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How to use percent_of_tests method in Lemoncheesecake

Best Python code snippet using lemoncheesecake

configuration.py

Source:configuration.py

1# coding: utf-823#Hoopaloo - Version 1.0 - 2008/20094#Author: Mariana Romao do Nascimento - mariana@dsc.ufcg.edu.br56from django.conf import settings78TEST_DEFAULT_CODE = "import unittest \n\n\n\nclass %s (unittest.TestCase): \n\n\tdef setUp(self):\n\t\t pass\n\n\n\tdef tearDown(self):\n\t\tpass"910UNDER_TEST_COMPLEMENT = "if __name__== '__main__':\n\tfrom unittest import TestResult\n\tloader = unittest.TestLoader()\n\tloader.testMethodPrefix = 'undertest'\n\tsuite = loader.loadTestsFromTestCase(%s)\n\tr = TestResult()\n\tsuite.run(r)\n\tresult_file = open(%s + 'result.txt', 'wb')\n\tresult_file.write(str(len(r.errors)))\n\tresult_file.write('\\n')\n\tresult_file.write(str(len(r.failures)))\n\tresult_file.write('\\n')\n\tresult_file.write(str(r.testsRun))\n\tresult_file.write('\\n')\n\tresult_file.write(str(r.wasSuccessful()))\n\tresult_file.write('\\n')\n\tfor e in r.errors:\n\t\tresult_file.write(e[1])\n\tfor f in r.failures:\n\t\tresult_file.write(f[1])\n\tresult_file.close()"1112TEST_APPEND = "if __name__== '__main__':\n\tfrom unittest import TestResult\n\tloader = unittest.TestLoader()\n\tsuite = loader.loadTestsFromTestCase(%s)\n\tr = TestResult()\n\tsuite.run(r)\n\tresult_file = open('result.txt', 'wb')\n\tresult_file.write(str(len(r.errors)))\n\tresult_file.write('\\n')\n\tresult_file.write(str(len(r.failures)))\n\tresult_file.write('\\n')\n\tresult_file.write(str(r.testsRun))\n\tresult_file.write('\\n')\n\tresult_file.write(str(r.wasSuccessful()))\n\tresult_file.write('\\n')\n\tfor e in r.errors:\n\t\tresult_file.write(e[1])\n\tfor f in r.failures:\n\t\tresult_file.write(f[1])\n\tresult_file.close()"1314TEST_APPEND_STUDENT_FOLDER = "if __name__== '__main__':\n\tfrom unittest import TestResult\n\tloader = unittest.TestLoader()\n\tsuite = loader.loadTestsFromTestCase(%s)\n\tr = TestResult()\n\tsuite.run(r)\n\tresult_file = open(%s + 'result.txt', 'wb')\n\tresult_file.write(str(len(r.errors)))\n\tresult_file.write('\\n')\n\tresult_file.write(str(len(r.failures)))\n\tresult_file.write('\\n')\n\tresult_file.write(str(r.testsRun))\n\tresult_file.write('\\n')\n\tresult_file.write(str(r.wasSuccessful()))\n\tresult_file.write('\\n')\n\tfor e in r.errors:\n\t\tresult_file.write(e[1])\n\tfor f in r.failures:\n\t\tresult_file.write(f[1])\n\tresult_file.close()"151617INFINITE_LOOP_MSG = "The program entered in infinite loop."1819EMAIL_SYSTEM = 'hoopaloo@dsc.ufcg.edu.br'20SMTP_SERVER = "anjinho.dsc.ufcg.edu.br" 21BACKUP_TEST_NAME = 'backup_test'2223PASSWORD_EMAIL = 'Welcome to Hoopaloo,\n\nYou are registered in the system and your login is: %s and your password is %s.\nThanks,\nHoopaloo.'24FORGOT_PASSWORD_EMAIL = 'Hello %s,\nYou requested a new password. This password is %s and you must change it when access Hoopaloo system at the next time.\n\nThanks, Hoopaloo.'2526RESULT_TEST_FILE = 'result.txt'2728PERCENT_OF_TESTS = [(100, 91), (90, 71), (70, 51), (50, 31), (30, 11), (10, 0)]29PERCENT_OF_SCORE = [(10.0, 9.1), (9.0, 8.1), (8.0, 7.1), (7.0, 6.1), (6.0, 5.1), (5.0, 4.1), (4.0, 3.1), (3.0, 2.1), (2.0, 1.1), (1.0, 0.0)]3031LOGIN_SUCESS = 'You are logged'32LOGOUT_SUCESS = 'You are unlogged'33UNDELIVERED_EXERCISES_MSG = 'You not submited the following exercises and the deadline for the submission is expired.'34#duvida na frase abaixo35DELIVERED_EXERCISES_MSG = 'You submit the following exercises. You can modify your submission if you want.'36AVAILABLE_EXERCISES_MSG = 'The following exercises are available for submission.'37UNDELIVERED_AVAILABLE_EXERCISES_MSG = 'You not submited the following exercises. You must verify the deadline for them.'3839REALIZED_SUBMISSIONS = 'All submissions that you realized in Hoopaloo are listed bellow.'40TEACHER_VIEW_EXPLICATION = 'There are not registered students.'4142PASSWORD_CHANGED_MSG = 'Your password was changed.'43PASSWORD_NOT_MATCHES = 'The two password fields did not match.'44INVALID_PASSWORD = 'The password is invalid.'4546FORGOT_PASSWORD = 'Please check your email. If you did not receive any message, check your spam folder.'4748ASSIGN_SUCESS = 'The assign students to assistant(s) was done sucessfully.'49ASSIGN_ERROR = 'You have not permission to assign students to assistants.'50REVIEW_ASSIGN = 'Review the assigns students to assistant(s) bellow. See usernames with attention.'5152EXERCISE_ADD_SUCESS = 'The exercise was added sucessfully. If you want edit the default test to this exercise click on link "Exercises > List Tests" and edit it.'53EXERCISE_ADD_ERROR = 'Some error exists in your form.'54EXERCISE_ADD_ERROR_DATE = 'Review the date.'55EXERCISE_EXISTS = 'An exercise with the same name already exists.'56EXERCISE_UPDATED_SUCESSFULLY = 'The exercise was updated sucessfully.'57EXERCISE_UPDATE_AVAILABILITY = 'The exercise was updated sucessfully. Please, check the deadline to this exercise.'58EXERCISE_UPDATE_AVAILABILITY_ERROR = 'The execise was not updated. Change the dead line for this exercise before.'59EXERCISE_DELETED = 'The exercise was deleted sucessfully.' 