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

2860ad63802d9b4247cfc5b4ea2a3cd53137c044

3,973

py

Python

src/anaplan_api/Upload.py

pieter-pot/anaplan-api

1b099cb102f98b114afa0794a40aaf0de19956c1

[ "BSD-2-Clause" ]

null

src/anaplan_api/Upload.py

pieter-pot/anaplan-api

1b099cb102f98b114afa0794a40aaf0de19956c1

[ "BSD-2-Clause" ]

null

src/anaplan_api/Upload.py

pieter-pot/anaplan-api

1b099cb102f98b114afa0794a40aaf0de19956c1

[ "BSD-2-Clause" ]

null

# =============================================================================== # Created: 1 Nov 2021 # @author: Jesse Wilson (Anaplan Asia Pte Ltd) # Description: Abstract Anaplan Authentication Class # Input: Username & Password, or SHA keypair # Output: Anaplan JWT and token expiry time # =============================================================================== import logging import requests from requests.exceptions import HTTPError, ConnectionError, SSLError, Timeout, ConnectTimeout, ReadTimeout from .File import File logger = logging.getLogger(__name__)

29.87218

106

0.686383

28631cb627e7dcbf9512e0e9d35ed83e8378693a

427

py

Python

startPWM.py

adeept/adeept_alter

6adf00eb141405fc3abad44965f81ba7797dd962

[ "MIT" ]

1

2021-12-21T15:50:57.000Z

startPWM.py

adeept/adeept_alter

6adf00eb141405fc3abad44965f81ba7797dd962

[ "MIT" ]

2

2021-03-14T22:05:42.000Z

2021-07-19T22:13:37.000Z

startPWM.py

adeept/adeept_alter

6adf00eb141405fc3abad44965f81ba7797dd962

[ "MIT" ]

null

import Adafruit_PCA9685 pwm = Adafruit_PCA9685.PCA9685() pwm.set_pwm_freq(50) initPWM = 320 setPWM = initPWM ctrlPort = 11 try: main() except KeyboardInterrupt: pwm.set_pwm(ctrlPort, 0, initPWM)

16.423077

35

0.651054

28658c7c561044400a64c09359dccf6abba3fb8e

2,042

py

Python

get_tracks.py

RamonPuon/Spotipy-Valence-Analysis

05f48e068097839d3dbd47d06f69608e48d1ac16

[ "MIT" ]

null

get_tracks.py

RamonPuon/Spotipy-Valence-Analysis

05f48e068097839d3dbd47d06f69608e48d1ac16

[ "MIT" ]

null

get_tracks.py

RamonPuon/Spotipy-Valence-Analysis

05f48e068097839d3dbd47d06f69608e48d1ac16

[ "MIT" ]

null

#cred.py, python script with my client ID and my client secret import cred import spotipy from spotipy.oauth2 import SpotifyClientCredentials import pandas as pd client_credential_manager = SpotifyClientCredentials(client_id= cred.client_ID, client_secret= cred.client_SECRET) sp = spotipy.Spotify(client_credentials_manager= client_credential_manager) #Function that returns every track from each album from a specific artist

39.269231

114

0.644466

28673f63b24f6a069e726650a9df5d529a4e2b9c

3,053

py

Python

Uzura/data/subsystem/stream.py

jskny/Uzura

356f8c25ceef5bd098b8e338e4acabb3f8653dca

[ "MIT" ]

null

Uzura/data/subsystem/stream.py

jskny/Uzura

356f8c25ceef5bd098b8e338e4acabb3f8653dca

[ "MIT" ]

null

Uzura/data/subsystem/stream.py

jskny/Uzura

356f8c25ceef5bd098b8e338e4acabb3f8653dca

[ "MIT" ]

null

#! /usr/bin/env python # -*- coding: utf-8 -*- # # Perl # 2012 / 11 / 14 # jskny # http://d.hatena.ne.jp/iacctech/20110429/1304090609 import sys, tweepy, urllib, urllib2 import os, time, subprocess, socket import re from tweepy.streaming import StreamListener, Stream from tweepy.auth import OAuthHandler from datetime import timedelta # host = '' port = 18385 serversock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) # serversock.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) serversock.bind((host, port)) serversock.listen(1) print 'Waiting for connections...' clientsock, client_address = serversock.accept() print 'Connection his Succeed...' # consumer_key = "oDiVnBOqcYjie0T8AN6XyA" consumer_secret = "0rsndWq3N3u8AJXKP7gfwrAcdwzPoFxAgZ5PuLt4Ww" access_key = "397948629-j4HutoScDcL5ncMZNvuA13JY6BA3D2zEJyZPdEAJ" access_secret = "N3UGJUwxDcrs0yz4mK3Y9cNhkw8IpO6kHnFIzHMH3pM" # # Tweepy if __name__ == "__main__": try: main() clientsock.close() sys.exit() except KeyboardInterrupt: clientsock.close() sys.exit()

24.821138

263

0.717327

286a9f1d8d066c57291a41e5d9d48a731a2d4a0c

541

py

Python

templates/django/djangoRest/app_dir/user/test/test_user_views.py

david-osas/create-basic-app

860fc579672855093ad8426fb01d010de4c7cff8

[ "MIT" ]

2

2020-12-01T11:33:36.000Z

2020-12-01T12:25:49.000Z

django-rest-framework-boilerplate/app_dir/user/test/test_user_views.py

PiotrZak/lem-golem

78f91f21b19725fca99c05d8c536330ef2785064

[ "MIT" ]

2

2020-11-25T14:38:57.000Z

2020-11-25T22:55:25.000Z

templates/django/djangoRest/app_dir/user/test/test_user_views.py

david-osas/create-basic-app

860fc579672855093ad8426fb01d010de4c7cff8

[ "MIT" ]

2

2020-11-26T08:59:50.000Z

2021-03-30T20:01:06.000Z

from django.test import TestCase from django.urls import reverse from rest_framework.test import APIClient from ...factories import UserFactory

28.473684

54

0.698706

286ba9afaaf93ad96524d8cf507a1bf2ad30a104

2,862

py

Python

port_mapping.py

sbalasa/CiscoFMC

024c9b6df3513e1e4a8e3e3f976a0c67b58c1909

[ "MIT" ]

1

2021-11-09T03:56:29.000Z

port_mapping.py

sbalasa/CiscoFMC

024c9b6df3513e1e4a8e3e3f976a0c67b58c1909

[ "MIT" ]

null

port_mapping.py

sbalasa/CiscoFMC

024c9b6df3513e1e4a8e3e3f976a0c67b58c1909

[ "MIT" ]

1

2021-11-09T03:56:06.000Z

ports = { "ssh": {"type": "PortLiteral", "port": "22", "protocol": "6",}, "udp/netbios-dgm": {"type": "PortLiteral", "port": "138", "protocol": "17",}, "udp/netbios-ns": {"type": "PortLiteral", "port": "137", "protocol": "17",}, "tcp/ssh": {"type": "PortLiteral", "port": "22", "protocol": "6",}, "tcp": {"type": "PortLiteral", "protocol": "6",}, "esp": {"type": "PortLiteral", "protocol": "50",}, "ah": {"type": "PortLiteral", "protocol": "51",}, "udp": {"type": "PortLiteral", "protocol": "17",}, "snmp": [ {"type": "PortLiteral", "port": "161", "protocol": "17",}, {"type": "PortLiteral", "port": "162", "protocol": "17",}, ], "udp/snmp": [ {"type": "PortLiteral", "port": "161", "protocol": "17",}, {"type": "PortLiteral", "port": "162", "protocol": "6",}, {"type": "PortLiteral", "port": "162", "protocol": "17",}, ], "udp/snmptrap": {"type": "PortLiteral", "port": "162", "protocol": "6",}, "snmptrap": [ {"type": "PortLiteral", "port": "162", "protocol": "6",}, {"type": "PortLiteral", "port": "162", "protocol": "17",}, ], "https": [ {"type": "PortLiteral", "port": "443", "protocol": "6",}, {"type": "PortLiteral", "port": "443", "protocol": "17",}, ], "tcp/https": {"type": "PortLiteral", "port": "443", "protocol": "6",}, "netbios-ssn": {"type": "PortLiteral", "port": "139", "protocol": "6",}, "tcp/netbios-ssn": {"type": "PortLiteral", "port": "139", "protocol": "6",}, "ntp": {"type": "PortLiteral", "port": "123", "protocol": "17",}, "udp/ntp": {"type": "PortLiteral", "port": "123", "protocol": "17",}, "tcp/tacacs": {"type": "PortLiteral", "port": "49", "protocol": "6",}, "udp/tacacs": {"type": "PortLiteral", "port": "49", "protocol": "17",}, "tcp/www": {"type": "PortLiteral", "port": "80", "protocol": "6",}, "udp/www": {"type": "PortLiteral", "port": "80", "protocol": "17",}, "tcp/http": {"type": "PortLiteral", "port": "80", "protocol": "6",}, "ldaps": {"type": "PortLiteral", "port": "636", "protocol": "6",}, "tcp/ldaps": {"type": "PortLiteral", "port": "636", "protocol": "6",}, "ldap": {"type": "PortLiteral", "port": "389", "protocol": "6",}, "tcp/ldap": {"type": "PortLiteral", "port": "389", "protocol": "6",}, "tcp/syslog": {"type": "PortLiteral", "port": "514", "protocol": "6",}, "udp/syslog": {"type": "PortLiteral", "port": "514", "protocol": "17",}, "tcp/domain": {"type": "PortLiteral", "port": "53", "protocol": "6", }, "udp/domain": {"type": "PortLiteral", "port": "53", "protocol": "17",}, "tcp/rsh": {"type": "PortLiteral", "port": "514", "protocol": "6",}, "icmp": {"type": "ICMPv4PortLiteral", "protocol": "1", "icmpType": "Any",}, "any": [], }

57.24

82

0.490217

286dae799942d25528e620a011ce5d17032d1ce7

2,336

py

Python

deep-learning-lab-00/binlogreg.py

BalderOdinson/Deep-Learning-Lab

70786ff1be40fc829d64a644585c1d5683c76538

[ "MIT" ]

null

deep-learning-lab-00/binlogreg.py

BalderOdinson/Deep-Learning-Lab

70786ff1be40fc829d64a644585c1d5683c76538

[ "MIT" ]

null

deep-learning-lab-00/binlogreg.py

BalderOdinson/Deep-Learning-Lab

70786ff1be40fc829d64a644585c1d5683c76538

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Mon Mar 18 18:38:38 2019 @author: Oshikuru """ import numpy as np import matplotlib.pyplot as plt import random import data import pdb import IPython param_delta = 0.5 param_niter = 100 param_lambda = 0.01 def binlogreg_train(X,Y_): ''' Argumenti X: podatci, np.array NxD Y_: indeksi razreda, np.array Nx1 Povratne vrijednosti w, b: parametri logistike regresije ''' N = Y_.shape[0] D = X.shape[1] w = np.random.randn(D, 1) b = np.random.randn(1,1) Y__ = np.hsplit(Y_, 2)[1] # gradijentni spust (param_niter iteracija) for i in range(param_niter): # klasifikacijske mjere scores = np.dot(X, w) + b # N x 1 # vjerojatnosti razreda c_1 probs = np.abs((1 / (1 + np.exp(scores))) - Y__) # N x 1 # gubitak loss = - (1 / N) * np.sum(np.log(probs)) + param_lambda * np.linalg.norm(w) # scalar # dijagnostiki ispis if i % 10 == 0: print("iteration {}: loss {}".format(i, loss)) # derivacije gubitka po klasifikacijskim mjerama dL_dscores = np.exp(scores) / (1 + np.exp(scores)) - Y__ # N x 1 # gradijenti parametara grad_w = np.expand_dims((1 / N) * np.sum(dL_dscores * X, axis=0), axis=1) + param_lambda * (1 / (2 * np.linalg.norm(w))) * 2 * w # D x 1 grad_b = (1 / N) * np.sum(dL_dscores) # 1 x 1 # poboljani parametri w += -param_delta * grad_w b += -param_delta * grad_b return w,b if __name__=="__main__": np.random.seed(100) # get the training dataset X,Y_ = data.sample_gauss(2, 100) # train the model w,b = binlogreg_train(X, data.class_to_onehot(Y_)) # evaluate the model on the training dataset probs = binlogreg_classify(X, w,b) Y = probs>0.5 # report performance accuracy, recall, precision = data.eval_perf_binary(Y[:,-1], Y_) AP = data.eval_AP(Y_) print (accuracy, recall, precision, AP) # graph the decision surface rect=(np.min(X, axis=0), np.max(X, axis=0)) data.graph_surface(lambda x: binlogreg_classify(x,w,b), rect, offset=0.5) # graph the data points data.graph_data(X, Y_, Y[:,-1], special=[]) plt.show()

24.851064

141

0.610445

286e9cde8312920eabbf75c1a2872023f23ceb28

778

py

Python

LintCode/1103.py

RENHANFEI/LintCode

d572dee248ba4c2a95b52cd737d76c7297f4e7b4

[ "CNRI-Python" ]

null

LintCode/1103.py

RENHANFEI/LintCode

d572dee248ba4c2a95b52cd737d76c7297f4e7b4

[ "CNRI-Python" ]

null

LintCode/1103.py

RENHANFEI/LintCode

d572dee248ba4c2a95b52cd737d76c7297f4e7b4

[ "CNRI-Python" ]

null

from collections import Counter

25.933333

71

0.417738

286fb0783887ca84bf84591d7e276b7bf74e2f66

2,867

py

Python

safe_eval/default_rules.py

bentheiii/safe_eval

caf9e7a6df3d6029e4bdac2abe11326d55c09ed2

[ "MIT" ]

1

2021-05-16T17:24:05.000Z

safe_eval/default_rules.py

bentheiii/safe_eval

caf9e7a6df3d6029e4bdac2abe11326d55c09ed2

[ "MIT" ]

null

safe_eval/default_rules.py

bentheiii/safe_eval

caf9e7a6df3d6029e4bdac2abe11326d55c09ed2

[ "MIT" ]

null

from _ast import In, NotIn, Is, IsNot from collections import deque, Counter from decimal import Decimal from fractions import Fraction from safe_eval.rules import BinOpRule, CallableTypeRule, CallableRule, GetattrTypeRule, CallableMethodRule k_view_type = type({}.keys()) v_view_type = type({}.values()) it_view_type = type({}.items()) trusted_iterator_types = set( type(iter(t())) for t in (str, tuple, bytes, list, set, frozenset, dict, deque, Counter) ) trusted_iterator_types.update(( type(iter({}.keys())), type(iter({}.values())), type(iter({}.items())), type(iter(range(0))), )) immutable_trusted = frozenset((int, bool, float, str, complex, frozenset, tuple, Decimal, Fraction, bytes, type(None), type(...), type(NotImplemented), object, range)) mutable_trusted = frozenset((list, set, dict, k_view_type, v_view_type, it_view_type, Exception, NameError, ValueError, LookupError, KeyError, TypeError, deque, Counter, *trusted_iterator_types)) trusted_types = immutable_trusted | mutable_trusted trusted_types |= trusted_iterator_types bin_op_trusted_types = trusted_types default_bin_rules = [ BinOpRule(..., op_set=(Is, IsNot)), BinOpRule(bin_op_trusted_types), BinOpRule(..., bin_op_trusted_types, (In, NotIn)) ] trusted_builtin_unary_funcs = frozenset(( abs, all, any, ascii, bin, bool, bytearray, bytes, chr, complex, dict, enumerate, float, format, frozenset, hasattr, hash, hex, int, iter, len, list, max, min, next, oct, property, range, repr, reversed, round, set, slice, sorted, str, sum, tuple, zip, )) safe_builtin_unary_funcs = frozenset(( id, callable, classmethod, ord, )) # todo a lot of functions are only fine if iteration is fine, do that default_callable_rules = [ CallableTypeRule(trusted_builtin_unary_funcs, trusted_types), CallableTypeRule(safe_builtin_unary_funcs, ...), CallableTypeRule(divmod, trusted_types, trusted_types), CallableRule((isinstance, issubclass), ..., trusted_types), CallableRule(object), CallableTypeRule(pow, trusted_types, trusted_types, trusted_types) ] imported_builtin_names = {*trusted_builtin_unary_funcs, *safe_builtin_unary_funcs, divmod, isinstance, issubclass, object, pow} default_namespace = {ibn.__name__: ibn for ibn in imported_builtin_names} default_attr_rules = [] _allow_method(str, str.join, trusted_types)

31.505495

118

0.702825

2870b3250a7dca1e04fe54265450ad0c248653be

6,745

py

Python

test/lib/mayaUsd/render/vp2RenderDelegate/testVP2RenderDelegatePointInstanceSelection.py

ika-rporter/maya-usd

8f216a4fb955fc44c0abda55caa53ed295aaa625

[ "Apache-2.0" ]

507

2019-07-30T20:05:10.000Z

2022-03-30T07:38:43.000Z

test/lib/mayaUsd/render/vp2RenderDelegate/testVP2RenderDelegatePointInstanceSelection.py

ika-rporter/maya-usd

8f216a4fb955fc44c0abda55caa53ed295aaa625

[ "Apache-2.0" ]

1,188

2019-07-31T11:27:27.000Z

2022-03-31T21:06:06.000Z

test/lib/mayaUsd/render/vp2RenderDelegate/testVP2RenderDelegatePointInstanceSelection.py

ika-rporter/maya-usd

8f216a4fb955fc44c0abda55caa53ed295aaa625

[ "Apache-2.0" ]

165

2019-07-30T22:27:57.000Z

2022-03-25T07:20:23.000Z

#!/usr/bin/env mayapy # # Copyright 2021 Autodesk # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # import fixturesUtils import imageUtils import mayaUtils import usdUtils from mayaUsd import lib as mayaUsdLib from mayaUsd import ufe as mayaUsdUfe from maya import cmds import ufe import os if __name__ == '__main__': fixturesUtils.runTests(globals())

37.265193

100

0.697999

2871778d5e8e5178dee6f9e80da7e8ac737d84a0

5,443

py

Python

cy_widgets/strategy/exchange/base.py

cragod/CYWidgets

b1df1e32c363ed9252737d3041a7557b1dc604fe

[ "MIT" ]

1

2021-06-17T02:25:25.000Z

cy_widgets/strategy/exchange/base.py

cragod/CYWidgets

b1df1e32c363ed9252737d3041a7557b1dc604fe

[ "MIT" ]

null

cy_widgets/strategy/exchange/base.py

cragod/CYWidgets

b1df1e32c363ed9252737d3041a7557b1dc604fe

[ "MIT" ]

1

2021-12-08T06:50:33.000Z

# -*- coding: utf-8 -*- import numpy as np import talib as ta from abc import ABC, abstractproperty, abstractclassmethod, abstractmethod

35.344156

165

0.533346

287237c213c17fd114b9833d581d53122d6ad18d

492

py

Python

app/core/admin/__init__.py

3darkman/faction-builder-api

9dda323ef44a1ca0976306a4f20f9cc3e13704ec

[ "MIT" ]

null

app/core/admin/__init__.py

3darkman/faction-builder-api

9dda323ef44a1ca0976306a4f20f9cc3e13704ec

[ "MIT" ]

null

app/core/admin/__init__.py

3darkman/faction-builder-api

9dda323ef44a1ca0976306a4f20f9cc3e13704ec

[ "MIT" ]

null

from django.contrib import admin from core import models from .category import CategoryAdmin from .trait import TraitAdmin from .user import UserAdmin admin.site.register(models.User, UserAdmin) admin.site.register(models.Ability) admin.site.register(models.Category, CategoryAdmin) admin.site.register(models.Trait, TraitAdmin) admin.site.register(models.Domain) admin.site.register(models.FactionType) admin.site.register(models.CategorySlot) admin.site.register(models.StartingProfile)

28.941176

51

0.835366

287358c4458cfef128d6223f0355c87f498e047c

2,196

py

Python

src/predict_video_file.py

irfanmustafas/TeethClassifierCNN

8c58b50162b3f9eb7f12251cbca9fcbd4d6c43b7

[ "MIT" ]

1

2018-12-05T01:49:54.000Z

src/predict_video_file.py

irfanmustafas/TeethClassifierCNN

8c58b50162b3f9eb7f12251cbca9fcbd4d6c43b7

[ "MIT" ]

null

src/predict_video_file.py

irfanmustafas/TeethClassifierCNN

8c58b50162b3f9eb7f12251cbca9fcbd4d6c43b7

[ "MIT" ]

null

import numpy as np import sys import caffe import glob import uuid import cv2 from util import transform_img from mouth_detector_dlib import mouth_detector from caffe.proto import caffe_pb2 import os import shutil from util import histogram_equalization from teeth_cnn import teeth_cnn mouth_detector_instance = mouth_detector() teeth_cnn_instance = teeth_cnn() size = cv2.getTextSize("Showing teeth", cv2.FONT_HERSHEY_PLAIN, 2, 1)[0] x,y = (50,250) # Define the codec and create VideoWriter object fourcc = cv2.cv.CV_FOURCC(*'mp4v') cap = cv2.VideoCapture('../elon.mp4') cap.set(1,19300); ret, frame = cap.read() #cv2.imshow('window_name', frame) # show frame on window w = cap.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH); h = cap.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT); out = cv2.VideoWriter('output_elon.avi',fourcc, 24, (int(w),int(h))) #cap.set(3,500) #cap.set(4,500) #cap.set(5,30) ret, frame = cap.read() while(cap.isOpened()): ret, frame = cap.read() copy_frame = frame.copy() result,prob,xf,yf,wf,hf = teeth_cnn_instance.predict(copy_frame,mouth_detector_instance) if result is not None: if(result == 1): cv2.rectangle(frame, (xf,yf),(wf,hf),(0,255,0),4,0) prob_round = prob[0][1]*100 print prob_round cv2.rectangle(frame, (xf-2,yf-25),(wf+2,yf),(0,255,0),-1,0) cv2.rectangle(frame, (xf-2,hf),(xf+((wf-xf)/2),hf+25),(0,255,0),-1,0) cv2.putText(frame, "Teeth!!",(xf,hf+14),cv2.FONT_HERSHEY_PLAIN,1.2,0,2) cv2.putText(frame, str(prob_round)+"%",(xf,yf-10),cv2.FONT_HERSHEY_PLAIN,1.2,0,2) #out.write(frame) print "SHOWING TEETH!!!" elif(result==0): cv2.rectangle(frame, (xf,yf),(wf,hf),(64,64,64),4,0) prob_round = prob[0][1]*100 print prob_round cv2.rectangle(frame, (xf-2,yf-25),(wf+2,yf),(64,64,64),-1,0) cv2.rectangle(frame, (xf-2,hf),(xf+((wf-xf)/2),hf+25),(64,64,64),-1,0) cv2.putText(frame, "Teeth??",(xf,hf+14),cv2.FONT_HERSHEY_PLAIN,1.2,0,2) cv2.putText(frame, str(prob_round)+"%",(xf,yf-10),cv2.FONT_HERSHEY_PLAIN,1.2,0,2) out.write(frame) cv2.imshow('frame',frame) if cv2.waitKey(200) & 0xFF == ord('q'): break cap.release() out.release() cv2.destroyAllWindows()

