class MyTestCase(unittest.TestCase): def setUp(self) -> None: self.statistics = Statistics() def test_instantiate_calculator(self): self.assertIsInstance(self.statistics, Statistics) def test_mean_statistics(self): test_data = CsvReader('Tests/Data/unit_test_mean.csv').data for row in test_data: result = int(row['Result']) self.assertEqual(self.statistics.mean(row['Value 1'], row['Value 2'], row['Value 3']), result) self.assertEqual(self.statistics.result, result) def test_median_statistics(self): test_data = CsvReader('Tests/Data/unit_test_median.csv').data for row in test_data: result = float(row['Result']) self.assertEqual(self.statistics.median(row['Value 1'], row['Value 2'], row['Value 3'], row['Value 4'], row['Value 5'], row['Value 6'], row['Value 7'], row['Value 8'], row['Value 9']), result) self.assertEqual(self.statistics.result, result) def test_mode_statistics(self): test_data = CsvReader('Tests/Data/unit_test_mode.csv').data for row in test_data: result = int(row['Result']) self.assertEqual(self.statistics.mode(row['Value 1'], row['Value 2'], row['Value 3'], row['Value 4'], row['Value 5'], row['Value 6'], row['Value 7'], row['Value 8']), result) self.assertEqual(self.statistics.result, result)
class MyTestCase(unittest.TestCase): def setUp(self): self.statistics = Statistics() def test_instantiate_calculator(self): self.assertIsInstance(self.statistics, Statistics) def test_decorator_calculator(self): self.assertIsInstance(self.statistics, Statistics) def test_statistics_calculator_return_variance(self): data = [1, 2, 3, 4, 5, 6] result = self.statistics.variance(data) self.assertEqual(2.9166666666666665, result) def test_statistics_calculator_return_quartiles(self): data = [2, 6, 7] result = self.statistics.quartile(data, 0.25, 0, None) self.assertEqual(4, result) def test_statistics_calculator_return_skew(self): data = [3, 5, 6, 5, 3, 2, 1, 40] result = self.statistics.skew(data, None, None) self.assertEqual(2.734386516915545, result)
class MyTestCase(unittest.TestCase): def setUp(self) -> None: self.testData = getRandomNums(1, 1, 100, 20) self.statistics = Statistics() def test_instantiate_calculator(self): self.assertIsInstance(self.statistics, Statistics) def test_mean_calculator(self): mean = self.statistics.mean(self.testData) self.assertEqual(mean, 38.95) def test_median_calculator(self): med = self.statistics.median(self.testData) self.assertEqual(med, 27.5) def test_mode_calculator(self): theMode = self.statistics.mode(self.testData) self.assertEqual(theMode, 2) def test_meanDev_calculator(self): meandev = self.statistics.meanDev(self.testData) self.assertEqual(meandev, 26.740000000000002) def test_stdDev_calculator(self): std = self.statistics.stdDev(self.testData) self.assertEqual(std, 29.052495589880053)
class MyTestCase(unittest.TestCase): def setUp(self): self.statistics = Statistics() def test_instantiate_calculator(self): self.assertIsInstance(self.statistics, Statistics) def test_decorator_calculator(self): self.assertIsInstance(self.statistics, Statistics) # Test Mean def test_statistics_calculator_return_mean(self): data = [1, 2, 3, 4, 5] result = self.statistics.mean(data) self.assertEqual(3, result) # Test Mode def test_statistics_calculator_return_mode(self): data = [1, 2, 3, 3, 4, 5] result = self.statistics.mode(data) self.assertEqual(3, result) def test_statistics_calculator_return_NoMode(self): data = [1, 2, 3, 4, 5] result = self.statistics.mode(data) self.assertEqual('no mode', result) # Test Median def test_statistics_calculator_return_median(self): data = [2, 4, 6, 8, 10] result = self.statistics.median(data) self.assertEqual(6, result)
class MyTestCase(unittest.TestCase): def setUp(self) -> None: self.statistics = Statistics() #def test_instantiate_calculator(self): #self.assertIsInstance(self.statistics, Statistics) def test_mean(self): test_data = CsvReader("/Tests/Data/Mean.csv").data for row in test_data: #result = float(row['Result']) self.assertEqual( self.statistics.mean(row['Value 1'], row['Value 2']), float(row['Result'])) self.assertEqual(self.statistics.result, float(row['Result'])) def test_median(self): test_data = CsvReader("/Tests/Data/Median.csv").data for row in test_data: #result = float(row['Result']) self.assertEqual( self.statistics.median(row['Value 1'], row['Value 2'], row['Value 3'], row['Value 4']), float(row['Result'])) self.assertEqual(self.statistics.result, float(row['Result']))
