Version 17, 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. * *
MersenneTwister 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. * *
MersenneTwisterFast is not a subclass of java.util.Random. It has * the same public methods as Random does, however, and it is * algorithmically identical to MersenneTwister. MersenneTwisterFast * 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 MersenneTwisterFast * instance cannot be shared by multiple threads. But all this helps * MersenneTwisterFast achieve well over twice the speed of MersenneTwister. * java.util.Random is about 1/3 slower than MersenneTwisterFast. * *
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: matumoto@math.keio.ac.jp * 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. * *
Changes since V16: Added nextDouble(includeZero, includeOne) and * nextFloat(includeZero, includeOne) to allow for half-open, fully-closed, and * fully-open intervals. * *
Changes Since V15: Added serialVersionUID to quiet compiler warnings * from Sun's overly verbose compilers as of JDK 1.5. * *
Changes Since V14: made strictfp, with StrictMath.log and StrictMath.sqrt * in nextGaussian instead of Math.log and Math.sqrt. This is largely just to be safe, * as it presently makes no difference in the speed, correctness, or results of the * algorithm. * *
Changes Since V13: clone() method CloneNotSupportedException removed. * *
Changes Since V12: clone() method added. * *
Changes Since V11: stateEquals(...) method added. MersenneTwisterFast * is equal to other MersenneTwisterFasts with identical state; likewise * MersenneTwister is equal to other MersenneTwister with identical state. * This isn't equals(...) because that requires a contract of immutability * to compare by value. * *
Changes Since V10: A documentation error suggested that * setSeed(int[]) required an int[] array 624 long. In fact, the array * can be any non-zero length. The new version also checks for this fact. * *
Changes Since V9: readState(stream) and writeState(stream) * provided. * *
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 MersenneTwisterFast * (but not MersenneTwister) stated that nextDouble selects uniformly from * the full-open interval [0,1]. It does not. nextDouble's contract is * identical across MersenneTwisterFast, MersenneTwister, 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 MersenneTwister but slower * than MersenneTwisterFast (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 MersenneTwister 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. * *
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. * *
MersenneTwister can be used reliably * on JDK version 1.1.5 or above. Earlier Java versions have serious bugs in * java.util.Random; only MersenneTwisterFast (and not MersenneTwister nor * java.util.Random) should be used with them. * *
Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are met: *
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 17
*/
// Note: this class is hard-inlined in all of its methods. This makes some of
// the methods well-nigh unreadable in their complexity. In fact, the Mersenne
// Twister is fairly easy code to understand: if you're trying to get a handle
// on the code, I strongly suggest looking at MersenneTwister.java first.
// -- Sean
public strictfp class MersenneTwisterFast implements Serializable, Cloneable
{
// Serialization
private static final long serialVersionUID = -8219700664442619525L; // locked as of Version 15
// 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;
private double __nextNextGaussian;
private boolean __haveNextNextGaussian;
/* We're overriding all internal data, to my knowledge, so this should be okay */
public Object clone()
{
try
{
MersenneTwisterFast f = (MersenneTwisterFast)(super.clone());
f.mt = (int[])(mt.clone());
f.mag01 = (int[])(mag01.clone());
return f;
}
catch (CloneNotSupportedException e) { throw new InternalError(); } // should never happen
}
public boolean stateEquals(Object o)
{
if (o==this) return true;
if (o == null || !(o instanceof MersenneTwisterFast))
return false;
MersenneTwisterFast other = (MersenneTwisterFast) o;
if (mti != other.mti) return false;
for(int x=0;x This version preserves all possible random values in the double range.
*/
public double nextDouble(boolean includeZero, boolean includeOne)
{
double d = 0.0;
do
{
d = nextDouble(); // grab a value, initially from half-open [0.0, 1.0)
if (includeOne && nextBoolean()) d += 1.0; // if includeOne, with 1/2 probability, push to [1.0, 2.0)
}
while ( (d > 1.0) || // everything above 1.0 is always invalid
(!includeZero && d == 0.0)); // if we're not including zero, 0.0 is invalid
return d;
}
public final double nextGaussian()
{
if (__haveNextNextGaussian)
{
__haveNextNextGaussian = false;
return __nextNextGaussian;
}
else
{
double v1, v2, s;
do
{
int y;
int z;
int a;
int b;
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)
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++)
{
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)
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++)
{
a = (mt[kk] & UPPER_MASK) | (mt[kk+1] & LOWER_MASK);
mt[kk] = mt[kk+M] ^ (a >>> 1) ^ mag01[a & 0x1];
}
for (; kk < N-1; kk++)
{
a = (mt[kk] & UPPER_MASK) | (mt[kk+1] & LOWER_MASK);
mt[kk] = mt[kk+(M-N)] ^ (a >>> 1) ^ mag01[a & 0x1];
