jdk/src/share/classes/java/util/Random.java
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/*
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 * Copyright (c) 1995, 2008, Oracle and/or its affiliates. All rights reserved.
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 * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
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 *
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 * This code is free software; you can redistribute it and/or modify it
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 * under the terms of the GNU General Public License version 2 only, as
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 * published by the Free Software Foundation.  Oracle designates this
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 * particular file as subject to the "Classpath" exception as provided
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 * by Oracle in the LICENSE file that accompanied this code.
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 *
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 * This code is distributed in the hope that it will be useful, but WITHOUT
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 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
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 * FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License
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 * version 2 for more details (a copy is included in the LICENSE file that
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 * accompanied this code).
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 *
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 * You should have received a copy of the GNU General Public License version
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 * 2 along with this work; if not, write to the Free Software Foundation,
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 * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
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 *
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 * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
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 * or visit www.oracle.com if you need additional information or have any
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 * questions.
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 */
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package java.util;
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import java.io.*;
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import java.util.concurrent.atomic.AtomicLong;
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import sun.misc.Unsafe;
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/**
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 * An instance of this class is used to generate a stream of
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 * pseudorandom numbers. The class uses a 48-bit seed, which is
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 * modified using a linear congruential formula. (See Donald Knuth,
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 * <i>The Art of Computer Programming, Volume 2</i>, Section 3.2.1.)
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 * <p>
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 * If two instances of {@code Random} are created with the same
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 * seed, and the same sequence of method calls is made for each, they
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 * will generate and return identical sequences of numbers. In order to
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 * guarantee this property, particular algorithms are specified for the
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 * class {@code Random}. Java implementations must use all the algorithms
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 * shown here for the class {@code Random}, for the sake of absolute
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 * portability of Java code. However, subclasses of class {@code Random}
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 * are permitted to use other algorithms, so long as they adhere to the
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 * general contracts for all the methods.
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 * <p>
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 * The algorithms implemented by class {@code Random} use a
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 * {@code protected} utility method that on each invocation can supply
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 * up to 32 pseudorandomly generated bits.
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 * <p>
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 * Many applications will find the method {@link Math#random} simpler to use.
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 *
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 * <p>Instances of {@code java.util.Random} are threadsafe.
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 * However, the concurrent use of the same {@code java.util.Random}
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 * instance across threads may encounter contention and consequent
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 * poor performance. Consider instead using
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 * {@link java.util.concurrent.ThreadLocalRandom} in multithreaded
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 * designs.
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 *
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 * <p>Instances of {@code java.util.Random} are not cryptographically
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 * secure.  Consider instead using {@link java.security.SecureRandom} to
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 * get a cryptographically secure pseudo-random number generator for use
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 * by security-sensitive applications.
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 *
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 * @author  Frank Yellin
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 * @since   1.0
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 */
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public
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class Random implements java.io.Serializable {
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    /** use serialVersionUID from JDK 1.1 for interoperability */
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    static final long serialVersionUID = 3905348978240129619L;
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    /**
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     * The internal state associated with this pseudorandom number generator.
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     * (The specs for the methods in this class describe the ongoing
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     * computation of this value.)
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     */
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    private final AtomicLong seed;
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    private static final long multiplier = 0x5DEECE66DL;
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    private static final long addend = 0xBL;
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    private static final long mask = (1L << 48) - 1;
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    /**
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     * Creates a new random number generator. This constructor sets
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     * the seed of the random number generator to a value very likely
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     * to be distinct from any other invocation of this constructor.
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     */
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    public Random() {
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        this(seedUniquifier() ^ System.nanoTime());
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    }
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    private static long seedUniquifier() {
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        // L'Ecuyer, "Tables of Linear Congruential Generators of
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        // Different Sizes and Good Lattice Structure", 1999
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        for (;;) {
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            long current = seedUniquifier.get();
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            long next = current * 181783497276652981L;
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            if (seedUniquifier.compareAndSet(current, next))
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                return next;
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        }
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    }
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    private static final AtomicLong seedUniquifier
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        = new AtomicLong(8682522807148012L);
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    /**
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     * Creates a new random number generator using a single {@code long} seed.
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     * The seed is the initial value of the internal state of the pseudorandom
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     * number generator which is maintained by method {@link #next}.
