Java tutorial

/* * Copyright (c) 1995, 2018, Oracle and/or its affiliates. All rights reserved. * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER. * * This code is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 2 only, as * published by the Free Software Foundation. Oracle designates this * particular file as subject to the "Classpath" exception as provided * by Oracle in the LICENSE file that accompanied this code. * * This code is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * version 2 for more details (a copy is included in the LICENSE file that * accompanied this code). * * You should have received a copy of the GNU General Public License version * 2 along with this work; if not, write to the Free Software Foundation, * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA. * * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA * or visit www.oracle.com if you need additional information or have any * questions. */ package java.util; import java.io.*; importjava.util.concurrent.atomic.AtomicLong; importjava.util.function.DoubleConsumer; importjava.util.function.IntConsumer; importjava.util.function.LongConsumer; importjava.util.stream.DoubleStream; importjava.util.stream.IntStream; importjava.util.stream.LongStream; importjava.util.stream.StreamSupport; import jdk.internal.misc.Unsafe; /** * An instance of this class is used to generate a stream of * pseudorandom numbers. The class uses a 48-bit seed, which is * modified using a linear congruential formula. (See Donald Knuth, * <i>The Art of Computer Programming, Volume 2</i>, Section 3.2.1.) * <p> * If two instances of {@code Random} are created with the same * seed, and the same sequence of method calls is made for each, they * will generate and return identical sequences of numbers. In order to * guarantee this property, particular algorithms are specified for the * class {@code Random}. Java implementations must use all the algorithms * shown here for the class {@code Random}, for the sake of absolute * portability of Java code. However, subclasses of class {@code Random} * are permitted to use other algorithms, so long as they adhere to the * general contracts for all the methods. * <p> * The algorithms implemented by class {@code Random} use a * {@code protected} utility method that on each invocation can supply * up to 32 pseudorandomly generated bits. * <p> * Many applications will find the method {@link Math#random} simpler to use. * * <p>Instances of {@code java.util.Random} are threadsafe. * However, the concurrent use of the same {@code java.util.Random} * instance across threads may encounter contention and consequent * poor performance. Consider instead using * {@link java.util.concurrent.ThreadLocalRandom} in multithreaded * designs. * * <p>Instances of {@code java.util.Random} are not cryptographically * secure. Consider instead using {@link java.security.SecureRandom} to * get a cryptographically secure pseudo-random number generator for use * by security-sensitive applications. * * @author Frank Yellin * @since 1.0 */ public classRandomimplements java.io.Serializable{ /** use serialVersionUID from JDK 1.1 for interoperability */ static final long serialVersionUID = 3905348978240129619L; /** * The internal state associated with this pseudorandom number generator. * (The specs for the methods in this class describe the ongoing * computation of this value.) */ private finalAtomicLongseed; private static final long multiplier = 0x5DEECE66DL; private static final long addend = 0xBL; private static final long mask = (1L << 48) - 1; private static final double DOUBLE_UNIT = 0x1.0p-53; // 1.0 / (1L << 53) // IllegalArgumentException messages static finalStringBadBound = "bound must be positive"; static finalStringBadRange = "bound must be greater than origin"; static finalStringBadSize = "size must be non-negative"; /** * 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. */ publicRandom() { this(seedUniquifier() ^System.nanoTime()); } private static long seedUniquifier() { // L'Ecuyer, "Tables of Linear Congruential