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package jhplot.math.num.pdf;


/**
 * 

 * The Uniform distribution (1).
 * 
 * 

 * References:
 * 

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

 * 
 * @since 1.1
 * @version $Revision: 1.3 $ $Date: 2007/11/18 23:51:21 $
 */
public class Uniform extends ContinuousDistribution {

    /** The lower bound parameter. */
    private double lower = -Double.MAX_VALUE;

    /** The range for this distribution. */
    private double range;

    /** The upper bound parameter. */
    private double upper = Double.MAX_VALUE;

    /**
     * Default constructor. The lower bound is set to 0 and the upper bound is
     * set to 1.
     */
    public Uniform() {
        this(0.0, 1.0);
    }

    /**
     * Create a distribution with the given lower bound and upper bound values.
     * 
     * @param a the lower bound parameter.
     * @param b the upper bound parameter.
     */
    public Uniform(double a, double b) {
        super();
        if (a <= b) {
            setLower(a);
            setUpper(b);
        } else {
            throw new IllegalArgumentException(
                "Lower bound must be less than upper bound.");
        }
    }

    /**
     * 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.
     */
    public double cumulativeProbability(double x) {
        double ret;

        if (Double.isNaN(x)) {
            ret = Double.NaN;
        } else if (x <= lower) {
            ret = 0.0;
        } else if (x >= upper) {
            ret = 1.0;
        } else {
            ret = (x - lower) / getRange();
        }

        return ret;
    }

    /**
     * Access the lower parameter.
     * 
     * @return the lower parameter.
     */
    public double getLower() {
        return lower;
    }

    /**
     * Access the range value.
     * 
     * @return the range.
     */
    private double getRange() {
        return range;
    }

    /**
     * Access the upper parameter.
     * 
     * @return the upper parameter.
     */
    public double getUpper() {
        return upper;
    }

    /**
     * The inverse CDF for this distribution. This method returns x such that,
     * P(X < x) = p.
     * 
     * @param p the cumulative probability.
     * @return x
     */
    public double inverseCumulativeProbability(double p) {
        double ret;

        if (p < 0.0 || p > 1.0 || Double.isNaN(p)) {
            ret = Double.NaN;
        } else if (p == 0.0) {
            ret = lower;
        } else if (p == 1.0) {
            ret = upper;
        } else {
            ret = lower + p * getRange();
        }

        return ret;
    }

    /**
     * Modify the lower bound parameter.
     * 
     * @param low the new lower bound value.
     */
    public void setLower(double low) {
        if (Double.isNaN(low)) {
            throw new IllegalArgumentException("Lower bound must be a number.");
        }
        if (low > upper) {
            throw new IllegalArgumentException(
                "Lower bound must be less than upper bound.");
        }
        this.lower = low;
        setRange(getUpper() - low);
    }

    /**
     * Modify the range value.
     * 
     * @param value the new range value.
     */
    private void setRange(double value) {
        this.range = value;
    }

    /**
     * Modify the upper bound parameter.
     * 
     * @param up the new upper bound value.
     */
    public void setUpper(double up) {
        if (Double.isNaN(up)) {
            throw new IllegalArgumentException("Upper bound must be a number.");
        }
        if (up < lower) {
            throw new IllegalArgumentException(
                "Upper bound must be greater than lower bound.");
        }
        this.upper = up;
        setRange(up - getLower());
    }
}