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     *
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     * <p>The invocation {@code new Random(seed)} is equivalent to:
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     *  <pre> {@code
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     * Random rnd = new Random();
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     * rnd.setSeed(seed);}</pre>
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     *
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     * @param seed the initial seed
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     * @see   #setSeed(long)
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     */
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    public Random(long seed) {
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        this.seed = new AtomicLong(initialScramble(seed));
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    }
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    private static long initialScramble(long seed) {
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        return (seed ^ multiplier) & mask;
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    }
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    /**
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     * Sets the seed of this random number generator using a single
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     * {@code long} seed. The general contract of {@code setSeed} is
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     * that it alters the state of this random number generator object
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     * so as to be in exactly the same state as if it had just been
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     * created with the argument {@code seed} as a seed. The method
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     * {@code setSeed} is implemented by class {@code Random} by
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     * atomically updating the seed to
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     *  <pre>{@code (seed ^ 0x5DEECE66DL) & ((1L << 48) - 1)}</pre>
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     * and clearing the {@code haveNextNextGaussian} flag used by {@link
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     * #nextGaussian}.
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     *
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     * <p>The implementation of {@code setSeed} by class {@code Random}
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     * happens to use only 48 bits of the given seed. In general, however,
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     * an overriding method may use all 64 bits of the {@code long}
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     * argument as a seed value.
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     *
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     * @param seed the initial seed
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     */
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    synchronized public void setSeed(long seed) {
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        this.seed.set(initialScramble(seed));
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        haveNextNextGaussian = false;
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    }
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    /**
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     * Generates the next pseudorandom number. Subclasses should
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     * override this, as this is used by all other methods.
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     *
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     * <p>The general contract of {@code next} is that it returns an
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     * {@code int} value and if the argument {@code bits} is between
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     * {@code 1} and {@code 32} (inclusive), then that many low-order
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     * bits of the returned value will be (approximately) independently
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     * chosen bit values, each of which is (approximately) equally
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     * likely to be {@code 0} or {@code 1}. The method {@code next} is
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     * implemented by class {@code Random} by atomically updating the seed to
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     *  <pre>{@code (seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1)}</pre>
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     * and returning
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     *  <pre>{@code (int)(seed >>> (48 - bits))}.</pre>
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     *
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     * This is a linear congruential pseudorandom number generator, as
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     * defined by D. H. Lehmer and described by Donald E. Knuth in
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     * <i>The Art of Computer Programming,</i> Volume 3:
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     * <i>Seminumerical Algorithms</i>, section 3.2.1.
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     *
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     * @param  bits random bits
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     * @return the next pseudorandom value from this random number
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     *         generator's sequence
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     * @since  1.1
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     */
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    protected int next(int bits) {
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        long oldseed, nextseed;
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        AtomicLong seed = this.seed;
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        do {
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            oldseed = seed.get();
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            nextseed = (oldseed * multiplier + addend) & mask;
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        } while (!seed.compareAndSet(oldseed, nextseed));
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        return (int)(nextseed >>> (48 - bits));
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    }
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    /**
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     * Generates random bytes and places them into a user-supplied
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     * byte array.  The number of random bytes produced is equal to
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     * the length of the byte array.
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     *
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     * <p>The method {@code nextBytes} is implemented by class {@code Random}
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     * as if by:
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     *  <pre> {@code
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     * public void nextBytes(byte[] bytes) {
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     *   for (int i = 0; i < bytes.length; )
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     *     for (int rnd = nextInt(), n = Math.min(bytes.length - i, 4);
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     *          n-- > 0; rnd >>= 8)
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     *       bytes[i++] = (byte)rnd;
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     * }}</pre>
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     *
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     * @param  bytes the byte array to fill with random bytes
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     * @throws NullPointerException if the byte array is null
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     * @since  1.1
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     */
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    public void nextBytes(byte[] bytes) {
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        for (int i = 0, len = bytes.length; i < len; )
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            for (int rnd = nextInt(),
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                     n = Math.min(len - i, Integer.SIZE/Byte.SIZE);
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                 n-- > 0; rnd >>= Byte.SIZE)
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                bytes[i++] = (byte)rnd;
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    }
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    /**
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     * Returns the next pseudorandom, uniformly distributed {@code int}
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     * value from this random number generator's sequence. The general
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     * contract of {@code nextInt} is that one {@code int} value is
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     * pseudorandomly generated and returned. All 2<font size="-1"><sup>32
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     * </sup></font> possible {@code int} values are produced with
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     * (approximately) equal probability.
