https://github.com/GPflow/GPflow
Tip revision: 6206625b55074c8f279331c403f2aa777f9a3ec6 authored by Jesper Nielsen on 17 October 2022, 12:38:58 UTC
Support determistic randomness.
Support determistic randomness.
Tip revision: 6206625
test_positive_semidefinite.py
# Copyright 2018 the GPflow authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import Type
import numpy as np
import pytest
import tensorflow as tf
from numpy.testing import assert_array_less
import gpflow.ci_utils
from gpflow import kernels
KERNEL_CLASSES = [
kernel
for cls in (kernels.Static, kernels.Stationary, kernels.Linear)
for kernel in gpflow.ci_utils.subclasses(cls)
if kernel not in (kernels.IsotropicStationary, kernels.AnisotropicStationary)
] + [kernels.ArcCosine]
rng = np.random.RandomState(42)
def pos_semidefinite(kernel: kernels.Kernel) -> None:
N, D = 100, 5
X = rng.randn(N, D)
cov = kernel(X)
eig = tf.linalg.eigvalsh(cov).numpy()
assert_array_less(-1e-12, eig)
@pytest.mark.parametrize("kernel_class", KERNEL_CLASSES)
def test_positive_semidefinite(kernel_class: Type[kernels.Kernel]) -> None:
"""
A valid kernel is positive semidefinite. Some kernels are only valid for
particular input shapes, see https://github.com/GPflow/GPflow/issues/1328
"""
kernel = kernel_class()
pos_semidefinite(kernel)
@pytest.mark.parametrize(
"base_class", [kernel for kernel in gpflow.ci_utils.subclasses(kernels.IsotropicStationary)]
)
def test_positive_semidefinite_periodic(base_class: Type[kernels.IsotropicStationary]) -> None:
"""
A valid kernel is positive semidefinite. Some kernels are only valid for
particular input shapes, see https://github.com/GPflow/GPflow/issues/1328
"""
kernel = kernels.Periodic(base_class())
pos_semidefinite(kernel)