def test_calculate_variance_of_single_value_list(self): variance_calc = VarianceCalc() variable_list = [12] expected = 0 actual = VarianceCalc.calculate_variance(variance_calc, variable_list) self.assertEqual(expected, actual, "variance( [12] ) = 0")
def test_calculate_variance_of_multi_value_list(self): variance_calc = VarianceCalc() variable_list = [12, 15, 75, 18, 52, 18] expected = 665.867 actual = VarianceCalc.calculate_variance(variance_calc, variable_list) self.assertAlmostEqual(expected, actual, 3, "variance( [12,15,75,18,52,18] ) = 665.867")
def test_calculate_variance_of_DRV_empty_probability_list(self): variance_calc = VarianceCalc() variable_list = [1, 2, 3, 4] probability_list = [] expected = "Error: list of probabilities must not be empty" actual = VarianceCalc.calculate_variance(variance_calc, variable_list, probability_list) self.assertEqual(expected, actual, "variance( [1,2,3,4], [] ) = Error")
def test_calculate_variance_of_DRV_single_values(self): variance_calc = VarianceCalc() variable_list = [1] probability_list = [1] expected = 0 actual = VarianceCalc.calculate_variance(variance_calc, variable_list, probability_list) self.assertEqual(expected, actual, "variance( [1], [1] ) = 0")
def test_calculate_variance_of_DRV_empty_variable_list(self): variance_calc = VarianceCalc() variable_list = [] probability_list = [0.2, 0.2, 0.1, 0.5] expected = "Error: list of random variables must not be empty" actual = VarianceCalc.calculate_variance(variance_calc, variable_list, probability_list) self.assertEqual(expected, actual, "variance( [], [0.2, 0.2, 0.1, 0.5] ) = Error")
def test_calculate_variance_of_DRV_probability_sum_less_than_one(self): variance_calc = VarianceCalc() variable_list = [1, 2, 3, 4] probability_list = [0.2, .05, 0.1, 0.5] expected = "Error: sum of probabilities must be equal to 1" actual = VarianceCalc.calculate_variance(variance_calc, variable_list, probability_list) self.assertEqual( expected, actual, "variance( [1,2,3,4], [0.2, .05, 0.1, 0.5] ) = Error")
def test_calculate_variance_of_DRV_multiple_values(self): variance_calc = VarianceCalc() variable_list = [1, 2, 3, 4, 5] probability_list = [0.1, 0.2, 0.3, 0.15, 0.25] expected = 0 actual = VarianceCalc.calculate_variance(variance_calc, variable_list, probability_list) self.assertEqual( expected, actual, "variance( [1,2,3,4,5], [0.1,0.2,0.3,0.15,0.25] ) = 0")
def test_calculate_variance_with_DRV_variable_probability_length_mismatch( self): variance_calc = VarianceCalc() variable_list = [1, 2, 3, 4, 5] probability_list = [0.2, 0.1, 0.5, 0.2] expected = "Error: variable list must be same length as probability list" actual = VarianceCalc.calculate_variance(variance_calc, variable_list, probability_list) self.assertEqual( expected, actual, "variance( [1,2,3,4,5], [0.2, 0.1, 0.5, 0.2] ) = Error") variable_list = [1, 2, 3, 4] probability_list = [0.2, 0.1, 0.5, 0.15, 0.05] actual = VarianceCalc.calculate_variance(variance_calc, variable_list, probability_list) self.assertEqual( expected, actual, "variance( [1,2,3,4], [0.2, 0.1, 0.5, 0.15, 0.05] ) = Error")
from list_parser import ListParser from mode import ModeCalc from list_storage import ListStorage from variance import VarianceCalc from binomial import BinomialCalc from median import MedianCalc from range import RangeCalc # Define static variables and objects mean_calc = MeanCalc() mode_calc = ModeCalc() # Create a list parser object list_p = ListParser() storage = ListStorage() binomial = BinomialCalc() variance = VarianceCalc() median = MedianCalc() range = RangeCalc() def main(): print( "Welcome to StatisticsCalc. You may begin calculating. Type 'help' and hit enter to view list of functions." ) # Program logic occurs inside this infinite loop while True: # Get user input from command line and store in variable user_input = raw_input('>>\t').replace(' ', '') # Create output variable
def test_calculate_variance_of_empty_list(self): variance_calc = VarianceCalc() self.assertIsNone(VarianceCalc.calculate_variance(variance_calc, []), "Variance = None")