1 /* 2 * Licensed to the Apache Software Foundation (ASF) under one or more 3 * contributor license agreements. See the NOTICE file distributed with 4 * this work for additional information regarding copyright ownership. 5 * The ASF licenses this file to You under the Apache License, Version 2.0 6 * (the "License"); you may not use this file except in compliance with 7 * the License. You may obtain a copy of the License at 8 * 9 * http://www.apache.org/licenses/LICENSE-2.0 10 * 11 * Unless required by applicable law or agreed to in writing, software 12 * distributed under the License is distributed on an "AS IS" BASIS, 13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 14 * See the License for the specific language governing permissions and 15 * limitations under the License. 16 */ 17 18 package org.apache.commons.math.random; 19 20 import java.util.Arrays; 21 22 import org.apache.commons.math.exception.DimensionMismatchException; 23 24 /** 25 * A {@link RandomVectorGenerator} that generates vectors with uncorrelated 26 * components. Components of generated vectors follow (independent) Gaussian 27 * distributions, with parameters supplied in the constructor. 28 * 29 * @version $Revision: 962515 $ $Date: 2010-07-09 15:15:28 +0200 (ven. 09 juil. 2010) $ 30 * @since 1.2 31 */ 32 33 public class UncorrelatedRandomVectorGenerator 34 implements RandomVectorGenerator { 35 36 /** Underlying scalar generator. */ 37 private final NormalizedRandomGenerator generator; 38 39 /** Mean vector. */ 40 private final double[] mean; 41 42 /** Standard deviation vector. */ 43 private final double[] standardDeviation; 44 45 /** Simple constructor. 46 * <p>Build an uncorrelated random vector generator from 47 * its mean and standard deviation vectors.</p> 48 * @param mean expected mean values for each component 49 * @param standardDeviation standard deviation for each component 50 * @param generator underlying generator for uncorrelated normalized 51 * components 52 */ 53 public UncorrelatedRandomVectorGenerator(double[] mean, 54 double[] standardDeviation, 55 NormalizedRandomGenerator generator) { 56 if (mean.length != standardDeviation.length) { 57 throw new DimensionMismatchException(mean.length, standardDeviation.length); 58 } 59 this.mean = mean.clone(); 60 this.standardDeviation = standardDeviation.clone(); 61 this.generator = generator; 62 } 63 64 /** Simple constructor. 65 * <p>Build a null mean random and unit standard deviation 66 * uncorrelated vector generator</p> 67 * @param dimension dimension of the vectors to generate 68 * @param generator underlying generator for uncorrelated normalized 69 * components 70 */ 71 public UncorrelatedRandomVectorGenerator(int dimension, 72 NormalizedRandomGenerator generator) { 73 mean = new double[dimension]; 74 standardDeviation = new double[dimension]; 75 Arrays.fill(standardDeviation, 1.0); 76 this.generator = generator; 77 } 78 79 /** Generate an uncorrelated random vector. 80 * @return a random vector as a newly built array of double 81 */ 82 public double[] nextVector() { 83 84 double[] random = new double[mean.length]; 85 for (int i = 0; i < random.length; ++i) { 86 random[i] = mean[i] + standardDeviation[i] * generator.nextNormalizedDouble(); 87 } 88 89 return random; 90 91 } 92 93 } 94
