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paulo037
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starcoder

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IAFNNESTA.py
JonathanAlis/IAFNNESTA
3
4124
def help(): return ''' Isotropic-Anisotropic Filtering Norm Nesterov Algorithm Solves the filtering norm minimization + quadratic term problem Nesterov algorithm, with continuation: argmin_x || iaFN(x) ||_1/2 subjected to ||b - Ax||_2^2 < delta If no filter is provided, solves the L1. Continuation is performed by sequentially applying Nesterov's algorithm with a decreasing sequence of values of mu0 >= mu >= muf The observation matrix A must be a projector (non projector not implemented yet) Inputs: IAFNNESTA(b, #Observed data, a m x 1 array A=identity,At=identity, # measurement matrix and adjoint (either a matrix, function handles) muf=0.0001, #final mu value, smaller leads to higher accuracy delta, #l2 error bound. This enforces how close the variable #must fit the observations b, i.e. || y - Ax ||_2 <= delta #If delta = 0, enforces y = Ax #delta = sqrt(m + 2*sqrt(2*m))*sigma, where sigma=std(noise). L1w=1,L2w=0, #weights of L1 (anisotropic) and L2(isotropic) norms verbose=0, #whether to print internal steps maxit=1000, #maximum iterations at the inner loop x0=[], #initial solution, if not provided, will be At(b) U=identity,Ut=identity, #Analysis/Synthesis operators stopTest=1, #stopTest == 1 : stop when the relative change in the objective function is less than TolVar stopTest == 2 : stop with the l_infinity norm of difference in the xk variable is less than TolVar TolVar = 1e-5, #tolerance for the stopping criteria AAtinv=[], #not implemented normU=1, #if U is provided, this should be norm(U) H=[],Ht=[]): #filter operations in sparse matrix form #also accepts the string 'tv' as input, #in that case, calculates the tv norm Outputs: return xk, #estimated x reconstructed signal niter, #number of iterations residuals #first column is the residual at every step, #second column is the value of f_mu at every step ''' import IAFNNesterov import numpy as np from scipy import sparse import fil2mat def identity(x): return x def IAFNNESTA(b,sig_size=0,A=identity,At=identity,muf=0.0001,delta=0,L1w=1,L2w=0,verbose=0,MaxIntIter=5,maxit=1000,x0=[],U=identity,Ut=identity,stopTest=1,TolVar = 1e-5,AAtinv=[],normU=1,H=[]): if delta<0: raise Exception('Delta must not be negative') if not callable(A): #If not function A=lambda x:np.matmul(A,x) At=lambda x:np.matmul(np.transpose(A),x) b=b.reshape((-1,1)) Atb=At(b) if sig_size==0: sig_size=Atb.shape if callable(AAtinv): AtAAtb = At( AAtinv(b) ) else: if len(AAtinv)>0: AAtinv=lambda x: np.matmul(AAtinv,x) AtAAtb = At( AAtinv(b) ) else: #default AtAAtb = Atb AAtinv=identity if len(x0)==0: x0 = AtAAtb if len(H)==0: Hf=identity Hft=identity else: if not sparse.issparse(H): if isinstance(H, str): if H=='tv': hs=[] hs.append(np.array([[1,-1]])) hs.append(np.array([[1],[-1]])) H,_,_,_=fil2mat.fil2mat(hs,sig_size) else: print('H not recognized. Must be a sparse matrix, a list of filters or the string tv') else: #list of filters: H,_,_,_=fil2mat.fil2mat(H,sig_size) #print(H.shape) #print(H) #print(type(H)) Ht=H.transpose() Hf=lambda x: H@x Hft=lambda x: Ht@x HU=lambda x: Hf(U(x)) UtHt=lambda x: Ut(Hft(x)) typemin='' if L1w>0: typemin+="iso" if L2w>0: typemin+="aniso" typemin+='tropic ' if callable(H): typemin+='filtering norm ' mu0=0 if L1w>0: mu0+=L1w*0.9*np.max(np.linalg.norm(HU(x0),1)) if L2w>0: mu0+=L2w*0.9*np.max(np.linalg.norm(HU(x0),2)) niter = 0 Gamma = np.power(muf/mu0,1/MaxIntIter) mu = mu0 Gammat= np.power(TolVar/0.1,1/MaxIntIter) TolVar = 0.1 for i in range(MaxIntIter): mu = mu*Gamma TolVar=TolVar*Gammat; if verbose>0: #if k%verbose==0: print("\tBeginning %s Minimization; mu = %g\n" %(typemin,mu)) xk,niter_int,res = IAFNNesterov.IAFNNesterov(b,A=A,At=At,mu=mu,delta=delta,L1w=L1w,L2w=L2w,verbose=verbose,maxit=maxit,x0=x0,U=U,Ut=Ut,stopTest=stopTest,TolVar = TolVar,AAtinv=AAtinv,normU=normU,H=Hf,Ht=Hft) xplug = xk niter = niter_int + niter if i==0: residuals=res else: residuals = np.vstack((residuals, res)) return xk.reshape(sig_size) if __name__ == "__main__": print(help())
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src/main.py
Merk0ff/PicRandomFromImgur
0
46128
import urllib.request import random import time import os from bs4 import BeautifulSoup chars = ["A","B","C","D","E","F","G","H","I","J","K","L","M","N","O","P","Q","R","S","T","U","V","W","X","Y","Z","a","b","c","d","e","f","g","h","i","j","k","l","m","n","o","p","q","r","s","t","u","v","w","x","y","z","0","1","2","3","4","5","6","7","8","9"] def GenerateUrl_postfix(): return random.choice(chars) + random.choice(chars) + random.choice(chars) + random.choice(chars) \ + random.choice(chars) def GenerateUrl(): url = 'https://imgur.com/' + GenerateUrl_postfix() try: urllib.request.urlopen(url, timeout=1) except urllib.error.URLError as e: print(url + " : " + str(e)) return -1 return url def GetImg( url ): try: html = urllib.request.urlopen(url, timeout=1) except urllib.error.URLError as e: print(url + ' : ' + str(e)) return soup = BeautifulSoup(html, "html.parser") img_src = soup.img['src'] if len(img_src) > 0: ex = img_src[14:] try: urllib.request.urlretrieve("https:" + img_src, "img/file_" + ex) except urllib.error.URLError as e: print("Some hell is going on: " + str(e)) def LoadProxy(): list = [] with open("./src/proxy.list", "r") as file: for line in file: list.append(line[0:-2]) return list def ConnectToProxy( proxy ): proxy = urllib.request.ProxyHandler({'http': proxy}) opener = urllib.request.build_opener(proxy) urllib.request.install_opener(opener) print("Proxy changed") def main(): i = 0 elem = 1 Plist = LoadProxy() ConnectToProxy(Plist[0]) while not False: if i >= 10: ConnectToProxy(Plist[elem]) elem += 1 if elem >= len(Plist): elem = 0 i = 0 url = GenerateUrl() if url != -1: GetImg(url) with open("log.txt", "a") as file: file.write(url + "\n") i += 1 time.sleep(0.1) if not os.path.exists("img"): os.makedirs("img") main()
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tests/test_successful_registration.py
jg-725/IS219-FlaskAppProject
0
158118
"""This test's if user successfully registered """ def test_successful_register(successful_registration): assert successful_registration.email == '<EMAIL>' assert successful_registration.password == 'Password' assert successful_registration.confirm == 'Password' response = successful_registration.get("/dashboard") assert response.status_code == 302 assert b'Congrats, registration success' in response.data
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Utils/Matrix.py
valavanisleonidas/Machine_Learning_Toolkit
0
10763
<reponame>valavanisleonidas/Machine_Learning_Toolkit import os import platform import numpy class Matrix: def __init__(self): if platform.system() == "Windows": self.delimiterForPath = "\\" else: self.delimiterForPath = "/" self.labelsDType = numpy.int32 self.imagesDType = numpy.float32 def deleteRows(self, array, rows, axis): return numpy.delete(array, rows, axis) def swapAxes(self, array, axe1, axe2): return numpy.swapaxes(array, axe1, axe2) def getImageCategoryFromPath(self, imagePath): # path in format : ..\\Category\\ImageName return numpy.array(imagePath.split(self.delimiterForPath, len(imagePath))[ len(imagePath.split(self.delimiterForPath, len(imagePath))) - 2], dtype=self.labelsDType) def getNumberOfClasses(self, array): return len(numpy.unique(array)) def getImagesInDirectory(self, folderPath, extensions=('.jpg', '.jpeg', '.png', '.bmp', '.gif')): imagesList = [] assert os.path.isdir(folderPath), 'No folder with that name exists : %r ' % folderPath # for all images in folder path for root, dirs, files in os.walk(folderPath): for name in files: if name.endswith(extensions): imagesList.append(root + self.delimiterForPath + name) return imagesList def addDimension(self, array, axis): return numpy.expand_dims(a=array, axis=axis) def ExtractImages(self, folderPath, image_size=(256, 256), convertion=None, imageChannels=3, preprocessImages=False ,normalize=True ,normalizeRange=(0,1) ): from Images.ImageProcessing import ImageProcessing imageList = self.getImagesInDirectory(folderPath=folderPath) assert len(imageList) > 0, 'No images in folder : %r' % folderPath if convertion != "Grayscale" and imageChannels != 3: if convertion == None: convertion = "RGB" raise ValueError(' %r supports only 3 image channels!' % convertion) images_list = [] labels_list = [] # for all images in folder path for imagePath in imageList: # get category of image and add category to array labels_list.append( self.getImageCategoryFromPath(imagePath=imagePath)) # get image array and add image to array images_list.append( ImageProcessing().getImageArray(imagePath=imagePath, imageSize=image_size, convertion=convertion, imageChannels=imageChannels,preprocessImages=preprocessImages, Normalize=normalize,NormalizeRange=normalizeRange)) # convert lists to numpy array allLabelsArray = numpy.array(labels_list).reshape(len(labels_list)) allImagesArray = numpy.array(images_list).reshape(len(imageList), imageChannels, image_size[0], image_size[1]) return [allImagesArray, allLabelsArray] # returns batches from data with size batchSize def chunker(self,data, batchSize): return (data[pos:pos + batchSize] for pos in xrange(0, len(data), batchSize)) def shuffleMatrix(self,array): numpy.random.shuffle(array) def shuffleMatrixAlongWithLabels(self, array1, array2): # shuffle array1 (images) with corresponding labels array2 from random import shuffle array1_shuf = [] array2_shuf = [] index_shuf = range(len(array1)) shuffle(index_shuf) for i in index_shuf: array1_shuf.append(array1[i]) array2_shuf.append(array2[i]) return [numpy.array(array1_shuf, dtype=self.imagesDType).astype('float32'), numpy.array(array2_shuf, dtype=self.labelsDType).astype('float32')] def TakeExamplesFromEachCategory(self,features,labels,maxImagesPerCategory=10): import gc import os validationArray = [] validation_labels=[] # for 0 to number of output classes for index in range(0,self.getNumberOfClasses(labels)): print ('mpika 1') # find indexes of category index indexes = numpy.where(labels == index) # if train has 1 instance don't take it for validation if len(indexes[0]) in [ 0 , 1 ]: continue # if instances are less than max categories given if len(indexes[0]) <= maxImagesPerCategory: # take half for validation maxImagesPerCategory= len(indexes[0])/2 print ('mpika 2') assert len(indexes[0]) >= maxImagesPerCategory ,\ "Error : Validation examples per category more than train instances. Category: {0}" \ " validation pes category : {1} , training examples : {2} ".format(index,maxImagesPerCategory,len(indexes[0]),) count = 0 # for indexes in category for catIndex in indexes[0]: print ('mpika 3') count +=1 if count > maxImagesPerCategory: print ('mpika 3.1') break print ('mpika 3.2') validationArray.append(features[catIndex]) print ('mpika 3.3') validation_labels.append(labels[catIndex ]) print ('mpika 3.4 catIndex' , catIndex) features = numpy.delete(features,catIndex,axis=0) print ('mpika 3.5') labels = numpy.delete(labels,catIndex,axis=0) print ('mpika 3.6') gc.collect() print ('mpika 4') return [features, numpy.array(validationArray,dtype=self.imagesDType).astype('float32'), labels, numpy.array(validation_labels,dtype=self.labelsDType).astype('int32')] def takeLastExamples(self,trainArray, train_labels, validationPercentage=.2): # take validationPercentage of training data for validation validationExamples = int(validationPercentage * len(trainArray)) # We reserve the last validationExamples training examples for validation. trainArray, validationArray = trainArray[:-validationExamples], trainArray[-validationExamples:] train_labels, validation_labels = train_labels[:-validationExamples], train_labels[-validationExamples:] return [trainArray, validationArray, train_labels, validation_labels] def SplitTrainValidation(self, trainArray, train_labels, validationPercentage=.2,takeLastExamples=False,maxImagesPerCategory=10): if takeLastExamples: return self.takeLastExamples(trainArray, train_labels, validationPercentage) else: return self.TakeExamplesFromEachCategory(trainArray, train_labels,maxImagesPerCategory) def moveFile(self, src, dest): import shutil shutil.move(src, dest) if __name__ == '__main__': trainFolder = 'C:\Users\l.valavanis\Desktop\Clef2013\TrainSet' testFolder = 'C:\Users\l.valavanis\Desktop\Clef2013\TestSet' # # trainFolder = 'C:\Users\l.valavanis\Desktop\Clef2013\SampleImages - Copy' # testFolder = 'C:\Users\l.valavanis\Desktop\Clef2013\SampleImages - Copy - Copy' # # # trainFolder = '/home/leonidas/Desktop/images/train' # # testFolder = '/home/leonidas/Desktop/images/test' # # [trainArray, train_labels, testArray, test_labels, validationArray, validation_labels, outputClasses] = \ # load_dataset(trainFolder, testFolder,imageSize=(3,3),convertion='L',imageChannels=1) # # print trainArray.shape # print trainArray # # print validation_labels # # print train_labels # # print trainArray # # print trainArray.shape # print train_labels.shape # print testArray.shape # print test_labels.shape # print validationArray.shape # print validation_labels.shape # # trainPath = 'C:\\Users\\l.valavanis\\Desktop\\Clef2013\\GBoC\Features\\train_2x2_CIELab_512.txt' # testPath = 'C:\\Users\\l.valavanis\\Desktop\\Clef2013\\GBoC\Features\\test_2x2_CIELab_512.txt' # trainLabelPath = 'C:\\Users\\l.valavanis\\Desktop\\Clef2013\\GBoC\Features\\train_2x2_CIELab_512_labels.txt' # testLabelPath = 'C:\\Users\\l.valavanis\\Desktop\\Clef2013\\GBoC\Features\\test_2x2_CIELab_512_labels.txt' # [trainArray, train_labels, testArray, test_labels, validationArray, validation_labels, # outputClasses] = loadFeatures(trainPath=trainPath, trainLabels=trainLabelPath, testPath=testPath, # testLabels=testLabelPath); i=0; for trainArray,train_labels in Matrix().getArrayOfImagesUsingMiniBatches(folderPath=trainFolder,image_size=(100,100),batch_size=15): print (trainArray.shape) print (train_labels.shape) i+=len(trainArray) print "aaasdasdas d : ",i # # print validation_labels # # print train_labels # # print trainArray # # print trainArray.shape # print train_labels.shape # print testArray.shape # print test_labels.shape # print validationArray.shape # print validation_labels.shape
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tests/test_wsgi.py
invenio-toaster/invenio-base
3
121959
<reponame>invenio-toaster/invenio-base # -*- coding: utf-8 -*- # # This file is part of Invenio. # Copyright (C) 2015-2018 CERN. # # Invenio is free software; you can redistribute it and/or modify it # under the terms of the MIT License; see LICENSE file for more details. """Test wsgi application.""" from __future__ import absolute_import, print_function import json import pytest from flask import Flask, jsonify, request from packaging import version from werkzeug import __version__ as werkzeug_version from invenio_base.wsgi import create_wsgi_factory, wsgi_proxyfix def test_create_wsgi_factory(): """Test wsgi factory creation.""" api = Flask('api') @api.route('/') def apiview(): return 'api' app = Flask('app') @app.route('/') def appview(): return 'app' # Test factory creation factory = create_wsgi_factory({'/api': lambda **kwargs: api}) app.wsgi_app = factory(app) with app.test_client() as client: assert client.get('/').status_code == 200 assert b'app' in client.get('/').data assert client.get('/api/').status_code == 200 assert b'api' in client.get('/api/').data @pytest.mark.parametrize('proxies,data', [ (2, b'4.3.2.1'), (None, b'1.2.3.4') ]) def test_proxyfix_wsgi_proxies(proxies, data): """Test wsgi factory creation.""" app = Flask('app') app.config['WSGI_PROXIES'] = proxies @app.route('/') def appview(): return str(request.remote_addr) # Test factory creation app.wsgi_app = wsgi_proxyfix()(app) e = {'REMOTE_ADDR': '1.2.3.4'} with app.test_client() as client: h = {'X-Forwarded-For': '5.6.7.8, 4.3.2.1, 8.7.6.5'} assert client.get('/', headers=h, environ_base=e).data == data @pytest.mark.parametrize( 'num_proxies,proxy_config', [ (n, {'x_for': n, 'x_proto': n, 'x_host': n, 'x_port': n, 'x_prefix': n}) for n in range(2)]) def test_proxyfix_wsgi_config(num_proxies, proxy_config): """Test wsgi factory creation with APP_WSGI_CONFIG set.""" if version.parse(werkzeug_version) < version.parse('0.15.0'): pytest.skip("Unsupported configuration for Werkzeug<0.15.0") app = Flask('app') app.config['PROXYFIX_CONFIG'] = proxy_config data = [ # application instance { 'x_for': '1.2.3.4', 'x_proto': 'http', 'x_host': 'localhost', 'x_port': '80', 'x_prefix': '', }, # proxy number 1 { 'x_for': '5.6.7.8', 'x_proto': 'https', 'x_host': 'host.external', 'x_port': '443', 'x_prefix': 'prefix.external', } ] @app.route('/') def appview(): data = { 'x_for': request.environ.get('REMOTE_ADDR'), 'x_proto': request.environ.get('wsgi.url_scheme'), 'x_host': request.environ.get('SERVER_NAME'), 'x_port': request.environ.get('SERVER_PORT'), 'x_prefix': request.environ.get('SCRIPT_NAME') } return jsonify(data) # Test factory creation app.wsgi_app = wsgi_proxyfix()(app) e = { 'REMOTE_ADDR': data[0].get('x_for'), 'wsgi.url_scheme': data[0].get('x_proto'), 'HTTP_HOST': data[0].get('x_host'), 'SERVER_PORT': data[0].get('x_port'), 'SCRIPT_NAME': data[0].get('x_prefix'), } with app.test_client() as client: h = { 'X-Forwarded-For': data[1].get('x_for'), 'X-Forwarded-Proto': data[1].get('x_proto'), 'X-Forwarded-Host': data[1].get('x_host'), 'X-Forwarded-Port': data[1].get('x_port'), 'X-Forwarded-Prefix': data[1].get('x_prefix'), } res = client.get('/', headers=h, environ_base=e) assert json.loads(res.get_data(as_text=True)) == data[num_proxies]
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tests/test_utils.py
marianoleonardo/device-manager
14
1608219
<reponame>marianoleonardo/device-manager import pytest import json import unittest from flask import Flask from DeviceManager.utils import format_response, get_pagination, get_allowed_service, decrypt, retrieve_auth_token from DeviceManager.utils import HTTPRequestError from .token_test_generator import generate_token class Request: def __init__(self, data): self.headers = data['headers'] self.args = data['args'] self.data = data['body'] class TestUtils(unittest.TestCase): app = Flask(__name__) def test_format_response(self): with self.app.test_request_context(): result = format_response(200, 'Unity test of message formatter') self.assertEqual(result.status, '200 OK') self.assertEqual(json.loads(result.response[0])[ 'message'], 'Unity test of message formatter') result = format_response(202) self.assertEqual(result.status, '202 ACCEPTED') self.assertEqual(json.loads(result.response[0])['message'], 'ok') result = format_response(404) self.assertEqual(result.status, '404 NOT FOUND') self.assertEqual(json.loads(result.response[0])[ 'message'], 'Request failed') def test_get_pagination(self): args = {'page_size': 10,'page_num': 1} req = {'headers': {'authorization': generate_token()},'args': args,'body': ''} page, per_page = get_pagination(Request(req)) self.assertEqual(page, 1) self.assertEqual(per_page, 10) with self.assertRaises(HTTPRequestError): args = {'page_size': 10,'page_num': 0} req = {'headers': {'authorization': generate_token()},'args': args,'body': ''} page, per_page = get_pagination(Request(req)) with self.assertRaises(HTTPRequestError): args = {'page_size': 0,'page_num': 2} req = {'headers': {'authorization': generate_token()},'args': args,'body': ''} page, per_page = get_pagination(Request(req)) def test_get_allowed_service(self): token = generate_token() with self.assertRaises(ValueError): get_allowed_service(None) result = get_allowed_service(token) self.assertIsNotNone(result) self.assertEqual(result, 'admin') with self.assertRaises(ValueError): get_allowed_service('Is.Not_A_Valid_Token') def test_decrypt(self): result = decrypt(b"\xa97\xa4o\xba\xddx\xe0\xe9\x8f\xe2\xc4V\x85\xf7'") self.assertEqual(result, b'') with self.assertRaises(ValueError): result = decrypt('12345678') def test_retrieve_auth_token(self): token = generate_token() req = {'headers': {'authorization': token},'args': '','body': ''} result = retrieve_auth_token(Request(req)) self.assertIsNotNone(result) self.assertEqual(result, token) with self.assertRaises(HTTPRequestError): req = {'headers': {},'args': '','body': ''} result = retrieve_auth_token(Request(req))
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tests/serve/test_metadata.py
outerbounds/tempo
75
33100
<reponame>outerbounds/tempo import pytest from tempo.serve.metadata import KubernetesRuntimeOptions @pytest.mark.parametrize( "runtime, replicas", [ ({"replicas": 2}, 2), ({}, 1), ], ) def test_runtime_options(runtime, replicas): r = KubernetesRuntimeOptions(**runtime) assert r.replicas == replicas
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ubi_api/api/models.py
rzhang74/Ubi
0
127996
from django.db import models from django.utils import timezone from django.contrib.auth.models import User # Create your models here. class Tag(models.Model): tid = models.AutoField(primary_key=True) name = models.CharField(max_length=100) class Video(models.Model): vid = models.AutoField(primary_key=True) name = models.CharField(max_length=100) address = models.CharField(max_length=300) thumbnail_address = models.CharField(max_length=300, default='/video.jpg') description = models.TextField(null=True) category = models.CharField(max_length=50) user = models.ForeignKey(User, on_delete=models.CASCADE, db_column="user") like = models.ManyToManyField(User, related_name="userLikeVideos") dislike = models.ManyToManyField(User, related_name="userDislikeVideos") tag = models.ManyToManyField(Tag, related_name="tagVideos") class Comment(models.Model): cid = models.AutoField(primary_key=True) vid = models.ForeignKey(Video, on_delete=models.CASCADE, db_column="vid") user = models.ForeignKey(User, on_delete=models.CASCADE, db_column="user") content = models.TextField() datetime = models.DateTimeField(auto_now_add=True) parent = models.ForeignKey("Comment", on_delete=models.CASCADE, db_column="p_cid", null=True) like = models.ManyToManyField(User, related_name="userLikeComments") dislike = models.ManyToManyField(User, related_name="userDisLikeComments") class Follow(models.Model): fid = models.AutoField(primary_key=True) follower = models.ForeignKey(User, on_delete=models.CASCADE, db_column="follower", related_name="user") user = models.ForeignKey(User, on_delete=models.CASCADE, db_column="user", related_name="follower") class Meta: unique_together = ('user', 'follower',) class CommunityMessage(models.Model): cmid = models.AutoField(primary_key=True) user = models.ForeignKey(User, on_delete=models.CASCADE, db_column="user") message = models.TextField(null=False) datetime = models.DateTimeField(auto_now_add=True) imageAddr = models.CharField(max_length=300, null=True) videoAddr = models.CharField(max_length=300, null=True) like = models.ManyToManyField(User, related_name="userLikeMessages") dislike = models.ManyToManyField(User, related_name="userDislikeMessages") class PlayList(models.Model): pid = models.AutoField(primary_key=True) user = models.ForeignKey(User, on_delete=models.CASCADE, db_column="user") name = models.CharField(max_length=100) vid = models.ManyToManyField(Video, related_name="videoPlayists")
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examples/incremental_learning/helmet_detection/training/eval.py
lidongen/sedna
1
1611164
<reponame>lidongen/sedna<gh_stars>1-10 # Copyright 2021 The KubeEdge Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import logging import sedna from validate_utils import validate LOG = logging.getLogger(__name__) max_epochs = 1 def main(): # load dataset. test_data = sedna.load_test_dataset(data_format='txt', with_image=False) # read parameters from deployment config. class_names = sedna.context.get_parameters("class_names") class_names = [label.strip() for label in class_names.split(',')] input_shape = sedna.context.get_parameters("input_shape") input_shape = tuple(int(shape) for shape in input_shape.split(',')) model = validate sedna.incremental_learning.evaluate(model=model, test_data=test_data, class_names=class_names, input_shape=input_shape) if __name__ == '__main__': main()
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changestream_insert.py
thekitp/python-mongodb-changestream
0
122411
import os import pymongo import time import random client = pymongo.MongoClient(os.environ['CHANGE_STREAM_DB']) while True: print(client.changestream.collection.insert_one({"temperature": random.random() * 100}).inserted_id) time.sleep(0.050)
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config.py
Zloklun/telepot-monitor-bot
0
1614614
<filename>config.py #!/usr/bin/python3 # -*- coding: utf-8 *-* import asyncio as aio from os.path import join, dirname from telepot.aio.delegate import exception def sync_exec(coro): aio.ensure_future(coro) DEBUG = True DIR = dirname(__file__) TOKEN_FILE = join(DIR, 'TOKEN') WHITELIST_FILE = join(DIR, 'whitelist_ids') ADMINS_FILE = join(DIR, 'admin_ids') def log(*args, **kwargs): """Placeholder for log()""" pass if DEBUG: from sys import stderr def log(*args, **kwargs): """Print debug messages""" if 'category' in kwargs: tag = '[{}]'.format(kwargs['category']) del kwargs['category'] print(tag, *args, file=stderr) else: print(*args, file=stderr) # Filling whitelist WHITELIST = None try: with open(WHITELIST_FILE) as f: WHITELIST = list(map(int, f.read().split())) log('Whitelist:', WHITELIST, category='Misc') except IOError: log('Whitelist not found. Filtering is off') # Filling admin list ADMINS_LIST = None try: with open(ADMINS_FILE) as f: ADMINS_LIST = list(map(int, f.read().split())) log('Admins:', ADMINS_LIST, category='Misc') except IOError: log('Admins list have not found. No admins supported') # Some seeder functions def _wrap_none(fn): """ Stolen from telepot.aio.delegate.py :param fn: function to wrap :return: wrapped function """ def w(*args, **kwargs): try: return fn(*args, **kwargs) except (KeyError, exception.BadFlavor): return None return w def per_admin(): """ :return: a seeder function that returns the from id only if the from id is in the ``ADMINS_LIST``. If ADMINS_LIST is None, returns None. """ if ADMINS_LIST is not None: return _wrap_none(lambda msg: None) else: return _wrap_none(lambda msg: 1 # msg['from']['id'] if msg['from']['id'] in ADMINS_LIST else None)
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operations/subtraction.py
anon-cand/nexpreval
0
159225
<filename>operations/subtraction.py from operations.operation import Operation class Subtraction(Operation): """ Representing an operation to perform Subtraction """ TAG = 'subtraction' __slots__ = ('minuend', 'subtrahend') def __init__(self): self.minuend = None self.subtrahend = None def __hash__(self): return hash(self.minuend) ^ hash(self.subtrahend) def __call__(self): """ Perform the operation on operands :return: a number representing the outcome of operation or NaN """ if self.minuend is not None and self.subtrahend is not None: return self.minuend() - self.subtrahend() return self.NAN def add_operand(self, operand, tag): """ Add an operand for this operation """ if not isinstance(operand, Operation): raise TypeError("Operand of type Operator is expected") if tag not in self.__slots__: raise ValueError("Tag value cannot only be one of following: ", *self.__slots__) if tag == 'minuend': self.minuend = operand elif tag == 'subtrahend': self.subtrahend = operand
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models/TF/VAE.py
sankhaMukherjee/vae
0
66456
import os os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' import tensorflow as tf from tensorflow.keras.layers import Dense, Input from tensorflow.keras import Model, layers class Encoder(layers.Layer): def __init__(self, nLatent, layers, activations, name='encoder'): super(Encoder, self).__init__(name=name) self.layers = [ Dense(l, activation=a) for l, a in zip(layers, activations) ] self.mean = Dense(nLatent) self.logVar = Dense(nLatent) def call(self, inputs): # Go through the Dense layers x = inputs * 1 for dl in self.layers: x = dl(x) # Create the latent layer (z) zMean = self.mean(x) zLogVar = self.logVar(x) epsilon = tf.random.normal( shape=zMean.shape, mean=0, stddev=1 ) z = zMean + tf.exp( 0.5 * zLogVar )*epsilon return zMean, zLogVar, z class Decoder(layers.Layer): def __init__(self, nInp, layers, activations, name='encoder'): super(Decoder, self).__init__(name=name) layers = list(reversed(layers)) activations = list(reversed(activations)) self.layers = [ Dense(l, activation=a) for l, a in zip(layers, activations) ] self.result = Dense(nInp, activation=None) def call(self, inputs): # Go through the Dense layers x = inputs * 1 for dl in self.layers: x = dl(x) result = self.result(x) return result class VAE(Model): def __init__(self, nInp, layers, activations, nLatent, lr = 1e-3, name='vae'): super(VAE, self).__init__(name=name) self.nInp = nInp self.nLatent = nLatent self.encoder = Encoder(nLatent=nLatent, layers=layers, activations=activations) self.decoder = Decoder(nInp, layers=layers, activations=activations) self.optimizer = tf.keras.optimizers.Adam(learning_rate = lr) def call(self, inputs): zMean, zLogVar, z = self.encoder(inputs) reconstructed = self.decoder(z) return reconstructed def step(self, x): with tf.GradientTape() as tape: zMean, zLogVar, z = self.encoder(x) xHat = self.decoder( z ) # Reconstruction Loss reconLoss = tf.nn.sigmoid_cross_entropy_with_logits( x, xHat ) reconLoss = tf.reduce_sum( reconLoss, 1 ) reconLoss = tf.reduce_mean( reconLoss ) reconLoss = reconLoss # KL - divergence loss klLoss = - 0.5 * tf.reduce_sum(zLogVar - tf.square(zMean) - tf.exp(zLogVar) + 1, 1) klLoss = tf.reduce_mean( klLoss ) klLoss = klLoss # Calculate the total loss loss = reconLoss + 1e1*klLoss # Optimize grads = tape.gradient(loss, self.trainable_weights) self.optimizer.apply_gradients(zip(grads, self.trainable_weights)) return reconLoss.numpy(), klLoss.numpy(), loss.numpy() def checkpoint(self, folder): folder = os.path.join( folder, 'model', 'modelData' ) os.makedirs( folder, exist_ok=True ) self.save_weights( folder ) return
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src/focus/api.py
RogerRueegg/lvw-young-talents
1
22514
from . import models from . import serializers from rest_framework import viewsets, permissions class CompetitionViewSet(viewsets.ModelViewSet): """ViewSet for the Competition class""" queryset = models.Competition.objects.all() serializer_class = serializers.CompetitionSerializer permission_classes = [permissions.IsAuthenticated] class TrainingViewSet(viewsets.ModelViewSet): """ViewSet for the Training class""" queryset = models.Training.objects.all() serializer_class = serializers.TrainingSerializer permission_classes = [permissions.IsAuthenticated] class CompetitorViewSet(viewsets.ModelViewSet): """ViewSet for the Competitor class""" queryset = models.Competitor.objects.all() serializer_class = serializers.CompetitorSerializer permission_classes = [permissions.IsAuthenticated] class TrainingpresenceViewSet(viewsets.ModelViewSet): """ViewSet for the Trainingpresence class""" queryset = models.Trainingpresence.objects.all() serializer_class = serializers.TrainingpresenceSerializer permission_classes = [permissions.IsAuthenticated] class DriverViewSet(viewsets.ModelViewSet): """ViewSet for the Driver class""" queryset = models.Driver.objects.all() serializer_class = serializers.DriverSerializer permission_classes = [permissions.IsAuthenticated] class EventViewSet(viewsets.ModelViewSet): """ViewSet for the Event class""" queryset = models.Event.objects.all() serializer_class = serializers.EventSerializer permission_classes = [permissions.IsAuthenticated] class ResultViewSet(viewsets.ModelViewSet): """ViewSet for the Result class""" queryset = models.Result.objects.all() serializer_class = serializers.ResultSerializer permission_classes = [permissions.IsAuthenticated] class LocationViewSet(viewsets.ModelViewSet): """ViewSet for the Location class""" queryset = models.Location.objects.all() serializer_class = serializers.LocationSerializer permission_classes = [permissions.IsAuthenticated]
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PyPoll/main.py
laquita44/python-challenge
0
102910
import os import csv import collections from collections import Counter # variables in list candidate_votes = [] candidate_selection = [] # set File path file_path = os.path.join("..", "Resources", "election_data.csv") # set path for reader with open(file_path) as csvfile: csv_reader = csv.reader(csvfile, delimiter=",") # read the header row first csv_header = next(csv_reader) # loop through each row for row in csv_reader: candidate_votes.append(row[2]) # change list to ascending order list = sorted(candidate_votes) # arrange the sorted list arrange_list = list # count votes per candidate in ascending order to append to list candidate_count = Counter (arrange_list) candidate_selection.append(candidate_count.most_common()) # calculate the percentage of votes per candidate for choice in candidate_selection: holder_one = format((choice[0][1])*100/(sum(candidate_count.values())),'.3f') holder_two = format((choice[1][1])*100/(sum(candidate_count.values())),'.3f') holder_three = format((choice[2][1])*100/(sum(candidate_count.values())),'.3f') holder_four = format((choice[3][1])*100/(sum(candidate_count.values())),'.3f') # Print values, sum, and percentages position print("Election Results") print("-------------------------") print(f"Total Votes: {sum(candidate_count.values())}") print("-------------------------") print(f"{candidate_selection[0][0][0]}: {holder_one}% ({candidate_selection[0][0][1]})") print(f"{candidate_selection[0][1][0]}: {holder_two}% ({candidate_selection[0][1][1]})") print(f"{candidate_selection[0][2][0]}: {holder_three}% ({candidate_selection[0][2][1]})") print(f"{candidate_selection[0][3][0]}: {holder_four}% ({candidate_selection[0][3][1]})") print("-------------------------") print(f"Winner: {candidate_selection[0][0][0]}") print("-------------------------") # -->> Export results to text file voter_info_file = os.path.join("out_pypoll.txt") with open(voter_info_file, "w") as outfile: outfile.write("Election Results\n") outfile.write("-------------------------\n") outfile.write(f"Total Votes: {sum(candidate_count.values())}\n") outfile.write("-------------------------\n") outfile.write(f"{candidate_selection[0][0][0]}: {holder_one}% ({candidate_selection[0][0][1]})\n") outfile.write(f"{candidate_selection[0][1][0]}: {holder_two}% ({candidate_selection[0][1][1]})\n") outfile.write(f"{candidate_selection[0][2][0]}: {holder_three}% ({candidate_selection[0][2][1]})\n") outfile.write(f"{candidate_selection[0][3][0]}: {holder_four}% ({candidate_selection[0][3][1]})\n") outfile.write("-------------------------\n") outfile.write(f"Winner: {candidate_selection[0][0][0]}\n") outfile.write("-------------------------\n")
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29961, 29900, 3816, 29906, 3816, 29896, 29962, 11606, 29876, 1159, 30004, 13, 1678, 714, 1445, 29889, 3539, 29898, 29888, 29908, 29912, 29883, 5380, 403, 29918, 21731, 29961, 29900, 3816, 29941, 3816, 29900, 29962, 6177, 426, 7694, 29918, 17823, 10560, 21313, 29883, 5380, 403, 29918, 21731, 29961, 29900, 3816, 29941, 3816, 29896, 29962, 11606, 29876, 1159, 30004, 13, 1678, 714, 1445, 29889, 3539, 703, 2683, 1378, 2612, 29876, 1159, 30004, 13, 1678, 714, 1445, 29889, 3539, 29898, 29888, 29908, 29956, 3993, 29901, 29871, 426, 29883, 5380, 403, 29918, 21731, 29961, 29900, 3816, 29900, 3816, 29900, 29962, 1012, 29876, 1159, 30004, 13, 1678, 714, 1445, 29889, 3539, 703, 2683, 1378, 2612, 29876, 1159, 1678, 6756, 13, 2 ]
ar_app/scripts/renamefiles.py
osetr/ar-opencv-python
1
46276
import os from natsort import natsorted path_to_directory = input("Enter path to directory: ") + "/" new_name = input("Enter new name for files: ") try: i = 0 list_of_files = natsorted(os.listdir(path_to_directory)) for file in list_of_files: i += 1 extension = file.split(".")[1] os.rename( path_to_directory + file, path_to_directory + new_name + str(i) + "." + extension, ) except FileNotFoundError: print("Got unccorect directory path")
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mayan/apps/document_comments/search.py
wan1869/dushuhu
1
53608
from django.utils.translation import ugettext_lazy as _ from mayan.apps.documents.search import document_page_search, document_search document_page_search.add_model_field( field='document_version__document__comments__comment', label=_('Comments') ) document_search.add_model_field( field='comments__comment', label=_('Comments') )
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cachex/caches/__init__.py
malversoft/cachex
0
61655
<reponame>malversoft/cachex # -*- coding: utf-8 -*- """Memoizing cache classes.""" import sys from .Helper import Helper # Setup module as caches pool. this_module = sys.modules[__name__] Helper.setup_pool(this_module) # Expose all properties and methods a pool has. __all__ = list(this_module.add().__dict__) # Convert and expose all cache classes. from .. import standard Helper.with_module_cache_classes(standard, ( add, lambda kls: __all__.append(kls.__name__), )) del sys, Helper, this_module, standard
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app/middlewares/apikey_auth.py
meongbego/IOT_ADRINI
1
38940
<reponame>meongbego/IOT_ADRINI<filename>app/middlewares/apikey_auth.py<gh_stars>1-10 from functools import wraps from app.helpers.rest import * from app import redis_store from flask import request from app.models import model as db import hashlib def apikey_required(f): @wraps(f) def decorated_function(*args, **kwargs): if 'apikey' not in request.headers: return response(400, message=" Invalid access apikey ") else: access_token = db.get_by_id( table="tb_channels", field="channels_key", value=request.headers['apikey'] ) if not access_token: return response(400, message=" Invalid access apikey ") return f(*args, **kwargs) return decorated_function
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cuda/bench.py
wsmoses/XSBench-Enzyme
0
194483
<filename>cuda/bench.py import os import subprocess def run(OPTIMIZE, FORWARD, INLINE, NEWCACHE, AA, PHISTRUCT, TEMPLATIZE, VERIFY, runs): comp = subprocess.run(f'OPTIMIZE={OPTIMIZE} FORWARD={FORWARD} INLINE={INLINE} NEWCACHE={NEWCACHE} AA={AA} PHISTRUCT={PHISTRUCT} TEMPLATIZE={TEMPLATIZE} VERIFY={VERIFY} make -B -j', shell=True, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL) print(f'OPTIMIZE={OPTIMIZE} FORWARD={FORWARD} INLINE={INLINE} NEWCACHE={NEWCACHE} AA={AA} PHISTRUCT={PHISTRUCT} TEMPLATIZE={TEMPLATIZE} VERIFY={VERIFY} make -B -j') # comp = subprocess.run(f'OPTIMIZE={OPTIMIZE} FORWARD={FORWARD} INLINE={INLINE} NEWCACHE={NEWCACHE} AA={AA} PHISTRUCT={PHISTRUCT} TEMPLATIZE={TEMPLATIZE} VERIFY={VERIFY} make -B -j', shell=True) assert (comp.returncode == 0) out = {} for s in range(1, 2): size = 17000000 * s res = [] for i in range(runs): res.append(os.popen("CUDA_VISIBLE_DEVICES=1 ./XSBench -m event -k 0 -l " + str(size) + "| grep \"Runtime\" | grep -e \"[0-9\.]*\" -o").read().strip()) out[size] = res print(f'OPTIMIZE={OPTIMIZE} FORWARD={FORWARD} INLINE={INLINE} NEWCACHE={NEWCACHE} AA={AA} PHISTRUCT={PHISTRUCT} TEMPLATIZE={TEMPLATIZE}', "\t", "\t".join(res), flush=True) return res vars = ["OPTIMIZE", "INLINE", "NEWCACHE", "AA", "PHISTRUCT", "TEMPLATIZE" , "FORWARD"] def do(remain, set): if len(remain) == 0: print(set) run(**set) else: strue = set.copy() strue[remain[0]] = "yes" do(remain[1:], strue) sfalse = set.copy() sfalse[remain[0]] = "no" do(remain[1:], sfalse) do(vars[0:], {"runs":5, "VERIFY":"no"})
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scripts/portal/map915020100_PT.py
Snewmy/swordie
9
87766
<filename>scripts/portal/map915020100_PT.py<gh_stars>1-10 # Ariant Treasure Vault Entrance (915020100) => Ariant Treasure Vault if 2400 <= chr.getJob() <= 2412 and not sm.hasMobsInField(): sm.warp(915020101, 1) elif sm.hasMobsInField(): sm.chat("Eliminate all of the intruders first.")
