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package org.fuzzydb.util;
import java.io.IOException;
import java.io.ObjectInputStream;
import java.io.ObjectOutputStream;
import java.io.Serializable;
/**
* MTRandom and MTRandomFast
* Version 9, based on version MT199937(99/10/29)
* of the Mersenne Twister algorithm found at
*
* The Mersenne Twister Home Page, with the initialization
* improved using the new 2002/1/26 initialization algorithm
* By Sean Luke, October 2004.
*
*
MTRandom is a drop-in subclass replacement
* for java.util.Random. It is properly synchronized and
* can be used in a multithreaded environment. On modern VMs such
* as HotSpot, it is approximately 1/3 slower than java.util.Random.
*
*
MTRandomFast is not a subclass of java.util.Random. It has
* the same public methods as Random does, however, and it is
* algorithmically identical to MTRandom. MTRandomFast
* has hard-code inlined all of its methods directly, and made all of them
* final (well, the ones of consequence anyway). Further, these
* methods are not synchronized, so the same MTRandomFast
* instance cannot be shared by multiple threads. But all this helps
* MTRandomFast achieve well over twice the speed of MTRandom.
* java.util.Random is about 1/3 slower than MTRandomFast.
*
*
About the Mersenne Twister
* This is a Java version of the C-program for MT19937: Integer version.
* The MT19937 algorithm was created by Makoto Matsumoto and Takuji Nishimura,
* who ask: "When you use this, send an email to: [email protected]
* with an appropriate reference to your work". Indicate that this
* is a translation of their algorithm into Java.
*
*
Reference.
* Makato Matsumoto and Takuji Nishimura,
* "Mersenne Twister: A 623-Dimensionally Equidistributed Uniform
* Pseudo-Random Number Generator",
* ACM Transactions on Modeling and Computer Simulation,
* Vol. 8, No. 1, January 1998, pp 3--30.
*
*
About this Version
*
* Changes Since V8: setSeed(int) was only using the first 28 bits
* of the seed; it should have been 32 bits. For small-number seeds the
* behavior is identical.
*
*
Changes Since V7: A documentation error in MTRandomFast
* (but not MTRandom) stated that nextDouble selects uniformly from
* the full-open interval [0,1]. It does not. nextDouble's contract is
* identical across MTRandomFast, MTRandom, and java.util.Random,
* namely, selection in the half-open interval [0,1). That is, 1.0 should
* not be returned. A similar contract exists in nextFloat.
*
*
Changes Since V6: License has changed from LGPL to BSD.
* New timing information to compare against
* java.util.Random. Recent versions of HotSpot have helped Random increase
* in speed to the point where it is faster than MTRandom but slower
* than MTRandomFast (which should be the case, as it's a less complex
* algorithm but is synchronized).
*
*
Changes Since V5: New empty constructor made to work the same
* as java.util.Random -- namely, it seeds based on the current time in
* milliseconds.
*
*
Changes Since V4: New initialization algorithms. See
* (see
* http://www.math.keio.ac.jp/matumoto/MT2002/emt19937ar.html)
*
*
The MTRandom code is based on standard MT19937 C/C++
* code by Takuji Nishimura,
* with suggestions from Topher Cooper and Marc Rieffel, July 1997.
* The code was originally translated into Java by Michael Lecuyer,
* January 1999, and the original code is Copyright (c) 1999 by Michael Lecuyer.
*
*
Java notes
*
* This implementation implements the bug fixes made
* in Java 1.2's version of Random, which means it can be used with
* earlier versions of Java. See
*
* the JDK 1.2 java.util.Random documentation for further documentation
* on the random-number generation contracts made. Additionally, there's
* an undocumented bug in the JDK java.util.Random.nextBytes() method,
* which this code fixes.
*
*
Just like java.util.Random, this
* generator accepts a long seed but doesn't use all of it. java.util.Random
* uses 48 bits. The Mersenne Twister instead uses 32 bits (int size).
* So it's best if your seed does not exceed the int range.
