001: /*
002: * Copyright 1995-2007 Sun Microsystems, Inc. All Rights Reserved.
003: * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
004: *
005: * This code is free software; you can redistribute it and/or modify it
006: * under the terms of the GNU General Public License version 2 only, as
007: * published by the Free Software Foundation. Sun designates this
008: * particular file as subject to the "Classpath" exception as provided
009: * by Sun in the LICENSE file that accompanied this code.
010: *
011: * This code is distributed in the hope that it will be useful, but WITHOUT
012: * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
013: * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
014: * version 2 for more details (a copy is included in the LICENSE file that
015: * accompanied this code).
016: *
017: * You should have received a copy of the GNU General Public License version
018: * 2 along with this work; if not, write to the Free Software Foundation,
019: * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
020: *
021: * Please contact Sun Microsystems, Inc., 4150 Network Circle, Santa Clara,
022: * CA 95054 USA or visit www.sun.com if you need additional information or
023: * have any questions.
024: */
025:
026: package java.util;
027:
028: import java.io.*;
029: import java.util.concurrent.atomic.AtomicLong;
030: import sun.misc.Unsafe;
031:
032: /**
033: * An instance of this class is used to generate a stream of
034: * pseudorandom numbers. The class uses a 48-bit seed, which is
035: * modified using a linear congruential formula. (See Donald Knuth,
036: * <i>The Art of Computer Programming, Volume 3</i>, Section 3.2.1.)
037: * <p>
038: * If two instances of {@code Random} are created with the same
039: * seed, and the same sequence of method calls is made for each, they
040: * will generate and return identical sequences of numbers. In order to
041: * guarantee this property, particular algorithms are specified for the
042: * class {@code Random}. Java implementations must use all the algorithms
043: * shown here for the class {@code Random}, for the sake of absolute
044: * portability of Java code. However, subclasses of class {@code Random}
045: * are permitted to use other algorithms, so long as they adhere to the
046: * general contracts for all the methods.
047: * <p>
048: * The algorithms implemented by class {@code Random} use a
049: * {@code protected} utility method that on each invocation can supply
050: * up to 32 pseudorandomly generated bits.
051: * <p>
052: * Many applications will find the method {@link Math#random} simpler to use.
053: *
054: * @author Frank Yellin
055: * @version 1.54, 05/05/07
056: * @since 1.0
057: */
058: public class Random implements java.io.Serializable {
059: /** use serialVersionUID from JDK 1.1 for interoperability */
060: static final long serialVersionUID = 3905348978240129619L;
061:
062: /**
063: * The internal state associated with this pseudorandom number generator.
064: * (The specs for the methods in this class describe the ongoing
065: * computation of this value.)
066: */
067: private final AtomicLong seed;
068:
069: private final static long multiplier = 0x5DEECE66DL;
070: private final static long addend = 0xBL;
071: private final static long mask = (1L << 48) - 1;
072:
073: /**
074: * Creates a new random number generator. This constructor sets
075: * the seed of the random number generator to a value very likely
076: * to be distinct from any other invocation of this constructor.
077: */
078: public Random() {
079: this (++seedUniquifier + System.nanoTime());
080: }
081:
082: private static volatile long seedUniquifier = 8682522807148012L;
083:
084: /**
085: * Creates a new random number generator using a single {@code long} seed.
086: * The seed is the initial value of the internal state of the pseudorandom
087: * number generator which is maintained by method {@link #next}.
088: *
089: * <p>The invocation {@code new Random(seed)} is equivalent to:
090: * <pre> {@code
091: * Random rnd = new Random();
092: * rnd.setSeed(seed);}</pre>
093: *
094: * @param seed the initial seed
095: * @see #setSeed(long)
096: */
097: public Random(long seed) {
098: this .seed = new AtomicLong(0L);
099: setSeed(seed);
100: }
101:
102: /**
103: * Sets the seed of this random number generator using a single
104: * {@code long} seed. The general contract of {@code setSeed} is
105: * that it alters the state of this random number generator object
106: * so as to be in exactly the same state as if it had just been
107: * created with the argument {@code seed} as a seed. The method
108: * {@code setSeed} is implemented by class {@code Random} by
109: * atomically updating the seed to
110: * <pre>{@code (seed ^ 0x5DEECE66DL) & ((1L << 48) - 1)}</pre>
111: * and clearing the {@code haveNextNextGaussian} flag used by {@link
112: * #nextGaussian}.
