class TestGaussianClass(unittest.TestCase):
def setUp(self):
self.gaussian = Gaussian(25, 2)
self.gaussian.read_data_file("numbers.txt")
def test_initialization(self):
self.assertEqual(self.gaussian.mean, 25, "incorrect mean")
self.assertEqual(self.gaussian.stdev, 2,
"incorrect standard deviation")
def test_readdata(self):
self.assertEqual(
self.gaussian.data,
[1, 3, 99, 100, 120, 32, 330, 23, 76, 44, 31],
"data not read in correctly",
)
def test_meancalculation(self):
self.assertEqual(
self.gaussian.calculate_mean(),
sum(self.gaussian.data) / float(len(self.gaussian.data)),
"calculated mean not as expected",
)
def test_stdevcalculation(self):
self.assertEqual(
round(self.gaussian.calculate_stdev(), 2),
92.87,
"sample standard deviation incorrect",
)
self.assertEqual(
round(self.gaussian.calculate_stdev(0), 2),
88.55,
"population standard deviation incorrect",
)
def test_pdf(self):
self.assertEqual(
round(self.gaussian.pdf(25), 5),
0.19947,
"pdf function does not give expected result",
)
self.gaussian.calculate_mean()
self.gaussian.calculate_stdev()
self.assertEqual(
round(self.gaussian.pdf(75), 5),
0.00429,
"pdf function after calculating mean and stdev does not give expected result",
)
def test_add(self):
gaussian_one = Gaussian(25, 3)
gaussian_two = Gaussian(30, 4)
gaussian_sum = gaussian_one + gaussian_two
self.assertEqual(gaussian_sum.mean, 55)
self.assertEqual(gaussian_sum.stdev, 5)
class TestGaussianClass(unittest.TestCase):
def setUp(self):
self.gaussian = Gaussian(25, 2)
self.gaussian.read_data_file('numbers.txt')
def test_initialization(self):
self.assertEqual(self.gaussian.mean, 25, 'incorrect mean')
self.assertEqual(self.gaussian.stdev, 2,
'incorrect standard deviation')
def test_readdata(self):
self.assertEqual(self.gaussian.data, \
[1, 3, 99, 100, 120, 32, 330, 23, 76, 44, 31], 'data not read in correctly')
def test_meancalculation(self):
self.assertEqual(
self.gaussian.calculate_mean(),
sum(self.gaussian.data) / float(len(self.gaussian.data)),
'calculated mean not as expected')
def test_stdevcalculation(self):
self.assertEqual(round(self.gaussian.calculate_stdev(), 2), 92.87,
'sample standard deviation incorrect')
self.assertEqual(round(self.gaussian.calculate_stdev(0), 2), 88.55,
'population standard deviation incorrect')
def test_pdf(self):
self.assertEqual(round(self.gaussian.pdf(25), 5), 0.19947,
'pdf function does not give expected results')
self.gaussian.calculate_mean()
self.gaussian.calculate_stdev()
self.assertEqual(
round(self.gaussian.pdf(75), 5), 0.00429,
'pdf function after calculating mean and stdev '
'does not give expected result')
def test_add(self):
gaussian_one = Gaussian(25, 3)
gaussian_two = Gaussian(30, 4)
gaussian_sum = gaussian_one + gaussian_two
self.assertEqual(gaussian_sum.mean, 55)
self.assertEqual(gaussian_sum.stdev, 5)
def test_confidenceintervals(self):
self.assertEqual(
self.gaussian.calculate_confidence_intervals(0.95),
[23.205529189316458, 132.97628899250174],
'calculate_confidence_intervals does not give'
'expected result')
self.assertEqual(
self.gaussian.calculate_confidence_intervals(0.99),
[6.123854832188144, 150.05796334963003],
'calculate_confidence_intervals does not give'
'expected result')
class TestGaussianClass(unittest.TestCase):
def setUp(self):
self.gaussian = Gaussian(25, 2)
def test_initialization(self):
self.assertEqual(self.gaussian.mean, 25, 'incorrect mean')
self.assertEqual(self.gaussian.stdev, 2,
'incorrect standard deviation')
def test_pdf(self):
self.assertEqual(round(self.gaussian.pdf(25), 5), 0.19947,
'pdf function does not give expected result')
def test_meancalculation(self):
self.gaussian.read_data_file('numbers.txt', True)
self.assertEqual(
self.gaussian.calculate_mean(),
sum(self.gaussian.data) / float(len(self.gaussian.data)),
'calculated mean not as expected')
def test_stdevcalculation(self):
self.gaussian.read_data_file('numbers.txt', True)
self.assertEqual(round(self.gaussian.stdev, 2), 92.87,
'sample standard deviation incorrect')
self.gaussian.read_data_file('numbers.txt', False)
self.assertEqual(round(self.gaussian.stdev, 2), 88.55,
'population standard deviation incorrect')
class TestGaussianClass(unittest.TestCase):
def setUp(self):