31.371429

89

0.679417

28738d283bf4868349454e25d748bec7dc9a9c6f

33,650

py

Python

sdk/python/pulumi_gcp/dataloss/prevention_deidentify_template.py

sisisin/pulumi-gcp

af6681d70ea457843409110c1324817fe55f68ad

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

121

2018-06-18T19:16:42.000Z

2022-03-31T06:06:48.000Z

sdk/python/pulumi_gcp/dataloss/prevention_deidentify_template.py

sisisin/pulumi-gcp

af6681d70ea457843409110c1324817fe55f68ad

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

492

2018-06-22T19:41:03.000Z

2022-03-31T15:33:53.000Z

sdk/python/pulumi_gcp/dataloss/prevention_deidentify_template.py

sisisin/pulumi-gcp

af6681d70ea457843409110c1324817fe55f68ad

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

43

2018-06-19T01:43:13.000Z

2022-03-23T22:43:37.000Z

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from .. import _utilities from . import outputs from ._inputs import * __all__ = ['PreventionDeidentifyTemplateArgs', 'PreventionDeidentifyTemplate'] class PreventionDeidentifyTemplate(pulumi.CustomResource): def __init__(__self__, resource_name: str, *args, **kwargs): resource_args, opts = _utilities.get_resource_args_opts(PreventionDeidentifyTemplateArgs, pulumi.ResourceOptions, *args, **kwargs) if resource_args is not None: __self__._internal_init(resource_name, opts, **resource_args.__dict__) else: __self__._internal_init(resource_name, *args, **kwargs) def _internal_init(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, deidentify_config: Optional[pulumi.Input[pulumi.InputType['PreventionDeidentifyTemplateDeidentifyConfigArgs']]] = None, description: Optional[pulumi.Input[str]] = None, display_name: Optional[pulumi.Input[str]] = None, parent: Optional[pulumi.Input[str]] = None, __props__=None): if opts is None: opts = pulumi.ResourceOptions() if not isinstance(opts, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') if opts.version is None: opts.version = _utilities.get_version() if opts.id is None: if __props__ is not None: raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource') __props__ = PreventionDeidentifyTemplateArgs.__new__(PreventionDeidentifyTemplateArgs) if deidentify_config is None and not opts.urn: raise TypeError("Missing required property 'deidentify_config'") __props__.__dict__["deidentify_config"] = deidentify_config __props__.__dict__["description"] = description __props__.__dict__["display_name"] = display_name if parent is None and not opts.urn: raise TypeError("Missing required property 'parent'") __props__.__dict__["parent"] = parent __props__.__dict__["name"] = None super(PreventionDeidentifyTemplate, __self__).__init__( 'gcp:dataloss/preventionDeidentifyTemplate:PreventionDeidentifyTemplate', resource_name, __props__, opts)

56.841216

422

0.624101

2874251d928931a6c2a13448e5d757c4351cb292

2,163

py

Python

examples/quickstart.py

miketlk/omfgp

6e5a0f52f2688d81bde3e5169a37311c9517fe1d

[ "MIT" ]

null

examples/quickstart.py

miketlk/omfgp

6e5a0f52f2688d81bde3e5169a37311c9517fe1d

[ "MIT" ]

null

examples/quickstart.py

miketlk/omfgp

6e5a0f52f2688d81bde3e5169a37311c9517fe1d

[ "MIT" ]

1

2021-08-16T10:19:52.000Z

import sys import omfgp as gp import time if gp.USES_USCARD: import uscard from machine import Pin def get_default_reader(): """Return default smart card reader.""" if gp.USES_USCARD: return uscard.Reader(name="Smart card reader", ifaceId=2, ioPin=Pin.cpu.A2, clkPin=Pin.cpu.A4, rstPin=Pin.cpu.G10, presPin=Pin.cpu.C2, pwrPin=Pin.cpu.C5) else: return None def card_status(card: gp.card.GPCard) -> list: """Display all kinds of smart card status information returning file list :param card: instance of smart card interface :return: list of load file AID """ isd_status = card.get_status(gp.StatusKind.ISD) app_sd_status = card.get_status(gp.StatusKind.APP_SSD) file_mod_status = card.get_status(gp.StatusKind.LOAD_FILES_MOD) file_status = card.get_status(gp.StatusKind.LOAD_FILES) print("\n=== ISD status ===\n", isd_status, "\n") print("\n=== Apps and SDs ===\n", app_sd_status, "\n") print("\n=== Load files & modules ===\n", file_mod_status, "\n") print("\n=== Load files only ===\n", file_status, "\n") return [s.aid for s in file_status] if __name__ == '__main__': main()

32.283582

77

0.631993

28742e12e6739c290a95e278f025627ff9c82803

685

py

Python

basic/myunittest/test_timeit.py

fplust/python3-cookbook

0eaca2e3631bb69deaf466c32023bbb2093513da

[ "Apache-2.0" ]

1

2019-07-25T09:09:54.000Z

basic/myunittest/test_timeit.py

fplust/python3-cookbook

0eaca2e3631bb69deaf466c32023bbb2093513da

[ "Apache-2.0" ]

null

basic/myunittest/test_timeit.py

fplust/python3-cookbook

0eaca2e3631bb69deaf466c32023bbb2093513da

[ "Apache-2.0" ]

null

#!/usr/bin/env python # -*- encoding: utf-8 -*- """ Topic: Desc : """ from timeit import timeit __author__ = 'Xiong Neng' if __name__ == '__main__': main()

17.125

58

0.563504

28753e72046917448d518c1d4a909cdfe502ee60

7,276

py

Python

tectosaur2/hmatrix/tree.py

tbenthompson/BIE_tutorials

02cd56ab7e63e36afc4a10db17072076541aab77

[ "MIT" ]

15

2021-08-31T15:02:45.000Z

2022-02-11T21:10:01.000Z

tectosaur2/hmatrix/tree.py

tbenthompson/BIE_tutorials

02cd56ab7e63e36afc4a10db17072076541aab77

[ "MIT" ]

79

2021-08-29T15:35:39.000Z

2022-03-25T14:56:42.000Z

tectosaur2/hmatrix/tree.py

tbenthompson/BIE_tutorials

02cd56ab7e63e36afc4a10db17072076541aab77

[ "MIT" ]

3

2022-03-12T14:44:41.000Z

2022-03-21T20:43:20.000Z

from dataclasses import dataclass from typing import Optional import matplotlib.pyplot as plt import numpy as np def build_tree(pts, radii, min_pts_per_box=10): # The tree construction process receives three parameters: # # pts: the center of each element. # # radii: the radius of each element. Remember that we're dealing with spherical # approximations to elements here instead of the triangular elements # themselves. # # min_pts_per_box: this determines when we'll stop splitting. If a box has more # than min_pts_per_box elements, we keep splitting. # We'll start with the element indices in the order that they were given to this function. # build_tree_node will re-order these indices at each step to enforce the rule that # left child indices must be less than right child indices. ordered_idxs = np.arange(pts.shape[0]) # The rest of the tree construction process will be handled by the recursive function: # build_tree_node. The last two parameters are idx_start and idx_end. For the root of the # tree, we pass the full set of elements: (0, pts.shape[0]) root = build_tree_node(pts, radii, min_pts_per_box, ordered_idxs, 0, pts.shape[0]) return Tree(ordered_idxs, pts, radii, root) def build_tree_node( all_pts, all_radii, min_pts_per_box, ordered_idxs, idx_start, idx_end ): # 1) Collect the relevant element data. # A view into the ordered_idxs array for the elements we're working on here. idx_view = ordered_idxs[idx_start:idx_end] # And the center and radius of each element. pts = all_pts[idx_view] radii = all_radii[idx_view] # 2) Define the bounding box. box_center = np.mean(pts, axis=0) sep = pts - box_center[None, :] box_axis_length = np.max(sep, axis=0) box_radius = np.max(np.linalg.norm(sep, axis=1) + radii) # 3) Build the node # To start with, the left and right child are absent and is_leaf=True. # If the node is not a leaf, we'll overwrite these below. node = TreeNode( idx_start, idx_end, box_center, box_radius, is_leaf=True, left=None, right=None ) # 4) Return if the node is a leaf node. # If there are fewer than min_pts_per_box elements in this node, then we do not split. if idx_end - idx_start <= min_pts_per_box: return node # 5) If the node is not a leaf, split! # First, find which axis of the box is longest split_d = np.argmax(box_axis_length) # Then identify which elements are on the left hand side of the box along that axis. split_val = np.median(pts[:, split_d]) is_left = pts[:, split_d] < split_val # 6) Re-arrange indices. # Since we're going to re-arrange indices, we need to save the relevant indices first. left_idxs = idx_view[np.where(is_left)[0]].copy() right_idxs = idx_view[np.where(~is_left)[0]].copy() n_left = left_idxs.shape[0] # Then assign the left side indices to the beginning of our index block idx_view[:n_left] = left_idxs # And assign the right side indices to the end of our index block. idx_view[n_left:] = right_idxs # 7) Create children! idx_split = idx_start + n_left node.is_leaf = False # We recursively call build_tree_node here. The key difference between the left and right # sides is that the left receives the index block [idx_start, idx_split) and the right # receives the index block [idx_split, idx_end). Thus, we've created a smaller, equivalent # problem. node.left = build_tree_node( all_pts, all_radii, min_pts_per_box, ordered_idxs, idx_start, idx_split ) node.right = build_tree_node( all_pts, all_radii, min_pts_per_box, ordered_idxs, idx_split, idx_end ) return node def _traverse(obs_node, src_node, safety_factor, direct_list, approx_list): dist = np.linalg.norm(obs_node.center - src_node.center) if dist > safety_factor * (obs_node.radius + src_node.radius): # We're far away, use an approximate interaction approx_list.append((obs_node, src_node)) elif obs_node.is_leaf and src_node.is_leaf: # If we get here, then we can't split the nodes anymore but they are # still close. That means we need to use a exact interaction. direct_list.append((obs_node, src_node)) else: # We're close by, so we should recurse and use the child tree nodes. # But which node should we recurse with? split_src = ( (obs_node.radius < src_node.radius) and not src_node.is_leaf ) or obs_node.is_leaf if split_src: _traverse(obs_node, src_node.left, safety_factor, direct_list, approx_list) _traverse(obs_node, src_node.right, safety_factor, direct_list, approx_list) else: _traverse(obs_node.left, src_node, safety_factor, direct_list, approx_list) _traverse(obs_node.right, src_node, safety_factor, direct_list, approx_list) def traverse(obs_node, src_node, safety_factor=1.5): direct_list = [] approx_list = [] _traverse(obs_node, src_node, safety_factor, direct_list, approx_list) return direct_list, approx_list def check_tree(pts, radii, tree, node): if node is None: return True idxs = tree.ordered_idxs[node.idx_start : node.idx_end] dist = np.linalg.norm(pts[idxs] - node.center, axis=1) + radii[idxs] if np.any(dist > node.radius): return False else: return check_tree(pts, radii, tree, node.left) and check_tree( pts, radii, tree, node.right ) def plot_tree_level(node, depth, **kwargs): if depth == 0: circle = plt.Circle(tuple(node.center[:2]), node.radius, fill=False, **kwargs) plt.gca().add_patch(circle) if node.left is None or depth == 0: return else: plot_tree_level(node.left, depth - 1, **kwargs) plot_tree_level(node.right, depth - 1, **kwargs) def plot_tree(tree): plt.figure(figsize=(9, 9)) for depth in range(9): plt.subplot(3, 3, 1 + depth) plt.title(f"level = {depth}") plot_tree_level(tree.root, depth, color="b", linewidth=0.5) plt.xlim( [ tree.root.center[0] - tree.root.radius, tree.root.center[0] + tree.root.radius, ] ) plt.ylim( [ tree.root.center[1] - tree.root.radius, tree.root.center[1] + tree.root.radius, ] ) plt.tight_layout() plt.show()

35.149758

94

0.665063

2875e4f861693b2c0256a550012c98712e49a11c

644

py

Python

2017/day2/corruptionChecksum.py

madeleine-adams/advent_of_code_2020

8f142a91d1a40390aad274c5e0513f50b168d029

[ "MIT" ]

null

2017/day2/corruptionChecksum.py

madeleine-adams/advent_of_code_2020

8f142a91d1a40390aad274c5e0513f50b168d029

[ "MIT" ]

null

2017/day2/corruptionChecksum.py

madeleine-adams/advent_of_code_2020

8f142a91d1a40390aad274c5e0513f50b168d029

[ "MIT" ]

null

file = open('corruptionChecksum_input.txt', 'r') spreadsheet = file.readlines() checksum = 0 for line in spreadsheet: cells = line.split() minimum = find_smallest(cells) maximum = find_largest(cells) checksum += maximum - minimum print(checksum)

20.774194

48

0.636646

287609c52314ac1d737c0937fa4d8b3058a4d68f

3,579

py

Python

neurst/cli/inspect_checkpoint.py

ishine/neurst

2ba322393fcfed4261b33f4a657e12bbe321baaa

[ "Apache-2.0" ]

208

2020-11-12T03:56:41.000Z

2022-03-27T07:01:27.000Z

neurst/cli/inspect_checkpoint.py

ishine/neurst

2ba322393fcfed4261b33f4a657e12bbe321baaa

[ "Apache-2.0" ]

16

2021-02-20T07:57:03.000Z

2022-01-27T07:36:31.000Z

neurst/cli/inspect_checkpoint.py

ishine/neurst

2ba322393fcfed4261b33f4a657e12bbe321baaa

[ "Apache-2.0" ]

33

2020-11-12T04:44:50.000Z

2022-03-23T09:22:29.000Z

# Copyright 2020 ByteDance Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import re import sys import tensorflow as tf from neurst.models.model_utils import _summary_model_variables from neurst.utils.compat import wrapper_var_name if __name__ == "__main__": cli_main()

41.137931

103

0.658843

28762253888319609860c7b7288acdb032a74ac2

1,621

py

Python

homepage/migrations/0005_professor_test_data.py

oriAdler/ClassRater

a68492ea8eab1475ab604da9d6efc99c73954d4b

[ "MIT" ]

1

2021-04-12T18:05:12.000Z

homepage/migrations/0005_professor_test_data.py

ellaml/ClassRater

d786f9fb4bb51041590e46165badf12a7beef67e

[ "MIT" ]

103

2021-03-09T07:12:20.000Z

2021-05-23T06:13:21.000Z

homepage/migrations/0005_professor_test_data.py

ellaml/ClassRater

d786f9fb4bb51041590e46165badf12a7beef67e

[ "MIT" ]

17

2021-03-09T07:07:44.000Z

2021-05-02T16:31:45.000Z

from django.db import migrations, transaction

33.770833

76

0.595312

2876482aeef7877b4183338fac2e85b74a0eaedf

1,220

py

Python

scripts/hsvanalyzer.py

acmerobotics/relic-recovery

4ff05bbf906829aef0a98bc32691e5d0eadc1d8f

[ "MIT" ]

32

2018-01-17T03:00:02.000Z

2022-01-15T18:30:48.000Z

scripts/hsvanalyzer.py

acmerobotics/relic-recovery

4ff05bbf906829aef0a98bc32691e5d0eadc1d8f

[ "MIT" ]

4

2017-10-21T20:28:27.000Z

2018-04-02T05:27:00.000Z

scripts/hsvanalyzer.py

acmerobotics/relic-recovery

4ff05bbf906829aef0a98bc32691e5d0eadc1d8f

[ "MIT" ]

7

2018-02-21T00:59:20.000Z

2021-01-21T21:52:17.000Z

import cv2 import numpy as np from matplotlib import pyplot as plt from util import resize_min_dim, smart_hsv_range IMAGE_FILENAME = '/Users/ryanbrott/Desktop/36.jpg' MIN_DIMENSION = 480 # LOWER_HSV, UPPER_HSV = (170, 80, 0), (7, 255, 255) LOWER_HSV, UPPER_HSV = (175, 80, 80), (22, 255, 255) image = cv2.imread(IMAGE_FILENAME) image = resize_min_dim(image, MIN_DIMENSION) hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV) mask = smart_hsv_range(hsv, LOWER_HSV, UPPER_HSV) hue_hist = cv2.calcHist([hsv], [0], None, [180], [0, 180]) plt.gcf().canvas.set_window_title(IMAGE_FILENAME) plt.subplot(2, 3, 1) plt.plot(hue_hist) plt.xlim([0, 180]) plt.title('Hue Histogram') plt.subplot(2, 3, 2) plt.imshow(hsv[:,:,0], cmap=plt.cm.binary) plt.title('Hue') plt.subplot(2, 3, 4) plt.imshow(hsv[:,:,1], cmap=plt.cm.binary) plt.title('Saturation') plt.subplot(2, 3, 5) plt.imshow(hsv[:,:,2], cmap=plt.cm.binary) plt.title('Value') plt.subplot(2, 3, 3) plt.imshow(mask, cmap=plt.cm.binary) plt.title('Mask') mask_3c = np.zeros(image.shape, np.uint8) for i in range(3): mask_3c[:,:,i] = mask plt.subplot(2, 3, 6) plt.imshow(cv2.cvtColor(cv2.bitwise_and(image, mask_3c), cv2.COLOR_BGR2RGB)) plt.title('Image') plt.show()

23.461538

76

0.705738

2876ee5a4ee75e47b6a9d9c1abc057001acf18bc

1,114

py

Python

FEniCSUI/AnalysesHub/models.py

nasserarbabi/FEniCSUI-dev

f8f161e1b49932843e01301212e7d031fff4f6c8

[ "MIT" ]

null

FEniCSUI/AnalysesHub/models.py

nasserarbabi/FEniCSUI-dev

f8f161e1b49932843e01301212e7d031fff4f6c8

[ "MIT" ]

8

2021-03-10T21:59:52.000Z

2021-09-22T19:12:57.000Z

FEniCSUI/AnalysesHub/models.py

nasserarbabi/FEniCSUI

f8f161e1b49932843e01301212e7d031fff4f6c8

[ "MIT" ]

null

from django.db import models from dashboard.models import projects

23.208333

42

0.672352

2877efb3076b7e16a9739c3098ef12ad38d235d3

1,924

py

Python

code/pyto/util/test/_test_numpy_plus.py

anmartinezs/pyseg_system

5bb07c7901062452a34b73f376057cabc15a13c3

[ "Apache-2.0" ]

12

2020-01-08T01:33:02.000Z

2022-03-16T00:25:34.000Z

code/pyto/util/test/_test_numpy_plus.py

anmartinezs/pyseg_system

5bb07c7901062452a34b73f376057cabc15a13c3

[ "Apache-2.0" ]

8

2019-12-19T19:34:56.000Z

2022-03-10T10:11:28.000Z

code/pyto/util/test/_test_numpy_plus.py

anmartinezs/pyseg_system

5bb07c7901062452a34b73f376057cabc15a13c3

[ "Apache-2.0" ]

2

2022-03-30T13:12:22.000Z

2022-03-30T18:12:10.000Z

""" ToDo: convert to proper format Tests for modules in this directory """ from __future__ import print_function # Author: Vladan Lucic, last modified 05.04.07 import scipy import scipy.ndimage import numpy import pyto.util.numpy_plus as np_plus # define test arrays aa = numpy.arange(12, dtype='int32') aa = aa.reshape((3,4)) bb = numpy.arange(6, dtype='int32') bb = bb.reshape((2,3))

26.722222

73

0.572245

2878821e6aef46d6ef7a165e5a576c9bd3a04754

922

py

Python

GithubRepositoryStatistics-Python3/Repository.py

SmileZXLee/GithubRepositoryStatistics

62eeddd715aecf268c48b39aa596f1168a3c2661

[ "MIT" ]

1

2020-07-15T14:12:53.000Z

GithubRepositoryStatistics-Python3/Repository.py

SmileZXLee/GithubRepositoryStatistics

62eeddd715aecf268c48b39aa596f1168a3c2661

[ "MIT" ]

null

GithubRepositoryStatistics-Python3/Repository.py

SmileZXLee/GithubRepositoryStatistics

62eeddd715aecf268c48b39aa596f1168a3c2661

[ "MIT" ]

null

#coding=utf-8 __author__ = 'zxlee' __github__ = 'https://github.com/SmileZXLee/GithubRepositoryStatistics'

26.342857

87

0.627983

287c433b713a1b08f3c14e17afb0adcebbc1cab6

3,242

py

Python

src/www/__init__.py

jbrezmorf/codecritic

190df65f2f12667469b55abed48a45de5dc18965

[ "MIT" ]

null

src/www/__init__.py

jbrezmorf/codecritic

190df65f2f12667469b55abed48a45de5dc18965

[ "MIT" ]

20

2019-05-26T12:13:19.000Z

2020-09-09T16:37:09.000Z

src/www/__init__.py

jbrezmorf/codecritic

190df65f2f12667469b55abed48a45de5dc18965

[ "MIT" ]

1

2020-04-13T09:02:48.000Z

#!/bin/python3 # author: Jan Hybs import enum import pathlib from bson import objectid from flask import Flask, redirect, session, render_template, url_for import flask.json from flask_cors import CORS from loguru import logger from entities.crates import ICrate from env import Env from functools import wraps render_template_ext = render_template_base(Env=Env, version=Env.version) app = Flask(__name__) app.config['SECRET_KEY'] = 'secret!' app.root_path = Env.www app.json_encoder = CustomJSONEncoder cors = CORS(app) # @app.context_processor # def override_url_for(): # """ # Generate a new token on every request to prevent the browser from # caching static files. # """ # return dict(url_for=dated_url_for) # # # def dated_url_for(endpoint, **values): # if endpoint == 'static': # filename = values.get('filename', None) # if filename: # file_path = os.path.join(app.root_path, endpoint, filename) # values['q'] = int(os.stat(file_path).st_mtime) # return url_for(endpoint, **values)

25.936

82

0.612585

287d78c0342acb7571ce49d00f17612456b0c4a2

18,740

py

Python

pages/getAltData.py

ngocuong0105/ts_webapp

4399862ead6eb2d0c993d36fffe14967984ad4b2

[ "MIT" ]

null

pages/getAltData.py

ngocuong0105/ts_webapp

4399862ead6eb2d0c993d36fffe14967984ad4b2

[ "MIT" ]

null

pages/getAltData.py

ngocuong0105/ts_webapp

4399862ead6eb2d0c993d36fffe14967984ad4b2

[ "MIT" ]

null

import base64 from collections import deque from io import BytesIO import os import time from PIL import Image import pandas as pd from pandas.core.arrays import boolean import praw import requests import streamlit as st import datetime import pytesseract pytesseract.pytesseract.tesseract_cmd ='context/tesseract' import tweepy from framework.page import Page from framework.utils import markdown_css, click_button

