/* * Copyright (c) 1995, 2022, 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.
*/
/** * An instance of this class is used to generate a stream of * pseudorandom numbers; its period is only 2<sup>48</sup>. * The class uses a 48-bit seed, which is * modified using a linear congruential formula. (See Donald E. Knuth, * <cite>The Art of Computer Programming, Volume 2, Third * edition: Seminumerical Algorithms</cite>, 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
*/
@RandomGeneratorProperties(
name = "Random",
i = 48, j = 0, k = 0,
equidistribution = 0
) publicclass Random implements RandomGenerator, java.io.Serializable {
/** * Class used to wrap a {@link java.util.random.RandomGenerator} to * {@link java.util.Random}.
*/
@SuppressWarnings("serial") privatestaticfinalclass RandomWrapper extends Random implements RandomGenerator { privatefinal RandomGenerator generator; //randomToWrap must never be null private RandomWrapper(RandomGenerator randomToWrap) { super(null); this.generator = randomToWrap;
}
/** * setSeed does not exist in {@link java.util.random.RandomGenerator} so can't * use it.
*/
@Override publicvoid setSeed(long seed) { thrownew UnsupportedOperationException();
}
@Override public IntStream ints(long streamSize) { returnthis.generator.ints(streamSize);
}
@Override public IntStream ints() { returnthis.generator.ints();
}
@Override public IntStream ints(long streamSize, int randomNumberOrigin, int randomNumberBound) { returnthis.generator.ints(streamSize, randomNumberOrigin, randomNumberBound);
}
@Override public IntStream ints(int randomNumberOrigin, int randomNumberBound) { returnthis.generator.ints(randomNumberOrigin, randomNumberBound);
}
@Override public LongStream longs(long streamSize) { returnthis.generator.longs(streamSize);
}
@Override public LongStream longs() { returnthis.generator.longs();
}
@Override public LongStream longs(long streamSize, long randomNumberOrigin, long randomNumberBound) { returnthis.generator.longs(streamSize, randomNumberOrigin, randomNumberBound);
}
@Override public LongStream longs(long randomNumberOrigin, long randomNumberBound) { returnthis.generator.longs(randomNumberOrigin, randomNumberBound);
}
@Override public DoubleStream doubles(long streamSize) { returnthis.generator.doubles(streamSize);
}
@Override public DoubleStream doubles() { returnthis.generator.doubles();
}
//This method should never be reached unless done by reflection so we should throw when tried
@Override protectedint next(int bits) { thrownew UnsupportedOperationException();
}
/** use serialVersionUID from JDK 1.1 for interoperability */
@java.io.Serial staticfinallong 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.)
*/ privatefinal AtomicLong seed;
/** * 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 Random(Void unused) { this.seed = null;
}
privatestaticlong seedUniquifier() { // L'Ecuyer, "Tables of Linear Congruential Generators of // Different Sizes and Good Lattice Structure", 1999 for (;;) { long current = seedUniquifier.get(); long next = current * 1181783497276652981L; if (seedUniquifier.compareAndSet(current, next)) return next;
}
}
privatestaticfinal 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}. * * @implSpec 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 overridden setSeed this.seed = new AtomicLong();
setSeed(seed);
}
}
/** * Returns an instance of {@code Random} that delegates method calls to the {@link RandomGenerator} * argument. If the generator is an instance of {@code Random}, it is returned. Otherwise, this method * returns an instance of {@code Random} that delegates all methods except {@code setSeed} to the generator. * The returned instance's {@code setSeed} method always throws {@link UnsupportedOperationException}. * The returned instance is not serializable. * * @param generator the {@code RandomGenerator} calls are delegated to * @return the delegating {@code Random} instance * @throws NullPointerException if generator is null * @since 19
*/ publicstatic Random from(RandomGenerator generator) {
Objects.requireNonNull(generator); if (generator instanceof Random rand) return rand;
returnnew RandomWrapper(generator);
}
/** * Sets or updates the seed of this random number generator using the * provided {@code long} seed value (optional operation). * * @implSpec * The implementation in this class alters the state of this random number * generator so that it is in the same state as if it had just been created with * {@link #Random(long) new Random(seed)}. It atomically updates the seed to * <pre>{@code (seed ^ 0x5DEECE66DL) & ((1L << 48) - 1)}</pre> * and clears the {@code haveNextNextGaussian} flag used by {@link #nextGaussian}. * Note that this uses only 48 bits of the given seed value. * * @param seed the seed value * @throws UnsupportedOperationException if the {@code setSeed} * operation is not supported by this random number generator
*/ publicsynchronizedvoid setSeed(long seed) { this.seed.set(initialScramble(seed));
haveNextNextGaussian = false;
}
