def test_simple_kernel(self):
"""Test square_kernel_matrix and kernel_matrix of the _mock_kernel above."""
X1 = [0.1, 0.4]
X2 = [0.1, 0.3, 0.5]
K1_expected = pnp.array([[1, 0.2], [0.2, 1]])
K2_expected = pnp.array([[1, 0.2, 0.2], [0.2, 0.2, 0.2]])
K1 = kern.square_kernel_matrix(X1, lambda x1, x2: _mock_kernel(x1, x2, []))
K2 = kern.kernel_matrix(X1, X2, lambda x1, x2: _mock_kernel(x1, x2, []))
assert np.array_equal(K1, K1_expected)
assert np.array_equal(K2, K2_expected)
def test_laplace_kernel(self):
"""Test square_kernel_matrix and kernel_matrix of the _laplace_kernel above."""
X1 = [0.1, 0.4, 0.2]
X2 = [0.0, 0.1, 0.3, 0.2]
K1_expected = pnp.exp(-np.array([[0.0, 0.3, 0.1], [0.3, 0.0, 0.2], [0.1, 0.2, 0.0]]))
K2_expected = pnp.exp(
-np.array([[0.1, 0.0, 0.2, 0.1], [0.4, 0.3, 0.1, 0.2], [0.2, 0.1, 0.1, 0.0]])
)
K1 = kern.square_kernel_matrix(X1, _laplace_kernel, assume_normalized_kernel=False)
K2 = kern.kernel_matrix(X1, X2, _laplace_kernel)
assert np.allclose(K1, K1_expected)
assert np.allclose(K2, K2_expected)