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")