def test_dirichlet_samples():
alphas = np.array([[100, 1, 1], [1, 100, 1], [1, 1, 100]],
dtype=config.floatX)
res = get_test_value(dirichlet(alphas))
assert np.all(np.diag(res) >= res)
res = get_test_value(dirichlet(alphas, size=2))
assert res.shape == (2, 3, 3)
assert all(np.all(np.diag(r) >= r) for r in res)
for i in range(alphas.shape[0]):
res = get_test_value(dirichlet(alphas[i]))
assert np.all(res[i] > np.delete(res, [i]))
res = get_test_value(dirichlet(alphas[i], size=2))
assert res.shape == (2, 3)
assert all(np.all(r[i] > np.delete(r, [i])) for r in res)
rng_state = np.random.RandomState(
np.random.MT19937(np.random.SeedSequence(1234)))
alphas = np.array([[1000, 1, 1], [1, 1000, 1], [1, 1, 1000]],
dtype=config.floatX)
assert dirichlet.rng_fn(rng_state, alphas, None).shape == alphas.shape
assert dirichlet.rng_fn(rng_state, alphas,
size=10).shape == (10, ) + alphas.shape
assert (dirichlet.rng_fn(rng_state, alphas,
size=(10, 2)).shape == (10, 2) + alphas.shape)
def test_dirichlet_rng():
alphas = np.array([[100, 1, 1], [1, 100, 1], [1, 1, 100]],
dtype=config.floatX)
with pytest.raises(ValueError, match="shape mismatch.*"):
# The independent dimension's shape is missing from size (i.e. should
# be `(10, 2, 3)`)
dirichlet.rng_fn(None, alphas, size=(10, 2))
def dirichlet_test_fn(mean=None, cov=None, size=None, random_state=None):
if size is None:
size = ()
return dirichlet.rng_fn(random_state, alphas, size)