/** * Generates the next pseudorandom number. This method returns an * {@code int} value such that, 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}. * * @apiNote * The other random-producing methods in this class are implemented * in terms of this method, so subclasses can override just this * method to provide a different source of pseudorandom numbers for * the entire class. * * @implSpec * The implementation in this class atomically updates the seed to * <pre>{@code (seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1)}</pre> * and returns * <pre>{@code (int)(seed >>> (48 - bits))}.</pre> * * <p>This is a linear congruential pseudorandom number generator, as * defined by D. H. Lehmer and described by Donald E. Knuth in * <cite>The Art of Computer Programming, Volume 2, Third edition: * Seminumerical Algorithms</cite>, section 3.2.1. * * @param bits random bits * @return the next pseudorandom value from this random number * generator's sequence * @since 1.1
*/ protectedint 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. * * @implSpec 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
*/
@Override publicvoid 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<sup>32</sup> possible * {@code int} values are produced with (approximately) equal probability. * * @implSpec 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
*/
@Override publicint 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 bound} possible * {@code int} values are produced with (approximately) equal * probability. * * @implSpec The method {@code nextInt(int bound)} is implemented by * class {@code Random} as if by: * <pre>{@code * public int nextInt(int bound) { * if (bound <= 0) * throw new IllegalArgumentException("bound must be positive"); * * if ((bound & -bound) == bound) // i.e., bound is a power of 2 * return (int)((bound * (long)next(31)) >> 31); * * int bits, val; * do { * bits = next(31); * val = bits % bound; * } while (bits - val + (bound-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 bound the upper bound (exclusive). Must be positive. * @return the next pseudorandom, uniformly distributed {@code int} * value between zero (inclusive) and {@code bound} (exclusive) * from this random number generator's sequence * @throws IllegalArgumentException if bound is not positive * @since 1.2
*/
@Override publicint nextInt(int bound) { if (bound <= 0) thrownew IllegalArgumentException(BAD_BOUND); int r = next(31); int m = bound - 1; if ((bound & m) == 0) // i.e., bound is a power of 2
r = (int)((bound * (long)r) >> 31); else { // reject over-represented candidates for (int u = r;
u - (r = u % bound) + m < 0;
u = next(31))
;
} return r;
} /** * 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. * * @implSpec 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
*/
@Override publiclong 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. * * @implSpec 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
*/
@Override publicboolean 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<sup>24</sup> possible * {@code float} values of the form <i>m x </i>2<sup>-24</sup>, * where <i>m</i> is a positive integer less than 2<sup>24</sup>, are * produced with (approximately) equal probability. * * @implSpec 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 0.0f} and {@code 1.0f} from this * random number generator's sequence
*/
@Override publicfloat nextFloat() { return next(Float.PRECISION) * FLOAT_UNIT;
}
/** * 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. * * @implSpec 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
*/
@Override publicdouble nextDouble() { return (((long)(next(Double.PRECISION - 27)) << 27) + next(27)) * DOUBLE_UNIT;
}
/** * 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. * * @implSpec 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 <cite>The Art of * Computer Programming, Volume 2, third edition: Seminumerical Algorithms</cite>, * 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
*/
@Override publicsynchronizeddouble nextGaussian() { // See Knuth, TAOCP, Vol. 2, 3rd edition, 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
*/
@java.io.Serial privatestaticfinal 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). * * @param s the {@code ObjectInputStream} from which data is read * * @throws IOException if an I/O error occurs * @throws ClassNotFoundException if a serialized class cannot be loaded
*/
@java.io.Serial privatevoid readObject(java.io.ObjectInputStream s) throws java.io.IOException, ClassNotFoundException {
// 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) thrownew 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. * * @param s the {@code ObjectOutputStream} to which data is written * * @throws IOException if an I/O error occurs
*/
@java.io.Serial privatesynchronizedvoid 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 privatestaticfinal Unsafe unsafe = Unsafe.getUnsafe(); privatestaticfinallong seedOffset; static { try {
seedOffset = unsafe.objectFieldOffset
(Random.class.getDeclaredField("seed"));
} catch (Exception ex) { thrownew Error(ex); }
} privatevoid resetSeed(long seedVal) {
unsafe.putReferenceVolatile(this, seedOffset, new AtomicLong(seedVal));
}
