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package jhplot.math.num.pdf;

import jhplot.math.num.NumericException;

/**
 * 

 * The Gamma distribution (1).
 * 
 * 

 * References:
 * 

 * 
 Eric W. Weisstein. "Gamma Distribution." From MathWorld--A Wolfram Web
 * Resource. 
 * http://mathworld.wolfram.com/Gamma.html 
 * 
 * 

 * 
 * @version $Revision: 1.2 $ $Date: 2007/10/25 04:44:10 $
 */
public class Gamma extends ContinuousDistribution {

    /** The alpha parameter. */
    private double alpha;

    /** The beta parameter. */
    private double beta;

    /**
     * Default constructor. Alpha and beta are both set to 1.
     */
    public Gamma() {
        this(1.0, 1.0);
    }

    /**
     * Create a distribution with the given alpha and beta values.
     * 
     * @param a the alpha parameter.
     * @param b the beta parameter.
     */
    public Gamma(double a, double b) {
        super();
        setAlpha(a);
        setBeta(b);
    }

    /**
     * The CDF for this distribution. This method returns P(X < x).
     * 
     * @param x the value at which the CDF is evaluated.
     * @return CDF for this distribution.
     * @throws NumericException if the cumulative probability can not be
     *         computed.
     */
    public double cumulativeProbability(double x) throws NumericException {
        double ret;

        if (x <= 0.0) {
            ret = 0.0;
        } else if (Double.isInfinite(x)) {
            ret = 1.0;
        } else {
            ret = jhplot.math.num.special.Gamma.regularizedGammaP(getAlpha(), x / getBeta());
        }

        return ret;
    }

    /**
     * Access the alpha parameter.
     * 
     * @return the alpha parameter.
     */
    public double getAlpha() {
        return alpha;
    }

    /**
     * Access the beta parameter.
     * 
     * @return the beta parameter.
     */
    public double getBeta() {
        return beta;
    }

    /**
     * The inverse CDF for this distribution. This method returns x such that,
     * P(X < x) = p.
     * 
     * @param p the cumulative probability.
     * @return x
     * @throws NumericException if the inverse cumulative probability can not be
     *         computed.
     */
    public double inverseCumulativeProbability(double p)
        throws NumericException {
        double ret;

        if (p < 0.0 || p > 1.0 || Double.isNaN(p)) {
            ret = Double.NaN;
        } else if (p == 0.0) {
            ret = 0.0;
        } else if (p == 1.0) {
            ret = Double.POSITIVE_INFINITY;
        } else if (p <= 0.5) {
            ret = findInverseCumulativeProbability(p, 0.0, 0.5 * getAlpha()
                * getBeta(), getAlpha() * getBeta());
        } else {
            ret = findInverseCumulativeProbability(p, 0.0, getAlpha()
                * getBeta(), Double.POSITIVE_INFINITY);
        }

        return ret;
    }

    /**
     * Modify the alpha parameter.
     * 
     * @param a the new alpha value.
     */
    public void setAlpha(double a) {
        if (a <= 0.0 || Double.isNaN(a)) {
            throw new IllegalArgumentException("Alpha must be positive.");
        }
        this.alpha = a;
    }

    /**
     * Modify the beta parameter.
     * 
     * @param b the new beta value.
     */
    public void setBeta(double b) {
        if (b <= 0.0 || Double.isNaN(b)) {
            throw new IllegalArgumentException("Beta must be positive.");
        }
        this.beta = b;
    }
}