Generators of // Different Sizes and Good Lattice Structure", 1999 for (;;) { long current = seedUniquifier.get(); long next = current * 1181783497276652981L; if (seedUniquifier.compareAndSet(current, next)) return next; } } private static finalAtomicLongseedUniquifier = newAtomicLong(8682522807148012L); /** * Creates a new random number generator using a single {@code long} seed. * The seed is the initial value of the internal state of the pseudorandom * number generator which is maintained by method {@link #next}. * * <p>The invocation {@code new Random(seed)} is equivalent to: * <pre> {@code * Random rnd = new Random(); * rnd.setSeed(seed);}</pre> * * @param seed the initial seed * @see #setSeed(long) */ publicRandom(long seed) { if (getClass() ==Random.class) this.seed = newAtomicLong(initialScramble(seed)); else { // subclass might have overridden setSeed this.seed = newAtomicLong();setSeed(seed); } } private static long initialScramble(long seed) { return (seed ^ multiplier) & mask; } /** * Sets the seed of this random number generator using a single * {@code long} seed. The general contract of {@code setSeed} is * that it alters the state of this random number generator object * so as to be in exactly the same state as if it had just been * created with the argument {@code seed} as a seed. The method * {@code setSeed} is implemented by class {@code Random} by * atomically updating the seed to * <pre>{@code (seed ^ 0x5DEECE66DL) & ((1L << 48) - 1)}</pre> * and clearing the {@code haveNextNextGaussian} flag used by {@link * #nextGaussian}. * * <p>The implementation of {@code setSeed} by class {@code Random} * happens to use only 48 bits of the given seed. In general, however, * an overriding method may use all 64 bits of the {@code long} * argument as a seed value. * * @param seed the initial seed */ public synchronized void setSeed(long seed) { this.seed.set(initialScramble(seed)); haveNextNextGaussian = false; } /** * Generates the next pseudorandom number. Subclasses should * override this, as this is used by all other methods. * * <p>The general contract of {@code next} is that it returns an * {@code int} value and if the argument {@code bits} is between * {@code 1} and {@code 32} (inclusive), then that many low-order * bits of the returned value will be (approximately) independently * chosen bit values, each of which is (approximately) equally * likely to be {@code 0} or {@code 1}. The method {@code next} is * implemented by class {@code Random} by atomically updating the seed to * <pre>{@code (seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1)}</pre> * and returning * <pre>{@code (int)(seed >>> (48 - bits))}.</pre> * * This is a linear congruential pseudorandom number generator, as * defined by D. H. Lehmer and described by Donald E. Knuth in * <i>The Art of Computer Programming,</i> Volume 2: * <i>Seminumerical Algorithms</i>, section 3.2.1. * * @param bits random bits * @return the next pseudorandom value from this random number * generator's sequence * @since 1.1 */ protected int next(int bits) { long oldseed, nextseed;AtomicLongseed = this.seed; do { oldseed = seed.get(); nextseed = (oldseed * multiplier + addend) & mask; } while (!seed.compareAndSet(oldseed, nextseed)); return (int) (nextseed >>> (48 - bits)); } /** * Generates random bytes and places them into a user-supplied * byte array. The number of random bytes produced is equal to * the length of the byte array. * * <p>The method {@code nextBytes} is implemented by class {@code Random} * as if by: * <pre> {@code * public void nextBytes(byte[] bytes) { * for (int i = 0; i < bytes.length; ) * for (int rnd = nextInt(), n = Math.min(bytes.length - i, 4); * n-- > 0; rnd >>= 8) * bytes[i++] = (byte)rnd; * }}</pre> * * @param bytes the byte array to fill with random bytes * @throws NullPointerException if the byte array is null * @since 1.1 */ public void nextBytes(byte[] bytes) { for (int i = 0, len = bytes.length; i < len;) for (int rnd =nextInt(), n =Math.min(len - i,Integer.SIZE /Byte.SIZE); n-- > 0; rnd >>=Byte.SIZE) bytes[i++] = (byte) rnd; } /** * The form of nextLong used by LongStream Spliterators. If * origin is greater than bound, acts as unbounded form of * nextLong, else as bounded form. * * @param origin the least value, unless greater than bound * @param bound the upper bound (exclusive), must not equal origin * @return a pseudorandom value */ final long internalNextLong(long origin, long bound) { long r =nextLong(); if (origin < bound) { 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; } /** * The form of nextInt used by IntStream Spliterators. * For the unbounded case: uses nextInt(). * For the bounded case with representable range: uses nextInt(int bound) * For the bounded case with unrepresentable range: uses nextInt() * * @param origin the least value, unless greater than bound * @param bound the upper bound (exclusive), must not equal origin * @return a pseudorandom value */ final int internalNextInt(int origin, int bound) { if (origin < bound) { int n = bound - origin; if (n > 0) { returnnextInt(n) + origin; } else { // range not representable as int int r; do { r =nextInt(); } while (r < origin || r >= bound); return r; } } else { returnnextInt(); } } /** * The form of nextDouble used by DoubleStream Spliterators. * * @param origin the least value, unless greater than bound * @param bound the upper bound (exclusive), must not equal origin * @return a pseudorandom value */ final double internalNextDouble(double origin, double bound) { double r =nextDouble(); if (origin < bound) { r = r * (bound - origin) + origin; if (r >= bound) // correct for rounding r =Double.longBitsToDouble(Double.doubleToLongBits(bound) - 1); } return r; } /** * 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. * * <p>The method {@code nextInt} is implemented by class {@code Random} * as if by: * <pre> {@code * public int nextInt() { * return next(32); * }}</pre> * * @return the next pseudorandom, uniformly distributed {@code int} * value from this random number generator's sequence */ public int nextInt() { returnnext(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. 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 */ public int nextInt(int bound) { if (bound <= 0) throw newIllegalArgumentException(BadBound); 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 { 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. * * <p>The method {@code nextLong} is implemented by class {@code Random} * as if by: * <pre> {@code * public long nextLong() { * return ((long)next(32) << 32) + next(32); * }}</pre> * * Because class {@code Random} uses a seed with only 48 bits, * this algorithm will not return all possible {@code long} values. * * @return the next pseudorandom, uniformly distributed {@code long} * value from this random number generator's sequence */ public long nextLong() { // it's okay that the bottom word remains signed. return ((long) (next(32)) << 32) +next(32); } /** * Returns the next pseudorandom, uniformly distributed * {@code boolean} value from this random number generator's * sequence. The general contract of {@code nextBoolean} is that one * {@code boolean} value is pseudorandomly generated and returned. The * values {@code true} and {@code false} are produced with * (approximately) equal probability. * * <p>The method {@code nextBoolean} is implemented by class {@code Random} * as if by: * <pre> {@code * public boolean nextBoolean() { * return next(1) != 0; * }}</pre> * * @return the next pseudorandom, uniformly distributed * {@code boolean} value from this random number generator's * sequence * @since 1.2 */ public boolean nextBoolean() { returnnext(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. * * <p>The method {@code nextFloat} is implemented by class {@code Random} * as if by: * <pre> {@code * public float nextFloat() { * return next(24) / ((float)(1 << 24)); * }}</pre> * * <p>The hedge "approximately" is used in the foregoing description only * because the next method is only approximately an unbiased source of * independently chosen bits. If it were a perfect source of randomly * chosen bits, then the algorithm shown would choose {@code float} * values from the stated range with perfect uniformity.