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     *
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     * <p>The method {@code nextInt} is implemented by class {@code Random}
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     * as if by:
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     *  <pre> {@code
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     * public int nextInt() {
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     *   return next(32);
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     * }}</pre>
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     *
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     * @return the next pseudorandom, uniformly distributed {@code int}
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     *         value from this random number generator's sequence
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     */
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    public int nextInt() {
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        return next(32);
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    }
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    /**
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     * Returns a pseudorandom, uniformly distributed {@code int} value
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     * between 0 (inclusive) and the specified value (exclusive), drawn from
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     * this random number generator's sequence.  The general contract of
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     * {@code nextInt} is that one {@code int} value in the specified range
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     * is pseudorandomly generated and returned.  All {@code n} possible
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     * {@code int} values are produced with (approximately) equal
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     * probability.  The method {@code nextInt(int n)} is implemented by
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     * class {@code Random} as if by:
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     *  <pre> {@code
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     * public int nextInt(int n) {
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     *   if (n <= 0)
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     *     throw new IllegalArgumentException("n must be positive");
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     *
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     *   if ((n & -n) == n)  // i.e., n is a power of 2
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     *     return (int)((n * (long)next(31)) >> 31);
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     *
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     *   int bits, val;
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     *   do {
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     *       bits = next(31);
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     *       val = bits % n;
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     *   } while (bits - val + (n-1) < 0);
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     *   return val;
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     * }}</pre>
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     *
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     * <p>The hedge "approximately" is used in the foregoing description only
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     * because the next method is only approximately an unbiased source of
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     * independently chosen bits.  If it were a perfect source of randomly
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     * chosen bits, then the algorithm shown would choose {@code int}
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     * values from the stated range with perfect uniformity.
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     * <p>
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     * The algorithm is slightly tricky.  It rejects values that would result
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     * in an uneven distribution (due to the fact that 2^31 is not divisible
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     * by n). The probability of a value being rejected depends on n.  The
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     * worst case is n=2^30+1, for which the probability of a reject is 1/2,
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     * and the expected number of iterations before the loop terminates is 2.
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     * <p>
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     * The algorithm treats the case where n is a power of two specially: it
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     * returns the correct number of high-order bits from the underlying
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     * pseudo-random number generator.  In the absence of special treatment,
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     * the correct number of <i>low-order</i> bits would be returned.  Linear
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     * congruential pseudo-random number generators such as the one
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     * implemented by this class are known to have short periods in the
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     * sequence of values of their low-order bits.  Thus, this special case
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     * greatly increases the length of the sequence of values returned by
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     * successive calls to this method if n is a small power of two.
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     *
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     * @param n the bound on the random number to be returned.  Must be
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     *        positive.
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     * @return the next pseudorandom, uniformly distributed {@code int}
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     *         value between {@code 0} (inclusive) and {@code n} (exclusive)
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     *         from this random number generator's sequence
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     * @throws IllegalArgumentException if n is not positive
2
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     * @since 1.2
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     */
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    public int nextInt(int n) {
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        if (n <= 0)
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            throw new IllegalArgumentException("n must be positive");
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        if ((n & -n) == n)  // i.e., n is a power of 2
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            return (int)((n * (long)next(31)) >> 31);
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        int bits, val;
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        do {
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            bits = next(31);
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            val = bits % n;
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        } while (bits - val + (n-1) < 0);
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        return val;
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    }
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    /**
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     * Returns the next pseudorandom, uniformly distributed {@code long}
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     * value from this random number generator's sequence. The general
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     * contract of {@code nextLong} is that one {@code long} value is
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     * pseudorandomly generated and returned.
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     *
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     * <p>The method {@code nextLong} is implemented by class {@code Random}
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     * as if by:
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     *  <pre> {@code
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     * public long nextLong() {
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     *   return ((long)next(32) << 32) + next(32);
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     * }}</pre>
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     *
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     * Because class {@code Random} uses a seed with only 48 bits,
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     * this algorithm will not return all possible {@code long} values.
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     *
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     * @return the next pseudorandom, uniformly distributed {@code long}
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     *         value from this random number generator's sequence
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     */
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    public long nextLong() {
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        // it's okay that the bottom word remains signed.
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        return ((long)(next(32)) << 32) + next(32);
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    }
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    /**
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     * Returns the next pseudorandom, uniformly distributed
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     * {@code boolean} value from this random number generator's
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     * sequence. The general contract of {@code nextBoolean} is that one
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     * {@code boolean} value is pseudorandomly generated and returned.  The
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     * values {@code true} and {@code false} are produced with
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     * (approximately) equal probability.
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     *
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     * <p>The method {@code nextBoolean} is implemented by class {@code Random}
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     * as if by:
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     *  <pre> {@code
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     * public boolean nextBoolean() {
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     *   return next(1) != 0;
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     * }}</pre>
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     *
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     * @return the next pseudorandom, uniformly distributed
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     *         {@code boolean} value from this random number generator's
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     *         sequence
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     * @since 1.2
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     */
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    public boolean nextBoolean() {
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        return next(1) != 0;
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    }
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    /**
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     * Returns the next pseudorandom, uniformly distributed {@code float}
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     * value between {@code 0.0} and {@code 1.0} from this random
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     * number generator's sequence.