/** * Returns a stream producing the given {@code streamSize} number of * pseudorandom {@code int} values. * * <p>A pseudorandom {@code int} value is generated as if it's the result of * calling the method {@link #nextInt()}. * * @param streamSize the number of values to generate * @return a stream of pseudorandom {@code int} values * @throws IllegalArgumentException if {@code streamSize} is * less than zero * @since 1.8
*/
@Override public IntStream ints(long streamSize) { return AbstractSpliteratorGenerator.ints(this, streamSize);
}
/** * Returns an effectively unlimited stream of pseudorandom {@code int} * values. * * <p>A pseudorandom {@code int} value is generated as if it's the result of * calling the method {@link #nextInt()}. * * @implNote This method is implemented to be equivalent to {@code * ints(Long.MAX_VALUE)}. * * @return a stream of pseudorandom {@code int} values * @since 1.8
*/
@Override public IntStream ints() { return AbstractSpliteratorGenerator.ints(this);
}
/** * Returns a stream producing the given {@code streamSize} number * of pseudorandom {@code int} values, each conforming to the given * origin (inclusive) and bound (exclusive). * * <p>A pseudorandom {@code int} value is generated as if it's the result of * calling the following method with the origin and bound: * <pre> {@code * int nextInt(int origin, int bound) { * int n = bound - origin; * if (n > 0) { * return nextInt(n) + origin; * } * else { // range not representable as int * int r; * do { * r = nextInt(); * } while (r < origin || r >= bound); * return r; * } * }}</pre> * * @param streamSize the number of values to generate * @param randomNumberOrigin the origin (inclusive) of each random value * @param randomNumberBound the bound (exclusive) of each random value * @return a stream of pseudorandom {@code int} values, * each with the given origin (inclusive) and bound (exclusive) * @throws IllegalArgumentException if {@code streamSize} is * less than zero, or {@code randomNumberOrigin} * is greater than or equal to {@code randomNumberBound} * @since 1.8
*/
@Override public IntStream ints(long streamSize, int randomNumberOrigin, int randomNumberBound) { return AbstractSpliteratorGenerator.ints(this, streamSize, randomNumberOrigin, randomNumberBound);
}
/** * Returns an effectively unlimited stream of pseudorandom {@code * int} values, each conforming to the given origin (inclusive) and bound * (exclusive). * * <p>A pseudorandom {@code int} value is generated as if it's the result of * calling the following method with the origin and bound: * <pre> {@code * int nextInt(int origin, int bound) { * int n = bound - origin; * if (n > 0) { * return nextInt(n) + origin; * } * else { // range not representable as int * int r; * do { * r = nextInt(); * } while (r < origin || r >= bound); * return r; * } * }}</pre> * * @implNote This method is implemented to be equivalent to {@code * ints(Long.MAX_VALUE, randomNumberOrigin, randomNumberBound)}. * * @param randomNumberOrigin the origin (inclusive) of each random value * @param randomNumberBound the bound (exclusive) of each random value * @return a stream of pseudorandom {@code int} values, * each with the given origin (inclusive) and bound (exclusive) * @throws IllegalArgumentException if {@code randomNumberOrigin} * is greater than or equal to {@code randomNumberBound} * @since 1.8
*/
@Override public IntStream ints(int randomNumberOrigin, int randomNumberBound) { return AbstractSpliteratorGenerator.ints(this, randomNumberOrigin, randomNumberBound);
}
/** * Returns a stream producing the given {@code streamSize} number of * pseudorandom {@code long} values. * * <p>A pseudorandom {@code long} value is generated as if it's the result * of calling the method {@link #nextLong()}. * * @param streamSize the number of values to generate * @return a stream of pseudorandom {@code long} values * @throws IllegalArgumentException if {@code streamSize} is * less than zero * @since 1.8
*/
@Override public LongStream longs(long streamSize) { return AbstractSpliteratorGenerator.longs(this, streamSize);
}
/** * Returns an effectively unlimited stream of pseudorandom {@code long} * values. * * <p>A pseudorandom {@code long} value is generated as if it's the result * of calling the method {@link #nextLong()}. * * @implNote This method is implemented to be equivalent to {@code * longs(Long.MAX_VALUE)}. * * @return a stream of pseudorandom {@code long} values * @since 1.8
*/
@Override public LongStream longs() { return AbstractSpliteratorGenerator.longs(this);
}
