def test_cause_info(s):
mechanism = (0, 1)
purview = (0, 2)
answer = hamming_emd(
s.cause_repertoire(mechanism, purview),
s.unconstrained_cause_repertoire(purview))
assert s.cause_info(mechanism, purview) == answer
def test_cause_info(s):
mechanism = (0, 1)
purview = (0, 2)
answer = hamming_emd(
s.cause_repertoire(mechanism, purview),
s.unconstrained_cause_repertoire(purview),
)
assert s.cause_info(mechanism, purview) == answer
def test_emd_validates_distribution_shapes():
a = np.ones((2, 2, 2)) / 8
b = np.ones((3, 3, 3)) / 27
with pytest.raises(ValueError):
distance.hamming_emd(a, b)
def test_emd_same_distributions():
a = np.ones((2, 2, 2)) / 8
b = np.ones((2, 2, 2)) / 8
assert distance.hamming_emd(a, b) == 0.0
def test_emd_validates_distribution_shapes():
a = np.ones((2, 2, 2)) / 8
b = np.ones((3, 3, 3)) / 27
with pytest.raises(ValueError):
distance.hamming_emd(a, b)
def test_emd_same_distributions():
a = np.ones((2, 2, 2)) / 8
b = np.ones((2, 2, 2)) / 8
assert distance.hamming_emd(a, b) == 0.0
def test_effect_info(s):
mechanism = (0, 1)
purview = (0, 2)
answer = hamming_emd(s.effect_repertoire(mechanism, purview),
s.unconstrained_effect_repertoire(purview))
assert s.effect_info(mechanism, purview) == answer