44.513064

143

0.596265

287d866f9124af9905e3876a7fc982e255ffcb59

157

py

Python

npt/pipelines/__init__.py

chbrandt/npt

7d58db9987c8f4d93c4e61e1fc98cce38733d06e

[ "MIT" ]

null

npt/pipelines/__init__.py

chbrandt/npt

7d58db9987c8f4d93c4e61e1fc98cce38733d06e

[ "MIT" ]

2

2022-02-18T16:38:13.000Z

2022-02-18T16:56:33.000Z

npt/pipelines/__init__.py

chbrandt/npt

7d58db9987c8f4d93c4e61e1fc98cce38733d06e

[ "MIT" ]

1

2022-03-15T09:03:51.000Z

from npt import log from . import search as Search from . import download as Download from . import processing as Processing from . import mosaic as Mosaic

22.428571

38

0.789809

287f3fa6bbdc5def4722251d903f7d2865df6fbb

324

py

Python

config.py

Shutey/ShuteyBot2.0

16f0baf6e8725bb452cac06fa60d6db023212f6c

[ "MIT" ]

2

2020-04-23T00:52:06.000Z

2020-04-23T00:56:24.000Z

config.py

Shutey/ShuteyBot2.0

16f0baf6e8725bb452cac06fa60d6db023212f6c

[ "MIT" ]

null

config.py

Shutey/ShuteyBot2.0

16f0baf6e8725bb452cac06fa60d6db023212f6c

[ "MIT" ]

null

token = 'Mzc5NTc3MDc1NTU3NzI4MjU2.DXixQA.DLLB8b81nSyB1IGNJ6WeEeukAQU' #Put Your bots token here prefix = '^^' #put prefix here link = 'https://discordapp.com/oauth2/authorize?client_id=379577075557728256&scope=bot&permissions=134659080' #put bot invite link here ownerid = '227860415709708288' #put your id here

36

136

0.774691

2881d51b1365029af80a4c7b248cb3bb598a7958

3,466

py

Python

frispy/throw_data.py

carrino/FrisPy

db9e59f465ee25d1c037d580c37da8f35b930b50

[ "MIT" ]

null

frispy/throw_data.py

carrino/FrisPy

db9e59f465ee25d1c037d580c37da8f35b930b50

[ "MIT" ]

null

frispy/throw_data.py

carrino/FrisPy

db9e59f465ee25d1c037d580c37da8f35b930b50

[ "MIT" ]

null

35.731959

124

0.638777

288275f551eb96263ac0a6a9893bc8305effff9d

7,754

py

Python

test/test_hankelutils.py

hlatkydavid/vnmrjpy

48707a1000dc87e646e37c8bd686e695bd31a61e

[ "MIT" ]

null

test/test_hankelutils.py

hlatkydavid/vnmrjpy

48707a1000dc87e646e37c8bd686e695bd31a61e

[ "MIT" ]

null

test/test_hankelutils.py

hlatkydavid/vnmrjpy

48707a1000dc87e646e37c8bd686e695bd31a61e

[ "MIT" ]

null

import unittest import vnmrjpy as vj import numpy as np import matplotlib.pyplot as plt import time #import cupy as cp RP={'rcvrs':4,'filter_size':(11,7),'virtualcoilboost':False} PLOTTING = False

39.969072

79

0.596595

2883fadc5c01ff1f187f68ba84f5e3ae0a52978b

1,057

py

Python

src/archive/test3.py

felipearcaro/indexing-repository-python

4fa504d3535495b30db443cc753ebc56e7e329c2

[ "BSD-2-Clause-FreeBSD" ]

null

src/archive/test3.py

felipearcaro/indexing-repository-python

4fa504d3535495b30db443cc753ebc56e7e329c2

[ "BSD-2-Clause-FreeBSD" ]

null

src/archive/test3.py

felipearcaro/indexing-repository-python

4fa504d3535495b30db443cc753ebc56e7e329c2

[ "BSD-2-Clause-FreeBSD" ]

null

#setup import docx2txt # extract text text = docx2txt.process("../documents/ambev.docx") text2 = docx2txt.process("../documents/ambev2.docx") text3 = docx2txt.process("../documents/ambev3.docx") from whoosh.fields import Schema, TEXT schema = Schema(title=TEXT, content=TEXT) import os, os.path from whoosh import index if not os.path.exists("indexdir"): os.mkdir("indexdir") ix = index.create_in("indexdir", schema) #indexando arquivos ix = index.open_dir("indexdir") writer = ix.writer() writer.add_document(title=u"ambev", content=text) writer.add_document(title=u"gleidson", content=text2) writer.add_document(title=u"gleidson", content=text3) writer.add_document(title=u"sato", content=u"thiago") writer.commit() #buscando with ix.searcher() as searcher: searcher = ix.searcher() from whoosh.query import * myquery = And([Term("content", u"chamorro")) from whoosh.qparser import QueryParser parser = QueryParser("content", ix.schema) myquery = parser.parse(querystring) results = searcher.search(myquery) print(len(results))

24.581395

53

0.746452

28846fa1c1e9c7ab3ae95eddc73455be7f366a02

196

py

Python

Source Code/web/backend/files_app/fileapi/urls.py

creosB/Virtual-pdf-library

edb334b16dfd0d3c616683f6fbb370e54f489560

[ "CC0-1.0" ]

11

2021-12-20T01:51:56.000Z

2022-01-01T10:17:47.000Z

Source Code/web/backend/files_app/fileapi/urls.py

creosB/Virtual-pdf-library

edb334b16dfd0d3c616683f6fbb370e54f489560

[ "CC0-1.0" ]

null

Source Code/web/backend/files_app/fileapi/urls.py

creosB/Virtual-pdf-library

edb334b16dfd0d3c616683f6fbb370e54f489560

[ "CC0-1.0" ]

1

2021-12-21T08:47:56.000Z

from django.urls import path from .views import FileList, FileDetail urlpatterns = [ path('',FileList.as_view()), path('<int:pk>/',FileDetail.as_view()), # individual items from django ]

24.5

74

0.704082

288538cbd5c881814ddd71394b3b7fcabde021bf

4,427

py

Python

barcodes/generateBarcodes.py

sbarton272/AcousticBarcodes-Explorations

73f019228988727575af7d67d1b7c7119f6c49a6

[ "MIT" ]

null

barcodes/generateBarcodes.py

sbarton272/AcousticBarcodes-Explorations

73f019228988727575af7d67d1b7c7119f6c49a6

[ "MIT" ]

null

barcodes/generateBarcodes.py

sbarton272/AcousticBarcodes-Explorations

73f019228988727575af7d67d1b7c7119f6c49a6

[ "MIT" ]

null

""" Generate barcode images with various encodings TODO - Include text at bottom - DXF instead """ #======================================================== # Imports #======================================================== from dxfwrite import DXFEngine as dxf #======================================================== # Constants #======================================================== START_BAND = [1,1] STOP_BAND = [0,1] #======================================================== # Hamming Codes #======================================================== #======================================================== # Barcode drawer #======================================================== #======================================================== # Parse options #======================================================== if __name__ == '__main__': codes = [[1,1,1],[0,0,0],[0,1,0],[1,0,1]] width = 15 height = 20 unit = 1 notchWidth = [.3,.5] for code in codes: codeStr = ''.join(map(str,code)) for n in notchWidth: filename = 'code' + codeStr + '-notch' + str(n) + '-len' + str(unit) + '.dxf' drawer = BarcodeDrawer(code, width=width, height=height, unitWidth=unit, notchWidth=n, includeText=True) drawer.draw(filename)

29.125

98

0.483171

2887834c88b90ae4d29891c6021442f87fb025c0

110

py

Python

example/cheeseshop/apps/catalog/admin.py

sflems/django-constance

e177292c74cbf158c7218d8818d5d6c34b17eee1

[ "BSD-3-Clause" ]

899

2015-12-17T09:24:11.000Z

2022-03-31T15:57:53.000Z

example/cheeseshop/apps/catalog/admin.py

sflems/django-constance

e177292c74cbf158c7218d8818d5d6c34b17eee1

[ "BSD-3-Clause" ]

342

2015-12-27T11:07:44.000Z

2022-03-24T13:34:46.000Z

example/cheeseshop/apps/catalog/admin.py

sflems/django-constance

e177292c74cbf158c7218d8818d5d6c34b17eee1

[ "BSD-3-Clause" ]

213

2015-12-23T00:32:34.000Z

2022-03-17T17:04:57.000Z

from django.contrib import admin from cheeseshop.apps.catalog.models import Brand admin.site.register(Brand)

22

48

0.836364

28878c846aed485a7bc9a73365300409e1defb8b

672

py

Python

leetcode/editor/cn/FindKPairsWithSmallestSums.py

huangge1199/leet-code-python

5d01bbb6f12a495ea7ea0a90b5b3b4aa92bcc2f7

[ "Apache-2.0" ]

1

2022-02-12T13:55:41.000Z

leetcode/editor/cn/FindKPairsWithSmallestSums.py

huangge1199/leet-code-python

5d01bbb6f12a495ea7ea0a90b5b3b4aa92bcc2f7

[ "Apache-2.0" ]

null

leetcode/editor/cn/FindKPairsWithSmallestSums.py

huangge1199/leet-code-python

5d01bbb6f12a495ea7ea0a90b5b3b4aa92bcc2f7

[ "Apache-2.0" ]

null

# 373: K # leetcode submit region begin(Prohibit modification and deletion) from heapq import heappop, heappush from typing import List # leetcode submit region end(Prohibit modification and deletion)

33.6

92

0.578869

288bed12c190fb35b526a110b53eefe990c1f7a5

2,505

py

Python

urls.py

Shakil-1501/Quizdjango

5e201d0f05ce2a49d36484009ff6032821365bc6

[ "MIT" ]

null

urls.py

Shakil-1501/Quizdjango

5e201d0f05ce2a49d36484009ff6032821365bc6

[ "MIT" ]

null

urls.py

Shakil-1501/Quizdjango

5e201d0f05ce2a49d36484009ff6032821365bc6

[ "MIT" ]

null

# Core Django imports. from django.urls import path from django.shortcuts import redirect, render # LMS app imports from lms.views.course.course_views import ( CourseListView,fetch_questions,compute_stats,display_lp,Edit_quiz,preview_quiz,fetch_questions_oneatatime,compute_html,enter_comment,quiz_lp ) from lms.views.dashboard.student.dashboard_views import ( DashboardHomeView, ) from lms.views.account.register_view import \ ( ActivateView, AccountActivationSentView, UserRegisterView, ) from lms.views.account.logout_view import UserLogoutView from lms.views.account.login_view import UserLoginView # Specifies the app name for name spacing. app_name = "lms" # lms/urls.py urlpatterns = [ # LMS URLS # # /home/ path( route='', view=CourseListView.as_view(), name='home' ), path('lms/course',compute_stats,name="compute_stats"), path('lms/quiz',fetch_questions_oneatatime,name="fetch_questions_oneatatime"), path('lms/quiz3',fetch_questions,name="fetch_questions"), path('lms/quizlp',quiz_lp,name="quiz_lp"), path('lms/quiz2',display_lp,name="display_lp"), path('admin/',Edit_quiz,name="Edit_quiz"), path('lms/quizs',preview_quiz,name="preview_quiz"), path('lms/file',compute_html,name="compute_html"), path('lms/enter_comment',enter_comment,name="enter_comment"), #path('quiz2', lambda request: render(request, 'templates/lms/quiz2.html')), # ACCOUNT URLS # # /account/login/ path( route='account/login/', view=UserLoginView.as_view(), name='login' ), # /account/login/ path( route='account/register/', view=UserRegisterView.as_view(), name='register' ), # /account/logout/ path( route='account/logout/', view=UserLogoutView.as_view(), name='logout' ), path(route='account_activation_sent/', view=AccountActivationSentView.as_view(), name='account_activation_sent' ), path(route='activate/<uidb64>/<token>/', view=ActivateView.as_view(), name='activate' ), # DASHBOARD URLS # # /author/dashboard/home/ path( route="student/dashboard/home/", view=DashboardHomeView.as_view(), name="dashboard_home" ), ]

22.567568

145

0.621956

288fb0e62147ed4c6a19e3faeb3476a5404525aa

270

py

Python

rasterio/errors.py

clembou/rasterio

57169c31dae04e1319b4c4b607345475a7122910

[ "BSD-3-Clause" ]

null

rasterio/errors.py

clembou/rasterio

57169c31dae04e1319b4c4b607345475a7122910

[ "BSD-3-Clause" ]

null

rasterio/errors.py

clembou/rasterio

57169c31dae04e1319b4c4b607345475a7122910

[ "BSD-3-Clause" ]

null

"""A module of errors."""

27

78

0.733333

2893612d9bb5f812e7e498a10ba625355b7d1dee

1,794

py

Python

clientV4.py

sekranmert/AWS-Arduino-SmartHomeSystem

80f4b6a5871fccb3bfc065d3fac5ba09feec525a

[ "MIT" ]

1

2021-06-24T14:24:39.000Z

clientV4.py

sekranmert/AWS-Arduino-SmartHomeSystem

80f4b6a5871fccb3bfc065d3fac5ba09feec525a

[ "MIT" ]

null

clientV4.py

sekranmert/AWS-Arduino-SmartHomeSystem

80f4b6a5871fccb3bfc065d3fac5ba09feec525a

[ "MIT" ]

null

import socket import threading helpMessage = '-q -- close connection\n-l -- list of connected devices\n-t -- server time \n-s "arduino/client ""reciever name" "message" -- send message (messages can be max 100 character) \nif reciever is an arduino board it can be controlled by this messsage:\n -s arduino "arduino name" led "0/1/status" \n' print("connecting...\n for command list write '-h' \n"+helpMessage) host = '127.0.0.1' # 127.0.0.1 for local port = 9999 # 9999 for local socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) socket.connect((host, port)) recvThread = threading.Thread(target=recvTh) sendThread = threading.Thread(target=sendTh) recvThread.start() sendThread.start()

32.618182

312

0.545151

289396e6e160ca17355478e692561082d33da8f2

3,885

py

Python

data_loader/data_loaders.py

ChunpingQiu/Sen2LCZ_CNN

5576567da658f945321280f37ff8d9bf46dd1818

[ "MIT" ]

null

data_loader/data_loaders.py

ChunpingQiu/Sen2LCZ_CNN

5576567da658f945321280f37ff8d9bf46dd1818

[ "MIT" ]

null

data_loader/data_loaders.py

ChunpingQiu/Sen2LCZ_CNN

5576567da658f945321280f37ff8d9bf46dd1818

[ "MIT" ]

1

2021-08-19T03:35:05.000Z

from torchvision import datasets, transforms from base import BaseDataLoader from torch.utils.data import Dataset, DataLoader import pandas as pd import torch from skimage import io#, transform import numpy as np

32.647059

121

0.621107

28957d205b560942a43fe20af3ee47c7d8d34a15

591

py

Python

eval_predictions.py

uporwal/sigir-2019-ecom-challenge

bffa7f99930321ad5d86e0cddd3c9ddfb98ba3d2

[ "MIT" ]

7

2019-06-05T01:42:54.000Z

2020-07-31T04:31:47.000Z

eval_predictions.py

uporwal/sigir-2019-ecom-challenge

bffa7f99930321ad5d86e0cddd3c9ddfb98ba3d2

[ "MIT" ]

5

2019-06-09T15:11:47.000Z

2019-06-28T18:35:48.000Z

eval_predictions.py

uporwal/sigir-2019-ecom-challenge

bffa7f99930321ad5d86e0cddd3c9ddfb98ba3d2

[ "MIT" ]

5

2019-06-04T17:06:33.000Z

2021-01-15T11:14:43.000Z

import evaluation_script import argparse parser = argparse.ArgumentParser(description='Evaluation script used in the eBay SIGIR 2019 eCommerce Search Challenge.') parser.add_argument('-g', '--ground-truth-file', required=True, help="Ground truth file") parser.add_argument('-p', '--prediction-file', required=True, help="Prediction file") parser.add_argument('-d', '--document-file', required=False, default=None, help="Document file") args = parser.parse_args() r = evaluation_script.evaluate_submission(args.ground_truth_file, args.prediction_file, args.document_file) print(); print(r)

45.461538

121

0.781726

2895a62d74a6cf74dd272cfa08d6a6029b8f3434

48

py

Python

starfish/__main__.py

haoxusci/starfish

d7bd856024c75f2ce41504406f2a663566c3814b

[ "MIT" ]

164

2018-03-21T21:52:56.000Z

2022-03-23T17:14:39.000Z

starfish/__main__.py

lbgbox/starfish

0e879d995d5c49b6f5a842e201e3be04c91afc7e

[ "MIT" ]

1,728

2018-03-15T23:16:09.000Z

2022-03-12T00:09:18.000Z

starfish/__main__.py

lbgbox/starfish

0e879d995d5c49b6f5a842e201e3be04c91afc7e

[ "MIT" ]

66

2018-03-25T17:21:15.000Z

2022-01-16T09:17:11.000Z

from .core.starfish import starfish starfish()

12

35

0.791667

2896d0048b215dc837ae66958ce2ac38e7c770f9

968

py

Python

coreapp/migrations/0058_auto_20200426_1348.py

Quanscendence/braynai

ab828ca95571c6dffef2b2392522e6a4160a2304

[ "MIT" ]

null

coreapp/migrations/0058_auto_20200426_1348.py

Quanscendence/braynai

ab828ca95571c6dffef2b2392522e6a4160a2304

[ "MIT" ]

null

coreapp/migrations/0058_auto_20200426_1348.py

Quanscendence/braynai

ab828ca95571c6dffef2b2392522e6a4160a2304

[ "MIT" ]

null

# Generated by Django 2.2 on 2020-04-26 08:18 from django.db import migrations, models

29.333333

144

0.597107

2897d15751315f822719f939136b75871bf6ecab

1,431

py

Python

server/price_cache.py

pareeohnos/ktrade

1eaed1ff16ded580d5649c667935357567e7b514

[ "MIT" ]

5

2021-09-08T11:04:15.000Z

2021-11-27T08:42:23.000Z

server/price_cache.py

pareeohnos/ktrade

1eaed1ff16ded580d5649c667935357567e7b514

[ "MIT" ]

36

2021-08-31T09:28:10.000Z

2021-12-10T06:47:04.000Z

server/price_cache.py

pareeohnos/ktrade

1eaed1ff16ded580d5649c667935357567e7b514

[ "MIT" ]

2

2021-08-29T02:53:54.000Z

2021-08-29T06:21:36.000Z

import logging from server.singleton_meta import SingletonMeta log = logging.getLogger(__name__)

31.108696

81

0.714186

289918d2c57a6904734431ddd51bb10c97d644f6

499

py

Python

series_loop.py

Akshara2820/Python_WhileLoop

d525b547bc8c8236cb2cd1881080ec4e6604fffc

[ "MIT" ]

1

2021-09-15T03:42:15.000Z

series_loop.py

Akshara2820/Python_WhileLoop

d525b547bc8c8236cb2cd1881080ec4e6604fffc

[ "MIT" ]

null

series_loop.py

Akshara2820/Python_WhileLoop

d525b547bc8c8236cb2cd1881080ec4e6604fffc

[ "MIT" ]

null

# (10,2,20,4,30,6,40,8,50) n=int(input("enter no--")) i=1 c=10 while i<=n: if i%2==0: c+=10 print(i,end=",") i+=1 i+=1 print(c,end=",") # (1+10=11, 11+20=31, 31+30=61, 61+40=101) n=int(input("enter no,-")) i=0 d=1 s=10 while i<n: print(d,end=",") d=d+s s+=10 i+=1 # (1+10=11, 11+20=31, 31+30=61, 61+40=101) n=int(input("enter no.==")) i=1 d=1 while i<=n: print(d,end=" ") d=d+10*i i+=1

12.794872

44

0.420842

289d03fd3a78072e9344f01958c2c279a5179efe

9,092

py

Python

modules/Manager.py

jurajkula/IBT

7b09f6d331433bfbf3e7955754a36b69b332bb4e

[ "MIT" ]

3

2019-05-16T18:54:49.000Z

2019-10-21T11:12:50.000Z

modules/Manager.py

jurajkula/IBT

7b09f6d331433bfbf3e7955754a36b69b332bb4e

[ "MIT" ]

null

modules/Manager.py

jurajkula/IBT

7b09f6d331433bfbf3e7955754a36b69b332bb4e

[ "MIT" ]

null

import os import time from os import mkdir from os.path import isdir from threading import Lock import cv2 import imutils from modules.Camera import Detect from modules.Camera.CameraHandler import CameraHandler from modules.Config import Config from modules.Fusion import Fusion from modules.Logger.Logger import Logger from modules.Radar.RadarHandler import RadarHandler

34.439394

114

0.478883

289e8099349c64172c6b2bf0ba568b861c6f1152

5,809

py

Python

train.py

okwrtdsh/3D-ResNets-PyTorch

f36a32ea8b283524d1d102937c49689b1f475b5f

[ "MIT" ]

null

train.py

okwrtdsh/3D-ResNets-PyTorch

f36a32ea8b283524d1d102937c49689b1f475b5f

[ "MIT" ]

null

train.py

okwrtdsh/3D-ResNets-PyTorch

f36a32ea8b283524d1d102937c49689b1f475b5f

[ "MIT" ]

null

import torch from torch.autograd import Variable import time import os import sys import numpy as np from utils import AverageMeter, calculate_accuracy, save_gif, accuracy from models.binarized_modules import binarizef

36.30625

88

0.484249

289f6d1cb4c2dff400bd79a40abc1c0e080f2635

477

py

Python

contact/views.py

ledomone/kurs_django

c24aaf8f8a22a695b41e2436bf9bf4d1ca665079

[ "MIT" ]

null

contact/views.py

ledomone/kurs_django

c24aaf8f8a22a695b41e2436bf9bf4d1ca665079

[ "MIT" ]

null

contact/views.py

ledomone/kurs_django

c24aaf8f8a22a695b41e2436bf9bf4d1ca665079

[ "MIT" ]

null

from django.contrib.contenttypes import fields from django.shortcuts import render from .forms import MessageForm, ContactForm from django.views.generic import DetailView, ListView, FormView

