work_dir(cfg, work_dir) raise ValueError( "Unable to render inventory with `--no-allow-missing-classes`. " + f"Class '{e.name}' not found. " + "Verify the provided values or allow missing classes." ) from e _cleanup_work_dir(cfg, work_dir) return components

30.683333

86

0.674633

0

475

0.258012

8d2771d9640e1def0fa9d63283dfdac05afbee62

25,468

py

Python

nova/pci/stats.py

bopopescu/nova-token

ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2

[ "Apache-2.0" ]

null

nova/pci/stats.py

bopopescu/nova-token

ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2

[ "Apache-2.0" ]

null

nova/pci/stats.py

bopopescu/nova-token

ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2

[ "Apache-2.0" ]

2

2017-07-20T17:31:34.000Z

2020-07-24T02:42:19.000Z

begin_unit comment|'# Copyright (c) 2013 Intel, Inc.' nl|'\n' comment|'# Copyright (c) 2013 OpenStack Foundation' nl|'\n' comment|'# All Rights Reserved.' nl|'\n' comment|'#' nl|'\n' comment|'# Licensed under the Apache License, Version 2.0 (the "License"); you may' nl|'\n' comment|'# not use this file except in compliance with the License. You may obtain' nl|'\n' comment|'# a copy of the License at' nl|'\n' comment|'#' nl|'\n' comment|'# http://www.apache.org/licenses/LICENSE-2.0' nl|'\n' comment|'#' nl|'\n' comment|'# Unless required by applicable law or agreed to in writing, software' nl|'\n' comment|'# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT' nl|'\n' comment|'# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the' nl|'\n' comment|'# License for the specific language governing permissions and limitations' nl|'\n' comment|'# under the License.' nl|'\n' nl|'\n' name|'import' name|'copy' newline|'\n' nl|'\n' name|'from' name|'oslo_config' name|'import' name|'cfg' newline|'\n' name|'from' name|'oslo_log' name|'import' name|'log' name|'as' name|'logging' newline|'\n' name|'import' name|'six' newline|'\n' nl|'\n' name|'from' name|'nova' name|'import' name|'exception' newline|'\n' name|'from' name|'nova' op|'.' name|'i18n' name|'import' name|'_LE' newline|'\n' name|'from' name|'nova' name|'import' name|'objects' newline|'\n' name|'from' name|'nova' op|'.' name|'objects' name|'import' name|'fields' newline|'\n' name|'from' name|'nova' op|'.' name|'objects' name|'import' name|'pci_device_pool' newline|'\n' name|'from' name|'nova' op|'.' name|'pci' name|'import' name|'utils' newline|'\n' name|'from' name|'nova' op|'.' name|'pci' name|'import' name|'whitelist' newline|'\n' nl|'\n' nl|'\n' DECL|variable|CONF name|'CONF' op|'=' name|'cfg' op|'.' name|'CONF' newline|'\n' DECL|variable|LOG name|'LOG' op|'=' name|'logging' op|'.' name|'getLogger' op|'(' name|'__name__' op|')' newline|'\n' nl|'\n' nl|'\n' DECL|class|PciDeviceStats name|'class' name|'PciDeviceStats' op|'(' name|'object' op|')' op|':' newline|'\n' nl|'\n' indent|' ' string|'"""PCI devices summary information.\n\n According to the PCI SR-IOV spec, a PCI physical function can have up to\n 256 PCI virtual functions, thus the number of assignable PCI functions in\n a cloud can be big. The scheduler needs to know all device availability\n information in order to determine which compute hosts can support a PCI\n request. Passing individual virtual device information to the scheduler\n does not scale, so we provide summary information.\n\n Usually the virtual functions provided by a host PCI device have the same\n value for most properties, like vendor_id, product_id and class type.\n The PCI stats class summarizes this information for the scheduler.\n\n The pci stats information is maintained exclusively by compute node\n resource tracker and updated to database. The scheduler fetches the\n information and selects the compute node accordingly. If a compute\n node is selected, the resource tracker allocates the devices to the\n instance and updates the pci stats information.\n\n This summary information will be helpful for cloud management also.\n """' newline|'\n' nl|'\n' DECL|variable|pool_keys name|'pool_keys' op|'=' op|'[' string|"'product_id'" op|',' string|"'vendor_id'" op|',' string|"'numa_node'" op|',' string|"'dev_type'" op|']' newline|'\n' nl|'\n' DECL|member|__init__ name|'def' name|'__init__' op|'(' name|'self' op|',' name|'stats' op|'=' name|'None' op|',' name|'dev_filter' op|'=' name|'None' op|')' op|':' newline|'\n' indent|' ' name|'super' op|'(' name|'PciDeviceStats' op|',' name|'self' op|')' op|'.' name|'__init__' op|'(' op|')' newline|'\n' comment|'# NOTE(sbauza): Stats are a PCIDevicePoolList object' nl|'\n' name|'self' op|'.' name|'pools' op|'=' op|'[' name|'pci_pool' op|'.' name|'to_dict' op|'(' op|')' nl|'\n' name|'for' name|'pci_pool' name|'in' name|'stats' op|']' name|'if' name|'stats' name|'else' op|'[' op|']' newline|'\n' name|'self' op|'.' name|'pools' op|'.' name|'sort' op|'(' name|'key' op|'=' name|'lambda' name|'item' op|':' name|'len' op|'(' name|'item' op|')' op|')' newline|'\n' name|'self' op|'.' name|'dev_filter' op|'=' name|'dev_filter' name|'or' name|'whitelist' op|'.' name|'Whitelist' op|'(' nl|'\n' name|'CONF' op|'.' name|'pci_passthrough_whitelist' op|')' newline|'\n' nl|'\n' DECL|member|_equal_properties dedent|'' name|'def' name|'_equal_properties' op|'(' name|'self' op|',' name|'dev' op|',' name|'entry' op|',' name|'matching_keys' op|')' op|':' newline|'\n' indent|' ' name|'return' name|'all' op|'(' name|'dev' op|'.' name|'get' op|'(' name|'prop' op|')' op|'==' name|'entry' op|'.' name|'get' op|'(' name|'prop' op|')' nl|'\n' name|'for' name|'prop' name|'in' name|'matching_keys' op|')' newline|'\n' nl|'\n' DECL|member|_find_pool dedent|'' name|'def' name|'_find_pool' op|'(' name|'self' op|',' name|'dev_pool' op|')' op|':' newline|'\n' indent|' ' string|'"""Return the first pool that matches dev."""' newline|'\n' name|'for' name|'pool' name|'in' name|'self' op|'.' name|'pools' op|':' newline|'\n' indent|' ' name|'pool_keys' op|'=' name|'pool' op|'.' name|'copy' op|'(' op|')' newline|'\n' name|'del' name|'pool_keys' op|'[' string|"'count'" op|']' newline|'\n' name|'del' name|'pool_keys' op|'[' string|"'devices'" op|']' newline|'\n' name|'if' op|'(' name|'len' op|'(' name|'pool_keys' op|'.' name|'keys' op|'(' op|')' op|')' op|'==' name|'len' op|'(' name|'dev_pool' op|'.' name|'keys' op|'(' op|')' op|')' name|'and' nl|'\n' name|'self' op|'.' name|'_equal_properties' op|'(' name|'dev_pool' op|',' name|'pool_keys' op|',' name|'dev_pool' op|'.' name|'keys' op|'(' op|')' op|')' op|')' op|':' newline|'\n' indent|' ' name|'return' name|'pool' newline|'\n' nl|'\n' DECL|member|_create_pool_keys_from_dev dedent|'' dedent|'' dedent|'' name|'def' name|'_create_pool_keys_from_dev' op|'(' name|'self' op|',' name|'dev' op|')' op|':' newline|'\n' indent|' ' string|'"""create a stats pool dict that this dev is supposed to be part of\n\n Note that this pool dict contains the stats pool\'s keys and their\n values. \'count\' and \'devices\' are not included.\n """' newline|'\n' comment|"# Don't add a device that doesn't have a matching device spec." nl|'\n' comment|'# This can happen during initial sync up with the controller' nl|'\n' name|'devspec' op|'=' name|'self' op|'.' name|'dev_filter' op|'.' name|'get_devspec' op|'(' name|'dev' op|')' newline|'\n' name|'if' name|'not' name|'devspec' op|':' newline|'\n' indent|' ' name|'return' newline|'\n' dedent|'' name|'tags' op|'=' name|'devspec' op|'.' name|'get_tags' op|'(' op|')' newline|'\n' name|'pool' op|'=' op|'{' name|'k' op|':' name|'getattr' op|'(' name|'dev' op|',' name|'k' op|')' name|'for' name|'k' name|'in' name|'self' op|'.' name|'pool_keys' op|'}' newline|'\n' name|'if' name|'tags' op|':' newline|'\n' indent|' ' name|'pool' op|'.' name|'update' op|'(' name|'tags' op|')' newline|'\n' dedent|'' name|'return' name|'pool' newline|'\n' nl|'\n' DECL|member|add_device dedent|'' name|'def' name|'add_device' op|'(' name|'self' op|',' name|'dev' op|')' op|':' newline|'\n' indent|' ' string|'"""Add a device to its matching pool."""' newline|'\n' name|'dev_pool' op|'=' name|'self' op|'.' name|'_create_pool_keys_from_dev' op|'(' name|'dev' op|')' newline|'\n' name|'if' name|'dev_pool' op|':' newline|'\n' indent|' ' name|'pool' op|'=' name|'self' op|'.' name|'_find_pool' op|'(' name|'dev_pool' op|')' newline|'\n' name|'if' name|'not' name|'pool' op|':' newline|'\n' indent|' ' name|'dev_pool' op|'[' string|"'count'" op|']' op|'=' number|'0' newline|'\n' name|'dev_pool' op|'[' string|"'devices'" op|']' op|'=' op|'[' op|']' newline|'\n' name|'self' op|'.' name|'pools' op|'.' name|'append' op|'(' name|'dev_pool' op|')' newline|'\n' name|'self' op|'.' name|'pools' op|'.' name|'sort' op|'(' name|'key' op|'=' name|'lambda' name|'item' op|':' name|'len' op|'(' name|'item' op|')' op|')' newline|'\n' name|'pool' op|'=' name|'dev_pool' newline|'\n' dedent|'' name|'pool' op|'[' string|"'count'" op|']' op|'+=' number|'1' newline|'\n' name|'pool' op|'[' string|"'devices'" op|']' op|'.' name|'append' op|'(' name|'dev' op|')' newline|'\n' nl|'\n' dedent|'' dedent|'' op|'@' name|'staticmethod' newline|'\n' DECL|member|_decrease_pool_count name|'def' name|'_decrease_pool_count' op|'(' name|'pool_list' op|',' name|'pool' op|',' name|'count' op|'=' number|'1' op|')' op|':' newline|'\n' indent|' ' string|'"""Decrement pool\'s size by count.\n\n If pool becomes empty, remove pool from pool_list.\n """' newline|'\n' name|'if' name|'pool' op|'[' string|"'count'" op|']' op|'>' name|'count' op|':' newline|'\n' indent|' ' name|'pool' op|'[' string|"'count'" op|']' op|'-=' name|'count' newline|'\n' name|'count' op|'=' number|'0' newline|'\n' dedent|'' name|'else' op|':' newline|'\n' indent|' ' name|'count' op|'-=' name|'pool' op|'[' string|"'count'" op|']' newline|'\n' name|'pool_list' op|'.' name|'remove' op|'(' name|'pool' op|')' newline|'\n' dedent|'' name|'return' name|'count' newline|'\n' nl|'\n' DECL|member|remove_device dedent|'' name|'def' name|'remove_device' op|'(' name|'self' op|',' name|'dev' op|')' op|':' newline|'\n' indent|' ' string|'"""Remove one device from the first pool that it matches."""' newline|'\n' name|'dev_pool' op|'=' name|'self' op|'.' name|'_create_pool_keys_from_dev' op|'(' name|'dev' op|')' newline|'\n' name|'if' name|'dev_pool' op|':' newline|'\n' indent|' ' name|'pool' op|'=' name|'self' op|'.' name|'_find_pool' op|'(' name|'dev_pool' op|')' newline|'\n' name|'if' name|'not' name|'pool' op|':' newline|'\n' indent|' ' name|'raise' name|'exception' op|'.' name|'PciDevicePoolEmpty' op|'(' nl|'\n' name|'compute_node_id' op|'=' name|'dev' op|'.' name|'compute_node_id' op|',' name|'address' op|'=' name|'dev' op|'.' name|'address' op|')' newline|'\n' dedent|'' name|'pool' op|'[' string|"'devices'" op|']' op|'.' name|'remove' op|'(' name|'dev' op|')' newline|'\n' name|'self' op|'.' name|'_decrease_pool_count' op|'(' name|'self' op|'.' name|'pools' op|',' name|'pool' op|')' newline|'\n' nl|'\n' DECL|member|get_free_devs dedent|'' dedent|'' name|'def' name|'get_free_devs' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' name|'free_devs' op|'=' op|'[' op|']' newline|'\n' name|'for' name|'pool' name|'in' name|'self' op|'.' name|'pools' op|':' newline|'\n' indent|' ' name|'free_devs' op|'.' name|'extend' op|'(' name|'pool' op|'[' string|"'devices'" op|']' op|')' newline|'\n' dedent|'' name|'return' name|'free_devs' newline|'\n' nl|'\n' DECL|member|consume_requests dedent|'' name|'def' name|'consume_requests' op|'(' name|'self' op|',' name|'pci_requests' op|',' name|'numa_cells' op|'=' name|'None' op|')' op|':' newline|'\n' indent|' ' name|'alloc_devices' op|'=' op|'[' op|']' newline|'\n' name|'for' name|'request' name|'in' name|'pci_requests' op|':' newline|'\n' indent|' ' name|'count' op|'=' name|'request' op|'.' name|'count' newline|'\n' name|'spec' op|'=' name|'request' op|'.' name|'spec' newline|'\n' comment|'# For now, keep the same algorithm as during scheduling:' nl|'\n' comment|'# a spec may be able to match multiple pools.' nl|'\n' name|'pools' op|'=' name|'self' op|'.' name|'_filter_pools_for_spec' op|'(' name|'self' op|'.' name|'pools' op|',' name|'spec' op|')' newline|'\n' name|'if' name|'numa_cells' op|':' newline|'\n' indent|' ' name|'pools' op|'=' name|'self' op|'.' name|'_filter_pools_for_numa_cells' op|'(' name|'pools' op|',' name|'numa_cells' op|')' newline|'\n' dedent|'' name|'pools' op|'=' name|'self' op|'.' name|'_filter_non_requested_pfs' op|'(' name|'request' op|',' name|'pools' op|')' newline|'\n' comment|'# Failed to allocate the required number of devices' nl|'\n' comment|'# Return the devices already allocated back to their pools' nl|'\n' name|'if' name|'sum' op|'(' op|'[' name|'pool' op|'[' string|"'count'" op|']' name|'for' name|'pool' name|'in' name|'pools' op|']' op|')' op|'<' name|'count' op|':' newline|'\n' indent|' ' name|'LOG' op|'.' name|'error' op|'(' name|'_LE' op|'(' string|'"Failed to allocate PCI devices for instance."' nl|'\n' string|'" Unassigning devices back to pools."' nl|'\n' string|'" This should not happen, since the scheduler"' nl|'\n' string|'" should have accurate information, and allocation"' nl|'\n' string|'" during claims is controlled via a hold"' nl|'\n' string|'" on the compute node semaphore"' op|')' op|')' newline|'\n' name|'for' name|'d' name|'in' name|'range' op|'(' name|'len' op|'(' name|'alloc_devices' op|')' op|')' op|':' newline|'\n' indent|' ' name|'self' op|'.' name|'add_device' op|'(' name|'alloc_devices' op|'.' name|'pop' op|'(' op|')' op|')' newline|'\n' dedent|'' name|'return' name|'None' newline|'\n' dedent|'' name|'for' name|'pool' name|'in' name|'pools' op|':' newline|'\n' indent|' ' name|'if' name|'pool' op|'[' string|"'count'" op|']' op|'>=' name|'count' op|':' newline|'\n' indent|' ' name|'num_alloc' op|'=' name|'count' newline|'\n' dedent|'' name|'else' op|':' newline|'\n' indent|' ' name|'num_alloc' op|'=' name|'pool' op|'[' string|"'count'" op|']' newline|'\n' dedent|'' name|'count' op|'-=' name|'num_alloc' newline|'\n' name|'pool' op|'[' string|"'count'" op|']' op|'-=' name|'num_alloc' newline|'\n' name|'for' name|'d' name|'in' name|'range' op|'(' name|'num_alloc' op|')' op|':' newline|'\n' indent|' ' name|'pci_dev' op|'=' name|'pool' op|'[' string|"'devices'" op|']' op|'.' name|'pop' op|'(' op|')' newline|'\n' name|'self' op|'.' name|'_handle_device_dependents' op|'(' name|'pci_dev' op|')' newline|'\n' name|'pci_dev' op|'.' name|'request_id' op|'=' name|'request' op|'.' name|'request_id' newline|'\n' name|'alloc_devices' op|'.' name|'append' op|'(' name|'pci_dev' op|')' newline|'\n' dedent|'' name|'if' name|'count' op|'==' number|'0' op|':' newline|'\n' indent|' ' name|'break' newline|'\n' dedent|'' dedent|'' dedent|'' name|'return' name|'alloc_devices' newline|'\n' nl|'\n' DECL|member|_handle_device_dependents dedent|'' name|'def' name|'_handle_device_dependents' op|'(' name|'self' op|',' name|'pci_dev' op|')' op|':' newline|'\n' indent|' ' string|'"""Remove device dependents or a parent from pools.\n\n In case the device is a PF, all of it\'s dependent VFs should\n be removed from pools count, if these are present.\n When the device is a VF, it\'s parent PF pool count should be\n decreased, unless it is no longer in a pool.\n """' newline|'\n' name|'if' name|'pci_dev' op|'.' name|'dev_type' op|'==' name|'fields' op|'.' name|'PciDeviceType' op|'.' name|'SRIOV_PF' op|':' newline|'\n' indent|' ' name|'vfs_list' op|'=' name|'objects' op|'.' name|'PciDeviceList' op|'.' name|'get_by_parent_address' op|'(' nl|'\n' name|'pci_dev' op|'.' name|'_context' op|',' nl|'\n' name|'pci_dev' op|'.' name|'compute_node_id' op|',' nl|'\n' name|'pci_dev' op|'.' name|'address' op|')' newline|'\n' name|'if' name|'vfs_list' op|':' newline|'\n' indent|' ' name|'for' name|'vf' name|'in' name|'vfs_list' op|':' newline|'\n' indent|' ' name|'self' op|'.' name|'remove_device' op|'(' name|'vf' op|')' newline|'\n' dedent|'' dedent|'' dedent|'' name|'elif' name|'pci_dev' op|'.' name|'dev_type' op|'==' name|'fields' op|'.' name|'PciDeviceType' op|'.' name|'SRIOV_VF' op|':' newline|'\n' indent|' ' name|'try' op|':' newline|'\n' indent|' ' name|'parent' op|'=' name|'pci_dev' op|'.' name|'get_by_dev_addr' op|'(' name|'pci_dev' op|'.' name|'_context' op|',' nl|'\n' name|'pci_dev' op|'.' name|'compute_node_id' op|',' nl|'\n' name|'pci_dev' op|'.' name|'parent_addr' op|')' newline|'\n' comment|'# Make sure not to decrease PF pool count if this parent has' nl|'\n' comment|'# been already removed from pools' nl|'\n' name|'if' name|'parent' name|'in' name|'self' op|'.' name|'get_free_devs' op|'(' op|')' op|':' newline|'\n' indent|' ' name|'self' op|'.' name|'remove_device' op|'(' name|'parent' op|')' newline|'\n' dedent|'' dedent|'' name|'except' name|'exception' op|'.' name|'PciDeviceNotFound' op|':' newline|'\n' indent|' ' name|'return' newline|'\n' nl|'\n' dedent|'' dedent|'' dedent|'' op|'@' name|'staticmethod' newline|'\n' DECL|member|_filter_pools_for_spec name|'def' name|'_filter_pools_for_spec' op|'(' name|'pools' op|',' name|'request_specs' op|')' op|':' newline|'\n' indent|' ' name|'return' op|'[' name|'pool' name|'for' name|'pool' name|'in' name|'pools' nl|'\n' name|'if' name|'utils' op|'.' name|'pci_device_prop_match' op|'(' name|'pool' op|',' name|'request_specs' op|')' op|']' newline|'\n' nl|'\n' dedent|'' op|'@' name|'staticmethod' newline|'\n' DECL|member|_filter_pools_for_numa_cells name|'def' name|'_filter_pools_for_numa_cells' op|'(' name|'pools' op|',' name|'numa_cells' op|')' op|':' newline|'\n' comment|"# Some systems don't report numa node info for pci devices, in" nl|'\n' comment|'# that case None is reported in pci_device.numa_node, by adding None' nl|'\n' comment|'# to numa_cells we allow assigning those devices to instances with' nl|'\n' comment|'# numa topology' nl|'\n' indent|' ' name|'numa_cells' op|'=' op|'[' name|'None' op|']' op|'+' op|'[' name|'cell' op|'.' name|'id' name|'for' name|'cell' name|'in' name|'numa_cells' op|']' newline|'\n' comment|'# filter out pools which numa_node is not included in numa_cells' nl|'\n' name|'return' op|'[' name|'pool' name|'for' name|'pool' name|'in' name|'pools' name|'if' name|'any' op|'(' name|'utils' op|'.' name|'pci_device_prop_match' op|'(' nl|'\n' name|'pool' op|',' op|'[' op|'{' string|"'numa_node'" op|':' name|'cell' op|'}' op|']' op|')' nl|'\n' name|'for' name|'cell' name|'in' name|'numa_cells' op|')' op|']' newline|'\n' nl|'\n' DECL|member|_filter_non_requested_pfs dedent|'' name|'def' name|'_filter_non_requested_pfs' op|'(' name|'self' op|',' name|'request' op|',' name|'matching_pools' op|')' op|':' newline|'\n' comment|'# Remove SRIOV_PFs from pools, unless it has been explicitly requested' nl|'\n' comment|'# This is especially needed in cases where PFs and VFs has the same' nl|'\n' comment|'# product_id.' nl|'\n' indent|' ' name|'if' name|'all' op|'(' name|'spec' op|'.' name|'get' op|'(' string|"'dev_type'" op|')' op|'!=' name|'fields' op|'.' name|'PciDeviceType' op|'.' name|'SRIOV_PF' name|'for' nl|'\n' name|'spec' name|'in' name|'request' op|'.' name|'spec' op|')' op|':' newline|'\n' indent|' ' name|'matching_pools' op|'=' name|'self' op|'.' name|'_filter_pools_for_pfs' op|'(' name|'matching_pools' op|')' newline|'\n' dedent|'' name|'return' name|'matching_pools' newline|'\n' nl|'\n' dedent|'' op|'@' name|'staticmethod' newline|'\n' DECL|member|_filter_pools_for_pfs name|'def' name|'_filter_pools_for_pfs' op|'(' name|'pools' op|')' op|':' newline|'\n' indent|' ' name|'return' op|'[' name|'pool' name|'for' name|'pool' name|'in' name|'pools' nl|'\n' name|'if' name|'not' name|'pool' op|'.' name|'get' op|'(' string|"'dev_type'" op|')' op|'==' name|'fields' op|'.' name|'PciDeviceType' op|'.' name|'SRIOV_PF' op|']' newline|'\n' nl|'\n' DECL|member|_apply_request dedent|'' name|'def' name|'_apply_request' op|'(' name|'self' op|',' name|'pools' op|',' name|'request' op|',' name|'numa_cells' op|'=' name|'None' op|')' op|':' newline|'\n' comment|'# NOTE(vladikr): This code maybe open to race conditions.' nl|'\n' comment|'# Two concurrent requests may succeed when called support_requests' nl|'\n' comment|'# because this method does not remove related devices from the pools' nl|'\n' indent|' ' name|'count' op|'=' name|'request' op|'.' name|'count' newline|'\n' name|'matching_pools' op|'=' name|'self' op|'.' name|'_filter_pools_for_spec' op|'(' name|'pools' op|',' name|'request' op|'.' name|'spec' op|')' newline|'\n' name|'if' name|'numa_cells' op|':' newline|'\n' indent|' ' name|'matching_pools' op|'=' name|'self' op|'.' name|'_filter_pools_for_numa_cells' op|'(' name|'matching_pools' op|',' nl|'\n' name|'numa_cells' op|')' newline|'\n' dedent|'' name|'matching_pools' op|'=' name|'self' op|'.' name|'_filter_non_requested_pfs' op|'(' name|'request' op|',' nl|'\n' name|'matching_pools' op|')' newline|'\n' name|'if' name|'sum' op|'(' op|'[' name|'pool' op|'[' string|"'count'" op|']' name|'for' name|'pool' name|'in' name|'matching_pools' op|']' op|')' op|'<' name|'count' op|':' newline|'\n' indent|' ' name|'return' name|'False' newline|'\n' dedent|'' name|'else' op|':' newline|'\n' indent|' ' name|'for' name|'pool' name|'in' name|'matching_pools' op|':' newline|'\n' indent|' ' name|'count' op|'=' name|'self' op|'.' name|'_decrease_pool_count' op|'(' name|'pools' op|',' name|'pool' op|',' name|'count' op|')' newline|'\n' name|'if' name|'not' name|'count' op|':' newline|'\n' indent|' ' name|'break' newline|'\n' dedent|'' dedent|'' dedent|'' name|'return' name|'True' newline|'\n' nl|'\n' DECL|member|support_requests dedent|'' name|'def' name|'support_requests' op|'(' name|'self' op|',' name|'requests' op|',' name|'numa_cells' op|'=' name|'None' op|')' op|':' newline|'\n' indent|' ' string|'"""Check if the pci requests can be met.\n\n Scheduler checks compute node\'s PCI stats to decide if an\n instance can be scheduled into the node. Support does not\n mean real allocation.\n If numa_cells is provided then only devices contained in\n those nodes are considered.\n """' newline|'\n' comment|'# note (yjiang5): this function has high possibility to fail,' nl|'\n' comment|'# so no exception should be triggered for performance reason.' nl|'\n' name|'pools' op|'=' name|'copy' op|'.' name|'deepcopy' op|'(' name|'self' op|'.' name|'pools' op|')' newline|'\n' name|'return' name|'all' op|'(' op|'[' name|'self' op|'.' name|'_apply_request' op|'(' name|'pools' op|',' name|'r' op|',' name|'numa_cells' op|')' nl|'\n' name|'for' name|'r' name|'in' name|'requests' op|']' op|')' newline|'\n' nl|'\n' DECL|member|apply_requests dedent|'' name|'def' name|'apply_requests' op|'(' name|'self' op|',' name|'requests' op|',' name|'numa_cells' op|'=' name|'None' op|')' op|':' newline|'\n' indent|' ' string|'"""Apply PCI requests to the PCI stats.\n\n This is used in multiple instance creation, when the scheduler has to\n maintain how the resources are consumed by the instances.\n If numa_cells is provided then only devices contained in\n those nodes are considered.\n """' newline|'\n' name|'if' name|'not' name|'all' op|'(' op|'[' name|'self' op|'.' name|'_apply_request' op|'(' name|'self' op|'.' name|'pools' op|',' name|'r' op|',' name|'numa_cells' op|')' nl|'\n' name|'for' name|'r' name|'in' name|'requests' op|']' op|')' op|':' newline|'\n' indent|' ' name|'raise' name|'exception' op|'.' name|'PciDeviceRequestFailed' op|'(' name|'requests' op|'=' name|'requests' op|')' newline|'\n' nl|'\n' DECL|member|__iter__ dedent|'' dedent|'' name|'def' name|'__iter__' op|'(' name|'self' op|')' op|':' newline|'\n' comment|"# 'devices' shouldn't be part of stats" nl|'\n' indent|' ' name|'pools' op|'=' op|'[' op|']' newline|'\n' name|'for' name|'pool' name|'in' name|'self' op|'.' name|'pools' op|':' newline|'\n' indent|' ' name|'tmp' op|'=' op|'{' name|'k' op|':' name|'v' name|'for' name|'k' op|',' name|'v' name|'in' name|'six' op|'.' name|'iteritems' op|'(' name|'pool' op|')' name|'if' name|'k' op|'!=' string|"'devices'" op|'}' newline|'\n' name|'pools' op|'.' name|'append' op|'(' name|'tmp' op|')' newline|'\n' dedent|'' name|'return' name|'iter' op|'(' name|'pools' op|')' newline|'\n' nl|'\n' DECL|member|clear dedent|'' name|'def' name|'clear' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' string|'"""Clear all the stats maintained."""' newline|'\n' name|'self' op|'.' name|'pools' op|'=' op|'[' op|']' newline|'\n' nl|'\n' DECL|member|__eq__ dedent|'' name|'def' name|'__eq__' op|'(' name|'self' op|',' name|'other' op|')' op|':' newline|'\n' indent|' ' name|'return' name|'cmp' op|'(' name|'self' op|'.' name|'pools' op|',' name|'other' op|'.' name|'pools' op|')' op|'==' number|'0' newline|'\n' nl|'\n' DECL|member|__ne__ dedent|'' name|'def' name|'__ne__' op|'(' name|'self' op|',' name|'other' op|')' op|':' newline|'\n' indent|' ' name|'return' name|'not' op|'(' name|'self' op|'==' name|'other' op|')' newline|'\n' nl|'\n' DECL|member|to_device_pools_obj dedent|'' name|'def' name|'to_device_pools_obj' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' string|'"""Return the contents of the pools as a PciDevicePoolList object."""' newline|'\n' name|'stats' op|'=' op|'[' name|'x' name|'for' name|'x' name|'in' name|'self' op|']' newline|'\n' name|'return' name|'pci_device_pool' op|'.' name|'from_pci_stats' op|'(' name|'stats' op|')' newline|'\n' dedent|'' dedent|'' endmarker|'' end_unit

