def test_B4():
""" Test B for xor distribution """
d = D(['000', '011', '101', '110'], [1 / 4] * 4)
assert_almost_equal(B(d), 2)
assert_almost_equal(B(d, [[0], [1], [2]]), 2)
assert_almost_equal(B(d, [[0], [1]], [2]), 1)
assert_almost_equal(B(d, [[0], [2]], [1]), 1)
assert_almost_equal(B(d, [[1], [2]], [0]), 1)
def test_B4():
""" Test B for xor distribution """
d = D(['000', '011', '101', '110'], [1 / 4] * 4)
assert B(d) == pytest.approx(2)
assert B(d, [[0], [1], [2]]) == pytest.approx(2)
assert B(d, [[0], [1]], [2]) == pytest.approx(1)
assert B(d, [[0], [2]], [1]) == pytest.approx(1)
assert B(d, [[1], [2]], [0]) == pytest.approx(1)
def test_tse1(i, j):
""" Test identity comparing TSE to B from Olbrich's talk """
d = n_mod_m(i, j)
indices = [[k] for k in range(i)]
tse = TSE(d)
x = 1 / 2 * sum(B(d, rv) / nCk(i, len(rv)) for rv in powerset(indices))
assert tse == pytest.approx(x)
def test_tse1():
""" Test identity comparing TSE to B from Olbrich's talk """
for i, j in zip(range(3, 6), range(2, 5)):
d = n_mod_m(i, j)
indices = [[k] for k in range(i)]
tse = TSE(d)
x = 1/2 * sum(B(d, rv)/nCk(i, len(rv)) for rv in powerset(indices))
yield assert_almost_equal, tse, x
def test_dtc_1():
"""
test max dtc
"""
d = uniform(['000', '111'])
max_dtc = MaxDualTotalCorrelationOptimizer(d, [[0], [1], [2]])
max_dtc.optimize()
dp = max_dtc.construct_dist()
assert B(dp) == pytest.approx(2.0, abs=1e-4)
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_B1():
""" Test B for two dependent variables """
d = D(['00', '11'], [1 / 2, 1 / 2])
assert_almost_equal(B(d), 1)
def test_B1():
""" Test B for two dependent variables """
d = D(['00', '11'], [1 / 2, 1 / 2])
assert B(d) == pytest.approx(1)
def test_B6():
""" Test that B fails on SDs """
d = SD([1 / 4] * 4)
with pytest.raises(ditException):
B(d)
def test_BR1():
""" Test that B + R = H """
d = D(['000', '001', '010', '100', '111'], [1 / 5] * 5)
assert B(d) + R(d) == pytest.approx(H(d))
def test_B2():
""" Test B for three dependent variables """
d = D(['000', '111'], [1 / 2, 1 / 2])
assert_almost_equal(B(d), 1)
assert_almost_equal(B(d, [[0], [1]], [2]), 0)
def test_B5():
""" Test B = I for two variables """
d = D(['00', '01', '11'], [1 / 3] * 3)
assert B(d) == pytest.approx(I(d, [0], [1]))
def test_B3():
""" Test B for four dependent variables """
d = D(['0000', '1111'], [1 / 2, 1 / 2])
assert B(d) == pytest.approx(1)
assert B(d, [[0], [1, 2]], [3]) == pytest.approx(0)
def test_B2():
""" Test B for three dependent variables """
d = D(['000', '111'], [1 / 2, 1 / 2])
assert B(d) == pytest.approx(1)
assert B(d, [[0], [1]], [2]) == pytest.approx(0)
def test_B3():
""" Test B for four dependent variables """
d = D(['0000', '1111'], [1 / 2, 1 / 2])
assert_almost_equal(B(d), 1)
assert_almost_equal(B(d, [[0], [1, 2]], [3]), 0)
def test_B5():
""" Test B = I for two variables """
d = D(['00', '01', '11'], [1 / 3] * 3)
assert_almost_equal(B(d), I(d, [0], [1]))
def test_BR1():
""" Test that B + R = H """
d = D(['000', '001', '010', '100', '111'], [1 / 5] * 5)
assert_almost_equal(B(d) + R(d), H(d))
