def test_mixture_distribution2():
# Test when pmfs are different lengths.
d = dit.Distribution(['A', 'B'], [0.5, 0.5])
d2 = dit.Distribution(['A', 'B'], [1, 0], sort=True, trim=True)
# Fails when it checks that all pmfs have the same length.
with pytest.raises(ValueError):
dit.mixture_distribution2([d, d2], [0.5, 0.5])
def test_mixture_distribution_weights():
d = dit.Distribution(['A', 'B'], [0.5, 0.5])
d2 = dit.Distribution(['A', 'B'], [1, 0])
with pytest.raises(ditException):
dit.mixture_distribution([d, d2], [1])
with pytest.raises(ditException):
dit.mixture_distribution2([d, d2], [1])
def test_mixture_distribution2():
# Test when pmfs are different lengths.
d = dit.Distribution(['A', 'B'], [0.5, 0.5])
d2 = dit.Distribution(['A', 'B'], [1, 0], sort=True, trim=True)
# Fails when it checks that all pmfs have the same length.
with pytest.raises(ValueError):
dit.mixture_distribution2([d, d2], [0.5, 0.5])
def test_mixture_distribution_weights():
d = dit.Distribution(['A', 'B'], [0.5, 0.5])
d2 = dit.Distribution(['A', 'B'], [1, 0])
with pytest.raises(ditException):
dit.mixture_distribution([d, d2], [1])
with pytest.raises(ditException):
dit.mixture_distribution2([d, d2], [1])
def test_mixture_distribution4():
# Sample spaces are compatible.
# But pmfs have a different lengths and orders.
d = dit.Distribution(['A', 'B'], [0.5, 0.5])
d2 = dit.Distribution(['B', 'A'], [1, 0], sort=False, trim=False, sparse=True)
d2.make_sparse(trim=True)
pmf = np.array([0.25, 0.75])
d3 = dit.mixture_distribution([d, d2], [0.5, 0.5])
assert np.allclose(pmf, d3.pmf)
with pytest.raises(ValueError):
dit.mixture_distribution2([d, d2], [0.5, 0.5])
def test_mixture_distribution3():
# Sample spaces are compatible.
# But pmfs have a different order.
d = dit.Distribution(['A', 'B'], [0.5, 0.5])
d2 = dit.Distribution(['B', 'A'], [1, 0], sort=False, trim=False, sparse=False)
pmf = np.array([0.25, 0.75])
d3 = dit.mixture_distribution([d, d2], [0.5, 0.5])
assert_true(np.allclose(pmf, d3.pmf))
d3 = dit.mixture_distribution2([d, d2], [0.5, 0.5])
assert_false(np.allclose(pmf, d3.pmf))
def test_mixture_distribution3():
# Sample spaces are compatible.
# But pmfs have a different order.
d = dit.Distribution(['A', 'B'], [0.5, 0.5])
d2 = dit.Distribution(['B', 'A'], [1, 0], sort=False, trim=False, sparse=False)
pmf = np.array([0.25, 0.75])
d3 = dit.mixture_distribution([d, d2], [0.5, 0.5])
assert np.allclose(pmf, d3.pmf)
d3 = dit.mixture_distribution2([d, d2], [0.5, 0.5])
assert not np.allclose(pmf, d3.pmf)