import java.io.*;

/** 
 *
 * FIXME: This is the version from the java-based Evolutionary Computation Research System (ECJ 19), with slight changes. Really we should use the same twister we use in Contrib, and maybe update that! - toad 
 *
 * <h3>MersenneTwister and MersenneTwisterFast</h3>
 * <p><b>Version 13</b>, based on version MT199937(99/10/29)
 * of the Mersenne Twister algorithm found at 
 * <a href="http://www.math.keio.ac.jp/matumoto/emt.html">
 * The Mersenne Twister Home Page</a>, with the initialization
 * improved using the new 2002/1/26 initialization algorithm
 * By Sean Luke, October 2004.
 * 
 * <p><b>MersenneTwister</b> 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.
 *
 * <p><b>MersenneTwisterFast</b> 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 <i>not</i> 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.
 *
 * <h3>About the Mersenne Twister</h3>
 * <p>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.
 *
 * <p><b>Reference. </b>
 * Makato Matsumoto and Takuji Nishimura,
 * "Mersenne Twister: A 623-Dimensionally Equidistributed Uniform
 * Pseudo-Random Number Generator",
 * <i>ACM Transactions on Modeling and Computer Simulation,</i>
 * Vol. 8, No. 1, January 1998, pp 3--30.
 *
 * <h3>About this Version</h3>
 *
 * <p><b>Changes Since V12:</b> clone() method added.
 *
 * <p><b>Changes Since V11:</b> 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.
 *
 * <p><b>Changes Since V10:</b> 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.
 *
 * <p><b>Changes Since V9:</b> readState(stream) and writeState(stream)
 * provided.
 *
 * <p><b>Changes Since V8:</b> 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.
 *
 * <p><b>Changes Since V7:</b> 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.
 *
 * <p><b>Changes Since V6:</b> 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).
 * 
 * <p><b>Changes Since V5:</b> New empty constructor made to work the same
 * as java.util.Random -- namely, it seeds based on the current time in
 * milliseconds.
 *
 * <p><b>Changes Since V4:</b> New initialization algorithms.  See
 * (see <a href="http://www.math.keio.ac.jp/matumoto/MT2002/emt19937ar.html"</a>
 * http://www.math.keio.ac.jp/matumoto/MT2002/emt19937ar.html</a>)
 *
 * <p>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.
 *
 * <h3>Java notes</h3>
 * 
 * <p>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 
 * <a href="http://www.javasoft.com/products/jdk/1.2/docs/api/java/util/Random.html">
 * the JDK 1.2 java.util.Random documentation</a> 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.
 *
 * <p> 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.
 *
 * <p>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.
 *
 * <h3>License</h3>
 *
 * Copyright (c) 2003 by Sean Luke. <br>
 * Portions copyright (c) 1993 by Michael Lecuyer. <br>
 * All rights reserved. <br>
 *
 * <p>Redistribution and use in source and binary forms, with or without 
 * modification, are permitted provided that the following conditions are met:
 * <ul>
 * <li> Redistributions of source code must retain the above copyright notice, 
 * this list of conditions and the following disclaimer.
 * <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> 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.
 * </ul>
 * <p>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 13
*/

public class MersenneTwister extends java.util.Random implements Serializable, Cloneable
    {
    // 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;

    /* We're overriding all internal data, to my knowledge, so this should be okay */
    public Object clone() throws CloneNotSupportedException
        {
        MersenneTwister f = (MersenneTwister)(super.clone());
        f.mt = (int[])(mt.clone());
        f.mag01 = (int[])(mag01.clone());
        return f;
        }

    public boolean stateEquals(Object o)
        {
        if (o==this) return true;
        if (o == null || !(o instanceof MersenneTwister))
            return false;
        MersenneTwister other = (MersenneTwister) o;
        if (mti != other.mti) return false;
        for(int x=0;x<mag01.length;x++)
            if (mag01[x] != other.mag01[x]) return false;
        for(int x=0;x<mt.length;x++)
            if (mt[x] != other.mt[x]) return false;
        return true;
        }