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ops.py
taki0112/CIPS-Tensorflow
6
158570
from cuda.upfirdn_2d import * from cuda.fused_bias_act import fused_bias_act ################################################################################## # Layers ################################################################################## class Conv2D(tf.keras.layers.Layer): def __init__(self, fmaps, kernel, resample_kernel, up, down, gain, lrmul, **kwargs): super(Conv2D, self).__init__(**kwargs) self.fmaps = fmaps self.kernel = kernel self.gain = gain self.lrmul = lrmul self.up = up self.down = down self.k, self.pad0, self.pad1 = compute_paddings(resample_kernel, self.kernel, up, down, is_conv=True) def build(self, input_shape): weight_shape = [self.kernel, self.kernel, input_shape[1], self.fmaps] init_std, self.runtime_coef = compute_runtime_coef(weight_shape, self.gain, self.lrmul) # [kernel, kernel, fmaps_in, fmaps_out] w_init = tf.random.normal(shape=weight_shape, mean=0.0, stddev=init_std) self.w = tf.Variable(w_init, name='w', trainable=True) def call(self, inputs, training=None, mask=None): x = inputs w = self.runtime_coef * self.w # actual conv if self.up: x = upsample_conv_2d(x, w, self.kernel, self.kernel, self.pad0, self.pad1, self.k) elif self.down: x = conv_downsample_2d(x, w, self.kernel, self.kernel, self.pad0, self.pad1, self.k) else: x = tf.nn.conv2d(x, w, data_format='NCHW', strides=[1, 1, 1, 1], padding='SAME') return x class ModulatedConv2D(tf.keras.layers.Layer): def __init__(self, fmaps, style_fmaps, kernel, resample_kernel, up, down, demodulate, fused_modconv, gain, lrmul, **kwargs): super(ModulatedConv2D, self).__init__(**kwargs) assert not (up and down) self.fmaps = fmaps self.style_fmaps = style_fmaps self.kernel = kernel self.demodulate = demodulate self.up = up self.down = down self.fused_modconv = fused_modconv self.gain = gain self.lrmul = lrmul self.k, self.pad0, self.pad1 = compute_paddings(resample_kernel, self.kernel, up, down, is_conv=True) # self.factor = 2 self.mod_dense = Dense(self.style_fmaps, gain=1.0, lrmul=1.0, name='mod_dense') self.mod_bias = BiasAct(lrmul=1.0, act='linear', name='mod_bias') def build(self, input_shape): x_shape, w_shape = input_shape[0], input_shape[1] in_fmaps = x_shape[1] weight_shape = [self.kernel, self.kernel, in_fmaps, self.fmaps] init_std, self.runtime_coef = compute_runtime_coef(weight_shape, self.gain, self.lrmul) # [kkIO] w_init = tf.random.normal(shape=weight_shape, mean=0.0, stddev=init_std) self.w = tf.Variable(w_init, name='w', trainable=True) def scale_conv_weights(self, w): # convolution kernel weights for fused conv weight = self.runtime_coef * self.w # [kkIO] weight = weight[np.newaxis] # [BkkIO] # modulation style = self.mod_dense(w) # [BI] style = self.mod_bias(style) + 1.0 # [BI] weight *= style[:, np.newaxis, np.newaxis, :, np.newaxis] # [BkkIO] # demodulation d = None if self.demodulate: d = tf.math.rsqrt(tf.reduce_sum(tf.square(weight), axis=[1, 2, 3]) + 1e-8) # [BO] weight *= d[:, np.newaxis, np.newaxis, np.newaxis, :] # [BkkIO] return weight, style, d def call(self, inputs, training=None, mask=None): x, y = inputs # height, width = tf.shape(x)[2], tf.shape(x)[3] # prepare weights: [BkkIO] Introduce minibatch dimension # prepare convoultuon kernel weights weight, style, d = self.scale_conv_weights(y) if self.fused_modconv: # Fused => reshape minibatch to convolution groups x = tf.reshape(x, [1, -1, x.shape[2], x.shape[3]]) # weight: reshape, prepare for fused operation new_weight_shape = [tf.shape(weight)[1], tf.shape(weight)[2], tf.shape(weight)[3], -1] # [kkI(BO)] weight = tf.transpose(weight, [1, 2, 3, 0, 4]) # [kkIBO] weight = tf.reshape(weight, shape=new_weight_shape) # [kkI(BO)] else: # [BIhw] Not fused => scale input activations x *= style[:, :, tf.newaxis, tf.newaxis] # Convolution with optional up/downsampling. if self.up: x = upsample_conv_2d(x, weight, self.kernel, self.kernel, self.pad0, self.pad1, self.k) elif self.down: x = conv_downsample_2d(x, weight, self.kernel, self.kernel, self.pad0, self.pad1, self.k) else: x = tf.nn.conv2d(x, weight, data_format='NCHW', strides=[1, 1, 1, 1], padding='SAME') # Reshape/scale output if self.fused_modconv: # Fused => reshape convolution groups back to minibatch x_shape = tf.shape(x) x = tf.reshape(x, [-1, self.fmaps, x_shape[2], x_shape[3]]) elif self.demodulate: # [BOhw] Not fused => scale output activations x *= d[:, :, tf.newaxis, tf.newaxis] return x class Dense(tf.keras.layers.Layer): def __init__(self, fmaps, gain=1.0, lrmul=1.0, **kwargs): super(Dense, self).__init__(**kwargs) self.fmaps = fmaps self.gain = gain self.lrmul = lrmul def build(self, input_shape): fan_in = tf.reduce_prod(input_shape[1:]) weight_shape = [fan_in, self.fmaps] init_std, self.runtime_coef = compute_runtime_coef(weight_shape, self.gain, self.lrmul) w_init = tf.random.normal(shape=weight_shape, mean=0.0, stddev=init_std) self.w = tf.Variable(w_init, name='w', trainable=True) def call(self, inputs, training=None, mask=None): weight = self.runtime_coef * self.w c = tf.reduce_prod(tf.shape(inputs)[1:]) x = tf.reshape(inputs, shape=[-1, c]) x = tf.matmul(x, weight) return x class LabelEmbedding(tf.keras.layers.Layer): def __init__(self, embed_dim, **kwargs): super(LabelEmbedding, self).__init__(**kwargs) self.embed_dim = embed_dim def build(self, input_shape): weight_shape = [input_shape[1], self.embed_dim] # tf 1.15 mean(0.0), std(1.0) default value of tf.initializers.random_normal() w_init = tf.random.normal(shape=weight_shape, mean=0.0, stddev=1.0) self.w = tf.Variable(w_init, name='w', trainable=True) def call(self, inputs, training=None, mask=None): x = tf.matmul(inputs, self.w) return x ################################################################################## # etc ################################################################################## class PixelNorm(tf.keras.layers.Layer): def __init__(self, **kwargs): super(PixelNorm, self).__init__(**kwargs) def call(self, inputs, training=None, mask=None): x = inputs * tf.math.rsqrt(tf.reduce_mean(tf.square(inputs), axis=1, keepdims=True) + 1e-8) return x class BiasAct(tf.keras.layers.Layer): def __init__(self, lrmul, act, **kwargs): super(BiasAct, self).__init__(**kwargs) self.lrmul = lrmul self.act = act def build(self, input_shape): b_init = tf.zeros(shape=(input_shape[1],), dtype=tf.float32) self.b = tf.Variable(b_init, name='b', trainable=True) def call(self, inputs, training=None, mask=None): b = self.lrmul * self.b x = fused_bias_act(inputs, b=b, act=self.act, alpha=None, gain=None) return x class Noise(tf.keras.layers.Layer): def __init__(self, **kwargs): super(Noise, self).__init__(**kwargs) def build(self, input_shape): self.noise_strength = tf.Variable(initial_value=0.0, dtype=tf.float32, trainable=True, name='w') def call(self, inputs, noise=None, training=None, mask=None): x_shape = tf.shape(inputs) # noise: [1, 1, x_shape[2], x_shape[3]] or None if noise is None: noise = tf.random.normal(shape=(x_shape[0], 1, x_shape[2], x_shape[3]), dtype=tf.float32) x = inputs + noise * self.noise_strength return x class MinibatchStd(tf.keras.layers.Layer): def __init__(self, group_size, num_new_features, **kwargs): super(MinibatchStd, self).__init__(**kwargs) self.group_size = group_size self.num_new_features = num_new_features def call(self, inputs, training=None, mask=None): s = tf.shape(inputs) group_size = tf.minimum(self.group_size, s[0]) y = tf.reshape(inputs, [group_size, -1, self.num_new_features, s[1] // self.num_new_features, s[2], s[3]]) y = tf.cast(y, tf.float32) y -= tf.reduce_mean(y, axis=0, keepdims=True) y = tf.reduce_mean(tf.square(y), axis=0) y = tf.sqrt(y + 1e-8) y = tf.reduce_mean(y, axis=[2, 3, 4], keepdims=True) y = tf.reduce_mean(y, axis=[2]) y = tf.cast(y, inputs.dtype) y = tf.tile(y, [group_size, 1, s[2], s[3]]) x = tf.concat([inputs, y], axis=1) return x def compute_runtime_coef(weight_shape, gain, lrmul): fan_in = tf.reduce_prod(weight_shape[:-1]) # [kernel, kernel, fmaps_in, fmaps_out] or [in, out] fan_in = tf.cast(fan_in, dtype=tf.float32) he_std = gain / tf.sqrt(fan_in) init_std = 1.0 / lrmul runtime_coef = he_std * lrmul return init_std, runtime_coef def lerp(a, b, t): out = a + (b - a) * t return out def lerp_clip(a, b, t): out = a + (b - a) * tf.clip_by_value(t, 0.0, 1.0) return out def get_coords(batch_size, height, width): x = tf.linspace(-1, 1, width) x = tf.reshape(x, shape=[1, 1, width, 1]) x = tf.tile(x, multiples=[batch_size, width, 1, 1]) y = tf.linspace(-1, 1, height) y = tf.reshape(y, shape=[1, height, 1, 1]) y = tf.tile(y, multiples=[batch_size, 1, height, 1]) coords = tf.concat([x, y], axis=-1) coords = tf.transpose(coords, perm=[0, 3, 1, 2]) coords = tf.cast(coords, tf.float32) return coords def grid_sample_tf(img, coords, align_corners=False, padding='border'): """ :param img: [B, C, H, W] :param coords: [B, C, H, W] :return: [B, C, H, W] """ def get_pixel_value(img, x, y): """ Utility function to get pixel value for coordinate vectors x and y from a 4D tensor image. Input ----- - img: tensor of shape (B, H, W, C) - x: flattened tensor of shape (B*H*W,) - y: flattened tensor of shape (B*H*W,) Returns ------- - output: tensor of shape (B, H, W, C) """ shape = tf.shape(x) batch_size = shape[0] height = shape[1] width = shape[2] batch_idx = tf.range(0, batch_size) batch_idx = tf.reshape(batch_idx, (batch_size, 1, 1)) b = tf.tile(batch_idx, (1, height, width)) indices = tf.stack([b, y, x], 3) return tf.gather_nd(img, indices) # rescale x and y to [0, W-1/H-1] img = tf.transpose(img, perm=[0, 2, 3, 1]) # -> [N, H, W, C] coords = tf.transpose(coords, perm=[0, 2, 3, 1]) # -> [N, H, W, C] x, y = coords[:, ..., 0], coords[:, ..., 1] x = tf.cast(x, 'float32') y = tf.cast(y, 'float32') side = tf.cast(tf.shape(img)[1], tf.int32) side_f = tf.cast(side, tf.float32) if align_corners: x = ((x + 1) / 2) * (side_f - 1) y = ((y + 1) / 2) * (side_f - 1) else: x = 0.5 * ((x + 1.0) * side_f - 1) y = 0.5 * ((y + 1.0) * side_f - 1) if padding == 'border': x = tf.clip_by_value(x, 0, side_f - 1) y = tf.clip_by_value(y, 0, side_f - 1) # -------------- Changes above -------------------- # grab 4 nearest corner points for each (x_i, y_i) x0 = tf.floor(x) x1 = x0 + 1 y0 = tf.floor(y) y1 = y0 + 1 # recast as float for delta calculation x0 = tf.cast(x0, 'float32') x1 = tf.cast(x1, 'float32') y0 = tf.cast(y0, 'float32') y1 = tf.cast(y1, 'float32') # calculate deltas wa = (x1 - x) * (y1 - y) wb = (x1 - x) * (y - y0) wc = (x - x0) * (y1 - y) wd = (x - x0) * (y - y0) # recast as int for img boundaries x0 = tf.cast(x0, 'int32') x1 = tf.cast(x1, 'int32') y0 = tf.cast(y0, 'int32') y1 = tf.cast(y1, 'int32') # clip to range [0, H-1/W-1] to not violate img boundaries x0 = tf.clip_by_value(x0, 0, side-1) x1 = tf.clip_by_value(x1, 0, side-1) y0 = tf.clip_by_value(y0, 0, side-1) y1 = tf.clip_by_value(y1, 0, side-1) # get pixel value at corner coords Ia = get_pixel_value(img, x0, y0) Ib = get_pixel_value(img, x0, y1) Ic = get_pixel_value(img, x1, y0) Id = get_pixel_value(img, x1, y1) # add dimension for addition wa = tf.expand_dims(wa, axis=3) wb = tf.expand_dims(wb, axis=3) wc = tf.expand_dims(wc, axis=3) wd = tf.expand_dims(wd, axis=3) # compute output out = wa * Ia + wb * Ib + wc * Ic + wd * Id # [N, H, W, C] out = tf.transpose(out, perm=[0, 3, 1, 2]) return out def torch_normalization(x): x /= 255. r, g, b = tf.split(axis=-1, num_or_size_splits=3, value=x) mean = [0.485, 0.456, 0.406] std = [0.229, 0.224, 0.225] x = tf.concat(axis=-1, values=[ (r - mean[0]) / std[0], (g - mean[1]) / std[1], (b - mean[2]) / std[2] ]) return x def inception_processing(filename): x = tf.io.read_file(filename) img = tf.image.decode_jpeg(x, channels=3, dct_method='INTEGER_ACCURATE') img = tf.image.resize(img, [256, 256], antialias=True, method=tf.image.ResizeMethod.BICUBIC) img = tf.image.resize(img, [299, 299], antialias=True, method=tf.image.ResizeMethod.BICUBIC) img = torch_normalization(img) # img = tf.transpose(img, [2, 0, 1]) return img
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pyrap/utils.py
danielnyga/pyrap
9
81366
<filename>pyrap/utils.py ''' Created on Nov 10, 2015 @author: nyga ''' import datetime import email import os import sys import collections from dnutils import edict # # case-insensitive dict taken from requests # class CaseInsensitiveDict(collections.MutableMapping): """ A case-insensitive ``dict``-like object. Implements all methods and operations of ``collections.MutableMapping`` as well as dict's ``copy``. Also provides ``lower_items``. All keys are expected to be strings. The structure remembers the case of the last key to be set, and ``iter(instance)``, ``keys()``, ``items()``, ``iterkeys()``, and ``iteritems()`` will contain case-sensitive keys. However, querying and contains testing is case insensitive:: cid = CaseInsensitiveDict() cid['Accept'] = 'application/json' cid['aCCEPT'] == 'application/json' # True list(cid) == ['Accept'] # True For example, ``headers['content-encoding']`` will return the value of a ``'Content-Encoding'`` response header, regardless of how the header name was originally stored. If the constructor, ``.update``, or equality comparison operations are given keys that have equal ``.lower()``s, the behavior is undefined. """ def __init__(self, data=None, **kwargs): self._store = dict() if data is None: data = {} self.update(data, **kwargs) def __setitem__(self, key, value): # Use the lowercased key for lookups, but store the actual # key alongside the value. self._store[key.lower()] = (key, value) def __getitem__(self, key): return self._store[key.lower()][1] def __delitem__(self, key): del self._store[key.lower()] def __iter__(self): return (casedkey for casedkey, mappedvalue in self._store.values()) def __len__(self): return len(self._store) def lower_items(self): """Like iteritems(), but with all lowercase keys.""" return ( (lowerkey, keyval[1]) for (lowerkey, keyval) in self._store.items() ) def __eq__(self, other): if isinstance(other, collections.Mapping): other = CaseInsensitiveDict(other) else: return NotImplemented # Compare insensitively return dict(self.lower_items()) == dict(other.lower_items()) # Copy is required def copy(self): return CaseInsensitiveDict(self._store.values()) def __repr__(self): return str(dict(self.items())) class RStorage(dict): ''' Recursive extension of web.util.Storage that applies the Storage constructor recursively to all value elements that are dicts. ''' __slots__ = [] def __init__(self, d=None): if d is not None: for k, v in d.items(): self[k] = v def __setattr__(self, key, value): if key in self.__slots__: self.__dict__[key] = value else: self[key] = value def __setitem__(self, key, value): dict.__setitem__(self, key, rstorify(value)) def __getattr__(self, key): if key in type(self).__slots__: return self.__dict__[key] else: try: return self[key] except KeyError as k: raise AttributeError(k) def __delattr__(self, key): try: del self[key] except KeyError as k: raise AttributeError(k) def __repr__(self): return ('<%s ' % type(self).__name__) + dict.__repr__(self) + '>' def rstorify(e): if type(e) is dict: return RStorage(d=e) elif type(e) in (list, tuple): return [rstorify(i) for i in e] else: return e def jsonify(o): if hasattr(o, 'json'): return o.json elif isinstance(o, dict): return {str(k): jsonify(v) for k, v in o.items()} elif type(o) in (list, tuple, map): return [jsonify(e) for e in o] elif isinstance(o, (int, float, bool, str, type(None))): return o else: raise TypeError('object of type "%s" is not jsonifiable: %s' % (type(o), repr(o))) class BiMap: ''' Bi-directional mapping. ''' def __init__(self, values=None): self._fwd = {} self._bwd = {} self += values self.__iter__ = self._fwd.__iter__ self.items = self._fwd.items self.keys = self._fwd.keys self.values = self._fwd.values def __iadd__(self, values): if type(values) in (list, tuple): for f, b in values: self[f:b] elif isinstance(values, (dict, BiMap)): for f, b in values.items(): self[f:b] return self def __add__(self, values): newmap = BiMap(self) newmap += values return newmap def __getitem__(self, s): if type(s) is slice: if not s.start and s.stop: return self._bwd[s.stop] if s.start and not s.stop: return self._fwd[s.start] if s.start and s.stop: self._fwd[s.start] = s.stop self._bwd[s.stop] = s.start else: raise AttributeError('Slice argument for BiMap cannot be empty') else: return self._fwd[s] def __contains__(self, e): return e in self._fwd or e in self._bwd def __str__(self): return ';'.join([str(e) for e in list(self._fwd.items())]) class BitMask(BiMap): def __init__(self, *values): BiMap.__init__(self) self._count = 0 for v in values: numval = 1 << self._count setattr(self, v, numval) self._count += 1 self[numval:v] def pparti(number, proportions): ''' Partition a number into a sum of n integers, proportionally to the ratios given in proportions. The result is guaranteed to sun up to ``number``, so it is cleaned wrt. to numerical instabilities. ''' Z = sum(proportions) percents = [float(p) / Z for p in proportions] result = [max(0, int(round(p * number))) for p in percents[:-1]] return result + [number - sum(result)] def bind(**kwargs): def wrap_f(function): def probeFunc(frame, event, arg): if event == 'call': frame.f_locals.update(kwargs) frame.f_globals.update(kwargs) elif event == 'return': for key in kwargs: kwargs[key] = frame.f_locals[key] sys.settrace(None) return probeFunc def traced(*args, **kwargs): sys.settrace(probeFunc) function(*args, **kwargs) return traced return wrap_f def parse_datetime(dt): return datetime.datetime.utcfromtimestamp(email.utils.mktime_tz(email.utils.parsedate_tz(dt))) def format_datetime(dt): return email.utils.formatdate(dt.timestamp(), True) if __name__ == '__main__': print(pparti(10, [.2, .2, .1, .5]))
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jet_bridge/serializers/sql.py
BradyBromley/jet-bridge
2
129013
from sqlalchemy import text from sqlalchemy.exc import SQLAlchemyError from jet_bridge import fields from jet_bridge.db import Session from jet_bridge.exceptions.sql import SqlError from jet_bridge.exceptions.validation_error import ValidationError from jet_bridge.fields.sql_params import SqlParamsSerializers from jet_bridge.serializers.serializer import Serializer class SqlSerializer(Serializer): query = fields.CharField() params = SqlParamsSerializers(required=False) class Meta: fields = ( 'query', 'params', ) def validate_query(self, value): forbidden = ['insert', 'update', 'delete', 'grant', 'show'] for i in range(len(forbidden)): forbidden.append('({}'.format(forbidden[i])) if any(map(lambda x: ' {} '.format(value.lower()).find(' {} '.format(x)) != -1, forbidden)): raise ValidationError('forbidden query') i = 0 while value.find('%s') != -1: value = value.replace('%s', ':param_{}'.format(i), 1) i += 1 return value def execute(self, data): session = Session() query = data['query'] params = data.get('params', []) try: result = session.execute( text(query), params ) rows = list(map(lambda x: x.itervalues(), result)) def map_column(x): if x == '?column?': return return x return {'data': rows, 'columns': map(map_column, result.keys())} except (SQLAlchemyError, TypeError) as e: raise SqlError(e) finally: session.close() class SqlsSerializer(Serializer): queries = SqlSerializer(many=True) def execute(self, data): serializer = SqlSerializer() return map(lambda x: serializer.execute(x), data['queries'])
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res/011-json.py
leialbert/keep-learning-python
0
107315
import json person = {'name':'John','age':28,'city':'New York','hasChildren':False} personJson = json.dumps(person,indent=4,separators=(':','='),sort_keys=True) print(personJson) with open('res/person.json', 'w') as f: json.dump(person,f,indent=4) person = {'name':'John','age':28,'city':'New York','hasChildren':False} personJson = json.dumps(person) person_new = json.loads(personJson) print(person_new) with open('res/person.json', 'r') as f: person = json.load(f) print(json) class User: def __init__(self,name,age): self.name = name self.age = age user = User('albert',29) def encode_user(o): if isinstance(o,User): return {'name':o.name,'age':o.age,o.__class__.__name__:True} else: raise TypeError('is not JSON serializable') userJSON = json.dumps(user,default=encode_user) print(userJSON) from json import JSONEncoder class UserEncoder(JSONEncoder): def default(self,o): if isinstance(o,User): return {'name':o.name,'age':o.age,o.__class__.__name__:True} userJSON = json.dumps(user,cls=UserEncoder) print(userJSON) userJSON2 = UserEncoder().encode(user) print(userJSON2) def decode_user(dct): if User.__name__ in dct: return User(name=dct['name'],age=dct['age']) return dct user = json.loads(userJSON,object_hook=decode_user) print(type(user)) print(user.name)
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tutorial/core/sockets.py
mburst/gevent-socketio-starterkit
6
164424
from socketio.namespace import BaseNamespace from socketio.mixins import RoomsMixin, BroadcastMixin from socketio.sdjango import namespace from collections import defaultdict import redis from gevent import Greenlet def home_redis_worker(): r = redis.StrictRedis(host='localhost', port=6379, db=0) tacosub = r.pubsub() tacosub.subscribe('tacos') for item in tacosub.listen(): if item['type'] == "message": for socket in HomeNamespace.sockets: socket.emit('taco', item['data']) home_greenlet = Greenlet.spawn(home_redis_worker) @namespace('/home') class HomeNamespace(BaseNamespace): sockets = set([]) def initialize(self): HomeNamespace.sockets.add(self) def recv_disconnect(self): HomeNamespace.sockets.discard(self) self.disconnect(silent=True) ########################### def user_redis_worker(): r = redis.StrictRedis(host='localhost', port=6379, db=0) usersub = r.pubsub() usersub.psubscribe('user_*') for item in usersub.listen(): if item['type'] == "pmessage": user = item['channel'][5:] for socket in UserNamespace.sockets[user]: socket.emit('taco', item['data']) user_greenlet = Greenlet.spawn(user_redis_worker) @namespace('/user') class UserNamespace(BaseNamespace): sockets = defaultdict(set) def on_set_user(self, username): self.username = username UserNamespace.sockets[username].add(self) def recv_disconnect(self): UserNamespace.sockets[self.username].discard(self) self.disconnect(silent=True)
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ptxt/mur/commonmark.py
mvasilkov/scrapheap
2
112865
<filename>ptxt/mur/commonmark.py<gh_stars>1-10 from collections import namedtuple from ctypes import CDLL, c_char_p, c_size_t, c_int from pathlib import WindowsPath import platform def _libcmark(): system = platform.system() if system == 'Darwin': return 'libcmark.dylib' if system == 'Windows': binary_dependencies = WindowsPath(__file__).parents[1] / 'binary_dependencies' return str(binary_dependencies / 'cmark.dll') return 'libcmark.so' cmark = CDLL(_libcmark()) cmark_markdown_to_html = cmark.cmark_markdown_to_html cmark_markdown_to_html.argtypes = (c_char_p, c_size_t, c_int) cmark_markdown_to_html.restype = c_char_p cmark_version = cmark.cmark_version cmark_version.restype = c_int Version = namedtuple('Version', 'major minor patchlevel') def commonmark(string): b = string.encode('utf-8') return cmark_markdown_to_html(b, len(b), 0).decode('utf-8') def version(): return Version(*cmark_version().to_bytes(3, byteorder='big'))
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frappe/core/doctype/prepared_report/test_prepared_report.py
oryxsolutions/frappe
0
194784
# -*- coding: utf-8 -*- # Copyright (c) 2018, Frappe Technologies and Contributors # License: MIT. See LICENSE import json import unittest import frappe class TestPreparedReport(unittest.TestCase): def setUp(self): self.report = frappe.get_doc({"doctype": "Report", "name": "Permitted Documents For User"}) self.filters = {"user": "Administrator", "doctype": "Role"} self.prepared_report_doc = frappe.get_doc( { "doctype": "Prepared Report", "report_name": self.report.name, "filters": json.dumps(self.filters), "ref_report_doctype": self.report.name, } ).insert() def tearDown(self): frappe.set_user("Administrator") self.prepared_report_doc.delete() def test_for_creation(self): self.assertTrue("QUEUED" == self.prepared_report_doc.status.upper()) self.assertTrue(self.prepared_report_doc.report_start_time)
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python/client.py
JonathanSchmalhofer/SelfDrivingRLCarGodot
10
188646
#!/usr/bin/env python import socket import time def DoEpisode(): s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s.settimeout(1) # 1 second s.connect((TCP_IP, TCP_PORT)) #print(" REGISTER"); s.send("(HEAD:10)(REGISTER)".encode('utf-8')) data = s.recv(BUFFER_SIZE) print(" RESPONSE: {}".format(data)) for i in range(0, 100): s.send("(HEAD:22)(CONTROL:0.3;0.1;-0.1)".encode('utf-8')) data = s.recv(BUFFER_SIZE).decode('utf-8').split(';') print(" RESPONSE: {}".format(data)) print("{} {} {} {} {}".format(data[2],data[3],data[4],data[5],data[6])) if data[1] == "True": print("Crash") break for i in range(0, 100): s.send("(HEAD:22)(CONTROL:0.6;0.15;0.4)".encode('utf-8')) data = s.recv(BUFFER_SIZE).decode('utf-8').split(';') if data[1] == "True": print("Crash") break #print(" RESPONSE: {}".format(data)) s.send("(HEAD:7)(CLOSE)".encode('utf-8')) s.close() s = None TCP_IP = '127.0.0.1' TCP_PORT = 42424 BUFFER_SIZE = 1024 for i in range(0, 100): print("Episode {}".format(i)) DoEpisode()
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dogpile/__init__.py
dhellmann/dogpile.cache
0
30256
__version__ = '0.9.3' from .lock import Lock # noqa from .lock import NeedRegenerationException # noqa
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raiden/transfer/channel.py
gcarq/raiden
0
60259
# -*- coding: utf-8 -*- # pylint: disable=too-many-lines import heapq from binascii import hexlify from collections import namedtuple from raiden.encoding.signing import recover_publickey from raiden.transfer.architecture import TransitionResult from raiden.transfer.balance_proof import signing_data from raiden.transfer.events import ( ContractSendChannelClose, ContractSendChannelSettle, ContractSendChannelUpdateTransfer, ContractSendChannelWithdraw, EventTransferReceivedInvalidDirectTransfer, EventTransferReceivedSuccess, EventTransferSentFailed, SendDirectTransfer, ) from raiden.transfer.mediated_transfer.state import LockedTransferUnsignedState from raiden.transfer.mediated_transfer.events import ( refund_from_sendmediated, SendBalanceProof, SendMediatedTransfer, ) from raiden.transfer.merkle_tree import ( LEAVES, merkleroot, compute_layers, compute_merkleproof_for, ) from raiden.transfer.state import ( CHANNEL_STATE_CLOSED, CHANNEL_STATE_CLOSING, CHANNEL_STATE_OPENED, CHANNEL_STATE_SETTLED, CHANNEL_STATE_SETTLING, CHANNEL_STATES_PRIOR_TO_CLOSED, CHANNEL_STATE_UNUSABLE, EMPTY_MERKLE_ROOT, EMPTY_MERKLE_TREE, BalanceProofUnsignedState, HashTimeLockState, MerkleTreeState, TransactionExecutionStatus, UnlockPartialProofState, UnlockProofState, ) from raiden.transfer.state_change import ( ActionChannelClose, ActionTransferDirect, Block, ContractReceiveChannelClosed, ContractReceiveChannelNewBalance, ContractReceiveChannelSettled, ContractReceiveChannelWithdraw, ReceiveTransferDirect, ) from raiden.utils import publickey_to_address, typing from raiden.settings import DEFAULT_NUMBER_OF_CONFIRMATIONS_BLOCK TransactionOrder = namedtuple( 'TransactionOrder', ('block_number', 'transaction') ) def is_known(end_state, hashlock): """True if the `hashlock` corresponds to a known lock.""" return ( hashlock in end_state.hashlocks_to_pendinglocks or hashlock in end_state.hashlocks_to_unclaimedlocks ) def is_deposit_confirmed(channel_state, block_number): if not channel_state.deposit_transaction_queue: return False return is_transaction_confirmed( channel_state.deposit_transaction_queue[0].block_number, block_number, ) def is_locked(end_state, hashlock): """True if the `hashlock` is known and the correspoding secret is not.""" return hashlock in end_state.hashlocks_to_pendinglocks def is_secret_known(end_state, hashlock): """True if the `hashlock` is for a lock with a known secret.""" return hashlock in end_state.hashlocks_to_unclaimedlocks def is_transaction_confirmed(transaction_block_number, blockchain_block_number): confirmation_block = transaction_block_number + DEFAULT_NUMBER_OF_CONFIRMATIONS_BLOCK return blockchain_block_number > confirmation_block def is_valid_signature(balance_proof, sender_address): data_that_was_signed = signing_data( balance_proof.nonce, balance_proof.transferred_amount, balance_proof.channel_address, balance_proof.locksroot, balance_proof.message_hash, ) try: # ValueError is raised if the PublicKey instantiation failed, let it # propagate because it's a memory pressure problem publickey = recover_publickey( data_that_was_signed, balance_proof.signature, ) except Exception: # pylint: disable=broad-except # secp256k1 is using bare Exception classes # raised if the recovery failed msg = 'Signature invalid, could not be recovered.' return (False, msg) is_correct_sender = sender_address == publickey_to_address(publickey) if is_correct_sender: return (True, None) msg = 'Signature was valid but the expected address does not match.' return (False, msg) def is_valid_directtransfer(direct_transfer, channel_state, sender_state, receiver_state): received_balance_proof = direct_transfer.balance_proof current_balance_proof = get_current_balanceproof(sender_state) current_locksroot, _, current_transferred_amount = current_balance_proof distributable = get_distributable(sender_state, receiver_state) expected_nonce = get_next_nonce(sender_state) amount = received_balance_proof.transferred_amount - current_transferred_amount is_valid, signature_msg = is_valid_signature( received_balance_proof, sender_state.address, ) if get_status(channel_state) != CHANNEL_STATE_OPENED: msg = 'Invalid direct message. The channel is already closed.' result = (False, msg) elif not is_valid: # The signature must be valid, otherwise the balance proof cannot be # used onchain. msg = 'Invalid DirectTransfer message. {}'.format(signature_msg) result = (False, msg) elif received_balance_proof.nonce != expected_nonce: # The nonces must increase sequentially, otherwise there is a # synchronization problem. msg = ( 'Invalid DirectTransfer message. ' 'Nonce did not change sequentially, expected: {} got: {}.' ).format( expected_nonce, received_balance_proof.nonce, ) result = (False, msg) elif received_balance_proof.locksroot != current_locksroot: # Direct transfers do not use hash time lock, so it cannot change the # locksroot, otherwise a lock could be removed. msg = ( "Invalid DirectTransfer message. " "Balance proof's locksroot changed, expected: {} got: {}." ).format( hexlify(current_locksroot).decode(), hexlify(received_balance_proof.locksroot).decode(), ) result = (False, msg) elif received_balance_proof.transferred_amount <= current_transferred_amount: # Direct transfers must increase the transferred_amount, otherwise the # sender is trying to play the protocol and steal token. msg = ( "Invalid DirectTransfer message. " "Balance proof's transferred_amount decreased, expected larger than: {} got: {}." ).format( current_transferred_amount, received_balance_proof.transferred_amount, ) result = (False, msg) elif received_balance_proof.channel_address != channel_state.identifier: # The balance proof must be tied to this channel, otherwise the # on-chain contract would be sucesstible to replay attacks across # channels. msg = ( 'Invalid DirectTransfer message. ' 'Balance proof is tied to the wrong channel, expected: {} got: {}' ).format( hexlify(channel_state.identifier).decode(), hexlify(received_balance_proof.channel_address).decode(), ) result = (False, msg) elif amount > distributable: # Direct transfer are limited to the current available balance, # otherwise the sender is doing a trying to play the protocol and do a # double spend. msg = ( 'Invalid DirectTransfer message. ' 'Transfer amount larger than the available distributable, ' 'transfer amount: {} maximum distributable: {}' ).format( amount, distributable, ) result = (False, msg) else: result = (True, None) return result def is_valid_mediatedtransfer(mediated_transfer, channel_state, sender_state, receiver_state): received_balance_proof = mediated_transfer.balance_proof current_balance_proof = get_current_balanceproof(sender_state) _, _, current_transferred_amount = current_balance_proof distributable = get_distributable(sender_state, receiver_state) expected_nonce = get_next_nonce(sender_state) lock = mediated_transfer.lock merkletree = compute_merkletree_with(sender_state.merkletree, lock.lockhash) if get_status(channel_state) != CHANNEL_STATE_OPENED: msg = 'Invalid direct message. The channel is already closed.' result = (False, msg, None) if merkletree is None: msg = 'Invalid MediatedTransfer message. Same lockhash handled twice.' result = (False, msg, None) else: locksroot_with_lock = merkleroot(merkletree) (is_valid, signature_msg) = is_valid_signature( received_balance_proof, sender_state.address, ) if not is_valid: # The signature must be valid, otherwise the balance proof cannot be # used onchain msg = 'Invalid MediatedTransfer message. {}'.format(signature_msg) result = (False, msg, None) elif received_balance_proof.nonce != expected_nonce: # The nonces must increase sequentially, otherwise there is a # synchronization problem msg = ( 'Invalid MediatedTransfer message. ' 'Nonce did not change sequentially, expected: {} got: {}.' ).format( expected_nonce, received_balance_proof.nonce, ) result = (False, msg, None) elif received_balance_proof.locksroot != locksroot_with_lock: # The locksroot must be updated to include the new lock msg = ( "Invalid MediatedTransfer message. " "Balance proof's locksroot didn't match, expected: {} got: {}." ).format( hexlify(locksroot_with_lock).decode(), hexlify(received_balance_proof.locksroot).decode(), ) result = (False, msg, None) elif received_balance_proof.transferred_amount != current_transferred_amount: # Mediated transfers must not change transferred_amount msg = ( "Invalid MediatedTransfer message. " "Balance proof's transferred_amount changed, expected: {} got: {}." ).format( current_transferred_amount, received_balance_proof.transferred_amount, ) result = (False, msg, None) elif received_balance_proof.channel_address != channel_state.identifier: # The balance proof must be tied to this channel, otherwise the # on-chain contract would be sucesstible to replay attacks across # channels. msg = ( 'Invalid MediatedTransfer message. ' 'Balance proof is tied to the wrong channel, expected: {} got: {}' ).format( hexlify(channel_state.identifier).decode(), hexlify(received_balance_proof.channel_address).decode(), ) result = (False, msg, None) # the locked amount is limited to the current available balance, otherwise # the sender is doing a trying to play the protocol and do a double spend elif lock.amount > distributable: msg = ( 'Invalid MediatedTransfer message. ' 'Lock amount larger than the available distributable, ' 'lock amount: {} maximum distributable: {}' ).format( lock.amount, distributable, ) result = (False, msg, None) else: result = (True, None, merkletree) return result def is_valid_unlock(unlock, channel_state, sender_state): received_balance_proof = unlock.balance_proof current_balance_proof = get_current_balanceproof(sender_state) lock = get_lock(sender_state, unlock.hashlock) if lock is not None: new_merkletree = compute_merkletree_without(sender_state.merkletree, lock.lockhash) locksroot_without_lock = merkleroot(new_merkletree) _, _, current_transferred_amount = current_balance_proof expected_nonce = get_next_nonce(sender_state) expected_transferred_amount = current_transferred_amount + lock.amount is_valid, signature_msg = is_valid_signature( received_balance_proof, sender_state.address, ) # TODO: Accept unlock messages if the node has not yet sent a transaction # with the balance proof to the blockchain, this will save one call to # withdraw on-chain for the non-closing party. if get_status(channel_state) != CHANNEL_STATE_OPENED: msg = 'Invalid Unlock message for {}. The channel is already closed.'