/*
 * 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.math.random;

import java.util.Arrays;

import org.apache.commons.math.MathRuntimeException;

/**
 * A {@link RandomVectorGenerator} that generates vectors with uncorrelated
 * components. Components of generated vectors follow (independent) Gaussian
 * distributions, with parameters supplied in the constructor.
 * 
 * @version $Revision$ $Date$
 * @since 1.2
 */

public class UncorrelatedRandomVectorGenerator implements RandomVectorGenerator {

	/**
	 * 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 MathRuntimeException.createIllegalArgumentException("dimension mismatch {0} != {1}", 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
	 * </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;

	}

	/** Mean vector. */
	private double[] mean;

	/** Standard deviation vector. */
	private double[] standardDeviation;

	/** Underlying scalar generator. */
	private NormalizedRandomGenerator generator;

}