60EXERCISE_UPDATE_FAIL = 'Select a date later than current date.'6162ADD_NOTE_ERROR = "The score must be a integer or a decimal number (use '.' in this case)."63ADD_NOTE_ERROR_2 = 'The score must be between 0 and 10.'6465EXECUTION_PASS = 'Your program passed in all tests (%d tests).'66EXECUTION_FAILED = 'Your program not passed in all tests. There are %d registered tests and you not passed in %d tests.'67#EXECUTION_FAILED = 'Your program passed in none tests.'68EXECUTION_LOOP = 'Your program entered in infinite loop.'69EXECUTION_AFTER = 'Your program was submited sucessfully, but at the moment there are not tests registered.\nWhen tests will be added, your program will be executed and the results sent to you by email.'7071EXECUTION_SUCESS = 'The program of student %s passed in all tests of exercise %s. The link to see the code of program is http://dataccc.gmf.ufcg.edu.br/hoopaloo/submission/student%d/exercise/id=%d'7273SUBMISSION_MSG = 'Do the upload of your program and select given exercise.'74SUBMISSION_ERROR = 'You must choose an exercise.'75SUBMISSION_FAIL = 'It exists some error in method names, imports or syntax of your program. Fix it and try submit again.'76SUBMISION_SUCESS = 'Your program was updated sucessfully. Check your code submission in table bellow.'7778ADD_COMMENT_SCORE_SUCESS = 'Comments/score are addedd sucessfully.'7980TEST_UPDATE_SUCESS = 'The test was updated sucessfully and it will be executed automatically to all students.'81TEST_ADD_SUCESSFULLY = 'The test was added sucessfully.'82TEST_EXISTS = 'A test with the same name already exists.'83TEST_ADD_ERROR = 'Some error exists in your form.'84UNDER_TEST_ADD_SUCESSFULLY = 'The test under test was added sucessfullty. Choose the student submissions to execute.'8586ASSISTANT_ADD_SUCESS = 'The assistants was added sucessfully.'87ASSISTANT_ADD_ERROR = 'The assistants bellow are not registered. Review usernames and emails for them.'88REVIEW_USERNAMES_AND_EMAILS = 'Rewiew usernames and emails.'8990STUDENT_ADD_SUCESS = 'The students were added successfully.'91STUDENT_ADD_ERROR = 'The students bellow are not registered. Review usernames, studentID and emails for them.'9293USER_DELETED = "The user was deleted successfully."94# PERMITIONS9596EXERCISE_ADD_NOT_PERMISSION = 'You have not permission to add exercises.'97TEST_UPDATE_NOT_PERMISSION = 'You have not permission to change tests.'98TESTS_ADD_NOT_PERMISSION = 'You have not permission to add tests.'99EXERCISE_UPDATE_NOT_PERMISSION = 'You have not permission to change exercises.'100EXERCISE_SEE_NOT_PERMISSION = 'You have not permission to see exercise details.'101ASSISTANT_ADD_NOT_PERMISSION = 'You have not permission to add assistants.'102VIEW_USERS_NOT_PERMISSION = 'You have not permissions to see user details.'103DELETE_USERS_NOT_PERMISSION = 'You have not permission to delete users.'104ASSIGN_STUDENTS_NOT_PERMISSION = 'You have not permission to assign students to assistants.'105RESULT_SEE_NOT_PERMISSION = 'You have not permission to see submission data of students.'106TEST_SEE_NOT_PERMISSION = 'You have not permission to see the test details.'107INVALIDATE_TEST_NOT_PERMISSION = 'You have not permission to annul a test.'108TEACHER_VIEW_NOT_PERMISSION = 'You are not a teacher.'109ASSISTANT_VIEW_NOT_PERMISSION = 'You are not a assistant.'110SEE_ACTIONS_NOT_PERMISSION = 'You have not permission to see the system actions.'111STUDENT_ADD_NOT_PERMISSION = 'You have not permission to add students.'112SUBMISSION_NOT_PERMISSION = 'You have not permission to submit programs.'113SUBMISSION_SEE_NOT_PERMISSION = 'You have not permission to see submission details.'114DELETE_ASSOCIATION_NOT_PERMISSION = 'You have not permission to delete assigns between students and assistants.'115116# ACTIONS #117LOG_LOGIN = "Realized login"118LOG_LOGOUT = "Realized logout"119LOG_CHANGE_PASSWORD = "Changed the password"120LOG_FORGOT_PASSWORD = "%s requested a new password to %s"121LOG_ASSIGN_STUDENTS = "Assign the assistant %s to students %s"122LOG_ADD_EXERCISE = "Registered new exercise: %s"123LOG_EDIT_EXERCISE = "Edited the exercise: %s"124LOG_EDIT_SUBMISSION = "Add coments or/and note to submission %d of student %s"125LOG_SUBMISSION = "Submit a solution to exercise %s"126LOG_ADD_TEST = "Registered new test: %s"127LOG_EDIT_TEST = "Edited the test: %s"128LOG_IVALIDATE_TEST = "Annuled a test: %s"129LOG_ADD_ASSISTANT = "Registered new assistant: %s"130LOG_ADD_STUDENT = "Registered new student: %s"131LOG_DELETE_EXERCISE = "Deleted the exercise %s"132LOG_DELETE_USER = "Deleted the user %s"
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network.py