.format( hexlify(unlock.hashlock).decode(), ) result = (False, msg, None) elif lock is None: msg = 'Invalid Secret message. There is no correspoding lock for {}'.format( hexlify(unlock.hashlock).decode(), ) result = (False, msg, None) elif not is_valid: # The signature must be valid, otherwise the balance proof cannot be # used onchain. msg = 'Invalid Secret message. {}'.format(signature_msg) result = (False, msg, None) elif received_balance_proof.nonce != expected_nonce: # The nonces must increase sequentially, otherwise there is a # synchronization problem. msg = ( 'Invalid Secret message. ' 'Nonce did not change sequentially, expected: {} got: {}.' ).format( expected_nonce, received_balance_proof.nonce, ) result = (False, msg, None) elif received_balance_proof.locksroot != locksroot_without_lock: # Secret messages remove a known lock, the new locksroot must have only # that lock removed, otherwise the sender may be trying to remove # additional locks. msg = ( "Invalid Secret message. " "Balance proof's locksroot didn't match, expected: {} got: {}." ).format( hexlify(locksroot_without_lock).decode(), hexlify(received_balance_proof.locksroot).decode(), ) result = (False, msg, None) elif received_balance_proof.transferred_amount != expected_transferred_amount: # Secret messages must increase the transferred_amount by lock amount, # otherwise the sender is trying to play the protocol and steal token. msg = ( "Invalid Secret message. " "Balance proof's wrong transferred_amount, expected: {} got: {}." ).format( expected_transferred_amount, received_balance_proof.transferred_amount, ) result = (False, msg, None) elif received_balance_proof.channel_address != channel_state.identifier: # The balance proof must be tied to this channel, otherwise the # on-chain contract would be sucesstible to replay attacks across # channels. msg = ( 'Invalid Secret message. ' 'Balance proof is tied to the wrong channel, expected: {} got: {}' ).format( channel_state.identifier, hexlify(received_balance_proof.channel_address).decode(), ) result = (False, msg, None) else: result = (True, None, new_merkletree) return result def get_amount_locked(end_state): total_pending = sum( lock.amount for lock in end_state.hashlocks_to_pendinglocks.values() ) total_unclaimed = sum( unlock.lock.amount for unlock in end_state.hashlocks_to_unclaimedlocks.values() ) return total_pending + total_unclaimed def get_balance(sender, receiver): sender_transferred_amount = 0 receiver_transferred_amount = 0 if sender.balance_proof: sender_transferred_amount = sender.balance_proof.transferred_amount if receiver.balance_proof: receiver_transferred_amount = receiver.balance_proof.transferred_amount return ( sender.contract_balance - sender_transferred_amount + receiver_transferred_amount ) def get_current_balanceproof(end_state): balance_proof = end_state.balance_proof if balance_proof: locksroot = balance_proof.locksroot nonce = balance_proof.nonce transferred_amount = balance_proof.transferred_amount else: locksroot = EMPTY_MERKLE_ROOT nonce = 0 transferred_amount = 0 return (locksroot, nonce, transferred_amount) def get_distributable(sender, receiver): return get_balance(sender, receiver) - get_amount_locked(sender) def get_known_unlocks(end_state): """Generate unlocking proofs for the known secrets.""" return [ compute_proof_for_lock( end_state, partialproof.secret, partialproof.lock, ) for partialproof in end_state.hashlocks_to_unclaimedlocks.values() ] def get_lock( end_state: 'NettingChannelEndState', hashlock: typing.Keccak256, ) -> HashTimeLockState: """Return the lock correspoding to `hashlock` or None if the lock is unknown. """ lock = end_state.hashlocks_to_pendinglocks.get(hashlock) if not lock: partial_unlock = end_state.hashlocks_to_unclaimedlocks.get(hashlock) if partial_unlock: lock = partial_unlock.lock assert isinstance(lock, HashTimeLockState) or lock is None return lock def get_next_nonce(end_state): if end_state.balance_proof: return end_state.balance_proof.nonce + 1 # 0 must not be used since in the netting contract it represents null. return 1 def get_status(channel_state): if channel_state.settle_transaction: finished_sucessfully = ( channel_state.settle_transaction.result == TransactionExecutionStatus.SUCCESS ) running = channel_state.settle_transaction.finished_block_number is None if finished_sucessfully: result = CHANNEL_STATE_SETTLED elif running: result = CHANNEL_STATE_SETTLING else: result = CHANNEL_STATE_UNUSABLE elif channel_state.close_transaction: finished_sucessfully = ( channel_state.close_transaction.result == TransactionExecutionStatus.SUCCESS ) running = channel_state.close_transaction.finished_block_number is None if finished_sucessfully: result = CHANNEL_STATE_CLOSED elif running: result = CHANNEL_STATE_CLOSING else: result = CHANNEL_STATE_UNUSABLE else: result = CHANNEL_STATE_OPENED return result def del_lock(end_state, hashlock): assert is_known(end_state, hashlock) if hashlock in end_state.hashlocks_to_pendinglocks: del end_state.hashlocks_to_pendinglocks[hashlock] if hashlock in end_state.hashlocks_to_unclaimedlocks: del end_state.hashlocks_to_unclaimedlocks[hashlock] def set_closed(channel_state, block_number): if not channel_state.close_transaction: channel_state.close_transaction = TransactionExecutionStatus( None, block_number, TransactionExecutionStatus.SUCCESS, ) elif not channel_state.close_transaction.finished_block_number: channel_state.close_transaction.finished_block_number = block_number channel_state.close_transaction.result = TransactionExecutionStatus.SUCCESS def set_settled(channel_state, block_number): if not channel_state.settle_transaction: channel_state.settle_transaction = TransactionExecutionStatus( None, block_number, TransactionExecutionStatus.SUCCESS, ) elif not channel_state.settle_transaction.finished_block_number: channel_state.settle_transaction.finished_block_number = block_number channel_state.settle_transaction.result = TransactionExecutionStatus.SUCCESS def update_contract_balance(end_state: 'NettingChannelEndState', contract_balance): if contract_balance > end_state.contract_balance: end_state.contract_balance = contract_balance def compute_proof_for_lock( end_state: 'NettingChannelEndState', secret: typing.Secret, lock: HashTimeLockState ) -> UnlockProofState: # forcing bytes because ethereum.abi doesn't work with bytearray merkle_proof = compute_merkleproof_for(end_state.merkletree, lock.lockhash) return UnlockProofState( merkle_proof, lock.encoded, secret, ) def compute_merkletree_with( merkletree: MerkleTreeState, lockhash: typing.Keccak256, ) -> typing.Optional[MerkleTreeState]: """Register the given lockhash with the existing merkle tree.""" # Use None to inform the caller the lockshash is already known result = None leaves = merkletree.layers[LEAVES] if lockhash not in leaves: leaves = list(leaves) leaves.append(lockhash) result = MerkleTreeState(compute_layers(leaves)) return result def compute_merkletree_without(merkletree, lockhash): # Use None to inform the caller the lockshash is unknown result = None leaves = merkletree.layers[LEAVES] if lockhash in leaves: leaves = list(leaves) leaves.remove(lockhash) if leaves: result = MerkleTreeState(compute_layers(leaves)) else: result = EMPTY_MERKLE_TREE return result def create_senddirecttransfer(channel_state, amount, identifier): our_balance_proof = channel_state.our_state.balance_proof if our_balance_proof: transferred_amount = amount + our_balance_proof.transferred_amount locksroot = our_balance_proof.locksroot else: transferred_amount = amount locksroot = EMPTY_MERKLE_ROOT nonce = get_next_nonce(channel_state.our_state) token = channel_state.token_address recipient = channel_state.partner_state.address balance_proof = BalanceProofUnsignedState( nonce, transferred_amount, locksroot, channel_state.identifier, ) direct_transfer = SendDirectTransfer( identifier, balance_proof, token, recipient, ) return direct_transfer def create_sendmediatedtransfer( channel_state, initiator, target, amount, identifier, expiration, hashlock): our_state = channel_state.our_state partner_state = channel_state.partner_state our_balance_proof = our_state.balance_proof # The caller must check the capacity prior to the call msg = 'caller must make sure there is enough balance' assert amount <= get_distributable(our_state, partner_state), msg lock = HashTimeLockState( amount, expiration, hashlock, ) merkletree = compute_merkletree_with( channel_state.our_state.merkletree, lock.lockhash, ) # The caller must ensure the same lock is not being used twice assert merkletree, 'lock is already registered' locksroot = merkleroot(merkletree) if our_balance_proof: transferred_amount = our_balance_proof.transferred_amount else: transferred_amount = 0 token = channel_state.token_address nonce = get_next_nonce(channel_state.our_state) recipient = channel_state.partner_state.address balance_proof = BalanceProofUnsignedState( nonce, transferred_amount, locksroot, channel_state.identifier, ) locked_transfer = LockedTransferUnsignedState( identifier, token, balance_proof, lock, initiator, target, ) mediatedtransfer = SendMediatedTransfer( locked_transfer, recipient, ) return mediatedtransfer, merkletree def create_unlock(channel_state, identifier, secret, lock): msg = 'caller must make sure the lock is known' assert is_known(channel_state.our_state, lock.hashlock), msg our_balance_proof = channel_state.our_state.balance_proof if our_balance_proof: transferred_amount = lock.amount + our_balance_proof.transferred_amount else: transferred_amount = lock.amount merkletree = compute_merkletree_without( channel_state.our_state.merkletree, lock.lockhash, ) locksroot = merkleroot(merkletree) token = channel_state.token_address nonce = get_next_nonce(channel_state.our_state) recipient = channel_state.partner_state.address balance_proof = BalanceProofUnsignedState( nonce, transferred_amount, locksroot, channel_state.identifier, ) unlock_lock = SendBalanceProof( identifier, token, recipient, secret, balance_proof, ) return unlock_lock, merkletree def send_directtransfer(channel_state, amount, identifier): direct_transfer = create_senddirecttransfer( channel_state, amount, identifier, ) channel_state.our_state.balance_proof = direct_transfer.balance_proof return direct_transfer def send_mediatedtransfer( channel_state, initiator, target, amount, identifier, expiration, hashlock): send_event, merkletree = create_sendmediatedtransfer( channel_state, initiator, target, amount, identifier, expiration, hashlock, ) transfer = send_event.transfer lock = transfer.lock channel_state.our_state.balance_proof = transfer.balance_proof channel_state.our_state.merkletree = merkletree channel_state.our_state.hashlocks_to_pendinglocks[lock.hashlock] = lock return send_event def send_refundtransfer( channel_state, initiator, target, amount, identifier, expiration, hashlock): msg = 'Refunds are only valid for *know and pending* transfers' assert hashlock in channel_state.partner_state.hashlocks_to_pendinglocks, msg send_mediated_transfer, merkletree = create_sendmediatedtransfer( channel_state, initiator, target, amount, identifier, expiration, hashlock, ) mediated_transfer = send_mediated_transfer.transfer lock = mediated_transfer.lock channel_state.our_state.balance_proof = mediated_transfer.balance_proof channel_state.our_state.merkletree = merkletree channel_state.our_state.hashlocks_to_pendinglocks[lock.hashlock] = lock refund_transfer = refund_from_sendmediated(send_mediated_transfer) return refund_transfer def send_unlock(channel_state, identifier, secret, hashlock): lock = get_lock(channel_state.our_state, hashlock) assert lock unlock_lock, merkletree = create_unlock( channel_state, identifier, secret, lock, ) channel_state.our_state.balance_proof = unlock_lock.balance_proof channel_state.our_state.merkletree = merkletree del_lock(channel_state.our_state, lock.hashlock) return unlock_lock def events_for_close(channel_state, block_number): events = list() if get_status(channel_state) in CHANNEL_STATES_PRIOR_TO_CLOSED: channel_state.close_transaction = TransactionExecutionStatus( block_number, None, None ) close_event = ContractSendChannelClose( channel_state.identifier, channel_state.token_address, channel_state.partner_state.balance_proof, ) events.append(close_event) return events def register_secret_endstate(end_state, secret, hashlock): if is_locked(end_state, hashlock): pendinglock = end_state.hashlocks_to_pendinglocks[hashlock] del end_state.hashlocks_to_pendinglocks[hashlock] end_state.hashlocks_to_unclaimedlocks[hashlock] = UnlockPartialProofState( pendinglock, secret, ) def register_secret(channel_state, secret, hashlock): """This will register the secret and set the lock to the unlocked stated. Even though the lock is unlock it's is *not* claimed. The capacity will increase once the next balance proof is received. """ our_state = channel_state.our_state partner_state = channel_state.partner_state register_secret_endstate(our_state, secret, hashlock) register_secret_endstate(partner_state, secret, hashlock) def handle_send_directtransfer(channel_state, state_change): events = list() amount = state_change.amount identifier = state_change.identifier distributable_amount = get_distributable(channel_state.our_state, channel_state.partner_state) is_open = get_status(channel_state) == CHANNEL_STATE_OPENED is_valid = amount > 0 can_pay = amount <= distributable_amount if is_open and is_valid and can_pay: direct_transfer = send_directtransfer( channel_state, amount, identifier, ) events.append(direct_transfer) else: if not is_open: failure = EventTransferSentFailed( state_change.identifier, 'Channel is not opened', ) events.append(failure) elif not is_valid: msg = 'Transfer amount is invalid. Transfer: {}'.format(amount) failure = EventTransferSentFailed(state_change.identifier, msg) events.append(failure) elif not can_pay: msg = ( 'Transfer amount exceeds the available capacity. ' 'Capacity: {}, Transfer: {}' ).format( distributable_amount, amount, ) failure = EventTransferSentFailed(state_change.identifier, msg) events.append(failure) return TransitionResult(channel_state, events) def handle_action_close(channel_state, close, block_number): msg = 'caller must make sure the ids match' assert channel_state.identifier == close.channel_identifier, msg events = events_for_close(channel_state, block_number) return TransitionResult(channel_state, events) def handle_receive_directtransfer(channel_state, direct_transfer): is_valid, msg = is_valid_directtransfer( direct_transfer, channel_state, channel_state.partner_state, channel_state.our_state, ) if is_valid: _, _, previous_transferred_amount = get_current_balanceproof(channel_state.partner_state) new_transferred_amount = direct_transfer.balance_proof.transferred_amount transfer_amount = new_transferred_amount - previous_transferred_amount channel_state.partner_state.balance_proof = direct_transfer.balance_proof event = EventTransferReceivedSuccess( direct_transfer.transfer_identifier, transfer_amount, channel_state.partner_state.address, ) events = [event] else: event = EventTransferReceivedInvalidDirectTransfer( direct_transfer.transfer_identifier, reason=msg, ) events = [event] return TransitionResult(channel_state, events) def handle_receive_mediatedtransfer( channel_state: 'NettingChannelState', mediated_transfer: 'LockedTransferSignedState' ): """Register the latest known transfer. The receiver needs to use this method to update the container with a _valid_ transfer, otherwise the locksroot will not contain the pending transfer. The receiver needs to ensure that the merkle root has the hashlock included, otherwise it won't be able to claim it. """ is_valid, msg, merkletree = is_valid_mediatedtransfer( mediated_transfer, channel_state, channel_state.partner_state, channel_state.our_state, ) if is_valid: channel_state.partner_state.balance_proof = mediated_transfer.balance_proof channel_state.partner_state.merkletree = merkletree lock = mediated_transfer.lock channel_state.partner_state.hashlocks_to_pendinglocks[lock.hashlock] = lock return is_valid, msg def handle_receive_refundtransfer(channel_state, refund_transfer): return handle_receive_mediatedtransfer(channel_state, refund_transfer) def handle_receive_secretreveal(channel_state, state_change): secret = state_change.secret hashlock = state_change.hashlock register_secret(channel_state, secret, hashlock) def handle_unlock(channel_state, unlock): is_valid, msg, unlocked_merkletree = is_valid_unlock( unlock, channel_state, channel_state.partner_state, ) if is_valid: channel_state.partner_state.balance_proof = unlock.balance_proof channel_state.partner_state.merkletree = unlocked_merkletree del_lock(channel_state.partner_state, unlock.hashlock) return is_valid, msg def handle_block(channel_state, state_change, block_number): assert state_change.block_number == block_number events = list() if get_status(channel_state) == CHANNEL_STATE_CLOSED: closed_block_number = channel_state.close_transaction.finished_block_number settlement_end = closed_block_number + channel_state.settle_timeout if state_change.block_number > settlement_end: channel_state.settle_transaction = TransactionExecutionStatus( state_change.block_number, None, None ) event = ContractSendChannelSettle(channel_state.identifier) events.append(event) while is_deposit_confirmed(channel_state, block_number): order_deposit_transaction = heapq.heappop(channel_state.deposit_transaction_queue) apply_channel_newbalance( channel_state, order_deposit_transaction.transaction, ) return TransitionResult(channel_state, events) def handle_channel_closed(channel_state, state_change): events = list() just_closed = ( state_change.channel_identifier == channel_state.identifier and get_status(channel_state) in CHANNEL_STATES_PRIOR_TO_CLOSED ) if just_closed: set_closed(channel_state, state_change.closed_block_number) balance_proof = channel_state.partner_state.balance_proof call_update = ( state_change.closing_address != channel_state.our_state.address and balance_proof ) if call_update: # The channel was closed by our partner, if there is a balance # proof available update this node half of the state update = ContractSendChannelUpdateTransfer( channel_state.identifier, balance_proof, ) events.append(update) unlock_proofs = get_known_unlocks(channel_state.partner_state) if unlock_proofs: withdraw = ContractSendChannelWithdraw( channel_state.identifier, unlock_proofs, ) events.append(withdraw) return TransitionResult(channel_state, events) def handle_channel_settled(channel_state, state_change): events = list() if state_change.channel_identifier == channel_state.identifier: set_settled(channel_state, state_change.settle_block_number) return TransitionResult(channel_state, events) def handle_channel_newbalance(channel_state, state_change, block_number): deposit_transaction = state_change.deposit_transaction if is_transaction_confirmed(deposit_transaction.deposit_block_number, block_number): apply_channel_newbalance(channel_state, state_change.deposit_transaction) else: order = TransactionOrder( deposit_transaction.deposit_block_number, deposit_transaction, ) heapq.heappush(channel_state.deposit_transaction_queue, order) events = list() return TransitionResult(channel_state, events) def apply_channel_newbalance(channel_state, deposit_transaction): participant_address = deposit_transaction.participant_address if participant_address == channel_state.our_state.address: new_balance = max( channel_state.our_state.contract_balance, deposit_transaction.contract_balance, ) channel_state.our_state.contract_balance = new_balance elif participant_address == channel_state.partner_state.address: new_balance = max( channel_state.partner_state.contract_balance, deposit_transaction.contract_balance, ) channel_state.partner_state.contract_balance = new_balance def handle_channel_withdraw(channel_state, state_change): hashlock = state_change.hashlock secret = state_change.secret our_withdraw = ( state_change.receiver == channel_state.our_state.address and is_locked(channel_state.partner_state, hashlock) ) # FIXME: must not remove the lock, otherwise a new unlock proof cannot be # made if our_withdraw: del_lock(channel_state.partner_state, hashlock) partner_withdraw = ( state_change.receiver == channel_state.partner_state.address and is_locked(channel_state.our_state, hashlock) ) if partner_withdraw: del_lock(channel_state.our_state, hashlock) # Withdraw is required if there was a refund in this channel, and the # secret is learned from the withdraw event. events = [] if is_locked(channel_state.our_state, hashlock): lock = get_lock(channel_state.our_state, hashlock) proof = compute_proof_for_lock(channel_state.our_state, secret, lock) withdraw = ContractSendChannelWithdraw(channel_state.identifier, [proof]) events.append(withdraw) register_secret(channel_state, secret, hashlock) return TransitionResult(channel_state, events) def state_transition(channel_state, state_change, block_number): # pylint: disable=too-many-branches,unidiomatic-typecheck events = list() iteration = TransitionResult(channel_state, events) if type(state_change) == Block: iteration = handle_block(channel_state, state_change, block_number) elif type(state_change) == ActionChannelClose: iteration = handle_action_close(channel_state, state_change, block_number) elif type(state_change) == ActionTransferDirect: iteration = handle_send_directtransfer(channel_state, state_change) elif type(state_change) == ContractReceiveChannelClosed: iteration = handle_channel_closed(channel_state, state_change) elif type(state_change) == ContractReceiveChannelSettled: iteration = handle_channel_settled(channel_state, state_change) elif type(state_change) == ContractReceiveChannelNewBalance: iteration = handle_channel_newbalance(channel_state, state_change, block_number) elif type(state_change) == ContractReceiveChannelWithdraw: iteration = handle_channel_withdraw(channel_state, state_change) elif type(state_change) == ReceiveTransferDirect: iteration = handle_receive_directtransfer(channel_state, state_change) return iteration
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script_example.py
op8867555/BGmi
0
20340
import datetime from bgmi.script import ScriptBase from bgmi.utils import parse_episode class Script(ScriptBase): class Model(ScriptBase.Model): bangumi_name = "TEST_BANGUMI" cover = "" update_time = "Mon" due_date = datetime.datetime(2017, 9, 30) def get_download_url(self): # fetch and return dict # ignore they are not same bangumi. resp = [ { "title": "[c.c动漫][4月新番][影之诗][ShadowVerse][01][简日][HEVC][1080P][MP4]", "link": "http://example.com/Bangumi/1/1.torrent", }, { "title": "[YMDR][慕留人 -火影忍者新时代-][2017][2][AVC][JAP][BIG5][MP4][1080P]", "link": "http://example.com/Bangumi/1/2.torrent", }, { "title": "[ZXSUB仲夏动漫字幕组][博人传-火影忍者次世代][03][720P繁体][MP4]", "link": "magnet:?xt=urn:btih:233", }, ] ret = {} for item in resp: e = parse_episode(item["title"]) if e: ret[e] = item["link"] return ret if __name__ == "__main__": s = Script() print(s.get_download_url())
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src/streamlink/plugins/clubbingtv.py
code-review-doctor/streamlink
0
92117
""" $url clubbingtv.com $type live, vod $account Login required """ import logging import re from streamlink.plugin import Plugin, PluginArgument, PluginArguments, pluginmatcher from streamlink.stream.hls import HLSStream log = logging.getLogger(__name__) @pluginmatcher(re.compile( r"https?://(www\.)?clubbingtv\.com/" )) class ClubbingTV(Plugin): _login_url = "https://www.clubbingtv.com/user/login" _live_re = re.compile( r'playerInstance\.setup\({\s*"file"\s*:\s*"(?P<stream_url>.+?)"', re.DOTALL, ) _vod_re = re.compile(r'<iframe src="(?P<stream_url>.+?)"') arguments = PluginArguments( PluginArgument( "username", required=True, requires=["password"], help="The username used to register with Clubbing TV.", ), PluginArgument( "password", required=True, sensitive=True, help="A Clubbing TV account password to use with --clubbingtv-username.", ), ) def login(self): username = self.get_option("username") password = self.get_option("password") res = self.session.http.post( self._login_url, data={"val[login]": username, "val[password]": password}, ) if "Invalid Email/User Name" in res.text: log.error( "Failed to login to Clubbing TV, incorrect email/password combination" ) return False log.info("Successfully logged in") return True def _get_live_streams(self, content): match = self._live_re.search(content) if not match: return stream_url = match.group("stream_url") yield from HLSStream.parse_variant_playlist(self.session, stream_url).items() def _get_vod_streams(self, content): match = self._vod_re.search(content) if not match: return stream_url = match.group("stream_url") log.info( "Fetching external stream from URL {0}".format(stream_url) ) return self.session.streams(stream_url) def _get_streams(self): if not self.login(): return self.session.http.headers.update({"Referer": self.url}) res = self.session.http.get(self.url) if "clubbingtv.com/live" in self.url: log.debug("Live stream detected") return self._get_live_streams(res.text) log.debug("VOD stream detected") return self._get_vod_streams(res.text) __plugin__ = ClubbingTV
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sjb/actions/deprovision.py
brenton/aos-cd-jobs
45
96180
from __future__ import absolute_import, print_function, unicode_literals from .interface import Action from .named_shell_task import render_task _DEPROVISION_TITLE = "DEPROVISION CLOUD RESOURCES" _DEPROVISION_ACTION = "oct deprovision" class DeprovisionAction(Action): """ A DeprovisionAction generates a post-build step that deprovisions the remote host. """ def generate_post_build_steps(self): return [render_task( title=_DEPROVISION_TITLE, command=_DEPROVISION_ACTION, output_format=self.output_format )]
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okdata/sdk/permission/user_types.py
oslokommune/okdata-sdk-python
2
109431
# TODO: Use these simplified dataclasses once support for Python 3.6 is # dropped. Meanwhile we'll use the "polyfill" classes defined below. # # from dataclasses import dataclass, field # # @dataclass # class Client: # user_id: str # user_type: str = field(default="client", init=False) # # # @dataclass # class Team: # user_id: str # user_type: str = field(default="team", init=False) # # # @dataclass # class User: # user_id: str # user_type: str = field(default="user", init=False) class Client: user_id: str user_type: str def __init__(self, user_id): self.user_id = user_id self.user_type = "client" class Team: user_id: str user_type: str def __init__(self, user_id): self.user_id = user_id self.user_type = "team" class User: user_id: str user_type: str def __init__(self, user_id): self.user_id = user_id self.user_type = "user" def asdict(obj): return obj.__dict__
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scripts/kmer/get_kmer_list.py
mahajrod/MAVR
10
196439
#!/usr/bin/env python __author__ = '<NAME>' import os import argparse from Bio import SeqIO os.environ['MPLCONFIGDIR'] = '/tmp/' import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt plt.ioff() from RouToolPa.GeneralRoutines.File import make_list_of_path_to_files from RouToolPa.Tools.Kmers import Jellyfish from RouToolPa.Routines.Sequence import rev_com_generator parser = argparse.ArgumentParser() parser.add_argument("-i", "--input_file", action="store", dest="input", type=lambda s: s.split(","), help="Comma-separated list of fasta or fastq files or directories containing them.") parser.add_argument("-m", "--kmer_length", action="store", dest="kmer_length", type=int, default=23, help="Length of kmers") parser.add_argument("-s", "--hash_size", action="store", dest="hash_size", type=str, default="10G", help="Size of hash. Estimation of hash size: for short reads S=(G + k*n)/0.8, " "G - genome size, k - kmer length, n - number of reads, for assembled sequences " "S=Sum(L)") parser.add_argument("-a", "--base_prefix", action="store", dest="base_prefix", default="jellyfish_db", help="Name of kmer database. Default: jellyfish_db") parser.add_argument("-t", "--threads", action="store", dest="threads", type=int, default=1, help="Number of threads") parser.add_argument("-b", "--count_both_strands", action="store_true", dest="count_both_strands", help="Count kmers in both strands. NOTICE: only mer or its reverse-complement, whichever " "comes first lexicographically, is stored and the count value is the number of " "occurrences of both. So this option is not suitable for generating sets of forward " "and reverse-complement kmers. For this case use -r/--add_reverse_complement option. " "Not compatible with -r/--add_reverse_complement option.") parser.add_argument("-r", "--add_reverse_complement", action="store_true", dest="add_rev_com", help="Add reverse-complement sequences before counting kmers. " "Works only for fasta sequences. " "Not compatible with -b/--count_both_strands option") parser.add_argument("-d", "--draw_distribution", action="store_true", dest="draw_distribution", help="Draw distribution of kmers") parser.add_argument("-j", "--jellyfish_path", action="store", dest="jellyfish_path", help="Path to jellyfish") parser.add_argument("-n", "--dont_extract_kmer_list", action="store_true", dest="dont_extract_kmer_list", help="Don't extract kmer list") args = parser.parse_args() args.input = make_list_of_path_to_files(args.input) if args.count_both_strands and args.add_rev_com: raise ValueError("Options -b/--count_both_strands and -r/--add_reverse_complement are not compatible") if args.add_rev_com: file_with_rev_com = args.base_prefix + "_with_rev_com.fasta" record_dict = SeqIO.index_db("temp_index.idx", args.input, format="fasta") SeqIO.write(rev_com_generator(record_dict, yield_original_record=True), file_with_rev_com, "fasta") args.base_prefix += "_with_rev_com" base_file = "%s_%i_mer.jf" % (args.base_prefix, args.kmer_length) kmer_table_file = "%s_%i_mer.counts" % (args.base_prefix, args.kmer_length) kmer_file = "%s_%i_mer.kmer" % (args.base_prefix, args.kmer_length) Jellyfish.threads = args.threads Jellyfish.path = args.jellyfish_path if args.jellyfish_path else "" Jellyfish.count(args.input if not args.add_rev_com else file_with_rev_com, base_file, kmer_length=args.kmer_length, hash_size=args.hash_size, count_both_strands=args.count_both_strands) if not args.dont_extract_kmer_list: Jellyfish.dump(base_file, kmer_table_file) sed_string = 'sed -e "s/\t.*//" %s > %s' % (kmer_table_file, kmer_file) os.system(sed_string) if args.draw_distribution: histo_file = "%s_%i_mer.histo" % (args.base_prefix, args.kmer_length) picture_prefix = "%s_%i_mer_histogram" % (args.base_prefix, args.kmer_length) Jellyfish.histo(base_file, histo_file, upper_count=10000000) counts = [] bins = [] with open(histo_file, "r") as histo_fd: for line in histo_fd: entry = line.strip().split() counts.append(entry[1]) bins.append(entry[0]) figure = plt.figure(1, figsize=(8, 8), dpi=300) subplot = plt.subplot(1, 1, 1) plt.suptitle("Distribution of %i-mers" % args.kmer_length, fontweight='bold') plt.plot(bins, counts) plt.xlabel("Multiplicity") plt.ylabel("Number of distinct kmers") subplot.set_yscale('log', basey=10) subplot.set_xscale('log', basex=10) for extension in ["png", "svg"]: plt.savefig("%s.%s" % (picture_prefix, extension)) if args.add_rev_com: os.remove("temp_index.idx")
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front_end/app.py
ofbennett/sentiment-analysis-app
2
174590
import dash import dash_core_components as dcc import dash_bootstrap_components as dbc import dash_html_components as html from dash.dependencies import Input, Output import config import requests from markdown import md1, md2 colors = {'background': 'lightcyan'} app = dash.Dash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP], meta_tags=[{"name": "viewport", "content": "width=device-width, initial-scale=1"}]) app.title = "Sentiment Analyser" sentiment_analysis_layout = html.Div( [ html.H1("Sentiment Analyzer", style={'padding-top':'20px','margin-bottom':'30px', 'text-decoration': 'underline'}), # html.Div(children="<NAME>, October 2020", style={'textAlign':'right', 'margin-right':'20px'}), html.Div(id="text-area", children=[ dcc.Textarea(id="text", placeholder="Write something here...", style={'width': '100%', 'height': 180}), dbc.Progress(id="bar", value=50, color='info') ]), html.Div(id="result", children="Sentiment Prediction", style={'margin': '10px', 'height': '1em'}), html.Div(id="markdown-area", children=[dcc.Markdown(md1, id="markdown1"), html.Img(src="assets/system_diagram.png",style = {"width": "75%", "display": "block", "margin-left": "auto", "margin-right": "auto"}), dcc.Markdown(md2, id="markdown2"),]) ], style={'textAlign':'center', 'backgroundColor': colors['background']}) app.layout = sentiment_analysis_layout @app.callback([Output('result', 'children'), Output('bar','value'), Output('bar','color')], [Input('text','value')], prevent_initial_call=True) def update_result(text): if text.strip() != '': json_data = {'text': text, 'pred_type': 'soft'} response = requests.post(config.API_URL, json=json_data) if response.status_code == 200: response_json_data = response.json() pred_val = response_json_data['pred'] pred_val = float(pred_val) if pred_val < 0.2: pred = 'Negative' bar_color = 'danger' elif 0.2 <= pred_val < 0.4: pred = 'Lean Negative' bar_color = 'info' elif 0.4 <= pred_val < 0.6: pred = 'Neutral' bar_color = 'info' elif 0.6 <= pred_val < 0.8: pred = 'Lean Positive' bar_color = 'info' else: pred = 'Positive' bar_color = 'success' return [pred, pred_val*100, bar_color] else: print(f"Error response from API. Code: {response.status_code}") return ['Sentiment Prediction', 50, 'info'] else: return ['Sentiment Prediction', 50, 'info'] server = app.server if __name__ == '__main__': app.run_server(debug=config.DEBUG, host=config.HOST)
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jina/drivers/convert.py
shivam-raj/jina
0
1616282
__copyright__ = "Copyright (c) 2020 Jina AI Limited. All rights reserved." __license__ = "Apache-2.0" import base64 import os import struct import urllib.parse import urllib.request import zlib import numpy as np from . import BaseDriver from .helper import guess_mime, array2pb, pb2array class BaseConvertDriver(BaseDriver): def __init__(self, target: str, override: bool = False, *args, **kwargs): """ Set a target attribute of the document by another attribute :param target: attribute to set :param override: override the target value even when exits :param args: :param kwargs: """ super().__init__(*args, **kwargs) self.override = override self.target = target def __call__(self, *args, **kwargs): for d in self.docs: if getattr(d, self.target) and not self.override: continue self.convert(d) def convert(self, d): raise NotImplementedError class MIMEDriver(BaseConvertDriver): """Guessing the MIME type based on the doc content Can be used before/after :class:`DocCraftDriver` to fill MIME type """ def __init__(self, target='mime', default_mime: str = 'application/octet-stream', *args, **kwargs): """ :param default_mime: for text documents without a specific subtype, text/plain should be used. Similarly, for binary documents without a specific or known subtype, application/octet-stream should be used. """ super().__init__(target, *args, **kwargs) self.default_mime = default_mime self.buffer_sniff = False try: import magic self.buffer_sniff = True except (ImportError, ModuleNotFoundError): self.logger.warning(f'can not sniff the MIME type ' f'MIME sniffing requires pip install "jina[http]" ' f'and brew install libmagic (Mac)/ apt-get install libmagic1 (Linux)') def convert(self, d): import mimetypes m_type = d.mime_type if m_type and (m_type not in mimetypes.types_map.values()): m_type = mimetypes.guess_type(f'*.{m_type}')[0] if not m_type: # for ClientInputType=PROTO, d_type could be empty d_type = d.WhichOneof('content') if d_type == 'buffer': d_content = getattr(d, d_type) if self.buffer_sniff: try: import magic m_type = magic.from_buffer(d_content, mime=True) except Exception as ex: self.logger.warning(f'can not sniff the MIME type due to the exception {ex}') if d.uri: m_type = guess_mime(d.uri) if m_type: d.mime_type = m_type else: d.mime_type = self.default_mime self.logger.warning(f'can not determine the MIME type, set to default {self.default_mime}') class Buffer2NdArray(BaseConvertDriver): """Convert buffer to numpy array""" def __init__(self, target='blob', *args, **kwargs): super().__init__(target, *args, **kwargs) def convert(self, d): d.blob.CopyFrom(array2pb(np.frombuffer(d.buffer))) class Blob2PngURI(BaseConvertDriver): """Simple DocCrafter used in :command:`jina hello-world`, it reads ``buffer`` into base64 png and stored in ``uri``""" def __init__(self, target='uri', width: int = 28, height: int = 28, *args, **kwargs): super().__init__(target, *args, **kwargs) self.width = width self.height = height def convert(self, d): arr = pb2array(d.blob) pixels = [] for p in arr[::-1]: pixels.extend([255 - int(p), 255 - int(p), 255 - int(p), 255]) buf = bytearray(pixels) # reverse the vertical line order and add null bytes at the start width_byte_4 = self.width * 4 raw_data = b''.join( b'\x00' + buf[span:span + width_byte_4] for span in range((self.height - 1) * width_byte_4, -1, - width_byte_4)) def png_pack(png_tag, data): chunk_head = png_tag + data return (struct.pack('!I', len(data)) + chunk_head + struct.pack('!I', 0xFFFFFFFF & zlib.crc32(chunk_head))) png_bytes = b''.join([ b'\x89PNG\r\n\x1a\n', png_pack(b'IHDR', struct.pack('!2I5B', self.width, self.height, 8, 6, 0, 0, 0)), png_pack(b'IDAT', zlib.compress(raw_data, 9)), png_pack(b'IEND', b'')]) d.uri = 'data:image/png;base64,' + base64.b64encode(png_bytes).decode() class URI2Buffer(BaseConvertDriver): """ Convert local file path, remote URL doc to a buffer doc. """ def __init__(self, target='buffer', *args, **kwargs): super().__init__(target, *args, **kwargs) def convert(self, d): if urllib.parse.urlparse(d.uri).scheme in {'http', 'https', 'data'}: page = urllib.request.Request(d.uri, headers={'User-Agent': 'Mozilla/5.0'}) tmp = urllib.request.urlopen(page) d.buffer = tmp.read() elif os.path.exists(d.uri): with open(d.uri, 'rb') as fp: d.buffer = fp.read() else: raise FileNotFoundError(f'{d.uri} is not a URL or a valid local path') class URI2DataURI(URI2Buffer): def __init__(self, target='uri', charset: str = 'utf-8', base64: bool = False, *args, **kwargs): """ Convert file path doc to data uri doc. Internally it first reads into buffer and then converts it to data URI. :param charset: charset may be any character set registered with IANA :param base64: used to encode arbitrary octet sequences into a form that satisfies the rules of 7bit. Designed to be efficient for non-text 8 bit and binary data. Sometimes used for text data that frequently uses non-US-ASCII characters. :param args: :param kwargs: """ super().__init__(target, *args, **kwargs) self.charset = charset self.base64 = base64 def __call__(self, *args, **kwargs): super().__call__() for d in self.docs: if d.uri and not self.override: continue if d.uri and urllib.parse.urlparse(d.uri).scheme == 'data': pass else: d.uri = self.make_datauri(d.mime_type, d.buffer) def make_datauri(self, mimetype, data, binary=True): parts = ['data:', mimetype] if self.charset is not None: parts.extend([';charset=', self.charset]) if self.base64: parts.append(';base64') from base64 import encodebytes as encode64 if binary: encoded_data = encode64(data).decode(self.charset).replace('\n', '').strip() else: encoded_data = encode64(data).strip() else: from urllib.parse import quote_from_bytes, quote if binary: encoded_data = quote_from_bytes(data) else: encoded_data = quote(data) parts.extend([',', encoded_data]) return ''.join(parts) class Buffer2URI(URI2DataURI): """Convert buffer to data URI""" def convert(self, d): if urllib.parse.urlparse(d.uri).scheme == 'data': pass else: d.uri = self.make_datauri(d.mime_type, d.buffer) class Text2URI(URI2DataURI): """Convert text to data URI""" def convert(self, d): d.uri = self.make_datauri(d.mime_type, d.text, binary=False) class All2URI(Text2URI, Buffer2URI): def convert(self, d): if d.text: Text2URI.convert(self, d) elif d.buffer: Buffer2URI.convert(self, d) else: raise NotImplementedError
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Chapter08/lecture02.py
ee06b056/IntoToProgramInPython
0
48797
import datetime class Person(object): def __init__(self, name): self.name = name try: lastBlank = name.rindex(' ') self.lastName = name[lastBlank+1:] except: self.lastName = name self.birthday = None def getName(self): return self.name def getLastName(self): return self.lastName def setBirthday(self, birthday): self.birthday = birthday def getAge(self): if self.birthday == None: raise ValueError return (datetime.date.today() - self.birthday).days def __lt__(self, other): if self.lastName == other.lastName: return self.name < other.name return self.lastName < other.lastName def __str__(self): return self.name class MITPerson(Person): nextIdNum = 0 def __init__(self,name): Person.__init__(self, name) self.idNum = MITPerson.nextIdNum MITPerson.nextIdNum += 1 def getIdNum(self): return self.idNum def __lt__(self, other): return self.idNum < other.idNum class Student(MITPerson): pass class UG(Student): def __init__(self, name, classYear): Student.__init__(self, name) self.year = classYear def getClass(self): return self.year class Grad(Student): pass class TransferStudent(Student): def __init__(self, name, fromSchool): Student.__init__(self, name) self.fromSchool = fromSchool def getOldSchool(self): return self.fromSchool class Grades(object): def __init__(self): self.students = [] p5 = Grad('<NAME>') p6 = UG('<NAME>', 1984) print(p5) print(type(p5)==Grad) print(p6, type(p6) == UG) print(UG) me = Person('<NAME>') him = Person('<NAME>') her = Person('Madonna') print(him.getLastName()) him.setBirthday(datetime.date(1961,8,4)) her.setBirthday(datetime.date(1958, 8, 16)) p1 = MITPerson('<NAME>') print(str(p1) + '\'s id number is ' + str(p1.getIdNum()))
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Game.py
RHorton97/Hangman-Game
0
148477
<reponame>RHorton97/Hangman-Game import random as rand class Game(): """Holds setup functions and key gameplay data such as the word being guessed""" def __init__(self): self.name = input("What is your name? ") self.guesses = 5 self.word = self.wordSelect() self.wordLength = len(self.word) self.unguessedLetters = self.wordLength self.wordWithGuesses = self.wordForGuesses(self.word) self.playerWins = False self.guessWrong = False self.gameOver = False def beginGame(self): """Begins the game by stating the length of the word and showing a blank space with underscores to represent each letter of the word""" print("You have " + str(self.guesses) + " wrong guesses") print("\nThe word is " + str(self.wordLength) + " letters long") print(self.unguessedLetters * "_ " + "\n") def resetGame(self): self.gameOver = False self.guesses = 5 self.word = self.wordSelect() self.wordLength = len(self.word) self.unguessedLetters = self.wordLength self.wordWithGuesses = self.wordForGuesses(self.word) def guessDown(self): """Remove one guess from total remaining guesses""" self.guesses = self.guesses - 1 def wordSelect(self): """Selects a word from the wordList file and stores it to be used in the game""" # wordNum range starts from 1 to ensuure that the source URL in the # wordList file is never selected as the word wordNum = rand.randint(1, 1000) wordList = open("wordList.txt", "r") for i in range(wordNum + 1): if i == wordNum: word = wordList.readline() word = word[:-1] else: wordList.readline() wordList.close() return word def wordForGuesses(self, word): """Creates a list containing one underscore as an element for each letter of the chosen word which is taken as input to the function""" wordListed = [] for letter in word: wordListed.append("_") return wordListed def wordGuess(self): """Allows the user to input a word as a guess, if the word is correct then the player wins the game, if the word is not correct then the player is told and the list of guessed and unguessed letters is printed so that it is visible to the player""" wordGuessed = input("What is your guess? ") if wordGuessed == self.word: self.playerWins = True print("Congratulations! You guessed correctly, the word was " + self.word + "!") self.gameWon() else: print("Sorry, that isn't the word") self.guessDown() self.lifeCheck() def letterGuess(self): """Allows the user to input a letter as a guess, if the letter is in the word then it replaces the appropriate characters in the list created by wordForGuesses, if the letter is not in the word then the player is told that they were wrong. The list containing underscores and letters is displayed at the end of the function each time in order to ensure it is visible to the player at all times""" letterGuessed = input("What is your guess? ") if letterGuessed in self.word: i = 0 for letter in self.word: if letter == letterGuessed: self.wordWithGuesses[i] = letterGuessed i = i + 1 else: print("Sorry, that letter isn't in the word") self.guessDown() self.lifeCheck() self.allLettersCheck() if self.playerWins == False: if self.unguessedLetters == 1: print("There is " + str(self.unguessedLetters) + " letter left to guess\n") else: print("There are " + str(self.unguessedLetters) + " letters left to guess\n") showWordGuesses = "" for letter in self.wordWithGuesses: showWordGuesses = showWordGuesses + letter + " " print(showWordGuesses + "\n") def allLettersCheck(self): """Checks if the player has guessed all the letters in the word correctly, if they have then the player wins the game, if not the function determines how many letters are left to be guessed and updates the unguessed letters value""" if "_" not in self.wordWithGuesses: self.playerWins = True self.gameWon() else: i = 0 for letter in self.wordWithGuesses: if letter == "_": i = i + 1 else: continue self.unguessedLetters = i def lifeCheck(self): if self.guesses <= 0: print("You have no wrong guesses remaining") self.gameLost() else: print("You have " + str(self.guesses) + " wrong guesses left") def gameWon(self): """This function tells the player they have won""" self.gameOver = True print("\nCongratulations " + self.name + "! You Win!") def gameLost(self): """This function tells the player they have lost""" self.gameOver = True print("\nThe word was " + self.word) print("\nSorry " + self.name + ". You Lose!")
