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 * Copyright (c) 2007, DoodleProject
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 * 
 * Redistributions in binary form must reproduce the above copyright
 * notice, this list of conditions and the following disclaimer in
 * the documentation and/or other materials provided with the
 * distribution.
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 * contributors may be used to endorse or promote products derived
 * from this software without specific prior written permission.
 * 
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND
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 * INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
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 */
package jhplot.math.num.random;

import jhplot.math.num.Constants;
import jhplot.math.num.special.Erf;

/**
 * 

 * A random variable generator for the Log Normal distribution.
 * 
 * 

 * References:
 * 

 * 
Wikipedia contributors, "Log-normal distribution," Wikipedia, The Free
 * Encyclopedia, 
 * http://en.wikipedia.org/wiki/Lognormal_distribution
 * 
 * 

 * 
 * @since 1.3
 * @version $Revision: 1.2 $ $Date: 2007/11/08 17:37:57 $
 */
public class LogNormalRandomVariable extends AbstractContinuousRandomVariable {

    /** The mean. */
    private double mean;

    /** The standard deviation. */
    private double standardDeviation;

    /**
     * Default constructor. Mean is set to zero and standard deviation is set to
     * one.
     */
    public LogNormalRandomVariable() {
        this(0.0, 1.0);
    }

    /**
     * Create a random variable with the given mean and standard deviation.
     * 
     * @param m the mean.
     * @param s the standard deviation.
     */
    public LogNormalRandomVariable(double m, double s) {
        this(m, s, new RandomRNG());
    }

    /**
     * Create a random variable with the given parameters.
     * 
     * @param m the mean.
     * @param s the standard deviation.
     * @param source the source generator.
     */
    public LogNormalRandomVariable(double m, double s, RNG source) {
        super(source);
        setMean(m);
        setStandardDeviation(s);
    }

    /**
     * Access the next random variable using the given generator.
     * 
     * @param m the mean.
     * @param s the standard deviation.
     * @param source the source generator.
     * @return the next random variable.
     */
    public static double nextRandomVariable(double m, double s, RNG source) {
        double u = source.nextRandomNumber();
        return Math.exp(Constants.SQRT_2 * s * Erf.inverseErf(2.0 * u - 1.0)
            + m);
    }

    /**
     * Access the mean.
     * 
     * @return the mean.
     */
    private double getMean() {
        return mean;
    }

    /**
     * Access the standard deviation.
     * 
     * @return the standard deviation.
     */
    private double getStandardDeviation() {
        return standardDeviation;
    }

    /**
     * Access the next random variable from this generator.
     * 
     * @return the next random variable.
     */
    public double nextRandomVariable() {
        return nextRandomVariable(getMean(), getStandardDeviation(),
            getSource());
    }

    /**
     * Modify the mean.
     * 
     * @param m the new mean value.
     */
    private void setMean(double m) {
        if (Double.isNaN(m)) {
            throw new IllegalArgumentException("Mean must be a valid number.");
        }
        this.mean = m;
    }

    /**
     * Modify the standard deviation.
     * 
     * @param std The new standard deviation value.
     */
    private void setStandardDeviation(double std) {
        if (std <= 0.0 || Double.isNaN(std)) {
            throw new IllegalArgumentException(
                "Standard deviation must be positive.");
        }
        this.standardDeviation = std;
    }
}