def setUp(self) -> None: #seed(5) self.statistics = Statistics() self.testData0 = random_code() self.testData1 = random_code_no_seed() self.testData2 = random_select() self.testData3 = random_select_no_seed() self.testZ = zValues(self.testData0) self.testZscore = zValues(self.testData0)
def setUp(self) -> None: self.testData = random_code() self.testData2 = random_code2() self.statistics = Statistics() # self.testData1 = random_code_withoutSeed() self.testZ = z_values(self.testData) self.testSystematic = Systematic(self.testData) self.testZscore = z_values(self.testData)
def setUp(self) -> None: random.seed(5) self.randomData = [] i = 0 while i < 6: self.randomData.append(random.randint(1, 100)) i += 1 #pprint.pprint(self.randomData) #[80, 33, 95, 46, 89, 95] self.statistics = Statistics()
def setUp(self) -> None: '''seed(5) self.testData = randint(0, 10, 20)''' random.seed(5) self.randomData = [] i = 0 while i < 6: self.randomData.append(random.randint(1, 100)) i += 1 #pprint.pprint(self.randomData) self.statistics = Statistics()
class MyTestCase(unittest.TestCase): def setUp(self) -> None: random.seed(5) self.randomData = [] i = 0 while i < 6: self.randomData.append(random.randint(1, 100)) i += 1 #pprint.pprint(self.randomData) #[80, 33, 95, 46, 89, 95] self.statistics = Statistics() def test_instantiate_calculator(self): self.assertIsInstance(self.statistics, Statistics) def test_mean_calculator(self): mean = self.statistics.mean([2, 4, 6, 8, 10]) self.assertEqual(mean, 6) def test_median_calculator(self): median = self.statistics.median([2, 4, 6, 8, 10]) self.assertEqual(median, 6) def test_mode_calculator(self): mode = self.statistics.mode([22, 33, 44, 44, 53]) self.assertEqual(mode, [44]) def test_variance_calculator(self): variance = self.statistics.variance(self.randomData) self.assertEqual(variance, 2235.5) def test_standard_deviation_calculator(self): standard_deviation = self.statistics.standard_deviation(self.randomData) self.assertEqual(standard_deviation, 47.281074437876306) def test_quartliles_statistics(self): quartiles = self.statistics.quartile(self.randomData) self.assertEqual(quartiles, (54.5, 84.5, 93.5)) def test_skewness_statisitcs(self): skewness = self.statistics.skewness(self.randomData) self.assertEqual(skewness, -0.4653024547677381) def test_samplecorrelation_statistics(self): correlation = self.statistics.sampleCorrelation(self.randomData, self.randomData) #should just be 1? self.assertEqual(correlation, 1.6112726459405051) def test_zscore_statisitcs(self): zscore = self.statistics.zScore(self.randomData) self.assertEqual(zscore, 0.4653024547677381) def test_meandeviation_statisitcs(self): meanDeviation = self.statistics.mean_deviation(self.randomData) self.assertEqual(meanDeviation, 2235.5)
def setUp(self) -> None: seed(5) self.testData = [] for i in range(0, 10): num = random.randint(0, 15) self.testData.append(num) self.mean_value = statistics.mean(self.testData) self.median_value = statistics.median(self.testData) self.mode_value = statistics.mode(self.testData) self.variance_value = statistics.variance(self.testData) self.standard_deviation_value = statistics.stdev(self.testData) self.statistics = Statistics()
class MyTestCase(unittest.TestCase): def setUp(self) -> None: self.statistics = Statistics('Data/unit_test_variance_pop_prop.csv') def test_sample_mean(self): mean_data = CsvReader('Data/unit_test_variance_pop_prop.csv').data for d in mean_data: data_list = [] first_val = int(d['Value 1']) data_list.append(first_val) second_val = int(d['Value 2']) data_list.append(second_val) third_val = int(d['Value 3']) data_list.append(third_val) four_val = int(d['Value 4']) data_list.append(four_val) five_val = int(d['Value 5']) self.assertAlmostEqual( self.statistics.variance_pop_proportion(data_list), float(d['Result']), places=2) self.assertAlmostEqual(self.statistics.result, float(d['Result']), places=3)
