def test_random(self):
def ref_rand(size, w, mu, sigma):
component = np.random.choice(w.size, size=size, p=w)
return np.random.normal(mu[component], sigma[component], size=size)
pymc_random(
NormalMixture,
{
"w": Simplex(2),
"mu": Domain([[0.05, 2.5], [-5.0, 1.0]], edges=(None, None)),
"sigma": Domain([[1, 1], [1.5, 2.0]], edges=(None, None)),
},
extra_args={"comp_shape": 2},
size=1000,
ref_rand=ref_rand,
change_rv_size_fn=Mixture.change_size,
)
pymc_random(
NormalMixture,
{
"w": Simplex(3),
"mu": Domain([[-5.0, 1.0, 2.5]], edges=(None, None)),
"sigma": Domain([[1.5, 2.0, 3.0]], edges=(None, None)),
},
extra_args={"comp_shape": 3},
size=1000,
ref_rand=ref_rand,
change_rv_size_fn=Mixture.change_size,
)
def test_simplex():
check_vector_transform(tr.simplex, Simplex(2))
check_vector_transform(tr.simplex, Simplex(4))
check_transform(tr.simplex,
MultiSimplex(3, 2),
constructor=at.dmatrix,
test=np.zeros((2, 2)))
def test_sum_to_1():
check_vector_transform(tr.sum_to_1, Simplex(2))
check_vector_transform(tr.sum_to_1, Simplex(4))
check_jacobian_det(tr.sum_to_1, Vector(Unit, 2), at.dvector,
np.array([0, 0]), lambda x: x[:-1])