anton-l/python_sample_10k · Datasets at Hugging Face

beexu/testlearngit

3,410,204,070,854

38a0d58103204ad1c0e3447449e0422044e245a7

9637558a4e4a94198342dd4ab7b1706d6bc682d9

/requests git/learnpython/testall.py

9b7d807bf1e24bb1f83e2a13350c26b4e9b091c6

[]

no_license

https://github.com/beexu/testlearngit

28e30efffa8280178b299a11e568f107e50a1f63

3b99237aaf78d09c5b2c473229702bd06aa7ad52

refs/heads/master

2022-04-22T05:39:48.398650

2020-04-25T06:54:35

258,698,945

0

null

# -*- coding: UTF-8 -*- import requests import sys import unittest # sys.path.insert(0, '..') # 这个可以 sys.path.append('..') # 这个不行 # print(sys.path) from learnexcel import * from learnfixexcel import * from learnjson import * from mytest.testinter import * class testurl(unittest.TestCase): def __init__(self): self.learnexcel1 = ExcelMethod() self.learnfixexcel1 = fixtest() self.learnjson1 = Getpython() self.testinter1 = interface1() def run(self, methon, path): self.url = "http://lovebee.crazylaw.cn/single/sign.php" if methon == "get": res, code = self.testinter1.send_get(self.url, path) return res, code elif methon == "post": res, code = self.testinter1.send_post(self.url, path) return res, code def test(self): row = self.learnexcel1.GettestRow() truepath = '' a = [] for i in range(1, row): print(i) url = self.learnfixexcel1.getexcelurl(i) methon = self.learnfixexcel1.getexcelmethon(i) path = self.learnfixexcel1.getexcelpath(i) try: truepath = {'url': ''} truepath['url'] = url # print(truepath) littletruepath = self.learnjson1.getjsonid(path) for key, value in littletruepath.items(): truepath[key] = littletruepath[key] # print('aaa') # print(truepath) except Exception as e: # traceback = __import__('traceback') # print(traceback.print_exc())print_exc print(e) result, code = self.run(methon, truepath) # 存入excel self.learnexcel1.WriteEXcel(i, result) self.learnexcel1.WriteCode(i, code) returndata = self.learnexcel1.Getreturn(i) self.assertIn(returndata, result) print("test") print(code) print(returndata) # result = self.testinter1.send_get('http://lovebee.crazylaw.cn/single/sign.php', truepath) # result = self.testinter1.send_post('http://lovebee.crazylaw.cn/single/sign.php', truepath) # print(result) one1 = type(result) a.append(result) return a if __name__ == '__main__': testa = testurl().test() print(testa)

UTF-8

Python

false

2,458

py

41

testall.py

38

0.550041

0.541427

0

79

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104

Hwlcoder/CNN_conflict_types

17,875,653,910,712

f0b72e5f9d9a2b5e6c1ff28c711cb67173e87b3c

4e7a7570381a344c7b156da9705e996ef1dccdbd

/CNN/SVM+OurInput.py

e01fcb0cf188001ca6c89b1668c2c9c574ff1109

[]

no_license

https://github.com/Hwlcoder/CNN_conflict_types

7dadea6093a55abeae1938c6113c506d84d23568

b049615de539fb3582f34cdda6d0fbf50722a30e

refs/heads/master

2020-06-17T05:27:54.540574

2019-07-08T13:06:11

195,811,301

0

null

#!/usr/bin/python # -*- coding: utf-8 -*- import tensorflow as tf from textProcess3 import * from sklearn.model_selection import StratifiedKFold import os from sklearn.decomposition import PCA from sklearn import svm from sklearn.externals import joblib import time os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' os.environ["CUDA_VISIBLE_DEVICES"] = "0" gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.5) sess = tf.Session(config=tf.ConfigProto(gpu_options=gpu_options)) #得到整个文本的矩阵（包括标签） all_dir_1 = 'data/cate300_cut/' all_dir_2 = 'data/parser/' categories, cat_to_id = read_category() all_xdata, all_ydata = process_file(all_dir_1,all_dir_2, cat_to_id) #N折交叉验证，先将all_xdata和all_ydata分成N组 stratified_folder = StratifiedKFold(n_splits=10, random_state=0, shuffle=False) train_acc = [] test_acc = [] train_xdata = np.zeros((270,3,3)) train_labels = np.zeros(270) test_xdata = np.zeros((30,3,3)) test_labels = np.zeros(30) fp = open('result/'+'AccurancyResultSVM.txt','w') for train_index, test_index in stratified_folder.split(all_xdata, all_ydata): for i in range(len(train_index)): train_xdata[i] = all_xdata[train_index[i]] train_labels[i] = all_ydata[train_index[i]] for i in range(len(test_index)): test_xdata[i] = all_xdata[test_index[i]] test_labels[i] = all_ydata[test_index[i]] t = time.time() # svm方法 nsamples, nx, ny = train_xdata.shape d2_train_dataset = train_xdata.reshape((nsamples, nx * ny)) nsamples1, nx1, ny1 = test_xdata.shape d2_test_dataset = test_xdata.reshape((nsamples1, nx1 * ny1)) pca = PCA(n_components=0.8, whiten=True) train_x = pca.fit_transform(d2_train_dataset) test_x = pca.transform(d2_test_dataset) svc = svm.SVC(kernel='rbf', C=10) svc.fit(train_x, train_labels) pre = svc.predict(test_x) acc = float((pre == test_labels).sum()) / len(test_x) test_acc.append(acc) print (u'准确率：%f,花费时间：%.2fs' % (acc, time.time() - t)) joblib.dump(svc, "train_svm_model.m") print ("Done\n") sum_acc = 0 for i in test_acc: sum_acc = sum_acc+i print (sum_acc/10) modeluse = joblib.load("train_svm_model.m") my_data_path1 = "data/test/liu/test_3/" my_data_path2 = "data/test/my/test_parser3/" categories, cat_to_id = read_category() test_1, test_2 = process_file(my_data_path1,my_data_path2,cat_to_id) nsamples, nx, ny = test_1.shape d2_test_data = test_1.reshape((nsamples, nx * ny)) d2_test_data_2 = pca.transform(d2_test_data) print(test_2) print(modeluse.predict(d2_test_data_2))

UTF-8

Python

false

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py

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SVM+OurInput.py

10

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Muzer/smartbot

10,823,317,626,496

facaa937cca505a07ebae77e5243694936eec16a

5ebe97e9597c1bd7b2162d7c092897f557472b51

/smartbot/backend.py

e0ff94bec31844d59a0edc379278d0b9f00a5ad0

[ "MIT" ]

permissive

https://github.com/Muzer/smartbot

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refs/heads/master

2021-01-24T21:47:23.583529

2015-05-05T15:09:22

16,807,677

0

null

from .events import Event class Backend: def __init__(self): self.storage = None self.event_listeners = [] self.on_connect = Event() self.on_disconnect = Event() self.on_ready = Event() self.on_join = Event() self.on_message = Event()

UTF-8

Python

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py

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backend.py

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36

Patchkat/Advent-Of-Code-2020

16,054,587,778,825

58814575ed7b4e1ad76e655afd36f0bcd48704a8

e71fd1e081af09cf3a5f8ccc3071bfbdb57ad5d1

/Day 9/AoC9A.py

542ca30dcb2ef0d9edebecb4f6d6fe0fe4fa61be

[]

no_license

https://github.com/Patchkat/Advent-Of-Code-2020

339b76ce2bd61cc1c91d225a2959a0acebbc43d9

7d3abee87c1c3df434cc907594b329b638839e0d

refs/heads/main

2023-04-28T01:54:38.975577

2021-05-04T16:27:09

318,089,752

0

null

f = [int(x.rstrip('\n')) for x in open('xmas.txt').readlines()] preamble_length = 25 for x in range(preamble_length, len(f)): current_nums = f[x-preamble_length:x] summed = False for y in current_nums: if (f[x] - y) in current_nums: summed = True if summed == False: print(f[x]) break

UTF-8

Python

false

337

py

39

AoC9A.py

39

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jakobpederson/tweetbot

8,074,538,543,671

a12f58a3d4d45e11d3cfdbd60fcf20304a15a99a

404a25c21c978ed0025be797c5639f5df8f0652a

/helloworld.py

e3aa6544a92f6a14a705eec171392beee1e88b2b

[]

no_license

https://github.com/jakobpederson/tweetbot

670b34dff5322b9a066c9a2d0cebc804ea21018a

8b1fb4b6e249e85a97dd5660ff8f4c0b671fe8f3

refs/heads/master

2021-01-20T00:14:45.139541

2017-04-23T23:42:07

89,100,049

0

null

#!/usr/bin/env python # -*- coding: utf-8 -*- from datetime import datetime import tweepy from tweepy.error import TweepError import time import random import string import sys import KEYS_AND_TOKENS # argfile = str(sys.argv[1]) CONSUMER_KEY = KEYS_AND_TOKENS.CONSUMER_KEY CONSUMER_SECRET = KEYS_AND_TOKENS.CONSUMER_SECRET ACCESS_KEY = KEYS_AND_TOKENS.ACCESS_KEY ACCESS_SECRET = KEYS_AND_TOKENS.ACCESS_SECRET auth = tweepy.OAuthHandler(CONSUMER_KEY, CONSUMER_SECRET) auth.set_access_token(ACCESS_KEY, ACCESS_SECRET) api = tweepy.API(auth) # filename = open(argfile, 'r') # f = filename.readlines() # filename.close() format = '%Y-%m-%d %H:%M' def deck(): cards = [ 'The Fool', 'The Magician', 'The High Priestess', 'The Empress', 'The Emperor', 'The Hierophant', 'The Lovers', 'The Chariot', 'Strength', 'The Hermit', 'Wheel of Fortune', 'Justice', 'The Hanged Man', 'Death', 'Temperance', 'The Devil', 'The Tower', 'The Star', 'The Moon', 'The Sun', 'Judgement', 'The World', ] houses = ["Cups", "Wands", "Swords", "Pentacles"] royals = ["Ace", "Page", "Knight", "Queen", "King"] number_deck = [] for house in houses: number_deck.extend(['{} of {}'.format(x, house) for x in list(range(2, 11))]) for house in houses: number_deck.extend(['{} of {}'.format(x, house) for x in royals]) cards.extend(number_deck) return cards while(True): try: hand = random.sample(deck(), 3) final_hand = [] for card in hand: orientation = random.sample(["", "Inverted"], 1) if orientation[0] == "Inverted": final_hand.append('{} ({})'.format(card, "Inverted")) else: final_hand.append('{}'.format(card)) final_hand.append(datetime.now().strftime(format)) message = '1.) {0}\n2.) {1}\n3.) {2}\n\n{3}'.format(*final_hand) api.update_status(message) print(message) except TweepError: print('pass') pass time.sleep(900)

UTF-8

Python

false

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py

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helloworld.py

1

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AZ015/design_patterns

19,095,424,625,678

7a83c60cd3f7dbb9998bf2964661b91cfccc581d

2e223fb4771146ad0f80085b60aee6110cfdeff7

/Behavioral/observer/push_observer/main.py

e83cb5624a82a5d627ba78cd1942aa29eebf202c

[]

no_license

https://github.com/AZ015/design_patterns

c6b2612ff5ce169f0c8e343c1f9e670b2b593e96

704c4b29d6fab2dfaf7c4e8923909276eaabbfa7

refs/heads/master

2020-12-21T00:59:08.009764

2020-02-05T12:02:29

236,259,486

0

null

from Behavioral.observer.push_observer import DataSource, SpreadSheet, Chart if __name__ == '__main__': data_source = DataSource() sheet_1 = SpreadSheet() sheet_2 = SpreadSheet() chart = Chart() data_source.add_observer(sheet_1) data_source.add_observer(sheet_2) data_source.add_observer(chart) data_source.value = 1

UTF-8

Python

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main.py

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Tamar20/Google-project

309,237,654,816

936ff441913f5a2238dbb77694875b432d2e06da

0f8a171012617f64df5a7c98845239a583225d53

/init.py

f3b9328fc4ca166f6edb05e764369a8d5a637e07

[]

no_license

https://github.com/Tamar20/Google-project

8608af4b242f052ae1341ad300561fe03ad16e3d

ffac4d8df66375c3077cbb98dee47a28200c2db6

refs/heads/master

2023-02-21T04:30:24.072228

2021-01-21T14:19:15

331,651,072

0

null

import os import string from trie import * def edit_sentence(prefix: str) -> str: prefix = prefix.translate(str.maketrans('', '', string.punctuation)) return ' '.join(prefix.lower().split()) def init_data(): trie = Trie() init_trie(trie) return trie def init_trie(trie): for line, path, line_num in uploading_files(): line = edit_sentence(line) offset = 1 while line != '': trie.insert(line, path, line_num, offset) line = line[1:] offset += 1 def uploading_files(): for root, dirs, files in os.walk(f"./data"): for file in files: curr_path = f"./{root}/{file}" with open(curr_path) as file: for line_num, line in enumerate(file, 1): yield line, curr_path, line_num

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Python

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init.py

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pengliu380/Feature-Detectors

12,429,635,354,752

fcfc26575f85ae113b706f4cc041f20da95fc164

6089d4b659071747aa623041c6b221096f8d07e7

/test.py

69e68f1dae1c3838cb28acd50df6e13d90b31ecc

[]

no_license

https://github.com/pengliu380/Feature-Detectors

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refs/heads/master

2020-04-02T16:55:51.586041

2018-10-25T08:43:24

154,635,415

4

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null

import cv2 as cv import numpy as np # Merge pictures classname = ['bikes_blur', 'graffiti_viewpoints', 'bark_zoom_rotation', 'cars_light'] method = ['hcd', 'dog', 'fast', 'mser'] for i in range(4): for j in range(4): filename = 'result/' + classname[i] +'/' + method[j] img = cv.imread(filename + '_1.jpg') for m in range(2): temp = cv.imread( filename + '_' + str(2*m+3) +'.jpg') img = np.hstack((img, temp)) cv.imwrite(filename + '.jpg', img)

UTF-8

Python

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test.py

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johnnyguogrit/Python--

2,894,807,968,924

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/food.py

5ebcc304d2ac2e9bcd8222308470db1300caffaf

[]

no_license

https://github.com/johnnyguogrit/Python--

23123220e8f7f5ed848b8e3593e47df000195f36

340c00f97449a8691ee3b2025729bdf97ff3a2a8

refs/heads/master

2020-08-14T21:03:16.767061

2019-10-18T11:07:04

215,232,213

4

0

null

false

2019-10-15T08:13:40

2019-10-15T07:15:16

2019-10-15T07:15:19

2019-10-15T08:13:40

0

null

false

my_foods = ['pizza', 'falafel', 'carrot cake'] friend_foods = my_foods[:] print("My favorite foods are:") my_foods.append('cannoli') print(my_foods) print("\nMy friends' favorite foods are:") friend_foods.append('ice cream') print(friend_foods) print("\nThe first three items in the list are:") print(friend_foods[:3]) print("\nThree items from the middle of the list are:") print(my_foods[int(len(my_foods)/2):int(len(my_foods)/2)+3]) print("\nLast three items in the list are") print(my_foods[-3:]) for my_food in my_foods: print(my_food) for friend_food in friend_foods: print(friend_food)

UTF-8

Python

false

606

py

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food.py

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movie5/deeplearning_from_scratch

10,033,043,616,744

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/ch1.헬로 파이썬/1.6.matplotlib.py

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[ "MIT" ]

permissive

https://github.com/movie5/deeplearning_from_scratch

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refs/heads/master

2023-05-29T23:19:28.262873

2023-05-02T04:52:34

283,549,037

0

MIT

true

2020-07-29T16:29:28

2020-07-29T16:29:27

2020-07-29T16:27:47

2019-03-15T04:34:44

60,444

0

null

false

import numpy as np import matplotlib.pyplot as plt from matplotlib.image import imread # 1.6.1 단순한 그래프 그리기 # 데이터 준비 x = np.arange(0, 6, 0.1) y = np.sin(x) # 그래프 그리기 # plt.plot(x, y) # plt.show() # 1.6.2 pyplot의 기능 # 데이터 준비 x = np.arange(0, 6, 0.1) y1 = np.sin(x) y2 = np.cos(x) # 그래프 그리기 plt.plot(x, y1, label="sin") plt.plot(x, y2, linestyle="--", label="cos") plt.xlabel("x") # 축이름 plt.ylabel("y") plt.title('sin & cos') plt.legend() plt.show() # 1.6.3 이미지 표시하기 img = imread('../dataset/lena.png') plt.imshow(img) plt.show()

UTF-8

Python

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shubhamverma1997/Sentiment-Dictionary

15,006,615,736,581

d433c7af2e70c4a8236a2661bc9b5b4030c5c242

8b4e33b960a7b89d4a82eb61546dd1fc53e943eb

/countForeign.py

7ebf770539917de9f0e402e209a6d3d06d68c358

[]

no_license

https://github.com/shubhamverma1997/Sentiment-Dictionary

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refs/heads/master

2020-03-23T16:19:07.790928

2018-05-15T14:26:28

null

0

null

import pandas as pd from langdetect import detect Dict = pd.read_csv('Dict.csv', delimiter = ",") wlist = [] for word in Dict['Word']: wlist.append(word) forCnt = 0 TotWord = len(wlist) print TotWord wordLang = {} for word in wlist: wordLang[word] = detect(word) df = pd.DataFrame(wordLang.items(), columns =['word', 'lang']) df.to_csv(path_or_buf = 'cntForeign.csv', sep = ',', index = False)

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Python

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countForeign.py

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Tilana/Classification

17,523,466,572,760

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/lda/Collection.py

c5941d04c289023320878b1efff904fc747dc5dc

[]

no_license

https://github.com/Tilana/Classification

76e111a52a1ceda6a2c090e65a03cd6c087c0fed

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refs/heads/develop

2020-05-23T07:53:12.885056

2018-05-08T07:29:29

80,451,934

3

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2018-04-12T08:11:26

2017-01-30T18:49:53

2018-04-09T23:49:41

2018-04-12T08:11:25

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# encoding=utf8 from docLoader import loadData from Preprocessor import Preprocessor #import preprocessor as tweetPreprocessor from FeatureExtractor import FeatureExtractor import cPickle as pickle import listUtils as utils import pandas as pd import numpy as np import os import pdb class Collection: def __init__(self, path=None): self.data = pd.DataFrame() if path: self.path = path self.data = loadData(path) self.nrDocs = len(self.data) def cleanDataframe(self, textField='text'): dataWithText = self.data[self.data[textField].notnull()] cleanDataframe = dataWithText.dropna(axis=1, how='all') self.data = cleanDataframe.reset_index() self.nrDocs = len(self.data) def vectorize(self, vecType='tfidf', vocabulary=None, field='text', ngrams=(1,2), maxFeatures=8000): self.buildVectorizer(vecType=vecType, ngram_range=ngrams, min_df=5, max_df=0.50, max_features=maxFeatures, binary=False, vocabulary=vocabulary) self.trainVectorizer(vecType, field) def buildVectorizer(self, vecType='tfIdf', min_df=10, max_df=0.5, stop_words='english', ngram_range = (1,2), max_features=8000, vocabulary=None, binary=False): self.preprocessor = Preprocessor(processor=vecType, min_df=min_df, max_df=max_df, stop_words=stop_words, ngram_range=ngram_range, max_features=max_features, vocabulary=vocabulary, binary=binary) def trainVectorizer(self, vecType='tfIdf', field='text'): trainDocs = self.data[field].tolist() self.data[vecType] = self.preprocessor.trainVectorizer(trainDocs) self.vocabulary = self.preprocessor.vocabulary def save(self, path): self.savePreprocessor(path) with open(path +'.pkl', 'wb') as f: pickle.dump(self, f, -1) def load(self, path): model = pickle.load(open(path+'.pkl', 'rb')) self.data = model.data self.loadPreprocessor(path) return self def savePreprocessor(self, path): if hasattr(self, 'preprocessor'): self.preprocessor.save(path) del self.preprocessor def loadPreprocessor(self, path): preprocessor = Preprocessor() if os.path.exists(path+'.pkl'): self.preprocessor = preprocessor.load(path) self.vocabulary = self.preprocessor.vocabulary def existsProcessedData(self, path): return os.path.exists(path + '.pkl') def cleanTexts(self): preprocessor = Preprocessor() self.applyToRows('text', preprocessor.removeHTMLtags, 'cleanText') self.applyToRows('cleanText', preprocessor.cleanText, 'cleanText') self.applyToRows('cleanText', preprocessor.numbersInTextToDigits, 'cleanText') def removeStopwords(self): preprocessor = Preprocessor() self.applyToRows('cleanText', preprocessor.removeStopwords, 'cleanTokens') def cleanTweets(self): self.applyToRows('decodeTweet', tweetPreprocessor.clean, 'cleanTweets') def extractDate(self): self.applyToRows('tweet_time', separateDateAndTime, 'date') def extractDate(self): self.data['date'] = self.data.apply(lambda doc: doc['tweet_time'].split('T')[0], axis=1) def extractEntities(self, path=None): featureExtractor = FeatureExtractor(path) self.applyToRows('text', featureExtractor.entities, 'entities') def setRelevantWords(self): self.applyToRows('tfidf', self.relevantWords, 'relevantWords') def relevantWords(self, wordWeights): sortedWeights = sorted(enumerate(wordWeights), key=lambda x: x[1], reverse=True) sortedWeights = [wordWeight for wordWeight in sortedWeights if wordWeight[1]>0] return [(self.vocabulary[wordIndex], weight) for (wordIndex, weight) in sortedWeights] def applyToRows(self, field, fun, name, args=None): if args: self.data[name] = self.data.apply(lambda doc: fun(doc[field], args), axis=1) else: self.data[name] = self.data.apply(lambda doc: fun(doc[field]), axis=1)

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Ayush1959/Python-prgs

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def big (x): tmp = max (x) return tmp def small (x): tmp = min (x) return tmp

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bpiche/sent2vec

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2020-04-07T14:45:12.243891

2018-11-20T22:38:28

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""" Slightly modified from https://github.com/peter3125/sentence2vec with some new methods for preprocessing sentences, calculating cosine similarity with sklearn, and a pipeline for comparing an input sentence against a corpus for some braindead question answering purposes """ from __future__ import print_function import time import gensim from gensim.corpora.wikicorpus import WikiCorpus from gensim.models.doc2vec import Doc2Vec import spacy import math import numpy as np import pandas as pd from sklearn.decomposition import PCA from sklearn.metrics.pairwise import cosine_similarity from typing import List nlp = spacy.load('en') gnews_model = gensim.models.KeyedVectors.load_word2vec_format('~/Downloads/GoogleNews-vectors-negative300.bin', binary=True) class Word: def __init__(self, text, vector): self.text = text self.vector = vector class Sentence: def __init__(self, word_list): self.word_list = word_list # return the length of a sentence def len(self): return(len(self.word_list)) def __str__(self): word_str_list = [word.text for word in self.word_list] return ' '.join(word_str_list) def __repr__(self): return self.__str__() def get_word_frequency(word_text, vec_model): wf = vec_model.vocab[word_text].count return(wf) def preloading_sentences(sentence_list, model): """ Converts a list of sentences into a list of Sentence (and Word) objects Pretty similar to what peter3125/sentence2vec.git does input: a list of sentences, embedding_size output: a list of Sentence objects, containing Word objects, which contain 'text' and word vector attributes """ embedding_size = 300 all_sent_info = [] for sentence in sentence_list: sent_info = [] spacy_sentence = nlp(sentence) for word in spacy_sentence: if word.text in model.vocab: sent_info.append(Word(word.text, model[word.text])) # todo: if sent_info > 0, append, else don't all_sent_info.append(Sentence(sent_info)) return(all_sent_info) def sentence_to_vec(sentence_list, embedding_size, a=1e-3): """ A SIMPLE BUT TOUGH TO BEAT BASELINE FOR SENTENCE EMBEDDINGS Sanjeev Arora, Yingyu Liang, Tengyu Ma Princeton University """ sentence_set = [] # intermediary list of sentence vectors before PCA sent_list = [] # return list of input sentences in the output for sentence in sentence_list: this_sent = [] vs = np.zeros(embedding_size) # add all w2v values into one vector for the sentence sentence_length = sentence.len() for word in sentence.word_list: this_sent.append(word.text) word_freq = get_word_frequency(word.text, gnews_model) a_value = a / (a + word_freq) # smooth inverse frequency, SIF vs = np.add(vs, np.multiply(a_value, word.vector)) # vs += sif * word_vector vs = np.divide(vs, sentence_length) # weighted average, normalized by sentence length sentence_set.append(vs) # add to our existing re-caculated set of sentences sent_list.append(' '.join(this_sent)) # calculate PCA of this sentence set pca = PCA(n_components=embedding_size) pca.fit(np.array(sentence_set)) u = pca.components_[0] # the PCA vector u = np.multiply(u, np.transpose(u)) # u x uT # pad the vector? (occurs if we have less sentences than embeddings_size) if len(u) < embedding_size: for i in range(embedding_size - len(u)): u = np.append(u, 0) # resulting sentence vectors, vs = vs -u * uT * vs sentence_vecs = [] for vs in sentence_set: sub = np.multiply(u, vs) sentence_vecs.append(np.subtract(vs, sub)) return(sentence_vecs, sent_list) def get_sen_embeddings(sentence_list): """ Create Sentence and Word objects from a list and pass them to sentence_to_vec() Return a list of _sentence embeddings_ for all sentences in the list """ embedding_size = 300 all_sent_info = preloading_sentences(sentence_list, gnews_model) sentence_vectors, sent_list = sentence_to_vec(all_sent_info, embedding_size) return(sentence_vectors, sent_list) def get_cos_distance(sentence_list): """ Create Sentence and Word objects from a list and pass them to sentence_to_vec() Return a matrix of the _cosine distance_ of elements in the matrix This is used for sentence similarity functions input: A list of plaintext sentences output: A list of sentence distances """ sentence_vectors, sent_list = get_sen_embeddings(sentence_list) cos_list = cosine_similarity(sentence_vectors, Y=None, dense_output=True) return(cos_list, sent_list) def get_most_similar(utterance, sentence_list): """ Takes an input utterance and a corpus sentence_list to compare it to, and returns a dict of the utterance, closest question, and relevant answer """ sentence_list.append(utterance) cos_list, sent_text = get_cos_distance(sentence_list) tmp_list = list(cos_list[len(cos_list)-1]) tmp_indx = tmp_list.index(max(tmp_list[0:len(tmp_list)-1])) return(tmp_indx) if __name__ == "__main__": # load questions to compare simliarity to input/test utterances faq_csv = pd.read_csv("./utterances_test.csv") sentence_list = list(faq_csv['utterance']) answer_list = list(faq_csv['answer']) max_idx = get_most_similar(utterance, sentence_list) # print the relevant question and answer pair sentence_list[max_idx] answer_list[max_idx]

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# GENERATED BY KOMAND SDK - DO NOT EDIT from setuptools import setup, find_packages setup(name='recorded_future-rapid7-plugin', version='1.0.2', description='Recorded Future arms threat analysts, security operators, and incident responders to rapidly connect the dots and reveal unknown threats', author='rapid7', author_email='', url='', packages=find_packages(), install_requires=['komand'], # Add third-party dependencies to requirements.txt, not here! scripts=['bin/komand_recorded_future'] )

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clbm/SESSDSA-2048-F19-X-ray-

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Inf = float('inf') import numpy as np Weight_L = np.array((1.0,1.05,1.1,1.15,1.2,1.2,1.2,1.2)) Weight_R = np.array((1.2,1.2,1.2,1.2,1.15,1.1,1.05,1.0)) def getmark(board, isFirst:bool): "评估函数" Value, Belong = np.array(board.getRaw()).transpose((2,0,1)) return np.sum(((Belong<<Value)*Weight_L-((1-Belong)<<Value)*Weight_R)*(1+0.02*Value))*(1 if isFirst else -1) def simulation(depth:int, Round:int, Gamemode:int, is_max:bool, board, alpha, beta): #模拟对战 global Inf mode,isFirst = Gamemode>>1,not Gamemode&1 if depth >= 6 or Round == 500: #大于最大深度时 alpha = getmark(board,isFirst) return (alpha,alpha) #以下为一般情况 if mode == 0: #落子阶段 #第一步，找出全部可行落子 Self_part = board.getNext(isFirst,Round) #自己棋盘落子的位置 #available为全部可行位置 available = [Self_part] if Self_part else [] if Round > 30:available += board.getNone(not isFirst) #对手棋盘可落子的位置 #第二步，迭代模拟 if len(available) == 0: #无合法移动的特殊情况 if not depth&1:return -Inf, -Inf return simulation(depth+1,Round,Gamemode+1,not is_max,board,alpha,beta) #一般情况 result = available[0] for position in available: #子树对决 new_board = board.copy() new_board.add(isFirst,position) alpha_beta = simulation(depth+1,Round,Gamemode+1,not is_max,new_board,alpha,beta) #更新alpha-beta if is_max: if not depth:old_alpha = alpha #对于树根，需要比较alpha值的变化 alpha = max(alpha, *alpha_beta) if not depth and alpha > old_alpha: result = position #当alpha值变大时，落子位置更新 else: beta = min(beta, *alpha_beta) if alpha >= beta: break#alpha-beta剪枝 #返回结果 if depth:return alpha, beta return result else: #合并阶段 No_available = True for move in range(4): #跳过非法合并 new_board = board.copy() if not new_board.move(isFirst, move):continue elif No_available: No_available = False if not depth: result = move #子树对决 alpha_beta = simulation(depth+1,Round+1-isFirst,(Gamemode+1)&3,not is_max,new_board,alpha,beta = beta) #更新alpha-beta if is_max: if not depth:old_alpha = alpha#对于树根，需要比较alpha值的变化 alpha = max(alpha, *alpha_beta) if not depth and alpha > old_alpha:result = move#当alpha值变大时，落子位置更新 else:beta = min(beta, *alpha_beta) if alpha >= beta:break#alpha-beta剪枝 #无合法移动的特殊情况 if No_available: if not depth&1: return -Inf, -Inf return simulation(depth+1,Round + 1-isFirst,(Gamemode+1)&3,not is_max,board,alpha,beta) else: if depth: return alpha, beta return result class Player: def __init__(self, isFirst:bool, array:list): self.isFirst = isFirst def output(self, currentRound:int, board, mode:str): if mode == 'position':Gamemode = 1^self.isFirst # 给出己方下棋的位置 elif mode == 'direction':Gamemode = 2+(1^self.isFirst) # 给出己方合并的方向 else:return return simulation(0, currentRound,Gamemode,True,board,-Inf,Inf)

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lishulongVI/rest-web

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from django_filters.rest_framework import DjangoFilterBackend from rest_framework import mixins, viewsets, serializers class BaseFilter(DjangoFilterBackend): def filter_queryset(self, request, queryset, view): old = request.GET._mutable request.GET._mutable = True if 'deleted' not in request.query_params: request.query_params['deleted'] = 0 request.GET._mutable = old return super().filter_queryset(request, queryset, view) class BaseViewSet(mixins.CreateModelMixin, mixins.ListModelMixin, mixins.RetrieveModelMixin, mixins.UpdateModelMixin, viewsets.GenericViewSet): filter_backends = (BaseFilter,) filterset_fields = ('deleted',) class BaseModelSerialize(serializers.ModelSerializer): update_datetime = serializers.DateTimeField(format="%Y-%m-%d %H:%M:%S", required=False, read_only=True)

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DCC-CC4401/2018-1-Soft-Where-T4

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from mainApp.models import Action, User from articlesApp.models import Article from django.db import models class Loan(Action): article = models.ForeignKey(Article, on_delete=models.CASCADE) admin = models.ForeignKey(User, related_name="admin_art_prestador", on_delete=models.CASCADE, default=None, null=True)

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kiruthihan10/Music-Classifier

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2020-05-03T10:36:16.601275

2019-03-30T16:37:01

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################################################## #Import Libs import scipy import sklearn as sk import matplotlib.pyplot as plt from PIL import Image import numpy import numpy as np from sklearn.pipeline import Pipeline from sklearn.preprocessing import StandardScaler from sklearn.svm import LinearSVC from sklearn.model_selection import cross_val_score from sklearn.ensemble import RandomForestRegressor from sklearn.linear_model import SGDClassifier from sklearn.base import BaseEstimator from sklearn.model_selection import cross_val_predict from sklearn.metrics import confusion_matrix ##################################################### #Get datas new = [] old = [] new_file = open("new_song_array.txt",'r') import time star = time.time() y=[] for line in new_file: data = line.strip().split(',') temp = [] for i in data: if i.isdigit(): temp.append(float(i)) data = temp new.append(data) y.append(1) #print(data) print(len(y)) print("done") new_file.close() old_file = open("old_song_array.txt",'r') for line in old_file: data = line.strip().split(',') temp = [] for i in data: if i.isdigit(): temp.append(float(i)) data = temp new.append(data) y.append(0) print(len(new)) print("done") print(time.time()-star) #################################################### #Shuffle chaos = np.random.permutation(len(new)) X=[] Y=[] for i in chaos: X.append(new[i]) Y.append(y[i]) train_X = X[:90] train_Y = Y[:90] test_X = X[90:] test_Y = Y[90:] print(np.array(train_X).shape) print(np.array(train_Y).shape) #################################################### #Create Classifications svm_clf = Pipeline((("Scaler",StandardScaler()),("linear_svc",LinearSVC(C=1, loss="hinge")),)) svm_clf.fit(train_X,train_Y) test = svm_clf.predict(test_X) n = 0 correct = 0 for i in test: if i == test_Y[n]: correct+=1 n+=1 print (float(correct)*100/len(test)) svm_score = cross_val_score(svm_clf,train_X,train_Y,cv=3,scoring="accuracy") print (svm_score) y_train_pred = cross_val_predict(svm_clf,train_X,train_Y,cv=3) print (confusion_matrix(train_Y,y_train_pred)) if True: sgd_clf = SGDClassifier(random_state=42) sgd_clf.fit(train_X,train_Y) test = sgd_clf.predict(test_X) # print len(test) # print len(test_Y) n = 0 correct = 0 for i in test: if i == test_Y[n]: correct+=1 n+=1 print (float(correct)*100/len(test)) #print test_Y sgd_score = cross_val_score(sgd_clf,train_X,train_Y,cv=3,scoring="accuracy") print (sgd_score) y_train_pred = cross_val_predict(sgd_clf,train_X,train_Y,cv=3) print (confusion_matrix(train_Y,y_train_pred))

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''' Created on Dec 11, 2013 @author: Jilin Yan ''' import datetime class Ticket(object): ''' Basic class for ticket ''' cities = { 'Boston' : 94, 'New York' : 123, 'Philadelphia' : 127, 'Washington' : 142, 'Toronto' : 145 } companies = { 'MegaBus' : 1, 'BoltBus' : 2 } def __init__(self, origin, destination, depart_date, depart_time, arrive_time, price, company): ''' Initializes the ticket's data ''' self.origin = origin self.destination = destination self.depart_date = depart_date.strftime("%Y-%m-%d") self.depart_time = self.get_depart_time(depart_time) self.arrive_time = self.get_arrive_time(depart_time, arrive_time) self.price = price self.company = company def get_origin_index(self): ''' Returns the origin city's index ''' return self.cities[self.origin] def get_destination_index(self): ''' Returns the destination city's index ''' return self.cities[self.destination] def get_depart_time(self, depart_time): ''' Returns the depart time ''' d_time = datetime.datetime.strptime(self.depart_date + " " + depart_time, '%Y-%m-%d %I:%M%p') return d_time.strftime("%Y-%m-%d %H:%M:%S") def get_arrive_time(self, depart_time, arrive_time): ''' Returns the arrive time ''' d_time = datetime.datetime.strptime(self.depart_date + " " + depart_time, '%Y-%m-%d %I:%M%p') a_time = datetime.datetime.strptime(self.depart_date + " " + arrive_time, '%Y-%m-%d %I:%M%p') if a_time < d_time: a_time += datetime.timedelta(days = 1) return a_time.strftime("%Y-%m-%d %H:%M:%S") def get_company_index(self): ''' Returns the company's index ''' return self.companies[self.company] def get_ticket(self): ''' Print the ticket information ''' print "origin: %s" % self.origin, print " | destination: %s" % self.destination, print " | depart_date: %s" % self.depart_date, print " | depart_time: %s" % self.depart_time, print " | arrive_time: %s" % self.arrive_time, print " | price: %.2f" % self.price, print " | company: %s" % self.company

UTF-8

Python

false

2,568

py

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ticket.py

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0.508956

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FabSchilling/WarframePrimeManager

1,176,821,039,661

6d5351e6af69c7c78e1531e40b0a109a900a3d50

11cdf3279144b6aaab299ec2878a5c6aad88b97a

/database_functions.py

537f491e595b47c538ad0003acb70809e753f05b

[]

no_license

https://github.com/FabSchilling/WarframePrimeManager

5cdfd530feec53327ebe63c6008e5ec4d80a5d72

ec42729ed1aab5c90270c9caff8e883e82f31fe8

refs/heads/master

2021-10-24T18:03:24.214454

2018-05-05T17:30:24

125,201,237

0

null

import json import re from six.moves import urllib from tinydb import TinyDB, Query db = TinyDB('db.json') qr = Query() def updateDatabase(): download_Path_allinone = "https://destiny.trade/JSON/allinone.json" urllib.request.urlretrieve(download_Path_allinone, "./allinone.json") resetDatabase() def resetDatabase(): db.purge() saveRelicDataToDatabase(loadDataFromJSON('./allinone.json')) def loadDataFromJSON(path): json_data=open(path).read() data = json.loads(json_data) return data def saveRelicDataToDatabase(data): relic_Data = data["relicRewards"] tier_list = ["Lith", "Meso", "Neo", "Axi"] for relics in relic_Data: for item in relic_Data[relics]['rewards']: db.insert({'tier': relic_Data[relics]['tier'], 'type': relic_Data[relics]['type'], 'name': item['name'], 'rarity': item['intact']['name'], 'vaulted': False}) vaulted_Relics = getVaultedRelicsFromData(data) for tier in tier_list: for relic_type in vaulted_Relics[tier_list.index(tier)]: db.update({'vaulted': True}, ((qr.tier == tier) & (qr.type == relic_type))) def getListOfPartsFromItem(item): parts = [] db_list = db.search((qr.name.matches(item))) for i in db_list: parts.append(i["name"]) return parts def getVaultedRelicsFromData(data): relic_data = getAllRelics() not_vaulted_relics = [[], [], [], []] vaulted_relics = relic_data pattern = '\w*\s\w*\sRelic' text = str(data) for match in re.findall(pattern, text): if match[:4] == 'Lith': if match[5:7] in relic_data[0]: not_vaulted_relics[0].append(match[5:7]) elif match[:4] == 'Meso': if match[5:7] in relic_data[1]: not_vaulted_relics[1].append(match[5:7]) elif match[:3] == 'Neo': if match[4:6] in relic_data[2]: not_vaulted_relics[2].append(match[4:6]) elif match[:3] == 'Axi': if match[4:6] in relic_data[3]: not_vaulted_relics[3].append(match[4:6]) not_vaulted_relics = [list(set(not_vaulted_relics[0])), list(set(not_vaulted_relics[1])), list(set(not_vaulted_relics[2])), list(set(not_vaulted_relics[3]))] count = 0 for tier in not_vaulted_relics: for type in tier: vaulted_relics[count].remove(type) count += 1 return vaulted_relics def getAllRelics(): relic_list =[] query_result = db.all() for tier in ['Lith', 'Meso', 'Neo', 'Axi']: sub_list = [] for relic in query_result: if relic["tier"] == tier: sub_list.append(relic["type"]) sub_list = list(set(sub_list)) sub_list = sorted(sub_list) relic_list.append(sub_list) return relic_list def isRelicVaulted(tier, type): relic = db.get((qr.tier == tier) & (qr.type == type)) return relic["vaulted"]

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database_functions.py

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hienha/python

2,697,239,493,916

de2e912c30d8b939d51fa2bf3dd65d1986c19e47

826b521587f1384b4d6de83819d6f75d59c2d71d

/apepy/codes/1-Python基础篇/1-2_Python基础进阶/1.8_递归列出目录里的文件.py

de6efe323789712d0302d6bf5fc738246d0ee49e

[]

no_license

https://github.com/hienha/python

b69be98bba5939b89fadd7feacb358b9b59de9d2

a7c1d44be3f7c3ee569dcbca0c7b5c202d40041e

refs/heads/master

2018-05-31T16:48:44.295948

2018-05-30T10:04:47

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#!/usr/bin/env python import os import sys def print_files(path): lsdir = os.listdir( path ) files = [ i for i in lsdir if os.path.isfile( os.path.join(path, i) ) ] dirs = [ i for i in lsdir if os.path.isdir( os.path.join(path,i) ) ] if files: for f in files: print os.path.join(path, f) if dirs: for d in dirs: print_files( os.path.join(path, d) ) print_files( sys.argv[1] )

UTF-8

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1.8_递归列出目录里的文件.py

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Texas-Waitlisters/BlinkLink

13,984,413,544,580

e700d7b079e4546c945d8c9e230881d0aad4591f

813b2275838f234190d7a325cf22cee4b589944a

/Redtooth/RedtoothWindows/Windows.py

e35d2c092dc81790198abd4557017a1a78726a65

[]

no_license

https://github.com/Texas-Waitlisters/BlinkLink

ef57c7750d6718124e0014026643bb55d9fb288d

7554cb227ab28767e9508f3d0c59d9f13ad3db20

refs/heads/master

2021-09-09T09:04:32.509724

2018-03-14T14:33:53

117,875,405

1

0

null

import time import os from urllib.request import urlopen import subprocess from uuid import getnode as get_mac ipAddress = "10.209.6.212" mac = str(hex(get_mac())) print(mac) #audio state def getVolumeStatus(): audiovalue = subprocess.Popen("ConsoleApplication1.exe", shell=False, stdout=subprocess.PIPE) val = audiovalue.communicate()[0].strip() == b'True' print(val) time.sleep(.15) audiovalue.kill() return val #Creates custom URL string def getURL(device, isPlaying): boolean = "false" if isPlaying: boolean = "true" url = "http://" + ipAddress + ":8080/redtooth/report/" + device + "/" + boolean print(url) return url #Ping database def pingDatabase(isPlaying): url = getURL(mac, isPlaying) response = urlopen(url).read() desiredMAC = response print(desiredMAC) return desiredMAC def Redtooth(): print("Running Core") while True: isPlaying = getVolumeStatus() deviceToPlay = pingDatabase(isPlaying) if (str(mac) in str(deviceToPlay)) and isPlaying: #bt on and pair print("Redtooth Activated") elif not(str(mac) in str(deviceToPlay)): #windows bt cmds off print("Redtooth De-activated") time.sleep(1) Redtooth()

UTF-8

Python

false

1,301

py

13

Windows.py

10

0.644889

0.631053

0

60

20.666667

97

opensciencegrid/osg-display-data

9,612,136,827,039

079daec333d98bf95b86a2f2a2c6ec216c1b01e5

52b5fd2bdc4906e1f944f9d03c9b98a3d1ec3fa6

/src/osg_display/transfer_datasource.py

5d3dbf6ecb4aeff7e0254bb8d25b7744ba7191dd

[]

no_license

https://github.com/opensciencegrid/osg-display-data

bba930f630d4eec8bd621e32d97129c18bd1df5d

93df8bc98f703a4c83fdd979357dd764148dc165

refs/heads/master

2021-07-18T02:10:31.200337

2021-06-28T16:55:00

55,262,958

0

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2021-06-28T16:55:01

2016-04-01T21:18:23

2020-10-27T22:02:11

2021-06-28T16:55:00

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Python

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import sys import time import pickle import datetime from .common import log, get_files, commit_files, euid import elasticsearch from elasticsearch_dsl import Search, A, Q import logging logging.basicConfig(level=logging.WARN) tracer = logging.getLogger('elasticsearch.trace') tracer.setLevel(logging.WARN) tracer.addHandler(logging.StreamHandler(sys.stderr)) transfers_raw_index = 'gracc.osg-transfer.raw-*' transfers_summary_index = 'gracc.osg-transfer.summary' def gracc_query_transfers(es, index, starttime, endtime, interval): s = Search(using=es, index=index) s = s.query('bool', filter=[ Q('range', StartTime={'gte': starttime, 'lt': endtime }) & ~Q('terms', SiteName=['NONE', 'Generic', 'Obsolete']) ] ) curBucket = s.aggs.bucket('StartTime', 'date_histogram', field='StartTime', interval=interval) curBucket = curBucket.metric('Network', 'sum', field='Network') curBucket = curBucket.metric('Records', 'sum', field='Njobs') response = s.execute() return response class TransferData(object): """ Information about a single hour's worth of tranfers from the DB. Meant to be saved in the cache, keeps track of the creationtime of the object itself so the cache knows when to expire it. """ def __init__(self): self.starttime = None self.endtime = None self.count = None self.volume_mb = None self.createtime = time.time() class DataSourceTransfers(object): """ A data source which queries (and caches!) hourly transfer information from GRACC """ def __init__(self, cp): self.cp = cp self.data = {} self.missing = set() def run(self): self.connect() self.load_cached() self.determine_missing() self.query_missing() def disconnect(self): pass def connect(self): gracc_url = self.cp.get("GRACC Transfer", "Url") #gracc_url = 'https://gracc.opensciencegrid.org/q' try: self.es = elasticsearch.Elasticsearch( [gracc_url], timeout=300, use_ssl=True, verify_certs=True) except Exception as e: log.exception(e) log.error("Unable to connect to GRACC database") raise def load_cached(self): try: data = pickle.load(open(self.cp.get("Filenames", "transfer_data") \ % {'uid': euid}, "rb")) # Verify we didn't get useless data for time, tdata in list(data.items()): assert isinstance(time, datetime.datetime) assert isinstance(tdata, TransferData) assert isinstance(tdata.starttime, datetime.datetime) assert isinstance(tdata.endtime, datetime.datetime) assert tdata.count != None assert tdata.volume_mb != None assert tdata.starttime != None self.data = data log.info("Successfully loaded transfer data from cache; %i" \ " cache entries." % len(data)) remove_data = [] now = globals()['time'].time() now_dt = datetime.datetime.now() for time, tdata in list(data.items()): if not hasattr(tdata, 'createtime') or not tdata.createtime: log.debug("Ignoring cached data from %s as it has no " \ "create time info." % time) remove_data.append(time) continue if now - tdata.createtime > 3600: log.debug("Ignoring cached data from %s as it is over " \ "an hour old." % time) remove_data.append(time) age_starttime = now_dt - tdata.starttime age_starttime = age_starttime.days*86400 + age_starttime.seconds if (now - tdata.createtime > 1800) and (age_starttime <= 12*3600): log.debug("Ignoring cached data from %s as it is over " \ "30 minutes old and is for a recent interval." % \ time) remove_data.append(time) for time in remove_data: del self.data[time] except Exception as e: log.warning("Unable to load cache; it may not exist. Error: %s" % \ str(e)) def save_cache(self): now = datetime.datetime.now() old_keys = [] for key in self.data.keys(): if (now - key).days >= 7: old_keys.append(key) for key in old_keys: del self.data[key] try: name, tmpname = get_files(self.cp, "transfer_data") fp = open(tmpname, 'wb') pickle.dump(self.data, fp) fp.close() commit_files(name, tmpname) log.debug("Saved data to cache.") except Exception as e: log.warning("Unable to write cache; message: %s" % str(e)) def _timestamp_to_datetime(self, ts): return datetime.datetime(*time.gmtime(ts)[:6]) def determine_missing(self): now = time.time() hour_now = now - (now % 3600) if (now-hour_now) < 15*60: hour_now -= 3600 self.missing.add(self._timestamp_to_datetime(hour_now)) self.missing.add(self._timestamp_to_datetime(hour_now-3600)) self.missing.add(self._timestamp_to_datetime(hour_now-2*3600)) self.missing.add(self._timestamp_to_datetime(hour_now-3*3600)) cur = hour_now hours = int(self.cp.get("GRACC Transfer", "hours")) while cur >= now - hours*3600: cur -= 3600 cur_dt = self._timestamp_to_datetime(cur) if cur_dt not in self.data: self.missing.add(cur_dt) def query_missing(self): now = time.time() log.info("Querying %i missing data entries." % len(self.missing)) for mtime in self.missing: starttime = mtime endtime = mtime + datetime.timedelta(0, 3600) results = self.query_transfers(starttime, endtime) if not results: log.warning("No transfer results found for %s." % starttime) for result in results: res_time, count, volume_mb = result res_time = float(res_time) starttime = self._timestamp_to_datetime(res_time) if now-res_time >= 3600: endtime = self._timestamp_to_datetime(res_time+3600) else: endtime = self._timestamp_to_datetime(now) if res_time > now: continue td = TransferData() td.starttime = starttime td.endtime = endtime td.count = count td.volume_mb = volume_mb self.data[starttime] = td log.debug("Successfully parsed results for %s." % starttime) self.save_cache() def query_transfers(self, starttime, endtime): log.info("Querying GRACC Transfer index for transfers from %s to %s." \ % (starttime.strftime("%Y-%m-%d %H:%M:%S"), endtime.strftime("%Y-%m-%d %H:%M:%S"))) params = {'interval': 'hour'} params['starttime'] = starttime params['endtime'] = endtime response = gracc_query_transfers(self.es, transfers_raw_index, **params) try: results = response.aggregations.StartTime.buckets except AttributeError: results = [] all_results = [ (x.key / 1000, x.Records.value, x.Network.value / 1024**2) for x in results ] return all_results def get_json(self): assert self.transfer_results != None assert self.transfer_volume_results != None total_transfers = sum(self.transfer_results) total_transfer_volume = sum(self.transfer_volume_results) return {'transfers_hourly': int(total_transfers), 'transfer_volume_mb_hourly': int(total_transfer_volume)} def get_data(self): all_times = list(self.data.keys()) all_times.sort() all_times = all_times[-26:-1] results = [] for time in all_times: results.append((int(self.data[time].count), self.data[time].volume_mb)) if results: self.transfer_results, self.transfer_volume_results = list(zip(*results)) else: self.transfer_results, self.transfer_volume_results = [[],[]] return results def get_volume_rates(self): all_times = list(self.data.keys()) all_times.sort() all_times = all_times[-26:-1] results = [] for time in all_times: td = self.data[time] interval = td.endtime - td.starttime interval_s = interval.days*86400 + interval.seconds results.append(td.volume_mb/interval_s) return results def get_rates(self): all_times = list(self.data.keys()) all_times.sort() all_times = all_times[-26:-1] results = [] for time in all_times: td = self.data[time] interval = td.endtime - td.starttime interval_s = interval.days*86400 + interval.seconds results.append(td.count/float(interval_s)) return results

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py

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transfer_datasource.py

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karthigkk/chicago_taxi_ss

15,693,810,531,077

a2fb8027ad655d8377ffb1124d8aa8915a37b1dd

c4e3edae8a27ff6f65a21fe9f41d6fb3cfd56fe3

/packages/regression_model/regression_model/pipeline.py

5998a7ecd1ed038ffdcc6f53e30b06e04763035a

[]

no_license

https://github.com/karthigkk/chicago_taxi_ss

648ef04626a10bef0380df14f9c56d1b3a3af6f7

942cd98ef2e3f381e09344713221f37f6e51cceb

refs/heads/master

2023-01-11T18:05:32.487938

2020-11-11T10:34:49

288,145,261

0

null

from regression_model.preprocessing.preprocessors import Preprocessdataframe from mmlspark.featurize import AssembleFeatures from mmlspark.lightgbm import LightGBMRegressor from mmlspark.stages import UDFTransformer, DropColumns from pyspark.sql.types import IntegerType from pyspark.sql.functions import udf # from pyspark.ml.feature import OneHotEncoderEstimator, StringIndexer, VectorAssembler # from pyspark.ml.regression import LinearRegression from regression_model.config import config class Buildpipeline: def __init__(self): pass @staticmethod def build_stages() -> list: get_week_day = udf(lambda z: z.weekday(), IntegerType()) get_year = udf(lambda z: z.year, IntegerType()) get_month = udf(lambda z: z.month, IntegerType()) get_hour = udf(lambda z: z.hour, IntegerType()) #preprocess = Preprocessdataframe() # build Pipeline # stringIndexer = StringIndexer(inputCol=config.CATEGORICAL_VAR, outputCol='Comp_Index') # encoder = OneHotEncoderEstimator(inputCols=[stringIndexer.getOutputCol()], outputCols=['Comp_classVec']) # inputfeatures = config.NUMERICAL_VARS + config.DERIVED_VARS + ['Comp_classVec'] # assembler = VectorAssembler(inputCols=inputfeatures, outputCol='features') # lr = LinearRegression(featuresCol='features', labelCol=config.TARGET, maxIter=2, regParam=0.3, elasticNetParam=0.8) # STAGES = [preprocess, stringIndexer, encoder, assembler, lr] assembler = AssembleFeatures( columnsToFeaturize=config.NUMERICAL_VARS + config.DERIVED_VARS + config.CATEGORICAL_VAR, numberOfFeatures=1) lgbm = LightGBMRegressor(learningRate=0.001, numIterations=50, featuresCol='features', labelCol=config.TARGET) STAGES = [UDFTransformer(inputCol='trip_start_timestamp', outputCol='Trip_Day_Of_Week', udf=get_week_day), UDFTransformer(inputCol='trip_start_timestamp', outputCol='Trip_Year', udf=get_year), UDFTransformer(inputCol='trip_start_timestamp', outputCol='Trip_Month', udf=get_month), UDFTransformer(inputCol='trip_start_timestamp', outputCol='Trip_Hour', udf=get_hour), DropColumns(cols=['trip_start_timestamp']), assembler, lgbm] return STAGES

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py

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pipeline.py

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0.711198

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deutranium/speed-ideating

11,424,613,033,155

c488ae41aae24984de02185ec7ba010a9c409764

c70ef424f4f15fcce67af55ed93248e21f0c2791

/bot.py

aeaab62c67272c1233e4091e7ea21a5f5721178c

[]

no_license

https://github.com/deutranium/speed-ideating

cfbb32ef8b1281ec379ed56b729dcd5115d1242c

9f955636d83ddb8a90ee7ca218c4619ba3c4297b

refs/heads/master

2023-01-05T10:06:23.802102

2020-10-27T17:28:30

305,782,759

0

null

false

2020-10-22T08:39:06

2020-10-20T17:23:04

2020-10-21T14:59:04

2020-10-22T08:39:05

16

0

Python

false

import os import sys from time import sleep import discord from tabulate import tabulate from dotenv import load_dotenv from sql import SQL load_dotenv() client = discord.Client() TOKEN = os.getenv("DISCORD_TOKEN") GUILD = os.getenv("DISCORD_GUILD") db = None history_channel = None # TODO: Add all the teams here # Make sure they are in order team_names = [ 'The Boys', 'MCDT', "Fluffy's 3 Heads", 'Mario & the other guy', 'www.', 'The Intrepids', 'Detty pigs', 'The Invincibles', 'Goal Diggers ', 'HoynaHoyna', 'El', 'Theen Bacche', 'Tesseract', 'XD', 'Ombani', 'Impostors', 'God particle', 'kryptomaniax ', 'Oreo Sheikhs', 'Sons of pitches', 'Strawberry Beans', ] # admin role ID ADMIN_ID = 767717031318782003 HISTORY_CHANNEL_ID = 768235871223676948 def help(): """ Shows help message """ help_msg = """ ``` Commands (prepend `!si` to all the commands): update <teamA> <teamB> <score>: Transfer `score` points FROM teamA TO teamB scoreboard: Display the scoreboard ``` """ return help_msg def print_scoreboard(): """ Returns the scoreboard as a string """ data = db.get_scoreboard() headers = ["Team #", "Name", "Score"] content = tabulate(data, headers) return "```\n" + content + "\n```" def update_score(from_team_id, to_team_id, score_delta): """ Updates the score If successful, returns the new scoreboard otherwise nothing """ if db.update_score(from_team_id, to_team_id, score_delta): return print_scoreboard() return None # TODO: ADD ALL THE UPDATES TO READ-ONLY HISTORY CHANNEL async def add_to_history(message): global history_channel if history_channel is None: history_channel = client.get_channel(HISTORY_CHANNEL_ID) await history_channel.send(message) @client.event async def on_ready(): print(f"{client.user} has connected to Discord!\n") guild = discord.utils.get(client.guilds, name=GUILD) print( f"{client.user} is connected to the following guild:\n" f"{guild.name}(id: {guild.id})" ) @client.event async def on_message(message): msg = "A valid command plox" cntnt = message.content.lower() # Check bot prefix if (cntnt.split()[0] != "!si") or message.author.bot: return # Check if the author is an admin if ADMIN_ID not in [i.id for i in message.author.roles]: await message.channel.send("Only admins allowed") return # remove the prefix cntnt = " ".join(cntnt.split()[1:]) # help if cntnt == "help": msg = help() # display scoreboard elif cntnt == "scoreboard": msg = print_scoreboard() # update team score elif cntnt.split()[0] == "update": _, from_team_id, to_team_id, delta = cntnt.split() if int(delta) < 0: msg = "Only positive score can be transferred.\nCheck !si.help" else: logs = f"{message.author} requested for transferring {delta} points from {from_team_id} to {to_team_id}" msg = update_score(int(from_team_id), int(to_team_id), int(delta)) if msg is None: msg = "Failed to update score" logs += "\n\nStatus: FAILED" else: logs += "\n\nStatus: Successful" await add_to_history(logs) await message.channel.send(msg) def main(): global db # setup database and tables db = SQL() db.setup_table() if db.count_rows() == 0: db.populate_table(team_names) client.run(TOKEN) if __name__ == "__main__": while True: try: main() except Exception as e: print(e) sleep(10)