class MyTestCase(unittest.TestCase): def setUp(self) -> None: self.statistics = Statistics( filepath='Data/unit_test_confidence_interval.csv') def test_sample_mean(self): try: mean_data = CsvReader( 'Data/unit_test_confidence_interval.csv').data for d in mean_data: data_list = [] first_val = int(d['Value 1']) data_list.append(first_val) second_val = int(d['Value 2']) data_list.append(second_val) third_val = int(d['Value 3']) data_list.append(third_val) fourth_val = int(d['Value 4']) data_list.append(fourth_val) fifth_val = int(d['Value 5']) data_list.append(fifth_val) six_val = int(d['Value 6']) self.assertAlmostEqual( self.statistics.confidence_interval(data_list, six_val), int(d['Result'])) self.assertAlmostEqual(self.statistics.result, int(d['Result'])) except: FileNotFoundError("Error. File was not found")
class MyTestCase(unittest.TestCase): def setUp(self) -> None: self.statistics = Statistics('Data/unit_test_median.csv') def test_sample_mean(self): try: mean_data = CsvReader('Data/unit_test_median.csv').data for d in mean_data: data_list = [] first_val = int(d['Value 1']) data_list.append(first_val) second_val = int(d['Value 2']) data_list.append(second_val) third_val = int(d['Value 3']) data_list.append(third_val) fourth_val = int(d['Value 4']) data_list.append(fourth_val) fifth_val = int(d['Value 5']) data_list.append(fifth_val) six_val = int(d['Value 6']) data_list.append(six_val) seven_val = int(d['Value 7']) data_list.append(seven_val) eight_val = int(d['Value 8']) data_list.append(eight_val) nine_val = int(d['Value 9']) data_list.append(nine_val) self.assertAlmostEqual(self.statistics.median(data_list), int(d['Result'])) self.assertAlmostEqual(self.statistics.result, int(d['Result'])) except: FileNotFoundError("Error. File was not found")
class MyTestCase(unittest.TestCase): def setUp(self) -> None: self.statistics = Statistics('Data/unit_test_standardized_score.csv') def test_sample_mean(self): mean_data = CsvReader('Data/unit_test_standardized_score.csv').data for d in mean_data: data_list = [] first_val = int(d['Value 1']) second_val = int(d['Value 2']) data_list.append(second_val) third_val = int(d['Value 3']) data_list.append(third_val) fourth_val = int(d['Value 4']) self.assertAlmostEqual(self.statistics.standardized_score( first_val, data_list, fourth_val), float(d['Result']), places=3) self.assertAlmostEqual(self.statistics.result, float(d['Result']), places=3)
class MyTestCase(unittest.TestCase): def setUp(self) -> None: self.statistics = Statistics('Data/unit_test_population_correlation_coefficient.csv') def test_sample_mean(self): mean_data = CsvReader('Data/unit_test_population_correlation_coefficient.csv').data for d in mean_data: x_vals = [] y_vals = [] X1 = int(d['X1']) x_vals.append(X1) Y1 = int(d['Y1']) y_vals.append(Y1) X2 = int(d['X2']) x_vals.append(X2) Y2 = int(d['Y2']) y_vals.append(Y2) X3 = int(d['X3']) x_vals.append(X3) Y3 = int(d['Y3']) y_vals.append(Y3) X4 = int(d['X4']) x_vals.append(X4) Y4 = int(d['Y4']) y_vals.append(Y4) X5 = int(d['X5']) x_vals.append(X5) Y5 = int(d['Y5']) y_vals.append(Y5) self.assertAlmostEqual(self.statistics.population_corre_coefficient(x_vals, y_vals), float(d['Result']), places=3) self.assertAlmostEqual(self.statistics.result, float(d['Result']), places=3)
class MyTestCase(unittest.TestCase): def setUp(self) -> None: self.statistics = Statistics('Data/unit_test_variance_sample_prop.csv') def test_sample_mean(self): try: mean_data = CsvReader( 'Data/unit_test_variance_sample_prop.csv').data for d in mean_data: data_list = [] first_val = int(d['Value 1']) data_list.append(first_val) second_val = int(d['Value 2']) data_list.append(second_val) third_val = int(d['Value 3']) data_list.append(third_val) fourth_val = int(d['Value 4']) data_list.append(fourth_val) self.assertEqual( self.statistics.variance_sample_proportion(data_list), int(d['Result']), places=2) self.assertEqual(self.statistics.result, int(d['Result']), places=2) except: FileNotFoundError("Error. File was not found")
