| /* |
| * Licensed to the Apache Software Foundation (ASF) under one or more |
| * contributor license agreements. See the NOTICE file distributed with |
| * this work for additional information regarding copyright ownership. |
| * The ASF licenses this file to You 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. |
| */ |
| package org.apache.commons.math4.legacy.distribution; |
| |
| import java.util.ArrayList; |
| import java.util.List; |
| |
| import org.apache.commons.math4.legacy.exception.DimensionMismatchException; |
| import org.apache.commons.math4.legacy.exception.NotPositiveException; |
| import org.apache.commons.math4.legacy.core.Pair; |
| |
| /** |
| * Multivariate normal mixture distribution. |
| * This class is mainly syntactic sugar. |
| * |
| * @see MixtureMultivariateRealDistribution |
| * @since 3.2 |
| */ |
| public class MixtureMultivariateNormalDistribution |
| extends MixtureMultivariateRealDistribution<MultivariateNormalDistribution> { |
| /** |
| * Creates a mixture model from a list of distributions and their |
| * associated weights. |
| * |
| * @param components Distributions from which to sample. |
| * @throws NotPositiveException if any of the weights is negative. |
| * @throws DimensionMismatchException if not all components have the same |
| * number of variables. |
| */ |
| public MixtureMultivariateNormalDistribution(List<Pair<Double, MultivariateNormalDistribution>> components) |
| throws NotPositiveException, |
| DimensionMismatchException { |
| super(components); |
| } |
| |
| /** |
| * Creates a multivariate normal mixture distribution. |
| * |
| * @param weights Weights of each component. |
| * @param means Mean vector for each component. |
| * @param covariances Covariance matrix for each component. |
| * @throws NotPositiveException if any of the weights is negative. |
| * @throws DimensionMismatchException if not all components have the same |
| * number of variables. |
| */ |
| public MixtureMultivariateNormalDistribution(double[] weights, |
| double[][] means, |
| double[][][] covariances) |
| throws NotPositiveException, |
| DimensionMismatchException { |
| this(createComponents(weights, means, covariances)); |
| } |
| |
| /** |
| * Creates components of the mixture model. |
| * |
| * @param weights Weights of each component. |
| * @param means Mean vector for each component. |
| * @param covariances Covariance matrix for each component. |
| * @return the list of components. |
| */ |
| private static List<Pair<Double, MultivariateNormalDistribution>> createComponents(double[] weights, |
| double[][] means, |
| double[][][] covariances) { |
| final List<Pair<Double, MultivariateNormalDistribution>> mvns |
| = new ArrayList<>(weights.length); |
| |
| for (int i = 0; i < weights.length; i++) { |
| final MultivariateNormalDistribution dist |
| = new MultivariateNormalDistribution(means[i], covariances[i]); |
| |
| mvns.add(new Pair<>(weights[i], dist)); |
| } |
| |
| return mvns; |
| } |
| } |