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     *
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     * <p>The general contract of {@code nextFloat} is that one
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     * {@code float} value, chosen (approximately) uniformly from the
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     * range {@code 0.0f} (inclusive) to {@code 1.0f} (exclusive), is
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     * pseudorandomly generated and returned. All 2<font
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     * size="-1"><sup>24</sup></font> possible {@code float} values
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     * of the form <i>m&nbsp;x&nbsp</i>2<font
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     * size="-1"><sup>-24</sup></font>, where <i>m</i> is a positive
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     * integer less than 2<font size="-1"><sup>24</sup> </font>, are
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     * produced with (approximately) equal probability.
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     *
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     * <p>The method {@code nextFloat} is implemented by class {@code Random}
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     * as if by:
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     *  <pre> {@code
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     * public float nextFloat() {
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     *   return next(24) / ((float)(1 << 24));
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     * }}</pre>
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     *
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     * <p>The hedge "approximately" is used in the foregoing description only
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     * because the next method is only approximately an unbiased source of
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     * independently chosen bits. If it were a perfect source of randomly
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     * chosen bits, then the algorithm shown would choose {@code float}
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     * values from the stated range with perfect uniformity.<p>
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     * [In early versions of Java, the result was incorrectly calculated as:
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     *  <pre> {@code
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     *   return next(30) / ((float)(1 << 30));}</pre>
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   385
     * This might seem to be equivalent, if not better, but in fact it
90ce3da70b43 Initial load
duke
parents:
diff changeset
   386
     * introduced a slight nonuniformity because of the bias in the rounding
90ce3da70b43 Initial load
duke
parents:
diff changeset
   387
     * of floating-point numbers: it was slightly more likely that the
90ce3da70b43 Initial load
duke
parents:
diff changeset
   388
     * low-order bit of the significand would be 0 than that it would be 1.]
90ce3da70b43 Initial load
duke
parents:
diff changeset
   389
     *
90ce3da70b43 Initial load
duke
parents:
diff changeset
   390
     * @return the next pseudorandom, uniformly distributed {@code float}
90ce3da70b43 Initial load
duke
parents:
diff changeset
   391
     *         value between {@code 0.0} and {@code 1.0} from this
90ce3da70b43 Initial load
duke
parents:
diff changeset
   392
     *         random number generator's sequence
90ce3da70b43 Initial load
duke
parents:
diff changeset
   393
     */
90ce3da70b43 Initial load
duke
parents:
diff changeset
   394
    public float nextFloat() {
90ce3da70b43 Initial load
duke
parents:
diff changeset
   395
        return next(24) / ((float)(1 << 24));
90ce3da70b43 Initial load
duke
parents:
diff changeset
   396
    }
90ce3da70b43 Initial load
duke
parents:
diff changeset
   397
90ce3da70b43 Initial load
duke
parents:
diff changeset
   398
    /**
90ce3da70b43 Initial load
duke
parents:
diff changeset
   399
     * Returns the next pseudorandom, uniformly distributed
90ce3da70b43 Initial load
duke
parents:
diff changeset
   400
     * {@code double} value between {@code 0.0} and
90ce3da70b43 Initial load
duke
parents:
diff changeset
   401
     * {@code 1.0} from this random number generator's sequence.
90ce3da70b43 Initial load
duke
parents:
diff changeset
   402
     *
90ce3da70b43 Initial load
duke
parents:
diff changeset
   403
     * <p>The general contract of {@code nextDouble} is that one
90ce3da70b43 Initial load
duke
parents:
diff changeset
   404
     * {@code double} value, chosen (approximately) uniformly from the
90ce3da70b43 Initial load
duke
parents:
diff changeset
   405
     * range {@code 0.0d} (inclusive) to {@code 1.0d} (exclusive), is
90ce3da70b43 Initial load
duke
parents:
diff changeset
   406
     * pseudorandomly generated and returned.
