J. Duke | 319a3b9 | 2007-12-01 00:00:00 +0000 | [diff] [blame^] | 1 | /* |
| 2 | * Copyright 1995-2007 Sun Microsystems, Inc. All Rights Reserved. |
| 3 | * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER. |
| 4 | * |
| 5 | * This code is free software; you can redistribute it and/or modify it |
| 6 | * under the terms of the GNU General Public License version 2 only, as |
| 7 | * published by the Free Software Foundation. Sun designates this |
| 8 | * particular file as subject to the "Classpath" exception as provided |
| 9 | * by Sun in the LICENSE file that accompanied this code. |
| 10 | * |
| 11 | * This code is distributed in the hope that it will be useful, but WITHOUT |
| 12 | * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or |
| 13 | * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License |
| 14 | * version 2 for more details (a copy is included in the LICENSE file that |
| 15 | * accompanied this code). |
| 16 | * |
| 17 | * You should have received a copy of the GNU General Public License version |
| 18 | * 2 along with this work; if not, write to the Free Software Foundation, |
| 19 | * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA. |
| 20 | * |
| 21 | * Please contact Sun Microsystems, Inc., 4150 Network Circle, Santa Clara, |
| 22 | * CA 95054 USA or visit www.sun.com if you need additional information or |
| 23 | * have any questions. |
| 24 | */ |
| 25 | |
| 26 | package java.util; |
| 27 | import java.io.*; |
| 28 | import java.util.concurrent.atomic.AtomicLong; |
| 29 | import sun.misc.Unsafe; |
| 30 | |
| 31 | /** |
| 32 | * An instance of this class is used to generate a stream of |
| 33 | * pseudorandom numbers. The class uses a 48-bit seed, which is |
| 34 | * modified using a linear congruential formula. (See Donald Knuth, |
| 35 | * <i>The Art of Computer Programming, Volume 3</i>, Section 3.2.1.) |
| 36 | * <p> |
| 37 | * If two instances of {@code Random} are created with the same |
| 38 | * seed, and the same sequence of method calls is made for each, they |
| 39 | * will generate and return identical sequences of numbers. In order to |
| 40 | * guarantee this property, particular algorithms are specified for the |
| 41 | * class {@code Random}. Java implementations must use all the algorithms |
| 42 | * shown here for the class {@code Random}, for the sake of absolute |
| 43 | * portability of Java code. However, subclasses of class {@code Random} |
| 44 | * are permitted to use other algorithms, so long as they adhere to the |
| 45 | * general contracts for all the methods. |
| 46 | * <p> |
| 47 | * The algorithms implemented by class {@code Random} use a |
| 48 | * {@code protected} utility method that on each invocation can supply |
| 49 | * up to 32 pseudorandomly generated bits. |
| 50 | * <p> |
| 51 | * Many applications will find the method {@link Math#random} simpler to use. |
| 52 | * |
| 53 | * @author Frank Yellin |
| 54 | * @since 1.0 |
| 55 | */ |
| 56 | public |
| 57 | class Random implements java.io.Serializable { |
| 58 | /** use serialVersionUID from JDK 1.1 for interoperability */ |
| 59 | static final long serialVersionUID = 3905348978240129619L; |
| 60 | |
| 61 | /** |
| 62 | * The internal state associated with this pseudorandom number generator. |
| 63 | * (The specs for the methods in this class describe the ongoing |
| 64 | * computation of this value.) |
| 65 | */ |
| 66 | private final AtomicLong seed; |
| 67 | |
| 68 | private final static long multiplier = 0x5DEECE66DL; |
| 69 | private final static long addend = 0xBL; |
| 70 | private final static long mask = (1L << 48) - 1; |