*
*
MTRandom can be used reliably
* on JDK version 1.1.5 or above. Earlier Java versions have serious bugs in
* java.util.Random; only MTRandomFast (and not MTRandom nor
* java.util.Random) should be used with them.
*
*
License
*
* 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.
*
@version 8
*/
public class MTRandom extends java.util.Random implements Serializable {
private static final long serialVersionUID = 3257009834682561590L;
// Global Instance ease of access
private static MTRandom instance = new MTRandom();
static public MTRandom getInstance() {
return instance;
}
// Period parameters
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[];
// a good initial seed (of int size, though stored in a long)
//private static final long GOOD_SEED = 4357;
/* implemented here because there's a bug in Random's implementation
of the Gaussian code (divide by zero, and log(0), ugh!), yet its
gaussian variables are private so we can't access them here. :-( */
private double __nextNextGaussian;
private boolean __haveNextNextGaussian;
/**
* Constructor using the default seed.
*/
public MTRandom() {
super();
// Random rnd = new Random();
// FIXME (nu->jc/ac): Why is seed not used??
// int seed = (int)(System.nanoTime()*hashCode() + System.currentTimeMillis()) + rnd.nextInt();
}
/**
* Constructor using a given seed. Though you pass this seed in
* as a long, it's best to make sure it's actually an integer.
*/
public MTRandom(final long seed)
{
super(seed); /* just in case */
setSeed(seed);
}
/**
* Constructor using an array.
*/
public MTRandom(final int[] array)
{
super(System.currentTimeMillis()); /* pick something at random just in case */
setSeed(array);
}
/**
* Initalize the pseudo random number generator. Don't
* pass in a long that's bigger than an int (Mersenne Twister
* only uses the first 32 bits for its seed).
*/
@Override
synchronized public void setSeed(final long seed)
{
// it's always good style to call super
super.setSeed(seed);
// Due to a bug in java.util.Random clear up to 1.2, we're
// doing our own Gaussian variable.
__haveNextNextGaussian = false;
mt = new int[N];
mag01 = new int[2];
mag01[0] = 0x0;
mag01[1] = MATRIX_A;
mt[0]= (int)(seed & 0xffffffff);
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.
*/
synchronized public 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 */
}
/**
* Returns an integer with bits bits filled with a random number.
*/
@Override
synchronized protected int next(final int bits)
{
int y;
if (mti >= N) // generate N words at one time
{
int kk;
final int[] mt = this.mt; // locals are slightly faster
final int[] mag01 = this.mag01; // locals are slightly faster
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)
return y >>> (32 - bits); // hope that's right!
}
/* If you've got a truly old version of Java, you can omit these
two next methods. */
private synchronized void writeObject(final ObjectOutputStream out)
throws IOException
{
// just so we're synchronized.
out.defaultWriteObject();
}
private void readObject (final ObjectInputStream in)
throws IOException, ClassNotFoundException
{
// just so we're synchronized.
in.defaultReadObject();
}
/** This method is missing from jdk 1.0.x and below. JDK 1.1
includes this for us, but what the heck.*/
@Override
public boolean nextBoolean() {return next(1) != 0;}
/** This generates a coin flip with a probability probability
of returning true, else returning false. probability must
be between 0.0 and 1.0, inclusive. Not as precise a random real
event as nextBoolean(double), but twice as fast. To explicitly
use this, remember you may need to cast to float first. */
public boolean nextBoolean (final float probability)
{
if (probability < 0.0f || probability > 1.0f)
throw new IllegalArgumentException ("probability must be between 0.0 and 1.0 inclusive.");
if (probability==0.0f) return false; // fix half-open issues
else if (probability==1.0f) return true; // fix half-open issues
return nextFloat() < probability;
}
/** This generates a coin flip with a probability probability
of returning true, else returning false. probability must
be between 0.0 and 1.0, inclusive. */
public boolean nextBoolean (final double probability)
{
if (probability < 0.0 || probability > 1.0)
throw new IllegalArgumentException ("probability must be between 0.0 and 1.0 inclusive.");
if (probability==0.0) return false; // fix half-open issues
else if (probability==1.0) return true; // fix half-open issues
return nextDouble() < probability;
}
/** This method is missing from JDK 1.1 and below. JDK 1.2
includes this for us, but what the heck. */
@Override
public int nextInt(final int n)
{
if (n<=0)
throw new IllegalArgumentException("n must be >= 0");
if ((n & -n) == n)
return (int)((n * (long)next(31)) >> 31);
int bits, val;
do
{
bits = next(31);
val = bits % n;
}
while(bits - val + (n-1) < 0);
return val;
}
/** This method is for completness' sake.