Source:network.py

1import random2import numpy as np3DICTIONARY = ['A', 'B', 'C']4NUMBER_OF_POSITIONS = 45START_POSITION = np.zeros(NUMBER_OF_POSITIONS)6START_POSITION[0] = 17NUMBER_OF_CHARS = len(DICTIONARY)8PERCENT_OF_TESTS = 0.19TenzToAdd = 2.010EPS = 10e-411NU = 0.712NU_ADDER = 0.313class NeuralNetwork:14    tensor = np.zeros([NUMBER_OF_POSITIONS, NUMBER_OF_CHARS, NUMBER_OF_POSITIONS])15    adder = np.zeros(NUMBER_OF_POSITIONS)16    def __init__(self):17        self.tensor = np.zeros([NUMBER_OF_POSITIONS, NUMBER_OF_CHARS, NUMBER_OF_POSITIONS])18        for fr in range(NUMBER_OF_POSITIONS):19            for ch in range(NUMBER_OF_CHARS):20                z = np.random.rand(NUMBER_OF_POSITIONS)21                z = normalize(z)22                for to in range(NUMBER_OF_POSITIONS):23                    self.tensor[to][ch][fr] = z[to]24        self.adder = np.zeros(NUMBER_OF_POSITIONS)25        for to in range(NUMBER_OF_POSITIONS):26            self.adder[to] = 1.0 * (to + 1) / (NUMBER_OF_POSITIONS) ### weird27    def check(self, word): # get a word output - forward propogation28        curr_pos = START_POSITION29        for k in range(len(word)):30            curr_word = char_to_vector(word[k])31            curr_pos = match(self, curr_word, curr_pos)32            curr_pos = normalize(curr_pos)33        return lastsum(self, curr_pos)34    def train_online(self, dataset):35        average_error = 1.036        epoch_number = 037        n = len(dataset)38        tests_size = int(PERCENT_OF_TESTS * n)39        while (average_error > EPS):40            random.shuffle(dataset)41            cases_left = len(dataset)42            epoch_number += 143            print('Epoch #' + str(epoch_number))44            while(cases_left > tests_size):45                self.train(dataset[cases_left - 1][0], dataset[cases_left - 1][1])46                cases_left -= 147            average_error = 0.048            for i in range(cases_left):49                average_error += cost_function(dataset[i][1], self.check(dataset[i][0]))50            average_error /= cases_left51            print("Average error: " + str(average_error))52    def train(self, word, exp):53        cut_v = np.vectorize(cut)54        word_length = len(word)55        positions = np.zeros([word_length + 1, NUMBER_OF_POSITIONS])56        before_normalize = np.zeros([word_length, NUMBER_OF_POSITIONS])57        d_tensor = np.zeros([NUMBER_OF_POSITIONS, NUMBER_OF_CHARS, NUMBER_OF_POSITIONS])58        d_adder = np.zeros(NUMBER_OF_POSITIONS)59        positions[0] = START_POSITION60        for k in range(word_length):61            curr_word = char_to_vector(word[k])62            before_normalize[k] = match(self, curr_word, positions[k])63            positions[k + 1] = normalize(before_normalize[k])64        answer = lastsum(self, positions[-1])65        error = cost_function(exp, answer)66        gradient = cost_function_derrivative(exp, answer)67        d_adder += lastsum_derrivative_adder(self, gradient, positions[-1])68        gradient = lastsum_derrivative(self, gradient)69        first_gradient = sum(abs(gradient)) * TenzToAdd70        for k in range(word_length - 1, -1, -1):71            curr_grad = sum(abs(gradient))72            if (curr_grad < 0.001):73                koef = 1.074            else:75                koef = first_gradient / sum(abs(gradient))76            gradient *= koef77            curr_word = char_to_vector(word[k])78            