--- jsr166/src/main/java/util/Random.java 2003/08/08 20:05:07 1.2 +++ jsr166/src/main/java/util/Random.java 2006/02/16 08:30:29 1.16 @@ -1,57 +1,46 @@ /* - * @(#)Random.java 1.38 02/03/04 + * %W% %E% * - * Copyright 2002 Sun Microsystems, Inc. All rights reserved. + * Copyright 2006 Sun Microsystems, Inc. All rights reserved. * SUN PROPRIETARY/CONFIDENTIAL. Use is subject to license terms. */ 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, - * The Art of Computer Programming, Volume 2, Section 3.2.1.) + * 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, + * The Art of Computer Programming, Volume 3, Section 3.2.1.) *
- * If two instances of 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 Random. Java implementations must use all the algorithms
- * shown here for the class Random, for the sake of absolute
- * portability of Java code. However, subclasses of class Random
- * are permitted to use other algorithms, so long as they adhere to the
+ * 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.
*
- * The algorithms implemented by class Random use a - * protected utility method that on each invocation can supply + * 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. *
- * Many applications will find the random
method in
- * class Math
simpler to use.
+ * Many applications will find the method {@link Math#random} simpler to use.
*
* @author Frank Yellin
- * @version 1.38, 03/04/02
- * @see java.lang.Math#random()
- * @since JDK1.0
+ * @version %I%, %G%
+ * @since 1.0
*/
public
class Random implements java.io.Serializable {
/** use serialVersionUID from JDK 1.1 for interoperability */
static final long serialVersionUID = 3905348978240129619L;
- // Setup to use Unsafe.compareAndSwapLong to update seed.
- 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); }
- }
-
/**
* The internal state associated with this pseudorandom number generator.
* (The specs for the methods in this class describe the ongoing
@@ -59,176 +48,176 @@ class Random implements java.io.Serializ
*
* @serial
*/
- private volatile long seed;
+ 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. Its seed is initialized to
- * a value based on the current time:
- *
- * 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 - *- * public Random() { this(System.currentTimeMillis()); }
long
seed:
- * - * Used by method next to hold - * the state of the pseudorandom number generator. + /** + * 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}. + * + *- * public Random(long seed) { setSeed(seed); }
The invocation {@code new Random(seed)} is equivalent to: + *
{@code + * Random rnd = new Random(); + * rnd.setSeed(seed);}* - * @param seed the initial seed. - * @see java.util.Random#setSeed(long) + * @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 - *
long
seed. The general contract of 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 seed as a seed. The method
- * setSeed is implemented by class Random as follows:
- * - * The implementation of setSeed by class Random - * 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: Even though seed is updated atomically, this method - * must still be synchronized to ensure correct semantics - * of haveNextNextGaussian. + * 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 + *- * synchronized public void setSeed(long seed) { - * this.seed = (seed ^ 0x5DEECE66DL) & ((1L << 48) - 1); - * haveNextNextGaussian = false; - * }
{@code (seed ^ 0x5DEECE66DL) & ((1L << 48) - 1)}+ * and clearing the {@code haveNextNextGaussian} flag used by {@link + * #nextGaussian}. + * + *
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. + * @param seed the initial seed */ synchronized public void setSeed(long seed) { - this.seed = (seed ^ multiplier) & mask; + seed = (seed ^ multiplier) & mask; + this.seed.set(seed); haveNextNextGaussian = false; } /** - * Generates the next pseudorandom number. Subclass should - * override this, as this is used by all other methods.