14.37246

1,148

0.61167

0

14,664

0.575781

8d29d50d0c950b859290e95b7cb057e02fb60ee8

4,045

py

Python

profit/models/torch/vae.py

ayushkarnawat/profit

f3c4d601078b52513af6832c3faf75ddafc59ac5

[ "MIT" ]

null

profit/models/torch/vae.py

ayushkarnawat/profit

f3c4d601078b52513af6832c3faf75ddafc59ac5

[ "MIT" ]

1

2021-09-15T13:13:12.000Z

profit/models/torch/vae.py

ayushkarnawat/profit

f3c4d601078b52513af6832c3faf75ddafc59ac5

[ "MIT" ]

null

"""Variational autoencoder model.""" from typing import Tuple import torch from torch import nn from torch.nn import functional as F class BaseVAE(nn.Module): """Base class for creating variational autoencoders (VAEs). The module is designed to connect user-specified encoder/decoder layers to form a latent space representation of the data. A general overview of the model can be described by: https://lilianweng.github.io/lil-log/2018/08/12/from-autoencoder-to-beta-vae.html """ def __init__(self) -> None: super(BaseVAE, self).__init__() def encode(self, x: torch.Tensor) -> Tuple[torch.Tensor, torch.Tensor]: """Builds the encoded representation of the input. The encoded model outputs the mean and logvar of the latent space embeddings/distribution, or in more mathematical terms, :math:: `q(z|x) = \\mathcal{N}(z| \\mu(x), \\sigma(x))` """ raise NotImplementedError def reparameterize(self, mu: torch.Tensor, logvar: torch.Tensor) -> torch.Tensor: """Reparamaterization trick. Computes the latent vector (`z`), which is a compressed low-dim representation of the input. This trick allows us to express the gradient of the expectation as the expectation of the gradient [1]. Additionally, it makes the variance of the estimate an order of magnitude lower than without using it. This allows us to compute the gradient during the backward pass more accurately, with better estimates [2]. References: ----------- -[1] https://gregorygundersen.com/blog/2018/04/29/reparameterization/ -[2] https://stats.stackexchange.com/a/226136 """ std = torch.exp(0.5*logvar) # eps=N(0,I), where the I is an identity matrix of same size as std eps = torch.randn_like(std) return mu + std*eps def decode(self, z: torch.Tensor) -> torch.Tensor: """Decodes the sampled latent vector (`z`) into the reconstructed output (`x'`). Ideally, the reconstructed output (`x'`) is identical to the original input (`x`). """ raise NotImplementedError def forward(self, x: torch.Tensor) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]: mu, logvar = self.encode(x) z = self.reparameterize(mu, logvar) return self.decode(z), mu, logvar, z class SequenceVAE(BaseVAE): """CbAS VAE model for (one-hot) encoded sequences.""" def __init__(self, seqlen: int, vocab_size: int, hidden_size: int = 64, latent_size: int = 20) -> None: super(SequenceVAE, self).__init__() self.seqlen = seqlen self.vocab_size = vocab_size self.hidden_size = hidden_size self.latent_size = latent_size # Probablistic encoder self.fc1 = nn.Linear(seqlen * vocab_size, hidden_size) self.fc21 = nn.Linear(hidden_size, latent_size) self.fc22 = nn.Linear(hidden_size, latent_size) # Probablistic decoder self.fc3 = nn.Linear(latent_size, hidden_size) self.fc4 = nn.Linear(hidden_size, seqlen * vocab_size) # Reshape occurs here (see self.decode()) # size is now: (seqlen * vocab_size) -> (seqlen, vocab_size) self.fc5 = nn.Linear(vocab_size, vocab_size) def encode(self, x: torch.Tensor) -> Tuple[torch.Tensor, torch.Tensor]: # Flatten (n, seqlen, vocab_size) -> (n, seqlen * vocab_size) x = x.view(x.size(0), -1) h1 = F.relu(self.fc1(x)) return self.fc21(h1), self.fc22(h1) def decode(self, z: torch.Tensor) -> torch.Tensor: # Input tensor: Latent vector z = (num_samples, latent_size) h3 = F.relu(self.fc3(z)) h4 = self.fc4(h3) reshaped = h4.view(h4.size(0), self.seqlen, self.vocab_size) # Return logits since F.cross_entropy computes log_softmax internally return self.fc5(reshaped)