29.8125

63

0.740042

289fb47f080457beca96ad6fa33ec1f46323cf2b

6,506

py

Python

commands/misc/settings.py

ii-Python/Prism

a404a61ddb16d045aa29d81908ce4ad80b24e24d

[ "MIT" ]

6

2020-09-28T13:19:37.000Z

2021-07-13T10:37:22.000Z

commands/misc/settings.py

BenjaminGotBanned/Prism

a404a61ddb16d045aa29d81908ce4ad80b24e24d

[ "MIT" ]

2

2020-10-06T17:59:40.000Z

2020-10-06T20:12:39.000Z

commands/misc/settings.py

BenjaminGotBanned/Prism

a404a61ddb16d045aa29d81908ce4ad80b24e24d

[ "MIT" ]

3

2021-01-05T13:33:58.000Z

2021-07-13T10:37:37.000Z

# Modules import discord from datetime import date from discord import Embed from json import loads, dumps from assets.prism import Tools from discord.ext import commands # Main Command Class # Link to bot def setup(bot): bot.add_cog(Settings(bot))

29.306306

196

0.527206

28a230764b88abf38e3cb6d2f0cf4df9e3778896

970

py

Python

core/test.py

awesome-archive/muzero-pytorch

2ff4ea145097050031d6026f0aa1a97de72d702d

[ "MIT" ]

null

core/test.py

awesome-archive/muzero-pytorch

2ff4ea145097050031d6026f0aa1a97de72d702d

[ "MIT" ]

null

core/test.py

awesome-archive/muzero-pytorch

2ff4ea145097050031d6026f0aa1a97de72d702d

[ "MIT" ]

null

import torch from .mcts import MCTS, Node from .utils import select_action

31.290323

93

0.565979

28a386192b68f112112b6e68f5293867934e803f

167

py

Python

demo/deep_learning/base/second_stage_bounding_box_prediction/dcn_feature_calibration.py

jihuacao/Putil

b753fc94bea4cbda00f483681c55f0e9f54adef2

[ "Apache-2.0" ]

1

2018-12-09T06:09:29.000Z

demo/deep_learning/base/second_stage_bounding_box_prediction/dcn_feature_calibration.py

jihuacao/Putil

b753fc94bea4cbda00f483681c55f0e9f54adef2

[ "Apache-2.0" ]

null

demo/deep_learning/base/second_stage_bounding_box_prediction/dcn_feature_calibration.py

jihuacao/Putil

b753fc94bea4cbda00f483681c55f0e9f54adef2

[ "Apache-2.0" ]

null

# coding=utf-8 import torch

20.875

60

0.712575

953703edf77bdad68e1e40c1a564d92c76b7a5a5

1,824

pyde

Python

listing_70/listing_70.pyde

tiranderel/2019-fall-polytech-cs

67f0482a0f143381f9b494a4348d6436ce8f8c1e

[ "MIT" ]

null

listing_70/listing_70.pyde

tiranderel/2019-fall-polytech-cs

67f0482a0f143381f9b494a4348d6436ce8f8c1e

[ "MIT" ]

null

listing_70/listing_70.pyde

tiranderel/2019-fall-polytech-cs

67f0482a0f143381f9b494a4348d6436ce8f8c1e

[ "MIT" ]

null

import math ballArray_one=[] ballArray_two=[]

26.057143

75

0.533991

953906e1815512ae7854e463509fe51bfa7374f8

1,340

py

Python

src/carim_discord_bot/discord_client/member_count.py

schana/carim-discord-bot

c1f5e868404744667156af7ad6d244939998b5a2

[ "Apache-2.0" ]

14

2020-04-06T17:58:09.000Z

2022-02-28T13:29:35.000Z

src/carim_discord_bot/discord_client/member_count.py

schana/carim-discord-bot

c1f5e868404744667156af7ad6d244939998b5a2

[ "Apache-2.0" ]

48

2020-04-05T11:24:10.000Z

2021-03-10T08:12:19.000Z

src/carim_discord_bot/discord_client/member_count.py

schana/carim-discord-bot

c1f5e868404744667156af7ad6d244939998b5a2

[ "Apache-2.0" ]

12

2020-03-31T15:08:56.000Z

2021-09-07T17:54:49.000Z

import asyncio import logging import discord from carim_discord_bot import managed_service, config from carim_discord_bot.discord_client import discord_service log = logging.getLogger(__name__) service = None

31.162791

102

0.698507

953acd7416847beb9014f4f513c188884ed30577

567

py

Python

GAPullTest.py

wrashi/GAReport

b58fb1ef8a8984761ba417879aa52c4100c61a0b

[ "Unlicense" ]

null

GAPullTest.py

wrashi/GAReport

b58fb1ef8a8984761ba417879aa52c4100c61a0b

[ "Unlicense" ]

null

GAPullTest.py

wrashi/GAReport

b58fb1ef8a8984761ba417879aa52c4100c61a0b

[ "Unlicense" ]

null

#!/usr/bin/env python3 from GAReport import GAReport VIEW_ID = 'PutViewIDHere' DIMENSIONS = ["Page", ] METRICS = ["Pageviews", "Unique Pageviews", "Avg. Time on Page", "Entrances", "Bounce Rate", "% Exit", "Page Value"] # Use these instructions for creating single and multiple filters: https://developers.google.com/analytics/devguides/reporting/core/v3/reference#filters FILTERS= "ga:pagePath=~news" report = GAReport(startdate="yesterday", enddate="yesterday", viewID=VIEW_ID, dimensions=DIMENSIONS, metrics=METRICS, filters=FILTERS) print(report.df.head(3))

43.615385

153

0.75485

953ca9b5b1450ae6da266d252be6ca5bb7c74e70

14,525

py

Python

model.py

coolEphemeroptera/AESRC2020

b64cdeeaaf74e8c1a741930b3a47dc8dcadca8de

[ "Apache-2.0" ]

35

2020-09-26T13:40:16.000Z

2022-03-22T19:42:20.000Z

model.py

coolEphemeroptera/ARNet

b64cdeeaaf74e8c1a741930b3a47dc8dcadca8de

[ "Apache-2.0" ]

4

2021-04-10T13:05:52.000Z

2022-03-14T03:22:32.000Z

model.py

coolEphemeroptera/ARNet

b64cdeeaaf74e8c1a741930b3a47dc8dcadca8de

[ "Apache-2.0" ]

7

2020-09-26T15:52:45.000Z

2021-06-11T05:05:23.000Z

from resnet import resnet18_,resnet34_,resnet50_,resnet101_, resnet152_ from keras.layers import Input, Dense, Lambda,Dropout,Conv2D,Activation,Bidirectional,GlobalAveragePooling1D,\ BatchNormalization,Reshape from keras_layer_normalization import LayerNormalization from keras.layers.cudnn_recurrent import CuDNNGRU,CuDNNLSTM from keras.models import Model from keras import backend as K from keras.regularizers import l2 from keras.constraints import unit_norm from keras.utils import multi_gpu_model from keras.optimizers import Adam import losses as ls import VLAD as vd """ ========================= Layers ========================= """ """ ========================= ctc constructors ========================= """ """ ========================= NetVLAD ========================= """ """ ========================= AR Module ========================= """ """ ========================= Model ========================= """ """ ====================== OTHER ====================== """ if __name__=="__main__": model,train_model = SAR_Net(input_shape=(1200,80,1), ctc_enable = True, ar_enable = True, disc_enable = True, res_type="res18", res_filters=32, hidden_dim=256, bn_dim=0, bpe_classes=1000, accent_classes=8, max_ctc_len=72, mto='vlad', vlad_clusters=8, ghost_clusters=2, metric_loss='cosface', margin=0.3, raw_model=None, lr=0.01, gpus = 1, name=None) sub_model(model,'x_data','y_accent') model.save_weights('exp/demo.h5') model.load_weights('exp/demo.h5')

34.748804

112

0.497969

953d34fa43582a04419407658a07c6d2cffc68aa

187

py

Python

tests/strategies/__init__.py

lycantropos/rsrc_web

6702840befa4fa70114ce10543144410b453aa30

[ "MIT" ]

null

tests/strategies/__init__.py

lycantropos/rsrc_web

6702840befa4fa70114ce10543144410b453aa30

[ "MIT" ]

4

2019-06-18T18:36:50.000Z

2019-07-10T13:14:48.000Z

tests/strategies/__init__.py

lycantropos/rsrc_web

6702840befa4fa70114ce10543144410b453aa30

[ "MIT" ]

null

from .literals import booleans from .models import (readable_web_streams, web_streams, writeable_web_streams) from .paths import web_url_strings

31.166667

43

0.663102

953d79768caec877a768ca7a6b3a2fc0176266ec

27,309

py

Python

main.py

ruotianluo/neural-summ-cnndm-pytorch

027b63107b748bc56356bd119b243cfdda684aa2

[ "MIT" ]

3

2018-10-22T23:03:40.000Z

2018-10-23T09:45:32.000Z

main.py

ruotianluo/neural-summ-cnndm-pytorch

027b63107b748bc56356bd119b243cfdda684aa2

[ "MIT" ]

null

main.py

ruotianluo/neural-summ-cnndm-pytorch

027b63107b748bc56356bd119b243cfdda684aa2

[ "MIT" ]

null

# -*- coding: utf-8 -*- import os cudaid = 0 os.environ["CUDA_VISIBLE_DEVICES"] = str(cudaid) import sys import time import numpy as np import cPickle as pickle import copy import random from random import shuffle import math import torch import torch.nn as nn from torch.autograd import Variable import data as datar from model import * from utils_pg import * from configs import * cfg = DeepmindConfigs() TRAINING_DATASET_CLS = DeepmindTraining TESTING_DATASET_CLS = DeepmindTesting if __name__ == "__main__": np.set_printoptions(threshold = np.inf) existing_model_name = sys.argv[1] if len(sys.argv) > 1 else None run(existing_model_name)

40.397929

211

0.587462

953e614df603a782bc861b2188ed97f796d8d6d2

471

py

Python

openbook_posts/migrations/0016_auto_20190214_1525.py

TamaraAbells/okuna-api

f87d8e80d2f182c01dbce68155ded0078ee707e4

[ "MIT" ]

164

2019-07-29T17:59:06.000Z

2022-03-19T21:36:01.000Z

openbook_posts/migrations/0016_auto_20190214_1525.py

TamaraAbells/okuna-api

f87d8e80d2f182c01dbce68155ded0078ee707e4

[ "MIT" ]

188

2019-03-16T09:53:25.000Z

2019-07-25T14:57:24.000Z

openbook_posts/migrations/0016_auto_20190214_1525.py

TamaraAbells/okuna-api

f87d8e80d2f182c01dbce68155ded0078ee707e4

[ "MIT" ]

80

2019-08-03T17:49:08.000Z

2022-02-28T16:56:33.000Z

# Generated by Django 2.1.5 on 2019-02-14 14:25 from django.db import migrations import imagekit.models.fields

23.55

108

0.641189

953e8e8b09e196ff5d7362c6a2eeb02c08425111

15,517

py

Python

blackjack.py

hackerboy9/blackjack

1346642e353719ab68c0dc3573aa33b688431bf8

[ "MIT" ]

null

blackjack.py

hackerboy9/blackjack

1346642e353719ab68c0dc3573aa33b688431bf8

[ "MIT" ]

1

2020-10-25T10:16:37.000Z

blackjack.py

hackerboy9/blackjack

1346642e353719ab68c0dc3573aa33b688431bf8

[ "MIT" ]

2

2017-07-16T08:00:29.000Z

2020-10-06T14:48:18.000Z

from collections import MutableMapping, MutableSet, namedtuple from operator import itemgetter NULL = Node(None, None, None, False) from unittest import TestCase

29.783109

82

0.566475

9540c7d295e0a61b349ecd6b4bc768783ff0138e

45,052

py

Python

ixnetwork_restpy/testplatform/sessions/ixnetwork/traffic/trafficitem/configelement/stack/linkOAM_template.py

OpenIxia/ixnetwork_restpy

f628db450573a104f327cf3c737ca25586e067ae

[ "MIT" ]

20

2019-05-07T01:59:14.000Z

2022-02-11T05:24:47.000Z

ixnetwork_restpy/testplatform/sessions/ixnetwork/traffic/trafficitem/configelement/stack/linkOAM_template.py

OpenIxia/ixnetwork_restpy

f628db450573a104f327cf3c737ca25586e067ae

[ "MIT" ]

60

2019-04-03T18:59:35.000Z

2022-02-22T12:05:05.000Z

ixnetwork_restpy/testplatform/sessions/ixnetwork/traffic/trafficitem/configelement/stack/linkOAM_template.py

OpenIxia/ixnetwork_restpy

f628db450573a104f327cf3c737ca25586e067ae

[ "MIT" ]

13

2019-05-20T10:48:31.000Z

2021-10-06T07:45:44.000Z

from ixnetwork_restpy.base import Base from ixnetwork_restpy.files import Files

43.319231

202

0.715551

954146cbdea7e57641fc5a1ec374f381deb7f479

3,967

py

Python

memos/memos/users/forms.py

iotexpert/docmgr

735c7bcbaeb73bc44efecffb175f268f2438ac3a

[ "MIT" ]

null

memos/memos/users/forms.py

iotexpert/docmgr

735c7bcbaeb73bc44efecffb175f268f2438ac3a

[ "MIT" ]

null

memos/memos/users/forms.py

iotexpert/docmgr

735c7bcbaeb73bc44efecffb175f268f2438ac3a

[ "MIT" ]

null

from flask import current_app from flask_wtf import FlaskForm from flask_wtf.file import FileField, FileAllowed from wtforms import StringField, PasswordField, SubmitField, BooleanField from wtforms.validators import DataRequired, Length, Email, EqualTo, ValidationError from flask_login import current_user from memos.models.User import User from memos.models.Memo import Memo from memos.models.MemoFile import MemoFile from memos.models.MemoSignature import MemoSignature

40.896907

98

0.659188

95419b554583bc803a43eac8c57ec34a913022a2

626

py

Python

app/models/encryption.py

janaSunrise/ZeroCOM

7197684ce708f080fe215b0a6e57c12836e4c0ab

[ "Apache-2.0" ]

6

2021-03-27T08:58:04.000Z

2021-05-23T17:07:09.000Z

app/models/encryption.py

janaSunrise/ZeroCOM

7197684ce708f080fe215b0a6e57c12836e4c0ab

[ "Apache-2.0" ]

2

2021-05-30T08:06:53.000Z

2021-06-02T17:02:06.000Z

app/models/encryption.py

janaSunrise/ZeroCOM

7197684ce708f080fe215b0a6e57c12836e4c0ab

[ "Apache-2.0" ]

null

import rsa

31.3

106

0.693291

954332209f4c21416110fe7a318ebf31b6100c2e

3,566

py

Python

Terminal_Bot.py

Data-Alchemy/Unix_Automation

3d5ee450e1b19f79509960f6d117c16fb8aa5313

[ "Apache-2.0" ]

null

Terminal_Bot.py

Data-Alchemy/Unix_Automation

3d5ee450e1b19f79509960f6d117c16fb8aa5313

[ "Apache-2.0" ]

null

Terminal_Bot.py

Data-Alchemy/Unix_Automation

3d5ee450e1b19f79509960f6d117c16fb8aa5313

[ "Apache-2.0" ]

null

import paramiko,time,sys,json,os,pandas ######################################################################################################################## ################################################### parms ############################################################# proxy = None Port = 22 Username = open('').read() #put username in txt file Pwd = open('').read() #put password in txt file Host = '' keys= '' #file with ssh keys sudo_user = '' #optional parameter fill in if using sudo option in function must be passed as full command ie: sudo su - user path = '' download_from = "" download_to = "" ## put commands one line at a time ## listofcommands=f''' ''' ######################################################################################################################## exec_remote_cmds(listofcommands,1,sudo_user)#sudo user is option must by passed as full sudo su - if used #write_file_to_remote(download_from,download_to,1,sudo_user) #download_remote_file(download_to,download_from,1)

37.93617

160

0.615536

95433e555cbe86270b9f0c26744b230b46b56f5a

825

py

Python

pnnl/models/__init__.py

rkini-pnnl/volttron-GS

60055438446a060176381468757ad0ec339f2371

[ "BSD-3-Clause" ]

1

2021-08-05T04:01:55.000Z

pnnl/models/__init__.py

kevinatkinson-pnnl/volttron-GS

479c614a6f7cd779fcc208e8e35d27d0961a16f8

[ "BSD-3-Clause" ]

null

pnnl/models/__init__.py

kevinatkinson-pnnl/volttron-GS

479c614a6f7cd779fcc208e8e35d27d0961a16f8

[ "BSD-3-Clause" ]

null

import importlib import logging from volttron.platform.agent import utils _log = logging.getLogger(__name__) utils.setup_logging() __version__ = "0.1" __all__ = ['Model']

29.464286

73

0.65697

95446537feef632a16bbea1d71d8483703929711

826

py

Python

src/cli.py

thisistrivial/cr-draft

25defcf03466b044c28ad42661536e27b6df1222

[ "MIT" ]

null

src/cli.py

thisistrivial/cr-draft

25defcf03466b044c28ad42661536e27b6df1222

[ "MIT" ]

null

src/cli.py

thisistrivial/cr-draft

25defcf03466b044c28ad42661536e27b6df1222

[ "MIT" ]

null

import draft import os run()

22.944444

69

0.521792

9547e7b57fef282a81e3052edbdb2d34bb2cd61a

222

py

Python

src/honey.py

terror/golf

9d38f8376c2ddbbb34360a3353ec6f4289736bd4

[ "Unlicense" ]

null

src/honey.py

terror/golf

9d38f8376c2ddbbb34360a3353ec6f4289736bd4

[ "Unlicense" ]

null

src/honey.py

terror/golf

9d38f8376c2ddbbb34360a3353ec6f4289736bd4

[ "Unlicense" ]

null

# https://open.kattis.com/problems/honey print(*(lambda x: [x[int(input())] for _ in range(int(input()))])([1, 0, 6, 12, 90, 360, 2040, 10080, 54810, 290640, 1588356, 8676360, 47977776, 266378112, 1488801600]), sep="\n")

55.5

179

0.657658

954b661a558c8d594bb41be0460c68998860e06c

4,712

py

Python

plaso/parsers/winreg_plugins/usbstor.py

Defense-Cyber-Crime-Center/plaso

4f3a85fbea10637c1cdbf0cde9fc539fdcea9c47

[ "Apache-2.0" ]

2

2016-02-18T12:46:29.000Z

2022-03-13T03:04:59.000Z

plaso/parsers/winreg_plugins/usbstor.py

Defense-Cyber-Crime-Center/plaso

4f3a85fbea10637c1cdbf0cde9fc539fdcea9c47

[ "Apache-2.0" ]

null

plaso/parsers/winreg_plugins/usbstor.py

Defense-Cyber-Crime-Center/plaso

4f3a85fbea10637c1cdbf0cde9fc539fdcea9c47

[ "Apache-2.0" ]

6

2016-12-18T08:05:36.000Z

2021-04-06T14:19:11.000Z

# -*- coding: utf-8 -*- """File containing a Windows Registry plugin to parse the USBStor key.""" import logging from plaso.events import windows_events from plaso.lib import eventdata from plaso.parsers import winreg from plaso.parsers.winreg_plugins import interface __author__ = 'David Nides (david.nides@gmail.com)' winreg.WinRegistryParser.RegisterPlugin(USBStorPlugin)

39.266667

79

0.695034

9550103d22b0d4fa16de9bf491fa914c8ddf64fb

4,877

py

Python

musicbot/modules/default/helpmsg.py

oKidd/PrendeMusic

b66d54d93ed36587193c20b71201c4447d80ad85

[ "MIT" ]

5

2018-09-07T12:17:27.000Z

2019-12-06T02:35:26.000Z

musicbot/modules/default/helpmsg.py

oKidd/PrendeMusic

b66d54d93ed36587193c20b71201c4447d80ad85

[ "MIT" ]

null

musicbot/modules/default/helpmsg.py

oKidd/PrendeMusic

b66d54d93ed36587193c20b71201c4447d80ad85

[ "MIT" ]

2

2020-04-25T00:35:17.000Z

2021-05-13T22:20:19.000Z

from collections import defaultdict from discord.ext.commands import Cog, command from discord.utils import get from ...utils import check_restricted from ... import exceptions from ... import messagemanager cogs = [Help]

44.743119

204

0.568792

95515f6c6551928915064695c2fceeeba21d268c

8,710

py

Python

flatpak_update.py

willsALMANJ/flatpak_update

84a8f59a11952a5daf57a18f0426b676f3a707c2

[ "0BSD" ]

1

2020-06-12T07:51:32.000Z

flatpak_update.py

willsALMANJ/flatpak_update

84a8f59a11952a5daf57a18f0426b676f3a707c2

[ "0BSD" ]

null

flatpak_update.py

willsALMANJ/flatpak_update

84a8f59a11952a5daf57a18f0426b676f3a707c2

[ "0BSD" ]

null

"Update a Flatpak repository for new versions of components" import argparse import asyncio import datetime from functools import total_ordering import hashlib from itertools import zip_longest import json from pathlib import Path import re import httpx import jinja2 import yaml GITHUB_DATE_FORMAT = "%Y-%m-%dT%H:%M:%SZ" async def get_version_scrape(spec): "Scrape raw HTML for version string regex to find latest version" matches = re.findall(spec["regex"], response.text) version = max(Version(m) for m in matches) return version def load_manifest(path): "Load json or yaml file" with path.open("r") as file_: if path.suffix == ".json": manifest = json.load(file_) else: manifest = yaml.load(file_, Loader=yaml.SafeLoader) return manifest def get_current_versions(manifest): "Parse versions from current Flatpak manifest" versions = {"runtime": Version(manifest["runtime-version"])} for module in manifest["modules"]: match = re.search(r"-([0-9\.]+)\.tar\.gz$", module["sources"][0]["url"]) versions[module["name"]] = Version(match.group(1)) return versions def get_template_vars(config, current_versions, new_versions, manifest): "Build up variables for jinja2 templates from version data" env = {} remote_sha256 = {} env["runtime_version"] = new_versions["runtime"] for spec in config["modules"]: name = spec["name"] env[f"{name}_version"] = new_versions[name] env[f"{name}_source_url"] = spec["source_url"].format( version=new_versions[name] ) env[f"{name}_version_date"] = new_versions[name].date if new_versions[name] > current_versions[name]: remote_sha256[name] = env[f"{name}_source_url"] else: for mod in manifest["modules"]: if mod["name"] == name: env[f"{name}_sha256"] = mod["sources"][0]["sha256"] new_sha256 = asyncio.run(get_sha256_set(remote_sha256)) env.update(**new_sha256) return env def render_templates(template_dir, env): "Render a .j2 templates using collected version information" for path in template_dir.glob("*.j2"): with path.open("r") as file_: template = jinja2.Template(file_.read()) with path.with_name(path.stem).open("w") as file_: file_.write(template.render(**env)) def parse_args(): "Parse command line arguments" parser = argparse.ArgumentParser() parser.add_argument("--config", "-c", required=True, help="Configuration file") parser.add_argument( "--manifest", "-m", required=True, help="Current flatpak manifest" ) parser.add_argument( "--template-dir", "-t", help="Directory with .j2 files to render" ) return parser.parse_args() def main(): "Main logic" args = parse_args() with open(args.config) as file_: config = yaml.load(file_, Loader=yaml.SafeLoader) new_versions = asyncio.run( get_latest_versions([config["runtime"]] + config["modules"]) ) manifest = load_manifest(Path(args.manifest)) current_versions = get_current_versions(manifest) env = get_template_vars(config, current_versions, new_versions, manifest) render_templates(Path(args.template_dir), env) if __name__ == "__main__": main()