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py

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0.596689

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zaswedyg/Algorithms

5,214,090,335,203

2eca1c78e7c0a5f5c3d5011fcc9aa7b100e9c3ee

96ca5294a67294885a7519c558e4036801815211

/HW2.py

0d62e3ac4b9902a685257c109d132f18cd8116b1

[]

no_license

https://github.com/zaswedyg/Algorithms

be8cf3d19b3a9b2c5c4e30a52a43ba3b980b716c

2954e26cececebcd5d74bcc4121b337ac441ea7b

refs/heads/main

2023-06-26T06:18:58.490317

2021-07-28T03:08:19

383,977,546

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# 1. Split in Half #Given a string. Split it into two equal parts. Swap these parts and return the result. #If the string has odd characters, the first part should be one character greater than the second part. #Example: string = 'bbbbbcaaaaa'. Result = ‘aaaaabbbbbc’. """ def split_in_half(s): first_half = "" second_half = "" string_length = len(s) if string_length % 2 == 0: first_half = s[0:(string_length/2-1)] second_half = s[string_length/2:] return (second_half + first_half) else: first_half = s[0:(string_length // 2 + 1)] second_half = s[string_length // 2 + 1:] return (second_half + first_half) print(split_in_half("bbbbbcaaaaa")) """ # 2. Unique Characters in String # Given a string, determine if it consists of all unique characters. # For example, the string 'abcde' has all unique characters and should return True. # The string 'aabcde' contains duplicate characters and should return False. """ def unique_char(s): chars = set() for char in s: if char in chars: return False else: chars.add(char) return True print(unique_char('abcde')) print(unique_char('aabcde')) """

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# coding=utf-8 # Some of structures or codes in this script are referenced from HuggingFace Inc. team. # Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team. # Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. # # 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. '''放置句子情感分類、屬性情感分析模型架構''' import torch import torch.nn as nn from torch.nn import BCEWithLogitsLoss from torch.nn import CrossEntropyLoss from torch.nn import NLLLoss from transformers import ( BertModel, BertPreTrainedModel, ) import numpy as np import os import torch.nn.functional as F from .utils import chg_labels_to_aspect_and_sentiment,get_domain_embedding class MyNewBertForSequenceClassification(BertPreTrainedModel): '''BERT輸出接上一層線性層；此外額外加入domain embedding layer，等於最後BERT輸出和domain embedding連接、饋入分類層，是句子情感分類的模型''' def __init__(self, config): super().__init__(config) self.num_labels = config.num_labels self.bert = BertModel(config) self.dropout = nn.Dropout(config.hidden_dropout_prob) ### 加入 domain embedding layer file_path = os.path.split(os.path.realpath(__file__))[0] + "/utils/new_restaurant_emb.vec.npy" get_domain_embedding(file_path) domain_emb = np.load(file_path) self.domain_embedding = nn.Embedding(domain_emb.shape[0], domain_emb.shape[1]) self.domain_embedding.weight = nn.Parameter(torch.from_numpy(domain_emb), requires_grad=True) self.first_classifier = nn.Linear(config.hidden_size+domain_emb.shape[1],config.hidden_size) self.classifier = nn.Linear(config.hidden_size, self.config.num_labels) self.init_weights() def forward( self, input_ids=None, attention_mask=None, token_type_ids=None, position_ids=None, head_mask=None, inputs_embeds=None, labels=None, ): outputs = self.bert( input_ids, attention_mask=attention_mask, token_type_ids=token_type_ids, position_ids=position_ids, head_mask=head_mask, inputs_embeds=inputs_embeds, ) pooled_output = outputs[1] pooled_output = self.dropout(pooled_output) ### 加入 domain embedding ### input_embedding = self.domain_embedding(input_ids) ### 將每筆資料中每個字的embedding拼起來平均 ### sent_embedding = torch.mean(input_embedding,dim=1) #針對seq部分做平均 ### 將平均後的embedding和bert的CLS位置輸出連接 ### combine_emb = torch.cat((sent_embedding,pooled_output),dim=1) ### 經過兩層線性層、中間添加tanh活化函數 ### firsts = self.first_classifier(combine_emb) firsts = torch.tanh(firsts) logits = self.classifier(firsts) outputs = (logits,) + outputs[2:] if labels is not None: loss_fct = BCEWithLogitsLoss() #改成多標籤分類(每個標籤做二元分類的感覺) labels = labels.float() loss = loss_fct(logits.view(-1, self.num_labels), labels.view(-1, self.num_labels)) outputs = (loss,) + outputs return outputs # class MyNewBertForSequenceClassification(BertPreTrainedModel): # '''BERT輸出接上一層線性層，是句子情感分類的模型''' # def __init__(self, config): # super().__init__(config) # self.num_labels = config.num_labels # self.bert = BertModel(config) # self.dropout = nn.Dropout(config.hidden_dropout_prob) # self.classifier = nn.Linear(config.hidden_size, self.config.num_labels) # self.init_weights() # def forward( # self, # input_ids=None, # attention_mask=None, # token_type_ids=None, # position_ids=None, # head_mask=None, # inputs_embeds=None, # labels=None, # ): # outputs = self.bert( # input_ids, # attention_mask=attention_mask, # token_type_ids=token_type_ids, # position_ids=position_ids, # head_mask=head_mask, # inputs_embeds=inputs_embeds, # ) # pooled_output = outputs[1] # pooled_output = self.dropout(pooled_output) # logits = self.classifier(pooled_output) # outputs = (logits,) + outputs[2:] # add hidden states and attention if they are here # if labels is not None: # loss_fct = BCEWithLogitsLoss() #改成多標籤分類(每個標籤做二元分類的感覺) # labels = labels.float() # loss = loss_fct(logits.view(-1, self.num_labels), labels.view(-1, self.num_labels)) # outputs = (loss,) + outputs # return outputs class MyNewBertForTokenClassification(BertPreTrainedModel): '''將BERT每個位置輸出接上線性層預測屬性，並輔以屬性轉移矩陣設置；另外將BERT輸出額外接上另一線性層預測情感，之後用情感轉移矩陣獲得最終情感預測結果，是屬性情感分析的模型''' def __init__(self, config): super().__init__(config) self.bert = BertModel(config) self.dropout = nn.Dropout(config.hidden_dropout_prob) ### 將BERT輸出傳到這層來做屬性標記預測 ### self.aspect_classfier = nn.Linear(config.hidden_size,3) #768 -> 3 (BIO) ### 增加屬性轉移矩陣 ### # transition_path = {'B': ['B','I', 'O'], # 'I': ['B', 'I', 'O'], # 'O': ['B','O']} self.transition_scores_aspect = [[1/3,1/3,1/3],[1/3,1/3,1/3],[1/2,0,1/2]] #3*3矩陣，為B/I/O到B/I/O的機率 self.transition_scores_aspect = np.array(self.transition_scores_aspect, dtype='float32').transpose() ### 增加情感轉移矩陣 (FOR 屬性標籤預測情感標籤) ### # transition_path = {'B': ['NEG','NEU','POS'], # 'I': ['NEG','NEU','POS'], # 'O': ['O']} self.transition_scores_sentiment = [[1/3,1/3,1/3,0],[1/3,1/3,1/3,0],[0,0,0,1]] #3*4矩陣，為B/I/O到NEG/NEU/POS/O的機率 self.transition_scores_sentiment = np.array(self.transition_scores_sentiment, dtype='float32').transpose() ### 將BERT輸出傳到這層來預測情感標記 ### self.sentiment_classifier = nn.Linear(config.hidden_size, 4) #768 -> 4 (POS/NEU/NEG/O) self.init_weights() def forward( self, input_ids=None, attention_mask=None, token_type_ids=None, position_ids=None, head_mask=None, inputs_embeds=None, labels=None, ): outputs = self.bert( input_ids, attention_mask=attention_mask, token_type_ids=token_type_ids, position_ids=position_ids, head_mask=head_mask, inputs_embeds=inputs_embeds, ) tagger_input = outputs[0] tagger_input = self.dropout(tagger_input) #### 以下開始對屬性部分做處理 #### aspect_tagger_pred = self.aspect_classfier(tagger_input) pred_aspect = F.softmax(aspect_tagger_pred,dim=2) if torch.cuda.is_available(): self.transitions_aspect = torch.tensor(self.transition_scores_aspect).cuda() else: self.transitions_aspect = torch.tensor(self.transition_scores_aspect) combined_aspect_pred = [] for bsz in range(pred_aspect.size(0)) : current_sample = pred_aspect[bsz] current_sample_transition = [] for t in range(current_sample.size(0)): if t == 0 or t == 1: #對 cls & 對 cls後的第一個字 => 兩者都不用做轉移矩陣運算 current_sample_transition.append(current_sample[t]) else: transition_pred = torch.mm(self.transitions_aspect,current_sample_transition[t-1].view(3,-1)) #轉移矩陣乘上前一個token已經權衡相加後的值 ### 計算 confidence value (用轉移矩陣算出的值的重要程度) ### val = torch.sum(current_sample_transition[t-1].view(3,-1) * current_sample_transition[t-1].view(3,-1)) alpha = val * 0.6 new_aspect_pred = alpha * transition_pred + (1-alpha) * current_sample[t].view(3,-1) current_sample_transition.append(new_aspect_pred.view(-1)) combined_aspect_pred.append(torch.stack(current_sample_transition, 0)) aspect_tagger = torch.stack(combined_aspect_pred, 0) ### 以下開始對情感部分做處理 ### sentiment_pred = self.sentiment_classifier(tagger_input) if torch.cuda.is_available(): self.transitions_sentiment = torch.tensor(self.transition_scores_sentiment).cuda() else: self.transitions_sentiment = torch.tensor(self.transition_scores_sentiment) sentiment_pred = F.softmax(sentiment_pred,dim=2) combined_sentiment_pred = [] for bsz in range(sentiment_pred.size(0)) : current_sample_aspect = aspect_tagger[bsz] current_sample_sentiment = sentiment_pred[bsz] current_sample_transition = [] for t in range(current_sample_sentiment.size(0)): if t == 0: #對cls不用做轉移矩陣運算 current_sample_transition.append(current_sample_sentiment[t]) else: transition_pred = torch.mm(self.transitions_sentiment,current_sample_aspect[t].view(3,-1)) #轉移矩陣乘上屬性預測標籤 ### 計算 confidence value (這個用轉移矩陣算出的值的重要程度) ### val = torch.sum(current_sample_aspect[t].view(3,-1) * current_sample_aspect[t].view(3,-1)) alpha = val * 0.6 new_sentiment_pred = alpha * transition_pred + (1-alpha) * current_sample_sentiment[t].view(4,-1) current_sample_transition.append(new_sentiment_pred.view(-1)) combined_sentiment_pred.append(torch.stack(current_sample_transition, 0)) logits = torch.stack(combined_sentiment_pred, 0) outputs = (aspect_tagger,) + (logits,) + outputs[2:] ### 輸入的label map: {'B-NEG': 0, 'B-NEU': 1, 'B-POS': 2, 'I-NEG': 3, 'I-NEU': 4, 'I-POS': 5, 'O': 6} ## 自定義的新label map : # aspect_labels : {"B" : 0, "I":1, "O": 2} # sentiment_labels {"NEG": 0 ,"NEU":1, "POS":2, "O":3} if labels is not None: #處理 labels、讓它符合joint屬性模型格式 aspect_labels, sentiment_labels = chg_labels_to_aspect_and_sentiment(labels) aspect_tagger = torch.log(aspect_tagger + 1e-20) #將屬性預測部分經過log logits = torch.log(logits + 1e-20) #將情感預測部分經過log loss_fct = NLLLoss() #因為已經過softmax和log，不能使用CrossEntropyLoss if attention_mask is not None: active_loss = attention_mask.view(-1) == 1 active_logits = aspect_tagger.view(-1, 3) active_labels = torch.where( active_loss, aspect_labels.view(-1), torch.tensor(loss_fct.ignore_index).type_as(labels) ) aspect_loss = loss_fct(active_logits, active_labels) active_loss = attention_mask.view(-1) == 1 active_logits = logits.view(-1, 4) active_labels = torch.where( active_loss, sentiment_labels.view(-1), torch.tensor(loss_fct.ignore_index).type_as(labels) ) sentiment_loss = loss_fct(active_logits, active_labels) loss = aspect_loss + sentiment_loss else: aspect_loss = loss_fct(aspect_tagger.view(-1, 3), aspect_labels.view(-1)) sentiment_loss = loss_fct(logits.view(-1, 4), sentiment_labels.view(-1)) loss = aspect_loss + sentiment_loss outputs = (loss,) + (aspect_loss,) + (sentiment_loss,) + outputs return outputs # class MyNewBertForTokenClassification(BertPreTrainedModel): # '''把bert輸出分別接上一層線性分類層，是屬性情感分析的模型''' # def __init__(self, config): # super().__init__(config) # self.bert = BertModel(config) # self.dropout = nn.Dropout(config.hidden_dropout_prob) # # 將bert輸出傳到這層來預測屬性標記 # self.aspect_classfier = nn.Linear(config.hidden_size,3) #768 -> 3 (BIO) # # 將bert輸出傳到這層來預測情感標記 # self.sentiment_classifier = nn.Linear(config.hidden_size, 4) #768 -> 4 (POS/NEU/NEG/O) # self.init_weights() # def forward( # self, # input_ids=None, # attention_mask=None, # token_type_ids=None, # position_ids=None, # head_mask=None, # inputs_embeds=None, # labels=None, # ): # outputs = self.bert( # input_ids, # attention_mask=attention_mask, # token_type_ids=token_type_ids, # position_ids=position_ids, # head_mask=head_mask, # inputs_embeds=inputs_embeds, # ) # tagger_input = outputs[0] # tagger_input = self.dropout(tagger_input) # aspect_tagger = self.aspect_classfier(tagger_input) #輸出預測的屬性標註, 維度是bsz,seq,num_labels (3,因為標BIO) # logits = self.sentiment_classifier(tagger_input) #得到最後經過情感標註後的結果 # outputs = (aspect_tagger,) + (logits,) + outputs[2:] # ### 輸入的label map: {'B-NEG': 0, 'B-NEU': 1, 'B-POS': 2, 'I-NEG': 3, 'I-NEU': 4, 'I-POS': 5, 'O': 6} # ## 需轉成自定義的新label map : # # aspect_labels : {"B" : 0, "I":1, "O": 2} # # sentiment_labels {"NEG": 0 ,"NEU":1, "POS":2, "O":3} # if labels is not None: # #處理 labels、讓它符合joint屬性模型格式 # aspect_labels, sentiment_labels = chg_labels_to_aspect_and_sentiment(labels) # loss_fct = CrossEntropyLoss() # if attention_mask is not None: # # 先算屬性標記的loss: # active_loss = attention_mask.view(-1) == 1 # active_logits = aspect_tagger.view(-1, 3) # active_labels = torch.where( # active_loss, aspect_labels.view(-1), torch.tensor(loss_fct.ignore_index).type_as(labels) # ) # aspect_loss = loss_fct(active_logits, active_labels) # active_loss = attention_mask.view(-1) == 1 # active_logits = logits.view(-1, 4) # active_labels = torch.where( # active_loss, sentiment_labels.view(-1), torch.tensor(loss_fct.ignore_index).type_as(labels) # ) # sentiment_loss = loss_fct(active_logits, active_labels) # loss = aspect_loss + sentiment_loss #兩個loss會一起訓練 # else: # aspect_loss = loss_fct(aspect_tagger.view(-1, 3), aspect_labels.view(-1)) # sentiment_loss = loss_fct(logits.view(-1, 4), sentiment_labels.view(-1)) # loss = aspect_loss + sentiment_loss #兩個loss會一起訓練 # outputs = (loss,) + (aspect_loss,) + (sentiment_loss,) + outputs # return outputs

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# -*- coding: utf-8 -*- """ Created on Wed May 6 21:30:25 2020 @author: DELL.E5430.SSD """ m = int(input('Digite la cantidad de filas: ')) n = int(input('Digite la cantidad de columnas: ')) matriz_a = [] matriz_b = [] matriz_suma = [] for i in range(m): matriz_a.append([0]*n) for i in range(m): matriz_b.append([0]*n) print('Matriz A:') for i in range(m): for j in range(n): matriz_a[i][j] = int(input(f'Matriz A --> Fila {i+1}, columna {j+1}: ')) print() print('Matriz B:') for i in range(m): for j in range(n): matriz_b[i][j] = int(input(f'Matriz B --> Fila {i+1}, columna {j+1}: ')) print() print('Matriz A') for i in matriz_a: print(i) print() print('Matriz B') for i in matriz_b: print(i) print() #sumamos for i in range(m): matriz_suma.append([0]*n) for i in range(m): for j in range(n): matriz_suma[i][j] = matriz_a[i][j] + matriz_b[i][j] print('La matriz suma es: ') for i in matriz_suma: print(i)

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#!/usr/local/bin/python3 from colored import stylize, fg from PIL import Image from PIL.ExifTags import TAGS # EXTRACT METADATA FROM IMG class Metadata: def __init__(self, file): self.file = file def __repr__(self): metadata = self.extract_metadata(self.file) if len(metadata) == 0: return stylize(f"\n{self.file} No metadata.\n", fg("red")) else: print(stylize(f"\nMetadata of {self.file}:\n", fg("red"))) for data in metadata: print(data) return "" def extract_metadata(self, file): image = Image.open(file) exifdata = image.getexif() metadata = [] for tag_id in exifdata: tag = TAGS.get(tag_id, tag_id) data = exifdata.get(tag_id) if isinstance(data, bytes): data = data.decode() metadata.append(f"{tag:25}: {data}") return metadata if __name__ == "__main__": filename = input("Filename: ") print(Metadata(filename))

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#calss header class _DOG(): def __init__(self,): self.name = "DOG" self.definitions = [u'a common animal with four legs, especially kept by people as a pet or to hunt or guard things: ', u'a man who is unpleasant or not to be trusted: ', u'a woman who is not attractive'] self.parents = [] self.childen = [] self.properties = [] self.jsondata = {} self.specie = 'nouns' def run(self, obj1 = [], obj2 = []): return self.jsondata

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# This script computes the halo bispectrum in real- and redshift-space. It takes as input # the first and last number of the wanted realizations, the cosmology and the snapnum # In redshift-space it computes the bispectrum along the 3 different axes. import argparse from mpi4py import MPI import numpy as np import sys,os import readgadget,readfof import redshift_space_library as RSL from pyspectrum import pyspectrum as pySpec ###### MPI DEFINITIONS ###### comm = MPI.COMM_WORLD nprocs = comm.Get_size() myrank = comm.Get_rank() # read the first and last realization to identify voids parser = argparse.ArgumentParser(description="This script computes the bispectrum") parser.add_argument("first", help="first realization number", type=int) parser.add_argument("last", help="last realization number", type=int) parser.add_argument("cosmo", help="folder with the realizations") parser.add_argument("snapnum", help="snapshot number", type=int) args = parser.parse_args() first, last, cosmo, snapnum = args.first, args.last, args.cosmo, args.snapnum # This routine computes and saves the bispectrum def find_Bk(folder, snapdir, snapnum, axis, Ngrid, step, Ncut, Nmax, do_RSD, fixed_Mmin, Mmin, Nhalos): # read header head = readgadget.header(snapdir) BoxSize = head.boxsize/1e3 #Mpc/h Omega_m = head.omega_m Omega_l = head.omega_l redshift = head.redshift Hubble = 100.0*np.sqrt(Omega_m*(1.0+redshift)**3+Omega_l)#km/s/(Mpc/h) h = head.hubble # read halo catalogue FoF = readfof.FoF_catalog(folder, snapnum, long_ids=False, swap=False, SFR=False, read_IDs=False) pos_h = FoF.GroupPos/1e3 #Mpc/h mass = FoF.GroupMass*1e10 #Msun/h vel_h = FoF.GroupVel*(1.0+redshift) #km/s if fixed_Mmin: indexes = np.where(mass>Mmin)[0] pos_h = pos_h[indexes]; vel_h = vel_h[indexes]; del indexes else: indexes = np.argsort(mass)[-Nhalos:] #take the Nhalos most massive halos pos_h = pos_h[indexes]; vel_h = vel_h[indexes]; del indexes # move halos to redshift-space if do_RSD: RSL.pos_redshift_space(pos_h, vel_h, BoxSize, Hubble, redshift, axis) # calculate bispectrum b123out = pySpec.Bk_periodic(pos_h.T, Lbox=BoxSize, Ngrid=Ngrid, step=step, Ncut=Ncut, Nmax=Nmax, fft='pyfftw', nthreads=1, silent=False) i_k = b123out['i_k1'] j_k = b123out['i_k2'] l_k = b123out['i_k3'] p0k1 = b123out['p0k1'] p0k2 = b123out['p0k2'] p0k3 = b123out['p0k3'] b123 = b123out['b123'] b_sn = b123out['b123_sn'] q123 = b123out['q123'] cnts = b123out['counts'] hdr = ('halo bispectrum; k_f = 2pi/%.1f, Nhalo=%i'%(BoxSize, pos_h.shape[0])) np.savetxt(fbk, np.array([i_k, j_k, l_k, p0k1, p0k2, p0k3, b123, q123, b_sn, cnts]).T, fmt='%i %i %i %.5e %.5e %.5e %.5e %.5e %.5e %.5e', delimiter='\t', header=hdr) root = '/simons/scratch/fvillaescusa/pdf_information' ##################################### INPUT ######################################### # Bk parameters Ngrid = 360 Nmax = 40 Ncut = 3 step = 3 # halo parameters fixed_Mmin = True #whether fix Mmin or nbar Mmin = 3.2e13 #Msun/h; fixed Mmin Nhalos = 150000 #also consider the Nhalos more massive of the sim (nbar fixed) # output folder name root_out = '/simons/scratch/fvillaescusa/pdf_information/Bk/Mmin_3.2e13/' ##################################################################################### # find the redshift z = {4:0, 3:0.5, 2:1, 1:2, 0:3}[snapnum] # create output folder if it does not exist if myrank==0: if not(os.path.exists(root_out+cosmo)): os.system('mkdir %s/%s/'%(root_out,cosmo)) # get the realizations each cpu works on numbers = np.where(np.arange(args.first, args.last)%nprocs==myrank)[0] numbers = np.arange(args.first, args.last)[numbers] ######## standard simulations ######### for i in numbers: folder = '%s/Halos/%s/%d'%(root,cosmo,i) #folder with the halo catalogue if not(os.path.exists(folder)): continue snapdir = '%s/%s/%d/snapdir_%03d/snap_%03d'%(root,cosmo,i,snapnum,snapnum) # real-space fbk = '%s/%s/Bk_%d_z=%s.txt'%(root_out,cosmo,i,z) if not(os.path.exists(fbk)): do_RSD, axis = False, 0 find_Bk(folder, snapdir, snapnum, axis, Ngrid, step, Ncut, Nmax, do_RSD, fixed_Mmin, Mmin, Nhalos) # redshift-space for axis in [0,1,2]: fbk = '%s/%s/Bk_RS%d_%d_z=%s.txt'%(root_out,cosmo,axis,i,z) if not(os.path.exists(fbk)): do_RSD = True find_Bk(folder, snapdir, snapnum, axis, Ngrid, step, Ncut, Nmax, do_RSD, fixed_Mmin, Mmin, Nhalos) ###### paired fixed realizations ###### for i in numbers: for pair in [0,1]: folder = '%s/Halos/%s/NCV_%d_%d'%(root,cosmo,pair,i) #halo catalogue folder if not(os.path.exists(folder)): continue snapdir = '%s/%s/NCV_%d_%d/snapdir_%03d/snap_%03d'\ %(root,cosmo,pair,i,snapnum,snapnum) # real-space fbk = '%s/%s/Bk_NCV_%d_%d_z=%s.txt'%(root_out,cosmo,pair,i,z) if not(os.path.exists(fbk)): do_RSD, axis = False, 0 find_Bk(folder, snapdir, snapnum, axis, Ngrid, step, Ncut, Nmax, do_RSD, fixed_Mmin, Mmin, Nhalos) # redshift-space for axis in [0,1,2]: fbk = '%s/%s/Bk_RS%d_NCV_%d_%d_z=%s.txt'%(root_out,cosmo,axis,pair,i,z) if not(os.path.exists(fbk)): do_RSD = True find_Bk(folder, snapdir, snapnum, axis, Ngrid, step, Ncut, Nmax, do_RSD, fixed_Mmin, Mmin, Nhalos)

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#!/usr/bin/env python from distutils.core import setup, Extension setup (name = "nkf", version="1.0", description="Python Interface to NKF", author="Matsumoto Tadashi", author_email="ma2@city.plala.jp", ext_modules = [ Extension("nkf", ["NKF_python.c"], extra_link_args = ['-s'])])

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Ebuyuktas/11-HAFTA-OOP

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/odev2.py

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#hafta 11 odev 2# #muzik listesi# import random class walkman(): liste=[] def cal(self,sarki): if sarki in self.liste: print(sarki,"yurutuluyor..") else: print("Malesef repertuvarimizda mevcut degil") def temizle(self): self.liste.clear() print("yurutme listesi bos") def goruntule(self): print("Sarkilar:\n") for i in self.liste: print(i) def ekle(self,sarki): self.liste.append(sarki) print(sarki,"eklendi iyi dinlemeler..\n\n") def sil(self,sarki): self.liste.pop(self.liste.index(sarki)) print(sarki,"listeden kaldirildi\n") def sonraki(self,sarki): x=self.liste.index(sarki) print("Bir sonraki parcamiz: ") print(self.liste[x+1],"caliniyor...") def onceki(self,sarki): x=self.liste.index(sarki) print("onceki sarkimiz: \n") print(self.liste[x-1], "caliniyor...") def karisik(self): karisik=random.randint(0,len(self.liste)) print(self.liste[karisik], "Caliniyor..") repertuvar= walkman() repertuvar.ekle("Sagopa-366. gun") repertuvar.ekle("Hayko Cepkin-Gelin olmus") repertuvar.ekle("Duman-Eski koprunun altinda") repertuvar.ekle("Cem karaca-kara sevda") repertuvar.ekle("Tarkan-Yolla") repertuvar.goruntule() repertuvar.sil("Hayko Cepkin-Gelin olmus") repertuvar.sonraki("Duman-Eski koprunun altinda") repertuvar.onceki("Sagopa-366. gun") repertuvar.karisik() repertuvar.temizle()

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jiamo/concurrent_server

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/epoll_server.py

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#!/usr/bin/env python """Simple server using epoll. running in linux""" from __future__ import print_function from contextlib import contextmanager import socket import select from enum import Enum class ProcessingState(Enum): INITIAL_ACK = 0 WAIT_FOR_MSG = 1 IN_MSG = 2 class PeerState: def __init__(self, process_state=None, sendbuf=None, sendbuf_end=None, sendptr=None): self.process_state = process_state self.sendbuf = sendbuf or [] self.sendbuf_end = sendbuf_end self.sendptr = sendptr SENDBUF_SIZE = 1024 MAX_SOCKS = 1000 global_states = [PeerState() for i in range(MAX_SOCKS)] class SockStatus: def __init__(self, want_read, want_write): self.want_read = want_read self.want_write = want_write sock_status_R = SockStatus(True, False) sock_status_W = SockStatus(False, True) sock_status_RW = SockStatus(True, True) sock_status_NORW = SockStatus(False, False) @contextmanager def socketcontext(*args, **kwargs): """Context manager for a socket.""" s = socket.socket(*args, **kwargs) try: yield s finally: print("Close socket") s.close() @contextmanager def epollcontext(*args, **kwargs): """Context manager for an epoll loop.""" e = select.epoll() e.register(*args, **kwargs) try: yield e finally: print("\nClose epoll loop") e.unregister(args[0]) e.close() def init_connection(server, connections, requests, responses, epoll): """Initialize a connection.""" connection, address = server.accept() connection.setblocking(0) fd = connection.fileno() epoll.register(fd, select.EPOLLIN) connections[fd] = connection requests[fd] = '' responses[fd] = '' def on_peer_connected(conn, address): print(f"on accept {address}") fd = conn.fileno() assert fd < MAX_SOCKS peer_state = global_states[fd] peer_state.process_state = ProcessingState.INITIAL_ACK peer_state.sendbuf.insert(0, "*") peer_state.sendptr = 0 peer_state.sendbuf_end = 1 return sock_status_W def on_peer_ready_recv(fd, connections): sock = connections[fd] peer_state = global_states[fd] print(f"on_peer_ready_recv {peer_state.process_state} {fd}") print(f"on_peer_ready_recv f{fd} {id(peer_state)}") if peer_state.process_state == ProcessingState.INITIAL_ACK or \ peer_state.sendptr < peer_state.sendbuf_end: return sock_status_W buffer_len = 1024 data = sock.recv(buffer_len) print(f"on_peer_ready_recv {data} {peer_state.process_state}") if not data: return sock_status_NORW # failed has except for simple reason don't handle it ready_to_send = False for i, ch in enumerate(data): if peer_state.process_state == ProcessingState.INITIAL_ACK: assert "can't reach here" elif peer_state.process_state == ProcessingState.WAIT_FOR_MSG: if data[i] == ord(b'^'): print("recv ^") peer_state.process_state = ProcessingState.IN_MSG elif peer_state.process_state == ProcessingState.IN_MSG: if data[i] == ord(b'$'): peer_state.process_state = ProcessingState.WAIT_FOR_MSG else: assert peer_state.sendbuf_end < 1024 peer_state.sendbuf.insert(peer_state.sendbuf_end, chr(data[i] + 1)) peer_state.sendbuf_end += 1 ready_to_send = True # change a little # return SockStatus( # want_read=(not ready_to_send), # want_write=ready_to_send, # ) if ready_to_send: return sock_status_W else: return sock_status_R def on_peer_ready_send(fd, connections): # print("on_peer_ready_send") sock = connections[fd] peer_state = global_states[fd] if peer_state.sendptr >= peer_state.sendbuf_end: return sock_status_RW send_len = peer_state.sendbuf_end - peer_state.sendptr send_data = peer_state.sendbuf[ peer_state.sendptr: peer_state.sendptr + send_len ] nsent = sock.send(''.join(send_data).encode()) if nsent < send_len: print("nsent < send_len") return sock_status_RW else: print(f"send {nsent} : {send_data}") peer_state.sendptr = 0 peer_state.sendbuf_end = 0 if peer_state.process_state == ProcessingState.INITIAL_ACK: peer_state.process_state = ProcessingState.WAIT_FOR_MSG return sock_status_R def do_register(peer_status, fd, epoll): if peer_status == sock_status_RW: try: epoll.register(fd, select.EPOLLIN | select.EPOLLOUT) except FileExistsError: epoll.modify(fd, select.EPOLLIN | select.EPOLLOUT) if peer_status == sock_status_R: try: epoll.register(fd, select.EPOLLIN) except FileExistsError: epoll.modify(fd, select.EPOLLIN) if peer_status == sock_status_W: try: epoll.register(fd, select.EPOLLOUT) except FileExistsError: epoll.modify(fd, select.EPOLLOUT) if peer_status == sock_status_NORW: try: epoll.unregister(fd) except FileNotFoundError: pass def run_server(socket_options, address): """Run a simple TCP server using epoll.""" with socketcontext(*socket_options) as server, \ epollcontext(server.fileno(), select.EPOLLIN) as epoll: server.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) server.bind(address) server.listen(5) server.setblocking(0) server.setsockopt(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1) print("Listening") connections = {} server_fd = server.fileno() while True: events = epoll.poll(1) for fileno, event in events: if fileno == server_fd: connection, client_address = server.accept() connection.setblocking(0) peer_status = on_peer_connected(connection, client_address) fd = connection.fileno() connections[fd] = connection # save fd sock relate do_register(peer_status, fd, epoll) elif event & select.EPOLLIN: peer_status = on_peer_ready_recv(fileno, connections) do_register(peer_status, fileno, epoll) elif event & select.EPOLLOUT: peer_status = on_peer_ready_send(fileno, connections) do_register(peer_status, fileno, epoll) else: print("event ", event) if __name__ == '__main__': try: run_server([socket.AF_INET, socket.SOCK_STREAM], ("0.0.0.0", 9090)) except KeyboardInterrupt as e: print("Shutdown")

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mark-barrett/Ticketr-2

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/account/views.py

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from django.contrib.auth import authenticate, login, logout from django.contrib.auth.models import User from django.shortcuts import render, redirect from django.contrib import messages # Create your views here. from django.views import View class SignIn(View): def get(self, request): if not request.user.is_authenticated: return render(request, 'sign-in.html') else: return redirect('/') def post(self, request): # Get the post information email = request.POST['email'] password = request.POST['password'] # Authenticate the user with their email as the username user = authenticate(username=email, password=password) # Check if the user logged in okay if user is not None: login(request, user) return redirect('/') else: messages.error(request, 'The email or password is invalid.') return redirect('/account/sign-in') class SignUp(View): def get(self, request): if not request.user.is_authenticated(): return render(request, 'sign-up.html') else: return redirect('/') def post(self, request): first_name = request.POST['first_name'] last_name = request.POST['last_name'] email = request.POST['email'] password = request.POST['password'] # Try find the user to see if they exist try: db_user = User.objects.get(username=email) messages.error(request, 'A user with that email already exists.') return redirect('/account/sign-up') except: user, created = User.objects.get_or_create(username=email, email=email) if created: user.set_password(password) # This line will hash the password user.first_name = first_name user.last_name = last_name user.save() # DO NOT FORGET THIS LINE # Check if the user logged in okay if user is not None: login(request, user) messages.success(request, 'Your account has been setup.') return redirect('/') else: messages.error(request, 'There was an error signing up') return redirect('/account/sign-up') class SignOut(View): def get(self, request): if request.user.is_authenticated: logout(request) messages.success(request, "Logged out. Thanks for stopping by!") return redirect('/') class ForgotPassword(View): def get(self, request): pass def post(self, request): pass

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from tqdm.auto import tqdm, trange import pickle import random import time import os.path as p from itertools import chain import torch import numpy as np import torch.nn.functional as F from datasets import load_from_disk, load_dataset from transformers import TrainingArguments from transformers import AdamW, get_linear_schedule_with_warmup from torch.utils.data import TensorDataset, DataLoader, RandomSampler from retrieval.dense import DenseRetrieval def get_retriever_dataset(args): if args.retriever.dense_train_dataset not in [ "train_dataset", "squad_kor_v1", "bm25_document_questions", "bm25_question_documents", ]: raise FileNotFoundError(f"{args.retriever.dense_train_dataset}은 DenseRetrieval 데이터셋이 아닙니다.") if args.retriever.dense_train_dataset == "squad_kor_v1": train_dataset = load_dataset(args.retriever.dense_train_dataset) else: dataset_path = p.join(args.path.train_data_dir, args.retriever.dense_train_dataset) assert p.exists(dataset_path), f"{args.retriever.dense_train_dataset}이 경로에 존재하지 않습니다." train_dataset = load_from_disk(dataset_path) return train_dataset def epoch_time(start_time, end_time): elapsed_time = end_time - start_time elapsed_mins = int(elapsed_time / 60) elapsed_secs = int(elapsed_time - (elapsed_mins * 60)) return elapsed_mins, elapsed_secs class DpRetrieval(DenseRetrieval): def __init__(self, args): super().__init__(args) # wiki context load self.mappings = [] self.window_size = 20 self.sample_per_phrase = 4 save_dir = p.join(args.path.embed, self.name) self.mappings_path = p.join(save_dir, "mappings.bin") def get_embedding(self): if p.isfile(self.embed_path) and p.isfile(self.encoder_path) and not self.args.retriever.retrain: with open(self.embed_path, "rb") as f: self.p_embedding = pickle.load(f) with open(self.mappings_path, "rb") as f: self.mappings = pickle.load(f) self.encoder = self._get_encoder() self.encoder.load_state_dict(torch.load(self.encoder_path)) else: self.p_embedding, self.encoder, self.mappings = self._exec_embedding() with open(self.embed_path, "wb") as f: pickle.dump(self.p_embedding, f) with open(self.mappings_path, "wb") as f: pickle.dump(self.mappings, f) torch.save(self.encoder.state_dict(), self.encoder_path) def get_relevant_doc_bulk(self, queries, topk=1): self.encoder.eval() # question encoder self.encoder.cuda() with torch.no_grad(): q_seqs_val = self.tokenizer( queries, padding="longest", truncation=True, max_length=512, return_tensors="pt" ).to("cuda") q_embedding = self.encoder(**q_seqs_val) q_embedding.squeeze_() # in-place q_embedding = q_embedding.cpu().detach().numpy() # p_embedding: numpy, q_embedding: numpy result = np.matmul(q_embedding, self.p_embedding.T) phrase_indices = np.argsort(result, axis=1)[:, -topk:][:, ::-1] doc_indices = [[self.mappings[phrase_indices[i][j]] for j in range(len(phrase_indices[i]))] for i in range(len(phrase_indices))] doc_scores = [] for i in range(len(phrase_indices)): doc_scores.append(result[i][[phrase_indices[i].tolist()]]) return doc_scores, doc_indices def _exec_embedding(self): p_encoder, q_encoder = self._load_model() train_dataset, eval_dataset = self._load_dataset(eval=True) args = TrainingArguments( output_dir="densephrase_retrieval", evaluation_strategy="epoch", learning_rate=self.args.retriever.learning_rate, per_device_train_batch_size=self.args.retriever.per_device_train_batch_size, per_device_eval_batch_size=self.args.retriever.per_device_eval_batch_size, num_train_epochs=self.args.retriever.num_train_epochs, weight_decay=self.args.retriever.weight_decay, gradient_accumulation_steps=self.args.retriever.gradient_accumulation_steps, ) p_encoder, q_encoder = self._train(args, train_dataset, p_encoder, q_encoder, eval_dataset) p_embedding = [] mappings = [] for idx, passage in enumerate(tqdm(self.contexts)): # wiki splitted = passage.split() for i in range(len(splitted) // self.window_size * 2): phrase = ' '.join(splitted[i*(self.window_size // 2):(i+2)*(self.window_size //2)]) phrase = self.tokenizer( phrase, padding="max_length", truncation=True, max_length=self.window_size, return_tensors="pt" ).to("cuda") p_emb = p_encoder(**phrase).to("cpu").detach().numpy() p_embedding.append(p_emb) mappings.append(idx) p_embedding = np.array(p_embedding).squeeze() # numpy return p_embedding, q_encoder, mappings class DPTrainMixin: def _load_dataset(self, eval=False): datasets = get_retriever_dataset(self.args) train_dataset = datasets["train"] # TODO delete # train_dataset = train_dataset.select(range(100)) # with negative examples questions = [] phrases = [] labels = [] for idx, question in enumerate(tqdm(train_dataset["question"])): answer_passage = train_dataset["context"][idx] splitted = answer_passage.split() for phrase_idx in range(len(splitted) // self.window_size * 2): phrase = ' '.join(splitted[phrase_idx*(self.window_size // 2):(phrase_idx+2)*(self.window_size //2)]) # NOTE: Overlap? while True: incorrect_passage = random.choice(train_dataset["context"]) incorrect_passage_splitted = incorrect_passage.split() if len(incorrect_passage_splitted) // self.window_size >= self.sample_per_phrase: break incorrect_phrase_indices = random.sample(range(0, len(incorrect_passage_splitted) // self.window_size), self.sample_per_phrase - 1) incorrect_phrases = [' '.join(incorrect_passage_splitted[i*(self.window_size // 2):(i+2)*(self.window_size //2)]) for i in incorrect_phrase_indices] incorrect_phrases.insert(phrase_idx % self.sample_per_phrase, phrase) questions.append(question) phrases.append(incorrect_phrases) labels.append(phrase_idx % self.sample_per_phrase) print('Dataset prepare success') print(f'Length : {len(questions)}') q_seqs = self.tokenizer( questions, padding="longest", truncation=True, max_length=512, return_tensors="pt" ) p_seqs = self.tokenizer( list(chain(*phrases)), padding="max_length", truncation=True, max_length=self.window_size, return_tensors="pt" ) embedding_size = p_seqs["input_ids"].shape[-1] for k in p_seqs.keys(): p_seqs[k] = p_seqs[k].reshape(-1, self.sample_per_phrase, embedding_size) train_dataset = TensorDataset( p_seqs["input_ids"], p_seqs["attention_mask"], p_seqs["token_type_ids"], q_seqs["input_ids"], q_seqs["attention_mask"], q_seqs["token_type_ids"], torch.tensor(labels) ) eval_dataset = None return train_dataset, eval_dataset def _train(self, training_args, train_dataset, p_model, q_model, eval_dataset): print("TRAINING IN DensePhrase TRAIN MIXIN") train_sampler = RandomSampler(train_dataset) train_dataloader = DataLoader( train_dataset, sampler=train_sampler, batch_size=training_args.per_device_train_batch_size, drop_last=True ) if eval_dataset: eval_sampler = RandomSampler(eval_dataset) eval_dataloader = DataLoader( eval_dataset, sampler=eval_sampler, batch_size=training_args.per_device_eval_batch_size ) optimizer_grouped_parameters = [{"params": p_model.parameters()}, {"params": q_model.parameters()}] optimizer = AdamW(optimizer_grouped_parameters, lr=training_args.learning_rate, eps=training_args.adam_epsilon) t_total = len(train_dataloader) // training_args.gradient_accumulation_steps * training_args.num_train_epochs scheduler = get_linear_schedule_with_warmup( optimizer, num_warmup_steps=training_args.warmup_steps, num_training_steps=t_total ) global_step = 0 p_model.train() q_model.train() p_model.zero_grad() q_model.zero_grad() torch.cuda.empty_cache() for epoch in range(training_args.num_train_epochs): train_loss = 0.0 start_time = time.time() for step, batch in enumerate(train_dataloader): if torch.cuda.is_available(): batch = tuple(t.cuda() for t in batch) embedding_size = batch[0].shape[-1] p_inputs = { "input_ids": batch[0].reshape(-1, embedding_size), "attention_mask": batch[1].reshape(-1, embedding_size), "token_type_ids": batch[2].reshape(-1, embedding_size) } q_inputs = { "input_ids": batch[3], "attention_mask": batch[4], "token_type_ids": batch[5] } adder = torch.arange(0, training_args.per_device_train_batch_size).long() * self.sample_per_phrase if torch.cuda.is_available(): adder = adder.to("cuda") label = torch.repeat_interleave(batch[6] + adder, self.sample_per_phrase) p_outputs = p_model(**p_inputs) q_outputs = q_model(**q_inputs) q_outputs = torch.repeat_interleave(q_outputs, self.sample_per_phrase, dim=0) sim_scores = torch.matmul(q_outputs, torch.transpose(p_outputs, 0, 1)) sim_scores = F.log_softmax(sim_scores, dim=1) loss = F.nll_loss(sim_scores, label) loss = loss / training_args.gradient_accumulation_steps # print(p_inputs["input_ids"].shape) # print(q_inputs["input_ids"].shape) # print(p_outputs.shape) # print(q_outputs.shape) # print(label.shape) # print(label) print(f"epoch: {epoch + 1:02} step: {step:02} loss: {loss}", end="\r") train_loss += loss.item() loss.backward() if ((step + 1) % training_args.gradient_accumulation_steps) == 0: optimizer.step() scheduler.step() p_model.zero_grad() q_model.zero_grad() global_step += 1 torch.cuda.empty_cache() end_time = time.time() epoch_mins, epoch_secs = epoch_time(start_time, end_time) print(f"Epoch: {epoch + 1:02} | Time: {epoch_mins}m {epoch_secs}s") print(f"\tTrain Loss: {train_loss / len(train_dataloader):.4f}") p_model.train() q_model.train() return p_model, q_model

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thipaulino/tpTools

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/tpRig/tpRigBuilder/tpBuildable.py

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[]

no_license

https://github.com/thipaulino/tpTools

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refs/heads/master

2023-02-20T04:11:49.767739

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class Buildable(object): def __init__(self): self.build_methods_list = [] self.top_level_item = 'FaceRig' self.register_build_method('Pre-Build Utils', 'root', background_color='dark_magenta') self.register_build_method(self.top_level_item, 'root', background_color='dark_cyan') self.register_build_method('Post Build Utils', 'root', background_color='dark_green') # when item no parent and no method is added in register, code is breaking - improve def register_build_method(self, action_name, parent_action, method=None, after=None, background_color=None): """ Data Structure [{'method_name': method_name, 'parent': parent_action_name, 'method': self.method, 'after': method_name to be placed after}, {...}] :param action_name: :param parent_action: :param method: :param after: :param background_color: :return: """ method_data = { 'method_name': action_name, 'parent': parent_action, 'method': method, 'after': after, 'background_color': background_color, 'stop_flag': False} self.build_methods_list.append(method_data)

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arthuroe/ibu_backend

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/api/patient/views.py

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[]

no_license

https://github.com/arthuroe/ibu_backend

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refs/heads/develop

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2020-04-03T06:30:23

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import logging from flask import Blueprint, request, make_response, jsonify from flask.views import MethodView from api.decorators import token_required from api.models import Patient class PatientView(MethodView): """ View to manage patients """ decorators = [token_required] def get(self, current_user, patient_id=None): try: if patient_id: patient = Patient.find_first(id=patient_id) if not patient: response = { 'status': 'fail', 'message': 'Patient does not exist' } return make_response(jsonify(response)), 400 response = { 'status': 'success', 'patient': patient.serialize() } return make_response(jsonify(response)), 200 patients = Patient.fetch_all() if not patients: response = { 'status': 'success', 'message': 'No patients have been added' } return make_response(jsonify(response)), 200 response = { 'status': 'success', 'patients': [patient.serialize() for patient in patients] } return make_response(jsonify(response)), 200 except Exception as e: logging.error(f"An error has occurred {e}") response = { 'status': 'fail', 'message': 'Failed to retrieve patients.' } return make_response(jsonify(response)), 500 def post(self, current_user): kwargs = request.json phone_number = kwargs.get('phone_number') if not phone_number: response = { 'status': 'fail', 'message': 'Phone number is required.' } return make_response(jsonify(response)), 400 patient = Patient.find_first(phone_number=kwargs.get('phone_number')) kp_code = ( kwargs.get('first_name')[0] + kwargs.get('second_name')[0] + kwargs.get('third_name')[0] + str( int(kwargs.get('date_of_birth')[5:7])) + str(int(kwargs.get('date_of_birth')[0:4])) + kwargs.get('gender')[0] ) kwargs.update({"kp_code": kp_code}) if not patient: try: patient = Patient(**kwargs) patient.save() response = { 'status': 'success', 'message': f"Successfully Added {kwargs.get('first_name')}." } return make_response(jsonify(response)), 201 except Exception as e: logging.error(f"An error has occurred {e}") response = { 'status': 'fail', 'message': 'Failed to add patient. Please try again.' } return make_response(jsonify(response)), 401 else: response = { 'status': 'fail', 'message': 'Patient already exists.', } return make_response(jsonify(response)), 409 def put(self, current_user, patient_id): kwargs = request.json kwargs.update({"id": patient_id}) try: patient = Patient.find_first(id=patient_id) if patient: patient.update(**kwargs) response = { 'status': 'success', 'message': f'Successfully updated {patient.first_name}.' } return make_response(jsonify(response)), 201 response = { 'status': 'fail', 'message': 'Patient does not exist.', } return make_response(jsonify(response)), 400 except Exception as e: logging.error(f"An error has occurred {e}") response = { 'status': 'fail', 'message': 'Update failed. Please try again.' } return make_response(jsonify(response)), 500 def delete(self, current_user, patient_id): try: patient = Patient.find_first(id=patient_id) if patient: patient.delete() response = { 'status': 'success', 'message': f'Successfully deleted {patient.first_name}.' } return make_response(jsonify(response)), 200 response = { 'status': 'fail', 'message': 'Patient does not exist.', } return make_response(jsonify(response)), 400 except Exception as e: logging.error(f"An error has occurred {e}") response = { 'status': 'fail', 'message': 'Delete failed. Please try again.' } return make_response(jsonify(response)), 500

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openstack/python-troveclient

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/troveclient/tests/test_root.py

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refs/heads/master

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2022-05-11T10:03:17

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2013-06-14T21:58:05

2021-04-29T02:44:53

2021-04-29T07:38:00

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# Copyright 2015 Tesora 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 testtools from unittest import mock from troveclient.v1 import root """ Unit tests for root.py """ class RootTest(testtools.TestCase): def setUp(self): super(RootTest, self).setUp() self.orig__init = root.Root.__init__ root.Root.__init__ = mock.Mock(return_value=None) self.root = root.Root() self.root.api = mock.Mock() self.root.api.client = mock.Mock() def tearDown(self): super(RootTest, self).tearDown() root.Root.__init__ = self.orig__init def _get_mock_method(self): self._resp = mock.Mock() self._body = None self._url = None def side_effect_func(url, body=None): self._body = body self._url = url return (self._resp, body) return mock.Mock(side_effect=side_effect_func) def test_delete(self): self.root.api.client.delete = self._get_mock_method() self._resp.status_code = 200 self.root.delete(1234) self.assertEqual('/instances/1234/root', self._url) self._resp.status_code = 400 self.assertRaises(Exception, self.root.delete, 1234)

UTF-8

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false

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test_root.py

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someshwar123/python

15,315,853,403,521

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c9d8671400781bc2ec1cfe560cf49f17d436afcb

/set-9/lcm.py

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[]

no_license

https://github.com/someshwar123/python

7d6e9d5d4969742a999d0d7083415bef76a79346

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refs/heads/master

2020-03-24T03:42:27.655146

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#------------------------------------------------------------------------------- # Name: module1 # Purpose: # # Author: Somesh # # Created: 14/08/2018 # Copyright: (c) Somesh 2018 # Licence: <your licence> #------------------------------------------------------------------------------- def lcm (a,b): if(a>b): greater=a else: greater=b while(True): if((greater%a==0) and(greater%b==0)): lcm =greater break greater =greater+1 return lcm a=int(input("enter the a value")) b=int(input("enter the b value")) z=lcm(48,60) print ("The lcm is : ",z)

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lcm.py

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BlaiseGratton/DataAnalysisNgin

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/anatolution/models/project_marker_option/__init__.py

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refs/heads/master

2016-09-23T10:53:24.412773

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""" anatolution.project_marker_option ~~~~~~~~~~~~~~~~~~ """ from ...core import Service from .project_marker_option import ProjectMarkerOption class ProjectMarkerOptionService(Service): __model__ = ProjectMarkerOption

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McDermott-Group/Analysis

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/projects/fluxNoise/python/analyze_P1_dwell_time.py

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[]

no_license

https://github.com/McDermott-Group/Analysis

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refs/heads/master

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import os import numpy as np import noiselib import importlib importlib.reload(noiselib) from noiselib import matpaths from dataChest import * import general.calibration as cal import matplotlib.pyplot as plt from scipy.optimize import curve_fit import datasets importlib.reload(datasets) from datasets import * # q, date, filesP1, filesT1, thresh = 'Q3', '04-29-20', range(112,493), range(0,381), 0.33 # really bad # q, date, filesP1, filesT1, thresh = 'Q3', '04-29-20', range(0,63), range(0,63), 0.25 # shows nothing # q, date, filesP1, filesT1, thresh = 'Q4', '04-30-20', range(0,231), range(0,231), 0.44 ################################# # ds = q4_0430_T1 # ds = q3_0501_T1 # ds = q1_0503_T1 ds = q2_0505_T1 fP1_I = matpaths(fileName='P1_I', fileNums='files_P1', **ds) fP1_X = matpaths(fileName='P1_X', fileNums='files_P1', **ds) dwellsDirty = np.array([]) dwellsClean = np.array([]) dwellsDirty1 = np.array([]) dwellsDirty2 = np.array([]) dwellsDirty3 = np.array([]) if 'recalibrate' in ds and ds['recalibrate']: data = noiselib.loadmat( fP1_I[0] ) iq0 = np.array((data['Is'],data['Qs'])) data = noiselib.loadmat( fP1_X[0] ) iq1 = np.array((data['Is'],data['Qs'])) c = cal.CalibratedStates( (0,iq0), (1,iq1), plot=False) for i,f in enumerate(fP1_I): try: data = noiselib.loadmat( f ) except: print('corrupted file:', f) data = {'Single_Shot_Occupations': [np.nan], 'Single_Shot_Occupation': [np.nan]} if 'recalibrate' in ds and ds['recalibrate']: states, SSO, _ = c.get_single_shot_occupation( np.array((data['Is'], data['Qs'])) ) else: states = data['Single_Shot_Occupations'] SSO = {1: data['Single_Shot_Occupation']} d0,d1 = noiselib.bin_dwell_times(states) if SSO[1] > ds['thresh_P1']: dwellsDirty = np.append(dwellsDirty, d0) if i in range(30,40): dwellsDirty1 = np.append(dwellsDirty, d0) elif i in range(80,88): dwellsDirty2 = np.append(dwellsDirty, d0) elif i in range(311,319): dwellsDirty3 = np.append(dwellsDirty, d0) else: dwellsClean = np.append(dwellsClean, d0) fig, ax = plt.subplots() ax.hist(dwellsDirty1, bins, color='red') ax.hist(dwellsDirty2, bins, color='blue', alpha=0.6) ax.hist(dwellsDirty3, bins, color='green', alpha=0.6) ax.set_xlabel('Dwell Time in 0 State Before Excitation [Reps=500us]') ax.set_ylabel('Counts') ax.set_yscale('log') fig.suptitle(ds['Q']+'\n'+str(ds['date'])) plt.draw() plt.pause(0.05) fig, ax = plt.subplots() hD, bins, _ = ax.hist(dwellsDirty,30, color='red') hC, bins, _ = ax.hist(dwellsClean, bins, color='blue', alpha=0.6) ax.set_xlabel('Dwell Time in 0 State Before Excitation [Reps=500us]') ax.set_ylabel('Counts') ax.set_yscale('log') fig.suptitle(ds['Q']+'\n'+str(ds['date'])) plt.draw() plt.pause(0.05) def exponential(t, a, tau): return a*np.exp(-t/tau) def poisoned_exponential(t, b, a, tau_r, n_qp, tau_qp): return b + a*np.exp(-t/tau_r)*np.exp(n_qp*(np.exp(-t/tau_qp)-1)) def poisoned_exponential_simul(t, a0, a1, tau_r, n_qp0, n_qp1, tau_qp0, tau_qp1): return np.ravel([poisoned_exponential(t, 0, a0, tau_r, n_qp0, tau_qp0), poisoned_exponential(t, 0, a1, tau_r, n_qp1, tau_qp1)]) t = (bins[1:]+bins[:-1])/2 poptD, pcovD = curve_fit(exponential, t[t.size/2:], hD[t.size/2:], p0=[hD.max()/2, .3]) poptC, pcovC = curve_fit(exponential, t[t.size/2:], hC[t.size/2:], p0=[hC.max()/2, .3]) ax.plot(t, exponential(t, *poptD), 'k:') ax.plot(t, exponential(t, *poptC), 'k:') ax.set_ylim([0.5, None]) plt.draw() plt.pause(0.05) popt, pcov = curve_fit(poisoned_exponential_simul, t, np.ravel([hD,hC]), p0=[poptD[0],poptC[0],poptC[1],1.,0.,.5,.5], bounds=(0,np.inf)) # bounds=([0,0,0,0,0,0,0],[np.inf,np.inf,np.inf,3,3,np.inf,np.inf])) fits = poisoned_exponential_simul(t, *popt).reshape((2,t.size)) ax.plot(t, np.transpose(fits), 'k', linewidth=2) plt.draw() plt.pause(0.05) text = '{:>7}{:>12}{:>12}\n'.format('','Dirty','Clean') # text += '{:>7}{:>12.3f}{:>12.3f}\n'.format('A',*popt[0:2]) text += '{:>7}{:>12.3f}{:>12}\n'.format('tau_R',popt[2]*500,'') text += '{:>7}{:>12.3f}{:>12.3f}\n'.format('n_QP',*popt[3:5]) text += '{:>7}{:>12.3f}{:>12.3f}\n'.format('tau_QP',popt[5]*500,popt[6]*500) text += '{:>7}{:>12.3f}{:>12.3f}\n'.format('tau',poptD[1]*500,poptC[1]*500) ax.text(t[-1],fits.max()/10, text, family='monospace', horizontalalignment='right') plt.draw() plt.pause(0.05)

