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)
Ejemplo n.º 2
0
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')
Ejemplo n.º 3
0
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')
Ejemplo n.º 4
0
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')
Ejemplo n.º 5
0
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)
Ejemplo n.º 6
0
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)
Ejemplo n.º 7
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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