30.138408

83

0.62721

955231e63fbff36ad8601f161f98440ad3a247cb

1,746

py

Python

base/env/test_processStrategy.py

stevenchen521/quant_ml

f7d5efc49c934724f97fcafacc560f4a35b24551

[ "MIT" ]

5

2019-02-14T03:12:22.000Z

2022-01-24T18:43:07.000Z

base/env/test_processStrategy.py

stevenchen521/quant_ml

f7d5efc49c934724f97fcafacc560f4a35b24551

[ "MIT" ]

null

base/env/test_processStrategy.py

stevenchen521/quant_ml

f7d5efc49c934724f97fcafacc560f4a35b24551

[ "MIT" ]

2

2019-11-13T18:56:13.000Z

2021-12-31T01:25:22.000Z

from unittest import TestCase import base.env.pre_process as pre_process import pandas as pd from sklearn.preprocessing import MinMaxScaler from helper.util import get_attribute from base.env.pre_process_conf import active_stragery, get_strategy_analyze import base.env.pre_process

38.8

143

0.708477

9552f2a3d627a440738e08b8175d69d9667e0003

12,194

py

Python

resources/lib/themoviedb/tmdb.py

bopopescu/ServerStatus

a883598248ad6f5273eb3be498e3b04a1fab6510

[ "MIT" ]

null

resources/lib/themoviedb/tmdb.py

bopopescu/ServerStatus

a883598248ad6f5273eb3be498e3b04a1fab6510

[ "MIT" ]

1

2015-04-21T22:05:02.000Z

2015-04-22T22:27:15.000Z

resources/lib/themoviedb/tmdb.py

GetSomeBlocks/Score_Soccer

a883598248ad6f5273eb3be498e3b04a1fab6510

[ "MIT" ]

2

2015-09-29T16:31:43.000Z

2020-07-26T03:41:10.000Z

#!/usr/bin/env python2.5 #encoding:utf-8 #author:dbr/Ben #project:themoviedb #forked by ccjensen/Chris #http://github.com/ccjensen/themoviedb """An interface to the themoviedb.org API """ __author__ = "dbr/Ben" __version__ = "0.2b" config = {} config['apikey'] = "a8b9f96dde091408a03cb4c78477bd14" config['urls'] = {} config['urls']['movie.search'] = "http://api.themoviedb.org/2.1/Movie.search/en/xml/%(apikey)s/%%s" % (config) config['urls']['movie.getInfo'] = "http://api.themoviedb.org/2.1/Movie.getInfo/en/xml/%(apikey)s/%%s" % (config) import urllib try: import xml.etree.cElementTree as ElementTree except ImportError: import elementtree.ElementTree as ElementTree # collections.defaultdict # originally contributed by Yoav Goldberg <yoav.goldberg@gmail.com> # new version by Jason Kirtland from Python cookbook. # <http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/523034> try: from collections import defaultdict except ImportError: # [XX] to make pickle happy in python 2.4: import collections collections.defaultdict = defaultdict def search(name = None): """Convenience wrapper for MovieDb.search - so you can do.. >>> import tmdb >>> tmdb.search("Fight Club") <Search results: [<MovieResult: Fight Club (1999-09-16)>]> """ mdb = MovieDb() return mdb.search(name) def getMovieInfo(id = None): """Convenience wrapper for MovieDb.search - so you can do.. >>> import tmdb >>> tmdb.getMovieInfo(187) <MovieResult: Sin City (2005-04-01)> """ mdb = MovieDb() return mdb.getMovieInfo(id) def main(): results = search("Fight Club") searchResult = results[0] movie = getMovieInfo(searchResult['id']) print movie['name'] print "Producers:" for prodr in movie['cast']['Producer']: print " " * 4, prodr['name'] print movie['images'] for genreName in movie['categories']['genre']: print "%s (%s)" % (genreName, movie['categories']['genre'][genreName]) if __name__ == '__main__': main()

33.31694

142

0.586354

955351f42a772eb848c0ae2b75d5d28ba1ff2a00

3,033

py

Python

mir3/lib/knn.py

pymir3/pymir3

c1bcca66a5ef1ff0ebd6373e3820e72dee6b0b70

[ "MIT" ]

12

2015-08-03T12:41:11.000Z

2020-08-18T07:55:23.000Z

mir3/lib/knn.py

pymir3/pymir3

c1bcca66a5ef1ff0ebd6373e3820e72dee6b0b70

[ "MIT" ]

1

2015-05-27T18:47:20.000Z

mir3/lib/knn.py

pymir3/pymir3

c1bcca66a5ef1ff0ebd6373e3820e72dee6b0b70

[ "MIT" ]

3

2016-03-18T03:30:02.000Z

2018-07-05T02:29:16.000Z

import numpy import numpy.linalg def distance_sum(inputs, references): """Sum of all distances between inputs and references Each element should be in a row! """ norms = numpy.zeros(inputs.shape[0]) for i in xrange(references.shape[0]): norms += numpy.apply_along_axis(numpy.linalg.norm, 1, inputs-references[i,:]) return norms def distance_min(inputs, references): """Minimum distances between inputs and any reference Each element should be in a row! """ norms = numpy.ones(inputs.shape[0])*99999999 for i in xrange(references.shape[0]): norms = numpy.minimum(norms, numpy.apply_along_axis(numpy.linalg.norm, 1, inputs-references[i,:])) return norms def distance_matrix(inputs): """Returns a distance matrix """ D = numpy.ones( (inputs.shape[0], inputs.shape[0]) )*99999999 for i in xrange(inputs.shape[0]): for j in xrange(i): D[i,j] = numpy.linalg.norm(inputs[i,:]-inputs[j,:]) D[j,i] = numpy.linalg.norm(inputs[i,:]-inputs[j,:]) return D def distance_mutual_min(inputs, references): """Distance using a mutual distance reference Inspired in: USING MUTUAL PROXIMITY TO IMPROVE CONTENT-BASED AUDIO SIMILARITY Dominik Schnitzer, Arthur Flexer, Markus Sched, Gerhard Widmer """ d = distance_matrix(inputs) a = distance_min(inputs, references) for i in xrange(len(a)): a[i] = a[i] - numpy.min(d[:,i]) return a def range_distance(inputs, references): """Minimum distance from boundaries of a rang """ mi = numpy.amin(references, 0) ma = numpy.amax(references, 0) norms = numpy.zeros(inputs.shape[0]) for i in xrange(inputs.shape[0]): for j in xrange(inputs.shape[1]): if (inputs[i,j] < mi[j]) or \ (inputs[i,j] > ma[j]): norms[i] += numpy.min([abs(inputs[i,j]-mi[j]),\ abs(inputs[i,j]-ma[j])])**2 norms[i] = norms[i]**(0.5) return norms def mutual_range_distance(inputs, references): """Minimum distance from boundaries of a range """ mi = numpy.amin(references, 0) ma = numpy.amax(references, 0) norms = numpy.zeros(inputs.shape[0]) d = distance_matrix(inputs) for i in xrange(inputs.shape[0]): for j in xrange(inputs.shape[1]): if (inputs[i,j] < mi[j]) or \ (inputs[i,j] > ma[j]): norms[i] += numpy.min([abs(inputs[i,j]-mi[j]),\ abs(inputs[i,j]-ma[j])])**2 norms[i] = norms[i]**(0.5) norms[i] = norms[i] - numpy.min(d[:,i]) return norms #a = numpy.array([[2, 4, 6], [4, 3, 2], [5, -2, -1], [10, 11, 12], [15, 20, 31]]) #b = numpy.array([[10, 11, 12], [-1, -2, -3]]) #print distance_sum(a, b) #print a #print b #print distance_min(a, b) #print distance_mutual_min(a, b)

31.59375

81

0.567755

9553b680206d84c135ef2d6c3b9397a51e5c12a9

17,984

py

Python

pysnmp/CABH-QOS2-MIB.py

agustinhenze/mibs.snmplabs.com

1fc5c07860542b89212f4c8ab807057d9a9206c7

[ "Apache-2.0" ]

11

2021-02-02T16:27:16.000Z

2021-08-31T06:22:49.000Z

pysnmp/CABH-QOS2-MIB.py

agustinhenze/mibs.snmplabs.com

1fc5c07860542b89212f4c8ab807057d9a9206c7

[ "Apache-2.0" ]

75

2021-02-24T17:30:31.000Z

2021-12-08T00:01:18.000Z

pysnmp/CABH-QOS2-MIB.py

agustinhenze/mibs.snmplabs.com

1fc5c07860542b89212f4c8ab807057d9a9206c7

[ "Apache-2.0" ]

10

2019-04-30T05:51:36.000Z

2022-02-16T03:33:41.000Z

# # PySNMP MIB module CABH-QOS2-MIB (http://snmplabs.com/pysmi) # ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/CABH-QOS2-MIB # Produced by pysmi-0.3.4 at Mon Apr 29 17:26:31 2019 # On host DAVWANG4-M-1475 platform Darwin version 18.5.0 by user davwang4 # Using Python version 3.7.3 (default, Mar 27 2019, 09:23:15) # ObjectIdentifier, OctetString, Integer = mibBuilder.importSymbols("ASN1", "ObjectIdentifier", "OctetString", "Integer") NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues") ConstraintsUnion, ValueRangeConstraint, ValueSizeConstraint, ConstraintsIntersection, SingleValueConstraint = mibBuilder.importSymbols("ASN1-REFINEMENT", "ConstraintsUnion", "ValueRangeConstraint", "ValueSizeConstraint", "ConstraintsIntersection", "SingleValueConstraint") clabProjCableHome, = mibBuilder.importSymbols("CLAB-DEF-MIB", "clabProjCableHome") ifIndex, = mibBuilder.importSymbols("IF-MIB", "ifIndex") InetAddress, InetAddressType, InetPortNumber = mibBuilder.importSymbols("INET-ADDRESS-MIB", "InetAddress", "InetAddressType", "InetPortNumber") SnmpAdminString, = mibBuilder.importSymbols("SNMP-FRAMEWORK-MIB", "SnmpAdminString") ObjectGroup, ModuleCompliance, NotificationGroup = mibBuilder.importSymbols("SNMPv2-CONF", "ObjectGroup", "ModuleCompliance", "NotificationGroup") MibIdentifier, iso, Bits, TimeTicks, MibScalar, MibTable, MibTableRow, MibTableColumn, Counter64, NotificationType, Integer32, Counter32, Gauge32, Unsigned32, ObjectIdentity, ModuleIdentity, IpAddress = mibBuilder.importSymbols("SNMPv2-SMI", "MibIdentifier", "iso", "Bits", "TimeTicks", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "Counter64", "NotificationType", "Integer32", "Counter32", "Gauge32", "Unsigned32", "ObjectIdentity", "ModuleIdentity", "IpAddress") RowStatus, TextualConvention, DisplayString, TimeStamp, TruthValue = mibBuilder.importSymbols("SNMPv2-TC", "RowStatus", "TextualConvention", "DisplayString", "TimeStamp", "TruthValue") cabhQos2Mib = ModuleIdentity((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8)) cabhQos2Mib.setRevisions(('2005-04-08 00:00',)) if mibBuilder.loadTexts: cabhQos2Mib.setLastUpdated('200504080000Z') if mibBuilder.loadTexts: cabhQos2Mib.setOrganization('CableLabs Broadband Access Department') cabhQos2Mib2Notifications = MibIdentifier((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 0)) cabhQos2MibObjects = MibIdentifier((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1)) cabhQos2Base = MibIdentifier((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 1)) cabhQos2PsIfAttributes = MibIdentifier((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 2)) cabhQos2PolicyHolderObjects = MibIdentifier((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3)) cabhQos2DeviceObjects = MibIdentifier((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 4)) cabhQos2SetToFactory = MibScalar((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 1, 1), TruthValue()).setMaxAccess("readwrite") if mibBuilder.loadTexts: cabhQos2SetToFactory.setStatus('current') cabhQos2LastSetToFactory = MibScalar((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 1, 2), TimeStamp()).setMaxAccess("readonly") if mibBuilder.loadTexts: cabhQos2LastSetToFactory.setStatus('current') cabhQos2PsIfAttribTable = MibTable((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 2, 1), ) if mibBuilder.loadTexts: cabhQos2PsIfAttribTable.setStatus('current') cabhQos2PsIfAttribEntry = MibTableRow((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 2, 1, 1), ).setIndexNames((0, "IF-MIB", "ifIndex")) if mibBuilder.loadTexts: cabhQos2PsIfAttribEntry.setStatus('current') cabhQos2PsIfAttribNumPriorities = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 2, 1, 1, 1), Unsigned32().subtype(subtypeSpec=ValueRangeConstraint(1, 8))).setMaxAccess("readonly") if mibBuilder.loadTexts: cabhQos2PsIfAttribNumPriorities.setStatus('current') cabhQos2PsIfAttribNumQueues = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 2, 1, 1, 2), Unsigned32().subtype(subtypeSpec=ValueRangeConstraint(1, 8))).setMaxAccess("readonly") if mibBuilder.loadTexts: cabhQos2PsIfAttribNumQueues.setStatus('current') cabhQos2PolicyHolderEnabled = MibScalar((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 1), TruthValue().clone('true')).setMaxAccess("readwrite") if mibBuilder.loadTexts: cabhQos2PolicyHolderEnabled.setStatus('current') cabhQos2PolicyAdmissionControl = MibScalar((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 2), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("enabled", 1), ("disabled", 2))).clone('disabled')).setMaxAccess("readwrite") if mibBuilder.loadTexts: cabhQos2PolicyAdmissionControl.setStatus('current') cabhQos2NumActivePolicyHolder = MibScalar((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 3), Gauge32().subtype(subtypeSpec=ValueRangeConstraint(0, 4294967295))).setMaxAccess("readonly") if mibBuilder.loadTexts: cabhQos2NumActivePolicyHolder.setStatus('current') cabhQos2PolicyTable = MibTable((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 4), ) if mibBuilder.loadTexts: cabhQos2PolicyTable.setStatus('current') cabhQos2PolicyEntry = MibTableRow((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 4, 1), ).setIndexNames((0, "CABH-QOS2-MIB", "cabhQos2PolicyOwner"), (0, "CABH-QOS2-MIB", "cabhQos2PolicyOwnerRuleId")) if mibBuilder.loadTexts: cabhQos2PolicyEntry.setStatus('current') cabhQos2PolicyOwner = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 4, 1, 1), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4))).clone(namedValues=NamedValues(("operatorOnly", 1), ("homeUser", 2), ("operatorForHomeUser", 3), ("upnp", 4)))) if mibBuilder.loadTexts: cabhQos2PolicyOwner.setStatus('current') cabhQos2PolicyOwnerRuleId = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 4, 1, 2), Unsigned32().subtype(subtypeSpec=ValueRangeConstraint(1, 4294967295))) if mibBuilder.loadTexts: cabhQos2PolicyOwnerRuleId.setStatus('current') cabhQos2PolicyRuleOrder = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 4, 1, 3), Unsigned32().subtype(subtypeSpec=ValueRangeConstraint(0, 4294967295))).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2PolicyRuleOrder.setStatus('current') cabhQos2PolicyAppDomain = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 4, 1, 4), SnmpAdminString().subtype(subtypeSpec=ValueSizeConstraint(0, 32))).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2PolicyAppDomain.setStatus('current') cabhQos2PolicyAppName = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 4, 1, 5), SnmpAdminString().subtype(subtypeSpec=ValueSizeConstraint(0, 32))).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2PolicyAppName.setStatus('current') cabhQos2PolicyServiceProvDomain = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 4, 1, 6), SnmpAdminString().subtype(subtypeSpec=ValueSizeConstraint(0, 32))).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2PolicyServiceProvDomain.setStatus('current') cabhQos2PolicyServiceName = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 4, 1, 7), SnmpAdminString().subtype(subtypeSpec=ValueSizeConstraint(0, 32))).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2PolicyServiceName.setStatus('current') cabhQos2PolicyPortDomain = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 4, 1, 8), SnmpAdminString().subtype(subtypeSpec=ValueSizeConstraint(0, 32))).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2PolicyPortDomain.setStatus('current') cabhQos2PolicyPortNumber = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 4, 1, 9), InetPortNumber()).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2PolicyPortNumber.setStatus('current') cabhQos2PolicyIpType = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 4, 1, 10), InetAddressType().clone('ipv4')).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2PolicyIpType.setStatus('current') cabhQos2PolicyIpProtocol = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 4, 1, 11), Unsigned32().subtype(subtypeSpec=ValueRangeConstraint(0, 255))).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2PolicyIpProtocol.setStatus('current') cabhQos2PolicySrcIp = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 4, 1, 12), InetAddress().clone(hexValue="00000000")).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2PolicySrcIp.setStatus('current') cabhQos2PolicyDestIp = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 4, 1, 13), InetAddress().clone(hexValue="00000000")).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2PolicyDestIp.setStatus('current') cabhQos2PolicySrcPort = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 4, 1, 14), InetPortNumber()).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2PolicySrcPort.setStatus('current') cabhQos2PolicyDestPort = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 4, 1, 15), InetPortNumber()).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2PolicyDestPort.setStatus('current') cabhQos2PolicyTraffImpNum = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 4, 1, 16), Unsigned32().subtype(subtypeSpec=ValueRangeConstraint(0, 7))).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2PolicyTraffImpNum.setStatus('current') cabhQos2PolicyUserImportance = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 4, 1, 17), Unsigned32().subtype(subtypeSpec=ValueRangeConstraint(0, 255))).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2PolicyUserImportance.setStatus('current') cabhQos2PolicyRowStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 3, 4, 1, 18), RowStatus()).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2PolicyRowStatus.setStatus('current') cabhQos2TrafficClassTable = MibTable((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 4, 1), ) if mibBuilder.loadTexts: cabhQos2TrafficClassTable.setStatus('current') cabhQos2TrafficClassEntry = MibTableRow((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 4, 1, 1), ).setIndexNames((0, "CABH-QOS2-MIB", "cabhQos2TrafficClassMethod"), (0, "CABH-QOS2-MIB", "cabhQos2TrafficClassIdx")) if mibBuilder.loadTexts: cabhQos2TrafficClassEntry.setStatus('current') cabhQos2TrafficClassMethod = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 4, 1, 1, 1), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("static", 1), ("upnp", 2)))) if mibBuilder.loadTexts: cabhQos2TrafficClassMethod.setStatus('current') cabhQos2TrafficClassIdx = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 4, 1, 1, 2), Unsigned32().subtype(subtypeSpec=ValueRangeConstraint(1, 4294967295))) if mibBuilder.loadTexts: cabhQos2TrafficClassIdx.setStatus('current') cabhQos2TrafficClassProtocol = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 4, 1, 1, 3), Unsigned32().subtype(subtypeSpec=ValueRangeConstraint(0, 256))).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2TrafficClassProtocol.setStatus('current') cabhQos2TrafficClassIpType = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 4, 1, 1, 4), InetAddressType().clone('ipv4')).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2TrafficClassIpType.setStatus('current') cabhQos2TrafficClassSrcIp = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 4, 1, 1, 5), InetAddress().clone(hexValue="00000000")).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2TrafficClassSrcIp.setStatus('current') cabhQos2TrafficClassDestIp = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 4, 1, 1, 6), InetAddress().clone(hexValue="00000000")).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2TrafficClassDestIp.setStatus('current') cabhQos2TrafficClassSrcPort = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 4, 1, 1, 7), InetPortNumber()).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2TrafficClassSrcPort.setStatus('current') cabhQos2TrafficClassDestPort = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 4, 1, 1, 8), InetPortNumber()).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2TrafficClassDestPort.setStatus('current') cabhQos2TrafficClassImpNum = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 4, 1, 1, 9), Unsigned32().subtype(subtypeSpec=ValueRangeConstraint(0, 7))).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2TrafficClassImpNum.setStatus('current') cabhQos2TrafficClassRowStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 1, 4, 1, 1, 10), RowStatus()).setMaxAccess("readcreate") if mibBuilder.loadTexts: cabhQos2TrafficClassRowStatus.setStatus('current') cabhQos2Conformance = MibIdentifier((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 2)) cabhQos2Compliances = MibIdentifier((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 2, 1)) cabhQos2Groups = MibIdentifier((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 2, 2)) cabhQos2Compliance = ModuleCompliance((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 2, 1, 1)).setObjects(("CABH-QOS2-MIB", "cabhQos2Group"), ("CABH-QOS2-MIB", "cabhQos2ClassifierGroup")) if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0): cabhQos2Compliance = cabhQos2Compliance.setStatus('current') cabhQos2Group = ObjectGroup((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 2, 2, 1)).setObjects(("CABH-QOS2-MIB", "cabhQos2SetToFactory"), ("CABH-QOS2-MIB", "cabhQos2LastSetToFactory"), ("CABH-QOS2-MIB", "cabhQos2PsIfAttribNumPriorities"), ("CABH-QOS2-MIB", "cabhQos2PsIfAttribNumQueues"), ("CABH-QOS2-MIB", "cabhQos2PolicyHolderEnabled"), ("CABH-QOS2-MIB", "cabhQos2PolicyAdmissionControl"), ("CABH-QOS2-MIB", "cabhQos2NumActivePolicyHolder"), ("CABH-QOS2-MIB", "cabhQos2PolicyRuleOrder"), ("CABH-QOS2-MIB", "cabhQos2PolicyAppDomain"), ("CABH-QOS2-MIB", "cabhQos2PolicyAppName"), ("CABH-QOS2-MIB", "cabhQos2PolicyServiceProvDomain"), ("CABH-QOS2-MIB", "cabhQos2PolicyServiceName"), ("CABH-QOS2-MIB", "cabhQos2PolicyPortDomain"), ("CABH-QOS2-MIB", "cabhQos2PolicyPortNumber"), ("CABH-QOS2-MIB", "cabhQos2PolicyIpProtocol"), ("CABH-QOS2-MIB", "cabhQos2PolicyIpType"), ("CABH-QOS2-MIB", "cabhQos2PolicySrcIp"), ("CABH-QOS2-MIB", "cabhQos2PolicyDestIp"), ("CABH-QOS2-MIB", "cabhQos2PolicySrcPort"), ("CABH-QOS2-MIB", "cabhQos2PolicyDestPort"), ("CABH-QOS2-MIB", "cabhQos2PolicyTraffImpNum"), ("CABH-QOS2-MIB", "cabhQos2PolicyUserImportance"), ("CABH-QOS2-MIB", "cabhQos2PolicyRowStatus"), ("CABH-QOS2-MIB", "cabhQos2TrafficClassProtocol"), ("CABH-QOS2-MIB", "cabhQos2TrafficClassIpType"), ("CABH-QOS2-MIB", "cabhQos2PolicySrcIp"), ("CABH-QOS2-MIB", "cabhQos2PolicyDestIp"), ("CABH-QOS2-MIB", "cabhQos2PolicySrcPort"), ("CABH-QOS2-MIB", "cabhQos2PolicyDestPort"), ("CABH-QOS2-MIB", "cabhQos2PolicyTraffImpNum"), ("CABH-QOS2-MIB", "cabhQos2PolicyUserImportance"), ("CABH-QOS2-MIB", "cabhQos2PolicyRowStatus")) if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0): cabhQos2Group = cabhQos2Group.setStatus('current') cabhQos2ClassifierGroup = ObjectGroup((1, 3, 6, 1, 4, 1, 4491, 2, 4, 8, 2, 2, 2)).setObjects(("CABH-QOS2-MIB", "cabhQos2TrafficClassProtocol"), ("CABH-QOS2-MIB", "cabhQos2TrafficClassIpType"), ("CABH-QOS2-MIB", "cabhQos2TrafficClassSrcIp"), ("CABH-QOS2-MIB", "cabhQos2TrafficClassDestIp"), ("CABH-QOS2-MIB", "cabhQos2TrafficClassSrcPort"), ("CABH-QOS2-MIB", "cabhQos2TrafficClassDestPort"), ("CABH-QOS2-MIB", "cabhQos2TrafficClassImpNum"), ("CABH-QOS2-MIB", "cabhQos2TrafficClassRowStatus")) if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0): cabhQos2ClassifierGroup = cabhQos2ClassifierGroup.setStatus('current') mibBuilder.exportSymbols("CABH-QOS2-MIB", cabhQos2PolicyAppName=cabhQos2PolicyAppName, cabhQos2PolicyEntry=cabhQos2PolicyEntry, cabhQos2TrafficClassProtocol=cabhQos2TrafficClassProtocol, cabhQos2TrafficClassRowStatus=cabhQos2TrafficClassRowStatus, cabhQos2SetToFactory=cabhQos2SetToFactory, cabhQos2Mib2Notifications=cabhQos2Mib2Notifications, cabhQos2PsIfAttribEntry=cabhQos2PsIfAttribEntry, cabhQos2PsIfAttribNumQueues=cabhQos2PsIfAttribNumQueues, cabhQos2PolicyHolderEnabled=cabhQos2PolicyHolderEnabled, cabhQos2PolicyIpProtocol=cabhQos2PolicyIpProtocol, PYSNMP_MODULE_ID=cabhQos2Mib, cabhQos2DeviceObjects=cabhQos2DeviceObjects, cabhQos2PolicyPortNumber=cabhQos2PolicyPortNumber, cabhQos2PolicyOwnerRuleId=cabhQos2PolicyOwnerRuleId, cabhQos2PsIfAttribTable=cabhQos2PsIfAttribTable, cabhQos2LastSetToFactory=cabhQos2LastSetToFactory, cabhQos2MibObjects=cabhQos2MibObjects, cabhQos2PsIfAttributes=cabhQos2PsIfAttributes, cabhQos2PolicyDestIp=cabhQos2PolicyDestIp, cabhQos2PolicyDestPort=cabhQos2PolicyDestPort, cabhQos2Compliances=cabhQos2Compliances, cabhQos2TrafficClassSrcPort=cabhQos2TrafficClassSrcPort, cabhQos2PolicyTraffImpNum=cabhQos2PolicyTraffImpNum, cabhQos2Conformance=cabhQos2Conformance, cabhQos2ClassifierGroup=cabhQos2ClassifierGroup, cabhQos2TrafficClassDestIp=cabhQos2TrafficClassDestIp, cabhQos2TrafficClassDestPort=cabhQos2TrafficClassDestPort, cabhQos2PolicyRowStatus=cabhQos2PolicyRowStatus, cabhQos2PolicySrcIp=cabhQos2PolicySrcIp, cabhQos2TrafficClassSrcIp=cabhQos2TrafficClassSrcIp, cabhQos2TrafficClassMethod=cabhQos2TrafficClassMethod, cabhQos2PolicySrcPort=cabhQos2PolicySrcPort, cabhQos2PolicyServiceName=cabhQos2PolicyServiceName, cabhQos2NumActivePolicyHolder=cabhQos2NumActivePolicyHolder, cabhQos2PolicyUserImportance=cabhQos2PolicyUserImportance, cabhQos2Compliance=cabhQos2Compliance, cabhQos2PsIfAttribNumPriorities=cabhQos2PsIfAttribNumPriorities, cabhQos2TrafficClassImpNum=cabhQos2TrafficClassImpNum, cabhQos2PolicyAdmissionControl=cabhQos2PolicyAdmissionControl, cabhQos2PolicyRuleOrder=cabhQos2PolicyRuleOrder, cabhQos2PolicyServiceProvDomain=cabhQos2PolicyServiceProvDomain, cabhQos2PolicyOwner=cabhQos2PolicyOwner, cabhQos2Groups=cabhQos2Groups, cabhQos2PolicyTable=cabhQos2PolicyTable, cabhQos2PolicyAppDomain=cabhQos2PolicyAppDomain, cabhQos2PolicyIpType=cabhQos2PolicyIpType, cabhQos2TrafficClassTable=cabhQos2TrafficClassTable, cabhQos2PolicyPortDomain=cabhQos2PolicyPortDomain, cabhQos2Mib=cabhQos2Mib, cabhQos2TrafficClassEntry=cabhQos2TrafficClassEntry, cabhQos2Group=cabhQos2Group, cabhQos2PolicyHolderObjects=cabhQos2PolicyHolderObjects, cabhQos2TrafficClassIpType=cabhQos2TrafficClassIpType, cabhQos2Base=cabhQos2Base, cabhQos2TrafficClassIdx=cabhQos2TrafficClassIdx)

