391 lines
12 KiB
Java
391 lines
12 KiB
Java
/* java.util.Random
|
|
Copyright (C) 1998, 1999, 2000, 2001 Free Software Foundation, Inc.
|
|
|
|
This file is part of GNU Classpath.
|
|
|
|
GNU Classpath is free software; you can redistribute it and/or modify
|
|
it under the terms of the GNU General Public License as published by
|
|
the Free Software Foundation; either version 2, or (at your option)
|
|
any later version.
|
|
|
|
GNU Classpath is distributed in the hope that it will be useful, but
|
|
WITHOUT ANY WARRANTY; without even the implied warranty of
|
|
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
|
|
General Public License for more details.
|
|
|
|
You should have received a copy of the GNU General Public License
|
|
along with GNU Classpath; see the file COPYING. If not, write to the
|
|
Free Software Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA
|
|
02111-1307 USA.
|
|
|
|
Linking this library statically or dynamically with other modules is
|
|
making a combined work based on this library. Thus, the terms and
|
|
conditions of the GNU General Public License cover the whole
|
|
combination.
|
|
|
|
As a special exception, the copyright holders of this library give you
|
|
permission to link this library with independent modules to produce an
|
|
executable, regardless of the license terms of these independent
|
|
modules, and to copy and distribute the resulting executable under
|
|
terms of your choice, provided that you also meet, for each linked
|
|
independent module, the terms and conditions of the license of that
|
|
module. An independent module is a module which is not derived from
|
|
or based on this library. If you modify this library, you may extend
|
|
this exception to your version of the library, but you are not
|
|
obligated to do so. If you do not wish to do so, delete this
|
|
exception statement from your version. */
|
|
|
|
|
|
package java.util;
|
|
|
|
/**
|
|
* This class generates pseudorandom numbers. It uses the same
|
|
* algorithm as the original JDK-class, so that your programs behave
|
|
* exactly the same way, if started with the same seed.
|
|
*
|
|
* The algorithm is described in <em>The Art of Computer Programming,
|
|
* Volume 2</em> by Donald Knuth in Section 3.2.1.
|
|
*
|
|
* If two instances of this class are created with the same seed and
|
|
* the same calls to these classes are made, they behave exactly the
|
|
* same way. This should be even true for foreign implementations
|
|
* (like this), so every port must use the same algorithm as described
|
|
* here.
|
|
*
|
|
* If you want to implement your own pseudorandom algorithm, you
|
|
* should extend this class and overload the <code>next()</code> and
|
|
* <code>setSeed(long)</code> method. In that case the above
|
|
* paragraph doesn't apply to you.
|
|
*
|
|
* This class shouldn't be used for security sensitive purposes (like
|
|
* generating passwords or encryption keys. See <code>SecureRandom</code>
|
|
* in package <code>java.security</code> for this purpose.
|
|
*
|
|
* For simple random doubles between 0.0 and 1.0, you may consider using
|
|
* Math.random instead.
|
|
*
|
|
* @see java.security.SecureRandom
|
|
* @see Math#random()
|
|
* @author Jochen Hoenicke */
|
|
public class Random implements java.io.Serializable
|
|
{
|
|
/**
|
|
* True if the next nextGaussian is available. This is used by
|
|
* nextGaussian, which generates two gaussian numbers by one call,
|
|
* and returns the second on the second call.
|
|
* @see #nextGaussian. */
|
|
private boolean haveNextNextGaussian;
|
|
/**
|
|
* The next nextGaussian if available. This is used by nextGaussian,
|
|
* which generates two gaussian numbers by one call, and returns the
|
|
* second on the second call.
|
|
* @see #nextGaussian.
|
|
*/
|
|
private double nextNextGaussian;
|
|
/**
|
|
* The seed. This is the number set by setSeed and which is used
|
|
* in next.
|
|
* @see #next
|
|
*/
|
|
private long seed;
|
|
|
|
private static final long serialVersionUID = 3905348978240129619L;
|
|
|
|
/**
|
|
* Creates a new pseudorandom number generator. The seed is initialized
|
|
* to the current time as follows.
|
|
* <pre>
|
|
* setSeed(System.currentTimeMillis());
|
|
* </pre>
|
|
* @see System#currentTimeMillis()
|
|
*/
|
|
public Random()
|
|
{
|
|
setSeed(System.currentTimeMillis());
|
|
}
|
|
|
|
/**
|
|
* Creates a new pseudorandom number generator, starting with the
|
|
* specified seed. This does:
|
|
* <pre>
|
|
* setSeed(seed);
|
|
* </pre>
|
|
* @param seed the initial seed.
