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package jhplot.math.num.pdf;

import jhplot.math.num.NumericException;

/**
 * 

 * The Geometric distribution.
 * 
 * 

 * References:
 * 

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

 * 
 * @since 1.2
 * @version $Revision: 1.2 $ $Date: 2007/10/25 04:44:10 $
 */
public class Geometric extends DiscreteDistribution {

    /** the probability of success for each trial. */
    private double probabilityOfSuccess;

    /**
     * Default constructor. The probability of success is set to 0.5.
     */
    public Geometric() {
        this(0.5);
    }

    /**
     * Create a distribution with the given probability of success.
     * 
     * @param p the probability of success.
     */
    public Geometric(double p) {
        super();
        setProbabilityOfSuccess(p);
    }

    /**
     * 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(int x) throws NumericException {
        double ret;

        if (x < 0) {
            ret = 0.0;
        } else {
            ret = simpleCumulativeProbability(0, x);
        }

        return ret;
    }

    /**
     * Access probability of success.
     * 
     * @return the probability of success.
     */
    public double getProbabilityOfSuccess() {
        return probabilityOfSuccess;
    }

    /**
     * The inverse CDF for this distribution. This method returns the largest x
     * such that, P(X ≤ x) ≤ p. The return value must also satisfy P(X
     * ≥ x) &ge 1 - p.
     * 
     * @param p the cumulative probability.
     * @return x
     * @throws NumericException if the inverse cumulative probability can not be
     *         computed.
     */
    public int inverseCumulativeProbability(double p) throws NumericException {
        int ret;

        if (p < 0.0 || p > 1.0 || Double.isNaN(p)) {
            ret = Integer.MIN_VALUE;
        } else if (p == 0.0) {
            ret = -1;
        } else if (p == 1.0) {
            ret = Integer.MAX_VALUE;
        } else {
            ret = findInverseCumulativeProbability(p, 0,
                (int) (1.0 / probabilityOfSuccess - 0.5), Integer.MAX_VALUE);
        }

        return ret;
    }

    /**
     * The PMF for this distribution. This method returns P(X = x).
     * 
     * @param x the value at which the probability is evaluated.
     * @return PMF for this distribution.
     */
    public double probability(int x) {
        double ret;
        if (x < 0) {
            ret = 0.0;
        } else {
            ret = Math.exp(SaddlePoint.logBinomialProbability(1,
                x + 1, probabilityOfSuccess, 1.0 - probabilityOfSuccess));
            ret /= (x + 1.0);
        }
        return ret;
    }

    /**
     * Modify probability of success.
     * 
     * @param p the new probability of success value.
     */
    public void setProbabilityOfSuccess(double p) {
        if (Double.isNaN(p) || p <= 0.0 || p >= 1.0) {
            throw new IllegalArgumentException("probability of success must"
                + "be between 0.0 and 1.0, exclusive.");
        }
        probabilityOfSuccess = p;
    }
}