Returns a long drawn uniformly from 0 to n-1. Suffice it to say,
n must be > 0, or an IllegalArgumentException is raised. */
public long nextLong(final long n)
{
if (n<=0)
throw new IllegalArgumentException("n must be >= 0");
long bits, val;
do
{
bits = (nextLong() >>> 1);
val = bits % n;
}
while(bits - val + (n-1) < 0);
return val;
}
/** A bug fix for versions of JDK 1.1 and below. JDK 1.2 fixes
this for us, but what the heck. */
@Override
public double nextDouble()
{
return (((long)next(26) << 27) + next(27))
/ (double)(1L << 53);
}
/** A bug fix for versions of JDK 1.1 and below. JDK 1.2 fixes
this for us, but what the heck. */
@Override
public float nextFloat()
{
return next(24) / ((float)(1 << 24));
}
/** A bug fix for all versions of the JDK. The JDK appears to
use all four bytes in an integer as independent byte values!
Totally wrong. I've submitted a bug report. */
@Override
public void nextBytes(final byte[] bytes)
{
for (int x=0;x
http://developer.java.sun.com/developer/bugParade/bugs/4254501.html
*/
@Override
synchronized public double nextGaussian()
{
if (__haveNextNextGaussian)
{
__haveNextNextGaussian = false;
return __nextNextGaussian;
}
else
{
double v1, v2, s;
do
{
v1 = 2 * nextDouble() - 1; // between -1.0 and 1.0
v2 = 2 * nextDouble() - 1; // between -1.0 and 1.0
s = v1 * v1 + v2 * v2;
} while (s >= 1 || s==0 );
double multiplier = /*Strict*/Math.sqrt(-2 * /*Strict*/Math.log(s)/s);
__nextNextGaussian = v2 * multiplier;
__haveNextNextGaussian = true;
return v1 * multiplier;
}
}
/**
* Tests the code.
*/
public static void main(String args[])
{
int j;
MTRandom r;
// CORRECTNESS TEST
// COMPARE WITH http://www.math.keio.ac.jp/matumoto/CODES/MT2002/mt19937ar.out
r = new MTRandom(new int[]{0x123, 0x234, 0x345, 0x456});
System.out.println("Output of MTRandom with new (2002/1/26) seeding mechanism");
for (j=0;j<1000;j++)
{
// first, convert the int from signed to "unsigned"
long l = r.nextInt();
if (l < 0 ) l += 4294967296L; // max int value
String s = String.valueOf(l);
while(s.length() < 10) s = " " + s; // buffer
System.out.print(s + " ");
if (j%5==4) System.out.println();
}
// SPEED TEST
final long SEED = 4357;
int xx; long ms;
System.out.println("\nTime to test grabbing 100000000 ints");
r = new MTRandom(SEED);
ms = System.currentTimeMillis();
xx=0;
for (j = 0; j < 100000000; j++)
xx += r.nextInt();
System.out.println("Mersenne Twister: " + (System.currentTimeMillis()-ms) + " Ignore this: " + xx);
System.out.println("To compare this with java.util.Random, run this same test on MTRandomFast.");
System.out.println("The comparison with Random is removed from MTRandom because it is a proper");
System.out.println("subclass of Random and this unfairly makes some of Random's methods un-inlinable,");
System.out.println("so it would make Random look worse than it is.");
// TEST TO COMPARE TYPE CONVERSION BETWEEN
// MTRandomFast.java AND MTRandom.java
System.out.println("\nGrab the first 1000 booleans");
r = new MTRandom(SEED);
for (j = 0; j < 1000; j++)
{
System.out.print(r.nextBoolean() + " ");
