/*
 * Copyright (c) 1995, 2013, Oracle and/or its affiliates. All rights reserved.
 * ORACLE PROPRIETARY/CONFIDENTIAL. Use is subject to license terms.
 *
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 */

package java.util;
import java.io.*;
import java.util.concurrent.atomic.AtomicLong;
import java.util.function.DoubleConsumer;
import java.util.function.IntConsumer;
import java.util.function.LongConsumer;
import java.util.stream.DoubleStream;
import java.util.stream.IntStream;
import java.util.stream.LongStream;
import java.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
class Random implements 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 final AtomicLong seed;

 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 final String BadBound = "bound must be positive";
 static final String BadRange = "bound must be greater than origin";
 static final String BadSize = "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.
 */
 public Random() {
 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 final 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}.
 *
 * <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)
 */
 public Random(long seed) {
 if (getClass() == Random.class)
 this.seed = new AtomicLong(initialScramble(seed));
 else {
 // subclass might have overriden setSeed
 this.seed = new AtomicLong();
 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;
 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.
 *
 * <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) {
 return nextInt(n) + origin;
 }
 else { // range not representable as int
 int r;
 do {
 r = nextInt();
 } while (r < origin || r >= bound);
 return r;
 }
 }
 else {
 return nextInt();
 }
 }

 /**
 * 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() {
 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. 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 new IllegalArgumentException(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() {
 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&nbsp;x&nbsp;</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() {
 return next(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
 */
 public IntStream ints(long streamSize) {
 if (streamSize < 0L)
 throw new IllegalArgumentException(BadSize);
 return StreamSupport.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
 */
 public IntStream ints() {
 return StreamSupport.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
 */
 public IntStream ints(long streamSize, int randomNumberOrigin,
 int randomNumberBound) {
 if (streamSize < 0L)
 throw new IllegalArgumentException(BadSize);
 if (randomNumberOrigin >= randomNumberBound)
 throw new IllegalArgumentException(BadRange);
 return StreamSupport.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
 */
 public IntStream ints(int randomNumberOrigin, int randomNumberBound) {
 if (randomNumberOrigin >= randomNumberBound)
 throw new IllegalArgumentException(BadRange);
 return StreamSupport.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
 */
 public LongStream longs(long streamSize) {
 if (streamSize < 0L)
 throw new IllegalArgumentException(BadSize);
 return StreamSupport.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
 */
 public LongStream longs() {
 return StreamSupport.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
 */
 public LongStream longs(long streamSize, long randomNumberOrigin,
 long randomNumberBound) {
 if (streamSize < 0L)
 throw new IllegalArgumentException(BadSize);
 if (randomNumberOrigin >= randomNumberBound)
 throw new IllegalArgumentException(BadRange);
 return StreamSupport.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
 */
 public LongStream longs(long randomNumberOrigin, long randomNumberBound) {
 if (randomNumberOrigin >= randomNumberBound)
 throw new IllegalArgumentException(BadRange);
 return StreamSupport.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
 */
 public DoubleStream doubles(long streamSize) {
 if (streamSize < 0L)
 throw new IllegalArgumentException(BadSize);
 return StreamSupport.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
 */
 public DoubleStream doubles() {
 return StreamSupport.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
 */
 public DoubleStream doubles(long streamSize, double randomNumberOrigin,
 double randomNumberBound) {
 if (streamSize < 0L)
 throw new IllegalArgumentException(BadSize);
 if (!(randomNumberOrigin < randomNumberBound))
 throw new IllegalArgumentException(BadRange);
 return StreamSupport.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
 */
 public DoubleStream doubles(double randomNumberOrigin, double randomNumberBound) {
 if (!(randomNumberOrigin < randomNumberBound))
 throw new IllegalArgumentException(BadRange);
 return StreamSupport.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 implements Spliterator.OfInt {
 final Random rng;
 long index;
 final long fence;
 final int origin;
 final int bound;
 RandomIntsSpliterator(Random rng, 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(IntConsumer consumer) {
 if (consumer == null) throw new NullPointerException();
 long i = index, f = fence;
 if (i < f) {
 consumer.accept(rng.internalNextInt(origin, bound));
 index = i + 1;
 return true;
 }
 return false;
 }

 public void forEachRemaining(IntConsumer consumer) {
 if (consumer == null) throw new NullPointerException();
 long i = index, f = fence;
 if (i < f) {
 index = f;
 Random r = rng;
 int o = origin, b = bound;
 do {
 consumer.accept(r.internalNextInt(o, b));
 } while (++i < f);
 }
 }
 }

 /**
 * Spliterator for long streams.
 */
 static final class RandomLongsSpliterator implements Spliterator.OfLong {
 final Random rng;
 long index;
 final long fence;
 final long origin;
 final long bound;
 RandomLongsSpliterator(Random rng, 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(LongConsumer consumer) {
 if (consumer == null) throw new NullPointerException();
 long i = index, f = fence;
 if (i < f) {
 consumer.accept(rng.internalNextLong(origin, bound));
 index = i + 1;
 return true;
 }
 return false;
 }

 public void forEachRemaining(LongConsumer consumer) {
 if (consumer == null) throw new NullPointerException();
 long i = index, f = fence;
 if (i < f) {
 index = f;
 Random r = rng;
 long o = origin, b = bound;
 do {
 consumer.accept(r.internalNextLong(o, b));
 } while (++i < f);
 }
 }

 }

 /**
 * Spliterator for double streams.
 */
 static final class RandomDoublesSpliterator implements Spliterator.OfDouble {
 final Random rng;
 long index;
 final long fence;
 final double origin;
 final double bound;
 RandomDoublesSpliterator(Random rng, 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(DoubleConsumer consumer) {
 if (consumer == null) throw new NullPointerException();
 long i = index, f = fence;
 if (i < f) {
 consumer.accept(rng.internalNextDouble(origin, bound));
 index = i + 1;
 return true;
 }
 return false;
 }

 public void forEachRemaining(DoubleConsumer consumer) {
 if (consumer == null) throw new NullPointerException();
 long i = index, f = fence;
 if (i < f) {
 index = f;
 Random r = 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 final 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).
 */
 private void readObject(java.io.ObjectInputStream s)
 throws java.io.IOException, ClassNotFoundException {

 ObjectInputStream.GetField fields = 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(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
 private static final Unsafe unsafe = Unsafe.getUnsafe();
 private static final long seedOffset;
 static {
 try {
 seedOffset = unsafe.objectFieldOffset
 (Random.class.getDeclaredField("seed"));
 } catch (Exception ex) { throw new Error(ex); }
 }
 private void resetSeed(long seedVal) {
 unsafe.putObjectVolatile(this, seedOffset, new AtomicLong(seedVal));
 }
}