113: *
114: * <p>The implementation of {@code setSeed} by class {@code Random}
115: * happens to use only 48 bits of the given seed. In general, however,
116: * an overriding method may use all 64 bits of the {@code long}
117: * argument as a seed value.
118: *
119: * @param seed the initial seed
120: */
121: synchronized public void setSeed(long seed) {
122: seed = (seed ^ multiplier) & mask;
123: this .seed.set(seed);
124: haveNextNextGaussian = false;
125: }
126:
127: /**
128: * Generates the next pseudorandom number. Subclasses should
129: * override this, as this is used by all other methods.
130: *
131: * <p>The general contract of {@code next} is that it returns an
132: * {@code int} value and if the argument {@code bits} is between
133: * {@code 1} and {@code 32} (inclusive), then that many low-order
134: * bits of the returned value will be (approximately) independently
135: * chosen bit values, each of which is (approximately) equally
136: * likely to be {@code 0} or {@code 1}. The method {@code next} is
137: * implemented by class {@code Random} by atomically updating the seed to
138: * <pre>{@code (seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1)}</pre>
139: * and returning
140: * <pre>{@code (int)(seed >>> (48 - bits))}.</pre>
141: *
142: * This is a linear congruential pseudorandom number generator, as
143: * defined by D. H. Lehmer and described by Donald E. Knuth in
144: * <i>The Art of Computer Programming,</i> Volume 3:
145: * <i>Seminumerical Algorithms</i>, section 3.2.1.
146: *
147: * @param bits random bits
148: * @return the next pseudorandom value from this random number
149: * generator's sequence
150: * @since 1.1
151: */
152: protected int next(int bits) {
153: long oldseed, nextseed;
154: AtomicLong seed = this .seed;
155: do {
156: oldseed = seed.get();
157: nextseed = (oldseed * multiplier + addend) & mask;
158: } while (!seed.compareAndSet(oldseed, nextseed));
159: return (int) (nextseed >>> (48 - bits));
160: }
161:
162: /**
163: * Generates random bytes and places them into a user-supplied
164: * byte array. The number of random bytes produced is equal to
165: * the length of the byte array.
166: *
167: * <p>The method {@code nextBytes} is implemented by class {@code Random}
168: * as if by:
169: * <pre> {@code
170: * public void nextBytes(byte[] bytes) {
171: * for (int i = 0; i < bytes.length; )
172: * for (int rnd = nextInt(), n = Math.min(bytes.length - i, 4);
173: * n-- > 0; rnd >>= 8)
174: * bytes[i++] = (byte)rnd;
175: * }}</pre>
176: *
177: * @param bytes the byte array to fill with random bytes
178: * @throws NullPointerException if the byte array is null
179: * @since 1.1
180: */
181: public void nextBytes(byte[] bytes) {
182: for (int i = 0, len = bytes.length; i < len;)
183: for (int rnd = nextInt(), n = Math.min(len - i,
184: Integer.SIZE / Byte.SIZE); n-- > 0; rnd >>= Byte.SIZE)
185: bytes[i++] = (byte) rnd;
186: }
187:
188: /**
189: * Returns the next pseudorandom, uniformly distributed {@code int}
190: * value from this random number generator's sequence. The general
191: * contract of {@code nextInt} is that one {@code int} value is
192: * pseudorandomly generated and returned. All 2<font size="-1"><sup>32
193: * </sup></font> possible {@code int} values are produced with
194: * (approximately) equal probability.
195: *
196: * <p>The method {@code nextInt} is implemented by class {@code Random}
197: * as if by:
198: * <pre> {@code
199: * public int nextInt() {
200: * return next(32);
201: * }}</pre>
202: *
203: * @return the next pseudorandom, uniformly distributed {@code int}
204: * value from this random number generator's sequence
205: */
206: public int nextInt() {
207: return next(32);
208: }
209:
210: /**
211: * Returns a pseudorandom, uniformly distributed {@code int} value
212: * between 0 (inclusive) and the specified value (exclusive), drawn from
213: * this random number generator's sequence. The general contract of
214: * {@code nextInt} is that one {@code int} value in the specified range
215: * is pseudorandomly generated and returned. All {@code n} possible
216: * {@code int} values are produced with (approximately) equal
217: * probability. The method {@code nextInt(int n)} is implemented by
218: * class {@code Random} as if by:
219: * <pre> {@code
220: * public int nextInt(int n) {
221: * if (n <= 0)
222: * throw new IllegalArgumentException("n must be positive");
223: *
224: * if ((n & -n) == n) // i.e., n is a power of 2
225: * return (int)((n * (long)next(31)) >> 31);
226: *
227: * int bits, val;
228: * do {
229: * bits = next(31);
230: * val = bits % n;
231: * } while (bits - val + (n-1) < 0);
232: * return val;
233: * }}</pre>
234: *
235: * <p>The hedge "approximately" is used in the foregoing description only
236: * because the next method is only approximately an unbiased source of
237: * independently chosen bits. If it were a perfect source of randomly
238: * chosen bits, then the algorithm shown would choose {@code int}
239: * values from the stated range with perfect uniformity.