class MyTestCase(unittest.TestCase): def setUp(self) -> None: self.statistics = Statistics('Tests/Data/UnitTestStats.csv') def test_instantiate_calculator(self): self.assertIsInstance(self.statistics, Statistics) def test_decorator_calculator(self): self.assertIsInstance(self.statistics, Statistics) def test_mean_statistics(self): test_data = CsvReader('Tests/Data/UnitTestStats.csv').data first_row = ([i for i in test_data if i['Mean'] != ''])[0] mean_value = float(first_row['Mean']) self.assertEqual(self.statistics.mean(), mean_value) def test_sample_mean_statistics(self): test_data = CsvReader('Tests/Data/UnitTestStats.csv').data first_row = ([i for i in test_data if i['Sample_Mean'] != ''])[0] sample_mean_value = float(first_row['Sample_Mean']) self.assertEqual(self.statistics.sample_mean(), sample_mean_value) def test_median_statistics(self): test_data = CsvReader('Tests/Data/UnitTestStats.csv').data first_row = ([i for i in test_data if i['Median'] != ''])[0] median_value = float(first_row['Median']) self.assertEqual(self.statistics.median(), median_value) def test_mode_statistics(self): test_data = CsvReader('Tests/Data/UnitTestStats.csv').data first_row = ([i for i in test_data if i['Mode'] != ''])[0] mode_value = float(first_row['Mode']) self.assertEqual(self.statistics.mode(), str(mode_value)) def test_pv_statistics(self): test_data = CsvReader('Tests/Data/UnitTestStats.csv').data first_row = ([i for i in test_data if i['Pop_Var'] != ''])[0] pop_var = float(first_row['Pop_Var']) self.assertEqual(self.statistics.pv(), pop_var) def test_psd_statistics(self): test_data = CsvReader('Tests/Data/UnitTestStats.csv').data first_row = ([i for i in test_data if i['Pop_Std_Dev'] != ''])[0] pop_std_dev = float(first_row['Pop_Std_Dev']) self.assertEqual(self.statistics.psd(), pop_std_dev) def test_pcc_statistics(self): test_data = CsvReader('Tests/Data/UnitTestStats.csv').data first_row = ([i for i in test_data if i['Pop_Cor_Coef'] != ''])[0] pop_cor_coef = float(first_row['Pop_Cor_Coef']) self.assertEqual(self.statistics.pcc(), pop_cor_coef) def test_zscore_statistics(self): test_data = CsvReader('Tests/Data/UnitTestStats.csv').data first_row = ([i for i in test_data if i['Z_Score'] != ''])[0] z_score = float(first_row['Z_Score']) self.assertEqual(self.statistics.z(), z_score)
class MyTestCase(unittest.TestCase): def setUp(self) -> None: seed(5) self.testData = randint(0, 10, 20) self.statistics = Statistics() def test_instantiate_calculator(self): self.assertIsInstance(self.statistics, Statistics) def test_mean_calculator(self): mean = self.statistics.mean(self.testData) self.assertEqual(mean, 4.25)
class MyTestCase(unittest.TestCase): def setUp(self) -> None: self.statistics = Statistics() def test_instantiate_calculator(self): self.assertIsInstance(self.statistics, Statistics) def test_mean_statistics(self): test_data = CsvReader('Tests/Data/UnitTestStats.csv').data for row in test_data: result = 'mean' self.assertEqual(self.statistics.mean(self.data, result))
class MyTestCase(unittest.TestCase): def setUp(self) -> None: self.testData = getRandomNums(9, 1, 10, 10) self.statistics = Statistics() def test_instantiate_statistics_calculator(self): self.assertIsInstance(self.statistics, Statistics) def test_statistics_mean(self): mean = self.statistics.mean(self.testData) self.assertEqual(mean, 5.9) print(self.testData)
class MyTestCase(unittest.TestCase): def setUp(self) -> None: self.testData = [ 813, 731, 560, 32, 361, 41, 461, 450, 317, 976, 6, 99, 99, 601, 45, 209, 994, 100, 49, 916 ] self.statistics = Statistics() def test_instantiate_calculator(self): self.assertIsInstance(self.statistics, Statistics) def test_mean_calculator(self): mean = self.statistics.mean(self.testData) self.assertEqual(mean, statistics.mean(self.testData)) def test_median_calculator(self): median = self.statistics.median(self.testData) self.assertEqual(median, statistics.median(self.testData)) def test_mode_calculator(self): mode = self.statistics.mode(self.testData) self.assertEqual(mode, statistics.mode(self.testData)) def test_variance_calculator(self): variance = self.statistics.variance(self.testData) self.assertEqual(variance, statistics.variance(self.testData)) def test_stdev_calculator(self): stdev = self.statistics.stdev(self.testData) self.assertEqual(stdev, statistics.stdev(self.testData)) def test_zscore_calculator(self): zscore = self.statistics.zscore(self.testData) self.assertEqual(zscore, stats_zscore(self.testData))