36.116071

90

0.634611

3,904

0.965142

0

1,979

0.489246

8d2ae38a47c725cb399a9f327008d51a718980eb

2,037

py

Python

backend/export/views.py

dmryutov/otus-python-0319-final

de07f36ee4bbd57dbfb16defaf762b08ec41fb0e

[ "Apache-2.0" ]

null

backend/export/views.py

dmryutov/otus-python-0319-final

de07f36ee4bbd57dbfb16defaf762b08ec41fb0e

[ "Apache-2.0" ]

6

2020-06-05T23:05:14.000Z

2022-02-10T10:42:31.000Z

backend/export/views.py

dmryutov/otus-python-0319-final

de07f36ee4bbd57dbfb16defaf762b08ec41fb0e

[ "Apache-2.0" ]

null

from django.http.response import HttpResponse from rest_framework import serializers, viewsets from rest_framework.decorators import action from rest_framework.permissions import IsAuthenticated from .excel import Excel XLSX_MIME = 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet' class ExportViewSet(viewsets.GenericViewSet): serializer_class = serializers.Serializer permission_classes = (IsAuthenticated,) @staticmethod def download_file(file_name, export_func, *args, **kwargs): """ Generate file and send it to client Args: file_name (str): Excel file name export_func (str): Export function args: Export function args kwargs: Export function kwargs Returns: django.http.response.HttpResponse: HTTP response """ response = HttpResponse(content_type=XLSX_MIME) response['Content-Disposition'] = 'attachment; filename="{}.xlsx"'.format(file_name) getattr(Excel(file_name), export_func)(*args, **kwargs).save(response) return response @action(methods=['post'], detail=False) def stl(self, request): """ Export time series decomposition results to Excel file """ self.check_permissions(request) data = request.data.get('data', []) result = request.data.get('result', {}) return self.download_file('STL', 'export_stl', data, result) @action(methods=['post'], detail=False) def forecast(self, request): """ Export time series forecasting results to Excel file """ self.check_permissions(request) data = request.data.get('data', []) result = request.data.get('result', {}) date_start = request.data.get('date_start', '2018-01-01') period_type = request.data.get('period_type', 'W') return self.download_file('Forecast', 'export_forecast', data, result, date_start, period_type)

32.333333

92

0.650957

1,731

0.849779

0

1,578

0.774669

0

725

0.355916

8d2b9627ee560b695980d399a9b852afb9663aac

1,593

py

Python

tests/test_clamp.py

josemolinagarcia/maya-math-nodes

1f83eef1d1efe0b0c3dbb1477ca31ed9f8911ee4

[ "MIT" ]

148

2018-01-12T20:30:45.000Z

2022-02-28T05:20:46.000Z

tests/test_clamp.py

josemolinagarcia/maya-math-nodes

1f83eef1d1efe0b0c3dbb1477ca31ed9f8911ee4

[ "MIT" ]

13

2018-01-17T18:02:13.000Z

2021-11-23T06:06:24.000Z

tests/test_clamp.py

josemolinagarcia/maya-math-nodes

1f83eef1d1efe0b0c3dbb1477ca31ed9f8911ee4

[ "MIT" ]

41

2018-01-16T01:41:29.000Z

2021-08-24T01:27:56.000Z

# Copyright (c) 2018 Serguei Kalentchouk et al. All rights reserved. # Use of this source code is governed by an MIT license that can be found in the LICENSE file. from node_test_case import NodeTestCase, cmds class TestClamp(NodeTestCase): def test_clamp(self): node = self.create_node('Clamp', {'input': 5.0, 'inputMin': 0.0, 'inputMax': 2.0}, 2.0) cmds.setAttr('{0}.{1}'.format(node, 'input'), -1.0) self.assertAlmostEqual(cmds.getAttr('{0}.output'.format(node)), 0.0) def test_clamp_int(self): node = self.create_node('ClampInt', {'input': 5, 'inputMin': 0, 'inputMax': 2}, 2) cmds.setAttr('{0}.{1}'.format(node, 'input'), -1) self.assertAlmostEqual(cmds.getAttr('{0}.output'.format(node)), 0) def test_clamp_angle(self): node = self.create_node('ClampAngle', {'input': 5.0, 'inputMin': 0.0, 'inputMax': 2.0}, 2.0) cmds.setAttr('{0}.{1}'.format(node, 'input'), -1.0) self.assertAlmostEqual(cmds.getAttr('{0}.output'.format(node)), 0.0) def test_remap(self): self.create_node('Remap', {'input': 0.5, 'low1': 0.0, 'high1': 1.0, 'low2': 0.0, 'high2': 10.0}, 5.0) def test_remap_angle(self): self.create_node('RemapAngle', {'input': 0.5, 'low1': 0.0, 'high1': 1.0, 'low2': 0.0, 'high2': 10.0}, 5.0) def test_remap_int(self): self.create_node('RemapInt', {'input': 5, 'low1': 0, 'high1': 10, 'low2': 0, 'high2': 100}, 50) def test_smoothstep(self): self.create_node('Smoothstep', {'input': 0.3}, 0.216)

44.25

114

0.595731

1,380

0.86629

0

503

0.315756

8d2bec83c642f547afb331d447ae8ff19041fd5a

1,111

py

Python

src/tests/tests_get_formatted_items.py

kazqvaizer/checklistbot

f715280fbe7035bc2ce4f69cbf95595d9fe3a225

[ "MIT" ]

5

2020-10-06T13:42:45.000Z

2021-12-21T07:35:08.000Z

src/tests/tests_get_formatted_items.py

kazqvaizer/checklistbot

f715280fbe7035bc2ce4f69cbf95595d9fe3a225

[ "MIT" ]

null

src/tests/tests_get_formatted_items.py

kazqvaizer/checklistbot

f715280fbe7035bc2ce4f69cbf95595d9fe3a225

[ "MIT" ]

null

import pytest from models import TodoItem pytestmark = [ pytest.mark.usefixtures("use_db"), ] @pytest.fixture def chat(factory): return factory.chat() @pytest.fixture def items(factory, chat): return [ factory.item(chat=chat, text="Hello"), factory.item(chat=chat, text="Nice!"), ] def test_format_without_strike(items, chat): lines = chat.get_formatted_items().split("\n") assert len(lines) == 2 assert "1. Hello" == lines[0] assert "2. Nice!" == lines[1] def test_format_with_strike(items, chat): items[0].is_checked = True items[0].save() lines = chat.get_formatted_items().split("\n") assert len(lines) == 2 assert "<s>1. Hello</s>" == lines[0] assert "2. Nice!" == lines[1] def test_respect_order_by_id(items, chat): TodoItem.update(id=100500).where(TodoItem.id == items[0].id).execute() lines = chat.get_formatted_items().split("\n") assert len(lines) == 2 assert "1. Nice!" == lines[0] assert "2. Hello" == lines[1] def test_no_items_is_okay(chat): assert chat.get_formatted_items() == ""

20.574074

74

0.640864

0

214

0.192619

0

103

0.092709

8d2cd1060b91fea7d66c9afe4a0c6e646802593b

3,945

py

Python

web/multilingual/database.py

mahoyen/web

1d190a86e3277315804bfcc0b8f9abd4f9c1d780

[ "MIT" ]

null

web/multilingual/database.py

mahoyen/web

1d190a86e3277315804bfcc0b8f9abd4f9c1d780

[ "MIT" ]

null

web/multilingual/database.py

mahoyen/web

1d190a86e3277315804bfcc0b8f9abd4f9c1d780

[ "MIT" ]

null

import copy import json from django.contrib import admin from django.db import models from web.multilingual.data_structures import MultiLingualTextStructure from web.multilingual.form import MultiLingualFormField, MultiLingualRichTextFormField, \ MultiLingualRichTextUploadingFormField from web.multilingual.widgets import MultiLingualTextInput, MultiLingualRichText, MultiLingualRichTextUploading class MultiLingualTextField(models.TextField): """ A database field for multilingual text fields """ widget = MultiLingualTextInput form_class = MultiLingualFormField use_default_if_empty = True def __init__(self, *args, **kwargs): # Allow for specification of a widget on creation, to allow for both textarea and text input self.widget = kwargs.pop("widget", self.widget) self.use_default_if_empty = kwargs.pop("use_default_if_empty", self.use_default_if_empty) super().__init__(*args, **kwargs) def to_python(self, value): """ Deserialization of the given value """ if value is None: return value if isinstance(value, MultiLingualTextStructure): return value return MultiLingualTextStructure(value, self.use_default_if_empty) def get_prep_value(self, value): """ Converts the given value to a value that can be saved in the database """ if value is None: return value if isinstance(value, MultiLingualTextStructure): # Save the content as a JSON object with languages as keys return json.dumps({language: value[language] for language in value.supported_languages}) return value def from_db_value(self, value, expression, connection): """ Converts the database value to the python representation """ return MultiLingualTextStructure(value, self.use_default_if_empty) def formfield(self, **kwargs): """ Sets up the form field """ defaults = {"form_class": self.form_class, "widget": self.widget} defaults.update(kwargs) return super().formfield(**defaults) class MultiLingualRichTextField(MultiLingualTextField): # CKEditor has specific requirements for its for form class and widget widget = MultiLingualRichText form_class = MultiLingualRichTextFormField class MultiLingualRichTextUploadingField(MultiLingualTextField): # CKEditor has specific requirements for its for form class and widget widget = MultiLingualRichTextUploading form_class = MultiLingualRichTextUploadingFormField class MultiLingualFieldAdmin(admin.ModelAdmin): """ Django admin does not render MultiValue fields correctly. This ModelAdmin object overrides the default Django admin rendering of the MultiLingual fields. """ def formfield_for_dbfield(self, db_field, request, **kwargs): # Want to override the Django admin fields if isinstance(db_field, MultiLingualTextField): properties = {} for key, value in db_field.widget.__dict__.items(): try: # Need to perform deep copies in case of mutable properties properties[key] = copy.deepcopy(value) except TypeError: # Some class properties are not possible to copy. These will not be mutable anyways properties[key] = value # Want to copy widget, as to not override the template for the normal forms widget = type("AdminMultiLingualTextField", (db_field.widget,), properties) # Different template for admin page, without Semantic UI widget.template_name = "web/forms/widgets/admin_multi_lingual_text_field.html" return db_field.formfield(widget=widget, **kwargs) return super().formfield_for_dbfield(db_field, request, **kwargs)

39.848485

119

0.694043

3,529

0.89455

0

1,249

0.316603

8d2fec927240532eb03988da6b6277edf3bec73d

2,859

py

Python

cart/tests/test_views.py

mohsenamoon1160417237/ECommerce-app

4cca492214b04b56f625aef2a2979956a8256710

[ "MIT" ]

null

cart/tests/test_views.py

mohsenamoon1160417237/ECommerce-app

4cca492214b04b56f625aef2a2979956a8256710

[ "MIT" ]

null

cart/tests/test_views.py

mohsenamoon1160417237/ECommerce-app

4cca492214b04b56f625aef2a2979956a8256710

[ "MIT" ]

null

from django.test import TestCase from shop.models import Product from django.contrib.auth.models import User from coupons.forms import CouponForm class CartAddViewTest(TestCase): def setUp(self): self.data = {"quantity" : 2, "update" : False} self.product = Product.objects.create(name='clothes', description='clothes', price=12.00 ) self.product.save() self.user = User.objects.create(username='mohsen' , email='[email protected]' , password='mohsen1160417237') self.user.save() self.url = '/cart/add/{}/'.format(self.product.id) def test_get_method_not_allowed(self): response = self.client.get(self.url , follow=True) self.assertEqual(response.status_code , 405) def test_cart_add_user_authenticated(self): self.client.force_login(self.user) response = self.client.post(self.url , data=self.data , follow=True) redirect_url = response.request['PATH_INFO'] self.assertEqual(response.status_code , 200) self.assertEqual(redirect_url , '/cart/detail/') def test_cart_add_user_not_authenticated(self): self.client.logout() response = self.client.post(self.url , data=self.data , follow=True) redirect_url = response.request['PATH_INFO'] self.assertEqual(response.status_code , 200) self.assertEqual(redirect_url , '/account/login/') class CartRemoveViewTest(TestCase): def setUp(self): self.product = Product.objects.create(name='clothes', description='clothes', price=12.00 ) self.product.save() self.url = '/cart/remove/{}/'.format(self.product.id) def test_get_method_not_allowed(self): response = self.client.get(self.url , follow=True) self.assertEqual(response.status_code , 405) def test_cart_remove_ok(self): response = self.client.post(self.url , follow=True) redirect_url = response.request['PATH_INFO'] self.assertEqual(response.status_code , 200) self.assertEqual(redirect_url , '/cart/detail/') class CartDetailViewTest(TestCase): def setUp(self): self.data = {''} self.url = '/cart/detail/' def test_cart_detail_ok(self): response = self.client.post(self.url) self.assertEqual(response.status_code , 200)

28.878788

77

0.550892

2,679

0.937041

0

233

0.081497

8d341997147380f82b39848b173c8f836285f331

2,134

py

Python

tests/conftest.py

gpontesss/botus_receptus

bf29f5f70a2e7ae3548a44287c636515f78e7e77

[ "BSD-3-Clause" ]

3

2019-04-15T01:45:46.000Z

2020-04-07T13:31:19.000Z

tests/conftest.py

gpontesss/botus_receptus

bf29f5f70a2e7ae3548a44287c636515f78e7e77

[ "BSD-3-Clause" ]

244

2020-04-20T22:10:23.000Z

2022-03-31T23:03:48.000Z

tests/conftest.py

gpontesss/botus_receptus

bf29f5f70a2e7ae3548a44287c636515f78e7e77

[ "BSD-3-Clause" ]

1

2021-11-08T08:52:32.000Z

from __future__ import annotations import asyncio from typing import Any import asynctest.mock # type: ignore import pytest # type: ignore import pytest_mock._util # type: ignore pytest_mock._util._mock_module = asynctest.mock class EventLoopClockAdvancer: """ A helper object that when called will advance the event loop's time. If the call is awaited, the caller task will wait an iteration for the update to wake up any awaiting handlers. """ __slots__ = ("offset", "loop", "sleep_duration", "_base_time") def __init__(self, loop, sleep_duration=1e-4): self.offset = 0.0 self._base_time = loop.time self.loop = loop self.sleep_duration = sleep_duration # incorporate offset timing into the event loop self.loop.time = self.time def time(self): """ Return the time according to the event loop's clock. The time is adjusted by an offset. """ return self._base_time() + self.offset async def __call__(self, seconds): """ Advance time by a given offset in seconds. Returns an awaitable that will complete after all tasks scheduled for after advancement of time are proceeding. """ # sleep so that the loop does everything currently waiting await asyncio.sleep(self.sleep_duration) if seconds > 0: # advance the clock by the given offset self.offset += seconds # Once the clock is adjusted, new tasks may have just been # scheduled for running in the next pass through the event loop await asyncio.sleep(self.sleep_duration) @pytest.fixture def advance_time(event_loop): return EventLoopClockAdvancer(event_loop) @pytest.fixture def mock_aiohttp(mocker: Any) -> None: mocker.patch('aiohttp.ClientSession', autospec=True) @pytest.fixture def mock_discord_bot(mocker: Any) -> None: mocker.patch('discord.ext.commands.Bot') @pytest.fixture(autouse=True) def add_async_mocks(mocker: Any) -> None: mocker.CoroutineMock = mocker.mock_module.CoroutineMock

28.837838

79

0.680412

1,450

0.679475

0

436

0.204311

666

0.31209

915

0.428772

8d352ba96be56207cce46e2dc458765a09de6f97

1,247

py

Python

Shark_Training/pyimagesearch/preprocessing/meanpreprocessor.py

crpurcell/MQ_DPI_Release

97444513e8b8d48ec91ff8a43b9dfaed0da029f9

[ "MIT" ]

null

Shark_Training/pyimagesearch/preprocessing/meanpreprocessor.py

crpurcell/MQ_DPI_Release

97444513e8b8d48ec91ff8a43b9dfaed0da029f9

[ "MIT" ]

null

Shark_Training/pyimagesearch/preprocessing/meanpreprocessor.py

crpurcell/MQ_DPI_Release

97444513e8b8d48ec91ff8a43b9dfaed0da029f9

[ "MIT" ]

null

#=============================================================================# # # # MODIFIED: 15-Jan-2019 by C. Purcell # # # #=============================================================================# import cv2 #-----------------------------------------------------------------------------# class MeanPreprocessor: def __init__(self, rMean, gMean, bMean, rgbOrder=True): self.rMean = rMean self.gMean = gMean self.bMean = bMean self.rgbOrder = rgbOrder def preprocess(self, image): # Split the image into its respective RGB channels if self.rgbOrder: (R, G, B) = cv2.split(image.astype("float32")) else: (B, G, R) = cv2.split(image.astype("float32")) # Subtract the means for each channel R -= self.rMean G -= self.gMean B -= self.bMean # Merge the channels back together and return the image if self.rgbOrder: return cv2.merge([R, G, B]) else: return cv2.merge([B, G, R])

