def test_mixture_api():
# Check basic API
p1 = Normal(mu=0.0, sigma=T.constant(1.0))
p2 = Normal(mu=1.0, sigma=2.0)
m = Mixture(components=[p1, p2], weights=[0.25])
assert len(m.components) == 2
assert len(m.weights) == 2
assert len(m.parameters_) == 4
assert len(m.constants_) == 1
assert len(m.observeds_) == 0
assert p1.mu in m.parameters_
assert p1.sigma in m.constants_
assert p2.mu in m.parameters_
assert p2.sigma in m.parameters_
assert m.X == p1.X
assert m.X == p2.X
assert m.ndim == p1.ndim
assert m.ndim == p2.ndim
m = Mixture(components=[p1, p2])
w = m.compute_weights()
assert_array_equal(w, [0.5, 0.5])
y = T.dscalar(name="y")
w1 = T.constant(0.25)
w2 = y * 2
m = Mixture(components=[p1, p2], weights=[w1, w2])
assert y in m.observeds_
# Check errors
assert_raises(ValueError, Mixture,
components=[p1, p1, p1], weights=[1.0])
def test_mixture_api():
# Check basic API
p1 = Normal(mu=0.0, sigma=T.constant(1.0))
p2 = Normal(mu=1.0, sigma=2.0)
m = Mixture(components=[p1, p2], weights=[0.25])
assert len(m.components) == 2
assert len(m.weights) == 2
assert len(m.parameters_) == 4
assert len(m.constants_) == 1
assert len(m.observeds_) == 0
assert p1.mu in m.parameters_
assert p1.sigma in m.constants_
assert p2.mu in m.parameters_
assert p2.sigma in m.parameters_
assert m.X == p1.X
assert m.X == p2.X
assert m.ndim == p1.ndim
assert m.ndim == p2.ndim
m = Mixture(components=[p1, p2])
w = m.compute_weights()
assert_array_equal(w, [0.5, 0.5])
y = T.dscalar(name="y")
w1 = T.constant(0.25)
w2 = y * 2
m = Mixture(components=[p1, p2], weights=[w1, w2])
assert y in m.observeds_
# Check errors
assert_raises(ValueError, Mixture, components=[p1, p1, p1], weights=[1.0])
