001/*
002 * Licensed to the Apache Software Foundation (ASF) under one or more
003 * contributor license agreements.  See the NOTICE file distributed with
004 * this work for additional information regarding copyright ownership.
005 * The ASF licenses this file to You under the Apache License, Version 2.0
006 * (the "License"); you may not use this file except in compliance with
007 * the License.  You may obtain a copy of the License at
008 *
009 *      http://www.apache.org/licenses/LICENSE-2.0
010 *
011 * Unless required by applicable law or agreed to in writing, software
012 * distributed under the License is distributed on an "AS IS" BASIS,
013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
014 * See the License for the specific language governing permissions and
015 * limitations under the License.
016 */
017package org.apache.commons.math4.distribution;
018
019import java.util.ArrayList;
020import java.util.List;
021
022import org.apache.commons.math4.exception.DimensionMismatchException;
023import org.apache.commons.math4.exception.NotPositiveException;
024import org.apache.commons.math4.util.Pair;
025
026/**
027 * Multivariate normal mixture distribution.
028 * This class is mainly syntactic sugar.
029 *
030 * @see MixtureMultivariateRealDistribution
031 * @since 3.2
032 */
033public class MixtureMultivariateNormalDistribution
034    extends MixtureMultivariateRealDistribution<MultivariateNormalDistribution> {
035    /**
036     * Creates a mixture model from a list of distributions and their
037     * associated weights.
038     *
039     * @param components Distributions from which to sample.
040     * @throws NotPositiveException if any of the weights is negative.
041     * @throws DimensionMismatchException if not all components have the same
042     * number of variables.
043     */
044    public MixtureMultivariateNormalDistribution(List<Pair<Double, MultivariateNormalDistribution>> components)
045        throws NotPositiveException,
046               DimensionMismatchException {
047        super(components);
048    }
049
050    /**
051     * Creates a multivariate normal mixture distribution.
052     *
053     * @param weights Weights of each component.
054     * @param means Mean vector for each component.
055     * @param covariances Covariance matrix for each component.
056     * @throws NotPositiveException if any of the weights is negative.
057     * @throws DimensionMismatchException if not all components have the same
058     * number of variables.
059     */
060    public MixtureMultivariateNormalDistribution(double[] weights,
061                                                 double[][] means,
062                                                 double[][][] covariances)
063        throws NotPositiveException,
064               DimensionMismatchException {
065        this(createComponents(weights, means, covariances));
066    }
067
068    /**
069     * Creates components of the mixture model.
070     *
071     * @param weights Weights of each component.
072     * @param means Mean vector for each component.
073     * @param covariances Covariance matrix for each component.
074     * @return the list of components.
075     */
076    private static List<Pair<Double, MultivariateNormalDistribution>> createComponents(double[] weights,
077                                                                                       double[][] means,
078                                                                                       double[][][] covariances) {
079        final List<Pair<Double, MultivariateNormalDistribution>> mvns
080            = new ArrayList<>(weights.length);
081
082        for (int i = 0; i < weights.length; i++) {
083            final MultivariateNormalDistribution dist
084                = new MultivariateNormalDistribution(means[i], covariances[i]);
085
086            mvns.add(new Pair<>(weights[i], dist));
087        }
088
089        return mvns;
090    }
091}