    /** Reads the entire state of the MersenneTwister RNG from the stream */
    public void readState(DataInputStream stream) throws IOException
        {
        int len = mt.length;
        for(int x=0;x<len;x++) mt[x] = stream.readInt();
        
        len = mag01.length;
        for(int x=0;x<len;x++) mag01[x] = stream.readInt();
        
        mti = stream.readInt();
        __nextNextGaussian = stream.readDouble();
        __haveNextNextGaussian = stream.readBoolean();
        }
        
    /** Writes the entire state of the MersenneTwister RNG to the stream */
    public void writeState(DataOutputStream stream) throws IOException
        {
        int len = mt.length;
        for(int x=0;x<len;x++) stream.writeInt(mt[x]);
        
        len = mag01.length;
        for(int x=0;x<len;x++) stream.writeInt(mag01[x]);
        
        stream.writeInt(mti);
        stream.writeDouble(__nextNextGaussian);
        stream.writeBoolean(__haveNextNextGaussian);
        }


    /**
     * Constructor using the default seed.
     */
    public MersenneTwister()
        {
        this(System.currentTimeMillis());
        }
    
    /**
     * 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 MersenneTwister(final long seed)
        {
        super(seed);    /* just in case */
        setSeed(seed);
        }
    
    /**
     * Constructor using an array of integers as seed.
     * Your array must have a non-zero length.  Only the first 624 integers
     * in the array are used; if the array is shorter than this then
     * integers are repeatedly used in a wrap-around fashion.
     */
    public MersenneTwister(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).   
     */

    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<N; mti++) 
            {
            mt[mti] = 
                (1812433253 * (mt[mti-1] ^ (mt[mti-1] >>> 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 */
            }
        }


    /**
     * Sets the seed of the MersenneTwister using an array of integers.
     * Your array must have a non-zero length.  Only the first 624 integers
     * in the array are used; if the array is shorter than this then
     * integers are repeatedly used in a wrap-around fashion.
     */

    synchronized public void setSeed(final int[] array)
        {
        if (array.length == 0)
            throw new IllegalArgumentException("Array length must be greater than zero");
        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 <i>bits</i> bits filled with a random number.
     */
    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 synchronized 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.*/
    public boolean nextBoolean() {return next(1) != 0;}

    /** This generates a coin flip with a probability <tt>probability</tt>
        of returning true, else returning false. <tt>probability</tt> 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 <tt>probability</tt>
        of returning true, else returning false. <tt>probability</tt> 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. */

    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. */
    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. */

    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. */

    public void nextBytes(final byte[] bytes)    
        {
        for (int x=0;x<bytes.length;x++) bytes[x] = (byte)next(8);
        }

    /** For completeness' sake, though it's not in java.util.Random.  */
    
    public char nextChar()
        {
        // chars are 16-bit UniCode values
        return (char)(next(16));
        }

    /** For completeness' sake, though it's not in java.util.Random. */
    
    public short nextShort()
        {
        return (short)(next(16));
        }

    /** For completeness' sake, though it's not in java.util.Random.  */

    public byte nextByte()
        {
        return (byte)(next(8));
        }


    /** A bug fix for all JDK code including 1.2.  nextGaussian can theoretically
        ask for the log of 0 and divide it by 0! See Java bug 
        <a href="http://developer.java.sun.com/developer/bugParade/bugs/4254501.html">
        http://developer.java.sun.com/developer/bugParade/bugs/4254501.html</a>
    */

    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;

        MersenneTwister r;

        // CORRECTNESS TEST
        // COMPARE WITH http://www.math.keio.ac.jp/matumoto/CODES/MT2002/mt19937ar.out
        
        r = new MersenneTwister(new int[]{0x123, 0x234, 0x345, 0x456});
        System.out.println("Output of MersenneTwister 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");
          
        r = new MersenneTwister(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 MersenneTwisterFast.");
        System.out.println("The comparison with Random is removed from MersenneTwister 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
        // MersenneTwisterFast.java AND MersenneTwister.java

        
        System.out.println("\nGrab the first 1000 booleans");
        r = new MersenneTwister(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 MersenneTwister(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 MersenneTwister(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 MersenneTwister(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 MersenneTwister(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 MersenneTwister(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 MersenneTwister(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 MersenneTwister(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 MersenneTwister(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 MersenneTwister(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 MersenneTwister(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 MersenneTwister(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 MersenneTwister(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();
        
        }
    
    }
