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)