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State.py
hhojatansari/DatasetDecoder
1
111179
import datetime as dt ClassLabel = { "NoLabel": "0", "Meal_Preparation": "1", "Relax": "2", "Eating": "3", "Work": "4", "Sleeping": "5", "Wash_Dishes": "6", "Bed_to_Toilet": "7", "Enter_Home": "8", "Leave_Home": "9", "Housekeeping": "10", "Respirate": "11" } class State: def __init__(self): self.overloaded = False self.counter = 0 self.datetime = dt.datetime.now() self.data = { "date": "00-00-00", "time": "00:00:00", "M001": "0", "M002": "0", "M003": "0", "M004": "0", "M005": "0", "M006": "0", "M007": "0", "M008": "0", "M009": "0", "M010": "0", "M011": "0", "M012": "0", "M013": "0", "M014": "0", "M015": "0", "M016": "0", "M017": "0", "M018": "0", "M019": "0", "M020": "0", "M021": "0", "M022": "0", "M023": "0", "M024": "0", "M025": "0", "M026": "0", "M027": "0", "M028": "0", "M029": "0", "M030": "0", "M031": "0", "T001": "20.0", "T002": "20.0", "T003": "20.0", "T004": "20.0", "T005": "20.0", "D001": "0", "D002": "0", "D003": "0", "D004": "0", "Label": "NoLabel" } def __eq__(self, other): if (self.data["date"] == other.data["date"] and self.data["time"] == other.data["time"]): return True def __sub__(self, other): dis = self.datetime - other.datetime return dis.days * 24 * 60 * 60 + dis.seconds - 1 def textParser(self, string): year, month, day = string.split()[0].split("-") hour, minute, second = string.split()[1].split(":") year = int(year) month = int(month) day = int(day) hour = int(hour) minute = int(minute) if(round(float(second), 0) > 59): second = int(eval(second)) self.overloaded = True else: second = int(round(float(second), 0)) self.datetime = dt.datetime(year, month, day, hour, minute, second) if(self.overloaded): self.incrementTime() self.data["date"] = str(self.datetime.year) + "-" + "{0:0=2d}".format(self.datetime.month) + \ "-" + "{0:0=2d}".format(self.datetime.day) self.data["time"] = "{0:0=2d}".format(self.datetime.hour) + ":" + "{0:0=2d}".format(self.datetime.minute) + \ ":" + "{0:0=2d}".format(self.datetime.second) if (len(string.split()) == 6 or len(string.split()) == 4): if (string.split()[3] == "ON" or string.split()[3] == "OPEN"): self.data[string.split()[2]] = "1" elif (string.split()[3] == "OFF" or string.split()[3] == "CLOSE"): self.data[string.split()[2]] = "0" else: self.data[string.split()[2]] = string.split()[3] if (len(string.split()) == 6): if (string.split()[5] == "begin"): self.data["Label"] = ClassLabel[string.split()[4]] elif (string.split()[5] == "end"): self.data["Label"] = ClassLabel["NoLabel"] else: print("Error:", "len of line is " + str(len(string.split()))) def writeState(self, file): file.write( self.data["date"] + " " + self.data["time"] + " " + self.data["M001"] + " " + self.data["M002"] + " " + self.data["M003"] + " " + self.data["M004"] + " " + self.data["M005"] + " " + self.data["M006"] + " " + self.data["M007"] + " " + self.data["M008"] + " " + self.data["M009"] + " " + self.data["M010"] + " " + self.data["M011"] + " " + self.data["M012"] + " " + self.data["M013"] + " " + self.data["M014"] + " " + self.data["M015"] + " " + self.data["M016"] + " " + self.data["M017"] + " " + self.data["M018"] + " " + self.data["M019"] + " " + self.data["M020"] + " " + self.data["M021"] + " " + self.data["M022"] + " " + self.data["M023"] + " " + self.data["M024"] + " " + self.data["M025"] + " " + self.data["M026"] + " " + self.data["M027"] + " " + self.data["M028"] + " " + self.data["M029"] + " " + self.data["M030"] + " " + self.data["M031"] + " " + self.data["T001"] + " " + self.data["T002"] + " " + self.data["T003"] + " " + self.data["T004"] + " " + self.data["T005"] + " " + self.data["D001"] + " " + self.data["D002"] + " " + self.data["D003"] + " " + self.data["D004"] + " " + self.data["Label"] + "\n") self.counter += 1 def printState(self): print(self.data["date"], self.data["time"], self.data["M001"], self.data["M002"], self.data["M003"], self.data["M004"], self.data["M005"], self.data["M006"], self.data["M007"], self.data["M008"], self.data["M009"], self.data["M010"], self.data["M011"], self.data["M012"], self.data["M013"], self.data["M014"], self.data["M015"], self.data["M016"], self.data["M017"], self.data["M018"], self.data["M019"], self.data["M020"], self.data["M021"], self.data["M022"], self.data["M023"], self.data["M024"], self.data["M025"], self.data["M026"], self.data["M027"], self.data["M028"], self.data["M029"], self.data["M030"], self.data["M031"], self.data["T001"], self.data["T002"], self.data["T003"], self.data["T004"], self.data["T005"], self.data["D001"], self.data["D002"], self.data["D003"], self.data["D004"], self.data["Label"]) def incrementTime(self): self.datetime = self.datetime + dt.timedelta(0, 1) self.data["date"] = str(self.datetime).split()[0] self.data["time"] = str(self.datetime).split()[1]
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app.py
abdulrasol/loly-ocr
0
137269
<reponame>abdulrasol/loly-ocr<gh_stars>0 from flask import Flask, redirect, request, render_template, send_file, send_from_directory from flask_session import Session from tempfile import mkdtemp import helpers, time, os app = Flask(__name__) # App Configs app.config["TEMPLATES_AUTO_RELOAD"] = True app.config["DEBUG"] = True app.config['UPLOAD_FOLDER'] = helpers.UPLOAD_FOLDER app.config['FILES_DIR'] = helpers.FILES_DIR app.config["SESSION_FILE_DIR"] = mkdtemp() app.config["SESSION_PERMANENT"] = False app.config["SESSION_TYPE"] = "filesystem" # utitize app.secret_key = 'super secret key' # Home def @app.route('/') def home(msg = None): if msg == None: msg = False return render_template('home.html', action='/editing', langs=helpers.langs, msg=msg, title='Loly | Upload file to extract text') # Editing Def @app.route('/editing', methods=["GET", "POST"]) def editing(msg = None): if request.method == 'POST': if request.form.get('lang') == None: return home('Selcet language!') if not(request.files['camera']): file = request.files['file'] else: file = request.files['camera'] get = helpers.ocr(file, language=request.form.get('lang')) if get['CODE'] == 0: return render_template('editing.html', action='/downloading', text = get['MSG'], title='Loly | editing extracted text') else: print(get) return home(get['MSG']) return home('Selcet file first!') # downloading file after editing @app.route('/downloading', methods=["GET", "POST"]) def downloading(): if request.method == 'POST': # save file as user request filename = time.strftime(f"%y%m%d%H%M%S.{request.form.get('get')}") with open(os.path.join(helpers.FILES_DIR,filename),'a') as file: file.write(request.form.get('text')) for file in os.listdir(helpers.FILES_DIR): file = os.path.join(helpers.FILES_DIR, file) if os.stat(file).st_mtime < time.time() - 900: os.remove(file) url = f'{request.url_root}{helpers.FILES_DIR}/{filename}' return render_template('downloading.html', url=url, title=f"Loly | download extracted text as{request.form.get('get')}") return home('Start by uploading file first!') # setup PWA app @app.route('/service-worker.js') def sw(): return app.send_static_file('js/service-worker.js'), 200, {'Content-Type': 'text/javascript'}
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dxtbx/tests/model/test_detector.py
jbeilstenedmands/cctbx_project
0
158090
from __future__ import absolute_import, division, print_function import six.moves.cPickle as pickle from dxtbx.model import Detector, Panel from libtbx.test_utils import approx_equal from scitbx.array_family import flex def tst_get_gain(detector): detector[0].set_gain(2.0) assert abs(detector[0].get_gain() - 2.0) < 1e-7 def tst_get_identifier(detector): detector[0].set_identifier("HELLO") assert detector[0].get_identifier() == "HELLO" detector2 = pickle.loads(pickle.dumps(detector)) assert detector[0].get_identifier() == detector2[0].get_identifier() def tst_get_pixel_lab_coord(detector): from scitbx import matrix eps = 1e-7 # Check lab coordinates at the origin orig = detector[0].get_pixel_lab_coord((0, 0)) dorig = abs(matrix.col(orig) - matrix.col(detector[0].get_origin())) assert(dorig < eps) # Check lab coordinate at the opposite corner corner = detector[0].get_pixel_lab_coord((512, 512)) corner2 = (512 * 0.172, 512 * 0.172, 200) dcorner = abs(matrix.col(corner) - matrix.col(corner)) assert(dcorner < eps) def tst_get_image_size_mm(detector): from scitbx import matrix eps = 1e-7 size = detector[0].get_image_size_mm() size2 = (512 * 0.172, 512 * 0.172) dsize = abs(matrix.col(size) - matrix.col(size2)) assert(dsize < eps) def tst_is_value_in_trusted_range(detector): """Check values are either inside or outside trusted range.""" assert(detector[0].is_value_in_trusted_range(-1) == False) assert(detector[0].is_value_in_trusted_range(0) == True) assert(detector[0].is_value_in_trusted_range(999) == True) assert(detector[0].is_value_in_trusted_range(1000) == False) def tst_is_coord_valid(detector): """Check points are either inside or outside detector range.""" assert(detector[0].is_coord_valid((-1, 256)) == False) assert(detector[0].is_coord_valid((256, 256)) == True) assert(detector[0].is_coord_valid((512, 256)) == False) assert(detector[0].is_coord_valid((256, -1)) == False) assert(detector[0].is_coord_valid((256, 256)) == True) assert(detector[0].is_coord_valid((256, 513)) == False) def tst_pixel_to_millimeter_to_pixel(detector): from scitbx import matrix from random import random eps = 1e-7 # Pick some random pixels and check that px -> mm -> px give px == px w, h = detector[0].get_image_size() random_pixel = lambda: (random() * w, random() * h) pixels = flex.vec2_double(random_pixel() for i in range(100)) xy_mm = detector[0].pixel_to_millimeter(pixels) xy_px = detector[0].millimeter_to_pixel(xy_mm) assert approx_equal(xy_px, pixels, eps=eps) for xy in pixels: xy_mm = detector[0].pixel_to_millimeter(xy) xy_px = detector[0].millimeter_to_pixel(xy_mm) assert(abs(matrix.col(xy_px) - matrix.col(xy)) < eps) def tst_parallax_correction(detector): from random import uniform from scitbx import matrix random_coord = lambda: ( uniform(-1000, 1000), uniform(-1000, 1000)) for i in range(10000): mm = random_coord() px = detector[0].millimeter_to_pixel(mm) mm2 = detector[0].pixel_to_millimeter(px) assert(abs(matrix.col(mm) - matrix.col(mm2)) < 1e-3) def tst_get_names(detector): names = detector.get_names() assert(len(names) == 1) assert(names[0] == 'Panel') def tst_get_thickness(detector): for panel in detector: assert(panel.get_thickness() == 0.1) def tst_get_material(detector): for panel in detector: assert(panel.get_material() == 'Si') def tst_set_mosflm_beam_centre(detector): from scitbx import matrix from dxtbx.model import Beam wavelength = 1 panel = detector[0] detector_normal = matrix.col(panel.get_normal()) origin = matrix.col(panel.get_origin()) fast_axis = matrix.col(panel.get_fast_axis()) slow_axis = matrix.col(panel.get_slow_axis()) image_size = panel.get_image_size_mm() s0 = (1.0/wavelength) * detector_normal beam = Beam(-s0.normalize(), wavelength) beam_centre = matrix.col(panel.get_beam_centre(beam.get_s0())) origin_shift = matrix.col((1, 0.5)) new_beam_centre = beam_centre + origin_shift new_mosflm_beam_centre = tuple(reversed(new_beam_centre)) from dxtbx.model.detector_helpers import set_mosflm_beam_centre set_mosflm_beam_centre(detector, beam, new_mosflm_beam_centre) assert (matrix.col(panel.get_beam_centre(beam.get_s0())) - matrix.col(tuple(reversed(new_mosflm_beam_centre)))).length() < 1e-6 def tst_detectors_are_same(detA, detB): '''Equality operator on detector objects must identify identical detectors''' assert(detA == detB) def tst_detectors_are_different(detA, detB): '''Equality operator on detector objects must find differences in origin''' assert(detA != detB) def tst_resolution(detector): from dxtbx.model import Beam beam = Beam(direction=(0,0,1), wavelength=1.0) d_min1 = detector.get_max_resolution(beam.get_s0()) d_min2 = detector.get_max_inscribed_resolution(beam.get_s0()) assert d_min1 < d_min2 def tst_panel_mask(): from dxtbx.model import Panel panel = Panel() panel.set_image_size((100, 100)) panel.add_mask(40,0,60,100) panel.add_mask(0,40,100,60) panel.set_trusted_range((-1, 10)) data = flex.double(flex.grid(100,100)) data[10,10] = -1 data[20,20] = 10 data[30,30] = 100 data[40,40] = -10 m1 = panel.get_untrusted_rectangle_mask() m2 = panel.get_trusted_range_mask(data) count = 0 for j in range(100): for i in range(40,60): assert(m1[j,i] == False) count += 1 for i in range(100): for j in range(40,60): if i >= 40 and i < 60: continue assert(m1[j,i] == False) count += 1 assert m1.count(False) == count, "%d, %d" % (m1.count(False), count) assert m2.count(False) == 4 assert m2[10,10] == False assert m2[20,20] == False assert m2[30,30] == False assert m2[40,40] == False def test_detector(): from dxtbx.model import ParallaxCorrectedPxMmStrategy def create_detector(offset = 0): # Create the detector detector = Detector(Panel( "", # Type "Panel", # Name (10, 0, 0), # Fast axis (0, 10, 0), # Slow axis (0 + offset, 0 + offset, 200 - offset), # Origin (0.172, 0.172), # Pixel size (512, 512), # Image size (0, 1000), # Trusted range 0.1, # Thickness "Si", # Material identifier="123")) # Identifier return detector detector = create_detector() # Perform some tests tst_get_identifier(detector) tst_get_gain(detector) tst_set_mosflm_beam_centre(detector) tst_get_pixel_lab_coord(detector) tst_get_image_size_mm(detector) tst_is_value_in_trusted_range(detector) tst_is_coord_valid(detector) tst_pixel_to_millimeter_to_pixel(detector) tst_get_names(detector) tst_get_thickness(detector) tst_get_material(detector) tst_resolution(detector) tst_panel_mask() # Attenuation length from cctbx.eltbx import attenuation_coefficient table = attenuation_coefficient.get_table("Si") mu = table.mu_at_angstrom(1) / 10.0 t0 = 0.320 # Create another detector with different origin detector_moved = create_detector(offset=100) tst_detectors_are_different(detector, detector_moved) detector_moved_copy = create_detector(offset=100) tst_detectors_are_same(detector_moved, detector_moved_copy) # Create the detector detector = Detector(Panel( "", # Type "", # Name (10, 0, 0), # Fast axis (0, 10, 0), # Slow axis (0, 0, 200), # Origin (0.172, 0.172), # Pixel size (512, 512), # Image size (0, 1000), # Trusted range 0.0, # Thickness "", # Material ParallaxCorrectedPxMmStrategy(mu, t0))) tst_parallax_correction(detector)
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setup.py
hanase/developer
3
68278
<gh_stars>1-10 # Install setuptools if not installed. try: import setuptools except ImportError: from ez_setup import use_setuptools use_setuptools() from setuptools import setup, find_packages setup( name='developer', version='0.3.0', description='UrbanSim developer model', author='<NAME>.', author_email='<EMAIL>', license='BSD', url='https://github.com/udst/developer', classifiers=[ 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3.5' ], packages=find_packages(exclude=['*.tests']), install_requires=[ 'numpy >= 1.1.0', 'pandas >= 0.16.0', 'orca >= 1.3.0', 'urbansim >= 0.1.1', ], extras_require={ 'pandana': ['pandana>=0.1'] } )
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plotting/plotly.py
TPei/jawbone_visualizer
0
37868
<gh_stars>0 __author__ = 'TPei' from plotting.plotly.graph_objs import * from data.DataHandler import get_all_the_data """ Working with the plotly api to create more interactive diagrams """ def sleep(): data = get_all_the_data() traces = [] categories = ['bed', 'sleep', 'sound', 'light', 'awake', 'averages'] sleep_data = [[], [], [], [], [], []] for date in data: entry = data[date] for i in range(0, len(categories)-1): sleep_data[i].append(entry[categories[i]]) total_sleep = 0 averages = [] for i in range(0, len(sleep_data[1])): total_sleep += sleep_data[1][i] averages.append(total_sleep / float(i+1)) sleep_data[5] = averages for i in range(0, len(sleep_data)): traces.append(Scatter(y=sleep_data[i], name=categories[i])) data = Data(traces) unique_url = py.plot(data, filename='sleep') ''' trace0 = Scatter( #x=[1, 2, 3, 4], y=sleep ) trace1 = Scatter( #x=[1, 2, 3, 4], y=[16, 5, 11, 9] ) data = Data([trace0, trace1]) unique_url = py.plot(data, filename = 'basic-line')''' def coffee_vs_sleep(): data = get_all_the_data() categories = ['0 cups', '1 or 2 cups', '3 or 4 cups', '5+ cups'] count = [0, 0, 0, 0] average_counter = [0, 0, 0, 0] average = [0, 0, 0, 0] import collections od = collections.OrderedDict(sorted(data.items())) print(od) category = 'sleep' for day in od: if 'coffee' in od[day] and category in od[day]: #coffee.append(od[day]['coffee']) if od[day]['coffee'] == 0: count[0] += od[day][category] average_counter[0] += 1 elif od[day]['coffee'] < 3: count[1] += od[day][category] average_counter[1] += 1 elif od[day]['coffee'] < 5: count[2] += od[day][category] average_counter[2] += 1 else: count[3] += od[day][category] average_counter[3] += 1 else: count[0] += od[day][category] average_counter[0] += 1 #calculate average for i in range(0, len(count)): if average_counter[i] == 0: average[i] = 0 else: average[i] = (count[i] / float(average_counter[i])) trace = Bar(y=average, x=categories) data = Data([trace]) unique_url = py.plot(data, filename='coffee_vs_sleep') if __name__ == '__main__': #sleep() coffee_vs_sleep()
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backend/backend/views.py
AurelienGasser/substra-backend
37
134325
<reponame>AurelienGasser/substra-backend import os from rest_framework.authtoken.views import ObtainAuthToken from rest_framework.throttling import AnonRateThrottle from rest_framework.authtoken.models import Token from rest_framework.response import Response from libs.expiry_token_authentication import token_expire_handler, expires_at from libs.user_login_throttle import UserLoginThrottle from rest_framework.views import APIView from substrapp.views.utils import get_channel_name from django.conf import settings class ExpiryObtainAuthToken(ObtainAuthToken): authentication_classes = [] throttle_classes = [AnonRateThrottle, UserLoginThrottle] def post(self, request, *args, **kwargs): serializer = self.serializer_class(data=request.data, context={'request': request}) serializer.is_valid(raise_exception=True) user = serializer.validated_data['user'] if os.environ.get('TOKEN_STRATEGY', 'unique') == 'reuse': token, created = Token.objects.get_or_create(user=user) # token_expire_handler will check, if the token is expired it will generate new one is_expired, token = token_expire_handler(token) else: # token should be new each time, remove the old one Token.objects.filter(user=user).delete() token = Token.objects.create(user=user) return Response({ 'token': token.key, 'expires_at': expires_at(token) }) class Info(APIView): def get(self, request, *args, **kwargs): channel_name = get_channel_name(request) channel = settings.LEDGER_CHANNELS[channel_name] return Response({ 'host': settings.DEFAULT_DOMAIN, 'channel': channel_name, 'config': { 'model_export_enabled': channel['model_export_enabled'], } }) obtain_auth_token = ExpiryObtainAuthToken.as_view() info_view = Info.as_view()
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Qcover/backends/__init__.py
BAQIS-Quantum/Qcover
38
22799
from .backend import Backend from .circuitbyqiskit import CircuitByQiskit from .circuitbyprojectq import CircuitByProjectq from .circuitbycirq import CircuitByCirq from .circuitbyqulacs import CircuitByQulacs # from .circuitbytket import CircuitByTket from .circuitbytensor import CircuitByTensor from .circuitbyqton import CircuitByQton import warnings warnings.filterwarnings("ignore") __all__ = [ 'Backend', 'CircuitByCirq', 'CircuitByQiskit', 'CircuitByProjectq', 'CircuitByTensor', 'CircuitByQulacs', 'CircuitByQton' ]
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fq2sam.py
IRRI-Bioinformatics/variant-calling-pipeline
0
143565
#fq2sam.py: Align fastq read pairs to reference genome. #created by: <NAME> #!/usr/bin/python import sys, getopt, re, os, subprocess def main(argv): #define variables bwa_threads = '' reference = '' read_pair1 = '' output_dir = '' genome_dir = '' #get arguments try: opts, args = getopt.getopt( argv, "hr:p:o:t:", ["ref=","read1=","out=","thread="]) except getopt.GetoptError: print 'fq2sam.py ' + \ '-r <reference> ' + \ '-p <read_pair1> ' + \ '-o <output_dir> ' + \ '-t <bwa_threads>' sys.exit(2) for opt, arg in opts: if opt == '-h': print 'fq2sam.py ' + \ '-r <reference> ' + \ '-p <read_pair1> ' + \ '-o <output_dir> ' + \ '-t <bwa_threads>' sys.exit() elif opt in ("-r", "--ref"): reference = arg elif opt in ("-p", "--read1"): read_pair1 = arg elif opt in ("-o", "--output_dir"): output_dir = arg elif opt in ("-t", "--bwa_threads"): bwa_threads = arg #get read pair names and sam assignment fq_file = ".fq.gz" if fq_file in read_pair1: read_pair2 = read_pair1.replace("1.fq.gz", "2.fq.gz") sam = read_pair1.replace("_1.fq.gz", ".sam") else: read_pair2 = read_pair1.replace("1.fastq.gz", "2.fastq.gz") sam = read_pair1.replace("_1.fastq.gz", ".sam") #extract directories and sam filename split_dir = re.search(r'(.*)/(.*)/(.*sam)', sam, re.M) if split_dir: input_dir = split_dir.group(1) genome_dir = split_dir.group(2) sam = split_dir.group(3) else: print "Nothing found!" #output directory check output_path = output_dir + '/' + genome_dir #output_path = output_dir #if not os.path.exists(output_path): # os.makedirs(output_path) #command for alignment align = 'bwa mem -M -t ' + \ bwa_threads + ' ' + \ reference + ' ' + \ read_pair1 + ' ' + \ read_pair2 + ' ' + \ '>' + ' ' + \ output_path + \ '/' + \ sam #execute command os.system(align) if __name__ == "__main__": main(sys.argv[1:])
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failures/mapper2_try.py
ALaks96/MapReduce_Pyspark_Large_Matrix_Multiplication
0
58512
#!/usr/bin/python import sys import numpy as np # We know the dimensions of A and B! length = int(200) + 1 width = int(200) + 1 # Initializing A_list and B_list to deal with sparsity A = [0]*(length*width) B = [0]*(length*width) for line in sys.stdin: # Retrieving elements of (key,value) pair of our map output lines = line.strip() element = lines.split("\t") # The provenance of the element and its row/column origin = element[0] # The intermediate index to keep the order within the original matrix index = int(element[1]) # The value associated to that element: val = int(element[2]) for i in range(0,201): if origin == "A" + str(i): A[length*i + index] = val print '%s\t%s' % (origin,val) if origin == "B" + str(i): B[width*i + index] = val print '%s\t%s' % (origin,val)
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dracoon/public_models.py
Quirinwierer/dracoon-python-api
3
33768
from dataclasses import dataclass from typing import List @dataclass class SystemInfo: languageDefault: str hideLoginPinputFields: bool s3Hosts: List[str] s3EnforceDirectUpload: bool useS3Storage: bool @dataclass class ActiveDirectoryInfoItem: id: int alias: str isGlobalAvailable: bool @dataclass class ActiveDirectoryInfo: items: List[ActiveDirectoryInfoItem] @dataclass class OpenIdInfoItem: id: int issuer: str alias: str isGlobalAvailable: bool @dataclass class OpenIdInfo: items: List[OpenIdInfoItem]
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4-ManipulandoTexto/des24.py
FelipeTellini/Python
0
159107
<gh_stars>0 print('\nVerificando as primeiras letras de um texto\n') cid = str(input('Que cidade você nasceu ? ')).strip() print(cid[:5].lower() == 'santo') fim = input('\nCurso de Python no YouTube, canal CURSO EM VIDEO.')
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server/webdriver_tests/shared.py
suhana13/website
0
140877
# Copyright 2020 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from selenium.webdriver.support.ui import WebDriverWait from selenium.webdriver.common.by import By from selenium.webdriver.support import expected_conditions as EC LOADING_WAIT_TIME_SEC = 3 MAX_NUM_SPINNERS = 3 """Common library for functions used by multiple webdriver tests""" def wait_for_loading(driver): """ Wait for loading spinners to appear then disappear. Sometimes, more than one spinner will appear and disappear, so wait for MAX_NUM_SPINNERS spinners to appear and disappear. Or finish waiting if it takes more than LOADING_WAIT_TIME_SEC seconds for the next spinner to appear. """ screen_present = EC.visibility_of_element_located((By.ID, 'screen')) screen_hidden = EC.invisibility_of_element_located((By.ID, 'screen')) num_tries = 0 while (num_tries < MAX_NUM_SPINNERS): try: WebDriverWait(driver, LOADING_WAIT_TIME_SEC).until(screen_present) WebDriverWait(driver, LOADING_WAIT_TIME_SEC).until(screen_hidden) num_tries += 1 except: break def click_sv_group(driver, svg_name): """ In the stat var widget, click on the stat var group titled svg_name """ sv_groups = driver.find_elements_by_class_name('node-title') for group in sv_groups: if svg_name in group.text: group.click() break
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golpy/util.py
Zeta611/py-game-of-life
5
83827
<filename>golpy/util.py import time from functools import wraps from typing import Dict class timeit: records: Dict[str, float] = {} on = False def __call__(self, func): @wraps(func) def wrapper(*args, **kwargs): if not self.on: return func(*args, **kwargs) name = func.__name__ start = time.perf_counter() result = func(*args, **kwargs) end = time.perf_counter() elapsed = end - start if name in self.records: self.records[name] += elapsed else: self.records[name] = elapsed return result return wrapper
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PyFlowPackages/PyFlowFreeCAD/Nodes/FreeCAD_Object.py
awgrover/NodeEditor
53
46861
<reponame>awgrover/NodeEditor ''' all still not categorized nodes ''' from PyFlow.Packages.PyFlowFreeCAD.Nodes import * from PyFlow.Packages.PyFlowFreeCAD.Nodes.FreeCAD_Base import timer, FreeCadNodeBase, FreeCadNodeBase2 class FreeCAD_Tube(FreeCadNodeBase2): ''' calculate the points for a parametric tube along a backbone curve ''' dok = 4 def __init__(self, name="MyToy"): super(self.__class__, self).__init__(name) self.inExec = self.createInputPin(DEFAULT_IN_EXEC_NAME, 'ExecPin', None, self.compute) self.outExec = self.createOutputPin(DEFAULT_OUT_EXEC_NAME, 'ExecPin') a=self.createInputPin('backbone', 'ShapePin') a.description="backbone curve for the tube" a=self.createInputPin('parameter', 'Float',structure=StructureType.Array) a.description="u parameter of the position of the ribs" a=self.createInputPin('radius', 'Float',structure=StructureType.Array) a.description="radius/size of the rib rings" a=self.createOutputPin('points', 'VectorPin',structure=StructureType.Array) a.description="array of poles for the postprocessing bspline surface" @staticmethod def description(): return FreeCAD_Tube.__doc__ @staticmethod def category(): return 'Object' def nodelist(): return [ FreeCAD_Tube, ] # hack wird irgendwo geladen warun #+# # muss wieder raus, weil schon in information !!! class FreeCAD_Object(FreeCadNodeBase2): def __init__(self, name="MyToy"): super(self.__class__, self).__init__(name) self.inExec = self.createInputPin(DEFAULT_IN_EXEC_NAME, 'ExecPin', None, self.compute) self.outExec = self.createOutputPin(DEFAULT_OUT_EXEC_NAME, 'ExecPin') pass
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ephemeral/baseline_autocorrelation_parcellated.py
BorgwardtLab/fMRI_Cubical_Persistence
10
156501
#!/usr/bin/env python # # Baseline calculation script for NIfTI data sets. After specifying such # a data set and an optional brain mask, converts each participant to an # autocorrelation-based matrix representation. # # The goal is to summarise each participant as a voxel-by-voxel matrix. # # This script is specifically built for handling parcellated data. Other # data sources are not possible right now, as they would probably exceed # computational resources quickly. import argparse import math import os import warnings import numpy as np import numpy.ma as ma from tqdm import tqdm def basename(filename): """Calculate basename of a file. Removes all extensions from a filename and returns the basename of the file. This function is required to handle filenames with *two* or more extensions. """ filename = os.path.basename(filename) def _split_extension(filename): return os.path.splitext(filename) filename, extension = _split_extension(filename) while extension: filename, extension = _split_extension(filename) return filename if __name__ == '__main__': parser = argparse.ArgumentParser() default_file = \ '../results/parcellated_data/shaefer_masked_subject_data_shifted.npy' parser.add_argument( '-i', '--input', type=str, help='Input file', default=default_file, ) parser.add_argument( '-o', '--output', type=str, help='Output directory. If not set, will default to the current ' 'directory.', default='.' ) args = parser.parse_args() data = np.load(args.input) n_participants = data.shape[0] + 1 # Used to generate nice output files that follow the naming # convention in the remainder of the paper. n_digits = int(math.log10(n_participants) + 1) for index, X in tqdm(enumerate(data), desc='Subject'): filename = f'{index+1:0{n_digits}d}.npz' filename = os.path.join(args.output, filename) # Make sure that we only calculate correlations with valid # voxels. This is only be relevant for the data sets which # actually include a certain brain mask. X = ma.corrcoef(ma.masked_invalid(X.T)) X = np.nan_to_num(X) assert np.isnan(X).sum() == 0 # Nothing should be overwritten. Else, the script might be used # incorrectly, so we refuse to do anything. if os.path.exists(filename): warnings.warn(f'File {filename} already exists. Refusing to ' f'overwrite it and moving on.') continue np.savez(filename, X=X)
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goofycoin.py
Shriyanshagro/goofycoins
0
114853
<reponame>Shriyanshagro/goofycoins #implementation of goofycoins from datetime import datetime import hashlib from random import randint # privatekey of goofy global goofykey global initcoin global inituser initcoin = 100 inituser = 5 # A class to catch error and exceptions class GoofycoinError(Exception): def __init__(self, message): self.message = message def __str__(self): return repr(self.message) class User(object): # mapping # {PrivateKey: PublicKey} def __init__(self): global goofykey self.user = {} self.keymap = {} key = hashlib.sha256() key.update("goofy") num = "privatekey" + str(randint(0,999999999)) key.update(num) goofykey = key.hexdigest() key = hashlib.sha256() key.update(goofykey) key.update("publickey") goofypublickey = key.hexdigest() self.user[goofykey] = {'publickey': goofypublickey, 'holdings':[]} self.keymap[goofypublickey] = goofykey print "privatekey==",goofykey, "\npublickey==", goofypublickey print "Goofy Created!!" def createuser(self): key = hashlib.sha256() key.update(self.user.keys()[-1]) num = "privatekey" + str(randint(0,999999999)) key.update(num) privatekey = key.hexdigest() key = hashlib.sha256() key.update(privatekey) key.update("publickey") publickey = key.hexdigest() holdings = [] self.user[privatekey] = {'publickey': publickey, 'holdings':holdings} self.keymap[publickey] = privatekey return privatekey, publickey, holdings # return list of all public keys def getPublicKeys(self): publickey = [] for value in self.user.values(): publickey.append(value['publickey']) return publickey # return publickey of provided privatekey def getPublicKey(self, privatekey): if not self.user.get(privatekey): raise GoofycoinError("Invalid privatekey") return self.user.get(privatekey)['publickey'] # return coin holdings of provided privatekey def getHolding(self, privatekey): if not self.user.get(privatekey): raise GoofycoinError("Invalid privatekey") return self.user.get(privatekey)['holdings'] def getPrivateKey(self, publickey): if not self.keymap.get(publickey): raise GoofycoinError("Invalid publickey") return self.keymap.get(publickey) class Coin(object): def __init__(self, User): self.coin = {} self.user = User self.ledger = [] # returns new id for coin creation def getnewid(self): return (len(self.coin) + 1) # cid = unique id of coin # pid = private key of creator def createCoin(self, cid, pid): global goofykey # creation is only allowed for goofy if pid==goofykey and cid==self.getnewid(): self.coin[cid] = [] # first transaction of cid ; transaction ledger is a list self.coin[cid].append(self.user.getPublicKey(pid)) transaction = {"creator": self.user.getPublicKey(pid), "Coinid": cid, "Timestamp": datetime.now().isoformat(), } # update ledger self.ledger.append(transaction) # update holding of user self.user.user[pid]['holdings'].append(cid) print "Successfull coin creation with id {}".format(cid) else: raise GoofycoinError("Sorry only Goofy is allowed to create\ new coins with unique id.") # rid = reciever's public key # pid = sender's private key def passcoin(self, cid, rid, pid): # validate coin's existence if cid not in self.coin.keys(): raise GoofycoinError("No such coin exist. Ask Gooofy to create \ one") if rid not in self.user.getPublicKeys(): raise GoofycoinError("Cross-Check reciever's public key") # validate whether user owns that coin? if not self.getOwner(cid) == self.user.getPublicKey(pid): raise GoofycoinError("Sorry, you doesn't owe coin {0}".format(cid)) # append coin's blockchain self.coin[cid].append(rid) # update holding of user self.user.user[pid]['holdings'].remove(cid) self.user.user[self.user.getPrivateKey(rid)]['holdings'].append(cid) transaction = {"sender": self.user.getPublicKey(pid), "reciever": rid, "Coinid": cid, "Timestamp": datetime.now().isoformat(), } # update ledger self.ledger.append(transaction) print "Transaction Successfull" def getOwner(self, cid): if cid not in self.coin.keys(): raise GoofycoinError("No such coin exist. Ask Gooofy to create \ one ") return self.coin[cid][-1] def getledger(self): return self.ledger def checkvalidy(self, cid): if cid not in self.coin.keys(): raise GoofycoinError("No such coin exist. Ask Gooofy to create \ one ") chain = "" for users in self.coin.get(cid): chain = chain + users + "--->>" return chain # dummy transctions def dummy(user, coin): global goofykey global initcoin global inituser initialcoins = initcoin # dummy creation of coins for i in range(0, initialcoins): coin.createCoin(coin.getnewid(), goofykey) i += 1 # number of coins to be divided among users coinequality = initialcoins/(inituser*2) # dummy users and distribution of coins for i in range(0, inituser): privatekey, publickey, holdings = user.createuser() print "privatekey==",privatekey, "\npublickey==", publickey for j in range(0, coinequality): coin.passcoin(initialcoins, publickey, goofykey) initialcoins -= 1 if __name__ == "__main__": user = User() coin = Coin(user) dummy(user, coin) while True: print "u: create user \n p:passcoin \n c:createcoin\n l:transaction \ ledger \n h: get your holding \n v: verify validy of coin" cmd = raw_input("Your command?") try: if cmd == 'u': privatekey, publickey, holdings = user.createuser() print "privatekey==",privatekey, "\npublickey==", publickey elif cmd== 'p': cid = int(raw_input("coin id?")) rid = raw_input("reciever's public key?") pid = raw_input("Your privatekey?") coin.passcoin(cid, rid, pid) elif cmd=='c': pid = raw_input("Your privatekey?") coin.createCoin(coin.getnewid(), pid) elif cmd=='l': print coin.getledger() elif cmd=='h': pid = raw_input("Your privatekey?") print user.getHolding(pid) elif cmd=='v': cid = int(raw_input("coin id?")) print coin.checkvalidy(cid) else: print "Provide valid command" print except GoofycoinError as e: print e.message
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SScriptCompiler/examples/caseTest.py
alklasil/SScript
0
82240
"""Simple if-else / swicth-case test.""" from src.SProgram import SProgram as program from src.conf.SStd import SStd def get_programData(): return { "confs": [ SStd ], "variableNameValuePairs": [ "i" ], "states": [ ("main", [ # synchronous execution [ # store state "case" into tmp # execute tmp (=="case") as a state "$=(const)=", "tmp", "@case", "$executeState", "tmp", # print i "$printInt_ln", "i" ], # The switch-case statement (state) can also be executed asynchronously: # (i.e., execute in the next loop.) # (may be good option if switch-case statement is more complex) # (There are multiple ways of executing the switch-case statement # asynchronously: below is one of them) # Set state=proxy, set proxyState=case, set returnState=main # (nextLoop) state::proxy::executeState(proxyState) # (nextLoop) state::proxy::set state=returnState ]), ("case", [ ["$=", "?", "i"], # case 0: i++ ["$if", "?", "0", [ "$+", "i", "1", "$return" ]], # case 1: i++, i++ ["$if", "?", "1", [ ["$+", "i", "1"]*2, "$return" ]], # default [ "$=", "i", "0", ] ]), ] } def main(argv=[], programData=get_programData()): # program p = program(**programData) # compile and print the program p.compile() if __name__ == "__main__": # execute only if run as a script main()
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detectTrimPoints_woh.py
cilt-uct/TrimPointDetector
0
181145
#!/usr/bin/python ''' Detects the start and end trimpoints of an audio file. ''' import sys import numpy import sklearn.cluster import time import scipy import os import ConfigParser from pyAudioAnalysis import audioFeatureExtraction as aF from pyAudioAnalysis import audioTrainTest as aT from pyAudioAnalysis import audioBasicIO import matplotlib.pyplot as plt from scipy.spatial import distance import matplotlib.pyplot as plt import matplotlib.cm as cm import sklearn.discriminant_analysis from pyAudioAnalysis import audioSegmentation as aS import itertools as it import wave import contextlib import argparse class Segment(object): def __init__(self, start, end, classification): self.start = int(start) self.end = int(end) self.diff = int(end) - int(start) self.classification = str(classification) def get_model_path(wave_file): # model used to predict mic model (boundary or lapel) mic_model = "model/svmDetectMicTypeModel" # lapel speech model lapel_model = "model/svmLapelSpeechModel" # boundary speech model boundary_model = "model/svmNoLapelSpeechModel" # run the classification model on the audio file [Result, P, classNames] = aT.fileClassification(wave_file, mic_model, "svm") Result = int(Result) #return boundary_model # if the winner class is boundary_speech return # the path of the boundary speech model, otherwise # return the path of thelapel speech model if (classNames[Result] == "boundry_speech"): return boundary_model else: return lapel_model def ConfigSectionMap(section): dict1 = {} options = Config.options(section) for option in options: try: dict1[option] = Config.get(section, option) #if dict1[option] == -1: # DebugPrint("skip: %s" % option) except: print("exception on %s!" % option) dict1[option] = None return dict1 def PrintEmptyOutput(_file, _duration, _time): f = open(_file, 'w') f.write('audio_trim_duration={}\n'.format(_duration)) f.write('audio_trim_autotrim=false\n') f.write('audio_trim_ishour=false\n') f.write('audio_trim_lapel=false\n') f.write('audio_trim_model=none\n') f.write('audio_trim_exec_time={};{}\n'.format(0, _time)) f.close() return parser = argparse.ArgumentParser(description='Audio Trim point detector') parser.add_argument('--version', action='version', version='Audio Trim point detector build UCT May 14 2018 14:53') parser.add_argument('--venue', dest='venue', type=str, default='none', help='The venue of this recording used for venue specific models') parser.add_argument('-i', '--input', dest='inputWavFile', type=str, required=True, metavar="wav", help='The wav file to detect trimpoints from') parser.add_argument('-o', '--output', dest='outputTextFile', type=str, required=True, metavar="txt", help='The file to write the properties in') parser.add_argument('--start-speech', dest='theshold_speech_start', type=int, default=3, metavar="(seconds)", help='Threshold for speech at the start of the recording [sec] (default: 3, >=)') parser.add_argument('--end-speech', dest='threshold_speech_end', type=int, default=5, metavar="(seconds)", help='Threshold value for speech at the end of the recording [sec] (default: 5, >=)') parser.add_argument('--non-speech', dest='threshold', type=int, default=90, metavar="(seconds)", help='Threshold value for non-speech segments [sec] (default: 90 >=)') parser.add_argument('--start-adjust', dest='adjust_speech_start', type=int, default=-20, metavar="(seconds)", help='Adjust the first speech segment start time by a number of seconds [sec] (default: -20)') parser.add_argument('--end-adjust', dest='adjust_speech_end', type=int, default=30, metavar="(seconds)", help='Adjust the last speech segments end time by a number of seconds [sec] (default: 30)') parser.add_argument('--start-buffer', dest='buffer_start', type=int, default=3, metavar="(seconds)", help='If the start of the segment list is 0 then use this buffer [sec] (default: 3)') parser.add_argument('--end-buffer', dest='buffer_end', type=int, default=1, metavar="(seconds)", help='If the last segment ends at the end of the wav file adjust by this buffer [sec] (default: 1)') parser.add_argument('--good-start', dest='good_start', type=int, default=300, metavar="(seconds)", help='Does the first segment start within this number of seconds, if true then good start [sec] (default: 300 = 5min)') parser.add_argument('--good-end', dest='good_end', type=int, default=600, metavar="(seconds)", help='Does the last segment end within this number of seconds, if true then good end [sec] (default: 600 = 10min)') parser.add_argument('-d', '--debug', action='store_true', help='print debug messages') args = vars(parser.parse_args()) start_time = time.time() Config = ConfigParser.ConfigParser() Config.read("config.ini") if (args['debug']): print('Start processing...') if not os.path.isfile(args['inputWavFile']): print('Cannot locate audio file {}'.format(args['inputWavFile'])) default_modelName = "model/svmNoLapelSpeechModel" modelName = "model/noModel" # get the duration of the wave file duration = 0 audio_trim_duration = 0 audio_trim_hour = 0 auto_trim = 1 # optimistic - we want to auto_trim with contextlib.closing(wave.open(args['inputWavFile'],'r')) as f: frames = f.getnframes() rate = f.getframerate() duration = int(frames / float(rate)) audio_trim_duration = int(duration*1000) audio_trim_hour = 1 if (int(duration) < 3700) else 0 if (args['debug']): print('\tDuration: {} {}'.format(audio_trim_hour, audio_trim_duration)) my_segments = [] model_time = 0 if (audio_trim_hour == 1): if (args['debug']): print('\tDetecting model...') # ONLY do this for recordings that are less than an 60 min # so if there is a venue that we have mapped then we are going to use that model # else we will use the appropriate mic configuration if args['venue'] in ConfigSectionMap("Venues"): modelName = 'model/' + ConfigSectionMap("Venues")[ args['venue'] ] if not os.path.isfile(modelName): modelName = default_modelName if not os.path.isfile(modelName): print('Cannot locate model file {}'.format(modelName)) else: # detect mic configuration by analyzing input wav file modelName = get_model_path(args['inputWavFile']) if (args['debug']): print ('\tusing: {}'.format(modelName)) model_time = time.time() - start_time modelType = "svm" gtFile = "" returnVal = aS.mtFileClassification(args['inputWavFile'], modelName, modelType, False, gtFile) flagsInd = returnVal[0] classNames = returnVal[1] flags = [classNames[int(f)] for f in flagsInd] (segs, classes) = aS.flags2segs(flags, 1) for s in range(len(segs)): sg = segs[s] diff = int(sg[1]) - int(sg[0]) if (args['debug']): print('{:>6} - {:>6} ({:>6}) : {}').format(sg[0], sg[1], diff, classes[s]) my_segments.append(Segment(int(sg[0]), int(sg[1]), str(classes[s]))) # Speech and non speech lists final_list = [] detected_list = [] segments_non_speech = filter(lambda x: (x.diff >= int(args['threshold'])) and (x.classification == "non-speech"), my_segments) segments_non_speech.sort(key=lambda x: x.end) segments_speech = filter(lambda x: x.classification == "speech", my_segments) segments_speech.sort(key=lambda x: x.end) segments_speech_start = filter(lambda x: (x.start >= int(args['theshold_speech_start'])), segments_speech) segments_speech_start.sort(key=lambda x: x.end) segments_speech_end = filter(lambda x: (x.end <= duration - int(args['threshold_speech_end'])), segments_speech) segments_speech_end.sort(key=lambda x: x.end) segments_speech_useable = filter(lambda x: (x.start >= int(args['theshold_speech_start'])) and (x.end <= duration - int(args['threshold_speech_end'])), segments_speech) segments_speech_useable.sort(key=lambda x: x.end) if len(segments_speech) > 0: if (args['debug']): print('found {} segments, speech {} \n'.format(len(my_segments), len(segments_speech))) # default start/end as detected without threshold check detected_list.append(segments_speech[0].start) detected_list.append(segments_speech[-1].end) for c in segments_non_speech: if (args['debug']): print('{:>6} - {:>6} ({:>6}) : {}').format(c.start, c.end, c.diff, c.classification) final_list.append(c.start) detected_list.append(c.start) tmp_segment = filter(lambda x: x.start == c.end, segments_speech) if (len(tmp_segment) > 1): #print('\t{:>6} - {:>6} ({:>6}) : {}').format(tmp_segment.start, tmp_segment.end, tmp_segment.diff, tmp_segment.classification) print(tmp_segment) final_list.append(c.end) detected_list.append(c.end) if (len(segments_speech_start) > 1): final_list.append(segments_speech_start[0].start + int(args['adjust_speech_start'])) if (args['debug']): print('\n|{:>6}|{:>6}|{:>6} Start'.format(segments_speech_start[0].start, args['adjust_speech_start'], segments_speech_start[0].start + args['adjust_speech_start'])) else: final_list.append(int(args['buffer_start'])) auto_trim = 0 # start is at 0 - bad start if (len(segments_speech_end) > 1): final_list.append(segments_speech_end[-1].end + int(args['adjust_speech_end'])) if (args['debug']): print('|{:>6}|{:>6}|{:>6} End'.format(segments_speech_end[-1].end, args['adjust_speech_end'], segments_speech_end[-1].start + args['adjust_speech_end'])) else: final_list.append(duration) auto_trim = 0 # end is length of recording - bad end # remove duplicates detected_list = set(detected_list) detected_list = list(detected_list) detected_list.sort() final_list = set(final_list) final_list = list(final_list) final_list.sort() if (final_list[0] <= 0): final_list[0] = int(args['buffer_start']) auto_trim = 0 # start is at 0 - bad start if (final_list[-1] > duration): final_list[-1] = duration auto_trim = 0 # end is length of recording - bad end if (args['debug']): print('\n') print(detected_list) print(final_list) stats = { 'len': len(my_segments), 'hour': audio_trim_hour, 'duration': audio_trim_duration, 'speech_no': len(segments_speech), 'speech_ms': sum(c.diff for c in segments_speech), 'nonspeech_no': len(segments_non_speech), 'nonspeech_ms': sum(c.diff for c in segments_non_speech), 'nonspeech_used_no': len(segments_speech_useable), 'nonspeech_used_ms': sum(c.diff for c in segments_speech_useable) } # first segment is always a x no of seconds from the start... if (final_list[0] == 0): final_list[0] = args['buffer_start'] stats['good_start'] = 0 auto_trim = 0 # start is at 0 - bad start else: stats['good_start'] = final_list[0] < args['good_start'] if (final_list[-1] == duration): final_list[-1] = duration - args['buffer_end'] stats['good_end'] = 0 auto_trim = 0 # end is length of recording - bad end else: stats['good_end'] = final_list[-1] + args['good_end'] > int(audio_trim_duration / 1000) final_list = map(lambda x: x * 1000, final_list) result = '' d = '-' for e in final_list: result = result + str(e) + d if (d == '-'): d = ';' else: d = '-' if (args['debug']): print(stats) print('modelName: {}'.format(modelName)) print('audio_trim_autotrim={}'.format("true" if ((stats['hour'] == 1) and (stats['nonspeech_used_no'] == 0) and stats['good_start'] and stats['good_end']) else "false")) print(result) f = open(args['outputTextFile'], 'w') #f.write('audio_trim_file=' + args['inputWavFile'] +'\n') #f.write('audio_trim_out_file=' + args['outputTextFile'] +'\n') f.write('audio_trim_duration={}\n'.format(stats['duration'])) f.write('audio_trim_autotrim={}\n'.format("true" if ((stats['hour'] == 1) and (stats['nonspeech_used_no'] == 0) and stats['good_start'] and stats['good_end']) else "false")) f.write('audio_trim_ishour={}\n'.format("true" if (stats['hour'] == 1) else "false")) f.write('audio_trim_good_start={}\n'.format("true" if (stats['good_start']) else "false")) f.write('audio_trim_good_end={}\n'.format("true" if (stats['good_end']) else "false")) f.write('audio_trim_detected={}\n'.format('-'.join(str(x) for x in detected_list))) f.write('audio_trim_segments={}\n'.format(result)) f.write('audio_trim_segments_len={}\n'.format(stats['len'])) f.write('audio_trim_segments_speech={}\n'.format(stats['speech_no'])) f.write('audio_trim_segments_speech_ms={}\n'.format(int(stats['speech_ms']) * 1000)) f.write('audio_trim_segments_notspeech={}\n'.format(stats['nonspeech_no'])) f.write('audio_trim_segments_notspeech_ms={}\n'.format(int(stats['nonspeech_ms']) * 1000)) f.write('audio_trim_segments_notspeech_used={}\n'.format(stats['nonspeech_used_no'])) f.write('audio_trim_segments_notspeech_used_ms={}\n'.format(int(stats['nonspeech_used_ms']) * 1000)) f.write('audio_trim_threshold={}:{};{}\n'.format(args['theshold_speech_start'], args['threshold_speech_end'], args['threshold'])) f.write('audio_trim_adjust={}:{}\n'.format(args['adjust_speech_start'], args['adjust_speech_end'])) f.write('audio_trim_buffer={}:{}\n'.format(args['buffer_start'], args['buffer_end'])) f.write('audio_trim_good={}:{}\n'.format(args['good_start'], args['good_end'])) f.write('audio_trim_model={}\n'.format(modelName.replace("/","_"))) f.write('audio_trim_lapel={}\n'.format("true" if ("NoLapel" not in modelName) else "false")) f.write('audio_trim_exec_time={};{}\n'.format(round(model_time, 3), round(time.time() - start_time, 3))) f.close() else: PrintEmptyOutput(args['outputTextFile'], audio_trim_duration, round(time.time() - start_time, 3)) else: PrintEmptyOutput(args['outputTextFile'], audio_trim_duration, round(time.time() - start_time, 3)) sys.exit(os.EX_OK) # code 0, all ok