145.032258

2,723

0.769462

9554b36b01a4be87039a97f47f4d8ef14a97ffe2

2,440

py

Python

nasafree/views.py

luanmalaquias/projeto_api_nasa_django

3441c404da821b4177571814014e89b0cff6a6b7

[ "MIT" ]

null

nasafree/views.py

luanmalaquias/projeto_api_nasa_django

3441c404da821b4177571814014e89b0cff6a6b7

[ "MIT" ]

null

nasafree/views.py

luanmalaquias/projeto_api_nasa_django

3441c404da821b4177571814014e89b0cff6a6b7

[ "MIT" ]

null

from django.shortcuts import redirect, render from .models import * from datetime import date from brain import ipfunc

34.366197

93

0.685246

9554dabbb9a81e2fbde331f2e40edcaa0f221585

805

py

Python

bslparloursite/videolibrary/models.py

natfarleydev/thebslparlour

ebb2588282cdb2a977ec6c5f8d82cec4e8fd1f99

[ "CC0-1.0" ]

1

2016-01-06T23:13:11.000Z

bslparloursite/videolibrary/models.py

natfarleydev/thebslparlour

ebb2588282cdb2a977ec6c5f8d82cec4e8fd1f99

[ "CC0-1.0" ]

4

2021-03-18T20:15:04.000Z

2021-06-10T17:52:31.000Z

bslparloursite/videolibrary/models.py

natfarleydev/thebslparlour

ebb2588282cdb2a977ec6c5f8d82cec4e8fd1f99

[ "CC0-1.0" ]

null

from django.db import models from django.utils import timezone from sizefield.models import FileSizeField # Create your models here.

29.814815

75

0.720497

9554ef14a15f7437ba6f8f9a2cf1620b9d8dfb4c

1,681

py

Python

location.py

TED-996/Nightshift

3cc76af96c8e85e913be8c2f8f70564ea9d9f95d

[ "MIT" ]

null

location.py

TED-996/Nightshift

3cc76af96c8e85e913be8c2f8f70564ea9d9f95d

[ "MIT" ]

null

location.py

TED-996/Nightshift

3cc76af96c8e85e913be8c2f8f70564ea9d9f95d

[ "MIT" ]

null

import os.path import json from astral import Astral appdata_folder = os.path.join(os.environ["LOCALAPPDATA"], "Nightshift")

28.982759

75

0.625223

95583195ca817a2531ead6462fb4ef3915b9a847

12,140

py

Python

src/awkward1/operations/reducers.py

martindurant/awkward-1.0

a3221ee1bab6551dd01d5dd07a1d2dc24fd02c38

[ "BSD-3-Clause" ]

null

src/awkward1/operations/reducers.py

martindurant/awkward-1.0

a3221ee1bab6551dd01d5dd07a1d2dc24fd02c38

[ "BSD-3-Clause" ]

null

src/awkward1/operations/reducers.py

martindurant/awkward-1.0

a3221ee1bab6551dd01d5dd07a1d2dc24fd02c38

[ "BSD-3-Clause" ]

null

# BSD 3-Clause License; see https://github.com/jpivarski/awkward-1.0/blob/master/LICENSE from __future__ import absolute_import import numpy import awkward1._util import awkward1._connect._numpy import awkward1.layout import awkward1.operations.convert ### The following are not strictly reducers, but are defined in terms of reducers and ufuncs. def moment(x, n, weight=None, axis=None, keepdims=False): with numpy.errstate(invalid="ignore"): if weight is None: sumw = count(x, axis=axis, keepdims=keepdims) sumwxn = sum(x**n, axis=axis, keepdims=keepdims) else: sumw = sum(x*0 + weight, axis=axis, keepdims=keepdims) sumwxn = sum((x*weight)**n, axis=axis, keepdims=keepdims) return numpy.true_divide(sumwxn, sumw) def covar(x, y, weight=None, axis=None, keepdims=False): with numpy.errstate(invalid="ignore"): xmean = mean(x, weight=weight, axis=axis, keepdims=keepdims) ymean = mean(y, weight=weight, axis=axis, keepdims=keepdims) if weight is None: sumw = count(x, axis=axis, keepdims=keepdims) sumwxy = sum((x - xmean)*(y - ymean), axis=axis, keepdims=keepdims) else: sumw = sum(x*0 + weight, axis=axis, keepdims=keepdims) sumwxy = sum((x - xmean)*(y - ymean)*weight, axis=axis, keepdims=keepdims) return numpy.true_divide(sumwxy, sumw) def corr(x, y, weight=None, axis=None, keepdims=False): with numpy.errstate(invalid="ignore"): xmean = mean(x, weight=weight, axis=axis, keepdims=keepdims) ymean = mean(y, weight=weight, axis=axis, keepdims=keepdims) xdiff = x - xmean ydiff = y - ymean if weight is None: sumwxx = sum(xdiff**2, axis=axis, keepdims=keepdims) sumwyy = sum(ydiff**2, axis=axis, keepdims=keepdims) sumwxy = sum(xdiff*ydiff, axis=axis, keepdims=keepdims) else: sumwxx = sum((xdiff**2)*weight, axis=axis, keepdims=keepdims) sumwyy = sum((ydiff**2)*weight, axis=axis, keepdims=keepdims) sumwxy = sum((xdiff*ydiff)*weight, axis=axis, keepdims=keepdims) return numpy.true_divide(sumwxy, numpy.sqrt(sumwxx * sumwyy)) def linearfit(x, y, weight=None, axis=None, keepdims=False): with numpy.errstate(invalid="ignore"): if weight is None: sumw = count(x, axis=axis, keepdims=keepdims) sumwx = sum(x, axis=axis, keepdims=keepdims) sumwy = sum(y, axis=axis, keepdims=keepdims) sumwxx = sum(x**2, axis=axis, keepdims=keepdims) sumwxy = sum(x*y, axis=axis, keepdims=keepdims) else: sumw = sum(x*0 + weight, axis=axis, keepdims=keepdims) sumwx = sum(x*weight, axis=axis, keepdims=keepdims) sumwy = sum(y*weight, axis=axis, keepdims=keepdims) sumwxx = sum((x**2)*weight, axis=axis, keepdims=keepdims) sumwxy = sum(x*y*weight, axis=axis, keepdims=keepdims) delta = (sumw*sumwxx) - (sumwx*sumwx) intercept = numpy.true_divide(((sumwxx*sumwy) - (sumwx*sumwxy)), delta) slope = numpy.true_divide(((sumw*sumwxy) - (sumwx*sumwy)), delta) intercept_error = numpy.sqrt(numpy.true_divide(sumwxx, delta)) slope_error = numpy.sqrt(numpy.true_divide(sumw, delta)) intercept = awkward1.operations.convert.tolayout(intercept, allowrecord=True, allowother=True) slope = awkward1.operations.convert.tolayout(slope, allowrecord=True, allowother=True) intercept_error = awkward1.operations.convert.tolayout(intercept_error, allowrecord=True, allowother=True) slope_error = awkward1.operations.convert.tolayout(slope_error, allowrecord=True, allowother=True) scalar = not isinstance(intercept, awkward1.layout.Content) and not isinstance(slope, awkward1.layout.Content) and not isinstance(intercept_error, awkward1.layout.Content) and not isinstance(slope_error, awkward1.layout.Content) if not isinstance(intercept, (awkward1.layout.Content, awkward1.layout.Record)): intercept = awkward1.layout.NumpyArray(numpy.array([intercept])) if not isinstance(slope, (awkward1.layout.Content, awkward1.layout.Record)): slope = awkward1.layout.NumpyArray(numpy.array([slope])) if not isinstance(intercept_error, (awkward1.layout.Content, awkward1.layout.Record)): intercept_error = awkward1.layout.NumpyArray(numpy.array([intercept_error])) if not isinstance(slope_error, (awkward1.layout.Content, awkward1.layout.Record)): slope_error = awkward1.layout.NumpyArray(numpy.array([slope_error])) out = awkward1.layout.RecordArray([intercept, slope, intercept_error, slope_error], ["intercept", "slope", "intercept_error", "slope_error"]) out.setparameter("__record__", "LinearFit") if scalar: out = out[0] return awkward1._util.wrap(out, awkward1._util.behaviorof(x, y)) def softmax(x, axis=None, keepdims=False): with numpy.errstate(invalid="ignore"): expx = numpy.exp(x) denom = sum(expx, axis=axis, keepdims=keepdims) return numpy.true_divide(expx, denom) __all__ = [x for x in list(globals()) if not x.startswith("_") and x not in ("collections", "numpy", "awkward1")]

48.174603

236

0.647117

9558fc73a95bcd6653e042be3bc2a2e8ae6c004c

4,758

py

Python

dotenv.py

ross-urban/django-dotenv

16cbf7bb78571174bc5376c95c85b213857cb9f9

[ "MIT" ]

null

dotenv.py

ross-urban/django-dotenv

16cbf7bb78571174bc5376c95c85b213857cb9f9

[ "MIT" ]

null

dotenv.py

ross-urban/django-dotenv

16cbf7bb78571174bc5376c95c85b213857cb9f9

[ "MIT" ]

1

2021-02-16T15:37:18.000Z

import os import re import sys import warnings __version__ = '1.4.3' line_re = re.compile(r""" ^ (?:export\s+)? # optional export ([\w\.]+) # key (?:\s*=\s*|:\s+?) # separator ( # optional value begin '(?:\'|[^'])*' # single quoted value | # or "(?:\"|[^"])*" # double quoted value | # or [^#\n]+ # unquoted value )? # value end (?:\s*\#.*)? # optional comment $ """, re.VERBOSE) variable_re = re.compile(r""" (\\)? # is it escaped with a backslash? (\$) # literal $ ( # collect braces with var for sub \{? # allow brace wrapping ([A-Z0-9_]+) # match the variable \}? # closing brace ) # braces end """, re.IGNORECASE | re.VERBOSE) overrides = ('source_env', 'source_up') def read_dotenv(dotenv=None, override=False): """ Read a .env file into os.environ. If not given a path to a dotenv path, does filthy magic stack backtracking to find manage.py and then find the dotenv. If tests rely on .env files, setting the overwrite flag to True is a safe way to ensure tests run consistently across all environments. :param override: True if values in .env should override system variables. """ if dotenv is None: frame_filename = sys._getframe().f_back.f_code.co_filename dotenv = os.path.join(os.path.dirname(frame_filename), '.env') if os.path.isdir(dotenv) and os.path.isfile(os.path.join(dotenv, '.env')): dotenv = os.path.join(dotenv, '.env') if os.path.exists(dotenv): with open(dotenv) as f: env = parse_dotenv(f.read()) for k, v in env.items(): if k in overrides: continue if override: os.environ[k] = v else: os.environ.setdefault(k, v) for k, v in env.items(): if k not in overrides: continue for fname in v: read_dotenv(fname, override) else: warnings.warn("Not reading {0} - it doesn't exist.".format(dotenv), stacklevel=2)

31.72

78

0.481084

955b60084410969a08f97fe22aa1d69988088bf0

16,755

py

Python

PsychoPy3 Experiments/ContrastDetection.py

mrhunsaker/ContrastDetection

bb058460c5f90119316d0637885cd47f7ca2a307

[ "MIT" ]

null

PsychoPy3 Experiments/ContrastDetection.py

mrhunsaker/ContrastDetection

bb058460c5f90119316d0637885cd47f7ca2a307

[ "MIT" ]