- * The general contract of next is that it returns an - * int value and if the argument bits is between 1 - * and 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 - * 0 or 1. The method next is implemented - * by class Random as follows: - *
- * This is a linear congruential pseudorandom number generator, as - * defined by D. H. Lehmer and described by Donald E. Knuth in The - * Art of Computer Programming, Volume 2: Seminumerical - * Algorithms, section 3.2.1. - * - * @param bits random bits - * @return the next pseudorandom value from this random number generator's sequence. - * @since JDK1.1 + * Generates the next pseudorandom number. Subclasses should + * override this, as this is used by all other methods. + * + *- * synchronized protected int next(int bits) { - * seed = (seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1); - * return (int)(seed >>> (48 - bits)); - * }
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 + *
{@code (seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1)}+ * and returning + *
{@code (int)(seed >>> (48 - bits))}.+ * + * This is a linear congruential pseudorandom number generator, as + * defined by D. H. Lehmer and described by Donald E. Knuth in + * The Art of Computer Programming, Volume 3: + * Seminumerical Algorithms, 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; - nextseed = (oldseed * multiplier + addend) & mask; - } while (!unsafe.compareAndSwapLong(this, seedOffset, - oldseed, nextseed)); + oldseed = seed.get(); + nextseed = (oldseed * multiplier + addend) & mask; + } while (!seed.compareAndSet(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 + * 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 + * + *
The method {@code nextBytes} is implemented by class {@code Random} + * as if by: + *
{@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; + * }}+ * + * @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) { - 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; - } - } + 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
int
- * value from this random number generator's sequence. The general
- * contract of nextInt is that one int value is
+ * 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 232
- * possible int values are produced with
- * (approximately) equal probability. The method nextInt is
- * implemented by class Random as follows:
- * + * possible {@code int} values are produced with + * (approximately) equal probability. + * + *- * public int nextInt() { return next(32); }
The method {@code nextInt} is implemented by class {@code Random} + * as if by: + *
{@code + * public int nextInt() { + * return next(32); + * }}* - * @return the next pseudorandom, uniformly distributed
int
- * value from this random number generator's sequence.
+ * @return the next pseudorandom, uniformly distributed {@code int}
+ * value from this random number generator's sequence
*/
- public int nextInt() { return next(32); }
+ public int nextInt() {
+ return next(32);
+ }
/**
- * Returns a pseudorandom, uniformly distributed int value
+ * 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
- * nextInt is that one int value in the specified range
- * is pseudorandomly generated and returned. All n possible
- * int values are produced with (approximately) equal
- * probability. The method nextInt(int n) is implemented by
- * class Random as follows:
- * - *+ * {@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: + *{@code * public int nextInt(int n) { - * if (n<=0) - * throw new IllegalArgumentException("n must be positive"); + * 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); + * 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; - * } - *
- * The hedge "approximately" is used in the foregoing description only + * int bits, val; + * do { + * bits = next(31); + * val = bits % n; + * } while (bits - val + (n-1) < 0); + * return val; + * }} + * + *
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 int + * 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. *
* The algorithm is slightly tricky. It rejects values that would result
@@ -249,14 +238,15 @@ class Random implements java.io.Serializ
*
* @param n the bound on the random number to be returned. Must be
* positive.
- * @return a pseudorandom, uniformly distributed int
- * value between 0 (inclusive) and n (exclusive).
- * @exception IllegalArgumentException n is not 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)
+ if (n <= 0)
throw new IllegalArgumentException("n must be positive");
if ((n & -n) == n) // i.e., n is a power of 2
@@ -266,25 +256,28 @@ class Random implements java.io.Serializ
do {
bits = next(31);
val = bits % n;
- } while(bits - val + (n-1) < 0);
+ } while (bits - val + (n-1) < 0);
return val;
}
/**
- * Returns the next pseudorandom, uniformly distributed long
- * value from this random number generator's sequence. The general
- * contract of nextLong is that one long value is pseudorandomly
- * generated and returned. All 264
- * possible long values are produced with (approximately) equal
- * probability. The method nextLong is implemented by class
- * Random as follows:
- *
+ * return ((long)next(32) << 32) + next(32); + * }} + * + * 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+ * 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. + * + *The method {@code nextLong} is implemented by class {@code Random} + * as if by: + *
{@code * public long nextLong() { - * return ((long)next(32) << 32) + next(32); - * }
long
- * value from this random number generator's sequence.