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demo/__main__.py
Dralan1912/HAICOR-demo
0
74926
# Copyright (c) 2020 <NAME> # # This software is released under the MIT License. # https://opensource.org/licenses/MIT from __future__ import annotations import argparse import csv import gzip import json import os import re import sqlite3 as sqlite from .app import database, APP_DIRECTORY from .models.assertions import Assertion, Dataset, License, Relation, Source from .models.concepts import Concept, Language, PartOfSpeech parser = argparse.ArgumentParser() parser.add_argument("conceptnet", action="store", type=str, help="Compiled ConceptNet assertions file (csv.gz)") parser.add_argument("description", action="store", type=str, help="Directory containing the description files (csv)") parser.add_argument("--commit-size", action="store", type=int, default=1000, help="The batch size of the database commit") INITIALIZATION_SQL = os.path.join(APP_DIRECTORY, "initialization.sql") TRANSFORMATION_SQL = os.path.join(APP_DIRECTORY, "transformation.sql") ENGLISH_REGEX = re.compile(r"^/a/\[/r/.+/,/c/en/.+/,/c/en/.+/\]$") CONCEPT_REGEX = re.compile(r"^/c/([^/]+)/([^/]+)/?([^/]+)?/?(.+)?$") if __name__ == "__main__": args = parser.parse_args() LANGUAGE = os.path.join(args.description, "languages.csv") RELATION = os.path.join(args.description, "relations.csv") PART_OF_SPEECH = os.path.join(args.description, "part-of-speeches.csv") # process data using in-memory database with sqlite.connect(":memory:") as temp_database: temp_database.row_factory = sqlite.Row cursor = temp_database.cursor() with open(INITIALIZATION_SQL, "r") as script: cursor.executescript(script.read()) temp_database.commit() with open(LANGUAGE, "r") as file: for language in csv.reader(file): cursor.execute( "INSERT INTO languages(code, name) VALUES(?,?)", language ) with open(RELATION, "r") as file: for relation, directed in csv.reader(file): cursor.execute( "INSERT INTO relations(relation, directed) VALUES(?,?)", (relation, directed == "directed") ) with open(PART_OF_SPEECH, "r") as file: for part_of_speech in csv.reader(file): cursor.execute( "INSERT INTO part_of_speeches(code, name) VALUES(?,?)", part_of_speech ) temp_database.commit() with gzip.open(args.conceptnet, "rt") as conceptnet: reader = csv.reader(conceptnet, delimiter='\t') filtered = filter(lambda x: re.match(ENGLISH_REGEX, x[0]), reader) for id, assertion in enumerate(filtered): print(f"{id + 1} English assertions processed", end='\r') assertion, relation, source, target, data = assertion if relation == "/r/ExternalURL": continue data = json.loads(data) cursor.execute( "INSERT INTO assertions VALUES(" + "?," * 18 + "?)", (id + 1, assertion, relation[3:], source, *re.match(CONCEPT_REGEX, source).groups(), target, *re.match(CONCEPT_REGEX, target).groups(), data["dataset"][3:], data["license"], data["weight"], data["surfaceText"] if "surfaceText" in data else None, data["surfaceStart"] if "surfaceStart" in data else None, data["surfaceEnd"] if "surfaceEnd" in data else None) ) for index, source in enumerate(data["sources"]): for field, value in source.items(): cursor.execute( ("INSERT INTO sources" "(assertion_id, [index], field, value) " "VALUES(?,?,?,?)"), (id + 1, index + 1, field, value) ) print() temp_database.commit() with open(TRANSFORMATION_SQL, "r") as script: cursor.executescript(script.read()) temp_database.commit() # populate app database database.drop_all() database.create_all() for r in cursor.execute("SELECT * FROM languages"): database.session.add(Language(**r)) for r in cursor.execute("SELECT * FROM relations"): database.session.add(Relation(**r)) for r in cursor.execute("SELECT * FROM part_of_speeches"): database.session.add(PartOfSpeech(**r)) for r in cursor.execute("SELECT * FROM datasets"): database.session.add(Dataset(**r)) for r in cursor.execute("SELECT * FROM licenses"): database.session.add(License(**r)) for i, r in enumerate(cursor.execute("SELECT * FROM concepts")): print(f"{i + 1} concepts inserted", end='\r') database.session.add(Concept(**r)) if (i + 1) % args.commit_size == 0: database.session.commit() print() for i, r in enumerate(cursor.execute("SELECT * FROM assertions")): print(f"{i + 1} assertions inserted", end='\r') database.session.add(Assertion(**r)) if (i + 1) % args.commit_size == 0: database.session.commit() print() for i, r in enumerate(cursor.execute("SELECT * FROM sources")): print(f"{i + 1} assertion source inserted", end='\r') database.session.add(Source(**r)) if (i + 1) % args.commit_size == 0: database.session.commit() print() database.session.commit()
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src/unicon/plugins/confd/csp/__init__.py
tahigash/unicon.plugins
1
936
__author__ = "<NAME> <<EMAIL>>" from unicon.plugins.confd import ConfdServiceList, ConfdConnection, ConfdConnectionProvider from .statemachine import CspStateMachine from .settings import CspSettings from . import service_implementation as csp_svc class CspServiceList(ConfdServiceList): def __init__(self): super().__init__() delattr(self, 'cli_style') self.reload = csp_svc.Reload class CspSingleRPConnection(ConfdConnection): os = 'confd' series = 'csp' chassis_type = 'single_rp' state_machine_class = CspStateMachine connection_provider_class = ConfdConnectionProvider subcommand_list = CspServiceList settings = CspSettings()
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nr_oai_pmh_harvester/rules/nusl/field998.py
Narodni-repozitar/oai-pmh-harvester
0
147562
from oarepo_oai_pmh_harvester.decorators import rule from oarepo_oai_pmh_harvester.transformer import OAITransformer from oarepo_taxonomies.utils import get_taxonomy_json @rule("nusl", "marcxml", "/998__/a", phase="pre") def call_provider(el, **kwargs): return provider(el, **kwargs) # pragma: no cover def provider(el, **kwargs): slug = provider_mapping().get(el) if not slug: # pragma: no cover return OAITransformer.PROCESSED return { "_administration": { "state": "new", "primaryCommunity": slug, "communities": [] }, "provider": get_taxonomy_json(code="institutions", slug=slug).paginated_data } def provider_mapping(): return { "agritec": "agritec", "agrotest_fyto": "agrotest_fyto", "akademie_muzickych_umeni_v_praze": "amu", "akademie_vytvarnych_umeni": "avu", "archeologicky_ustav_brno": "arub_cas", "archeologicky_ustav_praha": "arup_cas", "archip": "archip", "archiv_ing_arch_jana_moucky": "j_moucka", "archiv_doc_jiri_soucek": "j_soucek", "arnika": "arnika", "astronomicky_ustav": "asu_cas", "biofyzikalni_ustav": "bfu_cas", "biologicke_centrum": "bc_cas", "biotechnologicky_ustav": "ibt_cas", "botanicky_ustav": "ibot_cas", "cenia": "cenia", "centrum_dopravniho_vyzkumu": "cdv", "centrum_pro_dopravu_a_energetiku": "cde", "centrum_pro_regionalni_rozvoj": "crr", "centrum_pro_studium_vysokeho_skolstvi": "csvs", "centrum_pro_vyzkum_verejneho_mineni": "cvvm", "centrum_vyzkumu_globalni_zmeny": "cvgz_cas", "ceska_asociace_ergoterapeutu": "cae", "ceska_asociace_paraplegiku": "czepa", "ceska_narodni_banka": "cnb", "ceska_spolecnost_ornitologicka": "birdlife", "ceska_zemedelska_univerzita": "czu", "cesky_statisticky_urad": "csu", "chmelarsky_institut": "chizatec", "clovek_v_tisni": "clovek_v_tisni", "crdm": "crdm", "cvut": "cvut", "ekodomov": "ekodomov", "entomologicky_ustav": "entu_cas", "etnologicky_ustav": "eu_cas", "evropske_hodnoty": "evropske_hodnoty", "fairtrade_cz_sk": "fairtrade_cz_sk", "filosoficky_ustav": "flu_cas", "fyzikalni_ustav": "fzu_cas", "fyziologicky_ustav": "fgu_cas", "galerie_vytvarneho_umeni_v_ostrave": "gvuo", "gender_studies": "gender_studies", "geofyzikalni_ustav": "ig_cas", "geologicky_ustav": "gli_cas", "gle": "gle", "hestia": "hestia", "historicky_ustav": "hiu_cas", "hydrobiologicky_ustav": "hbu_cas", "institut_umeni": "idu", "iuridicum_remedium": "iure", "jihoceska_univerzita_v_ceskych_budejovicich": "jcu", "jihomoravske_muzeum_ve_znojme": "jmm_znojmo", "knihovna_av_cr": "knav", "masarykova_univerzita": "muni", "masarykuv_ustav_a_archiv": "mua_cas", "matematicky_ustav": "math_cas", "mendelova_univerzita_v_brne": "mendelu", "mikrobiologicky_ustav": "mbu_cas", "ministerstvo_obrany": "mo_cr", "ministerstvo_spravedlnosti": "ms_cr", "ministerstvo_zivotniho_prostredi": "mzp_cr", "moravska_galerie": "moravska_gal", "moravska_zemska_knihovna": "mzk", "muzeum_brnenska": "muz_brnenska", "muzeum_vychodnich_cech": "muzeumhk", "nacr": "nacr", "nadace_promeny": "nadace_promeny", "narodni_informacni_a_poradenske_stredisko_pro_kulturu": "nipos", "narodni_knihovna": "nk_cr", "narodni_lekarska_knihovna": "nlk", "narodni_muzeum": "nm", "narodni_muzeum_v_prirode": "nmvp", "narodni_pamatkovy_ustav": "npu", "narodni_technicka_knihovna": "ntk", "narodni_technicke_muzeum": "ntm", "narodni_zemedelske_muzeum": "nzm", "narodohospodarsky_ustav": "nhu_cas", "nulk": "nulk", "nuv": "nuv", "orientalni_ustav": "orient_cas", "oseva": "oseva", "ostravska_univerzita": "osu", "pamatnik_narodniho_pisemnictvi": "pamatnik_np", "parazitologicky_ustav": "paru_cas", "parlamentni_institut": "pi_psp", "prague_college": "prague_college", "psychologicky_ustav": "psu_cas", "sdruzeni_pro_integraci_a_migraci": "simi", "severoceske_muzeum_v_liberci": "muzeumlb", "siriri": "siriri", "slezske_zemske_muzeum": "szm", "slovansky_ustav": "slu_cas", "sociologicky_ustav": "soc_cas", "surao": "surao", "szpi": "szpi", "technologicke_centrum": "tc_cas", "ujep": "ujep", "umeleckoprumyslove_museum": "umprum_museum", "univerzita_karlova_v_praze": "uk", "upce": "upce", "urad_prumysloveho_vlastnictvi": "upv", "ustav_analyticke_chemie": "uiach_cas", "ustav_anorganicke_chemie": "uach_cas", "ustav_archeologicke_pamatkove_pece_severozapadnich_cech": "uappmost", "ustav_biologie_obratlovcu": "ivb_cas", "ustav_chemickych_procesu": "icpf_cas", "ustav_dejin_umeni": "udu_cas", "ustav_experimentalni_botaniky": "ueb_cas", "ustav_experimentalni_mediciny": "iem_cas", "ustav_fotoniky_a_elektroniky": "ufe_cas", "ustav_fyzikalni_chemie_j_heyrovskeho": "jh_inst_cas", "ustav_fyziky_atmosfery": "ufa_cas", "ustav_fyziky_materialu": "ipm_cas", "ustav_fyziky_plazmatu": "ipp_cas", "ustav_geoniky": "ugn_cas", "ustav_informatiky": "ics_cas", "ustav_jaderne_fyziky": "ujf_cas", "ustav_makromolekularni_chemie": "imc_cas", "ustav_molekularni_biologie_rostlin": "umbr_cas", "ustav_molekularni_genetiky": "img_cas", "ustav_organicke_chemie_a_biochemie": "uochb_cas", "ustav_pristrojove_techniky": "upt_cas", "ustav_pro_ceskou_literaturu": "ucl_cas", "ustav_pro_elektrotechniku": "ue_cas", "ustav_pro_hydrodynamiku": "ih_cas", "ustav_pro_jazyk_cesky": "ujc_cas", "ustav_pro_soudobe_dejiny": "usd_cas", "ustav_pro_studium_totalitnich_rezimu": "ustrcz", "ustav_pudni_biologie": "upb_cas", "ustav_statu_a_prava": "ilaw_cas", "ustav_struktury_a_mechaniky_hornin": "irsm_cas", "ustav_teoreticke_a_aplikovane_mechaniky": "itam_cas", "ustav_teorie_informace_a_automatizace": "utia_cas", "ustav_termomechaniky": "it_cas", "ustav_zivocisne_fyziologie_a_genetiky": "iapg_cas", "vscht": "vscht", "vugtk": "vugtk", "vutbr": "vutbr", "vuv_tgm": "vuv_tgm", "vvud": "vvud", "vysoka_skola_ekonomicka_v_praze": "vse", "vysoka_skola_evropskych_a_regionalnich_studii": "vsers", "vysoka_skola_financni_a_spravni": "vsfs", "vysoka_skola_manazerske_informatiky_a_ekonomiky": "vsmie", "vyzkumny_ustav_bezpecnosti_prace": "vubp", "vyzkumny_ustav_lesniho_hospodarstvi_a_myslivosti": "vulhm", "vyzkumny_ustav_potravinarsky": "vupp", "vyzkumny_ustav_prace_a_socialnich_veci": "vupsv", "vyzkumny_ustav_rostlinne_vyroby": "vurv", "vyzkumny_ustav_silva_taroucy": "vukoz", "woodexpert": "woodexpert", "zapadoceska_univerzita": "zcu", "zapadoceske_muzeum_v_plzni": "zcm" }
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server.py
drunkHatch/CMPUT404-assignment-webserver
0
12656
# coding: utf-8 import socketserver import re import socket import datetime import os import mimetypes as MT import sys # Copyright 2013 <NAME>, <NAME> # # 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. # # # Furthermore it is derived from the Python documentation examples thus # some of the code is Copyright © 2001-2013 Python Software # Foundation; All Rights Reserved # # http://docs.python.org/2/library/socketserver.html # # run: python freetests.py # try: curl -v -X GET http://127.0.0.1:8080/ # status codes could be handled STATUS_CODE_RESPONSE = { 0: " 0 Surprise!", 200: " 200 OK", 301: " 301 Moved Permanently", 404: " 404 Not Found", 405: " 405 Method Not Allowed" } # methods could be handled HTTP_REQUEST_METHODS = { "GET": 1, } # some hard coded text END_OF_LINE_RESPONSE = "\r\n" PROTOCOL_RESPONSE = "HTTP/1.1" DIRECTORY_TO_SERVE = "www" # open file error here GOODFILE = 1 ISADIRECTORY = 2 NOFILE = 3 # response generate class class MyServerResponse: def __init__(self, status=0, expire_time="-1", content_type="default", \ accept_ranges="none"): self.response_header = { "status_response": PROTOCOL_RESPONSE + STATUS_CODE_RESPONSE[status], "date_response": "Date: " + datetime.datetime.now().\ strftime('%A, %d %b %Y %X %Z'), "expires": "Expires: " + expire_time, "content_type": "Content-Type: " + content_type, "accept_ranges": "Accept-Ranges: " + accept_ranges, "redirect_address": "Location: http://", "allow_header": "ALlow: GET" } # send header via various status_code def send_header(self, conn, status_code): tmp = self.response_header["status_response"] + END_OF_LINE_RESPONSE conn.sendall(tmp.encode("utf-8")) if status_code == 200: tmp = self.response_header["expires"] + END_OF_LINE_RESPONSE conn.sendall(tmp.encode("utf-8")) tmp = self.response_header["content_type"] + END_OF_LINE_RESPONSE conn.sendall(tmp.encode("utf-8")) elif status_code == 301: tmp = self.response_header["redirect_address"] + \ END_OF_LINE_RESPONSE conn.sendall(tmp.encode("utf-8")) elif status_code == 405: tmp = self.response_header["allow_header"] + END_OF_LINE_RESPONSE conn.sendall(tmp.encode("utf-8")) def set_status_response(self, status_code): self.response_header["status_response"] = \ PROTOCOL_RESPONSE + STATUS_CODE_RESPONSE[status_code] # request for storing received request attributes class MyServerRequest: def __init__(self): self.method = None self.url = None def method_is_valid(self): if self.method in HTTP_REQUEST_METHODS: return True else: return False # add more implementation here def url_is_valid(self): return True class MyWebServer(socketserver.BaseRequestHandler): def handle(self): rest_protocol_flag = False standard_rest_cmd = "GET / HTTP/1.1" # init the socket self.request.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) full_data = b"" with self.request as conn: # declaration here new_request = MyServerRequest() status_code = 0 open_file = True file = None content_type = "void of magic" file_name = "none" type_of_file = "default" open_result = -100 new_response = MyServerResponse() # recv all data while True: data = conn.recv(1024) if not data: break full_data += data if b"\r\n" in data: break if b"utf" in full_data: print(full_data) pass str_full_data = full_data.decode("utf-8") splited_commands = re.split('[\r|\n]+', str_full_data) whole_request = splited_commands[0].split(' ') # if we can find request from recved data if len(whole_request) > 0: new_request.method = whole_request[0] # try to pick methods new_request.url = whole_request[1] # try to pick url # if method we get could not be handled if not new_request.method_is_valid(): status_code = 405 open_file = False content_type = "none" new_response.set_status_response(status_code) # if no errors occured and then try to open requested url if open_file: open_result, file, file_name = openRequestedFile(new_request.url) # try opening requested file, and return corresponding status_code status_code = checkErrorsOfOpenedFile\ (status_code, open_result, file, file_name) # SECURITY: check permission of opened file status_code = checkPermissionOfRequestedFile\ (status_code, open_result, file, file_name) new_response.set_status_response(status_code) if status_code == 200 and file_name != None: type_of_file = MT.guess_type(file_name, False)[0] elif status_code == 301: new_response.response_header["redirect_address"] += \ self.server.server_address[0] + ":" + \ str(self.server.server_address[1]) + \ new_request.url + "/" new_response.set_status_response(status_code) if open_result == GOODFILE and type_of_file != None: new_response.response_header["content_type"] = "Content-Type: " new_response.response_header["content_type"] += type_of_file new_response.send_header(conn, status_code) self.request.sendall(b"\r\n") # then open file/directory and send it if file: self.request.sendfile(file) #self.request.sendall(b"\r\n") conn.close() # argument: requested url # return value: open file result, opened file object, local path def openRequestedFile(client_request_url): cru = client_request_url if cru[-1] == r'/': cru += "index.html" complete_path = DIRECTORY_TO_SERVE + cru try: result = open(complete_path, 'rb') content_type = cru.split(".") return GOODFILE, result, cru except IsADirectoryError as e: return ISADIRECTORY, None, None except FileNotFoundError as n: return NOFILE, None, None # check type and error of opened file def checkErrorsOfOpenedFile(status_code,open_result, file, file_name): if open_result == GOODFILE: status_code = 200 type_of_file = MT.guess_type(file_name, False)[0] elif open_result == ISADIRECTORY: status_code = 301 elif open_result == NOFILE: status_code = 404 return status_code # SECURITY: check the permission of opened file def checkPermissionOfRequestedFile(status_code,open_result, file, file_name): if file_name == None: return status_code abs_path_of_serving_dir = os.getcwd() abs_path_of_serving_dir += "/www/" length_of_serving_dir = len(abs_path_of_serving_dir) abs_path_of_request = os.path.abspath(file.name) length_of_requested_object = len(abs_path_of_request) if length_of_serving_dir > length_of_requested_object: status_code = 404 elif abs_path_of_serving_dir != abs_path_of_request[:length_of_serving_dir]: status_code = 404 return status_code if __name__ == "__main__": HOST, PORT = "localhost", 8080 socketserver.TCPServer.allow_reuse_address = True # Create the server, binding to localhost on port 8080 server = socketserver.TCPServer((HOST, PORT), MyWebServer) # https://stackoverflow.com/questions/15260558/python-tcpserver-address-already-in-use-but-i-close-the-server-and-i-use-allow # Activate the server; this will keep running until you # interrupt the program with Ctrl-C try: server.serve_forever() except KeyboardInterrupt: # exit if ctrl+C sys.exit(0)
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pred_shots/main.py
RasmusRynell/Predicting-NHL
1
127030
<filename>pred_shots/main.py from handler import * import json import os os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' def print_help(): print("Current commands: ") print("1. help: Shows this") print("2. exit: Exits the process, nothing is saved") print("3. eval: ") print("4. und: Refreshes/Updates the local NHL database") print("5. and: Add nicknames to the database") print("6. ubd: Add \"old\" bets (from bookies that's located on a local file) to database") print("7. gen: Generate a CSV file containing all information for a player going back to 2017/09/15") print("8. pre: Perform preprocessing") if __name__ == "__main__": while True: arg_in = input(">>> ") # Initial commands if arg_in.lower() == 'help' or arg_in == '1' or arg_in == 'h': print_help() elif arg_in.lower() == 'exit' or arg_in == '2' or arg_in == 'e': print("Exiting...") break #elif arg_in.lower() == 'eval': # eval_bets() # Dev elif arg_in.lower() == 'und': update_nhl_db() print("Nhl database updated") elif arg_in.lower() == 'and': add_nicknames_nhl_db() print("Nicknames added") elif arg_in.lower() == 'ubd': print("What file do you want to add? (\"b\" for back) (EX: 2017-03-21.bet365) (Empty for all in folder)") f = input(">>> > ") if f == 'b': print("Back...") elif f == "": update_bets_db() print("Bets database updated") else: update_bets_db(f) print("Bets database updated") elif arg_in.lower() == 'gen': player_ids = [8471214]#, 8475167, 8478463, 8475744, 8477504, 8477492, 8480839, 8477499, 8476881] for player_id in player_ids: data = generate_csv(player_id) save_csv(data, str(player_id) + ".csv") elif arg_in.lower() == 'pred': bets = get_bets() # Remove all but last 5 bets in dict keys = list(bets.keys()) new_bets = {} for i in range(10, 15): new_bets[keys[i]] = bets[keys[i]] predictions = predict_games(new_bets) print("Predictions saved to file") print("Predictions: ") #print(json.dumps(predictions, indent=4)) # Save predictions dict to a file with open('./external/predictions/test.json', 'w') as f: json.dump(predictions, f) elif arg_in.lower() == 'eval': bets = {} # Read in bets from file with open('./external/predictions/test.json', 'r') as f: bets = json.load(f) evaluate_bets(bets) else: print(f"\"{arg_in}\" is no command")
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backend/project/posts/utils/PostAlbumUtil.py
winoutt/winoutt-django
0
151110
from project.posts.models import PostAlbum def create(post, photos): for photo in photos: PostAlbum.objects.create(post=post, photo=photo, photo_original=photo) def get_post_album(post): return PostAlbum.objects.filter(post=post)
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tests/test_disk_cache/test_disk_general.py
SHIELD616416/hello-world
0
172702
#!/usr/bin/python # -*- coding: utf-8 -*- # DATE: 2022/1/19 # Author: <EMAIL> import os import sqlite3.dbapi2 as sqlite3 import threading import time from typing import NoReturn import pytest from cache3 import SimpleDiskCache from cache3.disk import SessionDescriptor # api >>> SessionDescriptor.__set__ def test__set__() -> NoReturn: cache = SimpleDiskCache() assert isinstance(cache.session, sqlite3.Connection) with pytest.raises(ValueError, match='Expected .* to be an sqlite3.Connection.'): cache.session = 1 cache.session = sqlite3.connect('test.sqlite') os.remove('test.sqlite') # api >>> SessionDescriptor.__delete__, _close def test__close__(): cache = SimpleDiskCache() origin: sqlite3.Connection = cache.session assert isinstance(cache.session, sqlite3.Connection) del cache.session assert origin != cache.session # api >>> def test_init(): file = 'test1.sqlite' def h(file): cache = SimpleDiskCache(name=file, configure={'timeout': 0.01}) with cache._transact() as sqlite: sqlite( 'CREATE TABLE test(id integer)' ) time.sleep(1) sqlite( 'DROP TABLE test' ) def f(file): cache = SimpleDiskCache(name=file, configure={'timeout': 0.01}) cache.set('name', 'monkey') threading.Thread(target=h, args=(file, )).start() threading.Thread(target=f, args=(file, )).start() if __name__ == '__main__': pytest.main(["-s", __file__])
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check_constraints/models.py
theju/django-check-constraints
4
107384
# Dummy models.py file to allow for tests to run from django.db import models class CCTestModel(models.Model): name = models.CharField(max_length=10) age = models.IntegerField() gender = models.CharField(max_length=10) price = models.PositiveIntegerField() discount = models.PositiveIntegerField() mfg_date = models.DateField() class Meta: constraints = ()
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tests/test_channel.py
rwilhelm/aiormq
176
3426
import asyncio import uuid import pytest from aiomisc_pytest.pytest_plugin import TCPProxy import aiormq async def test_simple(amqp_channel: aiormq.Channel): await amqp_channel.basic_qos(prefetch_count=1) assert amqp_channel.number queue = asyncio.Queue() deaclare_ok = await amqp_channel.queue_declare(auto_delete=True) consume_ok = await amqp_channel.basic_consume(deaclare_ok.queue, queue.put) await amqp_channel.basic_publish( b"foo", routing_key=deaclare_ok.queue, properties=aiormq.spec.Basic.Properties(message_id="123"), ) message = await queue.get() # type: DeliveredMessage assert message.body == b"foo" cancel_ok = await amqp_channel.basic_cancel(consume_ok.consumer_tag) assert cancel_ok.consumer_tag == consume_ok.consumer_tag assert cancel_ok.consumer_tag not in amqp_channel.consumers await amqp_channel.queue_delete(deaclare_ok.queue) deaclare_ok = await amqp_channel.queue_declare(auto_delete=True) await amqp_channel.basic_publish(b"foo bar", routing_key=deaclare_ok.queue) message = await amqp_channel.basic_get(deaclare_ok.queue, no_ack=True) assert message.body == b"foo bar" async def test_blank_body(amqp_channel: aiormq.Channel): await amqp_channel.basic_qos(prefetch_count=1) assert amqp_channel.number queue = asyncio.Queue() deaclare_ok = await amqp_channel.queue_declare(auto_delete=True) consume_ok = await amqp_channel.basic_consume(deaclare_ok.queue, queue.put) await amqp_channel.basic_publish( b"", routing_key=deaclare_ok.queue, properties=aiormq.spec.Basic.Properties(message_id="123"), ) message = await queue.get() # type: DeliveredMessage assert message.body == b"" cancel_ok = await amqp_channel.basic_cancel(consume_ok.consumer_tag) assert cancel_ok.consumer_tag == consume_ok.consumer_tag assert cancel_ok.consumer_tag not in amqp_channel.consumers await amqp_channel.queue_delete(deaclare_ok.queue) deaclare_ok = await amqp_channel.queue_declare(auto_delete=True) await amqp_channel.basic_publish(b"foo bar", routing_key=deaclare_ok.queue) message = await amqp_channel.basic_get(deaclare_ok.queue, no_ack=True) assert message.body == b"foo bar" @pytest.mark.no_catch_loop_exceptions async def test_bad_consumer(amqp_channel: aiormq.Channel, loop): channel = amqp_channel # type: aiormq.Channel await channel.basic_qos(prefetch_count=1) declare_ok = await channel.queue_declare() future = loop.create_future() await channel.basic_publish(b"urgent", routing_key=declare_ok.queue) consumer_tag = loop.create_future() async def bad_consumer(message): await channel.basic_cancel(await consumer_tag) future.set_result(message) raise Exception consume_ok = await channel.basic_consume( declare_ok.queue, bad_consumer, no_ack=False, ) consumer_tag.set_result(consume_ok.consumer_tag) message = await future await channel.basic_reject(message.delivery.delivery_tag, requeue=True) assert message.body == b"urgent" future = loop.create_future() await channel.basic_consume( declare_ok.queue, future.set_result, no_ack=True, ) message = await future assert message.body == b"urgent" async def test_ack_nack_reject(amqp_channel: aiormq.Channel): channel = amqp_channel # type: aiormq.Channel await channel.basic_qos(prefetch_count=1) declare_ok = await channel.queue_declare(auto_delete=True) queue = asyncio.Queue() await channel.basic_consume(declare_ok.queue, queue.put, no_ack=False) await channel.basic_publish(b"rejected", routing_key=declare_ok.queue) message = await queue.get() assert message.body == b"rejected" await channel.basic_reject(message.delivery.delivery_tag, requeue=False) await channel.basic_publish(b"nacked", routing_key=declare_ok.queue) message = await queue.get() assert message.body == b"nacked" await channel.basic_nack(message.delivery.delivery_tag, requeue=False) await channel.basic_publish(b"acked", routing_key=declare_ok.queue) message = await queue.get() assert message.body == b"acked" await channel.basic_ack(message.delivery.delivery_tag) async def test_confirm_multiple(amqp_channel: aiormq.Channel): """ RabbitMQ has been observed to send confirmations in a strange pattern when publishing simultaneously where only some messages are delivered to a queue. It sends acks like this 1 2 4 5(multiple, confirming also 3). This test is probably inconsequential without publisher_confirms This is a regression for https://github.com/mosquito/aiormq/issues/10 """ channel = amqp_channel # type: aiormq.Channel exchange = uuid.uuid4().hex await channel.exchange_declare(exchange, exchange_type="topic") try: declare_ok = await channel.queue_declare(exclusive=True) await channel.queue_bind( declare_ok.queue, exchange, routing_key="test.5", ) for i in range(10): messages = [ asyncio.ensure_future(channel.basic_publish( b"test", exchange=exchange, routing_key="test.{}".format(i), )) for i in range(10) ] _, pending = await asyncio.wait(messages, timeout=0.2) assert not pending, "not all publishes were completed (confirmed)" await asyncio.sleep(0.05) finally: await channel.exchange_delete(exchange) async def test_exclusive_queue_locked(amqp_connection): channel0 = await amqp_connection.channel() channel1 = await amqp_connection.channel() qname = str(uuid.uuid4()) await channel0.queue_declare(qname, exclusive=True) try: await channel0.basic_consume(qname, print, exclusive=True) with pytest.raises(aiormq.exceptions.ChannelLockedResource): await channel1.queue_declare(qname) await channel1.basic_consume(qname, print, exclusive=True) finally: await channel0.queue_delete(qname) async def test_remove_writer_when_closed(amqp_channel: aiormq.Channel): with pytest.raises(aiormq.exceptions.ChannelClosed): await amqp_channel.queue_declare( "amq.forbidden_queue_name", auto_delete=True, ) with pytest.raises(aiormq.exceptions.ChannelInvalidStateError): await amqp_channel.queue_delete("amq.forbidden_queue_name") async def test_proxy_connection(proxy_connection, proxy: TCPProxy): channel = await proxy_connection.channel() # type: aiormq.Channel await channel.queue_declare(auto_delete=True) async def test_declare_queue_timeout(proxy_connection, proxy: TCPProxy): for _ in range(3): channel = await proxy_connection.channel() # type: aiormq.Channel qname = str(uuid.uuid4()) with proxy.slowdown(read_delay=5, write_delay=0): with pytest.raises(asyncio.TimeoutError): await channel.queue_declare( qname, auto_delete=True, timeout=0.5 )
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sumo/tools/contributed/sumopy/agilepy/lib_wx/test_app.py
iltempe/osmosi
0
1614205
<filename>sumo/tools/contributed/sumopy/agilepy/lib_wx/test_app.py import os import sys import wx from wx.lib.wordwrap import wordwrap if __name__ == '__main__': try: APPDIR = os.path.dirname(os.path.abspath(__file__)) except: APPDIR = os.path.dirname(os.path.abspath(sys.argv[0])) AGILEDIR = os.path.join(APPDIR, '..') print 'APPDIR,AGILEDIR', APPDIR, AGILEDIR sys.path.append(AGILEDIR) libpaths = [AGILEDIR, os.path.join( AGILEDIR, "lib_base"), os.path.join(AGILEDIR, "lib_wx"), ] for libpath in libpaths: print ' libpath=', libpath lp = os.path.abspath(libpath) if not lp in sys.path: # print ' append',lp sys.path.append(lp) from mainframe import * # import corepackages #from test_glcanvas import * from ogleditor import * ## ##import wx ## # try: ## dirName = os.path.dirname(os.path.abspath(__file__)) # except: ## dirName = os.path.dirname(os.path.abspath(sys.argv[0])) ## # sys.path.append(os.path.split(dirName)[0]) IMAGEDIR = os.path.join(os.path.dirname(__file__), "images") ICONPATH = os.path.join(IMAGEDIR, 'icon_color_small.png') # None class MyApp(wx.App): def __init__(self, redirect=False, filename=None): wx.App.__init__(self, redirect, filename) #self.frame = wx.Frame(None, wx.ID_ANY, title='My Title') self.mainframe = AgileMainframe( title='MyApp', size_toolbaricons=(32, 32)) if ICONPATH != None: icon = wx.Icon(ICONPATH, wx.BITMAP_TYPE_PNG, 16, 16) self.mainframe.SetIcon(icon) self.gleditor = self.mainframe.add_view("OGleditor", OGleditor) self.mainframe.Show() self.on_test() self.make_menu() self.make_toolbar() #canvas = gleditor.get_canvas() # canvas.add_element(lines) # canvas.add_element(triangles) # canvas.add_element(rectangles) def make_toolbar(self): tsize = self.mainframe.get_size_toolbaricons() new_bmp = wx.ArtProvider.GetBitmap(wx.ART_NEW, wx.ART_TOOLBAR, tsize) open_bmp = wx.ArtProvider.GetBitmap( wx.ART_FILE_OPEN, wx.ART_TOOLBAR, tsize) save_bmp = wx.ArtProvider.GetBitmap( wx.ART_FILE_SAVE, wx.ART_TOOLBAR, tsize) #cut_bmp = wx.ArtProvider.GetBitmap(wx.ART_CUT, wx.ART_TOOLBAR, tsize) #copy_bmp = wx.ArtProvider.GetBitmap(wx.ART_COPY, wx.ART_TOOLBAR, tsize) #paste_bmp= wx.ArtProvider.GetBitmap(wx.ART_PASTE, wx.ART_TOOLBAR, tsize) self.mainframe.add_tool('new', self.on_open, new_bmp, 'create new doc') self.mainframe.add_tool('open', self.on_open, open_bmp, 'Open doc') self.mainframe.add_tool('save', self.on_save, save_bmp, 'Save doc') # self.toolbar.AddSeparator() # self.add_tool('cut',self.on_open,cut_bmp,'Cut') # self.add_tool('copy',self.on_open,copy_bmp,'Copy') # self.add_tool('paste',self.on_open,paste_bmp,'Paste') def make_menu(self): self.mainframe.menubar.append_menu('file') self.mainframe.menubar.append_menu('file/doc') self.mainframe.menubar.append_item('file/doc/open', self.on_open, shortkey='Ctrl+o', info='open it out') self.mainframe.menubar.append_item('file/doc/save', self.on_save, shortkey='Ctrl+s', info='save it out') def on_save(self, event): print 'save it!!' def on_open(self, event): """Open a document""" #wildcards = CreateWildCards() + "All files (*.*)|*.*" print 'open it!!' def on_test(self, event=None): print '\non_test' vertices = np.array([ [[0.0, 0.0, 0.0], [0.2, 0.0, 0.0]], # 0 green [[0.0, 0.0, 0.0], [0.0, 0.9, 0.0]], # 1 red ]) colors = np.array([ [0.0, 0.9, 0.0, 0.9], # 0 [0.9, 0.0, 0.0, 0.9], # 1 ]) colors2 = np.array([ [0.5, 0.9, 0.5, 0.5], # 0 [0.9, 0.5, 0.9, 0.5], # 1 ]) colors2o = np.array([ [0.8, 0.9, 0.8, 0.9], # 0 [0.9, 0.8, 0.9, 0.9], # 1 ]) drawing = OGLdrawing() #------------------------------------------------------------------------- if 0: lines = Lines('lines', drawing) lines.add_drawobjs(vertices, colors) drawing.add_drawobj(lines) #------------------------------------------------------------------------- if 0: fancylines = Fancylines('fancylines', drawing) vertices_fancy = np.array([ [[0.0, -1.0, 0.0], [2, -1.0, 0.0]], # 0 green [[0.0, -1.0, 0.0], [0.0, -5.0, 0.0]], # 1 red ]) widths = [0.5, 0.3, ] # print ' vertices_fancy\n',vertices_fancy # FLATHEAD = 0 #BEVELHEAD = 1 #TRIANGLEHEAD = 2 #ARROWHEAD = 3 fancylines.add_drawobjs(vertices_fancy, widths, # width colors, beginstyles=[TRIANGLEHEAD, TRIANGLEHEAD], endstyles=[ARROWHEAD, ARROWHEAD]) drawing.add_drawobj(fancylines) #------------------------------------------------------------------------- if 0: polylines = Polylines('polylines', drawing, joinstyle=BEVELHEAD) colors_poly = np.array([ [0.0, 0.8, 0.5, 0.9], # 0 [0.8, 0.0, 0.5, 0.9], # 1 ]) vertices_poly = np.array([ [[0.0, 2.0, 0.0], [5.0, 2.0, 0.0], [ 5.0, 7.0, 0.0], [0.0, 7.0, 0.0]], # 0 green [[0.0, -2.0, 0.0], [-2.0, -2.0, 0.0]], # 1 red ], np.object) widths = [0.5, 0.3, ] # print ' vertices_poly\n',vertices_poly polylines.add_drawobjs(vertices_poly, widths, # width colors_poly, beginstyles=[ARROWHEAD, ARROWHEAD], endstyles=[ARROWHEAD, ARROWHEAD]) drawing.add_drawobj(polylines) #------------------------------------------------------------------------- if 1: polygons = Polygons('polygons', drawing, linewidth=5) colors_poly = np.array([ [0.0, 0.9, 0.9, 0.9], # 0 [0.8, 0.2, 0.2, 0.9], # 1 ]) vertices_poly = np.array([ [[0.0, 2.0, 0.0], [5.0, 2.0, 0.0], [ 5.0, 7.0, 0.0], [0.0, 7.0, 0.0]], # 0 green [[0.0, -2.0, 0.0], [-2.0, -2.0, 0.0], [-2.0, 0.0, 0.0]], # 1 red ], np.object) print ' vertices_polygon\n', vertices_poly polygons.add_drawobjs(vertices_poly, colors_poly) drawing.add_drawobj(polygons) canvas = self.gleditor.get_canvas() canvas.set_drawing(drawing) #lines.add_drawobj([[0.0,0.0,0.0],[-0.2,-0.8,0.0]], [0.0,0.9,0.9,0.9]) #circles.add_drawobj([1.5,0.0,0.0],0.6,colors2o[0], colors2[0]) # canvas.zoom_tofit() wx.CallAfter(canvas.zoom_tofit) if __name__ == '__main__': # if len(sys.argv)==3: # ident = sys.argv[1] # dirpath = sys.argv[2] # else: # ident = None # dirpath = None myapp = MyApp(0) myapp.MainLoop()
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rubi/datasets/vqa2.py
abhipsabasu/rubi.bootstrap.pytorch
83
16521