240: * <p>
241: * The algorithm is slightly tricky. It rejects values that would result
242: * in an uneven distribution (due to the fact that 2^31 is not divisible
243: * by n). The probability of a value being rejected depends on n. The
244: * worst case is n=2^30+1, for which the probability of a reject is 1/2,
245: * and the expected number of iterations before the loop terminates is 2.
246: * <p>
247: * The algorithm treats the case where n is a power of two specially: it
248: * returns the correct number of high-order bits from the underlying
249: * pseudo-random number generator. In the absence of special treatment,
250: * the correct number of <i>low-order</i> bits would be returned. Linear
251: * congruential pseudo-random number generators such as the one
252: * implemented by this class are known to have short periods in the
253: * sequence of values of their low-order bits. Thus, this special case
254: * greatly increases the length of the sequence of values returned by
255: * successive calls to this method if n is a small power of two.
256: *
257: * @param n the bound on the random number to be returned. Must be
258: * positive.
259: * @return the next pseudorandom, uniformly distributed {@code int}
260: * value between {@code 0} (inclusive) and {@code n} (exclusive)
261: * from this random number generator's sequence
262: * @exception IllegalArgumentException if n is not positive
263: * @since 1.2
264: */
265:
266: public int nextInt(int n) {
267: if (n <= 0)
268: throw new IllegalArgumentException("n must be positive");
269:
270: if ((n & -n) == n) // i.e., n is a power of 2
271: return (int) ((n * (long) next(31)) >> 31);
272:
273: int bits, val;
274: do {
275: bits = next(31);
276: val = bits % n;
277: } while (bits - val + (n - 1) < 0);
278: return val;
279: }
280:
281: /**
282: * Returns the next pseudorandom, uniformly distributed {@code long}
283: * value from this random number generator's sequence. The general
284: * contract of {@code nextLong} is that one {@code long} value is
285: * pseudorandomly generated and returned.
286: *
287: * <p>The method {@code nextLong} is implemented by class {@code Random}
288: * as if by:
289: * <pre> {@code
290: * public long nextLong() {
291: * return ((long)next(32) << 32) + next(32);
292: * }}</pre>
293: *
294: * Because class {@code Random} uses a seed with only 48 bits,
295: * this algorithm will not return all possible {@code long} values.
296: *
297: * @return the next pseudorandom, uniformly distributed {@code long}
298: * value from this random number generator's sequence
299: */
300: public long nextLong() {
301: // it's okay that the bottom word remains signed.
302: return ((long) (next(32)) << 32) + next(32);
303: }
304:
305: /**
306: * Returns the next pseudorandom, uniformly distributed
307: * {@code boolean} value from this random number generator's
308: * sequence. The general contract of {@code nextBoolean} is that one
309: * {@code boolean} value is pseudorandomly generated and returned. The
310: * values {@code true} and {@code false} are produced with
311: * (approximately) equal probability.
312: *
313: * <p>The method {@code nextBoolean} is implemented by class {@code Random}
314: * as if by:
315: * <pre> {@code
316: * public boolean nextBoolean() {
317: * return next(1) != 0;
318: * }}</pre>
319: *
320: * @return the next pseudorandom, uniformly distributed
321: * {@code boolean} value from this random number generator's
322: * sequence
323: * @since 1.2
324: */
325: public boolean nextBoolean() {
326: return next(1) != 0;
327: }
328:
329: /**
330: * Returns the next pseudorandom, uniformly distributed {@code float}
331: * value between {@code 0.0} and {@code 1.0} from this random
332: * number generator's sequence.
333: *
334: * <p>The general contract of {@code nextFloat} is that one
335: * {@code float} value, chosen (approximately) uniformly from the
336: * range {@code 0.0f} (inclusive) to {@code 1.0f} (exclusive), is
337: * pseudorandomly generated and returned. All 2<font
338: * size="-1"><sup>24</sup></font> possible {@code float} values
339: * of the form <i>m x </i>2<font
340: * size="-1"><sup>-24</sup></font>, where <i>m</i> is a positive
341: * integer less than 2<font size="-1"><sup>24</sup> </font>, are
342: * produced with (approximately) equal probability.