+ * @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.
@@ -293,104 +286,113 @@ class Random implements java.io.Serializ
/**
* Returns the next pseudorandom, uniformly distributed
- * boolean
value from this random number generator's
- * sequence. The general contract of nextBoolean is that one
- * boolean value is pseudorandomly generated and returned. The
- * values true
and false
are produced with
- * (approximately) equal probability. The method nextBoolean is
- * implemented by class Random as follows:
- * - * @return the next pseudorandom, uniformly distributed - *- * public boolean nextBoolean() {return next(1) != 0;} - *
boolean
value from this random number generator's
- * sequence.
+ * {@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.
+ *
+ * The method {@code nextBoolean} is implemented by class {@code Random} + * as if by: + *
{@code + * public boolean nextBoolean() { + * return next(1) != 0; + * }}+ * + * @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;} + public boolean nextBoolean() { + return next(1) != 0; + } /** - * Returns the next pseudorandom, uniformly distributed
float
- * value between 0.0
and 1.0
from this random
- * number generator's sequence. - * The general contract of nextFloat is that one float - * value, chosen (approximately) uniformly from the range 0.0f - * (inclusive) to 1.0f (exclusive), is pseudorandomly - * generated and returned. All 224 - * possible float values of the form - * m x 2-24, where - * m is a positive integer less than 224 - * , are produced with (approximately) equal probability. The - * method nextFloat is implemented by class Random as - * follows: - *
- * 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 or randomly - * chosen bits, then the algorithm shown would choose float + * return next(24) / ((float)(1 << 24)); + * }} + * + *+ * Returns the next pseudorandom, uniformly distributed {@code float} + * value between {@code 0.0} and {@code 1.0} from this random + * number generator's sequence. + * + *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 224 possible {@code float} values + * of the form m x 2-24, where m is a positive + * integer less than 224 , are + * produced with (approximately) equal probability. + * + *
The method {@code nextFloat} is implemented by class {@code Random} + * as if by: + *
{@code * public float nextFloat() { - * return next(24) / ((float)(1 << 24)); - * }
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.
* [In early versions of Java, the result was incorrectly calculated as: - *
- * 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- * return next(30) / ((float)(1 << 30));
float
- * value between 0.0
and 1.0
from this
- * random number generator's sequence.
+ * {@code + * return next(30) / ((float)(1 << 30));}+ * 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() { - int i = next(24); - return i / ((float)(1 << 24)); + return next(24) / ((float)(1 << 24)); } /** - * Returns the next pseudorandom, uniformly distributed - *
double
value between 0.0
and
- * 1.0
from this random number generator's sequence. - * The general contract of nextDouble is that one - * double value, chosen (approximately) uniformly from the - * range 0.0d (inclusive) to 1.0d (exclusive), is - * pseudorandomly generated and returned. All - * 253 possible float - * values of the form m x 2-53 - * , where m is a positive integer less than - * 253, are produced with - * (approximately) equal probability. The method nextDouble is - * implemented by class Random as follows: - *
+ * Returns the next pseudorandom, uniformly distributed + * {@code double} value between {@code 0.0} and + * {@code 1.0} from this random number generator's sequence. + * + *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. + * + *
The method {@code nextDouble} is implemented by class {@code Random} + * as if by: + *
{@code * public double nextDouble() { - * return (((long)next(26) << 27) + next(27)) - * / (double)(1L << 53); - * }
- * 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 or - * randomly chosen bits, then the algorithm shown would choose - * double values from the stated range with perfect uniformity. + * return (((long)next(26) << 27) + next(27)) + * / (double)(1L << 53); + * }} + * + *
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. *
[In early versions of Java, the result was incorrectly calculated as: - *
- * 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 - *- * return (((long)next(27) << 27) + next(27)) - * / (double)(1L << 54);
double
value between 0.0
and
- * 1.0
from this random number generator's sequence.
