class MyTestCase(unittest.TestCase):
def setUp(self) -> None:
self.calculator = Calculator()
def test_zscore(self):
test_data = CsvReader('/Tests/Data/unit_test_zscore.csv').data
for row in test_data:
self.assertEqual(self.calculator.zscore(row['Value 1'],row['Value 2'],row['Value 3']), Decimal(row['Result']).quantize(Decimal('.001')))
self.assertEqual(self.calculator.result, Decimal(row['Result']).quantize(Decimal('.001')))
def test_standardized_score(self):
test_data = CsvReader('/Tests/Data/unit_test_standardized_score.csv').data
for row in test_data:
self.assertEqual(self.calculator.standardized_score(row['Value 1'],row['Value 2'],row['Value 3']), Decimal(row['Result']).quantize(Decimal('.001')))
self.assertEqual(self.calculator.result, Decimal(row['Result']).quantize(Decimal('.001')))
def test_population_correlation_coefficient(self):
test_data = CsvReader('/Tests/Data/unit_test_population_correlation_coefficient.csv').data
for row in test_data:
self.assertEqual(self.calculator.population_correlation_coefficient(row['Value 1'],row['Value 2'],row['Value 3']), Decimal(row['Result']).quantize(Decimal('.001')))
self.assertEqual(self.calculator.result, Decimal(row['Result']).quantize(Decimal('.001')))
def test_confidence_interval(self):
test_data = CsvReader('/Tests/Data/unit_test_confidence_interval.csv').data
for row in test_data:
self.assertEqual(
self.calculator.confidence_interval(row['Value 1'], row['Value 2'], row['Value 3']),
Decimal(row['Result']).quantize(Decimal('.001')))
self.assertEqual(self.calculator.result, Decimal(row['Result']).quantize(Decimal('.001')))
class MyTestCase(unittest.TestCase):
def setUp(self) -> None:
self.calculator = Calculator()
def test_mean(self):
test_data = CsvReader('./Tests/Data/unit_test_mean.csv').data
for row in test_data:
nums = [float(val) for val in row['nums'].split('_')]
result = float(row['result'])
self.assertAlmostEqual(self.calculator.population_mean(nums),
result)
self.assertAlmostEqual(self.calculator.result, result)
self.assertNotEqual(self.calculator.population_mean(nums),
result - 1)
self.assertNotEqual(self.calculator.result, result - 1)
def test_median(self):
test_data = CsvReader('./Tests/Data/unit_test_median.csv').data
for row in test_data:
nums = [float(val) for val in row['nums'].split('_')]
result = float(row['result'])
self.assertAlmostEqual(self.calculator.median(nums), result)
self.assertAlmostEqual(self.calculator.result, result)
self.assertNotEqual(self.calculator.median(nums), result - 1)
self.assertNotEqual(self.calculator.result, result - 1)
def test_mode(self):
test_data = CsvReader('./Tests/Data/unit_test_mode.csv').data
for row in test_data:
nums = [float(val) for val in row['nums'].split('_')]
result = [
float(val) for val in row['result'].split('_') if val != ''
]
self.assertAlmostEqual(self.calculator.mode(nums), result)
self.assertAlmostEqual(self.calculator.result, result)
if len(
result
) != 0: #add some other number so we can check if the mode is not equal
result.append(result[0])
else:
result.append(0)
self.assertNotEqual(self.calculator.mode(nums), result)
self.assertNotEqual(self.calculator.result, result)
def test_sample_standard_deviation(self):
test_data = CsvReader(
'./Tests/Data/unit_test_sample_standard_deviation.csv').data
for row in test_data:
nums = [float(val) for val in row['nums'].split('_')]
result = float(row['result'])
self.assertAlmostEqual(
self.calculator.sample_standard_deviation(nums), result)
self.assertAlmostEqual(self.calculator.result, result)
self.assertNotEqual(
self.calculator.sample_standard_deviation(nums), result - 1)
self.assertNotEqual(self.calculator.result, result - 1)
def test_population_standard_deviation(self):
test_data = CsvReader(
'./Tests/Data/unit_test_population_standard_deviation.csv').data
for row in test_data:
nums = [float(val) for val in row['nums'].split('_')]
result = float(row['result'])
self.assertAlmostEqual(self.calculator.population_stdev(nums),
result)
self.assertAlmostEqual(self.calculator.result, result)
self.assertNotEqual(self.calculator.population_stdev(nums),
result - 1)
self.assertNotEqual(self.calculator.result, result - 1)
def test_population_variance(self):
test_data = CsvReader(
'./Tests/Data/unit_test_population_variance.csv').data
for row in test_data:
nums = [float(val) for val in row['nums'].split('_')]
result = float(row['result'])
self.assertAlmostEqual(self.calculator.population_variance(nums),
result)
self.assertAlmostEqual(self.calculator.result, result)
self.assertNotEqual(self.calculator.population_variance(nums),
result - 1)
self.assertNotEqual(self.calculator.result, result - 1)
