--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/jdk/src/share/classes/java/util/Random.java Sat Dec 01 00:00:00 2007 +0000
@@ -0,0 +1,546 @@
+/*
+ * Copyright 1995-2007 Sun Microsystems, Inc. All Rights Reserved.
+ * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
+ *
+ * This code is free software; you can redistribute it and/or modify it
+ * under the terms of the GNU General Public License version 2 only, as
+ * published by the Free Software Foundation. Sun designates this
+ * particular file as subject to the "Classpath" exception as provided
+ * by Sun in the LICENSE file that accompanied this code.
+ *
+ * This code 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
+ * version 2 for more details (a copy is included in the LICENSE file that
+ * accompanied this code).
+ *
+ * You should have received a copy of the GNU General Public License version
+ * 2 along with this work; if not, write to the Free Software Foundation,
+ * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
+ *
+ * Please contact Sun Microsystems, Inc., 4150 Network Circle, Santa Clara,
+ * CA 95054 USA or visit www.sun.com if you need additional information or
+ * have any questions.
+ */
+
+package java.util;
+import java.io.*;
+import java.util.concurrent.atomic.AtomicLong;
+import sun.misc.Unsafe;
+
+/**
+ * An instance of this class is used to generate a stream of
+ * pseudorandom numbers. The class uses a 48-bit seed, which is
+ * modified using a linear congruential formula. (See Donald Knuth,
+ * <i>The Art of Computer Programming, Volume 3</i>, Section 3.2.1.)
+ * <p>
+ * If two instances of {@code Random} are created with the same
+ * seed, and the same sequence of method calls is made for each, they
+ * will generate and return identical sequences of numbers. In order to
+ * guarantee this property, particular algorithms are specified for the
+ * class {@code Random}. Java implementations must use all the algorithms
+ * shown here for the class {@code Random}, for the sake of absolute
+ * portability of Java code. However, subclasses of class {@code Random}
+ * are permitted to use other algorithms, so long as they adhere to the
+ * general contracts for all the methods.
+ * <p>
+ * The algorithms implemented by class {@code Random} use a
+ * {@code protected} utility method that on each invocation can supply
+ * up to 32 pseudorandomly generated bits.
+ * <p>
+ * Many applications will find the method {@link Math#random} simpler to use.
+ *
+ * @author Frank Yellin
+ * @since 1.0
+ */
+public
+class Random implements java.io.Serializable {
+ /** use serialVersionUID from JDK 1.1 for interoperability */
+ static final long serialVersionUID = 3905348978240129619L;
+
+ /**
+ * The internal state associated with this pseudorandom number generator.
+ * (The specs for the methods in this class describe the ongoing
+ * computation of this value.)
+ */
+ private final AtomicLong seed;
+
+ private final static long multiplier = 0x5DEECE66DL;
+ private final static long addend = 0xBL;
+ private final static long mask = (1L << 48) - 1;
+
+ /**
+ * Creates a new random number generator. This constructor sets
+ * the seed of the random number generator to a value very likely
+ * to be distinct from any other invocation of this constructor.
+ */
+ public Random() { this(++seedUniquifier + System.nanoTime()); }
+ private static volatile long seedUniquifier = 8682522807148012L;
+
+ /**
+ * Creates a new random number generator using a single {@code long} seed.
+ * The seed is the initial value of the internal state of the pseudorandom
+ * number generator which is maintained by method {@link #next}.
+ *
+ * <p>The invocation {@code new Random(seed)} is equivalent to:
+ * <pre> {@code
+ * Random rnd = new Random();
+ * rnd.setSeed(seed);}</pre>
+ *
+ * @param seed the initial seed
+ * @see #setSeed(long)
+ */
+ public Random(long seed) {
+ this.seed = new AtomicLong(0L);
+ setSeed(seed);
+ }
+
+ /**
+ * Sets the seed of this random number generator using a single
+ * {@code long} seed. The general contract of {@code setSeed} is
+ * that it alters the state of this random number generator object
+ * so as to be in exactly the same state as if it had just been
+ * created with the argument {@code seed} as a seed. The method
+ * {@code setSeed} is implemented by class {@code Random} by
+ * atomically updating the seed to
+ * <pre>{@code (seed ^ 0x5DEECE66DL) & ((1L << 48) - 1)}</pre>
+ * and clearing the {@code haveNextNextGaussian} flag used by {@link
+ * #nextGaussian}.