| 71 | |
| 72 | /** |
| 73 | * Creates a new random number generator. This constructor sets |
| 74 | * the seed of the random number generator to a value very likely |
| 75 | * to be distinct from any other invocation of this constructor. |
| 76 | */ |
| 77 | public Random() { this(++seedUniquifier + System.nanoTime()); } |
| 78 | private static volatile long seedUniquifier = 8682522807148012L; |
| 79 | |
| 80 | /** |
| 81 | * Creates a new random number generator using a single {@code long} seed. |
| 82 | * The seed is the initial value of the internal state of the pseudorandom |
| 83 | * number generator which is maintained by method {@link #next}. |
| 84 | * |
| 85 | * <p>The invocation {@code new Random(seed)} is equivalent to: |
| 86 | * <pre> {@code |
| 87 | * Random rnd = new Random(); |
| 88 | * rnd.setSeed(seed);}</pre> |
| 89 | * |
| 90 | * @param seed the initial seed |
| 91 | * @see #setSeed(long) |
| 92 | */ |
| 93 | public Random(long seed) { |
| 94 | this.seed = new AtomicLong(0L); |
| 95 | setSeed(seed); |
| 96 | } |
| 97 | |
| 98 | /** |
| 99 | * Sets the seed of this random number generator using a single |
| 100 | * {@code long} seed. The general contract of {@code setSeed} is |
| 101 | * that it alters the state of this random number generator object |
| 102 | * so as to be in exactly the same state as if it had just been |
| 103 | * created with the argument {@code seed} as a seed. The method |
| 104 | * {@code setSeed} is implemented by class {@code Random} by |
| 105 | * atomically updating the seed to |
| 106 | * <pre>{@code (seed ^ 0x5DEECE66DL) & ((1L << 48) - 1)}</pre> |
| 107 | * and clearing the {@code haveNextNextGaussian} flag used by {@link |
| 108 | * #nextGaussian}. |
| 109 | * |
| 110 | * <p>The implementation of {@code setSeed} by class {@code Random} |
| 111 | * happens to use only 48 bits of the given seed. In general, however, |
| 112 | * an overriding method may use all 64 bits of the {@code long} |
| 113 | * argument as a seed value. |
| 114 | * |
| 115 | * @param seed the initial seed |
| 116 | */ |
| 117 | synchronized public void setSeed(long seed) { |
| 118 | seed = (seed ^ multiplier) & mask; |
| 119 | this.seed.set(seed); |
| 120 | haveNextNextGaussian = false; |
| 121 | } |
| 122 | |
| 123 | /** |
| 124 | * Generates the next pseudorandom number. Subclasses should |
| 125 | * override this, as this is used by all other methods. |
| 126 | * |
| 127 | * <p>The general contract of {@code next} is that it returns an |
| 128 | * {@code int} value and if the argument {@code bits} is between |
| 129 | * {@code 1} and {@code 32} (inclusive), then that many low-order |
| 130 | * bits of the returned value will be (approximately) independently |
| 131 | * chosen bit values, each of which is (approximately) equally |
| 132 | * likely to be {@code 0} or {@code 1}. The method {@code next} is |
| 133 | * implemented by class {@code Random} by atomically updating the seed to |
| 134 | * <pre>{@code (seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1)}</pre> |
| 135 | * and returning |
| 136 | * <pre>{@code (int)(seed >>> (48 - bits))}.</pre> |
| 137 | * |
| 138 | * This is a linear congruential pseudorandom number generator, as |
| 139 | * defined by D. H. Lehmer and described by Donald E. Knuth in |
| 140 | * <i>The Art of Computer Programming,</i> Volume 3: |
| 141 | * <i>Seminumerical Algorithms</i>, section 3.2.1. |
| 142 | * |
| 143 | * @param bits random bits |
| 144 | * @return the next pseudorandom value from this random number |
| 145 | * generator's sequence |
