import unittest

import numpy as np

from dsbox.ml.outliers import median_absolute_deviation, mad_outliers, fft_outliers, double_median_absolute_deviation


class UtilsOutliersTest(unittest.TestCase):
    def test_mad(self):
        # given
        a = [1, 2, 3, 3, 4, 4, 4, 5, 5.5, 6, 6, 6.5, 7, 7, 7.5, 8, 9, 12, 52, 90]

        # when
        mad_value = median_absolute_deviation(a)

        # then
        self.assertEqual(2.0, mad_value)

    def test_double_mad(self):
        # given
        a = [1, 4, 4, 4, 5, 5, 5, 5, 7, 7, 8, 10, 16, 30]

        # when
        double_mad_values = double_median_absolute_deviation(a)

        # then
        self.assertEqual((1, 11), double_mad_values)

    def test_mad_outliers(self):
        # given
        a = np.array([1, 0, 0, 1, 10, 2, 115, 110, 32, 16, 2, 0, 15, 1])

        # when
        outliers = mad_outliers(a, z_score_coeff=1.0)

        # then
        y_true = [False, False, False, False, True, False, True, True, True, True, False, False, True, False]

        self.assertListEqual(y_true, outliers.tolist())

    def test_fft_outliers(self):
        # given
        a = np.array([1, 0, 0, 1, 10, 2, 115, 110, 32, 16, 2, 0, 15, 1])

        # when
        outliers = fft_outliers(a, freq_cut_index=12, outlier_proportion=0.2)

        # then
        y_true = [False, False, False, False, False, False, True, True, False, False, False, False, False, False]

        self.assertListEqual(y_true, outliers.tolist())


if __name__ == '__main__':
    unittest.main()

import unittest

import numpy as np

from dsbox.ml.outliers import median_absolute_deviation, mad_outliers, fft_outliers, double_median_absolute_deviation


class UtilsOutliersTest(unittest.TestCase):
    def test_mad(self):
        # given
        a = [1, 2, 3, 3, 4, 4, 4, 5, 5.5, 6, 6, 6.5, 7, 7, 7.5, 8, 9, 12, 52, 90]

        # when
        mad_value = median_absolute_deviation(a)

        # then
        self.assertEqual(2.0, mad_value)

    def test_double_mad(self):
        # given
        a = [1, 4, 4, 4, 5, 5, 5, 5, 7, 7, 8, 10, 16, 30]

        # when
        double_mad_values = double_median_absolute_deviation(a)

        # then
        self.assertEqual((1, 11), double_mad_values)

    def test_mad_outliers(self):
        # given
        a = np.array([1, 0, 0, 1, 10, 2, 115, 110, 32, 16, 2, 0, 15, 1])

        # when
        outliers = mad_outliers(a, z_score_coeff=1.0)

        # then
        y_true = [False, False, False, False, True, False, True, True, True, True, False, False, True, False]

        self.assertListEqual(y_true, outliers.tolist())

    def test_fft_outliers(self):
        # given
        a = np.array([1, 0, 0, 1, 10, 2, 115, 110, 32, 16, 2, 0, 15, 1])

        # when
        outliers = fft_outliers(a, freq_cut_index=12, outlier_proportion=0.2)

        # then
        y_true = [False, False, False, False, False, False, True, True, False, False, False, False, False, False]

        self.assertListEqual(y_true, outliers.tolist())


if __name__ == '__main__':
    unittest.main()

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