+ *
+ * <p>The implementation of {@code setSeed} by class {@code Random}
+ * happens to use only 48 bits of the given seed. In general, however,
+ * an overriding method may use all 64 bits of the {@code long}
+ * argument as a seed value.
+ *
+ * @param seed the initial seed
+ */
+ synchronized public void setSeed(long seed) {
+ seed = (seed ^ multiplier) & mask;
+ this.seed.set(seed);
+ haveNextNextGaussian = false;
+ }
+
+ /**
+ * Generates the next pseudorandom number. Subclasses should
+ * override this, as this is used by all other methods.
+ *
+ * <p>The general contract of {@code next} is that it returns an
+ * {@code int} value and if the argument {@code bits} is between
+ * {@code 1} and {@code 32} (inclusive), then that many low-order
+ * bits of the returned value will be (approximately) independently
+ * chosen bit values, each of which is (approximately) equally
+ * likely to be {@code 0} or {@code 1}. The method {@code next} is
+ * implemented by class {@code Random} by atomically updating the seed to
+ * <pre>{@code (seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1)}</pre>
+ * and returning
+ * <pre>{@code (int)(seed >>> (48 - bits))}.</pre>
+ *
+ * This is a linear congruential pseudorandom number generator, as
+ * defined by D. H. Lehmer and described by Donald E. Knuth in
+ * <i>The Art of Computer Programming,</i> Volume 3:
+ * <i>Seminumerical Algorithms</i>, section 3.2.1.
+ *
+ * @param bits random bits
+ * @return the next pseudorandom value from this random number
+ * generator's sequence
+ * @since 1.1
+ */
+ protected int next(int bits) {
+ long oldseed, nextseed;
+ AtomicLong seed = this.seed;
+ do {
+ oldseed = seed.get();
+ nextseed = (oldseed * multiplier + addend) & mask;
+ } while (!seed.compareAndSet(oldseed, nextseed));
+ return (int)(nextseed >>> (48 - bits));
+ }
+
+ /**
+ * Generates random bytes and places them into a user-supplied
+ * byte array. The number of random bytes produced is equal to
+ * the length of the byte array.
+ *
+ * <p>The method {@code nextBytes} is implemented by class {@code Random}
+ * as if by:
+ * <pre> {@code
+ * public void nextBytes(byte[] bytes) {
+ * for (int i = 0; i < bytes.length; )
+ * for (int rnd = nextInt(), n = Math.min(bytes.length - i, 4);
+ * n-- > 0; rnd >>= 8)
+ * bytes[i++] = (byte)rnd;
+ * }}</pre>
+ *
+ * @param bytes the byte array to fill with random bytes
+ * @throws NullPointerException if the byte array is null
+ * @since 1.1
+ */
+ public void nextBytes(byte[] bytes) {
+ for (int i = 0, len = bytes.length; i < len; )
+ for (int rnd = nextInt(),
+ n = Math.min(len - i, Integer.SIZE/Byte.SIZE);
+ n-- > 0; rnd >>= Byte.SIZE)
+ bytes[i++] = (byte)rnd;
+ }
+
+ /**
+ * Returns the next pseudorandom, uniformly distributed {@code int}
+ * value from this random number generator's sequence. The general
+ * contract of {@code nextInt} is that one {@code int} value is
+ * pseudorandomly generated and returned. All 2<font size="-1"><sup>32
+ * </sup></font> possible {@code int} values are produced with
+ * (approximately) equal probability.