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tell-k/code-snippets

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from unicodedata import normalize import sys, codecs sys.stdout = codecs.getwriter("utf-8")(sys.stdout) with open('./templates/core/index.html') as f: hoge = f.readlines() hoge_body = "".join(hoge) hoge_nfc = normalize('NFC', hoge_body.decode('utf8')) print hoge_nfc

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convert_nfc.py

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sintetizzatore/dsp

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no_license

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2020-04-07T12:44:37.545561

2015-09-24T23:26:32

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import csv with open('faculty.csv', 'r') as book1: with open('emails.csv', 'r') as book2: reader1 = csv.reader(book1, delimiter=',') reader2 = csv.reader(book2, delimiter=',') both = [] fields = reader1.next() reader2.next() for row1, row2 in zip(reader1, reader2): row2.append(row1[-1]) both.append(row2) with open('emails2.csv', 'w') as output: writer = csv.writer(output, delimiter=',') writer.writerow(fields) writer.writerows(both)

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py

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advanced_python_csv.py

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BrutuZ/Flexget

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2023-08-30T22:31:16.746674

2023-08-28T15:14:04

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MIT

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2018-07-31T20:03:45

2022-03-19T22:29:58

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import re from urllib.parse import urlparse, urlunparse from loguru import logger from requests import RequestException from flexget import plugin from flexget.components.sites.urlrewriting import UrlRewritingError from flexget.event import event from flexget.utils.soup import get_soup logger = logger.bind(name='eztv') EZTV_MIRRORS = [('http', 'eztv.ch'), ('https', 'eztv-proxy.net'), ('http', 'eztv.come.in')] class UrlRewriteEztv: """Eztv url rewriter.""" def url_rewritable(self, task, entry): return urlparse(entry['url']).netloc == 'eztv.ch' def url_rewrite(self, task, entry): url = entry['url'] page = None for scheme, netloc in EZTV_MIRRORS: try: _, _, path, params, query, fragment = urlparse(url) url = urlunparse((scheme, netloc, path, params, query, fragment)) page = task.requests.get(url).content except RequestException: logger.debug('Eztv mirror `{}` seems to be down', url) continue break if not page: raise UrlRewritingError('No mirrors found for url %s' % entry['url']) logger.debug('Eztv mirror `{}` chosen', url) try: soup = get_soup(page) mirrors = soup.find_all('a', attrs={'class': re.compile(r'download_\d')}) except Exception as e: raise UrlRewritingError(e) logger.debug('{} torrent mirrors found', len(mirrors)) if not mirrors: raise UrlRewritingError('Unable to locate download link from url %s' % url) entry['urls'] = [m.get('href') for m in mirrors] entry['url'] = mirrors[0].get('href') @event('plugin.register') def register_plugin(): plugin.register(UrlRewriteEztv, 'eztv', interfaces=['urlrewriter'], api_ver=2)

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jongfranco/python-workshop-2

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/day-1/if-else.py

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no_license

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refs/heads/master

2022-11-16T17:26:52.490254

2020-07-15T18:39:15

null

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null

""" Structure of if else if predicate: code code code elif predicate2: (not cumpolsory) code code elif predicate3: (not cumpolsory) code code elif predicate4: (not cumpolsory) code code else: (not compulsory) code code elif --> else if """ # if 1 > 2: # print('i am in if block') # else: # print('i am in else block') # # print('i am outside if else') number = int(input()) if number < 5: print('less than 5') elif 5 <= number < 10: print('greater than equal to 5 and less than 10') elif 10 <= number < 20: print('very large number') else: print('OMG!!!!') print('outside if else block')

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willist/dailyprogrammer

14,207,751,820,130

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/049_hard.py

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no_license

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refs/heads/master

2020-04-01T08:12:57.865946

2012-05-08T14:54:34

2012-05-08T14:55:24

null

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null

import sys from collections import defaultdict from contextlib import contextmanager from itertools import product from math import factorial def dice_iter(n): for item in range(n): yield range(1,7) def count_sums(iterator): counter = defaultdict(int) for item in iterator: if sum(item) == 5: print item counter[sum(item)] += 1 return counter def dice_sums(n): return count_sums(product(*dice_iter(n))) @contextmanager def no_recursion_limit(): limit = sys.getrecursionlimit() sys.setrecursionlimit(100000) yield sys.setrecursionlimit(limit) def combos(num_dice, target_sum, prev_die=None): if num_dice == 1 and prev_die <= target_sum <= 6: yield [target_sum] else: start = 1 if prev_die is None else prev_die end = 7 for head in range(start, end): remaining_sum = target_sum - head remaining_dice = num_dice - 1 if remaining_dice <= remaining_sum <= (remaining_dice * 6): for tail in combos(remaining_dice, remaining_sum, head): yield [head] + tail def counter(iterator): counter = defaultdict(int) for item in iterator: counter[item] += 1 return counter def j(num_dice, sum_dice): total = 0 top = factorial(num_dice) with no_recursion_limit(): for index, combo in enumerate(combos(num_dice, sum_dice)): count = counter(combo) bottoms = [factorial(c) for c in count.values()] bottom = reduce(lambda x,y: x*y, bottoms) sub_total = top/bottom if not index % 100000: print combo, sub_total total += sub_total return total if __name__ == "__main__": assert j(02, 07) == 6 assert j(02, 10) == 3 assert j(02, 12) == 1 assert j(03, 10) == 27 assert j(05, 20) == 651 assert j(07, 30) == 12117 assert j(10, 50) == 85228 print j(20, 100) print j(1100, 5000) % pow(10,7)

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049_hard.py

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AMDevG/MarathonTrackerServer

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/marathonapp/models.py

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[]

no_license

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eb64bff7f4d030aa960b7c4506479a49be2d1d41

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refs/heads/master

2018-12-23T13:06:14.843724

2018-10-16T17:12:19

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null

from django.db import models class RunTrain(models.Model): date = models.DateTimeField(auto_now_add=True) distance = models.CharField(max_length=255, null=True, blank=True, default=None) time = models.CharField(max_length=255, null=True, blank=True, default=None) minsPerMile = models.CharField(max_length=255, null=True, blank=True, default=None) def __str__(self): return '{}'.format(self.name) class CrossTrain(models.Model): date = models.DateTimeField(auto_now_add=True) exercise = models.CharField(max_length=255, null=True, blank=True, default=None) time = models.CharField(max_length=255, null=True, blank=True, default=None) def __str__(self): return '{}'.format(self.name) class LiftTrain(models.Model): date = models.DateTimeField(auto_now_add=True) exercise = models.CharField(max_length=255, null=True, blank=True, default=None) time = models.CharField(max_length=255, null=True, blank=True, default=None) def __str__(self): return '{}'.format(self.name)

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JosephLevinthal/Research-projects

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/5 - Notebooks e Data/1 - Análises numéricas/Arquivos David/Atualizados/logDicas-master/data/2019-1/223/users/4444/codes/1716_2504.py

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[]

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refs/heads/master

2022-07-31T06:43:02.686109

2020-05-23T00:24:26

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null

v=int(input("quantidade de virus: ")) l=int(input("qtd leucocitos: ")) pv=float(input(" percentual de mut virus: ")) pl=float(input(" percentual de mut leococutos: ")) dias=0 i=0 while(l<=2*v): v=v+v*pv/100 l=l+l*pl/100 i=i+1 dias=dias+1 print(dias)

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oliverroick/rosi

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refs/heads/master

2020-03-30T12:51:21.319148

2018-10-06T11:20:06

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MIT

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2018-10-06T10:32:45

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null

def depth(L): return isinstance(L, list) and max(map(depth, L))+1

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liana-80/flask-vue-example

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/api_rest/privileges.py

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refs/heads/master

2022-09-25T12:39:55.975663

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MIT

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2020-06-04T15:03:11

2020-06-04T14:21:37

2020-06-04T14:34:59

2020-06-04T15:03:10

41

0

Python

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# coding=utf-8 """ desc: 定义权限 author: congqing.li date: 2016-10-31 """ from permission.permission import ItemPermission, VIEWNEEDS, MANAGENEEDS # 权限管理模块的查看权限 admin_view = ItemPermission("admin", u"用户角色管理", VIEWNEEDS) # 权限管理模块的管理权限 admin_manage = ItemPermission("admin", u"用户角色管理", MANAGENEEDS) # 学生管理权限 student_manage = ItemPermission("student", u"学生管理", MANAGENEEDS)

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au3641/HEPY_site

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/HEPY_django/HEPY_new/migrations/0005_auto_20170716_1903.py

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[]

no_license

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refs/heads/master

2020-05-20T15:06:10.032928

2017-07-24T21:30:40

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# -*- coding: utf-8 -*- # Generated by Django 1.11.3 on 2017-07-16 17:03 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('HEPY_new', '0004_auto_20170712_0716'), ] operations = [ migrations.AddField( model_name='question', name='group', field=models.IntegerField(blank=True, null=True), ), migrations.AlterField( model_name='answerweight', name='type', field=models.CharField(choices=[('risk', 'risk'), ('hepatitis_a_b', 'hepatitis_a_b'), ('not_a_b', 'not_a_b'), ('order', 'order')], default='risk', max_length=16), ), ]

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baehll/python-exercise

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/chapter12/managerui.py

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[]

no_license

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refs/heads/master

2020-03-13T16:13:17.082255

2018-05-15T14:11:28

131,192,437

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null

##################### # Aufgabe 1,12.4.3# # v1.0 # # baehll # # 02.05.2018 # ##################### import pickle from musical import * class Manager: __menuetext = """ Musical-Manager ------------------ (n)eue Vorstellung (U)eberblick Vorstellungen (S)torniere Vorstellung (E)nde """ def __init__(self, datei): self.__datei = datei self.__lade_musical() self.__run() def __run(self): print(self.__menuetext) wahl = "-" while wahl not in ["e", "E"]: wahl = input("Auswahl: ") if wahl in ["n", "N"]: self.__neueVorstellung() elif wahl in ["u", "U"]: print(self.__musical) elif wahl in ["s", "S"]: self.__storniere() print(self.__menuetext) print("Danke für die Benutzung vom Musical-Manager") self.__speichern() def __storniere(self): datum = input("Datum der Vorstellung: ") text = self.__musical.storniere(datum) print(text) def __neueVorstellung(self): datum = input("Termin: ") beginn = input("Beginn der Vorstellung: ") vorstellung = Vorstellung(datum, beginn, self.__musical.saal) self.__musical.neueVorstellung(vorstellung) def __neuesMusical(self): titel = input("Titel: ") eintrittspreis = float(input("Eintrittspreis: ")) anzahl_reihen = int(input("Anzahl Sitzreihen: ")) liste = [] for i in range(anzahl_reihen): sitze = int(input("Sitze in Reihe " + str(i + 1) + ": ")) liste.append(sitze) saal = Saal(liste) self.__musical = Musical(titel, eintrittspreis, saal) def __lade_musical(self): try: f = open(self.__datei, "rb") self.__musical = pickle.load(f) f.close() print("\n W I L L K O M M E N") print("beim Manangement-System für das Musical", self.__musical.titel) except: print("Kein Musical gespeichert") print("Richten Sie ein neues Musical ein.") self.__neuesMusical() def __speichern(self): f = open(self.__datei, "wb") pickle.dump(self.__musical, f) f.close() m = Manager("daten/hairspray.txt")

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managerui.py

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mfigat/public_rshpn_tool

1,151,051,275,070

81371fa5fb576508aa13a6fb0a0e0e41a2b53828

cfd374b34a6b1a6ae16b5d23f633a0c47ae471e1

/generated_python_code/ball_collector/teleoperated/scripts/subsystem_cs.py

a8addcfbb53cffe97cb94e2be8cea36f22e5d4af

[ "BSD-3-Clause" ]

