def test_g1k_multiple_dim(self): N = 10 X = np.random.randn(N,1) me = GaussianQuadraticTest(self.grad_log_normal) K = me.k_multiple_dim(X) g1k_alt = me.g1k_multiple_dim(X,K,0) g1k_orig = me.g1k_multiple(X[:,0]) np.testing.assert_almost_equal(g1k_alt, g1k_orig)
def test_g1k_multiple_dim(self): N = 10 X = np.random.randn(N, 1) me = GaussianQuadraticTest(self.grad_log_normal) K = me.k_multiple_dim(X) g1k_alt = me.g1k_multiple_dim(X, K, 0) g1k_orig = me.g1k_multiple(X[:, 0]) np.testing.assert_almost_equal(g1k_alt, g1k_orig)
def test_g1k_multiple_equals_g1k(self): N = 10 X = np.random.randn(N) me = GaussianQuadraticTest(self.grad_log_normal) G1K = me.g1k_multiple(X) for i in range(N): for j in range(N): g1k = me.g1k(X[i], X[j]) assert_almost_equal(G1K[i, j], g1k)