📄 random.java
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/* * @(#)Random.java 1.39 03/01/23 * * Copyright 2003 Sun Microsystems, Inc. All rights reserved. * SUN PROPRIETARY/CONFIDENTIAL. Use is subject to license terms. */package java.util;import java.io.*;import sun.misc.AtomicLong;/** * 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 2</i>, Section 3.2.1.) * <p> * If two instances of <code>Random</code> 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 <tt>Random</tt>. Java implementations must use all the algorithms * shown here for the class <tt>Random</tt>, for the sake of absolute * portability of Java code. However, subclasses of class <tt>Random</tt> * 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 <tt>Random</tt> use a * <tt>protected</tt> utility method that on each invocation can supply * up to 32 pseudorandomly generated bits. * <p> * Many applications will find the <code>random</code> method in * class <code>Math</code> simpler to use. * * @author Frank Yellin * @version 1.39, 01/23/03 * @see java.lang.Math#random() * @since JDK1.0 */publicclass 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.) * * @serial */ private 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. Its seed is initialized to * a value based on the current time: * <blockquote><pre> * public Random() { this(System.currentTimeMillis()); }</pre></blockquote> * Two Random objects created within the same millisecond will have * the same sequence of random numbers. * * @see java.lang.System#currentTimeMillis() */ public Random() { this(System.currentTimeMillis()); } /** * Creates a new random number generator using a single * <code>long</code> seed: * <blockquote><pre> * public Random(long seed) { setSeed(seed); }</pre></blockquote> * Used by method <tt>next</tt> to hold * the state of the pseudorandom number generator. * * @param seed the initial seed. * @see java.util.Random#setSeed(long) */ public Random(long seed) { this.seed = AtomicLong.newAtomicLong(0L); setSeed(seed); } /** * Sets the seed of this random number generator using a single * <code>long</code> seed. The general contract of <tt>setSeed</tt> * 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 <tt>seed</tt> as a seed. The method * <tt>setSeed</tt> is implemented by class Random as follows: * <blockquote><pre> * synchronized public void setSeed(long seed) { * this.seed = (seed ^ 0x5DEECE66DL) & ((1L << 48) - 1); * haveNextNextGaussian = false; * }</pre></blockquote> * The implementation of <tt>setSeed</tt> by class <tt>Random</tt> * happens to use only 48 bits of the given seed. In general, however, * an overriding method may use all 64 bits of the long argument * as a seed value. * * Note: Although the seed value is an AtomicLong, this method * must still be synchronized to ensure correct semantics * of haveNextNextGaussian. * * @param seed the initial seed. */ synchronized public void setSeed(long seed) { seed = (seed ^ multiplier) & mask; while(!this.seed.attemptSet(seed)); haveNextNextGaussian = false; } /** * Generates the next pseudorandom number. Subclass should * override this, as this is used by all other methods.<p> * The general contract of <tt>next</tt> is that it returns an * <tt>int</tt> value and if the argument bits is between <tt>1</tt> * and <tt>32</tt> (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 * <tt>0</tt> or <tt>1</tt>. The method <tt>next</tt> is implemented * by class <tt>Random</tt> as follows: * <blockquote><pre> * synchronized protected int next(int bits) { * seed = (seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1); * return (int)(seed >>> (48 - bits)); * }</pre></blockquote> * 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 2: <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 JDK1.1 */ protected int next(int bits) { long oldseed, nextseed; do { oldseed = seed.get(); nextseed = (oldseed * multiplier + addend) & mask; } while (!seed.attemptUpdate(oldseed, nextseed)); return (int)(nextseed >>> (48 - bits)); } private static final int BITS_PER_BYTE = 8; private static final int BYTES_PER_INT = 4; /** * 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. * * @param bytes the non-null byte array in which to put the * random bytes. * @since JDK1.1 */ public void nextBytes(byte[] bytes) { int numRequested = bytes.length; int numGot = 0, rnd = 0; while (true) { for (int i = 0; i < BYTES_PER_INT; i++) { if (numGot == numRequested) return; rnd = (i==0 ? next(BITS_PER_BYTE * BYTES_PER_INT) : rnd >> BITS_PER_BYTE); bytes[numGot++] = (byte)rnd; } } } /** * Returns the next pseudorandom, uniformly distributed <code>int</code> * value from this random number generator's sequence. The general * contract of <tt>nextInt</tt> is that one <tt>int</tt> value is * pseudorandomly generated and returned. All 2<font size="-1"><sup>32 * </sup></font> possible <tt>int</tt> values are produced with * (approximately) equal probability. The method <tt>nextInt</tt> is * implemented by class <tt>Random</tt> as follows: * <blockquote><pre> * public int nextInt() { return next(32); }</pre></blockquote> * * @return the next pseudorandom, uniformly distributed <code>int</code> * value from this random number generator's sequence. */ public int nextInt() { return next(32); } /** * Returns a pseudorandom, uniformly distributed <tt>int</tt> value * between 0 (inclusive) and the specified value (exclusive), drawn from * this random number generator's sequence. The general contract of * <tt>nextInt</tt> is that one <tt>int</tt> value in the specified range * is pseudorandomly generated and returned. All <tt>n</tt> possible * <tt>int</tt> values are produced with (approximately) equal * probability. The method <tt>nextInt(int n)</tt> is implemented by * class <tt>Random</tt> as follows: * <blockquote><pre> * 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></blockquote> * <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 <tt>int</tt> * 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 a pseudorandom, uniformly distributed <tt>int</tt> * value between 0 (inclusive) and n (exclusive). * @exception IllegalArgumentException 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
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