def test_ii3():
""" Test II and conditional II for xor """
d = Xor()
ii1 = interaction_information(d, [[0], [1], [2]], [2])
ii2 = interaction_information(d, [[0], [1]], [2])
assert ii1 == pytest.approx(0)
assert ii2 == pytest.approx(1)
def test_ii3():
""" Test II and conditional II for xor """
d = Xor()
ii1 = interaction_information(d, [[0], [1], [2]], [2])
ii2 = interaction_information(d, [[0], [1]], [2])
assert ii1 == pytest.approx(0)
assert ii2 == pytest.approx(1)
def test_ii3():
""" Test II and conditional II for xor """
d = Xor()
ii1 = interaction_information(d, [[0], [1], [2]], [2])
ii2 = interaction_information(d, [[0], [1]], [2])
assert_almost_equal(ii1, 0)
assert_almost_equal(ii2, 1)
def test_ii1():
""" Test II for giant bit distributions """
for i in range(2, 6):
outcomes = ['0'*i, '1'*i]
pmf = [1/2, 1/2]
d = D(outcomes, pmf)
yield assert_almost_equal, interaction_information(d), (-1)**i
def test_ii2(i):
""" Test II = -1^n * I for giant bit distributions """
outcomes = ['0'*i, '1'*i]
pmf = [1/2, 1/2]
d = D(outcomes, pmf)
ci = coinformation(d)
ii = interaction_information(d)
assert ii == pytest.approx((-1)**i * ci)
def test_ii2(i):
""" Test II = -1^n * I for giant bit distributions """
outcomes = ['0' * i, '1' * i]
pmf = [1 / 2, 1 / 2]
d = D(outcomes, pmf)
ci = coinformation(d)
ii = interaction_information(d)
assert ii == pytest.approx((-1)**i * ci)
def test_ii2():
""" Test II = -1^n * I for giant bit distributions """
for i in range(2, 6):
outcomes = ['0'*i, '1'*i]
pmf = [1/2, 1/2]
d = D(outcomes, pmf)
ci = coinformation(d)
ii = interaction_information(d)
yield assert_almost_equal, ii, (-1)**i * ci
def test_ii1(i):
""" Test II for giant bit distributions """
outcomes = ['0'*i, '1'*i]
pmf = [1/2, 1/2]
d = D(outcomes, pmf)
assert interaction_information(d) == pytest.approx((-1)**i)
def test_ii1(i):
""" Test II for giant bit distributions """
outcomes = ['0' * i, '1' * i]
pmf = [1 / 2, 1 / 2]
d = D(outcomes, pmf)
assert interaction_information(d) == pytest.approx((-1)**i)