+ *
+ * <p>The method {@code nextInt} is implemented by class {@code Random}
+ * as if by:
+ * <pre> {@code
+ * public int nextInt() {
+ * return next(32);
+ * }}</pre>
+ *
+ * @return the next pseudorandom, uniformly distributed {@code int}
+ * value from this random number generator's sequence
+ */
+ public int nextInt() {
+ return next(32);
+ }
+
+ /**
+ * Returns a pseudorandom, uniformly distributed {@code int} value
+ * between 0 (inclusive) and the specified value (exclusive), drawn from
+ * this random number generator's sequence. The general contract of
+ * {@code nextInt} is that one {@code int} value in the specified range
+ * is pseudorandomly generated and returned. All {@code n} possible
+ * {@code int} values are produced with (approximately) equal
+ * probability. The method {@code nextInt(int n)} is implemented by
+ * class {@code Random} as if by:
+ * <pre> {@code
+ * 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(31);
+ * val = bits % n;
+ * } while (bits - val + (n-1) < 0);
+ * return val;
+ * }}</pre>
+ *
+ * <p>The hedge "approximately" is used in the foregoing description only
+ * because the next method is only approximately an unbiased source of
+ * independently chosen bits. If it were a perfect source of randomly
+ * chosen bits, then the algorithm shown would choose {@code int}
+ * values from the stated range with perfect uniformity.
+ * <p>
+ * The algorithm is slightly tricky. It rejects values that would result
+ * in an uneven distribution (due to the fact that 2^31 is not divisible
+ * by n). The probability of a value being rejected depends on n. The
+ * worst case is n=2^30+1, for which the probability of a reject is 1/2,
+ * and the expected number of iterations before the loop terminates is 2.
+ * <p>
+ * The algorithm treats the case where n is a power of two specially: it
+ * returns the correct number of high-order bits from the underlying
+ * pseudo-random number generator. In the absence of special treatment,
+ * the correct number of <i>low-order</i> bits would be returned. Linear
+ * congruential pseudo-random number generators such as the one
+ * implemented by this class are known to have short periods in the
+ * sequence of values of their low-order bits. Thus, this special case
+ * greatly increases the length of the sequence of values returned by
+ * successive calls to this method if n is a small power of two.
+ *
+ * @param n the bound on the random number to be returned. Must be
+ * positive.
+ * @return the next pseudorandom, uniformly distributed {@code int}
+ * value between {@code 0} (inclusive) and {@code n} (exclusive)
+ * from this random number generator's sequence
+ * @exception IllegalArgumentException if n is not positive
+ * @since 1.2
+ */
+
+ 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(31);
+ val = bits % n;
+ } while (bits - val + (n-1) < 0);
+ return val;
+ }
+
+ /**
+ * Returns the next pseudorandom, uniformly distributed {@code long}
+ * value from this random number generator's sequence. The general
+ * contract of {@code nextLong} is that one {@code long} value is
+ * pseudorandomly generated and returned.
+ *
+ * <p>The method {@code nextLong} is implemented by class {@code Random}
+ * as if by:
+ * <pre> {@code
+ * public long nextLong() {
+ * return ((long)next(32) << 32) + next(32);
+ * }}</pre>
+ *
+ * Because class {@code Random} uses a seed with only 48 bits,
+ * this algorithm will not return all possible {@code long} values.
+ *
+ * @return the next pseudorandom, uniformly distributed {@code long}
+ * value from this random number generator's sequence
+ */
+ public long nextLong() {
+ // it's okay that the bottom word remains signed.
+ return ((long)(next(32)) << 32) + next(32);
+ }
+
+ /**
+ * Returns the next pseudorandom, uniformly distributed
+ * {@code boolean} value from this random number generator's
+ * sequence. The general contract of {@code nextBoolean} is that one
+ * {@code boolean} value is pseudorandomly generated and returned. The
+ * values {@code true} and {@code false} are produced with
+ * (approximately) equal probability.
+ *
+ * <p>The method {@code nextBoolean} is implemented by class {@code Random}
+ * as if by:
+ * <pre> {@code
+ * public boolean nextBoolean() {
+ * return next(1) != 0;
+ * }}</pre>
+ *
+ * @return the next pseudorandom, uniformly distributed
+ * {@code boolean} value from this random number generator's
+ * sequence
+ * @since 1.2
+ */
+ public boolean nextBoolean() {
+ return next(1) != 0;
+ }
+
+ /**
+ * Returns the next pseudorandom, uniformly distributed {@code float}
+ * value between {@code 0.0} and {@code 1.0} from this random
+ * number generator's sequence.
