/*
* 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.math3.random;
import java.util.Arrays;
import org.apache.commons.math3.exception.DimensionMismatchException;
import org.apache.commons.math3.util.Cloner;
/**
* A {@link RandomVectorGenerator} that generates vectors with uncorrelated
* components. Components of generated vectors follow (independent) Gaussian
* distributions, with parameters supplied in the constructor.
*
* @since 1.2
*/
public class UncorrelatedRandomVectorGenerator
implements RandomVectorGenerator {
/** Underlying scalar generator. */
private final NormalizedRandomGenerator generator;
/** Mean vector. */
private final double[] mean;
/** Standard deviation vector. */
private final double[] standardDeviation;
/** Simple constructor.
* <p>Build an uncorrelated random vector generator from
* its mean and standard deviation vectors.</p>
* @param mean expected mean values for each component
* @param standardDeviation standard deviation for each component
* @param generator underlying generator for uncorrelated normalized
* components
*/
public UncorrelatedRandomVectorGenerator(double[] mean,
double[] standardDeviation,
NormalizedRandomGenerator generator) {
if (mean.length != standardDeviation.length) {
throw new DimensionMismatchException(mean.length, standardDeviation.length);
}
this.mean = Cloner.clone(mean);
this.standardDeviation = Cloner.clone(standardDeviation);
this.generator = generator;
}
/** Simple constructor.
* <p>Build a null mean random and unit standard deviation
* uncorrelated vector generator</p>
* @param dimension dimension of the vectors to generate
* @param generator underlying generator for uncorrelated normalized
* components
*/
public UncorrelatedRandomVectorGenerator(int dimension,
NormalizedRandomGenerator generator) {
mean = new double[dimension];
standardDeviation = new double[dimension];
Arrays.fill(standardDeviation, 1.0);
this.generator = generator;
}
/** Generate an uncorrelated random vector.
* @return a random vector as a newly built array of double
*/
public double[] nextVector() {
double[] random = new double[mean.length];
for (int i = 0; i < random.length; ++i) {
random[i] = mean[i] + standardDeviation[i] * generator.nextNormalizedDouble();
}
return random;
}
}