}
a = (mt[N-1] & UPPER_MASK) | (mt[0] & LOWER_MASK);
mt[N-1] = mt[M-1] ^ (a >>> 1) ^ mag01[a & 0x1];
mti = 0;
}
a = mt[mti++];
a ^= a >>> 11; // TEMPERING_SHIFT_U(a)
a ^= (a << 7) & TEMPERING_MASK_B; // TEMPERING_SHIFT_S(a)
a ^= (a << 15) & TEMPERING_MASK_C; // TEMPERING_SHIFT_T(a)
a ^= (a >>> 18); // TEMPERING_SHIFT_L(a)
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++)
{
b = (mt[kk] & UPPER_MASK) | (mt[kk+1] & LOWER_MASK);
mt[kk] = mt[kk+M] ^ (b >>> 1) ^ mag01[b & 0x1];
}
for (; kk < N-1; kk++)
{
b = (mt[kk] & UPPER_MASK) | (mt[kk+1] & LOWER_MASK);
mt[kk] = mt[kk+(M-N)] ^ (b >>> 1) ^ mag01[b & 0x1];
}
b = (mt[N-1] & UPPER_MASK) | (mt[0] & LOWER_MASK);
mt[N-1] = mt[M-1] ^ (b >>> 1) ^ mag01[b & 0x1];
mti = 0;
}
b = mt[mti++];
b ^= b >>> 11; // TEMPERING_SHIFT_U(b)
b ^= (b << 7) & TEMPERING_MASK_B; // TEMPERING_SHIFT_S(b)
b ^= (b << 15) & TEMPERING_MASK_C; // TEMPERING_SHIFT_T(b)
b ^= (b >>> 18); // TEMPERING_SHIFT_L(b)
/* derived from nextDouble documentation in jdk 1.2 docs, see top */
v1 = 2 *
(((((long)(y >>> 6)) << 27) + (z >>> 5)) / (double)(1L << 53))
- 1;
v2 = 2 * (((((long)(a >>> 6)) << 27) + (b >>> 5)) / (double)(1L << 53))
- 1;
s = v1 * v1 + v2 * v2;
} while (s >= 1 || s==0);
double multiplier = StrictMath.sqrt(-2 * StrictMath.log(s)/s);
__nextNextGaussian = v2 * multiplier;
__haveNextNextGaussian = true;
return v1 * multiplier;
}
}
/** Returns a random float in the half-open range from [0.0f,1.0f). Thus 0.0f is a valid
result but 1.0f is not. */
public final float nextFloat()
{
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 >>> 8) / ((float)(1 << 24));
}
/** Returns a float in the range from 0.0f to 1.0f, possibly inclusive of 0.0f and 1.0f themselves. Thus:
This version preserves all possible random values in the float range.
*/
public double nextFloat(boolean includeZero, boolean includeOne)
{
float d = 0.0f;
do
{
d = nextFloat(); // grab a value, initially from half-open [0.0f, 1.0f)
if (includeOne && nextBoolean()) d += 1.0f; // if includeOne, with 1/2 probability, push to [1.0f, 2.0f)
}
while ( (d > 1.0f) || // everything above 1.0f is always invalid
(!includeZero && d == 0.0f)); // if we're not including zero, 0.0f is invalid
return d;
}
/** Returns an integer drawn uniformly from 0 to n-1. Suffice it to say,
n must be > 0, or an IllegalArgumentException is raised. */
public final int nextInt(final int n)
{
if (n<=0)
throw new IllegalArgumentException("n must be positive, got: " + n);
if ((n & -n) == n) // i.e., n is a power of 2
{
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 (int)((n * (long) (y >>> 1) ) >> 31);
}
int bits, val;
do
{
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)
bits = (y >>> 1);
val = bits % n;
} while(bits - val + (n-1) < 0);
return val;
}
/**
* Tests the code.
*/
public static void main(String args[])
{
int j;
MersenneTwisterFast r;
// CORRECTNESS TEST
// COMPARE WITH http://www.math.keio.ac.jp/matumoto/CODES/MT2002/mt19937ar.out
r = new MersenneTwisterFast(new int[]{0x123, 0x234, 0x345, 0x456});
System.out.println("Output of MersenneTwisterFast with new (2002/1/26) seeding mechanism");
for (j=0;j<1000;j++)
{
// first, convert the int from signed to "unsigned"
long l = (long)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");
Random rr = new Random(SEED);
xx = 0;
ms = System.currentTimeMillis();
for (j = 0; j < 100000000; j++)
xx += rr.nextInt();
System.out.println("java.util.Random: " + (System.currentTimeMillis()-ms) + " Ignore this: " + xx);
r = new MersenneTwisterFast(SEED);
ms = System.currentTimeMillis();
xx=0;
for (j = 0; j < 100000000; j++)
xx += r.nextInt();
System.out.println("Mersenne Twister Fast: " + (System.currentTimeMillis()-ms) + " Ignore this: " + xx);
// TEST TO COMPARE TYPE CONVERSION BETWEEN
// MersenneTwisterFast.java AND MersenneTwister.java
System.out.println("\nGrab the first 1000 booleans");
r = new MersenneTwisterFast(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 MersenneTwisterFast(SEED);
for (j = 0; j < 1000; j++)
{
System.out.print(r.nextBoolean((double)(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 MersenneTwisterFast(SEED);
for (j = 0; j < 1000; j++)
{
System.out.print(r.nextBoolean((float)(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 MersenneTwisterFast(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 MersenneTwisterFast(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 MersenneTwisterFast(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 MersenneTwisterFast(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 MersenneTwisterFast(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 MersenneTwisterFast(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 MersenneTwisterFast(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 MersenneTwisterFast(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 MersenneTwisterFast(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 MersenneTwisterFast(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();
}
}
Expression Interval
nextDouble(false, false) (0.0, 1.0)
nextDouble(true, false) [0.0, 1.0)
nextDouble(false, true) (0.0, 1.0]
nextDouble(true, true) [0.0, 1.0]
Expression Interval
nextFloat(false, false) (0.0f, 1.0f)
nextFloat(true, false) [0.0f, 1.0f)
nextFloat(false, true) (0.0f, 1.0f]
nextFloat(true, true) [0.0f, 1.0f]