|
|
*/
|
|
public Random(long seed)
|
|
{
|
|
setSeed(seed);
|
|
}
|
|
|
|
/**
|
|
* Sets the seed for this pseudorandom number generator. As described
|
|
* above, two instances of the same random class, starting with the
|
|
* same seed, should produce the same results, if the same methods
|
|
* are called. The implementation for java.util.Random is:
|
|
* <pre>
|
|
* public synchronized void setSeed(long seed) {
|
|
* this.seed = (seed ^ 0x5DEECE66DL) & ((1L << 48) - 1);
|
|
* haveNextNextGaussian = false;
|
|
* }
|
|
* </pre>
|
|
*/
|
|
public synchronized void setSeed(long seed)
|
|
{
|
|
this.seed = (seed ^ 0x5DEECE66DL) & ((1L << 48) - 1);
|
|
haveNextNextGaussian = false;
|
|
}
|
|
|
|
/**
|
|
* Generates the next pseudorandom number. This returns
|
|
* an int value whose <code>bits</code> low order bits are
|
|
* independent chosen random bits (0 and 1 are equally likely).
|
|
* The implementation for java.util.Random is:
|
|
* <pre>
|
|
* protected synchronized int next(int bits) {
|
|
* seed = (seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1);
|
|
* return (int) (seed >>> (48 - bits));
|
|
* }
|
|
* </pre>
|
|
* @param bits the number of random bits to generate. Must be in range
|
|
* 1..32.
|
|
* @return the next pseudorandom value.
|
|
* @since JDK1.1
|
|
*/
|
|
protected synchronized int next(int bits)
|
|
/*{ require { 1 <= bits && bits <=32 ::
|
|
"bits "+bits+" not in range [1..32]" } } */
|
|
{
|
|
seed = (seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1);
|
|
return (int) (seed >>> (48 - bits));
|
|
}
|
|
|
|
/**
|
|
* Fills an array of bytes with random numbers. All possible values
|
|
* are (approximately) equally likely.
|
|
* The JDK documentation gives no implementation, but it seems to be:
|
|
* <pre>
|
|
* public void nextBytes(byte[] bytes) {
|
|
* for (int i=0; i< bytes.length; i+=4) {
|
|
* int random = next(32);
|
|
* for (int j=0; i+j< bytes.length && j<4; j++)
|
|
* bytes[i+j] = (byte) (random & 0xff)
|
|
* random >>= 8;
|
|
* }
|
|
* }
|
|
* }
|
|
* </pre>
|
|
* @param bytes The byte array that should be filled.
|
|
* @since JDK1.1
|
|
*/
|
|
public void nextBytes(byte[] bytes)
|
|
/*{ require { bytes != null :: "bytes is null"; } } */
|
|
{
|
|
int random;
|
|
/* Do a little bit unrolling of the above algorithm. */
|
|
int max = bytes.length & ~0x3;
|
|
for (int i = 0; i < max; i += 4)
|
|
{
|
|
random = next(32);
|
|
bytes[i] = (byte) random;
|
|
bytes[i + 1] = (byte) (random >> 8);
|
|
bytes[i + 2] = (byte) (random >> 16);
|
|
bytes[i + 3] = (byte) (random >> 24);
|
|
}
|
|
if (max < bytes.length)
|
|
{
|
|
random = next(32);
|
|
for (int j = max; j < bytes.length; j++)
|
|
{
|
|
bytes[j] = (byte) random;
|
|
random >>= 8;
|
|
}
|
|
}
|
|
}
|
|
|
|
/**
|
|
* Generates the next pseudorandom number. This returns
|
|
* an int value whose 32 bits are independent chosen random bits
|
|
* (0 and 1 are equally likely). The implementation for
|
|
* java.util.Random is:
|
|
* <pre>
|
|
* public int nextInt() {
|
|
* return next(32);
|
|
* }
|
|
* </pre>
|
|
*
|
|
* @return the next pseudorandom value. */
|
|
public int nextInt()
|
|
{
|
|
return next(32);
|
|
}
|
|
|
|
/**
|
|
* Generates the next pseudorandom number. This returns
|
|
* a value between 0(inclusive) and <code>n</code>(exclusive), and
|
|
* each value has the same likelihodd (1/<code>n</code>).
|
|
* (0 and 1 are equally likely). The implementation for
|
|
* java.util.Random is:
|
|
* <pre>
|
|
* public int nextInt(int n) {
|
|
* if (n<=0)
|
|
* throw new IllegalArgumentException("n must be positive");
|
|
* if ((n & -n) == n) // i.e., n is a power of 2
|
|
* return (int)((n * (long)next(31)) >> 31);
|
|
* int bits, val;
|
|
* do {
|
|
* bits = next(32);
|
|
* val = bits % n;
|
|
* } while(bits - val + (n-1) < 0);
|
|
* return val;
|
|
* }
|
|
* </pre>
|
|
* This algorithm would return every value with exactly the same
|
|
* probability, if the next()-method would be a perfect random number
|
|
* generator.