gradient = normalize_derrivative(gradient, before_normalize[k])79            d_tensor += match_derrivative_tensor(gradient, curr_word, positions[k])80            gradient = match_derrivative(self, gradient, curr_word)81        d_tensor /= word_length82        self.tensor = cut_v(self.tensor - NU * d_tensor)83        self.adder = cut_v(self.adder - NU * NU_ADDER * d_adder)84        return error85    def get_automaton(self):86        for j in range(NUMBER_OF_POSITIONS):87            for i in range(NUMBER_OF_CHARS):88                max_ind = 089                for k in range(1, NUMBER_OF_POSITIONS):90                    if (nn.tensor[k][i][j] > nn.tensor[max_ind][i][j]):91                        max_ind = k92                print(str(j) + ' -> ' + str(max_ind) + ' [label="' + str(DICTIONARY[i]) + '"]')93        for k in range(NUMBER_OF_POSITIONS):94            if (nn.adder[k] > 0.5):95                print(str(k) + " [style=filled, fillcolor=red]")96def cost_function(exp, res):97    return (res - exp) ** 298def cost_function_derrivative(exp, res):99    return res - exp100def match(nn, ch, pos):101    new_pos = np.zeros(NUMBER_OF_POSITIONS)102    for k in range(NUMBER_OF_POSITIONS):103        for i in range (NUMBER_OF_CHARS):104            for j in range (NUMBER_OF_POSITIONS):105                new_pos[k] += nn.tensor[k][i][j] * ch[i] * pos[j]106    return new_pos107def match_derrivative(nn, dz, ch):108    derrivative = np.zeros([NUMBER_OF_POSITIONS, NUMBER_OF_POSITIONS])109    for i in range(NUMBER_OF_POSITIONS):110        for k in range(NUMBER_OF_POSITIONS):111            for j in range (NUMBER_OF_CHARS):112                derrivative[k][i] += nn.tensor[k][j][i] * ch[j]113    return np.dot(dz, derrivative)114def match_derrivative_tensor(dz, ch, pos):115    sample_matrix = np.zeros([NUMBER_OF_CHARS, NUMBER_OF_POSITIONS])116    for i in range(NUMBER_OF_CHARS):117        for j in range(NUMBER_OF_POSITIONS):118            sample_matrix[i][j] = ch[i] * pos[j]119    derrivative = np.zeros([NUMBER_OF_POSITIONS, NUMBER_OF_CHARS, NUMBER_OF_POSITIONS])120    for i in range(NUMBER_OF_POSITIONS):121        derrivative[i] = dz[i] * sample_matrix122    return derrivative123def normalize(t):124    return t / np.sum(t)125def normalize_derrivative(dz, inp):126    derrivative = np.zeros([NUMBER_OF_POSITIONS, NUMBER_OF_POSITIONS])127    sum = np.sum(inp)128    for i in range(NUMBER_OF_POSITIONS):129        for j in range(NUMBER_OF_POSITIONS):130            if(i == j):131                derrivative[i][j] = (sum - inp[i]) / (sum ** 2)132            else:133                derrivative[i][j] = -inp[i] / (sum ** 2)134    return np.dot(dz, derrivative)135def lastsum(nn, x):136    return np.dot(nn.adder, x)137def lastsum_derrivative(nn, dz):138    return np.dot(dz, nn.adder)139def lastsum_derrivative_adder(nn, dz, inp):140    derrivative = np.multiply(inp, nn.adder)141    return np.dot(dz, derrivative)142def char_to_vector(ch):143    index = DICTIONARY.index(ch)144    vec = np.zeros(NUMBER_OF_CHARS)145    vec[index] = 1.0146    return vec147def cut(x): # activation (~relu)148    if (x > 1.0):149        return 1.0150    if (x < 0.0):151        return 0.0152    return x153f = open('generate_dataset.txt', 'r')154dataset = []155for line in f:156    arr = line.split(' ')157    isOk = 1.0158    if arr[1][0] == '0':159        isOk = 0.0160    dataset.append([arr[0], isOk])161nn = NeuralNetwork()162nn.train_online(dataset)...

