--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/newrandom/Random.java Thu May 23 16:45:56 2019 -0400
@@ -0,0 +1,564 @@
+/*
+ * Copyright (c) 1995, 2013, 2019, Oracle and/or its affiliates. All rights reserved.
+ * ORACLE PROPRIETARY/CONFIDENTIAL. Use is subject to license terms.
+ *
+ *
+ *
+ *
+ *
+ *
+ *
+ *
+ *
+ *
+ *
+ *
+ *
+ *
+ *
+ *
+ *
+ *
+ *
+ *
+ */
+
+// package java.util;
+
+import java.io.*;
+import java.math.BigInteger;
+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 sun.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 extends AbstractSharedRng 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 * 181783497276652981L;
+ 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
+ */
+ synchronized public 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 3:
+ * <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));
+ }
+
+ static final BigInteger thePeriod = BigInteger.valueOf(1L<<48); // Period is 2**48
+
+ /**
+ * Returns the period of this random number generator.
+ *
+ * @return the period of this random number generator.
+ */
+ public BigInteger period() {
+ // Here we also take care of checking for instances of class SecureRandom,
+ // just so as not to bother the implementors of that class.
+ // (Any specific instance of SecureRandom can of course override this method.)
+ // The cast to (Object) is of course needed only during development.
+ return ((Object)this instanceof java.security.SecureRandom) ? Rng.HUGE_PERIOD : thePeriod;
+ }
+
+ /**
+ * 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;
+ }
+
+ /**
+ * 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 {@code int} value between zero (inclusive)
+ * and the specified bound (exclusive).
+ *
+ * @param bound the upper bound (exclusive). Must be positive.
+ * @return a pseudorandom {@code int} value between zero
+ * (inclusive) and the bound (exclusive)
+ * @throws IllegalArgumentException if {@code bound} is not positive
+ */
+ public int nextInt(int bound) {
+ if (bound <= 0)
+ throw new IllegalArgumentException(BadBound);
+ // Specialize internalNextInt for origin 0
+ int r = nextInt();
+ int m = bound - 1;
+ if ((bound & m) == 0) // power of two
+ r &= m;
+ else { // reject over-represented candidates
+ for (int u = r >>> 1;
+ u + m - (r = u % bound) < 0;
+ u = nextInt() >>> 1)
+ ;
+ }
+ 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 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() {
+ 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 3: <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
+ */
+ synchronized public 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;
+ }
+ }
+
+ /**
+ * 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.
+ */
+ synchronized private 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));
+ }
+}