+ *
+ * <p>The general contract of {@code nextFloat} is that one
+ * {@code float} value, chosen (approximately) uniformly from the
+ * range {@code 0.0f} (inclusive) to {@code 1.0f} (exclusive), is
+ * pseudorandomly generated and returned. All 2<font
+ * size="-1"><sup>24</sup></font> possible {@code float} values
+ * of the form <i>m x </i>2<font
+ * size="-1"><sup>-24</sup></font>, where <i>m</i> is a positive
+ * integer less than 2<font size="-1"><sup>24</sup> </font>, are
+ * produced with (approximately) equal probability.
+ *
+ * <p>The method {@code nextFloat} is implemented by class {@code Random}
+ * as if by:
+ * <pre> {@code
+ * public float nextFloat() {
+ * return next(24) / ((float)(1 << 24));
+ * }}</pre>
+ *
+ * <p>The hedge "approximately" is used in the foregoing description only
+ * because the next method is only approximately an unbiased source of
+ * independently chosen bits. If it were a perfect source of randomly
+ * chosen bits, then the algorithm shown would choose {@code float}
+ * values from the stated range with perfect uniformity.<p>
+ * [In early versions of Java, the result was incorrectly calculated as:
+ * <pre> {@code
+ * return next(30) / ((float)(1 << 30));}</pre>
+ * This might seem to be equivalent, if not better, but in fact it
+ * introduced a slight nonuniformity because of the bias in the rounding
+ * of floating-point numbers: it was slightly more likely that the
+ * low-order bit of the significand would be 0 than that it would be 1.]
+ *
+ * @return the next pseudorandom, uniformly distributed {@code float}
+ * value between {@code 0.0} and {@code 1.0} from this
+ * random number generator's sequence
+ */
+ public float nextFloat() {
+ return next(24) / ((float)(1 << 24));
+ }
+
+ /**
+ * Returns the next pseudorandom, uniformly distributed
+ * {@code double} value between {@code 0.0} and
+ * {@code 1.0} from this random number generator's sequence.
+ *
+ * <p>The general contract of {@code nextDouble} is that one
+ * {@code double} value, chosen (approximately) uniformly from the
+ * range {@code 0.0d} (inclusive) to {@code 1.0d} (exclusive), is
+ * pseudorandomly generated and returned.
+ *
+ * <p>The method {@code nextDouble} is implemented by class {@code Random}
+ * as if by:
+ * <pre> {@code
+ * public double nextDouble() {
+ * return (((long)next(26) << 27) + next(27))
+ * / (double)(1L << 53);
+ * }}</pre>
+ *
+ * <p>The hedge "approximately" is used in the foregoing description only
+ * because the {@code next} method is only approximately an unbiased
+ * source of independently chosen bits. If it were a perfect source of
+ * randomly chosen bits, then the algorithm shown would choose
+ * {@code double} values from the stated range with perfect uniformity.
+ * <p>[In early versions of Java, the result was incorrectly calculated as:
+ * <pre> {@code
+ * return (((long)next(27) << 27) + next(27))
+ * / (double)(1L << 54);}</pre>
+ * This might seem to be equivalent, if not better, but in fact it
+ * introduced a large nonuniformity because of the bias in the rounding
+ * of floating-point numbers: it was three times as likely that the
+ * low-order bit of the significand would be 0 than that it would be 1!
+ * This nonuniformity probably doesn't matter much in practice, but we
+ * strive for perfection.]
+ *
+ * @return the next pseudorandom, uniformly distributed {@code double}
+ * value between {@code 0.0} and {@code 1.0} from this
+ * random number generator's sequence
+ * @see Math#random
+ */
+ public double nextDouble() {
+ return (((long)(next(26)) << 27) + next(27))
+ / (double)(1L << 53);
+ }
+
+ private double nextNextGaussian;
+ private boolean haveNextNextGaussian = false;
+
+ /**
+ * Returns the next pseudorandom, Gaussian ("normally") distributed
+ * {@code double} value with mean {@code 0.0} and standard
+ * deviation {@code 1.0} from this random number generator's sequence.
+ * <p>
+ * The general contract of {@code nextGaussian} is that one
+ * {@code double} value, chosen from (approximately) the usual
+ * normal distribution with mean {@code 0.0} and standard deviation
+ * {@code 1.0}, is pseudorandomly generated and returned.
