def test_kullback_leibler_creation_calculation(self): """ Regression Test. """ self.fail("TO UPDATE") condensed_matrix = CondensedMatrix([1.0, 4.5, 7.2, 3.3, 6.8, 6.1, 8.5, 4.5, 4.6, 9.0, 1.0, 7.8, 1.0, 0.0, 6.5, 9.6, 2.9, 2.2, 4.4, 7.1, 8.0]) kl = KullbackLeiblerDivergence("pdb1", "pdb2", 5, 3, condensed_matrix) numpy.testing.assert_almost_equal( kl.get_calculated_KL_values(), (23.653473577868997, 25.657101457909057), 10)
def test_kullback_leibler_creation_calculation(self): """ Regression Test. """ self.fail("TO UPDATE") condensed_matrix = CondensedMatrix([ 1.0, 4.5, 7.2, 3.3, 6.8, 6.1, 8.5, 4.5, 4.6, 9.0, 1.0, 7.8, 1.0, 0.0, 6.5, 9.6, 2.9, 2.2, 4.4, 7.1, 8.0 ]) kl = KullbackLeiblerDivergence("pdb1", "pdb2", 5, 3, condensed_matrix) numpy.testing.assert_almost_equal( kl.get_calculated_KL_values(), (23.653473577868997, 25.657101457909057), 10)
def test_get_matrix_data(self): condensed_matrix = CondensedMatrix([ 1.0, 4.5, 7.2, 3.3, 6.8, 6.1, 8.5, 4.5, 4.6, 9.0, 1.0, 7.8, 1.0, 0.0, 6.5, 9.6, 2.9, 2.2, 4.4, 7.1, 8.0 ]) numpy.testing.assert_almost_equal(KullbackLeiblerDivergence.get_matrix_data(condensed_matrix, 0, 5),\ [ 1., 4.5, 7.2, 3.3, 8.5, 4.5, 4.6, 7.8, 1., 9.6],\ 5) numpy.testing.assert_almost_equal(KullbackLeiblerDivergence.get_matrix_data(condensed_matrix, 4, 3),\ [4.4, 7.1, 8.],\ 5)
def test_get_matrix_data(self): condensed_matrix = CondensedMatrix([1.0, 4.5, 7.2, 3.3, 6.8, 6.1, 8.5, 4.5, 4.6, 9.0, 1.0, 7.8, 1.0, 0.0, 6.5, 9.6, 2.9, 2.2, 4.4, 7.1, 8.0]) numpy.testing.assert_almost_equal(KullbackLeiblerDivergence.get_matrix_data(condensed_matrix, 0, 5),\ [ 1., 4.5, 7.2, 3.3, 8.5, 4.5, 4.6, 7.8, 1., 9.6],\ 5) numpy.testing.assert_almost_equal(KullbackLeiblerDivergence.get_matrix_data(condensed_matrix, 4, 3),\ [4.4, 7.1, 8.],\ 5)
def test_kullback_leibler_divergence_calculation(self): """ Regression Test. """ first_distribution_probs = [ 0.83, 0.1, 0.07] second_distribution_props = [0.65, 0.2, 0.15] screwed_distribution_props = [0.3, 0.0, 0.7] self.assertAlmostEqual(KullbackLeiblerDivergence.kullback_leibler_divergence_calculation(first_distribution_probs, second_distribution_props),\ 0.115749946056, 10)
def test_kullback_leibler_divergence_calculation(self): """ Regression Test. """ first_distribution_probs = [0.83, 0.1, 0.07] second_distribution_props = [0.65, 0.2, 0.15] screwed_distribution_props = [0.3, 0.0, 0.7] self.assertAlmostEqual(KullbackLeiblerDivergence.kullback_leibler_divergence_calculation(first_distribution_probs, second_distribution_props),\ 0.115749946056, 10)