null

PsychoPy3 Experiments/ContrastDetection.py

mrhunsaker/ContrastDetection

bb058460c5f90119316d0637885cd47f7ca2a307

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- """ This experiment was created using PsychoPy3 Experiment Builder (v2020.2.4post1), on October 27, 2020, at 14:06 If you publish work using this script the most relevant publication is: Peirce J, Gray JR, Simpson S, MacAskill M, Hchenberger R, Sogo H, Kastman E, Lindelv JK. (2019) PsychoPy2: Experiments in behavior made easy Behav Res 51: 195. https://doi.org/10.3758/s13428-018-01193-y """ from __future__ import absolute_import, division from psychopy import locale_setup from psychopy import prefs from psychopy import sound, gui, visual, core, data, event, logging, clock from psychopy.constants import (NOT_STARTED, STARTED, PLAYING, PAUSED, STOPPED, FINISHED, PRESSED, RELEASED, FOREVER) import numpy as np # whole numpy lib is available, prepend 'np.' from numpy import (sin, cos, tan, log, log10, pi, average, sqrt, std, deg2rad, rad2deg, linspace, asarray) from numpy.random import random, randint, normal, shuffle import os # handy system and path functions import sys # to get file system encoding from psychopy.hardware import keyboard # Ensure that relative paths start from the same directory as this script _thisDir = os.path.dirname(os.path.abspath(__file__)) os.chdir(_thisDir) # Store info about the experiment session psychopyVersion = '2020.2.4post1' expName = 'ContrastDetection' # from the Builder filename that created this script expInfo = {'participant': 's_001', 'ori': '10'} dlg = gui.DlgFromDict(dictionary=expInfo, sort_keys=False, title=expName) if dlg.OK == False: core.quit() # user pressed cancel expInfo['date'] = data.getDateStr() # add a simple timestamp expInfo['expName'] = expName expInfo['psychopyVersion'] = psychopyVersion # Data file name stem = absolute path + name; later add .psyexp, .csv, .log, etc filename = _thisDir + os.sep + 'data' + os.sep + '%s_%s' % (expInfo['participant'], expInfo['date']) # An ExperimentHandler isn't essential but helps with data saving thisExp = data.ExperimentHandler(name=expName, version='', extraInfo=expInfo, runtimeInfo=None, originPath='C:\\Users\\Ryan Hunsaker\\psychopy\\PsychoPy3 Experiments\\ContrastDetection.py', savePickle=True, saveWideText=True, dataFileName=filename) # save a log file for detail verbose info logFile = logging.LogFile(filename+'.log', level=logging.EXP) logging.console.setLevel(logging.WARNING) # this outputs to the screen, not a file endExpNow = False # flag for 'escape' or other condition => quit the exp frameTolerance = 0.001 # how close to onset before 'same' frame # Start Code - component code to be run before the window creation # Setup the Window win = visual.Window( size=[2496, 1664], fullscr=True, screen=0, winType='pyglet', allowGUI=False, allowStencil=False, monitor='testMonitor', color=[0,0,0], colorSpace='rgb', blendMode='avg', useFBO=True) # store frame rate of monitor if we can measure it expInfo['frameRate'] = win.getActualFrameRate() if expInfo['frameRate'] != None: frameDur = 1.0 / round(expInfo['frameRate']) else: frameDur = 1.0 / 60.0 # could not measure, so guess # create a default keyboard (e.g. to check for escape) defaultKeyboard = keyboard.Keyboard() # Initialize components for Routine "instr" instrClock = core.Clock() instructions = visual.TextStim(win=win, name='instructions', text="Press 'up' if you see the stimulus, 'down' if you didn't.\n\nAny key to start", font='Atkinson Hyperlegible', pos=[0, 0], height=0.1, wrapWidth=None, ori=0, color=[1, 1, 1], colorSpace='rgb', opacity=1, languageStyle='LTR', depth=0.0); ready = keyboard.Keyboard() # Initialize components for Routine "trial" trialClock = core.Clock() fixation = visual.GratingStim( win=win, name='fixation',units='pix', tex=None, mask=None, ori=0, pos=[0, 0], size=[25, 25], sf=1, phase=0.0, color=[1, 1, 1], colorSpace='rgb', opacity=1,blendmode='avg', texRes=512, interpolate=True, depth=0.0) gabor = visual.GratingStim( win=win, name='gabor',units='pix', tex='sin', mask='gauss', ori=expInfo['ori'], pos=[0, 0], size=[1024,1024], sf=0.025, phase=1.0, color='white', colorSpace='rgb', opacity=1,blendmode='avg', texRes=512, interpolate=True, depth=-1.0) resp = keyboard.Keyboard() # Create some handy timers globalClock = core.Clock() # to track the time since experiment started routineTimer = core.CountdownTimer() # to track time remaining of each (non-slip) routine # ------Prepare to start Routine "instr"------- continueRoutine = True # update component parameters for each repeat ready.keys = [] ready.rt = [] _ready_allKeys = [] # keep track of which components have finished instrComponents = [instructions, ready] for thisComponent in instrComponents: thisComponent.tStart = None thisComponent.tStop = None thisComponent.tStartRefresh = None thisComponent.tStopRefresh = None if hasattr(thisComponent, 'status'): thisComponent.status = NOT_STARTED # reset timers t = 0 _timeToFirstFrame = win.getFutureFlipTime(clock="now") instrClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip frameN = -1 # -------Run Routine "instr"------- while continueRoutine: # get current time t = instrClock.getTime() tThisFlip = win.getFutureFlipTime(clock=instrClock) tThisFlipGlobal = win.getFutureFlipTime(clock=None) frameN = frameN + 1 # number of completed frames (so 0 is the first frame) # update/draw components on each frame # *instructions* updates if instructions.status == NOT_STARTED and tThisFlip >= 0-frameTolerance: # keep track of start time/frame for later instructions.frameNStart = frameN # exact frame index instructions.tStart = t # local t and not account for scr refresh instructions.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(instructions, 'tStartRefresh') # time at next scr refresh instructions.setAutoDraw(True) # *ready* updates waitOnFlip = False if ready.status == NOT_STARTED and tThisFlip >= 0-frameTolerance: # keep track of start time/frame for later ready.frameNStart = frameN # exact frame index ready.tStart = t # local t and not account for scr refresh ready.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(ready, 'tStartRefresh') # time at next scr refresh ready.status = STARTED # keyboard checking is just starting waitOnFlip = True win.callOnFlip(ready.clock.reset) # t=0 on next screen flip win.callOnFlip(ready.clearEvents, eventType='keyboard') # clear events on next screen flip if ready.status == STARTED and not waitOnFlip: theseKeys = ready.getKeys(keyList=None, waitRelease=False) _ready_allKeys.extend(theseKeys) if len(_ready_allKeys): ready.keys = _ready_allKeys[-1].name # just the last key pressed ready.rt = _ready_allKeys[-1].rt # a response ends the routine continueRoutine = False # check for quit (typically the Esc key) if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]): core.quit() # check if all components have finished if not continueRoutine: # a component has requested a forced-end of Routine break continueRoutine = False # will revert to True if at least one component still running for thisComponent in instrComponents: if hasattr(thisComponent, "status") and thisComponent.status != FINISHED: continueRoutine = True break # at least one component has not yet finished # refresh the screen if continueRoutine: # don't flip if this routine is over or we'll get a blank screen win.flip() # -------Ending Routine "instr"------- for thisComponent in instrComponents: if hasattr(thisComponent, "setAutoDraw"): thisComponent.setAutoDraw(False) thisExp.addData('instructions.started', instructions.tStartRefresh) thisExp.addData('instructions.stopped', instructions.tStopRefresh) # check responses if ready.keys in ['', [], None]: # No response was made ready.keys = None thisExp.addData('ready.keys',ready.keys) if ready.keys != None: # we had a response thisExp.addData('ready.rt', ready.rt) thisExp.addData('ready.started', ready.tStartRefresh) thisExp.addData('ready.stopped', ready.tStopRefresh) thisExp.nextEntry() # the Routine "instr" was not non-slip safe, so reset the non-slip timer routineTimer.reset() # --------Prepare to start Staircase "trials" -------- # set up handler to look after next chosen value etc trials = data.StairHandler(startVal=0.9, extraInfo=expInfo, stepSizes=asarray([1,1,0.9,0.9,0.8,0.8,0.6, 0.6, 0.4,0.4,0.2]), stepType='log', nReversals=1, nTrials=30.0, nUp=1, nDown=3, minVal=0.0, maxVal=1.0, originPath=-1, name='trials') thisExp.addLoop(trials) # add the loop to the experiment level = thisTrial = 0.9 # initialise some vals for thisTrial in trials: currentLoop = trials level = thisTrial # ------Prepare to start Routine "trial"------- continueRoutine = True routineTimer.add(2.500000) # update component parameters for each repeat gabor.setColor([level, level, level], colorSpace='rgb') resp.keys = [] resp.rt = [] _resp_allKeys = [] # keep track of which components have finished trialComponents = [fixation, gabor, resp] for thisComponent in trialComponents: thisComponent.tStart = None thisComponent.tStop = None thisComponent.tStartRefresh = None thisComponent.tStopRefresh = None if hasattr(thisComponent, 'status'): thisComponent.status = NOT_STARTED # reset timers t = 0 _timeToFirstFrame = win.getFutureFlipTime(clock="now") trialClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip frameN = -1 # -------Run Routine "trial"------- while continueRoutine and routineTimer.getTime() > 0: # get current time t = trialClock.getTime() tThisFlip = win.getFutureFlipTime(clock=trialClock) tThisFlipGlobal = win.getFutureFlipTime(clock=None) frameN = frameN + 1 # number of completed frames (so 0 is the first frame) # update/draw components on each frame # *fixation* updates if fixation.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance: # keep track of start time/frame for later fixation.frameNStart = frameN # exact frame index fixation.tStart = t # local t and not account for scr refresh fixation.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(fixation, 'tStartRefresh') # time at next scr refresh fixation.setAutoDraw(True) if fixation.status == STARTED: # is it time to stop? (based on global clock, using actual start) if tThisFlipGlobal > fixation.tStartRefresh + 0.5-frameTolerance: # keep track of stop time/frame for later fixation.tStop = t # not accounting for scr refresh fixation.frameNStop = frameN # exact frame index win.timeOnFlip(fixation, 'tStopRefresh') # time at next scr refresh fixation.setAutoDraw(False) # *gabor* updates if gabor.status == NOT_STARTED and tThisFlip >= 0.5-frameTolerance: # keep track of start time/frame for later gabor.frameNStart = frameN # exact frame index gabor.tStart = t # local t and not account for scr refresh gabor.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(gabor, 'tStartRefresh') # time at next scr refresh gabor.setAutoDraw(True) if gabor.status == STARTED: # is it time to stop? (based on global clock, using actual start) if tThisFlipGlobal > gabor.tStartRefresh + 0.5-frameTolerance: # keep track of stop time/frame for later gabor.tStop = t # not accounting for scr refresh gabor.frameNStop = frameN # exact frame index win.timeOnFlip(gabor, 'tStopRefresh') # time at next scr refresh gabor.setAutoDraw(False) if gabor.status == STARTED: # only update if drawing gabor.setPhase(trialClock.getTime()*2, log=False) # *resp* updates waitOnFlip = False if resp.status == NOT_STARTED and tThisFlip >= 0.5-frameTolerance: # keep track of start time/frame for later resp.frameNStart = frameN # exact frame index resp.tStart = t # local t and not account for scr refresh resp.tStartRefresh = tThisFlipGlobal # on global time win.timeOnFlip(resp, 'tStartRefresh') # time at next scr refresh resp.status = STARTED # keyboard checking is just starting waitOnFlip = True win.callOnFlip(resp.clock.reset) # t=0 on next screen flip win.callOnFlip(resp.clearEvents, eventType='keyboard') # clear events on next screen flip if resp.status == STARTED: # is it time to stop? (based on global clock, using actual start) if tThisFlipGlobal > resp.tStartRefresh + 2.0-frameTolerance: # keep track of stop time/frame for later resp.tStop = t # not accounting for scr refresh resp.frameNStop = frameN # exact frame index win.timeOnFlip(resp, 'tStopRefresh') # time at next scr refresh resp.status = FINISHED if resp.status == STARTED and not waitOnFlip: theseKeys = resp.getKeys(keyList=['up', 'down'], waitRelease=False) _resp_allKeys.extend(theseKeys) if len(_resp_allKeys): resp.keys = _resp_allKeys[-1].name # just the last key pressed resp.rt = _resp_allKeys[-1].rt # was this correct? if (resp.keys == str('up')) or (resp.keys == 'up'): resp.corr = 1 else: resp.corr = 0 # check for quit (typically the Esc key) if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]): core.quit() # check if all components have finished if not continueRoutine: # a component has requested a forced-end of Routine break continueRoutine = False # will revert to True if at least one component still running for thisComponent in trialComponents: if hasattr(thisComponent, "status") and thisComponent.status != FINISHED: continueRoutine = True break # at least one component has not yet finished # refresh the screen if continueRoutine: # don't flip if this routine is over or we'll get a blank screen win.flip() # -------Ending Routine "trial"------- for thisComponent in trialComponents: if hasattr(thisComponent, "setAutoDraw"): thisComponent.setAutoDraw(False) trials.addOtherData('fixation.started', fixation.tStartRefresh) trials.addOtherData('fixation.stopped', fixation.tStopRefresh) trials.addOtherData('gabor.started', gabor.tStartRefresh) trials.addOtherData('gabor.stopped', gabor.tStopRefresh) # check responses if resp.keys in ['', [], None]: # No response was made resp.keys = None # was no response the correct answer?! if str('up').lower() == 'none': resp.corr = 1; # correct non-response else: resp.corr = 0; # failed to respond (incorrectly) # store data for trials (StairHandler) trials.addResponse(resp.corr) trials.addOtherData('resp.rt', resp.rt) trials.addOtherData('resp.started', resp.tStartRefresh) trials.addOtherData('resp.stopped', resp.tStopRefresh) thisExp.nextEntry() # staircase completed trials.saveAsExcel(filename + '.xlsx', sheetName='trials') trials.saveAsText(filename + 'trials.csv', delim=',') # Flip one final time so any remaining win.callOnFlip() # and win.timeOnFlip() tasks get executed before quitting win.flip() # these shouldn't be strictly necessary (should auto-save) thisExp.saveAsWideText(filename+'.csv', delim='comma') thisExp.saveAsPickle(filename) logging.flush() # make sure everything is closed down thisExp.abort() # or data files will save again on exit win.close() core.quit()

43.861257

102

0.66607

955b6290b3f098708424dbec65825578b92645dc

1,945

py

Python

self_driving_desktop/grammar.py

wasimakh2/self-driving-desktop

309b9b6614f8d3f2b85ed40c8e3cd9d72cd069a6

[ "MIT" ]

536

2019-05-08T02:54:27.000Z

2022-03-24T10:02:07.000Z

self_driving_desktop/grammar.py

JonTheNiceGuy/self-driving-desktop

309b9b6614f8d3f2b85ed40c8e3cd9d72cd069a6

[ "MIT" ]

17

2019-05-08T03:08:14.000Z

2021-03-02T12:52:53.000Z

self_driving_desktop/grammar.py

JonTheNiceGuy/self-driving-desktop

309b9b6614f8d3f2b85ed40c8e3cd9d72cd069a6

[ "MIT" ]

33

2019-05-08T03:50:56.000Z

2021-12-08T11:22:29.000Z

grammar = r""" start: (item ";")+ item: import | coords | playlist | step import : "import" string coords : "coords" coords_body coords_body : "{" coord_def ("," coord_def)* "}" coord_def: string ":" "{" coord_body ("," coord_body)* "}" coord_body: string ":" "[" int "," int "]" playlist : "playlist" string playlist_body playlist_body : "{" (step ";")* "}" step : screen | repeat | play | active | focus | delay | sleep | shell | coord_off | coord | mouse | drag | click | btnclick | btndown | btnup | scroll | hscroll | keypress | keydown | keyup | hotkeys | write | copy | paste | save_clipboard | load_clipboard | copy_clipboard | paste_clipboard screen: "screen" string repeat: "play" string+ int | "play" string+ number play: "play" string+ active: "active" string focus: "focus" string delay: "delay" number sleep: "sleep" number shell: ("shell"|"sh") string+ coord_off: ("coord"|"mc") string number number number coord: ("coord"|"mc") string number mouse: ("mouse"|"mv"|"mm") number number number drag: ("drag"|"md") string number number number click: "click" btnclick: ("btnclick"|"bc") string btndown: ("btndown"|"bd") string btnup: ("btnup"|"bu") string scroll: "scroll" number hscroll: "hscroll" number keypress: ("keypress"|"kp") string keydown: ("keydown"|"kd") string keyup: ("keyup"|"ku") string hotkeys: ("hotkeys"|"hk") string+ write: ("write"|"w"|"type"|"t") string number? copy: "copy" paste: "paste" save_clipboard: ("save_clipboard"|"scb") string load_clipboard: ("load_clipboard"|"lcb") string copy_clipboard: ("copy_clipboard"|"ccb") string paste_clipboard: ("paste_clipboard"|"pcb") string int: INT number: SIGNED_NUMBER string: ESCAPED_STRING COMMENT: /#[^\n]*/ IDENT: (LETTER|"_") (LETTER|INT|"-"|"_")* NAME: LETTER (LETTER|INT|"-"|"_")* WORD: LETTER+ %import common.LETTER %import common.ESCAPED_STRING %import common.INT %import common.SIGNED_NUMBER %import common.WS %ignore COMMENT %ignore WS """

19.45

58

0.682776

955dce71570249e6e13d912ac4f316735729f8a7

1,765

py

Python

BB/conf.py

poco0317/BarinadeBot-Rewrite

4f34246178ab2ee0fd4c0a79fff5a43adbed134c

[ "MIT" ]

2

2021-05-06T09:07:44.000Z

2021-05-11T23:45:38.000Z

BB/conf.py

poco0317/BarinadeBot-Rewrite

4f34246178ab2ee0fd4c0a79fff5a43adbed134c

[ "MIT" ]

null

BB/conf.py

poco0317/BarinadeBot-Rewrite

4f34246178ab2ee0fd4c0a79fff5a43adbed134c

[ "MIT" ]

null

import configparser import os import shutil import traceback

41.046512

155

0.602833

955f1cf7d1a0592b32cf0c5abbfe0bb9060df419

2,805

py

Python

geocamUtil/usng/convertUsngCsv.py

geocam/geocamUtilWeb

b64fc063c64b4b0baa140db4c126f2ff980756ab

[ "NASA-1.3" ]

4

2017-03-03T16:24:24.000Z

2018-06-24T05:50:40.000Z

geocamUtil/usng/convertUsngCsv.py

geocam/geocamUtilWeb

b64fc063c64b4b0baa140db4c126f2ff980756ab

[ "NASA-1.3" ]

1

2021-09-29T17:17:30.000Z

geocamUtil/usng/convertUsngCsv.py

geocam/geocamUtilWeb

b64fc063c64b4b0baa140db4c126f2ff980756ab

[ "NASA-1.3" ]

1

2017-12-19T20:45:53.000Z

#!/usr/bin/env python # __BEGIN_LICENSE__ #Copyright (c) 2015, United States Government, as represented by the #Administrator of the National Aeronautics and Space Administration. #All rights reserved. # __END_LICENSE__ """ Takes as input a CSV file in the format: 37 46 29.2080,-122 25 08.1336,San Francisco 37 27 13.8132,-122 10 55.7184,Menlo Park And outputs CSV in the format: 10S EG 51172 80985,San Francisco 10S EG 72335 45533,Menlo Park Optionally outputs a KML file of placemarks as well, where the placemark descriptions include USNG coordinates. """ import csv from geocamUtil.usng import usng from geocamUtil import KmlUtil if __name__ == '__main__': main()

30.824176

92

0.624242

955fa29268924998ee2dd6306f368b16b34e2595

478

py

Python

process_cifar10.py

IIGROUP/AttentionProbe

b2c88b064452741a7ccc6660a4b090743013cc73

[ "MIT" ]

11

2022-01-23T15:09:09.000Z

2022-03-18T10:27:04.000Z

process_cifar10.py

Wang-jiahao/AttentionProbe

41a3cc0d5454ec5bba78c3dace9cded00da8cff9

[ "MIT" ]

null

process_cifar10.py

Wang-jiahao/AttentionProbe

41a3cc0d5454ec5bba78c3dace9cded00da8cff9

[ "MIT" ]

null

from torchvision.datasets import CIFAR10 from torchvision.datasets import CIFAR100 import os root = '/database/cifar10/' from PIL import Image dataset_train = CIFAR10(root) for k, (img, label) in enumerate(dataset_train): print('processsing' + str(k)) if not os.path.exists(root + 'CIFAR10_image/' + str(label)+ '/'): os.mkdir(root + 'CIFAR10_image/' + str(label)+ '/') img.save(root + 'CIFAR10_image/' + str(label) + '/' + str(k) + '.png')

31.866667

75

0.650628

955fe4376191cdb0e3d9522af865a55375090411

246

py

Python

examples/fullproject/items/user.py

cnkailyn/toapi

03a49d02dd0a55f1f83270154144e1a08fae6b78

[ "Apache-2.0" ]

null

examples/fullproject/items/user.py

cnkailyn/toapi

03a49d02dd0a55f1f83270154144e1a08fae6b78

[ "Apache-2.0" ]

null

examples/fullproject/items/user.py

cnkailyn/toapi

03a49d02dd0a55f1f83270154144e1a08fae6b78

[ "Apache-2.0" ]

1

2019-11-12T20:15:50.000Z

from toapi import Item, XPath

22.363636

50

0.536585

95620b3f160fc0fb6d0c0896e86c4e7d56432d0b

722

py

Python

src/tests/test_fail.py

bspeagle/py_git_diff

1674afc1dfac0408372e11945f4a36b297b77e66

[ "MIT" ]

null

src/tests/test_fail.py

bspeagle/py_git_diff

1674afc1dfac0408372e11945f4a36b297b77e66

[ "MIT" ]

null

src/tests/test_fail.py

bspeagle/py_git_diff

1674afc1dfac0408372e11945f4a36b297b77e66

[ "MIT" ]

null

''' Failure tests ''' import os from typing import Any import pytest from helpers.github import API api = API() pass_token = Any fail_token = os.getenv('FAIL_TOKEN') fail_org = os.getenv('FAIL_ORG') fail_repo = os.getenv('FAIL_REPO') def test_fail_auth(): ''' Fail 'auth' to Github ''' with pytest.raises(SystemExit): api.authenticate(fail_token) def test_fail_org(token): ''' Fail 'get organization' ''' pass_token = token with pytest.raises(SystemExit): api.authenticate(pass_token) api.get_organization(fail_org) def test_fail_repo(): ''' Fail 'get repo' ''' with pytest.raises(SystemExit): api.get_repo("user", fail_repo)

16.044444

39

0.649584

9562440f3dc7a8e571a4195021e3f9febc5d8b84

3,042

py

Python

tutorials/mechanisms/tutorial_convenience_inhibition.py

AQ18/skimpy

435fc50244f2ca815bbb39d525a82a4692f5c0ac

[ "Apache-2.0" ]

13

2020-11-05T10:59:13.000Z

2022-03-21T01:38:31.000Z

tutorials/mechanisms/tutorial_convenience_inhibition.py

AQ18/skimpy

435fc50244f2ca815bbb39d525a82a4692f5c0ac

[ "Apache-2.0" ]

4

2022-01-27T10:23:40.000Z

2022-03-10T18:16:06.000Z

tutorials/mechanisms/tutorial_convenience_inhibition.py

AQ18/skimpy

435fc50244f2ca815bbb39d525a82a4692f5c0ac

[ "Apache-2.0" ]

6

2020-08-04T17:01:33.000Z

2022-03-21T01:38:32.000Z

# -*- coding: utf-8 -*- """ .. module:: skimpy :platform: Unix, Windows :synopsis: Simple Kinetic Models in Python .. moduleauthor:: SKiMPy team [---------] Copyright 2017 Laboratory of Computational Systems Biotechnology (LCSB), Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ import numpy as np # Test models from skimpy.core import * from skimpy.mechanisms import * name = 'pfk' SpecificConvenience = make_convenience_with_inhibition([-2, -1, 3], [1]) metabolites = SpecificConvenience.Reactants(substrate1 = 'A', substrate2 = 'B', product1 = 'C' ) inhibitors = SpecificConvenience.Inhibitors(inhibitor1 = 'I') # thermo_data = {'S': 1e-2, # 'P': 1e-2, # 'sig_S': 0.1, # 'sig_P': 0.1, # 'gamma': 0.1, # 'flux': 1.0, # 'E_tot': 1e-5} ## QSSA Method parameters = SpecificConvenience.Parameters( vmax_forward = 1.0, k_equilibrium=2.0, km_substrate1 = 10.0, km_substrate2 = 10.0, km_product1 = 10.0, ki_inhibitor1 = 1.0) pfk = Reaction(name=name, mechanism=SpecificConvenience, reactants=metabolites, inhibitors=inhibitors, ) name = 'inhib' metabolites = ReversibleMichaelisMenten.Reactants(substrate = 'C', product = 'I') ## QSSA Method parameters_inh = ReversibleMichaelisMenten.Parameters( vmax_forward = 1.0, k_equilibrium=2.0, km_substrate = 10.0, km_product = 10.0, total_enzyme_concentration = 1.0, ) inh = Reaction(name=name, mechanism=ReversibleMichaelisMenten, reactants=metabolites, ) this_model = KineticModel() this_model.add_reaction(pfk) this_model.add_reaction(inh) this_model.parametrize_by_reaction({inh.name:parameters_inh, pfk.name: parameters}) this_model.compile_ode(sim_type = QSSA) this_model.initial_conditions['A'] = 10.0 this_model.initial_conditions['B'] = 10.0 this_model.initial_conditions['C'] = 10.0 this_model.initial_conditions['I'] = 0.0 this_sol_qssa = this_model.solve_ode(np.linspace(0.0, 50.0, 500),solver_type = 'cvode') this_sol_qssa.plot('output/base_out_qssa.html')

29.25

87

0.610782

9564a1cacc7687a8261fe339aaf329a5f5fa587d

825

py

Python

advanced-python/05_advanced_classes_and_objects/enums.py

alexprodan99/python-workspace

8c805afc29fafe3916759d1cf07e597f945b8b45

[ "MIT" ]

null

advanced-python/05_advanced_classes_and_objects/enums.py

alexprodan99/python-workspace

8c805afc29fafe3916759d1cf07e597f945b8b45

[ "MIT" ]

null

advanced-python/05_advanced_classes_and_objects/enums.py

alexprodan99/python-workspace

8c805afc29fafe3916759d1cf07e597f945b8b45

[ "MIT" ]

null

from enum import Enum, unique, auto if __name__ == '__main__': main()

27.5

152

0.641212

9566a5fe7dd2b6c92ef1c6e1f73143b039776af9

3,313

py

Python

detector/detector.py

suhendaragung20/Object-Detection-Metrics

e756c9ba20ff1e89143c64e6d38288d2a8680f0e

[ "MIT" ]

null

detector/detector.py

suhendaragung20/Object-Detection-Metrics

e756c9ba20ff1e89143c64e6d38288d2a8680f0e

[ "MIT" ]

null

detector/detector.py

suhendaragung20/Object-Detection-Metrics

e756c9ba20ff1e89143c64e6d38288d2a8680f0e

[ "MIT" ]

null

# Import packages import os import cv2 import numpy as np import tensorflow as tf import sys from imutils.object_detection import non_max_suppression # This is needed since the notebook is stored in the object_detection folder. sys.path.append("..") # Import utilites from utils import label_map_util