|
|
*
|
|
* The loop at the bottom only accepts a value, if the random
|
|
* number was between 0 and the highest number less then 1<<31,
|
|
* which is divisible by n. The probability for this is high for small
|
|
* n, and the worst case is 1/2 (for n=(1<<30)+1).
|
|
*
|
|
* The special treatment for n = power of 2, selects the high bits of
|
|
* the random number (the loop at the bottom would select the low order
|
|
* bits). This is done, because the low order bits of linear congruential
|
|
* number generators (like the one used in this class) are known to be
|
|
* ``less random'' than the high order bits.
|
|
*
|
|
* @param n the upper bound.
|
|
* @exception IllegalArgumentException if the given upper bound is negative
|
|
* @return the next pseudorandom value.
|
|
*/
|
|
public int nextInt(int n)
|
|
/*{ require { n > 0 :: "n must be positive"; } } */
|
|
{
|
|
if (n <= 0)
|
|
throw new IllegalArgumentException("n must be positive");
|
|
if ((n & -n) == n) // i.e., n is a power of 2
|
|
return (int) ((n * (long) next(31)) >> 31);
|
|
int bits, val;
|
|
do
|
|
{
|
|
bits = next(32);
|
|
val = bits % n;
|
|
}
|
|
while (bits - val + (n - 1) < 0);
|
|
return val;
|
|
}
|
|
|
|
/**
|
|
* Generates the next pseudorandom long number. All bits of this
|
|
* long are independently chosen and 0 and 1 have equal likelihood.
|
|
* The implementation for java.util.Random is:
|
|
* <pre>
|
|
* public long nextLong() {
|
|
* return ((long)next(32) << 32) + next(32);
|
|
* }
|
|
* </pre>
|
|
* @return the next pseudorandom value.
|
|
*/
|
|
public long nextLong()
|
|
{
|
|
return ((long) next(32) << 32) + next(32);
|
|
}
|
|
|
|
/**
|
|
* Generates the next pseudorandom boolean. True and false have
|
|
* the same probability. The implementation is:
|
|
* <pre>
|
|
* public boolean nextBoolean() {
|
|
* return next(1) != 0;
|
|
* }
|
|
* </pre>
|
|
* @return the next pseudorandom boolean.
|
|
*/
|
|
public boolean nextBoolean()
|
|
{
|
|
return next(1) != 0;
|
|
}
|
|
|
|
/**
|
|
* Generates the next pseudorandom float uniformly distributed
|
|
* between 0.0f (inclusive) and 1.0 (exclusive). The
|
|
* implementation is as follows.
|
|
* <pre>
|
|
* public float nextFloat() {
|
|
* return next(24) / ((float)(1 << 24));
|
|
* }
|
|
* </pre>
|
|
* @return the next pseudorandom float. */
|
|
public float nextFloat()
|
|
{
|
|
return next(24) / ((float) (1 << 24));
|
|
}
|
|
|
|
/**
|
|
* Generates the next pseudorandom double uniformly distributed
|
|
* between 0.0f (inclusive) and 1.0 (exclusive). The
|
|
* implementation is as follows.
|
|
* <pre>
|
|
* public double nextDouble() {
|
|
* return (((long)next(26) << 27) + next(27)) / (double)(1 << 53);
|
|
* }
|
|
* </pre>
|
|
* @return the next pseudorandom double. */
|
|
public double nextDouble()
|
|
{
|
|
return (((long) next(26) << 27) + next(27)) / (double) (1L << 53);
|
|
}
|
|
|
|
/**
|
|
* Generates the next pseudorandom, Gaussian (normally) distributed
|
|
* double value, with mean 0.0 and standard deviation 1.0.
|
|
* The algorithm is as follows.
|
|
* <pre>
|
|
* public synchronized 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);
|
|
* double norm = Math.sqrt(-2 * Math.log(s)/s);
|
|
* nextNextGaussian = v2 * norm;
|
|
* haveNextNextGaussian = true;
|
|
* return v1 * norm;
|
|
* }
|
|
* }
|
|
* </pre>
|
|
* This is described in section 3.4.1 of <em>The Art of Computer
|
|
* Programming, Volume 2</em> by Donald Knuth.
|
|
*
|
|
* @return the next pseudorandom Gaussian distributed double.
|
|
*/
|
|
public synchronized 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);
|
|
double norm = Math.sqrt(-2 * Math.log(s) / s);
|
|
nextNextGaussian = v2 * norm;
|
|
haveNextNextGaussian = true;
|
|
return v1 * norm;
|
|
}
|
|
}
|
|
}
|