def get_kernel(kernel_name, input_shape):
"""Return a kernel for a given name."""
if kernel_name == "white_noise":
kernel = kernels.WhiteNoise(input_shape=input_shape)
elif kernel_name == "linear":
kernel = kernels.Linear(input_shape=input_shape)
elif kernel_name == "polynomial":
kernel = kernels.Polynomial(input_shape=input_shape)
elif kernel_name == "exp_quad":
kernel = kernels.ExpQuad(input_shape=input_shape)
elif kernel_name == "rat_quad":
kernel = kernels.RatQuad(input_shape=input_shape)
elif kernel_name == "matern12":
kernel = kernels.Matern(input_shape=input_shape, nu=0.5)
elif kernel_name == "matern32":
kernel = kernels.Matern(input_shape=input_shape, nu=1.5)
elif kernel_name == "matern52":
kernel = kernels.Matern(input_shape=input_shape, nu=2.5)
elif kernel_name == "matern72":
kernel = kernels.Matern(input_shape=input_shape, nu=3.5)
else:
raise ValueError(f"Kernel name '{kernel_name}' not recognized.")
return kernel
def test_add(kernel: kernels.Kernel):
k_whitenoise = kernels.WhiteNoise(input_shape=kernel.input_shape)
kernel_sum = kernel + k_whitenoise
assert isinstance(kernel_sum, SumKernel)
assert kernel_sum.input_shape == kernel.input_shape
assert kernel_sum.output_shape == kernel.output_shape
def test_sum_kernel_evaluation(kernel: kernels.Kernel, x0: np.ndarray):
k_whitenoise = kernels.WhiteNoise(input_shape=kernel.input_shape)
k_sum = SumKernel(kernel, k_whitenoise)
np.testing.assert_allclose(k_sum.matrix(x0),
kernel.matrix(x0) + k_whitenoise.matrix(x0))
def test_product_kernel_shape_mismatch_raises_error():
with pytest.raises(ValueError):
ProductKernel(kernels.WhiteNoise(input_shape=()),
kernels.WhiteNoise(input_shape=(1, )))
def test_non_scalar_raises_error():
with pytest.raises(TypeError):
ScaledKernel(kernel=kernels.WhiteNoise(input_shape=()),
scalar=np.array([0, 1]))