package edu.cornell.lassp.houle.RngPack;
import java.util.*;
import java.io.Serializable;
//
// RngPack 1.1a by Paul Houle
// http://www.honeylocust.com/RngPack/
//
/**
*
* Mersenne Twister --
* advanced psuedorandom generator with a period of 219937-1
*
*
*
*
* Source code is available.
*
* This class is derived from Sean Luke's
* implementation
*
*
*
*
*
License
*
* Copyright (c) 2003 by Paul Houle.
* Derived from a work copyright (c) 2003 by Sean Luke.
* Portions copyright (c) 1993 by Michael Lecuyer.
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* - Redistributions of source code must retain the above copyright notice,
* this list of conditions and the following disclaimer.
*
- 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.
*
- Neither the name of the copyright owners, their employers, nor the
* names of its contributors may be used to endorse or promote products
* derived from this software without specific prior written permission.
*
* 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 OWNERS 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.
*
*
*
* @author Paul Houle (E-mail: paul@honeylocust.com)
* @version 1.1a
*/
public class RanMT extends RandomSeedable implements Serializable {
private static final int N = 624;
private static final int M = 397;
private static final int MATRIX_A = 0x9908b0df; // private static final * constant vector a
private static final int UPPER_MASK = 0x80000000; // most significant w-r bits
private static final int LOWER_MASK = 0x7fffffff; // least significant r bits
// Tempering parameters
private static final int TEMPERING_MASK_B = 0x9d2c5680;
private static final int TEMPERING_MASK_C = 0xefc60000;
private int mt[]; // the array for the state vector
private int mti; // mti==N+1 means mt[N] is not initialized
private int mag01[];
public RanMT() {
this.setSeed(4357);
}
/*
*
* Note that this uses only the LSB 32 bits from the long
*
*/
public RanMT(long seed) {
this.setSeed(seed);
}
public RanMT(Date d) {
this.setSeed(d.getTime());
}
/**
*
* If a 32 bit seed isn't enough for you, you can pass an array of
* 624 integers. Any array of integers is fine so long as they
* aren't all zero.
*
*/
public RanMT(int array[]) {
this.setSeed(array);
}
private void setSeed(final long seed)
{
mt = new int[N];
mag01 = new int[2];
mag01[0] = 0x0;
mag01[1] = MATRIX_A;
mt[0]= (int)(seed & 0xfffffff);
for (mti=1; mti>> 30)) + mti);
/* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */
/* In the previous versions, MSBs of the seed affect */
/* only MSBs of the array mt[]. */
/* 2002/01/09 modified by Makoto Matsumoto */
mt[mti] &= 0xffffffff;
/* for >32 bit machines */
}
}
/**
* An alternative, more complete, method of seeding the
* pseudo random number generator. array must be an
* array of 624 ints, and they can be any value as long as
* they're not *all* zero.
*/
private void setSeed(final int[] array) {
int i, j, k;
setSeed(19650218);
i=1; j=0;
k = (N>array.length ? N : array.length);
for (; k!=0; k--) {
mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >>> 30)) * 1664525)) + array[j] + j; /* non linear */
mt[i] &= 0xffffffff; /* for WORDSIZE > 32 machines */
i++;
j++;
if (i>=N) { mt[0] = mt[N-1]; i=1; }
if (j>=array.length) j=0;
}
for (k=N-1; k!=0; k--) {
mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >>> 30)) * 1566083941)) - i; /* non linear */
mt[i] &= 0xffffffff; /* for WORDSIZE > 32 machines */
i++;
if (i>=N) {
mt[0] = mt[N-1]; i=1;
}
}
mt[0] = 0x80000000; /* MSB is 1; assuring non-zero initial array */
}
public final double raw() {
int y;
int z;
if (mti >= N) { // generate N words at one time
int kk;
for (kk = 0; kk < N - M; kk++) {
y = (mt[kk] & UPPER_MASK) | (mt[kk+1] & LOWER_MASK);
mt[kk] = mt[kk+M] ^ (y >>> 1) ^ mag01[y & 0x1];
}
for (; kk < N-1; kk++) {
y = (mt[kk] & UPPER_MASK) | (mt[kk+1] & LOWER_MASK);
mt[kk] = mt[kk+(M-N)] ^ (y >>> 1) ^ mag01[y & 0x1];
}
y = (mt[N-1] & UPPER_MASK) | (mt[0] & LOWER_MASK);
mt[N-1] = mt[M-1] ^ (y >>> 1) ^ mag01[y & 0x1];
mti = 0;
}
y = mt[mti++];
y ^= y >>> 11; // TEMPERING_SHIFT_U(y)
y ^= (y << 7) & TEMPERING_MASK_B; // TEMPERING_SHIFT_S(y)
y ^= (y << 15) & TEMPERING_MASK_C; // TEMPERING_SHIFT_T(y)
y ^= (y >>> 18); // TEMPERING_SHIFT_L(y)
if (mti >= N) { // generate N words at one time
int kk;
for (kk = 0; kk < N - M; kk++) {
z = (mt[kk] & UPPER_MASK) | (mt[kk+1] & LOWER_MASK);
mt[kk] = mt[kk+M] ^ (z >>> 1) ^ mag01[z & 0x1];
}
for (; kk < N-1; kk++) {
z = (mt[kk] & UPPER_MASK) | (mt[kk+1] & LOWER_MASK);
mt[kk] = mt[kk+(M-N)] ^ (z >>> 1) ^ mag01[z & 0x1];
}
z = (mt[N-1] & UPPER_MASK) | (mt[0] & LOWER_MASK);
mt[N-1] = mt[M-1] ^ (z >>> 1) ^ mag01[z & 0x1];
mti = 0;
}
z = mt[mti++];
z ^= z >>> 11; // TEMPERING_SHIFT_U(z)
z ^= (z << 7) & TEMPERING_MASK_B; // TEMPERING_SHIFT_S(z)
z ^= (z << 15) & TEMPERING_MASK_C; // TEMPERING_SHIFT_T(z)
z ^= (z >>> 18); // TEMPERING_SHIFT_L(z)
/* derived from nextDouble documentation in jdk 1.2 docs, see top */
return ((((long)(y >>> 6)) << 27) + (z >>> 5)) / (double)(1L << 53);
}
}