35.628571

79

0.36648

753

0.603849

0

634

0.50842

8d36012ec39c8b5de0335c08778adaf22f20af3c

985

py

Python

aiida_quantumespresso/parsers/constants.py

unkcpz/aiida-quantumespresso

fbac0993bb8b6cdeba85717453debcf0ab062b5a

[ "MIT" ]

null

aiida_quantumespresso/parsers/constants.py

unkcpz/aiida-quantumespresso

fbac0993bb8b6cdeba85717453debcf0ab062b5a

[ "MIT" ]

null

aiida_quantumespresso/parsers/constants.py

unkcpz/aiida-quantumespresso

fbac0993bb8b6cdeba85717453debcf0ab062b5a

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Physical or mathematical constants. Since every code has its own conversion units, this module defines what QE understands as for an eV or other quantities. Whenever possible, we try to use the constants defined in :py:mod:aiida.common.constants:, but if some constants are slightly different among different codes (e.g., different standard definition), we define the constants in this file. """ from aiida.common.constants import ( ang_to_m, bohr_si, bohr_to_ang, hartree_to_ev, invcm_to_THz, ry_si, ry_to_ev, timeau_to_sec, ) # From the definition of Quantum ESPRESSO, conversion from atomic mass # units to Rydberg units: # REAL(DP), PARAMETER :: AMU_SI = 1.660538782E-27_DP ! Kg # REAL(DP), PARAMETER :: ELECTRONMASS_SI = 9.10938215E-31_DP ! Kg # REAL(DP), PARAMETER :: AMU_AU = AMU_SI / ELECTRONMASS_SI # REAL(DP), PARAMETER :: AMU_RY = AMU_AU / 2.0_DP amu_Ry = 911.4442421323

31.774194

77

0.700508

0

786

0.79797

8d3e794674c7c132a4877a4a375649bf2399c45b

2,639

py

Python

venv/lib/python3.8/site-packages/keras/api/_v2/keras/applications/__init__.py

JIANG-CX/data_labeling

8d2470bbb537dfc09ed2f7027ed8ee7de6447248

[ "MIT" ]

1

2021-05-24T10:08:51.000Z

venv/lib/python3.8/site-packages/keras/api/_v2/keras/applications/__init__.py

JIANG-CX/data_labeling

8d2470bbb537dfc09ed2f7027ed8ee7de6447248

[ "MIT" ]

null

venv/lib/python3.8/site-packages/keras/api/_v2/keras/applications/__init__.py

JIANG-CX/data_labeling

8d2470bbb537dfc09ed2f7027ed8ee7de6447248

[ "MIT" ]

null

# This file is MACHINE GENERATED! Do not edit. # Generated by: tensorflow/python/tools/api/generator/create_python_api.py script. """Public API for tf.keras.applications namespace. """ from __future__ import print_function as _print_function import sys as _sys from keras.api._v2.keras.applications import densenet from keras.api._v2.keras.applications import efficientnet from keras.api._v2.keras.applications import imagenet_utils from keras.api._v2.keras.applications import inception_resnet_v2 from keras.api._v2.keras.applications import inception_v3 from keras.api._v2.keras.applications import mobilenet from keras.api._v2.keras.applications import mobilenet_v2 from keras.api._v2.keras.applications import mobilenet_v3 from keras.api._v2.keras.applications import nasnet from keras.api._v2.keras.applications import resnet from keras.api._v2.keras.applications import resnet50 from keras.api._v2.keras.applications import resnet_v2 from keras.api._v2.keras.applications import vgg16 from keras.api._v2.keras.applications import vgg19 from keras.api._v2.keras.applications import xception from keras.applications.densenet import DenseNet121 from keras.applications.densenet import DenseNet169 from keras.applications.densenet import DenseNet201 from keras.applications.efficientnet import EfficientNetB0 from keras.applications.efficientnet import EfficientNetB1 from keras.applications.efficientnet import EfficientNetB2 from keras.applications.efficientnet import EfficientNetB3 from keras.applications.efficientnet import EfficientNetB4 from keras.applications.efficientnet import EfficientNetB5 from keras.applications.efficientnet import EfficientNetB6 from keras.applications.efficientnet import EfficientNetB7 from keras.applications.inception_resnet_v2 import InceptionResNetV2 from keras.applications.inception_v3 import InceptionV3 from keras.applications.mobilenet import MobileNet from keras.applications.mobilenet_v2 import MobileNetV2 from keras.applications.mobilenet_v3 import MobileNetV3Large from keras.applications.mobilenet_v3 import MobileNetV3Small from keras.applications.nasnet import NASNetLarge from keras.applications.nasnet import NASNetMobile from keras.applications.resnet import ResNet101 from keras.applications.resnet import ResNet152 from keras.applications.resnet import ResNet50 from keras.applications.resnet_v2 import ResNet101V2 from keras.applications.resnet_v2 import ResNet152V2 from keras.applications.resnet_v2 import ResNet50V2 from keras.applications.vgg16 import VGG16 from keras.applications.vgg19 import VGG19 from keras.applications.xception import Xception del _print_function

47.981818

82

0.869269

0

182

0.068966

8d3ebf8c27b4787edb5db6336b9fad286f003b92

97

py

Python

flash/vision/embedding/__init__.py

alvin-chang/lightning-flash

481d4d369ff0a5d8c2b2d9e4970c5608a92b3ff5

[ "Apache-2.0" ]

2

2021-06-25T08:42:36.000Z

2021-06-25T08:49:29.000Z

flash/vision/embedding/__init__.py

alvin-chang/lightning-flash

481d4d369ff0a5d8c2b2d9e4970c5608a92b3ff5

[ "Apache-2.0" ]

null

flash/vision/embedding/__init__.py

alvin-chang/lightning-flash

481d4d369ff0a5d8c2b2d9e4970c5608a92b3ff5

[ "Apache-2.0" ]

null

from flash.vision.embedding.image_embedder_model import ImageEmbedder, ImageEmbedderDataPipeline

48.5

96

0.907216

0

8d3f8941dd6434ce1537415533cd51f289916f52

5,554

py

Python

configstruct/config_struct.py

bradrf/configstruct

aeea8fbba1e2daa0a0c38eeb9622d1716c0bb3e8

[ "MIT" ]

null

configstruct/config_struct.py

bradrf/configstruct

aeea8fbba1e2daa0a0c38eeb9622d1716c0bb3e8

[ "MIT" ]

16

2016-10-13T09:53:46.000Z

2022-03-24T15:04:51.000Z

configstruct/config_struct.py

bradrf/configstruct

aeea8fbba1e2daa0a0c38eeb9622d1716c0bb3e8

[ "MIT" ]

null

import os import sys import logging from configparser import ConfigParser from .open_struct import OpenStruct from .section_struct import SectionStruct # TODO: use file lock when read/write def choose_theirs(section, option, mine, theirs): '''Always prefer values for keys from file.''' return theirs def choose_mine(section, option, mine, theirs): '''Always prefer values for keys in memory.''' return mine LOG_LEVELS = ['debug-all', 'debug', 'info', 'warning', 'error', 'critical'] LOG_OPTIONS = {'log_level': 'info', 'log_file': 'STDERR'} class OtherLoggingFilter(logging.Filter): '''Quell logs from other modules using a different minimum level.''' def __init__(self, whitelisted_module, minimum_other_level): super(self.__class__, self).__init__(whitelisted_module) self._minimum_other_level = minimum_other_level def filter(self, record): rc = super(self.__class__, self).filter(record) if rc != 0: return rc # matched the whitelisted module return record.levelno >= self._minimum_other_level class ConfigStruct(OpenStruct): '''Provides simplified access for managing typed configuration options saved in a file. :param config_file: path to file that should house configuration items. :param log_options_parent: option key to use if this instance is expected to use the `LOG_OPTIONS` default values and allow configuration of basic logging :param sections_defaults: options that are provided as defaults (will be overridden by any options read from the `config_file`) ''' def __init__(self, config_file, log_options_parent=None, **sections_defaults): super(ConfigStruct, self).__init__() self._config_file = config_file self._log_options_parent = log_options_parent if log_options_parent: parent_options = sections_defaults.get(log_options_parent, {}) sections_defaults[log_options_parent] = LOG_OPTIONS.copy() sections_defaults[log_options_parent].update(parent_options) for (name, items) in sections_defaults.items(): self[name] = SectionStruct(name, **items) self._load(choose_theirs) # because above were basic defaults for the keys def configure_basic_logging(self, main_module_name, **kwargs): '''Use common logging options to configure all logging. Basic logging configuration is used to set levels for all logs from the main module and to filter out logs from other modules unless they are of one level in priority higher. :param main_module_name: name of the primary module for normal logging ''' if not self._log_options_parent: raise ValueError('Missing log_options_parent') options = self[self._log_options_parent] log_level_index = LOG_LEVELS.index(options.log_level) log_kwargs = { 'level': getattr(logging, options.log_level.upper()), 'format': '[%(asctime)s #%(process)d] %(levelname)-8s %(name)-12s %(message)s', 'datefmt': '%Y-%m-%dT%H:%M:%S%z', } if options.log_file == 'STDERR': log_kwargs['stream'] = sys.stderr elif options.log_file == 'STDOUT': log_kwargs['stream'] = sys.stdout else: log_kwargs['filename'] = options.log_file log_kwargs.update(kwargs) # allow overrides from caller logging.basicConfig(**log_kwargs) # now filter out any other module's logging unless it's one level above the main other_log_level = getattr(logging, LOG_LEVELS[log_level_index + 1].upper()) other_filter = OtherLoggingFilter(main_module_name, other_log_level) for handler in logging.root.handlers: handler.addFilter(other_filter) def save(self, conflict_resolver=choose_mine): '''Save all options in memory to the `config_file`. Options are read once more from the file (to allow other writers to save configuration), keys in conflict are resolved, and the final results are written back to the file. :param conflict_resolver: a simple lambda or function to choose when an option key is provided from an outside source (THEIRS, usually a file on disk) but is also already set on this ConfigStruct (MINE) ''' config = self._load(conflict_resolver) # in case some other process has added items with open(self._config_file, 'wb') as cf: config.write(cf) ###################################################################### # private def _load(self, resolver): config = ConfigParser() if os.path.exists(self._config_file): with open(self._config_file) as cf: config.readfp(cf) # use readfp as read somehow circumvents mockfs in tests loaded = self._sync_sections_with(config, resolver) self._add_new_sections(config, loaded) return config def _sync_sections_with(self, config, resolver): loaded = set() for name in config.sections(): if name not in self: self[name] = SectionStruct(name) self[name].sync_with(config, resolver) loaded.add(name) return loaded def _add_new_sections(self, config, seen): for name in self: if name not in seen: self[name].sync_with(config, choose_mine) # new ones, so always "mine"

40.540146

100

0.659705

4,982

0.897011

0

2,203

0.396651

8d4042ed9b0586457ce903d2cc6db6a880c03485

10,327

py

Python

test_apps/python_app/tests/compiler_test.py

Origen-SDK/o2

5b0f9a6d113ddebc73c7ee224931e8b2d0301794

[ "MIT" ]

null

test_apps/python_app/tests/compiler_test.py

Origen-SDK/o2

5b0f9a6d113ddebc73c7ee224931e8b2d0301794

[ "MIT" ]

127

2019-11-23T17:09:35.000Z

2021-09-02T11:06:20.000Z

test_apps/python_app/tests/compiler_test.py

Origen-SDK/o2

5b0f9a6d113ddebc73c7ee224931e8b2d0301794

[ "MIT" ]

null

import origen # pylint: disable=import-error import pytest, pathlib, os, stat, abc from os import access, W_OK, X_OK, R_OK from tests.shared import clean_falcon, clean_compiler, tmp_dir def user_compiler(): ''' End users should access the compiler via ``origen.app.compiler``. ''' return origen.app.compiler MakoRenderer = origen.compiler.MakoRenderer # JinjaRenderer = origen.compiler.JinjaRenderer def test_compiler_inits(clean_falcon): assert isinstance(user_compiler(), origen.compiler.Compiler) == True assert user_compiler().stack == [] assert user_compiler().renders == [] assert user_compiler().output_files == [] assert 'mako' in user_compiler().renderers assert user_compiler().renderers['mako'] is MakoRenderer def test_copmiler_selects_appropriate_syntax(clean_falcon): test = "myfile.txt.mako" assert user_compiler().select_syntax(test) == 'mako' assert user_compiler().select_syntax(pathlib.Path(test)) == 'mako' test = "myfile.txt.jinja" assert user_compiler().select_syntax(test) == 'jinja' assert user_compiler().select_syntax(pathlib.Path(test)) == 'jinja' test = "myfile.txt" assert user_compiler().select_syntax(test) is None assert user_compiler().select_syntax(pathlib.Path(test)) is None def test_compiler_text_render_requires_syntax(clean_falcon): with pytest.raises(origen.compiler.ExplicitSyntaxRequiredError): user_compiler().render("Test...", direct_src=True) class FixtureCompilerTest(abc.ABC): ''' Fixture conformance testing the child renderer ''' @property @abc.abstractclassmethod def extension(cls): raise NotImplementedError @property @abc.abstractclassmethod def syntax(cls): raise NotImplementedError @property def str_render(self): return "Hello " + self.templatify('"Origen"') + "!" @property def str_render_with_standard_context(self): return f"Hello from Origen version {self.templatify('origen.version')}!" @property def str_render_with_additional_context(self): return f"Hello from template compiler \"{self.templatify('test_renderer_name')}\"!" @property def expected_str_render(self): return "Hello Origen!" @property def expected_str_render_with_standard_context(self): # Make sure origen.version isn't woefully broken assert isinstance(origen.version, str) assert len(origen.version) > 0 return f"Hello from Origen version {origen.version}!" @property def expected_str_render_with_additional_context(self): return f"Hello from template compiler \"{self.syntax}\"!" @property def dummy_input_filename(self): return pathlib.Path( str(self.expected_output_filename) + f'.{self.extension}') @property def expected_output_filename(self): return tmp_dir().joinpath(f'test_file.txt') @property def expected_default_output_filename(self): s = user_compiler().renderers[self.syntax] return origen.app.output_dir.joinpath(f'compiled/test_file.txt') @property def input_filename(self): return origen.root.joinpath('templates/dut_info.txt' + f'.{self.extension}') @property def output_filename(self): return tmp_dir().joinpath('dut_info.txt') @property def expected_dut_info_output(self): return "\n".join([ self.expected_str_render_with_standard_context, self.expected_str_render_with_additional_context, 'The application name is "example"' ]) def test_compiler_resolves_default_filenames(self): # Test as string f = str(self.dummy_input_filename) r = user_compiler().resolve_filename(f) assert r == self.expected_default_output_filename # Test as pathlib.Path assert user_compiler().resolve_filename( self.dummy_input_filename) == self.expected_default_output_filename def test_compiler_resolves_filenames(self): # Test as string assert user_compiler().resolve_filename( str(self.dummy_input_filename), output_dir=tmp_dir()) == self.expected_output_filename # Test as pathlib.Path assert user_compiler().resolve_filename( self.dummy_input_filename, output_dir=tmp_dir()) == self.expected_output_filename @property def additional_context(self): return {'test_renderer_name': self.syntax} def test_render_file(self): ''' Test that the renderer can render a given file ''' rendered = user_compiler().render(self.input_filename, syntax=self.syntax, direct_src=False, output_dir=tmp_dir(), context=self.additional_context) assert isinstance(rendered, pathlib.Path) assert rendered == self.output_filename assert rendered.exists assert open(rendered, 'r').read() == self.expected_dut_info_output def test_render_str(self): ''' Test that the renderer can render a given string ''' rendered = user_compiler().render(self.str_render, syntax=self.syntax, direct_src=True) assert rendered == self.expected_str_render def test_render_with_standard_context(self): ''' Renders output using the standard context ''' rendered = user_compiler().render( self.str_render_with_standard_context, syntax=self.syntax, direct_src=True) assert rendered == self.expected_str_render_with_standard_context def test_render_with_additional_context(self): ''' Renders output using additional context given as an option -> Test that the renderer supports the 'additional_context' option ''' rendered = user_compiler().render( self.str_render_with_additional_context, syntax=self.syntax, direct_src=True, context={'test_renderer_name': self.syntax}) assert rendered == self.expected_str_render_with_additional_context @abc.abstractclassmethod def templatify(self, input): raise NotImplementedError class TestMakoCompiler(FixtureCompilerTest): extension = 'mako' syntax = 'mako' def templatify(self, input): return "${" + input + "}" # class TestJinjaCompiler: # pass class TestCompilerStack(): ''' Tests the compiler's stack-like interface ''' test_cases = TestMakoCompiler() ''' Borrow the Mako test cases for use here ''' def test_compiler_can_accept_requests(self, clean_falcon, clean_compiler): ''' Push can accept either a straight pathlib.Path or str object (interpreted as a file) or a tuple consisting of a 'src' and 'options' ''' assert len(user_compiler().stack) == 0 user_compiler().push('test.mako') assert len(user_compiler().stack) == 1 assert isinstance(user_compiler().stack[0], tuple) assert isinstance(user_compiler().stack[0][0], list) assert isinstance(user_compiler().stack[0][0][0], pathlib.Path) assert user_compiler().stack[0][1] == {} def test_compiler_can_clear_itself(self): assert len(user_compiler().stack) > 0 user_compiler().clear() assert user_compiler().stack == [] assert user_compiler().renders == [] assert user_compiler().output_files == [] def test_compiler_renders_text(self, clean_falcon, clean_compiler): origen.app.compile(self.test_cases.str_render, direct_src=True, syntax='mako') assert len(user_compiler().renders) == 1 assert len(user_compiler().stack) == 0 assert user_compiler( ).renders[0] == self.test_cases.expected_str_render origen.app.compile(self.test_cases.str_render_with_additional_context, context=self.test_cases.additional_context, direct_src=True, syntax='mako') assert len(user_compiler().renders) == 2 assert len(user_compiler().stack) == 0 assert user_compiler().renders[ 1] == self.test_cases.expected_str_render_with_additional_context assert user_compiler().renders[-1] == user_compiler().last_render def test_compiler_text_render_requires_syntax(self, clean_falcon, clean_compiler): assert len(user_compiler().stack) == 0 with pytest.raises(origen.compiler.ExplicitSyntaxRequiredError): origen.app.compile(self.test_cases.str_render, direct_src=True) def test_compiler_returns_templates_dir(self): assert user_compiler().templates_dir == origen.app.root.joinpath( 'templates') def test_compiler_renders_files(self, clean_falcon, clean_compiler): origen.app.compile('dut_info.txt.mako', output_dir=tmp_dir(), context=self.test_cases.additional_context, templates_dir=user_compiler().templates_dir) assert len(user_compiler().stack) == 0 assert len(user_compiler().output_files) == 1 compiled_file = user_compiler().output_files[0] compiled_file_status = os.stat(compiled_file) assert isinstance(compiled_file, pathlib.PurePath) == True assert compiled_file.exists() == True assert access(compiled_file, R_OK) == True # Check file permissions assert bool(compiled_file_status.st_mode & stat.S_IRUSR) == True assert bool(compiled_file_status.st_mode & stat.S_IWUSR) == True assert bool(compiled_file_status.st_mode & stat.S_IWUSR) == True