stats.py

Source:stats.py

...50    def run_cmd(self, cli_args):51        project = load_project()52        suites = load_suites_from_project(project, make_test_filter(cli_args))53        stats = compute_stats(suites)54        def percent_of_tests(val):55            return "%2d%%" % (float(val) / stats.tests_nb * 100)56        # Show tags57        lines = []58        for tag in sorted(stats.tags.keys(), key=lambda k: stats.tags[k], reverse=True):59            lines.append([bold(tag), stats.tags[tag], percent_of_tests(stats.tags[tag])])60        print_table(bold("Tags"), ["Tag", "Tests", "In %"], lines)61        # Show properties62        lines = []63        prop_names = sorted(64            stats.properties.keys(),65            key=lambda k: reduce(lambda x, y: x + y, stats.properties[k].values(), 0),66            reverse=True67        )68        for prop_name in prop_names:69            prop_values = sorted(70                stats.properties[prop_name].keys(),71                key=lambda k: stats.properties[prop_name][k],72                reverse=True73            )74            for prop_value in prop_values:75                lines.append([76                    bold(prop_name), bold(prop_value),77                    stats.properties[prop_name][prop_value],78                    percent_of_tests(stats.properties[prop_name][prop_value])79                ])80        print_table(bold("Properties"), ["Property", "Value", "Tests", "In %"], lines)81        # Show links82        lines = []83        for link in sorted(stats.links.keys(), key=lambda k: stats.links[k], reverse=True):84            lines.append([85                bold(link[1] or "-"), link[0], stats.links[link], percent_of_tests(stats.links[link])86            ])87        print_table(bold("Links"), ["Name", "URL", "Tests", "In %"], lines)88        tests_info = bold("%d tests" % stats.tests_nb)89        if stats.disabled_tests_nb > 0:90            tests_info += " (among which %s disabled tests)" % stats.disabled_tests_nb91        suites_info = bold("%d suites" % stats.non_empty_suites_nb)92        if stats.suites_nb > stats.non_empty_suites_nb:93            suites_info += " (+ %d empty suites)" % (stats.suites_nb - stats.non_empty_suites_nb)94        print("Total: %s in %s" % (tests_info, suites_info))95        print()...

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