def test_caekl_2(d):
"""
Ensure that it reduces to the mutual information for bivariate
distributions reduced from multivariate.
"""
rvs = [[0], [1]]
assert I(d, rvs) == pytest.approx(J(d, rvs))
def test_mis1(d):
"""
Test that all the mutual informations match for bivariate distributions.
"""
i = I(d)
t = T(d)
b = B(d)
j = J(d)
ii = II(d)
assert i == pytest.approx(t)
assert t == pytest.approx(b)
assert b == pytest.approx(j)
assert j == pytest.approx(ii)
def test_cis2(dist):
"""
Test that the common informations are ordered correctly.
"""
k = K(dist)
j = J(dist)
b = B(dist)
c = C(dist)
g = G(dist)
f = F(dist)
m = M(dist)
assert k <= j + epsilon
assert j <= b + epsilon
assert b <= c + epsilon
assert c <= g + epsilon
assert g <= f + epsilon
assert f <= m + epsilon
def test_caekl_4(d):
"""
Test that CAEKL is always less than or equal to the normalized total
correlation.
"""
assert J(d) <= (T(d) / 3) + 1e-6
def test_caekl_3():
"""
Test a known value.
"""
d = D(['000', '011', '101', '110'], [1 / 4] * 4)
assert J(d) == pytest.approx(0.5)
def test_caekl_1(d):
"""
Ensure that it reduces to the mutual information for bivariate
distributions.
"""
assert I(d) == pytest.approx(J(d))
