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)