| 146 | * @since 1.1 |
| 147 | */ |
| 148 | protected int next(int bits) { |
| 149 | long oldseed, nextseed; |
| 150 | AtomicLong seed = this.seed; |
| 151 | do { |
| 152 | oldseed = seed.get(); |
| 153 | nextseed = (oldseed * multiplier + addend) & mask; |
| 154 | } while (!seed.compareAndSet(oldseed, nextseed)); |
| 155 | return (int)(nextseed >>> (48 - bits)); |
| 156 | } |
| 157 | |
| 158 | /** |
| 159 | * Generates random bytes and places them into a user-supplied |
| 160 | * byte array. The number of random bytes produced is equal to |
| 161 | * the length of the byte array. |
| 162 | * |
| 163 | * <p>The method {@code nextBytes} is implemented by class {@code Random} |
| 164 | * as if by: |
| 165 | * <pre> {@code |
| 166 | * public void nextBytes(byte[] bytes) { |
| 167 | * for (int i = 0; i < bytes.length; ) |
| 168 | * for (int rnd = nextInt(), n = Math.min(bytes.length - i, 4); |
| 169 | * n-- > 0; rnd >>= 8) |
| 170 | * bytes[i++] = (byte)rnd; |
| 171 | * }}</pre> |
| 172 | * |
| 173 | * @param bytes the byte array to fill with random bytes |
| 174 | * @throws NullPointerException if the byte array is null |
| 175 | * @since 1.1 |
| 176 | */ |
| 177 | public void nextBytes(byte[] bytes) { |
| 178 | for (int i = 0, len = bytes.length; i < len; ) |
| 179 | for (int rnd = nextInt(), |
| 180 | n = Math.min(len - i, Integer.SIZE/Byte.SIZE); |
| 181 | n-- > 0; rnd >>= Byte.SIZE) |
| 182 | bytes[i++] = (byte)rnd; |
| 183 | } |
| 184 | |
| 185 | /** |
| 186 | * Returns the next pseudorandom, uniformly distributed {@code int} |
| 187 | * value from this random number generator's sequence. The general |
| 188 | * contract of {@code nextInt} is that one {@code int} value is |
| 189 | * pseudorandomly generated and returned. All 2<font size="-1"><sup>32 |
| 190 | * </sup></font> possible {@code int} values are produced with |
| 191 | * (approximately) equal probability. |
| 192 | * |
| 193 | * <p>The method {@code nextInt} is implemented by class {@code Random} |
| 194 | * as if by: |
| 195 | * <pre> {@code |
| 196 | * public int nextInt() { |
| 197 | * return next(32); |
| 198 | * }}</pre> |
| 199 | * |
| 200 | * @return the next pseudorandom, uniformly distributed {@code int} |
| 201 | * value from this random number generator's sequence |
| 202 | */ |
| 203 | public int nextInt() { |
| 204 | return next(32); |
| 205 | } |
| 206 | |
| 207 | /** |
| 208 | * Returns a pseudorandom, uniformly distributed {@code int} value |
| 209 | * between 0 (inclusive) and the specified value (exclusive), drawn from |
| 210 | * this random number generator's sequence. The general contract of |
| 211 | * {@code nextInt} is that one {@code int} value in the specified range |
| 212 | * is pseudorandomly generated and returned. All {@code n} possible |
| 213 | * {@code int} values are produced with (approximately) equal |
| 214 | * probability. The method {@code nextInt(int n)} is implemented by |
| 215 | * class {@code Random} as if by: |
| 216 | * <pre> {@code |
| 217 | * public int nextInt(int n) { |
| 218 | * if (n <= 0) |
| 219 | * throw new IllegalArgumentException("n must be positive"); |
| 220 | * |
| 221 | * if ((n & -n) == n) // i.e., n is a power of 2 |
| 222 | * return (int)((n * (long)next(31)) >> 31); |
| 223 | * |
| 224 | * int bits, val; |
| 225 | * do { |
| 226 | * bits = next(31); |
| 227 | * val = bits % n; |
| 228 | * } while (bits - val + (n-1) < 0); |
| 229 | * return val; |
| 230 | * }}</pre> |
| 231 | * |
| 232 | * <p>The hedge "approximately" is used in the foregoing description only |
| 233 | * because the next method is only approximately an unbiased source of |
