/* Random.java -- a pseudo-random number generator
Copyright (C) 1998, 1999, 2000, 2001, 2002 Free Software Foundation, Inc.
-This file is part of GNU Classpath.
+ 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 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.
+ 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., 51 Franklin Street, Fifth Floor, Boston, MA
-02110-1301 USA.
+ 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., 51 Franklin Street, Fifth Floor, Boston, MA
+ 02110-1301 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.
+ 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. */
+ 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. */
/**
*
* @see System#currentTimeMillis()
*/
- public Random()
- {
+ public Random() {
setSeed(System.currentTimeMillis());
}
*
* @param seed the initial seed
*/
- public Random(long seed)
- {
+ public Random(long seed) {
setSeed(seed);
}
* 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>
+
<pre>public synchronized void setSeed(long seed)
+ {
+ this.seed = (seed ^ 0x5DEECE66DL) & ((1L << 48) - 1);
+ haveNextNextGaussian = false;
+ }</pre>
*
* @param seed the new seed
*/
- public synchronized void setSeed(long seed)
- {
+ public synchronized void setSeed(long seed) {
this.seed = (seed ^ 0x5DEECE66DL) & ((1L << 48) - 1);
haveNextNextGaussian = false;
}
* 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>
+
<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, in the range 1..32
* @return the next pseudorandom value
* @since 1.1
*/
- protected synchronized int next(int bits)
- {
+ protected synchronized int next(int bits) {
seed = (seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1);
return (int) (seed >>> (48 - bits));
}
* 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++)
- {
+
<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>
+ }
+ }
+ }</pre>
*
* @param bytes the byte array that should be filled
* @throws NullPointerException if bytes is null
* @since 1.1
*/
- public void nextBytes(byte[] bytes)
- {
+ public void nextBytes(byte[] bytes) {
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++)
{
- 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;
- }
+ bytes[j] = (byte) random;
+ random >>= 8;
}
+ }
}
/**
* 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>
+ *
+
<pre>public int nextInt()
+ {
+ return next(32);
+ }</pre>
*
* @return the next pseudorandom value
*/
- public int nextInt()
- {
+ public int nextInt() {
return next(32);
}
* 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");
+ *
+ 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);
+ 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(31);
- val = bits % n;
- }
- while(bits - val + (n-1) < 0);
+ int bits, val;
+ do
+ {
+ bits = next(31);
+ val = bits % n;
+ }
+ while(bits - val + (n-1) < 0);
- return val;
-}</pre>
- *
+ return val;
+ }</pre>
+ *
* <p>This algorithm would return every value with exactly the same
* probability, if the next()-method would be a perfect random number
* generator.
* @return the next pseudorandom value
* @since 1.2
*/
- public int nextInt(int n)
- {
+ public int nextInt(int n) {
if (n <= 0)
- System.printString("ERROR: n must be positive\n");
+ System.printString("ERROR: n must be positive\n");
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(31);
- val = bits % n;
- }
- while (bits - val + (n - 1) < 0);
+ do {
+ bits = next(31);
+ val = bits % n;
+ } while (bits - val + (n - 1) < 0);
return val;
}
* 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>
+
<pre>public long nextLong()
+ {
+ return ((long) next(32) << 32) + next(32);
+ }</pre>
*
* @return the next pseudorandom value
*/
- public long nextLong()
- {
+ 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>
+ *
+
<pre>public boolean nextBoolean()
+ {
+ return next(1) != 0;
+ }</pre>
*
* @return the next pseudorandom boolean
* @since 1.2
*/
- public boolean nextBoolean()
- {
+ public boolean nextBoolean() {
return next(1) != 0;
}
* Generates the next pseudorandom float uniformly distributed
* between 0.0f (inclusive) and 1.0f (exclusive). The
* implementation is as follows.
- *
-<pre>public float nextFloat()
-{
- return next(24) / ((float)(1 << 24));
-}</pre>
+ *
+
<pre>public float nextFloat()
+ {
+ return next(24) / ((float)(1 << 24));
+ }</pre>
*
* @return the next pseudorandom float
*/
- public float nextFloat()
- {
+ public float nextFloat() {
return next(24) / (float) (1 << 24);
}
* between 0.0 (inclusive) and 1.0 (exclusive). The
* implementation is as follows.
*
-<pre>public double nextDouble()
-{
- return (((long) next(26) << 27) + next(27)) / (double)(1L << 53);
-}</pre>
+
<pre>public double nextDouble()
+ {
+ return (((long) next(26) << 27) + next(27)) / (double)(1L << 53);
+ }</pre>
*
* @return the next pseudorandom double
*/
- public double nextDouble()
- {
+ 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
- {
+ *
+
<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);
+ }
+ while (s >= 1);
- double norm = Math.sqrt(-2 * Math.log(s) / s);
- nextNextGaussian = v2 * norm;
- haveNextNextGaussian = true;
- return v1 * norm;
- }
-}</pre>
+ double norm = Math.sqrt(-2 * Math.log(s) / s);
+ nextNextGaussian = v2 * norm;
+ haveNextNextGaussian = true;
+ return v1 * norm;
+ }
+ }</pre>
*
* <p>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;
- }
+ public synchronized double nextGaussian() {
+ if (haveNextNextGaussian){
+ haveNextNextGaussian = false;
+ return nextNextGaussian;
+ }
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);
+ 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;
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