+ *
+ * <p>The method {@code nextGaussian} is implemented by class
+ * {@code Random} as if by a threadsafe version of the following:
+ * <pre> {@code
+ * private double nextNextGaussian;
+ * private boolean haveNextNextGaussian = false;
+ *
+ * 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 = StrictMath.sqrt(-2 * StrictMath.log(s)/s);
+ * nextNextGaussian = v2 * multiplier;
+ * haveNextNextGaussian = true;
+ * return v1 * multiplier;
+ * }
+ * }}</pre>
+ * This uses the <i>polar method</i> of G. E. P. Box, M. E. Muller, and
+ * G. Marsaglia, as described by Donald E. Knuth in <i>The Art of
+ * Computer Programming</i>, Volume 3: <i>Seminumerical Algorithms</i>,
+ * section 3.4.1, subsection C, algorithm P. Note that it generates two
+ * independent values at the cost of only one call to {@code StrictMath.log}
+ * and one call to {@code StrictMath.sqrt}.
+ *
+ * @return the next pseudorandom, Gaussian ("normally") distributed
+ * {@code double} value with mean {@code 0.0} and
+ * standard deviation {@code 1.0} from this random number
+ * generator's sequence
+ */
+ synchronized public double nextGaussian() {
+ // See Knuth, ACP, Section 3.4.1 Algorithm C.
+ if (haveNextNextGaussian) {
+ haveNextNextGaussian = false;
+ return nextNextGaussian;
+ } else {
+ double v1, v2, s;
+ do {
+ v1 = 2 * nextDouble() - 1; // between -1 and 1
+ v2 = 2 * nextDouble() - 1; // between -1 and 1
+ s = v1 * v1 + v2 * v2;
+ } while (s >= 1 || s == 0);
+ double multiplier = StrictMath.sqrt(-2 * StrictMath.log(s)/s);
+ nextNextGaussian = v2 * multiplier;
+ haveNextNextGaussian = true;
+ return v1 * multiplier;
+ }
+ }
+
+ /**
+ * Serializable fields for Random.
+ *
+ * @serialField seed long
+ * seed for random computations
+ * @serialField nextNextGaussian double
+ * next Gaussian to be returned
+ * @serialField haveNextNextGaussian boolean
+ * nextNextGaussian is valid
+ */
+ private static final ObjectStreamField[] serialPersistentFields = {
+ new ObjectStreamField("seed", Long.TYPE),
+ new ObjectStreamField("nextNextGaussian", Double.TYPE),
+ new ObjectStreamField("haveNextNextGaussian", Boolean.TYPE)
+ };
+
+ /**
+ * Reconstitute the {@code Random} instance from a stream (that is,
+ * deserialize it).
+ */
+ private void readObject(java.io.ObjectInputStream s)
+ throws java.io.IOException, ClassNotFoundException {
+
+ ObjectInputStream.GetField fields = s.readFields();
+
+ // The seed is read in as {@code long} for
+ // historical reasons, but it is converted to an AtomicLong.
+ long seedVal = (long) fields.get("seed", -1L);
+ if (seedVal < 0)
+ throw new java.io.StreamCorruptedException(
+ "Random: invalid seed");
+ resetSeed(seedVal);
+ nextNextGaussian = fields.get("nextNextGaussian", 0.0);
+ haveNextNextGaussian = fields.get("haveNextNextGaussian", false);
+ }
+
+ /**
+ * Save the {@code Random} instance to a stream.
+ */
+ synchronized private void writeObject(ObjectOutputStream s)
+ throws IOException {
+
+ // set the values of the Serializable fields
+ ObjectOutputStream.PutField fields = s.putFields();
+
+ // The seed is serialized as a long for historical reasons.
+ fields.put("seed", seed.get());
+ fields.put("nextNextGaussian", nextNextGaussian);
+ fields.put("haveNextNextGaussian", haveNextNextGaussian);
+
+ // save them
+ s.writeFields();
+ }
+
+ // Support for resetting seed while deserializing
+ private static final Unsafe unsafe = Unsafe.getUnsafe();
+ private static final long seedOffset;
+ static {
+ try {
+ seedOffset = unsafe.objectFieldOffset
+ (Random.class.getDeclaredField("seed"));
+ } catch (Exception ex) { throw new Error(ex); }
+ }
+ private void resetSeed(long seedVal) {
+ unsafe.putObjectVolatile(this, seedOffset, new AtomicLong(seedVal));
+ }
+}