How to use test_background method in pytest-bdd

Best Python code snippet using pytest-bdd_python

eval_frames.py

Source:eval_frames.py

1#!/usr/bin/env python32# -*- coding: utf-8 -*-3from gensim.models import Word2Vec, KeyedVectors4import argparse5from parse_frames import do_counts, words_to_pmi, seeds_to_real_lex, get_words_to_cut6from data_iters import FrameAnnotationsIter, BackgroundIter, get_sentence_level_test, load_json_as_list, load_codes, get_random_split, code_to_short_form, get_per_frame_split, FrameHardSoftIter7import os8from collections import Counter, defaultdict9import pickle10from random import shuffle11import operator12from scipy import spatial13import glob14from params import Params15from nltk.corpus import stopwords16stop_words = stopwords.words('english')17stop_words.append("''")18stop_words.append('``')19stop_words.append('--')20stop_words.append("'s")21stop_words.append("n't")22stop_words.append("said")23import string24def get_top_words(input_file):25    dir_name = os.path.basename(os.path.dirname(os.path.dirname(input_file)))26    base_name = os.path.join("cache", dir_name + ".counter")27    if (os.path.isfile(base_name)):28        return pickle.load(open(base_name, "rb"))29    c = Counter()30    num_articles = 031    article_counter = Counter()32    for words in BackgroundIter(glob.iglob(input_file), sent_level=False):33        c.update(words)34        num_articles += 135        article_counter.update(set(words))36    pickle.dump((c, num_articles, article_counter), open(base_name, "wb"))37    return c, num_articles, article_counter38# Theory that some frames we model better than others because they are less relavent to39# test text. Count how frequent each frame is in input text40def count_frames(code_to_str, frame_iter):41    frame_counter = Counter()42    text_count = 043    for text,frames,_ in frame_iter:44        for frame in frames:45            frame_counter[frame] += 146        text_count += 147    for f in sorted(frame_counter):48        print(code_to_str[f], ";", frame_counter[f])49# NEW WAY -- train on top of NYT model50def get_wv_nyt_name(input_file, split_type, params):51    if split_type == "random" or split_type == 'kfold' or split_type == 'dcard' or split_type == 'dcard_tune':52        base_name = params.ENGLISH_MFC_MODEL53    else:54        base_name = os.path.join("cache", split_type + ".nyt.model")55    nyt_model = params.ENGLISH_BASE_MODEL56    if (os.path.isfile(base_name)):57        return base_name58    sentence_iter = BackgroundIter(glob.iglob(input_file), verbose=False)59    base_model = Word2Vec.load(nyt_model)60    count = 061    for x in sentence_iter:62      count += 163    base_model.train(sentence_iter, total_examples=count, epochs=base_model.epochs)64    fp = open(base_name, "wb")65    base_model.wv.save(fp)66    fp.close()67    return base_name68class frameTracker():69  def __init__(self):70    self.correct_positive = 071    self.marked_positive = 072    self.true_positive = 073    self.marked_correct = 074  def get_metrics(self, total):75    # return precision, recall, accuracy76    return self.correct_positive / max(float(self.marked_positive), 0.0001), \77           self.correct_positive / float(self.true_positive),   \78           self.marked_correct / float(total)79def test_primary_frame(code_to_lex, code_to_str, text_iter, do_print = True):80    total = 081    correct = 082    del code_to_lex[15.0] # Don't guess Other83    for text,_,true_frame in text_iter:84        if true_frame == "null" or true_frame is None:85            continue86        total += 187        text_counter = Counter(text)88        sums = []89        for f in code_to_lex:90            sums.append((f, sum([text_counter[w] for w in code_to_lex[f]])))91        # we shuffle so that ties are randomly broken92        shuffle(sums)93        frame, word_count = max(sums, key=operator.itemgetter(1))94        # Mark as "Other" if it doesn't belong to any other frame95        if word_count < 4:96            frame = 15.097        if frame == true_frame:98            correct += 199    if do_print:100        print (float(correct) / float(total), total)101    return float(correct) / float(total)102# Find center of a set of vectors (unnormalized)103# by summing the vectors104def get_center(words, wv):105    embed_size = 0106    for w in words:107        if not w in wv:108            continue109        embed_size = len(wv[w])110        break111    center = [0 for i in range(0, embed_size)]112    for w in words:113        if not w in wv:114            continue115        center = [x+y for x,y in zip(center, wv[w])]116    return center117# First find center of context_words vectors, then return similarity between keyword and center118def get_mean_similarity(keywords, context_words, wv):119    context_center = get_center(context_words, wv)120    keywords_center = get_center(keywords, wv)121    return 1 - spatial.distance.cosine(context_center, keywords_center)122def test_primary_frame_wv(code_to_lex, code_to_str, text_iter, wv):123    total = 0124    correct = 0125    for text,_,true_frame in text_iter:126        if true_frame == "null" or true_frame is None:127            continue128        total += 1129        sums = []130        for f in code_to_lex:131            sums.append((f, get_mean_similarity(text, code_to_lex[f], wv)))132        # we shuffle so that ties are randomly broken133        shuffle(sums)134        frame, word_count = max(sums, key=operator.itemgetter(1))135        if frame == true_frame:136            correct += 1137    print (float(correct) / float(total), total)138def max_index(l):139    index, value = max(enumerate(l), key=operator.itemgetter(1))140    return str(index)141def test_sentence_annotations(code_to_lex, code_to_str, frame_to_contains, frame_to_doesnt):142    for f in sorted(code_to_lex):143        frame_tracker = frameTracker()144        total = 0145        for contains in frame_to_contains[f]:146            total += 1147            frame_tracker.true_positive += 1148            text_counter = Counter(contains)149            applies_frame = sum([text_counter[w] for w in code_to_lex[f]]) >= 1150            if applies_frame:151                frame_tracker.marked_correct += 1152                frame_tracker.marked_positive += 1153                frame_tracker.correct_positive += 1154        for doesnt in frame_to_doesnt[f]:155            total += 1156            text_counter = Counter(doesnt)157            applies_frame = sum([text_counter[w] for w in code_to_lex[f]]) >= 1158            if applies_frame:159                frame_tracker.marked_positive += 1160            else:161                frame_tracker.marked_correct += 1162        assert (frame_tracker.true_positive == len(frame_to_contains[f]))163        assert (total == len(frame_to_contains[f]) + len(frame_to_doesnt[f]))164        p,r,a = frame_tracker.get_metrics(total)165        if (p + r) == 0:166            print(code_to_str[f], "VERY BAD")167            continue168        print (code_to_str[f], ";",169           p, ";",170           r, ";",171           (2 * (p * r)/(p + r)), ";",172           a, ";")173def test_annotations(code_to_lex, code_to_str, frame_iter, lex_count=3, do_print=True):174  code_to_frame_tracker = {}175  for c in code_to_lex:176    code_to_frame_tracker[c] = frameTracker()177  total = 0178  for text,frames,_ in frame_iter:179    total += 1180    text_counter = Counter(text)181    for c in code_to_lex:182      applies_frame = (sum([text_counter[w] for w in code_to_lex[c]]) >= lex_count)183      gold_applies_frame = (c in frames)184      if applies_frame == gold_applies_frame:185        code_to_frame_tracker[c].marked_correct += 1186      if applies_frame:187        code_to_frame_tracker[c].marked_positive += 1188        if gold_applies_frame:189          code_to_frame_tracker[c].correct_positive += 1190      if gold_applies_frame:191        code_to_frame_tracker[c].true_positive += 1192  code_to_f1 = {}193  average_f1 = 0194  for c in sorted(code_to_frame_tracker):195    p,r,a = code_to_frame_tracker[c].get_metrics(total)196    if (p + r) == 0:197      code_to_f1[c] = 0198      continue199    code_to_f1[c] = (2 * (p * r)/(p + r))200    if do_print:201        print (code_to_str[c], ";",202               p, ";",203               r, ";",204               (2 * (p * r)/(p + r)), ";",205               a, ";")206        if code_to_str[c] == "Other":207            continue208        average_f1 += (2 * (p * r)/(p + r))209  if do_print:210      print ("AVERAGE", average_f1 / (len(code_to_frame_tracker) - 1))211  return code_to_f1212def test_hard_annotations(code_to_lex, code_to_str, frame_iter, lex_count=3):213  code_to_frame_tracker = {}214  for c in code_to_lex:215    code_to_frame_tracker[c] = frameTracker()216  total = 0217  for text,frame_to_all, frame_to_any in frame_iter:218    total += 1219    text_counter = Counter(text)220    for c in code_to_lex:221      applies_frame = (sum([text_counter[w] for w in code_to_lex[c]]) >= lex_count)222      # Check hard, it's only in doc if all annotators think it's in doc223      gold_applies_frame = frame_to_all[c]224      if applies_frame == gold_applies_frame:225        code_to_frame_tracker[c].marked_correct += 1226      if applies_frame:227        code_to_frame_tracker[c].marked_positive += 1228        if gold_applies_frame:229          code_to_frame_tracker[c].correct_positive += 1230      if gold_applies_frame:231        code_to_frame_tracker[c].true_positive += 1232  for c in sorted(code_to_frame_tracker):233    p,r,a = code_to_frame_tracker[c].get_metrics(total)234    if (p + r) == 0:235      print ("VERB BAD")236      return237    print (code_to_str[c], ";",238           p, ";",239           r, ";",240           (2 * (p * r)/(p + r)), ";",241           a, ";")242def get_data_split(split_type, params, frame = None):243  immigration = os.path.join(params.MFC_PATH, "immigration.json")244  tobacco = os.path.join(params.MFC_PATH, "tobacco.json")245  samsex = os.path.join(params.MFC_PATH, "samesex.json")246  full_background = os.path.join(params.MFC_RAW_PATH, "*/json/*.json")247  if split_type == 'tobacco':248      train_files = [immigration, samesex]249      test_files = tobacco250      test_background = os.path.join(params.MFC_RAW_PATH, "smoking/json/*.json")251  elif split_type == 'immigration':252      train_files = [tobacco, samesex]253      test_files = immigration254      test_background = os.path.join(params.MFC_RAW_PATH, "immigration/json/*.json")255  elif split_type == 'samesex':256      train_files = [tobacco, immigration]257      test_files = samesex258      test_background = os.path.join(params.MFC_RAW_PATH, "samesex/json/*.json")259  elif split_type == 'kfold':260      train_files = [tobacco, immigration, samesex]261      test_background = full_background262      assert(frame is not None)263      test_data, train_data = get_per_frame_split(train_files, frame)264      return train_data, test_data, test_background265  elif split_type == 'dcard':266      train_files = [immigration]267      test_background = full_background268      test_data, train_data = get_random_split(train_files, num_folds=10, filter_tone=True)269      return train_data, test_data, test_background270  elif split_type == 'dcard_tune':271      train_files = [immigration]272      test_background = full_background273      test_data, train_data = get_random_split(train_files, num_folds=50, filter_tone=True)274      return train_data, test_data, test_background275  else:276      assert (split_type == "random")277      # train_files = [tobacco, immigration, samesex]278      train_files = [immigration]279      test_background = full_background280      test_data, train_data = get_random_split(train_files)281      return train_data, test_data, test_background282  train_data = load_json_as_list(train_files)283  test_data = load_json_as_list([test_files])284  return train_data, test_data, test_background285def count_all_frames():286    immigration = os.path.join(params.MFC_PATH, "immigration.json")287    tobacco = os.path.join(params.MFC_PATH, "tobacco.json")288    samsex = os.path.join(params.MFC_PATH, "samesex.json")289    codes = os.path.join(params.MFC_PATH, "codes.json")290    train_files = [immigration, tobacco, samesex]291    code_to_str = load_codes(codes)292    train_data = load_json_as_list(train_files)293    doc_level_iter = FrameAnnotationsIter(train_data)294    count_frames(code_to_str, doc_level_iter)295def do_all(args, train_data, test_data, test_background, code_to_str, params, target_frame = None, do_print = True):296    wv_name = get_wv_nyt_name(test_background, args.split_type, params)297    corpus_counter, code_to_counter, word_to_article_count, total_article_count = do_counts(train_data)298    # Sometimes (kfold) we only care about 1 frame299    if target_frame is not None:300        code_to_counter = {f:code_to_counter[f] for f in [target_frame]}301    # cut infrequent words302    cut_words = get_words_to_cut(total_article_count, word_to_article_count, params.MIN_CUT, params.MAX_CUT)303    corpus_counter = Counter({c:corpus_counter[c] for c in corpus_counter if not c in cut_words})304    # calculate PMI305    corpus_count = sum([corpus_counter[k] for k in corpus_counter])306    code_to_lex = {}307    all_frames = set()308    for c in code_to_counter:309        if "primary" in code_to_str[c] or "headline" in code_to_str[c] or "primany" in code_to_str[c]:310            continue311        all_frames.add(c)312        # For the baseline, we just take 100 most frequent words313        if args.baseline:314            # remove stopwords315            code_to_counter[c] = Counter({w:code_to_counter[c][w] for w in code_to_counter[c] if w in corpus_counter and not w in stop_words and not w in string.punctuation})316            code_to_lex[c] = [q[0] for q in code_to_counter[c].most_common(100)]317        else:318            code_to_lex[c] = words_to_pmi(corpus_counter, corpus_count, code_to_counter[c], params.TO_RETURN_COUNT)319            # # Use same seeds as baseline320            # code_to_counter[c] = Counter({w:code_to_counter[c][w] for w in code_to_counter[c] if w in corpus_counter and not w in stop_words and not w in string.punctuation})321            # code_to_lex[c] = [q[0] for q in code_to_counter[c].most_common(100)]322    if do_print:323        print("*******************************************************************************")324        for c in code_to_lex:325            print (code_to_str[c], code_to_lex[c])326        print("*******************************************************************************")327        print("*******************************************************************************")328    top_words, num_articles, article_counter = get_top_words(test_background)329    vocab = sorted(top_words, key=top_words.get, reverse = True)[:params.VOCAB_SIZE]330    if args.baseline:331      code_to_new_lex = code_to_lex332    else:333      code_to_new_lex = {}334      for c in code_to_lex:335         code_to_new_lex[c] = seeds_to_real_lex(code_to_lex[c], wv_name, vocab, code_to_str[c], topn=params.VEC_SEARCH, threshold=params.SIM_THRESH)336#         code_to_new_lex[c] = code_to_lex[c] # Test no query expansions. This guy is pretty good337    # filter again, this time off of target corpus cause that's what we have to do in