permissive

https://github.com/mfigat/public_rshpn_tool

dd91d12e28d31a9c97c878b4d6e0a482a9bddfb6

3555cb8f1eb35ef12441b9aef63dae8f578c2aa7

refs/heads/master

2021-11-05T23:47:08.904506

2021-11-02T12:26:29

207,675,046

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#!/usr/bin/env python ''' Copyright (c) 2019, Robot Control and Pattern Recognition Group, Warsaw University of Technology All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the Warsaw University of Technology nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYright HOLDER> BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Author: Maksym Figat ''' # Import other scripts # from auxiliary_functions import * from auxiliary_agent_teleoperated import * from auxiliary_subsystem_cs import * # Temporary definitions # IS_LOG = False # Flag determining if logs are shown in the terminal # IS_PRINT = True # Flag indicating if debug information for developer are shown in the terminal # class cs: ##### Subsystem cs constructor ##### def __init__(self): self.log("__init__ function") rospy.init_node("cs") self._subsystemName="cs" self._subsystemFrequency=10; self._currentSubsystemBehaviour="Behaviour_initBehaviour"; self._subsystemIterations=0 self._behaviourIterations=0 self.initialiseCommunicationModel() self.auxiliaryFunctions = AuxiliaryFunctions(self._subsystemFrequency) # initialize all input flags self._in_flag_taskCommand=False self._in_flag_robotStatus=False self._in_flag_ballInfoTele=False self._in_flag_obstacleDetectedTele=False self._in_flag_ballCollected=False # initialize all output flags self._out_flag_taskStatus=False self._out_flag_desiredRobotCommandTele=False pass ##### Start subsystem ##### def startSubsystem(self): self.log("startSubsystem") try: while self.auxiliaryFunctions.isSubsystemOK(): ''' Execute behaviour associated with _currentSubsystemBehaviour -- choose appropriate state based on _currentSubsystemBehaviour ''' if self._currentSubsystemBehaviour=="Behaviour_initBehaviour": self.log("_currentSubsystemBehaviour==Behaviour_initBehaviour") self.subsystemBehaviour_initBehaviour() continue if self._currentSubsystemBehaviour=="Behaviour_idleBehaviour": self.log("_currentSubsystemBehaviour==Behaviour_idleBehaviour") self.subsystemBehaviour_idleBehaviour() continue if self._currentSubsystemBehaviour=="Behaviour_terminateBehaviour": self.log("_currentSubsystemBehaviour==Behaviour_terminateBehaviour") self.subsystemBehaviour_terminateBehaviour() continue if self._currentSubsystemBehaviour=="Behaviour_terminatedBehaviour": self.log("_currentSubsystemBehaviour==Behaviour_terminatedBehaviour") self.subsystemBehaviour_terminatedBehaviour() continue if self._currentSubsystemBehaviour=="Behaviour_stopBehaviour": self.log("_currentSubsystemBehaviour==Behaviour_stopBehaviour") self.subsystemBehaviour_stopBehaviour() continue if self._currentSubsystemBehaviour=="Behaviour_moveFasterBehaviour": self.log("_currentSubsystemBehaviour==Behaviour_moveFasterBehaviour") self.subsystemBehaviour_moveFasterBehaviour() continue if self._currentSubsystemBehaviour=="Behaviour_moveSlowerBehaviour": self.log("_currentSubsystemBehaviour==Behaviour_moveSlowerBehaviour") self.subsystemBehaviour_moveSlowerBehaviour() continue if self._currentSubsystemBehaviour=="Behaviour_vacuumOnBehaviour": self.log("_currentSubsystemBehaviour==Behaviour_vacuumOnBehaviour") self.subsystemBehaviour_vacuumOnBehaviour() continue if self._currentSubsystemBehaviour=="Behaviour_vacuumOffBehaviour": self.log("_currentSubsystemBehaviour==Behaviour_vacuumOffBehaviour") self.subsystemBehaviour_vacuumOffBehaviour() continue if self._currentSubsystemBehaviour=="Behaviour_moveBackwardBehaviour": self.log("_currentSubsystemBehaviour==Behaviour_moveBackwardBehaviour") self.subsystemBehaviour_moveBackwardBehaviour() continue if self._currentSubsystemBehaviour=="Behaviour_moveFrontBehaviour": self.log("_currentSubsystemBehaviour==Behaviour_moveFrontBehaviour") self.subsystemBehaviour_moveFrontBehaviour() continue if self._currentSubsystemBehaviour=="Behaviour_moveRightBehaviour": self.log("_currentSubsystemBehaviour==Behaviour_moveRightBehaviour") self.subsystemBehaviour_moveRightBehaviour() continue if self._currentSubsystemBehaviour=="Behaviour_moveLeftBehaviour": self.log("_currentSubsystemBehaviour==Behaviour_moveLeftBehaviour") self.subsystemBehaviour_moveLeftBehaviour() continue if self._currentSubsystemBehaviour=="Behaviour_rotateLeftBehaviour": self.log("_currentSubsystemBehaviour==Behaviour_rotateLeftBehaviour") self.subsystemBehaviour_rotateLeftBehaviour() continue if self._currentSubsystemBehaviour=="Behaviour_rotateRightBehaviour": self.log("_currentSubsystemBehaviour==Behaviour_rotateRightBehaviour") self.subsystemBehaviour_rotateRightBehaviour() continue if self._currentSubsystemBehaviour=="Behaviour_whatCanYouSeeBehaviour": self.log("_currentSubsystemBehaviour==Behaviour_whatCanYouSeeBehaviour") self.subsystemBehaviour_whatCanYouSeeBehaviour() continue except Exception as e: print e self.error("Error found in function startSubsystem -- file subsystem_cs.py!") pass ##### Update data for input buffer: taskCommand ##### def update_taskCommand(self, data): self.log("update_taskCommand") self.taskCommand=data self._in_flag_taskCommand=True pass ##### Update data for input buffer: ballInfoTele ##### def update_ballInfoTele(self, data): self.log("update_ballInfoTele") self.ballInfoTele=data self._in_flag_ballInfoTele=True pass ##### Update data for input buffer: obstacleDetectedTele ##### def update_obstacleDetectedTele(self, data): self.log("update_obstacleDetectedTele") self.obstacleDetectedTele=data self._in_flag_obstacleDetectedTele=True pass ##### Update data for input buffer: ballCollected ##### def update_ballCollected(self, data): self.log("update_ballCollected") self.ballCollected=data self._in_flag_ballCollected=True pass ##### Initialise communication model ##### def initialiseCommunicationModel(self): self.log("initialiseCommunicationModel") self.initialiseSendChannel() self.initialiseSendChannelForDiagnostics() self.initialiseReceiveChannel() pass ##### Initialise send channel ##### def initialiseSendChannel(self): self.log("initialiseSendChannel") # Buffer name=taskStatus - Sender using NON-BLOCKING mode, receiver using NON-BLOCKING mode self._sender_taskStatus=rospy.Publisher("taskStatusChannelTele", String, queue_size=CHANNEL_SIZE) # Buffer name=desiredRobotCommandTele - Sender using NON-BLOCKING mode, receiver using NON-BLOCKING mode self._sender_desiredRobotCommandTele=rospy.Publisher("desiredRobotCommandChannelTele", String, queue_size=CHANNEL_SIZE) pass ##### Initialise send channel for diagnostics ##### def initialiseSendChannelForDiagnostics(self): self.log("initialiseSendChannelForDiagnostics") self._vectorOfSenderDiagnostics=[] self._vectorOfSenderDiagnostics.append(rospy.Publisher('cs/_currentSubsystemBehaviour', String, queue_size=CHANNEL_SIZE)) self._vectorOfSenderDiagnostics.append(rospy.Publisher('cs/_subsystemFrequency', Float64, queue_size=CHANNEL_SIZE)) self._vectorOfSenderDiagnostics.append(rospy.Publisher('cs/_subsystemName', String, queue_size=CHANNEL_SIZE)) self._vectorOfSenderDiagnostics.append(rospy.Publisher('cs/_subsystemIterations', Int64, queue_size=CHANNEL_SIZE)) self._vectorOfSenderDiagnostics.append(rospy.Publisher('cs/_behaviourIterations', Int64, queue_size=CHANNEL_SIZE)) self._vectorOfSenderDiagnostics.append(rospy.Publisher('cs/isNewCommandReceived', Int64, queue_size=CHANNEL_SIZE)) self._vectorOfSenderDiagnostics.append(rospy.Publisher('cs/_in_flag_taskCommand', Bool, queue_size=CHANNEL_SIZE)) self._vectorOfSenderDiagnostics.append(rospy.Publisher('cs/_in_flag_robotStatus', Bool, queue_size=CHANNEL_SIZE)) self._vectorOfSenderDiagnostics.append(rospy.Publisher('cs/_in_flag_ballInfoTele', Bool, queue_size=CHANNEL_SIZE)) self._vectorOfSenderDiagnostics.append(rospy.Publisher('cs/_in_flag_obstacleDetectedTele', Bool, queue_size=CHANNEL_SIZE)) self._vectorOfSenderDiagnostics.append(rospy.Publisher('cs/_in_flag_ballCollected', Bool, queue_size=CHANNEL_SIZE)) self._vectorOfSenderDiagnostics.append(rospy.Publisher('cs/_out_flag_taskStatus', Bool, queue_size=CHANNEL_SIZE)) self._vectorOfSenderDiagnostics.append(rospy.Publisher('cs/_out_flag_desiredRobotCommandTele', Bool, queue_size=CHANNEL_SIZE)) pass ##### Initialise receive channel based on input buffers ##### def initialiseReceiveChannel(self): self.log("initialiseReceiveChannel") # Buffer name=taskCommand sender NON-BLOCKING mode - receiver NON-BLOCKING mode self._subscriber_taskCommand=rospy.Subscriber("taskCommandChannel", String, self.update_taskCommand) # Buffer name=ballInfoTele sender NON-BLOCKING mode - receiver NON-BLOCKING mode self._subscriber_ballInfoTele=rospy.Subscriber("ballInfoChannelTele", CameraMessage, self.update_ballInfoTele) # Buffer name=obstacleDetectedTele sender NON-BLOCKING mode - receiver NON-BLOCKING mode self._subscriber_obstacleDetectedTele=rospy.Subscriber("obstacleDetectedChannelTele", ObstacleDetected, self.update_obstacleDetectedTele) # Buffer name=ballCollected sender NON-BLOCKING mode - receiver NON-BLOCKING mode self._subscriber_ballCollected=rospy.Subscriber("ballCollectedChannelTele", Bool, self.update_ballCollected) pass ##### Wait for all messages ##### def waitForAllMessages(self): self.log("waitForAllMessages") #rospy.wait_for_message("", String, timeout=TOPIC_TIMEOUT) #rospy.wait_for_message("", String, timeout=TOPIC_TIMEOUT) #rospy.wait_for_message("", CameraMessage, timeout=TOPIC_TIMEOUT) #rospy.wait_for_message("", ObstacleDetected, timeout=TOPIC_TIMEOUT) #rospy.wait_for_message("", Bool, timeout=TOPIC_TIMEOUT) pass ##### Publish on topics diagnostic data concerning the subsystem state ##### def sendDataForDiagnostics(self): self._vectorOfSenderDiagnostics[0].publish(self._currentSubsystemBehaviour) self._vectorOfSenderDiagnostics[1].publish(self._subsystemFrequency) self._vectorOfSenderDiagnostics[2].publish(self._subsystemName) self._vectorOfSenderDiagnostics[3].publish(self._subsystemIterations) self._vectorOfSenderDiagnostics[4].publish(self._behaviourIterations) ###### internal state ##### if(12 < len(self._vectorOfSenderDiagnostics) ): self._vectorOfSenderDiagnostics[5].publish(self.isNewCommandReceived) self._vectorOfSenderDiagnostics[6].publish(self._in_flag_taskCommand) self._vectorOfSenderDiagnostics[7].publish(self._in_flag_robotStatus) self._vectorOfSenderDiagnostics[8].publish(self._in_flag_ballInfoTele) self._vectorOfSenderDiagnostics[9].publish(self._in_flag_obstacleDetectedTele) self._vectorOfSenderDiagnostics[10].publish(self._in_flag_ballCollected) self._vectorOfSenderDiagnostics[11].publish(self._out_flag_taskStatus) self._vectorOfSenderDiagnostics[12].publish(self._out_flag_desiredRobotCommandTele) pass ##### Behaviour definitions ##### ##### Behaviour initBehaviour ##### ##### Terminal condition ##### def terminalCondition_initBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour initBehaviour] -- Checking Terminal Condition") return True pass ##### Error condition ##### def errorCondition_initBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour initBehaviour] -- Checking Error Condition") return False pass ##### Transition function ##### def transitionFunction_initBehaviour(self): self.log("[Behaviour initBehaviour] -- Calculating Transition Function") # Transition function # self.log("TRANSITION FUNCTION - initBehaviour consists of the following partial transition functions (decomposition based on output buffers)") # Partial transition function call: fun1 self.transitionFunction_initBehaviour_fun1() # Partial transition function call: set_buffer_flags_function self.transitionFunction_initBehaviour_set_buffer_flags_function() pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_initBehaviour_fun1(self): self.log("[Behaviour initBehaviour] -- Calculating Partial Transition Function fun1") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - initBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_initBehaviour_fun1_0() pass ##### Partial transition function: fun1_0 based on input buffers True ##### def transitionFunction_initBehaviour_fun1_0(self): self.log("[Behaviour initBehaviour] -- Calculating Partial Transition Function fun1_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - initBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code print("[CS - teleoperated] -- initBehaviour") self.taskCommand=String("empty") self.taskStatus=String("empty") self.desiredRobotCommandTele=String("empty") self.robotStatus=String("empty") self.isNewCommandReceived=Int64(0) # End - Partial Transition Function Code pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_initBehaviour_set_buffer_flags_function(self): self.log("[Behaviour initBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - initBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_initBehaviour_set_buffer_flags_function_0() pass ##### Partial transition function: set_buffer_flags_function_0 based on input buffers True ##### def transitionFunction_initBehaviour_set_buffer_flags_function_0(self): self.log("[Behaviour initBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - initBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code # End - Partial Transition Function Code pass ##### End of transition function ##### ##### Send data to other subsystems ##### def sendData_initBehaviour(self): self.log("[Behaviour initBehaviour] -- Sending Data") # DIAGNOSTICS SEND # self.sendDataForDiagnostics() # END OF DIAGNOSTICS SEND # # TYPICAL SEND CALL # # check if output buffer taskStatus has new data - i.e. is ready to send new data if( self._out_flag_taskStatus ): # send data from output buffer taskStatus # Buffer taskStatus - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_taskStatus.publish(self.taskStatus) # sending data from output buffer taskStatus # # indicate that data was sent and now the output buffer taskStatus is empty self._out_flag_taskStatus=False # check if output buffer desiredRobotCommandTele has new data - i.e. is ready to send new data if( self._out_flag_desiredRobotCommandTele ): # send data from output buffer desiredRobotCommandTele # Buffer desiredRobotCommandTele - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_desiredRobotCommandTele.publish(self.desiredRobotCommandTele) # sending data from output buffer desiredRobotCommandTele # # indicate that data was sent and now the output buffer desiredRobotCommandTele is empty self._out_flag_desiredRobotCommandTele=False # END OF TYPICAL SEND CALL # # BEGIN OF BODY SEND CALL # # END OF BODY SEND CALL # pass ##### Receive data from other subsystems ##### def receiveData_initBehaviour(self): self.log("[Behaviour initBehaviour] -- Receiving Data") # TYPICAL RECEIVE CALL # # Buffer taskCommand - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer taskCommand # Buffer ballInfoTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballInfoTele # Buffer obstacleDetectedTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer obstacleDetectedTele # Buffer ballCollected - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballCollected self.waitForAllMessages() # # END OF TYPICAL RECEIVE CALL # # BEGIN OF RECEIVE BODY CALL # # END OF RECEIVE BODY CALL # pass ##### Execute behaviour initBehaviour ##### def executeBehaviour_initBehaviour(self): self.log("[Behaviour initBehaviour] -- Executing initBehaviour Behaviour") stopBehaviourIteration=False # Execution of a single iteration of a behaviour initBehaviour # _behaviourIterations=0 # Starts execution! # while True: # Sleep is a method from class AuxiliaryFunctions which executes sleep from ROS # self.auxiliaryFunctions.sleep() # Calculates transition function -- output and internal buffers can only be modified by this function! # self.transitionFunction_initBehaviour() # Sends data! # self.sendData_initBehaviour() # Updates index! -- i.e. i:i+1 -- increment number of behaviour iterations and number of subsystem iterations # self._behaviourIterations=self._behaviourIterations+1 # Receives data! # self.receiveData_initBehaviour() # Check both conditions, i.e. terminal condition and error condition # stopBehaviourIteration = self.terminalCondition_initBehaviour() or self.errorCondition_initBehaviour() if stopBehaviourIteration or not self.auxiliaryFunctions.isSubsystemOK(): ''' Iterate within the while loop until stopBehaviourIteration is set true, i.e. one of error and terminal condition is fulfilled and isSubsystemOK is true. Otherwise subsystem must have been switched to another state or SIGINT was sent ''' break # Stops execution! # pass ##### Behaviour idleBehaviour ##### ##### Terminal condition ##### def terminalCondition_idleBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour idleBehaviour] -- Checking Terminal Condition") return checkCommand(self.taskCommand.data) and self.isNewCommandReceived.data>0 pass ##### Error condition ##### def errorCondition_idleBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour idleBehaviour] -- Checking Error Condition") return False pass ##### Transition function ##### def transitionFunction_idleBehaviour(self): self.log("[Behaviour idleBehaviour] -- Calculating Transition Function") # Transition function # self.log("TRANSITION FUNCTION - idleBehaviour consists of the following partial transition functions (decomposition based on output buffers)") # Partial transition function call: fun1 self.transitionFunction_idleBehaviour_fun1() # Partial transition function call: set_buffer_flags_function self.transitionFunction_idleBehaviour_set_buffer_flags_function() pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_idleBehaviour_fun1(self): self.log("[Behaviour idleBehaviour] -- Calculating Partial Transition Function fun1") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - idleBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if self._in_flag_taskCommand: self.transitionFunction_idleBehaviour_fun1_0() elif not (self._in_flag_taskCommand): self.transitionFunction_idleBehaviour_fun1_1() pass ##### Partial transition function: fun1_0 based on input buffers self._in_flag_taskCommand ##### def transitionFunction_idleBehaviour_fun1_0(self): self.log("[Behaviour idleBehaviour] -- Calculating Partial Transition Function fun1_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - idleBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code print("[CS - teleoperated] -- idleBehaviour - TRUE") self.isNewCommandReceived.data=1 # End - Partial Transition Function Code pass ##### Partial transition function: fun1_1 based on input buffers not (self._in_flag_taskCommand) ##### def transitionFunction_idleBehaviour_fun1_1(self): self.log("[Behaviour idleBehaviour] -- Calculating Partial Transition Function fun1_1") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - idleBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code print("[CS - teleoperated] -- idleBehaviour - FALSE") self.isNewCommandReceived.data=0 # End - Partial Transition Function Code pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_idleBehaviour_set_buffer_flags_function(self): self.log("[Behaviour idleBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - idleBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_idleBehaviour_set_buffer_flags_function_0() pass ##### Partial transition function: set_buffer_flags_function_0 based on input buffers True ##### def transitionFunction_idleBehaviour_set_buffer_flags_function_0(self): self.log("[Behaviour idleBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - idleBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code self._in_flag_taskCommand=False # End - Partial Transition Function Code pass ##### End of transition function ##### ##### Send data to other subsystems ##### def sendData_idleBehaviour(self): self.log("[Behaviour idleBehaviour] -- Sending Data") # DIAGNOSTICS SEND # self.sendDataForDiagnostics() # END OF DIAGNOSTICS SEND # # TYPICAL SEND CALL # # check if output buffer taskStatus has new data - i.e. is ready to send new data if( self._out_flag_taskStatus ): # send data from output buffer taskStatus # Buffer taskStatus - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_taskStatus.publish(self.taskStatus) # sending data from output buffer taskStatus # # indicate that data was sent and now the output buffer taskStatus is empty self._out_flag_taskStatus=False # check if output buffer desiredRobotCommandTele has new data - i.e. is ready to send new data if( self._out_flag_desiredRobotCommandTele ): # send data from output buffer desiredRobotCommandTele # Buffer desiredRobotCommandTele - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_desiredRobotCommandTele.publish(self.desiredRobotCommandTele) # sending data from output buffer desiredRobotCommandTele # # indicate that data was sent and now the output buffer desiredRobotCommandTele is empty self._out_flag_desiredRobotCommandTele=False # END OF TYPICAL SEND CALL # # BEGIN OF BODY SEND CALL # # END OF BODY SEND CALL # pass ##### Receive data from other subsystems ##### def receiveData_idleBehaviour(self): self.log("[Behaviour idleBehaviour] -- Receiving Data") # TYPICAL RECEIVE CALL # # Buffer taskCommand - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer taskCommand # Buffer ballInfoTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballInfoTele # Buffer obstacleDetectedTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer obstacleDetectedTele # Buffer ballCollected - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballCollected self.waitForAllMessages() # # END OF TYPICAL RECEIVE CALL # # BEGIN OF RECEIVE BODY CALL # # END OF RECEIVE BODY CALL # pass ##### Execute behaviour idleBehaviour ##### def executeBehaviour_idleBehaviour(self): self.log("[Behaviour idleBehaviour] -- Executing idleBehaviour Behaviour") stopBehaviourIteration=False # Execution of a single iteration of a behaviour idleBehaviour # _behaviourIterations=0 # Starts execution! # while True: # Sleep is a method from class AuxiliaryFunctions which executes sleep from ROS # self.auxiliaryFunctions.sleep() # Calculates transition function -- output and internal buffers can only be modified by this function! # self.transitionFunction_idleBehaviour() # Sends data! # self.sendData_idleBehaviour() # Updates index! -- i.e. i:i+1 -- increment number of behaviour iterations and number of subsystem iterations # self._behaviourIterations=self._behaviourIterations+1 # Receives data! # self.receiveData_idleBehaviour() # Check both conditions, i.e. terminal condition and error condition # stopBehaviourIteration = self.terminalCondition_idleBehaviour() or self.errorCondition_idleBehaviour() if stopBehaviourIteration or not self.auxiliaryFunctions.isSubsystemOK(): ''' Iterate within the while loop until stopBehaviourIteration is set true, i.e. one of error and terminal condition is fulfilled and isSubsystemOK is true. Otherwise subsystem must have been switched to another state or SIGINT was sent ''' break # Stops execution! # pass ##### Behaviour terminateBehaviour ##### ##### Terminal condition ##### def terminalCondition_terminateBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour terminateBehaviour] -- Checking Terminal Condition") return False pass ##### Error condition ##### def errorCondition_terminateBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour terminateBehaviour] -- Checking Error Condition") return False pass ##### Transition function ##### def transitionFunction_terminateBehaviour(self): self.log("[Behaviour terminateBehaviour] -- Calculating Transition Function") # Transition function # self.log("TRANSITION FUNCTION - terminateBehaviour consists of the following partial transition functions (decomposition based on output buffers)") # Partial transition function call: fun1 self.transitionFunction_terminateBehaviour_fun1() # Partial transition function call: set_buffer_flags_function self.transitionFunction_terminateBehaviour_set_buffer_flags_function() pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_terminateBehaviour_fun1(self): self.log("[Behaviour terminateBehaviour] -- Calculating Partial Transition Function fun1") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - terminateBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_terminateBehaviour_fun1_0() pass ##### Partial transition function: fun1_0 based on input buffers True ##### def transitionFunction_terminateBehaviour_fun1_0(self): self.log("[Behaviour terminateBehaviour] -- Calculating Partial Transition Function fun1_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - terminateBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code self._out_flag_taskStatus=True self._out_flag_desiredRobotCommandTele=True print("[CS - teleoperated] -- terminateBehaviour") if(self.taskStatus.data=="task terminated"): self._out_flag_taskStatus=False self._out_flag_desiredRobotCommandTele=False else: self.taskStatus.data="task terminated" self.desiredRobotCommandTele.data="terminate" # End - Partial Transition Function Code pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_terminateBehaviour_set_buffer_flags_function(self): self.log("[Behaviour terminateBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - terminateBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_terminateBehaviour_set_buffer_flags_function_0() pass ##### Partial transition function: set_buffer_flags_function_0 based on input buffers True ##### def transitionFunction_terminateBehaviour_set_buffer_flags_function_0(self): self.log("[Behaviour terminateBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - terminateBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code # End - Partial Transition Function Code pass ##### End of transition function ##### ##### Send data to other subsystems ##### def sendData_terminateBehaviour(self): self.log("[Behaviour terminateBehaviour] -- Sending Data") # DIAGNOSTICS SEND # self.sendDataForDiagnostics() # END OF DIAGNOSTICS SEND # # TYPICAL SEND CALL # # check if output buffer taskStatus has new data - i.e. is ready to send new data if( self._out_flag_taskStatus ): # send data from output buffer taskStatus # Buffer taskStatus - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_taskStatus.publish(self.taskStatus) # sending data from output buffer taskStatus # # indicate that data was sent and now the output buffer taskStatus is empty self._out_flag_taskStatus=False # check if output buffer desiredRobotCommandTele has new data - i.e. is ready to send new data if( self._out_flag_desiredRobotCommandTele ): # send data from output buffer desiredRobotCommandTele # Buffer desiredRobotCommandTele - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_desiredRobotCommandTele.publish(self.desiredRobotCommandTele) # sending data from output buffer desiredRobotCommandTele # # indicate that data was sent and now the output buffer desiredRobotCommandTele is empty self._out_flag_desiredRobotCommandTele=False # END OF TYPICAL SEND CALL # # BEGIN OF BODY SEND CALL # # END OF BODY SEND CALL # pass ##### Receive data from other subsystems ##### def receiveData_terminateBehaviour(self): self.log("[Behaviour terminateBehaviour] -- Receiving Data") # TYPICAL RECEIVE CALL # # Buffer taskCommand - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer taskCommand # Buffer ballInfoTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballInfoTele # Buffer obstacleDetectedTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer obstacleDetectedTele # Buffer ballCollected - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballCollected self.waitForAllMessages() # # END OF TYPICAL RECEIVE CALL # # BEGIN OF RECEIVE BODY CALL # # END OF RECEIVE BODY CALL # pass ##### Execute behaviour terminateBehaviour ##### def executeBehaviour_terminateBehaviour(self): self.log("[Behaviour terminateBehaviour] -- Executing terminateBehaviour Behaviour") stopBehaviourIteration=False # Execution of a single iteration of a behaviour terminateBehaviour # _behaviourIterations=0 # Starts execution! # while True: # Sleep is a method from class AuxiliaryFunctions which executes sleep from ROS # self.auxiliaryFunctions.sleep() # Calculates transition function -- output and internal buffers can only be modified by this function! # self.transitionFunction_terminateBehaviour() # Sends data! # self.sendData_terminateBehaviour() # Updates index! -- i.e. i:i+1 -- increment number of behaviour iterations and number of subsystem iterations # self._behaviourIterations=self._behaviourIterations+1 # Receives data! # self.receiveData_terminateBehaviour() # Check both conditions, i.e. terminal condition and error condition # stopBehaviourIteration = self.terminalCondition_terminateBehaviour() or self.errorCondition_terminateBehaviour() if stopBehaviourIteration or not self.auxiliaryFunctions.isSubsystemOK(): ''' Iterate within the while loop until stopBehaviourIteration is set true, i.e. one of error and terminal condition is fulfilled and isSubsystemOK is true. Otherwise subsystem must have been switched to another state or SIGINT was sent ''' break # Stops execution! # pass ##### Behaviour terminatedBehaviour ##### ##### Terminal condition ##### def terminalCondition_terminatedBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour terminatedBehaviour] -- Checking Terminal Condition") return False pass ##### Error condition ##### def errorCondition_terminatedBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour terminatedBehaviour] -- Checking Error Condition") return False pass ##### Transition function ##### def transitionFunction_terminatedBehaviour(self): self.log("[Behaviour terminatedBehaviour] -- Calculating Transition Function") # Transition function # self.log("TRANSITION FUNCTION - terminatedBehaviour consists of the following partial transition functions (decomposition based on output buffers)") # Partial transition function call: fun1 self.transitionFunction_terminatedBehaviour_fun1() # Partial transition function call: set_buffer_flags_function self.transitionFunction_terminatedBehaviour_set_buffer_flags_function() pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_terminatedBehaviour_fun1(self): self.log("[Behaviour terminatedBehaviour] -- Calculating Partial Transition Function fun1") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - terminatedBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_terminatedBehaviour_fun1_0() pass ##### Partial transition function: fun1_0 based on input buffers True ##### def transitionFunction_terminatedBehaviour_fun1_0(self): self.log("[Behaviour terminatedBehaviour] -- Calculating Partial Transition Function fun1_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - terminatedBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code print("[CS - teleoperated] -- terminatedBehaviour") # End - Partial Transition Function Code pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_terminatedBehaviour_set_buffer_flags_function(self): self.log("[Behaviour terminatedBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - terminatedBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_terminatedBehaviour_set_buffer_flags_function_0() pass ##### Partial transition function: set_buffer_flags_function_0 based on input buffers True ##### def transitionFunction_terminatedBehaviour_set_buffer_flags_function_0(self): self.log("[Behaviour terminatedBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - terminatedBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code # End - Partial Transition Function Code pass ##### End of transition function ##### ##### Send data to other subsystems ##### def sendData_terminatedBehaviour(self): self.log("[Behaviour terminatedBehaviour] -- Sending Data") # DIAGNOSTICS SEND # self.sendDataForDiagnostics() # END OF DIAGNOSTICS SEND # # TYPICAL SEND CALL # # check if output buffer taskStatus has new data - i.e. is ready to send new data if( self._out_flag_taskStatus ): # send data from output buffer taskStatus # Buffer taskStatus - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_taskStatus.publish(self.taskStatus) # sending data from output buffer taskStatus # # indicate that data was sent and now the output buffer taskStatus is empty self._out_flag_taskStatus=False # check if output buffer desiredRobotCommandTele has new data - i.e. is ready to send new data if( self._out_flag_desiredRobotCommandTele ): # send data from output buffer desiredRobotCommandTele # Buffer desiredRobotCommandTele - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_desiredRobotCommandTele.publish(self.desiredRobotCommandTele) # sending data from output buffer desiredRobotCommandTele # # indicate that data was sent and now the output buffer desiredRobotCommandTele is empty self._out_flag_desiredRobotCommandTele=False # END OF TYPICAL SEND CALL # # BEGIN OF BODY SEND CALL # # END OF BODY SEND CALL # pass ##### Receive data from other subsystems ##### def receiveData_terminatedBehaviour(self): self.log("[Behaviour terminatedBehaviour] -- Receiving Data") # TYPICAL RECEIVE CALL # # Buffer taskCommand - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer taskCommand # Buffer ballInfoTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballInfoTele # Buffer obstacleDetectedTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer obstacleDetectedTele # Buffer ballCollected - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballCollected self.waitForAllMessages() # # END OF TYPICAL RECEIVE CALL # # BEGIN OF RECEIVE BODY CALL # # END OF RECEIVE BODY CALL # pass ##### Execute behaviour terminatedBehaviour ##### def executeBehaviour_terminatedBehaviour(self): self.log("[Behaviour terminatedBehaviour] -- Executing terminatedBehaviour Behaviour") stopBehaviourIteration=False # Execution of a single iteration of a behaviour terminatedBehaviour # _behaviourIterations=0 # Starts execution! # while True: # Sleep is a method from class AuxiliaryFunctions which executes sleep from ROS # self.auxiliaryFunctions.sleep() # Calculates transition function -- output and internal buffers can only be modified by this function! # self.transitionFunction_terminatedBehaviour() # Sends data! # self.sendData_terminatedBehaviour() # Updates index! -- i.e. i:i+1 -- increment number of behaviour iterations and number of subsystem iterations # self._behaviourIterations=self._behaviourIterations+1 # Receives data! # self.receiveData_terminatedBehaviour() # Check both conditions, i.e. terminal condition and error condition # stopBehaviourIteration = self.terminalCondition_terminatedBehaviour() or self.errorCondition_terminatedBehaviour() if stopBehaviourIteration or not self.auxiliaryFunctions.isSubsystemOK(): ''' Iterate within the while loop until stopBehaviourIteration is set true, i.e. one of error and terminal condition is fulfilled and isSubsystemOK is true. Otherwise subsystem must have been switched to another state or SIGINT was sent ''' break # Stops execution! # pass ##### Behaviour stopBehaviour ##### ##### Terminal condition ##### def terminalCondition_stopBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour stopBehaviour] -- Checking Terminal Condition") return True pass ##### Error condition ##### def errorCondition_stopBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour stopBehaviour] -- Checking Error Condition") return False pass ##### Transition function ##### def transitionFunction_stopBehaviour(self): self.log("[Behaviour stopBehaviour] -- Calculating Transition Function") # Transition function # self.log("TRANSITION FUNCTION - stopBehaviour consists of the following partial transition functions (decomposition based on output buffers)") # Partial transition function call: fun1 self.transitionFunction_stopBehaviour_fun1() # Partial transition function call: set_buffer_flags_function self.transitionFunction_stopBehaviour_set_buffer_flags_function() pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_stopBehaviour_fun1(self): self.log("[Behaviour stopBehaviour] -- Calculating Partial Transition Function fun1") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - stopBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_stopBehaviour_fun1_0() pass ##### Partial transition function: fun1_0 based on input buffers True ##### def transitionFunction_stopBehaviour_fun1_0(self): self.log("[Behaviour stopBehaviour] -- Calculating Partial Transition Function fun1_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - stopBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code self._out_flag_taskStatus=True self._out_flag_desiredRobotCommandTele=True print("[CS - teleoperated] -- stopBehaviour") self.desiredRobotCommandTele.data="stop" self.taskStatus.data="task status: stop robot" # End - Partial Transition Function Code pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_stopBehaviour_set_buffer_flags_function(self): self.log("[Behaviour stopBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - stopBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_stopBehaviour_set_buffer_flags_function_0() pass ##### Partial transition function: set_buffer_flags_function_0 based on input buffers True ##### def transitionFunction_stopBehaviour_set_buffer_flags_function_0(self): self.log("[Behaviour stopBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - stopBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code # End - Partial Transition Function Code pass ##### End of transition function ##### ##### Send data to other subsystems ##### def sendData_stopBehaviour(self): self.log("[Behaviour stopBehaviour] -- Sending Data") # DIAGNOSTICS SEND # self.sendDataForDiagnostics() # END OF DIAGNOSTICS SEND # # TYPICAL SEND CALL # # check if output buffer taskStatus has new data - i.e. is ready to send new data if( self._out_flag_taskStatus ): # send data from output buffer taskStatus # Buffer taskStatus - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_taskStatus.publish(self.taskStatus) # sending data from output buffer taskStatus # # indicate that data was sent and now the output buffer taskStatus is empty self._out_flag_taskStatus=False # check if output buffer desiredRobotCommandTele has new data - i.e. is ready to send new data if( self._out_flag_desiredRobotCommandTele ): # send data from output buffer desiredRobotCommandTele # Buffer desiredRobotCommandTele - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_desiredRobotCommandTele.publish(self.desiredRobotCommandTele) # sending data from output buffer desiredRobotCommandTele # # indicate that data was sent and now the output buffer desiredRobotCommandTele is empty self._out_flag_desiredRobotCommandTele=False # END OF TYPICAL SEND CALL # # BEGIN OF BODY SEND CALL # # END OF BODY SEND CALL # pass ##### Receive data from other subsystems ##### def receiveData_stopBehaviour(self): self.log("[Behaviour stopBehaviour] -- Receiving Data") # TYPICAL RECEIVE CALL # # Buffer taskCommand - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer taskCommand # Buffer ballInfoTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballInfoTele # Buffer obstacleDetectedTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer obstacleDetectedTele # Buffer ballCollected - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballCollected self.waitForAllMessages() # # END OF TYPICAL RECEIVE CALL # # BEGIN OF RECEIVE BODY CALL # # END OF RECEIVE BODY CALL # pass ##### Execute behaviour stopBehaviour ##### def executeBehaviour_stopBehaviour(self): self.log("[Behaviour stopBehaviour] -- Executing stopBehaviour Behaviour") stopBehaviourIteration=False # Execution of a single iteration of a behaviour stopBehaviour # _behaviourIterations=0 # Starts execution! # while True: # Sleep is a method from class AuxiliaryFunctions which executes sleep from ROS # self.auxiliaryFunctions.sleep() # Calculates transition function -- output and internal buffers can only be modified by this function! # self.transitionFunction_stopBehaviour() # Sends data! # self.sendData_stopBehaviour() # Updates index! -- i.e. i:i+1 -- increment number of behaviour iterations and number of subsystem iterations # self._behaviourIterations=self._behaviourIterations+1 # Receives data! # self.receiveData_stopBehaviour() # Check both conditions, i.e. terminal condition and error condition # stopBehaviourIteration = self.terminalCondition_stopBehaviour() or self.errorCondition_stopBehaviour() if stopBehaviourIteration or not self.auxiliaryFunctions.isSubsystemOK(): ''' Iterate within the while loop until stopBehaviourIteration is set true, i.e. one of error and terminal condition is fulfilled and isSubsystemOK is true. Otherwise subsystem must have been switched to another state or SIGINT was sent ''' break # Stops execution! # pass ##### Behaviour moveFasterBehaviour ##### ##### Terminal condition ##### def terminalCondition_moveFasterBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour moveFasterBehaviour] -- Checking Terminal Condition") return True pass ##### Error condition ##### def errorCondition_moveFasterBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour moveFasterBehaviour] -- Checking Error Condition") return False pass ##### Transition function ##### def transitionFunction_moveFasterBehaviour(self): self.log("[Behaviour moveFasterBehaviour] -- Calculating Transition Function") # Transition function # self.log("TRANSITION FUNCTION - moveFasterBehaviour consists of the following partial transition functions (decomposition based on output buffers)") # Partial transition function call: fun1 self.transitionFunction_moveFasterBehaviour_fun1() # Partial transition function call: set_buffer_flags_function self.transitionFunction_moveFasterBehaviour_set_buffer_flags_function() pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_moveFasterBehaviour_fun1(self): self.log("[Behaviour moveFasterBehaviour] -- Calculating Partial Transition Function fun1") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - moveFasterBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_moveFasterBehaviour_fun1_0() pass ##### Partial transition function: fun1_0 based on input buffers True ##### def transitionFunction_moveFasterBehaviour_fun1_0(self): self.log("[Behaviour moveFasterBehaviour] -- Calculating Partial Transition Function fun1_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - moveFasterBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code self._out_flag_taskStatus=True self._out_flag_desiredRobotCommandTele=True print("[CS - teleoperated] -- moveFasterBehaviour") self.desiredRobotCommandTele.data="move faster" self.taskStatus.data="task status: move faster" # End - Partial Transition Function Code pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_moveFasterBehaviour_set_buffer_flags_function(self): self.log("[Behaviour moveFasterBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - moveFasterBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_moveFasterBehaviour_set_buffer_flags_function_0() pass ##### Partial transition function: set_buffer_flags_function_0 based on input buffers True ##### def transitionFunction_moveFasterBehaviour_set_buffer_flags_function_0(self): self.log("[Behaviour moveFasterBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - moveFasterBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code # End - Partial Transition Function Code pass ##### End of transition function ##### ##### Send data to other subsystems ##### def sendData_moveFasterBehaviour(self): self.log("[Behaviour moveFasterBehaviour] -- Sending Data") # DIAGNOSTICS SEND # self.sendDataForDiagnostics() # END OF DIAGNOSTICS SEND # # TYPICAL SEND CALL # # check if output buffer taskStatus has new data - i.e. is ready to send new data if( self._out_flag_taskStatus ): # send data from output buffer taskStatus # Buffer taskStatus - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_taskStatus.publish(self.taskStatus) # sending data from output buffer taskStatus # # indicate that data was sent and now the output buffer taskStatus is empty self._out_flag_taskStatus=False # check if output buffer desiredRobotCommandTele has new data - i.e. is ready to send new data if( self._out_flag_desiredRobotCommandTele ): # send data from output buffer desiredRobotCommandTele # Buffer desiredRobotCommandTele - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_desiredRobotCommandTele.publish(self.desiredRobotCommandTele) # sending data from output buffer desiredRobotCommandTele # # indicate that data was sent and now the output buffer desiredRobotCommandTele is empty self._out_flag_desiredRobotCommandTele=False # END OF TYPICAL SEND CALL # # BEGIN OF BODY SEND CALL # # END OF BODY SEND CALL # pass ##### Receive data from other subsystems ##### def receiveData_moveFasterBehaviour(self): self.log("[Behaviour moveFasterBehaviour] -- Receiving Data") # TYPICAL RECEIVE CALL # # Buffer taskCommand - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer taskCommand # Buffer ballInfoTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballInfoTele # Buffer obstacleDetectedTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer obstacleDetectedTele # Buffer ballCollected - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballCollected self.waitForAllMessages() # # END OF TYPICAL RECEIVE CALL # # BEGIN OF RECEIVE BODY CALL # # END OF RECEIVE BODY CALL # pass ##### Execute behaviour moveFasterBehaviour ##### def executeBehaviour_moveFasterBehaviour(self): self.log("[Behaviour moveFasterBehaviour] -- Executing moveFasterBehaviour Behaviour") stopBehaviourIteration=False # Execution of a single iteration of a behaviour moveFasterBehaviour # _behaviourIterations=0 # Starts execution! # while True: # Sleep is a method from class AuxiliaryFunctions which executes sleep from ROS # self.auxiliaryFunctions.sleep() # Calculates transition function -- output and internal buffers can only be modified by this function! # self.transitionFunction_moveFasterBehaviour() # Sends data! # self.sendData_moveFasterBehaviour() # Updates index! -- i.e. i:i+1 -- increment number of behaviour iterations and number of subsystem iterations # self._behaviourIterations=self._behaviourIterations+1 # Receives data! # self.receiveData_moveFasterBehaviour() # Check both conditions, i.e. terminal condition and error condition # stopBehaviourIteration = self.terminalCondition_moveFasterBehaviour() or self.errorCondition_moveFasterBehaviour() if stopBehaviourIteration or not self.auxiliaryFunctions.isSubsystemOK(): ''' Iterate within the while loop until stopBehaviourIteration is set true, i.e. one of error and terminal condition is fulfilled and isSubsystemOK is true. Otherwise subsystem must have been switched to another state or SIGINT was sent ''' break # Stops execution! # pass ##### Behaviour moveSlowerBehaviour ##### ##### Terminal condition ##### def terminalCondition_moveSlowerBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour moveSlowerBehaviour] -- Checking Terminal Condition") return True pass ##### Error condition ##### def errorCondition_moveSlowerBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour moveSlowerBehaviour] -- Checking Error Condition") return False pass ##### Transition function ##### def transitionFunction_moveSlowerBehaviour(self): self.log("[Behaviour moveSlowerBehaviour] -- Calculating Transition Function") # Transition function # self.log("TRANSITION FUNCTION - moveSlowerBehaviour consists of the following partial transition functions (decomposition based on output buffers)") # Partial transition function call: fun1 self.transitionFunction_moveSlowerBehaviour_fun1() # Partial transition function call: set_buffer_flags_function self.transitionFunction_moveSlowerBehaviour_set_buffer_flags_function() pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_moveSlowerBehaviour_fun1(self): self.log("[Behaviour moveSlowerBehaviour] -- Calculating Partial Transition Function fun1") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - moveSlowerBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_moveSlowerBehaviour_fun1_0() pass ##### Partial transition function: fun1_0 based on input buffers True ##### def transitionFunction_moveSlowerBehaviour_fun1_0(self): self.log("[Behaviour moveSlowerBehaviour] -- Calculating Partial Transition Function fun1_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - moveSlowerBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code self._out_flag_taskStatus=True self._out_flag_desiredRobotCommandTele=True print("[CS - teleoperated] -- moveSlowerBehaviour") self.desiredRobotCommandTele.data="move slower" self.taskStatus.data="task status: move slower" # End - Partial Transition Function Code pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_moveSlowerBehaviour_set_buffer_flags_function(self): self.log("[Behaviour moveSlowerBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - moveSlowerBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_moveSlowerBehaviour_set_buffer_flags_function_0() pass ##### Partial transition function: set_buffer_flags_function_0 based on input buffers True ##### def transitionFunction_moveSlowerBehaviour_set_buffer_flags_function_0(self): self.log("[Behaviour moveSlowerBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - moveSlowerBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code # End - Partial Transition Function Code pass ##### End of transition function ##### ##### Send data to other subsystems ##### def sendData_moveSlowerBehaviour(self): self.log("[Behaviour moveSlowerBehaviour] -- Sending Data") # DIAGNOSTICS SEND # self.sendDataForDiagnostics() # END OF DIAGNOSTICS SEND # # TYPICAL SEND CALL # # check if output buffer taskStatus has new data - i.e. is ready to send new data if( self._out_flag_taskStatus ): # send data from output buffer taskStatus # Buffer taskStatus - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_taskStatus.publish(self.taskStatus) # sending data from output buffer taskStatus # # indicate that data was sent and now the output buffer taskStatus is empty self._out_flag_taskStatus=False # check if output buffer desiredRobotCommandTele has new data - i.e. is ready to send new data if( self._out_flag_desiredRobotCommandTele ): # send data from output buffer desiredRobotCommandTele # Buffer desiredRobotCommandTele - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_desiredRobotCommandTele.publish(self.desiredRobotCommandTele) # sending data from output buffer desiredRobotCommandTele # # indicate that data was sent and now the output buffer desiredRobotCommandTele is empty self._out_flag_desiredRobotCommandTele=False # END OF TYPICAL SEND CALL # # BEGIN OF BODY SEND CALL # # END OF BODY SEND CALL # pass ##### Receive data from other subsystems ##### def receiveData_moveSlowerBehaviour(self): self.log("[Behaviour moveSlowerBehaviour] -- Receiving Data") # TYPICAL RECEIVE CALL # # Buffer taskCommand - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer taskCommand # Buffer ballInfoTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballInfoTele # Buffer obstacleDetectedTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer obstacleDetectedTele # Buffer ballCollected - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballCollected self.waitForAllMessages() # # END OF TYPICAL RECEIVE CALL # # BEGIN OF RECEIVE BODY CALL # # END OF RECEIVE BODY CALL # pass ##### Execute behaviour moveSlowerBehaviour ##### def executeBehaviour_moveSlowerBehaviour(self): self.log("[Behaviour moveSlowerBehaviour] -- Executing moveSlowerBehaviour Behaviour") stopBehaviourIteration=False # Execution of a single iteration of a behaviour moveSlowerBehaviour # _behaviourIterations=0 # Starts execution! # while True: # Sleep is a method from class AuxiliaryFunctions which executes sleep from ROS # self.auxiliaryFunctions.sleep() # Calculates transition function -- output and internal buffers can only be modified by this function! # self.transitionFunction_moveSlowerBehaviour() # Sends data! # self.sendData_moveSlowerBehaviour() # Updates index! -- i.e. i:i+1 -- increment number of behaviour iterations and number of subsystem iterations # self._behaviourIterations=self._behaviourIterations+1 # Receives data! # self.receiveData_moveSlowerBehaviour() # Check both conditions, i.e. terminal condition and error condition # stopBehaviourIteration = self.terminalCondition_moveSlowerBehaviour() or self.errorCondition_moveSlowerBehaviour() if stopBehaviourIteration or not self.auxiliaryFunctions.isSubsystemOK(): ''' Iterate within the while loop until stopBehaviourIteration is set true, i.e. one of error and terminal condition is fulfilled and isSubsystemOK is true. Otherwise subsystem must have been switched to another state or SIGINT was sent ''' break # Stops execution! # pass ##### Behaviour vacuumOnBehaviour ##### ##### Terminal condition ##### def terminalCondition_vacuumOnBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour vacuumOnBehaviour] -- Checking Terminal Condition") return True pass ##### Error condition ##### def errorCondition_vacuumOnBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour vacuumOnBehaviour] -- Checking Error Condition") return False pass ##### Transition function ##### def transitionFunction_vacuumOnBehaviour(self): self.log("[Behaviour vacuumOnBehaviour] -- Calculating Transition Function") # Transition function # self.log("TRANSITION FUNCTION - vacuumOnBehaviour consists of the following partial transition functions (decomposition based on output buffers)") # Partial transition function call: fun1 self.transitionFunction_vacuumOnBehaviour_fun1() # Partial transition function call: set_buffer_flags_function self.transitionFunction_vacuumOnBehaviour_set_buffer_flags_function() pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_vacuumOnBehaviour_fun1(self): self.log("[Behaviour vacuumOnBehaviour] -- Calculating Partial Transition Function fun1") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - vacuumOnBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_vacuumOnBehaviour_fun1_0() pass ##### Partial transition function: fun1_0 based on input buffers True ##### def transitionFunction_vacuumOnBehaviour_fun1_0(self): self.log("[Behaviour vacuumOnBehaviour] -- Calculating Partial Transition Function fun1_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - vacuumOnBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code self._out_flag_taskStatus=True self._out_flag_desiredRobotCommandTele=True print("[CS - teleoperated] -- vacuumOnBehaviour") self.desiredRobotCommandTele.data="vacuum turn on" self.taskStatus.data="task status: vacuum turn on" # End - Partial Transition Function Code pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_vacuumOnBehaviour_set_buffer_flags_function(self): self.log("[Behaviour vacuumOnBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - vacuumOnBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_vacuumOnBehaviour_set_buffer_flags_function_0() pass ##### Partial transition function: set_buffer_flags_function_0 based on input buffers True ##### def transitionFunction_vacuumOnBehaviour_set_buffer_flags_function_0(self): self.log("[Behaviour vacuumOnBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - vacuumOnBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code # End - Partial Transition Function Code pass ##### End of transition function ##### ##### Send data to other subsystems ##### def sendData_vacuumOnBehaviour(self): self.log("[Behaviour vacuumOnBehaviour] -- Sending Data") # DIAGNOSTICS SEND # self.sendDataForDiagnostics() # END OF DIAGNOSTICS SEND # # TYPICAL SEND CALL # # check if output buffer taskStatus has new data - i.e. is ready to send new data if( self._out_flag_taskStatus ): # send data from output buffer taskStatus # Buffer taskStatus - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_taskStatus.publish(self.taskStatus) # sending data from output buffer taskStatus # # indicate that data was sent and now the output buffer taskStatus is empty self._out_flag_taskStatus=False # check if output buffer desiredRobotCommandTele has new data - i.e. is ready to send new data if( self._out_flag_desiredRobotCommandTele ): # send data from output buffer desiredRobotCommandTele # Buffer desiredRobotCommandTele - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_desiredRobotCommandTele.publish(self.desiredRobotCommandTele) # sending data from output buffer desiredRobotCommandTele # # indicate that data was sent and now the output buffer desiredRobotCommandTele is empty self._out_flag_desiredRobotCommandTele=False # END OF TYPICAL SEND CALL # # BEGIN OF BODY SEND CALL # # END OF BODY SEND CALL # pass ##### Receive data from other subsystems ##### def receiveData_vacuumOnBehaviour(self): self.log("[Behaviour vacuumOnBehaviour] -- Receiving Data") # TYPICAL RECEIVE CALL # # Buffer taskCommand - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer taskCommand # Buffer ballInfoTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballInfoTele # Buffer obstacleDetectedTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer obstacleDetectedTele # Buffer ballCollected - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballCollected self.waitForAllMessages() # # END OF TYPICAL RECEIVE CALL # # BEGIN OF RECEIVE BODY CALL # # END OF RECEIVE BODY CALL # pass ##### Execute behaviour vacuumOnBehaviour ##### def executeBehaviour_vacuumOnBehaviour(self): self.log("[Behaviour vacuumOnBehaviour] -- Executing vacuumOnBehaviour Behaviour") stopBehaviourIteration=False # Execution of a single iteration of a behaviour vacuumOnBehaviour # _behaviourIterations=0 # Starts execution! # while True: # Sleep is a method from class AuxiliaryFunctions which executes sleep from ROS # self.auxiliaryFunctions.sleep() # Calculates transition function -- output and internal buffers can only be modified by this function! # self.transitionFunction_vacuumOnBehaviour() # Sends data! # self.sendData_vacuumOnBehaviour() # Updates index! -- i.e. i:i+1 -- increment number of behaviour iterations and number of subsystem iterations # self._behaviourIterations=self._behaviourIterations+1 # Receives data! # self.receiveData_vacuumOnBehaviour() # Check both conditions, i.e. terminal condition and error condition # stopBehaviourIteration = self.terminalCondition_vacuumOnBehaviour() or self.errorCondition_vacuumOnBehaviour() if stopBehaviourIteration or not self.auxiliaryFunctions.isSubsystemOK(): ''' Iterate within the while loop until stopBehaviourIteration is set true, i.e. one of error and terminal condition is fulfilled and isSubsystemOK is true. Otherwise subsystem must have been switched to another state or SIGINT was sent ''' break # Stops execution! # pass ##### Behaviour vacuumOffBehaviour ##### ##### Terminal condition ##### def terminalCondition_vacuumOffBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour vacuumOffBehaviour] -- Checking Terminal Condition") return True pass ##### Error condition ##### def errorCondition_vacuumOffBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour vacuumOffBehaviour] -- Checking Error Condition") return False pass ##### Transition function ##### def transitionFunction_vacuumOffBehaviour(self): self.log("[Behaviour vacuumOffBehaviour] -- Calculating Transition Function") # Transition function # self.log("TRANSITION FUNCTION - vacuumOffBehaviour consists of the following partial transition functions (decomposition based on output buffers)") # Partial transition function call: fun1 self.transitionFunction_vacuumOffBehaviour_fun1() # Partial transition function call: set_buffer_flags_function self.transitionFunction_vacuumOffBehaviour_set_buffer_flags_function() pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_vacuumOffBehaviour_fun1(self): self.log("[Behaviour vacuumOffBehaviour] -- Calculating Partial Transition Function fun1") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - vacuumOffBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_vacuumOffBehaviour_fun1_0() pass ##### Partial transition function: fun1_0 based on input buffers True ##### def transitionFunction_vacuumOffBehaviour_fun1_0(self): self.log("[Behaviour vacuumOffBehaviour] -- Calculating Partial Transition Function fun1_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - vacuumOffBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code self._out_flag_taskStatus=True self._out_flag_desiredRobotCommandTele=True print("[CS - teleoperated] -- vacuumOffBehaviour") self.desiredRobotCommandTele.data="vacuum off" self.taskStatus.data="task status: vacuum off" # End - Partial Transition Function Code pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_vacuumOffBehaviour_set_buffer_flags_function(self): self.log("[Behaviour vacuumOffBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - vacuumOffBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_vacuumOffBehaviour_set_buffer_flags_function_0() pass ##### Partial transition function: set_buffer_flags_function_0 based on input buffers True ##### def transitionFunction_vacuumOffBehaviour_set_buffer_flags_function_0(self): self.log("[Behaviour vacuumOffBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - vacuumOffBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code # End - Partial Transition Function Code pass ##### End of transition function ##### ##### Send data to other subsystems ##### def sendData_vacuumOffBehaviour(self): self.log("[Behaviour vacuumOffBehaviour] -- Sending Data") # DIAGNOSTICS SEND # self.sendDataForDiagnostics() # END OF DIAGNOSTICS SEND # # TYPICAL SEND CALL # # check if output buffer taskStatus has new data - i.e. is ready to send new data if( self._out_flag_taskStatus ): # send data from output buffer taskStatus # Buffer taskStatus - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_taskStatus.publish(self.taskStatus) # sending data from output buffer taskStatus # # indicate that data was sent and now the output buffer taskStatus is empty self._out_flag_taskStatus=False # check if output buffer desiredRobotCommandTele has new data - i.e. is ready to send new data if( self._out_flag_desiredRobotCommandTele ): # send data from output buffer desiredRobotCommandTele # Buffer desiredRobotCommandTele - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_desiredRobotCommandTele.publish(self.desiredRobotCommandTele) # sending data from output buffer desiredRobotCommandTele # # indicate that data was sent and now the output buffer desiredRobotCommandTele is empty self._out_flag_desiredRobotCommandTele=False # END OF TYPICAL SEND CALL # # BEGIN OF BODY SEND CALL # # END OF BODY SEND CALL # pass ##### Receive data from other subsystems ##### def receiveData_vacuumOffBehaviour(self): self.log("[Behaviour vacuumOffBehaviour] -- Receiving Data") # TYPICAL RECEIVE CALL # # Buffer taskCommand - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer taskCommand # Buffer ballInfoTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballInfoTele # Buffer obstacleDetectedTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer obstacleDetectedTele # Buffer ballCollected - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballCollected self.waitForAllMessages() # # END OF TYPICAL RECEIVE CALL # # BEGIN OF RECEIVE BODY CALL # # END OF RECEIVE BODY CALL # pass ##### Execute behaviour vacuumOffBehaviour ##### def executeBehaviour_vacuumOffBehaviour(self): self.log("[Behaviour vacuumOffBehaviour] -- Executing vacuumOffBehaviour Behaviour") stopBehaviourIteration=False # Execution of a single iteration of a behaviour vacuumOffBehaviour # _behaviourIterations=0 # Starts execution! # while True: # Sleep is a method from class AuxiliaryFunctions which executes sleep from ROS # self.auxiliaryFunctions.sleep() # Calculates transition function -- output and internal buffers can only be modified by this function! # self.transitionFunction_vacuumOffBehaviour() # Sends data! # self.sendData_vacuumOffBehaviour() # Updates index! -- i.e. i:i+1 -- increment number of behaviour iterations and number of subsystem iterations # self._behaviourIterations=self._behaviourIterations+1 # Receives data! # self.receiveData_vacuumOffBehaviour() # Check both conditions, i.e. terminal condition and error condition # stopBehaviourIteration = self.terminalCondition_vacuumOffBehaviour() or self.errorCondition_vacuumOffBehaviour() if stopBehaviourIteration or not self.auxiliaryFunctions.isSubsystemOK(): ''' Iterate within the while loop until stopBehaviourIteration is set true, i.e. one of error and terminal condition is fulfilled and isSubsystemOK is true. Otherwise subsystem must have been switched to another state or SIGINT was sent ''' break # Stops execution! # pass ##### Behaviour moveBackwardBehaviour ##### ##### Terminal condition ##### def terminalCondition_moveBackwardBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour moveBackwardBehaviour] -- Checking Terminal Condition") return True pass ##### Error condition ##### def errorCondition_moveBackwardBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour moveBackwardBehaviour] -- Checking Error Condition") return False pass ##### Transition function ##### def transitionFunction_moveBackwardBehaviour(self): self.log("[Behaviour moveBackwardBehaviour] -- Calculating Transition Function") # Transition function # self.log("TRANSITION FUNCTION - moveBackwardBehaviour consists of the following partial transition functions (decomposition based on output buffers)") # Partial transition function call: fun1 self.transitionFunction_moveBackwardBehaviour_fun1() # Partial transition function call: set_buffer_flags_function self.transitionFunction_moveBackwardBehaviour_set_buffer_flags_function() pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_moveBackwardBehaviour_fun1(self): self.log("[Behaviour moveBackwardBehaviour] -- Calculating Partial Transition Function fun1") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - moveBackwardBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_moveBackwardBehaviour_fun1_0() pass ##### Partial transition function: fun1_0 based on input buffers True ##### def transitionFunction_moveBackwardBehaviour_fun1_0(self): self.log("[Behaviour moveBackwardBehaviour] -- Calculating Partial Transition Function fun1_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - moveBackwardBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code self._out_flag_taskStatus=True self._out_flag_desiredRobotCommandTele=True print("[CS - teleoperated] -- moveBackwardBehaviour") self.desiredRobotCommandTele.data="move backwards" self.taskStatus.data="task status: move backwards" # End - Partial Transition Function Code pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_moveBackwardBehaviour_set_buffer_flags_function(self): self.log("[Behaviour moveBackwardBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - moveBackwardBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_moveBackwardBehaviour_set_buffer_flags_function_0() pass ##### Partial transition function: set_buffer_flags_function_0 based on input buffers True ##### def transitionFunction_moveBackwardBehaviour_set_buffer_flags_function_0(self): self.log("[Behaviour moveBackwardBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - moveBackwardBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code # End - Partial Transition Function Code pass ##### End of transition function ##### ##### Send data to other subsystems ##### def sendData_moveBackwardBehaviour(self): self.log("[Behaviour moveBackwardBehaviour] -- Sending Data") # DIAGNOSTICS SEND # self.sendDataForDiagnostics() # END OF DIAGNOSTICS SEND # # TYPICAL SEND CALL # # check if output buffer taskStatus has new data - i.e. is ready to send new data if( self._out_flag_taskStatus ): # send data from output buffer taskStatus # Buffer taskStatus - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_taskStatus.publish(self.taskStatus) # sending data from output buffer taskStatus # # indicate that data was sent and now the output buffer taskStatus is empty self._out_flag_taskStatus=False # check if output buffer desiredRobotCommandTele has new data - i.e. is ready to send new data if( self._out_flag_desiredRobotCommandTele ): # send data from output buffer desiredRobotCommandTele # Buffer desiredRobotCommandTele - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_desiredRobotCommandTele.publish(self.desiredRobotCommandTele) # sending data from output buffer desiredRobotCommandTele # # indicate that data was sent and now the output buffer desiredRobotCommandTele is empty self._out_flag_desiredRobotCommandTele=False # END OF TYPICAL SEND CALL # # BEGIN OF BODY SEND CALL # # END OF BODY SEND CALL # pass ##### Receive data from other subsystems ##### def receiveData_moveBackwardBehaviour(self): self.log("[Behaviour moveBackwardBehaviour] -- Receiving Data") # TYPICAL RECEIVE CALL # # Buffer taskCommand - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer taskCommand # Buffer ballInfoTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballInfoTele # Buffer obstacleDetectedTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer obstacleDetectedTele # Buffer ballCollected - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballCollected self.waitForAllMessages() # # END OF TYPICAL RECEIVE CALL # # BEGIN OF RECEIVE BODY CALL # # END OF RECEIVE BODY CALL # pass ##### Execute behaviour moveBackwardBehaviour ##### def executeBehaviour_moveBackwardBehaviour(self): self.log("[Behaviour moveBackwardBehaviour] -- Executing moveBackwardBehaviour Behaviour") stopBehaviourIteration=False # Execution of a single iteration of a behaviour moveBackwardBehaviour # _behaviourIterations=0 # Starts execution! # while True: # Sleep is a method from class AuxiliaryFunctions which executes sleep from ROS # self.auxiliaryFunctions.sleep() # Calculates transition function -- output and internal buffers can only be modified by this function! # self.transitionFunction_moveBackwardBehaviour() # Sends data! # self.sendData_moveBackwardBehaviour() # Updates index! -- i.e. i:i+1 -- increment number of behaviour iterations and number of subsystem iterations # self._behaviourIterations=self._behaviourIterations+1 # Receives data! # self.receiveData_moveBackwardBehaviour() # Check both conditions, i.e. terminal condition and error condition # stopBehaviourIteration = self.terminalCondition_moveBackwardBehaviour() or self.errorCondition_moveBackwardBehaviour() if stopBehaviourIteration or not self.auxiliaryFunctions.isSubsystemOK(): ''' Iterate within the while loop until stopBehaviourIteration is set true, i.e. one of error and terminal condition is fulfilled and isSubsystemOK is true. Otherwise subsystem must have been switched to another state or SIGINT was sent ''' break # Stops execution! # pass ##### Behaviour moveFrontBehaviour ##### ##### Terminal condition ##### def terminalCondition_moveFrontBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour moveFrontBehaviour] -- Checking Terminal Condition") return True pass ##### Error condition ##### def errorCondition_moveFrontBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour moveFrontBehaviour] -- Checking Error Condition") return False pass ##### Transition function ##### def transitionFunction_moveFrontBehaviour(self): self.log("[Behaviour moveFrontBehaviour] -- Calculating Transition Function") # Transition function # self.log("TRANSITION FUNCTION - moveFrontBehaviour consists of the following partial transition functions (decomposition based on output buffers)") # Partial transition function call: fun1 self.transitionFunction_moveFrontBehaviour_fun1() # Partial transition function call: set_buffer_flags_function self.transitionFunction_moveFrontBehaviour_set_buffer_flags_function() pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_moveFrontBehaviour_fun1(self): self.log("[Behaviour moveFrontBehaviour] -- Calculating Partial Transition Function fun1") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - moveFrontBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_moveFrontBehaviour_fun1_0() pass ##### Partial transition function: fun1_0 based on input buffers True ##### def transitionFunction_moveFrontBehaviour_fun1_0(self): self.log("[Behaviour moveFrontBehaviour] -- Calculating Partial Transition Function fun1_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - moveFrontBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code self._out_flag_taskStatus=True self._out_flag_desiredRobotCommandTele=True print("[CS - teleoperated] -- moveFrontBehaviour") self.desiredRobotCommandTele.data="move front" self.taskStatus.data="task status: move front" # End - Partial Transition Function Code pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_moveFrontBehaviour_set_buffer_flags_function(self): self.log("[Behaviour moveFrontBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - moveFrontBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_moveFrontBehaviour_set_buffer_flags_function_0() pass ##### Partial transition function: set_buffer_flags_function_0 based on input buffers True ##### def transitionFunction_moveFrontBehaviour_set_buffer_flags_function_0(self): self.log("[Behaviour moveFrontBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - moveFrontBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code # End - Partial Transition Function Code pass ##### End of transition function ##### ##### Send data to other subsystems ##### def sendData_moveFrontBehaviour(self): self.log("[Behaviour moveFrontBehaviour] -- Sending Data") # DIAGNOSTICS SEND # self.sendDataForDiagnostics() # END OF DIAGNOSTICS SEND # # TYPICAL SEND CALL # # check if output buffer taskStatus has new data - i.e. is ready to send new data if( self._out_flag_taskStatus ): # send data from output buffer taskStatus # Buffer taskStatus - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_taskStatus.publish(self.taskStatus) # sending data from output buffer taskStatus # # indicate that data was sent and now the output buffer taskStatus is empty self._out_flag_taskStatus=False # check if output buffer desiredRobotCommandTele has new data - i.e. is ready to send new data if( self._out_flag_desiredRobotCommandTele ): # send data from output buffer desiredRobotCommandTele # Buffer desiredRobotCommandTele - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_desiredRobotCommandTele.publish(self.desiredRobotCommandTele) # sending data from output buffer desiredRobotCommandTele # # indicate that data was sent and now the output buffer desiredRobotCommandTele is empty self._out_flag_desiredRobotCommandTele=False # END OF TYPICAL SEND CALL # # BEGIN OF BODY SEND CALL # # END OF BODY SEND CALL # pass ##### Receive data from other subsystems ##### def receiveData_moveFrontBehaviour(self): self.log("[Behaviour moveFrontBehaviour] -- Receiving Data") # TYPICAL RECEIVE CALL # # Buffer taskCommand - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer taskCommand # Buffer ballInfoTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballInfoTele # Buffer obstacleDetectedTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer obstacleDetectedTele # Buffer ballCollected - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballCollected self.waitForAllMessages() # # END OF TYPICAL RECEIVE CALL # # BEGIN OF RECEIVE BODY CALL # # END OF RECEIVE BODY CALL # pass ##### Execute behaviour moveFrontBehaviour ##### def executeBehaviour_moveFrontBehaviour(self): self.log("[Behaviour moveFrontBehaviour] -- Executing moveFrontBehaviour Behaviour") stopBehaviourIteration=False # Execution of a single iteration of a behaviour moveFrontBehaviour # _behaviourIterations=0 # Starts execution! # while True: # Sleep is a method from class AuxiliaryFunctions which executes sleep from ROS # self.auxiliaryFunctions.sleep() # Calculates transition function -- output and internal buffers can only be modified by this function! # self.transitionFunction_moveFrontBehaviour() # Sends data! # self.sendData_moveFrontBehaviour() # Updates index! -- i.e. i:i+1 -- increment number of behaviour iterations and number of subsystem iterations # self._behaviourIterations=self._behaviourIterations+1 # Receives data! # self.receiveData_moveFrontBehaviour() # Check both conditions, i.e. terminal condition and error condition # stopBehaviourIteration = self.terminalCondition_moveFrontBehaviour() or self.errorCondition_moveFrontBehaviour() if stopBehaviourIteration or not self.auxiliaryFunctions.isSubsystemOK(): ''' Iterate within the while loop until stopBehaviourIteration is set true, i.e. one of error and terminal condition is fulfilled and isSubsystemOK is true. Otherwise subsystem must have been switched to another state or SIGINT was sent ''' break # Stops execution! # pass ##### Behaviour moveRightBehaviour ##### ##### Terminal condition ##### def terminalCondition_moveRightBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour moveRightBehaviour] -- Checking Terminal Condition") return True pass ##### Error condition ##### def errorCondition_moveRightBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour moveRightBehaviour] -- Checking Error Condition") return False pass ##### Transition function ##### def transitionFunction_moveRightBehaviour(self): self.log("[Behaviour moveRightBehaviour] -- Calculating Transition Function") # Transition function # self.log("TRANSITION FUNCTION - moveRightBehaviour consists of the following partial transition functions (decomposition based on output buffers)") # Partial transition function call: fun1 self.transitionFunction_moveRightBehaviour_fun1() # Partial transition function call: set_buffer_flags_function self.transitionFunction_moveRightBehaviour_set_buffer_flags_function() pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_moveRightBehaviour_fun1(self): self.log("[Behaviour moveRightBehaviour] -- Calculating Partial Transition Function fun1") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - moveRightBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_moveRightBehaviour_fun1_0() pass ##### Partial transition function: fun1_0 based on input buffers True ##### def transitionFunction_moveRightBehaviour_fun1_0(self): self.log("[Behaviour moveRightBehaviour] -- Calculating Partial Transition Function fun1_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - moveRightBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code self._out_flag_desiredRobotCommandTele=True self._out_flag_taskStatus=True print("[CS - teleoperated] -- moveRightBehaviour") self.desiredRobotCommandTele.data="move right" self.taskStatus.data="task status: move right" # End - Partial Transition Function Code pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_moveRightBehaviour_set_buffer_flags_function(self): self.log("[Behaviour moveRightBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - moveRightBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_moveRightBehaviour_set_buffer_flags_function_0() pass ##### Partial transition function: set_buffer_flags_function_0 based on input buffers True ##### def transitionFunction_moveRightBehaviour_set_buffer_flags_function_0(self): self.log("[Behaviour moveRightBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - moveRightBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code # End - Partial Transition Function Code pass ##### End of transition function ##### ##### Send data to other subsystems ##### def sendData_moveRightBehaviour(self): self.log("[Behaviour moveRightBehaviour] -- Sending Data") # DIAGNOSTICS SEND # self.sendDataForDiagnostics() # END OF DIAGNOSTICS SEND # # TYPICAL SEND CALL # # check if output buffer taskStatus has new data - i.e. is ready to send new data if( self._out_flag_taskStatus ): # send data from output buffer taskStatus # Buffer taskStatus - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_taskStatus.publish(self.taskStatus) # sending data from output buffer taskStatus # # indicate that data was sent and now the output buffer taskStatus is empty self._out_flag_taskStatus=False # check if output buffer desiredRobotCommandTele has new data - i.e. is ready to send new data if( self._out_flag_desiredRobotCommandTele ): # send data from output buffer desiredRobotCommandTele # Buffer desiredRobotCommandTele - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_desiredRobotCommandTele.publish(self.desiredRobotCommandTele) # sending data from output buffer desiredRobotCommandTele # # indicate that data was sent and now the output buffer desiredRobotCommandTele is empty self._out_flag_desiredRobotCommandTele=False # END OF TYPICAL SEND CALL # # BEGIN OF BODY SEND CALL # # END OF BODY SEND CALL # pass ##### Receive data from other subsystems ##### def receiveData_moveRightBehaviour(self): self.log("[Behaviour moveRightBehaviour] -- Receiving Data") # TYPICAL RECEIVE CALL # # Buffer taskCommand - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer taskCommand # Buffer ballInfoTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballInfoTele # Buffer obstacleDetectedTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer obstacleDetectedTele # Buffer ballCollected - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballCollected self.waitForAllMessages() # # END OF TYPICAL RECEIVE CALL # # BEGIN OF RECEIVE BODY CALL # # END OF RECEIVE BODY CALL # pass ##### Execute behaviour moveRightBehaviour ##### def executeBehaviour_moveRightBehaviour(self): self.log("[Behaviour moveRightBehaviour] -- Executing moveRightBehaviour Behaviour") stopBehaviourIteration=False # Execution of a single iteration of a behaviour moveRightBehaviour # _behaviourIterations=0 # Starts execution! # while True: # Sleep is a method from class AuxiliaryFunctions which executes sleep from ROS # self.auxiliaryFunctions.sleep() # Calculates transition function -- output and internal buffers can only be modified by this function! # self.transitionFunction_moveRightBehaviour() # Sends data! # self.sendData_moveRightBehaviour() # Updates index! -- i.e. i:i+1 -- increment number of behaviour iterations and number of subsystem iterations # self._behaviourIterations=self._behaviourIterations+1 # Receives data! # self.receiveData_moveRightBehaviour() # Check both conditions, i.e. terminal condition and error condition # stopBehaviourIteration = self.terminalCondition_moveRightBehaviour() or self.errorCondition_moveRightBehaviour() if stopBehaviourIteration or not self.auxiliaryFunctions.isSubsystemOK(): ''' Iterate within the while loop until stopBehaviourIteration is set true, i.e. one of error and terminal condition is fulfilled and isSubsystemOK is true. Otherwise subsystem must have been switched to another state or SIGINT was sent ''' break # Stops execution! # pass ##### Behaviour moveLeftBehaviour ##### ##### Terminal condition ##### def terminalCondition_moveLeftBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour moveLeftBehaviour] -- Checking Terminal Condition") return True pass ##### Error condition ##### def errorCondition_moveLeftBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour moveLeftBehaviour] -- Checking Error Condition") return False pass ##### Transition function ##### def transitionFunction_moveLeftBehaviour(self): self.log("[Behaviour moveLeftBehaviour] -- Calculating Transition Function") # Transition function # self.log("TRANSITION FUNCTION - moveLeftBehaviour consists of the following partial transition functions (decomposition based on output buffers)") # Partial transition function call: fun1 self.transitionFunction_moveLeftBehaviour_fun1() # Partial transition function call: set_buffer_flags_function self.transitionFunction_moveLeftBehaviour_set_buffer_flags_function() pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_moveLeftBehaviour_fun1(self): self.log("[Behaviour moveLeftBehaviour] -- Calculating Partial Transition Function fun1") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - moveLeftBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_moveLeftBehaviour_fun1_0() pass ##### Partial transition function: fun1_0 based on input buffers True ##### def transitionFunction_moveLeftBehaviour_fun1_0(self): self.log("[Behaviour moveLeftBehaviour] -- Calculating Partial Transition Function fun1_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - moveLeftBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code self._out_flag_taskStatus=True self._out_flag_desiredRobotCommandTele=True print("[CS - teleoperated] -- moveLeftBehaviour") self.desiredRobotCommandTele.data="move left" self.taskStatus.data="task status: move left" # End - Partial Transition Function Code pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_moveLeftBehaviour_set_buffer_flags_function(self): self.log("[Behaviour moveLeftBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - moveLeftBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_moveLeftBehaviour_set_buffer_flags_function_0() pass ##### Partial transition function: set_buffer_flags_function_0 based on input buffers True ##### def transitionFunction_moveLeftBehaviour_set_buffer_flags_function_0(self): self.log("[Behaviour moveLeftBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - moveLeftBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code # End - Partial Transition Function Code pass ##### End of transition function ##### ##### Send data to other subsystems ##### def sendData_moveLeftBehaviour(self): self.log("[Behaviour moveLeftBehaviour] -- Sending Data") # DIAGNOSTICS SEND # self.sendDataForDiagnostics() # END OF DIAGNOSTICS SEND # # TYPICAL SEND CALL # # check if output buffer taskStatus has new data - i.e. is ready to send new data if( self._out_flag_taskStatus ): # send data from output buffer taskStatus # Buffer taskStatus - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_taskStatus.publish(self.taskStatus) # sending data from output buffer taskStatus # # indicate that data was sent and now the output buffer taskStatus is empty self._out_flag_taskStatus=False # check if output buffer desiredRobotCommandTele has new data - i.e. is ready to send new data if( self._out_flag_desiredRobotCommandTele ): # send data from output buffer desiredRobotCommandTele # Buffer desiredRobotCommandTele - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_desiredRobotCommandTele.publish(self.desiredRobotCommandTele) # sending data from output buffer desiredRobotCommandTele # # indicate that data was sent and now the output buffer desiredRobotCommandTele is empty self._out_flag_desiredRobotCommandTele=False # END OF TYPICAL SEND CALL # # BEGIN OF BODY SEND CALL # # END OF BODY SEND CALL # pass ##### Receive data from other subsystems ##### def receiveData_moveLeftBehaviour(self): self.log("[Behaviour moveLeftBehaviour] -- Receiving Data") # TYPICAL RECEIVE CALL # # Buffer taskCommand - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer taskCommand # Buffer ballInfoTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballInfoTele # Buffer obstacleDetectedTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer obstacleDetectedTele # Buffer ballCollected - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballCollected self.waitForAllMessages() # # END OF TYPICAL RECEIVE CALL # # BEGIN OF RECEIVE BODY CALL # # END OF RECEIVE BODY CALL # pass ##### Execute behaviour moveLeftBehaviour ##### def executeBehaviour_moveLeftBehaviour(self): self.log("[Behaviour moveLeftBehaviour] -- Executing moveLeftBehaviour Behaviour") stopBehaviourIteration=False # Execution of a single iteration of a behaviour moveLeftBehaviour # _behaviourIterations=0 # Starts execution! # while True: # Sleep is a method from class AuxiliaryFunctions which executes sleep from ROS # self.auxiliaryFunctions.sleep() # Calculates transition function -- output and internal buffers can only be modified by this function! # self.transitionFunction_moveLeftBehaviour() # Sends data! # self.sendData_moveLeftBehaviour() # Updates index! -- i.e. i:i+1 -- increment number of behaviour iterations and number of subsystem iterations # self._behaviourIterations=self._behaviourIterations+1 # Receives data! # self.receiveData_moveLeftBehaviour() # Check both conditions, i.e. terminal condition and error condition # stopBehaviourIteration = self.terminalCondition_moveLeftBehaviour() or self.errorCondition_moveLeftBehaviour() if stopBehaviourIteration or not self.auxiliaryFunctions.isSubsystemOK(): ''' Iterate within the while loop until stopBehaviourIteration is set true, i.e. one of error and terminal condition is fulfilled and isSubsystemOK is true. Otherwise subsystem must have been switched to another state or SIGINT was sent ''' break # Stops execution! # pass ##### Behaviour rotateLeftBehaviour ##### ##### Terminal condition ##### def terminalCondition_rotateLeftBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour rotateLeftBehaviour] -- Checking Terminal Condition") return True pass ##### Error condition ##### def errorCondition_rotateLeftBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour rotateLeftBehaviour] -- Checking Error Condition") return False pass ##### Transition function ##### def transitionFunction_rotateLeftBehaviour(self): self.log("[Behaviour rotateLeftBehaviour] -- Calculating Transition Function") # Transition function # self.log("TRANSITION FUNCTION - rotateLeftBehaviour consists of the following partial transition functions (decomposition based on output buffers)") # Partial transition function call: fun1 self.transitionFunction_rotateLeftBehaviour_fun1() # Partial transition function call: set_buffer_flags_function self.transitionFunction_rotateLeftBehaviour_set_buffer_flags_function() pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_rotateLeftBehaviour_fun1(self): self.log("[Behaviour rotateLeftBehaviour] -- Calculating Partial Transition Function fun1") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - rotateLeftBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_rotateLeftBehaviour_fun1_0() pass ##### Partial transition function: fun1_0 based on input buffers True ##### def transitionFunction_rotateLeftBehaviour_fun1_0(self): self.log("[Behaviour rotateLeftBehaviour] -- Calculating Partial Transition Function fun1_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - rotateLeftBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code self._out_flag_taskStatus=True self._out_flag_desiredRobotCommandTele=True print("[CS - teleoperated] -- rotateLeftBehaviour") self.desiredRobotCommandTele.data="rotate left" self.taskStatus.data="task status: rotate left" # End - Partial Transition Function Code pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_rotateLeftBehaviour_set_buffer_flags_function(self): self.log("[Behaviour rotateLeftBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - rotateLeftBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_rotateLeftBehaviour_set_buffer_flags_function_0() pass ##### Partial transition function: set_buffer_flags_function_0 based on input buffers True ##### def transitionFunction_rotateLeftBehaviour_set_buffer_flags_function_0(self): self.log("[Behaviour rotateLeftBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - rotateLeftBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code # End - Partial Transition Function Code pass ##### End of transition function ##### ##### Send data to other subsystems ##### def sendData_rotateLeftBehaviour(self): self.log("[Behaviour rotateLeftBehaviour] -- Sending Data") # DIAGNOSTICS SEND # self.sendDataForDiagnostics() # END OF DIAGNOSTICS SEND # # TYPICAL SEND CALL # # check if output buffer taskStatus has new data - i.e. is ready to send new data if( self._out_flag_taskStatus ): # send data from output buffer taskStatus # Buffer taskStatus - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_taskStatus.publish(self.taskStatus) # sending data from output buffer taskStatus # # indicate that data was sent and now the output buffer taskStatus is empty self._out_flag_taskStatus=False # check if output buffer desiredRobotCommandTele has new data - i.e. is ready to send new data if( self._out_flag_desiredRobotCommandTele ): # send data from output buffer desiredRobotCommandTele # Buffer desiredRobotCommandTele - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_desiredRobotCommandTele.publish(self.desiredRobotCommandTele) # sending data from output buffer desiredRobotCommandTele # # indicate that data was sent and now the output buffer desiredRobotCommandTele is empty self._out_flag_desiredRobotCommandTele=False # END OF TYPICAL SEND CALL # # BEGIN OF BODY SEND CALL # # END OF BODY SEND CALL # pass ##### Receive data from other subsystems ##### def receiveData_rotateLeftBehaviour(self): self.log("[Behaviour rotateLeftBehaviour] -- Receiving Data") # TYPICAL RECEIVE CALL # # Buffer taskCommand - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer taskCommand # Buffer ballInfoTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballInfoTele # Buffer obstacleDetectedTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer obstacleDetectedTele # Buffer ballCollected - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballCollected self.waitForAllMessages() # # END OF TYPICAL RECEIVE CALL # # BEGIN OF RECEIVE BODY CALL # # END OF RECEIVE BODY CALL # pass ##### Execute behaviour rotateLeftBehaviour ##### def executeBehaviour_rotateLeftBehaviour(self): self.log("[Behaviour rotateLeftBehaviour] -- Executing rotateLeftBehaviour Behaviour") stopBehaviourIteration=False # Execution of a single iteration of a behaviour rotateLeftBehaviour # _behaviourIterations=0 # Starts execution! # while True: # Sleep is a method from class AuxiliaryFunctions which executes sleep from ROS # self.auxiliaryFunctions.sleep() # Calculates transition function -- output and internal buffers can only be modified by this function! # self.transitionFunction_rotateLeftBehaviour() # Sends data! # self.sendData_rotateLeftBehaviour() # Updates index! -- i.e. i:i+1 -- increment number of behaviour iterations and number of subsystem iterations # self._behaviourIterations=self._behaviourIterations+1 # Receives data! # self.receiveData_rotateLeftBehaviour() # Check both conditions, i.e. terminal condition and error condition # stopBehaviourIteration = self.terminalCondition_rotateLeftBehaviour() or self.errorCondition_rotateLeftBehaviour() if stopBehaviourIteration or not self.auxiliaryFunctions.isSubsystemOK(): ''' Iterate within the while loop until stopBehaviourIteration is set true, i.e. one of error and terminal condition is fulfilled and isSubsystemOK is true. Otherwise subsystem must have been switched to another state or SIGINT was sent ''' break # Stops execution! # pass ##### Behaviour rotateRightBehaviour ##### ##### Terminal condition ##### def terminalCondition_rotateRightBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour rotateRightBehaviour] -- Checking Terminal Condition") return True pass ##### Error condition ##### def errorCondition_rotateRightBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour rotateRightBehaviour] -- Checking Error Condition") return False pass ##### Transition function ##### def transitionFunction_rotateRightBehaviour(self): self.log("[Behaviour rotateRightBehaviour] -- Calculating Transition Function") # Transition function # self.log("TRANSITION FUNCTION - rotateRightBehaviour consists of the following partial transition functions (decomposition based on output buffers)") # Partial transition function call: fun1 self.transitionFunction_rotateRightBehaviour_fun1() # Partial transition function call: set_buffer_flags_function self.transitionFunction_rotateRightBehaviour_set_buffer_flags_function() pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_rotateRightBehaviour_fun1(self): self.log("[Behaviour rotateRightBehaviour] -- Calculating Partial Transition Function fun1") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - rotateRightBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_rotateRightBehaviour_fun1_0() pass ##### Partial transition function: fun1_0 based on input buffers True ##### def transitionFunction_rotateRightBehaviour_fun1_0(self): self.log("[Behaviour rotateRightBehaviour] -- Calculating Partial Transition Function fun1_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - rotateRightBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code self._out_flag_taskStatus=True self._out_flag_desiredRobotCommandTele=True print("[CS - teleoperated] -- rotateRightBehaviour") self.desiredRobotCommandTele.data="rotate right" self.taskStatus.data="task status: rotate right" # End - Partial Transition Function Code pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_rotateRightBehaviour_set_buffer_flags_function(self): self.log("[Behaviour rotateRightBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - rotateRightBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_rotateRightBehaviour_set_buffer_flags_function_0() pass ##### Partial transition function: set_buffer_flags_function_0 based on input buffers True ##### def transitionFunction_rotateRightBehaviour_set_buffer_flags_function_0(self): self.log("[Behaviour rotateRightBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - rotateRightBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code # End - Partial Transition Function Code pass ##### End of transition function ##### ##### Send data to other subsystems ##### def sendData_rotateRightBehaviour(self): self.log("[Behaviour rotateRightBehaviour] -- Sending Data") # DIAGNOSTICS SEND # self.sendDataForDiagnostics() # END OF DIAGNOSTICS SEND # # TYPICAL SEND CALL # # check if output buffer taskStatus has new data - i.e. is ready to send new data if( self._out_flag_taskStatus ): # send data from output buffer taskStatus # Buffer taskStatus - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_taskStatus.publish(self.taskStatus) # sending data from output buffer taskStatus # # indicate that data was sent and now the output buffer taskStatus is empty self._out_flag_taskStatus=False # check if output buffer desiredRobotCommandTele has new data - i.e. is ready to send new data if( self._out_flag_desiredRobotCommandTele ): # send data from output buffer desiredRobotCommandTele # Buffer desiredRobotCommandTele - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_desiredRobotCommandTele.publish(self.desiredRobotCommandTele) # sending data from output buffer desiredRobotCommandTele # # indicate that data was sent and now the output buffer desiredRobotCommandTele is empty self._out_flag_desiredRobotCommandTele=False # END OF TYPICAL SEND CALL # # BEGIN OF BODY SEND CALL # # END OF BODY SEND CALL # pass ##### Receive data from other subsystems ##### def receiveData_rotateRightBehaviour(self): self.log("[Behaviour rotateRightBehaviour] -- Receiving Data") # TYPICAL RECEIVE CALL # # Buffer taskCommand - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer taskCommand # Buffer ballInfoTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballInfoTele # Buffer obstacleDetectedTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer obstacleDetectedTele # Buffer ballCollected - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballCollected self.waitForAllMessages() # # END OF TYPICAL RECEIVE CALL # # BEGIN OF RECEIVE BODY CALL # # END OF RECEIVE BODY CALL # pass ##### Execute behaviour rotateRightBehaviour ##### def executeBehaviour_rotateRightBehaviour(self): self.log("[Behaviour rotateRightBehaviour] -- Executing rotateRightBehaviour Behaviour") stopBehaviourIteration=False # Execution of a single iteration of a behaviour rotateRightBehaviour # _behaviourIterations=0 # Starts execution! # while True: # Sleep is a method from class AuxiliaryFunctions which executes sleep from ROS # self.auxiliaryFunctions.sleep() # Calculates transition function -- output and internal buffers can only be modified by this function! # self.transitionFunction_rotateRightBehaviour() # Sends data! # self.sendData_rotateRightBehaviour() # Updates index! -- i.e. i:i+1 -- increment number of behaviour iterations and number of subsystem iterations # self._behaviourIterations=self._behaviourIterations+1 # Receives data! # self.receiveData_rotateRightBehaviour() # Check both conditions, i.e. terminal condition and error condition # stopBehaviourIteration = self.terminalCondition_rotateRightBehaviour() or self.errorCondition_rotateRightBehaviour() if stopBehaviourIteration or not self.auxiliaryFunctions.isSubsystemOK(): ''' Iterate within the while loop until stopBehaviourIteration is set true, i.e. one of error and terminal condition is fulfilled and isSubsystemOK is true. Otherwise subsystem must have been switched to another state or SIGINT was sent ''' break # Stops execution! # pass ##### Behaviour whatCanYouSeeBehaviour ##### ##### Terminal condition ##### def terminalCondition_whatCanYouSeeBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour whatCanYouSeeBehaviour] -- Checking Terminal Condition") return True pass ##### Error condition ##### def errorCondition_whatCanYouSeeBehaviour(self): # String taskCommand, String robotStatus, CameraMessage ballInfoTele, ObstacleDetected obstacleDetectedTele, Bool ballCollected, Int64 isNewCommandReceived, std_msgs::Bool _in_flag_taskCommand, std_msgs::Bool _in_flag_robotStatus, std_msgs::Bool _in_flag_ballInfoTele, std_msgs::Bool _in_flag_obstacleDetectedTele, std_msgs::Bool _in_flag_ballCollected, std_msgs::Bool _out_flag_taskStatus, std_msgs::Bool _out_flag_desiredRobotCommandTele # self.log("[Behaviour whatCanYouSeeBehaviour] -- Checking Error Condition") return False pass ##### Transition function ##### def transitionFunction_whatCanYouSeeBehaviour(self): self.log("[Behaviour whatCanYouSeeBehaviour] -- Calculating Transition Function") # Transition function # self.log("TRANSITION FUNCTION - whatCanYouSeeBehaviour consists of the following partial transition functions (decomposition based on output buffers)") # Partial transition function call: fun1 self.transitionFunction_whatCanYouSeeBehaviour_fun1() # Partial transition function call: set_buffer_flags_function self.transitionFunction_whatCanYouSeeBehaviour_set_buffer_flags_function() pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_whatCanYouSeeBehaviour_fun1(self): self.log("[Behaviour whatCanYouSeeBehaviour] -- Calculating Partial Transition Function fun1") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - whatCanYouSeeBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_whatCanYouSeeBehaviour_fun1_0() pass ##### Partial transition function: fun1_0 based on input buffers True ##### def transitionFunction_whatCanYouSeeBehaviour_fun1_0(self): self.log("[Behaviour whatCanYouSeeBehaviour] -- Calculating Partial Transition Function fun1_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - whatCanYouSeeBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code self._out_flag_taskStatus=True self._out_flag_desiredRobotCommandTele=True print("[CS - teleoperated] -- whatCanYouSeeBehaviour") self.desiredRobotCommandTele.data="what can you see" self.taskCommand.data="empty" self.taskStatus.data="task status: what can you see" # End - Partial Transition Function Code pass ##### Decomposition of partial transition function based on input buffers ##### def transitionFunction_whatCanYouSeeBehaviour_set_buffer_flags_function(self): self.log("[Behaviour whatCanYouSeeBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function") # Partial Transition Function - the first layer # self.log("PARTIAL TRANSITION FUNCTION - FIRST LAYER - whatCanYouSeeBehaviour consists of the following partial transition functions (decomposition based on input buffers)") if True: self.transitionFunction_whatCanYouSeeBehaviour_set_buffer_flags_function_0() pass ##### Partial transition function: set_buffer_flags_function_0 based on input buffers True ##### def transitionFunction_whatCanYouSeeBehaviour_set_buffer_flags_function_0(self): self.log("[Behaviour whatCanYouSeeBehaviour] -- Calculating Partial Transition Function set_buffer_flags_function_0") # Partial Transition Function - the second layer # self.log("PARTIAL TRANSITION FUNCTION - SECOND LAYER - whatCanYouSeeBehaviour consists of the following partial transition functions (decomposition based on input buffers)") # Begin - Partial Transition Function Code # End - Partial Transition Function Code pass ##### End of transition function ##### ##### Send data to other subsystems ##### def sendData_whatCanYouSeeBehaviour(self): self.log("[Behaviour whatCanYouSeeBehaviour] -- Sending Data") # DIAGNOSTICS SEND # self.sendDataForDiagnostics() # END OF DIAGNOSTICS SEND # # TYPICAL SEND CALL # # check if output buffer taskStatus has new data - i.e. is ready to send new data if( self._out_flag_taskStatus ): # send data from output buffer taskStatus # Buffer taskStatus - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_taskStatus.publish(self.taskStatus) # sending data from output buffer taskStatus # # indicate that data was sent and now the output buffer taskStatus is empty self._out_flag_taskStatus=False # check if output buffer desiredRobotCommandTele has new data - i.e. is ready to send new data if( self._out_flag_desiredRobotCommandTele ): # send data from output buffer desiredRobotCommandTele # Buffer desiredRobotCommandTele - NON-BLOCKING Sender mode - NON-BLOCKING Receiver mode self._sender_desiredRobotCommandTele.publish(self.desiredRobotCommandTele) # sending data from output buffer desiredRobotCommandTele # # indicate that data was sent and now the output buffer desiredRobotCommandTele is empty self._out_flag_desiredRobotCommandTele=False # END OF TYPICAL SEND CALL # # BEGIN OF BODY SEND CALL # # END OF BODY SEND CALL # pass ##### Receive data from other subsystems ##### def receiveData_whatCanYouSeeBehaviour(self): self.log("[Behaviour whatCanYouSeeBehaviour] -- Receiving Data") # TYPICAL RECEIVE CALL # # Buffer taskCommand - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer taskCommand # Buffer ballInfoTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballInfoTele # Buffer obstacleDetectedTele - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer obstacleDetectedTele # Buffer ballCollected - Sender using NON-BLOCKING MODE - Receiver using NON-BLOCKING MODE # ROS topic generated for the input buffer ballCollected self.waitForAllMessages() # # END OF TYPICAL RECEIVE CALL # # BEGIN OF RECEIVE BODY CALL # # END OF RECEIVE BODY CALL # pass ##### Execute behaviour whatCanYouSeeBehaviour ##### def executeBehaviour_whatCanYouSeeBehaviour(self): self.log("[Behaviour whatCanYouSeeBehaviour] -- Executing whatCanYouSeeBehaviour Behaviour") stopBehaviourIteration=False # Execution of a single iteration of a behaviour whatCanYouSeeBehaviour # _behaviourIterations=0 # Starts execution! # while True: # Sleep is a method from class AuxiliaryFunctions which executes sleep from ROS # self.auxiliaryFunctions.sleep() # Calculates transition function -- output and internal buffers can only be modified by this function! # self.transitionFunction_whatCanYouSeeBehaviour() # Sends data! # self.sendData_whatCanYouSeeBehaviour() # Updates index! -- i.e. i:i+1 -- increment number of behaviour iterations and number of subsystem iterations # self._behaviourIterations=self._behaviourIterations+1 # Receives data! # self.receiveData_whatCanYouSeeBehaviour() # Check both conditions, i.e. terminal condition and error condition # stopBehaviourIteration = self.terminalCondition_whatCanYouSeeBehaviour() or self.errorCondition_whatCanYouSeeBehaviour() if stopBehaviourIteration or not self.auxiliaryFunctions.isSubsystemOK(): ''' Iterate within the while loop until stopBehaviourIteration is set true, i.e. one of error and terminal condition is fulfilled and isSubsystemOK is true. Otherwise subsystem must have been switched to another state or SIGINT was sent ''' break # Stops execution! # pass ##### Definition of functions responsible for switching subsystem cs between states : Behaviour_initBehaviour Behaviour_idleBehaviour Behaviour_terminateBehaviour Behaviour_terminatedBehaviour Behaviour_stopBehaviour Behaviour_moveFasterBehaviour Behaviour_moveSlowerBehaviour Behaviour_vacuumOnBehaviour Behaviour_vacuumOffBehaviour Behaviour_moveBackwardBehaviour Behaviour_moveFrontBehaviour Behaviour_moveRightBehaviour Behaviour_moveLeftBehaviour Behaviour_rotateLeftBehaviour Behaviour_rotateRightBehaviour Behaviour_whatCanYouSeeBehaviour ##### # Behaviour initBehaviour: # def subsystemBehaviour_initBehaviour(self): self.log("subsystemBehaviour_initBehaviour") # Executing behaviour initBehaviour # self.executeBehaviour_initBehaviour() # Behaviour has been terminated # # Checking initial condition for behaviour initBehaviour: switching to behaviour idleBehaviour # if self.initialCondition_From_Behaviour_initBehaviour_To_Behaviour_idleBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_idleBehaviour" pass # Behaviour idleBehaviour: # def subsystemBehaviour_idleBehaviour(self): self.log("subsystemBehaviour_idleBehaviour") # Executing behaviour idleBehaviour # self.executeBehaviour_idleBehaviour() # Behaviour has been terminated # # Checking initial condition for behaviour idleBehaviour: switching to behaviour terminateBehaviour # if self.initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_terminateBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_terminateBehaviour" # Checking initial condition for behaviour idleBehaviour: switching to behaviour stopBehaviour # if self.initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_stopBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_stopBehaviour" # Checking initial condition for behaviour idleBehaviour: switching to behaviour moveFasterBehaviour # if self.initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_moveFasterBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_moveFasterBehaviour" # Checking initial condition for behaviour idleBehaviour: switching to behaviour moveSlowerBehaviour # if self.initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_moveSlowerBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_moveSlowerBehaviour" # Checking initial condition for behaviour idleBehaviour: switching to behaviour vacuumOnBehaviour # if self.initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_vacuumOnBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_vacuumOnBehaviour" # Checking initial condition for behaviour idleBehaviour: switching to behaviour vacuumOffBehaviour # if self.initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_vacuumOffBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_vacuumOffBehaviour" # Checking initial condition for behaviour idleBehaviour: switching to behaviour moveBackwardBehaviour # if self.initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_moveBackwardBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_moveBackwardBehaviour" # Checking initial condition for behaviour idleBehaviour: switching to behaviour moveFrontBehaviour # if self.initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_moveFrontBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_moveFrontBehaviour" # Checking initial condition for behaviour idleBehaviour: switching to behaviour moveRightBehaviour # if self.initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_moveRightBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_moveRightBehaviour" # Checking initial condition for behaviour idleBehaviour: switching to behaviour moveLeftBehaviour # if self.initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_moveLeftBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_moveLeftBehaviour" # Checking initial condition for behaviour idleBehaviour: switching to behaviour rotateLeftBehaviour # if self.initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_rotateLeftBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_rotateLeftBehaviour" # Checking initial condition for behaviour idleBehaviour: switching to behaviour rotateRightBehaviour # if self.initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_rotateRightBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_rotateRightBehaviour" # Checking initial condition for behaviour idleBehaviour: switching to behaviour whatCanYouSeeBehaviour # if self.initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_whatCanYouSeeBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_whatCanYouSeeBehaviour" pass # Behaviour terminateBehaviour: # def subsystemBehaviour_terminateBehaviour(self): self.log("subsystemBehaviour_terminateBehaviour") # Executing behaviour terminateBehaviour # self.executeBehaviour_terminateBehaviour() # Behaviour has been terminated # # Checking initial condition for behaviour terminateBehaviour: switching to behaviour terminatedBehaviour # if self.initialCondition_From_Behaviour_terminateBehaviour_To_Behaviour_terminatedBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_terminatedBehaviour" pass # Behaviour terminatedBehaviour: # def subsystemBehaviour_terminatedBehaviour(self): self.log("subsystemBehaviour_terminatedBehaviour") # Executing behaviour terminatedBehaviour # self.executeBehaviour_terminatedBehaviour() # Behaviour has been terminated # pass # Behaviour stopBehaviour: # def subsystemBehaviour_stopBehaviour(self): self.log("subsystemBehaviour_stopBehaviour") # Executing behaviour stopBehaviour # self.executeBehaviour_stopBehaviour() # Behaviour has been terminated # # Checking initial condition for behaviour stopBehaviour: switching to behaviour idleBehaviour # if self.initialCondition_From_Behaviour_stopBehaviour_To_Behaviour_idleBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_idleBehaviour" pass # Behaviour moveFasterBehaviour: # def subsystemBehaviour_moveFasterBehaviour(self): self.log("subsystemBehaviour_moveFasterBehaviour") # Executing behaviour moveFasterBehaviour # self.executeBehaviour_moveFasterBehaviour() # Behaviour has been terminated # # Checking initial condition for behaviour moveFasterBehaviour: switching to behaviour idleBehaviour # if self.initialCondition_From_Behaviour_moveFasterBehaviour_To_Behaviour_idleBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_idleBehaviour" pass # Behaviour moveSlowerBehaviour: # def subsystemBehaviour_moveSlowerBehaviour(self): self.log("subsystemBehaviour_moveSlowerBehaviour") # Executing behaviour moveSlowerBehaviour # self.executeBehaviour_moveSlowerBehaviour() # Behaviour has been terminated # # Checking initial condition for behaviour moveSlowerBehaviour: switching to behaviour idleBehaviour # if self.initialCondition_From_Behaviour_moveSlowerBehaviour_To_Behaviour_idleBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_idleBehaviour" pass # Behaviour vacuumOnBehaviour: # def subsystemBehaviour_vacuumOnBehaviour(self): self.log("subsystemBehaviour_vacuumOnBehaviour") # Executing behaviour vacuumOnBehaviour # self.executeBehaviour_vacuumOnBehaviour() # Behaviour has been terminated # # Checking initial condition for behaviour vacuumOnBehaviour: switching to behaviour idleBehaviour # if self.initialCondition_From_Behaviour_vacuumOnBehaviour_To_Behaviour_idleBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_idleBehaviour" pass # Behaviour vacuumOffBehaviour: # def subsystemBehaviour_vacuumOffBehaviour(self): self.log("subsystemBehaviour_vacuumOffBehaviour") # Executing behaviour vacuumOffBehaviour # self.executeBehaviour_vacuumOffBehaviour() # Behaviour has been terminated # # Checking initial condition for behaviour vacuumOffBehaviour: switching to behaviour idleBehaviour # if self.initialCondition_From_Behaviour_vacuumOffBehaviour_To_Behaviour_idleBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_idleBehaviour" pass # Behaviour moveBackwardBehaviour: # def subsystemBehaviour_moveBackwardBehaviour(self): self.log("subsystemBehaviour_moveBackwardBehaviour") # Executing behaviour moveBackwardBehaviour # self.executeBehaviour_moveBackwardBehaviour() # Behaviour has been terminated # # Checking initial condition for behaviour moveBackwardBehaviour: switching to behaviour idleBehaviour # if self.initialCondition_From_Behaviour_moveBackwardBehaviour_To_Behaviour_idleBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_idleBehaviour" pass # Behaviour moveFrontBehaviour: # def subsystemBehaviour_moveFrontBehaviour(self): self.log("subsystemBehaviour_moveFrontBehaviour") # Executing behaviour moveFrontBehaviour # self.executeBehaviour_moveFrontBehaviour() # Behaviour has been terminated # # Checking initial condition for behaviour moveFrontBehaviour: switching to behaviour idleBehaviour # if self.initialCondition_From_Behaviour_moveFrontBehaviour_To_Behaviour_idleBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_idleBehaviour" pass # Behaviour moveRightBehaviour: # def subsystemBehaviour_moveRightBehaviour(self): self.log("subsystemBehaviour_moveRightBehaviour") # Executing behaviour moveRightBehaviour # self.executeBehaviour_moveRightBehaviour() # Behaviour has been terminated # # Checking initial condition for behaviour moveRightBehaviour: switching to behaviour idleBehaviour # if self.initialCondition_From_Behaviour_moveRightBehaviour_To_Behaviour_idleBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_idleBehaviour" pass # Behaviour moveLeftBehaviour: # def subsystemBehaviour_moveLeftBehaviour(self): self.log("subsystemBehaviour_moveLeftBehaviour") # Executing behaviour moveLeftBehaviour # self.executeBehaviour_moveLeftBehaviour() # Behaviour has been terminated # # Checking initial condition for behaviour moveLeftBehaviour: switching to behaviour idleBehaviour # if self.initialCondition_From_Behaviour_moveLeftBehaviour_To_Behaviour_idleBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_idleBehaviour" pass # Behaviour rotateLeftBehaviour: # def subsystemBehaviour_rotateLeftBehaviour(self): self.log("subsystemBehaviour_rotateLeftBehaviour") # Executing behaviour rotateLeftBehaviour # self.executeBehaviour_rotateLeftBehaviour() # Behaviour has been terminated # # Checking initial condition for behaviour rotateLeftBehaviour: switching to behaviour idleBehaviour # if self.initialCondition_From_Behaviour_rotateLeftBehaviour_To_Behaviour_idleBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_idleBehaviour" pass # Behaviour rotateRightBehaviour: # def subsystemBehaviour_rotateRightBehaviour(self): self.log("subsystemBehaviour_rotateRightBehaviour") # Executing behaviour rotateRightBehaviour # self.executeBehaviour_rotateRightBehaviour() # Behaviour has been terminated # # Checking initial condition for behaviour rotateRightBehaviour: switching to behaviour idleBehaviour # if self.initialCondition_From_Behaviour_rotateRightBehaviour_To_Behaviour_idleBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_idleBehaviour" pass # Behaviour whatCanYouSeeBehaviour: # def subsystemBehaviour_whatCanYouSeeBehaviour(self): self.log("subsystemBehaviour_whatCanYouSeeBehaviour") # Executing behaviour whatCanYouSeeBehaviour # self.executeBehaviour_whatCanYouSeeBehaviour() # Behaviour has been terminated # # Checking initial condition for behaviour whatCanYouSeeBehaviour: switching to behaviour idleBehaviour # if self.initialCondition_From_Behaviour_whatCanYouSeeBehaviour_To_Behaviour_idleBehaviour(): # incrementing the number determining how many times subsystem has switched between behaviours # self._subsystemIterations=self._subsystemIterations+1 self._currentSubsystemBehaviour="Behaviour_idleBehaviour" pass ##### Initial condition for behaviour initBehaviour: switching to behaviour idleBehaviour ##### def initialCondition_From_Behaviour_initBehaviour_To_Behaviour_idleBehaviour(self): # Initial condition specified by user # return True ##### Initial condition for behaviour idleBehaviour: switching to behaviour terminateBehaviour ##### def initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_terminateBehaviour(self): # Initial condition specified by user # return self.taskCommand.data=="terminate" ##### Initial condition for behaviour idleBehaviour: switching to behaviour stopBehaviour ##### def initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_stopBehaviour(self): # Initial condition specified by user # return self.taskCommand.data=="stop" ##### Initial condition for behaviour idleBehaviour: switching to behaviour moveFasterBehaviour ##### def initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_moveFasterBehaviour(self): # Initial condition specified by user # return self.taskCommand.data=="speed up" ##### Initial condition for behaviour idleBehaviour: switching to behaviour moveSlowerBehaviour ##### def initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_moveSlowerBehaviour(self): # Initial condition specified by user # return self.taskCommand.data=="speed down" ##### Initial condition for behaviour idleBehaviour: switching to behaviour vacuumOnBehaviour ##### def initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_vacuumOnBehaviour(self): # Initial condition specified by user # return self.taskCommand.data=="vacuum turn on" ##### Initial condition for behaviour idleBehaviour: switching to behaviour vacuumOffBehaviour ##### def initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_vacuumOffBehaviour(self): # Initial condition specified by user # return self.taskCommand.data=="vacuum off" ##### Initial condition for behaviour idleBehaviour: switching to behaviour moveBackwardBehaviour ##### def initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_moveBackwardBehaviour(self): # Initial condition specified by user # return self.taskCommand.data=="backwards" ##### Initial condition for behaviour idleBehaviour: switching to behaviour moveFrontBehaviour ##### def initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_moveFrontBehaviour(self): # Initial condition specified by user # return self.taskCommand.data=="front" ##### Initial condition for behaviour idleBehaviour: switching to behaviour moveRightBehaviour ##### def initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_moveRightBehaviour(self): # Initial condition specified by user # return self.taskCommand.data=="right" ##### Initial condition for behaviour idleBehaviour: switching to behaviour moveLeftBehaviour ##### def initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_moveLeftBehaviour(self): # Initial condition specified by user # return self.taskCommand.data=="left" ##### Initial condition for behaviour idleBehaviour: switching to behaviour rotateLeftBehaviour ##### def initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_rotateLeftBehaviour(self): # Initial condition specified by user # return self.taskCommand.data=="rotate left" ##### Initial condition for behaviour idleBehaviour: switching to behaviour rotateRightBehaviour ##### def initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_rotateRightBehaviour(self): # Initial condition specified by user # return self.taskCommand.data=="rotate right" ##### Initial condition for behaviour idleBehaviour: switching to behaviour whatCanYouSeeBehaviour ##### def initialCondition_From_Behaviour_idleBehaviour_To_Behaviour_whatCanYouSeeBehaviour(self): # Initial condition specified by user # return self.taskCommand.data=="what can you see" ##### Initial condition for behaviour terminateBehaviour: switching to behaviour terminatedBehaviour ##### def initialCondition_From_Behaviour_terminateBehaviour_To_Behaviour_terminatedBehaviour(self): # Initial condition specified by user # return True ##### Initial condition for behaviour stopBehaviour: switching to behaviour idleBehaviour ##### def initialCondition_From_Behaviour_stopBehaviour_To_Behaviour_idleBehaviour(self): # Initial condition specified by user # return True ##### Initial condition for behaviour moveFasterBehaviour: switching to behaviour idleBehaviour ##### def initialCondition_From_Behaviour_moveFasterBehaviour_To_Behaviour_idleBehaviour(self): # Initial condition specified by user # return True ##### Initial condition for behaviour moveSlowerBehaviour: switching to behaviour idleBehaviour ##### def initialCondition_From_Behaviour_moveSlowerBehaviour_To_Behaviour_idleBehaviour(self): # Initial condition specified by user # return True ##### Initial condition for behaviour vacuumOnBehaviour: switching to behaviour idleBehaviour ##### def initialCondition_From_Behaviour_vacuumOnBehaviour_To_Behaviour_idleBehaviour(self): # Initial condition specified by user # return True ##### Initial condition for behaviour vacuumOffBehaviour: switching to behaviour idleBehaviour ##### def initialCondition_From_Behaviour_vacuumOffBehaviour_To_Behaviour_idleBehaviour(self): # Initial condition specified by user # return True ##### Initial condition for behaviour moveBackwardBehaviour: switching to behaviour idleBehaviour ##### def initialCondition_From_Behaviour_moveBackwardBehaviour_To_Behaviour_idleBehaviour(self): # Initial condition specified by user # return True ##### Initial condition for behaviour moveFrontBehaviour: switching to behaviour idleBehaviour ##### def initialCondition_From_Behaviour_moveFrontBehaviour_To_Behaviour_idleBehaviour(self): # Initial condition specified by user # return True ##### Initial condition for behaviour moveRightBehaviour: switching to behaviour idleBehaviour ##### def initialCondition_From_Behaviour_moveRightBehaviour_To_Behaviour_idleBehaviour(self): # Initial condition specified by user # return True ##### Initial condition for behaviour moveLeftBehaviour: switching to behaviour idleBehaviour ##### def initialCondition_From_Behaviour_moveLeftBehaviour_To_Behaviour_idleBehaviour(self): # Initial condition specified by user # return True ##### Initial condition for behaviour rotateLeftBehaviour: switching to behaviour idleBehaviour ##### def initialCondition_From_Behaviour_rotateLeftBehaviour_To_Behaviour_idleBehaviour(self): # Initial condition specified by user # return True ##### Initial condition for behaviour rotateRightBehaviour: switching to behaviour idleBehaviour ##### def initialCondition_From_Behaviour_rotateRightBehaviour_To_Behaviour_idleBehaviour(self): # Initial condition specified by user # return True ##### Initial condition for behaviour whatCanYouSeeBehaviour: switching to behaviour idleBehaviour ##### def initialCondition_From_Behaviour_whatCanYouSeeBehaviour_To_Behaviour_idleBehaviour(self): # Initial condition specified by user # return True ##### Function indicating basic log/debug message ##### def log(self, str): if(IS_LOG): rospy.loginfo("[SUBSYSTEM cs] -- LOG -- "+str) if(IS_PRINT): print "[SUBSYSTEM cs] -- LOG -- " + str pass ##### Function indicating basic error message ##### def error(self, str): sys.stderr.write("[SUBSYSTEM cs] -- ERROR -- " + str) if(IS_LOG): rospy.loginfo("[SUBSYSTEM cs] -- ERROR -- "+str) sys.exit() pass ##### MAIN FUNCTION FOR SUBSYSTEM cs ##### if __name__ == '__main__': try: subsystem_cs = cs() subsystem_cs.startSubsystem() except rospy.ROSInterruptException: pass

