def testComputeCovAgainstNumpy(self):
with tf_ops.Graph().as_default(), self.test_session() as sess:
npr.seed(0)
random_seed.set_random_seed(200)
x = npr.randn(100, 3)
cov = ff.compute_cov(array_ops.constant(x))
np_cov = np.dot(x.T, x) / x.shape[0]
self.assertAllClose(sess.run(cov), np_cov)
def testComputeCovAgainstNumpy(self):
with tf_ops.Graph().as_default(), self.test_session() as sess:
npr.seed(0)
random_seed.set_random_seed(200)
x = npr.randn(100, 3)
cov = ff.compute_cov(array_ops.constant(x))
np_cov = np.dot(x.T, x) / x.shape[0]
self.assertAllClose(sess.run(cov), np_cov)
def testComputeCovAgainstNumpyWithAlternativeNormalizer(self):
with tf_ops.Graph().as_default(), self.test_session() as sess:
npr.seed(0)
random_seed.set_random_seed(200)
normalizer = 10.
x = npr.randn(100, 3)
cov = ff.compute_cov(array_ops.constant(x), normalizer=normalizer)
np_cov = np.dot(x.T, x) / normalizer
self.assertAllClose(sess.run(cov), np_cov)
def testComputeCovAgainstNumpyWithAlternativeNormalizer(self):
with tf_ops.Graph().as_default(), self.test_session() as sess:
npr.seed(0)
random_seed.set_random_seed(200)
normalizer = 10.
x = npr.randn(100, 3)
cov = ff.compute_cov(array_ops.constant(x), normalizer=normalizer)
np_cov = np.dot(x.T, x) / normalizer
self.assertAllClose(sess.run(cov), np_cov)