| /* |
| * Copyright (c) 1995, 2010, Oracle and/or its affiliates. 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. Oracle designates this |
| * particular file as subject to the "Classpath" exception as provided |
| * by Oracle 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 Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA |
| * or visit www.oracle.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 2</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. |
| * |
| * <p>Instances of {@code java.util.Random} are threadsafe. |
| * However, the concurrent use of the same {@code java.util.Random} |
| * instance across threads may encounter contention and consequent |
| * poor performance. Consider instead using |
| * {@link java.util.concurrent.ThreadLocalRandom} in multithreaded |
| * designs. |
| * |
| * <p>Instances of {@code java.util.Random} are not cryptographically |
| * secure. Consider instead using {@link java.security.SecureRandom} to |
| * get a cryptographically secure pseudo-random number generator for use |
| * by security-sensitive applications. |
| * |
| * @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 static final long multiplier = 0x5DEECE66DL; |
| private static final long addend = 0xBL; |
| private static final 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 long seedUniquifier() { |
| // L'Ecuyer, "Tables of Linear Congruential Generators of |
| // Different Sizes and Good Lattice Structure", 1999 |
| for (;;) { |
| long current = seedUniquifier.get(); |
| long next = current * 181783497276652981L; |
| if (seedUniquifier.compareAndSet(current, next)) |
| return next; |
| } |
| } |
| |
| private static final AtomicLong seedUniquifier |
| = new AtomicLong(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) { |
| if (getClass() == Random.class) |
| this.seed = new AtomicLong(initialScramble(seed)); |
| else { |
| // subclass might have overriden setSeed |
| this.seed = new AtomicLong(); |
| setSeed(seed); |
| } |
| } |
| |
| private static long initialScramble(long seed) { |
| return (seed ^ multiplier) & mask; |
| } |
| |
| /** |
| * 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) { |
| this.seed.set(initialScramble(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 |
| * @throws 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 = 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)); |
| } |
| } |