UTF-8

Python

false

174,238

py

59

subsystem_cs.py

32

0.750795

0.748252

0

3,007

56.943798

554

nagpureabhirag/Graph-1

17,471,926,969,178

a932817460a1c07c44956c28efae9a826375e875

1c5de78c2f731a6e5c34524880912bfe89593048

/find_the_town_judge.py

12cfdfc1cc478a69e5a4e72aa60fe3afcd2924e1

[]

no_license

https://github.com/nagpureabhirag/Graph-1

cc6a19178e5e9e26e4e588088ebb009f152e2619

a813d3b086bb6c899fb79f1a5b1438f69ab16fd2

refs/heads/master

2023-08-26T09:08:26.208774

2021-10-18T16:09:05

null

0

null

# Did this code successfully run on Leetcode : YES # approach # calculate difference between indegrees and outdegrees # TC: O(N) # SC: O(N) class Solution: def findJudge(self, n: int, trust: List[List[int]]) -> int: degrees = [0 for _ in range(n)] for [i, j] in trust: degrees[j-1] += 1 degrees[i-1] -= 1 for d in range(n): if degrees[d] == n-1: return d+1 return -1

UTF-8

Python

false

456

py

2

find_the_town_judge.py

2

0.537281

0.519737

0

17

25.882353

63

Ochwada/Thesis_-Data_Analysis-Public

11,012,296,162,218

0f851d8f9f361781b6b920668062ea119f13c6f0

1c7c2690c4439be51135c85533f6f0d3cf4ff1ce

/wind_histogram.py

af10a3026442e4295738734ad0702b60f4a5657f

[]

no_license

https://github.com/Ochwada/Thesis_-Data_Analysis-Public

516c4c15464511f0ef969f56c8bbb648c2767b94

ac1e8a7bff96521c9e9b2134d56f3a09c1a72524

refs/heads/master

2020-04-09T02:45:24.202761

2018-12-01T14:48:49

159,952,732

1

0

null

# -*- coding: utf-8 -*- # -*- codiing for wind_histogram -*- import matplotlib.pyplot as plt import numpy as np #import scipy.stats as stats from scipy import stats import matplotlib.mlab as mlab import statsmodels.api as sm import wind_data as wd import plot_winddata as pwd from helper import date_to_doy, doy_to_date, moving_average, altitude_to_int, weib import project_config as conf import math #import matplotlib.font_manager as font_manager axis_font = {'fontname':'Arial', 'size':'16'} # ----------------------------------------------------------------------- #Central Tendency # ----------------------------------------------------------------------- #mean def mean_speed(data): total = 0 mean = 0 for item in data: total += item mean_speed = total/float(len(data)) return mean_speed def mean_power(data): total = 0 mean = 0 for item in data: total+= item mean_power = total/float(len(data)) return mean_power # ----------------------------------------------------------------------- #Weibull pdf # ----------------------------------------------------------------------- def weibull_plot_speed(data, params): bins = np.arange(0, 32.0, 0.5) plt.hist(data, bins, histtype='bar', edgecolor='black',normed=True, alpha=0.5, rwidth=1.0); x = np.arange(0, 32.0, 0.1) plt.plot(x,stats.exponweib.pdf(x, *params), label="Weibull PDF") mean_value = data.mean() plt.axvline(mean_value, color='m', linestyle='dashed', linewidth=1, label="Mean power" ) #plt.title('Wind speed distribution for Germany at Level 1') plt.xlabel('Wind Speed (m/s)', **axis_font) plt.ylabel('Wind speed frequency', **axis_font) plt.legend(loc=1, prop={'size': 16}) plt.show() #plt.savefig('image1') #print(result) #======================================================================= if __name__ == '__main__': # ----------------------------------------------------------------------- # ----------------------------------------------------------------------- #Central Tendancy - Compute for 0-9 speedall = conf.load_all_windspeeds() meanspeed = mean_speed(speedall[:,1]) #print(meanspeed) powerall = conf.load_all_windpower() meanpower = mean_power(powerall[:,8]) #print(meanpower) #--------------------------Weibull PDF---------------------- #----------------------------------------------------------- #------------windspeed speedall = conf.load_all_windspeeds() data_speed = speedall [:,1] #params_speed = stats.exponweib.fit(data_speed,floc=0) #windspeed -----stats.exponweib.fit(data_speed,floc=0) params_speed = (1.1113449643109912, 1.6809413157101651, 0, 7.2972382976005772)#Level 1 #params_speed =(1.0635878486058918, 1.7129895275983615, 0, 8.0111689684382323)#Level 2 #params_speed =(1.0704643275819068, 1.6853620845145747, 0, 8.3604171276602486)#Level 3 #params_speed =(1.1113173256840196, 1.6301269094327573, 0, 8.4365496561132183)#Level 4 #params_speed =(1.1600496620157552, 1.5765771265205082, 0, 8.4068808687607639)#Level 5 #params_speed =(1.2147903730266001, 1.5256215491691232, 0, 8.3224080743411264)#Level 6 #params_speed =(1.2558199288860206, 1.4950921999766487, 0, 8.2474385764630327)#Level 7 #params_speed =(1.2949475501898591, 1.469286787656831, 0, 8.1859121591777537)#Level 8 #params_speed =(1.3035611603623392, 1.4695586916574541, 0, 8.2236837246717638)#Level 9 print('p\n', params_speed) #weibull_plot_speed(data_speed, params_speed) #------------windpower dist = stats.lognorm powerall = conf.load_all_windpower() data_power = powerall [:,9] #params_power = dist.fit(data_power,floc=0) params_power = (2.1848911866776488, 0, 195.85401224562315) #lognorm print('p\n', params_power) #--2--params_power=(1.0945801093499283, 0.56150661053208051, 0, 274.89152413198588)#Level 1 #weibull_plot_power(data_power, params_power, dist) #================================================================================================== #------------windpower location base -------- dist = stats.lognorm wind_Konigssee = wd.WindMeasurements().load(conf.connected_filename(47.5, 13.5) ) data_power_Konigssee = wind_Konigssee.windpower[:,9] params_power_Konigssee = dist.fit(data_power_Konigssee,floc=0) print('p\n', params_power_Konigssee) #weibull_plot_power(data_power_Konigssee, params_power_Konigssee, dist) #------------------------------------------------- #------------------------------------------------- #speedall = conf.load_all_windspeeds() #mediumspeed = median_speed(speedall [:,0]) #print(mediumspeed) #powerall = conf.load_all_windpower() #mediumpower = median_power(powerall [:,0]) #print(mediumpower) # ----------------------------------------------------------------------- #indata_Konigssee = wd.WindMeasurements().load(conf.connected_filename(47.5, 13.5) ) # Ten years at this location #check_distribution(indata_Konigssee.get_windspeed_at(0)) #speedall = conf.load_all_windspeeds() # np.load(conf.npz_folder_path + "windspeed_complete.npz", allow_pickle=False)['arr_0'] #powerall = conf.load_all_windpower() # np.load(conf.npz_folder_path + "windspower_complete.npz", allow_pickle=False)['arr_0'] #print(speedall.shape) #check_distribution(speedall[:,1]) #pass

UTF-8

Python

false

5,467

py

10

wind_histogram.py

9

0.56338

0.449241

0

140

38.057143

131

TheDrHax/streamlink

8,693,013,818,674

d3c223fe1854552333643c1d17387b59ce411cbb

716501ff054d10f095879f986d74882778fa72c5

/tests/plugins/test_webcast_india_gov.py

9e83d7dded01b3393c4227b4e511a4f73a88d4bd

[ "BSD-2-Clause" ]

permissive

https://github.com/TheDrHax/streamlink

017fdfd999277089a0c89a209ba4f64df9e54916

4dfd0d516fd8484438389518985e3b5131b7a253

refs/heads/master

2021-10-26T17:43:50.402219

2020-10-11T22:43:53

2021-10-25T19:10:01

223,461,822

4

0

BSD-2-Clause

true

2019-11-22T18:25:47

2019-11-22T18:25:46

2019-11-22T15:37:19

2019-11-22T16:48:00

35,041

0

null

false

from streamlink.plugins.webcast_india_gov import WebcastIndiaGov from tests.plugins import PluginCanHandleUrl class TestPluginCanHandleUrlWebcastIndiaGov(PluginCanHandleUrl): __plugin__ = WebcastIndiaGov should_match = [ "http://webcast.gov.in/ddpunjabi/", "http://webcast.gov.in/#Channel1", "http://webcast.gov.in/#Channel3", ]

UTF-8

Python

false

368

py

111

test_webcast_india_gov.py

103

0.711957

0.706522

0

12

29.666667

64

colinmipapi/italian

14,190,571,951,544

437a9635f279630430e9296b4f70dd2f82ab51b9

cfbf93c27ea19920d620dabd1f0648fe082f9391

/blog/models.py

5980326e7c80d5d524c45e9763a75f9e549ebb9e

[]

no_license

https://github.com/colinmipapi/italian

63c8ee03e55c3a572d89c42f3211687c60422ea1

8dbd270d6c7b9b2acb9f5e5fd964379030731f37

refs/heads/master

2021-01-21T17:17:17.988107

2017-03-16T03:36:58

85,148,252

0

null

from __future__ import unicode_literals from django.db import models from django.core.validators import MinValueValidator, MaxValueValidator from django.http import HttpResponseRedirect # Create your models here. class Post(models.Model): title = models.CharField(max_length=300) slug = models.CharField(max_length=100, unique=True) content = models.TextField() published = models.BooleanField(default=False) pub_date = models.DateTimeField(auto_now_add=True) rating_info = models.ForeignKey( 'blog.rating', on_delete=models.CASCADE, ) image_one = models.ImageField( upload_to='static/blog/media/uploads', default = '/None/no-img.jpg') def __unicode__(self): return '%s' % self.title class Rating(models.Model): sandwich_name = models.CharField(max_length=300, null = True) bread_quality = models.PositiveIntegerField(default=0, validators=[MaxValueValidator(10),], null = True) meat_quality = models.PositiveIntegerField(default=0, validators=[MaxValueValidator(10),], null = True) meat_quantity = models.PositiveIntegerField(default=0, validators=[MaxValueValidator(10),],null = True) veg_quality = models.PositiveIntegerField(default=0, validators=[MaxValueValidator(10),],null = True) veg_quantity = models.PositiveIntegerField(default=0, validators=[MaxValueValidator(10),],null = True) dressing_quality = models.PositiveIntegerField(default=0, validators=[MaxValueValidator(10),],null = True) dressing_quantity = models.PositiveIntegerField(default=0, validators=[MaxValueValidator(10),],null = True) def __unicode__(self): return '%s' % self.sandwich_name def score(self): b_ql = int(self.bread_quality) m_ql = int(self.meat_quality) m_qt = int(self.meat_quantity) v_ql = int(self.veg_quality) v_qt = int(self.veg_quantity) d_ql = int(self.dressing_quality) d_qt = int(self.dressing_quantity) total = b_ql + m_ql + m_qt + v_ql + v_qt + d_ql + d_qt return total class Restaurant(models.Model): name = models.CharField( max_length=200, unique=True, ) address = models.CharField(max_length=500, null = True) website = models.CharField(max_length=200, null = True) phone_number = models.CharField(max_length=12, null = True) email = models.CharField(max_length=75, null = True) rating_info = models.ForeignKey( 'blog.rating', on_delete=models.CASCADE, null=True, blank = True, ) latitude = models.IntegerField( blank=True, null=True, ) longitude = models.IntegerField( blank=True, null=True, ) def __unicode__(self): return '%s' % self.name def get_lat_long(self): from googlemaps import GoogleMaps gmaps = GoogleMaps(italian-1489414695369) Address = self.address lat, lng = gmaps.address_to_latlng(address) self.latitude = lat self.longitude = lng save()

UTF-8

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false

3,074

py

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models.py

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0.639558

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112

kurodo/apiprueba

17,583,596,128,773

11fd527bb4ed0167cf1e1591b7391d99580f4e52

b41805d913e7bc0f09399bec558d7079863e331b

/catalogo/urls.py

ed0ac18afd608514b00565f422339fde25d38631

[]

no_license

https://github.com/kurodo/apiprueba

21fb5cd569ba2311d0f2de887c34ed0e8c065c98

7db0682f2b054dcfdbc4d98e713cb3b067651f09

refs/heads/master

2020-05-17T15:55:53.227062

2019-05-05T00:17:18

183,805,181

0

null

from django.urls import path, include from rest_framework import routers from .views import * router = routers.DefaultRouter() router.register(r'producto', ProductoViewSet) router.register(r'precio', PrecioProductoViewSet) router.register(r'variacion', VariacionViewSet) router.register(r'producto_variacion', ProdcutoVariacionViewSet) router.register(r'categoria', CategoriaViewSet) urlpatterns = [ path('', include(router.urls)), path('build/variaciones/<int:pk>/',CrearVariaciones.as_view()) ] urlpatterns += router.urls

UTF-8

Python

false

535

py

38

urls.py

36

0.781308

0

17

30.470588

66

mengyuqianxun/Python-Algorithm-interview

6,854,767,851,226

8150bdd89ac24e0504450d895cabe091697ec4be

fdfbcf4451f3f165ad6c897c74563dc1f04908db

/ch3_binary_tree/5.py

f2f7763f7f731f78996a097caa6eae12752983dd

[]

no_license

https://github.com/mengyuqianxun/Python-Algorithm-interview

3c9baac00657fea68786876706b526140c1f7799

95b6aa69fdffb2e8cbc696cc958d8d5ee8eb5c29

refs/heads/master

2020-08-29T06:50:37.178084

2020-02-17T03:11:48

217,958,936

4

1

null

import math class BiTNode: def __init__(self): self.data = None self.lchild = None self.rchild = None def array2tree(arr,start,end): root = None if end >= start: root = BiTNode() mid = math.floor((start + end +1)/2) root.data = arr[mid] root.lchild = array2tree(arr,start,mid-1) root.rchild = array2tree(arr,mid+1,end) else: root =None return root class Test: def __init__(self): self.pHead = None self.pEnd = None def BiT2List(self,root): if root == None: return #转换root的左子树 self.BiT2List(root.lchild) root.lchild = self.pEnd if self.pEnd == None: self.pHead = root else: self.pEnd.rchild = root self.pEnd = root self.BiT2List(root.rchild) if __name__ == "__main__": arr =[1,2,3,4,5,6,7] root = array2tree(arr,0,len(arr)-1) test = Test() print(u'双向链表正向遍历：') test.BiT2List(root) cur = test.pHead while cur != None: print(cur.data,end = ' ') cur = cur.rchild print('\n'+u'转换后双向链表逆向遍历：') cur = test.pEnd while cur != None: print(cur.data,end = ' ') cur = cur.lchild

UTF-8

Python

false

1,328

py

84

5.py

68

0.518838

0.502355

0

55

21.963636

49

2877992943/count_record

19,679,540,180,773

bfc7192cf95786ec3455a8b28e8f3de0dadcfd5a

fca9fbaae9bff52d5ebb9cbce424983734101143

/demo1028_tagitApp_QueryCleanData_chenyuTeam_walkRunRid_countRecord_ios.py

f4129a769e2470e2da3e54c04dd1903914e5bca0

[]

no_license

https://github.com/2877992943/count_record

c15383b38b10334eac482b49e3bcd3661acf6cc5

cfd53d30c606a9dadca9f9a33b66ad670b1934f9

refs/heads/master

2016-09-01T16:07:57.582265

2015-11-23T12:17:09

46,718,267

0

null

#!/usr/bin/env python # encoding=utf-8 """ tagit app android count the number of record for each data collector not visualize,cleaning,store data """ import numpy as np import cPickle,math,random from leancloud import Object from leancloud import Query import leancloud import time,os deviceId={'huawei':'ffffffff-c7a8-3cd1-ffff-ffffea16e571', 'xiaomi':'ffffffff-c7a7-c7d4-0000-000031a92fbe', 'mine':'ffffffff-c95d-196f-0000-00007e282437', 'chenyu':'ffffffff-c43f-692d-ffff-fffff4d57110', 'wangx':'ffffffff-c28a-1bf0-0000-00005e774605', 'zhangx':'ffffffff-f259-8a54-0000-0000300c3e8c', 'liyt':'ffffffff-c7a8-3c91-ffff-ffffa2dc21fc', 'donggy':'ffffffff-c95e-eae5-ffff-ffffce758366', 'hangwz':'ffffffff-c43f-77d4-0000-00001b78f081', 'wangf':'ffffffff-c7a8-3bf6-ffff-ffffb8d6d318', 'biany':'ffffffff-c28b-7966-0000-000049d75b84', 'liuxuan':'ffffffff-f259-8a2f-0000-0000040de9c1', 'wangzhenfang':'00000000-53a7-c4ef-ffff-fffffd609c24', 'cuiyajie':'ffffffff-910d-998f-0000-0000585e3d7e' } sensor_list=["magneticSensor","accelerometer","proximity"] inst_id_zhangnn_ios='L2OGFhzaHM2IbNzJ1NjEHceroElYVdk2' inst_id_chenyu_ios='yg80UzhxQFPPcwicTtU4lDTyP9IcqDs2' inst_id_lb_ios='G93jbBRhtiWVGFULyLR9gPHDjUkl3S3R' inst_id_zhangnn1_ios='GsjMrEReu1OC2wtkUpM5asbWEyJ5AdQ1' #######################each class generate fea c_list=['running','walking','riding','sitting','driving'] dataPath='/home/yr/magnetic_fea/data1027/' test_pack=11040#01234 #012 not sure walk |mod<15 rid | mod>=15 walkrun|but differ between people para_pack=0#1with liangbin riding into trainset class_type=c_list[1] ###########query label.data device=deviceId['wangzhenfang'] sensor=sensor_list[1] ##########query log.tracer txt_i=2 see_flag=True inst_id=inst_id_chenyu_ios ########## def generate_stamp(period): #[8,28,8,33]->[(2015, 10, 20, 22, 30, 0, 0, 0, 0),(2015, 10, 20, 22, 48, 0, 0, 0, 0)]->stamp dur= [(2015, period[0], period[1], period[2], period[3], 0, 0, 0, 0),\ (2015, period[4], period[5], period[6], period[7], 0, 0, 0, 0)] stamp_range0=[time2stamp(dur[0]),time2stamp(dur[1])] stamp_range=[t*1000 for t in stamp_range0] return stamp_range def time2stamp(t): #t = (2015, 9, 28, 12, 36, 38, 0, 0, 0) stamp = int(time.mktime( t )) ; return stamp def connect_db_label():#label.data import leancloud,cPickle appid = "ckjjqzf3jqwl8k1u4o10j2hqp0rm0q6ferqcfb0xpw00e8zl" appkey = "rn0qw8ib96xl0km63kylo6v5afuxclc8jti5ol8rx4kylqob" leancloud.init(appid, appkey) def connect_db_log():##sensor.log.tracer not label.sensor, import leancloud,cPickle appid = "9ra69chz8rbbl77mlplnl4l2pxyaclm612khhytztl8b1f9o" appkey = "1zohz2ihxp9dhqamhfpeaer8nh1ewqd9uephe9ztvkka544b" #appid = "ckjjqzf3jqwl8k1u4o10j2hqp0rm0q6ferqcfb0xpw00e8zl" #appkey = "rn0qw8ib96xl0km63kylo6v5afuxclc8jti5ol8rx4kylqob" leancloud.init(appid, appkey) ##################### def get_content(results):#result is from find() obs={}; r=results for i in range(1): #print type(r.get("events")) if len(r.get("events"))>=1: print r.get("motion"),r.get("events").__len__() ll=r.get("events") #ll=[ {},{}...] for dic in ll[:]:#dic={timestamp:xxxx,value:[1,2,3]...} #print dic["timestamp"],' ',dic["values"][0],' ',dic["values"][1],' ',dic["values"][2] if dic["timestamp"] not in obs.keys(): obs[ dic["timestamp"] ]=[r.get("motion"),\ dic["values"][0],dic["values"][1],dic["values"][2] ] ###data form: {timestamp:[obs],...} [obs]=[motion,x,y,z] ########################### """ for k,v in obs.items(): print k,' ',v """ print 'final',obs.__len__() #print 'i',i,count #query-has-limit100,real-count=320 ###################3 return obs def get_all(query,skip,result): limit=500 query.limit(limit) query.skip(skip) found=query.find() if found and len(found)>0: result.extend(found) print 'av_utils get all,now result len:',len(result),'skip',skip return get_all(query,skip+limit,result) else: return result def save2pickle(c,name): write_file=open(dataPath+str(name),'wb') cPickle.dump(c,write_file,-1)#[ (timestamp,[motion,x,y,z]),...] write_file.close() def load_pickle(path_i): f=open(path_i,'rb') data=cPickle.load(f)#[ [time,[xyz],y] ,[],[]...] f.close() #print data.__len__(),data[0] return data def see_record_num(period_label_dic): valid_num=0 ####init connect_db_log() log = leancloud.Object.extend('Log') log_query = leancloud.Query(log) #print 'all',log_query.count()##error inst_query = leancloud.Query(leancloud.Installation) #print 'install',inst_query.count()#2335 inst = inst_query.equal_to('objectId', inst_id).find();#print '1',inst[0] # for label,periods in period_label_dic.items(): for period in periods: stamp_range=generate_stamp(period) #################each period log_query.equal_to('installation', inst[0]).equal_to("type",'sensor').\ less_than("timestamp", stamp_range[1]).greater_than("timestamp",stamp_range[0]) print label,period,'count',log_query.count() if log_query.count()>0:valid_num+=log_query.count() print 'total valid count',valid_num def remove_punct(line): for punct in ['.','-',':','/','\\']: if punct in line:line=line.replace(punct,' ') return line ############3 if __name__=="__main__": txt_path='/home/yr/magnetic_fea/txt_1123/' period_label={}; for filename in os.listdir(txt_path)[txt_i:txt_i+1]: print 'file '+filename inpath=txt_path+filename content=open(inpath,'r') line=content.readline().strip('\n').strip('\r').strip(' ') #period=[0,0,0,0,0,0,0,0]#month day minu sec .... while line: line=remove_punct(line) line=line.split(' ');print line period=[int(line[0]),int(line[1]),int(line[2]),int(line[3]),\ int(line[0]),int(line[1]),int(line[4]),int(line[5])] label=line[-1] if label not in period_label: period_label[label]=[period] elif label in period_label: period_label[label].append(period) #####next line=content.readline().strip('\n').strip('\r').strip(' ') ################### for k,v in period_label.items():#{label:[period,p,...],label:{}... print k,v.__len__() #########see valid record if see_flag==True : see_record_num(period_label) elif see_flag==False:print 'file '+filename

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demo1028_tagitApp_QueryCleanData_chenyuTeam_walkRunRid_countRecord_ios.py

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ohjho/pyp-w1-gw-language-detector

3,762,391,372,115

43d54a81c4a6636972bcb519188cdebf60cc6d2b

23c333a9db3bedf1688a346bf1573e2f5bd34117

/language_detector/main.py

c39596f4d92bac9f2427cb78c0c74dfafbd361ab

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permissive

https://github.com/ohjho/pyp-w1-gw-language-detector

ee5215e35dea4a304fefe77c6a58c77bce37b1c1

d40f9ab7b02eb568208c02a8add591a81b627236

refs/heads/master

2021-01-23T10:56:34.334393

2017-06-02T02:18:48

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2017-06-01T23:56:54

2017-01-12T23:09:17

2017-06-01T23:29:51

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0

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# -*- coding: utf-8 -*- def detect_language(text, languages): """Returns the detected language of given text.""" count = {} for language in languages: matches = (len(set(text.split(' ')) & set(language['common_words']))) count[language['name']] = matches return max(count, key=count.get)

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main.py

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h-mayorquin/mnist_deep_neural_network_BPNNs

9,500,467,661,736

3b1d73bd2a961ffa0f686f1e0d7d42812d8a511e

a5aa4c7d0b7b2a6202c1befadd11a4a31d571da1

/distort_pattern.py

4275c3c6cc4172597e08ac47102c25f4db06ce6e

[]

no_license

https://github.com/h-mayorquin/mnist_deep_neural_network_BPNNs

793b60985df41f4895e266829b8308bbf62952dd

a679e09b5f5b18ce95282e6963662ab700c227d6

refs/heads/master

2021-01-01T19:47:19.908058

2015-05-08T16:57:37

31,664,159

1

0

null

import numpy as np import matplotlib.pyplot as plt from load_binary_files import training_ims, training_labels from corrupt_functions import distort_binnary from copy import deepcopy # Select quantity of data to use N_data_total = len(training_labels) percentage = 0.01 N_to_use = int(percentage * N_data_total) # Decide how much data to use X = training_ims[0:N_to_use] Y = training_labels[0:N_to_use] N_hypercolumns = X.shape[1] units_per_hypercolumn = 2 index = 0 size = 28 percentage = 0.1 pattern = deepcopy(X[index]) dis_pattern = distort_binnary(index, percentage, X) plt.subplot(1, 3, 1) plt.title('Corrupted') plt.imshow(dis_pattern.reshape((size, size))) plt.subplot(1, 3, 2) plt.title('Normal pattern') plt.imshow(pattern.reshape((size, size))) plt.subplot(1, 3, 3) plt.title('Normal should be') plt.imshow(X[index].reshape((size, size))) plt.show()

UTF-8

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false

867

py

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distort_pattern.py

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TheClearwind/DeepISP

1,228,360,690,722

5a3fae6bb03628b93bdb2cea8b2499dbdcd1edca

3a37356348b1961a70dac753980c61e21a7ae725

/utils.py

936648a6bd9a083ea261ce16a58beb617b73277d

[]

no_license

https://github.com/TheClearwind/DeepISP

cf328be53ba42ca5ba929fd56bd5f33bdc582eef

0e88c8915eab0723989a5f8632b09f2fa57d240d

refs/heads/master

2022-11-23T06:43:51.022142

2020-07-15T06:44:21

279,495,723

8

0

null

import numpy as np def extract_bayer_channels(raw): # RGGB模式 ch_B = raw[1::2, 1::2] ch_Gb = raw[0::2, 1::2] ch_R = raw[0::2, 0::2] ch_Gr = raw[1::2, 0::2] return ch_R, ch_Gr, ch_B, ch_Gb def extract_bayer_channels_v2(raw): # RGGB模式 ch_R = np.zeros_like(raw) ch_G = np.zeros_like(raw) ch_B = np.zeros_like(raw) ch_B[1::2, 1::2] = raw[1::2, 1::2] ch_R[0::2, 0::2] = raw[0::2, 0::2] ch_G[0::2, 1::2] = raw[0::2, 1::2] ch_G[1::2, 0::2] = raw[1::2, 0::2] return ch_R, ch_G, ch_B def pack_raw(raw): ch_B, ch_Gb, ch_R, ch_Gr = extract_bayer_channels(raw) packed = np.dstack((ch_B, ch_Gb, ch_R, ch_Gr)) packed = np.transpose(packed, [2, 0, 1]) return packed def pack_raw_v2(raw): ch_R, ch_G, ch_B = extract_bayer_channels_v2(raw) packed = np.dstack((ch_R, ch_G, ch_B)) packed = np.transpose(packed, [2, 0, 1]) return packed if __name__ == '__main__': raw = np.random.randn(224, 224) packed = pack_raw_v2(raw) print(packed.shape)

UTF-8

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utils.py

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Sovetnikov/livelock

2,413,771,641,869

7e88346d92d017aba1a4973a11d39333d2302304

6b6a99d78765d71b1024c3876753013cb3cb0398

/livelock/server.py

816cf39bbb09849538eee4f0ced410c3be7bd101

[]

no_license

https://github.com/Sovetnikov/livelock

a8beead745405f957576e6f8e2af0e82b1436c6a

237b01c2ab2efebf5e74c2a5653ca5168ede65dd

refs/heads/master

2022-12-24T14:46:43.013963

2022-12-14T15:32:24

193,243,160

0

null

import asyncio import logging import os import signal import socket import time import uuid from asyncio import StreamReader, IncompleteReadError, Event from timeit import default_timer from livelock.memory_storage import InMemoryLockStorage from livelock.shared import DEFAULT_RELEASE_ALL_TIMEOUT, DEFAULT_BIND_TO, DEFAULT_LIVELOCK_SERVER_PORT, get_settings, DEFAULT_MAX_PAYLOAD, pack_resp, DEFAULT_SHUTDOWN_SUPPORT, \ DEFAULT_PROMETHEUS_PORT, DEFAULT_TCP_KEEPALIVE_TIME, DEFAULT_TCP_KEEPALIVE_INTERVAL, DEFAULT_TCP_KEEPALIVE_PROBES, DEFAULT_LOGLEVEL, DEFAULT_DISABLE_DUMP_LOAD, \ DEFAULT_TCP_USER_TIMEOUT_SECONDS, DEFAULT_MAINTENANCE_TIMEOUT_MS, DEFAULT_MAINTENANCE_PERIOD, get_float_settings, get_int_settings, SERVER_TERMINATING, CONN_HAS_ID_ERROR, \ WRONG_ARGS, CONN_REQUIRED_ERROR, UNKNOWN_COMMAND_ERROR, PASS_ERROR, ERRORS, LazyArg from livelock.stats import latency, max_lock_live_time, stats_collection_time, prometheus_client_installed, maintenance_time, stats_collection_count, maintenance_count, lock_count from livelock.storage import LockStorage from livelock.tcp_opts import set_tcp_keepalive ABSOLUTE_PATH = lambda x: os.path.abspath(os.path.join(os.path.abspath(os.path.dirname(__file__)), x)) logger = logging.getLogger(__name__) # Надо сделать # 3. Протоколирование длительности операций # 4. Хранение clientinfo class StorageAdaptor(LockStorage): def __init__(self, store): self.store = store self.kill_active = False self._storage_operations_in_process = 0 self._commands_in_process = 0 self._data_dumped = False self._maintenance_event = Event() signal.signal(signal.SIGINT, self._on_kill_requested) signal.signal(signal.SIGTERM, self._on_kill_requested) super().__init__() def terminate(self): self._on_kill_requested() def on_storage_operation_start(self): self._storage_operations_in_process += 1 def on_storage_operation_end(self): self._storage_operations_in_process -= 1 if self._storage_operations_in_process < 0: raise Exception('Storage active operations counter broken') if self.kill_active and not self._storage_operations_in_process: # Last storage operation ended, good point to dump storage data # then exit() after sending replies to clients self.dump_before_die() def is_commands_in_process(self): return self._commands_in_process > 0 async def on_command_start(self): await self._maintenance_event.wait() self._commands_in_process += 1 def on_command_end(self): self._commands_in_process -= 1 if self.kill_active and not self._commands_in_process: if self._storage_operations_in_process: logger.error('Last command executed, but storage operations counter has value') self.die() def _on_kill_requested(self, *args, **kwargs): # Must wait for active commands to complete, then dump data, close all connections and exit self.kill_active = True logger.info('Received terminate signal %s %s', args, kwargs) if not self._storage_operations_in_process: # Good time to dump and exit(), but there is chance that some client's will not get their responses self.dump_before_die() # In case any storage operations is in progress, we will dump data after last operations completes # and will exit() when last reply is sent if not self._commands_in_process: self.die() def dump_before_die(self): # Just dump data, because all storage operations ended self.store.dump() self._data_dumped = True logger.debug('Dumped data') def die(self): # All commands processed, can exit safely if not self._data_dumped: self.store.dump() logger.debug('Exit') exit(1) def acquire(self, *args, **kwargs): with StorageOperationGuard(self): return self.store.acquire(*args, **kwargs) def release(self, *args, **kwargs): with StorageOperationGuard(self): return self.store.release(*args, **kwargs) def release_all(self, client_id): with StorageOperationGuard(self): return self.store.release_all(client_id=client_id, timeout=self.release_all_timeout) def unrelease_all(self, *args, **kwargs): with StorageOperationGuard(self): return self.store.unrelease_all(*args, **kwargs) def locked(self, *args, **kwargs): return self.store.locked(*args, **kwargs) def set_client_last_address(self, *args, **kwargs): with StorageOperationGuard(self): return self.store.set_client_last_address(*args, **kwargs) def add_signal(self, *args, **kwargs): with StorageOperationGuard(self): return self.store.add_signal(*args, **kwargs) def has_signal(self, *args, **kwargs): return self.store.has_signal(*args, **kwargs) def remove_signal(self, *args, **kwargs): with StorageOperationGuard(self): return self.store.remove_signal(*args, **kwargs) def get_client_last_address(self, *args, **kwargs): return self.store.get_client_last_address(*args, **kwargs) def find(self, *args, **kwargs): return self.store.find(*args, **kwargs) def dump(self): return self.store.dump() def load_dump(self): return self.store.load_dump() def clear_dump(self): return self.store.clear_dump() def stats(self): return self.store.stats() def maintenance(self, *args, **kwargs): logger.debug('Doing maintenance') try: self._maintenance_event.clear() return self.store.maintenance(*args, **kwargs) finally: self._maintenance_event.set() class CommandProtocol(asyncio.Protocol): def __init__(self, tcp_keepalive_time=None, tcp_keepalive_interval=None, tcp_keepalive_probes=None, tcp_user_timeout_seconds=None, *args, **kwargs): self.transport = None self._reader = None """ https://blog.cloudflare.com/when-tcp-sockets-refuse-to-die/ http://coryklein.com/tcp/2015/11/25/custom-configuration-of-tcp-socket-keep-alive-timeouts.html Keep-Alive Process There are three configurable properties that determine how Keep-Alives work. On Linux they are1: tcp_keepalive_time default 7200 seconds tcp_keepalive_probes default 9 tcp_keepalive_intvl default 75 seconds The process works like this: 1. Client opens TCP connection 2. If the connection is silent for tcp_keepalive_time seconds, send a single empty ACK packet.1 3. Did the server respond with a corresponding ACK of its own? - No 1. Wait tcp_keepalive_intvl seconds, then send another ACK 2. Repeat until the number of ACK probes that have been sent equals tcp_keepalive_probes. 3. If no response has been received at this point, send a RST and terminate the connection. - Yes: Return to step 2 """ self.tcp_keepalive_time = int(tcp_keepalive_time) self.tcp_keepalive_interval = int(tcp_keepalive_interval) self.tcp_keepalive_probes = int(tcp_keepalive_probes) self.tcp_user_timeout_seconds = int(tcp_user_timeout_seconds) super().__init__(*args, **kwargs) def data_received(self, data): if self.kill_active: return self._reader.feed_data(data) def connection_made(self, transport): if self.kill_active: return sock = transport.get_extra_info('socket') set_tcp_keepalive(sock, opts=dict(tcp_keepalive=True, tcp_keepalive_idle=self.tcp_keepalive_time, tcp_keepalive_intvl=self.tcp_keepalive_interval, tcp_keepalive_cnt=self.tcp_keepalive_probes, )) # https://eklitzke.org/the-caveats-of-tcp-nodelay sock.setsockopt(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1) if hasattr(socket, 'TCP_USER_TIMEOUT'): logger.debug('Setting TCP_USER_TIMEOUT to %s', self.tcp_user_timeout_seconds * 1000) sock.setsockopt(socket.SOL_TCP, socket.TCP_USER_TIMEOUT, self.tcp_user_timeout_seconds * 1000) self.transport = transport self._reader = StreamReader() self._reader.set_transport(transport) loop = asyncio.get_event_loop() loop.create_task(self.receive_commands()) super().connection_made(transport) def connection_lost(self, exc): if self.kill_active: return if self._reader is not None: if exc is None: self._reader.feed_eof() else: self._reader.set_exception(exc) super().connection_lost(exc) def eof_received(self): if self.kill_active: return self._reader.feed_eof() return super().eof_received() async def _read_int(self): if self.kill_active: return line = await self._reader.readuntil(b'\r\n') return int(line.decode().strip()) async def _read_float(self): if self.kill_active: return line = await self._reader.readuntil(b'\r\n') return float(line.decode().strip()) async def _read_bytes(self): if self.kill_active: return len = await self._read_int() line = await self._reader.readexactly(max(2, len + 2)) if line[-1] != ord(b'\n'): raise Exception(r"line[-1] != ord(b'\n')") if line[-2] != ord(b'\r'): raise Exception(r"line[-2] != ord(b'\r')") if len < 0: return None if len == 0: return b'' return line[:-2] async def _read_array(self): if self.kill_active: return len = await self._read_int() r = [] while len: c = await self._reader.readexactly(1) value = await self._receive_resp(c) r.append(value) len -= 1 return r async def _receive_resp(self, c): if self.kill_active: return if c == b':': return await self._read_int() elif c == b'$': return await self._read_bytes() elif c == b'*': return await self._read_array() elif c == b',': return await self._read_float() else: raise Exception('Unknown RESP start char %s' % c) async def receive_commands(self): while True: if self.kill_active: self.reply_terminating() return try: c = await self._reader.readexactly(1) if c in b':*$,': value = await self._receive_resp(c) if not isinstance(value, list): value = [value, ] else: command = c + await self._reader.readuntil(b'\r\n') value = [x.strip().encode() for x in command.decode().split(' ')] except (ConnectionAbortedError, ConnectionResetError, IncompleteReadError, TimeoutError) as e: # Connection is closed self.receive_commands_end(e) return await self.on_command_received(*value) async def on_command_received(self, command): raise NotImplemented() def reply_terminating(self): raise NotImplemented() def receive_commands_end(self, exc): raise NotImplemented() class LiveLockProtocol(CommandProtocol): def __init__(self, adaptor, password, max_payload, shutdown_support=False, *args, **kwargs): self.password = password self.adaptor = adaptor self.max_payload = max_payload self.client_id = None self.client_info = None self.shutdown_support = shutdown_support self._authorized = None self.transport = None self.debug = get_settings(None, 'LIVELOCK_DEBUG', False) self.lazy_client_display = LazyArg(self.client_display) super().__init__(*args, **kwargs) def client_display(self): if self.transport: peername = self.transport.get_extra_info('peername') else: peername = 'no_peer_address' return f'{peername} ({self.client_info}), client={self.client_id}' def connection_made(self, transport): if self.adaptor.kill_active: return logger.debug('Connection from %s', LazyArg(lambda: transport.get_extra_info('peername'))) self.transport = transport super().connection_made(transport) def receive_commands_end(self, exc): logger.debug('Receive command loop ended for %s, Exception=%s', self.lazy_client_display, exc) def eof_received(self): logger.debug('EOF received for %s', self.lazy_client_display) return super().eof_received() def connection_lost(self, exc): peername = self.transport.get_extra_info('peername') if self.adaptor.kill_active: logger.debug('Connection lost on active kill %s client=%s, Exception=%s', self.lazy_client_display, self.client_id, exc) return logger.debug('Connection lost %s, Exception=%s', self.lazy_client_display, exc) if self.client_id: last_address = self.adaptor.get_client_last_address(self.client_id) if last_address is None: logger.warning('Client last address is empty') if (last_address and last_address == peername) or last_address is None: # Releasing all client locks only if last known connection is dropped # other old connection can be dead self.adaptor.release_all(self.client_id) super().connection_lost(exc) @property def kill_active(self): return self.adaptor.kill_active async def on_command_received(self, command, *args): st = default_timer() verb = 'unknown' try: verb = await self.process_command(command, *args) finally: latency.labels(verb if verb is not None else 'unknown').observe(max(default_timer() - st, 0)) async def process_command(self, command, *args): if self.kill_active: self.reply_terminating() return peername = self.transport.get_extra_info('peername') verb = command.decode().lower() logger.debug('Got command %s from %s', command, self.lazy_client_display) await self.adaptor.on_command_start() try: if self.password and not self._authorized: if verb == 'pass': if len(args) == 1 and args[0]: password = args[0].decode() if password == self.password: self._authorized = True self._reply(True) return self._reply(PASS_ERROR) self.transport.close() if verb == 'conn': if self.client_id: self._reply(CONN_HAS_ID_ERROR) if args: if not args[0]: self._reply(WRONG_ARGS) return self.client_id = args[0].decode() # Restoring client locks self.adaptor.unrelease_all(self.client_id) else: self.client_id = str(uuid.uuid4()) # Saving client last connection source address for making decision to call release_all on connection lost self.adaptor.set_client_last_address(self.client_id, peername) self._reply(self.client_id) return else: if not self.client_id: self._reply(CONN_REQUIRED_ERROR) return if verb == 'conninfo': if len(args) != 1 or not args[0]: self._reply(WRONG_ARGS) return try: client_info = args[0].decode() except: self._reply(WRONG_ARGS) return logger.debug('Got client info for %s = %s', self.lazy_client_display, client_info) if self.client_info: if self.client_info != client_info: logger.warning('Client info changed for %s', self.lazy_client_display) self.client_info = client_info self._reply(True) elif verb in ('aq', 'aqr'): if len(args) != 1 or not args[0]: self._reply(WRONG_ARGS) return try: lock_id = args[0].decode() except: self._reply(WRONG_ARGS) return res = self.acquire(client_id=self.client_id, lock_id=lock_id, reentrant=(verb == 'aqr')) self._reply(res) elif verb == 'release': if len(args) != 1 or not args[0]: self._reply(WRONG_ARGS) return try: lock_id = args[0].decode() except: self._reply(WRONG_ARGS) return res = self.release(client_id=self.client_id, lock_id=lock_id) self._reply(res) elif verb == 'locked': if len(args) != 1 or not args[0]: self._reply(WRONG_ARGS) return try: lock_id = args[0].decode() except: self._reply(WRONG_ARGS) return res = self.locked(lock_id=lock_id) self._reply(res) elif verb == 'sigset': if len(args) != 2 or not args[0] or not args[1]: self._reply(WRONG_ARGS) return try: lock_id = args[0].decode() signal = args[1].decode() except: self._reply(WRONG_ARGS) return res = self.add_signal(lock_id, signal) self._reply(res) elif verb == 'sigexists': if len(args) != 2 or not args[0] or not args[1]: self._reply(WRONG_ARGS) return try: lock_id = args[0].decode() signal = args[1].decode() except: self._reply(WRONG_ARGS) return res = self.has_signal(lock_id, signal) self._reply(res) elif verb == 'sigdel': if len(args) != 2 or not args[0] or not args[1]: self._reply(WRONG_ARGS) return try: lock_id = args[0].decode() signal = args[1].decode() except: self._reply(WRONG_ARGS) return res = self.remove_signal(lock_id, signal) self._reply(res) elif verb == 'ping': self._reply('PONG') elif verb == 'find': if len(args) != 1 or not args[0]: self._reply(WRONG_ARGS) return result = list(self.adaptor.find(args[0].decode())) self._reply_data(result) elif verb == 'stats': if len(args): self._reply(WRONG_ARGS) return result = self.adaptor.stats() self._reply_data(result) elif verb == 'shutdown' and self.shutdown_support: logger.debug('SHUTDOWN invoked by %s', self.lazy_client_display) self.adaptor.terminate() self._reply('1') else: if self.debug: if verb == 'dump': if hasattr(self.adaptor, 'dump'): self.adaptor.dump() self._reply('1') else: self._reply('0') return self._reply(UNKNOWN_COMMAND_ERROR) finally: self.adaptor.on_command_end() # For stats returning verb return verb def _reply_data(self, data): payload = pack_resp(data) self.transport.write(payload) def reply_terminating(self): self._reply(SERVER_TERMINATING) def _reply(self, content): prefix = '+' if content is True: content = '1' elif content is False: content = '0' elif isinstance(content, int): content = '%s %s' % (content, ERRORS[content]) prefix = '-' payload = '%s%s\r\n' % (prefix, content) payload = payload.encode() self.transport.write(payload) def acquire(self, client_id, lock_id, reentrant): res = self.adaptor.acquire(client_id, lock_id, reentrant) return res def release(self, client_id, lock_id): res = self.adaptor.release(client_id, lock_id) return res def locked(self, lock_id): res = self.adaptor.locked(lock_id) return res def add_signal(self, lock_id, signal): res = self.adaptor.add_signal(lock_id, signal.lower()) return res def has_signal(self, lock_id, signal): res = self.adaptor.has_signal(lock_id, signal.lower()) return res def remove_signal(self, lock_id, signal): res = self.adaptor.remove_signal(lock_id, signal.lower()) return res class StorageOperationGuard(object): def __init__(self, parent): self.parent = parent def __enter__(self): if self.parent.kill_active: raise Exception('Lock storage write operations disabled') self.parent.on_storage_operation_start() def __exit__(self, exc_type, exc_val, exc_tb): self.parent.on_storage_operation_end() async def stats_collector(adaptor): while True: st = time.time() max_live_lock = 0 locks = list(adaptor.find('*')) if locks: now = time.time() first_lock = min(locks, key=lambda x: x[1]) max_live_lock = int(now - first_lock[1]) lock_count.set(len(locks)) max_lock_live_time.set(max_live_lock) stats_collection_time.inc(time.time() - st) stats_collection_count.inc() await asyncio.sleep(5) async def maintenance_scheduler(adaptor, period, timeout_ms): """ "Sampling" scheduler of maintenance call """ logger.debug('Starting maintenance scheduler, period %s, timeout_ms %s', period, timeout_ms) while True: if not adaptor.is_commands_in_process() and not adaptor.kill_active: # Can do maintenance st = time.time() adaptor.maintenance(timeout_ms=timeout_ms) ed = time.time() t = (ed - st) * 1000 logger.debug('Maintenance time %s ms', t) if t > timeout_ms: logger.warning('Maintenance timeout exceeded, configured=%s ms, actual=%s ms, ', timeout_ms, t) maintenance_time.inc(t) maintenance_count.inc() else: logger.debug('Skipping maintenance') await asyncio.sleep(period) async def live_lock_server(bind_to, port, release_all_timeout, password=None, max_payload=None, data_dir=None, shutdown_support=None, tcp_keepalive_time=None, tcp_keepalive_interval=None, tcp_keepalive_probes=None, tcp_user_timeout_seconds=None, disable_dump_load=None, ): # Sanitize values tcp_keepalive_time = int(tcp_keepalive_time) if tcp_keepalive_time else None tcp_keepalive_interval = int(tcp_keepalive_interval) if tcp_keepalive_interval else None tcp_keepalive_probes = int(tcp_keepalive_probes) if tcp_keepalive_probes else None tcp_user_timeout_seconds = int(tcp_user_timeout_seconds) if tcp_user_timeout_seconds else None loop = asyncio.get_running_loop() try: port = int(port) except: raise Exception(f'Live lock server port is not integer: {port}') if data_dir: os.chdir(data_dir) else: data_dir = os.getcwd() storage = InMemoryLockStorage(release_all_timeout=release_all_timeout) if not disable_dump_load: logger.info('Loading dump') storage.load_dump() stats = storage.stats() logger.info('Locks loaded from dump: %s', stats.get("lock_count", 0)) logger.info('Starting live lock server at %s, %s', bind_to, port) logger.debug('release_all_timeout=%s', release_all_timeout) logger.debug('data_dir=%s', data_dir) adaptor = StorageAdaptor(storage) server = await loop.create_server(lambda: LiveLockProtocol(adaptor=adaptor, password=password, max_payload=max_payload, shutdown_support=shutdown_support, tcp_keepalive_time=tcp_keepalive_time, tcp_keepalive_interval=tcp_keepalive_interval, tcp_keepalive_probes=tcp_keepalive_probes, tcp_user_timeout_seconds=tcp_user_timeout_seconds, ), bind_to, port) def exception_handler(loop, context): if not isinstance(context['exception'], SystemExit): raise context['exception'] loop.set_exception_handler(exception_handler) if prometheus_client_installed: stats_collector_task = loop.create_task(stats_collector(adaptor)) maintenance_scheduler_task = loop.create_task(maintenance_scheduler(adaptor, period=get_float_settings(None, 'LIVELOCK_MAINTENANCE_PERIOD', DEFAULT_MAINTENANCE_PERIOD), timeout_ms=get_int_settings(None, 'LIVELOCK_MAINTENANCE_TIMEOUT_MS', DEFAULT_MAINTENANCE_TIMEOUT_MS))) async with server: await server.serve_forever() if prometheus_client_installed: stats_collector_task.cancel() maintenance_scheduler_task.cancel() def start(bind_to=DEFAULT_BIND_TO, port=None, release_all_timeout=None, password=None, max_payload=None, data_dir=None, shutdown_support=None, tcp_keepalive_time=None, tcp_keepalive_interval=None, tcp_keepalive_probes=None, tcp_user_timeout_seconds=None, disable_dump_load=None, ): sentry_dsn = get_settings(None, 'SENTRY_DSN', None) if sentry_dsn: logger.debug('Turning ON sentry') try: import sentry_sdk sentry_sdk.init(dsn=sentry_dsn) except ImportError: logger.error('No sentry-sdk installed') env_loglevel = get_settings(None, 'LIVELOCK_LOGLEVEL', DEFAULT_LOGLEVEL) loglevel = getattr(logging, env_loglevel.upper()) logging.basicConfig(level=loglevel, format='%(name)s:[%(levelname)s]: %(message)s') prometheus_port = get_settings(port, 'LIVELOCK_PROMETHEUS_PORT', DEFAULT_PROMETHEUS_PORT) if prometheus_port: try: prometheus_port = int(prometheus_port) except: logger.critical('Wrong prometheus port %s', prometheus_port) prometheus_port = None if prometheus_port: try: from prometheus_client import start_http_server except ImportError: logger.info('Prometheus port is set but prometheus_client not installed (pip install prometheus-client)') prometheus_port = None if prometheus_port: logger.info('Starting prometheus metrics server at port %s', prometheus_port) start_http_server(prometheus_port) asyncio.run(live_lock_server(bind_to=get_settings(bind_to, DEFAULT_BIND_TO, 'LIVELOCK_BIND_TO'), port=get_settings(port, 'LIVELOCK_PORT', DEFAULT_LIVELOCK_SERVER_PORT), release_all_timeout=get_settings(release_all_timeout, 'LIVELOCK_RELEASE_ALL_TIMEOUT', DEFAULT_RELEASE_ALL_TIMEOUT), password=get_settings(password, 'LIVELOCK_PASSWORD', None), max_payload=get_settings(max_payload, 'LIVELOCK_MAX_PAYLOAD', DEFAULT_MAX_PAYLOAD), data_dir=get_settings(data_dir, 'LIVELOCK_DATA_DIR', None), shutdown_support=get_settings(shutdown_support, 'LIVELOCK_SHUTDOWN_SUPPORT', DEFAULT_SHUTDOWN_SUPPORT), tcp_keepalive_time=get_settings(tcp_keepalive_time, 'LIVELOCK_TCP_KEEPALIVE_TIME', DEFAULT_TCP_KEEPALIVE_TIME), tcp_keepalive_interval=get_settings(tcp_keepalive_interval, 'LIVELOCK_TCP_KEEPALIVE_INTERVAL', DEFAULT_TCP_KEEPALIVE_INTERVAL), tcp_keepalive_probes=get_settings(tcp_keepalive_probes, 'LIVELOCK_TCP_KEEPALIVE_PROBES', DEFAULT_TCP_KEEPALIVE_PROBES), tcp_user_timeout_seconds=get_settings(tcp_user_timeout_seconds, 'LIVELOCK_TCP_USER_TIMEOUT_SECONDS', DEFAULT_TCP_USER_TIMEOUT_SECONDS), disable_dump_load=get_settings(disable_dump_load, 'LIVELOCK_DISABLE_DUMP_LOAD', DEFAULT_DISABLE_DUMP_LOAD), ))