def setUp(self) -> None: random.seed(5) #self.testData = [0,1,2,3,4,5,6,6] #randint(0, 10, 20) self.statistics = Statistics() self.testData = [] self.zscoredata = [] dataset_reader = CsvReader('Tests/Dataset.csv').data for row in dataset_reader: self.testData.append(int(row['DataSet'])) stat_answers = CsvReader('Tests/UnitTestStatAnswers.csv').data for row in stat_answers: self.mean = float(row['mean']) self.median = float(row['median']) self.mode = float(row['mode']) self.variance = float(row['variance']) self.stddev = float(row['stddev']) zscore_reader = CsvReader('Tests/UnitTestZScoreAnswers.csv').data for row in zscore_reader: self.zscoredata.append(float(row['zscore']))
class MyTestCase(unittest.TestCase): def setUp(self): self.statistics = Statistics() def test_instantiate_calculator(self): self.assertIsInstance(self.statistics, Statistics) def test_decorator_calculator(self): self.assertIsInstance(self.statistics, Statistics) # Test Mean ------------------------------------------------------------- def test_statistics_calculator_return_mean(self): data = [1, 2, 3, 4, 5] result = self.statistics.mean(data) self.assertEqual(3, result)
class MyTestCase(unittest.TestCase): def setUp(self) -> None: random.seed(5) #self.testData = [0,1,2,3,4,5,6,6] #randint(0, 10, 20) self.statistics = Statistics() self.testData = [] self.zscoredata = [] dataset_reader = CsvReader('Tests/Dataset.csv').data for row in dataset_reader: self.testData.append(int(row['DataSet'])) stat_answers = CsvReader('Tests/UnitTestStatAnswers.csv').data for row in stat_answers: self.mean = float(row['mean']) self.median = float(row['median']) self.mode = float(row['mode']) self.variance = float(row['variance']) self.stddev = float(row['stddev']) zscore_reader = CsvReader('Tests/UnitTestZScoreAnswers.csv').data for row in zscore_reader: self.zscoredata.append(float(row['zscore'])) def test_instantiate_calculator(self): self.assertIsInstance(self.statistics, Statistics) def test_mean_calculator(self): mean = self.statistics.mean(self.testData) self.assertEqual(mean, self.mean) def test_median_calculator(self): median = self.statistics.median(self.testData) self.assertEqual(median, self.median) def test_mode_calculator(self): mode = self.statistics.mode(self.testData) self.assertEqual(mode, self.mode) def test_stddev_calculator(self): stddev = self.statistics.stddev(self.testData) self.assertEqual(stddev, self.stddev) def test_variance_calculator(self): variance = self.statistics.variance(self.testData) self.assertEqual(variance, self.variance) def test_zscore_calculator(self): ZScore = self.statistics.zscore(self.testData) for i in range(0, len(ZScore) - 1): self.assertEqual(round(ZScore[i], 4), round(self.zscoredata[i], 4))
class MyTestCase(unittest.TestCase): def setUp(self) -> None: seed(5) self.testData = [] for i in range(0, 10): num = random.randint(0, 15) self.testData.append(num) self.mean_value = statistics.mean(self.testData) self.median_value = statistics.median(self.testData) self.mode_value = statistics.mode(self.testData) self.variance_value = statistics.variance(self.testData) self.standard_deviation_value = statistics.stdev(self.testData) self.statistics = Statistics() def test_instantiate_calculator(self): self.assertIsInstance(self.statistics, Statistics) def test_mean_calculator(self): mean = self.statistics.stats_mean(self.testData) self.assertEqual(mean, self.mean_value) def test_median_calculator(self): median = self.statistics.stats_median(self.testData) self.assertEqual(median, self.median_value) def test_mode_calculator(self): mode = self.statistics.stats_mode(self.testData) self.assertEqual(mode, self.mode_value) def test_median_calculator(self): median = self.statistics.stats_median(self.testData) self.assertEqual(median, self.median_value) def test_mode_calculator(self): mode = self.statistics.stats_mode(self.testData) self.assertEqual(mode, self.mode_value) def test_variance_calculator(self): variance = self.statistics.stats_variance(self.testData) self.assertEqual(variance, round((self.variance_value), 1)) def test_standard_deviation_calculator(self): standard_deviation = self.statistics.stats_standard_deviation( self.testData) self.assertEqual(standard_deviation, round((self.standard_deviation_value), 1))