/** * Returns a stream producing the given {@code streamSize} number of * pseudorandom {@code long}, each conforming to the given origin * (inclusive) and bound (exclusive). * * <p>A pseudorandom {@code long} value is generated as if it's the result * of calling the following method with the origin and bound: * <pre> {@code * long nextLong(long origin, long bound) { * long r = nextLong(); * long n = bound - origin, m = n - 1; * if ((n & m) == 0L) // power of two * r = (r & m) + origin; * else if (n > 0L) { // reject over-represented candidates * for (long u = r >>> 1; // ensure nonnegative * u + m - (r = u % n) < 0L; // rejection check * u = nextLong() >>> 1) // retry * ; * r += origin; * } * else { // range not representable as long * while (r < origin || r >= bound) * r = nextLong(); * } * return r; * }}</pre> * * @param streamSize the number of values to generate * @param randomNumberOrigin the origin (inclusive) of each random value * @param randomNumberBound the bound (exclusive) of each random value * @return a stream of pseudorandom {@code long} values, * each with the given origin (inclusive) and bound (exclusive) * @throws IllegalArgumentException if {@code streamSize} is * less than zero, or {@code randomNumberOrigin} * is greater than or equal to {@code randomNumberBound} * @since 1.8
*/
@Override public LongStream longs(long streamSize, long randomNumberOrigin, long randomNumberBound) { return AbstractSpliteratorGenerator.longs(this, streamSize, randomNumberOrigin, randomNumberBound);
}
/** * Returns an effectively unlimited stream of pseudorandom {@code * long} values, each conforming to the given origin (inclusive) and bound * (exclusive). * * <p>A pseudorandom {@code long} value is generated as if it's the result * of calling the following method with the origin and bound: * <pre> {@code * long nextLong(long origin, long bound) { * long r = nextLong(); * long n = bound - origin, m = n - 1; * if ((n & m) == 0L) // power of two * r = (r & m) + origin; * else if (n > 0L) { // reject over-represented candidates * for (long u = r >>> 1; // ensure nonnegative * u + m - (r = u % n) < 0L; // rejection check * u = nextLong() >>> 1) // retry * ; * r += origin; * } * else { // range not representable as long * while (r < origin || r >= bound) * r = nextLong(); * } * return r; * }}</pre> * * @implNote This method is implemented to be equivalent to {@code * longs(Long.MAX_VALUE, randomNumberOrigin, randomNumberBound)}. * * @param randomNumberOrigin the origin (inclusive) of each random value * @param randomNumberBound the bound (exclusive) of each random value * @return a stream of pseudorandom {@code long} values, * each with the given origin (inclusive) and bound (exclusive) * @throws IllegalArgumentException if {@code randomNumberOrigin} * is greater than or equal to {@code randomNumberBound} * @since 1.8
*/
@Override public LongStream longs(long randomNumberOrigin, long randomNumberBound) { return AbstractSpliteratorGenerator.longs(this, randomNumberOrigin, randomNumberBound);
}
/** * Returns a stream producing the given {@code streamSize} number of * pseudorandom {@code double} values, each between zero * (inclusive) and one (exclusive). * * <p>A pseudorandom {@code double} value is generated as if it's the result * of calling the method {@link #nextDouble()}. * * @param streamSize the number of values to generate * @return a stream of {@code double} values * @throws IllegalArgumentException if {@code streamSize} is * less than zero * @since 1.8
*/
@Override public DoubleStream doubles(long streamSize) { return AbstractSpliteratorGenerator.doubles(this, streamSize);
}
/** * Returns an effectively unlimited stream of pseudorandom {@code * double} values, each between zero (inclusive) and one * (exclusive). * * <p>A pseudorandom {@code double} value is generated as if it's the result * of calling the method {@link #nextDouble()}. * * @implNote This method is implemented to be equivalent to {@code * doubles(Long.MAX_VALUE)}. * * @return a stream of pseudorandom {@code double} values * @since 1.8
*/
@Override public DoubleStream doubles() { return AbstractSpliteratorGenerator.doubles(this);
}
/** * Returns a stream producing the given {@code streamSize} number of * pseudorandom {@code double} values, each conforming to the given origin * (inclusive) and bound (exclusive). * * @param streamSize the number of values to generate * @param randomNumberOrigin the origin (inclusive) of each random value * @param randomNumberBound the bound (exclusive) of each random value * @return a stream of pseudorandom {@code double} values, * each with the given origin (inclusive) and bound (exclusive) * @throws IllegalArgumentException {@inheritDoc} * @since 1.8
*/
@Override public DoubleStream doubles(long streamSize, double randomNumberOrigin, double randomNumberBound) { return AbstractSpliteratorGenerator.doubles(this, streamSize, randomNumberOrigin, randomNumberBound);
}
/** * Returns an effectively unlimited stream of pseudorandom {@code * double} values, each conforming to the given origin (inclusive) and bound * (exclusive).
* @implNote This method is implemented to be equivalent to {@code * doubles(Long.MAX_VALUE, randomNumberOrigin, randomNumberBound)}. * * @param randomNumberOrigin the origin (inclusive) of each random value * @param randomNumberBound the bound (exclusive) of each random value * @return a stream of pseudorandom {@code double} values, * each with the given origin (inclusive) and bound (exclusive) * @throws IllegalArgumentException {@inheritDoc} * @since 1.8
*/
@Override public DoubleStream doubles(double randomNumberOrigin, double randomNumberBound) { return AbstractSpliteratorGenerator.doubles(this, randomNumberOrigin, randomNumberBound);
}
}
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