<reponame>abhipsabasu/rubi.bootstrap.pytorch import os import csv import copy import json import torch import numpy as np from os import path as osp from bootstrap.lib.logger import Logger from bootstrap.lib.options import Options from block.datasets.vqa_utils import AbstractVQA from copy import deepcopy import random import tqdm import h5py class VQA2(AbstractVQA): def __init__(self, dir_data='data/vqa2', split='train', batch_size=10, nb_threads=4, pin_memory=False, shuffle=False, nans=1000, minwcount=10, nlp='mcb', proc_split='train', samplingans=False, dir_rcnn='data/coco/extract_rcnn', adversarial=False, dir_cnn=None ): super(VQA2, self).__init__( dir_data=dir_data, split=split, batch_size=batch_size, nb_threads=nb_threads, pin_memory=pin_memory, shuffle=shuffle, nans=nans, minwcount=minwcount, nlp=nlp, proc_split=proc_split, samplingans=samplingans, has_valset=True, has_testset=True, has_answers_occurence=True, do_tokenize_answers=False) self.dir_rcnn = dir_rcnn self.dir_cnn = dir_cnn self.load_image_features() # to activate manually in visualization context (notebo# to activate manually in visualization context (notebook) self.load_original_annotation = False def add_rcnn_to_item(self, item): path_rcnn = os.path.join(self.dir_rcnn, '{}.pth'.format(item['image_name'])) item_rcnn = torch.load(path_rcnn) item['visual'] = item_rcnn['pooled_feat'] item['coord'] = item_rcnn['rois'] item['norm_coord'] = item_rcnn.get('norm_rois', None) item['nb_regions'] = item['visual'].size(0) return item def add_cnn_to_item(self, item): image_name = item['image_name'] if image_name in self.image_names_to_index_train: index = self.image_names_to_index_train[image_name] image = torch.tensor(self.image_features_train['att'][index]) elif image_name in self.image_names_to_index_val: index = self.image_names_to_index_val[image_name] image = torch.tensor(self.image_features_val['att'][index]) image = image.permute(1, 2, 0).view(196, 2048) item['visual'] = image return item def load_image_features(self): if self.dir_cnn: filename_train = os.path.join(self.dir_cnn, 'trainset.hdf5') filename_val = os.path.join(self.dir_cnn, 'valset.hdf5') Logger()(f"Opening file {filename_train}, {filename_val}") self.image_features_train = h5py.File(filename_train, 'r', swmr=True) self.image_features_val = h5py.File(filename_val, 'r', swmr=True) # load txt with open(os.path.join(self.dir_cnn, 'trainset.txt'.format(self.split)), 'r') as f: self.image_names_to_index_train = {} for i, line in enumerate(f): self.image_names_to_index_train[line.strip()] = i with open(os.path.join(self.dir_cnn, 'valset.txt'.format(self.split)), 'r') as f: self.image_names_to_index_val = {} for i, line in enumerate(f): self.image_names_to_index_val[line.strip()] = i def __getitem__(self, index): item = {} item['index'] = index # Process Question (word token) question = self.dataset['questions'][index] if self.load_original_annotation: item['original_question'] = question item['question_id'] = question['question_id'] item['question'] = torch.tensor(question['question_wids'], dtype=torch.long) item['lengths'] = torch.tensor([len(question['question_wids'])], dtype=torch.long) item['image_name'] = question['image_name'] # Process Object, Attribut and Relational features # Process Object, Attribut and Relational features if self.dir_rcnn: item = self.add_rcnn_to_item(item) elif self.dir_cnn: item = self.add_cnn_to_item(item) # Process Answer if exists if 'annotations' in self.dataset: annotation = self.dataset['annotations'][index] if self.load_original_annotation: item['original_annotation'] = annotation if 'train' in self.split and self.samplingans: proba = annotation['answers_count'] proba = proba / np.sum(proba) item['answer_id'] = int(np.random.choice(annotation['answers_id'], p=proba)) else: item['answer_id'] = annotation['answer_id'] item['class_id'] = torch.tensor([item['answer_id']], dtype=torch.long) item['answer'] = annotation['answer'] item['question_type'] = annotation['question_type'] else: if item['question_id'] in self.is_qid_testdev: item['is_testdev'] = True else: item['is_testdev'] = False # if Options()['model.network.name'] == 'xmn_net': # num_feat = 36 # relation_mask = np.zeros((num_feat, num_feat)) # boxes = item['coord'] # for i in range(num_feat): # for j in range(i+1, num_feat): # # if there is no overlap between two bounding box # if boxes[0,i]>boxes[2,j] or boxes[0,j]>boxes[2,i] or boxes[1,i]>boxes[3,j] or boxes[1,j]>boxes[3,i]: # pass # else: # relation_mask[i,j] = relation_mask[j,i] = 1 # relation_mask = torch.from_numpy(relation_mask).byte() # item['relation_mask'] = relation_mask return item def download(self): dir_zip = osp.join(self.dir_raw, 'zip') os.system('mkdir -p '+dir_zip) dir_ann = osp.join(self.dir_raw, 'annotations') os.system('mkdir -p '+dir_ann) os.system('wget http://visualqa.org/data/mscoco/vqa/v2_Questions_Train_mscoco.zip -P '+dir_zip) os.system('wget http://visualqa.org/data/mscoco/vqa/v2_Questions_Val_mscoco.zip -P '+dir_zip) os.system('wget http://visualqa.org/data/mscoco/vqa/v2_Questions_Test_mscoco.zip -P '+dir_zip) os.system('wget http://visualqa.org/data/mscoco/vqa/v2_Annotations_Train_mscoco.zip -P '+dir_zip) os.system('wget http://visualqa.org/data/mscoco/vqa/v2_Annotations_Val_mscoco.zip -P '+dir_zip) os.system('unzip '+osp.join(dir_zip, 'v2_Questions_Train_mscoco.zip')+' -d '+dir_ann) os.system('unzip '+osp.join(dir_zip, 'v2_Questions_Val_mscoco.zip')+' -d '+dir_ann) os.system('unzip '+osp.join(dir_zip, 'v2_Questions_Test_mscoco.zip')+' -d '+dir_ann) os.system('unzip '+osp.join(dir_zip, 'v2_Annotations_Train_mscoco.zip')+' -d '+dir_ann) os.system('unzip '+osp.join(dir_zip, 'v2_Annotations_Val_mscoco.zip')+' -d '+dir_ann) os.system('mv '+osp.join(dir_ann, 'v2_mscoco_train2014_annotations.json')+' ' +osp.join(dir_ann, 'mscoco_train2014_annotations.json')) os.system('mv '+osp.join(dir_ann, 'v2_mscoco_val2014_annotations.json')+' ' +osp.join(dir_ann, 'mscoco_val2014_annotations.json')) os.system('mv '+osp.join(dir_ann, 'v2_OpenEnded_mscoco_train2014_questions.json')+' ' +osp.join(dir_ann, 'OpenEnded_mscoco_train2014_questions.json')) os.system('mv '+osp.join(dir_ann, 'v2_OpenEnded_mscoco_val2014_questions.json')+' ' +osp.join(dir_ann, 'OpenEnded_mscoco_val2014_questions.json')) os.system('mv '+osp.join(dir_ann, 'v2_OpenEnded_mscoco_test2015_questions.json')+' ' +osp.join(dir_ann, 'OpenEnded_mscoco_test2015_questions.json')) os.system('mv '+osp.join(dir_ann, 'v2_OpenEnded_mscoco_test-dev2015_questions.json')+' ' +osp.join(dir_ann, 'OpenEnded_mscoco_test-dev2015_questions.json'))
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riberry/policy/helpers.py
srafehi/riberry
2
100818
from .engine import Rule, AttributeContext, Policy class ShorthandRule(Rule): def __init__(self, func): self.func = func def target_clause(self, context: AttributeContext) -> bool: return True def condition(self, context: AttributeContext) -> bool: return self.func(context) class ShorthandPolicy(Policy): def __init__(self, func, *collection): super(ShorthandPolicy, self).__init__(*collection) self.func = func def target_clause(self, context: AttributeContext) -> bool: return True def condition(self, context: AttributeContext) -> bool: return self.func(context) class ShorthandPolicySet(Policy): def __init__(self, func, *collection): super(ShorthandPolicySet, self).__init__(*collection) self.func = func def target_clause(self, context: AttributeContext) -> bool: return True def condition(self, context: AttributeContext) -> bool: return self.func(context) def rule(func): return ShorthandRule(func) def policy(func): def builder(*collection): return ShorthandPolicy(func, *collection) return builder def policy_set(func): def builder(*collection): return ShorthandPolicySet(func, *collection) return builder
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djapi/authtoken/models.py
Suor/djapi
12
38104
<reponame>Suor/djapi<gh_stars>10-100 import binascii import os from django.conf import settings from django.db import models from django.utils.encoding import python_2_unicode_compatible from django.utils.translation import ugettext_lazy as _ @python_2_unicode_compatible class Token(models.Model): """ The default authorization token model. """ key = models.CharField(_("Key"), max_length=40, primary_key=True) user = models.OneToOneField( settings.AUTH_USER_MODEL, related_name='auth_token', on_delete=models.CASCADE, verbose_name=_("User") ) created = models.DateTimeField(_("Created"), auto_now_add=True) class Meta: verbose_name = _("Token") verbose_name_plural = _("Tokens") def save(self, *args, **kwargs): if not self.key: self.key = self.generate_key() return super(Token, self).save(*args, **kwargs) def generate_key(self): return binascii.hexlify(os.urandom(20)).decode() def __str__(self): return self.key
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packages/pytest-simcore/src/pytest_simcore/minio_service.py
elisabettai/osparc-simcore
0
65001
<gh_stars>0 # pylint: disable=redefined-outer-name # pylint: disable=unused-argument # pylint: disable=unused-variable import logging from distutils.util import strtobool from typing import Dict, Iterator import pytest import tenacity from _pytest.monkeypatch import MonkeyPatch from minio import Minio from minio.datatypes import Object from minio.deleteobjects import DeleteError, DeleteObject from tenacity import Retrying from .helpers.utils_docker import get_localhost_ip, get_service_published_port log = logging.getLogger(__name__) def _ensure_remove_bucket(client: Minio, bucket_name: str): if client.bucket_exists(bucket_name): # remove content objs: Iterator[Object] = client.list_objects( bucket_name, prefix=None, recursive=True ) # FIXME: minio 7.1.0 does NOT remove all objects!? Added in requirements/constraints.txt to_delete = [DeleteObject(o.object_name) for o in objs] errors: Iterator[DeleteError] = client.remove_objects(bucket_name, to_delete) list_of_errors = list(errors) assert not any(list_of_errors), list(list_of_errors) # remove bucket client.remove_bucket(bucket_name) assert not client.bucket_exists(bucket_name) @pytest.fixture(scope="module") def minio_config( docker_stack: Dict, testing_environ_vars: Dict, monkeypatch_module: MonkeyPatch ) -> Dict[str, str]: assert "pytest-ops_minio" in docker_stack["services"] config = { "client": { "endpoint": f"{get_localhost_ip()}:{get_service_published_port('minio')}", "access_key": testing_environ_vars["S3_ACCESS_KEY"], "secret_key": testing_environ_vars["S3_SECRET_KEY"], "secure": strtobool(testing_environ_vars["S3_SECURE"]) != 0, }, "bucket_name": testing_environ_vars["S3_BUCKET_NAME"], } # nodeports takes its configuration from env variables for key, value in config["client"].items(): monkeypatch_module.setenv(f"S3_{key.upper()}", str(value)) monkeypatch_module.setenv("S3_SECURE", testing_environ_vars["S3_SECURE"]) monkeypatch_module.setenv("S3_BUCKET_NAME", config["bucket_name"]) return config @pytest.fixture(scope="module") def minio_service(minio_config: Dict[str, str]) -> Iterator[Minio]: client = Minio(**minio_config["client"]) for attempt in Retrying( wait=tenacity.wait_fixed(5), stop=tenacity.stop_after_attempt(60), before_sleep=tenacity.before_sleep_log(log, logging.WARNING), reraise=True, ): with attempt: # TODO: improve as https://docs.min.io/docs/minio-monitoring-guide.html if not client.bucket_exists("pytest"): client.make_bucket("pytest") client.remove_bucket("pytest") bucket_name = minio_config["bucket_name"] # cleans up in case a failing tests left this bucket _ensure_remove_bucket(client, bucket_name) client.make_bucket(bucket_name) assert client.bucket_exists(bucket_name) yield client # cleanup upon tear-down _ensure_remove_bucket(client, bucket_name) @pytest.fixture(scope="module") def bucket(minio_config: Dict[str, str], minio_service: Minio) -> Iterator[str]: bucket_name = minio_config["bucket_name"] _ensure_remove_bucket(minio_service, bucket_name) minio_service.make_bucket(bucket_name) yield bucket_name _ensure_remove_bucket(minio_service, bucket_name)
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libs/enums.py
paulirish/covid-data-model
1
141237
import enum # Fips code chosen for all unknown fips values. # TODO: This should maybe be unique per state. UNKNOWN_FIPS = "99999" class Intervention(enum.Enum): NO_MITIGATION = 0 HIGH_MITIGATION = 1 # on the webiste, strictDistancingNow MODERATE_MITIGATION = 3 # weak distancingNow on the website SELECTED_MITIGATION = 4 # look at what the state is and get the file for that # We are using enum 2 for consistency with the website OBSERVED_MITIGATION = 2 # given the previous pattern, how do we predict going forward @classmethod def county_supported_interventions(cls): return [ Intervention.NO_MITIGATION, Intervention.HIGH_MITIGATION, Intervention.MODERATE_MITIGATION, Intervention.SELECTED_MITIGATION, ] @classmethod def from_webui_data_adaptor(cls, label): if label == "suppression_policy__no_intervention": return cls.NO_MITIGATION elif label == "suppression_policy__flatten_the_curve": return cls.HIGH_MITIGATION elif label == "suppression_policy__inferred": return cls.OBSERVED_MITIGATION elif label == "suppression_policy__social_distancing": return cls.MODERATE_MITIGATION raise Exception(f"Unexpected WebUI Data Adaptor label: {label}") @classmethod def from_str(cls, label): if label == "shelter_in_place": return cls.HIGH_MITIGATION elif label == "social_distancing": return cls.MODERATE_MITIGATION else: return cls.NO_MITIGATION
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pywebcopy/schedulers.py
rajatomar788/pywebcopy7
5
83078
# Copyright 2020; <NAME> # See license for more details import logging import threading import weakref from requests import ConnectionError from six import PY3 from six import string_types from six.moves.urllib.parse import urlparse from .elements import VoidResource from .elements import CSSResource from .elements import JSResource from .elements import AbsoluteUrlResource from .elements import GenericResource from .elements import HTMLResource from .elements import UrlRemover from .helpers import RecentOrderedDict logger = logging.getLogger(__name__) class Index(RecentOrderedDict): """Files index dict. ..todo:: make it database synced """ def __init__(self, *args, **kwargs): super(Index, self).__init__(*args, **kwargs) self.lock = threading.Lock() def add_entry(self, k, v): with self.lock: self.__setitem__(k, v) def get_entry(self, k, default=None): return self.get(k, default=default) def add_resource(self, resource): location = resource.filepath self.add_entry(resource.context.url, location) if hasattr(resource.response, 'url'): self.add_entry(resource.response.url, location) if resource.response.history: for r in resource.response.history: self.add_entry(r.url, location) index_resource = add_resource class SchedulerBase(object): """A Synchronised resource processor. File paths would be based on the content-type header returned by the server but this would be slow because of being synchronous but is very reliable. """ style_tags = frozenset(['link', 'style']) img_tags = frozenset(['img']) script_tags = frozenset(['script']) meta_tags = frozenset(['meta']) internal_tags = (style_tags | img_tags | script_tags | meta_tags) external_tags = frozenset(['a', 'form', 'iframe']) tags = (internal_tags | external_tags) def __init__(self, default=None, **data): self.data = dict() self.data.update(data) self.default = default self.index = Index() self.block_external_domains = True self.logger = logger.getChild(self.__class__.__name__) def set_default(self, default): self.default = default self.logger.info("Set the scheduler default as: [%r]" % default) def register_handler(self, key, value): self.data.__setitem__(key, value) self.logger.info( "Set the scheduler handler for %s as: [%r]" % (key, value)) add_handler = register_handler def deregister_handler(self, key): self.data.__delitem__(key) self.logger.info("Removed the scheduler handler for: %s" % key) remove_handler = deregister_handler def get_handler(self, key, *args, **params): if key not in self.data: if self.default is None: raise KeyError(key) return self.default(*args, **params) else: return self.data[key](*args, **params) invalid_schemas = tuple([ 'data', 'javascript', 'mailto', ]) def validate_url(self, url): if not isinstance(url, string_types): self.logger.error( "Expected string type, got %r" % url) return False scheme, host, port, path, query, frag = urlparse(url) if scheme in self.invalid_schemas: self.logger.error( "Invalid url schema: [%s] for url: [%s]" % (scheme, url)) return False return True def validate_resource(self, resource): if not isinstance(resource, GenericResource): self.logger.error( "Expected GenericResource, got %r" % resource) return False if isinstance(resource, VoidResource): self.logger.error( "Skipping VoidResource: %r" % resource) return False if not isinstance(resource.url, string_types): self.logger.error( "Expected url of string type, got %r" % resource.url) return False if isinstance(resource, HTMLResource) and self.block_external_domains: # FIXME: Change the algorithm to evaluate redirects. # print(resource.url, resource.context) if not resource.url.startswith(resource.context.base_url): self.logger.error( "Blocked resource on external domain: %s" % resource.url) return False return self.validate_url(resource.url) def handle_resource(self, resource): indexed = self.index.get_entry(resource.url) if indexed: self.logger.debug( "[Cache] Resource Key: [%s] is available in the cache with value: [%s]" % (resource.url, indexed) ) # modify the resources path resolution mechanism. return resource.__dict__.__setitem__('filepath', indexed) #: Update the index before doing any processing so that later calls #: in index finds this entry without going in infinite recursion #: Response could have been already present on disk self.index.add_entry(resource.context.url, resource.filepath) if self.validate_resource(resource): self.logger.debug("Processing valid resource: %r" % resource) return self._handle_resource(resource) self.logger.error("Discarding invalid resource: %r" % resource) def _handle_resource(self, resource): raise NotImplementedError() class Collector(SchedulerBase): """A simple resource collector to use when debugging or requires manual collection of sub-files.""" def __init__(self, *args, **kwargs): super(Collector, self).__init__(*args, **kwargs) self.children = list() def _handle_resource(self, resource): self.children.append(resource) class Scheduler(SchedulerBase): def _handle_resource(self, resource): try: self.logger.debug('Scheduler trying to get resource at: [%s]' % resource.url) resource.get(resource.context.url) # NOTE :meth:`get` can change the :attr:`filepath` of the resource self.index.add_resource(resource) except ConnectionError: self.logger.error( "Scheduler ConnectionError Failed to retrieve resource from [%s]" % resource.url) # self.index.add_entry(resource.url, resource.filepath) except Exception as e: self.logger.exception(e) # self.index.add_entry(resource.url, resource.filepath) else: self.logger.debug('Scheduler running handler for: [%s]' % resource.url) resource.retrieve() self.index.add_resource(resource) class ThreadingScheduler(Scheduler): def __init__(self, *args, **kwargs): super(ThreadingScheduler, self).__init__(*args, **kwargs) self.threads = weakref.WeakSet() self.timeout = 1 def __del__(self): self.close() def close(self, timeout=None): if not timeout: timeout = self.timeout threads = self.threads self.threads = None for thread in threads: if thread.is_alive() and thread is not threading.current_thread(): thread.join(timeout) def _handle_resource(self, resource): def run(r): self.logger.debug('Scheduler trying to get resource at: [%s]' % r.url) # r.response = r.session.get(r.context.url) r.get(r.context.url) self.logger.debug('Scheduler running handler for: [%s]' % r.url) r.retrieve() return r.context.url, r.filepath thread = threading.Thread(target=run, args=(resource,)) thread.start() self.threads.add(thread) class GEventScheduler(Scheduler): def __init__(self, maxsize=None, *args, **kwargs): super(GEventScheduler, self).__init__(*args, **kwargs) try: from gevent.pool import Pool except ImportError: raise ImportError( "gevent module is not installed. " "Install it using pip: $ pip install gevent" ) self.pool = Pool(maxsize) def __del__(self): self.close() def close(self, timeout=None): self.pool.kill(timeout=timeout) def _handle_resource(self, resource): def run(r): self.logger.debug('Scheduler trying to get resource at: [%s]' % resource.url) r.response = r.session.get(r.context.url) self.logger.debug('Scheduler running retrieving process: [%s]' % resource.url) r.retrieve() return r.context.url, r.filepath g = self.pool.spawn(run, resource) g.link_value(lambda gl: logger.info("Written the file from <%s> to <%s>" % gl.value)) g.link_exception(lambda gl: logger.error(str(gl.exception))) if PY3: class ThreadPoolScheduler(Scheduler): def __init__(self, maxsize=None, *args, **kwargs): super(ThreadPoolScheduler, self).__init__(*args, **kwargs) import concurrent.futures self.pool = concurrent.futures.ThreadPoolExecutor(maxsize) def __del__(self): self.close() def close(self, wait=None): self.pool.shutdown(wait) def _handle_resource(self, resource): def run(r): self.logger.debug('Scheduler trying to get resource at: [%s]' % resource.url) r.response = r.session.get(r.context.url) self.logger.debug('Scheduler running retrieving process: [%s]' % resource.url) r.retrieve() return r.context.url, r.filepath def callback(ret): if ret.exception(): self.logger.error(str(ret.exception())) else: self.logger.info("Written the file from <%s> to <%s>" % ret.result()) g = self.pool.submit(run, resource) g.add_done_callback(callback) def thread_pool_default_scheduler(maxsize=4): ans = ThreadPoolScheduler(maxsize=maxsize) fac = default_scheduler() ans.default = fac.default ans.data = fac.data del fac return ans def thread_pool_crawler_scheduler(maxsize=4): ans = thread_pool_default_scheduler(maxsize=maxsize) for k in ans.meta_tags: ans.register_handler(k, HTMLResource) for k in ans.external_tags: ans.register_handler(k, HTMLResource) return ans else: class ThreadPoolScheduler(object): def __init__(self, *args, **kwargs): raise RuntimeError( "Python 2 does not have `futures` modules, " "hence you should use any other scheduler link gevent.!" ) def thread_pool_scheduler(maxsize=4): raise RuntimeError( "Python 2 does not have futures modules, " "hence you should use any other scheduler link gevent.!", maxsize ) def thread_pool_crawler_scheduler(maxsize=4): raise RuntimeError( "Python 2 does not have futures modules, " "hence you should use any other scheduler link gevent.!", maxsize ) def default_scheduler(): ans = Scheduler() ans.default = GenericResource for k in ans.style_tags: ans.register_handler(k, CSSResource) for k in ans.img_tags: ans.register_handler(k, GenericResource) for k in ans.script_tags: ans.register_handler(k, JSResource) for k in ans.meta_tags: ans.register_handler(k, GenericResource) for k in ans.external_tags: ans.register_handler(k, AbsoluteUrlResource) return ans def no_js_scheduler(): ans = default_scheduler() for k in ans.script_tags: ans.register_handler(k, UrlRemover) return ans def crawler_scheduler(): ans = default_scheduler() for k in ans.meta_tags: ans.register_handler(k, HTMLResource) for k in ans.external_tags: ans.register_handler(k, HTMLResource) return ans def threading_default_scheduler(): ans = ThreadingScheduler() fac = default_scheduler() ans.default = fac.default ans.data = fac.data del fac return ans def threading_crawler_scheduler(): ans = threading_default_scheduler() for k in ans.meta_tags: ans.register_handler(k, HTMLResource) for k in ans.external_tags: ans.register_handler(k, HTMLResource) return ans def gevent_default_scheduler(maxsize=4): ans = GEventScheduler(maxsize=maxsize) fac = default_scheduler() ans.default = fac.default ans.data = fac.data del fac return ans def gevent_crawler_scheduler(): ans = gevent_default_scheduler() for k in ans.meta_tags: ans.register_handler(k, HTMLResource) for k in ans.external_tags: ans.register_handler(k, HTMLResource) return ans def base64_scheduler(): raise NotImplemented
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kardioml/segmentation/teijeiro/model/interpretation.py
Seb-Good/physionet-challenge-2020
13
120358
<gh_stars>10-100 # -*- coding: utf-8 -*- # pylint: disable-msg=E0202, E0102, E1101, E1103, E1001 """ Created on Fri Jan 24 09:46:28 2014 This module contains the definition of the interpretation class, which is the basic unit of the search process which tries to solve interpretation problems. @author: <NAME> """ from .observable import Observable, EventObservable, between, overlap, end_cmp_key from .interval import Interval as Iv from .constraint_network import verify import kardioml.segmentation.teijeiro.knowledge.abstraction_patterns as ap import kardioml.segmentation.teijeiro.knowledge.constants as C import kardioml.segmentation.teijeiro.acquisition.obs_buffer as obsbuf import sortedcontainers import weakref import copy import numpy as np from collections import deque, namedtuple as nt ################################################## ## Utility functions to detect merge situations ## ################################################## def _pat_mergeable(p1, p2): """ Compare two *AbstractionPattern* instances for equality regarding an interpretation merging operation. Evidence and hypothesis comparison is assumed to be positive, so only the automata and the initial and final states are compared. """ if p1 is None or p2 is None: return p1 is p2 return p1.automata is p2.automata and p1.istate == p2.istate and p1.fstate == p2.fstate def _focus_mergeable(f1, f2): """ Compare two focuses of attention for equality regarding an interpretation merging operation. The length of the lists within the two focuses are assumed to be equal, but this has to be tested separately. """ return all( f1._lst[i][0] == f2._lst[i][0] and _pat_mergeable(f1._lst[i][1], f2._lst[i][1]) for i in range(len(f1._lst) - 1, -1, -1) ) class PastMetrics(nt('PastMetrics', 'time, abst, abstime, nhyp')): """ Tuple to store relevant information to evaluate an interpretation until a specific time, to allow discard old observations. """ __slots__ = () def diff(self, other): """ Obtains the difference between two PastMetrics tuples, returned as a numpy array with three components. *time* attribute is excluded from diff. """ return np.array((self.abst - other.abst, self.abstime - other.abstime, self.nhyp - other.nhyp)) def patch(self, patch): """ Obtains a new PastMetrics object by applying a difference array, obtained by the *diff* method. Parameters ---------- patch: Array, list or tuple with exactly three numerical values. """ return PastMetrics(self.time, *np.array(self[1:] + patch)) class Focus(object): """ This class represents the focus of attention of an interpretation, and it encapsulates all data and functionality related with its management. """ __slots__ = '_lst' def __init__(self, parent_focus=None): """ Initializes a new empty focus of attention, or a shallow copy of an existing focus. Instance Properties ------------------- _lst: Stack containing a number of tuples (observation_or_finding, pattern). If 'observation_or_finding' is a finding, then 'pattern' is the abstraction pattern generating such finding. If is an observation, then 'pattern' is the pattern for which the observation is its hypothesis, or None if it is an initial observation. """ if parent_focus is None: self._lst = [] else: self._lst = parent_focus._lst[:] def __len__(self): return len(self._lst) def __contains__(self, key): return any(key is v for v, _ in self._lst) def __nonzero__(self): return bool(self._lst) def push(self, obs, pattern): """ Inserts a new observation or finding in the focus of attention. """ self._lst.append((obs, pattern)) def pop(self, n=1): """Removes 'n' elements from the focus of attention (1 by default)""" del self._lst[-n] @property def top(self): """Obtains the element at the top of the focus of attention""" return self._lst[-1] @top.setter def top(self, value): """Modifies the element at the top of the focus of attention""" self._lst[-1] = value @property def patterns(self): """ Obtains an iterator over the patterns supporting the observations or findings in the focus of attention, starting at the top of the stack. """ return (p for _, p in reversed(self._lst)) @property def nhyp(self): """Returns the number of abstraction hypotheses in this focus""" return sum(1 for o, p in self._lst if p is not None and o is p.hypothesis) @property def earliest_time(self): """ Returns the minimum starting time of observations or findings in this focus of attention. """ return min(o.earlystart for o, _ in self._lst) def get_delayed_finding(self, observation): """ Obtains the finding that will be matched with an observation once the observation is fully observed, or None if the observation will not be matched with a finding. """ for i in range(len(self._lst) - 1, 0, -1): if self._lst[i][0] is observation: f, p = self._lst[i - 1] if p is not None and f is p.finding: return f break return None def match(self, finding, obs): """ Performs a matching operation between the finding at the top of the focus with a given observation, checking the time and value consistency of the matching. After consistency is checked, the finding is removed from the focus by means of a pop() operation. """ f, pat = self._lst[-1] assert finding is f verify( obs not in pat.evidence[pat.get_evidence_type(f)[0]], 'Observation {0} is already in the evidence of {1} pattern', (obs, pat), ) patcp = copy.copy(pat) patcp.match(f, obs) # The hypothesis generating the finding is updated self._lst[-2] = (patcp.hypothesis, patcp) # And the matched finding removed from the focus del self._lst[-1] class Interpretation(object): """ This class represents the interpretation entity, which is a consistent group of abstraction hypotheses combined by the knowledge expressed in abstraction patterns. It is the basic entity in our search process, and the result of an interpretation process. """ __slots__ = ( 'name', '_parent', 'child', 'observations', 'unintelligible', 'singletons', 'abstracted', 'nabd', 'focus', 'past_metrics', 'predinfo', '__weakref__', ) counter = 0 def __init__(self, parent=None): """ Creates a new empty interpretation, initializing its attributes as a shallow copy or a direct assigment of the attributes of the parent. If parent is None, the attributes will be empty. Instance Properties ------------------- name: Unique identificator of the interpretation. parent: Interpretation from which this one is derived, or None if this is a root interpretation. child: List of interpretations derived from this one. past_metrics: Summary of old information used for heuristics calculation. observations: Sortedlist containing all the observations in the interpretation, ordered by their start time. NOTE: This property is directly assigned from parent interpretation by default. singletons: Set with all Singleton hypotheses that are present in this interpretation. NOTE: This property is directly assigned from parent interpretation by default. abstracted: SortedList containing all the observations that are abstracted by some abstraction pattern in this interpretation. NOTE: This property is directly assigned from parent interpretation by default unintelligible: SortedList containing all the observations that cannot be abstracted by any abstraction pattern. NOTE: This property is directly assigned from parent interpretation by default. nabd: Number of hypotheses in the interpretation that can be abstracted by a higher-level hypothesis. This value is used for the evaluation of the interpretation. focus: Stack containing the focus of attention of the interpretation. Each element in this stack is an observation or a non-matched finding of a pattern. predinfo: Dictionary to store predecessor information for consecutive observations. Each entry is a 2-tuple (observation, type) with the predecessor observation and the type declared by the pattern for the consecutivity relation. NOTE: This property is directly assigned from parent interpretation by default. """ self.name = str(Interpretation.counter) if parent is None: self._parent = None self.child = [] self.observations = sortedcontainers.SortedList(key=end_cmp_key) self.singletons = set() self.abstracted = sortedcontainers.SortedList(key=end_cmp_key) self.unintelligible = sortedcontainers.SortedList(key=end_cmp_key) self.nabd = 0 self.past_metrics = PastMetrics(0, 0, 0, 0) self.focus = Focus() self.predinfo = {} else: self._parent = weakref.ref(parent, self._on_parent_deleted) self.child = [] self.parent.child.append(self) self.observations = parent.observations self.singletons = parent.singletons self.abstracted = parent.abstracted self.unintelligible = parent.unintelligible self.nabd = parent.nabd self.past_metrics = parent.past_metrics self.focus = Focus(parent.focus) self.predinfo = parent.predinfo Interpretation.counter += 1 def __str__(self): """ Obtains the representation of the interpretation as a character string. """ return self.name def __repr__(self): return self.name def _on_parent_deleted(self, _): """ Callback function called when the parent interpretation is deleted. """ self._parent = None def _get_types(self, obs): """ Obtains a tuple with the types that are used respect to an observation, both as hypothesis and as evidence of different patterns. """ types = {type(obs)}.union({p.get_evidence_type(obs)[0] for p in self.pat_map[obs][1]}) dmatch = self.get_delayed_finding(obs) if dmatch is not None: types = types.union( {type(dmatch)}, {p.get_evidence_type(dmatch)[0] for p in self.pat_map[dmatch][1]} ) return tuple(types) def _get_proper_obs(self, clazz=Observable, start=0, end=np.inf, filt=lambda obs: True, reverse=False): """ Obtains a list of observations matching the search criteria, ordered by the earliest time of the observation. Parameters ---------- clazz: Only instances of the *clazz* class (or any subclass) are returned. start: Only observations whose earlystart attribute is after or equal this parameter are returned. end: Only observations whose lateend attribute is lower or equal this parameter are returned. filt: General filter provided as a boolean function that accepts an observation as a parameter. Only the observations satisfying this filter are returned. reverse: Boolean parameter. If True, observations are returned in reversed order, from last to first. """ dummy = EventObservable() if start == 0: idx = 0 else: dummy.time.value = Iv(start, start) idx = self.observations.bisect_left(dummy) if end == np.inf: udx = len(self.observations) else: dummy.time.value = Iv(end, end) udx = self.observations.bisect_right(dummy) return ( obs for obs in self.observations.islice(idx, udx, reverse) if obs.earlystart >= start and isinstance(obs, clazz) and filt(obs) ) @property def is_firm(self): """ Checks if an interpretation is firm, that is, there are no unmatched findings and all the abstraction patterns involved have a sufficient set of evidence to support their hypothesis. """ return all(p is None or p.sufficient_evidence for p in self.focus.patterns) @property def time_point(self): """ Obtains the time point of an interpretation, that is, the end time value of the last base evidence being considered as evidence of any hypothesis in the interpretation. If there are no hypothesis in the interpretation, then the time point is just before the first available observation. """ lastfocus = max( 0, ( self.focus.top[0].earlystart - 1 if self.focus else next(self.get_observations()).earlystart - 1 ), ) return max(self.abstracted[-1].lateend, lastfocus) if self.abstracted else lastfocus @property def parent(self): """ Obtains the parent of an interpretation. """ return self._parent() if self._parent is not None else None @parent.setter def parent(self, interpretation): """ Establishes the parent of this interpretation, changing the corresponding references in the old and new parents. """ if self._parent is not None and self in self.parent.child: self.parent.child.remove(self) if interpretation is not None: self._parent = weakref.ref(interpretation, self._on_parent_deleted) self.parent.child.append(self) else: self._parent = None @property def ndescendants(self): """Obtains the number of descendants of this interpretation""" stack = [self] ctr = 0 while stack: ctr += 1 interp = stack.pop() stack.extend(interp.child) return ctr def is_mergeable(self, other): """ Checks if two interpretations can be merged, that is, they represent exactly the same interpretation from the time point in the past_metrics structure. """ nobs = len(self.observations) nabs = len(self.abstracted) nunint = len(self.unintelligible) nfocus = len(self.focus) return ( self is not other and len(other.observations) == nobs and len(other.abstracted) == nabs and len(other.unintelligible) == nunint and len(other.focus) == nfocus and self.singletons == other.singletons and _focus_mergeable(self.focus, other.focus) and all(self.unintelligible[i] == other.unintelligible[i] for i in range(nunint - 1, -1, -1)) and all(self.abstracted[i] == other.abstracted[i] for i in range(nabs - 1, -1, -1)) and all(self.observations[i] == other.observations[i] for i in range(nobs - 1, -1, -1)) ) def is_ancestor(self, interpretation): """ Checks if a given interpretation is an ancestor in the hierarchy of this interpretation. The same interpretation is not considered an ancestor. """ if int(self.name) < int(interpretation.name): return False parent = self.parent while True: if parent is interpretation: return True elif parent is None: return False parent = parent.parent def verify_exclusion(self, obs): """ Checks if an observation violates the exclusion relation in this interpretation. """ excluded = ap.get_excluded(type(obs)) other = obsbuf.find_overlapping(obs, excluded) verify(other is None, 'Exclusion relation violation between {0} and {1}', (other, obs)) dummy = EventObservable() dummy.end.value = Iv(obs.latestart, obs.latestart) idx = self.observations.bisect_right(dummy) while idx < len(self.observations): other = self.observations[idx] verify( other is obs or not isinstance(other, excluded) or not overlap(other, obs), 'Exclusion relation violation between {0} and {1}', (other, obs), ) idx += 1 def verify_consecutivity_violation(self, obs): """ Checks if an observation violates the consecutivity constraints in this interpretation. """ idx = self.observations.bisect_left(obs) for obs2 in ( o for o in self.observations[idx:] if o in self.predinfo and isinstance(obs, self.predinfo[o][1]) ): verify( not between(self.predinfo[obs2][0], obs, obs2), '{1} violates the consecutivity constraint between {0} and {2}', (self.predinfo[obs2][0], obs, obs2), ) def verify_consecutivity_satisfaction(self, obs1, obs2, clazz): """ Checks if a consecutivity constraint defined by two observations is violated by some observation in this interpretation or in the observations buffer. """ idx = self.observations.bisect_right(obs1) dummy = EventObservable() dummy.end.value = Iv(obs2.earlyend, obs2.earlyend) udx = self.observations.bisect_left(dummy) for obs in self.observations.islice(idx, udx): verify( obs is obs2 or not isinstance(obs, clazz), '{1} violates the consecutivity constraint between {0} and {2}', (obs1, obs, obs2), ) hole = Observable() hole.start.value = Iv(obs1.lateend, obs1.lateend) hole.end.value = Iv(obs2.earlystart, obs2.earlystart) other = obsbuf.find_overlapping(hole, clazz) verify( other is None, '{1} violates the consecutivity constraint between {0} and {2}', (obs1, other, obs2), ) def get_observations(self, clazz=Observable, start=0, end=np.inf, filt=lambda obs: True, reverse=False): """ Obtains a list of observations matching the search criteria, ordered by the earliest time of the observation. Parameters ---------- clazz: Only instances of the *clazz* class (or any subclass) are returned. start: Only observations whose earlystart attribute is after or equal this parameter are returned. end: Only observations whose lateend attribute is lower or equal this parameter are returned. filt: General filter provided as a boolean function that accepts an observation as a parameter. Only the observations satisfying this filter are returned. reverse: Boolean parameter. If True, observations are returned in reversed order, from last to first. """ # We perform a combination of the observations from the global buffer # and from the interpretation. geng = obsbuf.get_observations(clazz, start, end, filt, reverse) genl = self._get_proper_obs(clazz, start, end, filt, reverse) dummy = EventObservable() dummy.start.value = Iv(np.inf, np.inf) nxtg = next(geng, dummy) nxtl = next(genl, dummy) while True: nxt = min(nxtg, nxtl) if nxt is dummy: return elif nxt is nxtg: nxtg = next(geng, dummy) else: nxtl = next(genl, dummy) yield nxt def remove_old(self, time=None): """Removes old observations from the interpretation.""" if time is None: time = max(self.past_metrics.time, self.focus.earliest_time) - C.FORGET_TIMESPAN # A minimum number of observations is kept nmin = min(C.MIN_NOBS, len(self.observations)) if nmin > 0: time = max(self.past_metrics.time, min(time, self.observations[-nmin].lateend - 1)) dummy = EventObservable() dummy.end.value = Iv(time, time) nhyp = abst = abstime = 0.0 # Old observations are removed from all lists. for lstname in ('observations', 'abstracted', 'unintelligible'): lst = getattr(self, lstname) idx = lst.bisect_right(dummy) if idx > 0 and self.parent is not None and getattr(self.parent, lstname) is lst: lst = lst.copy() setattr(self, lstname, lst) if lstname == 'observations': nhyp = idx elif lstname == 'abstracted': abstime = sum( o.earlyend - o.latestart + 1 for o in lst[:idx] if ap.get_obs_level(type(o)) == 0 ) abst = idx del lst[:idx] self.past_metrics = PastMetrics( time, self.past_metrics.abst + abst, self.past_metrics.abstime + abstime, self.past_metrics.nhyp + nhyp, ) def recover_all(self): """ Recovers all observations from the ancestor interpretations, in order to have the full interpretation from the beginning of the process. Hypotheses in the focus of attention are also included in the *observations* attribute. """ allobs = set(self.observations) interp = self.parent while interp is not None: allobs |= set(interp.observations) interp = interp.parent allobs.update((o for o, p in self.focus._lst if p is not None and o is p.hypothesis)) allobs = sortedcontainers.SortedList(allobs) # Duplicate removal (set only prevents same references, not equality) i = 0 while i < len(allobs) - 1: obs = allobs[i] while allobs[i + 1] == obs: allobs.pop(i + 1) if i == len(allobs) - 1: break i += 1 self.observations = sortedcontainers.SortedList(allobs) def detach(self, reason=''): """ Detachs this interpretation from the interpretations tree, being from that moment a new root. """ # Uncomment to debug. # print str(self), reason if self.parent is not None: parent = self.parent parent.child.remove(self) self.parent = None def discard(self, reason=''): """ Discards this interpretation, and recursively all the descendant interpretations. """ self.detach(reason) stack = self.child[:] while stack: interp = stack.pop() interp.detach('Parent interpretation discarded') stack.extend(interp.child) def get_child(self, name): """ Obtains the child interpretation of this one with the given id. """ name = str(name) queue = deque([self]) while queue: head = queue.popleft() if head.name == name: return head for subbr in head.child: queue.append(subbr) raise ValueError('No child interpretation with such name')
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extensions/log.py
MerelyServices/Merely-Framework
1
194403
<gh_stars>1-10 """ Log - User activity recording and error tracing Features: to file, to channel, command, responses to a command, errors, misc Recommended cogs: Error """ import traceback from types import TracebackType from typing import Union import disnake from disnake.ext import commands class Log(commands.Cog): """ Record messages, commands and errors to file or a discord channel """ def __init__(self, bot:commands.Bot): self.bot = bot self.logchannel = None # ensure config file has required data if not bot.config.has_section('log'): bot.config.add_section('log') if 'logchannel' not in bot.config['log']: bot.config['log']['logchannel'] = '' @commands.Cog.listener('on_ready') async def get_logchannel(self): """ Connect to the logging channel """ if self.bot.config['log']['logchannel'].isdigit(): self.logchannel = await self.bot.fetch_channel(int(self.bot.config['log']['logchannel'])) def truncate(self, string:str, maxlen:int=30): return string[:maxlen] + ('...' if len(string) > maxlen else '') def wrap(self, content:str, author:disnake.User, channel:disnake.abc.Messageable): """ Format log data consistently """ if isinstance(channel, disnake.TextChannel): return f"[{self.truncate(channel.guild.name, 10)}#{self.truncate(channel.name)}] {self.truncate(author.name, 10)}#{author.discriminator}: {self.truncate(content)}" elif isinstance(channel, disnake.DMChannel): if channel.recipient: return f"[DM({self.truncate(channel.recipient.name, 10)}#{channel.recipient.discriminator})] {author.name}#{author.discriminator}: {self.truncate(content)}" else: return f"[DM] {self.truncate(author.name, 10)}#{author.discriminator}: {self.truncate(content)}" elif isinstance(channel, disnake.Thread): return f"[Thread] {self.truncate(author.name, 10)}#{author.discriminator}: {self.truncate(content)}" else: return f"[Unknown] {self.truncate(author.name, 10)}#{author.discriminator}: {self.truncate(content)}" @commands.Cog.listener('on_command') async def log_command(self, ctx:commands.Context): """ Record any command calls """ logentry = self.wrap(ctx.message.content, ctx.message.author, ctx.message.channel) print(logentry) if self.logchannel: await self.logchannel.send(logentry, embed=ctx.message.embeds[0] if ctx.message.embeds else None) @commands.Cog.listener('on_command_completion') async def log_response(self, ctx:commands.Context): """ Record any replies to a command """ responses = [] async for msg in ctx.history(after=ctx.message): if msg.author == self.bot.user and msg.reference.message_id == ctx.message.id: responses.append(msg) for response in responses: logentry = self.wrap(response.content, response.author, response.channel) print(logentry) if self.logchannel: await self.logchannel.send(logentry, embed=response.embeds[0] if response.embeds else None) async def log_misc_message(self, msg:disnake.Message): """ Record a message that is in some way related to a command """ logentry = self.wrap(msg.content, msg.author, msg.channel) print(logentry) if self.logchannel: await self.logchannel.send(logentry, embed=msg.embeds[0] if msg.embeds else None) async def log_misc_str(self, ctx:Union[commands.Context, disnake.Interaction], content:str): """ Record a string and context separately """ logentry = self.wrap(content, ctx.author, ctx.channel) print(logentry) if self.logchannel: await self.logchannel.send(logentry) @commands.Cog.listener('on_command_error') async def report_error(self, _:commands.Context, error:Exception): """ Record errors """ ex = traceback.format_exception(type(error), error, error.__traceback__) logentry = f"caused an error:\n```\n{''.join(ex)}```" print(logentry) if self.logchannel: await self.logchannel.send(logentry) def setup(bot): """ Bind this cog to the bot """ bot.add_cog(Log(bot))