| 234 | * independently chosen bits. If it were a perfect source of randomly |
| 235 | * chosen bits, then the algorithm shown would choose {@code int} |
| 236 | * values from the stated range with perfect uniformity. |
| 237 | * <p> |
| 238 | * The algorithm is slightly tricky. It rejects values that would result |
| 239 | * in an uneven distribution (due to the fact that 2^31 is not divisible |
| 240 | * by n). The probability of a value being rejected depends on n. The |
| 241 | * worst case is n=2^30+1, for which the probability of a reject is 1/2, |
| 242 | * and the expected number of iterations before the loop terminates is 2. |
| 243 | * <p> |
| 244 | * The algorithm treats the case where n is a power of two specially: it |
| 245 | * returns the correct number of high-order bits from the underlying |
| 246 | * pseudo-random number generator. In the absence of special treatment, |
| 247 | * the correct number of <i>low-order</i> bits would be returned. Linear |
| 248 | * congruential pseudo-random number generators such as the one |
| 249 | * implemented by this class are known to have short periods in the |
| 250 | * sequence of values of their low-order bits. Thus, this special case |
| 251 | * greatly increases the length of the sequence of values returned by |
| 252 | * successive calls to this method if n is a small power of two. |
| 253 | * |
| 254 | * @param n the bound on the random number to be returned. Must be |
| 255 | * positive. |
| 256 | * @return the next pseudorandom, uniformly distributed {@code int} |
| 257 | * value between {@code 0} (inclusive) and {@code n} (exclusive) |
| 258 | * from this random number generator's sequence |
| 259 | * @exception IllegalArgumentException if n is not positive |
| 260 | * @since 1.2 |
| 261 | */ |
| 262 | |
| 263 | public int nextInt(int n) { |
| 264 | if (n <= 0) |
| 265 | throw new IllegalArgumentException("n must be positive"); |
| 266 | |
| 267 | if ((n & -n) == n) // i.e., n is a power of 2 |
| 268 | return (int)((n * (long)next(31)) >> 31); |
| 269 | |
| 270 | int bits, val; |
| 271 | do { |
| 272 | bits = next(31); |
| 273 | val = bits % n; |
| 274 | } while (bits - val + (n-1) < 0); |
| 275 | return val; |
| 276 | } |
| 277 | |
| 278 | /** |
| 279 | * Returns the next pseudorandom, uniformly distributed {@code long} |
| 280 | * value from this random number generator's sequence. The general |
| 281 | * contract of {@code nextLong} is that one {@code long} value is |
| 282 | * pseudorandomly generated and returned. |
| 283 | * |
| 284 | * <p>The method {@code nextLong} is implemented by class {@code Random} |
| 285 | * as if by: |
| 286 | * <pre> {@code |
| 287 | * public long nextLong() { |
| 288 | * return ((long)next(32) << 32) + next(32); |
| 289 | * }}</pre> |
| 290 | * |
| 291 | * Because class {@code Random} uses a seed with only 48 bits, |
| 292 | * this algorithm will not return all possible {@code long} values. |
| 293 | * |
| 294 | * @return the next pseudorandom, uniformly distributed {@code long} |
| 295 | * value from this random number generator's sequence |
| 296 | */ |
| 297 | public long nextLong() { |
| 298 | // it's okay that the bottom word remains signed. |
| 299 | return ((long)(next(32)) << 32) + next(32); |
| 300 | } |
| 301 | |
| 302 | /** |
| 303 | * Returns the next pseudorandom, uniformly distributed |
| 304 | * {@code boolean} value from this random number generator's |
| 305 | * sequence. The general contract of {@code nextBoolean} is that one |
| 306 | * {@code boolean} value is pseudorandomly generated and returned. The |