def test_zscore(self):
test_data = CsvReader('./Tests/Data/unit_test_zscore.csv').data
for row in test_data:
nums = [float(val) for val in row['nums'].split('_')]
sample = float(row['sample'])
result = float(row['result'])
self.assertAlmostEqual(self.calculator.zscore(nums, sample),
result)
self.assertAlmostEqual(self.calculator.result, result)
self.assertNotEqual(self.calculator.zscore(nums, sample),
result - 1)
self.assertNotEqual(self.calculator.result, result - 1)
def test_standardized_score(self):
test_data = CsvReader(
'./Tests/Data/unit_test_standardized_score.csv').data
for row in test_data:
nums = [float(val) for val in row['nums'].split('_')]
sample = float(row['sample'])
result = float(row['result'])
self.assertAlmostEqual(self.calculator.zscore(nums, sample),
result)
self.assertAlmostEqual(self.calculator.result, result)
self.assertNotEqual(self.calculator.zscore(nums, sample),
result - 1)
self.assertNotEqual(self.calculator.result, result - 1)
def test_population_correlation_coefficient(self):
test_data = CsvReader(
'./Tests/Data/unit_test_population_correlation_coefficient.csv'
).data
for row in test_data:
numsx = [float(val) for val in row['numsx'].split('_')]
numsy = [float(val) for val in row['numsy'].split('_')]
result = float(row['result'])
self.assertAlmostEqual(
self.calculator.population_correlation_coefficient(
numsx, numsy), result)
self.assertAlmostEqual(self.calculator.result, result)
self.assertNotEqual(
self.calculator.population_correlation_coefficient(
numsx, numsy), result - 1)
self.assertNotEqual(self.calculator.result, result - 1)
def test_confidence_interval(self):
test_data = CsvReader(
'./Tests/Data/unit_test_confidence_interval.csv').data
for row in test_data:
nums = [float(val) for val in row['nums'].split('_')]
sampleMean = float(row['sampleMean'])
result = [float(val) for val in row['result'].split('_')]
val = self.calculator.confidence_interval(nums, sampleMean)
self.assertAlmostEqual(val[0], result[0])
self.assertAlmostEqual(val[1], result[1])
self.assertNotEqual(val[0], result[0] - 1)
self.assertNotEqual(val[1], result[1] - 1)
def test_p_value(self):
test_data = CsvReader('./Tests/Data/unit_test_p_value.csv').data
for row in test_data:
nums = [float(val) for val in row['nums'].split('_')]
hypothesisMean = float(row['hypothesisMean'])
populationStdev = float(row['populationStdev'])
result = float(row['result'])
self.assertAlmostEqual(
self.calculator.p_value(nums, hypothesisMean, populationStdev),
result)
self.assertAlmostEqual(self.calculator.result, result)
self.assertNotEqual(
self.calculator.p_value(nums, hypothesisMean, populationStdev),
result - 1)
self.assertNotEqual(self.calculator.result, result - 1)
def test_proportion(self):
test_data = CsvReader('./Tests/Data/unit_test_proportion.csv').data
for row in test_data:
a = float(row['a'])
b = float(row['b'])
result = float(row['result'])
self.assertAlmostEqual(self.calculator.proportion(a, b), result)
self.assertAlmostEqual(self.calculator.result, result)
self.assertNotEqual(self.calculator.proportion(a, b), result - 1)
self.assertNotEqual(self.calculator.result, result - 1)
def test_sample_mean(self):
test_data = CsvReader('./Tests/Data/unit_test_sample_mean.csv').data
for row in test_data:
nums = [float(val) for val in row['nums'].split('_')]
result = float(row['result'])
self.assertAlmostEqual(self.calculator.population_mean(nums),
result)
self.assertAlmostEqual(self.calculator.result, result)
self.assertNotEqual(self.calculator.population_mean(nums),
result - 1)
self.assertNotEqual(self.calculator.result, result - 1)
def test_variance_of_sample_proportion(self):
test_data = CsvReader(
'./Tests/Data/unit_test_variance_of_sample_proportion.csv').data
for row in test_data:
nums = [float(val) for val in row['nums'].split('_')]
result = float(row['result'])
self.assertAlmostEqual(
self.calculator.variance_of_sample_proportion(nums), result)
self.assertAlmostEqual(self.calculator.result, result)
self.assertNotEqual(
self.calculator.variance_of_sample_proportion(nums),
result - 1)
self.assertNotEqual(self.calculator.result, result - 1)
def test_variance_of_population_proportion(self):
test_data = CsvReader(
'./Tests/Data/unit_test_variance_of_population_proportion.csv'
).data
for row in test_data:
nums = [float(val) for val in row['nums'].split('_')]
result = float(row['result'])
self.assertAlmostEqual(
self.calculator.variance_of_population_proportion(nums),
result)
self.assertAlmostEqual(self.calculator.result, result)
self.assertNotEqual(
self.calculator.variance_of_population_proportion(nums),
result - 1)
self.assertNotEqual(self.calculator.result, result - 1)
