def test_observed(self):
"""
Test observation of Bernoulli node
"""
Z = Binomial(10, 0.3)
Z.observe(10)
u = Z._message_to_child()
self.assertAllClose(u[0], 10)
Z = Binomial(10, 0.9)
Z.observe(2)
u = Z._message_to_child()
self.assertAllClose(u[0], 2)
pass
def test_observed(self):
"""
Test observation of Bernoulli node
"""
Z = Binomial(10, 0.3)
Z.observe(10)
u = Z._message_to_child()
self.assertAllClose(u[0], 10)
Z = Binomial(10, 0.9)
Z.observe(2)
u = Z._message_to_child()
self.assertAllClose(u[0], 2)
pass
def test_moments(self):
"""
Test the moments of binomial nodes.
"""
# Simple test
X = Binomial(1, 0.7)
u = X._message_to_child()
self.assertEqual(len(u), 1)
self.assertAllClose(u[0],
0.7)
# Test n
X = Binomial(10, 0.7)
u = X._message_to_child()
self.assertAllClose(u[0],
10*0.7)
# Test plates in p
n = np.random.randint(1, 10)
p = np.random.rand(3)
X = Binomial(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.rand()
X = Binomial(n, p)
u = X._message_to_child()
self.assertAllClose(u[0],
p*n)
# Test plates in p and n
n = np.random.randint(1, 10, size=(4,1))
p = np.random.rand(3)
X = Binomial(n, p)
u = X._message_to_child()
self.assertAllClose(u[0],
p*n)
# Test with beta prior
P = Beta([7, 3])
logp = P._message_to_child()[0]
p0 = np.exp(logp[0]) / (np.exp(logp[0]) + np.exp(logp[1]))
X = Binomial(1, P)
u = X._message_to_child()
self.assertAllClose(u[0],
p0)
# Test with broadcasted plates
P = Beta([7, 3], plates=(10,))
X = Binomial(5, P)
u = X._message_to_child()
self.assertAllClose(u[0] * np.ones(X.get_shape(0)),
5*p0*np.ones(10))
pass
def test_moments(self):
"""
Test the moments of binomial nodes.
"""
# Simple test
X = Binomial(1, 0.7)
u = X._message_to_child()
self.assertEqual(len(u), 1)
self.assertAllClose(u[0], 0.7)
# Test n
X = Binomial(10, 0.7)
u = X._message_to_child()
self.assertAllClose(u[0], 10 * 0.7)
# Test plates in p
n = np.random.randint(1, 10)
p = np.random.rand(3)
X = Binomial(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.rand()
X = Binomial(n, p)
u = X._message_to_child()
self.assertAllClose(u[0], p * n)
# Test plates in p and n
n = np.random.randint(1, 10, size=(4, 1))
p = np.random.rand(3)
X = Binomial(n, p)
u = X._message_to_child()
self.assertAllClose(u[0], p * n)
# Test with beta prior
P = Beta([7, 3])
logp = P._message_to_child()[0]
p0 = np.exp(logp[0]) / (np.exp(logp[0]) + np.exp(logp[1]))
X = Binomial(1, P)
u = X._message_to_child()
self.assertAllClose(u[0], p0)
# Test with broadcasted plates
P = Beta([7, 3], plates=(10, ))
X = Binomial(5, P)
u = X._message_to_child()
self.assertAllClose(u[0] * np.ones(X.get_shape(0)),
5 * p0 * np.ones(10))
pass
