def testChi2Variance(self):
with self.cached_session():
df_v = np.array([1., 3, 5], np.float64)
expected_variances = stats.chi2.var(df_v)
chi2 = chi2_lib.Chi2(df=df_v)
self.assertEqual(chi2.variance().get_shape(), (3,))
self.assertAllClose(chi2.variance().eval(), expected_variances)
def testChi2Entropy(self):
with self.cached_session():
df_v = np.array([1., 3, 5], dtype=np.float64)
expected_entropy = stats.chi2.entropy(df_v)
chi2 = chi2_lib.Chi2(df=df_v)
self.assertEqual(chi2.entropy().get_shape(), (3,))
self.assertAllClose(chi2.entropy().eval(), expected_entropy)
def testChi2CDF(self):
with self.cached_session():
batch_size = 6
df = constant_op.constant([2.0] * batch_size, dtype=np.float64)
df_v = 2.0
x = np.array([2.5, 2.5, 4.0, 0.1, 1.0, 2.0], dtype=np.float64)
chi2 = chi2_lib.Chi2(df=df)
expected_cdf = stats.chi2.cdf(x, df_v)
cdf = chi2.cdf(x)
self.assertEqual(cdf.get_shape(), (6,))
self.assertAllClose(cdf.eval(), expected_cdf)