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)