<p> * [In early versions of Java, the result was incorrectly calculated as: * <pre> {@code * return next(30) / ((float)(1 << 30));}</pre> * This might seem to be equivalent, if not better, but in fact it * introduced a slight nonuniformity because of the bias in the rounding * of floating-point numbers: it was slightly more likely that the * low-order bit of the significand would be 0 than that it would be 1.] * * @return the next pseudorandom, uniformly distributed {@code float} * value between {@code 0.0} and {@code 1.0} from this * random number generator's sequence */ public float nextFloat() { returnnext(24) / ((float) (1 << 24)); } /** * Returns the next pseudorandom, uniformly distributed * {@code double} value between {@code 0.0} and * {@code 1.0} from this random number generator's sequence. * * <p>The general contract of {@code nextDouble} is that one * {@code double} value, chosen (approximately) uniformly from the * range {@code 0.0d} (inclusive) to {@code 1.0d} (exclusive), is * pseudorandomly generated and returned. * * <p>The method {@code nextDouble} is implemented by class {@code Random} * as if by: * <pre> {@code * public double nextDouble() { * return (((long)next(26) << 27) + next(27)) * / (double)(1L << 53); * }}</pre> * * <p>The hedge "approximately" is used in the foregoing description only * because the {@code next} method is only approximately an unbiased * source of independently chosen bits. If it were a perfect source of * randomly chosen bits, then the algorithm shown would choose * {@code double} values from the stated range with perfect uniformity. * <p>[In early versions of Java, the result was incorrectly calculated as: * <pre> {@code * return (((long)next(27) << 27) + next(27)) * / (double)(1L << 54);}</pre> * This might seem to be equivalent, if not better, but in fact it * introduced a large nonuniformity because of the bias in the rounding * of floating-point numbers: it was three times as likely that the * low-order bit of the significand would be 0 than that it would be 1! * This nonuniformity probably doesn't matter much in practice, but we * strive for perfection.] * * @return the next pseudorandom, uniformly distributed {@code double} * value between {@code 0.0} and {@code 1.0} from this * random number generator's sequence * @see Math#random */ public double nextDouble() { return (((long) (next(26)) << 27) +next(27)) * DOUBLE_UNIT; } private double nextNextGaussian; private boolean haveNextNextGaussian = false; /** * Returns the next pseudorandom, Gaussian ("normally") distributed * {@code double} value with mean {@code 0.0} and standard * deviation {@code 1.0} from this random number generator's sequence. * <p> * The general contract of {@code nextGaussian} is that one * {@code double} value, chosen from (approximately) the usual * normal distribution with mean {@code 0.0} and standard deviation * {@code 1.0}, is pseudorandomly generated and returned. * * <p>The method {@code nextGaussian} is implemented by class * {@code Random} as if by a threadsafe version of the following: * <pre> {@code * private double nextNextGaussian; * private boolean haveNextNextGaussian = false; * * public double nextGaussian() { * if (haveNextNextGaussian) { * haveNextNextGaussian = false; * return nextNextGaussian; * } else { * double v1, v2, s; * do { * v1 = 2 * nextDouble() - 1; // between -1.0 and 1.0 * v2 = 2 * nextDouble() - 1; // between -1.0 and 1.0 * s = v1 * v1 + v2 * v2; * } while (s >= 1 || s == 0); * double multiplier = StrictMath.sqrt(-2 * StrictMath.log(s)/s); * nextNextGaussian = v2 * multiplier; * haveNextNextGaussian = true; * return v1 * multiplier; * } * }}</pre> * This uses the <i>polar method</i> of G. E. P. Box, M. E. Muller, and * G. Marsaglia, as described by Donald E. Knuth in <i>The Art of * Computer Programming</i>, Volume 2: <i>Seminumerical Algorithms</i>, * section 3.4.1, subsection C, algorithm P. Note that it generates two * independent