90ce3da70b43 Initial load
duke
parents:
diff changeset
   407
     *
90ce3da70b43 Initial load
duke
parents:
diff changeset
   408
     * <p>The method {@code nextDouble} is implemented by class {@code Random}
90ce3da70b43 Initial load
duke
parents:
diff changeset
   409
     * as if by:
90ce3da70b43 Initial load
duke
parents:
diff changeset
   410
     *  <pre> {@code
90ce3da70b43 Initial load
duke
parents:
diff changeset
   411
     * public double nextDouble() {
90ce3da70b43 Initial load
duke
parents:
diff changeset
   412
     *   return (((long)next(26) << 27) + next(27))
90ce3da70b43 Initial load
duke
parents:
diff changeset
   413
     *     / (double)(1L << 53);
90ce3da70b43 Initial load
duke
parents:
diff changeset
   414
     * }}</pre>
90ce3da70b43 Initial load
duke
parents:
diff changeset
   415
     *
90ce3da70b43 Initial load
duke
parents:
diff changeset
   416
     * <p>The hedge "approximately" is used in the foregoing description only
90ce3da70b43 Initial load
duke
parents:
diff changeset
   417
     * because the {@code next} method is only approximately an unbiased
90ce3da70b43 Initial load
duke
parents:
diff changeset
   418
     * source of independently chosen bits. If it were a perfect source of
90ce3da70b43 Initial load
duke
parents:
diff changeset
   419
     * randomly chosen bits, then the algorithm shown would choose
90ce3da70b43 Initial load
duke
parents:
diff changeset
   420
     * {@code double} values from the stated range with perfect uniformity.
90ce3da70b43 Initial load
duke
parents:
diff changeset
   421
     * <p>[In early versions of Java, the result was incorrectly calculated as:
90ce3da70b43 Initial load
duke
parents:
diff changeset
   422
     *  <pre> {@code
90ce3da70b43 Initial load
duke
parents:
diff changeset
   423
     *   return (((long)next(27) << 27) + next(27))
90ce3da70b43 Initial load
duke
parents:
diff changeset
   424
     *     / (double)(1L << 54);}</pre>
90ce3da70b43 Initial load
duke
parents:
diff changeset
   425
     * This might seem to be equivalent, if not better, but in fact it
90ce3da70b43 Initial load
duke
parents:
diff changeset
   426
     * introduced a large nonuniformity because of the bias in the rounding
90ce3da70b43 Initial load
duke
parents:
diff changeset
   427
     * of floating-point numbers: it was three times as likely that the
90ce3da70b43 Initial load
duke
parents:
diff changeset
   428
     * low-order bit of the significand would be 0 than that it would be 1!
90ce3da70b43 Initial load
duke
parents:
diff changeset
   429
     * This nonuniformity probably doesn't matter much in practice, but we
90ce3da70b43 Initial load
duke
parents:
diff changeset
   430
     * strive for perfection.]
90ce3da70b43 Initial load
duke
parents:
diff changeset
   431
     *
90ce3da70b43 Initial load
duke
parents:
diff changeset
   432
     * @return the next pseudorandom, uniformly distributed {@code double}
90ce3da70b43 Initial load
duke
parents:
diff changeset
   433
     *         value between {@code 0.0} and {@code 1.0} from this
90ce3da70b43 Initial load
duke
parents:
diff changeset
   434
     *         random number generator's sequence
90ce3da70b43 Initial load
duke
parents:
diff changeset
   435
     * @see Math#random
90ce3da70b43 Initial load
duke
parents:
diff changeset
   436
     */
90ce3da70b43 Initial load
duke
parents:
diff changeset
   437
    public double nextDouble() {
90ce3da70b43 Initial load
duke
parents:
diff changeset
   438
        return (((long)(next(26)) << 27) + next(27))
90ce3da70b43 Initial load
duke
parents:
diff changeset
   439
            / (double)(1L << 53);
90ce3da70b43 Initial load
duke
parents:
diff changeset
   440
    }
90ce3da70b43 Initial load
duke
parents:
diff changeset
   441
90ce3da70b43 Initial load
duke
parents:
diff changeset
   442
    private double nextNextGaussian;
90ce3da70b43 Initial load
duke
parents:
diff changeset
   443
    private boolean haveNextNextGaussian = false;
90ce3da70b43 Initial load
duke
parents:
diff changeset
   444
90ce3da70b43 Initial load
duke
parents:
diff changeset
   445
    /**
90ce3da70b43 Initial load
duke
parents:
diff changeset
   446
     * Returns the next pseudorandom, Gaussian ("normally") distributed
90ce3da70b43 Initial load
duke
parents:
diff changeset
   447
     * {@code double} value with mean {@code 0.0} and standard
90ce3da70b43 Initial load
duke
parents:
diff changeset
   448
     * deviation {@code 1.0} from this random number generator's sequence.
90ce3da70b43 Initial load
duke
parents:
diff changeset
   449
     * <p>
90ce3da70b43 Initial load
duke
parents:
diff changeset
   450
     * The general contract of {@code nextGaussian} is that one
90ce3da70b43 Initial load
duke
parents:
diff changeset
   451
     * {@code double} value, chosen from (approximately) the usual
90ce3da70b43 Initial load
duke
parents:
diff changeset
   452
     * normal distribution with mean {@code 0.0} and standard deviation
90ce3da70b43 Initial load
duke
parents:
diff changeset
   453
     * {@code 1.0}, is pseudorandomly generated and returned.