Russian338    words_to_cut = get_words_to_cut(num_articles, article_counter, params.MIN_CUT, params.MAX_CUT)339    for c in code_to_new_lex:340        code_to_new_lex[c] = [w for w in code_to_new_lex[c] if not w in words_to_cut]341    # make data iters342    doc_level_iter = FrameAnnotationsIter(test_data)343    short_codes = set([code_to_short_form(code) for code in code_to_str])344    hard_iter = FrameHardSoftIter(test_data, short_codes)345    # sentence level tests346    frame_to_contains, frame_to_doesnt = get_sentence_level_test(test_data, all_frames)347    # just return everything348    if not do_print:349        return code_to_new_lex, doc_level_iter350    for x in code_to_new_lex:351        print (code_to_str[x])352        print (code_to_new_lex[x])353    # print("*******************************************************************************")354    # print("Frame Counts;")355    # count_frames(code_to_str, doc_level_iter)356    print("*******************************************************************************")357    print("DOC")358    test_annotations(code_to_new_lex, code_to_str, doc_level_iter, lex_count=params.LEX_COUNT)359    # print("*******************************************************************************")360    # Skipping this for now361    # print("DOC HARD")362    # test_hard_annotations(code_to_new_lex, code_to_str, hard_iter)363    # print("*******************************************************************************")364    # print("SENTENCE")365    # test_sentence_annotations(code_to_new_lex,code_to_str, frame_to_contains, frame_to_doesnt)366    print("*******************************************************************************")367    print("PRIMARY")368    test_primary_frame(code_to_new_lex, code_to_str, doc_level_iter)369    print("*******************************************************************************")370    # # Real slow and doesn't work well371    # print("PRIMARY WV")372    # test_primary_frame_wv(code_to_new_lex, code_to_str, doc_level_iter, KeyedVectors.load(wv_name))373    to_save = {}374    for x in code_to_new_lex:375      to_save[code_to_str[x]] = code_to_new_lex[x]376    pickle.dump(to_save, open("cache/" + args.split_type + "_lex.pickle", "wb"))377    to_save = {}378    for x in code_to_lex:379      to_save[code_to_str[x]] = code_to_new_lex[x]380    pickle.dump(to_save, open("cache/" + args.split_type + "_base_lex.pickle", "wb"))381def main():382    parser = argparse.ArgumentParser()383    parser.add_argument("--baseline", action='store_true')384    # specify what to use as training data and what to use as test set. If random, hold out 20% of data of test385    # if kfold, we do a different data split for each frame, so that test and train data have same proportion386    # of the frame at the document level387    parser.add_argument("--split_type", choices=['tobacco', 'immigration', 'samesex', 'random', 'kfold', 'dcard', 'dcard_tune'])388    args = parser.parse_args()389    p = Params()390    code_file = os.path.join(p.MFC_PATH, "codes.json")391    code_to_str = load_codes(code_file)392    if args.split_type == 'kfold':393        codes = set([code_to_short_form(code) for code in code_to_str])394        codes.remove(0.0) # Skip "None"395        codes.remove(16.0) # Skip "Irrelevant396        codes.remove(17.0) # Skip tones397        codes.remove(18.0)398        codes.remove(19.0)399        for code in codes:400            print(code)401            train_data, test_data, test_background = get_data_split(args.split_type, p, code)402            do_all(args, train_data, test_data, test_background, code_to_str, p, code)403    else:404        train_data, test_data, test_background = get_data_split(args.split_type, p)405        do_all(args, train_data, test_data, test_background, code_to_str, p)406if __name__ == "__main__":...