values at the cost of only one call to {@code StrictMath.log} * and one call to {@code StrictMath.sqrt}. * * @return the next pseudorandom, Gaussian ("normally") distributed * {@code double} value with mean {@code 0.0} and * standard deviation {@code 1.0} from this random number * generator's sequence */ public synchronized double nextGaussian() { // See Knuth, ACP, Section 3.4.1 Algorithm C. if (haveNextNextGaussian) { haveNextNextGaussian = false; return nextNextGaussian; } else { double v1, v2, s; do { v1 = 2 *nextDouble() - 1; // between -1 and 1 v2 = 2 *nextDouble() - 1; // between -1 and 1 s = v1 * v1 + v2 * v2; } while (s >= 1 || s == 0); double multiplier =StrictMath.sqrt(-2 *StrictMath.log(s) / s); nextNextGaussian = v2 * multiplier; haveNextNextGaussian = true; return v1 * multiplier; } } // stream methods, coded in a way intended to better isolate for // maintenance purposes the small differences across forms. /** * 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 */ publicIntStreamints(long streamSize) { if (streamSize < 0L) throw newIllegalArgumentException(BadSize); returnStreamSupport.intStream(new RandomIntsSpliterator(this, 0L, streamSize,Integer.MAX_VALUE, 0), false); } /** * 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 */ publicIntStreamints() { returnStreamSupport.intStream(new RandomIntsSpliterator(this, 0L,Long.MAX_VALUE,Integer.MAX_VALUE, 0), false); } /** * 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 */ publicIntStreamints(long streamSize, int randomNumberOrigin, int randomNumberBound) { if (streamSize < 0L) throw newIllegalArgumentException(BadSize); if (randomNumberOrigin >= randomNumberBound) throw newIllegalArgumentException(BadRange); returnStreamSupport.intStream( new RandomIntsSpliterator(this, 0L, streamSize, randomNumberOrigin, randomNumberBound), false); } /** * 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 */ publicIntStreamints(int randomNumberOrigin, int randomNumberBound) { if (randomNumberOrigin >= randomNumberBound) throw newIllegalArgumentException(BadRange); returnStreamSupport.intStream( new RandomIntsSpliterator(this, 0L,Long.MAX_VALUE, randomNumberOrigin, randomNumberBound), false); } /** * 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 */ publicLongStreamlongs(long streamSize) { if (streamSize < 0L) throw newIllegalArgumentException(BadSize); returnStreamSupport.longStream(new RandomLongsSpliterator(this, 0L, streamSize,Long.MAX_VALUE, 0L), false); } /** * 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 */ publicLongStreamlongs() { returnStreamSupport.longStream(new RandomLongsSpliterator(this, 0L,Long.MAX_VALUE,Long.MAX_VALUE, 0L), false); } /** * 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 */ publicLongStreamlongs(long streamSize, long randomNumberOrigin, long randomNumberBound) { if (streamSize < 0L) throw newIllegalArgumentException(BadSize); if (randomNumberOrigin >= randomNumberBound) throw newIllegalArgumentException(BadRange); returnStreamSupport.longStream( new RandomLongsSpliterator(this, 0L, streamSize, randomNumberOrigin, randomNumberBound), false); } /** * 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 */ publicLongStreamlongs(long randomNumberOrigin, long randomNumberBound) { if (randomNumberOrigin >= randomNumberBound) throw newIllegalArgumentException(BadRange); returnStreamSupport.longStream( new RandomLongsSpliterator(this, 0L,Long.MAX_VALUE, randomNumberOrigin, randomNumberBound), false); } /** * 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 */ publicDoubleStreamdoubles(long streamSize) { if (streamSize < 0L) throw newIllegalArgumentException(BadSize); returnStreamSupport.doubleStream(new RandomDoublesSpliterator(this, 0L, streamSize,Double.MAX_VALUE, 0.0), false); } /** * 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 */ publicDoubleStreamdoubles() { returnStreamSupport.doubleStream(new RandomDoublesSpliterator(this, 0L,Long.MAX_VALUE,Double.MAX_VALUE, 0.0), false); } /** * Returns a stream producing the given {@code streamSize} number of * pseudorandom {@code