343: *
344: * <p>The method {@code nextFloat} is implemented by class {@code Random}
345: * as if by:
346: * <pre> {@code
347: * public float nextFloat() {
348: * return next(24) / ((float)(1 << 24));
349: * }}</pre>
350: *
351: * <p>The hedge "approximately" is used in the foregoing description only
352: * because the next method is only approximately an unbiased source of
353: * independently chosen bits. If it were a perfect source of randomly
354: * chosen bits, then the algorithm shown would choose {@code float}
355: * values from the stated range with perfect uniformity.<p>
356: * [In early versions of Java, the result was incorrectly calculated as:
357: * <pre> {@code
358: * return next(30) / ((float)(1 << 30));}</pre>
359: * This might seem to be equivalent, if not better, but in fact it
360: * introduced a slight nonuniformity because of the bias in the rounding
361: * of floating-point numbers: it was slightly more likely that the
362: * low-order bit of the significand would be 0 than that it would be 1.]
363: *
364: * @return the next pseudorandom, uniformly distributed {@code float}
365: * value between {@code 0.0} and {@code 1.0} from this
366: * random number generator's sequence
367: */
368: public float nextFloat() {
369: return next(24) / ((float) (1 << 24));
370: }
371:
372: /**
373: * Returns the next pseudorandom, uniformly distributed
374: * {@code double} value between {@code 0.0} and
375: * {@code 1.0} from this random number generator's sequence.
376: *
377: * <p>The general contract of {@code nextDouble} is that one
378: * {@code double} value, chosen (approximately) uniformly from the
379: * range {@code 0.0d} (inclusive) to {@code 1.0d} (exclusive), is
380: * pseudorandomly generated and returned.
381: *
382: * <p>The method {@code nextDouble} is implemented by class {@code Random}
383: * as if by:
384: * <pre> {@code
385: * public double nextDouble() {
386: * return (((long)next(26) << 27) + next(27))
387: * / (double)(1L << 53);
388: * }}</pre>
389: *
390: * <p>The hedge "approximately" is used in the foregoing description only
391: * because the {@code next} method is only approximately an unbiased
392: * source of independently chosen bits. If it were a perfect source of
393: * randomly chosen bits, then the algorithm shown would choose
394: * {@code double} values from the stated range with perfect uniformity.
395: * <p>[In early versions of Java, the result was incorrectly calculated as:
396: * <pre> {@code
397: * return (((long)next(27) << 27) + next(27))
398: * / (double)(1L << 54);}</pre>
399: * This might seem to be equivalent, if not better, but in fact it
400: * introduced a large nonuniformity because of the bias in the rounding
401: * of floating-point numbers: it was three times as likely that the
402: * low-order bit of the significand would be 0 than that it would be 1!
403: * This nonuniformity probably doesn't matter much in practice, but we
404: * strive for perfection.]
405: *
406: * @return the next pseudorandom, uniformly distributed {@code double}
407: * value between {@code 0.0} and {@code 1.0} from this
408: * random number generator's sequence
409: * @see Math#random
410: */
411: public double nextDouble() {
412: return (((long) (next(26)) << 27) + next(27))
413: / (double) (1L << 53);
414: }
415:
416: private double nextNextGaussian;
417: private boolean haveNextNextGaussian = false;
418:
419: /**
420: * Returns the next pseudorandom, Gaussian ("normally") distributed
421: * {@code double} value with mean {@code 0.0} and standard
422: * deviation {@code 1.0} from this random number generator's sequence.
423: * <p>
424: * The general contract of {@code nextGaussian} is that one
425: * {@code double} value, chosen from (approximately) the usual
426: * normal distribution with mean {@code 0.0} and standard deviation
427: * {@code 1.0}, is pseudorandomly generated and returned.