test_syntheticdataset2_shapes.py

Source:test_syntheticdataset2_shapes.py

1from SyntheticDataset2.ElementsCreator import *2import unittest3from PIL import Image4class UpdatedSyntheticDatasetShapesTestCase(unittest.TestCase):5    def test_rectangle(self):6        width = 1007        height = 508        color = (255,0,0)9        rotation = 4510        midpoint = (250,250)11        test_background = Image.new('RGBA', (500,500), color=(0,0,255))12        test_rectangle = Rectangle(width, height, color, rotation)13        self.assertEqual(test_rectangle.draw().getpixel((50,25)), (255,0,0,255))14        self.assertEqual(test_rectangle.draw().getpixel((80,40)), (255,0,0,255))15        test_rectangle.overlay(midpoint, test_background)16        self.assertEqual(test_background.getpixel(midpoint), (255,0,0,255))17        self.assertEqual(test_background.getpixel((265,210)), (255,0,0,255))18    def test_triangle(self):19        base = 10020        height = 10021        color = (255,0,0)22        rotation = 4523        midpoint = (250,250)24        test_background = Image.new('RGBA', (500,500), color=(0,0,255))25        test_triangle = Triangle(base,height,color,rotation)26        self.assertEqual(test_triangle.draw().getpixel((100,100)), (255,0,0,255))27        self.assertEqual(test_triangle.draw().getpixel((75,130)), (255,0,0,255))28        test_triangle.overlay(midpoint, test_background)29        self.assertEqual(test_background.getpixel(midpoint), (255,0,0,255))30        self.assertEqual(test_background.getpixel((250,250)), (255,0,0,255))31    def test_circle(self):32        radius = 10033        color = (255,0,0)34        midpoint = (250,250)35        test_background = Image.new('RGBA', (500,500), color=(0,0,255))36        test_circle = Circle(radius,color)37        self.assertEqual(test_circle.draw().getpixel((50,25)), (255,0,0,255))38        self.assertEqual(test_circle.draw().getpixel((60,50)), (255,0,0,255))39        test_circle.overlay(midpoint, test_background)40        self.assertEqual(test_background.getpixel(midpoint), (255,0,0,255))41        self.assertEqual(test_background.getpixel((260,160)), (255,0,0,255))42    def test_half_circle(self):43        radius = 10044        color = (255,0,0)45        rotation = 4546        midpoint = (250,250)47        test_background = Image.new('RGBA', (500,500), color=(0,0,255))48        test_half_cirlce = HalfCircle(radius,color,rotation)49        self.assertEqual(test_half_cirlce.draw().getpixel((100,100)), (255,0,0,255))50        self.assertEqual(test_half_cirlce.draw().getpixel((75,200)), (255,0,0,255))51        test_half_cirlce.overlay(midpoint, test_background)52        self.assertEqual(test_background.getpixel(midpoint), (255,0,0,255))53        self.assertEqual(test_background.getpixel((215,340)), (255,0,0,255))54    def test_square(self):55        base = 10056        color = (255,0,0)57        rotation = 4558        midpoint = (250,250)59        test_background = Image.new('RGBA', (500,500), color=(0,0,255))60        test_square = Square(base,color,rotation)61        self.assertEqual(test_square.draw().getpixel((50,25)), (255,0,0,255))62        self.assertEqual(test_square.draw().getpixel((20,70)), (255,0,0,255))63        test_square.overlay(midpoint, test_background)64        self.assertEqual(test_background.getpixel(midpoint), (255,0,0,255))65        self.assertEqual(test_background.getpixel((250,195)), (255,0,0,255))66    def test_trapezoid(self):67        base1 = 7568        base2 = 10069        height = 10070        color = (255,0,0)71        rotation = 4572        midpoint = (250,250)73        test_background = Image.new('RGBA', (500,500), color=(0,0,255))74        test_trapezoid = Trapezoid(base1,base2,height,color,rotation)75        self.assertEqual(test_trapezoid.draw().getpixel((50,25)), (255,0,0,255))76        self.assertEqual(test_trapezoid.draw().getpixel((70,30)), (255,0,0,255))77        test_trapezoid.overlay(midpoint, test_background)78        self.assertEqual(test_background.getpixel(midpoint), (255,0,0,255))79        self.assertEqual(test_background.getpixel((300,250)), (255,0,0,255))80    def test_quarter_circle(self):81        radius = 10082        color = (255,0,0)83        rotation = 4584        midpoint = (250,250)85        test_background = Image.new('RGBA', (500,500), color=(0,0,255))86        