+ * {@code + * return (((long)next(27) << 27) + next(27)) + * / (double)(1L << 54);}+ * 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() { - long l = ((long)(next(26)) << 27) + next(27); - return l / (double)(1L << 53); + return (((long)(next(26)) << 27) + next(27)) + / (double)(1L << 53); } private double nextNextGaussian; @@ -398,43 +400,48 @@ class Random implements java.io.Serializ /** * Returns the next pseudorandom, Gaussian ("normally") distributed - *
double
value with mean 0.0
and standard
- * deviation 1.0
from this random number generator's sequence.
+ * {@code double} value with mean {@code 0.0} and standard
+ * deviation {@code 1.0} from this random number generator's sequence.
* - * The general contract of nextGaussian is that one - * double value, chosen from (approximately) the usual - * normal distribution with mean 0.0 and standard deviation - * 1.0, is pseudorandomly generated and returned. The method - * nextGaussian is implemented by class Random as follows: - *
- * This uses the polar method of G. E. P. Box, M. E. Muller, and - * G. Marsaglia, as described by Donald E. Knuth in The Art of - * Computer Programming, Volume 2: Seminumerical Algorithms, + * 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. + * + *- * synchronized 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 = Math.sqrt(-2 * Math.log(s)/s); - * nextNextGaussian = v2 * multiplier; - * haveNextNextGaussian = true; - * return v1 * multiplier; - * } - * }
The method {@code nextGaussian} is implemented by class + * {@code Random} as if by a threadsafe version of the following: + *
{@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; + * } + * }}+ * This uses the polar method of G. E. P. Box, M. E. Muller, and + * G. Marsaglia, as described by Donald E. Knuth in The Art of + * Computer Programming, Volume 3: Seminumerical Algorithms, * section 3.4.1, subsection C, algorithm P. Note that it generates two - * independent values at the cost of only one call to Math.log - * and one call to Math.sqrt. + * 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 - *
double
value with mean 0.0
and
- * standard deviation 1.0
from this random number
- * generator's sequence.
+ * @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.
@@ -443,12 +450,12 @@ class Random implements java.io.Serializ
return nextNextGaussian;
} else {
double v1, v2, s;
- do {
+ do {
v1 = 2 * nextDouble() - 1; // between -1 and 1
- v2 = 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 = Math.sqrt(-2 * Math.log(s)/s);
+ double multiplier = StrictMath.sqrt(-2 * StrictMath.log(s)/s);
nextNextGaussian = v2 * multiplier;
haveNextNextGaussian = true;
return v1 * multiplier;
@@ -469,45 +476,56 @@ class Random implements java.io.Serializ
new ObjectStreamField("seed", Long.TYPE),
new ObjectStreamField("nextNextGaussian", Double.TYPE),
new ObjectStreamField("haveNextNextGaussian", Boolean.TYPE)
- };
+ };
/**
- * Reconstitute the Random instance from a stream (that is,
- * deserialize it). The seed is read in as long for
- * historical reasons, but it is converted to an AtomicLong.
+ * 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();
- long seedVal;
- seedVal = (long) fields.get("seed", -1L);
+ // 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");
- seed = seedVal;
+ resetSeed(seedVal);
nextNextGaussian = fields.get("nextNextGaussian", 0.0);
haveNextNextGaussian = fields.get("haveNextNextGaussian", false);
}
-
/**
- * Save the Random instance to a stream.
- * The seed of a Random is serialized as a long for
- * historical reasons.
- *
+ * Save the {@code Random} instance to a stream.
*/
- synchronized private void writeObject(ObjectOutputStream s) throws IOException {
+ synchronized private void writeObject(ObjectOutputStream s)
+ throws IOException {
+
// set the values of the Serializable fields
ObjectOutputStream.PutField fields = s.putFields();
- fields.put("seed", seed);
+
+ // 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));
+ }
+}