39.117424

97

0.637165

8,743

0.846616

0

2,216

0.214583

0

1,614

0.156289

8d42c2702dd5a391e27f8a389f8a934778ba0c95

999

py

Python

api/api.py

devSessions/crvi

1ecc68d6c968294bcc5ceea747604ee237f6080c

[ "MIT" ]

25

2017-12-31T06:51:54.000Z

2021-11-17T11:29:30.000Z

api/api.py

amittomar-1/crvi

1ecc68d6c968294bcc5ceea747604ee237f6080c

[ "MIT" ]

23

2020-01-28T21:34:12.000Z

2022-03-11T23:11:54.000Z

api/api.py

amittomar-1/crvi

1ecc68d6c968294bcc5ceea747604ee237f6080c

[ "MIT" ]

11

2018-01-04T12:30:33.000Z

2020-12-01T18:08:59.000Z

from flask import Flask, jsonify, request import predict import socket app = Flask(__name__) @app.route('/') @app.route('/home') def home(): """Renders the home page.""" return ( "Welcome Guest!!!" ) #to spedicy route after url @app.route('/api', methods=['POST']) def get_tasks(): #get url from form # url = request.form['url'] url = request.files['url'] #sends url for prediction sender = predict.predict(url) #get values from prediction rec = sender.predict_only() # #list of out values # outputlist=[rec] # #for multiple json apis # tasks = [] # tasks1 = [ # { # 'value': outputlist[0], # }, # ] # tasks.append(tasks1) # return jsonify({'tasks': tasks}) return jsonify({'cash': rec}) if __name__ == '__main__': #for remote host ip = socket.gethostbyname(socket.gethostname()) app.run(port=5000,host=ip) #for local host #app.run(debug=True, port=5000)

19.211538

51

0.58959

0

684

0.684685

0

470

0.47047

8d4484e9d066b90a85e8763af3ea488f55a3ae34

68

py

Python

exe/__init__.py

whisperaven/0ops.exed

ab9f14868fec664fe78edab6fb7eb572b3048c58

[ "MIT" ]

10

2017-03-17T02:15:18.000Z

2019-10-26T23:54:21.000Z

exe/__init__.py

whisperaven/0ops

ab9f14868fec664fe78edab6fb7eb572b3048c58

[ "MIT" ]

1

2017-03-20T03:17:17.000Z

2017-03-20T04:04:26.000Z

exe/__init__.py

whisperaven/0ops

ab9f14868fec664fe78edab6fb7eb572b3048c58

[ "MIT" ]

3

2017-03-17T02:46:23.000Z

2018-04-14T15:49:56.000Z

17

44

0.661765

0

51

0.75

8d4492744de35276bcea0bf1ccb409c9aa59295e

418

py

Python

Special_Viewer.py

Akivamelka/unsupervised_mid_semester

5393185d7b0327bbb7cd4b3700d4d00704a5623f

[ "MIT" ]

null

Special_Viewer.py

Akivamelka/unsupervised_mid_semester

5393185d7b0327bbb7cd4b3700d4d00704a5623f

[ "MIT" ]

null

Special_Viewer.py

Akivamelka/unsupervised_mid_semester

5393185d7b0327bbb7cd4b3700d4d00704a5623f

[ "MIT" ]

null

from Dimension_Reduction import Viewer import pandas as pd view_tool = Viewer() reduc = 'pca' suffix = '5' data_plot = pd.read_csv(f"{reduc}_dim2_{suffix}.csv", delimiter=",") models = ['km', 'fuzz', 'gmm', 'dbsc', 'hier', 'spec' ] for model in models: print(model) labels = pd.read_csv(f"labels_{model}_{suffix}.csv", delimiter=",") view_tool.view_vs_target(data_plot, labels, suffix, model)

32.153846

72

0.669856

0

105

0.251196

8d481fde3510821315275850b3a25299bc9b350d

6,621

py

Python

pytumblr/types.py

9999years/pytumblr

fe9b2fb60866785141fc0deb5a357a773c0f4229

[ "Apache-2.0" ]

null

pytumblr/types.py

9999years/pytumblr

fe9b2fb60866785141fc0deb5a357a773c0f4229

[ "Apache-2.0" ]

null

pytumblr/types.py

9999years/pytumblr

fe9b2fb60866785141fc0deb5a357a773c0f4229

[ "Apache-2.0" ]

null

from collections import UserList from dataclasses import dataclass, field from datetime import datetime from typing import List, Dict, Any, Optional, Type DATE_FORMAT = '%Y-%m-%d %H:%M:%S %Z' def parse_date(tumblr_date: str) -> datetime: return datetime.strptime(tumblr_date, DATE_FORMAT) @dataclass class Link: """ An objects in a _links hash """ href: str type: str @dataclass class NavigationLink(Link): pass @dataclass class ActionLink(Link): method: str query_params: Dict[str, Any] _link_classes = {'navigation': NavigationLink, 'action': ActionLink} @dataclass class Tag: tag: str is_tracked: bool featured: bool thumb_url: Optional[str] = None @dataclass class BaseBlog: name: str updated: int title: str description: str @dataclass class Blog(BaseBlog): url: str @dataclass class BlogInfo(BaseBlog): posts: int ask: bool ask_anon: bool likes: int is_blocked_from_primary: bool @dataclass class UserBlogInfo: url: str title: str primary: bool followers: int tweet: str facebook: str type: str @dataclass class UserInfo: following: int default_post_format: str name: str likes: int blogs: List[UserBlogInfo] def __post_init__(self): self.blogs = [UserBlogInfo(**blog) for blog in self.blogs] @dataclass class Avatar: avatar_url: str @dataclass class Post: id: int type: str blog_name: str post_url: str timestamp: int date: datetime format: str reblog_key: str tags: List[str] total_posts: int blog: Optional[BlogInfo] = None bookmarks: Optional[bool] = None mobile: Optional[bool] = None source_url: Optional[str] = None source_title: Optional[str] = None liked: Optional[bool] = None state: Optional[str] = None is_blocks_post_format: Optional[bool] = None def __new__(cls, *args, **kwargs): if 'blog_name' in kwargs and 'blog' not in kwargs: return DashboardPost(*args, **kwargs) else: return POST_CLASSES[kwargs['type']](*args, **kwargs) def __eq__(self, other): return self.id == other.id def __hash__(self): return hash(self.id) def __post_init__(self): self.date = parse_date(self.date) self.blog = BlogInfo(**self.blog) @dataclass class DashboardPost(Post): blog: None = None @dataclass class Submission(Post): slug: str = None short_url: str = None post_author: Optional[str] = None is_submission: Optional[bool] = True anonymous_name: Optional[str] = None anonymous_email: Optional[str] = None state: Optional[str] = 'submission' @dataclass class LegacyTextPost(Post): title: Optional[str] = None body: Optional[str] = None @dataclass class ImageSize: width: int height: int url: str @dataclass class Photo: caption: str alt_sizes: List[ImageSize] def __post_init__(self): self.alt_sizes = [ImageSize(**size) for size in self.alt_sizes] @dataclass class VerbosePhoto(Photo): original_size: ImageSize width: int height: int url: str def __post_init__(self): self.original_size = ImageSize(**self.original_size) @dataclass class LegacyPhotoPost(Post): """ A photo or photoset post """ caption: Optional[str] = None width: Optional[int] = None height: Optional[int] = None photos: List[Photo] = field(default_factory=list) def __post_init__(self): self.photos = [Photo(**photo) for photo in self.photos] @dataclass class LegacyQuotePost(Post): text: Optional[str] = None # HTML source, not an attribution source: Optional[str] = None @dataclass class LegacyLinkPost(Post): title: Optional[str] = None description: Optional[str] = None url: Optional[str] = None author: Optional[str] = None excerpt: Optional[str] = None publisher: Optional[str] = None photos: List[VerbosePhoto] = field(default_factory=list) def __post_init__(self): self.photos = [VerbosePhoto(**photo) for photo in self.photos] @dataclass class ChatLine: name: str label: str phrase: str @dataclass class LegacyChatPost(Post): title: Optional[str] = None body: Optional[str] = None dialogue: List[ChatLine] = field(default_factory=list) def __post_init__(self): self.dialogue = [ChatLine(**line) for line in self.dialogue] @dataclass class LegacyAudioPost(Post): caption: Optional[str] = None player: Optional[str] = None plays: Optional[int] = None album_art: Optional[str] = None artist: Optional[str] = None album: Optional[str] = None track_name: Optional[str] = None track_number: Optional[int] = None year: Optional[int] = None @dataclass class VideoPlayer: width: int embed_code: str @dataclass class LegacyVideoPost(Post): caption: Optional[str] = None player: List[Any] = field(default_factory=[]) @dataclass class LegacyAnswerPost(Post): asking_name: Optional[str] = None asking_url: Optional[str] = None question: Optional[str] = None answer: Optional[str] = None # a type -> class dict POST_CLASSES: Dict[str, Type] = { 'photo': LegacyPhotoPost, 'quote': LegacyQuotePost, 'link': LegacyLinkPost, 'chat': LegacyChatPost, 'audio': LegacyAudioPost, 'video': LegacyVideoPost, 'answer': LegacyAnswerPost, } @dataclass class Likes: liked_posts: List[Post] liked_count: int def __post_init__(self): self.liked_posts = [Post(**post) for post in self.liked_posts] @dataclass class Following: blogs: List[BlogInfo] total_blogs: int def __post_init__(self): self.blogs = [BlogInfo(**blog) for blog in self.blogs] @dataclass class Follower: name: str following: bool url: str updated: int @dataclass class Followers: total_users: int users: List[Follower] def __post_init__(self): self.users = [Follower(**user) for user in self.users] @dataclass class Reblog: comment: str tree_html: str @dataclass class Dashboard: posts: List[DashboardPost] def __post_init__(self): self.posts = [DashboardPost(**post) for post in self.posts] @dataclass class Posts: posts: List[Post] def __post_init__(self): self.posts = [Post(**post) for post in self.posts] @dataclass class BlogPosts(Posts): blog: BlogInfo def __post_init__(self): self.blog = BlogInfo(**self.blog)

19.247093

71

0.661683

5,493

0.829633

0

5,867

0.88612

0

263

0.039722

8d4876f42fc49dd8332e5b4739b6a7de0c8b9bb2

311

py

Python

simple_jobs_scraper.py

Engnation/Jobs-Scraper

6f8b1207731da9f187db406a5be6916774ba3bc5

[ "MIT" ]

null

simple_jobs_scraper.py

Engnation/Jobs-Scraper

6f8b1207731da9f187db406a5be6916774ba3bc5

[ "MIT" ]

null

simple_jobs_scraper.py

Engnation/Jobs-Scraper

6f8b1207731da9f187db406a5be6916774ba3bc5

[ "MIT" ]

null

from jobs_scraper import JobsScraper # Let's create a new JobsScraper object and perform the scraping for a given query. position_var = "Python" scraper = JobsScraper(country="ca", position=position_var, location="Toronto", pages=3) df = scraper.scrape() df.to_csv(rf'{position_var} jobs.csv', index = False)

34.555556

87

0.768489

0

131

0.421222

8d4a0164b56629bd4e65dd24b9c1a1fba70a5ea1

810

py

Python

mac/redRMacUpdater.py

PiRSquared17/r-orange

6bc383f1db3c10c59e16b39daffc44df904ce031

[ "Apache-2.0" ]

1

2019-04-15T13:50:30.000Z

mac/redRMacUpdater.py

PiRSquared17/r-orange

6bc383f1db3c10c59e16b39daffc44df904ce031

[ "Apache-2.0" ]

null

mac/redRMacUpdater.py

PiRSquared17/r-orange

6bc383f1db3c10c59e16b39daffc44df904ce031

[ "Apache-2.0" ]

1

2016-01-21T23:00:21.000Z

import tarfile, sys,os from PyQt4.QtCore import * from PyQt4.QtGui import * app = QApplication(sys.argv) try: zfile = tarfile.open(sys.argv[1], "r:gz" ) zfile.extractall(sys.argv[2]) zfile.close() mb = QMessageBox('Red-R Updated', "Red-R has been updated'", QMessageBox.Information, QMessageBox.Ok | QMessageBox.Default, QMessageBox.NoButton, QMessageBox.NoButton) except: mb = QMessageBox('Red-R Updated', "There was an Error in updating Red-R.\n\n%s" % sys.exc_info()[0], QMessageBox.Information, QMessageBox.Ok | QMessageBox.Default, QMessageBox.NoButton, QMessageBox.NoButton) app.setActiveWindow(mb) mb.setFocus() mb.show() app.exit(0) #mb.exec_() sys.exit(app.exec_()) os.remove(sys.argv[1])