| 307 | * values {@code true} and {@code false} are produced with |
| 308 | * (approximately) equal probability. |
| 309 | * |
| 310 | * <p>The method {@code nextBoolean} is implemented by class {@code Random} |
| 311 | * as if by: |
| 312 | * <pre> {@code |
| 313 | * public boolean nextBoolean() { |
| 314 | * return next(1) != 0; |
| 315 | * }}</pre> |
| 316 | * |
| 317 | * @return the next pseudorandom, uniformly distributed |
| 318 | * {@code boolean} value from this random number generator's |
| 319 | * sequence |
| 320 | * @since 1.2 |
| 321 | */ |
| 322 | public boolean nextBoolean() { |
| 323 | return next(1) != 0; |
| 324 | } |
| 325 | |
| 326 | /** |
| 327 | * Returns the next pseudorandom, uniformly distributed {@code float} |
| 328 | * value between {@code 0.0} and {@code 1.0} from this random |
| 329 | * number generator's sequence. |
| 330 | * |
| 331 | * <p>The general contract of {@code nextFloat} is that one |
| 332 | * {@code float} value, chosen (approximately) uniformly from the |
| 333 | * range {@code 0.0f} (inclusive) to {@code 1.0f} (exclusive), is |
| 334 | * pseudorandomly generated and returned. All 2<font |
| 335 | * size="-1"><sup>24</sup></font> possible {@code float} values |
| 336 | * of the form <i>m x </i>2<font |
| 337 | * size="-1"><sup>-24</sup></font>, where <i>m</i> is a positive |
| 338 | * integer less than 2<font size="-1"><sup>24</sup> </font>, are |
| 339 | * produced with (approximately) equal probability. |
| 340 | * |
| 341 | * <p>The method {@code nextFloat} is implemented by class {@code Random} |
| 342 | * as if by: |
| 343 | * <pre> {@code |
| 344 | * public float nextFloat() { |
| 345 | * return next(24) / ((float)(1 << 24)); |
| 346 | * }}</pre> |
| 347 | * |
| 348 | * <p>The hedge "approximately" is used in the foregoing description only |
| 349 | * because the next method is only approximately an unbiased source of |
| 350 | * independently chosen bits. If it were a perfect source of randomly |
| 351 | * chosen bits, then the algorithm shown would choose {@code float} |
| 352 | * values from the stated range with perfect uniformity.<p> |
| 353 | * [In early versions of Java, the result was incorrectly calculated as: |
| 354 | * <pre> {@code |
| 355 | * return next(30) / ((float)(1 << 30));}</pre> |
| 356 | * This might seem to be equivalent, if not better, but in fact it |
| 357 | * introduced a slight nonuniformity because of the bias in the rounding |
| 358 | * of floating-point numbers: it was slightly more likely that the |
| 359 | * low-order bit of the significand would be 0 than that it would be 1.] |
| 360 | * |
| 361 | * @return the next pseudorandom, uniformly distributed {@code float} |
| 362 | * value between {@code 0.0} and {@code 1.0} from this |
| 363 | * random number generator's sequence |
| 364 | */ |
| 365 | public float nextFloat() { |
| 366 | return next(24) / ((float)(1 << 24)); |
| 367 | } |
| 368 | |
| 369 | /** |
| 370 | * Returns the next pseudorandom, uniformly distributed |
| 371 | * {@code double} value between {@code 0.0} and |
| 372 | * {@code 1.0} from this random number generator's sequence. |
| 373 | * |
| 374 | * <p>The general contract of {@code nextDouble} is that one |
| 375 | * {@code double} value, chosen (approximately) uniformly from the |
| 376 | * range {@code 0.0d} (inclusive) to {@code 1.0d} (exclusive), is |
| 377 | * pseudorandomly generated and returned. |
| 378 | * |
| 379 | * <p>The method {@code nextDouble} is implemented by class {@code Random} |
| 380 | * as if by: |
| 381 | * <pre> {@code |
| 382 | * public double nextDouble() { |
