def test_multiple_phi(self):
vb = VariationalBayes()
gamma = array([2.0, 2.0, 2.0])
beta = self.init_beta
phi = vb.new_phi(gamma, beta, 0, 2)
prop = 0.27711205238850234
normalizer = sum(x * prop for x in beta[:, 0]) / 2.0
self.assertAlmostEqual(phi[0], beta[0][0] * prop / normalizer)
self.assertAlmostEqual(phi[1], beta[1][0] * prop / normalizer)
self.assertAlmostEqual(phi[2], beta[2][0] * prop / normalizer)
def test_multiple_phi(self):
vb = VariationalBayes()
gamma = array([2.0, 2.0, 2.0])
beta = self.init_beta
phi = vb.new_phi(gamma, beta, 0, 2)
prop = 0.27711205238850234
normalizer = sum(x * prop for x in beta[:, 0]) / 2.0
self.assertAlmostEqual(phi[0], beta[0][0] * prop / normalizer)
self.assertAlmostEqual(phi[1], beta[1][0] * prop / normalizer)
self.assertAlmostEqual(phi[2], beta[2][0] * prop / normalizer)
def test_m(self):
vb = VariationalBayes()
vb.init([], "stuck", 3)
topic_count = array([[5., 4., 3., 2., 1.], [0., 2., 2., 4., 1.],
[1., 1., 1., 1., 1.]])
new_beta = vb.m_step(topic_count)
self.assertAlmostEqual(new_beta[2][3], .2)
self.assertAlmostEqual(new_beta[0][0], .33333333)
self.assertAlmostEqual(new_beta[1][4], .11111111)
self.assertAlmostEqual(new_beta[0][3], .13333333)
def test_m(self):
vb = VariationalBayes()
vb.init([], "stuck", 3)
topic_count = array([[5., 4., 3., 2., 1.],
[0., 2., 2., 4., 1.],
[1., 1., 1., 1., 1.]])
new_beta = vb.m_step(topic_count)
self.assertAlmostEqual(new_beta[2][3], .2)
self.assertAlmostEqual(new_beta[0][0], .33333333)
self.assertAlmostEqual(new_beta[1][4], .11111111)
self.assertAlmostEqual(new_beta[0][3], .13333333)
