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Parallel Colt is a multithreaded version of Colt - a library for high performance scientific computing in Java. It contains efficient algorithms for data analysis, linear algebra, multi-dimensional arrays, Fourier transforms, statistics and histogramming.
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/*
Copyright (C) 1999 CERN - European Organization for Nuclear Research.
Permission to use, copy, modify, distribute and sell this software and its documentation for any purpose 
is hereby granted without fee, provided that the above copyright notice appear in all copies and 
that both that copyright notice and this permission notice appear in supporting documentation. 
CERN makes no representations about the suitability of this software for any purpose. 
It is provided "as is" without expressed or implied warranty.
 */
package cern.jet.random.tdouble;

import cern.jet.random.tdouble.engine.DoubleRandomEngine;

/**
 * Von Mises distribution.
 * 
 * Valid parameter ranges: k > 0.
 * 

 * Instance methods operate on a user supplied uniform random number generator;
 * they are unsynchronized.
 * 
Static methods operate on a default uniform random number generator; they
 * are synchronized.
 * 
 * Implementation:
 * 
Method: Acceptance Rejection.
 * This is a port of mwc.c from the C-RAND /
 * WIN-RAND library. C-RAND's implementation, in turn, is based upon
 * 
 * D.J. Best, N.I. Fisher (1979): Efficient simulation of the von Mises
 * distribution, Appl. Statist. 28, 152-157.
 * 
 * @author [email protected]
 * @version 1.0, 09/24/99
 */
public class VonMises extends AbstractContinousDoubleDistribution {
    /**
     * 
     */
    private static final long serialVersionUID = 1L;

    protected double my_k;

    // cached vars for method nextDouble(a) (for performance only)
    private double k_set = -1.0;

    private double tau, rho, r;

    // The uniform random number generated shared by all static methods.
    protected static VonMises shared = new VonMises(1.0, makeDefaultGenerator());

    /**
     * Constructs a Von Mises distribution. Example: k=1.0.
     * 
     * @throws IllegalArgumentException
     *             if k <= 0.0.
     */
    public VonMises(double freedom, DoubleRandomEngine randomGenerator) {
        setRandomGenerator(randomGenerator);
        setState(freedom);
    }

    /**
     * Returns a random number from the distribution.
     */

    public double nextDouble() {
        return nextDouble(this.my_k);
    }

    /**
     * Returns a random number from the distribution; bypasses the internal
     * state.
     * 
     * @throws IllegalArgumentException
     *             if k <= 0.0.
     */
    public double nextDouble(double k) {
        /***********************************************************************
         * * Von Mises Distribution - Acceptance Rejection * *
         * ***************************************************************** *
         * FUNCTION : - mwc samples a random number from the von Mises *
         * distribution ( -Pi <= x <= Pi) with parameter * k > 0 via rejection
         * from the wrapped Cauchy * distibution. * REFERENCE: - D.J. Best, N.I.
         * Fisher (1979): Efficient * simulation of the von Mises distribution,
         * * Appl. Statist. 28, 152-157. * SUBPROGRAM: - drand(seed) ...
         * (0,1)-Uniform generator with * unsigned long integer *seed. * *
         * Implemented by F. Niederl, August 1992 *
         **********************************************************************/
        double u, v, w, c, z;

        if (k <= 0.0)
            throw new IllegalArgumentException();

        if (k_set != k) { // SET-UP
            tau = 1.0 + Math.sqrt(1.0 + 4.0 * k * k);
            rho = (tau - Math.sqrt(2.0 * tau)) / (2.0 * k);
            r = (1.0 + rho * rho) / (2.0 * rho);
            k_set = k;
        }

        // GENERATOR
        do {
            u = randomGenerator.raw(); // U(0/1)
            v = randomGenerator.raw(); // U(0/1)
            z = Math.cos(Math.PI * u);
            w = (1.0 + r * z) / (r + z);
            c = k * (r - w);
        } while ((c * (2.0 - c) < v) && (Math.log(c / v) + 1.0 < c)); // Acceptance/Rejection

        return (randomGenerator.raw() > 0.5) ? Math.acos(w) : -Math.acos(w); // Random
        // sign
        // //
        // 0 <= x <= Pi : -Pi <= x <= 0 //
    }

    /**
     * Sets the distribution parameter.
     * 
     * @throws IllegalArgumentException
     *             if k <= 0.0.
     */
    public void setState(double k) {
        if (k <= 0.0)
            throw new IllegalArgumentException();
        this.my_k = k;
    }

    /**
     * Returns a random number from the distribution.
     * 
     * @throws IllegalArgumentException
     *             if k <= 0.0.
     */
    public static double staticNextDouble(double freedom) {
        synchronized (shared) {
            return shared.nextDouble(freedom);
        }
    }

    /**
     * Returns a String representation of the receiver.
     */

    public String toString() {
        return this.getClass().getName() + "(" + my_k + ")";
    }

    /**
     * Sets the uniform random number generated shared by all static
     * methods.
     * 
     * @param randomGenerator
     *            the new uniform random number generator to be shared.
     */
    private static void xstaticSetRandomGenerator(DoubleRandomEngine randomGenerator) {
        synchronized (shared) {
            shared.setRandomGenerator(randomGenerator);
        }
    }
}