def test_disc_entropy_constant_vals_2d():
"""If each column in x (matrix), then H(x) = 0"""
same_val_arr_zero = np.zeros((50, 1))
same_val_arr_ones = np.ones((50, 1))
same_multi_val_arr = np.concatenate((same_val_arr_ones, same_val_arr_zero),
axis=1)
H_hat = _estimate_disc_entropy(same_multi_val_arr)
assert 0 == H_hat
def test_cont_disc_entropy_differs_cont():
"""Expect cont, disc columns to have different entropy"""
cont = asarray2d(np.arange(50)) + 0.5
epsilon = _compute_epsilon(cont)
H_cont = _estimate_cont_entropy(cont, epsilon)
H_disc = _estimate_disc_entropy(cont)
assert H_cont != H_disc
def test_disc_entropy_two_values():
"""Entropy of fair coin ~= log(2)"""
same_val_arr_zero = np.zeros((50, 1))
same_val_arr_ones = np.ones((50, 1))
diff_val_arr = np.concatenate((same_val_arr_ones, same_val_arr_zero),
axis=0)
expected_h = np.log(2)
H_hat = _estimate_disc_entropy(diff_val_arr)
assert round(abs(expected_h - H_hat), 7) == 0
def test_disc_entropy_two_values(self):
"""Entropy of fair coin ~= log(2)"""
same_val_arr_zero = np.zeros((50, 1))
same_val_arr_ones = np.ones((50, 1))
diff_val_arr = np.concatenate((same_val_arr_ones, same_val_arr_zero),
axis=0)
expected_h = np.log(2)
H_hat = _estimate_disc_entropy(diff_val_arr)
self.assertAlmostEqual(expected_h, H_hat)
def test_cont_disc_entropy_differs_disc(get_disc_columns):
"""Expect cont, disc columns to have different entropy"""
disc = asarray2d(np.arange(50))
# we run into trouble here because as disc as *actually* discrete,
# epsilon would not be calculated (it is set to some dummy value of
# -inf). instead, we patch get_disc_columns and "force" epsilon to be
# calculated
epsilon = _compute_epsilon(disc)
H_cont = _estimate_cont_entropy(disc, epsilon)
H_disc = _estimate_disc_entropy(disc)
assert H_cont != H_disc
def test_disc_entropy_constant_vals_1d():
"""If x (column vector) is constant, then H(x) = 0"""
same_val_arr_ones = np.ones((50, 1))
H_hat = _estimate_disc_entropy(same_val_arr_ones)
assert 0 == H_hat