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/*
 * 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 org.apache.commons.math3.exception.DimensionMismatchException;

import java.util.Arrays;

/**
 * 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.
     *
     * @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 = 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
     */
    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;
    }
}