To reference or cite the objects present in the Software Heritage archive, permalinks based on SoftWare Heritage persistent IDentifiers (SWHIDs) must be used.
Select below a type of object currently browsed in order to display its associated SWHID and permalink.
# 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. import numpy as np from numpy.random import randn import pytest from gpflow import logdensities from scipy.stats import multivariate_normal as mvn from numpy.testing import assert_allclose rng = np.random.RandomState(1) @pytest.mark.parametrize("x", [randn(4, 10), randn(4, 1)]) @pytest.mark.parametrize("mu", [randn(4, 10), randn(4, 1)]) @pytest.mark.parametrize("cov_sqrt", [randn(4, 4), np.eye(4)]) def test_multivariate_normal(x, mu, cov_sqrt): cov = np.dot(cov_sqrt, cov_sqrt.T) L = np.linalg.cholesky(cov) gp_result = logdensities.multivariate_normal(x, mu, L) if mu.shape > 1: if x.shape > 1: sp_result = [ mvn.logpdf(x[:, i], mu[:, i], cov) for i in range(mu.shape) ] else: sp_result = [ mvn.logpdf(x.ravel(), mu[:, i], cov) for i in range(mu.shape) ] else: sp_result = mvn.logpdf(x.T, mu.ravel(), cov) assert_allclose(gp_result, sp_result)