jdk/src/share/classes/java/util/Random.java
changeset 2 90ce3da70b43
child 51 6fe31bc95bbc
--- /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&nbsp;x&nbsp</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));
+    }
+}