KaneAI - World’s First E2E Software Testing Agent.Book a Demo Join TestMu Conference

How to use test_yes method in green

Best Python code snippet using green

naive_bayes.py

Source:naive_bayes.py

1import numpy as np2"""Data: 57 features, 4601 data points"""3yes = []; no = []; outcome = []4ratio = 0.85#Reading the data from data.txt:6with open('data.txt', 'r') as data:7	for line in data.readlines():8		#train_cat.append(map(lambda x: np.float64(x), line.split(',')))9		point = (map(lambda x: np.float64(x), line.split(' ')))10		outcome.append(point[-1])11		if point[-1] == 1:12			yes.append(point[:len(point)-1])13		else:14			no.append(point[:len(point)-1])15"""print(0, int(round(ratio*len(yes), 0))-1)16print(int(round(ratio*len(yes), 0)), int(round(len(yes), 0))-1)17print(len(yes), int(round(len(yes) + ratio*len(no), 0))-1)18print(int(round(len(yes) + ratio*len(no), 0)), int(round(len(yes) + len(no), 0))-1)"""19#Indices:20ind1 = 021ind2 = int(round(ratio*len(yes), 0))22ind3 = int(round(len(yes), 0))23ind4 = int(round(len(yes) + ratio*len(no), 0))24ind5 = int(round(len(yes) + len(no), 0))25train_yes = yes[:ind2]; train_yes = np.transpose(train_yes)26train_no  = no [:int(round(ratio*len(no),0))]; train_no = np.transpose(train_no)27outcome_test = outcome[ind2:ind3] + outcome[ind4:ind5]28test_yes = yes[ind2:]; test_no = no [int(round(ratio*len(no),0)):]29"""train_yes = yes[:int(round(.8*len(yes), 0))]; train_yes = np.transpose(train_yes)30train_no  = no [:int(round(.8*len(no ), 0))]; train_no  = np.transpose(train_no )31outcome_test = outcome[1450:1813] + outcome[4043:4601]32test_yes = yes[int(round(.8*len(yes), 0)):] ; test_no  = no [int(round(.8*len(no ), 0)):]"""33print("len(yes) = {}, len(train_yes) = {}, len(test_yes) = {}\nlen(no ) = {}, len(train_no ) = {}, len(test_no ) = {}".format(len(yes), np.shape(train_yes)[1], len(test_yes), len(no), np.shape(train_no)[1], len(test_no)))34mean_yes = np.mean(train_yes, 1); mean_no  = np.mean(train_no, 1)35cov_yes = np.cov(train_yes); cov_no  = np.cov(train_no)36Y = test_yes + test_no37#print("Y.shape = {}x{}".format(len(Y), len(Y[0])))38output = []39p_yes = float(len(yes))/(len(yes) + len(no)); p_no  = float(len(no ))/(len(yes) + len(no))40term1 = -1*(len(Y[0])/2) * np.log10(2*np.pi)41term2_yes = -0.5* np.log10(np.linalg.det(cov_yes)); term12_yes = term1 + term2_yes42term2_no  = -0.5* np.log10(np.linalg.det(cov_no)) ; term12_no  = term1 + term2_no43cov_inv_yes = np.linalg.inv(cov_yes)44cov_inv_no  = np.linalg.inv(cov_no )45for point in Y:46	term3_yes = np.matmul(np.transpose(point - mean_yes), cov_inv_yes)47	term3_yes = -0.5 * np.matmul(term3_yes, point - mean_yes) + p_yes48	term3_no  = np.matmul(np.transpose(point - mean_no ), cov_inv_no )49	term3_no  = -0.5 * np.matmul(term3_no, point - mean_no ) + p_no50	if (term12_yes + term3_yes >= term12_no + term3_no):51		output.append(1)52	else:53		output.append(0)54wrong_spam  = 0; wrong_non_spam = 055for i in range(len(output)):56	if outcome_test[i] == 1 and output[i] == 0:57		wrong_non_spam += 158	if outcome_test[i] == 0 and output[i] == 1:59		wrong_spam += 160error = np.float64(wrong_spam + wrong_non_spam)61print("Result: With training:testing ratio of {}, accuracy = 1 - {}/{} = {}".format(ratio, error, len(Y), 1-(error/len(Y))))62print("Fraction of non-spam incorrectly detected as spam = {}, fraction of spam incorrectly detected as non-spam = {}".format(np.float64(wrong_spam)/len(test_no), np.float64(wrong_non_spam)/len(test_yes)))63"""With ration = 0.8, 64len(yes) = 1813, len(train_yes) = 1450, len(test_yes) = 36365len(no ) = 2788, len(train_no ) = 2230, len(test_no ) = 55866cov_yes.shape = (57, 57)67Y.shape = 921x5768p_yes = 0.394044772875, p_no = 0.605955227125...

test_env.py

Source:test_env.py

1# -*- coding: utf-8 -*-2# Copyright (C) Duncan Macleod (2018-2020)3#4# This file is part of GWpy.5#6# GWpy is free software: you can redistribute it and/or modify7# it under the terms of the GNU General Public License as published by8# the Free Software Foundation, either version 3 of the License, or9# (at your option) any later version.10#11# GWpy is distributed in the hope that it will be useful,12# but WITHOUT ANY WARRANTY; without even the implied warranty of13# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the14# GNU General Public License for more details.15#16# You should have received a copy of the GNU General Public License17# along with GWpy.  If not, see <http://www.gnu.org/licenses/>.18"""Tests for :mod:`gwpy.utils.env`19"""20from unittest import mock21import pytest22from .. import env as utils_env23BOOL_TRUE = {24    'TEST_y': 'y',25    'TEST_Y': 'Y',26    'TEST_yes': 'yes',27    'TEST_Yes': 'Yes',28    'TEST_YES': 'YES',29    'TEST_ONE': '1',30    'TEST_true': 'true',31    'TEST_True': 'True',32    'TEST_TRUE': 'TRUE',33}34BOOL_FALSE = {35    'TEST_no': 'no',36    'TEST_No': 'No',37    'TEST_ZERO': '0',38    'TEST_false': 'false',39    'TEST_False': 'False',40    'TEST_FALSE': 'FALSE',41    'TEST_OTHER': 'blah',42}43BOOL_ENV = BOOL_TRUE.copy()44BOOL_ENV.update(BOOL_FALSE)45@mock.patch.dict('os.environ', values=BOOL_ENV)46@pytest.mark.parametrize(47    'env, result',48    [(k, True) for k in sorted(BOOL_TRUE)]49    + [(k, False) for k in sorted(BOOL_FALSE)],50)51def test_bool_env(env, result):52    """Test :meth:`gwpy.utils.env.bool_env` _without_ the `default` keyword53    """54    assert utils_env.bool_env(env) is result55@mock.patch.dict('os.environ', values=BOOL_TRUE)56@pytest.mark.parametrize('env, default, result', [57    ('TEST_YES', False, True),58    ('TEST_MISSING', True, True),59])60def test_bool_env_default(env, default, result):61    """Test :meth:`gwpy.utils.env.bool_env` _with_ the `default` keyword62    """...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.