if (j%8==7) System.out.println();
}
if (!(j%8==7)) System.out.println();
System.out.println("\nGrab 1000 booleans of increasing probability using nextBoolean(double)");
r = new MTRandom(SEED);
for (j = 0; j < 1000; j++)
{
System.out.print(r.nextBoolean((j/999.0)) + " ");
if (j%8==7) System.out.println();
}
if (!(j%8==7)) System.out.println();
System.out.println("\nGrab 1000 booleans of increasing probability using nextBoolean(float)");
r = new MTRandom(SEED);
for (j = 0; j < 1000; j++)
{
System.out.print(r.nextBoolean((j/999.0f)) + " ");
if (j%8==7) System.out.println();
}
if (!(j%8==7)) System.out.println();
byte[] bytes = new byte[1000];
System.out.println("\nGrab the first 1000 bytes using nextBytes");
r = new MTRandom(SEED);
r.nextBytes(bytes);
for (j = 0; j < 1000; j++)
{
System.out.print(bytes[j] + " ");
if (j%16==15) System.out.println();
}
if (!(j%16==15)) System.out.println();
byte b;
System.out.println("\nGrab the first 1000 bytes -- must be same as nextBytes");
r = new MTRandom(SEED);
for (j = 0; j < 1000; j++)
{
System.out.print((b = r.nextByte()) + " ");
if (b!=bytes[j]) System.out.print("BAD ");
if (j%16==15) System.out.println();
}
if (!(j%16==15)) System.out.println();
System.out.println("\nGrab the first 1000 shorts");
r = new MTRandom(SEED);
for (j = 0; j < 1000; j++)
{
System.out.print(r.nextShort() + " ");
if (j%8==7) System.out.println();
}
if (!(j%8==7)) System.out.println();
System.out.println("\nGrab the first 1000 ints");
r = new MTRandom(SEED);
for (j = 0; j < 1000; j++)
{
System.out.print(r.nextInt() + " ");
if (j%4==3) System.out.println();
}
if (!(j%4==3)) System.out.println();
System.out.println("\nGrab the first 1000 ints of different sizes");
r = new MTRandom(SEED);
int max = 1;
for (j = 0; j < 1000; j++)
{
System.out.print(r.nextInt(max) + " ");
max *= 2;
if (max <= 0) max = 1;
if (j%4==3) System.out.println();
}
if (!(j%4==3)) System.out.println();
System.out.println("\nGrab the first 1000 longs");
r = new MTRandom(SEED);
for (j = 0; j < 1000; j++)
{
System.out.print(r.nextLong() + " ");
if (j%3==2) System.out.println();
}
if (!(j%3==2)) System.out.println();
System.out.println("\nGrab the first 1000 longs of different sizes");
r = new MTRandom(SEED);
long max2 = 1;
for (j = 0; j < 1000; j++)
{
System.out.print(r.nextLong(max2) + " ");
max2 *= 2;
if (max2 <= 0) max2 = 1;
if (j%4==3) System.out.println();
}
if (!(j%4==3)) System.out.println();
System.out.println("\nGrab the first 1000 floats");
r = new MTRandom(SEED);
for (j = 0; j < 1000; j++)
{
System.out.print(r.nextFloat() + " ");
if (j%4==3) System.out.println();
}
if (!(j%4==3)) System.out.println();
System.out.println("\nGrab the first 1000 doubles");
r = new MTRandom(SEED);
for (j = 0; j < 1000; j++)
{
System.out.print(r.nextDouble() + " ");
if (j%3==2) System.out.println();
}
if (!(j%3==2)) System.out.println();
System.out.println("\nGrab the first 1000 gaussian doubles");
r = new MTRandom(SEED);
for (j = 0; j < 1000; j++)
{
System.out.print(r.nextGaussian() + " ");
if (j%3==2) System.out.println();
}
if (!(j%3==2)) System.out.println();
}
}