test_quarter_circle = QuarterCircle(radius,color,rotation)87        self.assertEqual(test_quarter_circle.draw().getpixel((100,100)), (255,0,0,255))88        self.assertEqual(test_quarter_circle.draw().getpixel((70,20)), (255,0,0,255))89        test_quarter_circle.overlay(midpoint, test_background)90        self.assertEqual(test_background.getpixel(midpoint), (255,0,0,255))91        self.assertEqual(test_background.getpixel((250,300)), (255,0,0,255))92    def test_cross(self):93        height = 10094        color = (255,0,0)95        rotation = 4596        midpoint = (250,250)97        test_background = Image.new('RGBA', (500,500), color=(0,0,255))98        test_cross = Cross(height,color,rotation)99        self.assertEqual(test_cross.draw().getpixel((100,100)), (255,0,0,255))100        self.assertEqual(test_cross.draw().getpixel((45,40)), (255,0,0,255))101        test_cross.overlay(midpoint, test_background)102        self.assertEqual(test_background.getpixel(midpoint), (255,0,0,255))103        self.assertEqual(test_background.getpixel((225,285)), (255,0,0,255))104    def test_pentagon(self):105        radius = 100106        color = (255,0,0)107        rotation = 45108        midpoint = (250,250)109        test_background = Image.new('RGBA', (500,500), color=(0,0,255))110        test_pentagon = Pentagon(radius,color,rotation)111        self.assertEqual(test_pentagon.draw().getpixel((150,150)), (255,0,0,255))112        self.assertEqual(test_pentagon.draw().getpixel((125,60)), (255,0,0,255))113        test_pentagon.overlay(midpoint, test_background)114        self.assertEqual(test_background.getpixel(midpoint), (255,0,0,255))115        self.assertEqual(test_background.getpixel((210,330)), (255,0,0,255))116    def test_star(self):117        radius = 100118        color = (255,0,0)119        rotation = 45120        midpoint = (250,250)121        test_background = Image.new('RGBA', (500,500), color=(0,0,255))122        test_star = Star(radius,color,rotation)123        self.assertEqual(test_star.draw().getpixel((150,150)), (255,0,0,255))124        self.assertEqual(test_star.draw().getpixel((170,100)), (255,0,0,255))125        test_star.overlay(midpoint, test_background)126        self.assertEqual(test_background.getpixel(midpoint), (255,0,0,255))127        self.assertEqual(test_background.getpixel((230,200)), (255,0,0,255))128    def test_hexagon(self):129        radius = 100130        color = (255,0,0)131        rotation = 45132        midpoint = (250,250)133        test_background = Image.new('RGBA', (500,500), color=(0,0,255))134        test_hexagon = Hexagon(radius,color,rotation)135        self.assertEqual(test_hexagon.draw().getpixel((150,150)), (255,0,0,255))136        self.assertEqual(test_hexagon.draw().getpixel((90,100)), (255,0,0,255))137        test_hexagon.overlay(midpoint, test_background)138        self.assertEqual(test_background.getpixel(midpoint), (255,0,0,255))139        self.assertEqual(test_background.getpixel((260,200)), (255,0,0,255))140    def test_heptagon(self):141        radius = 100142        color = (255,0,0)143        rotation = 45144        midpoint = (250,250)145        test_background = Image.new('RGBA', (500,500), color=(0,0,255))146        test_heptagon = Heptagon(radius,color,rotation)147        self.assertEqual(test_heptagon.draw().getpixel((150,150)), (255,0,0,255))148        self.assertEqual(test_heptagon.draw().getpixel((70,150)), (255,0,0,255))149        test_heptagon.overlay(midpoint, test_background)150        self.assertEqual(test_background.getpixel(midpoint), (255,0,0,255))151        self.assertEqual(test_background.getpixel((235,185)), (255,0,0,255))152    def test_octagon(self):153        radius = 100154        color = (255,0,0)155        rotation = 45156        midpoint = (250,250)157        test_background = Image.new('RGBA', (500,500), color=(0,0,255))158        test_octagon = Octagon(radius,color,rotation)159        self.assertEqual(test_octagon.draw().getpixel((150,150)), (255,0,0,255))160        self.assertEqual(test_octagon.draw().getpixel((100,170)), (255,0,0,255))161        test_octagon.overlay(midpoint, test_background)162        self.assertEqual(test_background.getpixel(midpoint), (255,0,0,255))...

Automation Testing Tutorials

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