import java.util.*;
import java.lang.*;
import java.io.*;
// Генерация последовательности с помощью MersenneTwister по определенному seed
class SequenceCreation {
// вход в нашу программу
// Считываем указанное пользователем смещение (seed) из stdin.
// Берется из текстовой презентации последовательности в игре.
long seed = readStdIn();
// Создаем наш генератор с указанным смещением
MersenneTwister генератор = new MersenneTwister(seed);
// Генерируем 135 пар заров в цикле
for (int счётчик = 1; счётчик <= 135; счётчик++) {
// вызов "генератор.nextInt(6)" — выдает нам из последовательности
// следующее целое число от 0 до 5, соответственно к результату прибавляем единицу
int кубик1 = генератор.nextInt(6) + 1; // генерируем первый кубик
int кубик2 = генератор.nextInt(6) + 1; // генерируем второй кубик
// выводим на экран разделяя оба кубика двоеточием и ставя запятую с пробелом после
System.
out.
print(кубик
1 + ":" + кубик
2 + ", "); }
} // конец
public static long readStdIn() {
try {
byte[] buf
= new byte[System.
in.
available()]; System.
out.
println("Неверно задано смещение"); return 0;
}
}
// Все что ниже, это сам Вихрь Мерссена
// взят отсюда _https://c...content-available-to-author-only...u.edu/~sean/research/
// код _https://c...content-available-to-author-only...u.edu/~sean/research/mersenne/MersenneTwister.java
// ec.util.MersenneTwister;
/**
* <h3>MersenneTwister and MersenneTwisterFast</h3>
* <p><b>Version 20</b>, based on version MT199937(99/10/29)
* of the Mersenne Twister algorithm found at
* <a href="http://w...content-available-to-author-only...c.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 V19:</b> nextFloat(boolean, boolean) now returns float,
* not double.
*
* <p><b>Changes since V18:</b> Removed old final declarations, which used to
* potentially speed up the code, but no longer.
*
* <p><b>Changes since V17:</b> Removed vestigial references to &= 0xffffffff
* which stemmed from the original C code. The C code could not guarantee that
* ints were 32 bit, hence the masks. The vestigial references in the Java
* code were likely optimized out anyway.
*
* <p><b>Changes since V16:</b> Added nextDouble(includeZero, includeOne) and
* nextFloat(includeZero, includeOne) to allow for half-open, fully-closed, and
* fully-open intervals.
*
* <p><b>Changes Since V15:</b> Added serialVersionUID to quiet compiler warnings
* from Sun's overly verbose compilers as of JDK 1.5.
*
* <p><b>Changes Since V14:</b> 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.
*
* <p><b>Changes Since V13:</b> clone() method CloneNotSupportedException removed.
*
* <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://w...content-available-to-author-only...c.jp/matumoto/MT2002/emt19937ar.html"</a>
* http://w...content-available-to-author-only...c.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://w...content-available-to-author-only...t.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 20
*/
{
// Serialization
private static final long serialVersionUID = -4035832775130174188L; // 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;
/* 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 */
{
try
{
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 */
{
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 */
{
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(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(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(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);
mt[0] = (int) seed;
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(int[] array)
{
if (array.length == 0)
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(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. */
{
// just so we're synchronized.
out.defaultWriteObject();
}
{
// 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 (float probability)
{
if (probability < 0.0f || probability > 1.0f)
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 (double probability)
{
if (probability < 0.0 || probability > 1.0)
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(int n)
{
if (n<=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(long n)
{
if (n<=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);
}
/** Returns a double in the range from 0.0 to 1.0, possibly inclusive of 0.0 and 1.0 themselves. Thus:
<p><table border=0>
<th><td>Expression<td>Interval
<tr><td>nextDouble(false, false)<td>(0.0, 1.0)
<tr><td>nextDouble(true, false)<td>[0.0, 1.0)
<tr><td>nextDouble(false, true)<td>(0.0, 1.0]
<tr><td>nextDouble(true, true)<td>[0.0, 1.0]
</table>
<p>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;
}
/** 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));
}
/** Returns a float in the range from 0.0f to 1.0f, possibly inclusive of 0.0f and 1.0f themselves. Thus:
<p><table border=0>
<th><td>Expression<td>Interval
<tr><td>nextFloat(false, false)<td>(0.0f, 1.0f)
<tr><td>nextFloat(true, false)<td>[0.0f, 1.0f)
<tr><td>nextFloat(false, true)<td>(0.0f, 1.0f]
<tr><td>nextFloat(true, true)<td>[0.0f, 1.0f]
</table>
<p>This version preserves all possible random values in the float range.
*/
public float 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;
}
/** 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(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://d...content-available-to-author-only...n.com/developer/bugParade/bugs/4254501.html">
http://d...content-available-to-author-only...n.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 );
__nextNextGaussian = v2 * multiplier;
__haveNextNextGaussian = true;
return v1 * multiplier;
}
}
}
}