428: *
429: * <p>The method {@code nextGaussian} is implemented by class
430: * {@code Random} as if by a threadsafe version of the following:
431: * <pre> {@code
432: * private double nextNextGaussian;
433: * private boolean haveNextNextGaussian = false;
434: *
435: * public double nextGaussian() {
436: * if (haveNextNextGaussian) {
437: * haveNextNextGaussian = false;
438: * return nextNextGaussian;
439: * } else {
440: * double v1, v2, s;
441: * do {
442: * v1 = 2 * nextDouble() - 1; // between -1.0 and 1.0
443: * v2 = 2 * nextDouble() - 1; // between -1.0 and 1.0
444: * s = v1 * v1 + v2 * v2;
445: * } while (s >= 1 || s == 0);
446: * double multiplier = StrictMath.sqrt(-2 * StrictMath.log(s)/s);
447: * nextNextGaussian = v2 * multiplier;
448: * haveNextNextGaussian = true;
449: * return v1 * multiplier;
450: * }
451: * }}</pre>
452: * This uses the <i>polar method</i> of G. E. P. Box, M. E. Muller, and
453: * G. Marsaglia, as described by Donald E. Knuth in <i>The Art of
454: * Computer Programming</i>, Volume 3: <i>Seminumerical Algorithms</i>,
455: * section 3.4.1, subsection C, algorithm P. Note that it generates two
456: * independent values at the cost of only one call to {@code StrictMath.log}
457: * and one call to {@code StrictMath.sqrt}.
458: *
459: * @return the next pseudorandom, Gaussian ("normally") distributed
460: * {@code double} value with mean {@code 0.0} and
461: * standard deviation {@code 1.0} from this random number
462: * generator's sequence
463: */
464: synchronized public double nextGaussian() {
465: // See Knuth, ACP, Section 3.4.1 Algorithm C.
466: if (haveNextNextGaussian) {
467: haveNextNextGaussian = false;
468: return nextNextGaussian;
469: } else {
470: double v1, v2, s;
471: do {
472: v1 = 2 * nextDouble() - 1; // between -1 and 1
473: v2 = 2 * nextDouble() - 1; // between -1 and 1
474: s = v1 * v1 + v2 * v2;
475: } while (s >= 1 || s == 0);
476: double multiplier = StrictMath.sqrt(-2 * StrictMath.log(s)
477: / s);
478: nextNextGaussian = v2 * multiplier;
479: haveNextNextGaussian = true;
480: return v1 * multiplier;
481: }
482: }
483:
484: /**
485: * Serializable fields for Random.
486: *
487: * @serialField seed long
488: * seed for random computations
489: * @serialField nextNextGaussian double
490: * next Gaussian to be returned
491: * @serialField haveNextNextGaussian boolean
492: * nextNextGaussian is valid
493: */
494: private static final ObjectStreamField[] serialPersistentFields = {
495: new ObjectStreamField("seed", Long.TYPE),
496: new ObjectStreamField("nextNextGaussian", Double.TYPE),
497: new ObjectStreamField("haveNextNextGaussian", Boolean.TYPE) };
498:
499: /**
500: * Reconstitute the {@code Random} instance from a stream (that is,
501: * deserialize it).
502: */
503: private void readObject(java.io.ObjectInputStream s)
504: throws java.io.IOException, ClassNotFoundException {
505:
506: ObjectInputStream.GetField fields = s.readFields();
507:
508: // The seed is read in as {@code long} for
509: // historical reasons, but it is converted to an AtomicLong.
510: long seedVal = (long) fields.get("seed", -1L);
511: if (seedVal < 0)
512: throw new java.io.StreamCorruptedException(
513: "Random: invalid seed");
514: resetSeed(seedVal);
515: nextNextGaussian = fields.get("nextNextGaussian", 0.0);
516: haveNextNextGaussian = fields
517: .get("haveNextNextGaussian", false);
518: }
519:
520: /**
521: * Save the {@code Random} instance to a stream.
522: */
523: synchronized private void writeObject(ObjectOutputStream s)
524: throws IOException {
525:
526: // set the values of the Serializable fields
527: ObjectOutputStream.PutField fields = s.putFields();
528:
529: // The seed is serialized as a long for historical reasons.
530: fields.put("seed", seed.get());
531: fields.put("nextNextGaussian", nextNextGaussian);
532: fields.put("haveNextNextGaussian", haveNextNextGaussian);
533:
534: // save them
535: s.writeFields();
536: }
537:
538: // Support for resetting seed while deserializing
539: private static final Unsafe unsafe = Unsafe.getUnsafe();
540: private static final long seedOffset;
541: static {
542: try {
543: seedOffset = unsafe.objectFieldOffset(Random.class
544: .getDeclaredField("seed"));
545: } catch (Exception ex) {
546: throw new Error(ex);
547: }
548: }
549:
550: private void resetSeed(long seedVal) {
551: unsafe.putObjectVolatile(this , seedOffset, new AtomicLong(
552: seedVal));
553: }
554: }
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