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13, 2 ]
0531 Binary Matrix Leftmost One.py
ansabgillani/binarysearchcomproblems
1
60450
<reponame>ansabgillani/binarysearchcomproblems<gh_stars>1-10 class Solution: def solve(self, matrix): return min((bisect_left(row,1) for row in matrix if row and bisect_left(row,1) < len(row) and row[bisect_left(row,1)] == 1), default=-1)
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5oop-data-type.py
syedmurad1/OOP-Python
0
102950
# Text Type: str # Numeric Types: int, float, complex # Sequence Types: list, tuple, range # Mapping Type: dict # Set Types: set, frozenset # Boolean Type: bool # Binary Types: bytes, bytearray, memoryview x = float(1) # x will be 1.0 y = float(2.8) # y will be 2.8 z = float("3") # z will be 3.0 w = float("4.2") # w will be 4.2 print("--------------------------------------------------------") num =6 print(num) print(str(num)+ " is my num") # print(num + "my num") # print(num + "my num") - will not work print("--------------------------------------------------------")
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src/gfx/map.py
MartinKondor/leap-of-time
0
1604955
""" Map class for playable and useable maps. """ import os import pygame from src.config import CONFIG from src.gfx.tileset import Tileset from src.gfx.map_layer import MapLayer import lib.PAdLib.occluder as occluder import lib.PAdLib.shadow as shadow class Map: def __init__(self, file_name): self.tileset = None self.layers = [] self.layer_size = (0, 0,) # Load the map for the correct level map_file = open(file_name) layer_will_be_solid = False in_layer = False for line in map_file.read().splitlines(): if not line: continue for ch in line + '\n': if ch == '#': # Ignore comments break if (not ch or ch.isspace()) and ch != '\n': # Ignore whitespace continue if ch == '{': in_layer = True self.layers.append([]) continue if ch == '}': self.layers[-1] = MapLayer(self.layers[-1], is_solid=layer_will_be_solid) in_layer = False layer_will_be_solid = False continue if in_layer and not ch.isspace(): self.layers[-1].append([int(l.strip()) - 1 for l in line.strip().split(',') if l.strip()]) # Parse line break elif ch == '*': layer_will_be_solid = True continue elif ch == '=': key, value = self.parse_key_value(line) # Set the given key if key == 'tileset': # Load the tileset self.tileset = Tileset(CONFIG.BASE_FOLDER + 'tilesets/' + value) break map_file.close() self.layers = self.layers[::-1] self.layer_size = ( self.tileset.tile_size[0] * max([len(layer[0]) for layer in self.layers]), self.tileset.tile_size[1] * max([len(layer) for layer in self.layers]) ) def parse_key_value(self, line: str): key, value = line.split('=') key = key.strip() if '"' in value: value = value.strip().split('"')[1] else: value = value.strip() return key, value def display(self, screen: pygame.Surface, player, entities): """ Draw the tiles what the user can see. """ """ shad = shadow.Shadow() occluders = [] """ for layer in self.layers: start_x = player.camera_x / self.tileset.tile_size[0] - 1 start_y = player.camera_y / self.tileset.tile_size[1] - 1 end_x = (CONFIG.WINDOW_WIDTH + player.camera_x) / self.tileset.tile_size[0] end_y = (CONFIG.WINDOW_HEIGHT + player.camera_y) / self.tileset.tile_size[1] if start_x < 0: start_x = 0 if start_y < 0: start_y = 0 for y, tiles in enumerate(layer): if y < start_y: continue elif y > end_y: break for x, tile in enumerate(tiles): if tile == -1 or x < start_x: continue elif x > end_x: break """ if layer.is_solid: xp = x * self.tileset.tile_size[0] - player.camera_x yp = y * self.tileset.tile_size[1] - player.camera_y occluders.append( occluder.Occluder([[xp, yp], [xp + self.tileset.tile_size[0], yp], [xp + self.tileset.tile_size[0], yp + self.tileset.tile_size[1]], [xp, yp + self.tileset.tile_size[1]]]) ) """ screen.blit(self.tileset.tiles[tile], (x * self.tileset.tile_size[0] - player.camera_x, y * self.tileset.tile_size[1] - player.camera_y,)) """ surf_lighting = pygame.Surface(screen.get_size()) surf_falloff = pygame.image.load(CONFIG.BASE_FOLDER + '../lib/PAdLib/examples/light_falloff100.png').convert() shad.set_light_position((player.x_pos - player.camera_x + player.body.width / 2, player.y_pos - player.camera_y + player.body.height / 2,)) shad.set_occluders(occluders) shad.set_radius(100.0) mask, draw_pos = shad.get_mask_and_position(False) mask.blit(surf_falloff, (0, 0,), special_flags=pygame.locals.BLEND_MULT) surf_lighting.fill((90, 90, 90)) surf_lighting.blit(mask, draw_pos, special_flags=pygame.locals.BLEND_MAX) screen.blit(surf_lighting, (0, 0,), special_flags=pygame.locals.BLEND_MULT) """
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members/crm/migrations/0017_profile_qb_realm_id.py
ocwc/ocwc-members
0
49826
# -*- coding: utf-8 -*- # Generated by Django 1.11.14 on 2019-01-20 12:04 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [("crm", "0016_profile")] operations = [ migrations.AddField( model_name="profile", name="qb_realm_id", field=models.TextField(blank=True, default=b""), ) ]
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tests/person_api/__init__.py
DerPate/OpenSlides
1
162721
<gh_stars>1-10 # -*- coding: utf-8 -*- VERSION = (9999, 9999, 9999, 'alpha', 1)
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Py Apple Dynamics V7.3 SRC/PA-Dynamics V7.3/PA_ATTITUDE.py
musen142/py-apple-dynamics
1
31837
<reponame>musen142/py-apple-dynamics<filename>Py Apple Dynamics V7.3 SRC/PA-Dynamics V7.3/PA_ATTITUDE.py from math import sin,cos,pi def cal_ges(PIT,ROL,l,b,w,x,Hc): YA=0 P=PIT*pi/180 R=ROL*pi/180 Y=YA*pi/180 #腿1 ABl_x=l/2 - x -(l*cos(P)*cos(Y))/2 + (b*cos(P)*sin(Y))/2 ABl_y=w/2 - (b*(cos(R)*cos(Y) + sin(P)*sin(R)*sin(Y)))/2 - (l*(cos(R)*sin(Y) - cos(Y)*sin(P)*sin(R)))/2 ABl_z= - Hc - (b*(cos(Y)*sin(R) - cos(R)*sin(P)*sin(Y)))/2 - (l*(sin(R)*sin(Y) + cos(R)*cos(Y)*sin(P)))/2 #腿2 AB2_x=l/2 - x - (l*cos(P)*cos(Y))/2 - (b*cos(P)*sin(Y))/2 AB2_y=(b*(cos(R)*cos(Y) + sin(P)*sin(R)*sin(Y)))/2 - w/2 - (l*(cos(R)*sin(Y) - cos(Y)*sin(P)*sin(R)))/2 AB2_z=(b*(cos(Y)*sin(R) - cos(R)*sin(P)*sin(Y)))/2 - Hc - (l*(sin(R)*sin(Y) + cos(R)*cos(Y)*sin(P)))/2 #腿3 AB3_x=(l*cos(P)*cos(Y))/2 - x - l/2 + (b*cos(P)*sin(Y))/2 AB3_y=w/2 - (b*(cos(R)*cos(Y) + sin(P)*sin(R)*sin(Y)))/2 + (l*(cos(R)*sin(Y) - cos(Y)*sin(P)*sin(R)))/2 AB3_z=(l*(sin(R)*sin(Y) + cos(R)*cos(Y)*sin(P)))/2 - (b*(cos(Y)*sin(R) - cos(R)*sin(P)*sin(Y)))/2 - Hc #腿4 AB4_x=(l*cos(P)*cos(Y))/2 - x - l/2 - (b*cos(P)*sin(Y))/2 AB4_y=(b*(cos(R)*cos(Y) + sin(P)*sin(R)*sin(Y)))/2 - w/2 + (l*(cos(R)*sin(Y) - cos(Y)*sin(P)*sin(R)))/2 AB4_z=(b*(cos(Y)*sin(R) - cos(R)*sin(P)*sin(Y)))/2 - Hc + (l*(sin(R)*sin(Y) + cos(R)*cos(Y)*sin(P)))/2 x1=ABl_x y1=ABl_z x2=AB2_x y2=AB2_z x3=AB4_x y3=AB4_z x4=AB3_x y4=AB3_z return x1,x2,x3,x4,y1,y2,y3,y4
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torchtools/tensors/tensor_group.py
cjwcommuny/torch-tools
0
22494
<reponame>cjwcommuny/torch-tools from typing import Dict, Tuple import torch from torch import Tensor from torchtools.tensors.function import unsqueeze class TensorGroup: def __init__(self, tensors: Dict[str, Tensor], check_validity: bool=True): self.tensors = tensors if check_validity: assert self.check_tensors_len(), "tensors don't has same length" def check_tensors_len(self) -> bool: return len(set(map(lambda x: len(x), self.tensors.values()))) == 1 @property def columns(self): return self.tensors.keys() def __len__(self): return len(next(iter(self.tensors.values()))) def __getitem__(self, item): if isinstance(item, str): return self.tensors[item] else: return TensorGroup( {key: tensor[item] for key, tensor in self.tensors.items()}, check_validity=False ) def __setitem__(self, key, value): if isinstance(key, str): self.tensors[key] = value else: for k in self.tensors.keys(): self.tensors[k][key] = value def min(self, input: str) -> Tuple['TensorGroup', Tensor]: indices = self.tensors[input].argmin(dim=0, keepdim=True) return ( TensorGroup( {key: tensor[indices] for key, tensor in self.tensors.items()}, check_validity=False ), indices ) def max(self, input: str) -> Tuple['TensorGroup', Tensor]: indices = self.tensors[input].argmax(dim=0, keepdim=True) return ( TensorGroup( {key: tensor[indices] for key, tensor in self.tensors.items()}, check_validity=False ), indices ) def sort(self, input: str, descending: bool=False) -> Tuple['TensorGroup', Tensor]: indices = self.tensors[input].argsort(dim=0, descending=descending) return ( TensorGroup( {key: tensor[indices] for key, tensor in self.tensors.items()}, check_validity=False ), indices ) def topk(self, input: str, k: int, largest: bool=True, sorted: bool=True) -> Tuple['TensorGroup', Tensor]: _, indices = self.tensors[input].topk(k, largest=largest, sorted=sorted) return ( TensorGroup( {key: tensor[indices] for key, tensor in self.tensors.items()}, check_validity=False ), indices ) @staticmethod def __mask_reshape_to_broadcast(tensor: Tensor, mask: Tensor) -> Tensor: result = unsqueeze(mask, dim=1, num=tensor.dim() - 1) print(f"mask.shape: {result.shape}") return result def masked_select(self, mask: Tensor) -> 'TensorGroup': assert mask.dim() == 1 print(f"mask: {mask.shape}") print(f"features: {self.tensors['features'].shape}") print(f"frame_id: {self.tensors['frame_id'].shape}") return TensorGroup( {key: tensor.masked_select(self.__mask_reshape_to_broadcast(tensor, mask)) for key, tensor in self.tensors.items()}, check_validity=False ) def index_select(self, indices: Tensor) -> 'TensorGroup': assert indices.dim() == 1 return self[indices] def lt_select(self, input: str, other) -> 'TensorGroup': """ NOTE: tensor.dim() must all be 1 """ mask = torch.lt(self.tensors[input], other) return self.masked_select(mask) def le_select(self, input: str, other) -> 'TensorGroup': """ NOTE: tensor.dim() must all be 1 """ mask = torch.le(self.tensors[input], other) return self.masked_select(mask) def gt_select(self, input: str, other) -> 'TensorGroup': """ NOTE: tensor.dim() must all be 1 """ mask = torch.gt(self.tensors[input], other) return self.masked_select(mask) def ge_select(self, input: str, other) -> 'TensorGroup': """ NOTE: tensor.dim() must all be 1 """ mask = torch.ge(self.tensors[input], other) return self.masked_select(mask) def ne_select(self, input: str, other) -> 'TensorGroup': """ NOTE: tensor.dim() must all be 1 """ mask = torch.ne(self.tensors[input], other) return self.masked_select(mask) def eq_select(self, input: str, other) -> 'TensorGroup': """ NOTE: tensor.dim() must all be 1 """ mask = torch.eq(self.tensors[input], other) return self.masked_select(mask)
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dbs/dal/Whiteport.py
xinghejd/opencanary_web
633
24609
#!/usr/bin/env python # -*- coding:utf-8 -*- """ Author: pirogue Purpose: 白名单端口表操作 Site: http://pirogue.org Created: 2018-08-03 17:32:54 """ from dbs.initdb import DBSession from dbs.models.Whiteport import Whiteport from sqlalchemy import desc,asc from sqlalchemy.exc import InvalidRequestError # import sys # sys.path.append("..") class WhitePort: """增删改查""" def __init__(self): self.session=DBSession # 查询白名单表port数据 def select_white_port(self): try: white_port_res = self.session.query(Whiteport.dst_port).all() return white_port_res except InvalidRequestError: self.session.rollback() except Exception as e: print(e) finally: self.session.close() # 增加白名单 def insert_white_port(self, dst_port): try: wip_insert = Whiteport(dst_port=dst_port) self.session.merge(wip_insert) self.session.commit() except InvalidRequestError: self.session.rollback() except Exception as e: print(e) finally: self.session.close() # 删除白名单端口表数据 def delete_white_port(self): try: self.session.query(Whiteport).delete() self.session.commit() except InvalidRequestError: self.session.rollback() except Exception as e: print(e) finally: self.session.close()
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examples/multi_client_example.py
ondewo/ondewo-csi-client-python
0
32971
<reponame>ondewo/ondewo-csi-client-python<filename>examples/multi_client_example.py #!/usr/bin/env python # coding: utf-8 # # Copyright 2021 ONDEWO GmbH # # 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 ondewo.nlu.agent_pb2 as agent import ondewo.s2t.speech_to_text_pb2 as s2t import ondewo.t2s.text_to_speech_pb2 as t2s from ondewo.nlu.client import Client as NluClient from ondewo.nlu.client_config import ClientConfig as NluClientConfig from ondewo.s2t.client.client import Client as S2tClient from ondewo.t2s.client.client import Client as T2sClient from ondewo.csi.client.client import Client as CsiClient from ondewo.csi.client.client_config import ClientConfig with open("csi.json") as fi: config = ClientConfig.from_json(fi.read()) with open("csi.json") as fi: nlu_config = NluClientConfig.from_json(fi.read()) csi_client = CsiClient(config=config) s2t_client = S2tClient(config=config) t2s_client = T2sClient(config=config) nlu_client = NluClient(config=nlu_config) s2t_pipelines = s2t_client.services.speech_to_text.list_s2t_pipelines(request=s2t.ListS2tPipelinesRequest()) t2s_pipelines = t2s_client.services.text_to_speech.list_t2s_pipelines(request=t2s.ListT2sPipelinesRequest()) print(f"Speech to text pipelines: {[pipeline.id for pipeline in s2t_pipelines.pipeline_configs]}") print(f"Text to speech pipelines: {[pipeline.id for pipeline in t2s_pipelines.pipelines]}") agents = nlu_client.services.agents.list_agents(request=agent.ListAgentsRequest()) print(f"Nlu agents: {[agent.agent.parent for agent in agents.agents_with_owners]}")
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audioroutines.py
jmcmellen/sameeas
17
70800
<reponame>jmcmellen/sameeas<filename>audioroutines.py import math, struct, random, array pi = math.pi def getFIRrectFilterCoeff(fc, sampRate, filterLen=20): 'Calculate FIR lowpass filter weights using hamming window' 'y(n) = w0 * x(n) + w1 * x(n-1) + ...' ft = float(fc) / sampRate #print ft m = float(filterLen - 1) weights = [] for n in range(filterLen): try: weight = math.sin( 2 * pi * ft * (n - (m / 2))) / (pi * (n - (m / 2))) hamming = 0.54 - 0.46 * math.cos( 2 * pi * n / m) weight = weight * hamming except: weight = 2 * ft hamming = 0.54 - 0.46 * math.cos( 2 * pi * n / m) weight = weight * hamming weights.append(weight) return weights def filterPCMaudio(fc, sampRate, filterLen, sampWidth, numCh, data): 'Run samples through a filter' samples = array.array('h', data) filtered = "" w = getFIRrectFilterCoeff(fc, sampRate, filterLen) for n in range(len(w), len(samples) - len(w)): acc = 0 for i in range(len(w)): acc += w[i] * samples[n - i] filtered += struct.pack('<h', int(math.floor(acc))) return filtered def recursiveFilterPCMaudio(fc, sampRate, sampWidth, numCh, data): 'Predefined filter values, Butterworth lowpass filter' a0 = 0.02008337 #0.01658193 a1 = 0.04016673 #0.03316386 a2 = a0 b1 = -1.56101808 #-1.60413018 b2 = 0.64135154 #0.67045791 samples = array.array('h', data) filtered = data[0:2] y = [0, 0, 0] for n in range(2, len(samples) - 2): sample = (a0 * samples[n] + a1 * samples[n -1] + a2 * samples[n-2] - b1 * y[1] - b2 * y[2]) y[2] = y[1] y[1] = sample filtered += struct.pack('<h', int(math.floor(sample))) return filtered def bpButterworthFilter6(fc, sampRate, sampWidth, numCh, data): a0 = 1 a1 = -4.16740087e+00 a2 = 9.56715918e+00 a3 = -1.52777374e+01 a4 = 1.88165959e+01 a5 = -1.84592133e+01 a6 = 1.46959044e+01 a7 = -9.50055587e+00 a8 = 4.97057565e+00 a9 = -2.04987349e+00 a10 = 6.42775774e-01 a11 = -1.38591530e-01 a12 = 1.72096260e-02 b0 = 3.36990647e-03 b1 = 0 b2 = -2.02194388e-02 b3 = 0 b4 = 5.05485971e-02 b5 = -2.15330343e-17 b6 = -6.73981294e-02 b7 = 2.15330343e-17 b8 = 5.05485971e-02 b9 = 0 b10 = -2.02194388e-02 b11 = 0 b12 = 3.36990647e-03 samples = array.array('h', data) print len(samples) filtered = data[0:12] y = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] for n in range(12, len(samples) - 12): sample = (a0 * samples[n] + a1 * samples[n -1] + a2 * samples[n-2] + a3 * samples[n-3] + a4 * samples[n-4] + a5 * samples[n-5] + a6 * samples[n-6] + a7 * samples[n-7] + a8 * samples[n-8] + a9 * samples[n-9] + a10 * samples[n-10] + a11 * samples[n-11] + a12 * samples[n-12] - b0 * y[0] - b1 * y[1] - b2 * y[2] - b3 * y[3] - b4 * y[4] - b5 * y[5] - b6 * y[6] - b7 * y[7] - b8 * y[8] - b9 * y[9] - b10 * y[10] - b11 * y[11] - b12 * y[12] ) y[12] = y[11] y[11] = y[10] y[10] = y[9] y[9] = y[8] y[8] = y[7] y[7] = y[6] y[6] = y[5] y[5] = y[4] y[4] = y[3] y[3] = y[2] y[2] = y[1] y[1] = sample filtered += struct.pack('<h', int(math.floor(sample))) return filtered def convertdbFStoInt( level, sampWidth): return math.pow(10, (float(level) / 20)) * 32767 def generateSimplePCMToneData(startfreq, endfreq, sampRate, duration, sampWidth, peakLevel, numCh): """Generate a string of binary data formatted as a PCM sample stream. Freq is in Hz, sampRate is in Samples per second, duration is in seconds, sampWidth is in bits, peakLevel is in dBFS, and numCh is either 1 or 2.""" phase = 0 * pi level = convertdbFStoInt(peakLevel, sampWidth) pcm_data = '' freq = startfreq slope = 0.5 * (endfreq - startfreq) / float(sampRate * duration) fade_len = int(0.001 * sampRate) * 0 numSamples = int( round( sampRate * duration)) #print duration * sampRate for i in range(0, numSamples): freq = slope * i + startfreq fade = 1.0 if i < fade_len: fade = 0.5 * (1 - math.cos(pi * i / (fade_len - 1))) elif i > (numSamples - fade_len): fade = 0.5 * (1 - math.cos(pi * (numSamples - i) / (fade_len - 1))) for ch in range(numCh): sample = int(( fade * level * math.sin( (freq * 2 * pi * i)/ sampRate + phase) )) #print sample pcm_data += struct.pack('<h', sample) return pcm_data def generateDualTonePCMData(freq1, freq2, sampRate, duration, sampWidth, peakLevel, numCh): """Generate a string of binary data formatted as a PCM sample stream. Mix two freq together such as in alert tones or DTMF""" phase = 0 * pi level = convertdbFStoInt(peakLevel, sampWidth) pcm_data = '' fade_len = int(0.001 * sampRate) * 0 numSamples = int( round( sampRate * duration)) #print duration * sampRate for i in range(0, numSamples): fade = 1.0 if i < fade_len: fade = 0.5 * (1 - math.cos(pi * i / (fade_len - 1))) elif i > (numSamples - fade_len): fade = 0.5 * (1 - math.cos(pi * (numSamples - i) / (fade_len - 1))) for ch in range(numCh): sample = int(( fade * level * (0.5 * math.sin( (freq1 * 2 * pi * i)/ sampRate + phase) + 0.5 * math.sin((freq2 * 2 * pi * i)/ sampRate + phase) ))) #print sample pcm_data += struct.pack('<h', sample) return pcm_data def main(): import wave numCh = 1 peakLevel = -10 sampWidth = 16 sampRate = 44100 file = wave.open('testchirp.wav', 'rb') samples = file.readframes( file.getnframes()) file.close() #data = generateDualTonePCMData(853, 960, sampRate, 8, sampWidth, peakLevel, numCh) data = bpButterworthFilter6(0, sampRate, sampWidth, numCh, samples) fileout = wave.open( 'test.wav', 'wb') fileout.setparams( (numCh, sampWidth/8, sampRate, sampRate, 'NONE', '') ) fileout.writeframes(data) fileout.close() if __name__ == "__main__": main()
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src/AoC_2021/d12_paths_through_caves_bfs_adjacency_dict_networkx/cave_navigating_graph_with_networkx_vis.py
derailed-dash/Advent-of-Code
9
156494
<filename>src/AoC_2021/d12_paths_through_caves_bfs_adjacency_dict_networkx/cave_navigating_graph_with_networkx_vis.py<gh_stars>1-10 r""" Author: Darren Date: 12/12/2021 Solving https://adventofcode.com/2021/day/12 We need to find all the paths through a network of caves, and then determine the best path. The cave map is provided in the form of connected pairs (edges). E.g. start-A start-b start A-c / \ A-b c--A-----b--d b-d \ / A-end end b-end Caves can be connected to 0, 1 or more other caves. Lowercase is for small caves. Uppercase is for large caves. Solution 2: Still using a BFS, but using NetworkX to build the graph. This saves on having to manually create the nodes or the adjacency dictionaries. Also allows easy visualisation. Part 1: We want to find the number of distinct paths from start to end, where we can visit small caves once, but other caves any number of times. We wanted an undirected unweighted graph, and then to find number of distinct paths from start to end, only visiting small caves (lowercase) 0 or 1 times. Create an adjacency dictionary, so we can get all neighbours of any cave. Determine which are small and which are large. To find all the unique paths, do a BFS. Store (start, path) in the queue. While items in the queue: - Pop (cave, path) - If the cave is the end, we've determined a valid route, so store it and continue. - Otherwise, get all the neighbours. - If the neighbour is new or big cave, update the path and append to the queue. - If not new, then if start/end/small, then skip. Part 2: Now we want to be able to visit a single small cave twice. Update the BFS so that the queue tuple also contains an attribute for whether we've "visited_twice" for any cave. Now, if the neighbour is in the path, and the neighbour is a small cave, and we haven't yet visited twice, then we can enqueue with visited twice option. """ import logging from pathlib import Path import time from collections import deque import matplotlib.pyplot as plt import networkx as nx logging.basicConfig(format="%(asctime)s.%(msecs)03d:%(levelname)s:%(name)s:\t%(message)s", datefmt='%H:%M:%S') logger = logging.getLogger(__name__) logger.setLevel(level=logging.INFO) SCRIPT_DIR = Path(__file__).parent INPUT_FILE = "input/input.txt" # INPUT_FILE = "input/sample_input.txt" RENDER = True OUTPUT_DIR = Path(SCRIPT_DIR / "output/") OUTPUT_FILE = Path(OUTPUT_DIR / "cave_graph.png") # where we'll save the animation to class CaveGraph(): """ Stores pairs of connected caves, i.e. edges. Determines all caves from supplied edges. Determines which caves are small, and which are large. Creates a lookup to obtain all caves linked to a given cave. Finally, knows how to determine all unique paths from start to end, according to the rules given. """ START = "start" END = "end" def __init__(self, edges:set[tuple[str, str]]) -> None: """ Takes a set of edges, where each edge is in the form (a, b) """ self.start = CaveGraph.START self.end = CaveGraph.END self._graph = nx.Graph() # Internal implementation of the graph self._graph.add_edges_from(edges) # Build the graph self._small_caves: set[str] = set() self._large_caves: set[str] = set() self._categorise_caves() # populate the empty fields assert self.start in self._graph, "Start needs to be mapped" assert self.end in self._graph, "Finish needs to be mapped" def _categorise_caves(self): """ Build a set of all caves from the edges. This will also initialise small_caves and large_caves """ for edge in self.edges: for cave in edge: if cave not in (self.start, self.end): if cave.islower(): self._small_caves.add(cave) else: self._large_caves.add(cave) def render(self, file): _ = plt.subplot(121) pos = nx.spring_layout(self._graph) # set colours for each node in the array, in the same order as the nodes colours = [] for node in self.nodes: if node in (CaveGraph.START, CaveGraph.END): colours.append("green") elif node in self.large_caves: colours.append("blue") else: colours.append("red") nx.draw(self._graph, pos=pos, node_color=colours, with_labels=True) dir_path = Path(file).parent if not Path.exists(dir_path): Path.mkdir(dir_path) plt.savefig(file) @property def edges(self) -> tuple[str,str]: """ All the edges. An edge is one cave linked to another. """ return self._graph.edges @property def nodes(self): return self._graph.nodes @property def small_caves(self): """ Caves labelled lowercase. Subset of self.caves. """ return self._small_caves @property def large_caves(self): """ Caves labelled uppercase. Subset of self.caves. """ return self._large_caves def get_paths_through(self, small_cave_twice=False) -> set[tuple]: """ Get all unique paths through from start to end, using a BFS. Args: small_cave_twice (bool, optional): Whether we can visit a small cave more than once. Defaults to False. """ start = (self.start, [self.start], False) # (starting cave, [path with only start], used twice) queue = deque() queue.append(start) unique_paths: set[tuple] = set() # To store each path that goes from start to end while queue: # If we popleft(), we do a BFS. If we simply pop(), we're doing a DFS. # Since we need to discover all paths, it makes no difference to performance. cave, path, used_twice = queue.popleft() # current cave, paths visited, twice? if cave == self.end: # we've reached the end of a desired path unique_paths.add(tuple(path)) continue for neighbour in self._graph[cave]: new_path = path + [neighbour] # Need a new path object if neighbour in path: # big caves fall through and can be re-added to the path if neighbour in (self.start, self.end): continue # we can't revisit start and finish if neighbour in self.small_caves: if small_cave_twice and not used_twice: # If we've visited this small cave once before # Then add it again, but "use up" our used_twice queue.append((neighbour, new_path, True)) continue assert neighbour in self.large_caves # If we're here, it's either big caves or neighbours not in the path queue.append((neighbour, new_path, used_twice)) logger.debug(new_path) return unique_paths def main(): input_file = Path(SCRIPT_DIR, INPUT_FILE) with open(input_file, mode="rt") as f: edges = set(tuple(line.split("-")) for line in f.read().splitlines()) graph = CaveGraph(edges) # Create graph from edges supplied in input logger.debug("Nodes=%s", graph.nodes) logger.debug("Edges=%s", graph.edges) if RENDER: graph.render(OUTPUT_FILE) # Part 1 unique_paths = graph.get_paths_through() logger.info("Part 1: unique paths count=%d", len(unique_paths)) # Part 2 unique_paths = graph.get_paths_through(small_cave_twice=True) logger.info("Part 2: unique paths count=%d", len(unique_paths)) if __name__ == "__main__": t1 = time.perf_counter() main() t2 = time.perf_counter() logger.info("Execution time: %0.4f seconds", t2 - t1)
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dustbin/py2app/.eggs/py2app-0.12-py2.7.egg/py2app/script_py2applet.py
orangeYao/twiOpinion
0
137678
""" Create an applet from a Python script. You can drag in packages, Info.plist files, icons, etc. It's expected that only one Python script is dragged in. """ from __future__ import print_function import os, sys from distutils.core import setup from plistlib import Plist import py2app import tempfile import shutil import imp import pprint from py2app.util import copy_tree from py2app import build_app try: set except NameError: from sets import Set as set if sys.version_info[0] == 3: raw_input = input HELP_TEXT = """ usage: py2applet --make-setup [options...] script.py [data files...] or: py2applet [options...] script.py [data files...] or: py2applet --help """ SETUP_TEMPLATE = '''""" This is a setup.py script generated by py2applet Usage: python setup.py py2app """ from setuptools import setup APP = %s DATA_FILES = %s OPTIONS = %s setup( app=APP, data_files=DATA_FILES, options={'py2app': OPTIONS}, setup_requires=['py2app'], ) ''' def get_option_map(): optmap = {} for option in build_app.py2app.user_options: opt_long, opt_short = option[:2] if opt_short: optmap['-' + opt_short] = opt_long.rstrip('=') return optmap def get_cmd_options(): options = set() for option in build_app.py2app.user_options: opt_long, opt_short = option[:2] if opt_long.endswith('=') and opt_short: options.add('-' + opt_short) return options def main(): if not sys.argv[1:]: print(HELP_TEXT) return scripts = [] data_files = [] packages = [] args = [] plist = {} iconfile = None parsing_options = True next_is_option = False cmd_options = get_cmd_options() is_make_setup = False for fn in sys.argv[1:]: if parsing_options: if next_is_option: args.append(fn) next_is_option = False continue elif fn == '--make-setup': is_make_setup = True continue elif fn.startswith('-'): args.append(fn) if fn in cmd_options: next_is_option = True continue parsing_options = False if not is_make_setup: fn = os.path.abspath(fn) if fn.endswith('.py'): if scripts: data_files.append(fn) else: scripts.append(fn) elif os.path.basename(fn) == 'Info.plist': plist = Plist.fromFile(fn) elif fn.endswith('.icns') and not iconfile: iconfile = os.path.abspath(fn) elif os.path.isdir(fn): sys.path.insert(0, [os.path.dirname(fn)]) try: path = imp.find_module(os.path.basename(fn))[0] except ImportError: path = '' del sys.path[0] if os.path.realpath(path) == os.path.realpath(fn): packages.append(os.path.basename(fn)) else: data_files.append(fn) else: data_files.append(fn) options = dict( packages=packages, plist=plist, iconfile=iconfile, ) for k,v in list(options.items()): if not v: del options[k] if is_make_setup: make_setup(args, scripts, data_files, options) else: build(args, scripts, data_files, options) def make_setup(args, scripts, data_files, options): optmap = get_option_map() cmd_options = get_cmd_options() while args: cmd = args.pop(0) if cmd in cmd_options: cmd = optmap[cmd] options[cmd.replace('-', '_')] = args.pop(0) elif '=' in cmd: cmd, val = cmd.split('=', 1) options[cmd.lstrip('-').replace('-', '_')] = val else: cmd = optmap.get(cmd, cmd) options[cmd.lstrip('-').replace('-', '_')] = True if os.path.exists('setup.py'): res = '' while res.lower() not in ('y', 'n'): res = raw_input('Existing setup.py detected, replace? [Y/n] ') if not res: break if res == 'n': print('aborted!') return f = open('setup.py', 'w') tvars = tuple(map(pprint.pformat, (scripts, data_files, options))) f.write(SETUP_TEMPLATE % tvars) f.flush() f.close() print('Wrote setup.py') def build(args, scripts, data_files, options): old_argv = sys.argv sys.argv = [sys.argv[0], 'py2app'] + args old_path = sys.path path_insert = set() for script in scripts: path_insert.add(os.path.dirname(script)) sys.path = list(path_insert) + old_path old_dir = os.getcwd() tempdir = tempfile.mkdtemp() os.chdir(tempdir) try: d = setup( app=scripts, data_files=data_files, options={'py2app': options}, ) for target in d.app: copy_tree( target.appdir, os.path.join( os.path.dirname(target.script), os.path.basename(target.appdir), ), preserve_symlinks=True, ) finally: os.chdir(old_dir) shutil.rmtree(tempdir, ignore_errors=True) sys.argv = old_argv sys.path = old_path if __name__ == '__main__': main()
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tests/test_bic.py
KayJay89/schwifty
0
71578
import pytest from schwifty import BIC def test_bic(): bic = BIC("GENODEM1GLS") assert bic.formatted == "GENO DE M1 GLS" assert bic.validate() def test_bic_allow_invalid(): bic = BIC("GENODXM1GLS", allow_invalid=True) assert bic assert bic.country_code == "DX" with pytest.raises(ValueError): bic.validate() def test_bic_no_branch_code(): bic = BIC("GENODEM1") assert bic.branch_code is None assert bic.formatted == "GENO DE M1" def test_bic_properties(): bic = BIC("GENODEM1GLS") assert bic.length == 11 assert bic.bank_code == "GENO" assert bic.country_code == "DE" assert bic.location_code == "M1" assert bic.branch_code == "GLS" assert bic.domestic_bank_codes == ["43060967", "43060988"] assert bic.bank_names == [ "GLS Gemeinschaftsbank", "GLS Gemeinschaftsbank (GAA)", ] assert bic.bank_short_names == [ "GLS Bank in Bochum (GAA)", "GLS Gemeinschaftsbk Bochum", ] with pytest.warns(DeprecationWarning): assert bic.bank_name == "GLS Gemeinschaftsbank" with pytest.warns(DeprecationWarning): assert bic.bank_short_name == "GLS Bank in Bochum (GAA)" assert bic.exists assert bic.type == "passive" def test_unknown_bic_properties(): bic = BIC("ABNAJPJTXXX") assert bic.length == 11 assert bic.bank_code == "ABNA" assert bic.country_code == "JP" assert bic.location_code == "JT" assert bic.branch_code == "XXX" assert bic.country_bank_code is None assert bic.domestic_bank_codes == [] assert bic.bank_name is None assert bic.bank_names == [] assert bic.bank_short_name is None assert bic.bank_short_names == [] assert not bic.exists assert bic.type == "default" @pytest.mark.parametrize( "code,type", [ ("GENODEM0GLS", "testing"), ("GENODEM1GLS", "passive"), ("GENODEM2GLS", "reverse billing"), ("GENODEMMGLS", "default"), ], ) def test_bic_type(code, type): bic = BIC(code) assert bic.type == type @pytest.mark.parametrize( "code", [ "AAAA", # Too short "AAAADEM1GLSX", # Too long "12ABDEM1GLS", # Wrong structure in banc-id "GENOD1M1GLS", # Wrong structure in country-code "GENOXXM1GLS", # Wrong country-code ], ) def test_invalid_bic(code): with pytest.raises(ValueError): BIC(code) def test_bic_from_bank_code(): bic = BIC.from_bank_code("DE", "43060967") assert bic.compact == "GENODEM1GLS" def test_bic_from_unknown_bank_code(): with pytest.raises(ValueError): BIC.from_bank_code("PO", "12345678") def test_bic_is_from_primary_bank_code(): bic = BIC.from_bank_code("DE", "20070024") assert bic.compact == "DEUTDEDBHAM" def test_magic_methods(): bic = BIC("GENODEM1GLS") assert bic == "GENODEM1GLS" assert bic == BIC("GENODEM1GLS") assert bic != BIC("GENODEMMXXX") assert bic != 12345 assert bic < "GENODEM1GLT" assert str(bic) == "GENODEM1GLS" assert hash(bic) == hash("GENODEM1GLS") assert repr(bic) == "<BIC=GENODEM1GLS>"
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tests/test_request_body.py
jaraco/aspen
1
131724
<filename>tests/test_request_body.py from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals from pytest import raises from aspen.http.request import Headers import aspen.body_parsers as parsers from aspen.exceptions import MalformedBody, UnknownBodyType FORMDATA = object() WWWFORM = object() def make_body(raw, headers=None, content_type=WWWFORM): if isinstance(raw, unicode): raw = raw.encode('ascii') if headers is None: defaults = { FORMDATA: "multipart/form-data; boundary=AaB03x", WWWFORM: "application/x-www-form-urlencoded" } headers = {"Content-Type": defaults.get(content_type, content_type)} if not 'content-length' in headers: headers['Content-length'] = str(len(raw)) body_parsers = { "application/json": parsers.jsondata, "application/x-www-form-urlencoded": parsers.formdata, "multipart/form-data": parsers.formdata } headers['Host'] = 'Blah' return parsers.parse_body(raw, Headers(headers), body_parsers) def test_body_is_unparsed_for_empty_content_type(): raw = "cheese=yes" raises(UnknownBodyType, make_body, raw, headers={}) def test_body_barely_works(): body = make_body("cheese=yes") actual = body['cheese'] assert actual == "yes" UPLOAD = """\ --AaB03x Content-Disposition: form-data; name="submit-name" Larry --AaB03x Content-Disposition: form-data; name="files"; filename="file1.txt" Content-Type: text/plain ... contents of file1.txt ... --AaB03x-- """ def test_body_barely_works_for_form_data(): body = make_body(UPLOAD, content_type=FORMDATA) actual = body['files'].filename assert actual == "file1.txt" def test_simple_values_are_simple(): body = make_body(UPLOAD, content_type=FORMDATA) actual = body['submit-name'] assert actual == "Larry" def test_multiple_values_are_multiple(): body = make_body("cheese=yes&cheese=burger") assert body.all('cheese') == ["yes", "burger"] def test_params_doesnt_break_www_form(): body = make_body("statement=foo" , content_type="application/x-www-form-urlencoded; charset=UTF-8; cheese=yummy" ) actual = body['statement'] assert actual == "foo" def test_malformed_body_jsondata(): with raises(MalformedBody): make_body("foo", content_type="application/json") def test_malformed_body_formdata(): with raises(MalformedBody): make_body("", content_type="multipart/form-data; boundary=\0")
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src/ppu.py
condector/pynes
2
190342
<filename>src/ppu.py import threading import multiprocessing import time from array import array from renderer import RendererManager class PPU: class VolatileMemory: def __init__(self, size): self.ram = array('B', [0x00] * size) def read(self, a=0x0): return self.ram[a] def write(self, a=0x0, v=0x0): self.ram[a] = v class VBlank: def __init__(self, console): self.status = False self._console = console def enter(self): if self._console.PPU.NMI: self._console.CPU.InterruptRequest = 0x4E # N self.status = True while True: try: self._console.PPU.renderer.display.blit() break except: pass def exit(self): self.status = False self._console.PPU.renderer.display.clear() def __init__(self, console=None): print("Initializing PPU...") self.console = console self.nameTableAddress = 0 self.incrementAddress = 1 self.spritePatternTable = 0 self.backgroundPatternTable = 0 self.spriteSize = 8 self.NMI = False self.colorMode = True self.clippingBackground = False self.clippingSprites = False self.showBackground = False self.showSprites = False self.colorIntensity = 0 self.spriteRamAddr = 0 self.vRamWrites = 0 self.scanlineSpriteCount = 0 self.sprite0Hit = 0 self.spriteHitOccured = False self.VRAMAddress = 0 self.VRAMBuffer = 0 self.firstWrite = True self.ppuScrollX = 0 self.ppuScrollY = 0 self.ppuStarted = 0 self.ppuMirroring = 0 self.addressMirroring = 0 self.colorPallete = [(0x75, 0x75, 0x75), (0x27, 0x1B, 0x8F), (0x00, 0x00, 0xAB), (0x47, 0x00, 0x9F), (0x8F, 0x00, 0x77), (0xAB, 0x00, 0x13), (0xA7, 0x00, 0x00), (0x7F, 0x0B, 0x00), (0x43, 0x2F, 0x00), (0x00, 0x47, 0x00), (0x00, 0x51, 0x00), (0x00, 0x3F, 0x17), (0x1B, 0x3F, 0x5F), (0x00, 0x00, 0x00), (0x00, 0x00, 0x00), (0x00, 0x00, 0x00), (0xBC, 0xBC, 0xBC), (0x00, 0x73, 0xEF), (0x23, 0x3B, 0xEF), (0x83, 0x00, 0xF3), (0xBF, 0x00, 0xBF), (0xE7, 0x00, 0x5B), (0xDB, 0x2B, 0x00), (0xCB, 0x4F, 0x0F), (0x8B, 0x73, 0x00), (0x00, 0x97, 0x00), (0x00, 0xAB, 0x00), (0x00, 0x93, 0x3B), (0x00, 0x83, 0x8B), (0x00, 0x00, 0x00), (0x00, 0x00, 0x00), (0x00, 0x00, 0x00), (0xFF, 0xFF, 0xFF), (0x3F, 0xBF, 0xFF), (0x5F, 0x97, 0xFF), (0xA7, 0x8B, 0xFD), (0xF7, 0x7B, 0xFF), (0xFF, 0x77, 0xB7), (0xFF, 0x77, 0x63), (0xFF, 0x9B, 0x3B), (0xF3, 0xBF, 0x3F), (0x83, 0xD3, 0x13), (0x4F, 0xDF, 0x4B), (0x58, 0xF8, 0x98), (0x00, 0xEB, 0xDB), (0x00, 0x00, 0x00), (0x00, 0x00, 0x00), (0x00, 0x00, 0x00), (0xFF, 0xFF, 0xFF), (0xAB, 0xE7, 0xFF), (0xC7, 0xD7, 0xFF), (0xD7, 0xCB, 0xFF), (0xFF, 0xC7, 0xFF), (0xFF, 0xC7, 0xDB), (0xFF, 0xBF, 0xB3), (0xFF, 0xDB, 0xAB), (0xFF, 0xE7, 0xA3), (0xE3, 0xFF, 0xA3), (0xAB, 0xF3, 0xBF), (0xB3, 0xFF, 0xCF), (0x9F, 0xFF, 0xF3), (0x00, 0x00, 0x00), (0x00, 0x00, 0x00), (0x00, 0x00, 0x00)] #try: self.renderer = RendererManager(self.console.RENDERER_TYPE) #except: # print ("Cannot initialize Renderer") self.VBLANK = self.VBlank(self.console) self.VRAM = self.VolatileMemory(0x10000) self.SPRRAM = self.VolatileMemory(0x100) self.load_vram_data() self.setMirroring(self.console.cartridge.mirror) super(PPU, self).__init__() def load_vram_data(self): maxdata = self.console.cartridge.chrRomData.__len__() k = 0 while k < maxdata: v = self.console.cartridge.chrRomData[k] self.VRAM.write(k, v) k += 1 self.renderer.display.reset() def setMirroring(self, mirroring): # 0 = horizontal mirroring # 1 = vertical mirroring self.ppuMirroring = mirroring self.addressMirroring = 0x400 << self.ppuMirroring def processControlReg1(self, value): # Check bits 0-1 aux = value & 0x3 if aux == 0: self.nameTableAddress = 0x2000 elif aux == 1: self.nameTableAddress = 0x2400 elif aux == 2: self.nameTableAddress = 0x2800 else: self.nameTableAddress = 0x2C00 # Check bit 2 if value & (1 << 2): self.incrementAddress = 32 else: self.incrementAddress = 1 # Check bit 3 if value & (1 << 3): self.spritePatternTable = 0x1000 else: self.spritePatternTable = 0x0000 # Check bit 4 if value & (1 << 4): self.backgroundPatternTable = 0x1000 else: self.backgroundPatternTable = 0x0000 # Check bit 5 if value & (1 << 5): self.spriteSize = 16 else: self.spriteSize = 8 # Bit 6 not used # Check bit 7 if value & (1 << 7): self.NMI = True else: self.NMI = False def processControlReg2(self, value): # Check bit 0 if value & 1: self.colorMode = True else: self.colorMode = False # Check bit 1 if value & (1 << 1): self.clippingBackground = True else: self.clippingBackground = False # Check bit 2 if value & (1 << 2): self.clippingSprites = True else: self.clippingSprites = False # Check bit 3 if value & (1 << 3): self.showBackground = True else: self.showBackground = False # Check bit 4 if value & (1 << 4): self.showSprites = True else: self.showSprites = False # Check bits 5-7 self.colorIntensity = value >> 5 # process register 0x2005 def processPPUSCROLL(self, value): if self.firstWrite: self.ppuScrollX = value self.firstWrite = False else: self.ppuScrollY = value self.firstWrite = True # process register 0x2006 def processPPUADDR(self, value): if self.firstWrite: self.VRAMAddress = (value & 0xFF) << 8 self.firstWrite = False else: self.VRAMAddress += (value & 0xFF) self.firstWrite = True # process register 0x2007 (write) def writeVRAM(self, value): #Todo: Verificar se esta certo # NameTable write mirroring. if self.VRAMAddress >= 0x2000 and self.VRAMAddress < 0x3F00: self.VRAM.write(self.VRAMAddress + self.addressMirroring, value) self.VRAM.write(self.VRAMAddress, value) # Color Pallete write mirroring. elif self.VRAMAddress >= 0x3F00 and self.VRAMAddress < 0x3F20: if self.VRAMAddress == 0x3F00 or self.VRAMAddress == 0x3F10: self.VRAM.write(0x3F00, value) self.VRAM.write(0x3F04, value) self.VRAM.write(0x3F08, value) self.VRAM.write(0x3F0C, value) self.VRAM.write(0x3F10, value) self.VRAM.write(0x3F14, value) self.VRAM.write(0x3F18, value) self.VRAM.write(0x3F1C, value) else: self.VRAM.write(self.VRAMAddress, value) self.VRAMAddress += self.incrementAddress # process register 0x2007 (read) def readVRAM(self): value = 0 address = self.VRAMAddress & 0x3FFF if address >= 0x3F00 and address < 0x4000: address = 0x3F00 + (address & 0xF) self.VRAMBuffer = self.VRAM.read(address) value = self.VRAM.read(address) elif address < 0x3F00: value = self.VRAMBuffer self.VRAMBuffer = self.VRAM.read(address) self.VRAMAddress += self.incrementAddress return value def writeSprRam(self, value): self.SPRRAM.write(self.spriteRamAddr,value) self.spriteRamAddr = (self.spriteRamAddr + 1) & 0xFF def writeSprRamDMA(self, value): address = value * 0x100 i = 0 while i < 256: self.SPRRAM.write(i, self.console.CPU.RAM.read(address)) address += 1 i += 1 def readStatusFlag(self): value = 0 value |= (self.vRamWrites << 4) value |= (self.scanlineSpriteCount << 5) value |= (self.sprite0Hit << 6) value |= (int(self.VBLANK.status) << 7) self.firstWrite = True self.VBLANK.exit() return value def doScanline(self): if self.showBackground: self.drawBackground(self.console.CPU.scanline) if self.showSprites: self.drawSprites(self.console.CPU.scanline) def drawBackground(self, scanline): tileY = int(scanline / 8) Y = int(scanline % 8) maxTiles = 32 if (self.ppuScrollX % 8) != 0: maxTiles = 33 currentTile = int(self.ppuScrollX / 8) v = int(self.nameTableAddress + currentTile) pixel = 0 first = 0 if self.clippingBackground else 1 tiles = array('B', list(range(first, maxTiles))) for i in tiles: fromByte = 0 toByte = 8 ppuScrollFlag = (self.ppuScrollX %8) if ppuScrollFlag != 0: if i == 0: toByte = 7 - (ppuScrollFlag) if i == (maxTiles - 1): fromByte = 8 - (ppuScrollFlag) ptrAddress = self.VRAM.read(v + int(tileY*0x20)) pattern1 = self.VRAM.read(self.backgroundPatternTable + (ptrAddress*16) + Y) pattern2 = self.VRAM.read(self.backgroundPatternTable + (ptrAddress*16) + Y + 8) # blockX e blockY sao as coordenadas em relacao ao block blockX = i % 4 blockY = tileY % 4 block = int(i / 4) + (int(tileY / 4) * 8) addressByte = int((v & ~0x001F) + 0x03C0 + block) byteAttributeTable = self.VRAM.read(addressByte) colorIndex = 0x3F00 if blockX < 2: if blockY >= 2: colorIndex |= ((byteAttributeTable & 0b110000) >> 4) << 2 else: colorIndex |= (byteAttributeTable & 0b11) << 2 elif blockX >= 2 and blockY < 2: colorIndex |= ((byteAttributeTable & 0b1100) >> 2) << 2 else: colorIndex |= ((byteAttributeTable & 0b11000000) >> 6) << 2 k = array('B', list(range(fromByte, toByte))) for j in k: bit1 = ((1 << j) & pattern1) >> j bit2 = ((1 << j) & pattern2) >> j colorIndexFinal = colorIndex colorIndexFinal |= ((bit2 << 1) | bit1) color = self.colorPallete[self.VRAM.read(colorIndexFinal)] x = (pixel + ((j * (-1)) + (toByte - fromByte) - 1)) y = scanline if (bytes(color) != self.renderer.display.LAYER_B.read(x, y)): self.renderer.display.LAYER_B.write(x, y, color) j += 1 pixel += toByte - fromByte if (v & 0x001f) == 31: v &= ~0x001F #v ^= self.addressMirroring v ^= 0x400 else: v += 1 del k del tiles def drawSprites(self, scanline): numberSpritesPerScanline = 0 Y = scanline % 8 secondaryOAM = array('B', [0xFF] * 32) indexSecondaryOAM = 0 k = array('B', list(range(0, 256, 4))) for currentSprite in k: spriteY = self.SPRRAM.read(currentSprite) if numberSpritesPerScanline == 8: break if spriteY <= scanline < spriteY + self.spriteSize: sprloop = array('B', list(range(4))) for i in sprloop: secondaryOAM[indexSecondaryOAM + i] = self.SPRRAM.read(currentSprite+i) indexSecondaryOAM += 4 numberSpritesPerScanline += 1 del sprloop del k k = array('B', list(range(28, -1, -4))) for currentSprite in k: spriteX = secondaryOAM[currentSprite + 3] spriteY = secondaryOAM[currentSprite] if spriteY >= 0xEF or spriteX >= 0xF9: continue currentSpriteAddress = currentSprite + 2 flipVertical = secondaryOAM[currentSpriteAddress] & 0x80 flipHorizontal = secondaryOAM[currentSpriteAddress] & 0x40 Y = scanline - spriteY ptrAddress = secondaryOAM[currentSprite + 1] patAddress = self.spritePatternTable + (ptrAddress * 16) + ((7 - Y) if flipVertical else Y) pattern1 = self.VRAM.read(patAddress) pattern2 = self.VRAM.read(patAddress + 8) colorIndex = 0x3F10 colorIndex |= ((secondaryOAM[currentSprite +2] & 0x3) << 2) sprloop = array('B', range(8)) for j in sprloop: if flipHorizontal: colorIndexFinal = (pattern1 >> j) & 0x1 colorIndexFinal |= ((pattern2 >> j) & 0x1 ) << 1 else: colorIndexFinal = (pattern1 >> (7 - j)) & 0x1 colorIndexFinal |= ((pattern2 >> (7 - j)) & 0x1) << 1 colorIndexFinal += colorIndex if (colorIndexFinal % 4) == 0: colorIndexFinal = 0x3F00 color = self.colorPallete[(self.VRAM.read(colorIndexFinal) & 0x3F)] # Add Transparency if color == self.colorPallete[self.VRAM.read(0x3F10)]: color += (0,) self.renderer.display.LAYER_A.write(spriteX + j, spriteY + Y, color) checkColor=self.renderer.display.LAYER_A.read(spriteX + j, spriteY + Y) if self.showBackground and not(self.spriteHitOccured) and currentSprite == 0 and checkColor == bytes(color): self.sprite0Hit = True self.spriteHitOccured = True del sprloop del k def run(self): print("PPU OK") if self.console.THREAD_MODE == "SINGLE": pass else: self.console.CPU = self.console.CPU while True: self.console.CPU.end.wait() self.console.CPU.end.clear() print(self.console.CPU.scanline) self.renderer.display.blit() self.console.CPU.scanline = 0
