def test_12_34_and_ones(self):
"""Compute mi for identical arrays [[1, 2], [2, 4]]."""
L = [[1, 2], [3, 4]]
self.x_dataframe = pd.DataFrame(np.array(L))
self.y_dataframe = pd.DataFrame(np.ones((2, 2)))
self.clr_matrix, self.mi_matrix = mi.MIDriver().run(
self.x_dataframe, self.y_dataframe)
self.assertTrue(np.isnan(self.clr_matrix.values).all())
def test_mixed(self):
"""Compute mi for mixed arrays."""
L = [[1, 2, 1], [3, 4, 6]]
L2 = [[3, 7, 1], [9, 0, 2]]
self.x_dataframe = pd.DataFrame(np.array(L))
self.y_dataframe = pd.DataFrame(np.array(L2))
self.clr_matrix, self.mi_matrix = mi.MIDriver().run(
self.x_dataframe, self.y_dataframe)
expected = np.array([[0, 1], [1, 0]])
def test_12_34_identical(self):
"""Compute mi for identical arrays [[1, 2, 1], [2, 4, 6]]."""
L = [[1, 2, 1], [3, 4, 6]]
self.x_dataframe = pd.DataFrame(np.array(L))
self.y_dataframe = pd.DataFrame(np.array(L))
self.clr_matrix, self.mi_matrix = mi.MIDriver().run(
self.x_dataframe, self.y_dataframe)
expected = np.array([[0, 1], [1, 0]])
np.testing.assert_almost_equal(self.clr_matrix.values, expected)