double} values, each conforming to the given origin * (inclusive) and bound (exclusive). * * <p>A pseudorandom {@code double} value is generated as if it's the result * of calling the following method with the origin and bound: * <pre> {@code * double nextDouble(double origin, double bound) { * double r = nextDouble(); * r = r * (bound - origin) + origin; * if (r >= bound) // correct for rounding * r = Math.nextDown(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 double} values, * each with the given origin (inclusive) and bound (exclusive) * @throws IllegalArgumentException if {@code streamSize} is * less than zero * @throws IllegalArgumentException if {@code randomNumberOrigin} * is greater than or equal to {@code randomNumberBound} * @since 1.8 */ publicDoubleStreamdoubles(long streamSize, double randomNumberOrigin, double randomNumberBound) { if (streamSize < 0L) throw newIllegalArgumentException(BadSize); if (!(randomNumberOrigin < randomNumberBound)) throw newIllegalArgumentException(BadRange); returnStreamSupport.doubleStream( new RandomDoublesSpliterator(this, 0L, streamSize, randomNumberOrigin, randomNumberBound), false); } /** * Returns an effectively unlimited stream of pseudorandom {@code * double} values, each conforming to the given origin (inclusive) and bound * (exclusive). * * <p>A pseudorandom {@code double} value is generated as if it's the result * of calling the following method with the origin and bound: * <pre> {@code * double nextDouble(double origin, double bound) { * double r = nextDouble(); * r = r * (bound - origin) + origin; * if (r >= bound) // correct for rounding * r = Math.nextDown(bound); * return r; * }}</pre> * * @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 if {@code randomNumberOrigin} * is greater than or equal to {@code randomNumberBound} * @since 1.8 */ publicDoubleStreamdoubles(double randomNumberOrigin, double randomNumberBound) { if (!(randomNumberOrigin < randomNumberBound)) throw newIllegalArgumentException(BadRange); returnStreamSupport.doubleStream( new RandomDoublesSpliterator(this, 0L,Long.MAX_VALUE, randomNumberOrigin, randomNumberBound), false); } /** * Spliterator for int streams. We multiplex the four int * versions into one class by treating a bound less than origin as * unbounded, and also by treating "infinite" as equivalent to * Long.MAX_VALUE. For splits, it uses the standard divide-by-two * approach. The long and double versions of this class are * identical except for types. */ static final class RandomIntsSpliterator implementsSpliterator.OfInt{ finalRandomrng; long index; final long fence; final int origin; final int bound; RandomIntsSpliterator(Randomrng, long index, long fence, int origin, int bound) { this.rng = rng; this.index = index; this.fence = fence; this.origin = origin; this.bound = bound; } public RandomIntsSpliterator trySplit() { long i = index, m = (i + fence) >>> 1; return (m <= i) ? null : new RandomIntsSpliterator(rng, i, index = m, origin, bound); } public long estimateSize() { return fence - index; } public int characteristics() { return (Spliterator.SIZED |Spliterator.SUBSIZED |Spliterator.NONNULL |Spliterator.IMMUTABLE); } public boolean tryAdvance(IntConsumerconsumer) { if (consumer == null) throw newNullPointerException(); long i = index, f = fence; if (i < f) { consumer.accept(rng.internalNextInt(origin, bound)); index = i + 1; return true; } return false; } public void forEachRemaining(IntConsumerconsumer) { if (consumer == null) throw newNullPointerException(); long i = index, f = fence; if (i < f) { index = f;Randomr = rng; int o = origin, b = bound; do { consumer.accept(r.internalNextInt(o, b)); } while (++i < f); } } } /** * Spliterator for long streams. */ static final class RandomLongsSpliterator implementsSpliterator.OfLong{ finalRandomrng; long index; final long fence; final long origin; final long bound; RandomLongsSpliterator(Randomrng, long index, long fence, long origin, long bound) { this.rng = rng; this.index = index; this.fence = fence; this.origin = origin; this.bound = bound; } public