90ce3da70b43 Initial load
duke
parents:
diff changeset
   454
     *
90ce3da70b43 Initial load
duke
parents:
diff changeset
   455
     * <p>The method {@code nextGaussian} is implemented by class
90ce3da70b43 Initial load
duke
parents:
diff changeset
   456
     * {@code Random} as if by a threadsafe version of the following:
90ce3da70b43 Initial load
duke
parents:
diff changeset
   457
     *  <pre> {@code
90ce3da70b43 Initial load
duke
parents:
diff changeset
   458
     * private double nextNextGaussian;
90ce3da70b43 Initial load
duke
parents:
diff changeset
   459
     * private boolean haveNextNextGaussian = false;
90ce3da70b43 Initial load
duke
parents:
diff changeset
   460
     *
90ce3da70b43 Initial load
duke
parents:
diff changeset
   461
     * public double nextGaussian() {
90ce3da70b43 Initial load
duke
parents:
diff changeset
   462
     *   if (haveNextNextGaussian) {
90ce3da70b43 Initial load
duke
parents:
diff changeset
   463
     *     haveNextNextGaussian = false;
90ce3da70b43 Initial load
duke
parents:
diff changeset
   464
     *     return nextNextGaussian;
90ce3da70b43 Initial load
duke
parents:
diff changeset
   465
     *   } else {
90ce3da70b43 Initial load
duke
parents:
diff changeset
   466
     *     double v1, v2, s;
90ce3da70b43 Initial load
duke
parents:
diff changeset
   467
     *     do {
90ce3da70b43 Initial load
duke
parents:
diff changeset
   468
     *       v1 = 2 * nextDouble() - 1;   // between -1.0 and 1.0
90ce3da70b43 Initial load
duke
parents:
diff changeset
   469
     *       v2 = 2 * nextDouble() - 1;   // between -1.0 and 1.0
90ce3da70b43 Initial load
duke
parents:
diff changeset
   470
     *       s = v1 * v1 + v2 * v2;
90ce3da70b43 Initial load
duke
parents:
diff changeset
   471
     *     } while (s >= 1 || s == 0);
90ce3da70b43 Initial load
duke
parents:
diff changeset
   472
     *     double multiplier = StrictMath.sqrt(-2 * StrictMath.log(s)/s);
90ce3da70b43 Initial load
duke
parents:
diff changeset
   473
     *     nextNextGaussian = v2 * multiplier;
90ce3da70b43 Initial load
duke
parents:
diff changeset
   474
     *     haveNextNextGaussian = true;
90ce3da70b43 Initial load
duke
parents:
diff changeset
   475
     *     return v1 * multiplier;
90ce3da70b43 Initial load
duke
parents:
diff changeset
   476
     *   }
90ce3da70b43 Initial load
duke
parents:
diff changeset
   477
     * }}</pre>
90ce3da70b43 Initial load
duke
parents:
diff changeset
   478
     * This uses the <i>polar method</i> of G. E. P. Box, M. E. Muller, and
90ce3da70b43 Initial load
duke
parents:
diff changeset
   479
     * G. Marsaglia, as described by Donald E. Knuth in <i>The Art of
90ce3da70b43 Initial load
duke
parents:
diff changeset
   480
     * Computer Programming</i>, Volume 3: <i>Seminumerical Algorithms</i>,
90ce3da70b43 Initial load
duke
parents:
diff changeset
   481
     * section 3.4.1, subsection C, algorithm P. Note that it generates two
90ce3da70b43 Initial load
duke
parents:
diff changeset
   482
     * independent values at the cost of only one call to {@code StrictMath.log}
90ce3da70b43 Initial load
duke
parents:
diff changeset
   483
     * and one call to {@code StrictMath.sqrt}.
90ce3da70b43 Initial load
duke
parents:
diff changeset
   484
     *
90ce3da70b43 Initial load
duke
parents:
diff changeset
   485
     * @return the next pseudorandom, Gaussian ("normally") distributed
90ce3da70b43 Initial load
duke
parents:
diff changeset
   486
     *         {@code double} value with mean {@code 0.0} and
90ce3da70b43 Initial load
duke
parents:
diff changeset
   487
     *         standard deviation {@code 1.0} from this random number
90ce3da70b43 Initial load
duke
parents:
diff changeset
   488
     *         generator's sequence
90ce3da70b43 Initial load
duke
parents:
diff changeset
   489
     */
90ce3da70b43 Initial load
duke
parents:
diff changeset
   490
    synchronized public double nextGaussian() {
90ce3da70b43 Initial load
duke
parents:
diff changeset
   491
        // See Knuth, ACP, Section 3.4.1 Algorithm C.