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/oneflow_onnx/oneflow2onnx/handlers/math.py

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[]

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https://github.com/Oneflow-Inc/oneflow_convert_tools

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2023-03-07T07:38:58

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""" Copyright 2020 The OneFlow Authors. All rights reserved. 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. """ # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT license. from __future__ import division from __future__ import print_function from __future__ import unicode_literals from __future__ import absolute_import import logging import math import oneflow import numpy as np from onnx import onnx_pb from onnx import TensorProto from oneflow_onnx import constants, util from oneflow_onnx.oneflow2onnx.handler import flow_op from oneflow_onnx.oneflow2onnx.handlers import common logger = logging.getLogger(__name__) # pylint: disable=unused-argument,missing-docstring @flow_op(["broadcast_add", "scalar_add_by_tensor"], onnx_op="Add") @flow_op(["broadcast_sub", "scalar_sub_by_tensor"], onnx_op="Sub", flow_ibns=["x", "y"]) @flow_op(["multiply", "broadcast_mul", "scalar_mul_by_tensor"], onnx_op="Mul") @flow_op(["broadcast_div", "scalar_div_by_tensor"], onnx_op="Div", flow_ibns=["x", "y"]) class BroadcastOp(common.BroadcastOp): pass @flow_op("scalar_mul", "Mul") @flow_op("scalar_add", "Add") @flow_op("scalar_div", "Div") class ScalarBinaryOp: @classmethod def Version_6(cls, ctx, node, **kwargs): scalar_val = node.attrs["int_operand"] if node.attrs["has_int_operand"] else node.attrs["float_operand"] np_dtype = util.Onnx2NumpyDtype(ctx.get_dtype(node.input_tensor_names[0])) scalar_node = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("scalar"), np.array([scalar_val]).astype(np_dtype)) node.input_tensor_names.append(scalar_node.output_tensor_names[0]) @flow_op("add_n", onnx_op="Add") class AddN: @classmethod def Version_1(cls, ctx, node, **kwargs): input_length = len(node.input_tensor_names) if input_length <= 2: pass else: ctx.RemoveNode(node.name) ctx.MakeNode("Sum", node.input_tensor_names, outputs=[node.output_tensor_names[0]], op_name_scope=node.name, name="mul") @flow_op("bias_add", onnx_op="Add", flow_ibns=["a", "b"]) class BiasAdd(common.BroadcastOp): @classmethod def Version_6(cls, ctx, node, **kwargs): axis = node.attrs["axis"] unsqueeze_axes = [] x_rank = len(ctx.get_shape(node.input_tensor_names[0])) for i in range(x_rank): if axis != i: unsqueeze_axes.append(i) unsqueeze_shape = [1] * x_rank assert len(ctx.get_shape(node.input_tensor_names[1])) == 1 unsqueeze_shape[axis] = ctx.get_shape(node.input_tensor_names[1])[0] unsqueeze_dtype = ctx.get_dtype(node.input_tensor_names[1]) ctx.InsertNewNodeOnInput(node, "Unsqueeze", node.input_tensor_names[1], axes=unsqueeze_axes) ctx.set_shape(node.input_tensor_names[1], unsqueeze_shape) ctx.set_dtype(node.input_tensor_names[1], unsqueeze_dtype) super().Version_6(ctx, node, **kwargs) @classmethod def Version_13(cls, ctx, node, **kwargs): axis = node.attrs["axis"] unsqueeze_axes = [] x_rank = len(ctx.get_shape(node.input_tensor_names[0])) for i in range(x_rank): if axis != i: unsqueeze_axes.append(i) assert len(ctx.get_shape(node.input_tensor_names[1])) == 1 shape_node = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("shape"), np.array(unsqueeze_axes)) ctx.InsertNewNodeOnInput(node, "Unsqueeze", [node.input_tensor_names[1], shape_node.output_tensor_names[0]]) super().Version_6(ctx, node, **kwargs) @flow_op(["leaky_relu", "softplus"], onnx_op=["LeakyRelu", "Softplus"]) class DirectOpSinceOpset1: @classmethod def Version_1(cls, ctx, node, **kwargs): pass @flow_op("prelu", onnx_op="PRelu", flow_ibns=["x", "alpha"]) class PReLUOp: @classmethod def Version_1(cls, ctx, node, **kwargs): input_shape = ctx.get_shape(node.input_tensor_names[0]) alpha_shape = ctx.get_shape(node.input_tensor_names[1]) if len(alpha_shape) == 1: new_shape = [] new_shape.append(alpha_shape[0]) for _ in range(1, len(input_shape) - 1): new_shape.append(1) ctx.set_shape(node.input_tensor_names[1], new_shape) @flow_op( [ "abs", "ceil", "elu", "exp", "floor", "log", "neg", "sigmoid", "sigmoid_v2", "sqrt", "tanh", "reciprocal", "relu", ], [ "Abs", "Ceil", "Elu", "Exp", "Floor", "Log", "Neg", "Sigmoid", "Sigmoid", "Sqrt", "Tanh", "Reciprocal", "Relu", ], ) class DirectOp: @classmethod def Version_1(cls, ctx, node, **kwargs): pass @classmethod def Version_6(cls, ctx, node, **kwargs): pass @flow_op( ["acos", "asin", "atan", "cos", "sin", "tan"], ["Acos", "Asin", "Atan", "Cos", "Sin", "Tan"], ) class TrigOpSinceOpset7: @classmethod def Version_7(cls, ctx, node, **kwargs): pass @flow_op( ["acosh", "asinh", "atanh", "cosh", "sinh"], ["Acosh", "Asinh", "Atanh", "Cosh", "Sinh"], ) class TrigOpSinceOpset9: @classmethod def Version_9(cls, ctx, node, **kwargs): pass def _MakeMinOrMaxOp(ctx, op_type, inputs, outputs, output_shapes=None, output_dtypes=None): # support more dtype supported_dtypes = [ onnx_pb.TensorProto.FLOAT, onnx_pb.TensorProto.FLOAT16, onnx_pb.TensorProto.DOUBLE, ] target_dtype = onnx_pb.TensorProto.FLOAT need_cast = False cast_inputs = [] for inp in inputs: dtype = ctx.get_dtype(inp) util.MakeSure(dtype is not None, "dtype of {} is None".format(inp)) if dtype not in supported_dtypes: cast_inp = ctx.MakeNode("Cast", [inp], attr={"to": target_dtype}) cast_inputs.append(cast_inp.output_tensor_names[0]) need_cast = True else: cast_inputs.append(inp) node = ctx.MakeNode(op_type, cast_inputs, shapes=output_shapes) actual_outputs = node.output_tensor_names if need_cast: origin_dtype = ctx.get_dtype(inputs[0]) if output_dtypes is not None: origin_dtype = output_dtypes[0] ctx.set_dtype(node.output_tensor_names[0], target_dtype) cast_name = oneflow._oneflow_internal.UniqueStr(node.name) cast_node = ctx.InsertNewNodeOnOutput("Cast", node.output_tensor_names[0], name=cast_name, to=origin_dtype) ctx.set_dtype(cast_node.output_tensor_names[0], origin_dtype) ctx.CopyShape(node.output_tensor_names[0], cast_node.output_tensor_names[0]) actual_outputs = cast_node.output_tensor_names ctx.MakeNode( "Identity", actual_outputs, outputs=outputs, shapes=output_shapes, dtypes=output_dtypes, ) # onnx < opset 8 does not support broadcasting # handle this by doing something like: # y = min(x1, add(x2, sub(x1, x1))), where x1, x2 are the inputs and x2 is a scalar # this will create a tensor of zeros of the shape of x1, adds x2 to it (which broadcasts) and use that for min. shapeo = ctx.get_shape(node.output_tensor_names[0]) needs_broadcast_op = [] has_correct_shape = [] if ctx.opset < 8: for i, input_name in enumerate(node.input_tensor_names): if ctx.get_shape(input_name) != shapeo: needs_broadcast_op.append(i) else: has_correct_shape.append(input_name) if needs_broadcast_op: has_correct_shape = has_correct_shape[0] for i in needs_broadcast_op: input_node = node.input_nodes[i] # get a tensor with zeros (since there is no Fill op as of opset8) sub_node = ctx.MakeNode( "Sub", [has_correct_shape, has_correct_shape], op_name_scope=input_node.name, ) # use add as 'broadcast' op add_node = ctx.MakeNode( "Add", [input_node.output_tensor_names[0], sub_node.output_tensor_names[0]], op_name_scope=input_node.name, ) node.input_tensor_names[i] = add_node.output_tensor_names[0] @flow_op("broadcast_minimum", onnx_op="Min") @flow_op("broadcast_maximum", onnx_op="Max") @flow_op("elementwise_minimum", onnx_op="Min") @flow_op("elementwise_maximum", onnx_op="Max") class MinMaxOp: @classmethod def Version_1(cls, ctx, node, **kwargs): shapes = node.output_shapes dtypes = node.output_dtypes ctx.RemoveNode(node.name) _MakeMinOrMaxOp( ctx, node.op_type, node.input_tensor_names, node.output_tensor_names, shapes, dtypes, ) @flow_op("hardswish", onnx_op="HardSwish") class HardSwish: @classmethod def Version_1(cls, ctx, node, **kwargs): dtypes = node.output_dtypes node1 = ctx.MakeNode("HardSigmoid", [node.input_tensor_names[0]], op_name_scope=node.name, name="hard_sigmoid", dtypes=dtypes, attr={"alpha": 1.0 / 6}) ctx.RemoveNode(node.name) ctx.MakeNode("Mul", [node.input_tensor_names[0], node1.output_tensor_names[0]], outputs=[node.output_tensor_names[0]], op_name_scope=node.name, name="mul") @classmethod def Version_14(cls, ctx, node, **kwargs): pass @flow_op("silu", onnx_op="Mul") class Silu: @classmethod def Version_1(cls, ctx, node, **kwargs): dtypes = node.output_dtypes sigmoid_node = ctx.MakeNode("Sigmoid", [node.input_tensor_names[0]], op_name_scope=node.name, name="sigmoid", dtypes=dtypes) ctx.RemoveNode(node.name) ctx.MakeNode("Mul", [node.input_tensor_names[0], sigmoid_node.output_tensor_names[0]], outputs=[node.output_tensor_names[0]], op_name_scope=node.name, name="mul") @classmethod def Version_10(cls, ctx, node, **kwargs): cls.Version_1(ctx, node, **kwargs) @flow_op(["gelu", "fast_gelu", "quick_gelu"]) class Gelu: @classmethod def Version_9(cls, ctx, node, **kwargs): dtypes = node.output_dtypes if node.op_type == "fast_gelu": kBeta = math.sqrt(2 / math.pi) kKappa = 0.044715 beta = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("beta"), np.array(kBeta, dtype=util.Onnx2NumpyDtype(dtypes[0]))) kappa = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("kKappa"), np.array(kKappa, dtype=util.Onnx2NumpyDtype(dtypes[0]))) one = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("one"), np.array(1.0, dtype=util.Onnx2NumpyDtype(dtypes[0]))) half = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("half"), np.array(0.5, dtype=util.Onnx2NumpyDtype(dtypes[0]))) mul_node_1 = ctx.MakeNode("Mul", [node.input_tensor_names[0], node.input_tensor_names[0]], op_name_scope=node.name, name="mul1", dtypes=dtypes) cube = ctx.MakeNode("Mul", [node.input_tensor_names[0], mul_node_1.output_tensor_names[0]], op_name_scope=node.name, name="cube", dtypes=dtypes) mul_node_2 = ctx.MakeNode("Mul", [kappa.output_tensor_names[0], cube.output_tensor_names[0]], op_name_scope=node.name, name="mul2", dtypes=dtypes) add_node_1 = ctx.MakeNode("Add", [mul_node_2.output_tensor_names[0], node.input_tensor_names[0]], op_name_scope=node.name, name="add1", dtypes=dtypes) inner = ctx.MakeNode("Mul", [add_node_1.output_tensor_names[0], beta.output_tensor_names[0]], op_name_scope=node.name, name="inner", dtypes=dtypes) tanh_node = ctx.MakeNode("Tanh", [inner.output_tensor_names[0]], op_name_scope=node.name, name="tanh", dtypes=dtypes) add_node_2 = ctx.MakeNode("Add", [tanh_node.output_tensor_names[0], one.output_tensor_names[0]], op_name_scope=node.name, name="add2", dtypes=dtypes) mul_node_3 = ctx.MakeNode("Mul", [add_node_2.output_tensor_names[0], node.input_tensor_names[0]], op_name_scope=node.name, name="mul3", dtypes=dtypes) ctx.RemoveNode(node.name) ctx.MakeNode("Mul", [mul_node_3.output_tensor_names[0], half.output_tensor_names[0]], outputs=[node.output_tensor_names[0]], op_name_scope=node.name, name="mul4", dtypes=dtypes) elif node.op_type == "gelu": _sqrt2 = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("sqrt2"), np.array(1.4142135623730951, dtype=util.Onnx2NumpyDtype(dtypes[0]))) div1 = ctx.MakeNode("Div", [node.input_tensor_names[0], _sqrt2.output_tensor_names[0]], op_name_scope=node.name, name="div1", dtypes=dtypes) erf = ctx.MakeNode("Erf", [div1.output_tensor_names[0]], op_name_scope=node.name, name="erf", dtypes=dtypes) one = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("one"), np.array(1.0, dtype=util.Onnx2NumpyDtype(dtypes[0]))) erf_plusone = ctx.MakeNode("Add", [one.output_tensor_names[0], erf.output_tensor_names[0]], op_name_scope=node.name, name="erf_plusone", dtypes=dtypes) half = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("half"), np.array(0.5, dtype=util.Onnx2NumpyDtype(dtypes[0]))) mul_node_1 = ctx.MakeNode("Mul", [node.input_tensor_names[0], erf_plusone.output_tensor_names[0]], op_name_scope=node.name, name="mul1", dtypes=dtypes) ctx.RemoveNode(node.name) ctx.MakeNode("Mul", [mul_node_1.output_tensor_names[0], half.output_tensor_names[0]], outputs=[node.output_tensor_names[0]], op_name_scope=node.name, name="mul2", dtypes=dtypes) elif node.op_type == "quick_gelu": beta = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("beta"), np.array(1.702, dtype=util.Onnx2NumpyDtype(dtypes[0]))) mul_node_1 = ctx.MakeNode("Mul", [node.input_tensor_names[0], beta.output_tensor_names[0]], op_name_scope=node.name, name="mul1", dtypes=dtypes) sigmoid_node = ctx.MakeNode("Sigmoid", [mul_node_1.output_tensor_names[0]], op_name_scope=node.name, name="sigmoid", dtypes=dtypes) ctx.RemoveNode(node.name) ctx.MakeNode("Mul", [node.input_tensor_names[0], sigmoid_node.output_tensor_names[0]], outputs=[node.output_tensor_names[0]], op_name_scope=node.name, name="mul2", dtypes=dtypes) @flow_op("hardsigmoid", onnx_op="HardSigmoid") class HardSigmoid: @classmethod def Version_1(cls, ctx, node, **kwargs): node.attrs["alpha"] = 1.0 / 6 pass @flow_op("scalar_pow", onnx_op="Pow") class ScalarPow: @classmethod def Version_1(cls, ctx, node, **kwargs): np_dtype = util.Onnx2NumpyDtype(ctx.get_dtype(node.input_tensor_names[0])) if node.attrs["has_float_operand"]: y = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("start"), np.array(node.attrs["float_operand"]).astype(np_dtype)) node.input_tensor_names.append(y.output_tensor_names[0]) else: y = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("start"), np.array(node.attrs["int_operand"]).astype(np_dtype)) node.input_tensor_names.append(y.output_tensor_names[0]) @flow_op("scalar_logical_less", onnx_op="Less") @flow_op("scalar_logical_greater", onnx_op="Greater") class ScalarPow: @classmethod def Version_1(cls, ctx, node, **kwargs): np_dtype = util.Onnx2NumpyDtype(ctx.get_dtype(node.input_tensor_names[0])) node.attrs["broadcast"] = 1 if node.attrs["has_float_operand"]: y = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("start"), np.array(node.attrs["float_operand"]).astype(np_dtype)) node.input_tensor_names.append(y.output_tensor_names[0]) elif node.attrs["has_int_operand"]: y = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("start"), np.array(node.attrs["int_operand"]).astype(np_dtype)) node.input_tensor_names.append(y.output_tensor_names[0]) @flow_op("arange", onnx_op="Range") class Arange: @classmethod def Version_1(cls, ctx, node, **kwargs): if node.attrs["dtype"] == 1: starts = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("start"), np.array(node.attrs["float_start"])) node.input_tensor_names.append(starts.output_tensor_names[0]) limits = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("limit"), np.array(node.attrs["float_limit"])) node.input_tensor_names.append(limits.output_tensor_names[0]) delta = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("delta"), np.array(node.attrs["float_delta"])) node.input_tensor_names.append(delta.output_tensor_names[0]) else: starts = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("start"), np.array(node.attrs["integer_start"])) node.input_tensor_names.append(starts.output_tensor_names[0]) limits = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("limit"), np.array(node.attrs["integer_limit"])) node.input_tensor_names.append(limits.output_tensor_names[0]) delta = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("delta"), np.array(node.attrs["integer_delta"])) node.input_tensor_names.append(delta.output_tensor_names[0]) @classmethod def Version_11(cls, ctx, node, **kwargs): cls.Version_1(ctx, node, **kwargs) class ClipOps: @classmethod def Version_1(cls, ctx, node, min_val=None, max_val=None, **kwargs): # relu6 = min(max(features, 0), 6) node.op_type = "Clip" if min_val is not None: node.attrs["min"] = float(min_val) if max_val is not None: node.attrs["max"] = float(max_val) @classmethod def Version_11(cls, ctx, node, min_val=None, max_val=None, **kwargs): # add min and max as inputs node.op_type = "Clip" onnx_dtype = ctx.get_dtype(node.input_tensor_names[0]) np_dtype = util.ONNX_2_NUMPY_DTYPE[onnx_dtype] if min_val is not None: clip_min = ctx.MakeConst( oneflow._oneflow_internal.UniqueStr("{}_min".format(node.name)), np.array(min_val, dtype=np_dtype), ) node.input_tensor_names.append(clip_min.output_tensor_names[0]) else: node.input_tensor_names.append("") if max_val is not None: clip_max = ctx.MakeConst( oneflow._oneflow_internal.UniqueStr("{}_max".format(node.name)), np.array(max_val, dtype=np_dtype), ) node.input_tensor_names.append(clip_max.output_tensor_names[0]) else: node.input_tensor_names.append("") @flow_op("hardtanh", onnx_op="Clip") class HardTanh(ClipOps): @classmethod def Version_1(cls, ctx, node, **kwargs): min_val = 0.0 max_val = 6.0 super().Version_1(ctx, node, min_val, max_val) @flow_op(["clip_by_scalar", "clip_by_scalar_min", "clip_by_scalar_max"], onnx_op="Clip") class ClipByValueOp(ClipOps): @classmethod def Version_1(cls, ctx, node, **kwargs): min_val = node.attrs.get("floating_min", None) or node.attrs.get("integral_min", None) max_val = node.attrs.get("floating_max", None) or node.attrs.get("integral_max", None) super().Version_1(ctx, node, min_val, max_val) @classmethod def Version_11(cls, ctx, node, **kwargs): min_val = node.attrs.get("floating_min", None) or node.attrs.get("integral_min", None) max_val = node.attrs.get("floating_max", None) or node.attrs.get("integral_max", None) super().Version_11(ctx, node, min_val, max_val) @flow_op("softmax", "Softmax") class Softmax: @classmethod def Version_1(cls, ctx, node, **kwargs): # T output = Softmax(T logits). The axis softmax would be performed on is always on -1. # T output = Softmax(T input, @int axis). Default axis is 1. logits_rank = len(ctx.get_shape(node.input_tensor_names[0])) node.attrs["axis"] = logits_rank - 1 @classmethod def Version_11(cls, ctx, node, **kwargs): cls.Version_1(ctx, node, **kwargs) @flow_op("square", None) class Square: @classmethod def Version_1(cls, ctx, node, **kwargs): node.op_type = "Mul" node.input_tensor_names.append(node.input_tensor_names[0]) @flow_op("rsqrt", None) class Rsqrt: @classmethod def Version_1(cls, ctx, node, **kwargs): node.op_type = "Sqrt" op_name = oneflow._oneflow_internal.UniqueStr(node.name) reciprocal = ctx.InsertNewNodeOnOutput("Reciprocal", node.output_tensor_names[0], name=op_name) ctx.CopyShape(node.output_tensor_names[0], reciprocal.output_tensor_names[0]) @flow_op("squared_difference", None) class SquaredDifference: @classmethod def Version_1(cls, ctx, node, **kwargs): node.op_type = "Sub" op_name = oneflow._oneflow_internal.UniqueStr(node.name) mul = ctx.InsertNewNodeOnOutput("Mul", node.output_tensor_names[0], name=op_name) mul.input_tensor_names.append(node.output_tensor_names[0]) @flow_op("sign", onnx_op="Sign") class Sign: @classmethod def Version_1(cls, ctx, node, **kwargs): """Sign op.""" # T sign = Sign(T Input) node_dtype = ctx.get_dtype(node.output_tensor_names[0]) util.MakeSure(node_dtype, "Dtype of {} is None".format(node.name)) if node_dtype in [ onnx_pb.TensorProto.COMPLEX64, onnx_pb.TensorProto.COMPLEX128, ]: raise ValueError("dtype " + str(node_dtype) + " is not supported in onnx for now") zero_name = oneflow._oneflow_internal.UniqueStr("{}_zero".format(node.name)) ctx.MakeConst(zero_name, np.array(0, dtype=np.float32)) if node_dtype not in [ onnx_pb.TensorProto.FLOAT16, onnx_pb.TensorProto.FLOAT, onnx_pb.TensorProto.DOUBLE, ]: cast_node_0 = ctx.MakeNode("Cast", [node.input_tensor_names[0]], {"to": onnx_pb.TensorProto.FLOAT}) greater_node = ctx.MakeNode("Greater", [cast_node_0.output_tensor_names[0], zero_name]) less_node = ctx.MakeNode("Less", [cast_node_0.output_tensor_names[0], zero_name]) else: greater_node = ctx.MakeNode("Greater", [node.input_tensor_names[0], zero_name]) less_node = ctx.MakeNode("Less", [node.input_tensor_names[0], zero_name]) cast_node_1 = ctx.MakeNode("Cast", [greater_node.output_tensor_names[0]], {"to": node_dtype}) cast_node_2 = ctx.MakeNode("Cast", [less_node.output_tensor_names[0]], {"to": node_dtype}) shapes = node.output_shapes dtypes = node.output_dtypes ctx.RemoveNode(node.name) ctx.MakeNode( "Sub", [cast_node_1.output_tensor_names[0], cast_node_2.output_tensor_names[0]], outputs=[node.output_tensor_names[0]], shapes=shapes, dtypes=dtypes, ) @classmethod def Version_9(cls, ctx, node, **kwargs): node_dtype = ctx.get_dtype(node.output_tensor_names[0]) util.MakeSure(node_dtype, "dtype of {} is None".format(node.name)) if node_dtype in [ onnx_pb.TensorProto.BOOL, onnx_pb.TensorProto.COMPLEX64, onnx_pb.TensorProto.COMPLEX128, ]: raise ValueError("dtype " + str(node_dtype) + " is not supported in onnx for now") @flow_op(["matmul", "batch_matmul", "broadcast_matmul"], "MatMul", flow_ibns=["a", "b"]) class MatMul: @classmethod def Version_1(cls, ctx, node, **kwargs): transpose_a = node.attrs.get("transpose_a", 0) transpose_b = node.attrs.get("transpose_b", 0) alpha = node.attrs.get("alpha") if transpose_a != 0: shape = ctx.get_shape(node.input_tensor_names[0]) if shape: perm = list(range(0, len(shape))) tmp = perm[-1] perm[-1] = perm[-2] perm[-2] = tmp ctx.InsertNewNodeOnInput(node, "Transpose", node.input_tensor_names[0], perm=perm) if transpose_b != 0: shape = ctx.get_shape(node.input_tensor_names[1]) if shape: perm = list(range(0, len(shape))) tmp = perm[-1] perm[-1] = perm[-2] perm[-2] = tmp ctx.InsertNewNodeOnInput(node, "Transpose", node.input_tensor_names[1], perm=perm) unsupported = ["a_is_sparse", "b_is_sparse"] for i in unsupported: val = node.attrs.get(i, 0) if val != 0: raise ValueError(node.op_type + " attribute " + i + " is not supported") if alpha != 1.0: dtypes = node.output_dtypes alpha = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("alpha"), np.array(alpha, dtype=util.Onnx2NumpyDtype(dtypes[0]))) op_name = oneflow._oneflow_internal.UniqueStr(node.name) mul = ctx.InsertNewNodeOnOutput("Mul", node.output_tensor_names[0], op_name_scope=node.name, name=op_name) mul.input_tensor_names.append(alpha.output_tensor_names[0]) ctx.set_dtype(mul.output_tensor_names[0], ctx.get_dtype(node.output_tensor_names[0])) ctx.CopyShape(node.output_tensor_names[0], mul.output_tensor_names[0]) @flow_op("fused_self_attention_query_mul_key_and_value") class FusedSelfAttention: @classmethod def Version_1(cls, ctx, node, **kwargs): head_size = node.attrs.get("head_size") scope = node.name output_name1 = node.output_tensor_names[0] output_name2 = node.output_tensor_names[1] dtypes = node.output_dtypes shape = ctx.get_shape(node.input_tensor_names[0]) new_shape = [shape[0], shape[1], int(shape[2] / 3 / head_size), 3 * head_size] starts_q = ctx.MakeConst( oneflow._oneflow_internal.UniqueStr("start_q"), np.array([0]).astype(np.int64), ) ends_q = ctx.MakeConst( oneflow._oneflow_internal.UniqueStr("stop_q"), np.array([head_size]).astype(np.int64), ) starts_k = ctx.MakeConst( oneflow._oneflow_internal.UniqueStr("start_k"), np.array([head_size]).astype(np.int64), ) ends_k = ctx.MakeConst( oneflow._oneflow_internal.UniqueStr("stop_k"), np.array([2 * head_size]).astype(np.int64), ) starts_v = ctx.MakeConst( oneflow._oneflow_internal.UniqueStr("start_v"), np.array([2 * head_size]).astype(np.int64), ) ends_v = ctx.MakeConst( oneflow._oneflow_internal.UniqueStr("stop_v"), np.array([3 * head_size]).astype(np.int64), ) steps = ctx.MakeConst( oneflow._oneflow_internal.UniqueStr("steps"), np.array([1]).astype(np.int64), ) axes = ctx.MakeConst( oneflow._oneflow_internal.UniqueStr("axes"), np.array([3]).astype(np.int64), ) # reshape new_shape_name = oneflow._oneflow_internal.UniqueStr("new_shape") ctx.MakeConst(new_shape_name, np.array(new_shape, dtype=np.int64)) reshape = ctx.MakeNode("Reshape", [node.input_tensor_names[0], new_shape_name]) # query slice_node_q = ctx.MakeNode( "Slice", [ reshape.output_tensor_names[0], starts_q.output_tensor_names[0], ends_q.output_tensor_names[0], axes.output_tensor_names[0], steps.output_tensor_names[0], ], ) transpose_node_q = ctx.MakeNode("Transpose", [slice_node_q.output_tensor_names[0]], attr={"perm": [1, 2, 0, 3]}) # key slice_node_k = ctx.MakeNode( "Slice", [ reshape.output_tensor_names[0], starts_k.output_tensor_names[0], ends_k.output_tensor_names[0], axes.output_tensor_names[0], steps.output_tensor_names[0], ], ) transpose_node_k = ctx.MakeNode("Transpose", [slice_node_k.output_tensor_names[0]], attr={"perm": [1, 2, 3, 0]}) # value slice_node_v = ctx.MakeNode( "Slice", [ reshape.output_tensor_names[0], starts_v.output_tensor_names[0], ends_v.output_tensor_names[0], axes.output_tensor_names[0], steps.output_tensor_names[0], ], ) transpose_node_v = ctx.MakeNode("Transpose", [slice_node_v.output_tensor_names[0]], attr={"perm": [1, 2, 0, 3]}) # q * k matmul_node_qk = ctx.MakeNode( "MatMul", [transpose_node_q.output_tensor_names[0], transpose_node_k.output_tensor_names[0]], name="matmul_qk", op_name_scope=scope, ) ctx.RemoveNode(node.name) ctx.MakeNode("Identity", [matmul_node_qk.output_tensor_names[0]], outputs=[output_name1], op_name_scope=node.name, dtypes=[dtypes[0]]) ctx.MakeNode("Identity", [transpose_node_v.output_tensor_names[0]], outputs=[output_name2], op_name_scope=node.name, dtypes=[dtypes[0]]) @flow_op("erf", onnx_op="Erf") class Erf: @classmethod def Version_1(cls, ctx, node, **kwargs): """Error function.""" # constant names a1 = "erf_a1" a2 = "erf_a2" a3 = "erf_a3" a4 = "erf_a4" a5 = "erf_a5" p = "erf_p" one = "erf_one" null = "erf_null" n = node.name output_name = node.output_tensor_names[0] erf_a1_node = ctx.get_node_by_output("erf_a1") if erf_a1_node is None: # insert the constants for erf once ctx.MakeConst(a1, np.array(0.254829592, dtype=np.float32)) ctx.MakeConst(a2, np.array(-0.284496736, dtype=np.float32)) ctx.MakeConst(a3, np.array(1.421413741, dtype=np.float32)) ctx.MakeConst(a4, np.array(-1.453152027, dtype=np.float32)) ctx.MakeConst(a5, np.array(1.061405429, dtype=np.float32)) ctx.MakeConst(p, np.array(0.3275911, dtype=np.float32)) ctx.MakeConst(one, np.array(1.0, dtype=np.float32)) ctx.MakeConst(null, np.array(0.0, dtype=np.float32)) x = node.input_tensor_names[0] # erf(x): # sign = 1 if x >= 0 else -1 # x = abs(x) # # A&S formula 7.1.26 # t = 1.0 / (1.0 + p * x) # y = 1.0 - (((((a5 * t + a4) * t) + a3) * t + a2) * t + a1) * t * math.exp(-x * x) # return sign * y # erf(-x) = -erf(x) x_node = ctx.MakeNode("Abs", [x], op_name_scope=node.name, name="x") negx_node = ctx.MakeNode("Sub", [null, x], op_name_scope=node.name, name="negx") is_positive_node = ctx.MakeNode("Greater", [x, null], op_name_scope=node.name, name="isPositive") is_positive_value_node = ctx.MakeNode( "Cast", is_positive_node.output_tensor_names, op_name_scope=node.name, name="isPositiveValue", attr={"to": onnx_pb.TensorProto.FLOAT}, ) is_neg_node = ctx.MakeNode("Less", [x, null], op_name_scope=node.name, name="isNeg") ig_neg_value_node = ctx.MakeNode( "Cast", is_neg_node.output_tensor_names, op_name_scope=node.name, name="isNegValue", attr={"to": onnx_pb.TensorProto.FLOAT}, ) sign0_node = ctx.MakeNode( "Sub", [ is_positive_value_node.output_tensor_names[0], ig_neg_value_node.output_tensor_names[0], ], op_name_scope=node.name, name="sign0", ) sign_add_one_node = ctx.MakeNode( "Add", [sign0_node.output_tensor_names[0], one], op_name_scope=node.name, name="signAddOne", ) non_zero_node = ctx.MakeNode( "Abs", sign0_node.output_tensor_names, op_name_scope=node.name, name="nonZero", ) sign_node = ctx.MakeNode( "Sub", [ sign_add_one_node.output_tensor_names[0], non_zero_node.output_tensor_names[0], ], op_name_scope=node.name, name="sign", ) num_4_node = ctx.MakeNode("Mul", [x_node.output_tensor_names[0], p], op_name_scope=node.name, name="4") num_5_node = ctx.MakeNode( "Add", [num_4_node.output_tensor_names[0], one], op_name_scope=node.name, name="5", ) t_node = ctx.MakeNode( "Div", [one, num_5_node.output_tensor_names[0]], op_name_scope=node.name, name="t", ) xsq_node = ctx.MakeNode( "Mul", [x, negx_node.output_tensor_names[0]], op_name_scope=node.name, name="xsq", ) num_6_node = ctx.MakeNode("Exp", xsq_node.output_tensor_names, op_name_scope=node.name, name="6") num_7_node = ctx.MakeNode( "Mul", [num_6_node.output_tensor_names[0], t_node.output_tensor_names[0]], op_name_scope=node.name, name="7", ) num_8_node = ctx.MakeNode( "Mul", [t_node.output_tensor_names[0], a5], op_name_scope=node.name, name="8", ) num_9_node = ctx.MakeNode( "Add", [num_8_node.output_tensor_names[0], a4], op_name_scope=node.name, name="9", ) num_10_node = ctx.MakeNode( "Mul", [num_9_node.output_tensor_names[0], t_node.output_tensor_names[0]], op_name_scope=node.name, name="10", ) num_11_node = ctx.MakeNode( "Add", [num_10_node.output_tensor_names[0], a3], op_name_scope=node.name, name="11", ) num_12_node = ctx.MakeNode( "Mul", [num_11_node.output_tensor_names[0], t_node.output_tensor_names[0]], op_name_scope=node.name, name="12", ) num_13_node = ctx.MakeNode( "Add", [num_12_node.output_tensor_names[0], a2], op_name_scope=node.name, name="13", ) num_14_node = ctx.MakeNode( "Mul", [num_13_node.output_tensor_names[0], t_node.output_tensor_names[0]], op_name_scope=node.name, name="14", ) num_15_node = ctx.MakeNode( "Add", [num_14_node.output_tensor_names[0], a1], op_name_scope=node.name, name="15", ) num_16_node = ctx.MakeNode( "Mul", [num_15_node.output_tensor_names[0], num_7_node.output_tensor_names[0]], op_name_scope=node.name, name="16", ) num_17_node = ctx.MakeNode( "Sub", [one, num_16_node.output_tensor_names[0]], op_name_scope=node.name, name="17", ) shapes = node.output_shapes dtypes = node.output_dtypes ctx.RemoveNode(node.name) ctx.MakeNode( "Mul", [num_17_node.output_tensor_names[0], sign_node.output_tensor_names[0]], outputs=[output_name], name=n, shapes=shapes, dtypes=dtypes, ) @classmethod def Version_9(cls, ctx, node, **kwargs): pass @flow_op("broadcast_floor_mod", onnx_op="FloorMod") class FloorMod: @classmethod def Version_7(cls, ctx, node, **kwargs): # T output = FloorMod(T x, T y) div = ctx.MakeNode(op_type="Div", inputs=node.input_tensor_names) dtype = ctx.get_dtype(node.input_tensor_names[0]) if dtype in [ onnx_pb.TensorProto.FLOAT, onnx_pb.TensorProto.FLOAT16, onnx_pb.TensorProto.DOUBLE, ]: div = ctx.MakeNode(op_type="Floor", inputs=div.output_tensor_names) mul = ctx.MakeNode( op_type="Mul", inputs=[div.output_tensor_names[0], node.input_tensor_names[1]], ) # res node will take over shape&dtype&output connection info of original "node" shapes = node.output_shapes dtypes = node.output_dtypes ctx.RemoveNode(node.name) ctx.MakeNode( op_type="Sub", inputs=[node.input_tensor_names[0], mul.output_tensor_names[0]], name=node.name, outputs=node.output_tensor_names, shapes=shapes, dtypes=dtypes, ) @flow_op("round", onnx_op="Round") class Round: @classmethod def Version_11(cls, ctx, node, **kwargs): pass def _AddCastToInputs(graph, node, supported_dtypes, target_dtype): is_support = True for inp in node.input_tensor_names: if graph.get_dtype(inp) not in supported_dtypes: is_support = False break if not is_support: for inp in node.input_tensor_names: inp_cast = graph.InsertNewNodeOnInput(node, "Cast", inp, to=target_dtype) graph.CopyShape(inp, inp_cast.output_tensor_names[0]) graph.set_dtype(inp_cast.output_tensor_names[0], target_dtype) def _AddCastToOutput(graph, node): # oneflow logical ops produce int8 tensor while onnx logical ops produce bool tensor output = node.output_tensor_names[0] cast_node = graph.InsertNewNodeOnOutput("Cast", output, oneflow._oneflow_internal.UniqueStr("cast"), to=graph.get_dtype(output)) graph.CopyShape(output, node.output_tensor_names[0]) graph.set_dtype(node.output_tensor_names[0], TensorProto.BOOL) # oneflow doesn't have logical_not and broadcast_logical_or, but # it is easy to implement onnx converter in advance @flow_op("logical_not", onnx_op="Not") class DirectOp: @classmethod def Version_1(cls, ctx, node, **kwargs): _AddCastToOutput(ctx, node) @flow_op("broadcast_logical_and", onnx_op="And", flow_ibns=["x", "y"]) @flow_op("broadcast_logical_or", onnx_op="Or", flow_ibns=["x", "y"]) class BroadcastOp(common.BroadcastOp): @classmethod def Version_1(cls, ctx, node, **kwargs): _AddCastToOutput(ctx, node) super().Version_1(ctx, node, **kwargs) @flow_op( ["broadcast_equal", "broadcast_not_equal"], ["Equal", "NotEqual"], flow_ibns=["x", "y"], ) class Equal: @classmethod def Version_7(cls, ctx, node, **kwargs): # T2 output = Equal(T1, x, T1 y), T1 \in {bool, int32, int64} _AddCastToOutput(ctx, node) need_not = node.op_type == "NotEqual" supported_dtypes = [TensorProto.BOOL, TensorProto.INT32, TensorProto.INT64] if any([ctx.get_dtype(inp) not in supported_dtypes for inp in node.input_tensor_names]): raise ValueError("Version 7 Equal op only supports bool, int32 and int64 inputs. Please set opset > 11 and try again.") if need_not: node.op_type = "Equal" output_name = node.output_tensor_names[0] not_node = ctx.InsertNewNodeOnOutput("Not", output_name, name=oneflow._oneflow_internal.UniqueStr(node.name)) ctx.CopyShape(output_name, not_node.output_tensor_names[0]) ctx.CopyDtype(output_name, not_node.output_tensor_names[0]) @classmethod def Version_11(cls, ctx, node, **kwargs): # starting with opset-11, equal supports all types _AddCastToOutput(ctx, node) need_not = node.op_type == "NotEqual" if need_not: node.op_type = "Equal" output_name = node.output_tensor_names[0] not_node = ctx.InsertNewNodeOnOutput("Not", output_name, name=oneflow._oneflow_internal.UniqueStr(node.name)) ctx.CopyShape(output_name, not_node.output_tensor_names[0]) ctx.CopyDtype(output_name, not_node.output_tensor_names[0]) @flow_op(["broadcast_greater", "broadcast_less"], ["Greater", "Less"], flow_ibns=["x", "y"]) class GreaterLess: @classmethod def Version_7(cls, ctx, node, **kwargs): _AddCastToOutput(ctx, node) # T2 output = Greater(T1 x, T1 y), T2=tensor(bool) # T2 output = Less(T1 x, T1 y), T2=tensor(bool) # Great/Less in opset7 only supports limited types, insert Cast if needed supported_dtypes = [TensorProto.FLOAT, TensorProto.FLOAT16, TensorProto.DOUBLE] target_dtype = TensorProto.FLOAT _AddCastToInputs(ctx, node, supported_dtypes, target_dtype) @flow_op("broadcast_greater_equal", onnx_op="Less", flow_ibns=["x", "y"]) @flow_op("broadcast_less_equal", onnx_op="Greater", flow_ibns=["x", "y"]) class GreaterLessEqual: @classmethod def Version_7(cls, ctx, node, **kwargs): _AddCastToOutput(ctx, node) GreaterLess.Version_7(ctx, node, **kwargs) output_name = node.output_tensor_names[0] new_node = ctx.InsertNewNodeOnOutput("Not", output_name, name=oneflow._oneflow_internal.UniqueStr(node.name)) ctx.CopyShape(output_name, new_node.output_tensor_names[0]) ctx.set_dtype(new_node.output_tensor_names[0], ctx.get_dtype(output_name)) @flow_op(["var"]) class Var: @classmethod def Version_13(cls, ctx, node, **kwargs): origin_dim = node.attrs.get("dim", None) unbiased = node.attrs.get("unbiased", None) keepdim = node.attrs.get("keepdim", None) num_elements = 1 dtypes = node.output_dtypes input_shape = ctx.get_shape(node.input_tensor_names[0]) keepdim_mean = 0 if origin_dim is None else keepdim if origin_dim is None: dim = [] for i in range(len(input_shape)): num_elements *= input_shape[i] dim.append(i) reduce_mean_node = ctx.MakeNode("ReduceMean", [node.input_tensor_names[0]], op_name_scope=node.name, name="reduce_mean", dtypes=dtypes, attr={"axes": dim, "keepdims": 0}) t_mean = reduce_mean_node.output_tensor_names[0] else: reduce_mean_node = ctx.MakeNode("ReduceMean", [node.input_tensor_names[0]], op_name_scope=node.name, name="reduce_mean", dtypes=dtypes, attr={"axes": origin_dim, "keepdims": 1}) t_mean = reduce_mean_node.output_tensor_names[0] for i in range(len(origin_dim)): num_elements *= input_shape[i] sub_node = ctx.MakeNode("Sub", [node.input_tensor_names[0], t_mean], op_name_scope=node.name, name="sub", dtypes=dtypes) sub_v = sub_node.output_tensor_names[0] mul_node = ctx.MakeNode("Mul", [sub_v, sub_v], op_name_scope=node.name, name="mul", dtypes=dtypes) sqr_sub = mul_node.output_tensor_names[0] if unbiased is None: unbiased = False ctx.RemoveNode(node.name) if unbiased: var_node = ctx.MakeNode("ReduceMean", [sqr_sub], op_name_scope=node.name, name="var", dtypes=dtypes, attr={"axes": origin_dim, "keepdims": keepdim_mean}) var = var_node.output_tensor_names[0] scalar_node = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("scalar"), np.array([num_elements]).astype(np.float32)) one = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("constant"), np.array([1]).astype(np.float32)) num_elements = scalar_node.output_tensor_names[0] mul = ctx.MakeNode("Mul", [var, num_elements]) sub = ctx.MakeNode("Sub", [num_elements, one.output_tensor_names[0]]) var = ctx.MakeNode("Div", [mul.output_tensor_names[0], sub.output_tensor_names[0]], outputs=[node.output_tensor_names[0]]) else: var_node = ctx.MakeNode( "ReduceMean", [sqr_sub], op_name_scope=node.name, name="var", dtypes=dtypes, attr={"axes": origin_dim, "keepdims": keepdim_mean}, outputs=[node.output_tensor_names[0]] ) @flow_op("fill_", onnx_op="Constant") class Fill: @classmethod def Version_1(cls, ctx, node, **kwargs): is_floating_value = node.attrs["is_floating_value"] output_name = node.output_tensor_names[0] out_shape = ctx.get_shape(output_name) if is_floating_value: values = np.full(shape=out_shape, fill_value=node.attrs["floating_value"], dtype=np.float32) else: values = np.full(shape=out_shape, fill_value=node.attrs["integral_value"], dtype=np.float32) ctx.RemoveNode(node.name) ctx.MakeConst(output_name, values) @classmethod def Version_9(cls, ctx, node, **kwargs): cls.Version_1(ctx, node, **kwargs) @classmethod def Version_11(cls, ctx, node, **kwargs): cls.Version_1(ctx, node, **kwargs) @classmethod def Version_13(cls, ctx, node, **kwargs): cls.Version_1(ctx, node, **kwargs) @flow_op("fused_bias_add_scale_mask_softmax_dropout") class FusedBiasAddScaleMaskSoftmaxDropout: @classmethod def Version_1(cls, ctx, node, **kwargs): dtypes = node.output_dtypes scale_value = node.attrs.get("scale_value") mask_fill_value = node.attrs.get("mask_fill_value") output_name1 = node.output_tensor_names[0] output_name2 = node.output_tensor_names[1] scale = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("scale"), np.array(scale_value, dtype=util.Onnx2NumpyDtype(dtypes[0]))) mask_fill = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("mask_fill"), np.array(mask_fill_value, dtype=util.Onnx2NumpyDtype(dtypes[0]))) one = ctx.MakeConst(oneflow._oneflow_internal.UniqueStr("one"), np.array(1, dtype=util.Onnx2NumpyDtype(dtypes[0]))) ctx.set_dtype(node.input_tensor_names[2], ctx.get_dtype(one.output_tensor_names[0])) add_node_1 = ctx.MakeNode("Add", [node.input_tensor_names[0], node.input_tensor_names[1]], op_name_scope=node.name, name="add_node_1", dtypes=[dtypes[0]]) mul_node_1 = ctx.MakeNode("Mul", [add_node_1.output_tensor_names[0], node.input_tensor_names[2]], op_name_scope=node.name, name="mul_node_1", dtypes=[dtypes[0]]) masked = ctx.MakeNode("Mul", [mul_node_1.output_tensor_names[0], scale.output_tensor_names[0]], op_name_scope=node.name, name="masked", dtypes=[dtypes[0]]) unmask = ctx.MakeNode("Sub", [one.output_tensor_names[0], node.input_tensor_names[2]], op_name_scope=node.name, name="unmask", dtypes=[dtypes[0]]) mul_node_2 = ctx.MakeNode("Mul", [mask_fill.output_tensor_names[0], unmask.output_tensor_names[0]], op_name_scope=node.name, name="mul_node_2", dtypes=[dtypes[0]]) mul_node_3 = ctx.MakeNode("Mul", [masked.output_tensor_names[0], node.input_tensor_names[2]], op_name_scope=node.name, name="mul_node_3", dtypes=[dtypes[0]]) sub_node_1 = ctx.MakeNode("Sub", [mul_node_2.output_tensor_names[0], mul_node_3.output_tensor_names[0]], op_name_scope=node.name, name="sub_node_1", dtypes=[dtypes[0]]) add_node_2 = ctx.MakeNode("Add", [sub_node_1.output_tensor_names[0], masked.output_tensor_names[0]], op_name_scope=node.name, name="add_node_2", dtypes=[dtypes[0]]) softmax_y = ctx.MakeNode("Softmax", [add_node_2.output_tensor_names[0]], attr={"axis": 2}, op_name_scope=node.name, name="softmax_node_1", dtypes=[dtypes[0]]) ctx.RemoveNode(node.name) ctx.MakeNode("Identity", [softmax_y.output_tensor_names[0]], outputs=[output_name1], op_name_scope=node.name, dtypes=[dtypes[0]]) ctx.MakeNode("Identity", [softmax_y.output_tensor_names[0]], outputs=[output_name2], op_name_scope=node.name, dtypes=[dtypes[0]])

