def test_lower_bound(self):
"""
Test lower bound for multinomial node.
"""
# Test for a bug found in multinomial
X = Multinomial(10, [0.3, 0.5, 0.2])
l = X.lower_bound_contribution()
self.assertAllClose(l, 0.0)
pass
def test_lower_bound(self):
"""
Test lower bound for multinomial node.
"""
# Test for a bug found in multinomial
X = Multinomial(10, [0.3, 0.5, 0.2])
l = X.lower_bound_contribution()
self.assertAllClose(l, 0.0)
pass
def test_init(self):
"""
Test the creation of multinomial nodes.
"""
# Some simple initializations
X = Multinomial(10, [0.1, 0.3, 0.6])
X = Multinomial(10, Dirichlet([5, 4, 3]))
# Check that plates are correct
X = Multinomial(10, [0.1, 0.3, 0.6], plates=(3, 4))
self.assertEqual(X.plates, (3, 4))
X = Multinomial(10, 0.25 * np.ones((2, 3, 4)))
self.assertEqual(X.plates, (2, 3))
n = 10 * np.ones((3, 4), dtype=np.int)
X = Multinomial(n, [0.1, 0.3, 0.6])
self.assertEqual(X.plates, (3, 4))
X = Multinomial(n, Dirichlet([2, 1, 9], plates=(3, 4)))
self.assertEqual(X.plates, (3, 4))
# Probabilities not a vector
self.assertRaises(ValueError, Multinomial, 10, 0.5)
# Invalid probability
self.assertRaises(ValueError, Multinomial, 10, [-0.5, 1.5])
self.assertRaises(ValueError, Multinomial, 10, [0.5, 1.5])
# Invalid number of trials
self.assertRaises(ValueError, Multinomial, -1, [0.5, 0.5])
self.assertRaises(ValueError, Multinomial, 8.5, [0.5, 0.5])
# Inconsistent plates
self.assertRaises(ValueError,
Multinomial,
10,
0.25 * np.ones((2, 4)),
plates=(3, ))
# Explicit plates too small
self.assertRaises(ValueError,
Multinomial,
10,
0.25 * np.ones((2, 4)),
plates=(1, ))
pass
def test_moments(self):
"""
Test the moments of multinomial nodes.
"""
# Simple test
X = Multinomial(1, [0.7,0.2,0.1])
u = X._message_to_child()
self.assertEqual(len(u), 1)
self.assertAllClose(u[0],
[0.7,0.2,0.1])
# Test n
X = Multinomial(10, [0.7,0.2,0.1])
u = X._message_to_child()
self.assertAllClose(u[0],
[7,2,1])
# Test plates in p
n = np.random.randint(1, 10)
p = np.random.dirichlet([1,1], size=3)
X = Multinomial(n, p)
u = X._message_to_child()
self.assertAllClose(u[0],
p*n)
# Test plates in n
n = np.random.randint(1, 10, size=(3,))
p = np.random.dirichlet([1,1,1,1])
X = Multinomial(n, p)
u = X._message_to_child()
self.assertAllClose(u[0],
p*n[:,None])
# Test plates in p and n
n = np.random.randint(1, 10, size=(4,1))
p = np.random.dirichlet([1,1], size=3)
X = Multinomial(n, p)
u = X._message_to_child()
self.assertAllClose(u[0],
p*n[...,None])
# Test with Dirichlet prior
P = Dirichlet([7, 3])
logp = P._message_to_child()[0]
p0 = np.exp(logp[0]) / (np.exp(logp[0]) + np.exp(logp[1]))
p1 = np.exp(logp[1]) / (np.exp(logp[0]) + np.exp(logp[1]))
X = Multinomial(1, P)
u = X._message_to_child()
p = np.array([p0, p1])
self.assertAllClose(u[0],
p)
# Test with broadcasted plates
P = Dirichlet([7, 3], plates=(10,))
X = Multinomial(5, P)
u = X._message_to_child()
self.assertAllClose(u[0] * np.ones(X.get_shape(0)),
5*p*np.ones((10,1)))
pass
def test_moments(self):
"""
Test the moments of multinomial nodes.
"""
# Simple test
X = Multinomial(1, [0.7, 0.2, 0.1])
u = X._message_to_child()
self.assertEqual(len(u), 1)
self.assertAllClose(u[0], [0.7, 0.2, 0.1])
# Test n
X = Multinomial(10, [0.7, 0.2, 0.1])
u = X._message_to_child()
self.assertAllClose(u[0], [7, 2, 1])
# Test plates in p
n = np.random.randint(1, 10)
p = np.random.dirichlet([1, 1], size=3)
X = Multinomial(n, p)
u = X._message_to_child()
self.assertAllClose(u[0], p * n)
# Test plates in n
n = np.random.randint(1, 10, size=(3, ))
p = np.random.dirichlet([1, 1, 1, 1])
X = Multinomial(n, p)
u = X._message_to_child()
self.assertAllClose(u[0], p * n[:, None])
# Test plates in p and n
n = np.random.randint(1, 10, size=(4, 1))
p = np.random.dirichlet([1, 1], size=3)
X = Multinomial(n, p)
u = X._message_to_child()
self.assertAllClose(u[0], p * n[..., None])
# Test with Dirichlet prior
P = Dirichlet([7, 3])
logp = P._message_to_child()[0]
p0 = np.exp(logp[0]) / (np.exp(logp[0]) + np.exp(logp[1]))
p1 = np.exp(logp[1]) / (np.exp(logp[0]) + np.exp(logp[1]))
X = Multinomial(1, P)
u = X._message_to_child()
p = np.array([p0, p1])
self.assertAllClose(u[0], p)
# Test with broadcasted plates
P = Dirichlet([7, 3], plates=(10, ))
X = Multinomial(5, P)
u = X._message_to_child()
self.assertAllClose(u[0] * np.ones(X.get_shape(0)), 5 * p * np.ones(
(10, 1)))
pass