| 383 | * return (((long)next(26) << 27) + next(27)) |
| 384 | * / (double)(1L << 53); |
| 385 | * }}</pre> |
| 386 | * |
| 387 | * <p>The hedge "approximately" is used in the foregoing description only |
| 388 | * because the {@code next} method is only approximately an unbiased |
| 389 | * source of independently chosen bits. If it were a perfect source of |
| 390 | * randomly chosen bits, then the algorithm shown would choose |
| 391 | * {@code double} values from the stated range with perfect uniformity. |
| 392 | * <p>[In early versions of Java, the result was incorrectly calculated as: |
| 393 | * <pre> {@code |
| 394 | * return (((long)next(27) << 27) + next(27)) |
| 395 | * / (double)(1L << 54);}</pre> |
| 396 | * This might seem to be equivalent, if not better, but in fact it |
| 397 | * introduced a large nonuniformity because of the bias in the rounding |
| 398 | * of floating-point numbers: it was three times as likely that the |
| 399 | * low-order bit of the significand would be 0 than that it would be 1! |
| 400 | * This nonuniformity probably doesn't matter much in practice, but we |
| 401 | * strive for perfection.] |
| 402 | * |
| 403 | * @return the next pseudorandom, uniformly distributed {@code double} |
| 404 | * value between {@code 0.0} and {@code 1.0} from this |
| 405 | * random number generator's sequence |
| 406 | * @see Math#random |
| 407 | */ |
| 408 | public double nextDouble() { |
| 409 | return (((long)(next(26)) << 27) + next(27)) |
| 410 | / (double)(1L << 53); |
| 411 | } |
| 412 | |
| 413 | private double nextNextGaussian; |
| 414 | private boolean haveNextNextGaussian = false; |
| 415 | |
| 416 | /** |
| 417 | * Returns the next pseudorandom, Gaussian ("normally") distributed |
| 418 | * {@code double} value with mean {@code 0.0} and standard |
| 419 | * deviation {@code 1.0} from this random number generator's sequence. |
| 420 | * <p> |
| 421 | * The general contract of {@code nextGaussian} is that one |
| 422 | * {@code double} value, chosen from (approximately) the usual |
| 423 | * normal distribution with mean {@code 0.0} and standard deviation |
| 424 | * {@code 1.0}, is pseudorandomly generated and returned. |
| 425 | * |
| 426 | * <p>The method {@code nextGaussian} is implemented by class |
| 427 | * {@code Random} as if by a threadsafe version of the following: |
| 428 | * <pre> {@code |
| 429 | * private double nextNextGaussian; |
| 430 | * private boolean haveNextNextGaussian = false; |
| 431 | * |
| 432 | * public double nextGaussian() { |
| 433 | * if (haveNextNextGaussian) { |
| 434 | * haveNextNextGaussian = false; |
| 435 | * return nextNextGaussian; |
| 436 | * } else { |
| 437 | * double v1, v2, s; |
| 438 | * do { |
| 439 | * v1 = 2 * nextDouble() - 1; // between -1.0 and 1.0 |
| 440 | * v2 = 2 * nextDouble() - 1; // between -1.0 and 1.0 |
| 441 | * s = v1 * v1 + v2 * v2; |
| 442 | * } while (s >= 1 || s == 0); |
| 443 | * double multiplier = StrictMath.sqrt(-2 * StrictMath.log(s)/s); |
| 444 | * nextNextGaussian = v2 * multiplier; |
| 445 | * haveNextNextGaussian = true; |
| 446 | * return v1 * multiplier; |
| 447 | * } |
| 448 | * }}</pre> |
| 449 | * This uses the <i>polar method</i> of G. E. P. Box, M. E. Muller, and |
| 450 | * G. Marsaglia, as described by Donald E. Knuth in <i>The Art of |
| 451 | * Computer Programming</i>, Volume 3: <i>Seminumerical Algorithms</i>, |
| 452 | * section 3.4.1, subsection C, algorithm P. Note that it generates two |
| 453 | * independent values at the cost of only one call to {@code StrictMath.log} |
| 454 | * and one call to {@code StrictMath.sqrt}. |