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from datetime import datetime, timedelta import urllib.parse from urllib3.util.retry import Retry import pytz import logging import re import dateparser import concurrent.futures import math import requests from requests.adapters import HTTPAdapter import io import json from .version import __version__ version_string = __version__ def linkify(url, params): p = ['='.join((str(x), str(y))) for x, y in params.items()] p = '&'.join(p) return '?'.join((url, p)) def split_link(url): url, qs = url.split('?') params = dict([p.split('=') for p in qs.split('&')]) return (url, params) class DasClient(object): """ DasClient provides basic access to a DAS API. It requires the coordinates of a DAS API service as well as valid credentials for a user. The boiler-plate code handles authentication, so you don't have to think about Oauth2 or refresh tokens. As of May 12, 2017 it includes just a basic set of functions to access Subject data and to post observations. June 6, 2017: Added methods to add a photo or document to an Event. """ def __init__(self, **kwargs): """ Initialize a DasClient instance. :param username: DAS username :param password: DAS password :param service_root: The root of the DAS API (Ex. https://demo.pamdas.org/api/v1.0) :param token_url: The auth token url for DAS (Ex. https://demo.pamdas.org/oauth2/token) :param provider_key: provider-key for posting observation data (Ex. xyz_provider) :param client_id: Auth client ID (Ex. das_web_client) """ self.auth = None self.auth_expires = pytz.utc.localize(datetime.min) self._http_session = None self.max_retries = kwargs.get('max_http_retries', 5) self.service_root = kwargs.get('service_root') self.client_id = kwargs.get('client_id') self.provider_key = kwargs.get('provider_key') self.token_url = kwargs.get('token_url') self.username = kwargs.get('username') self.password = kwargs.get('password') self.realtime_url = kwargs.get('realtime_url') if kwargs.get('token'): self.token = kwargs.get('token') self.auth = dict(token_type='Bearer', access_token=kwargs.get('token')) self.auth_expires = datetime(2099, 1, 1, tzinfo=pytz.utc) self.user_agent = 'das-client/{}'.format(version_string) self.logger = logging.getLogger(self.__class__.__name__) self._http_session = requests.Session() retries = Retry(total = 5, backoff_factor=1.5, status_forcelist=[502]) self._http_session.mount("http", HTTPAdapter(max_retries=retries)) self._http_session.mount("https", HTTPAdapter(max_retries=retries)) def _auth_is_valid(self): return self.auth_expires > pytz.utc.localize(datetime.utcnow()) def auth_headers(self): if self.auth: if not self._auth_is_valid(): if not self.refresh_token(): if not self.login(): raise DasClientException('Login failed.') else: if not self.login(): raise DasClientException('Login failed.') return {'Authorization': '{} {}'.format(self.auth['token_type'], self.auth['access_token']), 'Accept-Type': 'application/json'} def refresh_token(self): payload = {'grant_type': 'refresh_token', 'refresh_token': self.auth['refresh_token'], 'client_id': self.client_id } return self._token_request(payload) def login(self): payload = {'grant_type': 'password', 'username': self.username, 'password': self.password, 'client_id': self.client_id } return self._token_request(payload) def _token_request(self, payload): response = requests.post(self.token_url, data=payload) if response.ok: self.auth = json.loads(response.text) expires_in = int(self.auth['expires_in']) - 5 * 60 self.auth_expires = pytz.utc.localize( datetime.utcnow()) + timedelta(seconds=expires_in) return True self.auth = None self.auth_expires = pytz.utc.localize(datetime.min) return False def _das_url(self, path): return '/'.join((self.service_root, path)) def _get(self, path, stream=False, **kwargs): headers = {'User-Agent': self.user_agent} headers.update(self.auth_headers()) if(not path.startswith("http")): path = self._das_url(path) response = None if(self._http_session): response = self._http_session.get(path, headers=headers, params=kwargs.get('params'), stream=stream) else: response = requests.get(path, headers=headers, params=kwargs.get('params'), stream=stream) if response.ok: if kwargs.get('return_response', False): return response data = json.loads(response.text) if 'metadata' in data: return data['metadata'] elif 'data' in data: return data['data'] else: return data if response.status_code == 404: # not found self.logger.error(f"404 when calling {path}") raise DasClientNotFound() if response.status_code == 403: # forbidden try: _ = json.loads(response.text) reason = _['status']['detail'] except: reason = 'unknown reason' raise DasClientPermissionDenied(reason) self.logger.debug("Fail: " + response.text) raise DasClientException( f"Failed to call DAS web service at {response.url}. {response.status_code} {response.text}") def _call(self, path, payload, method, params=None): headers = {'Content-Type': 'application/json', 'User-Agent': self.user_agent} headers.update(self.auth_headers()) def time_converter(t): if isinstance(t, datetime): return t.isoformat() body = json.dumps(payload, default=time_converter) fmap = None if(self._http_session): fmap = {'POST': self._http_session.post, 'PATCH': self._http_session.patch} else: fmap = {'POST': requests.post, 'PATCH': requests.patch} try: fn = fmap[method] except KeyError: self.logger.error('method must be one of...') else: response = fn(self._das_url(path), data=body, headers=headers, params=params) if response and response.ok: res_json = response.json() if('data' in res_json): return res_json['data'] else: return res_json if response.status_code == 404: # not found self.logger.error(f"Could not load {path}") raise DasClientNotFound() try: _ = json.loads(response.text) reason = _['status']['detail'] except: reason = 'unknown reason' if response.status_code == 403: # forbidden raise DasClientPermissionDenied(reason) if response.status_code == 504 or response.status_code == 502: # gateway timeout or bad gateway self.logger.error(f"ER service unavailable", extra=dict(provider_key=self.provider_key, service=self.service_root, path=path, status_code=response.status_code, reason=reason, text=response.text)) raise DasClientServiceUnavailable(f"ER service unavailable") self.logger.error(f"ER returned bad response", extra=dict(provider_key=self.provider_key, service=self.service_root, path=path, status_code=response.status_code, reason=reason, text=response.text)) message = f"provider_key: {self.provider_key}, service: {self.service_root}, path: {path},\n\t {response.status_code} from ER. Message: {reason} {response.text}" raise DasClientException( f"Failed to {fn} to DAS web service. {message}") def _post(self, path, payload, params={}): return self._call(path, payload, "POST", params) def _patch(self, path, payload, params={}): return self._call(path, payload, "PATCH", params) def add_event_to_incident(self, event_id, incident_id): params = { 'to_event_id': event_id, 'type': 'contains' } result = self._post('activity/event/' + incident_id + '/relationships', params) def remove_event_from_incident(self, event_id, incident_id, relationship_type='contains'): result = self._delete( f'activity/event/{incident_id}/relationship/{relationship_type}/{event_id}/') def _delete(self, path): headers = {'User-Agent': self.user_agent} headers.update(self.auth_headers()) resonse = None if(self._http_session): response = self._http_session.delete(self._das_url(path), headers=headers) else: response = requests.delete(self._das_url(path), headers=headers) if response.ok: return True if response.status_code == 404: # not found self.logger.error(f"404 when calling {path}") raise DasClientNotFound() if response.status_code == 403: # forbidden try: _ = json.loads(response.text) reason = _['status']['detail'] except: reason = 'unknown reason' raise DasClientPermissionDenied(reason) raise DasClientException( f'Failed to delete: {response.status_code} {response.text}') def delete_event(self, event_id): self._delete('activity/event/' + event_id + '/') def delete_source(self, source_id): self._delete('source/' + source_id + '/') def delete_subject(self, subject_id): self._delete('subject/' + subject_id + '/') def delete_message(self, message_id): self._delete('messages/' + message_id + '/') def delete_patrol(self, patrol_id): self._delete('activity/patrols/' + patrol_id + '/') def _post_form(self, path, body=None, files=None): headers = {'User-Agent': self.user_agent} headers.update(self.auth_headers()) body = body or {} response = requests.post(self._das_url( path), data=body, headers=headers, files=files) if response and response.ok: return json.loads(response.text)['data'] if response.status_code == 404: # not found raise DasClientNotFound() if response.status_code == 403: # forbidden try: _ = json.loads(response.text) reason = _['status']['detail'] except: reason = 'unknown reason' raise DasClientPermissionDenied(reason) self.logger.error('provider_key: %s, path: %s\n\tBad result from das service. Message: %s', self.provider_key, path, response.text) raise DasClientException('Failed to post to DAS web service.') def post_eventprovider(self, eventprovider): self.logger.debug('Posting eventprovider: %s', eventprovider) result = self._post('activity/eventproviders/', payload=eventprovider) self.logger.debug('Result of eventprovider post is: %s', result) return result def post_eventsource(self, eventprovider_id, eventsource): self.logger.debug('Posting eventsource: %s', eventsource) result = self._post(f'activity/eventprovider/{eventprovider_id}/eventsources', payload=eventsource) self.logger.debug('Result of eventsource post is: %s', result) return result def post_event_photo(self, event_id, image): raise ValueError('post_event_photo is no longer valid.') photos_path = 'activity/event/' + str(event_id) + '/photos/' with open(image, "rb") as image_file: files = {'image': image_file} return self._post_form(photos_path, files=files) def post_camera_trap_report(self, camera_trap_payload, file=None): camera_trap_report_path = f'sensors/camera-trap/' + self.provider_key + '/status/' if file: files = {'filecontent.file': file} return self._post_form(camera_trap_report_path, body=camera_trap_payload, files=files) else: file_path = camera_trap_payload.get('file') with open(file_path, "rb") as f: files = {'filecontent.file': f} return self._post_form(camera_trap_report_path, body=camera_trap_payload, files=files) def delete_event_file(self, event_id, file_id): self._delete(f"activity/event/{event_id}/file/{file_id}") def delete_event_note(self, event_id, note_id): path = f"activity/event/{event_id}/note/{note_id}" self._delete(path) def post_event_file(self, event_id, filepath=None, comment=''): documents_path = 'activity/event/' + str(event_id) + '/files/' with open(filepath, "rb") as f: files = {'filecontent.file': f} return self._post_form(documents_path, body={'comment': comment}, files=files) def post_event_note(self, event_id, notes): created = [] if(not isinstance(notes, list)): notes = [notes, ] for note in notes: notesRequest = { 'event': event_id, 'text': note } result = self._post('activity/event/' + event_id + '/notes', notesRequest) created.append(result) return created def get_me(self): """ Get details for the 'me', the current DAS user. :return: """ return self._get('user/me') def post_subject(self, subject): ''' Post a subject payload to create a new subject. :param subject: :return: ''' self.logger.debug(f"Posting subject {subject.get('name')}") return self._post('subjects', payload=subject) def post_source(self, source): ''' Post a source payload to create a new source. :param source: :return: ''' self.logger.debug('Posting source for manufacturer_id: %s', source.get('manufacturer_id')) return self._post('sources', payload=source) def _clean_observation(self, observation): if hasattr(observation['recorded_at'], 'isoformat'): observation['recorded_at'] = observation['recorded_at'].isoformat() return observation def _clean_event(self, event): return event def post_radio_observation(self, observation): # Clean-up data before posting observation['recorded_at'] = observation['recorded_at'].isoformat() self.logger.debug('Posting observation: %s', observation) result = self._post( 'sensors/dasradioagent/{}/status'.format(self.provider_key), payload=observation) self.logger.debug('Result of post is: %s', result) return result def post_radio_heartbeat(self, data): self.logger.debug('Posting heartbeat: %s', data) result = self._post( 'sensors/dasradioagent/{}/status'.format(self.provider_key), payload=data) self.logger.debug('Result of heartbeat post is: %s', result) def post_observation(self, observation): """ Post a new observation, or a list of observations. """ if isinstance(observation, (list, set)): payload = [self._clean_observation(o) for o in observation] else: payload = self._clean_observation(observation) self.logger.debug('Posting observation: %s', payload) return self._post('observations', payload=payload) def post_sensor_observation(self, observation, sensor_type='generic'): """ Post a new observation, or a list of observations. """ if isinstance(observation, (list, set)): payload = [self._clean_observation(o) for o in observation] else: payload = self._clean_observation(observation) self.logger.debug('Posting observation: %s', observation) result = self._post( 'sensors/{}/{}/status'.format(sensor_type, self.provider_key), payload=observation) self.logger.debug('Result of post is: %s', result) return result def post_patrol(self, data): payload = self._clean_event(data) self.logger.debug('Posting patrol: %s', payload) result = self._post('activity/patrols', payload=payload) self.logger.debug('Result of patrol post is: %s', result) return result def patch_event_type(self, event_type): self.logger.debug('Patching event type: %s', event_type) result = self._patch( f"activity/events/eventtypes/{event_type['id']}", payload=event_type) self.logger.debug('Result of event type patch is: %s', result) return result def post_event_type(self, event_type): self.logger.debug('Posting event type: %s', event_type) result = self._post('activity/events/eventtypes/', payload=event_type) self.logger.debug('Result of event type post is: %s', result) return result def post_report(self, data): payload = self._clean_event(data) self.logger.debug('Posting report: %s', payload) result = self._post('activity/events', payload=payload) self.logger.debug('Result of report post is: %s', result) return result def post_event_category(self, data): self.logger.debug('Posting event category: %s', data) result = self._post('activity/events/categories', payload=data) self.logger.debug('Result of report category post is: %s', result) return result def patch_event_category(self, data): self.logger.debug('Patching event category: %s', data) result = self._patch( f'activity/events/categories/{data["id"]}', payload=data) self.logger.debug('Result of report category patch is: %s', result) return result def post_event(self, event): """ Post a new Event. """ return self.post_report(event) def add_events_to_patrol_segment(self, events, patrol_segment): for event in events: payload = { 'id': event['id'], 'patrol_segments': [ patrol_segment['id'] ] } result = self._patch( f"activity/event/{event['id']}", payload=payload) def patch_event(self, event_id, payload): self.logger.debug('Patching event: %s', payload) result = self._patch('activity/event/' + event_id, payload=payload) self.logger.debug('Result of event patch is: %s', result) return result def get_file(self, url): return self._get(url, stream=True, return_response=True) def get_event_type(self, event_type_name): return self._get(f'activity/events/schema/eventtype/{event_type_name}') def get_event_categories(self, include_inactive=False): return self._get(f'activity/events/categories', params={"include_inactive": include_inactive}) def get_messages(self): results = self._get(path='messages') while True: if results and results.get('results'): for r in results['results']: yield r if results and results['next']: url, params = split_link(results['next']) p['page'] = params['page'] results = self._get(path='messages') else: break def get_event_types(self, include_inactive = False, include_schema = False): return self._get('activity/events/eventtypes', params = {"include_inactive": include_inactive, "include_schema": include_schema}) def get_event_schema(self, event_type): return self._get(f'activity/events/schema/eventtype/{event_type}') def _get_objects_count(self, params): params = params.copy() params["page"] = 1 params["page_size"] = 1 events = self._get(params['object'], params=params) if events and events.get('count'): return events['count'] return 0 def get_objects(self, **kwargs): params = dict((k, v) for k, v in kwargs.items() if k not in ('page')) if(not params.get('object')): raise ValueError("Must specify object URL") self.logger.debug(f"Getting {params['object']}: ", params) count = 0 results = self._get(params['object'], params=params) while True: if(not results): break if('results' in results): for result in results['results']: yield result count += 1 if(('max_results' in params) and (count >= params['max_results'])): return next = results.get('next') if (next and ('page' not in params)): url = next self.logger.debug('Getting more objects: ' + url) results = self._get(url) else: break elif(type(results) == list): for o in results: yield o break else: yield results break def get_objects_multithreaded(self, **kwargs): threads = kwargs.get("threads", 5) params = dict((k, v) for k, v in kwargs.items() if k not in ('page')) if(not params.get('object')): raise ValueError("Must specify object URL") if(not params.get('page_size')): params['page_size'] = 100 count = self._get_objects_count(params) self.logger.debug(f"Loading {count} {params['object']} from ER with page size {params['page_size']} and {threads} threads") with concurrent.futures.ThreadPoolExecutor(max_workers = threads) as executor: futures = [] for page in range(1,math.ceil(count/params['page_size'])+1): temp_params = params.copy() temp_params["page"] = page futures.append(executor.submit(self._get, params['object'], params=temp_params)) for future in concurrent.futures.as_completed(futures): max_retries = kwargs.get("retries", 0) tries = 0 while(True): tries += 1 try: result = future.result() for e in result['results']: yield e break except Exception as e: if(tries > max_retries): logging.error(f"Error occurred loading events: {e}") raise e else: logging.warning(f"Attempt {tries} of {max_retries}: Error occurred loading events: {e}.") def get_events(self, **kwargs): params = dict((k, v) for k, v in kwargs.items() if k in ('state', 'page_size', 'page', 'event_type', 'filter', 'include_notes', 'include_related_events', 'include_files', 'include_details', 'updated_since', 'include_updates', 'max_results', 'oldest_update_date', 'event_ids')) self.logger.debug('Getting events: ', params) events = self._get('activity/events', params=params) count = 0 while True: if events and events.get('results'): for result in events['results']: yield result count += 1 if(('max_results' in params) and (count >= params['max_results'])): return if events['next'] and ('page' not in params): url = events['next'] url = re.sub('.*activity/events?', 'activity/events', events['next']) self.logger.debug('Getting more events: ' + url) events = self._get(url) else: break def get_patrols(self, **kwargs): params = dict((k, v) for k, v in kwargs.items() if k in ('state', 'page_size', 'page', 'event_type', 'filter')) self.logger.debug('Getting patrols: ', params) patrols = self._get('activity/patrols', params=params) while True: if patrols and patrols.get('results'): for result in patrols['results']: yield result if patrols['next']: url = patrols['next'] url = re.sub('.*activity/patrols?', 'activity/patrols', patrols['next']) self.logger.debug('Getting more patrols: ' + url) patrols = self._get(url) else: break def get_events_export(self, filter=None): params = None if filter: params = { 'filter': filter} response = self._get('activity/events/export/', params=params, return_response=True) return response def pulse(self, message=None): """ Convenience method for getting status of the DAS api. :param message: :return: """ return self._get('status') def get_subject_sources(self, subject_id): return self._get(path=f'subject/{subject_id}/sources') def get_subjectsources(self, subject_id): return self._get(path=f'subject/{subject_id}/subjectsources') def get_source_provider(self, provider_key): results = self.get_objects(object="sourceproviders") for r in results: if(r.get('provider_key') == provider_key): return r return None def get_subject_tracks(self, subject_id='', start=None, end=None): """ Get the latest tracks for the Subject having the given subject_id. """ p = {} if start is not None and isinstance(start, datetime): p['since'] = start.isoformat() if end is not None and isinstance(end, datetime): p['until'] = end.isoformat() return self._get(path='subject/{0}/tracks'.format(subject_id), params=p) def get_subject_trackingdata(self, subject_id=None, subject_chronofile=None, include_inactive=True, start=None, end=None, out_format='json', filter_flag=0, current_status=False): p = {} if start is not None and isinstance(start, datetime): p['after_date'] = start.isoformat() if end is not None and isinstance(end, datetime): p['before_date'] = end.isoformat() if subject_id: p['subject_id'] = subject_id elif subject_chronofile: p['subject_chronofile'] = subject_chronofile else: raise ValueError('specify subject_id or subject_chronofile') p['include_inactive'] = include_inactive p['format'] = out_format # should be 'json' or 'csv' p['filter'] = 'null' if filter_flag is None else filter_flag p['current_status'] = current_status return self._get(path='trackingdata/export', params=p) def get_subject_trackingmetadata(self, include_inactive=True, out_format='json'): p = {} p['include_inactive'] = include_inactive p['format'] = out_format # should be 'json' or 'csv' return self._get(path='trackingmetadata/export', params=p) def get_subject_observations(self, subject_id, start=None, end=None, filter_flag=0, include_details=True, page_size=10000): return self.get_observations(subject_id=subject_id, start=start, end=end, filter_flag=filter_flag, include_details=include_details, page_size=page_size) def get_source_observations(self, source_id, start=None, end=None, filter_flag=0, include_details=True, page_size=10000): return self.get_observations(source_id=source_id, start=start, end=end, filter_flag=filter_flag, include_details=include_details, page_size=page_size) def get_observations(self, subject_id=None, source_id=None, start=None, end=None, filter_flag=0, include_details=True, page_size=10000): p = {} if start is not None and isinstance(start, datetime): p['since'] = start.isoformat() if end is not None and isinstance(end, datetime): p['until'] = end.isoformat() if subject_id: p['subject_id'] = subject_id elif source_id: p['source_id'] = source_id p['filter'] = 'null' if filter_flag is None else filter_flag p['include_details'] = include_details p['page_size'] = page_size # current limit results = self._get(path='observations', params=p) while True: if results and results.get('results'): for r in results['results']: yield r if results and results['next']: url, params = split_link(results['next']) p['page'] = params['page'] results = self._get(path='observations', params=p) else: break def get_subjects(self, subject_group_id=None, **kwargs): """ Get the list of subjects to whom the user has access. :return: """ params = dict((k, v) for k, v in kwargs.items() if k in ('subject_group', 'include_inactive')) return self._get('subjects', params=params) def get_subject(self, subject_id=''): """ get the subject given the subject id :param subject_id: the UUID for the subject :return: """ return self._get(path='subject/{0}'.format(subject_id)) def get_source_by_id(self, id): """ get the source by id :param id: source id :return: """ return self._get(path='source/{0}'.format(id)) def get_source_by_manufacturer_id(self, id): """ get the source by manufacturer id or collar id :param id: the manufacturer id :return: """ return self._get(path='source/{0}'.format(id)) def get_subjectgroups(self, include_inactive=False, include_hidden=True, isvisible=True, flat=True, group_name=None): """Get the list of visible subjectgroups including members. By default don't include inactive subjects to get all subject groups whether visible or not, call with include_hidden=True Args: include_inactive (bool, optional): set to True to include inactive subjects. Defaults to False. include_hidden (bool, optional): include subject groups that are not visible (isvisible flag is false). Defaults to True. isvisible (bool, optional): either include all visible groups, or only include not visible groups. Defaults to True. flat (bool, optional): unnest parent/child subjectgroups returning a flat list of subjectgroups group_name (string, optional): filter the subjectgroups to this name Returns: [type]: [description] """ p = dict() p['include_inactive'] = include_inactive p['include_hidden'] = include_hidden p['isvisible'] = isvisible p['flat'] = flat p['group_name'] = group_name return self._get('subjectgroups', params=p) def get_sources(self, page_size=100): """Return all sources""" params = dict(page_size=page_size) sources = 'sources' results = self._get(path=sources, params=params) while True: if results and results.get('results'): for r in results['results']: yield r if results and results['next']: _, qparam = split_link(results['next']) params['page'] = qparam['page'] results = self._get(path=sources, params=params) else: break def get_users(self): return self._get('users') class DasClientException(Exception): pass class DasClientPermissionDenied(DasClientException): pass class DasClientServiceUnavailable(DasClientException): pass class DasClientNotFound(DasClientException): pass

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34,143

py

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dasclient.py

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0.558387

0.555165

0

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MaxT2/EWPythonDevelopment

14,774,687,502,634

49def9b3e9840ab2ea8c904543c6cf2385d290ad

f05e792af806f1069238aae3ce966a3268708f41

/RandomStuff/SpaceBackgroundScreenshot/SpaceBackgroundCreator.py

84dc5d491e56d1d093bd144c91ab3e9748bb6c83

[]

no_license

https://github.com/MaxT2/EWPythonDevelopment

9de608e32f319132b85e0ea4a1548872d2c90b55

6154b85a0b35438bb51944eddc742684469e6b60

refs/heads/master

2020-06-18T12:10:56.381449

2019-07-11T18:39:04

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0

null

# import pygame library so we can use it! import pygame import random from pathlib import Path from PythonCodingClub import pygameColors # class definitions class Star(pygame.sprite.Sprite): def __init__(self, screen_width, screen_height): pygame.sprite.Sprite.__init__(self) # setup random numbers self.x_speed = 0 self.y_speed = 0 #setup pygame image stuff self.random_size = random.randint(1, 5) self.image = pygame.Surface((self.random_size, self.random_size)) self.image.fill((255, 255, 255)) # setup create bounding box and set position self.rect = self.image.get_rect() self.rect.center = (random.randint(0, screen_width), random.randint(0, screen_height)) # def update(self): # self.rect.x += self.x_speed # self.rect.y += self.y_speed # # # check to see if sprite left screen and reverse direction # if self.rect.top > display_height: # self.kill() # game code that needs to run only once pygame.init() # setup display dimensions display_width = 1000 display_height = 1000 gameSurface = pygame.display.set_mode((display_width, display_height)) # pygame.display.set_caption('Window Caption!') # setup game clock FPS = 60 clock = pygame.time.Clock() # setup game resources # color definitions # create a sprite group to keep track of sprites all_sprites = pygame.sprite.Group() # create stars and put them into all_sprites group so we can update and draw them for x in range(200): all_sprites.add(Star(display_width, display_height)) # draw the display sprites once and show them # fill entire screen with color gameSurface.fill(pygameColors.BLACK) all_sprites.draw(gameSurface) pygame.display.flip() # save a screenshot of the background # check if file exists is not working properly so it always takes a screenshot image_screen_shot = Path("/spaceBackground.jpg") if image_screen_shot.exists(): print("screenshot already exists") else: pygame.image.save(gameSurface, "screenshot1.jpg") print("screenshot saved") # main game loop running = True # when running is True game loop will run while running == True: # get input events and respond to them # if event is .QUIT for event in pygame.event.get(): if event.type == pygame.QUIT: running = False # UPDATE STUFF # if all_sprites.__sizeof__() < 50: # all_sprites.add(Star(display_width, display_height)) # only update FPS (60) times a second clock.tick(FPS) # run update on all sprites in all_sprites group # all_sprites.update() # DRAW STUFF # clear display every frame(redraw background) # gameSurface.fill(pygameColors.BLACK) # draw all sprites in all_sprites groups # all_sprites.draw(gameSurface) # update and redraw entire screen # pygame.display.flip() # update some of the screen # pygame.display.update()

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SpaceBackgroundCreator.py

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eshenkulovilias/month_3

10,110,353,014,800

247546cead6969bef3fe65b9ae4fa2d6bdabdd22

3575106d0386044a3e010c3d454d74bf2ec911f9

/twit_post.py

728aee6ade9be404c405cea9cd23046df533e212

[]

no_license

https://github.com/eshenkulovilias/month_3

92d4a2b7198e18a48ef5c6d8be2471cfb735666b

716e1b5b1677fc47951c21aa78abffbf983ec6a1

refs/heads/main

2023-05-08T11:52:31.614816

2021-06-02T03:26:39

370,043,570

0

null

class CharField: def __init__(self, char, max_length): self.char = char self.max_length = max_length def __str__(self): return self.char class User: def __init__(self, name, age): self.name = name self.age = age def __str__(self): return self.name class Post: def __init__(self, title, body, author): self.title = CharField(title, 10) self.body = CharField(body, 140) self.author = author def __str__(self): return f'Author: {self.author}\nTitle: {self.title}\n{self.body}' user = User('John', 18) post = Post('Welcome!', 'Hi, my name is John.', user) print(post)

UTF-8

Python

false

677

py

5

twit_post.py

5

0.564254

0.553914

0

31

20.83871

73

joelcolucci/mailgunpi

16,595,753,656,094

1e69a10db5d8d50c33bb5ef62518a657c8110332

52fc554d8f11e2b3e2e3dda9a13815b2adc45b62

/tests/mailgunservice/test_api.py

471a57de418665730ecc87a30d8d5ad0f8164757

[]

no_license

https://github.com/joelcolucci/mailgunpi

759fc0b47b8b72062a3a11a867271fccfe4e2ed1

186109e1b5f0aa7575ae2b8ff6636e0c003c6786

refs/heads/master

2016-06-13T15:00:22.305192

2016-06-13T03:00:02

56,538,257

0

null

"""Unit tests for mailgunservice api blueprint """ import json from unittest import TestCase from unittest import main from flask import Flask from smokinggun.mailgunservice import service_api # Create Flask application for blueprint only app = Flask(__name__) app.register_blueprint(service_api, url_prefix='') class MailgunServiceApiTestCase(TestCase): def setUp(self): app.config['TESTING'] = True self.app = app.test_client() def tearDown(self): pass def test_event_endpoint(self): """Test events endpoint returns json response""" response = self.app.get('/mailgunservice/api/v1/event') try: data = json.loads(response.data) except Exception: self.fail("Endpoint did not return JSON") self.assertIsInstance(data, dict) def test_unsubscribe_endpoint(self): """Test events unsubscribe returns json response""" response = self.app.get('/mailgunservice/api/v1/unsubscribe') try: data = json.loads(response.data) except Exception: self.fail("Endpoint did not return JSON") self.assertIsInstance(data, dict) def test_complaint_endpoint(self): """Test events complaint returns json response""" response = self.app.get('/mailgunservice/api/v1/complaint') try: data = json.loads(response.data) except Exception: self.fail("Endpoint did not return JSON") self.assertIsInstance(data, dict) def test_bounce_endpoint(self): """Test events bounce returns json response""" response = self.app.get('/mailgunservice/api/v1/bounce') try: data = json.loads(response.data) except Exception: self.fail("Endpoint did not return JSON") self.assertIsInstance(data, dict) if __name__ == '__main__': main()

UTF-8

Python

false

1,917

py

20

test_api.py

15

0.636411

0.634324

0

74

24.905405

69

andarabr/simvas

9,981,504,029,995

38507d86a308dd2fcec2f25c7e32375450b98f4e

aa694370905208d986a0e29a678f18aef328dfed

/mvasapi/apps.py

c74bb7d6f33348d8467c74b96c6ae71b00c12627

[]

no_license

https://github.com/andarabr/simvas

4d1369a5f2935554f42b330e1630ce7831706016

bb4a9bbc16c0e4c84e754194947756fb7d568b12

refs/heads/master

2023-08-26T22:43:55.396918

2021-11-11T07:54:47

421,659,325

0

null

false

2021-11-11T07:54:48

2021-10-27T03:07:03

2021-11-10T09:29:24

2021-11-11T07:54:47

41

0

Python

false

from django.apps import AppConfig class MvasapiConfig(AppConfig): default_auto_field = 'django.db.models.BigAutoField' name = 'mvasapi'

UTF-8

Python

false

146

py

21

apps.py

14

0.746575

0

6

23.333333

56

mhw32/PersistentHomology

2,585,570,342,328

45c4fe229c4ade63c2971be48a2e4956c18cb776

3096e153fa8400f7c4686ba94d733d0e05c6a54f

/paper/image_tools/gen_fig9_v2.py

2183276ba0f1f46d7be6339905402babe56590f3

[]

no_license

https://github.com/mhw32/PersistentHomology

be9982fcf022cb63541187cfff6421e889dce6ca

db806a5e091eb9c14f03c0720d11eabe9dd089de

refs/heads/master

2021-05-01T12:36:15.017641

2017-10-31T06:24:20

42,668,152

1

0

null

false

2017-04-22T17:05:36

2015-09-17T16:36:51

2017-01-16T18:58:49

2017-04-22T17:05:36

355,699

0

1

Jupyter Notebook

null

import sys, numpy as np sys.path.append('/Users/mikewu/Desktop/Research/persist-homology/') import sub_parse reload(sub_parse) import matplotlib.pyplot as plt import matplotlib import seaborn as sns import warnings warnings.filterwarnings('ignore') name = '/Users/mikewu/Desktop/Research/persist-homology/saved_states/large_sub_set_test/results-' norm = 'True' base = '0.1' paths = [name+str(i)+'-'+base+'baseNorm'+norm+'.txt' for i in range(1, 101)] singles = ['all-silh', 'euler', 'all-euler', 'silh-euler'] doubles = ['indiv_silh', 'indiv-euler', 'contour'] resArr = np.array([sub_parse.parse(f) for f in paths]) bighash = {} for characteristic in singles: bighash[characteristic] = sub_parse.prepare1d(resArr, characteristic) for characteristic in doubles: for dim in [0,1,2]: bighash[characteristic+'-dim-'+str(dim)] = sub_parse.prepare2d(resArr, characteristic, dim) def safelog10(B, noise=1e-5): B[B == 0] += noise return np.log10(B) import rpy2.robjects as robjects from rpy2.robjects.numpy2ri import numpy2ri import numpy as np def rds_to_np(Rfile): ''' Convert .RData to be able to load the array into Python. Rfile := (str) location of file to translate to Python. ''' raw = robjects.r['readRDS'](Rfile) return raw # bighash for CORR: if norm == 'False': corr_data = np.array(rds_to_np('/Users/mikewu/Desktop/Research/persist-homology/correlation/sub_output/voronoi_proba_norm(0).rds')) pi_data = np.load('/Users/mikewu/Desktop/Research/persist-homology/intensity/output/sub_proba/nonorm/ans-voronoi-nodim.npy') wkc_data = np.load('/Users/mikewu/Desktop/Research/persist-homology/intensity/output/sub_proba/nonorm/ans-voronoi-bydim.npy') else: corr_data = np.array(rds_to_np('/Users/mikewu/Desktop/Research/persist-homology/correlation/sub_output/voronoi_proba_norm(1).rds')) pi_data = np.load('/Users/mikewu/Desktop/Research/persist-homology/intensity/output/sub_proba/yesnorm/ans-voronoi-nodim.npy') wkc_data = np.load('/Users/mikewu/Desktop/Research/persist-homology/intensity/output/sub_proba/yesnorm/ans-voronoi-bydim.npy') bighash_corr = {'corr': np.array(corr_data.T)} # bighash for wik wkc_data = np.log(1 - np.exp(wkc_data)) pi_data = np.log(1 - np.exp(pi_data)) wkc_0 = wkc_data[:, 0, :] wkc_1 = wkc_data[:, 1, :] wkc_2 = wkc_data[:, 2, :] pi_all = pi_data bighash_wik = {'wik_0': np.array(wkc_0.T), 'wik_1': np.array(wkc_1.T), 'wik_2': np.array(wkc_2.T), 'pi': np.array(pi_data.T) } def get_align_dict(keys, step=0.01): alignment_hash = {} mid_pt = len(allkeys) / 2 base_val = mid_pt * -step for i, key in enumerate(allkeys): alignment_hash[key] = base_val base_val += step return alignment_hash def hard_line_plot(allkeys, allticks, allcolors, bighash, custom_ylim=None, save_path=None): xvalues = np.arange(0.1, 0.35, 0.05) align_values = get_align_dict(allkeys, 0.005) matplotlib.rc('xtick', labelsize=27) matplotlib.rc('ytick', labelsize=27) fig, ax = plt.subplots(figsize=(20,5)) plt.ylabel(r'$log_{10}(p)$', fontsize=40) plt.xlabel('PercFil', fontsize=40) for it in range(5): store_error_max = [] store_error_min = [] for k, c, t in zip(allkeys, allcolors, allticks): xvalue = xvalues[it] + align_values[k] yvalue = [np.percentile(np.log10(np.exp(i)), 50) for i in bighash[k]][it] lower_error = [np.percentile(np.log10(np.exp(i)), 25) for i in bighash[k]] upper_error = [np.percentile(np.log10(np.exp(i)), 75) for i in bighash[k]] store_error_min.append(lower_error[it]) store_error_max.append(upper_error[it]) store_error_min = np.array(store_error_min) store_error_max = np.array(store_error_max) for k, c, t in zip(allkeys, allcolors, allticks): xvalue = xvalues[it] + align_values[k] yvalue = [np.percentile(np.log10(np.exp(i)), 50) for i in bighash[k]][it] lower_error = [np.percentile(np.log10(np.exp(i)), 25) for i in bighash[k]] upper_error = [np.percentile(np.log10(np.exp(i)), 75) for i in bighash[k]] pos = [xvalue] ypt = [yvalue] err = [[yvalue - lower_error[it]], [upper_error[it] - yvalue]] plt.errorbar(pos, ypt, yerr=err, lw=6, alpha=0.4, color=c, capsize=20, capthick=6) for k, c, t in zip(allkeys, allcolors, allticks): xvalue = xvalues[it] + align_values[k] yvalue = [np.percentile(np.log10(np.exp(i)), 50) for i in bighash[k]][it] plt.scatter([xvalue], [yvalue], color=c, marker='o', alpha=1, s=300) # put it here so dots are the legend plt.legend(allticks, fontsize=30, loc='lower left') ax.xaxis.grid(False) plt.tick_params(axis='both', which='major', labelsize=35) plt.tight_layout() plt.xlim(0.02, 0.33) ax.set_xticklabels([0.00, '', '10%', '15%', '20%', '25%', '30%']) if not custom_ylim is None: plt.ylim(custom_ylim[0], custom_ylim[1]) if save_path: plt.savefig(save_path) else: plt.show() def merge_dicts(*dict_args): ''' Given any number of dicts, shallow copy and merge into a new dict, precedence goes to key value pairs in latter dicts. ''' result = {} for dictionary in dict_args: result.update(dictionary) return result # allkeys = ['euler', 'all-euler', 'indiv-euler-dim-0', 'indiv-euler-dim-1', 'indiv-euler-dim-2'] # allticks = ['EC', 'EC (0:2)', 'EC (0)', 'EC (1)', 'EC (2)'] # allcolors = ['#44B3C2', '#F1A94E', '#E45641', '#5D4C46', '#7B8D8E'] # hard_line_plot(allkeys, allticks, allcolors, bighash, custom_ylim=[-7, 1], save_path='figure_8_euler_group_normed.pdf') # allkeys = ['silh-euler', 'all-silh', 'indiv_silh-dim-0', 'indiv_silh-dim-1', 'indiv_silh-dim-2'] # allticks = ['SIL (EC)', 'SIL (0:2)', 'SIL (0)', 'SIL (1)', 'SIL (2)'] # allcolors = ['#44B3C2', '#F1A94E', '#E45641', '#5D4C46', '#7B8D8E'] # hard_line_plot(allkeys, allticks, allcolors, bighash, custom_ylim=[-3.5, 0.5], save_path='figure_8_silhouette_group_normed.pdf') # allkeys = ['contour-dim-0', 'contour-dim-1', 'contour-dim-2'] # allticks = ['IK (0)', 'IK (1)', 'IK (2)'] # allcolors = ['#44B3C2', '#F1A94E', '#E45641', '#5D4C46', '#7B8D8E'] # hard_line_plot(allkeys, allticks, allcolors, bighash, custom_ylim=[-1.8, 0], save_path='figure_8_contour_group_normed.pdf') # allkeys = ['corr'] # allticks = ['CORR'] # allcolors = ['#44B3C2'] # hard_line_plot(allkeys, allticks, allcolors, bighash_corr, custom_ylim=[-5, 1], save_path='figure_8_correlation_group_normed.pdf') # allkeys = ['wik_0', 'wik_1', 'wik_2', 'pi'] # allticks = ['WIK (0)', 'WIK (1)', 'WIK (2)', 'PI'] # allcolors = ['#44B3C2', '#F1A94E', '#E45641', '#5D4C46'] # hard_line_plot(allkeys, allticks, allcolors, bighash_wik, custom_ylim=[-1.2, 0], save_path='figure_8_weighted_contour_group_normed.pdf') bighash_best = merge_dicts(bighash, bighash_wik) allkeys = ['euler', 'silh-euler', 'contour-dim-2', 'wik_2'] allticks = ['EC', 'SIL (EC)', 'IK (2)', 'WIK (2)'] allcolors = ['#44B3C2', '#F1A94E', '#E45641', '#5D4C46'] hard_line_plot(allkeys, allticks, allcolors, bighash_best, save_path='figure_8_best_group_normed.pdf')

UTF-8

Python

false

7,749

py

70

gen_fig9_v2.py

61

0.597755

0.562137

0

198

38.131313

138

mongesan/Atcoder-m0_ngesan-py

18,236,431,170,095

a3b01ee380964443acd439460f9528f168f60863

d27af9d58b91b8cd998ac0eb87d980d304ff0670

/Beginner-Contest/ABC178/ABC178_F.py

63f77f925218a53ab97c450c0ccb5e4a53ff520f

[]

no_license

https://github.com/mongesan/Atcoder-m0_ngesan-py

29dd79daab149003ffc8b6b6bad5fa2e7daa9646

6654af034d4ff4cece1be04c2c8b756976d99a4b

refs/heads/master

2023-08-20T19:50:04.547025

2021-10-27T12:24:51

258,486,105

1

0

null

cnt=0 for i in range(10): for j in range(10): if 0<i<9 and 0<j<9: continue else: print(i,j) cnt+=1 print(cnt)

UTF-8

Python

false

165

py

193

ABC178_F.py

191

0.436364

0.375758

0

9

17.444444

27

nadav7679/Hopfield-Model

12,386,685,716,093

6099dd1004f63e91ffaa7fd7d2b0ff502d11f37c

0aca4f6434bf86958205098f4bc669790ef8c93b

/network.py

c7b16613fdcce7620adefc1f7808754fa81075f0

[]

no_license

https://github.com/nadav7679/Hopfield-Model

6650869509cc2cf429c8cd9b56a864eeb4b275c4

77cfcd5a2bad3ca4979b008e81d4ddc40a0b47e3

refs/heads/master

2022-06-26T11:41:07.779961

2020-05-10T20:42:59

262,868,494

0

null

# Hopfield model - Network class ## By Nadav Porat # ------------------------------------ import numpy as np import matplotlib.pyplot as plt import idx2numpy from scipy.special import erfc from PIL import Image import matplotlib.animation as animation from IPython.display import HTML get_ipython().run_line_magic('matplotlib', 'inline') # -------------- Helpful functions ------------------# def heaviside(value): if value > 0: return 1 else: return -1 def arrayToCell(arr): # A small helpfull function that makes Cell arrays from int arrays res = [] for i in arr: res.append(heaviside(i-0.2)) return res def matrixToArray(mat): arr = [] for i in range(np.shape(mat)[0]): for j in range(np.shape(mat)[1]): arr.append(mat[i][j]) return arr def arrayToMatrix(arr, n, m): # n is the numer of rows, m is the number of columes mat = np.zeros((n,m)) count = 0 for i in range(n): for j in range(m): mat[i][j] = arr[count] count += 1 return mat def overlap(arr1,arr2): if not len(arr1) == len(arr2): print ("Error - The configuration you have entered needs to be a Cell array with length = N") return summ = 0 for i in range(len(arr1)): summ += arr1[i] * arr2[i] return summ/len(arr1) def noiseItUp(arr, p = 0.3): N = len(arr) amount = int(p*N) res = np.copy(arr) for i in range(amount): res[np.random.randint(N)] *= -1 return res def jpgToMatrix(path): im = Image.open(path) im_np = np.asarray(im) try: im_np = im_np[:, :, 0] except IndexError: pass im_np = np.where(im_np<128, -1, 1) return im_np # -------------- The Network Class ------------------# class Network: def __init__(self,N,error=0.01): # Creats a Neuronal network with N neurons and maximum error. # N += 1 # IMPORTENT: I add one artificial Cell to the Network, netTemp = [] # its job is to prevent the system from going in the "Inverted" direction weights = np.zeros((N,N)) for i in range(N): netTemp.append(1) self.length = N self.net = netTemp self.maxError = error self.weights = weights self.numOfMem = 0 self.pError = 0 self.maxMem = 0 prob = 0 while prob < self.maxError: self.maxMem += 1 prob = 0.5*erfc(np.sqrt(N/(2*self.maxMem))) # Calculating the maximum amount of memories that are allowed #to enter the Network def insertMemory(self,mem): # Inserting a memory to the system, mem needs to be an N lengthed array self.numOfMem += 1 N = self.length if len(mem) != len(self.net): # Dealing with wrong enteries print ("Error - The memory you have entered needs to be a Cell array with length = N") return # if self.numOfMem != 1: # self.weights *= (self.numOfMem-1) # This line's intent is to remove the previous normalization. #You can imagine how annoyed iv'e beeb when I realized I missed this petty detial at first. for i in range(len(mem)): for j in range(len(mem)): if i == j: self.weights[i][j] = 0 else: self.weights[i][j] += (mem[i] * mem[j])/N # Adding in the Generalized-Hebb-rule weights # self.weights *= 1/self.numOfMem # Re-normalization self.pError = 0.5*erfc(np.sqrt(self.length/(2*self.numOfMem))) # Recalculating the current error of the Network with the new memory def update(self): # Updating a single random Cell in the network omega = self.weights N = self.length net = self.net num = np.random.randint(0,N) summ = 0 for i in range(N): summ += omega[num][i]*net[i] # Weighted sum self.net[num] = heaviside(summ) # Updating the num Cell def quickUpdate(self): # Updating the system N times (N number of Cells) for i in range(self.length): self.update() def printNet(self): for i in range(self.length): if i == 0: print("[%d" %self.net[i], end="") elif i == self.length-1: print(", %d]" %self.net[i]) # Just trying to make it pretty :) else: print(", %d" %self.net[i],end="") def setNet(self,config): # Setting some configuration to the system if not len(config) == self.length: print ("Error - The configuration you have entered needs to be a Cell array with length = N") return for i in range(self.length): self.net[i] = heaviside(config[i]) def clear(self): N = self.length netTemp = [] weights = np.zeros((N,N)) for i in range(N): netTemp.append(1) self.net = netTemp self.weights = weights self.numOfMem = 0 self.pError = 0 def energy(self): summ = 0 for i in range(self.length): for j in range(self.length): if i == j: continue summ += self.weights[i][j]*self.net[i]*self.net[j] return (-1/2)*summ def crosstalk(self,mem, num = -100): # The memory inserted (mem) must be a memory that is already embedded in the Network (otherwise the result has no meaning) # The crosstalk is calculated for a single cell denoted with num. If a cell is not given, one is chosen randomly. N = self.length if num == -100 : num = np.random.randint(0,N) weights = self.weights summ = 0 if not len(mem) == self.length: print ("Error - The configuration you have entered needs to be a Cell array with length = N") for i in range(N): for j in range(N): weights[i][j] -= mem[i] summ += weights[num][i]*mem[i] return summ*mem[num]*(-1) # -------------- Network assisting functions ------------------# def loadMatToNet(Net,mat): mem = matrixToArray(mat) mem1 = arrayToCell(mem) Net.insertMemory(mem1) def makeVid(net,updates = -1,test = None, name = None, title = None): if updates == -1: updates = 5*net.length ims = [] length = int(np.sqrt(net.length)) step = 5*(1+int(length/100)) # The step size is taken from trial and error fig = plt.figure(figsize=(6,6)) for i in range(updates): if i%step == 0: if test != None: net_copy = np.copy(net.net) for j in range(net.length): if net_copy[j] != test[j]: net_copy[j] = -0.2 if title != None: plt.title(title) mat = arrayToMatrix(net_copy,length,length) im = plt.imshow(mat, animated=True,cmap="gray") plt.axis("off") else: if title != None: plt.title(title) mat = arrayToMatrix(net.net,length,length) im = plt.imshow(mat, animated=True,cmap="gray") plt.axis("off") ims.append([im]) net.update() ani = animation.ArtistAnimation(fig, ims, interval=10, blit=True,repeat_delay=500) HTML(ani.to_html5_video()) if name != None: ani.save(name + ".mp4") return

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Python

false

8,258

py

2

network.py

2

0.49782

0.486922

0

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141

liman21/qiyexinyong

7,567,732,390,180

b176ece3f890b701874475bfacff3a832fe0791b

5c6df020950d6f684903d3c6cd22f74c7bacbf34

/企查查/xin/zhanghao.py

8449b8016c8cf75e386e33bdb6791bf31a85d497

[]

no_license

https://github.com/liman21/qiyexinyong

5a569b1a03ec5492897b81cc856ab81e0d0c7e4d

9f05332e934c33b2ce446f78a699e29abda93485

refs/heads/master

2022-12-05T11:35:33.193184

2020-08-31T03:26:27

291,604,379

0

null

import requests,re url='https://www.yinsiduanxin.com/' con=requests.get(url).content.decode('utf-8').replace('\n','').replace('\t','').replace('\r','') conts=re.findall(' <a href="/(\w+)-phone-number/verification-code-(\d+)\.html" class="clickA"',con) for cont in conts: tell=cont[1] link='https://www.yinsiduanxin.com/'+cont[0]+f'-phone-number/verification-code-{tell}.html' con1 = requests.get(link).content.decode('utf-8').replace('\n', '').replace('\t', '').replace('\r', '') print('vv')

UTF-8

Python

false

508

py

23

zhanghao.py

20

0.637795

0.627953

0

10

49.9

107

gabbpuy/django-discordbot

3,856,880,636,815

fbe1308b848910334c5fe10724e5ed508fb66f71

24c9e2bdb02debeb5f95ac439760f36f3c7171f1

/discordbot/botevents/__init__.py

50bac56d1297158acafb5275ff808f78d1efea0b

[ "MIT" ]

permissive

https://github.com/gabbpuy/django-discordbot

a63f3ce0b042c56475863158a3d6a2595627f127

7da39206b9b01f615447ca824851e79fafbe9305

refs/heads/master

2023-05-24T10:19:32.436866

2021-06-10T19:05:34

null

0

null

from discordbot.botevents.on_command_error import setup as setup_on_command_error from discordbot.botevents.on_command import setup as setup_on_command from discordbot.botevents.on_message import setup as setup_on_message from discordbot.botevents.general import setup as setup_general def setup(bot): setup_on_command_error(bot) setup_on_command(bot) setup_on_message(bot) setup_general(bot)

UTF-8

Python

false

409

py

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__init__.py

55

0.792176

0

10

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81

manch93/vfs-slots-api-monitor

10,849,087,412,761

b85c047a7fee80b48de14eb40b1f024c3fb8f963

e0089c60a870e1837c321ef9a1293ff75359a306

/PingVFS.py

97d55a252966331c7d061363ad124b7cad438325

[ "MIT" ]

permissive

https://github.com/manch93/vfs-slots-api-monitor

bf6fdbdf1bc0843199837ee69f90b3636701d747

864342fd1e144971df2a31e45b120fb22536f2bd

refs/heads/main

2023-06-14T21:30:16.700534

2021-07-15T02:19:11

null

0

null

#!/usr/bin/env python import os import sys import time import json import requests import subprocess from playsound import playsound from urllib.parse import urlencode, quote_plus from datetime import datetime, timedelta class PingVFS: # default constructor def __init__(self, params): self.url = params["url"] self.urlparams = params["urlparams"] self.paths = params["paths"] self.auth = "" self.start_time = datetime.now() self.sound = params["sound"] def get_auth_token(self): if not os.path.isfile(self.paths["auth"]): return False path = os.path.realpath(self.paths["auth"]) read = open(path, "r") auth = read.read().replace("\n", " ") read.close() if auth == self.auth: return self.auth self.auth = auth # os.remove(path) return self.auth def store_output(self, output): # Saving the output in result.txt. with open(self.paths["output"], "a") as file_object: # Append 'hello' at the end of file file_object.write(output) def get_foramtted_date(self, date): return datetime.strptime(str(date), "%Y-%m-%d").strftime("%d/%m/%Y") def hit_vfs(self): headers = { "Content-length" : "0", "Content-type" : "application/json", } headers["Authorization"] = self.auth from_date = datetime.now().date() + timedelta(days = 1) to_date = from_date + timedelta(days = 90) self.urlparams["fromDate"] = str(self.get_foramtted_date(from_date)) self.urlparams["toDate"] = str(self.get_foramtted_date(to_date)) url = self.url \ + "?" \ + urlencode(self.urlparams, quote_via=quote_plus) try: resp = requests.get(url, headers=headers) except: return "ERROR Connection Refused" if os.path.isfile(self.paths["auth"]): self.get_auth_token() try: resp = resp.json() except: return "ERROR " + str(resp.status_code) return json.dumps(resp) def init(self): auth = self.get_auth_token() count = 0 print(""" ██ ██ ███████ ███████ ███████ ██ ██████ ████████ ███████ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ █████ ███████ ███████ ██ ██ ██ ██ ███████ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ████ ██ ███████ ███████ ███████ ██████ ██ ███████ ██ ██ ██""") print("\n") print("Started at:", end =" ") print(datetime.now()) print("Trying to access VFS appointment API for slots...") print("\n") while True: time.sleep(5) request = self.hit_vfs() count += 1 output = "\nOutput: " \ + str(request) \ + "\nTime: " \ + str(datetime.now()) \ + "\nCount: " \ + str(count) \ + "\n===" self.store_output(output) # Printing the output in terminal. # print(output) print(".", end="", flush=True), if request == "[[]]": continue try: request = json.loads(request) except: continue try: if request[0]["counters"] != None: break except: continue subprocess.call([ "/usr/bin/notify-send", "VFS Slots!!!", "Something Positive May Have Happend." ]) print("\n") print(str(count) + " times HTTP 200 response received.") print("Ended at:", end =" ") print(datetime.now()) time_diff = datetime.now() - self.start_time time_diff = time_diff.total_seconds() / 60.0 print("Script ran for " + str(time_diff) + " minutes") # Will play the alert sound. playsound(self.sound) def main(params): if not os.path.isfile(params): return False path = os.path.realpath(params) read = open(path, "r") params = json.loads(read.read()) read.close() ping = PingVFS(params) ping.init() if __name__ == "__main__": main("./ping_creds.json")

UTF-8

Python

false

5,062

py

9

PingVFS.py

4

0.463415

0.46031

0

158

27.544304

83

vanshdevgan/Crypton

1,589,137,913,906

c2f4cf155aba2b72dc6902c883daec4683d19376

9c923224c9422f4da3336bb6bdadb9d550a30eb0

/RSA-encryption/Attack-Coppersmith/exploit.py

41062c7e23746cd15d55bb7b3f5e2422642b7c3d

[ "MIT" ]

permissive

https://github.com/vanshdevgan/Crypton

d8f79f6d0a456fb13253913ffb27ebc6f47a6454

92033a94bc6e7a543117dcef51407121ac7acfa2

refs/heads/master

2021-07-02T08:40:40.068449

2020-10-02T15:57:58

181,874,564

0

2

MIT

true

2020-10-16T16:10:05

2019-04-17T11:08:37

2020-10-02T15:58:02

2020-10-02T15:57:59

1,138

0

2

1

Python

false

from sage.all import * # f is the monic polynomial f(x) = (m + x)**e - c whose roots we have to find def stereotyped(f, N): P.<x> = PolynomialRing(Zmod(N)) beta = 1 dd = f.degree() # Degree of the polynomial epsilon = beta/7 XX = ceil(N**((beta**2/dd) - epsilon)) rt = f.small_roots(XX, beta, epsilon) return rt def N-factorize(f, N): P.<x> = PolynomialRing(Zmod(N)) beta = 0.5 dd = f.degree() # Degree of the polynomial epsilon = beta/7 XX = ceil(N**((beta**2/dd) - epsilon)) rt = f.small_roots(XX, beta, epsilon) return rt