30

105

0.646914

0

117

0.144444

8d4be9a3c0385e4ebdfd3712a699e128c38acafc

9,346

py

Python

darknet_websocket_demo.py

wutianze/darknet-superb-service

fdee5a932c8a3898701c1e302e4642fbff853630

[ "MIT" ]

null

darknet_websocket_demo.py

wutianze/darknet-superb-service

fdee5a932c8a3898701c1e302e4642fbff853630

[ "MIT" ]

null

darknet_websocket_demo.py

wutianze/darknet-superb-service

fdee5a932c8a3898701c1e302e4642fbff853630

[ "MIT" ]

null

from ctypes import * #from multiprocessing import Process, Queue import queue import time from threading import Lock,Thread from fastapi import FastAPI from fastapi import Request from fastapi import WebSocket, WebSocketDisconnect import uvicorn #from yolo_service import * import socket import random from typing import List import darknet import cv2 import time import io import struct import os import numpy as np import base64 import json from jtracer.tracing import init_tracer import pynng from PIL import Image from opentracing.propagation import Format def convert2relative(bbox,darknet_height,darknet_width): """ YOLO format use relative coordinates for annotation """ x, y, w, h = bbox _height = darknet_height _width = darknet_width return x/_width, y/_height, w/_width, h/_height def convert2original(image, bbox,darknet_height,darknet_width): x, y, w, h = convert2relative(bbox,darknet_height,darknet_width) image_h, image_w, __ = image.shape orig_x = int(x * image_w) orig_y = int(y * image_h) orig_width = int(w * image_w) orig_height = int(h * image_h) bbox_converted = (orig_x, orig_y, orig_width, orig_height) return bbox_converted class SuperbFrame: def __init__(self,darknet_height,darknet_width): self.image = None self.results = None self.darknet_image = darknet.make_image(darknet_width,darknet_height,3) self.recv_timestamp = 0 self.send_timestamp = 0 self.inference_time = 0 self.final_image = None self.bytes = None self.span = None def port_is_used(port,ip="0.0.0.0"): s = socket.socket(socket.AF_INET,socket.SOCK_STREAM) try: s.connect((ip,port)) s.shutdown(2) return True except Exception as e: return False app = FastAPI() class ConnectionManager: def __init__(self): # 存放激活的ws连接对象 self.active_connections: List[WebSocket] = [] self.ports = set() self.port_lock = Lock() async def connect(self, ws: WebSocket): # 等待连接 await ws.accept() # 存储ws连接对象 self.active_connections.append(ws) def disconnect(self, ws: WebSocket): # 关闭时移除ws对象 self.active_connections.remove(ws) manager = ConnectionManager() @app.get("/get_port") def get_port(request:Request): while True: manager.port_lock.acquire() port_tmp = random.randint(int(os.getenv("SUPB_MIN_PORT")),int(os.getenv("SUPB_MAX_PORT"))) if port_tmp in manager.ports or port_is_used(port_tmp): manager.port_lock.release() continue else: manager.ports.add(port_tmp) manager.port_lock.release() return port_tmp # port_tmp is the key for a client def parse_data(data,tracer): head_length, msg_length = struct.unpack("ii", data[0:8]) head_length, msg_length, msg_head, msg = struct.unpack("ii"+ str(head_length) + "s" + str(msg_length) + "s", data) if head_length > 2: span_dict = json.loads(msg_head) span_ctx = tracer.extract(Format.TEXT_MAP, span_dict) return span_ctx, msg else: return None, msg def send_index(send_queue, sock,keep_alive): while keep_alive: try: span_reply = send_queue.get(block=False,timeout=20) sock.send(span_reply) except pynng.Timeout: print("sock.send timeout") except: pass # no msg to send def send_then_recv(input_address,send_queue,input_queue,tracer,darknet_width,darknet_height,sock,keep_alive): #sock = pynng.Pair1(recv_timeout=100,send_timeout=100) #sock.listen(input_address) while keep_alive: #try: # span_reply = send_queue.get(block=False,timeout=20) # sock.send(span_reply) #except pynng.Timeout: # print("sock.send timeout") #except: # pass # no msg to send try: msg = sock.recv() except pynng.Timeout: continue recv_time = time.time() newFrame = SuperbFrame(darknet_height,darknet_width) newFrame.recv_timestamp = int(recv_time*1000.0) # in ms # msg handling span_ctx, msg_content = parse_data(msg,tracer) if span_ctx is not None: newFrame.span = tracer.start_span('image_procss',child_of=span_ctx) header = msg_content[0:24] hh,ww,cc,tt = struct.unpack('iiid',header) newFrame.send_timestamp = int(tt*1000.0) hh,ww,cc,tt,ss = struct.unpack('iiid'+str(hh*ww*cc)+'s',msg_content) newFrame.image = cv2.cvtColor((np.frombuffer(ss,dtype=np.uint8)).reshape(hh,ww,cc), cv2.COLOR_BGR2RGB) darknet.copy_image_from_bytes(newFrame.darknet_image,cv2.resize(newFrame.image,(darknet_width,darknet_height),interpolation=cv2.INTER_LINEAR).tobytes()) #if span_ctx is not None: # newFrame.span.finish() try: input_queue.put(newFrame,block=False,timeout=100) except: print("input_queue is full, discard current msg") continue def keep_inference(send_queue,input_queue,result_queue,network,class_names,keep_alive): while keep_alive: try: #print("get newFrame") newFrame = input_queue.get(block=False,timeout=100) except: #print("inference get fail") continue prev_time = time.time() newFrame.results = darknet.detect_image(network, class_names, newFrame.darknet_image, thresh=0.2) newFrame.inference_time = int((time.time()-prev_time)*1000.0) # s -> ms darknet.free_image(newFrame.darknet_image) if newFrame.span is not None: index = newFrame.span.get_baggage_item('index') newFrame.span.finish() try: send_queue.put(index.encode()) #sock.send(index.encode()) except: print("send_queue is full, discard current msg") try: result_queue.put(newFrame,block=False,timeout=10) except: print("result_queue is full, discard current msg") continue def generate_output(result_queue,need_bytes,keep_alive,class_colors,darknet_height,darknet_width,resizew=960,resizeh=480): while keep_alive: try: newFrame = result_queue.get(block=False,timeout=30) except: continue detections_adjusted = [] if newFrame is not None: for label, confidence, bbox in newFrame.results: bbox_adjusted = convert2original(newFrame.image, bbox,darknet_height,darknet_width) detections_adjusted.append((str(label), confidence, bbox_adjusted)) image = darknet.draw_boxes(detections_adjusted, newFrame.image, class_colors) cv2.cvtColor(image,cv2.COLOR_BGR2RGB) newFrame.final_image = image if need_bytes: img = Image.fromarray(image).resize((resizew,resizeh)) img_byte_arr = io.BytesIO() img.save(img_byte_arr, format='PNG') img_byte_arr.seek(0) newFrame.bytes = base64.b64encode(img_byte_arr.read()).decode() return newFrame else: continue @app.websocket("/ws/{port}")# user is the received port_tmp async def stream_handler(websocket: WebSocket, port: str): print("a new websocket connected") await manager.connect(websocket) network,class_names,class_colors = darknet.load_network( "./cfg/yolov4.cfg", "./cfg/coco.data", "./yolov4.weights", batch_size=1 ) darknet_width = darknet.network_width(network) darknet_height = darknet.network_height(network) tracer = init_tracer("image-process") input_queue = queue.Queue(maxsize=5) result_queue = queue.Queue(maxsize=5) send_queue = queue.Queue(maxsize=5) input_address = "tcp://0.0.0.0:"+port sock = pynng.Pair1(recv_timeout=100,send_timeout=100) sock.listen(input_address) keep_alive = True p0 = Thread(target=send_then_recv,args=(input_address,send_queue,input_queue,tracer,darknet_width,darknet_height,sock,keep_alive)) p1 = Thread(target=keep_inference,args=(send_queue,input_queue,result_queue,network,class_names,keep_alive)) p2 = Thread(target=send_index,args=(send_queue,sock,keep_alive)) p0.start() p1.start() p2.start() try: while keep_alive: superbFrame = generate_output(result_queue,True,keep_alive,class_colors,darknet_width,darknet_height) send1_time = int(time.time()*1000.0) payload = {"img": "data:image/png;base64,%s"%(superbFrame.bytes),"send0_time":superbFrame.send_timestamp,"recv_time":superbFrame.recv_timestamp,"send1_time":send1_time} await websocket.send_json(payload) except WebSocketDisconnect: keep_alive = False p0.join() p1.join() p2.join() sock.close() manager.disconnect(websocket) manager.ports.discard(port) if __name__ == "__main__": uvicorn.run("darknet_websocket_demo:app",host="0.0.0.0",port=int(os.getenv("SUPB_SERVICE_PORT")),log_level="info")

35.003745

180

0.652044

873

0.092892

0

2,295

0.244201

1,912

0.203448

1,236

0.131517

8d4d42f7498f1a4af52daeaede069016fb2ef667

2,389

py

Python

tests/unit/test_sherman_morrison.py

willwheelera/pyqmc

0c8d1f308bbccb1560aa680a5a75e7a4fe7a69fb

[ "MIT" ]

44

2019-06-04T13:53:26.000Z

2022-03-31T08:36:30.000Z

tests/unit/test_sherman_morrison.py

willwheelera/pyqmc

0c8d1f308bbccb1560aa680a5a75e7a4fe7a69fb

[ "MIT" ]

121

2019-05-13T14:05:20.000Z

2022-02-16T19:24:37.000Z

tests/unit/test_sherman_morrison.py

willwheelera/pyqmc

0c8d1f308bbccb1560aa680a5a75e7a4fe7a69fb

[ "MIT" ]

35

2019-04-26T21:57:50.000Z

2022-02-14T07:56:34.000Z

import numpy as np from pyqmc.slater import sherman_morrison_row from pyqmc.slater import sherman_morrison_ms def test_sherman_morrison(): ratio_err, inv_err = run_sherman_morrison() assert ratio_err < 1e-13, f"ratios don't match {ratio_err}" assert inv_err < 1e-13, f"inverses don't match {inv_err}" ratio_err, inv_err = run_sherman_morrison(ms=True) assert ratio_err < 1e-13, f"ratios don't match {ratio_err}" assert inv_err < 1e-13, f"inverses don't match {inv_err}" def construct_mat(nconf, n, ndet=None): u, s, v = np.linalg.svd(np.random.randn(n, n)) if ndet is None: shape = (nconf, n) else: shape = (nconf, ndet, n) svals = (np.random.rand(*shape) + 1) * np.random.choice([-1, 1], shape) matrix = np.einsum("ij,...hj,jk->...hik", u, svals, v) return matrix def construct_vec(matrix, nconf, n, e, ndet=None): if ndet is None: coef = np.random.randn(nconf, n - 1) else: coef = np.random.randn(nconf, ndet, n - 1) not_e = np.arange(n) != e vec_ = np.einsum("i...j,i...jk->i...k", coef, matrix[..., not_e, :]) proj = (np.random.random(nconf) - 1) * 2 proj += np.sign(proj) * 0.5 vec = vec_ + np.einsum("i...k,i->i...k", matrix[..., e, :], proj) return vec def run_sherman_morrison(ms=False): n = 10 nconf = 4 e = 2 ndet = 8 if ms else None # construct matrix that isn't near singular matrix = construct_mat(nconf, n, ndet=ndet) inv = np.linalg.inv(matrix) # make sure new matrix isn't near singular newmatrix = matrix.copy() vec = construct_vec(matrix, nconf, n, e, ndet=ndet) newmatrix[..., e, :] = vec # compute ratios and inverses directly and by update if ndet is None: smratio, sminv = sherman_morrison_row(e, inv, vec) else: smratio, sminv = sherman_morrison_ms(e, inv, vec) npratio = np.linalg.det(newmatrix) / np.linalg.det(matrix) npinv = np.linalg.inv(newmatrix) ratio_err = np.amax(np.abs(npratio - smratio)) inv_err = np.amax(np.abs(npinv - sminv)) return ratio_err, inv_err if __name__ == "__main__": r_err, inv_err = list(zip(*[run_sherman_morrison() for i in range(2000)])) print(np.amax(r_err)) print(np.amax(inv_err)) counts, bins = np.histogram(np.log10(inv_err), bins=np.arange(-16, 0)) print(np.stack([counts, bins[1:]]))

30.628205

78

0.631226

0

337

0.141063

8d4df1f93edc3b8bb4e583e03cb8610d1cc0439f

1,543

py

Python

script/licel-plotter.py

FedeVerstraeten/smn-lidar-controller

7850fd48702d5f2e00d07b499812b3b2fb2b7676

[ "MIT" ]

null

script/licel-plotter.py

FedeVerstraeten/smn-lidar-controller

7850fd48702d5f2e00d07b499812b3b2fb2b7676

[ "MIT" ]

1

2021-10-05T03:53:55.000Z

script/licel-plotter.py

FedeVerstraeten/smnar-lidar-controller

7850fd48702d5f2e00d07b499812b3b2fb2b7676

[ "MIT" ]

null

#!/usr/bin/env python3 import sys import socket import time import numpy as np import matplotlib.pyplot as plt HOST = '10.49.234.234' PORT = 2055 def command_to_licel(licelcommand): data=None with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.connect((HOST, PORT)) s.sendall(bytes(licelcommand+'\r\n','utf-8')) time.sleep(2) # wait TCP adquisition data = s.recv(8192) # 8192 = 4096 * 2 print("Len:",len(data),"type:",type(data)) return data if __name__ == '__main__': # Select TR command_select='SELECT 0' rsp=repr(command_to_licel(command_select)) print('Received',rsp) # Clear memory command_clear='MCLEAR' rsp=repr(command_to_licel(command_clear)) print('Received',rsp) # Start TR command_start='MSTART' rsp=repr(command_to_licel(command_start)) print('Received',rsp) time.sleep(5) # Stop TR command_stop='MSTOP' rsp=repr(command_to_licel(command_stop)) print('Received',rsp) # Get data command_data='DATA? 0 4001 LSW A' rsp=command_to_licel(command_data) #print('Received',rsp) # with open('outputlicel', 'w') as f: # f.write(rsp) data_output=rsp # Plot t = np.arange(0, len(data_output), 1) data_arr=[] for data_byte in data_output: data_arr.append(int(data_byte)) fig, ax = plt.subplots() ax.plot(t, data_arr) ax.set(xlabel='time (s)', ylabel='voltage (mV)',title='SMN LICEL') ax.grid() fig.savefig("test.png") plt.show()

24.109375

70

0.644848

0

389

0.252106

8d500786de7e53c7c13f50132e8ecbc760d095db

13,860

py

Python

horizon/openstack_dashboard/dashboards/identity/account/tables.py

yianjiajia/openstack_horizon

9e36a4c3648ef29d0df6912d990465f51d6124a6

[ "Apache-2.0" ]

null

horizon/openstack_dashboard/dashboards/identity/account/tables.py

yianjiajia/openstack_horizon

9e36a4c3648ef29d0df6912d990465f51d6124a6

[ "Apache-2.0" ]

null

horizon/openstack_dashboard/dashboards/identity/account/tables.py

yianjiajia/openstack_horizon

9e36a4c3648ef29d0df6912d990465f51d6124a6

[ "Apache-2.0" ]