90ce3da70b43 Initial load
duke
parents:
diff changeset
   492
        if (haveNextNextGaussian) {
90ce3da70b43 Initial load
duke
parents:
diff changeset
   493
            haveNextNextGaussian = false;
90ce3da70b43 Initial load
duke
parents:
diff changeset
   494
            return nextNextGaussian;
90ce3da70b43 Initial load
duke
parents:
diff changeset
   495
        } else {
90ce3da70b43 Initial load
duke
parents:
diff changeset
   496
            double v1, v2, s;
90ce3da70b43 Initial load
duke
parents:
diff changeset
   497
            do {
90ce3da70b43 Initial load
duke
parents:
diff changeset
   498
                v1 = 2 * nextDouble() - 1; // between -1 and 1
90ce3da70b43 Initial load
duke
parents:
diff changeset
   499
                v2 = 2 * nextDouble() - 1; // between -1 and 1
90ce3da70b43 Initial load
duke
parents:
diff changeset
   500
                s = v1 * v1 + v2 * v2;
90ce3da70b43 Initial load
duke
parents:
diff changeset
   501
            } while (s >= 1 || s == 0);
90ce3da70b43 Initial load
duke
parents:
diff changeset
   502
            double multiplier = StrictMath.sqrt(-2 * StrictMath.log(s)/s);
90ce3da70b43 Initial load
duke
parents:
diff changeset
   503
            nextNextGaussian = v2 * multiplier;
90ce3da70b43 Initial load
duke
parents:
diff changeset
   504
            haveNextNextGaussian = true;
90ce3da70b43 Initial load
duke
parents:
diff changeset
   505
            return v1 * multiplier;
90ce3da70b43 Initial load
duke
parents:
diff changeset
   506
        }
90ce3da70b43 Initial load
duke
parents:
diff changeset
   507
    }
90ce3da70b43 Initial load
duke
parents:
diff changeset
   508
90ce3da70b43 Initial load
duke
parents:
diff changeset
   509
    /**
90ce3da70b43 Initial load
duke
parents:
diff changeset
   510
     * Serializable fields for Random.
90ce3da70b43 Initial load
duke
parents:
diff changeset
   511
     *
90ce3da70b43 Initial load
duke
parents:
diff changeset
   512
     * @serialField    seed long
90ce3da70b43 Initial load
duke
parents:
diff changeset
   513
     *              seed for random computations
90ce3da70b43 Initial load
duke
parents:
diff changeset
   514
     * @serialField    nextNextGaussian double
90ce3da70b43 Initial load
duke
parents:
diff changeset
   515
     *              next Gaussian to be returned
90ce3da70b43 Initial load
duke
parents:
diff changeset
   516
     * @serialField      haveNextNextGaussian boolean
90ce3da70b43 Initial load
duke
parents:
diff changeset
   517
     *              nextNextGaussian is valid
90ce3da70b43 Initial load
duke
parents:
diff changeset
   518
     */
90ce3da70b43 Initial load
duke
parents:
diff changeset
   519
    private static final ObjectStreamField[] serialPersistentFields = {
90ce3da70b43 Initial load
duke
parents:
diff changeset
   520
        new ObjectStreamField("seed", Long.TYPE),
90ce3da70b43 Initial load
duke
parents:
diff changeset
   521
        new ObjectStreamField("nextNextGaussian", Double.TYPE),
90ce3da70b43 Initial load
duke
parents:
diff changeset
   522
        new ObjectStreamField("haveNextNextGaussian", Boolean.TYPE)
90ce3da70b43 Initial load
duke
parents:
diff changeset
   523
    };
90ce3da70b43 Initial load
duke
parents:
diff changeset
   524
90ce3da70b43 Initial load
duke
parents:
diff changeset
   525
    /**
90ce3da70b43 Initial load
duke
parents:
diff changeset
   526
     * Reconstitute the {@code Random} instance from a stream (that is,
90ce3da70b43 Initial load
duke
parents:
diff changeset
   527
     * deserialize it).
90ce3da70b43 Initial load
duke
parents:
diff changeset
   528
     */
90ce3da70b43 Initial load
duke
parents:
diff changeset
   529
    private void readObject(java.io.ObjectInputStream s)
90ce3da70b43 Initial load
duke
parents:
diff changeset
   530
        throws java.io.IOException, ClassNotFoundException {
90ce3da70b43 Initial load
duke
parents:
diff changeset
   531
90ce3da70b43 Initial load
duke
parents:
diff changeset
   532
        ObjectInputStream.GetField fields = s.readFields();
90ce3da70b43 Initial load
duke
parents:
diff changeset
   533
90ce3da70b43 Initial load
duke
parents:
diff changeset
   534
        // The seed is read in as {@code long} for
90ce3da70b43 Initial load
duke
parents:
diff changeset
   535
        // historical reasons, but it is converted to an AtomicLong.
