def test_kl3(self):
x_probs = np.array([0.25, 0.20, 0, 0.55])
xy_probs = np.array([0.20, 0, 0.25, 0.55])
self.assertAlmostEqual(entropy.kullback_leiber_divergence(x_probs,
xy_probs),
float('inf'))
def test_kl2(self):
x_probs = np.array([0.04, 0.16] * 5 + [0])
xy_probs = np.array([0.02, 0.18] * 5 + [0])
dkl = 0
for i in range(len(x_probs) - 1):
div = x_probs[i] / xy_probs[i]
dkl += x_probs[i] * math.log(div, 2)
self.assertAlmostEqual(entropy.kullback_leiber_divergence(x_probs,
xy_probs),
dkl)