37.224719

107

0.690915

9566c8358fb6d074b645539d82fffd8a430711c8

1,770

py

Python

processDiscoveryNews4chat.py

data-henrik/watson-chatbot-discovery-news

d63d579718d4fc529af29bb413c73fdbd9b52361

[ "Apache-2.0" ]

3

2019-05-03T20:28:45.000Z

2019-06-28T09:58:25.000Z

processDiscoveryNews4chat.py

psaupsau/watson-chatbot-discovery-news

d63d579718d4fc529af29bb413c73fdbd9b52361

[ "Apache-2.0" ]

null

processDiscoveryNews4chat.py

psaupsau/watson-chatbot-discovery-news

d63d579718d4fc529af29bb413c73fdbd9b52361

[ "Apache-2.0" ]

4

2019-04-25T16:49:47.000Z

2020-07-02T15:27:05.000Z

# Handle client-side action for an IBM Watson Assistant chatbot # # The code requires my Watson Conversation Tool. For details see # https://github.com/data-henrik/watson-conversation-tool # # # Setup: Configure your credentials # - for Watson Assistant see instructions for the tool # - for Discovery change username / password below # # # Written by Henrik Loeser import json from watson_developer_cloud import DiscoveryV1

35.4

95

0.714124

9566fa933abad53d06086af6a6e451a81990671d

2,977

py

Python

test_scripts/test_residual_solver_dynamic.py

JoZimmer/ParOptBeam

50d15d8d822a2718f2932807e06c4a7e02f866a3

[ "BSD-3-Clause" ]

1

2021-04-09T14:08:20.000Z

test_scripts/test_residual_solver_dynamic.py

JoZimmer/ParOptBeam

50d15d8d822a2718f2932807e06c4a7e02f866a3

[ "BSD-3-Clause" ]

2

2021-04-28T15:05:01.000Z

2021-11-10T15:12:56.000Z

test_scripts/test_residual_solver_dynamic.py

JoZimmer/ParOptBeam

50d15d8d822a2718f2932807e06c4a7e02f866a3

[ "BSD-3-Clause" ]

2

2021-02-01T08:49:45.000Z

2021-08-10T02:07:36.000Z

import numpy as np import matplotlib.pyplot as plt from cycler import cycler from source.solving_strategies.strategies.residual_based_newton_raphson_solver import ResidualBasedNewtonRaphsonSolver from source.solving_strategies.strategies.residual_based_picard_solver import ResidualBasedPicardSolver from source.model.structure_model import StraightBeam np.set_printoptions(suppress=False, precision=2, linewidth=140) params = { "name": "CaarcBeamPrototypeOptimizable", "domain_size": "3D", "system_parameters": { "element_params": { "type": "CRBeam", "is_nonlinear": True }, "material": { "density": 7850.0, "youngs_modulus": 2069000000, "poisson_ratio": 0.29, "damping_ratio": 0.1 }, "geometry": { "length_x": 1.2, "number_of_elements": 1, "defined_on_intervals": [{ "interval_bounds": [0.0, "End"], "length_y": [1.0], "length_z": [1.0], "area": [0.0001], "shear_area_y": [0.0], "shear_area_z": [0.0], "moment_of_inertia_y": [0.0001], "moment_of_inertia_z": [0.0001], "torsional_moment_of_inertia": [0.0001], "outrigger_mass": [0.0], "outrigger_stiffness": [0.0]}] } }, "boundary_conditions": "fixed-free" } dt = 0.1 tend = 10. steps = int(tend / dt) array_time = np.linspace(0.0, tend, steps + 1) array_time_kratos = np.linspace(0.1, 10, 101)

34.616279

118

0.566006

9567e6ba5dc9af36046c391fbc5d4e1144009cc8

378

py

Python

objects/regex_deleter.py

Egor2005l/cho

c7cb165394089b277be5c306edde0b8fb42e466d

[ "MIT" ]

null

objects/regex_deleter.py

Egor2005l/cho

c7cb165394089b277be5c306edde0b8fb42e466d

[ "MIT" ]

null

objects/regex_deleter.py

Egor2005l/cho

c7cb165394089b277be5c306edde0b8fb42e466d

[ "MIT" ]

null

from typing import Dict from objects.base import BaseModel

19.894737

38

0.531746

95697b5d755424cb46ff8e11e52fcff72a602bf4

639

py

Python

cartridge_external_payment/admin.py

thomasWajs/cartridge-external-payment

02c1c2b43504a17547a908622c3d54a331945c77

[ "BSD-2-Clause" ]

7

2015-02-14T20:25:27.000Z

2021-04-10T16:05:00.000Z

cartridge_external_payment/admin.py

thomasWajs/cartridge-external-payment

02c1c2b43504a17547a908622c3d54a331945c77

[ "BSD-2-Clause" ]

2

2015-11-30T17:54:19.000Z

2016-09-09T21:21:01.000Z

cartridge_external_payment/admin.py

thomasWajs/cartridge-external-payment

02c1c2b43504a17547a908622c3d54a331945c77

[ "BSD-2-Clause" ]

3

2015-10-19T15:22:18.000Z

2017-11-13T23:22:17.000Z

from copy import deepcopy from django.contrib import admin from cartridge.shop.admin import OrderAdmin from cartridge.shop.models import Order order_fieldsets = deepcopy(admin.site._registry[Order].fieldsets) order_fieldsets[2][1]["fields"] = list(order_fieldsets[2][1]["fields"]) order_fieldsets[2][1]["fields"].insert(0, 'payment_done') admin.site.unregister(Order) admin.site.register(Order, ExternalPaymentOrderAdmin)

33.631579

74

0.748044

9569b1f581ecb174ee905898df207343952c8b6e

1,483

py

Python

webeditor/app/attrdict.py

lshen1120/web-editor

170ac96b47bf957a3a42a99092e45e88e584c49a

[ "Apache-2.0" ]

4

2018-07-25T03:57:08.000Z

2018-07-25T06:34:59.000Z

webeditor/app/attrdict.py

lshen1120/web-editor

170ac96b47bf957a3a42a99092e45e88e584c49a

[ "Apache-2.0" ]

null

webeditor/app/attrdict.py

lshen1120/web-editor

170ac96b47bf957a3a42a99092e45e88e584c49a

[ "Apache-2.0" ]

null

#!/usr/bin/env python # -*- coding:utf-8 -*- import copy

26.017544

68

0.574511

956a1d409e8bf27f1eb1d39023f7ad436c2f2c6c

16,034

py

Python

EVeP/EVeP.py

amandaortega/EVeP

4bca562c814210b1d835e9be63ab80385c93320b

[ "MIT" ]

null

EVeP/EVeP.py

amandaortega/EVeP

4bca562c814210b1d835e9be63ab80385c93320b

[ "MIT" ]

null

EVeP/EVeP.py

amandaortega/EVeP

4bca562c814210b1d835e9be63ab80385c93320b

[ "MIT" ]

null

""" Author: Amanda Ortega de Castro Ayres Created in: September 19, 2019 Python version: 3.6 """ from Least_SRMTL import Least_SRMTL import libmr from matplotlib import pyplot, cm from matplotlib.patches import Circle from mpl_toolkits.mplot3d import Axes3D, art3d import numpy as np import numpy.matlib import sklearn.metrics

40.489899

247

0.591493

956c1145058b098a2e217c047220f62e14dea6e3

5,375

py

Python

bigml/modelfields.py

alanponce/python

9423b4c4968b81ee14cef1ab6cd62d23dfa8bd26

[ "Apache-2.0" ]

1

2021-06-20T11:51:22.000Z

bigml/modelfields.py

alanponce/python

9423b4c4968b81ee14cef1ab6cd62d23dfa8bd26

[ "Apache-2.0" ]

null

bigml/modelfields.py

alanponce/python

9423b4c4968b81ee14cef1ab6cd62d23dfa8bd26

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- #!/usr/bin/env python # # Copyright 2013-2016 BigML # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. """A BasicModel resource. This module defines a BasicModel to hold the main information of the model resource in BigML. It becomes the starting point for the Model class, that is used for local predictions. """ import logging LOGGER = logging.getLogger('BigML') from bigml.util import invert_dictionary, DEFAULT_LOCALE from bigml.fields import DEFAULT_MISSING_TOKENS def check_model_structure(model): """Checks the model structure to see if it contains all the needed keys """ return (isinstance(model, dict) and 'resource' in model and model['resource'] is not None and ('object' in model and 'model' in model['object'] or 'model' in model))

37.852113

77

0.596279

956d8de300f81dc8c0786d5a4d8868b85762da6f

16,229

py

Python

networks/infill/func_intersect_ub.py

LArbys/ublarcvserver

02381c937f49a2eab2f754017ab431c3f6fa70d7

[ "Apache-2.0" ]

2

2020-07-09T19:34:03.000Z

2021-06-21T23:09:23.000Z

networks/larflow/models/func_intersect_ub.py

LArbys/ublarcvserver

02381c937f49a2eab2f754017ab431c3f6fa70d7

[ "Apache-2.0" ]

null

networks/larflow/models/func_intersect_ub.py

LArbys/ublarcvserver

02381c937f49a2eab2f754017ab431c3f6fa70d7

[ "Apache-2.0" ]

null

import os,time import torch from larcv import larcv import numpy as np import ROOT as rt from array import array if __name__=="__main__": device = torch.device("cuda:0") #device = torch.device("cpu") IntersectUB.load_intersection_data() IntersectUB.set_img_dims(512,832) IntersectUB.print_intersect_grad() # save a histogram rout = rt.TFile("testout_func_intersect_ub.root","recreate") ttest = rt.TTree("test","Consistency 3D Loss test data") dloss = array('d',[0]) dtime = array('d',[0]) ttest.Branch("loss",dloss,"loss/D") ttest.Branch("dtime",dtime,"dtime/D") # as test, we process some pre-cropped small samples io = larcv.IOManager() io.add_in_file( "../testdata/smallsample/larcv_dlcosmictag_5482426_95_smallsample082918.root" ) # create a unit test file (csv) io.initialize() nentries = io.get_n_entries() print "Number of Entries: ",nentries start = time.time() istart=0 iend=nentries #istart=155 #iend=156 for ientry in xrange(istart,iend): tentry = time.time() io.read_entry( ientry ) if os.environ["LARCV_VERSION"]=="1": ev_adc_test = io.get_data(larcv.kProductImage2D,"adc") ev_flowy2u_test = io.get_data(larcv.kProductImage2D,"larflow_y2u") ev_flowy2v_test = io.get_data(larcv.kProductImage2D,"larflow_y2v") ev_trueflow_test = io.get_data(larcv.kProductImage2D,"pixflow") ev_truevisi_test = io.get_data(larcv.kProductImage2D,"pixvisi") flowy2u = ev_flowy2u_test.Image2DArray()[0] flowy2v = ev_flowy2v_test.Image2DArray()[0] truey2u = ev_trueflow_test.Image2DArray()[0] truey2v = ev_trueflow_test.Image2DArray()[1] visiy2u = ev_truevisi_test.Image2DArray()[0] visiy2v = ev_truevisi_test.Image2DArray()[1] source_meta = ev_adc_test.Image2DArray()[2].meta() targetu_meta = ev_adc_test.Image2DArray()[0].meta() targetv_meta = ev_adc_test.Image2DArray()[1].meta() elif os.environ["LARCV_VERSION"]=="2": ev_adc_test = io.get_data("image2d","adc") ev_flowy2u_test = io.get_data("image2d","larflow_y2u") ev_flowy2v_test = io.get_data("image2d","larflow_y2v") ev_trueflow_test = io.get_data("image2d","pixflow") ev_truevisi_test = io.get_data("image2d","pixvisi") flowy2u = ev_flowy2u_test.as_vector()[0] flowy2v = ev_flowy2v_test.as_vector()[0] truey2u = ev_trueflow_test.as_vector()[0] truey2v = ev_trueflow_test.as_vector()[1] visiy2u = ev_truevisi_test.as_vector()[0] visiy2v = ev_truevisi_test.as_vector()[1] source_meta = ev_adc_test.as_vector()[2].meta() targetu_meta = ev_adc_test.as_vector()[0].meta() targetv_meta = ev_adc_test.as_vector()[1].meta() # numpy arrays index = (0,1) if os.environ["LARCV_VERSION"]=="2": index = (1,0) np_flowy2u = larcv.as_ndarray(flowy2u).transpose(index).reshape((1,1,source_meta.cols(),source_meta.rows())) np_flowy2v = larcv.as_ndarray(flowy2v).transpose(index).reshape((1,1,source_meta.cols(),source_meta.rows())) np_visiy2u = larcv.as_ndarray(visiy2u).transpose(index).reshape((1,1,source_meta.cols(),source_meta.rows())) np_visiy2v = larcv.as_ndarray(visiy2v).transpose(index).reshape((1,1,source_meta.cols(),source_meta.rows())) np_trueflowy2u = larcv.as_ndarray(truey2u).transpose(index).reshape((1,1,source_meta.cols(),source_meta.rows())) np_trueflowy2v = larcv.as_ndarray(truey2v).transpose(index).reshape((1,1,source_meta.cols(),source_meta.rows())) #print "NAN indices (flow-Y2U): ",np.argwhere( np.isnan(np_flowy2u) ) #print "NAN indices (flow-Y2V): ",np.argwhere( np.isnan(np_flowy2v) ) #print "NAN indices (visi-Y2U): ",np.argwhere( np.isnan(np_visiy2u) ) #print "NAN indices (visi-Y2V): ",np.argwhere( np.isnan(np_visiy2v) ) # tensor conversion predflow_y2u_t = torch.from_numpy( np_flowy2u ).to(device=device).requires_grad_() predflow_y2v_t = torch.from_numpy( np_flowy2v ).to(device=device).requires_grad_() trueflow_y2u_t = torch.from_numpy( np_trueflowy2u ).to(device=device).requires_grad_() trueflow_y2v_t = torch.from_numpy( np_trueflowy2v ).to(device=device).requires_grad_() truevisi_y2u_t = torch.from_numpy( np_visiy2u ).to(device=device) truevisi_y2v_t = torch.from_numpy( np_visiy2v ).to(device=device) #print "requires grad: ",predflow_y2u_t.requires_grad,predflow_y2v_t.requires_grad #y2u_t = predflow_y2u_t #y2v_t = predflow_y2v_t y2u_t = trueflow_y2u_t y2v_t = trueflow_y2v_t source_origin = torch.zeros( (1) ).to(device=device) targetu_origin = torch.zeros( (1) ).to(device=device) targetv_origin = torch.zeros( (1) ).to(device=device) for b in xrange(1): source_origin[0] = source_meta.min_x() targetu_origin[0] = targetu_meta.min_x() targetv_origin[0] = targetv_meta.min_x() posyz_fromy2u,posyz_fromy2v = IntersectUB.apply( y2u_t, y2v_t, source_origin, targetu_origin, targetv_origin ) mask = truevisi_y2u_t*truevisi_y2v_t diff = (posyz_fromy2u-posyz_fromy2v) #print "diff.shape=",diff.shape #print "mask.shape=",mask.shape diff[:,0,:,:] *= mask[:,0,:,:] diff[:,1,:,:] *= mask[:,0,:,:] l2 = diff[:,0,:,:]*diff[:,0,:,:] + diff[:,1,:,:]*diff[:,1,:,:] #print "l2 shape: ",l2.shape if mask.sum()>0: lossval = l2.sum()/mask.sum() else: lossval = l2.sum() # backward test tback = time.time() lossval.backward() print " runbackward: ",time.time()-tback," secs" print "Loss (iter {}): {}".format(ientry,lossval.item())," iscuda",lossval.is_cuda dloss[0] = lossval.item() dtime[0] = time.time()-tentry ttest.Fill() end = time.time() tloss = end-start print "Time: ",tloss," secs / ",tloss/nentries," secs per event" rout.cd() ttest.Write() rout.Close()

48.735736

182

0.644217

956dfd3898d4db0373cc4caa6c858737d336c6e2

3,270

py

Python

simple_api/object/permissions.py

ladal1/simple_api

1b5d560476bccad9f68a7331d092dbdb68c48bf7

[ "MIT" ]

1

2021-02-24T22:14:59.000Z

simple_api/object/permissions.py

ladal1/simple_api

1b5d560476bccad9f68a7331d092dbdb68c48bf7

[ "MIT" ]

null

simple_api/object/permissions.py

ladal1/simple_api

1b5d560476bccad9f68a7331d092dbdb68c48bf7

[ "MIT" ]

null

from inspect import isclass

34.0625

119

0.663609

95728ec4185daad9b5e30451603845ad35ca972b

290

py

Python

Desafios/MODULO 1/Desafio 12.py

deneyjunior/python-mundos-cev

4bc82bf0630f65cf66e5442ae57b72fd4b0207fc

[ "MIT" ]

null

Desafios/MODULO 1/Desafio 12.py

deneyjunior/python-mundos-cev

4bc82bf0630f65cf66e5442ae57b72fd4b0207fc

[ "MIT" ]

null

Desafios/MODULO 1/Desafio 12.py

deneyjunior/python-mundos-cev

4bc82bf0630f65cf66e5442ae57b72fd4b0207fc

[ "MIT" ]

null

# Faa um algoritmo que leia o preo de um produto e mostre o novo preo com um desconto. preco = float(input('Digite o preo atual do produto: R$ ')) desconto = float(input('Digite o valor do desconto (0.X): ')) novopreco = preco * desconto print('O novo preo R$ {}.'.format(novopreco))

58

89

0.713793

957446e0b2daddda7b2cb6fdb76915dc45c186cf

1,188

py

Python

test.py

Ericqle/Senior-Design-Project

aa8e2134b26aef151d3736d306a4fbc9fe69790e

[ "MIT" ]

null

test.py

Ericqle/Senior-Design-Project

aa8e2134b26aef151d3736d306a4fbc9fe69790e

[ "MIT" ]

null

test.py

Ericqle/Senior-Design-Project

aa8e2134b26aef151d3736d306a4fbc9fe69790e

[ "MIT" ]

null

from draw_control import DrawControl if __name__ == '__main__': zotter = DrawControl() test = input("track, rail, pen, hor, ver, diag: ") while(test): if test == "track": dir_in = input('dir step: ') dir = dir_in.split(" ") zotter.track.spin_fixed_step(int(dir[0]), int(dir[1])) elif test == "rail": dir_in = input('dir step: ') dir = dir_in.split(" ") zotter.rail.spin_fixed_step(int(dir[0]), int(dir[1])) elif test == "pen": angle = float(input("angle: ")) zotter.pen_holder.turn_angle(angle) elif test == "hor": steps = input('steps: ') s = int(steps) zotter.draw_hor_line(0, s) elif test == "ver": steps = input('steps: ') s = int(steps) zotter.draw_ver_line(0, s) elif test == "diag": dir_in = input('dir1 dir2 steps1 steps2: ') dir = dir_in.split(" ") zotter.draw_diagonal(int(dir[0]), int(dir[1]), int(dir[2]), int(dir[3])) test = input("track, rail, pen, hor, ver, diag: ") zotter.close_board()

29.7

84

0.505051

95770242fba26f6f07dd35c5f3e789a8b70b5318

2,961

py

Python

fcos/datasets/cityscapes.py

rosshemsley/fcos

de30bb2c78df54cae6814282c7166beed333d34c

[ "MIT" ]

5

2020-08-02T11:03:25.000Z

2021-12-12T19:37:09.000Z

fcos/datasets/cityscapes.py

rosshemsley/fcos

de30bb2c78df54cae6814282c7166beed333d34c

[ "MIT" ]

null

fcos/datasets/cityscapes.py

rosshemsley/fcos

de30bb2c78df54cae6814282c7166beed333d34c

[ "MIT" ]

1

2021-03-05T12:19:48.000Z

import pathlib import logging from torch import nn import numpy as np import torch import torch.functional as F import torchvision.transforms as T from torch.utils.data import Dataset from torchvision.datasets.cityscapes import Cityscapes import cv2 from torchvision.transforms import ToPILImage from torch.utils.data import DataLoader from torchvision.transforms import ( RandomResizedCrop, RandomHorizontalFlip, Normalize, RandomErasing, Resize, ToTensor, RandomAffine, Compose, ColorJitter, ) logger = logging.getLogger(__name__) from enum import Enum def collate_fn(batch): return ( torch.stack([b[0] for b in batch], dim=0), [b[1] for b in batch], [b[2] for b in batch], ) def tensor_to_image(t) -> np.ndarray: """ Return a PIL image (RGB) """ img = Compose([ToPILImage(),])(t) return np.array(img) def _poly_to_labels(image_tensor, poly): _, img_height, img_width = image_tensor.shape # TODO(Ross): fix this. h = poly["imgHeight"] w = poly["imgWidth"] scaling = img_height / h box_labels = [] class_labels = [] for obj in poly["objects"]: if obj["label"] == "car": polygon = obj["polygon"] min_x = min(x for x, _ in polygon) * scaling max_x = max(x for x, _ in polygon) * scaling max_y = max(y for _, y in polygon) * scaling min_y = min(y for _, y in polygon) * scaling box_labels.append(torch.FloatTensor([min_x, min_y, max_x, max_y])) class_labels.append(torch.IntTensor([1])) if len(class_labels) == 0: return torch.zeros((0, 1)), torch.zeros(0, 4) return torch.stack(class_labels), torch.stack(box_labels) def _get_split(split_name: str) -> Split: if split_name is Split.TEST: return "test" elif split_name is Split.VALIDATE: return "val" elif split_name is Split.TRAIN: return "train" else: raise ValueError(f"unknown split kind {split_name}")

24.882353

90

0.628842

957893734aaf183904dce73b5e054520162c5d69

11,838

py

Python

flask_jquery/app.py

lmj0328/SocialMediaReport

555aa3551844b5ee67bcf9296d574fd99977982d

[ "MIT" ]

1

2021-02-28T05:01:37.000Z

flask_jquery/app.py

lmj0328/SocialMediaReport

555aa3551844b5ee67bcf9296d574fd99977982d

[ "MIT" ]

null

flask_jquery/app.py

lmj0328/SocialMediaReport

555aa3551844b5ee67bcf9296d574fd99977982d

[ "MIT" ]

1

2020-03-12T02:08:10.000Z

from flask import Flask, render_template, request, jsonify from flask import request from flask import Response from flask import url_for from flask import jsonify import GetOldTweets3 as got import pandas as pd import datetime import numpy as np import requests import json from pyquery import PyQuery as pq app = Flask(__name__) if __name__ == '__main__': app.run(debug=True, threaded=True)

41.391608

755

0.598496