null

# Copyright 2012 Nebula, Inc. # # 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 logging import json from django.utils.translation import ugettext_lazy as _ from django.utils.translation import ungettext_lazy from django.conf import settings from horizon import forms from horizon import tables from horizon.utils import filters from openstack_dashboard import api from openstack_dashboard import policy LOG = logging.getLogger(__name__) POLICY_CHECK = getattr(settings, "POLICY_CHECK_FUNCTION", lambda p, r: True) class CreateAccount(tables.LinkAction): name = "create" verbose_name = _("Create Account") url = "horizon:identity:account:create" classes = ("ajax-modal",) icon = "plus" policy_rules = (("identity", "identity:create_user"),) class DeleteAccountAction(tables.DeleteAction): help_text = _( "This Operation will delete all configuration and resources(network, images, servers, disks, VPN, firewall, keypair) and !!! Please confirm your operation.") @staticmethod def action_present(count): return ungettext_lazy( u"Delete User", u"Delete Users", count ) @staticmethod def action_past(count): return ungettext_lazy( u"Deleted User", u"Deleted Users", count ) name = "delete" policy_rules = (("identity", "identity:update_user"),) def allowed(self, request, user): if not api.keystone.keystone_can_edit_user(): return False self.enabled = True if not user: return False else: return user.enabled def delele_billing_account(self, request, obj_id): client = api.billing.RequestClient(request) account = client.get_account(obj_id) if account: ret = client.api_request('/account/delete/' + account['account_id'], method='DELETE') user = json.loads(ret.read()) if user['success'] != 'success': raise def delete(self, request, obj_id): LOG.info('Deleting User "%s".' % obj_id) try: api.keystone.user_update_enabled(request, obj_id, False) user = api.keystone.user_get(request, obj_id) api.keystone.tenant_update(request, user.default_project_id, enabled=False) self.delele_billing_account(request, user.default_project_id) # operation log config = _('User ID: %s') % obj_id api.logger.Logger(request).create(resource_type='account', action_name='Deletes User', resource_name='Account', config=config, status='Success') except Exception: # operation log config = _('User ID: %s') % obj_id api.logger.Logger(request).create(resource_type='account', action_name='Deletes User', resource_name='Account', config=config, status='Error') class EnableAccountAction(tables.DeleteAction): help_text = _( "This Operation will enable the user and project!!! Please confirm your operation.") @staticmethod def action_present(count): return ungettext_lazy( u"Enable User", u"Enable Users", count ) @staticmethod def action_past(count): return ungettext_lazy( u"Enabled User", u"Enabled Users", count ) name = "enable" policy_rules = (("identity", "identity:update_user"),) def allowed(self, request, user): if not api.keystone.keystone_can_edit_user(): return False self.enabled = True if not user: return False else: return not user.enabled def enable_billing_account(self, request, obj_id): client = api.billing.RequestClient(request) account = client.get_account(obj_id) if account: params = {} params['account'] = {} params['account']['status'] = 'normal' params['account']['frozen_status'] = 'normal' ret = client.api_request('/account/update/' + account['account_id'], method='PUT', data=json.dumps(params)) user = json.loads(ret.read()) if user['success'] != 'success': raise def action(self, request, obj_id): LOG.info('Enable User "%s".' % obj_id) try: api.keystone.user_update_enabled(request, obj_id, True) user = api.keystone.user_get(request, obj_id) api.keystone.tenant_update(request, user.default_project_id, enabled=True) self.enable_billing_account(request, user.default_project_id) # operation log config = _('User ID: %s') % obj_id api.logger.Logger(request).create(resource_type='account', action_name='Enables User', resource_name='Account', config=config, status='Success') except Exception: # operation log config = _('User ID: %s') % obj_id api.logger.Logger(request).create(resource_type='account', action_name='Enables User', resource_name='Account', config=config, status='Error') class AccountFilterAction(tables.FilterAction): name = "filter_account" filter_type = "server" filter_choices = (('sname', _("Name"), True), ('scompany', _("Company Name"), True), ('enabled', _("Status"), True),) class EditAccountInfoLink(tables.LinkAction): name = "edit" verbose_name = _("Edit") url = "horizon:identity:account:update_info" classes = ("ajax-modal",) icon = "pencil" policy_rules = (("identity", "identity:update_user"),) def allowed(self, request, datum=None): if not datum: return False else: user = api.keystone.user_get(request, datum) return user.enabled class AdjustQuotaLink(tables.LinkAction): name = "update_quota" verbose_name = _("Modify Quotas") url = "horizon:identity:account:update_quota" classes = ("ajax-modal",) icon = "pencil" policy_rules = (("identity", "identity:update_project"),) def allowed(self, request, datum=None): # only display when the modified user have this region region_choices = [] regions = api.keystone.list_regions_for_user(request, datum.id) for region in regions: region_choices.append(region['id']) if request.user.services_region not in region_choices: return False if not datum: return False else: user = api.keystone.user_get(request, datum) return user.enabled class RoleChangeLink(tables.BatchAction): name = "adjust_quota" classes = ('btn-danger',) icon = "pencil" help_text = _("Please do it carefully!") policy_rules = (("identity", "identity:update_user"),) @staticmethod def action_present(count): return ungettext_lazy( u"Role Change", u"Role Changes", count ) @staticmethod def action_past(count): return ungettext_lazy( u"Role Changed", u"Role Changed", count ) def allowed(self, request, datum=None): policy = (("identity", "identity:create_grant"), ("identity", "identity:revoke_grant"),) # only normal user can change their role # only support and admin can do this action if not datum: return False else: user = api.keystone.user_get(request, datum) if user.enabled: default_role = api.keystone.get_default_role(request) if user.default_role_id != default_role.id: return False return POLICY_CHECK(policy, request) else: return False def action(self, request, obj_id): try: user = api.keystone.user_get(request, obj_id) default_user_role = api.keystone.get_default_role(request) default_project_admin_role = api.keystone.get_default_project_admin_role(request) api.keystone.remove_tenant_user_role(request, project=user.default_project_id, user=user.id, role=default_user_role.id) api.keystone.user_update(request, obj_id, **{'default_role_id': default_project_admin_role.id}) api.keystone.add_tenant_user_role(request, project=user.default_project_id, user=user.id, role=default_project_admin_role.id) # operation log config = _('Old role %s, new role %s') % (default_user_role.name, default_project_admin_role.name) api.logger.Logger(request).create(resource_type='account', action_name='Role_Change', resource_name='Account', config=config, status='Success') except Exception: # operation log config = _('Old role %s, new role %s') % (default_user_role.name, default_project_admin_role.name) api.logger.Logger(request).create(resource_type='account', action_name='Role_Change', resource_name='Account', config=config, status='Error') class ChangePasswordLink(policy.PolicyTargetMixin, tables.LinkAction): name = "change_password" verbose_name = _("Change Password") url = "horizon:identity:account:change_password" classes = ("ajax-modal",) icon = "key" policy_rules = (("identity", "identity:change_password"),) policy_target_attrs = (("user_id", "id"),) def allowed(self, request, datum=None): if not datum: return False else: user = api.keystone.user_get(request, datum) return user.enabled and api.keystone.keystone_can_edit_user() class UpdateRegionsLink(policy.PolicyTargetMixin, tables.LinkAction): name = "regions" verbose_name = _("Update Regions") url = "horizon:identity:account:regions" classes = ("ajax-modal",) icon = "pencil" policy_rules = (("identity", "identity:update_user_regions"),) def allowed(self, request, datum=None): if not datum: return False else: user = api.keystone.user_get(request, datum) return user.enabled class UpdateMembersLink(tables.LinkAction): name = "users" verbose_name = _("Manage Members") url = "horizon:identity:account:update_member" classes = ("ajax-modal",) icon = "pencil" policy_rules = (("identity", "identity:list_users"), ("identity", "identity:list_grants")) def allowed(self, request, datum=None): if not datum: return False else: user = api.keystone.user_get(request, datum) return user.enabled STATUS_DISPLAY_CHOICES = ( (False, _("Delete")), (True, _("Normal")), ) class AccountsTable(tables.DataTable): id = tables.Column('id', hidden=True) # project_id = tables.Column('project_id', hidden=True) name = tables.Column('name', verbose_name=_('User Name'), form_field=forms.CharField(), link='horizon:identity:account:detail' ) company = tables.Column('company', verbose_name=_('Company Name'), form_field=forms.CharField()) # email = tables.Column('email', verbose_name=_('Email'), # form_field=forms.CharField(required=False), # filters=(lambda v: defaultfilters # .default_if_none(v, ""), # defaultfilters.escape, # defaultfilters.urlize) # ) enabled = tables.Column('enabled', verbose_name=_('Status'), # status=True, # status_choices=STATUS_CHOICES, display_choices=STATUS_DISPLAY_CHOICES, empty_value="False") created_at = tables.Column('created_at', verbose_name=_('Created_at'), filters=[filters.parse_isotime]) class Meta(object): name = "accounts" verbose_name = _("AccountList") table_actions = (AccountFilterAction, CreateAccount) row_actions = (EditAccountInfoLink, AdjustQuotaLink, UpdateRegionsLink, UpdateMembersLink, RoleChangeLink, ChangePasswordLink, DeleteAccountAction, EnableAccountAction)

37.258065

165

0.581818

12,695

0.915945

0

956

0.068975

0

3,529

0.254618

8d5291b6a1ce7e03aab2c5b10e8c178dc0212bb3

2,278

py

Python

3Sum.py

Muthu2093/Algorithms-practice

999434103a9098a4361104fd39cba5913860fa9d

[ "MIT" ]

null

3Sum.py

Muthu2093/Algorithms-practice

999434103a9098a4361104fd39cba5913860fa9d

[ "MIT" ]

null

3Sum.py

Muthu2093/Algorithms-practice

999434103a9098a4361104fd39cba5913860fa9d

[ "MIT" ]

null

## Given an array nums of n integers, are there elements a, b, c in nums such that a + b + c = 0? Find all unique triplets in the array which gives the sum of zero. ## Note: ## The solution set must not contain duplicate triplets. ## Example: ## Given array nums = [-1, 0, 1, 2, -1, -4], ## A solution set is: ## [ ## [-1, 0, 1], ## [-1, -1, 2] ## ] class Solution: def quickSort(self, nums, l, r): if(l<r): pi = self.partition(nums, l, r) self.quickSort(nums, l, pi-1) self.quickSort(nums, pi+1, r) def partition(self, nums, low, high): pivot = nums[high] j=low-1 for i in range(low, high): if nums[i] <= pivot: j += 1 nums[i],nums[j] = nums[j],nums[i] nums[high],nums[j+1] = nums[j+1],nums[high] return (j+1) def threeSum(self, nums): """ :type nums: List[int] :rtype: List[List[int]] """ if len(nums) <= 2: return [] if len(nums) == 3: if sum(nums) == 0: lis = [] lis.append(nums) return lis #self.quickSort(nums, 0 , len(nums)-1) nums.sort() lis =[] for m in range (1,len(nums)-1): l=0 r=len(nums)-1 if (m+2 <= r and nums[m] == nums[m+2]): k=m+3 while(k<=r and nums[m] != nums[k]): k = k + 1 if k > r: break m=k-2 l=k-3 while (l<m and m<r): if (nums[l] + nums[m] + nums[r] == 0): lis.append((nums[l],nums[m],nums[r])) while(l<r and nums[l] == nums[l+1]): l = l+1 while(l<r and nums[r] == nums[r-1]): r = r-1 if (nums[l] + nums[m] + nums[r] < 0): l = l + 1 else: r = r - 1 lis = list(set(lis)) return lis

27.780488

164

0.368306

1,893

0.830992

0

459

0.201493

8d52b06f889e9040ed2102aec6867ed5ea6a3b70

684

py

Python

moim/models.py

gyukebox/django-tutorial-moim

ea9bea85dadf22bff58ae26ee1ac59171bbe0240

[ "MIT" ]

null

moim/models.py

gyukebox/django-tutorial-moim

ea9bea85dadf22bff58ae26ee1ac59171bbe0240

[ "MIT" ]

4

2018-01-01T09:26:30.000Z

2018-01-06T07:13:01.000Z

moim/models.py

gyukebox/django-tutorial-moim

ea9bea85dadf22bff58ae26ee1ac59171bbe0240

[ "MIT" ]

null

from django.db import models from user.models import UserModel class MoimModel(models.Model): title = models.CharField(max_length=20) creator = models.ForeignKey(UserModel, on_delete=models.CASCADE) created_at = models.DateTimeField(auto_now_add=True) starts_at = models.DateTimeField() max_attendee = models.PositiveIntegerField() attendees = models.ManyToManyField( UserModel, related_name='Attendee', blank=True) summary = models.CharField(max_length=100) description = models.TextField() image = models.FileField(blank=True, upload_to='static/images') def __str__(self): return '{} : {}'.format(self.title, self.summary)

36

68

0.730994

618

0.903509

0

34

0.049708

8d5338ad6760bdfbd08440494b1ea9d0eab1dc53

1,809

py

Python

developers_chamber/scripts/gitlab.py

dstlmrk/developers-chamber

93f928048f57c049f1c85446d18078b73376462a

[ "MIT" ]

8

2019-08-23T15:46:30.000Z

2021-03-23T20:12:21.000Z

developers_chamber/scripts/gitlab.py

dstlmrk/developers-chamber

93f928048f57c049f1c85446d18078b73376462a

[ "MIT" ]

14

2019-09-17T20:24:18.000Z

2021-05-18T21:10:12.000Z

developers_chamber/scripts/gitlab.py

dstlmrk/developers-chamber

93f928048f57c049f1c85446d18078b73376462a

[ "MIT" ]

6

2019-08-23T15:46:21.000Z

2022-02-18T11:01:18.000Z

import os import click from developers_chamber.git_utils import get_current_branch_name from developers_chamber.gitlab_utils import \ create_merge_request as create_merge_request_func from developers_chamber.scripts import cli DEFAULT_API_URL = os.environ.get('GITLAB_API_URL', 'https://gitlab.com/api/v4') DEFAULT_PROJECT = os.environ.get('GITLAB_PROJECT') DEFAULT_TARGET_BRANCH = os.environ.get('GITLAB_TARGET_BRANCH', 'next') DEFAULT_TOKEN = os.environ.get('GITLAB_TOKEN') @cli.group() def gitlab(): """GitLab commands""" @gitlab.command() @click.option('--api-url', help='GitLab instance API URL (defaults to gitlab.com)', type=str, required=True, default=DEFAULT_API_URL) @click.option('--token', help='token (can be set as env variable GITLAB_TOKEN)', type=str, required=True, default=DEFAULT_TOKEN) @click.option('--source-branch', help='source Git branch', type=str) @click.option('--target-branch', help='target Git branch (defaults to env variable GITLAB_TARGET_BRANCH)', type=str, default=DEFAULT_TARGET_BRANCH) @click.option('--project', help='GitLab project name (defaults to env variable GITLAB_PROJECT)', type=str, required=True, default=DEFAULT_PROJECT) def create_release_merge_request(api_url, token, source_branch, target_branch, project): """Create a new merge request in GitLab project after release""" if not source_branch: source_branch = get_current_branch_name() mr_url = create_merge_request_func( api_url=api_url, token=token, title=f'Merge branch "{source_branch}"', description='', source_branch=source_branch, target_branch=target_branch, project=project, ) click.echo(f'Merge request was successfully created: {mr_url}')

38.489362

116

0.726368

0

1,320

0.729685

0

585

0.323383

8d5577a30127caeb2ef24f4e9b841abc050103d0

15,790

py

Python

tests_pytest/state_machines/autoinstall/test_autoinstall_smbase.py

tessia-project/tessia

b9ded8dc7f0b9a7a0ea00d95b5ccc4af4d2e7540

[ "Apache-2.0" ]

5

2020-06-04T10:20:33.000Z

2020-10-26T15:09:19.000Z

tests_pytest/state_machines/autoinstall/test_autoinstall_smbase.py

tessia-project/tessia

b9ded8dc7f0b9a7a0ea00d95b5ccc4af4d2e7540

[ "Apache-2.0" ]

null

tests_pytest/state_machines/autoinstall/test_autoinstall_smbase.py

tessia-project/tessia

b9ded8dc7f0b9a7a0ea00d95b5ccc4af4d2e7540

[ "Apache-2.0" ]

