UncorrelatedRandomVectorGenerator.java
/*
* 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
*
* https://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.
*/
/*
* This is not the original file distributed by the Apache Software Foundation
* It has been modified by the Hipparchus project
*/
package org.hipparchus.random;
import java.util.Arrays;
import org.hipparchus.exception.LocalizedCoreFormats;
import org.hipparchus.exception.MathIllegalArgumentException;
/**
* A {@link RandomVectorGenerator} that generates vectors with uncorrelated components.
* <p>
* Components of generated vectors follow (independent) Gaussian distributions,
* with parameters supplied in the constructor.
*/
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 MathIllegalArgumentException(LocalizedCoreFormats.DIMENSIONS_MISMATCH, mean.length,
standardDeviation.length);
}
this.mean = mean.clone();
this.standardDeviation = standardDeviation.clone();
this.generator = generator;
}
/**
* Simple constructor.
* <p>
* Build a null mean random and unit standard deviation uncorrelated
* vector generator.
*
* @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
*/
@Override
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;
}
}