MersenneTwister.java

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *      https://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

/*
 * This is not the original file distributed by the Apache Software Foundation
 * It has been modified by the Hipparchus project
 */
package org.hipparchus.random;

import java.io.Serializable;

import org.hipparchus.util.FastMath;


/**
 * This class implements a powerful pseudo-random number generator
 * developed by Makoto Matsumoto and Takuji Nishimura during
 * 1996-1997.
 * <p>
 * <b>Caveat:</b> It is recommended to use one of WELL generators rather
 * than the MersenneTwister generator (see
 * <a href="http://www.iro.umontreal.ca/~panneton/WELLRNG.html">
 * this paper</a> for more information).
 * </p>
 * <p>
 * This generator features an extremely long period
 * (2<sup>19937</sup>-1) and 623-dimensional equidistribution up to 32
 * bits accuracy. The home page for this generator is located at <a
 * href="http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html">
 * http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html</a>.
 * </p>
 * <p>
 * This generator is described in a paper by Makoto Matsumoto and
 * Takuji Nishimura in 1998: <a
 * href="http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/ARTICLES/mt.pdf">Mersenne
 * Twister: A 623-Dimensionally Equidistributed Uniform Pseudo-Random
 * Number Generator</a>, ACM Transactions on Modeling and Computer
 * Simulation, Vol. 8, No. 1, January 1998, pp 3--30.
 * </p>
 * <p>
 * This class is mainly a Java port of the 2002-01-26 version of
 * the generator written in C by Makoto Matsumoto and Takuji
 * Nishimura. Here is their original copyright:
 * </p>
 * <blockquote>
 * <p>Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura,
 *     All rights reserved.</p>
 * <p>Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions
 * are met:</p>
 * <ol>
 *   <li>Redistributions of source code must retain the above copyright
 *       notice, this list of conditions and the following disclaimer.</li>
 *   <li>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.</li>
 *   <li>The names of its contributors may not be used to endorse or promote
 *       products derived from this software without specific prior written
 *       permission.</li>
 * </ol>
 *
 * <p><strong>THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND
 * CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES,
 * INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
 * MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 * DISCLAIMED.  IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS
 * BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY,
 * OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
 * PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
 * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
 * OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE
 * USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH
 * DAMAGE.</strong></p>
 * </blockquote>
 */
public class MersenneTwister extends IntRandomGenerator implements Serializable {

    /** Serializable version identifier. */
    private static final long serialVersionUID = 20160529L;

    /** Size of the bytes pool. */
    private static final int   N     = 624;

    /** Period second parameter. */
    private static final int   M     = 397;

    /** X * MATRIX_A for X = {0, 1}. */
    private static final int[] MAG01 = { 0x0, 0x9908b0df };

    /** Bytes pool. */
    private int[] mt;

    /** Current index in the bytes pool. */
    private int   mti;

    /**
     * Creates a new random number generator.
     * <p>
     * The instance is initialized using the current time plus the
     * system identity hash code of this instance as the seed.
     */
    public MersenneTwister() {
        mt = new int[N];
        setSeed(System.currentTimeMillis() + System.identityHashCode(this));
    }

    /**
     * Creates a new random number generator using a single int seed.
     * @param seed the initial seed (32 bits integer)
     */
    public MersenneTwister(int seed) {
        mt = new int[N];
        setSeed(seed);
    }

    /**
     * Creates a new random number generator using an int array seed.
     * @param seed the initial seed (32 bits integers array), if null
     * the seed of the generator will be related to the current time
     */
    public MersenneTwister(int[] seed) {
        mt = new int[N];
        setSeed(seed);
    }

    /**
     * Creates a new random number generator using a single long seed.
     * @param seed the initial seed (64 bits integer)
     */
    public MersenneTwister(long seed) {
        mt = new int[N];
        setSeed(seed);
    }