null

# Copyright 2021 IBM Corp. # # 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. """ Test base autoinstall machine A smallest implementation on SmBase is used to test common features """ # pylint: disable=invalid-name # we have really long test names # pylint: disable=redefined-outer-name # use of fixtures # pylint: disable=unused-argument # use of fixtures for their side effects # # IMPORTS # from pathlib import Path from tessia.baselib.hypervisors.hmc.volume_descriptor import FcpVolumeDescriptor from tessia.server.config import Config from tessia.server.state_machines.autoinstall import plat_lpar, plat_zvm, plat_kvm from tessia.server.state_machines.autoinstall import plat_base, sm_base from tessia.server.state_machines.autoinstall.model import AutoinstallMachineModel from tessia.server.state_machines.autoinstall.sm_base import SmBase from tests_pytest.decorators import tracked from tests_pytest.state_machines.ssh_stub import SshClient from tests_pytest.state_machines.null_hypervisor import NullHypervisor import pytest import yaml # # CONSTANTS AND DEFINITIONS # CREDS = {'user': 'unit', 'password': 'test'} # # CODE # class NullMachine(SmBase): """ Concrete SmBase implementation This implementation helps trigger all common paths without having any distro specifics (i.e. termination conditions or log lines) """ def __init__(self, model: AutoinstallMachineModel, platform: plat_base.PlatBase, *args, **kwargs): """ Initialize SmBase """ super().__init__(model, platform, *args, **kwargs) @property @classmethod def DISTRO_TYPE(cls): # pylint: disable=invalid-name """ Return the type of linux distribution supported. """ return "null" # DISTRO_TYPE def wait_install(self): """ Consider operating system installed and return immediately """ # wait_install() class NullPostInstallChecker: """ PostInstallChecked that checks that it has been called """ @tracked def verify(self): """ Public method to verify installed system """ return [] class TestModelUpdate: """ Test model updates during autoinstallation """ class UpdatingHypervisor(NullHypervisor): """ Hypervisor that returns some valid data about storage volumes """ @tracked def query_dpm_storage_devices(self, guest_name): """Query storage devices on DPM""" return [ FcpVolumeDescriptor( **{'uri': '/api/storage-volumes/1', 'attachment': 'fcp', 'is_fulfilled': True, 'size': 19.07, 'uuid': '6005076309FFD435000000000000CD0F', 'paths': [{'device_nr': 'FC00', 'wwpn': '5005076309049435', 'lun': 'CD0F0000'}] })] @pytest.fixture def scsi_volume_without_paths(self): """ A single-partition SCSI volume """ result = AutoinstallMachineModel.ZfcpVolume( 'cd0f0000', 20_000_000, multipath=True, wwid='36005076309ffd435000000000000cd0f') result.set_partitions('msdos', [{ 'mount_point': '/data', 'size': 18_000, 'filesystem': 'ext4', 'part_type': 'primary', 'mount_opts': None, }]) yield result @pytest.fixture(autouse=True) def mock_hypervisors(self, monkeypatch): """ Use hypevisor stub instead of real sessions """ monkeypatch.setattr(plat_lpar, 'HypervisorHmc', TestModelUpdate.UpdatingHypervisor) def test_model_update_adds_fcp_paths( self, lpar_scsi_system, default_os_tuple, tmpdir, scsi_volume_without_paths): """ Attempt to install "nothing" on an LPAR on SCSI disk Verify that hypervisor is called with correct parameters and post-install checker is run """ model = AutoinstallMachineModel(*default_os_tuple, lpar_scsi_system, CREDS) model.system_profile.add_volume(scsi_volume_without_paths) checker = NullPostInstallChecker() hyp = plat_lpar.PlatLpar.create_hypervisor(model) platform = plat_lpar.PlatLpar(model, hyp) # autoinstall machines use their own working directory # and have to be initialized in a temporary environment with tmpdir.as_cwd(): smbase = NullMachine(model, platform, checker) smbase.start() assert len(model.system_profile.volumes) == 2 assert model.system_profile.volumes[1].paths @pytest.fixture(autouse=True) def mock_config(monkeypatch, tmp_path): """ Set default configuration """ def get_config(): """ Configuration for use in tests """ # use a temporary path for storing templates return { 'auto_install': { 'url': 'http://server_1:5000/', 'dir': str(tmp_path), 'live_img_passwd': 'liveimage' } } monkeypatch.setattr(Config, 'get_config', get_config) @pytest.fixture(autouse=True) def mock_hypervisors(monkeypatch): """ Use hypevisor stub instead of real sessions """ monkeypatch.setattr(plat_lpar, 'HypervisorHmc', NullHypervisor) monkeypatch.setattr(plat_zvm, 'HypervisorZvm', NullHypervisor) monkeypatch.setattr(plat_kvm, 'HypervisorKvm', NullHypervisor) @pytest.fixture(autouse=True) def mock_ssh(monkeypatch): """ Use ssh stub instead of real sessions """ monkeypatch.setattr(plat_base, 'SshClient', SshClient) monkeypatch.setattr(plat_kvm, 'SshClient', SshClient) monkeypatch.setattr(sm_base, 'SshClient', SshClient) def test_boot_and_postinstall_check_on_lpar_dasd( lpar_dasd_system, default_os_tuple, tmpdir): """ Attempt to install "nothing" on an LPAR on DASD disk Verify that hypervisor is called with correct parameters and post-install checker is run """ model = AutoinstallMachineModel(*default_os_tuple, lpar_dasd_system, CREDS) checker = NullPostInstallChecker() hyp = plat_lpar.PlatLpar.create_hypervisor(model) platform = plat_lpar.PlatLpar(model, hyp) # autoinstall machines use their own working directory # and have to be initialized in a temporary environment with tmpdir.as_cwd(): smbase = NullMachine(model, platform, checker) smbase.start() assert checker.verify.called_once sys, cpus, mem, attrs, *_ = hyp.start.calls[0] assert sys == lpar_dasd_system.hypervisor.boot_options['partition-name'] assert cpus == lpar_dasd_system.cpus assert mem == lpar_dasd_system.memory # installation device does not show up in HmcHypervisor boot, # it is only used later during installation assert attrs['boot_params']['boot_method'] == 'dasd' assert attrs['boot_params']['devicenr'] == \ lpar_dasd_system.hypervisor.boot_options['boot-device'] def test_boot_and_postinstall_check_on_lpar_scsi( lpar_scsi_system, default_os_tuple, tmpdir): """ Attempt to install "nothing" on an LPAR on SCSI disk Verify that hypervisor is called with correct parameters and post-install checker is run """ model = AutoinstallMachineModel(*default_os_tuple, lpar_scsi_system, CREDS) checker = NullPostInstallChecker() hyp = plat_lpar.PlatLpar.create_hypervisor(model) platform = plat_lpar.PlatLpar(model, hyp) # autoinstall machines use their own working directory # and have to be initialized in a temporary environment with tmpdir.as_cwd(): smbase = NullMachine(model, platform, checker) smbase.start() assert checker.verify.called_once sys, cpus, mem, attrs, *_ = hyp.start.calls[0] assert sys == lpar_scsi_system.hypervisor.boot_options['partition-name'] assert cpus == lpar_scsi_system.cpus assert mem == lpar_scsi_system.memory # installation device does not show up in HmcHypervisor boot, # it is only used later during installation assert attrs['boot_params']['boot_method'] == 'dasd' assert attrs['boot_params']['devicenr'] == \ lpar_scsi_system.hypervisor.boot_options['boot-device'] def test_boot_and_postinstall_check_on_vm_dasd( vm_dasd_system, default_os_tuple, tmpdir): """ Attempt to install "nothing" on a VM on DASD disk Verify that hypervisor is called with correct parameters and post-install checker is run """ model = AutoinstallMachineModel(*default_os_tuple, vm_dasd_system, CREDS) checker = NullPostInstallChecker() hyp = plat_zvm.PlatZvm.create_hypervisor(model) platform = plat_zvm.PlatZvm(model, hyp) # autoinstall machines use their own working directory # and have to be initialized in a temporary environment with tmpdir.as_cwd(): smbase = NullMachine(model, platform, checker) smbase.start() assert checker.verify.called_once sys, cpus, mem, attrs, *_ = hyp.start.calls[0] assert sys == vm_dasd_system.system_name assert cpus == vm_dasd_system.cpus assert mem == vm_dasd_system.memory assert vm_dasd_system.volumes[0].device_id == \ attrs['storage_volumes'][0]['devno'] def test_boot_and_postinstall_check_on_vm_scsi( vm_scsi_system, default_os_tuple, tmpdir): """ Attempt to install "nothing" on a VM on SCSI disk Verify that hypervisor is called with correct parameters and post-install checker is run """ model = AutoinstallMachineModel(*default_os_tuple, vm_scsi_system, CREDS) checker = NullPostInstallChecker() hyp = plat_zvm.PlatZvm.create_hypervisor(model) platform = plat_zvm.PlatZvm(model, hyp) # autoinstall machines use their own working directory # and have to be initialized in a temporary environment with tmpdir.as_cwd(): smbase = NullMachine(model, platform, checker) smbase.start() assert checker.verify.called_once sys, cpus, mem, attrs, *_ = hyp.start.calls[0] assert sys == vm_scsi_system.system_name assert cpus == vm_scsi_system.cpus assert mem == vm_scsi_system.memory assert vm_scsi_system.volumes[0].lun == \ attrs['storage_volumes'][0]['lun'] def testboot_and_postinstall_check_on_kvm_scsi( kvm_scsi_system, default_os_tuple, tmpdir): """ Attempt to install "nothing" on a KVM on SCSI disk Verify correct device paths and that hypervisor is called with correct parameters and post-install checker is run """ model = AutoinstallMachineModel(*default_os_tuple, kvm_scsi_system, CREDS) checker = NullPostInstallChecker() hyp = plat_kvm.PlatKvm.create_hypervisor(model) platform = plat_kvm.PlatKvm(model, hyp) # autoinstall machines use their own working directory # and have to be initialized in a temporary environment with tmpdir.as_cwd(): smbase = NullMachine(model, platform, checker) smbase.start() assert checker.verify.called_once sys, cpus, mem, attrs, *_ = hyp.start.calls[0] assert sys == kvm_scsi_system.system_name assert cpus == kvm_scsi_system.cpus assert mem == kvm_scsi_system.memory assert kvm_scsi_system.volumes[0].lun == \ attrs['storage_volumes'][0]['volume_id'] for volume in model.system_profile.volumes: assert '/dev/disk/by-path/ccw' in volume.device_path def test_network_boot_on_lpar_scsi( scsi_volume, osa_iface, default_os_tuple, tmpdir): """ Attempt to install "nothing" on an LPAR on SCSI disk using network boot Verify that hypervisor is called with correct parameters """ ins_file = 'user@password:inst.local/some-os/boot.ins' hmc_hypervisor = AutoinstallMachineModel.HmcHypervisor( 'hmc', 'hmc.local', {'user': '', 'password': ''}, { 'partition-name': 'LP10', 'boot-method': 'network', 'boot-uri': 'ftp://' + ins_file, }) system = AutoinstallMachineModel.SystemProfile( 'lp10', 'default', hypervisor=hmc_hypervisor, hostname='lp10.local', cpus=2, memory=8192, volumes=[scsi_volume], interfaces=[(osa_iface, True)] ) model = AutoinstallMachineModel(*default_os_tuple, system, CREDS) hyp = plat_lpar.PlatLpar.create_hypervisor(model) platform = plat_lpar.PlatLpar(model, hyp) with tmpdir.as_cwd(): smbase = NullMachine(model, platform) smbase.start() sys, cpus, mem, attrs, *_ = hyp.start.calls[0] assert sys == hmc_hypervisor.boot_options['partition-name'] assert cpus == system.cpus assert mem == system.memory assert attrs['boot_params']['boot_method'] == 'ftp' assert attrs['boot_params']['insfile'] == ins_file def test_template_lpar_dasd(lpar_dasd_system, default_os_tuple, tmpdir): """ Test major template parameters """ *os_tuple, _, _ = default_os_tuple package_repo = AutoinstallMachineModel.PackageRepository( 'aux', 'http://example.com/repo', 'package repo') model = AutoinstallMachineModel( *os_tuple, [], [package_repo], lpar_dasd_system, CREDS) hyp = plat_lpar.PlatLpar.create_hypervisor(model) platform = plat_lpar.PlatLpar(model, hyp) with tmpdir.as_cwd(): smbase = NullMachine(model, platform) autofile_path = (Path.cwd() / 'lp10-default') smbase.start() autofile = yaml.safe_load(autofile_path.read_text()) assert autofile['system']['type'] == 'LPAR' assert autofile['system']['hostname'] == 'lp10.local' assert autofile['gw_iface']['type'] == 'OSA' assert autofile['gw_iface']['osname'] == 'enccw0b01' assert autofile['gw_iface']['search_list'] == ['example.com', 'local'] assert autofile['ifaces'][0]['osname'] == 'enccw0b01' assert autofile['volumes'][0]['type'] == 'DASD' assert autofile['volumes'][0]['partitions'] == [ {'fs': 'ext4', 'mp': '/', 'size': '18000M'} ] assert autofile['repos'][0]['name'] == 'os-repo' assert autofile['repos'][1]['name'] == 'aux' def test_template_kvm_scsi(kvm_scsi_system, default_os_tuple, tmpdir): """ Test major template parameters """ model = AutoinstallMachineModel(*default_os_tuple, kvm_scsi_system, CREDS) hyp = plat_kvm.PlatKvm.create_hypervisor(model) platform = plat_kvm.PlatKvm(model, hyp) with tmpdir.as_cwd(): smbase = NullMachine(model, platform) autofile_path = (Path.cwd() / 'kvm54-default') smbase.start() autofile = yaml.safe_load(autofile_path.read_text()) assert autofile['system']['type'] == 'KVM' assert autofile['system']['hostname'] == 'kvm54.local' assert autofile['gw_iface']['type'] == 'MACVTAP' assert autofile['gw_iface']['osname'] == 'eth0' assert autofile['ifaces'][0]['is_gateway']

34.326087

82

0.664155

3,663

0.231982

499

0.031602

2,804

0.177581

0

5,652

0.357948

8d5578255a37005da9d4bcc07955742be9a91579

2,261

py

Python

tests/test_command/test_cat_command.py

bbglab/openvariant

ea1e1b6edf0486b0dea34f43227ba333df1071cc

[ "BSD-3-Clause" ]

null

tests/test_command/test_cat_command.py

bbglab/openvariant

ea1e1b6edf0486b0dea34f43227ba333df1071cc

[ "BSD-3-Clause" ]

null

tests/test_command/test_cat_command.py

bbglab/openvariant

ea1e1b6edf0486b0dea34f43227ba333df1071cc

[ "BSD-3-Clause" ]

null

import unittest from os import getcwd from click.testing import CliRunner from openvariant.commands.openvar import cat class TestCatCommand(unittest.TestCase): def test_cat_command(self): runner = CliRunner() result = runner.invoke(cat, [f'{getcwd()}/tests/data/dataset']) self.assertEqual(result.exit_code, 0) self.assertNotEqual(result.output, None) def test_cat_command_all_flags(self): runner = CliRunner() result = runner.invoke(cat, [f'{getcwd()}/tests/data/dataset', '--header', '--where', "variant == 'DEL'", '--annotations', f'{getcwd()}/tests/data/dataset/dataset.yaml']) self.assertEqual(result.exit_code, 0) self.assertNotEqual(result.output, None) def test_cat_path_no_exist_command_input(self): runner = CliRunner() result = runner.invoke(cat, [f'{getcwd()}/tests/data/no_exist']) self.assertTrue(f"Error: Invalid value for '[INPUT_PATH]': Path '{getcwd()}/tests/data/no_exist' does not exist." in result.output) self.assertEqual(result.exit_code, 2) def test_cat_path_command_no_exist_where_flag(self): runner = CliRunner() result = runner.invoke(cat, [f'{getcwd()}/tests/data/dataset', '--where', "variant=no_exist"]) self.assertEqual(result.exit_code, 1) def test_cat_command_invalid_where(self): runner = CliRunner() result = runner.invoke(cat, [f'{getcwd()}/tests/data/dataset', '--where']) self.assertEqual(result.exit_code, 2) def test_cat_command_no_exist_annotation(self): runner = CliRunner() result = runner.invoke(cat, [f'{getcwd()}/tests/data/dataset', '--annotations', f'{getcwd()}/tests/data/dataset/no_exist.yaml']) self.assertEqual(result.exit_code, 2) def test_cat_command_invalid_annotation(self): runner = CliRunner() result = runner.invoke(cat, [f'{getcwd()}/tests/data/dataset', '--annotations']) self.assertEqual(result.exit_code, 2) def test_cat_command_no_args(self): runner = CliRunner() result = runner.invoke(cat, []) self.assertEqual(result.exit_code, 1)

37.065574

121

0.640867

2,137

0.945157

0

531

0.234852

8d559eab2b8075257716e7bc85f5c9d82b0d3221

4,766

py

Python

resnet.py

rVSaxena/VAE

26aa3452a0c8f663153d8cfc8bf1686e242d2fac

[ "Unlicense" ]

null

resnet.py

rVSaxena/VAE

26aa3452a0c8f663153d8cfc8bf1686e242d2fac

[ "Unlicense" ]

null

resnet.py

rVSaxena/VAE

26aa3452a0c8f663153d8cfc8bf1686e242d2fac

[ "Unlicense" ]

null

import torch import torch.nn as nn class ResidualEncoderBlock(nn.Module): """ Implements ResidualBlock for rectangular feature maps with input shape == output shape OR input shape == (output shape)*2 ie in all dimensions (except the batch dimension). In the latter case, input_shape must be even in all dimensions (expect the batch dimension) """ def __init__(self, in_channels, out_channels, downsample, kernel_dim=3, normalizer=nn.BatchNorm2d, **kwargs): """ in_channels: int out_channels: int downsample: Boolean kernel_dim: int use nn.Identity to skip normalization """ assert kernel_dim%2==1, "Only odd kernel dimensions supported. Received {}".format(kernel_dim) super(ResidualEncoderBlock, self).__init__() self.downsample=downsample self.in_channels=in_channels self.out_channels=out_channels self.Normalizer1=normalizer(out_channels) self.Normalizer2=normalizer(out_channels) # SAK is shape adjusting kernel if self.downsample or (in_channels!=out_channels): if not self.downsample: self.SAK=nn.Conv2d(in_channels, out_channels, 1, stride=1, bias=False) else: self.SAK=nn.Conv2d(in_channels, out_channels, 1, stride=2, bias=False) stride=2 if self.downsample else 1 self.conv1=nn.Conv2d(in_channels, out_channels, kernel_dim, stride=stride, padding=int((kernel_dim-1)/2)) self.conv2=nn.Conv2d(out_channels, out_channels, kernel_dim, padding=int((kernel_dim-1)/2)) # this one maintains shape. So stride 1 and padd=(k-1)/2 work self.activation1=nn.ReLU(inplace=True) self.activation2=nn.ReLU(inplace=True) return def forward(self, x): """ The shape of x must be accd to (n,c,h,w) """ # compute the first block out=self.conv1(x) out=self.Normalizer1(out) out=self.activation1(out) # ready the input for addition if self.downsample or (self.in_channels!=self.out_channels): x=self.SAK(x) # compute the output out=self.conv2(out) out=self.Normalizer2(out)+x out=self.activation2(out) return out class ResidualDecoderBlock(nn.Module): """ Implements ResidualBlock for rectangular feature maps with input shape == output shape OR 2*input shape == output shape ie in all dimensions (except the batch dimension). In the latter case, input_shape must be even in all dimensions (expect the batch dimension) """ def __init__(self, in_channels, out_channels, upsample, kernel_dim=3, normalizer=nn.BatchNorm2d, **kwargs): """ in_channels: int out_channels: int upsample: Boolean kernel_dim: int use nn.Identity to skip normalization """ assert kernel_dim%2==1, "Only odd dimension supported, got {}".format(kernel_dim) super(ResidualDecoderBlock, self).__init__() self.upsample=upsample self.in_channels=in_channels self.out_channels=out_channels self.Normalizer1=normalizer(out_channels) self.Normalizer2=normalizer(out_channels) # SAK is shape adjusting kernel if self.upsample or (in_channels!=out_channels): if not self.upsample: self.SAK=nn.ConvTranspose2d(in_channels, out_channels, 1, stride=1, bias=False, padding=0) else: self.SAK=nn.ConvTranspose2d(in_channels, out_channels, 1, stride=2, bias=False, padding=0, output_padding=1) stride=2 if self.upsample else 1 output_pad=1 if self.upsample else 0 self.conv1=nn.ConvTranspose2d(in_channels, out_channels, kernel_dim, stride=stride, padding=int((kernel_dim-1)/2), output_padding=output_pad) self.conv2=nn.ConvTranspose2d(out_channels, out_channels, kernel_dim, padding=int((kernel_dim-1)/2)) # this one maintains shape. So stride 1 and padd=(k-2)/2 work self.activation1=nn.ReLU(inplace=True) self.activation2=nn.ReLU(inplace=True) return def forward(self, x): """ The shape of x must be accd to (n,c,h,w) """ # compute the first block out=self.conv1(x) out=self.Normalizer1(out) out=self.activation1(out) # ready the input for addition if self.upsample or (self.in_channels!=self.out_channels): x=self.SAK(x) # compute the output out=self.conv2(out) out=self.Normalizer2(out)+x out=self.activation2(out) return out

34.042857

170

0.640579

4,724

0.991188

0

1,479

0.310323

8d56bf9a638e31e26421d0d5ccd052c3c7de5f95

246

py

Python

camknows/camknows.py

dreoporto/camknows

769aeb91ff16ff654aa1b182f3564dd26a0f7ad6

[ "MIT" ]

2

2021-09-20T12:29:57.000Z

2021-09-28T11:09:06.000Z

camknows/camknows.py

dreoporto/camknows

769aeb91ff16ff654aa1b182f3564dd26a0f7ad6

[ "MIT" ]

null

camknows/camknows.py

dreoporto/camknows

769aeb91ff16ff654aa1b182f3564dd26a0f7ad6

[ "MIT" ]

null

from camera import Camera def main() -> None: try: camera = Camera() camera.start_camera_loop() except KeyboardInterrupt: print('Application closed (KeyboardInterrupt)') if __name__ == '__main__': main()

15.375

55

0.630081

0

50

0.203252