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example/front_end_validator_example/views.py
johnfraney/django-front-end-validators
18
1606067
from django.views.generic import CreateView from .forms import SampleModelForm from .models import SampleModel class SampleModelCreate(CreateView): model = SampleModel form_class = SampleModelForm
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src/yellowdog_client/common/server_sent_events/sse4python/chained_thread.py
yellowdog/yellowdog-sdk-python-public
0
105562
<gh_stars>0 from threading import Thread class ChainedThread(Thread): def __init__(self, callback, target): # NOSONAR super(ChainedThread, self).__init__() self.__target = target self.__callback = callback def run(self): try: res = self.__target() finally: del self.__target self.__callback(res)
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forum/migrations/0001_initial.py
michaelyou/One-piece-forum
1
70801
# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations import django.contrib.auth.models import django.utils.timezone from django.conf import settings import django.core.validators import forum.models class Migration(migrations.Migration): dependencies = [ ('auth', '0006_require_contenttypes_0002'), ] operations = [ migrations.CreateModel( name='ForumUser', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('password', models.CharField(max_length=128, verbose_name='password')), ('last_login', models.DateTimeField(null=True, verbose_name='last login', blank=True)), ('is_superuser', models.BooleanField(default=False, help_text='Designates that this user has all permissions without explicitly assigning them.', verbose_name='superuser status')), ('username', models.CharField(error_messages={'unique': 'A user with that username already exists.'}, max_length=30, validators=[django.core.validators.RegexValidator('^[\\w.@+-]+$', 'Enter a valid username. This value may contain only letters, numbers and @/./+/-/_ characters.', 'invalid')], help_text='Required. 30 characters or fewer. Letters, digits and @/./+/-/_ only.', unique=True, verbose_name='username')), ('first_name', models.CharField(max_length=30, verbose_name='first name', blank=True)), ('last_name', models.CharField(max_length=30, verbose_name='last name', blank=True)), ('email', models.EmailField(max_length=254, verbose_name='email address', blank=True)), ('is_staff', models.BooleanField(default=False, help_text='Designates whether the user can log into this admin site.', verbose_name='staff status')), ('is_active', models.BooleanField(default=True, help_text='Designates whether this user should be treated as active. Unselect this instead of deleting accounts.', verbose_name='active')), ('date_joined', models.DateTimeField(default=django.utils.timezone.now, verbose_name='date joined')), ('nickname', models.CharField(max_length=200, null=True, blank=True)), ('avatar', models.CharField(max_length=200, null=True, blank=True)), ('signature', models.CharField(max_length=500, null=True, blank=True)), ('location', models.CharField(max_length=200, null=True, blank=True)), ('website', models.URLField(null=True, blank=True)), ('company', models.CharField(max_length=200, null=True, blank=True)), ('role', models.IntegerField(null=True, blank=True)), ('balance', models.IntegerField(null=True, blank=True)), ('reputation', models.IntegerField(null=True, blank=True)), ('self_intro', models.CharField(max_length=500, null=True, blank=True)), ('updated', models.DateTimeField(null=True, blank=True)), ('twitter', models.CharField(max_length=200, null=True, blank=True)), ('github', models.CharField(max_length=200, null=True, blank=True)), ('douban', models.CharField(max_length=200, null=True, blank=True)), ('groups', models.ManyToManyField(related_query_name='user', related_name='user_set', to='auth.Group', blank=True, help_text='The groups this user belongs to. A user will get all permissions granted to each of their groups.', verbose_name='groups')), ('user_permissions', models.ManyToManyField(related_query_name='user', related_name='user_set', to='auth.Permission', blank=True, help_text='Specific permissions for this user.', verbose_name='user permissions')), ], options={ 'abstract': False, 'verbose_name': 'user', 'verbose_name_plural': 'users', }, managers=[ ('objects', django.contrib.auth.models.UserManager()), ], ), migrations.CreateModel( name='Favorite', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('involved_type', models.IntegerField(null=True, blank=True)), ('created', models.DateTimeField(null=True, blank=True)), ], ), migrations.CreateModel( name='Node', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('name', models.CharField(max_length=200, null=True, blank=True)), ('slug', models.SlugField(max_length=200, null=True, blank=True)), ('thumb', models.CharField(max_length=200, null=True, blank=True)), ('introduction', models.CharField(max_length=500, null=True, blank=True)), ('created', models.DateTimeField(null=True, blank=True)), ('updated', models.DateTimeField(null=True, blank=True)), ('topic_count', models.IntegerField(null=True, blank=True)), ('custom_style', forum.models.NormalTextField(null=True, blank=True)), ('limit_reputation', models.IntegerField(null=True, blank=True)), ], ), migrations.CreateModel( name='Notification', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('content', forum.models.NormalTextField(null=True, blank=True)), ('status', models.IntegerField(null=True, blank=True)), ('involved_type', models.IntegerField(null=True, blank=True)), ('occurrence_time', models.DateTimeField(null=True, blank=True)), ], ), migrations.CreateModel( name='Plane', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('name', models.CharField(max_length=200, null=True, blank=True)), ('created', models.DateTimeField(null=True, blank=True)), ('updated', models.DateTimeField(null=True, blank=True)), ], ), migrations.CreateModel( name='Reply', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('content', forum.models.NormalTextField(null=True, blank=True)), ('created', models.DateTimeField(null=True, blank=True)), ('updated', models.DateTimeField(null=True, blank=True)), ('up_vote', models.IntegerField(null=True, blank=True)), ('down_vote', models.IntegerField(null=True, blank=True)), ('last_touched', models.DateTimeField(null=True, blank=True)), ('author', models.ForeignKey(related_name='reply_author', blank=True, to=settings.AUTH_USER_MODEL, null=True)), ], ), migrations.CreateModel( name='Topic', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('title', models.CharField(max_length=200, null=True, blank=True)), ('slug', models.SlugField(max_length=200, null=True, blank=True)), ('content', forum.models.NormalTextField(null=True, blank=True)), ('status', models.IntegerField(null=True, blank=True)), ('hits', models.IntegerField(null=True, blank=True)), ('created', models.DateTimeField(null=True, blank=True)), ('updated', models.DateTimeField(null=True, blank=True)), ('reply_count', models.IntegerField(null=True, blank=True)), ('last_replied_time', models.DateTimeField(null=True, blank=True)), ('up_vote', models.IntegerField(null=True, blank=True)), ('down_vote', models.IntegerField(null=True, blank=True)), ('last_touched', models.DateTimeField(null=True, blank=True)), ('author', models.ForeignKey(related_name='topic_author', blank=True, to=settings.AUTH_USER_MODEL, null=True)), ('last_replied_by', models.ForeignKey(related_name='topic_last', blank=True, to=settings.AUTH_USER_MODEL, null=True)), ('node', models.ForeignKey(blank=True, to='forum.Node', null=True)), ], ), migrations.CreateModel( name='Transaction', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('type', models.IntegerField(null=True, blank=True)), ('reward', models.IntegerField(null=True, blank=True)), ('current_balance', models.IntegerField(null=True, blank=True)), ('occurrence_time', models.DateTimeField(null=True, blank=True)), ('involved_reply', models.ForeignKey(related_name='trans_reply', blank=True, to='forum.Reply', null=True)), ('involved_topic', models.ForeignKey(related_name='trans_topic', blank=True, to='forum.Topic', null=True)), ('involved_user', models.ForeignKey(related_name='trans_involved', blank=True, to=settings.AUTH_USER_MODEL, null=True)), ('user', models.ForeignKey(related_name='trans_user', blank=True, to=settings.AUTH_USER_MODEL, null=True)), ], ), migrations.CreateModel( name='Vote', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('status', models.IntegerField(null=True, blank=True)), ('involved_type', models.IntegerField(null=True, blank=True)), ('occurrence_time', models.DateTimeField(null=True, blank=True)), ('involved_reply', models.ForeignKey(related_name='vote_reply', blank=True, to='forum.Reply', null=True)), ('involved_topic', models.ForeignKey(related_name='vote_topic', blank=True, to='forum.Topic', null=True)), ('involved_user', models.ForeignKey(related_name='vote_user', blank=True, to=settings.AUTH_USER_MODEL, null=True)), ('trigger_user', models.ForeignKey(related_name='vote_trigger', blank=True, to=settings.AUTH_USER_MODEL, null=True)), ], ), migrations.AddField( model_name='reply', name='topic', field=models.ForeignKey(blank=True, to='forum.Topic', null=True), ), migrations.AddField( model_name='notification', name='involved_reply', field=models.ForeignKey(related_name='notify_reply', blank=True, to='forum.Reply', null=True), ), migrations.AddField( model_name='notification', name='involved_topic', field=models.ForeignKey(related_name='notify_topic', blank=True, to='forum.Topic', null=True), ), migrations.AddField( model_name='notification', name='involved_user', field=models.ForeignKey(related_name='notify_user', blank=True, to=settings.AUTH_USER_MODEL, null=True), ), migrations.AddField( model_name='notification', name='trigger_user', field=models.ForeignKey(related_name='notify_trigger', blank=True, to=settings.AUTH_USER_MODEL, null=True), ), migrations.AddField( model_name='node', name='plane', field=models.ForeignKey(blank=True, to='forum.Plane', null=True), ), migrations.AddField( model_name='favorite', name='involved_reply', field=models.ForeignKey(related_name='fav_reply', blank=True, to='forum.Reply', null=True), ), migrations.AddField( model_name='favorite', name='involved_topic', field=models.ForeignKey(related_name='fav_topic', blank=True, to='forum.Topic', null=True), ), migrations.AddField( model_name='favorite', name='owner_user', field=models.ForeignKey(related_name='fav_user', blank=True, to=settings.AUTH_USER_MODEL, null=True), ), ]
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edge-tool/cbor_converter.py
hckim-kornic/mbed-edge-kornic
0
16902
#!/usr/bin/env python # ---------------------------------------------------------------------------- # Copyright 2018 ARM Ltd. # # SPDX-License-Identifier: Apache-2.0 # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ---------------------------------------------------------------------------- import os import cbor2 import struct from pyclibrary import CParser from collections import namedtuple CERTIFICATE_KEYS = ('MBED_CLOUD_DEV_BOOTSTRAP_DEVICE_CERTIFICATE', 'MBED_CLOUD_DEV_BOOTSTRAP_SERVER_ROOT_CA_CERTIFICATE', 'arm_uc_default_certificate') KEY_KEYS = ('MBED_CLOUD_DEV_BOOTSTRAP_DEVICE_PRIVATE_KEY') UPDATE_KEYS = ('arm_uc_default_certificate', 'arm_uc_class_id', 'arm_uc_vendor_id') KEY_MAP = { 'MBED_CLOUD_DEV_BOOTSTRAP_DEVICE_CERTIFICATE': 'mbed.BootstrapDeviceCert', 'MBED_CLOUD_DEV_BOOTSTRAP_SERVER_ROOT_CA_CERTIFICATE': 'mbed.BootstrapServerCACert', 'MBED_CLOUD_DEV_BOOTSTRAP_DEVICE_PRIVATE_KEY': 'mbed.BootstrapDevicePrivateKey', 'MBED_CLOUD_DEV_BOOTSTRAP_ENDPOINT_NAME': 'mbed.EndpointName', 'MBED_CLOUD_DEV_BOOTSTRAP_SERVER_URI': 'mbed.BootstrapServerURI', 'MBED_CLOUD_DEV_ACCOUNT_ID': 'mbed.AccountID', 'MBED_CLOUD_DEV_MANUFACTURER': 'mbed.Manufacturer', 'MBED_CLOUD_DEV_MODEL_NUMBER': 'mbed.ModelNumber', 'MBED_CLOUD_DEV_SERIAL_NUMBER': 'mbed.SerialNumber', 'MBED_CLOUD_DEV_DEVICE_TYPE': 'mbed.DeviceType', 'MBED_CLOUD_DEV_HARDWARE_VERSION': 'mbed.HardwareVersion', 'MBED_CLOUD_DEV_MEMORY_TOTAL_KB': 'mbed.MemoryTotalKB', 'arm_uc_default_certificate': 'mbed.UpdateAuthCert', 'arm_uc_class_id': 'mbed.ClassId', 'arm_uc_vendor_id': 'mbed.VendorId' } ConfigParam = namedtuple('ConfigParam', ['Data', 'Name']) Certificate = namedtuple('Certificate', ['Data', 'Format', 'Name']) Key = namedtuple('Key', ['Data', 'Format', 'Name', 'Type']) class CBORConverter(): def __init__(self, development_certificate, update_resource, cbor_file): self.development_certificate = development_certificate self.update_resource = update_resource self.cbor_file = cbor_file def __check_file_exists(self, path): if not os.path.isfile(path): print("File '%s' does not exist.") return False return True def parse_c_file(self): if not self.__check_file_exists(self.development_certificate) or \ not self.__check_file_exists(self.update_resource): return None values = {} values.update(CParser([self.development_certificate]).defs.get('values')) values.update(CParser([self.update_resource], macros={ 'MBED_CLOUD_DEV_UPDATE_ID' : 1, 'MBED_CLOUD_DEV_UPDATE_CERT' : 1 }).defs.get('values')) return values def create_cbor_data(self, vars): cbor_data = {'Certificates': [], 'Keys' : [], 'ConfigParams': [], 'SchemeVersion': '0.0.1'} use_bootstrap = 1 if 'MBED_CLOUD_DEV_BOOTSTRAP_SERVER_URI' in vars.keys() else 0 cbor_data['ConfigParams'].append(ConfigParam(use_bootstrap, 'mbed.UseBootstrap')._asdict()) for key in vars.keys(): var = vars.get(key) cbor_var_key = KEY_MAP.get(key, None) if cbor_var_key: if key in CERTIFICATE_KEYS: byte_data = struct.pack('%sB' % len(var), *var); certificate = Certificate(byte_data, 'der', cbor_var_key)._asdict() cbor_data['Certificates'].append(certificate) elif key in KEY_KEYS: byte_data = struct.pack('%sB' % len(var), *var); private_key = Key(byte_data, 'der', cbor_var_key, 'ECCPrivate')._asdict() cbor_data['Keys'].append(private_key) elif key in UPDATE_KEYS: byte_data = struct.pack('%sB' % len(var), *var) config_param = ConfigParam(byte_data, cbor_var_key)._asdict() cbor_data['ConfigParams'].append(config_param) else: config_param = ConfigParam(var, cbor_var_key)._asdict() cbor_data['ConfigParams'].append(config_param) else: print("Key %s not in KEY_MAP." % key) return cbor_data def convert_to_cbor(self): vars = self.parse_c_file() if not vars: print("No variables parsed.") else: cbor_data = self.create_cbor_data(vars) with open(self.cbor_file, 'wb') as out_file: cbor2.dump(cbor_data, out_file)
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distributed/deploy/adaptive_core.py
arpit1997/distributed
0
70888
<reponame>arpit1997/distributed import collections import math from tornado.ioloop import IOLoop import toolz from ..metrics import time from ..utils import parse_timedelta, PeriodicCallback class AdaptiveCore: """ The core logic for adaptive deployments, with none of the cluster details This class controls our adaptive scaling behavior. It is intended to be sued as a super-class or mixin. It expects the following state and methods: **State** plan: set A set of workers that we think should exist. Here and below worker is just a token, often an address or name string requested: set A set of workers that the cluster class has successfully requested from the resource manager. We expect that resource manager to work to make these exist. observed: set A set of workers that have successfully checked in with the scheduler These sets are not necessarily equivalent. Often plan and requested will be very similar (requesting is usually fast) but there may be a large delay between requested and observed (often resource managers don't give us what we want). **Functions** target : -> int Returns the target number of workers that should exist. This is often obtained by querying the scheduler workers_to_close : int -> Set[worker] Given a target number of workers, returns a set of workers that we should close when we're scaling down scale_up : int -> None Scales the cluster up to a target number of workers, presumably changing at least ``plan`` and hopefully eventually also ``requested`` scale_down : Set[worker] -> None Closes the provided set of workers Parameters ---------- minimum: int The minimum number of allowed workers maximum: int The maximum number of allowed workers wait_count: int The number of scale-down requests we should receive before actually scaling down interval: str The amount of time, like ``"1s"`` between checks """ def __init__( self, minimum: int = 0, maximum: int = math.inf, wait_count: int = 3, interval: str = "1s", ): self.minimum = minimum self.maximum = maximum self.wait_count = wait_count self.interval = parse_timedelta(interval, "seconds") if interval else interval self.periodic_callback = None def f(): self.periodic_callback = PeriodicCallback(self.adapt, self.interval * 1000) self.periodic_callback.start() if self.interval: try: self.loop.add_callback(f) except AttributeError: IOLoop.current().add_callback(f) try: self.plan = set() self.requested = set() self.observed = set() except Exception: pass # internal state self.close_counts = collections.defaultdict(int) self._adapting = False self.log = collections.deque(maxlen=10000) def stop(self): if self.periodic_callback: self.periodic_callback.stop() self.periodic_callback = None async def target(self) -> int: """ The target number of workers that should exist """ raise NotImplementedError() async def workers_to_close(self, target: int) -> list: """ Give a list of workers to close that brings us down to target workers """ # TODO, improve me with something that thinks about current load return list(self.observed)[target:] async def safe_target(self) -> int: """ Used internally, like target, but respects minimum/maximum """ n = await self.target() if n > self.maximum: n = self.maximum if n < self.minimum: n = self.minimum return n async def recommendations(self, target: int) -> dict: """ Make scale up/down recommendations based on current state and target """ plan = self.plan requested = self.requested observed = self.observed if target == len(plan): self.close_counts.clear() return {"status": "same"} elif target > len(plan): self.close_counts.clear() return {"status": "up", "n": target} elif target < len(plan): not_yet_arrived = requested - observed to_close = set() if not_yet_arrived: to_close.update((toolz.take(len(plan) - target, not_yet_arrived))) if target < len(plan) - len(to_close): L = await self.workers_to_close(target=target) to_close.update(L) firmly_close = set() for w in to_close: self.close_counts[w] += 1 if self.close_counts[w] >= self.wait_count: firmly_close.add(w) for k in list(self.close_counts): # clear out unseen keys if k in firmly_close or k not in to_close: del self.close_counts[k] if firmly_close: return {"status": "down", "workers": list(firmly_close)} else: return {"status": "same"} async def adapt(self) -> None: """ Check the current state, make recommendations, call scale This is the main event of the system """ if self._adapting: # Semaphore to avoid overlapping adapt calls return self._adapting = True try: target = await self.safe_target() recommendations = await self.recommendations(target) if recommendations["status"] != "same": self.log.append((time(), dict(recommendations))) status = recommendations.pop("status") if status == "same": return if status == "up": await self.scale_up(**recommendations) if status == "down": await self.scale_down(**recommendations) except OSError: self.stop() finally: self._adapting = False
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data_management/data.py
School-courses/covid19-forecast
0
95780
import os from functools import reduce import numpy as np import pandas as pd from sklearn.preprocessing import minmax_scale, scale class Data(): def __init__(self, no_hist_days, no_hist_weeks, target_label, root_dir="", begin_test_date=None, scale_data=None): data_daily = os.path.join(root_dir, "data/slovenia_daily.csv") data_weekly = os.path.join(root_dir, "data/slovenia_weekly.csv") self.df_daily = pd.read_csv(data_daily) self.df_weekly = pd.read_csv(data_weekly) self.df_daily['date'] = pd.to_datetime(self.df_daily['date']) self.df_weekly['date'] = pd.to_datetime(self.df_weekly['date']) self.target_label = target_label self.no_hist_days = no_hist_days self.no_hist_weeks = no_hist_weeks self.begin_test_date = begin_test_date self.scale_data = scale_data self.predictors_col_names = [] self.df_data_table = self._create_data_table() def _create_base_table(self): """ Create base table filled with daily values, target value and date""" list_hist_vals = [] for timestamp in self.df_weekly['date']: end_date = timestamp - pd.DateOffset(6) # 6 day (1 week) offset for week prediction start_date = end_date - pd.DateOffset(self.no_hist_days) mask_dates = (self.df_daily["date"] > start_date) & (self.df_daily["date"] <= end_date) predictors = self.df_daily[mask_dates].loc[:, self.target_label].to_numpy() list_hist_vals.append(predictors) bool_hist_vals = [len(hist_vals) == self.no_hist_days for hist_vals in list_hist_vals] num = len(list_hist_vals) - sum(bool_hist_vals) # remove num instances which are not equal to self.no_hist_vals target_df = self.df_weekly[self.target_label].loc[num:].reset_index(drop=True).to_frame("target") date_target_df = self.df_weekly["date"].loc[num:].reset_index(drop=True).to_frame() col_names = [f"d_{idx}" for idx in reversed(range(1, len(list_hist_vals[num])+1))] predictors_df = pd.DataFrame(list_hist_vals[num:], columns=col_names) self.predictors_col_names.extend(col_names) df_base_table = pd.concat([date_target_df, target_df, predictors_df], axis=1) return df_base_table def _create_weekly_table(self, df_base_table): """ Create table with weekly values""" list_hist_vals = [] for timestamp in df_base_table['date']: end_date = timestamp - pd.DateOffset(weeks=1) # 1 week offset for prediction start_date = end_date - pd.DateOffset(weeks=self.no_hist_weeks) mask_dates = (self.df_weekly["date"] > start_date) & (self.df_weekly["date"] <= end_date) predictors = self.df_weekly[mask_dates].loc[:, self.target_label].to_numpy() list_hist_vals.append(predictors) bool_hist_vals = [len(hist_vals) == self.no_hist_weeks for hist_vals in list_hist_vals] num = len(list_hist_vals) - sum(bool_hist_vals) date_target_df = df_base_table["date"].loc[num:].reset_index(drop=True).to_frame() col_names = [f"w_{idx}" for idx in reversed(range(1, len(list_hist_vals[num])+1))] predictors_df = pd.DataFrame(list_hist_vals[num:], columns=col_names) self.predictors_col_names.extend(col_names) df_weekly_table = pd.concat([date_target_df, predictors_df], axis=1) return df_weekly_table def _create_other_table(self): """ Create table with additional informations""" df_other = self.df_weekly.copy() df_other = df_other.drop(columns=["week", "new_cases", "new_deaths"]) df_other["date"] = df_other["date"].shift(-1) # predictions from last week df_other = df_other[:-1] col_names = df_other.drop(columns=["date"]).columns.to_list() self.predictors_col_names.extend(col_names) return df_other def _create_data_table(self): base_table = self._create_base_table() weekly_table = self._create_weekly_table(base_table) other_table = self._create_other_table() dfs = [base_table, weekly_table, other_table] data_table = reduce(lambda left, right: pd.merge(left, right, how="inner", on="date"), dfs) data_table = self._scale_data_table(data_table) return data_table def _scale_data_table(self, data_table): if self.scale_data == "scale": data_table[self.predictors_col_names] = scale(data_table[self.predictors_col_names]) elif self.scale_data == "minmax": data_table[self.predictors_col_names] = minmax_scale(data_table[self.predictors_col_names]) return data_table def get_data(self, save=False): if save: self.df_data_table.to_csv("data/data_table.csv", index=False) def convert_to_numpy(df): X = df.reindex(columns = self.predictors_col_names).to_numpy() y = df.loc[:, "target"].to_numpy() y = np.expand_dims(y, axis = 1) return X, y df_train = self.df_data_table[self.df_data_table["date"] < self.begin_test_date] df_test = self.df_data_table[self.df_data_table["date"] >= self.begin_test_date] X_train, y_train = convert_to_numpy(df_train) X_test, y_test = convert_to_numpy(df_test) return X_train, y_train, X_test, y_test if __name__ == "__main__": from skmultiflow.data import DataStream, RegressionGenerator target_label = "new_cases" no_hist_days = 0 no_hist_weeks = 2 begin_test_date = "2021-11-06" scale_data = None data = Data( no_hist_days=no_hist_days, no_hist_weeks=no_hist_weeks, target_label=target_label, begin_test_date=begin_test_date, scale_data=scale_data ) X_train, y_train, X_test_t, y_test_t = data.get_data() stream = DataStream(X_test_t, y_test_t)
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apps/accounts/conf.py
sotkonstantinidis/testcircle
3
192258
from django.conf import settings # noqa from appconf import AppConf class AccountConf(AppConf): """ Custom settings for the account module. Mainly settings required for the login on the remote system. """ PID = 3 LOGIN_TYPE = 'login' LOGIN_SUCCESS_URL = 'home' # The name of the UNCCD role as provided by the remote system. UNCCD_ROLE_NAME = 'UNCCD Focal Point'
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libs/raw_image.py
guatek/Dual-Mag-Data
0
172404
<filename>libs/raw_image.py # -*- coding: utf-8 -*- import os import cv2 import json import struct import datetime import numpy as np from tifffile import TiffWriter from psutil import virtual_memory from loguru import logger __author__ = "<NAME>" __copyright__ = "Copyright 2020 Guatek" __credits__ = ["Guatek"] __license__ = "MIT" __maintainer__ = "<NAME>" __email__ = "<EMAIL>" __doc__ = ''' Handle loading and exporting raw bin files from pcam-like cameras @author: __author__ @status: __status__ @license: __license__ ''' class RawImage: """Load, process and export raw bin files """ def __init__(self, filepath, output_path=None): self.filepath = filepath self.output_path = output_path self.file_header_format = '<iiQiQQ' self.file_header_params = [ 'file_type', 'frames_per_file', 'bits_per_pixel', 'pixel_format', 'image_width', 'image_height' ] self.frame_header_format = '<QQQQ' self.frame_header_params = [ 'marker', 'frame_id', 'frame_timestamp', 'system_timestamp', ] # exports self.tiff_exports = [] self.jpeg_exports = [] self.thumbnail_exports = [] self.image_items = [] self.can_do_ram = False self.file_fmt = 0 self.file_header_length = 36 self.frame_header_size = 32 self.file_header = None self.frame_headers = [] self.frame_data = [] self.field_correction = None self.background = None # actual image width and height with raw size and binning self.img_width = 0 self.img_height = 0 # Try to open the file and read try: self.file_handle = open(self.filepath, "rb") self.file_valid = True self.file_size = os.path.getsize(self.filepath) self.file_valid = self.file_size > 0 except FileNotFoundError as e: logger.error(e) self.file_valid = False if not self.file_valid: logger.error("Zero size file.") return # read the file header and set image sizes accordingly self.read_file_header() # check if we can load all frames into RAM self.ram_available = virtual_memory().available # Get the number of frames in the file self.frames_in_file = int((self.file_size - self.file_header_length) / self.frame_size_in_bytes()) logger.info('Found ' + str(self.frames_in_file) + ' frames in ' + self.filepath) def unpack(self, format_string, names, raw_data): output = {} if not self.file_valid: return try: logger.debug("Unpacking data in format: " + format_string) logger.debug("Expected header size in bytes: " + str(struct.calcsize(format_string))) data = struct.unpack(format_string, raw_data) for ind, d in enumerate(data): output[names[ind]] = d except struct.error as e: logger.error(e) return output def correct_flat_field(self, data): if not self.file_valid: return if self.field_correction is None: logger.info("Estimating flat field correction from images") data_array = None for i in range(0, self.frames_in_file): header, raw_data = self.read_frame(i) if data_array is None: data_array = np.zeros((data.shape[0],data.shape[1],self.frames_in_file)) data_array[:,:,i] = raw_data self.field_correction = np.median(data_array, 2) self.field_correction[self.field_correction < 1] = 1 self.field_correction = self.field_correction.astype('float') / np.min(self.field_correction) # remove color from the correction h, w = self.field_correction.shape self.field_correction = cv2.resize(self.field_correction, (int(w/2), int(h/2)), interpolation=cv2.INTER_AREA) self.field_correction = cv2.resize(self.field_correction, (w, h), interpolation=cv2.INTER_LINEAR) self.background = np.median(data_array, 2) / self.field_correction # apply the correction data = data / self.field_correction data = data - self.background data[data<0.0] = 0.0 if self.bpp == 2: data = data.astype('uint16') else: data = data.astype('uint8') return data def export_8bit_jpegs(self, output_path=None, bayer_pattern=cv2.COLOR_BayerRG2RGB, flat_field=True, gamma=1.0, thumbnails=True): if not self.file_valid: return file_info = {} file_info['file_header'] = self.file_header file_info['frame_headers'] = [] self.jpeg_exports = [] self.thumbnail_exports = [] for i in range(0, self.frames_in_file): image_item = {} header, data = self.read_frame(i) if flat_field: data = self.correct_flat_field(data) if bayer_pattern: logger.debug("Converting color...") data = cv2.cvtColor(data,bayer_pattern) # RGB needed to get RGB format in opencv # Clip any negative values if self.bpp == 2: data = data/256/256 else: data = data/256 data = data**(gamma) data=data*255 data[data>255] = 255 data = np.uint8(data) filename = os.path.basename(self.filepath)[:-4] + '-' + str(header['frame_id']) + '-' + str(header['system_timestamp']) +'.jpeg' if thumbnails: thumbnail_name = os.path.basename(self.filepath)[:-4] + '-' + str(header['frame_id']) + '-' + str(header['system_timestamp']) +'_thumb.jpeg' timestamp = int(header['system_timestamp']/1000000) subdir = str(int(timestamp/864)) if output_path is None: if self.output_path is None: output_path = os.path.dirname(self.filepath) output_subdir = os.path.join(os.path.dirname(self.filepath), subdir) else: output_path = self.output_path output_subdir = os.path.join(self.output_path, subdir) else: output_subdir = os.path.join(output_path, subdir) if not os.path.exists(output_subdir): try: os.makedirs(output_subdir) except FileExistsError as e: logger.warning(e) pass jpeg_path = os.path.join(output_subdir, filename) self.jpeg_exports.append(jpeg_path) cv2.imwrite(jpeg_path, data) image_item['src'] = os.path.basename(os.path.normpath(output_path)) + '/' + subdir + '/' + filename image_item['fullWidth'] = data.shape[1] image_item['fullHeight'] = data.shape[0] timestamp = datetime.datetime.fromtimestamp(float(header['system_timestamp'])/1000000) image_item['timestring'] = timestamp.isoformat() if thumbnails: thumbnail_size = (int(data.shape[1]/10), int(data.shape[0]/10)) jpeg_thumbnail_path = os.path.join(output_subdir, thumbnail_name) cv2.imwrite(jpeg_thumbnail_path, cv2.resize(data, thumbnail_size, interpolation=cv2.INTER_LINEAR)) self.thumbnail_exports.append(jpeg_thumbnail_path) image_item['thumbnailWidth'] = thumbnail_size[0] image_item['thumbnailHeight'] = thumbnail_size[1] image_item['thumbnail'] = os.path.basename(os.path.normpath(output_path)) + '/' + subdir + '/' + thumbnail_name else: image_item['thumbnailWidth'] = 0 image_item['thumbnailHeight'] = 0 image_item['thumbnail'] = '' self.image_items.append(image_item) def export_as_tiff(self, output_path=None, bayer_pattern=cv2.COLOR_BayerRG2BGR, flat_field=True): if not self.file_valid: return file_info = {} file_info['file_header'] = self.file_header file_info['frame_headers'] = [] self.tiff_exports = [] if output_path is None: if self.output_path is None: tiff_path = self.filepath[:-4] + '.tif' json_path = self.filepath[:-4] + '.json' else: tiff_path = os.path.join(self.output_path, os.path.basename(self.filepath)[:-4] + '.tif') json_path = os.path.join(self.output_path, os.path.basename(self.filepath)[:-4] + '.json') else: tiff_path = os.path.join(output_path, os.path.basename(self.filepath)[:-4]) + '.tif' json_path = os.path.join(output_path, os.path.basename(self.filepath)[:-4]) + '.json' self.tiff_exports.append(tiff_path) logger.info("Exporting headers to " + json_path) logger.info("Exporting frames to " + tiff_path) with TiffWriter(tiff_path, append=True) as tif: for i in range(0, self.frames_in_file): header, data = self.read_frame(i) if flat_field: data = self.correct_flat_field(data) if bayer_pattern: logger.debug("Converting color...") data = cv2.cvtColor(data,bayer_pattern) # BGR needed to get RGB format in TiffWriter timestamp = float(header['system_timestamp']) dt = datetime.datetime.fromtimestamp(timestamp/1000000.0) file_info['frame_headers'].append(header) frame_header_string = json.dumps(header) xtag = (65000, 's', 0, frame_header_string, False) tif.save( data, description=json.dumps(file_info), datetime=dt, extratags=[xtag] ) with open(json_path, "w") as f: json.dump(file_info, f, indent=4, sort_keys=True) def read_file_header(self): if self.file_valid: # read the rest of the header self.file_handle.seek(0) res = self.file_handle.read(self.file_header_length) logger.debug("Read file header of length: " + str(self.file_header_length)) self.file_header = self.unpack(self.file_header_format, self.file_header_params, res) self.file_fmt = self.file_header['file_type'] self.img_height = int(self.file_header['image_height']) self.img_width = int(self.file_header['image_width']) self.bpp = int(self.file_header['bits_per_pixel'] / 8) # in bytes-per-pixel from bits-per-pixel logger.debug(self.file_header) def frame_size_in_bytes(self): if self.file_valid: return self.frame_header_size + self.bpp * self.img_width * self.img_height else: return 0 def frame_pixels(self): if self.file_valid: return self.img_width*self.img_height else: return 0 def read_frame(self, index): if not self.file_valid: return frame_offset = self.file_header_length + index * self.frame_size_in_bytes() frame_pixels = self.frame_pixels() if self.file_valid: # seek to the start of the frame self.file_handle.seek(frame_offset, 0) # read the header frame_header = self.unpack( self.frame_header_format, self.frame_header_params, self.file_handle.read(self.frame_header_size) ) # read the frame pixels if self.bpp == 1: res = np.fromfile(self.file_handle, dtype='uint8', count=frame_pixels) else: res = np.fromfile(self.file_handle, dtype='uint16', count=frame_pixels) if len(res) <= 0: logger.error('Error reading frame ' + str(index) + " from file " + self.filepath) return None else: # reshape into image image = np.reshape(res, (self.img_height, self.img_width)) return frame_header, image
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GUI.py
wtarimo/CFCScorePredictor
0
44723
""" <NAME> COSI 157 - Final Project: CFC Score Predictor This module manages instances of games 11/11/2012 """ from Game import * def userInputBox(win): """Creates and diplays graphical fields for user signing and registration""" Text(Point(55,50), "Full Name:").draw(win) rName = Entry(Point(245,50),30); rName.draw(win) Text(Point(55,75), "Username:").draw(win) rUsername = Entry(Point(200,75),20); rUsername.draw(win) Text(Point(56,100), "Password:").draw(win) rPassword1 = Entry(Point(200,100),20); rPassword1.draw(win) Text(Point(56,125), "Password:").draw(win) rPassword2 = Entry(Point(200,125),20); rPassword2.draw(win) Text(Point(55,225), "Username:").draw(win) lUsername = Entry(Point(200,225),20); lUsername.draw(win) Text(Point(56,250), "Password:").draw(win) lPassword = Entry(Point(200,250),20); lPassword.draw(win) rButton = Buttons(win,Point(230,160),120,25,"REGISTER"); rButton.Activate() lButton = Buttons(win,Point(230,285),120,25,"LOGIN"); lButton.Activate() def fixtureInputBox(win): """Creates and diplays graphical fields for fixture input""" Text(Point(113,50), "Game #:").draw(win) fgame = Entry(Point(240,50),20); fgame.draw(win) Text(Point(103,75), "Opponent:").draw(win) fopponent = Entry(Point(240,75),20); fopponent.draw(win) Text(Point(118,100), "Time:").draw(win) ftime = Entry(Point(240,100),20); ftime.draw(win) Text(Point(116,125), "Venue:").draw(win) fvenue = Entry(Point(240,125),20); fvenue.draw(win) Text(Point(116,150), "Result:").draw(win) fresult = Entry(Point(240,150),20); fresult.draw(win) Text(Point(100,175), "cfcScorers:").draw(win) fcfcScorers = Entry(Point(240,175),20); fcfcScorers.draw(win) Text(Point(75,200), "OppositionScorers:").draw(win) foppositionScorers = Entry(Point(240,200),20); foppositionScorers.draw(win) submitFButton = Buttons(win,Point(230,235),150,25,"SUBMIT FIXTURE"); submitFButton.Activate() Text(Point(113,300), "Game #:").draw(win) ugame = Entry(Point(240,300),20); ugame.draw(win) Text(Point(116,325), "Result:").draw(win) uresult = Entry(Point(240,325),20); uresult.draw(win) Text(Point(100,350), "cfcScorers:").draw(win) ucfcScorers = Entry(Point(240,350),20); ucfcScorers.draw(win) Text(Point(75,375), "OppositionScorers:").draw(win) uoppositionScorers = Entry(Point(240,375),20); uoppositionScorers.draw(win) updateFButton = Buttons(win,Point(230,415),150,25,"UPDATE RESULTS"); updateFButton.Activate() def predictionInputBox(win): """Creates and diplays graphical fields for prediction input""" Text(Point(111,50), "Game #:").draw(win) game = Entry(Point(240,50),20); game.draw(win) Text(Point(116,80), "Result:").draw(win) result = Entry(Point(240,80),20); result.draw(win) Text(Point(107,110), "Scoreline:").draw(win) scoreline = Entry(Point(240,110),20); scoreline.draw(win) Text(Point(100,140), "cfcScorers:").draw(win) cfcScorers = Entry(Point(240,140),20); cfcScorers.draw(win) Text(Point(75,170), "OppositionScorers:").draw(win) oppositionScorers = Entry(Point(240,170),20); oppositionScorers.draw(win) submitRButton = Buttons(win,Point(230,235),170,25,"SUBMIT RESULT"); submitRButton.Activate() def displayStandings(win,standings): """Displays the game standings on user points""" text = Text(Point(725,40),"GAME STANDINGS"); text.setFill('grey'); text.setStyle('bold');text.setSize(20); text.draw(win) #standings = registry.getStandings() if len(standings)>10: standings=standings[:10] Text(Point(700,70), " _________Name:__________ _Points:_ _Accuracy:_").draw(win) (x,y) = (600,95) for i in range(3): y = 95 x = [600,780,850][i] for record in standings: Text(Point(x,y),record[i]).draw(win) y+=20 def displaySchedule(win,fixtures,game): """Displays the schedule for the 5 recent fixtures by game #""" text = Text(Point(730,325),"FIXTURE SCHEDULE"); text.setFill('grey'); text.setStyle('bold');text.setSize(20); text.draw(win) #fixtures = schedule.fixtures if len(fixtures)>5: fixtures = fixtures[:5] fixtures = [[str(f.game),f.opponent.split()[0],f.time,str(f.result),str(f.cfcScorers),str(f.oppositionScorers)] for f in fixtures] Text(Point(710,350), "Game#: __Opponent:__ ____Time:____ _Result_ _cfcScorers_ _oppScorers_").draw(win) (x,y) = (470,375) for i in range(6): y = 375 x = [465,545,665,755,830,940][i] for record in fixtures: text = Text(Point(x,y),record[i]) if i==0 and int(record[0])>game: text = Text(Point(x,y),record[0]+" Future") elif i==0 and int(record[0])==game: text = Text(Point(x,y),record[0]+" Next") elif i==0 and int(record[0])<game: text = Text(Point(x,y),record[0]+" Played") text.setFill('blue') if int(record[0])>game else text.setFill('red') if int(record[0])==game: text.setFill('green4') text.setSize(10); text.draw(win) y+=20 def displayPredictions(win,pDB,username,game): """Diplays predictions sumbmitted by the user""" text = Text(Point(730,505),"YOUR PREDICTIONS"); text.setFill('grey'); text.setStyle('bold');text.setSize(20); text.draw(win) predictions = pDB.getPredictions(username) if len(predictions)>5: predictions = predictions[:5] predictions = [[str(p.game),str(p.result),str(p.scoreline),str(p.cfcScorers),str(p.oppositionScorers),str(p.points)] for p in predictions] Text(Point(700,530), "_Game#:_ _Result:_ _Scoreline:_ _cfcScorers_ _oppScorers_ _Points:_").draw(win) for i in range(6): y = 555 x = [475,550,640,740,830,920][i] for record in predictions: text = Text(Point(x,y),record[i]) text.setFill('blue') if int(record[0])>game else text.setFill('red') if int(record[0])==game: text.setFill('green4') text.setSize(11); text.draw(win) y+=20 def displayOutput(win,text): """Displays info to the user at the bottom left windows""" text = text.split(",") x,y = 215,485 for record in text: text = Text(Point(x,y),record); text.setFill('grey2') text.setSize(11); text.draw(win) y+=25
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