RandomLongsSpliterator trySplit() { long i = index, m = (i + fence) >>> 1; return (m <= i) ? null : new RandomLongsSpliterator(rng, i, index = m, origin, bound); } public long estimateSize() { return fence - index; } public int characteristics() { return (Spliterator.SIZED |Spliterator.SUBSIZED |Spliterator.NONNULL |Spliterator.IMMUTABLE); } public boolean tryAdvance(LongConsumerconsumer) { if (consumer == null) throw newNullPointerException(); long i = index, f = fence; if (i < f) { consumer.accept(rng.internalNextLong(origin, bound)); index = i + 1; return true; } return false; } public void forEachRemaining(LongConsumerconsumer) { if (consumer == null) throw newNullPointerException(); long i = index, f = fence; if (i < f) { index = f;Randomr = rng; long o = origin, b = bound; do { consumer.accept(r.internalNextLong(o, b)); } while (++i < f); } } } /** * Spliterator for double streams. */ static final class RandomDoublesSpliterator implementsSpliterator.OfDouble{ finalRandomrng; long index; final long fence; final double origin; final double bound; RandomDoublesSpliterator(Randomrng, long index, long fence, double origin, double bound) { this.rng = rng; this.index = index; this.fence = fence; this.origin = origin; this.bound = bound; } public RandomDoublesSpliterator trySplit() { long i = index, m = (i + fence) >>> 1; return (m <= i) ? null : new RandomDoublesSpliterator(rng, i, index = m, origin, bound); } public long estimateSize() { return fence - index; } public int characteristics() { return (Spliterator.SIZED |Spliterator.SUBSIZED |Spliterator.NONNULL |Spliterator.IMMUTABLE); } public boolean tryAdvance(DoubleConsumerconsumer) { if (consumer == null) throw newNullPointerException(); long i = index, f = fence; if (i < f) { consumer.accept(rng.internalNextDouble(origin, bound)); index = i + 1; return true; } return false; } public void forEachRemaining(DoubleConsumerconsumer) { if (consumer == null) throw newNullPointerException(); long i = index, f = fence; if (i < f) { index = f;Randomr = rng; double o = origin, b = bound; do { consumer.accept(r.internalNextDouble(o, b)); } while (++i < f); } } } /** * Serializable fields for Random. * * @serialField seed long * seed for random computations * @serialField nextNextGaussian double * next Gaussian to be returned * @serialField haveNextNextGaussian boolean * nextNextGaussian is valid */ private static finalObjectStreamField[] serialPersistentFields = { newObjectStreamField("seed",Long.TYPE), newObjectStreamField("nextNextGaussian",Double.TYPE), newObjectStreamField("haveNextNextGaussian",Boolean.TYPE) }; /** * Reconstitute the {@code Random} instance from a stream (that is, * deserialize it). */ private void readObject(java.io.ObjectInputStreams) throws java.io.IOException,ClassNotFoundException{ObjectInputStream.GetFieldfields = s.readFields(); // The seed is read in as {@code long} for // historical reasons, but it is converted to an AtomicLong. long seedVal = fields.get("seed", -1L); if (seedVal < 0) throw new java.io.StreamCorruptedException("Random: invalid seed");resetSeed(seedVal); nextNextGaussian = fields.get("nextNextGaussian", 0.0); haveNextNextGaussian = fields.get("haveNextNextGaussian", false); } /** * Save the {@code Random} instance to a stream. */ private synchronized void writeObject(ObjectOutputStreams) throwsIOException{ // set the values of the Serializable fieldsObjectOutputStream.PutFieldfields = s.putFields(); // The seed is serialized as a long for historical reasons. fields.put("seed", seed.get()); fields.put("nextNextGaussian", nextNextGaussian); fields.put("haveNextNextGaussian", haveNextNextGaussian); // save them s.writeFields(); } // Support for resetting seed while deserializing private static final Unsafe unsafe = Unsafe.getUnsafe(); private static final long seedOffset; static { try { seedOffset = unsafe.objectFieldOffset(Random.class.getDeclaredField("seed")); } catch (Exceptionex) { throw newError(ex); } } private void resetSeed(long seedVal) { unsafe.putReferenceVolatile(this, seedOffset, newAtomicLong(seedVal)); } }