| 455 | * |
| 456 | * @return the next pseudorandom, Gaussian ("normally") distributed |
| 457 | * {@code double} value with mean {@code 0.0} and |
| 458 | * standard deviation {@code 1.0} from this random number |
| 459 | * generator's sequence |
| 460 | */ |
| 461 | synchronized public double nextGaussian() { |
| 462 | // See Knuth, ACP, Section 3.4.1 Algorithm C. |
| 463 | if (haveNextNextGaussian) { |
| 464 | haveNextNextGaussian = false; |
| 465 | return nextNextGaussian; |
| 466 | } else { |
| 467 | double v1, v2, s; |
| 468 | do { |
| 469 | v1 = 2 * nextDouble() - 1; // between -1 and 1 |
| 470 | v2 = 2 * nextDouble() - 1; // between -1 and 1 |
| 471 | s = v1 * v1 + v2 * v2; |
| 472 | } while (s >= 1 || s == 0); |
| 473 | double multiplier = StrictMath.sqrt(-2 * StrictMath.log(s)/s); |
| 474 | nextNextGaussian = v2 * multiplier; |
| 475 | haveNextNextGaussian = true; |
| 476 | return v1 * multiplier; |
| 477 | } |
| 478 | } |
| 479 | |
| 480 | /** |
| 481 | * Serializable fields for Random. |
| 482 | * |
| 483 | * @serialField seed long |
| 484 | * seed for random computations |
| 485 | * @serialField nextNextGaussian double |
| 486 | * next Gaussian to be returned |
| 487 | * @serialField haveNextNextGaussian boolean |
| 488 | * nextNextGaussian is valid |
| 489 | */ |
| 490 | private static final ObjectStreamField[] serialPersistentFields = { |
| 491 | new ObjectStreamField("seed", Long.TYPE), |
| 492 | new ObjectStreamField("nextNextGaussian", Double.TYPE), |
| 493 | new ObjectStreamField("haveNextNextGaussian", Boolean.TYPE) |
| 494 | }; |
| 495 | |
| 496 | /** |
| 497 | * Reconstitute the {@code Random} instance from a stream (that is, |
| 498 | * deserialize it). |
| 499 | */ |
| 500 | private void readObject(java.io.ObjectInputStream s) |
| 501 | throws java.io.IOException, ClassNotFoundException { |
| 502 | |
| 503 | ObjectInputStream.GetField fields = s.readFields(); |
| 504 | |
| 505 | // The seed is read in as {@code long} for |
| 506 | // historical reasons, but it is converted to an AtomicLong. |
| 507 | long seedVal = (long) fields.get("seed", -1L); |
| 508 | if (seedVal < 0) |
| 509 | throw new java.io.StreamCorruptedException( |
| 510 | "Random: invalid seed"); |
| 511 | resetSeed(seedVal); |
| 512 | nextNextGaussian = fields.get("nextNextGaussian", 0.0); |
| 513 | haveNextNextGaussian = fields.get("haveNextNextGaussian", false); |
| 514 | } |
| 515 | |
| 516 | /** |
| 517 | * Save the {@code Random} instance to a stream. |
| 518 | */ |
| 519 | synchronized private void writeObject(ObjectOutputStream s) |
| 520 | throws IOException { |
| 521 | |
| 522 | // set the values of the Serializable fields |
| 523 | ObjectOutputStream.PutField fields = s.putFields(); |
| 524 | |
| 525 | // The seed is serialized as a long for historical reasons. |
| 526 | fields.put("seed", seed.get()); |
| 527 | fields.put("nextNextGaussian", nextNextGaussian); |
| 528 | fields.put("haveNextNextGaussian", haveNextNextGaussian); |
| 529 | |
| 530 | // save them |
| 531 | s.writeFields(); |
| 532 | } |
| 533 | |
| 534 | // Support for resetting seed while deserializing |
| 535 | private static final Unsafe unsafe = Unsafe.getUnsafe(); |
| 536 | private static final long seedOffset; |
| 537 | static { |
| 538 | try { |
| 539 | seedOffset = unsafe.objectFieldOffset |
| 540 | (Random.class.getDeclaredField("seed")); |
| 541 | } catch (Exception ex) { throw new Error(ex); } |
| 542 | } |
| 543 | private void resetSeed(long seedVal) { |
| 544 | unsafe.putObjectVolatile(this, seedOffset, new AtomicLong(seedVal)); |
| 545 | } |
| 546 | } |