class MyTestCase(unittest.TestCase): def setUp(self) -> None: self.statistics = Statistics() test_data = CsvReader('Tests/CSVFiles/TestCaseData.csv').data test_answer = CsvReader('Tests/CSVFiles/TestAnswers.csv').data zscore_ans = CsvReader('Tests/CSVFiles/ZScores.csv').data zdata = [float(row['zscore']) for row in zscore_ans] column1 = [int(row['Value 1']) for row in test_data] column2 = [int(row['Value 2']) for row in test_data] def test_instantiate_calculator(self): self.assertIsInstance(self.statistics, Statistics) def test_mean_statistics(self): global row for row in self.test_answer: pprint(row["mean"]) self.assertEqual(self.statistics.mean(self.column1), float(row['mean'])) self.assertEqual(self.statistics.result, float(row['mean'])) def test_median_statistics(self): global row for row in self.test_answer: pprint(row["median"]) self.assertEqual(self.statistics.median(self.column1), float(row['median'])) self.assertEqual(self.statistics.result, float(row['median'])) def test_mode_statistics(self): for row in self.test_answer: pprint(row["mode"]) self.assertEqual(self.statistics.mode(self.column1), float(row['mode'])) self.assertEqual(self.statistics.result, float(row['mode'])) def test_standard_deviation_statistics(self): for row in self.test_answer: pprint(row["stddev"]) self.assertEqual(self.statistics.stddev(self.column1), float(row['stddev'])) self.assertEqual(self.statistics.result, float(row['stddev'])) def test_variance_statistics(self): for row in self.test_answer: pprint(row['variance']) self.assertEqual(self.statistics.variance(self.column1), float(row['variance'])) self.assertEqual(self.statistics.result, float(row['variance'])) def test_correlation_statistics(self): for row in self.test_answer: pprint(row['correlation']) self.assertEqual(self.statistics.correlation(self.column1, self.column2), float(row['correlation'])) self.assertEqual(self.statistics.result, float(row['correlation']))
class MyTestCase(unittest.TestCase): def setUp(self) -> None: self.statistics = Statistics('Data/unit_test_mean.csv') def test_sample_mean(self): mean_data = CsvReader('Data/unit_test_mean.csv').data for d in mean_data: data_list = [] first_val = int(d['Value 1']) data_list.append(first_val) second_val = int(d['Value 2']) data_list.append(second_val) third_val = int(d['Value 3']) data_list.append(third_val) self.assertAlmostEqual(self.statistics.population_mean(data_list), int(d['Result'])) self.assertAlmostEqual(self.statistics.result, int(d['Result']))
class MyTestCase(unittest.TestCase): def setUp(self): self.random = Random() self.statistics = Statistics() def test_instantiate_calculator(self): self.assertIsInstance(self.random, Random) def test_decorator_calculator(self): self.assertIsInstance(self.random, Random) # Test Random ------------------------------------------------------------- def test_random_int_seed(self): testdata = self.random.Random_int_nums(1, 100, 5, 5) mean = self.statistics.mean(testdata) self.assertEqual(mean, 48.2) def test_random_int(self): testdata = self.random.Random_int_nums(1, 100, 5, None) testdata2 = self.random.Random_int_nums(1, 100, 5, None) mean = self.statistics.mean(testdata) mean2 = self.statistics.mean(testdata2) self.assertNotEqual(mean, mean2) def test_random_float_seed(self): testdata = self.random.Random_float_nums(1.0, 100.0, 5, 3) testdata2 = self.random.Random_float_nums(1.0, 100.0, 5, 3) mean = self.statistics.mean(testdata) mean2 = self.statistics.mean(testdata2) self.assertAlmostEqual(mean, mean2) def test_random_float(self): testdata = self.random.Random_float_nums(1.0, 100.0, 5, None) testdata2 = self.random.Random_float_nums(1.0, 100.0, 5, None) mean = self.statistics.mean(testdata) mean2 = self.statistics.mean(testdata2) self.assertNotEqual(mean, mean2)
def setUp(self): self.statistics = Statistics()