self.gaussian = Gaussian('numbers_gaussian.txt')
def test_readdata(self):
self.assertEqual(self.gaussian.data[0:7], [36, 37, 38, 38, 39, 39, 40],
'data not read in correctly')
def test_meancalculation(self):
self.assertEqual(round(self.gaussian.calculate_mean(),2),
round(sum(self.gaussian.data) / float(len(self.gaussian.data)),2),\
'calculated mean not as expected')
def test_stdevcalculation(self):
self.assertEqual(round(self.gaussian.calculate_stdev(), 2), 3.92,\
'sample standard deviation incorrect')
self.assertEqual(round(self.gaussian.calculate_stdev(0), 2), 3.90,\
'population standard deviation incorrect')
def test_pdf(self):
self.assertEqual(round(self.gaussian.pdf(40), 5), 0.03803,\
'propability density function does not give expected result')
def test_def(self):
self.assertEqual(
str(self.gaussian), "mean {}, variance {}".format(45.5, 15.36),
'parameters of the Gaussian\
not as expected')
class TestGaussianClass(unittest.TestCase):
def setUp(self):
self.gaussian = Gaussian(25, 2)
self.gaussian.read_file('numbers.txt')
def test_initialization(self):
self.assertEqual(self.gaussian.mean, 25, 'incorrect mean')
self.assertEqual(self.gaussian.stdev, 2,
'incorrect standard deviation')
def test_readdata(self):
self.assertEqual(self.gaussian.data,\
[1, 3, 99, 100, 120, 32, 330, 23, 76, 44, 31], 'data not read in correctly')
def test_meancalculation(self):
self.assertEqual(self.gaussian.calculate_mean(), 78.0909090909091,
'calculated mean not as expected')
def test_stdevcalculation(self):
self.assertEqual(round(self.gaussian.calculate_stdev(True), 2), 92.87,
'sample standard deviation incorrect')
self.assertEqual(round(self.gaussian.calculate_stdev(0), 2), 88.55,
'population standard deviation incorrect')
def test_pdf(self):
self.assertEqual(round(self.gaussian.density(25), 5), 0.19947,\
'pdf function does not give expected result')
self.gaussian.replace_stats_with_data()
self.assertEqual(round(self.gaussian.density(75), 5), 0.00429,\
'pdf function after calculating mean and stdev does not give expected result')
def test_add(self):
gaussian_one = Gaussian(25, 3)
gaussian_two = Gaussian(30, 4)
gaussian_sum = gaussian_one + gaussian_two
self.assertEqual(gaussian_sum.mean, 55)
self.assertEqual(gaussian_sum.stdev, 5)
class TestGaussianClass(unittest.TestCase):
def setUp(self):
self.gaussian = Gaussian(25, 2)
self.gaussian.read_data_file('numbers.txt')
def test_readdata(self):
self.assertEqual(self.gaussian.data,\
[1, 3, 99, 100, 120, 32, 330, 23, 76, 44, 31], 'data not read in correctly')
def test_meancalculation(self):
self.assertEqual(self.gaussian.calculate_mean(),\
sum(self.gaussian.data) / float(len(self.gaussian.data)), 'calculated mean not as expected')
def test_stdevcalculation(self):
self.gaussian.read_data_file('numbers.txt', True)
self.assertEqual(round(self.gaussian.stdev, 2), 92.87,
'sample standard deviation incorrect')
self.gaussian.read_data_file('numbers.txt', False)
self.assertEqual(round(self.gaussian.stdev, 2), 88.55,
'population standard deviation incorrect')
def test_pdf(self):
self.gaussian = Gaussian(25, 2)
self.assertEqual(round(self.gaussian.pdf(25), 5), 0.19947,\
'pdf function does not give expected result')
self.gaussian.read_data_file('numbers.txt')
self.assertEqual(round(self.gaussian.pdf(75), 5), 0.00429,\
'pdf function after calculating mean and stdev does not give expected result')
def test_add(self):
gaussian_one = Gaussian(25, 3)
gaussian_two = Gaussian(30, 4)
gaussian_sum = gaussian_one + gaussian_two
self.assertEqual(gaussian_sum.mean, 55)
self.assertEqual(gaussian_sum.stdev, 5)
from distributions import Gaussian
# initialize two gaussian distributions
gaussian_one = Gaussian(25, 3)
gaussian_two = Gaussian(30, 2)
# initialize a third gaussian distribution reading in a data efile
gaussian_three = Gaussian()
gaussian_three.read_data_file('numbers.txt')
gaussian_three.calculate_mean()
gaussian_three.calculate_stdev()
print(gaussian_one.mean)
print(gaussian_two.mean)
print(gaussian_one.stdev)
print(gaussian_two.stdev)
print(gaussian_three.mean)
print(gaussian_three.stdev)
# plot histogram of gaussian three
gaussian_three.plot_histogram_pdf()
# add gaussian_one and gaussian_two together
gaussian_one + gaussian_two
