X-Git-Url: https://oss.titaniummirror.com/gitweb?a=blobdiff_plain;f=libjava%2Fjava%2Futil%2FRandom.java;fp=libjava%2Fjava%2Futil%2FRandom.java;h=0000000000000000000000000000000000000000;hb=6fed43773c9b0ce596dca5686f37ac3fc0fa11c0;hp=1365acde8799495b7e59cea59f0e85d9e2ff12e5;hpb=27b11d56b743098deb193d510b337ba22dc52e5c;p=msp430-gcc.git
diff --git a/libjava/java/util/Random.java b/libjava/java/util/Random.java
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-/* 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 The Art of Computer Programming,
- * Volume 2 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 next() and
- * setSeed(long) 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 SecureRandom
- * in package java.security 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.
- *
- * setSeed(System.currentTimeMillis());
- *
- * @see System#currentTimeMillis()
- */
- public Random()
- {
- setSeed(System.currentTimeMillis());
- }
-
- /**
- * Creates a new pseudorandom number generator, starting with the
- * specified seed. This does:
- *
- * setSeed(seed);
- *
- * @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:
- *
- * public synchronized void setSeed(long seed) {
- * this.seed = (seed ^ 0x5DEECE66DL) & ((1L << 48) - 1);
- * haveNextNextGaussian = false;
- * }
- *
- */
- 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 bits low order bits are
- * independent chosen random bits (0 and 1 are equally likely).
- * The implementation for java.util.Random is:
- *
- * protected synchronized int next(int bits) {
- * seed = (seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1);
- * return (int) (seed >>> (48 - bits));
- * }
- *
- * @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:
- *
- * 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;
- * }
- * }
- * }
- *
- * @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:
- *
- * public int nextInt() {
- * return next(32);
- * }
- *
- *
- * @return the next pseudorandom value. */
- public int nextInt()
- {
- return next(32);
- }
-
- /**
- * Generates the next pseudorandom number. This returns
- * a value between 0(inclusive) and n(exclusive), and
- * each value has the same likelihodd (1/n).
- * (0 and 1 are equally likely). The implementation for
- * java.util.Random is:
- *
- * 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;
- * }
- *
- * 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:
- *
- * public long nextLong() {
- * return ((long)next(32) << 32) + next(32);
- * }
- *
- * @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:
- *
- * public boolean nextBoolean() {
- * return next(1) != 0;
- * }
- *
- * @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.
- *
- * public float nextFloat() {
- * return next(24) / ((float)(1 << 24));
- * }
- *
- * @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.
- *
- * public double nextDouble() {
- * return (((long)next(26) << 27) + next(27)) / (double)(1 << 53);
- * }
- *
- * @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.
- *
- * 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;
- * }
- * }
- *
- * This is described in section 3.4.1 of The Art of Computer
- * Programming, Volume 2 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;
- }
- }
-}