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################################################################################
# Copyright (C) 2014 Jaakko Luttinen
#
# This file is licensed under the MIT License.
################################################################################
"""
Unit tests for `bernoulli` module.
"""
import numpy as np
import scipy
from bayespy.nodes import (Bernoulli,
Beta,
Mixture)
from bayespy.utils import random
from bayespy.utils.misc import TestCase
class TestBernoulli(TestCase):
"""
Unit tests for Bernoulli node
"""
def test_init(self):
"""
Test the creation of Bernoulli nodes.
"""
# Some simple initializations
X = Bernoulli(0.5)
X = Bernoulli(Beta([2,3]))
# Check that plates are correct
X = Bernoulli(0.7, plates=(4,3))
self.assertEqual(X.plates,
(4,3))
X = Bernoulli(0.7*np.ones((4,3)))
self.assertEqual(X.plates,
(4,3))
X = Bernoulli(Beta([4,3], plates=(4,3)))
self.assertEqual(X.plates,
(4,3))
# Invalid probability
self.assertRaises(ValueError,
Bernoulli,
-0.5)
self.assertRaises(ValueError,
Bernoulli,
1.5)
# Inconsistent plates
self.assertRaises(ValueError,
Bernoulli,
0.5*np.ones(4),
plates=(3,))
# Explicit plates too small
self.assertRaises(ValueError,
Bernoulli,
0.5*np.ones(4),
plates=(1,))
pass
def test_moments(self):
"""
Test the moments of Bernoulli nodes.
"""
# Simple test
X = Bernoulli(0.7)
u = X._message_to_child()
self.assertEqual(len(u), 1)
self.assertAllClose(u[0],
0.7)
# Test plates in p
p = np.random.rand(3)
X = Bernoulli(p)
u = X._message_to_child()
self.assertAllClose(u[0],
p)
# 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 = Bernoulli(P)
u = X._message_to_child()
self.assertAllClose(u[0],
p0)
# Test with broadcasted plates
P = Beta([7, 3], plates=(10,))
X = Bernoulli(P)
u = X._message_to_child()
self.assertAllClose(u[0] * np.ones(X.get_shape(0)),
p0*np.ones(10))
pass
def test_mixture(self):
"""
Test mixture of Bernoulli
"""
P = Mixture([2,0,0], Bernoulli, [0.1, 0.2, 0.3])
u = P._message_to_child()
self.assertEqual(len(u), 1)
self.assertAllClose(u[0], [0.3, 0.1, 0.1])
pass
def test_observed(self):
"""
Test observation of Bernoulli node
"""
Z = Bernoulli(0.3)
Z.observe(2 < 3)
pass
def test_random(self):
"""
Test random sampling in Bernoulli node
"""
p = [1.0, 0.0]
with np.errstate(divide='ignore'):
Z = Bernoulli(p, plates=(3,2)).random()
self.assertArrayEqual(Z, np.ones((3,2))*p)
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