    /**
     * Reinitialize the generator as if just built with the given int seed.
     * <p>
     * The state of the generator is exactly the same as a new
     * generator built with the same seed.
     *
     * @param seed the initial seed (32 bits integer)
     */
    @Override
    public void setSeed(int seed) {
        // we use a long masked by 0xffffffffL as a poor man unsigned int
        long longMT = seed & 0xffffffffL;
        // NB: unlike original C code, we are working with java longs,
        // the cast below makes masking unnecessary
        mt[0]= (int) longMT;
        for (mti = 1; mti < N; ++mti) {
            // See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier.
            // initializer from the 2002-01-09 C version by Makoto Matsumoto
            longMT = (1812433253l * (longMT ^ (longMT >> 30)) + mti) & 0xffffffffL;
            mt[mti]= (int) longMT;
        }

        clearCache(); // Clear normal deviate cache
    }

    /**
     * Reinitialize the generator as if just built with the given int array seed.
     * <p>
     * The state of the generator is exactly the same as a new
     * generator built with the same seed.
     *
     * @param seed the initial seed (32 bits integers array), if null
     * the seed of the generator will be the current system time plus the
     * system identity hash code of this instance
     */
    @Override
    public void setSeed(int[] seed) {

        if (seed == null) {
            setSeed(System.currentTimeMillis() + System.identityHashCode(this));
            return;
        }

        setSeed(19650218);
        int i = 1;
        int j = 0;

        for (int k = FastMath.max(N, seed.length); k != 0; k--) {
            long l0 = (mt[i] & 0x7fffffffl)   | ((mt[i]   < 0) ? 0x80000000l : 0x0l);
            long l1 = (mt[i-1] & 0x7fffffffl) | ((mt[i-1] < 0) ? 0x80000000l : 0x0l);
            long l  = (l0 ^ ((l1 ^ (l1 >> 30)) * 1664525l)) + seed[j] + j; // non linear
            mt[i]   = (int) (l & 0xffffffffl);
            i++; j++;
            if (i >= N) {
                mt[0] = mt[N - 1];
                i = 1;
            }
            if (j >= seed.length) {
                j = 0;
            }
        }

        for (int k = N - 1; k != 0; k--) {
            long l0 = (mt[i] & 0x7fffffffl)   | ((mt[i]   < 0) ? 0x80000000l : 0x0l);
            long l1 = (mt[i-1] & 0x7fffffffl) | ((mt[i-1] < 0) ? 0x80000000l : 0x0l);
            long l  = (l0 ^ ((l1 ^ (l1 >> 30)) * 1566083941l)) - i; // non linear
            mt[i]   = (int) (l & 0xffffffffL);
            i++;
            if (i >= N) {
                mt[0] = mt[N - 1];
                i = 1;
            }
        }

        mt[0] = 0x80000000; // MSB is 1; assuring non-zero initial array

        clearCache(); // Clear normal deviate cache
    }

    /** {@inheritDoc} */
    @Override
    public int nextInt() {

        int y;

        if (mti >= N) { // generate N words at one time
            int mtNext = mt[0];
            for (int k = 0; k < N - M; ++k) {
                int mtCurr = mtNext;
                mtNext = mt[k + 1];
                y = (mtCurr & 0x80000000) | (mtNext & 0x7fffffff);
                mt[k] = mt[k + M] ^ (y >>> 1) ^ MAG01[y & 0x1];
            }
            for (int k = N - M; k < N - 1; ++k) {
                int mtCurr = mtNext;
                mtNext = mt[k + 1];
                y = (mtCurr & 0x80000000) | (mtNext & 0x7fffffff);
                mt[k] = mt[k + (M - N)] ^ (y >>> 1) ^ MAG01[y & 0x1];
            }
            y = (mtNext & 0x80000000) | (mt[0] & 0x7fffffff);
            mt[N - 1] = mt[M - 1] ^ (y >>> 1) ^ MAG01[y & 0x1];

            mti = 0;
        }

        y = mt[mti++];

        // tempering
        y ^=  y >>> 11;
        y ^= (y <<   7) & 0x9d2c5680;
        y ^= (y <<  15) & 0xefc60000;
        y ^=  y >>> 18;

        return y;
    }

}