51
6fe31bc95bbc 6600143: Remove another 450 unnecessary casts
martin
parents: 2
diff changeset
   536
        long seedVal = fields.get("seed", -1L);
2
90ce3da70b43 Initial load
duke
parents:
diff changeset
   537
        if (seedVal < 0)
90ce3da70b43 Initial load
duke
parents:
diff changeset
   538
          throw new java.io.StreamCorruptedException(
90ce3da70b43 Initial load
duke
parents:
diff changeset
   539
                              "Random: invalid seed");
90ce3da70b43 Initial load
duke
parents:
diff changeset
   540
        resetSeed(seedVal);
90ce3da70b43 Initial load
duke
parents:
diff changeset
   541
        nextNextGaussian = fields.get("nextNextGaussian", 0.0);
90ce3da70b43 Initial load
duke
parents:
diff changeset
   542
        haveNextNextGaussian = fields.get("haveNextNextGaussian", false);
90ce3da70b43 Initial load
duke
parents:
diff changeset
   543
    }
90ce3da70b43 Initial load
duke
parents:
diff changeset
   544
90ce3da70b43 Initial load
duke
parents:
diff changeset
   545
    /**
90ce3da70b43 Initial load
duke
parents:
diff changeset
   546
     * Save the {@code Random} instance to a stream.
90ce3da70b43 Initial load
duke
parents:
diff changeset
   547
     */
90ce3da70b43 Initial load
duke
parents:
diff changeset
   548
    synchronized private void writeObject(ObjectOutputStream s)
90ce3da70b43 Initial load
duke
parents:
diff changeset
   549
        throws IOException {
90ce3da70b43 Initial load
duke
parents:
diff changeset
   550
90ce3da70b43 Initial load
duke
parents:
diff changeset
   551
        // set the values of the Serializable fields
90ce3da70b43 Initial load
duke
parents:
diff changeset
   552
        ObjectOutputStream.PutField fields = s.putFields();
90ce3da70b43 Initial load
duke
parents:
diff changeset
   553
90ce3da70b43 Initial load
duke
parents:
diff changeset
   554
        // The seed is serialized as a long for historical reasons.
90ce3da70b43 Initial load
duke
parents:
diff changeset
   555
        fields.put("seed", seed.get());
90ce3da70b43 Initial load
duke
parents:
diff changeset
   556
        fields.put("nextNextGaussian", nextNextGaussian);
90ce3da70b43 Initial load
duke
parents:
diff changeset
   557
        fields.put("haveNextNextGaussian", haveNextNextGaussian);
90ce3da70b43 Initial load
duke
parents:
diff changeset
   558
90ce3da70b43 Initial load
duke
parents:
diff changeset
   559
        // save them
90ce3da70b43 Initial load
duke
parents:
diff changeset
   560
        s.writeFields();
90ce3da70b43 Initial load
duke
parents:
diff changeset
   561
    }
90ce3da70b43 Initial load
duke
parents:
diff changeset
   562
90ce3da70b43 Initial load
duke
parents:
diff changeset
   563
    // Support for resetting seed while deserializing
90ce3da70b43 Initial load
duke
parents:
diff changeset
   564
    private static final Unsafe unsafe = Unsafe.getUnsafe();
90ce3da70b43 Initial load
duke
parents:
diff changeset
   565
    private static final long seedOffset;
90ce3da70b43 Initial load
duke
parents:
diff changeset
   566
    static {
90ce3da70b43 Initial load
duke
parents:
diff changeset
   567
        try {
90ce3da70b43 Initial load
duke
parents:
diff changeset
   568
            seedOffset = unsafe.objectFieldOffset
90ce3da70b43 Initial load
duke
parents:
diff changeset
   569
                (Random.class.getDeclaredField("seed"));
90ce3da70b43 Initial load
duke
parents:
diff changeset
   570
        } catch (Exception ex) { throw new Error(ex); }
90ce3da70b43 Initial load
duke
parents:
diff changeset
   571
    }
90ce3da70b43 Initial load
duke
parents:
diff changeset
   572
    private void resetSeed(long seedVal) {
90ce3da70b43 Initial load
duke
parents:
diff changeset
   573
        unsafe.putObjectVolatile(this, seedOffset, new AtomicLong(seedVal));
90ce3da70b43 Initial load
duke
parents:
diff changeset
   574
    }
90ce3da70b43 Initial load
duke
parents:
diff changeset
   575
}