UTF-8

Python

false

588

py

204

exploit.py

69

0.585034

0.573129

0

20

28.4

77

ytgw/01_MicroMouse2016

7,567,732,402,304

db987e08beaf2aff796f56c2b59b79bc9e700208

20ab163d5c8052322e8ea235d2c32fd99ab83c03

/middleware.py

a0b13829539f5f440f0e29ca9a5703efbd3f7da4

[]

no_license

https://github.com/ytgw/01_MicroMouse2016

3eea19a1c3567ddc33d0d57b71124ae4e4aced9c

b4bc0c1d0f6e940be88b3b8b7bf6b6cd3d0cfea8

refs/heads/master

2017-04-26T19:41:35.663047

2016-08-30T13:25:13

66,799,173

0

null

true

2016-08-29T00:51:29

2016-08-04T16:18:10

2016-08-28T16:35:15

876

0

null

# coding: UTF-8 #-----------------------------------------------------------------------------# # Declation # #-----------------------------------------------------------------------------# # 各デバイスドライバのパス sensor_driver = "/dev/rtlightsensor0" switch_driver = [ "/dev/rtswitch0", "/dev/rtswitch1"] buzzer_driver = "/dev/rtbuzzer0" motor_driver = [ "/dev/rtmotor_raw_l0", "/dev/rtmotor_raw_r0"] led_driver = [ "/dev/rtled0", "/dev/rtled1", "/dev/rtled2", "/dev/rtled3"] # デバイスドライバから取得した値を格納する配列 sensor_data = [0, 0, 0, 0] # [距離センサー0の取得値, 1の値, 2の値, 3の値] switch_state = [0, 0, 0] # [タクトスイッチ0の取得値, 1の値, 2の値] #-----------------------------------------------------------------------------# # Input system (入力系) # #-----------------------------------------------------------------------------# def sensorinfo(): # 距離センサの値を取得する # デバイスドライバが見つかった場合 => tryの処理 # デバイスドライバが見つからなかった場合 => exceptの処理 try: filename = sensor_driver with open(filename,"r") as f: # f.readlin() の返り値は 8要素の配列データ(すべての要素は文字列) # 要素0 = 距離センサ0の取得値(文字列) # 要素1 = スペース(文字列) # 要素2 = 距離センサ1の取得値(文字列) # 要素3 = スペース(文字列) # 要素4 = 距離センサ2の取得値(文字列) # 要素5 = スペース(文字列) # 要素6 = 距離センサ3の取得値(文字列) # 要素7 = \n(改行コード) temp = f.readline() # デバイスドライバから取得できる値は文字列なので数値に変換する # 要素1,要素3, 要素5のスペースを削除 # 要素7の改行コードを削除 info = [int(temp[0]), int(temp[2]), int(temp[4]), int(temp[6])] except: # デバイスドライバが見つからない場合は全ての要素に数値の255を代入する info = [ 255, 255, 255, 255 ] sensor_info = info return sensor_info def switchstate(): # タクトスイッチの値を取得する # デバイスドライバが見つかった場合 => tryの処理 # デバイスドライバが見つからなかった場合 => exceptの処理 try: for i, filename in enumerate(switch_driver): with open(filename,"r") as f: # f.readlin() の返り値は 2要素の配列データ(すべての要素は文字列) # 要素0 = "0":押されてない or "1":押されている # 要素1 = \n(改行コード) temp = f.readline() # デバイスドライバから取得できる値は文字列なので数値に変換する # 要素1は改行コードなので削除 state[i] = int(temp[0]) except: # デバイスドライバが見つからない場合は全ての要素に数値の-1を代入する state = [ -1, -1, -1 ] switch_state = state return switch_state #-----------------------------------------------------------------------------# # Output system (出力系) # #-----------------------------------------------------------------------------# def buzzer(frequency): # ブザーを鳴らす # 引数は鳴らす音の周波数(Hz) # デバイスドライバが見つかった場合 => tryの処理 # デバイスドライバが見つからなかった場合 => exceptの処理 try: filename = buzzer_driver with open(filename,"w") as f: f.write(frequency) ret = True except: ret = False return ret def motor(speed): # モーターを駆動する # 引数は配列データ( speed = [ 左モータの回転数(Hz), 右モータの回転数(Hz) ] ) # デバイスドライバが見つかった場合 => tryの処理 # デバイスドライバが見つからなかった場合 => exceptの処理 try: for i, filename in enumerate(motor_driver): with open(filename,"w") as f_r_m: f.write(str(speed[i])) ret = True except: ret = False return ret def led(led_state): # LEDを駆動する # 引数は配列データ( led_state = [ led_0, led_1, led_2,led_3 ] ) # "led_X = 0" => Off , "led_X = 1" => ON # デバイスドライバが見つかった場合 => tryの処理 # デバイスドライバが見つからなかった場合 => exceptの処理 try: for i,filename in enumerate(led_driver): with open(filename,'w') as f: f.write(led_state[i]) ret = True except: ret = False return ret

UTF-8

Python

false

5,152

py

4

middleware.py

3

0.455315

0.434691

0

110

33.390909

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jl223vy/Catching-a-Python

19,628,000,563,000

b804a6f8f0ea07a96eabbe6fc2fbd9bc1a4293e4

8689bf35529fd245df659abbbeaaa158d91cf749

/Test/用户登录（三次机会）.py

de98a903bb9a96e1308bb385078c9560ddc45d6c

[]

no_license

https://github.com/jl223vy/Catching-a-Python

56a5ebd5994b221233b6504dd0de975fa7b4738e

1a8495bfc35f4a98d061783c65d84bfe415c3f13

refs/heads/master

2021-05-08T19:05:39.701496

2018-07-09T13:58:44

119,550,132

1

0

null

def main(): name = "Kate" psw = "666666" flag = 1 for i in range(3): tName = input() tPsw = input() if tName == name and tPsw == psw: print("登录成功！") break else: flag = 0 if flag == 0: print("3次用户名或者密码均有误！退出程序。") main()

UTF-8

Python

false

361

py

41

用户登录（三次机会）.py

40

0.429022

0.394322

0

17

17.647059

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abbasjam/abbas_repo

2,319,282,364,171

5dd40a792a30e6f0134a1eb3beb7501b77d0d1c9

8ff01e8bbb04a6411a16766f29ff6bc94878be0c

/python/dev-ops/python/pythan-class/set_example2.py

3d3fac7648bca127372c2422830502278c8a1e23

[]

no_license

https://github.com/abbasjam/abbas_repo

5642db639e12b5ec99f88834b472e44567b5e3aa

6a55288ba7c7e44f55f034b0e4978c51da6d2116

refs/heads/master

2020-08-17T23:12:47.168145

2020-03-23T09:15:41

215,722,331

4

null

print ("Set Manipulations") print ("-----------------") x={1,2,3,4,5,6} print ("Given x is :",x) x.discard(5) print ("after discard(5):",x) x.discard(100) print ("After discard(100):",x)

UTF-8

Python

false

187

py

229

set_example2.py

153

0.572193

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0

8

22.375

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Kuroko0o/eje_python

13,683,765,806,392

617cc3362893cf70d5fb52e38a59a92b155bef2b

d2078cf5931ceb38307ee74da918ada83d28b867

/promedios.py

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permissive

https://github.com/Kuroko0o/eje_python

98255d08ba262b343ea75eaf375bf827812cd1fe

12580bdcb2b70b89b20e2566bf17870ba4532ef2

refs/heads/master

2022-11-09T13:34:46.832207

2020-06-21T03:58:29

273,349,945

0

null

print(" ****** Bienvenido al Registro de Promedios por Materias Y Alumnos ****** ") print(" ") print ("*******************************************************") print(" ") k = input("Ingresar la cantidad deseada de nombres de alumnos y promedios que desea conseguir: \n") try: cant = int(k) except : print("La Cantidad ingresada no es valida! Intentelo nuevamente reiniciando el registro!") for cuenta in range(cant): a = input("Ingresar nombre de alumno completo: \n") b = input("Ingresar la materia (Lengua/Historia/Matematica/Geografia/Quimica/ Etc.): \n") c = input("Ingresar Calificación del Primer Trimestre: \n") d = input("Ingresar Calificación del Segundo Trimestre: \n") e = input ("Ingresar Calificación del Tercer Trimestre: \n") try: n = float(c) nu = float(d) num = float(e) except : print("-----------------------------------------------------------------------------") print("Valor ingresado en calificación NO es valido, vuelva a intentarlo!") print("-----------------------------------------------------------------------------") break total = (n + nu + num) / 3 print("---------------------------------------------------------------------------------") print(" El alumno: \n", a , "\n tiene un promedio de: \n", total, "\n en la materia: \n", b) print("---------------------------------------------------------------------------------") print("************************************************************") print(" ****** Sus promedios fueron mostrados, gracias por usar el registro ******")

UTF-8

Python

false

1,630

py

5

promedios.py

3

0.456335

0.45572

0

32

49.8125

99

xielinshai1992/PyQt5

11,553,462,035,406

787724c7d651a4e447a4673a2d5a4868a3ff5b0e

b9004f0539279fe61539164076d8e71b8a884965

/create_airportdata/adsb_mainForm.py

2c8360d0b8ccf90a19ad819d51850de563a8581d

[]

no_license

https://github.com/xielinshai1992/PyQt5

2576eaa3dd672da94a0cab389ad3a1a5eb48df50

a295b8d97165f8fec7f7e4b64ffc75604ac91269

refs/heads/master

2021-06-15T18:18:12.748160

2021-05-14T09:02:52

200,157,657

1

0

null

# -*- coding: utf-8 -*- # Form implementation generated from reading ui file 'adsb_mainForm.ui' # # Created by: PyQt5 UI code generator 5.11.3 # # WARNING! All changes made in this file will be lost! from PyQt5 import QtCore, QtGui, QtWidgets class Ui_MainWindow(object): def setupUi(self, MainWindow): MainWindow.setObjectName("MainWindow") MainWindow.resize(1550, 880) MainWindow.setMaximumSize(QtCore.QSize(1550, 880)) icon = QtGui.QIcon() icon.addPixmap(QtGui.QPixmap("C:/Users/Administrator/.designer/backup/pic/airport.png"), QtGui.QIcon.Normal, QtGui.QIcon.Off) MainWindow.setWindowIcon(icon) MainWindow.setToolTipDuration(0) self.centralwidget = QtWidgets.QWidget(MainWindow) self.centralwidget.setObjectName("centralwidget") self.groupBox_2 = QtWidgets.QGroupBox(self.centralwidget) self.groupBox_2.setGeometry(QtCore.QRect(920, 370, 611, 491)) font = QtGui.QFont() font.setFamily("宋体") font.setPointSize(11) self.groupBox_2.setFont(font) self.groupBox_2.setObjectName("groupBox_2") self.tabWidget = QtWidgets.QTabWidget(self.groupBox_2) self.tabWidget.setGeometry(QtCore.QRect(10, 25, 591, 461)) self.tabWidget.setObjectName("tabWidget") self.tab = QtWidgets.QWidget() self.tab.setObjectName("tab") self.frame_target = QtWidgets.QFrame(self.tab) self.frame_target.setGeometry(QtCore.QRect(0, 0, 591, 421)) self.frame_target.setFrameShape(QtWidgets.QFrame.StyledPanel) self.frame_target.setFrameShadow(QtWidgets.QFrame.Raised) self.frame_target.setObjectName("frame_target") self.groupBox_tcas_target1 = QtWidgets.QGroupBox(self.frame_target) self.groupBox_tcas_target1.setGeometry(QtCore.QRect(310, 50, 271, 361)) self.groupBox_tcas_target1.setObjectName("groupBox_tcas_target1") self.btn_stopsend_tcas_target1 = QtWidgets.QPushButton(self.groupBox_tcas_target1) self.btn_stopsend_tcas_target1.setGeometry(QtCore.QRect(10, 318, 251, 28)) self.btn_stopsend_tcas_target1.setObjectName("btn_stopsend_tcas_target1") self.layoutWidget = QtWidgets.QWidget(self.groupBox_tcas_target1) self.layoutWidget.setGeometry(QtCore.QRect(10, 40, 251, 261)) self.layoutWidget.setObjectName("layoutWidget") self.gridLayout_3 = QtWidgets.QGridLayout(self.layoutWidget) self.gridLayout_3.setContentsMargins(0, 0, 0, 0) self.gridLayout_3.setObjectName("gridLayout_3") self.label_27 = QtWidgets.QLabel(self.layoutWidget) self.label_27.setScaledContents(True) self.label_27.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_27.setObjectName("label_27") self.gridLayout_3.addWidget(self.label_27, 0, 0, 1, 1) self.txt_Track_ID_target1 = QtWidgets.QLineEdit(self.layoutWidget) self.txt_Track_ID_target1.setEnabled(False) self.txt_Track_ID_target1.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_Track_ID_target1.setText("") self.txt_Track_ID_target1.setObjectName("txt_Track_ID_target1") self.gridLayout_3.addWidget(self.txt_Track_ID_target1, 0, 1, 1, 1) self.label_26 = QtWidgets.QLabel(self.layoutWidget) self.label_26.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_26.setObjectName("label_26") self.gridLayout_3.addWidget(self.label_26, 1, 0, 1, 1) self.txt_Tcas_Altitude_target1 = QtWidgets.QLineEdit(self.layoutWidget) self.txt_Tcas_Altitude_target1.setEnabled(False) self.txt_Tcas_Altitude_target1.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_Tcas_Altitude_target1.setText("") self.txt_Tcas_Altitude_target1.setObjectName("txt_Tcas_Altitude_target1") self.gridLayout_3.addWidget(self.txt_Tcas_Altitude_target1, 1, 1, 1, 1) self.label_23 = QtWidgets.QLabel(self.layoutWidget) self.label_23.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_23.setObjectName("label_23") self.gridLayout_3.addWidget(self.label_23, 2, 0, 1, 1) self.txt_Relative_Direction_target1 = QtWidgets.QLineEdit(self.layoutWidget) self.txt_Relative_Direction_target1.setEnabled(False) self.txt_Relative_Direction_target1.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_Relative_Direction_target1.setText("") self.txt_Relative_Direction_target1.setObjectName("txt_Relative_Direction_target1") self.gridLayout_3.addWidget(self.txt_Relative_Direction_target1, 2, 1, 1, 1) self.label_21 = QtWidgets.QLabel(self.layoutWidget) self.label_21.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_21.setObjectName("label_21") self.gridLayout_3.addWidget(self.label_21, 3, 0, 1, 1) self.txt_Relative_Distance_target1 = QtWidgets.QLineEdit(self.layoutWidget) self.txt_Relative_Distance_target1.setEnabled(False) self.txt_Relative_Distance_target1.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_Relative_Distance_target1.setText("") self.txt_Relative_Distance_target1.setObjectName("txt_Relative_Distance_target1") self.gridLayout_3.addWidget(self.txt_Relative_Distance_target1, 3, 1, 1, 1) self.btn_import_info_target1 = QtWidgets.QPushButton(self.frame_target) self.btn_import_info_target1.setGeometry(QtCore.QRect(10, 15, 241, 28)) self.btn_import_info_target1.setObjectName("btn_import_info_target1") self.groupBox_adsb_target1 = QtWidgets.QGroupBox(self.frame_target) self.groupBox_adsb_target1.setGeometry(QtCore.QRect(10, 50, 291, 361)) self.groupBox_adsb_target1.setObjectName("groupBox_adsb_target1") self.layoutWidget1 = QtWidgets.QWidget(self.groupBox_adsb_target1) self.layoutWidget1.setGeometry(QtCore.QRect(9, 34, 271, 318)) self.layoutWidget1.setObjectName("layoutWidget1") self.gridLayout_2 = QtWidgets.QGridLayout(self.layoutWidget1) self.gridLayout_2.setContentsMargins(0, 0, 0, 0) self.gridLayout_2.setObjectName("gridLayout_2") self.label_4 = QtWidgets.QLabel(self.layoutWidget1) self.label_4.setMaximumSize(QtCore.QSize(144, 16777215)) self.label_4.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_4.setObjectName("label_4") self.gridLayout_2.addWidget(self.label_4, 2, 0, 1, 1) self.txt_Heading_Track_Angle_target1 = QtWidgets.QLineEdit(self.layoutWidget1) self.txt_Heading_Track_Angle_target1.setEnabled(False) self.txt_Heading_Track_Angle_target1.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_Heading_Track_Angle_target1.setText("") self.txt_Heading_Track_Angle_target1.setObjectName("txt_Heading_Track_Angle_target1") self.gridLayout_2.addWidget(self.txt_Heading_Track_Angle_target1, 7, 1, 1, 1) self.txt_FlightID_target1 = QtWidgets.QLineEdit(self.layoutWidget1) self.txt_FlightID_target1.setEnabled(False) self.txt_FlightID_target1.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_FlightID_target1.setText("") self.txt_FlightID_target1.setObjectName("txt_FlightID_target1") self.gridLayout_2.addWidget(self.txt_FlightID_target1, 1, 1, 1, 1) self.txt_V_EW_target1 = QtWidgets.QLineEdit(self.layoutWidget1) self.txt_V_EW_target1.setEnabled(False) self.txt_V_EW_target1.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_V_EW_target1.setText("") self.txt_V_EW_target1.setObjectName("txt_V_EW_target1") self.gridLayout_2.addWidget(self.txt_V_EW_target1, 4, 1, 1, 1) self.txt_Latitude_target1 = QtWidgets.QLineEdit(self.layoutWidget1) self.txt_Latitude_target1.setEnabled(False) self.txt_Latitude_target1.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_Latitude_target1.setText("") self.txt_Latitude_target1.setObjectName("txt_Latitude_target1") self.gridLayout_2.addWidget(self.txt_Latitude_target1, 5, 1, 1, 1) self.label_11 = QtWidgets.QLabel(self.layoutWidget1) self.label_11.setMaximumSize(QtCore.QSize(90, 16777215)) self.label_11.setScaledContents(True) self.label_11.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_11.setObjectName("label_11") self.gridLayout_2.addWidget(self.label_11, 0, 0, 1, 1) self.label_12 = QtWidgets.QLabel(self.layoutWidget1) self.label_12.setMaximumSize(QtCore.QSize(16777215, 16777214)) self.label_12.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_12.setObjectName("label_12") self.gridLayout_2.addWidget(self.label_12, 3, 0, 1, 1) self.txt_V_SN_target1 = QtWidgets.QLineEdit(self.layoutWidget1) self.txt_V_SN_target1.setEnabled(False) self.txt_V_SN_target1.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_V_SN_target1.setText("") self.txt_V_SN_target1.setObjectName("txt_V_SN_target1") self.gridLayout_2.addWidget(self.txt_V_SN_target1, 3, 1, 1, 1) self.label_15 = QtWidgets.QLabel(self.layoutWidget1) self.label_15.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_15.setObjectName("label_15") self.gridLayout_2.addWidget(self.label_15, 4, 0, 1, 1) self.label_14 = QtWidgets.QLabel(self.layoutWidget1) self.label_14.setMaximumSize(QtCore.QSize(90, 16777215)) self.label_14.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_14.setObjectName("label_14") self.gridLayout_2.addWidget(self.label_14, 1, 0, 1, 1) self.txt_Longitude_target1 = QtWidgets.QLineEdit(self.layoutWidget1) self.txt_Longitude_target1.setEnabled(False) self.txt_Longitude_target1.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_Longitude_target1.setText("") self.txt_Longitude_target1.setObjectName("txt_Longitude_target1") self.gridLayout_2.addWidget(self.txt_Longitude_target1, 6, 1, 1, 1) self.label_17 = QtWidgets.QLabel(self.layoutWidget1) self.label_17.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_17.setObjectName("label_17") self.gridLayout_2.addWidget(self.label_17, 8, 0, 1, 1) self.label_18 = QtWidgets.QLabel(self.layoutWidget1) self.label_18.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_18.setObjectName("label_18") self.gridLayout_2.addWidget(self.label_18, 7, 0, 1, 1) self.label_13 = QtWidgets.QLabel(self.layoutWidget1) self.label_13.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_13.setObjectName("label_13") self.gridLayout_2.addWidget(self.label_13, 5, 0, 1, 1) self.txt_ICAO_target1 = QtWidgets.QLineEdit(self.layoutWidget1) self.txt_ICAO_target1.setEnabled(False) self.txt_ICAO_target1.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_ICAO_target1.setText("") self.txt_ICAO_target1.setObjectName("txt_ICAO_target1") self.gridLayout_2.addWidget(self.txt_ICAO_target1, 0, 1, 1, 1) self.txt_Altitude_target1 = QtWidgets.QLineEdit(self.layoutWidget1) self.txt_Altitude_target1.setEnabled(False) self.txt_Altitude_target1.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_Altitude_target1.setText("") self.txt_Altitude_target1.setObjectName("txt_Altitude_target1") self.gridLayout_2.addWidget(self.txt_Altitude_target1, 2, 1, 1, 1) self.label_16 = QtWidgets.QLabel(self.layoutWidget1) self.label_16.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_16.setObjectName("label_16") self.gridLayout_2.addWidget(self.label_16, 6, 0, 1, 1) self.txt_GroundSpeed_target1 = QtWidgets.QLineEdit(self.layoutWidget1) self.txt_GroundSpeed_target1.setEnabled(False) self.txt_GroundSpeed_target1.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_GroundSpeed_target1.setText("") self.txt_GroundSpeed_target1.setObjectName("txt_GroundSpeed_target1") self.gridLayout_2.addWidget(self.txt_GroundSpeed_target1, 8, 1, 1, 1) self.btn_stopsend_adsb_target1 = QtWidgets.QPushButton(self.layoutWidget1) self.btn_stopsend_adsb_target1.setObjectName("btn_stopsend_adsb_target1") self.gridLayout_2.addWidget(self.btn_stopsend_adsb_target1, 9, 0, 1, 2) self.tabWidget.addTab(self.tab, "") self.groupBox_3 = QtWidgets.QGroupBox(self.centralwidget) self.groupBox_3.setGeometry(QtCore.QRect(1230, 0, 301, 361)) font = QtGui.QFont() font.setFamily("宋体") font.setPointSize(11) self.groupBox_3.setFont(font) self.groupBox_3.setObjectName("groupBox_3") self.btn_start = QtWidgets.QPushButton(self.groupBox_3) self.btn_start.setGeometry(QtCore.QRect(50, 120, 201, 28)) self.btn_start.setObjectName("btn_start") self.btn_stop = QtWidgets.QPushButton(self.groupBox_3) self.btn_stop.setEnabled(False) self.btn_stop.setGeometry(QtCore.QRect(50, 180, 201, 28)) self.btn_stop.setObjectName("btn_stop") self.groupBox = QtWidgets.QGroupBox(self.centralwidget) self.groupBox.setGeometry(QtCore.QRect(920, 0, 291, 361)) font = QtGui.QFont() font.setFamily("宋体") font.setPointSize(11) self.groupBox.setFont(font) self.groupBox.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignTop) self.groupBox.setFlat(False) self.groupBox.setCheckable(False) self.groupBox.setObjectName("groupBox") self.layoutWidget2 = QtWidgets.QWidget(self.groupBox) self.layoutWidget2.setGeometry(QtCore.QRect(20, 30, 241, 318)) self.layoutWidget2.setObjectName("layoutWidget2") self.gridLayout = QtWidgets.QGridLayout(self.layoutWidget2) self.gridLayout.setContentsMargins(0, 0, 0, 0) self.gridLayout.setObjectName("gridLayout") self.txt_GroundSpeed_own = QtWidgets.QLineEdit(self.layoutWidget2) self.txt_GroundSpeed_own.setEnabled(False) self.txt_GroundSpeed_own.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_GroundSpeed_own.setText("") self.txt_GroundSpeed_own.setObjectName("txt_GroundSpeed_own") self.gridLayout.addWidget(self.txt_GroundSpeed_own, 13, 2, 1, 1) self.label_2 = QtWidgets.QLabel(self.layoutWidget2) self.label_2.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_2.setObjectName("label_2") self.gridLayout.addWidget(self.label_2, 2, 1, 1, 1) self.txt_Altitude_own = QtWidgets.QLineEdit(self.layoutWidget2) self.txt_Altitude_own.setEnabled(False) self.txt_Altitude_own.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_Altitude_own.setText("") self.txt_Altitude_own.setObjectName("txt_Altitude_own") self.gridLayout.addWidget(self.txt_Altitude_own, 3, 2, 1, 1) self.txt_FlightID_own = QtWidgets.QLineEdit(self.layoutWidget2) self.txt_FlightID_own.setEnabled(False) self.txt_FlightID_own.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_FlightID_own.setText("") self.txt_FlightID_own.setObjectName("txt_FlightID_own") self.gridLayout.addWidget(self.txt_FlightID_own, 2, 2, 1, 1) self.txt_V_EW_own = QtWidgets.QLineEdit(self.layoutWidget2) self.txt_V_EW_own.setEnabled(False) self.txt_V_EW_own.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_V_EW_own.setText("") self.txt_V_EW_own.setObjectName("txt_V_EW_own") self.gridLayout.addWidget(self.txt_V_EW_own, 5, 2, 1, 1) self.label_7 = QtWidgets.QLabel(self.layoutWidget2) self.label_7.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_7.setObjectName("label_7") self.gridLayout.addWidget(self.label_7, 6, 1, 1, 1) self.txt_V_SN_own = QtWidgets.QLineEdit(self.layoutWidget2) self.txt_V_SN_own.setEnabled(False) self.txt_V_SN_own.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_V_SN_own.setText("") self.txt_V_SN_own.setObjectName("txt_V_SN_own") self.gridLayout.addWidget(self.txt_V_SN_own, 4, 2, 1, 1) self.label_9 = QtWidgets.QLabel(self.layoutWidget2) self.label_9.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_9.setObjectName("label_9") self.gridLayout.addWidget(self.label_9, 9, 1, 1, 1) self.label_3 = QtWidgets.QLabel(self.layoutWidget2) self.label_3.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_3.setObjectName("label_3") self.gridLayout.addWidget(self.label_3, 3, 1, 1, 1) self.label_6 = QtWidgets.QLabel(self.layoutWidget2) self.label_6.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_6.setObjectName("label_6") self.gridLayout.addWidget(self.label_6, 5, 1, 1, 1) self.txt_Heading_Track_Angle_own = QtWidgets.QLineEdit(self.layoutWidget2) self.txt_Heading_Track_Angle_own.setEnabled(False) self.txt_Heading_Track_Angle_own.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_Heading_Track_Angle_own.setText("") self.txt_Heading_Track_Angle_own.setObjectName("txt_Heading_Track_Angle_own") self.gridLayout.addWidget(self.txt_Heading_Track_Angle_own, 9, 2, 1, 1) self.label_8 = QtWidgets.QLabel(self.layoutWidget2) self.label_8.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_8.setObjectName("label_8") self.gridLayout.addWidget(self.label_8, 8, 1, 1, 1) self.txt_Longitude_own = QtWidgets.QLineEdit(self.layoutWidget2) self.txt_Longitude_own.setEnabled(False) self.txt_Longitude_own.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_Longitude_own.setText("") self.txt_Longitude_own.setObjectName("txt_Longitude_own") self.gridLayout.addWidget(self.txt_Longitude_own, 8, 2, 1, 1) self.label = QtWidgets.QLabel(self.layoutWidget2) self.label.setScaledContents(True) self.label.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label.setObjectName("label") self.gridLayout.addWidget(self.label, 1, 1, 1, 1) self.txt_Latitude_own = QtWidgets.QLineEdit(self.layoutWidget2) self.txt_Latitude_own.setEnabled(False) self.txt_Latitude_own.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_Latitude_own.setText("") self.txt_Latitude_own.setObjectName("txt_Latitude_own") self.gridLayout.addWidget(self.txt_Latitude_own, 6, 2, 1, 1) self.label_5 = QtWidgets.QLabel(self.layoutWidget2) self.label_5.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_5.setObjectName("label_5") self.gridLayout.addWidget(self.label_5, 4, 1, 1, 1) self.label_10 = QtWidgets.QLabel(self.layoutWidget2) self.label_10.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_10.setObjectName("label_10") self.gridLayout.addWidget(self.label_10, 13, 1, 1, 1) self.txt_ICAO_own = QtWidgets.QLineEdit(self.layoutWidget2) self.txt_ICAO_own.setEnabled(False) self.txt_ICAO_own.setMaximumSize(QtCore.QSize(150, 16777215)) self.txt_ICAO_own.setText("") self.txt_ICAO_own.setObjectName("txt_ICAO_own") self.gridLayout.addWidget(self.txt_ICAO_own, 1, 2, 1, 1) self.btn_import_info_own = QtWidgets.QPushButton(self.layoutWidget2) self.btn_import_info_own.setObjectName("btn_import_info_own") self.gridLayout.addWidget(self.btn_import_info_own, 0, 1, 1, 2) self.horizontalLayoutWidget = QtWidgets.QWidget(self.centralwidget) self.horizontalLayoutWidget.setGeometry(QtCore.QRect(10, 10, 901, 851)) self.horizontalLayoutWidget.setObjectName("horizontalLayoutWidget") self.horizontalLayout_3 = QtWidgets.QHBoxLayout(self.horizontalLayoutWidget) self.horizontalLayout_3.setContentsMargins(0, 0, 0, 0) self.horizontalLayout_3.setObjectName("horizontalLayout_3") self.layoutWidget3 = QtWidgets.QWidget(self.centralwidget) self.layoutWidget3.setGeometry(QtCore.QRect(0, 0, 2, 2)) self.layoutWidget3.setObjectName("layoutWidget3") self.horizontalLayout = QtWidgets.QHBoxLayout(self.layoutWidget3) self.horizontalLayout.setContentsMargins(0, 0, 0, 0) self.horizontalLayout.setObjectName("horizontalLayout") self.layoutWidget4 = QtWidgets.QWidget(self.centralwidget) self.layoutWidget4.setGeometry(QtCore.QRect(0, 0, 2, 2)) self.layoutWidget4.setObjectName("layoutWidget4") self.horizontalLayout_2 = QtWidgets.QHBoxLayout(self.layoutWidget4) self.horizontalLayout_2.setContentsMargins(0, 0, 0, 0) self.horizontalLayout_2.setObjectName("horizontalLayout_2") self.layoutWidget5 = QtWidgets.QWidget(self.centralwidget) self.layoutWidget5.setGeometry(QtCore.QRect(0, 0, 2, 2)) self.layoutWidget5.setObjectName("layoutWidget5") self.verticalLayout = QtWidgets.QVBoxLayout(self.layoutWidget5) self.verticalLayout.setContentsMargins(0, 0, 0, 0) self.verticalLayout.setObjectName("verticalLayout") self.layoutWidget6 = QtWidgets.QWidget(self.centralwidget) self.layoutWidget6.setGeometry(QtCore.QRect(0, 0, 2, 2)) self.layoutWidget6.setObjectName("layoutWidget6") self.horizontalLayout_4 = QtWidgets.QHBoxLayout(self.layoutWidget6) self.horizontalLayout_4.setContentsMargins(0, 0, 0, 0) self.horizontalLayout_4.setObjectName("horizontalLayout_4") MainWindow.setCentralWidget(self.centralwidget) self.statusbar = QtWidgets.QStatusBar(MainWindow) self.statusbar.setObjectName("statusbar") MainWindow.setStatusBar(self.statusbar) self.action1 = QtWidgets.QAction(MainWindow) self.action1.setObjectName("action1") self.action2 = QtWidgets.QAction(MainWindow) self.action2.setObjectName("action2") self.retranslateUi(MainWindow) self.tabWidget.setCurrentIndex(0) QtCore.QMetaObject.connectSlotsByName(MainWindow) def retranslateUi(self, MainWindow): _translate = QtCore.QCoreApplication.translate MainWindow.setWindowTitle(_translate("MainWindow", "模拟飞机数据产生软件")) self.groupBox_2.setTitle(_translate("MainWindow", "目标机信息")) self.groupBox_tcas_target1.setTitle(_translate("MainWindow", "TCAS")) self.btn_stopsend_tcas_target1.setText(_translate("MainWindow", "暂停发送TCAS数据")) self.label_27.setText(_translate("MainWindow", "Track_ID：")) self.label_26.setText(_translate("MainWindow", "压强高度(m)：")) self.label_23.setText(_translate("MainWindow", "相对本机方位(deg)：")) self.label_21.setText(_translate("MainWindow", "相对本机距离(km)：")) self.btn_import_info_target1.setText(_translate("MainWindow", "导入飞机信息")) self.groupBox_adsb_target1.setTitle(_translate("MainWindow", "ADS-B")) self.label_4.setText(_translate("MainWindow", "压强高度(m)：")) self.label_11.setText(_translate("MainWindow", "ICAO码：")) self.label_12.setText(_translate("MainWindow", "南北速度(km/h)：")) self.label_15.setText(_translate("MainWindow", "东西速度(km/h):")) self.label_14.setText(_translate("MainWindow", "航班号：")) self.label_17.setText(_translate("MainWindow", "地速(km/h)：")) self.label_18.setText(_translate("MainWindow", "航向角(deg)：")) self.label_13.setText(_translate("MainWindow", "纬度(deg):")) self.label_16.setText(_translate("MainWindow", "经度(deg)：")) self.btn_stopsend_adsb_target1.setText(_translate("MainWindow", "暂停发送ADS-B数据")) self.tabWidget.setTabText(self.tabWidget.indexOf(self.tab), _translate("MainWindow", "1号目标机")) self.groupBox_3.setTitle(_translate("MainWindow", "控制台")) self.btn_start.setText(_translate("MainWindow", "开始")) self.btn_stop.setText(_translate("MainWindow", "停止")) self.groupBox.setTitle(_translate("MainWindow", "本机信息")) self.label_2.setText(_translate("MainWindow", "航班号：")) self.label_7.setText(_translate("MainWindow", "纬度(deg):")) self.label_9.setText(_translate("MainWindow", "航向角(deg):")) self.label_3.setText(_translate("MainWindow", "压强高度(m)：")) self.label_6.setText(_translate("MainWindow", "东西速度(km/h):")) self.label_8.setText(_translate("MainWindow", "经度(deg):")) self.label.setText(_translate("MainWindow", "ICAO码：")) self.label_5.setText(_translate("MainWindow", "南北速度(km/h)：")) self.label_10.setText(_translate("MainWindow", "地速(km/h):")) self.btn_import_info_own.setText(_translate("MainWindow", "导入飞机信息")) self.action1.setText(_translate("MainWindow", "本机")) self.action2.setText(_translate("MainWindow", "目标机"))

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py

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adsb_mainForm.py

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0.697866

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ruoyuryc/Deep-Learning-and-Practice-2020-Spring

10,015,863,742,504

cf013a25a98a87241155c3a652812f76407a55a8

1a7b47bb1ff483b236211aaa5cc648b9c7854853

/Lab6/dataset/preprocess.py

d7f6f828773917338ced47463e4c8f1aed341920

[]

no_license

https://github.com/ruoyuryc/Deep-Learning-and-Practice-2020-Spring

4929ed3aa83312029daf724d76554f8768a23e4c

7ac9fc9163635aff8ae386c610396ae4646f8095

refs/heads/master

2022-10-20T04:45:37.648427

2020-06-15T15:24:25

null

0

null

import PIL from PIL import Image import torch import json from torchvision import transforms from tqdm import tqdm with open('objects.json', 'r') as f: objects = json.load(f) with open('labels.json', 'r') as f: labels = json.load(f) trans = transforms.Compose([ transforms.Resize((64, 64)), transforms.ToTensor(), transforms.Normalize( mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5] ) ]) torch.save(trans(PIL.Image.open('png/background.png').convert('RGB')), 'background.pth') lbls = [] imgs = [] for idx in tqdm(range(6004)): for sub_idx in range(3): key = f'CLEVR_train_{idx:06}_{sub_idx}.png' lbls.append(torch.LongTensor([objects[labels[key][-1]]])) imgs.append(trans(PIL.Image.open(f'png/{key}').convert("RGB"))) lbls = torch.stack(lbls) imgs = torch.stack(imgs) torch.save(lbls, 'labels.pth') torch.save(imgs, 'images.pth')

UTF-8

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py

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preprocess.py

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0.638581

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radtek/Server-Monitoring

9,423,158,281,982

7219366ebfbf87e59f6fdd2fd5ccae0112e74180

5cd16658110d9a65556b63a16cf07a9b6ea338fc

/Ver2.0/zabbix/CentOS-7/vdisk_status.py

7c0126bdacdb53b979ffaff12a108657d624781c

[]

no_license

https://github.com/radtek/Server-Monitoring

60a21c837bddd786bddb41ee463ba2f5c11acce5

9f3ca9876a0ed5e9f4971cec873e524f06fd87ab

refs/heads/master

2023-05-02T16:20:52.299839

2021-05-19T14:57:15

null

0

null

import os import re import sys def get_pdisk_status(logicaldrive): conent=os.popen("sudo hpacucli ctrl all show config").readlines() for index in range(len(conent)): if logicaldrive in conent[index] and re.split(r'[ ]',conent[index])[7].strip()==logicaldrive: return re.split(r'[) ]',conent[index])[12].strip() if __name__=='__main__': if get_pdisk_status(sys.argv[1])=="OK": print 1 else: print 0

UTF-8

Python

false

413

py

74

vdisk_status.py

40

0.677966

0.663438

0

15

26.533333

95

baidw/languages

11,965,778,916,584

d13a61b51cf2af8b54e138d63029d9326688fd45

2f4c7fae43c7d13d1925f8d5a53d05021865c34b

/python/trainning/train_001_farbic.py

e23676cea992ef58f7f2852115628f5ac1a9a023

[]

no_license

https://github.com/baidw/languages

87aafe620d6873e6bffc6d0aafe517939784bba0

5e7cccc737cc6f415e0b1e91f441a84b6286603b

refs/heads/master

2020-05-22T06:40:33.668235

2018-10-23T05:59:22

60,157,718

0

null

#!/usr/bin/env python # -*- coding:utf-8 -*- __author__='baidw' def tribonacci(signature,n): #your code here temp = signature slen=len(temp) if n ==0: return [] if n==1 and len(list(set(signature)))==1: return signature[:1] while slen<n: temp.append(int(temp[slen-1])+int(temp[slen-2])+int(temp[slen-3])) slen=len(temp) return temp x= tribonacci([1,1,1],1) print x

UTF-8

Python

false

434

py

78

train_001_farbic.py

66

0.56682

0.539171

0

21

19.714286

74

cpressland/dictfilter

15,693,810,512,280

73cec6a3d0e754d20788f3fe19326ddf0f70fc83

80cad9acb46be23437f22344e23b79caf3c45e98

/dictfilter/__init__.py

64fa0354e1a5c9182228aaf6b3a9d30c6ed0590a

[ "MIT" ]

permissive

https://github.com/cpressland/dictfilter

fbd1e5ba6b47253c529eb2c25b666e223dcae90c

a55f68d1719bc951e283b8dccbd7eee315bbdee5

refs/heads/master

2023-03-12T16:08:14.512146

2023-02-28T13:46:46

289,022,266

0

null

true

2020-08-20T14:05:32

2020-08-20T14:05:31

2020-08-20T13:57:11

2020-08-20T13:57:07

0

null

false

from dictfilter.core import query # noqa

UTF-8

Python

false

42

py

10

__init__.py

5

0.785714

0

1

41

dcherix/apiontology-demonstrator

1,829,656,074,901

1c132bae81dadeec1fa82712aa2177961c35223c

d62283766afd59ddde1a630c80eb92d52cf3df0f

/apiontology-demonstrator-example-services/citylatlong.py

15ff810ace2780c3d5a5ec1a00e3a9b56c1af313

[]

no_license

https://github.com/dcherix/apiontology-demonstrator

129d16e4081f22677642f38a62a7ec49ecb1c1b1

9a4974f1cfdbba6b7e05e5f64beaa7e2792592cd

refs/heads/master

2022-12-22T17:19:40.697607

2018-10-18T05:14:53

2019-09-04T19:56:21

42,429,342

2

0

null

false

2022-12-16T09:52:56

2015-09-14T05:40:31

2019-09-04T19:57:03

2022-12-16T09:52:52

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2

0

10

Java

false

''' service returns for a given city and adminarea the corresponding lat,long @author a.both ''' from service import init_service import csv from pprint import pprint def citylatlong( cityname, adminarea ): ''' returns the companys city, country and stock name as strings for a given company name ''' global citylatlong_data try: result = citylatlong_data[cityname][adminarea] except: result = {} print("in: ",cityname,adminarea," out: ",result) return result def main(): # read data from CSV file reader = csv.reader(open('citylatlong.csv', 'r')) global citylatlong_data citylatlong_data = {} for row in reader: cityname,adminarea,latlong = row #print cityname,adminarea,latlong long,lat = latlong.split() citylatlong_data[cityname] = { adminarea: {'lat':lat, 'long':long} } init_service( port=8182, servicename='CityLatLong', userfunction=citylatlong, args={'cityname':str, 'adminarea':str}, returns={'lat':str, 'long':str} ) if __name__ =='__main__': main()

UTF-8

Python

false

1,064

py

75

citylatlong.py

49

0.665414

0.661654

0

45

22.666667

89

Richard-CH-NG/djangular_project

3,728,031,638,696

55d208038bc4f61ccdeddc5720f80405fe8a0516

cc8445d0af32a7134ffd8c5b45851d7bd73069a3

/accounts/forms.py

7a2d40f0ee12fb875f5e64ca998d198314a07b1e

[]

no_license

https://github.com/Richard-CH-NG/djangular_project

5a5ad33b080bc25ae7a93f15e7e507961d1f4a9f

fa121457cf9ae81886df034692811141d8868daa

refs/heads/master

2017-07-31T17:12:25.470749

2017-06-29T06:00:07

95,001,627

0

null

from django import forms from django.contrib.auth import ( authenticate, get_user_model, login, logout, ) User = get_user_model() class UserLoginForm(forms.Form): username = forms.CharField() password = forms.CharField(widget=forms.PasswordInput) def clean(self): username = self.cleaned_data['username'] password = self.cleaned_data['password'] user = authenticate(username=username, password=password) if not user: raise forms.ValidationError("This username/password does not exist.") # if not user.check_password(password): # raise forms.ValidationError("Incorrect Password.") if not user.is_active: raise forms.ValidationError("This user is no longer active") # if everthing's okay, return the default clean return super(UserLoginForm, self).clean() class UserRegisterForm(forms.ModelForm): email2 = forms.EmailField(label="Confirm Email") class Meta: model = User fields = [ 'username', 'email', 'email2', 'password', ] widgets = { 'password' : forms.PasswordInput } # if use clean_email method, will give KeyError # becuz order matter, email2 exists after email, # so u won't see email2 in cleaned_data yet when "cleaning" email def clean(self): """cleaning email for which the default does not do that""" print(self.cleaned_data) email = self.cleaned_data['email'] email2 = self.cleaned_data['email2'] if email != email2: raise forms.ValidationError("Email input fields do not match.") if User.objects.filter(email=email).exists(): raise forms.ValidationError("This email has already been registered.") return super(UserRegisterForm, self).clean()

UTF-8

Python

false

1,894

py

31

forms.py

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0.629356

0.62566

0

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32.821429

82

guchio3/kaggle-homecredit

14,671,608,304,654

4e58d936853ac71598de202f0ec4a27cc48d6fd4

e29103f2f7e4a44dbb4626f4f138ed09555d2dcc

/protos/shared_kfold/split.py

c66a33d0cee56735c0558f7ee054e78c3d7075c4

[]

no_license

https://github.com/guchio3/kaggle-homecredit

e800eac42dd0f2428de9099d6052139c2df6e2ac

210a7bb3a5e124bd4a9895cf95be8d5269c1a225

refs/heads/master

2020-04-27T23:56:57.408848

2019-03-16T07:05:56

174,797,829

0

null

from sklearn.cross_validation import KFold import numpy as np def splitter(clf, x_train, y, x_test): NFOLDS = 5 SEED = 71 kf = KFold(len(x_train), n_folds=NFOLDS, shuffle=True, random_state=SEED) fold_train_test = {} for i, (train_index, test_index) in enumerate(kf): fold_train_test[i] = { 'train_index': train_index, 'test_index':test_index } return fold_train_test import glob, gc import pandas as pd df = pd.read_pickle('../my-nural/00-dump.pkl') train_df = df[df['TARGET'].notnull()] test_df = df[df['TARGET'].isnull()] feats = [f for f in train_df.columns if f not in ['TARGET','SK_ID_CURR','SK_ID_BUREAU','SK_ID_PREV','index']] y = train_df['TARGET'] # この差は4件あるが、7.95だしているカーネルによるとこれは、正しい print(train_df.shape) print(pd.read_csv('../input/application_train.csv').shape) check = pd.read_pickle('../my-nural/00-dump.pkl') print( check[check['TARGET'].notnull()].shape ) fold_train_test = splitter(None, train_df, y.values, test_df) import pickle pickle.dump(fold_train_test, open('fold_train_test.pkl', 'wb')) # pickle形式で保存 # 例) 2foldのtrain_indexにアクセス # fold_train_test = pickle.load(open('fold_train_test.pkl', 'rb')) print(fold_train_test[2]['train_index'] )

UTF-8

Python

false

1,280

py

307

split.py

16

0.684474

0.673623

0

35

33.2

109

eymenkurdoglu/ml_projects

15,882,789,085,006

f3e620a9e29086f57bc765a48ed5564769bf515d

1c1d8f76da7fb157af608ece27d9759b0b6c8bbf

/time-ser-forecast/svr.py

9df9f4792ee82d1b15e818763f01bc5158dd512a

[]

no_license

https://github.com/eymenkurdoglu/ml_projects

f3a4c7b160621e4d603bd2b5e2c000897e6da0a0

1756d6a274952864ad23b835843734684a6ca17f

refs/heads/master

2021-04-15T15:10:24.684323

2018-03-27T02:24:27

126,917,214

0

null

import csv import numpy as np from sklearn.svm import SVR import matplotlib.pyplot as plt dates = [] prices = [] def get_data(filename): with open(filename, 'r') as csvfile: csvFileReader = csv.reader(csvfile) next(csvFileReader) for row in csvFileReader: dates.append(int(row[0].split('-')[0])) prices.append(float(row[1])) return def predict_price(dates, prices, x): dates = np.reshape(dates,(len(dates),1)) # convert to vector of length n svr_lin = SVR( kernel = 'linear', C = 1e3 ) svr_poly = SVR( kernel = 'poly', C = 1e3, degree = 2 ) svr_rbf = SVR( kernel = 'rbf', C = 1e3, gamma = 0.1 ) svr_lin.fit( dates, prices ) svr_poly.fit( dates, prices ) svr_rbf.fit( dates, prices ) plt.scatter( dates, prices, color = 'black', label = 'Data' ) plt. plot( dates, svr_lin.predict( dates ), color= 'green', label= 'Linear model' ) plt. plot( dates, svr_poly.predict( dates ), color= 'blue', label= 'Polynomial model' ) plt. plot( dates, svr_rbf.predict( dates ), color= 'red', label= 'RBF model' ) plt.xlabel('Date') plt.ylabel('Price') plt.legend() plt.show() return svr_rbf.predict(x)[0], svr_lin.predict(x)[0], svr_poly.predict(x)[0] get_data('googl.csv') predicted_price = predict_price(dates, prices, 29)

UTF-8

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false

1,254

py

3

svr.py

1

0.660287

0.645933

0

42

28.857143

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Semenyshyn/CodeWars

17,076,789,999,317

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72220530641dd387f5cf178a3ed53b4a6815a22f

/Sum consecutives.py

73e43ffbb2590369dd4777cfa0c4333b20b05881

[]

no_license

https://github.com/Semenyshyn/CodeWars

7516d7ba27e46ab47364c5266ef578de95b4be7b

131ac35c55402853ddbeda38a8e27210ac1a7c7c

refs/heads/master

2020-06-23T13:41:04.134166

2016-08-20T11:56:11

66,144,292

0

null

s = [1, 1, 1, 0, 1, 2, 2, -3, -3, -3] def sum_consecutives(s): prev = None x = [] for i in s: if i == prev: x[-1] += i else: x.append(i) prev = i return x print(sum_consecutives(s))

UTF-8

Python

false

248

py

15

Sum consecutives.py

15

0.407258

0.362903

0

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uit-no/python-open-mike

14,499,809,609,993

31abe97f6eb43e59b864334d735deeb9ef29e6d2

21d7c98b8c7d62dd182f04d3a9ea092b8c330dea

/solutions/2/most-frequent/most_frequent.py

59149faf9558d3034f132ce342cbdf43313baac3

[]

no_license

https://github.com/uit-no/python-open-mike

951678870b61d63203e0b8c248c9189687473d9a

2a83b27ca31959f0c0de2ee6f72abca440d76ec8

refs/heads/gh-pages

2020-03-30T12:42:37.311093

2019-09-11T14:13:06

151,236,182

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null

false

2018-11-19T13:12:01

2018-10-02T10:16:25

2018-11-19T09:41:01

2018-11-19T13:12:00

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0

2

0

Python

false

null

#!/usr/bin/env python3 from collections import Counter def strip_special_chars(string): return "".join(char for char in string if char.isalpha()) def char_counter(string, number): chars = filter(str.isalpha, string) return Counter(chars).most_common(number) def word_counter(string, number): words = map(strip_special_chars, string.split()) return Counter(words).most_common(number) if __name__ == "__main__": file_name = "poem.txt" with open(file_name) as page: lines = page.read().lower() print("# Most frequent words:", word_counter(lines, 5)) print("# Most frequent chars:", char_counter(lines, 5))

UTF-8

Python

false

655

py

45

most_frequent.py

31

0.668702

0.664122

0

24

26.291667

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Jayashsatolia403/Projects

13,889,924,259,540

c3f9d3dc3dfdc3c8f7b66286d5c85f2a008a25ff

6e083faecc108f78210c9b43f5e19f2e29be8b56

/EcommerceFullStack/FullStack/EcommerceProject/order/migrations/0013_remove_order_users.py

82051cd23177920bbada0bcf7f77dc24f244d320

[]

no_license

https://github.com/Jayashsatolia403/Projects

d86240124ca189c00f706d5788b78c360b433cab

d98dc8600e29ae8e751da6c68d31902d3f5e9142

refs/heads/master

2023-06-26T01:01:49.983012

2021-07-20T11:28:01

385,829,888

0

null

# Generated by Django 3.1.7 on 2021-04-13 20:28 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('order', '0012_auto_20210414_0150'), ] operations = [ migrations.RemoveField( model_name='order', name='users', ), ]

UTF-8

Python

false

324

py

114

0013_remove_order_users.py

97

0.574074

0.478395

0

17

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w-x-me/PyImageSearch

1,486,058,703,088

ce640a62583d401723fadc67b29991ba287401e4

e1def0cb3ea2f1b9e7e8c9183ef3eae6eb4f2d97

/Moudel1/Threshold3.py

a4fc0edef07bce52f351456350845733feb4a2e4

[]

no_license

https://github.com/w-x-me/PyImageSearch

58084fd4834457a10a75383702093f5d98a0e6e4

fc6034ae43767f9ec5cc0d4e6bb771d70a866a56

refs/heads/master

2020-03-20T07:50:17.690517

2018-06-14T02:08:51

134,201,710

1

0

null

from skimage.filters import threshold_adaptive import argparse import cv2 ap = argparse.ArgumenParser() ap.add_argument("-i", "--image", required = True, help = "Path to the image") args = vars(ap.parse_args()) image = cv2.imread(args["image"]) image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) blurred = cv2.GussianBlur(image, (5, 5), 0) cv2.imshow("Image", image) thresh = cv2.adaptiveThreshold(blurred, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY_INV, 25, 15) cv2.imshow("OpenCV Mean Thresh", thresh) thresh = threshold_adaptive(blurred, 29, offset = 5).astype("uint8") * 255 thresh = cv2.bitwise_not(thresh) cv2.imshow("scikit-image Mean Thresh", thresh) cv2.waitKey(0)

UTF-8

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Threshold3.py

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machukhinktato/test_tasks_python

11,003,706,223,296

7e317a238433dece7c80b26c1d27912986d35974

c4ad8eb9ad11e821806c01953e630617a2dc274a

/task2/SRC/task2.py

1322ab674b152fa8add9dacb98f8056a10cdba7e

[]

no_license

https://github.com/machukhinktato/test_tasks_python

09cac9d2d2fac651efbe4bff8cb8327e62aa3b54

7dcf494742dbd24e6a271db368be91e64eeed26f

refs/heads/master

2023-02-17T00:21:15.459882

2021-01-20T15:48:50

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import json def file_loader(name): """Загружает json файл с данынми""" with open(name) as f: try: file = json.load(f) except: file = f.readlines() f.close() return file def main(filename): """ Основная функция, принимает исходные значения, сортирует данные и отдаёт их на обработку профильным функциям """ # task_dict = file_loader(input('Enter the file name, to start program: ')) task_dict = file_loader(filename) sphere_coords, line_coords = [], [] for i in range(3): sphere_coords.append(( ((task_dict.get('sphere').get('center')[i]) - (task_dict.get('sphere').get('radius'))), (((task_dict.get('sphere').get('center')[i])) + (task_dict.get('sphere').get('radius')))) ) line_coords.append(( [task_dict.get('line')[0][i], task_dict.get('line')[1][i]] )) line = {'sections': { 'x': line_coords[0], 'y': line_coords[1], 'z': line_coords[2], }} result = comparison(line, sphere_coords) try: for key in result.keys(): # ok.append(f"{key} = {result.get(key)}") print(f"{key} : {result.get(key)}") return '' except: return print('Коллизий не найдено') def comparison(line, sphere): """Функция находящая точки внутри сферы""" x = 0 section = line.get('sections') for key in section.keys(): for i in range(2): if section[key][i] >= sphere[0][0] and section[key][i] <= sphere[x][1]: section.get(key).append(True) else: section.get(key).append(None) x += 1 return cross_finder(line, sphere) def cross_finder(sections, sphere): """ Функция производящая финальную оценку по точкам линии проходящим через или входящим в сферу """ x = 0 sections = sections.get('sections') crosspoints = dict() for key in sections.keys(): if sections[key][2] and sections[key][3] == True or \ float(sections[key][0]) < min(sphere[x]) and \ float(sections[key][1]) < min(sphere[x]) or \ float(sections[key][0]) > max(sphere[x]) and \ float(sections[key][1]) > max(sphere[x]): continue elif sections[key][2] == True: if sections[key][0] > sections[key][1]: # Номера присватваются в зависимот от элемента вхождения crosspoints[key + '_1'] = sphere[x][0] else: crosspoints[key + '_1'] = sphere[x][1] elif sections[key][3] == True: if sections[key][1] > sections[key][0]: crosspoints[key + '_2'] = sphere[x][0] else: crosspoints[key + '_2'] = sphere[x][1] cords = ['x_1', 'y_1', 'z_1', 'x_2', 'y_2', 'z_2'] for point in cords: if point in crosspoints: return crosspoints if __name__ == '__main__': main('test.txt')

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task2.py

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Alicia1529/ComputerScience

14,267,881,406,749

45a2b31320d52a14c4382ce3c0753920e5f9fa04

77106803619fd019cca5ec2b7744bfd1a70e0fc9

/CodeJam/2019-pre/test3.py

09dcb33583f132eb0ee90396d2039e3e5d92d812

[]

no_license

https://github.com/Alicia1529/ComputerScience

dc18960eeb4f7a4deb2a6b99d33bcf08c1afe583

4529f4cb2797d59684fa68c615c8a0b6525f7004

refs/heads/master

2020-06-28T17:01:05.363189

2019-08-02T20:59:53

200,290,236

0

null

def foundInit(n,N): for i in range(1,N): if is_prime(i) and is_prime(n//i) and (n//i)*i==n: return i,n//i def is_prime(n): if n == 2 or n == 3: return True if n < 2 or n%2 == 0: return False if n < 9: return True if n%3 == 0: return False r = int(n**0.5) f = 5 while f <= r: if n%f == 0: return False if n%(f+2) == 0: return False f +=6 return True num = input().strip() while num=="": num = input().strip() num = int(num) for i in range(num): line = input().strip() while line=="": line = input().strip() N,L = line.split(" ") N,L = int(N),int(L) line = input().strip() while line=="": line = input().strip() data = line.split(" ") array = [] for j in range(len(data)): if j==0: this,nextOne = foundInit(int(data[j]),N) if (int(data[j+1])//nextOne)*nextOne==int(data[j+1]) and is_prime(int(data[j+1])//nextOne): pass else: this,nextOne = nextOne,this array.append(this) array.append(nextOne) else: array.append(int(data[j])//nextOne) nextOne = int(data[j])//nextOne index = list(set(array)) index.sort() output = [] for j in range(len(array)): idx = index.index(array[j]) letter = chr(65+idx) output.append(letter) string = "Case #"+str(i+1)+":" print(string,"".join(output))

UTF-8

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false

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test3.py

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Donnadonnam/SOEN487-ResoluteLeopards

5,823,975,674,440

c79e22863ade7eef8a81289ba398b028fd7e5658

86eae54c21c850a3c00c7dffa22f2b76c35cc857

/user_api/config.py

22faf3814a7c33eb41c95eeb53a87fe193e55190

[]

no_license

https://github.com/Donnadonnam/SOEN487-ResoluteLeopards

916675735645db319c20e1017871354844abd493

48de7ba82ddcbe3627920e9e435bb05b49845186

refs/heads/master

2023-03-18T15:49:20.944037

2020-03-04T12:38:00

null

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null

import os class Config(object): SQLALCHEMY_DATABASE_URI = r"sqlite:///userdb.sqlite" SQLALCHEMY_TRACK_MODIFICATIONS = False class ProdConfig(Config): pass class DevConfig(Config): KEY_LIST_PATH = os.path.join(os.path.dirname(__file__), "keys/keylist.json") DEBUG = True class TestConfig(Config): TESTING = True KEY_LIST_PATH = os.path.join(os.path.dirname(__file__), "tests/keys/keylist.json") SQLALCHEMY_DATABASE_URI = r"sqlite:///tests/test_userdb.sqlite"

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Python

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config.py

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